0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 Bagamoyo Kisarawe Kibaha Mkuranga Rufiji Mafia 37,477ha 5,215ha 12,653ha 6,472ha 8,413ha 90ha 0.4t/ha 0.1t/ha 0.4t/ha 0.3t/ha 0.2t/ha 0.5t/ha 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Tanzania Agriculture Sample Census Maize Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.11 PWANI Planted Area and Yield of Maize by District Map 3.12 PWANI Area Planted per Maize Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 25 Rufiji Kisarawe Kibaha Bagamoyo Mafia 0.6ha 0.5ha 0.5ha 0.7ha 0.6ha 0.4ha Mkuranga 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 5,226ha 3,794ha 1,707ha 5,837ha 10,516ha 1,431ha 0.1t/ha 0.1t/ha 0.4t/ha 0.2t/ha 0.4t/ha 0.5t/ha 8,480 to 10,600 6,360 to 8,480 4,240 to 6,360 2,120 to 4,240 0 to 2,120 Tanzania Agriculture Sample Census Paddy Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.13 PWANI Planted Area and Yield of Paddy by District Map 3.14 PWANI Area Planted per Paddy Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 26 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 There was a sharp rise in the production of paddy in 1995/96 compared to 1994/95. The production rose from 3,000 tonnes in 1994/95 to 34,000 tonnes in 1995/96 after which it dropped to 16,000 tonnes in 1996/97 and to 12,000 tonnes in the following year. Thereafter the yield increased gradually to 32,000 tonnes in 1999/2000 and this was followed by another decline in 2002/03 to 7,000 tonnes. Charts 3.23 and 3.25 show that, whilst the yield of paddy dropped dramatically over the 8-year period (1994/95 to 2002/2003), the quantity produced increased and this was due to a large increase in the planted area. The time series chart of paddy shows that the area planted with paddy remained constant over the period from 1995/96 to 1996/97 after which the area under production increased rapidly till year 1999/2000 then declined to 28,511 ha in 2003. The chart also shows that there was a general decline in yield over the period 1996 to 2003 (down to 0.7 t/ha) except for a one-year sharp increase from 1997/98 to 1998/99. (Chart 3.25). 3.3.4.3 Other Cereals Other cereals were produced in small quantities. A small quantity of sorghum was produced in Bagamoyo (1887 ha), Rufiji (1,114), Kibaha (962 ha), Kisarawe (263 ha) and Mkuranga (247 ha). fingermillet was produced in Rufiji district only (101 ha) and bulrush millet was produced in Kibaha and Mkuranga districts (28 ha and 14 ha respectively) (Chart 3.26). Chart 3.23 Total Planted Area and Area of Paddy per Household by District 1,431 1,707 3,794 5,226 5,837 10,516 0 2,000 4,000 6,000 8,000 10,000 12,000 Rufiji Mkuranga Bagamoyo Kibaha Kisarawe Mafia District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Area planted per household Area Planted (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - PWANI 32 16 12 30 7 3 34 0 10 20 30 40 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.25 Time Series of Paddy Planted Area and Yield - PWANI 0 10000 20000 30000 40000 50000 60000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 Yield (t/ha) Planted Area Yield 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 Area (Ha) Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.26 Area Planted with Sorghum, Bulrush millet and Finger Millet by District Sorghum Bulrush Millet Finger Millet RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 72,661 tonnes. Cassava production was the highest with a total production of 71,190 tonnes representing 98 percent of the total root and tuber crops production. This was followed by sweet potatoes with 1,408 tonnes (1.9%), Irish potatoes (41t, 0.1%) and yams (22t, 0.03%). (Table 3.3). The area planted with cassava was larger than any other root and tuber crops and it was the most important crop in Pwani in terms of planted area (27.7% of the total area planted with annual crops and vegetables) and it accounted for 96.3 percent of the area planted with roots and tubers, followed by sweet potatoes (3.5%), yams (0.1%), and Irish potatoes (0.05%). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava is reported under the long rainy season. However, excluding cassava, 0.3 percent of the area planted with roots and tubers was during the short rainy season with sweet potatoes having 99 percent of its production in the short rainy season. While a very low percent of yams (1%) was produced during the short rainy season, a slightly higher percentage of Irish potatoes (1.8%) was produced during the long rainy season. The percentage of yams produced during the long rainy season was estimated at 4.6 percent. There was a significant increase in area planted with cassava and sweet potatoes from 1994/95 to 2002/03. The areas for Irish potato and yams were insignificant. The estimated yield was highest for Irish potatoes (1.71t/ha) and cassava (1.45 t/ha), followed by sweet potatoes (0.8 t/ha) and yams (0.32 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 74,449. This represents 53 percent of the total crop growing households in the region. The total production of cassava during the census year was 71,190 tonnes from a planted area of 49,270 hectares resulting in a yield of 1.4 t/ha. Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 4970 4837 973 44301 66353 1498 49270 71190 1445 Sweet Potatoes 521 637 1223 1275 771 605 1796 1408 784 Irish Potatoes 0 0 0 24 41 1688 24 41 1708 Yams 5 22 4199 62 0 0 67 22 328 TOTAL 5,496 5,496 45,662 67,165 51,158 72,661 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10000 20000 30000 40000 50000 60000 Cassava Sweet Potatoes Irish Potatoes Yams Crop Area Planted (ha) 0 1000 2000 Yield (kg/ha) Yield (kg/ha) Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 10,000 20,000 30,000 40,000 50,000 60,000 1994/95 1995/ 96 1998/ 99 2002/ 03 Ye ar Cassava RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 Previous censuses and surveys indicate that the area planted with cassava increased over the period 1996 to 1999. Since 1999 the area planted with cassava dropped from 54,196 ha to 49,270 ha (Chart 3.28). The area planted with cassava accounted for 27.7 percent of the total area planted with annual crops and vegetables in the census year. Mkuranga district had the largest planted area for cassava (17,569 ha, 36% of the cassava planted area in the region), followed by Rufiji (9761 ha, 20%), Kisarawe (9411 ha, 19%), Bagamoyo (6199 ha, 13%), Kibaha (5314 ha, 11%) and Mafia (1,015 ha, 2%) (Map 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Mkuranga district (46.8%). This was followed by Kisarawe (45%), Mafia (32.7%), Kibaha (27.6%), Rufiji (27.1%) and Bagamoyo (10.2%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.7 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Rufiji (0.8 ha). This was followed by Mkuranga (0.7 ha), Kisarawe (0.6 ha), Kibaha (0.6 ha), Bagamoyo (0.5 ha) and Mafia (0.4 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Pwani region was 4,872 (1,835 in the short rainy season and 3,036 in the long rainy season). This was 7.1 percent of the total root and tuber crop growing households during the long rainy season. The total production of sweet potatoes during the census year was 1,408 tonnes from a planted area of 1,796 hectares resulting in a yield of 0.8t/ha. Kibaha district has the largest planted area for sweet potatoes (553 ha, 30.8%), followed by Mkuranga (488 ha, 27.2%), Bagamoyo (430 ha, 24%), Mafia (145 ha, 8.1%), Kisarawe (133 ha, 7.4%) and Rufiji (47 ha, 2.6%) (Chart 3.31). Other root and tuber crops were of minor importance in terms of area planted compared to cassava and sweet potatoes. Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 35.7 19.8 19.1 12.6 10.8 2.1 0 5 10 15 20 25 30 35 40 Mkuranga Rufiji Kisarawe Bagamoyo Kibaha Mafia District Percent of Total Area Planted 0 10 20 30 40 50 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.81 0.73 0.63 0.62 0.52 0.35 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Area per Household Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.31 Total Area Planted with Sweet Potatoes and Planted Area per Household by District 47 133 145 430 488 553 0 100 200 300 400 500 600 Kibaha Mkuranga Bagamoyo Mafia Kisarawe Rufiji District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area Planted per Household Planted Area (ha) Area per hh Mkuranga Rufiji Kisarawe Kibaha Bagamoyo Mafia 0.7ha 0.8ha 0.6 0.6ha 0.5ha 0.4ha 0.72 to 0.8 0.64 to 0.72 0.56 to 0.64 0.48 to 0.56 0.4 to 0.48 Bagamoyo Kibaha Kisarawe Rufiji Mafia Mkuranga 6,199ha 5,314ha 9,411ha 17,569ha 9,761ha 1,015ha 1.4t/ha 0.9t/ha 2.4t/ha 1t/ha 1.8t/ha 1.2t/ha 14,400 to 18,000 10,800 to 14,400 7,200 to 10,800 3,600 to 7,200 0 to 3,600 Tanzania Agriculture Sample Census Cassava Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.15 PWANI Planted Area and Yield of Cassava by District Map 3.16 PWANI Area Planted per Cassava Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 30 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 31 3.3.6 Pulse Crops Production The total area planted with pulses was 17,552 hectares out of which 16,223 ha were planted with cowpeas (92.4 percent of the total area planted with pulses), followed by green gram (1,265 ha, 7.2%), beans (18 ha, 0.1%), mung beans (16 ha, 0.1%) and bambaranuts (15 ha, 0.1%). Field peas crop was not cultivated in the region. The area planted with pulses in the short rainy season was 12,039 ha which represented 68.6 percent of total area planted with pulses during the year. Cowpeas was the most dominant crop during long rainy season with 5,167 ha (93.7 % of the total area planted with pulses in that particular season), followed only by green gram (345 ha, 6.3%). Other pulses were not grown during the long rainy season. The total production of pulses was 2,299 tonnes. Cowpeas were the most cultivated crop producing 2,208 tonnes which accounted for 96 percent of the total pulse production. Hence almost all pulses were cowpeas. This was followed by green gram (84t, 3.7%), beans (3t, 0.1%), chick peas (2t, 0.1%) and bambaranuts (1t, 0.06%). Chick peas and beans had relatively higher yields of 247 and 171 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were cowpeas 136 kgs/ha, bambaranuts 89 kgs/ha and green gram 67 kgs/ha. Although mung beans and pigeon peas had areas planted, no harvests were recorded. (Chart 3.32). 3.3.6.1 Cowpeas Cowpeas dominate the production of pulse crops in the region. The number of households growing cowpeas in Pwani region was 54,072. The total production of cowpeas in the region was 2,208 tonnes from a planted area of 16,223 hectares resulting in a yield of 0.1 t/ha. Table 3.4: Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 171 Cowpeas 11,056 1,681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick peas 10 2 247 0 0 0 10 2 247 Bambaranuts 15 1 89 0 0 0 15 1 89 TOTAL 12,039 1,747 5,513 552 17,552 2,299 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Cowpeas Green Gram Beans Mung Beans Bambaranuts Chich Peas Pigeon Peas Crop Area Planted (ha) 0 50 100 150 200 250 300 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Cowpeas Planted Area and Percent of Total Land with Cowpeas by District 0 5 10 15 20 25 30 35 40 45 Bagamoyo Mkuranga Kisarawe Kibaha Rufiji Mafia District Percent of Land 0 2 4 6 8 10 12 14 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.55 0.48 0.38 0.29 0.24 0.18 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area per Household Rufiji Mkuranga Bagamoyo Kibaha Kisarawe Mafia District Chart 3.34 Area Planted per Cowpeas Growing Household by District (Long Rainy Season Only) RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 32 The largest area planted with cowpeas in the region was in Bagamoyo (6,622 ha, 40.8%) (Chart 3.33 and Map 3.17), however, the largest area planted with cowpeas per household was in Bagamoyo district (0.3 ha). The average area planted per household in the region during the long rainy season was 0.35 ha (Chart 3.34). With exception of Bagamoyo district, the variations in area planted with cowpeas for the rest of the districts were small ranging from 0.13 ha in Mafia district to 0.32 ha in Kibaha district (Map 3.18). In Pwani region, almost all pulses (96%) are cowpeas hence in these charts the time series data for cowpeas are represented by the time series for pulses which are available over a range of years. Other types of pulses are insignificant both in planted area and production rendering cowpeas highly significant for pulses over same range of years. Cowpeas (pulses) production increased rapidly over the period 1996 to 1999 from 800 tonnes in 1996 to 34,700 tonnes in 1999, then dropped drastically to about 2,200 tons in 2003. (Chart 3.35). Charts 3.35 and 3.36 show that within the period of those 7 years, the trend for yield of cowpeas was similar to that of production trend but was dropping gradually from its peak of 1.3t/ha in 1998 to 1t/ha in 2003. The quantity produced decreased due to a decrease in the area under production. (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 448 tonnes planted on an area of 2,920 hectares.. The total planted area of oilseeds in the long rainy season was 2,552 ha representing 87.4 percent of the total area planted with oil seeds. Simsim was the most important oilseed crop with 2,552 ha (87.4% of the total area planted with oil seeds), followed by groundnuts 11.7%), sunflower (0.7%) and soya beans (0.2%) (Chart 3.37). The yield of sunflower was moderate (449 kg/ha). Groundnuts had a yield of 316 kg/ha and simsim 129 kg/ha. In terms of production, simsim was 330 tonnes and accounted for 73.7 percent of the total production of oil seeds, followed by groundnuts (24%), sunflower (2%) and none for soya beans. Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 21 10 0 21 10 476 Simsim 166 18 109 2,386 312 0 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Total 368 113 2,552 335 2,920 448 Chart 3.35: Time Series Data on Cowpeas Production - PWANI 10.6 0.8 2.2 23 34.7 0 10 20 30 40 1996/97 1997/1998 1998/99 1999/00 2002/03 Year Production ('000') tons Chart 3.36 Time Series of Cowpeas Planted Area & Yield - PWANI 0 10 20 30 40 50 60 1996/97 1997/1998 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.3 0.6 0.9 Yield (t/ha) Area Yield Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 500 1,000 1,500 2,000 2,500 3,000 Simsim Groundnuts Sunflower Crop Area Planted (ha) 0 100 200 300 400 500 Yield (kg/ha) Yield (kg/ha) Bagamoyo Kibaha Mkuranga Kisarawe Rufiji Mafia 0ha 0.2ha 0ha 0.1ha 0ha 0ha 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Rufiji Kisarawe Mkuranga Kibaha Bagamoyo Mafia 0ha 4ha 0ha 12ha 2ha 0ha 0t/ha 0t/ha 0t/ha 0.2t/ha 0.6t/ha 0t/ha 8 to 12 6 to 8 4 to 6 2 to 4 0 to 2 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.17 PWANI Planted Area and Yield of Beans by District Map 3.18 PWANI Area Planted per Beans Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 33 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 3.3.7.1 Groundnuts Groundnuts was the second most important oilseed crop in Pwani region. The number of households growing groundnuts was only 1,557. The total production of groundnuts in the region was 108 tonnes from a planted area of 342 hectares resulting in a yield of 0.3 t/ha. There has been a moderate increase in production of groundnuts over the period 1996 to 2003, from 105.5 tonnes in 1996/97 to 108.04 tonnes in 2002/03. (Chart 3.38). Thirty eight percent of the area planted with groundnuts was located in Kisarawe district (130 ha, 38%) followed by Mkuranga (122 ha, 35.7%), Kibaha (43 ha, 12.5%), Bagamoyo (26 ha, 7.7%), Rufiji (16 ha, 4.7%) and Mafia (5 ha, 1.3%). (Map 3.19). The highest proportion of land with groundnuts was found in Kisarawe followed by Mkuranga, Kibaha, Mafia, Rufiji and Bagamoyo (Chart 3.39 and Map 3.20). The largest area planted per groundnut growing household was found in Mkuranga district (0.4 ha) and the lowest was in Bagamoyo (0.1). In Kibaha no groundnuts were grown in the long rainy season; otherwise, the range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruits and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short rainy season is relatively important for fruit and vegetables production since 52.7 percent of the total area planted with fruit and vegetables was during the short rainy season. For chillies, onions, spinnach, okra, amaranths, cucumber and water melon Chart 3.38 Time Series Data on Groundnut Production - PWANI 0 108.04 0 105.5 0 500 1994/95 1996/97 1998/99 2002/03 Year Production ( tonnes) Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 Kisarawe Mkuranga Kibaha Bagamoyo Rufiji Mafia District Percent of Land 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 Area per Household (ha) Mkuranga Kisarawe Rufiji Mafia Bagamoyo Kibaha District Chart 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 100 200 300 400 500 600 700 800 900 1,000 Tomatoes Water Mellon Pumpkins Okra Amaranths Radish Cucumber Others Crop A rea Planted (ha) 0 1000 2000 3000 4000 Y ield (kg/ha) Rufiji Kisarawe Kibaha Mafia 0.2ha 0.2ha 0.2ha 0.1ha 0.2ha 0.3ha Mkuranga Bagamoyo 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 Rufiji Mkuranga Mafia Kibaha Bagamoyo 16ha 122ha 130ha 43ha 26ha 5ha 0t/ha 0.3t/ha 0.1t/ha 0.7t/ha 0.9t/ha 0.5t/ha Kisarawe 104 to 130 78 to 104 52 to 78 26 to 52 0 to 26 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.19 PWANI Planted Area and Yield of Groundnuts by District Map 3.20 PWANI Area Planted per Groundnuts Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 35 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 over 60 percent of the planted area of each crop was during the short rainy season. The planted areas for radish and egg plant in the long rainy season were abnormally large (100% of the total planted area was in the long rainy season). Reliable historical data for time series analysis of fruit and vegetables were not available. The total production of fruits and vegetables was 3,682 tonnes. The most cultivated fruit and vegetable crop was the tomato with a production of 1,944 tonnes (53% of the total fruit and vegetables produced) followed by water melon (1,124t, 31%) pumpkins (225t, 5%) and amaranths (115t, 3%). The production of the other fruits and vegetables crops was relatively small. (Table 3.6). The yield of water melon was 3,787 kg/ha, egg plant (3,073 kg/ha), tomatoes (2,172 kg/ha), okra (852 kg/ha), cucumber (989 kg/ha) and spinnach (218 kg/ha). (Chart 3.42). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 1,486 and 1,815 households in the short rainy season. This represented 2.1 percent of the total crop growing households in the region during the long rainy season and 1.9 percent during the short rainy season. Kibaha district had the largest planted area for tomatoes (51.2% of the total area planted with tomatoes in the region), followed by Mkuranga (26.4%), Bagamoyo (8.9%), Kisarawe (7.1%), Mafia (3.5%) and Rufiji (2.8%) (Map 3.21). The highest proportion of land with tomatoes was in Kibaha, followed by Mkuranga district. The rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Kibaha district (0.43 ha) followed by Kisarawe (0.23 ha), Mkuranga (0.19 ha), Mafia (0.14 ha), Rufiji (0.10 ha) and none for Bagamoyo. (Chart 3.44 and Map 3.22). The total area planted with Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 98 35 353 28 73 2,585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Onions 22 15 697 2 4 1,976 24 19 800 Cabbage 13 0 0 13 19 1,506 26 19 729 Tomatoes 404 840 2,077 491 1,104 2,250 895 1,944 2,172 Spinnach 24 2 93 6 4 726 30 6 218 Chillies 6 1 222 0 0 0 6 1 222 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1,328 264 225 853 Cucumber 57 45 794 29 39 1,378 86 85 989 Egg Plant 0 0 0 12 37 3,073 12 37 3,073 Water Mellon 183 921 5027 114 203 1,785 297 1,124 3,787 Total 1,046 2,019 940 1,664 1,987 3,682 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Kibaha Mkuranga Bagamoyo Kisarawe Mafia Rufiji District Percent of Land 0.00 0.50 1.00 1.50 2.00 2.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 0.50 Area per Household (ha Kibaha Kisarawe Mkuranga Mafia Rufiji Bagamoyo District Chart 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season) Kibaha Rufiji Mafia 0.2ha 0.4ha 0.2ha 0.2ha 0.1ha 0.2ha Kisarawe Mkuranga Bagamoyo 0.34 to 0.4 0.28 to 0.34 0.22 to 0.28 0.16 to 0.22 0.1 to 0.16 Mafia Kibaha Kisarawe 31ha 80ha 458ha 237ha 64ha 25ha 2t/ha 1.4t/ha 2.4t/ha 1.5t/ha 3.8t/ha 2t/ha Rufiji Mkuranga Bagamoyo 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.21 PWANI Planted Area and Yield of Tomatoes by District Map 3.22 PWANI Area Planted per Tomatoes Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 37 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 tomatoes accounted for 0.5 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.2 Water Mellon The number of households growing water mellon in the region during the long rainy season was 246 and 794 in the short rainy season. This represented 0.35 percent of the total crop growing households in the region in the long rainy season and 0.84 percent in the short rainy season. Mkuranga district had the largest planted area for water mellon (242 ha, 81.5% of the total area planted with water mellon in the region), followed by Kisarawe (27 ha, 9.1%), Bagamoyo (20 ha, 6.7%), Kibaha (8 ha, 2.7%) and none for Rufiji and Mafia (Chart 3.45). The total area planted with water mellon accounted for 0.17 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Pumpkins The number of households growing pumpkins in the region during the long rainy season was 436 households and 1,007 in the short rainy season. This represents 0.62 percent of the total crop growing households in the region in the long rainy season and 1.05 percent in the short rainy season. Mkuranga district had the largest planted area for pumpkins (179 ha, 67.8% of the total area planted with pumpkins in the region), followed by Kibaha (30 ha, 11.4%), Rufiji (29 ha, 11%), Kisarawe (17ha, 6.4%) and Bagamoyo (9 ha, 3.4%) districts. Pumpkins were not produced in Mafia district. The largest proportion of the area planted with pumpkins was found in Mkuranga district (0.24%), followed by Kibaha (0.08%), Rufiji (0.05%), Kisarawe (0.03%) and Bagamoyo (0.01) (Chart 3.46). The total area planted with pumpkins accounted for 0.15 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 171 180 1,055 183 188 0 354 368 1,039 Cotton 82 0 0 59 117 1,976 141 117 832 TOTAL 252 180 243 305 495 485 Chart 3.45 Percent of Water mellon Planted Area and Percent of Total Land with Water mellon by District 0.0 25.0 50.0 75.0 100.0 Mkuranga Kisarawe Bagamoyo Kibaha Rufiji Mafia District Percent of Land 0.00 0.20 0.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District 0.0 20.0 40.0 60.0 80.0 Mkuranga Kibaha Rufiji Kisarawe Bagamoyo Mafia District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 39 3.3.9 Other Annual Crops Production Most of the other annual crops are cash crops. An area of 495ha was planted with other annual crops and seaweed was the most prominent crop followed by cotton. The area planted with annual cash crops in short rainy season was 252 ha which represented 50.9 percent of the total area planted with other annual cash crops in short and long rainy season. 3.3.9.1 Cotton Only 117 tonnes of cotton were produced in Pwani Region on a planted area of 141 ha. All production was during the long rainy season only. The crop was grown in Bagamoyo district only (Map 3.23) and an average of 0.5 ha was grown per household (Map 3.24). 3.3.9.2 Seaweed The quantity of seaweed produced was 368 tonnes. Seaweed had a planted area of 354 ha, most of which was planted in the long rainy season. Seaweed production was concentrated in 2 districts only, with Mafia having the largest planted area (72% of total area planted with seaweed in the region), followed by Bagamoyo (28%). (Chart 3.48) (Map 3.29 and 3.30). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 82,031 hectares (32% of the total area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area planted if crops planted more than once on it, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops could be higher than indicated in Chart 3.49. Chart 3.47 Area planted with Annual Cash Crops Seaweed, 354, 72% Cotton, 141, 28% Chart 3.48 Percent of Seaweed Planted Area and Percent of Total Land with Seaweed by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Mafia Bagamoyo Kibaha Kisarawe Mkuranga Rufiji District Percent of Land 0.00 2.00 4.00 6.00 8.00 10.00 12.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted for Annual and Permanent Crops Annual , 177,672, 68% Permanent , 82,031 32% Rufiji Mkuranga Kisarawe Kibaha Mafia 0ha 0ha 0ha 0ha 0.5ha 0ha Bagamoyo 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Kisarawe Mkuranga Rufiji Mafia Bagamoyo Kibaha 0ha 0ha 0ha 0ha 141ha 0ha 0t/ha 0t/ha 0t/ha 0t/ha 0.8t/ha 0t/ha 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.23 PWANI Planted Area and Yield of Cotton by District Map 3.24 PWANI Area Planted per Cotton Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 40 RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 The most important permanent crop in Pwani region is the cashewnut which had a planted area of 42,263 ha, (51.5% of the planted area of all permanent crops) followed by coconuts (17,300 ha, 21.1%), oranges (7,635 ha, 9.3%), pineapples (3,628 ha, 4.4%), banana (3,538 ha, 4.3%) and mango 2,244 ha, 2.7%). Each of the remaining permanent crops had an area of less than 2 percent of the total area planted with permanent crops (Chart 3.50). Mkuranga district had the largest area under smallholder permanent crops (29,168 ha, 36%). This is followed by Bagamoyo (15,810 ha, 19%), Rufiji (15,378 ha, 19%), Kisarawe (10,389 ha, 13%), Mafia (6,390 ha, 8%) and Kibaha (4,896 ha, 6%). However, Mafia had the largest area per permanent crop growing household (1.3 ha) followed by Kibaha (1.1 ha), Bagamoyo (0.9 ha), Rufiji (0.8 ha), Mkuranga (0.7 ha) and Kisarawe (0.4 ha) (Chart 3.51). 3.4.1 Cashewnuts The total production of cashewnuts by smallholders was 12,711 tonnes. In terms of area planted, cashewnuts was the most important permanent crop grown by smallholders in the region. They were grown by 40,199 households (28.8% of the total crop growing households). The average area planted with cashewnuts per household was relatively small at around 1.05 ha per cashewnut growing household and the average yield obtained by smallholders was 416 kg/ha from a harvest area of 30,529 hectares. Mkuranga had the largest area of cashewnuts in the region (19,636 ha, 46.5%) followed by Rufiji (10,591 ha, 25.1%), Bagamoyo (6,214 ha, 14.7%), Kisarawe (3,541 ha, 8.4%), Kibaha (2,062 ha, 4.9%) and Mafia (220 ha, 0.5%). (Map 3.25). However, the average area planted with cashew nuts per cashew nut growing household was highest in Bagamoyo (1.5 ha) followed by Rufiji (1.2 ha), Mkuranga (1.1 ha), Kibaha (0.7 ha) and Mafia (0.4 ha) (Chart 3.52 and Map 3.26). Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 19.3 18.7 12.7 7.8 6.0 35.6 0.0 10.0 20.0 30.0 40.0 Mkuranga Bagamoyo Rufiji Kisarawe Mafia Kibaha District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.50 Area Planted with the Main Perennial Crops Other, 511, 1% Pawpaw, 497, 0.6% Pigeon Pea, 1,513, 1.8% Manderine/Tangeri ne 1,395, 1.7% Mpesheni, 165, 0.2% Coconut, 17,300, 21.1% Lime/Lemon, 192, 0.2% Pineapple, 3,628, 4.4% Banana, 3,538, 4.3% Orange, 7,635, 9.3% Mango, 2,244, 2.7% Cashewnut, 42,263, 51.5% Jack Fruit, 1,149, 1.4% Chart 3.52 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.5 25.1 8.4 46.5 4.9 14.7 0.0 20.0 40.0 60.0 Mkuranga Rufiji Bagamoyo Kisarawe Kibaha Mafia District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 1.3 1.5 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 1.2ha 1.1ha 0.6ha 0.7ha 1.5ha 0.4ha 1.2 > 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 Mafia Rufiji Mkuranga Kisarawe Kibaha Bagamoyo 220ha 10,591ha 19,636ha 3,541ha 2,062ha 6,214ha 0.5t/ha 0.2t/ha 0.3t/ha 0.4t/ha 0.6t/hs 0.2t/ha 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area(ha) Planted Area(ha) Map 3.25 PWANI Planted Area and Yield of Cashewnut by District Yield (t/ha) Tanzania Agriculture Sample Census Area Planted Per Household Map 3.26 PWANI Area Planted per Cashewnut Growing Household by District Planted Area Per Household RESULTS 42 RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 3.4.2 Coconuts The total production of coconuts by smallholders was 30,732 tonnes. In terms of area planted, the coconut was the second most important permanent crop grown by smallholders in the region. It was grown by 24,094 households (17.3% of the total crop growing households). The average area planted with coconuts per household was relatively small at around 0.72 ha per coconut growing household and the average yield obtained by smallholders was 2,333 kg/ha from a harvest area of 13,171 hectares. Mafia had the largest area of coconuts in the region (4778 ha, 27.6%) followed by Mkuranga (4569 ha, 26.4%), Bagamoyo (3155 ha, 18.2%), Rufiji (1906 ha, 11%), Kisarawe (1575 ha, 9.1%) and Kibaha (1317 ha, 7.6%) (Map 3.28). However, the average area planted with coconuts per coconut planting household was highest in Kibaha (2.08 ha) followed by Mafia (1.34 ha), Bagamoyo (0.96 ha), Rufiji (0.78 ha), Mkuranga (0.52 ha) and Kisarawe (0.3 ha) (Chart 3.53 and Map 3.28). 3.4.3 Oranges The total production of oranges by smallholders was 18,807 tonnes. In terms of area planted, oranges were the third most important permanent crops grown by smallholders in the region. They were grown by 15,006 households (10.8% of the total crop growing households). The average area planted with oranges per household was 0.51 ha per orange growing household and the average yield obtained by smallholders was 5,266 kg/ha from a harvested area of 3,571 hectares. Bagamoyo had the largest planted area of oranges in the region (2,001 ha, 26.1%) followed by Kisarawe (1,937 ha, 25.4%), Rufiji (1,294 ha, 17%), Kibaha (1,201 ha, 15.7%), Mkuranga (1,162 ha, 15.2%) and Mafia (40 ha, 0.5%) (Map 3.29). However, the area planted with oranges per orange growing household was highest in Kibaha (6.58 ha), followed by Bagamoyo (0.96 ha), Rufiji (0.53 ha), Kisarawe (0.31 ha), Mkuranga (0.3 ha) and Mafia (0.2 ha) (Chart 3.54 and Map 3.30). 3.4.4 Pineapples The total production of pineapples by smallholders was 9,419 tonnes. In terms of area planted, pineapples were the fourth most important permanent crop grown by smallholders in the region. They were grown by 5,370 households (3.9% of the total crop growing households). The average area planted with pineapples per household was relatively small at around 0.68 ha per pineapples growing household and the average yield obtained by smallholders was 4,498 kg /ha from a harvest area of 2,094 hectares. Chart 3.53 Percent of Area Planted with Coconuts and Average Planted Area per Household by District 9.1 7.6 18.2 26.4 11.0 27.6 0.0 20.0 40.0 Mafia Mkuranga Bagamoyo Rufiji Kisarawe Kibaha District % of Total Area Planted -0.05 0.20 0.45 0.70 0.95 1.20 1.45 1.70 1.95 2.20 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.54 Percent of Area Planted with Oranges and Average Planted Area per Household by District 0.53 16.94 15.22 26.21 15.73 25.36 0.00 10.00 20.00 30.00 Bagamoyo Kisarawe Rufiji Kibaha Mkuranga Mafia District % of Total Area Planted 0.00 2.00 4.00 6.00 8.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 1ha 2.1ha 0.3ha 0.5ha 0.8ha 1.3ha 1.9 to 2.3 1.5 to 1.9 1.1 to 1.5 0.7 to 1.1 0.3 to 0.7 Kibaha Kisarawe Mkuranga Rufiji Bagamoyo Mafia 1,317ha 1,575ha 4,569ha 1,906ha 3,155ha 4,778ha 0.7t/ha 1.5t/ha 2.2t/ha 1.1t/ha 1.5t/ha 2.2t/ha 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.27 PWANI Planted Area and Yield of Coconuts by District Map 3.28 PWANI Area Planted per Coconut Growing Household by District Yield (t/ha) Planted Area Per Household (ha) RESULTS 44 Kisarawe Bagamoyo Kibaha Rufiji Mkuranga Mafia 0.3ha 1ha 6.6ha 0.5ha 0.3ha 0.2ha Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 2,001ha 1,201ha 1,937ha 1,162ha 1,294ha 40ha 1.1t/ha 0.8t/ha 3.9t/ha 1.1t/ha 4.4t/ha 33t/ha Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.29 PWANI Planted Area and Yield of Oranges by District Map 3.30 PWANI Area Planted per Oranges Growing Household by District Yield (t/ha) Planted Area Per Household 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 5.4 to 6.7 4.1 to 5.4 2.8 to 4.1 1.5 to 2.8 0.2 to 1.5 RESULTS 45 RESULTS – Input/Implement Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 Bagamoyo has the largest area of pineapples in the region (1,762 ha, 48.6%) followed by Mkuranga (906 ha, 25%), Rufiji (533 ha, 14.7%), Mafia (372 ha, 10.3%), Kibaha (31 ha, 0.9%) and Kisarawe (23 ha, 0.6%) (Map 3.37). However, the average area planted per pineapple growing household was highest in Mafia (6.25 ha), followed by Bagamoyo (1.19 ha), Kisarawe (0.49 ha), Mkuranga (0.41 ha), Kibaha (0.39 ha), and Rufiji (0.36 ha), (Chart 3.55 and Map 3.38). Although Kisarawe had a planted area of 23 ha, the district reported no pineapples production. 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period, while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region during the long rainy season was 61,869 ha which represented 92.1 percent of the total planted area. Bush clearance, tractor slashing and burning are less important methods for land clearing and they represent 7.9 percent in total. (Table3.8). 3.5.2 Methods of Soil Preparation Hand cultivation is mostly used for soil preparation as it was used in an area of 128,353 ha which represented 95 percent of the total planted area, followed by ox-ploughing (4,137 ha, 3%) and tractor ploughing (3,132 ha, 2%). (Chart 3.57). Table 3.8: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 64,915 61,869 92 90,001 64,224 95 154,916 126,093 93 Mostly Bush Clearance 2,929 2,533 4 4,074 2,690 4 7,003 5,223 4 No Land Clearing 1,275 1,123 2 641 352 1 1,916 1,475 1 Mostly Tractor Slashing 458 731 1 154 71 0 612 802 1 Mostly Burning 410 928 1 986 531 1 1,396 1,460 1 Other 0 0 0 142 69 0 142 69 0 Total 69,986 67,185 100.0 95,998 67,937 100 165,985 135,122 100 Chart 3.55 Percent of Area Planted with Pineapples and Average Planted Area per Household by District 0.6 25.0 10.3 48.6 0.9 14.7 0.0 10.0 20.0 30.0 40.0 50.0 Bagamoyo Mkuranga Rufiji Mafia Kibaha Kisarawe District % of Total Area Planted 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 64,915 2,929 1,275 458 410 0 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Mostly Hand Slashing Mostly Bush Clearance No Land Clearing Mostly Tractor Slashing Mostly Burning Other Method of Land Clearing Number of Households Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 4,137, 3% Mostly Hand Hoe Ploughing, 128,353, 95% Mostly Tractor Ploughing, 3,132, 2% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 More hand cultivation was used during short rainy season at 96 percent against 94 percent for the long rainy season, whereas, oxen and tractor ploughing in the long rainy season were 3.4 percent and 3.0 percent respectively. For the short rainy season the corresponding percentages were 2.7 and 1.6 respectively. In Pwani region, Kibaha district had the largest planted area cultivated with oxen (1,157 hectares, 28%) followed by Bagamoyo (1,149 ha, 27.8%), Rufiji (1,099 ha, 26.6%), Kisarawe (336 ha, 8.1%), Mkuranga (333 ha, 8.0%) and Mafia (64 ha, 1.6%). During the long rainy season, 2.4 percent of the total area cultivated by using oxen was planted with cereals followed by roots and tubers (0.3%), pulses (0.3%), oil seeds (0.3%), fruit and vegetables (0%) and cash crops (0%). 3.5.3 Improved Seeds Use The planted area using improved seeds was estimated at 15,403 ha which represents 12 percent of the total planted with the annual crops and vegetables area. Cereals had the largest planted area with improved seeds (14,868 ha, 70% of the planted area with improved seeds) followed by pulses (2,443 ha, 12%), roots and tubers (1,815 ha, 9%), fruit and vegetables (1,345 ha, 6%), Oil seed (380 ha, 2%) and cash crops (374 ha, 2%). (Chart 3.60). However, the use of improved seeds in cash crops and fruit and vegetables is much greater than in other crop types (76% and 68% respectively), only 13 percent of the planted area for oil seed crops used improved seeds (Chart 3.61, Map 3.34). Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 1,815, 9% Pulses, 2,443, 12% Oilseeds , 380, 2% Fruits & Vegetables, 1,345, 6% Cereals, 14,868, 70% Cash Crops, 374, 2% 0 10 20 30 40 50 60 70 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals 0 10,000 20,000 30,000 40,000 50,000 60,000 Area Cultivated Bagamoyo Rufiji Mkuranga Kibaha Kisarawe Mafia District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.59 Planted Area of Improved Seeds - PWANI With Improved Seeds, 15,403 , 12% Without Improved Seeds, 114,829 , 88% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 3.5.4 Fertilizers Use The use of fertilisers on annual crops is very small with a planted area of only 14,284 ha (8% of the total planted area in the region). The planted area without fertiliser for annual crops was 163,388 hectares representing 92 percent of the total planted area with annual crops. Of the planted area with fertiliser application, compost was applied to 8,040 ha which represents 4.5 percent of the total planted area (59.3% of the area planted with fertiliser application in the region). This was followed by farm yard manure (4,669 ha, 2.6%). Inorganic fertilizers were used on a very small area and represented only 0.9 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizers (all types) was in Bagamoyo district (47.8%) followed by Mkuranga (25.4%), Kibaha (11.6%), Kisarawe (7.8%), Mafia (5.6%), and Rufiji (1.8%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 163,888 households, 90%) (Map 3.31). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (53% of the area planted with these fruit and vegetables during the long rainy season had an application of fertilizers). This was followed by cash crops (24%), oil seeds (20.2%), pulses (19.7%) cereals (10%) and roots and tubers (4%) Table3.9 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Bagamoyo 861 5,409 561 6,832 53,931 Kibaha 1,099 362 203 1,664 17,620 Kisarawe 337 706 68 1,112 19,808 Mkuranga 1,732 1,324 565 3,621 33,945 Rufiji 96 131 31 258 35,775 Mafia 543 107 148 797 2,308 Total 4,669 8,040 1,575 14,284 163,388 Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 560 624 2,403 4,105 451 417 29,270 32,856 32,684 44,062 Kibaha 559 670 265 204 106 42 8,090 8,723 9,019 9,905 Kisarawe 95 102 474 263 0 . 5,781 3,364 6,350 13,056 Mkuranga 385 425 834 439 158 98 7,965 4,872 9,342 23,162 Rufiji 0 . 72 52 0 . 10,008 8,782 10,080 17,846 Mafia 541 260 230 84 9 5 2,145 1,093 2,926 1,499 Total 2,141 2,081 4,277 5,147 724 562 63,258 59,691 70,400 109,531 Chart 3.62 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 163,388, 91% Mostly Compost, 8,040, 5% Mostly Inorganic Fertilizer, 1,575, 1% Mostly Farm Yard Manure, 4,669, 3% 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Area (ha) Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Pwani region was 4,810 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 4,690 and it was applied to 2,222 ha representing 2 percent of the total area planted during that season. (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (59%), followed by fruit and vegetables (18%), pulses (14%), roots and tubers (10%). For oil seeds and cash crops it was insignificant. However, fruit and vegetables had the highest percent of the planted area with farm yard manure (43% of the total area of fruit and vegetables in Pwani). This was followed by pulses (4%), cereals (3%), roots and tubers (1%), oil seeds (1%), and none for cash crops. (Chart 3.64 and Chart 3.65a). Farm yard manure is mostly used in Mafia (17.5% of the total planted area in the district), followed by Kibaha (5.7%), Mkuranga (4.6%), Kisarawe (1.6%), Bagamoyo (1.4%) and Rufiji (0.3%). (Chart 3.65b). For permanent crops, most farm yard manure is used for the production of cashew nuts (38.4%), followed by coconuts (32.8%), bananas (9.6%) and pawpaw (7.1%). Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - PWANI Cash Crops, 0, 0% Cereals, 2,817, 58% Fruits & Vegetables, 852, 18% Oilseeds, 21, 0% Pulses, 660, 14% Roots & Tubers, 460, 10% 0 5 10 15 20 25 30 35 40 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - PWANI Pulses, 218, 13.4% Oilseeds, 23, 1.4% Cereals, 1,031, 63.2% Roots & Tubers, 168, 10.3% Fruits & Vegetables, 192, 12.8% Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - PWANI 0.0 5.0 10.0 15.0 20.0 Mafia Kibaha Mkuranga Kisarawe Bagamoyo Rufiji District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Pwani region was 1,632 ha which represents 0.92 percent of the total planted area with annuals in the region and 10.2 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizers on their annual crops during the long rainy season was 1,291 and it was applied to 619 ha representing 1.2 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (63% of the total area applied with inorganic fertilizers), followed by pulses (13%), fruit and vegetables (12%) and roots and tubers (10%) (Chart 3.66). However, the proportion of fruits and vegetables with inorganic fertilizers was 10 percent, higher than other crop types, followed by pulses (1.2%), cereals (1%) and oil seeds (0.8%). (Chart 3.67a). Inorganic fertiliser is mostly used in Mafia (4.8% of the total planted area in the district), followed by Mkuranga (1.5%). Kibaha (1.1%), Bagamoyo (0.9%), Kisarawe (0.3%) and Rufiji (0.1%). (Chart 3.67b). In permanent crops inorganic fertiliser were used on cashew nuts (61%), followed by pineapples (21%), coconuts (13.2%), and pigeon peas (3.6%). 3.5.4.3 Compost Use The total planted area applied with compost was 9,553 ha which represents only 5.4 percent of the total planted area with annual crops in the region and 59.7 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 10,347 and it was applied to 6,660 ha representing 9.4 percent of the total area planted (Table 3.10). The proportion of area applied with compost was low for each type of crop (3 to 18%); however the distribution of the total area using compost manure shows that 59.5 percent of this area was cultivated with cereals, followed by roots & tubers (18.1%), pulses (15.4%), oil seeds (5.6%), fruits and vegetables (0.8%) and cash crops (0.6%). (Chart 3.68b). Compost is mostly used in Bagamoyo (8.9% of the total planted area in the district), and this is closely followed by Mkuranga (3.5%), Mafia (3.5%), Kisarawe (3.4%), Kibaha (1.9%), and Rufiji (0.4%). (Chart 3.68c). 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - PWANI Chart 3.68a Planted Area with Compost by Crop Type - PWANI Roots & Tubers 1,729, 18.1% Cereals, 5,679, 59.1% Fruits & Vegetables, 77, 0.8% Pulses, 1,475, 15.4% Oilseeds, 533, 5.6% Cash Crop, 59, 0.6% Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - PWANI 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Mafia Mkuranga Kibaha Bagamoyo Kisarawe Rufiji District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 In permanent crops, compost was mostly used for the production of cashew nuts (69%) followed by oranges (14.3%), coconuts (9.9%) and mango (2.4%). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 11,840 ha of annual crops and vegetables. Insecticides are the most common pesticides used in the region (44% of the total area applied with pesticides). This was followed by fungicides (33%) and herbicides (23%) (Chart 3.69). 3.5.5.1 Insecticides Use The planted area applied with insecticides represented 3.2 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (3,106 ha, 54% of the total planted area with insecticides) followed by fruit and vegetables (1,123 ha, 19.5%), pulses (791 ha, 13.7%), roots and tubers (658 ha, 11.4%), cash crops (59 ha, 1%) and oil seed (18 ha, 0.3%) (Chart 3.70). However, the percent of insecticides used in fruits and vegetables and 0 2 4 6 8 10 12 14 16 18 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type - PWANI Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 59, 1.0% Cereals, 3,106, 54.0% Fruits & Vegetables, 1,123, 19.5% Oil seeds & Oil nuts, 18, 0.3% Pulses, 791, 13.7% Roots & Tubers, 658 11.4% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.68c Proportion of Planted Area Applied with Compost by District - PWANI 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Bagamoyo Mkuranga Mafia Kisarawe Kibaha Rufiji District Percent Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 3,884, 33% Herbicides, 2,691, 23% Insecticides, 5,265, 44% Tanzania Agriculture Sample Census Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 35,672ha 32,567ha 19,777ha 17,490ha 53,864ha 2,306ha 99% 86.7% 94.5% 90.7% 88.6% 74.3% 44,000 to 55,000 33,000 to 44,000 22,000 to 33,000 11,000 to 22,000 0 to 11,000 Area Planted With no Fertilizer Applied Area Planted With no Fertilizer Applied Map 3.31 PWANI Planted Area and Percent of Planted Area With No Application of Fertilizer by District Percent of Area Planted With no Fertilizer Applied RESULTS 52 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 cash crops is much greater than in other crop types (56.5 and 12% respectively), while only 0.6 percent of oil seed crops were applied with insecticides (Chart 3.71). Although cereals had 54% insecticides use, only maize ranked highest with 36.6%. Hence, there were no annual crops with more than 50 percent insecticides use. Kibaha had the highest percent of planted area with insecticides (5.3% of the total planted area with annual crops in the district). This was closely followed by Mkuranga (3.1%) then Rufiji (3.0%), Bagamoyo (2.5%) and Kisarawe (2.2%). The smallest percentage use was recorded in Mafia district (0.1%) (Chart 3.72). 3.5.5.2 Herbicides Use The planted area applied with herbicides was 3,524 ha which represented 2.0 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (2,049 ha, 58%) followed by roots and tuber (877 ha, 25%), pulses (372 ha, 11%), fruits and vegetables (185 ha, 5%) and oil seed (41 ha, 1%). None for cash crops. (Chart 3.73). However, the percent of herbicides use on fruit and vegetables and pulses was much greater than in other crop types (9.3% and 2.1% respectively) while only 1.4 percent of oil seeds was applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (38%), cassava (25%), paddy (17%), cowpeas (9%), sorghum (4%) and water melon (2%). Rufiji had the highest percent of planted area with herbicides (2.5% of the total planted area with annual crops in the district). This was followed by Mkuranga (1.9%) then Mafia (1.4%), Bagamoyo (1.3%) and Kibaha (1%). The smallest percentage use was recorded in Kisarawe district (0.4%) (Chart 3.75). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Roots & Tubers 877, 25% Pulses, 372, 11% Oil seeds & Oil nuts, 41, 1% Fruits & Vegetables, 185, 5% Cereals, 2,049, 58% Cash crops, 0, 0% 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent of Planted Area Fruits & Vegetables Pulses Cereals Roots & Tubers Oil seeds & Oil nuts Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - PWANI 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Rufiji Mkuranga Mafia Bagamoyo Kibaha Kisarawe District Percent Chart 3.72 Percent of Planted Area Applied with Insecticides by District - PWANI 0.0 2.0 4.0 6.0 Kibaha Mkuranga Rufiji Bagamoyo Kisarawe Mafia District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 3.5.5.3 Fungicides Use The planted area applied with fungicides was 5,039 ha which represented 2.8 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (3.5%) was higher than the corresponding percentage for the long rainy season (2.4%). Cereals had the largest planted area applied with fungicides (2,606ha, 52%) followed by fruits and vegetables (1,062 ha, 21%), pulses (662 ha, 13%), roots and tubers (631 ha, 12.5%), cash crops (59 ha, 1%) and oil seeds (18 ha, 0.4%) (Chart 3.76). However, the percentage use of fungicides in fruits and vegetables and cash crops was much greater than in other crop types (53% and 12% respectively), while only 0.6 percent of oil seeds was applied with fungicides (Chart 3.77). Annual crops with more than 40 percent fungicides use were field peas (100%), tomatoes (81%), cotton (79%), cucumber (78%), Onions (74%), chillies (43%) and egg plants (42%). Mkuranga had the highest percent of planted area with fungicides (3.5% of the total planted area with annual crops in the district). This was closely followed by Kibaha (3.0%) and Rufiji (2.0%). The smallest percentage use was recorded in Mafia district (0.5%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (2.7%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 53 percent of the total area planted with cereals during the long rainy season being threshed by hand. Human powered tools and engine driven machines were only used on crops harvested from 0.4 percent and 2.3 percent of the total planted area respectively. No draft animals were used during threshing. Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 631, 13% Pulses, 662, 13% Oil seeds, 18, 0.4% Fruits & Vegetables, 1,062, 21% Cereals, 2,606, 52% Cash crops, 59, 1% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent of Planted Area Fruits & Vegetables Cash crops Pulses Cereals Roots & Tubers Oil seeds Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - PWANI 0.0 1.0 2.0 3.0 4.0 Mkuranga Kibaha Rufiji Bagamoyo Kisarawe Mafia District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Pwani region, the area of annual crops under irrigation was 58,870 ha representing 33.1 percent of the total area planted (Chart 3.79). The area under irrigation during the short rainy season was 1,512 ha accounting for 2.6 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season, 64 percent of the area planted with vegetables was irrigated, whilst 57 percent of the vegetables were irrigated in the long rainy season. The district with the largest planted area under irrigation with annual crops was Mkuranga (18,275 ha, 40.7% of the total irrigated planted area with annual crops in the region). This is closely followed by Rufiji with (9,711 ha, 21.6%) and then Kisarawe (9,482 ha, 21.1%). The smallest is Mafia (117 ha, 0.3%). When expressed as a percentage of the total area planted in each district, Mkuranga had the highest with 49 percent of the planted area in the district under irrigation. This is followed by Kisarawe (45%), Rufiji (27%), Bagamoyo (10%), Kibaha (5%), and Mafia (4%) (Chart 3.80 and Map 3.32). edit chart title Of all the different crops and in terms of proportion of the irrigated planted area, onions, cabbage, chillies and spinach were the most irrigated crops with 100 percent irrigation followed by water melon (98%), amaranthus (89%), egg plant (83%) and cucumber (82%). In terms of crop type, the area under irrigation with roots and tubers was 41,916 ha (93% of the total area under irrigation), followed by cereals with 1,535 ha (3%), fruit and vegetables (1,210 ha, 3%) and pulses (255 ha, 0.6%). All of the irrigation on cereals was applied to sorghum, maize and paddy. Chart 3.79 Area of Irrigated Land Unirrigated Area, 132,752, 75% Irrigated Area, 44,920, 25% Chart 2.80 Planted Area with Irrigation by District - PWANI Region 0 4,000 8,000 12,000 16,000 20,000 Mkuranga Rufiji Kisarawe Bagamoyo Kibaha Mafia Region Irrigated A rea (h a) 0 10 20 30 40 50 60 Percen ta ge Irrigation Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation - PWANI 2,908 3,815 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 1995/96 2002/03 Agriculture Year Planted Area ubder Irrigation Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 9,711ha 18,275ha 9,482ha 984ha 6,351ha 117ha 26.9% 48.6% 45.3% 5.1% 10.5% 3.8% 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Planted Area With Irrigation Map 3.32 PWANI Area Planted and Percent of Total Planted Area With Irrigation by District Planted Area With Irrigation Percent of Total Planted Area With Irrigation RESULTS 56 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 Chart 3.82 Number of Households with Irrigation by Source of Water Borehole, 158, 3% Pipe water, 342, 6% Dam, 374, 7% Well, 2,132, 40% River, 1,871, 35% Canal, 432, 8% Canal River Well Dam Pipe water Borehole The area of fruit and vegetables under irrigation was 1,210 ha which represents 61 percent of the total planted area with fruit and vegetables. Onions, cabbages, chillies and spinach were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Pwani region appears to have increased over the 10 year intercensal period from 2,908 to 3,815 hectares. This may not be statically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from wells (40% of households with irrigation). This was followed by river (35%) and canal (8%). Only 3 percent of the households used water from boreholes and the proportion of households that used dams and pipe as a source of water for irrigation were very few (7% and 6% respectively). Most households using irrigation in Rufiji and Bagamoyo get their irrigation water from rivers (100 and 60 % respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common means of getting water for irrigation with 80.1 percent of households using this method. The remaining methods (hand pump, motor pump and gravity) were of minor importance (Chart 3.83). Hand bucket was used by most households with irrigation in Mkuranga (49.7%), followed by Kibaha (20.2%), Bagamoyo (16.3%), Kisarawe (7.6%), Rufiji (3.7%) and Mafia (2.5%). Gravity was more common in Bagamoyo with 41.1 percent of households using the method to get water for irrigation, followed by Mkuranga (35.2), Kibaha (17.2%), Mafia (6.5%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Bagamoyo and Mkuranga districts used some hand and motor pumps for obtaining water. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 238, 4.5% Hand Bucket, 4,251, 80.1% Motor Pump, 259, 4.9% Hand Pump, 262, 4.9% Other, 299, 5.6% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 98, 2% Bucket / Watering Can, 4,195, 79% Flood, 913, 17% Water Hose, 104, 2% Flood Bucket / Watering Can Sprinkler Water Hose RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.6.4 Methods of Water Application Most households used hand bucket/watering can irrigation (79% of households using irrigation) as a method of field application. This was closely followed by flood (17%). Water hose and Sprinklers were not widely used (2% and 1.8% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seeds for planting in the following season. The results for Pwani region show that there were 43,973 crop growing households (31.5% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 28,351 households storing 6,888 tonnes. This was followed by beans and other pulses (11,798 households, 208t), paddy (11,095 households, 1,538t) and sorghum & millet (2,466 households, 196t). Other crops were stored in very small amounts. 3.7.1.1 Methods of Storage The region had 25848 crop growing households storing their produce in locally made traditional structures (59% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 12,447 (28%). This was followed by: unprotected piles (1,740 households, 4%), improved locally made structures (1,538 households, 3%), air tight drums (795 households, 21%) and modern stores (138 households, 0.3%) and other methods (1,467 households, 3%). Locally made traditional structures were the dominant storage method in all districts, with the highest percent of households in Rufiji using this method (69% of the total number of households storing crop products). This was followed by Kisarawe (68%), Bagamoyo (63%), Mkuranga (47%), Mafia (28%) and Kibaha (23%). (Chart 3.87). The highest percent of households using sacks and open drum was in Mafia and Kibaha districts (68% and 63% of the total number of households storing crops), followed by Bagamoyo (27%), Kisarawe (27%), Mkuranga (23%), and Rufiji (11%). Chart 3.85 Number of Households and Quantity Stored by Crop Type - PWANI 0 5,000 10,000 15,000 20,000 25,000 30,000 Maize Beans & P uls es P addy Cas hewnut So rghum & MilletGro undnuts /Bambara Nuts Crop Number of households 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.86 Number of households by Storage Methods - PWANI Locally Made Traditional Crib, 25,848, 59% Sacks / Open Drum, 12,447, 28% Modern Store, 138, 0% Airtight Drum, 795, 2% Other, 1,467, 3% Improved Locally Made Crib, 1,538, 3% Unprotected Pile, 1,740, 4% Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.1.2 Duration of Storage Most households (51.0% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of less than 3 months (27%). The minority of households stored their crop for a period of over 6 months (22%). Most households that stored pulses stored them for a period of 3 to 6 months followed by less than 3 months. A small number of households stored pulses for the period of over 6 months (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Bagamoyo district (55%) followed by Rufiji (54%), Mkuranga (52%), Kibaha (48%), Mafia (46%) and Kisarawe (44%). (Map 3.33). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Kisarawe district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize with household consumption as the main purpose of storage was 88.2 percent followed by seeds for planting. A high percent of the stored permanent crops was for household consumption as was the case of cashew nuts (66.2%). This was followed by selling at a higher price (23.2%) (Chart 3.90). 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Quantity (tonnes) 0 5 10 15 20 25 30 35 40 45 % Stored Quantity harvested Quantity stored % stored 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of H o useho lds Maize Paddy Sorghum & Mi... Beans & Pulses Wheat Cashewnut G'nuts/BambNuts Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Rufiji Mkuranga Kisarawe Kibaha Mafia Bagamoyo 18,600 24,950 11,381 6,662 12,132 4,732 60% 72% 61% 47% 33% 80% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Rufiji Kibaha Mafia 9% 12% 5% 4% 19% 3% Kisarawe Mkuranga Bagamoyo 16 to 20 12 to 16 8 to 12 4 to 8 0 to 4 Tanzania Agriculture Sample Census Percent of Households Storing Crops Percent of Households Storing Crops Number of Households Selling Crops Map 3.33 PWANI Percent of households storing crops for 3 to 6 months by district Map 3.44 PWANI Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops Percent of Total Households Selling Crops RESULTS 60 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.7.1.4 The Magnitude of Storage Loss About 76.3 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as cashew nuts, groundnuts and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (0.025% of the total number of households that stored crops). This was followed by beans and pulses (0.024%), maize (0.018%), groundnuts and paddy (0.006%). Most households that stored cash crops such as cashew nuts had little or no loss (98.6%). All households storing wheat had no storage loss (100%) (Table 3.10). 3.7.2 Agro-processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Pwani region (55,704 households, 40% of the total crop growing households). (Chart 3.91a). The percent of households processing crops was low in most districts. Kisarawe and Kibaha had the highest percent of households processing crops (77% and 44% of crop growing households respectively). (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops on- farm by hand representing 72 percent (40,175 households). This was followed by those processing using neighbour’s machines (13,010 households, 23.4%), on-farm by machine (1,183 households, 2.1%) trader (586 households, 1.1%). The remaining methods of processing were used by very few households (each less than 1%). Although processing on-farm by hand was the most common processing method in all districts in Pwani region, district differences existed. Bagamoyo had a higher percent of processing using neighbour’s machine than other districts.(63%), followed by Kibaha (32%), Rufiji (21%) and Kisarawe (15%). Processing by trader was dominated by Bagamoyo (6%), whilst processing on farm by machine was more prevalent in Bagamoyo, Mkuranga and Rufiji. (Chart 3.92). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Bagamoyo 9,759 3,548 1,573 201 15,080 Kibaha 3,127 105 79 0 3,312 Kisarawe 7,261 426 1,265 145 9,098 Mkuranga 3,891 235 323 0 4,449 Rufiji 7,243 1,693 406 81 9,423 Mafia 2,281 272 43 17 2,614 Total 33,563 6,279 3,688 444 43,974 Chart 3.91a Households Processing Crops Households Processing, 55,704, 39% Households not Processing, 85,826, 61% 0 20 40 60 80 Percent of Households Processing Kisarawe Kibaha Mkuranga Rufiji Mafia Bagamoyo District Chart 3.91b Percentage of Households Processing Crops by District Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader Other By Factory RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is the secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 41,056 households processing crops into flour (74%) followed by grain with 8,234 households (15%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 75 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 24,692 households (57%) followed by shell (9,446 households, 22%), husk (3,807 households, 8%) and pulp (1,576 households, 3%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Bagamoyo was the only district that used primary products as fuel for cooking and all of it from maize crop. Out of 6,584 households that sold processed products, 3,799 were from Rufiji (57.7% of the total number of households selling processed products in the region), followed by Bagamoyo with 1,212 households (18.4%), Mkuranga with 805 households (12.2%), Kisarawe with 366 households (5.6%), Kibaha with 357 households (5.4%), and Mafia with 45 households (0.7%) (Chart 3.96). Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal 74% Pulp 0.1% Other 5% Juice 0.0% Oil 6% Grain 15% Chart 3.95 Use of Processed Product Household/ human consumption, 72,982, 98.2% Fuel for Cooking, 100, 0.1% Sale Only, 390, 1% Did Not Use, 583, 1% Animal Consumption, 173, 0.2% Chart 3.94 Number of Households by Type of By-product Husk, 3,807, 8% Bran, 24,692, 57% Pulp, 1,576, 3% Cake, 3,072, 7% Other, 1,081, 2% Shell, 9,446, 22% Juice, 87, 0% 0.00 10.00 20.00 30.00 40.00 50.00 60.00 Percentage of households Rufiji Bagamoyo Mkuranga Kisarawe Kibaha Mafia District Chart 3.96 Percentage of Households Selling Processed Crops by District RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold to other unspecified outlets (3664 households, 56% of households that sold crops). This was followed by selling to neighbours (1,571 households, 24%), trader at farm (529 households, 8%), local market and trade stores (377 households, 6%), marketing co-operatives (183 households, 3%), large scale farm (129 households, 2%) and farmers associations (44 households, 1%). (Chart 3.97). There were large differences between districts in the proportion of households selling processed products to neighbours with Mafia district having all the households in the district selling to neighbours (100%), whereas Bagamoyo had only 6 percent. Mkuranga had a higher percent of households relying on trader at farm than other outlets. Compared to other districts, Mkuranga had the highest percent of households selling processed products to local market and trade stores. In Kisarawe, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Kisarawe, Kibaha and Bagamoyo. (Chart 3.98). 3.7.3 Crop Marketing The number of households that reported selling crops was 78,458 which represented 56 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Mafia (80%) followed by Mkuranga (72%), Kisarawe (61%), Rufiji (60%), Kibaha (47%) and Bagamoyo (33%). (Chart 3.99 and Map 3.34). Chart 3.97 Location of Sale of Processed Products Neighbours, 1,571, 24% Local Market / Trade Store, 377, 6% Marketing Co- operative, 183, 3% Other, 3,750, 57% Trader at Farm, 529, 8% Large Scale Farm, 129, 2% Farmers Association, 44, 1% Chart 3.98 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Bagamoyo Kibaha Kisaraw e Mkuranga Rufiji Mafia District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 5,000 10,000 15,000 20,000 25,000 30,000 Mkuranga Rufiji Bagamoyo Kisarawe Kibaha Mafia District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (77% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (6%), lack of transport (4%), high transport costs (4%), lack of buyers (4%) other marketing problems (3%), and lack of market information (2%). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 54 percent of the smallholders, followed by other unspecified reasons (41%). The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts except for Kibaha and Rufiji where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (49% and 47% respectively). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census results show that in Pwani region very few agricultural households (1,681, 1.2%) accessed credit out of which 1,521 (90%) were male-headed households and 160 (10%) were female headed households. While no district had only female headed households getting agricultural credit whereas in Bagamoyo, and Rufiji districts only male households (100%) accessed credit. In Mkuranga district both male and female headed households accessed agricultural credit (Table 3.12). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Pwani region were cooperatives who collectively provided credit to 1,094 agricultural households (65% of the total number of households that accessed credit), followed by religious Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 34,380 54.4 Other 25,884 41.0 Price Too Low 914 1.4 Co-operative Problems 902 1.4 Trade Union Problems 497 0.8 Government Regulatory Board Problems 353 0.6 Market Too Far 124 0.2 Farmers Association Problems 108 0.2 Total 63,161 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Bagamoyo 98 100 0 0 98 Mkuranga 1,339 89 160 11 1,499 Rufiji 83 100 0 0 83 Total 1,521 90 160 10 1,681 Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Bagamoyo Mkuranga Rufiji District Percent of Households Family, Friend and Relative Commercial Banks Saving & Credit Society Trader/Trade Store Religious Organisation/NGO/Project Other Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Lack of Market Information 2% Other 3% Co-operative Problems 1% Market too Far 5% Transport Cost Too High 4% No Transport 4% Farmers Association Problems 1% No Buyer 4% Government Regulatory Board Problems 1% Open Market Price Too Low 77% Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 6% Religious Organisation / NGO / Project 37% Private Individual 5% Co-operative 65% Other 0% Trader / Trade Store 10% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 organizations/non governmental organizations/ projects (15%), trader/trade store (10%), commercial bank (6%), private individuals (5%) and none from other sources (0%). (Chart 3.101). Commercial banks were the sole source of credit in Bagamoyo district and savings and credit societies were found in Mkuranga district only. Trader/trader stores were credit providers in Mkuranga district only. Religious organizations, NGO’s and projects were more involved in funding a relatively great number of households in Mkuranga and Rufiji districts only. (Chart 3.102). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credits provided to agricultural households in the region were used on agro- chemicals (30%), followed by fertilizers (12%), irrigation structures (11%), livestock (11%), hiring labour (10%), and others (10%). (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting for 61 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (21%), followed by “not wanting to go into debt” (8.0%) The rest of the reasons were collectively less than 9 percent of the households. 3.8.2 Crop Extension The number of agricultural households that received crop extension was 46,727 (34% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Kisarawe having a relatively high proportion of households (61%) that received crop extension messages in the district followed by Kibaha (43%), Bagamoyo (32%), Mkuranga (28%), Rufiji (25%) and Mafia (4%). (Chart 3.106 and Map 4.35). Chart 3.104 Reasons for not Using Credit (% of Households) Not available, 29,261, 21% Did not want to go into debt, 11,805, 8.4% Difficult bureaucracy procedure, 4,227, 3% Not needed, 4,635, 3.3% Interest rate/cost too high, 3,410, 2% Credit granted too late, 620, 0.4% Other, 361, 0.3% Don't know about credit, 60,631, 43.4% Did not know how to get credit, 24,900, 17.8% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 11% Labour 10% Fertilizers 12% Other 10% Agro-chemicals 30% Irrigation Structures 11% Tools / Equipment 8% Seeds 8% Rufiji Mkuranga Kisarawe Kibaha Mafia 1,880 6,412 5,016 5,165 9,643 772 1% 4% 3% 3% 6% 0% Bagamoyo 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 7,603 9,560 11,435 6,049 11,835 245 24.6% 27.5% 61.4% 43.1% 31.7% 4.1% 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Number of Households Receiving Crop Extension Percent of Total Households Receiving Crop Extension Number Of Households Using Improved Seeds Map 3.35 PWANI Number of Households and Percent of Total Households Receiving Crop Extension Services by District Map 3.36 PWANI Number Of Households and Percent of Households Using Improved Seeds By District Percent of Households Using Improved Seeds Percent of Total Households Receiving Crop Extension Number Of Households Using Improved Seeds RESULTS 66 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the government provided the greatest proportion of the services (96.8%, 44,669 households) followed by large scale farms 1.6%, cooperatives 0.8%, NGOs provided 0.5%, and the remaining providers (0.3 percent (Chart 3.107). However district differences exist with the proportion of the households receiving advice from government services ranging from between 82.0 percent and 100 percent in Mafia and Rufiji respectively. 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 66 percent of the households receiving extension ranked the service as being good followed by average (16%), very good (16%), no good (1%) and poor (1%). (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 94,803, 67% Households Receiving Extension , 46,727, 33% Chart 3.106 Number of Households Receiving Extension by District 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 Kisarawe Kibaha Bagamoyo Mkuranga Rufiji Mafia District Number of Households 0 20 40 60 80 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 1.6% Cooperative 0.8% NGO / Development Project 0.5% Other 0.3% Government 96.8% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 30,499, 65.8% Average, 7,605, 16.4% Poor, 357, 0.8% No Good, 390, 0.8% Very Good, 7,474, 16.1% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Pwani region regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm e.g. inorganic fertilizers, fungicides, and herbicides. In Pwani region, improved seeds were used by 21,121 households which represents 15 percent of the total number of crop growing households. This was followed by households using pesticides/fungicides (12%), compost (8.2%) farm yard manure (6.7%), inorganic fertilisers (2.7%), and herbicides (0.2%). (Table 3.14). 3.9.1 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Pwani mostly purchased them from the local market/trade store (93.2% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers were of minor importance. (Chart 3.109). Access to inorganic fertilisers was mainly more than 10 km from the household with most households residing more tha 20 km from the source (43.2%), followed by between 10 and 20 km (17.4%) and between 3 and 10 km (16.2%) (Chart 3.110). Due to the small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertilisers was not the main reason for not using it. Other reasons such as cost are more important with 70 percent of households responding to cost factors as the main reason for not using. In other words, if the cost was affordable the demand would be higher and inorganic fertilisers would be made more available. More smallholders use inorganic fertilisers in Mkuranga than in other districts in Pwani region (54% of households using inorganic fertilisers), followed by Bagamoyo (22%), and Kibaha (11%). While Mafia and Kisarawe districts use very little inorganic fertiliser, it is none for Rufiji. Table 3.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Improved seeds 21,121 15.1 118,323 84.9 Pestcides/Fungicide 17,019 12.2 122,425 87.8 Compost 11,417 8.2 128,027 91.8 Farm yard manure 9,311 6.7 130,133 93.3 Inorganic fertiliser 3,801 2.7 135,643 97.3 Herbicide 326 0.2 139,118 99.8 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 93.2 5.4 0.9 0.5 0.0 0.0 0 500 1000 1500 2000 2500 3000 3500 4000 Local Market / Trade Store Neighbour Co-operative Locally Produced by Household Large Scale Farm Development Project Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 3.9.2 Improved Seeds The percent of households that use improved seeds was 15 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (74%). Other but less important sources of improved seeds were neighbours (11.6%), development partners (5.3%), and locally produced by household (3%). Only 0.5 percent of households using improved seeds obtained them from large scale farms. (Chart 3.111). Access to improved seeds was slightly better than access to chemical inputs with 41 percent of households obtaining the input more than 20 km from the household. (Chart 3.112). This is in line with the higher use of improved seeds compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that used improved seeds most was Bagamoyo (28.8 percent of the total number of households using improved seeds in Pwani region), followed by Mkuranga (24.8%), Kisarawe (22.4%), and Kibaha (16.2%). Use of improved seeds in Rufiji and Mafia districts is of minor importance. 3.9.3 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (55% of the total number of fungicides users), followed by local farmers’ group (28%). Other sources of insecticides/ fungicides were of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticides/fungicides. The small number of households using insecticides/fungicides coupled with the 13 percent of Chart 3.111 Number of Households by Source of Improved Seed 0.7 0.5 1.1 0.9 1.4 1.4 3.0 5.3 11.6 74.0 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Local Market / Trade Store Neighbour Development Project Locally Produced by Household Crop Buyers Local Farmers Group Other Co-operative Secondary Market Large Scale Farm Source of Improved Seed Number of Households Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 5 10 15 20 25 30 35 40 45 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of H ouseholds Chart 3.113 Number of Households by Source of Insecticide/fungicide 54.9 27.9 8.7 3.6 2.2 1.5 0.5 0.7 0.0 0.0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Local Market / Trade Store Local Farmers Group Co-operative Neighbour Crop Buyers Development Project Other Large Scale Farm Locally Produced by Household Secondary Market Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 households responding to “not available” as the reason for not using them, it may be assumed that access was not the main reason for not using them. Other reasons such as cost were more important with 73 percent of households responding to cost factors as the main reason for not using. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were used more in Mkuranga district (58.7 percent of the total number of households that use fungicides in the region), followed by Rufiji (12.8%), Bagamoyo (11.9%) and Kibaha (11.1%). Insecticides/fungicides use in Kisarawe and Mafia districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 3,240 representing 2 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 351,510 trees. The average number of trees planted per household planting trees was 109 trees. The main species planted by smallholders is Melicia excelsa (124,182 trees, 35.3%), followed by Senna Spp (71,987, 20.5%), then Tectona Grandis (59,168, 16.8%), Acacia Spp (24,4791 trees, 7%), Eucalyptus Spp (15,570, 4.4%), Gravellis (14,480, 4.1%), Moringa Spp (12,936, 3.7%) and Cyprus Spp (11,693, 3.3%). The remaining trees species are planted in comparatively small numbers (Chart 3.116). Kibaha has the largest number of smallholders with planted trees than any other district (64.5%) and is dominated by Melicia excelsa. This is followed by Bagamoyo (11.6%) which is dominated by Tectona Grandis and Gravellis, Rufiji (11.2%) dominated by Tectona Grandis, Kisarawe (7.7%) which is mainly planted with Moringa Spp and Mkuranga (4.1%) which is dominated by Eucalyptus Spp. (Chart 3.117 and Map 3.37.). Smallholders mostly plant trees scattered around fields. The proportion of households that plant trees scattered around fields is 40 percent, followed by planted on boundary of fields (35%) and then trees planted in a plantation or coppice (25%) (Chart 3.118). Chart 3.115 Number of Households with Planted Trees Growing trees, 3,240, 2% Not growing trees, 138,290, 98% Chart 3.116 Number of Planted Trees by Species - PWANI 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Melicia excelsa Senna Spp Tectona Grandis Acacia Spp Eucalyptus Spp Gravellis Moringa Spp Cyprus Spp Azadritachta Spp Leucena Spp Casurina Equisetfilia Others Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and District 0 50,000 100,000 150,000 200,000 250,000 Kibaha Bagamoyo Rufiji Kisaraw e Mkuranga Mafia District N umber o f T rees Melicia excelsa Senna Spp Tectona Grandis Acacia Spp Eucalyptus Spp Gravellis Moringa Spp Cyprus Spp Azadritachta Spp Leucena Spp Casurina Equisetfilia Others RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 The main purpose of planting trees is to obtain planks/timber (46.2%). This is followed by wood for fuel (30.1%), shade (10.8%), poles (10.5%), other purposes (2.0%), and medicinal (0.6%). (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 1,935 which represents 1 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Kisarawe district (4%) followed by Mkuranga (2%), Mafia (2%), Kibaha (1%), Bagamoyo (1%) and none in Rufiji. (Chart 3.121). Erosion control bunds accounted for 39.5 percent of the total number of structures, followed by Tree belts (31.3%), water harvesting bunds (25%), Gabions (1.9%), Vetiver (1.0%), Dam (0.7%) and Terraces (0.6%). (Chart 3.122 and Map 3.38). Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 1,935, 1% Households Without Facilities, 139,595, 99% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 4 2 2 1 1 0 0 100 200 300 400 500 600 700 800 Kisarawe Mkuranga Mafia Kibaha Bagamoyo Rufiji District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.118 Number of Trees Planted by Location Field boundary, 123,290, 35% Scattered in field, 141,125, 40% Plantation, 86,947, 25% Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Wood for Fuel Shade Poles Other Medicinal Charcoal Use Percent of Households Rufiji Mkuranga Kisarawe Kibaha Mafia 508 182 575 8,418 428 122 5% 1.8% 5.6% 82.3% 4.2% 1.2% Bagamoyo 6,000 > 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 0 490 2,899 0 0 2,820 0% 2% 11.7% 0% 0% 11.4% Tanzania Agriculture Sample Census Number of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households with Water Harvesting Bunds Map 3.37 PWANI Number and Percent of Smallholder Planted Trees by District Map 3.38 PWANI Number and Percent of Households with Water Harvesting Bunds by District Percent of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Number of Households with Water Harvesting Bunds RESULTS 72 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 Erosion control bunds, tree belts and water harvesting bunds together had 23,758 structures. This represented 96 percent of the total structures in the region. The remaining 4 percentage were shared among the rest of the erosion control methods mentioned above. Mkuranga, Mafia and Kibaha districts had 19,049 erosion control structures (77 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 122,308. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 0.7 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Pwani region was 110,360 (90.2% of the total number of cattle in the region), 10,809 cattle (8.8%) were dairy breeds and 1,140 cattle (0.9%) were beef breeds. The census results show that 5,568 agricultural households in the region (4% of total agricultural households) kept 0.12 million cattle. This was equivalent to an average of 22 heads of cattle per cattle- keeping-household. The district with the largest number of cattle was Bagamoyo which had about 94,401cattle (77.2% of the total cattle in the region). This was followed by Mafia (11,781 cattle, 9.6%), Kibaha (9,144 cattle, 7.5%), Rufiji (3,503 cattle, 2.9%), and Kisarawe (3,190 cattle, 2.6%). Mkuranga district had the least number of cattle (289 cattle, 0.2%) (Chart 3.123 and Map 3.39). However Mafia district had the highest density (54 head per km2 ) (Map 3.40). Although Bagamoyo district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and no beef cattle were recorded. However, the district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (0.9%). (Chart 3.124). Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.6 0.7 1.0 1.9 25.1 31.3 39.5 0 2,000 4,000 6,000 8,000 10,000 12,000 Erosion Control Bunds Tree Belts Water Harvesting Bunds Gabions / Sandbag Vetiver Grass Dam Terraces Type of Facility Number of Structures 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Number of Cattle ('000') Bagamoyo Mafia Kibaha Rufiji Kisarawe Mkuranga Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Districts Number of Cattle Indigenous Beef Dairy Bagamoyo Kibaha Rufiji Mafia 29.8 10.4 0.3 2.1 0.6 53.7 Kisarawe Mkuranga 40 > 30 to 40 20 to 30 10 to 20 0 to 10 Rufiji Kibaha Bagamoyo Mafia 3,503 289 3,190 9,144 94,401 11,781 Kisarawe Mkuranga 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Number of Cattle Number of Cattle Number of Cattle Per Square Km Map 3.39 PWANI Cattle population by District as of 1st October 2003 Map 3.40 PWANI Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km RESULTS 74 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 75 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 N u m b er o f G o a ts ('0 0 0 '). Bagamoyo Rufiji Mkuranga Kibaha Kisarawe Mafia District Chart 3.127 Total Number of Goats ('000') by District 3.12.1.2 Herd Size Forty percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 23% percent of all cattle in the region. Only 17 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 79 percent of total cattle rearing households had herds of size 1-30 cattle and owned 28 percent of total cattle in the region, resulting in an average of 8 cattle per cattle rearing household. There were about 102 households with a herd size of more than 151 cattle each (23,405 cattle in total) resulting in an average of 229 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Pwani increased during the eight-year period from 40,490 in 1995 to 122,308 cattle in 2003. This trend depicts an overall annual positive growth rate of 14.8 percent. (Chart 3.125). There was a very sharp increase in number of cattle during the four-year period from 1995 to 1999 at the rate of 25.9 percent whereby the number increased from 40,490 to 101,594. Also, the number of cattle is estimated to have increased moderately from 101,594 in 1999 to 122,308 in 2003 at the rate of 4.7 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Pwani region was 11,948 (10,809 dairy and 1,140 improved beef). The dairy cattle constituted 8.8 percent of the total cattle and 90.5 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 9.5 percent of the total number of the improved cattle and 0.9 percent of the total cattle. The number of improved cattle increased drastically from 1,450 in 1999 to 11,948 in 2003 at an annual growth rate of 69.4 percent. (Chart 3.126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Pwani region ranked 20th out of the 21 regions with 0.8 percent of the total goats on the Mainland. 40,490 101,594 122,308 - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend - 1,450 11,948 - 2,000 4,000 6,000 8,000 10,000 12,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Improved Cattle Population Trend RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 3.12.2.1 Goat Population The number of goat-rearing-households in Pwani region was 7,621 (5% of all agricultural households in the region) with a total of 98,604 goats giving an average of 13 head of goats per goat-rearing-household. Bagamoyo had the largest number of goats (68,472 goats, 69.4% of all goats in the region), followed by Rufiji (13,406 goats, 13.6%), Mkuranga (5,714 goats, 5.8%), Kibaha (5,226 goats, 5.3%) and Kisarawe (4,847 goats, 5%). Mafia district had the least number of goats (940 goats, 1%). (Chart 3.127 and Map 3.41). However Bagamoyo district had the highest density (21.6 head per km2 ) (Map 3.42). 3.12.2.2 Goat Herd Size Thirty-three percent of the goat-rearing households had herds of 1-4 goats with an average of 2 goats per goat rearing household. Seventy-seven percent of total goat-rearing households had herds of 1-14 goats and owned 37 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 678 households (9%) with herds of 40 or more goats each (39,616 goats in total), resulting in an average of 58 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.7 percent of the total goats in Pwani region. Improved goats for meat and diary goats constituted 0.4 and 0.9 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 23.6 percent. This positive trend implies eight years of population increase from 18,152 in 1995 to 98,604 in 2003. The number of goats increased from 18,152 in 1995 at an estimated annual rate of 37.9 percent to 65,659 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 10.7 percent. (Chart 3.128). 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Pwani region after cattle and goats. The region ranked 19 out of 21 Mainland regions and had 0.6 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 1,503 (1.06% of all agricultural households in Pwani region) rearing 24,334 sheep, giving an average of 16 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Bagamoyo with 21,754 sheep (89.4%of total sheep in Pwani region) followed by Rufiji (1,492 sheep, 6.1%), Kibaha (719 sheep, 3%). Mkuranga District had the least number of sheep (369 sheep, 1.5%). (Chart 3.129 and Map 3.43). Bagamoyo district also had the highest density (7 head per km2 ) (Map 3.44). 18,152 65,659 98,604 - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 5000 10000 15000 20000 25000 N u m b er of sh eep Bagamoyo Rufiji Kibaha Mkuranga District Chart 3.129 Total Number of Sheep by District Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 2.5 5.2 3.1 5.9 21.6 4.3 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 13,406 5,714 4,847 5,226 68,472 940 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Goat Number of Goat Number of Goat Per Square Km Map 3.41 PWANI Goat population by District as of 1st October 2003 Map 3.42 PWANI Goat Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 77 Rufiji Kibaha Mkuranga Kisarawe Mafia 0.3 0 0.8 6.9 0.3 0 Bagamoyo 5.6 to 7 4.2 to 5.6 2.8 to 4.2 1.4 to 2.8 0 to 1.4 Rufiji Kisarawe Kibaha Bagamoyo Mafia 1,492 369 0 719 21,754 0 Mkuranga 18,000 to 22,500 13,500 to 18,000 9,000 to 13,500 4,500 to 9,000 0 to 4,500 Tanzania Agriculture Sample Census Number of Sheep Number of Sheep Number of Sheep Per Square Km Map 3.43 PWANI Sheep population by District as of 1st October 2003 Map 3.44 PWANI Sheep Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 78 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 Sheep rearing was dominated by indigenous breeds that accounted for all the sheep. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 was estimated at 51.9 percent. The population increased at an annual rate of 73.8 percent from 860 in 1995 to 7,845 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 32.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 18 out of 21 Mainland regions and had 0.4 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Pwani region was 353 (0.2% of the total agricultural households in the region) rearing 3,673 pigs. This gives an average of 10 pigs per pig-rearing household. The district with the largest number of pigs was Kisarawe with 2,226 pigs (61% of the total pig population in the region) followed by Mkuranga (761 pigs, 21%), Kibaha (392 pigs, 11%), Bagamoyo (294 pigs, 8%). (Chart 3.131 and Map 3.45). However Kisarawe district had the highest density (1.4 head per km2 ) (Map 3.46). There were no pigs in Mafia and Rufiji districts. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the period from 1999 to 2003 was 0.64 percent. During this period the population grew from 3,581 to 3,673. (Chart 3.132). 860 7,845 24,334 - 5,000 10,000 15,000 20,000 25,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend - 3,581 3,673 - 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 N um ber of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 500 1,000 1,500 2,000 2,500 N u m b er o f P ig s Kisarawe Mkuranga Kibaha Bagamoyo District Chart 3.131 Total Number of Pigs by District Rufiji Mkuranga Kisarawe Kibaha Mafia 0 0.7 1.4 0.4 0.1 0 Bagamoyo 1.12 to 1.4 0.84 to 1.12 0.56 to 0.84 0.28 to 0.56 0 to 0.28 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 0 761 2,226 392 294 0 1,800 to 2,250 1,350 to 1,800 900 to 1,350 450 to 900 0 to 450 Tanzania Agriculture Sample Census Number of Pig Number of Pig Number of Pig Per Square Km Map 3.45 PWANI Pig population by District as of 1st October 2003 Map 3.46 PWANI Pig Density by District as of 1st October 2003 Number of Pig Per Square Km RESULTS 80 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 81 3.12.5 Chicken Production The poultry sector in Pwani region was dominated by chicken production. The region contributed 4.3 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 79507 raising about 1,420,152 chicken. This gives an average of 18 chicken per chicken-rearing household. In terms of total number of chicken in the country, Pwani region was ranked 13th out of the 21 Mainland regions. The District with largest number of chicken was Bagamoyo (370,049 chicken, 26.1% of the total number of chicken in the region) followed by Mkuranga (322,132, 22.7%), Rufiji (311,759, 22%), Kisarawe (246,120, 17.3%), Kibaha (102,338, 7.2%). Mafia district had the smallest number of chicken (67,754, 4.8%). (Chart 3.133 and Map 3.47). However Mafia district had the highest density (308 head per km2 ) (Map 3.48). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 3.23 percent. The population decreased at a rate of - 7.2 percent from 1995 to 1999 after which it increased at the rate of 14.8 percent for the four year period from 1999 to 2003 (Chart 3.134). Eighty eight percent of all chicken in Pwani region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chicken in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 70.4 percent of all chicken-rearing households were keeping 1-19 chicken with an average of 9 chicken per holder. About 29.2 percent of holders were reported to be keeping the flock size of 20 to 99 chicken with an average of 32 chicken per holder. Only 0.4 percent of holders kept the flock sizes of more than 100 chicken at an average of 655 chicken per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 12,480 16 33,830 3 5-9 17,795 23 120,208 7 10-19 25,092 32 321,845 13 20-29 12,254 16 273,881 22 30-39 5,868 7 184,373 31 40-49 2,196 3 92,214 42 50-99 2,673 3 178,300 67 100+ 329 0 215,501 655 Total 78,687 100 1,420,152 18 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 N u m b er of C h ick en s Bagamoyo Mkuranga Rufiji Kisarawe Kibaha Mafia District Chart 3.133 Total Number of Chickens by District 1,101,377 816,765 1,420,152 - 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend Rufiji Kisarawe Kibaha Bagamoyo Mafia 293.7 116.5 57.5 159.4 116.9 308.6 Mkuranga 280 to 320 210 to 280 140 to 210 70 to 140 0 to 70 Bagamoyo Rufiji Kisarawe Kibaha Mafia 370,049 322,132 311,759 246,120 102,338 67,754 Mkuranga 320,000 to 400,000 240,000 to 320,000 160,000 to 240,000 80,000 to 160,000 0 to 80,000 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken Number of Chicken Per Square Km Map 3.47 PWANI Chicken population by District as of 1st October 2003 Map 3.48 PWANI Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km RESULTS 82 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 83 3.12.5.4 Improved Chicken Breeds (Layers and Broilers) Layers chicken population in Pwani Region increased at an annual rate of 111.3 percent during the period of four years from 6,306 in 1999 to 125,649 in 2003. The number of improved chicken was most significant in Kisarawe District followed by Rufiji District (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 7.9 percent during which the population grew from 22,005 to 40,358. The annual growth rate was negative (-45.9%) for the period of four years from 1995 to 1999. The broiler population exhibited an increasing trend at the rate of 115.02 percent per annum for the period of four years resulting at increase from 1,888 in 1999 to 40,358 in 2003 (Chart 3.136). 3.12.6. Other Livestock There were 53,420 ducks, 13,100 turkeys, 11,371 rabbits and 193 donkeys raised by the rural agricultural households in Pwani region. Table 3.16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Bagamoyo district (41% of all ducks in the region), followed by Mafia (32%), Rufiji (18.7%) and Kisarawe (5.2%). Kibaha district had the least number of ducks estimated to be 3 percent of total ducks in the region and no ducks were recorded in Mkuranga. Turkeys were reported only in Mafia and Mkuranga districts (97% and 3% respectively). (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 27 percent and 20 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were lowest in Rufiji district. However ticks problems were highest in Mafia followed by Kisarawe district (Map 3.49). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Bagamoyo 21,949 0 9,198 0 1,828 Kibaha 1,624 0 53 0 0 Kisarawe 2,784 0 1,409 0 0 Mkuranga 0 404 0 0 0 Rufiji 9,968 0 711 0 0 Mafia 17,094 12,696 0 193 65 Total 53,420 13,100 11,371 193 1,893 931 0 2852 7743 42523 30935 67879 0 11464 1679 0 10000 20000 30000 40000 50000 60000 70000 Number of Chickens Bagamoyo Kibaha Kisarawe Rufiji Mafia District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers - 30,000 60,000 90,000 120,000 150,000 Number of Improved Chicken 1995 1999 2003 Year Chart 3.136 Improved Chicken Population Trend Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 10 20 30 40 50 60 70 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent Ticks Tsetseflies RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 The most practiced method of tick controlling was spraying with 64 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (8%), smearing (6%) and other traditional methods like hand picking (12%). However, 9 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 45 percent of livestock-rearing households, followed by dipping (11%). However, 44 percent of the livestock rearing households did not use any of the two aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 4,657 (38.2% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 72 percent, goats (35%), sheep (7%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 10,168, representing 83.5 percent of the total livestock- rearing households and 7.2 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 97 percent of all households receiving livestock extension services. The rest of the households got services from Cooperatives (12%), NGOs/ development projects (1%) and large-scale farmers (0.4%). About 64 percent of livestock rearing households described the general quality of livestock extension services as being good, 21 percent said they were very good and 9 percent said they were average. However, 6 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor. (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Some veterinary clinics were not located far from livestock rearing households. About 51.6 percent of the livestock rearing households accessed the services, at a distance of less than 14 kms, while 48.4 percent of them accessed the services more than 14 kms from their dwellings (Chart 3.140). The most affected district was Bagamoyo district with more than half of livestock rearing households accessing the services at a distance of more than 14 kms. Mafia district was the most affected because almost all the livestock rearing households accessed the service at least a distance of 14 kms. from their dwellings. (Chart 3.141). 0 10 20 30 40 50 60 70 80 90 Percent Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 6% Very Good 21% Good, 64% Average, 9% Poor, 1% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 2,494 (71% of livestock rearing households in Pwani region) whilst 674 households (19%) resided between 5 and 14 kms. However, 358 households (10%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Rufiji and Mafia districts had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Kibaha and Bagamoyo districts. In Bagamoyo district about 37 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Pwani region was very limited with only 46 households (0.03% of the total crop growing households in the region) using them (Chart 3.144). Chart 3.142 Number of Households by Distance to Village Watering Points 15 or more kms, 358, 10% 5-14 kms, 674, 19% Less than 5 kms, 2,494, 71% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 200 400 600 800 1,000 1,200 1,400 1,600 Bagamoyo Kibaha Mafia Rufiji District Number of Households Less than 5 kms 5-14 kms 15 or more kms Chart 3.140 Number of Households by Distance to Verinary Clinic Less than 14km, 3,530, 52% More than 14km, 3,306, 48% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 200 400 600 800 1,000 1,200 1,400 1,600 Rufiji Bagamoyo Mafia Kibaha Kisarawe Mkuranga District Number of Households Less than 14 kms More than 14kms RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 86 The 46 households in Pwani region that used draft animals were all in Mafia district. Use of draft animals was not reported in the other districts (Chart 3.145 and Map 3.50). The region had 92 oxen (all in Mafia district) that were used to cultivate 19 hectares of land. This represents only 0.004 percent of the total oxen found on the Mainland. The area cultivated using oxen was found in Mafia district only. 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Pwani region was 15,882 (11% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 13,326 ha of which 4,772 hectares (36% of the total area applied with organic fertiliser or 4.4% of the area planted with annual crops and vegetables in Pwani region during the long rainy season) was applied with farm yard manure (Map 3.51). 3.12.9.4 Use of Compost Only 8,553 ha (64% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Bagamoyo district with 1,389 hectares (29% of the total area applied with farm yard manure) followed by Mkuranga (1,098 ha, 23%), Kibaha (923 ha, 19.4%), Mafia (757 ha, 16%), Kisarawe (421 ha, 8.8%), and Rufiji (183 ha, 3.8%) (Chart 3.147 and Map 3.52). 0 5 10 15 20 25 30 35 40 45 50 Number of Households Mafia Bagamoyo Kibaha Kisarawe Mkuranga Rufiji District Chart 3.145 Number of Households Using Draft Animals by District - PWANI Chart 3.146 Number of Households Using Organic Fertiliser Not Using Organic Fertilizer, 124,331, 89% Using Organic Fertilizer, 15,882, 11% Chart 3.147 Area of Application of Organic Fertiliser by District PWANI 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 Mkuranga Bagamo yo Kis arawe Kibaha Rufiji Mafia District Area of Fertiliser Application (ha) Farm Yard Manure Compost 3.144 Number of Households Using Draft Amimals Using draft animal, 46, 0.03% Not using draft animal, 141,398, 99.97% Rufiji Mkuranga Kisarawe Kibaha Mafia 0 0 0 0 0 46 0 0 0 0 0 0 Bagamoyo 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Rufiji Mkuranga Kisarawe Kibaha Mafia 305 197 422 216 1,112 1,061 2.8 1.8 3.9 2 10.3 9.8 Bagamoyo 950 to 1,200 700 to 950 500 to 700 250 to 500 0 to 250 Tanzania Agriculture Sample Census Number of Households Infected withTicks Number of Households Infected withTicks Number of Households Using Draft Animals Map 3.49 PWANI Number and Percent of Households Infected with Ticks by District Map 3.50 PWANI Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Percent of Households Infected withTicks Percent of Households Using Draft Animals RESULTS 87 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 235 2,601 737 465 5,409 107 0.1 1.5 0.4 0.3 3 0.1 4,400 to 5,500 3,300 to 4,400 2,200 to 3,300 1,100 to 2,200 0 to 1,100 Rufiji Kisarawe Kibaha Bagamoyo Mafia 96 1,804 337 1,099 928 545 0.1 1 0.2 0.6 0.5 0.3 Mkuranga 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure application Planted Area with Farm Yard Manure application Planted Area with Compost application Map 3.51 PWANI Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District Map 3.52 PWANI Planted Area and Percent of Total Planted Area with Compost application by District Planted Area with Compost application Percent of Planted Area with Farm Yard Manure application Percent Planted Area with Compost application RESULTS 88 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 89 3.12.10 Fish Farming Fish farming was not practiced in Pwani region. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was a service that was located farthest from most of the household’s dwellings than any other service. It was located at an average distance of 130 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tertiary market (64.4), hospital (48.2), tarmac road (31.5), secondary market (31.1), secondary school (23.7), primary market (17.4), health clinic (7), all weather road (4.2), primary school (2.4) and feeder road (1.3). (Table 3.15). Only 9 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 20 percent reported them to be average. Seventeen percent of the agricultural households said the infrastructure and services were poor, and 21 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (125,877 households, 88.9% of all rural agricultural households) 2,463 households (1.7%) use improved pit latrine and 4,236 households (3%) use flush toilets. The remaining 23 household (0.02%) use other toilets facilities. However, 8,932 households (6.3%) in the region had no toilet facilities (Chart 3.148). The distribution of the households without toilets within the region indicates that 31.6 percent of them were found in Rufiji District and 25.4 percent were from Bagamoyo. The percentages of households without toilets in other districts were as follows Mafia (15.5%), Mkuranga (14.5%), Kisarawe (6.8%), and Kibaha (6.1%). Map 3.53). Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Bagamoyo 21.2 2.3 2.9 1.8 68.6 5.3 101.6 13.0 33.5 68.1 10.8 Kibaha 27.1 1.8 1.7 0.6 39.6 9.2 48.4 10.3 18.9 42.5 10.4 Kisarawe 17.4 1.9 4.5 0.6 43.7 6.9 97.3 17.4 26.2 61.2 51.6 Mkuranga 26.0 3.0 4.3 1.0 37.9 7.5 118.7 13.0 21.9 45.2 17.9 Rufiji 25.1 2.3 5.9 1.6 46.1 8.2 213.0 18.3 35.6 78.1 37.0 Mafia 30.1 2.6 8.4 2.2 26.6 2.7 238.6 82.9 90.3 143.6 200.5 Total 23.7 2.4 4.2 1.3 48.2 7.0 130.0 17.4 31.1 64.4 31.5 Chart 3.148 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 125,877, 88.9% Flush Toilet, 4,236, 3.0% No Toilet , 8,932, 6.3% Other Type, 23, 0.02% Improved Pit Latrine , 2,463, 1.7% Mkuranga Kisarawe Kibaha Mafia Rufiji 2,826 1,293 610 549 2,272 1,383 2 0.9 0.4 0.4 1.6 1 Bagamoyo 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Tanzania Agriculture Sample Census Number of Households Without Toilets Number of Households Without Toilets Map 3.53 PWANI Number and Percent of Households Without Toilets by District Percent of Households Without Toilets RESULTS 90 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Pwani region with 98,795 households (69.8% of the agriculture households in the region) owning the asset. followed by bicycle ( 63,644 households, 45%), iron (20,556 households, 14.5%), wheelbarrow (4,371 households, 3.1%), mobile phone (2,542 households, 1.8%), television/video (1,754 households, 1.2%), vehicle (1,354 households, 1%) and landline phone (415 households, 0.3%) (Chart 3.149). 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region. with 78.5 percent of the total rural households using this source of energy followed by hurricane lamp (15%), pressure lamp (3%), mains electricity (1.8%), firewood (1.3%), solar (0.2%), candle (0.3%) and other (0.02%). (Chart 3.150). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.8 percent of all rural agricultural households in Pwani region. This was followed by charcoal (4.5%). The rest of energy sources accounted for 0.7 percent. These were bottled gas (0.2%), crop residues (0.1%), solar (0.1%), livestock dung (0.1%), parrafin/kerosene (0.1%) and gas/biogas (0.1%). (Chart 3.151). Chart 3.149 Percentage Distribution of Households Owning the Assets 3.1 1.8 1.2 1.0 0.3 69.8 45.0 14.5 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 1,856, 1.3% Solar, 263, 0.2% Candles, 395, 0.3% Hurricane Lamp, 21,204, 15% Pressure Lamp, 4,243, 3% Mains Electricity, 2,481, 1.8% Other, 31, 0.02% Wick Lamp, 111,057, 78.5% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 305, 0.2% Crop Residues, 156, 0.1% Mains Electricity, 0, 0% Solar, 80, 0.1% Livestock Dung, 204, 0.1% Charcoal, 6,374, 4.5% Firewood, 134,132, 94.8% Parraffin / Kerosine, 197, 0.1% Gas (Biogas), 81, 0.1% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 3.13.6 Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 66 percent of the rural agricultural households. This was followed by iron sheets (26.7%), grass/mud (6.5%), asbestos (0.4%), tiles (0.3%), and others (0.2%). (Chart 3.152). Mafia district had the highest percentage of households with grass/leaves roofing material (91%) and was followed by Mkuranga district.(78%), Rufiji (71%), Kisarawe (65%), Bagamoyo (53%), and Kibaha (52%). (Chart 3.153) and Map 3.54). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Pwani region was the unprotected well (55 percent of households use unprotected wells during the wet season and 52.6 percent of the households during the dry seasons. This was followed by surface water (12% of households in the wet season and 16.5% during dry season), piped water (12% of households during the wet season and 13.7% in the dry season), protected well (8% of households during the wet season and 9.5% in the dry season) and uncovered rainwater with 8% of households during the wet season and 2.4% in the dry season. Unprotected spring was used as a main source by 3 percent of the households in the wet season and by 2.9 percent in the dry season . (Chart 3.154). About 62 percent of the rural agricultural households in Pwani region obtained drinking water within a distance of less than one kilometer during wet season compared to 43 percent of the households during the dry season. However, 37 percent of the agricultural households obtained drinking water from a Chart 3.152 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.4% Grass & Mud 6.5% Iron Sheets 26.7% Grass / Leaves 65.9% Tiles 0.3% Other 0.2% Concrete 0.0% Chart 3.153 Percentage Distribution of Households with Grassy/Leafy Roofs by District 52 53 65 71 78 91 0 25 50 75 100 Mafia Mkuranga Rufiji KisaraweBagamoyo Kibaha District Percent Chart 3.154 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 40 50 60 Upro tected Well Surface Water (Lake / Dam / River / Stream) P iped WaterP ro tected Well Unco vered Rainwater Catchment Unpro tected Spring Other Main source Percent of Households Wet Season Dry Season Chart 3.155 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and abo ve Distance Percent wet season Dry season RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 distance of one or more kilometers during wet compared to 56 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km. (Chart 3.155). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Pwani region normally have 3 meals per day (64.7 percent of the households in the region). This is followed by 2 meals per day (28.1 percent) and 1 meal per day (5.4 percent). Only 1.8 percent of the households have 4 meals per day (Chart 3.156). Kisarawe district had the largest percent of households eating one meal per day whilst Bagamoyo had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.55). 3.13.8.2 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 67,290 (47.5% of the agricultural households in Pwani region) with 34,327 households (51% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (29%). Very few households had meat three or more times during the respective week. About 52 percent of the agricultural households in Pwani region did not eat meat during the week preceding the census (Chart 3.157 and Map 356). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 114,687 (81% of the total agricultural households in Pwani region) with 26,216 households (22.9% of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish once a week (20%). The number of households that consumed fish twice or more during the week in Pwani region was 91,738 (80% of the agricultural households that ate fish in the region during the respective period). About 19 percent of the agricultural households in Pwani region did not eat fish during the week preceding the census. (Chart 3.157 and Map 3.57). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Bagamoyo 496 1.3 9801 26.3 26993 72.4 0 0.0 37290 Kibaha 1004 7.2 5554 39.6 6844 48.8 626 4.5 14029 Kisarawe 1627 8.7 7009 37.6 10002 53.7 0 0.0 18637 Mkuranga 2185 6.3 6586 19.0 24130 69.4 1844 5.3 34744 Rufiji 2017 6.5 9224 29.8 19589 63.4 75 0.2 30906 Mafia 324 5.5 1538 26.0 4063 68.6 0 0.0 5924 Total 7,653 5.4 39,711 28.1 91,620 64.7 2,545 1.8 141,530 Chart 3.156 Number of Agriculural Households by Number of Meals per Day Tw o Meals, 39,711, 28% One Meal, 7,653, 5% Four Meals, 2,545, 2% Three Meals, 91,620, 65% Chart 3.157 Number of Households by Frequency of Meat and Fish Consumption 0 5000 10000 15000 20000 25000 30000 35000 40000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 21,830 27,014 12,050 7,237 19,768 5,371 15.4 19.1 8.5 5.1 14 3.8 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Bagamoyo Rufiji Mkuranga Kisarawe Kibaha Mafia 26,993 19,589 24,130 10,002 6,844 4,063 19 14 17 7 5 3 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tanzania Agriculture Sample Census Number of Households Using Grass/ Leaves for Roofing Number of Households Using Grass/ Leaves for Roofing Map 3.54 PWANI Number and Percent of Households Using Grass/Leaves for Roofing Material by District Percent of Households Using Grass/ Leaves for Roofing Number of Households Eating 3 Meals per Day Map 3.55 PWANI Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Percent of Households Eating 3 Meals per Day RESULTS 94 Kisarawe Rufiji Kibaha Bagamoyo Mafia 4,306 4,706 2,756 2,661 8,143 378 3 3 2 2 6 0 Mkuranga 6,800 to 8,500 5,100 to 6,800 3,400 to 5,100 1,700 to 3,400 0 to 1,700 Mafia Rufiji Kibaha Bagamoyo 8,385 1,480 8,863 7,702 3,727 4,171 5.9 1 6.3 5.4 2.6 2.9 Kisarawe Mkuranga 7,600 to 9,500 5,700 to 7,600 3,800 to 5,700 1,900 to 3,800 0 to 1,900 Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Map 3.56 PWANI Number and Percent of Households Eating Meat Once per Week by District Percent of Households Eating Meat Once per Week Number of Households Eating Fish Once per Week Map 3.57 PWANI Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Percent of Households Eating Fish Once per Week RESULTS 95 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 3.13.9 Food Security In Pwani region, 53,900 households (38.1% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 12,124 (8.6%) said they sometimes experience problems, 20.9 often experienced problems and 6.3 percent always had problems in satisfying the household food requirement. About 26.2 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.58). 3.13.10 Main Sources of Cash Income The main source of cash income of the households in Pwani region was from selling cash crops (22.7 percent of smallholder households), followed by sale of food crops (22.4%), selling of forest products (19.2%), casual cash earnings (10.8%), businesses (8.6%) and cash remittances (5.6%), fishing (4.5%), wages and salaries in cash (2.9%). Only 1.5% of smallholder households reported the sale of livestock products as their main source of income, followed by other unspecified sources (0.9%), and lastly, sale of livestock (0.9%). (Chart 3.158). Chart 3.158: Percentage Distribution of the Number of Households by Main Source of Income not applicable, 0% Other, 0.9% Livestock, 0.9% Livestock Products, 1.5% Forest Products, 19.2% Wages & Salaries, 2.9% Remittance, 5.6% Business Income, 8.6% Cash Crops, 22.7% Fishing, 4.5% Food Crops, 22.4% Other Casual Cash Earnings,10.8% Kisarawe Kibaha Bagamoyo Mafia 2,554 942 1,252 1,043 2,969 173 1.8 0.7 0.9 0.7 2.1 0.1 Rufiji Mkuranga 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Map 3.58 PWANI Number and Percent of Households Reporting Food Insufficiency by District Percent of Households Reporting Food Insufficiency RESULTS 97 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 4 PWANI PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Pwani Region Profile The region profile describes the status of the agriculture sector in the region and compares it with those of other regions in the country. Pwani region has a land area of around 250,700 hectares under crop production but had a small number of crop growing households and very few with livestock, compared to other regions. It ranked 15th in the number of crop growing households per square kilometer. The available planted land area per household was (1.8 ha/household) and almost all the land available to smallholders was utilized. The region has two rainy seasons with the long rainy season being more important. Cereal production is not important (ranked 19th among regions on Mainland) and it had one of the smallest planted areas of maize in the country. However paddy production was relatively important but sorghum was grown in small quantities. Cassava was moderately important; beans or groundnuts were insignificant in the region. Vegetable production was small compared to other regions. Pwani had the 4th largest planted area of cashew nuts but ranked first in the planted area for coconuts. It had the second largest area planted with oranges in the country. Compared to other regions, Pwani had a very small planted area under irrigation in the country. The number of households practicing irrigation appears to have increased over the period of 8 years prior to the census. The source of irrigation water was equally split between wells and rivers followed by dams. Use of buckets/watering cans was the most common method of obtaining irrigation water closely followed by unspecified means. Irrigation application was mostly by buckets/watering cans and to a lesser extent, the flood method. Water hose and sprinklers were not widely used. The method of cultivation in Pwani was almost entirely by hand and virtually no fertilizers or pesticides were used. Storage was predominantly in locally made traditional cribs. Pwani had little crop produce to sell and the percent of households selling was very low. Compared to other regions, the percentage of smallholder households processing crops was insignificant. However, it had the highest percent of households processing crops by hand. In the case of those who process crops, the region had the least number of households selling processed products compared to other regions. Compared to other regions, the percent of smallholders receiving extension services was moderate, most of them from the government followed by large scale farms. Pwani had a small number of planted trees by smallholders. Compared to other regions, the percent of households with erosion control/water harvesting facilities was insignificant to low, with erosion control bunds being one of the most prominent, followed by tree belts. Pwani was among the regions with the lowest livestock population and even lower in terms of cattle density, ranking 19th in the country. Most of the cattle kept were the indigenous type and cattle rearing came first in the region, followed by goats, sheep and pigs. Milk production was very low (ranking 18th in the country) and since the demand was very high, the farm gate price of milk was correspondingly high. Goats as well as sheep and pigs were few, in line with the fact that the region was among the last ranked regions in livestock rearing. Pwani ranked 13th in the population of chicken compared DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 to other regions, almost all was entirely made up of layer breed but it was among the three leading regions in layers population in the country. Its egg production was among the lowest in the country. The use of organic fertilizers was very low (ranked 17th) and percentage of area being applied per livestock rearing household was also low. Use of draft animals for cultivation in the region was very limited, with an insignificant percentage of households using them. The disease infection rate was moderate to high for most diseases. The region ranked 7th in the rate of helminthiosis infection compared to other regions. Access to livestock infrastructure and services was between average and poor. In relation to livestock population Pwani ranked 18th but received disproportionately more extension advice compared to other regions with much higher livestock populations such as Shinyanga, Arusha, Manyara, Mwanza and Tabora regions. It ranked 15th in the percentage of households receiving extension advice but was among the last in number of livestock kept. The Agricultural Census did not capture any fish farmers in Pwani region; hence no information is available on this in the report. Pwani region has the fourth smallest rural agriculture population in Tanzania (712,995 persons of which 354,379 are males and 358,616 females). It has a moderate number of rural households involved in agriculture (141,530) compared to other regions. It has 89.7 percent of rural households and 78.5 percent of total households in the region (including urban) that are involved in agriculture. The region has an average household size of 5 persons per household and it has a low percent of female headed households (19%) compared to other regions. Crop only farming dominates and there is virtually no pastoralists in the region. The number of households keeping livestock only is very small. Land under customary law is the predominant type of land ownership, accounting for 76 percent of the total rural smallholder owned land. There is a very small amount of land under official titles. The region has an average access to their fields with about 50 percent of the rural agriculture households having their nearest field less than 100 m from the homestead. Access from the field to the nearest road is relatively poor. Pwani region has comparatively low percent literate rural agriculture population in the country (63%) compared to other regions and the difference between the literacy rate of males and females is fourth highest with 13.4 percent more literate males than females. It has a comparatively low percent of the rural agriculture population that have completed school and a moderate percent of household heads with no education. The most important livelihood activity is crop farming followed by livestock keeping/rearing and tree/forest resources. Off farm income is the least important livelihood activity. The percent of the rural agriculture population working full time in farming is high (more than 75%). The main source of cash income for Pwani is from the sale of food crops followed by sale of cash crops and sale of forest products. Pwani has a low percent of households receiving credit mainly from cooperatives (65%). The region has a low percent of households that use modern roofing material (around 27%) and the rest is mainly with grass/leaves/mud. Almost all households in the region have toilet facilities (93.7%). Energy for lighting is mainly from wick lamps 78.5%) and about 15 percent of households use hurricane lamps. Most water used for drinking in Pwani is from unprotected wells (53%), however, 14 percent of households use piped drinking water. About 10 percent of households in Pwani region obtain drinking water from protected wells. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 100 Most rural agriculture smallholders in Pwani are living a subsistence existence with about 25 percent of the agriculture households using more than 50 percent of their livelihood activities for non subsistence purposes. Most households eat three per day (64.7). It has a low percent of households that do not eat animal protein in one week and a relatively high percent of households that eat animal protein every day. The region has the highest percent of households that face problems in satisfying the household food requirements. It has a moderate access to services and infrastructure in the country. About 36 percent of the households in the region reported insufficiency of land which is moderate in the country. Pwani Region has the same number of males and females (50% males and 50% females). The region has a very slender population pyramid over the ages 20 to 44 and this is more so for males than it is for females. This would suggest that there is a large out-migration from the region over this age range and that more males have the opportunity to leave than females. The result is a relatively moderate feminisation of the agriculture sector in this region. Over the 15 to 19 age range there are more males than females in the region. The region has an active agriculture population of 358,210 of which 168,746 are males and 189,464 are females and there is a small difference between the percent of total male and female active population in the region (47% and 53% respectively). The region has the 2nd lowest number of households in the country compared to other regions (141,530, out of which 115,108 are male headed and 26,422 are female headed). It also has the 11th highest percent of female headed households in the country. The average household size is the similar to the National average (5.3 members per household for male headed households and 4.1 for female headed households), resulting in a difference in the household size of 1.2 more members in male headed households compared to female headed households. Pwani region has the lowest percent of households keeping livestock and, whilst a higher percent of males keep livestock compared to females, the difference is the smallest in the country. There is a relatively large difference in the dependency ratio between male and female headed households (109 dependants for every 100 active members in male headed households and 121 dependants for every 100 active members in female headed households). The region has a large difference in sex ratio of the active agriculture population between male and female headed households (103:100 in male headed households compared to 50:100 in female headed households. Pwani has the 12th largest difference in literacy rates between male and female household heads with an illiteracy rate of 22 percent of male household heads and 54 percent of female household heads. Taking the overall population of male and female members in the region there are 13 percentage points more illiterate females than males and this is 2nd highest difference in the country Pwani has a moderate to low percent of orphans in the country and there is little difference between male and female headed households. No orphan heads of households were detected in Pwani. Pwani has around 10 percent of children with off farm income and this is more prevalent in female headed households (15% with off farm income) compared to male headed. As with all regions, Pwani has more land per household in male headed households than in female headed households. However the difference is small compared to other regions. Pwani region had one of the smallest percent of households reporting insufficiency of land (38%), however there is no difference between male and female headed households. Female headed households in Pwani have around 38 percentage points more female land holders compared to male headed households and this difference is moderate compared to other regions. Pwani has 38 percent of female headed households with female land holders. Assuming that male household members of female headed households do not have rights to land, this would imply that 62 percent of female headed households have insecure access to land in Pwani. Pwani has a DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 101 higher percent of female headed households using customary land compared to male headed households, whilst a higher percent of male headed households have land under certificate of ownership and bought land. Pwani has a low percent of households with cattle compared to other regions and differences between male and female headed households could not be detected. Pwani has the lowest percent of households with goats and the difference in the percent of male and female headed households keeping goats is relatively small. However the number of goats per household is high and there is a difference between male and female headed households with male headed households having 8 more goats per household compared to female headed households. Sheep keeping is not important in Pwani. Pig keeping in Pwani is also not important however it is important in female headed households with 26 percent of female headed households keeping compared to 1 percent in male headed households. Compared to other regions, a moderate percent of households use improved seeds in Pwani region and a higher percent female headed households use improved seed compared to male headed households (11 percentage points more female than male headed households) and this is the highest differential in favour of female headed households in the country. The region has one of the smallest usage of insecticides in the country. It also has one of the highest percent of households not using fertiliser and there is little difference between male and female headed households. Little farm yard manure is used and only by male headed households, however the region has the highest percent of households using compost with slightly more male headed households than female headed households. Very little inorganic fertiliser is used in Pwani region. The region has the 3rd smallest area under irrigation in and there is little difference in the percent area under irrigation in male headed households compared to female headed households, with only 3 percentage points more male headed households than female headed households having irrigation. About 25 percent of the households in Pwani region receive extension advice and the difference between male and female headed households is small. In terms of planted area, Pwani has a smaller short rainy season compared to the long rain season. In Pwani, 49.0 percent of male headed households plant crops compared to 52.8 percent of female headed households in the long rainy season and for those that do not plant the main reason is associated with rains. However a relatively high percent of households do not plant crops and this was followed by illness. There is little difference in the percent of male and female headed households planting during the short rainy season (3.2 percentage points more male than female headed households) and the main reason for not planting during this season was due to rains (60% male headed and 71% female headed households). Pwani has a high percent of planted area with maize in the country and there is no difference between male and female headed households. The yield of maize in the region is one of the lowest in the country and there is no difference between male and female headed households. Pwani has the third highest percent of households growing paddy in the country and there is no difference between male and female headed households and there is no difference in yield. Pwani has a small percent of households utilising secondary products and there is little difference between male and female headed households. Pwani has a high number of cattle sold per household (2.0/hh) compared to other regions and there is a large difference between male and female headed households (2.0 cattle sold per household in male headed households compared to 0.4 per female headed household). More female headed households consume cattle than male headed households. In Pwani region, a large number of goats are sold per household compared to other regions (2.2/hh) and male headed households sell 0.8 more goats per household than female headed households. The number consumed per household is higher than in any other region and it is almost entirely by male headed households. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 Pwani region has a moderate percent of active agriculture household members working full time on farm (60% of active members) and there is a small difference between male and female headed households (5 percentage points more are working full time in male headed households compared to female headed households). Of the most active agriculture population (18 to 44 years of age) 73 percent of males and 81 percent of females are mainly involved in agriculture. In male headed households, 75 percent of the male members and 81 percent of female members are mainly involved in agriculture, whilst in female headed households 63 percent of males and 76 percent of females are mainly involved in agriculture. Pwani region has one of the smallest percent of boys and girls involved in agriculture (9 percent of boys and girls). There is no difference in the percent of boys involved in agriculture in female headed households compared to male headed households and there is no difference in the percent of girls involved in agriculture between male and female headed households. Thirty percent more elderly males compared to elderly females in male headed households are involved in agriculture in the region. Pwani region has the smallest percent of households storing crops (25% of households) and there is no difference in the percent of households storing crops between male and female headed households. More female headed households store crops in locally made traditional cribs compared to male headed households and it has the highest percent difference in storage in modern stores in favour of female headed households. This is in contrast to male headed households where a higher percent of male headed households store crops in sacks/open drums and improved cribs compared to female headed households. Male headed households have 25 percentage points more households having up to a quarter loss compared to female headed households. A higher percent of male headed households process crops in Pwani region compared to female headed households. Very little credit is provided in Pwani region (1% of households) and slightly more is provided to male headed households, The main reason for not using credit is that they do not know how to access it followed by not available and don’t know about credit. The region has the one of the smallest percent of households with modern roofing material in the country (41% of households in the region) and there is no difference between male and female headed households. Most households use wick lamps/firewood and there is no difference between male and female headed households. Most households use firewood for cooking and there is no difference between male and female headed households. The region has a small percent of households with piped drinking water (10%) and there is little difference between male and female headed households. Nine percent of households have no toilets and female headed households have 3 percentage points more compared to male headed households. The difference in the ownership of assets (radio, iron and bicycle) between male and female households is high, in favour of male headed households, for all regions. Pwani has a moderate percent of households with radios and irons and it has a comparatively high percent of bicycles. In Pwani male headed households have 27 percentage points more radios, 7 percentage points more irons and 32 percentage points more bicycles than female headed households. There is no difference between male and female headed households in the number of meals household members eat per day in all regions. In Pwani region, a higher percent of male headed households eat meat more times per meek than female headed households and the difference is comparatively moderate. Pwani region has a small to moderate difference between male and female headed households in the percent of households facing food shortages (about 7 percentage points more female headed households face food shortage problems compared to male headed households). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 4.2 District Profiles The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Bagamoyo Bagamoyo district had the largest number of households in the region one quarter of which were involved in smallholder agriculture in the region. Most smallholders were either involved in crops only or crops and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bagamoyo district was annual crop farming, followed by tree/forest resources and off farm income activity. The district had the third highest percent of households with no off- farm activities and more than a ninety percent of its total households having more than one member with off-farm income. The percentage was second highest for the agricultural households with off farm income. Compared to other districts in the region, Bagamoyo had the second highest percent of female headed households (28%) but was ranked 5th in the average age of household heads (48.8 years). With an average household size of 5.1 members per household it had the third highest for the region. The district had the highest literacy rate among smallholder households and this was also reflected by the highest level of school attendance in the region. The literacy rate for the heads of household was high compared to most districts in the region. However the situation in the region is that the majority of heads of agricultural households (54%) had primary level education whereas only 3% had post primary education. Bagamoyo had the smallest percentage (68%) of utilized land area indicating that the available or usable land for agricultural activities was not fully utilized like that of Mafia which was highest (94%). The total planted area was the largest in the region due to the presence of good wet and dry seasons. It had the second highest planted area per household (1.8ha). Also Bagamoyo ranked 3rd highest in quantity harvested. The average areas planted with annual crops in small holdings during the short and long rainy seasons were 0.52ha and 0.59ha respectively. The planted area for cereals crops (maize, paddy, sorghum, finger millet and bulrush millet) and maize in particular ranked first in the region. Bagamoyo ranked first in planted area for maize with a planted area of 37,477 ha. Bagamoyo was also the leading district in regard to the size of planted area per maize-growing households in the region. Paddy production ranked 3rd with a planted area of only 5,226 hectares and the production of sorghum though on a planted area of 1,887 hectares was highest in the region. Area planted with cassava was the 4th largest and the production was moderate accounting for 12 percent of the total cassava harvested, and it was the region’s second favourite annual crop. Among the six grouped categories of annual crops, the production of pulses in Bagamoyo was the highest in the region with a planted area of 7,332ha (42%). In terms of planted area for oilseeds and oilnuts, Bagamoyo ranked first in the region accounting for 64.1% of the total planted area. However the district ranked 4th in groundnuts which was the region’s 14th crop in terms of planted area. Sunflower was grown only in Bagamoyo district, in the long rain season. Vegetable production was of moderate importance in the district as it was second lowest in terms of planted area. It ranked third in the area planted with tomatoes (80ha.) as well as for water mellon (20ha). Chillies production was insignificant even in the region except for Mkuranga’s 6ha planted area. Total traditional cash crops grown in Pwani were contributed by cotton in Bagamoyo (141ha.) and seaweed in Mafia district (354ha.). Compared to other districts in the region, Bagamoyo had the second largest planted area for permanent crops (19.3%) which were dominated by cashewnuts (6,214 ha), coconuts (3,155 ha), oranges (2001 ha), pineapples (1,762 ha), mango (1,261 ha), bananas (790 ha), pawpaw (207 ha) and pigeon peas (206 ha). Other permanent crops were either not grown or were grown in very small quantities. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 104 As with other districts in the region, most land clearing and preparation was done by bush clearance or leaving the land without clearing. Ploughing was mainly done using the traditional handhoe (94.7% of planted area during the long rainy season and 96% during the two combined seasons) followed by tractor and oxen ploughing. The use of inputs in the region was very small, however district differences existed. Bagamoyo had the largest planted area applied with improved seeds in the region and this was due to the highest planted area of cereals followed by pulses and had the largest number of households using improved seeds. The district had the largest planted area with fertilizers (farm yard manure, compost and inorganic fertilisers), however most of this was compost. Compared to other districts in the region, Bagamoyo district ranked 4th in the level of insecticides use as well as fungicides. It had the second largest area under irrigation compared to other districts. The most common sources of water for irrigation were rivers and wells. Bucket/watering cans and flood water were the most common means of irrigation water application and only a very small amount of sprinkler irrigation was used. Use of water hose was insignificant. The most common method of crop storage was in locally made traditional cribs followed by sacks and open drums. However the proportion of households storing crops in the district was third highest, with the highest quantity in tons of stored crops than other districts in the region. The district had the largest number of households selling crops. Regarding those who did not sell, the main reason for not selling was insufficient production followed by prices being too low. The district had the 4th highest percent of households processing crops in the region and almost all processing was done using neighbour’s machine. The district had the least percent of households selling processed crops and the portion sold was to other unspecified groups, followed by traders on farm. Although very small, credit in the district was only accessed by male headed households and the sole source was from commercial banks option. The largest number of households receiving extension services was in Bagamoyo and most of this was from the government (96%). The quality of extension services was rated between good and very good by the majority of the households. Tree farming was of low importance in Bagamoyo (with 40,698 or 11.6% planted trees) and most of these were tectona grandis spp. The households ranked fifth or 8% of those involved with erosion control and water harvesting structures in Pwani region. These structures were mostly erosion control bunds followed by tree belts. The district had the largest number of cattle in the region and they were almost all indigenous followed by dairy. The district also ranked first in the production of goats, sheep and chicken but had the least number of pigs. Although small, the district had the largest number of layers in the region but no broilers. It ranked first in number of ducks, rabbits and other unspecified livestock; but no turkeys or donkeys were found in the district. The largest number of households reporting tsetse and tick problems were recorded in Bagamoyo district and it had the largest number of households de- worming livestock (54% of the region’s households reporting on this). The use of draft animals in the district was absent; fish farming was not only absent in the district but also in the region. It had a second best access to secondary schools, primary schools, health clinics and primary markets compared to other districts . It also had a better access to tarmac roads, all weather roads and the regional capital. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 105 Bagamoyo district had the second highest percent of households with no toilet facilities (25.4%). It had the highest percent of households owning a radio, bicycle, iron, mobile phones, wheelbarrow, vehicle and tv/video but the lowest in landline phones. It ranked first in percentage (38%) of households using mains electricity. The most common source of energy for lighting was the wick lamp (ranked first though constituted a quarter of all households in the region using this lighting facility) and practically the district ranked first in households using firewood for cooking accounting for 25% of total households in the region who reported using this source of energy. The district had the smallest percent of households with grass roofs, ranking 5th although 53% of its households confirmed of grass roofs and 34% confirmed about iron sheet roofs ranking second in the region. The most common source of drinking water in the region in the wet season was from unprotected wells followed by piped water and surface water. Bagamoyo ranked first in households using piped water (58%) and also ranked first in use of surface water (lakes/dams/rivers/streams) accounting for 45% in the region. It had the highest percent of households in the district having three meals per day compared to other districts and one quarter of its households has 2 meals per day, ranking 4th in the region. The district had the highest percent of households that did not eat meat (27%) and highest percent (50%) who did not eat fish during the week prior to enumeration. However most households never had problems with food satisfaction, ranking second in the region. 4.2.2 Kibaha Kibaha district ranked 4th in the number of households in Pwani region and had the second smallest percent of households involved in smallholder agriculture. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households and no pastoralists. No pastoralists were captured by this Census in Pwani region. The most important livelihood activity for smallholder households in Kibaha district was annual crop farming, followed by off-farm income then permanent crop farming. The district had the 3rd lowest percent of households with no off-farm activities and had the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kibaha had the second highest percent of female headed households (20%) and it had a moderately high average age for the household heads in the region (49.1 years). Its average household size of 4.5 members per household was the lowest in the region. Next to Mafia, Kibaha had a significantly high literacy rate among smallholder households though not reflected the level of school attendance which was moderately low. It had the third largest utilized land area per household (1.7ha) and 77 percent of the available area was currently being utilised. The district had the second lowest planted area per household in the region, and the third highest in average planted area per household being 0.53ha. in the combined seasons or 0.65ha in the long rainy season and 0.31 in the short rainy season. The district ranked fifth in maize production in the region with a planted area of over 5,215ha, but the planted area per maize growing household came second in the region. The district had the third lowest planted area of paddy in the region with 3,794 hectares. The area planted per sorghum household came second. Although bulrush millet was grown no production was recorded. Finger millet, wheat and barley were not grown in the district. Cassava production was second lowest, accounting for 7 percent of the quantity harvested in the region. The production of beans in Kibaha district was highest with a planted area of 12ha., and also ranked highest in area planted per household (0.21ha.) Kibaha district had the second smallest oilseeds crops planted area in Pwani region with a planted area of 123 ha. The district came third in DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 106 groundnut crop planted area with a planted area per groundnut growing household of 0.2 ha an area which was close to the region’s average. Sunflower was not grown in Kibaha district. Vegetable production was of great importance in the district and had the largest planted area for tomatoes (458 ha) in the region but came fourth in production of water melon. No planted area was recorded for chillies, radish, onions, cabbage, spinnach and bitter aubergine although they were grown elsewhere in the region. Okra was grown but no production was recorded. Traditional cash crops (e.g. tobacco and cotton) were not grown in Kibaha district. Compared to other districts in the region, Kibaha had the smallest planted area for permanent crops (6%) which was dominated by cashewnuts (2,062 ha), coconuts 1,317 ha), oranges (1,201 ha), grapefruits (149 ha), and bananas (64 ha) and pigeon peas (46 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation were done by hand slashing, however a very small amount of land preparation was done by bush clearance followed by the option of no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Kibaha had the second largest area planted with improved seeds in the region and this was due to the dominance of cereals and pulses within the district. It had the third highest proportion of households using improved seeds. The district had the third largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), most of which was farm yard manure. Compared to other districts in the region, Kibaha district had the highest level of insecticides use. The use of fungicides was the second highest but it had the fourth application of herbicides in the region. With 467ha of irrigated land, it had the second largest area under irrigation. The most common source of water for irrigation were rivers using gravity as well as wells. Bucket/watering cans and water hose were the two most common means of irrigation water application in the district. The most common method of crop storage in Kibaha district was sacks/open drums followed by locally made cribs. Of the households storing crops in the district, it ranked second in quantity stored. Kibaha district had the second least number of households selling crops. Kibaha was among the districts with the lowest percent of households processing crops in Pwani region and this was almost all done on farm by hand. No agricultural households accessed credit in the district. The district had the second least number of households that received extension services and all of these were from the government (95%) and large scale farms. The quality of extension services was rated between good and average by the majority of the households. Tree farming was of highest importance in Kibaha (with 226,797 planted trees or 64.5%) and most trees were melicia excelsa, senna spp, acacia spp and eucalyptus spp. The 3rd highest proportion of households with erosion control and water harvesting structures was found in Kibaha district and these were mostly erosion control bunds and tree belts. Also Kibaha had use of terraces and dams not recorded in the other districts. The district had the 3rd largest number of cattle as well as sheep, goats and pigs in the region and about 77.4% of cattle were indigenous, followed by dairy cattle. It ranked fifth in the number of chicken in the region and most of those were broilers. Ducks, turkeys, rabbits and other livestock in the district were insignificant in number. It ranked fifth in the DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 107 number of households that reported tsetse and tick problems had the second highest percent of households de-worming livestock. The district had no households using draft animals or fish farming. It had the best access to secondary schools, primary schools, primary and secondary markets compared to other districts. It also had one the best accesses to all weather roads, regional capital, feeder roads and tarmac roads. The percentages of households without toilet facility in Kibaha district was 6 percent and this was the lowest in the region. Also it ranked fifth in percentage of households that owned various household assets and these were radios, bicycles, irons, mobile phones, wheelbarrows but had a moderate number of households owning landline phones, vehicles and tv/video. The most common source of energy for lighting was the wick lamp followed by the hurricane lamp and mains electricity. Practically all the agricultural households used firewood for cooking followed by charcoal. Within the district, roofing materials were grass/leaves (52% and ranked last in region), and iron sheets (46%, ranking first in region). The most common source of drinking water in the wet season was from piped water followed by unprotected wells and surface water. Though it ranked last, half of its households reported having three meals per day. However it ranked first in households having two meals compared to other districts. The district had the second lowest percent of households that did not eat meat but a higher percent of those that did not eat fish during the week prior to enumeration. A moderately low number of households seldom had problems with food satisfaction and ranked fourth accounting for 12% in the region regarding this aspect. 4.2.3 Kisarawe Kisarawe district had the second least number of households in the region and it had the fourth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Kisarawe district was permanent crop farming, followed by annual crop farming and then tree/forest resources. However, the district had the lowest percent of households with no off-farm activities and third lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kisarawe had the second lowest percent of female headed households (16%) but second highest average age of the household heads in the region. Its average household size of 4.6 members per household was below the average for the region. Kisarawe had a comparatively moderate literacy rate among smallholder households and this was reflected by the relatively moderate level of school attendance in the region. The literacy rate for the heads of household was the second in the region. It had the second least utilized land area per household (1.5ha) and lower than the regional average of 1.8ha. Ninety one percent of the allocated area was currently being utilised. The total planted area was 3rd lowest in the region due to the absence of good wet and dry seasons. Also it had the second lowest planted area per household (0.42ha). The district came fourth in maize production in the region with a planted area of over 6,472ha. The planted area per household was 0.4ha which was the second lowest in the region. In paddy production it came fifth in the region. with a planted area of 1,707 hectares. Bulrush millet, finger millet, wheat and barley were not produced in the district. The district had the third largest planted area for cassava accounting for 19.1 percent of the cassava planted area in the region but first in quantity harvested (31%). The production of beans in Kisarawe was important as it ranked second in planted area. Oilseed crops were important in Kisarawe with 38 percent of the region’s planted for groundnuts being in that DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 108 district. Sunflower was not grown in the district. Vegetable production was fairly important in the district and it had the fourth largest planted area for tomatoes and the second largest for water mellon (64 ha and 27 ha respectively) and accounted for 12 percent of the tomato production and 14 percent of the water mellon production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Kisarawe district. Permanent crops were fairly important in Kisarawe district as 12.7% of the total permanent crop planted area in Pwani region was found in the district. The most prominent permanent crops in the district were cashew nuts (3,541 ha), oranges (1,937 ha), coconuts (1,575 ha), bananas (1,100 ha), jackfruits (1,042 ha), pigeon peas (441 ha), mango (302 ha.) and pawpaws (170 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was also done by bush clearance followed by no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Kisarawe had the third largest planted with improved seeds and this was due to the dominance of cereals, roots and tubers crops. However, it had the fourth highest percentage of households using improved seeds. The district had the fourth largest area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), and most of this was compost. Compared to other districts in the region, Kisarawe district had the second least application of insecticides and fungicides, and it came last in the use of herbicides. It had the second least area under irrigation with 193 ha of irrigated land. The most common source of water for irrigation was the well, using hand bucket. Bucket/watering cans was the most common means of irrigation water application. The most common method of crop storage in Kisarawe was locally made traditional crib. However the proportion of households storing crops in the district was second highest in the region but the quantity stored was the least. The district had the fourth highest percent of households selling crops, however for those few that did not sell, the main reason for not selling was insufficient production followed by trade union problems. Kisarawe district ranked first in processing crops and almost all of it was done on farm by hand and to a lesser extent, using a neighbour’s machine. The district had the fourth highest percent of households selling processed crops and selling to neighbours ranking high in the district. No households accessed credit in the district. Kisarawe had the second largest number of households receiving crop extension services most of which were from the government (98%). The quality of extension services was rated between good and average by the majority of the households. Tree farming was of low priority in Kisarawe district (with 27,184 planted trees, 7.7%) and these were mostly cyprus spp, moringa spp, with some senna spp. The fourth highest proportion of households with water harvesting bunds and erosion control bunds were found in Kisarawe district. It also had the only recorded gabions/sandbags in the region as a measure against erosion in the region. The district had 2.6% of the total cattle in the region and ranked fifth. The cattle were almost all indigenous followed by the dairy breed. In regard to the number of goats it came fourth and there was no sheep production recorded. It had the least number of pigs in the region (2,226 or 61%) and one of the least number of chicken ranking fourth. Most of the chicken were of the indigenous breed followed by layers and broilers breeds. However, the district had around 14% of all the indigenous chicken in the region. As for improved breed, it ranked second in layers and highest in the number of broilers. The district had the fourth largest number of ducks, and no rabbits nor donkeys recorded but ranked second in rabbits. All DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 109 other unspecified types of other livestock category in the region were not recorded in Kisarawe . It had the third highest number of households reporting tsetse and tick problems. Though small, de-worming of livestock was moderately practiced as it ranked fifth. Kisarawe did not use draft animals to cultivate the land; also it did not practice fish farming. It had moderate access to secondary schools, primary schools, health clinics, feeder roads, all weather roads and primary markets compared to other districts. Also it had a moderate access to feeder roads and the regional capital. Kisarawe district had the second lowest percent (6.8%) of households with no toilet facilities and it was among the high percentages of households owning household facilities in general ranking fourth in the region. It owned radio, bicycles, iron, wheel barrows, Tv/video and vehicles; had the lowest percent of landlines and mobile phones. It had the second least number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp followed by hurricane lamp, firewood and pressure lamp. Practically all households used firewood for cooking. The district had the fourth highest percent of households with grass roofs (65%) and 26 percent of households having iron sheets roofing. The most common source of drinking water was the unprotected well followed by uncovered rainwater catchments. Thirty eight percent of the households in the district reported having one or two meals per day and it ranked first in households which reported having three meals per day at most. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration, however the district had the highest percentage of its households that often had problems with food satisfaction than the other categories. 4.2.4 Mkuranga Mkuranga district had the third largest number of households in the region and it had about one quarter of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had neither livestock only households nor pastoralists. The most important livelihood activity for smallholder households in Mkuranga district was permanent crop farming, followed by annual crop farming and off farm income. However, the district had the highest percent of households with no off-farm activities and one quarter of its total households with more than one member with off-farm income. Compared to other districts in the region, Mkuranga had the third highest percent of female headed households (22%) and was the first in average age of the household heads (50.8 years). With an average household size of 5.2 members per household it had the second highest for the region. Mkuranga had a comparatively high literacy rate among smallholder households and this was reflected by the concomitant high level of school attendance in the region.. The literacy rate for the heads of household was also higher than most of districts in the region. It had the highest utilized land area per household (2.12ha) and above the regional average of 1.8ha. indicating that the allocated area was almost fully utilized (86%). The total planted area was the second largest in the region due to the presence of good wet and dry seasons, however it had the fourth highest planted area per household (0.5ha) and ranks second highest in the number of smallholders in the district. The district ranked third in planted area for maize production in the region with a planted area of 8,413 ha, and the planted area per household was third lowest in the region. Paddy production was very important with a planted area of 5,837 hectares but the production of sorghum was insignificant. Cassava production was also very important accounting for 24 percent of the quantity harvested in the region. The district had the largest planted area of cassava, a crop which ranked second in the region (after maize) in terms of the area planted with annual crops (17,569 ha). The production of beans was DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 110 nil, were produced only in Kibaha, Kisarawe and Bagamoyo districts only. Oilseed crops were not important in Mkuranga and accounted for 7.1% of all oilseed crops planted area in the region. However it ranked second in the production of groundnuts which was the region’s 11th crop nationally in terms of planted area. Sunflower was not grown in Mkuranga district. Vegetable production was very important, ranking first in the region. It had the second largest area planted with tomatoes as well as water mellon (237 ha and 242 ha respectively). However, it was the only district with planted area for chillies and accounted for 100 percent of the chillies production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Mkuranga district. Compared to other districts in the region, Mkuranga ranked first in planted area with permanent crops (36%) which was dominated by cashewnuts (19,636 ha), coconuts (4,569 ha), mandarines/tangerines (1,190 ha), oranges (1,162 ha), pinaeapples (906 ha), pigeon peas (613 ha), and mangoes (457 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was done by bush clearance followed by option of no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Mkuranga had the third largest area planted with improved seeds in Pwani region and this was due to the high planted area of vegetables and ranked second in the number of households using improved seeds. The district had the second largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), most of which was compost. Compared to other districts in the region, Mkuranga district ranked second in the level of insecticides use. In the use of fungicides although small, it ranked first in the region and in the use of herbicides it ranked second. It had the largest area under irrigation compared to other districts with 1,974 ha of irrigated land. The most common sources of water for irrigation were wells and canals. Bucket/watering cans and flood water were the most common means of irrigation water application. The most common method of crop storage was locally made traditional cribs where it ranked fourth in the region, however the proportion of households storing crops in the district was moderate, with moderate quantities in tons of stored crops in the region. The district had the third largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. It was the second highest percent of households processing crops in Pwani region and almost all processing was done on farm by hand followed by on farm by machine. The district also had a high percentage of households selling processed crops to traders at farm and no sales were made to marketing cooperatives. The distribution of households accessing credit was 89% for male headed households and 11% for female headed households. The main sources were savings and credit, NGO’s traders/trade stores and lastly, family friends and relatives. Mkuranga had the third largest number of households receiving extension services and most of these were from the government (95%). The quality of extension services was rated between good and very good by the majority of the households. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 111 Tree farming was of low importance in Mkuranga (with 14,512 or 4.1% planted trees) and most of these were eucalyptus, azadritachta spp and cyprus spp. The highest proportion of households with erosion control and water harvesting structures were found in Mkuranga district and these were mostly tree belts and erosion control bunds. It had the highest number of vetiver grass, unlike other districts which had none. The district had the least number of cattle in the region and they were almost all improved dairy followed by indigenous. Goats and also sheep were among lowest. Pigs production ranked second compared to other districts in the region. It had a large number of chicken (all indigenous) and ranked second in turkeys, but no ducks, rabbits or donkeys were recorded. It had the least number of households reporting tsetse and tick problems and it also had the least number of households de- worming livestock. No draft animals were used in the district and there was also no fish farming. It had a better access to health clinics, hospitals and primary and secondary markets compared to other districts. It also had a better access to feeder roads and tarmac roads. Mkuranga district had 14.5% of households in the region with no toilet facilities and in this it ranked fourth in the region. It also ranked fourth in the percentage of households owning radios, bicycles, irons, wheelbarrows and tv/videos but the lowest in mobile phones, and vehicles. It had a low number of households (7%) using mains electricity in the region. The most common source of energy for lighting was the wick lamp followed by hurricane lamp and practically all households used firewood for cooking having a quarter of total households that used firewood in the region. The district had the second highest percent (78%) of households with grass roofs and 20 percent of households having iron sheets. The most common source of drinking water in the wet season was the unprotected well followed by unprotected springs. It had the highest percent of households having one meal per day compared to other districts and two thirds of its households have 3 meals per day. The district had the second highest percent of households that did not eat meat and second lowest percent (4%) who did not eat fish during the week prior to enumeration. However most households never had problems with food satisfaction, ranking first in the region. 4.2.5 Rufiji Rufiji district had the second largest number of households in the region and it had the second highest percent of households involved in smallholder agriculture. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Rufiji district was annual crop farming, followed by tree/forest resources and permanent crop farming. The district had the second highest percent of households with no off- farm activities and had the third highest percent of households with more than one member with off-farm income. Rufiji had very few households with more than one member having off farm income. Compared to other districts in the region, Rufiji had the second highest percent of female headed households (25%) and it had one of the high average age of the household head in the region (49 years). With a household size of 5.4 members per household it had the highest for the region. Rufiji had a low literacy rate among smallholder households and this was reflected by the district having a moderate level of school attendance and highest percentage of those who never attended school. It had the fourth largest utilized land area per household (1.6ha) and 86 percent of the allocated area was currently being utilised. The district had the third highest planted area in the region, and second highest in planted area per household either season (0.69ha in the long rainy season and 0.47ha in the short rainy season). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 112 The district was second in importance for maize production in the region with a planted area of over 12,653ha, and the planted area per maize growing household was also high for the region. The district had the largest planted area of paddy in the region with 10,516 hectares. Bulrush millet, and wheat were not grown in the district; however, sorghum was very important and it ranked second in planted area. Cassava production was important, accounting for 25 percent of the quantity harvested in the region. The production of beans in Rufiji district was insignificant. Rufiji district had the second largest planted area for oilseeds crops with a planted area of 559ha. The district was second least in groundnuts planted area and a planted area per groundnut growing household of 0.2ha an area which was lower than the region’s average. In Rufiji district, vegetable production ranked third in importance and it had the smallest planted area for tomatoes (25ha.) and no water mellon. No planted area was recorded for chillies, cucumbers, eggplants, onions and cabbages although they were grown elsewhere in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Rufiji district. Compared to other districts in the region, Rufiji had third largest planted area for permanent crops (18.7%) which were dominated by cashewnuts (10,591 ha), coconuts (1,906 ha), oranges (1,294 ha), pineapples (533 ha), bananas (484 ha), pigeon peas (207 ha), and mangoes (160 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was done by bush clearance followed by no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Rufiji had second least area planted with improved seeds in the region and this was due to the moderate planted area of cereals and cassava. However, it had the second least proportion of households using improved seeds. The district had the least planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers) and most of this was compost. Compared to other districts in the region, Rufiji district ranked third in the level of insecticides use. In the use of fungicides it ranked third and in the application of herbicides it ranked first in the region. It had the third largest area under irrigation compared to other districts with 298 ha of irrigated land. The most common sources of water for irrigation were wells and rivers using gravity. Flood water and bucket/watering cans were the two means of irrigation water application in Rufiji district. The most common method of crop storage in Rufiji district was locally made traditional structure followed by sacks/open drums; however the quantity in tons of stored crops in the district ranked second. Rufiji district was second in the number of households selling crops in the region. Rufiji was among the districts with the highest percent of households processing crops in the region and almost all processing was done on farm by hand. Although very small, access to credit in the district was to male headed households only and the source was religious organisations/NGO’s/projects only. A moderately large number of households received extension services in Rufiji district and these were from the government (100%). The quality of extension services was rated between good and very good by the majority of the households. Tree farming was third highest in the region (with 39,439 planted trees or 11.2%) and most trees were tectona and leucena spp. There were no households with erosion control and water harvesting structures in Rufiji district The district had the fourth largest number of cattle in the region and they were mostly indigenous followed by improved beef. In goats and sheep production it ranked second but had no pigs. It had the third largest number of chicken mostly indigenous and layers but no broilers. In ducks and rabbits production it ranked third but no turkeys and donkeys were found in the district. It had the least number of households reporting tsetse and tick problems and the lowest percent of households de-worming livestock. The district had no households using draft animals or involved in fish farming. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 113 It had a fairly good access to secondary schools, primary schools, primary markets compared to other districts but also had one of the worst access to the regional capital. The percentage of households without toilet facility in Rufiji district was highest in the region (32 percent). It was among the districts with moderately high percent of households owning radios, tv/video and mobile phones and a moderate number owning bicycles but ranked first in wheelbarrows. Next to Bagamoyo, it ranked second highest in the number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp. Rufiji ranked third and practically all households used firewood for cooking accounting for 22% of total households that used firewood in the region. The district had the third highest percent (71%) of its households with grass roofs and ranked fifth with 18 percent of its households having iron sheets. The common source of drinking water in the wet season was from unprotected wells and unprotected springs. It had moderate to low percent of households having one to two meals per day compared to other districts and two thirds of its households have 3 meals per day. The district had one of the highest percentages of households that did not eat meat but among lowest percentages of who did not eat fish during the week prior to enumeration. However most households never experienced problems with food satisfaction, ranking third in the region. 4.2.6 Mafia Mafia district had the smallest number of households in the region as well as the lowest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Mafia district was annual crop farming, followed by permanent crop farming and off farm income. However, the district had the second lowest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mafia had the lowest percent of female headed households (3%) and also the lowest average age of the household head in the region (45 years). With an average household size of 4.5 members per household it almost had the average for the region. Mafia had the highest literacy rate among smallholder households members but this was not reflected by the low level of school attendance in the region. It also had the lowest percentage of heads of agricultural households with both primary education and secondary education. It had the least utilized land area per household (1.4ha) far below the regional average of 1.8ha but ranked first in percentage of the allocated area currently being utilized (94%). The total planted area was the lowest in the region due to the absence of good wet and dry seasons. Also it had the lowest planted area per household (0.37ha) attributed to the lowest in the region the number of smallholders in the district. The area planted per household was lowest in the long rainy season but ranked third lowest in the short rainy season. The district was not important for maize production in the region with a planted area of about 90ha. and the planted area per household was 0.2ha which was the lowest in the region. Paddy production an annual crop which came third in the region after cassava and maize was of low importance with a planted area of 1,431 hectares. Bulrush millet, sorghum, finger millet, wheat and barley were not produced in the district. The district had the smallest planted area of cassava accounting for 1.7 percent of the cassava production in the region. Beans were not produced in Mafia. Oilseed crops were of less importance in Mafia with less than 1 percent of the groundnuts grown in the district. Sunflower was not grown in the district. Vegetable production was less important in the district. It had the second least planted area for tomatoes and no water mellon (31 ha) than other districts in the region and accounted for 3.3 percent of the tomato production in the region. The only traditional cash crop grown in Mafia was seaweed (100%). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 114 Permanent crops were of least importance in Mafia district and planted area with permanent crops (7.8%) were dominated by coconuts (4,778 ha), bananas (920 ha), pineapples (372 ha), cashewnuts (220 ha), mangoes (50 ha) and oranges (40 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation were done by hand, however a very small area of land preparation was done by bush clearance followed by no land clearing.. Ploughing was by hand hoe followed by oxen but no tractor ploughing. The use of inputs in the region was very small, however district differences existed. Mafia had the least area planted with improved seeds in Pwani region and this was due to limited agricultural activity. It also had the least percentage of households using improved seeds. The district had the second least planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), however it ranked first in the use of farm yard manure and inorganic fertilizers. Compared to other districts in the region, Mafia district had the least application of insecticides and fungicides to its planted area and ranked third in herbicides. It had the least area under irrigation compared to other districts with 32 ha of irrigated land. The most common sources of water for irrigation were wells and rivers using hand bucket and gravity. Bucket/watering cans and flood water were the most common means of irrigation water application. The most common method of crop storage in Mafia was sacks and open drums, in which it ranked first followed by Kibaha. The proportion of households storing crops in the district was highest in the region and it ranked third in quantity in tons of crops stored in the region. The district had the least percent of households selling crops, however for those few that did not sell, the main reason for not selling was insufficient production followed by trade union problems. Mafia district was one of the districts in Pwani region with lowest percent (4%) of households processing crops and all processing was done on farm by hand. The district had the second least percent of households selling processed crops (35%) and all sales were to neighbours. There was no incidence of access to credit in the district. Mafia had the least number of households receiving crop extension services and most of these were from the government (82%). The quality of extension services was rated between good and average by the majority of the households. In tree farming it was last in the region (with 2,879 planted trees or 0.8%) and these were mostly moringa spp, with some melicia excelsa. The second highest proportion of households with water harvesting bunds and erosion control bunds. The district had the second largest number of cattle in the region though only one tenth of the total in region and these were 84% indigenous followed by dairy and beef. Goats and sheep production were notably absent in Mafia as was the case with Kisarawe. Mafia had no pigs and had the least number of chicken most of which were indigenous followed by layers. The district had a large number of ducks, turkeys (97% and highest in region), but no rabbits. All other unspecified types under other livestock were found in Mafia ranking second in the region or 3%. It had the second highest number of households reporting tsetse and tick problems. Although small, de-worming of livestock was moderately practiced. Mafia was the only district in the region using draft animals to cultivate the land. No fish farming was practiced in any district in Pwani region. It had a poor access to tarmac roads, tertiary markets, regional capital, secondary schools, primary schools, feeder roads, all weather roads and primary markets compared to other districts but it had a good access to health clinics. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 115 The percentage of households without toilet facility in Mafia district was third highest in the region (16 percent). Though it ranked first in radio ownership, it had the lowest percent (4%) of households owning assets in general and ranked last in wheelbarrows and bicycles. It ranked last in the percentage (3%) of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp but Mafia was the least user of wick lamps and the hurricane lamps. Firewood was used in Mafia for cooking accounting for 4.2% of total households that used firewood in the region. The district had the highest percent (91%) of its households with grass roofs and lowest percent (9%) with iron sheets much below the region’s average of 27%. The common source of drinking water in the wet season was from unprotected wells followed by protected wells and uncovered rain-water catchments. It had moderate to low percent of households having two meals per day compared to other districts but among the highest with its households having 3 meals per day. The district had the least percentages of households that neither ate meat nor fish during the week prior to enumeration. Although almost half of the households (47%) within the district never experienced problems with food satisfaction, the district came last compared to other districts as it accounted for 8% of total households that never had such problems in the region. APPENDIX II 116 4. APPENDICES APPENDIX I Tabulation List ............................................................................................................................. 117 APPENDIX II Tables............................................................................................................................................. 132 APPENDIX III Questionnaires.............................................................................................................................. 273 APPENDIX II 117 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD....................................................................................................... 132 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 133 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year. 133 NUMBER OF AGRICULTURE HOUSEHOLDS............................................................................................... 134 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .................................................................................. 135 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District.................................................................................................................. 135 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.......................................................................... 136 3.1a First Most Importance................................................................................................................................. 137 3.1b Second Most Importance ............................................................................................................................ 137 3.1c Third Most Importance ............................................................................................................................... 137 3.1d Fourth Most Importance ............................................................................................................................. 137 3.1e Fifth Most Importance ................................................................................................................................ 137 3.1f Sixth Most Importance................................................................................................................................ 138 3.1g Seventh Most Importance ........................................................................................................................... 138 HOUSEHOLDS DEMOGRAPHS......................................................................................................................... 140 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) ...................................................................................................................................................... 141 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (Column %)................................................................................................................................................ 141 3.4 Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year...... 142 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year ................................................ 142 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ......................................................................................................................... 142 3.7 Number of Agricultural Household Members by Main Activity and District ............................................ 142 cont… Number of Agricultural Household Members by Main Activity and District................................. 143 cont… Number of Agricultural Household Members by Main Activity and District................................. 143 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year .......................................................................................................................... 143 APPENDIX II 118 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year..................................................................................................... 145 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year .................................................................. 145 3.12 Number of Heads of Agricultural Households by Maximum Education Level Attained and District, 2002/03 Agricultural Year`......................................................................................................................... 145 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District.......................................... 145 3.14 Time Series of Male and Female Headed Households ............................................................................... 146 3.15 Literacy Rate of Heads of Households by Sex and District........................................................................ 146 LAND USE............................................................................................................................................................... 148 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year149 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year ........................... 149 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year...................................................................................................... 149 5.4 Number of Agricultural Households by whether they consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year............................................................... 149 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year................................................... 149 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION SHORT AND LONG RAINY SEASONS.... 152 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District. .......................... 153 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District...................................... 153 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 154 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 – Short and Long Rainy Seasons, Pwani Region ....................................... 155 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Short and Long Rainy Season, Pwani ..................................................................................... 156 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season, Pwani ................................................. 156 APPENDIX II 119 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District Short and Long Rainy Season, 2002/03 Agriculture Year......................................................................... 156 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season. .......................................................... 157 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season............................................................. 157 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season Season................................................. 158 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season Season................................................. 158 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON ............................................. 160 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District – LONG RAINY SEASON, Pwani Region................................................................................... 161 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Pwani Region .............................. 161 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during LONG RAINY SEASON, 2002/03 Agriculture Year, Pwani Region................................ 161 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 162 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 162 7.2f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 163 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON ................................................................ 163 7.2h Planted Area and Number of Crop Growing Households During LONG RAINY SEASON by Method of Land Clearing and Crops; 2002/03 Agriculture Year............................................................................. 165 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 166 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year.......................................................... 166 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 166 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 166 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 167 APPENDIX II 120 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrush millet Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 167 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 167 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 167 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 169 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 169 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 169 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 169 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Pigeon peas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 170 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Water melon Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 171 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 APPENDIX II 121 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 PERMANENT CROPS .......................................................................................................................................... 174 7.3.1 Production of Permanent Crops by Crop Type and District – Pwani.......................................................... 175 7.3.2 Area Planted by Crop Type - Pwani Region............................................................................................... 178 7.3.3 Area Planted with Cashew nuts Coconuts by District................................................................................. 178 7.3.4 Area planted with Coconuts by District...................................................................................................... 178 7.3.5 Area planted with Orange by District ......................................................................................................... 179 7.3.6 Area Planted with Pineapples by District.................................................................................................... 179 7.3.7 Planted Area with Fertilizer by Fertilizer Type and Crop........................................................................... 179 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 180 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 180 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 181 AGROPROCESSING............................................................................................................................................. 182 8.1.1a Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year ............................................................................................................. 183 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year183 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Pwani Region .............................................................................................................. 183 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Pwani Region ........................................ 184 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Pwani Region.... 184 APPENDIX II 122 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Pwani Region....................................................................................... 185 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Pwani Region.......................................................................... 185 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Pwani Region................................................................................................... 185 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Pwani Region................................................................................................... 185 MARKETING ......................................................................................................................................................... 186 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Pwani Region...................................................................................................... 187 10.2 Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Pwani Region........................................................................ 187 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Pwani Region ...................................................................................... 187 IRRIGATION/EROSION CONTROL ................................................................................................................. 188 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District ....................................................................................................................... 189 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year ................... 189 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year............................................................................................ 189 11.4 Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year............................................................................................................... 189 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year ................................................................................ 190 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District....... 190 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year..................................................................................................... 190 ACCESS TO FARM INPUTS................................................................................................................................ 191 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year192 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year............................................................................................................... 192 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year.................................................................................................. 192 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year.................................................................................................. 193 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year .. 193 APPENDIX II 123 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year............................................................................................................... 193 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year...................................................................................................... 194 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year .......................................................................................................................... 194 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................... 195 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................... 195 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year.... 195 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.. 196 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ............................................................................................................ 196 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ......................................................................................................................... 197 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.17 Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................................... 199 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................................... 199 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................................ 199 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ............................................................................................................ 201 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................................... 201 APPENDIX II 124 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................................ 201 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year ........................................................................................................... 203 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.35 Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 204 AGRICULTURE CREDIT .................................................................................................................................... 205 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year ......................................................................................................... 206 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year .......................................................................................................................... 206 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year ......................................................................................................... 207 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year ......................................................................................................... 207 TREE FARMING AND AGROFORESTRY ....................................................................................................... 209 14.1 Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Pwani Region.............................................................................................................................................. 210 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Pwani Region................................ 211 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 211 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Pwani Region.................................................................... 212 APPENDIX II 125 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 212 CROP EXTENSION............................................................................................................................................... 213 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Pwani Region.................................................................... 214 15.2 Number of Households by Quality of Extension Services and District During the 2002/03 Agricultural Year, Pwani Region........................................................................................... 214 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region................................................................................. 214 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 215 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................ 215 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............ 215 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 216 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 216 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................... 216 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................ 217 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............ 217 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 217 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 219 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 219 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Pwani Region ................................. 219 APPENDIX II 126 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Pwani Region ................................. 220 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Pwani Region ................................. 220 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Pwani Region.................... 220 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Pwani Region.................... 221 ANIMAL CONTRIBUTION TO CROP PRODUCTION .................................................................................. 223 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Pwani Region............................................................................. 224 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Pwani Region............................................................................. 224 cont… Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Pwani Region............................................................................. 224 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Pwani...................................................................................................... 224 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 225 CATTLE PRODUCTION...................................................................................................................................... 227 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 228 18.2 Number of Cattle By Type and District as of 1st October, 2003 ................................................................ 228 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003............................................................................................................... 228 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003................................................... 229 18.5 Number of Indigenous Cattle by Category and District as on 1st October, 2003 ....................................... 229 18.6 Number of Improved Beef Cattle by Category and District as on 1st October, 2003................................. 229 18.7 Number of Improved Dairy Cattle by Category and District as on 1st October, 2003 ............................... 230 18.8 Number of Cattle by Category and District as on 1st October, 2003.......................................................... 230 GOATS PRODUCTION......................................................................................................................................... 231 19.1 Total Number of Goats by Type and District as on 1st October, 2003....................................................... 232 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ............................................... 232 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District .................... 233 APPENDIX II 127 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003................................ 233 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003 ............................ 233 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ..................................... 234 19.7 Total Number of Goats by Category and District on 1st October, 2003..................................................... 234 SHEEP PRODUCTION ......................................................................................................................................... 135 20.1 Total Number of Sheep by Breed and on 1st October 2003 ....................................................................... 136 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003.............................. 136 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03................................................. 136 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003........................................ 136 20.5 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003............................... 137 20.6 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Pwani Region ............... 137 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003............................... 137 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 ................................................. 137 PIGS PRODUCTION ............................................................................................................................................. 139 21.1 Number of Households and Pigs by Herd Size on 1st October 2003.......................................................... 240 21.2 Number of Households and Pigs by District on 1st October 2003.............................................................. 240 21.3 Number of Pigs by Type and District on 1st October, 2003....................................................................... 240 LIVESTOCK PESTS AND PARASITE CONTROL.......................................................................................... 241 22.1 Number of Livestock Rearing households de-worming Livestock by District during 2002/03 Agricultural Year............................................................................................................... 242 22.2 Number of Livestock Rearing Households that de-wormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year......................................................................................................... 242 22.3 Number and Percent of agricultural households reporting to have encountered tick problems ` during 2002/03 Agriculture Year by District.............................................................................................. 242 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year........................................................................................................ 242 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District.............................................................................................. 243 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year........................................................................................................ 243 OTHER LIVESTOCK............................................................................................................................................ 245 23a Total Number of Other Livestock by Type on 1st October 2003................................................................ 246 APPENDIX II 128 23b Number of Chicken by Category of Chicken and District on 1st October 2003......................................... 246 23c Head Number of Other Livestock by Type of Livestock and District ........................................................ 246 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 ......................... 246 23e Livestock/Poultry Population Trend ........................................................................................................... 246 FISH FARMING..................................................................................................................................................... 247 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year.. 248 28.2 Number of Agricultural Households by System of Farming and District during the 2002/03 Agricultural Year .................................................................................................................... 248 LIVESTOCK EXTENSION................................................................................................................................... 249 29.1a Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year .................................................................................................................... 250 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year .................................................................................................................... 250 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.3 Number of Agricultural Households Receiving Extension Advice on Housing by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking by Source and District, 2002/03 Agricultural Year......................................................................................... 251 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control by Source and District, 2002/03 Agricultural Year.......................................................................................... 252 29.7 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection by Source and District, 2002/03 Agricultural Year.......................................................................................... 252 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection by Source and District, 2002/03 Agricultural Year.......................... 253 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening by Source and District, 2002/03 Agricultural Year ............................................................. 253 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing by Source and District, 2002/03 Agricultural Year.......................................................................................... 254 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls by Source and District, 2002/03 Agricultural Year.......................................................................................... 254 29.12 Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year .......................................................................................................................... 255 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES ........................................................................ 257 APPENDIX II 129 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts.......................... 258 33.01b Number of Households by Distance to Secondary School by District for 2002/03 agriculture year.......... 258 33.01c Number of Households by Distance to All Weather Road by District for 2002/03 agriculture year.......... 259 33.01d Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year................... 259 33.01e Number of Households by Distance to Hospital by District for 2002/03 agriculture year ......................... 259 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year ................ 260 33.01g Number of Households by distance to Primary School for 2002/03 agriculture year................................. 260 33.01h Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year............ 260 33.01i Number of Households by Distance to District Capital by District for 2002/03 agriculture year .............. 261 33.01j Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year ................ 261 33.01k Number of Households by Distance to Primary Market by District for 2002/03 agricultural year ............ 262 33.01l Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year ............ 262 33.01m Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year......... 262 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year……………………………………………………………………263 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year...................................................................................................... 263 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year...................................................................................................... 263 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Laboratories and District, 2002/03 Agricultural Year...................................................................................................... 264 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year...................................................................................................... 264 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year...................................................................................................... 264 HOUSEHOLD FACILITIES................................................................................................................................. 265 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year266 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ............................................................................................................ 266 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ........................................................................................................................ 266 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year ......................................................................................................................... 267 APPENDIX II 130 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year .......................................................................................................................... 267 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ........................................................................................... 268 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ........................................................................................... 268 34.8 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ................................................................ 269 34.9 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ................................................................ 269 34.10 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District ............................................................................................................................ 270 34.11 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ........................................................................................................................ 270 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ........................................................................................................................ 271 34.13 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.......................................................................................................................... 271 34.14 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .......................................................................................................................... 272 34.15 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year.. 272 APPENDIX II 131 APPENDIX II: CROP TABLES Type of Agriculture Household............................................................................................................................................ 132 Number of Agriculture Households ..................................................................................................................................... 134 Rank of Importance of Livelihood Activities....................................................................................................................... 136 Households Demography..................................................................................................................................................... 140 Land Access/Ownership....................................................................................................................................................... 146 Land Use……………… ...................................................................................................................................................... 148 Annual Crop and Vegetable Production Long Rainy Seasons............................................................................................. 160 Permanent Crop Production ................................................................................................................................................. 174 Agro-processing .......................................................................................................................................................... 182 Marketing .......................................................................................................................................................... 186 Irrigation/Erosion Control.................................................................................................................................................... 188 Access to Farm Inputs ......................................................................................................................................................... 191 Agriculture Credit .......................................................................................................................................................... 205 Tree Farming and Agro-forestry .......................................................................................................................................... 209 Crop Extension .......................................................................................................................................................... 213 Animal Contribution to Crop Production............................................................................................................................. 223 Cattle Production .......................................................................................................................................................... 228 Goat Production .......................................................................................................................................................... 231 Sheep Production .......................................................................................................................................................... 235 Pig Production .......................................................................................................................................................... 239 Livestock Pests and Parasite Control ................................................................................................................................... 241 Other Livestock .......................................................................................................................................................... 245 Fishing Farming .......................................................................................................................................................... 247 Livestock Extension .......................................................................................................................................................... 249 Access to Infrastructure and other services.......................................................................................................................... 257 Household Facilities .......................................................................................................................................................... 265 Appendix II 132 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 133 Rural Households Involved in Agriculture % of Total Rural Households Rural Households NOT Involved in Agriculture % of Total Rural Households Total Rural Households % of Total Households Urban Households % of Total Households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Bagamoyo 37,290 26 3,342 8 40,632 81 9,727 19 50,359 Kibaha 14,029 10 3,090 18 17,119 56 13,358 44 30,477 Kisarawe 18,637 13 1,014 5 19,651 86 3,298 14 22,949 Mkuranga 34,744 25 3,418 9 38,162 89 4,775 11 42,937 Rufiji 30,906 22 3,718 11 34,624 78 9,718 22 44,342 Mafia 5,924 4 1,599 21 7,523 76 2,332 24 9,855 Total 141,530 100 16,182 10 157,711 78 43,208 22 200,919 Number of Households % Number of Households % Number of Households % Bagamoyo 31,426 24 1,384 66 4,479 44 37,290 35,905 5,864 Kibaha 12,976 10 339 16 714 7 14,029 13,689 1,053 Kisarawe 17,645 14 47 2 945 9 18,637 18,590 992 Mkuranga 34,251 26 0 0 493 5 34,744 34,744 493 Rufiji 28,997 22 221 11 1,688 17 30,906 30,685 1,909 Mafia 4,055 3 94 5 1,775 18 5,924 5,830 1,869 Total 129,349 100 2,086 100 10,094 100 141,530 139,444 12,180 District Total Number of Households Growing Crops 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year District Agriculture, Non Agriculture and Urban Households Total Number of Households Rearing Livestock Crops Only Livestock Only Total Number of Agriculture Households Crops & Livestock 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year Type of Agriculture Household Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 134 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 135 Number % Average Household Size Number % Average Household Size Number % Bagamoyo 29,938 80 5 7,351 20 5 37,290 100 5 Kibaha 11,272 80 5 2,757 20 4 14,029 100 5 Kisarawe 15,622 84 5 3,015 16 4 18,637 100 5 Mkuranga 28,858 83 5 5,886 17 4 34,744 100 5 Rufiji 24,404 79 6 6,502 21 4 30,906 100 5 Mafia 5,013 85 5 911 15 5 5,924 100 5 Total 115,108 81 5 26,422 19 4 141,530 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 1 4 5 3 6 7 2 Kibaha 1 3 5 2 6 7 4 Kisarawe 2 1 6 4 5 7 3 Mkuranga 2 1 5 3 6 7 4 Rufiji 1 3 7 4 6 5 2 Mafia 1 2 5 3 7 4 6 Total 1 2 5 4 6 7 3 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size 3.1 The livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Male Female Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 136 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 137 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 10,286 3,869 1,920 10,439 2,020 974 7,381 Kibaha 7,990 1,607 362 2,559 912 0 600 Kisarawe 6,341 11,791 48 141 42 0 94 Mkuranga 13,455 14,318 79 3,250 824 865 1,500 Rufiji 22,916 3,351 72 1,876 302 1,141 1,093 Mafia 576 2,311 62 1,482 146 1,282 45 Total 61,564 37,247 2,542 19,747 4,246 4,262 10,714 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 16,035 5,478 1,786 5,623 1,605 100 6,477 Kibaha 3,379 4,258 656 3,026 703 520 1,473 Kisarawe 6,045 4,286 278 2,850 1,310 47 4,044 Mkuranga 12,456 14,684 1,341 3,474 899 377 1,510 Rufiji 5,372 9,784 446 4,163 2,063 3,147 5,386 Mafia 3,054 1,363 410 464 54 472 22 Total 46,341 39,852 4,919 19,601 6,634 4,663 18,911 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 7,087 5,454 3,977 5,943 2,621 301 10,863 Kibaha 1,334 2,370 1,177 2,750 806 62 3,546 Kisarawe 3,135 1,081 837 3,328 2,393 235 6,577 Mkuranga 3,363 2,776 3,352 8,727 3,473 698 8,986 Rufiji 1,612 4,799 2,495 4,280 1,952 1,040 9,654 Mafia 1,431 867 761 887 194 234 168 Total 17,961 17,347 12,598 25,915 11,439 2,570 39,794 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 1,677 4,845 3,969 3,875 2,596 367 7,647 Kibaha 382 1,000 1,581 1,418 585 155 3,499 Kisarawe 396 309 1,142 2,817 1,412 47 5,557 Mkuranga 2,010 1,270 4,599 5,675 1,561 688 7,090 Rufiji 345 2,236 2,281 1,998 817 878 6,289 Mafia 151 192 1,031 502 82 375 312 Total 4,962 9,853 14,603 16,286 7,054 2,510 30,392 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 194 1,244 1,363 1,135 556 76 3,189 Kibaha 42 236 899 323 364 0 1,378 Kisarawe 82 0 951 851 504 0 1,199 Mkuranga 1,376 815 2,294 1,568 912 472 2,704 Rufiji 58 945 515 593 538 153 2,166 Mafia 0 0 170 245 24 114 281 Total 1,753 3,240 6,193 4,715 2,898 815 10,916 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Important 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Important 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Important 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Important 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Important Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 138 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 85 76 403 199 153 0 273 Kibaha 0 81 205 80 82 0 0 Kisarawe 90 0 91 137 95 0 142 Mkuranga 230 124 378 293 365 174 585 Rufiji 0 164 158 152 223 0 53 Mafia 24 0 24 34 0 23 138 Total 428 445 1,258 896 917 197 1,191 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 0 0 0 0 91 91 0 Kibaha 0 0 0 0 0 0 0 Kisarawe 89 94 0 47 0 0 0 Mkuranga 0 0 45 0 0 79 0 Rufiji 154 0 72 0 83 0 164 Mafia 0 0 0 0 47 0 0 Total 243 94 117 47 221 170 164 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Important 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Important Tanzania Agriculture Sample Census - 2003 Pwani 139 Appendix II 140 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 141 Number % Number % Number % Less than 4 47,013 52 43,497 48 90,510 100 05 - 09 52,490 52 48,993 48 101,482 100 10 - 14 55,708 52 52,064 48 107,773 100 15 - 19 39,173 53 34,204 47 73,377 100 20 - 24 23,194 46 27,766 54 50,960 100 25 - 29 18,140 40 26,783 60 44,922 100 30 - 34 19,508 47 22,010 53 41,517 100 35 - 39 15,160 48 16,610 52 31,770 100 40 - 44 13,083 46 15,543 54 28,626 100 45 - 49 9,749 42 13,627 58 23,376 100 50 - 54 11,982 44 15,070 56 27,052 100 55 - 59 8,666 54 7,378 46 16,045 100 60 - 64 10,091 49 10,473 51 20,564 100 65 - 69 7,821 50 7,814 50 15,635 100 70 - 74 9,403 56 7,419 44 16,822 100 75 - 79 5,827 68 2,753 32 8,580 100 80 - 84 4,757 55 3,850 45 8,608 100 Above 85 2,614 49 2,762 51 5,376 100 Total 354,379 50 358,616 50 712,995 100 Number % Number % Number % Less than 4 47,013 13 43,497 12 90,510 13 05 - 09 52,490 15 48,993 14 101,482 14 10 - 14 55,708 16 52,064 15 107,773 15 15 - 19 39,173 11 34,204 10 73,377 10 20 - 24 23,194 7 27,766 8 50,960 7 25 - 29 18,140 5 26,783 7 44,922 6 30 - 34 19,508 6 22,010 6 41,517 6 35 - 39 15,160 4 16,610 5 31,770 4 40 - 44 13,083 4 15,543 4 28,626 4 45 - 49 9,749 3 13,627 4 23,376 3 50 - 54 11,982 3 15,070 4 27,052 4 55 - 59 8,666 2 7,378 2 16,045 2 60 - 64 10,091 3 10,473 3 20,564 3 65 - 69 7,821 2 7,814 2 15,635 2 70 - 74 9,403 3 7,419 2 16,822 2 75 - 79 5,827 2 2,753 1 8,580 1 80 - 84 4,757 1 3,850 1 8,608 1 Above 85 2,614 1 2,762 1 5,376 1 Total 354,379 100 358,616 100 712,995 100 3.2 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 142 Number % Number % Number % Bagamoyo 93,429 49 98,463 51 191,892 100 Kibaha 32,297 51 31,009 49 63,306 100 Kisarawe 43,332 50 42,783 50 86,115 100 Mkuranga 90,704 51 88,783 49 179,487 100 Rufiji 80,883 49 84,511 51 165,394 100 Mafia 13,734 51 13,068 49 26,802 100 Total 354,379 50 358,616 50 712,995 100 Number % Number % Number % Number % Number % Bagamoyo 104,236 63 2,482 1 196 0 59,412 36 166,326 100 Kibaha 38,208 66 2,348 4 0 0 17,132 30 57,687 100 Kisarawe 47,609 64 808 1 0 0 25,930 35 74,347 100 Mkuranga 89,154 57 6,469 4 2,415 2 57,752 37 155,790 100 Rufiji 78,610 54 4,521 3 589 0 60,881 42 144,600 100 Mafia 16,677 70 622 3 155 1 6,281 26 23,734 100 Total 374,493 60 17,250 3 3,354 1 227,388 37 622,485 100 Number % Number % Number % Number % Bagamoyo 48,081 29 62,518 38 55,728 34 166,326 100 Kibaha 15,021 26 25,720 45 16,945 29 57,687 100 Kisarawe 22,003 30 28,511 38 23,833 32 74,347 100 Mkuranga 40,476 26 52,431 34 62,883 40 155,790 100 Rufiji 41,279 29 43,206 30 60,116 42 144,600 100 Mafia 6,942 29 10,194 43 6,598 28 23,734 100 Total 173,802 28 222,580 36 226,104 36 622,485 100 Number % Number % Number % Number % Number % Bagamoyo 72,090 43 5,104 3 2,035 1 677 0 1,198 1 Kibaha 26,343 46 796 1 0 0 83 0 1,127 2 Kisarawe 37,353 50 238 0 0 0 94 0 313 0 Mkuranga 76,533 49 144 0 0 0 1,353 1 444 0 Rufiji 72,469 50 218 0 0 0 3,546 2 833 1 Mafia 10,231 43 46 0 0 0 1,788 8 252 1 Total 295,018 47 6,546 1 2,035 0 7,541 1 4,166 1 3.6 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members 5 Years and Above by School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.5 HOUSEHOLDS DEMOGRAPHICS: Number of Agriculture Household Members 5 Years and Above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.7 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 143 Number % Number % Number % Number % Number % Bagamoyo 4,531 3 1,904 1 4,148 2 4,330 3 1,621 1 Kibaha 584 1 1,192 2 2,265 4 1,497 3 1,191 2 Kisarawe 377 1 1,133 2 665 1 2,743 4 690 1 Mkuranga 2,567 2 1,431 1 1,414 1 4,958 3 1,979 1 Rufiji 991 1 1,812 1 1,195 1 1,470 1 1,046 1 Mafia 1,111 5 250 1 72 0 184 1 199 1 Total 10,160 2 7,721 1 9,759 2 15,180 2 6,726 1 Number % Number % Number % Number % Number % Number % Bagamoyo 777 0 3,321 2 45,777 28 17,565 11 1,249 1 166,326 100 Kibaha 286 0 1,688 3 14,262 25 4,834 8 1,540 3 57,687 100 Kisarawe 138 0 1,743 2 20,967 28 6,776 9 1,117 2 74,347 100 Mkuranga 1,200 1 2,943 2 37,072 24 21,264 14 2,490 2 155,790 100 Rufiji 771 1 390 0 37,701 26 18,837 13 3,321 2 144,600 100 Mafia 23 0 427 2 6,474 27 2,217 9 463 2 23,734 100 Total 3,195 1 10,512 2 162,253 26 71,492 11 10,181 2 622,485 100 Number % Number % Number % Number % Number % Bagamoyo 35,941 22 10,559 6 71,308 43 48,518 29 166,326 100 Kibaha 25,593 44 4,307 7 10,708 19 17,078 30 57,687 100 Kisarawe 36,142 49 3,309 4 11,801 16 23,096 31 74,347 100 Mkuranga 64,407 41 7,870 5 31,402 20 52,112 33 155,790 100 Rufiji 65,224 45 5,922 4 23,481 16 49,974 35 144,600 100 Mafia 8,120 34 2,163 9 5,986 25 7,465 31 23,734 100 Total 235,426 38 34,130 5 154,686 25 198,242 32 622,485 100 District Not Working & Available Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Total Main Activity Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled cont... HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Unpaid Family Helper (Non Agriculture) 3.8 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Level of Involvement in Farming Activivty and District, 2002/03 Agricultural Year District Other District Involvement in Farming Works Full- time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 144 Number % Number % Number % Number % Number % Bagamoyo 377 1 476 1 1,463 2 1,931 3 7,785 12 Kibaha 344 1 34 0 303 1 484 2 2,720 11 Kisarawe 96 0 48 0 980 3 1,124 4 2,356 8 Mkuranga 484 1 370 1 1,438 3 1,232 2 5,247 10 Rufiji 616 1 340 1 1,166 3 1,279 3 4,895 11 Mafia 252 2 89 1 57 1 144 1 474 5 Total 2,168 1 1,357 1 5,406 2 6,194 3 23,478 11 Number % Number % Number % Number % Number % Bagamoyo 43,936 70 804 1 0 0 98 0 0 0 Kibaha 18,192 71 441 2 140 1 0 0 82 0 Kisarawe 19,191 67 659 2 189 1 48 0 0 0 Mkuranga 34,886 67 414 1 238 0 217 0 139 0 Rufiji 29,230 68 482 1 204 0 159 0 58 0 Mafia 7,754 76 42 0 11 0 0 0 0 0 Total 153,189 69 2,843 1 781 0 522 0 280 0 Number % Number % Number % Number % Number % Bagamoyo 96 0 0 0 767 1 0 0 98 0 Kibaha 212 1 23 0 658 3 76 0 364 1 Kisarawe 319 1 43 0 378 1 143 1 128 0 Mkuranga 302 1 0 0 1,148 2 168 0 0 0 Rufiji 153 0 0 0 475 1 0 0 72 0 Mafia 142 1 0 0 150 1 0 0 23 0 Total 1,224 1 66 0 3,576 2 387 0 685 0 Number % Number % Number % Bagamoyo 98 0 1,277 2 62,518 100 Kibaha 310 1 713 3 25,720 100 Kisarawe 47 0 1,293 5 28,511 100 Mkuranga 77 0 4,149 8 52,431 100 Rufiji 0 0 1,681 4 43,206 100 Mafia 5 0 634 6 10,194 100 Total 536 0 9,746 4 222,580 100 District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Level of Formal Education Completed and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Level of Formal Education Completed and District, 2002/03 Agricultural Year District Total Form Six Training After Secondary Education University & Other Tertiary Education Education Level Adult Education 3.9 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Level of Formal Education Completed and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completed and District, 2002/03 Agricultural Year District Under Standard One Standard One Standard Two Standard Three District Education Level Education Level Standard Four Education Level Form One Form Two Form Three Form Four Standard Seven Standard Eight Training After Primary Education Pre Form One Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 145 H/holds % Average Household Size H/holds % Average Household Size H/holds % Bagamoyo 29,938 80 5 7,351 20 5 37,290 100 5 Kibaha 11,272 80 5 2,757 20 4 14,029 100 5 Kisarawe 15,622 84 5 3,015 16 4 18,637 100 5 Mkuranga 28,858 83 5 5,886 17 4 34,744 100 5 Rufiji 24,404 79 6 6,502 21 4 30,906 100 5 Mafia 5,013 85 5 911 15 5 5,924 100 5 Total 115,108 81 5 26,422 19 4 141,530 100 5 Number Percent Number Percent Number Percent Number Percent Bagamoyo 16,813 49 10,042 29 7,389 22 34,244 100 Kibaha 6,736 53 3,577 28 2,291 18 12,604 100 Kisarawe 11,918 65 5,387 29 973 5 18,279 100 Mkuranga 17,474 61 6,935 24 4,025 14 28,434 100 Rufiji 17,284 69 5,134 21 2,551 10 24,970 100 Mafia 2,277 49 1,568 34 819 18 4,663 100 Total 72,502 59 32,643 26 18,048 15 123,194 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Bagamoyo 13,107 22,403 0 664 98 98 920 37,290 Kibaha 4,738 7,753 99 514 100 310 515 14,029 Kisarawe 6,642 10,424 48 326 86 47 1,063 18,637 Mkuranga 13,848 16,784 157 1,092 0 77 2,786 34,744 Rufiji 13,289 15,814 132 527 72 0 1,072 30,906 Mafia 1,847 3,527 33 192 0 5 321 5,924 Total 53,472 76,706 468 3,315 356 536 6,677 141,530 Mean Median Mode Mean Median Mode Mean Median Mode Bagamoyo 47 44 35 55 56 70 49 46 35 Kibaha 48 45 35 53 53 65 49 48 60 Kisarawe 48 45 30 57 58 80 49 48 60 Mkuranga 50 50 60 53 51 65 51 50 60 Rufiji 49 50 60 49 50 70 49 50 70 Mafia 43 40 30 55 59 60 45 42 30 Total 48 45 35 53 52 70 49 48 60 District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHICS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHICS: Mean, Median, Mode of Age of Head of Agricultural Household and District 3.11 HOUSEHOLD DEMOGRAPHICS: Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.10 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Household Size Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 146 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads (In Thousands) 175 179 192 204 124 115 Female Heads (In Thousands) 38 51 63 64 28 26 Total (In Thousands) 213 230 255 268 152 141 Male headed (Percentage) 81 81 81 81 82 81 Female headed (Percentage) 19 19 19 19 18 19 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Bagamoyo 74 31 66 26 69 34 100 100 100 Kibaha 76 41 70 24 59 30 100 100 100 Kisarawe 69 38 64 31 62 36 100 100 100 Mkuranga 74 44 69 26 56 31 100 100 100 Rufiji 66 41 61 34 59 39 100 100 100 Mafia 81 34 74 19 66 26 100 100 100 Total 72 38 66 28 62 34 100 100 100 Literacy Rate (%) 3.14 Time Series of Male and Female Headed Households Can Read and Write Cannot Read and Write Total 3.15 Literacy Rates of Heads of Households by Sex and District District Tanzania Agriculture Sample Census - 2003 Pwani 147 Appendix II 148 LAND USE Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 149 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture House holds with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Area of Land Utilized by Household Total Number of Househol ds Bagamoyo 25,160 8,428 8,884 6,808 5,543 1,463 4,457 1,182 682 278 1,541 11,620 76,965 37,290 Kibaha 7,249 4,388 2,440 2,160 4,740 151 977 122 150 94 420 3,082 25,062 14,029 Kisarawe 2,116 3,642 4,209 5,041 12,511 188 696 95 330 190 297 2,605 29,041 18,637 Mkuranga 13,116 5,658 10,515 12,684 18,302 144 3,195 498 375 332 1,073 3,463 75,310 34,744 Rufiji 12,005 13,316 9,295 4,535 7,160 0 1,559 293 381 156 956 3,765 51,539 30,906 Mafia 4,485 370 3,109 1,218 358 68 185 0 44 0 138 468 8,386 5,924 Total 64,131 35,802 38,452 32,444 48,613 2,014 11,069 2,190 1,961 1,051 4,425 25,003 266,304 141,530 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Bagamoyo 30,273 9,251 7,847 9,246 6,976 4,345 7,654 3,356 314 1,060 2,475 17,538 100,335 Kibaha 7,344 4,020 2,152 2,454 6,701 1,265 1,042 398 48 36 1,593 3,981 31,034 Kisarawe 1,338 2,727 2,765 6,064 14,850 265 623 497 138 271 243 2,362 32,143 Mkuranga 8,086 5,092 15,777 19,046 23,195 40 3,665 726 36 373 2,428 4,632 83,096 Rufiji 9,719 12,254 9,153 5,044 13,511 . 1,635 341 145 78 901 4,904 57,686 Mafia 2,709 222 3,348 1,583 300 16 169 41 61 253 8,701 Total 59,468 33,566 41,042 43,438 65,532 5,932 14,787 5,319 722 1,818 7,702 33,671 312,996 % 19.0 10.7 13.1 13.9 20.9 1.9 4.7 1.7 0.2 0.6 2.5 10.8 100.0 5.1 LAND USE: Number of Agricultural Households by Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts Type of Land Use 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 150 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Bagamoyo 17,842 50 18,063 50 35,905 100 Bagamoyo 24,616 69 11,289 31 35,905 100 Kibaha 8,352 61 5,337 39 13,689 100 Kibaha 8,621 63 5,069 37 13,689 100 Kisarawe 15,486 83 3,104 17 18,590 100 Kisarawe 13,261 71 5,329 29 18,590 100 Mkuranga 24,276 70 10,468 30 34,744 100 Mkuranga 22,621 65 12,123 35 34,744 100 Rufiji 22,569 74 8,115 26 30,685 100 Rufiji 16,704 54 13,981 46 30,685 100 Mafia 3,885 67 1,945 33 5,830 100 Mafia 3,035 52 2,795 48 5,830 100 Total 92,412 66 47,032 34 139,444 100 Total 88,856 64 50,587 36 139,444 100 Number Percent Number Percent Number Percent Bagamoyo 13,652 38 22,253 62 35,905 100 Kibaha 2,288 17 11,401 83 13,689 100 Kisarawe 4,816 26 13,774 74 18,590 100 Mkuranga 9,060 26 25,684 74 34,744 100 Rufiji 4,725 15 25,959 85 30,685 100 Mafia 2,259 39 3,571 61 5,830 100 Total 36,799 26 102,644 74 139,444 100 5.5: Number of Agricultural Households by Whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have Customary Right for Land? Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you Have Sufficient Land for the Hh? Yes No Total 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Pwani 151 Appendix II 152 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 153 Number of households Planted area (hectare) Number of Households Planted Area (hectare) Bagamoyo 21,024 16,701 32,684 44,062 60,763 27.48 Kibaha 10,492 9,378 9,019 9,905 19,284 48.63 Kisarawe 13,913 7,863 6,350 13,056 20,920 37.59 Mkuranga 23,721 14,405 9,342 23,162 37,566 38.34 Rufiji 23,774 18,188 10,080 17,846 36,033 50.47 Mafia 3,298 1,606 2,926 1,499 3,106 51.73 Total 96,222 68,141 70,400 109,531 177,672 38.35 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Bagamoyo 21,024 16,266 32,684 4,605 35,905 Kibaha 10,492 3,537 9,019 5,010 13,689 Kisarawe 13,913 4,724 6,350 12,287 18,590 Mkuranga 23,721 11,023 9,342 25,402 34,744 Rufiji 23,774 7,132 10,080 20,826 30,685 Mafia 3,298 2,626 2,926 2,999 5,830 Total 96,222 45,307 70,400 71,129 139,444 District Dry Season Wet Season Total Number of Crop Growing Households 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area Planted in Dry Season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Dry Season Wet Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 154 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 38,019 11,561 304 32,300 11,430 354 70,319 22,991 327 Paddy 9,937 2,305 232 18,574 4,756 256 28,511 7,062 248 Sorghum 798 425 533 3,675 855 233 4,473 1,280 286 Bulrush Millet 41 2 50 0 0 0 41 2 0 Finger Millet 30 18 618 71 4 59 101 23 224 Wheat 0 0 0 0 0 0 0 0 0 Barley 114 0 0 0 0 0 114 0 0 CEREALS 48,940 14,312 54,620 17,046 103,560 31,358 Cassava 4,970 4,837 973 44,301 66,353 1,498 49,270 71,190 1,445 Sweet Potatoe 521 637 1,223 1,275 771 605 1,796 1,408 784 Irish Potatoes 0 0 0 24 41 1,688 24 41 1,688 Yams 5 22 4,199 62 0 0 67 22 323 Cocoyam 0 0 0 0 0 0 0 0 0 ROOTS & TUB 5,496 5,496 45,662 67,165 51,158 72,661 Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 0 Cowpeas 11,056 1,681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick Peas 10 2 247 0 0 0 10 2 0 Bambaranuts 15 1 89 0 0 0 15 1 0 Field Peas 0 0 0 0 0 0 0 0 0 PULSES 12,039 1,747 5,513 552 100 17,552 2,299 Sunflower 0 0 0 21 10 449 21 10 449 Simsim 166 18 109 2,386 312 131 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & 368 113 2,552 335 131 2,920 448 Okra 98 35 353 28 73 2,585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergin 0 0 0 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 0 0 0 Onions 22 15 697 2 4 1,976 24 19 800 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 13 0 0 13 19 1,506 26 19 729 Tomatoes 404 840 2,077 491 1,104 2,250 895 1,944 2,172 Spinnach 24 2 93 6 4 726 30 6 218 Carrot 0 0 0 0 0 0 0 0 0 Chillies 6 1 222 0 0 0 6 1 0 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1,328 264 225 853 Cucumber 57 45 794 29 39 1,378 86 85 989 Egg Plant 0 0 0 12 37 3,073 12 37 3,073 Water Mellon 183 921 5,027 114 203 1,785 297 1,124 3,787 Cauliflower 0 0 0 0 0 0 0 0 0 FRUITS & VE 1,046 2,019 940 1,664 1,987 3,682 Seaweed 171 180 1,055 183 188 1,024 354 368 1,039 Cotton 82 0 0 59 117 1,976 141 117 832 Tobacco 0 0 0 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 CASH CROPS 252 180 243 305 495 485 Total 68,141 109,531 177,672 *The total area planted include the sum of the planted area for both Long and Short Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long Season to estimate physical land area under production to different crops. 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Pwani Region Crop Dry season Wet Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 155 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Maize 71,919 38,019 40,193 32,300 70,319 54 Paddy 19,136 9,937 30,542 18,574 28,511 35 Sorghum 2,443 798 6,090 3,675 4,473 18 Bulrush Millet 111 41 0 0 41 100 Finger Millet 74 30 84 71 101 30 Wheat 0 0 0 0 0 0 Barley 130 114 0 0 114 100 CEREALS 93,813 48,940 76,909 54,620 103,560 47.3 Cassava 8,988 4,970 65,461 44,301 49,270 10 Sweet 1,835 521 3,036 1,275 1,796 29 Irish Potatoes 0 0 130 24 24 0 Yams 67 5 98 62 67 8 Cocoyam 0 0 0 0 0 0 ROOTS & 10,891 5,496 68,725 45,662 51,158 10.7 Mung Beans 39 16 0 0 16 100 Beans 204 18 0 0 18 100 Cowpeas 39,454 11,056 14,618 5,167 16,223 68 Green Gram 3,406 920 951 345 1,265 73 Pigeon Peas 27 6 0 0 6 100 Chick Peas 82 10 0 0 10 100 Bambaranuts 72 15 0 0 15 100 Field Peas 0 0 0 0 0 0 PULSES 43,283 12,039 15,570 5,513 17,552 69 Sunflower 0 0 96 21 21 0 Simsim 574 166 4,894 2,386 2,552 6 Groundnuts 1,048 202 508 140 342 59 Soya Beans 0 0 47 5 5 0 Castor Seed 0 0 0 0 0 0 OIL SEEDS 1,622 368 5,546 2,552 2,920 13 Okra 232 98 119 28 126 78 Radish 0 0 84 101 101 0 Turmeric 0 0 0 0 0 0 Bitter 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 Onions 131 22 47 2 24 92 Ginger 0 0 0 0 0 0 Cabbage 47 13 192 13 26 52 Tomatoes 1,815 404 1,486 491 895 45 Spinnach 150 24 145 6 30 80 Carrot 0 0 0 0 0 0 Chillies 73 6 0 0 6 100 Amaranths 729 84 263 36 120 70 Pumpkins 1,007 155 436 109 264 59 Cucumber 237 57 65 29 86 67 Egg Plant 0 0 62 12 12 0 Water Mellon 794 183 246 114 297 62 Cauliflower 0 0 0 0 0 0 FRUITS & 5,215 1,046 3,145 940 1,987 53 Seaweed 316 171 316 183 354 48 Cotton 102 82 195 59 141 58 Tobacco 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 Jute 0 0 0 0 0 0 CASH 418 252 511 243 495 51.0 Total 155,243 68,141 170,406 109,531 177,672 38.4 % Area Planted in Dry Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Pwani Region Crop Dry season Wet Season Total Area Planted Short & Long Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 156 Number of Households Planted Area (ha) Number of Households Planted Area (ha) Number of Households Planted Area (ha) Number of Households Planted Area (ha) Bagamoyo 2,162 1,657 1,209 1,042 50,338 52,004 35,905 54,703 Kibaha 564 1,069 664 948 18,284 17,001 13,689 19,018 Kisarawe 43 6 648 360 19,572 11,227 18,590 11,593 Mkuranga 161 110 954 317 31,948 19,810 34,744 20,238 Rufiji 248 122 1,295 1,237 32,311 25,663 30,685 27,022 Mafia 0 0 188 64 6,035 2,984 5,830 3,048 Total 3,177 2,964 4,958 3,969 158,488 128,690 139,444 135,622 Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Bagamoyo 939 861 3,990 5,409 747 561 30,228 53,931 35,905 60,763 Kibaha 1,104 1,099 462 362 279 203 11,844 17,620 13,689 19,284 Kisarawe 425 337 1,275 706 138 68 16,752 19,808 18,590 20,920 Mkuranga 2,085 1,732 2,483 1,324 1,152 565 29,024 33,945 34,744 37,566 Rufiji 303 96 328 131 76 31 29,978 35,775 30,685 36,033 Mafia 1,150 543 299 107 267 148 4,114 2,308 5,830 3,106 Total 6,007 4,669 8,837 8,040 2,659 1,575 121,940 163,388 139,444 177,672 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Bagamoyo 457 447 53,251 54,256 35,905 60,763 0.7 Kibaha 847 718 18,664 18,300 13,689 19,284 3.7 Kisarawe 319 234 19,944 11,358 18,590 20,920 1.1 Mkuranga 1,419 1,006 31,644 19,232 34,744 37,566 2.7 Rufiji 631 699 33,222 26,323 30,685 36,033 1.9 Mafia 142 60 6,082 2,989 5,830 3,106 1.9 Total 3,815 3,164 162,808 132,458 139,444 177,672 1.8 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet & Dry Season, 2002/03 Agriculture Year 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Wet & Dry Season, Pwani Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Pwani Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,587 1,534 34,318 59,229 35,905 60,763 2.5 Kibaha 1,433 1,028 12,256 18,256 13,689 19,284 5.3 Kisarawe 609 456 17,981 20,464 18,590 20,920 2.2 Mkuranga 1,477 1,177 33,267 36,389 34,744 37,566 3.1 Rufiji 946 1,067 29,739 34,966 30,685 36,033 3.0 Mafia 15 3 5,815 3,103 5,830 3,106 0.1 Total 6,067 5,265 133,376 172,407 139,444 177,672 3.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 650 769 35,256 53,934 35,905 60,763 1.3 Kibaha 184 185 13,505 18,833 13,689 19,284 1.0 Kisarawe 228 90 18,362 11,503 18,590 20,920 0.4 Mkuranga 820 706 33,924 19,532 34,744 37,566 1.9 Rufiji 1,635 898 29,050 26,125 30,685 36,033 2.5 Mafia 101 43 5,729 3,006 5,830 3,106 1.4 Total 3,617 2,691 135,826 132,931 139,444 177,672 1.5 % 2.6 1.5 97.4 74.8 100 100 % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,033 1,003 52,675 53,700 35,905 60,763 1.7 Kibaha 893 581 18,619 18,437 13,689 19,284 3.0 Kisarawe 422 233 19,841 11,360 18,590 20,920 1.1 Mkuranga 1,769 1,332 31,294 18,906 34,744 37,566 3.5 Rufiji 845 719 33,008 26,303 30,685 36,033 2.0 Mafia 59 16 6,165 3,032 5,830 3,106 0.5 Total 5,021 3,884 161,602 131,738 139,444 177,672 2.2 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 9,643 8,409 44,065 46,294 35,905 54,703 15.4 Kibaha 5,165 5,123 14,347 13,895 13,689 19,018 26.9 Kisarawe 5,016 2,694 15,247 8,899 18,590 11,593 23.2 Mkuranga 6,412 3,359 26,651 16,879 34,744 20,238 16.6 Rufiji 1,880 1,218 31,973 25,804 30,685 27,022 4.5 Mafia 772 422 5,451 2,627 5,830 3,048 13.8 Total 28,888 21,224 137,734 114,398 139,444 135,622 15.6 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Improved Seeds District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Pwani 159 Appendix II 160 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,335 1,186 778 879 30,572 35,938 32,684 44,062 Kibaha 340 696 399 617 8,281 8,326 9,019 9,905 Kisarawe 0 . 138 62 6,212 3,667 6,350 13,056 Mkuranga 82 33 557 193 8,703 5,607 9,342 23,162 Rufiji 0 . 250 432 9,830 8,403 10,080 17,846 Mafia 0 . 105 33 2,821 1,409 2,926 1,499 Total 1,756 1,915 2,226 2,216 66,418 63,350 70,400 109,531 % 2 2 3 2 94 58 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 560 624 2,403 4,105 451 417 29,270 32,856 32,684 44,062 Kibaha 559 670 265 204 106 42 8,090 8,723 9,019 9,905 Kisarawe 95 102 474 263 0 . 5,781 3,364 6,350 13,056 Mkuranga 385 425 834 439 158 98 7,965 4,872 9,342 23,162 Rufiji 0 . 72 52 0 . 10,008 8,782 10,080 17,846 Mafia 541 260 230 84 9 5 2,145 1,093 2,926 1,499 Total 2,141 2,081 4,277 5,147 724 562 63,258 59,691 70,400 109,531 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 276 382 32,408 37,620 32,684 44,062 0.87 Kibaha 527 368 8,492 9,272 9,019 9,905 3.71 Kisarawe 87 63 6,264 3,667 6,350 13,056 0.48 Mkuranga 229 288 9,113 5,545 9,342 23,162 1.25 Rufiji 238 406 9,842 8,428 10,080 17,846 2.28 Mafia 64 29 2,862 1,413 2,926 1,499 1.94 Total 1,420 1,536 68,981 65,945 70,400 109,531 1.40 % 2 1 98 60 100 100 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Pwani Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - LONG RAINY SEASON, Pwani Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of Planted Area Under Irrigation in Dry Season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during LONG RAINY SEASON, 2002/03 Agriculture Year, Pwani Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 819 913 31,865 37,089 32,684 44,062 2.07 Kibaha 786 600 8,233 9,040 9,019 9,905 6.06 Kisarawe 186 128 6,164 3,602 6,350 13,056 0.98 Mkuranga 224 253 9,118 5,581 9,342 23,162 1.09 Rufiji 230 288 9,849 8,546 10,080 17,846 1.62 Mafia 15 3 2,910 1,439 2,926 1,499 0.21 Total 2,261 2,185 68,140 65,296 70,400 109,531 2.00 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 365 609 32,319 37,393 32,684 44,062 1.38 Kibaha 116 104 8,904 9,536 9,019 9,905 1.05 Kisarawe 133 32 6,217 3,698 6,350 13,056 0.24 Mkuranga 85 69 9,257 5,765 9,342 23,162 0.30 Rufiji 602 361 9,478 8,474 10,080 17,846 2.02 Mafia 40 23 2,886 1,419 2,926 1,499 1.52 Total 1,339 1,197 69,061 66,284 70,400 109,531 1.09 % 1.9 1.1 98.1 60.5 100.0 100.0 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 163 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 733 763 31,951 37,240 32,684 44,062 1.73 Kibaha 496 370 8,524 9,269 9,019 9,905 3.74 Kisarawe 138 44 6,212 3,685 6,350 13,056 0.34 Mkuranga 393 302 8,949 5,532 9,342 23,162 1.30 Rufiji 75 31 10,004 8,804 10,080 17,846 0.17 Mafia 37 12 2,889 1,430 2,926 1,499 0.78 Total 1,872 1,522 68,528 65,960 70,400 109,531 1.39 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bagamoyo 5,765 6,238 26,919 31,764 32,684 38,002 16.42 Kibaha 2,483 2,393 6,537 7,246 9,019 9,640 24.83 Kisarawe 1,357 903 4,993 2,827 6,350 3,730 24.21 Mkuranga 1,720 1,063 7,621 4,771 9,342 5,833 18.22 Rufiji 559 339 9,520 8,496 10,080 8,835 3.84 Mafia 362 207 2,563 1,235 2,926 1,442 14.37 Total 12,246 11,144 58,155 56,338 70,400 67,481 16.51 % 17 17 83 83 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under irrigation in dry season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Pwani 164 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 38019 11561 304 32,300 11,430 354 70,319 22,991 327 Paddy 9937 2305 232 18,574 4,756 256 28,511 7,062 248 Sorghum 798 425 533 3,675 855 233 4,473 1,280 286 Bulrush Millet 41 2 50 0 0 0 41 2 0 Finger Millet 30 18 618 71 4 59 101 23 224 Wheat 0 0 0 0 0 0 0 0 0 Barley 114 0 0 0 0 0 114 0 0 CEREALS 48940 14312 54,620 17,046 103,560 31,358 Cassava 4970 4837 973 44,301 66,353 1498 49,270 71,190 1445 Sweet Potatoes 521 637 1223 1,275 771 605 1,796 1,408 784 Irish Potatoes 0 0 0 24 41 1688 24 41 1688 Yams 5 22 4199 62 0 0 67 22 323 Cocoyam 0 0 0 0 0 0 0 0 0 ROOTS & TUBERS 5496 5496 45,662 67,165 51,158 72,661 Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 0 Cowpeas 11056 1681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick Peas 10 2 247 0 0 0 10 2 0 Bambaranuts 15 1 89 0 0 0 15 1 0 Field Peas 0 0 0 0 0 0 0 0 0 PULSES 12039 1747 5,513 552 100 17,552 2,299 Sunflower 0 0 0 21 10 449 21 10 449 Simsim 166 18 109 2,386 312 131 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 368 113 2,552 335 131 2,920 448 Okra 98 35 353 28 73 2585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 0 0 0 Onions 22 15 697 2 4 1976 24 19 800 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 13 0 0 13 19 1506 26 19 729 Tomatoes 404 840 2077 491 1,104 2250 895 1,944 2172 Spinnach 24 2 93 6 4 726 30 6 218 Carrot 0 0 0 0 0 0 0 0 0 Chillies 6 1 222 0 0 0 6 1 0 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1328 264 225 853 Cucumber 57 45 794 29 39 1378 86 85 989 Egg Plant 0 0 0 12 37 3073 12 37 3073 Water Mellon 183 921 5027 114 203 1785 297 1,124 3787 Cauliflower 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 1046 2019 940 1,664 1,987 3,682 Seaweed 171 180 1055 183 188 1024 354 368 1039 Cotton 82 0 0 59 117 1976 141 117 832 Tobacco 0 0 0 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 CASH CROPS 252 180 243 305 495 485 Total 68,141 109,531 177,672 *The total area planted include the sum of the planted area for both Wet and Dry Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Wet Season to estimat 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Pwani Region Crop Dry season Wet Season Total Appendix II 165 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 1,951 51,346 516 404 112 0 54,329 Maize 1,416 990 37,900 30,593 119 333 350 213 182 49 0 . 39,967 32,177 Paddy 1,240 933 28,653 17,227 230 183 0 . 98 63 0 . 30,221 18,406 Sorghum 46 28 5,693 3,455 0 . 350 191 0 . 0 . 6,090 3,675 Bulrush Millet 0 . 0 . 0 . 0 . 0 . 0 . 0 . Finger Millet 0 . 84 71 0 . 0 . 0 . 0 . 84 71 Wheat 0 . 0 . 0 . 0 . 0 . 0 . 0 . Barley 0 . 0 . 0 . 0 . 0 . 0 . 0 . ROOTS & TUBERS 1,661 342 2,577 69 0 623 0 16,338 3,611 Cassava 254 122 3,193 1,527 0 . 0 . 685 602 0 . 4,132 2,251 Sweet Potatoes 369 203 2,411 980 122 69 0 . 114 21 0 . 3,016 1,274 Irish Potatoes 85 17 46 7 0 . 0 . 0 . 0 . 130 24 Yams 0 . 98 62 0 . 0 . 0 . 0 . 98 62 Cocoyam 0 . 0 . 0 . 0 . 0 . 0 . 0 . PULSES 2,655 201 5,052 40 0 198 0 5,491 Mung Beans 0 . 0 . 0 . 0 . 0 . 0 . 0 . Beans 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cowpeas 814 201 12,984 4,712 80 35 0 . 647 198 0 . 14,525 5,146 Green Gram 0 . 917 340 34 6 0 . 0 . 0 . 951 345 Pigeon Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chich Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bambaranuts 0 . 0 . 0 . 0 . 0 . 0 . 0 . Field Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . OIL SEEDS & OIL NUTS 0 2,531 0 21 0 0 2,552 Sunflower 0 . 96 21 0 . 0 . 0 . 0 . 96 21 Simsim 0 . 4,820 2,365 0 . 74 21 0 . 0 . 4,894 2,386 Groundnuts 0 . 508 140 0 . 0 . 0 . 0 . 508 140 Soya Beans 0 . 47 5 0 . 0 . 0 . 0 . 47 5 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 50 717 55 80 0 40 940 Okra 0 . 119 28 0 . 0 . 0 . 0 . 119 28 Radish 0 . 84 101 0 . 0 . 0 . 0 . 84 101 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 0 . 0 . 0 . 0 . 0 . 0 . Garlic 0 . 0 . 0 . 0 . 0 . 0 . 0 . Onions 0 . 47 2 0 . 0 . 0 . 0 . 47 2 Ginger 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cabbage 0 . 192 13 0 . 0 . 0 . 0 . 192 13 Tomatoes 82 50 1,273 347 34 55 0 . 0 . 98 40 1,486 491 Spinnach 0 . 145 6 0 . 0 . 0 . 0 . 145 6 Carrot 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chillies 0 . 0 . 0 . 0 . 0 . 0 . 0 . Amaranths 0 . 263 36 0 . 0 . 0 . 0 . 263 36 Pumpkins 0 . 436 109 0 . 0 . 0 . 0 . 436 109 Cucumber 0 . 65 29 0 . 0 . 0 . 0 . 65 29 Egg Plant 0 . 62 12 0 . 0 . 0 . 0 . 62 12 Water Mellon 0 . 186 34 0 . 60 80 0 . 0 . 246 114 Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 0 115 4 0 124 0 243 Seaweed 0 . 84 55 21 4 0 . 211 124 0 . 316 183 Cotton 0 . 195 59 0 . 0 . 0 . 0 . 195 59 Tobacco 0 . 0 . 0 . 0 . 0 . 0 . 0 . Pyrethrum 0 . 0 . 0 . 0 . 0 . 0 . 0 . Jute 0 . 0 . 0 . 0 . 0 . 0 . 0 . Total 2,545 62,338 684 505 1,056 40 67,168 % 4 93 1 1 2 0 100 Crop Table 7.2h: Planted Area and Number of Crop Growing Households During LONG RAINY SEASON by Method of Land Clearing and Crops; 2002/03 Agriculture Year Land Clearing Method Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Other Total Not Cleared Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 18,053 12,166 3,254 0.268 26,539 25,311 10,412 0.411 37,477 13,667 0.365 Kibaha 5,650 2,876 434 0.151 3,534 2,338 165 0.070 5,215 598 0.115 Kisarawe 12,570 4,722 1,751 0.371 4,438 1,750 309 0.176 6,472 2,059 0.318 Mkuranga 15,278 7,089 1,395 0.197 2,676 1,324 120 0.091 8,413 1,515 0.180 Rufiji 20,114 11,098 4,701 0.424 2,862 1,555 408 0.263 12,653 5,110 0.404 Mafia 253 68 26 0.380 143 21 16 0.744 90 42 0.466 Total 71,919 38,019 11,561 0.304 40,193 32,300 11,430 0.354 70,319 22,991 0.327 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 8,839 5,226 431 0.083 5,226 431 0.083 Kibaha 1,294 644 98 0.152 4,210 3,150 353 0.112 3,794 450 0.119 Kisarawe 1,717 747 485 0.649 1,858 960 138 0.144 1,707 623 0.365 Mkuranga 5,678 2,815 417 0.148 5,906 3,022 605 0.200 5,837 1,022 0.175 Rufiji 8,784 5,015 1,028 0.205 8,126 5,501 2,853 0.519 10,516 3,881 0.369 Mafia 1,664 716 278 0.389 1,603 715 376 0.526 1,431 654 0.457 Total 19,136 9,937 2,305 0.232 30,542 18,574 4,756 0.000 28,511 7,062 0.248 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 296 18 15 0.832 3,326 1,869 248 0.133 1,887 263 0.140 Kibaha 163 47 2 0.045 1,194 915 379 0.414 962 381 0.396 Kisarawe 460 103 25 0.241 354 159 0 0.001 263 25 0.095 Mkuranga 399 227 10 0.045 82 20 5 0.247 247 15 0.061 Rufiji 1,125 403 373 0.926 1,134 711 223 0.314 1,114 596 0.535 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 2,443 798 425 0.533 6,090 3,675 855 0.233 4,473 1,280 0.286 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 130 114 0 0.000 0 0 0 0.000 114 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 130 114 0 0.000 0 0 0 0.000 114 0 0.000 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Paddy District Short Rainy Season Long Rainy Season Total Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Sorghum District Short Rainy Season Long Rainy Season Total Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District;2002/03 Agricultural Year Barley District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year Maize District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 167 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 74 30 18 0.618 84 71 5 0.068 101 23 0.230 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 74 30 18 0.618 84 71 4 0.059 101 23 0.224 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 34 28 0 0.006 0 0 0 0.000 28 0 0.006 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 76 14 2 0.140 0 0 0 0.000 14 2 0.140 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 111 41 2 0.050 0 0 0 0.000 41 2 0.050 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 261 120 0 0.000 11,715 6,079 8,476 1.394 6,199 8,476 1.367 Kibaha 5,229 3,423 3,318 0.969 3,332 1,892 1,353 0.715 5,314 4,671 0.879 Kisarawe 142 48 14 0.296 14,779 9,362 22,400 2.393 9,411 22,414 2.382 Mkuranga 549 212 35 0.164 23,495 17,358 16,747 0.965 17,569 16,782 0.955 Rufiji 1,135 569 759 1.334 10,921 9,192 16,893 1.838 9,761 17,652 1.808 Mafia 1,672 597 711 1.190 1,219 418 484 1.158 1,015 1,195 1.177 Total 8,988 4,970 4,837 0.973 65,461 44,301 66,353 1.498 49,270 71,190 1.445 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 98 16 0 0.000 715 414 171 0.412 430 171 0.397 Kibaha 330 106 48 0.448 695 447 36 0.081 553 84 0.152 Kisarawe 323 102 206 2.021 313 31 42 1.377 133 248 1.872 Mkuranga 792 250 281 1.127 722 238 221 0.927 488 502 1.029 Rufiji 161 17 13 0.746 74 30 4 0.124 47 17 0.351 Mafia 132 30 89 2.967 516 115 297 2.585 145 386 2.664 Total 1,835 521 637 1.223 3,036 1,275 771 0.605 1,796 1,408 0.784 Long Rainy Season Total Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Short Rainy Season Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Short Rainy Season Long Rainy Season Total Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Short Rainy Season Long Rainy Season Total Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrush millet Harvested (tons) by Season and District;2002/03 Agricultural Year Bulrush millet District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 168 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 62 0 0.000 62 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 67 5 22 4.199 0 0 0 0.000 5 22 4.199 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 67 5 22 4.199 98 62 0 0.000 67 22 0.323 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 85 17 10 0.608 17 10 0.608 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 46 7 30 4.347 7 30 4.347 Total 0 0 0 0.000 130 24 41 1.688 24 41 1.688 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 11,834 3,846 483 0.126 7,311 2,776 267 0.096 6,622 750 0.113 Kibaha 5,785 1,884 201 0.107 2,256 664 25 0.037 2,548 226 0.089 Kisarawe 8,668 1,885 277 0.147 2,845 671 63 0.094 2,557 340 0.133 Mkuranga 10,467 2,713 434 0.160 1,815 866 41 0.048 3,580 475 0.133 Rufiji 2,675 727 287 0.394 325 177 129 0.728 904 416 0.460 Mafia 23 0 0 0.000 65 12 2 0.157 12 2 0.157 Total 39,454 11,056 1,681 0.152 14,618 5,167 527 0.102 16,223 2,208 0.136 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 1,051 432 12 0.027 647 277 11 0.040 708 23 0.032 Kibaha 449 118 3 0.028 115 30 4 0.127 149 7 0.048 Kisarawe 142 27 3 0.095 190 38 10 0.270 65 13 0.197 Mkuranga 1,764 343 41 0.121 0 0 0 0.000 343 41 0.121 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 3,406 920 59 0.064 951 345 25 0.073 1,265 84 0.067 Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Short Rainy Season Long Rainy Season Total Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Cow peas Harvested (tons) by Season and District;2002/03 Agricultural Year Cow peas District Short Rainy Season Long Rainy Season Total Table 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Yams District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 169 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 98 2 1 0.618 0 0 0 0.000 2 1 0.618 Kibaha 59 12 2 0.166 0 0 0 0.000 12 2 0.166 Kisarawe 47 4 0 0.000 0 0 0 0.000 4 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 204 18 3 0.171 0 0 0 0.000 18 3 0.171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 39 16 0 0.000 0 0 0 0.000 16 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 39 16 0 0.000 0 0 0 0.000 16 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 72 15 1 0.089 0 0 0 0.000 15 1 0.089 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 72 15 1 0.089 0 0 0 0.000 15 1 0.089 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 82 10 2 0.247 0 0 0 0.000 10 2 0.247 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 82 10 2 0.247 0 0 0 0.000 10 2 0.247 Long Rainy Season Total Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Short Rainy Season Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick Peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick Peas District Short Rainy Season Long Rainy Season Total Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Short Rainy Season Long Rainy Season Total Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung beans District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 170 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 27 6 0 0.000 0 0 0 0.000 6 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 27 6 0 0.000 0 0 0 0.000 6 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 3,824 1,824 265 0.145 1,824 265 0.145 Kibaha 0 0 0 0.000 243 81 1 0.010 81 1 0.010 Kisarawe 47 19 2 0.124 0 0 0 0.000 19 2 0.124 Mkuranga 316 86 6 0.066 0 0 0 0.000 86 6 0.066 Rufiji 211 61 10 0.164 828 482 46 0.097 543 57 0.104 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 574 166 18 0.109 4,894 2,386 312 0.131 2,552 330 0.129 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 102 16 20 1.267 100 10 3 0.247 26 23 0.873 Kibaha 210 43 31 0.721 0 0 0 0.000 43 31 0.721 Kisarawe 424 90 18 0.200 137 41 1 0.029 130 19 0.146 Mkuranga 312 54 26 0.483 169 68 7 0.101 122 33 0.269 Rufiji 0 0 0 0.000 80 16 0 0.000 16 0 0.000 Mafia 0 0 0 0.000 23 5 2 0.494 5 2 0.494 Total 1,048 202 95 0.470 508 140 13 0.092 342 108 0.316 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 96 21 10 0.449 21 10 0.449 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 96 21 10 0.449 21 10 0.449 Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Short Rainy Season Long Rainy Season Total Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Short Rainy Season Long Rainy Season Total Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Pigeon peas Harvested (tons) by Season and District;2002/03 Agricultural Year Pigeon peas District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 47 5 0 0.000 5 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 47 5 0 0.000 5 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 397 80 112 1.401 80 112 1.401 Kibaha 323 140 315 2.247 788 318 797 2.506 458 1,112 2.427 Kisarawe 238 54 151 2.790 47 10 90 9.426 64 242 3.785 Mkuranga 901 170 285 1.678 166 67 79 1.189 237 364 1.540 Rufiji 242 25 49 1.987 0 0 0 0.000 25 49 1.987 Mafia 110 15 39 2.562 87 16 25 1.533 31 64 2.028 Total 1,815 404 840 2.077 1,486 491 1,104 2.250 895 1,944 2.172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 20 112 5.659 20 112 5.659 Kibaha 65 4 0 0.000 41 4 4 0.988 8 4 0.482 Kisarawe 95 17 135 7.770 47 10 20 2.100 27 155 5.750 Mkuranga 634 162 787 4.868 60 80 120 1.497 242 906 3.752 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 794 183 921 5.027 246 114 203 1.785 297 1,124 3.787 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 91 4 0 0.000 87 5 0 0.000 9 0 0.000 Kibaha 219 19 14 0.699 101 11 8 0.774 30 22 0.725 Kisarawe 48 17 0 0.000 0 0 0 0.000 17 0 0.000 Mkuranga 565 94 25 0.262 164 85 12 0.140 179 37 0.205 Rufiji 83 20 42 2.058 83 8 125 14.820 29 167 5.812 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 1,007 155 80 0.517 436 109 145 1.328 264 225 0.853 Long Rainy Season Total Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya beans District Short Rainy Season Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Pumpkins District Short Rainy Season Long Rainy Season Total Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Water melon Harvested (tons) by Season and District;2002/03 Agricultural Year Water melon District Short Rainy Season Long Rainy Season Total Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 34 11 0 0.000 11 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 158 23 35 1.499 85 17 73 4.248 40 107 2.671 Rufiji 74 75 0 0.000 0 0 0 0.000 75 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 232 98 35 0.353 119 28 73 2.585 126 107 0.852 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 20 0 0.000 20 0 0.000 Kibaha 31 2 3 1.900 31 5 2 0.380 6 5 0.760 Kisarawe 0 0 0 0.000 95 7 20 3.035 7 20 3.035 Mkuranga 464 55 63 1.146 0 0 0 0.000 55 63 1.146 Rufiji 158 18 7 0.393 0 0 0 0.000 18 7 0.393 Mafia 77 9 6 0.667 40 5 13 2.717 14 19 1.372 Total 729 84 79 0.943 263 36 35 0.979 120 115 0.954 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 84 101 0 0.000 101 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 84 101 0 0.000 101 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 34 11 16 1.520 65 29 39 1.378 39 56 1.417 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 203 46 29 0.626 0 0 0 0.000 46 29 0.626 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 237 57 45 0.794 65 29 39 1.378 86 85 0.989 Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Okra District Short Rainy Season Long Rainy Season Total Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Short Rainy Season Long Rainy Season Total Table 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Short Rainy Season Long Rainy Season Total Table 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Cucumber District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 173 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 4 0 0.000 4 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 47 2 4 2.223 2 4 2.223 Mkuranga 76 9 0 0.043 0 0 0 0.000 9 0 0.043 Rufiji 74 15 2 0.124 0 0 0 0.000 15 2 0.124 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 150 24 2 0.093 145 6 4 0.726 30 6 0.218 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 4 0 0.000 4 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 47 13 0 0.000 95 9 19 2.195 22 19 0.860 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 47 13 0 0.000 192 13 19 1.506 26 19 0.729 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 316 171 180 1.055 316 183 188 1.024 354 368 1.039 Total 316 171 180 1.055 316 183 188 1.024 354 368 1.039 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 102 82 0 0.000 195 59 117 1.976 141 117 0.832 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 102 82 0 0.000 195 59 117 1.976 141 117 0.832 Table 7.2.29: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinnach District Short Rainy Season Long Rainy Season Total Table 7.2.30: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Cabbage District Short Rainy Season Long Rainy Season Total Table 7.2.31: Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year Seaweed District Short Rainy Season Long Rainy Season Total Table 7.2.32: Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Cotton District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 174 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 175 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Bagamoyo Pigeon Pea 206 173 65.07 316.1 Star Fruit 70 30 7.73 110.7 Coconut 3,155 2,772 4,659.34 1,476.7 Cashewnut 6,214 3,027 1,317.44 212.0 Wattle 0 0 0.00 0.0 Sugarcane 67 10 10.19 153.0 Jack Fruit 16 12 282.96 17,207.4 Banana 790 512 1,274.16 1,612.1 Avocado 0 32 34.12 0.0 Mango 1,261 577 12,710.48 10,080.9 Pawpaw 207 26 43.03 208.0 Pineapple 1,762 1,185 7,545.44 4,281.8 Orange 2,001 674 2,115.42 1,057.1 Mandarine/Tangerine 0 0 4.56 0.0 Guava 0 0 0.00 0.0 Lime/Lemon 60 60 48.56 805.6 Total 15,810 9,091 30,118.50 1,905.0 Kibaha Rubber Vine Fruit 0 0 0.00 0.0 Pigeon Pea 46 32 4.21 91.8 Palm Oil 0 1 4.13 0.0 Coconut 1,317 72 938.12 712.2 Cashewnut 2,062 819 1,199.08 581.6 Sugarcane 9 0 0.00 0.0 Mshelisheli 0 0 0.21 0.0 Jack Fruit 0 2 23.64 0.0 Mpesheni 0 0 0.74 16,666.7 Banana 64 27 262.32 4,084.4 Mango 14 44 240.67 17,501.9 Pawpaw 0 0 39.55 0.0 Pineapple 31 20 136.61 4,364.3 Orange 1,201 74 979.32 815.5 Grape Fruit 149 0 0.00 0.0 Mandarine/Tangerine 3 0 7.98 2,557.2 Guava 0 0 4.34 48,756.1 Lime/Lemon 0 0 6.63 0.0 Total 4,896 1,090 3,847.56 785.9 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 176 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Kisarawe Pigeon Pea 441 313 121.13 274.8 Star Fruit 21 18 688.26 32,559.1 Palm Oil 67 10 6.39 94.9 Coconut 1,575 1,284 2,358.02 1,497.1 Cashewnut 3,541 2,205 1,306.36 368.9 Jack Fruit 1,042 84 853.58 819.1 Mpesheni 4 4 0.00 0.0 Banana 1,100 901 3,133.89 2,849.4 Mango 302 277 1,132.63 3,752.1 Pawpaw 170 115 516.17 3,041.9 Pineapple 23 0 0.00 0.0 Orange 1,937 1,366 7,485.26 3,865.2 Mandarine/Tangerine 153 120 1,063.68 6,931.0 Lime/Lemon 13 8 8.10 619.6 Total 10,389 6,705 18,673.45 1,797.5 Mkuranga Pigeon Pea 613 533 99.85 162.8 Star Fruit 48 19 238.36 4,923.2 Palm Oil 20 20 42.92 2,175.9 Coconut 4,569 4,581 10,276.31 2,249.2 Cashewnut 19,636 17,137 6,339.61 322.9 Jack Fruit 71 46 126.75 1,777.7 Mpesheni 161 138 354.18 2,201.5 Banana 179 122 590.02 3,299.4 Mango 457 389 1,233.60 2,698.5 Pawpaw 59 59 137.41 2,325.1 Pineapple 906 599 823.92 909.0 Orange 1,162 824 1,240.73 1,067.3 Mandarine/Tangerine 1,190 149 116.34 97.8 Guava 4 4 3.62 950.0 Lime/Lemon 92 71 141.41 1,531.6 Total 29,168 24,692 21,765.03 746.2 Rufiji Pigeon Pea 207 79 19.50 94.1 Palm Oil 3 0 0.30 114.4 Coconut 1,906 1,223 2,130.23 1,117.9 Cashewnut 10,591 7,182 2,436.95 230.1 Jack Fruit 19 16 0.00 0.0 Banana 484 394 1,600.81 3,304.2 Avocado 19 9 5.85 308.8 Mango 160 0 279.10 1,739.1 Pawpaw 61 29 324.23 5,294.9 Pineapple 533 192 876.00 1,642.9 Orange 1,294 623 5,649.58 4,367.0 Mandarine/Tangerine 48 48 0.00 0.0 Guava 33 0 0.00 0.0 Lime/Lemon 20 3 23.58 1,188.1 Total 15,378 9,799 13,346.13 867.9 cont…. PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 177 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Mafia Star Fruit 2 2 2.63 1,315.0 Coconut 4,778 3,238 10,369.68 2,170.2 Cashewnut 220 159 111.38 507.1 Banana 920 313 727.72 790.6 Mango 50 38 334.41 6,675.3 Pineapple 372 98 36.61 98.3 Orange 40 9 1,337.11 33,037.7 Lime/Lemon 7 4 2.66 391.4 Total 6,390 3,861 12,922.20 2,022.2 Total Rubber Vine Fruit 0 0 0 0.0 Pigeon Pea 1,513 1,129 309.75 204.7 Star Fruit 141 69 936.98 6,627.8 Palm Oil 90 31 53.74 599.4 Coconut 17,300 13,171 30,731.70 1,776.4 Cashewnut 42,263 30,529 12,710.83 300.8 Wattle 0 0 0.00 0.0 Sugarcane 75 10 10.19 135.7 Mshelisheli 0 0 0.21 0.0 Jack Fruit 1,149 159 1,286.93 1,120.1 Mpesheni 165 142 354.92 2,153.5 Banana 3,538 2,268 7,588.92 2,144.8 Avocado 19 41 39.96 2,110.3 Mango 2,244 1,325 15,930.89 7,098.7 Pawpaw 497 230 1,060.39 2,134.0 Pineapple 3,628 2,094 9,418.57 2,595.8 Orange 7,635 3,571 18,807.42 2,463.2 Grape Fruit 149 0 0.00 0.0 Mandarine/Tangerine 1,395 317 1,192.55 855.0 Guava 36 4 7.96 218.7 Lime/Lemon 192 146 230.95 1,200.7 Total 82,031 55,237 100,672.88 1,227.3 cont…. PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 178 Crop Area Planted % Cashewnut 42,263 51.5 Coconut 17,300 21.1 Orange 7,635 9.3 Pineapple 3,628 4.4 Banana 3,538 4.3 Mango 2,244 2.7 Pigeon Pea 1,513 1.8 Mandarine/Tangerine 1,395 1.7 Jack Fruit 1,149 1.4 Pawpaw 497 0.6 Lime/Lemon 192 0.2 Mpesheni 165 0.2 Grape Fruit 149 0.2 Star Fruit 141 0.2 Palm Oil 90 0.1 Sugarcane 75 0.1 Guava 36 0.0 Avocado 19 0.0 Rubber Vine Fruit 0 0.0 Wattle 0 0.0 Mshelisheli 0 0.0 Total 82,031 100.0 District Area planted with cashewnuts(Ha) Total Area planted (ha) % of Total Area Planted hh with cashewnuts Average Planted Area per Household Bagamoyo 6,214 15,810 15 4,085 1.52 Kibaha 2,062 4,896 5 2,889 0.71 Kisarawe 3,541 10,389 8 6,254 0.57 Mkuranga 19,636 29,168 46 17,404 1.13 Rufiji 10,591 15,378 25 9,026 1.17 Mafia 220 6,390 1 542 0.41 Total 42,263 82,031 100 40,199 1.05 District Area planted with coconuts Total Area planted (ha) % of Total Area Planted hh with coconuts Average Planted Area per Household Bagamoyo 3,155 29,168 18 3,292 0.96 Kibaha 1,317 15,378 8 634 2.08 Kisarawe 1,575 15,810 9 5,302 0.30 Mkuranga 4,569 10,389 26 8,836 0.52 Rufiji 1,906 4,896 11 2,456 0.78 Mafia 4,778 6,390 28 3,572 1.34 Total 17,300 82,031 100 24,094 0.72 Coconuts 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Pwani Region Cashewnuts 7.3.3 PERMANENT CROPS: Area Planted with Cashewnuts by District 7.3.4 PERMANENT CROPS: Area planted with Coconuts by District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 179 District Area planted with oranges(Ha) Total Area planted (ha) % of Total Area Planted hh with oranges Average Planted Area per Household Bagamoyo 2,001 15,810 26 2,076 0.96 Kibaha 1,201 4,896 16 182 6.58 Kisarawe 1,937 10,389 25 6,226 0.31 Mkuranga 1,162 29,168 15 3,863 0.30 Rufiji 1,294 15,378 17 2,455 0.53 Mafia 40 6,390 1 203 0.20 Total 7,635 82,031 100 15,006 0.51 District Area planted with pineapples(Ha) Total Area planted (ha) % of Total Area Planted hh with pineapples Average Planted Area per Household Bagamoyo 1,762 15,810 49 1,486 1.19 Kibaha 31 4,896 1 79 0.39 Kisarawe 23 10,389 1 47 0.49 Mkuranga 906 29,168 25 2,213 0.41 Rufiji 533 15,378 15 1,485 0.36 Mafia 372 6,390 10 60 6.25 Total 3,628 82,031 100 5,370 0.68 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Rubber Vine Fruit . . . . . Pigeon Pea 8 . 59 1,426 1,493 Star Fruit . . . 141 141 Palm Oil . 26 . 63 90 Coconut 958 556 219 15,519 17,252 Cashewnut 1,122 3,834 1,011 35,069 41,036 Wattle . . . . . Sugarcane . . . 75 75 Mshelisheli . . . . . Jack Fruit . . . 1,145 1,145 Mpesheni . 53 . 112 165 Banana 279 120 . 3,138 3,538 Avocado . 19 . . 19 Mango 125 136 . 1,981 2,243 Pawpaw 207 . . 290 497 Pineapple 15 15 346 3,252 3,628 Orange 200 798 20 6,595 7,613 Grape Fruit . . . 149 149 Mandarine/Tangerine . . . 1,386 1,386 Guava . . . 36 36 Lime/Lemon 8 34 . 150 192 Total 2,922 5,592 1,655 70,531 80,699 7.3.7 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Fertilizer Use Crop 7.3.5 PERMANENT CROPS: Area planted with Oranges by District 7.3.6 PERMANENT CROPS: Area Planted with Pineapples by District Pineapples Oranges Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 180 Crop Mostly Farm Yard Manure Total % Sour Soup 0 0 0.0 Pigeon Pea 8 1,493 0.5 Star Fruit 0 141 0.0 Palm Oil 0 90 0.0 Coconut 958 17,252 5.6 Cashewnut 1,122 41,036 2.7 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 0 165 0.0 Avocado 279 3,538 7.9 Mango 0 19 0.0 Pawpaw 125 2,243 5.6 Pineapple 207 497 41.6 Orange 15 3,628 0.4 Grape 200 7,613 2.6 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 8 192 4.0 Total 2,922 80,699 3.6 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 0 0.0 Pigeon Pea 59 1,493 3.9 Star Fruit 0 141 0.0 Palm Oil 0 90 0.0 Coconut 219 17,252 1.3 Cashewnut 1,011 41,036 2.5 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 0 165 0.0 Avocado 0 3,538 0.0 Mango 0 19 0.0 Pawpaw 0 2,243 0.0 Pineapple 0 497 0.0 Orange 346 3,628 9.5 Grape 20 7,613 0.3 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 0 192 0.0 Total 1,655 80,699 2.1 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 181 Crop Mostly Compost Total % Sour Soup 0 0 0.0 Pigeon Pea 0 1,493 0.0 Star Fruit 0 141 0.0 Palm Oil 26 90 29.5 Coconut 556 17,252 3.2 Cashewnut 3,834 41,036 9.3 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 53 165 32.0 Avocado 120 3,538 3.4 Mango 19 19 100.0 Pawpaw 136 2,243 6.1 Pineapple 0 497 0.0 Orange 15 3,628 0.4 Grape 798 7,613 10.5 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 34 192 17.8 Total 5,592 80,699 6.9 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 182 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 183 Number % Number % Number % Bagamoyo 10,153 27 27,137 73 37,290 100 Kibaha 6,210 44 7,819 56 14,029 100 Kisarawe 14,332 77 4,305 23 18,637 100 Mkuranga 12,179 35 22,565 65 34,744 100 Rufiji 10,781 35 20,124 65 30,906 100 Mafia 2,049 35 3,876 65 5,924 100 Total 55,704 39 85,826 61 141,530 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader Other By Factory Total Bagamoyo 2,317 584 6,377 99 190 586 0 0 10,153 Kibaha 4,122 84 2,003 0 0 0 0 0 6,210 Kisarawe 11,654 90 2,208 0 0 0 380 0 14,332 Mkuranga 11,811 224 145 0 0 0 0 0 12,179 Rufiji 8,222 202 2,277 0 0 0 0 81 10,781 Mafia 2,049 0 0 0 0 0 0 0 2,049 Total 40,175 1,183 13,010 99 190 586 380 81 55,704 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader Other By Factory Total Maize 11,079 1,087 12,408 99 190 586 0 0 25,448 Paddy 8,020 162 917 0 0 0 0 81 9,180 Sorghum 1,513 0 481 0 0 42 0 0 2,036 Cassava 25,938 141 982 0 0 0 380 0 27,442 Sweet Potatoes 88 0 0 0 0 0 0 0 88 Cowpeas 681 0 0 0 0 0 0 82 763 Pigeon Peas 40 0 0 0 0 0 0 0 40 Simsim 42 0 0 0 0 0 0 0 42 Groundnut 109 0 0 0 0 0 0 0 109 Oil Palm 351 0 0 0 0 0 0 0 351 Coconut 5,893 0 85 0 0 0 0 0 5,978 Cashewnut 2,513 0 85 0 0 0 0 0 2,598 Banana 72 0 0 0 0 0 0 0 72 Mango 61 0 0 0 0 0 0 0 61 Orange 105 0 0 0 0 0 0 0 105 Total 56,506 1,390 14,957 99 190 629 380 163 74,313 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Pwani Region Method of Processing Method of Processing 8.1.1a: Number of Crop Growing Households Reported to Have Processed Crops by District; 2002/03 Agriculture Year District Households that Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 184 Household / Human Consumption Fuel for Cooking Sale Only Animal Consump tion Did Not Use Other Total Maize 25,064 100 0 0 200 85 25,448 Paddy 9,078 0 0 33 70 0 9,180 Sorghum 2,036 0 0 0 0 0 2,036 Cassava 27,300 0 0 35 107 0 27,442 Sweet Potatoes 88 0 0 0 0 0 88 Cowpeas 689 0 0 0 74 0 763 Pigeon Peas 40 0 0 0 0 0 40 Simsim 0 0 42 0 0 0 42 Groundnut 109 0 0 0 0 0 109 Oil Palm 192 0 159 0 0 0 351 Coconut 5,688 0 53 105 133 0 5,978 Cashewnut 2,462 0 136 0 0 0 2,598 Banana 72 0 0 0 0 0 72 Mango 61 0 0 0 0 0 61 Orange 105 0 0 0 0 0 105 Total 72,982 100 390 173 583 85 74,313 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 161 48 0 145 0 129 98 2,050 22,817 25,448 Paddy 108 0 85 38 0 0 24 1,719 7,206 9,180 Sorghum 0 0 0 0 0 0 0 85 1,951 2,036 Cassava 776 244 0 47 141 0 380 916 24,937 27,442 Sweet Potatoes 0 0 0 0 0 0 0 0 88 88 Cowpeas 40 0 0 0 0 0 0 75 648 763 Pigeon Peas 0 0 0 0 0 0 0 0 40 40 Simsim 0 0 0 0 0 0 42 0 0 42 Groundnut 0 0 0 0 0 0 0 0 109 109 Oil Palm 0 0 0 0 0 0 159 0 192 351 Coconut 565 85 0 0 0 0 0 0 5,328 5,978 Cashewnut 96 0 0 0 0 0 40 0 2,462 2,598 Banana 0 0 0 0 0 0 0 0 72 72 Mango 0 0 0 0 0 0 0 0 61 61 Orange 0 0 0 0 0 0 0 0 105 105 Total 1,747 377 85 231 141 129 742 4,846 66,014 74,313 Crop 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing Crops During 2002/03 Agricultural Year by Use of Product and Crop, Pwani Region Crop Product Use 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing Crops During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Pwani Region Where Sold Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 185 Flour / Meal Grain Oil Juice Pulp Other Total Bagamoyo 9,159 993 0 0 0 0 10,153 Kibaha 4,461 1,080 102 0 0 566 6,210 Kisarawe 11,788 1,282 189 0 39 1,034 14,332 Mkuranga 8,060 1,277 2,044 0 0 799 12,179 Rufiji 7,563 2,540 678 0 0 0 10,781 Mafia 24 1,061 445 20 0 499 2,049 Total 41,056 8,234 3,457 20 39 2,898 55,704 Household / Human Consumptio n Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Other Total Bagamoyo 11,663 100 0 0 0 0 11,763 Kibaha 7,882 0 117 35 34 0 8,069 Kisarawe 21,336 0 39 0 193 0 21,568 Mkuranga 15,275 0 159 0 85 0 15,518 Rufiji 14,374 0 53 105 250 85 14,867 Mafia 2,452 0 22 33 22 0 2,528 Total 72,982 100 390 173 583 85 74,313 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Bagamoyo 76 0 0 98 0 0 98 941 8,941 10,153 Kibaha 276 0 0 38 0 0 42 0 5,853 6,210 Kisarawe 180 48 0 47 44 47 0 0 13,966 14,332 Mkuranga 157 250 0 0 0 82 315 0 11,375 12,179 Rufiji 837 79 85 0 0 0 74 2,724 6,983 10,781 Mafia 45 0 0 0 0 0 0 0 2,004 2,049 Total 1,571 377 85 183 44 129 529 3,664 49,120 55,704 Bran Cake Husk Juice Pulp Shell No by- product Other Total Bagamoyo 7,021 100 298 87 0 0 2,647 0 10,153 Kibaha 2,344 66 154 0 74 1,135 2,437 0 6,210 Kisarawe 5,020 331 0 0 0 6,899 1,985 97 14,332 Mkuranga 2,754 2,006 522 0 169 1,139 5,178 411 12,179 Rufiji 7,127 525 1,443 0 1,390 211 0 85 10,781 Mafia 425 45 1,028 0 0 63 0 487 2,049 Total 24,692 3,072 3,445 87 1,633 9,446 12,247 1,081 55,704 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Pwani Region 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Pwani Region District Main Product Product Use District 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Pwani Region District District By Product 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Pwani Region Where Sold Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 186 MARKETING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 187 Number % Number % Bagamoyo 12,132 33 25,158 67 37,290 Kibaha 6,662 47 7,367 53 14,029 Kisarawe 11,381 61 7,257 39 18,637 Mkuranga 24,950 72 9,794 28 34,744 Rufiji 18,600 60 12,305 40 30,906 Temeke 4,732 80 1,192 20 5,924 Total 78,458 55 63,072 45 141,530 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bagamoyo 302 13,648 0 0 298 96 0 8,468 11,246 34,058 Kibaha 243 2,809 20 20 0 0 59 3,065 6,750 12,967 Kisarawe 47 4,768 0 0 0 184 0 3,075 10,426 18,500 Mkuranga 134 5,355 81 0 327 169 82 4,808 20,856 31,810 Rufiji 143 6,577 0 72 278 0 213 6,346 16,179 29,808 Mafia 45 1,223 23 15 0 48 0 121 4,320 5,796 Total 914 34,380 124 108 902 497 353 25,884 69,778 132,939 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bagamoyo 0.9 40.1 0.0 0.0 0.9 0.3 0.0 24.9 33.0 100 Kibaha 1.9 21.7 0.2 0.2 0.0 0.0 0.5 23.6 52.1 100 Kisarawe 0.3 25.8 0.0 0.0 0.0 1.0 0.0 16.6 56.4 100 Mkuranga 0.4 16.8 0.3 0.0 1.0 0.5 0.3 15.1 65.6 100 Rufiji 0.5 22.1 0.0 0.2 0.9 0.0 0.7 21.3 54.3 100 Mafia 0.8 21.1 0.4 0.3 0.0 0.8 0.0 2.1 74.5 100 Total 0.7 25.9 0.1 0.1 0.7 0.4 0.3 19.5 52.5 100 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Pwani Region Main Reasons for Not Selling Crops District District Main Reasons for Not Selling Crops 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Pwani Region 10.1: Number of Crop Growing Households Reported to have Sold Agricultural Produce by District During 2002/03; Pwani Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 188 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 189 Number of Household % Number of Household % Number of Household % Bagamoyo 988 2.7 36301 97.3 37290 100.0 Kibaha 1045 7.4 12984 92.6 14029 100.0 Kisarawe 324 1.7 18313 98.3 18637 100.0 Mkuranga 2436 7.0 32308 93.0 34744 100.0 Rufiji 395 1.3 30510 98.7 30906 100.0 Mafia 121 2.0 5803 98.0 5924 100.0 Total 5309 3.8 136220 96.2 141530 100.0 District Irrigatable Area (ha) Irrigated Land (ha) % of Irrigatable land used Bagamoyo 240 172 71.7 Kibaha 467 363 77.7 Kisarawe 193 93 48.4 Mkuranga 1974 1608 81.4 Rufiji 298 298 100.0 Mafia 32 29 91.6 Total 3204 2563 80.0 River Dam Well Borehole Canal Pipe water Total Bagamoyo 595 98 198 0 98 0 988 Kibaha 604 111 204 0 23 102 1045 Kisarawe 0 0 324 0 0 0 324 Mkuranga 242 164 1321 158 311 240 2436 Rufiji 395 0 0 0 0 0 395 Mafia 35 0 86 0 0 0 121 Total 1871 374 2132 158 432 342 5309 Gravity Hand Bucket Hand Pump Motor Pump Other Total Bagamoyo 98 693 98 99 0 988 Kibaha 41 858 85 0 61 1045 Kisarawe 0 324 0 0 0 324 Mkuranga 84 2113 80 160 0 2436 Rufiji 0 158 0 0 238 395 Mafia 15 106 0 0 0 121 Total 238 4251 262 259 299 5309 Method of Obtaining Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total District 11.4: IRRIGATION: Number of Agriculture Households by Method Used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON Irrigated Land by District during 2002/03 Agriculture Year 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by Districts During the 2002/03 Agricultural Year Source of Irrigation Water District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 190 Flood Sprinkler Water Hose Bucket / Watering Can Total Bagamoyo 295 98 0 596 988 Kibaha 41 0 104 900 1,045 Kisarawe 0 0 0 324 324 Mkuranga 324 0 0 2,112 2,436 Rufiji 238 0 0 158 395 Mafia 15 0 0 106 121 Total 913 98 104 4,195 5,309 Number % Number % Bagamoyo 276 1 37,014 99 37,290 Kibaha 141 1 13,888 99 14,029 Kisarawe 666 4 17,972 96 18,637 Mkuranga 738 2 34,006 98 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 115 2 5,809 98 5,924 Total 1,935 1 139,595 99 141,530 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Bagamoyo . 1,529 . . 498 . . . 2,027 Kibaha 141 3,274 . . 1,590 . . 164 5,168 Kisarawe . 332 473 . . 2,899 . . 3,703 Mkuranga . 2,077 . 244 5,616 490 . . 8,428 Mafia . 2,587 . . 46 2,820 . . 5,453 Total 141 9,799 473 244 7,749 6,209 . 164 24,779 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 A Year District Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility Type of Erosion Control District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 191 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 192 No of households % No of households % Bagamoyo 840 2 36,450 98 37,290 Kibaha 424 3 13,605 97 14,029 Kisarawe 229 1 18,408 99 18,637 Mkuranga 2,046 6 32,698 94 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 262 4 5,662 96 5,924 Total 3,801 3 137,728 97 141,530 No of households % No of households % Bagamoyo 1,651 4 35,741 96 37,391 Kibaha 1,097 8 12,963 92 14,060 Kisarawe 889 5 17,749 95 18,637 Mkuranga 3,511 10 31,157 90 34,668 Rufiji 551 2 30,437 98 30,988 Mafia 1,613 27 4,311 73 5,924 Total 9,311 7 132,358 93 141,669 No of households % No of households % Bagamoyo 2,255 6 35,035 94 37,290 Kibaha 714 5 13,315 95 14,029 Kisarawe 896 5 17,741 95 18,637 Mkuranga 4,820 14 29,999 86 34,820 Rufiji 2,153 7 28,753 93 30,906 Mafia 578 10 5,346 90 5,924 Total 11,417 8 130,189 92 141,605 Table 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 193 No of households % No of households % Bagamoyo 2,023 5 35,367 95 37,390 Kibaha 1,888 13 12,141 87 14,029 Kisarawe 833 4 17,804 96 18,637 Mkuranga 9,990 29 24,754 71 34,744 Rufiji 2,185 7 28,638 93 30,823 Mafia 100 2 5,825 98 5,924 Total 17,019 12 124,528 88 141,548 No of households % No of households % Bagamoyo 183 0 37,107 100 37,290 Kibaha 42 0 13,987 100 14,029 Kisarawe 0 0 18,637 100 18,637 Mkuranga 79 0 34,665 100 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 22 0 5,903 100 5,924 Total 326 0 141,204 100 141,530 No of households % No of households % Bagamoyo 6,085 16 31,205 84 37,290 Kibaha 3,415 24 10,614 76 14,029 Kisarawe 4,722 25 13,915 75 18,637 Mkuranga 5,230 15 29,514 85 34,744 Rufiji 1,207 4 29,698 96 30,906 Mafia 462 8 5,462 92 5,924 Total 21,121 15 120,409 85 141,530 Table 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 194 Neighbour Not applicable Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 840 2 0 0 0 0 36,450 98 37,290 100 Kibaha 34 0 391 3 0 0 0 0 13,605 97 14,029 100 Kisarawe 0 0 229 1 0 0 0 0 18,408 99 18,637 100 Mkuranga 0 0 1,887 5 0 0 159 0 32,698 94 34,744 100 Rufiji 0 0 0 0 0 0 0 0 30,906 100 30,906 100 Mafia 0 0 196 3 21 0 46 1 5,662 96 5,924 100 Total 34 0 3,542 3 21 0 205 0 137,728 97 141,530 100 Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 0 0 0 0 0 0 0 0 Kibaha 0 0 23 0 109 1 118 1 0 0 34 0 Kisarawe 0 0 0 0 44 0 0 0 0 0 139 1 Mkuranga 162 0 0 0 73 0 0 0 85 0 693 2 Rufiji 0 0 0 0 0 0 0 0 0 0 0 0 Mafia 23 0 24 0 24 0 0 0 0 0 21 0 Total 185 0 48 0 250 0 118 0 85 0 887 1 Number % Number % Number % Number % Number % Bagamoyo 645 2 1,005 3 0 0 35,741 96 37,391 100 Kibaha 328 2 445 3 41 0 12,963 92 14,060 100 Kisarawe 520 3 186 1 0 0 17,749 95 18,637 100 Mkuranga 837 2 1,601 5 60 0 31,157 90 34,668 100 Rufiji 238 1 313 1 0 0 30,437 98 30,988 100 Mafia 1,168 20 329 6 24 0 4,311 73 5,924 100 Total 3,736 3 3,879 3 125 0 132,358 93 141,669 100 Local Market / Trade Store Not applicable Total Development Project Crop Buyers Total Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Locally Produced by Household Locally Produced by Household Neighbour Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Other District Co-operative Local Farmers Group Large Scale Farm Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 195 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 0 0 0 0 0 0 2,255 6 0 0 0 0 35,035 94 37,290 100 Kibaha 0 0 0 0 0 0 0 0 0 0 653 5 61 0 0 0 13,315 95 14,029 100 Kisarawe 0 0 0 0 0 0 0 0 0 0 896 5 0 0 0 0 17,741 95 18,637 100 Mkuranga 162 0 81 0 0 0 0 0 0 0 4,498 13 0 0 80 0 29,999 86 34,820 100 Rufiji 1,628 5 197 1 256 1 0 0 0 0 0 0 72 0 0 0 28,753 93 30,906 100 Mafia 140 2 94 2 24 0 70 1 23 0 228 4 0 0 0 0 5,346 90 5,924 100 Total 1,929 1 372 0 279 0 70 0 23 0 8,531 6 133 0 80 0 130,189 92 141,605 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 695 2 0 0 1,229 3 0 0 0 0 0 0 99 0 0 0 35,367 95 37,390 100 Kibaha 198 1 39 0 1,526 11 42 0 0 0 0 0 42 0 42 0 12,141 87 14,029 100 Kisarawe 233 1 276 1 281 2 44 0 0 0 0 0 0 0 0 0 17,804 96 18,637 100 Mkuranga 327 1 3,579 10 5,306 15 0 0 214 1 80 0 399 1 85 0 24,754 71 34,744 100 Rufiji 0 0 842 3 942 3 171 1 159 1 0 0 71 0 0 0 28,638 93 30,823 100 Mafia 23 0 20 0 57 1 0 0 0 0 0 0 0 0 0 0 5,825 98 5,924 100 Total 1,476 1 4,755 3 9,340 7 257 0 374 0 80 0 612 0 127 0 124,528 88 141,548 100 Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 183 0 37,107 100 37,290 100 Kibaha 42 0 0 0 0 0 13,987 100 14,029 100 Kisarawe 0 0 0 0 0 0 18,637 100 18,637 100 Mkuranga 0 0 79 0 0 0 34,665 100 34,744 100 Rufiji 0 0 0 0 0 0 30,906 100 30,906 100 Mafia 0 0 0 0 22 0 5,903 100 5,924 100 Total 42 0 79 0 205 0 141,204 100 141,530 100 Neighbour Other Not applicable Neighbour Other Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Co-operative Local Farmers Group Local Market / Trade Store District Locally Produced by Household Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Development Project Large Scale Farm Development Project Crop Buyers Local Farmers Group Local Market / Trade Store Local Farmers Group Crop Buyers Total Total Not applicable Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store District Co-operative Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 196 Crop Buyers Number % Number % Number % Number % Number % Number Number % Bagamoyo 195 1 201 1 3,811 10 98 0 0 0 0 102 0 Kibaha 0 0 0 0 3,384 24 0 0 0 0 31 0 0 Kisarawe 0 0 90 0 2,513 13 0 0 1,054 6 0 0 0 Mkuranga 0 0 0 0 4,706 14 60 0 0 0 0 0 0 Rufiji 0 0 0 0 1,051 3 0 0 74 0 0 0 0 Mafia 0 0 0 0 167 3 0 0 0 0 274 0 0 Total 195 0 290 0 15,632 11 157 0 1,128 1 305 102 0 Number % Number % Number % Number % Number % Bagamoyo 0 0 1,489 4 189 1 31,205 84 37,290 100 Kibaha 0 0 0 0 0 0 10,614 76 14,029 100 Kisarawe 325 2 696 4 45 0 13,915 75 18,637 100 Mkuranga 224 1 240 1 0 0 29,514 85 34,744 100 Rufiji 83 0 0 0 0 0 29,698 96 30,906 100 Mafia 0 0 21 0 0 0 5,462 92 5,924 100 Total 632 0 2,446 2 234 0 120,409 85 141,530 100 Number % Number % Number % Number % Number % Bagamoyo 0 0 95 11 196 23 198 24 351 42 840 Kibaha 72 17 102 24 143 34 84 20 23 6 424 Kisarawe 0 0 0 0 0 0 0 0 229 100 229 Mkuranga 479 23 85 4 233 11 303 15 946 46 2,046 Mafia 53 20 0 0 42 16 77 29 91 35 262 Total 603 16 281 7 614 16 662 17 1,641 43 3,801 District Locally Produced by Household Neighbour Other Not applicable Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number cont…...12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Large Scale Farm Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 197 Number % Number % Number % Number % Number % Bagamoyo 1,161 70 490 30 0 0 0 0 0 0 1,651 Kibaha 709 65 256 23 102 9 31 3 0 0 1,097 Kisarawe 616 69 91 10 91 10 0 0 91 10 889 Mkuranga 1,852 53 1,051 30 233 7 296 8 80 2 3,511 Rufiji 467 85 0 0 0 0 84 15 0 0 551 Mafia 1,515 94 21 1 67 4 0 0 11 1 1,613 Total 6,319 68 1,908 20 492 5 411 4 181 2 9,311 Between 10 and 20 km 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 198 Number % Number % Number % Bagamoyo 2,255 100 0 0 0 0 2,255 Kibaha 678 95 36 5 0 0 714 Kisarawe 896 100 0 0 0 0 896 Mkuranga 4,738 98 0 0 83 2 4,820 Rufiji 2,153 100 0 0 0 0 2,153 Mafia 578 100 0 0 0 0 578 Total 11,298 99 36 0 83 1 11,417 Number % Number % Number % Number % Number % Bagamoyo 1,582 26 718 12 1,239 20 586 10 1,960 32 6,085 Kibaha 202 6 498 15 1,291 38 507 15 917 27 3,415 Kisarawe 982 21 599 13 289 6 522 11 2,330 49 4,722 Mkuranga 922 18 307 6 389 7 516 10 3,096 59 5,230 Rufiji 156 13 322 27 491 41 0 0 238 20 1,207 Mafia 190 41 15 3 0 0 40 9 217 47 462 Total 4,035 19 2,460 12 3,700 18 2,170 10 8,757 41 21,121 Less than 1 km Number % Number % Number % Number % Number % Bagamoyo 490 24 392 19 391 19 401 20 348 17 2,023 Kibaha 334 18 274 15 455 24 273 14 552 29 1,888 Kisarawe 229 27 184 22 96 11 0 0 324 39 833 Mkuranga 2,132 21 1,521 15 3,008 30 375 4 2,954 30 9,990 Rufiji 1,171 54 309 14 161 7 244 11 301 14 2,185 Mafia 0 0 0 0 20 20 43 43 37 37 100 Total 4,357 26 2,680 16 4,131 24 1,336 8 4,517 27 17,019 District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 10 and 20 km Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 199 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 8,063 22 17,986 49 890 2 76 0 1,680 5 6,325 17 100 0 1,328 4 36,450 100 Kibaha 663 5 9,351 69 126 1 0 0 265 2 2,493 18 0 0 706 5 13,605 100 Kisarawe 4,357 24 8,973 49 279 2 0 0 535 3 3,885 21 0 0 379 2 18,408 100 Mkuranga 2,987 9 21,458 66 662 2 81 0 2,311 7 4,763 15 79 0 358 1 32,698 100 Rufiji 12,176 39 12,939 42 1,030 3 71 0 1,680 5 2,604 8 85 0 321 1 30,906 100 Mafia 1,186 21 3,494 62 0 0 0 0 235 4 610 11 16 0 120 2 5,662 100 Total 29,432 21 74,200 54 2,987 2 229 0 6,706 5 20,681 15 281 0 3,212 2 137,728 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 14,109 39 2,980 8 7,683 21 1,684 5 2,258 6 5,781 16 199 1 1,046 3 35,741 100 Kibaha 4,781 37 1,578 12 3,568 28 385 3 422 3 1,912 15 0 0 318 2 12,963 100 Kisarawe 11,727 66 1,843 10 1,380 8 139 1 719 4 1,896 11 0 0 45 0 17,749 100 Mkuranga 17,585 56 5,718 18 1,338 4 970 3 2,935 9 2,247 7 79 0 285 1 31,157 100 Rufiji 17,909 59 757 2 5,293 17 295 1 3,000 10 3,013 10 85 0 85 0 30,437 100 Mafia 1,677 39 646 15 879 20 296 7 198 5 561 13 0 0 55 1 4,311 100 Total 67,788 51 13,521 10 20,141 15 3,768 3 9,531 7 15,410 12 364 0 1,834 1 132,358 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 3,037 9 3,692 11 9,608 27 893 3 11,976 34 4,538 13 522 1 769 2 35,035 100 Kibaha 2,327 17 2,145 16 3,589 27 982 7 1,603 12 1,888 14 170 1 611 5 13,315 100 Kisarawe 1,992 11 593 3 8,142 46 270 2 4,564 26 1,994 11 42 0 143 1 17,741 100 Mkuranga 3,138 10 4,255 14 5,513 18 537 2 13,538 45 2,252 8 79 0 686 2 29,999 100 Rufiji 9,454 33 771 3 5,447 19 1,277 4 8,537 30 3,096 11 85 0 85 0 28,753 100 Mafia 705 13 1,271 24 1,404 26 280 5 903 17 629 12 0 0 155 3 5,346 100 Total 20,653 16 12,728 10 33,702 26 4,239 3 41,121 32 14,399 11 898 1 2,449 2 130,189 100 Total Too Much Labour Required Too Much Labour Required Do not Know How to Use Locally Produced by Household Other Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Input is of No Use Locally Produced by Household Do not Know How to Use Input is of No Use 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Total Not Available Price Too High No Money to Buy Other Input is of No Use Locally Produced by Household 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 200 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 4,398 12 24,203 68 904 3 185 1 1,400 4 2,760 8 185 1 1,331 4 35,367 100 Kibaha 444 4 8,844 73 79 1 34 0 259 2 1,936 16 0 0 544 4 12,141 100 Kisarawe 2,196 12 13,516 76 187 1 0 0 1,256 7 510 3 0 0 140 1 17,804 100 Mkuranga 1,099 4 20,896 84 607 2 0 0 857 3 1,089 4 0 0 206 1 24,754 100 Rufiji 7,276 25 17,153 60 568 2 81 0 1,814 6 1,130 4 0 0 615 2 28,638 100 Mafia 521 9 3,580 61 142 2 22 0 650 11 776 13 0 0 134 2 5,825 100 Total 15,934 13 88,192 71 2,488 2 322 0 6,236 5 8,202 7 185 0 2,970 2 124,528 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 6,448 17 24,071 65 591 2 0 0 1,968 5 2,706 7 85 0 1,238 3 37,107 100 Kibaha 1,010 7 9,212 66 15 0 218 2 783 6 2,343 17 0 0 406 3 13,987 100 Kisarawe 2,109 11 13,350 72 233 1 0 0 2,616 14 233 1 0 0 95 1 18,637 100 Mkuranga 2,309 7 21,749 63 566 2 0 0 5,113 15 4,515 13 0 0 413 1 34,665 100 Rufiji 8,667 28 15,848 51 999 3 71 0 3,573 12 1,347 4 0 0 400 1 30,906 100 Mafia 398 7 3,707 63 95 2 22 0 716 12 846 14 0 0 118 2 5,903 100 Total 20,942 15 87,938 62 2,498 2 312 0 14,768 10 11,991 8 85 0 2,671 2 141,204 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 6,305 20 20,710 66 679 2 188 1 787 3 1,500 5 98 0 938 3 31,205 100 Kibaha 1,577 15 7,545 71 0 0 42 0 122 1 803 8 37 0 487 5 10,614 100 Kisarawe 4,114 30 9,076 65 48 0 0 0 225 2 362 3 46 0 45 0 13,915 100 Mkuranga 7,757 26 18,229 62 562 2 0 0 1,601 5 932 3 149 1 285 1 29,514 100 Rufiji 11,411 38 14,947 50 572 2 80 0 1,419 5 893 3 58 0 318 1 29,698 100 Mafia 2,101 38 2,748 50 96 2 46 1 141 3 212 4 0 0 118 2 5,462 100 Total 33,266 28 73,254 61 1,957 2 356 0 4,295 4 4,702 4 388 0 2,191 2 120,409 100 Too Much Labour Required Input is of No Use Price Too High Total Total Do not Know How to Use Locally Produced by Household Other Input is of No Use 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT Using Improved Seeds by District, 2002/03 Agricultural Year District Not Available No Money to Buy 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT Using Insecticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Input is of No Use Other Total Other 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Tanzania Agriculture Sample Census - 2003 Pwani 201 Number % Number % Number % Number % Number % Bagamoyo 565 67 174 21 0 0 100 12 840 100 Kibaha 31 7 353 83 41 10 0 0 424 100 Kisarawe 91 40 138 60 0 0 0 0 229 100 Mkuranga 605 30 1,278 62 163 8 0 0 2,046 100 Mafia 118 45 99 38 46 17 0 0 262 100 Total 1,410 37 2,041 54 250 7 100 3 3,801 100 Total 565 23 1,741 70 161 6 13 1 2,480 100 Number % Number % Number % Number % Number % Bagamoyo 690 42 803 49 158 10 0 0 1,651 100 Kibaha 255 23 698 64 103 9 41 4 1,097 100 Kisarawe 328 37 465 52 95 11 0 0 889 100 Mkuranga 929 26 2,254 64 328 9 0 0 3,511 100 Rufiji 84 15 467 85 0 0 0 0 551 100 Mafia 546 34 876 54 191 12 0 0 1,613 100 Total 2,831 30 5,564 60 875 9 41 0 9,311 100 Number % Number % Number % Number % Number % Number % Bagamoyo 1,266 56 646 29 179 8 82 4 82 4 2,255 100 Kibaha 0 0 450 63 264 37 0 0 0 0 714 100 Kisarawe 288 32 465 52 143 16 0 0 0 0 896 100 Mkuranga 974 20 1,510 31 2,252 47 85 2 0 0 4,820 100 Rufiji 1,073 50 1,008 47 72 3 0 0 0 0 2,153 100 Mafia 204 35 327 57 46 8 0 0 0 0 578 100 Total 3,806 33 4,406 39 2,957 26 166 1 82 1 11,417 100 Poor 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 District Excellent Good Average Does not Work Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Average Poor Total Total Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizers by District, 2002/03 Agricultural Year District Excellent Good Average Poor District Excellent Good Tanzania Agriculture Sample Census - 2003 Pwani 202 Number % Number % Number % Number % Number % Number % Bagamoyo 632 31 898 44 394 19 0 0 99 5 2,023 100 Kibaha 81 4 1,735 92 73 4 0 0 0 0 1,888 100 Kisarawe 376 45 267 32 142 17 48 6 0 0 833 100 Mkuranga 2,187 22 5,729 57 1,515 15 401 4 157 2 9,990 100 Rufiji 1,088 50 867 40 146 7 85 4 0 0 2,185 100 Mafia 60 60 20 20 20 20 0 0 0 0 100 100 Total 4,424 26 9,516 56 2,289 13 534 3 256 2 17,019 100 Number % Number % Number % Bagamoyo 0 0 183 100 183 100 Kibaha 0 0 42 100 42 100 Mkuranga 79 100 0 0 79 100 Mafia 22 100 0 0 22 100 Total 101 31 224 69 326 100 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 2,375 39 2,371 39 1,254 21 0 0 85 1 6,085 100 Bagamoyo 6,165 17 31,124 83 37,290 100 Kibaha 366 11 2,765 81 266 8 0 0 18 1 3,415 100 Kibaha 3,417 24 10,611 76 14,029 100 Kisarawe 1,350 29 2,990 63 383 8 0 0 0 0 4,722 100 Kisarawe 2,451 13 16,186 87 18,637 100 Mkuranga 1,883 36 3,008 58 339 6 0 0 0 0 5,230 100 Mkuranga 5,355 15 29,389 85 34,744 100 Rufiji 247 20 887 73 0 0 0 0 74 6 1,207 100 Rufiji 1,668 5 29,237 95 30,906 100 Mafia 316 68 102 22 23 5 21 5 0 0 462 100 Mafia 1,635 28 4,289 72 5,924 100 Total 6,536 31 12,123 57 2,265 11 21 0 176 1 21,121 100 Total 20,692 15 120,838 85 141,530 100 Total Does not Work Total Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Total District Excellent Good 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year District District Excellent Good Average Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 203 Number % Number % Number % Number % Bagamoyo 8,236 22 29,155 78 37,391 Bagamoyo 7,756 21 29,534 79 37,290 Kibaha 4,343 31 9,717 69 14,060 Kibaha 3,358 24 10,671 76 14,029 Kisarawe 2,260 12 16,377 88 18,637 Kisarawe 1,921 10 16,716 90 18,637 Mkuranga 9,499 27 25,169 73 34,668 Mkuranga 11,986 34 22,833 66 34,820 Rufiji 1,837 6 29,151 94 30,988 Rufiji 1,310 4 29,596 96 30,906 Mafia 2,416 41 3,509 59 5,924 Mafia 1,197 20 4,728 80 5,924 Total 28,591 20 113,078 80 141,669 Total 27,528 19 114,077 81 141,605 Number % Number % Number % Number % Bagamoyo 10,540 28 26,850 72 37,390 Bagamoyo 5,940 16 31,349 84 37,290 Kibaha 5,054 36 8,975 64 14,029 Kibaha 1,447 10 12,582 90 14,029 Kisarawe 3,649 20 14,988 80 18,637 Kisarawe 1,865 10 16,772 90 18,637 Mkuranga 16,392 47 18,352 53 34,744 Mkuranga 2,737 8 32,007 92 34,744 Rufiji 5,813 19 25,011 81 30,823 Rufiji 694 2 30,211 98 30,906 Mafia 900 15 5,024 85 5,924 Mafia 799 13 5,125 87 5,924 Total 42,349 30 99,199 70 141,548 Total 13,482 10 128,047 90 141,530 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Next Year Farm Yard Manure Agricultural Households With NO Plan to Use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use COMPOST ManureNext Year Agricultural Households With NO Plan to use Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With a Plan to Use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With a Plan to Use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Herbicides Next Year g Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 204 Number % Number % Bagamoyo 17,411 47 19,879 53 37,290 Kibaha 7,950 57 6,079 43 14,029 Kisarawe 7,657 41 10,980 59 18,637 Mkuranga 11,760 34 22,984 66 34,744 Rufiji 4,812 16 26,094 84 30,906 Mafia 1,844 31 4,080 69 5,924 Total 51,434 36 90,096 64 141,530 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Improved Seeds Next Year Agricultural Households With NO Plan to Use Improved Seeds Next Year Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 205 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 206 Number % Number % Bagamoyo 98 100 0 0 98 Mkuranga 1,339 89 160 11 1,499 Rufiji 83 100 0 0 83 Total 1,521 90 160 10 1,681 Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Bagamoyo 0 98 0 0 0 98 Mkuranga 80 0 1,094 162 163 1,499 Rufiji 0 0 0 0 83 83 Total 80 98 1,094 162 247 1,681 Total 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households Receiving Credit by Sex of Household Head and District During the 2002/03 Agriculture Year Total District Male Female Source of Credit Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 207 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Bagamoyo 1,139 8,064 3,848 764 14,888 1,474 0 102 6,913 37,192 Kibaha 704 4,575 1,485 475 4,261 318 413 84 1,715 14,029 Kisarawe 95 5,578 1,418 684 6,044 237 0 0 4,580 18,637 Mkuranga 1,643 3,058 3,090 1,097 17,279 1,367 85 0 5,625 33,245 Rufiji 626 7,233 1,625 147 15,323 592 75 154 5,046 30,822 Mafia 429 753 338 243 2,835 239 47 20 1,022 5,924 Total 4,635 29,261 11,805 3,410 60,631 4,227 620 361 24,900 139,849 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Bagamoyo 0 0 0 0 0 98 98 0 196 Mkuranga 478 400 554 1,424 400 400 400 400 4,455 Rufiji 0 0 0 0 0 0 0 83 83 Total Credits 478 400 554 1,424 400 498 498 483 4,734 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main Reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year District Credit Use Tanzania Agriculture Sample Census - 2003 Pwani 208 Appendix II 209 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 210 District Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Terminalia Ivorensis Leucena Spp Bagamoyo 1,292 13,666 . 613 . . . 24,471 . . . Kibaha 68,155 164 24,199 6,142 . 122,769 2,017 . . . 42 Kisarawe 2,461 237 280 1,184 9,520 95 . . . 947 1,895 Mkuranga 79 414 . 7,631 2,173 1,078 . . . . . Rufiji . . . . . . 1,260 34,697 . . 2,519 Mafia . . . . . 240 . . 240 . . Total 71,987 14,480 24,479 15,570 11,693 124,182 3,276 59,168 240 947 4,455 % 20.5 4.1 7.0 4.4 3.3 35.3 0.9 16.8 0.1 0.3 1.3 District Syszygium Spp Azadritacht a Spp Moringa Spp Saraca Spp Total Bagamoyo 91 565 . . 40,698 Kibaha 41 2,207 1,064 . 226,797 Kisarawe . 950 9,473 142 27,184 Mkuranga 79 2,724 . 335 14,512 Rufiji . 963 . . 39,439 Mafia . . 2,399 . 2,879 Total 211 7,409 12,936 477 351,509 % 0.1 2.1 3.7 0.1 100.0 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Specie and District During the 2002/03 Agriculture Year, Pwani Region cont. 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Specie and District During the 2002/03 Agriculture Year, Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 211 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Bagamoyo 656 40,698 0 . 0 . 656 40,698 Kibaha 71 64,006 231 130,526 20 32,265 322 226,797 Kisarawe 275 2,927 133 337 95 23,920 503 27,184 Mkuranga 714 4,309 466 10,056 0 . 1,181 14,365 Rufiji 310 10,700 0 . 151 28,739 461 39,439 Mafia 20 240 0 . 24 2,639 44 2,879 Total 2,045 122,881 831 140,919 290 87,563 3,166 351,362 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bagamoyo 8,931 1,148 9,152 1,595 144 0 20,971 Kibaha 3,685 425 845 945 0 504 6,403 Kisarawe 3,305 2,002 424 834 0 87 6,653 Mkuranga 0 0 0 77 0 0 77 Rufiji 106 0 106 318 0 0 530 Mafia 147 98 0 0 49 97 391 Total 16,214 3,785 10,527 3,870 193 735 35,324 14.3 ON FARM TREE PLANTING: Number of Responses by Main Use of Planted Trees and District for the 2002/03 agriculture year, Pwani Region District 14.2 TREE FARMING: Number of Households with Planted Trees on Their Land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Pwani Region Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Main Use Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 212 1-9 1-19 20-29 30-39 40-49 60+ Bagamoyo 89 182 0 0 0 0 Kibaha 0 0 15 0 0 0 Kisarawe 47 0 0 47 514 0 Mkuranga 394 208 85 0 0 299 Rufiji 420 0 0 0 0 0 Mafia 0 0 22 23 0 11 Total 949 390 121 70 514 309 % 40.3 16.6 5.1 3.0 21.8 13.1 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Bagamoyo 0 0 0 6 1 1 1 9 Kibaha 2 4 0 10 2 1 0 19 Kisarawe 2 5 0 7 0 2 1 17 Mkuranga 1 3 1 6 4 3 1 19 Rufiji 0 2 0 2 0 1 0 5 Mafia 1 0 0 0 1 0 1 3 Total 6 14 1 31 8 8 4 72 District 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Pwani Region District 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Pwani Region Distance to Community Planted Forest (km) Second Use Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 213 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 214 Number % Number % Bagamoyo 11,835 31.7 25,454 68.3 37,290 Kibaha 6,049 43.1 7,980 56.9 14,029 Kisarawe 11,435 61.4 7,202 38.6 18,637 Mkuranga 9,560 27.5 25,184 72.5 34,744 Rufiji 7,603 24.6 23,303 75.4 30,906 Mafia 245 4.1 5,680 95.9 5,924 Total 46,727 33.0 94,803 67.0 141,530 Number % Number % Number % Number % Number % Number % Bagamoyo 2,576 22.3 6,338 54.8 2,382 20.6 0 0.0 262 2.3 11,558 100.0 Kibaha 256 4.2 4,085 67.5 1,501 24.8 164 2.7 42 0.7 6,049 100.0 Kisarawe 617 5.4 9,354 82.2 1,415 12.4 0 0.0 0 0.0 11,386 100.0 Mkuranga 1,514 15.8 6,906 72.2 1,095 11.5 45 0.5 0 0.0 9,560 100.0 Rufiji 2,496 33.2 3,623 48.1 1,175 15.6 148 2.0 85 1.1 7,527 100.0 Mafia 15 6.3 192 78.5 37 15.2 0 0.0 0 0.0 245 100.0 Total 7,474 16.1 30,499 65.8 7,605 16.4 357 0.8 390 0.8 46,325 100.0 Number % Number % Number % Number % Number % Number % Number % Bagamoyo 11,256 95.9 0 0.0 197 1.7 286 2.4 0 0.0 0 0.0 11,739 100.0 Kibaha 5,711 95.0 42 0.7 0 0.0 220 3.7 42 0.7 0 0.0 6,015 100.0 Kisarawe 11,245 98.3 143 1.2 0 0.0 0 0.0 0 0.0 47 0.4 11,435 100.0 Mkuranga 8,730 94.5 0 0.0 160 1.7 249 2.7 98 1.1 0 0.0 9,237 100.0 Rufiji 7,541 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 7,541 100.0 Mafia 186 81.5 42 18.5 0 0.0 0 0.0 0 0.0 0 0.0 228 100.0 Total 44,669 96.7 227 0.5 357 0.8 755 1.6 140 0.3 47 0.1 46,195 100.0 Total 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Pwani Region Very Good Good Average Poor No Good Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Pwani Region Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 215 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 10,852 0 197 286 0 0 11,335 37,290 30.4 Kibaha 5,631 42 0 178 42 0 5,893 14,029 42.0 Kisarawe 11,061 143 0 0 0 47 11,250 18,637 60.4 Mkuranga 8,206 0 160 249 98 0 8,713 34,744 25.1 Rufiji 7,467 0 0 0 0 0 7,467 30,906 24.2 Mafia 154 22 0 0 0 0 176 5,924 3.0 Total 43,371 207 357 713 140 47 44,834 141,530 31.7 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 7,009 87 98 100 0 0 7,294 37,290 19.6 Kibaha 3,845 84 0 88 0 131 4,149 14,029 29.6 Kisarawe 4,601 183 0 0 0 48 4,832 18,637 25.9 Mkuranga 6,914 53 157 165 53 0 7,342 34,744 21.1 Rufiji 4,765 0 0 0 0 157 4,922 30,906 15.9 Mafia 49 20 0 0 0 42 111 5,924 1.9 Total 27,184 427 255 353 53 378 28,649 141,530 20.2 Government NGO / Developme nt Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 4,441 0 0 85 93 4,619 37,290 12.4 Kibaha 2,148 83 20 58 0 2,309 14,029 16.5 Kisarawe 2,012 474 0 0 95 2,582 18,637 13.9 Mkuranga 3,208 85 0 0 227 3,520 34,744 10.1 Rufiji 3,337 159 0 0 85 3,582 30,906 11.6 Mafia 9 22 0 0 20 51 5,924 0.9 Total 15,155 823 20 143 521 16,663 141,530 11.8 % of total number of households Spacing 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Use of Agrochemicals Total Number of Households District District Total Number of Households % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households District Erosion Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 216 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 6,098 0 98 0 0 146 6,342 37,290 17.0 Kibaha 3,398 76 0 130 0 62 3,666 14,029 26.1 Kisarawe 3,541 505 0 0 0 95 4,141 18,637 22.2 Mkuranga 5,929 85 160 147 0 81 6,401 34,744 18.4 Rufiji 4,128 0 0 0 0 85 4,214 30,906 13.6 Mafia 170 22 0 0 20 0 212 5,924 3.6 Total 23,265 688 258 276 20 469 24,976 141,530 17.6 Government NGO / Development Cooperative Large Scale Other Not applicable Total Bagamoyo 5,649 0 98 199 0 0 5,946 37,290 15.9 Kibaha 2,641 42 0 88 27 135 2,933 14,029 20.9 Kisarawe 2,512 131 47 0 0 231 2,922 18,637 15.7 Mkuranga 4,655 0 0 0 0 154 4,809 34,744 13.8 Rufiji 3,831 0 0 0 0 157 3,988 30,906 12.9 Mafia 69 0 0 0 0 20 89 5,924 1.5 Total 19,358 173 145 287 27 698 20,687 141,530 14.6 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 8,146 0 197 85 0 100 8,527 37,290 22.9 Kibaha 4,678 124 0 79 27 274 5,183 14,029 36.9 Kisarawe 7,216 994 0 89 0 225 8,525 18,637 45.7 Mkuranga 5,313 0 79 0 0 81 5,473 34,744 15.8 Rufiji 5,199 0 0 0 0 85 5,284 30,906 17.1 Mafia 75 0 0 0 20 41 135 5,924 2.3 Total 30,626 1,119 276 254 47 806 33,127 141,530 23.4 % of total number of households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Organic Fertilizer Use District District Use of Improved Seed Inorganic Fertilizer Use % of total number of households District Total Number of Households 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 217 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 5,490 0 0 85 0 227 5,803 37,290 15.9 Kibaha 2,124 40 0 0 0 192 2,356 14,029 20.9 Kisarawe 562 531 47 0 0 0 1,140 18,637 15.7 Mkuranga 608 0 0 0 0 81 689 34,744 13.8 Rufiji 3,521 0 0 0 72 146 3,739 30,906 12.9 Mafia 0 0 0 0 0 20 20 5,924 1.5 Total 12,306 571 47 85 72 666 13,747 141,530 14.6 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 3,061 99 98 98 282 3,638 37,290 9.8 Kibaha 2,346 110 0 80 58 2,594 14,029 18.5 Kisarawe 1,438 0 47 0 0 1,485 18,637 8.0 Mkuranga 4,298 0 0 0 0 4,298 34,744 12.4 Rufiji 3,044 72 0 0 0 3,116 30,906 10.1 Mafia 0 0 0 0 20 20 5,924 0.3 Total 14,187 281 145 178 360 15,151 141,530 10.7 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 6,670 0 0 0 82 345 7,096 37,290 19.0 Kibaha 2,841 60 0 35 0 112 3,048 14,029 21.7 Kisarawe 4,238 48 0 0 0 46 4,332 18,637 23.2 Mkuranga 3,640 0 79 0 0 73 3,793 34,744 10.9 Rufiji 5,002 0 0 0 0 0 5,002 30,906 16.2 Mafia 24 0 0 0 0 20 44 5,924 0.7 Total 22,413 108 79 35 82 596 23,314 141,530 16.5 % of total number of households 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Household s Total Number of Households Crop Storage District District District Mechanisation / LST Total Number of Households % of total number of households % of total number of households Irrigation Technology Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 218 Government NGO / Development Project Large Scale Farm Not applicable Total Bagamoyo 7,341 0 435 0 7,777 37,290 20.9 Kibaha 4,637 15 98 239 4,989 14,029 35.6 Kisarawe 8,292 48 0 92 8,432 18,637 45.2 Mkuranga 5,059 80 205 0 5,345 34,744 15.4 Rufiji 4,987 0 0 74 5,061 30,906 16.4 Mafia 45 0 0 20 65 5,924 1.1 Total 30,363 143 739 424 31,669 141,530 22.4 Government NGO / Development Project Other Not applicable Total Bagamoyo 2,829 100 85 274 3,288 37,290 8.8 Kibaha 1,703 27 0 0 1,730 14,029 12.3 Kisarawe 2,634 740 0 0 3,374 18,637 18.1 Mkuranga 3,688 0 85 238 4,011 34,744 11.5 Rufiji 3,367 0 0 0 3,367 30,906 10.9 Mafia 0 0 0 20 20 5,924 0.3 Total 14,221 867 170 532 15,789 141,530 11.2 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 1,624 82 0 0 0 1,706 37,290 4.6 Kibaha 2,186 200 20 35 0 2,441 14,029 17.4 Kisarawe 2,190 231 0 0 47 2,468 18,637 13.2 Mkuranga 3,644 1,220 160 0 73 5,097 34,744 14.7 Rufiji 2,656 0 0 0 0 2,656 30,906 8.6 Mafia 24 0 0 0 20 44 5,924 0.7 Total 12,324 1,733 180 35 141 14,412 141,530 10.2 District Agro-forestry District District Agro-progressing Total Number of Households % of total number of households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-forestry by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households % of total number of households Vermin Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 219 Government NGO / Development Project Not applicable Total Bagamoyo 223 96 93 412 37,290 1.1 Kibaha 252 47 23 322 14,029 2.3 Kisarawe 228 48 0 276 18,637 1.5 Mkuranga 147 132 79 357 34,744 1.0 Rufiji 2,511 62 0 2,573 30,906 8.3 Mafia 0 0 20 20 5,924 0.3 Total 3,361 385 215 3,960 141,530 2.8 Government NGO / Development Project Cooperative Not applicable Total Bagamoyo 223 96 0 93 412 37,290 1.1 Kibaha 142 62 0 0 204 14,029 1.5 Kisarawe 229 48 47 0 324 18,637 1.7 Mkuranga 302 0 0 0 302 34,744 0.9 Rufiji 2,131 0 0 0 2,131 30,906 6.9 Mafia 0 0 0 20 20 5,924 0.3 Total 3,027 206 47 113 3,392 141,530 2.4 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 11,335 10,883 96 6,942 2,534 37 4,106 1,742 42 Kibaha 5,818 5,007 86 4,056 1,363 34 2,078 593 29 Kisarawe 11,250 10,153 90 4,695 1,259 27 2,344 656 28 Mkuranga 8,713 7,937 91 7,342 5,004 68 3,212 965 30 Rufiji 7,386 6,223 84 4,628 1,039 22 3,135 290 9 Mafia 176 119 68 69 20 29 31 31 100 Total 44,677 40,322 90 27,732 11,219 40 14,906 4,278 29 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region District District Beekeeping Fish Farming 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region District Use of Agrochemicals Erosion Control Spacing 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households % of total number of households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 220 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 6,051 1,758 29 5,549 956 17 8,129 2,286 28 Kibaha 3,589 870 24 2,765 572 21 5,177 2,211 43 Kisarawe 3,950 1,199 30 2,459 234 10 8,521 4,423 52 Mkuranga 6,401 4,030 63 4,644 1,325 29 5,452 3,317 61 Rufiji 3,841 232 6 3,841 83 2 5,209 534 10 Mafia 208 184 89 69 28 40 95 25 26 Total 24,040 8,272 34 19,327 3,197 17 32,583 12,797 39 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 5,462 839 15 2,381 1,369 58 6,999 4,892 70 Kibaha 2,184 468 21 2,287 826 36 2,993 1,517 51 Kisarawe 806 0 0 1,357 329 24 4,337 2,519 58 Mkuranga 286 0 0 4,217 1,534 36 3,871 386 10 Rufiji 3,516 391 11 2,422 864 36 5,149 1,844 36 Mafia 0 0 0 0 0 0 24 24 100 Total 12,254 1,697 14 12,663 4,924 39 23,372 11,182 48 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 7,667 5,932 77 2,604 2,625 101 1,511 1,166 77 Kibaha 4,962 3,129 63 1,504 1,006 67 2,367 905 38 Kisarawe 8,432 7,966 94 3,334 2,799 84 2,372 902 38 Mkuranga 5,207 4,897 94 3,773 1,683 45 5,097 2,291 45 Rufiji 5,065 2,231 44 3,065 1,154 38 2,145 387 18 Mafia 45 45 100 0 0 0 0 0 0 Total 31,379 24,200 77 14,280 9,268 65 13,492 5,650 42 District District District Organic Fertilizer Use Vermin Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Pwani Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Pwani Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Pwani Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 221 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 177 372 0 177 270 0 0 95 0 Kibaha 200 124 62 102 0 0 1,094 1,090 100 Kisarawe 182 39 22 142 87 61 179 95 53 Mkuranga 279 53 19 147 0 0 208 132 64 Rufiji 2,501 62 2 2,059 218 11 927 80 9 Mafia 0 0 0 0 0 0 0 0 0 Total 3,338 650 19 2,627 575 22 2,408 1,492 62 Other Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Pwani Region District Beekeeping Tanzania Agriculture Sample Census - 2003 Pwani 222 Appendix II 223 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 224 Number % Number % Bagamoyo 0 0 37,290 100 37,290 Kibaha 0 0 14,029 100 14,029 Kisarawe 0 0 18,637 100 18,637 Mkuranga 0 0 34,744 100 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 46 1 5,878 99 5,924 Total 46 0 141,484 100 141,530 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Mafia 92 92 19 92 92 19 Total 92 92 19 92 92 19 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Mafia 92 92 45.9 92 92 45.9 Total 92 92 45.9 92 92 45.9 Number % Number % Number % Bagamoyo 3,524 22.2 33,234 26.7 36,758 26.2 Kibaha 1,040 6.5 12,834 10.3 13,874 9.9 Kisarawe 1,361 8.6 17,229 13.9 18,589 13.3 Mkuranga 5,847 36.8 28,816 23.2 34,663 24.7 Rufiji 2,352 14.8 28,142 22.6 30,494 21.7 Mafia 1,758 11.1 4,076 3.3 5,834 4.2 Total 15,882 100.0 124,331 100.0 140,213 100.0 Type of Craft 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 Agriculture Year, Pwani Region 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Agriculture Households Using Draft Animal to cultivate Land by District During 2002/03 Agriculture Year, Pwani Region Households Using Draft Animals Household Not Using Draft Animals Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft by Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 Agriculture Year, Pwani Region District Oxen Bulls 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer by District During 2002/03 Agriculture Year, Pwani Oxen District Total Type of Draft District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 225 Area (Ha) % Area (Ha) % Area (Ha) % Bagamoyo 1,389 29.1 2,982 34.9 4,371 32.8 Kibaha 923 19.4 204 2.4 1,127 8.5 Kisarawe 421 8.8 449 5.2 869 6.5 Mkuranga 1,098 23.0 4,621 54.0 5,719 42.9 Rufiji 183 3.8 171 2.0 355 2.7 Mafia 757 15.9 127 1.5 885 6.6 Total 4,772 100.0 8,553 100.0 13,326 100.0 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application by District during 2002/03 Agriculture Year, Pwani Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census - 2003 Pwani 226 Appendix II 227 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 228 Number % Number % Bagamoyo 2,132 5.7 35,158 94.3 37,290 5,864 Kibaha 621 4.4 13,408 95.6 14,029 1,053 Kisarawe 475 2.5 18,162 97.5 18,637 992 Mkuranga 144 0.4 34,600 99.6 34,744 493 Rufiji 612 2.0 30,294 98.0 30,906 1,909 Mafia 1,585 26.7 4,340 73.3 5,924 1,869 Total 5,568 3.9 135,961 96.1 141,530 12,180 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Bagamoyo 2,132 88,405 94 0 0 0 507 5,996 6 2,132 94,401 77 Kibaha 265 7,076 77 18 18 0 429 2,051 22 621 9,144 7 Kisarawe 428 2,331 73 0 0 0 95 859 27 475 3,190 3 Mkuranga 60 60 21 0 0 0 144 229 79 144 289 0 Rufiji 460 2,608 74 152 823 23 72 72 2 612 3,503 3 Mafia 1,520 9,880 84 161 299 3 340 1,602 14 1,585 11,781 10 Total 4,864 110,360 90 331 1,140 1 1,588 10,809 9 5,568 122,308 100 Number % Number % 1-5 2,224 40 6,161 5 3 6-10 907 16 7,176 6 8 11-15 472 8 6,040 5 13 16-20 544 10 9,692 8 18 21-30 228 4 5,625 5 25 31-40 252 5 8,762 7 35 41-50 249 4 11,277 9 45 51-60 102 2 5,315 4 52 61-100 349 6 25,177 21 72 101-150 99 2 12,587 10 127 151+ 102 2 23405 19 229 Total 5568 100 122308 100 22 18.1 CATTLE PRODUCTION: Total Number Households Rearing Cattle by District during 2002/03 Agriculture Year, Pwani Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture Households Total livestock Keeping Households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size ` Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 229 Number % Number % Number % Number % Bulls 9,617 80.0 526 4.4 1,882 15.7 12,025 9.8 Cows 30,337.0 91.9 284.8 0.9 2,394.6 7.3 33,016.4 27.0 Steers 7,691.4 98.8 24.2 0.3 65.6 0.8 7,781.3 6.4 Heifers 32,788.2 90.7 114.8 0.3 3,232.0 8.9 36,135.1 29.5 Male Calves 12,436.3 89.6 94.9 0.7 1,341.3 9.7 13,872.5 11.3 Female Calves 17,490 89.8 95 0.5 1,893 9.7 19,478 15.9 Total 110,360 90.2 1,140 0.9 10,809 8.8 122,308 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 7,760 21,731 6,579 28,753 9,419 14,165 88,405 Kibaha 468 2,306 779 1,406 809 1,309 7,076 Kisarawe 285 714 95 666 334 238 2,331 Mkuranga . 60 . . . . 60 Rufiji 429 1,173 . 177 428 401 2,608 Mafia 675 4,354 239 1,787 1,446 1,379 9,880 Total 9,617 30,337 7,691 32,788 12,436 17,490 110,360 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo . . . . . . . Kibaha 18 . . . . . 18 Kisarawe . . . . . . . Mkuranga . . . . . . . Rufiji 463 216 . . 72 72 823 Mafia 45 69 24 115 23 23 299 Total 526 285 24 115 95 95 1,140 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Category of Cattle 18.6 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 230 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 1,427 702 . 2,240 707 920 5,996 Kibaha 271 758 18 367 238 399 2,051 Kisarawe . 382 . 191 143 143 859 Mkuranga . 60 . 85 85 . 229 Rufiji . . . 72 . . 72 Mafia 185 492 48 277 169 431 1,602 Total 1,882 2,395 66 3,232 1,341 1,893 10,809 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 9,186 22,433 6,579 30,993 10,126 15,085 94,401 Kibaha 757 3,064 796 1,773 1,046 1,708 9,144 Kisarawe 285 1,096 95 857 477 380 3,190 Mkuranga . 120 . 85 85 . 289 Rufiji 892 1,389 . 249 500 473 3,503 Mafia 904 4,915 312 2,179 1,638 1,833 11,781 Total 12,025 33,016 7,781 36,135 13,873 19,478 122,308 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 231 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 232 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Bagamoyo 3,913 67,982 99.3 0 . 0.0 98 489 0.7 4,011 68,472 69.4 Kibaha 335 4,748 90.9 69 377 7.2 67 101 1.9 403 5,226 5.3 Kisarawe 748 4,847 100.0 0 . 0.0 0 . 0.0 748 4,847 4.9 Mkuranga 702 5,545 97.0 0 . 0.0 169 169 3.0 871 5,714 5.8 Rufiji 1,437 13,406 100.0 0 . 0.0 0 . 0.0 1,437 13,406 13.6 Mafia 130 810 86.2 0 . 0.0 22 130 13.8 152 940 1.0 Total 7,265 97,337 98.7 69 377 0.4 356 890 0.9 7,621 98,604 100.0 Number % Number % 1-4 2,491 33 6,113 6 2 5-9 1,879 25 12,668 13 7 10-14 1,484 19 17,335 18 12 15-19 746 10 13,481 14 18 20-24 155 2 3,407 3 22 30-39 187 2 5,984 6 32 40+ 678 9 39,616 40 58 Total 7,621 100 98,604 100 13 Total Goats District 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Goats Herd Size Goat Rearing Households Number of Goats Average Number Per Household Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 233 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 13,706 98.1 77 0.6 187 1.3 13,970 14.2 Castrated Goat 4,690 99.4 31 0.6 . 0.0 4,721 4.8 She Goat 50,501 98.9 192 0.4 379 0.7 51,072 51.8 Male Kid 13,762 98.6 77 0.6 120 0.9 13,958 14.2 She Kid 14,678 98.6 . 0.0 204 1.4 14,883 15.1 Total 97,337 98.7 377 0.4 890 0.9 98,604 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 9,416 3,301 34,270 9,952 11,044 67,982 Kibaha 509 371 2,401 732 735 4,748 Kisarawe 611 861 2,198 657 520 4,847 Mkuranga 982 . 3,075 617 871 5,545 Rufiji 2,091 158 8,046 1,703 1,409 13,406 Mafia 97 . 512 101 100 810 Total 13,706 4,690 50,501 13,762 14,678 97,337 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo . . . . . . Kibaha 77 31 192 77 . 377 Kisarawe . . . . . . Mkuranga . . . . . . Rufiji . . . . . . Mafia . . . . . . Total 77 31 192 77 . 377 Total Category of Goats 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Improved Dairy Goats 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 234 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 98 . 196 98 98 489 Kibaha 67 . 34 . . 101 Kisarawe . . . . . . Mkuranga . . 84 . 85 169 Rufiji . . . . . . Mafia 22 . 65 22 22 130 Total 187 . 379 120 204 890 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 9,514 3,301 34,465 10,050 11,142 68,472 Kibaha 653 401 2,627 809 735 5,226 Kisarawe 611 861 2,198 657 520 4,847 Mkuranga 982 . 3,159 617 955 5,714 Rufiji 2,091 158 8,046 1,703 1,409 13,406 Mafia 118 . 577 122 122 940 Total 13,970 4,721 51,072 13,958 14,883 98,604 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 235 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 236 Number % Number % Number % Ram 3,345 100 . 0 3,345 23 Castrated Sheep 1,361 100 . 0 1,361 8 She Sheep 11,322 100 . 0 11,322 51 Male Lamb 4,416 100 . 0 4,416 10 She Lamb 3,891 100 . 0 3,891 8 Total 24,334 100 . 0 24,334 100 Number % Number % Bagamoyo 1,087 3 36,202 97 37,290 5,864 Kibaha 77 1 13,952 99 14,029 1,053 Kisarawe 0 0 18,637 100 18,637 992 Mkuranga 53 0 34,691 100 34,744 493 Rufiji 286 1 30,620 99 30,906 1,909 Mafia 0 0 5,924 100 5,924 1,869 Total 1,503 1 140,027 99 141,530 12,180 Number % Number % Number % Bagamoyo 21,754 100 0 0 21,754 89 Kibaha 719 100 0 0 719 3 Mkuranga 369 100 0 0 369 2 Rufiji 1,492 100 0 0 1,492 6 Total 24,334 100 0 0 24,334 100 Herd Size Number of Households % Number of Sheep % Average Number Per Household 1-4 434 29 1,474 6 3 5-9 483 32 3,032 12 6 10-14 197 13 2,477 10 13 15-19 99 7 1,487 6 15 25-29 102 7 2,555 11 25 40+ 187 12 13,309 55 71 Total 1,503 100 24,334 100 16 20.1 Total Number of Sheep By Breed and on 1st October 2003 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households Breed Number of Indigenous sheep District 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 237 Number of Households Average sheep Number of Households Average sheep Number of Households Average sheep Bagamoyo 205 4 0 0 205 4 Kibaha Kisarawe Mkuranga Rufiji 0 0 0 0 0 0 Mafia 80 5 0 0 80 5 Total 284 5 0 3 284 5 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 266 17 448 97 58 886 Kibaha Kisarawe Mkuranga Rufiji . . . . . . Mafia 35 83 208 33 45 404 Total 300 100 656 130 103 1,290 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 0 0 0 0 0 0 Kibaha 0 0 0 0 0 0 Kisarawe 0 0 0 0 0 0 Mkuranga 0 0 0 0 0 0 Rufiji 0 0 0 0 0 0 Mafia 0 0 0 0 0 0 Total 0 0 0 0 0 0 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 2,523 1,361 9,833 4,257 3,779 21,754 Kibaha 74 . 459 74 112 719 Mkuranga 158 . 211 . . 369 Rufiji 590 . 818 84 . 1,492 Total 3,345 1,361 11,322 4,416 3,891 24,334 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Pwani Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Pwani 238 Appendix II 239 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 240 Number % Number % 1-4 121 34 317 9 3 5-9 185 52 1,367 37 7 40+ 47 13 1,989 54 42 Total 353 100 3,673 100 10 District Number of Households Number of Pigs Average Number Per Households Bagamoyo 98 294 3 Kibaha 76 392 5 Kisarawe 95 2,226 24 Mkuranga 85 761 9 Total 353 3,673 10 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Bagamoyo 294 . . . . 294 Kibaha 35 18 287 . 53 392 Kisarawe 142 332 474 568 710 2,226 Mkuranga 254 . 507 . . 761 Total 724 349 1,268 568 763 3,673 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 241 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 242 Number of Households % Number of Households % Bagamoyo 2,499 44 3,161 56 5,660 Kibaha 646 61 407 39 1,053 Kisarawe 285 30 660 70 945 Mkuranga 197 40 296 60 493 Rufiji 395 22 1,369 78 1,765 Mafia 635 39 978 61 1,613 Total 4,657 40 6,871 60 11,528 Number of Households % Number of Households % Number of Households % Number of Households % Bagamoyo 1,578 60 2,216 55 698 84 146 33 Kibaha 330 12 604 15 77 9 18 4 Kisarawe 237 9 285 7 0 0 95 21 Mkuranga 137 5 144 4 53 6 85 19 Rufiji 320 12 164 4 0 0 76 17 Mafia 40 2 619 15 0 0 24 5 Total 2,642 100 4,032 100 828 100 442 100 Number of Households % Number of Households % Bagamoyo 1,112 23 3,655 77 4,767 Kibaha 216 22 765 78 982 Kisarawe 422 43 570 57 992 Mkuranga 197 40 296 60 493 Rufiji 305 17 1,524 83 1,829 Mafia 1,061 62 649 38 1,709 Total 3,313 31 7,459 69 10,772 Spraying Dipping Number % age Number % age Number % age Number % age Number % age Number % age Bagamoyo 46 4 590 53 201 18 198 18 76 7 1,112 100 Kibaha 0 0 216 100 0 0 0 0 0 0 216 100 Kisarawe 0 0 333 79 0 0 0 0 90 21 422 100 Mkuranga 0 0 197 100 0 0 0 0 0 0 197 100 Rufiji 80 26 224 74 0 0 0 0 0 0 305 100 Mafia 184 17 560 53 70 7 15 1 232 22 1,061 100 Total 311 9 2,120 64 271 8 214 6 398 12 3,313 100 Other Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year District None Smearing Method of Tick Control District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tick Problems During 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that Dewormed Livestock by Type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing Households Deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 243 Number of Households % Number of Households % Bagamoyo 1,109 23 3,756 77 4,865 Kibaha 252 26 730 74 982 Kisarawe 375 38 618 62 992 Mkuranga 137 28 356 72 493 Rufiji 224 12 1,605 88 1,829 Mafia 311 19 1,325 81 1,636 Total 2,408 22 8,389 78 10,797 Number % age Number % age Number % age Bagamoyo 477 43 444 40 187 17 1,109 Kibaha 161 64 20 8 71 28 252 Kisarawe 90 24 285 76 0 0 375 Mkuranga 137 100 0 0 0 0 137 Rufiji 0 0 224 100 0 0 224 Mafia 204 65 108 35 0 0 311 Total 1,069 44 1,081 45 258 11 2,408 Total District None Dipping Spray Method of Tsetse Flies Control 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tsetse Flies Problems During 2002/03 Agriculture Year by District Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse Flies Control Use and District During the 2002/03 Agricultural Year District Tsetse Flies Problems No Tsetse Flies Problems Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 241 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 242 Number of Households % Number of Households % Bagamoyo 2,499 44 3,161 56 5,660 Kibaha 646 61 407 39 1,053 Kisarawe 285 30 660 70 945 Mkuranga 197 40 296 60 493 Rufiji 395 22 1,369 78 1,765 Mafia 635 39 978 61 1,613 Total 4,657 40 6,871 60 11,528 Number of Households % Number of Households % Number of Households % Number of Households % Bagamoyo 1,578 60 2,216 55 698 84 146 33 Kibaha 330 12 604 15 77 9 18 4 Kisarawe 237 9 285 7 0 0 95 21 Mkuranga 137 5 144 4 53 6 85 19 Rufiji 320 12 164 4 0 0 76 17 Mafia 40 2 619 15 0 0 24 5 Total 2,642 100 4,032 100 828 100 442 100 Number of Households % Number of Households % Bagamoyo 1,112 23 3,655 77 4,767 Kibaha 216 22 765 78 982 Kisarawe 422 43 570 57 992 Mkuranga 197 40 296 60 493 Rufiji 305 17 1,524 83 1,829 Mafia 1,061 62 649 38 1,709 Total 3,313 31 7,459 69 10,772 Spraying Dipping Number % age Number % age Number % age Number % age Number % age Number % age Bagamoyo 46 4 590 53 201 18 198 18 76 7 1,112 100 Kibaha 0 0 216 100 0 0 0 0 0 0 216 100 Kisarawe 0 0 333 79 0 0 0 0 90 21 422 100 Mkuranga 0 0 197 100 0 0 0 0 0 0 197 100 Rufiji 80 26 224 74 0 0 0 0 0 0 305 100 Mafia 184 17 560 53 70 7 15 1 232 22 1,061 100 Total 311 9 2,120 64 271 8 214 6 398 12 3,313 100 Other Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year District None Smearing Method of Tick Control District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tick Problems During 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that Dewormed Livestock by Type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing Households Deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 243 Number of Households % Number of Households % Bagamoyo 1,109 23 3,756 77 4,865 Kibaha 252 26 730 74 982 Kisarawe 375 38 618 62 992 Mkuranga 137 28 356 72 493 Rufiji 224 12 1,605 88 1,829 Mafia 311 19 1,325 81 1,636 Total 2,408 22 8,389 78 10,797 Number % age Number % age Number % age Bagamoyo 477 43 444 40 187 17 1,109 Kibaha 161 64 20 8 71 28 252 Kisarawe 90 24 285 76 0 0 375 Mkuranga 137 100 0 0 0 0 137 Rufiji 0 0 224 100 0 0 224 Mafia 204 65 108 35 0 0 311 Total 1,069 44 1,081 45 258 11 2,408 Total District None Dipping Spray Method of Tsetse Flies Control 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tsetse Flies Problems During 2002/03 Agriculture Year by District Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse Flies Control Use and District During the 2002/03 Agricultural Year District Tsetse Flies Problems No Tsetse Flies Problems Tanzania Agriculture Sample Census - 2003 Pwani 244 Appendix II 245 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 246 Number % Type Number Type Number Indigenous 1,254,145 88 Ducks 53,420 Donkeys 193 Layer 125,649 9 Turkeys 13,100 Horse 0 Broiler 40,358 3 Rabbits 11,371 Other 1,893 Total 1,420,152 100 Total 77,891 Total 2,086 Indigenous Chicken Layer Broiler Ducks Turkeys Rabbits Donkeys Other Bagamoyo 369,118 931 0 370,049 Bagamoyo 21,949 0 9,198 0 1,828 Kibaha 91,743 2,852 7,743 102,338 Kibaha 1,624 0 53 0 0 Kisarawe 172,662 42,523 30,935 246,120 Kisarawe 2,784 0 1,409 0 0 Mkuranga 322,132 0 0 322,132 Mkuranga 0 404 0 0 0 Rufiji 243,880 67,879 0 311,759 Rufiji 9,968 0 711 0 0 Mafia 54,610 11,464 1,679 67,754 Mafia 17,094 12,696 0 193 65 Total 1,254,145 125,649 40,358 1,420,152 Total 53,420 13,100 11,371 193 1,893 Type of Livestock/Poultry 1999 2003 Number % Cattle 101,594 122308 1 - 4 12,480 15.9 33,830 3 Improved cattle 1,450.0 11,948.0 5 - 9 17,795 22.6 120,208 7 Goats 65,659.0 98,604.0 10 - 19 25,092 31.9 321,845 13 Sheep 7,845.0 24,334.0 20 - 29 12,254 15.6 273,881 22 Pigs 3,581.0 3,673.0 30 - 39 5,868 7.5 184,373 31 Indigenous Chicken 808,574.0 1,254,145.0 40 - 49 2,196 2.8 92,214 42 Layers 6,306.0 125,649.0 50 - 99 2,673 3.4 178,300 67 Broilers 1,888.0 40,358.0 100+ 329 0.4 215,501 655 Total Chicken 816,765 1420152 Total 78,687 100 1,420,152 18 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e OTHER LIVESTOCK: Livestock/Poultry Population Trend Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household District 23c OTHER LIVESTOCK: Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 Type of Livestock Chicken Type Other Livestock 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 247 FISH FARMING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 248 Number % Number % Bagamoyo 0 0.0 37,290 100 37,290 Kibaha 0 0.0 14,029 100 14,029 Kisarawe 0 0.0 18,637 100 18,637 Mkuranga 0 0.0 34,744 100 34,744 Rufiji 0 0.0 30,906 100 30,906 Mafia 0 0.0 5,924 100 5,924 Total 0 0.0 141,530 100 141,530 Dug out Pond Total Bagamoyo 0 0 Kibaha 0 0 Kisarawe 0 0 Mkuranga 0 0 Rufiji 0 0 Mafia 0 0 Total 0 0 28.2 FISH FARMING: Number of Agricultural Households by System of Fish Farming and District during the 2002/03 Agricultural Year District Fish Farming System 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 249 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 250 Number % Number % Bagamoyo 2,656 7 34,633 93 37,290 5,864 45 Kibaha 1,397 10 12,632 90 14,029 1,053 133 Kisarawe 2,032 11 16,605 89 18,637 992 205 Mkuranga 2,868 8 31,876 92 34,744 493 582 Rufiji 973 3 29,932 97 30,906 1,909 51 Mafia 242 4 5,683 96 5,924 1,869 13 Total 10,168 7 131,362 93 141,530 12,180 83 Number % Number % Number % Number % Number % Number % Bagamoyo 2,284 35 1,209 18 1,163 18 1,163 18 759 12 6,578 100 Kibaha 1,343 47 745 26 519 18 137 5 137 5 2,882 100 Kisarawe 2,032 49 828 20 650 16 608 15 42 1 4,160 100 Mkuranga 2,699 67 145 4 1,200 30 0 0 0 0 4,043 100 Rufiji 741 56 218 16 218 16 74 6 74 6 1,325 100 Mafia 198 30 134 20 115 17 130 19 93 14 669 100 Total 9,296 47 3,279 17 3,864 20 2,113 11 1,105 6 19,657 100 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year Total Total Total Number of Households Raising Livestock Source of extension advice Large Scale Farmer Other % receiving advice out of total District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households by Source of Extension Services and District during the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 251 Government NGO / Development Project Large Scale Farmer Total Government NGO / Development Project Large Scale Farmer Total Bagamoyo 1,477 0 0 1,477 5,864 25.2 Bagamoyo 2,002 0 0 2,002 5,864 34.1 Kibaha 1,001 54 27 1,082 1,053 102.7 Kibaha 1,010 89 27 1,125 1,053 106.8 Kisarawe 952 0 0 952 992 95.9 Kisarawe 1,108 47 0 1,155 992 116.4 Mkuranga 2,088 0 0 2,088 493 423.5 Mkuranga 2,141 0 0 2,141 493 434.2 Rufiji 302 0 0 302 1,909 15.8 Rufiji 669 0 0 669 1,909 35.0 Mafia 91 0 0 91 1,869 4.8 Mafia 81 23 0 104 1,869 5.6 Total 5,911 54 27 5,992 12,180 49.2 Total 7,011 159 27 7,196 12,180 59.1 % 98.7 0.9 0.4 100.0 % 97.4 2.2 0.4 100.0 Government NGO / Development Project Co-operative Total Government NGO / Development Project Co-operative Total Bagamoyo 404 46 102 553 5,864 9.4 Bagamoyo 504 46 102 652 5,864 11.1 Kibaha 264 20 0 284 1,053 27.0 Kibaha 264 20 0 284 1,053 27.0 Kisarawe 235 47 0 283 992 28.5 Kisarawe 236 47 0 284 992 28.6 Mkuranga 305 0 0 305 493 61.8 Mkuranga 225 0 0 225 493 45.6 Rufiji 222 0 0 222 1,909 11.6 Rufiji 226 0 0 226 1,909 11.8 Mafia 22 23 0 45 1,869 2.4 Mafia 0 23 0 23 1,869 1.2 Total 1,452 137 102 1,691 12,180 13.9 Total 1,454 137 102 1,693 12,180 13.9 % 85.9 8.1 6.0 100.0 % 85.9 8.1 6.0 100.0 % receiving advice out of total District District Source of Advice on Milk Hygiene Total Number of households raising livestock % receiving advice out of total Total Number of households raising livestock Source of Advice on Proper Milking 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene by Source and District, 2002/03 Agricultural Year District 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking by Source and District, 2002/03 Agricultural Year Total Number of households raising livestock Source of Advice on Feeds and Proper Feeding Total Number of households raising livestock Source of Advice on Housing % receiving advice out of total 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding by Source and District, 2002/03 Agricultural Year District % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 252 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Bagamoyo 1,514 0 102 0 0 1,616 5,864 27.6 Kibaha 435 89 0 27 0 551 1,053 52.3 Kisarawe 689 47 0 0 47 784 992 79.0 Mkuranga 2,140 0 0 0 0 2,140 493 434.1 Rufiji 593 0 0 0 0 593 1,909 31.1 Mafia 103 0 0 39 0 142 1,869 7.6 Total 5,475 136 102 66 47 5,827 12,180 47.8 % 94.0 2.3 1.8 0.8 100.0 Government NGO / Development Project Co-operative Total Bagamoyo 604 0 102 706 5,864 12 Kibaha 495 0 0 495 1,053 47 Kisarawe 92 0 0 92 992 9 Mkuranga 80 0 0 80 493 16 Rufiji 74 0 0 74 1,909 4 Mafia 0 23 0 23 1,869 1 Total 1,345 23 102 1,470 12,180 12 % 91.5 1.6 7.0 100 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District District Source of Advice on Herd/Flock Size % receiving advice out of total Total Number of households raising livestock Total Number of households raising livestock % receiving advice out of total Source of Advice on Disease Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 253 Government NGO / Development Project Total Bagamoyo 595 0 595 5,864 10 Kibaha 146 35 181 1,053 17 Kisarawe 189 47 236 992 24 Mkuranga 145 0 145 493 29 Rufiji 154 0 154 1,909 8 Total 1,229 82 1,311 12,180 11 % 93.7 6.3 100 Government NGO / Development Project Co-operative Total Bagamoyo 505 0 102 607 5,864 10.4 Kibaha 488 35 0 522 1,053 49.6 Kisarawe 413 173 0 586 992 59.1 Mkuranga 1,641 0 0 1,641 493 332.9 Rufiji 362 0 0 362 1,909 19.0 Mafia 0 23 0 23 1,869 1.2 Total 3,409 231 102 3,742 12,180 30.7 % 91.1 6.2 2.7 100.0 Total Number of households raising livestock Source of Advice on Pasture Establishment and Selection 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year Source of Advice on Group Formation and Strengthening Total Number of households raising livestock % receiving advice out of total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District % receiving advice out of total District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 254 Government NGO / Development Project Co-operative Large Scale Farmer Total Bagamoyo 739 0 102 0 841 5,864 14.3 Kibaha 282 35 0 0 317 1,053 30.1 Kisarawe 237 47 0 0 284 992 28.6 Mkuranga 145 0 0 0 145 493 29.3 Rufiji 146 0 0 0 146 1,909 7.7 Mafia 27 0 0 15 43 1,869 2.3 Total 1,576 82 102 15 1,776 12,180 14.6 % 88.7 4.6 5.8 0.9 100.0 Government NGO / Development Project Large Scale Farmer Total Bagamoyo 1,022 0 0 1,022 5,864 17.4 Kibaha 295 35 0 330 1,053 31.3 Kisarawe 142 143 0 285 992 28.7 Mkuranga 60 85 0 145 493 29.3 Rufiji 218 0 0 218 1,909 11.4 Mafia 34 0 31 65 1,869 3.5 Total 1,771 263 31 2,065 12,180 16.9 % 85.8 12.7 1.5 100.0 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Total Number of households raising livestock 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock Source of Advice on Use of Improved Bulls District District Source of Advice on Calf Rearing Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 255 Number % Number % Number % Number % Number % Bagamoyo 1,686 55 753 25 100 3 0 0 517 17 3,055 Kibaha 85 3 1,922 76 448 18 82 3 0 0 2,536 Kisarawe 263 10 1,759 69 414 16 0 0 126 5 2,561 Mkuranga 120 3 3,552 91 132 3 0 0 85 2 3,888 Rufiji 662 41 879 54 0 0 0 0 72 4 1,613 Mafia 120 23 181 34 227 43 0 0 0 0 528 Total 2,935 21 9,044 64 1,320 9 82 1 799 6 14,180 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census - 2003 Pwani 256 Appendix II 257 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 258 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Bagamoyo 21.2 2.3 2.9 1.8 68.6 5.3 101.6 13.0 33.5 68.1 10.8 Kibaha 27.1 1.8 1.7 0.6 39.6 9.2 48.4 10.3 18.9 42.5 10.4 Kisarawe 17.4 1.9 4.5 0.6 43.7 6.9 97.3 17.4 26.2 61.2 51.6 Mkuranga 26.0 3.0 4.3 1.0 37.9 7.5 118.7 13.0 21.9 45.2 17.9 Rufiji 25.1 2.3 5.9 1.6 46.1 8.2 213.0 18.3 35.6 78.1 37.0 Mafia 30.1 2.6 8.4 2.2 26.6 2.7 238.6 82.9 90.3 143.6 200.5 Total 23.7 2.4 4.2 1.3 48.2 7.0 130.0 17.4 31.1 64.4 31.5 Regional Capital 130.0 Tertiary Market 64.4 Hospitals 48.2 Tarmac roads 31.5 Secondary Market 31.1 Secondary Schools 23.7 Primary Markets 17.4 Health Clinics 7.0 All weather roads 4.2 Primary Schools 2.4 Feeder roads 1.3 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 259 No of households % No of households % No of households % No of households % No of households % Bagamoyo 1159 3.1 1,745 4.7 8358 22.4 9793 26.3 16234 43.5 37290 21.2 Kibaha 321 2.3 1,344 9.6 5153 36.7 3649 26.0 3562 25.4 14029 27.1 Kisarawe 130 0.7 2,006 10.8 6593 35.4 3649 19.6 6259 33.6 18637 17.4 Mkuranga 339 1.0 1,038 3.0 7385 21.3 7611 21.9 18372 52.9 34744 26.0 Rufiji 265 0.9 1,538 5.0 3610 11.7 7236 23.4 18258 59.1 30906 25.1 Mafia 0 0.0 25 0.4 594 10.0 2075 35.0 3230 54.5 5924 30.1 Total 2214 1.6 7,695 5.4 31693 22.4 34013 24.0 65915 46.6 141530 23.7 No of households % No of households % No of households % No of households % No of households % Bagamoyo 21330 57.2 8,095 21.7 5677 15.2 541 1.4 1647 4.4 37290 2.9 Kibaha 8812 62.8 3,375 24.1 1665 11.9 57 0.4 119 0.9 14029 1.7 Kisarawe 7245 38.9 3,286 17.6 4989 26.8 2980 16.0 138 0.7 18637 4.5 Mkuranga 16469 47.4 7,652 22.0 6818 19.6 2565 7.4 1240 3.6 34744 4.3 Rufiji 16042 51.9 4,654 15.1 4865 15.7 2827 9.1 2519 8.1 30906 5.9 Mafia 1697 28.6 1,582 26.7 2074 35.0 200 3.4 372 6.3 5924 8.4 Total 71594 50.6 28,644 20.2 26088 18.4 9170 6.5 6035 4.3 141530 4.2 No of households % No of households % No of households % No of households % No of households % Bagamoyo 26,232 70.3 8,219 22.0 2182 5.9 170 0.5 488 1.3 37,290 1.8 Kibaha 10,768 76.8 2,705 19.3 445 3.2 111 0.8 0 0.0 14,029 0.6 Kisarawe 13,358 71.7 4,399 23.6 832 4.5 48 0.3 0 0.0 18,637 0.6 Mkuranga 21,419 61.6 10,224 29.4 3102 8.9 0 0.0 0 0.0 34,744 1.0 Rufiji 18,185 58.8 9,210 29.8 1871 6.1 828 2.7 811 2.6 30,906 1.6 Mafia 4,046 68.3 1,293 21.8 252 4.3 0 0.0 333 5.6 5,924 2.2 Total 94,006 66.4 36,050 25.5 8684 6.1 1157 0.8 1,632 1.2 141,530 1.3 Mean Distance Above 20 km 33.01b: Number of Households by Distance to Secondary School by District for 2002/03 Agriculture Year District Distance to Secondary School Total Number of Households Mean Distance Less than 1 km 1-2.9 km 10.0-19.9 3.0-9.9 Mean Distance Above 20 km 1-2.9 km Above 20 km 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 Agriculture Year District Distance to All Weather Road Total Number of Households Less than 1 km 1-2.9 km 3.0-9.9 3.0-9.9 10.0-19.9 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 Agriculture Year District Distance to Feeder Road Total Number of Households 10.0-19.9 Less than 1 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 260 No of households % No of households % No of households % No of households % No of households % Bagamoyo 102 0.3 102 0.3 1,354 3.6 5,016 13.5 30,716 82.4 37,290 68.6 Kibaha 100 0.7 577 4.1 1,737 12.4 3,532 25.2 8,083 57.6 14,029 39.6 Kisarawe 48 0.3 0 0.0 759 4.1 2,107 11.3 15,723 84.4 18,637 43.7 Mkuranga 82 0.2 623 1.8 2,543 7.3 5,405 15.6 26,090 75.1 34,744 37.9 Rufiji 336 1.1 642 2.1 2,379 7.7 2,829 9.2 24,719 80.0 30,906 46.1 Mafia 9 0.2 131 2.2 228 3.8 2,070 34.9 3,486 58.9 5,924 26.6 Total 677 0.5 2,075 1.5 9,000 6.4 20,960 14.8 108,817 76.9 141,530 48.2 No of households % No of households % No of households % No of households % No of households % Bagamoyo 5,636 15.1 12,438 33.4 12,734 34.1 5,748 15.4 734 2.0 37,290 5.3 Kibaha 1,813 12.9 3,654 26.0 5,550 39.6 1,792 12.8 1,220 8.7 14,029 9.2 Kisarawe 1,528 8.2 2,512 13.5 11,404 61.2 2,682 14.4 511 2.7 18,637 6.9 Mkuranga 1,878 5.4 3,673 10.6 18,802 54.1 9,156 26.4 1,235 3.6 34,744 7.5 Rufiji 7,281 23.6 6,916 22.4 8,309 26.9 3,022 9.8 5,377 17.4 30,906 8.2 Mafia 1,263 21.3 2,117 35.7 2,422 40.9 99 1.7 23 0.4 5,924 2.7 Total 19,399 13.7 31,310 22.1 59,221 41.8 22,500 15.9 9,100 6.4 141,530 7.0 No of households % No of households % No of households % No of households % No of households % Bagamoyo 10,008 26.8 16,101 43.2 10,000 26.8 1,092 2.9 89 0.2 37,290 2.3 Kibaha 2,777 19.8 7,834 55.8 3,376 24.1 42 0.3 0 0.0 14,029 1.8 Kisarawe 5,081 27.3 8,132 43.6 5,141 27.6 284 1.5 0 0.0 18,637 1.9 Mkuranga 7,256 20.9 13,482 38.8 12,076 34.8 1,851 5.3 79 0.2 34,744 3.0 Rufiji 12,927 41.8 8,678 28.1 7,213 23.3 1,928 6.2 159 0.5 30,906 2.3 Mafia 1,459 24.6 2,888 48.7 1,538 26.0 0 0.0 40 0.7 5,924 2.6 Total 39,508 27.9 57,115 40.4 39,342 27.8 5,197 3.7 367 0.3 141,530 2.4 Above 20 km Above 20 km 33.01e: Number of Households by Distance to Hospital by District for 2002/03 Agriculture Year District Distance to hospital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01g: Number of Households by distance to Primary School for 2002/03 Agriculture Year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 Agricultural Year District Health clinic Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 261 No of households % No of households % No of households % No of households % No of households % Bagamoyo 0 0.0 0 0.0 0 0.0 294 0.8 36,996 99.2 37,290 101.6 Kibaha 0 0.0 412 2.9 540 3.8 3,116 22.2 9,961 71.0 14,029 48.4 Kisarawe 0 0.0 0 0.0 0 0.0 759 4.1 17,878 95.9 18,637 97.3 Mkuranga 165 0.5 0 0.0 0 0.0 0 0.0 34,579 99.5 34,744 118.7 Rufiji 137 0.4 0 0.0 0 0.0 80 0.3 30,688 99.3 30,906 213.0 Mafia 0 0.0 0 0.0 0 0.0 0 0.0 5,924 100.0 5,924 238.6 Total 303 0.2 412 0.3 540 0.4 4,249 3.0 136,026 96.1 141,530 130.0 No of households % No of households % No of households % No of households % No of households % Bagamoyo 102 0.3 193 0.5 1,175 3.1 4,965 13.3 30,854 82.7 37,290 79.4 Kibaha 39 0.3 452 3.2 577 4.1 3,143 22.4 9,819 70.0 14,029 45.0 Kisarawe 0 0.0 0 0.0 711 3.8 777 4.2 17,150 92.0 18,637 51.1 Mkuranga 0 0.0 539 1.6 2,295 6.6 5,309 15.3 26,601 76.6 34,744 39.9 Rufiji 281 0.9 333 1.1 573 1.9 2,530 8.2 27,189 88.0 30,906 63.6 Mafia 18 0.3 57 1.0 235 4.0 2,070 34.9 3,543 59.8 5,924 27.9 Total 440 0.3 1,574 1.1 5,565 3.9 18,795 13.3 115,156 81.4 141,530 56.9 No of households % No of households % No of households % No of households % No of households % Bagamoyo 9,085 24.4 4,638 12.4 8,332 22.3 9,746 26.1 5,490 14.7 37,290 10.8 Kibaha 1,325 9.4 1,565 11.2 4,956 35.3 3,494 24.9 2,689 19.2 14,029 10.4 Kisarawe 95 0.5 0 0.0 1,711 9.2 1,733 9.3 15,098 81.0 18,637 51.6 Mkuranga 2,712 7.8 3,266 9.4 13,180 37.9 3,704 10.7 11,882 34.2 34,744 17.9 Rufiji 1,412 4.6 1,880 6.1 3,975 12.9 4,726 15.3 18,914 61.2 30,906 37.0 Mafia 0 0.0 22 0.4 0 0.0 0 0.0 5,902 99.6 5,924 200.5 Total 14,628 10.3 11,371 8.0 32,153 22.7 23,403 16.5 59,974 42.4 141,530 31.5 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 Agriculture Year District Distance to Regional Capital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 Agriculture Year District Distance to District Capital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 Agricultural Year District Tarmac Road Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 262 No of households % No of households % No of households % No of households % No of households % Bagamoyo 3,979 10.7 5,981 16.0 11,678 31.3 7,989 21.4 7,663 20.5 37,290 13.0 Kibaha 624 4.4 2,180 15.5 5,427 38.7 3,777 26.9 2,021 14.4 14,029 10.3 Kisarawe 1,034 5.5 2,611 14.0 5,535 29.7 3,990 21.4 5,467 29.3 18,637 17.4 Mkuranga 3,460 10.0 6,215 17.9 11,434 32.9 5,905 17.0 7,730 22.2 34,744 13.0 Rufiji 9,674 31.3 3,631 11.7 4,234 13.7 1,620 5.2 11,747 38.0 30,906 18.3 Mafia 1,803 30.4 490 8.3 680 11.5 409 6.9 2,543 42.9 5,924 82.9 Total 20,572 14.5 21,108 14.9 38,989 27.5 23,689 16.7 37,171 26.3 141,530 17.4 No of households % No of households % No of households % No of households % No of households % Bagamoyo 833 2.2 1,339 3.6 5,369 14.4 5,079 13.6 24,669 66.2 37,290 68.1 Kibaha 352 2.5 1,348 9.6 3,243 23.1 3,795 27.1 5,291 37.7 14,029 42.5 Kisarawe 42 0.2 0 0.0 1,041 5.6 1,828 9.8 15,726 84.4 18,637 61.2 Mkuranga 1,338 3.9 1,370 3.9 5,417 15.6 4,361 12.6 22,258 64.1 34,744 45.2 Rufiji 4,337 14.0 1,567 5.1 2,127 6.9 3,432 11.1 19,442 62.9 30,906 78.1 Mafia 340 5.7 135 2.3 55 0.9 845 14.3 4,549 76.8 5,924 143.6 Total 7,242 5.1 5,757 4.1 17,253 12.2 19,341 13.7 91,936 65.0 141,530 64.4 No of households % No of households % No of households % No of households % No of households % Bagamoyo 2,536 6.8 1,753 4.7 8,567 23.0 6,545 17.6 17,888 48.0 37,290 33.5 Kibaha 875 6.2 1,352 9.6 3,872 27.6 4,213 30.0 3,717 26.5 14,029 18.9 Kisarawe 323 1.7 787 4.2 3,969 21.3 5,267 28.3 8,292 44.5 18,637 26.2 Mkuranga 1,246 3.6 1,520 4.4 11,661 33.6 4,268 12.3 16,049 46.2 34,744 21.9 Rufiji 6,251 20.2 1,616 5.2 3,459 11.2 3,021 9.8 16,558 53.6 30,906 35.6 Mafia 984 16.6 358 6.0 311 5.3 1,145 19.3 3,126 52.8 5,924 90.3 Total 12,216 8.6 7,386 5.2 31,839 22.5 24,459 17.3 65,630 46.4 141,530 31.1 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 Agricultural Year District Primary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 Agricultural Year District Tertiary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 Agricultural Year District Secondary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 263 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 3,044 12.1 6,017 23.9 4,584 18.2 748 3.0 10,734 42.7 25,127 Kibaha 419 3.8 2,803 25.8 2,574 23.7 4,179 38.4 904 8.3 10,879 Kisarawe 371 15.9 1,114 47.9 428 18.4 271 11.7 142 6.1 2,327 Mkuranga 180 2.8 4,447 70.2 290 4.6 1,418 22.4 0 0.0 6,335 Rufiji 811 14.0 2,561 44.3 1,265 21.9 1,064 18.4 79 0.0 5,780 Mafia 154 2.7 1,006 17.5 1,848 32.2 2,290 39.8 449 7.8 5,746 Total 4,978 8.9 17,948 31.9 10,989 19.6 9,970 17.7 12,308 21.9 56,194 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 1,786 17.3 4,649 45.0 2,258 21.8 319 3.1 1,327 12.8 10,339 Kibaha 0 0.0 2,144 47.5 1,404 31.1 806 17.8 162 3.6 4,516 Kisarawe 235 16.9 785 56.3 285 20.4 90 6.5 0 0.0 1,396 Mkuranga 60 1.3 4,314 92.3 85 1.8 217 4.6 0 0.0 4,675 Rufiji 229 8.7 1,440 54.3 566 21.3 416 15.7 0 0.0 2,651 Mafia 68 3.8 639 35.2 495 27.2 569 31.3 46 2.5 1,816 Total 2,379 9.4 13,970 55.0 5,092 20.1 2,417 9.5 1,535 6.0 25,393 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 100 3.6 292 10.4 13 496 0 0.0 1,910 68.3 2,798 Kibaha 118 11.1 20 1.9 82 760 71.6 82 7.7 1,062 Kisarawe 45 19.1 47 20.1 0 0 0.0 142 60.8 234 Mkuranga 0 0.0 73 30.8 0 164 69.2 0 0.0 238 Rufiji 85 8.6 486 49.1 763 336 83 8.4 0 0.0 990 Mafia 0 0.0 22 5.9 122 48 229 62.3 69 18.7 368 Total 348 6.1 940 16.5 898 962 1,237 21.7 2,203 38.7 5,691 Satisfaction of Using Veterinary Clinic 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Total Number of Households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total Number of Households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total Number of Households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 264 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 455 15.9 0 0.0 577 20 76 2.7 1,747 61.2 2,855 Kibaha 107 8.8 56 4.6 298 24 674 55.3 82 6.7 1,218 Kisarawe 45 33.3 47 34.9 0 0 43 31.8 0 0.0 134 Mkuranga 0 0.0 0 0.0 0 0 349 100.0 0 0.0 349 Rufiji 0 0.0 374 56.0 83 12 132 19.8 79 11.8 668 Mafia 0 0.0 0 0.0 45 16 163 58.8 69 24.8 277 Total 607 3.5 477 7.1 1,003 30 1,437 49.0 1,976 10.0 5,500 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 301 10.4 198 6.8 396 14 95 3.3 1,910 65.8 2,901 Kibaha 81 4.1 178 9.1 468 24 790 40.5 435 22.3 1,951 Kisarawe 0 0.0 94 25.1 143 38 138 36.8 0 0.0 375 Mkuranga 0 0.0 60 13.4 126 28 262 58.5 0 0.0 448 Rufiji 295 40.9 128 17.8 219 30 79 10.9 0 0.0 721 Mafia 54 3.5 39 2.5 678 44 620 40.2 150 9.7 1,541 Total 731 9.2 697 8.8 2,031 26 1,984 25.0 2,496 31.4 7,938 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 200 6.3 499 15.8 460 15 162 5.1 1,828 58.1 3,149 Kibaha 112 12.2 84 9.1 101 11 577 63.1 41 4.5 915 Kisarawe 46 33.0 94 67.0 0 0 0 0.0 0 0.0 140 Mkuranga 60 19.7 0 0.0 79 26 164 54.2 0 0.0 303 Rufiji 202 58.4 0 0.0 62 18 83 23.8 0 0.0 347 Mafia 31 2.4 280 21.1 553 42 415 31.3 46 3.5 1,325 Total 651 10.5 956 15.5 1,255 20 1,400 22.7 1,915 31.0 6,178 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total Number of Households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total Number of Households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total Number of Households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 265 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 266 No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Bagamoyo 2,272 1,658 33,099 260 0 37,290 Kibaha 549 661 11,790 1,029 0 14,029 Kisarawe 610 230 17,152 646 0 18,637 Mkuranga 1,293 162 32,985 305 0 34,744 Rufiji 2,826 1,454 26,457 168 0 30,906 Mafia 1,383 70 4,394 55 23 5,924 Total 8,932 4,236 125,877 2,463 23 141,530 % 6.3 3.0 88.9 1.7 0.0 100.0 District Average Number of Rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Number of Households Bagamoyo 3 12,815 99 0 440 19,768 3,878 289 37,290 Kibaha 2 6,465 99 0 0 7,237 227 0 14,029 Kisarawe 3 4,874 44 0 0 12,050 1,670 0 18,637 Mkuranga 3 7,570 79 0 0 27,014 81 0 34,744 Rufiji 3 5,494 58 53 62 21,830 3,409 0 30,906 Mafia 3 531 0 0 22 5,371 0 0 5,924 Total 3 37,749 380 53 524 93,270 9,265 289 141,530 % 26.7 0.3 0.0 0.4 65.9 6.5 0.2 100 Number of Households % Number of Households % Number of Households % Number of Households % Radio 25,965 26 10,086 10 11,902 12 25,934 26 Bicycle 18,686 29 6,194 10 7,445 12 16,109 25 Iron 5,276 26 3,478 17 2,253 11 5,605 27 Wheelbarrow 1,033 24 436 10 286 7 1,214 28 Mobile phone 1,103 43 741 29 0 0 564 22 Television / Video 185 11 358 20 143 8 327 19 Vehicle 369 27 383 28 234 17 213 16 Landline phone 98 24 162 39 0 0 79 19 Total Number of Households 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Radio 20,164 20 4,743 5 98,795 69.8 Bicycle 12,928 20 2,282 4 63,644 45.0 Iron 3,135 15 809 4 20,556 14.5 Wheelbarrow 1,273 29 129 3 4,371 3.1 Mobile phone 134 5 0 0 2,542 1.8 Television / Video 673 38 68 4 1,754 1.2 Vehicle 155 11 0 0 1,354 1.0 Landline phone 76 18 0 0 415 0.3 Total Number of Households 30,906 22 5,924 4 141,530 100.0 Rufiji Mafia District 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Cont. 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Kisarawe Type of Owned Asset 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year 34.2 Number of Agriculture Households by type of Roofing Material and District, 2002/03 Agricultural Year District TOTAL Type of toilet Type of Owned Asset Bagamoyo District Mkuranga Kibaha Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 267 Number of Households % Number of Households % Number of Households % Number of Households % Wick Lamp 27,954 25 10,485 9 15,938 14 26,650 24 Hurricane Lamp 7,230 34 2,364 11 1,393 7 5,894 28 Pressure Lamp 958 23 494 12 417 10 1,309 31 Mains Electricity 946 38 591 24 95 4 165 7 Firewood 202 11 37 2 700 38 399 22 Candles 0 0 27 7 94 24 79 20 Solar 0 0 0 0 0 0 247 94 Other 0 0 31 100 0 0 0 0 Total 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Wick Lamp 26,201 24 3,830 3 111,057 78.5 Hurricane Lamp 2,603 12 1,719 8 21,204 15.0 Pressure Lamp 879 21 186 4 4,243 3.0 Mains Electricity 616 25 68 3 2,481 1.8 Firewood 449 24 70 4 1,856 1.3 Candles 158 40 36 9 395 0.3 Solar 0 0 16 6 263 0.2 Other 0 0 0 0 31 0.0 Total 30,906 22 5,924 4 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Firewood 34,782 26 12,507 9 18,193 14 33,234 25 Charcoal 2,054 32 1,522 24 353 6 1,149 18 Bottled Gas 96 32 0 0 47 16 162 53 Livestock Dung 204 100 0 0 0 0 0 0 Parraffin / Kerocine 76 39 0 0 44 22 60 30 Crop Residues 76 49 0 0 0 0 79 51 Gas (Biogas) 0 0 0 0 0 0 60 74 Solar 0 0 0 0 0 0 0 0 Total 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Firewood 29,723 22 5,693 4 134,132 94.8 Charcoal 1,102 17 193 3 6,374 4.5 Bottled Gas 0 0 0 0 305 0.2 Livestock Dung 0 0 0 0 204 0.1 Parraffin / Kerocine 0 0 17 9 197 0.1 Crop Residues 0 0 0 0 156 0.1 Gas (Biogas) 0 0 21 26 81 0.1 Solar 80 100 0 0 80 0.1 Total 30,906 22 5,924 4 141,530 100.0 Cont. 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Cooking Rufiji Mafia District TOTAL Mkuranga District 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Lighting Rufiji Mafia Main Source of Energy for Cooking Bagamoyo Kibaha Kisarawe Mkuranga 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year District District TOTAL Cont. 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year Main Source of Energy for Lighting Bagamoyo Kibaha Kisarawe Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 268 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Total wet season 9,488 4,021 752 302 1,559 272 16,394 dry season 10,579 4,866 1,663 457 1,539 248 19,353 wet season 2,275 790 2,198 3,517 1,860 1,232 11,872 Dry season 2,556 1,479 3,466 3,173 1,185 1,611 13,470 wet season 298 267 284 128 305 71 1,353 Dry season 196 94 415 76 160 110 1,051 wet season 10,600 3,944 13,209 27,762 19,300 2,868 77,684 Dry season 7,194 2,887 11,883 28,921 20,345 3,215 74,445 wet season 1,531 584 598 1,166 328 119 4,327 Dry season 1,158 550 648 1,405 256 119 4,137 wet season 7,958 3,433 378 759 4,685 363 17,575 Dry season 13,871 3,524 515 507 4,893 23 23,334 wet season 0 0 0 351 0 26 377 Dry season 82 0 47 79 80 16 304 wet season 4,001 990 1,128 759 2,869 930 10,677 Dry season 102 205 0 82 2,445 514 3,348 wet season 89 0 90 0 0 0 179 Dry season 832 71 0 45 0 21 969 wet season 0 0 0 0 0 0 0 Dry season 195 0 0 0 0 5 200 wet season 1,050 0 0 0 0 42 1,092 Dry season 525 352 0 0 0 42 919 37,290 14,029 18,637 34,744 30,906 5,924 141,530 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Total wet season 25.4 28.7 4.0 0.9 5.0 4.6 11.6 dry season 28.4 34.7 8.9 1.3 5.0 4.2 13.7 wet season 6.1 5.6 11.8 10.1 6.0 20.8 8.4 Dry season 6.9 10.5 18.6 9.1 3.8 27.2 9.5 wet season 0.8 1.9 1.5 0.4 1.0 1.2 1.0 Dry season 0.5 0.7 2.2 0.2 0.5 1.9 0.7 wet season 28.4 28.1 70.9 79.9 62.4 48.4 54.9 Dry season 19.3 20.6 63.8 83.2 65.8 54.3 52.6 wet season 4.1 4.2 3.2 3.4 1.1 2.0 3.1 Dry season 3.1 3.9 3.5 4.0 0.8 2.0 2.9 wet season 21.3 24.5 2.0 2.2 15.2 6.1 12.4 Dry season 37.2 25.1 2.8 1.5 15.8 0.4 16.5 wet season 0.0 0.0 0.0 1.0 0.0 0.4 0.3 Dry season 0.2 0.0 0.3 0.2 0.3 0.3 0.2 wet season 10.7 7.1 6.1 2.2 9.3 15.7 7.5 Dry season 0.3 1.5 0.0 0.2 7.9 8.7 2.4 wet season 0.2 0.0 0.5 0.0 0.0 0.0 0.1 Dry season 2.2 0.5 0.0 0.1 0.0 0.4 0.7 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry season 0.5 0.0 0.0 0.0 0.0 0.1 0.1 wet season 2.8 0.0 0.0 0.0 0.0 0.7 0.8 Dry season 1.4 2.5 0.0 0.0 0.0 0.7 0.6 g District Source Season District Source Season Surface Water (Lake / Dam / River / Stream) District Other Piped Water Protected Well Protected / Covered Spring Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Other 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Tanker Truck Tanker Truck Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 269 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia wet season 3,495 712 427 489 3,112 523 Dry season 2,673 631 236 81 2,343 360 wet season 8,680 4,944 4,302 12,000 7,296 2,440 Dry season 5,229 2,484 3,063 6,677 4,750 1,758 wet season 3,964 1,648 898 4,120 3,711 667 Dry season 2,489 1,003 642 3,101 3,213 799 wet season 9,236 2,845 4,792 9,095 7,177 1,051 Dry season 5,690 1,791 2,322 8,603 5,680 1,279 wet season 1,920 930 1,447 1,022 758 149 Dry season 1,342 474 682 1,471 1,084 212 wet season 5,330 1,003 1,357 3,092 1,402 452 Dry season 3,616 828 491 1,944 1,087 325 wet season 4,664 1,948 5,415 4,926 7,449 643 Dry season 16,251 6,817 11,201 12,867 12,749 1,191 37,290 14,029 18,637 34,744 30,906 5,924 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia wet season 9 5 2 1 10 9 Dry season 7 4 1 0 8 6 wet season 23 35 23 35 24 41 Dry season 14 18 16 19 15 30 wet season 11 12 5 12 12 11 Dry season 7 7 3 9 10 13 wet season 25 20 26 26 23 18 Dry season 15 13 12 25 18 22 wet season 5 7 8 3 2 3 Dry season 4 3 4 4 4 4 wet season 14 7 7 9 5 8 Dry season 10 6 3 6 4 5 wet season 13 14 29 14 24 11 Dry season 44 49 60 37 41 20 Total Agricultural Households per District above one Hour 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes District 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 Agriculture Year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season above one Hour 40 - 49 Minutes 50 - 59 Minutes District 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 Agriculture Year 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 270 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 496 6.5 1,004 13.1 1,627 21.3 2,185 28.5 2,017 26.4 324 4.2 7,653 5.4 Two 9,801 24.7 5,554 14.0 7,009 17.6 6,586 16.6 9,224 23.2 1,538 3.9 39,711 28.1 Three 26,993 29.5 6,844 7.5 10,002 10.9 24,130 26.3 19,589 21.4 4,063 4.4 91,620 64.7 Four 0 0.0 626 24.6 0 0.0 1,844 72.5 75 3.0 0 0.0 2,545 1.8 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 19,728 26.6 6,281 8.5 10,051 13.5 17,441 23.5 17,436 23.5 3,304 4.5 74,240 52.5 One 8,385 24.4 4,171 12.2 3,727 10.9 8,863 25.8 7,702 22.4 1,480 4.3 34,327 24.3 Two 5,392 27.4 2,254 11.4 2,578 13.1 5,168 26.2 3,703 18.8 595 3.0 19,689 13.9 Three 1,811 27.1 730 10.9 1,311 19.6 1,446 21.6 1,314 19.6 82 1.2 6,694 4.7 Four 1,232 42.4 240 8.3 418 14.4 632 21.8 320 11.0 64 2.2 2,906 2.1 Five 481 23.1 186 9.0 370 17.8 714 34.4 137 6.6 189 9.1 2,077 1.5 Six 100 9.8 64 6.4 47 4.7 481 47.4 138 13.6 184 18.1 1,014 0.7 Seven 162 27.8 103 17.7 135 23.2 0 0.0 155 26.6 28 4.7 582 0.4 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District Mkuranga Rufiji Mafia Bagamoyo Kibaha Kisarawe District Total Number of Meals per Day Total District 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Kibaha Kisarawe Mkuranga Bagamoyo Rufiji Mafia Number of Days Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 271 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 13,351 49.7 3,606 13.4 5,906 22.0 1,137 4.2 2,819 10.5 23 0.1 26,843 19.0 One 8,143 35.5 2,661 11.6 4,306 18.8 2,756 12.0 4,706 20.5 378 1.6 22,950 16.2 Two 7,460 28.5 2,993 11.4 4,109 15.7 5,108 19.5 6,232 23.8 314 1.2 26,216 18.5 Three 3,714 21.5 2,419 14.0 2,441 14.1 4,545 26.3 3,768 21.8 405 2.3 17,293 12.2 Four 1,465 9.9 1,281 8.6 936 6.3 5,943 40.0 4,848 32.7 374 2.5 14,847 10.5 Five 1,100 11.1 441 4.5 562 5.7 3,930 39.6 3,119 31.5 762 7.7 9,915 7.0 Six 277 7.3 305 8.0 95 2.5 1,420 37.2 875 22.9 844 22.1 3,814 2.7 Seven 1,778 9.0 322 1.6 283 1.4 9,907 50.4 4,539 23.1 2,824 14.4 19,653 13.9 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 7,492 20.2 4,307 11.6 3,640 9.8 12,586 34.0 6,207 16.8 2,785 7.5 37,016 26.2 Seldom 14,542 27.0 4,498 8.3 6,238 11.6 13,836 25.7 12,909 23.9 1,877 3.5 53,900 38.1 Sometimes 4,964 40.9 1,545 12.7 998 8.2 2,553 21.1 1,480 12.2 585 4.8 12,124 8.6 Often 7,323 24.8 2,636 8.9 6,510 22.0 4,827 16.3 7,756 26.2 504 1.7 29,557 20.9 Always 2,969 33.2 1,043 11.7 1,252 14.0 942 10.5 2,554 28.6 173 1.9 8,933 6.3 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Number of Days Bagamoyo Kibaha Kisarawe District Total Mkuranga Rufiji Mafia Status of Food Satisfaction District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 272 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 12,815 33.9 6,465 17.1 4,874 12.9 7,570 20.1 5,494 14.6 531 1.4 37,749 26.7 Tiles 99 26.1 99 26.2 44 11.5 79 20.9 58 15.4 0 0.0 380 0.3 Concrete 0 0.0 0 0.0 0 0.0 0 0.0 53 100.0 0 0.0 53 0.0 Asbestos 440 84.0 0 0.0 0 0.0 0 0.0 62 11.8 22 4.2 524 0.4 Grass / Leaves 19,768 21.2 7,237 7.8 12,050 12.9 27,014 29.0 21,830 23.4 5,371 5.8 93,270 65.9 Grass & Mud 3,878 41.9 227 2.5 1,670 18.0 81 0.9 3,409 36.8 0 0.0 9,265 6.5 Other 289 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 289 0.2 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 2,234 7.0 4,524 14.3 1,391 4.4 4,982 15.7 18,280 57.7 283 0.9 31,695 22.4 Sale of Livestock 876 66.2 278 21.0 0 0.0 0 0.0 148 11.2 21 1.6 1,323 0.9 Sale of Livestock Products 1,334 63.3 281 13.3 95 4.5 313 14.9 0 0.0 83 4.0 2,106 1.5 Sales of Cash Crops 5,334 16.6 2,009 6.3 4,554 14.2 14,528 45.2 3,237 10.1 2,447 7.6 32,109 22.7 Sale of Forest Products 10,593 39.0 1,685 6.2 7,490 27.6 5,448 20.1 1,820 6.7 113 0.4 27,149 19.2 Business Income 3,550 29.2 1,142 9.4 1,386 11.4 3,954 32.6 1,633 13.4 477 3.9 12,141 8.6 Wages & Salaries in Cash 1,015 24.7 713 17.3 462 11.2 657 16.0 702 17.1 566 13.8 4,116 2.9 Other Casual Cash Earning 8,473 55.5 2,045 13.4 1,627 10.7 2,162 14.2 547 3.6 399 2.6 15,254 10.8 Cash Remittance 2,334 29.6 1,082 13.7 1,539 19.5 1,626 20.6 1,115 14.2 186 2.4 7,882 5.6 Fishing 1,073 16.7 160 2.5 47 0.7 949 14.8 2,900 45.2 1,289 20.1 6,418 4.5 Other 473 35.4 110 8.2 46 3.5 125 9.3 524 39.2 59 4.4 1,336 0.9 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Roofing Materials District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Main Source of Cash Income District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Tanzania Agriculture Sample Census - 2003 Pwani 273 APPENDIX III QUESTIONNAIRES Appendix III 274 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 275 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 276 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 277 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 278 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 279 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 280 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 281 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 282 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 283 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 284 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 285 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 286 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 287 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 288 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 289 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 290 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 291 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 292 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 293 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 294 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 295 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 296 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source \"a\" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 297 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 298 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 299 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 300 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 301 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 302 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 303 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 304 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 305 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 306 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 307 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 308 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 309 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 310 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 311 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 312 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 313 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 314 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 315 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 316 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 317 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 318 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 319 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":162,"cells":{"data":{"kind":"string","value":"# Extracted Content CHAPTER 3 RAINFALL DISTRIBUTION Table 3.1 : Monthly Rainfall (in mm) at selected stations for the year 1997 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 95.4 20.5 163.2 340.7 170.3 2.2 17.1 62.6 101.6 252.3 408.4 352.4 1,986.7 Mwanza 166.1 23.7 170.6 334.6 93.0 48.1 2.0 1.2 1.0 145.7 238.7 181.2 1,405.9 Musoma 56.9 26.2 126.3 269.7 74.6 34.8 14.0 18.6 2.0 104.2 294.4 205.5 1,227.2 Shinyanga 74.9 157.2 62.7 174.1 175.9 0.0 0.0 0.0 0.0 0.0 92.0 475.4 1,212.2 Arusha 17.4 8.8 82.0 177.1 139.2 31.9 12.6 0.0 0.0 74.8 180.3 425.3 1,149.4 Kilimanjaro 4.2 0.0 58.1 330.5 196.3 38.0 11.1 0.0 0.0 49.2 72.3 144.5 904.2 Moshi 0.0 12.6 126.9 375.3 177.1 26.2 14.7 0.6 1.0 125.5 108.8 67.1 1,035.8 Tanga 0.0 1.7 97.1 254.3 194.3 152.6 13.7 55.6 44.5 805.5 271.2 75.4 1,965.9 Karume 0.4 0.0 296.7 479.5 77.2 159.8 149.0 7.8 0.7 372.0 142.0 245.8 1,930.9 Dar es salaam 1.7 0.3 232.8 167.0 98.8 173.5 5.6 5.8 2.9 244.7 164.7 184.3 1,282.1 Morogoro 13.8 55.6 156.6 246.5 35.7 39.5 4.4 2.0 0.0 88.5 93.9 252.3 988.8 Mtwara 45.2 122.9 342.1 136.3 44.6 45.5 11.6 1.0 5.0 13.1 160.8 194.3 1,122.4 Dodoma 46.4 82.5 22.0 26.7 52.6 0.0 0.0 0.0 0.0 1.8 89.5 310.4 631.9 Tabora 178.6 152.9 139.4 179.7 68.3 7.2 0.0 0.0 0.0 0.0 49.8 462.0 1,237.9 Kigoma 150.6 6.2 107.9 118.2 111.1 0.0 0.0 0.0 0.0 224.1 111.0 173.2 1,002.3 Iringa A/P 75.7 176.7 29.6 75.1 67.2 0.0 0.0 0.0 0.0 1.1 47.3 287.6 760.3 Mbeya A/P 134.9 182.1 51.4 192.1 0.0 0.0 1.4 0.0 0.0 22.7 158.5 481.2 1,224.3 Songea 185.3 316.0 49.5 66.6 0.0 10.7 0.0 0.0 0.0 2.7 6.5 258.9 896.2 Mahenge 149.3 168.6 476.6 566.8 24.9 149.2 16.4 0.0 0.0 110.9 227.2 413.1 2,303.0 Source : Directorate of Meteorology, Ministry of Communications and Transport A/P= Air Port Table 3.2: Monthly Rainfall (in mm) at selected Stations with full Data for the Year 1998 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 251.6 178.6 205.8 367.4 213.7 132.4 76.8 0.0 140.0 136.1 159.0 97.7 2057.2 Mwanza 151.5 115.8 94.4 234.2 24.2 80.1 1.2 0.0 16.5 45.4 86.2 27.4 876.9 Arusha 171.1 87.3 152.1 261.6 170.1 12.5 9.6 0.3 2.5 0.4 17.7 14.8 900.0 Sumbawanga 245.5 105.7 121.4 181.6 37.8 0.0 0.0 0.3 0.0 0.5 57.8 77.8 828.4 Iringa 199.5 170.1 91.1 108.0 98.9 0.0 0.0 0.0 0.0 0.0 0.7 18.9 687.2 Mbeya 191.5 352.0 124.2 86.9 8.8 0.0 0.0 0.0 0.0 16.5 8.6 76.6 865.1 Tabora 279.0 96.4 112.5 97.8 55.5 0.0 0.0 0.0 29.2 - 26.2 114.8 811.4 NB: Figure for October for Tabora region was not obtained Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.3: Monthly Rainfall (in mm) at selected Stations for the Year 1999 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 212.4 43.8 311.0 222.4 279.6 11.6 9.6 58.8 148.4 75.7 208.1 243.4 1,824.8 Mwanza 94.1 0.1 184.0 169.8 18.6 0.0 0.0 59.2 5.4 68.4 228.0 227.7 1,055.3 Musoma 93.9 12.8 343.5 136.3 64.1 0.0 0.0 4.9 11.1 31.4 181.1 33.4 912.5 Shinyanga 116.0 58.7 108.3 229.6 0.5 0.0 0.0 0.2 4.6 0.0 100.1 91.2 709.2 Arusha 35.1 13.5 176.2 95.8 75.2 15.2 8.2 6.7 1.1 0.7 130.0 29.6 587.3 Kilimanjaro 3.0 0.8 250.4 165.7 113.9 50.8 10.7 15.3 5.8 1.6 37.3 4.2 659.5 Moshi 20.8 0.6 229.8 393.4 91.7 72.8 14.9 24.9 13.6 1.7 71.4 23.1 958.7 Tanga 5.5 8.8 208.2 227.3 274.3 145.3 127.3 118.8 69.0 71.3 102.7 8.6 1,367.1 Same 28.2 15.8 127.1 77.0 40.7 27.5 7.2 27.5 2.7 5.7 182.0 25.3 566.7 Karume 58.3 1.5 271.6 514.6 502.0 186.6 78.3 59.8 28.0 36.4 67.2 60.4 1,864.7 Kisauni 65.8 51.1 194.0 311.5 179.5 158.3 55.4 80.9 31.3 17.0 249.4 120.3 1,514.5 Dar es salaam 26.4 112.6 220.6 267.1 148.0 79.8 60.8 22.2 13.5 27.2 115.0 173.8 1,267.0 Morogoro 8.3 29.0 186.2 202.7 89.8 27.5 38.7 21.6 16.1 11.5 33.6 60.7 725.7 Mtwara 180.3 170.3 168.7 240.5 48.5 31.5 7.8 2.1 23.3 1.1 52.1 74.3 1,000.5 Dodoma 137.2 49.9 226.2 73.3 0.1 0.0 0.0 0.0 0.1 0.0 0.0 114.8 601.6 Tabora 137.4 50.3 301.1 34.8 2.4 0.0 0.0 1.8 3.0 0.0 203.5 46.7 781.0 Kigoma 88.6 46.7 191.9 114.0 0.0 0.0 0.0 21.9 0.8 71.6 273.9 113.3 922.7 Sumbawanga 137.7 86.3 219.8 105.1 7.4 1.1 0.0 9.6 0.0 10.7 25.2 96.9 699.8 Iringa 115.4 104.8 190.4 35.7 0.0 0.5 0.0 0.0 0.0 0.0 1.0 70.5 518.3 Mbeya 327.0 116.1 330.3 125.2 52.6 2.5 0.0 4.9 2.1 3.1 12.1 144.7 1,120.6 Songea 128.1 125.1 396.3 168.4 15.3 0.0 0.0 2.0 2.7 2.8 10.0 83.9 934.6 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.4: Monthly Rainfall (in mm) for the Year 2000 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 52.2 90.7 115.7 199.2 212.8 39.2 48.2 69.8 77.7 130.2 234.2 223.4 1493.3 Mwanza 88.7 41.0 51.0 67.6 14.1 5.9 0.0 0.0 0.0 69.9 129.8 - 468.0 Musoma 11.8 37.1 122.7 106.4 41.9 9.4 0.0 43.8 15.2 39.2 88.6 190.3 706.4 Arusha 38.2 26.7 44.3 144.3 30.8 10.5 3.3 15.8 4.0 0.0 101.4 104.3 523.6 Kilimanjaro A/P 10.0 3.1 13.8 41.4 52.0 22.2 4.2 15.9 11.5 1.1 123.3 46.4 344.9 Moshi A/P 1.4 2.0 121.4 121.9 54.1 27.0 4.4 15.3 2.2 6.0 16.9 29.0 401.6 Same 0.0 0.4 104.3 60.2 38.5 40.1 1.1 4.9 17.6 2.1 56.5 26.4 352.1 Karume 7.4 0.0 157.5 369.9 19.9 82.7 35.4 0.7 13.6 14.7 76.6 104.0 882.4 Zanzibar 1.4 0.0 270.9 352.0 86.9 195.9 40.6 4.4 35.3 6.2 191.1 217.0 1401.7 Dar es salaam 1.8 3.5 108.4 261.2 70.0 126.9 18.7 24.0 3.2 6.2 79.2 220.0 923.1 Morogoro 68.8 37.9 183.0 110.3 47.8 48.0 5.2 0.3 4.9 0.0 49.5 205.0 760.7 Mtwara 127.6 60.3 360.5 72.4 54.9 25.1 28.7 16.6 20.3 10.1 97.1 154.1 1027.7 Dodoma 126.0 85.9 172.5 35.8 0.0 0.0 0.0 0.0 0.0 0.0 60.7 274.0 754.9 Tabora A/P 94.4 97.8 178.3 126.4 0.0 0.0 0.0 0.0 1.0 23.5 239.3 192.0 952.7 Kigoma 44.7 58.9 140.2 59.9 32.8 0.0 0.0 0.0 2.0 4.0 204.1 - 546.6 Iringa A/P 97.8 52.8 87.3 50.4 0.0 0.0 0.0 0.0 0.0 0.0 199.0 90.0 577.3 Mbeya A/P 147.3 174.0 205.5 70.1 0.0 0.0 0.0 0.0 0.0 0.0 163.0 259.0 1018.9 Songea A/P 191.4 162.7 189.3 120.6 11.4 1.0 0.0 3.1 0.0 0.0 111.8 248.0 1039.3 Tanga A/P - 0.0 109.3 164.4 246.6 266.1 80.7 35.5 34.1 44.7 35.3 51.7 1068.4 Source: Food Security Department (Meteorological Unit), Ministry of Agriculture and Food Security 'A/P (Air Port) Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Table 3.5: Monthly Rainfall (in mm) for the Year 2001 Bukoba 181.4 210.0 140.8 284.4 287.7 125.3 41.9 9.0 41.5 147.9 139.0 164.8 1773.7 Mwanza 210.6 113.5 72.3 164.2 25.2 1.6 25.4 38.3 31.1 104.7 219.6 139.6 1146.1 Musoma 74.0 34.9 271.2 207.7 129.1 21.8 32.7 19.0 16.2 98.5 89.7 24.3 1019.1 Arusha 225.1 23.5 178.9 108.5 47.7 16.9 0.0 3.0 0.4 0.2 43.3 55.7 703.2 Kilimanjaro A/P107.4 45.6 169.9 107.2 31.4 10.5 0.0 2.7 0.2 0.0 21.7 1.8 498.4 Moshi A/P 136.4 30.1 182.9 294.0 145.4 14.8 1.0 0.3 7.0 11.5 63.0 3.9 890.3 Same 121.9 14.4 42.4 127.0 15.0 62.6 0.0 0.0 0.2 0.0 45.7 42.6 471.8 Zanzibar 88.2 47.0 63.5 642.8 290.3 34.6 26.8 16.2 17.3 9.3 31.4 64.2 1331.6 Dar es salaam 64.5 71.3 139.0 296.6 162.5 14.0 19.6 3.9 5.0 6.7 15.5 82.2 880.8 Morogoro 104.3 99.0 172.5 224.6 90.4 4.6 5.8 0.0 0.0 11.1 0.0 71.7 784.0 Mtwara 298.9 155.6 244.7 124.8 11.0 0.0 7.2 9.9 5.0 56.4 12.8 99.4 1025.7 Dodoma 312.5 45.4 47.0 85.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 103.0 593.3 Tabora A/P 175.9 201.2 171.5 92.0 18.1 0.0 27.7 0.3 0.6 40.1 66.4 285.1 1078.9 Kigoma 161.5 59.6 228.3 31.0 39.0 17.7 0.5 22.0 30.6 64.1 71.4 91.0 816.7 Iringa A/P 437.6 247.4 184.4 33.6 6.0 0.0 0.0 1.3 4.2 0.0 6.2 229.2 1149.9 Mbeya A/P 451.3 106.5 103.0 95.6 24.1 0.0 0.0 0.0 8.6 21.6 33.3 175.4 1019.4 Songea A/P 269.1 118.5 290.5 52.4 20.4 0.0 0.0 0.0 1.3 0.0 10.4 127.9 890.5 Tanga A/P 39.1 28.5 53.4 157.7 204.7 122.6 17.1 25.0 7.2 24.3 57.9 76.3 813.8 Pemba 44.9 44.2 50.1 755.9 226.1 86.4 35.1 20.5 0.5 3.5 19.2 100.2 1386.6 Shinyanga 109.4 100.8 140.1 84.8 25.6 0.0 1.4 0.0 8.3 55.0 44.1 177.5 747.0 Sumbawanga 302.8 159.3 186.4 110.6 54.3 2.1 0.0 0.0 15.6 10.5 49.1 152.1 1042.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 97.5 103.3 440.8 428.3 62.3 23.5 14.2 28.5 92.0 175.0 267.5 174.5 1907.4 Mwanza 140.4 68.0 240.5 206.1 122.6 0.0 0.0 0.0 1.1 61.1 143.0 299.2 1282.0 Musoma 64.7 19.4 165.2 167.1 164.6 18.2 17.2 5.5 24.5 49.1 165.3 209.0 1069.8 Arusha 124.8 136.3 151.6 220.2 42.3 7.6 1.6 15.8 43.0 97.8 36.8 131.9 1009.7 Kilimanjaro A/P 89.4 66.3 101.6 162.4 27.1 2.5 0.7 25.6 19.2 110.3 49.0 134.2 788.3 Moshi A/P 69.5 21.7 177.8 490.0 71.8 1.6 3.7 39.8 116.2 72.3 27.1 129.0 1220.5 Same 67.7 55.5 88.8 58.1 4.8 0.0 0.0 28.9 30.8 171.0 48.4 114.0 668.0 Zanzibar 123.1 144.6 109.6 705.4 78.3 19.4 87.6 104.6 77.7 133.8 204.9 176.4 1965.4 Dar es salaam 97.5 103.3 440.8 428.3 62.3 23.5 14.2 28.5 92.0 175.0 267.5 174.5 1907.4 Morogoro 35.6 116.8 187.4 264.6 24.6 1.1 4.9 8.7 13.6 70.2 60.5 157.1 945.1 Mtwara 361.3 193.1 332.3 176.7 4.0 7.6 2.4 40.8 48.4 4.5 172.6 245.6 1589.3 Dodoma 285.0 97.6 71.3 4.6 2.5 0.0 0.0 0.0 0.0 1.5 0.0 187.5 650.0 Tabora A/P 145.7 100.8 224.9 142.4 80.2 0.0 0.0 0.0 0.0 39.5 66.4 228.5 1028.4 Kigoma 289.7 26.3 167.8 233.0 4.3 0.0 0.0 0.0 0.0 29.0 186.4 106.3 1042.8 Iringa A/P 170.6 92.0 178.0 20.1 3.8 0.0 0.0 0.0 0.0 0.0 4.4 141.4 610.3 Mbeya A/P 191.5 182.7 152.0 61.4 0.0 0.0 0.0 0.0 0.8 3.2 21.4 153.9 766.9 Songea A/P 360.0 192.8 298.0 116.3 1.7 2.0 0.0 0.0 0.2 1.1 87.2 198.3 1257.6 Tanga A/P 41.8 23.5 94.3 312.6 160.5 16.7 47.8 143.8 168.9 205.6 144.2 159.2 1518.9 Pemba 49.7 7.6 68.4 472.7 108.2 53.9 67.8 55.7 121.6 68.5 79.9 160.4 1314.4 Shinyanga 200.1 96.5 185.3 125.5 31.5 0.0 0.0 8.0 0.0 79.9 134.6 109.7 971.1 Sumbawanga 236.2 110.2 170.6 91.5 4.3 0.0 0.0 0.0 0.0 0.0 89.3 116.7 818.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.6: Monthly Rainfall (in mm) for the Year 2002 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 118.5 33.0 240.5 237.5 185.7 120.0 99.0 81.4 117.4 92.2 241.1 108.7 1675.0 Mwanza 44.7 20.1 186.0 154.1 86.2 0.5 13.0 21.1 6.4 21.8 85.8 251.3 891.0 Musoma 0.4 0.7 93.8 180.3 130.5 38.8 18.3 33.1 16.1 19.7 59.6 60.3 651.6 Arusha 33.0 49.2 53.0 39.4 128.3 17.3 2.8 0.1 7.3 22.9 18.1 77.2 448.6 Kilimanjaro A/P 9.7 14.6 18.4 40.8 188.9 12.2 3.8 0.0 5.0 2.1 0.0 43.1 338.6 Moshi A/P 3.7 10.1 62.0 159.4 191.4 53.8 9.7 2.8 0.4 0.0 1.1 19.0 513.4 Same 8.5 66.2 56.1 31.3 85.5 11.6 0.0 1.8 0.0 0.5 47.4 23.5 332.4 Zanzibar 4.1 3.0 44.7 32.4 209.7 38.4 42.3 15.3 17.2 108.7 88.5 75.1 679.4 Dar es salaam 20.1 22.2 122.4 13.7 130.8 109.5 26.1 0.9 3.5 22.4 89.2 24.6 585.4 Morogoro 63.0 30.5 162.3 54.5 51.2 13.2 11.4 0.0 0.0 55.2 4.3 50.1 495.7 Mtwara 141.3 111.5 92.2 51.8 32.4 0.0 0.0 2.4 1.5 2.2 6.5 39.8 481.6 Dodoma 90.4 68.2 51.9 7.7 17.8 0.0 0.0 0.0 0.0 76.2 0.6 175.5 488.3 Tabora A/P 186.7 113.2 80.0 159.4 38.7 0.0 0.0 0.0 13.0 32.5 76.8 136.1 836.4 Kigoma 164.7 153.1 161.0 170.9 6.5 8.3 0.0 3.8 22.0 73.0 91.8 84.8 939.9 Iringa A/P 156.9 93.6 58.1 44.0 14.3 0.0 0.0 0.0 0.0 13.5 2.4 93.5 476.3 Mbeya A/P 247.7 111.2 167.0 43.5 0.0 0.0 3.4 0.0 0.0 16.6 80.7 146.3 816.4 Songea A/P 160.3 226.1 254.6 67.2 12.8 0.0 0.0 0.0 0.0 0.0 22.9 217.5 961.4 Tanga A/P 0.6 0.0 6.1 43.2 285.8 36.9 27.0 53.3 39.3 104.0 86.2 10.4 692.8 Pemba 17.6 1.5 45.2 130.6 472.3 49.7 71.3 28.1 23.8 92.9 3.1 22.0 958.1 Shinyanga 159.7 14.4 106.9 171.6 58.5 0.0 0.0 2.7 3.8 27.1 24.2 86.1 655.0 Sumbawanga 172.2 24.2 112.7 62.0 10.9 3.3 4.1 0.0 0.0 0.0 28.1 203.0 620.5 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.8: Total Monthly Rainfall (in mm) for selected stations 2004 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 211.0 171.1 251.2 327.1 223.8 10.1 43.1 47.3 118.8 161.1 121.3 165.3 1851.2 Musoma 88.6 76.8 139.7 191.3 145.9 3.3 0.0 0.0 4.1 12.7 83.3 96.5 842.2 Mwanza 91.3 84.0 122.5 115.7 32.4 26.2 0.0 2.4 25.7 147.5 183.3 198.1 1029.1 Shinyanga 138.7 84.4 159.9 170.0 4.3 0.0 0.0 0.9 30.1 17.3 75.8 177.0 858.4 Kigoma 126.1 139.6 85.2 54.4 0.0 0.0 0.0 10.2 47.9 38.3 83.4 164.9 750.0 Tabora 145.8 134.7 164.8 92.8 0.0 0.0 0.0 11.4 36.3 24.8 102.5 473.9 1187.0 Dodoma 112.9 148.2 161.9 56.9 0.0 0.0 0.0 0.0 0.0 0.0 90.4 177.3 747.6 Mbeya 269 184.0 214.0 135.7 0.0 0.0 0.0 0.0 8.0 7.4 28.5 283.4 1130.0 Iringa 197.5 168.1 248.2 89.2 0.0 0.0 0.0 0.0 0.0 0.2 22.8 95.4 821.4 Sumbawanga 195.7 127.4 109.2 63.8 0.0 0.0 0.0 0.0 20.5 0.0 81.6 289.1 887.3 Morogoro 142.3 196.3 127.7 215.8 1.5 2.8 1.2 0.0 0.0 38.4 56.3 38.9 821.2 Songea 264.2 174.5 199.8 128.2 0.0 0.0 0.0 0.0 0.0 1.7 59.9 236.4 1064.7 Mahenge 287.9 298.6 311.5 369.3 53.5 26.8 0.0 10.2 26.3 92.8 156.8 351.9 1985.6 Arusha 86.3 72.2 57.2 97.7 0.0 10.2 0.0 0.0 7.3 30.7 25.0 80.4 467.0 Kilimanjaro 36.4 27.9 48.2 91.9 9.5 7.5 0.0 0.0 1.9 18.9 28.6 86.5 357.3 Moshi 41.4 31.4 55.9 196.0 65.8 0.0 2.4 0.0 0.0 61.1 27.6 39.6 521.2 Same 0.0 44 80.2 47.8 11.3 5.9 2.2 0.0 0.0 29.4 70.3 50.8 341.9 Tanga 148.0 82.4 62.9 209.2 46.2 128.4 2.2 11.8 24.3 97.8 185.4 103.0 1101.6 Dar es salaam 77.2 149.8 131.2 297.6 19.3 42.2 0.0 13.6 31.1 93.5 47.4 181.3 1084.2 Table 3.7: Monthly Rainfall (in mm) for the Year 2003 Mtwara 205.8 273.6 96.7 152.4 0.0 2.9 0.0 0.0 0.0 105 135.8 354.7 1326.9 Singida 56.7 275.7 160.0 85.7 0.0 0.0 0.0 0.0 0.0 0.0 80.4 73.2 731.7 Handeni 203.5 124.0 177.4 195.3 2.4 29.7 4.2 0.0 0.0 141.4 76.7 41.2 995.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.9: Total Monthly Rainfall (in mm) for selected stations 2005 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 156.3 103.2 281.5 308.2 125.9 76.3 42.5 56.8 83.2 67.8 105.9 102.9 1510.5 Musoma 161.9 73.7 183.8 117.8 62.4 39.7 10.3 23.1 25.5 49.9 53.2 28.1 829.4 Mwanza 169.2 8.1 232.8 117.6 87.5 0.8 11.0 19.2 170.6 86.8 34.5 101.6 1039.7 Shinyanga 90.3 44.3 141.9 67.3 38.6 0.2 0.0 0.8 2.2 13.9 27.0 76.8 503.3 Kigoma 265.4 29.6 80.3 35.1 10.5 0.0 0.0 2.5 0.0 22.7 153.7 31.0 630.8 Tabora 177.6 34.7 184.2 89.8 41.0 0.0 0.0 0.0 0.0 6.2 34.6 86.9 655 Dodoma 33.1 58.6 129 17.2 0.0 0.0 0.0 0.0 0.0 36.0 8.7 45.7 328.3 Mbeya 165.0 70.9 141.7 56.3 0.0 0.0 0.0 0.0 0.0 1.5 45.8 116.6 597.8 Iringa 175.2 105 83 19.2 0.0 0.0 0.0 0.0 0.0 0.7 4.0 10.5 397.6 Sumbawanga 174.2 78.8 165.1 29.4 1.8 0.0 0.0 0.0 2.0 1.0 6.9 148.2 607.4 Morogoro 115.1 51.9 131.3 102.2 28.6 11.2 0.0 0.0 0.0 4.6 23.3 11.2 479.4 Songea 129.8 65.5 254.5 55.9 1.9 0.0 0.0 0.0 0.0 0.0 0.0 86.8 594.4 Mahenge 221.3 463.7 389.1 450.9 118.3 30.3 1.1 1.3 10.2 4.4 14.8 99.1 1804.5 Arusha 13.4 6.2 120 130.1 56.2 10.7 0.0 0.2 2.9 58.7 86.5 23.0 507.9 Kilimanjaro 23.7 9.2 96.5 123.4 49.5 11.1 0.0 0.0 2.2 10.3 12.2 2.0 340.1 Moshi 0.0 2.8 55.2 150 40.1 26.8 0.0 1.4 1.9 30.5 23.7 0.3 332.7 Same 31.7 0.5 39.1 108.7 42.2 12.8 0.0 0.0 10.8 24.6 15.8 5.8 292 Tanga 35.7 0.1 19.1 192.2 81.5 40.7 11.4 25.1 15.5 48.9 107.0 3.7 580.9 Dar es salaam 55.5 174.1 70.2 119.5 63.0 11.7 2.3 0.0 10.5 91.6 24.5 13.4 636.3 Mtwara 290.0 55.7 219.5 118.7 37.6 0.0 0.0 0.0 18.1 8.9 1.4 27.6 777.5 Singida 82.4 45.3 145.7 60.6 18.6 0.0 0.0 0.0 0.0 20.1 8.1 17.9 398.7 Handeni 30.1 0.2 295.6 130.6 33.7 0.8 0.0 0.0 45.0 16.6 16.5 0.0 569.1 Source : Directorate of Meteorology, Ministry of Communications and Transport"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":163,"cells":{"data":{"kind":"string","value":"# Extracted Content CHAPTER 8 RESEARCH AND TRAINING Table 8.1: Agricultural Research Zones in Tanzania Zone Regions Covered Zonal Centre Research Stations Research Mandate CENTRAL Dodoma, Singida Mpwapwa Hombolo, Makutupora Sorghum, Millet and Grapes EASTERN Dar es Salaam, Pwani, Morogoro, Tanga ARI-Ilonga Ilonga, KATRIN,Cholim a/Dakawa, Mlingano, Kibaha, Mikocheni Maize, rice, sorghum and millet, grainlegumes, horticulture, soil and water management, horticulture,sugarcane, root and tubers, spices, coconut, biotechnology LAKE Kagera, Mwanza, Shinyanga, Mara ARI-Ukiriguru Ukiriguru, Maruku Phaseolus Beans, Grain legumes,Root and Tubers, sorghum and millets, rice, bananas, NORTHERN Kilimanjaro, Arusha, Manyara ARI-Selian Selian, Hort- Tengeru Wheat and Barley, Bananas, Horticulture,Maize, Phaseolus beans, irish potatoes, sweet potatoes SOUTHERN Mtwara, Lindi ARI-Naliendele Naliendele Cashewnut, Oilseeds, cassava SOUTHERN HIGHLANDS Mbeya, Iringa, Rukwa, Ruvuma ARI-Uyole Uyole, Kifyulilo Maize, Phaseolus beans,wheat, pyrethrum,horticulture,ric e, irish potatoes WESTERN Tabora, Kigoma ARI-Tumbi Tumbi, Seatondale Agroforestry Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives 141 Table 8.2: Number of Research Scientists by Qualifications as of January 2006 ZONE Station BA/BSc MA/MSc PhD CENTRAL MAKUTUPORA 1 2 1 HOMBOLO 1 2 0 Sub-Total Central 2 4 1 EASTERN ILONGA 9 10 6 MLINGANO 5 13 6 MIKOCHENI 5 11 5 KATRIN 2 3 0 KIBAHA 4 5 2 CHOLIMA/DAKAWA 2 7 0 Sub-Total Eastern 27 49 19 LAKE UKIRIGURU 10 19 3 MARUKU 6 5 1 Sub-Total Lake 16 24 4 NORTHERN SELIAN 8 27 9 HORT-TENGERU 6 7 1 Sub-Total Northern 14 34 10 SOUTHERN NALIENDELE 9 9 8 Sub-Total Southern 9 9 8 SOUTHERN HIGHLANDS UYOLE 9 29 8 KIFYULILO 0 2 0 Sub-Total Southern Highlands 9 31 8 WESTERN TUMBI 10 9 3 Sub-Total Western 10 9 3 DRT-DSM DRT-HQ 2 17 5 Sub-Total DRT-HQ Temeke 2 17 5 Total 89 177 58 Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives Table 8.3: Number of research Scientists by Gender by Qualifications Qualification Female Male Total PhD 11 47 58 MSc/MA 34 144 178 BSc/BA 28 61 89 Total 73 252 325 Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives 142"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":164,"cells":{"data":{"kind":"string","value":"# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE Government City-Mtumba P. O BOX 2182 40487 DODOMA Email: ps@kilimo.go.tz BUILDING A BETTER TOMORROW: YOUTH INITIATIVES FOR AGRIBUSINESS (BBT-YIA) THE PROPOSED ESTABLISHMENT OF CHINANGALI II BLOCK FARM LOCATED AT MWEGAMILE VILLAGE, BUIGIRI WARD, CHAMWINO DISTRICT COUNCIL IN DODOMA REGION RESETTLEMENT ACTION PLAN CONSULTANT Eng. Lait A.Simukanga Registered Environmental Consultant, Reg. No NEMC/EIA/0032 Practicing License No. NEMC/PC/EIA/2021/0020 Kimara Street Plot No. 0095, P.O. Box 13033, DAR ES SALAAM, Email: lsimukanga@gmail.com Mobile: +255 754 271175 Date of Submission: 01 May 2024 RAP for Chinangali II Block Farm May, 2024 ii EXECUTIVE SUMMARY The Ministry of Agriculture is in the process of developing Chinangali II Block Farms in Chamwino district Council Dodoma Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm followed by the Resettlement Action Plan (April 2024) The community in the proposed BBT farm occupied the land through customary land ownership which includes inheritance from the ancestors and purchasing from neighbours. The Village Council in collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of the block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. A series of village assembly and village council meetings were conducted since March 2023 with staffs from Chamwino District Council along with visiting the proposed project area site on regular basis. These meetings came out with the decision that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village. Based on the assessments and negotiations carried out within the context of the resettlement for the works (development/construction) of the project, and by mutual agreement, the PAP receives the sum of Tsh. 1,000,000/= per acre. The Total land acquired through purchasing is estimated to be 1,552 acres. Considering the economic importance required for development of Chinangali II BBT farm and the people that were using the land for subsistence farming located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. This requires preparation of a RAP to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: Nature and category of impacts S/N Property Category of Impact Number of PAPs 1 Purchased Land Loss of agricultural land 1,552 acres Number of PAPs Livelihood 226 2 Residential Structure Temporary Houses 0 3 Entire residential structures House owners 0 Residential tenants 0 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners 7 Amount of funds set aside for land purchase 1,152,000,000 RAP for Chinangali II Block Farm May, 2024 iii 8 Number of PAPs paid and Amount 210 PAPs Tsh. 1,074,690,000 9 Number of PAPs not paid and Amount 16 PAPs Tsh. 77,610,000 Evidences of remittance for payment to RAP are attached as Appendix III and a full list of remittance payment is attached as a separate document. Reason for not being paid is due to bank transfer logistics challenges for 16 PAPs. The District Council is liasing with the banks to resolve the problem for payments to the remaining PAPs. The Cost of RAP implementation including payments to the remaining PAPs, monitoring and follow up is estimated to be Tsh 103,610,000/=. The funds for RAP implementation are available. RAP for Chinangali II Block Farm May, 2024 iv Contents EXECUTIVE SUMMARY .......................................................................................................................................... ii LIST OF TABLES ....................................................................................................................................................... v LIST OF PLATES ........................................................................................................................................................ v ABBREVIATIONS ..................................................................................................................................................... vi 1.0 INTRODUCTION .................................................................................................................................................. 1 1.1Project Background ............................................................................................................................................. 1 1.2 Objective of the project ...................................................................................................................................... 1 1.3 Project Justification ............................................................................................................................................ 2 1.4 Project Beneficiaries ........................................................................................................................................... 2 1.5 Need for Resettlement Action Plan .................................................................................................................... 3 1.6 Objective of Resettlement Action Plan............................................................................................................... 4 1.7 Methodology for Preparation of RAP ................................................................................................................ 4 1.7.1 Conducting Literature Review ......................................................................................................................... 4 2.0 PROJECT DESCRIPTION .................................................................................................................................... 5 2.1 Location .............................................................................................................................................................. 5 2.1.1 General project location .......................................................................................................................... 5 2.2.2 Specific project Location ............................................................................................................................. 5 2.2 Overview of the project affected area ................................................................................................................. 5 2.2.1 Characteristics of PAPs in Chinangali II BBT farm .................................................................................... 6 2.2.3 House conditions ......................................................................................................................................... 6 3.0 LAND ACQUISITION PROCESS ........................................................................................................................ 7 3.1 Land purchase and price ..................................................................................................................................... 7 3.2 Land Tittle Deed ................................................................................................................................................. 8 4.0 LEGAL AND INSTITUTION PRAMEWORK FOR LAND ACQUISITION IN TANZANIA........................... 9 4.1 Land Tenure and Ownership in Tanzania ........................................................................................................... 9 4.2 Land categories in Tanzania ............................................................................................................................... 9 4.2.1 General land ................................................................................................................................................ 9 4.2.2 Village land ................................................................................................................................................. 9 4.2.3 Reserved land .............................................................................................................................................. 9 4.3 Land acquisition process for Chinangali II Block Farms ..................................................................................10 4.4 Method of Land acquisition ...............................................................................................................................10 4.5 Lively Hood Restoration mechanism ................................................................................................................10 5.0 CUT-OFF DATE ................................................................................................................................................11 6.0 GRIVANCES AND DISPUTE RESOLUTION ...................................................................................................12 6.1 Grievances Procedures ......................................................................................................................................12 6.2 Proposed Grievance Management and Redress Mechanism .........................................................................13 6.2.1 Grievance Redress Committees ..................................................................................................................13 6.2.2 Apeal ..........................................................................................................................................................13 6.2.3 Eligibility ....................................................................................................................................................14 7.0 IMPLEMENTATION SCHEDULE ......................................................................................................................15 RAP for Chinangali II Block Farm May, 2024 v 8.0 MONITORING PROGRAMME ...........................................................................................................................16 9.0 RAP BUDGET AND SCHEDULE .......................................................................................................................17 APPENDICES .............................................................................................................................................................18 Appendix I: Consent Letter from DED-Chamwino and Minutes of agreements with Community who sold land for Chinangali II Block Farm ............................................................................................................................................18 Appendix II: Land Tittle Deed for Chinangali II block farm ......................................................................................26 Appendix III: Sale Agreement between Chamwino District Council and Mega Beverage Limited ...........................30 Appendix IV: Sample Contract with PAPs on sale of Land ........................................................................................34 Appendix V(a): Letter from Chamwino District Council-Submission of Land Purchases report to the Ministry of Agriculture ..................................................................................................................................................................42 Appendix V(b): Names of PAPs who has received payments .....................................................................................43 Appendix V(c): Names of PAPs who have not received payments .............................................................................48 Appendix VI: Report on Funds Remittances to PAP ..................................................................................................49 LIST OF TABLES Table 1: Population at Chinangali II block farm and surrounding villages .................................................................. 5 Table 2: Population at Buigiri ward and Surrounding village ...................................................................................... 6 Table 3: PAPs within Chinangali II BBT farm ............................................................................................................ 8 Table 4: Budget for RAP Implementation ...................................................................................................................17 LIST OF PLATES Plate 1: Current land use .............................................................................................................................................. 6 RAP for Chinangali II Block Farm May, 2024 vi ABBREVIATIONS AfDB African Development Bank BBT-YIA Building a Better Tomorrow: Youth Initiatives for Agribusiness Program CDOs Community Development Organizations CSA Climate Smart Agriculture DPs Development Partners EIA Environmental Impact Assessment GDP Gross Domestic Product GOT Government of Tanzania LGA Local Government Authority MLHHSD Ministry of Land, Housing and Human Settlements Development MoA Ministry of Agriculture MoFP Ministry of Finance and Planning NEMC National Environment Management Council NGO Non-Governmental Organization PAP Project Affected Person NGOs Non-Governmental Organizations PO-RALG President’s Office - Regional Administration and Local Governments RAP Resettlement Action Plan ( RSs Regional Secretariats URT United Republic of Tanzania VEO Village Executive Officer RAP for Chinangali II Block Farm May, 2024 1 1.0 INTRODUCTION 1.1Project Background The Ministry of Agriculture is in the process of developing Chinangali II Block Farm in Chamwino district Council Dodoma Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm. The EIA documents indicated that the project will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. The important undertakings, land acquisition, farm clearing infrastructure development such as borehole drilling and water storage reservoir will ensure sustainable development of the farm in terms of water supply and crop production. Moreover, smallholder farmers in the surrounding villages will benefit from modern farming technologies and operations. The block farm is intended to support youth farmers aged between 18 and 40 years and they will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. Furthermore, the project will be advantageous to the private sector investors’ who have the insights knowledge of farm's operations. In addition, the government will enhance its tax base and benefit from tax collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Block Farms will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.2 Objective of the project The overall project objective is to promote the engagement of the identified Tanzanian youth in agriculture and agribusiness for sustainable improved livelihoods. This will be achieved through attaining the following strategic objectives: i) Youth to engage in agribusiness through effective communication for changing their negative behavior and attitude toward agriculture and agribusiness; ii) Youth through practical and hands on agribusiness and entrepreneurship skills development and access to new technologies; iii) Enhancing the youth in agribusiness through facilitating their access to productive resources, finance and markets; and iv) Facilitating and monitoring (M&E) of youth agribusiness for enhancing learning, partnerships/synergy, and efficient and effective utilization of resources. The Specific Objectives of Chinangali II projects are to: i) Engage up to 310 youths for training in agricultural production and agribusiness; ii) Develop a 1,552 acres block farm for various crop value chains; iii) Construct 38 Shamba houses and RAP for Chinangali II Block Farm May, 2024 2 iv) provide models for production and productivity enhancement through collaborative efforts of large farmers working together with youth 1.3 Project Justification The Government of Tanzania is encouraging large scale cultivation in order to boost the agricultural sector which is the backbone of the country’s economy. The initiative of block farming and value chain infrastructure development is linked to private sector initiatives to invest in the agricultural and rural development. Chinangali II Block Farm will provide models for production and productivity enhancement through collaborative efforts of large farmers working together for mutual benefits of youth. Participation of potential investors in new large scale commercial block farms is in line with the Ministry of Agriculture’s efforts to encourage private sector involvement in commercial agricultural development which is now taking place at a high pace. The poor response of private investors and the youth involvement in agriculture has mainly been due to the potential risks associated with the business. Among the risks are the possibility of not recovering the capital investment due to several factors such as crop failure due to poor rains, crop failure due to pests and diseases; the assurance on availability of water, land title deeds and poor market infrastructure. Since the involvement of the private sector investing in agriculture is very important for assurance of food security, significant contribution to national income and employment, the Ministry of Agriculture has taken a bold measure to leverage the youth and private sector as an incentive to invest in large scale commercial farming blocks. The establishment of Chinangali II block farm will have a number of significant positive impacts compared to the possible negative impacts. Borehole drilling and water storage reservoir development is one of the important undertakings to provide reliable water supply for crop production. Also, the crop will add value to the crops for better competitive market price within and outside the country. The smallholder farmers surrounding the project area will also benefit from the farm technology and operations. Youth farmers will access improved agricultural services like supply of inputs, farmers training, formation and strengthening of organizations and networks, processing of agricultural produce, and provision of loans and microfinance services. Technologies that will be disseminated to the identified youth include the use of improved seeds and varieties, water management systems, agro-mechanization, value addition techniques, and modern crop husbandry such as improved seeding, planting, weeding and fertilizer application. Value addition activities such as vegetables and fruits sorting and packagingwill encourage other youth and neighboring farmers to invest in crop production for increased income and food security. 1.4 Project Beneficiaries The primary beneficiaries of Chinangali II block farm are youth aged between 18 to 40 years old up to 310 youth (217 Male and 93 Female) will directly benefit from Chinangali II block farm. RAP for Chinangali II Block Farm May, 2024 3 Others beneficiaries include service providers both public and private sectors. For the case of private sector beneficiaries will include processors, input suppliers, traders, financial institutions, and communities in neighboring villages where the project will be implemented. On the other hand, for public sector beneficiaries of the project comprise research and academic institutions. The government will also benefit from the tax collection on the sale of the products from the farm. 1.5 Need for Resettlement Action Plan At Chinangali II the community in the proposed BBT farm occupied the land through customary land ownership which includes inheritance from the ancestors and purchasing from neighbours. The Village Council in Collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of the block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. This gave an opportunity for the community to sell their land for public use and obtained their concerns. A series of village assembly and village council meetings were conducted since March 2023 (Minutes in Appendix 1) with staff from Chamwino District Council along with visiting the proposed project area site on regular bases. These meetings came out with the decision that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village which was Tsh. 1,000,000/= per acre. The Total land acquired through purchasing is estimated to be 1,552 acres. The Ministry of Agriculture in collaboration with Chamwino district council prepared land purchasing contracts which were signed by each individual who volunteered to sell his/her land for BBT use at a market price. After purchasing processes were completed, the Land for BBT block farm at Chinangali II block farm was entitled to the right of occupancy to the Ministry of Agriculture in January 2024 for a term of ninety-nine (99) years. The Land is known as Plot No. 3 Block “c” situated at Chinangali II village in Chamwino District. The Land Title deed granted is No 91072 -DIR containing an area of 579.8 Hectares. According to the Urban Planning (Use Groups and Use Classes) Regulations, 2018. The land shall be used for urban farm purposes under user group “R” Use class “c”. However as of April 2024 some few community members 16 in number were yet to be paid. The AfDB mission which was in the Country from 3rd -12th April 2024 indicated the need to prepare a Resettlement Action Plan (RAP) for Chinangali II block farms to regularize and document the process for the resettlement of the Project Affected People (PAPs). The RAP will provide a road map for the manner in which displacement and resettlement issues were dealt with. Among the activities that would be undertaken for developing Resettlement Action Plan (RAP) include the following: RAP for Chinangali II Block Farm May, 2024 4 i) Assessment of the possible land acquisition process /resettlement impacts for the proposed block farms in accordance with national policies and legislations and AfDB’s Integrated Safeguards System (ISS 2023). ii) Consultation with the communities and project affected persons whenever necessary; iii) Assessing whether the land was purchased at the land market value iv) Compile documents on the land purchased contracts and the reasons for few PAPs who have not yet been compensated. 1.6 Objective of Resettlement Action Plan Considering the economic importance required for development of Chinangali II BBT farm and the people that were using the land for subsistence farming located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. The main objective of this RAP is to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: i) Lay down the agreed principles that were applied to the resettlement of the community ii) Document as far as possible, those people who sold their land for use by BBT project; iii) Identify if there are physical and /or economic displacement losses; iv) Describe the legal and institutional framework for dealing with displacement; v) Provide a general socio-economic profile of the affected persons living in areas where displacement is likely to occur; vi) Set out the criteria used to determine market price for purchase of Land vii) Identify and document Project Affected Persons (PAPs); 1.7 Methodology for Preparation of RAP The main methodology involved in preparation of this RAP, is based on data obtained from Chamwino district council, the Ministry of Agriculture, census, observation and consultation. The data from the project area were collected by the Consultant for the purpose of RAP preparation. The preparation of RAP involved various activities. The philosophical underpinning of the plan preparation is the use of a participatory approach of stakeholders including affected communities and PAPs. Among others, the methods and activities employed in the process of developing the RAP include: 1.7.1 Conducting Literature Review The filed visits were complemented by reviewing the existing literatures related to the resettlement. The literature review involved the identification of the applicable legal and administrative frameworks and policies of the United Republic of Tanzania, AfDB and the Environmental and Social Impact Assessment Report for the Chinangali II block farm 2024 RAP for Chinangali II Block Farm May, 2024 5 2.0 PROJECT DESCRIPTION 2.1 Location 2.1.1 General project location The project is located in Chamwino District which is one of the seven districts of Dodoma region. It lies on the central plateau of Tanzania in the western bearing along Dar es Salaam Road. The district lies between latitudes 40° S and 80° S and between longitudes 35° E and 37° E of Greenwich meridians. The district has a total area of 8,056 km. square. The District borders Dodoma City on the western front, Chemba, Kondoa District on the North Kongwa and Kiteto Districts on the East and Mpwapwa District and Iringa rural on the Southwest, also, Bahi District on south east front. Administratively the district council is divided into 5 divisions 36 wards, 107 villages and 814 hamlets. 2.2.2 Specific project Location Specifically, the proposed Chinangali II block farm is located at Mwegamile Village Buigiri ward in Chamwino District in Dodoma Region. The site is accessible through Dodoma-Dar es salaam highway, 56km from Dodoma City Center and 1.5km from the main road on the left side on the way to Morogoro. It is adjacent to the CHABUMA AMCOS grape farm and a private investor known as Mega Beverage Company Limited producing grapes as well. Table 1: Population at Chinangali II block farm and surrounding villages S/N Ward Villages Number of household Population 2022 Buigiri Buigiri 1,124 6,440 Chinangali II 750 2,308 Mwegamile 834 2,130 TOTAL 2,708 10,878 2.2 Overview of the project affected area The vegetation of the Project area is characterised by scattered woodland trees especially dominated by baobab trees (Adansonia), umbrella thorn tree (Acacia tortillis) and open grassland with very few miombo trees. The major food crops grown at Chinangali II village are sorghum, maize and finger millet. Cash crops are groundnuts, sunflower, sesame, and finger millet. At the project area, there are very few indigeneous tree species which might be endangered, however it is an ecological important to consider these vegetation cover species during construction phase. RAP for Chinangali II Block Farm May, 2024 6 Plate 1: Current land use 2.2.1 Characteristics of PAPs in Chinangali II BBT farm The population of Chinangali II village is dominated by Gogo ethnic group which covers about 95% of the village population while the remaining 5% is Kagulu and other small ethnic groups. Youth within the age between 15 and 35 are 506 (male 223 and female 286) which is 27% of the village population (Village population). Table 2: Population at Buigiri ward and Surrounding village Ward Villages Number of household 2012 population Projected 2022 population Buigiri Buigiri 1,124 4,915 6,440 Chinangali II 750 1,873 2,308 Mwegamile 834 2,085 2,130 TOTAL 2,708 8,873 10,878 2.2.3 House conditions There are no settlements in the project area. The settlement is concentrated at the village center. RAP for Chinangali II Block Farm May, 2024 7 3.0 LAND ACQUISITION PROCESS The Ministry of Agriculture requested the President’s Office Regional Administration and Local Government (PO-RALG) to identify areas suitable for establishment of large farms to be used for Building a Better Tomorrow Block Farms for youth. The PO-RALG further liaised with Chamwino District Council to identify suitable land for BBT Block Farms. Chamwino District Councils in collaboration with Buigiri Ward and Mwegamile Village Council in consultation with the Ministry of Lands, Housing and Human Settlements earmarked and allocated arable land for Chinangali II block farm. However; the land allocated for Chinangali II block farm was owned by individuals through inheritance from ancestors, rented or purchased which is common for most of village land ownership in Tanzania. The Land Act and Village Land Act (1999) create three categories of land namely i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. The Land within the proposed Chinangali II block farm falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chamwino District Council Land Officer there was no Certificates of Customary Rights of Occupancy (CCROs) within the project area. The Village Council in Collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of Chinangali II block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. This gave an opportunity to village leaders to meet the people who will be interested to sell their land for public use and to obtain their concerns. The Ministry of Agriculture in collaboration with Chamwino district council prepared land purchasing contracts which were signed by each individual who all volunteered to sell their land for BBT use (Refer attached contract samples in Appendix 1V). 3.1 Land purchase and price A series of village assembly and village council meetings were conducted since March 2023 (Minutes in Appendix 1) with staff from Chamwino District Council along with visiting the proposed project area site on regular basis. These meetings came out with an agreement that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village which was Tsh. 1,000,000/= per acre. The list of people who sold their land is 226 and the total land acquired through purchasing is estimated to be 1,552.3 acres. The list of people and their land sizes is attached as Appendix V (a) –(c). A comparative price check was also made with the private company who purchased land adjacent to the BBT project area in 2019. The MEGA BEVERAGE COMPANY bought the land at a price of Tsh. 500,000/= per acre. RAP for Chinangali II Block Farm May, 2024 8 3.2 Land Tittle Deed After fulfilling these requirements, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture for a term of ninety nine years (99) from January 2024. The Land is known as Plot No. 3 situated at Chinangali II Village in Chamwino District. The Land Title deed granted is No. 91072 DRL containing an area of 579.80 Hectares (Appendix II Certificate of Occupancy). According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for Urban Agriculture under user group “R” Use class “c”. Therefore, the proposed Chinangali II Block Farms are located in an area designated for agricultural production. Table 3: PAPs within Chinangali II BBT farm S/N Property Category of Impact Number of PAPs 1 Purchased Land Loss of agricultural land 1,552 acres Number of PAPs Livelihood 226 2 Residential Structure Temporary Houses 0 3 Entire residential structures House owners 0 Residential tenants 0 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners 7 Amount of funds set aside for land purchase 1,152,300,000 8 Number of PAPs paid and Amount 210 PAPs Tsh. 1,074,690,000 9 Number of PAPs not paid and Amount 16 PAPs Tsh. 77,610,000 Reason for not being paid is due to bank transfer logistic challenges for 16 PAPs. The District Council is liaising with the banks to solve the problem for payments to the remaining PAPs (Refer Appendix II for list of PAPs paid and not paid). Evidences of remittance are attached as Appendix III and a full list of remittance payment is attached as a separate document. RAP for Chinangali II Block Farm May, 2024 9 4.0 LEGAL AND INSTITUTIONAL FRAMEWORK FOR LAND ACQUISITION IN TANZANIA 4.1 Land Tenure and Ownership in Tanzania Land tenure and ownership in Tanzania is governed by statutes such as the 1977 Constitution, National Land Act No. 4 of 1999, Village Land Act No. 5 of 1999, Land Acquisition Act 1967, and Land Ordinance, 1923 Cap. 113. Land in Tanzania is owned by the state (vested in the President as a trustee). For the purpose of management of land under the land Act No. 4 of 1999 and all other laws applicable to land, public land in Tanzania is either categorised as:i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. 4.2 Land categories in Tanzania 4.2.1 General land The general Land in Tanzania is described as consisting of all land, which is neither village land nor reserved land. All urban land falls under this category, except land, which is covered by laws constituting reserved land, or that which is considered hazard land. General land is governed by the Land Act and, hence, is under the control and jurisdiction of the Commissioner for Lands. This ministerial key person has delegated much of the powers to local government land officers. Property rights can be created over general land in terms of a granted Rights of Occupancy for a period of 33, 66 or 99 years confirmed by a Certificate of Title. Longstanding occupation of land except on government land is recognized as conferring property rights. In the case of land acquisition all occupiers of land irrespective of whether they have a granted right of occupancy or not, are eligible to compensation. Granted rights of occupancy carry conditions including land development and the payment of land rent. Failure to abide with these conditions can lead to the loss of the right. 4.2.2 Village land This is defined as being the land falling under the jurisdiction and management of a registered village. As Tanzania consists of a vast countryside with only a few urban areas, most land in the country is village land. Village land is held under customary tenure and the government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. Customary tenure is akin to freehold. 4.2.3 Reserved land This is defined as land being reserved areas including environmental protection areas, such as national parks, forest reserves, wildlife reserves, and marine parks as well as areas intended and set aside for spatial planning and (future) infrastructure development. The Commissioner for Lands can convert land from one category to the other. By far the majority of land occupiers have no certificates of Land title deed in part because land has to be surveyed before it can be issued with a title deed. However, there is a lot of \"de facto\" recognition of property rights for the majority of land occupiers. RAP for Chinangali II Block Farm May, 2024 10 4.3 Land acquisition process for Chinangali II Block Farms The Land within the proposed Chinangali block farms falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chamwino District Council Land Officers there were no Certificates of Customary Rights of Occupancy (CCROs) within the proposed block farms. 4.4 Method of Land acquisition The Land was purchased from the community at a Market price 4.5 Lively Hood Restoration mechanism There is neither legal requirement nor regulation for restoring livelihoods or providing assistance towards the restoration of such livelihoods in Tanzania. Those who sold their land will continue to sustain their lively hood through other land they occupy within the village. The land which was purchased was not fully utilized by the owners as there were few farm plots within the proposed BBT area. RAP for Chinangali II Block Farm May, 2024 11 5.0 CUT-OFF DATE The actual number of affected PAPs and their land sizes was identified within the land to be acquired for the Chinangali II BBT farm. The cut-off date for PAPs is the date the respective PAPs receive the remittance payments of the funds according to the agreed market price and the size of the land owned. Therefore, the overall cut of date was July 2023 which was communicated to PAPs during land size determination and sales agreement signed. Any person who undertakes any development activity in the demarcated project area after the cut-off date will not be eligible for payments. It should, however be noted that the implementation of the cut-off date should also be observed by project implementer who is required to pay PAPs once the land holding size has been approved and sale agreement signed. This RAP recommends that the project implementer needs to have frequent communication with PAPs through Chinangali Village Government Officials to update PAPs on when they should expect to receive their funds. or any other changes associated with implementation of the project. RAP for Chinangali II Block Farm May, 2024 12 6.0 GRIVANCES AND DISPUTE RESOLUTION 6.1 Grievances Procedures The RAP will be made available to the public, the appeal structures at various levels, specifying the responsible parties and their response time. Before starting with the grievance sequence and where appropriate (i.e. in case of complaints of minor entity), aggrieved parties will take their complaints to the community or traditional meetings for dispute resolution. If need arises, the local NGOs will be contracted and involved to hear complaints and attempt to affect a resolution before they enter the legal and administrative appeals hierarchy. In normal circumstances, grievances will be dealt with either statutory through courts and tribunals, or administratively using government or traditional institutions. Using the courts in determining grievances related to and resettlement is not the best option as it is tedious, costly and lengthy. The simple and affordable procedures in place to lodge complaints or claims are as elaborated hereunder. Local authorities could handle the disputes and grievances in the first place. In summary those seeking redress will have to notify local government and ward offices. If this fails, disputes can be referred to district level. Resolution of disputes shall be speedy, just and fair and local NGOs that are conversant with these issues could be engaged by the project. The first stop, the Village Grievance Redress Committee (VGRC), has one week to resolve the dispute. If a given dispute is not resolved in one week it will go to the District Grievance Redress Committee (DGRC), which has two weeks to resolve the dispute. Unresolved disputes shall be referred to appropriate level of land courts established by law. If local courts are unable to resolve the disputes application can be made to the High Court of Appeal of Tanzania, this is the highest appellate judge in the system and its decision will be final. Potential grievances and disputes that arise during the course of implementation of the resettlement and compensation programme are often related to the following issues: i) Inventory mistakes made during census survey as well as inadequate valuation of properties; ii) Mistakes related to identification and disagreements on boundaries between affected iii) individual(s) and specifying their land parcels and associated development; iv) Divorces, successor and the family issues resulting into ownership dispute or dispute share between in heirs or family; v) Disputed ownership of given Assets (two or more affected individual(s) claim on the same); RAP for Chinangali II Block Farm May, 2024 13 6.2 Proposed Grievance Management and Redress Mechanism The mechanisms for grievance management and redressed mechanisms are to be \"affordable and accessible,\" and third parties independent of the implementers should be available at the appropriate point in the process. The grievance procedure will be simple, administered in the first instance at the local level to facilitate access, flexibility and open to various proofs taking into account the need for speedy, just and fair resolution of their grievances. The process suggested for resolving individual grievances is presented below. 6.2.1 Grievance Redress Committees There are two committees which will be involved in redressing grievances arising from the PAPs in the project area; a) Village Grievance Redress Committee (VGRC) and, District Grievance Redress Committee (DGRC) known as Social Service Committee (SSC) Composition of VGRC VGRC is comprised of: i) Village Chairperson, ii) Village Executive Officer (VEO), iii) Representative from the PAPs, iv) Community Development Officer from the Ward, Representative from NGO to be identified b) District Grievance Redress Committee (DGRC) Composition of DGRC DGRC is comprised of: i) District Commissioner Chairman ii) District Land office Member, iii) District Valuer; iv) RAP Implementing Agency Member v) PAP representative/ local NGO Member vi) Representative of Regional Secretariat Member 6.2.2 Apeal Land related grievances shall be resolved using the land courts established under the Land Disputes Courts Act. No. 2 of 2002 with its regulations. That is Village Land Council; the Ward Tribunal; the District Land and Housing Tribunal; the High Court (Land Division) and The Court of Appeal of Tanzania. RAP for Chinangali II Block Farm May, 2024 14 6.2.3 Eligibility The eligible individual(s) are those who sold their land to the Ministry of Agriculture and were directly affected through Chinangali II BBT farm development and they had to have land plots within the boundaries of the farm. The PAPs were considered irrespective of their tenure status, with respect to land that they occupy or use provided they occupy or use the affected land prior to the cut-off-date. Cut-off date for eligibility to payments settlement. RAP for Chinangali II Block Farm May, 2024 15 7.0 IMPLEMENTATION SCHEDULE Implementation of RAP consists of several resettlement activities. Efficient implementation of RAP activities requires several measures to be taken prior to startup of implementation. These include setting up of relevant committees at district level, hiring of NGO or consultant etc. In principle project civil works may not start until all PAPs determined to be entitled for ressettlement are duly fully paid out. The land acquisition took place after payments were received by the PAPs prior to land take for BBT only 16 PAPs have not received their payouts due. The time frame of 3 months on the implementation schedule ensures that all PAPs will have received their funds . • Finalization and payements to the remaining 16 PAPs • RAP disclosure and circulation; • Grievance Redress Mechanisms set at Mtaa and District Levels (Grievances Redress Process) • Monitoring and evaluation. RAP for Chinangali II Block Farm May, 2024 16 8.0 MONITORING PROGRAMME RAP implementation is one of the central components of this project its monitoring is critical to solve challenges or obstacles in the areas of PAPs relocation. The monitoring and evaluation procedures will include external and internal evaluation of the compliance of the actual implementation with objectives and methods as agreed, and monitoring of specific situations. 8.1 Internal Monitoring The Project implementation unit will be responsible for internal monitoring while the Consultants may provide technical assistance in implementing RAP. At the conclusion of the RAP implementation the full information on every individual impacted by the project will provide the evaluation of status of PAPs and measuring Resettlement Plans (RAP) performance. Several indicators are used to measure these impacts, namely: a comparison of income levels before-and-after the project; changes in standards of housing and living conditions; access to various social services i.e. health care, education, water supply, road, markets etc. and improvements in level of participation in sub-project activities. Measures to verify these basic indicators would be mainly to compare these new conditions with pre-project conditions. Monitoring will ensure the following: • Verification of payments to the remaining 16 PAPs; • Information dissemination has been carried out; • Effective operation of grievances Committee; • BBT Secretariat shall be responsible for monitoring day to day RAP activities; • The Consultants shall be responsible for overall project level monitoring. RAP for Chinangali II Block Farm May, 2024 17 9.0 RAP BUDGET AND SCHEDULE Table 4: Budget for RAP Implementation S/N Resettlement Activity Activity Cost (Tsh) Source of fund/ Responsibility Timeline/ Deadlines 1. Payments to remaining PAPs 77,610,000 MoA May 2024 2 Grievance handling 1,000,000 MoA Through RAP implementation 3. Management & administration 5,000,000 MoA Through RAP implementation 4 Monitoring & evaluation 10,000,000 MoA Through RAP implementation TOTAL 103,610,000 RAP for Chinangali II Block Farm May, 2024 18 APPENDICES Appendix I: Consent Letter from DED-Chamwino and Minutes of agreements with Community who sold land for Chinangali II Block Farm RAP for Chinangali II Block Farm May, 2024 19 RAP for Chinangali II Block Farm May, 2024 20 RAP for Chinangali II Block Farm May, 2024 21 RAP for Chinangali II Block Farm May, 2024 22 RAP for Chinangali II Block Farm May, 2024 23 RAP for Chinangali II Block Farm May, 2024 24 RAP for Chinangali II Block Farm May, 2024 25 RAP for Chinangali II Block Farm May, 2024 26 Appendix II: Land Tittle Deed for Chinangali II block farm RAP for Chinangali II Block Farm May, 2024 27 RAP for Chinangali II Block Farm May, 2024 28 RAP for Chinangali II Block Farm May, 2024 29 RAP for Chinangali II Block Farm May, 2024 30 Appendix III: Sale Agreement between Chamwino District Council and Mega Beverage Limited RAP for Chinangali II Block Farm May, 2024 31 RAP for Chinangali II Block Farm May, 2024 32 RAP for Chinangali II Block Farm May, 2024 33 RAP for Chinangali II Block Farm May, 2024 34 Appendix IV: Sample Contract with PAPs on sale of Land RAP for Chinangali II Block Farm May, 2024 35 RAP for Chinangali II Block Farm May, 2024 36 RAP for Chinangali II Block Farm May, 2024 37 RAP for Chinangali II Block Farm May, 2024 38 RAP for Chinangali II Block Farm May, 2024 39 RAP for Chinangali II Block Farm May, 2024 40 RAP for Chinangali II Block Farm May, 2024 41 RAP for Chinangali II Block Farm May, 2024 42 Appendix V(a): Letter from Chamwino District Council-Submission of Land Purchases report to the Ministry of Agriculture RAP for Chinangali II Block Farm May, 2024 43 Appendix V(b): Names of PAPs who has received payments RAP for Chinangali II Block Farm May, 2024 44 RAP for Chinangali II Block Farm May, 2024 45 RAP for Chinangali II Block Farm May, 2024 46 RAP for Chinangali II Block Farm May, 2024 47 RAP for Chinangali II Block Farm May, 2024 48 Appendix V(c): Names of PAPs who have not received payments RAP for Chinangali II Block Farm May, 2024 49 Appendix VI: Report on Funds Remittances to PAP RAP for Chinangali II Block Farm May, 2024 50 RAP for Chinangali II Block Farm May, 2024 51 RAP for Chinangali II Block Farm May, 2024 52 RAP for Chinangali II Block Farm May, 2024 53 RAP for Chinangali II Block Farm May, 2024 54 RAP for Chinangali II Block Farm May, 2024 55 RAP for Chinangali II Block Farm May, 2024 56 RAP for Chinangali II Block Farm May, 2024 57 RAP for Chinangali II Block Farm May, 2024 9"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":165,"cells":{"data":{"kind":"string","value":"# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE Government City-Mtumba P. O BOX 2182 40487 DODOMA Email: ps@kilimo.go.tz BUILDING A BETTER TOMORROW: YOUTH INITIATIVES FOR AGRIBUSINESS (BBT-YIA) THE PROPOSED ESTABLISHMENT OF MAPOGORO BLOCK FARM No. 59569 - MBYLR LOCATED AT MAPOGORO VILLAGE, CHOKAA WARD, CHUNYA DISTRICT COUNCIL IN MBEYA REGION RESETTLEMENT ACTION PLAN CONSULTANT Eng. Lait A.Simukanga Registered Environmental Consultant, Reg. No NEMC/EIA/0032 Practicing License No. NEMC/PC/EIA/2021/0020 Kimara Street Plot No. 0095, P.O. Box 13033, DAR ES SALAAM, Email: lsimukanga@gmail.com Mobile: +255 754 271175 Date of Submission: 1 May 2024 RAP Mapogoro BBT farm April 2024 i TABLE OF CONTENT LIST OF TABLES\\ ........................................................................................................................ ii LIST OF PLATES .......................................................................................................................... ii ABBREVIATIONS ....................................................................................................................... iii 1.0 INTRODUCTION ..................................................................................................................... 1 1.1 Project Background ................................................................................................................ 1 1.2 Objective of Resettlement Action Plan .................................................................................. 1 1.3 Project Rationale .................................................................................................................... 2 1.4 Project Beneficiaries .............................................................................................................. 2 1.5 Need for Resettlement Action Plan........................................................................................ 3 1.6 Methodology for Preparation of RAP .................................................................................... 3 1.6.1 Conducting Field Visits ...................................................................................................... 3 1.6.2 Conducting Literature Review ............................................................................................ 4 2.0 PROJECT DESCRIPTION ....................................................................................................... 5 2.1 Location ................................................................................................................................. 5 2.1.1 General project location ................................................................................................ 5 2.1.2 Specific Location of the project....................................................................................... 5 2.2 Overview of the project affected area .................................................................................... 5 2.2.1 Characteristics of PAPs in Mapogoro BBT farm ............................................................ 5 2.2.2 Ethinic groups .................................................................................................................. 5 2.2.3 House conditions ............................................................................................................. 6 2.3 Potential impacts .................................................................................................................... 7 2.3.1 Loss of land rights ............................................................................................................. 7 2.3.2 Loss of Utilities ............................................................................................................... 7 3.0 CONSULTATION WITH PAPs AND COMMUNITY PARTICIPATION ............................ 8 3.1 Identification of PAPs for Consultation ................................................................................. 8 3.2 Methods of Stakeholder Participation .................................................................................... 8 3.2.1 Notification to PAPs ........................................................................................................ 9 3.2.2 Official meetings with Village leaders ............................................................................ 9 3.2.3 Meetings with District officials ....................................................................................... 9 4.0 COMPENSATION OF PAPs.................................................................................................. 10 5.0 LEGAL AND INSTITUTION PRAMEWORK FOR LAND ACQUISITION IN TANZANIA .................................................................................................................................. 11 5.1 Land Tenure and Ownership in Tanzania ............................................................................ 11 5.2 Land categories in Tanzania ................................................................................................ 11 5.2.1 General land ................................................................................................................... 11 RAP Mapogoro BBT farm April 2024 ii 5.2.2 Village land ................................................................................................................... 11 5.2.3 Reserved land ................................................................................................................ 11 5.3 Land acquisition process for Mapogoro Block Farms ......................................................... 12 5.4 Method of Compensation ..................................................................................................... 12 6.0 GRIVANCES AND DISPUTE RESOLUTION ................................................................. 14 6.1 Grievances Procedures ......................................................................................................... 14 6.2 Proposed Grievance Management and Redress Mechanism ............................................ 15 6.2.1 Grievance Redress Committees ..................................................................................... 15 6.2.2 Apeal .............................................................................................................................. 15 6.2.3 Eligibility ....................................................................................................................... 15 7.0 LIVELY HOOD RESTORATION .................................................................................... 16 8.0 CUT-OFF DATE .................................................................................................................. 17 9.0 IMPLEMENTATION SCHEDULE ....................................................................................... 18 10.0 MONITORING PROGRAMME .......................................................................................... 19 11.0 RAP BUDGET AND SCHEDULE ...................................................................................... 20 APPENDICES ............................................................................................................................... 21 Appendix I: Map indicating Location of PAPs within the Mapogoro BBT farm ......................... 21 Appendix II: List of PAPS with thir signatures who agreed to be re-settled at Mapogoro BBT farm ............................................................................................................................................... 22 Appendix III: Map indicating area for re-settlement of PAPs ...................................................... 26 Appendix IV: Report on PAP Households Inventory at Mapogoro BBT Farm ........................... 27 Appendix V: Names of PAPs, Number of Tenants, Year encroached the land and land method of Land acquisition (Typed) .............................................................................................................. 29 Appendix VI: Translations of Appendix IV .................................................................................. 31 Appendix VII: Proposal for Land Range Clusters for PAPs ......................................................... 33 Appendix VII: Map indicating Areas where PAPs will be re-located .......................................... 37 LIST OF TABLES\\ Table 1: Identification of individula PAPs ...................................................................................... 6 Table 2: Areas identified and allocated for re-settlement of agro-pastoralists .................................... 10 Table 3: Budget for RAP Implementation .................................................................................... 20 LIST OF PLATES Plate 1: Typical Sukuma and Mang’ati settlement at the middle of Mapogoro BBT farm ............ 6 RAP Mapogoro BBT farm April 2024 iii ABBREVIATIONS AfDB African Development Bank BBT-YIA Building a Better Tomorrow: Youth Initiatives for Agribusiness Program CDOs Community Development Organizations CSA Climate Smart Agriculture DPs Development Partners EIA Environmental Impact Assessment GDP Gross Domestic Product GOT Government of Tanzania LGA Local Government Authority MLHHSD Ministry of Land Housing and Human Settlement Development MLHHSD Ministry of Land, Housing and Human Settlements Development MoA Ministry of Agriculture MoFP Ministry of Finance and Planning NEMC National Environment Management Council NGO Non-Governmental Organization OP/BP Operation Policy/Bank Policy PAP Project Affected Person NGOs Non-Governmental Organizations PO-RALG President’s Office - Regional Administration and Local Governments RAP Resettlement Action Plan ( RSs Regional Secretariats URT United Republic of Tanzania VEO Village Executive Officer RAP Mapogoro BBT farm April 2024 1 1.0 INTRODUCTION 1.1 Project Background The Ministry of Agriculture is in the process of developing Mapogoro Block Farms in Chunya district Mbeya Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm. The EIA documents indicated that the projects will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. The important undertakings, land acquisition, farm clearing infrastructure development such as borehole drilling and water storage reservoir will ensure sustainable development of the farm in terms of water supply and crop production. Moreover, smallholder farmers in the surrounding villages will benefit from modern farming technologies and operations. The block farm is intended to support for youth farmers aged between 18 and 40 years and they will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. Furthermore, the project will be advantageous for the private sector investors’ who have the insights knowledge of farm's operations. In addition, the government will enhance its tax base and benefit from tax collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Block Farms will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.2 Objective of Resettlement Action Plan Considering the economic importance required for development of Mapogoro BBT Farm and few settlement that are located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. The main objective of this RAP is to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: i) Identification of Project Affected Persons (PAPs); ii) Identification of land parcels to be acquired for development of project infrastructure; iii) Collection of qualitative and quantitative baseline socio-economic data of PAPs; iv) Establishment of entitlements to PAPs; v) Collection of preference for resettlement; vi) Collection of comments and perceptions of the PAPs with regard to the project; vii) Involve PAPs and other stakeholders in developing a plan for physical relocation viii) Provide information that will be used to implement the resettlement plan; and ix) Outline institutional arrangements for the implementation of the RAP; and x) Development of a Resettlement Action Plan (RAP) RAP Mapogoro BBT farm April 2024 2 1.3 Project Rationale The Government of Tanzania is making concerted efforts to boost the country's economy by encouraging large-scale cultivation in the agricultural sector, which serves as its backbone. To facilitate this, the introduction of block farming and the development of value chain infrastructure are linked to private sector initiatives aimed at investing in agricultural and rural development. The Mapogoro Block Farm represents a model for production and productivity enhancement, emphasizing collaborative efforts among large farmers to benefit the youth. Encouraging potential investors to participate in new large-scale commercial block farms aligns with the Ministry of Agriculture's mission which is to promote private sector involvement in commercial agricultural development, which is rapidly gaining momentum. The low response from private investors and youth engagement in agriculture can be attributed to the perceived risks associated with the business. Such risks include capital investment, assurance of water availability, land availability, and the availability of marketing infrastructure. Recognizing the critical importance of the private sector involvement in agriculture for ensuring food security, contributing significantly to national income, and generating employment opportunities, the Ministry of Agriculture has taken decisive action to leverage the participation of the youth and the private sector by providing incentives for investing in large-scale commercial farming blocks. The Mapogoro Block Farm Project will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. Important undertakings, such as borehole drilling and water storage reservoir development, will ensure a reliable supply of water for crop production. Moreover, smallholder farmers in Mapogoro will benefit from modern farming technologies and operations. Youth farmers will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. 1.4 Project Beneficiaries The main beneficiaries of Mapogoro block farm are the youth and women aged between 18 to 40 years old. About 1,000 to 4,000 youths (1400-2800 Male and 600-1200 Female) will be engaged at Mapogoro BBT Farm through direct and indirect employment. Various service providers from both the public and the private sectors will benefit from the project through availability of the market for their services. The private sector beneficiaries will include processors, input suppliers, traders, financial institutions, and communities in neighboring villages where the project will be implemented. These entities will experience positive effects such as improved incomes from the project's activities and outcomes. Furthermore, the project will be advantageous for the public sector beneficiaries, particularly research and academic institutions, as they can gain valuable insights and knowledge from the farm's operations. In addition, the government will enhance its tax base and benefit from tax RAP Mapogoro BBT farm April 2024 3 collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Mapogoro Block Farm will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.5 Need for Resettlement Action Plan At Mapogoro block farm in Chunya district the land is open and dominated by Miombo wood land under the village government council. Since the land was planned for Agriculture, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture and Chunya District Council as occupies of the Land in common and equal shares for a term of ninety nine years (99) from 6th March 2023. The Land is known as Plot No. 1573 situated at Mapogoro Village in Chunya District. The Land Title deed granted is No. 59568 MBYLR containing an area of 11,007 Hectares. According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for farm purposes under user group “R” Use class “C”. Therefore, the proposed Mapogoro block farms is located in an area designated for agricultural activities. Within the proposed Mapogoro block farm there are few Agro-Pastoralist -about 51 households invaded the land by clearing and established settlement known as “bomas”. The AfDB mission which was in the Country from 3rd -12th April 2024 indicated the need to prepare Resettlement Action Plan (RAP) for Mapogoro block farm which would entail agreed plan for the resettlement for Project Affected People (PAPs). The RAP will provide a road map for the manner in which displacement and resettlement issues were resolved. 1.6 Methodology for Preparation of RAP The Resettlement Action Plan (RAP) covers relocation and replacement (in kind,) of the agro- pastoralist who will be affected by the project implementation. The methodology involved in preparation of this RAP, is based on data obtained from the study, census, observation and consultation. The data from the project area were collected by the Ministry of Agriculture, Mbeya Regional Secretariat and Chunya District Council (Land Officer and Agricultural Officer) for preparation of RAP. The preparation of RAP involved various activities. The philosophical underpinning of the plan preparation is the use of a participatory approach of stakeholders including affected communities and PAPs. Among others, the methods and activities employed in the process of developing the RAP included: 1.6.1 Conducting Field Visits The field visit to project area was done from 8-17 April 2024 and RAP was finalized towards the end of April 2024. The field visits were essential to fully visualize the project site capture RAP Mapogoro BBT farm April 2024 4 biophysical environment and the socio-economic conditions in the project area. In the field, among others, the project informations were collected from various sources including Mbeya Regional Secretariat and Chunya District Executive Director’s Officer. The field visits were conducted to identify the people to be affected by the project. During the field visits, the following tasks were performed: Observation of social and physical setting of the PAPs; i) Inventory and confirmation of number of PAPs in the project area (Name of head of household, number of residents); ii) Status of land ownership; iii) Structures within the proposed block farm iv) Held interviews and discussions with officials from the project area and local government including Village Government officials; v) Held interviews with the affected people and other community members in the project area; vi) Observed people's activities and learn their perception on the proposed project; and vii) Pick Coordinates of the settlements 1.6.2 Conducting Literature Review The filed visits were complemented by reviewing the existing literatures related to the resettlement. The literature review involved the identification of the applicable legal and administrative frameworks and policies of the United Republic of Tanzania, AfDB and the Environmental and Social Impact Assessment Report for the Mapogoro farm 2024. RAP Mapogoro BBT farm April 2024 5 2.0 PROJECT DESCRIPTION 2.1 Location 2.1.1 General project location The project is loacted in Chunya District council which is one of the seven (7) district councils of Mbeya region of Tanzania. Other councils are Mbarali, Rungwe, Kyela, Mbeya Rural, Busokelo and Mbeya City. It is situated in the North-Western part of Mbeya Regional Headquarter and it lies between latitudes 7° and 9° South of the Equator and 32° and 34° Longitudes East of Greenwich Meridians. The total area of the district covers 13,149 square kilometers. The district is bordered by Singida and Tabora regions to the North; Iringa region and Mbarali district to the East; Songwe and Mbeya districts to the South; Rukwa region and lake Rukwa to the West. Administratively, the district council is subdivided into 2 divisions namely Kiwanja and Kipembawe, 20 wards, 43 Villages, and 233 hamlets. This organizational structure ensures effective governance and service delivery to various communities within the district. 2.1.2 Specific Location of the project The proposed Mapogoro block farm is situated at Wafugaji hamlet within Mapogoro Village, Chokaa ward, Chunya District in Mbeya Region. The site is accessible through Chunya - Tabora highway, being located approximately 13 kilometers from Chunya bus stand and 19 kilometers from Mapogoro Village center to Mapogoro BBT farm. 2.2 Overview of the project affected area 2.2.1 Characteristics of PAPs in Mapogoro BBT farm Thorough investigation was done in the project are by picking co-oridnates of each PAPs settelement in the project area. A total number of 51 Households were identified and recording on a Map (Appendix I.). These PAPs invaded/encroched the area at different time from 1998 to 2021 (Attachement in Appendix V). All PAPs identified were pastrolalist with temporaly shelters as indicated in the photographs below. Their main activities is grazing and growing subsistance crops such as sweet potaotes, sughum and maize in small plots. 2.2.2 Ethinic groups Keeping large number of livestock is not a native tribes’ practice in the area. It is a practice of the new tribes who come with large herds from other places of the country and settled in the area mainly the Mang’ati, Mbulu, and Sukuma in search for grazing land and water. They keep different types of livestock including cattle, goats, donkeys and sheep which are largely kept on the peripheral of the Village agricultural lands to avoid conflict between farmers and pastoralists and ensure sustainable grazing practices. Indeed, the Village has land use planning being utilized firmly. Other animals kept in small numbers include pigs and domesticated birds - chicken and ducks kept for meat or eggs or both. The Sukuma are agro-pastoralists i.e. they concurrently grow crops for food production and livestock for income generation and sustenance while the Mang’ati and Mbulu ethnic groups are RAP Mapogoro BBT farm April 2024 6 pastoralists majorly. Livestock keeping is mainly carried out through freely or continuous grazing practices, where the animals are allowed to move from one area to another in search of pasture and water. During wet seasons, livestock graze on fallow fields amongst the cultivated ones while on dry seasons when natural grasses become scarce, animals feed on any remaining crop residues in the harvested farms or moved to Usangu plain and Lake Rukwa basin to meet their dietary needs. This is a coping livelihood strategy to livestock keepers for better management of livestock during times of limited resources. 2.2.3 House conditions There are no permanent settlement in the project area. The habitations are temporaly made of timber and thatched with grass. There are no toilet facilites as the agro-pastoralist take the advantage of bushes. The settelement is sparcely located ranging from 500m to 1km apart. Plate 1: Typical Sukuma and Mang’ati settlement at the middle of Mapogoro BBT farm Table 1: Identification of individual PAPs S/N Property Category of Impact Number of PAPs 1 Land Encroached/Invaded land 2 Residential Structure Temporary Houses 51 3 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners RAP Mapogoro BBT farm April 2024 7 2.3 Potential impacts Social dislocation and displacement will occur due to land needed for development of Mapogoro BBT farm. The agro-pastoralist livelihoods will be affected in one way or another. The houses to be affected in the project area, most of them are temporary built with locally available materials such as grass, poles and timber. No burnt bricks, blocks or and corrugated iron sheets. The affected houses/structures are used as shelters by the pastoralist can be easily erected once relocated. 2.3.1 Loss of land rights For the project implementation, 51 households/ PAPs in the proposed BBT farm will be affected by the project implementation. Preference shall be given to land-based resettlement strategies for displaced persons whose livelihoods are land-based. These strategies will include resettlement on public land, acquired for resettlement at Masiano hamlet for residence and Shoga and Mapogoro grazing cluster. Whenever replacement land is offered, the PAPs will be provided with land which has a combination of productivity potential, pasture, water and other factors that are at least equivalent to the advantages of the land acquired for BBT farm. Adequate land for compensation was demonstrated and documented (Appendix III), the PAPs were satisfied with the proposed compensation arrangements. 2.3.2 Loss of Utilities There are no utilities such as water supply pipes, electricity reticulation poles, telephone cables and fibers in the project area. The PAPs were using natural water course to get water and dug shallow wells on dry water ways. RAP Mapogoro BBT farm April 2024 8 3.0 CONSULTATION WITH PAPs AND COMMUNITY PARTICIPATION Preparation of Resettlement Action Plan requires regular consultation with PAPs. PAPs in this case are defined as stakeholders including any individual or group affected by the project negatively including the host community. PAPs were identified through survey and demarcation of BBT farm required to be cleared-off human activities during farm preparation these were further confirmed through consultations with the village administrations who keep registers of all village members. These PAPs were notified and were consulted on site one by one and signed an agreement to be re-settled to three identified areas known as Shoga and Mapogoro Mazimbo, Mafyeko and Butimanyanga, Supa and Kambi Katoto (See Table 2 below The objectives of PAP participation and consultation were: to i) Ensure transparency in all activities related to the resettlement and its potential impacts; ii) Share fully the information about the proposed project, its components and activities; iii) Obtain information about the needs and priorities of the various stakeholders, as well as information about their reactions; iv) Minimize conflicts and delays in implementation in relation to resettlement; v) Involve PAP at large together with their responsible institutions and organizations in the project design and planning; vi) Information dissemination to the PAPs about the project and resettlement; and vii) Understanding perceptions of PAPs towards the project 3.1 Identification of PAPs for Consultation The site visits were carried out in December 2023 where preliminary identification of PAPs falling within the demarcated farm boundaries were identified. Adequate information on the site issues related to the Resettlement Action Plan were collected, identification of spatial boundaries and identification of all stakeholders who will be affected by the project were done in April 2024. The following stakeholders were identified and consulted: i) Local governments; ii) Chunya District Council; iii) Chokaa Wards; and iv) Mapogoro Village government Officials 3.2 Methods of Stakeholder Participation PAPs interviews and consultations were the main methods followed during the process of this Resettlement Action Plan. The team involved the key identified stakeholders in order to generate issues of concern in relation to project implementation. In respect of the intended project activities, the PAPs that were consulted raised one major concern on availability of alternative land for their livestock. The concerns were addressed adequately by authorities in charge and local leadership who indicated that a Land-Use plan had been developed to guide proper landuse and minimize conflicts while maximizing benefits. Proposed grazing/ranching zones had been identified in several areas that the PAPs will be relocated. RAP Mapogoro BBT farm April 2024 9 3.2.1 Notification to PAPs PAPs were notified prior meeting with them. Notifications were through use of mobile phone communication and physical visits. 3.2.2 Official meetings with Village leaders Village officials including Chairperson, Village Executive Officer (VEO) and committee members were invited and participated effectively. 3.2.3 Meetings with District officials The Chunya District Council officials were notified and consulted. Open discussions were applied during meeting with them. RAP Mapogoro BBT farm April 2024 10 4.0 COMPENSATION OF PAPs Land-for-land replacement or compensation was the PAP’s preference. Land-for-land replacement shall be of maximum plot of acceptable size under the relevant law(s) or a plot of equivalent size, whichever is larger, in the nearby allocated land for agro-pastoralists. Resettlement area with adequate physical infrastructure systems for livestock keeping such as cattle troughs and cattle dips. Table 2: Areas identified and allocated for re-settlement of agro-pastoralists S/N Name of allocated grazing land Size (Ha) 1 Shoga and Mapogoro 23,563.24 2 Mazimbo,Mafyeko and Butimanyanga 49.626.36 3 Supa and Kambi Katoto 37.626.36 RAP Mapogoro BBT farm April 2024 11 5.0 LEGAL AND INSTITUTION FRAMEWORK FOR LAND ACQUISITION IN TANZANIA 5.1 Land Tenure and Ownership in Tanzania Land tenure and ownership in Tanzania is governed by statutes such as the 1977 Constitution, National Land Act No. 4 of 1999, Village Land Act No. 5 of 1999, Land Acquisition Act 1967, and Land Ordinance, 1923 Cap. 113. Land in Tanzania is owned by the state (vested in the President as a trustee). For the purpose of management of land under the land Act No. 4 of 1999 and all other laws applicable to land, public land in Tanzania is either categorised as:i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. 5.2 Land categories in Tanzania 5.2.1 General land The general Land in Tanzania is described as consisting of all land, which is neither village land nor reserved land. All urban land falls under this category, except land, which is covered by laws constituting reserved land, or that which is considered hazard land. General land is governed by the Land Act and, hence, is under the control and jurisdiction of the Commissioner for Lands. This ministerial key person has delegated much of the powers to local government land officers. Property rights can be created over general land in terms of a granted Rights of Occupancy for a period of 33, 66 or 99 years confirmed by a Certificate of Title. Longstanding occupation of land except on government land is recognized as conferring property rights. In the case of land acquisition all occupiers of land irrespective of whether they have a granted right of occupancy or not, are eligible to compensation. Granted rights of occupancy carry conditions including land development and the payment of land rent. Failure to abide with these conditions can lead to the loss of the right. 5.2.2 Village land This is defined as being the land falling under the jurisdiction and management of a registered village. As Tanzania consists of a vast countryside with only a few urban areas, most land in the country is village land. Village land is held under customary tenure and the government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. Customary tenure is akin to freehold. 5.2.3 Reserved land This is defined as land being reserved areas including environmental protection areas, such as national parks, forest reserves, wildlife reserves, and marine parks as well as areas intended and set aside for spatial planning and (future) infrastructure development The Commissioner for Lands can convert land from one category to the other. By far the majority of land occupiers have no certificates of Land title deed in part because land has to be surveyed before it can be issued with a title deed. However, there is a lot of \"de facto\" recognition of property rights for the majority of land occupiers RAP Mapogoro BBT farm April 2024 12 5.3 Land acquisition process for Mapogoro Block Farms The Land within the proposed Mapogoro block farms falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chunya District Council Land Officers there were no Certificates of Customary Rights of Occupancy (CCROs) within the proposed block farms. The Ministry of Agriculture requested the President’s Office through the Regional Administration and Local Government (PO-RALG) to identify areas suitable for establishment of a large farm to be used for Building Better Tomorrow Block Farms for the youth. The PO- RALG further liased with Chunya District Council to identify suitable land for BBT Block Farms within the district. Chunya District Council in collaboration with Mapogoro Village Government in consultation with the Ministry of Lands, Housing and Human Settlements earmarked and allocated arable land for Mapogoro Block Farm. After fulfilling these requirements, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture and Chunya District Council as occupies of the Land in common and equal shares for a term of ninety nine years (99) from 6th March 2023. The Land is known as Plot No. 1573 situated at Mapogoro Village in Chunya District. The Land Title deed granted is No. 59568 MBYLR containing an area of 11,007 Hectares (Appendix IV Certificate of Occupancy). According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for farm purposes under user group “R” Use class “c”. Therefore, the proposed Mapogoro block farms is located in an area designated for agricultural production. 5.4 Method of Compensation Compensation for PAPs depending on agro-pastrol activities will be land-based compensations. Land-based strategies include the provision of replacement land, ensuring greater security of tenure, and/or upgrading livelihoods of people to be resettled without legal land titles. The replacement land will address the need of PAPs who are mainly livestock keepers. Therefore access to grazing land and subsistance farming will contnue in the newly established resettlement land. Also, the traditional rights of the Sukuma, Mangati and Masai will be maintained. The replacement lands, for PAPs, is within the vicinity of the affected lands and is of comparable productive capacity and potential as the previously occupied land. The residential and farming land is at Masiano hamlet and livestock will be grazed at Shoga and Mapogoro ranch. The site for resettlement was identified so that it minimizes the social disruption of those affected; the lands have access to social and economic services and facilities that were unavailable in the RAP Mapogoro BBT farm April 2024 13 lands affected. The PAPs were involved in the process of developing and expected too in the implementing of the resettlement plan. RAP Mapogoro BBT farm April 2024 14 6.0 GRIVANCES AND DISPUTE RESOLUTION 6.1 Grievances Procedures The RAP will be made available to the public, the appeal structures at various levels, specifying the responsible parties and their response time. Before starting with the grievance sequence and where appropriate (i.e. in case of complaints of minor entity), aggrieved parties will take their complaints to the community or traditional meetings for dispute resolution. If need arises, the local NGOs will be contracted and involved to hear complaints and attempt to affect a resolution before they enter the legal and administrative appeals hierarchy. In normal circumstances, grievances will be dealt with either statutory through courts and tribunals, or administratively using government or traditional institutions. Using the courts in determining grievances related to and resettlement is not the best option as it is tedious, costly and lengthy. The simple and affordable procedures in place to lodge complaints or claims are as elaborated hereunder. Local authorities could handle the disputes and grievances in the first place. In summary those seeking redress will have to notify local government and ward offices. If this fails, disputes can be referred to district level. Resolution of disputes shall be speedy, just and fair and local NGOs that are conversant with these issues could be engaged by the project. The first stop, the Village Grievance Redress Committee (VGRC), has one week to resolve the dispute. If a given dispute is not resolved in one week it will go to the District Grievance Redress Committee (DGRC), which has two weeks to resolve the dispute. Unresolved disputes shall be referred to appropriate level of land courts established by law. If local courts are unable to resolve the disputes application can be made to the High Court of Appeal of Tanzania, this is the highest appellate judge in the system and its decision will be final. Potential grievances and disputes that arise during the course of implementation of the resettlement and compensation programme are often related to the following issues: i) Inventory mistakes made during census survey as well as inadequate valuation of properties; ii) Mistakes related to identification and disagreements on boundaries between affected iii) individual(s) and specifying their land parcels and associated development; iv) Divorces, successor and the family issues resulting into ownership dispute or dispute share between in heirs or family; v) Disputed ownership of given Assets (two or more affected individual(s) claim on the same); RAP Mapogoro BBT farm April 2024 15 6.2 Proposed Grievance Management and Redress Mechanism The mechanisms for grievance management and redressed mechanisms are to be \"affordable and accessible,\" and third parties independent of the implementers should be available at the appropriate point in the process. The grievance procedure will be simple, administered in the first instance at the local level to facilitate access, flexibility and open to various proofs taking into account the need for speedy, just and fair resolution of their grievances. The process suggested for resolving individual grievances is presented below. 6.2.1 Grievance Redress Committees There are two committees which will be involved in redressing grievances arising from the PAPs in the project area; a) Village Grievance Redress Committee (VGRC) and, District Grievance Redress Committee (DGRC) known as Social Service Committee (SSC) Composition of VGRC VGRC is comprised of: i) Village Chairperson, ii) Village Executive Officer (VEO), iii) Representative from the PAPs, iv) Community Development Officer from the Ward, Representative from NGO to be identified b) District Grievance Redress Committee (DGRC) Composition of DGRC DGRC is comprised of: i) District Commissioner Chairman ii) District Land office Member, iii) District Valuer; iv) RAP Implementing Agency Member v) PAP representative/ local NGO Member vi) Representative of Regional Secretariat Member 6.2.2 Appeal Land related grievances shall be resolved using the land courts established under the Land Disputes Courts Act. No. 2 of 2002 with its regulations. That is Village Land Council; the Ward Tribunal; the District Land and Housing Tribunal; the High Court (Land Division) and The Court of Appeal of Tanzania. 6.2.3 Eligibility The eligible individual(s) are those who will be directly affected through Mapogoro BBT farm development and are staying within the boundaries of the farm: RAP Mapogoro BBT farm April 2024 16 The PAPs were considered irrespective of their tenure status, with respect to land that they occupy or use provided they occupy or use the affected land prior to the cut-off-date. Cut-off date for eligibility to resettlement entitlements for the project was when the survey of affected properties was completed (i.e. 16\" April 2024). 7.0 LIVELIHOOD RESTORATION There is neither legal requirement nor regulation for restoring livelihoods or aiding towards the restoration of such livelihoods in Tanzania, the Livelihood Restoration Program (LRP) for those affected people. As such, the PAPs requested land to land compensation as their livelihood depends more on livestock keeping. Therefore, suitable land for livestock grazing was their preference. The government has allocated settlement and farming land for the PAPs at Masiano hamlet and range land for their livestock at Shoga and Mapogoro ranch. (Appendix III). RAP Mapogoro BBT farm April 2024 17 8.0 CUT-OFF DATE The actual identification of affected PAPs has been carried within the land to be acquired for the Mapogoro BBT farm. The cut-off date was set as 16 April, 2024 and communicated with each PAP during property identification and meeting. Any person who undertakes any development activity in the demarcated project area after the cut-off date will not be eligible for land to land compensation. It should, however be noted that the implementation of the cut-off date should also be observed by project implementer who is required to locate land for PAPs Six (6) months after the RAP has been approved. This RAP recommends that the project implementer needs to have frequent communication with PAPs through Mapogoro Village Government Officials to update PAPs on when they should expect to move or any other changes associated with implementation of the project. RAP Mapogoro BBT farm April 2024 18 9.0 IMPLEMENTATION SCHEDULE Implementation of RAP consists of several resettlement activities. Efficient implementation of RAP activities requires several measures to be taken prior to startup of implementation. These include setting up of relevant committees at district level, hiring of NGO or consultant etc. In principle project civil works may not start until all PAPs determined to be entitled for ressettlement are resettled. The time frame of 12 months on the implementation schedule ensures that no PAP or affected household will be displaced due to civil works activity before ressetlemnt is done and is undertaken when all necessary approvals have been obtained. • Finalization and Approval of RAP; • RAP disclosure and circulation; • Grievance Redress Mechanisms set at Mtaa and District Levels (Grievances Redress • Process) • Provision of notice period for relocation of property (public meetings) • Monitoring and evaluation. RAP Mapogoro BBT farm April 2024 19 10.0 MONITORING PROGRAMME RAP implementation is one of the central components of this project its monitoring is critical to solve challenges or obstacles in the areas of PAPs relocation. The monitoring and evaluation procedures will include external and internal evaluation of the compliance of the actual implementation with objectives and methods as agreed, and monitoring of specific situations. 10.1 Internal Monitoring The Project implementation unit will be responsible for internal monitoring while the Consultants may provide technical assistance in implementing RAP. At the conclusion of the RAP implementation the full information on every individual impacted by the project will provide the evaluation of status of PAPs and measuring Resettlement Plans (RAP) performance. Several indicators are used to measure these impacts, namely: a comparison of income levels before-and-after the project; changes in standards of housing and living conditions; access to various social services i.e. health care, education, water supply, road, markets etc. and improvements in level of participation in sub-project activities. Measures to verify these basic indicators would be mainly to compare these new conditions with pre-project conditions. Monitoring will ensure the following: • Verification of land set aside for PAPs been carried out as planned; • Information dissemination has been carried out; • Status of new land preparation for PAPs • Relocation of PAPs if applicable; • Effective operation of grievances Committee; • Funds for preparation of grazing land are available in timely manner, are sufficient for the purpose and spent according to Plan; • The Consultants shall submit reports on monthly basis documenting the RAP progress implementation; • Project Unit shall be responsible for monitoring day to day resettlement activities; • Performance data sheet shall be developed to monitor at the field level; and • The Consultants shall be responsible for overall project level monitoring. RAP Mapogoro BBT farm April 2024 20 11.0 RAP BUDGET AND SCHEDULE Table 3: Budget for RAP Implementation S/N Resettlement Activity Activity Cost (Tsh) Source of fund/ Responsibili t Timeline/ Deadlines 1. Grievance handling 15,000,000 MoA Through RAP implementation 2. Management & administration 20,000,000 MoA Through RAP implementation 3 Monitoring & evaluation 100,000,000 MoA Through RAP implementation TOTAL 135,000,000 RAP Mapogoro BBT farm April 2024 21 APPENDICES Appendix I: Map indicating Location of PAPs within the Mapogoro BBT farm RAP Mapogoro BBT farm April 2024 22 Appendix II: List of PAPS with thir signatures who agreed to be re-settled at Mapogoro BBT farm RAP Mapogoro BBT farm April 2024 23 RAP Mapogoro BBT farm April 2024 24 RAP Mapogoro BBT farm April 2024 25 RAP Mapogoro BBT farm April 2024 26 Appendix III: Map indicating area for re-settlement of PAPs RAP Mapogoro BBT farm April 2024 27 Appendix IV: Report on PAP Households Inventory at Mapogoro BBT Farm RAP Mapogoro BBT farm April 2024 28 RAP Mapogoro BBT farm April 2024 29 Appendix V: Names of PAPs, Number of Tenants, Year encroached the land and land method of Land acquisition (Typed) RAP Mapogoro BBT farm April 2024 30 RAP Mapogoro BBT farm April 2024 31 Appendix VI: Translations of Appendix IV CHUNYA DISTRICT COUNCIL HOUSEHOLD VERIFICATION REPORT AT MAPOGORO FARM AREA 1. INTRODUCTION In 2021, Chunya District Council surveyed farms for investment in the village areas of Mapogoro, Lualaje, and Nkungungu, including issuing land title deed. These farm areas have been found to be invaded by people who are farming and establishing settlements while continuing with other various human activities. In implementing the development of these farms, Chunya District Council Executive Director formed a team to inspect the households within the Mapogoro farm area to verify the number of households and residents living there, and to get their signatures from those who agreed to leave the farm area to make way for the BBT project. The team officially started working on April 6, 2024 for the verification of households within the BBT Mapogoro farm. 2. TEAM STRUCTURE The director of the Chunya District Council formed a five-person team with the following structure: i) Lameck Matukulu - Agricultural Officer - Chairman ii) Abdallah Msenga - Land Surveyor - Secretary iii) Shaban Kawambwa - Mapping Expert - Member iv) Zebedayo Geofrey - Land Surveyor - Member v) Ambokile Samson - Land Surveyor - Member 3. TEAM RESPONSIBILITIES To monitor the number of households within the BBT Mapogoro area, the team used the following terms of reference: i) Name of the head of the household and the number of household members in each home. ii) The land ownership status. iii) Inspection of citizen identification within the area, including NIDA identification or voter ID iv) Coordinates of each household to determine its geographical location within the farm area 4. IMPLEMENTATION OF THE TERMS OF REFERENCE The team officially started working on April 6, 2024 adhering to the terms of reference. RAP Mapogoro BBT farm April 2024 32 4.1 IDENTIFYING THE NUMBER OF HOUSEHOLDS WITHIN THE FARM The team successfully identified a total of 51 households within the BBT Mapogoro area who had invaded at different times, engaging in activities such as livestock keeping and farming for food. A list of the heads of these households is attached to this report. STATUS OF LAND OWNERSHIP BY RESIDENTS WITHIN THE FARM AREA i) The team discovered that some invaders had begun illegally selling the land, whereby seven households sold land areas to each other and started livestock keeping and crop cultivation. ii) The team received information about only two people who exchanged land to establish household farms. iii) The team found that the heads of 38 households, representing 75%, entered the area without the consent of the village government or any other person. iv) The team also found that the households that entered through buying or receiving land did not have any documents to verify this. HOUSEHOLDS DISTRIBUTION WITHIN THE BBT MAPOGORO AREA The community living in these areas consists of the Sukuma and Mang'ati community, whose main activities within the area are agriculture and livestock keeping. Their households are distributed ranging from one household to another at distances of 500 meters to 1 kilometer. CONCLUSION Considering that these residents are not legally in the specified area and since the village has a plan for better land use which we are continuing to implement, we have reached an agreement, and they have consented to move to the allocated areas for living and farming in the Masiano hamlet, and their livestock will be moved to the Shoga and Mapogoro grazing areas where all services will be provided. Along with this report, I have attached a sketch map of the residential and agricultural areas and a list of the heads of all 51 households that will be relocated to these areas for essential life activities. I submit. Cuthbert G. Mwinuka For District’s Executive Director RAP Mapogoro BBT farm April 2024 33 Appendix VII: Proposal for Land Range Clusters for PAPs RAP Mapogoro BBT farm April 2024 34 RAP Mapogoro BBT farm April 2024 35 RAP Mapogoro BBT farm April 2024 36 RAP Mapogoro BBT farm April 2024 37 Appendix VII: Map indicating Areas where PAPs will be re-located"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":166,"cells":{"data":{"kind":"string","value":"# Extracted Content THE UNITED REPUBLIC OF TANZANIA PRIME MINISTER’S OFFICE Southern Agricultural Growth Corridor of Tanzania (SAGCOT) Investment Project INTEGRATED PEST MANAGEMENT PLAN (IPMP) MARCH 2014 Page i of 110 TABLE OF CONTENTS TABLE OF CONTENTS ........................................................................................................................ i LIST OF TABLES ................................................................................................................................. iii ABBREVIATIONS AND ACRONYMS.............................................................................................. iv EXECUTIVE SUMMARY ................................................................................................................... vi 1. BACKGROUND ............................................................................................................................. 1 1.1. INTRODUCTION ..................................................................................................................... 1 1.2. METHODOLOGY .................................................................................................................... 2 2. DESCRIPTION OF PROPOSED PROJECT .............................................................................. 4 2.1. INTRODUCTION ..................................................................................................................... 4 2.2. PROJECT COMPONENTS ...................................................................................................... 4 2.3. PROJECT IMPLEMENTATION ARRANGEMENTS ............................................................... 5 2.3.1 The Catalytic Fund ......................................................................................................... 5 2.3.2 The SAGCOT Centre ..................................................................................................... 5 2.3.3 Tanzania Investment Centre ......................................................................................... 6 3. THE GENESIS OF AGRICULTURAL PEST MANAGEMENT PRACTICES ..................... 8 3.1. INTRODUCTION ..................................................................................................................... 8 3.2. THE MEANING AND IMPORTANCE OF IPM ....................................................................... 8 3.3. FUNDAMENTALS OF IPM ..................................................................................................... 9 3.4. KEY CHARACTERISTICS OF AN IPM APPROACH .............................................................. 9 3.5. THE PRINCIPLES OF AN IPM ............................................................................................. 10 4. EXISTING AND ANTICIPATED PEST PROBLEMS ............................................................ 11 4.1 FOOD CROPS ........................................................................................................................ 11 4.2 CASH CROPS ......................................................................................................................... 28 4.3 HORTICULTURAL CROPS ................................................................................................... 38 4.4 MIGRATORY AND OUTBREAK PESTS ................................................................................ 50 5. POLICY, REGULATORY AND INSTITUTIONAL FRAMEWORK ................................... 55 5.1 INTRODUCTION ................................................................................................................... 55 5.2 POLICIES AND STRATEGIES ............................................................................................... 55 5.3 PROGRAMMES AND STRATEGIES ..................................................................................... 57 5.3.1 Africa Stockpiles Programme (ASP) ........................................................................... 57 5.3.2 Empty Pesticides Container Management Strategy .................................................. 57 6. PEST CONTROL AND MANAGEMENT OPTIONS ............................................................. 59 6.1 INTRODUCTION ................................................................................................................... 59 6.2 BIOLOGICAL CONTROL ...................................................................................................... 59 6.3 CULTURAL AND CROP SANITATION PRACTICES ........................................................... 61 6.4 PHYSICAL AND MECHANICAL CONTROL ........................................................................ 62 Page ii of 110 6.5 CHEMICAL CONTROL ......................................................................................................... 62 6.6 BOTANICAL PESTICIDES .................................................................................................... 64 7. EXPERIENCES ON IPM IN TANZANIA ................................................................................ 66 7.1 INTRODUCTION ................................................................................................................... 66 7.2 GTZ/PHS-IPM ........................................................................................................................ 66 7.3 KAGERA AGRICULTURAL AND ENVIRONMENTAL MANAGEMENT PROGRAMME (KAEMP) ............................................................................................................................................ 68 7.4 MARA REGION FARMER INITIAITIVE PROJECT (MARAFIP) ......................................... 69 7.5 MBEYA: SOUTHERN HIGHLANDS EXTENSION & RURAL FINANCIAL SERVICES PROJECT/IFAD ................................................................................................................................. 70 7.6 MOROGORO SPECIAL PROGRAMME FOR FOOD SECURITY (SPFS) /FAO PROJECT 70 7.7 LESSONS AND GENERAL DISCUSSION ............................................................................. 71 7.7.1 Approach ....................................................................................................................... 71 7.7.2 Capacity Building ......................................................................................................... 71 7.7.3 Institutional Collaboration .......................................................................................... 72 7.7.4 Funding and Logistical Support .................................................................................. 72 7.7.5 Political support ............................................................................................................ 72 8. IMPLEMENTATION STRATEGY ........................................................................................... 73 8.1 INTRODUCTION ................................................................................................................... 73 8.2 INSTITUTIONAL ROLES AND RESPONSIBILILTIES ......................................................... 73 8.2.1 MGF Applicant/ Recipient ........................................................................................... 73 8.2.2 Catalytic Fund............................................................................................................... 74 8.2.3 Ministry of Health and Social Welfare ....................................................................... 74 8.2.4 Ministry of Agriculture, Food Security and Cooperatives ........................................ 74 8.3 PROMOTION OF IPM UNDER SAGCOT ............................................................................ 74 8.3.1 Specific PMP for Sub-Projects .................................................................................... 74 8.3.2 IPM to be Part of Environmental and Social Management Plan ............................. 75 8.3.3 The IPM Strategies for Promoting its Adoption ........................................................ 75 8.3.4 SAGCOT to Advice Investors on IPM Practices ....................................................... 76 8.3.5 SAGCOT to Support IPM Training in Research and Training Institutions ........... 76 8.3.6 SAGCOT to Support IPM Training and National Policy ......................................... 76 8.4 SPECIFIC PEST MANAGEMENT MEASURES .................................................................... 77 8.4.1 Rules for Safe Handling of Pesticides.......................................................................... 77 8.4.2 Recommended Pesticides in Tanzania ........................................................................ 77 8.4.3 Pesticides Banned in Tanzania .................................................................................... 79 8.5 MONITORING AND EVALUATION ARRANGEMENT......................................................... 80 8.6 WORKPLAN AND BUDGET ................................................................................................. 81 9. RECOMMENDAITONS ............................................................................................................. 84 REFERENCES ..................................................................................................................................... 85 APPENDICES ...................................................................................................................................... 90 Appendix 1: Names of Experts Involved in Preparing This IPMP for SAGCOT ................................ 90 Appendix 2: Persons Consulted During the Preparation of IPMP for ASDP .................................... 90 Appendix 3: An IPM Checklist for Planning and Implementing Pest Control on Crops .................... 94 Appendix 4: Pesticide Classification List – WHO .............................................................................. 97 Appendix 5: SAGCOT Corridor and Clusters .................................................................................. 103 Page iii of 110 LIST OF TABLES Table 3.1: Zone, Altitude and rainfall classes Table 4.1: Summary of major food, cash and horticulture crops grown in different agro-ecological zone of Tanzania Table 4.2: Major maize pest problems and recommended management practices Table 4.3: List of pesticides recommended for use on maize in all zones Table 4.4: Important weeds in Tanzania Table 4.5: Major pests of rice and recommended management practices Table 4.6: Sorghum major pests and recommended management practices Table 4.7 The major pests of pearl millet and recommended management practices Table 4.8: Banana major pest problems and recommended management practices for Lake and Northern Zones Table 4.9 Cassava major pests and recommended management practices Table 4.10 The major pest problems of beans and recommended management practices Table 4.11 The major pests of sweet potato and recommended management practices Table 4.12 Coffee pest problems and recommended management practices Table 4.13 List of recommended pesticides for use in coffee Table 4.14 Cotton pest problems and recommended management practices in the WCGA Table 4.15 List of pesticides recommended for use on cotton in the WCGA Table 4.16 Cotton pest problems and recommended management practices in the ECGA Table 4.17 List of pesticides recommended for use on cotton in the ECGA Table 4.18 Major pests and recommended management practices in cashew Table 4.19 Pesticides recommended for use on cashew Table 4.20 Major pests and recommended control practices for coconut Table 4.21 Key pests of mangoes and current farmer practices to reduce losses Table 4.22 Major pest problems of citrus and recommended management practices Table 4.23 Major pest problems of pineapples and recommended management practices Table 4.24 Major pests of tomatoes and recommended management practices for northern zone Table 4.25 List of pesticides recommended for use on tomatoes Table 4.26 Major pest problems and recommended management practices Table 4.27 Major pests of brassicas and recommended practices Table 4.28 Rodent control 2003 Table 4.29 Quelea Quelea invaded regions year 2003 Table 4.30 Quelea quelea outbreaks and cereal damage in some regions of Tanzania, 1998-2002 Table 4.31 Invaded area and treatment used Table 4.32 Armywork outbreaks in Tanzania Table 4.33 Damage of various crops by armyworms during the 2001/2002 cropping seasons in some region of Tanzania Table 5.1 List of recommended and TPRI registered pesticides for crop production in Tanzania Table 5.2 List of potential plants that can be used to prepare botanical extracts for pre and post harvest pest control Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania Table 8.2 List of pesticides whose use are subject to the Prior Informed Consent (PIC) procedure in Tanzania Table 8.3: Workplan and Budget for IPM implantation Page iv of 110 ABBREVIATIONS AND ACRONYMS AIDS Acquired Immunodeficiency Syndrome ASDP Agricultural Sector Development Programme ASDS Agriculture Sector Development Strategy ASP Agriculture Services Providers ASSP Agricultural Services Support Programme CF AVRDC Catalytic Fund Asian Vegetable Research Development Centre CBB Coffee Berry Borer CBD Coffee Berry Disease CBO Community Based Organisation CBSD Cassava Brown Streak Disease CLR Coffee Leaf Rust CMD Cassava Mosaic Disease CORMA Client-Oriented Research and Development Management Approach DADP District Agriculture Development Plans DGIC Directorate General for International Cooperation DPPO District Plant Protection Officer DRDP District Rural Development Programme ECGA Eastern Cotton Growing Area ESMF Environmental Social Management Framework ESMP Environmental and Social Management Plan EMP Environmental Monitoring Plan FFS Farmers Field Schools FM Fund Manager GLS Grey Leaf Spot GTZ Gesellschaft fur Technische Zusammenarbeit HPR Host Plant Resistance ICIPE International Centre of Insect Physiology and Ecology IDA International Development Agency IFAD International Fund for Agricultural Development IPM Integrated Pest Management IPN Integrated Plant Nutrition IPM Integrated Pest Management IPMP Integrated Pest Management Plan JICA Japan International Cooperation Agency KAEMP Kagera Agricultural Environmental Management Project LGA Local government authority LGB Larger Grain Borer LVEMP Lake Victoria Environmental Management Project LZARDI Lake Zone Agricultural Research and Development Institute M&E Monitoring and Evaluation MAFC Ministry of Agriculture, Food Security and Cooperatives MANREC Ministry of Agriculture, Natural Resources, Environmental and Cooperatives MARA-FIP Mara Region—Farmers’ Initiative Project MGF Matching Grant Fund MOA Memorandum Of Agreement MSV Maize Streak Virus MWLD Ministry of Water and Livestock Development NAEP National Agricultural Extension Programme NALP National Agricultural and Livestock Policy NARS National Agricultural Research Systems NEMC National Environment Management Council NGO NPPAC Non Governmental Organizations National Plant Protection Advisory Committee NPV Nucleopolyhedrovirus OPEC Organization of Petroleum Cooperation PADEP Participatory Agriculture Empowerment Project Page v of 110 PCS Pest Control Services PHS Plant Health Services PMD Powder Mildew Disease PMP Pesticides Management Plan POP Persistent Organic Pollutants PPD Plant Protection Division PRA Participatory Rural Appraisals RAS Regional Administrative Secretary RPF Resettlement Policy Framework RGZ Revolutionary Government of Zanzibar RYMV Rice Yellow Mottle Virus SAGCOT Southern Agricultural Growth Corridor of Tanzania SVCF Social Venture Capital Fund SGR Strategic Grain Reserve SIIC Smallholder Irrigation Improvement Component SMS Subject Matter Specialist SPFMV Sweet potato feathery mottle virus SPFS Special Programme for Food Security SPSVV Sweet potato sunken vein virus SPVD Sweet Potato Virus Disease SUA Sokoine University of Agriculture SRESA Strategic Regional Environmental and Social Assessment URT United Republic of Tanzania TIC Tanzania Investment Centre TPRI Tropical Pesticides Research Institute UDSM University of Dar es Salaam ULV Ultra Low Volume USD United States Dollars VEO Village Extension Officer WCGA Western cotton growing areas WFF Ward Farmers Forum WHO World Health Organization ZARDEF Zonal Agricultural Research and Development Funds ZARDI Zonal Agriculture Research and Development Institutes ZEC Zonal Executive Committees Page vi of 110 EXECUTIVE SUMMARY This integrated pest management plan (IPMP) addresses the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) Investment Project’s need to monitor and mitigate negative environmental impacts of the project by promoting biological and ecosystem based pest management. The overall SAGCOT Program is broadly identified as a public-private partnership intended to improve the incomes, employment opportunities and food security of smallholder farmers across the southern corridor of Tanzania. This will be done by linking them to internationally competitive supply chains and accelerating commercial agricultural development, in particular by using foreign direct investment attracted by the removal of policy and infrastructural constraints to competitiveness and by facilitated access to land. SAGCOT lies along an existing road, rail and power corridor running from Dar es Salaam west through Iringa to Mbeya and beyond. Initially investments will be focused on six areas with high potential for quick agricultural development (\"clusters\"), including the Kilombero Valley. Over the next 20 years, the initiative aims to bring 350,000 hectare of land into commercial production, increase annual farming revenues by US$1.2 billion, and lift some 450,000 farming households out of poverty. The Project will promote intensive commercial agriculture in tropical and subtropical environments with significant pest and disease control challenges. Pesticide use and management will be guided by Tanzanian law, the World Bank policy OP 4.09 (Pest Management), international best practice, and experience with Integrated Pest Management (IPM) in the agricultural sector in Tanzania. It specifically draws heavily from related work done to prepare for the Agricultural Sector Dvelopment Program (ASDP) which the Government of Tanzania (GoT) has been implementing since 2006. The management aspects of pests and diseases of the key major crops have been discussed in detail. These include food crops such as maize, sorghum, beans, banana, sweet potatoes, finger millet, rice; cash crops: coffe, cotton, cashewnuts, etc. horticultural crops: coconuts, mangoes, citrus, pineapples, tomatoes, onions and brasiccas (cabbages and kale) and migratory and outbreak pests: rodents, birds (quelea quelea spp) and armyworms. The GoT have taken deliberate measures for promotion of IPM in all crop production systems. In 1997, the GoT formulated and introduced the Agriculture and Livestock Policy and the National Environmental Policy. In line with these two policies, a Plant Protection Legislation was encacted in 1997 followed by its regulations of 1999. Umbrella framework legislation, the Environmental Management Act No. 20 of 2004 is in place. All these policies and legislation emphasise use of sustainable production approaches particularly IPM. The IPMP for SAGCOT is based on the experiences gained during the implementation of IPM experience in Tanzania Mainland and information obtained through review of published materials and discussion with crop experts, researchers, farmers and extension workers. It provides a framework for the development of IPM programme for food, cash and horticultural crops in the SAGCOT Programme to identify, understand and manage pest problems in the components, reduce human and environmental health risks associated with pesticides use, and protect ecosystem by conserving beneficial agents such as natural enemies of pests and pollinators to increase productivity. The IPMP also provides guidelines for pest management in accordance to the IPM approach. It augments the biological, chemical and cultural control aspects of the management of pests and diseases. An outline of the specific pest management measures to be incorporated (including a \"positive list\" for procurement, rules for safe handling of pesticides, and promotion of IPM); and an implementable workplan outlining those specific measures (e.g. budget, timeline, institutional roles and responsibilities) are given in this IPMP. Page 1 of 110 1. BACKGROUND 1.1. INTRODUCTION The overall SAGCOT Program is broadly identified as a public-private partnership intended to improve the incomes, employment opportunities and food security of smallholder farmers across the southern corridor of Tanzania. This will be done by linking them to internationally competitive supply chains and accelerating commercial agricultural development, in particular by using foreign direct investment attracted by the removal of policy and infrastructural constraints to competitiveness and by facilitated access to land. SAGCOT lies along an existing road, rail and power corridor running from Dar es Salaam west through Iringa to Mbeya and beyond. Initially investments will be focused on six areas with high potential for quick agricultural development (\"clusters\"), including the Kilombero Valley (see Appendix 5: SAGCOT Corridor and Clusters). Over the next 20 years the initiative aims to bring 350,000 ha of land into commercial production, increase annual farming revenues by US$1.2 billion, and lift some 450,000 farming households out of poverty. The Government of Tanzania (GoT) has requested support from the International Development Agency (IDA, part of the World Bank) to assist in implementation of the SAGCOT concept. The proposed World Bank support (\"the Project\") will be in the form of a Specific Investment Loan (SIL). The World Bank Operational Policy 4.09 Pest Managetment is triggered as the Project will promote intensive commercial agriculture in tropical and subtropical environments with significant pest and disease control challenges. Although the Catalytic Fund will not directly support purchase of any pesticides, in the field improvements envisioned under the MGF and SCVF could increase the use of inputs - particularly chemical fertilisers, improved seeds and irrigation facilities. This may lead to an increase in the use of synthetic pesticides, and associated potential human and environmental hazards, and hence the requirements for mitigation plan. Pesticides Management Plan (PMP) identifies and addresses changes in pest management practices and concerns that may arise out any increase in chemical pesticides use and propose mitigation in compliance with the World Bank Safeguard Policy on Pest Management (OP 4.09). Pesticide use and management will be guided by Tanzanian law, World Bank policy (including OP 4.09), international best practice, and experience with IPM in the agricultural sector in Tanzania. It specifically draws heavily from related work done to prepare for the Agricultural Sector Dvelopment Project (ASDP). To support such efforts, SAGCOT will also apply the standards set under the International Code of Conduct on the Distribution and Use of Pesticides which encourages responsible and generally accepted trade practices and sets out the “conduct for public and private entities engaged or associated with the distribution and use of pesticides.” The Code is designed for use within the context of national legislation as a basis whereby government authorities, pesticide manufacturers, those engaged in trade and any citizens concerned may judge whether their proposed actions and the actions of others constitute acceptable practices. In addition, it describes the shared responsibility of many sectors of society to work together so that the benefits to be derived from the necessary and acceptable use of pesticides are achieved without significant adverse effects on human health or the environment. The main purpose of preparing this Integrated Pest Management Plan (IPMP) is to: (i) assess the current and anticipate pest problems in the programme areas; (ii) review the country experiences on IPMP; (iii) develop a pest management plans (IPMPs) using recommended best-practices; (v) develop monitoring and evaluation systems for the various pest management practices of the IPMPs based on the government laws and the World Bank policy. It draws upon experience with other IPMPs in Tanzania, including that of the Agricultural Sector Development Project (ASDP). Page 2 of 110 1.2. METHODOLOGY Preparation of this IPMP builds on the following approach and methods that were used to gather information from relevant stakeholders for ASDP IPMP: (i) Participatory approach The preparation of the IPM guidelines used a participatory process aimed at facilitating a broad based dialogue and transparency in identification of key pesticides problems and management issues. Moreover, the extensive consultations with farmers, district staff, communities, lead IPM researchers and practitioners, crop specialists, etc. in Tanzania Mainland and Zanzibar helped to solicit relevant information on pest management. (ii) Review of literature and checklists of documentation Relevant SAGCOT program/ project documents; Policy and legal documents used in Tanzania pesticide industry, namely Plant Protection Act 1997, Pesticide Regulations 2002, Agriculture Policy 1997, National Environmental Policy 1996 and the Environmental Management Act No. 20 of 2004. In Zanzibar the following documents were consulted: Agriculture Policy of 2002, Environmental Management for Sustainable Development Act of 1996 and Plant protection Act of 1997; and World Bank Safeguard Policies in particular OP 4.09 (iii) Questionnaires and checklists for guiding consultative meetings with following stakeholders: ASSP preparation team The ASDP Secretariat Ministry of Agriculture and Food Security, namely Department of Research and Development, Departments of Crop Production, Plant Health Services, Agricultural Extension Services, Participatory Agriculture Empowerment Project (PADEP), Smallholder Irrigation Improvement Component (SIIC), etc. Ministry of Water and Livestock Development, namely Veterinary services Zonal Research and Development Institutes, namely Lake Zone, Northern Zone, Eastern Zone, Western Zone, Southern Highland Zone Ministry of Agriculture, Environment, Natural Resources and Cooperatives, Zanzibar and Zanzibar Agriculture Research Institute in Kizimbani Tanzania Pesticides Research Institute Sokoine University of Agriculture, namely Pest Management Research Centre Division of Environment, Vice-President Office National Environmental Management Council District Councils Farmers representatives NGOs IPM, bird control and armyworm projects (iv) Questionnaires and checklists for guiding consultative meetings with following stakeholders: Ministry of Agriculture and Food Security, namely Department of Research and Development, Departments of Crop Production, Plant Health Services, Agricultural Extension Services, Participatory Agriculture Empowerment Project (PADEP), Smallholder Irrigation Improvement Component (SIIC), etc. Ministry of Water and Livestock Development, namely Veterinary services Page 3 of 110 Zonal Research and Development Institutes, namely Lake Zone, Northern Zone, Eastern Zone, Western Zone, Southern Highland Zone Ministry of Agriculture, Environment, Natural Resources and Cooperatives, Zanzibar and Zanzibar Agriculture Research Institute in Kizimbani Tanzania Pesticides Research Institute Sokoine University of Agriculture, namely Pest Management Research Centre Division of Environment, Vice-President Office National Environmental Management Council District Councils Farmers representatives Page 4 of 110 2. DESCRIPTION OF PROPOSED PROJECT 2.1. INTRODUCTION The proposed Project Development Objective (PDO) will be to: create and expand partnerships between smallholder farmers and agribusinesses in the Southern Corridor leading to adoption of new technologies and improved market access by smallholders. 2.2. PROJECT COMPONENTS The SAGCOT Project comprises three components that will be implemented over a five year period: Component 1: Strengthening of SAGCOT Support Institutions (total USD15.99 million, IDA USD8.67 million). The objective of this component will be to strengthen the capacity of the main SAGCOT support institutions in order to pursue their functions of information and data provision, support of investment planning and guidance, government/private sector intermediation, business enabling environment and investment promotion. The component will support two institutions under the following sub-components: o SAGCOT Centre (total USD10.82 million, IDA USD3.50 million): under this sub-component the Project will jointly with other donors support the SAGCOT-Centre, which was established as a public private partnership entity in 2011 to: (i) Facilitate agri-business and partnership development; (ii) Ensure inclusive and sustainable investment and development; and (iii) Advocate for an improved enabling environment. The Project will support the Centre by providing financing for staff and operational costs, studies and consulting services to be contracted by the Centre. o Tanzanian Investment Centre (Government institution) (total USD5.17 million, IDA USD5.17 million): under this sub-component the Project will support the TIC which was established as a public sector entity in 1977 and designated as the first point of call and a “one-stop facilitation centre” for all potential investors coming into the country. The Project will support TIC to reform its processes with the aim to: (i) strengthen its capacity to leverage high quality, responsible, inclusive and sustainable commercial investments (ii) provide a competitive framework for tendering and (iii) monitor and evaluate investments. The Project will finance incremental equipment, technical assistance and consultancies. Component 2: Strengthening Smallholder Business Linkages (total USD77.68 million, IDA USD45.00 million): The objective of this component will be to link smallholder farmers to agricultural value chains. The component will (a) expand the number of smallholders linked to agribusinesses in successful commercial partnerships and (b) improve the revenues derived by smallholders and rural communities from these partnerships in the form of growth in agricultural productivity, income and employment. This component will comprise two sub-components: o Fund Management (total USD13.00 million, IDA USD6.50 million): under this sub-component the Project will jointly with other donors support a management structure responsible for the implementation of the Catalytic Trust Fund (including Board, Secretariat and Fund Manager). Project support will include fees and salaries, goods and equipment, office operational costs, meetings and workshops, communications and technical assistance. o Matching Grants (total USD64.68 million, IDA USD38.50 million): Matching Grants (MG) at a size of USD250,000 up to USD1.5 million with a matching contribution of 30 percent (national businesses) and 40 percent (international business operators) will be awarded to existing agribusiness operators with undisputed land rights following a defined process of application, evaluation and competitive selection. The grants can be used for operational cost Page 5 of 110 and capital costs directly related to expanding smallholder participation in competitive agricultural supply chains. Component 3: Project Management and Evaluation (total USD6.33 million, (of which USD3.00 million were provided as Project Preparation Advance) IDA USD6.33 million): The component will establish project management and M&E systems and provide financing for salaries, office equipment, transportation and technical assistance services. It will support the coordination between implementation agencies at all levels and with other government programs and institutions. Pesticide issues are considered to be most relevant in the Matching Grants included in Component 2, as such grants will support expansion of outgrower activities that are likely to involve expanded use of pesticides. As such, the IPMP focuses on incorporating measures to ensure necessary capacity, tools (including safety equipment) and monitoring are in place for subprojects supported through the Matching Grants window. 2.3. PROJECT IMPLEMENTATION ARRANGEMENTS The implementation of SAGCOT will take place through the use of existing government structures as well as the SAGCOT Centre, through their mandates to implement the SAGCOT programme. These institutions and their SAGCOT responsibilities are described below. 2.3.1 The Catalytic Fund The Fund Manager(s) of the Catalytic Fund (CF) will identify, finance, and develop viable investments across the value chain in the Corridor. It will also assist in the process of raising third-party commercial finance once the opportunities are “investment ready”. In the process, the Fund Manager(s) will ensure that projects are developed in ways that maximise a range of financial, economic, social and commercial developmental impacts. The Fund Manager(s) shall have the mandate and function of: (a) raising additional Funds subject to the consent of the Board; (b) preparing the investment pricing policy of the Social Venture Capital Fund for approval by the Board; (c) marketing the Funds, (d) approval of applications and (e) operational management of the Funds. The bulk of World Bank support will go to the Catalytic Fund via the Matching Grant Facility. Therefore, the CF must have in place a set of procedures that assure compliance with both GoT environmental regulations and World Bank safeguards, including those of World Bank OP 4.09 Pest Management. 2.3.2 The SAGCOT Centre The SAGCOT Centre is the key coordinator of the SAGCOT programme with numerous cross-cutting roles. The SAGCOT Centre has been established to facilitate investment and manage the coordination of the partnership to ensure the successful achievement of its objectives. Its activities include: (i). Managing and expanding the SAGCOT Partnership; (ii). Information provision & Market intelligence; (iii). Facilitating introductions; (iv). Facilitating access to finance; (v). Coordination of cluster and corridor development; Page 6 of 110 (vi). Identification of enabling environment obstructions and helping to address these; and (vii). Monitoring and evaluating progress. With this remit, the SAGCOT Centre will be instrumental in communicating the principals of sustainable investment across stakeholders in both the public and private sectors. To accomplish this mandate, the SAGCOT Centre will need to have the capacity to undertake the following; (i). keep stakeholders updated on environmental and social issues surrounding development in the Corridor, including those associated with pest management; (ii). communicate to potential investors, in collaboration with TIC, the sustainable and green investment principles which SAGCOT will promote; (iii). be the first “stop” for all investments regarding transparent land transfer requirements; (iv). provide preliminary information on clean technology and reduced carbon footprint opportunities for investors. (v). Finally, the SAGCOT Centre will also be the focal point for annual reporting on safeguard progress across the implementing agencies and organizations to the World Bank. 2.3.3 Tanzania Investment Centre The Tanzania Investment Centre (TIC) was established under the provisions of the Tanzania Investment Act, Cap 38 (Act No 26 of 1997). The Centre is designated to be a one-stop shop for investors and is mandated to co-ordinate, encourage, promote and facilitate investment in Tanzania and to advise the Government on investment policy and related matters. Within this remit, the TIC has the authority to: (i). identify investment sites, estates or land together with associated facilities on these, for the purposes of investors and investments in general; (ii). assist investors to obtain permits, licence approvals consents, authorisations, registrations and other matters required by law for a person to set up and investment; and (iii). enable certificates issued by the Centre to have full effect. TIC will assist in incorporation and registration of enterprises; promote both foreign and local investment activities, and grant certificates of incentives. As the first port of call, the TIC will need to develop a set of guidelines for potential investors that detail the principles of sound sustainable agriculture development in the Corridor, including those for resettlement. These principles should cover the following topics: (i). reliable information on land availability with maps (in a modern format (GIS)); (ii). information linking land suitability to potential crop production; (iii). transparent methods for land transfer, registration and leasing arrangements; (iv). land lease revenue options or equivalents; (v). corporate social responsibility and community development funds, including those related to resettlement and livelihood restoration programmes; Page 7 of 110 (vi). the role of grievance mechanisms, tribunal or adjudication assurance for investors and villagers, and (vii). potential “road blocks” and ways to navigate around these complex issues. The guidelines will be developed using technical information from the Ministry of Lands, Housing and Human Settlements Development and also the Rufiji Basin Development Authority (RUBADA)1. 1 RUBADA is not receiving support under the World Bank Specific Investment Loan, but it is an institution that is relevant to implementation of SAGCOT Page 8 of 110 3. THE GENESIS OF AGRICULTURAL PEST MANAGEMENT PRACTICES 3.1. INTRODUCTION The pest management practices have existed for quite long in the history of agricultural systems having a key drive on human population trends. Until half a century ago crop protection practices were integral parts of any cropping system. Growing world population required dramatic increases of agricultural production. From the 1940’s to the 1970’s, a spectacular increase in yield was obtained with the aid of an intensive development of technology, including the development of a variety of agro-pesticides. In many countries this advancement was coupled with the development of education of farmers and efficient extension services. In many development countries, however, this foreign technology was dumped without adequate support systems. Agro-pesticides were often used injudiciously. Misuse and over-use was stimulated by heavy subsidies on agro-chemicals. Many developing countries adopted a system of technology transfer in which a research apparatus developed or adapted technology that was transferred to farmers by an extension unit. Crop protection measures were often reduced to easy-to-use pesticide application recipes, aimed at immediate and complete destruction of the causal organism. In places where the use of improved varieties was propagated, packages of high-yielding varieties with high inputs of agro-pesticides and fertilisers made farmers dependent on high external inputs. Recently, it was realised that this conventional approach has its disadvantages. Conspicuous drawbacks are undesirable side-effects of pesticides which includes the following: human toxicity; poisoning and residue problems; destruction of natural enemies and other non-target organisms; development of resistance in target organisms; and environmental pollution and degradation. Pesticides are expensive and good management of their use requires skills and knowledge. For various reasons the (Research-Extension–Farmers) transfer of technology often does not work well. The technology is frequently inadequate and not adapted to the specific local needs. Based on above, it can be revealed that; relying on the use of pesticides in not sustainable as their unjudicial use is not human and environmental friendly. Thereby the need to improve the development and transfer of technology down to end users. 3.2. THE MEANING AND IMPORTANCE OF IPM What is IPM? Integrated Pest Management (IPM) could be defined as a comprehensive approach to pest control that uses combined means to reduce the status of pests to tolerable levels while maintaining a quality environment. In OP 4.09, the definition of IPM uses the same principles but emphasizes the following points: 1. The IPM approach must be ecologically-based (making use of the ecosystem ‘s ability to regulate pest populations); 2. Emphasis is on Pest Management as opposed to Pest Eradication; and 3. Reliance on multiple tactics as opposed to the “Silver bullet” approach (Chemical pesticides) The definition is the policy allows for selecting and applying pesticides, in a way that minimizes adverse effects on beneficial organisms, humans, and the environment. Page 9 of 110 Why IPM? The experience on drawbacks in the agricultural pest management systems, necesitated a crop protection approach that is centred on local farmer needs that are sustainable, appropriate, environmentally sound and economically viable. Such approach is called Integrated Pest Management (IPM). It should also be noted that when pesticides are applied in a given crop its only 1% hits direct the targed pest the rest 99% it becomes a burden to the environment and human health. The IPM approach encourages; the use all available, suitable methods of prevention and control, including resistant varieties, cultural methods such as planting time, intercropping and crop rotation, biological control. Pesticides will only be used as a last resort when plant protection decisions are made based on the damage/economic thresholds. Thus the soft and selective pesticides are used to minimise detrimental effects on humans, natural enemies and other non-target organisms. The philosophy of IPM is layed on the; no total eradication of all noxious organisms, but keeping them at levels below injury and conservation of the ecosystem that stimulate the presence of natural enemies. The technology can widely be since it has to be developed by farmers in collaboration with researchers and extensionists. Compliance: the integrated pest management approach is in line with the WB OP 4.09, whereby the policy supports safe, effective, and environmentally sound pest management aspects, such as the use of biological and environmental friendly control methods. As outlined in the Environmental Social Management Framework (ESMF) for SAGCOT. Since the IPM approach is location and crop specific, most sub-projects under the program may need a specific pest management plans for addressing the concerns on board. More importantly, the IPMP for the SAGCOT Project will serve as a guidance and reference document for the preparation of specific subprojects PMP. 3.3. FUNDAMENTALS OF IPM An understanding of the ecological interrelationships within a farming system; crop, plant, pests organisms and factors influencing their development; An understanding of economical factors within a production system; infestation: loss ratio, market potential and product prices; An understanding of socio-cultural decision-making behaviour of the farmers; traditional preferences, risk behaviour, etc; The involvement of the farmers in the analysis of the plant protection problems and in the elaboration of solutions; and The successive creation of a legislative and agricultural policy framework conducive to a sustainable IPM strategy; plant protection and pesticides legislation; pesticides registration and price policy. 3.4. KEY CHARACTERISTICS OF AN IPM APPROACH Use all available, suitable methods of prevention and control, including resistant varieties, cultural methods such as planting time, intercropping and crop rotation, biological control. Pesticides will only be used as a last resort, but preferably selective ones, or used in a selective way to prevent detrimental effects on natural enemies and other non-target organisms. Conservation of the ecosystem, stimulate the presence of natural enemies No total eradication of all noxious organisms, but keeping them at a low level Technology is developed by farmers in close co-operation with researchers and extensionists Farmers make their own decisions and carry them out. Page 10 of 110 3.5. THE PRINCIPLES OF AN IPM Grow a healthy crop; Recognise pests, diseases, and natural enemies; Carry out regular observations; and Make the right crop protection decisions, through discussion with fellow farmers. Page 11 of 110 4. EXISTING AND ANTICIPATED PEST PROBLEMS The existing and anticipated pest problems in the SAGCOT Project Area are described in this chapter. A list on food, cash and horticultural crops and migratory and outbreak pests is presented and an analysis is made on existing and anticipated pest problems and their management practices. 4.1 FOOD CROPS The major food crops shown in Table 4.1 which are grown in the target project areas are maize, rice, sorghum, millet, beans, cassava, and banana. The importance of each crop varies from one area to another and the priority list varies depending on the source of information. However, maize is the most popular staple of many Tanzanians, and is a major cash and food crop in many parts of the Southern Highlands. This is followed by rice, sorghum, millet, bananas, beans, cassava, sweet potato, wheat and legumes. Some of these crops such as rice, maize, beans, sorghum and millet are regarded as food and cash crops depending on the area. Table 4.1: Summary of major food, cash and horticulture crops grown in the SAGCOT Project Area Zone Regions Major crops Horticultural crops Food Cash Eastern Morogoro Coast Tanga Dar es Salaam Maize Rice Beans Cassava Round potatoes Sorghum Banana Coffee Cotton Cashew Sugarcane Tea Citrus fruits Pineapples Brassicas Tomatoes Mangoes Coconuts Southern Highlands Iringa Mbeya Ruvuma Rukwa Maize Sorghum Fingermillet Rice Beans Cassava Sweet Found potatoes Tea Tobacco Coffee Rice Cotton Sunflower Wheat Cashew Pyrethrum Palm oil Bananas Tomatoes Mangoes Pineapples Potatoes Peas Brassicas Maize Maize is the major staple food crop and it is grown in all the agro-ecological zones. It can be grown over a wide range of altitude ranging from 0-2400m a.s.l. Maize requires an optimum rainfall of 1800 mm. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 1,564,000 ha and 2,810,490 ha were put under maize cultivation in 1995/6-2002/03 respectively with overall production of 1,831,200 and 3,415,600 tons. In terms of percentage contribution in 2002/03, the Southern Highlands produce 45%, followed by Lake Zone (20%), Northern Zone (11.0%), Western Zone (10%), Eastern Zone (8%), Central Zone (4%), and Southern Zone (2.5%). The southern highlands supplies 90% of the strategic grain reserve (SGR), thus making it the national grain basket. The major insect pests of maize are: African maize stakeborer (Bossuela fusca), pink stalkborer (Sesamia calamistis), spotted stalkborer (chilo partellus), American bollworm (Helicoverpa armigera), cutworms- greasy cutworm (Agrotis ipsilion), and maize leafhopper (Cecadulina mbila). The major diseases of maize are: leaf rusts (Puccinia sorghi and P.polysora), leaf blights (Helminghtosporium turcicum and maydis), Maydis leaf blight (Helminthosparium maydis), maize streak disease (maize streak virus), grey leaf spot (GLS) (Cerospora zaea-maydis), Gibberella Ear Rots, common sut. Page 12 of 110 Because the crop is grown under different agro-ecological zones, pest problems (pre and post harvest) associated with it and the recommended management options vary accordingly (Table 4.2). Table 4.2: Major maize pest problems and recommended management practices Zone Pest Recommended management practices Southern Highlands Insects Pre-harvest Stalk borers (Busseola fusca) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Use the extract of Neuratanenia mitis, a botanical pesticide African armyworm (Spodoptera exempta) Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical extract timely (Table 4.3) Seedling weevils (Tanymecus spp. & Mesokeuvus spp) Timely planting to escape damage Scout the crop Apply lambda cyhalothrin if necessary (Table 4.3) Page 13 of 110 Zone Pest Recommended management practices Post harvest Larger grain borer (LGB) Weevils Moths Selection of tolerant varieties Timely harvest Dehusking and shelling Proper drying Sorting and cleaning of the produce Cleaning & repair of the storage facilities Use rodent guards in areas with rat problems Use improved granaries Use appropriate natural grain protectants e.g. where applicable or Use recommended insecticides at recommended dosage (Table 4.3) and/or Keep the grain in air tight containers and store these in a shady place, preferably in-doors Carry out regular inspection of the store and produce. Timely detection of any damage to the grain and/or storage structure is essential to minimise potential loss or damage Promote biological control of LGB using Teretriosoma nigrescens (Tn) to minimise infestation from wild sources. This is the task of the national plant protection services because the agents have to be reared and released in strategic sites. However, the farmers will benefit from this strategy. Diseases Grey leaf spots (GLS) Crop rotation Plant recommended resistant varieties e.g. H6302, UH6010, TMV-2 Observe recommended time of planting Removal of infected plant debris by deep ploughing Maize streak virus Early planting Plant recommended resistant varieties e.g. TMV-1 in areas below 1500m above sea level, Kilima ST and Katumani ST and Staha Northern leaf blight Rotation Deep plough of the crop residues Plant recommended resistant varieties e.g. H6302, UH6010, TMV-2, H614 Page 14 of 110 Zone Pest Recommended management practices Weeds All types See Table 3.4 Hand pulling and hoe weeding Intercropping Use resistant/tolerant varieties Improvement of soil fertility Tillage Proper land preparation Timely weeding (at 2 and 5-6 weeks after planting) Apply recommended herbicides Eastern Insects Pre harvest Stalk borers Follow recommended time of planting Proper disposal of crop residue Armyworms Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 4.3) Post harvest Larger grain borer (LGB), Weevils, Moths As Northern Diseases Maize streak virus Observe recommended planting dates Plant recommended tolerant varieties e.g. Kito-ST, Staha-ST, Kilima-ST Weeds All types Proper land preparation Timely weeding (at 2 and 4 weeks after planting) Use recommended herbicide (Table 4.3) Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000; Mbwaga et.al. 1993. Table 4.3: List of pesticides recommended for use on maize Chemical Common name Formulatio n Application rate Target pest Comments Insecticides Post harvest Cypermethrin 0.5% D 100gm/100kgs LGB Permethrin 0.5%D 100gm/100kgs LGB Pirimiphos methyl 2% D 200- 500gm/100kgs All storage insect pests for all grains Not good enough against LGB Pirimiphos methyl + permethrin 1.6% + 0.3%D 100gm/100kgs All storage insect pests for all grains Herbicides Atrazine + metalochlor 50% FW 4l/ha All types Apply pre-emergence Atrazine 80% WP 2.5 to 3.0 l/ha All types Pre/post emergence Notes: 1. All herbicides are applied using knapsack sprayers. Page 15 of 110 2. All the insecticides for storage pests are in dust form and therefore used as supplied without mixing with anything else. 3. The pre-harvest insecticides are used without mixing. 4. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn in the market. Therefore always consult the nearest plant protection extension worker if in doubt. Rice In Tanzania rice is considered to be cash and food crop. Almost half of the world population use rice as its staple food in Asia and Africa. Tanzania is the largest producer and consumer of rice in the East, Central and Southern African region after Madagascar (Banwo (2001). According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 439,300 ha and 626,300 ha were put under rice cultivation in 1996/97-2002/03 respectively with overall production of 549,700 and 1,283,700 tons. The major rice production areas are the coastal zone, western zone up to Lake Victoria, areas around the lakes and other area with enough water such as Kilombero valley and southern plains. The crop is grown under different agro-ecological areas (upland, lowland and irrigated environments) and therefore, the pest pressure varies accordingly (Table 4.5). Overall, upland rice contributes 80% while lowland rice is only 20% of the total production (Kanyeka, et.al.1995). Locally, the economic value of rice depends largely on where it is grown. In Mwanza and Shinyanga regions, it is grown mostly for cash whereas in Morogoro, it is a cash-food crop (Table 4.1). Because it is grown in many parts of the country and under different management systems (rain-fed and under irrigation), the pest problems and management tactics also vary (Table 4.5). Unfortunately and until recently, issues related to pest management in rice production were given low priority (Banwo et al.2001), and therefore, available information on pest control options is scanty (Table 4.5). The most devastating pest of rice in Tanzania is the rice yellow mottle virus (RYMV). Although indigenous to Africa, the disease was reported in Tanzania in 1980s and now has spread to all the major growing areas notably in Morogoro, Mbeya and Mwanza (Banwo, et al. 2001). The disease can cause up to 92% yield loss on \"super\", the most popular rice variety in Tanzania (Banwo, 2003). The only viable control option for the disease is by planting resistant varieties). Unfortunately, only a few of the local varieties in the SSD-1, SSD-3, SSD-5, SSD-7, SSD-35 series have same level of resistance to the disease. Table 4.5: Major pests of rice and recommended management practices Pests Recommended management practices Insects Stem borers (Chilo partellus, C. orichalcociliellus, Maliarpha separatella, Sesamia calamistis) Plant recommended early maturing varieties Destruction of eggs in the seedbeds Early planting Proper fertilisation Use recommended plant spacing Observe simultaneous planting Destruction of stubble after harvest Clean weeding Plough after harvest to expose the eggs to natural enemies Stalk-eyed fly (Diopsis spp) African rice gall midge (Orseolia oryzivora) Small rice grasshoppers (Oxya spp.) (Senene) African armyworm (Spodoptera exempta) Resistance varieties Stalk management in dry season Flea beetles (Chaetocnema varicornis) Suspected to be the key vector of RYMV (Banwo, et al. in press; Kibanda, 2001). No known control measures. Rice hispa (Dicladispa sp) Page 16 of 110 Pests Recommended management practices Weeds Cyperus rotandus, striga All types (see Table 4.5) Early clean weeding Use recommended herbicides if necessary Diseases Rice yellow mottle virus Field sanitation including buring of crop residues and removal of volunteer plants Use of resistant varieties Rice blast (Pyricularia oryzae) Destruction of crop residues Clean seeds Avoid use of excessive nitrogen fertilizers Use of wide spacing to avoid overcrowding Use resistance varieties Appropriate crop rotation Timely planting Burying crop debris Brown leaf spot (Helminthosporium spp) Sheath rot (Acrocylindrium oryzae) Vermines Birds Wild pigs Hippopotamus Rats Scaring Bush clearing Early weeding Early harvesting Spraying against Quelea Queleas Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 Sorghum Sorghum is an important subsistence food crop in Tanzania that is grown mainly in Morogoro, Lindi, Tabora, Dodoma, Singida, Mwanza, Shinyanga and Mara regions. Sorghum is a drought resistant crop. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 622,400 ha and 557,323 ha were put under sorghum cultivation in 1996/97-2002/03 respectively with overall production of 498,500 and 461,400 tons. Sorghum needs a minimum of 300-380 mm of rainfall during growth and has a wide range of pests (Table4.6). The recommended pest management strategies are summarised in Table 4.6. Table 4.6: Sorghum major pests and recommended management practices Pest Recommended management practices Insects Pre harvest Shootfly (Atherigoma soccata) Observe recommended time of planting to avoid the pest Plant recommended varieties Destroy infected crop residues by burying Apply recommended insecticides if necessary e.g. endosulfan or fenitrothion Stalk borers (Busseola fusca & Chilo partellus) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Use the extract of Neuratanenia mitis, a botanical pesticide Page 17 of 110 Pest Recommended management practices African armyworm ((Spodoptera exempta) Cutworms (agrotis ipsilon) Plough a month before sowing Rapid seedling growth Weeding early Use of plant treated seeds Treat the seed bed with wood ash Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 3.3) Post harvest LGB, weevils and moths Use of botanicals, e.g. Neem or pili-pili Bio-control (use of natural enemies) Diseases Grain moulds Plant recommended tolerant/resistant varieties e.g. IS 9470, IS23599, IS24995, cv. Framida and cv. Serena Observe recommended time of planting Field sanitation Practice good crop rotation Grey leaf spot (Cercospora sorghi) Observe recommended time of planting Field sanitation Practice good crop rotation Use clean planting material Anthracnose (Colletotrichum graminiocola) Plant recommended tolerant varieties e.g. Tegemeo, Serena, Framida and Segaolane Observe recommended time of planting Field sanitation Rust (Puccinia purpurea) Use disease free seeds and follow recommended spacing Plough in crops immediately after harvesting Crop rotation Observe recommended time of planting Field sanitation Leaf blight (Exserohilum turcicum) Plant recommended tolerant varieties e.g. Tegemeo and Serena Observe recommended time of planting Field sanitation Ladder leaf spot (Cercospora fusimaculans) Observe recommended time of planting Field sanitation Practice good crop rotation Use clean planting material Sooty stripe (Ramulispora sorghi) Zonate leaf spot (Gleocercospora sorghi) Weeds Witchweed (Striga asiatica) As for maize in Kagera region Page 18 of 110 Pest Recommended management practices Vermines Quelea quelea spp Warthog Hippopotamus Scaring Bird trapping Farmers to scout potential breeding sites and destroy nests Monitoring and organised aerial spraying using fenthion 60%ULV at the rate of 2.0l/ha Spot spraying, targeting roosting sites Source: LZARDI-Ukiriguru 2000; Mbwaga, et.al. (1993) and MAFS: Plant Pests Field Book: A guide to management, 2002 Pearl millet Pearl millet (burlush millet) is one of the indigenous subsistence food crops which grow well in areas with reliable rainfall such as those found in central Tanzania. The crop has many advantages over other cereal crops in that it is drought tolerant and therefore suitable for the semi-arid areas of the country (Mbwaga et.al. 1993). Pearl millet grows best on reasonably fertile soils but they have the ability to give satisfactory yields on infertile soils. It is one of the most import food crops in the dry semi-arid regions, mainly Dodoma and Singida. Significant quantities of pearly millet are also produced in Shinyanga, Mwanza and Tabora regions. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 353,360 ha and 242,100 ha were put under millet (bulrush and finger millet) cultivation in 1995/6-2002/03 respectively with overall production of 347,700 and 118,200 tons. There has been limited local research work on the crop and therefore available information on its major pest problems and management options is scanty (Table 4.7). Table 4.7 The major pests of pearl millet and recommended management practices Pest Recommended management practices Insects Pre harvest Shootfly (Atherigoma soccata) Observe recommended time of planting to avoid the pest Plant recommended varieties Destroy infected crop residues by burying Apply recommended insecticides if necessary e.g. fenitrothion Stalk borers (Busseola fusca & Chilo partellus) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Carbofuran and carbaryl are effective insecticides Use the extract of Neuratanenia mitis, a botanical pesticide Page 19 of 110 Pest Recommended management practices African armyworm ((Spodoptera exempta) Cutworms (agrotis ipsilon) Plough a month before sowing Rapid seedling growth Weeding early Use of plant treated seeds Treat the seed bed with wood ash Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 3.3) Leaf spot No recommendation Rust (Puccinia penniseti) Observe recommended time of planting Field sanitation Plant recommended tolerant varieties if available Smut (Moesziomyce bullatus) Plant resistant varieties e.g. ICMV 82132, ICMPS 900-9-3 & ICMPS 1500-7-3-2 Downy mildew (Sclerospora graminicola) Early sowing Use of disease free seed Transplanting the crop suffers less from the disease Roughing of infected plants to avoid secondary infection Weeds Witchweed (Striga spp) Farm yard manure Weeding Birds Quelea quelea spp Scaring Bird trapping Farmers to scout potential breeding sites and destroy nests Monitoring and organised aerial spraying using fenthion 60%ULV at the rate of 2.0l/ha Spot spraying, targeting roosting sites Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 Mbwaga et.al. 1993. Banana Banana is a major food crop for about 4.0 million people in Kilimanjaro, Arusha, Kagera, Mbeya and Kigoma (Table 4.1 and maps). The produce has various uses but it is mostly used as a fruit and/or vegetable. It is therefore eaten either cooked, or as desert when ripe. Bananas are of great importance to the rural population in the Chagga homegardening and to those living in the Pare and Usambara mountains. The crop provides households with both food and income, while its produce includes leaves for thatching houses and pseudostema to feed livestock (although of poor nutritional value). Bananas are growing in association with various other crops, such as coffee, beans, maize, cocoyams and fruit trees. Farmers apply no chemical control measures to protect the crop. According to Basic Data Agriculture Sector 1996/97- 2002/2003 (MAFS 2004), it is estimated that 241,400 ha and 390,200 ha were put under banana cultivation in 1996/7-2002/03 respectively with overall production of 604.100 and 1,898,800 tons. The major disease to bananas is Panama wilt (Fusarium), while balck S igatoka or balck leaf streak disease is of lesser importance. Both diseases are caused by fungi and can destroy all susceptible varities within a large area. Panama disease are caused is soil borne and spreads through soil and infected planting materials. Black Sigatoka is soil borne and spreads by wind, water dripping or splashing, but also by infected planting materials. Farmers’ control of both diseases is limited to removal of diseased plants, application of large Page 20 of 110 quantities of farmyard manure and avoidance of planting susceptible varieties. Options for their control by IPM include field sanitation (such as rotation), use of clean suckers and planting of resistant varieties. Application of farmyard manure reduces the damaging effect of the two diseases. Two important pests causing great loss of harvest are banana weevils and nematodes. The latter cause toppling of the plants because the rooting system is seriously weakened. Weevils cause snapping at ground level of the bananas. Both pests may be present in planting materials and hence infect new fields. The extent of damage by weevils and nematodes is further enhanced by poor soil fertility management. Weevils can be trapped and removed by using split pseudo stems and corns, but application of botanicals, such as Tephrosia, tobacco and Mexican marigold can also be tried. The key pests and their management options for the northern zone and Kagera regions are summarised in Tables 4.8. It has to be noted that, local agronomic practices and agro-ecological conditions influence the pest types and pressure. Therefore, farmers in other banana growing areas should be advised to select and experiment with the options developed for the northern zone where similar pest problems are experienced. Table 4.8: Banana major pest problems and recommended management practices for Lake and Northern Zones Pest Recommended management practices Insects Banana weevil (Cosmopolites sordidus) (Temnoschoita delumbrata) Kiswahili name: Funza ya migomba Practice crop rotation Intercropping with legume which reduce weevil movement Sanitation/crop hygiene Use healthy planting material (use a combination of corm paring and hot water (at 550C for 20 minutes or solarisation ) treatment Sequential planting to avoid nematode infested areas Rational use of weevil trapping with using bate (split pseudostems or discs and corns) Use of repellent botanicals, such as Tephrosia, tobacco, Mexican marigold, Neem and Iboza multiflora Improved soil fertility management and crop husbandry Mulching Deep planting to discourage egg-laying Application of high quantities of manure to improve soil fertility Harvest hygiene Ants Trapping Diseases Panama disease or Fusarium wilt (Fusarium oxysporum f.sp. cubense) Kiswahili name: Mnyauko panama Grow banana cultivars with resistance to pest and disease like the East African Highland bananas (Matoke) Fallow or rotation Sanitation/crop hygiene Planting of clean suckers Establish new crop on disease free sites Mulching Application of high quantities of manure Destroy debris of wilted plants by burning Black and yellow sigatoka (Mycosphaerella fijiensis) Kiswahili name: Sigatoka Resistant cultivars Uproot and burn the affected parts Page 21 of 110 Pest Recommended management practices nyeusi Use of large quantities of farmyard manure Pland and field sanitation Use disease free seeds Prune, remove suckers and weed frequently Avoid close spacing Avoid transfer of seeds from affected areas to unaffected areas Nematodes Burrowing nematodes, e.g. Pratylenchus goodeyi, Radophilus similis, Meloidogyne spp. and Helichotylenchus multicintus Improved farm management, including sequential replanting and soil fertility Practice crop rotation Sanitation/crop hygiene Farmer training in disease identification and control measures Use healthy planting material Establish new crop on disease free sites Mulching to enhance beneficial soil organisms to suppress nematodes Treatment of infested suckers with hot water Application of high quantities of manure Sterilise planting material through solarization and/or the hot water method as for weevil control Vermines Rodents Trapping by using local methods Cleanliness of the farm Source: MAFS: Plant Pests Field Book: A guide to management, 2003, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000; Anania & Sayi (2001), Paul, et.al. (2000) Cassava Cassava is one of the major food crops in all areas except in the northern zone. Increased production is affected by pre-harvest and post harvest pest problems. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 1,426,000 ha and 2,503,500 ha were put under casava cultivation in 1996/7-2002/03 respectively with overall production of 2,149,100 and 2,833,200 tons. Table 4.9: Cassava major pests and recommended management practices Pest Recommended management practices Insects Pre harvest Cassava mealybugs (Phenococcus manihot) Improve the soil fertility by manuring, mulching and intercropping Practice crop rotation Use clean planting material Resistant varieties Plant health stem cuttings Plant as the beginning of the wet season Cassava green mites (Mononychellus tanajaa) Improve the soil fertility by manuring, mulching and intercropping Practice crop rotation Use clean planting material Resistant varieties Plant health stem cuttings Plant as the beginning of the wet season Page 22 of 110 Pest Recommended management practices Cassava root scale (Stictococus vayssierra) Plant health stem cuttings Plant as the beginning of the wet season Cassave white scale (Aonidomytilus albus) Plant health stem cuttings Plant as the beginning of the wet season Variegated grasshopper (Zonocerus variegates) Destructing the breeding sites Dig egg-laying sites of variegates grasshopper in the wet season to expose and destroy egg pod of the pest Biological control: use fungal pathogens, e.g. Metarlizium spp Spiralling whitefly (Aleurodicus dispersus) Crop rotation Plant health stem cuttings Plant as the beginning of the wet season White fly (Bemisia tabaci) Eliminate the sources of the virus Plant health stem cuttings Plant as the beginning of the wet season Post harvest LGB, Weevils and Red flour beetle Use of botanicals, e.g. Neem or pili-pili Bio-control (use of natural enemies) Diseases Cassava mosaic disease (CMD) Improve the soil by manuring, mulching and intercrops Plant health stem cuttings After harvesting destroy infected cassava stems Use resistance varieties that tolerate CMD like Kibaha, Msitu Zanzibar, Aipin Valencia, Kigoma nyekundu and Mzungu Manipulate sowing date and planting spacing to reduce incidence of the disease Plan resistance varities against TMS 4(2)1425, TMS 81983, TMS 83/01762 Cassava bacterial blight (Xanthomorias ampestris) Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Avoid growing cassava consecutively on the same field Check field regularly Fallow practice Use of resistant varieties Rogue and destroy plants Page 23 of 110 Pest Recommended management practices Cassava Anthracnose (Colletotrichum graminiocola) Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Avoid growing cassava consecutively on the same field Check field regularly Rogue and destroy plants Cassava brown streak disease Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Harvest early Grow resistance varieties like Mzungu Cassava root rot disease (Phytophtora, Pithium and Fusarium spp) Harvest early Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Weeds Acanthospermum spp Cultural methods Vermines Baboons, Monkeys and rats (Lake Zone) Hunting farmer groups Use of traps Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru 2000; Pre-harvest Cassava mealybugs (Phenococcus manihot) The pest is widespread with frequent outbreaks in Ruvuma, Kigoma, Dodoma and Mara regions. Effective control is achieved through biological control using a wasp (Apoanagrus lopezi). This wasp has reduced the population significantly in most parts of Tanzania (Anon, 1999). However, in parts of Mara, Mwanza, Iringa and Kigoma, the pest is still devastating cassava. In these areas, another bio-control agent, (Hyperapsis notata), a predator, was released to compliment the wasp. Because of limited funding, the predator has been released in a few areas only (Anon, 1999). Page 24 of 110 Cassava Green mites (Mononychellus tanajoa) This pest is also widespread but is more devastating in the Lake zone. The pest can cause 60% to 80% crop loss if left uncontrolled (Anon, 1999). Like the case of the mealybugs, effective control can be achieved through biological control. To affect this, an exotic predatory mite, Tyhlodromallus aripo, was imported and first released 1998 (Anon, 1999). The agent has spread too many areas including the southern zone, parts of Coast, Lake and S. Highlands. Where the agent has established, the pest population has been reduced considerably (Anon, 1999). Cassava white mites This is a major pest in the Lake zone. Currently, the only recommended management option is uprooting and burning of infected plants. However, some local selections are known to be tolerant to the pest. Such varieties should be identified, popularised, multiplied and distributed to farmers. Cassava mosaic disease (East AfricaCMV, ACMV) The disease is widespread but is more devastating in Mwanza, Mara, Kigoma and Coast regions where an incidence of 60% to 80% has been recorded (Dr. Rose Mohamed, personal communication). Farmers in affected areas are advised to uproot and burn infected plants and encouraged to plant resistant varieties. Currently, multiplication of resistant varieties (TMS 60142, TMS 30337, TMS 4(2) 1425, TMS 30572) is being done at Lake Zone Research and Development Institute in Maruku and Ukiriguru in collaboration with IITA. In addition, TMS 4(2) 1425 and TMS83/01762 (6) were multiplied in Mara region in collaboration with MARAFIP for distribution to farmers. An open quarantine site at Maruku, Bukoba was established in 1999 to further facilitate efforts to introduce resistant varieties from neighbouring countries (Anon, 2000). Cassava mosaic disease Uganda variant (UgV) The disease is devastating in the Lake zone, particularly in Shinyanga, Kagera, Geita district and Kigoma (R. Mohamed, personal communication). Use of resistant varieties is the only suitable management strategy. Such varieties are not available in the country. Through the East African cassava disease control programme, a resistant variety, Serere selection 4 (SS4), has been identified in Uganda. This material has been brought in the country for multiplication under the CMD East African programme. Cassava brown streak disease The problem is common along the coast (from 0-500m above sea level, from Tanga to Mtwara and around Lake Nyasa. The only viable management option is through planting of tolerant/resistant varieties. Some resistant varieties have already been identified in Kenya. These varieties will be imported through Mwele- Tanga open quarantine for multiplication and distribution to farmers. The work has not yet started due to lack of funds. It is estimated that the national programme will need about US$ 20,000 for two seasons to facilitate importation, multiplication and distribution of clean cuttings to affected areas. Post harvest The larger grain borer (LGB) is the most damaging pest of dried cassava. Loss of about 35% can occur in a period of 4-6 months if uncontrolled (Mallya, 1999). Rodents, particularly the multi-mammate rat (Mastomys natalensis) attacks dried cassava chips and can cause high losses (quality and quantity) and therefore farmers should adopt and use recommended strategies to minimise potential attack. The current integrated stored products guidelines (Nyakunga & Riwa, undated) if adopted, will go a long way in reducing potential losses due to LGB and rodents on dried cassava. Page 25 of 110 Common Beans (Phaseolus) Common beans or phaseolus may be regarded as on e of the principal sources of protein as well as income to most farmers in Tanzania. According to Basic Data Agriculture Sector 2001/2002-2002/2003 (MAFS 2004), it is estimated that 732.200 ha and 651,000 ha were put under rice cultivation in 2001/2002-2002/03 respectively with overall production of 562,200 and 603,200 tons. Beans are grown throughout the country with major production in the southern highlands, northern, eastern and some parts of Lake Zone Consequently, the pest pressure and type varies due to agro-ecological and management differences. Small-scale farmers grow beans mainly as intercrop with maize, while large-scale farmers grow them as monocrop. In contract to large-scale farmers, who apply a wide spectrum of chemicals, small scale farmers mainly apply cultural practices, and storage insecticides to control pests and disease in beans. The most common diseases in beans are angular leaf spot disease, anthracnose, bean rust, and root rots. These are disease transmitted by fungi. One of the common causes of sever damage is the intensive cultivation of beans without sufficient rotation, the cultivation of resistant varieties and seed dressing are potential IPM control measures, but farmers have also to be trained in the proper diagnosis of the diseases. Common pests in beans are stem maggots, brochids and foliage beetles. Maggots of the bean fly and foliate beetles cause damage to the beans while in the field. Brochids are storage insects that may cause severe loss of crop. Storage hygiene, improved storage structures and the application of ash, vegetable oil and botanicals, such as Neem and Tephrosia, are among the potential IPM control measures of bean bruchids. Maggots and foliage beetles may be controlled by seed dressing or spraying with botanicals, or by cultural practices, including rotation, post harvest tillage and earthing-up mulching. Overall, some of the major diseases have been taken care of through breeding and selection for tolerance/resistance (Table 4.10). Farmers in different parts of the country already grow some of the disease tolerant/resistant varieties. The pest management options as summarised in Table 4.10 have been developed for the southern zone but can also be used by farmers in other areas. However, since this is not a blue print, farmers should be advised to select and try them out before full adoption. Table 4.10: The major pest problems of beans and recommended management practices Zone Pest Recommended management practices Southern Highlands Insects Pre- harvest Bean stem maggot (Ophiomyia spp) Seed dressing Apply recommended insecticide or botanical extracts within five days after emergence Plant tolerant/resistant varieties if available Improvement of soil fertility through application of manure and/or fertilisers Bean aphids (Aphis fabae) Practice early planting Apply recommended insecticides or botanical extracts if necessary Bean leaf beetle (Ootheca benningseni) Observe recommended time of planting Practice good crop rotation Post harvest ploughing where possible Apply recommended insecticides Bean pod borer (Helicoverpa armigera) Apply recommended insecticides or botanical extracts Page 26 of 110 Zone Pest Recommended management practices Post harvest Bean bruchids (Acanthoscelides obtectus) Ensure the beans are dry and well cleaned before storage Apply recommended storage insecticide/ botanical extracts Diseases Bean anthracnose Practice good crop rotation Sanitation and crop hygiene Use certified seed Observe recommended time of planting Plant tolerant/resistant varieties e.g. Uyole 98, Uyole 84 & Kabanima Angular leaf spot As above Rust (Uromyces appendiculatus) Avoid planting beans in high altitude areas Practice good crop rotation Sanitation and crop hygiene Plant tolerant/resistant varieties e.g. Ilomba, & Uyole 90 Observe recommended time of planting Spray with recommended fungicide when necessary Haloblight (Pseudomonas sp) Plant tolerant/resistant varieties e.g. Uyole 84 Spray with recommended fungicide when necessary Use certified seed Ascochyta (Phoma sp) Avoid planting beans in high altitude areas Spray with recommended fungicide when necessary Plant tolerant/resistant varieties e.g. Ilomba & Uyole 98 Sanitation and crop hygiene Bean common mosaic virus (BCMV) Plant tolerant/resistant varieties if available Effect good control of aphids Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru 2000; IPM working group in the Northern Zone 2001; Anania, et.al. (2001); Paul, et.al (2000), Madata, et.al. (2001). Sweet Potato The food crop is mainly grown in most small scale farming system. Cultivated areas under sweet potatoes in 2002/2003 were in Mbeya (69,000 ha), Kigoma (27,800 ha), Shinyanga (73,800 ha) and Mwanza (90,200 ha) regions. In 2002/2003 sweet potatoes production was as follows: Kigoma (233,400 tonnes), Shinyanga (164,100 tonnes), Mwanza (150,800 tonnes), Rukwa (87,900 tonnes), Kagera (69,000) and Mbeya (47,000 tonnes). According to Basic Data Agriculture Sector 1996/7/2002-2002/2003 (MAFS 2004), it is estimated that 287,000 ha and 470,600 ha were put under sweet potatoes cultivation in respectively with overall production of 477,700 and 957,500 tons. Sweet potatoes plan an important role during periods of food scarcity and are part of the survival strategies employed by rural households. The crop suffers from two major pests, which reduce significantly its yield: mole rats and may provoke other Page 27 of 110 pathogens to enter and cause rotting. Factors that contribute to the presence of these pests include monocropping, use of infested planting materials (weevils), drought and late harvesting. Table 4.11 presents pests and management practices. Table 4.11 : The major pests of sweet potato and recommended management practices Pest Recommended management practices Insects Sweet potato weevil (Cylas brnneus) Kiswahili name: Fukuzi wa viazi (adult) and Funza wa viazi (larva) Sanitation Use of clean materials Crop rotation Plant varieties that form tubers at a greater depth Early harvesting of tubers; as soon as weevil damage is observed on tuber tips, harvesting should begin Keeping distance (at least 500m) between successive sweet potatoes plots Destroy infected crop residues by burying Planting of repellent species, such as Tephrosia, tobacco and Mexican Hilling up twice (at 4th and 8th week after planting) in the season to cover soil cracks and exposed to minimize eggs laying Traps with pheromones Rough sweet potato weevil (Blosyrus sp) Crop rotation Sanitation Planting of repellent species Botanical pesticide Striped sweet potato weevil (Alcidodes dentipes) Sanitation Use of clean materials Crop rotation Plant varieties that form tubers at a greater depth Early harvesting of tubers; as soon as weevil damage is observed on tuber tips, harvesting should begin Diseases Sweet potato feathery mottle virus (SPFMV) Use of resistant varieties Crop rotation Sanitation Sweet potato sunken vein virus (SPSVV) Avoid disease plants as a source of planting materials Use of resistant varieties Sweet potato virus disease (SPVD) Sanitation Use of resistant varieties Crop rotation Page 28 of 110 Pest Recommended management practices Vermin’s Mole rats (Tachyoryctes splendens) Kiswahili name: fuko Planting of repellent species, such as Tephrosia, tobacco, onion, garlic and Mexican marigold in the field and its boundaries Insert pars of repellent plant species into tunnels Monkeys, wild pigs Local scaring Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 4.2 CASH CROPS The major cash and export crops grown in the target project areas include coffee, cotton, cashew, tea, sisal and tobacco. Coffee, cotton, cashew and tobacco are largely small holder crops. The cash crops have special agro-ecological requirements and therefore are grown in specific zones and areas within the Corridor. Similarly, the pest pressure and management tactics recommended for the crop varies between zones. Coffee In Tanzania coffee is one of main export crops and leading foreign exchange earner. It accounts for about 20% of total domestic export. It is predominantly a small scale crop grown by about 420,000 farmers who produce over 90% of the crop and depend on it for their income and hence social welfare (Nyange 1999). There are two major types of coffee grown in the country. Arabica coffee (Coffee arabica) is grown in all coffee zones (Northern, S. Highlands, Lake and Eastern) while the robusta coffee (Coffee canefora) is mainly grown in Kagera with small amounts in Tanga and Morogoro regions. ). According to Basic Data Agriculture Sector 1996/97-2002/2003 MAFS 2004), it was estimated that overall production in the country was 52,220 and 53,220 in 1997 and 2003 tons respectively. Coffee production for mild, hard arabica and robusta was 29,835, 2,383 and 17,184 tonnes in 2002/2002. Moreover, the bulk of the crop is grown in the northern zone. Coffee insects and other coffee pests are some of the major factors that undermine coffee productivity by direct reduction of crop yield and quality to coffee growers. There are about 850 species of insect pest known (Le Pelly 1973). In Tanzania there are more than 25 insect pests which attach coffee and pests of economic importance. Arabica coffee is much affected by pests, of which the most important species Antesia bug and white stem borer. Of less importance are leaf miner, coffee berry moth, scale insects, mealy bugs, coffee berry borer and rood-knot nematodes. Table 4.12: Coffee pest problems and recommended management practices Zone Pest Recommended management practices Ruvuma sub-zone Insects Antestia bugs (Antestiopsis spp.) Pruning Mbuni stripping Apply recommended insecticides at recommended dosage if necessary Page 29 of 110 Zone Pest Recommended management practices White stem borer and yellow headed stem borer Sanitation and crop hygiene Stem cleaning Mechanical (hook the larvae out if possible) Mealybugs and scale insects Proper planting depth Build the plant \"skirt\" soon after the first harvest to deter ants from climbing through branches to enhance build up of natural enemies Diseases CBD & CLR Management as for the northern zone Fusarium wilt Plant recommended tolerant varieties e.g. KP 423 (locally known as \"nylon\" Field sanitation Proper pruning Weeds All types Clean hand weeding Apply herbicide if necessary. Use recommended herbicides (Table 4.13) Southern Highlands Insects As for Ruvuma sub-zone As for Ruvuma sub-zone Diseases CBD & CLR As for northern zone Fusarium wilt Plant recommended varieties e.g. N36, which should be obtained from certified seed multiplication farms only. Field sanitation Maintain good drainage Uproot and burn any diseased plants and avoid replanting in the same hole for 2 years Source: MAFS: Plant Pests Field Book: A guide to management, 2003; LZARDI-Ukiriguru 2000; IPM working group in the Northern Zone 2001 Table 4.13: List of recommended pesticides for use in coffee Chemical Chemical common name Formulation Lts product/ha Comments Insecticides Diazinon 600EW 1.0 -1.5 Deltamethrin 25%EC 0.5 Chlorpyrifos 4 EC 1.25-2.0 Carbofuran 5%G 60gm/plant Spread the granules around the plant when the soil is wet and rake it into the soil Page 30 of 110 Chemical Chemical common name Formulation Lts product/ha Comments Fenitrothion 50%EC 1.0 -2.0 Profenophos 720EC 0.2 - 0.7 Endosulfan 35%EC 1.0 - 1.5 Fungicides Cyproconazole 100SL 1.0 - 2.0 kg Hexaconazole 5% FL 25-100ml/100l of water CLR Triadimefon 25%EC 1.0 CLR Propineb 25%EC 1.0kg CLR chlorothalonil 50% FW 2.0 - 5.0 CBD & CLR W75 4.5 CBD & CLR 54%FW 4.5 CLR Cupric hydroxide 50WP 7.0 - 8.0kg CBD Cuprous oxide 50WP CBD & CLR Copper oxychloride 50WP 7.0 - 8.0 kg CDB & CLR Herbicides Gyphosate 36% SC 3-6l/ha All types, post emergence Paraquat 20%EC 1-3l/ha All types, post emergence Notes: 1. All pesticides except carbofuran are applied with a knapsack sprayer. 2. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt Cotton Cotton in Tanzania is purely a smallholder crop. The crop is grown in two major zones based on agro- ecological difference. The western cotton growing area (WCGA) include Mwanza, Shinyanga, Mara, Kigoma, Tabora, parts of Kagera, Singida and Kigoma regions, while the eastern cotton growing areas [ECGA] cover Morogoro, parts of Kilimanjaro, Coast and Iringa regions. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it was estimated that overall production of cotton was 221,280 and 188,200 tons in 1997 and 2003 respectively. Similar to coffee, the pest problems and the recommended management options vary depending on location (Tables 4.14, 4.15 & 4.16). The recommended current cotton pest management strategies emphasises integration of several aspects of IPM (Tables 4.14 & 4.15). However not all farmers in all the cotton growing areas are aware and informed about the approaches. Page 31 of 110 A cotton quarantine established in 1946 (Cotton plant quarantine GN 265 of 1946: quarantine areas: Southern Province) is meant to prevent the entry of the red bollworm (Diparopsis castanea) from the neighbouring countries in the south (Malawi, Zambia & Mozambique) to the major traditional cotton area (the WCGA & ECGA). The quarantine has been effective in preventing the entry of the pest in the cotton area to date, and must therefore be maintained. Any attempt to grow cotton in the quarantine area should therefore be strongly discouraged. Should the pest enter the traditional cotton areas, the pest management strategies must be changed, and will probably lead to more use of pesticides, increased health and environmental problems in the traditional cotton growing areas. Crop scouting (regular crop inspection) was recommended in the late 1980s as another IPM component to optimise insecticide cotton spraying in the WCGA. However, to date, only a few farmers in Shinyanga, Kagera and Mara regions practice it. Only the IPM farmer groups and their immediate neighbours practice crop scouting before spraying. It is important to recognise that scouting for a pest is a prerequisite for good crop pest management and judicious use of pesticides. There is therefore a need to mobilise farmers through appropriate training, to inform and enhance wider use of regular crop inspection as a means to optimise the benefits of pesticide use if they have to be used. Crop scouting guidelines have not yet been developed for the ECGA but the approach developed for the WCGA could be tested and fine-tuned by farmers for adoption. Traditionally, spraying against aphids in the WCGA was discouraged for two major reasons. First, it is not economically justified in most seasons. Secondly, aphids are usually controlled by a wide range of its indigenous natural enemies (predators and parasitoids) that builds up in the crop early in the season. In addition, the aphid populations are often washed away by the heavy rains in March/April. Occasionally, the population can build up to damaging levels (resulting to sooty mould, which can damage the quality of the crop). When this occurs, insecticides recommended for the bollworms can be used effectively. The indigenous aphid natural enemies are polyphagous and will also feed on the eggs and larvae of H. armigera, the key pest of cotton in the area. Insecticide mixtures e.g. profenophos + cypermethrin (Table 4.14) were discouraged to safeguard and promote the build up of the natural enemies to further extend integration of bio-control agents in the cotton systems. Table 4.14: Cotton pest problems and recommended management practices in the WCGA Pest Recommended management practices Insects Jassids (Empoasca sp) Plant recommended UK varieties (resistant plant varieties) Spray in case of a severe attack at seedling stage American bollworm (Helicoverpa armigera) The host plants should be inspected regularly Souting Encourage natural enemies Use botanical pesticides like neem and Utupa Plant recommended UK varieties (inditerminant varieties) Early planting Spray with recommended insecticides after scouting (Table 3.13) Page 32 of 110 Pest Recommended management practices Aphids (Aphis gossypii) No spraying. Encourage build up of natural enemies like birds Populations often washed off by rain Spiny bollworm (Earias insulana and E.biplaga) The host plants should be inspected regularly Scouting Encourage natural enemies like birds Use botanical pesticides like neem and Utupa Early planting Lygus (Lygus vosseleri) Spray with insecticides in case of an early season attack Cotton stainers (Dysdercus spp) Observe the close season Early and frequent picking avoid build-up of stainers Sanitation in and around cotton ginneries and buying posts Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Blue bugs (Calidea dregii) Observe the close season Early and frequent picking avoid build-up of stainers Sanitation in and around cotton ginneries and buying posts Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Diseases Bacterial blight (Xanthomonas malvacearum) Rotation Plant recommended UK 82 varieties (resistant plant varieties) Observe the close season Crop sanitation Fusarium wilt (Fusarium oxysporum f.sp. vasinfectum) Rotation Crop sanitation Plant recommended UK 77 or 91 varieties (resistant plant varieties) Alternaria leafspot (Alternaria macrospora) Rotation Field sanitation Page 33 of 110 Pest Recommended management practices Weeds All types (See Table 3.4) Proper land preparation Early clean weeding Use recommended herbicides (Table 12) Vermines Field rats, monkeys and baboons Scaring Trapping Source: MAFS: Plant Pests Field Book: A guide to management, 2003; LZARDI-Ukiriguru 2000 Table 4.15: List of pesticides recommended for use on cotton in the WCGA Chemical Chemical common name Formulation Application rate g a.i./ha Comments Insecticides Endosulfan 25% ULV 625 Cypermethrin 1.8% ULV 45 Fenvalerate 3% ULV 75 Flucythrinate 1.7% ULV 42.5 Lambda cyhalothrin 0.6% ULV 15 Esfenvalerate 0.5% ULV 12.5 Alpha cypermethrin 0.8% ULV 20 Biphenthrin 2%ULV 50 Betacyfluthrin 0.5%ULV 12.5 *Profenofos + cypermethrin 1% + 16% ULV 400+ 25 *Deltamethrin + dimethoate 0.3+ 12 % ULV 7.5 + 300 Flucythrinate 1.33% Me/ULV 33.25 Fungicides Bronopol 10% dust 5/100kg Cuprous oxide 45% dust 5/100kg Herbicides Diuron 80W 1000 For use on light soils only Fluometuron 500FW 2000 For use in light soils only Metalachlor + Dipropetrin 400EC 800+1200 For use in light soils only Page 34 of 110 Notes: All the insecticides are applied using ULV pumps at the rate of 2.5l/ha at a swath width of 4.5 meters. The target pest is the American bollworm and farmers are advised to scout the crop starting from when the first buds are formed or 10 weeks after planting until first boll split before spraying. Early season (before first flower) spraying is strongly discouraged, as this will interfere with the build up of indigenous natural enemies of aphids and the bollworms. All herbicides should be applied pre-emergence. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt *These pesticides are unnecessary for the WCGA as continued use will jeopardise conservation and use on natural bio-control in the cropping system. Table 4.16: Cotton pest problems and recommended management practices in the ECGA Pest Recommended management practices Insects Jassids (Empoasca sp) Plant recommended IL varieties (resistant plant varieties) Spray in case of a severe attack at seedling stage American bollworm (Helicoverpa armigera) Plant recommended IL varieties Early planting Aphids (Aphis gossypii) Spray using recommended insecticides (Table 14) Cotton stainers (Dysdercus spp) Observe the close season (mid-September to early November) Early frequent picking Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Sanitation in and around cotton ginneries and buying posts Pink bollworm (Pectinophora gossypiella) Early planting and early picking Close season Diseases Bacterial blight (Xanthomonas malvacearum) Plant recommended IL varieties (resistant varieties) Observe close season Alternaria leafspot (Alternaria macrospora) Plant dressed seed only (Table 14) Weeds All types see Table 3.4 Cultural control Good land preparation Early hand weeding Use recommended herbicides (Table 14) Page 35 of 110 Table 4.17: List of pesticides recommended for use on cotton in the ECGA Chemical Chemical common name Formulation Application rate g a.i./ha Lts product/ha Comments Insecticides Cypermethrin 1.8% ULV 45 2.5 Cypermethrin 10%EC 45 0.45 Fenvalerate 20% EC 75 0.375 Flucythrinate 10% EC 42.5 0.425 Lambda cyhalothrin 0.6% ULV 15 2.5 5% EC 20 0.4 Esfenvalerate 2.5% EC 20 0.8 Deltamethrin 0.3% ULV 7.5 2.5 0.5% ULV 12.5 2.5 2.5%EC 7.5 0.2 Fluvalinate 2%EC 100 0.2 Fungicides Bronopol 10% dust 5/100kg Cuprous oxide 45% dust 5/100kg Herbicides Fluometuron 500W 2500-3000 3500 5.0 - 6.0 7.0 Light and medium soils Heavy soils Notes: The herbicides should be applied pre-emergence only. All ULV formulations are applied using the ULV pump at a swath width of 4.5 m. Spraying is done once a week beginning 8 weeks after planting and should continue until boll split. All the EC formulations are applied by knapsack sprayers at the rate of 120l/ha The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt Cashewnuts In the southern zone widespread planting of cashew was carried out after 1945 and in a relatively short period of time, it developed into an important cash crop for smallholders. It appears that expansion first started on the Western Makonde Plateau and then spread northwards into Lindi and Coast regions and eastwards into Ruvuma. Cashew is mostly grown on poor soils in the coastal districts and the south of the country; Mtwara, Lindi and Ruvuma produce about 70% of the crop. By 1960, the region gave 40,000 tonnes of nuts which were being exported and it had become Tanzania’s fourth most valuable export. Production continued to increase and reached a peak of 145,000 tonnes in 1973/4. From the peak year there was a catastrophic decline in production to a low of 16,500 tonnes in 1986/7. Some of the reasons for such a dramatic fall in production were due to a complex of socio-economic and biological factors (Brown, et. al. 1984). The biological factors which are relevant in the context of this report: The onset of powdery mildew disease (Oidium anacardii Noack) Overcrowding of trees According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it was estimated overall production of cashewnuts was 65,400 and 92,200 in 1997 and 2003 respectively. Powder mildew disease (PMD) Oldium anacardii Page 36 of 110 The most serious biological constraint to cashew production in East and Southern Africa is powdery mildew disease, Oldium anacardii. In East Africa, PMD develops on young growing tissue, e.g. new shoots with tender leaves, panicles from the very young to the mature, apples and young nuts. The infected parts look as though they are covered in a white/grey powder. Severely infected young leaves change colour from green to brown, become deformed and eventually drop off prematurely. Mature, older leaves, with a well-developed cucile, are not attached. Prior to early 1970’s, PMP was not a problem in East and Southern Africa. It was first officially reported in Tanzania and for that matter, Africa, in 1979 (Casuli 1979). PMD was one of the factors responsible for the catastrophic decline in cashew production with tool place in Tanzania from 1973 to 1986. A range of different control measures against PMD were developed by research, to try and cater for different farmer types and address various environmental concerns. Very fine sulphur dust (usually 99% pure) has been used in Tanzania for more than 15 years to control PMD; the dust is blown on the trees using motorized blowers. However, only 22% of the dust is deposited on the tree and if dew is absent at the time of application, the percentage deposited on the tree drops off dramatically (Smith at.al1995). Most of sulphur ends up on the soil, where in the longer term, it has caused soil acidification in various parties on the Makonde plateau in Mtwara region (Ngatunga, 2001). Other diseases but of less economic importance in Tanzania include anthracnose (Colletrotrichum gloeosporides Penz), dieback (Phomopsis anacardii Punith), cercospora leaf spot (Pseudocercospora anacardii Nova), pestalotia leaf spot (Pestalotia hetercornis Guba) and wilting syndrome which causes shedding of leaves and sometimes death, is a minor, sporadic problems (Sijaona 1997). Sucking Pests (Helopeltis and Pseudotheraptus) The sucking pests Helopeltis and Pseudotheraptus Miller (Hemiptera: Miridae), H. schoutedenii Reuter and Pseudotheraptus way (Hemiptra: Corediae) are the main insect pests of cashew in East Africa. Sucking pest damage can be very variable from year to year and place and place. In Tanzania, Helopetis populations tend to build up on cashew from May/June to September/Octover, coincind with the period of leaf flush and panicle development (Topper 1998). Sucking pest leaf damage can stake the form of black lesions on petioles or on the leaf midrib, or black angular spots on the leaf surface. The presence of the weaver ant, Oecophyla longinoda (Hymenoptera: Fromicidae) has been shown to have a significant effect in reducing sucking pest damage. It is possible to assist these predators in colonising new trees and thereby enhance their capacity for control of sucking pests. Other less important insect pests are trunk borer (Mecocorynus loripes, Coleoptera, Curculionidae) – the larvae of this large weevil bore through the sapwood of branches and trunks, which result in the death of the infected part of the whole tree. This is the main cash crop of the southern zone and along the coast in the eastern zone. The pest problems and respective recommended management approaches are similar in all cashew-growing areas. Although the current pest management options advocate use of IPM approaches (Table 3.14), there is evidence to show that there is an increase in insect pest pressure due to excessive use of sulphur to control powdery mildew (Anon, 2000). Alternative pesticides have been identified and registered since 1994 (Anon, 2000) but the new products have not yet been popularised among growers. Education and mobilisation of farmers is needed to promote wide adoption and use of the recommended disease tolerant/resistant clones and cultural practices (Table 15) to reduce over reliance on chemical pesticides (Table 4.17) for the control of the major diseases. Table 4.18: Major pests and recommended management practices in cashew Page 37 of 110 Pest Recommended management practices Insects Coreid bugs (Pseudotheraptus wayi) Biological control using the African weaver ant (Oecophilla longinoda). T o enhance effectiveness of the bio-control agents, farmers are advised to do the following: 1- Apply Hydramethyl to control Brown house ants (Pheidole megasephala) when necessary 2- Interplant coconut with recommended suitable host trees of weaver ants 3- Construct artificial aerial bridges to facilitate mobility of weaver ants between trees 4- Plant weaver ant nests in areas where they do not occur naturally Apply recommended insecticide at recommended dosage (Table 16) in case of severe outbreaks Holopetlis bugs (Helopeltis anacardi) Kiswahili name: Mbu wa mikorosho Biological control using the African weaver ant (Oecophilla longinoda). (Maji Moto) Not intercropping pigeon pea with cashew Apply recommended insecticide at recommended dosage (Table 16) in case of severe outbreaks Cashew mealybugs (Pseudococcus longispinus) Crop sanitation (removal & proper disposal of affected plant parts) Biological control Thrips (Selenothrips rubrocinctus) Control should mainly target larvae stage during early stages of flowering Stem borers, Weevils, (Mecocorynus loripes) Adults should be collected and destroyed by hand Mechanical, using a recommended hooks If the tree is severely attacked, cut and dispose properly Diseases Powdery mildew (Oidium anacardii) Prune to provide good ventilation and aeration within trees making microclimate not conducive to the pathogen multiplication Scouting For established plantations, practice selective thinning Remove off-season young shoots which can be sources of fresh innoculum during the season Sanitation Thin densely populated trees and leave them well spaced, to reduce or delay mildew epidemic due to changes in microclimate in the field Plant recommended tolerant clones e.g. AC4, AC10/220, AZA2 and at recommended spacing Apply recommended fungicides as appropriate (Table 16) Anthracnose (Colletotrichum gloeosporioides) Remove and burning of all infected organs before the start of the cashew season. Plant recommended tolerant clones e.g. AC4, AC10/220, AZA2 and at recommended spacing Apply at recommended pesticide at correct rate and time (Table 16) Dieback (Phonopsis anacardii) Remove and burning of all infected organs before the start of the cashew season. Apply at recommended pesticide at correct rate and time (Table 16) Wilt syndrome Source: MAFS: Plant Pests Field Book: A guide to management, 2003; Topper, et, al, 2003 Page 38 of 110 Table 4.19: Pesticides recommended for use on cashew Chemical Chemical common name Formulation Application rate Target pest Comments Insecticide Fenitrothion 50% EC 17ml/tree Thrips Profenofos 48%EC Cashew mealybugs lambda cyhalothrin 5%EC 5ml in 1 l of water per tree Helopeltis & Coreid bugs Hydamethyl Brown house ants (Table 11) Fungicides Sulphur D 250gm/tree Powdery mildew Apply with motorised blower Hexaconazole 5%FL 10-15 ml in 0.75 - 1.25 l of water, three sprays at 21 days interval Penconazole 10%EC Triadimenol 25%EC Copper hydroxide 50%WP Anthracnose Note: 1. All the pesticides except for sulphur, are applied using a knapsack sprayer or with a mist blower (Sijaona, & Anthony, 1998; Sijaona & Barbanas, 1998) 2. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt. 4.3 HORTICULTURAL CROPS A wide range of horticultural crops are grown in Tanzania (Table 4.1). However, the sub-sector is still under developed and poorly exploited for several main reasons. First, the resources allocated for research and development to the sub sector has always been inadequate. At the national level, the sub sector has been accorded only medium to low priority. IPM research on vegetable and fruit crops has a very low profile as reflected by the state of inadequate funding for research and development as well as lack of staff continuity in the sub sector. On-going research activities are patchy and uncoordinated. Consequently, local information on appropriate pest management tactics for the major horticultural crops is scanty except for coconut and tomatoes. The coconut programme based at ARI Mikocheni has done commendable work by developing appropriate IPM approaches for coconut cropping systems that can be extended to farming communities in the coconut growing areas (Table 4.17). Effort to improve tomato production through breeding and selection for tolerance and/or resistance to key pests, particularly diseases, in the country has been facilitated by the AVRDC Arusha station beginning in 1994. For the majority of crops, e.g. mangoes, farmers are experimenting with borrowed ideas and fine-tuning them to solve pertinent pest problems. The cut flower industry, which is a domain of large-scale growers, operates independent of the national system, and therefore, each grower has in-house capacity and capability to address pest problems. Coconuts Coconut production is basically a smallholder crop largely confined to the coastal belt from Tanga to Mtwara, mostly in Eastern and Southern regions. The agro-ecological conditions and the management practices of the crop are similar in all the growing areas and therefore, the pest problems and recommended control options are the same (Table 4.17). Page 39 of 110 The research and development programme at ARI Mikocheni through support by the GTZ, has developed and formulated appropriate farmer friendly IPM approaches for the coconut cropping system. However, extension of the knowledge to farmers has been hampered by a lack of adequate funding. Table 4.20: Major pests and recommended control practices for coconut Pest Recommended management practices Insects Coreid bugs (Pseudotheraptus wayi) Biological control using the African weaver ant (Oecophilla longinoda). To enhance the effectiveness of the weaver ants, farmers are advised to do the following: 1- Apply Hydramethyl to control brown house ants (Pheidole megasephala) when necessary 2- Interplant coconut with recommended suitable host trees of weaver ants 3- Construct artificial aerial bridges to facilitate mobility of weaver ants between trees 4- Plant weaver ant nests in areas where they do not occur naturally African rhinoceros beetle (Orytes monoceros) Cultural removal of breeding sites of the pest Mechanical, using recommended hooks Coconut mites (Aceria guerreronis) This is a new pest and therefore no control measures available Coconut termites (Macrotermes spp.) For species living above ground, the termitarium can be destroyed physically Apply recommended insecticides at the recommended dosage rates Diseases Lethal Disease caused by phytoplasma Plant recommended tolerant/resistant varieties. E.g. East African Tall sub populations Proper destruction of diseased plants Avoid movement of seedlings from infested to non infested areas Location specific replanting Source: Source: MAFS: Plant Pests Field Book: A guide to management, 2003 The only pesticide recommended for use on coconut is hydramethyl for the control of the brown house ants, which interfere with the effectiveness of the weaver ants. Mango Mangoes are grown for the local and export market, mostly as a smallholder crop. Despite its popularity, there has been limited research on its major pest problems and producers develop pest control tactics on a need basis (Table 4.18). Therefore, much need to be done to improve the crop, and also to address the key pest problems as summarised below. Table 4.21: Key pests of mangoes and current farmer practices to reduce losses Pest Farmer practices Insects Fruit flies (Ceratitis spp) Harvest as much fruit as possible; sort out the edible fruit and bury all those that are infested Apply chlorpyrifos when necessary Use toxic bait sprays e.g. yeast products mixed with malathion or fenthion around the tree base Removal of infested fruits and proper disposal (collect and bury Page 40 of 110 Pest Farmer practices at least 10 feet deep) Mango weevils (Sternochetus mangifera) Removal of infested fruits at least twice a week and proper disposal (collect and bury at least 10 feet deep) Selected less sucsceptibe varieties , such as Ngowe, Kitovu or Boribo Maintain field sanitation at the end of the season by clearing all seeds under the tree canopy Mango mealybug Spray contact/systemic insecticides Control of attendant ants to reduce spread of the pest Diseases Mango anthracnose (Colletratrichum gloesporiodes) Apply available registered fungicides Proper pruning to reduce excessive and minimise disease build- up Use the recommended post-harvesting treatment Powdery mildew (Oidium spp) Apply recommended fungicides Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Citrus Like mangoes, citrus fruits are produced for the local and export markets but resources allocated for research and development are insufficient and therefore, the pest management strategies used by farmers to date have been borrowed from elsewhere and fine-tuned for local use on a need basis. Table 19 is a summary of the key pest problems and some of the available management options. The biological control of the woolly whitefly, which is a new pest of citrus in Africa south of Sahara, is a recent good example. The programme, a collaborative initiative between PHS and GTZ-IPM, was embarked on after promising results were reported in Uganda and Kenya where successful initial releases were done. The biological control of the citrus black flies is a spill-over from releases done on the Kenya coast in the 1970s. The efficacy of this bio-control agent has to be facilitated by controlling the attendant ants, which facilitate the spread of the pest and also interfere with the efficacy of the wasps (Dr. Z. Seguni, personal communication). Farmers in the coconut and cashew cropping systems can benefit from the technology already developed for the management of attendant ants on respective crops. Overall, local information on sustainable management of citrus, particularly pest problems, are lacking (Table 4.22). Adequate resources must be allocated to enhance development and promotion of the crop. Table 4.22: Major pest problems of citrus and recommended management practices Pest Recommended management practices Insects Scale insects Normally ants protect aphids against natural enemies Mealybugs (Planococus citri-Risso) Trees with dead brown leaves should be uprooted and replaced Aphids (Toxptera citricidus) Normally ants protect aphids against natural enemies Page 41 of 110 Pest Recommended management practices False codling moth (Cryptophlebia leucotrata) Field sanitation (collect all fallen fruits and bury them at least 50 cm deep) Remove wild castor (“Mbarika”) around the orchard Orange dog (Pappilio demodercus) Regular scouting and hand picking of caterpillars Apply contact insecticides in case of a severe attack The wooly white fly (Aleurothrixus flocossus) Biological control using imported parasitic wasps Management of attendant ants to reduce spread and facilitate the efficacy of natural bio-control agents Black flies (Aleurocanthus sp) Management of attendant ants to reduce spread and facilitate the efficacy of natural bio-control agents Giant coreid bug (Anoplenemis curvipes) New pest but farmers are encouraged to introduce and enhance the activity of weaver ants (refer to cashew & coconut approach) Citrus leafminer Crop sanitation and mulching Apply recommended systemic insecticides when necessary Diseases Greening disease (Liberobacter africana) Propogation of disease free planting materials Eliminate all infested trees Strict quarantine measures Natural enemies Hymenopterous chalcids such as Tetrastichus spp and Diaphorencytrus aligarhenses Use clean planting material Good plant nutrition Gummosis (Phytophthora spp) Budded at least 20cm from ground should be chosen Cut infected trees Affected orchards should not be excessively irrigated Tristeza (Virus localized in phlorm tissue) Use disease free budwood Green moulds (Pencillium italicum) Handle fruit carefully to reduce skin injury Treat bruches, graders, etc Use the recommended post harvesting treatment Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Pineapple Pineapples are largely grown for the domestic market and have few known major pest problems in Tanzania. These include the pineapple mealybugs (Dysmicoccus brevipes & D. neobrevipes and pineapple wilt disease, which are transmitted by Dysmicoccus brevipes. The recommended pest management tactics therefore target the control of Dysmicoccus brevipes, the vector. The only viable approach is through effective management of attendant ants to reduce spread and build up of mealybugs in the crop. Table 4.23: Major pest problems of pineapples and recommended management practices Pest Recommended management practices Mealybugs (Pseodococcus brevipes) Use clean planting materials Trees with dead brown leaves should be uprooted and replaced Diseases Top and root rot (Phytophthora spp) Use well-drained soils from pineapple growing Plant on raised beds at least 23 cm high after settling Provide drainage system to get rid of excess water without causing soil erosion Deep-trip down the slope before hilling if subsurface soil compaction is evident Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Tomato Page 42 of 110 Tomato is most important horticultural crop, grown by almost all small farmers in northern and southern Tanzania. There are two types of tomatoes grown in Tanzania. These are the tall or intermediate varieties e.g. Money maker and Maglobe, and the dwarf varieties e.g. Roma Vf and Tanya. Both types are grown across the country although consumer preference also influences local production. Tomatoes are grown for cash and domestic use mostly by women and youths in Kilimanjaro, Arusha, Tanga, Iringa, Dodoma, Mbeya, Morogoro and Mwanza regions. It is also important for local processing, with processing plants in Iringa and Arusha. Some of the products from these plants are sold on the local market while the bulk is exported. In some areas, e.g. in the northern zone, more resources are invested in tomato production than in coffee production because tomatoes gives better and fast returns (personal observation). Farmers use fungicide or insecticide available at the rural markets and often do not respect proper timing and dosage instructions. Moreover, they do not wear protective gear when applying the chemicals and do not use the proper equipment (e.g. application by using naps in stead of sprayers). Tomato production is seriously hampered by diseases, i.e. late blight, yellow leaf curl virus, powdery mildew and various wilts. The yellow leaf curl virus is transmitted by white flies, while late blight is caused by the Phytophthora infestans air borne fungus. Powdery mildew is a result of infestation by the obligate parasite Oidium lycopersici. Yellow leaf curl virus results in stunted plants with chlorotic leaves. Late blight causes leaf lesions and rotting of affected fruits. Powdery mildew causes discoloration of foliage that eventually dies. Year round cultivation of tomatoes without proper rotation is one of the major causes of the spread of these diseases. Later blight and bacterial spot develop under moist conditions, while dry weather conditions are favourable to yellow leaf curl virus and powdery mildew. Cultural practices, such as rotation and field hygiene, can be applied to reduce the effect of the diseases. Botanicals, such as Tephrosia, Neem and Mexican marigold, should be tested on their effect on white flies. New, tolerant tomato varieties may contribute to the IPM control of the diseases. Farmer Field Schools would be effective tools to improve farmers’ knowledge about the diseases and their IPM control. A specific category of diseases affecting tomato nurseries are damping of pathogens, such as Pythium, Fusarium, Rhizoctonia, Phytophthora and Alternaria. These pathogens cause damping off, wilting and rotting of the nursery plants. The spread of the rot fungi is enhanced by excessive moisture, continuous cultivation of tomatoes and the presence of volunteer plants. Seedbed hygiene (sterilization by fire or polythene sheets, removal of crop debris, rotation) is the best IPM control measure that should be promoted amongst tomato growers. Various species of root-knot nematodes and red spider mites are among the major pests affecting tomato yield. Red spider mites are sucking insects that appear under dry weather conditions. Root-knot nematodes damage plants by devitalizing root tips and either stopping their growth or causing excessive root production and root are swelling. Major causes to both pests are lack of rotation or fallow and year round cultivation of tomatoes. Root-knot nematodes can be controlled by cultural practices, such as field sanitation, deep ploughing, and the use of clean planting materials and tolerant or resistant varieties. Red spider mites may also be controlled by botanicals, such as Mexican marigold, Tephrosia and Neem. However, the effect of these botanicals has to be confirmed. Farmers must be informed of the currently recommended control measures, including safe handling of chemicals. Page 43 of 110 Table 4.24: Major pests of tomatoes and recommended management practices for northern zone Pest Recommended management practices Insects American bollworm (Helicoverpa armigera) Destroy infected crop residues and fruit after harvesting Encourage natural enemies (parasites, ants, Anghocorid-bugs and egg predators) Use maize ads a trap crop (timing of crop stage; tasseling stage coincides with attack) Inspect the crop regularly for new infestations Use botanicals like Neem extract Apply recommended insecticides at recommended dosage rate Cutworms (Agrotis spp) Early ploughing to expose cutworms to predators Apply wood ash around plants Inspect the crop regularly soon after transplanting because this is the most susceptible stage of the crop Mechanical (hand collect and crush them) Use appropriate trapping methods. Crush the caterpillars or feed them to chicken Use repellent botanicals Spray with recommended insecticide if necessary (Table 21) Nematodes Root knot nematodes (Meloidogyne) Kiswahili: Mnyauko nyanya Optima rotation and fallow Deep ploughing Avoid contaminated water Plant tolerant/resistant varieties Sterilise the seedbed before sowing Avoid planting a new crop on infested areas Mites Red spider mites (Tetranychus spp) Kiswahili name: Utitiri wekundu Rogue infected plants Avoid dusty conditions during extreme dry season Encourage moist microclimate by frequent irrigation Hedge planting to reduce dust, invasion by mites blown by wind Encourage natural enemies by mulching and hedging Use neem as alternative sprays Observe recommended time of planting Application of irrigation Plant tolerant/resistant varieties e.g. ARP 367-2 or Rossol Sanitation and crop hygiene Use healthy planting material Frequent weeding Inspect the crop regularly for new infestations Use neem oil with cow urine (mfori) Apply a recommended miticide if necessary (Table 21) Page 44 of 110 Pest Recommended management practices Diseases Late blight (Phytophthora infestants) Kiswahili name: Baka jani chelewa Regular crop scouting to detect early attack Field sanitation after harvest by removal of infected plant parts Crop rotation Avoid moist microclimate at shady places Use wide spacing (wet season) Observe recommended time of planting Plant at correct spacing Shade management Decrease humidity through pruning, desuckering, staking and weeding Avoiding the humid season and mulch to avoid rain splash causing infections Early blight (Alternaria solani) Remove infected plants staring from nursery Weed out Solanacea plants Try botanicals and other natural pesticides Observe recommended time of planting Regular crop scouting to detect early attack Apply recommended fungicide if necessary Powdery mildew (Oidium lycopersicum) Sanitation , remove infested leaves and plants Practice crop rotation Use botanical and other natural pesticides Regular crop scouting to detect early attack Apply recommended fungicide if necessary (Table 21) Bacterial wilt (Pseudomonas solanacearum) Practice good crop rotation Practice deep ploughing/post harvesting cultivation to expose soil to sun Add organic matter to the soil (cow dung, mulch, green manure) Rogue affected crops and weed-hosts, destroy or bury outside the field Avoid transferring infested soil including soil on roots of plants Do not irrigate with contaminated water from infested areas Choose seedbed in clean uninfected area Page 45 of 110 Pest Recommended management practices Fusarium wilt (Fusarium oxysporum) Kiswahili: Mnyauko nyanya Use resistant varieties (like Tengeru 97) are the best practical measure to manage the disease in the field. Tengeru 97 is resistant to both fusarim wilt races 1 and 2 Practice good crop rotation Sanitation and crop hygiene Deep ploughing Avoid transferring infested soil including soil on roots of plants Do not irrigate with contaminated water from infested areas Add organic matter to the soil (cow dung, mulch, green manure) Bactoria spot (Xanthomonas compestris pv. Vesicatoria) Kiswahili name: Madoa bakteria Use clean seed Three year crop rotation Avoid working in fields under wet conditions Avoiding of injuries to fruits Tomato yellow leaf curl (TYLC)-virus transmitted by whitefly (Bemisia tabaci) Kiswahili names: Rasta, Ngumi, Bondia Use disease free planting materials Time of planting Scouting of the disease and removal of affected plants Intercrop with onion. This also reduces aphids in tomatoes Intercrop with eggplants as traps to draw whiteflies away from less tolant and virus prone crops like tomatoes Use repellent botanicals, such as Tephrosia and Mexican marigold Regular crop scouting to detect early attack Good management of irrigation water Remove and destroy crop residues immediately after the final harvest Avoid planting Lantana camara near tomatoes Encourage beneficial insects, such as Encasis Spray if necessary but use recommended insecticides (Table 21) Source: MAFS: Plant Pests Field Book: A guide to management, 2003, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Table 4.25: List of pesticides recommended for use on tomatoes Chemical Chemical common name Formulation Application rate Target pest Comments Insecticides Pirimiphos methyl 50%EC fruit worms Profenofos 72%EC Whitefly Miticide Azocyclotin 25%WP Red spider mites Registered for use on greenhouse roses for spider mite control Page 46 of 110 Chemical Chemical common name Formulation Application rate Target pest Comments Fungicides Metalaxyl + mancozeb 7.5% + 56%WP 3.0 to 3.5 kg/ha Early & late blight Mancozeb 80% WP 1.5 to 2.5 kg/ha Chlorothalonil 50%FW 2.0 to 5.0 l/ha Copper hydroxide 50%WP 4.0 to 5.0 kg/ha Source: Paul, Mwaiko & Mwangi, 2000 All pesticides on tomatoes are applied using a knapsack sprayer. The list of pesticides (Table 3.21) can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt. Onion Onion cultivation takes place throughout the Northern Zone and the Central Zone, but most production is located in the cooler, higher altitude areas, such as the mountains of Mbulu, Lushoto, Pare and Usambara and the foot slopes of Mount Meru and Mount Kilimanjaro. Most onions are cultivated under irrigation during the dry season. The crop is often grown year after year on the same field without sufficient rotation, a practice that encourages the build-up of pest and disease epidemics. Downy mildew and storage rots are among the most important diseases affecting onions. Downy mildew can be controlled by field sanitation, wide spacing and weed control, rotation and use of tolerant varieties. Storage rots, such as Botrytis, Erwinia, Mucor and Fusarium can be controlled by ventilation and storage of onions on racks, use of polypropylene or netted bamboo baskets, drying of onions before storage and removal of tops. These control measures are applicable by all categories of farmers and can be disseminated through leaflets and brochures. Onion thrips are the most common insect pest affecting onion production. Development of thrips populations is encouraged by insufficient rotation and presence of crop debris. Cultural control measures include deep ploughing, field sanitation, crop rotation, timely planting, mulching and irrigation. Botanicals, such as Neem oil, and other control agents should be identified and tested on their effect on thrips. Information on major pest problems in the central agro-ecological zone is scanty, and therefore Table 4.25 gives a summary of the major pests and respective management options for some parts of the northern zone only. However, these pest management options (Table 4.25) can also be refined and adopted by farmers in other areas. Table 4.26 : Major pest problems and recommended management practices Pest Recommended management practices Insects Onion thrips (Thrips tabaci) Kiswahili name: Vithripi Sanitation Scouting Separate seed bed and field to reduce danger of carrying over thrips from one site to the other Crop rotation Mixed cropping of carrots and onions Observe recommended time of planting Field sanitation and crop hygiene Transplant clean seedlings Mulching reduces thrips infestation considerably Plough deep after the harvest to bury the pupae Irrigation/adequate watering Enhance beneficials (predatory mits, bugs, fungal pathogens like Page 47 of 110 Pest Recommended management practices Metarhizium) Inspect the crop regularly Use botanical extract like Neem oil, Tephrosia, tobacco, etc. Diseases Downy mildew (Peronospora destructor) Kiswahili name: Ubwiri unyoya Use resistant varieties (red creole) and crop rotation for at least five years Sanitation: remove crop remains after harvest, do no leave volunteer plants in the field and avoid over fertilization Wide spacing and good drainage to decrease humidity in the plant stand Apply mulch to avoid rain splash Inspect the crop regularly Purple blotch (Alternaria porri) Sanitation: remove crop remains after harvest, do not leave volunteer plants in the field Crop rotation Mulching to avoid rain splash Plant at recommended spacing Inspect the crop regularly Apply recommended fungicide at correct dosage Storage rots (Bortytis, Erwinia, Mucor, Fusarium) Kiswahili name: Uozo ghalani Use of netted bamboo baskets Avoid heaps exceeding 30 cm depth and use racks of 1m high Ventilated stores Minimize damage during handling Drying of onions before storage Remove tops Avoid thick neck/split Source: MAFS: Plant Pests Field Book: A guide to management, 2002, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Brassicas (cabbages and kale) Cabbages and kale are grown in the cool highlands. It is a valuable relish for urban dwellers where it is used as vegetable salad and as stew to accompany the starchy foods (rice, ugali, cassava etc.). To date, the crop has few major pest problems whenever it is grown in the country (Table 3.23). The crop is mainly grown for income generation. Like tomatoes, farmers apply available chemicals mainly to control insect pests. The most common disease affecting cabbage is black rot. The disease can reduce yield by 90% during the rainy season. Black rot is caused by the Xanthomonas campestris bacteria which are spread by infested seed and through crop debris. Wet warm weather conditions encourage the development of bacteria populations. Cultural control measures, such as deep ploughing, crop rotation and field sanitation considerably reduce the damage by blank rot. Other potential IPM control techniques include seed dressing with Bacillus bacteria, seed treatment with hot water or antibiotics, and resistant varieties. Diamond back moth and cabbage head worm (in lowland areas) are the most devastating insect pests affecting cabbages. The pests may yield by 60% if no control measures are taken. Dry and hot weather conditions and the presence of host plants encourage the insect populations to develop. Farmers apply insecticides or cow dung and urine to control the pests. Application of Neem oil has proven to be effective, while the effect of natural enemies and other botanicals, such as Diadegma, Tephrosia and Annona seeds Page 48 of 110 should be verified. An alternative control agent is Bt-Bacillus thuringiensis. Farmer Field Schools would be helpful instruments in training farmers in pest identification and evaluation of control measures. Few pesticides are recommended for use in the production of cabbages, mainly for insect pest control. However, since cabbage and kale are grown in coffee cropping systems, farmers tend to use pesticides recommended for use on coffee to control brassica pests. Table 4.27: Major pests of brassicas and recommended practices Pest Recommended management practices Insects Diamondback moth (Plutella xylostella) Kiswahili names: Nondo mgono and Almasi Scouting Use botanical and other control agents Observe recommended time of planting Transplant healthy seedlings Inspect the crop regularly to detect early attacks Encourage natural enemies (predatory hoverfly larvae, coccinellids, parasitic wasps) by enhancing diversity Use botanicals (Neem oil, chillies, etc.) Aphids (Brevicoryne brassicae) Sawflies Cabbage webworms Diseases Blackrot (Xanthomonas compestris) Kiswahili name: Uozo mweusi Seed dressing with Bacillus bacteria Seed treatment with hot water Mulching Deep ploughing 3-year crop rotation Field and crop hygiene Transplant only healthy seedlings Plant certified seeds Plant tolerant/resistant varieties like Glory, Amigo FI Sterilise the seed bed before sowing Good drainage, and mulch to avoid infections from rain splash Downy mildew (Peronospora destructor) Kiswahili name: Ubwiri unyoya Practice good crop rotation Observe recommended time of planting Transplant only healthy seedlings Plant at recommended spacing Alternaria leaf spot (Alternatira spp) Avoid overhead irrigation Practice good crop rotation Observe recommended time of planting Transplant only healthy seedlings Plant at recommended spacing Cabbage club rot (Plasmodiaphora brassicae) Crop rotation Plant in well drained soils Adjust soil pH to alkaline by adding hydrated lime Page 49 of 110 Pest Recommended management practices Black rot (Xanthomonos compestris pv. Compestris) Crop rotation Use of pathogen free seeds Avoid overhead irrigation Use of resistance cultivars (Glory FA, Amigo F1) Sanitation: remove crop residues – plough under, compost or feed to animals Good drainage, and mulch to avoid infections from rain splash Cauliflower mosaic virus (CaMV) Remove brassica weeds Rogue young plants showing disease symptoms and immediately burns them Dumpting off (Fusarium Spp, Rhizoctonia spp. Pytium spp and Phytophotra spp) Provide good soil structure and drainage Avoid overwatering Apply wood ash in seedbed Sterilise seedbed Use treated beds Pricking excessive seedlings (thinning) Bacterial soft rot (Erwinia carotovora var. carotovora, Pseudomonas spp) Avoid harvesting when the whether is wet Handle produce carefully and store in cool, well-ventilated areas Plough in crops immediately after harvesting Practice crop rotation and provide good drainage Timely planting to coincide with dry season Source: MAFS: Plant Pests Field Book: A guide to management, 2002, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Deltamethrin 25%EC, diazinon 60% EC and profenopos 72%EC are recommended for use on cabbage and kales but the pesticides are also recommended for use on coffee. Page 50 of 110 4.4 MIGRATORY AND OUTBREAK PESTS The key migratory and outbreak pests of economic significance in Tanzania are armyworm (Spodoptera exempta), birds, notably the Quelea (Quelea quelea spp), the red locust, rodents (particularly the field rats) and the elegant grasshopper (Zenocerus elagans). With an exception of the elegant grasshopper, the management of the rest of the pests under this heading is co-ordinated by the Plant Health Service of the Ministry of Agriculture and Food Security. Rodents Rodents, particularly the multi-mammate shamba rat, (Mastomys natalensis), are major pests of food crops. The most affected crops are maize, millets, paddy and cassava. Virtually all regions are affected with more frequent outbreaks in Lindi, Mtwara, Coast, Tanga, Rukwa (Lake Rukwa valley) and in the cotton areas of Shinyanga regions. Maize is the most susceptible of all the crops. At the pre-harvest stage, maize is attacked at planting (the rodents retrieve sown seeds from the soil causing spatial germination). In some cases, as much as 100% of the seeds are destroyed, this forcing farmers to replant (Anon, 1999). Losses of cereals are usually quite high and are in average about 15%. This loss of cereals could provide enough food for 2.3 of population for a whole year. Annual control costs for rodents are approximately 217 million Tanzanians Shillings (MAFS 2004). Farmers in outbreak areas are strongly advised to do the following (Mwanjabe & Leirs, 1997; Bell, undated) to reduce potential damage to crops and the environment: 1. Regular surveillance. The earlier the presence of rodents is observed, the cheaper and simpler any subsequent action will be and losses will remain negligible 2. Sanitation. It is much easier to notice the presence of rodents if the store is clean and tidy 3. Proofing i.e. making the store rat-proof in order to discourage rodents from entering 4. Trapping. Place the traps in strategic positions 5. Use recommended rodenticide. However, bait poisons should be used only if rats are present. In stores or buildings, use single-dose anticoagulant poisons, preferably as ready-made baits. 6. Encourage team approach for effectiveness. The larger the area managed or controlled with poison, the more effective the impact 7. Predation. Keep cats in stores and homesteads. In the cotton growing areas of Shinyanga, rats are a serious problem in cotton at planting and harvesting. At planting, the rodents pick out the seeds after planting, this leading to uneven germination and poor establishment. At harvesting, the rats feed on the seeds, leaving the farmer with lint only. Through feeding the rats not only reduce the value of the crop but also affect its quality by contamination by faeces and urine. To reduce rat damage on cotton during harvesting, farmers are advised to pick the crop frequently and to sale it immediately after picking. Birds (Quelea quelea spp) Birds are serious migratory pests of cereal crops, namely wheat, rice, sorghum and millet across the country. The quelea birds, which in Tanzania occur are swarms ranging from thousands to a few millions, have been responsible for famines of varying proportions in some areas. In 2001, total loss (100%) in 700 ha of wheat was experienced in Basuto wheat farms, Hanang District (MAFS 2001). Similarly, about 25% loss of rice was experienced on 1125 has in the Lower Moshi Irrigation Rice Project in 1997/8 due to quelea birds (MAFS 1998). Table 3.25 shows quelea invaded regions in 2003. Page 51 of 110 Table 4.29: Quelea Quelea invaded regions year 2003 Year Invaded regions Sprayed Coverage (Ha) Queleatox (l) Number of birds killed January 2003 to December 2003 Arusha Kilimanjaro Dodoma, Mbeya, Singida, Shinyanga, Manyara 2,123.50 7,654 191.8 million Source: MAFS (2004): Basic data agriculture sector 1995/96-2002/2003 Table 4.30: Quelea quelea outbreaks and cereal damage in some regions of Tanzania, 1998-2002 Region Number of hectares destroyed per year 1998 1999 2000 2001 2002 Manyara 320.5 167 0 0 288 Dodoma 145 600 430 186 230 Mbeya 170 522 573 342 190 Mwanza 24 370 110 80 0 Shinyanga 56 0 350 48 357 Singida 150 0 41 194 123 Kilimanjaro 0 102 0 0 0 Mara 0 500 125 0 73 Morogoro 0 254.5 36 202.5 191 Tabora 0 215 663 0 127 Total hectares 865.5 2730.5 2328 1052.5 1579 Source: Ministry of Agriculture and Food Security Report, 1998-2002 Bird pest problems in agriculture have proved difficult to resolve due in large part to the behavioural versatility associated with flocking. The array of food choices available to birds is also complex, hence forth; necessary information is needed for successful control strategies. The total damaged per bird per day, if the bird is exclusively feeding on cereal crops, has been estimated at 8 g (Winkfield, 1989) and 10 g (Elloitt, 1989). The control of migrant pests such as Quelea is a major concern to most farmers and the Ministry of Agriculture and Food Security. Several techniques have been tried to reduce bird populations to levels where crop damage is minimal. Traditional methods, slings, bird scares, and scarecrows, are still being used in many parts. Modern techniques of frightening devices, chemical repellents, less preferred crop varities and alternative cultural practices have been evaluated. All the methods have minimal value in situations where bird pressure is high and where habitation is likely to develop through repetitive repellent use and other methods, which may alleviate damage in small plots or in large fields for a short time. The aerial spraying of chemical (fenthion) on nesting and roosting sites, the most widely used technique to date. Currently, only fenthion 60%ULV aerial formulation is being used. Fenthion is registered under restricted use category such that the pesticide is recommended to be used at the rate of 2.0l/ha. The concerns over possible human health problems and environmental damage resulting from the large- scale application of chemical pesticide for quelea control have let to a proposal for alternative non-lethal control strategy. Chemical pesticide applied for quelea control represent a risk for human, terrestrial, non- target fauna and aquatic ecosystems. The chemical pose risk by directly poisoning or by food contamination/depletion. Among the terrestrial non-target invertebrates, there are beneficial species. Some are responsible for organic matter cycling; others are predators, and parasitoids of crop pests. Some assure pollination of crops and wild plants, while others again produce honey and silk. The fact that non-target Page 52 of 110 birds and, occasionally, other vertebrates may be killed by quelea control operations is well-established (Keita, et.al. 1994; van der Walt et.al. 1998; Verdoorn, 1998) The risk of human health problems and environmental damage can be mitigated considerably by development of integrated environmentally sound control strategies including Net-Catching. These methods will educate farmers become custodians of the environment. A new emphasis is the possibility of harvesting quelea for food. Since quelea is a good source of protein and preferred by many people. This method offers more rapid prospects for implementation which enable farmers to continue making their own decisions important for the control of quelea in their area. While present indications are that harvesting is probably not an option as a crop protection technique, it offers the possibility of providing income to rural populations in compensation for crop losses. (T. N. Mtobesya, pers.comm). A sustainable and environmentally sound control strategy for quelea in Tanzania undated research document by B.Mtobesya). In respect of quelea birds, FAO is currently encouraging the use of IPM approaches to the problem of bird attacks on cereal crops. This means working with farmers in examing all aspects of farming practice in relation to quelea damage, and seeking to minimise external inputs, especially pesticides. In includes modifying crop husbandry, planting time, week reduction, crop substitution, bird scaring, exclusion neeting, etc. and only using lethal control for birds directly threatening crops when the other methods have failed. It is also important for farmers to be aware of the costs of control using pesticides, and in the case of commericial farmers, for them to bear some or all of the costs. A major likely benefit of IPM is reduced environmental side-effects resulting from decreased pesticide use. Although some elements of IPM have been tried in bird pest management, a major effort has yet to be made, for quelea, to focus on farmers in all aspects of the problem (Elloit, 2000). Locust Locusts live and breed in numerous grassland plains, the best ecologically favourable ones are known as outbreak areas. During periods with favourable weather, locust multiply rapidly and form large swarms which escape and may result into a plagau. There are eight known red locusts outbreak in East and Central Africa, four of these are found in Tanzania. The include the Rukewa Valley and Iku/Katavi plains in the Southern West, the Malagarasi River basin in the West and Wembere Plains in the Centre. They cover a total of 8000 km2. The strategy for red locust control combines regular monitoring of breeding sites followed by aerial application of fenitrothion 96.8% ULV to eliminate potential threatening hopper populations. Table 4.30 shows invaded area and treatment used for red locust. Table 4.31: Invaded area and treatment used Year Type Investigated areas Invaded area Treatment Area coverage (Ha) Type of chemical used Remarks January 2003 to December 2003 Red locust Wembere Plains (Tabora) Malagarasi Basin (Kigoma) Iku/Katasi Plains (Rukwa) 1. Iku/Kutanvi Plains (Rukwa) 2. Wembere Plains (Tabora) 2,600 600 4500 Metarhizium anisopline Fenitrothion technical Fenitrothion technical Observation, shows Metarhizium anisophiae as a more effective chemical in controllong the spread of Red Locusts Source: MAFS (2004): Basic data agriculture sector 1995/96-2002/2003 Recently, the red locust regional programme has started to investigate the viability Metarhizium anisopliae, a biopesticide, for locust control. This is a collaborative initiative funded by DFID between NRI-UK, Tanzania and Zambia Governments. If viable, the agent can also be used as an option in the management of the elegant grasshopper and the edible grasshopper (locally known as nsenene). Page 53 of 110 The edible grasshopper (Ruspolia nitidula, Scopoli) has become increasingly damaging on cereal crops (maize, wheat sorghum, rice and millets) in parts of the country, notably northern, eastern and lake zones in recent years (PHS, pers.comm.). There being no research done on the management of the pest, farmers have been forced to use any recommended insecticide as in the interim. Armyworm The African armyworm (Spodoptera exempta) is a major threat to basic food production in a number of east and southern African countries Armyworm is a major pest of cereal crops (maize, rice, sorghum and millets) as well as pasture (grass family) and therefore a threat to food security and livestock. Overall losses of 30% for crops have been estimated though in major outbreak years losses in maize of up to 92% are recorded. Armyworm outbreaks vary from year to year but serious outbreaks occur frequentely as depicted in Table 4.31. Table 4.32: Armywork outbreaks in Tanzania Seasonal Year Area Invesed (Hactres) 1989/90 28,768 1990/91 15,214 1991/92 517,233 1992/3 34,844 1993/94 45,504 1994/95 4,798 1995/96 3,187 1996/97 577 1997/8 35,174 1998/9 311,560 1999/2000 50 2001/2002 157,942 Table 4.33: Damage of various croups by armyworms during the 2001/2002 cropping seasons in some region of Tanzania Region District Crops damaged Hectares infested Arusha Hanang Maize, sorghum, millet, pasture 25,910 Kiteto Maize, millet, pasture 15,570 Karatu Maize, sorghum, millet 2,500 Monduli Maize 100 Babati Maize 3,090 Arumeru Maize, pasture 2,500 Simanjiro Maize, pasture 2,230 Dodoma Dodoma Rural Maize, sorghum, millet, pasture 21,300 Page 54 of 110 Region District Crops damaged Hectares infested Dodoma Urban Maize, sorghum, millet 6,613 Mpwapwa Maize, sorghum, millet, pasture 5,906 Kondoa Maize, sorghum, millet, pasture 17,268 Kongwa Maize, sorghum, millet, pasture 21,328 Kilimanjaro Hai Maize, paddy, pasture 3,500 Rombo Maize 110 Mwanga Maize, pasture 281 Same Maize, paddy, pasture 251 Moshi Maize, paddy, pasture 15,000 Tanga Korogwe Maize, paddy, pasture 1,050 Handeni Maize, pasture 6,445 Morogoro Morogoro Rural Maize, paddy, sugarcane 5,483 Iringa Kilosa Maize, paddy 617 Kilombero Maize, paddy, sugarcane 747 Iringa Rural Maize 9 Ludewa Maize 113 Mbeya Mbozi Maize 22 Total hectares infested 157,943 Source: Ministry of Agriculture and Food Security Report, 2001-2002 Due to its economic significance, management and control is centrally co-ordinated by PHS. Its control combines monitoring in identified breeding areas, forecasting and early warning of potential outbreaks. The national armyworm control programme based at Tengeru-Arusha, runs a network of 100 traps distributed throughout the country (Anon, 1999). The traps are placed at district offices, research stations and in large- scale farms. Weekly returns from these traps are used in forecasting potential outbreaks for the following week (Anon, 1999). The information about potential outbreaks is passed to the regions and districts from where it is further passed to farming communities through the extension system. Farmers are advised to inspect their fields for signs of infestation. If the crop is attacked, farmers should spray with diazinon, fenitrothion or chlorpyrifos, whichever is available at the nearest pesticide store. Both ULV and knapsack sprayers can be used depending on available formulation in the outbreak areas. This service could be improved through a better monitoring and reporting system that empowers farmers to be partners in a co-ordinated network. This will require the following activities: Development of community based monitoring and early warning approaches Formulating and implementing appropriate training for district plant protection officers (DPPOs), village extension officers (VEOs) and farmers to impart simple reliable monitoring skills Formulating and implementing a reliable community based early warning network This approach is likely to have a number of benefits. One, less pesticides will be used because farmers will be able to identify and apply control measures on the most vulnerable stage of the pest, which is not possible in the current set-up. Secondly, farmers can use less toxic and environmentally friendly proven alternatives to pesticides e.g. botanical extracts and/or biopesticides at relatively low cost with minimum environmental hazards. Thirdly, if well co-ordinated, the information generated by farming communities can be integrated in the nation monitoring and early warning system to improve the quality of the information at national and international level. A new natural control for armyworm is being developed by using a natural disease of the armyworm as biological control in place of toxic chemeak insecticides (W. Mushobozi, pers.comm.). This disease of armyworm is caused by specific agent, the Spodoptera exempta nucleopolyhedrovirus (or NPV). It has been observed since the early 1960s the late in the season many armmworm outbreaks collapse due to the occurrence of a disease that killed up to 98% of caterpillars. NPV can be sprayed like chemicals onto pest outbreaks causing epidemics of NPV desease that kill off the pests, effectively acting as a natural insecticide. What is more, the killed insects produce more NPV Page 55 of 110 spreading the disease further. The NPV produced by dying insects can infect later generations of armyworms so that the effect is longer lasting than chemical insecticdes (Mushobozi, et.al. undated). 5. POLICY, REGULATORY AND INSTITUTIONAL FRAMEWORK 5.1 INTRODUCTION Tanzania’s legislation on plant protection and pesticides dates back to 1997. Accordingly, though the review of previous legislation was primarily based on IPM applications, these laws have not taken into account the New Revised Text of the 1997 International Plant Protection Convention (IPPC), which is cited by the World Trade Organization (WTO) Sanitary and Phytosanitary Agreement (SPS Agreement) as the authoritative standard setting body for plant protection. One of the purposes of the legal component is to ensure the compliance of Tanzanian legislation with these standards. As a member of the WTO, Tanzania is required to comply with the international standards within the WTO framework. Phytosanitary measures include all relevant laws, decrees, regulations, requirements and procedures taken by a state in order to protect plant health and prevent the spread of diseases and pests. However, in order to prevent such measures becoming disguised restrictions on trade, the WTO SPS Agreement requires harmonizing such measures at international level. Conversely, such standards can be argued to be an important way of ensuring market access for Tanzania’s international exports. Also Maximum Residue Levels (MRL) set by large target export markets such as the EU, US and Japan require that agricultural products do not have pesticides residues that exceed established quantities. Pesticides control is also a considerable concern nationally, with unacceptable MRLs on some agricultural crops for the domestic market. Greater regulation through strengthened legislation will contribute to the judicious application and safe use of pesticides. 5.2 POLICIES AND STRATEGIES National Environmental Management Policy (1997) The National Environmental Management Policy (NEM) is set to achieve the following in terms of environmental management: “Integrated multisectoral approaches necessary in addressing the totality of the environment; Fostering government-wide commitment to the integration of environmental concerns in the sectoral policies, strategies and investment decisions; Creating the context for planning and coordination at a multisectoral level, to ensure a more systematic approach, focus and consistency, for the ever-increasing variety of players and intensity of environmental activities”. The policy has identified six key major environmental issues in the country. These are land degradation, water pollution, air pollution, loss of wildlife habitats, deterioration of aquatic systems and deforestation. Hence the policy has the following objectives with respect to environmental management in agriculture: ensure sustainability, security and equitable and sustainable use of natural resources; prevent and control degradation of land, water, vegetation, and air; conserve biological diversity of the unique ecosystems the country; raise public awareness and understanding of the essential linkages between environment and development, and to promote individual and community participation in environmental action. National Agricultural and Livestock Policy (1997) The ultimate goal of having this Policy is to improve the well being of the population whose principal occupation is based on agriculture. The focus of the policy is to commercialise agriculture so as to increase the livelihood of the smallholder farmers/livestock keepers. The policy’s main objectives include: ensure basic food security for the nation and to improve national standards of nutrition, by increasing output, quality and availability of food commodities; improve standards of living in the rural areas through increased income generation from agricultural and livestock production; increase foreign exchange earnings for the nation by encouraging production and increased exportation of agricultural and livestock products; Page 56 of 110 promote integrated and sustainable use and management of natural resources such as land, soil, water and vegetation in order to conserve the environment; provide support services to the agricultural sector, which cannot be provided efficiently by the private sector. Plant Protection Act No. 13 (1997) This Act has made provisions for consolidation of plant protection to prevent introduction and spread of harmful organisms, to ensure sustainable plant and environmental protection, to control the importation and use of plant protection substances, to regulate export and imports of plant and plant products and ensure fulfilment of international commitments, and to entrust all plant protection regulatory functions to the government and for matters incidental thereto or connected therewith. The activities of Tanzania Pesticides Research Institute (TPRI) are incorporated into the Act. In relation to IPM, importation of biological control agents is not allowed unless under the prescribed permit by the Ministry. Environmental Management Act of 2004 This Act requires establishment of sector environmental management Units at each Ministry, with the responsibility of ensuring compliance on environmental matters. The sector environmental Units have, among others, the responsibilities of Advising and implementing policies of the government on the protection and management of environment Coordinating activities related to the environment of all persons within the Ministry Ensure that environmental concerns are integrated into the Ministry development planning and project implementation in a way which protects the environment To prepare and coordinate the implementation of environmental action plans at the national and local levels as required under this Act To refer to the council any matter related to the enforcement of the purposes of this Act To ensure that sectoral environmental standards are environmentally sound In relation to the Management of dangerous materials and processes, of which agricultural chemicals may fall, the Minister shall have the power to make regulations pertaining to persistent organic pollutants (POP) and pesticides issues, to ensure that they are in compliance with the Stockholm Convention on POP of 2001 and Rotterdam Convention on the Prior Informed Consent Procedure for Certain Hazardous Chemicals and Pesticides in International Trade of 1998. The Minister shall also have the powers to make regulations regarding the prevention and control of pollution. However, this mainly relates to the discharge of hazardous substances such as chemicals or mixtures containing oil in water or any other segment of the environment, except in accordance with guidelines prescribed under this Act or any other written law. It is an offence punishable by law to discharge such chemicals, and in this regard there is payment on the costs of removal, and those incurred during the restoration of environment. The Institution/organisation is expected to give immediate notice of the discharge to the Council or relevant sector Ministry, and commence clean up operations using the best available clean-up methods, and comply with such directions as the Council may prescribe. In this context, services that relate to the regulation of agricultural chemicals in the Ministry of Agriculture and Food Security shall be at the forefront to ensure the judicial use of agropesticides. In relation to Plant Health Services the Ministry has taken measures to improve and strengthen Plant health services in order to minimise crop losses resulting from pests and diseases. Hence the Ministry strongly advocates using IPM approaches to be disseminated to farmers through the agricultural extension services. On the aspects of migratory pests and diseases, the Ministry cooperates fully with the neighbouring countries (through regional initiatives on outbreak pest control) in the collective effort to control the damage of such pests. The Ministry also has in place supervisory and regulatory instruments to register, license, monitor and supervise manufacturers, importers, distributors and users of agricultural inputs such as pesticides, fertilizers and herbicides. Page 57 of 110 5.3 PROGRAMMES AND STRATEGIES 5.3.1 Africa Stockpiles Programme (ASP) Although the Africa Stockpiles Programme (ASP) focused on obsolete pesticides and their associated waste, the Prevention component carried out legislative review under this project for the United Republic of Tanzania (URT) including plant protection matters for both mainland Tanzania legislation and Zanzibar. Through consultative meetings with the pesticide industry stakeholders, International trade requirements and harmonisation of the sanitary and phytosanitary systems. The Plant protection Act 1997 was split into two legislations: The Pesticide Management Act 2013 (Draft) and The Plant Protection Act 2013 (Draft). The programme also addressed the major issues in prevention of accumulation of obsolete pesticides and its associated wastes by putting in place an empty pesticides container maintenance strategy and the ASP sustainability Roadmap. The Plant Protection Act 2013 (Draft) The main objective of this Act is to prevent the introduction or spread of plant disease or pests; provide for phytosanitary control measures; facilitate trade in plants and plant products and to regulate other matters connected thereto. The Act is meant to establish a National Plant Protection Organization (NPPO). The NPPO core function will serve as a national contact point for the IPPC and shall develop mechanisms for consultation between responsible authorities for enforcement of the phytosanitary legislation for Tanzania and Promotion of integrated pest management and control. A cabinet paper for this Act has been presented to the cabinet first sitting, issues raised from this seating has been addressed ready for the second sitting later this year (2014) before the Act is tabled by the Attorney general - Chief Draftsmen to the Parliament. The Pesticide Management Act 2013 (Draft) An Act to provide for the life-cycle management of pesticides, regulating the manufacture, formulation, importation into and exportation from the country, transport, storage, distribution, sale, use and disposal of pesticides and to regulate other matters connected thereto. This Act will establish the Tanzania Pesticides Control Authority (TPCA) responsible for monitoring the trade and use of pesticides, and collecting statistical and other information concerning the import, export, manufacture, distribution, sale and use of pesticides, about pesticide residues and safe use. The act prohibits the importation, manufacturing, formulating, transportation, distribution, exportation or sell of banned, obsolete pesticides under: PIC and POPs and any other pesticide banned or severely restricted in the country of origin under any circumstances within the country or any pesticide for which is not in the category/group currently under use. In relation to IPM the authority suggests development and availability of safer alternatives to existing pesticides as per latest global research and development without compromising the importation of biological control agents as allowed in the Biological control agents protocol developed within the Plant Protection Act of 1997. Like “The Plant Protection Act 2013 (Draft)”, a cabinet paper for “The Pesticide Management Act 2013 (Draft)” has been presented to the cabinet first sitting, issues raised from this seating has been addressed ready for the second sitting later this year (2014) before the Act is tabled by the Attorney general - Chief Draftsmen to the Parliament. 5.3.2 Empty Pesticides Container Management Strategy Pesticide use by small scale farmers has been on the increase in the recent years. This has been attributed by availability of affordable convenient packaging. The bulk of the pesticides distributed in Tanzania are in small packs resulting to increased number of empty pesticide containers. This has resulted in the accumulation of empty pesticide containers in the farming environment. The greatest challenge facing the use of pesticides is recovery and disposal of empty pesticide containers. Currently there is no legal framework mechanism to guide on the disposal of the containers. Also the absence of organized disposal Page 58 of 110 system has rendered farmers and other users of pesticides dispose containers by throwing them away or putting them in the solid waste system in urban areas. In addition, the absence of information to rural communities on the risks pertaining to reuse of empty containers has created a major challenge. The strategy identifies the mechanism of dealing with empty pesticide containers and provided the framework of up-scaling the process through the stakeholder partnership and cost sharing initiatives. If not streamlined in the Good Agricultural Practices, the export market of agricultural produce will give a negative impact internationally. The strategy addressed the following critical issues: (i) increase awareness amongst pesticide users on the best practice of handling pest containers; (ii) sensitize the communities on risks of reusing empty pesticide containers for other purposes; (iii) provision of training and support of local agricultural authorities to promote safer use of pesticides; (iv) The quantification of the build-up of empty pesticide containers in the government stores and the farming communities; and (v) establishment of the recycling facilities of the pesticide packaging for which sustainable disposal/recycling options is needed. The stakeholders and target beneficiaries of the strategy are: (i) farmers who benefit from the disposal of containers (ii) rural communities who benefit from tighter controls on pesticide container disposal mechanisms (iii) policy makers at several government departments and agencies with regard to improved pesticide use and management; and (iv) recycling industry benefit from availability of raw materials. Page 59 of 110 6. PEST CONTROL AND MANAGEMENT OPTIONS 6.1 INTRODUCTION Insect control techniques for IPM have been known and are in use for along time. Some of the most effective non-chemical techniques such as biological control, host plant resistance, crop rotation, etc were widely used before the synthetic insecticides appear in scene. Recent problems of insecticide resistance in insect pests, other side effects and increasing cost of the insecticides have renewed interest in the non-chemical techniques. The techniques can be conveniently categorized in order of preference in IPM as biological control, the use of attractant, pheremones, repellents, genetic manipulation, insect growth regulators and the use of plant extracts. In this section biological control, cultural control, chemical control, quarantine and physical or mechanical control, chemical control and botanical control are presented. Biological control should not confused with natural control which is collective action of environmental factors that maintain the population of pests within certain upper and lower limits over a period of time (van den Bosch, 1982). 6.2 BIOLOGICAL CONTROL Every living organism has its natural enemies and diseases which kept its population at equilibrium. The natural enemies include predators, parasitoids, nematodes, fungi, bacteria, viruses etc. The use of predators, parasitoids, nematodes, fungi, bacteria and viruses for to maintain the population density of pests at a lowest level than would occur in their absence is called biological control (bio-control). Tanzania has some experience based on the successful control of the cassava mealy bug, the cassava green mite and the water hyacinth (Anon, 1999). The National Plant Protection Policy is also conducive to the promotion and use of bio-control as a strong IPM component. However, at national level, the capacity and capability to implement an effective nation-wide programme is limited. Approaches to biological control There are three approaches are used in biological control. These include conservation/enhancement, augmentation and introduction. Conservation/enhancement This refers to optimization of the impact of living agents that already exist in the ecosystem Augmentation This refers to as an artificially increasing the numbers of natural enemies in the agroecosystem Introduction This refers as importing new natural enemies’ species in the system where they were not found before. Host Plant Resistance The IPM concept stresses the need to use multiple tactics to maintain pest populations and damage below levels of economic significance. Thus a major advantage of the use of pest resistance crop varieties is its compatibility with other methods of direct control. Pest resistant cultivars allow a synergy of the effects of cultural, biological and even chemical pest control tactics. Host plant resistance (HPR) is of particular importance in developing countries where farmers lack the resources for other control measures. There are many examples of resistant varieties significantly increases crops productivity. However, farmers continue to grow varieties which are susceptible because resistant varieties can reduce the burden of pest control by using chemicals. Resistance to pests is the rule rather than the exception the plant kingdom. In the co-evolution of pests and host, plants have evolved defense mechanism. Such mechanism may be either physical (waxy surface, hairly leaves etc) or chemical (production of secondary metabolites) in nature. Pest-resistant crop varieties either suppress pest abundance or elevate the damage Page 60 of 110 tolerance level of the plant. In other words, genetic resistance alters the relationship between pest and host. The functional of the pest to the resistance may be non preference or antibiosis (early death, abnormal development). Also genetic transformation of the plant (expression of the bacillus thuringiensis toxins, protease inhibitors). The development of transgenic plants that are resistance plants that are resistant to viruses and insects has been more successful than for resistance to bacteria and fungi, but this gap is readily closing. Resistance genes for fungal and bacterial genes have now been cloned and there is a greater molecular understanding of plant pathogen interactions. The inherent genetically based resistance of a plant can protect it against pests or diseases without resource to pesticides. Moreover to use it the farmer has no need to buy extra equipment or learn new techniques. For example on farm in some parts of Kenya, up to 80% of plants exhibit symptoms of diseases in banana fields, but the use of plant resistance in bananas is the most effective approach to management of fusarium wilt and is the most economic and practical long term option for small scale farmers in Africa. Different Institutions in Nigeria and Uganda have developed banana cultivars with resistance to pests and diseases. Another example of varieties which are resistance to pest attack are maize varieties (TMVI, Staha, Kilima) which are either resistant or tolerant to maize streak the viral disease that cause significant yield loss to late planted maize. Other examples of resistant varieties are coffee clones (MS1, MS2, MS3 and MS6) against coffee leaf rust, banana varieties FHIAs which are resistant to Nematodes, Panama and Black Sigatoka. In cotton, host plant has been of the importance especially for small scale farmers who has low income. Great losses have been observed in cotton production due to insects like bollworm, aphids, leaf miner, jassids and diseases like fusarium wilt and bacterial blight. For pests like jassids though there is a means of spraying but it seems to be expensive because of high prices in buying chemicals and low farmers income to buy the chemicals. Thus all of varieties produced at Ukiriguru had resistance to jassids since they have hairs to interfere sucking insect pests. Also in the control of bollworm up to now still is a problem but in other countries the genetic transformation is used to transfer Bacillus thuringiensis to cottone plants in order to improve insect resistance in cotton cultivars. Cotton cultivars produced already showed success and had good response from farmers. The disease like fusarium wilt and bacterial blight, have the ability to reduce cotton yield to a high percentage. The effort to combat this situation is done on producing cultivars with resistance to these diseases. All Ukiriguru cotton varieties are resistant to bacterial blight and UK91 and UK77 varieties are resistant to fusarium wilt. In other crops like sweet potato to avoid the weevils’ infestation, other varieties are producing their tubers far away from the soil surface. Also sorghum to avoid bird attack some varieties have gooseneck that the bird can’t reach grains easily. For rice some varieties have awns to prevent themselves from bird attack. With host plant, the rate of spread and the rate of symptom development can be very slow. Also this tends to reduce the cost of pests and disease controls through buying chemicals also time consuming in bird scaring. Since pests and diseases reduce the quality of the produce thus the use of the host resistance materials assures the good quality for home consumption as well as for marketing where you are able to fetch a lot of income. All these efforts are made to reduce the costs involved in pests and disease control as well as to safe guide the environment. Pest resistance genes are predominantly found in wild species within the same genus or family as the crop plant. Because such plants are in dynamic equilibrium with the pests, the resistance genes are present in a high frequency to be readily found. Unfortunately resistance genes from wild species are often combined in linkages with undesirable genes and many recombination and selection steps are require incorporating them into useful cultivars. Another source of resistance genes is primitive cultivars or landraces, although this is much smaller reservoir diversity than wild species. For example, in potato, high levels of resistance to the green peach (Myzus persicae) has been identified in about 6% of examined accessions of wild Solunum species (Flanders, et al. 1992). Wild crop relatives have yielded pathogen resistance in, amongst Page 61 of 110 others, rice, wheat, barley, cassava, sweet potato, tomato, sunflower, grapes, tobacco, cacao, sugarcane and Musa. Host plant resistance (HPR) is also recognised in the new Plant Protection Policy as an invaluable component in IPM. Breeding and selecting for resistance to serious pest problems is an issue mandated to the National Agricultural Research programmes. These programmes have produced substantial results in terms of releasing varieties with necessary qualities and tolerance/resistance to a wide range of otherwise devastating pests of cotton, maize, sorghum, beans and cassava. Therefore, the Directorate of Research and Development in MAFS has the capacity and infrastructure to contribute HPR materials to farmers given the necessary logistical support. Considering the scope of the proposed programme, it will be appropriate for the project to provide logistical support for the multiplication, popularisation and distribution of crop varieties already proven to posses acceptable levels of tolerance/resistance to pests of economic importance. The issue of the grey leaf spot disease of maize, cassava mosaic diseases and rice yellow mottle virus must be given priority to ensure household and national food security. Rapid multiplication and distribution of cassava varieties with proven tolerance/resistance to cassava mosaic diseases and cassava streak diseases is equally important. Programme should allocate adequate funding to facilitate this activity. In addition, logistical support to facilitate the multiplication and distribution of the earmarked coffee varieties with resistance to CBD and CLR will be required as soon as Tanzania Coffee Research Institute releases them. Fast multiplication and distribution of the material is essential to speed up reduced use of copper-based fungicides in the coffee cropping systems in the northern zone. 6.3 CULTURAL AND CROP SANITATION PRACTICES This is one of the IPM components, which is used by farmers in controlling/reducing pests and diseases in crops. The cultural practices modify/destruct the environmental of crop pests and diseases by depressing their breeding/growing areas. The cultural practices are the same/different in single/groups. These practices are: Crop rotation: This practice is used to depress weeds and/insect pests and diseases in some crops. Example: A weed Striga in sorghum and millet can be controlled/reduced by planting a trap crop like groundnuts, cotton Intercropping: The field is used to grow two or more crops at the same time. Relay cropping: Example: Banana relayed with mucuna to reduce the infestation of weevils. Fallow: The field is not cultivated for some years in order to control various parasitic weeds. Cover crops: These are leguminous crops, which are grown to suppress weeds in the field. They can be intercropped or not and they prostrate and cover the field e.g pumpkins, canavallia etc. Trap crops: These induce the germination of a pest. The trap crop can be intercropped or rotated with a susceptible host (e.g groundnuts, bambaranuts, cotton etc). Mulching: This is covering of crop fields by dry grasses to control weeds and conserve soil moisture (e.g in coffee, banana, tomato field etc). Hand pulling and hoes weeding: These practices are the most common and being used by small-scale farmers. Burning: Land clearing and destroying infected plants/crops. Page 62 of 110 Fertilizer/manure application: The application of nutrients in the form of either inorganic fertilizer or farm-yard manure reduces both the infestation of fields by weeds (e.g Striga) and losses in crop yield. Use of disease free planting material e.g: cassava cuttings, sweet potato vines etc. Pruning: Done in coffee, tea orange tree etc. to reduce insect pests and diseases that might infest the crop. Thinning: Done to reduce plant population in the field (e.g in maize, sorghum and millet, cotton etc). Other cultural methods include spacing, desuckering, which is done in bananas; use of local tolerant varieties, sun drying to reduce moisture content of the material to be stored; and use of traditional storage method e.g ‘Vihenge’, banana sheaths, botanicals, clay soils etc. 6.4 PHYSICAL AND MECHANICAL CONTROL Physical and mechanical controls are the measures kill the insect pest, disrupt its physiological or adversely the environment of the insect pest. These differ from cultural control in that the devices or actions are directed against the insect pest instead of modifying agricultural practices. For examples, hand picking of cotton stainers from cotton plants, banana weevils from banana pseudostems, tailed caterpillars from coffee, killing stem borers in coffee or American bollworm from tomato plants are the forms of physical control while use of a fly swatter against annoying flies is a form of mechanical control. Common physical and mechanical control methods include the utilization of high and low temperature for instant hot water treatment of banana planting materials for control of nematodes, sun drying of stored grains, cool storage of maize grain, reducing humidity, utilizing insect attraction to light traps (lepidopteran insect pests viz. Armyworm and cotton bollworm). 6.5 CHEMICAL CONTROL It is important to recognise that, all the registered pesticides (Table 5.1 below) are recommended as part of IPM components in all production/cropping systems as indicated in the previous sections of this report. All the pesticides included on the list above are registered by TPRI Act, 1979 and Pesticides Control Regulations GN 193 of 1984) [Anon, 2001b], and this is why some pesticides e.g. paraquat, one of the 'dirty dozen', is still officially registered and allowed to be used in Tanzania. It is therefore strongly recommended that, the pesticide registrar ban all further importation and subsequent use of paraquat in Tanzania and others in the same category, with immediate effect. Those pesticides in WHO class Ib, namely endosulfan, chlorpyrifos, quinalphos, carbofuran, and isazophos, should be deregistered with immediate effect and phased out by year three of the programme and encourage use of less toxic and more IPM friendly pesticides. Both WHO class I and II are still featuring on the list of registered pesticides mostly because, the WHO class III, which are new generation pesticides known to be less toxic and therefore more environmentally and IPM friendly, are relatively more expensive and therefore beyond the means of most smallholder agricultural producers in Tanzania. In addition, the majority of such pesticides are not locally available. Therefore, judicious use of through integrated use of other pest management options is recommended to ensure reduction of potential health and environmental hazards. It is evident, albeit from Table 5.1, that, the current list of registered pesticides is outdated and also not in line with international standards. It is therefore strongly recommended that, the registrar of pesticides must review the current list of registered pesticides in line with the WHO guidelines immediately. The current list of pesticides registered in Tanzania indicates trade name, registration number, common name, registrant and usage. This is not informative enough given the wide range of its users. It is therefore recommended that, the proposed revised list should include the WHO class, oral LD50, active ingredient, and application rate. Page 63 of 110 Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania: Oral LD50 and WHO classification Chemical Common name *Oral LD50/kg WHO class Comments Insecticides Betacyfluthrin 500-800 II Biphenthrin Carbaryl 850 II Chlorpyrifos 135-163 Ib Deregister & Phaseout Cypemethrin 251-4125 III Cypermethrin + Dimethoate 251-4125 + 2350 III Deltamethrin 153-5000 III Dealtamethrin + Dimethoate 153-5000+2350 III Diazinon 220 II Dimethoate 2350 III Endosulfan 55-110 Ib Deregister & Phaseout Esfenvalerate 451 II Fenitrothion 800 II Fenvalerate 451 II Fenvalerate + Fenitrothion 451+ 800 II Flucythrinate Hydrmethyl Lambda cyhalothrin 243 II Permethrin 430-4000 III Pirimiphos methyl 2050 III Pirimiphos methyl + permethrin 2050 + 430-4000 III Profenophos 358 II Profenophos + cypermethrin 358 + 251-4123 II Quinalphos 62-137 Ib Deregister & Phaseout Nematicides Carbofuran 8-14 Ib Dazomet 520 II Isazophos 40-60 Ib Deregister & Phaseout Herbicides Atrazine Diuron Fluometuron Glyphosate Metolachlor + Atrazine Metalachlor + Dipropetrin Paraquat Dirty Dozen: should be banned with immediate effect Chemical Common name *Oral LD50/kg WHO class Comments Avicides Fenthion Cyanophos Rodenticides Bromodiolone Coumatetralyl Page 64 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Diphacinone Fungicides Bronopol Chlorothalonil 10,000+ III Copper hydroxide 1,000 II Copper oxychloride 70-800 II Cupric hydroxide 1,000 II Cuprous oxide Cyproconazole 1,000 II Hexaconazole 2189 III Mancozeb 5000+ III Metalaxyl + Mancozeb 633 + 5000+ III Penconazole Propineb 1,000 II Triadimefon 1,000 II Sulfur Sources: TPRI: List of Pesticides Registered in Tanzania, May 2004 and Nyambo 2002 It may be noticed that Tanzania has ratified the Convention on Persistent Organic Pollutants (POPs) in April 2004 (pers.comm. A.Madate, Division of Environment and National POPs Project Coordinator), but has not yet banned the highly harardous pesticides (WHO classes Ia, Ib, II). However, projects involving use of chemical pesticides under WHO Class Ia, Ib and Class II will not be financed under the proposed SAGCOT Investment Project. Appendix 3 provides WHO classification of chemical pesticides. 6.6 BOTANICAL PESTICIDES Assessment of botanical pesticides for pre and post harvest is being done by a number of institutions in the country and some of the potential ones have been recommended for use in crop production (Paul et al. 2001). In beans, extracts of Tephrosia vogelii and Neuratanenia mitis have been recommended and farmers are using them because they are easily available and less costly. Where these do not occur naturally, farmers have also established the plants in their home gardens to ensure availability when needed. The GTZ-IPM project in Arusha in collaboration with IPM farmer groups and the extension staff has compiled a list of useful botanical pesticides (Table 5.2) that could be used on a wide range of vegetables and other food crops. The information is useful but has to be used with caution. Most of the botanical extracts are already in use by small-scale farmers as crude in-house preparations. However, they should be used with caution. It has to be remembered that not all botanical extracts are safe. Tobacco extract is one of the deadly substances and should therefore not be promoted for use on vegetable production. Tephrosia spp extract and leaves are toxic to fish (local fishermen use the leaves for fishing) and therefore should be used with caution. None of the suggested botanical extracts (Table 5.2) are registered in Tanzania because they have not been researched enough. In particular, information on dosage rate, mammalian toxicity (LD50), side effects on non-target organisms especially potential bio-control agents, biodegradation and reduce analysis data, is not available. However, 3 neem-based and 2 pyrethrum-based commercial formulations are being processed for registration. These two botanicals have been researched and registered in Kenya and elsewhere. Page 65 of 110 Table 8.2 List of potential plants that can be used to prepare botanical extracts for pre and post harvest pest control Kiswahili name English name Scientific name Mustafeli Soursoap Annona muricata Mtopetope Bull-oxheart A. reticulata. Mtopetope mdogo Custard apple A. squamosa Vitunguu saumu Garlic Allium sativa Mwarobaini Neem Azadirachta indica Kishonanguo Black Jack Bidens pilosa Pilipili kali Chili Capsicum frutenscens Mpapai Pawpaw Carica papaya Mnanaa Thorn apple Datura stramonium Mnyaa/utupa Milk bush Euphorbia tirucalii Mchunga kaburi Barbados nut Jatropha curcas Mwingajini Wild sage Lantana camara Tumbaku Tobacco Nicotiana spp Kivumbasi Mosquito bush Ocimum suave Mbagi mwitu Mexican marigold Tagetes spp Alizeti mwitu Wild sunflower Tithonia diversifolia Utupa Tephrosia Tephosia vogelii Source: Paul (2000) and Madata (2001). Page 66 of 110 7. EXPERIENCES ON IPM IN TANZANIA 7.1 INTRODUCTION During her study Nyambo (2002) gave a comprehensive analysis of the Tanzania Mainland experience on participatory IPM. Information from the analysis and visit to key stakeholders, namely the Minsitry of Agriculture and Food Security’s Plant Health Services, Zonal Agriculture Research and Development Institutes (ZARDI), Sokoin University of Agriculture, districts and farmers are summarized in this section. The national research institutions have developed IPM approaches for a wide range of key pests of the major crops mentioned earlier. Some of the information is locality specific e.g. in cotton, maize, coffee and beans. Unfortunately, a lot of the information has not reached target farmers. The information that has filtered through to farmers is not user friendly and/or not appropriately formulated and therefore farmers are unable to optimise the benefits of such options (Nyambo, Masaba & Hakiza, 1996). This is a result of the \"top-down\" syndrome, which dominates the national research and extension systems. A change in attitude in the national research and extension system is needed to pave way for participatory knowledge development and transfer. Researchers, extension workers, farmers and other stakeholders must work as partners to achieve effective and sustainable technology development and transfer. Farmers must be active participants in the process of problem identification, development and formulation of appropriate solutions to identified pest problems in the context of other production constraints. In recognition of the shortcomings of the traditional top down extension system in promoting sustainable IPM approaches and to prepare a foundation to facilitate and enhance grass-root based system of extension, the Ministry of Agriculture and Food Security, in collaboration with GTZ, FAO and IFAD, had implemented IPM pilot projects to promote farmer participatory integrated pest management approaches in different parts of the country and cropping systems. The lessons from the above projects will be integrated in the IPMP to support decision making in the dissemination and promotion of appropriate IPM options in different cropping systems under SAGCOT. 7.2 GTZ/PHS-IPM The IPM project was initatied in 1992 by the Ministry of Agriculture and Food Security, namely Plant Health Services (PHS) and the German Agency for Technical Cooperation (GTZ). The IPM pilot area was the western growing zone (Shinynanga). This was the area using a lot of pesticides to redcue losses emanating from pests. The IPM project was resource intensive with the GTZ granting Tshs 500 million which is 90% of the budget allocated for IPM implementation annually and the counterpar funding by MAFS was Tshs 50 million per annum. The project operated for 11 years under the following phases: Baseline and diagnostic surveys, training of counterpart staff, introducing IPM concept at farmers’ level, etc. Phase I (1992-1994) Developmemnt, testing and dissemination of the IPM technical packages on priority crops in the pilot area of the western zone Dissemination and extension of IPM technical packages to other regions in the western and northern zones respectively: Tabora, Kigoma, Kagera, Mara, Mwanza, Arusha, Kilimanjaro, Tanga. Phase II (1997-2002) Handing over and consolidating the achievements. The project came to end in September 2003. IPM recommendations accomplished by the project indlcude: 6 recommendations in cereals (maize and sorghum) 4 recommendations in cassava 12 recommendations in beans 8 recommendations in onions 3 recommendations in cotton 2 recommendations in sweet potato 5 recommendations in vegitables and fruits 2 recommendations on weed management Page 67 of 110 The project was also instrumental to the production of the Plant Protection Act 1997, which was operationalized in July 2001. The knowledge base and capacity of the project is centred in PHS HQ and its plant health services zonal offices in the country. Approach and Organizational structure: The project used a modified farming systems approach for planning, development and field evaluation of IPM options. This is a mixture of participatory and exploratory methods, as deemed appropriate depending on the level of training of the extension workers and the problem to be addressed. The key elements in the approach include socio-economic baseline (knowledge, attitude & practices) and diagnostic technical plant protection surveys done by experts. These surveys generated a wide range of background information and a basis for M&E. This was followed by participatory technology development and transfer through farmer groups, referred to as IPM Working Groups, in different agro-ecological areas in respective regions. The baseline information was later used in the extrapolation of data and options to other areas in the project areas. In this approach, the IPM Working Groups are equivalent to the Farmers Research Groups used in the farming systems approach. Group formation: The IPM Working Groups (self formed groups) were initiated by the project with assistance from VEOs and local community development officers for purposes of training and promoting IPM. However, if there were already existing self-formed farmer groups in the village, these were also considered for collaboration. After clarification of the expectations and roles of the partners, the groups were recruited. Group management and promotion of IPM: The project technical staff visited the IPM Working Groups frequently (several times a week at the beginning of the project) to establish rapport with the group members, to set-up on-farm trials and demonstrations, test extension materials as well as plan and evaluate group activities. The project provides technical information on IPM options, training and group facilitation (moderation). The role of the groups is testing and fine-tuning of IPM options and other extension recommendations. Once the IPM Working Groups have approved a technology, the group results are disseminated to other farmers in other similar agro-ecological areas. After several seasons of training, the IPM Working Group is transformed to an IPM Farmer Training Group and a new IPM Working Group is initiated in another village and the process continues. Participatory Group Training approach: The IPM Working Group in collaboration with the project technical staff identified key limiting pest problems and other production constraints for each crop in the area. The project technical staff provides a range of recommended relevant solutions for testing by farmer groups. For selected crops, individual members in the group tested the options in demonstration plots, one crop per farmer. The members make joint visits and analysis of the demonstration plots throughout the growing period until harvest. During the training sessions, farmers are facilitated to recognise the major pest problems, potential damage, management options, insect pest's natural enemies and good post harvest practices with emphasis on IPM. Essentially, group training involved four stages that are summarised as follows: 1. Capacity building to impart knowledge on IPM and participatory methods of technology transfer, group formation and management to selected project technical staff. 2. Demonstration within groups whereby the technology or information is tested for the first time by a farmer within the group under close supervision by the project technical staff. All group members make continuous visits and observations and participate in the analysis of the results. 3. Adaptations in farmer own plots by group members. Farmers are encouraged to keep field records, share the information with group members and carry out joint analysis of the results. 4. Village cycle spill-over whereby the technology is applied by non-IPM farmer groups in the same village. Page 68 of 110 5. The technology was finally approved for dissemination to other areas with similar crops/pests and agro-ecological similarities. Participatory evaluation of results and practices: At the end of each crop season, the project technical staff guides the group members to evaluate the trial results using simple PRA tools. To motivate the groups, a meeting of representatives from all IPM Working Groups was convened once a year for joint evaluation of results. Internal M & E: The project has an established continuous internal M & E to assess project impact and spill-over. The project was using an evaluation form, which was supported by regular field visits for verification. Spill-over and role model effects: KAEMP and MARAFIP have copied the project approach. Capacity Building: The project has trained 999 VEOs/DPPOs in IPM within the project area, i.e. 697 in the Western and 302 in the Northern Zones. The IPM project and the District Councils through their respective support programmes, i.e. MARA-FIP, KAEMP, Care, Farmafrica, DRDPs, Faida, Ecotrust, World Vision, LVEMP, etc. have jointly financed the training. The VEO have in turn trained 484,825 farmers in IPM, i.e. 421,487 in the Western and 63,338 in the Northern Zones. The VEOs were also facilitated formation of 44 IPM working groups, each with an average of 15 farmers (14 IPM groups in the Western and 30 IPM groups in the Northern Zones). These groups play a role model for IPM development, testing of recommendations, validating, implementing and disseminating. Impacts: The extent of impact achievement with regard to the benefits of IPM such as environmental conservation, restoration of beneficial organisms, etc. has not been evaluated. The following impacts have observed (Nyakunga 2003): The use of conventional pesticides in cotton in Shinyanga has been reduced from 6 calender sprays to maximum 3 sprays without negatively affecting production. The evidence of this is the increased cotton production in the Western Zone from 38,000 tons in 1994/95 to 69,900 tons in 2000/01 Safety of users against conventional pesticides: The National Plant Protection Advisory Committee has been instituted in line with the Plant Protection Act of 1997 and is actively guiding and monitoring implementation of plant protection activities in Tanzania. A cost recovery system for the services rendered under the PPA of 1997 is in place with the PHS is able to strengthening the phytosanitary and quarantine measures at the major entry points. The IPM has also been integrated in the Agriculture and Livestock Policy as a national policy on plant protectin and the ASDP has provided that IPM should be disseminated country wide. The success of the GTZ/PHS-IPM initiative was a result of team approach, institutional collaboration (NGOs, national research and extension institutions, and international institutions) harmonisation of technical information between collaborators, adequate flow of funds, good organisational and supervisory skills and staff continuity. 7.3 KAGERA AGRICULTURAL AND ENVIRONMENTAL MANAGEMENT PROGRAMME (KAEMP) KAEMP was a multi-sectoral initiative of the Kagera region (Lake Zone) jointly funded by IFAD, BSF/JP and OPEC with contributions from the beneficiaries. The project was implemented by RAS Kagera and managed by the local government machinery. Its main focus was on improvement of food security and poverty elevation, and therefore, has a holistic approach (addresses agriculture, health, livestock, environment management, rural access roads and marketing) to rural development. In this setup, IPM has been embraced as the key pest management in all crops. To support gradual and sustainable adaptation of IPM and integrated plant nutrition (IPN) by resource poor farmers, the project promoted validated and recommended technologies from national and international agricultural research institution. Selected technologies must be applicable, economically viable and environmentally friendly. Page 69 of 110 The major crops grown in the region are cotton, coffee, banana, cassava and beans. As mentioned above, KAEMP borrowed the IPM approach (baseline studies, group formation and training, internal M & E etc.) from the GTZ/PHS-IPM Shinyanga project. In addition, the linkage between the two projects was strong. GTZ/PHS-IPM technical staff were used as resource persons by KAEMP while Kagera farmers visits the IPM Farmer Training Groups in Shinyanga for learning purposes. However, due to the nature of the KAEMP set-up, some modifications of the Shinyanga approach were deemed necessary in order to accommodate the overall goals of the project. In crop production, declining crop yields, soils fertility and increased pest pressure were identified as major constraints. To address the issues, the project farmer groups were known as IPM/IPN groups (integrated pests management/integrated plant nutrition groups). Capacity building: Since the project is an integral part of the regional development plan, all extension staff (from the district to the village level) were given training in IPM, IPN, and participatory methods of technology transfer with emphasis on group approaches. In this approach, the district extension officer was the foci for new extension messages. It was the responsibility of each district extension officer to ensure proper technology transfer to end-users and hence the need for them to be well informed about participatory methods of extension. In summary, capacity building in KAEMP was implemented in several stages 1. District technology transfer manager (master trainer) was trained in IPM/IPN concepts and approaches including participatory methods of technology transfer through farmer groups; 2. The master trainer trains the VEOs; and 3. The VEOs train farmer groups. To enhance the learning process between groups, the project facilitated farmer-farmer learning through group exchange visits between groups within and between villages and districts. A few farmer representatives visited the Shinyanga IPM farmer training groups. To promote spillover, KAEMP organised and facilitated field days. The IPM/IPN farmer groups were also used for the transfer of other development messages e.g health, water, environmental management etc. and therefore were foci for all extension messages. The KAEMP initiative started in September 1999. By May 2001, the adoption of IPM/IPN within groups was 60% whereas the spillover (diffusion) after 20 months of operation was 1:3, which is quite impressive (J. B. Anania, E. A. M. Anyosisye, personal communication). KAEMP owes much of its success to the GTZ/PHS-IPM Shinyanga experience. The entire stakeholders at regional, district, village and farm level has received the approach with enthusiasm. Successes:The achievements of the project was a result of good political support at regional level, team spirit, sufficient funding, effective capacity building, institutional collaboration, good organisational abilities and focused selection of appropriate technology for transfer to target clients. 7.4 MARA REGION FARMER INITIAITIVE PROJECT (MARAFIP) MARFIP was an initiative of Mara region whose main objective was poverty alleviation through strengthening of capacity of the local institutions to respond to farmer's felt needs related to food, agriculture and livestock. The project was organised and implemented by RAS and funded by IFAD. As mentioned above, MARAFIP was another offspring of the GTZ/PHS-IPM project (S. O. Y. Sassi, personal communication) and therefore, has many common features. However, MARAFIP used the FAO IPM-FFS approach of group training and technology transfer. Capacity building: All district plant protection officers and VEOs were given training in IPM concepts to raise awareness about IPM to facilitate their supervisory role. Five VEOs (project staff) of selected villages Page 70 of 110 for FFS pilot groups were given one-month split course in IPM, group management and participatory technology transfer methods to provide them the capacity to organise and conduct IPM-FFS. There were 5 IPM-FFS groups in the region, one per district. The main focus crops were cassava, cotton, maize, sorghum, legumes (cowpeas, field beans) and sweet potato. The IPM messages/technologies introduced to the FFS groups were borrowed from the Shinyanga IPM project without further refinement. In one case, the \"broken telephone message syndrome\" was noted with concern. At farmer level, the approach has been received with enthusiasm and adoption of some messages among group members was estimated to be about 25% (one year after IPM training). The IPM-FFS groups were also used as entry points for other extension messages e.g. soil and water management, livestock management and community health, which is in line with the regional objectives. However, funding to facilitate technical support to farmer groups was a constraint, and scheduled activities have been shelved. 7.5 MBEYA: SOUTHERN HIGHLANDS EXTENSION & RURAL FINANCIAL SERVICES PROJECT/IFAD This initiative started with organised extension farmer groups in 1996/97 using a modified T&V extension method to enhance technology transfer at farm level. Essentially, the approach was still strongly based on the traditional \"top-down\" extension method (E.D. Y. Kiranga and A. H. Urio, personal communication). In 1998/99 the project introduced IPM-FFS pilots in Mbeya (focused on tomatoes, cabbage, round potatoes and wheat) and Ruvuma (focused on coffee and maize) regions. The IPM-FFS and extension groups ran parallel in the same villages. IPM-FFS capacity building (IFAD/FAO initiative): Two VEOs (master trainers) attended a 3 months course in Zimbabawe under the sponsorship of FAO. The project supervisors visited IPM-FFS groups in Kenya for two weeks to gain some basic experience on how to organise and conduct IPM-FFS. This was followed by 2-weeks residential training course in IPM and farmer participatory methods of technology transfer for 25 VEOs in Mbeya and Mbinga districts. The graduates reported back to their duty stations to organise and conduct IPM-FFS in their respective villages. Similar to the GTZ/PHS-IPM project, farmer-farmer learning through exchange visits between farmer groups and within group members was facilitated. Like in the other initiatives, organised field days and exchange visits were used to encourage spillover to non-group members. Institutional collaboration was also emphasised during the project implementation phase. The IPM-FFS approach was highly appreciated by farmers and the VEOs because it was participatory and learning by doing. 7.6 MOROGORO SPECIAL PROGRAMME FOR FOOD SECURITY (SPFS) /FAO PROJECT This was an initiative of the Ministry of Agriculture and Food Security in collaboration with FAO that targets Morogoro and Kilombero districts, with a focus on maize and rice (the major crops in the area) and promotion of small livestock (poultry, milk goats and chicken). The project started in 1996 and ended in1998. The initiative promoted farmer participatory group approaches of technology transfer. Because this capacity was not within the project staff, training in participatory approaches was organised and provided by the Co-operative College Moshi for the project core staff (E. Shayo, personal communication). Baseline surveys and group formation was the same as for the GTZ/PHS-IPM project detailed above. Although the project benefited from the southern highlands initiative, there was limited integration of the IPM-FFS approaches in the Morogoro farmer groups. At the time of the visit, seleceted VEOs were being given a course in IPM-FFS. Page 71 of 110 Capacity building 1. Master trainers were trained by Co-operative College Moshi to impart participatory methods of technology transfer to selected extension workers. 2. Selected VEOs and farmers from targeted farmer groups were given whole season training at one training site on selected crop and extension messages that included aspects of plant protection. The graduates were used for field demonstrations of identified and proven extension messages in target groups in their villages. This stage has some attributes of IPM-FFS. 3. The demonstration farmers in collaboration with the VEO trained group members. Once the technology is approved by the group, it is ready for dispersion to the whole village. This approach has many attributes of the GTZ/PHS-IPM and KAEMP approaches. As in the other projects, the training groups in SPFS/FAO project were also used as entry points to transfer other extension information e.g. water control and management, exploitation of groundwater in crop production, marketing (input supply), credit system, record keeping, diversification of farm enterprises, shallow wells etc. In the first year, the project provided free inputs to the demonstration farmers as motivation. In the second year, inputs were provided on credit with 50% advance payment to wean them off. There was some adoption by group members and spillover particularly of those technologies that directly addressed farmer felt needs. Farmers, village leadership, VEOs, district and regional leadership also appreciated participatory group training as a means to effect quick and efficient technology transfer. However, due to a lack of logistical support, new training groups have not been formed. 7.7 LESSONS AND GENERAL DISCUSSION 7.7.1 Approach All the projects discussed in the previous sections above were actively promoting participatory technology transfer to increase food security and cash income at farm level through self formed farmer groups. Some of these groups are now officially registered. All the initiatives emphasised IPM in their farmer groups. The groups were used as entry points for other innovations on a felt need basis irrespective of the original purpose. The IPM farmer groups were used as foci for the extension of a wide range relevant and appropriate technology and knowledge, this enhancing group cohesion and overall development. The participatory group approach to technology transfer was received with enthusiasm by all the farmers and VEOs in all the visited projects. This is because it involved hands-on-learning, an observation made by all the farmers visited. 7.7.2 Capacity Building These model projects have a lot in common. Capacity building with emphasis on participatory methods of technology transfer, group formation and management were deemed necessary and essential for the project technical staff before training farmer groups. Collaboration and sharing of experiences between projects was key to the success of new initiatives in different parts of the country. The GTZ/PHS-IPM project played a major role in the set up and organisation of KAEMP and MARAFIP, whereas the Morogoro region initiative benefited from the experiences of the southern highlands project. Page 72 of 110 7.7.3 Institutional Collaboration This was observed as key input in the success of the entire visited pilot projects. Institutional collaboration (as indicated in the GTZ/PHS-IPM initiative) ensured harmonisation of technical information, optimisation of scarce resources and ensured farmers of the best remedies to priority problems. As indicated above, collaboration between projects within the country was a healthy avenue for sharing experiences that facilitated speedy setup of new initiatives. 7.7.4 Funding and Logistical Support This is very crucial in all the projects. Adequate and timely release of funds determined the progress of the projects. Currently, and in particular where donor funding has been phased out, project activities have been constrained by a lack of continuous flow of funds, this resulting to infrequent visit and training of established farmer groups. Scheduled activities have been affected in most areas and technical input in existing farmer groups have been curtailed. Fund flow from district councils to support extension services, particularly the farmer groups, after decentralisation is minimal and/or non-existence. The lack of logistical support from the district councils is purported to be largely due to lack of awareness among district decision makers on the significance of promoting participatory group approaches in extension. 7.7.5 Political support Local political support is also crucial in the implementation and sustainability of group approach to IPM promotion. KAEMP is the only initiative that seems to have stronger support. This is most likely a result of the project set-up and its holistic approach that addresses the broader needs of the region. Page 73 of 110 8. IMPLEMENTATION STRATEGY 8.1 INTRODUCTION Implementation of PMP in the project area of SAGCOT is highly recommended. This PMP will address the project needs to monitor and mitigate negative impact of any increase in the use of agrochemicals, particularly chemical pesticides by promoting ecological and biological control of pest management. The PMP shall provide an information basis for stakeholder groups to establish functional mechanism enabling selected farmers to identify, understand and manage pest problems in the further development of community and farmer groups agriculture, reduce personal and environmental health risks associated with pesticide use, and protect beneficial biodiversity such as natural enemies of pests in the farmers’ efforts to increase productivity. The PMP also raises the need of stakeholders to understand and respond to the situations where introduction of alien invasive species necessitates quarantine and stringent minimum pesticide residue levels. The PMP also proposes collaboration with national and international IPM institutions (plant protection organisations -research-extension- private partners) strengthening policy and institional framework and building capacity. The main objectives of the PMP is to enable SAGCOT to oversee in holistic the implementation of the IPM as a tool for pest management including monitoring of pests and disease vectors and mitigate negative environmental impacts associated with pest control in the project area and promote agro-ecosystem management. The plan provides decision-makers, key stakeholders and investors under SAGCOT with clearer guidelines on IPM approaches and options to reduce crop and livestock losses while protecting human and environmental risks. For all sub-projects which triggers OP 4.09 the MGF recipient must adhere to the provisions and recommendations of this IPMP. It is also recommended that the requirements indicated in the IPMP be incorporated by binding references in the project legal agreement. Further to this the SAGCOT Investment Project’s Operational Manual should include the list of pesticide products authorised for procurement under the sub-project (table 8.1 and 8.2) as well as the WHO pesticides classification lists which dictates pesticides that are not permissible in the Project (Appendix 3). 8.2 INSTITUTIONAL ROLES AND RESPONSIBILILTIES Various stakeholders will be critical for the implementation of the IPMP. The roles and responsibilities of these stakeholders are described below. 8.2.1 MGF Applicant/ Recipient As part of the MGF application the MGF Applicant should include basic information on current use of pesticides, potential impacts from the proposed sub-project on pesticides use, any existing pest management systems used by the Applicant, and the Applicant’s proposed approach to address potential impacts. Appendix 2 contains an IPM checklist to guide the planning and implementation of pest controls on crops. For category A and B sub-projects the MGF Applicant is responsible for preparing an Environmental and Social Management Plan (ESMP). The ESMP will outline Environmental & Social actions to be implemented by the MGF Applicant against a proposed timeframe, and this will be reviewed by the FM and discussed with the Applicant to ensure the adequacy of the ESAP. The ESMP should consolidate actions from all required safeguard studies which must be prepared and submitted along with the grant application (e.g. PMP if applicable). If the sub-project intends to introduce new pest management practices or expand the use of pesticides or other agrochemicals, and a Pest Management Plan is required (as determined by screening, scoping and/or the EIA), the MGF applicant will have to include in the grant application (in the text or in an annex) a list of pesticide products authorised for procurement under the sub-project2, or an indication of when and how 2 The World Bank does not finance formulated products that fall in WHO classes IA and IB, or formulations of products in Class II, if (a) the country lacks restrictions on their distribution and use; (b) they are likely to be used by, or be accessible to, lay personnel, Page 74 of 110 this list will be developed and agreed on. This authorised list will also be referenced in the ESAP. In the case where a proposed sub-project has been approved the implementation of the PMP will be the responsibility of the MGF Applicant (now the project implementing entity). The project implementing entity shall also cover all costs associated with the implementation of the PMP including training and awareness activities and submit regular status report on the E&S performance (including pest management performance and pest use) to the FM. 8.2.2 Catalytic Fund The Fund Manager (FM) will undertake a preliminary screening of proposed sub-projects based on the inherent environmental and social risks associated with the sub-project type and requirements (location, size, etc.), using the Screening form in Annex 8 of the ESMF. The results of the preliminary screening form exercise will be used to determine (i) the eligibility of the sub-project for further processing, (ii) the environmental category of the proposed sub-project, and (iii) the environmental and social due diligence work required in order to prepare a detailed application (including preparation of safeguard instruments such as a PMP). If the sub-project intends to introduce or expand the use of pesticides or other agrochemicals the FM will trigger OP 4.09 and require the MGF Applicant to prepare a PMP which will be reviewed and approved by the FM. OP 4.09 should also be triggered if sub-projects plans introduce new cropping methods or diversify into new crops, particularly those that require intensive pest control. The FM will be responsible for carrying out compliance monitoring by visiting selected sub-projects on a regular basis and reviewing the effectiveness of implementation of the activities specified in the sub-project ESAP including mitigation measures related to pest management. 8.2.3 Ministry of Health and Social Welfare Health facilities (hospitals, health centres and dispensaries) in the SAGCOT area should set up databases on incidence of data on poisining, effect of pesticides on human health and environmental contamination. This data will then be used to measure and validate the ameliorating effects of IPM adoption and pilot PMP implementation that is expected to reduce risks to pesticides exposure. Considering the number of Class II pesticides that might be used and Rodent control products (Ia), it would be wise to strenghthen the poison centers or units of the hospital and equipe them with key antidotes (vitamin K in case Rodenticide poisoning and Atropine for Organophosphate poisoning. 8.2.4 Ministry of Agriculture, Food Security and Cooperatives The Ministry of Agriculture, Food Security and Cooperatives (MAFC) is key stakeholder responsible for ensuring that promotion of IPM as standard practice for SAGCOT investors and associated smallholder/outgrower operations. 8.3 PROMOTION OF IPM UNDER SAGCOT 8.3.1 Specific PMP for Sub-Projects As mentioned, all sub-projects which triggeres OP. 4.09 are required to prepare a detailed PMP. The PMP should address those aspects of a chemical pesticide’s life cycle that are part of project activities, from pesticide production to distribution, handling, transport, storage, and application, to its final disposal. The plan should also include provisions to supply necessary safety equipment and training for their use. For all PMP activities detailed budget lines must be specified and included in the overall budget for the sub- project. farmers, or others without training, equipment, and facilities to handle, store, and apply these products properly. Therefore, in compliance with this requirement, under SAGCOT, sub-projects involving use of chemical pesticides under WHO Class IA, IB and Class II will not be financed. Page 75 of 110 In cases where MGF recipients during project implementation wish to procure or use pesticides which are not included in the list of pesticide products authorised for procurement the pesticide product is subject to a screening and approval done by the FM. The criteria for the selection and use of pesticides specifically require that: “(i) They must have negligible adverse human health effects; (ii) They must be shown to be effective against the target species; (iii) They must have minimal effect on non-target species and the natural environment. The methods, timing, and frequency of pesticide application are aimed to minimize damage to natural enemies. Pesticides used in public health programs must be demonstrated to be safe for inhabitants and domestic animals in the treated areas, as well as for personnel applying them; and (iv) Their use must take into account the need to prevent the development of resistance in pests. 8.3.2 IPM to be Part of Environmental and Social Management Plan Each of the subprojects to be financed through the SAGCOT Investment Project will be subject to environmental and social screening, assessment, and approval process as required by SAGCOT’s Environmental and Social Management Framework (ESMF). The process complies with both the World Bank’s safeguard policies and Tanzanian EIA regulations and related guidelines. It is also consistent with the Investment Policies and Operating Guidelines for the Matching Grants Facility and Social Venture Capital Fund outlined in the Trust Deed of the SAGCOT Catalytic Trust Fund (which includes Environmental and Social Review Procedures). For category A subprojects a site specific Environmental and Social Impact Assessment (ESIA) will be conducted. For both category A and B sub-projects grant applications must include an Environmental and Social Action Plan (ESMP). The ESMP include activities, impacts, mitigation and enhancement measures, time schedule, costs, responsibilities and commitments proposed. Subsequently, the ESMP will inform the environmental management system (EMS) of the project through: (a) Ensuring that its activities are in line with applicable environmental laws and regulations; (b) Determining priorities and set objectives and targets to be met by the EMS. A reporting mechanism shall also be established so as to determine whether the targets are met or not, and for record purposes; (c) Identify training needs vis-à-vis the environmental and social objectives and targets, and put a plan for capacity building among staff in place; and (d) Establish environmental and social management programs to be undertaken within given time frames and by particular persons to take corrective measures. As such, roles and responsibilities shall be defined, documented and communicated for effective environmental and social management. In essence, where the use of pesticides is considered necessary, ESIA studies will dwell around the following information which must be obtainedas minimum:- Pest and beneficial populations in the field crop; Assessment of economic pest damage; Target crops and possibly growth stages; Recommended pesticides for the crop and its problem, their price and where obtainable; Pests and beneficials spectrum covered, including growth stages of the target organisms; Dose rates, dilution, timing and frequency of application; Waiting period (particularly for vegetables and stored produce); Method of application and equipment; Costs of application; Precautions to be taken (safety gears and measures); and Storage conditions and shelf life. 8.3.3 The IPM Strategies for Promoting its Adoption The main strategy to promote IPM in the project area could be embedded as: “Sensitize-Capacitate-Adapt and Scale Out”. All key stakeholders are sensitized on the benefits of IPM, and the necessary capacity provided at different levels. This is mainly; training, provision of resources and logistic support. Page 76 of 110 Technological options are then tested in collaboration with Research Extension and farmers and those proven to work are adopted and spread by farmers among themselves. As the process becomes dynamic and self-propelling, the technical team continues into new areas and the extension agents continue to backstop. Participatory approaches and tools (IPM working groups, Farmer Field Schools (FFS) etc) are the hub of the strategy, and where necessary, the strategy avoids duplication of efforts by consolidating outputs and experiences from the previous pilot IPM Tanzania/GTZ project and other IPM/ FFS projects. Since the IPM strategy has not been widely adopted, the SAGCOT could adequately mainstream the IPM policy directives, organize and coordinate IPM platform nationally and or regionally. The strategy could bring on board other non-government IPM initiatives (Private Sector, NGOs and Development projects) whose approaches and strategies are not integrated into the national strategy. For some reasons of lack of adequate and sustainable resource allocation, popularization of IPM strategy outside the former pilot area has been limited, and therefore use of technologies and experiences from previous projects has not been fully exploited. SAGCOT could therefore make use of this experience where applicable. However, SAGCOT project initiatives and operational procedures on IPM could be the fundamental process through which IPM can be popularized. The strategies and operational procedures could also be complemented by strategies from elsewhere in Africa. 8.3.4 SAGCOT to Advice Investors on IPM Practices As a rule of thumb, Farmers practicing IPM are regularly advised by the agricultural extensionists who could receive training on IPM from projects and elsewhere. This is part of their day-to-day activities but due to problems of transport and other logistic support, advice to farmers throughout the cropping cycle cannot be guaranteed. SAGCOT could harmonize with the local government authorities to organize field days for IPM farmer groups where many farmers are advised at a time. Moreover, SAGCOT could fund the preparation and printing of extension material and be provided to the extension services. Other avenues for disseminating information could include the use of mass media, particularly the radios, TVs and annual agricultural shows at district and regional levels. 8.3.5 SAGCOT to Support IPM Training in Research and Training Institutions Currently, in the curriculum of MAFC agricultural colleges, IPM is a subtopic under a major topic of Insect Pest Control Methods, and it is the last on the list of these subtopics. Other topics include methods of controlling field and storage pests, physical and mechanical control, biological control, legislative control, cultural control, host plant resistance and chemical control. Students are only made aware of IPM but nothing detailed. The learning objective in the curriculum states that students should be able to explain the importance of IPM in conserving biodiversity. Sokoine University of Agriculture has a pest management centre. The centre provides tailor made training on IPM on request. In the faculty of agriculture, IPM is a subject in pathology, entomology and weed science. At master’s degree, IPM is one of the optional research subjects (personal communication). Generally, there is not a common understanding of IPM among training institutes at different levels due to misconceptions reflected in some of the curricula. Lack of policy direction with regard to IPM research and training is a limitation in integrating IPM training in academic and research institutions. However, the aforementioned inclusion of IPM in the curricula at different levels of training and research institutions is an opportunity to capitalize on in capacity building and mainstreaming of IPM training. 8.3.6 SAGCOT to Support IPM Training and National Policy Since Farmer Field Schools have been embraced within the extension service as participatory approach of choice, in support of this, MAFC has designated four farmer training centres in the country (Mkindo– Morogoro; Bihawana- Dodoma; Inyala- Mbeya, and Ichenga- Iringa). The SAGCOT project could support by putting efforts to facilitate development of sustainable capacity to research and disseminate different options for testing/validation and adoption by farmers in the different agro ecological settings. In the FFS, farmers are very enthusiastic on the concept of biological control. They are good at scouting to identify the beneficial organisms but they may not tell why they are beneficial nor which pests the natural organisms Page 77 of 110 can control unless are given adequate trainings. In part this interest in biological control stems from their experience of various national biological control programs. The notable one is the classical biological control of cassava mealybug (Phenacoccus manihoti) by use of a wasp (Apoanagrus lopezi), an experience known by almost every Tanzania cassava farmer. Others include control of water hyacinth (Eichhorniae crassipes) using Neochetina bruchi and N. Eichhorniae and citrus woolly white fly using Encarsia haipiaensis. 8.4 SPECIFIC PEST MANAGEMENT MEASURES 8.4.1 Rules for Safe Handling of Pesticides All pesticides are poisonous and thus rules have to be observed to avoid human health impairment and environmental pollution. In addition to material safety data sheet (MSDS) accompanied with any given pesticide, the following general rules will have to be observed: Keep only closed original containers with labels. Keep pesticides under lock and key in a cool, dry and ventilated place away from fire, food, feed, water and out of reach of children. In the same room also the spraying equipment can be stored. Pesticides should be shelved and the floor be of cement to be able to detect leakage and clean it early enough where applicable. Equipment for weighing and mixing pesticides should only be used for this purpose and be locked in the store. Protective clothing should be used only for spraying purposes. Absorb spillage immediately with sawdust or earth; sweep up, burn or bury. Have cement floor for better cleaning. Do not re-use empty containers. Empty containers should be burnt if possible or crushed and bury in a sanitary landfill. Use a well aerated store and sales room. Instruct your personnel on safety precautions before (!) it is too late. Make contacts to a qualified physician for emergencies. In view of the above, the use of protective equipment and capacity building on pesticide management aspects, which would be the responsibility of the Matching Grant applicant/ recipient, will be critical. 8.4.2 Recommended Pesticides in Tanzania Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania3 Chemical Common name *Oral LD50/kg WHO class Comments Insecticides Betacyfluthrin 500-800 II Biphenthrin Chlorpyrifos 135-163 Ib Deregister & Phaseout Cypemethrin 251-4125 III Cypermethrin + Dimethoate 251-4125 + 2350 III 3 This table has been slightly updated. Important notice is that an extraordinary meeting of the National Plant Protection Advisory Committee (NPPAC), a body responsible for review of the pesticide list, took place in February 2014; the new list has been approved and the Pesticide Registrar’s Office is expected to publish the list before June 2014. Page 78 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Deltamethrin 153-5000 III Dealtamethrin + Dimethoate 153-5000+2350 III Diazinon 220 II Dimethoate 2350 III Esfenvalerate 451 II Fenitrothion 800 II Fenvalerate 451 II Fenvalerate + Fenitrothion 451+ 800 II Flucythrinate Hydrmethyl Lambda cyhalothrin 243 II Permethrin 430-4000 III Pirimiphos methyl 2050 III Pirimiphos methyl + permethrin 2050 + 430-4000 III Profenophos 358 II Profenophos + cypermethrin 358 + 251-4123 II Quinalphos 62-137 Ib Deregister & Phaseout Nematicides Dazomet 520 II Isazophos 40-60 Obsolete Deregister & Phaseout Herbicides Atrazine Diuron Fluometuron Glyphosate Metolachlor + Atrazine Metalachlor + Dipropetrin Paraquat Dirty Dozen: should be banned with immediate effect Chemical Common name *Oral LD50/kg WHO class Comments Avicides Fenthion II Cyanophos II Rodenticides Bromodiolone Ia Coumatetralyl Ia Diphacinone Ia Fungicides Bronopol Chlorothalonil 10,000+ III Copper hydroxide 1,000 II Copper oxychloride 70-800 II Cupric hydroxide 1,000 II Cuprous oxide Cyproconazole 1,000 II Hexaconazole 2189 III Mancozeb 5000+ III Metalaxyl + Mancozeb 633 + 5000+ III Page 79 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Penconazole Propineb 1,000 II Triadimefon 1,000 II Sulfur As expressed in the footnote 3 above, the above list is subject to review by relevant authorities in Tanzania. SAGCOT Investment Project will adhere to reviewed list(s) that will be released by such authorities any time during the implementation of the project. As part of monitoring and evaluation (Section 8.5), the project will also inform the authorities of pesticides required to be phased out for reported health concerns. 8.4.3 Pesticides Banned in Tanzania The following pesticides considered as persistent organic polluntants (POPs) are banned in Tanzania and will therefore not recommended for use by any investor under SAGCOT: Aldrin, Camphechlor; Chlordane; Ddt; Dibenzofurans (Chlorinated); Dieldrin; Endrin; Heptachlor; Hexachlorobenzene; Mirex; Polychlorinated Biphenyls; and Polychlorinated Dibenzo-P-Dioxins. On the other hand, the importation and use of chemicals indicated in the table below are Subject to the Prior Informed Consent (PIC) procedure in Tanzania. Table 8.2 List of pesticides whose use are subject to the Prior Informed Consent (PIC) procedure in Tanzania Chemical Category Registration Status in Tanzania Import Decision 2,4,5-T and its salts and esters Pesticide Not registered No consent Aldrin Pesticide Restricted registration for use in soil against termites Consent Binapacryl Pesticide Not registered No consent Captafol Pesticide Banned since 1986 No consent Chlordane Pesticide Restricted registration for use in soil against grubs, termites, ants and crickets Consent Chlordimeform Pesticide Not registered No consent Chlorobenzilate Pesticide Not registered No consent DDT Pesticide Banned for agricultural use, restricted for public health Consent for public health Dieldrin Pesticide Restricted registration for emergency cases in limited amount consent Dinitro-ortho-cresol (DNOC) and its salts (such as ammonium salt, potassium salt and sodium salt) Pesticide Not registered No consent Dinoseb and its salts and esters Pesticide Not registered No consent 1,2-dibromoethane(EDB) Pesticide Restricted registration for fumigation application on soil consent Ethylene dichloride Pesticide Not registered No consent Ethylene oxide Pesticide Not registered No consent Fluoroacetamide Pesticide Not registered No consent HCH (mixed isomers) Pesticide Not registered No consent Chemical Category Registration Status in Tanzania Import Decision Heptachlor Pesticide Registered for use in various crops against termites and other soil pests consent Hexachlorobenzene Pesticide Not Registered No consent Lindane Pesticide Registered hides and skins Consent Mercury compounds, including inorganic mercury compounds, alkyl mercury compounds and alkyloxyalkyl and aryl mercury compounds Pesticide Not Registered No consent Monocrotophos Pesticide Not registered No consent Page 80 of 110 Chemical Category Registration Status in Tanzania Import Decision Parathion Pesticide Banned in 1986 No consent Pentachlorophenol and its salts and esters Pesticide Not registered No consent Toxaphene Pesticide Banned in 1986 No consent Dustable powder formulations containing a combination of: - Benomyl at or above 7 per cent, - Carbofuran at or above 10 per cent,& - Thiram at or above 15 per cent Severely hazardous pesticide formulation Not registered No consent Monocrotophos (Soluble liquid formulations of the substance that exceed 600 g active ingredient/l) Severely hazardous pesticide Not registered No consent Methamidophos (Soluble liquid formulations of the substance that exceed 600 g active ingredient/l) Severely hazardous pesticide Not registered No consent Phosphamidon (Soluble liquid formulations of the substance that exceed 1000 g active ingredient/l) Severely hazardous pesticide Not registered No consent Methyl-parathion (emulsifiable concentrates (EC) at or above 19.5% active ingredient and dusts at or above 1.5% active ingredient) Severely hazardous pesticide Banned in 1986 No consent Parathion (all formulations – aero-sols, dustable powder (DP), emulsifiable concentrate (EC), granules (GR) and wettable powders (WP) - of this subs- tance are included, except capsule suspensions (CS)) Severely hazardous pesticide formulation Not registered No consent Source: Designated National Authority - Prio Informed Consent Procedure (DNA PIC) 8.5 MONITORING AND EVALUATION ARRANGEMENT Successful implementation of IPMP will require regular monitoring and evaluaton of activities undertaken by individual SAGCOT investors. It is also crucial to evaluate the prevailing trends in the benefits of reducing pesticide distribution, application and misues as well as the progress in national policy reform regarding IPM implementation and regulatory control on handling and use of pesticides. New situations on pesticides risks that arise during project implementation should also be monitored. The indicators that require regular monitoring and evaluation during the programme implementation include the following: The IPM capacity building SAGCOT investors; Numbers of investors who have adopted IPM practices as crop protection strategy in their crop production efforts; evaluate the rate of IPM adoption; How many investors have adopted IPM and improved the production derived from adopting IPM; Economic benefits: increase in crop productivity due to adoption of IPM practices; increase in revenue resulting from adoption of IPM practices, compared with conventional practices; Numbers of IPM networks operational and types of activities undertaken; Extent to which pesticides are used for crop production; Effeciency of pesticide use and handling and reduction in pesticide poisoning and environmental contamination; Levels of reduction of pesticide use and handling and reduction in pesticide poisoning and environmental contamination; Number of IPM participatory research project completed; Pesticide residues in groundwater or in surface water downstream from irrigation schemes; Pesticide residues in food (e.g.: crops, drinking water, fodder, livestock); Impact on non-target organisms (e.g.: beneficial insects, fish and other aquatic life, wildlife, non- target crops and plants through herbicide drift). Page 81 of 110 Influence of the results of IPM participatory research on implementation of IPM and crop production; and Overall assessment of activities that are on-going according to plans; activities that need improvement; and remedial actions required. The above indicators will have to be appropriately made part of Environmental and Social Management Plan (ESMP) and Environmental Monitoring Plan (EMP) for any individual category A or B subproject. The ESMP include monitoring measures, parameters to be measured, sampling methods to be used, sampling locations, analytical techniques to be used, frequency of measurements, recording of data, data analysis, and dissemination of information collected and decision reached. The ESMP and EMP will define thresholds that will signal the need for corrective actions. 8.6 WORKPLAN AND BUDGET The SAGCOT Centre will be responsible in the implementation of this IPMP and estimated costs for the various activities under this program will be build in the budget. Most funds would be provided by the Matching Grants applicants as part of their co-financing. The core activities will include capacity building, advisory services, environmental management, and project management. Annual workplan will be developed by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre in consultation with all key stakeholders. Approximately USD 1,375,000.00 will be required to effectively implement the IPMP over a five-year period (Table 8.3 below). Page 82 of 110 Table 8.3: Workplan and Budget for IPM implantation Line item Year 1 Year 2 Year 3 Year 4 Year 5 Total (USD) 1. Capacity Building 1.1 IPM orientation workshop for MGF recipients/ beneficieries 50,000 0 0 0 0 50,000 1.2 Annual workshops on progress and reviews are held by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre 0 30,000 30,000 30,000 30,000 120,000 1.3 Hiring of Project IPM Advisor responsible for capacity building, coordinanation, monitoring and evaluation 25,000 25,000 25,000 25,000 25,000 125,000 Sub-total 75,000 55,000 55,000 55,000 55,000 295,000 2. Advisory Services 2.1 IPM diagnostic baseline surveys are undertaken at the beginning of the Project 50,000 0 0 0 0 50,000 2.2 IPM technologies are developed (field guides/IPM materials) and made available for MGF applicants and recepients 10,000 10,000 10,000 10,000 10,000 50,000 2.3 Create and promote public awareness programes and advocacy 15,000 10,000 5,000 5,000 5,000 40,000 2.4 Undertaking regular pest/ vector surveillance 0 30,000 30,000 30,000 30,000 120,000 Sub-total 75,000 50,000 45,000 45,000 45,000 260,000 3. Environmental Management 3.1 Pesticides risk reduction through IPM implementation are integrated and streamlined into ESMPs and EMP of SAGCOT’s specific invetments 70,000 50,000 0 0 0 120,000 3.2 Support to IPM research and development in the project area 100,000 0 100,000 0 100,000 300,000 Sub-total 170,000 50,000 100,000 0 100,000 420,000 4. Project Management 4.1 IPMP implementation coordination 30,000 30,000 30,000 30,000 30,000 150,000 4.2 Monitoring and evaluation of IPMP implementation 50,000 50,000 50,000 50,000 50,000 250,000 Sub-total 80,000 80,000 80,000 80,000 80,000 400,000 Grand Total 400,000 235,000 280,000 180,000 280,000 1,375,000 Page 83 of 110 Workplan Notes 1. Capacity Building Notes 1.1 IPM orientation workshop for MGF recipients/ beneficieries This workshop is recommended to be done in the first year of project implementation. It could as well be scheduled to be done alongside all other safeguard tools (SRESA, ESMF and RPF) to all MGF recipients and other key stakeholders. 1.2 Annual workshops on progress and reviews are held by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre These will be workshops for disseminating progress made and challenges encountered in the implementation of IPM requirements. 1.3 Hiring of Project IPM Advisor responsible for capacity building, coordinanation, monitoring and evaluation Given the nature and the size of the project, and the expected magnitude of pesticide use in the entire project area, a local national IPM advisor is being proposed to coordinate all matters related to IPM. It should be noted that it could be appropriate to get an advisor who can cover for SRESA, ESMF and RPF but IPM needs an expert with specialized knowledge and skills. 2. Advisory Services 2.1 IPM diagnostic baseline surveys are undertaken at the beginning of the Project These surveys would give current baseline data in specific project areas which could also be included in EIA studies. 2.2 IPM technologies are developed (field guides/IPM materials) and made available for MGF applicants and recepients Field guides could be needed for some specific pesticides 2.3 Create and promote public awareness programs and advocacy The programs could be in form of TV and radio jingles, posters, and sensitization workshops. 2.4 Undertaking regular pest/ vector surveillance Field assessment and sample collection as monitoring/ control studies. 3. Environmental Management 3.1 Pesticides risk reduction through IPM implementation are integrated and streamlined into ESMPs and EMP of SAGCOT’s specific invetments Refer to activity 2.1 above 3.2 Support to IPM research and development in the project area SAGCOT centre could work with relevant research institutions such as Tanzania Pesticide Reserach Institute (TPRI) and Sokoine University of Agriculture (SUA) to undertake adaptation research and development in SAGCOT project area. 4. Project Management 4.1 IPMP implementation coordination Supervison and general coordination responsibilities. 4.2 Monitoring and evaluation of IPMP implementation For routine and ad hoc vfield visits for monitoring and evaluation missions. Page 84 of 110 9. RECOMMENDAITONS In order for the SAGCOT to ensure compliance with OP 4.09 and adopt ecologically-based IPM as the standard approach to pest management, the following are recommended: (i). Promote IPM by following the ways presented in this document; (ii). Establish ecologically-based IPM as a guiding principle for development at SAGCOT and realign relevant activities and strategies to support rather than undermine IPM and OP 4.09; (iii). Discourage conflicts of interest by screening out inappropriate SAGCOT partnerships that threaten to undermine IPM; (iv). Encourage effective collaboration across IPM projects, sectors and departments to support the integration of IPM and sustainable agriculture into SAGCOT; (v). Make better use of locally and regionally available knowledge and expertise in IPM and improve collaboration with farmers groups, NGOs, national and international institutions with expertise in participatory and environmentally sustainable approaches to agriculture; and (vi). A new/ reviewed list of approved pesticides is expected to be published before June 2014. This will have to be observed by the SAGCOT Invetsment Project management for adoption. 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Page 90 of 110 APPENDICES Appendix 1: Names of Experts Involved in Preparing This IPMP for SAGCOT Expert 1: Team Leader Expert 2 Expert 3 Kayonko Juma Kayonko, Registered Environmental Expert, (NEMC/EIA/0162 and NEMC /EA/0034), 10th FL, Mawasiliano Towers, 20 Sam Nujoma Road, P. O. Box 30, Dar es Salaam, Tanzania Mobile: (+255) 0787/ 0754 616 700 Email: kayonkoj@gmail.com Skype: juma.kayonko Gasana Damian Rwabufigiri. Officer In Charge PQPS Dar es salaam Port Field officer Outbreak pest control. Ministry of Agriculture Food Security and Cooperatives. Plant Health Services P. O. Box 9071, Dar es Salaam, Tanzania Mobile:+255784410184. +255762787336 E-mail gasanadamian@yahoo.com, damiangasana512@gmail.com Lazaro W. Kitandu, National IPM Coordinator, Ministry of Agriculture, Food Security and Cooperatives, Plant Health Services, P. O. Box 54802, Dar Es Salaam Phone: +255 22 286 5641/2 Cell: +255 754 673 154 Email: lazkitandu@hotmail.com Skype: lazaro.kitandu Appendix 2: Persons Consulted During the Preparation of IPMP for ASDP Ministry of Agriculture and Food Security Dr. George Sempeho, DED Mr. Chacha Nyakomari, ASDP Mr. Muro, PADEP Mr. Masija, SIIP Mr. Maro, FAO/Food Security Mr. S. Semgelewe, Planning Dr. L. Ngatunga, DED Ministry of Water and Livestock Development Mr. D. Shirima Principal Economics Planner Policy and Planning Division Dr. H. Mjengera Director Water Laboratories Unit Mr. J. Mihayo Director Water Resources Division Dr.. R. Mngodo Head Hydrology and Geographic Information Systems (GIS) Unit Water Resources Division Division of Environmental, Vice President Office Ms. Angelina Madate Assistant Director, Pollution Control Mr. Muungi Assistant Director, EIA National Environmental Management Council Ms. E.Kerario Director, EIA Mr. P. Kijazi Pollution Control Officer Agricultural Research Institute Ukiriguru Mr. Peter Kapingu ZDRD – Lake Mr. Robert Kileo Zonal Research Coordinator Ms. Epihania Temu Zonal Information Liaison Officer Musingwe District Council Mr. Michael Fundo District Agriculture and Livestock Officer Mr. Gerald Krange SMS Mechanization Mr. Kachrima Manager, Participatory Irrigation Development Project Page 91 of 110 Kwimba District Council Mr. Stephen M. Solo District Extension Officer Mr. John Enock Extension Officer Agricultural Research Institute Selian Director of Zonal Research NP Massawa - Zonal Research Coordinator A.K.Kissiwa - Zonal Extension Liaison Officer Roma Ngatoluwa - Head of Special Program Hussein Mansoor - Scientist Special Programme F.Ngulu - Phytopathologist S.Sluma - Entomologist Kitgenge - Breeder Matovo - Agronomist Mbaga - Entomologist Peter Xavery - Socio-economist/database management Phillemon Mushi - Computer Manager and NZARDI Website Manager Horti-Tengeru Research Institute Mr. Safamali Tengeru – Division of Plant Health Services Mwangi Jubilant - IPM – Technical Adviser (Northern Zone) M.S. Marawit - Plant Health Service Inspector K.K Mngara Post-Harvesting Management Coordinator Steven Mirau - Bird Control Unit Wilferd Mushobzi - Arm worms – National Control Center Coordinator Tanzania Pesticides Research Institute Charles J. Mkangirwa Director of Research Jonathan Ak’habuhaya Registrar of Pesticides Arusha Municipal Council Joseph Y. Mkwizu Coordinator- SCAPA Aremeru District Council District Planning Officer Mwihayo SMS - Irrigation Tanzania Coffee Research Institute Grace Chipangohelo Prinicipal Research Officer Msonjo Humphrey Temu Extension Agronomist Muheza District Council Manpower officer Planning officer Isipor Mweumpya DALDO Mzirya Agriculture Extension Officer Agriculture Research Institute Mlingano Dr. Adolf Nyaki Depute Director – Eastern Zone Ms. Catherine Senkoro Information Liaison Officer Joseph D.J. Mbogoni GIS Unit Shabani Hamisi Coordinator for Sisal Research Mrs Lady Swai Plant Pathologist Page 92 of 110 Agriculture Research Institute Ilonga Joseph Asenga – Breeder Sokoine University of Agriculture Professor Ludovick Kinabo - Project Coordinator TARP II – SUA Project Professor A.J.P Tarimo - Extension services and linkage specialist Professor LLL Lulandala - Agroforestery researcher Profesor Vicent Nsoloma - Coordinator – Mushroom research Dr. A. Massawe - Pest Management Centre Dr. L.S Mulungu - Pest Management Centre Professor K.P Sibuga - Project Coordinator - ICE Dr. Gaspar Ashimogo - Entrepreneurship and Agribusiness Manager – The Focal Programme Tabora District LGA Ms. R Elipenda - District Executive Director Uyui District Council Mr. F. Kashiridye - District Livestock Devt Office Uyui District Council Mr. M. Ndunguru - Plant Protection Office Uyui District Council Mr. T. Toziri - Livestock Ward Extension Officer Magiri Uyui District Council Mr. H. Ikandilo - Ward Executive Office Magiri Uyui District Council ZARDI Western Zone Dr.B. Mbaga Zonal Director – Tumbi Mr B. Gama Zonal Research Liason Coordinator Mr. R. Shenkalwa Head, Crop Sciences Mr. J. Chiligati Head Research Extension Officer Mr. M. Kusekwa Head Livestock Research Program Dr. D. Byamungu Ag. Head, Crop Research Program District staff Mr. L. Muliahela Ag. District Executive Director and District Agricultural & Livestock officer Mbeya (Rural) Mr. M. Mwandiga Ag. District Planning Offier Mbeya (Rural) Mr. M. Matambi IPM Specialist District Agr & Livestock Devt Mbeya (Rural) Page 93 of 110 Mr. G. Lihemula Land use Planner District Agr. & Livestock Office Mr. C. Mtono District Agr. & Livestock Office Mbeya (Rural) Ms. S. Msemwa District Agr. & Livestock Extension Office Mbeya (Rural) Southern Highlands Zone staff Dr. M Msabaha Zonal Director – Uyole Dr. R. Mbwile Ag. Zonal Research Coordinator and Head, Livestock Research Programme Dr. Z. Malley Head, Special Research Programme Mr. E. Kiranga Zonal Research Extension & Liason Officer Mr. C. Madata Head, Crop Research Program Ms. C. Kabungo Ag. Head, Socio-economic Unit Page 94 of 110 Appendix 3: An IPM Checklist for Planning and Implementing Pest Control on Crops I. Is Pest Control Necessary? A pest is an unwanted organism - animal, plant, bacteria, fungus or virus. What pest problem do you have? What collections are affected? ___________________________________ II. Will Your Pest Control Be Effective? What chemical or non-chemical treatment are you using? __________________________________ Is the problem persisting? __________________________________ Does the pest return? How often? __________________________________ Where is the pest problem? __________________________________ What is the original source of the pest? __________________________________ What does it like to eat? __________________________________ What is the pest's life cycle? __________________________________ What does it need to survive? (food, light, temperature, humidity, habitat) __________________________________ Integrated pest management uses biological and non-chemical methods to reduce and eliminate pest problems in the following steps: 1. Inspection (a) Pre-harvesting. Does the crop invite pests into the farm via the soil, other crops, wind, bad sanitation, etc. (b) Post-harvesting. Do storage facilities attract pests, or make the storage a better place for the pests to live? 2. Diagnosis & Reporting (a) Catch pest examples (do not squish); use sticky baited and/or unbaited traps. Lures might include pheromones or black (UV) lights. Page 95 of 110 Note: Some insects will not be attracted to baits or traps. (b) Collect examples of pest damage and waste. (c) Have an entomologist identify the pest. (d) Learn the pest's preferred diet, life cycle and habitat. (e) Record the location and date pests were found to determine what areas of the collection are infested. 3. Planning Integrated Pest Management Match the pest control treatment to the particular pest: to where it lives and what it eats, to the crop.. (a) Mechanical and physical control. These constitute the physical collection and subsequent destruction of pests. (b) Cultural control. These constitute sanitation and farm hygiene, selection of planting sites and selection of planting dates (avoids pest attack) and intercropping/strip cropping/ crop rotation, trapping/pseudostem and mulching/solarization (suppress pest population) (c) Use of pest resistant plants. This is genetically inherited ability of plant species to withstand or tolerate pests or diseases. Have you used pest resistant plants? (d) Biological control. These use natural occurring organisms to regulate pest population to acceptable levels. Will another organism solve the problem or combines with other control measures? (e) Chemical control. This is the use of pesticides to control pests. Try to avoid use of pesticides or try local treatment, specific to the habits of the pest. 4. Implementing Pest Management Plan (a) Inform everyone in the village, ward and districts why changes must be made and how they can change their habits. (b) Record what you have done, the date it was done, and where it was done. (c) Investigate any IPM method you plan to use: or pesticides use is it legal and the least invasive or least toxic method available? (d) Apply biological pest control methods properly. (e) Know what dosage (concentration) to use and in what form of botanic pesticides. (f) Know how long a treatment lasts at the temperature and relative humidity of your climate (g) Be certain that a pesticide will not affect vegetation or groundwater. Know how safe it is for humans. 5. Evaluate the Results (a) Monitor with sticky traps, baits, pheromone traps, or black light traps; document numbers, location, Page 96 of 110 and date. Check traps on a regular basis (every week or every month). (b) Survey a sample of the susceptible collection. For example, look in a different part of your farm every month to inspect different pests. III. How Toxic is a Pesticide to You? Toxic means poisonous. Types of toxicity include: (1) Acute poisoning is measured as LD50, meaning the lethal dosage for 50 percent of the animals tested. Sometimes it is measured as LC50 meaning the lethal dosage in the air for 50 percent of the animals tested. The lower the LD50 or the LC50, the more poisonous the pesticide. (2) Chronic poisoning affects an animal or human over a long period of time after small, repeated doses. There is no widely recognized measure of chronic toxicity. Poisons enter the body in three, measurable, ways: (1) Dermal toxicity refers to poison absorbed through the skin. Some areas of the body are more susceptible than others. (2) Oral toxicity refers to poison that is ingested. Pesticides on hands can be ingested while eating, drinking or smoking. (3) Inhalation refers to poisons breathed through your nose. Breathing the vapor of the pesticide can cause harm. A pesticide is a chemical or other agent that will destroy a pest or protect something from a pest. There are two types: (1) A residual pesticide destroys pests and keeps them from causing damage for long periods of time after it is applied. (2) A short-term pesticide breaks down almost immediately after application into nontoxic by- products. For example, a fumigant is a poisonous gas that kills when absorbed or inhaled. Most are highly toxic but have no residual effects. IV. Will Farmer Field School approach to IPM be useful? This approach should be promoted by ASSP and IPM Farmer Groups play key role in dissemination of ecological based pest management. Is IPM integrated into the Programme activities of each component and is it in compliance with OP 4.12? . Page 97 of 110 Appendix 4: Pesticide Classification List – WHO Table1: Extremely hazardous (Class 1a) technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Aldicarb Difethialone Parathion – methyl 1 Brodifacoum Diphacinone Phenylmercury acetate Bromadiolone Disulfoton Phorate Bromethalin Ethoprophos Phosphamidon Calcium cyanide Flocoumafen Sodium fluoroacetate Captafol Fonofos Sulfotep Chlorethoxyfos Hexachlorobenzene Tebupirimfos Chlormephos Mercuric chloride Terbufos Chlorophacinone Meviphos Difenacoum Parathion Table 2: Highly hazardous (Class 1b) technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Acrolein Ethionfencarb Omethoate Ally alcohol Famphur Oxamyl Azinphos – methyl Fenamiphos Oxydemeton-methyl Azinphos- methyl Flucythrinate Paris green (C) Blasticidin – S Fluoroacetamide Pentachlorophenol Butocarboxim Forrmetanate Pindone Butoxycarboxim Furathiocarb Pirimiphos-ethyl Cadusafos Heptenophos Propaphos Calcium arsenate Isazofos Propetamphos Carbofuran Isofenphos Sodium arsenate Chlorfenvinphos Isoxathion Sodium cyanide 3-chloro-1,2-propanediol Lead arsenate Strychnine Coumaphos Mecarban Tefluthrin Coumatetralyl Mercuric oxide Thallium sulfate Zeta-cypermethrin Methamidophos Thiometon Demeton-S-methyl Methidathion Thiometon Dichlorvos Methidocarb Triazophos Dicrotophos Methomyl Vamidothion Dinoterb Monocrotophos Warfarin Edinofenphos Nicotine Zinc phosphide Table 3: Moderately hazardous (Class II technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Alanycarb Endosulfan Paraguat Anilofos Endothal-sodium Pebulate Azaconazole Esfenvalerate Permethrin Azocyclotin Ethion Phenthoate Bendiocarb Etrimfos Phosalone Bensulide Fenitrothion Phoxin Bifenthrin Fenobucarb Piperophos Bilanafos Fepropidin Pirimicarb Bioallethrin Fenpropathrin Prallethrin Bromoxynil Fenthion Profenofos Brobuconazole Fentin acetate Propiconazole Page 98 of 110 Bronopol Fentin hydroxide Propoxur Butamifos Fenvalerate Prosulfocarb Butymine Fipronil Prothiofos Carbaryl Fluxofenim Pyraclofos Carbosulfan Formothion Pyrazophos Cartap Pyrethrnis Fuberidazole Chloralose Gamma-HCH Pyroquilon Cholordane Guazatine Quinalphos Chlofenapyr Haloxyfop Quizalofop-p-tefuryl Chlorphonium chloride Heptachlor Rotenone Chlorpyrifos Imazalil Sodium fluoride Clomazone Imidacloprid Sodium hexafluorosilicate Copper sulfate Iminoctadine Spriroxamine Cuprous oxide Ioxynil Sulprofos Cyanazine Ioxynil octanoate Terbumeton Cyanophos Isoprocarb Tetraconazole Cyfluthrin Lambda-cynalothrin Thiacloprid Beta-cyfluthrin Merchurous chloride Thiobencarb Cynalothrn Metaldehyde Thiocylam Cypermethrin Metam-sodium Thiodicarb Alpha-cypermethrin Methacrifos Triazamate Cyphermethrin Methasulfocarb Trichlorfon Deltamethrin Methyl isothiocyanate Tricyclazole Diazinon Metolcarb Tridemorph Difenzoquat Metribuzin Vernlate Dimethoate Molinate Xylylcarb Dinobuton Naban Diquat Naled Table 4: Slightly hazardous (Class III) technical grade active ingredients of pesticides (common name) – Permissible in the SAGCOT Investment Project under IPM Acephate Chlormequat (chloride) Dichlorbenzene Acetochlor Chloracetic acid Dichlorophen Acifluorfen Chlorthiamid Dichlorprop Alachlor Copper hydroxide Diclofop Allethrin Copper oxychloride Dienochlor Ametryn Cucloate Diethyltoluamide Amitryn Cyhexatin Difenoconazole Azamethiphos Cymoxanil Dimepiperate Bensultap Cyproconazole Dimetethachlor Bentazone Dazomet Dimethamethryn Bromofenoxim Desmethryn Dimethipin Butroxydim Dicamba Dimethylarsinic acid Chinomethionat Dichlormid Diniconazole Page 99 of 110 Table 5: Technical grade active ingredients of pesticides unlikely to present acute hazard in normal use (Common name) – Permissible in the SAGCOT Investment Project Acephate Mecoprop Bentazone Acetochlor Mecoprop-P Bromofenoxim Acifluorfen Mefluidide Butroxydim Alachlor Mepiquat Chinomethionat Allthrin Metalaxyl Chlormequat (chloride) Dinocap Metamitron Chloracetic acid Diphenamid Metconazole Chloracetiamid Dithianon Methylarsonic acid Copper hydroxide Dodine Metolachlor Copper oxychloride Emphenthrin Myclobutanil Nuarimole Esrocarb 2-Napthyloxyacetic acid Octhilinone Etridiazole Nitrapyrin N-octylbicycloheptene Fenothiocarb Ametryn Dicarboximide Ferimzone Amitraz Oxadixyl Fluazifop-p-butyl Azamethiphos Paclobutrazol Fluchloralin Bensultap Pendimethalin Flufenacet Mecoprop Pimaricin Fluoroglycofen Mecoprop-P Pirimiphos-methyl Flurprimidol Mefluidide Prochloraz Flusilazole Mepiquat Propachlor Flutriafol Metalaxyl Propanil Fomesafen Metamitron Propargite Furalaxyl Metchnazole Pyrazoxyfen Glufosinate Methylarsonic acid Pyridaben Hexazinone Metolachlor Pyridaphenthion Hydramethylnon Myclobutanil Pyridate Iprobenfos 2-Napthyloxyacetic acid Pyrifenox Isoprothiolane Nitrapyrin Quinoclamine Isoproturon Ametryn Quizalofop Isouron Amitraz Resmthrin Malathion Azamethiphos Sethoxydim MCPA – thioethyl Bensultap Simetryn Sodium Dithianon Nuarimole Dodine Octhilinone Sulfluramid Empenthrin N-octylbicycloheptene Tebuconazole Tebufenpyrad Esrocarb Dicarboximide Tebuthiuron Etridiazole Oxadixyl Thiram Fenothocarb Paclobutrazol Tralkoxydim Ferimzone Pendimethalin Triadimefon Fluazifop-p-butyl Pimaricin Triadimenol Fluchloralin Pirimiphos-methyl Tri-allate Flufenacet Prochloraz Triclopyr Fluoroglycofen Propachlor Triflumizole Flurprimidol Propanil Undecan-2-one Flusilazole Propargite Uniconazole Flutriafol Pyrazonxyfen Ziram Fomesafen Pyridaben Furalaxyl Pyridaphenthion Cycloate Glufosinate Pyridate Page 100 of 110 Cyhexatin Hexazinone Pyrifenox Cyproconazole Hydramethylnon Quinoclamine Cymoxanil Iprobenfos Quizalofop Dazomet Isoprothiolane Resmethrin Desmetryn Isoproturon Sethoxydim Dichlormid Isouron Simetryn Dichlorbenzene Malathion Sodium chlorate Dichlorophen MCPA-thioethyl Sulfluramid Dichlorprop Mecoprop Tebuconazole Diclofop Mecoprop-P Tebufenpyrad Dienochlor Mefluidide Tebuthiuron Diethyltoluamide Mepiquat Thiram Difenoconazole Metalaxyl Tralkoxydim Dimepiperate Metamitron Triadimefon Dimethachlor Metconazole Triadimenol Dimethamethryn Methylarsonic acid Tri-allate Dimethipin Metolachlor Triclopyr Dimethylarsinic acid Myclobutanil Triflumizole Diniconazole 2-Napthyloxyacetic acid Undecan-2-one Dinocap Nitrapyrin Uniconazole Diphenamid Ziram Table 6: Technical grade ingredients of pesticides unlikely to present acute hazard in normal use (common name) – Permissible in the SAGCOT Investment Project Aclonifen Chlorthal-dimethyl Fenhexamid Acrinathrin Chlozolinate Fenoxycarb Alloxydin Cinmethylin Fenpiclonil Amitrole Cinosulfuron Fenpropimorph Ammonium sulfamate Clofentezine Fenuron Ancymidol Clomeprop Fenuron-TCA Anthraquinone Clopyralid Ferbam Asulam Cloxyfonac Flamprop Atrazine Cryolite (c) Flucarbazone-sodium Azimsulfuron Cycloprothrin Flucycloxuron Azoxystrobine Cyclosulfamuron Flufenoxuron Benalaxyl Cycloxydim Flumetralin Benafluralin Cyhalofop Flumetsulam Benfuresate Cyromazine Fluometuron Benomyl Daimuron Flupropanate Benoxacor Dalapon Flupyrsulfuron Benuslfuron-methyl Daminozide Flurenol Bifenox Desmedipham Fluridone Bioresmethrin Diafenthiuron Flurochloridone Biphenyl Dichlobenil Fluroxypyr Bispyribac Dichlofluanid Fluthiacet Bitertanol Diclomezine Flutolanil Borax Dicloran Tau-fluvalinate Page 101 of 110 Bromacil Diclosulam Folpet Bromobutide Diethofencarb Fosamine Bromopropylate Diflubenzuron Fosetyl Bupirimate Diflufenican Gibberellic acid Buprofezin Dikeculac Glyphosate Butachlor Dimefuron Hexaconazole Butralin Dimethirimol Hexaflumuron Butylate Dimethomorph Hexythiazox Captan Dimethyl phtalate Hydroprene Carbendazim Dinitramine Hymexazol Carbetamid Dipropil isocinchomerate Imazamethabenzmethyl Carboxin Dithiopyr Imazapyr Carpropamid Diuron Imazaquin Chlomethoxyfen Dodemorph Imazethapyr Chloramben Ethalfluralin Imebenconazole Chloransulam methyl Ethefon Inabenfide Chlorbromuron Ethirimol Iprodione Chlorfluazuron Ethofumesate Iprovalicarb Chloridazon Etofenprox Isoxaben Chlorimuron Famoxadone Kasugamycin Chlorothalonil Fenarimol Lenacil Chlorotoluron Fenbutatin oxide Linuron Chlorpropham Fenchlorazole Maleic hydrazide Chlorpyrifos methyl Fenchlorim Mancozeb Chlorsulfuron Fenfuram Maneb Mefenacet Pentanochlor Rimsulfuron Mepanipyrim Phenmedipham Siduron Mepronil Phenothrin Simazine Metazachlor Phnylphenol Spinosad Methabenzthiazuron Phosphorus acid Sulfometuron Methoprene Phtalide Sulphur Methoxychlor Picloram Tebutam Methyldymron Piperonyl butoxide Tecnazene Metiram Pretilachlor Teflubenzuron Metobromuron Promisulfuron Temphos Metosulam Probenazole Terbacil Metoxuron Procymidone Terbuthylazine Metsulfuron methyl Prodiamine Terbutryn Monolinuron Prometon Tetrachlorvinphos 2-(1-Naphthyl) acetamide Prometryn Tetradifon 1-naphthylacetic acid Propamocarb Tetramethrin Napropamide Propaquizafop Thiabendazole Naptalam Propazine Thidiazuron Neburon Propham Thifensulfuron-methyl Niclosamide Propineb Thiophanate-methyl Nicosulfuron Propyzamide Thiocarbazil Nitrothal-isopropyl Pyrazolynate Tolclofos-methyl Norfluzaron Pyrazosulfuron Tolyfluanid Ofurace Pyrimethanil Transfluthrin Page 102 of 110 Oryzalin Pyriminobac Triasulfuron Oxadiazon Pyripoxyfen Tribenuron Oxine-copper Pyrithiobac sodium Trietazine Oxycarboxyn Quinclorac Triflumuron Oxyfluorfen Quinmerac Trifluralin Penconazole Quinoxyfen Trifulusulfuron-methyl Pencycuron Quintozene Triforine Triticonazole Validamycin Vinclozolin Zine Page 103 of 110 Appendix 5: SAGCOT Corridor and Clusters Note: International border shown for Lake Malawi is the median boundary: this is not accepted by all riparian states."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":167,"cells":{"data":{"kind":"string","value":"# Extracted Content CHAPTER 138 THE RUFIJI BASIN DEVELOPMENT AUTHORITY ACT [PRINCIPAL LEGISLATION] ARRANGEMENT OF SECTIONS Section Title PART I PRELIMINARY PROVISIONS 1. Short title. 2. Interpretation. PART II RUFIJI BASIN DEVELOPMENT AUTHORITY 3. Development Area. 4. Establishment of Authority. 5. Board of Directors. 6. Functions of the Authority. 7. President may give directions. PART III POWERS OF THE AUTHORITY 8. Powers in relation to generation of electricity. 9. President may transfer to Authority certain additional powers. PART IV ADMINISTRATION AND FINANCIAL PROVISIONS 10. Appointment of employees. 11. Remuneration and allowances of members of Board. 12. Superannuation benefits. 13. Agents and contractors. 14. Power of Board to delegate. 15. Funds and resources of the Authority. 16. Annual and supplementary budget. 17. Reserve and special funds. 18. Investment. 19. Power to borrow. 20. Accounts and audit. 21. Report by Board. PART V MISCELLANEOUS PROVISIONS 22. Liability of members. 23. By-laws. SCHEDULE CHAPTER 138 THE RUFIJI BASIN DEVELOPMENT AUTHORITY ACT An Act to establish Rufiji Basin Development Authority, to provide for the functions and powers of the Authority and for related matters. [1st July, 1975] [G.N. No. 146 of 1975] Act No. 5 of 1975 PART I PRELIMINARY PROVISIONS 1. Short title This Act may be cited as the Rufiji Basin Development Authority Act. 2. Interpretation In this Act, unless the context otherwise requires– \"Authority\" means the Rufiji Basin Development Authority established by section 4; \"Board\" means the Board of Directors of the Authority established under section 5; \"Development Area\" means the Rufiji Basin Development Area the boundaries of which are defined in accordance with the provisions of section 3; \"Minister\" means the Minister for the time being responsible for development planning; \"Rufiji River\" includes each and every tributary of that river. PART II RUFIJI BASIN DEVELOPMENT AUTHORITY 3. Development Area (1) For the purposes of this Act, the Rufiji Basin Development Area shall be an area of land through or along which the Rufiji River flows as and defined in accordance with the provisions of subsection (2). (2) The President may, by proclamation, define the boundaries of the Rufiji Basin Development Area and may, from time to time, by proclamation, vary the boundaries as so defined. 4. Establishment of Authority (1) There is hereby established an authority which shall be known as the Rufiji Basin Development Authority. (2) The Authority shall be a body corporate with perpetual succession and a common seal and shall be capable in law of suing and being sued in its corporate name, of purchasing, holding, alienating, managing and disposing of any property, whether movable or immovable and, whether by way of investment or otherwise, and capable of entering into any such contract as may be necessary or expedient for the performance of its functions under this Act or under any other written law. 5. Board of Directors (1) The management and functions of the Authority shall vest in a Board of Directors. (2) The provisions of the Schedule to this Act shall have effect as to the constitution and proceedings of, and otherwise in relation to, the Board of Directors. (3) The President may by order in the Gazette, amend, add to, vary or replace the Schedule to this Act. 6. Functions of the Authority The functions of the Authority shall be– (a) to generate electricity by means of hydro-electric works in the Development Area and to supply, on such terms and conditions as the Board may, subject to the provisions of this Act, approve, electricity so generated for the promotion of industries and the general welfare of the people of the United Republic; (b) to undertake measures for flood control; (c) to promote and regulate industrial activities within the Development Area; (d) to promote and regulate agricultural activities within the Development Area; (e) to promote and regulate the development of forestry within the Development Area and to take measures to ensure the prevention or minimisation of soil erosion; (f) to promote and regulate fishing industry in the rivers, lakes and dams within the Development Area; (g) to promote and regulate public inland water and road transport systems within the Development Area; (h) to promote tourism within the Development Area and to provide for or encourage the provision of facilities necessary or expedient for the promotion of tourism; (i) to do all such acts and things as, in the opinion of the Board may be necessary to uphold and support the credit of the Authority and to obtain and justify public confidence and, to avert and minimise any loss to the Authority; and (j) to do anything or enter into any transaction which, in the opinion of the Board, is calculated to facilitate the proper and efficient exercise by the Authority of its functions under this Act, including– (i) the carrying on of any of the activities of the Authority in collaboration with any other person; (ii) the acquisition by agreement, of interests in companies and firms engaged in activities in which the Authority may lawfully be engaged under this Act and the management of the affairs or the continuance of the business of such companies and firms; (iii) the establishment of branches within the United Republic and elsewhere. 7. President may give directions The President may give to the Authority directions of a general or specific character as to the exercise by the Authority, of any of its functions under this Act and the Authority shall give effect to every such direction. PART III POWERS OF THE AUTHORITY 8. Powers in relation to generation of electricity (1) For the purposes of performing its function of generating electricity by means of hydro- electric works in the Development Area, the Authority shall have power to construct, maintain, operate, protect, manage and control works– (a) for the collection, diversion and storage of water in the Development Area; (b) for the generation and transmission of electricity; and (c) incidental or related to the construction, maintenance, operation, protection, management or control, of any works specified in paragraph (a) or (b). (2) The Authority shall have power to construct, maintain, operate, protect, manage and control, works which, in the opinion of the Board, are necessary or desirable for the purpose of preventing or mitigating injurious effects of any works referred to in subsection (1). 9. President may transfer to Authority certain additional powers (1) Where the President is satisfied that for the proper and efficient performance by the Authority of any of its functions under this Act, it is necessary or desirable that the Authority enjoy, in relation to the Development Area, any power which is by any other written law, conferred upon any other person, whether generally or in relation to any specified area, whether or not such specified area includes the Development Area or any part of it, the President may, by order in the Gazette, provide that, subject to such limitations and restrictions as he may in such order specify, the Authority may exercise such power in relation to the Development Area as if such power, were, in relation to the Development Area, conferred upon the Authority by such other written law. (2) Where the President makes an order under subsection (1) conferring upon the Authority any power provided for in any other written law, he may, by the same or by any subsequent order, modify such other written law to such extent as he may deem necessary for the avoidance of any inconsistency or conflict between the provisions of such other written law and the provisions of the order made under subsection (1) or for providing for an appeal against the decision of the Authority in the exercise of such power or for any matter incidental to or connected with the exercise by the Authority of such power. (3) The provisions of any order made under subsection (2) shall have the same effect as if such provisions were made by and set out in this Act. PART IV ADMINISTRATION AND FINANCIAL PROVISIONS 10. Appointment of employees (1) The Board may from time to time appoint at such salaries and upon such terms and conditions as it may think fit, such officers and employees of the Authority as it may deem necessary for the proper and efficient conduct of the business and activities of the Authority. (2) The President shall appoint a Director-General of the Authority who shall be the chief executive officer of the Authority. 11. Remuneration and allowances of members of Board The members of the Board shall be entitled to receive such remuneration, allowances and other benefits as the Minister may direct. 12. Superannuation benefits The Board may– (a) grant gratuities or other retirement allowances or benefits to the officers and employees of the Authority; (b) establish and contribute to a superannuation fund and a medical benefits fund for the officers and employees of the Authority; (c) require any officer or employee of the Authority to contribute to any such superannuation fund or medical benefits fund and fix the amounts and method of payment of such contribution. 13. Agents and contractors The Board may, from time to time, appoint and employ upon such terms and conditions as it thinks fit, such agents and contractors of the Authority as the Board may deem necessary. 14. Power of Board to delegate (1) Subject to subsection (6), the Board may from time to time, in writing under the seal of the Authority delegate, subject to such terms, conditions or restrictions as it may specify, to any committee of the Board or to any officer or employee of the Authority, all or any of the functions, powers, authorities or duties conferred by or under this Act upon the Authority or upon the Board, and where any delegation is so made the delegated function, power, authority or duty may be performed or, as the case may be, exercised by the delegatee subject to the terms, conditions or restrictions specified in the writing. (2) Any delegation under subsection (1) may be made to the holder of an office under the Authority specifying the office but without naming the holder and in every case each successive holder of the office in question and each person who occupies or performs the duties of that office may, without any further authority, perform or, as the case may be, exercise the delegated function, power, authority or duty in accordance with the delegation made. (3) The Board may revoke a delegation made by it under this section. (4) No delegation made under this section shall prevent the Authority or the Board from itself performing or exercising the function, power, authority or duty delegated. (5) Any delegation made under this section may be published in the Gazette, and upon such publication shall be judicially noticed and shall be presumed to be in force unless the contrary is proved. (6) The Board shall not have power under this section to delegate– (a) its power of delegation; or (b) any power conferred upon the Authority or the Board by an order under section 9 except where such order expressly allows such delegation; (c) the power to approve the annual budget or any supplementary budget or receipts and expenditure, the annual balance sheet or any statement of account. 15. Funds and resources of the Authority The funds and resources of the Authority shall consist of– (a) such sums as may be provided for the purposes of the Authority by Parliament, either by way of grant or loan; (b) any loan or subsidy granted to the Authority by the Government or any other person; (c) any sum or property which may in any manner become vested in the Authority as a result of the performance by the Authority of any of its functions. 16. Annual and supplementary budget (1) In this Act \"financial year\" means any period not exceeding twelve consecutive months designated in that behalf by the Board: Provided that the first financial year after the commencement of this Act, shall commence on the date of the commencement of this Act and may be of a period longer or shorter than twelve months. (2) Not less than two months before the beginning of any financial year, other than the first financial year, the Board shall, at its meeting specially convened for that purpose, pass a detailed budget in this Act called the annual budget, of the amounts respectively– (a) expected to be received; and (b) expected to be disbursed, by the Authority during that financial year. (3) If in any financial year the Authority requires to make any disbursement not provided for or of an amount in excess of the amount provided for, in the annual budget for the year, the Board shall, at a meeting, pass a supplementary budget detailing such disbursement. (4) The annual budget and every supplementary budget shall be in such form and include such details as the Minister may direct. (5) Immediately upon the passing of any annual budget or any supplementary budget the Board shall submit the same to the Minister for approval. (6) The Minister shall, upon receipt of the annual budget or any supplementary budget, approve or disapprove the same or may approve subject to such amendment as he may deem fit. (7) Where the Minister has approved with or without amendment, any annual budget or supplementary budget, the budget, as approved by him, shall be binding on the Authority which, subject to the provisions of subsection (8), shall confine its disbursements within the items and the amounts contained in the applicable estimates as approved by the Minister. (8) The Board may– (a) with the sanction in writing of the Minister, make a disbursement notwithstanding that such disbursement is not provided for in any budget; (b) from the amount of expenditure provided for in any budget in respect of any item, transfer a sum not exceeding fifty thousand shillings to any other item contained in such budget; (c) adjust expenditure limits to take account of circumstances not reasonably foreseeable at the time the budget was prepared, subject to submitting a supplementary budget to the Minister within two months of such alteration of expenditure limits becoming necessary. 17. Reserve and special funds The Board may, and shall, if so directed by the Minister, establish and maintain such reserve or special funds of the Authority as the Board or the Minister may consider necessary or expedient and shall make into or from any such funds, such payments as the Board may deem fit or, in the case of a fund established pursuant to a direction by the Minister, as the Minister may direct. 18. Investment (1) With the prior approval of the Minister, the Board may, from time to time, invest any part of the moneys available in any fund of the Authority, in such manner as the Board may deem fit. (2) The Minister may, after consultation with the Minister for the time being responsible for Finance, give the Board directions as to the disposal of the Authority's surplus funds and the Board shall give effect to every such direction. 19. Power to borrow (1) With the prior approval of the Minister, the Board may, from time to time borrow moneys for the purposes of the Authority, by way of loan or overdraft and upon such security and such terms and conditions relating to the repayment of the principal and the payment of interest as, subject to any direction by the Minister, the Board may deem fit. (2) A person lending money to the Authority shall not be bound to enquire whether the borrowing of that money by the Authority has been approved by the Minister. 20. Accounts and audit (1) The Board shall cause to be provided and kept proper books of accounts and records with respect to– (a) the receipt and expenditure of moneys by, and other financial transactions of the Authority; (b) the assets and liabilities of the Authority, and shall cause to be made out for every financial year a balance sheet and a statement showing details of the income and expenditure of the Authority and all its assets and liabilities. (2) Not later than six months after the close of every financial year the accounts including the balance sheet of the Authority relating to that financial year, shall be audited by the Tanzania Audit Corporation established by the Tanzania Audit Corporation Act. (3) As soon as the accounts of the Authority have been audited, and in any case not later than six months after such audit, the Board shall submit to the Minister a copy of the audited statement of accounts together with a copy of the report made by the auditors. (4) As soon as practicable after receipt by him of the copy of the statement together with the copy of the report submitted pursuant to subsection (3), the Minister shall lay a copy of the statement together with a copy of the auditors' report before the National Assembly. 21. Report by Board The Board shall, within six months after the end of each financial year, make a report to the Minister on the conduct of the Authority's business during that financial year and the Minister shall lay a copy of such report before the National Assembly, together with a copy of the statement of accounts required by section 20, to be laid before the National Assembly. PART V MISCELLANEOUS PROVISIONS 22. Liability of members Without prejudice to the provisions of section 284A of the Penal Code or of the Public Officers (Recovery of Debts) Act, no act or thing done or omitted to be done, by any member of the Board or by any officer, employee or agent of the Authority shall, if done or omitted bona fide in the execution or purported execution of his duties as such member, officer, employee or agent, subject any such person to any action, liability or demand. 23. By-laws (1) The Authority may, with the consent of the Minister make by-laws– (a) providing for the protection of hydro-electric and other works within the Development Area; (b) prohibiting or regulating access to any part or parts of the Development Area by unauthorised persons; (c) regulating the use of waters from the Rufiji River, lakes and dams within the Development Area; (d) designed to minimising pollution of the waters of any river, lake or dam within the Development Area; (e) providing for the safety of persons employed in the construction, maintenance, operation, protection, management or control of hydro-electric and other works within the Development Area; (f) generally in relation to any matter or thing which in the opinion of the Board it is necessary, expedient or desirable to make by-laws in order to enable the Authority to perform its functions under this Act or to exercise any power conferred upon it by or under this Act, efficiently. (2) There may be annexed to the breach of any by-law made under this section a penalty not exceeding a fine of twenty thousand shillings or a term of imprisonment not exceeding three years or both. (3) Where by an order made under section 9 any power to make regulations under any other written law in relation to any matter provided for in such written law is conferred upon the Authority, the Authority may exercise such power by making by-laws in relation to such matter as if such matter were a matter in relation to which the Authority is empowered by subsection (1) to make by-laws, and unless a contrary intention is expressed in the order under section 9, the Authority may annex to the breach of any such by-law a penalties specified in subsection (2), notwithstanding that, but for the provisions of this subsection, the provisions of subsection (2) would not have applied in relation to the breach of such by-law. SCHEDULE (Section 5(2)) 1. Constitution (1) The Board shall consist of the following members– (a) a Chairman appointed by the President; (b) the Director-General; (c) not less than eight and not more than ten other members appointed by the President. (2) The members of the Board shall, from among their number, elect a Vice-Chairman, who shall hold office for so long as he remains a member of the Board. (3) A member of the Board shall, unless his appointment is sooner determined by the Presidents or he otherwise ceases to be a member, hold office for such period as the President may specify in his appointment or if no period is so specified, for a period of three years from the date of appointment and shall be eligible for reappointment: Provided that a member who is a member by virtue of holding some other office, shall cease to be a member upon ceasing to hold that office. (4) Any member of the Board may at any time resign by giving notice in writing to the Permanent Secretary to the President's Office and from the date specified by the notice or, if no date is specified, from the date of the receipt of the notice by the Permanent Secretary, shall cease to be a member. 2. Secretary The Board may appoint any member of the Board or officer of the Authority or a public officer to be the Secretary of the Board. 3. Casual vacancies Where any member ceases to be a member for any reason before the expiration of the term of office, the President shall appoint another person and the person so appointed shall hold office for the remainder of the term of office of the predecessor. 4. Meetings (1) An ordinary meeting of the Board shall be convened by the Chairman and the notice specifying the place, date and time of the meeting shall be sent to each member at his usual place of business or residence not less than fourteen days before the date of such meeting and in case the Chairman is unable to act by reason of illness, absence from the United Republic or other sufficient cause, the Vice-Chairman may convene such meeting. (2) The Chairman or in his absence, the Vice-Chairman shall be bound to convene a special meeting of the Board upon receipt of a request in writing in that behalf signed by not less than five members of the Board: Provided that not less than fourteen days' notice of such meeting shall be given to all members of the Board in the manner prescribed in subparagraph (1). (3) The Chairman, the Vice-Chairman, or a temporary Chairman elected in accordance with the provisions of subparagraph (2) of paragraph 5 presiding at any meeting of the Board may invite any person who is not a member to participate in the deliberations of the Board, but any such person shall not be entitled to vote. 5. Procedure (1) One-half of the total number of the members of the Board or five members, whichever is the lesser number, shall form a quorum for a meeting of the Board. (2) In the absence of the Chairman from a meeting of the Board, the Vice-Chairman shall preside and in the absence of both the Chairman and the Vice-Chairman, the members present shall elect one of their number to be a temporary Chairman of that meeting. (3) At any meeting of the Board a decision of the majority of the members present and voting shall be deemed to be a decision of the Board and. In the event of an equality of votes, the Chairman of the meeting shall have a casting vote in addition to the deliberative vote. 6. Decision by circulation of papers Notwithstanding the provisions of paragraph 5, where the Chairman so directs, a decision may be made by the Board without a meeting by circulation of the relevant papers among all the members and the expression in writing of their views, but any member shall be entitled to require that any such decision is deferred until the subject matter shall be considered at a meeting of the Board. 7. Minutes of meetings Minutes of each meeting of the Board shall be kept and shall be confirmed by the Board at the next meeting and signed by the Chairman of the meeting. 8. The seal of Authority The seal of the Authority shall not be affixed to any instrument except in the presence of the Director-General or of the Secretary and one member of the Board. 9. Vacancies not to invalidate proceedings Subject to the provisions of paragraph 5 relating to quorum, the Board may act notwithstanding any vacancy in the membership and no act or proceeding of the Board shall be invalid by reason only of some defect in the appointment of a person who purports to be a member. 10. Signing of documents All orders, by-laws, regulations, directions, notices or documents made or issued by the Authority or by the Board shall be signed by– (a) the Director-General; or (b) any member of the Board or other officer of the Authority authorised in writing by the Director-General in that behalf. 11. Board may regulate its own proceedings Subject to the provisions of this Schedule, the Board shall have power to regulate its own proceedings."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":168,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vo: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vi: REGIONAL REPORT: RUKWA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary......................................................................................................................................................... vi Illustrations..................................................................................................................................................................... xii CENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ....................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area .......................................................................................................................................................... 1 1.4 Climate............................................................................................................................................................... 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population.......................................................................................................................................................... 1 1.6 Socio-economic Indicators................................................................................................................................ 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture.................................................... 3 2.2 Census Objectives ............................................................................................................................................. 3 2.3 Census Coverage and Scope ............................................................................................................................. 4 2.4 Legal Authority of the National Sample Census of Agriculture...................................................................... 5 2.5 Reference Period ............................................................................................................................................... 5 2.6 Census Methodology......................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Holding Characteristics................................................................................................................................ 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Literacy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 23 3.3.4.3 Other Cereals.................................................................................................................. 26 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava........................................................................................................................... 27 3.3.5.2 Irish Potatoes .................................................................................................................. 28 3.3.6 Pulse Crops Production .................................................................................................................... 28 3.3.6.1 Beans............................................................................................................................... 30 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts ..................................................................................................................... 32 3.3.8 Fruits and Vegetables ........................................................................................................................ 33 3.3.8.1 Tomatoes ........................................................................................................................ 35 3.3.8.2 Cabbage .......................................................................................................................... 37 3.3.8.3 Chillies............................................................................................................................ 37 3.3.9 Other Annual Crops Production....................................................................................................... 40 3.3.9.1 Cotton .............................................................................................................................. 40 3.3.9.2 Tobacco .......................................................................................................................... 40 3.4 Permanent Crops........................................................................................................................................... 40 3.4.1 Coconuts ........................................................................................................................................ 43 3.4.2 Oranges ........................................................................................................................................ 45 3.4.3 Banana ........................................................................................................................................ 45 3.4.4 Cashew Nuts ..................................................................................................................................... 45 3.5 Inputs/Implements Use................................................................................................................................. 48 3.5.1 Methods of land clearing................................................................................................................... 48 3.5.2 Methods of soil preparation.............................................................................................................. 48 3.5.3 Improved seeds use........................................................................................................................... 50 3.5.4 Fertilizers use.................................................................................................................................... 51 3.5.4.1 Farm Yard Manure Use.................................................................................................. 51 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 52 3.5.4.3 Compost Use .................................................................................................................. 53 3.5.5 Pesticide Use..................................................................................................................................... 54 3.5.5.1 Insecticide Use................................................................................................................ 54 3.5.5.2 Herbicide Use................................................................................................................. 55 3.5.5.3 Fungicide Use................................................................................................................. 55 3.5.6 Harvesting Methods.......................................................................................................................... 56 3.5.7 Threshing Methods .......................................................................................................................... 56 3.6 Irrigation .................................................................................................................................................... 56 3.6.1 Area planted with annual crops and under irrigation....................................................................... 56 3.6.2 Sources of water used for irrigation................................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................................ 59 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iii 3.6.4 Methods of water application .......................................................................................................... 59 3.7 Crop Storage, Processing and Marketing .................................................................................................. 59 3.7.1 Crop Storage ..................................................................................................................................... 59 3.7.1.1 Method of Storage.......................................................................................................... 60 3.7.1.2 Duration of Storage ........................................................................................................ 60 3.7.1.3 Purpose of Storage.......................................................................................................... 61 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 61 3.7.2 Agro processing and by-products...................................................................................................... 62 3.7.2.1 Processing Methods........................................................................................................ 62 3.7.2.2 Main Agro-processing Products..................................................................................... 62 3.7.2.3 Main use of primary processed Products....................................................................... 63 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 63 3.7.3 Crop Marketing................................................................................................................................. 64 3.7.3.1 Main Marketing Problems.............................................................................................. 64 3.7.3.2 Reasons for Not Selling.................................................................................................. 64 3.8 Access to Crop Production Services............................................................................................................ 65 3.8.1 Access to Agricultural Credits ......................................................................................................... 65 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits............................................................................................ 65 3.8.1.3 Reasons for not using agricultural credits...................................................................... 66 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of crop extension messages.............................................................................. 66 3.8.2.2 Quality of extension ....................................................................................................... 68 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.2 Inorganic Fertilisers .......................................................................................................................... 68 3.9.3 Improved Seeds ................................................................................................................................. 69 3.9.4 Insecticides and Fungicide ................................................................................................................ 69 3.10 Tree Planting................................................................................................................................................... 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population....................................................................................................................... 73 3.12.1.2 Herd size......................................................................................................................... 73 3.12.1.3 Cattle Population Trend ................................................................................................. 75 3.12.1.4 Improved Cattle Breeds.................................................................................................. 75 3.12.2 Goat Production................................................................................................................................ 75 3.12.2.1 Goat Population.............................................................................................................. 75 3.12.2.2 Goat Herd Size ............................................................................................................... 77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 79 3.12.4 Pig Production .................................................................................................................................. 79 3.12.4.1 Pig Population Trend...................................................................................................... 79 TOC __________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iv 3.12.5 Chicken Production .......................................................................................................................... 81 3.12.5.1 Chicken Population ........................................................................................................ 81 3.12.5.2 Chicken Population Trend.............................................................................................. 81 3.12.5.3 Chicken Flock Size......................................................................................................... 81 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 82 3.12.6 Other Livestock ................................................................................................................................ 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming..................................................................................................................... 82 3.12.8 Access to Livestock Services ........................................................................................................... 84 3.12.8.1 Access to livestock extension Services.......................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to village watering points/dam .......................................................................... 85 3.12.9 Animal Contribution to Crop Production......................................................................................... 85 3.12.9.1 Use of Draft Power......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 86 3.12.9.4 Use of Compost ............................................................................................................ 86 3.12.10 Fish Farming..................................................................................................................................... 86 3.6.0 Access to Infrastructure and Other Services.................................................................................... 89 3.13 Poverty Indicators......................................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services.................................................................................... 89 3.13.2 Type of Toilets.................................................................................................................................. 90 3.13.3 Household’s assets............................................................................................................................ 90 3.13.4 Sources of Light Energy................................................................................................................... 90 3.13.5 Sources of Energy for Cooking........................................................................................................ 90 3.13.6 Roofing Materials............................................................................................................................. 91 3.13.7 Access to Drink Water...................................................................................................................... 91 3.13.8 Food Consumption Pattern............................................................................................................... 92 3.13.8.1 Number of Meals per Day.............................................................................................. 92 3.13.8.2 Meat Consumption Frequencies..................................................................................... 92 3.13.8.3 Fish Consumption Frequencies...................................................................................... 92 3.13.9 Food Security.................................................................................................................................... 92 3.13.10 Main Source of Cash Income........................................................................................................... 93 PART IV: RUKWA PROFILES................................................................................................................................ 95 4.1 Region Profile ................................................................................................................................................. 96 4.2 District Profiles............................................................................................................................................... 96 4.2.1 Mpanda .............................................................................................................................................. 96 4.2.2. Sumbawanga Rural............................................................................................................................ 98 4.2.3 Nkasi ................................................................................................................................................100 4.2.4 Sumbawanga Urban.........................................................................................................................102 ACRONYMS __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Rukwa region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Rukwa region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Rukwa region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Rukwa region were 172,261 out of which 114,069 (67.3%) were involved in growing crops only, 416 (0.2%) rearing livestock only and 57,776 (33.5%) were involved in crop production as well as livestock. However, there was no pastoralist which was found in the region. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off-farm income, livestock keeping/herding, permanent crops remittances and fishing/hunting and gathering. The region has a literacy rate of 72 percent. The highest literacy rate was found in Sumbawanga Rural and Sumbawanga Urban districts with (75%) followed by Nkasi district (71%) and Mpanda district (70%). The number of heads of agricultural households with formal education in Rukwa region was 118,763 (67%), those without formal education were 53,498 (31%) and those with only adult education were 6,019 (4%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Rukwa region 59,888 household members (35%) were involved in one off-farm income generating activity, 53,457 (31%) involved in two off-farm income generating activities and 18,456 (11%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 574,291 ha. The regional average land area utilised for crop production per crop growing household was only 2.4 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 303,393 hectares out of which 1,049 hectares (0.3%) were planted during short rainy season and 302,345 hectares (99.7%) during long rainy season. An estimated area of 203,500 ha (67.3% of the total planted area with annual and vegetable crops) was with cereals, followed by 77,017 hectares (18.0%) of pulses, (37,551 hectares, 12.4%), of roots and tubers, (28,595 hectares, 9.5%), oil seeds (28,178 hectares, 9.3%), cash crops (3,295 hectares (1.1%) and fruits and vegetables, (1,225 hectares (0.4%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii Cereal Crop Production The total production of cereals was 240,623 tonnes from a total planted area of 203,928 hectares. These cereal crops include: Maize, Paddy, Finger Millet, Sorghum, Wheat and Bulrush Millet Maize Maize is the dominant annual crop grown in Rukwa region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 73.6 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) are paddy, finger millet, sorghum, wheat, bulrush millets. Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Rukwa region during the long rainy season was 30,132. This represented 17.6 percent of the total crop growing households in Rukwa Region in the long rainy season. • Roots and Tuber Crops Production The total production of roots and tubers crops was 45,702 tonnes from planted area of 28,594 hectares. These root and tuber crops included: cassava, sweet potatoes, irish potatoes, yams and cocoyam. Cassava The area planted with cassava was larger than any other root and tuber crop in Rukwa in terms of planted area (8.3% of the total area planted with annual crops and vegetables) and it accounted for 87 percent of the area planted with roots and tubers. Oil Seed Production The total production of oilseed crops was 17,419 tonnes planted on an area of 28,520 hectares. These oil crops included groundnuts, sunflowers, soya beans and simsim. Pulse Crops Production The total area planted with pulses was 37,831 hectares. This area was planted with beans, bambaranuts, green grams, cowpeas and field peas. Fruit and Vegetables The total production of fruit and vegetables was 4,211 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 2,136 tonnes, which amounts to 48 percent of the total fruit and vegetable production, followed by cabbage 3,472 tonnes (18%) and chilies 1,973 tonnes (10%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 62,403 hectares which is 13 percent of the area planted with annual crops in the region. The most important permanent crop is coconuts which accounts for 24 percent of the total area planted with permanent crops followed by oranges (15%), banana (13%) and cashew (13%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Improved Seeds The planted area using improved seeds was 52,089 ha which represents 13 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was 13.4 percent which is slightly higher than the corresponding percentage use for the long rainy season (12.73%). Use of Fertilizers Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 367,237 hectares representing 85.6 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 45,411 ha which represented 10.6 percent of the total planted area (73.3 % of the area planted with fertiliser application). This was followed by compost (12,491 ha, 20.1%). Inorganic fertilizers were used on a very small area and represented only 6.6 percent of the area planted with fertilizers. Irrigation In Rukwa region, the area of annual crops and vegetables under irrigation was 41,089 ha representing 9.6 percent of the total area planted. The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 12.3 percent compared with 5 percent in the short rainy season. Crop Storage There were 228,187 crop growing households (87% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and pulses (104,155 households and 1,914 tonnes), paddy (14,828 households and 827 tonnes) and groundnuts and bambara nuts (1,674 households and 54 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 197,168 which represents 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Rukwa (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%). Agricultural Credit In Rukwa region, few agricultural households (1,022, 0.4%) accessed credit, out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got credit for agriculture purposes, whereas in Korogwe, Rukwa and Handeni districts only male households accessed credit. In Muheza district both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.96). Korogwe district had a relatively high proportion of households that received crop extension messages (84%), followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Rukwa (14%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 30,288. This number represents 11 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Lushoto District (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Rukwa (1%) Pangani (0.5%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 378,338. Cattle rearing is the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 350,210 head (92.6% of the total number of cattle in the region), 27,829 (7%) were dairy breeds and only 298 (1.4%) were beef breeds. Goats The number of goat-rearing-households in the region was 68,764 (26% of all agricultural households) with a total of 514,620 goats giving an average of 7 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 35,381 (13% of all agricultural households) with a total of 164,209 sheep giving an average of 5 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 176,806, raising 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Rukwa ranked eighth out of the 21 Mainland regions. Use of Draft Power The region has 738 oxen and they were only found in two districts, Korogwe and Kilindi with 592 and 146 head respectively. Rukwa region has 0.03 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 2,653 hectares of land. Fish Farming The number of households involved in fish farming was 1,423 (0.5 percent of the total agricultural households in the region). Korogwe was the leading district with 634 agricultural households involved in fish farming (1.4%) followed by Lushoto 430 (0.5%), Muheza 336 (0.7%) and Rukwa 23 (0.3%). Fish farming was not practiced in Pangani and Handeni districts. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x iv) Poverty Indicators Availability of Toilets It was estimated that 86.5 percent of all rural agricultural households used the traditional pit latrines, 1.8 percent used improved pit latrine and 0.7 percent had flush toilets. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 11 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (61.3% of households) followed by bicycle (32.1%), iron (18.9%), wheelbarrow (3.4%), mobile phone (1.9%), television/video (1.0%), vehicle (0.9%) and landline phone (0.5%). Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. About 77 percent of the total rural households used this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), parrafin/kerosene (0.03%) and gas/biogas (0.01%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households however, this was closely followed by iron sheets (43.6%). Other roofing materials are grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%). Number of Meals per Day About 72.3 percent of the holders in the region took three meals per day, 25.2 percent took two meals, 2.4 percent took one meal and 0.1 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 42 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 8.3 percent whereas those with little problems represent 7.6 percent. About 7 percent of agriculture households always faced food shortages whilst 35 percent had not experienced any food shortage problems. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 25.5 percent of all rural agricultural households. The second main cash income earning activity was casual labour (20.9%) followed by selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Other income earning activities were employment (5.0%), sale of livestock (4.0%), sale of forest products (2.5%), sale of livestock products (1.7%) and fishing (0.9%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ............................................................................................................................................ 10 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 22 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 25 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop....................................... 27 3.4 Area, Quantity Harvested and Yield of Pulses by Season ..................................................................................30 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 37 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 37 3.8 Land Clearing Methods....................................................................................................................................... 43 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season...................................... 56 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ............................................... 61 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 61 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 64 3.15 Total Number of Households and Chickens Raised by Flock Size ....................................................................77 3.16 Head Number of Other Livestock by Type of Livestock and District............................................................... 80 3.17 Mean distances from holders dwellings to infrastructure and services by districts .......................................... 88 3.18 Number of Households by Number of meals the Household normally has per Day and District .................... 93 List of Charts 3.1 Agricultural Households by Type of Holdings....................................................................................................10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head..............................................11 3.3 Percentage Distribution of Population by Age and Sex in 2003.........................................................................11 3.4 Percentage Literacy Level of Household Members by District..........................................................................11 3.5 Literacy Rates for Heads of Household by Sex and District...............................................................................15 3.6 Percentage of Persons Aged 5 years and above by District and Educational Status..........................................15 3.7 Percentage of Persons Aged 5 years and Above in Agricultural Households by Education Status .................15 3.8 Percentage Distribution of Heads of Household by Educational Attainment ....................................................15 3.9 Number of Household by Number of Members with Off-Farm Income – Rukwa Region ...............................16 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities..................................16 3.11 Utilized and Usable Land per Household by District..........................................................................................17 3.12 Land Area by Type of Land Use..........................................................................................................................17 3.13 Area Planted (ha) with Annual Crops by Season................................................................................................17 3.14 Area Planted with Annual Crops by Season and District....................................................................................18 3.15 Area Planted with Annual Crops per Household by Season and District...........................................................18 3.16 Planted Area (ha) for the Main Annual Crops.....................................................................................................21 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type......................................................21 3.18 Area planted with Annual Crops by Type of Crops and Season.........................................................................21 3.19 Area Planted and Yield of Major Cereal Crops...................................................................................................21 3.20 Time Series Data on Maize Production – Rukwa Region...................................................................................22 3.21 Maize: Total Area Planted and Planted Area per Household by District ...........................................................22 3.22 Time Series of Maize Planted Area and Yield – Rukwa Region........................................................................22 3.23 Total Planted Area and Area of Paddy per Household by District .....................................................................23 3.24 Time Series Data on Paddy Production – Rukwa Region...................................................................................23 3.25 Time Series of Paddy Planted Area and Yield – Rukwa Region........................................................................23 3.26 Area Planted With Sorghum, Finger Millet, Bulrush Millet and Wheat by District..........................................25 3.27 Area Planted and Yield of Major Root and Tuber Crops....................................................................................25 3.28 Area planted with Cassava during the Census/Survey Years .............................................................................25 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................27 3.30 Cassava Planted Area per Cassava Growing Households by District ................................................................27 3.31 Sweet Potatoes: Total area and Planted Area per Household by District...........................................................27 3.32 Area Planted and Yield of Major Pulse Crops ....................................................................................................28 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District .............................................28 3.34 Area Planted per Bean Growing Household by District (Wet Season) ..............................................................28 3.35 Time Series Data on Beans Production – Rukwa Region.................................................................................. 28 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiii 3.36 Time Series of Beans Planted Area and Yield - Rukwa......................................................................................28 3.37 Area Planted and Yield of Major Oil Seed Crops...............................................................................................30 3.38 Time Series Data on Groundnut production – Rukwa Region ...........................................................................30 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District .........................30 3.40 Area Planted per Groundnut Growing Household by District (Wet Season).....................................................31 3.42 Area Planted and Yield of Fruit and Vegetables.................................................................................................31 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ......................................34 3.44 Area Planted per Tomato Growing Household by District (Wet Season ).........................................................34 3.45 Percent of Onions Planted Area and Percent of Total Land with Cabbage by District......................................34 3.46 Percent of Cabbage Planted Area and Percent of Total Land with Chillies by District.....................................34 3.47 Area planted with Annual Cash Crops ................................................................................................................37 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................37 3.49 Area Planted for Annual and Permanent Crops...................................................................................................37 3.50 Area Planted with the Main Perennial Crops ......................................................................................................38 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District ...................................38 3.52 Percent of Area Planted with Lime/Lemon and Average Planted Area per Household by District ..................38 3.53 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District.......................54 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District ...........................54 3.55 Percent of Area Planted with Mangoes and Average Planted Area per Household by District.........................43 3.56 Number of Households by Method of Land Clearing During the Wet Season..................................................43 3.57 Area Cultivated by Cultivation Method...............................................................................................................44 3.58 Area Cultivated by Method of Cultivation and District......................................................................................44 3.59 Planted Area with Improved Seed by Crop Type................................................................................................44 3.60 Planted Area with Improved Seed by Crop Type................................................................................................44 3.61 Percentage of Crop Type by planted Area with Improved Seeds- Annuals .......................................................45 3.62 Area of Fertilizer Application by Type of Fertilizer and District.......................................................................46 3.63 Area of fertilizer Application by Type of Fertiliser and District ........................................................................46 3.64 Planted Area with Farm Yard Manure by Crop type .........................................................................................46 3.65a Percentage of Planted Area with Farm Yard Manure by Crop Type................................................................46 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District .........................................................46 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals.........................................................................47 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type..................................................................47 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District..........................................................47 3.68a Planted Area with Compost by Crop Type......................................................................................................... 47 3.68b Percentage of Planted Area with Compost by Crop Type ..................................................................................49 3.68c Proportion of Planted Area Applied with Compost by District..........................................................................49 3.69 Planted area (ha) by Pesticide Use.......................................................................................................................49 3.70 Planted Area applied with Insecticides by Crop Type ........................................................................................50 3.71 Percentage of Crop Type Planted Area applied with Insecticides......................................................................50 3.72 Proportion of Planted Area applied with Insecticides by District.......................................................................50 3.73 Planted Area applied with Herbicides by Crop Type..........................................................................................50 3.74 Percentage of Crop Type Planted Area Applied with Herbicides.......................................................................51 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season......................51 3.76 Planted Area applied with Fungicides by Crop Type..........................................................................................51 3.77 Percentage of Crop Type Planted Area Applied with Fungicides ......................................................................51 3.78 Proportion of Planted Area Applied with Fungicides by District.......................................................................52 3.79 Area of Irrigated Land..........................................................................................................................................52 3.80 Planted Area Irrigation by District.......................................................................................................................52 3.81 Time Series of Households with Irrigation Practices – Rukwa ..........................................................................53 8.82 Number of Households with Irrigation by Source of Water...............................................................................53 3.83 Number of Households by Method of Obtaining Irrigation Water.....................................................................53 3.84 Number of Households with Irrigation by Method of Field Application...........................................................54 3.85 Number of Households and Quantity Stored by Crop Type...............................................................................54 3.86 Number of Households by Storage Methods.......................................................................................................55 3.87 Number of Households by Method of Storage and District (Based on the Mo.st important Household Crop) 55 3.88 Normal Length of Storage for Selected Crops ....................................................................................................55 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ...................................................55 3.90 Number of Households by Purpose of Storage and Crop Type..........................................................................56 3.91a Households Processing Crops..............................................................................................................................58 3.91b Percent of Households Processing Crops by District..........................................................................................58 3.92 Percent of Crop Processing Households by Method of Processing....................................................................58 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiv 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 58 3.94 Number of Households by Type of By-product..................................................................................................59 3.95 Use of Processed Product.....................................................................................................................................59 3.96 Percentage of Households Selling Processed Crops by District.........................................................................59 3.97 Location of Sale of Processed Products...............................................................................................................59 3.98 Percentage of Households Selling Processed Products by Outlet for sale and District .....................................60 3.99 Number of Crop Growing Households that Selling Crops by District ...............................................................60 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ....................60 3.101 Percentage Distribution of Households that Received Credit by Main Sources ................................................62 3.102 Number of Households Receiving Credit by Main Source of Credit and District .............................................62 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit .....................................................62 3.104 Reasons for Not using Credit (% of Households) ...............................................................................................62 3.105 Number of Households Receiving Extension Advice.........................................................................................63 3.106 Number of Households that Received Extension by District..............................................................................63 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider..................................63 3.108 Number of Households Receiving Extension by Reported Quality of Services ................................................63 3.109 Number of Households by Source of Inorganic Fertiliser ..................................................................................64 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser...................................................66 3.111 Number of Households by Source of Improved Seed.........................................................................................66 3.112 Number of Households reporting Distance to Improved Seed ...........................................................................66 3.113 Number of Households by Source of Insecticide/Fungicide...............................................................................67 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides............................................67 3.115 Number of Households with Planted Trees by District.......................................................................................67 3.116 Number of Planted Trees by Species...................................................................................................................69 3.117 Number of Trees Planted by Smallholders by Species and District ...................................................................69 3.118 Number of Trees Planted by Location.................................................................................................................69 3.119 Number of Households by purpose of Planted Trees..........................................................................................69 3.120 Number of Households with Erosion Control/Water Harvesting Facilities .......................................................69 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............70 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility...................................................70 3.123 Total Number of Cattle ('000') by District...........................................................................................................71 3.124 Numbers of Cattle by Type and District..............................................................................................................71 3.125 Cattle Population Trend .......................................................................................................................................72 3.126 Dairy Cattle Population Trend.............................................................................................................................72 3.127 Total Number of Goats ('000') by District...........................................................................................................72 3.128 Goat Population Trend........................................................................................................................................ 73 3.129 Total Number of Sheep by District......................................................................................................................73 3.130 Sheep Population Trend.......................................................................................................................................76 3.131 Total Number of Pigs by District.........................................................................................................................76 3.132 Pig Population Trend............................................................................................................................................76 3.133 Total Number of Chicken by District ..................................................................................................................77 3.134 Chicken Population Trend ...................................................................................................................................77 3.135 Number of Improved Chicken by Type and District...........................................................................................80 3.136 Layer Population Trend........................................................................................................................................80 3.137 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District.......80 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............82 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........82 3.140 Number of Households by Distance to Veterinary Clinic...................................................................................82 3.141 Number of Households by Distance to Veterinary Clinic and District...............................................................82 3.142 Number of Households by Distance to Village Watering Point .........................................................................83 3.143 Number of Households by Distance to Watering Point and District..................................................................83 3.144 Number of Households using Draft Animals ......................................................................................................83 3.145 Number of Households using Draft Animals by District....................................................................................84 3.146 Number of Households using Organic Fertiliser.................................................................................................84 3.147 Area of Application of Organic Fertiliser by District .........................................................................................84 3.148 Number of Households Practicing Fish Farming – Rukwa.................................................................................84 3.149 Number of Households Practicing Fish Farming by District – Rukwa ..............................................................87 3.150 Fish Production.....................................................................................................................................................87 3.151 Agricultural Households by Type of Toilet Facility ...........................................................................................87 3.152 Percentage Distribution of Households Owning the Assets................................................................................88 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................88 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xv 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 90 3.155 Percentage Distribution of Households by Type of Roofing Material ...............................................................90 Percentage Distribution of Households With Grass/Leaves Roofs by District ..................................................92 3.157 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season....92 3.158 Percentage Distribution of the Number of Households by Main Source of Income..........................................92 3.159 Number of Agriculture Households by Number of Meals per day.....................................................................92 3.160 Number of Households by Frequency of Meat and Fish Consumption..............................................................93 3.161 Percent Distribution of the Number of Households by Main Source of Income................................................93 List of Maps 3.1 Total Number of Agricultural Households by District........................................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District..........................................................12 3.3 Number of Crop Growing Households by District..............................................................................................13 3.4 Percent of Crop Growing Households by District...............................................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................14 3.6 Percent of Crop and Livestock Households by District ......................................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land ..........................................................................19 3.8 Total Planted Area (annual crops) by District.....................................................................................................19 3.9 Area planted and Percentage During the Short Rainy Season by District..........................................................20 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................20 3.11 Planted Area and Yield of Maize by District ......................................................................................................24 3.12 Area Planted per Maize Growing Household......................................................................................................24 3.13 Planted Area and Yield of Paddy by District ......................................................................................................26 3.14 Area Planted per Paddy Growing Household......................................................................................................26 3.15 Planted Area and Yield of Cassava by District ...................................................................................................26 3.16 Area Planted per Cassava Growing Household....................................................................................................... 3.27 Planted Area and Yield of Onion by District ......................................................................................................35 3.28 Planted Area and Yield of Onion by District .....................................................................................................35 3.29 Planted Area and Yield of Tobbaco by District ..................................................................................................40 3.30 Area Planted per Tobacco Growing Household..................................................................................................40 3.24 Area Planted per Cabbage Growing Household..................................................................................................36 3.23 Planted Area and Yield of Cabbage by District ..................................................................................................36 3.19 Planted Area and Yield of Groundnuts by District .............................................................................................32 3.20 Area Planted per Groundnuts Growing Household.............................................................................................32 3.25 Planted Area and Yield of Tomatoes by District................................................................................................33 3.26 Area Planted per Tomatoeso Growing Household..............................................................................................33 3.23 Planted Area and Yield of Cabbage by District ..................................................................................................36 3.24 Area Planted per Cabbage Growing Household..................................................................................................36 3.27 Planted Area and Yield of Cotton by District......................................................................................................39 3.28 Area Planted per Cotton Growing Household.....................................................................................................39 3.33 Planted Area and Yield of Oranges by District...................................................................................................57 3.34 Area Planted per Orange Growing Household....................................................................................................57 3.35 Planted Area and Yield of Banana by District ....................................................................................................42 3.36 Area Planted per Banana Growing Household....................................................................................................42 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..................................48 3.41 Percent of households storing crops for 3 to 6 weeks by district........................................................................57 3.42 Number of Households and Percent of Total Households Selling Crops by District.........................................57 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .....65 3.44 Number and Percent of Crop Growing Households using Improved Seed by District .....................................65 3.45 Number and percent of smallholder planted trees by district..............................................................................68 3.47 Cattle population by District as of 1st Octobers 2003.........................................................................................74 3.48 Cattle Density by District as of 1st October 2003...............................................................................................74 3.49 Goat population by District as of 1st Octobers 2003 ..........................................................................................75 3.50 Goat Density by District as of 1st October 2003.................................................................................................75 3.51 Sheep population by District as of 1st Octobers 2003 ........................................................................................78 3.52 Sheep Density by District as of 1st October 2003...............................................................................................78 3.53 Pig population by District as of 1st Octobers 2003.............................................................................................79 3.54 Pig Density by District as of 1st October 2003 ...................................................................................................79 3.55 Number of Chickens by District as of 1st October 2003 ....................................................................................81 3.56 Density of Chickens by District as of 1st October 2003.....................................................................................81 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xvi 3.57 Number and Percent of Households Infected with Ticks by District .................................................................85 3.58 Number and Percent of Households Using Draft Animals by District...............................................................85 3.59 Number and Percent of Households Using Farm Yard Manure by District.......................................................86 3.60 Number and Percent of Households using Compost by District.........................................................................86 3.61 Number and Percent of Households Practicing Fish Farming by District..........................................................89 3.62 Number and Percent of Households Without Toilets by District .......................................................................89 3.63 Number and Percent of Households using Grass/Leaves for roofing material by District ................................91 3.64 Number and Percent of Households eating 3 meals per day by District ............................................................91 3.65 Number and Percent of Households eating Meat Once per Week by District ...................................................94 3.66 Number and Percent of Households eating Fish Once per Week by District.....................................................94 3.67 Number and percent of Households Reporting food insufficiency by District ................................................. 95 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Rukwa region is situated in the South West of the country between Latitude 50 and 90degrees south of Equartor and between Longitudes 300 and 33 degrees East. A good part of Rukwa region lies within the Western branch of east African Rift Valley known as the “ Western rift Land Province” Rukwa region, with an area of 75,240 sq. km, (68,635 sq. km. of land and 6,605sq. km. of inland water), takes up abouit 8% of the total land of Tanzania Mainland. The region is borded by Zambia in the South West, Lake Tanganyika in the west, Ki8goma region in the North west, Tabora region in the North East and Mbeya region in the East. The region comprises four districts namely Mpanda Sumbawanga Rural, Nkasi and Sumbawanga Urban. Land Area The region has an area of over 340,000 square kilometers, of which 28,695 square kilometers are arable land. 1.4 Climate The region enjoys favourable climate conditions, varying from a dry sub-humid climate. Rainfall: Rukwa region has an average rainfall ranging from 800mm. to 1,300mm The region has one main rainy season; from mid November to mid May, that is long rains (Wet) season Temperature: The Mean annual maximum temperature in the region varies between 240C and 270C and the minimum temperature between 130C and 160C. 1.5 Population According to the 2002 Population and Housing Census, there were 1,642,015 inhabitants in Rukwa region. The population of Rukwa region ranked 10th out of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 348,926 millions with a per capita income of shillings 236,115. The region held 10th position among regions on GDP and contributed about 4.3 percent to the national GDP1 Rukwa region is famous for limestone and gypsum mineral deposits, all of which are used in the cement factory situated in the region. The region is famous for producing both food crops. The main food crops produced in Rukwa region include: maize, paddy, beans and sorghum. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Rukwa region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field protesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc-View and Freehand. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS This part of the report presents the census results for Rukwa region based on the data tables in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Survey, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators compared to previous censuses and surveys, more effort has been made in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Rukwa region was 172,261. The largest number of agriculture households was in Sumbawanga Rural (68,935) followed by Mpanda (59,533), Nkasi (30,483) and Sumbawanga Urban (13,309) (Map 3.1). The highest density of households was found in Sumbawanga Urban (22 households/km2) and Sumbawanga Rural (13 households/ km2 ) (Map 3.2). Most households (114,069 66.2%) were involved in growing crops only, 416 households (0.2%) rearing livestock only and 57,776 (33.5%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Rukwa region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, ff-farm income, livestock keeping/herding, permanent crops, remittances, and fishing/hunting and gathering. (Table 3.1) Sumbawanga Rural and Sumbawanga Urban were the only districts where remittances were the fifty most important source of livelihood. Moreover, Nkasi was the only district where fishing/hunting and gathering was the fifth most important source of livelihood. Table. 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Annual Crop Farmin g Permanent Crop Farming Lives tock Keep ing / Herdi ng Off Farm Inco me Remittances Fishing / Hunting & Gatherin g Tree / Forest Resource s Mpanda 1 5 4 3 6 7 2 Sumbawanga R 1 6 4 3 5 7 2 Nkasi 1 7 4 3 6 5 2 Sumbawanga U 1 6 4 3 5 7 2 Total 1 5 4 3 6 7 2 Chart 3.1 Agriculture Households by Type - Rukwa Pastoralists, 0, 0% Livestock Only, 416, 0.2% Crops Only, 114,069, 66.2% Crops and Livestock, 57,776, 33.5% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Rukwa region was 150, 902 (88% of the total regional agricultural households) whilst the female-headed households were 21,359 12% of the total regional agricultural households). The mean age of household heads was 41 years (40 years for male heads and 46 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Rukwa region had a total rural agricultural population of 942,269 of which 476,244 (51%) were males and 466,024 (49%) were females. Whereas age group 0-14 constituted 48 percent of the total rural agricultural population, age group 15–64 (active population) was only 46 percent. Rukwa region had an average household size of 5.5 with Sumbawanga Rural district having the lowest household size of 5. (Chart 3.3) 3.1.5 Level of Education In order to obtain information on the level of education, data was gathered from all persons aged five years and above in all selected households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Chart 3.3 Percent Distribution of Population by Age and Sex - RUKWA 0 6 12 18 Age Group Percen t Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 19 9 4 /9 5 EAS 19 9 5/9 6 EAS 19 9 6 /9 7 IAS 19 9 7/9 8 DIAS 19 9 8 /9 9 NSCA 2 0 0 2 /0 3 Year Percent of Households Male headed households Female headed households Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 Sumbawanga Urban Nkasi Sumbawanga Rural Mpanda District Percen t Sumbawanga Urban Sumbawanga Rural 22 13 6 3 Mpanda Nkasi 30 to 40 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 13,309 68,935 30,483 59,533 Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Agricultural Households Total Number of Agricultural Households by District MAP 3.1 RUKWA MAP 3.2 RUKWA Number of Agricultural Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer 12 RESULT Sumbawanga Urban Sumbawanga Rural 100% 99% 100% 100% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Sumbawanga Urban Sumbawanga Rural 13,309 68,520 30,483 59,533 Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Crop Growing Household Number of Crop Growing Households by District MAP 3.3 RUKWA MAP 3.4 RUKWA Percent of Crop Growing Households by District Tanzania Agriculture Sample Census Percent of Crop Growing Household Number of Crop Growing Household Percent of Crop Growing Household RESULT 13 Sumbawanga Rural Sumbawanga Urban 43.2% 42.8% 35.1% 19.5% Mpanda Nkasi 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 22 13 6 3 Mpanda Nkasi 30 to 40 30 to 40 20 to 30 10 to 20 0 to 10 Number of Crop Growing Household per Square Km Number of Crop Growing Households per Square Kilometer of Land by District MAP 3.5 RUKWA MAP 3.6 RUKWA Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census Percent of Crop and Livestock Household Number of Crop Growing Household per Square Kilometer Percent of Crop and Livestock Household RESULT 14 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 Literacy Level for Household Members Rukwa region had a total literacy rate of 61 percent. The highest literacy rate was found in Sumbawanga Urban (66%) followed by Nkasi district (62%) and Sumbawanga Rural district (65%). Mpanda district had the lowest literacy rates of (60%) (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 72 percent. The literacy rates among the male and female heads of households were 78 and 36 percent respectively. The literacy rate for male headed of households was higher than that of females in all districts. However, Sumbawanga Rural and Sumbawanga Urban districts had the highest literacy rate amongst heads of households which was (75%) each followed by Nkasi (71%) and Mpanda (70% (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 38 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 28 percent were still attending school. Those who have never attended school were 34 percent (Chart 3.6). Agricultural households in Sumbawanga Urban district had the highest percentage (40%) of population aged 5 years and above who had completed different levels of education. This was followed by Nkasi district with (39%) while Sumbawanga Rural and Mpanda had the lowest percentages of (38%) Chart 3.7) The number of heads of agricultural households with formal education in Rukwa region was 118,763 (68.9%) and those Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.2% Never Attended 34.1% Attending School 27.7% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District P ercent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Post Primary 3.9% Adult Educ. 3.5% NO education 27.6% Primary Education 65.0% Chart 3.5 Literacy Rates of Head of Household by Sex and District - RUKWA 0 25 50 75 100 Sumbawanga Rural Sumbawanga Urban Nkasi Mpanda District Percent Male Female Total RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 without formal education were 53,498 (31.1%) and those with only adult education who were 6,019 (3.5%). The majority of heads of agricultural households (65.0%) had primary level education whereas only (3.9%) had post primary education. With regard to the heads of agricultural households with primary or secondary education in Rukwa region, Sumbawanga Urban district had the highest percentages (69.2% for primary and 2.8% for secondary). This was followed by Sumbawanga Rural (67.0% primary and 4.8% secondary), Nkasi (65.4% primary and 3.7% secondary) and Mpanda (61.6% primary and 3.3% secondary). (Chart 3.8) 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Rukwa with 76.5 percent of households having at least one member with off-farm income. In Rukwa region there were 59,888 households (34.8%) with only one member aged 5 and above involved in only one off-farm income generating activity, 53,457 households (31.0%) had two members involved in off-farm income generating activities and 18,456 households (10.7 %) had more than two members involved in off-farm income generating activities. Nkasi district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with higher percent of agriculture households with off-farm income were Sumbawanga Urban (81%) and Sumbawanga Rural (75%) while Mpanda district had the lowest percent of agriculture households with off-farm income (67%). The district with the highest percent of agriculture households with more than one member with off-farm income was Nkasi (65 %) followed by Sumbawanga Urban (49%), Sumbawanga Rural (43%) and Mpanda (27%) 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income One, 59,888, 35% NO Off-farm, 40,459, 23% Mo re than Two , 18,456, 11% Two , 53,457, 31% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb Districts Percent One Two Mo re Than Two NONE RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 country, however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 574,291 ha. The regional average land area utilised for agriculture per household was only 2.4 ha. This figure is slightly above the national average which is estimated at 2.0 hectares. Seventy three percent of the total land available to smallholders was utilised. Only 27.1 percent of usable land available to smallholders was not used (Chart 3.11). Small differences in land area utilised per household exist between districts with Sumbawanga Rural and Nkasi utilizing 2.7 and 2.5 ha per household respectively. The smallest land area utilised per household was found in Mpanda and Sumbawanga Urban with (2.0 ha) each. The percentage utilized of the usable land per household was highest in Sumbawanga Urban (86.2%) and lowest in Mpanda (63.2%). Seventy three percent of the total land available to smallholders was utilised. Only 27 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 226,716 hectares (39.5% of the total land available to smallholders in Rukwa), followed by uncultivated usable land (134,711 ha, 23.5%), temporary mixed crops (76,412 ha, 13.3%), area under fallow (55,734 ha, 9.5%), under natural bush (17,243 ha, 3.0%), permanent/annual mix/area rented to others/unusable area had (2,2%) each and permanent mono crop/permanent mixed crop/area under pasture/area under planted trees had (1%) each (chart 3.12) 3.3 Annual Crop and Vegetable Production Rukwa region has one rainy seasons, namely the wet season or the long rainy season (October to March). The quantity of crops produced in the wet season will be used as a base for comparison with the past surveys and censuses. Chart 3.12 Land Area by Type of Use 23.5 39.5 13.3 9.7 3.0 2.2 2.2 1.8 1.5 1.4 1.1 0.9 0 100,000 200,000 300,000 Area under Permanent Mono Crops Area under Planted Trees Area under Permanent Mixed Crops Area under Pasture Area Rented to Others Area under Permanent / Annual Mix Area Unusable Area under Natural Bush Area under Fallow Area under Temporary Mixed Crops Area of Uncultivated Usable Land Area under Temporary Mono Crops Land Use Area (hectares) Chart 3.11 Utilized and Usable Land per household by district 0.0 1.0 2.0 3.0 4.0 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Districts Area/household 0.0 20.0 40.0 60.0 80.0 100.0 Percentage utilized Area utilis ed (Ha ) To tal Us able Area ava ilable (ha) P e rcent Utilis atio n Chart 3.13 Area Planted (Ha) with Annual Crops by Season Dry Season, 1,049, 0.3% Wet Season, 302,345, 99.7% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 3.3.1 Area Planted The area planted with annual crops and vegetables was 303,393 hectares out of which 1,049 hectares (0.3%) were planted during dry season and 302,345 hectares (99.7%) during wet season. The average areas planted per household during the dry and wet rainy seasons was (1.4 ha) and (1.8 ha) respectively (Chart 3.13). The districts with dry season cultivation were Sumbawanga Rural with the average planted area of 1.8 ha per household followed with Nkasi (0.8 ha) and Sumbawanga Urban (0.5 ha). The district with the largest area planted per household in wet season was Sumbawanga Rural (2.0 ha), Nkasi (1.8ha), Mpanda (1.5 ha) and Sumbawanga Urban (1.5 ha). The district with the smallest average area planted in both dry and wet rainy seasons was Sumbawanga Urban with (56 ha and 20,109 ha ). Therefore, it can be concluded that Rukwa Region had mono- agricultural season which is wet season (Chart 3.14 and Map 3.8). The planted area occupied by cereals during the wet season was 203,500 ha (67.3% of the total area planted with annuals). This was followed by pulses (37,551 hectares, 12.4%), roots and tubers (28,595 hectares, 9.5%), oil seeds (28,178 hectares, 9.3%) cash crops (3,295 hectares (1.1%) and fruits and vegetables (1,225 hectares (0.4%). The average area planted per household during the wet season in Rukwa region was 1.8 hectares, however, there were large district differences. Sumbawanga Rural had the largest planted area per household (2.0 ha) followed by Nkasi (1.8 ha), Mpanda (1.6 ha) and Sumbawanga Urban (1.5 ha) each. (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. Chart 3.15 Area Planted with Annual C rops per Household by Season and District 0.000 1.000 2.000 3.000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Area Planted (ha) Wet Seas o n Wet Seas o n Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Sumbawanga Urban Sumbawanga Rural Nkansi Mpanda District Area Planted (ha) 0.00 0.50 1.00 1.50 2.00 Percentage Planted Wet Season Dry Season % Area planted in Dry season Sumbawanga Urban Sumbawanga Rural 20,109 ha 132,698 ha 53,306 ha 96,231 ha Mpanda Nkasi 160,000 to 200,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Sumbawanga Urban Sumbawanga Rural 63.2% 86.2% 79.1% 72.2% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Utilized Land Area Utilized Land Area Expressed as a Percent of Available Land by District MAP 3.7 RUKWA MAP 3.8 RUKWA Total Planted Area (Annual Crops) by District Tanzania Agriculture Sample Census Area Planted Annual Crop Utilized Land Area Expressed as a Percent Area Planted Annual Crop RESULT 19 Sumbawanga Urban Sumbawanga Rural 42ha 0ha 97ha 288ha 0.21% 0% 0.22% 0.18% Mpanda Nkasi 240 to 290 180 to 240 120 to 180 60 to 120 0 to 60 Sumbawanga Urban Sumbawanga Rural 1,047ha 17,901ha 1,446ha 8,741ha 5.2% 13.5% 2.7% 9.1% Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Area Planted and Percentage During the Short Rainy Season by District MAP 3.9 RUKWA MAP 3.10 RUKWA Area Planted with Cereals and Percent of Total Land Planted With Cereals by District Tanzania Agriculture Sample Census Planted Area (ha) Percent of Total Land Planted With Cereals Crop Percentage of Area Planted During the Short Rainy Season Planted Area (ha) Planted Area (ha) RESULT 20 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 21 3.3.2 Crop Importance Maize is the dominant annual crop grown in Rukwa region and it had a planted area 4.6 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 94.8 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are beans, cassava, paddy, finger millet, groundnuts, sunflower, sorghum, tobacco, sweet potatoes, wheat and tomatoes. (Chart 3.16) Households that grow finger millet, maize, paddy wheat and sorghum had larger planted areas per household than those growing other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Rukwa region. The area planted with cereals during the wet season was 203,500 hectares (67.3% of the total planted area), followed by pulses with (37,551 ha, 12.4%), root and tubers 28,595 hectares (9.5%), oil seeds 28,178 hectares (9.3%), cash crops 3 295 hectares (1.1%) and fruits and vegetables 1,225 hectares (0.4%) (Chart 3.17b). Cereals and pulses are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because dry season production was very small compared to wet season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.17b Percentage Distribution of Planted Area with Annual Crops by Crop Type Cash Crops 1.1% Fruits & Vegetables 0.4% Oil Seess & Oil Nuts 9.3% Roots & Tubers 9.5% Pulses 12.4% Cereals 67.3% Chart 3.17a Planted Area (ha) per Household by Selected Crop - RUKWA 0.00 0.35 0.70 1.05 Finger Millet Maize Paddy Wheat Sorghum Tobacco Sunflower Cowpeas Beans Cassava Yams Bambaranuts Groundnuts Cotton Sweet Potatoes Soya Beans Irish Potatoes Cocoyam Field Peas Bulrush Millet Simsim Crop Planted Area (ha) 4 2 7 3 7,551 2 79 2 8 ,59 5 0 2 8 ,178 3 4 3 3 ,2 9 5 0 1,2 2 5 0 0 50,000 100,000 150,000 200,000 Area (hectares) Cereals Pulses Roots & T ubers Oil Seeds & Oil Nuts Cash Crops Fruits & Vegetables Crop Type C hart 3.18 Are a Planted with Annual C rops by C rop Type and Se ason Wet Season Dry Season Chart 3.16 Planted Area (ha) for the Main Crops - RUKWA 0 60000 120000 Maize Beans Cassava Paddy Finger Millet Groundnuts Sunflower Sorghum Tobacco Sweet Potatoes Wheat Tomatoes Crop Planted Area (ha) RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 22 3.3.4 Cereal Crop Production The total production of cereals was 240,623 tonnes. Maize was the dominant cereal crop with the production of 163,432 tonnes which was 67.9 percent of total cereal crops produced, followed by paddy (20.6%), finger millet (6.6%) sorghum (4.1%), wheat (0.8%) and) bulrush millet (0.01). (Map 3.10). The area planted with maize was dominant and it represented 73.6 percent of the total area planted with cereal crops, followed by paddy (12.5%), finger millet (9.3%), Sorghum (3.6%), wheat 1.0%), and bulrush millet (0.01%). Paddy had the highest yield of (1940kg/ha), followed by sorghum (1,343 kg/ha), bulrush millet (1,186 kg/ha), maize (1,089 kg/ha), wheat (966 kg/ha) and finer millet (833 kg/ha) (Chart 3.19). 3.3.4.1 Maize Maize dominated the production of cereal crops in the region. The number of households growing maize in Rukwa region during the wet season was 159,160 (72.0% of the total crop growing households in the region during the wet season). The total production of maize during wet season was 163,277 tonnes from a planted area of 149,606 hectares resulting in a yield of (1.09 t/ha). (Chart 3.20) indicates the maize production trend (in thousand metric tonnes) for the wet season. There was a sharp decrease in maize production over the period of 1996 to 1998 after which the production increased sharply by the year 1998. In the year 1999 to 2000 the production was almost stable after which the production increased steadily up to the year 2003. The average area planted with maize per household was 0.94 hectares; however it ranged from 0.78 hectares in Mpanda district to 1.04 hectares in both Sumbawanga rural and Nkasi. (Map 3.21). Sumbawanga Rural district had the largest area for maize (66,238 ha) followed by Mpanda (43,301 ha), Nkasi (28,111 ha). Sumbawanga Urban district had the smallest planted area (12,382 ha) (Chart 3.21 and Map 3.11). Table 3.2: Area, Production and Yield of Cereal Crops by Season Wet Season Crop Area Planted (ha) Quantity harvested (tonnes) Yield (kg/ha) Maize 150,033 163,432 1,089 Paddy 25,526 49,520 1,940 Finger Millet 18,967 15,798 833 Sorghum 7,405 9,942 1,343 Wheat 1,979 1,911 966 Bulrush Millet 17 20 1,176 Total 203,928 240,623 Chart 3.20: Time Series Data on Maize Production - RUKWA 126 172 136 163 126 70 120 0 50 100 150 200 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 66,238 43,301 28,111 12,383 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Sumbawanga Rural Mpanda Nkansi Sumbawanga Urban District Area (Ha) 0.00 0.20 0.40 0.60 0.80 1.00 1.20 Area Planted per Household Planted Area (ha) are/hh RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 Charts (3.20 and 3.22) show that, both production and yield of maize dropped sharply from 1995/96 to 1997/98 after which both increased gradually up to 2002/03. On the other hand the planted area was almost stable from 1994/95 to 1996/97 and after increasing rapidly in the year 1997/98 but the exceeding years from 1998 to 2003 the yield remained almost constant the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 2000 and the area has remained constant ever since. (Chart 3.22) 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Rukwa region during the wet season was 30,132. This represented 17.6 percent of the total annual crop growing households in Rukwa region in the wet season. The total production of paddy was 49,520 tonnes from a planted area of 25,526 hectares resulting in a yield of (1.9 t/ha). The district with the largest area planted with Paddy was Sumbawanga Rural (12,505 ha) followed by Nkasi (11,605 ha). Mpanda and Sumbawanga Urban did not grow any paddy. (Map 3.13) There was a small insignificant variation in the average planted area per crop growing household between the two districts of Nkasi and Sumbawanga Rural ranging from 0.85 hectares to 0.95 hectares respectively (Chart 3.23 and Map 3.14) . There was a sharp decrease in the production of paddy from 1994/95 to 1995/96. From 1997/98 and 1998/99 the production increased. The production dropped from 7,941 tons in 1995/96 to 3642 tonnes in 1997/98 after which it rose to over 6,000 tonnes in the following two years of 1998/99 and 1999/2000. Thereafter the yield had been almost stable fluctuating between (2500 kg/ha ) and 900kg/ha) Charts 3.23 and 3.25 Chart 3.22 Time Series of Maize Planted Area & Yield - RUKWA 0 40,000 80,000 120,000 160,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 1.2 2.3 Yield (t/ha) Area Yield Chart 3.25 Time Series of Paddy Planted Area and Yield - RUKWA 0 2500 5000 7500 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Agriculture Year Area (hectares) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Yield (t/ha) Area Planted Yield 0 Chart 3.23 Total Planted Area and Area of Paddy per Household by District 12,505 11,605 0 0 4,000 8,000 12,000 16,000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Area (Ha) 0.00 0.50 1.00 Area planted per household Planted Area (ha) Area /hh Chart 3.24 Time Series Data on Paddy Production - TANGA 8 7 7 13 5 26 16 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Sumbawanga Urban Sumbawanga Rural 0.9ha 0.8ha 1ha 1ha Mpanda Nkasi 0.96 to 1 0.92 to 0.96 0.88 to 0.92 0.84 to 0.88 0.8 to 0.84 Sumbawanga Urban Sumbawanga Rural 12,383ha 66,238ha 28,111ha 43,301ha 1.1t/ha 0.9t/ha 1.3t/ha 1.0t/ha Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Planted Area (ha) Planted Area and Yield of Maize by District MAP 3.11 RUKWA MAP 3.12 RUKWA Area Planted per Maize Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 24 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 25 3.3.4.3 Other Cereals Other cereals produced in Rukwa Region included: sorghum (7,405 ha), finger millet (18,967 ha), bulrush millet (17 ha) and wheat (1,979 ha). While bulrush millet was grown in Nkasi district only, wheat was produced in all districts except Mpanda. (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 45,702 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 39,818 tonnes representing 87 percent of the total root and tuber crops production. This was followed by sweet potatoes (4,699 tonnes, 10%), Irish potatoes with 1,031 tonnes (2%), yams (127t, 0.3%) and coco yams (27t, 0.06%) (Table 3.3) The area planted with cassava was therefore larger than any other root and tuber crops and it was the most important root and tuber crop in Rukwa in terms of planted area. It accounted for 89.6 percent of the area planted with roots and tubers, followed by sweet potatoes (9.4%), Irish potatoes 1.0%), cocoyam (0.05%). and cocoyam (0.02%) There was a significant increase in the area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potatoes and yams remained more or less constant. The estimated yield was high for yams (9.7 t/ha) and cocoyam (3.9t/ha). Irish potatoes (3.7t/ha), sweet potatoes (1.8 t/ha) and cassava (1.6 t/ha) 3.3.5.1 Cassava The number of households growing cassava in the region was 53,929. This represents 31.4 percent of the total crop growing households in the region. The total production of cassava during the census year was 39,818 tonnes from a planted area of 25,611 hectares resulting in a yield of (1.6t/ha). Table 3.3: Area, Production and Yield of Roots & Tuber Crops Crops by Season Wet Season Crop Area Planted (ha) Quantity harvested (tonnes) Yield (kg/ha) Cassava 25,611 39,818 1,555 Sweet Potatoes 2,681 4,699 1,753 Irish Potatoes 282 1,031 3,656 Yams 13 127 9,669 Cocoyam 7 27 3,857 Total 28,594 45,702 Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10,000 20,000 30,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 2,000 4,000 6,000 8,000 10,000 Yield (kg/ha) Yield (kg/ha) Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Y e ar Cassava 0 3,000 6,000 9,000 12,000 Area (Ha) S umbawanga Rural Mpanda Nkasi S umbawanga Urban District Chart 3.26 Area Planted with Sorghum, Finger Millet, Bulrush Millet and Wheat by District Sorghum Finger Millet Bulrush Millet Wheat Sumbawanga Urban Sumbawanga Rural 0.3ha 0.5ha 0.6ha 0.4ha Mpanda Nkasi 0.54 to 0.61 0.48 to 0.54 0.42 to 0.48 0.36 to 0.42 0.3 to 0.36 Sumbawanga Urban Sumbawanga Rural 6,817ha 146ha 6,165ha 12,483ha 1.5t/ha 1.6t/ha 2.3t/ha 1.2t/ha Mpanda Nkasi 12,000 to 13,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Planted Area (ha) Planted Area and Yield of Cassava by District MAP 3.15 RUKWA MAP 3.15 RUKWA Area Planted per Cassava Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 26 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 Previous censuses and surveys indicate that the area planted with cassava increased from 1995/96 to 2002/03 (3.28). The planted area with cassava accounted for 8.5 percent of the total planted with annual crops. Sumbawanga Rural district had the largest planted area of cassava (12,483 ha, 48.7% of the total cassava planted area in the region) followed by Nkasi (6,817 ha, 26.6%), Mpanda ( 6,165 ha, 24.1%) and Sumbawanga Urban (146 ha, 0.6%). (Map 3.15). However, the district with the highest proportion of land planted with cassava was Sumbawanga Rural district (23.4%) followed by Mpanda (6.4%), Nkasi (5.1%) and Sumbawanga Urban (0.7%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.47 hectares. There were small district variations. The area planted per cassava growing household was greatest in Nkasi (0.57 ha), this was followed by Sumbawanga Rural (0.53 ha), Mpanda (0.42 ha) and Sumbawanga Urban (0.27ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Rukwa region was 9,530. This was 14.7 percent of the total root and tuber crop growing households during the wet season. The total production of sweet potatoes during the census year was 4,699 tonnes from a planted area of 2,681 hectares resulting in a yield of (1.75t/ha). Mpanda District has the largest planted area for sweet potatoes (1,400 ha, 52.2%), followed by Sumbawanga Rural (728 ha, 27.1%), Nkasi (469 ha, 17.5%) and Sumbawanga Urban (85 ha, 3.2%). 3.3.6 Pulse Crops Production The total area planted with pulses was 37,831 hectares out of which 37,530 ha were planted with beans (99.2 percent of the total area planted with pulses), followed by bambaranuts (108 ha, 0.29%), green grams (102 ha, 0.27%), cowpeas (68 ha, 0.18%) and field peas (23 ha, 0.06). Mung beans, pigeon peas and chick peas were not grown in the region. Table 3.4: Area, Production and Yield of Pulses by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 37,251 17,265 463 37,530 17,308 461 Bambaranuts 108 93 861 108 93 861 Green Gram 102 151 1,480 102 151 1,480 Cowpeas 68 47 691 68 47 691 Field Peas 23 11 478 23 11 478 Total 37,552 17,567 37,831 17,610 0.57 0.53 0.42 0.27 0.00 0.20 0.40 0.60 Area per Household Nkasi Sumbawanga Rur Mpanda Sumbawanga Urb District Chart 3.30: Cassava Planted Area per Cassava Growing Households by District Chart 3.31: Sweet Potatoes: Total Area Planted and Planted Area Per Household 0 500 1,000 1,500 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Area Planted (ha) 0.00 0.18 0.36 0.54 Area Planted per Household Area Planted Area per Household Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 48.7 26.6 24.1 0.6 0.0 25.0 50.0 Sumbawanga Rural Nkasi Mpanda Sumbawanga Urban District Percent of Total Area Planted 0 10 20 30 Percent Area Planted of Total Land Area % o f Area P lanted with Cas s ava P ro po rtio n o f Land Area RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 The total production of pulses was 17,610 tonnes. Beans were the most cultivated crop producing 17,308 tonnes which accounted for 98.3 percent of the total pulse production. This was followed by green grams (151t, 0.86%), bambaranuts (93t, 0.53%), cowpeas (47t, 0.27%) and field peas (11t, 0.06%). Green grams and bambaranuts had relatively higher yields of 1,480 and 861 kgs/ha) respectively. The yields of the rest of the pulses in kilograms per hectare were cowpeas (691 kgs/ha), field peas (478 kgs/ha) and beans (461 kgs/ha) (Chart 3.32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Rukwa region during the wet season was 78,216. The total production of beans in the region was 17,265 tonnes from a planted area of 37,251 hectares resulting in a yield of (0.46 t/ha).The largest area planted with beans in the region was in Sumbawanga Rural district (17,142 ha, 46.0%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per beans growing household was in Sumbawanga Rural district (0.56 ha) (Chart 3.34). The average area planted per household in the region during the wet season was (0.48 ha). The variations in area planted with beans per household among districts in the region was not significant important as it ranged from (0.37 ha) in Sumbawanga Urban to (0.45 ha) in Mpanda. (Map 3.18). Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 8,000 16,000 24,000 32,000 40,000 Beans Bambaranuts Green Gram Cowpeas Field Peas Crop Area Planted (ha) 0 400 800 1,200 1,600 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 6 12 18 Sumbawanga Urb Sumbawanga Rur Nkasi Mpanda District Percent of Land 0 2 4 6 Percent Area Planted of Total Land Area % of area planted with beans Proportion of land Chart 3.35: Time Series Data on Beans Production - RUKWA 16 2 53 16 17 46 37 0 10 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Prod u ction ('000') ton s 0.56 0.45 0.42 0.37 0.00 0.15 0.30 0.45 0.60 Area per Household Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District Chart 3.34 Area Planted per Bean Growing Household by District Wet Season Chart 3.36: Time Series of Beans Planted Area & Yield - RUKWA 0 14,000 28,000 42,000 1996/97 1998/99 1999/2000 2002/03 Agriculture Year A rea (hecta res) 0.00 0.15 0.30 0.45 Y ield (t/ha ) Beans (Ha) Yild (kg/ha Sumbawanga Urban Sumbawanga Rural 0.6ha 0.4ha 0.5ha 0.4ha Mpanda Nkasi 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Sumbawanga Urban Sumbawanga Rural 3,043ha 17,142ha 6,810ha 10,255ha 0.4t/ha 0.5t/ha 0.4t/ha 0.5t/ha Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Planted Area and Yield of Beans by District MAP 3.17 RUKWA MAP 3.18 RUKWA Area Planted per Beans Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 29 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 In Rukwa region, bean production was fluctuating from the year 1995/96 to 1998/99 after which the production increased steadily over the period 1998/99 to 2003 from 16,000 tonnes in 1998/99 to 17,000 tonnes in 2002/2003 (Chart 3.35). Charts 3.35 and 3.36 shows that whilst the yield of beans remained fairly constant in the last 3 years, the quantity produced had remained stable ranging between 40,000 in the year 1998 to 37,000 tonnes tin 2003 (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 17,419 tonnes planted on an area of 28,520 hectares. Groundnuts were most important oilseed crop with 16,570 hectares (58.1% of the total area planted with oil seeds), followed by sunflower (11,758 ha, 41.2%), soya beans (127 ha, 0.45%) and simsim (65 ha, 0.23%). The production of groundnuts was 11,126 tonnes which accounted for 63.9 percent of the total production of oil seeds, followed by sunflower (35.0%), soya beans (0.88%) and simsim (0.20%). 3.3.7.1 Groundnuts During the wet season the number of households growing groundnuts in that season was 44,997. The total production of groundnuts in the region was 11,055 tonnes from a planted area of 16,522 hectares resulting in a yield of (0.67 t/ha). Area planted had been increased from 1,292 hectares in 1994/95 to 16,570 hectares in 2002/03 (Chart 3.38) Table 3.5: Area, Quantity Harvested and Yield of Oil Crops by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Groundnuts 16,522 11,126 16,570 11,126 671 Sunflower 11,758 6,103 11,758 6,103 519 Soya Beans 127 154 127 154 1208 Simsim 65 35 65 35 540 Total 28,520 17,419 28,520 17,419 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 5,000 10,000 15,000 Groundnuts Sunflower Soya Beans Simsim Crop Area Planted (ha) -200 200 600 1000 1400 Yield (kg/ha) Yield (kg/ha) 1,292 3,178 8,703 16,570 0 5,000 10,000 15,000 20,000 Planted Area 1994/95 1995/96 1998/99 2002/03 Year Chart 3.38 Time Series Data on Groundnuts Planted Area Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 5.0 10.0 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District P ercent o f La nd 0.00 0.40 0.80 1.20 P ercent A rea P la nted o f To ta l La nd A rea Percent of Land Proportion of Land RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 31 Sixty percent of the area planted with groundnuts was located in Mpanda district (9,874 ha) followed by Sumbawanga Rural (5,136 ha, 31%), Nkasi (1,333 ha, 8%) and Sumbawanga Urban (180 ha, 1%). (Map 3.19) The district with the highest proportion of land with groundnuts was Sumbawanga Rural, followed by Mpanda, Sumbawanga Urban and Nkasi. (Chart 3.39 and Map 3.20) The largest area planted per groundnut growing household was found in Mpanda district (0.48 ha) and the lowest was in Sumbawanga Urban (0.20 ha). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. The total production of fruits and vegetables was 4,211 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 2,136 tonnes (48% of the total fruit and vegetables produced) followed by onions (1,139t, 22%), Cabbage (739t, 14%) and Amaranths (110t, 10%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 3,665 kg/ha, onions (4,279 kg/ha), cabbage (4,212 kg/ha), Amaranths (879 kg/ha), spinach (1,336 kg/ha), pumpkins (540 kg/ha) and carrot (2kg/ha) (Chart 3.42). 3.3.8.1 Tomatoes Sumbawanga Rural district had the largest planted area of tomatoes (42% of the total area planted with tomatoes in the region), followed by Mpanda (29%), Sumbawanga Urban (22%) and Nkasi (6%) (Map 3.21). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tomatoes 583 2,136 3,665 583 2,136 3,665 Onions 266 1,139 4,279 266 1,139 4,279 Cabbage 176 739 4,212 176 739 4,212 Amaranths 125 110 879 125 110 879 Spinnach 51 68 1,336 51 68 1,336 Pumpkins 22 12 540 22 12 540 Carrot 3 7 2 3 7 2 Total 1,225 4,211 1,225 4,211 Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 300 600 Tomatoes Onions Cabbage Amaranths Spinnach Pumpkins Carrot Crop A rea P la n ted (h a ) 0 1,000 2,000 3,000 4,000 5,000 Y ield (k g /h a ) 0.48 0.29 0.27 0.20 0.00 0.20 0.40 0.60 A rea p er H o u seh o ld (h a ) Mpanda Nkasi Sumbawanga Rur Sumbawanga Urb District Chart 3.40 Area Planted per Groundnut Growing Households by District (Wet Season ) Sumbawanga Urban Sumbawanga Rural 0.3ha 0.2ha 0.3ha 0.5ha Mpanda Nkasi 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Sumbawanga Urban Sumbawanga Rural 5,136ha 180ha 1,333ha 9,874ha 0.5t/ha 0.5t/ha 1.2t/ha 0.7t/ha Mpanda Nkasi 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Planted Area (ha) Planted Area and Yield of Groundnuts by District MAP 3.19 RUKWA MAP 3.20 RUKWA Area Planted per Groundnuts Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 32 Sumbawanga Urban Sumbawanga Rural 0.1ha 0.2ha 0.2ha 0.2ha Mpanda Nkasi 0.18 to 0.2 0.16 to 0.18 0.14 to 0.16 0.12 to 0.14 0.1 to 0.12 Sumbawanga Urban Sumbawanga Rural 129ha 35ha 173ha 245ha 5t/ha 0.9t/ha 1.9t/ha 4.6t/ha Mpanda Nkasi 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Planted Area (ha) Planted Area and Yield of Tomatoes by District MAP 3.21 RUKWA MAP 3.22 RUKWA Area Planted per Tomatoes Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 33 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 The district with the highest proportion of land with tomatoes was Sumbawanga Rural followed by Sumbawanga Urban district. With exception of Sumbawanga Rural district, the rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Mpanda district (0.22 ha) followed by Nkasi (0.21 ha), Sumbawanga Urban (0.16 ha) and Sumbawanga Rural (0.14 ha) (Chart 3.44 and Map 3.22). The total area planted with tomatoes accounted for 0.19 percent of the total area planted with annual crops and vegetables during the wet season. 3.3.8.2 Onions The number of households growing onions in the region during the wet season was 1,718. This represented 1.0 percent of the total crop growing households in the region. The district with the largest planted area with onions was Sumbawanga Urban (110 ha, 41.3% of the total area planted with onions in the region), followed by Mpanda (68 ha, 25.6%), Sumbawanga Rural (68 ha, 25.6%) and Nkasi (20 ha, 7.4%) (Chart 3.45 and Map 3.23 and 2,24). The total area planted with onions accounted for 0.09 percent of the total area planted with annual crops and vegetables during the wet seasons. 3.3.8.3 Cabbage The number of households growing cabbages in the region during the wet season was 1,032 households in the wet season. This represents 0.6 percent of the total crop growing households in the region. Nkasi district had the largest planted area of cabbage (60 ha, 34.2% of the total area planted with cabbage in the region), followed by Sumbawanga Rural (59.6 ha, 33.9.9%), Sumbawanga Urban (42.2 ha, 24.1%) and Mpanda (13.6 ha, 7.8%) (Map 3.25 and 3.26) The district with the largest proportion of the area planted with cabbage was Nkasi district (0.101 ha), followed by Sumbawanga Rural (0.012 ha), Mpanda (0.003%) and Sumbawanga Urban (0.002) (Chart 3.46). The total area planted with cabbage accounted for 0.06 percent of the total area planted with annual crops and vegetables during the wet seasons. Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0 15 30 45 60 Sumbawanga Rur Mpanda Sumbawanga Urb Nkasi District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area P ercent of Land P ropo rtio n o f land 0.22 0.21 0.16 0.14 0.00 0.08 0.16 0.24 Area per Household (ha).. Mpanda Nkasi Sumbawanga Urb Sumbawanga Rur District Chart 3.44 Area Planted per Tomato Growing Household by District (Wet Season ) Chart 3.46 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 10.0 20.0 30.0 40.0 Nkasi Sumbawanga Rur Sumbawanga Urb Mpanda District Percent of Land -0.015 0.040 0.095 0.150 Percent Area Planted of Total Land Area P ercent o f Land P ro po rtio n o f Land Chart 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District 0.00 0.15 0.30 0.45 Mpanda Sumbawanga Urb Sumbawanga Rur Nkasi District Percent of Land 0.000 0.020 0.040 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Sumbawanga Rural Sumbawanga Urban 0.3ha 0.2ha 0.1ha 0.1ha Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 60ha 42ha 60ha 14ha 7.6t/ha 4.5t/ha 1t/ha 3t/ha Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Planted Area (ha) Planted Area and Yield of Cabbage by District MAP 3.23 RUKWA MAP 3.24 RUKWA Area Planted per Cabbage Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 RESULT 35 Sumbawanga Rural Sumbawanga Urban 0.1ha 0.3ha 0.2ha 0.1ha Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 20ha 68ha 68ha 110ha 3.7t/ha 6.5t/ha 5.4t/ha 2.3t/ha Mpanda Nkasi 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Planted Area (ha) Planted Area and Yield of Onions by District MAP 3.25 RUKWA MAP 3.26 RUKWA Area Planted per Onions Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 RESULT 36 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 37 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 3,295 ha was planted with cash crops and tobacco was the most prominent followed by cotton. 3.3.9.1 Tobacco The quantity of tobacco produced was 3,251 tonnes. Tobacco had a planted area of 3,256 hectares with all of being planted in the wet season. Tobacco production was concentrated in two districts with Nkasi having the largest planted area (99.3% of total area planted with tobacco in the region) and Sumbawanga Rural had (0.7%). (Chart 3.43) (Map 3.29 and 3.30). 3.3.9.2 Cotton The production of cotton in Rukwa Region was only 13 tonnes from the planted area of 39 ha. It was produced during the wet season. The crop was only grown in Mpanda district (Map 3.27) with an average planted area of 0.3 hectares per cotton growing household (Map 3.28) (Chart 3.48) 3.4 Permanent Crops Permanent crops (sometimes referred as permanent crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature but survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Wet Season Total Crop Area Planted (ha) Quantity harvested (Tons) Yield Area Planted (ha) Quantity harvested (Tons) Yield Tobacco 3,256 3,251 998 3,256 3,251 998 Cotton 39 13 333 39 13 333 Pyrethrum 0 0 0 0 0 0 Jute 0 0 0 0 0 0 Total 3,295 3,264 3,295 3,264 Chart 3.47 Area planted with Annual Cash Crops Tobacco 98.8% cotton 1.2% Pyrethrum 0% Jute 0% Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.00 0.04 0.08 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Percent of Land 0.0000 0.0010 0.0020 0.0030 0.0040 0.0050 Percent Area Planted of Total Land Area Percent of Land Percent of Land Chart 3.49: Area Planted for Annual and Permanent Crops Permanent, 8,810, 2.8% Annual , 302,344, 97.2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 The area of smallholders planted with permanent crops was 8,810 hectares (2.8% of the area planted with both annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it double counts the area planted more than once in the same year whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in (Chart 3.49). The most important permanent crop in Rukwa region is lime/lemon accounts for a planted area of 3,877 ha, (43% of the planted area of all permanent crops) followed by sugarcane (1,797 ha, 21%), banana (1,490 ha, 21%), mangoes (547 ha, 6%),orange (190 ha, 2%), pigeon pea (162 ha, 2%), guava (152 ha, 2%),palm oil (138 ha, 2%) and coconuts (60 ha, 1%). The remaining permanent crops are produced in very small quantities (Chart 3.50). The district with the largest area planted with permanent crops by smallholders was Sumbawanga Rural district (4,635 ha, 52.2%). This is followed by Nkasi (2,187 ha, 24.6%), Mpanda (1,554 ha, 17.5%) and Sumbawanga Urban (5.3 ha, 5.7%). However, Sumbawanga Rural district had the largest area planted per permanent crop growing household (0.57 ha) followed by Nkasi (0.28 ha), Sumbawanga Urban (0.18 ha) and Mpanda (0.17 ha) (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Sumbawanga Rural had the highest (23%) followed by Mpanda (3%), Nkasi (2%) and Sumbawanga Urban (0.4%). 3.4.1 Lime/lemon The total production of lime/lemon by smallholders was 133 tonnes. In terms of area planted, lime/lemon was the most important permanent crop grown by smallholders in the region. There were 401 lime/lemon growing households (0.23% of the total crop growing households). The average area planted with lime/lemon per household was relatively small at around 9.7 ha per lime/lemon growing household and the average yield obtained by smallholders was (7,389 kg/ha) from a harvest area of 18 hectares. Chart 3.50: Area Planted with the Main Perennial Crops Lime/Lemon, 3,877, 43% Sugarcane, 1,797, 21% Banana, 1,790, 21% Orange, 190, 2% Mango, 547, 6% Guava, 155, 2% Coconut, 60, 1% Palm Oil, 138, 2% Pigeon Pea, 162, 2% Chart 3.52 Percent of Area Planted with Lime/Lemon and Average Planted Area per Household by District 0.1 50.0 0.0 49.9 0.0 20.0 40.0 60.0 Sumbawanga Urban Mpanda Nkasi Sumbawanga Rural District % of Total Area Planted 0.00 4.00 8.00 12.00 16.00 20.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 25 18 6 52 0 20 40 60 Sumbawanga Rural Nkasi Mpanda Sumbawanga Urban District % of Total Area Planted 0.0 1.5 3.0 4.5 Average Planted Area per H ousehold % of T otal Area Planted Average Planted Area per Household Sumbawanga Rural Sumbawanga Urban 0ha 0ha 0ha 0.3ha Mpanda Nkasi 0.24 to 0.31 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Sumbawanga Urban Sumbawanga Rural Nkasi 0ha 0ha 39ha 0ha 0t/ha 0t/ha 0.3t/ha 0t/ha Mpanda 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Planted Area (ha) Planted Area and Yield of Cotton by District MAP 3.27 RUKWA MAP 3.28 RUKWA Area Planted per Cotton Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 39 Sumbawanga Urban Sumbawanga Rural 0ha 24ha 0ha 3,233ha 0t/ha 1.7t/ha 0t/ha 1t/ha Mpanda Nkasi 2,800 to 3,300 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Sumbawanga Urban Sumbawanga Rural 0ha 0.2ha 0ha 0.7hhhha Mpanda Nkasi 0.56 to 0.7 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Planted Area (ha) Planted Area and Yield of Tobbaco by District MAP 3.29 RUKWA MAP 3.30 RUKWA Area Planted per Tobbaco Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Household Planted Area Per Household RESULT 40 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 Sumbawanga Urban district had the largest area planted with lime/lemon (3,877 ha, 50.0%) followed closely by Mpanda (3,866 ha, 49.9%) and Nkasi (11 ha, (0.1%). Sumbawanga Rural did not grow any lime/lemon. (Map 3.31). However, the average area planted with lime/lemon per growing household was highest in Mpanda (14.4 ha) followed by Sumbawanga Urban (9.7 ha) and Nkasi (0.08 ha) (Chart 3.52 and Map 3.32). 3.4.2 Sugarcane The total production of sugarcane by smallholders was 54,638 tonnes. In terms of area planted, sugarcane was the second most important permanent crop grown by smallholders in the region. There were 4,327 households (2.5% of the total crop growing households). The average area planted with sugarcane per household was relatively small at around 0.9 ha per sugarcane growing household and the average yield obtained by smallholders was (13,381 kg/ha) from a harvest area of 4,083 hectares. Sumbawanga Rural district had the largest area planted with sugarcane (1,356 ha, 75%) followed by Nkasi (346 ha, 19%), Sumbawanga Urban (74 ha, 4%) and Mpanda (22 ha, 1%) (Map 3.31). However, the average area planted with sugarcane per growing household was highest in Nkasi district (1.43 ha) followed by Sumbawanga Rural (0.43 ha), Mpanda (0.16 ha) Sumbawanga Urban (0.06 ha) (Chart 3.52 and Map 3.32).ha) (Chart 3.53 and Map 3.34). 3.4.3 Banana The total production of banana by smallholders was 11,471 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 7,261 households (4.2% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.25 ha per banana growing household and the average yield obtained by smallholders was 11,357 kg/ha from a harvested area of 1010 hectares. Sumbawanga Rural district had the largest planted area of bananas in the region (758 ha, 42%) followed closely by Mpanda (694 ha, 39%), Sumbawanga Urban (272 ha, 15%) and Nkasi (66ha, 4%) (Map 3.35). The districts with largest area planted with banana per banana growing household were Sumbawanga Rural and Nkasi having (0.27ha) each followed by Sumbawanga Urban (0.25 ha) and Mpanda (0.23 ha) (Chart 3.49 and Map 3.36). Chart 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District 38.79 3.66 42.35 15.20 0.00 20.00 40.00 Sumbawanga Rural Mpanda Sumbawanga Urban Nkasi District % of Total Area Planted 0.00 0.15 0.30 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District 19 1 75 4 0 20 40 60 80 Sumbawanga Rural Nkasi Sumbawanga Urban Mpanda District % o f To ta l A rea P la nted -0.40 0.20 0.80 1.40 2.00 A v era g e P la nted A rea per H o useho ld % of Total Area Planted Average Planted Area per Household Sumbawanga Rural Sumbawanga Urban 0.27ha 0.24ha 0.27ha 0.23ha Mpanda Nkasi 0.262 to 0.27 0.254 to 0.262 0.246 to 0.254 0.238 to 0.246 0.23 to 0.238 Sumbawanga Rural Sumbawanga Urban 758ha 272ha 66ha 694ha 8.2t/ha 6.1t/ha 7.3t/ha 2t/ha Mpanda Nkasi 800 to 800 600 to 800 400 to 600 200 to 400 0 to 200 Planted Area (ha) Planted Area and Yield of Banana by District MAP 3.31 RUKWA MAP 3.32 RUKWA Area Planted per Banana Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Household Planted Area Per Household RESULT 42 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 3 .4.4 Mangoes The total production of mangoes by smallholders was 15,571 tonnes. In terms of area planted, mangoes were the fourth most important permanent crop grown by smallholders in the region. It was grown by 4,033 households (2.3% of the total crop growing households). The average area planted with mangoe per household was relatively small at around 0.4 ha per mangoes growing household and the average yield obtained by smallholders was (6,537 kg/ha) from a harvested area of (2,382 ha). Nkasi has the largest area of mangoes in the region (2,020 ha, 78.7%) followed by Mpanda (392 ha, 15.3%) and Sumbawanga Rural (155 ha, 6.0%). However, Sumbawanga Urban district did not grow any mango (Map 3.37). Moreover, Nkasi district had the highest average area planted per mangoes growing household of (1.9 ha), Sumbawanga Rural (0.14 ha) and Mpanda (0.13 ha) (Map 3.38). 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the wet season was 266,794 ha which represented 88.2 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 6.4, 3.08 and 0.9 percent respectively (Chart 3.56 and Table 3.8 ). Table 3.8: Land Clearing Methods Wet Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 150,853 266,794 88.2 150,853 266,794 88.2 No Land Clearing 2,075 3,557 1.2 2,075 3,557 1.2 Mostly Bush Clearance 10,293 19,399 6.4 10,293 19,399 6.4 Mostly Burning 7,257 9,070 3.0 7,257 9,070 3.0 Mostly Tractor Slashing 499 789 0.3 499 789 0.3 Other 1,283 2,735 0.9 1,283 2,735 0.9 Total 172,261 302,344 100 172,261 302,344 100.0 Chart 3.56: Number of Households by Method of Land Clearing During the Wet Season 499 1,283 2,075 7,257 10,293 150,853 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Other Mostly Tractor Slashing Method of Land Clearing Number of Households Chart 3.55 Percent of Area Planted with Mangoes and Average Planted Area per Household by District 6.04 78.69 0.00 15.26 0.00 20.00 40.00 60.00 80.00 Nkasi Mpanda Sumbawanga Rural Sumbawanga Urban District % of Total Area Planted 0.00 0.25 0.50 Average Planted Area per Household % of T otal Area Planted Average Planted Area per Household RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 44 3.5.2 Methods of Soil Preparation Oxen ploughing was the most used method for soil preparation as it was used in an area of 181,141 ha which represented 60.2 percent of the total prepared area, followed by hand hoe ploughing (119,096 ha, 39.6%) and tractor ploughing (583 ha, 0.2%) (Chart 3.57). In Rukwa region, Sumbawanga Rural district has the largest planted area cultivated with oxen (106,662 hectares, 58.7%) followed by Nkasi (37,412 ha, 20.6%), Mpanda (19,499, 10.7%) and Sumbawanga Urban (18,070 ha, 9.9%). 3.5.3 Improved Seed Use-* The planted area using improved seeds during the wet season was estimated at 29,135 ha which represents 9.6 percent of the total planted with the annual crops and vegetables during the season. The area planted without using improved seeds was (273,210 ha, 90.4%) Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 181,643, 60.6% Mostly Hand Hoe Ploughing, 117,273, 39.1% Mostly Tractor Ploughing, 855, 0.3% Chart 3.60 Planted Area with Improved Seed by Crop Type Pulses, 2,654, 9% Roots &Tubers, 1,836, 6% Oil seeds, 3,404, 12% Fruits & Vegetables, 541, 2% Cash crop, 2,919, 10% Cereals, 17,781, 61% 0 20,000 40,000 60,000 80,000 100,000 120,000 Area Cultivated Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostly T ractor Ploughing Chart 3.59 Area Planted with Improved Seeds - RUKWA With Improved Seeds, 29,135, 9.60% Without Improved Seeds, 273,210, 90.4% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 Cereals had the largest area planted with improved seeds (17,781 ha, 61% of the planted area with improved seeds) followed by oil seed (3,404 ha, 12%) cash crops (2,919 ha, 10%) pulses (2,654 ha, 9%), roots and tubers (1,836 ha, 6%) and fruit and vegetables (541 ha, 2%), (Chart 3.54). However, of all crop types fruits and vegetables had the largest proportion of its planted area under improved seeds. with improved seeds (Chart 3.55). 3.5.4 Fertilizers Use The use of fertilisers on annual crops was very small with a planted area of only 42,191 ha (14% of the total planted area in the region). The planted area without fertiliser for annual crops was 260,153 hectares representing 86 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 26,741 ha which represents 8.8 percent of the total planted area (63.3% of the area planted with fertiliser application in the region). This was followed by Inorganic fertilizers 11,968 ha, 3.9 percent of total area planted (28.3 of the area planted with fertiliser application) compost was used on a very small area (3,518 ha, 1.2%) of the total planted area and 8.3 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Sumbawanga Urban district (37.3%) followed by Nkasi (12.7%), Sumbawanga Rural (12.3%) and Mpanda (12.0%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households used different fertilisers (approximately 171,578 households, 99.6%) (Map 3.39). The percentage of the planted area with applied fertilisers was highest for cereals (89.3% of the area planted with fertilizers). This was far followed by pulses (4.9%), oilseeds & oil nuts together with fruits & vegetables had (2.1%) each and cash crops had (0.4%) (Table 3.9) Table3.9 Planted Area by Type of Fertiliser Use and District - Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Planted Area Planted Area Planted Area Planted Area Planted Area Mpanda 2,746 762 8,030 84,693 96,231 Sumbawanga Rural 12,857 1,974 1,555 116,312 132,698 Nkasi 6,028 308 459 46,511 53,306 Sumbawanga Urban 5,110 475 1,923 12,601 20,109 Total 26,741 3,518 11,968 260,117 302,344 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 46 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Rukwa region during wet season was 26,741 hectares, this is equivalent to 8.8 percent of the total area planted during that season. The number of households that applied farm yard in their annual crops during the wet season was 18,756. (Table 3.9). Cereals had the largest area applied with farm yard manure (89.3%), followed by pulses (4.9%). Oil seeds and oil nuts together with fruits and vegetables had (2.1%), roots and tubers (1.3%) and cash crops (0.4%) (Chart 3.64a). Sumbawanga Rural district had the largest area applied with farm yard manure (48.1% of the total planted area in the region) followed by Nkasi (22.5%), Nkasi (6.9%) Sumbawanga Urban (19.1%) and Mpanda (10.3%) (Table 3.9). Chart 3.62 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 260,117, 86% Mostly Inorganic Fertilizer, 11,968, 4% Mostly Compost, 3,518, 1% Mostly Farm Yard Manure, 26,741, 9% 0 30,000 60,000 90,000 Area (ha) Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - RUKW A 0.0 10.0 20.0 30.0 Sumbawanga Urban Nkasi Sumbawanga Rural Mpanda District Percent Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - RUKWA Roots & Tubers, 340, 1% Pulses, 1,300, 5% Cerals, 23,776, 89% Oil & Oil Nuts, 552, 2% Fruits & Vegetables, 552, 2% Cash Crops, 108, 0% 0 20 40 60 80 100 Percent of Planted Area Cerals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.65a Percentage of Planted Area with Farm Yard Manure by Crop Type - RUKWA RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 The proportion of planted area applied with farm yard manure was highest for cereals (89.3%), followed by pulses (4.9%), fruits and vegetables together with oil seeds and oil nuts had (2.1%) each, roots and tubers and cash crops (0.4%) (Chart 3.65a). Proportionally, farm yard manure was mostly used in Sumbawanga urban by (25.4% of the total planted area in the district) followed by Nkasi (11.3%), Sumbawanga Rural (9.7%), and Mpanda (2.9%) (Chart 3.65b). For permanent crops, most farm yard manure was used in the production of sugarcane (72.7%), followed by banana (19.8%), coconut (6.9%) and guava (0.5%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Rukwa region was 11,968 hectares which represents 3.9 percent of the total planted area with annuals in the region and 28.3 percent of the total planted area with fertilisers. The number of households that applied inorganic fertilizer on their annual crops during the wet season was 8,412 Cereals had the largest area applied with inorganic fertilizers was on cereals (69.5% of the total area applied with inorganic fertilizers), followed by cash crops (25%), pulses (4.2%), oil seeds (0.8%), roots and tubers (0.3%) and fruit and vegetables (0.2%) (Chart 3.66). However, the proportion of planted area applied with inorganic fertilizers was highest for fruits and vegetables at 12.7 percent followed by roots and tubers (1.1%), pulses (0.8%) and cereals (0.3%) (Chart 3.67a). Inorganic fertiliser is mostly used in Mpanda (8.3% of the total planted area in the district) followed by Sumbawanga Rural (2.9%), Nkasi (2.3%) and Sumbawanga Urban (1.4%) (Chart 3.67b). In permanent crops inorganic fertiliser were used on coconut (70%), sugarcane (25.6%), banana (6.8%) and guavas (1.9%). 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - RUKW A Chart 3.66 Planted Area with Inorganic by Crop Type - RUKWA Cash Crops, 2,990, 25% Fruits & Vegetables, 29, 0.2% Oil Seeds , 91, 0.8% Pulses, 504, 4.2% Roots & Tubers, 32, 0.3% Cereals, 8,323, 69.5 Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - RUKWA 0.0 3.0 6.0 9.0 Mpanda S,mbawanga Rural Nkasi S,mbawanga Urban District Percen t Chart 3.68a Planted Area with Compost by Crop Type - RUKWA Roots & Tubers, 126, 4% Pulses, 373, 11% Cash Crops, 0, 0% Fruits & Vegetables, 15, 0.4% Oil Seeds & Oil Nuts, 68, 2% Cereals, 2,936, 83% Sumbawanga Urban Sumbawanga Rural 1,146ha 1,138ha 9,983ha 7.5% 14.1% 2.1% 1.2% Mpanda Nkasi 2,830ha 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Nkasi Sumbawanga Urban Sumbawanga Rural Mpanda 85,095ha 49,234ha 113,529ha 11,383ha 88.4% 85.6% 56.6% 92.4% 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Planted Area with no Fertilizer Applied Planted Area and Percent of Planted Area with No Application of Fertilizer by District MAP 3.35 RUKWA MAP 3.36 RUKWA Area Planted and Percent of Total Planted Area With Irrigation by District Tanzania Agriculture Sample Census Planted Area with no Fertilizer Applied Percent of Planted Area with no Fertilizer Applied Percent of Planted Area with Irrigation Applied Planted Area with Irrigation Applied Planted Area with Irrigation Applied RESULT 48 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 3.5.4.3 Compost Use The total planted area applied with compost was 3,518 hectares; this represents only 1.2 percent of the total planted area with annual crops in the region and 8.3 percent of the total planted area with fertiliser in the region. The number of households that applied compost on their annual crops during the wet season was 3,131 which is equivalent to 1.8 percent of the total crop growing households in the region during the wet season (Table 3.9 and Chart 3.68a). The proportion of area applied with compost was very low for each type of crop (0 to 8.3%); however the distribution of the total area using compost shows that 83 percent of this area was cultivated with cereals, followed by pulses (10.6%), roots & tubers (3.6%), oil seeds & oil nuts (1.9%) and fruits & vegetables (0.4%). No compost manure was applied on cash crops Chart 3.68a). Compost was mostly used in Sumbawanga Urban (2.4% of the total planted area in the district), and this is closely followed by Sumbawanga Rural (1.5%), Mpanda (0.8%) and Nkasi (0.6%) (Chart 3.68b). In permanent crops, compost was mostly used to sugarcane (100.0%) 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 25,121 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (81% of the total area applied with pesticides). This was followed by fungicides (11%) and herbicides (8%) (Chart 3.69). Chart 3.69 Planted Area (ha) by Pesticide Use Insecticides, 27,634, 81% Herbicides, 2,578, 8% Fungicides, 3,782, 11% 0.0 25.0 50.0 75.0 100.0 P e r c e n t o f P la n t e d A r e a Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type - RUKWA Chart 3.68c Proportion of Planted Area Applied with Compost Fertiliser by District - RUKWA 0.0 1.0 2.0 3.0 Sumbawanga Urban Sumbawanga Rural Mpanda Nkasi District Percen t RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.5.1 Insecticide Use The planted area applied with insecticides during the wet season was estimated at 27,634 hectares which represented 9.1 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (22,004 ha, 79.6% of the total planted area with insecticides) followed by cash crops (2,444 ha, 8.8%), pulses (1,864 ha, 6.7%), oil seed (583 ha, 2.1%) fruit and vegetables (378 ha, 1.4%) and roots and tubers (362 ha, 1.3%) (Chart 3.70). However, the proportion of area applied with insecticides was highest for cash crops and fruits and vegetables being (74 and 31% respectively, while in cereals the proportion was (11%), pulses (5%), oil seeds 2%) and roots and tubers (1%) (Chart 3.71). The annual crops with more than 50 percent insecticide use was maize (76.9%). The remaining annual crops used insecticides on less than 50 percent of the planted area Sumbawanga Urban had the highest percent of planted area with insecticides (40.4% of the total planted area with annual crops in the district). This was far followed by Sumbawanga Rural (8.3%), Nkasi (6.9%) and Mpanda (5.0%) (Chart 3.72). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 2,578 hectares which represented 0.85 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,664 ha, 64.6%) followed by roots & tubers (427 ha, 16.6%), pulses (257 ha, 10.0%) oil seeds & oil nuts (189 ha, 7.3%) and fruits & vegetables (41 ha, 1.6%). No herbicides were applied on cash crops (Chart 3.73). Chart 3.70 Planted Area Applied with Insecticides by Crop Type Oil Seeds & Oil Nuts, 583, 2.1% Fruits & Vegetables, 378, 1.4% Cash Crops, 2,444, 8.8% Roots & T ubers, 362, 1% Pulses, 1,864, 6.7% Cereals, 22,004, 79.6% 0 5 10 15 20 P ercent o f P la nted A rea Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - RUKW A 0.0 15.0 30.0 45.0 Saumbawanga Urban Sumbawanga rural Nkasi Mpanda District Percent Chart 3.73 Planted Area Applied with Herbicides by Crop Type Roots & T ubers, 427, 17% Pulses, 257, 10% Oil Seeds & Oil Nuts, 189, 7% Fruits & Vegetables, 41, 2% Cash Crops, 0, 0% Cereals, 1,664, 64% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 However, the proportion of planted area applied with herbicides was highest for fruits and vegetables and roots and tubers being (3.3% and 1.5% respectively). The proportion of cereals ( 0.8%) and for oil seeds and oil nuts it was (0.7%) (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (55%), cassava (16.6%), beans (10%), sunflower (6.5%), sorghum (3.6%) and groundnuts (0.9%). Sumbawanga Rural had the highest percent of planted area applied with herbicides (1.3% of the total planted area with annual crops in the district). It was followed by Nkasi (0.8%) then Sumbawanga Urban and Mpanda had (0.4%) each (Chart 3.75). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 3,782 hectares which represented 1.3 percent of the total planted area for annual crops and vegetables. Cash crops had the largest planted area applied with fungicides (1,905ha, 50.4%) followed by cereals (909 ha, 24.0%), roots and tubers (340 ha, 9.0%), fruits and vegetables (276 ha, 7.3%), pulses (260 ha, 6.9%) and oil seeds (93 ha, 2.5%) (Chart 3.76). However, the proportion of planted area applied with fungicides was highest for cash crops and fruits and vegetables being 57.8% and 22.5% respectively. The proportion for roots and tubers was (1.2%), pulses (0.7%), cereals (0.4%) and oil seeds (0.3%). (Chart 3.77). 0.0 1.5 3.0 4.5 P ercent of Planted Area Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - TANGA 0.00 0.30 0.60 0.90 1.20 1.50 Sumbawanga Rural Nkasi Sumbawanga Urban Mpanda District Percent Chart 3.76 Planted Area Applied with Fungicides by Crop Type Cereals, 909, 24% Roots & T ubers, 340, 9% Pulses, 260, 7% Oil Seeds & Oil Nuts, 93, 2% Fruits & Vegetables, 276, 7% Cash Crops, 1,905, 51% 0.0 20.0 40.0 60.0 P ercent o f P la nted A rea Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 52 The annual crop with more than 40 percent fungicide use was tobacco (59%).Tomatoes had (34.4%), cassava (1.3%), beans (0.7%), maize (0.6%) and groundnuts (0.4%). Mpanda had the highest percent of planted area with fungicides (2.8% of the total planted area with annual crops in the district). This was followed by Sumbawanga Urban (2.2%). The smallest percentage use was recorded in Sumbawanga Rural and Nkasi districts being (0.2% and 0.7% respectively) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.2%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 89 percent of the total area planted with cereals during the long rainy season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1%, 0.1 percent and 0.2 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Rukwa region, the area of annual crops under irrigation was (7,523 ha) representing 2 percent of the total area planted (Chart 3.79). Some cereal crops such as maize and paddy were predominantly irrigated The district with the largest planted area under irrigation for annual crops was Sumbawanga Rural (5,487 ha, 73% of the total irrigated planted area with annual crops in the region). This was followed by Mpanda (844 ha, 11%), Sumbawanga Urban (730 ha, 10%) and Nkasi (462 ha, 6%). Chart 3.78 Proportion of Planted Area with Fungicides by District - RUKWA 0.0 0.6 1.2 1.8 2.4 3.0 Mpanda Sumbawanga Urban Nkasi Sumbawanga Rural District Percent Chart 2.80 Planted Area with Irrigation by District - RUKWA Region 0 2,000 4,000 6,000 Sumbawanga Rural Mpanda Sumbawanga Urban Nkansi District Ir r ig a t e d A r e a ( h a ) 0.0 1.6 3.2 4.8 P e r c e n t a g e Ir r ig a t io n Area Irrigated Land this Year Percentage of Irrigated Land Chart 3.79 Area of Irrigated Land Non-Irigated area, 294,921, 98% Irrigated Area, 7,523, 2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 When expressed as a percentage of the total area planted in each district Sumbawanga Rural had the largest area under irrigation at (4.1%). This was followed by Sumbawanga Urban (3.6%). Mpanda and Nkasi districts had (0.9%) each (Chart 3.80 and Map 3.40). Of all the different crops and in terms of proportion of the irrigated planted area, paddy was the most irrigated crop with 35 percent irrigation followed by maize (28%), cassava (17%), beans (5%) and tomatoes (2%). In terms of crop type, the area under irrigation for cereals was 10,470 hectares (69.4% of the total area under irrigation), followed by roots and tubers with 2,782 hectares (18.4%), pulses (754 ha, 5%), fruits and vegetables (601 ha, 4%), cash crops (273 ha, 1.8%) and oil seeds (218 ha, 1.4%). All of the irrigation for cereals was applied to paddy and maize The number of agricultural households practicing irrigation in Rukwa region appears to have decreased by (26.8%) from 8,958 agricultural households in 1995/96 to 6,561 agricultural households in 2002/03. This may not be statically significant due to the small number of households sampled with irrigation (Chart 3.81) 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from rivers (66% of households with irrigation). This was followed by wells (19%), canal (9%), boreholes (3%), dams (2%) and lake (1%). 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 65 percent of households using this method. This was far followed by hand bucket with 29 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.76). Gravity was used by most households with irrigation in Sumbawanga Rural (66%), followed by Sumbawanga Urban Chart 3.82 Number of Households with Irrigation by Source of Water Borehole, 435, 3% Dam, 344, 2% Lake, 148, 1% Well, 3,137, 19% Canal, 1,593, 9% River, 11,225, 66% River Well Canal Borehole Dam Lake Chart 3.81 Time Series of Households with Irrigation - RUKW A 6,561 8,958 0 3,000 6,000 9,000 12,000 1995/96 2002/03 Agriculture Year P la nted A rea ubder Irrig a tio n Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 4,974, 29% Gravity, 11,028, 65% Hand Pump, 133, 1% Other, 602, 4% Motor Pump, 146, 1% Gravity Hand Bucket Other Motor P ump Hand P ump RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 (13%), Mpanda (11%) and Nkasi (10%). Hand bucket was more common in Mpanda with 40 percent of households using the method to obtain water for irrigation, followed by Sumbawanga Urban (26), Sumbawanga Rural (23%) and Nkasi (11%). While the method of obtaining irrigation water by hand pumps was the most common method in Mpanda district, motor pump was the most common method of obtaining irigation water in Nkasi and Sumbawanga Urban. 3.6.4 Methods of Water Application Most households used flooding (67.4% of households using irrigation) as a method of field application. This was followed by hand bucket/watering can (30.3%). Water hose and sprinklers were not widely used as they were 1.5% and 0.8% of the households respectively. 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Rukwa region show that there were 164,147 crop growing households (95.3% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 152,974 households storing 43,758 tonnes as of 1st January 2004. This was followed by sorghum/millets (24,085 households, 9,873 tons), paddy (26,058 households, 5,923t), beans/pulses (70,698 households, 5,339t) and groundnuts/bambaranuts (32,955 households, 3,463t). Other crops were stored in very small amounts. Chart 3.84 Number of Households with Irrigation by Method of Field Application Flood, 11,381, 67.0% Sprinkler, 143, 0.8% Water Hose, 248, 1.5% Bucket / Watering Can, 5,111, 30.3% Flood Bucket / Watering Can Water Hose Sprinkler Chart 3.85 Number of Households and Q uantity Stored by Crop Type - RUKWA 0 40,000 80,000 120,000 160,000 M aize Sorghum & M illet Paddy Beans & Pulses G'nuts/B amb Nut W h eat Cottton Co ffee Cashewnut Tob acco Crop N u m b e r o f h o u s e h o ld s 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 Q u a n t it y ( t ) Number of households Quantity stored (Tons) RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.7.1.1 Methods of Storage The region had 120,769 crop growing households storing their produce in sacks/open drums (73.6% of households that stored crops in the region). The number of households that stored their produce in locally made traditional cribs was 41,282 (25.1%). This was followed by those that stored their produce in improved locally made cribs (765 households, 0.5%), unprotected piles (651 households, 0.4%), air tight drums (276 households, 0.2%), modern store (203 households 0.1%) and other (201 households, 0.1%). Sacks/open drums were the dominant storage method in all districts, with the highest percent of households in Sumbawanga Urban using this method (89% of the total number of households storing crop products). This is followed by Nkasi (81%), Sumbawanga Rural (74%) and Mpanda (66%) (Chart 3.80). The highest percent of households using locally made structures were in Mpanda and Sumbawanga Rural districts (32% and 25% of the total number of households storing crops respectively), followed by Nkasi (18.9%) and Sumbawanga Urban (8%) 3.7.1.2 Duration of Storage Most households (49.3% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (45.6%) and those households who stored the crop for the period of less than 3 months were (5.1%) (Chart 3.88) Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0.00 10.00 20.00 30.00 40.00 50.00 Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Quantity (tonnes) 0 5 10 15 20 25 30 35 % Stored Quantity Harvested Quantity Stored % stored Chart 3.86 Number of households by Storage Methods - RUKWA Sacks / Open Drum, 120,769, 73.6% Unprotected Pile, 651, 0.4% Airtight Drum, 276, 0.2% Modern Store, 203, 0.1% Other, 201, 0.1% Improved Locally Made Structure, 765, 0.5% Locally Made Traditional Structure, 41,282, 25% 0 20,000 40,000 60,000 80,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 Months 3 to 6 Months Over 6 Months RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mpanda district (58%) followed by Nkasi (49%), Sumbawanga Urban (46.2%) and Sumbawanga Rural (41.5%) (Map 3.41). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Sumbawanga Urban district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was probably determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 88.6 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at higher price (Chart 3.10). 3.7.1.4 The Magnitude of Storage Loss About 86.4 percent of households that stored crops had little or no loss; however the proportion of households that experienced a loss up to a quarter was 11.1 percent. (Table 3.10) The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (9.3% of the total number of households that stored crops). This was followed by maize (9.1%), groundnuts and bambaranut (5.4%), beans and pulses (2.9%) and paddy (1.1%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (94%) 3.10: Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Mpanda 54,498 3,163 402 269 58,332 Sumbawanga Rural 53,339 9,491 1,168 712 64,708 Nkansi 23,714 3,746 709 78 28,247 Sumbawanga Urban 10,228 1,885 577 169 12,859 Total 141,778 18,285 2,856 1,228 164,147 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses G'Nuts/Bamb Nuts Wheat Cottton Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other Sumbawanga Rural Sumbawanga Urban 46,242 59,911 24,110 81.47% 86.97% 79.17% 77.7% Mpanda Nkasi 10,835 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Sumbawanga Urban Sumbawanga Rural 41.5% 46.2% 48.8% 57.9% Mpanda Nkasi 54.7 to 57.9 51.4 to 54.7 48.1 to 51.4 44.8 to 48.1 41.5 to 44.8 Percent of Household Storing Crops Percent of Households Storing Crops For 3 to 6 Months by District MAP 3.37 RUKWA MAP 3.38 RUKWA Number of Households and Percent of Total Households Selling Crops by District Tanzania Agriculture Sample Census Percent of Household Storing Crops Percent of Households Selling Crops Number of Households Selling Crops Number of Households Selling Crops RESULT 57 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Rukwa region (167,155 households, 97% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 80%). Mpanda and Sumbawanga Rural had the lowest percent of households processing crops (96% and 97% of crop growing households respectively) (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households (133,195 households) processed their crops using neighbour’s machines, this representing 80 percent This was followed by those processing on-farm by hand (20,209 households, 12.1%), trader (9,585 households, 5.2%) and on-farm by machine (3,397 households, 2%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Rukwa region, however district differences existed. Mpanda has a higher percent of hand processing than other districts (17%), followed by Nkasi (14%), Sumbawanga Rural (9%) and Sumbaweanga Urban (2%). Processing by trader was more common in Sumbawanga Rurasl and Sumbawanga Urban (14.3% and 0.3% respectively), whilst processing on farm by machine was more prevalent in all four districts of Nkasi, Sumbawanga Urban, Sumbawanga rural and Mpanda (Chart 3.92). 0 20 40 60 80 100 Percent of Households Processing Nkansi Sumbawanga Urban Sumbawanga Rural Mpanda District Chart 3.91b: Percentage of Households Processing Crops by District Chart 3.92: Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Co-operative Union By Trader Other By Factory Chart 3.93 Percent of Households by Type of Main Processed Product Flour / M eal 92.8% Juice 0.1% Oil 1.7% Rubber 0.04% Grain 5.4% Chart 3.91a : Households Processing Crops Households Processing, 167,155, 97% Households Not Processing, 4,690, 3% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 155,071 households processing crops into flour (92.8%) followed by grain with 9,077 households (5.4%) and oil 2,751 households (1.7%). The remaining products such as juice and rubber were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 33.6 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 29,934 households (53.5%) followed by Husks (13,429 households, 23.9%), cake (7,281 households, 13%) and shell (4,131 households, 7.4%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Mpanda and Sumbawanga Rural were the only districts that used primary products as fuel for cooking. Chart 3.94 Number of Households by Type of By-product Fiber, 205, 0% Juice, 34, 0% Pulp, 484, 1% Husk, 13,429, 24% Cake, 7,281, 13% Oil, 201, 0% Shell, 4,131, 7% Other, 284, 1% Bran, 29,934, 54% Chart 3.95 Use of Processed Product Animal Consumption, 451, 0.2% Did Not Use, 710, 0.3% Sale Only, 3,510, 1.2% Fuel for Cooking, 912, 0.4% Household/ human consumption, 277,966, 97.7% 0.00 2.00 4.00 6.00 8.00 10.00 Percentage of households Mpanda Sumbawanga Rural Sumbawanga Urban Nkansi District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Secondary Market, 823, 7.7% Farmers Association, 568, 5.3% Local Market / Trade Store, 596, 5.6% Neighbours, 6,568, 61.5% Marketing Co- operative, 132, 1.2% Large Scale Farm, 34, 0.3% Trader at Farm, 1,851, 17.3% Other, 115, 1.1% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 Out of 10,687 households that sold processed products, 6,158 were from Mpanda (57.6% of the total number of households selling processed products in the region), followed by Sumbawanga Rural with 3,529 households (33%), Nkasi with 654 households (6.1%) and Sumbawanga Urban with 345 households (3.2%) (Chart 3.96). Compared to other districts in Rukwa region, Mpanga had the highest percent of households (10.8%) that sold processed products. This is followed by Sumbawanga Rural (5.3%), Sumbawanga Urban (2.6%), and Nkasi (2.2%). 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold them to neighbours (7,582 households, 35%), local market and trade stores (6,568 households, 61.5% of households that sold crops). This was followed by selling to trader at farm (1,851 households, 17.3%), secondary market (823 households, 7.7%), local market trade store (596 households, 5.6%), farm associations (568 households (5.3%), marketing co-operatives (132 households, 1.2%), other (115 households, 1.1%) and larege scale farms (34 households, 0.3%) and other places (115 households, 1.1%)(Chart 3.97). There are large differences between districts in the proportion of households selling processed products to neighbours with Mpanda district having the largest percentage (57.4%) and Sumbawanga Urban having the lowest (0.5%). Compared to other districts, Sumbawanga Rural had the highest percent of households selling processed products to traders at farm. Both Sumbawanga Rural and Urban districts sold processed produce to farmer associations most. The district which had the highest proportion of households selling processed products to marketing cooperative was Nkansi. 3.7.3 Crop Marketing The number of households that reported selling crops was 141,097 which represent 81.9 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Sumbawanga Rural (42%) followed by Mpanda (33%), Nkasi (17.1%) and Sumbawanga Urban (8%) (Chart 3.99 and Map 3.42) Chart 3.98 Percent of Households S elling Processed Products by Outlet for S ale and District 0% 20% 40% 60% 80% 100% Mpanda Sumbaw anga Rural Nkansi Sumbaw anga Urban District Percent of Households Selling Neighbours Local Market / T rade Store Marketing Co-operative Farmers Association Large Scale Farm T rader at Farm Secondary Market Other Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of roblem Open Market P rice Too Low 79% Other 0% No Transport 3% Farmers Association P roblems 0% Co-operative P roblems 0% No Buyer 0% Lack of Market Information 2% Transport Cost Too High 6% Market too Far, 9624, 10% Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 Sumbawanga Rural Mpanda Nkansi Sumbawanga Urban District Number of Households 0.0 30.0 60.0 90.0 Percent Number o f Ho us eho lds Selling Cro ps Percentage of Householdss Slling crops RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.7.3.1 Main Marketing Problems Open market price too low for agricultural produce was the main marketing problem reported by most households (78.1% of crop growing households) followed by longer distances to the markets (10.1%), high transport costs (5.7%), lack of transport (5.7%), lack of market information (2.1%) and other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell” which accounted for 90 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts in Rukwa region. 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Rukwa region very few agricultural households (7,365, 4.3%) accessed credit out of which 6,833 (93%) were male-headed households and 533 (7%) were female-headed households. In Nkasi district only female-headed households got agricultural credit whereas in Mpanda, Sumbawanga Rural and Sumbawanga Urban districts both male and female headed households accessed credit. (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Rukwa region were co-operatives 2,685 agricultural households (35.8% of the total number of households that accessed credit) this was followed by traders/trade stores (34.9%), family, friends and relatives (25.9%), private individuals (2.1%) and religious organization, NGO and projects (1.3%) (Chart 3.101). Co- operative and religious organization, NGO and projects were the sole source of agricultural credit in Mpanda and Sumbawanga Urban districts respectively. Family, Friends and Relatives provided agricultural credits in all four districts in the region (Chart 3.102). Table 3.12 Reasons for Not Selling Crop Produce Number of Household % Production Insufficient to Sell 96,997 90.0 Price Too Low 6,450 6.0 Other 2,652 2.5 Market Too Far 992 0.9 Trade Union Problems 303 0.3 Government Regulatory Board Problems 198 0.2 Farmers Association Problems 134 0.1 Total 107,725 100 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male % Female % Total District 4,552 94 270 6 4,821 Sumbawanga Rural 2,146 95 116 5 2,261 Nkansi 0 0 80 100 80 Sumbawanga Urban 135 67 67 33 202 Total 6,833 93 533 7 7,365 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on buying fertilizers (30%), this was followed by hiring labour (20%), buying seeds (18%) and agro-chemicals (17%). The proportion of agricultural credits intended to be used for buying tools/equipments, irrigation structures, and others was very low (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was that, credits were not available accounting to 31 percent of the agricultural households. This was followed by households reporting the lack of credit awareness (27%), the knowledge of credit (19%). Also other households did not want to go into debits (13%). The rest of the reasons were collectively less than 8 percent of the households. C hart 3.102: Num ber of Households Receiving C re dit by Main Source of C re dit and District 0% 20% 40% 60% 80% 100% Nkansi Sumbawanga Rural Sumbawanga Urban Mpanda District Percent of Households Family, Friend and Relative Co-operative T rader / T rade Store Private Individual Religious Organisation / NGO / Project C hart 3.101: Percentage Distribution of Households RecievingC redit by Main Source Co-operative 36% Trader / Trade Store 35% Private Individual 2% Religious Organisation / NGO / Project 1% Family, Friend and Relative 26% Chart 3.104 Reasons for not Using Credit (% of Households) Did not want to go into debt 13% Interest rate- cost too high 3% Did not know how to get credit 26% Difficult bureaucracy procedure 3% Credit granted- too late 0% Not available 32% Not needed 4% Don't know about credit 19% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Other, 270, 2% Irrigation Structures, 537, 4% Agro-chemicals, 2,210, 17% Fertilizers, 3,966, 30% Seeds, 2,353, 18% Labour, 2,594, 20% Tools / Equipment, 1,178, 9% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 9,046 (17% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Sumbawanga Rural having a relatively high proportion of households (20%) that received crop extension messages in the district followed by Mpanda (19%), Sumbawanga Urban (15%) and Nkasi (6%) (Chart 3.106 and Map 4.43). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (85%, 24,535 households). NGO/Development projects provided (10.3%), large scale farms (3%), co-operatives (1.1%).The remaining extension source of extension provided only (0.6%) Chart 3.107). However, district differences exist with the proportion of the households receiving extension advices from government services ranging from between 73 percent and 100 percent in Mpanda to 90 percent in Sumbawanga Urban. Chart 3.105 Number of Households Receiving Extension Advice Households Receiving Extension 9,046, 17% Households Not Receiving Extension 3,215, 83% Chart 3.106 Number of Households Receiving Extension by District 0 3,000 6,000 9,000 12,000 15,000 Sumbawanga Rural Mpanda Sumbawanga Urban Nkansi District Number of H ouseholds 0 10 20 30 Percent of Households Number of Households Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Other 1% Government 85% NGO / Development Project 10% Cooperative 1% Large Scale Farm 3% Chart 3.108 Number of Households Receiving Extension by Quality of Services Very Good, 2,657, 9.2% Poor, 1,675, 5.8% Average, 8,059, 27.9% Good, 16,539, 57.2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.8.2.2 Quality of Extension An assessment of the quality of extension indicated that 57.2 percent of the households receiving extension ranked the service as being good followed by average (27.9 %), very good (9.2%) and poor (5.8%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops. Because of this, some of the figures presented in this section may be slightly different from those in previous section on insecticides inputs use (Section 3.5). Data on sources of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Rukwa region farm yard manure was used by 19,966 households which represent 12 percent of the total number of crop growing households. This was followed by households using insecticides/fungicides (11.3%), inorganic fertilisers had (6.5%), improved seeds (5.2%) compost (1.9%) and herbicide (0.2%) (Table 2.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Rukwa mostly purchase from the local market/trade store (58.8% of the total number of inorganic fertiliser users) followed by co-operatives (24.3%) and crop buyers (12.1%). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Table 2.13 Use of Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm yard manure 19,966 11.6 152,375 88.4 Improved seeds 9,018 5.2 163,243 94.8 Pestcides/Fungicide 19,503 11.3 152,758 88.7 Inorganic fertiliser 11,103 6.5 160,960 93.5 Compost 11,103 6.5 160,960 93.5 Herbicide 269 0.2 171,991 99.8 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 58.8 24.3 12.1 3.5 1.2 0 2,000 4,000 6,000 8,000 Local Market / Trade Store Co-operative Crop Buyers Local Farmers Group Secondary Market S o u r c e o f I n o r g a n ic F e r t ilis e r Number of Households Sumbawanga Rural Sumbawanga Urban 19,434 1,964 11,454 1,911 14.87% 19.27% 6.37% 28.27% Mpanda Nkasi 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Sumbawanga Urban Sumbawanga Rural 2,002 11,351 13,859 1,834 157% 20.17% 67% 19.17% Mpanda Nkasi 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Household Receiving Crop Extension Services Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.39 RUKWA MAP 3.40 RUKWA Number and Percent of Crop Growing Households Using Improved Seed by District Tanzania Agriculture Sample Census Number of Household Receiving Crop Extension Services Percent of Number of Household Receiving Crop Extension Services Percent of Households Growing Crops Using Improved Seed Number of Households Growing Crops Using Improved Seed Number of Households Growing Crops Using Improved Seed RESULT 65 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 The source of inorganic fertiliser was mainly more than 10 km from the household with most households residing between 10 and 20 km from the source (29%), followed by between 3 and 10 km (28%), 20 km and above (20%), between 1 km and 3km (14%) and less than 1 km (9%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 69 percent of households responding to cost factors as the main reason for not using. In other words, it may be assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. More smallholders use inorganic fertilisers in Mpanda than in other districts in Rukwa region (83.4% of households using inorganic fertilisers), followed by Sumbawanga Urban (8.5%). Other districts use very little inorganic fertiliser. 3.9.3 Improved Seeds The percentage of households that used improved seeds was 5.2 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (55.9%) followed by co-operatives (20.9%) and crop buyers (12.3%). Other less important sources of improved seed are from neighbours (5.7%), local farmers groups (2.9%), development partners (1.4%) and large scale farms (0.9%) (Chart 3.111). Access to improved seed is better than access to chemical inputs with 30 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly used improved seeds are Mpanda (66.3 percent of the total number of households using improved seeds in Rukwa region), followed by Sumbawanga Rural (20.7%) and Sumbawanga Urban (8.7%) and Nkasi (4.3%) (Map 3.44). C hart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111 Number of Households by Source of Improved Seed 0.9 1.4 2.9 5.7 12.3 20.9 55.8 0 1,500 3,000 4,500 6,000 Local Market / T rade Store Co-operative Crop Buyers Neighbour Local Farmers Group Development Project Large Scale Farm Source of Improved Seed Number of Households RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchased them from locally produced by households’ (41.9% of the total number of fungicide users) and local farmers group (26.7%). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). However, Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 7 percent of households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 66 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Sumbawanga Urban district (36.1 percent of the total number of households that use fungicide in the region), followed by Sumbawanga Rural 32.1%), Mpanda (24.1%) and Nkasi (7.7%). 3.9 Tree Planting The number of households involved in tree farming was 29,439 representing 17.1 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allocated land was 2,101,632 trees. The average number of trees planted per household planting trees was 71 trees Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of H ouseholds Chart 3.113 Number of Households by Source of Insecticide/fungicide 41.9 26.7 8.6 8.5 7.5 5.8 1.0 0 1,000 2,000 3,000 4,000 Locally Produced by Household Local Farmers Group Crop Buyers Neighbour Secondary Market Local Market / Trade Store Large Scale Farm Source of Insecticide/fungicide Number of Households Chart 3.115 Number of Households with Planted Trees - RUKWA Households without Planted Trees, 142822, 83% Households with Planted Trees, 29439, 17% Sumbawanga Urban Sumbawanga Rural 2,830 1,138 1,146 9,983 14.1% 7.5% 2.1% 1.2% Mpanda Nkasi 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Number of Smallhohders Planted Trees Number and Percent of Smallholder Planted Trees by District MAP 3.41 RUKWA Tanzania Agriculture Sample Census Number of Smallhohders Planted Trees Percent of Smallhohders Planted Trees RESULT 68 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 The main species planted by smallholders is Eucalyptus (1,778,915, 85%), senna spp (222,188, 11%), Gravellia spp (58,385 trees, 3%), jacaranda spp (17,556 trees, 1% and afzelia quanzensis ( 10,399 trees, 0.5%). The remaining trees species are planted in comparatively small numbers (Chart116.). Sumbawanga Urban district has the largest number of planted trees than any other district (79.3%) and is dominated by Eucalyptus species. This is followed by Sumbawanga Rural (8.2%) which is dominated by Eucalyptus species, Nkasi (7.3%) and Mpanda (5.2%) which is mainly planted with Eucalyptus (Chart 3.117 and Map 3.45.). Smallholders mostly plant trees on the plantation or coppices. The proportion of trees that planted on field plantation or copies was 78 percent, followed by scattered around fields (12%) and then trees planted in a field or plot boundaries (10%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (35.9%). This is followed by wood for fuel (30.1%), shade (22.7%) and poles (9.8%), medicinal (1.1%), charcoal and other had (0.26%) each (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 16,883 which represent 10 percent of the total number of agricultural households in the region (Chart 3.120). C hart 3.118 Number of Trees Planted by Location Mostly on Field / Plot Boundaries, 4,272, 9.9% Mostly Scattered in Field, 5,027, 11.7% Mostly in Plantation / Coppice, 33,850, 78.4% Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Household Without Facilities, 155,378, 90% Household With Facilities, 16,883, 10% Chart 2.116 Number of Planted Trees by Species - RUKWA 0 400,000 800,000 1,200,000 1,600,000 2,000,000 Eucalyptus Spp Senna Spp Gravellis Jakaranda Spp Afzelia Quanzensis Cyprus Spp Acacia Spp Pinus Spp Azadritachta Spp Trichilia Spp Melicia excelsa Casurina Tectona Grandis Syszygium Spp Leucena Spp Calophylum Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and Region 0 180,000 360,000 540,000 720,000 900,000 1,080,000 Sumbawanga Urban Sumbawanga Rural Nkansi Mpanda District Number of Trees Eucalyptus Spp Senna Spp Gravellis Afzelia Quanzens is Cyprus Spp Acacia Spp P inus Spp Melicia excels a Cas urina Equis etfilia Tecto na Grandis J akaranda Spp Chart 3.119 Number of Households by Purpose of Planted Trees 0.00 10.00 20.00 30.00 40.00 Planks / T imber Fuel for Wood Shade Poles Medicinal Charcoal Other Use Percent of Households RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 The proportion of households with soil erosion control and water harvesting facilities was highest in Sumbawanga Urban district (16%) followed by Mpanda (12%) and Sumbawanga Rural (8%). Nkasi district had the lowest proportion of (5%) (Chart 3.121). Erosion control bunds accounted for 82.5 percent of the total number of structures, followed by water harvesting bunds (14%), drainage ditches (2.5%), tree belts (0.5%), dam (0.4%), terraces and vetiver grass had (0.1%) each. However, gabions/sandbags were not used in the district (Chart 3.122) and Map 3.46 Erosion control bunds and water harvesting bunds together had 261,070 structures. This represented 96.5 percent of the total structures in the region. The remaining 3.5 percentages were shared among the rest of the erosion control methods mentioned above. Mpanda and Sumbawanga Rural districts had 260,332 erosion control structures which is equivalent to 96.2 percent of the total erosion structures in the region. Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.0 0.1 0.1 0.4 0.5 2.5 14.0 82.5 0 50000 100000 150000 200000 250000 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches Tree Belts Dam Vetiver Grass Terraces Gabions / Sandbag T y p e o f F a c ilit y Number of Structures Chart 3.121 Number of Households With Erosion Control/Water Harvesting Facilities 12 8 16 5 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Mpanda Sumbawanga Rural Sumbawanga Urban Nkansi District Number of Households 0 5 10 15 20 Percent No of Households Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 504,727. Cattle were the most dominant livestock type in the region followed by goats, sheep and pigs. The region had 3.0 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Rukwa region was 504,345 (99.7 % of the total number of cattle in the region), 1,107 cattle (0.2%) were dairy breeds and 274 cattle (0.1%) were beef breeds. The census results show that 43,551 agricultural households in the region (25.3% of total agricultural households) kept 0.5 million cattle. Therefore, the average number of cattle per household was 12 (Chart 3.123 and Map 3.47). However Sumbawanga Urban district had the highest density (61 head per km2) (Map 3.48). Although Sumbawanga Rural district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle was very small and there was no beef cattle kept in the respective district. Mpanda district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Thirteen percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 37 percent of all cattle in the region. Only 14 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 50.2 percent of total cattle rearing households had herds of size 1-30 cattle and owns 50.1 percent of total cattle in the region, resulting in an average of 6 cattle per cattle rearing household. There were about 463 households with a herd size of more than 151 cattle each (123,239 cattle in total) resulting in an average of 266 cattle per household. 0 50,000 100,000 150,000 200,000 250,000 Number of Cattle ('000') Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 110,000 220,000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban Districts N u m b e r o f C a t t le Indigenous Improved Beef Improved Dairy RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.12.1.3 Cattle Population Trend Cattle population in Rukwa decreased during the period of eight years from 426,329 in 1995 to 378,338 cattle in 2003. This trend depicts an overall annual negative growth rate of -1.48 percent (Chart 3.125). However, there was a very sharp decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –2.55 percent whereby the number dropped from 426,329 to 384,410. Moreover, the number of cattle was estimated to have slightly decreased from 384,410 in 1999 to 378,338in 2003 at the rate of -1.48 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Rukwa region was 1,328 (1,107 dairy and 274 improved beef). The diary cattle constituted 0.2 percent of the total cattle and 88.4 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 20.6 percent of the total number of the improved cattle and 0.1 percent of the total cattle. The number of improved cattle increased from 448 in 1995 to 1,107 in 2003 at an annual growth rate of 12.10. The growth rate was higher for the period from 1995 to 1999 (63.54%) than from 1999 to 2003 when it dropped by -23.16 percent (Chart 126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Rukwa region ranked 16 out of the 21 regions with 2.5 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Rukwa region was 43,150 (25% of all agricultural households in the region) with a total of 292,849 goats giving an average of 7 head of goats per goat-rearing-household. Sumbawanga Rural district had the largest number of goats (118,607 goats, 40.5% of all goats in the region) followed by Mpanda (118,261 goats, 40.4%) and Nkasi (42,696 goats, 14.6%). Sumbawanga Urban district had the least number of goats (13,285 goats, 4.5%) (Chart 3.127 and Map 3.49) However both Sumbawanga Urban and Sumbawanga Rural districts had the highest density of goats (22 head per km2 ) each (Map 3.50). 426,329 384,410 378,338 - 150,000 300,000 450,000 N u m b er of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 448 3,176 1,107 - 1,500 3,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend 0 30,000 60,000 90,000 N u m b e r o f G o a t s ( '0 0 0 ') . Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Chart 3.127 Total Number of Goats ('000') by District RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 3.12.2.2 Goat Herd Size Forty nine percent of the goat-rearing households had herd size of 1-4 goats with an average of 2 goats per goat rearing household. Sixty six percent of total goat-rearing households had herd size of 1-14 goats and owned 66.3 percent of the total goats in the region resulting in an average of 5 goats per goat-rearing households. The region had 321 households (0.7%) with herd sizes of 40 or more goats each (16,877 goats in total), resulting in an average of 53 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.6 percent of the total goats in the region. Improved goats for meat and diary goats constituted 0.8 and 0.6 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 6.05 percent. This positive trend implies eight years of population increase from 183,041 in 1995 to 292,849 in 2003. The number of goats increased from 183,041 in 1995 at an estimated annual rate of 7.18 percent to 241,546 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 4.93 percent (Chart 128). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Rukwa region after cattle and goats. The region ranked 16 out of 21 Mainland regions and had 0.9 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 4,770 (2.8 % of all agricultural households in Rukwa region) rearing 36,073 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Mpanda with 13,967 sheep (38.7% of total sheep in Rukwa region) followed by Sumbawanga Rural (10,953 sheep, 30.4%) and Nkasi (10,756 sheep, 29.8%). Sumbawanga Urban district had the least number of sheep (397 sheep, 1.1%) (Chart 3.129 and Map 3.51). Sumbawanga Rural and Nkasi districts also had the highest density (2 head per km2 ) (Map 3.52) each.All sheep kept were indigenous breed 183,041 241,546 292,849 - 120,000 240,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 5,000 10,000 15,000 N u m b er o f s h eep Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Chart 3.129 Total Number of Sheep by District Sumbawanga Rural Sumbawanga Urban 44 61 29 5 Mpanda Nkasi 49.8 to 61 38.6 to 49.8 27.4 to 38.6 16.2 to 27.4 5 to 16.2 Sumbawanga Urban Nkasi Mpanda Sumbawanga Rural 36,156 149,080 82,871 236,620 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Number of Cattle Cattle Population by District as of 1st Octobers 2003 MAP 3.42 RUKWA MAP 3.43 RUKWA Cattle Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Cattle Population Number of Cattle of per Square Km Cattle Density RESULT 74 Sumbawanga Rural Sumbawanga Urban 8 7 22 22 Mpanda Nkasi 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 13,285 118,607 42,696 118,261 Mpanda Nkasi 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Number of Goats Goats Population by District as of 1st Octobers 2003 MAP 3.44 RUKWA MAP 3.45 RUKWA Goats Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Goats Population Number of Goats of per Square Km Goats Density RESULT 75 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at 22.92 percent. The population increased at an annual rate of 17.11 percent from 6,923 in 1995 to 13,021 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 22.92 percent (Chart 3.130). 3.12.4. Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 16 out of 21 Mainland regions and is 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Rukwa region was 12,101 (7% of the total agricultural households in the region) rearing 51,840 pigs. This gives an average of 4 pigs per pig-rearing household. The district with the largest number of pigs was Sumbawanga Rural with 36,455 pigs (70.3% of the total pig population in the region) followed by Nkansi (8,396 pigs, 16.2%), Mpanda (4,837 pigs, 9.3%) Sumbawanga Urban (2,152 pigs, 4.2%) (Chart 3.131 and Map 3.53). However Sumbawanga Urban district had the highest density (3.6 head per km2 ) (Map 3.54). 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population over the eight years period from 1995 to 2003 was 20.33 percent. During this period the population grew from 11,794 to 51,840. The pig population increased from 11,794 in 1995 to 22,341 in 1999 at a rate of 17.32 percent. The growth rate increased to 23.42 percent during the following four years from 1999 to 2003 in which pig population increased from 22,341 to 51,840 (Chart 3.132). 6,923 13,021 36,073 - 15,000 30,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 11,794 22,341 51,840 - 30,000 60,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 15,000 30,000 N u m b e r o f P ig s Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Chart 3.131 Total Number of Pigs by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 77 3.12.5 Chicken Production The poultry sector in Rukwa region was dominated by chicken production. The region contributed 3.4 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 109,912 raising about 1,122,432 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Rukwa region was ranked eighth out of the 21 Mainland regions. The District with largest number of chickens was Mpanda (492,601 chickens, 43.9% of the total number of chickens in the region) followed by Sumbawanga Rural (445,939 39.7%) and Nkasi (130,643, 11.6%). Sumbawanga Urban district had the smallest number of chickens (53,250, 4.7%) (Chart 3.133 and Map 3.55). However Sumbawanga Urban district had the highest density (90 chicken per km2 ) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 2.24 percent. The population decreased at a rate of - 2.15 percent from 1995 to 1999 after which it increased at a rate of 6.83 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Rukwa region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 86.5 percent of all chicken- rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 13.3 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 32chickens per holder. Only 0.22 percent of holders kept the flock sizes of 100 chickens or more at an average of 150 chickens per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 38,452 35.0 92,665 2 5-9 31,281 28.5 204,580 7 10 -19 25,278 23.0 321,753 13 20-29 6,961 6.3 155,776 22 30-39 4,248 3.9 136,546 32 40-49 2,087 1.9 87,172 42 50-99 1,365 1.2 87,994 64 100+ 240 0.2 35,946 150 Total 109,912 100 1,122,432 10 428,055 392,442 511,221 - 300,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 N u m b er o f C h ick en s Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Chart 3.133 Total Number of Chickens by District Sumbawanga Rural Sumbawanga Urban 2 0.7 2.1 0.8 Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 10,756 13,967 397 10,953 Mpanda Nkasi 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Sheep Sheep Population by District as of 1st Octobers 2003 MAP 3.46 RUKWA MAP 3.47 RUKWA Sheep Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Sheep Population Number of Sheep of per Square Km Sheep Density 1.9 to 2.1 1.6 to 1.9 1.3 to 1.6 1 to 1.3 0.7 to 1 RESULT 78 Sumbawanga Urban Sumbawanga Rural 3.6 6.8 1.6 0.3 Mpanda Nkasi 5.2 to 6.8 3.9 to 5.2 2.6 to 3.9 1.3 to 2.6 0 to 1.3 Sumbawanga Urban Sumbawanga Rural 2,152 36,455 8,396 4,837 Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Pig Pig Population by District as of 1st Octobers 2003 MAP 3.48 RUKWA MAP 3.49 RUKWA Pig Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Pig Population Number of Pig of per Square Km Pig Density RESULT 79 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Rukwa Region increased at an annual rate of 72.35 percent for the period of four years from 823 in 1999 to 7,261 in 2003. The number of improved chicken was most significant in Nkasi district followed by Sumbawanga Rural and Sumbawanga Urban districts (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 33.38 percent during which the population grew from 725 to 7,261. The annual growth rate was (72.35%) for the period of four years from 1995 to 1999. The broiler population exhibited an increasing trend at the rate of 63.59 percent per annum for the period of four years from 1995 to 1999 before decreasing at an annual rate of -50.67 from 1999 to 2003. The overall annual growth rate for broilers was -10.17 during the eight-years period from 1,450 chicken in 1995 to 615 chicken in 2003 (Chart 3.136). 3.12.6. Other Livestock There were 88,647 ducks, 2,686 turkeys, 17,876 rabbits and 11,190 donkeys raised by rural agricultural households in Rukwa region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Sumbawanga Rural district (45.5% of all ducks in the region), followed by Mpanda (43.3%) and Nkansi (10.5%). Sumbawanga Urban district had the least number of ducks estimated at 0.7 percent of total ducks in the region. Turkeys were reported in Sumbawanga Rural and Sumbawanga Urban districts only (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 64 percent and 11 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. (Chart 3.137) shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Mpanda district but lowest in Sumbawanga Rural district (Map 3.57). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Mpanda 38,381 0 5,650 4,265 0 Sumbawanga Rural 40,326 2,516 5,263 3,578 7,644 Nkasi 9,294 0 3,561 2,629 9,765 Sumbawanga Urban 646 170 3,402 718 0 Total 88,647 2,686 17,,876 11,190 17,409 725 1,450 823 10,385 7,261 615 - 4,000 8,000 12,000 N um ber o f la y ers 1995 1999 2003 Year Chart 3.136 Improved Chicken Population Trend 0 0 2,414 213 1,144 402 3,703 0 0 1,200 2,400 3,600 N u m b er o f C h ick en s Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 15 30 45 60 75 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Percent T icks T setseflies Sumbawanga Urban Sumbawanga Rural 89.7 83.2 25.7 27.9 Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 53,250 492,601 130,643 445,939 Mpanda Nkasi 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Number of Chicken Chicken Population by District as of 1st Octobers 2003 MAP 3.50 RUKWA MAP 3.50 RUKWA Chicken Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Chicken Population Number of Chicken of per Square Km Chicken Density 70 to 90 60 to 70 40 to 60 20 to 40 0 to 20 RESULT 81 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 The most practiced method of tick controlling was spraying with 35 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (4%), smearing (2%) and other traditional methods like hand picking (10%). However, 49 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 11 percent of livestock- rearing households This was followed by dipping (6%) and trapping (2%). However, 81 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 48,587 (57% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 38 percent, goats (32%), sheep (17%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 17,928, representing 30.8 percent of the total livestock-rearing households and 10.4 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 93.9 percent of all households receiving livestock extension services. The rest of the households got services from large-scale farmers (3.58%), Co- operatives and others provided (1%) each and NGO/developing Projects had (0.3). 0 20 40 60 P ercen t Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Average 23% Poor 4% No Good 3% Very Good 4% Good 66% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 6,000 12,000 Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District N u m b e r o f H o u se h o ld s Less than 14km More than 14km Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 34,807, 73% Less than 14km, 12,808, 27% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 83 About 66 percent of livestock rearing households described the general quality of livestock extension services as being good, 23 percent said they were average and 4 percent said they were very good and also 4 percent of livestock rearing households said the service was poor. Moreover, 3 percent of the livestock rearing households said the quality was not good (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 73.1 percent of the livestock rearing households accessed the services, at a distance of more than 14 kilometers. Only 26.9 percent of them accessed the services within 14 kilometers from their dwellings (Chart 3.140). The most affected district was Sumbawanga Rural with almost all livestock rearing households (89%) accessing the services at a distance of more than 14 kms. Sumbawanga Urban district was the least affected because about 36 percent of the households could access the service at a distance of more than 14 kilometers. (Chart 3.141). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 7,525 (78.8% of livestock rearing households in Rukwa region) whilst 443 households (4.6%) resided between 5 and 14 kms. However, 1,587 households (16.6%) had to travel a distance of 15 or more kms to f the nearest watering point (Chart 3.142). Mpanda and Nkansi districts had the best livestock water supply with all of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Sumbawanga Rural then Sumbawanga Urban districts. In Sumbawanga rural district about 38 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 6,000 12,000 Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District N u m b e r o f H o u se h o ld s Less than 14km More than 14km Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 34,807, 73% Less than 14km, 12,808, 27% Chart 3.142 Number of Households by Distance to Village W atering Points 15 or more kms, 1587, 16.6% 5-14 kms, 444, 4.6% Less than 5 kms, 7,525, 78.8% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 1,500 3,000 4,500 Mpanda Sumbawanga Rural Sumbawanga Urban Nkasi District Number of H ouseholds Less than 5 kms 5-14 kms 15 or more kms DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Rukwa region was relatively important with 79,406 households (46% of the total households in the region) using them (Chart 3.144). The number of households that used draft animals in Sumbawanga Rural was 47,115 representing 59 percent of the households using draft animals in the region, this was followed by Nkasi (16,622 households, 21%), Sumbawanga Urban (11,547 households, 15%) and Mpanda (4,121 households, 5%) (Chart 3.145 and Map 3.58). Proportionally, the district whose households used more draft animals was Sumbawanga Urban by (87%) followed by Sumbawanga Rural 68%) and Nkansi (55%). Mpanda district made the least use of draft animals (7%) of households only. The region used 247,856 oxen that cultivated 178,167 hectares. This represents only 5.9 percent of the total number of oxen found on the Mainland. Out of this (140, 521 oxen) were used in sumbawanga rural, Nkasi (55,435 oxen), Sumbawanga Urban (29,683 oxen) and Mpanda (22,217 oxen) The largest area cultivated using oxen was found in Sumbawanga Rural district (259,293 ha, 58.9% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of households using organic fertilizers in Rukwa region was 18,756 (11% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 30,877 hectares or (73.9% of the total area applied with fertilisers or (10.2 %) of the area planted with annual crops and vegetables in Rukwa region during the wet season) was applied with farm yard manure (Map 3.59). 0 16,000 32,000 48,000 N um ber o f H o useho lds Sumbawanga Rural Nkansi Sumbawanga Urban Mpanda District Chart 3.145 Number of Households Using Draft Animals by District - RUKWA 3.144 Number of Households Using Draft Amimals Using Draft Animals, 79,406, 46% Not Using Draft Animals, 92,855, 54% Chart 3.146 Number of Households Using O rganic Fertilisers Not Using Organic fertilisers, 158,442, 92% Using Organic fertilisers, 13819, 8% Chart 3.147 Area planted with the Application of Fertilisers - RUKWA 0 7,000 14,000 Sumbawanga Rural Sumbawanga Urban Nkasi Mpanda District A rea (H a ) o f F ertiliser A pplica tio n Farm Yard Manure Compost Sumbawanga Urban Sumbawanga Rural 11,547 47,115 4,121 16,622 86.8% 68.3% 54.5% 6.9% Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Sumbawanga Urban Sumbawanga Rural Nkasi 4,663 21,579 6,637 4,616 82.9% 62.5% 72.8% 41.1% Mpanda 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Household Infected with Ticks Number and Percent of Households Infected with Ticks by District MAP 3.52 RUKWA MAP 3.53 RUKWA Number and Percent of Households Using Draft Animals by District Tanzania Agriculture Sample Census Number of Household Infected with Ticks Percent of Household Infected with Ticks Percent of Households Using Draft Animal Number of Households Using Animal Draft Number of Households Using Animal Draft RESULT 85 Sumbawanga Urban Sumbawanga Rural 762 308 475 1,974 0.8% 0.6% 2.4% 1.5% Mpanda Nkasi 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Sumbawanga Urban Sumbawanga Rural 12,857 6,028 2,746 9.7% 25.4% 11.3% 2.9% Mpanda Nkasi 5,110 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Planted Area with Farm Yard Manure Applied Planted Area and Percent of Planted Area With Farm Yard Manure Application by District MAP 3.54 RUKWA MAP 3.55 RUKWA Planted Area and Percent of Planted Area With Compost Manure Application by District Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure Applied Percent of Planted Area with Farm Yard Manure Applied Percent of Planted Area with Compost Manure Applied Planted Area with Compost Manure Applied Planted Area with Compost Manure Applied RESULT 86 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 87 3.12.9.4 Use of Compost Only 1,721 hectares (5.4% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost manure was found in Sumbawanga Rural district with 16,082 hectares (67% of the total area applied with compost manure) followed by Sumbawanga urban (3,941 ha, 17%), Nkasi (313 ha, 12%) and Mpanda (109 ha, 4%) (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Rukwa region was 80, representing 0.05 percent of the total agricultural households in the region (Chart 3.148 and Map 3.61). Fish farming was practiced in Nkasi district only. No fish farming was practiced in any other district of Rukwa region. (Chart 3.149). The main source of fingerings was from the neighbours. All fish farming households in the region used the natural ponds. The number of fish harvested in Rukwa region was 8,018 all of them being tilapia by type. Eighty (80) fish were sold to traders at farm. Chart 3.148 Number of Households Practicing Fish Farming - RUKWA Households Not Practicing Fish Farmining, 172181, 99.9% Households Practicing Fish Farmining, 80, 0.05% 0 25 50 75 100 N umber of Households Nkasi Mpanda Sumbawanga Rural Sumbawanga Urban District Chart 3.149 Number of Households Practicing Fish Farming by District - RUKW A Chart 3.150 Fish Production Number of T ilapia, 8,018, 100% Number of Carp, 0, 0% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, tarmac roads were a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 185.2 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were regional capital (155.5 km), hospitals (71.6 km), tertiary markets (65.5 km), secondary schools (25.1 km), secondary market (22.4 km), primary markets (16.3 km), health clinics (8 km), all weather roads (5 km), primary school (2.1) and feeder road (1.1) (Table 3.15). Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Mpanda 27.7 2.9 4.3 1.1 74.4 7.0 283.7 23.3 27.3 70.2 303.4 Sumbawanga Rural 20.9 1.7 5.6 0.9 90.3 9.7 92.4 8.4 19.1 81.4 129.1 Nkasi 36.9 1.9 6.7 1.5 48.6 6.8 109.2 22.6 24.6 42.9 145.8 Sumbawanga Urban 8.2 1.1 1.0 1.1 15.1 5.7 15.4 10.9 12.2 14.3 37.0 Total 25.1 2.1 5.0 1.1 71.6 8.0 155.5 16.3 22.4 65.5 185.2 Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 29 percent reported them to be average. Twenty four percent of the agricultural households said the infrastructure and services were poor were , and 20 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households used traditional pit latrines (159,267 households, 92.5% of all rural agricultural households). Other types of toilets were used as follows: flush toilets (4,395 households (2.6%), improved pit latrines (1,376 households, 0.8%) and other toilets facilities (34 households, 0.02%). However, 7,189 households or (4.2%) had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicated that 67.6 percent of them were found in Sumbawanga Rural district and 20.5 percent were from Mpanda. The percentages of households without toilets in other districts were as follows Nkasi (6.7%) and Sumbawanga Urban (5.2%) Map 3.62). Chart 3.152 Percentage Distribution of Households Owning the Assets 3.0 0.6 0.5 0.5 0.2 13.7 37.5 41.8 0.0 15.0 30.0 45.0 Radio Bicycle Iron Wheelbarrow Vehicle Television / Video Mobile phone Landline phone Assets P ercent Chart 3.151 Agricultural Households by Type of Toilet Facility No Toilet / Bush, 7,189, 4.2% Improved Pit Latrine - hh Owned, 1,376, 0.8% Other Type, 34, 0.02% Flush Toilet, 4,395, 2.6% Traditional Pit Latrine, 159,267, 92.5% Sumbawanga Urban Sumbawanga Rural 480 1,477 371 4,861 1.6% 2.5% 7.1% 2.8% Mpanda Nkasi 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Sumbawanga Rural Sumbawanga Urban 80 0 0 0 0.3% 0% 0% 0% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Households Practicing Fish Farming Number and Percent of Households Practicing Fish Farming by District MAP 3.56 RUKWA MAP 3.57 RUKWA Number and Percent of Households Without Toilets by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming Percent of Households Without Toilets Number of Households Without Toilets Number of Households Without Toilets RESULT 89 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Rukwa region with 72,043 households (41.8% of the agriculture households in the region) owning the asset this was followed by bicycle ( 64,577 households, 37.5%), iron (23,642 households, 13.7%), wheelbarrows (5,199 households, 3.0%), vehicles (1,070 households, 0.6%), television/video (849 households, 0.5%), mobile phones (784 households, 0.5%) and landline phones (267 households, 0.2%) (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 76.6 percent of the total rural households using this source of energy followed by hurricane lamp (16.9%), pressure lamp (3.4%), firewood (2.6%), mains electricity (0.3%), candle (0.1%) and others (0.1%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.8 percent of all rural agricultural households in Rukwa region. This was followed by charcoal (3.0%), crop residues (0.2%) and livestock dung (0.02%) (Chart 3.154). 3.13.6 Roofing Materials The most common material for roofing for the main dwelling was grass and/or leaves which used by 75.4 percent of the rural agricultural households. This was far followed by iron sheets (18.6%), grass/mud (4.0%), asbestos (1.3%), tiles (0.6%) and concrete (0.1%) (Chart 3.155). Proportionally, Mpanda and Nkasi districts had the highest percentage of households with grass/leaves roofing (80.5%) each followed by Sumbawanga Rural district (71.6%). Sumbawanga Urban district had the lowest percentage (60.7%) of households with grass/leaves as rooting material (23%) (Chart 3.156 and Map 3.63) Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Grass/Mud 4% Grass/Leaves 75% Tiles 1% Concrete 0% Asbestos 1% Iron Sheets 19% Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 38.0 36.9 18.9 6.2 0.0 18.0 36.0 Sumbawanga Rural Mpanda Nkasi Sumbawanga Urban D is t ric t Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 131,944, 76.6% Firewood, 4,542, 2.6% Mains Electricity, 440, 0.3% Candles, 187, 0.1% Other, 154, 0.1% Pressure Lamp, 5,922, 3.4% Hurricane Lamp, 29,072, 16.9% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Charcoal, 5,185, 3.0% Crop Residues, 385, 0.2% Livestock Dung, 35, 0.02% Firewood, 166,657, 96.8% Sumbawanga Urban Sumbawanga Rural 3,684 11,368 468 4,052 5.9% 3.5% 12.1% 19.1% Mpanda Nkasi 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Sumbawanga Urban Sumbawanga Rural 24,538 47,907 8,078 49,355 80.5% 80.5% 71.6% 60.7% Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Using Grass or Leaves for Roofing Material Number and Percent of Households Using Grass/Leaves for Roofing Material by District MAP 3.58 RUKWA MAP 3.59 RUKWA Number and Percent of Households Eating 3 Meals per Day by District Tanzania Agriculture Sample Census Number of Households Using Grass or Leaves for Roofing Material Percent of Households Using Grass or Leaves for Roofing Material Percent of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day RESULT 91 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Rukwa region was protected wells which were used by 25 percent of the households during both the wet and dry seasons. This was followed by unprotected wells (24% of households during wet season and 26 percent during dry season), surface water (20% of households during the wet season) and 15% in the dry season), piped water (17% of households in the wet season and 15% during dry season) and unprotected spring water (10% of households in both the wet and dry seasons, protected/covered spring (2.4% of households in wet season and 2.5% of households in dry season. The remaining sources had below 1 percent of households in both wet and dry seasons respectively. Chart 3.157) About 55 percent of the rural agricultural households in Rukwa region obtained drinking water within a distance of less than one kilometer during wet season compared to 46 percent of the households during the dry season. However, 45 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 54 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Rukwa region normally had two (2) meals per day (81.8 percent of the households in the region). This was followed by three (3) meals per day (11.4%) and one (1) meal per day (6.7 percent). Only 0.05 percent of the households had (4) meals per day (Chart 3.159). Chart 3.158 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Distance P ercent Wet Seas o n Dry Seas o n Chart 3.159 Number of Agriculural Households by Number of Meals per Day One Meal, 11,622, 7% T hree Meals, 19,573, 11% Four meals, 82, 0.05% T wo Meals, 140,983, 82% Chart 3.157 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 P rotected Well Uprotected Well Surface Water (Lake / Dam / River / Stream) P iped WaterUnprotected Spring P rotected / Covered Spring Uncovered Rainwater Catchment Covered Rainwater Catchment Tanker Truck Other M a in s o urc e We t S e a s o n D ry S e a s o n DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 Sumbawanga Urban district had the largest percent of households eating one meal per day whilst Mpanda district had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.64) 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 93,105 (54.0% of the agricultural households in Rukwa region) out of which 49,584 households (53.3 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week 27,198 (29.2%). Very few households (16,323 households, 12.5%) had meat three or more times during the respective week. However, 79,156 (46.0 percent of the agricultural households in Rukwa region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 122,835 (71.3% of the total agricultural households in Rukwa region) of which 30,971 households (25.2% of those who consumed fish twice during the respective week. This was followed by those who had fish three times 17,793 (14.5%). In general, the percentage of households that consumed fish twice or more during the week in Rukwa region was 85,452 (69.6% of the agricultural households that ate fish in the region during the respective period). Moreover, 49,425 (28.7%) of the agricultural households in Rukwa region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66). 3.13.9 Food Security In Rukwa region, 55,848 households (32.4% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 11,957 (6.9%) said they sometimes experience problems, 13,212 (7.7%) often experienced problems and 8,509 (4.9%) always had problems in satisfying the household food requirement. However, 82,734 (48%) agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main source of cash income for the households in Rukwa region was from selling food crops (48.9 percent of smallholder households), followed by businesses income (16.0%), other casual cash earnings (14.2%), fishing (5.4%), sales of forest products (4.6%) and selling of cash crops (4.2%). Only (2.5%) of smallholder households reported the cash remittances as their main source of income, this was then followed by wages and salaries in cash (2.3%), sales of livestock (1.1%), other sales (0.5%) and sales of livestock products (0.2%) (Chart 3.161). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Mpanda 2,412 4.1 45,753 76.9 11,368 19.1 0 0 59,533 Sumbawanga Rural 5,766 8.4 59,117 85.8 4,052 5.9 0 0 68,935 Nkasi 950 3.1 25,767 84.5 3,684 12.1 82 0.3 30,483 Sumbawanga Urban 2,495 18.7 10,346 77.7 468 3.5 0 0.0 13,309 Total 11,622 6.7 140,983 81.8 19,573 11.4 82 0.05 172,261 Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 15,000 30,000 45,000 60,000 Once T wice T hree T imes Four T imes Five T imes Six T imes Seven T imes Frequency Number of Households Meat Fish Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Other 0% Livestock 1% Livestock Products 0% Cash Remittance 3% Forest Products 5% Cash Crops 4% Wages & Salaries 2% not applicable 0% Food Crops 50% Fishing 5% Other Casual Cash Earnings 14% Business Income 16% Sumbawanga Urban Sumbawanga Rural 13,023 3,645 13,719 6,996 21.9% 27.4% 19.9% 23% Mpanda Nkasi 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Sumbawanga Urban Sumbawanga Rural 4,117 7,828 19,522 18,118 5.9% 3.5% 12.1% 19.1% Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Number of Households Eating Meat Once per Week Number and Percent of Households Eating Meat Once per Week by District MAP 3.60 RUKWA MAP 3.61 RUKWA Number and Percent of Households Eating Fish Once per Week by District Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week RESULT 94 Mpanda Sumbawanga Urban Sumbawanga Rural 7,821 32,599 14,873 31,883 48.2% 56.6% 55.6% 53.5% Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Reporting Food Insufficiency Number and Percent of Households Reporting Food Insufficiency by District MAP 3.62 RUKWA Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency RESULT 95 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 RUKWA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Rukwa Rukwa has over 340,000 hectares of land under crops and is dominated by annual cropping. It has one a moderate to high available land area per crop growing household and the smallest percent utilized. Of the 3.0 ha per crop growing household land available only 2 ha was utilized. The number of crop growing households is moderate to low. The region has no short rainy season. Rukwa has a moderate planted area of cereals the majority of which is maize, however it is the fifth most important region in terms of the quantity produced. Beans and groundnuts are planted in moderate amounts and the region is the fourth most important in terms of quantity produced. Paddy is produced in moderate to small amounts compared to other regions and a small amount of sorghum is also produced. Cassava is produced in moderate to low amounts. Rukwa is not important for vegetable production; however a small amount of tobacco is grown. Rukwa has the smallest percentage of the total planted area of permanent crops in the country. The area under irrigation in Rukwa is moderate to low compared to other regions and the number of households with irrigation has not changed for 10 years. For the small number of households with irrigation, the source of irrigation water is mostly from rivers, the method of obtaining water is largely by gravity and application of the irrigation water is mostly by flood. More than half of the land cultivation is done by oxen and the region is one of the few regions using non manual cultivation methods. Fertilizer application is almost non existent and little pesticides are used. Rukwa stores a relatively large amount of maize mostly in sacks/open drums. A high percent of households in the region sells crops. Most processing is by neighbours machine and it also has one of the highest percentages of processing done by traders. Few households sell their processed crops, mostly to neighbours. Rukwa receives the second least amount of extension services per household. The region has a small number of planted trees by smallholder households, and most of these are eucalyptus. It has a moderate number of households with erosion control/water harvesting facilities and most of them are for erosion control. 4.2.1 Mpanda Mpanda district has a comparative large number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has no livestock only households or pastoralists. The most important livelihood activity for smallholder households in Mpanda district is Annual Crop Farming, followed by tree/forest resources, off-farm income, livestock keeping, Permanent crops, remittances and fishing/hunting and gathering. However, the district has the lowest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mpanda has a relatively high percent of female headed households (49%) and it has the highest average ages of the household head. With an average household size of 6 members per household it is slightly above the average for the region. Mpanda has a DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively low level of school attendance in the region. The literacy rates for the heads of household is also slightly lower than most of districts in the region. It has the smallest utilized land area per household (2.0 ha) and the allocated area is not fully utilized indicating that there is -low level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (1.5ha) attributed to the high number of smallholders in the district. The district is moderately important for maize production in the region with a planted area of over 43,000 ha, however the planted area per household is the lowest in the region. Paddy production is not important as it was not grown in the district and the production of sorghum is very small. Mpanda is the only district in the region which did not grow wheat. Cassava production though small but it is higher accounting for 39 percent of the quantity harvested in the region. Mpanda is the only district in the region that did not grow Irish potatoes. The production of beans in Mpanda is the second highest in the region with a planted area of 10,255 ha. Oilseed crops are important in Mpanda and groundnuts were grown in the district. Vegetable production is important in the district. It has the second largest planted area with tomatoes but lowest in cabbage production, chilies were not grown in the district, it accounts for 27 percent of the tomato production, 8 percent of the cabbage production. Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. Compared to other districts in the region, Mpanda has a moderate planted area with permanent crops which is dominated by Lime/lemon (3,866 ha), banana (694 ha) and mangoes (392 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is very small, however district differences exist. Mpanda has the second largest planted area with improved seed in Rukwa region and this is due to the higher planted area of vegetables. The district has moderate to low planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is inorganic manure. Compared to other districts in the region, Mpanda district has a lowest level of insecticide use. The use of fungicides, although small, was the highest compared to other districts. Virtually no herbicide was used. It has the smallest area with irrigation compared to other districts with 1,138 hectares of irrigated land. The most common source of water for irrigation is from rivers using hand buckets. Bucket and flood and are the most common means of irrigation water application and a very small amount of water hose irrigation is used. No sprinkler used for irrigation. The most common method of crop storage is in sacks/open drums; however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the largest number of households not selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The lowest percent of households processing crops in Rukwa region is found in Mpanda district and is almost all done by using by neighbours Machines. The district also has a higher percent of households selling processed crops to neighbours than other districts and no sales are neither to market co-operatives, farmer’s associations nor large scale farms. Although very small, access DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 to credit in the district is to both men and women and the main sources are co-operatives, traders/trade stores, and family friends and relatives. A comparatively larger number of households receive extension services in Mpanda and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Mpanda district by having planted 2,251 trees only and is mostly senna spp with some eucalyptus and gravellis. The highest proportion of households with erosion control and water harvesting structures is found in Mpanda district and is mostly erosion control bunds however it also has the highest number of water harvesting bunds than other districts. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat production is the highest when compared to other districts; also, it has the largest population of sheep in the region. It has the second smallest number of pigs in the region but highest number of chickens. Mpanda is the only district in the region which did not have layers. Big number of ducks but small number of rabbits and donkeys both are found in the district. The largest number of households reporting Tsetse and tick problems was in Mpanda district and it had the largest number of households de-worming livestock. The use of draft animals in the district is very small. There was no any household in the district who did practice fish farming. It has amongst the worst access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to all weather roads and regional capital. Mpanda district has the second lowest percent of households with no toilet facilities and it has the highest percent of households owning bicycles, vehicles and tv/video and mobile phones. It has the second lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the largest percent of households with grass roofs with 16.4 percent of households having iron sheets. The most common source of drinking water is from protected wells. It has the lowest percent of households having two and second lowest district with households having one meal per day compared to other districts and the highest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat but highest number of households that did not eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.2 Sumbawanga Rural Sumbawanga Rural district has the largest number of households in the region and it has a high percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very large number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Sumbawanga Rural district is Annual Crop Farming, followed by tree/forest resources. The district has the fourth highest percent of households with no off-farm activities although it has the fourth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sumbawanga Rural has a relatively high percent of female headed households (23%) and it has DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 one of the lowest average age of the household head in the region. With a household size of 5 members per household it is average for the region. Sumbawanga Rural has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. It has a highest utilized land area per household (2.7 ha) and 79.1 percent of the allocated area is currently being utilized. The district has the largest planted area in the region and the largest planted area per household (0.8ha in the wet season. The district is very important for maize production in the region with a planted area of over 65,900 ha, and the planted area per maize growing household is also moderate for the region. The district has the second largest planted area of paddy in the region with 11,605 hectares. Sorghum is also grown in the district. Cassava production is moderate to high, accounting for 25.2 percent of the quantity harvested in the region. The district has a very small planted area of Irish potatoes (49 ha). The production of beans in Sumbawanga Rural district is higher with a planted area of 17,142 ha. Sumbawanga Rural district has the second largest groundnut planted area in Rukwa region with a planted area per groundnut growing household of 0.27 ha. Vegetable production is moderately important in the district. Although small, it has the largest planted area with tomatoes and cabbage and chilies (245 ha and 60 ha respectively). A traditional cash crop (e.g. tobacco) was grown in very small quantities. No cultivation of cotton in the district Compared to other districts in the region, Sumbawanga Rural has the largest planted area with permanent crops which is dominated by sugarcane (1,356 ha), banana (758 ha) and Mango (155 ha). As with other districts in the region, most land clearing is done by hand slashing; however there is a substantial area with no land clearing indicating bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Sumbawanga Rural has the largest planted area with improved seed in the region as well as the highest proportion of households using improved seeds. Though small, the district has the second highest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts in the region, Sumbawanga Rural district has a moderate level of insecticide use. The use of fungicides and herbicides is low. It has the largest area with irrigation compared to other districts with 9,983 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity methods. Flood is the most common means of irrigation water application followed by bucket/watering can and a very small amount of water hose is used. The most common method of crop storage in Sumbawanga Rural district is in sacks/open drums, however the proportion of households not storing crops is slightly above for the region. Sumbawanga Rural has the highest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Sumbawanga Rural is among the districts with the lowest percent of households processing crops in Rukwa region and is almost all done by neighbours machine. The district also has the second highest percent of households selling processed crops to neighbours as well as to traders at farm than other districts and no sales is to marketing co-operatives or large scale farms. Access to credit in the district though small but it was second in the region. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 100 A comparatively larger number of households receive extension services in Sumbawanga Rural district and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is relative important in Sumbawanga Rural (with 3,551 planted trees) and is mostly Eucalyptus, jacaranda and senna spp. The highest proportion of households with erosion control and water harvesting structures is found in Sumbawanga Rural district and is mostly erosion control bunds and water harvesting bunds, however it also has the a number of drainage ditches, tree belts dams terraces and vetiver grasses. The district has the largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts; however it has the second largest population of sheep in the region. It has the largest number of pigs in the region and a moderate number of chickens. Some ducks, rabbits and donkeys are also found in the district. A number of households reported tsetse and tick problems and it has the second largest number of households de-worming livestock. A small number of households use draft animals, however it is the highest in the region. No any households in the district who did practice fish farming. It has amongst the best access to feeder roads, primary schools, all weather roads, primary markets and health clinics compared to other districts. However, it has one of the worst accesses to tarmac roads. The percentage of households without toilet facility in Sumbawanga Rural district is comparatively low. It is amongst the districts with the highest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is grass/leaves (72%), however it has the second highest percent of households with iron sheet roofing (19%) compared to most other districts. The most common source of drinking water is from unprotected springs. It is one of the districts with the moderate percent of households having three meals per day. The district had one of the lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Nkasi Nkasi district has the third largest number of households in the region and it has moderate to higher percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It one of the districts with very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Njkasi district is Annual Crop Farming, followed by tree/forest resources, off-farm income, livestock keeping, fishing/hunting/gathering, remittances and permanent crops. However, the district has the highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Nkasi a relatively high percent of female headed households (13%) and it has one of the highest averages of the household head in the region. With an average household size of 5 members per household it is the average for the region. Nkasi has a comparatively DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 101 high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The land area utilized per household (2.4 ha) is above the average for the region which is estimated at 2.0 hectares.75 percent of the allocated area is currently being utilized which is moderate to high for the region. Sumbawanga Rural and Nkasi utilizing 2.7 and 2.5 ha per household respectively. The smallest land area utilised per household was found in Mpanda and Sumbawanga Urban with (2.0 ha) each. The percentage utilized of the usable land per household was highest in Sumbawanga Urban (86.2%) and lowest in Mpanda (63.2%). Seventy three percent of the total land available to smallholders was utilised. Only 27 percent of usable land available to smallholders was not The district is moderately important for maize production in the region with a planted area of over 28,000 ha and the planted area per household is 1.03 ha which is slightly above of average for the region. Paddy production is not important with a planted area of only 1,416 hectares; however it is the third highest in the region. Sorghum, Irish potatoes and wheat are all produced in the district. The district has the second largest planted area of cassava accounting for 27 percent of the cassava planted area in the region. The production of beans in Nkasi is second lower in the region with a planted area of 6,810ha. Oilseed crops are relative important in Nkasi with 8.1 percent of the groundnuts grown in the district. Vegetable production is not important and tobacco was grown in the district. Permanent crops are very important in Nkasi district (24.6% of the total permanent crop planted area in Rukwa region ) and are more important than any other district in the region. The most prominent permanent crops in the district include mangoes (2,020 ha), sugarcane (74 ha), bananas (66 ha) and coconuts (16 ha). It has one of the lowest area with oranges in the region (4 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is very small, however district differences exist. Muheza has the smallest planted area with improved seed in Rukwa region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and practically all is with farm yard manure. Compared to other districts in the region, Muheza district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively small. It has one the smallest area with irrigation in the region with 1,146 ha of irrigated land. The most common source of water for irrigation is from rivers and wells and almost all water application is by using flood and hand buckets. The most common method of crop storage is in Nkasi is by using sacks or open drums and locally made traditional cribs, and the proportion of households not storing crops in the district is moderate to low for the region. The district has the third highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Nkasi district has a high percent of households processing crops in the region and is almost all done by neighbour machines; however, there was no any household in the district who did process crops by trader. Small quantities of processed crops are sold and very few households have access to credit. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 A moderate number of households receive extension services in Nkasi district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Nkasi district (with 3,148 planted trees) and is mostly Eucalyptus spp with some Senna Spp and Jacaranda Spp. The lowest proportion of households with water harvesting bunds is found in Nkasi district and it also has the third highest number of erosion control bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the second largest number of pigs in the region and the second lowest number of chickens, all of which are indigenous. Virtually no broilers chicken was found in the district. The district has one of the smallest number of ducks, and a small number of rabbits and turkeys are found in the district. A moderate number of households reported tsetse and problems in Nkasi district. A relative small amount of de-worming of livestock is practiced in the district. Draft animals are used in the district. Fish farming is practiced by a small number of households; however it is the only district which did practice fish farming in the region. It has amongst the best access to feeder roads, all weather roads, and health clinics compared to other districts. However, it has one of the worst accesses to tarmac roads and the regional capital. The percentage of households without toilet facility in Nkasi district is below the average for the region; however it has the lowest percent of households with no toilet facilities. It has the lowest percent of households owning vehicles and second highest owing tvs/video but NO land line phones. It has the second highest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the highest percent of households with grass roofs (81%) and only 16 percent of households have iron sheet roofing. The most common source of drinking water is from unprotected wells. Forty four percent of the households in the district reported having one or two meals per day and virtually 82 household reported having more than three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Sumbawanga Urban Sumbawanga Urban district has an average number of households for the region and it has the smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Sumbawanga Urban district is annual crop farming followed by trees/forest resources. It has the second highest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sumbawanga Urban district has a relatively high percent of female headed households (13%) and it has one of the highest average ages of the household head. With an average household size of 5.4 members per household it is average for the region. Sumbawanga Urban district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 It has the second smallest utilized land area per household (2.0 ha) and only 86.2 percent of the allocated land area is utilized. The total planted area is the smallest in the region however it has the second lowest planted area per household (0.61ha in the wet season. Sumbawanga Urban district is not important for maize production in the region with a planted area of only 12,341 ha, and the planted area per household is among the lowest in the region. Paddy production is also not important as there was no any cultivation of paddy in the district hectares and the production of sorghum is small. Cassava and bean production in Rukwa district was small and Irish potato and wheat are also grown. Oilseed crops and vegetables are not important in the district however, whist the district has one of the smallest planted area with tomatoes it is the first in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Sumbawanga Urban district has the smallest planted area with permanent crops (5.7% of total permanent crop planted area) which is dominated by sugarcane (346 ha), banana (272ha), A small area of orange and coconut are grown. Apart from a minor amount of coffee, lime/lemon and guavas no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. The use of inputs in the region is very small, however district differences exist. Sumbawanga Urban district has the smallest planted area with improved seed; however it has the lowest planted area per household in the region. The district also has the second smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts in the region, Sumbawanga Urban district has the second highest area planted with insecticide but has the lowest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the lowest for herbicides. It has one of the largest areas of irrigation 2,830 ha. The most common source of water for irrigation is from rivers using gravity. Floods and watering cans are the most common means of irrigation water application. The most common method of crop storage is in sacks/open drums; however the proportion of households not storing crops in Sumbawanga Urban district is one of the highest in the region. The number of households selling crops in the district is also among the biggest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The second biggest percent of households processing crops in the region is found in Sumbawanga Urban district and processing is mostly done by neighbours machine. The district has the smallest number of households processing crops on farm by machine. It also has the lowest number of households processing crops on farm by hand. Most households that sell crops sell to farmers association, traders on farm and large scale farms, but, no sales on local market/trade stores, secondary market nor marketing co-operatives. Access to credit in the district is very small. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 104 A very small number of households receive extension services in Sumbawanga Urban district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming though small but it is important in Sumbawanga Urban district (with 34,199 planted trees) and almost all of them are Eucalyptus Spp. The largest proportion of households in Sumbawanga Urban district use terraces for erosion control. Sumbawanga Urban district has the smallest number of cattle in the region and most of them are indigenous. It is one of the districts with the least number of goats in the region, however the district has the highest density (87 head per km2) Rukwa is also one of the districts with the smallest number of sheep, pigs and chicken, however it has the largest number of improved chickens (layers) in the region, broilers are not raised in the district. Small numbers of ducks, rabbits, turkeys and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Sumbawanga Urban district and it had one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and very few households practice fish farming. It is amongst the districts with the best access to secondary schools, primary schools, feeder roads, all weather roads, health clinics, hospitals, regional capital, tarmac roads and tertiary markets compared to other districts. However, it has the worst access to primary and secondary markets. Sumbawanga Urban district has though small number of households with no toilet facilities but it is the second highest in the region. The district has the highest percent of households owning wheel barrows, vehicles and television/video, land line and mobile phones and it has the second highest percent of households with radio, bicycles and irons. It has one of the smallest numbers of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the lowest percent of households with grass roofs with 33 percent of households having iron sheets. The most common source of drinking water is piped water and it has the highest percent of households having one meal per day and third with households having two meals per day compared to other districts and the fourth lowest percent with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration but has the second lowest percent of households that did not eat fish. Most households seldom had problems with food satisfaction. APPENDIX II 105 4. APPENDICES APPENDIX I TABULATION LIST...................................................................................................................106 APPENDIX II TABLES..........................................................................................................................................123 APPENDIX III QUESTIONNAIRES....................................................................................................................267 APPENDIX II 106 NUMBER OF AGRICULTURAL HOUSEHOLDS...............................................................123 2.1 Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year..............................................................................................................124 2.2 Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year.............................................................................................................124 HOUSEHOLDS DEMOGRAPHS............................................................................................125 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year........................................................126 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District.....................................................................................................126 3.2 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year.............................................................................................................127 3.3 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year.............................................................................................................127 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year .................................................................................................................................128 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year..........128 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year.........................................................................128 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year.............................................................................................................128 cont…. Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year.............................................................................................................129 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year..........................................................129 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year..........................................................................130 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.............................................131 3.1a First Most Importance .....................................................................................................132 3.1b Second Most Importance.................................................................................................132 3.1c Third Most Importance....................................................................................................132 APPENDIX II 107 3.1d Fourth Most Importance..................................................................................................132 3.1e: Fifth Most Importance.....................................................................................................133 3.1f: Sixth Most Importance ....................................................................................................133 3.1g Seventh Most Importance................................................................................................133 LAND ACCESS/OWNERSHIP................................................................................................135 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year...............................................................................................136 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year .................................................................................................................................136 LAND USE..................................................................................................................................137 5.1 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year.............................................................................................................138 5.2 Area of Land (ha) by type of Land Use and District for 2002/03 Agricultural Year......138 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.........................................................139 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ...........................................139 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ...........................................139 ANNUAL CROP AND VEGE PRODUCTION ....................................................................141 7.1 & 7.2a Number of Crop Growing Households and Planted Area (ha) by season and District 142 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District ........142 7.1 & 7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year ......................................................................................................143 7.1 & 7.2d: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year ......................................................................................................144 7.1 & 7.2h Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region...................145 7.1 & 7.2e Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Wet & Dry Seasons- Rukwa Region...............................145 APPENDIX II 108 7.1 & 7.2f Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region.............146 7.1 & 7.2g Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region............146 7.1 $ 7.2j: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year WET SEASON ................................................147 7.1&7.2k: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - WET & DRY SEASONS ........................147 7.1a Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Rukwa Region......................148 7.1b Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - DRY SEASON,Rukwa Region.................................................................148 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, DRY SEASON, Rukwa Region. ........................................................................148 7.1d Number of Crop Growing Households and Planted Area By Pesticide Use and District, DRY SEASON, Rukwa Region. .......................................................................149 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District, DRY SEASON, Ruwa Region ..........................................................................149 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District DRY SEASON, Rukwa Region. .......................................................................150 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, DRY SEASON..................................................................................................150 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, WET SEASON, Rukwa Region..............................................151 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District WET SEASON, Rukwa Region........................................................................151 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During WET SEASON ......................................................................................151 7.2d Number of Crop Growing Households and Planted Area By Insecticide Use and District WET SEASON, Rukwa Region.........................................................................152 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District WET SEASON, Rukwa Region.........................................................................152 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03..............................................................................................................152 APPENDIX II 109 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 WET SEASON, Rukwa Region........................................................................153 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, WET SEASON, Rukwa Region.......................................................................153 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year154 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year................................................155 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.5 Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year...............................158 7.2.6 Number of Crop Growing Households, Planted Area (ha) and Wheat Harevsted (tons) by season and District 2002/03 Agricultural Year................................................158 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year................................................158 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year...............................158 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year...............................159 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.13 Number of Crop Growing Households, Planted Area (ha) and Cowpeas Harevsted (tons) by season and District 2002/03 Agricultural Year................................................160 7.2.14 Number of Crop Growing Households, Planted Area (ha) and Green Gram Harevsted (tons) by season and District 2002/03 Agricultural Year...............................160 APPENDIX II 110 7.2.15 Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year...............................160 7.2.16 Number of Crop Growing Households, Planted Area (ha) and Field Peas Harevsted (tons) by season and District 2002/03 Agricultural Year................................................160 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.20 Number of Crop Growing Households, Planted Area (ha) and Soya Beans Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year................................................163 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year...............................163 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year...............................163 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year................................................163 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year...............................164 PERMANENT CROPS .................................................................................................................165 7.3 Production of Permanent Crops by Crop Type and District, Rukwa Region..................166 APPENDIX II 111 AGROPROCESSING ...................................................................................................................171 8.0a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year..............................................................................172 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District......172 8.1.1 Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop ....................................173 8.1.1a Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop ....................................174 8.1.1 Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop....................175 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop176 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District .............................................................................................................178 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District, Rukwa Region. .................................................178 8.1.1f Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District..........................................................................................179 8.1.1g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District, Rukwa Region....................................................................................179 MARKETING ...........................................................................................................................................181 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03, Rukwa Region.........................................................................182 10.2 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District ......................................182 10.3 Proportion of Households who Reported Not Selling Their Crops by District During 2002/03 Agricultural Year, Rukwa Region.....................................................................182 IRRIGATION/EROSION CONTROL ...................................................................................................183 11.1: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year By District ...........................................................................................184 11.2: Area (ha)of Irrigated and Non Irriga (ha) Land By District............................................184 APPENDIX II 112 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District................................................................184 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District.............................................................................................................184 11.5 Number of Households Using Irrigation By Method of Irrigation Application By District.............................................................................................................................185 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District..............................................................................................................185 11.7 Number of Erosion Control Harvesting Structures By Type and District.......................185 ACCESS TO FARM INPUTS .................................................................................................................187 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year.............................................................................................................189 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year .................................................................................................................................189 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................189 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year...............................................................................................190 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year...............................................................................................190 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year...............................................................................................190 12.1.10 Number of Agricultural Households and Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year...............................................................................................191 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year.............................................................................................................191 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................191 APPENDIX II 113 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................192 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................192 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year............................................................................193 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year.................................................................................193 12.1.16 Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year............................................................................193 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................194 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................194 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ..............................................................194 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year............................................................................195 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year............................................................................195 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year .................................................................195 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................196 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................196 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year............................................................................196 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year...............................................................................................197 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year.............................................................................................................197 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year.................................................................................197 APPENDIX II 114 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year...........................................................197 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ..............................................................198 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ..............................................................198 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides /Fungicides by District, 2002/03 Agricultural Year........................................................199 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year............................................................................199 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................199 AGRICULTURE CREDITS .....................................................................................................201 13.2a: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District .......................................................................................................................202 13.2c: Number of Households Receiving Credit By Source of Credit By District ....................202 13.1a: Number of Households Receiving Credit By Reason for Not Using Credit By District203 13.1b: Number of Credits Received By Main Purpose of Credit and District ............................203 TREE FARMING AND AGROFORESTRY ..........................................................................205 14.1: Number of Planted Trees By Species and District, Rukwa Region ................................205 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District.........................................................................................205 14.3: Main Use of Trees By District.........................................................................................205 14.4: Number of Households By Distance to Community Planted Forest (Km) By District...207 14.5: Number of responses by second use of planted trees and District for the 2002/03.........207 14.6 Number of responses by main use of planted trees and District for the 2002/03 agricultural year, Rukwa Region.....................................................................................207 CROP EXTENSION ..................................................................................................................209 15.1 Number of Households Receiving Extension Messages By District ..............................210 APPENDIX II 115 15.1 Number of Households By Quality of Extension Services By District During the 2002/03 agricultural year, Rukwa Region.......................................................................210 15.3 Number of Households By Source of Crop Extension Messages By District During 2002/03 Agricultural Year, Rukwa Region.....................................................................210 15.4 Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................211 15.5: Number of Households By Receivingf Advice on the Use of Agro-chemicals By Source of Messages By District Rukwa Region..............................................................211 15.6: Number of Households By Receivingf Advice on the Erosion Control By Source of Messages By District Rukwa Region..............................................................................211 15.7: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................212 158: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........212 15.9: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........212 15.9: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................213 15.11: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........213 15.12: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........213 15.13: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Rukwa Region.........................................214 15.14: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .......................214 15.15: Number of Households By Receivingf Advice on Agro-Forestry By Source of Messages By District during 2002/03 agricultural year, Rukwa Region.........................................214 15.16: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .............................................215 15.17: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .......................215 15.18: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Rukwa Region..............................215 APPENDIX II 116 15.19: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Rukwa Region...............216 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Rukwa Region...............216 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 4) During the 2002/03 Agricultural Year, Rukwa Region...............217 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Rukwa Region. ...............217 ANIMAL CONTRIBUTION TO CROP PRODUCTION .....................................................219 17.1: Number of Households Using Draft Animal to Cultivate Land By District During 2002/03 agricultural year, Rukwa Region.......................................................................220 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year................................................................................................220 17.3 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year................................................................................................221 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year..............................................................................................................221 CATTLE PRODUCTION .........................................................................................................223 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Rukwa Region .......................................................................................................224 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03...........................................................................224 18.4.1 Number of Cattle by Category and Type of Cattle as of 1st October 2003.....................224 18.2 Number of Cattle By Type and District as of 1st October, 2003 ....................................225 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003..................................................................................................................225 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................225 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................226 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................226 GOAT PRODUCTION..............................................................................................................227 19.1: Total Number of Goats by Type and District as of 2st October, 2003............................228 APPENDIX II 117 19.2: Total Number of Households Rearing Goats and Heads of Goats by Herd size on 1st October 2003...................................................................................................................228 19.:3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District.............................................................................................................................229 19.4 Number of Indigenous Goat by Category and District as of 1st October, 2003..............229 19.5: Number of Improved Meat Goat by Category and District as of 1st October, 2003.......229 19.6: Number of Improved Dairy Goat by Category and District as of 1st October, 2003......230 19.7: Number of Total Goat by Category and District as of 1st October, 2003.......................230 SHEEP PRODUCTION.............................................................................................................231 20.1: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year..............232 20.2: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year .................................................................................................................................232 20.3: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03.................232 20.4: Number of Sheep per Household by Category and district as of 1st October 2003........232 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003............233 20.6: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year................................................................................................233 20.8 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year..............................................................................................................233 PIGS PRODUCTION ................................................................................................................235 21.1 Number of Households Raising Pig by District during 2002/03 Agriculture Year.........236 21.2: Number of Households Raising Pig by District during 2002/03 Agriculture Year.........236 21.3: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003............236 LIVESTOCK PESTS AND PARASITE CONTROL .............................................................237 22.1 Number of Livestock Rearing Households deworming Livestock by District during 2002/03 Agricultural Year............................................................................................. 238` 22.2: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock............238 APPENDIX II 118 22.3: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ......238 22.4: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year ....................238 OTHER LIVESTOCK...............................................................................................................239 23a: Total number of Other Livestock by Type as of 1st October 2003.................................240 23b: Number of chicken by Category of Chicken and District as of 1st October, 2003 .........240 23d: Number of households with chicken and Category of Chicken by Flock Size ...............240 23c: Number of Households Rearing and number of Other Livestock by Type and District .240 FISH FARMING ........................................................................................................................241 28.1a: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year.............................................................................................................242 28.2a: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year.............................................................................................................242 28.2b Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year.............................................................................................................242 28.2c: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year.............................................................................................................242 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year.......242 LIVESTOCK EXTENSION......................................................................................................243 29.1a: Number of Agricultural Households Receiving Advice By District during the 2002/03 Agricultural Year.............................................................................................................244 29.1b Number of Households By Source of Extension and District, 2002/03 Agricultural Year244 29.1c Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year..............................................................244 29.1d Number of Agricultural Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year..........................................................................245 29.1e Number of Agricultural Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year..............................................................245 29.1f Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year..................................245 APPENDIX II 119 29.1g Number of Agricultural Households Receiving Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ........................................246 29.1h Number of Agricultural Households Receiving Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year ...............................246 29.1i Number of Agricultural Households Receiving Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.................................................................................246 29.1j Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year...............................................247 29.1j Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year...............................................................................................247 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES...........................................249 33.01a: Mean distances from horders dwellings to Infrastructures and services by District ......250 33.01b: Mean distance from holders dwellings to infrastrures and services by District.............251 33.01c: Mean distance from holders dwellings to all Weather roads by District........................251 33.01d: Mean distance from holders dwellings to Feeder Roads by District..............................251 33.01e: Mean distance from holders dwellings to Hospital by District ......................................252 33.01f: Mean distance from holders dwellings to Health Clinic by District...............................252 33.01g: Mean distance from holders dwellings to Primary School by District...........................252 33.1h: Number of Households to Regional Capital....................................................................252 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year.............................................................................................................253 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year .................................................................................................................................253 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year .................................................................................................................................253 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year .................................................................................................................................253 SATISFACTION OF USING VETERINARY CLINIC............................................................... 33.19b Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year.............................................................................................................254 APPENDIX II 120 33.19c Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year.............................................................................................................254 33.19d Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year...............................................................................................255 33.19e Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year...............................................................................................255 33.19f Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year ..........................................256 33.19G Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year.............................................................................................................256 HOUSEHOLD FACILITIES ...................................................................................................................257 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year..............................................................................................................258 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year............................................................................258 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year .............................................................................................258 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year..............................................................................................259 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year...............................................................................................259 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.................................................260 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.........................................260 34.8 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year.....................261 34.9 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year.....................261 34.10 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District.................................................................................................262 34.11 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District.............................................................................................262 APPENDIX II 121 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District.............................................................................................263 34.13 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.............................................................................263 34.14 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year...............................................................................................264 34.15.1 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year..............................................................................................................264 34-16 Number of Households by Main Source of Income and District, 2002/03 Agricultural Year ................................................................................................................................265 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year.............................................................................................................266 APPENDIX II 122 APPENDIX II: CROPS Type of Agriculture Household.................................................................................................................. 121 Number of Agriculture Households ............................................................................................................123 Rank of Importance of Livelihood Activities..............................................................................................125 Households Demography ............................................................................................................................129 Land Access/Ownership..............................................................................................................................137 Land Use………………..............................................................................................................................139 Total Annual Crop and Vege Production Long and short Seasons.............................................................143 Annual Crop and Vege Production Long Rainy Seasons............................................................................151 Permanent Crop Production.........................................................................................................................167 Agro-processing .................................................................................................................................177 Marketing .................................................................................................................................181 Irrigation/Erosion Control ...........................................................................................................................183 Access to Farm Inputs ................................................................................................................................ 187 Agriculture Credit .................................................................................................................................203 Tree Farming and Agro-forestry..................................................................................................................207 Crop Extension .................................................................................................................................211 Animal Contribution to Crop Production ....................................................................................................221 Cattle Production .................................................................................................................................225 Goat Production .................................................................................................................................229 Sheep Production .................................................................................................................................233 Pig Production .................................................................................................................................237 Livestock Pests and Parasite Control...........................................................................................................239 Other Livestock .................................................................................................................................243 Fishing Farming .................................................................................................................................245 Livestock Extension .................................................................................................................................247 Access to Infrastructure and other services .................................................................................................255 Household Facilities .................................................................................................................................263 Appendix II 123 NUMBER OF AGRICULTURAL HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 124 Mpanda 59,533 80 1,212 2 60,745 82 13,476 18 74,221 Sumbawanga 68,935 90 2,874 4 71,809 94 4,892 6 76,701 Nkasi 30,483 73 4,048 10 34,531 83 6,945 17 41,476 Sumbawanga 13,309 44 336 1 13,645 45 16,825 55 30,470 Total 172,261 77 8,469 4 180,730 81 42,138 19 222,868 Number % Number % Number % Number % Mpanda 47,900 42 0 0 11,633 20 59,533 35 59,533 59,533 0 Sumbawanga 38,769 34 416 100 29,751 51 68,935 40 68,935 68,520 416 Nkasi 19,786 17 0 0 10,697 19 30,483 18 30,483 30,483 0 Sumbawanga 7,614 7 0 0 5,695 10 13,309 8 13,309 13,309 0 Total 114,069 100 416 100 57,776 100 172,261 100 172,261 171,845 416 Total % of Total Rural Households Total Number of Households (From 2002 Pop Census) 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year District Type of Agriculture Household Total Number of Agricultural Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock Crops Only Livestock Only % of Total Rural Households Total Rural Households Crops & Livestock 2.1 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households % of Total Rural Households Urban Households District Rural Households Involved in Agriculture % of Total Rural Households Rural Households NOT Involved in Agriculture Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 125 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 126 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Mpanda 327,178 52,383 6 30,191 7,150 4 357,369 59,533 6 Sumbawanga Rural 321,441 60,260 5 33,267 8,675 4 354,708 68,935 5 Nkasi 145,125 26,660 5 13,259 3,824 3 158,384 30,483 5 Sumbawanga Urban 65,457 11,599 6 6,351 1,710 4 71,808 13,309 5 Total 859,201 150,902 6 83,068 21,359 4 942,269 172,261 5 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 1 5 4 3 6 7 2 Sumbawanga Rural 1 6 4 3 5 7 2 Nkasi 1 7 4 3 6 5 2 Sumbawanga Urban 1 6 4 3 5 7 2 Total 1 7 4 6 3 5 2 Table. 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture sample Census - 2003 Rukwa Appendix II 127 Number % Number % Number % Less than 4 84,200 50 84,323 50 168,523 100 05 - 09 78,168 50 78,480 50 156,649 100 10 - 14 68,091 51 65,523 49 133,614 100 15 - 19 50,935 51 48,417 49 99,352 100 20 - 24 36,308 47 41,500 53 77,808 100 25 - 29 34,203 47 38,194 53 72,397 100 30 - 34 29,158 54 24,656 46 53,814 100 35 - 39 20,352 47 22,881 53 43,234 100 40 - 44 20,166 53 18,053 47 38,219 100 45 - 49 17,029 55 13,959 45 30,988 100 50 - 54 11,148 55 8,976 45 20,123 100 55 - 59 7,123 55 5,779 45 12,902 100 60 - 64 6,290 63 3,721 37 10,010 100 65 - 69 3,878 39 6,170 61 10,048 100 70 - 74 3,314 53 2,944 47 6,258 100 75 - 79 2,943 69 1,329 31 4,272 100 80 - 84 2,274 80 560 20 2,834 100 Above 85 664 54 559 46 1,223 100 Total 476,244 51 466,024 49 942,269 100 Number % Number % Number % Less than 4 84,200 18 84,323 18 168,523 18 05 - 09 78,168 16 78,480 17 156,649 17 10 - 14 68,091 14 65,523 14 133,614 14 15 - 19 50,935 11 48,417 10 99,352 11 20 - 24 36,308 8 41,500 9 77,808 8 25 - 29 34,203 7 38,194 8 72,397 8 30 - 34 29,158 6 24,656 5 53,814 6 35 - 39 20,352 4 22,881 5 43,234 5 40 - 44 20,166 4 18,053 4 38,219 4 45 - 49 17,029 4 13,959 3 30,988 3 50 - 54 11,148 2 8,976 2 20,123 2 55 - 59 7,123 1 5,779 1 12,902 1 60 - 64 6,290 1 3,721 1 10,010 1 65 - 69 3,878 1 6,170 1 10,048 1 70 - 74 3,314 1 2,944 1 6,258 1 75 - 79 2,943 1 1,329 0 4,272 0 80 - 84 2,274 0 560 0 2,834 0 Above 85 664 0 559 0 1,223 0 Total 476,244 100 466,024 100 942,269 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 128 Number % Number % Number % Mpanda 181,669 51 175,700 49 357,369 100 Sumbawanga Rur 180,938 51 173,770 49 354,708 100 Nkasi 78,286 49 80,098 51 158,384 100 Sumbawanga Urb 35,352 49 36,456 51 71,808 100 Total 476,244 51 466,024 49 942,269 100 Number % Number % Number % Number % Number % Mpanda 170,079 58 6,374 2 133 0 118,192 40 294,777 100 Sumbawanga Rur 161,987 56 12,498 4 357 0 113,807 39 288,649 100 Nkasi 74,949 57 6,426 5 80 0 49,956 38 131,411 100 Sumbawanga Urb 36,843 63 2,087 4 63 0 19,916 34 58,909 100 Total 443,857 57 27,385 4 634 0 301,870 39 773,745 100 Number % Number % Number % Number % Mpanda 85,137 29 112,331 38 97,309 33 294,777 100 Sumbawanga Rur 76,336 26 108,360 38 103,952 36 288,649 100 Nkasi 34,921 27 51,883 39 44,606 34 131,411 100 Sumbawanga Urb 17,898 30 23,288 40 17,724 30 58,909 100 Total 214,292 28 295,862 38 263,591 34 773,745 100 Number % Number % Number % Number % Mpanda 159,510 54 5,653 2 0 0 2,168 1 Sumbawanga Rur 159,114 55 4,927 2 0 0 4,441 2 Nkasi 69,264 53 3,084 2 80 0 4,085 3 Sumbawanga Urb 29,198 50 642 1 0 0 70 0 Total 417,086 54 14,306 2 80 0 10,764 1 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed School Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English y Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Fishing 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District p Farming Keeping / Pastoralist Main Activity Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 129 Self Employed (Non Farmimg) without Unpaid Family Helper (Non Agriculture) Not Working & Available Not Working & Unavailable Housemaker / Housewife Number % Number % Number % Number % Number % Mpanda 4,945 2 6,049 2 133 0 132 0 1,077 0 Sumbawanga Rural 3,053 1 7,261 3 100 0 112 0 538 0 Nkasi 2,288 2 554 0 0 0 0 0 71 0 Sumbawanga Urban 1,080 2 1,453 2 0 0 0 0 307 1 Total 11,365 1 15,317 2 233 0 244 0 1,993 0 Number % Number % Number % Number % Mpanda 83,953 28 23,434 8 134 0 294,777 100 Sumbawanga Rural 73,975 26 29,323 10 226 0 288,649 100 Nkasi 33,226 25 17,600 13 92 0 131,411 100 Sumbawanga Urban 17,383 30 7,486 13 34 0 58,909 100 Total 208,537 27 77,843 10 486 0 773,745 100 Number % Number % Number % Number % Number % Mpanda 141,045 48 5,710 2 102,728 35 45,295 15 294,777 100 Sumbawanga Rural 151,379 52 12,759 4 75,999 26 48,511 17 288,649 100 Nkasi 66,110 50 7,032 5 31,508 24 26,761 20 131,411 100 Sumbawanga Urban 27,383 46 1,197 2 22,139 38 8,190 14 58,909 100 Total 385,917 50 26,698 3 232,375 30 128,756 17 773,745 100 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Student Unable to Work / Too Old / Retired Other Total cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 130 Number % Number % Number % Number % Mpanda 269 0 1,077 1 5,312 5 4,661 4 Sumbawanga Rural 0 0 456 0 2,482 2 4,011 4 Nkasi 0 0 695 1 1,144 2 1,410 3 Sumbawanga Urban 104 0 238 1 982 4 747 3 Total 374 0 2,466 1 9,920 3 10,829 4 Number % Number % Number % Number % Number % Mpanda 73,010 65 535 0 937 1 390 0 0 0 Sumbawanga Rural 82,194 76 338 0 340 0 0 0 235 0 Nkasi 35,628 69 455 1 222 0 82 0 70 0 Sumbawanga Urban 16,180 69 69 0 101 0 0 0 34 0 Total 207,011 70 1,398 0 1,600 1 472 0 339 0 Number % Number % Number % Number % Number % Mpanda 269 0 0 0 1,708 2 0 0 135 0 Sumbawanga Rural 682 1 223 0 2,466 2 241 0 89 0 Nkasi 283 1 70 0 545 1 0 0 217 0 Sumbawanga Urban 135 1 0 0 202 1 0 0 34 0 Total 1,369 0 293 0 4,922 2 241 0 476 0 Number % Number % Number % Mpanda 0 0 6,044 5 112,331 100 Sumbawanga Rural 0 0 1,471 1 108,360 100 Nkasi 72 0 2,020 4 51,883 100 Sumbawanga Urban 33 0 717 3 23,288 100 Total 105 0 10,252 3 295,862 100 cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Form Six Training After Secondary Education cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Form Two Form Three Form Four University & Other Tertiary Education Adult Education Total District Form One cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Standard Three 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Standard Seven Standard Eight Training After Primary Education Pre Form One District Under Standard One Standard One Standard Two Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 131 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 132 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 50923 134 269 6285 918 354 926 Sumbawanga Rural 56737 101 699 7005 454 3190 617 Nkasi 25570 82 247 1650 222 2420 152 Sumbawanga Urban 9947 166 301 2188 443 69 233 Total 143176 483 1516 17128 2037 6033 1928 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 7,688 7,799 8,388 21,165 1,589 892 12,822 Sumbawanga Rural 11,340 2,461 18,179 15,049 3,077 2,225 16,708 Nkasi 3,972 715 7,213 12,696 879 1,895 3,421 Sumbawanga Urban 2,794 743 3,374 3,999 336 35 2,270 Total 25,794 11,717 37,154 52,909 5,881 5,047 35,222 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 521 6,842 7,574 8,417 1,067 1,045 29,510 Sumbawanga Rural 429 4,188 10,528 11,035 5,462 453 33,603 Nkasi 708 390 3,473 9,129 1,572 138 14,288 Sumbawanga Urban 437 745 1,906 2,704 710 35 5,983 Total 2,095 12,166 23,482 31,285 8,811 1,671 83,384 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 0 4,356 7,754 2,536 1,180 647 13,111 Sumbawanga Rural 210 5,111 7,900 11,754 5,311 1,068 13,694 Nkasi 151 1,349 5,192 3,947 1,112 292 10,663 Sumbawanga Urban 97 1,028 1,614 1,328 1,407 0 3,469 Total 459 11,844 22,459 19,565 9,011 2,007 40,937 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 133 District Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 748 2,677 917 0 110 2,494 Sumbawanga Rural 3,377 2,981 4,597 2,837 1,059 2,267 Nkasi 1,485 1,707 610 705 0 1,635 Sumbawanga Urban 652 578 443 674 0 1,019 Total 6,262 7,942 6,567 4,216 1,169 7,415 District Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 0 244 244 0 0 0 Sumbawanga Rural 1,170 239 334 701 223 111 Nkasi 244 227 46 0 73 82 Sumbawanga Urban 102 0 69 370 0 134 Total 1,516 710 693 1,072 295 327 District Annual Crop Farming Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 266 0 0 132 0 Sumbawanga Rural 0 111 0 118 119 Nkasi 0 0 0 73 0 Sumbawanga Urban 0 33 35 35 0 Total 266 144 35 358 119 3.1e: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census - 2003 Rukwa 134 Appendix II 135 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 136 Households with Area Owned Under Customary Law Households with Area Bought From Others Households with Area Rented From Others Households with Area Borrowed From Others Households with Area Shared Croped From Others Households with Area under Other Forms of Tenure Total Number of Households No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % % Mpanda 1,476 2 44,634 75 12,473 21 5,225 9 4,886 8 536 1 1,330 2 59,533 Sumbawanga Rural 1,119 2 55,844 81 20,170 29 8,505 12 7,183 10 240 0 2,336 3 68,935 Nkasi 471 2 25,449 83 6,969 23 713 2 3,735 12 322 1 740 2 30,483 Sumbawanga Urban 239 2 11,267 85 3,819 29 655 5 954 7 139 1 665 5 13,309 Total 3,305 2 137,194 80 43,431 25 15,099 9 16,758 10 1,238 1 5,072 3 172,261 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Mpanda 3,939 133,807 38,583 5,601 4,323 639 1,810 188,703 Sumbawanga Rural 3,245 162,802 50,391 12,332 8,478 85 4,202 241,535 Nkasi 927 85,792 14,801 1,546 7,377 1,215 682 112,339 Sumbawanga Urban 264 22,409 6,112 930 805 140 441 31,102 Total 8,376 404,810 109,887 20,409 20,983 2,079 7,135 573,679 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Land Access District Land Access/ Ownership (Hectare) 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Households with Area Leased/Certificate of Ownership Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 137 LAND USE Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 138 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households Fallow Households with Natural Bush Households with Planted Trees Households with Rented to Others Households with Unusable Households with Uncultivated Usable Land Total Number of Households Mpanda 45,386 35,834 2,219 4,819 6,373 1,052 7,942 5,732 5,498 1,736 3,873 32,355 59,533 Sumbawanga Rural 62,466 15,414 7,672 3,297 2,652 1,052 15,549 2,927 3,371 3,093 2,894 27,258 68,935 Nkasi 22,834 12,502 1,025 787 968 736 6,658 896 2,590 1,395 3,352 13,406 30,483 Sumbawanga Urban 11,239 6,488 1,799 309 639 300 2,179 517 3,846 337 859 4,008 13,309 Total 141,925 70,239 12,714 9,212 10,632 3,140 32,328 10,071 15,306 6,562 10,978 77,028 172,261 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Mpanda 55,296 36,591 452 2,369 5,973 2,319 9,225 10,678 2,341 2,299 3,702 57,458 188,703 Sumbawanga Rural 117,391 19,238 3,419 4,179 4,539 1,667 32,616 5,155 1,209 4,943 3,058 44,733 242,146 Nkasi 39,362 14,666 314 1,511 1,851 4,131 11,735 1,127 1,501 2,274 5,267 28,600 112,339 Sumbawanga Urban 14,667 5,917 712 105 260 324 2,159 282 987 1,056 713 3,920 31,102 Total 226,716 76,412 4,897 8,164 12,623 8,441 55,734 17,243 6,038 10,572 12,739 134,711 574,291 % 39 13 1 1 2 1 10 3 1 2 2 23 100 District Land Use Area 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Type of Land Use 5.2 LAND USE: Area of Land (ha) by type of Land Use and District for 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 139 Total Total Number % Number % Number Number Percent Number Percent Number Mpanda 17,480 29 42,054 71 59,533 Mpanda 41,743 70 17,790 30 59,533 Sumbawanga Rural 27,846 41 40,674 59 68,520 Sumbawanga Rural 43,553 64 24,966 36 68,520 Nkasi 11,375 37 19,109 63 30,483 Nkasi 18,324 60 12,160 40 30,483 Sumbawanga Urban 6,850 51 6,459 49 13,309 Sumbawanga Urban 5,302 40 8,007 60 13,309 Total 63,550 37 108,295 63 171,845 Total 108,922 63 62,923 37 171,845 Number % Number % Number Percent Mpanda 41,743 70 17,790 30 59,533 100 Sumbawanga Rural 43,553 64 24,966 36 68,520 100 Nkasi 18,324 60 12,160 40 30,483 100 Sumbawanga Urban 5,302 40 8,007 60 13,309 100 Total 108,922 63 62,923 37 171,845 100 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Yes No Was all Land Available to the Hh Used During 2002/03? 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total Tanzania Agriculture Sample Census - 2003 Rukwa 140 Appendix II 141 ANNUAL CROP AND VEGETABLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 142 Dry Season Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 158400 96231 96231 0.0 Sumbawanga Rural 474 863 177594 132698 133561 0.6 Nkansi 160 130 74856 53306 53436 0.2 Sumbawanga Urban 104 56 32727 20109 20166 0.3 Total 738 1049 443,577 302,344 303,393 0.3 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Mpanda 0 59533 59533 0 59533 Sumbawanga Rural 118 68817 67939 996 68935 Nkansi 80 30403 30403 80 30483 Sumbawanga Urban 35 13274 13240 69 13309 Total 233 172027 171,116 1,145 172,261 District 7.1 & 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District Total Number of Crop Growing Households Wet Season Dry Season 7.1 & 7.2a: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) by season and District District Total Area Planted (hectare) % Area planted in Dry season Wet Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 143 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 427 155 363 203,500 240,468 1,182 203,928 240,623 1,180 Maize 427 155 363 149,606 163,277 1,091 150,033 163,432 1,089 Paddy 0 0 0 25,526 49,520 1,940 25,526 49,520 1,940 Sorghum 0 0 0 7,405 9,942 1,343 7,405 9,942 1,343 Bulrush Millet 0 0 0 17 20 1,186 17 20 1,186 Finger Millet 0 18,967 15,798 833 18,967 15,798 833 Wheat 0 0 0 1,979 1,911 966 1,979 1,911 966 ROOTS & TUBERS 0 0 28,595 45,702 1,598 28,595 45,702 1,598 Cassava 0 0 0 25,611 39,818 1,555 25,611 39,818 1,555 Sweet Potatoes 0 0 0 2,681 4,699 1,753 2,681 4,699 1,753 Irish Potatoes 0 0 0 282 1,031 3,653 282 1,031 3,653 Yams 0 0 0 13 127 9,485 13 127 9,485 Cocoyam 0 0 0 7 27 3,952 7 27 3,952 PULSES 279 44 156 37,551 17,567 468 37,831 17,610 466 Mung Beans 0 0 0 0 0 0 0 0 0 Beans 279 44 37,251 17,265 463 37,530 17,308 461 Cowpeas 0 0 0 68 47 687 68 47 687 Green Gram 0 0 0 102 151 1,482 102 151 1,482 Chich Peas 0 0 0 0 0 0 0 0 0 Bambaranuts 0 0 0 108 93 865 108 93 865 Field Peas 0 0 0 23 11 494 23 11 494 OIL SEEDS & OIL NUTS 343 217 634 28,178 17,201 610 28,520 17,419 611 Sunflower 295 146 11,463 5,957 520 11,758 6,103 519 Simsim 0 0 0 65 35 540 65 35 540 Groundnuts 48 71 16,522 11,055 669 16,570 11,126 671 Soya Beans 0 0 0 127 154 1,208 127 154 1,208 Castor Seed 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 0 0 0 1,225 4,211 3,437 1,225 4,211 3,437 Okra 0 0 0 0 0 0 0 0 0 Radish 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 0 0 0 Onions 0 0 0 266 1,139 0 266 1,139 4,279 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 176 739 0 176 739 4,212 Tomatoes 0 0 0 583 2,136 0 583 2,136 3,665 Spinnach 0 0 0 51 68 0 51 68 1,336 Carrot 0 0 0 3 7 0 3 7 2,134 Chillies 0 0 0 0 0 0 0 Amaranths 0 0 0 125 110 0 125 110 879 Pumpkins 0 0 0 22 12 0 22 12 540 Cucumber 0 0 0 0 0 0 0 0 0 Egg Plant 0 0 0 0 0 0 0 0 0 Water Mellon 0 0 0 0 0 0 0 0 0 CASH CROPS 0 0 0 3,295 3,263 990 3,295 3,263 990 Pyrethrum 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 39 13 0 39 13 329 Tobacco 0 0 0 3,256 3,251 0 3,256 3,251 998 Jute 0 0 0 0 0 0 0 0 0 Total 1,049 302,344 303,393 Table 7.1 & 7.2c: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Crop Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Number of Households Area Planted (ha) Number of Households Area Planted (ha) CEREALS 233 427 220,959 203500 203,928 0.2 Maize 233 427 159160 149606 150033 0.3 Paddy 0 0 30132 25526 25526 0.0 Sorghum 0 0 10613 7405 7405 0.0 Bulrush Millet 0 0 82 17 17 0.0 Finger Millet 0 0 18635 18967 18967 0.0 Wheat 0 0 2337 1979 1979 0.0 ROOTS & TUBERS 0 0 64889 28595 28595 0.0 Cassava 0 0 53929 25611 25611 0.0 Sweet Potatoes 0 0 9530 2681 2681 0.0 Irish Potatoes 0 0 1364 282 282 0.0 Yams 0 0 33 13 13 0.0 Cocoyam 0 0 34 7 7 0.0 PULSES 233 279 78866 37551 37831 0.7 Mung Beans 0 0 78216 0 0 0.0 Beans 233 279 151 37251 37530 0.7 Cowpeas 0 0 120 68 68 0.0 Green Gram 0 0 0 102 102 0.0 Chich Peas 0 0 0 0 0 0.0 Bambaranuts 0 0 266 108 108 0.0 Field Peas 0 0 112 23 23 0.0 OIL SEEDS & OIL NUTS 272 343 65842 28178 28520 1.2 Sunflower 153 295 19960 11463 11758 2.5 Simsim 0 0 357 65 65 0.0 Groundnuts 118 48 44997 16522 16570 0.3 Soya Beans 0 0 528 127 127 0.0 Castor Seed 0 0 0 0 0 0.0 FRUITS & VEGETABLES 0 0 1225 1225 0.0 Okra 0 0 0 0 0 0.0 Radish 0 0 0 0 0 0.0 Bitter Aubergine 0 0 0 0 0 0.0 Onions 0 0 0 266 266 0.0 Ginger 0 0 0 0 0 0.0 Cabbage 0 0 1032 176 176 0.0 Tomatoes 0 0 3499 583 583 0.0 Spinnach 0 0 420 51 51 0.0 Carrot 0 0 34 3 3 0.0 Chillies 0 0 0 0 0.0 Amaranths 0 0 1157 125 125 0.0 Pumpkins 0 0 215 22 22 0.0 Cucumber 0 0 0 0 0 0.0 Egg Plant 0 0 0 0 0 0.0 Water Mellon 0 0 0 0 0 0.0 CASH CROPS 0 0 0 3295 3295 0.0 Pyrethrum 0 0 0 0 0 0.0 Cotton 0 0 128 39 39 0.0 Tobacco 0 0 4818 3256 3256 0.0 Jute 0 0 0 0 0 0.0 Total 1,049 4,945 302,344 303,393 0.0 Table 7.1 & 7.2d: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Crop Wet Season Dry Season Total Area Planted Dry & Wet seasons % Area Planted in Dry Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 145 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 5,092 11,021 158,400 96,231 11.5 Sumbawanga Rural 0 0 7,774 19,216 177,594 132,698 14.5 Nkansi 0 0 1,696 6,698 74,856 53,306 12.6 Sumbawanga Urban 35 56 7,736 12,832 32,727 20,109 63.8 Total 35 56 22,298 49,767 443,577 302,344 16.5 District Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 403 571 59,533 96,231 0.6 Sumbawanga Rural 0 0 460 918 68,401 132,698 0.7 Nkansi 0 0 80 422 30,403 53,306 0.8 Sumbawanga Urban 0 0 70 120 13,240 20,109 0.6 Total 0 0 1,013 2,031 171,578 302,344 0.7 7.1 & 7.2h TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region. Insecticide Use % of Planted Area using Insecticide Insecticide Use Insecticide Use Total District 7.1 & 7.2iTOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region. % of Planted Area using Insecticide Total Herbicide Use Insecticide Use Insecticide Use Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 146 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 129 679 0 303,101 53,421 75,999 53,550 192,461 Sumbawanga Rural 119 72 0 177,758 21,908 23,611 22,027 133,561 Nkansi 0 0 0 77,974 14,606 15,748 14,606 53,436 Sumbawanga Urban 69 104 0 21,476 1,968 1,915 2,037 20,166 Total 316 855 0 580,309 91,903 117,273 92,219 303,393 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Total Planted Area Mpanda 1,200 3,089 134 109 3,894 7,937 113,838 181,326 192,461 Sumbawanga Rural 5,532 16,068 924 1,682 117 1,420 61,947 114,392 133,561 Nkansi 1,426 3,671 391 313 145 88 28,522 49,364 53,436 Sumbawanga Urban 3,941 6,550 272 421 781 1,755 8,282 11,439 20,166 Total 12,098 29,379 1,721 2,524 4,937 11,200 153,055 260,290 303,393 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 1,071 1,980 3,050 5,030 4,121 7,009 28 Sumbawanga Rural 5,971 10,422 16,393 26,815 22,364 37,237 28 Nkansi 948 2,521 3,469 5,991 4,417 8,512 30 Sumbawanga Urban 2,355 4,284 6,639 10,922 8,993 15,206 28 Total 10,344 19,207 29,551 48,758 39,895 67,965 28 Household Using Irrigation Household NOT Using Irrigation Total 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region. District Irrigation Use % of Planted Area using Insecticide District Fertilisers Use y Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region. 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Wet & Dry Seasons- Rukwa Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 147 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,227 6,178 56,306 90,053 59,533 96,231 3.4 Sumbawanga Rural 680 597 67,721 132,101 68,401 132,698 0.5 Nkasi 315 705 30,089 52,601 30,403 53,306 0.6 Sumbawanga Urban 583 1,286 12,657 18,823 13,240 20,109 2.9 Total 4,805 8,766 166,773 293,578 171,578 302,344 1.6 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,082 5,507 56,451 90,670 59,533 96,178 5.7 Sumbawanga Rural 6,712 18,377 61,227 111,967 67,939 130,345 14.1 Nkansi 569 1,183 29,834 51,977 30,403 53,160 2.2 Sumbawanga Urban 694 1,990 12,564 18,961 13,258 22,078 9.0 Total 11,057 27,058 160,077 273,576 171,133 302,400 8.9 7.1&7.2k: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - WET & DRY SEASONS District Improved Seed Use % of area planted using Improved Seeds Households Using Improved Seed Households Not Using Improved Seed Total 7.1 $ 7.2j: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year WET SEASON District Fungicide Use % of area planted using Fungicides Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Rukwa Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 0 0 118 863 Nkansi 0 0 80 130 0 0 80 130 Sumbawanga Urban 0 0 35 56 0 0 35 56 Total 0 0 233 1,049 0 0 233 1,049 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 0 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 118 863 118 863 Nkansi 0 0 0 0 0 0 80 130 80 130 Sumbawanga Urban 0 0 0 0 0 0 35 56 35 56 Total 0 0 0 0 0 0 233 1,049 233 1,049 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 Household Using Irrigation Mostly Farm Yard Manure Household NOT Using Irrigation Total 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, DRY SEASON, Rukwa Region. Irrigation Use % of Planted Area using Insecticide District Total Fertilisers Use Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Rukwa Region 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - DRY SEASON,Rukwa Region. District District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Compost Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 149 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 Nkansi 0 0 80 130 80 130 Sumbawanga Urban 35 56 0 0 35 56 Total 35 56 199 993 233 1,049 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 % Planted Area using Herbicide Household NOT Using Irrigation Total 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District, DRY SEASON, Rukwa Region. District Herbicide Use Household Using Irrigation Household NOT Using Irrigation Total 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District, DRY SEASON, Ruwa Region District Insecticide Use Household Using Irrigation Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 150 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 118 863 0 0 118 863 100 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 118 863 115 186 233 1,049 82 % 51 82 49 18 100 100 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District DRY SEASON, Rukwa Region. District Improved Seed Use % Planted Area using Herbicide Household Using Irrigation Household NOT Using Irrigation Total 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, DRY SEASON District Fungicide Use % Planted Area using Herbicide Household Using Irrigation Household NOT Using Irrigation Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 151 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 129 679 5,984 19,499 53,421 75,999 59,533 96,178 Sumbawanga Rural 119 72 45,912 106,662 21,908 23,611 67,939 130,345 Nkansi 0 0 15,797 37,412 14,606 15,748 30,403 53,160 Sumbawanga Urban 69 104 11,204 18,069 1,968 1,915 13,240 20,088 Total 316 855 78,897 181,643 91,903 117,273 171,116 299,771 % 0.2 0.3 46.1 60.6 53.7 39.1 160.9 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Total Planted Area Mpanda 1,200 3,089 134 109 3,894 7,937 54,305 85,095 59,533 96,231 Sumbawanga Rural 5,532 16,068 924 1,682 117 1,420 61,828 113,529 68,401 132,698 Nkansi 1,426 3,671 391 313 145 88 28,442 49,234 30,403 53,306 Sumbawanga Urban 3,941 6,550 272 421 781 1,755 8,247 11,383 13,240 20,109 Total 12,098 29,379 1,721 2,524 4,937 11,200 152,822 259,241 171,578 302,344 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Mpanda 1,071 1,980 58,463 94,251 59,533 96,231 2.1 Sumbawanga Rural 5,971 10,422 62,430 122,276 68,401 132,698 8 Nkasi 948 2,521 29,455 50,785 30,403 53,306 5 Sumbawanga Urban 2,355 4,284 10,886 15,826 13,240 20,109 21 Total 10,344 19,207 161,234 283,137 171,578 302,344 6.4 % 6 6 94 94 100 100 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District WET SEASON, Rukwa Region Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During WET SEASON District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of Area Planted Under Irrigation in Wet Season District Fertilisers Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, WET SEASON, Rukwa Region District Soil Preparation Mostly Tractor Ploughing Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 152 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 5,092 11,021 54,441 85,210 59,533 96,231 Sumbawanga Rural 7,774 19,216 60,627 113,482 68,401 132,698 Nkasi 1,696 6,698 28,707 46,608 30,403 53,306 Sumbawanga Urban 7,736 12,832 5,504 7,277 13,240 20,109 Total 22,298 49,767 149,280 252,577 171,578 302,344 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 403 571 59,130 95,659 59,533 96,231 0.6 Sumbawanga Rural 460 918 67,941 131,781 68,401 132,698 0.7 Nkasi 80 422 30,323 52,884 30,403 53,306 0.8 Sumbawanga Urban 70 120 13,171 19,990 13,240 20,109 0.6 Total 1,013 2,031 170,565 300,314 171,578 302,344 0.7 % 0.6 0.7 99.4 99.3 100.0 100.0 Total Number of Households Number % Number % Number Mpanda 46,242 78 13,292 22 59,533 Sumbawanga Rural 59,911 87 9,024 13 68,935 Nkansi 24,110 79 6,374 21 30,483 Sumbawanga Urban 10,835 81 2,474 19 13,309 Total 141,097 82 31,164 18 172,261 Households that Sold Produce Households that Did not Sold Produce District % of Area Planted Using Herbicide 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District WET SEASON, Rukwa Region. 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03 District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District WET SEASON, Rukwa Region District Insecticide Use Households Using Pesticide Households Not Using Pesticide Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 153 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,227 6,178 56,306 90,053 59,533 96,231 6.4 Sumbawanga Rural 680 597 67,721 132,101 68,401 132,698 0.4 Nkasi 315 705 30,089 52,601 30,403 53,306 1.3 Sumbawanga Urban 583 1,286 12,657 18,823 13,240 20,109 6.4 Total 4,805 8,766 166,773 293,578 171,578 302,344 2.9 % 3 3 97 97 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,082 5,507 56,451 90,670 59,533 96,178 5.7 Sumbawanga Rural 6,712 18,377 61,227 111,967 67,939 130,345 14.1 Nkansi 569 1,183 29,834 51,977 30,403 53,160 2.2 Sumbawanga Urban 676 1,127 12,564 18,961 13,240 20,088 5.6 Total 11,039 26,195 160,077 273,576 171,116 299,771 8.7 % 6 9 94 91 100 100 % of Planted Area Using Improved Seed 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, WET SEASON, Rukwa Region District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted Area Using Fungicide 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 WET SEASON, Rukwa Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Maize 3,884 1,604 51,453 41,568 0 . 129 47 0 . 55,467 43,219 Paddy 402 136 12,576 12,071 120 194 129 105 0 . 13,227 12,505 Sorghum 0 . 1,568 2,048 0 . 0 . 0 . 1,568 2,048 Finger Millet 0 . 1,464 545 0 . 0 . 0 . 1,464 545 CEREALS 4,286 1,739 67,061 56,232 120 194 258 152 0 . 71,726 58,316 Cassava 3,756 1,488 25,745 10,942 0 . 0 . 0 . 29,501 12,430 Sweet Potatoes 0 . 4,555 1,400 0 . 0 . 0 . 4,555 1,400 ROOTS & TUBERS 3,756 1,488 30,300 12,342 0 . 0 . 0 . 34,056 13,830 Beans 3,085 1,569 20,928 8,655 0 . 129 31 0 . 24,142 10,255 Bambaranuts 133 54 133 54 0 . 0 . 0 . 266 108 PULSES 3,218 1,622 21,061 8,709 0 . 129 31 0 . 24,408 10,363 Sunflower 134 27 0 . 0 . 0 . 0 . 134 27 Simsim 0 . 135 16 0 . 0 . 0 . 135 16 Groundnuts 2,277 841 18,292 9,007 0 . 133 27 0 . 20,702 9,874 Soya Beans 0 . 269 68 0 . 0 . 0 . 269 68 OIL SEEDS & OIL NUTS 2,411 868 18,696 9,091 0 . 133 27 0 . 21,240 9,986 Onions 0 . 270 68 0 . 0 . 0 . 270 68 Cabbage 0 . 135 14 0 . 0 . 0 . 135 14 Tomatoes 0 . 803 173 0 . 0 . 0 . 803 173 Spinnach 0 . 134 22 0 . 0 . 0 . 134 22 Amaranths 0 . 536 52 0 . 0 . 0 . 536 52 FRUITS & VEGETABLES 0 . 1,878 329 0 . 0 . 0 . 1,878 329 Cotton 0 . 128 39 0 . 0 . 0 . 128 39 Tobacco 134 54 4,566 3,178 0 . 0 . 0 . 4,700 3,233 CASH CROPS 134 54 4,693 3,217 0 . 0 . 0 . 4,827 3,271 Total 13,805 5,772 143,689 89,920 120 194 520 210 0 . 158,135 96,096 Sumbawanga Rural Maize 4,642 5,881 53,555 56,992 345 207 4,287 2,623 581 248 63,410 65,951 Paddy 728 736 10,358 8,978 113 46 1,029 649 1,294 1,104 13,522 11,514 Sorghum 355 605 5,958 3,907 0 . 1,078 461 0 . 7,391 4,973 Finger Millet 1,717 2,098 8,410 9,362 0 . 826 407 0 . 10,953 11,867 Wheat 0 . 224 91 0 . 0 . 0 . 224 91 CEREALS 7,441 9,320 78,505 79,331 458 253 7,220 4,140 1,875 1,351 95,500 94,395 Cassava 566 357 8,471 4,107 0 . 0 . 0 . 9,037 4,464 Sweet Potatoes 117 47 2,897 664 111 11 0 . 117 5 3,242 728 Irish Potatoes 101 20 230 28 0 . 0 . 0 . 331 49 ROOTS & TUBERS 784 424 11,598 4,799 111 11 0 . 117 5 12,610 5,240 Beans 2,085 1,278 26,551 14,897 121 98 1,835 791 230 79 30,821 17,142 Sumbawanga Rural Green Gram 0 . 120 102 0 . 0 . 0 . 120 102 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Mpanda Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Field Peas 0 . 112 23 0 . 0 . 0 . 112 23 PULSES 2,085 1,278 26,783 15,022 121 98 1,835 791 230 79 31,053 17,266 Sunflower 443 220 10,552 6,997 0 . 918 429 0 . 11,912 7,646 Simsim 0 . 118 24 0 . 0 . 0 . 118 24 Groundnuts 1,126 247 17,249 4,841 111 11 241 37 0 . 18,728 5,136 Soya Beans 0 . 225 46 0 . 0 . 0 . 225 46 OIL SEEDS & OIL NUTS 1,570 467 28,144 11,907 111 11 1,159 466 0 . 30,983 12,851 Onions 0 . 451 68 0 . 0 . 0 . 451 68 Cabbage 0 . 326 60 0 . 0 . 0 . 326 60 Tomatoes 0 . 1,598 241 0 . 0 . 117 5 1,715 245 Spinnach 0 . 218 22 0 . 0 . 0 . 218 22 Amaranths 0 . 452 60 0 . 0 . 0 . 452 60 Pumpkins 0 . 100 10 0 . 115 12 0 . 215 22 FRUITS & VEGETABLES 0 . 3,145 461 0 . 115 12 117 5 3,377 477 Tobacco 0 . 118 24 0 . 0 . 0 . 118 24 CASH CROPS 0 . 118 24 0 . 0 . 0 . 118 24 Total 11,880 11,490 148,293 111,543 801 373 10,329 5,407 2,338 1,439 173,641 130,253 Nkansi Maize 365 361 26,206 26,943 0 . 506 695 73 15 27,149 28,014 Paddy 0 . 3,197 1,409 0 . 0 . 73 7 3,270 1,416 Sorghum 60 7 1,425 359 0 . 0 . 0 . 1,485 366 Bulrush Millet 0 . 82 17 0 . 0 . 0 . 82 17 Finger Millet 165 167 5,375 6,154 0 . 0 . 0 . 5,540 6,321 Wheat 0 . 239 129 80 32 0 . 0 . 319 161 CEREALS 589 535 36,524 35,010 80 32 506 695 145 22 37,845 36,294 Cassava 666 291 9,615 5,681 0 . 60 18 145 29 10,486 6,020 Sweet Potatoes 0 . 1,525 469 0 . 0 . 0 . 1,525 469 Irish Potatoes 0 . 409 149 0 . 0 . 0 . 409 149 ROOTS & TUBERS 666 291 11,549 6,299 0 . 60 18 145 29 12,420 6,638 Beans 163 75 14,524 6,566 0 . 294 167 76 3 15,056 6,810 Cowpeas 82 33 0 . 0 . 0 . 0 . 82 33 PULSES 245 108 14,524 6,566 0 . 294 167 76 3 15,138 6,844 Sunflower 165 75 3,522 1,806 0 . 70 57 0 . 3,757 1,938 Groundnuts 82 8 4,422 1,202 80 65 70 57 0 . 4,654 1,333 OIL SEEDS & OIL NUTS 247 83 7,944 3,008 80 65 141 114 0 . 8,412 3,270 Onions 0 . 244 20 0 . 0 . 0 . 244 20 Cabbage 0 . 234 60 0 . 0 . 0 . 234 60 Tomatoes 0 . 164 35 0 . 0 . 0 . 164 35 FRUITS & VEGETABLES 0 . 642 115 0 . 0 . 0 . 642 115 Total 1,747 1,017 71,183 50,997 160 97 1,000 994 367 55 74,457 53,160 Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Sumbawanga Urban Maize 238 264 9,409 8,601 35 72 2,310 1,885 870 1,404 12,861 12,226 Sorghum 0 . 137 12 0 . 32 7 0 . 169 18 Finger Millet 70 28 470 143 0 . 105 57 0 . 644 228 Wheat 0 . 1,725 1,586 35 70 35 71 0 . 1,794 1,728 CEREALS 308 292 11,740 10,342 69 142 2,482 2,019 870 1,404 15,469 14,199 Cassava 35 28 364 83 0 . 32 13 0 . 431 125 Sweet Potatoes 0 . 69 11 0 . 139 74 0 . 208 85 Irish Potatoes 0 . 589 81 0 . 0 . 35 4 624 85 Yams 0 . 33 13 0 . 0 . 0 . 33 13 Cocoyam 0 . 0 . 0 . 34 7 0 . 34 7 ROOTS & TUBERS 35 28 1,055 188 0 . 205 94 35 4 1,330 314 Beans 69 24 6,460 2,147 35 13 1,008 329 625 531 8,197 3,043 Cowpeas 0 . 69 35 0 . 0 . 0 . 69 35 PULSES 69 24 6,529 2,182 35 13 1,008 329 625 531 8,266 3,078 Sunflower 136 55 3,035 1,353 0 . 846 395 139 49 4,156 1,852 Simsim 0 . 69 11 0 . 0 . 35 14 104 25 Groundnuts 0 . 671 127 0 . 171 31 70 21 913 180 Soya Beans 0 . 34 14 0 . 0 . 0 . 34 14 OIL SEEDS & OIL NUTS 136 55 3,810 1,505 0 . 1,017 426 244 85 5,207 2,070 Onions 0 . 720 107 0 . 34 3 0 . 754 110 Cabbage 33 3 271 32 0 . 34 7 0 . 338 42 Tomatoes 33 3 785 126 0 . 0 . 0 . 818 129 Spinnach 0 . 68 7 0 . 0 . 0 . 68 7 Carrot 0 . 34 3 0 . 0 . 0 . 34 3 Amaranths 0 . 135 10 0 . 34 3 0 . 169 13 FRUITS & VEGETABLES 66 7 2,013 284 0 . 101 14 0 . 2,180 305 Total 613 406 25,147 14,502 104 155 4,813 2,881 1,773 2,023 32,451 19,966 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 157 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 55,602 43,301 38,976 0.9 43,301 38,976 0.9 Sumbawanga Rural 118 288 118 0.4 63,410 65,951 84,223 1.3 66,238 84,342 1.3 Nkansi 80 97 19 0.2 27,149 28,014 27,028 1.0 28,111 27,047 1.0 Sumbawanga Urban 35 42 17 0.4 12,999 12,341 13,050 1.1 12,383 13,068 1.1 Total 233 427 155 0.4 159,160 149,606 163,277 1.1 150,033 163,432 1.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 13,227 12,505 26,729 2.1 12,505 26,729 2.1 Nkansi 0 0 0 0.0 13,635 11,605 20,209 1.7 11,605 20,209 1.7 Sumbawanga Urban 0 0 0 0.0 0 0 0 0 0 0.0 Total 0 0 0 0.0 3,270 1,416 2,583 1.8 1,416 2,583 1.8 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 1,568 2,048 4,645 2.3 2,048 4,645 2.3 Sumbawanga Rural 0 0 0 0.0 7,391 4,973 5,108 1.0 4,973 5,108 1.0 Nkansi 0 0 0 0.0 1,485 366 181 0.5 366 181 0.5 Sumbawanga Urban 0 0 0 0.0 169 18 8 0.5 18 8 0.5 Total 0 0 0 0.0 10,613 7,405 9,942 1.3 7,405 9,942 1.3 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 1,464 545 690 1.3 545 690 1.3 Sumbawanga Rural 0 0 0 0.0 10,953 11,867 9,746 0.8 11,867 9,746 0.8 Nkansi 0 0 0 0.0 5,540 6,321 5,087 0.8 6,321 5,087 0.8 Sumbawanga Urban 0 0 0 0.0 679 235 276 1.2 235 276 1.2 Total 0 0 0 0.0 18,635 18,967 15,798 0.8 18,967 15,798 0.8 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year. District Finger millet Dry Season Wet Season Total 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sorghum Dry Season Wet Season Total District Paddy Dry Season Wet Season Total 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year. 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year. District Maize Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 158 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 82 17 20 1.2 17 20 1.2 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 82 17 20 1.2 17 20 1.2 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 224 91 57 0.6 91 57 0.6 Nkansi 0 0 0 0.0 319 161 58 0.4 161 58 0.4 Sumbawanga Urban 0 0 0 0.0 1,794 1,728 1,796 1.0 1,728 1,796 1.0 Total 0 0 0 0.0 2,337 1,979 1,911 1.0 1,979 1,911 1.0 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 29,632 12,483 15,556 1.2 12,483 15,556 1.2 Sumbawanga Rural 0 0 0 0.0 12,877 6,817 10,050 1.5 6,817 10,050 1.5 Nkansi 0 0 0 0.0 10,885 6,165 13,975 2.3 6,165 13,975 2.3 Sumbawanga Urban 0 0 0 0.0 535 146 238 1.6 146 238 1.6 Total 0 0 0 0.0 53,929 25,611 39,818 1.6 25,611 39,818 1.6 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 4,555 1,400 2,548 1.8 1,400 2,548 1.8 Sumbawanga Rural 0 0 0 0.0 3,242 728 1,468 2.0 728 1,468 2.0 Nkansi 0 0 0 0.0 1,525 469 614 1.3 469 614 1.3 Sumbawanga Urban 0 0 0 0.0 208 85 69 0.8 85 69 0.8 Total 0 0 0 0.0 9,530 2,681 4,699 1.8 2,681 4,699 1.8 Dry Season Wet Season Total District Cassava Dry Season Wet Season Total 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sweet Poatatoes 7.2.6 Number of Crop Growing Households, Planted Area (ha) and Wheat Harevsted (tons) by season and District 2002/03 Agricultural Year. District Wheat Dry Season Wet Season Total 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 7.2.5 Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year. District Bulrush Millet Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 159 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 331 49 70 1.4 49 70 1.4 Nkansi 0 0 0 0.0 409 149 618 4.1 149 618 4.1 Sumbawanga Urban 0 0 0 0.0 624 85 343 4.1 85 343 4.1 Total 0 0 0 0.0 1,364 282 1,031 3.7 282 1,031 3.7 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 33 13 127 9.5 13 127 9.5 Total 0 0 0 0.0 33 13 127 9.5 13 127 9.5 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 7 27 4.0 7 27 4.0 Total 0 0 0 0.0 34 7 27 4.0 7 27 4.0 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 24,142 10,255 5,210 0.0 0 0 0.0 Sumbawanga Rural 118 240 24 0.1 30,821 17,142 8,029 0.5 17,382 8,053 0.5 Nkansi 80 32 19 0.6 15,056 6,810 2,747 0.4 6,843 2,767 0.4 Sumbawanga Urban 35 7 1 0.1 8,197 3,043 1,278 0.4 3,050 1,279 0.4 Total 233 279 44 0.2 78,216 37,251 17,265 0.5 37,530 17,308 0.5 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Beans Dry Season Wet Season Total Coco Yams Dry Season Wet Season Total Yams Dry Season Wet Season Total 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Irish Poatatoes Dry Season Wet Season Total 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 160 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 82 33 30 0.5 33 30 0.5 Sumbawanga Urban 0 0 0 0.0 69 35 17 1.3 35 17 1.3 Total 0 0 0 0.0 151 68 47 0.7 68 47 0.7 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 120 102 151 1.5 102 151 1.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 1.5 0 0 1.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 266 108 93 0.9 108 93 0.9 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 266 108 93 0.9 108 93 0.9 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 112 23 11 0.5 23 11 0.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 112 23 11 0.5 23 11 0.5 Dry Season Bambaranuts 7.2.13 Number of Crop Growing Households, Planted Area (ha) and Cowpeas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cowpeas Dry Season Wet Season Total Total 7.2.14 Number of Crop Growing Households, Planted Area (ha) and Green Gram Harevsted (tons) by season and District 2002/03 Agricultural Year. District Green gram Dry Season Wet Season Total 7.2.15 Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year. District Wet Season Total 7.2.16 Number of Crop Growing Households, Planted Area (ha) and Field Peas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Field Peas Dry Season Wet Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 161 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 27 24 0.9 27 24 0.9 Sumbawanga Rural 118 288 142 0.5 11,912 7,646 3,976 0.5 7,934 4,118 0.5 Nkansi 0 0 0 0.0 3,757 1,938 973 0.5 1,938 973 0.5 Sumbawanga Urban 35 7 4 0.6 4,156 1,852 984 0.5 1,859 988 0.5 Total 153 295 146 0.5 19,960 11,463 5,957 0.5 11,758 6,103 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 27 24 0.9 27 24 0.9 Sumbawanga Rural 118 288 142 0.5 11,912 7,646 3,976 0.5 7,934 4,118 0.5 Nkansi 0 0 0 0.0 3,757 1,938 973 0.5 1,938 973 0.5 Sumbawanga Urban 35 7 4 0.6 4,156 1,852 984 0.5 1,859 988 0.5 Total 153 295 146 0.5 19,960 11,463 5,957 0.5 11,758 6,103 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 20,702 9,874 6,617 0.7 9,874 6,617 0.7 Sumbawanga Rural 118 48 71 1.5 18,728 5,136 2,820 0.5 5,184 2,891 0.6 Nkansi 0 0 0 0.0 4,654 1,333 1,535 1.2 1,333 1,535 1.2 Sumbawanga Urban 0 0 0 0.0 913 180 84 0.5 180 84 0.5 Total 118 48 71 1.5 44,997 16,522 11,055 0.7 16,570 11,126 0.7 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 269 68 139 2.0 68 139 2.0 Sumbawanga Rural 0 0 0 0.0 225 46 5 0.1 46 5 0.1 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 14 10 0.7 14 10 0.7 Total 0 0 0 0.0 528 127 154 1.2 127 154 1.2 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.20 Number of Crop Growing Households, Planted Area (ha) and Soya Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Soya Beans Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 162 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 270 68 443 6.5 68 443 6.5 Sumbawanga Rural 0 0 0 0.0 451 68 365 5.4 68 365 5.4 Nkansi 0 0 0 0.0 244 20 74 3.7 20 74 3.7 Sumbawanga Urban 0 0 0 0.0 754 110 257 2.3 110 257 2.3 Total 0 0 0 0.0 1,718 266 1,139 4.3 266 1,139 4.3 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 135 14 40 3.0 14 40 3.0 Sumbawanga Rural 0 0 0 0.0 326 60 451 7.6 60 451 7.6 Nkansi 0 0 0 0.0 234 60 59 1.0 60 59 1.0 Sumbawanga Urban 0 0 0 0.0 338 42 189 4.5 42 189 4.5 Total 0 0 0 0.0 1,032 176 739 4.2 176 739 4.2 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 803 173 331 1.9 173 331 1.9 Sumbawanga Rural 0 0 0 0.0 1,715 245 1,122 4.6 245 1,122 4.6 Nkansi 0 0 0 0.0 164 35 33 0.9 35 33 0.9 Sumbawanga Urban 0 0 0 0.0 818 129 651 5.0 129 651 5.0 Total 0 0 0 0.0 3,499 583 2,136 3.7 583 2,136 3.7 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 22 61 2.8 22 61 2.8 Sumbawanga Rural 0 0 0 0.0 218 22 4 0.2 22 4 0.2 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 68 7 3 0.4 7 3 0.4 Total 0 0 0 0.0 420 51 68 1.3 51 68 1.3 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year. District Onions Dry Season Wet Season Total 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cabbage Dry Season Wet Season Total 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tomatoes Dry Season Wet Season Total 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year. District Spinach Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 3 7 2.1 3 7 2.1 Total 0 0 0 0.0 34 3 7 2.1 3 7 2.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 536 52 87 1.7 52 87 1.7 Sumbawanga Rural 0 0 0 0.0 452 60 11 0.2 60 11 0.2 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 169 13 11 0.9 13 11 0.9 Total 0 0 0 0.0 1,157 125 110 0.9 125 110 0.9 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 215 22 12 0.5 22 12 0.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 215 22 12 0.5 22 12 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 128 39 13 0.3 39 13 0.3 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 128 39 13 0.3 39 13 0.3 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year. District Carrot Dry Season Wet Season Total 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Amaranthas Dry Season Wet Season Total 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year. District Pumpkins Dry Season Wet Season Total 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cotton Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 164 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 4,700 3,233 3,209 1.0 3,233 3,209 1.0 Sumbawanga Rural 0 0 0 0.0 118 24 41 1.7 24 41 1.7 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 4,818 3,256 3,251 1.0 3,256 3,251 1.0 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tobacco Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 165 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 166 District/Crop Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Mangostine . . 12 Pigeon Pea 162 162 40 247 Palm Oil 138 72 2,063 28,598 Coconut . . . 0 Rubber . . 72 0 Sugarcane 22 22 16 741 Mpesheni . . 83 0 Banana 694 299 5,978 20,005 Avocado . . 9 0 Mango 392 283 10,753 38,048 Pawpaw 21 43 1,236 28,751 Orange 81 630 1,343 2,133 Grape Fruit 22 . . 0 Mandarine/Tangerine . . 32 0 Guava 29 38 363 9,512 Lime/Lemon 3,866 5 41 7,581 Total 5,429 1,554 22,040 14,182 Pigeon Pea . 48 57 1,200 Star Fruit . 0 207 0 Palm Oil . . 289 0 Coconut 2 0 37 0 Coffee 24 24 7 296 Sugarcane 1,356 3,946 43,680 11,069 Banana 758 506 4,132 8,168 Avocado . . 15 0 Mango 155 79 4,180 52,749 Pawpaw . . 12 0 Pineapple . . 2 0 Orange 36 26 160 6,072 Mandarine/Tangerine . . . 0 Guava 120 0 173 0 Pears 6 5 1 247 Lime/Lemon . . . 0 Total 2,456 4,635 52,954 11,426 Palm Oil . 8 54 7,008 Coconut 16 16 14 911 Sugarcane 74 57 681 11,873 Jack Fruit . . 4 0 Banana 66 82 602 7,338 Mango . 2,020 638 316 Pawpaw . 0 9 0 Orange . 4 61 15,385 Guava . 0 85 0 Lime/Lemon . . 7 0 Total 155 2,187 2,156 986 Nkansi 7.3 Production of Permanent Crops by Crop Type and District, Rukwa Region Mpanda Sumbawanga Rural Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 167 Sour Soup 7 0 . 0 Coconut 42 42 10 247 Coffee 10 . . 0 Sugarcane 346 301 10,261 34,060 Cardamon 3 3 2 504 Mpesheni . 0 0 0 Banana 272 124 759 6,138 Avocado . . 1 0 Orange 73 10 4 364 Guava 5 8 28 3,438 Plums . 0 3 0 Pitches . 1 5 3,952 Lime/Lemon 11 12 85 7,002 Total 770 503 11,159 22,189 Sour Soup 7 0 . 0 Mangostine . . 12 0 Pigeon Pea 162 210 98 464 Star Fruit . 0 207 0 Palm Oil 138 80 2,405 30,144 Coconut 60 58 62 1,064 Coffee 35 24 7 296 Rubber . . 72 0 Sugarcane 1,797 4,327 54,638 12,628 Cardamon 3 3 2 504 Jack Fruit . . 4 0 Mpesheni . 0 83 0 Banana 1,790 1,010 11,471 11,353 Avocado . . 25 0 Mango 547 2,382 15,571 6,537 Pawpaw 21 43 1,257 29,248 Pineapple . . 2 0 Orange 190 671 1,569 2,339 Grape Fruit 22 . . 0 Mandarine/Ta. . 32 0 Guava 155 46 649 14,025 Plums . 0 3 0 Pears 6 5 1 247 Pitches . 1 5 3,952 Lime/Lemon 3,877 18 133 7,554 Total 8,810 8,879 88,310 9,946 Sumbawanga Urban Total cont……… Production of Permanent Crops by Crop Type and District, Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 168 Crop Area Planted % Lime/Lemon 3,877 44 Sugarcane 1,797 20 Banana 1,790 20 Mango 547 6 Orange 190 2 Pigeon Pea 162 2 Guava 155 2 Palm Oil 138 2 Coconut 60 1 Coffee 35 0 Grape Fruit 22 0 Pawpaw 21 0 Sour Soup 7 0 Pears 6 0 Cardamon 3 0 Mangostine 0 0 Star Fruit 0 0 Rubber 0 0 Jack Fruit 0 0 Mpesheni 0 0 Avocado 0 0 Pineapple 0 0 Mandarine/Tangerine 0 0 Plums 0 0 Pitches 0 0 Total 8,810 100 cont…..Area Planted by crop Type - Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 169 cont…Planted Area with Fertiliser by Fertiliser Type and crop Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0 0 0 7 7 Pigeon Pea 0 0 0 162 162 Palm Oil 0 0 0 138 138 Coconut 42 0 0 17 60 Coffee 0 0 0 35 35 Sugarcane 444 4 0 1,349 1,797 Cardamon 0 . 0 3 3 Banana 121 3 0 1,665 1,790 Mango 0 0 0 547 547 Pawpaw 0 0 0 21 21 Orange 0 0 0 190 190 Grape Fruit 0 0 0 22 22 Guava 3 0 0 152 155 Pears 0 0 0 6 6 Lime/Lemon 0 0 0 3,877 3,877 Total 611 7 0 8,192 8,810 Mostly Farm Yard Manure Total % Sour Soup 0 7 0.0 Pigeon Pea 0 162 0.0 Palm Oil 0 138 0.0 Coconut 42 60 70.9 Coffee 0 35 0.0 Sugarcane 444 1,797 24.7 Cardamon 0 3 0.0 Banana 121 1,790 6.8 Mango 0 547 0.0 Pawpaw 0 21 0.0 Orange 0 190 0.0 Grape Fruit 0 22 0.0 Guava 3 155 2.2 Pears 0 6 0.0 Lime/Lemon 0 3,877 0.0 Total 611 8,810 6.9 Mostly Compost Total % Sour Soup 0 7 0.0 Pigeon Pea 0 162 0.0 Palm Oil 0 138 0.0 Coconut 0 60 0 Coffee 0 35 0 Sugarcane 4 1,797 0 Cardamon . 3 0 Banana 3 1,790 0 Mango 0 547 0 Pawpaw 0 21 0 Orange 0 190 0 Grape Fruit 0 22 0 Guava 0 155 0 Pears 0 6 0 Lime/Lemon 0 3,877 0.0 Total 7 8,810 0.08 cont…Planted Area with Fertiliser by Fertiliser Type and crop cont…Planted Area with Fertiliser by Fertiliser Type and crop Tanzania Agriculture Sample Census - 2003 Rukwa 170 Appendix II 171 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 172 Number % Number % Number % Mpanda 57,127 96 2,407 4 59,533 100 Sumbawanga Rural 66,890 97 2,045 3 68,935 100 Nkansi 30,037 99 446 1 30,483 100 Sumbawanga Urban 13,101 98 208 2 13,309 100 Total 167,155 97 5,106 3 172,261 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Other By Factory Total Mpanda 9,773 400 46,954 0 0 0 0 57,127 Sumbawanga Rural 6,092 1,396 49,404 119 9,550 331 0 66,890 Nkansi 4,073 1,227 24,416 0 0 0 321 30,037 Sumbawanga Urban 270 375 12,422 0 35 0 0 13,101 Total 20,209 3,397 133,195 119 9,585 331 321 167,155 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District District Method of Processing 8.0a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year. Households That Households That Did Not Total District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 173 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 4,956 400 48,099 0 0 0 0 0 53,454 Paddy 3,948 130 8,240 0 0 0 0 0 12,318 Sorghum 261 0 1,173 0 0 0 0 0 1,434 Finger Millet 0 0 798 0 0 0 0 0 798 Cassava 12,313 135 3,861 0 0 0 0 0 16,310 Beans 134 0 0 0 0 0 0 0 134 Sunflower 0 0 134 0 0 0 0 0 134 Groundnut 2,745 0 673 0 0 0 0 0 3,417 Soya Beans 0 0 269 0 0 0 0 0 269 Maize 2,989 1,637 47,050 119 9,441 0 230 0 61,466 Paddy 5,213 929 3,127 0 0 0 316 0 9,584 Sorghum 481 120 5,829 0 109 0 0 0 6,538 Finger Millet 801 118 3,570 0 1,482 0 0 0 5,970 Wheat 0 0 115 0 109 0 0 0 224 Cassava 3,564 229 3,463 0 0 0 0 0 7,257 Sweet Potato 691 0 0 0 0 0 0 0 691 Beans 205 0 119 0 0 0 0 0 324 Sunflower 466 0 1,042 0 3,090 0 0 117 4,714 Groundnut 2,671 0 121 0 0 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 0 0 121 Banana 111 0 0 0 0 0 0 0 111 Maize 1,091 1,238 23,775 0 0 0 0 0 26,104 Paddy 1,035 81 2,078 0 0 0 0 0 3,194 Sorghum 148 208 1,046 0 0 0 0 0 1,402 Finger Millet 813 0 3,775 0 0 0 0 0 4,588 Wheat 0 0 78 0 0 0 0 0 78 Cassava 3,776 126 4,961 0 0 0 0 0 8,864 Sweet Potato 158 0 82 0 0 0 0 0 240 Sunflower 78 80 1,274 0 211 0 0 767 2,411 Groundnut 3,556 0 473 0 0 0 0 0 4,030 Maize 270 375 12,285 0 0 0 0 0 12,930 Sorghum 0 0 99 0 0 0 0 0 99 Finger Millet 68 0 310 0 0 0 0 0 378 Wheat 0 102 621 0 0 0 0 0 723 Cassava 65 0 98 0 0 0 0 0 162 Cocoyams 34 0 0 0 0 0 0 0 34 Sunflower 0 34 676 0 136 34 35 103 1,017 Groundnut 65 0 0 0 0 0 0 0 65 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop Crop Method of Processing Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 174 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,769 120 253 0 0 0 1,070 0 48,243 53,454 Paddy 534 254 954 0 0 0 1,409 110 9,057 12,318 Sorghum 0 0 0 0 0 0 0 0 1,434 1,434 Finger Millet 403 0 0 0 0 0 0 0 394 798 Cassava 1,347 0 0 0 0 0 268 0 14,695 16,310 Beans 134 0 0 0 0 0 0 0 0 134 Sunflower 0 0 0 0 0 0 0 0 134 134 Groundnut 539 134 0 0 0 0 0 0 2,744 3,417 Soya Beans 134 0 0 0 0 0 0 0 135 269 Total 6,862 508 1,207 0 0 0 2,746 110 76,836 88,269 Maize 2,044 121 230 0 353 0 115 0 58,602 61,466 Paddy 593 357 111 0 0 0 0 0 8,522 9,584 Sorghum 0 0 0 0 0 0 0 0 6,538 6,538 Finger Millet 0 0 0 0 0 0 115 0 5,855 5,970 Wheat 0 0 0 0 0 0 0 0 224 224 Cassava 239 0 118 0 0 0 89 0 6,810 7,257 Sweet Potato 0 0 0 0 0 0 0 0 691 691 Beans 0 0 0 0 0 0 0 0 324 324 Sunflower 921 462 0 0 0 0 349 0 2,982 4,714 Groundnut 353 118 0 0 0 0 236 0 2,086 2,792 Oil Palm 0 0 0 0 0 0 0 0 121 121 Banana 111 0 0 0 0 0 0 0 0 111 Total 4,262 1,058 460 0 353 0 905 0 92,754 99,792 Maize 165 0 0 72 76 0 69 0 25,723 26,104 Paddy 148 0 0 0 76 0 0 0 2,970 3,194 Sorghum 0 0 0 0 0 0 0 0 1,402 1,402 Finger Millet 82 0 0 0 0 0 78 0 4,428 4,588 Wheat 78 0 0 0 0 0 0 0 0 78 Cassava 129 0 0 60 0 0 0 0 8,675 8,864 Sweet Potato 0 0 0 0 0 0 0 0 240 240 Sunflower 453 0 0 0 0 0 70 80 1,807 2,411 Groundnut 152 0 0 0 0 0 0 0 3,877 4,030 Total 1,208 0 0 132 151 0 217 80 49,123 50,912 Maize 0 0 0 0 139 34 104 34 12,618 12,930 Sorghum 0 0 0 0 0 0 0 0 99 99 Finger Millet 0 0 0 0 0 0 34 0 344 378 Wheat 0 0 0 0 0 0 0 0 723 723 Cassava 0 0 0 0 0 0 0 0 162 162 Cocoyams 0 0 0 0 0 0 0 0 34 34 Sunflower 172 34 0 35 0 0 34 33 709 1,017 Groundnut 0 32 0 0 0 0 0 0 34 65 Total 172 66 0 35 139 34 172 67 14,724 15,409 Maize 5,978 240 484 72 568 34 1,358 34 145,186 153,954 Paddy 1,276 611 1,065 0 76 0 1,409 110 20,550 25,097 Sorghum 0 0 0 0 0 0 0 0 9,474 9,474 Finger Millet 486 0 0 0 0 0 227 0 11,021 11,734 Wheat 78 0 0 0 0 0 0 0 948 1,026 Cassava 1,715 0 118 60 0 0 357 0 30,342 32,592 Sweet Potato 0 0 0 0 0 0 0 0 931 931 Cocoyams 0 0 0 0 0 0 0 0 34 34 Beans 134 0 0 0 0 0 0 0 324 458 Sunflower 1,547 496 0 35 0 0 454 113 5,632 8,276 Groundnut 1,045 284 0 0 0 0 236 0 8,740 10,305 Oil Palm 0 0 0 0 0 0 0 0 121 121 Soya Beans 134 0 0 0 0 0 0 0 135 269 Banana 111 0 0 0 0 0 0 0 0 111 Total 12,505 1,631 1,667 167 643 34 4,040 257 233,437 254,382 Where Sold Mpanda Sumbawanga Rural 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Nkansi Sumbawanga Urban Total Crop Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 175 District Crop On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 4,956 400 48,099 0 0 0 0 0 53,454 Paddy 3,948 130 8,240 0 0 0 0 0 12,318 Sorghum 261 0 1,173 0 0 0 0 0 1,434 Finger Millet 0 0 798 0 0 0 0 0 798 Cassava 12,313 135 3,861 0 0 0 0 0 16,310 Beans 134 0 0 0 0 0 0 0 134 Sunflower 0 0 134 0 0 0 0 0 134 Groundnut 2,745 0 673 0 0 0 0 0 3,417 Soya Beans 0 0 269 0 0 0 0 0 269 Maize 2,989 1,637 47,050 119 9,441 0 230 0 61,466 Paddy 5,213 929 3,127 0 0 0 316 0 9,584 Sorghum 481 120 5,829 0 109 0 0 0 6,538 Finger Millet 801 118 3,570 0 1,482 0 0 0 5,970 Wheat 0 0 115 0 109 0 0 0 224 Cassava 3,564 229 3,463 0 0 0 0 0 7,257 Sweet Potatoes 691 0 0 0 0 0 0 0 691 Beans 205 0 119 0 0 0 0 0 324 Sunflower 466 0 1,042 0 3,090 0 0 117 4,714 Groundnut 2,671 0 121 0 0 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 0 0 121 Banana 111 0 0 0 0 0 0 0 111 Maize 1,091 1,238 23,775 0 0 0 0 0 26,104 Paddy 1,035 81 2,078 0 0 0 0 0 3,194 Sorghum 148 208 1,046 0 0 0 0 0 1,402 Finger Millet 813 0 3,775 0 0 0 0 0 4,588 Wheat 0 0 78 0 0 0 0 0 78 Cassava 3,776 126 4,961 0 0 0 0 0 8,864 Sweet Potatoes 158 0 82 0 0 0 0 0 240 Sunflower 78 80 1,274 0 211 0 0 767 2,411 Groundnut 3,556 0 473 0 0 0 0 0 4,030 Maize 270 375 12,285 0 0 0 0 0 12,930 Sorghum 0 0 99 0 0 0 0 0 99 Finger Millet 68 0 310 0 0 0 0 0 378 Wheat 0 102 621 0 0 0 0 0 723 Cassava 65 0 98 0 0 0 0 0 162 Cocoyams 34 0 0 0 0 0 0 0 34 Sunflower 0 34 676 0 136 34 35 103 1,017 Groundnut 65 0 0 0 0 0 0 0 65 8.1.1a AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop Method of Processing Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 176 d / Human Consumpt ion Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 53,454 0 0 0 0 0 53,454 Paddy 12,318 0 0 0 0 0 12,318 Sorghum 1,434 0 0 0 0 0 1,434 Finger Millet 798 0 0 0 0 0 798 Cassava 16,175 0 0 0 135 0 16,310 Beans 134 0 0 0 0 0 134 Sunflower 134 0 0 0 0 0 134 Groundnut 2,878 539 0 0 0 0 3,417 Soya Beans 135 134 0 0 0 0 269 Total 87,461 674 0 0 135 0 88,269 Maize 60,298 0 582 238 233 115 61,466 Paddy 8,658 122 704 100 0 0 9,584 Sorghum 6,425 0 0 113 0 0 6,538 Finger Millet 5,735 0 235 0 0 0 5,970 Wheat 224 0 0 0 0 0 224 Cassava 6,897 0 239 0 121 0 7,257 Sweet Potatoes 691 0 0 0 0 0 691 Beans 324 0 0 0 0 0 324 Sunflower 3,542 117 940 0 116 0 4,714 Groundnut 2,203 0 589 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 121 Banana 111 0 0 0 0 0 111 Total 95,228 239 3,290 451 469 115 99,792 Maize 26,104 0 0 0 0 0 26,104 Paddy 3,049 0 73 0 73 0 3,194 Sorghum 1,402 0 0 0 0 0 1,402 Finger Millet 4,506 0 0 0 0 82 4,588 Wheat 78 0 0 0 0 0 78 Cassava 8,864 0 0 0 0 0 8,864 Sweet Potatoes 240 0 0 0 0 0 240 Sunflower 2,331 0 80 0 0 0 2,411 Groundnut 4,030 0 0 0 0 0 4,030 Total 50,604 0 153 0 73 82 50,912 Maize 12,930 0 0 0 0 0 12,930 Sorghum 99 0 0 0 0 0 99 Finger Millet 378 0 0 0 0 0 378 Wheat 723 0 0 0 0 0 723 Cassava 162 0 0 0 0 0 162 Cocoyams 0 0 0 0 34 0 34 Sunflower 949 0 68 0 0 0 1,017 Groundnut 65 0 0 0 0 0 65 Total 15,307 0 68 0 34 0 15,409 Maize 152,786 0 582 238 233 115 153,954 Paddy 24,025 122 777 100 73 0 25,097 Sorghum 9,361 0 0 113 0 0 9,474 Finger Millet 11,416 0 235 0 0 82 11,734 Wheat 1,026 0 0 0 0 0 1,026 Cassava 32,098 0 239 0 255 0 32,592 Sweet Potatoes 931 0 0 0 0 0 931 Cocoyams 0 0 0 0 34 0 34 Beans 458 0 0 0 0 0 458 Sunflower 6,956 117 1,088 0 116 0 8,276 Groundnut 9,177 539 589 0 0 0 10,305 Oil Palm 121 0 0 0 0 0 121 Soya Beans 135 134 0 0 0 0 269 Banana 111 0 0 0 0 0 111 Total 248,601 912 3,510 451 710 198 254,382 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop Product Use Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Total Crop Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 177 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,769 120 253 0 0 0 1,070 0 48,243 53,454 Paddy 534 254 954 0 0 0 1,409 110 9,057 12,318 Sorghum 0 0 0 0 0 0 0 0 1,434 1,434 Finger Millet 403 0 0 0 0 0 0 0 394 798 Cassava 1,347 0 0 0 0 0 268 0 14,695 16,310 Beans 134 0 0 0 0 0 0 0 0 134 Sunflower 0 0 0 0 0 0 0 0 134 134 Groundnut 539 134 0 0 0 0 0 0 2,744 3,417 Soya Beans 134 0 0 0 0 0 0 0 135 269 Total 6,862 508 1,207 0 0 0 2,746 110 76,836 88,269 Maize 2,044 121 230 0 353 0 115 0 58,602 61,466 Paddy 593 357 111 0 0 0 0 0 8,522 9,584 Sorghum 0 0 0 0 0 0 0 0 6,538 6,538 Finger Millet 0 0 0 0 0 0 115 0 5,855 5,970 Wheat 0 0 0 0 0 0 0 0 224 224 Cassava 239 0 118 0 0 0 89 0 6,810 7,257 Sweet Potatoes 0 0 0 0 0 0 0 0 691 691 Beans 0 0 0 0 0 0 0 0 324 324 Sunflower 921 462 0 0 0 0 349 0 2,982 4,714 Groundnut 353 118 0 0 0 0 236 0 2,086 2,792 Oil Palm 0 0 0 0 0 0 0 0 121 121 Banana 111 0 0 0 0 0 0 0 0 111 Total 4,262 1,058 460 0 353 0 905 0 92,754 99,792 Maize 165 0 0 72 76 0 69 0 25,723 26,104 Paddy 148 0 0 0 76 0 0 0 2,970 3,194 Sorghum 0 0 0 0 0 0 0 0 1,402 1,402 Finger Millet 82 0 0 0 0 0 78 0 4,428 4,588 Wheat 78 0 0 0 0 0 0 0 0 78 Cassava 129 0 0 60 0 0 0 0 8,675 8,864 Sweet Potatoes 0 0 0 0 0 0 0 0 240 240 Sunflower 453 0 0 0 0 0 70 80 1,807 2,411 Groundnut 152 0 0 0 0 0 0 0 3,877 4,030 Total 1,208 0 0 132 151 0 217 80 49,123 50,912 Maize 0 0 0 0 139 34 104 34 12,618 12,930 Sorghum 0 0 0 0 0 0 0 0 99 99 Finger Millet 0 0 0 0 0 0 34 0 344 378 Wheat 0 0 0 0 0 0 0 0 723 723 Cassava 0 0 0 0 0 0 0 0 162 162 Cocoyams 0 0 0 0 0 0 0 0 34 34 Sunflower 172 34 0 35 0 0 34 33 709 1,017 Groundnut 0 32 0 0 0 0 0 0 34 65 Total 172 66 0 35 139 34 172 67 14,724 15,409 Maize 5,978 240 484 72 568 34 1,358 34 145,186 153,954 Paddy 1,276 611 1,065 0 76 0 1,409 110 20,550 25,097 Sorghum 0 0 0 0 0 0 0 0 9,474 9,474 Finger Millet 486 0 0 0 0 0 227 0 11,021 11,734 Wheat 78 0 0 0 0 0 0 0 948 1,026 Cassava 1,715 0 118 60 0 0 357 0 30,342 32,592 Sweet Potatoes 0 0 0 0 0 0 0 0 931 931 Cocoyams 0 0 0 0 0 0 0 0 34 34 Beans 134 0 0 0 0 0 0 0 324 458 Sunflower 1,547 496 0 35 0 0 454 113 5,632 8,276 Groundnut 1,045 284 0 0 0 0 236 0 8,740 10,305 Oil Palm 0 0 0 0 0 0 0 0 121 121 Soya Beans 134 0 0 0 0 0 0 0 135 269 Banana 111 0 0 0 0 0 0 0 0 111 Total 12,505 1,631 1,667 167 643 34 4,040 257 233,437 254,382 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Crop Where Sold Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 178 Flour / Meal Grain Oil Juice Rubber Total Mpanda 53,178 3,949 0 0 0 57,127 Sumbawanga Rural 61,492 3,148 2,135 116 0 66,890 Nkansi 27,574 1,911 481 0 71 30,037 Sumbawanga Urban 12,827 69 135 69 0 13,101 Total 155,071 9,077 2,751 185 71 167,155 Household / Human Consumption Sale Only Animal Consumption Did Not Use Other Total Mpanda 57,127 0 0 0 0 57,127 Sumbawanga Rural 65,380 691 351 354 115 66,890 Nkansi 29,892 73 0 73 0 30,037 Sumbawanga Urban 13,101 0 0 0 0 13,101 Total 165,499 764 351 426 115 167,155 District Product Use 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 179 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Mpanda 3,769 254 593 0 0 0 1,543 0 50,968 57,127 Sumbawanga Rural 2,398 342 230 0 353 0 205 0 63,362 66,890 Nkansi 366 0 0 132 76 0 0 80 29,383 30,037 Sumbawanga Urban 34 0 0 0 139 34 104 34 12,756 13,101 Total 6,568 596 823 132 568 34 1,851 115 156,468 167,155 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Mpanda 19,440 134 6,481 0 133 134 0 1,209 29,461 134 57,127 Sumbawanga Rural 9,309 3,907 4,360 0 0 350 121 817 48,028 0 66,890 Nkansi 658 2,389 2,588 0 72 0 80 2,105 21,995 150 30,037 Sumbawanga Urban 528 851 0 34 0 0 0 0 11,688 0 13,101 Total 29,934 7,281 13,429 34 205 484 201 4,131 111,172 284 167,155 District By Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District, Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa 180 Appendix II 181 MARKETING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 182 Total Number % Number % Number Mpanda 46,242 78 13,292 22 59,533 Sumbawanga Rural 59,911 87 9,024 13 68,935 Nkansi 24,110 79 6,374 21 30,483 Sumbawanga Urban 10,835 81 2,474 19 13,309 Total 141,097 81.9 31,164 18.1 172,261 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Trade Union Problems Regulatory Board Problems Other Not applicable Total Mpanda 1,200 44,338 535 134 0 0 537 12,788 59,533 Sumbawanga Rural 3,294 30,710 456 0 233 115 1,123 32,085 68,016 Nkansi 1,408 15,404 0 0 0 82 958 12,510 30,362 Sumbawanga Urban 547 6,545 0 0 69 0 35 6,078 13,275 Total 6,450 96,997 992 134 303 198 2,652 63,461 171,186 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Trade Union Problems Regulatory Board Problems Other Not applicable Total Mpanda 2.02 74.48 0.90 0.23 0.00 0.00 0.90 21.48 100.00 Sumbawanga Rural 4.84 45.15 0.67 0.00 0.34 0.17 1.65 47.17 100.00 Nkansi 4.64 50.73 0.00 0.00 0.00 0.27 3.15 41.20 100.00 Sumbawanga Urban 4.12 49.30 0.00 0.00 0.52 0.00 0.26 45.79 100.00 Total 3.77 56.66 0.58 0.08 0.18 0.12 1.55 37.07 100.00 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03, Rukwa Region Households that sold Number of Households that Did not Sell District 10.2 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District District Main Reasons for Not Selling Crops District Main Reasons for Not Selling Crops 10.3 Proportion of Households who Reported Not Selling Their Crops by District During 2002/03 Agricultural Year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 183 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 184 Total Number of Household % Number of Household % Number of Household Mpanda 3,343 6 56,190 94 59,533 Sumbawanga Rural 8,564 12 60,371 88 68,935 Nkansi 1,718 6 28,766 94 30,483 Sumbawanga Urban 3,258 24 10,051 76 13,309 Total 16,883 10 155,378 90 172,261 District Irrigated Area Area Irrigated Land this Year % Mpanda 915 844 92 Sumbawanga Rural 9,278 5,487 59 Nkansi 799 462 58 Sumbawanga Urban 1,588 730 46 Total 12,578 7,523 60 River Lake Dam Well Borehole Canal Total Mpanda 1,877 0 0 1,065 401 0 3,343 Sumbawanga Rural 7,058 0 344 592 0 571 8,564 Nkansi 788 148 0 474 0 307 1,718 Sumbawanga Urban 1,502 0 0 1,005 35 715 3,258 Total 11,225 148 344 3,137 435 1,593 16,883 Gravity Hand Bucket Hand Pump Motor Pump Other Total Mpanda 1,204 2,006 133 0 0 3,343 Sumbawanga Rural 7,296 1,150 0 0 118 8,564 Nkansi 1,099 541 0 78 0 1,718 Sumbawanga Urban 1,429 1,277 0 68 484 3,258 Total 11,028 4,974 133 146 602 16,883 Table 11.1: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year By District Households Practicing Irrigation Households not Practicing Irrigation 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District District Method of Obtaining Water 11.2: Area (ha)of Irrigated and Non Irrigatable (ha) Land By District 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 185 Flood Sprinkler Water Hose Bucket / Watering Can Total Mpanda 1,206 0 133 2,004 3,343 Sumbawanga Rural 7,305 0 115 1,144 8,564 Nkansi 1,027 76 0 615 1,718 Sumbawanga Urban 1,843 67 0 1,348 3,258 Total 11,381 143 248 5,111 16,883 % 67 1 1 30 100 Number % Number % Number % Mpanda 6,967 12 52,566 88 59,533 100 Sumbawanga Rural 5,546 8 63,389 92 68,935 100 Nkansi 1,549 5 28,934 95 30,483 100 Sumbawanga Urban 2,143 16 11,166 84 13,309 100 Total 16,206 9 156,055 91 172,261 100 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Mpanda . 105,686 . . 532 28,191 2,000 . 136,409 Sumbawanga Rural . 111,614 . . 595 8,675 2,315 723 123,923 Nkansi 0 3,452 . . . 73 606 234 4,365 Sumbawanga Urban 136 2,414 . 299 208 964 1,783 . 5,804 Total 136 223,167 . 299 1,336 37,903 6,705 957 270,502 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control 11.5 IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District District Method of Application Total 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District District Does the Household Have Any Erosion Control/Water Harvesting Have facility Does Not Have Tanzania Agriculture Sample Census - 2003 Rukwa 186 Appendix II 187 ACCESS TO INPUTS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 188 No. of Households % No. of Households % Mpanda 9,261 16 50,273 84 59,533 Sumbawanga Rural 454 1 68,363 99 68,817 Nkasi 439 1 29,964 99 30,403 Sumbawanga Urban 949 7 12,360 93 13,309 Total 11,103 6 160,960 94 172,063 No. of Households % No. of Households % Mpanda 2,273 4 57,260 96 59,533 Sumbawanga Rur 9,319 14 59,616 86 68,935 Nkasi 2,940 10 27,623 90 30,563 Sumbawanga Urb 5,434 41 7,875 59 13,309 Total 19,966 12 152,375 88 172,341 No. of Households % No. of Households % Mpanda 666 1 58,867 99 59,533 Sumbawanga Rur 1,406 2 67,529 98 68,935 Nkasi 686 2 29,797 98 30,483 Sumbawanga Urb 540 4 12,769 96 13,309 Total 3,298 2 168,962 98 172,261 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Total Crop Growing Households Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year NOT Using Chemical Fertilizers Using Chemical Fertilizers District Farm Yard Manure NOT Using Farm Yard Manure Total Crop Growing Households Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Using COMPOST Manure NOT Using COMPOST Manure Total Crop Growing Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 189 No. of Households % No. of Households % Mpanda 4,699 8 54,834 92 59,533 Sumbawanga Rural 6,263 9 62,672 91 68,935 Nkasi 1,504 5 28,980 95 30,483 Sumbawanga Urban 7,038 53 6,271 47 13,309 Total 19,503 11 152,758 89 172,261 No. of Households % No. of Households % Mpanda 269 0 59,264 100 59,533 Sumbawanga Rur 0 0 68,935 100 68,935 Nkasi 0 0 30,483 100 30,483 Sumbawanga Urb 0 0 13,309 100 13,309 Total 269 0 171,991 100 172,261 No. of Households % No. of Households % Mpanda 5,977 10 53,556 90 59,533 Sumbawanga Rur 1,869 3 67,067 97 68,935 Nkasi 388 1 30,096 99 30,483 Sumbawanga Urb 784 6 12,525 94 13,309 Total 9,018 5 163,243 95 172,261 Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Using Improved SeedsNOT Using Improved Seed Total number of Growing Households Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Using Herbicides Number of Agricultural Households NOT Using Herbicides Total number of Growing Households Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Using Insecticide/Fungicides NOT Using Pesticides/Fungicides Total number of Growing Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 190 Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Not applicable Total Number % Number % Number % Number % Number % Number % Number Mpanda 2,694 5 395 1 4,691 8 134 0 1,347 2 50,273 84 59,533 Sumbawanga Rural 0 0 0 0 454 1 0 0 0 0 68,363 99 68,817 Nkasi 0 0 0 0 439 1 0 0 0 0 29,964 99 30,403 Sumbawanga Urban 0 0 0 0 949 7 0 0 0 0 12,360 93 13,309 Total 2,694 2 395 0 6,533 4 134 0 1,347 1 160,960 94 172,063 Local Market / Trade Store Secondary Market Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 135 0 0 0 0 0 0 0 0 0 1,735 3 403 1 0 0 57,260 96 59,533 Sumbawanga Rural 233 0 224 0 121 0 0 0 0 0 4,334 6 4,408 6 0 0 59,616 86 68,935 Nkasi 0 0 0 0 0 0 0 0 78 0 1,422 5 1,283 4 157 1 27,623 90 30,563 Sumbawanga Urb 0 0 35 0 70 1 34 0 0 0 3,114 23 2,182 16 0 0 7,875 59 13,309 Total 368 0 258 0 190 0 34 0 78 0 10,605 6 8,275 5 157 0 152,375 88 172,341 Local Market / Trade Store Locally Produce d by Neighbour Not applicable Number % Number % Number % Number % Mpanda 134 0 532 1 0 0 58,867 99 59,533 Sumbawanga Rural 476 1 692 1 238 0 67,529 98 68,935 Nkasi 0 0 611 2 76 0 29,797 98 30,483 Sumbawanga Urb 68 1 472 4 0 0 12,769 96 13,309 Total 679 0 2,306 1 314 0 168,962 98 172,261 Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year District Total Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Local Farmers Group Large Scale Farm Locally Produced by Household Co-operative Neighbour Other Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 191 District Co- operative Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Large Scale Farm Locally Produced by Household Neighbour Not applicable Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 2,155 4 261 0 1,611 3 0 0 672 1 0 0 0 0 0 0 54,834 92 59,533 Sumbawanga Rur 0 0 115 0 4,141 6 230 0 0 0 0 0 1,186 2 591 1 62,672 91 68,935 Nkasi 0 0 0 0 1,106 4 316 1 0 0 82 0 0 0 0 0 28,980 95 30,483 Sumbawanga Urb 34 0 101 1 4,445 33 69 1 35 0 0 0 2,250 17 103 1 6,271 47 13,309 Total 2,190 1 477 0 11,303 7 616 0 706 0 82 0 3,436 2 694 0 152,758 89 172,261 District Local Market / Trade Store Crop Buyers Not applicable Total Number % Number % Number % Number Mpanda 135 0 135 0 59,264 100 59,533 Sumbawanga Rur 0 0 0 0 68,935 100 68,935 Nkasi 0 0 0 0 30,483 100 30,483 Sumbawanga Urb 0 0 0 0 13,309 100 13,309 Total 135 0 135 0 171,991 100 172,261 District Co- operative Local Farmers Group Local Market / Trade Store Development Project Crop Buyers Large Scale Farm Neighbour Not applicable Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,886 3 261 0 2,626 4 128 0 1,077 2 0 0 0 0 53,556 90 59,533 Sumbawanga Rur 0 0 0 0 1,354 2 0 0 0 0 0 0 515 1 67,067 97 68,935 Nkasi 0 0 0 0 306 1 0 0 0 0 82 0 0 0 30,096 99 30,483 Sumbawanga Urb 0 0 0 0 750 6 0 0 35 0 0 0 0 0 12,525 94 13,309 Total 1,886 1 261 0 5,036 3 128 0 1,111 1 82 0 515 0 163,243 95 172,261 Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 192 District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 941 10 1,209 13 2,551 28 2,955 32 1,605 17 9,261 Sumbawanga Rural 0 0 0 0 0 0 0 0 454 100 454 Nkasi 0 0 297 68 0 0 72 16 70 16 439 Sumbawanga Urban 67 7 69 7 543 57 169 18 100 11 949 Total 1,008 9 1,576 14 3,094 28 3,195 29 2,230 20 11,103 District Less than 1 km Between 1 and 3 km Between 3 and 10 km 20 km and Above Total Number % Number % Number % Number % Number Mpanda 2,004 88 135 6 0 0 134 6 2,273 Sumbawanga Rural 6,441 69 1,848 20 1,031 11 0 0 9,319 Nkasi 2,453 83 243 8 165 6 78 3 2,940 Sumbawanga Urban 4,385 81 612 11 437 8 0 0 5,434 Total 15,283 77 2,838 14 1,632 8 213 1 19,966 Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertil Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 193 Less than 1 km Between 1 and 3 km Number % Number % Mpanda 666 100 0 0 666 Sumbawanga Rural 1,297 92 0 0 1,297 Nkasi 611 89 76 11 686 Sumbawanga Urban 371 69 33 6 405 Total 2,946 89 109 3 3,054 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 135 2 940 16 1,210 20 1,471 25 2,221 37 5,977 Sumbawanga Rur 317 17 107 6 542 29 0 0 903 48 1,869 Nkasi 0 0 0 0 0 0 153 40 234 60 388 Sumbawanga Urb 0 0 34 4 475 61 68 9 208 27 784 Total 452 5 1,081 12 2,226 25 1,693 19 3,566 40 9,018 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 135 3 1,209 26 809 17 1,345 29 1,201 26 4,699 Sumbawanga Rur 1,296 21 460 7 471 8 468 7 3,569 57 6,263 Nkasi 149 10 82 5 407 27 0 0 867 58 1,504 Sumbawanga Urb 1,734 25 581 8 2,447 35 862 12 1,414 20 7,038 Total 3,313 17 2,332 12 4,134 21 2,675 14 7,050 36 19,503 District Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Total Number District Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 194 Total Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,574 3 36,226 72 778 1.5 0 0.0 269 0.5 11,299 22.5 128 0.3 50,273 Sumbawanga Rural 10,835 16 43,471 64 1,204 1.8 109 0.2 1,769 2.6 10,540 15.4 435 0.6 68,363 Nkasi 6,028 20 19,705 66 78 0.3 0 0.0 1,935 6.5 2,218 7.4 0 0.0 29,964 Sumbawanga Urban 311 3 11,614 94 34 0.3 0 0.0 70 0.6 297 2.4 34 0.3 12,360 Total 18,748 12 111,016 69 2,094 1.3 109 0.1 4,043 2.5 24,353 15.1 597 0.4 160,960 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 26,484 46 3,994 7 11,704 20 1,210 2 2,945 5 10,520 18 135 0 270 0 57,260 Sumbawanga Rural 5,333 9 4,586 8 28,681 48 10,556 18 2,454 4 6,848 11 0 0 1,158 2 59,616 Nkasi 4,938 18 2,021 7 14,055 51 1,538 6 2,251 8 2,494 9 0 0 327 1 27,623 Sumbawanga Urban 2,676 34 912 12 2,297 29 1,853 24 69 1 0 0 0 0 68 1 7,875 Total 39,431 26 11,513 8 56,736 37 15,157 10 7,719 5 19,861 13 135 0 1,823 1 152,375 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,733 3 4,137 7 18,643 32 2,273 4 20,896 35 10,916 19 0 0 269 0 58,867 Sumbawanga Rur 2,950 4 2,838 4 20,937 31 7,945 12 24,297 36 6,822 10 1,049 2 691 1 67,529 Nkasi 3,751 13 1,761 6 8,556 29 384 1 12,490 42 2,691 9 0 0 163 1 29,797 Sumbawanga Urb 2,011 16 905 7 3,002 24 1,411 11 5,239 41 202 2 0 0 0 0 12,769 Total 10,445 6 9,642 6 51,138 30 12,013 7 62,922 37 20,631 12 1,049 1 1,123 1 168,962 Input is of No Use Locally Produced by Household Other Other Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 195 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 8,422 15 40,479 74 1,040 2 245 0 269 0 4,252 8 0 0 128 0 54,834 Sumbawanga Rural 14,759 24 38,491 61 1,169 2 352 1 3,005 5 4,212 7 0 0 683 1 62,672 Nkasi 7,282 25 17,512 60 235 1 242 1 2,347 8 1,363 5 0 0 0 0 28,980 Sumbawanga Urban 1,142 18 4,489 72 103 2 0 0 66 1 403 6 35 1 34 1 6,271 Total 31,605 21 100,971 66 2,547 2 838 1 5,687 4 10,230 7 35 0 845 1 152,758 Total Number % Number % Number % Number % Number % Number % Number % Number Mpanda 12,565 21 40,102 68 1,042 2 0 0 674 1 4,500 8 381 1 59,264 Sumbawanga Rural 18,549 27 28,428 41 941 1 235 0 15,179 22 5,032 7 571 1 68,935 Nkasi 8,833 29 17,691 58 244 1 0 0 2,262 7 1,453 5 0 0 30,483 Sumbawanga Urban 173 1 9,195 69 208 2 0 0 2,359 18 1,339 10 34 0 13,309 Total 40,121 23 95,416 55 2,435 1 235 0 20,475 12 12,324 7 986 1 171,991 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 8,739 16 40,567 76 638 1 0 0 134 0 3,082 6 134 0 262 0 53,556 Sumbawanga Rural 23,987 36 37,828 56 934 1 235 0 1,861 3 1,757 3 0 0 464 1 67,067 Nkasi 6,799 23 19,916 66 395 1 240 1 1,483 5 1,102 4 161 1 0 0 30,096 Sumbawanga Urban 2,640 21 9,302 74 172 1 35 0 69 1 169 1 70 1 69 1 12,525 Total 42,165 26 107,613 66 2,138 1 510 0 3,547 2 6,109 4 365 0 796 0 163,243 Locally Produced by Household Other Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Other Input is of No Use Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 196 Total Number % Number % Number % Number % Number Mpanda 3,086 33 5,639 61 536 6 0 0 9,261 Sumbawanga Rural 117 26 117 26 220 49 0 0 454 Nkasi 70 16 369 84 0 0 0 0 439 Sumbawanga Urban 239 25 576 61 68 7 66 7 949 Total 3,512 32 6,701 60 824 7 66 1 11,103 Total Number % Number % Number % Number % Number Mpanda 1,208 53 930 41 135 6 0 0 2,273 Sumbawanga Rural 3,141 34 5,423 58 648 7 107 1 9,319 Nkasi 1,039 35 1,822 62 78 3 0 0 2,940 Sumbawanga Urban 1,844 34 3,452 64 138 3 0 0 5,434 Total 7,233 36 11,627 58 999 5 107 1 19,966 Total Number % Number % Number % Number % Number Mpanda 0 0 539 81 0 0 128 19 666 Sumbawanga Rural 0 0 1,182 84 224 16 0 0 1,406 Nkasi 0 0 611 89 76 11 0 0 686 Sumbawanga Urban 35 6 370 69 135 25 0 0 540 Total 35 1 2,702 82 434 13 128 4 3,298 Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 197 Total Number % Number % Number % Number Mpanda 1,744 37 2,955 63 0 0 4,699 Sumbawanga Rural 1,024 16 4,293 69 946 15 6,263 Nkasi 230 15 1,274 85 0 0 1,504 Sumbawanga Urban 2,239 32 4,595 65 204 3 7,038 Total 5,236 27 13,116 67 1,150 6 19,503 Total Number % Number Mpanda 269 100 269 Total 269 100 269 Total Total Number % Number % Number % Number % Number Number % Number % Number Mpanda 932 16 5,045 84 0 0 0 0 5,977 Mpanda 14,215 24 45,319 76 59,533 Sumbawanga Rural 352 19 1,277 68 120 6 120 6 1,869 Sumbawanga Rural 10,256 15 58,561 85 68,817 Nkasi 70 18 317 82 0 0 0 0 388 Nkasi 3,265 11 27,139 89 30,403 Sumbawanga Urban 309 39 440 56 35 4 0 0 784 Sumbawanga Urban 1,847 14 11,462 86 13,309 Total 1,665 18 7,079 78 155 2 120 1 9,018 Total 29,582 17 142,480 83 172,063 Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Number of Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average District Excellent Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Poor District Excellent Good Average Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 198 Total Number % Number % Number Mpanda 2,794 5 56,739 95 59,533 Sumbawanga Rural 19,435 28 49,500 72 68,935 Nkasi 6,710 22 23,854 78 30,563 Sumbawanga Urban 7,162 54 6,147 46 13,309 Total 36,102 21 136,239 79 172,341 Total Number % Number % Number Mpanda 1,060 2 58,474 98 59,533 Sumbawanga Rural 4,615 7 64,321 93 68,935 Nkasi 1,470 5 29,013 95 30,483 Sumbawanga Urban 813 6 12,496 94 13,309 Total 7,958 5 164,302 95 172,261 Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year COMPOST Manure Agricultural Households With NO Plan to use Next Year COMPOST Manure Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 199 Total Number % Number % Number Mpanda 6,152 10 53,381 90 59,533 Sumbawanga Rural 15,043 22 53,892 78 68,935 Nkasi 3,496 11 26,987 89 30,483 Sumbawanga Urban 8,071 61 5,238 39 13,309 Total 32,762 19 139,499 81 172,261 Total Number % Number % Number Mpanda 1,185 2 58,348 98 59,533 Sumbawanga Rural 1,624 2 67,312 98 68,935 Nkasi 705 2 29,779 98 30,483 Sumbawanga Urban 35 0 13,274 100 13,309 Total 3,549 2 168,712 98 172,261 Total Number % Number % Number Mpanda 7,039 12 52,494 88 59,533 Sumbawanga Rural 9,022 13 59,913 87 68,935 Nkasi 2,291 8 28,192 92 30,483 Sumbawanga Urban 1,821 14 11,488 86 13,309 Total 20,175 12 152,086 88 172,261 Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved District Agricultural Households With Plan to use Next Year Improved Seeds Agricultural Households With NO Plan to use Next Year Improved Seeds Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Pesticides/Fungicides Agricultural Households With NO Plan to use Next Year Pesticides/Fungicides Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Herbicides Agricultural Households With NO Plan to use Next Year Herbicides Tanzania Agriculture Sample Census - 2003 Rukwa 200 Appendix II 201 AGRICULTURE CREDITS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 202 Number % Number % Mpanda 4,552 94 270 6 4,821 Sumbawanga Rural 2,146 95 116 5 2,261 Nkansi 0 0 80 100 80 Sumbawanga Urban 135 67 67 33 202 Total 6,833 93 533 7 7,365 % 93 7 District Family, Friend and Relative Co- operative Trader / Trade Store Private Individual Religious Organisation / NGO / Project Total Mpanda 653 2,685 1,616 0 0 4,954 Sumbawanga Rural 1,174 0 966 121 0 2,261 Nkansi 80 0 0 0 0 80 Sumbawanga Urban 34 0 34 34 101 202 Total 1,941 2,685 2,616 155 101 7,499 % 26 36 35 2 1 100 13.2c: AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District Total 13.2a: AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District District Male Female Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 203 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucrac y procedure Credit granted too late Don't know about credit Total Mpanda 2,395 10,223 5,567 2,355 19,074 3,151 0 11,814 54,579 Sumbawanga Rural 2,296 27,400 11,635 1,772 11,677 567 115 11,211 66,674 Nkansi 999 9,302 2,750 881 9,917 313 76 6,165 30,403 Sumbawanga Urban 508 4,732 1,947 654 2,912 444 202 1,706 13,107 Total 6,198 51,657 21,899 5,662 43,580 4,476 393 30,897 164,762 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Other Mpanda 388 2,285 3,898 2,143 1,078 537 0 Sumbawanga Rural 2,025 0 0 0 0 0 237 Nkansi 80 0 0 0 0 0 0 Sumbawanga Urban 101 68 68 67 101 0 34 Total Credits 2,594 2,353 3,966 2,210 1,178 537 270 13.1a: AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District 13.1b: AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District Tanzania Agriculture Sample Census - 2003 Rukwa 204 Appendix II 205 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 206 Eucalyptus Spp Senna Spp Gravellis Afzelia Quanzensi s Jakaranda Spp Acacia Spp Cyprus Spp Trichilia Spp Pinus Spp Azadrit achta Spp Melicia excelsa Casuri na Equiset filia Tectona Grandis Leucena Spp Syszygiu m Spp Calophylum Inophyllum Total 342 1,480 419 . 3 . . . . 2 5 . . . . . 2,251 3,487 22 . . 23 8 . . 3 6 . . . . 2 . 3,551 2,593 276 24 . 152 . 69 10 10 . . 5 5 2 . 2 3,148 33,724 . 10 300 67 82 16 . . . . . . . . . 34,199 40,146 1,778 453 300 245 90 85 10 13 8 5 5 5 2 2 2 43,149 93 4 1 1 1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 Number of Househol ds Number of Trees Number of Household s Number of Trees Number of Househol ds Number of Trees Number of Househ olds Number of Trees Mpanda 61 925 43 1,016 2 310 106 2,251 Sumbawanga Rural 33 531 11 1,813 11 1,207 55 3,551 Nkansi 39 462 5 107 11 2,579 55 3,148 Sumbawanga Urban 49 2,354 22 2,091 65 29,754 136 34,199 Total 182 4,272 81 5,027 89 33,850 352 43,149 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 9 0 41 60 1 0 112 Sumbawanga Rural 34 11 0 4 9 2 0 60 Nkansi 17 1 0 27 15 1 1 62 Sumbawanga Urban 84 16 1 42 2 0 0 145 Total 136 37 1 114 86 4 1 379 14.3: ON FARM TREE PLANTING: Main Use of Trees By District District Main Use 14.1: ON FARM TREE PLANTING: Number of Planted Trees By Species and District, Rukwa Region 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 207 0-9 1-19 20-29 30-39 40-49 60+ Total Mpanda 2,281 3,198 2,618 378 0 131 8,606 Sumbawanga Rural 4,364 1,339 1,554 628 0 2,555 10,440 Nkansi 6,357 619 81 493 329 326 8,205 Sumbawanga Urban 5,592 1,950 996 611 136 0 9,285 Total 18,593 7,105 5,250 2,110 465 3,012 36,536 % 51 19 14 6 1 8 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 11 4 59 35 0 2 112 Sumbawanga Rural 6 21 1 26 5 2 0 61 Nkansi 12 10 0 19 18 2 1 62 Sumbawanga Urban 29 30 0 81 3 2 0 145 Total 48 72 5 185 61 6 3 380 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 9 0 41 60 1 0 112 Sumbawanga Rural 34 11 0 4 9 2 0 60 Nkansi 17 1 0 27 15 1 1 62 Sumbawanga Urban 84 16 1 42 2 0 0 145 Total 136 37 1 114 86 4 1 379 14.6: TREE FARMING: Number of responses by main use of planted trees and District for the 2002/03 agricultural year, Rukwa Region District Main Use 14.5: TREE FARMING: Number of responses by second use of planted trees and District for the 2002/03 District Second Use 14.4: TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) Tanzania Agriculture Sample Census - 2003 Rukwa 208 Appendix II 209 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 210 Total Number of Households Number % Number % Number Mpanda 11,351 19 48,182 81 59,533 Sumbawanga Rural 13,859 20 55,076 80 68,935 Nkansi 1,834 6 28,649 94 30,483 Sumbawanga Urban 2,002 15 11,307 85 13,309 Total 29,046 17 143,215 83 172,261 Total Number % Number % Number % Number % Number Mpanda 667 6 6,021 53 3,023 27 1,640 14 11,351 Sumbawanga Rural 1,661 12 7,930 58 4,151 30 0 0 13,742 Nkansi 225 12 927 51 682 37 0 0 1,834 Sumbawanga Urban 103 5 1,660 83 203 10 35 2 2,002 Total 2,657 9 16,539 57 8,059 28 1,675 6 28,930 Total Number % Number % Number % Number % Number % Number % Number Mpanda 8,141 73 2,405 21 135 1 401 4 135 1 11,217 81 11,217 Sumbawanga Rural 13,037 94 350 3 117 1 355 3 0 0 13,859 80 13,859 Nkansi 1,596 87 82 4 78 4 78 4 0 0 1,834 94 1,834 Sumbawanga Urban 1,761 90 138 7 0 0 33 2 35 2 1,967 85 1,967 Total 24,535 85 2,975 10 330 1 867 3 170 1 28,877 83 28,877 15.1 CROP EXTENSION\" Number of Households Receiving Extension Messages By District District District 15.1 CROP EXTENSION: Number of Households By Quality of Extension Services By District During the 2002/03 agricultural year, Rukwa Region Households Receiving Extension Advice Households Not Receiving Extension Advice Very Good Good Average Poor District 15.3: EXTENSION MESSAGES: Number of Households By Source of Crop Extension Messages By District During 2002/03 Agricultural Year, Rukwa Region Government NGO / Development Project Cooperative Large Scale Farm Other Not Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 211 Government NGO / Development Project Cooperative Large Scale Farm Other Total Househol ds receiving advice Total Number of Households % of total number of households Mpanda 6,231 2,151 135 133 135 8,785 59,533 15 Sumbawanga Rural 11,794 238 0 120 0 12,152 68,935 18 Nkansi 1,362 82 78 78 0 1,601 30,483 5 Sumbawanga Urban 1,693 138 0 33 0 1,864 13,309 14 Total 21,080 2,610 213 364 135 24,402 172,261 14 Government NGO / Development Project Cooperative Large Scale Farm Not applica ble Total Total Number of Households % of total number of households Mpanda 2,112 1,346 134 0 0 3,591 59,533 6 Sumbawanga Rural 8,108 119 117 116 120 8,579 68,935 12 Nkansi 387 82 78 0 70 618 30,483 2 Sumbawanga Urban 1,218 241 0 33 0 1,492 13,309 11 Total 11,825 1,787 329 149 190 14,280 172,261 8 Government NGO / Development Project Cooperative Large Scale Farm Not applica ble Total Total Number of Households % of total number of households Mpanda 1,587 269 0 0 0 1,857 59,533 3 Sumbawanga Rural 7,115 119 117 116 115 7,580 68,935 11 Nkansi 527 82 78 0 0 687 30,483 2 Sumbawanga Urban 881 207 0 0 0 1,088 13,309 8 Total 10,110 676 195 116 115 11,212 172,261 7 15.4: EXTENSION MESSAGES: Number of Households By Receiving Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District Erosion Control 15.6: EXTENSION MESSAGES: Number of Households By Receiving Advice on the Erosion Control By Source of Messages By District Rukwa Region District Use of Agrochemicals District Spacing 15.5: EXTENSION MESSAGES: Number of Households By Receiving Advice on the Use of Agro-chemicals By Source of Messages By District Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 212 Government NGO / Development Project Cooperative Large Scale Farm Other Total Total Number of Households % of total number of households Mpanda 1,460 0 135 0 0 1,594 59,533 3 Sumbawanga Rural 10,561 357 0 361 0 11,279 68,935 16 Nkansi 452 82 78 0 0 612 30,483 2 Sumbawanga Urban 1,217 308 0 35 35 1,594 13,309 12 Total 13,689 746 213 396 35 15,080 172,261 9 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 1,998 2,019 133 0 135 4,285 59,533 7 Sumbawanga Rural 5,735 348 0 0 120 6,203 68,935 9 Nkansi 446 82 78 0 0 606 30,483 2 Sumbawanga Urban 1,213 103 0 67 0 1,384 13,309 10 Total 9,392 2,553 212 67 255 12,478 172,261 7 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 5,516 1,616 0 0 135 7,267 59,533 12 Sumbawanga Rural 8,837 822 115 0 120 9,893 68,935 14 Nkansi 820 82 0 78 0 980 30,483 3 Sumbawanga Urban 1,384 103 0 0 68 1,555 13,309 12 Total 16,557 2,623 115 78 323 19,696 172,261 11 15.7: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.8: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 213 Government NGO / Development Project Not applicable Total Total Number of Households % of total number of households Mpanda 402 0 0 402 59,533 1 Sumbawanga Rural 1,559 0 122 1,681 68,935 2 Nkansi 152 70 0 222 30,483 1 Sumbawanga Urban 0 35 33 68 13,309 1 Total 2,113 105 155 2,373 172,261 1 Government NGO / Development Project Cooperative Large Scale Farm Other Total Total Number of Households % of total number of households Mpanda 529 404 0 133 0 1,066 59,533 2 Sumbawanga Rural 4,520 119 0 120 0 4,758 68,935 7 Nkansi 451 0 78 0 0 529 30,483 2 Sumbawanga Urban 341 104 0 0 35 480 13,309 4 Total 5,840 628 78 253 35 6,834 172,261 4 Government NGO / Development Project Cooperative Large Scale Farm Total Total Number of Households % of total number of households Mpanda 6,548 270 0 0 6,818 59,533 11 Sumbawanga Rural 10,437 119 109 121 10,785 68,935 16 Nkansi 992 0 78 78 1,149 30,483 4 Sumbawanga Urban 1,148 206 0 0 1,354 13,309 10 Total 19,125 595 187 199 20,106 172,261 12 Mechanisation / LST Irrigation Technology 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Crop Storage District District District 15.11: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.12: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 214 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 803 0 0 135 0 938 59,533 2 Sumbawanga Rural 3,700 118 121 121 0 4,060 68,935 6 Nkansi 379 0 78 78 0 536 30,483 2 Sumbawanga Urban 342 35 0 0 35 412 13,309 3 Total 5,225 153 199 334 35 5,946 172,261 3 % 88 3 3 6 1 100 Government NGO / Development Project Other Not applicable Total Total Number of Households % of total number of households Mpanda 1,467 0 135 0 1,602 59,533 3 Sumbawanga Rural 4,820 119 0 0 4,939 68,935 7 Nkansi 299 0 0 0 299 30,483 1 Sumbawanga Urban 207 136 0 35 378 13,309 3 Total 6,793 255 135 35 7,218 172,261 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Mpanda 132 390 135 135 133 0 924 59,533 2 Sumbawanga Rural 3,813 119 121 121 0 121 4,293 68,935 6 Nkansi 377 78 0 0 0 0 455 30,483 1 Sumbawanga Urban 847 237 0 33 0 0 1,116 13,309 8 Total 5,168 823 255 289 133 121 6,789 172,261 4 % 76 12 4 4 2 2 100 District Vermin Control Agro-progressing Agro-Forestry 15.13: EXTENSION MESSAGES: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.15: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-Forestry By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.14: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 215 Government Total Total Number of Households % of total number of households Mpanda 0 0 59,533 0 Sumbawanga Rural 602 602 68,935 1 Nkansi 0 0 30,483 0 Sumbawanga Urban 0 0 13,309 0 Total 602 602 172,261 0 % 100 100 Government Total Total Number of Households % of total number of households Mpanda 0 0 59,533 0.0 Sumbawanga Rural 241 241 68,935 0.4 Nkansi 0 0 30,483 0.0 Sumbawanga Urban 0 0 13,309 0.0 Total 241 241 172,261 0.0 Received Adopted % Received Adopted % Received Adopted % Mpanda 8,785 6,538 74 3,591 2,386 66 1,857 803 43 Sumbawanga Rural 12,152 11,556 95 8,579 3,184 37 7,461 3,331 45 Nkansi 1,601 1,530 96 548 322 59 687 534 78 Sumbawanga Urban 1,864 1,629 87 1,492 1,188 80 1,088 685 63 Total 24,402 21,252 87 14,209 7,080 50 11,093 5,352 48 15.16: EXTENSION MESSAGES: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during Beekeeping Fish Farming 15.17: EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District 15.18: CROP EXTENSION\" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Rukwa Region. Spacing Use of Agrochemicals District Erosion Control Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 216 Received Adopted % Received Adopted % Received Adopted % Mpanda 1,594 531 33 4,153 3,225 78 7,267 2,922 40 Sumbawanga Rural 11,286 5,040 45 5,972 932 16 9,893 2,548 26 Nkansi 612 310 51 606 70 12 980 305 31 Sumbawanga Urban 1,525 1,221 80 1,314 405 31 1,554 372 24 Total 15,017 7,101 47 12,045 4,633 38 19,694 6,147 31 Received Adopted % Received Adopted % Received Adopted % Mpanda 135 0 0 800 671 84 6,818 4,829 71 Sumbawanga Rural 1,442 0 0 4,530 1,539 34 10,785 10,659 99 Nkansi 222 153 69 459 236 52 1,149 1,149 100 Sumbawanga Urban 35 103 296 380 309 81 1,319 1,253 95 Total 1,833 255 14 6,169 2,755 45 20,071 17,889 89 15.19: CROP EXTENSION\" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Rukwa Region. Inorganic Fertilizer Use Use of Improved Seed Organic Fertilizer Use District 15.20: CROP EXTENSION\" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Rukwa Region. District Crop Storage Irrigation Technology Mechanisation / LST Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 217 Received Adopted % Received Adopted % Received Adopted % Mpanda 804 670 83 1,602 1,468 92 924 536 58 Sumbawanga Rural 4,060 3,346 82 4,707 4,467 95 4,293 2,870 67 Nkansi 536 536 100 299 299 100 373 225 60 Sumbawanga Urban 174 277 159 343 276 81 1,116 716 64 Total 5,573 4,830 87 6,951 6,510 94 6,707 4,347 65 Received Adopted % Received Adopted % Received Adopted % Mpanda 924 536 58 0 0 0 0 0 Sumbawanga Rural 4,293 2,870 67 481 240 50 241 0 0 Nkansi 373 225 60 0 0 0 0 0 0 Sumbawanga Urban 1,116 716 64 0 0 0 34 0 0 Total 6,707 4,347 65 481 240 50 241 34 0 15.20: CROP EXTENSION\" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 4) During the 2002/03 Agricultural Year, Rukwa Region. District 15.20: CROP EXTENSION\" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Rukwa Region. District Vermin Control Agro-progressing Agro-forestry Agro-forestry Beekeeping Fish Farming Tanzania Agriculture Sample Census - 2003 Rukwa 218 Appendix II 219 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 220 No. of Households % No. of Households % Mpanda 4,121 7 55,412 93 59,533 Sumbawanga Rural 47,115 68 21,820 32 68,935 Nkansi 16,622 55 13,861 45 30,483 Sumbawanga Urban 11,547 87 1,762 13 13,309 Total 79,406 46 92,855 54 172,261 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Mpanda 15,523 22,217 38,844 8,368 0 0 35,062 0 0 392 392 1,308 59,346 22,609 40,152 Sumbawanga Rural 60,728 140,521 259,293 35,116 333 0 86,142 3,684 0 2,493 116 0 184,479 144,654 259,293 Nkansi 30,126 55,435 97,932 16,222 3,150 23 28,090 0 0 5,708 0 0 80,146 58,585 97,955 Sumbawanga Urban 13,079 29,683 44,003 5,342 2,255 51 17,338 1,469 17 6,535 336 0 42,294 33,743 44,071 Total 119,456 247,856 440,072 65,048 5,738 74 166,631 5,153 17 15,128 844 1,308 366,264 259,592 441,471 17.1: ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District During 2002/03 agricultural year, Rukwa Region Households Using Draft Animals Household Not Using Draft Animals District Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 221 Total Number % Number % Number Mpanda 2,401 12 56,864 38 59,266 Sumbawanga Rural 9,358 45 59,577 39 68,935 Nkansi 3,476 17 27,007 18 30,483 Sumbawanga Urban 5,361 26 7,948 5 13,309 Total 20,597 100 151,397 100 171,993 Area (%) % Area (%) % Area (%) % Mpanda 1,063 7 357 65 1,420 9 Sumbawanga Rural 7,851 50 63 11 7,914 49 Nkansi 3,398 22 80 15 3,478 22 Sumbawanga Urban 3,286 21 52 9 3,338 21 Total 15,598 100 551 100 16,150 100 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost District Farm Yard Manure Area Applied Compost Area Applied Total District Using Organic Fertilizer Not Using Organic Fertilizer Did you apply organic fertilizer during 2002/03? Tanzania Agriculture Sample Census - 2003 Rukwa 222 Appendix II 223 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 224 Total Agricultural Households Total Livestock Keeping Households Number % Number % Mpanda 4,580 8 54,954 92 59,533 0 Sumbawanga Rural 24,593 36 44,342 64 68,935 416 Nkansi 9,021 30 21,463 70 30,483 0 Sumbawanga Urban 5,357 40 7,952 60 13,309 0 Total 43,551 25 128,710 75 172,261 416 Number of Household % Number of Cattle % Average Number Per Household Number % Number % Number 1-5 25,854 59 66,582 13 3 6-10 7,656 18 58,255 12 8 11-15 3,971 9 51,045 10 13 16-20 1,471 3 26,283 5 18 21-30 2,033 5 51,019 10 25 31-40 650 1 23,832 5 37 41-50 573 1 27,494 5 48 51-60 347 1 20,178 4 58 61-100 233 1 18,672 4 80 101-150 299 1 38,128 8 127 151+ 463 1 123,239 24 266 Total 43,551 100 504,727 100 12 Type Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total Cattle % Bulls 36,029 99 171 0 214 1 36,413 7 Cows 170,403 100 0 0 504 0 170,907 34 Steers 124,331 100 0 0 0 0 124,331 25 Heifers 68,310 100 104 0 213 0 68,627 14 Male Calves 42,726 100 0 0 142 0 42,868 8 Female Calves 61,546 100 0 0 33 0 61,580 12 Total 503,345 100 274 0 1,107 0 504,727 100 18.4.1 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 Herd Size 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Rukwa Region District Households Rearing Cattle Households Not Rearing Cattle Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 225 Improved Beef Improved Dairy Total Cattle Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Mpanda 4,447 82,470 100 0.0 0 0 401 401 0.5 4,580 82,871 16.41898276 Sumbawanga Rural 24,593 236,511 100 0.0 0 0 109 109 0.0 24,593 236,620 46.88081187 Nkansi 8,949 148,683 100 0.0 0 0 235 397 0.3 9,021 149,080 29.5367702 Sumbawanga Urban 5,357 35,682 99 69 274 1 133 200 0.6 5,357 36,156 7.163435173 Total 43,345 503,345 100 69 274 0.1 878 1,107 0.2 43,551 504,727 100 Bulls Cows Steers Heifers Male Calves Female Total Mpanda 6,334 24,220 18,083 17,232 7,648 8,952 82,470 Sumbawanga Rural 18,228 89,268 60,245 22,211 17,518 29,041 236,511 Nkansi 8,757 46,112 34,172 25,138 14,651 19,852 148,683 Sumbawanga Urban 2,709 10,802 11,831 3,730 2,908 3,701 35,682 Total 36,029 170,403 124,331 68,310 42,726 61,546 503,345 Bulls Cows Steers Heifers Male Calves Female Total Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 0 Nkansi 0 0 0 0 0 0 0 Sumbawanga Urban 171 0 0 104 0 0 274 Total 171 0 0 104 0 0 274 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Number - Improved Beef Cattle 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 226 Bulls Cows Steers Heifers Male Calvesemale Calves Total Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 0 Nkansi 0 0 0 0 0 0 0 Sumbawanga Urban 171 0 0 104 0 0 274 Total 171 0 0 104 0 0 274 Bulls Cows Steers Heifers Male Calvesemale Calves Total Mpanda 6,468 24,354 18,083 17,365 7,648 8,952 82,871 Sumbawanga Rural 18,228 89,268 60,245 22,211 17,627 29,041 236,620 Nkansi 8,838 46,349 34,172 25,218 14,651 19,852 149,080 Sumbawanga Urban 2,880 10,935 11,831 3,834 2,942 3,734 36,156 Total 36,413 170,907 124,331 68,627 42,868 61,580 504,727 District Category - Total Cattle 18.7CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Beef Cattle 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 227 GOAT PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 228 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Mpanda 16,384 116,377 98 134 806 1 269 1,077 1 16,384 118,261 Sumbawanga 16,895 116,919 99 346 1,044 1 107 645 1 16,895 118,607 Nkansi 6,538 42,696 100 0 0 0 0 0 0 6,538 42,696 Sumbawanga 3,334 12,869 97 104 416 3 0 0 0 3,334 13,285 Total 43,150 288,862 99 584 2,265 1 377 1,722 1 43,150 292,849 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 20,967 48.6 51,397 17.6 2 5-9 12,819 29.7 82,580 28.2 6 10-14 5,226 12.1 60,060 20.5 11 15-19 1,578 3.7 26,125 8.9 17 20-24 1,199 2.8 24,764 8.5 21 25-29 558 1.3 15,316 5.2 27 30-39 482 1.1 15,731 5.4 33 40+ 321 0.7 16,877 5.8 53 Total 43,150 100.0 292,849 100.0 7 19.2: GOAT PRODUCTION: Total Number of Households Rearing Goats and Heads of Goats by Herd size on 1st October 2003 19.1: GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Total Goat Improved Dairy Improved for Meat Indigenous Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 229 Number % Number % Number % Number % Billy Goat 45,529 95 1,775 4 645 1 47,949 16 Castrated Goat 4,372 94 0 0 269 6 4,641 2 She Goat 149,160 100 70 0 0 0 149,229 51 Male Kid 45,118 98 109 0 808 2 46,035 16 She Kid 44,684 99 311 1 0 0 44,995 15 Total 288,862 99 2,265 1 1,722 1 292,849 100 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 19,821 1,679 60,811 17,727 16,339 116,377 Sumbawanga Rural 16,410 1,944 59,624 18,309 20,632 116,919 Nkansi 7,557 618 21,169 7,358 5,994 42,696 Sumbawanga Urban 1,741 130 7,555 1,724 1,719 12,869 Total 45,529 4,372 149,160 45,118 44,684 288,862 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 806 0 0 0 0 806 Sumbawanga Rural 691 0 0 109 243 1,044 Nkansi 0 0 0 0 0 0 Sumbawanga Urban 278 0 70 0 68 416 Total 1,775 0 70 109 311 2,265 District Number of Improved for Meat 19.4 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Type 19.5: GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 19.:3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Category of Goats Total Goat Number of Improved Dairy Number of Improved for Meat Number of Indigenous Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 230 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda . 269 . 808 . 1,077 Sumbawanga Rural 645 . . . . 645 Nkansi . . . . . . Sumbawanga Urban . . . . . . Total 645 269 . 808 . 1,722 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 20,627 1,948 60,811 18,535 16,339 118,261 Sumbawanga Rural 17,746 1,944 59,624 18,418 20,876 118,607 Nkansi 7,557 618 21,169 7,358 5,994 42,696 Sumbawanga Urban 2,019 130 7,625 1,724 1,787 13,285 Total 47,949 4,641 149,229 46,035 44,995 292,849 District Total Goat 19.6: GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, District Number of Improved Dairy 19.7: GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 231 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 232 Breed Number of Indigenous % Number of Improved for Mutton % Total Sheep % Ram 6,365 100 0 0 6,365 18 Castrated Sheep 134 100 0 0 134 0 She Sheep 18,517 100 0 0 18,517 51 Male Lamb 5,311 100 0 0 5,311 15 She Lamb 5,746 100 0 0 5,746 16 Total 36,073 100 0 0 36,073 100 District Total Livestock Keeping Households Number % Number % Mpanda 1,955 3 57,579 97 59,533 0 Sumbawanga Rural 1,478 2 67,457 98 68,935 416 Nkansi 1,237 4 29,246 96 30,483 0 Sumbawanga Urban 99 1 13,210 99 13,309 0 Total 4,770 3 167,491 97 172,261 416 Number % Number % Number % Mpanda 13,967 100 0 0 13,967 39 Sumbawanga Rural 10,953 100 0 0 10,953 30 Nkansi 10,756 100 0 0 10,756 30 Sumbawanga Urban 397 100 0 0 397 1 Total 36,073 100 0 0 36,073 100 Number of Households Average Sheep Number of Households Average Sheep Mpanda 1,955 0 0 0 1,955 7 Sumbawanga Rural 1,478 0 0 0 1,478 7 Nkansi 1,237 0 0 0 1,237 9 Sumbawanga Urban 99 0 0 0 99 4 Total 4,770 0 0 0 4,770 8 Total Numbver of Households Number of Indigenous Number of Improved for Mutton Total Sheep 20.3: SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 District Total Households Raising Sheep Average Sheep 20.4: Number of Sheep per Household by Category and district as of 1st October 2003. 20.1: SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year District Number of Indigenous Number of Improved for Mutton 20.2: SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year Households Raising Sheep Households Not Raising Sheep Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 233 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 2,021 42 5,313 15 3 5-9 1,574 33 11,157 31 7 10-14 448 9 4,833 13 11 15-19 442 9 7,296 20 17 20-24 130 3 2,608 7 20 30-39 154 3 4,866 13 32 Total 4,770 100 36,073 100 8 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Number of Indigenous Mpanda 1,801 134 7,073 2,216 2,743 13,967 Sumbawanga Rural 2,184 0 5,422 1,734 1,613 10,953 Nkansi 2,281 0 5,756 1,361 1,357 10,756 Sumbawanga Urban 99 0 265 0 33 397 Total 6,365 134 18,517 5,311 5,746 36,073 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Sheep Mpanda 1,801 134 7,073 2,216 2,743 13,967 Sumbawanga Rural 2,184 . 5,422 1,734 1,613 10,953 Nkansi 2,281 . 5,756 1,361 1,357 10,756 Sumbawanga Urban 99 . 265 . 33 397 Total 6,365 134 18,517 5,311 5,746 36,073 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003. 20.8 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep 20.6: SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Sheep Tanzania Agriculture Sample Census - 2003 Rukwa 234 Appendix II 235 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 236 Number % Number % 1-4 8,000 66 13,781 27 2 5-9 2,769 23 19,645 38 7 10-14 859 7 9,228 18 11 15-19 163 1 2,526 5 16 30-39 194 2 5,968 12 31 40+ 115 1 691 1 6 Total 12,101 100 51,840 100 4 District Number of Household Number of Pig Average Number Per Household Mpanda 1,343 4,837 4 Sumbawanga Rural 8,350 36,455 4 Nkansi 1,007 8,396 8 Sumbawanga Urban 1,400 2,152 2 Total 12,101 51,840 4 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Mpanda 804 . 1,074 1,076 1,883 4,837 Sumbawanga Rural 3,968 334 11,131 10,305 10,716 36,455 Nkansi 608 80 1,722 3,557 2,428 8,396 Sumbawanga Urban 373 35 1,508 136 101 2,152 Total 5,753 449 15,435 15,074 15,128 51,840 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year District 21.2: PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.3: PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Pigs Type District Households Raising Pig Herds of Pigs Average Number Per Household Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 237 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 238 Total Number % age Number % age Number Mpanda 6,198 53 5,435 47 11,633 Sumbawanga Rural 8,564 28 21,602 72 30,166 Nkasi 3,538 33 7,159 67 10,697 Sumbawanga Urban 2,720 48 2,975 52 5,695 Total 21,021 36 37,171 64 58,192 Number of Households % Number of Households % Number of Households % Number of Households % Mpanda 3,163 53 4,357 27 130 10 803 25 Sumbawanga Rural 1,754 29 5,881 37 930 72 1,661 53 Nkasi 768 13 3,147 20 226 18 317 10 Sumbawanga Urban 265 4 2,583 16 0 0 380 12 Total 5,950 100 15,968 100 1,286 100 3,161 100 Total No. of Households % age No. of Households % age No. of Households Mpanda 1,604 14 9,493 86 11,097 Sumbawanga Rur 3,226 11 25,665 89 28,891 Nkasi 1,668 16 9,028 84 10,697 Sumbawanga Urb 100 2 5,527 98 5,627 Total 6,598 12 49,714 88 56,312 Total No. of Households % age No. of Households % age No. of Households % age No. of Households % age No. of Households Mpanda 531 33 539 34 401 25 134 8 1,604 Sumbawanga Rur 3,226 100 0 0 0 0 0 0 3,226 Nkasi 1,514 91 154 9 0 0 0 0 1,668 Sumbawanga Urb 65 65 35 35 0 0 0 0 100 Total 5,336 81 727 11 401 6 134 2 6,598 Trapping Method of Tsetse Flies Control Spray NO Tsetse Flies Problems 22.4: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Dipping District None Tsetse Flies Problems 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households deworming Livestock by District during 2002/03 Agricultural Year District No. of Households Demworming Livestock No. of Households NOT Demworming their animals 22.2: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock Dewormed Goats Dewormed Cattles 22.3: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year Dewormed Sheep Dewormed Pigs District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 239 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 240 Number % Type Number Indigenous Chicken 1,114,556 99 Ducks 88,647 Layer 7,261 1 Turkeys 2,686 Broiler 615 0 Rabbits 17,876 0 Donkeys 11,190 Total 1,122,432 100 120,399 Indigenous Chicken Layer Broiler Total Ducks Turkeys Rabbits Donkeys Other Mpanda 492,601 . 0 492,601 Mpanda 38,381 0 5,650 4,265 0 Sumbawanga Rural 443,312 2,414 213 445,939 Sumbawanga Rural 40,326 2,516 5,263 3,578 7,644 Nkasi 129,096 1,144 402 130,643 Nkasi 9,294 0 3,561 2,629 9,765 Sumbawanga Urban 49,547 3,703 0 53,250 Sumbawanga Urban 646 170 3,402 718 0 Total 1,114,556 7,261 615 1,122,432 Total 88,647 2,686 17,876 11,190 17,409 1,122,432 Number % 1 - 4 38,452 35 92,665 2 5 - 9 31,281 28 204,580 7 10 - 19 25,278 23 321,753 13 20 - 29 6,961 6 155,776 22 30 - 39 4,248 4 136,546 32 40 - 49 2,087 2 87,172 42 50 - 99 1,365 1 87,994 64 100+ 240 0 35,946 150 Total 109,912 100 1,122,432 10 23a: OTHER LIVESTOCK: Total number of Other Livestock by Type as of 1st October 2003 Type Number of Chicken 23b: OTHER LIVESTOCK: Number of chicken by Category of Chicken and District as of 1st October, 2003 Chicken Number of chicken Average chicken per household Flock Size Others Chicken rearing Households 23d: OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size 23c: OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Type of Livestock District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 241 FISH FARMING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 242 Total Number % Number % Number Mpanda 0 0.0 59,533 100.0 59,533 Sumbawanga Rural 0 0.0 68,935 100.0 68,935 Nkasi 80 0.3 30,403 99.7 30,483 Sumbawanga Urban 0 0.0 13,309 100.0 13,309 Total 80 0.0 172,181 100.0 172,261 Natural Pond Total Nkasi 80.2 80.2 Total 80.2 80.2 Source of Fingerlings Neighbour Total Number Number Nkasi 80 80 Total 80 80 Where sold Trader at Farm Total Number Number Nkasi 80 80 Total 80 80 District Number of Tilapia Number of Carp Number of Others Nkasi 8,018 0 0 Total 8,018 0 0 District 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.2b FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year District 28.2c: FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year District System of Fish Farming Was fish farming carried out by this household during 2002/03? District 28.1a: FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year Yes No 28.2a: FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 243 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 244 District Number % Number % Mpanda 3,632 6 55,901 94 59,533 11,633 31.2 Sumbawanga Rural 9,265 13 59,671 87 68,935 29,751 31.1 Nkasi 1,999 7 28,485 93 30,483 10,697 18.7 Sumbawanga Urban 2,170 16 11,139 84 13,309 5,695 38.1 Total 17,065 10 155,195 90 172,261 57,776 29.5 Governmen t NGO / Development Project Co- operative Large Scale Farmer Other Mpanda 2,565 0 0 134 0 Sumbawanga Rur 5,522 0 121 120 120 Nkasi 1,399 0 0 78 0 Sumbawanga Urb 1,967 35 0 134 0 Total 11,452 35 121 466 120 Advice Governmen t NGO / Development Project Mpanda 135 0 135 11,633 1 Sumbawanga Rur 1,425 0 1,425 29,751 5 Nkasi 0 0 0 10,697 0 Sumbawanga Urb 169 33 202 5,695 4 Total 1,729 33 1,762 % receiving advice out of total Total 29.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Total Number of households raising livestock % 29.1a: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By District during the 2002/03 Agricultural Year 29.1b Livestock Extension Providers: Number of Households By Source of Extension and District, 2002/03 Agricultural Year District Source of Advice Received Livestock Advice Did NOT Receiving Livestock Advice Total Number of households raising livestock Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 245 Governmen t NGO / Development Project Other Mpanda 135 0 0 135 11,633 1.2 Sumbawanga Rural 1,662 0 0 1,662 29,751 5.6 Nkansi 0 0 0 0 10,697 0.0 Sumbawanga Urban 238 33 0 271 5,695 4.8 Total 2,035 33 0 2,068 57,776 3.6 % 98 2 0 100 Governmen t NGO / Development Project Co-operative Large Scale Farmer Other Total Mpanda 2,565 0 0 134 0 2,699 11,633 23 Sumbawanga Rur 5,522 0 121 120 120 5,882 29,751 20 Nkasi 1,399 0 0 78 0 1,477 10,697 14 Sumbawanga Urb 1,967 35 0 134 0 2,135 5,695 37 Total 11,452 35 121 466 120 12,193 57,776 21 % 93.9 0.3 1.0 3.8 1.0 100.0 Governmen t NGO / Development Project Other Total Mpanda 403 0 0 403 11,633 3 Sumbawanga Rur 1,556 0 120 1,676 29,751 6 Nkasi 153 0 0 153 10,697 1 Sumbawanga Urb 69 35 0 104 5,695 2 Total 2,182 35 120 2,337 57,776 4 % 93.4 1.5 5.1 100 % receiving advice out of total Total Number of households raising livestock % receiving advice out of total 29.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice on Milk Hygene Total Number of households raising livestock District Source of Advice on Herd Flock/Flock Size Total Number of households raising livestock 29.1f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 246 Governmen t NGO / Development Project Other Mpanda 134 0 0 134 11,633 1 Sumbawanga Rural 1,302 117 0 1,419 29,751 5 Nkansi 0 0 0 0 10,697 0 Sumbawanga Urban 170 100 0 270 5,695 5 Total 1,606 216 0 1,823 57,776 3 % 88 12 0 100 Governmen t NGO / Development Project Co-operative Mpanda 267 0 0 267 11,633 2 Sumbawanga Rural 2,934 0 240 3,174 29,751 11 Nkasi 150 0 0 150 10,697 1 Sumbawanga Urban 337 234 0 571 5,695 10 Total 3,688 234 240 4,163 57,776 7 % 89 6 6 100 Governmen t NGO / Development Project Other Mpanda 404 0 0 404 11,633 3 Sumbawanga Rural 2,143 0 0 2,143 29,751 7 Nkasi 78 82 0 160 10,697 1 Sumbawanga Urban 205 101 0 306 5,695 5 Total 2,830 183 0 3,013 57,776 5 % 94 6 0 100 Source of Advice on Group Formation Total District Source of Advice on Calf Rearing Total Number of households raising livestock Source of Advice on Pasture Establishment Total 29.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total District 29.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total Number of households raising livestock % receiving advice out of total District Total 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 247 Government NGO / Development Project Co- operative Total Mpanda 269 0 0 269 11,633 2 Sumbawanga Rural 1,782 0 121 1,902 29,751 6 Nkasi 162 0 0 162 10,697 2 Sumbawanga Urban 169 101 0 270 5,695 5 Total 2,382 101 121 2,604 57,776 5 % 91 4 5 100 Number % Number % Number % Number % Number % Number Mpanda 130 3 1,734 44 1,309 33 742 19 0 0 3,916 Sumbawanga Rural 362 4 6,295 66 2,284 24 0 0 600 6 9,542 Nkasi 78 4 1,618 81 302 15 0 0 0 0 1,999 Sumbawanga Urban 69 3 2,097 85 305 12 0 0 0 0 2,472 Total 641 4 11,745 66 4,200 23 742 4 600 3 17,928 Total District Very Good Good Average Poor No Good Quality of Service 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice on the Use of Improved Bulls 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Rukwa 248 Appendix II 249 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 250 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Mpanda 28 3 4 1 74 7 284 23 27 70 303 Sumbawanga Rural 21 2 6 1 90 10 92 8 19 81 129 Nkasi 37 2 7 2 49 7 109 23 25 43 146 Sumbawanga Urban 8 1 1 1 15 6 15 11 12 14 37 Total 25 2 5 1 72 8 156 16 22 66 185 Regional Capital 75 All Weather Roads 5 Tarmac Roads 185 Hospitals 72 Tertiary Markets 66 Secondary Market 22 Secondary Schools 25 Primary Markets 16 Health Clinics 8 Primary Schools 2 Feeder Roads 1 Table 33.01a: Mean distances from horders dwellings to Infrastructures and services by District District Mean Distance to Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 251 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % % Mpanda 934 2 1,601 3 11,759 20 15,719 26 29,520 50 59,533 28 Sumbawanga Rural 4,649 7 1,376 2 12,239 18 14,916 22 35,755 52 68,935 21 Nkasi 0 0 162 1 7,603 25 8,571 28 14,147 46 30,483 37 Sumbawanga Urban 138 1 1,889 14 6,894 52 4,077 31 311 2 13,309 8 Total 5,721 3 5,029 3 38,495 22 43,283 25 79,733 46 172,261 25 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households %f households % Mpanda 29,251 49 9,341 16 13,400 23 4,877 8 2,664 4 59,533 4 Sumbawanga Rural 34,480 50 9,650 14 9,880 14 6,289 9 8,636 13 68,935 6 Nkasi 13,091 43 2,678 9 6,953 23 4,475 15 3,287 11 30,483 7 Sumbawanga Urban 9,369 70 2,289 17 1,583 12 68 1 0 0 13,309 1 Total 86,191 50 23,957 14 31,816 18 15,709 9 14,587 8 172,261 5 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of h% Mpanda 38,481 65 11,972 20 8,281 14 800 1 0 0 59,533 1 Sumbawanga Rural 52,920 77 9,216 13 5,452 8 1,025 1 322 0 68,935 1 Nkasi 20,915 69 4,101 13 3,958 13 1,509 5 0 0 30,483 2 Sumbawanga Urban 10,323 78 2,400 18 550 4 0 0 35 0 13,309 1 Total 122,639 71 27,690 16 18,242 11 3,333 2 357 0 172,261 1 Total Number of Households 33.01c: Mean distance from holders dwellings to all Weather roads by District District Distance to All Weather Roads Total Number of Households Mean Distance 33.01b: Mean distance from holders dwellings to infrastrures and services by District District Distance to Feeder Road Total Number of Households Mean Distance Mean Distance Distance to Secondary School District 33.01d: Mean distance from holders dwellings to Feeder Roads by District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 252 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % f households % Mpanda 134 0.2 134 0.2 1,302 2 9,918 17 48,045 81 59,533 74 Sumbawanga Rural 119 0.2 120 0.2 566 1 669 1 67,462 98 68,935 90 Nkasi 71 0.2 513 1.7 4,196 14 4,765 16 20,939 69 30,483 49 Sumbawanga Urban 68 0.5 0 0.0 4,669 35 5,993 45 2,579 19 13,309 15 Total 392 0.2 767 0.4 10,732 6 21,344 12 139,025 81 172,261 72 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % f households % Mpanda 7,488 13 7,807 13 27,274 46 13,941 23 3,023 5 59,533 7 Sumbawanga Rural 19,914 29 10,046 15 19,684 29 10,335 15 8,957 13 68,935 10 Nkasi 3,950 13 2,872 9 16,362 54 5,859 19 1,440 5 30,483 7 Sumbawanga Urban 3,342 25 2,512 19 6,166 46 1,254 9 35 0 13,309 6 Total 34,694 20 23,236 13 69,486 40 31,390 18 13,455 8 172,261 8 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % No of households % No of households % Mpanda 16,818 28 20,799 35 19,800 33 1,060 2 1,056 2 59,533 Sumbawanga Rural 34,714 50 21,967 32 10,886 16 1,246 2 122 0 68,935 Nkasi 19,494 64 5,768 19 4,927 16 82 0 212 1 30,483 Sumbawanga Urban 7,602 57 4,372 33 1,266 10 68 1 0 0 13,309 Total 78,629 46 52,906 31 36,880 21 2,456 1 1,389 1 172,261 District Less than 1 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Mean Distance Mpanda 0 0 135 59,398 59,533 283.7 Sumbawanga Rural 0 111 0 68,824 68,935 92.4 Nkasi 162 155 0 30,167 30,483 109.2 Sumbawanga Urban 35 4,532 6,128 2,614 13,309 15.4 Total 196 4,798 6,263 161,003 172,261 155.5 33.1h: Number of Households to Regional Capital 33.01g: Mean distance from holders dwellings to Primary School by District District Total Number of Households Distance to Primary School 33.01f: Mean distance from holders dwellings to Health Clinic by District District Distance to Health Clinic Total Number of Households Mean Distance 33.01e: Mean distance from holders dwellings to Hospital by District District Distance to Hospital Total Number of Households Mean Distance Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 253 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 135 132 0 135 59,131 59,533 303 Sumbawanga Rural 716 0 119 120 67,980 68,935 129 Nkasi 78 0 0 81 30,323 30,483 146 Sumbawanga Urban 225 0 4,205 5,504 3,375 13,309 37 Total 1,155 132 4,324 5,840 160,809 172,261 185 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 4,917 12,259 9,400 14,247 18,711 59,533 23 Sumbawanga Rural 20,032 9,266 16,216 10,622 12,800 68,935 8 Nkasi 8,131 664 7,436 5,989 8,262 30,483 23 Sumbawanga Urban 3,764 2,184 3,140 2,655 1,566 13,309 11 Total 36,844 24,373 36,192 33,513 41,338 172,261 16 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 267 398 4,384 9,254 45,230 59,533 70 Sumbawanga Rural 1,736 1,838 1,068 2,235 62,058 68,935 81 Nkasi 1,030 954 4,988 4,565 18,946 30,483 43 Sumbawanga Urban 67 0 4,671 5,992 2,579 13,309 14 Total 3,100 3,191 15,111 22,047 128,813 172,261 66 District Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 3,637 2,932 12,910 15,920 24,135 59,533 27 Sumbawanga Rural 7,399 4,489 11,568 15,679 29,801 68,935 19 Nkasi 1,849 1,442 11,843 6,901 8,448 30,483 25 Sumbawanga Urban 1,299 581 5,190 3,695 2,544 13,309 12 Total 14,184 9,443 41,510 42,195 64,928 172,261 22 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 254 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 1,200 0.3 1,458 0.4 1,304 0.4 1,197 0.3 132 0.0 357,200 Sumbawanga Rural 0 0.0 1,148 0.3 2,639 0.6 2,754 0.7 6,552 1.6 413,611 Nkasi 158 0.1 2,800 1.5 2,815 1.5 2,973 1.6 1,032 0.6 182,900 Sumbawanga Urban 0 0.0 752 0.9 276 0.3 570 0.7 35 0.0 79,854 Total 1,358 0.1 6,158 0.6 7,035 0.7 7,494 0.7 7,751 0.7 1,033,565 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 399 22 791 43 257 14 401 22 0 0 1,848 Sumbawanga Rural 0 0 117 6 689 33 363 18 905 44 2,073 Nkasi 80 2 1,307 38 1,162 34 687 20 219 6 3,454 Sumbawanga Urban 0 0 35 52 0 0 32 48 0 0 67 Total 479 6 2,250 30 2,107 28 1,483 20 1,123 15 7,442 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 0 0 0 0 265 100 0 0 265 Sumbawanga Rural 0 0 112 6 0 0 363 21 1,244 72 1,718 Nkasi 78 5 157 9 862 51 442 26 147 9 1,686 Sumbawanga Urban 0 0 70 34 0 0 134 66 0 0 203 Total 78 2 338 9 862 22 1,204 31 1,391 36 3,873 District Research Station Total Number of Households 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Satisfaction of Using Veterinary Clinic District 33.19c TYPE OF SERVICE: Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year Total Number of Households 33.19b TYPE OF SERVICE: Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total Number of Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 255 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 0 0 135 100 0 0 0 0 135 Sumbawanga Rural 0 0 0 0 0 0 482 25 1,463 75 1,945 Nkasi 0 0 0 0 0 0 522 78 147 22 669 Sumbawanga Urban 0 0 0 0 0 0 32 100 0 0 32 Total 0 0 0 0 135 0 1,036 37 1,610 58 2,781 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 532 40 269 20 135 10 262 20 132 10 1,330 Sumbawanga Rural 0 0 0 0 808 33 601 25 1,018 42 2,426 Nkasi 0 0 0 0 0 0 369 71 147 29 516 Sumbawanga Urban 0 0 205 30 208 30 238 35 35 5 686 Total 532 11 474 10 1,150 23 1,470 30 1,332 27 4,958 33.19e TYPE OF SERVICE: Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total Number of Households 33.19d TYPE OF SERVICE: Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year District Plant Protection Lab. Total Number of Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 256 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 135 35 120 31 135 35 0 389 Sumbawanga Rural 0 0 688 23 1,143 38 583 20 565 19 2,979 Nkasi 0 0 0 0 78 12 442 66 147 22 667 Sumbawanga Urban 0 0 103 76 0 0 32 24 0 0 135 Total 0 0 925 22 1,341 32 1,191 29 713 17 4,170 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Veterinary Clinic 1,358 0 6,158 1 7,035 1 7,494 1 7,751 1 1,033,565 Extension Services 479 6 2,250 30 2,107 28 1,483 20 1,123 15 7,442 Research Station 78 2 338 9 862 22 1,204 31 1,391 36 3,873 Plant Protection Lab 0 0 0 0 135 5 1,036 37 1,610 58 2,781 Land Registration Office 532 11 474 10 1,150 23 1,470 30 1,332 27 4,958 Livestock Development Centre 0 925 22 1,341 32 1,191 29 713 17 4,170 33.19f TYPE OF SERVICE: Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year District Livestock Development Centre Total Number of Households Total Number of Households LEVEL OF SATISFACTION OF THE SERVICE TYPE OF SERVICE 33.19G TYPE OF SERVICE: Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 257 HOUSEHOLDS FACILITIES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 258 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Number of Househol ds Mpanda 1,477 1,749 55,910 397 0 59,533 Sumbawanga Rural 4,861 2,426 61,307 341 0 68,935 Nkasi 480 150 29,316 538 0 30,483 Sumbawanga Urban 371 69 12,734 101 34 13,309 Total 7,189 4,395 159,267 1,376 34 172,261 % 4 3 92 1 0 100 Average Number of rooms per Household Iron sheet Tiles Concreat e Asbestos Grass/Le aves Grass & Mud Other Total Number of Households Mpanda 3 9,757 270 135 536 47,907 929 0 59,533 Sumbawanga Rur 2 12,882 445 0 1,371 49,355 4,883 0 68,935 Nkasi 2 5,006 213 82 278 24,538 367 0 30,483 Sumbawanga Urb 2 4,437 35 0 0 8,078 759 0 13,309 Total 2 32,082 962 216 2,186 129,877 6,937 0 172,261 % 19 1 0 1 75 4 0 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 29,457 41 23,873 33 14,229 20 4,484 6 72,043 42 Landline phones 267 100 0 0 0 0 0 0 267 0 Mobile Phones 134 17 359 46 290 37 0 0 784 0 Iron 9,486 40 7,846 33 4,613 20 1,698 7 23,642 14 Wheelbarrow 1,570 30 2,793 54 397 8 439 8 5,199 3 Bicycles 34,455 53 17,544 27 7,564 12 5,014 8 64,577 37 Vehicles 529 49 459 43 82 8 0 0 1,070 1 Television/Video 535 63 107 13 207 24 0 0 849 0 Total Number of Households 76,433 44 52,980 31 27,383 16 11,635 7 172,261 100 34-1: Number of Agricultural Households by Type of TOILET by Districtduring the 2002/03 Agricultural Year Type of Toilet District 34-2: Number of Agricultural Households Reported Average Number of Rooms and Type of Roofing Materials by District for the 2002/03 Agricultural Year District Type of Owned Asset Total Type of Roofing materials District Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.3: Number of Agricultural Households by Type of Owned Assets and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 259 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 133 30 235 53 72 16 0 0 440 0 Hurricane Lamp 11,300 39 9,321 32 7,648 26 803 3 29,072 17 Pressure Lamp 2,239 38 2,410 41 1,064 18 209 4 5,922 3 Wick Lamp 45,056 34 53,197 40 21,462 16 12,228 9 131,944 77 Candles 0 0 115 61 72 39 0 0 187 0 Firewood 806 18 3,538 78 164 4 34 1 4,542 3 Other 0 0 120 78 0 0 34 22 154 0 Total Number of Households 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Charcoal 1,877 36 1,526 29 1,620 31 162 3 5,185 3 Firewood 57,657 35 67,095 40 28,793 17 13,112 8 166,657 97 Crop Residues 0 0 314 82 70 18 0 0 385 0 Livestock dung 0 0 0 0 0 0 35 100 35 0 Total Number of Households 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Sumbawanga Urban Mpanda Sumbawanga Rural Nkasi Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.4 Number of Agricultural Households by Main Source of Energe Used for Lighting and District, 2002/03 Agricultural Year District Main Source of Energe for Lighting Total 34.5: Number of Agricultural Households by Main Source of Energe Used for Cooking and District, 2002/03 Agricultural Year Main Source of Energe for Lighting District Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 260 Source Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Piped Water Wet 11,669 11,568 2,105 4,523 Dry 11,012 9,437 2,176 3,977 Protected Well Wet 14,432 12,777 14,981 1,468 Dry 15,098 12,462 14,115 1,367 Protected / Covered Spring Wet 940 2,066 141 970 Dry 805 2,421 141 935 Uprotected Well Wet 13,336 18,799 4,796 3,534 Dry 14,894 21,297 4,797 3,669 Unprotected Spring Wet 6,247 5,363 3,995 1,779 Dry 5,985 5,837 3,637 1,877 Surface Water (Lake / Dam / River / Stream Wet 12,392 17,780 4,068 551 Dry 11,215 17,021 5,373 1,067 Covered Rainwater Catchment Wet 0 0 152 0 Dry 0 0 80 0 Uncovered Rainwater Catchment Wet 383 583 165 452 Dry 389 460 82 417 Tanker Truck Wet 134 0 0 0 Dry 134 0 0 0 Other Wet 0 0 81 32 Dry 0 0 81 0 Total Agricultural Households per District 59,533 68,935 30,483 13,309 Source Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Piped Water Wet 20 17 7 34 Dry 18 14 7 30 Protected Well Wet 24 19 49 11 Dry 25 18 46 10 Protected / Covered Spring Wet 2 3 0 7 Dry 1 4 0 7 Uprotected Well Wet 22 27 16 27 Dry 25 31 16 28 Unprotected Spring Wet 10 8 13 13 Dry 10 8 12 14 Surface Water (Lake / Dam / River / Stream Wet 21 26 13 4 Dry 19 25 18 8 Covered Rainwater Catchment Wet 0 0 0 0 Dry 0 0 0 0 Wet 1 1 1 3 Dry 1 1 0 3 Wet 0 0 0 0 Dry 0 0 0 0 Wet 0 0 0 0 Dry 0 0 0 0 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year Season District Other Tanker Truck Uncovered Rainwater Catchment District Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 261 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Less than 100m Wet 2,257 6,975 960 232 Dry 1,860 6,855 984 100 100 - 299 m Wet 13,639 13,807 9,151 2,842 Dry 12,599 12,188 8,889 2,809 300 - 499 m Wet 6,570 6,549 5,759 2,044 Dry 6,307 5,480 5,462 1,979 500 - 999 m Wet 16,234 14,640 9,572 4,718 Dry 16,231 15,700 9,364 4,682 1 - 1.99 Km Wet 12,611 18,849 3,994 2,383 Dry 11,672 15,726 4,269 2,276 2 - 2.99 Km Wet 4,103 5,700 966 918 Dry 5,414 8,134 1,471 1,259 3 - 4.99 Km Wet 3,449 2,072 0 102 Dry 4,244 3,582 0 134 5 - 9.99 Km Wet 671 343 82 69 Dry 1,206 1,270 46 69 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Less than 100m Wet 4 10 3 2 Dry 3 10 3 1 100 - 299 m Wet 23 20 30 21 Dry 21 18 29 21 300 - 499 m Wet 11 9 19 15 Dry 11 8 18 15 500 - 999 m Wet 27 21 31 35 Dry 27 23 31 35 1 - 1.99 Km Wet 21 27 13 18 Dry 20 23 14 17 2 - 2.99 Km Wet 7 8 3 7 Dry 9 12 5 9 3 - 4.99 Km Wet 6 3 0 1 Dry 7 5 0 1 5 - 9.99 Km Wet 1 0 0 1 Dry 2 2 0 1 Distance to main Source of Drinking Water Season District 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year District Distance to main Source of Drinking Water Season 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 262 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Wet 808 1,687 151 132 Dry 672 1,330 151 136 Wet 12,900 12,596 12,451 3,315 Dry 11,843 12,142 12,136 3,349 Wet 6,191 9,872 5,629 2,420 Dry 5,925 8,218 5,617 2,420 Wet 15,369 21,137 5,495 3,730 Dry 15,105 20,338 5,601 3,285 Wet 4,598 5,824 1,212 1,157 Dry 4,456 6,273 1,080 1,159 Wet 5,052 3,156 3,267 883 Dry 4,521 3,281 3,229 852 Wet 14,615 14,663 2,279 1,672 Dry 17,011 17,354 2,670 2,109 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Wet 1 2 0 1 Dry 1 2 0 1 Wet 22 18 41 25 Dry 20 18 40 25 Wet 10 14 18 18 Dry 10 12 18 18 Wet 26 31 18 28 Dry 25 30 18 25 Wet 8 8 4 9 Dry 7 9 4 9 Wet 8 5 11 7 Dry 8 5 11 6 Wet 25 21 7 13 Dry 29 25 9 16 Distance to main Source of Drinking Water Season District 34.10: Number of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Distance to main Source of Drinking Water Season District 34.11: Proportion of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 263 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % One 2,412 21 5,766 50 950 8 2,495 19 11,622 7 Two 45,753 32 59,117 42 25,767 18 10,346 78 140,983 82 Three 11,368 58 4,052 21 3,684 19 468 4 19,573 11 Four 0 0 0 0 82 100 0 0 82 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 24,155 31 36,652 46 12,615 16 5,733 7 79,156 46 One 19,522 39 18,118 37 7,828 16 4,117 8 49,584 29 Two 10,142 37 9,995 37 4,699 17 2,362 9 27,198 16 Three 3,326 31 2,993 28 3,630 34 722 7 10,671 6 Four 1,852 48 707 18 1,014 26 275 7 3,848 2 Five 269 32 122 15 407 49 35 4 833 0 Six 135 65 0 0 72 35 0 0 207 0 Seven 133 17 348 46 217 28 65 9 763 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Days District Total Number of Meals per Day Total Nkasi Sumbawanga 34.12: Number of Households by Number of Meals the Household Normally Took per Day by District District Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.13: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Mpanda Sumbawanga Rural Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 264 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 22,709 46 18,803 38 5,145 10 2,768 6 49,425 29 One 13,023 35 13,719 37 6,996 19 3,645 10 37,383 22 Two 11,770 38 10,652 34 4,573 15 3,976 13 30,971 18 Three 5,460 31 7,596 43 2,936 17 1,801 10 17,793 10 Four 2,535 25 4,907 48 1,998 20 687 7 10,127 6 Five 669 11 3,053 49 2,215 35 332 5 6,268 4 Six 255 7 2,235 59 1,275 34 0 0 3,766 2 Seven 3,113 19 7,970 48 5,345 32 100 1 16,528 10 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Never 27,693 33 35,734 43 13,537 16 5,770 7 82,734 48 Seldom 20,904 37 21,058 38 9,689 17 4,198 8 55,848 32 Sometimes 3,196 27 5,964 50 1,777 15 1,020 9 11,957 7 Often 5,207 39 4,221 32 2,376 18 1,408 11 13,212 8 Always 2,533 30 1,958 23 3,105 36 914 11 8,509 5 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Number of Days District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34-15: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceeding Year by District Status of Food Satisfaction District Total Mpanda Sumbawanga Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Sales of Food Crops 30,051 36 36,355 43 12,760 15 5,141 6 84,309 49 Sale of Livestock 370 20 902 48 325 17 267 14 1,864 1 Sale of Livestock Products 134 32 0 0 82 20 204 48 420 0 Sales of Cash Crops 6,437 90 237 3 76 1 439 6 7,189 4 Sale of Forest Products 6,462 23 12,781 46 5,615 20 2,761 10 27,620 16 Business Income 6,462 23 12,781 46 5,615 20 2,761 10 27,620 16 Wages & Salaries in Cash 1,204 31 1,435 37 889 23 403 10 3,931 2 Other Casual Cash Earnings 9,401 38 7,637 31 4,707 19 2,743 11 24,488 14 Cash Remittance 1,028 24 1,938 45 856 20 509 12 4,331 3 Fishing 329 4 4,708 50 4,298 46 35 0 9,370 5 Other 383 48 0 0 79 10 335 42 796 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34-16: Number of Households by Main Source of Income and District, 2002/03 Agricultural Year Main Source of Cash Income District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 266 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Iron Sheets 9,757 30 12,882 40 5,006 16 4,437 14 32,082 19 Tiles 270 28 445 46 213 22 35 4 962 1 Concreate 135 62 0 0 82 38 0 0 216 0 Asbestos 536 25 1,371 63 278 13 0 0 2,186 1 Grass/leaves 47,907 37 49,355 38 24,538 19 8,078 6 129,877 75 Grass & Mud 929 13 4,883 70 367 5 759 11 6,937 4 Other 0 0 0 0 0 0 0 0 0 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year Roofing Materials District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa 267 APPENDIX III QUESTIONNAIRES Appendix III 268 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 269 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 270 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 271 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 272 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 273 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 274 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 275 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 276 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 277 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 278 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 279 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 280 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 281 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 282 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 283 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 284 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 285 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 286 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 287 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 288 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 289 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 290 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source \"a\" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 291 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 292 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 293 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 294 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 295 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 296 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 297 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 298 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 299 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 300 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 301 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 302 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 303 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 304 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 305 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 306 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 307 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 308 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 309 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 310 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 311 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 312 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 313 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":169,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vj: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vk: REGIONAL REPORT: RUVUMA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms......................................................................................................................................................................... v Preface ..........................................................................................................................................................................vi Executive summary........................................................................................................................................................ vii Illustrations..................................................................................................................................................................... xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 1 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Household Characteristics ........................................................................................................................... 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Litaracy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 23 3.3.4.3 Other Cereals.................................................................................................................. 26 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava........................................................................................................................... 27 3.3.5.2 Sweet Potatoes................................................................................................................ 28 3.3.6 Pulse Crops Production .................................................................................................................... 28 3.3.6.1 Beans............................................................................................................................... 30 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts ..................................................................................................................... 32 3.3.8 Fruits and Vegetables ........................................................................................................................ 33 3.3.8.1 Tomatoes ........................................................................................................................ 35 3.3.8.2 Cabbage .......................................................................................................................... 37 3.3.8.3 Onions............................................................................................................................. 37 3.3.9 Other Annual Crops Production....................................................................................................... 40 3.3.9.1 Tobacco .......................................................................................................................... 40 3.4 Permanent Crops........................................................................................................................................... 40 3.4.1 Cashewnuts....................................................................................................................................... 43 3.4.2 Coffee ........................................................................................................................................ 45 3.4.3 Banana ........................................................................................................................................ 45 3.4.4 Pigeon peas ....................................................................................................................................... 45 3.5 Inputs/Implements Use................................................................................................................................. 48 3.5.1 Methods of land clearing................................................................................................................... 48 3.5.2 Methods of soil preparation.............................................................................................................. 48 3.5.3 Improved seeds use........................................................................................................................... 50 3.5.4 Fertilizers use.................................................................................................................................... 51 3.5.4.1 Farm Yard Manure Use.................................................................................................. 51 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 52 3.5.4.3 Compost Use .................................................................................................................. 53 3.5.5 Pesticide Use..................................................................................................................................... 54 3.5.5.1 Insecticide Use................................................................................................................ 54 3.5.5.2 Herbicide Use................................................................................................................. 55 3.5.5.3 Fungicide Use................................................................................................................. 55 3.5.6 Harvesting Methods.......................................................................................................................... 56 3.5.7 Threshing Methods .......................................................................................................................... 56 3.6 Irrigation .................................................................................................................................................... 56 3.6.1 Area planted with annual crops and under irrigation....................................................................... 56 3.6.2 Sources of water used for irrigation................................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................................ 59 3.6.4 Methods of water application .......................................................................................................... 59 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing .................................................................................................. 59 3.7.1 Crop Storage ..................................................................................................................................... 59 3.7.1.1 Method of Storage.......................................................................................................... 60 3.7.1.2 Duration of Storage ........................................................................................................ 60 3.7.1.3 Purpose of Storage.......................................................................................................... 61 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 61 3.7.2 Agro processing and by-products...................................................................................................... 62 3.7.2.1 Processing Methods........................................................................................................ 62 3.7.2.2 Main Agro-processing Products..................................................................................... 62 3.7.2.3 Main use of primary processed Products....................................................................... 63 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 63 3.7.3 Crop Marketing................................................................................................................................. 64 3.7.3.1 Main Marketing Problems.............................................................................................. 64 3.7.3.2 Reasons for Not Selling.................................................................................................. 64 3.8 Access to Crop Production Services............................................................................................................ 65 3.8.1 Access to Agricultural Credits ......................................................................................................... 65 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits............................................................................................ 65 3.8.1.3 Reasons for not using agricultural credits...................................................................... 66 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of crop extension messages.............................................................................. 66 3.8.2.2 Quality of extension ....................................................................................................... 68 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.2 Inorganic Fertilisers .......................................................................................................................... 68 3.9.3 Improved Seeds ................................................................................................................................. 69 3.9.4 Insecticides and Fungicide ................................................................................................................ 69 3.10 Tree Planting................................................................................................................................................... 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population............................................................................................................ 73 3.12.1.2 Herd size......................................................................................................................... 73 3.12.1.3 Cattle Population Trend ................................................................................................. 75 3.12.1.4 Improved Cattle Breeds.................................................................................................. 75 3.12.2 Goat Production................................................................................................................................ 75 3.12.2.1 Goat Population.............................................................................................................. 75 3.12.2.2 Goat Herd Size ............................................................................................................... 77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 79 3.12.4 Pig Production .................................................................................................................................. 79 3.12.4.1 Pig Population Trend...................................................................................................... 79 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census iv 3.12.5 Chicken Production .......................................................................................................................... 81 3.12.5.1 Chicken Population ........................................................................................................ 81 3.12.5.2 Chicken Population Trend.............................................................................................. 81 3.12.5.3 Chicken Flock Size......................................................................................................... 81 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 82 3.12.6 Other Livestock ................................................................................................................................ 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming..................................................................................................................... 82 3.12.8 Access to Livestock Services ........................................................................................................... 84 3.12.8.1 Access to livestock extension Services.......................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to village watering points/dam .......................................................................... 85 3.12.9 Animal Contribution to Crop Production......................................................................................... 85 3.12.9.1 Use of Draft Power......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 86 3.12.9.4 Use of Compost ............................................................................................................. 86 3.12.10 Fish Farming..................................................................................................................................... 86 3.13 Poverty Indicators......................................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services.................................................................................... 89 3.13.2 Type of Toilets.................................................................................................................................. 90 3.13.3 Household’s assets............................................................................................................................ 90 3.13.4 Sources of Light Energy................................................................................................................... 90 3.13.5 Sources of Energy for Cooking........................................................................................................ 90 3.13.6 Roofing Materials............................................................................................................................. 91 3.13.7 Access to Drinking Water ................................................................................................................ 91 3.13.8 Food Consumption Pattern............................................................................................................... 92 3.13.8.1 Number of Meals per Day.............................................................................................. 92 3.13.8.2 Meat Consumption Frequencies..................................................................................... 92 3.13.8.3 Fish Consumption Frequencies...................................................................................... 92 3.13.9 Food Security.................................................................................................................................... 92 3.13.10 Main Source of Cash Income........................................................................................................... 93 PART IV: RUVUMA PROFILES ............................................................................................................................. 95 4.1 Region Profile ................................................................................................................................................. 95 4.2 District Profiles................................................................................................................................................... 4.2.1 Tunduru.............................................................................................................................................. 96 4.2.2. Songea Rural...................................................................................................................................... 98 4.2.3 Mbinga.............................................................................................................................................100 4.2.4 Songea Urban...................................................................................................................................102 4.2.5 Namtumbo .......................................................................................................................................104 ACRONYMS _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Ruvuma region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in th e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina Chuwa The Director General National Bureau of Statistics ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Ruvuma region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Ruvuma region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Ruvuma region was 191,175 out of which 141,619 (74.1%) were involved in growing crops only, 132 (0.1%) rearing livestock only, and 49,424 (25.9%) were involved in crop production as well as livestock keeping. In summary, Ruvuma region had 191,043 households involved in crop production and 49,556 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, off-farm income, livestock keeping/herding, remittances, fish/hunting/gathering and tree/forest resources. The region has a literacy rate of 75 percent. The highest literacy rate was found in Songea Urban district (83%) followed by Mbinga district (80%) and Songea Rural district (78%). Tunduru and Namtumbo districts had the lowest literacy rates of 64 and 75 percent respectively. The literacy rate for the heads of households in the region was 83 percent. The number of heads of agricultural households with formal education in Ruvuma region was 157,638 (82%), those without education were 30,529 (16%) and those with only adult education were 3,007 (2%). The majority of heads of agricultural households (77%) had primary level education whereas only 5 percent had post primary education. In Ruvuma region 74,141 households (39%) had only one member aged 5 and above involved in only one off-farm income generating activity, 40,234 households (21%) had two members involved in off-farm income generating activities and 11,565 households (6%) had more than two members involved in off-farm income generating activities ii) Crop Production Land Area The total area of land available to smallholders was 799,230 ha. The Regional average land area utilised for agriculture per household was only 3.0 ha. This figure is above the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 358,203 hectares out of which 110 hectares (0.03%) were planted during dry season and 358,093 hectares (99.97%) during wet season. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census viii An estimated area of 194,211 ha (54.2% of the total planted area with annuals) was with cereals, followed by roots and tubers (94,522 hectares, 26.4%), pulses (39,697 hectares, 11.1%), oil seeds (17,464 hectares, 4.9%), cash crops (7,169 hectares, 2.0%) and fruit and vegetables (5,140 hectares, 1.4%). Maize Maize was the dominant cereal crop grown in Ruvuma region. The area planted with maize represented 71.9 percent of the total area planted with cereal crops. The total production of maize was 179,283 tonnes from a planted area of 139,505 hectares resulting in a yield of 1.3 t/ha. There was a sharp increase in maize production (48%) in 1999 after which the production leveled in 2000 and then it declined during the year 2003. The average area planted with maize per household was 0.8 hectares, however it ranged from 0.6 hectares in Tunduru district to 1.0 hectares in Namtumbo district. In the wet season, Mbinga district had the largest area of maize (50,346 ha) followed by Namtumbo (28,809 ha), Songera Rural (28,503 ha), Tunduru (27,246 ha), and Songea Urban (4,600 ha). Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Ruvuma region was 81,184. This represented 42 percent of the total crop growing households in Ruvuma region. The total production of paddy was 39,510 tonnes from a planted area of 38,178 hectares resulting in a yield of 1.03 t/ha. Cassava The area planted with cassava was larger than any other root and tuber crop in Ruvuma region. It accounted for 87.0 percent of the total roots and tubers production. The total production of cassava during the census year was 101,965 tonnes from a planted area of 87,522 hectares resulting in a yield of 1.2t/ha Fruit and Vegetables The total production of fruits and vegetables was 16,087 tonnes. The most cultivated fruit and vegetable crop was the tomato crop with a production of 7,328 tonnes (46% of the total fruit and vegetables produced) followed by cabbage (4,119t, 26%) and onions (1,704t, 11%). The production of other fruit and vegetable crops were relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 124,910 hectares which is 35 percent of the area planted with annual crops in the region. The most important permanent crop in Ruvuma region is cashewnut which had a planted area of 74,124 ha, (61% of the planted area of all permanent crops) followed by coffee (29,961 ha, 24%), and banana (7,751 ha, 6%). Improved Seeds The planted area using improved seeds was estimated at 35,208 ha which represents 8 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the dry season was 13.6 percent, slightly higher than the corresponding percentage use in the wet season (9.8%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census ix Use of Fertilizers The planted area without fertiliser for annual crops was 281,740 hectares representing 78.7 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertilizers were applied to 43,402 ha which represents 12.1 percent of the total planted area (56.8% of the area planted with fertiliser application in the region). This was followed by farm yard manure (29,470 ha, 38.5%). Compost fertilizers were used on a very small area which represented only 47 percent of the area planted with fertilizers. Irrigation In Ruvuma region, the area of annual crops under irrigation was 9,104 ha representing 3 percent of the total area planted. The area under irrigation during the wet season was 15 ha accounting for 0.16 percent of the total area under irrigation. The district with the largest planted area under irrigation with annual crops was Mbinga (2,731 ha, 30% of the total irrigated planted area with annual crops in the region). This was followed by Namtumbo with (2,122 ha, 23%) and then Tunduru (2,025 ha, 22%). When expressed as a percentage of the total area planted in each district, Songea Urban had the highest with 10.8% of the planted area in the district under irrigation. This is followed by Namtumbo (3.0%), Tunduru (2.4%), Mbinga (2.1%) and Songea Rural (1.7%) Crop Storage There were 181,775 crop growing households (95.1% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 172,771 households storing 34,081 tonnes as of 1st January 2004. This was followed by paddy (72,495 households, 3,273t), beans and other pulses (86,592 households, 2,599), sorghum and millet (27,879 households, 910t), groundnuts and bambara nuts (21,827 households, 469t) and seeweed (8,550 households, 461t). Other crops were stored in very small quantities. Crop Marketing The number of households that reported selling crops was 176,924 which represent 92.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Tunduru (96%) followed by Namtumbo (94%), Mbinga (91%), Songea Rural (91%) and Songea Urban (82%) Agricultural Credit The census result shows that in Ruvuma region a considerable number of agricultural households (38,567, 18.6%) accessed credit out of which 32,939 (85%) were male-headed households and 5,628 (15%) were female headed households. In all districts both male and female headed households accessed agricultural credit. Crop Extension Services The number of Agricultural households that received crop extension was 67,199 (35% of total crop growing households in the region). Some districts had more access to extension services than others, with Namtumbo having a relatively high proportion of households (55%) that received crop extension messages followed by Songea Urban (40%), Mbinga (35%), Tunduru(30%) and Songea Rural (23%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census x Soil Erosion and Water Harvesting Facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 12,403 which represent 6 percent of the total number of agricultural households in the region. The proportion of households with soil erosion control and water harvesting facilities was highest in Mbinga district (12%) followed by Songea Urban (11%), Songea Rural (3%), Namtumbo (1%) and Tunduru (1%) iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 121,175. Cattle were the dominant livestock type in the region followed by goats, pigs and sheep. The region had 0.7 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Ruvuma region was 105,884 (87.4 % of the total number of cattle in the region), 15,111 cattle (12.5%) were dairy breeds and 181 cattle (0.1%) were beef breeds. Goats The number of goat-rearing-households in Ruvuma region was 68,381 (36% of all agricultural households in the region) with a total of 309,595 goats giving an average of 5 head of goats per goat-rearing-household. Sheep The number of sheep-rearing households was 7,390 (4% of all agricultural households in Ruvuma region) rearing 24,458 sheep, giving an average of 3 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chicken was 139,284 raising about 1,555,617 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Ruvuma region was ranked eighth out of the 11 Mainland regions. Use of Draft Power The region had 55 oxen. Only Songea Urban had 55 oxen which were used to cultivate 33 hectares of land. This represented only 0.001 percent of the total oxen found on the Mainland Fish Farming The number of households involved in fish farming in Ruvuma region was 4,035, representing 2 percent of the total agricultural households in the region. Songea Rural was the leading district with 1,294 households (32.1% of agricultural households involved in fish farming. In the region).This was followed by Namtumbo (933 households, 23.1%), Mbinga (910 households, 22.5%), Songea Urban (610 households, 14.9%) and Tunduru (298 households, 7.4%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xi iv) Poverty Indicators Availability of Toilets It was estimated that 96 percent of all rural agricultural households used the traditional pit latrines, 1 percent used improved pit latrine and 2 percent had flush toilets. Households with no toilet facilities represented 1 percent of the total agriculture households in the region. Household Assets Radios were owned by most rural agricultural households in Ruvuma region with 109,159 households (57.1% of the agriculture households in the region) owning the asset, followed bicycles (69,706 households, 36.5%), irons (49,616 households, 26.0%), wheelbarrows (7,944 households, 4.2%), mobile phones (2,460 households, 1.3%), vehicles (2,284 households, 1.2%), TVs/Videos (1,549 households, 0.8%) and landline phones (1,496 households, 0.8%) Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 50.7 percent of the total rural households using this source of energy followed by hurricane lamp (44.2%), pressure lamp (3.0%), firewood (1.0%), gas or biogas (0.3%) mains electricity (0.3%), candle (0.3%) and solar (0.2%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.1 percent of all rural agricultural households in Ruvuma region. This was followed by charcoal (1.9%). The rest of energy sources accounted for 1.0 percent. Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 69.2 percent of the rural agricultural households. This was followed by iron sheets (33.4%), grass/mud (4.0%), tiles (0.6%), concrete (0.2%) and asbestos (0.0%). Number of Meals per Day About 64.5 percent of the holders in the region took three meals per day, 33.4 percent took two meals and 1.9 percent took one meal. Only 0.2 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 25.2 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 6.6 percent whereas those with little problems represent 2.5 percent. About 3.2 percent of agriculture households always faced food shortages whilst 62.5 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 49.5 percent of all rural agricultural households. The second main cash income earning activity was selling of cash crops (26%) followed by other casual cash earnings (8%), business income (4%), wages and salaries (4%), fishing (3%), and remittance (3%). Only 1% of smallholder households reported the sale of livestock as their main source of cash income. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .............................................................................................................................................. 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 23 3.3 Area, Production and Yield of Root and Tuber Crops by Season................................................................................ 29 3.4 Area, Quantity Harvested and Yield of Pulses by Season ................................................................................. 34 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 34 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 38 3.8 Land Clearing Methods....................................................................................................................................... 44 3.9 Planted Area by Type of Fertilizer Use and District – Wet and Dry Rainy Season.......................................... 46 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during Wet Season ...............................................................................................................................................46 3.11 Number of Households Storing Crops by Estimated Storage Loss and Crop ................................................... 11 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 61 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 62 3.14 Access to Inputs................................................................................................................................................... 64 3.15 Total Number of Households and Chickens Raised by Flock Size ....................................................................75 3.16 Head Number of Other Livestock by Type of Livestock and District............................................................... 78 3.17 Mean distances from holders dwellings to infrastructure and services by districts ...........................................86 3.18 Number of Households by Number of meals the Household normally takes per Day and District ................. 90 List of Charts 3.1 Agricultural Households by Type of Holdings................................................................................................... 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 15 3.3 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District.............................................................................. 16 3.6 Percentage of Persons Aged 5 Years and Above by Education Status.............................................................. 16 3.7 Percentage of Population Aged 5 years and Above by District and Educational Status........................................................................................................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Number of Households by Number of Members with Off-farm Income Generating Activities ...................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Members with Off-farm Income Generating Activities ............................................................................................................................. 17 3.11 Utilized and Usable Land per Household by District..........................................................................................18 3.12 Percentage Distribution of Land Area by Type of Land Use............................................................................. 18 3.13 Area Planted with Annual Crops (ha) by Season ............................................................................................... 20 3.14 Area Planted with Annual Crops by Season and District................................................................................... 20 3.15 Area Planted per household by Season and District........................................................................................... 20 3.16 Planted Area for the Main Annual Crops (ha).................................................................................................... 21 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type..................................................... 21 3.18 Area planted with Annual Crops by Type of Crops and Season........................................................................ 21 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 23 3.20 Time Series Data on Maize Production ............................................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 25 3.22 Time Series of Maize Planted Area and Yield – Ruvuma Region..................................................................... 25 3.23 Total Planted Area and Area of Paddy per Household by District .................................................................... 25 3.24 Time Series Data on Paddy Production – Ruvuma Region ............................................................................... 25 3.25 Time Series of Paddy Planted Area and Yield – Ruvuma Region..................................................................... 27 3.26 Area Planted With Sorghum, Bulrush Millet, Finger Millet and Wheat and Barley by District ...................... 27 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................... 27 3.28 Area planted with Cassava during the census/survey years................................................................................29 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................29 3.30 Cassava Planted Area per Cassava Growing Households by District ............................................................... 29 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xiii 3.31 Total Area Planted with Irish Potatoes and Planted Area per Household by District....................................... 30 3.32 Area Planted and Yield of Major Pulse Crops ................................................................................................... 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 32 3.34 Area Planted per Bean Growing Household by District (Wer Season Only).................................................... 32 3.35 Time Series Data on Bean Production – Ruvuma Region ................................................................................. 32 3.36 Time Series of Beans Planted Area and Yield - Ruvuma .................................................................................. 32 3.37 Area Planted and Yield of Major Oil Seed Crops.............................................................................................. 34 3.38 Time Series Data on Groundnut production – Ruvuma Region ........................................................................ 34 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District ........................ 34 3.40 Area Planted per Groundnut Growing Household by District (Wet Season Only)........................................... 34 3.41 Area Planted and Yield of Fruit and Vegetables................................................................................................ 35 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 36 3.43 Area Planted per Tomato Growing Household by District (Wet Season Only)................................................ 36 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District .................................. 36 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District ....................................... 38 3.46 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................38 3.47 Area Planted for Annual and Permanent Crops.................................................................................................. 38 3.48 Area Planted with the Main Permanent Crops ................................................................................................... 39 3.49 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 39 3.50 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District................... 39 3.51 Percent of Area Planted with Coffee and Average Planted Area per Household by District ........................... 41 3.52 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 41 3.53 Percent of Area Planted with Pigeon peas and Average Planted Area per Household by District................... 41 3.54 Number of Households by Method of Land Clearing during Wet Season........................................................ 44 3.55 Area Cultivated by Cultivation Method...............................................................................................................44 3.56 Area Cultivated by Method of Cultivation and District..................................................................................... 44 3.57 Planted Area with Improved Seed ...................................................................................................................... 44 3.58 Planted Area with Improved Seed by Crop Type............................................................................................... 46 3.59 Percentage of Crop Type Planted Area with Improved Seeds........................................................................... 46 3.60 Area of Fertilizer Application by Type of Fertilizer .......................................................................................... 47 3.61 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 47 3.62 Planted Area with Farm Yard Manure by Crop type ......................................................................................... 47 3.63a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 47 3.63b Proportion of Planted Area Applied with Farm Yard Manure by District ........................................................ 47 3.64 Planted Area with Inorganic Fertiliser by Crop type – Annuals........................................................................ 50 3.65a Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 50 3.65b Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 50 3.66a Planted Area with Compost by Crop Type......................................................................................................... 50 3.66b Percentage of Planted Area with Compost by Crop Type ................................................................................. 51 3.66c Proportion of Planted Area Applied with Compost by District......................................................................... 51 3.67 Planted area (ha) by Pesticide use....................................................................................................................... 51 3.68 Planted Area applied with Insecticides by Crop Type ....................................................................................... 51 3.69 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 51 3.70 Percent of Planted Area Applied with Insecticides by District - Ruvuma......................................................... 53 3.71 Planted Area applied with herbicides by Crop Type.......................................................................................... 53 3.72 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 53 3.73 Proportion of Planted Area applied with Herbicides by District ...................................................................... 53 3.74 Planted Area applied with Fungicides by Crop Type......................................................................................... 54 3.75 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 54 3.76 Proportion of Planted Area applied with Fungicides by District....................................................................... 54 3.77 Area of Irrigated Land......................................................................................................................................... 55 3.78 Planted Area and Percentage of Planted Area with Irrigation by District......................................................... 55 3.79 Time Series of Households with Irrigation – Ruvuma....................................................................................... 55 8.80 Number of Households with Irrigation by Source of Water.............................................................................. 56 3.81 Number of Households by Method of Obtaining Irrigation Water.................................................................... 56 3.82 Number of Households with Irrigation by Method of Field Application.......................................................... 56 3.83 Number of Households and Quantity Stored by Crop Type.............................................................................. 56 3.84 Number of households by Storage Methods....................................................................................................... 57 3.85 Number of households by method of storage and District (based on the most important household crop)..... 57 3.86 Normal Length of Storage for Selected Crops ................................................................................................... 57 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .................................................. 58 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xiv 3.88 Number of Households by Purpose of Storage and Crop Type......................................................................... 58 3.89a Percentage of Households Processing Crops...................................................................................................... 59 3.89b Percent of Households Processing Crops by District......................................................................................... 59 3.90 Percent of Crop Processing Households by Method of Processing....................................................................59 3.91 Percent of Households by Type of Main Processed Product ............................................................................. 59 3.92 Number of Households by Type of Bi-product.................................................................................................. 60 3.93 Use of Processed Product.................................................................................................................................... 60 3.94 Percentage of Households Selling Processed Crops by District........................................................................ 60 3.95 Location of Sale of Processed Products.............................................................................................................. 60 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District ......................................... 61 3.97 Number of Crop Growing Households Selling Crops by District ..................................................................... 61 3.98 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 61 3.99 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 62 3.100 Proportion of Households who Received Credit by Main Source of Credit and District ................................. 62 3.101 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 62 3.102 Reasons for Not using Credit.............................................................................................................................. 62 3.103 Number of Households Receiving Extension Advice........................................................................................ 63 3.104 Number of Households that Received Extension by District............................................................................. 63 3.105 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 64 3.106 Number of Households that Received Extension by Reported Quality of Services.......................................... 64 3.107 Number of Households by Source of Inorganic Fertilizers................................................................................ 64 3.108 Number of Households Reporting Distance to Source of Inorganic Fertilizers................................................ 66 3.109 Number of Households by Source of Improved Seed........................................................................................ 66 3.110 Number of Households reporting Distance to Source of Improved Seeds........................................................ 66 3.111 Number of Households by Source of Insecticides/Fungicides........................................................................... 67 3.112 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 67 3.113 Number of Households with Planted Trees........................................................................................................ 67 3.114 Number of Planted Trees by Species...................................................................................................................68 3.115 Number of Trees Planted by Smallholders by Species and District .................................................................. 68 3.116 Number of Trees Planted by Location................................................................................................................ 68 3.117 Number of Households by purpose of Planted Trees......................................................................................... 68 3.118 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 68 3.119 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District........... 69 3.120 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 69 3.121 Total Number of Cattle ('000') by District.......................................................................................................... 71 3.122 Numbers of Cattle by Type and District............................................................................................................. 71 3.123 Cattle Population Trend ...................................................................................................................................... 72 3.124 Dairy Cattle Population Trend............................................................................................................................ 72 3.125 Total Number of Goats ('000') by District.......................................................................................................... 72 3.126 Goat Population Trend........................................................................................................................................ 73 3.127 Total Number of Sheep by District..................................................................................................................... 73 3.128 Sheep Population Trend...................................................................................................................................... 74 3.129 Total Number of Pigs by District........................................................................................................................ 74 3.130 Pig Population Trend........................................................................................................................................... 74 3.131 Total Number of Chicken by District ................................................................................................................. 75 3.132 Chicken Population Trend .................................................................................................................................. 75 3.133 Number of Improved Chicken by Type and District...........................................................................................75 3.134 Layer Population Trend....................................................................................................................................... 78 3.135 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District...... 78 3.136 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............79 3.137 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........ 79 3.138 Number of Households by Distance to Veterinary Clinic.................................................................................. 79 3.139 Number of Households by Distance to Veterinary Clinic and District.............................................................. 79 3.140 Number of Households by Distance to Village Watering Point ........................................................................ 82 3.141 Number of Households by Distance to Watering Point and District................................................................. 82 3.142 Number of Households using Draft Animals ..................................................................................................... 82 3.143 Number of Households using Draft Animals by District................................................................................... 82 3.144 Number of Households using Organic Fertilizers.............................................................................................. 84 3.145 Area of Application of Organic Fertilizers by District....................................................................................... 84 3.146 Number of Households Practicing Fish Farming – Ruvuma ............................................................................. 84 3.147 Number of Households Practicing Fish Farming by District – Ruvuma........................................................... 85 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xv 3.148 Fish Production.................................................................................................................................................... 85 3.149 Agricultural Households by Type of Toilet Facility .......................................................................................... 86 3.150 Percentage Distribution of Households Owning the Assets............................................................................... 86 3.151 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................86 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 87 3.153 Percentage Distribution of Households by Type of Roofing Material .............................................................. 87 3.154 Percentage Distribution of Households With Grass/Leaves Roofs by District ................................................. 87 3.155 Percentage Distribution of Households Reporting Main Source of Drinking Water and Season..................... 87 3.156 Percentage Distribution of Households by Distance to Main Source Drinking Water and Season.................. 90 3.157 Number of Agriculture Households by Number of Meals per day.................................................................... 90 3.158 Number of Households by Frequency of Meat and Fish Consumption..............................................................91 3.159 Percent Distribution of the Number of Households by Main Source of Income............................................... 91 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................... 19 3.9 Area planted and Percentage During Wet Season by District............................................................................ 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District .................................. 22 3.11 Area Planted per Maize Growing Household..................................................................................................... 24 3.12 Planted Area and Yield of Maize by District ..................................................................................................... 24 3.13 Planted Area and Yield of Paddy by District ..................................................................................................... 26 3.14 Area Planted per Paddy Growing Household..................................................................................................... 26 3.15 Planted Area and Yield of Cassava by District .................................................................................................. 28 3.16 Area Planted per Cassava Growing Household.................................................................................................. 28 3.17 Planted Area and Yield of Beans by District...................................................................................................... 31 3.18 Area Planted per Beans Growing Household..................................................................................................... 31 3.19 Planted Area and Yield of Groundnuts by District ............................................................................................ 33 3.20 Area Planted per Groundnuts Growing Household............................................................................................ 33 3.24 Planted Area and Yield of Onions by District.................................................................................................... 39 3.25 Planted Area and Yield of Tobacco by District.................................................................................................. 40 3.26 Area Planted per Tobacco Growing Household................................................................................................. 40 3.27 Planted Area and Yield of Cashewnuts by District............................................................................................ 41 3.28 Area Planted per Cashewnut Growing Household............................................................................................. 41 3.31 Planted Area and Yield of Coffee by District..................................................................................................... 42 3.32 Area Planted per Coffee Growing Household.................................................................................................... 42 3.33 Planted Area and Yield of Banana by District ................................................................................................... 43 3.34 Area Planted per Banana Growing Household................................................................................................... 43 3.35 Planted Area and Yield of Pigeon Peas by District............................................................................................ 45 3.36 Area Planted per Pigeon Peas Growing Household ........................................................................................... 45 3.41 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 48 3.42 Number and Percent of Crop Growing Households using Improved Seed by District .....................................48 3.35 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 49 3.36 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 49 3.56 Planted Area and Percent of Planted Area with Farm Yard Manure application by District.............................52 3.57 Planted Area and Percent of Planted Area with Compost application by District ............................................ 52 3.37 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 65 3.38 Number of Households and Percent of Total Households Selling Crops by District........................................ 65 3.42 Number and Percent of Households with water Harvesting Bunds by District................................................. 70 3.43 Cattle population by District as of 1st Octobers 2003.........................................................................................76 3.44 Cattle Density by District as of 1st October 2003...............................................................................................76 3.45 Goat population by District as of 1st Octobers 2003 ......................................................................................... 77 3.46 Goat Density by District as of 1st October 2003................................................................................................ 77 3.47 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 80 3.48 Sheep Density by District as of 1st October 2003.............................................................................................. 80 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xvi 3.49 Pig population by District as of 1st Octobers 2003............................................................................................ 81 3.50 Pig Density by District as of 1st October 2003 .................................................................................................. 81 3.51 Number of Chickens by District as of 1st October 2003 ................................................................................... 83 3.52 Density of Chickens by District as of 1st October 2003.................................................................................... 83 3.59 Number and Percent of Households Practicing Fish Farming by District......................................................... 88 3.60 Number and Percent of Households Without Toilets by District ...................................................................... 88 3.61 Number and Percent of Households using Grass/Leaves for roofing material by District ............................... 92 3.62 Number and Percent of Households eating 3 meals per day by District ........................................................... 92 3.63 Number and percent of Households Reporting food insufficiency by District ................................................. 93 3.62 Number and Percent of Households eating Meat Once per Week by District .................................................. 93 3.63 Number and Percent of Households eating Fish Once per Week by District.................................................... 96 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Ruvuma region is situated in the southern part of the country along with Mtwara and Lindi regions. It borders the Republic of Mozambique in the south, Lake Nyasa in the west and Iringa and Morogoro regions in the north. The region comprises five districts of Tunduru, Songea Rural, Mbinga, Songea Urban and Namtumbo. The region headquarters is located in Songea Urban District. 1.3 Land Area The region has an area of 66,477 square kilometers, of which about 50,540 square kilometers are arable land. Also out of the total area 2,979 square kilometers are under water bodies while 63,498 square kilometers are land area. The forest reserves cover 6,958 square kilometers. 1.4 Climate 1.4.1 Temperature The temperature in the region is moderately mild at an average temperature of 23oC depending on the altitude and season. The months of June, July and August are chilly with the temperature dropping to 13oC , particularly in the areas surrounding Matengo highlands in Mbinga district. October and November are the hottest months with an average temperature of 30oC in the lowlands. 1.4.2 Rainfall The region has two seasons, the dry and the wet seasons. The dry season (vuli) is from October to November and the wet season (Masika) from April to May. The average rainfall is between 800 and 1,800 millimeters. The amount varies from one district to another. Mbinga district has the highest average annual rainfall of 1,225 millimeters while Tunduru district has the lowest rainfall which is usually less than 900 millimeters per year. 1.5 Population According to the 2002 Population and Housing Census, there were 1,117,166 inhabitants in Ruvuma region. The population of Ruvuma region ranked 17th of the 21 regions of Tanzania Mainland. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 376,616 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 Million with a per capita income of shillings 337,117. The region held 10th position among regions on GDP and contributed about 3.8 percent of the national GDP1 . The region is famous for producing both food and cash crops. The main food crops produced in Ruvuma region include: maize, beans, sorghum, cassava, millet, paddy, wheat, sweet potatoes, irish potatoes, yams, sunflower, simsim and grounnuts. The main cash crops include cashew nut, tobacco and coffee. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 141 villages were from Ruvuma region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three Urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census for Ruvuma region. based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Ruvuma region was 191,175. The largest number of agriculture households was in Mbinga (79,589) followed by Tunduru (45,053), Songea Rural (28,109), Namtumbo (27,456) and Songea Urban (5,717) (Map 3.1). The highest density of households was found in Songea Urban (45/km2) followed by Mbinga (18/ km2) (Map 3.2). Most households 141,619 (74.1%) were involved in growing crops only, 132 (0.1%) were rearing livestock only, and 49,424 (25.9%) were involved in crop production as well as livestock keeping. There were no pastoralists in the region (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income In Ruvuma region most of the agricultural households ranked annual crop farming as the activity that provides most of their cash income followed by permanent crop farming, off farm income, livestock keeping/herding, remittances, fishing/hunting & gathering and tree/forest resources (Table 3.1). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittanc es Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 1 2 4 3 5 6 7 Songea Rural 1 2 4 3 5 6 7 Mbinga 1 2 3 4 5 6 7 Songea Urban 1 3 4 2 5 6 7 Namtumbo 1 2 3 4 5 6 7 Total 1 2 4 3 5 6 7 Chart 3.1 Agriculture Households by Type - Ruvuma Crops and livestock only 25.9% Livestock only 0.1% Crops only 74.1% Songea Urban Namtumbo Songea Rural 29,115 30,772 6,943 46,898 77,447 Mbinga Tunduru Namtumbo Songea Urban Songea Rural 3 45 6 7 18 Mbinga Tunduru 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 80,000 to 80,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Number of Agricultural Households Total Number of Agricultural Households by District MAP 3.01 RUVUMA MAP 3.02 RUVUMA Number of Agricultural Households Per Square Kilometer of Land by District Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer RESULTS 12 Songea Urban Mbinga Namtumbo Songea Rural 6,943 29,115 30,772 77,315 46,898 Tunduru Namtumbo Songea Urban Songea Rural 100% 100% 100% 100% 99.8% Mbinga Tunduru Number of Crop Growing Households by District MAP 3.03 RUVUMA MAP 3.04 RUVUMA Percent of Crop Growing Households by District Percent of Crop Growing Households Tanzania Agriculture Sample Census 80,000 to 80,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Crop Growing Households 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Crop Growing Households Percent of Crop Growing Households RESULTS 13 Songea Rural Songea Urban Namtumbo 6 45 3 7 17 Mbinga Tunduru Songea Rural Songea Urban Namtumbo 17% 17% 11% 4% 51% Mbinga Tunduru Number of Crop Growing Households Per Square Kilometer of Land by District MAP 3.05 RUVUMA Percent of Crop and Livestock Households MAP 3.06 RUVUMA Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census Number of Crop Growing Households Per Square Kilometer 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 40 to 60 30 to 40 20 to 30 10 to 20 0 to 10 Number of Crop Growing Households Per Square Kilometer Percent of Crop and Livestock Households RESULTS 14 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Ruvuma region was 169,347 (86% of the total regional agricultural households) while the female-headed households were 26,828 (14% of the total regional agricultural households). The mean age of household heads was 45 years (44 years for male heads and 49 years for female heads) (Chart 3.2). The results from six censuses/surveys years show that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Ruvuma region had a total rural agricultural population of 891,662 of which 438,796 (49%) were males and 452,866 (51%) were females. Whereas age group 0-14 constituted 43 percent of the total rural agricultural population, age group 15–64 (active population) was only 53 percent (Chart 3.3). Ruvuma region had an average household size of 4.7 with Mbinga district having the lowest household size of 4.4. 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Ruvuma region had a total literacy rate of 75 percent. The highest literacy rate was found in Songea Urban district (83%) followed by Mbinga district (80%) and Songea Rural district (78%). Tunduru and Namtumbo districts had the lowest literacy rates of 64 and 75 percent respectively (Chart 3.4). Chart 3.3 Percent Distribution of Population by Age and Sex - RUVUMA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Figure 3.4 Percentage LiterateLevel of Household Members by District 0 20 40 60 80 100 Songea Urb Mbinga Songea Rur Namtumbo Tunduru Districts Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 83 percent. The literacy rates for the male male heads was 85% and that of female heads of households was 68 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Songea Urban (89.4%) followed by Mbinga (87.6%), Songea Rural (85.2%), Namtumbo (83.8%) and Tunduru (72.8%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 50 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 30 percent were still attending school. Those who have never attended school were 20 percent (Chart 3.6). Agricultural households in Mbinga district had the highest percentage (55%) of population aged 5 years and above who had completed different levels of education. It was followed by Songea Rural and Songea Urban districts each with 53 percent. Tunduru and Namtumbo districts had the lowest percentages of 42 and 49 respectively. The number of heads of agricultural households with formal education in Ruvuma region was 157,638 (82%), those without education were 30,529 (16%) and those with only adult education were 3,007 (2%). The majority of heads of agricultural households (77%) had primary level education whereas only 5 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Ruvuma region, Mbinga had the highest percentages (43% for primary and 59% for secondary). This was followed by Tunduru (21% primary and 9% Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Attending School 30.0% Never Attended 20.0% Completed 50.0% Chart 3.5 Literacy Rates of Head of Household by Sex and District - RUVUMA 0.0 25.0 50.0 75.0 100.0 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent Male Female Total Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 2% Post Primary Education 5% No Education 16% Primary Education 77% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent Attending School Completed Never Attended RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 secondary), Songea Rural (17% primary and 11% secondary) and Namtumbo (16% primary and 15% secondary). Songea Urban had the lowest percentage of heads of agricultural households with primary education (4%) and secondary education (6%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important in agriculture households in Ruvuma with 66 percent of househiolds having at least one member with off-farm income. In Ruvuma region, of the households with a member engaged in off-farm income generating activities, 74,141 households (39%) had only one member aged 5 and above involved in only one off-farm income generating activity, 40,234 households (21%) had two members involved in off-farm income generating activities and 11,565 households (6%) had more than two members involved in off-farm income generating activities Songea Urban district had the highest percentage of agriculture households with their members engaged in off-farm income generating activities (over 55% of total agriculture households in the district). Other districts with high percentages were Songea Rural (74%) and Mbinga (69%). Namtumbo and Tunduru districts had the lowest percentages of agriculture households with off-farm income (63% and 56% respectively). The district with the highest percent of agriculture households having more than one member involved in off-farm income was Songea Urban (36%). Tunduru district had very few households with more than one member having off-farm income (18%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income None, 65,230, 65,230, 34% One, 74,141, 74,141, 39% Two, 40,239, 40,239, 21% More than Two, 11,565, 11,565, 6% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo Districts Percent More than Two Two One None RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 country, but the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 799,230 ha. The Regional average land area utilised for agriculture per household was only 3.0 ha. This figure is above the national average which is estimated at 2.0 hectares. Seventy five percent of the total land available to smallholders was utilised. Only 25 percent of usable land available to smallholders was not used (Chart 3.11). Large differences in land area utilised per household exist between districts with Songea Urban and Tunduru utilizing between 2.0 and 3.6 ha per household. The smallest land area utilised per household was found in Songea Urban (2.0 ha). The percentage utilized of the usable land per household was highest in Tunduru (82%) and lowest in Namtumbo (63%). (Map 3.7) 3.2.2 Types of Land Use The area of land under temporary monocrops was 204,996 hectares (25.6% of the total land available to smallholders in Ruvuma), followed by permanent/ monocrops (120,484 ha, 15.1%), uncultivatable usable land (115,091 ha, 14.4%), natural bush (79,522 ha, 9.9%), area under fallow (71,887 ha, 9.0%), permanent/annual mixed crops (66,045, ha, 8.3%), temporary mixed crops (46,471 ha, 5.8%), permanent mixed crops (39,451, ha, 4.9%), unusable area (24,297 ha, 3.0%), area planted with trees (10,991 ha, 1.4%), area rented to others (10,766 ha, 1.3%), and area under pasture (9,228 ha, 1.2%). 3.3 Annual Crop and Vegetable Production Ruvuma region has two seasons, namely the dry season (October to November) and the wet season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Districts Area/household 0 10 20 30 40 50 60 70 80 90 Percentage utilized Total Usable Area available (ha) Area utilised (ha) Percent Utilisation Chart 3.12 Land Area by Type of Use 15.0 26.0 14.0 10.0 9.0 8.0 6.0 5.0 3.0 1.0 1.0 1.0 0 50,000 100,000 150,000 200,000 250,000 Pasture Planted Trees Rented to Others Unusable Permanent Mixed Crops Temporary Mixed Crops Permanent / Annual Mix Fallow Natural Bush Uncultivated Usable Land Permanent Mono Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (hectares) Wet Season, 358,093, 99.97% Dry Season, 110, 0.03% Wet Season Dry Season Songea Urban Namtumbo Songea Rural 10,920ha 61,969ha 70,385ha 84,544ha 130,386ha Mbinga Tunduru Songea Urban Songea Rural Namtumbo 76.9% 68.1% 63.3% 81.6% 79.4% Mbinga Tunduru Utilized Land Area Expressed as a Percent of Available Land by District Total Planted Area (Annual Crops) MAP 3.08 RUVUMA Total Planted Area (Annual Crops) by District Percent of Utilized Land Area MAP 3.07 RUVUMA 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Percent of Utilized Land Area Total Planted Area (Annual Crops) Tanzania Agriculture Sample Census RESULTS 19 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 3.3.1 Area Planted The area planted with annual crops and vegetables was 358,203 hectares out of which 110 hectares (0.03%) were planted during dry season and 358,093 hectares (99.97%) during wet season (Chart 3.13). Mbinga had the largest area planted with annual crop and vegetables (130,386ha, 36.4%) followed by Tunduru (84,544 ha, 23.6%), Namtumbo (70, 385 ha, 19.6%), Songea Rural (61,969 ha, 17.3%) and Songea Urban (10,920 ha, 3.0%) (Chart 3.14 and Map 3.8). The average areas planted per household during the dry and wet seasons were 1.5 and 1.9 ha respectively. The districts with the largest planted area per household (the average of the two seasons) were Namtumbo (2.4 ha) followed by Songea Rural (2.0 ha) The district with the smallest average area planted was Songea Urban (1.6ha). The planted area occupied by cereals was 194,211 ha (54.2%of the total area planted with annuals). This was followed by roots and tubers (94,522 hectares, 26.4%), pulses (39,697 hectares, 11.1%), oil seeds (17,464 hectares, 4.9%), cash crops (7,169 hectares, 2.0%) and fruit and vegetables (5,140 hectares, 1.4%). The average area planted per household during the wet season in Ruvuma region was 1.9 hectares, however, there were small district differences. Namtumbo had the largest planted area per household (2.43 ha) followed by Songea Rural (2.02 ha) and Tunduru (1.81 ha). The smallest planted area per household was in Songea Urban (1.57 ha). In Namtumbo the area planted per household in the dry season represents 100 percent of the total planted area per household, whereas in the remaining districts the corresponding figure is 0 percent (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether it is annual or permanent. The second section contains an analysis on production based on crop types. Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Region Area Planted (ha) 0.00 0.04 0.08 0.12 0.16 0.20 Percentage Planted Dry Season Wet Season % Area planted in Dry Season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0 1 2 3 4 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Area Planted (ha) Wet Season Dry Season RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 3.3.2 Crop Importance Maize was the dominant annual crop grown in Ruvuma region and it had a planted area 1.59 times greater than cassava, which had the second largest planted area. The area planted with maize constituted 39 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) were paddy, beans, finger millet, groundnuts, tobacco and sweet potatoes (Chart 3.16). Households that grew maize, soya beans and cassava had larger planted areas per household than other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Ruvuma region. The area planted with cereals was 194,211 ha (54.2% of the total planted area), followed by root and tubers with 94,522 ha (26.4%), pulses 39,697 ha (11.1%), oil seeds 17,464 ha (4.9%), cash crops 7,169 ha (2.0%). Fruits and vegetables had the least planted area of about 5,140 ha (1.4%) (Chart 3.17b). Cereals and pulses were the dominant crops in both seasons and other crop types were of minor importance in comparison. There was little difference in the proportions of the different crop types grown between seasons and because the production in the dry season was very small compared to that of the wet season, it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.16 Planted Area (ha) for the Main Crops Ruvuma 0 50,000 100,000 150,000 Maize Cassava Paddy Beans Finger Millet Groundnuts Tobacco Sweet Potatoes Simsim Wheat Bambaranuts Cow Peas Sorghum Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - RUVUMA 0.00 0.20 0.40 0.60 0.80 Maize Soya Beans Cassava Carrot Tobacco Mung Beans Paddy Wheat Beans Pigeon Peas Finger Millet Simsim Sorghum Field Peas Groundnuts Sunflower Barley Crop Planted Area (ha) Chart 3.17b: Percentage Distribution of Area planted with Annual Crops by Crop Type Pulses 11.1% Cereal 54.2% Cash Crops 2.0% Oil seeds & Oil nuts 4.9% Fruits and Veg 1.4% Roots and Tubers 26.4% 66 94,522 0 39,697 0 17,435 29 7,169 0 5,125 15 0 50,000 100,000 150,000 200,000 A r e a ( h e c t a r e s) Cereal Roots and Tubers Pulses Oil seeds & Oil nuts Cash Crops Fruits and Veg Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Wet Season Dry Season Songea Urban Songea Rural Mbinga 0ha 110ha 0ha 0ha 0ha 0% 0% 0.2% 0% 0% Namtumbo Tunduru 88 to 110 66 to 88 44 to 66 22 to 44 0 to 22 Mbinga Namtumbo Songea Urban Songea Rural 48,989ha 61,595ha 40,018ha 37,655ha 5,953ha 57.9% 47.2% 56.9% 60.8% 54.5% Tunduru Area planted and Percentage During the Short Rainy Season by District MAP 3.09 RUVUMA Area Planted (ha) MAP 3.10 RUVUMA Area Planted With Cereals and Percent of Total Land Planted With Cereals by District 40,000 to 70,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Area planted (ha) Area Planted During the Short Rainy Season Percentage of Area Planted and During the Short Rainy Season Area Planted With Cereals Crops Percent of Total Land Planted With Cereals Crops Tanzania Agriculture Sample Census RESULTS 22 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.4 Cereal Crop Production The total production of cereals was 227,514 tonnes. Maize was the dominant cereal crop with 179,312 tonnes which was 79 percent of total cereal production, followed by paddy (17%), finger millet (2.66%), wheat (0.73%), sorghum (0.42%) and barley (0.01%). Mbinga district had the largest planted area of cereals in the region (61,595ha) followed by Tunduru (48,989ha), Namtumbo (40,018ha), Songea Rural (37,655) and Songea Urban 5,953) (Map 3.10). The total area planted with cereals during the dry and wet seasons was 194,211 ha out of which 66 ha (0.03%) were planted in the dry season and 194,145 ha (99.97%) were planted during the wet season. The wet season accounted for 99.98 percent of the total cereals produced in both seasons. The area planted with maize during the dry season was 56.1 percent of the total area planted with cereals in that season followed by Paddy (43.9%) (Table 3.2). The area planted with maize was dominant and it represented 71.9 percent of the total area planted with cereal crops, then followed by paddy (19.67%), finger millet (5.30%), wheat (2.08), Sorghum (1.07%), bulrush millet (0.02%) and barley (0.01%) . The yield of maize was 1,285 kg/ha, followed by paddy (1,034 kg/ha), barley (741 kg/ha), finger millet (588 kg/ha), sorghum (462 kg/ha), wheat (409 kg/ha) and bulrush (345 kg/ha). (Chart 3.19). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Ruvuma region during was 178,837 (94% of the total crop growing households in the region). The total production of maize was 179,283 tonnes from a planted area of 139,505 hectares resulting in a yield of 1.3 t/ha. Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 37 29 790 139,505 179,283 1,285 139,541 179,312 1,285 Paddy 29 4 124 38,178 39,510 1,035 38,207 39,514 1,034 Sorghum 0 0 0 2,079 961 462 2,079 961 462 Bulrush Millet 0 0 0 38 13 345 38 13 345 Finger Millet 0 0 0 10,287 6,046 588 10,287 6,046 588 Wheat 0 0 0 4,036 1,652 409 4,036 1,652 409 Barley 0 0 0 22 16 741 22 16 741 Total 66 33 194,145 227,482 194,211 227,514 Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 Maize Paddy Finger Millet Wheat Sorghum Bulrush Millet Barley Crop Area Planted (ha) 0.00 1.00 2.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.20: Time Series Data on Maize Production - RUVUMA 234 177 158 234 179 203 189 0 100 200 300 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Census/Survey year Production ('000') tonnes Tanzania Agriculture Sample Census Mbinga Namtumbo Songea Rural Songea Urban 0.6ha 0.7ha 1ha 0.9ha 0.7ha Tunduru Songea Urban Songea Rural Tunduru Namtumbo Mbinga 4,600ha 28,809ha 50,346ha 28,503ha 27,246ha 1.4t/ha 1.4t/ha 1.3t/ha 1.7t/ha 0.7t/ha Planted Area and Yield of Maize by District MAP 3.11 RUVUMA Planted Area Per Household MAP 3.12 RUVUMA Area Planted Per Maize Growing Household by District 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Planted Area Per Household RESULTS 24 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 25 Chart 3.20 indicates production trend (in thousand metric tonnes) for maize. There was a sharp increase in maize production (48%) in 1999 after which the production leveled in 2000 and then it declined during the year 2003. The average area planted with maize per household was 0.8 hectares, however it ranged from 0.6 hectares in Tunduru district to 1.0 hectares in Namtumbo district (Map 3.11). In the wet season, Mbinga district had the largest area of maize (50,346 ha) followed by Namtumbo (28,809 ha), Songera Rural (28,503 ha), Tunduru (27,246 ha), and Songea Urban (4,600 ha) (Chart 3.21 and Chart 3.22)(Map 3.12). Charts 3.20 and 3.22 shows that, with exception of the year 2003, there was a positive relationship between the quantity of maize produced and the yield. The area planted with maize remained constant over the two different period whereby the first period was from 1995 to 1997 the second one which was higher than the first one started from 1998 to 2000. Then the area under production dropped from the year 2000 to 2003. However, the yield of maize has shown a decline over the period 1996 to 2003 (from 1.9 t/ha in 1995 to 1.3 t/ha in 2003) (Chart 3.22). 3.3.4.2 Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Ruvuma region was 81,184. This represented 42 percent of the total crop growing households in Ruvuma region . The total production of paddy was 39,510 tonnes from a planted area of 38,178 hectares resulting in a yield of 1.03 t/ha. The district with the largest area planted with Paddy was Tunduru (19,750 ha) followed by Namtumbo (7,440 ha), Songea Rural(6,187 ha), Mbinga (3,721 ha), and Songea Urban (1,080 ha) (Map 3.15). There were small variations in the average area planted per crop growing household among the districts with the areas ranging from 0.36 ha in Songea Urban to 0.53 ha in Tunduru (Chart 3.23 and Map 3.16). Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 50,346 28,809 28,503 27,246 4,600 0 10,000 20,000 30,000 40,000 50,000 60,000 Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Area Planted per Household Area Planted (ha) Area Planted/hh Chart 3.22 Time Series of Maize Planted Area & Yield -RUVUMA 0 100,000 200,000 300,000 400,000 500,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Area Yield Chart 3.23 Total Planted Area and Area of Paddy per Household by District 1,080 3,721 6,187 7,440 19,750 0 5,000 10,000 15,000 20,000 25,000 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - RUVUMA 28 9 55 28 40 27 32 0 10 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Census/Survey year Production ('000') tons Namtumbo Songea Urban Songea Rural Mbinga 0.5ha 0.4ha 0.4ha 0.3ha 0.3ha Tunduru Songea Urban Namtumbo Songea Rural Mbinga 1,080ha 7,440ha 19,750ha 6,187ha 3,721ha 1t/ha 1.2t/ha 1.6t/ha 0.8t/ha 0.8t/ha Tunduru Planted Area and Yield of Paddy by District MAP 3.15 RUVUMA Area Planted Per Household MAP 3.16 RUVUMA Area Planted Per Paddy Growing Household by Distict Planted Area (ha) 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 26 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 There was a decline in the production of paddy from 1995/96 (32,000 tons) to 1996/97 (9,000 tons) there after a sharp rise in production from 1996/97 to 1997/98 (55,000 tons). Then a drop between 1997/98 and 1998/99 (28,000 tons) observed after that a constant production from 1998/99 to 1999/2000 (28,000 tons) followed by a rise to 2002/2003 (40,000 tons). Charts 3.24 and 3.25 show that, whilst the yield of paddy has dropped dramatically over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with paddy remained constant over the period from 1995 to 1997 after which the area under production expanded rapidly until 1999 after which it declined to 38,178 ha in 2003. Over the period 1995 to 1997 the yield of paddy fluctuated at around 2t/ha. However, there was a decline in yield over the period 1997 to 1999 (down to 0.5 t/ha) and it has then increased up to 1.0 t/ha in 2003 (Chart 3.25). 3.3.4.3 Other Cereals Other cereals were produced in small quantities. Sorghum was produced in Tunduru (1,845 ha), Namtumbo (180 ha), Mbinga (38 ha) and Songea Rural (15 ha). Fingermillet was produced in Mbinga (3,504 ha), Namtumbo (3,497 ha), Songea Rural (2,941 ha), Songea Urban (272 ha) and Tunduru (72 ha). Wheat was produced in Mbinga (3,986 ha), Tunduru (43 ha) and Songea Rural (8 ha). Bulrush millet was produced in Tunduru ( 13 ha ) and Namtumbo (25 ha) and barley was produced in Tunduru only (22 ha) (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 117,187 tonnes. Cassava production was higher than that of any other root and tuber crop in the region with a total production of 101,965 tonnes representing 87.0 percent of the total root and tuber crops production. This was followed by Sweet potatoes with 13,950 tonnes (11%), coco yam (876t, 0.8%), Chart 3.25 Time Series of Paddy Planted Area and Yield - RUVUMA 0 10,000 20,000 30,000 40,000 50,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.5 1.0 1.5 2.0 2.5 Yield (t/ha) Planted Area (ha) Yield (t/ha) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Area (Ha) Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.26 Area Planted with Sorghum, Bulrush Millet, Finger Millet, Wheat and Barley by District Sorghum Bulrush Millet Finger Millet Wheat Barley Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 30,000 60,000 90,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Mbinga Namtumbo Songea Urban Songea Rural 0.8ha 0.6ha 0.5ha 0.5ha 0.4ha Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Songea Urban Songea Rural Tunduru Mbinga Namtumbo 2,175ha 39,712ha 11,465ha 22,565ha 11,605ha 1.5t/ha 1.1t/ha 1.1 1.3t/ha 1.1t/ha 40,000 to 40,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area and Yield of Cassava by District MAP 3.13 RUVUMA MAP 3.14 RUVUMA Area Planted Per Cassava Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area(ha) Yield(t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 28 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 29 Irish potatoes (223t, 0.2%) and yams (173t, 0.1%) (Table 3.3). For the area under roots and tubers, the area planted with cassava was the largest in the region. Its planted area accounted for 92.6 percent of the area planted with roots and tubers, followed by sweet potatoes (6.7%), coco yams (0.5%), Irish potatoes (0.2%), and yams (0.1%). It is difficult to determine the total planted area and production for the dry and wet seasons for roots and tubers as the total production of cassava has been reported under the wet season. However, there was no area planted with roots and tubers during the dry season hence no crop production. There was a significant increase in area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potato remained more or less constant while there was a decrease in the area of yams from 1998/99 to 2002/03. The total production of roots and tubers was estimated at 117,187 tonnes. Cassava with an estimate of 101,965 tonnes was the most important root and tuber crop. It accounted for 87.0 percent of the total roots and tubers production, followed by sweet potatoes with 13,950 tonnes (11.9%), coco yams with 876 tonnes (0.7%) Irish potatoes with 223 tonnes (0.2%) and yams with 173 tonnes (0.1%). estimated yield was high for sweet potatoes (2.2 and t/ha) coco yams (2.0 t/ha), followed by yams (1.8 t/ha, Irish potatoes (1.6 t/ha and cassava (1.2 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 137,409. This represents 72 percent of the total crop growing households in the region. The total production of cassava during the census year was 101,965 tonnes from a planted area of 87,522 hectares resulting in a yield of 1.2t/ha. Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 0 0 0 87,522 101,965 1,165 87,522 101,965 1,165 Sweet Potatoes 0 0 0 6,316 13,950 2,209 6,316 13,950 2,209 Irish Potatoes 0 0 0 143 223 1,559 143 223 1,559 Yams 0 0 0 96 173 1,802 96 173 1,802 Cocoyam 0 0 0 446 876 1,964 446 876 1,964 TOTAL 0 0 94,522 117,187 94,522 117,187 Note: Cassava is produced in both the wet and dry season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the wet season only. Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 20,000 40,000 60,000 80,000 100,000 1994/95 1995/96 1998/99 2002/03 Ye ar Cassava Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 45.4 25.8 13.3 13.1 2.5 0.0 20.0 40.0 60.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent of Total Area Planted 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.76 0.64 0.53 0.51 0.41 0.00 0.20 0.40 0.60 0.80 Area per Household Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 Previous censuses and surveys indicate that the area planted with cassava was increasing for the period 1995 to 1999. Since 1999 the area planted with cassava dropped from 96,039 ha in 1988 to 87,522 ha in 2003 (Chart 3.28). The area planted with cassava accounted for 24 percent of the total area planted with annual crops and vegetables in the census year. Mbinga district had the largest planted area of cassava (39,712 ha, 45.4% of the cassava planted area in the region), followed by Tunduru (22,565 ha, 25.8%), Namtumbo (11,605 ha, 13.3%), Songea Rural (11,465 ha, 13.1%) and Songea Urban (2,175 ha, 2.5%) (Map 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Mbinga district (30.5%). This was followed by Tunduru (26.7%), Songea Urban (19.9%), Songea Rural (18.5%) and Namtumbo (16.5%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.64 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Mbinga (0.76 ha). This was followed by Tunduru (0.64 ha), Namtumbo (0.53 ha), Songea Rural (0.51 ha) and Songea Urban (0.41 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Ruvuma region was 35,326. The total production of sweet potatoes during the census year was 13,950 tonnes from a planted area of 6,316 hectares resulting in a yield of 2.2t/ha. Mbinga District has the largest planted area for sweet potatoes (3,648 ha, 58%), followed by Songea Rural (817 ha, 13%), Tunduru (711, 11%), Songea Urban (639, 10%) and Namtumbo (501 ha, 8%) (Chart 3.31).Other root and tuber crops were of minor importance in terms of area planted compared to cassava and sweet potatoes. 3.3.6 Pulse Crops Production The total area planted with pulses was 39,697 hectares out of which 34,237 ha were planted with beans (86 percent of the total area planted with pulses), followed by bambaranuts ( 2,570 ha, 6.5%), cow peas (2,438 ha, 6.1%), field peas (189 ha, 0.5%), green gram (138 ha, 0.3%), mung beans (73 ha, 0.2%) and pigeon peas (51 ha, 0.1%). Chick peas were not cultivated in the region. Pulses were not grown during the dry season. The total production of pulses was 17,234 tonnes. Beans were the most cultivated crop producing 15,059 tonnes which accounted for 87 percent of the total pulse production. This was followed by bambaranuts (1,126t, 6.5%), cow peas (821t, 4.8%), field peas (154t, 0.9%), green gram and (each 37t, 0.2%), mung beans (34t, 0.1%) and pigeon peas (3t, 0.02%). Table 3.4: Area, Production and Yield of Pulses by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 73 34 466 73 34 466 Beans 0 0 0 34,237 15,059 440 34,237 15,059 440 Cowpeas 0 0 0 2,438 821 337 2,438 821 337 Green Gram 0 0 0 138 37 268 138 37 268 Pigeon Peas 0 0 0 51 3 59 51 3 59 Bambaranuts 0 0 0 2,570 1,126 438 2,570 1,126 438 Field Peas 0 0 0 189 154 815 189 154 815 TOTAL 0 0 39,697 17,234 39,697 17,234 Chart 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 501 639 3,648 817 711 0 1,000 2,000 3,000 4,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Area (Ha) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Area Planted per Household Planted Area (ha) Planted Area per hh Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 10,000 20,000 30,000 40,000 Beans Bambaranuts Cowpeas Field Peas Green Gram Mung Beans Pigeon Peas Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) Songea Urban Mbinga Songea Rural Namtumbo 0.2ha 0.4ha 0.4ha 0.3ha 0.5ha Tunduru Songea Urban Tunduru Namtumbo Songea Rural Mbinga 897ha 1,812ha 20,544ha 4,877ha 6,108ha 0.3t/ha 0.6t/ha 0.4t/ha 0.4t/ha 0.5t/ha 16,000 to 21,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area and Yield of Beans by District MAP 3.17 RUVUMA Area Planted Per Beans Growing Household MAP 3.18 RUVUMA Area Planted Per Beans Growing Household by District Planted Area and Yield of Beans Planted Area(ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Beans Growing Household Tanzania Agriculture Sample Census RESULTS 31 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 Chick peas were not grown in the region. Field peas had the highest yield of 815 kgs/ha. The yields of the rest of the pulses in kilograms per hectare were mung beans 466 kgs/ha, beans 440 kgs/ha, bambaranuts 438 kgs/ha, cowpeas 337 kgs/ha and green gram 268 kgs/ha. Pigeon peas had the lowest yield of 59 kgs/ha (Chart 3,32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Ruvuma region was 86,699. The total production of beans in the region was 15,059 tonnes from a planted area of 34,237 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Mbinga district (20,544 ha, 60%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per household was in Tunduru district (0.48 ha) (Chart 3.34). The average area planted per household in the region during the wet season was 0.39 ha. The variations in area planted with beans for the rest of the districts were small with the areas ranging from 0.21 ha in Songea Urban district to 0.48 ha in Tunduru district (Map 3.18). In Ruvuma region, bean production over the period 1995 to 2003 was normally about 10,000 tonnes except for the year 1998 where the production was highest at 62,267 tonnes (Chart 3.35). Charts 3.35 and 3.36 show that, the yield of beans remained fairly constant the previous 8 years and the quantity produced also remained generally constant. The area planted with beans has decreased over the period from 1986 to 2003. Over the period 1997 to 2003 the yield of beans remained constant at around 0.3 t/ha. (Chart 3.36). Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 80 Mbinga Songea Rural Namtumbo Tunduru Songea Urban District Percent of Land 0 10 20 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.48 0.44 0.36 0.33 0.21 0.00 0.15 0.30 0.45 0.60 Area per Household Tunduru Mbinga Songea Rural Namtumbo Songea Urban District Chart 3.34 Area Planted per Bean Growing Household by District (Wet Season Only) Chart 3.35: Time Series Data on Beans Production - RUVUMA 10 8 7 15 10 62 13 0 15 30 45 60 75 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Chart 3.36 Time Series of Beans Planted Area & Yield - RUVUMA 0 20,000 40,000 60,000 80,000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 0.8 Yield (t/ha) Area Yield Mbinga Namtumbo Songea Urban Songea Rural 0.2ha 0.3ha 0.2ha 0.3ha 0.2ha Tunduru 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0 to 0.2 Songea Urban Songea Rural Tunduru Namtumbo Mbinga 225ha 1,980ha 4,088ha 2,046ha 1,193ha 1t/ha 0.5 0.5t/ha 0.5t/ha 0.4t/ha Planted Area and Yield of Groundnuts by District MAP 3.21 RUVUMA Area Planted Per Household MAP 3.22 RUVUMA Area Planted Per Groundnuts Growing Household by District 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 33 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.7 Oil Seed Production The total production of oilseed crops was 7,752 tonnes planted on an area of 17,464 hectares. The total planted area of oilseeds in the wet season was 17,435 ha representing 99.8 percent of the total area planted with oil seeds. Groundnuts were the most important oilseed crop with 9,561 ha (55% of the total area planted with oil seeds), followed by simsim (36%), soya beans (5%) and sunflower (5%) (Chart 3.37). The yield of sunflower was moderate (501 kg/ha). Groundnuts had a yield of 496 kg/ha, simsim of 378 kg /ha and soya beans 297 kg/ha. In terms of production, groundnuts was 4,732 tonnes and accounted for 61 percent of the total production of oil seeds, followed by simsim (31%), sunflower (5%) and soya beans (3%). 3.3.7.1 Groundnuts The number of households growing groundnuts in Ruvuma region was only 39,911. The total production of groundnuts in the region was 4,732 tonnes from a planted area of 9,561 hectares resulting in a yield of 0.5 t/ha. There was a sharp increase in production of groundnuts over the period 1995 to 1996, from 78 tonnes in 1994/95 to 100,417 tonnes in 1995/96, and then a sharp decrease to 4732 tonnes in 2002/03. The area planted dropped from 5,129.27 hectares in 1994/95 to 3,359.82 hectares in 1995/96 after which it increased to 9,561 hectares in 2002/03 (Chart 3.38). With 4,117 ha of groundnuts, 43.1% of the total area planted with groundnuts in the region, Tunduru had the largest planted area followed by Namtumbo (2,046 ha, 21.2%), Songea Rural (1,980 ha, 20.8%), Mbinga (1,193 ha, 12.5%) and Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 796 399 501 796 399 501 Simsim 0 0 0 6,279 2,376 378 6,279 2,376 378 Groundnuts 29 1 49 9,532 4,731 496 9,561 4,732 495 Soya Beans 0 0 0 828 246 297 828 246 297 Total 29 1 17,435 7,751 17,464 7,752 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 2,500 5,000 7,500 10,000 Groundnuts Simsim Sunflower Soya Beans Crop Area Planted (ha) 0 200 400 600 800 1000 Yield (kg/ha) Yield (kg/ha) Chart 3.38 Time Series Data on Groundnut Production - RUVUMA 4,731 78 100,417 0 20,000 40,000 60,000 80,000 100,000 1994/95 1995/96 2002/03 Year Production ( tonnes) 0 0.1 0.2 0.3 Area per Household (ha) Tunduru Songea Urban Songea Rural Namtumbo Mbinga District Chart 3.40 Area Planted per Groundnut Growing Households by District (Wet Season Only) Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 10.0 20.0 30.0 40.0 50.0 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District Percent of Land 0.0 1.0 2.0 3.0 4.0 5.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 Songea Urban (225 ha, 2.4%) (Map 3.19). The highest proportion of land with groundnuts was found in Tunduru (4.8%) followed by Songea Rural (3.2%), Namtumbo (2.9%), Songea Urban (2.1%) and Mbinga (0.9%) (Chart 3.39). The largest area planted per groundnut growing household was found in Tunduru District (0.27 ha) and the smallest was in Mbinga (0.18). The range between the district with the highest and the lowest area planted per household indicates small variations in area planted among the districts (Chart 3.40 and Map 3.20). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The dry season is relatively not important for fruit and vegetables production since 0.3 percent of the total area planted with fruit and vegetables was during the dry season. For cabbage and amaranths below 3 percent of the planted area of each crop was during the dry season. Excluding cabbage and amaranths, the planted area for each crop in the wet season was abnormally large (100% of the total planted area was in the wet season). Reliable historical data for the time series analysis of fruit and vegetables were not available. The total production of fruits and vegetables was 16,087 tonnes. The most cultivated fruit and vegetable crop was the tomato crop with a production of 7,328 tonnes (46% of the total fruit and vegetables produced) followed by cabbage (4,119t, 26%) and onions (1,704t, 11%). The production of other fruit and vegetable crops were relatively small (Table 3.6). The yield of okra was 16,134 kg/ha, tomatoes (3,804 kg/ha), cabbage (3,386 kg/ha), and onion (2,915 kg/ha). Radish and carrot had yields of 267 and 294 kg/ha respectively (Chart 3.41). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during wet was 13,606 and no household grew tomatoes during dry season. This represented 7.1 percent of the total crop growing households during wet season. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Dry season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Okra 0 0 0 3 45 16,134 3 45 16,134 Radish 0 0 0 7 2 267 7 2 267 Onions 0 0 0 585 1,704 2,915 585 1,704 2,915 Cabbage 7 11 1,482 1,209 4,109 3,397 1,217 4,119 3,386 Tomatoes 0 0 0 1,927 7,328 3,804 1,927 7,328 3,804 Spinnach 0 0 0 465 854 1,837 465 854 1,837 Carrot 0 0 0 72 21 294 72 21 294 Chillies 0 0 0 27 28 1,007 27 28 1,007 Amaranths 7 8 1,087 349 854 2,449 356 862 2,421 Pumpkins 0 0 0 448 1,048 2,342 448 1,048 2,342 Cucumber 0 0 0 22 27 1,219 22 27 1,219 Egg Plant 0 0 0 12 48 3,987 12 48 3,987 Total 15 19 5,125 16,068 5,139 16,087 Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 500 1,000 1,500 2,000 Tomatoes Cabbage Onions Spinnach Pumpkins Amaranths Others Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 36 Mbinga district had the largest planted area of tomatoes (33% of the total area planted with tomatoes in the region), followed by Tunduru (29%), Songea Urban (15%), Namtumbo (14%) and Songea Rural (10%) (Chart 3.42 and Map 21). The highest proportion of land with tomatoes was found in Songea Urban, followed by Tunduru district. The rest of the districts had low proportions of land used for tomato production (Chart 3.42). The largest area planted per tomato growing household was found in Tunduru district (0.20 ha) followed by Songea Urban (0.15 ha), Mbinga (0.13 ha), Namtumbo (0.12 ha) and Songea Rural (0.08 ha) (Chart 3.43 and Map 3.22). The total area planted with tomatoes accounted for 0.5 percent of the total area planted with annual crops and vegetables during the dry and wet seasons . 3.3.8.2 Cabbage The number of households growing cabbages in the region during wet season was 10,900 and 72 in the dry season. This represented 5.7 percent of the total crop growing households in the region in the wet season and 0.04 percent in the dry season. Mbinga district had the largest planted area of cabbage (432 ha, 35.5% of the total area planted with cabbage in the region), followed by Namtumbo (260 ha, 21.4%), Songea Rural (248 ha, 20.4%), Songea Urban (201 ha, 16.5%) and Tunduru (75 ha, 6.2%) (Chart 3.44 and Map 3.23). The total area planted with cabbages accounted for 0.3 percent of the total area planted with annual crops and vegetables during the dry and wet season. 3.3.8.3 Onions The number of households growing onions in the region during the wet season was 4,075 households and there were no households growing onions in the dry season. This represents 2.1 percent of the total crop growing households in the region in the wet season and zero percent in the dry season. Namtumbo district had the largest planted area of onions (186 ha, 31.9% of the total area planted with onions in the region), followed by Mbinga (158 ha, 27.0%), Tunduru (135 ha, 23.1%), Songea Urban (54ha, 9.2%) and Songea Rural (51 ha, 8.8%) districts (Map 3.24). Chart 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0 10 20 30 40 Mbinga Tunduru Songea Urban Namtumbo Songea Rural District Percent of Land 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 Area per Household (ha) Tunduru Songea Urban Mbinga Namtumbo Songea Rural District Chart 3.43 Area Planted per Tomato Growing Household by District (Wet Season) Chart 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 10.0 20.0 30.0 40.0 Mbinga Namtumbo Songea Rural Songea Urban Tunduru District Percent of Land 0.00 0.50 1.00 1.50 2.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Namtumbo Songea Urban Songea Rural Mbinga 72ha 3,497ha 3,504ha 272ha 2,941ha 0.2t/ha 0.5t/ha 0.7t/ha 0.8t/ha 0.6t/ha Tunduru Mbinga Songea Rural Songea Urban Namtumbo 0.4ha 0.3ha 0.3ha 0.2ha 0.3ha Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 2,800 to 3,600 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Planted Area and Yield of Finger Millet by District MAP 3.19 RUVUMA Area Planted Per Household MAP 3.20 RUVUMA Area Planted Per Finger Millet Growing Household by District Planted Area (ha) Planted Area (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 37 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 38 The largest proportion of the area planted with onions was found in Songea Urban district (0.49%), followed by Namtumbo (0.26%), Tunduru (0.16%), Mbinga (0.12%) and Songea Rural (0.08) (Chart 3.45). The total area planted with onions accounted for 0.16 percent of the total area planted with annual crops and vegetables during the dry and wet seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 7,169 ha was planted with other annual crops and tobacco was the only annual cash crop grown in the region. No area was planted with tobacco during the dry season. 3.3.9.1 Tobacco The quantity of tobacco produced was 4,371 tonnes. Tobacco had a planted area of 7,169 ha, all of which was planted in the wet season. Namtumbo had the largest planted area (78.1% of total area planted with tobacco in the region), followed by Tunduru (9.2%), Songea Rural (8.7%), Mbinga (2.4%) and Songea Urban (1.5%) (Chart 3.46) (Map 3.25 and 3.26). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 124,910 hectares (35% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops should be higher than indicated in Chart 3.47. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tobacco 0 0 0 7,169 4,371 610 7,169 4,371 610 TOTAL 0 0 7,169 4,371 7,169 4,371 Chart 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District 0.0 10.0 20.0 30.0 40.0 Namtumbo Mbinga Tunduru Songea Urban Songea Rural District Percent of Land 0.00 0.15 0.30 0.45 0.60 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 30.0 60.0 90.0 Namtumbo Tunduru Songea Rural Mbinga Songea Urban District Percent of Land 0.00 3.00 6.00 9.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.47 Area Planted for Annual and Permanent Crops Annual Crops, 358,203, 74% Permanent Crops, 124,910, 26% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 The most important permanent crop in Ruvuma region is cashewnut which had a planted area of 74,124 ha, (61% of the planted area of all permanent crops) followed by coffee (29,961 ha, 24%), and banana (7,751 ha, 6%). The remaining permanent crops accounted for 10 percent of the total area planted with permanent crops (Chart 3.48). Tunduru district had the largest area under smallholder permanent crops (79,226 ha, 63.4%). This was followed by Mbinga (33,195 ha, 26.6%), Songea Rural (5,655 ha, 4.5%), Namtumbo (5,233 ha, 4.2%) and Songea Urban (1,603 ha, 1.3%). However, Tunduru had the largest area per permanent crop growing household (1.58 ha) followed by Mbinga (0.58 ha), Songea Urban (0.46 ha), Songea Rural (0.42 ha) and Namtumbo (0.39) (Chart 3.49). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Tuduru had the highest (48%) followed by Songea Urban (20%), Songea Rural (13%), Mbinga (8%), and Namtumbo (7%). 3.4.1 Cashewnut The total production of cashewnut by smallholders was 9,278 tonnes. In terms of area planted, cashewnut was the most important permanent crop grown by smallholders in the region. They were grown by 39,985 households (20.9% of the total crop growing households). The average area planted with cashewnut per household per cashew nut growing household was 1.85 ha and the average yield obtained by smallholders was 176 kg/ha from a harvest area of 52,08 hectares. Tunduru had the largest area of cashewnut in the region (71,527 ha, 96.5%) followed by Namtumbo (1.228 ha, 1.7%), Mbinga (917 ha, 1.2%), Songea Rural (451 ha, 0.6%) and Songea Urban (1 ha, 0.0%) (Map 3.27). However, the average area planted with cashewnut per cashewnut growing household was highest in Tunduru (1.99 ha) followed by Songea Rural (0.86 ha), Namtumbo (0.83 ha), Mbinga (0.45 ha) and Songea Urban (0.04 ha) (Chart 3.50 and Map 3.28). Chart 3.49 Percent of Area Planted and Average Planted Area with Permanent Crops by District 26.6 1.3 4.5 4.2 63.4 0.0 30.0 60.0 Tunduru Mbinga Songea Urban Songea Rural Namtumbo District % of Total Area Planted 0.00 0.30 0.60 0.90 1.20 1.50 1.80 Average Planted Area per Household % of Area Area per Hh Chart 3.48 Area Planted with the Main Perennial Crops Sugarcane, 1,482, 1% Mango, 1,359, 1% Cashewnut, 74,124, 61% Coffee, 29,961, 24% Banana, 7,751, 6% Pigeon Pea, 5,159, 4% Orange, 2,827, 2% Coconut, 989, 1% Avocado, 249, 0% Sour Soup, 252, 0% Chart 3.50 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 96.5 1.2 0.6 1.7 0.0 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Tunduru Songea Rural Namtumbo Mbinga Songea Urban District % of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Songea Urban Songea Rural 0.4ha 0.6ha 0.4ha 0.5ha 0.4ha Mbinga Namtumbo Tunduru Namtumbo Songea Urban Songea Rural 0.6t/ha 0.5t/ha 0.5t/ha 0.8t/ha 0.4t/ha 5,602ha 110ha 623ha 174ha 660ha Mbinga Tunduru Planted Area and Yield of Tobacco by District MAP 3.23 RUVUMA Area Planted Per Household MAP 3.24 RUVUMA Area Planted Per Tobacco Growing Household by District Planted Area (ha) 6,000 to 7,500 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 40 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 3.4.2 Coffee The total production of coffee by smallholders was 12,388 tonnes. In terms of area planted, coffee was the second most important permanent crop grown by smallholders in the region. It was grown by 41,347 households (21.6% of the total crop growing households). The average area planted with coffee per household was relatively small at around 0.73 ha per coffee growing household and the average yield obtained by smallholders was 475 kg/ha from a harvest area of 26,030 hectares. Mbinga had the largest area of coffee in the region (29,312 ha, 97.8%) followed by Songea Rural (582 ha, 1.9%), Songea Urban (42 ha, 0.1%) and Tunduru (25 ha, 0.08%). Coffee was not grown in Namtumbo district (Map 3.29). However, the average area planted with coffee per coffee planting household was highest in Mbinga (0.7 ha) followed by Songea Rural (0.5 ha), Songea Urban (0.4 ha) and Tunduru (0.2 ha) (Chart 3.51 and Map 3.30). 3.4.3 Banana The total production of banana by smallholders was 37,890 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 24,420 households (12.8% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.32 ha per banana growing household and the average yield obtained by smallholders was 4,888 kg/ha from a harvested area of 7,751 hectares. Namtumbo had the largest planted area of bananas in the region (2,704 ha, 35%) followed by Songea Rural (1,622 ha, 21%), Songea Urban (1,307 ha, 17%), Mbinga (1,096 ha, 14%) and Tunduru (1,022 ha, 13%) (Map 3.31). However, the area planted with banana per banana growing household was highest in Songea Urban (0.68 ha), followed by Tunduru (0.51 ha), Namtumbo (0.40 ha), Songea Rural (0.23 ha) and Mbinga (0.17 (Chart 3.52 and Map 3.32). 3.4.4 Pigeon Peas The total production of pigeon peas by smallholders was 515 tonnes. In terms of area planted, pigeon peas was the fourth most important permanent crop grown by smallholders in the region. It was grown by 9,069 households (4.7% of the total crop growing households). The average area planted with pigeon peas per household was relatively small at around 0.57 ha per pigeon peas growing household and the average yield obtained by smallholders was 100 kg /ha from a harvest area of 5,159hectares. Chart 3.51 Percent of Area Planted with Coffee and Average Planted Area per Household by District 0.14 0.00 97.83 0.08 1.94 0.00 20.00 40.00 60.00 80.00 100.00 Mbinga Songea Rural Songea Urban Tunduru Namtumbo District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Banana and Average Planted Area per Household by District 21 14 35 13 17 0 10 20 30 40 Namtumbo Songea Rural Songea Urban Mbinga Tunduru District % of Total Area Planted 0.00 0.20 0.40 0.60 0.80 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Pegeon peas and Average Planted Area per Household by District 7.52 0.00 92.19 0.00 0.29 0.00 20.00 40.00 60.00 80.00 100.00 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Songea Urban Namtumbo Songea Rural 0.4ha 0.2ha 0ha 0.5ha 0.7ha Mbinga Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Songea Rural Songea Urban Namtumbo 0.5 0.2t/ha 0.4t/ha 0t/ha 0.1t/ha 582ha 42ha 29,312ha 0ha 25ha Mbinga Tunduru Planted Area and Yield of Coffee by District MAP 3.31 RUVUMA Area Planted Per Household MAP 3.32 RUVUMA Area Planted Per Coffee Growing Household by District Planted Area (ha) Planted Area (ha) Yield (t/ha) 20,000 to 50,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 42 Songea Urban Namtumbo Songea Rural Mbinga 0.7ha 0.5ha 0.4ha 0.2ha 0.2ha Tunduru Namtumbo Songea Urban Songea Rural 2,704ha 1,022ha 1,307ha 1,622ha 1,096ha 2.2t/ha 1.6t/ha 1.7t/ha 3.2t/ha 20.7t/ha Mbinga Tunduru Planted Area and Yield of Banana by District MAP 3.33 RUVUMA Area Planted Per Household MAP 3.34 RUVUMA Area Planted Per Banana Growing Household by District Planted Area and (ha) Planted Area (ha) Yield (t/ha) 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 43 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 44 Tunduru had the largest area of pigeon peas in the region (4,758 ha, 92.19%) followed by Namtumbo (388 ha, 7.52%) and Songea Rural (15 ha, 0.29%). Pigeon peas was not grown in Mbinga and Songea Urban (Map 3.33). However, the average area planted per pigeon peas growing household was highest in Tunduru (0.62 ha), followed by Namtumbo (0.28 ha) and Songea Rural (Chart 53 and Map 3.34). 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region during the wet season was 196,846 ha which represented 72.8 percent of the total area cleared. Bush clearance, burning and tractor slashing are less important methods for land clearing and they accounted 16.8, 9.3 and 1.1 percent of the area cleared respectively (Chart 3.54 and Table 3.8). 3.5.2 Methods of Soil Preparation Hand cultivation is the most used method for soil preparation and was used in an area of 255,944 ha which represented 94 percent of the total planted area, followed by ox-ploughing (10,809 ha, 4%) and tractor ploughing (4,525 ha, 2%) (Chart 3.55). Table 3.8: Land Clearing Methods Wet Season Dry Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 136,593 196,846 72.8 145 15 13.6 136,738 196,86 1 72.8 Mostly Bush Clearance 31,923 45,315 16.8 217 95 86.4 32,140 45,410 16.8 Mostly Burning 15,927 25,069 9.3 0 0 0.0 15,927 25,069 9.3 No Land Clearing 2,084 2,875 1.1 0 0 0.0 2,084 2,875 1.1 Mostly Tractor Slashing 181 245 0.1 0 0 0.0 181 245 0.1 Other 0 0 0.0 0.0 0 0 0.0 Total 186,708 270,350 100.0 362 110 100.0 187,070 270,460 100.0 Chart 3.54 Number of Households by Method of Land Clearing during the Wet Season 136,593 31,923 15,927 2,084 181 0 0 100,000 200,000 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.57 Planted Area of Improved Seeds - RUVUMA Without Improved Seeds, 236,071, 87% With Improved Seeds, 35,208, 13% Chart 3.55 Area Cultivated by Cultivation Method Mostly Hand Cultivation, 255,944, 94% Mostly Oxen Ploughing, 10,809, 4% Mostlly Tractor Ploughing, 4,525, 2% 0 20,000 40,000 60,000 80,000 100,000 Area Cultivated (ha) Tunduru Songea Urban Songea Rural Namtumbo Mbinga District Chart 3.56 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostlly Tractor Ploughing Songea Urban Tunduru Namtumbo Songea Rural Mbinga 0ha 4,756ha 388ha 15ha 0ha 0t/ha 0.2t/ha 0.1t/ha 0.2t/ha 0t/ha 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Songea Urban Songea Rural 0ha 0ha 0.2ha 0.3ha 0.6ha Mbinga Namtumbo Tunduru Planted Area and Yield of Pigeon Peas by District MAP 3.35 RUVUMA Area Planted Per Household MAP 3.36 RUVUMA Area Planted Per Pigeon Peas Growing Household by District Planted Area and Yield of Pigeon Peas Planted Area of Pigeon Peas Yield of Pigeon Peas 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 45 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 While all land preparation was done by hand during the dry season, the area so was 72% of the total planted area during the wet season. All preparation by oxen and tractor was done during the wet season. In Ruvuma region, Tunduru district had the largest planted area cultivated with oxen (4,907 hectares, 45.4%) followed by Songea Urban (2,268 ha, 21.0%), Songea Rural (2,095 ha, 19.4%), Namtumbo (1,405 ha, 13.0%) and Mbinga (134 ha, 1.2%). During the wet season, 76.6 percent of the total area cultivated by using oxen was planted with cereals followed by pulses (11.5%), oil seeds (6.2%), fruits and vegetables (2.4%), cash crops (1.9%) and roots and tubers (1.4%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 35,208 ha which represents 8 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the dry season was 13.6 percent, slightly higher than the corresponding percentage use in the wet season (9.8%). Cereals had the largest planted area with improved seeds (21,034 ha, 60% of the planted area with improved seeds) followed by roots and tubers (6,755 ha, 19%), fruit and vegetables (2,975 ha, 8%) , cash crops (2,665 ha, 8%), pulses (1,206 ha, 3%) and Oil seed (593 ha, 2%) (Chart 3.58). However, the use of improved seed in roots and tubers and fruits and vegetables is much greater than in other crop types (89% and 59% respectively), only 3 percent of the planted area for oil seed crops used improved seed (Chart 3.59). 3.5.4 Fertilizer Use The use of fertilisers on annual crops was small with its application on a planted area of only 76,463 ha (21.3% of the total planted area in the region). The planted area without fertiliser for annual crops was 281,740 hectares representing 78.7 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertilizers were applied to 43,402 ha which represents 12.1 percent of the total planted area (56.8% of the area planted with fertiliser application in the region). This was followed by farm yard manure (29,470 ha, 38.5%). Compost fertilizers were used on a very small area which represented only 47 percent of the area planted with fertilizers. Table3.9 Planted Area by Type of Fertilizer Use and District – Wet and Dry Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total applied No Fertilizer Applied Tunduru 1,163 649 5,457 7,269 77,275 Songea Rural 5,952 829 9,312 16,094 45,875 Mbinga 17,981 1,561 12,325 31,867 98,519 Songea Urban 2,098 159 3,857 6,114 4,806 Namtumbo 2,277 394 12,449 15,120 55,265 Total 29,470 3,591 43,402 76,463 281,740 Table 3.10: Number of Crop Growing Households and Planted Area By Type of Fertilizer Use and District – Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 Namtumbo 1,150 2,277 143 394 5,540 12,340 22,282 55,265 29,115 70,275 Total 13,938 29,470 1,671 3,591 23,638 43,292 151,614 281,740 190,861 358,093 Chart 3.58 Planted Area with Improved Seed by Crop Type Roots & Tubers, 6,755, 19% Oilseeds , 593, 2% Cereals, 21,034, 60% Pulses, 1,206, 3% Cash Crops, 2,663, 8% Fruits & Vegetables, 2,975, 8% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Fruits & Vegetables Cash Crops Pulses Oilseeds Crop Type Chart 3.59 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 47 The highest percentage of the area planted with fertilizers (all types) was in Mbinga district (41.7%) followed by Songea Rural (21%), Namtumbo (20%), Tunduru (10%) and Songea Urban (8%) (Table 3.9 and Charts 3.60 and 3.61). Most annual crop growing households do not use any fertiliser (approximately 39,247 households, 20.6%) (Map 3.35). The percentage of the planted area with applied fertilizer was highest for cereals (75.1% of the area planted with these creals during the wet season had an application of fertilizers). This was followed by pulses (6.7%), roots and tubers (6.6%), cash crops (5.7%), fruits and vegetables (3.7%) and oil seeds (2.1%) (Table 3.10). 3.5.4.1 Farm Yard Manure Use The planted area applied with farm yard manure in Ruvuma region during wet season was 29,470 ha representing 8.2% of the total planted area during that season. The number of households that applied farm yard manure in their annual crops during wet season was 13,938. (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (65%), followed by fruit and vegetables (14%), roots and tubers (11%), pulses (9%), oil seeds (1%) and cash crops (0.3%). Fruit and vegetables had the highest percent of the planted area with farm yard manure (84.5% of the total area planted with fruit and vegetables in Ruvuma). This was followed by roots and tubers (53%), pulses (46%), cereals (35%), oil seeds (21%) and cash crops (1%) (Charts 3.62 and 3.63a). Farm yard manure is mostly used in Songea Urban (19.2% of the total planted area in the district), followed by Mbinga (13.8%), Songea Rural (9.6%), Namtumbo (3.2%) and Tunduru (1.4%) (Chart 3.63b). Chart 3.60 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 281,740, 79% Mostly Compost, 3,591, 1% Mostly Inorganic Fertilizer, 43,402, 12% Mostly Farm Yard Manure, 29,470, 8% Chart 3.63b Proportion of Planted Area Applied with Farm Yard Manure by District - RUVUMA 0.0 5.0 10.0 15.0 20.0 Songea Urban Mbinga Songea Rural Namtumbo Tunduru District Percent Chart 3.62 Planted Area with Farm Yard Manure by Crop Type - RUVUMA Fruits & Vegetables, 4,055, 14% Cash Crop, 95, 0% Oilseeds, 288, 1% Pulses, 2,602, 9% Roots & Tubers, 3,269, 11% Cereals, 19,162, 65% 0 25 50 75 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.63a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals 0 50,000 100,000 150,000 Area (ha) Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Chart 3.61 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Mbinga Tunduru Namtumbo Songea Urban Songea Rural 10,036 2,164 4,963 2,625 6,857 13% 4.6% 17% 37.8% 22.3% Namtumbo Songea Urban Songea Rural 15,958 2,805 7,223 27,165 14,048 54.8% 23.5% 40.4% 35.1% 30% Mbinga Tunduru Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.41 RUVUMA Number of Crop Growing Households Using Improved Seed MAP 3.42 RUVUMA Number and Percent of Crop Growing Households Using Improved Seed by District Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services Percent of Crop Growing Households Using Improved Seed 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Households Crop Growing Using Improved Seed Tanzania Agriculture Sample Census RESULTS 48 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Songea Urban Songea Rural 8,774ha 44,231ha 73,755ha 49,669ha 60,879ha 80% 71% 57% 71% 72% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 4,806ha 45,875ha 98,519ha 55,265ha 77,275ha 44% 74% 76% 79% 91% Mbinga Namtumbo Tunduru Planted Area and Percent of Planted Area With No Application of Fertilizer by District MAP 3.37 RUVUMA Area Planted With Irrigation Application MAP 3.38 RUVUMA Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area With no Fertilizer Applied Planted Area With no Fertilizer Applied Percent of Planted Area With no Fertilizer Applied 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Area Planted With Irrigation Application Percent of Area Planted With Irrigation Application Tanzania Agriculture Sample Census RESULTS 49 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 For permanent crops, most farm yard manure is used for the production of coffee (89.5%), followed by banana (6.6%) and cashewnut (1.0%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Ruvuma region during wet season was 43,292 ha which represented 12.1 percent of the total planted area with annuals in the region and 56.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 23,638 and it was applied to 43,292 ha representing 12.1 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (79% of the total area applied with inorganic fertilizers), followed by cash crop (7%), pulses (5%), roots and tubers (5%), oil seeds (2%) and fruit and vegetables (2%) and (Chart 3.64). However, the proportion of cash crop with inorganic fertilizers was higher than other crop types (96%), followed by oil crops (75%), cereals (62%), Pulses (40%), roots and tubers (33%) and fruits and vegetables (15%) (Chart 3.65a). Inorganic fertiliser is mostly used in Songea Urban (35.3% of the total planted area in the district), followed by Namtumbo (17.7%), Songea Rural (15.0%), Mbinga (9.5%) and Tunduru (6.5%) Chart 3.65b). In permanent crops inorganic fertiliser were mostly used on passion fruits (90.6%), followed by pineapple (18.0%), coffee (17.8%), sugarcane (10.5%), mangoes (9.6%), coconut (3.0%), cashew (1.8%), pigeon peas (1.6%) and banana (1.4%). 3.5.4.3 Compost Use he total planted area applied with compost was 3,591 ha which represents only 1.0 percent of the total planted area with annual crops in the region and 5 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the wet season was 1,671 and it was applied to 3,591 ha representing 1.4 percent of the total area planted (Table 3.10 and Chart 3.66a). The proportion of area applied with compost was very low for each type of crop (0 to 14%); however the distribution of the total area using compost manure shows that 52.9 percent of this area was cultivated with cereals, followed Chart 3.65b Proportion of Planted Area Applied with Inorganic Fertiliser by District - RUVUMA 0.0 10.0 20.0 30.0 40.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent Chart 3.64 Planted Area with Inorganic Fertilizer by Crop Type - RUVUMA Pulses, 2,295, 5% Oilseeds, 1,041, 2% Fruits & Vegetables, 722, 2% Cash Crop, 3,126, 7% Roots & Tubers, 2,034, 5% Cereals, 34,074, 79% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.65a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - RUVUMA Chart 3.66a Planted Area with Compost by Crop Type - RUVUMA Cash Crop, 19, 1% Oilseeds, 62, 2% Fruits & Vegetables, 20, 1% Pulses, 774, 22% Roots & Tubers, 816, 22% Cereals, 1,900, 52% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 by roots & tubers (22.7%), pulses (21.5%), oil seed (1.7%), fruit and vegetables (0.6%) and cash crop (0.5%) (Chart 3.66b). Compost is mostly used in Songea Urban (1.5% of the total planted area in the district), and this is closely followed by Songea Rural (1.3%), Mbinga (1.2%), Tunduru (0.8%) and Namtumbo (0.6%) (Chart 3.66b). In permanent crops, compost was mostly used to banana (6.8%) followed by sugarcane (2.1%), coffee (1.2%), mango (0.6%) and cashewnut (0.1%). 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 102,510 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (77% of the total area applied with pesticides). This was followed by fungicides (17%) and herbicides (6%) (Chart 3.67). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 78,958 ha which represented 22.0 percent of the total planted area for annual crops and vegetables. 0 5 10 15 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.66b Percentage of Planted Area with Compost by Crop Type - RUVUMA Chart 3.66c Proportion of Planted Area Applied with Compost by District - RUVUMA 0.0 0.5 1.0 1.5 2.0 Songea Urban Songea Rural Mbinga Tunduru Namtumbo District Percent Chart 3.67 Planted Area (ha) by Pesticide Use Insecticide, 78,958, 77% Herbicide, 6,121, 6% Fungicide, 17,431, 17% Chart 3.68 Planted Area Applied with Insecticides by Crop Type Roots & Tubers, 3,844, 5% Cash crops, 2,451, 3% Oil seeds & Oil nuts, 1,168, 1% Pulses, 3,374, 4% Fruits & Vegetables, 4,665, 6% Cereals, 63,465, 81% 0.0 20.0 40.0 60.0 80.0 100.0 Percent of Planted Area Fruits & Vegetables Cereals Pulses Oil seeds & Oil nuts Cash crops Roots & Tubers Crop Type Chart 3.69 Percentage of Crop Type Planted Area Applied with Insecticides Songea Urban Songea Rural 159ha 829ha 1,561ha 394ha 649ha 1.5% 1.3% 1.2% 0.6% 0.8% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 2,098ha 5,952ha 17,981ha 2,277ha 1,163ha 19.2% 9.6% 13.8% 3.2% 1.4% Mbinga Namtumbo Tunduru 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area and Percent of Planted Manure Applied by District MAP 3.57 RUVUMA Planted Area (ha) MAP 3.58 RUVUMA Planted Area and Percent of Planted Area with Compost Application by District Planted Area (ha) Planted Area with Farm Yard Manure Applied Percent of Planted Area with Farm Yard Manure Applied 1,200 to 1,600 900 to 1,200 600 to 900 300 to 600 0 to 300 Tanzania Agriculture Sample Census Area Planted with Farm Yard Planted Area with Compost Manure Applied Percent of Planted Area with Compost Yard Manure Applied RESULTS 52 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 Cereals had the largest planted area applied with insecticides (63,465 ha, 81% of the total planted area with insecticides) followed by fruit and vegetables (4,665 ha, 6%), roots and tubers (3,844 ha, 5%), pulses (3,374 ha, 4%), cash crops (2,451 ha, 3%) and oil crops (1,168 ha, 1%)(Chart 3.68). However, the percent of insecticides used in fruits and vegetables is much greater than in other crop types (90.8%), while only 4.1 percent of roots and tubers crops were applied with insecticides (Chart 3.69). Annual Crops with more than 50 percent insecticide use were spinach (60.3%) and egg plant (55.0%). Songea Urban had the highest percent of planted area with insecticides (47.9% of the total planted area with annual crops in the district). This was followed Mbinga (33.3%) then Songea Rural (17.3%) and Namtumbo (15.8%). The smallest percentage use was recorded in Tunduru district (9.9%) (Chart 3.70). 5. 5.2 Herbicide Use The planted area applied with herbicides was 6,121 ha which represented 1.7 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (3,334 ha, 55%) followed by roots and tuber (1,336 ha, 22%), pulses (907 ha, 15%), oil crops (316 ha, 5%), fruits and vegetables (143 ha, 2%) and cash crops (84 ha, 1%) (Chart 3.71). However, the percent of herbicide use on fruit and vegetables and pulses was much greater than in other crop types (2.8% and 2.3% respectively) while only 1.4 percent of roots and tubers was applied with herbicides (Chart 3.72). The top six annual crops with highest percentage use of herbicides in terms of planted area were spinach (5.4%), tomatoes (4.3%), simsim (3.7%), sunflower (3.3%), beans (2.4%) and cabbages (2.0%). Tunduru had the highest percent of planted area with herbicides (2.7% of the total planted area with annual crops in the district). This was followed by Mbinga (2.5%) then Songea Urban (1.8%) and Namtumbo (0.4%). The smallest percentage use was recorded in Songea Rural district (0.3%) (Chart 3.73). Chart 3.70 Percent of Planted Area Applied with Insecticides by District - RUVUMA 0.0 20.0 40.0 60.0 Songea Urban Mbinga Songea Rural Namtumbo Tunduru District Percent Chart 3.71 Planted Area Applied with Herbicides by Crop Type Fruits and Vegetables, 143, 2% Cash crops, 84, 1% Oil Seeds & Nuts, 316, 5% Pulses, 907, 15% Roots and Tubers, 1,336, 22% Cereals, 3,334, 55% 0.0 1.0 2.0 3.0 Percent of Planted Area Cereals Roots and Tubers Pulses Oil Seeds & Nuts Fruits and Vegetables Cash crops Crop Type Chart 3.72 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.73 Proportion of Planted Area Applied with Herbicides by District - RUVUMA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Tunduru Mbinga Songea Urban Namtumbo Songea Rural District Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 3.5.5.3 Fungicide Use The planted area applied with fungicides was 17,431 ha which represented 4.9 percent of the total planted area for annual crops and vegetables. There was no fungicide use during the dry season. Cereals had the largest planted area applied with fungicides (9,263ha, 53%) followed by fruits and vegetables (3,251 ha, 18%), roots and tubers (2,502 ha, 14%), pulses (2,502 ha, 12%) and oil crops (488 ha, 3%). The lowest was cash crops (10 ha,0.1% )(Chart 3.74). However, the percentage use of fungicide in fruits and vegetables and pulses was much greater than in other crop types (34.2% and 2.8% respectively), while only 1.4 percent of roots and tubers was applied with fungicides (Chart 3.75). There was no more than 40 percent fungicide use in Ruvuma region. Mbinga had the highest percent of planted area with insecticides (5.3% of the total planted area with annual crops in the district). This was followed by Tunduru (3.5%) and Namtumbo (2.1%). The smallest percentage use was recorded in Songea Urban district (0.7%) (Chart 3.76). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.01%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 73 percent of the total area planted with cereals during the wet season being threshed by hand. Draft animals, engine driven machines and human powered tools were only used on crops harvested from 0.1 percent and 2.4 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. Chart 3.76 Proportion of Planted Area with Fungicides by District - RUVUMA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent Chart 3.74 Planted Area Applied with Fungicides by Crop Type Oil Seeds and Nuts, 488, 3% Pulses, 2,094, 12% Roots and Tubers, 2,502, 14% Fruits and Vegetables, 3,251, 18% Cash Crops, 10, 0% Cereals, 9,263, 53% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Percent of Planted A rea Cereals Roots and Tubers Pulses Oil Seeds and Nuts Fruits and Vegetables Cash Crops Crop Type Chart 3.75 Percentage of Crop Type Planted Area Applied with Fungicides RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 3.6.1 Area Planted with Annual Crops and Under Irrigation In Ruvuma region, the area of annual crops under irrigation was 9,104 ha representing 3 percent of the total area planted (Chart 3.77). The area under irrigation during the wet season was 15 ha accounting for 0.16 percent of the total area under irrigation. The district with the largest planted area under irrigation with annual crops was Mbinga (2,731 ha, 30% of the total irrigated planted area with annual crops in the region). This is followed by Namtumbo with (2,122 ha, 23%) and then Tunduru (2,025 ha, 22%). When expressed as a percentage of the total area planted in each district, Songea Urban had the highest with 10.8% of the planted area in the district under irrigation. This is followed by Namtumbo (3.0%), Tunduru (2.4%), Mbinga (2.1%) and Songea Rural (1.7%) (Chart 3.78 and Map 3.36). Of all the different crops and in terms of proportion of the irrigated planted area, egg plant was the most irrigated crop with 100 percent irrigation followed by carrot (99%), chillies (98%), cabbage (91%) and amaranths (77%). In terms of crop type, the area under irrigation with cereals was 3,880 ha (4% of the total area under irrigation), followed by fruit and vegetables (3,580 ha,4%) pulses (772 ha, 1%) and roots and tubers (171 ha, 0.05%. All of the irrigation on cereals was applied to maize, paddy, sorghum and finger millet. The area of fruit and vegetables under irrigation was 3,580 ha which represents 70 percent of the total planted area with fruit and vegetables. Tomatoes, cabbages and onions were the most irrigated crops. The number of households practicing irrigation in Ruvuma region appears to have increased over the 10 year intercensal period from 3,319 households in 1995/96 to 3,942 households in 2002/03. This may not be statically significant due to the small number of households sampled with irrigation. Chart 3.79 Time Series of Households with Irrigation - RUVUMA 3,319 3,942 0 1,000 2,000 3,000 4,000 5,000 1995/96 2002/03 Agriculture Year Planted Area under Irrigation Chart 3.77 Area of Irrigated Land Unirrigated Area, 349,099, 97% Irrigated Area, 9,104, 3% Chart 3.78 Planted Area with Irrigation by District-RUVUMA Region 0 600 1200 1800 2400 3000 Mbinga Namtumbo Tunduru Songea Urban Songea Rural District Irrigated Area (ha) 0 3 6 9 12 Percentage with Irrigation Irrigated Land (ha) Percentage of Irrigated Land RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was obtained from river (64% of households with irrigation). This was followed by canals (23%) and wells (7%). Only 0.3 percent of the households used water from boreholes and the percents of households that used dams, pipe water and lakes as a source of water for irrigation were (3%, 2% and 1% respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common method of getting water for irrigation with 57.2 percent of households using this method. This was closely followed by gravity with 41.3 percent of households. The remaining methods (motor pump and others) were of minor importance (Chart 3.81). Hand bucket was used by most households with irrigation in Mbinga (43.9%), followed by Tunduru (19.9%), Songea Rural (16.8%), Songea Urban (10.7%) and Namtumbo (8.7%). Gravity was more common in Namtumbo with 30.5 percent of households using the method to get water for irrigation, followed by Mbinga (26.9), Songea Rural (19.5%), Songea Urban (13.5%) and Tunduru (9.5%). 3.6.4 Methods of Water Application Most households used bucket/watering can irrigation (64% of households using irrigation) as a method of field application. This was followed by flood (30%) Sprinklers (5%) and water hose (1%). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Ruvuma region show that there were 181,775 crop growing households that stored various agricultural products in the region. Chart 3.80 Number of Households with Irrigation by Source of Water Lake, 234, 1% Borehole, 72, 0% Pipe water, 406, 2% Dam, 774, 3% Well, 1,646, 7% Canal, 5,744, 23% River, 15,798, 64% River Canal Well Dam Pipe water Lake Borehole Chart 3.82 Number of Households with Irrigation by Method of Field Application Sprinkler, 1,245, 5% Flood, 7,419, 30% Bucket / Watering Can, 15,691, 64% Water Hose, 205, 1% Bucket / Watering Can Flood Sprinkler Water Hose Chart 3.83 Number of Households and Quantity Stored by Crop Type - RUVUMA 0 40,000 80,000 120,000 160,000 200,000 Maize Beans & Pulses Paddy Sorghum & Millet Groundnuts/Bambara Nuts Seaweed Cashewnut Cloves Crop Number of households 0 10,000 20,000 30,000 40,000 Quantity (t) Number of Households Quantity Stored(Tons) Chart 3.81 Number of Households by Method of Obtaining Irrigation Water Gravity, 10,137, 41% Motor Pump, 250, 1% Other, 132, 1% Hand Bucket, 14,040, 57% Hand Bucket Gravity Motor Pump Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 The most important stored crop was maize with 172,771 households storing 34,081 tonnes as of 1st January 2004. This was followed by paddy (72,495 households, 3,273t), beans and other pulses (86,592 households, 2,599), sorghum and millet (27,879 households, 910t), groundnuts and bambara nuts (21,827 households, 469t) and seeweed (8,550 households, 461t). Other crops were stored in very small quantities. 3.7.1.1 Methods of Storage The region had 108,032 crop growing households storing their produce in sacks/open drum (60% of households that stored crops in the region). The number of households that stored their produce in locally made traditional structure was 66,102 (36%). This was followed by : improved locally made structures (3,702households, 2%) other ( 1,821 households, 1%) unprotected piles (1,490 households, 1%), , modern stores (381 households, recorded 0%), air tight drums (247 households, also recorded 0%). Sacks/open drum were the dominant storage method in all districts, with the highest percent of households in Mbinga using this method (86% of the total number of households storing crop products). This was followed by Songea Urban (67%), Songea Rural (60%), Namtumbo (36%) and Tunduru (30%) (Chart 3.85). The highest percent of households using locally made traditional structure were in Tunduru (66 % of households storing crops) and Namtubo (62%), followed by Songea Rural (36%), Songea Urban (31%) and Mbinga (8%). 3.7.1.2 Duration of Storage Most households (49% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored them for a period of over 6 months. The minority of households stored their crops for a period of less than 3 months (12%). Most households that stored pulses stored them for a period of 3 to 6 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.86). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mbinga district (58%) followed by Tunduru (52%), Namtumbo (39%), Songea Rural (37%) and Songea Urban (36%) (Map 3.37). Chart 3.84 Number of households by Storage Methods - RUVUMA Locally Made Traditional Crib, 66,102, 36% Improved Locally made Crib, 3,702, 2% Other, 1,821, 1% Airtight Drum, 247, 0% Unprotected Pile, 1,490, 1% Sacks/Open Drum, 108,032, 60% Modern Store, 381, 0% Chart 3.85 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 30,000 60,000 90,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.86 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.87). 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 92.4 percent followed by seed for planting. Practically all stored cash crops, were stored for selling at higher price. A high percent of the stored permanent crops was for selling at higher price, in case of cloves (100%) and seed for planting in case of cashewnuts (68.4%). In case of cashewnuts it was followed by selling at higher price (31.6%) (Chart 3.88). 3.7.1.4 The Magnitude of Storage Loss About 86 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for maize (3.1% of the total number of households that stored crops). This was followed by beans and pulses (2.4%), paddy (1.5%) and groundnuts and bambaranuts (1.0%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (88%) (Table 3.11). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and Crop Estimate Storage Loss Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Number of Households % Number of Households % Number of Households % Number of Households % Total Number of Households Maize 147,610 85.4 19,919 11.5 3,654 2.1 1,661 1.0 172,844 Paddy 66,700 91.6 5,056 6.9 1,067 1.5 0 0.0 72,823 Sorghum & Millet 26,626 95.3 1,069 3.8 255 0.9 0 0.0 27,950 Beans & Pulses 78,470 90.5 6,177 7.1 1,636 1.9 412 0.5 86,695 Seaweed 8,473 99.1 77 0.9 0 0.0 0 0.0 8,550 Cloves 128 100.0 0 0.0 0 0.0 0 0.0 128 Cashewnut 337 100.0 0 0.0 0 0.0 0 0.0 337 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 Coconut 0 0.0 0 0.0 0 0.0 0 0.0 0 Groundnuts/Bambara Nuts 19,457 88.8 2,234 10.2 209 1.0 0 0.0 21,900 Chart 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 40,000 80,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Quantity (tonnes) 0 4 8 12 16 20 24 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum/Millet Beans & Pulses Seaweed Cloves Cashewnut Coconut Gnuts/Bamb... Crop Type Chart 3.88 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Ruvuma region (188,975 households, 99% of the total crop growing households) (Chart 3.89a). The percent of households processing crops was very high in most districts (above 98%). Songea Urban had the lowest percent of households processing crops (98% of crop growing households) (Chart 3.89b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 66 percent (125,177 households). This was followed by those processing on-farm by hand (48,305 households, 26%), on-farm by machine (10,442 households, 6%) and by trader (4,328 households, 2%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Ruvuma region, district differences existed. Tunduru had a higher percent of hand processing than other districts (52%), followed by Mbinga (21%) and Namtumbo (14%). Processing by on farm by machine was more common in Mbinga and Namtumbo (10% and 4% respectively), whilst processing on farm by trader was more prevalent in Mbinga and Songea Rural (Chart 3.90). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. 0 20 40 60 80 100 Percent of Households Processing Songea Rural Namtumbo Tunduru Mbinga Songea Urban District Chart 3.89b Percentage of Households Processing Crops by District Chart 3.90 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.89a Households Processing Crops Households Processing, 188,975, 99% Households not Processing, 2,068, 1% Chart 3.91 Percent of Households by Type of Main Processed Product Grain 11% Oil 0.1% Juice 0.1% Other 0% Pulp 0.0% Flour / Meal 89% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 The main processed product was flour/meal with 168,023 households processing crops into flour (89%) followed by grain with 20,713 households (11%). The remaining products were produced and by a small numbers of households (Chart 3.91). The number of households producing by-products accounted for 91.8 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 152,339 households (88%) followed by Husks (20,484 households, 12%). The remaining by-products were produced by a small numbers of households (Chart 3.92). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most main use was household/human consumption which accounted for 99 percent of the total households that used primary processed product (Chart 3.93). Mbinga was the only district that used primary products as fuel for cooking. Out of 854 households that sold processed products, 386 were from Mbinga (45% of the total number of households selling processed products in the region), followed by Songea Rural with 231 households (27.0%), Tunduru with 210 households (24.6%) and Songea Urban with 27 households (3.1%) (Chart 3.94). Compared to other districts in Ruvuma region, Mbinga had the highest percent of households that sold processed products. This is followed by Songea Rural (0.76), Songea Urban (0.39%) and Tunduru (0.28%). 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to others (10,412 households, 56% of households that sold crops). This was followed by selling to neighbours (5,114 households, 27%), trader at farm (1,263 households, 7%), local market and trade stores (907 households, 5% of households that sold crops), marketing co-operatives (465 households, 2%), large scale farm (365 households, 2%) and Farmers Associations (105 households, 1%) (Chart 3.95). Chart 3.92 Number of Households by Type of By-product Cake, 212, 0% Shell, 213, 0% Juice, 212, 0% Pulp, 0, 0% Other, 0, 0% Husk, 20,484, 12% Bran, 152,339, 88% Chart 3.93 Use of Processed Product Fuel for Cooking, 521, 0% Other, 575, 0% Did Not Use, 517, 0% Animal Consumption, 587, 0% Sale Only, 3,919, 1% Household / Human Consumption, 412,092, 99% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of households Mbinga Songea Rural Tunduru Songea Urban Namtumbo District Chart 3.94 Percentage of Households Selling Processed Crops by District Chart 3.95 Location of Sale of Processed Products Neighbours, 5,114, 27% Local Market / Trade Store, 907, 5% Marketing Co-operative, 465, 2% Other, 10,412, 56% Trader at Farm, 1,263, 7% Large Scale Farm, 365, 2% Farmers Association, 105, 1% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 There are large differences between districts in the proportion of households selling processed products to neighbours with Songea Urban district having the largest percent of households in the district selling to neighbours (62%), whereas Namtumbo had only 9 percent. Songea Urban had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Songea Rural had the highest percent of households selling processed products to traders at farm. In Tunduru, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Namtumbo and Tunduru. 3.7.3 Crop Marketing The number of households that reported selling crops was 176,924 which represent 92.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Tunduru (96%) followed by Namtumbo (94%), Mbinga (91%), Songea Rural (91%) and Songea Urban (82%) (Chart 3.97 and Map 3.38). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (84% of crop growing households). Apart from low market prices, other problems were high transport costs (6%), longer distances to the markets (5%), lack of transport (1%), lack of market information (1%) and lack of buyers (1%) and. Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 89 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts except for Songea Rural and Tunduru where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (2.4% and 1.9% respectively). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 26,823 88.5 Price Too Low 1,156 3.8 Trade Union Problems 942 3.1 Market Too Far 518 1.7 Co-operative Problems 498 1.6 Other 303 1.0 Farmers Association Problems 72 0.2 Total 30,314 100.0 Chart 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.97 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Mbinga Tunduru Songea Rural Namtumbo Songea Urban District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.98 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Lack of Market Information 1% Market too Far 5% Transport Cost Too High 6% No Buyer 1% No Transport 2% Other 0% Open Market Price Too Low 84% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Ruvuma region a considerable number of agricultural households (38,567, 18.6%) accessed credit out of which 32,939 (85%) were male-headed households and 5,628 (15%) were female headed households. In all districts both male and female headed households accessed agricultural credit (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Ruvuma region were family, friends and relatives which collectively provided credit to 15,355 agricultural households (39% of the total number of households that accessed credit), followed by co- operative (39%), trader/trade store (7%), saving and credit society (6%), religious organizations/non governmental organizations/ projects (5% ), private individual (2%), commercial bank (1%) and other sources (1%) (Chart 3.99). Commercial banks provided credit to very few households in Songea Rural and Mbinga. Savings and credit societies provided credits in all districts except Namtumbo. Trader/trader store privided credits to a small numbe of households in Tunduru, Songea Rural and Namtumbo districts. Religious organization, cooperative provided credit in all districts while private individuals provided credit mainly in Songea Rural district. NGOs and projects funded a relatively large number of households in Songea Rural disrtict (Chart 3.100). 3.8.1.2 Use of Agricultural Credit Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Tunduru 2,992 93 212 7 3,204 Songea Rural 4,149 70 1,813 30 5,962 Mbinga 12,568 91 1,302 9 13,870 Songea Urban 566 78 161 22 727 Namtumbo 12,664 86 2,140 14 14,804 Total 32,939 85 5,628 15 38,567 Chart 3.99 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 1% Other 1% Private Individual 2% Family, Friend and Relative 39% Co-operative 39% Trader / Trade Store 7% Saving & Credit Society 6% Religious Organisation / NGO / Project 5% Chart 3.101 Proportion of Households Receiving Credit by Main Purpose of the Credit Other 8% Seeds 7% Fertilizers 43% Labour 16% Livestock 4% Irrigation Structures 0% Tools / Equipment 5% Agro-chemicals 17% Chart 3.102 Reasons for not Using Credit (% of Households) Credit granted too late, 797, 1% Don't know about credit, 24,187, 16% Other, 506, 0% Difficult bureaucracy procedure, 5,694, 4% Did not know how to get credit, 47,344, 31% Interest rate/cost too high, 8,916, 6% Did not want to go into debt, 16,752, 11% Not available, 43,069, 28% Not needed, 5,238, 3% Chart 3.100 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader/Trade Store Private Individual Religious Organisation/NGO/Project Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 A large proportion of the agricultural credit provided to agricultural households in the region was used on fertilizers (43%), followed by agro-chemicals (17%) and hiring labour (16%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment, seeds and unspecified was very low (Chart 3.101). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 31 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (28%), “not wanting to go into debt” (11%) and interest too high (6%). The rest of the reasons were given by 8 percent of the households. Chart 3.104 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Number of Househo 0 20 40 60 Percent of Househol Households Receiving Extension Percentage of Households Receiving Extension Chart 3.103 Number of Households Receiving Extension Advice Households Receiving Extension , 67,199, 35% Households Not Receiving Extension , 123,844, 65% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 67,199 (35% of total crop growing households in the region) (Chart 3.103). Some districts had more access to extension services than others, with Namtumbo having a relatively high proportion of households (55%) that received crop extension messages followed by Songea Urban (40%), Mbinga (35%), Tunduru(30%) and Songea Rural (23%) (Chart 3.104 and Map 3.39). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (89.1%, 59,075 households). Large scale farms 3.8 percent and cooperative 2.9 pecent and the remaining sources provided 4.2 percent (Chart 3.105), however district differences did exist with the proportion of the households receiving advice from government services ranging from 83.3 percent in Mbinga to 93.6 percent in Tunduru. 3.8.2.2 Quality of Extension On the quality of extension, 69percent of the households receiving extension ranked the service as being good followed by average (18 %), very good (11%), poor (1%) and no good (1%) (Chart 3.106). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Ruvuma Region regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households used inputs and this was particularly true for inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertilisers and herbicides. In Ruvuma region inorganic fertiliser were used by 91,930 households which Table 2.14 Access to Inputs Households With Access to Inputs Households Without Access to Inputs Type of Input Number % Number % Farm yard manure 61,064 31.9 129,979 68.0 Improved seeds 26,646 13.9 164,397 86.1 Insecticides/Fungicide 65,929 34.5 125,114 65.5 Compost 6,305 3.3 184,738 96.7 Inorganic fertilizers 91,930 48.1 99,113 51.9 Herbicide 2,011 1.1 189,032 98.9 Chart 3.105 Number of Households Receiving Extension Messages by Type of Extension Provider Government 89.1% Other 1.5% NGO / Development Project 2.7% Cooperative 2.9% Large Scale Farm 3.8% Chart 3.106 Number of Households Receiving Extension by Quality of Services Very Good, 7,192, 10.8% No Good, 668, 1.0% Poor, 1,068, 1.6% Average, 11,967, 17.9% Good, 45,969, 68.8% Chart 3.107 Number of Households by Source of Inorganic Fertiliser 0.1 0.2 0.2 0.6 0.8 1.9 2.3 16.9 77.0 0 20,000 40,000 60,000 80,000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Crop Buyers Secondary Market Other Locally Produced by Household Large Scale Farm Source of Inorganic Fertiliser Number of Households Songea Urban Songea Rural 5,717 28,109 70,589 27,456 45,053 82.3% 91.3% 91.1% 94.3% 96.1% Mbinga Namtumbo Tunduru Songea Rural Namtumbo Songea Urban 37% 39% 36% 58% 52% Mbinga Tunduru Percent of Households Storing Crops for 3 to 6 Months by District MAP 3.39 RUVUMA Number of Households Selling Crops MAP 3.40 RUVUMA Number of Households and Percent of Total Households Selling Crops by District Percent of Households Storing Crops for 3 to 6 Months Percent of Households Storing Crops for 3 to 6 Months Number of Households Selling Crops Percent of Total Households Selling Crops 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census RESULTS 65 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 represents 48.1 percent of the total number of crop growing households. This was followed by households using fungicides (34.5%), farm yard manure (31.9%), improved seeds (13.9%), compost (3.3%) and herbicide (1.1%) (Table 2.14). 3.9.2 Inorganic Fertilisers Smallholders that used inorganic fertilisers in Ruvuma, mostly purchased them from the local market/trade store (77.0% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.107). Access to inorganic fertiliser was mainly above 3 km from the household with most households residing above 20 km from the source (28%), followed by less than 1 km (24%) and between 10 and 20 km (20%) (Chart 3.108). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (6% ) as the reason for not using, it may be assumed that access to inorganic fertiliser was not the main reason for not using them. Other reasons such as cost were more important. In other words, if the cost was affordable the demand would be higher and inorganic fertiliser would be made more available. More smallholders used inorganic fertilisers in Songea Rural than in other districts in Ruvuma region (28% of households using inorganic fertilisers), followed by Namtumbo (26%), Mbinga (23%), Tunduru (16%) and Songea Urban (7.1%). 3.9.3 Improved Seeds The percent of households that use improved seeds was 14 percent of the total number of crop growing households. Most of the improved seeds were obtained from the local market/trade store (78.8%). Other less important sources of improved seeds were cooperative (9.6%), neighbours (7.6%) and local farmers group (0.9%). Only 0.9 percent of households using improved seed obtained them from crop buyers (Chart 3.109). Access to improved seeds was poorer than access to chemical inputs with 31 percent of households obtaining from 20 km and above from the household (Chart 3.110). This is in line with the higher use of chemical inputs compared to other improved seed, which further supports the contention that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. Chart 3.108 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.109 Number of Households by Source of Improved Seed 78.8 9.6 7.6 0.9 0.9 0.8 0.4 0.6 0.1 0.4 0 10,000 20,000 30,000 Local Market / Trade Store Co-operative Neighbour Local Farmers Group Crop Buyers Development Project Other Secondary Market Large Scale Farm Locally Produced by Household Source of Improved Seed Number of Households Chart 3.110 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 The districts that used improved seeds most was Mbinga (37.7 percent of the total number of households using improved seeds in Ruvuma region), followed by Songea Rural (25.7%) and Namtumbo (18.6%). Use of improved seeds in other districts is of minor importance (Map 3.40). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (49.6% of the total number of fungicide users). This was followed by cooperative (25.7%), local farmers group (16.1%), neighbour (4.6%) and crop buyers (3.1%). Other sources of insecticides/ fungicides are of minor importance (Chart 3.111). Chart 3.112 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. From the small number of households using insecticides/fungicides, coupled with the 34 percent of households responding to “not available” as the reason for not using it may be assumed that access was not the main reason for not using Them. Other reasons such as cost were more important with 74 percent of households responding to cost factors as the main reason for not using them. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were used more in Mbinga district (57.9 percent of the total number of households that use fungicide in the region), followed by Tunduru (29.2%). Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 43,315 representing 23 percent of the total number of agriculture households (Chart 3.113 and Map 3.41). Chart 3.111 Number of Households by Source of Insecticide/fungicide 0.2 0.2 0.5 3.1 4.6 16.1 25.7 49.6 0 6,000 12,000 18,000 24,000 30,000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Crop Buyers Locally Produced by Household Other Development Project Source of Insecticide/Fungicide Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.113 Number of Households with Planted Trees hh growing trees, 43,336, 23% Not growing trees, 147,839, 77% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 The number of trees planted by smallholders on their allotted land was 10,594,983 trees. The average number of trees planted per household planting trees was 245 trees. The main specie planted by smallholders is eucalyptus spp (7,638,602 trees, 72.1%), followed by Cyprus spp (1,298,088 trees, 12.3%) and gravellis (714,902 trees, 6.7%), senna (243,200 trees, 2.3%), pinnus (224,651 trees, 2.1%), acacia (210,757 trees, 2.0%) and calophylum inophylum (173,727 trees, 1.6%). The remaining trees species are planted in comparatively small numbers (Chart114.). Mbinga has the largest number of smallholders with planted trees than any other district (92.5%) and is dominated by eucalyptus species. This is followed by Songea Urban (3.2%) which is dominated by eucalyptus. Then Songea Rural (3.0%) which is mainly planted with calophylum inophylum species and Namtumbo (1.2%) which is planted with senna species (Chart 3.115). Most trees were planted on plantations or coppice. The proportion of trees that were planted on plantations was 69 percent, followed trees scattered around fields (17%) and then trees planted on the boundaries (14%) (Chart 3.116). The main purpose of planting trees was to obtain planks/timber (37.2%). This is followed by shade (29.5%), wood for fuel (24.5%) and poles (7.6%) (Chart 3.117). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and Chart 3.118 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 178,772, 94% Households with facilities, 12,403, 6% Chart 3.116 Number of Trees Planted by Location Field boundary, 1,436,584, 14% Scattered in field, 1,758,712, 17% Plantation, 7,399,687, 69% Chart 3.117 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 P lanks / Timber Shade Wo o d fo r Fuel P o les Medicinal Other Charco al Use Percent of Households Chart 3.114 Number of Planted Trees by Species - RUVUMA 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 8,000,000 Eucalyptus Spp Cyprus Spp Gravellis Senna Spp Pinus Spp Acacia Spp Calophylum Inophyllum Albizia Spp Kyaya Spp Jakaranda Spp Melicia excelsa Others Tree Species Number of Trees Chart 3.115 Number of Trees Planted by Smallholders by Species and Region 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 Songea Rural Mbinga Songea Urban Namtumbo Thousands Region Number of Trees Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Senna Spp P inus Spp Albizia Spp Calo phylum Ino phyllum J akaranda Spp Kyaya Spp Melicia excels a Others RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 water harvesting facilities on their farms was 12,403 which represent 6 percent of the total number of agricultural households in the region (Chart 3.118). The proportion of households with soil erosion control and water harvesting facilities was highest in Mbinga district (12%) followed by Songea Urban (11%), Songea Rural (3%), Namtumbo (1%) and Tunduru (1%) (Chart 3.119 and Map 3.42). Terraces accounted for 42.6 percent of the total number of structures, followed by erosion control bunds (28.8%), water harvesting bunds (18.7%), tree belts (3.7%), drainage ditches (3.7%), vetiver grass (2.0%), dams (0.3%) and gabions/sandsbags (0.1%) (Chart 3.120). Erosion control by terraces, erosion control bunds and water harvesting bunds together had 179,029 structures. This represented 90 percent of the total structures in the region. The remaining 10 percent was shared among the rest of the erosion control methods mentioned above. Mbinga and Songea Rural districts had 10,617 erosion control structures (86 percent of the total erosion structures in the region). Chart 3.120 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.1 0.3 2.0 3.7 3.7 18.7 28.8 42.6 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Terraces Erosion Control Bunds Water Harvesting Bunds Tree Belts Drainage Ditches Vetiver Grass Dam Gabions / Sandbag T y p e o f F a c ilit y Number of Structures Chart 3.119 Number of Households with Erosion Control/Water Harvesting Facilities 12 3 11 1 1 0 2,000 4,000 6,000 8,000 10,000 12,000 Mbinga Songea Rural Songea Urban Tunduru Namtumbo District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Songea Urban Songea Rural Tunduru 1,840 2,868 215 0 32,259 21.9% 56.8% 12% 0% 17.8% Mbinga Namtumbo Songea Rural Songea Urban 8,048 3,572 28,452 3,243 0 26.2% 51.4% 36.7% 11.1% 0% Mbinga Namtumbo Tunduru Number and Percent of Smallholder Planted Trees by District MAP 3.43 RUVUMA Number of Households With Water Harvesting Bunds MAP 3.44 RUVUMA Number and Percent of Households With Water Harvesting Bunds by District Number and Percent of Smallholder Planted Trees Number of Smallholder Planted Trees Percent of Smallholder Planted Trees Percent of Households With Water Harvesting Bunds Number and Percent of Households With Water Harvesting Bunds 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census RESULTS 70 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 121,175. Cattle were the dominant livestock type in the region followed by goats, pigs and sheep. The region had 0.7 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Ruvuma region was 105,884 (87.4 % of the total number of cattle in the region), 15,111 cattle (12.5%) were dairy breeds and 181 cattle (0.1%) were beef breeds. The census results show that 16,887 agricultural households in the region (8.8% of total agricultural households) kept 0.1 million cattle. This was equivalent to an average of 7 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Mbinga which had about 100,907 (83.3% of the total cattle in the region). This was followed by Songea Rural (11,164 cattle, 9.2%), Tunduru (4,040 cattle, 3.3%) and Namtumbo (2,815 cattle, 2.3%). Songea Urban district had the least number of cattle (2,250 cattle, 1.9%) (Chart 3.121 and Map 3.43). However Mbinga district had the highest density (23 head per km2 ) (Map 3.44). Although Mbinga district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and there were no beef cattle. However, Mbinga district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.122). 3.12.1.2 Herd Size Ninety percent of the cattle-rearing households had herds of size 1-5 cattle with an average of two cattle per household. Herd sizes of 6-30 accounted for about 13 percent of all cattle in the region. Only 1 percent of the cattle rearing households had herd sizes of 31- 151 and above cattle. About 98.8 percent of total cattle rearing households had herds of size 1-30 cattle and owns 43 percent of total cattle in the region, resulting in an average of 3 cattle per cattle rearing household. There were about 129 households with a herd size of more than 151 cattle each (66,366 cattle in total) resulting in an average of 513 cattle per household. 0 20 40 60 80 100 120 Number of Cattle ('000') Mbinga Songea Rural Tunduru Namtumbo Songea Urban Districts Chart 3.121 Total Number of Cattle ('000') by District Chart 3.122 Number of Cattle by Type and District 0 40,000 80,000 120,000 Mbinga Songea Rural Tunduru Songea Urban Namtumbo Districts Number of Cattle Indigenous Beef Dairy RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.12.1.3 CattlePopulation Trend Cattle population in Ruvuma increased during the eight-year period from 75,027 in 1995 to 121,175 cattle in 2003. This implies an overall positive average annual growth rate of 6.2 percent (Chart 3.123). There was a small increase in number of cattle during the five-year period from 1995 to 1999 at the rate of 1.6 percent whereby the number increased from 75,027 to 79,969. Moreover, the number of cattle is estimated to have increased from 79,969 in 1999 to 121,175 in 2003at the rate of 10.9 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Ruvuma region was 15,292 (15,111 dairy and 181 improved beef). The diary cattle constituted 12.5 percent of the total cattle and 99 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 1 percent of the total number of the improved cattle and 0.2 percent of the total cattle. The number of improved cattle increased from 1,325 in 1995 to 15,111 in 2003 at an average annual growth rate of 35.6 percent. The growth rate was lower from 1995 to 1999 (35.6%) than from 1999 to 2003 (41.8%) (Chart 124). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by pig and sheep rearing. In terms of total number of goats on the Mainland, Ruvuma region ranked 15 out of the 21 regions with 2.6 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Ruvuma region was 68,381 (36% of all agricultural households in the region) with a total of 309,595 goats giving an average of 5 head of goats per goat- rearing-household. Mbinga had the largest number of goats (122,564 goats, 40% of all goats in the region), followed by Namtumbo (72,649 goats, 23%) and Songea Rural (60,790 goats, 20%). Tunduru and Songea Urban districts had the 75,027 79,969 121,175 - 40,000 80,000 120,000 160,000 Number of cattle 1995 1999 2003 Year Chart 3.123 Cattle Population Trend 1,325 3,738 15,111 - 10,000 20,000 Number of cattle 1995 1999 2003 Year Chart 3.124 Dairy Cattle Population Trend 0 40 80 120 160 Number of Goats ('000') Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Chart 3.125 Total Number of Goats ('000') by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 least number of goats (43,548 goats, 14% and 10,044 goats, 3% respectively) (Chart 3.125 and Map 3.45). However Songea Urban district had the highest density (62 head per km2 ) (Map 3.46) 3.12.2.2 Goat Herd Size Sixty two percent of the goat-rearing households had herd sizes of 1-4 goats with an average of 2 goats per goat rearing household. Ninety seven percent of total goat-rearing households had herd sizes of 1-14 goats and owned 97 percent of the total goats in the region resulting in an average of 4 goats per goat-rearing households. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98 percent of the total goats in Ruvuma region. Both improved goats for meat and diary goats constituted 1 percent each of total goats in the region. 3.12.2.4 Goat Population Trend The overall average annual growth rate of goat population from 1995 to 2003 was -1.5 percent. This negative trend implies eight years of population decrease from 348,509 in 1995 to 309,595 in 2003. The number of goats increased from 348,509 in 1995 at an estimated annual rate of 11.5 percent to 537,843 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -12.9percent (Chart 126). 3.12.3. Sheep Production Sheep rearing was the fourth important livestock keeping activity in Ruvuma region after cattle goats and pigs. The region ranked 18 out of 21 Mainland regions and had 1 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 7,390 (4% of all agricultural households in Ruvuma region) rearing 24,458 sheep, giving an average of 3 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Mbinga with 13,073 sheep (53%of total sheep in Ruvuma region) followed by Tunduru (5,671 sheep, 23%), Songea Rural (4,070 sheep, 17%) and Namtumbo (1,371, 6%). Songea Urban District had the least number of sheep (275 sheep, 1%) (Chart 3.127and Map 3.47). Mbinga district also had the highest density (3 head per km2 ) (Map 3.48). Sheep rearing was dominated by indigenous breeds that constituted 96 percent of all sheep kept in the region. Only 4 percent of the total sheep in the region were improved breeds. 348,509 537,843 309,595 - 200,000 400,000 600,000 Number of goats 1995 1999 2003 Year Chart 3.126 Goat Population Trend 0 5,000 10,000 15,000 Number of sheep Mbinga Tunduru Songea Rural Namtumbo Songea Urban District Chart 3.127 Total Number of Sheep by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight-year period from 1995 to 2003 was estimated at -6.5 percent. The population increased at an annual rate of 4.4 percent from 41,890 in 1995 to 49,801 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -16.3 percent (Chart 3.128). 3.12.4. Pig Production Piggery was the third most important livestock keeping activity in the region after cattle and goats. The region ranks 5 out of 21 Mainland regions and had 14.0 percent of the total pigs on Tanzania. The number of pig-rearing agricultural households in Ruvuma region was 54,852(29% of the total agricultural households in the region) rearing 134,951 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Mbinga with 102,373 pigs (76% of the total pig population in the region) followed by Songea Rural (20,763 pigs, 15%), Namtumbo (6,909 pigs, 5%) , Songea Urban (3,308 pigs, 2%) and Tunduru (1,598 pigs, 1%) (Chart 3.129 and Map 3.49). Mbinga district had the highest density (23 head per km2 ) (Map 3.50). 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 5.3 percent. During this period the population grew from 89,600 to 134,951. The pig population increased from 89,600 in 1995 to 182,347 in 1999 at the rate of 19.4 percent. The growth rate dropped to -7.2 percent during the following four years from 1999 to 2003 in which pig population decreased from 182,347 to 134,951 (Chart 3.130). 41,890 49,801 24,458 - 20,000 40,000 60,000 Number of sheep 1995 1999 2003 Year Chart 3.128 Sheep Population Trend 0 40,000 80,000 120,000 Number of Pigs Mbinga Songea Rural Namtumbo Songea Urban Tunduru District Chart 3.129 Total Number of Pigs by District 89,600 182,347 134,951 - 40,000 80,000 120,000 Number of pigs 1995 1999 2003 Year Chart 3.130 Pig Population Trend RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 75 3.12.5 Chicken Production The poultry sector in Ruvuma region was dominated by chicken production. The region contributed 4.7 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 139,284 raising about 1,555,617 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Ruvuma region was ranked eighth out of the 11 Mainland regions. The District with largest number of chickens was Mbinga (647,834 chickens, 42% of the total number of chickens in the region) followed by Namtumbo (304,763, 20%), Songea Rural (279,909, 18%) and Tunduru (257,329, 17%). Songea Urban district had the smallest number of chickens (65,782, 4%) (Chart 3.133 and Map 3.51). However Songea Urban district had the highest density (422 head per km2 ) (Map 3.52). 3.12.5.2 Chicken Population Trend The overall annual population growth rate for chicken during the eight-year period from 1995 to 2003 was 4.5 percent. The population increased at a rate of 13.3 percent from 1995 to 1999 after which it decreased at -3.6 percent for the four-year period from 1999 to 2003 (Chart 3.132). Ninety nine percent of all chicken in Ruvuma region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 85 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 15 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 41 chickens per holder (Table 3.15). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 36,278 26 96,787 3 5 - 9 40,716 29 268,983 7 10 - 19 41,041 29 546,003 13 20 - 29 12,834 9 287,289 22 30 - 39 4,822 3 156,927 33 40 - 49 1,490 1 66,756 45 50 - 99 2,103 2 132,872 63 Total 139,284 100 1,555,617 11 1,092,234 1,799,158 1,555,617 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.132 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Number of Chickens Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Chart 3.131 Total Number of Chickens by District Songea Urban Songea Rural Mbinga Namtumbo 14.4 2 22.8 0.3 0.6 Tunduru 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Songea Urban Tunduru Namtumbo Songea Rural 2,250 100,907 4,040 2,815 11,164 Mbinga Cattle population as of 1st Octobers 2003 by District MAP 3.45 RUVUMA Number of Cattle per Square Km MAP 3.46 RUVUMA Cattle Density as of 1st October 2003 by District Number of Cattle 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 Number of Population Cattle Density Tanzania Agriculture Sample Census RESULTS 76 Songea Urban Songea Rural 64.4 11 27.7 8.5 6.2 Mbinga Namtumbo Tunduru Songea Urban Songea Rural 10,044 60,790 122,564 72,649 43,548 Mbinga Namtumbo Tunduru Goat population as of 1st Octobers 2003 by District MAP 3.47 RUVUMA Number of mGoat per Square Km MAP 3.48 RUVUMA Goat Density as of 1st October 2003 by District Goat Population 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 60 to 75 45 to 60 30 to 45 15 to 30 0 to 15 Goat Density Goat Population Tanzania Agriculture Sample Census RESULTS 77 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Ruvuma region increased at an annual rate of 15.3 percent for the four-year period from 11,709 in 1999 to 6,037 in 2003. The number of improved chicken was most significant in Songea Urban district followed by Songea Rural district (Chart 3.133). The overall average annual growth rate for broilers during the eight-year period from 1995 to 2003 was 38.6 percent during which the population grew from 974 to 13,250. The annual growth rate was higher (135.7%) for the first four-year (1995 to 1999). The broiler population exhibited a decreasing trend at the rate of -18.5 percent per annum for the period of four years resulting at increase from 30,064 in 1999 to 13,250 in 2003 (Chart 3.134). 3.12.6. Other Livestock There were 42,163 rabbits, 868 turkeys, 38,878 ducks and 4,600 donkeys raised by rural agricultural households in Ruvuma region. Table 3-32 indicates the number of livestock kept in each district. The biggest number of rabbits in the region was found in Mbinga district (74% of all rabbits in the region), followed by Namtumbo (11%), Songea Rural (7%) and Songea Urban (6%). Tunduru district had the least number of rabbits estimated at 2 percent of total rabbits in the region. Ducks were reported mainly in Tunduru and Mbinga districts (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 32 percent and 15 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.135 shows that there was a predominance of tick related diseases over tsetse related diseases. While tick incidences were highest in Mbinga and lowest in Tunduru, tsetse incidences were highest in Tunduru and lowest in Songea Urban.(Chart 3.135 and Map 3.53). Table 3.16 Number of Other Livestock by Type of Livestock and District Types of Livestock District Rabbits Turkeys Ducks Donkeys Other Tunduru 984 0 15,865 984 14,460 Songea Rural 2,963 689 3,422 0 0 Mbinga 31,130 124 10,426 3,616 1,580 Songea Urban 2,472 55 2,970 0 408 Namtumbo 4,614 0 6,195 0 576 Total 42,163 868 38,878 4,600 17,025 0 640 0 5,318 2,749 646 2,499 2,884 788 3,762 0 1,000 2,000 3,000 4,000 5,000 6,000 Number of Chickens Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.133 Number of Improved Chicken by Type and District Layer Broiler - 974 11,709 30,064 6,037 13,250 - 10,000 20,000 30,000 40,000 Number of layers 1995 1999 2003 Year Chart 3.134 Layers Population Trend Layers Broilers Chart 3.135 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 10 20 30 40 Mbinga Songea Rural Namtumbo Songea Urban Tunduru District Percent Ticks Tsetseflies RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 79 The most practiced method of tick controlling was spraying with 43 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (7%), smearing (2%) and other traditional methods like hand picking (19%). However, 29 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 31 percent of livestock-rearing households This was followed by dipping (2%) and trapping (1%). However,66 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 21,145 (43% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 65 percent, goats (7%), sheep (29%) and pigs (23%) (Chart 3.136). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 30,585 representing 62 percent of the total livestock-rearing households and 16.0 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 79.4 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (9.5%), large-scale farmers (5.1%) and cooperatives (3.7%). About 66 percent of livestock rearing households described the general quality of livestock extension services as being good, 16 percent said they were very good and 14 percent said they were average. However, 3 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.137). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 68 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 32 percent of them accessed the services within 0 20 40 60 Percent Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.136 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.137 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good 66% Very Good 16% Poor 1% No good 3% Average 14% Chart 3.138 Number of Households by Distance to Verinary Clinic More than 14 km, 26,298, 68% Less than 14 km, 12,466, 32% Chart 3.139 Number of Households by Distance to Verterinary Clinic and District 0 5,000 10,000 15,000 Tunduru Namtumbo Songea Rural Mbinga Songea District Number of Households Less than 14 kms More than 14 kms Mbinga Songea Rural Songea Urban Namtumbo Tunduru 3 0.7 1.8 0.8 0.2 Songea Urban Songea Rural 275 13,073 4,070 1,371 5,671 Mbinga Namtumbo Tunduru Sheep population as of 1st Octobers 2003 by District MAP 3.49 RUVUMA Sheep Density MAP 3.50 RUVUMA Sheep Density as of 1st October 2003 by District Number of Sheep 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 3.2 to 4 2.4 to 3.2 1.6 to 2.4 0.8 to 1.6 0 to 0.8 Number of Sheep pe Square Km Sheep Population Tanzania Agriculture Sample Census RESULTS 80 Songea Urban Mbinga Namtumbo Songea Rural 21.2 23.1 0.2 0.8 3.7 Tunduru 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Songea Urban Tunduru Namtumbo Songea Rural 3,308 20,763 1,598 6,909 102,373 Mbinga Pig population as of 1st Octobers 2003 by District MAP 3.51 RUVUMA MAP 3.52 RUVUMA Pig Density as of 1st October 2003 by District Number of Pig 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Pig Density Number of Pig per Square Km Pig Population Tanzania Agriculture Sample Census RESULTS 81 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 14 kms from their dwellings (Chart 3.138). The most affected district was Songea Urban district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Mbinga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.139). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 10,626 (93% of livestock rearing households in Ruvuma region) whilst 584 households (5%) resided between 5 and 29 kms. However, 201 households (2%) had to travel a distance of 30 or more kms to f the nearest watering point (Chart 3.140). Tunduru district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Mbinga, Songea Rural and Songea Urban districts. In Namtumbo district about 43 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.141). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Ruvuma region was very limited with only 172 households (0.09% of the total households in the region) using them (Chart 3.142). The large number of households that used draft animals were in Songea Rural ( 76 households, 44%), followed by Namtumbo (69 households,40%) and Songea Urban (27 households, 16%). whilst in Kilindi only 49 households (11%) used draft animals. Use of draft animals was not reported in the other districts (Chart 3.143 and Map 3.54). 3.142 Number of Households Using Draft Amimals Not Using Draft Animals, 191,003, 99.9% Using Draft Animals, 172, 0.1% 0 20 40 60 80 Number of Household Songea Rural Namtumbo Songea Urban Tunduru Mbinga District Chart 3.143 Number of Households Using Draft Animals by District - RUVUMA Chart 3.140 Number of Households by Distance to Village Watering Points 30 or more kms, 201, 2% 5-29 kms, 584, 5% Less than 5 kms, 10,626, 93% Chart 3.141 Number of Households by Distance to Village Watering Point and District 0 1,000 2,000 3,000 4,000 5,000 Tunduru Mbinga Songea Rural Songea Urban Namtumbo District Number of Households Less than 5 kms 5-29 kms 30 or more kms Mbinga Namtumbo Songea Rural Songea Urban 146.4 36.6 35.8 50.5 422.1 Tunduru Tunduru Namtumbo Songea Urban Songea Rural 257,329 304,763 65,782 279,909 647,834 Mbinga Chicken Density Number of Chicken by District as of 1st October 2003 MAP 3.53 RUVUMA MAP 3.54 RUVUMA Density of Chicken by District as of 1st October 2003 Number of Chicken per Square Km Tanzania Agriculture Sample Census Number of Chicken Chicken Population 600,000 to 750,000 450,000 to 600,000 300,000 to 450,000 150,000 to 300,000 0 to 150,000 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 RESULTS 83 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 The region had 55 oxen. Only Songea Urban had 55 oxen which were used to cultivate 33 hectares of land. This represented only 0.001 percent of the total oxen found on the Mainland. 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Ruvuma region was 54,534 (29% of total crop growing households in the region) (Chart 3.144). The total area applied with with farm yard manure was 22,227 hectares (95% of the total area applied with organic fertiliser and 6.2% of the area planted with annual crops and vegetables in Ruvuma region in the wet season). The largest area applied with farm yard manure was found in Mbinga district with 17,255 hectares (78% of the total area applied with farm yard manure) followed by Songea Rural (1,842 ha, 8%), Tunduru (1,439 ha, 6%), Namtumbo (1,108 ha, 5%) and Songea Urban (585 ha, 3%) (Chart 3.145and Map 3.55). 3.12.9.4 Use of Compost Only 3,591 ha (5% of the area of organic fertilizer application) was applied with compost. Mbinga had the largest planted area with compost application (1,561 ha, 43.5% of the total area applied with compost in the region), followed by Songea Rural (829 ha, 23.1%), Tunduru (649 ha, 18.1%), Namtumbo (394 ha, 11.0%) and Songea Urban (394 ha, 4.4%) (Map 3.56) 3.12.10 Fish Farming The number of households involved in fish farming in Ruvuma region was 4,035, representing 2 percent of the total agricultural households in the region (Chart 3.146). Songea Rural was the leading district with 1,294 households (32.1% of agricultural households involved in fish farming. In the region).This was followed by Namtumbo (933 households, 23.1%), Mbinga (910 households, 22.5%), Songea Urban (610 households, 14.9%) and Tunduru (298 households, 7.4%). (Chart 3.147 and Map 3.57). Chart 3.144 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 54,534, 29% Not Using Organic Fertilizer, 134,261, 71% Chart 3.145 Area of Application of Organic Fertiliser by District RUVUMA 0 6,000 12,000 18,000 Mbinga Songea Rural Tunduru Namtumbo Songea Urban District Farm Yard Manure Area Applied Compost Area Applied Chart 3.146 Number of Households Practicing Fish Farming - RUVUMA Households NOT Practicing Fish Farming, 187,140, 98% Households Practicing Fish Farming, 4,035, 2% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 The main source of fingerings was the neighbours which provided fingering to 76 percent of the fish farming households. About 12 percent of households practicing fish farming got fingerings from government institutions and 9 percent got them from non governmental organizations and/or projects. The fish farming households in the region used various fish farming systems (natural pond, dug out pond, water reservoir and others not identified) and the main fish species planted was Tilapia. The number of fish harvested in Ruvuma region was 758,065 of which 691,048 fish (91.2%) were tilapia, 22,353 (2.9%) were carp and 44,663 (5.9%) were not identified (Chart 3.148). About 36 percent of the fish farming households sold their fish to neighbours, those who sold to traders were 4%, and selling to others were 2% while 57 percent did not sell. Chart 3.148 Fish Production Number of Carp, 22,353, 3.1% Number of Tilapia, 691,048, 96.9% 0 200 400 600 800 1,000 1,200 1,400 Number of Households Songea Rural Namtumbo Mbinga Songea Urban Tunduru District Chart 3.147 Number of Households Practicing Fish Farming by District - Ruvuma RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services Table 3.17 Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather Roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Markets Tertiary Markets Tarmac Roads Tunduru 18.7 1.5 10.9 3.0 32.0 7.6 288.3 4.5 22.7 43.9 274.1 Songea Rural 18.0 1.5 3.2 0.5 46.6 8.5 54.2 14.6 44.6 40.8 23.6 Mbinga 14.9 2.7 8.6 2.5 27.0 6.1 125.0 8.8 34.8 43.3 106.4 Songea Urban 5.0 4.3 1.3 0.9 10.8 8.3 7.6 5.1 9.1 7.8 4.4 Namtumbo 15.4 1.3 19.8 3.6 70.5 6.6 79.7 7.6 56.6 62.3 73.4 Total 16.0 2.1 9.7 2.4 37.4 7.0 142.5 8.4 35.8 44.6 125.5 The results indicate that among the evaluated services, regional capital was a service located farthest from most of the household’s dwellings. It was located at an average distance of 143 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (126), tertiary market (45), hospital (37), secondary market (36), secondary school (16), all weather road (10), primary market (8), health clinic (7), feeder road 2) and primary school (2) (Table 3.17). 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (181,572 households, 96% of all rural agricultural households) 4767 households (2%) use flush toilets and 2,745 households (1%) use improved pit latrine. However, 2,090 households (1%) had no toilet facilities (Chart 3.119). The distribution of the households without toilets within the region indicates that 49.6 percent of them were found in Tunduru District and 3.3 percent were from Namtumbo. The percentages of households without toilets in other districts were as follows Mbinga (25.1%), Songea Rural (18.1%) and Songea Urban (3.9%) (2.5%) (Map 3.58). 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Ruvuma region with 109,159 households (57.1% of the agriculture households in the region) owning the asset, followed bicycles (69,706 households, 36.5%), irons (49,616 households, 26.0%), wheelbarrows (7,944 households, 4.2%), mobile phones (2,460 households, 1.3%), vehicles (2,284 households, 1.2%), TVs/Videos (1,549 households, 0.8%) and landline phones (1,496 households, 0.8%) (Chart 3.150). Chart 3.149 Agricultural Households by Type of Toilet Facility No Toilet , 2,090, 1% Improved Pit Latrine , 2,745, 1% Flush Toilet, 4,767, 2% Traditional Pit Latrine, 181,572, 96% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Lighting Pressure Lamp, 5,722, 3.0% Gas (Biogas), 564, 0.3% Mains Electricity, 559, 0.3% Solar, 438, 0.2% Firewood, 1,926, 1.0% Candles, 479, 0.3% Hurricane Lamp, 84,477, 44.2% Wick Lamp, 97,011, 50.7% Chart 3.150 Percentage Distribution of Households Owning the Assets 4.2 1.3 1.2 0.8 0.8 57.1 36.5 26.0 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Vehicle Television / Video Landline phone Assets Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 50.7 percent of the total rural households using this source of energy followed by hurricane lamp (44.2%), pressure lamp (3.0%), firewood (1.0%), gas or biogas (0.3%) mains electricity (0.3%), candle (0.3%) and solar (0.2%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.1 percent of all rural agricultural households in Ruvuma region. This was followed by charcoal (1.9%). The rest of energy sources accounted for 1.0 percent. These were solar (0.4%), bottled gas (0.2%), crop residues (0.1%), mains electricity (0.1%), solar (0.1%), livestock dung (0.1%), gas/biogas (0.1%), parrafin/kerosene (0.0%) and others (0.0%) (Chart 3.152). 3.13.6 Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 69.2 percent of the rural agricultural households. This was followed by iron sheets (33.4%), grass/mud (4.0%), tiles (0.6%), concrete (0.2%) and asbestos (0.0%) (Chart 3.153). Namtumbo district had the highest percentage of households with grass/leaves roofing (34.3%) followed by Mbinga district (31.4%), Songea Urban (16.8%), Tunduru (14.2%) and Songea Rural (3.2%) (Chart 3.154 and Map 3.59). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Ruvuma region was unprotected well (28 percent of households use unprotected wells during the wet season and 29 percent of the households during the dry seasons. This is followed by piped water (27% of households during the wet season and 26 percent during dry season), unprotected spring (18 % of households during the wet season and 19% in the dry season), protected well (15% of households for each season), lake/river (6 % of households in wet season and 8 % in dry season) and protected spring (4% of households in each season) Chart 3.155) Chart 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 185,686, 97.13% Others, 72, 0.04% Gas (Biogas), 227, 0.12% Parraffin / Kerocine, 77, 0.04% Livestock Dung, 174, 0.09% Solar, 698, 0.37% Mains Electricity, 225, 0.12% Crop Residues, 149, 0.08% Bottled Gas, 312, 0.16% Charcoal, 3,555, 1.86% Chart 3.153 Percentage Distribution of Households by Type of Roofing Material Tiles 0.6% Grass & Mud 4.0% Iron Sheets 33.4% Grass/Leaves 61.7% Concrete 0.2% Asbestos 0.0% Chart 3.154 Percentage Distribution of Households with Grassy/Leafy Roofs by District 34.3 31.4 16.8 14.2 3.2 0.0 25.0 50.0 Namtumbo Mbinga Songea Urban Tunduru Songea Rural D is t ric t Chart 3.155 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Upro tected Well P iped Water Unpro tected Spring P ro tected Well Lake/River P ro tected Spring Other Main source Percent of Households Wet Season Dry Season Songea Urban Songea Rural 82 379 524 69 1,036 1.2% 1.2% 0.7% 0.2% 2.2% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 601 1,294 910 933 298 8.7% 4.2% 1.2% 3.2% 0.6% Mbinga Namtumbo Tunduru Number and Percent of Households Practicing Fish Farming by District MAP 3.59 RUVUMA Number of Households Without Toilets MAP 3.60 RUVUMA Number and Percent of Households Leaving Without Toilets by District Number Households Practicing Fish Farming 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 1,000 to 1,250 750 to 1,000 500 to 750 250 to 500 0 to 250 Tanzania Agriculture Sample Census Number of Households Leaving Without Toilets Percent of Number of Households Leaving Without Toilets Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming RESULTS 88 Songea Urban Songea Rural Mbinga 27 76 69 0 0.2 0.4 0 0.2 0 Namtumbo Tunduru Songea Urban Namtumbo Songea Rural 9,358 906 302 1,661 2,814 19.1 20.9 33.4 21.1 Mbinga Tunduru Number and Percent of Households Infected with Ticks by District MAP 3.55 RUVUMA Number and Percent of Households Using Draft Animals- MAP 3.56 RUVUMA Number and Percent of Households Using Draft Animals by District Number of Households Infected with Ticks Number of Households Infected with Ticks Percent of Households Infected with Ticks Number of Households Using Draft Animals Percent of Households Using Draft Animals 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census RESULTS 89 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 90 About 88 percent of the rural agricultural households in Ruvuma region obtained drinking water within a distance of less than one kilometer during wet season compared to 86 percent of the households during the dry season. However, 12 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 16 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.156). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Ruvuma region normally have 3 meals per day (64.5 percent of the households in the region). This is followed by 2 meals per day (33.4 percent) and 1 meal per day (1.9 percent). Only 0.2 percent of the households have 4 meals per day (Chart 3.157). Songea Urban district had the largest percent of households eating one meal per day whilst Tunduru had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.60). 3.13.8.2 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 125,147 (65% of the agricultural households in Ruvuma region) with 52,566 households (42 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (32%). Very few households had meat three or more times during the respective week. About 35 percent of the agricultural households in Ruvuma region did not eat meat during the week preceding the census (Chart 3.159 and Map 3.61). Table 3.18 Number of Households by Number of Meals the Household Normally Takes per Day and District Number of Meals per Day District One % Two % Three % Four % Total Tunduru 318 0.7 7537 16.1 39043 83.3 0 0.0 46898 Songea Rural 0 0.0 12028 39.1 18668 60.7 76 0.2 30772 Mbinga 2,325 3.0 35,417 45.7 39,440 50.9 265 0.3 77,447 Songea Urban 409 5.9 1992 28.7 4542 65.4 0 0.0 6943 Namtumbo 553 1.9 6895 23.7 21598 74.2 69 0.2 29115 Total 3,605 1.9 63,869 33.4 123,291 64.5 409 0.2 191,175 Chart 3.157 Number of Agriculural Households by Number of Meals per Day One, 3,605, 2% Four, 409, 0% Two, 63,869, 33% Three, 123,291, 65% Chart 3.156 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 40 < 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance P er ce nt wet season Dry season RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 159,245 (83% of the total agricultural households in Ruvuma region) with 43,373 households (27 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (25%). In general, the percentage of households that consumed fish twice or more during the week in Ruvuma region was 115,872 (72.8% of the agricultural households that ate fish in the region during the respective period). About 16.7 percent of the agricultural households in Ruvuma region did not eat fish during the week preceding the census (Chart 3.158 and Map 3.62). 3.13.9 Food Security In Ruvuma region, 48,168 households (25% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements. However 12,550 (6.6%) said they sometimes experienced problems, 2.5 often experienced problems and 3.2 percent always had problems in satisfying the household food requirements. About 63 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.63). 3.13.10 Main Sources of Cash Income The main cash income of the households in Ruvuma region was from selling food crops (49.5 percent of smallholder households), followed by selling of cash crops (26%), other casual cash earnings (8%), business income (4%), wages and salaries (4%), fishing (3%), and remittance (3%). Only 1% of smallholder households reported the sale of livestock as their main source of income, followed by other (1%), forest products (1%) and livestock products (0%) (Chart3.159). Chart 3.158 Number of Households by Frequency of Meat and Fish Cosumption 0 15,000 30,000 45,000 60,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Chart 3.159: Percentage Distribution of the Number of Households by Main Source of Income Cash Crops, 26.2 Food Crops, 49.5 Other Casual Cash Earnings, 7.6 Business Income, 4.1 Wages & Salaries, 3.6 Livestock, 1.3 Livestock Products, 0.3 Forest Products, 0.8 Remittance, 2.6 Fishing, 2.7 Other, 1.2 Namtumbo Songea Urban Mbinga Songea Rural 21,598 39,043 4,542 39,440 18,668 74.2% 83.3% 65.4% 60.7% 50.9% Tunduru Songea Urban Songea Rural 55 3,099 2,501 419 1,492 10.1% 0.8% 3.2% 1.4% 3.2% Mbinga Namtumbo Tunduru 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Number and Percent of Households Using Grass/Mud for Roofing Material by District MAP 3.61 RUVUMA MAP 3.62 RUVUMA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Tanzania Agriculture Sample Census Number of Households Using Grass/Mud for Roofing Material Number of Households Using Grass/Mud for Roofing Material Number of Households Eating 3 Meals per Day Percent of Households Using Grass/Mud for Roofing Material Percent of Households Eating 3 Meals per Day 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 92 Namtumbo Songea Urban Mbinga Songea Rural 8,553 27,777 1,720 10,566 23,020 29.4% 35.9% 24.8% 34.3% 49.1% Tunduru Number and percent of Households Reporting food insufficiency by District MAP 3.65 RUVUMA Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Ruvuma region RESULTS 93 DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 RUVUMA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Ruvuma Region Profile Ruvuma had a land area of 575,000 hectares under crop production. Although it had a moderate number of crop farming households compared to other regions, it had one of the lowest number of crop growing households per square kilometre. The available land area per household is 4.1 hectares. Of the total available land in the region, it had one of the lowest land utilisation percentages in Tanzania and this is reflected by the lowest number of households responding to insufficient land. Ruvuma has no short rainy season. Compared to other regions, the average planted area of annual crops per household was above average. Cereal production in the region was moderate and it was mostly maize and paddy production with one of the smallest areas of sorghum in the country. Cassava was an important crop in the region and the planted area of tobacco was the second largest in the country. Beans and groundnuts were produced in moderate to low quantities, however the region was important for vegetables production. Ruvuma was the second most important region for the production of cashew nuts, fourth for coffee and fifth for oranges. sugar cane and pigeon peas were also grown in the region. The region had a small but moderate level of irrigation compared to other regions. There was a slight change in the number of households using irrigation for a period of 10 years. The main source of water for irrigation was rivers and the method of obtaining irrigation water was mostly by buckets/watering cans, closely followed by gravity. Buckets/watering cans were also the most common methods of applying irrigation water. Practically all land was cultivated by hand. Almost 50 percent of the planted area in Ruvuma was applied with fertilisers and it had the highest percent of inorganic fertilisers application in the country. It had a low to moderate application of pesticides compared to other regions in the country. Most storage was in sacks/open drums and this was closely followed by locally made traditional structures. The region has the highest percent of households selling crops in the country. Most processing is done by neighbours machine and very little of the processed crops is sold. The number of households receiving extension is moderate to low. The predominant implement used in the region was the hand hoe, however it had the highest percent of hand powered sprayers and the second highest percent of threshers/shellers. Ruvuma was the fourth region with largest number of planted trees mostly eucalyptus. The number of households with erosion control/water harvesting structures was low, however it had a moderate number of terraces compared to other regions. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 4.2 District Profiles Thee following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Tunduru Tundura district had the second largest number of households in the region as the highest percent of households in the district that are involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It had very few livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Tunduru district is annual crop farming, followed by permanent crop farming, then off farm income. The district has the highest percent of households without off-farm activities and lowest percent households with more than one member with off-farm income. Compared to other districts in the region, Tunduru had one of the lowest percent of female headed households (13%) and it had one of the lowest average ages of the household head. With an average household size of 4.7 members per household it was average for the region. Tunduru has a comparatively low literacy rate among smallholder households and this is reflected by the high percent of household members that have not attended school. The literacy rates for the heads of household was also lowest in the region. The district has the largest utilized land area per household (3.2 ha) and it has the highest percent of allocated land that is utilized (82%) in the region, indicating a higher level of land pressure. The total planted area is second largest than in other districts in the region. Compared to other districts in the region, Tunduru had a moderate production of maize with a planted area of 27,246 hectares, however the planted area per household is the lowest in the region. Tunduru is very important for rice production compared to other districts in the region with planted area of 19,760 hectares it is almost three times more than the other districts in the region. It has also the largest planted area per household compared to other districts in the region. A small amount of sorghum was grown in the Ruvuma region and most of this was grown in Tundudu district (1,845 ha). Cassava production is important in the region accounting for 26 percent of the area planted in the region. The largest planted area with groundnuts was in Tunduru (9.561 ha) and it also had the largest planted area per household. Other oilseed crops were not important in the district. Tomatoes, onions, cabbage and pumpkin were grown in the district, however tomatoes were the most important. A traditional cash crop (e.g. tobacco or cotton) were not important in the district.. Compared to other districts in the region, Tunduri has the highest planted area with permanent crops (79,226), which is dominated by Cashewnuts (71,527 ha). Pigeon peas are also important with a planted area of 4,758 hectares and is highest in the region. Other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The use of inputs in the district is small. The district has one of the lowest planted areas with fertilizers however, of the small area with fertilizer most was with inorganic fertilizer. Compared to other districts in the region, Tunduru district has the smallest level of insecticide use, however it had the highest herbicide use and the second highest fungicide use in the DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 96 region. The district had a moderate to high planted area under irrigation compared to other districts with around 2,100ha of irrigated land. The most common source of water for irrigation is from rivers using hand bucket. Bucket/watering can is the most common means of application. The most common method of crop storage is in locally made traditional cribs. Tundura had stored the smallest proportion of its crop. Tunduru has the highest percent of households processing on farm by hand and it sold practically none of its processed products. Although very small, access to credit in the district is mainly to men and the main sources are from Co-operative and saving and credit societies. Tundura had one of the lowest percent of households receiving extension and all of this is from the government. Tree farming in Tunduru was not reported and erosion control/water harvesting facilities were not common. Tunduru district has a small number of cattle (4,040 head)e in the region and they are all indigenous. Goat production is the second smallest compared to other districts, however it has the second largest population of sheep in the region. It has the smallest number of pigs in the region and the second smallest number of chickens. The district has the no layers, but a small number of broilers. It has the largest number of ducks in the region and small numbers of rabbits and donkeys are kept. The highest percent of households reporting tsetse fly problems was in Tunduru district while the percent of households reporting tick problems in the district was the smallest. It had the fourth largest percent of households de- worming livestock. The use of draft animals in the district was almost absent, Tunduru had the least number of households practicing fish farming. It has the one of the best access to primary schools and and primary markets compared to other districts. However, it has the worst access to Secondary schools, tarmac roads, feeder roads and regional capital. Tunduru district has the highest percent of households with no toilet facilities and it the second highest percent of households owning a radio. The most common form of energy for lighting is the wick lamp followed by hurricane lamp. A small number of farmers use mains electricity and practically all households use firewood for cooking. The district has the second smallest percent of households with grass roofs. The most common source of drinking water is from unprotected wells. It has the highest percent of households having three meals per day compared to other districts and one of the lowest percent with two meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2 Songea Rural Songea Rural district had the second smallest number of households in the region and the third highest percentage of households in the district that were involved in smallholder agriculture compared to other districts in the region. Most smallholders were involved in crop farming only, followed crop and livestock. It has no livestock only households or pastoralists. The most important livelihood activity for smallholder households Songea Rural district is annual crop farming, followed by permanent crop farming and off farm income. It had the lowest percent of households with no off-farm activities and it had the highest percent of households with more than two members with off-farm income. Compared to other districts in DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 the region, Songea Rural had the highest percent of female headed households (18%) and it had one of the highest average ages of the household head in the region. With an average household size of 4.6 members per household it was almost average for the region. It has a moderate utilized land area per household (1.9 ha) and only 69 percent of the allocated area is currently being utilized. The district has the third largest planted area in the region. The district is moderately important for maize production in the region with a planted area of 28,503 hectares, however the planted area per household is high for the region. Paddy production is low to moderate with a planted area of 6,187 hectares. Finger millet is grown in moderate amounts (2,941 ha) and cereals are not important in the district. Songea Rural had a planted area of 11,465 hectares under cassava (second lowest in the region) and the production of sweet potatoes was small. The district had a small planted area of groundnuts. The district is one of the least important for vegetable production and the most important are tomatoes, cabbage and onions. Compared to other districts in the region, Songea Rural has a small to moderate area with permanent crops of with 5,655 hectares. This is dominated by bananas (1,622 ha) and a small area of pigeon peas (582 ha). Other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The use of inputs in the district is moderate. The district has a moderate planted area with fertilisers (Farm yard manure, compost and inorganic fertilizer and most of this is inorganic fertiliser. Compared to other districts in the region, Songea Rural district has one of the highest levels of insecticide use. It has the smallest use of herbicides in the region and one of the smallest uses of fungicides. It has the smallest area with irrigation compared to other districts with 3,377 ha of irrigated land. Although the district has the second largest number of cattle in the region it only has a small number and they are mostly indigenous with some dairy. Goat and sheep production is moderate compared to other districts in the region. It has a small number of pigs and a moderate number of chickens. Some ducks, rabbits and turkeys are also found in the district, however donkeys are absent. A percent of households reporting tick problems in Songea Rural district is second highest compared to other districts in the region and it had moderate percent of households reporting tsetse problems. It had the second highest percent of households de-worming livestock. The district has a small number of households using draft animals. It has the largest number of households practicing fish farming. It has one of the worst access to secondary schools, hospitals, health clinics and primary and secondary markets, however it has good access to primary schools and feeder roads compared to other districts. The percentages of households without toilet facility in Songea Rural district is 18.1 percent. It has very few households using mains electricity. The most common source of energy for lighting is the hurricane lamp followed by wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 grass/leaves (55%) and iron sheets (34%). The most common source of drinking water is from protected wells. It has the highest percent of households having two meals per day. The district had the second lowest percent of households that did not eat meat or fish during the week prior to enumeration and it has a low to moderate percent of households that always had problems with food satisfaction. 4.3 Mbinga Mbinga district had the largest number of households in the region and it has the forth largest percent of households in the district involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by both crop and livestock. It has a small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mbinga district is annual crop farming, followed by permanent crop farming. The district has the third highest percent of households with no off-farm income activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mbinga has the third highest percent of female headed households (15%). With an average household size of 4.6 members per household it is around average for the region. Mbinga has the second highest literacy rate among smallholder households and the second lowest number household members that have never attended school in the region. The land area utilized per household (2.9ha) is around the average for the region of 3.0 hectares and 80 percent of the allocated area is currently being utilized which is moderate for the region. The district has the highest planted area in the region, and the second smallest planted area per household. Mbinga is the most important district in the region maize production planted area of 50,346 ha and the planted area per household of 0.74 hectares which is equal to the average for the region (0.8 ha). Paddy production is not important with a planted area of only 3,721 hectares and it is second lowest in the region. Wheat and finger millet were grown in the region. The district had the largest planted area of cassava accounting for 45 percent of the cassava planted area in the region. The district also had the largest planted area of beans (3,648 ha) Groundnut production was not important in the district and a small area of vegetables are grown (tomatoes, cabbage and onions). Mbinga has the second highest area planted with permanent crops (33,295 ha) and this is dominated by coffee (29,312 ha) which is the highest in the region. Bananas were also grown (1,096 ha) and other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the largest number of cattle in the region and they are almost all indigenous apart from a small number of dairy cattle. It has the largest number of goat, sheep, pigs and chickens compared to other districts in the region. It has the second largest number of pigs in the region and the largest number of chickens. The district has the largest number of rabbits and donkeys in the region and second highest number of ducks. The district had the highest percent of households reporting tick problems in the region. Mbinga had the highest percent of households deworming livestock. The use of draft DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 animals in the district is very small. A small number of households practice fish farming, however the district has the third largest number in the region. Compared to other districts, it has a moderate access to infrastructure and services. Mbinga district has a moderate percent of households with no toilet facilities compared to other districts in the region and it has a high number of households owning radios and irons. Very few households use mains electricity in the region. The most common source of energy for lighting is the hurricane lamp followed by wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (52%) with 44 percent of households having iron sheets. The most common source of drinking water is from unprotected springs and wells. Fifty percent of the households in the district reported having three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration; however a large percent of households never had problems with food satisfaction. 4.4 Songea Urban Songea Urban district had the lowest number of households in the region and the third lowest percent of households in the district that were involved in smallholder agriculture compared to other districts in the region. Most smallholders were involved in crop farming only, followed by crop and livestock. It had no livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Songea Urban district is annual crop farming followed off farm income and permanent crop farming. It has the lowest percent of households with no off-farm income activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Songea Urban district has the second highest percent of female headed households in the district (28%). With an average household size of 4.8 members per household it is slightly above average for the region. Songea Urban district has the highest literacy rate among smallholder households in the region and this is reflected by the lowest percent of household members that have never attended schools in the region. It has the smallest utilized land area per household (2 ha) and 78 percent of the allocated land area was utilized. The total planted area was very low compared to other districts in the region and it had the smallest planted area per household. Maize production is the most important crop in the district with a planted area of (4,600 ha,) and a planted area per household of 0.64 ha. However the area planted is the lowest in the region. Paddy production is not important in the district and other cereals were either not grown or were grown in very small quantities. Roots and tubers are not important in the district in the region and beans were grown in moderate to small quantities. Oilseed crops are not important, however vegetables are important in terms of the percent of the area of land in the district with vegetables. Cash crops are not important in the district. Compared to other districts in the region, Songeo Urban district is not important for permanent crops (1,603 ha) with practically all being under bananas (1,307 ha). DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however it has the highest proportion of its planted area with fertilizer application and most of this is with inorganic fertilizer. Compared to other districts in the region, Songea Urban district has the percent of its planted area with insecticide, a comparatively moderate percent with herbicides and a low percent with fungicides. It has one of the smallest areas of irrigation in the region. The most common method of obtaining and applying water is by hand buckets/Bucket Songea Urban has the smallest number of cattle in the region and all of them are dairy. It has the least number of goats and sheep and the second lowest number of pigs in the region. It has also the smallest number of chickens. Small numbers of ducks and rabbits are also found in the district. A small percent of households reported Tsetse and tick problems and it had the lowest percent of households de-worming livestock. The use of draft animals in the district is very small. Very small number of households practice fish farming in the district. It has the best access to infrastructure and services in the region. Songea Urban district has the smallest percent of households with no toilet facilities in the region. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp followed by hurricane lamp and most households use firewood for cooking, however it had the highest percent using charcoal. The district has the highest percent of households with using iron sheet roofing (45%) with 55 percent of households using grass. The most common source of drinking water is unprotected well. Three meals per day is the most common and it has the third highest percent of households that did not eat meat during the week prior to enumeration. However most households never or seldom have problems with food satisfaction. 4.5 Namtumbo Namtumbo district has the third highest number of households in the region and it has the forth highest percent of households in the district involved in agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a relatively small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Namtumbo district is Annual Crop Farming followed by Permanent Crop Farming, Livestock Keeping/Herding and Off-Farm Income. The district has the second highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Namtumbo has the lowest percent of female headed households (9%). With an average household size of 5.3 members per household it is higher than the regional average of 4.7 members. Namtumbo has the second lowest literacy rate among smallholder households in the region. It has the second highest utilized land area per household (3.2 ha) which is the same as the regional average. Around 95 percent of the allocated land is utilized. The district only has one season. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 The district has the second largest planted area of maize compared to other districts in the region (28,809ha) and the planted area per household is among the highest in the region. Paddy production is moderately important with a planted area of 7,440 hectares. Finger Millet is also grown in the district with a planted area of 3,497 hectares. Other cereals are grown in minor quantities. Namtumbo has the third largest planted area of Cassava (11,605ha) in the region. Other root and tuber crops were grown in small quantities. The production of beans in the district is moderate to low (4,877 ha) and groundnut production was also low (2,046 ha). Vegetable production is not very important, however tobacco is an important cash crop in the district with a planted area of 5,602 hectares. Compared to other districts in the region, Namtumbo district is not important for permanent crops (5,233 ha) with bananas being the most important (2,704 ha) and is the highest in the region. As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the largest planted area with inorganic fertilizer and one of the smallest planted areas with farm yard manure. Namtumbo has one of the smallest percent of its planted area applied with insecticides and herbicides. The district has the second largest planted area and gravity is the most common means of conveying water and field application by flood was most common. The district has the second smallest number of cattle in the region and they are mostly dairy. It has the second highest number of goats and second lowest number of sheep. It has a the second highest number of chickens. Ducks and rabbits found in the district in small numbers. A moderate number of households reported Tsetse and tick problems in the district. The use of draft animals in the district is small however it has the second d highest number of households practicing fish farming in the region It is amongst the districts with the best access to primary schools and health clinics, however it has one of the worst access to all weather roads, feeder roads, hospitals, secondary markets and tertiary markets. Namtumbo district has the second highest percent of households with no toilet facilities. It has the second largest number of households using mains electricity in the region. The most common source of energy for lighting is the hurricane lamp followed by the wick lamp and practically all households use firewood for cooking. The district has one of the largest percent of households with grass roofs (68%) and only 29 percent of households have iron sheets. The most common source of drinking water is piped water. It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a high percent of households with 3 meals per day. Most households in the district n ever have problems with food satisfaction. APPENDIX II 102 4. APPENDICES APPENDIX I TABULATION LIST.........................................................................................103 APPENDIX II TABLES............................................................................................................121 APPENDIX III QUESTIONNAIRES.......................................................................................271 APPENDIX II 103 TYPE OF AGRICULTURE HOUSEHOLD ...............................................................................121 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year ..........................................................................................................122 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year .........................................................................................................122 NUMBER OF AGRICULTURE HOUSEHOLDS..................................................................123 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year................................................124 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District..................................................................................................124 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.............................................125 3.1a First Most Importance..................................................................................................126 3.1b Second Most Importance..............................................................................................126 3.1c Third Most Importance ................................................................................................126 3.1d Fourth Most Importance...............................................................................................126 3.1e Fifth Most Importance..................................................................................................127 3.1f Sixth Most Importance.................................................................................................127 HOUSEHOLDS DEMOGRAPHS............................................................................................129 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) ...........................................................................................130 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) .....................................................................................130 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year .........................................................................................................131 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year .......131 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year......................................................................131 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year .........................................................................................................131 APPENDIX II 104 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year.......................................................132 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year...................................................133 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.......................................134 3.11 Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year.......134 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year........................................................134 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District...........134 3.14 Time Series of Male and Female Headed Households ................................................135 3.15 Literacy Rate of Heads of Households by Sex and District.........................................135 LAND ACCESS/OWNERSHIP................................................................................................137 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year .....................................................................................138 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year .........................................................................................................138 LAND USE..................................................................................................................................139 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year .........................................................................................................140 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year .........................................................................................................140 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year ..................................141 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year..............141 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year.......141 APPENDIX II 105 TOTAL ANNUAL CROP & VEGES PRODUCTION WET & DRY SEASONS ...............143 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District. .........................................................................................144 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District.........144 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Ruvuma Region .............................................................................145 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Ruvuma Region .............................................146 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Ruvuma.................................................147 7.1 & 7.2gTotal Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year ...............................................147 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................147 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................148 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................148 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season............................148 ANNUAL CROP & VEGES PRODUCTION DRY SEASON...............................................151 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - DRY SEASON, Ruvuma Region.................................................................................152 7.1b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - DRY SEASON, Ruvuma Region.........................152 7.1c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Dry Season, 2002/03 Agriculture Year, Ruvuma Region.................................152 7.1d ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Dry Season. .........................................................................................................................153 7.1e ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Dry Season. .........................................................................................................................153 APPENDIX II 106 7.1f ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season .........................................................................................................................154. 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - DRY SEASON ..............................................................154 ANNUAL CROP & VEGES PRODUCTION WET SEASON ..............................................155 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, Ruvuma Region. ................................................................156 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, Ruvuma Region............156 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, Ruvuma Region ...................156 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season..............................................157 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season..............................................157 7.2f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET SEASON........................................158 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON .................................................158 7.2h: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year ................................159 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 APPENDIX II 107 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year............................................164 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 APPENDIX II 108 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 PERMANENT CROPS..............................................................................................................167 7.3.1 Production of Permanent Crops by Crop Type and District – Ruvuma Region ..........168 7.3.2 Area Planted by Crop Type - Ruvuma Region ............................................................171 7.3.3 Area Planted with Cashewnut by District ....................................................................171 7.3.4 Area planted with Coffee by District ...........................................................................173 7.3.5 Area planted with Banana by District ..........................................................................173 7.3.6 Area Planted with Pigeon by District...........................................................................173 7.3.7 Planted Area with Fertilizer by Fertilizer Type and Crop............................................174 AGROPROCESSING................................................................................................................177 8.1.1a: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year ..............................................................................178 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year .........................................................................................................178 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Ruvuma Region.......................................................................178 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Ruvuma Region..........................................................................................................................179 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Ruvuma Region............................................................................................................179 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Ruvuma Region ..............................................................................180 APPENDIX II 109 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Ruvuma Region .......................................180 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Ruvuma Region ................................................................180 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Ruvuma Region ................................................................180 MARKETING ............................................................................................................................181 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Ruvuma Region ..............................................................182 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Ruvuma Region .....................................182 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Ruvuma Region.......................................182 IRRIGATION/EROSION CONTROL ....................................................................................183 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District ........................................................................................184 11.2 Area (ha) of Irriga and NON irrigated land by district during 2002/03 agriculture year.. 11.3: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year ............................................................184 11.4: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year ...........................................................................................184 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year .................................................185 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District....................................................................................................................185 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year ...........................................................................................185 ACCESS TO FARM INPUTS...................................................................................................187 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year .........................................................................................................188 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year ...........................................................................................188 APPENDIX II 110 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year ...........................................................................................188 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year ...........................................................................................189 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year .........................................................................................................189 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year ...........................................................................................189 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year ...........................................................................................190 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ...........................................................................................190 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ...........................................................................................191 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................191 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year .........................................................................................................192 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................193 cont.Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................193 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................193 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................194 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year...........................................................194 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .............................................................................194 12.1.17a Number of Agricultural Households and Distance to Source of Insecticide /Fungicides by District, 2002/03 Agricultural Year.....................................................195 12.1.17b Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year .............................................................................195 APPENDIX II 111 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................196 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year...........................................................196 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................196 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year..................................197 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ........................................................................197 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ..............................................................197 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................198 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ...........................................................................................198 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................198 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................199 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year ...........................................................................................199 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................199 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year.......................................................200 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year......................................................200 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ........................................................................200 12.1.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year...............................................................200 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year .............................................................................201 APPENDIX II 112 AGRICULTURE CREDIT........................................................................................................203 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year ............................................................204 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year ............................................................................................204 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year ........................................................205 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year ............................................................................................205 TREE FARMING AND AGROFORESTRY ..........................................................................207 14.1 Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................208 Cont Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region..................................................................................................208 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Ruvuma Region..................................................................................................209 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region ................................................................................209 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Ruvuma Region.......210 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region ................................................................................210 CROP EXTENSION ..................................................................................................................211 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Ruvuma Region .................................212 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Ruvuma Region ...............................................................212 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region...........................212 APPENDIX II 113 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................213 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................213 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................213 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................215 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................215 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................215 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................216 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................216 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................216 APPENDIX II 114 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................219 ANIMAL CONTRIBUTION TO CROP PRODUCTION .....................................................221 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Ruvuma Region.....................................222 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region ....................................222 cont… Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region...................222 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Ruvuma Region ..................................................................222 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Ruvuma Region ................................................................................223 CATTLE PRODUCTION .........................................................................................................225 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Ruvuma Region............................................................................................................226 18.2 Number of Cattle By Type and District as of 1st October, 2003 .................................226 APPENDIX II 115 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 ........................................................226 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003....................267 18.5 Number of Indigenous Cattle By Category and District as on 1st October, 2003 .......227 18.6 Number of Improved Beef Cattle By Category and District as on 1st October, 2003.227 18.7 Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 .........................................................................................................228 18.8 Number of Cattle By Category and District as on 1st October, 2003..........................228 GOATS PRODUCTION............................................................................................................229 19.1 Total Number of Goats by Type and District as on 1st October, 2003........................230 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ................230 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District..........................................................................................................................231 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 .........................................................................................................231 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003 .........................................................................................................231 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ......232 19.7 Total Number of Goats by Category and District on 1st October, 2003.....................232 SHEEP PRODUCTION.............................................................................................................233 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03..................234 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 ........234 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Ruvuma Region............................................................................................................235 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 ..........................................................................................................235 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ..........................................................................................................235 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003..................235 APPENDIX II 116 PIGS PRODUCTION ................................................................................................................137 21.1 Number of Households and Pigs by Herd Size on 1st October 2003...........................138 21.2 Number of Households and Pigs by District on 1st October 2003 ..............................138 21.3 Number of Pigs by Type and District on 1st October, 2003........................................138 LIVESTOCK PESTS AND PARASITE CONTROL .............................................................139 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. .......................................240 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year ............................................................240 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District ...........................241 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year ..............................................241 OTHER LIVESTOCK...............................................................................................................243 23a Total Number of Other Livestock by Type on 1st October 2003 ................................244 23b Number of Chicken by Category of Chicken and District on 1st October 2003..........244 23c Head Number of Other Livestock by Type of Livestock and District .........................244 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 ..........................................................................................................244 23e LIVESTOCK/POULTRY POPULATION TREND .............................................................244 FISH FARMING ........................................................................................................................245 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year ...........................................................................................246 28.2 Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year..........................................................................246 28.3 Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year..........................................................................246 28.4 Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year..........................................................................246 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....246 APPENDIX II 117 LIVESTOCK EXTENSION......................................................................................................247 29.1a Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year ...........................................................................................248 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year..........................................................................248 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year.....................................................250 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year........................................251 29.7 Number of Agricultural Households Receiving Extension Advice on Herd / Flock Size and Selection By Source and District, 2002/03 Agricultural Year ............251 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year.......252 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year .....252 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year .......................................253 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year.......................253 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year ...........................................................................................254 ACCESS TO INFRASRUCTURE AND OTHER SERVICES..............................................255 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts ...................................................................................................................256 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year ............................................................................................................257 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year ............................................................................................................257 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year ............................................................................................................257 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year ............................................................................................................258 APPENDIX II 118 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year ...........................................................................................................258 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year ...........................................................................................................258 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year ............................................................................................................259 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year ............................................................................................................259 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year ...........................................................................................................259 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................261 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year .............................................................................261 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year .............................................................................261 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ..............................................................262 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ...........................................................262 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year .....................................262 HOUSEHOLD FACILITIES ....................................................................................................263 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year.......................................................................................264 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ........................................................264 APPENDIX II 119 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ...........................................................................................264 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year................................................................................265 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year................................................................................265 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year .........................266 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ....................266 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year..................267 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ............................................................................................................267 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District..............................................................................................268 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ........................................................................268 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ........................................................................269 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District .......................................................269 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .....................................................................................270 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year ............................................................................................270 APPENDIX II 120 APPENDIX II: CROPS Type of Agriculture Household.................................................................................................................. 121 Number of Agriculture Households ............................................................................................................123 Rank of Importance of Livelihood Activities..............................................................................................125 Households Demography ............................................................................................................................129 Land Access/Ownership..............................................................................................................................137 Land Use………………..............................................................................................................................139 Total Annual Crop and Vege Production Long and short Seasons.............................................................143 Annual Crop and Vege Production Long Rainy Seasons............................................................................155 Permanent Crop Production.........................................................................................................................167 Agro-processing .................................................................................................................................177 Marketing .................................................................................................................................181 Irrigation/Erosion Control ...........................................................................................................................183 Access to Farm Inputs ................................................................................................................................ 187 Agriculture Credit .................................................................................................................................203 Tree Farming and Agro-forestry..................................................................................................................207 Crop Extension .................................................................................................................................211 Animal Contribution to Crop Production ....................................................................................................221 Cattle Production .................................................................................................................................225 Goat Production .................................................................................................................................229 Sheep Production .................................................................................................................................233 Pig Production .................................................................................................................................237 Livestock Pests and Parasite Control...........................................................................................................239 Other Livestock .................................................................................................................................243 Fishing Farming .................................................................................................................................245 Livestock Extension .................................................................................................................................247 Access to Infrastructure and other services .................................................................................................255 Household Facilities....................................................................................................................................263 Appendix II 121 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census-2003 Ruvuma Appendix II 122 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Tunduru 46,898 98 1,094 2 47,992 90 5,065 10 53,057 Songea Rural 30,772 99 386 1 31,158 99 356 1 31,514 Mbinga 77,447 98 1,929 2 79,376 94 5,293 6 84,669 Songea Urban 6,943 99 61 1 7,004 23 23,098 77 30,102 Namtumbo 29,115 99 269 1 29,384 89 3,614 11 32,998 Total 191,175 98 3,739 2 194,914 84 37,426 16 232,340 Number of households % Number of households % Number of households % Number of households % Tunduru 41,622 29 0 0 5,276 11 46,898 25 46,898 46,898 5,276 Songea Rural 22,195 16 0 0 8,578 17 30,772 16 30,772 30,772 8,578 Mbinga 52,111 37 132 100 25,204 77,447 41 77,447 77,315 25,335 Songea Urban 5,144 4 0 0 1,799 4 6,943 4 6,943 6,943 1,799 Namtumbo 20,548 15 0 0 8,567 17 29,115 15 29,115 29,115 8,567 Total 141,619 100 132 100 49,424 100 191,175 100 191,175 191,043 49,556 Total Number of Households Rearing Livestock Crops Only Livestock Only 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Crops & Livestock Total District Agriculture, Non Agriculture and Urban Households 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year District Type of Agriculture Household Total Number of Agriculture Households Total Number of Households Growing Crops Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 123 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 124 Number % Average Household Size Number % Average Household Size Number % Tunduru 40,976 87 5 5,922 13 4 46,898 100 5 Songea Rural 25,232 82 5 5,540 18 4 30,772 100 5 Mbinga 65,745 85 5 11,701 15 4 77,447 100 4 Songea Urban 5,852 84 5 1,090 16 4 6,943 100 5 Namtumbo 26,542 91 5 2,573 9 4 29,115 100 5 Total 164,347 86 5 26,827 14 4 191,175 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 1 2 4 3 5 6 7 Songea Rural 1 2 4 3 5 6 7 Mbinga 1 2 3 4 5 6 7 Songea Urban 1 3 4 2 5 6 7 Namtumbo 1 2 3 4 5 6 7 Total 1 2 4 3 5 6 7 Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of District Livelihood Activity 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of District Male Female Total Average Household Size Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 125 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 126 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 25,225 15,535 318 4,772 522 98 421 Songea Rural 23,860 680 530 4,485 841 227 303 Mbinga 26,035 33,408 2,303 8,352 2,473 4,993 0 Songea Urban 3,573 431 245 2,446 220 0 82 Namtumbo 26,033 1,360 0 1,146 286 142 434 Total 104,726 51,415 3,396 21,201 4,341 5,460 1,241 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 17,901 21,111 1,028 4,335 422 107 2,317 Songea Rural 5,850 7,005 5,692 9,945 758 380 1,672 Mbinga 32,750 17,986 12,877 10,934 1,926 875 1,017 Songea Urban 2,554 2,372 628 1,120 134 0 241 Namtumbo 2,432 12,389 4,466 6,613 861 145 2,281 Total 61,487 60,862 24,691 32,948 4,101 1,507 7,528 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 2,932 4,029 5,919 9,302 1,220 960 21,581 Songea Rural 835 8,345 8,443 4,261 1,127 380 7,229 Mbinga 11,287 10,217 27,135 14,607 2,577 1,270 5,915 Songea Urban 569 2,458 1,445 1,034 189 27 1,004 Namtumbo 361 5,675 8,289 4,453 1,290 360 7,326 Total 15,983 30,724 51,231 33,657 6,404 2,997 43,055 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 2,059 5,138 3,337 2,071 213 16,809 Songea Rural 152 6,385 6,469 2,356 1,287 303 11,619 Mbinga 3,372 6,082 16,348 12,283 2,860 2,323 11,656 Songea Urban 136 706 2,071 870 439 54 1,990 Namtumbo 218 3,162 4,509 4,163 720 429 10,947 Total 3,877 18,394 34,536 23,009 7,377 3,322 53,021 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 127 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 1,026 2,595 1,024 1,233 318 3,789 Songea Rural 0 4,872 2,591 1,682 534 0 6,915 Mbinga 2,063 1,396 3,726 4,286 3,120 645 11,879 Songea Urban 82 190 573 191 220 137 2,530 Namtumbo 73 1,648 2,443 1,144 217 214 6,905 Total 2,218 9,132 11,927 8,328 5,324 1,314 32,018 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 0 320 0 107 0 318 Songea Rural 0 306 229 154 0 76 382 Mbinga 248 381 380 521 785 132 2,326 Songea Urban 0 0 54 27 0 0 218 Namtumbo 0 0 71 73 0 0 290 Total 248 687 1,053 775 892 208 3,535 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES:Sixth Most Importance Tanzania Agriculture Sample Census - 2003 Ruvuma 128 Appendix II 129 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 130 Number % Number % Number % Less than 4 62,317 49 64,189 51 126,506 100 05 - 09 63,411 50 63,734 50 127,146 100 10 - 14 65,022 51 63,131 49 128,153 100 15 - 19 47,274 50 47,037 50 94,311 100 20 - 24 33,005 44 42,356 56 75,361 100 25 - 29 29,388 45 35,733 55 65,121 100 30 - 34 28,779 48 31,479 52 60,259 100 35 - 39 23,264 48 25,396 52 48,660 100 40 - 44 20,803 53 18,285 47 39,087 100 45 - 49 14,503 51 14,002 49 28,504 100 50 - 54 11,783 47 13,401 53 25,184 100 55 - 59 9,615 51 9,352 49 18,968 100 60 - 64 8,432 51 8,191 49 16,624 100 65 - 69 7,675 52 7,201 48 14,876 100 70 - 74 6,752 59 4,701 41 11,453 100 75 - 79 3,187 63 1,865 37 5,052 100 80 - 84 2,365 66 1,241 34 3,606 100 Above 85 1,221 44 1,571 56 2,792 100 Total 438,796 49 452,866 51 891,662 100 Number % Number % Number % Less than 4 62,317 14 64,189 14 126,506 14 05 - 09 63,411 14 63,734 14 127,146 14 10 - 14 65,022 15 63,131 14 128,153 14 15 - 19 47,274 11 47,037 10 94,311 11 20 - 24 33,005 8 42,356 9 75,361 8 25 - 29 29,388 7 35,733 8 65,121 7 30 - 34 28,779 7 31,479 7 60,259 7 35 - 39 23,264 5 25,396 6 48,660 5 40 - 44 20,803 5 18,285 4 39,087 4 45 - 49 14,503 3 14,002 3 28,504 3 50 - 54 11,783 3 13,401 3 25,184 3 55 - 59 9,615 2 9,352 2 18,968 2 60 - 64 8,432 2 8,191 2 16,624 2 65 - 69 7,675 2 7,201 2 14,876 2 70 - 74 6,752 2 4,701 1 11,453 1 75 - 79 3,187 1 1,865 0 5,052 1 80 - 84 2,365 1 1,241 0 3,606 0 Above 85 1,221 0 1,571 0 2,792 0 Total 438,796 100 452,866 100 891,662 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 131 Number % Number % Number % Tunduru 107,710 49 110,626 51 218,336 100 Songea Rural 71,487 50 70,183 50 141,670 100 Mbinga 167,019 49 176,141 51 343,160 100 Songea Urban 16,819 50 16,549 50 33,368 100 Namtumbo 75,761 49 79,367 51 155,128 100 Total 438,796 49 452,866 51 891,662 100 Number % Number % Number % Number % Number % Tunduru 119,349 63.3 1,460 0.8 105 0.1 67,557 35.8 188,472 100 Songea Rural 90,934 74.5 4,435 3.6 77 0.1 26,688 21.9 122,134 100 Mbinga 217,425 73.7 18,116 6.1 0 0.0 59,370 20.1 294,911 100 Songea Urban 23,106 78.7 1,337 4.6 0 0.0 4,904 16.7 29,347 100 Namtumbo 92,540 71.0 4,902 3.8 145 0.1 32,706 25.1 130,292 100 Total 543,354 71.0 30,250 4.0 327 0.0 191,226 25.0 765,156 100 Number % Number % Number % Number % Tunduru 48,507 26 79,091 42 60,873 32 188,472 100 Songea Rural 37,861 31 65,226 53 19,047 16 122,134 100 Mbinga 90,889 31 160,895 55 43,127 15 294,911 100 Songea Urban 10,688 36 15,502 53 3,157 11 29,347 100 Namtumbo 39,758 31 64,470 49 26,065 20 130,292 100 Total 227,703 30 385,184 50 152,269 20 765,156 100 Number % Number % Number % Number % Number % Tunduru 111,709 59 0 0 0 0 0 0 1,215 1 Songea Rural 68,463 56 1,213 1 0 0 0 0 905 1 Mbinga 167,881 57 1,343 0 259 0 3,480 1 2,624 1 Songea Urban 13,452 46 80 0 0 0 0 0 490 2 Namtumbo 76,107 58 217 0 0 0 69 0 718 1 Total 437,613 57 2,854 0 259 0 3,550 0 5,953 1 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By District School Attendancy Attending School Completed School Total 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, District Main Activity p Farming p g Herding Livestock Pastoralist Fishing Parastatal Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 132 Number % Number % Number % Number % Number % Tunduru 1,237 1 660 0 1,328 1 1,739 1 422 0 Songea Rural 1,367 1 1,218 1 994 1 454 0 304 0 Mbinga 2,713 1 129 0 1,799 1 500 0 626 0 Songea Urban 648 2 627 2 1,027 4 216 1 109 0 Namtumbo 644 0 575 0 72 0 285 0 141 0 Total 6,609 1 3,207 0 5,221 1 3,195 0 1,603 0 Number % Number % Number % Number % Number % Number % Tunduru 315 0 703 0 46,197 25 21,921 12 1,024 1 188,472 100 Songea Rural 228 0 230 0 36,642 30 10,042 8 73 0 122,134 100 Mbinga 388 0 1,543 1 85,860 29 25,248 9 518 0 294,911 100 Songea Urban 27 0 511 2 10,121 34 1,956 7 82 0 29,347 100 Namtumbo 72 0 284 0 37,392 29 13,357 10 358 0 130,292 100 Total 1,031 0 3,270 0 216,213 28 72,523 9 2,055 0 765,156 100 Number % Number % Number % Number % Number % Tunduru 106,478 56 4,442 2 51,740 27 25,812 14 188,472 100 Songea Rural 68,155 56 4,258 3 37,943 31 11,777 10 122,134 100 Mbinga 168,834 57 4,769 2 84,808 29 36,500 12 294,911 100 Songea Urban 13,312 45 2,248 8 11,854 40 1,933 7 29,347 100 Namtumbo 74,736 57 1,646 1 40,593 31 13,316 10 130,292 100 Total 431,515 56 17,363 2 226,938 30 89,339 12 765,156 100 cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Not Working & Available cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Other Total 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 133 Number % Number % Number % Number % Number % Tunduru 106 0 0 0 1,250 2 1,879 2 7,452 9 Songea Rural 306 0 378 1 989 2 2,198 3 12,839 20 Mbinga 503 0 1,011 1 4,146 3 2,606 2 23,293 14 Songea Urban 27 0 55 0 355 2 300 2 2,070 13 Namtumbo 217 0 359 1 648 1 1,078 2 7,831 12 Total 1,159 0 1,803 0 7,388 2 8,061 2 53,485 14 Number % Number % Number % Number % Number % Tunduru 2,008 3 2,583 3 59,324 75 213 0 103 0 Songea Rural 1,130 2 832 1 43,151 66 760 1 669 1 Mbinga 2,050 1 1,670 1 114,611 71 1,580 1 503 0 Songea Urban 82 1 270 2 11,061 71 356 2 107 1 Namtumbo 864 1 1,369 2 48,363 75 355 1 363 1 Total 6,134 2 6,725 2 276,511 72 3,264 1 1,745 0 Pre-Form One Number % Number % Number % Number % Number % Tunduru 0 0 0 0 105 0 105 0 924 1 Songea Rural 0 0 76 0 226 0 0 0 1,211 2 Mbinga 781 0 512 0 1,410 1 386 0 4,360 3 Songea Urban 0 0 55 0 55 0 81 1 408 3 Namtumbo 72 0 215 0 357 1 362 1 1,005 2 Total 853 0 858 0 2,154 1 934 0 7,908 2 Number % Number % Number % Number % Number % Tunduru 0 0 107 0 621 1 2,311 3 79,091 100 Songea Rural 0 0 0 0 77 0 384 1 65,226 100 Mbinga 132 0 237 0 840 1 264 0 160,895 100 Songea Urban 0 0 82 1 27 0 109 1 15,502 100 Namtumbo 0 0 69 0 217 0 724 1 64,470 100 Total 132 0 496 0 1,783 0 3,791 1 385,184 100 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Under Standard One Standard One Standard Two Standard Three Standard Four cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Standard Five Standard Six Standard Seven Standard Eight Training After Primary Education cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Form One Form Two Form Three Form Four cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Form Five Form Six Training After Secondary Education Adult Education Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 134 Number % Average Household Size Number % Average Household Size Number % Tunduru 40,976 87 5 5,922 13 4 46,898 100 5 Songea Rural 25,232 82 5 5,540 18 4 30,772 100 5 Mbinga 65,745 85 5 11,701 15 4 77,447 100 4 Songea Urban 5,852 84 5 1,090 16 4 6,943 100 5 Namtumbo 26,542 91 5 2,573 9 4 29,115 100 5 Total 164,347 86 5 26,827 14 4 191,175 100 5 Number Percent Number Percent Number Percent Number Percent Tunduru 17,359 67 6,511 25 2,164 8 26,034 100 Songea Rural 13,452 59 7,221 32 2,135 9 22,808 100 Mbinga 30,267 57 18,378 35 4,452 8 53,097 100 Songea Urban 3,209 56 1,742 31 740 13 5,691 100 Namtumbo 9,853 54 6,388 35 2,074 11 18,315 100 Total 74,141 59 40,239 32 11,565 9 125,945 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Tunduru 12,755 31,110 0 729 311 1,993 46,898 Songea Rural 4,024 24,943 519 902 77 307 30,772 Mbinga 8,676 62,636 503 4,638 730 264 77,447 Songea Urban 706 5,666 27 435 27 81 6,943 Namtumbo 4,367 22,873 218 1,151 145 362 29,115 Total 30,529 147,227 1,267 7,854 1,290 3,007 191,175 Mean Median Mode Mean Median Mode Mean Median Mode Tunduru 43 40 30 44 42 45 43.4 40 30 Songea Rural 44 41 30 48 44 40 45.0 42 30 Mbinga 40 37 28 49 49 50 41.2 38 28 Songea Urban 44 42 35 48 48 50 44.9 43 35 Namtumbo 42 39 30 44 41 35 42.6 40 30 Total 42 39 30 47 45 40 42.7 40 30 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Househol d Size 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Median, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 135 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 147,966 153,884 159,880 193,242 189,665 164,347 Female Heads 14,109 22,335 22,286 23,024 22,692 26,827 Total 162,075 176,219 182,166 216,266 212,357 191,175 Male headed (Percentage) 91 87 88 89 89 86 Female headed (Percentage) 9 13 12 11 11 14 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Tunduru 31,049 3,103 34,151 9,927 2,820 12,746 40,976 5,922 46,898 Songea Rural 22,267 3,951 26,218 2,965 1,589 4,554 25,232 5,540 30,772 Mbinga 58,988 8,887 67,875 6,758 2,814 9,572 65,745 11,701 77,447 Songea Urban 5,501 709 6,210 352 381 733 5,852 1,090 6,943 Namtumbo 22,666 1,721 24,388 3,876 852 4,728 26,542 2,573 29,115 Total 140,471 18,371 158,841 23,877 8,457 32,333 164,347 26,827 191,175 3.14 Time Series of Male and Female Headed Households 3.15 Literacy Rate of Heads of Households by Sex and District Literacy District Know Don't know Total Tanzania Agriculture Sample Census - 2003 Ruvuma 136 Appendix II 137 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 138 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 1,583 3 43,448 76 6,799 12 793 1 2,881 5 311 1 1,136 2 57,050 Songea Rural 4,028 10 27,214 69 2,719 7 1,208 3 2,350 6 230 1 1,526 4 39,372 Mbinga 2,376 2 68,928 64 14,257 13 7,009 6 8,513 8 384 0 6,341 6 107,903 Songea Urban 567 5 5,751 53 1,498 14 540 5 867 8 409 4 1,178 11 10,898 Namtumbo 217 1 27,171 85 1,289 4 288 1 1,580 5 289 1 1,151 4 32,080 Total 8,770 4 172,512 70 26,563 11 9,839 4 16,190 7 1,624 1 11,332 5 246,926 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Tunduru 6,850 180,902 16,512 1,526 3,320 452 1,182 210,743 Songea Rural 12,201 109,889 5,974 1,183 1,704 93 968 132,013 Mbinga 9,375 220,227 28,460 4,495 6,078 129 13,839 282,603 Songea Urban 728 13,191 1,997 381 677 210 835 18,019 Namtumbo 702 140,892 4,088 468 2,629 387 6,726 155,891 Total 29,855 665,101 57,032 8,052 14,408 1,270 23,550 799,269 % 4 83 7 1 2 0 3 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Land Access Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Total Number of Households 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 139 LAND USE Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 140 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Total Number of Households Tunduru 40,827 9,497 29,504 6,632 29,622 316 8,616 3,748 103 413 735 14,390 144,403 Songea Rural 27,886 10,123 16,167 3,486 11,674 1,520 13,483 10,167 9,887 2,105 2,735 11,780 121,013 Mbinga 66,798 20,913 51,788 33,488 6,657 7,438 31,030 14,906 25,154 5,536 8,787 25,251 297,744 Songea Urban 5,748 3,718 3,019 1,614 2,805 190 355 272 2,865 217 299 3,267 24,368 Namtumbo 27,764 10,419 18,865 3,089 6,077 999 11,350 10,491 2,357 1,663 3,669 17,477 114,220 Total 169,022 54,671 119,342 48,308 56,836 10,463 64,835 39,584 40,366 9,933 16,224 72,165 701,748 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Tunduru 35,322 10,806 60,306 10,426 42,189 299 10,944 10,999 125 357 1,296 27,636 210,704 Songea Rural 38,149 7,409 8,107 1,901 9,735 1,891 15,741 24,025 2,108 2,544 3,344 17,060 132,013 Mbinga 78,902 14,927 40,236 24,198 6,631 5,494 30,558 21,625 6,472 5,002 14,919 33,637 282,603 Songea Urban 5,463 2,458 1,405 595 1,992 145 277 191 1,023 368 173 3,930 18,019 Namtumbo 47,161 10,871 10,431 2,329 5,499 1,399 14,368 22,682 1,264 2,495 4,565 32,827 155,891 Total 204,996 46,471 120,484 39,451 66,045 9,228 71,887 79,522 10,991 10,766 24,297 115,091 799,230 % 26 6 15 5 8 1 9 10 1 1 3 14 100 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Type of Land Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 141 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Tunduru 22,329 48 24,569 52 46,898 100 Tunduru 39,708 85 7,190 15 46,898 100 Songea Rural 4,790 16 25,982 84 30,772 100 Songea Rural 24,176 79 6,596 21 30,772 100 Mbinga 24,824 32 52,491 68 77,315 100 Mbinga 52,305 68 25,010 32 77,315 100 Songea Urban 3,051 44 3,891 56 6,943 100 Songea Urban 4,482 65 2,461 35 6,943 100 Namtumbo 4,447 15 24,668 85 29,115 100 Namtumbo 23,749 82 5,366 18 29,115 100 Total 59,442 31 131,601 69 191,043 100 Total 144,421 76 46,622 24 191,043 100 Number Percent Number Percent Number Percent Tunduru 9,341 20 37,557 80 46,898 100 Songea Rural 5,306 17 25,466 83 30,772 100 Mbinga 10,647 14 66,668 86 77,315 100 Songea Urban 1,037 15 5,906 85 6,943 100 Namtumbo 2,862 10 26,253 90 29,115 100 Total 29,192 15 161,851 85 191,043 100 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Ruvuma 142 Appendix II 143 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 144 Number of household Planted area (hectare) Number of household Planted Area (hectare) Tunduru 0 0 46,589 84,544 84,544 0.00 Songea Rural 0 0 30,696 61,969 61,969 0.00 Mbinga 0 0 73,950 130,386 130,386 0.00 Songea Urban 0 0 6,943 10,920 10,920 0.00 Namtumbo 72 110 28,970 70,275 70,385 0.16 Total 72 110 187,149 358,093 358,203 0.03 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Tunduru 0 46,589 46,589 0 46,589 Songea Rural 0 30,696 30,696 0 30,696 Mbinga 0 73,950 73,950 0 73,950 Songea Urban 0 6,943 6,943 0 6,943 Namtumbo 72 28,970 28,970 72 29,043 Total 72 187,149 187,149 72 187,221 District Dry Season Wet Season Total Number of Crop Growing Households 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Dry Season Wet Season 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area planted in Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 145 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 37 29 790 139,505 179,283 1,285 139,541 179,312 1,285 Paddy 29 4 124 38,178 39,510 1,035 38,207 39,514 1,034 Sorghum 0 0 0 2,079 961 462 2,079 961 462 Bulrush Millet 0 0 0 38 13 345 38 13 345 Finger Millet 0 0 0 10,287 6,046 588 10,287 6,046 588 Wheat 0 0 0 4,036 1,652 409 4,036 1,652 409 Barley 0 0 0 22 16 741 22 16 741 CEREALS 66 33 494 194,145 227,482 1,172 194,211 227,514 1,171 Cassava 0 0 0 87,522 101,965 1,165 87,522 101,965 1,165 Sweet Potatoes 0 0 0 6,316 13,950 2,209 6,316 13,950 2,209 Irish Potatoes 0 0 0 143 223 1,563 143 223 1,563 Yams 0 0 0 96 173 1,803 96 173 1,803 Cocoyam 0 0 0 446 876 1,965 446 876 1,965 ROOTS & TUBERS 0 0 94,522 117,187 1,240 94,522 117,187 1,240 Mung Beans 0 0 0 73 34 458 73 34 458 Beans 0 0 0 34,237 15,059 440 34,237 15,059 440 Cowpeas 0 0 0 2,438 821 337 2,438 821 337 Green Gram 0 0 0 138 37 270 138 37 270 Pigeon Peas 0 0 0 51 3 51 51 3 51 Chich Peas 0 0 0 . . 0 . . 0 Bambaranuts 0 0 2,570 1,126 438 2,570 1,126 438 Field Peas 0 0 0 189 154 814 189 154 814 PULSES 0 0 0 39,697 17,234 434 39,697 17,234 434 Sunflower 0 0 49 796 399 501 796 399 501 Simsim 0 0 0 6,279 2,376 378 6,279 2,376 378 Groundnuts 29 1 49 9,532 4,731 496 9,561 4,732 495 Soya Beans 0 0 0 828 246 297 828 246 297 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 29 1 49 17,435 7,751 17,464 7,752 444 Okra 0 0 0 3 45 16,134 3 45 16,134 Radish 0 0 0 7 2 267 7 2 267 Onions 0 0 0 585 1,704 2,915 585 1,704 2,915 Cabbage 7 11 1,482 1,209 4,109 3,397 1,217 4,119 3,386 Tomatoes 0 0 0 1,927 7,328 3,804 1,927 7,328 3,804 Spinnach 0 0 0 465 854 1,837 465 854 1,837 Carrot 0 0 0 72 21 294 72 21 294 Chillies 0 0 0 27 28 1,007 27 28 1,007 Amaranths 7 8 1,087 349 854 2,449 356 862 2,421 Pumpkins 0 0 0 448 1,048 2,342 448 1,048 2,342 Cucumber 0 0 0 22 27 1,219 22 27 1,219 Egg Plant 0 0 0 12 48 3,987 12 48 3,987 FRUITS & VEGETABLES 15 19 1,284 5,125 16,068 3,135 5,139 16,087 3,130 Seaweed 0 0 0 0 0 0 0 0 Cotton 0 0 0 0 0 0 0 0 Tobacco 0 0 0 7,169 4,371 610 7,169 4,371 Pyrethrum 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 CASH CROPS 0 0 0 7,169 4,371 610 7,169 4,371 Total 110 1,725 1,761 358,093 258,478 393 358,203 260,203 395 *The total area planted include the sum of the planted area for both Wet and Dry Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Wet Season to estimate physical land area under production to different crops 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Ruvuma Region Crop Dry season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 146 Number of Households Planted area (ha) Number of Households Planted area (ha) CEREALS 145 66 308,200 194,145 194,211 Maize 72 37 178,837 139,505 139,541 0 Paddy 72 29 81,184 38,178 38,207 0 Sorghum 0 0 7,711 2,079 2,079 0 Bulrush Millet 0 0 313 38 38 0 Finger Millet 0 0 30,738 10,287 10,287 0 Wheat 0 0 9,309 4,036 4,036 0 Barley 0 0 107 22 22 0 ROOTS & TUBERS 0 0 179,886 94,522 94,522 0 Cassava 0 0 137,409 87,522 87,522 0 Sweet Potatoes 0 0 35,326 6,316 6,316 0 Irish Potatoes 0 0 1,618 143 143 0 Yams 0 0 952 96 96 0 Cocoyam 0 0 4,582 446 446 0 PULSES 0 0 117,582 39,697 39,697 0 Mung Beans 0 0 145 73 73 0 Beans 0 0 86,699 34,237 34,237 0 Cowpeas 0 0 12,806 2,438 2,438 0 Green Gram 0 0 1,027 138 138 0 Pigeon Peas 0 0 145 51 51 0 Chich Peas 0 0 0 . 0 0 Bambaranuts 0 0 16,049 2,570 2,570 0 Field Peas 0 0 711 189 189 0 OIL SEEDS & OIL NUTS 72 29 66,052 17,435 17,464 0.2 Sunflower 0 0 3,537 796 796 0.0 Simsim 0 0 21,421 6,279 6,279 0.0 Groundnuts 72 29 39,839 9,532 9,561 0.3 Soya Beans 0 0 1,255 828 828 0.0 Castor Seed 0 0 0 . 0 0.0 FRUITS & VEGETABLES 145 15 42,583 5,125 5,140 0 Okra 0 0 27 3 3 0 Radish 0 0 73 7 7 0 Turmeric 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 Onions 0 0 4,075 585 585 0 Ginger 0 0 0 0 0 0 Cabbage 72 7 10,900 1,209 1,217 1 Tomatoes 0 0 13,606 1,927 1,927 0 Spinnach 0 0 4,367 465 465 0 Carrot 0 0 130 72 72 0 Chillies 0 0 241 27 27 0 Amaranths 72 7 3,950 349 356 2 Pumpkins 0 0 4,866 448 448 0 Cucumber 0 0 221 22 22 0 Egg Plant 0 0 127 12 12 0 Water Mellon 0 0 0 0 0 0 Cauliflower 0 0 0 0 0 0 Total 72 110 763,656 358,093 358,203 0 Total Area Planted Dry & Wet Season % Area Planted in Dry Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Ruvuma Region Wet Season Dry Season Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 147 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 203 173 829 1,405 45,558 60,541 46,589 62,119 Songea Rural 460 435 1,438 2,095 28,798 48,170 30,696 50,700 Mbinga 2,840 3,408 3,471 4,907 67,639 82,466 73,950 90,781 Songea Urban 357 292 162 134 6,423 8,326 6,943 8,752 o 72 217 1,003 2,268 27,968 56,441 29,042 58,927 Total 3,931 4,525 6,903 10,809 176,387 255,944 187,221 271,279 % 2 4 94 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 o 1,150 2,277 143 394 5,612 12,450 22,282 55,265 29,187 70,385 Total 13,938 29,470 1,671 3,591 23,710 43,402 151,614 281,740 190,933 358,203 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Tunduru 30,899 60,879 15,893 23,665 46,792 84,544 72.01 Songea Rural 20,996 44,231 9,700 17,738 30,696 61,969 71.38 Mbinga 43,932 73,755 33,383 56,630 77,315 130,386 56.57 Songea Urban 5,154 8,774 1,788 2,146 6,943 10,920 80.35 Namtumb o 18,971 49,669 10,145 20,606 29,115 70,275 70.68 Total 119,953 237,308 70,909 120,785 190,861 358,093 66.27 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year % of Area Planted Under Irrigation District Irrigation Use Households Using Households not Using Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Ruvuma District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Wet & Dry Season, Ruvuma District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 148 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 3,526 8,397 43,267 76,147 46,792 84,544 9.93 Songea Rural 4,462 10,713 26,234 51,256 30,696 61,969 17.29 Mbinga 22,527 43,482 54,788 86,903 77,315 130,386 33.35 Songea Urban 2,486 5,236 4,457 5,684 6,943 10,920 47.95 Namtumbo 4,254 11,130 24,934 59,255 29,187 70,385 15.81 Total 37,254 78,958 153,679 279,245 190,933 358,203 22.04 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 636 2,244 46,156 82,300 46,792 84,544 2.65 Songea Rural 76 170 30,620 61,799 30,696 61,969 0.27 Mbinga 1,531 3,264 75,784 127,121 77,315 130,386 2.50 Songea Urban 82 195 6,860 10,725 6,943 10,920 1.78 Namtumbo 145 248 29,042 70,137 29,187 70,385 0.35 Total 2,471 6,121 188,462 352,082 190,933 358,203 1.71 % 1.3 1.7 98.7 98.3 100 100 % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 149 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 2,273 4,588 44,519 79,956 46,792 84,544 5.43 Songea Rural 909 2,335 29,787 59,634 30,696 61,969 3.77 Mbinga 3,377 6,915 73,937 123,470 77,315 130,386 5.30 Songea Urban 411 904 6,532 10,015 6,943 10,920 8.28 Namtumbo 939 2,689 28,248 67,697 29,187 70,385 3.82 Total 7,910 17,431 183,024 340,772 190,933 358,203 4.87 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 1,973 3,088 44,616 59,141 46,589 62,119 4.97 Songea Rural 5,254 11,165 25,442 39,535 30,696 50,700 22.02 Mbinga 7,487 11,609 66,463 79,172 73,950 90,781 12.79 Songea Urban 1,394 1,993 5,549 6,760 6,943 8,752 22.77 Namtumbo 2,809 7,354 26,305 51,683 29,114 59,037 12.46 Total 18,917 35,208 168,376 236,181 187,293 271,388 12.97 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Improved Seeds District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Ruvuma 150 Appendix II 151 ANNUAL CROP & VEGETABLES PRODUCTION DRY SEASON Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 72 110 72 110 Total 0 0 0 0 72 110 72 110 % 0 0 0 0 100 100 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 72 110 0 0 72 110 Total 72 110 0 0 72 110 % 0 0 0 0 100 100 0 0 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 % 0 0 100 100 100 100 Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - DRY SEASON, Ruvuma Region. District Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Tractor Ploughing Soil Preparation 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - DRY SEASON, Ruvuma Region District % of planted area under irrigation in dry season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Dry Season, 2002/03 Agriculture Year, Ruvuma Region Irrigation Use Households Using Irrigation Households Not Using Irrigation Total District Fertilizer Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 72 110 72 110 0 % of Planted Area Using Insecticides Household Using Insecticides 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Dry Season. Households Not Using Insecticides Total Insecticide Use Households Not Using Herbicidess Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Dry Season. Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 . 72 110 72 110 0 Total 0 . 72 110 72 110 0 % 0 0 100 100 100 100 0 7.1f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season. Fungicide Use % of Planted Area Using Fungicides Household Using Fungicides Households Not Using Fungicides Total % of Planted Area Using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - DRY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 155 ANNUAL CROP & VEGETABLES PRODUCTION WET SEASON Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 203 173 829 1,405 45,558 60,541 46,589 62,119 Songea Rural 460 435 1,438 2,095 28,798 48,170 30,696 50,700 Mbinga 2,840 3,408 3,471 4,907 67,639 82,466 73,950 90,781 Songea Urban 357 292 162 134 6,423 8,326 6,943 8,752 Namtumbo 72 217 1,003 2,268 27,896 56,331 28,970 58,817 Total 3,931 4,525 6,903 10,809 176,315 255,834 187,149 271,169 % 2 2 4 4 94 94 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 Namtumbo 1,150 2,277 143 394 5,540 12,340 22,282 55,265 29,115 70,275 Total 13,938 29,470 1,671 3,591 23,638 43,292 151,614 281,740 190,861 358,093 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 30,899 60,879 15,893 23,665 46,792 84,544 72 Songea Rural 20,996 44,231 9,700 17,738 30,696 61,969 71 Mbinga 43,932 73,755 33,383 56,630 77,315 130,386 57 Songea Urban 5,154 8,774 1,788 2,146 6,943 10,920 80 Namtumbo 18,971 49,669 10,145 20,606 29,115 70,275 71 Total 119,953 237,308 70,909 120,785 190,861 358,093 66 % 63 66 37 34 100 100 66 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, Ruvuma Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, Ruvuma Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of planted area under irrigation in dry season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, Ruvuma Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 3,526 8,397 43,267 76,147 46,792 84,544 10 Songea Rural 4,462 10,713 26,234 51,256 30,696 61,969 17 Mbinga 22,527 43,482 54,788 86,903 77,315 130,386 33 Songea Urban 2,486 5,236 4,457 5,684 6,943 10,920 48 Namtumbo 4,254 11,130 24,862 59,145 29,115 70,275 16 Total 37,254 78,958 153,607 279,135 190,861 358,093 22 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 636 2,244 46,156 82,300 46,792 84,544 2.65 Songea Rural 76 170 30,620 61,799 30,696 61,969 0.27 Mbinga 1,531 3,264 75,784 127,121 77,315 130,386 2.50 Songea Urban 82 195 6,860 10,725 6,943 10,920 1.78 Namtumbo 145 248 28,970 70,027 29,115 70,275 0.35 Total 2,471 6,121 188,390 351,972 190,861 358,093 1.71 % 1.3 1.7 98.7 98.3 100 100 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 2,273 4,588 44,519 79,956 46,792 84,544 5 Songea Rural 909 2,335 29,787 59,634 30,696 61,969 4 Mbinga 3,377 6,915 73,937 123,470 77,315 130,386 5 Songea Urban 411 904 6,532 10,015 6,943 10,920 8 Namtumbo 939 2,689 28,176 67,587 29,115 70,275 4 Total 7,910 17,431 182,952 340,662 190,861 358,093 5 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 1,973 3,088 44,616 59,141 46,589 62,119 5 Songea Rural 5,254 11,165 25,442 39,535 30,696 50,700 22 Mbinga 7,487 11,609 66,463 79,172 73,950 90,781 13 Songea Urban 1,394 1,993 5,549 6,760 6,943 8,752 23 Namtumbo 2,809 7,354 26,233 51,573 29,042 58,927 12 Total 18,917 35,208 168,304 236,071 187,221 271,278 13 % 10 13 90 87 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under irrigation in dry season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 159 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 44,152 31,867 320,540 140,886 3,444 203 87,597 18,312 15,889 2,346 471,622 193,613 Maize 34,027 23,928 126,531 100,018 77 76 16,064 13,801 1,725 1,249 178,423 139,073 Paddy 7,506 4,424 65,147 29,681 104 127 6,568 2,966 1,728 946 81,054 38,143 Sorghum 4,023 1,238 3,518 795 0 . 171 46 0 . 7,711 2,079 Bulrush Millet 0 . 313 38 0 . 0 . 0 . 313 38 Finger Millet 5,460 2,198 19,749 6,382 0 . 4,751 1,490 438 151 30,397 10,222 Wheat 128 78 9,104 3,950 0 . 77 8 0 . 9,309 4,036 Barley 0 . 107 22 0 . 0 . 0 . 107 22 ROOTS & TUBERS 1,661 514 10,730 6,732 0 0 3,244 277 703 21 16,338 7,544 Cassava 132 107 1,075 474 0 . 148 16 0 . 1,355 598 Sweet Potatoes 1,729 403 31,790 5,595 0 . 1,414 256 155 21 35,087 6,275 Irish Potatoes 77 3 1,541 139 0 . 0 . 0 . 1,618 143 Yams 0 . 845 91 0 . 107 5 0 . 952 96 Cocoyam 0 . 4,450 432 0 . 0 . 0 . 4,450 432 PULSES 2,655 5,469 40,432 30,934 228 81 10,548 2,818 2,179 160 56,043 39,461 Mung Beans 0 . 145 73 0 . 0 . 0 . 145 73 Beans 6,884 3,092 71,823 28,030 205 81 7,261 2,681 206 118 86,378 34,001 Cowpeas 6,578 1,342 5,955 1,057 0 . 171 19 103 21 12,806 2,438 Green Gram 0 . 1,027 138 0 . 0 . 0 . 1,027 138 Pigeon Peas 0 . 145 51 0 . 0 . 0 . 145 51 Chich Peas 0 . 0 . 0 . 0 . 0 . 0 . Bambaranuts 6,362 1,036 8,852 1,407 0 . 732 107 103 21 16,049 2,570 Field Peas 0 . 683 178 0 . 27 11 0 . 711 189 OIL SEEDS & OIL NUTS 3,540 12,044 44 1,716 27 17,371 Sunflower 153 22 2,777 669 0 . 295 59 74 7 3,299 757 Simsim 2,585 633 14,924 4,545 145 44 3,489 1,011 98 20 21,240 6,254 Groundnuts 11,188 2,855 26,462 6,241 0 . 2,189 436 0 . 39,839 9,532 Soya Beans 75 30 644 588 0 . 536 209 0 . 1,255 828 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 220 4,639 0 236 0 5,095 Okra 0 . 27 3 0 . 0 . 0 . 27 3 Radish 0 . 73 7 0 . 0 . 0 . 73 7 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 0 . 0 . 0 . 0 . 0 . Garlic 0 . 0 . 0 . 0 . 0 . 0 . Onions 324 45 3,647 530 0 . 103 10 0 . 4,075 585 Ginger 0 . 0 . 0 . 0 . 0 . 0 . Cabbage 311 19 10,178 1,147 0 . 273 28 0 . 10,763 1,193 Tomatoes 437 87 12,395 1,738 0 . 719 88 0 . 13,551 1,913 Spinnach 273 22 3,558 365 0 . 536 78 0 . 4,367 465 Carrot 76 2 55 70 0 . 0 . 0 . 130 72 Chillies 0 . 241 27 0 . 0 . 0 . 241 27 Amaranths 176 8 3,697 333 0 . 77 8 0 . 3,950 349 Pumpkins 318 39 4,244 383 0 . 305 26 0 . 4,866 448 Cucumber 0 . 221 22 0 . 0 . 0 . 221 22 Egg Plant 0 . 127 12 0 . 0 . 0 . 127 12 Water Mellon 0 . 0 . 0 . 0 . 0 . 0 . Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 2,285 4,390 0 465 14 7,154 Seaweed 0 . 0 . 0 . 0 . 0 . 0 . Cotton 0 . 0 . 0 . 0 . 0 . 0 . Tobacco 4,287 2,285 8,184 4,390 0 . 1,122 465 71 14 13,664 7,154 Pyrethrum 0 . 0 . 0 . 0 . 0 . 0 . Jute 0 . 0 . 0 . 0 . 0 . 0 . Total 65,890 43,895 512,020 199,624 5,294 327 143,652 23,824 27,829 2,568 754,685 270,238 % 16 74 0 9 1 100 Crop Table 7.2h: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 160 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 43,774 27,246 18,891 0.693 27,246 18,891 0.693 Songea Rural 0 0 0 0.000 30,316 28,503 47,070 1.651 28,503 47,070 1.651 Mbinga 0 0 0 0.000 69,226 50,346 65,950 1.310 50,346 65,950 1.310 Songea Urban 0 0 0 0.000 6,833 4,600 6,655 1.447 4,600 6,655 1.447 Namtumbo 72 37 29 0.790 28,688 28,809 40,718 1.413 28,846 40,747 1.413 Total 72 37 29 0.790 178,837 139,505 179,283 1.285 139,541 179,312 1.285 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 107 13 3 0.222 13 3 0.222 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 206 25 10 0.409 25 10 0.409 Total 0 0 0 0.000 313 38 13 0.345 38 13 0.345 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 36,922 19,750 15,811 0.801 19,750 15,811 0.801 Songea Rural 0 0 0 0.000 14,641 6,187 7,676 1.241 6,187 7,676 1.591 Mbinga 0 0 0 0.000 9,753 3,721 3,037 0.816 3,721 3,037 1.591 Songea Urban 0 0 0 0.000 3,033 1,080 1,105 1.023 1,080 1,105 1.023 Namtumbo 72 29 4 0.000 16,835 7,440 11,881 1.597 7,470 11,884 1.591 Total 72 29 4 0.000 81,184 38,178 39,510 1.035 38,207 39,514 1.034 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 6,168 1,845 850 0.461 1,845 850 0.461 Songea Rural 0 0 0 0.000 150 15 3 0.220 15 3 0.220 Mbinga 0 0 0 0.000 255 38 42 1.092 38 42 1.092 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 1,139 180 65 0.363 180 65 0.363 Total 0 0 0 0.000 7,711 2,079 961 0.462 2,079 961 0.462 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Burlush millet District Dry Season Wet Season Total Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and Paddy District Dry Season Wet Season Total Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season Sorghum District Dry Season Wet Season Total Wet Season Total Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and Maize District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 161 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 422 72 15 0.208 72 15 0.208 Songea Rural 0 0 0 0.000 10,031 2,941 1,752 0.771 2,941 1,752 0.596 Mbinga 0 0 0 0.000 7,854 3,504 2,404 0.771 3,504 2,404 0.686 Songea Urban 0 0 0 0.000 984 272 210 0.771 272 210 0.771 Namtumbo 0 0 0 0.000 11,447 3,497 1,665 0.476 3,497 1,665 0.476 Total 0 0 0 0.000 30,738 10,287 6,046 0.588 10,287 6,046 0.588 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 3,756 1,812 706 0.389 1,812 706 0.389 Songea Rural 0 0 0 0.000 16,963 6,108 3,416 0.559 6,108 3,416 0.559 Mbinga 0 0 0 0.000 47,031 20,544 8,272 0.403 20,544 8,272 0.403 Songea Urban 0 0 0 0.000 4,205 897 305 0.340 897 305 0.340 Namtumbo 0 0 0 0.000 14,744 4,877 2,360 0.484 4,877 2,360 0.484 Total 0 0 0 0.000 86,699 34,237 15,059 0.440 34,237 15,059 0.440 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 1,027 138 37 0.270 138 37 0.270 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 1,027 138 37 0.270 138 37 0.270 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 145 73 34 0.458 73 34 0.458 Total 0 0 0 0.000 145 73 34 0.458 73 34 0.458 Wet Season Total Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Dry Season Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung beans District Dry Season Wet Season Total Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Dry Season Wet Season Total Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 162 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 10,419 2,099 693 0.330 2,099 693 0.330 Songea Rural 0 0 0 0 305 39 13 0.321 39 13 0.321 Mbinga 0 0 0 0 132 13 3 0.198 13 3 0.198 Songea Urban 0 0 0 0 27 4 1 0.247 4 1 0.247 Namtumbo 0 0 0 0 1,923 282 112 0.397 282 112 0.397 Total 0 0 0 0 12,806 2,438 821 0.337 2,438 821 0.337 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 10,324 1,819 744 0.409 1,819 744 0.409 Songea Rural 0 0 0 0 1,809 256 118 0.462 256 118 0.462 Mbinga 0 0 0 0 1,424 158 75 0.474 158 75 0.474 Songea Urban 0 0 0 0 137 22 8 0.369 22 8 0.369 Namtumbo 0 0 0 0 2,354 314 180 0.574 314 180 0.574 Total 0 0 0 0 16,049 2,570 1,126 0.438 2,570 1,126 0.438 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 35,486 22,565 28,658 1.270 22,565 28,658 1.270 Songea Rural 0 0 0 0 22,595 11,465 12,309 1.074 11,465 12,309 1.074 Mbinga 0 0 0 0 51,931 39,712 45,044 1.134 39,712 45,044 1.134 Songea Urban 0 0 0 0 5,320 2,175 3,159 1.452 2,175 3,159 1.452 Namtumbo 0 0 0 0 22,077 11,605 12,795 1.103 11,605 12,795 1.103 Total 0 0 0 0 137,409 87,522 101,965 1.165 87,522 101,965 1.165 Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Dry Season Wet Season Total Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick peas District Dry Season Wet Season Total Table 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Dry Season Wet Season Total Wet Season Total Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Cowpeas District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 163 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 3,066 711 1,711 2.407 711 1,711 2.407 Songea Rural 0 0 0 0.000 5,249 817 2,640 3.231 817 2,640 3.231 Mbinga 0 0 0 0.000 23,166 3,648 6,763 0.000 3,648 6,763 1.854 Songea Urban 0 0 0 0.000 2,051 639 2,203 3.449 639 2,203 3.449 Namtumbo 0 0 0 0.000 1,794 501 634 1.265 501 634 1.265 Total 0 0 0 0.000 35,326 6,316 13,950 2.209 6,316 13,950 2.209 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 229 34 52 1.530 34 52 1.530 Mbinga 0 0 0 0.000 1,289 94 162 1.730 94 162 1.730 Songea Urban 0 0 0 0.000 27 7 4 0.545 7 4 0.545 Namtumbo 0 0 0 0.000 73 7 4 0.593 7 4 0.593 Total 0 0 0 0.000 1,618 143 223 1.563 143 223 1.563 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 15,342 4,088 2,001 0.489 4,088 2,001 0.489 Songea Rural 0 0 0 0.000 7,974 1,980 908 0.458 22,540 8,899 0.395 Mbinga 0 0 0 0.000 6,780 1,193 522 0.438 16,091 5,074 0.315 Songea Urban 0 0 0 0.000 849 225 227 1.009 28,042 12,472 0.445 Namtumbo 72 29 1 0.049 8,894 2,046 1,072 0.524 8,513 2,908 0.342 Total 72 29 1 0.049 39,839 9,532 4,731 0.496 79,274 31,353 0.396 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 831 174 119 0.684 174 119 0.684 Mbinga 0 0 0 0.000 1,924 404 176 0.436 404 176 0.436 Songea Urban 0 0 0 0.000 137 29 48 1.635 29 48 1.635 Namtumbo 0 0 0 0.000 645 189 56 0.296 189 56 0.296 Total 0 0 0 0.000 3,537 796 399 0.501 796 399 0.501 Wet Season Total Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Dry Season Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Dry Season Wet Season Total Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Dry Season Wet Season Total Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 164 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 2,619 747 264 0.354 747 264 0.354 Songea Rural 0 0 0 0 6,317 1,522 524 0.345 1,522 524 0.345 Mbinga 0 0 0 0 1,512 472 141 0.299 472 141 0.299 Songea Urban 0 0 0 0 82 11 5 0.418 11 5 0.418 Namtumbo 0 0 0 0 10,891 3,527 1,442 0.409 3,527 1,442 0.409 Total 0 0 0 0 21,421 6,279 2,376 0.378 6,279 2,376 0.378 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0 989 363 184 0.508 363 184 0.508 Mbinga 0 0 0 0 122 407 15 0.038 407 15 0.038 Songea Urban 0 0 0 0 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0 144 58 46 0.786 58 46 0.786 Total 0 0 0 0 1,255 828 246 0.297 828 246 0.297 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 801 75 163 2.177 75 163 2.177 Songea Rural 0 0 0 0 2,883 248 476 1.920 248 476 1.920 Mbinga 0 0 0 0 3,059 432 1,381 3.197 432 1,381 3.197 Songea Urban 0 0 0 0 1,782 201 1,181 5.872 201 1,181 5.872 Namtumbo 72 7 11 0 2,375 253 907 3.580 261 918 3.521 Total 72 7 11 0 10,900 1,209 4,109 3.397 1,217 4,119 3.386 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 27 3 45 16 3 45 16.134 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 27 3 45 16 3 45 16.134 Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya beans District Dry Season Wet Season Total Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Cabbage District Dry Season Wet Season Total Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Okra District Dry Season Wet Season Total Wet Season Total Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 165 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 73 7 2 0.267 7 2 0.267 Total 0 0 0 0 73 7 2 0.267 7 2 0.267 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 821 135 291 2.154 135 291 2.154 Songea Rural 0 0 0 0 686 51 204 3.975 51 204 3.975 Mbinga 0 0 0 0 757 158 93 0.589 158 93 0.589 Songea Urban 0 0 0 0 438 54 107 1.977 54 107 1.977 Namtumbo 0 0 0 0 1,372 186 1,010 5.418 186 1,010 5.418 Total 0 0 0 0 4,075 585 1,704 2.915 585 1,704 2.915 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 2,770 551 1,186 2.150 551 1,186 2.150 Songea Rural 0 0 0 0 1,898 202 681 3.376 202 681 3.376 Mbinga 0 0 0 0 4,799 632 2,207 3.491 632 2,207 3.491 Songea Urban 0 0 0 0 1,915 280 1,251 4.475 280 1,251 4.475 Namtumbo 0 0 0 0 2,224 262 2,004 7.652 262 2,004 7.652 Total 0 0 0 0 13,606 1,927 7,328 3.804 1,927 7,328 3.804 Wet Season Total Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Dry Season Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Dry Season Wet Season Total Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Dry Season Wet Season Total Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year Tumeric District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 104 8 7 0.865 8 7 0.865 Songea Rural 0 0 0 0 1,223 130 147 1.127 130 147 1.127 Mbinga 0 0 0 0 1,164 111 279 2.508 111 279 2.508 Songea Urban 0 0 0 0 298 53 53 0.995 53 53 0.995 Namtumbo 0 0 0 0 1,578 162 368 2.276 162 368 2.276 Total 0 0 0 0 4,367 465 854 1.837 465 854 1.837 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0 76 2 4 2.470 2 4 2.470 Mbinga 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0 55 70 17 0.247 70 17 0.247 Namtumbo 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 130 72 21 0.294 72 21 0.294 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 104 11 4 0.395 11 4 0.395 Songea Rural 0 0 0 0 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0 137 17 23 1.388 17 23 1.388 Namtumbo 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 241 27 28 1.007 27 28 1.007 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 1,011 102 116 1.131 102 116 1.131 Songea Rural 0 0 0 0 607 49 62 1.261 49 62 1.261 Mbinga 0 0 0 0 1,025 76 97 1.281 76 97 1.281 Songea Urban 0 0 0 0 516 45 217 4.839 45 217 4.839 Namtumbo 72 7 8 0 791 77 362 4.731 84 370 4.413 Total 72 7 8 0 3,950 349 854 2.449 356 862 2.421 Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year Carrot District Dry Season Wet Season Total Table 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year Chillies District Dry Season Wet Season Total Table 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Dry Season Wet Season Total Wet Season Total Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 167 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 168 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Sour Soup 252 252 21 82 Pigeon Pea 4,756 1,223 442 361 Star Fruit 20 20 18 889 Coconut 668 177 407 2,305 Cashewnut 71,527 51,947 8,827 170 Coffee 25 16 3 200 Sugarcane 373 152 4,467 29,423 Banana 1,022 604 1,684 2,789 Mango 401 132 824 6,233 Pawpaw 0 0 5 0 Orange 153 179 1,173 6,544 Mandarine/Tangerine 20 20 8 395 Guava 4 4 3 844 Lime/Lemon 6 6 5 906 Total 79,226 54,731 17,888 327 Pigeon Pea 15 15 3 221 Coconut 48 15 2 163 Cashewnut 451 19 8 420 Coffee 582 334 288 862 Sugarcane 238 386 2,980 7,722 Cinamon 12 12 3 278 Jack Fruit 0 0 0 0 Mpesheni 3 3 9 2,964 Banana 1,622 844 5,267 6,238 Avocado 0 0 50 0 Mango 340 159 10,904 68,477 Pawpaw 12 12 46 3,871 Pineapple 13 5 13 2,683 Orange 2,309 17 418 24,725 Grape Fruit 0 0 . 0 Mandarine/Tangerine 1 0 12 0 Guava 8 3 46 15,016 Plums 0 0 0 0 Lime/Lemon 0 0 16 0 Bilimbi 0 0 3 0 Total 5,655 1,825 20,070 10,994 Black Pepper 0 0 0 0 Malay Apple 0 0 2 0 Palm Oil 73 72 159 2,198 Coconut 186 20 120 6,125 Cashewnut 917 268 36 133 Sisal 104 104 71 679 Coffee 29,312 25,652 12,087 471 Kapok 0 0 . 0 Sugarcane 479 159 5,186 32,621 Jack Fruit 0 . 19 0 Banana 1,096 942 22,721 24,130 Avocado 249 43 95 2,229 Mango 449 470 6,136 13,064 Pawpaw 26 26 459 17,380 Pineapple 82 56 214 3,818 Orange 173 113 886 7,842 Grape 0 0 . 0 Mandarine/Tangerine 42 42 63 1,524 Guava 0 1 184 356,784 Plums 0 0 14 0 Apples 0 0 . 0 Pears 0 0 12 0 Pitches 0 0 278 0 District/Crop Songea Rural 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Tunduru Mbinga Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 169 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) District/Crop 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Lime/Lemon 0 0 4 0 Bilimbi 6 0 . 0 Total 33,195 27,966 48,746 1,743 Pigeon Pea 0 0 0 0 Star Fruit 3 3 10 3,444 Cashewnut 1 0 . 0 Coffee 42 28 10 343 Sugarcane 82 46 456 9,965 Cardamon 0 0 0 0 Jack Fruit 0 0 0 0 Banana 1,307 291 2,239 7,696 Avocado 0 0 5 0 Mango 82 93 2,891 30,952 Pawpaw 12 12 83 6,799 Pineapple 22 14 49 3,468 Orange 19 75 143 1,910 Grape 0 0 0 0 Mandarine/Tangerine 0 0 39 0 Guava 30 25 243 9,901 Plums 0 0 1 0 Apples 2 2 12 5,558 Pears 0 0 0 0 Lime/Lemon 0 0 78 0 Bilimbi 0 0 149 0 Total 1,603 589 6,410 10,879 Pigeon Pea 388 391 69 176 Palm Oil 59 29 2 62 Coconut 87 47 137 2,935 Cashewnut 1,228 473 407 861 Wattle 7 0 . 0 Sugarcane 310 440 2,173 4,937 Mpesheni 29 0 . 0 Banana 2,704 1,025 5,979 5,832 Avocado . . 9 0 Mango 87 247 3,445 13,955 Pawpaw 82 64 92 1,426 Pineapple 44 19 235 12,295 Orange 172 118 798 6,770 Grape Fruit 15 0 . 0 Guava 20 3 222 75,547 Total 5,233 2,857 13,567 4,749 Sour Soup 252 252 21 82 Black Pepper 0 0 0 0 Pigeon Pea 5,159 1,630 515 316 Malay Apple 0 0 2 0 Star Fruit 23 23 27 1,202 Palm Oil 132 102 161 1,583 Coconut 989 258 666 2,585 Cashewnut 74,124 52,708 9,278 176 Sisal 104 104 71 679 Coffee 29,961 26,030 12,388 476 Wattle 7 0 0 0 Kapok 0 0 0 0 Sugarcane 1,482 1,183 15,262 12,906 Cardamon 0 0 0 0 Cinamon 12 12 3 278 Jack Fruit 0 0 20 0 Mpesheni 32 3 9 2,964 Banana 7,751 3,706 37,890 10,225 Songea Urban Namtumbo Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 170 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) District/Crop 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Avocado 249 43 159 3,718 Mango 1,359 1,101 24,200 21,973 Pawpaw 133 115 685 5,959 Pineapple 161 94 511 5,422 Orange 2,827 502 3,418 6,809 Grape Fruit 15 0 0 0 Grape 0 0 0 0 Mandarine/Tangerine 62 62 123 1,991 Guava 62 35 699 19,939 Plums 0 0 15 0 Apples 2 2 12 5,558 Pears 0 0 12 0 Pitches 0 0 278 0 Lime/Lemon 6 6 103 17,273 Bilimbi 6 0 152 0 Total 124,910 87,969 106,681 1,213 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 171 Crop Area Planted % Cashewnut 74,124 59.34 Coffee 29,961 23.99 Banana 7,751 6.21 Pigeon Pea 5,159 4.13 Orange 2,827 2.26 Sugarcane 1,482 1.19 Mango 1,359 1.09 Coconut 989 0.79 Sour Soup 252 0.20 Avocado 249 0.20 Pineapple 161 0.13 Pawpaw 133 0.11 Palm Oil 132 0.11 Sisal 104 0.08 Mandarine/Tangerine 62 0.05 Guava 62 0.05 Mpesheni 32 0.03 Star Fruit 23 0.02 Grape Fruit 15 0.01 Cinamon 12 0.01 Wattle 7 0.01 Lime/Lemon 6 0.00 Bilimbi 6 0.00 Apples 2 0.00 Pears 0 0.00 Black Pepper 0 0.00 Malay Apple 0 0.00 Kapok 0 0.00 Cardamon 0 0.00 Jack Fruit 0 0.00 Grape 0 0.00 Plums 0 0.00 Pitches 0 0.00 Total 124,910 100.00 District Area Planted with Cashewnut Total Area Planted (Ha) % of Total Area Planted Households with Cashewnut Average Planted Area per Household Tunduru 71,527 79,226 90.3 35,899 2.0 Songea Rural 451 5,655 8.0 527 0.9 Mbinga 917 33,195 2.8 2,050 0.4 Songea Urban 1 1,603 0.1 27 0.0 Namtumbo 1,228 5,233 23.5 1,482 0.8 Total 74,124 124,910 59.3 39,985 1.9 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Ruvuma Region Cashewnut 7.3.3 PERMANENT CROPS: Area Planted with Cashewnut by District Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 172 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 173 District Area Planted with Coffee Total Area Planted (Ha) % of Total Area Planted Households with Coffee Average Planted Area per Household Tunduru 25 79,226 0.03 104 0.2 Songea Rural 582 5,655 10.29 1,227 0.5 Mbinga 29,312 33,195 88.30 39,846 0.7 Songea Urban 42 1,603 2.62 109 0.4 Namtumbo 0 5,233 0.00 0 0.0 Total 29,961 124,910 23.99 41,286 0.7 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Households with Banana Average Planted Area per Household Tunduru 1022 79,226 1.3 1987 0.5 Songea Rural 1622 5,655 28.7 7151 0.2 Mbinga 1096 33,195 3.3 6565 0.2 Songea Urban 1307 1,603 81.6 1935 0.7 Namtumbo 2704 5,233 51.7 6782 0.4 Total 7751 124,910 6.2 24420 0.3 District Area Planted with Pigeon Peas Total Area Planted (Ha) % of Total Area Planted Households with Pigeon Peas Average Planted Area per Household Tunduru 4,756 79,226 6.00 7,625 0.62 Songea Rural 15 5,655 0.27 77 0.19 Mbinga 0 33,195 0.00 0 0.00 Songea Urban 0 1,603 0.00 0 0.00 Namtumbo 388 5,233 7.41 1,368 0.28 Total 5,159 124,910 4.13 9,070 0.57 Coffee 7.3.4 PERMANENT CROPS: Area planted with Coffee by District 7.3.5 PERMANENT CROPS: Area planted with Banana by District Banana 7.3.6 PERMANENT CROPS: Area Planted with Pigeon by District Pigeon Peas Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 174 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0 0 0 252 252 Black Pepper 0 0 0 0 0 Pigeon Pea 0 0 80 5,011 5,092 Malay Apple 0 0 0 0 0 Star Fruit 23 0 0 0 23 Palm Oil 0 0 0 132 132 Coconut 0 0 30 959 989 Cashewnut 202 106 1,342 71,467 73,116 Sisal 104 0 0 0 104 Coffee 18,375 346 5,322 5,784 29,827 Wattle 0 0 0 7 7 Kapok 0 0 0 0 0 Sugarcane 157 31 152 1,142 1,482 Cardamon 0 0 0 0 0 Cinamon 0 0 0 12 12 Jack Fruit 0 0 0 0 0 Mpesheni 0 0 29 3 32 Banana 1,348 530 110 5,758 7,745 Avocado 43 0 0 207 249 Mango 3 8 131 1,172 1,314 Pawpaw 9 0 0 123 133 Pineapple 44 0 29 88 161 Orange 141 0 0 2,683 2,824 Grape Fruit 0 0 0 15 15 Grape 0 0 0 0 0 Mandarine/Tanger 62 0 0 0 62 Guava 10 0 0 44 54 Plums 0 0 0 0 0 Apples 0 0 0 2 2 Pears 0 0 0 0 0 Pitches 0 0 0 0 0 Lime/Lemon 6 0 0 0 6 Bilimbi 0 0 0 6 6 Total 20,526 1,021 7,226 94,867 123,640 7.3.7 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Fertilizer Use Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 175 Crop Mostly Farm Yard Manure Total % Sour Soup 0 252 0.0 Black Pepper 0 0 0.0 Pigeon Pea 0 5,092 0.0 Malay Apple 0 0 0.0 Star Fruit 23 23 100.0 Palm Oil 0 132 0.0 Coconut 0 989 0.0 Cashewnut 202 73,116 0.3 Sisal 104 104 100.0 Coffee 18,375 29,827 61.6 Wattle 0 7 0.0 Kapok 0 0 0.0 Sugarcane 157 1,482 10.6 Cardamon 0 0 0.0 Cinamon 0 12 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 32 0.0 Banana 1,348 7,745 17.4 Avocado 43 249 17.1 Mango 3 1,314 0.2 Pawpaw 9 133 7.1 Pineapple 44 161 27.4 Orange 141 2,824 5.0 Grape Fruit 0 15 0.0 Grape 0 0 0.0 Mandarine/Tangerine 62 62 99.4 Guava 10 54 18.5 Plums 0 0 0.0 Apples 0 2 0.0 Pears 0 0 0.0 Pitches 0 0 0.0 Lime/Lemon 6 6 100.0 Bilimbi 0 6 0.0 Total 20,526 123,640 16.6 cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 176 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 252 0.0 Black Pepper 0 0 0.0 Pigeon Pea 80 5,092 1.6 Malay Apple 0 0 0.0 Star Fruit 0 23 0.0 Palm Oil 0 132 0.0 Coconut 30 989 3.0 Cashewnut 1,342 73,116 1.8 Sisal 0 104 0.0 Coffee 5,322 29,827 17.8 Wattle 0 7 0.0 Kapok 0 0 0.0 Sugarcane 152 1,482 10.3 Cardamon 0 0 0.0 Cinamon 0 12 0.0 Jack Fruit 0 0 0.0 Mpesheni 29 32 90.5 Banana 110 7,745 1.4 Avocado 0 249 0.0 Mango 131 1,314 10.0 Pawpaw 0 133 0.0 Pineapple 29 161 18.2 Orange 0 2,824 0.0 Grape Fruit 0 15 0.0 Grape 0 0 0.0 Mandarine/Tangerine 0 62 0.0 Guava 0 54 0.0 Plums 0 0 0.0 Apples 0 2 0.0 Pears 0 0 0.0 Pitches 0 0 0.0 Lime/Lemon 0 6 0.0 Bilimbi 0 6 0.0 Total 7,226 123,640 5.8 cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 177 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 178 Number % Number % Number % Tunduru 46,378 99 520 1 46,898 100 Songea Rural 30,547 99 226 1 30,772 100 Mbinga 76,416 99 1,031 1 77,447 100 Songea Urban 6,806 98 137 2 6,943 100 Namtumbo 28,829 99 286 1 29,115 100 Total 188,975 99 2,200 1 191,175 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- opertaive Union By Trader On Large Scale Farm Other Total Tunduru 24,319 918 21,035 0 0 0 0 105 46,378 Songea Rural 3,724 307 25,478 0 76 886 76 0 30,547 Mbinga 15,884 7,736 49,059 132 132 3,343 129 0 76,416 Songea Urban 244 188 6,346 0 0 27 0 0 6,806 Namtumbo 4,134 1,294 23,258 0 72 72 0 0 28,829 Total 48,305 10,442 125,177 132 280 4,328 206 105 188,975 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- opertaive Union By Trader On Large Scale Farm Other Total Maize 20,297 10,338 130,475 132 280 4,280 206 0 172,139 Paddy 43,016 1,382 24,048 0 149 666 103 416 73,214 Sorghum 4,850 107 1,433 0 0 74 0 0 6,463 Bulrush Millet 244 0 0 0 0 0 0 0 244 Finger Millet 3,676 430 12,555 0 76 74 0 0 17,314 Cassava 40,092 997 39,600 0 153 0 0 358 101,622 Beans 1,905 0 27 0 0 129 0 0 2,193 Cowpeas 179 0 0 0 0 0 0 0 179 Bambaranut 675 0 0 0 0 0 0 0 675 Simsim 8,927 0 323 0 0 0 0 0 9,379 Groundnut 20,801 0 141 0 0 0 0 0 22,080 Coconut 1,505 0 0 0 0 0 0 0 1,633 Cashewnut 333 0 107 0 0 0 0 0 440 Soya Beans 225 0 0 0 0 0 0 0 225 Coffee 0 76 529 0 0 0 0 0 737 Banana 217 0 622 0 0 0 0 72 910 Cabbage 76 0 0 0 0 0 0 0 76 Sweet Potatoes 0 0 54 0 0 74 0 0 128 Sunflower 254 0 0 0 0 0 0 0 1,034 Wheat 0 660 4,951 0 128 129 0 0 7,056 Sugarcane 0 0 26 0 0 0 0 0 26 Tomatoes 69 0 0 0 0 0 0 27 95 Irish Potatoes 73 0 0 0 0 0 0 0 73 Pumpkins 3,467 307 25,556 0 76 886 76 0 30,368 Method of Processing 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Ruvuma Region Method of Processing 8.1.1a: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Processed Crops Households That did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 179 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 171,419 0 233 280 207 0 172,139 Paddy 70,980 178 1,623 149 283 0 73,214 Sorghum 6,359 0 0 104 0 0 6,463 Bulrush Millet 244 0 0 0 0 0 244 Finger Millet 16,414 72 402 0 0 427 17,314 Wheat 7,056 0 0 0 0 0 7,056 Cassava 101,115 128 226 54 27 72 101,622 Sweet Potatoes 128 0 0 0 0 0 128 Irish Potatoes 73 0 0 0 0 0 73 Beans 2,121 0 73 0 0 0 2,193 Cowpeas 179 0 0 0 0 0 179 Bambaranut 675 0 0 0 0 0 675 Sunflower 1,034 0 0 0 0 0 1,034 Simsim 9,163 0 216 0 0 0 9,379 Groundnut 21,282 144 576 0 0 77 22,080 Coconut 1,633 0 0 0 0 0 1,633 Cashewnut 440 0 0 0 0 0 440 Soya Beans 153 0 72 0 0 0 225 Coffee 265 0 472 0 0 0 737 Sugarcane 0 0 26 0 0 0 26 Banana 910 0 0 0 0 0 910 Cabbage 76 0 0 0 0 0 76 Tomatoes 95 0 0 0 0 0 95 Pumpkins 278 0 0 0 0 0 278 Total 412,092 521 3,919 587 517 575 418,212 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,321 551 488 0 132 934 9,505 157,208 172,139 Paddy 3,147 505 134 284 358 977 3,861 63,947 73,214 Sorghum 107 0 0 0 0 0 640 5,716 6,463 Bulrush Millet 0 0 0 0 0 0 0 244 244 Finger Millet 220 0 72 0 0 145 1,333 15,544 17,314 Wheat 132 0 0 0 128 0 0 6,795 7,056 Cassava 3,564 146 0 75 325 0 6,414 91,097 101,622 Sweet Potatoes 0 0 0 0 0 0 0 128 128 Irish Potatoes 0 0 0 0 0 0 0 73 73 Beans 286 0 286 0 0 73 724 824 2,193 Cowpeas 0 0 0 0 0 0 73 107 179 Bambaranut 0 0 0 0 0 0 73 603 675 Sunflower 0 0 0 0 0 0 0 1,034 1,034 Simsim 0 0 143 0 0 72 723 8,441 9,379 Groundnut 787 73 0 0 105 359 1,340 19,417 22,080 Coconut 0 0 0 0 0 0 0 1,633 1,633 Cashewnut 0 0 0 0 0 0 0 440 440 Soya Beans 0 0 72 0 0 0 0 153 225 Coffee 0 0 208 132 0 0 132 265 737 Sugarcane 0 0 0 0 0 0 0 26 26 Banana 0 0 0 0 0 0 217 693 910 Cabbage 0 0 0 0 0 0 0 76 76 Tomatoes 0 0 0 0 0 0 0 95 95 Pumpkins 0 0 0 0 0 0 0 278 278 Total 11,564 1,275 1,403 492 1,049 2,560 25,033 374,836 418,212 Crop Where Sold Product Use Crop 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Ruvuma Region 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 180 Flour / Meal Grain Oil Juice Total Tunduru 31,588 14,578 106 106 46,378 Songea Rural 28,644 1,902 0 0 30,547 Mbinga 73,255 3,161 0 0 76,416 Songea Urban 6,424 354 0 27 6,806 Namtumbo 28,111 718 0 0 28,829 Total 168,023 20,713 106 133 188,975 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Tunduru 46,168 0 210 0 0 46,378 Songea Rural 30,165 0 231 76 76 30,547 Mbinga 75,638 128 386 132 131 76,416 Songea Urban 6,779 0 27 0 0 6,806 Namtumbo 28,757 0 0 72 0 28,829 Total 187,506 128 854 280 207 188,975 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Tunduru 740 107 107 105 105 106 1,366 43,742 46,378 Songea Rural 303 77 0 0 0 384 1,436 28,347 30,547 Mbinga 3,081 615 0 0 260 257 794 71,408 76,416 Songea Urban 271 109 0 0 0 27 27 6,371 6,806 Namtumbo 718 0 358 0 0 489 6,789 20,475 28,829 Total 5,114 907 465 105 365 1,263 10,412 170,343 188,975 Bran Cake Husk Juice Fiber Shell No by- product Total Tunduru 23,674 212 16,138 212 105 213 5,824 46,378 Songea Rural 29,020 0 458 0 0 0 1,069 30,547 Mbinga 64,462 0 3,665 0 0 0 8,289 76,416 Songea Urban 6,641 0 82 0 0 0 82 6,806 Namtumbo 28,543 0 141 0 0 0 145 28,829 Total 152,339 212 20,484 212 105 213 15,410 188,975 District Product Use District 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Ruvuma Region Main Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Ruvuma Region District By Product 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Ruvuma Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 181 MARKETING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 182 Number % Number % Tunduru 45,053 96.1 1,845 3.9 46,898 Songea Rural 28,109 91.3 2,663 8.7 30,772 Mbinga 70,589 91.1 6,857 8.9 77,447 Songea Urban 5,717 82.3 1,226 17.7 6,943 Namtumbo 27,456 94.3 1,659 5.7 29,115 Total 176,924 92.5 14,250 7.5 191,175 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Other Not Applicabl e Total Tunduru 745 3,612 0 0 105 942 106 40,557 46,067 Songea Rural 77 2,966 0 0 0 0 73 27,120 30,236 Mbinga 254 16,843 518 0 393 0 123 56,858 74,989 Songea Urban 81 1,390 0 0 0 0 0 5,362 6,833 Namtumbo 0 2,014 0 72 0 0 0 26,741 28,827 Total 1,156 26,823 518 72 498 942 303 156,637 186,951 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Other Not Applicabl e Total Tunduru 1.62 7.84 0.00 0.00 0.23 2.05 0.23 88.04 100.00 Songea Rural 0.25 9.81 0.00 0.00 0.00 0.00 0.24 89.69 100.00 Mbinga 0.34 22.46 0.69 0.00 0.52 0.00 0.16 75.82 100.00 Songea Urban 1.19 20.34 0.00 0.00 0.00 0.00 0.00 78.47 100.00 Namtumbo 0.00 6.99 0.00 0.25 0.00 0.00 0.00 92.76 100.00 Total 0.62 14.35 0.28 0.04 0.27 0.50 0.16 83.79 100.00 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Ruvuma Region District Main Reasons for Not Selling Crops Main Reasons for Not Selling Crops District 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Ruvuma Region 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Ruvuma Region Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 183 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 184 Number of Household % Number of Household % Number of Household % Tunduru 3,871 8 43,027 92 46,898 100 Songea Rural 4,485 15 26,287 85 30,772 100 Mbinga 9,024 12 68,422 88 77,447 100 Songea Urban 2,865 41 4,078 59 6,943 100 Namtumbo 4,314 15 24,801 85 29,115 100 Total 24,560 13 166,615 87 191,175 100 District Irrigatable Area (ha) Irrigated Land (ha) % Tunduru 2,126 1,298 61.0 Songea Rural 2,708 785 29.0 Mbinga 2,464 1,555 63.1 Songea Urban 1,229 866 70.4 Namtumbo 3,984 1,549 38.9 Total 12,510 6,052 48.4 River Lake Dam Well Borehole Canal Pipe water Total Tunduru 2,516 106 529 317 0 299 104 3,871 Songea Rural 3,798 0 76 534 0 77 0 4,485 Mbinga 3,689 128 0 129 0 4,948 132 9,024 Songea Urban 2,266 0 54 381 0 136 27 2,865 Namtumbo 3,529 0 0 285 72 284 143 4,314 Total 15,798 234 660 1,646 72 5,744 406 24,560 Gravity Hand Bucket Motor Pump Other Total Tunduru 968 2,800 104 0 3,871 Songea Rural 1,980 2,358 147 0 4,485 Mbinga 2,726 6,166 0 132 9,024 Songea Urban 1,366 1,499 0 0 2,865 Namtumbo 3,097 1,217 0 0 4,314 Total 10,137 14,040 250 132 24,560 District Method of Obtaining Water 11.4: IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 185 Flood Sprinkler Water Hose Bucket / Watering Can Total Tunduru 969 104 205 2,593 3,871 Songea Rural 1,438 229 0 2,818 4,485 Mbinga 2,060 393 0 6,571 9,024 Songea Urban 789 520 0 1,556 2,865 Namtumbo 2,162 0 0 2,152 4,314 Total 7,419 1,245 205 15,691 24,560 Number % Number % Tunduru 615 1 46,283 99 46,898 Songea Rural 1,063 3 29,709 97 30,772 Mbinga 9,554 12 67,893 88 77,447 Songea Urban 739 11 6,204 89 6,943 Namtumbo 432 1 28,684 99 29,115 Total 12,403 6 178,772 94 191,175 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Tunduru 0 1,036 0 977 0 0 0 0 2,014 Songea Rural 0 537 0 456 1,115 2,868 76 0 5,052 Mbinga 84,628 54,132 0 1,159 2,451 32,259 6,294 386 181,309 Songea Urban 27 1,125 137 1,201 3,479 1,840 577 0 8,387 Namtumbo 0 360 0 215 361 215 361 287 1,799 Total 84,655 57,191 137 4,008 7,407 37,183 7,307 672 198,561 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census - 2003 Ruvuma 186 Appendix II 187 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 188 No of households % No of households % Songea Rural 25,515 82.9 5,257 17.1 30,772 Namtumbo 23,957 82.3 5,158 17.7 29,115 Mbinga 20,791 26.8 56,656 73.2 77,447 Tunduru 15,104 32.2 31,793 67.8 46,898 Songea Urban 6,562 94.5 380 5.5 6,943 Total 91,930 48.1 99,245 51.9 191,175 No of households % No of households % Tunduru 4,103 9 42,795 91 46,898 Songea Rural 9,789 32 20,983 68 30,772 Mbinga 38,666 50 38,780 50 77,447 Songea Urban 2,751 40 4,192 60 6,943 Namtumbo 5,755 20 23,360 80 29,115 Total 61,064 32 130,111 68 191,175 No of households % No of households % Tunduru 296 0.6 46,602 99.4 46,898 Songea Rural 1,145 3.7 29,628 96.3 30,772 Mbinga 3,740 4.8 73,707 95.2 77,447 Songea Urban 269 3.9 6,674 96.1 6,943 Namtumbo 855 2.9 28,260 97.1 29,115 Total 6,305 3.3 184,870 96.7 191,175 Table 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 189 No of households % No of households % Mbinga 38,195 49 39,252 51 77,447 Tunduru 19,224 41 27,674 59 46,898 Songea Rural 3,934 13 26,838 87 30,772 Songea Urban 2,130 31 4,812 69 6,943 Namtumbo 2,445 8 26,670 92 29,115 Total 65,929 34 125,245 66 191,175 No of households % No of households % Tunduru 0 0 46,898 100 46,898 Songea Rural 228 1 30,544 99 30,772 Mbinga 1,701 2 75,746 98 77,447 Songea Urban 82 1 6,860 99 6,943 Namtumbo 0 0 29,115 100 29,115 Total 2,011 1 189,163 99 191,175 No of households % No of households % Tunduru 2,164 5 44,734 95 46,898 Songea Rural 6,857 22 23,915 78 30,772 Mbinga 10,036 13 67,411 87 77,447 Songea Urban 2,625 38 4,318 62 6,943 Namtumbo 4,963 17 24,152 83 29,115 Total 26,646 14 164,529 86 191,175 Table 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 190 Number % Number % Number % Number % Number % Tunduru 1,381 2.9 719 1.5 12,060 25.7 0 0.0 309 0.7 107 0.2 Songea Rural 1,438 4.7 0 0.0 23,250 75.6 150 0.5 150 0.5 0 0.0 Mbinga 2,238 2.9 1,304 1.7 16,589 21.4 0 0.0 132 0.2 0 0.0 Songea Urban 27 0.4 53 0.8 6,454 93.0 27 0.4 0 0.0 0 0.0 Namtumbo 10,459 35.9 72 0.2 12,422 42.7 358 1.2 143 0.5 0 0.0 Total 15,544 8.1 2,148 1.1 70,774 37.0 535 0.3 735 0.4 107 0.1 Total Number % Number % Number % Number % Number Tunduru 0 0.0 423 0.9 105 0.2 31793 67.8 46,898 Songea Rural 147 0.5 303 0.9 77 0.3 5256.9 17.1 30,772 Mbinga 0 0.0 527 0.9 0 0.0 56656 73.2 77,447 Songea Urban 0 0.0 0 0.9 0 0.0 380.41 5.5 6,943 Namtumbo 0 0.0 504 0.9 0 0.0 5158.4 17.7 29,115 Total 147 0.1 1,757 0.9 182 0.1 99245 51.9 191,175 Number % Number % Number % Number % Number % Tunduru 107 0.2 0 0.0 107 0.2 0 0.0 0 0.0 0 0.0 Songea Rural 0 0.0 0 0.0 76 0.2 0 0.0 74 0.2 0 0.0 Mbinga 0 0.0 0 0.0 0 0.0 0 0.0 128 0.2 132 0.2 Songea Urban 0 0.0 81 1.2 82 1.2 27 0.4 27 0.4 0 0.0 Namtumbo 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 107 0.1 81 0.0 265 0.1 27 0.0 229 0.1 132 0.1 Crop Buyers Local Market/Trade Sotre Secondary Market Secondary Market Development Project District Large Scale Farm Crop Buyers District Cooperatives Local Farmers Group Local Market/Trade Sotre Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year cont...Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year Locally Produced by Household Neighbour Other Not applicable District Cooperatives Local Farmers Group Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 191 Total Number % Number % Number % Number % Number % Number Tunduru 0 0.0 1,216 2.6 2,673 5.7 0 0.0 42,795 91.3 46,898 Songea Rural 226 0.7 6,296 20.5 2,964 9.6 153 0.5 20,983 68.2 30,772 Mbinga 397 0.5 33,984 43.9 4,025 5.2 0 0.0 38,780 50.1 77,447 Songea Urban 0 0.0 2,043 29.4 491 7.1 0 0.0 4,192 60.4 6,943 Namtumbo 434 1.5 3,308 11.4 1,942 6.7 72 0.2 23,360 80.2 29,115 Total 1,057 0.6 46,848 24.5 12,095 6.3 224 0.1 130,111 68.1 191,175 Total Number % Number % Number % Number % Number % Number % Tunduru 0 0.0 0 0.0 208 0.4 0 0.0 89 0.2 46,602 99.4 46,898 Songea Rural 0 0.0 0 0.0 991 3.2 154 0.5 0 0.0 29,628 96.3 30,772 Mbinga 0 0.0 254 0.3 3,230 4.2 256 0.3 0 0.0 73,707 95.2 77,447 Songea Urban 27 0.4 27 0.4 215 3.1 0 0.0 0 0.0 6,646 96.1 6,915 Namtumbo 0 0.0 0 0.0 783 2.7 72 0.2 0 0.0 28,260 97.1 29,115 Total 27 0.0 281 0.1 5,426 2.8 482 0.3 89 0.0 184,842 96.7 191,147 Number % Number % Number % Number % Number % Tunduru 6,744 14.4 5,744 12.2 6,005 12.8 103 0.2 107 0.2 Songea Rural 757 2.5 0 0.0 2,880 9.4 0 0.0 0 0.0 Mbinga 9,317 12.0 4,190 5.4 20,118 26.0 0 0.0 1,960 2.5 Songea Urban 0 0.0 27 0.4 2,103 30.3 0 0.0 0 0.0 Namtumbo 141 0.5 644 2.2 1,589 5.5 0 0.0 0 0.0 Total 16,959 8.9 10,605 5.5 32,694 17.1 103 0.1 2,067 1.1 Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Local Farmers Group Local Market/Trade Store Locally Produced by Household Neighbour Other District Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Development Project Crop Buyers District Cooperatives Local Market/Trade Store Local Farmers Group cont…..Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Large Scale Farm Locally Produced by Household Neighbour Other Not applicable Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 192 Total Number % Number % Number % Number % Number Tunduru 0 0.0 420 0.9 103 0.2 27,674 59.0 46,898 Songea Rural 76 0.2 223 0.7 0 0.0 26,838 87.2 30,772 Mbinga 264 0.3 2,346 3.0 0 0.0 39,252 50.7 77,447 Songea Urban 0 0.0 0 0.0 0 0.0 4,812 69.3 6,943 Namtumbo 0 0.0 72 0.2 0 0.0 26,670 91.6 29,115 Total 340 0.2 3,060 1.6 103 0.1 125,245 65.5 191,175 Total Number % Number % Number % Number % Number % Number Tunduru 0 0.0 0 0.0 0 0.0 0 0.0 46,898 100.0 46,898 Songea Rural 76 0.2 0 0.0 76 0.2 77 0.3 30,544 99.3 30,772 Mbinga 394 0.5 1,046 1.4 0 0.0 260 0.3 75,746 97.8 77,447 Songea Urban 0 0.0 82 1.2 0 0.0 0 0.0 6,833 98.8 6,915 Namtumbo 0 0.0 0 0.0 0 0.0 0 0.0 29,115 100.0 29,115 Total 470 0.2 1,128 0.6 76 0.0 337 0.2 189,136 98.9 191,147 Neighbour Not applicable Other Not applicable cont...Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Cooperative Local Market/Trade Store Locally Produced by Household Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year District Locally Produced by Household Neighbour Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 193 Number % Number % Number % Number % Number % Number % Number % Tunduru 205 0.4 0 0.0 1,035 2.2 0 0.0 0 0.0 105 0.2 107 0.2 Songea Rural 914 3.0 0 0.0 5,641 18.3 0 0.0 0 0.0 0 0.0 0 0.0 Mbinga 132 0.2 128 0.2 8,765 11.3 110 0.1 129 0.2 0 0.0 0 0.0 Songea Urban 0 0.0 110 1.6 2,378 34.2 0 0.0 0 0.0 55 0.8 0 0.0 Namtumbo 1,298 4.5 0 0.0 3,166 10.9 0 0.0 73 0.2 72 0.2 0 0.0 Total 2,549 1.3 237 0.1 20,984 11.0 110 0.1 201 0.1 232 0.1 107 0.1 Total Number % Number % Number % Number % Number Tunduru 0 0.0 610 1.3 103 0.22 44,734 95.39 46,898 Songea Rural 0 0.0 303 1.0 0 0 23,915 77.72 30,772 Mbinga 0 0.0 773 1.0 0 0 67,411 87.04 77,447 Songea Urban 27 0.4 55 0.8 0 0 4,318 62.19 6,943 Namtumbo 0 0.0 285 1.0 69 0.24 24,152 82.95 29,115 Total 27 0.0 2,026 1.1 171 0.09 164,529 86.06 191,175 Number % Number % Number % Number % Number % Tunduru 4,445 29 816 5 2,520 17 1,681 11 5,642 37 15,104 Songea Rural 3,248 13 1,206 5 3,164 12 8,551 34 9,346 37 25,515 Mbinga 3,209 15 2,709 13 4,792 23 4,525 22 5,555 27 20,791 Songea Urban 240 4 748 11 3,522 54 1,944 30 109 2 6,562 Namtumbo 10,923 46 4,316 18 2,510 10 1,444 6 4,764 20 23,957 Total 22,065 24 9,794 11 16,509 18 18,145 20 25,416 28 91,930 Not applicable Between 10 and 20 km 20 km and Above Total Number District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Large Scale Farm cont...12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Locally Produced by Household Neighbour Other 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Cooperative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 194 Number % Number % Number % Number % Number % Tunduru 3,793 92 105 3 205 5 0 0 0 0 4,103 Songea Rural 9,030 92 455 5 304 3 0 0 0 0 9,789 Mbinga 37,360 97 261 1 393 1 520 1 132 0 38,666 Songea Urban 2,504 91 82 3 165 6 0 0 0 0 2,751 Namtumbo 4,959 86 362 6 72 1 362 6 0 0 5,755 Total 57,646 94 1,265 2 1,139 2 882 1 132 0 61,064 Total Number % Number % Number % Number % Number Tunduru 296 100 0 0 0 0 0 0 296 Songea Rural 1,145 100 0 0 0 0 0 0 1,145 Mbinga 3,611 97 0 0 129 3 0 0 3,740 Songea Urban 242 90 27 10 0 0 0 0 269 Namtumbo 642 75 72 8 69 8 72 8 855 Total 5,935 94 100 2 198 3 72 1 6,305 Number % Number % Number % Number % Number % Tunduru 1,023 47 0 0 213 10 0 0 928 43 2,164 Songea Rural 1,135 17 77 1 836 12 1,987 29 2,824 41 6,857 Mbinga 1,603 16 774 8 2,596 26 2,491 25 2,573 26 10,036 Songea Urban 162 6 188 7 1,562 60 685 26 27 1 2,625 Namtumbo 1,578 32 648 13 434 9 362 7 1,941 39 4,963 Total 5,501 21 1,686 6 5,641 21 5,524 21 8,293 31 26,646 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number Between 10 and 20 km 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 195 Less than 1 km Number % Number % Number % Number % Number % Tunduru 11,190 58 1,658 9 1,741 9 2,009 10 2,627 14 19,224 Songea Rural 377 10 302 8 679 17 686 17 1,890 48 3,934 Mbinga 9,191 24 7,858 21 6,113 16 8,522 22 6,511 17 38,195 Songea Urban 0 0 162 8 1,149 54 820 38 0 0 2,130 Namtumbo 854 35 217 9 0 0 218 9 1,156 47 2,445 Total 21,612 33 10,198 15 9,681 15 12,255 19 12,184 18 65,929 Total Number % Number % Number % Number % Number Songea Rural 152 66 0 0 0 0 77 34 228 Mbinga 523 31 391 23 526 31 260 15 1,701 Songea Urban 0 0 82 100 0 0 0 0 82 Total 675 34 474 24 526 26 337 17 2,011 Between 10 and 20 km 20 km and Above Table 12.1.17(b) ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above District Less than 1 km Between 3 and 10 km 12.1.17(a) ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total Number Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 196 Input is of No Use Number % Number % Number % Number % Number % Number % Number % Tunduru 1,032 3 29,722 93 318 1 106 0 402 1 0 0 213 1 31,793 Songea Rural 832 16 3,965 75 0 0 76 1 154 3 0 0 230 4 5,257 Mbinga 3,504 6 43,769 77 378 1 521 1 8,220 15 263 0 0 0 56,656 Songea Urban 0 0 353 93 0 0 0 0 27 7 0 0 0 0 380 Namtumbo 217 4 4,725 92 144 3 0 0 0 0 0 0 72 1 5,158 Total 5,586 6 82,534 83 840 1 703 1 8,804 9 263 0 515 1 99,245 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 19,156 45 1,355 3 10,661 25 210 0 10,484 24 525 1 104 0 300 1 42,795 Songea Rural 10,527 50 2,444 12 3,129 15 458 2 2,822 13 1,147 5 76 0 381 2 20,983 Mbinga 17,535 45 2,428 6 8,813 23 1,043 3 1,658 4 4,821 12 0 0 2,482 6 38,780 Songea Urban 2,481 59 461 11 1,087 26 54 1 0 0 27 1 0 0 82 2 4,192 Namtumbo 11,503 49 937 4 7,045 30 143 1 3,732 16 0 0 0 0 0 0 23,360 Total 61,202 47 7,625 6 30,736 24 1,908 1 18,696 14 6,520 5 179 0 3,245 2 130,111 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 3,785 8 1,475 3 22,360 48 104 0 17,843 38 413 1 416 1 205 0 46,602 Songea Rural 1,214 4 2,745 9 10,638 36 978 3 11,146 38 1,606 5 228 1 1,072 4 29,628 Mbinga 10,325 14 1,919 3 38,109 52 1,296 2 13,583 18 6,257 8 784 1 1,434 2 73,707 Songea Urban 1,632 24 488 7 3,604 54 55 1 759 11 81 1 0 0 54 1 6,674 Namtumbo 3,900 14 1,446 5 11,821 42 144 1 10,805 38 0 0 73 0 72 0 28,260 Total 20,856 11 8,073 4 86,534 47 2,576 1 54,136 29 8,358 5 1,500 1 2,836 2 184,870 No Money to Buy Total Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Input is of No Use Not Available Price Too High Do not Know How to Use Input is of No Use Too Much Labour Required Too Much Labour Required Do not Know How to Use Total Locally Produced by Household Other Other No Money to Buy 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Price Too High 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Locally Produced by Household District Not Available Price Too High No Money to Buy Do not Know How to Use Not Available Total Locally Produced by Household Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 197 Number % Number % Number % Number % Number % Number % Number % Tunduru 2,734 10 23,191 84 211 1 0 0 845 3 692 3 0 0 27,674 Songea Rural 1,900 7 19,069 71 153 1 153 1 2,130 8 3,129 12 304 1 26,838 Mbinga 5,146 13 28,036 71 633 2 132 0 387 1 4,792 12 124 0 39,252 Songea Urban 27 1 3,838 80 160 3 27 1 82 2 677 14 0 0 4,812 Namtumbo 927 3 22,353 84 1,014 4 0 0 1,651 6 652 2 72 0 26,670 Total 10,735 9 96,487 77 2,171 2 313 0 5,096 4 9,942 8 501 0 125,245 Number % Number % Number % Number % Number % Number % Number % Tunduru 7,822 17 30,276 65 106 0 0 0 7,683 16 904 2 107 46,898 Songea Rural 1,897 6 18,002 59 151 0 77 0 4,322 14 5,712 19 383 30,544 Mbinga 6,335 8 51,180 68 886 1 263 0 1,790 2 15,167 20 124 75,746 Songea Urban 242 4 4,304 63 409 6 27 0 680 10 1,171 17 27 6,860 Namtumbo 1,649 6 21,495 74 722 2 0 0 2,082 7 3,168 11 0 29,115 Total 17,946 9 125,257 66 2,274 1 367 0 16,557 9 26,122 14 641 189,163 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 12,404 28 30,996 69 0 0 0 0 932 2 193 0 105 0 104 0 44,734 Songea Rural 2,276 10 20,346 85 381 2 0 0 533 2 302 1 0 0 76 0 23,915 Mbinga 14,358 21 49,558 74 500 1 132 0 782 1 2,080 3 0 0 0 0 67,411 Songea Urban 134 3 4,046 94 27 1 0 0 0 0 27 1 0 0 82 2 4,318 Namtumbo 2,069 9 20,420 85 579 2 0 0 939 4 145 1 0 0 0 0 24,152 Total 31,242 19 125,367 76 1,488 1 132 0 3,185 2 2,748 2 105 0 262 0 164,529 Other Input is of No Use Total Total 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Other Other Input is of No Use Input is of No Use Locally Produced by Household 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High Too Much Labour Required Do not Know How to Use 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year No Money to Buy Total Too Much Labour Required Do not Know How to Use District Not Available Price Too High No Money to Buy Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 198 Number % Number % Number % Number % Tunduru 5,567 37 8,263 55 1,170 8 105 1 15,104 Songea Rural 8,806 35 15,716 62 841 3 152 1 25,515 Mbinga 4,647 22 13,757 66 2,265 11 122 1 20,791 Songea Urban 872 13 5,041 77 543 8 106 2 6,562 Namtumbo 6,419 27 16,965 71 572 2 0 0 23,957 Total 26,311 29 59,743 65 5,392 6 485 1 91,930 Number % Number % Number % Number % Tunduru 1,118 27 2,771 68 213 5 0 0 4,103 Songea Rural 2,806 29 6,219 64 763 8 0 0 9,789 Mbinga 15,310 40 19,689 51 3,668 9 0 0 38,666 Songea Urban 431 16 1,992 72 273 10 55 2 2,751 Namtumbo 1,223 21 3,958 69 503 9 72 1 5,755 Total 20,888 34 34,629 57 5,420 9 127 0 61,064 Number % Number % Number % Songea Rural 0 0 228 100 0 0 228 Mbinga 520 31 921 54 260 15 1,701 Songea Urban 0 0 82 100 0 0 82 Total 520 26 1,231 61 260 13 2,011 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total Average Total Poor Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor District Excellent Good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 199 Number % Number % Number % Number % Number % Tunduru 4,103 21 11,140 58 3,771 20 105 1 105 1 19,224 Songea Rural 1,059 27 2,799 71 77 2 0 0 0 0 3,934 Mbinga 6,531 17 28,542 75 2,342 6 780 2 0 0 38,195 Songea Urban 328 15 1,638 77 110 5 55 3 0 0 2,130 Namtumbo 641 26 1,659 68 145 6 0 0 0 0 2,445 Total 12,661 19 45,778 69 6,444 10 941 1 105 0 65,929 Number % Number % Number % Songea Rural 0 0 228 100 0 0 228 Mbinga 520 31 921 54 260 15 1,701 Songea Urban 0 0 82 100 0 0 82 Total 520 26 1,231 61 260 13 2,011 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Tunduru 838 39 1,222 56 104 5 0 0 2,164 Tunduru 25,472 54 21,425 46 46,898 Songea Rural 1,830 27 4,797 70 230 3 0 0 6,857 Songea Rural 27,346 89 3,426 11 30,772 Mbinga 3,075 31 6,307 63 522 5 131 1 10,036 Mbinga 35,197 45 42,250 55 77,447 Songea Urban 383 15 2,025 77 190 7 27 1 2,625 Songea Urban 6,725 97 218 3 6,943 Namtumbo 569 11 4,322 87 72 1 0 0 4,963 Namtumbo 26,692 92 2,424 8 29,115 Total 6,695 25 18,673 70 1,118 4 159 1 26,646 Total 121,432 64 69,742 36 191,175 Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year Total District Excellent Good Average Total District Excellent Good Average Total 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year Total District District Excellent Good Average Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 200 Number % Number % Number % Number % Tunduru 5,253 11 41,644 89 46,898 Tunduru 1,563 3 45,334 97 46,898 Songea Rural 10,793 35 19,979 65 30,772 Songea Rural 2,134 7 28,639 93 30,772 Mbinga 46,041 59 31,405 41 77,447 Mbinga 8,553 11 68,894 89 77,447 Songea Urban 3,079 44 3,864 56 6,943 Songea Urban 516 7 6,427 93 6,943 Namtumbo 7,194 25 21,921 75 29,115 Namtumbo 1,065 4 28,050 96 29,115 Total 72,361 38 118,814 62 191,175 Total 13,832 7 177,343 93 191,175 Number % Number % Number % Number % Tunduru 24,030 51 22,868 49 46,898 Tunduru 1,153 2 45,745 98 46,898 Songea Rural 5,238 17 25,535 83 30,772 Songea Rural 993 3 29,780 97 30,772 Mbinga 42,719 55 34,728 45 77,447 Mbinga 4,445 6 73,002 94 77,447 Songea Urban 2,159 31 4,784 69 6,943 Songea Urban 165 2 6,778 98 6,943 Namtumbo 3,093 11 26,023 89 29,115 Namtumbo 647 2 28,468 98 29,115 Total 77,237 40 113,938 60 191,175 Total 7,403 4 183,772 96 191,175 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use COMPOST ManureNext Year Agricultural Households With NO Plan to use COMPOST Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Herbicides Next Year g Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 201 Number % Number % Tunduru 6,578 14 40,320 86 46,898 Songea Rural 8,753 28 22,019 72 30,772 Mbinga 23,214 30 54,233 70 77,447 Songea Urban 2,734 39 4,209 61 6,943 Namtumbo 6,764 23 22,351 77 29,115 Total 48,043 25 143,132 75 191,175 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Improved Seeds Next Year Agricultural Households With NO Plan to use Improved Seeds Next Year Total Tanzania Agriculture Sample Census - 2003 Ruvuma 202 Appendix II 203 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 204 Number % Number % Tunduru 2,992 93 212 7 3,204 Songea Rural 4,149 70 1,813 30 5,962 Mbinga 12,568 91 1,302 9 13,870 Songea Urban 566 78 161 22 727 Namtumbo 12,664 86 2,140 14 14,804 Total 32,939 85 5,628 15 38,567 Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader / Trade Store Private Individual Religious Organisati on / NGO / Project Other Total Tunduru 609 0 1,244 1,246 105 0 0 0 3,204 Songea Rural 2,621 77 1,137 678 150 380 920 0 5,962 Mbinga 7,228 260 3,550 390 1,693 378 239 132 13,870 Songea Urban 399 0 54 27 165 53 27 0 727 Namtumbo 4,498 72 8,868 73 433 141 650 69 14,804 Total 15,355 408 14,853 2,414 2,547 953 1,836 201 38,567 District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year Total District Male Female Source of Credit 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 205 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Tunduru 98 14,650 2,479 931 15,586 1,576 104 204 7,960 43,587 Songea Rural 841 6,926 3,345 1,978 6,687 1,746 77 76 3,134 24,810 Mbinga 3,117 19,364 5,403 2,223 20,840 1,279 517 0 10,834 63,577 Songea Urban 246 684 1,137 330 2,077 515 27 81 1,119 6,216 Namtumbo 937 1,445 4,388 3,454 2,153 577 72 145 1,140 14,311 Total 5,238 43,069 16,752 8,916 47,344 5,694 797 506 24,187 152,501 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Tunduru 507 0 726 2,274 0 0 98 0 3,606 Songea Rural 1,049 611 4,383 454 305 77 227 226 7,331 Mbinga 2,951 634 3,375 4,195 1,699 0 1,435 1,547 15,837 Songea Urban 187 136 512 54 0 0 53 27 971 Namtumbo 2,422 1,484 9,734 214 71 0 0 1,661 15,586 Total Credits 7,117 2,866 18,730 7,191 2,075 77 1,814 3,462 43,331 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year District Credit Use 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Ruvuma 206 Appendix II 207 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 208 District Senna Spp Gravellis Afzelia Quanzensi s Acacia Spp Pinus Spp Eucalyptu s Spp Cyprus Spp Calophylu m Inophyllu m Melicia excelsa Casurina Equisetfili a Terminalia Catapa Songea Rural 245 341 . 181 1422 352 44 1058 60 . . Mbinga 1046 5220 . 1342 900 58739 9865 40 10 . 59 Songea Urban 164 55 5 760 3 7638 322 3230 61 16 25 Namtumbo 1195 60 20 . . 114 130 . 35 . . Total 2650 5676 25 2283 2325 66843 10361 4328 166 16 84 % 3 6 0 2 2 70 11 5 0 0 0 District Terminalia Ivorensis Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Albizia Spp Kyaya Spp Sesbania Spp Calliandra Spp Trichilia Spp Total Songea Rural . 71 . 1 10 267 166 . 10 . 4228 Mbinga 50 6 . 13 . 4 . . . 11 77305 Songea Urban . . 55 2 . 19 . 3 . . 12358 Namtumbo . . . 113 146 . . . . . 1813 Total 50 77 55 129 156 290 166 3 10 11 95704 % 0 0 0 0 0 0 0 0 0 0 100 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region cont… ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Regiont Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 209 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Songea Rural 62 1,393 32 687 13 2,148 107 4,228 Mbinga 35 9,505 93 12,643 91 55,157 219 77,305 Songea Urban 74 1,769 38 1,979 16 8,590 128 12,338 Namtumbo 32 904 8 209 5 700 45 1,813 Total 203 13,571 171 15,518 125 66,595 499 95,684 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Total Songea Rural 114 4 0 8 3 2 264 Mbinga 52 31 1 85 120 1 582 Songea Urban 136 2 0 36 15 1 382 Namtumbo 30 0 0 19 8 0 114 Total 332 37 1 148 146 4 1,342 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region District 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Ruvuma Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Main Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 210 1-9 1-19 20-29 30-39 40-49 60+ Total Tunduru 0 104 0 0 0 0 104 Songea Rural 4,641 1,141 1,607 672 381 606 9,047 Mbinga 7,314 3,892 3,109 2,345 1,559 1,034 19,252 Songea Urban 165 247 275 55 27 0 769 Namtumbo 862 354 502 837 142 72 2,768 Total 12,982 5,738 5,492 3,908 2,109 1,712 31,940 % 41 18 17 12 7 5 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Songea Rural 11 5 0 106 8 0 2 132 Mbinga 63 64 5 137 9 1 12 291 Songea Urban 20 10 1 131 19 1 9 191 Namtumbo 8 7 0 19 21 0 2 57 Total 102 86 6 393 57 2 25 671 District Second Use 14.4TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Ruvuma Region District Distance to Community Planted Forest (km) 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 211 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 212 Number % Number % Tunduru 14,048 30 32,849 70 46,898 Songea Rural 7,223 23 23,549 77 30,772 Mbinga 27,165 35 50,281 65 77,447 Songea Urban 2,805 40 4,138 60 6,943 Namtumbo 15,958 55 13,158 45 29,115 Total 67,199 35 123,975 65 191,175 Number % Number % Number % Number % Number % Number % Tunduru 529 4 9,313 66 4,100 29 106 1 0 0 14,048 100 Songea Rural 228 3 5,317 74 1,678 23 0 0 0 0 7,223 100 Mbinga 3,638 14 18,592 69 3,762 14 385 1 525 2 26,901 100 Songea Urban 215 8 2,398 85 192 7 0 0 0 0 2,805 100 Namtumbo 2,581 16 10,349 65 2,235 14 577 4 143 1 15,886 100 Total 7,192 11 45,969 69 11,967 18 1,068 2 668 1 66,864 100 Number % Number % Number % Number % Number % Number % Number % Tunduru 13,146 94 213 2 98 1 291 2 300 2 0 0 14,048 100 Songea Rural 6,696 93 299 4 153 2 76 1 0 0 0 0 7,223 100 Mbinga 22,524 83 780 3 767 3 1,695 6 480 2 790 3 27,037 100 Songea Urban 2,618 93 0 0 27 1 0 0 160 6 0 0 2,805 100 Namtumbo 14,093 88 499 3 861 5 432 3 72 0 0 0 15,958 100 Total 59,075 88 1,791 3 1,907 3 2,495 4 1,013 2 790 1 67,071 100 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region District Source of Crop Extension 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Ruvuma Region Very Good Good Average Poor No Good Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Ruvuma Region District Households Receiving Extension Households Not Receiving Extension Total Number of Households Other Not applicable Total Government NGO / Development Project Cooperative Large Scale Farm Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 213 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Tunduru 11,058 213 98 98 212 0 11,679 46,898 24.9 Songea Rural 5,557 223 153 76 0 0 6,009 30,772 19.5 Mbinga 15,456 396 378 1,431 480 790 18,931 77,447 24.4 Songea Urban 2,482 0 27 0 133 0 2,643 6,943 38.1 Namtumbo 13,230 358 789 72 72 0 14,522 29,115 49.9 Total 47,783 1,189 1,446 1,677 898 790 53,783 191,175 28.1 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 8,511 106 203 208 89 104 9,221 46,898 19.7 Songea Rural 1,605 754 76 76 0 0 2,510 30,772 8.2 Mbinga 14,516 772 642 392 0 132 16,454 77,447 21.2 Songea Urban 1,337 0 0 27 0 0 1,364 6,943 19.7 Namtumbo 7,277 72 649 72 0 0 8,070 29,115 27.7 Total 33,246 1,703 1,569 776 89 236 37,619 191,175 19.7 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 1,375 0 0 98 0 0 1,473 46,898 3.1 Songea Rural 1,458 151 0 0 0 76 1,684 30,772 5.5 Mbinga 8,328 252 124 521 131 656 10,014 77,447 12.9 Songea Urban 795 0 0 27 55 0 877 6,943 12.6 Namtumbo 5,332 72 72 72 0 145 5,692 29,115 19.6 Total 17,287 475 196 719 186 877 19,741 191,175 10.3 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Use of Agrochemicals Total Number of Households District District Spacing Total Total Number of Households % of total number of households % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Erosion Control Total Number of Households District Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 214 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,790 0 203 104 0 0 4,097 46,898 9 Songea Rural 3,428 831 0 0 0 0 4,259 30,772 14 Mbinga 17,833 513 775 791 131 128 20,172 77,447 26 Songea Urban 1,552 55 0 0 137 0 1,744 6,943 25 Namtumbo 8,694 72 72 360 0 142 9,341 29,115 32 Total 35,298 1,471 1,050 1,256 268 270 39,612 191,175 21 Government NGO / Development Cooperative Large Scale Other Not applicable Total Tunduru 7,873 213 0 210 0 0 8,296 46,898 18 Songea Rural 4,269 754 151 77 0 76 5,327 30,772 17 Mbinga 11,851 265 630 790 0 260 13,796 77,447 18 Songea Urban 2,014 27 0 0 27 0 2,069 6,943 30 Namtumbo 11,354 505 2,448 0 142 0 14,448 29,115 50 Total 37,362 1,763 3,229 1,076 170 336 43,936 191,175 23 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,466 213 0 0 0 0 3,678 46,898 8 Songea Rural 3,500 601 153 153 0 0 4,407 30,772 14 Mbinga 11,574 132 373 0 0 265 12,344 77,447 16 Songea Urban 1,828 0 0 55 82 0 1,965 6,943 28 Namtumbo 9,270 789 575 216 72 0 10,921 29,115 38 Total 29,638 1,735 1,101 423 154 265 33,316 191,175 17 Total Number of Households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Organic Fertilizer Use Inorganic Fertilizer Use District % of total number of households Use of Improved Seed District District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households Total Number of Households % of total number of households % of total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 215 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Tunduru 723 104 0 106 0 934 46,898 2 Songea Rural 308 153 0 76 0 537 30,772 2 Mbinga 1,022 0 0 0 643 1,665 77,447 2 Songea Urban 27 0 0 0 0 27 6,943 0 Namtumbo 4,467 0 72 0 145 4,683 29,115 16 Total 6,547 257 72 182 788 7,846 191,175 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 2,952 0 0 89 0 105 3,146 46,898 7 Songea Rural 1,987 0 0 0 0 0 1,987 30,772 6 Mbinga 4,695 128 124 124 131 529 5,732 77,447 7 Songea Urban 1,172 0 0 0 110 0 1,281 6,943 18 Namtumbo 7,421 72 0 287 0 0 7,780 29,115 27 Total 18,226 200 124 501 241 634 19,926 191,175 10 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 5,500 0 0 0 212 0 5,712 46,898 12 Songea Rural 2,967 151 0 76 0 0 3,194 30,772 10 Mbinga 9,626 128 124 260 260 917 11,315 77,447 15 Songea Urban 1,823 0 0 0 192 27 2,043 6,943 29 Namtumbo 8,993 145 215 0 71 0 9,424 29,115 32 Total 28,910 424 339 335 735 945 31,688 191,175 17 Crop Storage District District District Mechanisation / LST Total Number of Households 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region % of total number of households % of total number of households 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region % of total number of households Total Number of Households Total Number of Households Irrigation Technology Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 216 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tunduru 1,155 0 0 0 105 0 46,898 0.00 Songea Rural 1,760 227 0 0 0 0 30,772 0.00 Mbinga 5,971 0 124 128 0 657 77,447 0.85 Songea Urban 876 0 0 0 55 0 6,943 0.00 Namtumbo 7,200 72 215 288 71 69 29,115 0.24 Total 16,962 298 340 416 231 726 191,175 0.38 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,806 0 98 0 0 0 3,905 46,898 8 Songea Rural 1,683 152 0 0 0 0 1,835 30,772 6 Mbinga 4,578 0 385 260 131 917 6,272 77,447 8 Songea Urban 814 0 0 0 247 27 1,089 6,943 16 Namtumbo 6,905 72 144 72 0 0 7,193 29,115 25 Total 17,787 224 628 332 379 945 20,294 191,175 11 Government NGO / Development Project Cooperative Other Not applicable Total Tunduru 312 0 0 0 0 312 46,898 1 Songea Rural 999 149 0 0 0 1,148 30,772 4 Mbinga 5,595 256 124 260 397 6,632 77,447 9 Songea Urban 653 82 0 27 0 762 6,943 11 Namtumbo 6,331 215 0 0 0 6,546 29,115 22 Total 13,889 702 124 287 397 15,400 191,175 8 % of total number of households District Agro-progressing Agro-forestry District District Total Number of Households % of total number of households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households % of total number of households Total Number of Households Vermin Control Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 217 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tunduru 105 0 0 0 0 105 46,898 0 Songea Rural 308 0 0 0 0 308 30,772 1 Mbinga 785 256 0 0 265 1,306 77,447 2 Songea Urban 191 165 27 27 0 411 6,943 6 Namtumbo 5,331 359 0 0 0 5,690 29,115 20 Total 6,720 780 27 27 265 7,819 191,175 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 0 0 0 0 0 0 0 46898 0 Songea Rural 536 153 74 0 0 0 763 30772 2 Mbinga 1,313 128 0 0 0 265 1,706 77447 2 Songea Urban 301 302 0 0 27 0 631 6943 9 Namtumbo 5,268 216 0 69 73 72 5,698 29115 20 Total 7,419 798 74 69 100 336 8,797 191175 5 Received Adopted % Received Adopted % Received Adopted % Tunduru 11,679 11,581 99 9,117 6,259 69 1,369 0 0 Songea Rural 5,932 5,702 96 2,433 1,674 69 1,608 1,610 100 Mbinga 18,008 17,888 99 15,804 13,718 87 9,355 6,234 67 Songea Urban 2,670 2,507 94 1,419 1,118 79 877 713 81 Namtumbo 14,522 14,235 98 7,784 2,885 37 5,185 2,162 42 Total 52,811 51,912 98 36,557 25,653 70 18,394 10,719 58 Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Beekeeping District District 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region District Use of Agrochemicals Erosion Control Spacing 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households % of total number of households Total Number of Households % of total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 218 Received Adopted % Received Adopted % Received Adopted % Tunduru 3,780 1,359 36 8,189 5,757 70 3,678 1,356 37 Songea Rural 3,800 3,193 84 5,480 5,252 96 4,407 2,652 60 Mbinga 20,036 17,308 86 13,381 10,882 81 11,946 6,071 51 Songea Urban 1,689 1,444 85 2,124 2,015 95 1,965 1,503 76 Namtumbo 8,479 3,167 37 14,594 14,233 98 10,994 5,398 49 Total 37,782 26,472 70 43,768 38,140 87 32,991 16,980 51 Received Adopted % Received Adopted % Received Adopted % Tunduru 410 0 0 2,619 822 31 5,712 4,759 83 Songea Rural 613 0 0 1,987 1,068 54 3,194 2,965 93 Mbinga 388 1,171 302 4,155 3,374 81 10,778 10,657 99 Songea Urban 27 27 100 1,281 1,118 87 2,070 1,907 92 Namtumbo 4,393 216 5 7,780 3,892 50 9,208 8,850 96 Total 5,832 1,415 24 17,821 10,275 58 30,963 29,139 94 Received Adopted % Received Adopted % Received Adopted % Tunduru 1,155 1,045 90 3,691 3,697 100 104 0 0 Songea Rural 1,987 1,759 89 1,835 1,610 88 1,148 1,148 100 Mbinga 5,055 5,839 115 5,865 6,387 109 6,231 4,141 66 Songea Urban 960 0 1,062 1,062 100 790 653 83 Namtumbo 7,842 6,843 87 7,051 6,325 90 6,546 2,006 31 Total 16,999 16,254 96 19,504 19,080 98 14,819 7,947 54 District District District Organic Fertilizer Use Vermin Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Ruvuma Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Ruvuma Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Ruvuma Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 219 Received Adopted % Received Adopted % Tunduru 0 0 0 0 0 0 Songea Rural 308 0 0 610 302 50 Mbinga 1,041 909 87 1,309 649 50 Songea Urban 357 0 0 658 191 29 Namtumbo 5,546 506 9 5,554 866 16 Total 7,252 1,415 20 8,131 2,009 25 Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Ruvuma Region District Beekeeping Tanzania Agriculture Sample Census - 2003 Ruvuma 220 Appendix II 221 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 222 Number % Number % Tunduru 0 0 46,898 100 46,898 Songea Rural 76 0 30,697 100 30,772 Mbinga 0 0 77,447 100 77,447 Songea Urban 27 0 6,915 100 6,943 Namtumbo 69 0 29,046 100 29,115 Total 172 0 191,003 100 191,175 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Songea Rural . . . . . . Songea Urban 55 55 33 . . . Namtumbo . . . . 757 Total 55 55 33 . 757 . Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Songea Rural 227 151 0 227 151 0 Songea Urban . . . 55 55 33 Namtumbo . . . . 757 . Total 227 151 0 282 963 33 Number % Number % Number % Tunduru 3,668 7 43,230 32 46,898 25 Songea Rural 8,799 16 20,903 16 29,701 16 Mbinga 35,657 65 41,299 31 76,956 41 Songea Urban 1,878 3 5,038 4 6,915 4 Namtumbo 4,532 8 23,792 18 28,325 15 Total 54,534 100 134,261 100 188,795 100 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Ruvuma Region Households Using Draft Animals Household Not Using Draft Animals Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region District Oxen Type of Craft Bulls Type of Craft District cont… ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Ruvuma Region Cows Total District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 223 Area (Ha) % Area (Ha) % Area (Ha) % Tunduru 1,439 6 56 5 1,495 6 Songea Rural 1,842 8 117 10 1,959 8 Mbinga 17,255 78 835 74 18,089 77 Songea Urban 585 3 17 2 602 3 Namtumbo 1,108 5 99 9 1,207 5 Total 22,227 100 1,124 100 23,351 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Ruvuma Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census - 2003 Ruvuma 224 Appendix II 225 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 226 Number % Number % Tunduru 501 1 46,397 99 46,898 5,276 Songea Rural 2,269 7 28,503 93 30,772 8,578 Mbinga 12,325 16 65,122 84 77,447 25,335 Songea Urban 734 11 6,209 89 6,943 1,799 Namtumbo 1,008 3 28,107 97 29,115 8,567 Total 16,837 9 174,338 91 191,175 49,556 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Tunduru 205 3,536 87.5 0 . 0.00 296 504 12.5 501 4,040 3.3 Songea Rural 1,293 7,853 70.3 153 153 0.00 1,204 3,157 0.0 2,269 11,164 9.2 Mbinga 10,797 93,097 92.3 0 . 0.00 2,575 7,810 7.7 12,325 100,907 83.3 Songea Urban 325 894 39.7 27 27 0.00 462 1,329 59.1 734 2,250 1.9 Namtumbo 289 504 17.9 0 . 0.00 864 2,311 82.1 1,008 2,815 2.3 Total 12,909 105,884 87.4 181 181 0.15 5,401 15,111 12.5 16,837 121,175 100.0 Number % Number % 1-5 15,088 90 36,610 30 2 6-10 1,009 6 7,464 6 7 11-15 297 2 3,667 3 12 16-20 130 1 2,076 2 16 21-30 107 1 2,453 2 23 31-40 77 0 2,539 2 33 151+ 129 1 66,366 55 513 Total 16,837 100 121,175 100 7 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Ruvuma Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture households Total livestock keeping households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 227 Number % Number % Number % Number % Bulls 6,792 78.3 27 0.3 1,853 21.4 8,673 7.2 Cows 18,705 76.5 76 0.3 5,658 23.2 24,440 20.2 Steers 187 71.2 . 0.0 76 0.0 263 0.2 Heifers 70,178 95.8 . 0.0 3,077 4.2 73,256 60.5 Male Calves 5,362 68.3 77 1.0 2,414 30.7 7,853 6.5 Female Calves 4,658 69.6 . 0.0 2,033 30.4 6,691 5.5 Total 105,884 87.4 181 0.1 15,111 12.5 121,175 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru 312 1,879 . 107 632 607 3,536 Songea Rural 1,611 2,831 . 1,815 909 687 7,853 Mbinga 4,789 13,508 132 67,922 3,643 3,102 93,097 Songea Urban 80 272 55 190 107 191 894 Namtumbo . 216 . 144 72 72 504 Total 6,792 18,705 187 70,178 5,362 4,658 105,884 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru . . . . . . . Songea Rural . 76 . . 77 . 153 Mbinga . . . . . . . Songea Urban 27 . . . . . 27 Namtumbo . . . . . . . Total 27 76 . . 77 . 181 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle mproved Beef Cattle Improved Dairy Cattle Category of Cattle 18.6 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 228 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru . 207 . 89 104 103 504 Songea Rural 299 1,201 76 380 747 455 3,157 Mbinga 874 2,924 . 1,948 1,022 1,043 7,810 Songea Urban 245 459 . 301 107 216 1,329 Namtumbo 435 866 . 360 434 216 2,311 Total 1,853 5,658 76 3,077 2,414 2,033 15,111 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru 312 2,086 . 195 736 710 4,040 Songea Rural 1,910 4,109 76 2,195 1,733 1,142 11,164 Mbinga 5,663 16,432 132 69,870 4,664 4,145 100,907 Songea Urban 353 731 55 491 214 407 2,250 Namtumbo 435 1,082 . 504 505 288 2,815 Total 8,673 24,440 263 73,256 7,853 6,691 121,175 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 229 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 230 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Tunduru 6,145 42,927 98.6 104 622 1.4 0 . 0.0 6,145 43,548 14.1 Songea Rural 13,477 57,045 93.8 229 1,221 0.0 460 2,524 4.2 13,477 60,790 19.6 Mbinga 32,782 121,530 99.2 394 527 0.0 250 508 0.4 32,782 122,564 39.6 Songea Urban 2,428 9,720 96.8 81 108 1.1 81 216 2.1 2,455 10,044 3.2 Namtumbo 13,450 71,144 97.9 289 1,006 1.4 286 499 0.7 13,522 72,649 23.5 Total 68,282 302,365 97.7 1,097 3,483 1.1 1,078 3,747 1.2 68,381 309,595 100.0 Number % Number % 1-4 42,519 62 104,318 34 2 5-9 20,673 30 129,592 42 6 10-14 2,948 4 32,845 11 11 15-19 1,435 2 23,169 7 16 20-24 418 1 8,552 3 20 25-29 212 0 5,835 2 27 30-39 176 0 5,285 2 30 Total 68,381 100 309,595 100 5 Total Goat District 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Herd Size Goat Rearing Households Head of Goats Average Number Per Household Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 231 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 46,354 97.3 507 1.1 779 1.6 47,640 15.4 Castrated Goat 2,805 77.5 427 0.0 386 0.0 3,617 1.2 She Goat 175,170 99.5 492 0.3 446 0.3 176,108 56.9 Male Kid 34,555 96.3 591 1.6 719 2.0 35,865 11.6 She Kid 43,481 93.8 1,466 3.2 1,417 3.1 46,365 15.0 Total 302,365 97.7 3,483 1.1 3,747 1.2 309,595 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru 6,252 422 21,475 6,927 7,851 42,927 Songea Rural 8,826 154 34,332 5,999 7,734 57,045 Mbinga 18,493 1,529 74,987 12,801 13,719 121,530 Songea Urban 1,528 . 5,354 1,035 1,803 9,720 Namtumbo 11,255 701 39,022 7,792 12,374 71,144 Total 46,354 2,805 175,170 34,555 43,481 302,365 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru . . . . 622 622 Songea Rural . . 228 461 533 1,221 Mbinga . . 265 131 131 527 Songea Urban . . . . 108 108 Namtumbo 507 427 . . 73 1,006 Total 507 427 492 591 1,466 3,483 Improved Dairy Goats 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Total Category of Goats 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 232 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru . . . . . . Songea Rural 537 . 77 692 1,218 2,524 Mbinga . 386 122 . . 508 Songea Urban 27 . 108 27 54 216 Namtumbo 215 . 139 . 145 499 Total 779 386 446 719 1,417 3,747 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru 6,252 422 21,475 6,927 8,472 43,548 Songea Rural 9,362 154 34,636 7,152 9,486 60,790 Mbinga 18,493 1,915 75,373 12,932 13,851 122,564 Songea Urban 1,555 . 5,462 1,062 1,965 10,044 Namtumbo 11,977 1,127 39,161 7,792 12,591 72,649 Total 47,640 3,617 176,108 35,865 46,365 309,595 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 233 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 234 Number % Number % Number % Ram 3,840 100 . 0 3,840 16 Castrated Sheep 179 100 . 0 179 1 She Sheep 14,616 100 . 0 14,616 60 Male Lamb 1,918 67 924 0 2,842 12 She Lamb 2,980 100 . 0 2,980 12 Total 23,534 96 924 4 24,458 100 Number % Number % Tunduru 1,446 3 45,452 97 46,898 5,276 Songea Rural 1,135 4 29,637 96 30,772 8,578 Mbinga 4,438 6 73,008 94 77,447 25,335 Songea Urban 82 1 6,860 99 6,943 1,799 Namtumbo 288 1 28,827 99 29,115 8,567 Total 7,390 4 183,785 96 191,175 49,556 Number % Number % Number % Tunduru 5,671 100 . 0 5,671 23 Songea Rural 4,070 100 . 0 4,070 17 Mbinga 12,148 93 924 7 13,073 53 Songea Urban 275 100 . 0 275 1 Namtumbo 1,371 100 . 0 1,371 6 Total 23,534 96 924 4 24,458 100 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 5,621 77 13,430 55 2 5-9 1,506 21 9,705 40 6 10-14 132 2 1,323 5 10 Total 7,258 100 24,458 100 3 20.1 Total Number of Sheep By Breed and on 1st October 2003 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households Breed Number of Indigenous District 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 235 Number of Households Average Number of Households Average Number of Households Average Tunduru 1,446 4 0 . 1,446 4 Songea Rural 1,135 4 0 . 1,135 4 Mbinga 4,176 3 263 4 4,307 3 Songea Urban 82 3 0 . 82 3 Namtumbo 288 5 0 . 288 5 Total 7,128 3 263 4 7,258 3 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru 799 . 3,301 628 943 5,671 Songea Rural 830 . 2,639 303 299 4,070 Mbinga 1,969 124 7,718 915 1,421 12,148 Songea Urban 27 55 165 . 27 275 Namtumbo 216 . 794 72 289 1,371 Total 3,840 179 14,616 1,918 2,980 23,534 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru . . . . . . Songea Rural . . . . . . Mbinga . . . 924 . 924 Songea Urban . . . . . . Namtumbo . . . . . . Total . . . 924 . 924 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru 799 . 3,301 628 943 5,671 Songea Rural 830 . 2,639 303 299 4,070 Mbinga 1,969 124 7,718 1,840 1,421 13,073 Songea Urban 27 55 165 . 27 275 Namtumbo 216 . 794 72 289 1,371 Total 3,840 179 14,616 2,842 2,980 24,458 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Ruvuma Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Ruvuma 236 Appendix II 237 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 238 Number % Number % 1-4 45,332 86 80,159 59 2 5-9 5,941 11 37,676 28 6 10-14 1,262 2 13,447 10 11 15-19 211 0 3,669 3 17 Total 52,746 100 134,951 100 3 District Number of Household Number of Pig Average Number Per Household Mbinga 40,973 102,373 2 Songea Rural 8,397 20,763 2 Namtumbo 2,439 6,909 3 Songea Urban 849 3,308 4 Tunduru 89 1,598 18 Total 52,746 134,951 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Tunduru 89 . 621 355 533 1,598 Songea Rural 2,677 2,217 7,630 2,596 5,642 20,763 Mbinga 15,232 5,861 39,488 16,512 25,280 102,373 Songea Urban 899 218 901 494 796 3,308 Namtumbo 1,006 576 3,450 650 1,228 6,909 Total 19,903 8,872 52,090 20,607 33,479 134,951 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 239 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 240 Number of Households % Number of Households % Tunduru 1,310 26 3,756 74 5,066 Songea Rural 4,495 52 4,082 48 8,578 Mbinga 11,855 47 13,349 53 25,203 Songea Urban 820 49 845 51 1,664 Namtumbo 2,666 31 5,902 69 8,567 Total 21,145 43 27,933 57 49,078 Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 826 17 404 4 396 18 193 2 Songea Rural 1,221 26 2,434 22 381 18 2,444 20 Mbinga 1,674 35 6,046 55 1,028 47 8,248 67 Songea Urban 329 7 354 3 82 4 438 4 Namtumbo 719 15 1,804 16 287 13 1,008 8 Total 4,770 100 11,042 100 2,175 100 12,331 100 Number of Households % Number of Households % Tunduru 906 19 3,845 81 4,751 Songea Rural 2,814 33 5,611 67 8,425 Mbinga 9,358 39 14,594 61 23,952 Songea Urban 302 20.9 1,146 79 1,448 Namtumbo 1,661 21.1 6,201 79 7,863 Total 15,041 32 31,397 68 46,438 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 510 56 194 21 98 11 103 11 0 0 906 Songea Rural 917 33 1,209 43 153 5 0 0 536 19 2,814 Mbinga 2,212 24 4,156 44 789 8 132 1 2,069 22 9,358 Songea Urban 55 18 220 73 0 0 0 0 27 9 302 Namtumbo 723 44 649 39 0 0 0 0 289 17 1,661 Total 4,417 29 6,428 43 1,041 7 235 2 2,921 19 15,041 Dipping Smearing Other 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year Method of Tick Control Total District None Spraying District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 241 Number of Households % Number of Households % Tunduru 1,023 20 4,042 80 5,066 Songea Rural 1,220 14 7,358 86 8,578 Mbinga 3,350 14 20,327 86 23,677 Songea Urban 110 7 1,393 93 1,503 Namtumbo 1,230 15 6,848 85 8,078 Total 6,933 15 39,968 85 46,902 Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 611 60 308 30 0 0 104 10 1,023 Songea Rural 764 63 456 37 0 0 0 0 1,220 Mbinga 2,303 69 916 27 132 4 0 0 3,350 Songea Urban 27 25 82 75 0 0 0 0 110 Namtumbo 868 71 362 29 0 0 0 0 1,230 Total 4,574 66 2,124 31 132 2 104 1 6,933 Trapping Method of Tsetse Flies Control 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year Total District None Spray Dipping District Tsetse Flies Problems No Tsetse Flies Problems 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District Total Tanzania Agriculture Sample Census - 2003 Ruvuma 242 Appendix II 243 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 244 Number % Type Number Indigenous 1,536,330 99 Ducks 38,878 Layer 6,037 0 Turkeys 868 Broiler 13,250 1 Rabbits 42,163 . . . Donkeys 4,600 . . . Horse 0 . . . Other 17,025 Total 1,555,617 100 103,534 Indigenous Chicken Layer Broiler Ducks Turkeys Rabbits Donkeys Other Tunduru 256,689 . 640 257,329 Tunduru 15,865 . 984 984 14,460 Songea Rural 274,591 . 5,318 279,909 Songea Rural 3,422 689 2,963 . . Mbinga 644,439 2,749 646 647,834 Mbinga 10,426 124 31,130 3,616 1,580 Songea Urban 60,398 2,499 2,884 65,782 Songea Urban 2,970 55 2,472 . 408 Namtumbo 300,212 788 3,762 304,763 Namtumbo 6,195 . 4,614 . 576 Total 1,536,330 6,037 13,250 1,555,617 Total 38,878 868 42,163 4,600 17,025 Type of Livestock/Poultry 1995 1999 2003 Number % Cattle 75,027 79,969 121,175 1 - 4 36,278 26 96,787 3 Improved Cattle 1,325 3,738 15,292 5 - 9 40,716 29 268,983 7 Goats 348,509 537,843 309,595 10 - 19 41,041 29 546,003 13 Sheep 41,890 49,801 24,458 20 - 29 12,834 9 287,289 22 Pigs 89,600 182,347 134,951 30 - 39 4,822 3 156,927 33 Indigenous Chicken 1,091,260 1,757,385 1,536,330 40 - 49 1,490 1 66,756 45 Layers - 11,709 6,037 50 - 99 2,103 2 132,872 63 Broilers 974 30,064 13,250 Total 139,284 100 1,555,617 11 Total Chickens 1,092,234 1,799,158 1,555,617 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e LIVESTOCK/POULTRY POPULATION TREND Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household District 23c Head Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 Type of Livestock Chicken Type Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 245 FISH FARMING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 246 Number % Number % Tunduru 298 0.6 46,600 99.4 46,898 Songea Rural 1,294 4.2 29,479 95.8 30,772 Mbinga 910 1.2 76,537 98.8 77,447 Songea Urban 601 8.7 6,342 91.3 6,943 Namtumbo 933 3.2 28,182 96.8 29,115 Total 4,035 2.1 187,140 97.9 191,175 Natural Pond Dug out PonWater ResevOther Total Tunduru 0 298 0 0 298 Songea Rural 77 1,369 0 0 1,446 Mbinga 0 910 132 0 1,042 Songea Urban 0 792 0 27 819 Namtumbo 361 789 0 72 1,222 Total 438 4,158 132 100 4,827 Own Pond Governmen t Institution NGOs / Project Neighbour Other Total Number Number Number Number Number Number Tunduru 0 0 89 209 0 298 Songea Rural 77 77 227 1,065 0 1,446 Mbinga 0 0 132 910 0 1,042 Songea Urban 0 137 0 682 0 819 Namtumbo 0 361 0 788 73 1,222 Total 77 575 448 3,654 73 4,827 Neighbor Trader at Farm Did not Sell Other Total Number Number Number Number Number Tunduru 0 0 209 89 298 Songea Rural 612 77 684 0 1,372 Mbinga 0 0 918 124 1,042 Songea Urban 435 27 357 0 819 Namtumbo 720 0 641 0 1,361 Total 1,767 104 2,808 213 4,893 District Number of Tilapia Number of Carp Number of Others Tunduru 27,263 0 0 Songea Rural 169,846 2,923 0 Mbinga 49,022 0 5,159 Songea Urban 197,054 439 19,282 Namtumbo 247,863 18,990 20,222 Total 691,048 22,353 44,663 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year District 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the District Source of Fingerling 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year District 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year Fish Farming System 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 247 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 248 Number % Number % Tunduru 3,918 8.4 42,980 91.6 46,898 5,276 74 Songea Rural 5,527 18.0 25,245 82.0 30,772 8,578 64 Mbinga 14,420 18.6 63,027 81.4 77,447 25,335 57 Songea Urban 1,336 19.2 5,606 80.8 6,943 1,799 74 Namtumbo 5,384 18.5 23,731 81.5 29,115 8,567 63 Total 30,585 16.0 160,590 84.0 191,175 49,556 62 Number % Number % Number % Number % Number % Tunduru 3,623 100.0 0 0.0 0 0.0 0 0.0 0 0.0 Songea Rural 5,377 75.0 675 9.4 448 6.2 522 7.3 149 2.1 Mbinga 13,366 80.3 1,832 11.0 395 2.4 781 4.7 263 1.6 Songea Urban 1,282 45.4 515 18.2 432 15.3 350 12.4 247 8.7 Namtumbo 5,167 85.8 429 7.1 71 1.2 214 3.6 143 2.4 Total 28,815 79.4 3,450 9.5 1,346 3.7 1,868 5.1 802 2.2 Other Source of extension advice Total Total Number of households raising livestock % receiving advice out of total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Large Scale Farmer District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 249 Government NGO / Development Project Large Scale Farmer Total Tunduru 2,276 0 0 2,276 5,276 43.1 Songea Rural 2,130 152 74 2,356 8,578 27.5 Mbinga 7,262 0 129 7,391 25,335 29.2 Songea Urban 682 110 0 791 1,799 44.0 Namtumbo 2,723 0 72 2,796 8,567 32.6 Total 15,073 261 275 15,609 49,556 31.5 % 96.6 1.7 1.8 100 Government NGO / Development Project Large Scale Farmer Other(forme r coding) Other Total Tunduru 1,847 0 0 0 0 1,847 5,276 35.0 Songea Rural 2,439 227 0 0 0 2,667 8,578 31.1 Mbinga 10,149 128 394 123 0 10,794 25,335 42.6 Songea Urban 677 82 0 0 27 787 1,799 43.7 Namtumbo 3,223 0 72 0 0 3,295 8,567 38.5 Total 18,336 437 465 123 27 19,390 49,556 39.1 % 95 2 2 1 0 100 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District District Total Number of households raising livestock % receiving advice out of total Source of Advice on Feeds and Proper Feeding Total Number of households raising livestock % receiving advice out of total Source of Advice on Housing Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 250 Government NGO / Development Project Large Scale Farmer Other Total Tunduru 202 0 0 0 202 5,276 3.8 Songea Rural 532 76 76 0 684 8,578 8.0 Mbinga 2,311 0 0 0 2,311 25,335 9.1 Songea Urban 245 136 0 27 408 1,799 22.7 Namtumbo 1,298 0 0 0 1,298 8,567 15.1 Total 4,588 212 76 27 4,903 49,556 9.9 % 93.6 4.3 1.5 0.5 100.0 Government NGO / Development Project Total Tunduru 103 0 103 5,276 2.0 Songea Rural 530 76 605 8,578 7.1 Mbinga 2,047 0 2,047 25,335 8.1 Songea Urban 299 82 381 1,799 21.2 Namtumbo 1,298 0 1,298 8,567 15.1 Total 4,276 158 4,434 49,556 8.9 % 96.4 3.6 100 District District % receiving advice out of total Source of Advice on Milk Hygene Total Number of households raising livestock 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total Number of households raising livestock Source of Advice on Proper Milking Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 251 Government NGO / Development Project Large scale Farmer Total Tunduru 1,146 0 0 1,146 5,276 22 Songea Rural 3,170 76 0 3,246 8,578 38 Mbinga 9,057 128 129 9,314 25,335 37 Songea Urban 761 110 0 871 1,799 48 Namtumbo 3,736 0 72 3,808 8,567 44 Total 17,871 314 201 18,385 49,556 37 % 97.2 1.7 1.1 100 Government Total Songea Rural 302 302 8,578 4 Mbinga 2,084 2,084 25,335 8 Songea Urban 135 135 1,799 8 Namtumbo 358 358 8,567 4 Total 2,879 2,879 44,280 7 % 100.0 100.0 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control District Total Number of households raising livestock Source of Advice on Herd/Flock Size 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 252 Government NGO / Development Project Large Scale Farmer Other Songea Rural 379 0 0 0 379 8,578 4 Mbinga 2,332 128 129 0 2,589 25,335 10 Songea Urban 163 55 0 27 246 1,799 14 Namtumbo 1,649 0 0 0 1,649 8,567 19 Total 4,524 183 129 27 4,863 44,280 11 % 93.0 3.8 2.7 0.6 100 Government NGO / Development Project Co-operative Total Songea Rural 685 76 76 836 8,578 10 Mbinga 4,944 132 265 5,341 25,335 21 Songea Urban 436 27 0 463 1,799 26 Namtumbo 1,938 72 217 2,227 8,567 26 Total 8,003 308 557 8,868 44,280 20 % 90.2 3.5 6.3 100 District 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Source of Advice on Pasture Establishment and Selection Total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Source of Advice on Group Formation and Strenghthening Total Number of households raising livestock Total Number of households raising livestock Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 253 Government NGO / Development Project Large Scale Farmer Total Tunduru 104 0 0 104 5,276 2 Songea Rural 532 76 0 608 8,578 7 Mbinga 2,325 0 129 2,454 25,335 10 Songea Urban 268 110 0 378 1,799 21 Namtumbo 1,515 0 0 1,515 8,567 18 Total 4,745 186 129 5,059 49,556 10 % 93.8 3.7 2.5 100 Government NGO / Development Project Large Scale Farmer Other Total Tunduru 203 0 0 0 203 5,276 3.8 Songea Rural 831 76 0 0 907 8,578 10.6 Mbinga 3,636 0 0 0 3,636 25,335 14.4 Songea Urban 216 55 27 27 326 1,799 18.1 Namtumbo 1,798 0 0 0 1,798 8,567 21.0 Total 6,684 131 27 27 6,870 49,556 13.9 % 97.3 1.9 0.4 0.4 100.0 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Total Number of households raising livestock Total Number of households raising livestock District Source of Advice on Calf Rearing % receiving advice out of total Source of Advice on Improved Bulls % receiving advice out of total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 254 Number % Number % Number % Number % Number % Tunduru 624 17 2,783 75 319 9 0 0 0 0 3,727 Songea Rural 450 8 3,321 61 1,602 29 76 1 0 0 5,449 Mbinga 2,708 18 9,892 65 1,681 11 129 1 787 5 15,197 Songea Urban 355 19 1,038 54 493 26 27 1 0 0 1,914 Namtumbo 710 18 3,008 75 216 5 0 0 71 2 4,005 Total 4,848 16 20,043 66 4,311 14 232 1 858 3 30,292 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 255 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 256 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads District Capital Tunduru 18.7 1.5 10.9 3.0 32.0 7.6 288.3 4.5 22.7 43.9 274.1 53.8 Songea Rural 18.0 1.5 3.2 0.5 46.6 8.5 54.2 14.6 44.6 40.8 23.6 54.2 Mbinga 14.9 2.7 8.6 2.5 27.0 6.1 125.0 8.8 34.8 43.3 106.4 47.8 Songea Urban 5.0 4.3 1.3 0.9 10.8 8.3 7.6 5.1 9.1 7.8 4.4 7.8 Namtumbo 15.4 1.3 19.8 3.6 70.5 6.6 79.7 7.6 56.6 62.3 73.4 56.9 Total 16.0 2.1 9.7 2.4 37.4 7.0 142.5 8.4 35.8 44.6 125.5 50.2 Regional Capital 142.5 Tarmac Roads 125.5 District Capital 50.2 Tertiary Market 44.6 Hospitals 37.4 Secondary Market 35.8 Secondary Schools 16.0 All weather roads 9.7 Primary Markets 8.4 Health Clinics 7.0 Feeder Roads 2.4 Primary Schools 2.1 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 257 No of households % No of households % No of households % No of households % No of households % Tunduru 1,401 3.0 2,421 5.2 11,261 24.0 14,773 31.5 17,042 36.3 46,898 18.7 Songea Rural 380 1.2 1,819 5.9 9,718 31.6 10,103 32.8 8,752 28.4 30,772 18.0 Mbinga 3,621 4.7 10,340 13.4 23,756 30.7 23,386 30.2 16,344 21.1 77,447 14.9 Songea Urban 541 7.8 1,377 19.8 3,985 57.4 1,040 15.0 0 0.0 6,943 5.0 Namtumbo 780 2.7 3,694 12.7 9,555 32.8 7,865 27.0 7,222 24.8 29,115 15.4 Total 6,723 3.5 19,651 10.3 58,274 30.5 57,167 29.9 49,360 25.8 191,175 16.0 No of households % No of households % No of households % No of households % No of households % Tunduru 24,121 51.4 2,719 5.8 8,103 17.3 2,560 5.5 9,395 20.0 46,898 10.9 Songea Rural 21,474 69.8 4,876 15.8 2,752 8.9 230 0.7 1,440 4.7 30,772 3.2 Mbinga 29,271 37.8 15,930 20.6 11,907 15.4 11,040 14.3 9,299 12.0 77,447 8.6 Songea Urban 4,425 63.7 1,668 24.0 795 11.4 0 0.0 55 0.8 6,943 1.3 Namtumbo 19,601 67.3 3,076 10.6 714 2.5 1,734 6.0 3,990 13.7 29,115 19.8 Total 98,892 51.7 28,269 14.8 24,271 12.7 15,564 8.1 24,179 12.6 191,175 9.7 No of households % No of households % No of households % No of households % No of households % Tunduru 28,261 60.3 10,812 23.1 6,975 14.9 213 0.5 638 1.4 46,898 3.0 Songea Rural 27,646 89.8 2,131 6.9 919 3.0 0 0.0 77 0.3 30,772 0.5 Mbinga 48,059 62.1 18,317 23.7 7,018 9.1 1,830 2.4 2,223 2.9 77,447 2.5 Songea Urban 5,602 80.7 930 13.4 301 4.3 0 0.0 110 1.6 6,943 0.9 Namtumbo 24,395 83.8 1,855 6.4 701 2.4 1,445 5.0 719 2.5 29,115 3.6 Total 133,962 70.1 34,045 17.8 15,914 8.3 3,488 1.8 3,766 2.0 191,175 2.4 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year District Distance to Secondary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of households Mean Distance Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 258 No of households % No of households % No of households % No of households % No of households % Tunduru 1,040 2.2 1,409 3.0 4,372 9.3 10,625 22.7 29,451 62.8 46,898 32.0 Songea Rural 0 0.0 76 0.2 5,237 17.0 6,869 22.3 18,590 60.4 30,772 46.6 Mbinga 3,060 4.0 5,692 7.3 14,968 19.3 20,386 26.3 33,341 43.1 77,447 27.0 Songea Urban 0 0.0 531 7.6 4,304 62.0 1,807 26.0 302 4.3 6,943 10.8 Namtumbo 72 0.2 0 0.0 144 0.5 574 2.0 28,325 97.3 29,115 70.5 Total 4,172 2.2 7,708 4.0 29,026 15.2 40,261 21.1 110,008 57.5 191,175 37.4 No of households % No of households % No of households % No of households % No of households % Tunduru 14,108 30.1 6,937 14.8 20,475 43.7 4,547 9.7 831 1.8 46,898 7.6 Songea Rural 4,865 15.8 6,702 21.8 13,943 45.3 3,596 11.7 1,666 5.4 30,772 8.5 Mbinga 9,284 12.0 26,766 34.6 28,584 36.9 10,076 13.0 2,737 3.5 77,447 6.1 Songea Urban 548 7.9 1,482 21.3 3,487 50.2 1,290 18.6 136 2.0 6,943 8.3 Namtumbo 4,591 15.8 8,903 30.6 7,618 26.2 4,237 14.6 3,766 12.9 29,115 6.6 Total 33,396 17.5 50,790 26.6 74,107 38.8 23,745 12.4 9,137 4.8 191,175 7.0 No of households % No of households % No of households % No of households % No of households % Tunduru 27,318 58.2 14,200 30.3 5,065 10.8 107 0.2 209 0.4 46,898 1.5 Songea Rural 11,077 36.0 15,770 51.2 3,772 12.3 77 0.3 77 0.2 30,772 1.5 Mbinga 28,312 36.6 38,270 49.4 9,969 12.9 527 0.7 369 0.5 77,447 2.7 Songea Urban 2,421 34.9 2,915 42.0 1,525 22.0 0 0.0 82 1.2 6,943 4.3 Namtumbo 11,929 41.0 14,823 50.9 1,932 6.6 287 1.0 144 0.5 29,115 1.3 Total 81,057 42.4 85,977 45.0 22,263 11.6 997 0.5 881 0.5 191,175 2.1 Above 20 km Above 20 km 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 259 No of households % No of households % No of households % No of households % No of households % Tunduru 0 0.0 0 0.0 0 0.0 418 0.9 46,480 99.1 46,898 288.3 Songea Rural 76 0.2 0 0.0 228 0.7 5,871 19.1 24,598 79.9 30,772 54.2 Mbinga 748 1.0 0 0.0 380 0.5 110 0.1 76,209 98.4 77,447 125.0 Songea Urban 55 0.8 505 7.3 4,494 64.7 1,834 26.4 55 0.8 6,943 7.6 Namtumbo 216 0.7 0 0.0 0 0.0 72 0.2 28,827 99.0 29,115 79.7 Total 1,095 0.6 505 0.3 5,102 2.7 8,306 4.3 176,168 92.2 191,175 142.5 No of households % No of households % No of households % No of households % No of households % Tunduru 0 0.0 994 2.1 2,478 5.3 3,389 7.2 40,037 85.4 46,898 53.8 Songea Rural 77 0.3 0 0.0 152 0.5 5,794 18.8 24,749 80.4 30,772 54.2 Mbinga 110 0.1 1,425 1.8 6,485 8.4 16,056 20.7 53,371 68.9 77,447 47.8 Songea Urban 0 0.0 505 7.3 4,522 65.1 1,834 26.4 82 1.2 6,943 7.8 Namtumbo 0 0.0 1,012 3.5 1,589 5.5 2,316 8.0 24,198 83.1 29,115 56.9 Total 187 0.1 3,936 2.1 15,225 8.0 29,389 15.4 142,438 74.5 191,175 50.2 No of households % No of households % No of households % No of households % No of households % Tunduru 603 1.3 0 0.0 98 0.2 0 0.0 46,196 98.5 46,898 274.1 Songea Rural 4,078 13.3 2,714 8.8 5,768 18.7 6,203 20.2 12,010 39.0 30,772 23.6 Mbinga 2,060 2.7 264 0.3 380 0.5 393 0.5 74,349 96.0 77,447 106.4 Songea Urban 1,121 16.1 1,570 22.6 3,377 48.6 848 12.2 27 0.4 6,943 4.4 Namtumbo 1,499 5.1 0 0.0 215 0.7 2,163 7.4 25,238 86.7 29,115 73.4 Total 9,362 4.9 4,548 2.4 9,838 5.1 9,607 5.0 157,821 82.6 191,175 125.5 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 260 No of households % No of households % No of households % No of households % No of households % Tunduru 21,190 45.2 4,948 10.6 17,147 36.6 3,293 7.0 320 0.7 46,898 4.5 Songea Rural 3,598 11.7 1,658 5.4 7,491 24.3 10,172 33.1 7,853 25.5 30,772 14.6 Mbinga 14,702 19.0 15,512 20.0 26,743 34.5 11,692 15.1 8,799 11.4 77,447 8.8 Songea Urban 788 11.3 1,347 19.4 4,177 60.2 603 8.7 27 0.4 6,943 5.1 Namtumbo 5,887 20.2 8,040 27.6 6,824 23.4 6,349 21.8 2,015 6.9 29,115 7.6 Total 46,164 24.1 31,504 16.5 62,382 32.6 32,110 16.8 19,015 9.9 191,175 8.4 No of households % No of households % No of households % No of households % No of households % Tunduru 2,828 6.0 568 1.2 2,674 5.7 5,201 11.1 35,625 76.0 46,898 43.9 Songea Rural 1,935 6.3 761 2.5 3,548 11.5 5,791 18.8 18,738 60.9 30,772 40.8 Mbinga 2,963 3.8 1,534 2.0 8,059 10.4 18,425 23.8 46,466 60.0 77,447 43.3 Songea Urban 82 1.2 611 8.8 4,252 61.2 1,916 27.6 82 1.2 6,943 7.8 Namtumbo 788 2.7 1,299 4.5 1,377 4.7 2,388 8.2 23,264 79.9 29,115 62.3 Total 8,597 4.5 4,773 2.5 19,910 10.4 33,721 17.6 124,175 65.0 191,175 44.6 No of households % No of households % No of households % No of households % No of households % Tunduru 13,925 29.7 213 0.5 1,906 4.1 2,008 4.3 28,846 61.5 46,898 22.7 Songea Rural 2,091 6.8 0 0.0 4,783 15.5 6,788 22.1 17,110 55.6 30,772 44.6 Mbinga 9,061 11.7 699 0.9 2,105 2.7 6,348 8.2 59,234 76.5 77,447 34.8 Songea Urban 1,296 18.7 433 6.2 2,882 41.5 1,619 23.3 713 10.3 6,943 9.1 Namtumbo 1,772 6.1 1,217 4.2 1,303 4.5 1,663 5.7 23,160 79.5 29,115 56.6 Total 28,146 14.7 2,563 1.3 12,979 6.8 18,425 9.6 129,063 67.5 191,175 35.8 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 261 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 3,141 1 13,881 5 7,107 3 4,854 2 2,671 1 249,734 89 281,387 Songea Rural 1,966 1 11,710 6 5,086 3 1,442 1 1,061 1 163,368 88 184,633 Mbinga 3,252 1 18,515 4 21,961 5 11,930 3 3,548 1 405,472 87 464,680 Songea Urban 327 1 2,404 6 713 2 189 0 54 0 37,969 91 41,657 Namtumbo 1,943 1 13,169 8 10,169 6 862 0 504 0 148,044 85 174,692 Total 10,629 1 59,679 5 45,037 4 19,278 2 7,838 1 1,004,587 88 1,147,049 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 716 6 8,573 68 1,986 16 950 8 308 2 12,532 Songea Rural 222 2 8,364 73 2,137 19 682 6 76 1 11,480 Mbinga 2,348 10 14,881 62 4,831 20 1,568 7 263 1 23,892 Songea Urban 137 7 1,500 75 302 15 53 3 0 0 1,992 Namtumbo 1,436 10 10,938 78 1,652 12 72 1 0 0 14,098 Total 4,859 8 44,255 69 10,909 17 3,325 5 647 1 63,994 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 0 0 618 31 408 21 532 27 410 21 1,968 Songea Rural 227 75 0 0 0 0 76 25 0 0 303 Mbinga 648 5 2,430 18 5,367 39 4,272 31 1,134 8 13,851 Songea Urban 0 0 0 0 0 0 54 100 0 0 54 Namtumbo 0 0 1,438 39 2,026 55 72 2 144 4 3,680 Total 875 4 4,486 23 7,800 39 5,006 25 1,689 9 19,856 Total number of households Satisfaction of Using Veterinary Clinic Not Applicable 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 262 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 0 0 213 15 498 35 319 22 410 28 1,441 Songea Rural 758 91 0 0 0 0 76 9 0 0 834 Mbinga 0 0 0 0 264 50 261 50 0 0 525 Songea Urban 54 50 0 0 0 0 55 50 0 0 109 Namtumbo 289 45 0 0 360 55 0 0 0 0 649 Total 1,100 31 213 6 1,122 32 711 20 410 12 3,557 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 2,001 27 2,059 28 2,156 29 722 10 410 6 7,348 Songea Rural 77 2 455 15 1,655 53 229 7 682 22 3,098 Mbinga 124 1 808 7 5,868 49 4,413 37 755 6 11,968 Songea Urban 0 0 301 48 274 44 0 0 54 9 628 Namtumbo 0 0 649 15 2,741 63 575 13 360 8 4,325 Total 2,202 8 4,270 16 12,694 46 5,940 22 2,261 8 27,367 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 213 5 1,570 39 817 20 956 23 517 13 4,073 Songea Rural 302 67 0 0 76 17 74 16 0 0 452 Mbinga 132 2 396 5 5,366 66 1,155 14 1,134 14 8,184 Songea Urban 54 66 27 34 0 0 0 0 0 0 82 Namtumbo 73 14 0 0 360 71 72 14 0 0 504 Total 773 6 1,994 15 6,619 50 2,257 17 1,651 12 13,294 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 263 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 264 Table 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Total number of households Tunduru 1,036 1,049 44,724 89 46,898 Songea Rural 379 76 29,789 528 30,772 Mbinga 524 2,732 73,108 1,082 77,447 Songea Urban 82 191 6,128 542 6,943 Namtumbo 69 718 27,824 504 29,115 Total 2,090 4,767 181,572 2,745 191,175 % 1.1 2.5 95.0 1.4 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Total number of household s Tunduru 4 7,929 103 320 0 37,054 1,492 46,898 Songea Rural 3 10,485 306 76 0 16,807 3,099 30,772 Mbinga 3 33,950 524 0 0 40,472 2,501 77,447 Songea Urban 3 3,097 0 0 0 3,791 55 6,943 Namtumbo 4 8,485 218 73 73 19,849 419 29,115 Total 3 63,946 1,150 468 73 117,971 7,566 191,175 % 33.4 0.6 0.2 0.0 61.7 4.0 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 21,532 20 20,803 19 43,081 39 4,740 4 19,003 17 109,159 44.7 Landline phone 404 27 77 5 851 57 165 11 0 0 1,496 0.6 Mobile phone 309 13 302 12 1,224 50 487 20 138 6 2,460 1.0 Iron 8,238 17 8,490 17 22,196 45 2,126 4 8,566 17 49,616 20.3 Wheelbarrow 1,031 13 759 10 4,412 56 757 10 985 12 7,944 3.3 Bicycle 69,706 28.5 Vehicle 207 9 383 17 1,394 61 82 4 218 10 2,284 0.9 Television / Video 1,549 0.6 Total Number of Households 31,721 30,814 13 73,157 30 8,357 3 28,910 12 244,215 100.0 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District District Table 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Type of Owned Asset Total Tunduru Type of toilet Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 104 18.58 0 0 372 66.67 82 14.75 0 0 559 0.3 Solar 98 22.46 0 0 240 54.87 27 6.214 72 16.455 438 0.2 Gas (Biogas) 105 18.56 0 0 388 68.83 0 0.0 71 12.612 564 0.3 Hurricane Lamp 12,077 14.3 16,492 19.52 38,763 45.89 3,046 3.605 14,099 16.69 84,477 44.2 Pressure Lamp 1,053 18.4 909 15.89 2,612 45.65 220 3.84 928 16.223 5,722 3.0 Wick Lamp 32,404 33.4 13,069 13.47 34,589 35.66 3,568 3.678 13,381 13.793 97,011 50.7 Candles 107 22.26 0 0 228 47.65 0 0.0 144 30.099 479 0.3 Firewood 951 49.36 302 15.7 253 13.14 0 0.0 420 21.796 1,926 1.0 Total 46,898 25 30,772 16 77,447 41 6,943 3.6 29,115 15 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 0.0 153 68.0 0 0.0 0 0.0 72 32.0 225 0.1 Solar 104 14.9 150 21.5 389 55.7 55 7.9 0 0.0 698 0.4 Gas (Biogas) 104 45.9 0 0.0 123 54.1 0 0.0 0 0.0 227 0.1 Bottled Gas 104 33.4 76 24.3 132 42.4 0 0.0 0 0.0 312 0.2 Parraffin / Kerocine 0 0.0 77 99.4 0 0.0 0 0.0 0 0.0 77 0.0 Charcoal 500 14.1 532 15.0 1,894 53.3 487 13.7 143 4.0 3,555 1.9 Firewood 45,987 24.8 29,633 16.0 74,909 40.3 6,401 3.4 28,756 15.5 185,686 97.1 Crop Residues 0 0.0 77 51.4 0 0.0 0 0.0 72 48.6 149 0.1 Livestock Dung 98 56.5 76 43.5 0 0.0 0 0.0 0 0.0 174 0.1 Others 0.0 0.0 0.0 0.0 72 100.0 72 0.0 Total 46,898 24.5 30,772 16.1 77,447 40.5 6,943 3.6 29,115 15.2 191,175 100.0 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Cooking District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year Main Source of Energy for Lighting District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 266 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Total wet season 10,361 8,842 17,766 734 14,491 52,195 dry season 10,379 7,851 16,618 680 13,336 48,864 wet season 10,585 10,150 1,140 1,339 5,723 28,937 Dry season 9,859 10,147 1,399 1,366 5,723 28,493 wet season 417 4,391 1,928 273 1,301 8,311 Dry season 311 4,394 1,796 273 1,301 8,075 wet season 15,684 4,257 23,192 3,148 6,591 52,871 Dry season 15,860 5,171 23,432 3,010 7,458 54,932 wet season 5,982 2,297 24,468 1,340 434 34,520 Dry season 6,503 2,373 24,602 1,423 434 35,335 wet season 2,272 835 8,218 82 430 11,837 Dry season 3,986 835 9,125 110 430 14,487 wet season 0 0 0 27 0 27 Dry season 0 0 0 27 0 27 wet season 1,597 0 0 0 0 1,597 Dry season - - - - - - wet season 0 0 132 0 0 132 Dry season 0 0 0 27 72 100 wet season 0 0 475 0 0 475 Dry season 0 0 475 27 216 718 wet season 0 0 128 0 145 273 dry season 0 0 0 0 145 145 46,898 30,772 77,447 6,943 29,115 191,175 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Total wet season 22 29 23 11 50 27 dry season 22 26 21 10 46 26 wet season 23 33 1 19 20 15 Dry season 21 33 2 20 20 15 wet season 1 14 2 4 4 4 Dry season 1 14 2 4 4 4 wet season 33 14 30 45 23 28 Dry season 34 17 30 43 26 29 wet season 13 7 32 19 1 18 Dry season 14 8 32 20 1 18 wet season 5 3 11 1 1 6 Dry season 8 3 12 2 1 8 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 3 0 0 0 0 1 Dry season - - - - - - wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 1 0 0 0 Dry season 0 0 1 0 1 0 wet season 0 0 0 0 0 0 dry season 0 0 0 0 0 0 Total Agricultural Households per District 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season District Other District Source Season Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Tanker Truck Piped Water 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Protected Well Protected / Covered Spring Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Other Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Tanzania Agriculture sample Census - 2003 Ruvuma Region Appendix II 267 Tunduru Songea Rural Mbinga Songea Urban Namtumbo wet season 924 688 5,971 134 4,324 Dry season 840 610 6,073 159 4,542 wet season 13,670 13,505 28,655 2,504 10,619 Dry season 10,044 12,590 27,873 2,449 9,985 wet season 8,057 6,848 16,936 1,365 4,172 Dry season 8,453 6,847 16,927 1,394 4,098 wet season 10,262 5,861 11,269 1,066 2,793 Dry season 9,884 6,627 11,407 1,093 2,658 wet season 4,841 529 2,458 137 867 Dry season 5,455 529 2,206 110 852 wet season 4,825 2,654 6,843 1,273 3,087 Dry season 3,861 2,350 7,102 1,273 3,230 wet season 4,320 686 5,315 464 3,253 Dry season 8,361 1,219 5,859 465 3,750 Tunduru Songea Rural Mbinga Songea Urban Namtumbo wet season 2 2 8 2 15 Dry season 2 2 8 2 16 wet season 29 44 37 36 36 Dry season 21 41 36 35 34 wet season 17 22 22 20 14 Dry season 18 22 22 20 14 wet season 22 19 15 15 10 Dry season 21 22 15 16 9 wet season 10 2 3 2 3 Dry season 12 2 3 2 3 wet season 10 9 9 18 11 Dry season 8 8 9 18 11 wet season 9 2 7 7 11 Dry season 18 4 8 7 13 above one Hour 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes District 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season District above one Hour 40 - 49 Minutes 50 - 59 Minutes 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 268 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 318 1 0 0 2,325 3 409 6 553 2 3,605 1.9 Two 7,537 16 12,028 39 35,417 46 1,992 29 6,895 24 63,869 33.4 Three 39,043 83 0 39,440 51 4,542 65 21,598 74 123,291 64.5 Four 0 0 76 0 265 0 0 0 69 0 409 0.2 Total 46,898 100 30,772 100 77,447 100 6,943 100 29,115 100 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 26,776 57 8,968 29 20,819 27 1,911 28 7,554 26 66,028 35 One 9,702 21 10,484 34 20,819 27 2,207 32 9,354 32 52,566 27 Two 5,758 12 6,774 22 19,147 25 1,711 25 6,904 24 40,294 21 Three 2,896 6 2,881 9 10,653 14 706 10 3,938 14 21,074 11 Four 1,256 3 531 2 3,714 5 380 5 860 3 6,741 4 Five 210 0 681 2 1,422 2 27 0 361 1 2,702 1 Six 89 0 151 0 241 0 0 0 0 0 480 0 Seven 211 0 302 1 631 1 0 0 144 0 1,289 1 Total 46,898 100 30,772 100 77,447 100 6,943 100 29,115 100 191,175 100 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 269 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 10,069 32 5,326 17 9,519 30 822 3 6,194 19 31,930 17 One 6,863 16 9,520 22 17,299 40 1,798 4 7,892 18 43,373 23 Two 8,167 21 6,768 17 15,283 39 1,499 4 7,344 19 39,061 20 Three 7,166 24 5,243 17 12,406 41 1,301 4 4,082 14 30,198 16 Four 6,150 34 1,965 11 7,432 41 949 5 1,801 10 18,297 10 Five 4,369 34 1,420 11 5,637 43 464 4 1,082 8 12,971 7 Six 1,578 39 229 6 1,914 47 82 2 289 7 4,091 2 Seven 2,536 23 302 3 7,956 71 27 0 432 4 11,254 6 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 23,878 20 20,206 17 49,669 42 5,223 4 20,562 17 119,538 62.5 Seldom 14,136 29 6,626 14 19,938 41 1,204 2 6,264 13 48,168 25.2 Sometimes 4,044 32 2,808 22 4,367 35 192 2 1,138 9 12,550 6.6 Often 1,762 37 456 10 1,675 35 107 2 791 17 4,790 2.5 Always 3,078 50 677 11 1,797 29 217 4 360 6 6,129 3.2 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Status of Food Satisfaction District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Number of Days District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 270 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 7,929 12 10,485 16 33,950 53 3,097 5 8,485 13 63,946 33.4 Tiles 103 9 306 27 524 46 0 0 218 19 1,150 0.6 Concrete 320 68 76 16 0 0 0 0 73 15 468 0.2 Asbestos 0 0 0 0 0 0 0 0 73 100 73 0.0 Grass / Leaves 37,054 31 16,807 14 40,472 34 3,791 3 19,849 17 117,971 61.7 Grass & Mud 1,492 20 3,099 41 2,501 33 55 1 419 6 7,566 4.0 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 19,525 21 22,344 24 29,869 32 3,106 3 19,741 21 94,585 49.5 Sale of Livestock 98 4 379 16 1,671 69 191 8 72 3 2,412 1.3 Sale of Livestock Products 0 0 152 29 260 50 108 21 0 0 520 0.3 Sales of Cash Crops 15,144 30 906 2 27,586 55 244 0 6,282 13 50,162 26.2 Sale of Forest Products 844 52 227 14 0 0 110 7 434 27 1,615 0.8 Business Income 2,548 32 760 10 3,138 40 816 10 650 8 7,912 4.1 Wages & Salaries in Cash 1,306 19 1,284 19 2,978 43 761 11 574 8 6,903 3.6 Other Casual Cash Earnings 5,261 36 3,119 21 4,333 30 1,006 7 791 5 14,510 7.6 Cash Remittance 841 17 917 18 2,606 52 220 4 428 9 5,011 2.6 Fishing 213 4 227 4 4,751 91 27 1 0 0 5,217 2.7 Other 1,116 48 459 20 254 11 354 15 144 6 2,327 1.2 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Energy for Cooking District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year Roofing Materials District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma 271 APPENDIX III QUESTIONNAIRES Appendix III 272 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 273 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 274 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 275 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 276 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 277 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 278 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 279 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 280 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 281 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 282 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 283 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 284 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 285 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 286 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 287 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 288 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 289 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 290 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 291 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 292 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 293 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 294 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source \"a\" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 295 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 296 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 297 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 298 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 299 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 300 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 301 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 302 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 303 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 304 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 305 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 306 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 307 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 308 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 309 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 310 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 311 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 312 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 313 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 314 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 315 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 316 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 317 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":170,"cells":{"data":{"kind":"string","value":"# Extracted Content Page 69 AGREEMENT ON THE APPLICATION OF SANITARY AND PHYTOSANITARY MEASURES Members, Reaffirming that no Member should be prevented from adopting or enforcing measures necessary to protect human, animal or plant life or health, subject to the requirement that these measures are not applied in a manner which would constitute a means of arbitrary or unjustifiable discrimination between Members where the same conditions prevail or a disguised restriction on international trade; Desiring to improve the human health, animal health and phytosanitary situation in all Members; Noting that sanitary and phytosanitary measures are often applied on the basis of bilateral agreements or protocols; Desiring the establishment of a multilateral framework of rules and disciplines to guide the development, adoption and enforcement of sanitary and phytosanitary measures in order to minimize their negative effects on trade; Recognizing the important contribution that international standards, guidelines and recommendations can make in this regard; Desiring to further the use of harmonized sanitary and phytosanitary measures between Members, on the basis of international standards, guidelines and recommendations developed by the relevant international organizations, including the Codex Alimentarius Commission, the International Office of Epizootics, and the relevant international and regional organizations operating within the framework of the International Plant Protection Convention, without requiring Members to change their appropriate level of protection of human, animal or plant life or health; Recognizing that developing country Members may encounter special difficulties in complying with the sanitary or phytosanitary measures of importing Members, and as a consequence in access to markets, and also in the formulation and application of sanitary or phytosanitary measures in their own territories, and desiring to assist them in their endeavours in this regard; Desiring therefore to elaborate rules for the application of the provisions of GATT 1994 which relate to the use of sanitary or phytosanitary measures, in particular the provisions of Article XX(b)1; Hereby agree as follows: Article 1 General Provisions 1. This Agreement applies to all sanitary and phytosanitary measures which may, directly or indirectly, affect international trade. Such measures shall be developed and applied in accordance with the provisions of this Agreement. 1In this Agreement, reference to Article XX(b) includes also the chapeau of that Article. Page 70 2. For the purposes of this Agreement, the definitions provided in Annex A shall apply. 3. The annexes are an integral part of this Agreement. 4. Nothing in this Agreement shall affect the rights of Members under the Agreement on Technical Barriers to Trade with respect to measures not within the scope of this Agreement. Article 2 Basic Rights and Obligations 1. Members have the right to take sanitary and phytosanitary measures necessary for the protection of human, animal or plant life or health, provided that such measures are not inconsistent with the provisions of this Agreement. 2. Members shall ensure that any sanitary or phytosanitary measure is applied only to the extent necessary to protect human, animal or plant life or health, is based on scientific principles and is not maintained without sufficient scientific evidence, except as provided for in paragraph 7 of Article 5. 3. Members shall ensure that their sanitary and phytosanitary measures do not arbitrarily or unjustifiably discriminate between Members where identical or similar conditions prevail, including between their own territory and that of other Members. Sanitary and phytosanitary measures shall not be applied in a manner which would constitute a disguised restriction on international trade. 4. Sanitary or phytosanitary measures which conform to the relevant provisions of this Agreement shall be presumed to be in accordance with the obligations of the Members under the provisions of GATT 1994 which relate to the use of sanitary or phytosanitary measures, in particular the provisions of Article XX(b). Article 3 Harmonization 1. To harmonize sanitary and phytosanitary measures on as wide a basis as possible, Members shall base their sanitary or phytosanitary measures on international standards, guidelines or recommendations, where they exist, except as otherwise provided for in this Agreement, and in particular in paragraph 3. 2. Sanitary or phytosanitary measures which conform to international standards, guidelines or recommendations shall be deemed to be necessary to protect human, animal or plant life or health, and presumed to be consistent with the relevant provisions of this Agreement and of GATT 1994. 3. Members may introduce or maintain sanitary or phytosanitary measures which result in a higher level of sanitary or phytosanitary protection than would be achieved by measures based on the relevant international standards, guidelines or recommendations, if there is a scientific justification, or as a consequence of the level of sanitary or phytosanitary protection a Member determines to be appropriate Page 71 in accordance with the relevant provisions of paragraphs 1 through 8 of Article 5.2 Notwithstanding the above, all measures which result in a level of sanitary or phytosanitary protection different from that which would be achieved by measures based on international standards, guidelines or recommendations shall not be inconsistent with any other provision of this Agreement. 4. Members shall play a full part, within the limits of their resources, in the relevant international organizations and their subsidiary bodies, in particular the Codex Alimentarius Commission, the International Office of Epizootics, and the international and regional organizations operating within the framework of the International Plant Protection Convention, to promote within these organizations the development and periodic review of standards, guidelines and recommendations with respect to all aspects of sanitary and phytosanitary measures. 5. The Committee on Sanitary and Phytosanitary Measures provided for in paragraphs 1 and 4 of Article 12 (referred to in this Agreement as the \"Committee\") shall develop a procedure to monitor the process of international harmonization and coordinate efforts in this regard with the relevant international organizations. Article 4 Equivalence 1. Members shall accept the sanitary or phytosanitary measures of other Members as equivalent, even if these measures differ from their own or from those used by other Members trading in the same product, if the exporting Member objectively demonstrates to the importing Member that its measures achieve the importing Member's appropriate level of sanitary or phytosanitary protection. For this purpose, reasonable access shall be given, upon request, to the importing Member for inspection, testing and other relevant procedures. 2. Members shall, upon request, enter into consultations with the aim of achieving bilateral and multilateral agreements on recognition of the equivalence of specified sanitary or phytosanitary measures. Article 5 Assessment of Risk and Determination of the Appropriate Level of Sanitary or Phytosanitary Protection 1. Members shall ensure that their sanitary or phytosanitary measures are based on an assessment, as appropriate to the circumstances, of the risks to human, animal or plant life or health, taking into account risk assessment techniques developed by the relevant international organizations. 2. In the assessment of risks, Members shall take into account available scientific evidence; relevant processes and production methods; relevant inspection, sampling and testing methods; prevalence 2For the purposes of paragraph 3 of Article 3, there is a scientific justification if, on the basis of an examination and evaluation of available scientific information in conformity with the relevant provisions of this Agreement, a Member determines that the relevant international standards, guidelines or recommendations are not sufficient to achieve its appropriate level of sanitary or phytosanitary protection. Page 72 of specific diseases or pests; existence of pest- or disease-free areas; relevant ecological and environmental conditions; and quarantine or other treatment. 3. In assessing the risk to animal or plant life or health and determining the measure to be applied for achieving the appropriate level of sanitary or phytosanitary protection from such risk, Members shall take into account as relevant economic factors: the potential damage in terms of loss of production or sales in the event of the entry, establishment or spread of a pest or disease; the costs of control or eradication in the territory of the importing Member; and the relative cost-effectiveness of alternative approaches to limiting risks. 4. Members should, when determining the appropriate level of sanitary or phytosanitary protection, take into account the objective of minimizing negative trade effects. 5. With the objective of achieving consistency in the application of the concept of appropriate level of sanitary or phytosanitary protection against risks to human life or health, or to animal and plant life or health, each Member shall avoid arbitrary or unjustifiable distinctions in the levels it considers to be appropriate in different situations, if such distinctions result in discrimination or a disguised restriction on international trade. Members shall cooperate in the Committee, in accordance with paragraphs 1, 2 and 3 of Article 12, to develop guidelines to further the practical implementation of this provision. In developing the guidelines, the Committee shall take into account all relevant factors, including the exceptional character of human health risks to which people voluntarily expose themselves. 6. Without prejudice to paragraph 2 of Article 3, when establishing or maintaining sanitary or phytosanitary measures to achieve the appropriate level of sanitary or phytosanitary protection, Members shall ensure that such measures are not more trade-restrictive than required to achieve their appropriate level of sanitary or phytosanitary protection, taking into account technical and economic feasibility.3 7. In cases where relevant scientific evidence is insufficient, a Member may provisionally adopt sanitary or phytosanitary measures on the basis of available pertinent information, including that from the relevant international organizations as well as from sanitary or phytosanitary measures applied by other Members. In such circumstances, Members shall seek to obtain the additional information necessary for a more objective assessment of risk and review the sanitary or phytosanitary measure accordingly within a reasonable period of time. 8. When a Member has reason to believe that a specific sanitary or phytosanitary measure introduced or maintained by another Member is constraining, or has the potential to constrain, its exports and the measure is not based on the relevant international standards, guidelines or recommendations, or such standards, guidelines or recommendations do not exist, an explanation of the reasons for such sanitary or phytosanitary measure may be requested and shall be provided by the Member maintaining the measure. 3For purposes of paragraph 6 of Article 5, a measure is not more trade-restrictive than required unless there is another measure, reasonably available taking into account technical and economic feasibility, that achieves the appropriate level of sanitary or phytosanitary protection and is significantly less restrictive to trade. Page 73 Article 6 Adaptation to Regional Conditions, Including Pest- or Disease-Free Areas and Areas of Low Pest or Disease Prevalence 1. Members shall ensure that their sanitary or phytosanitary measures are adapted to the sanitary or phytosanitary characteristics of the area - whether all of a country, part of a country, or all or parts of several countries - from which the product originated and to which the product is destined. In assessing the sanitary or phytosanitary characteristics of a region, Members shall take into account, inter alia, the level of prevalence of specific diseases or pests, the existence of eradication or control programmes, and appropriate criteria or guidelines which may be developed by the relevant international organizations. 2. Members shall, in particular, recognize the concepts of pest- or disease-free areas and areas of low pest or disease prevalence. Determination of such areas shall be based on factors such as geography, ecosystems, epidemiological surveillance, and the effectiveness of sanitary or phytosanitary controls. 3. Exporting Members claiming that areas within their territories are pest- or disease-free areas or areas of low pest or disease prevalence shall provide the necessary evidence thereof in order to objectively demonstrate to the importing Member that such areas are, and are likely to remain, pest- or disease-free areas or areas of low pest or disease prevalence, respectively. For this purpose, reasonable access shall be given, upon request, to the importing Member for inspection, testing and other relevant procedures. Article 7 Transparency Members shall notify changes in their sanitary or phytosanitary measures and shall provide information on their sanitary or phytosanitary measures in accordance with the provisions of Annex B. Article 8 Control, Inspection and Approval Procedures Members shall observe the provisions of Annex C in the operation of control, inspection and approval procedures, including national systems for approving the use of additives or for establishing tolerances for contaminants in foods, beverages or feedstuffs, and otherwise ensure that their procedures are not inconsistent with the provisions of this Agreement. Page 74 Article 9 Technical Assistance 1. Members agree to facilitate the provision of technical assistance to other Members, especially developing country Members, either bilaterally or through the appropriate international organizations. Such assistance may be, inter alia, in the areas of processing technologies, research and infrastructure, including in the establishment of national regulatory bodies, and may take the form of advice, credits, donations and grants, including for the purpose of seeking technical expertise, training and equipment to allow such countries to adjust to, and comply with, sanitary or phytosanitary measures necessary to achieve the appropriate level of sanitary or phytosanitary protection in their export markets. 2. Where substantial investments are required in order for an exporting developing country Member to fulfil the sanitary or phytosanitary requirements of an importing Member, the latter shall consider providing such technical assistance as will permit the developing country Member to maintain and expand its market access opportunities for the product involved. Article 10 Special and Differential Treatment 1. In the preparation and application of sanitary or phytosanitary measures, Members shall take account of the special needs of developing country Members, and in particular of the least-developed country Members. 2. Where the appropriate level of sanitary or phytosanitary protection allows scope for the phased introduction of new sanitary or phytosanitary measures, longer time-frames for compliance should be accorded on products of interest to developing country Members so as to maintain opportunities for their exports. 3. With a view to ensuring that developing country Members are able to comply with the provisions of this Agreement, the Committee is enabled to grant to such countries, upon request, specified, time- limited exceptions in whole or in part from obligations under this Agreement, taking into account their financial, trade and development needs. 4. Members should encourage and facilitate the active participation of developing country Members in the relevant international organizations. Article 11 Consultations and Dispute Settlement 1. The provisions of Articles XXII and XXIII of GATT 1994 as elaborated and applied by the Dispute Settlement Understanding shall apply to consultations and the settlement of disputes under this Agreement, except as otherwise specifically provided herein. 2. In a dispute under this Agreement involving scientific or technical issues, a panel should seek advice from experts chosen by the panel in consultation with the parties to the dispute. To this end, Page 75 the panel may, when it deems it appropriate, establish an advisory technical experts group, or consult the relevant international organizations, at the request of either party to the dispute or on its own initiative. 3. Nothing in this Agreement shall impair the rights of Members under other international agreements, including the right to resort to the good offices or dispute settlement mechanisms of other international organizations or established under any international agreement. Article 12 Administration 1. A Committee on Sanitary and Phytosanitary Measures is hereby established to provide a regular forum for consultations. It shall carry out the functions necessary to implement the provisions of this Agreement and the furtherance of its objectives, in particular with respect to harmonization. The Committee shall reach its decisions by consensus. 2. The Committee shall encourage and facilitate ad hoc consultations or negotiations among Members on specific sanitary or phytosanitary issues. The Committee shall encourage the use of international standards, guidelines or recommendations by all Members and, in this regard, shall sponsor technical consultation and study with the objective of increasing coordination and integration between international and national systems and approaches for approving the use of food additives or for establishing tolerances for contaminants in foods, beverages or feedstuffs. 3. The Committee shall maintain close contact with the relevant international organizations in the field of sanitary and phytosanitary protection, especially with the Codex Alimentarius Commission, the International Office of Epizootics, and the Secretariat of the International Plant Protection Convention, with the objective of securing the best available scientific and technical advice for the administration of this Agreement and in order to ensure that unnecessary duplication of effort is avoided. 4. The Committee shall develop a procedure to monitor the process of international harmonization and the use of international standards, guidelines or recommendations. For this purpose, the Committee should, in conjunction with the relevant international organizations, establish a list of international standards, guidelines or recommendations relating to sanitary or phytosanitary measures which the Committee determines to have a major trade impact. The list should include an indication by Members of those international standards, guidelines or recommendations which they apply as conditions for import or on the basis of which imported products conforming to these standards can enjoy access to their markets. For those cases in which a Member does not apply an international standard, guideline or recommendation as a condition for import, the Member should provide an indication of the reason therefor, and, in particular, whether it considers that the standard is not stringent enough to provide the appropriate level of sanitary or phytosanitary protection. If a Member revises its position, following its indication of the use of a standard, guideline or recommendation as a condition for import, it should provide an explanation for its change and so inform the Secretariat as well as the relevant international organizations, unless such notification and explanation is given according to the procedures of Annex B. 5. In order to avoid unnecessary duplication, the Committee may decide, as appropriate, to use the information generated by the procedures, particularly for notification, which are in operation in the relevant international organizations. Page 76 6. The Committee may, on the basis of an initiative from one of the Members, through appropriate channels invite the relevant international organizations or their subsidiary bodies to examine specific matters with respect to a particular standard, guideline or recommendation, including the basis of explanations for non-use given according to paragraph 4. 7. The Committee shall review the operation and implementation of this Agreement three years after the date of entry into force of the WTO Agreement, and thereafter as the need arises. Where appropriate, the Committee may submit to the Council for Trade in Goods proposals to amend the text of this Agreement having regard, inter alia, to the experience gained in its implementation. Article 13 Implementation Members are fully responsible under this Agreement for the observance of all obligations set forth herein. Members shall formulate and implement positive measures and mechanisms in support of the observance of the provisions of this Agreement by other than central government bodies. Members shall take such reasonable measures as may be available to them to ensure that non-governmental entities within their territories, as well as regional bodies in which relevant entities within their territories are members, comply with the relevant provisions of this Agreement. In addition, Members shall not take measures which have the effect of, directly or indirectly, requiring or encouraging such regional or non-governmental entities, or local governmental bodies, to act in a manner inconsistent with the provisions of this Agreement. Members shall ensure that they rely on the services of non-governmental entities for implementing sanitary or phytosanitary measures only if these entities comply with the provisions of this Agreement. Article 14 Final Provisions The least-developed country Members may delay application of the provisions of this Agreement for a period of five years following the date of entry into force of the WTO Agreement with respect to their sanitary or phytosanitary measures affecting importation or imported products. Other developing country Members may delay application of the provisions of this Agreement, other than paragraph 8 of Article 5 and Article 7, for two years following the date of entry into force of the WTO Agreement with respect to their existing sanitary or phytosanitary measures affecting importation or imported products, where such application is prevented by a lack of technical expertise, technical infrastructure or resources. Page 77 ANNEX A DEFINITIONS4 1. Sanitary or phytosanitary measure - Any measure applied: (a) to protect animal or plant life or health within the territory of the Member from risks arising from the entry, establishment or spread of pests, diseases, disease-carrying organisms or disease-causing organisms; (b) to protect human or animal life or health within the territory of the Member from risks arising from additives, contaminants, toxins or disease-causing organisms in foods, beverages or feedstuffs; (c) to protect human life or health within the territory of the Member from risks arising from diseases carried by animals, plants or products thereof, or from the entry, establishment or spread of pests; or (d) to prevent or limit other damage within the territory of the Member from the entry, establishment or spread of pests. Sanitary or phytosanitary measures include all relevant laws, decrees, regulations, requirements and procedures including, inter alia, end product criteria; processes and production methods; testing, inspection, certification and approval procedures; quarantine treatments including relevant requirements associated with the transport of animals or plants, or with the materials necessary for their survival during transport; provisions on relevant statistical methods, sampling procedures and methods of risk assessment; and packaging and labelling requirements directly related to food safety. 2. Harmonization - The establishment, recognition and application of common sanitary and phytosanitary measures by different Members. 3. International standards, guidelines and recommendations (a) for food safety, the standards, guidelines and recommendations established by the Codex Alimentarius Commission relating to food additives, veterinary drug and pesticide residues, contaminants, methods of analysis and sampling, and codes and guidelines of hygienic practice; (b) for animal health and zoonoses, the standards, guidelines and recommendations developed under the auspices of the International Office of Epizootics; (c) for plant health, the international standards, guidelines and recommendations developed under the auspices of the Secretariat of the International Plant Protection Convention in cooperation with regional organizations operating within the framework of the International Plant Protection Convention; and 4For the purpose of these definitions, \"animal\" includes fish and wild fauna; \"plant\" includes forests and wild flora; \"pests\" include weeds; and \"contaminants\" include pesticide and veterinary drug residues and extraneous matter. Page 78 (d) for matters not covered by the above organizations, appropriate standards, guidelines and recommendations promulgated by other relevant international organizations open for membership to all Members, as identified by the Committee. 4. Risk assessment - The evaluation of the likelihood of entry, establishment or spread of a pest or disease within the territory of an importing Member according to the sanitary or phytosanitary measures which might be applied, and of the associated potential biological and economic consequences; or the evaluation of the potential for adverse effects on human or animal health arising from the presence of additives, contaminants, toxins or disease-causing organisms in food, beverages or feedstuffs. 5. Appropriate level of sanitary or phytosanitary protection - The level of protection deemed appropriate by the Member establishing a sanitary or phytosanitary measure to protect human, animal or plant life or health within its territory. NOTE: Many Members otherwise refer to this concept as the \"acceptable level of risk\". 6. Pest- or disease-free area - An area, whether all of a country, part of a country, or all or parts of several countries, as identified by the competent authorities, in which a specific pest or disease does not occur. NOTE: A pest- or disease-free area may surround, be surrounded by, or be adjacent to an area - whether within part of a country or in a geographic region which includes parts of or all of several countries - in which a specific pest or disease is known to occur but is subject to regional control measures such as the establishment of protection, surveillance and buffer zones which will confine or eradicate the pest or disease in question. 7. Area of low pest or disease prevalence - An area, whether all of a country, part of a country, or all or parts of several countries, as identified by the competent authorities, in which a specific pest or disease occurs at low levels and which is subject to effective surveillance, control or eradication measures. Page 79 ANNEX B TRANSPARENCY OF SANITARY AND PHYTOSANITARY REGULATIONS Publication of regulations 1. Members shall ensure that all sanitary and phytosanitary regulations5 which have been adopted are published promptly in such a manner as to enable interested Members to become acquainted with them. 2. Except in urgent circumstances, Members shall allow a reasonable interval between the publication of a sanitary or phytosanitary regulation and its entry into force in order to allow time for producers in exporting Members, and particularly in developing country Members, to adapt their products and methods of production to the requirements of the importing Member. Enquiry points 3. Each Member shall ensure that one enquiry point exists which is responsible for the provision of answers to all reasonable questions from interested Members as well as for the provision of relevant documents regarding: (a) any sanitary or phytosanitary regulations adopted or proposed within its territory; (b) any control and inspection procedures, production and quarantine treatment, pesticide tolerance and food additive approval procedures, which are operated within its territory; (c) risk assessment procedures, factors taken into consideration, as well as the determination of the appropriate level of sanitary or phytosanitary protection; (d) the membership and participation of the Member, or of relevant bodies within its territory, in international and regional sanitary and phytosanitary organizations and systems, as well as in bilateral and multilateral agreements and arrangements within the scope of this Agreement, and the texts of such agreements and arrangements. 4. Members shall ensure that where copies of documents are requested by interested Members, they are supplied at the same price (if any), apart from the cost of delivery, as to the nationals6 of the Member concerned. 5Sanitary and phytosanitary measures such as laws, decrees or ordinances which are applicable generally. 6When \"nationals\" are referred to in this Agreement, the term shall be deemed, in the case of a separate customs territory Member of the WTO, to mean persons, natural or legal, who are domiciled or who have a real and effective industrial or commercial establishment in that customs territory. Page 80 Notification procedures 5. Whenever an international standard, guideline or recommendation does not exist or the content of a proposed sanitary or phytosanitary regulation is not substantially the same as the content of an international standard, guideline or recommendation, and if the regulation may have a significant effect on trade of other Members, Members shall: (a) publish a notice at an early stage in such a manner as to enable interested Members to become acquainted with the proposal to introduce a particular regulation; (b) notify other Members, through the Secretariat, of the products to be covered by the regulation together with a brief indication of the objective and rationale of the proposed regulation. Such notifications shall take place at an early stage, when amendments can still be introduced and comments taken into account; (c) provide upon request to other Members copies of the proposed regulation and, whenever possible, identify the parts which in substance deviate from international standards, guidelines or recommendations; (d) without discrimination, allow reasonable time for other Members to make comments in writing, discuss these comments upon request, and take the comments and the results of the discussions into account. 6. However, where urgent problems of health protection arise or threaten to arise for a Member, that Member may omit such of the steps enumerated in paragraph 5 of this Annex as it finds necessary, provided that the Member: (a) immediately notifies other Members, through the Secretariat, of the particular regulation and the products covered, with a brief indication of the objective and the rationale of the regulation, including the nature of the urgent problem(s); (b) provides, upon request, copies of the regulation to other Members; (c) allows other Members to make comments in writing, discusses these comments upon request, and takes the comments and the results of the discussions into account. 7. Notifications to the Secretariat shall be in English, French or Spanish. 8. Developed country Members shall, if requested by other Members, provide copies of the documents or, in case of voluminous documents, summaries of the documents covered by a specific notification in English, French or Spanish. 9. The Secretariat shall promptly circulate copies of the notification to all Members and interested international organizations and draw the attention of developing country Members to any notifications relating to products of particular interest to them. 10. Members shall designate a single central government authority as responsible for the implementation, on the national level, of the provisions concerning notification procedures according to paragraphs 5, 6, 7 and 8 of this Annex. Page 81 General reservations 11. Nothing in this Agreement shall be construed as requiring: (a) the provision of particulars or copies of drafts or the publication of texts other than in the language of the Member except as stated in paragraph 8 of this Annex; or (b) Members to disclose confidential information which would impede enforcement of sanitary or phytosanitary legislation or which would prejudice the legitimate commercial interests of particular enterprises. Page 82 ANNEX C CONTROL, INSPECTION AND APPROVAL PROCEDURES7 1. Members shall ensure, with respect to any procedure to check and ensure the fulfilment of sanitary or phytosanitary measures, that: (a) such procedures are undertaken and completed without undue delay and in no less favourable manner for imported products than for like domestic products; (b) the standard processing period of each procedure is published or that the anticipated processing period is communicated to the applicant upon request; when receiving an application, the competent body promptly examines the completeness of the documentation and informs the applicant in a precise and complete manner of all deficiencies; the competent body transmits as soon as possible the results of the procedure in a precise and complete manner to the applicant so that corrective action may be taken if necessary; even when the application has deficiencies, the competent body proceeds as far as practicable with the procedure if the applicant so requests; and that upon request, the applicant is informed of the stage of the procedure, with any delay being explained; (c) information requirements are limited to what is necessary for appropriate control, inspection and approval procedures, including for approval of the use of additives or for the establishment of tolerances for contaminants in food, beverages or feedstuffs; (d) the confidentiality of information about imported products arising from or supplied in connection with control, inspection and approval is respected in a way no less favourable than for domestic products and in such a manner that legitimate commercial interests are protected; (e) any requirements for control, inspection and approval of individual specimens of a product are limited to what is reasonable and necessary; (f) any fees imposed for the procedures on imported products are equitable in relation to any fees charged on like domestic products or products originating in any other Member and should be no higher than the actual cost of the service; (g) the same criteria should be used in the siting of facilities used in the procedures and the selection of samples of imported products as for domestic products so as to minimize the inconvenience to applicants, importers, exporters or their agents; (h) whenever specifications of a product are changed subsequent to its control and inspection in light of the applicable regulations, the procedure for the modified product is limited to what is necessary to determine whether adequate confidence exists that the product still meets the regulations concerned; and 7Control, inspection and approval procedures include, inter alia, procedures for sampling, testing and certification. Page 83 (i) a procedure exists to review complaints concerning the operation of such procedures and to take corrective action when a complaint is justified. Where an importing Member operates a system for the approval of the use of food additives or for the establishment of tolerances for contaminants in food, beverages or feedstuffs which prohibits or restricts access to its domestic markets for products based on the absence of an approval, the importing Member shall consider the use of a relevant international standard as the basis for access until a final determination is made. 2. Where a sanitary or phytosanitary measure specifies control at the level of production, the Member in whose territory the production takes place shall provide the necessary assistance to facilitate such control and the work of the controlling authorities. 3. Nothing in this Agreement shall prevent Members from carrying out reasonable inspection within their own territories."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":171,"cells":{"data":{"kind":"string","value":"# Extracted Content THE SEEDS ACT, 2003 ARRANGEMENT OF SECTIONS Section Title PART I PRELIMINARY PROVISIONS 1. Short title and commencement. 2 Interpretation. PART II ESTABLISHMENT OF THE NATIONAL SEEDS COMMITTEE 3. Establishment of the National Seeds Committee. 4. Committee membership. 5. Functions of the Committee. 6. Meeting of the Committee. 7. Establishment of the Sub-Committee. 8. Appointment of other staff. 9. Issuance of Permit. 10. Establishment of the Seed Certification Institute. 11. Delegation of Powers of the Minister. 12. Minister to make orders. PART III IMPORTATION, EXPORTATION, AND SALES OF SEEDS 13. Condition for Importation, Exportation and Sale of seeds. 14. Restriction on sale importation or exportation of seeds. PART IV REGISTRATION OF SEEDS DEALERS 15. Registration of seeds dealers. 16. Issuance of certificate of registration. 17. Cancellation of certificate of registration. 18. Appeals. 19. Prohibition. 20. Duty to keep records. 21. Approval and listing of varieties. 1 2003 Seeds No. 18 2 22. Powers of Inspectors. 23. Obstruction of Inspectors. 24. Analysis of a sample. 25. Tempering with samples. PART V MISCELLANEOUS PROVISIONS 26. Offences and Penalties. 27. Offences by a body corporate or firm. 28. Evidence. 29. Limitation. 30. Indemnity. 31. Exempted sales. 32. Repeal and Savings. 33. Power to make regulations. SCHEDULE Seeds 2003 No. 18 4 and identity to provide a source for the initial and recurring increase of seeds;or if of foreign origin, that the seed is certified by a recognised certification agency or by the Chief Seed Quality Controller as being of basic grade; ''breeders grade'' means approved seed of a variety that has been produced by the breeder responsible for breeding and maintanance of that variety under condition which ensure that the specific characteristics of the variety are mantained and which provide the source for the initial land recurent increases of seeds of the pedigree grades; or if of foreign origin, that the seed is certified by a recognised certification agency as being of breeders grade; ''Certification Agency'' means an agency appointed by the Minister pursuant to section 10; ''certified grade'' means the approved progeny of breeder, foundation, registered or certified seed managed to mantain satisfactory genetic identity and purity the production of which is supervised and approved by the Institute and which provides the source of the initial and recurring increase of seeds; or if of foreign origin, that the seed is certified by a recognised certification agency or by the Chief Quality Controller as being of certified grade; ''Committee'' means the National Seed Committee established under section 3 of this Act; \"class name'' includes any mark, description or designation of a class; ''inspector'' means a person appointed or designated as an inspector pursuant to section 8; ''Director'' means a person responsible for Agricultural Development; ''label'' includes any legend, word, mark, symbol or design applied or attached to, included in, belonging to or accompanying any seed or package; ''Minister'' means the Minister responsible for agriculture; \"noxious weed seed'' means any seed potentially injurious to agriculture so declared by the Minister by notice published in the Gazette to be noxious weed seed for the purposes of this Act; ''package'' includes a sack, bag, barrel, case or any other container in which seed is placed or packed; \"place'' includes any building, vehicle, vessel, railway, car or aircraft; \"person'' includes an individual, corporation, society, association, enterprise, trustee, receiver, or any other institution; ''Quality Declared Seed'' means seed produced by a registered smallholder farmer which conforms to the specified standards for crop 4 2003 No. 18 2003 5 Seeds species concerned and which has been subject to the quality control I measures prescribed in the regulations to be made under this Act; ''Recognised Certification Agency'' means a registered certification agency of a country, which is a member to an International Seed Organization to which Tanzania is also a member or an official seed certification agency from a country, whose seed quality standards have been approved by the Director to be similar or higher than those prescribed under this Act or Regulations; ''standard seed'' means emergency seed authorized for use by the Minister; ''seed'' means that part of plant which is or is intended to be used for propagation and includes any true seed, any vegetative material including seedling, corm, cutting, bulb, bulbil, layer, marcott, root, runner, scion, set, split, stem, stock, stump, sucker or tuber so used or intended to be so used; \"seed dealer'' include importers, exporters, processors, producers, sellers and distributors of seeds and owners of seed testing laboratories or any other person dealing with seed under this Act; \"sell'' includes sell, offer for sell expose for sell, have in possesion for sale, and distribution or give away; ''Subcommittee'' means the Seed Sub-Committee established under section 7; ''Tanzania Pedigree Class'' means a class that contains one of the words ''Breeders'', ''Basic'', ''Certified 1 '', ''Certified 2'', where 1 means first generation 2 means second generation; ''Variety'' means plant variety. ''weed seed'' means any plant injurious to agriculture, which is declared to be so by the Minister for the purpose of the Plant Protection Act. PART II ESTABLISHMENT OF THE NATIONAL SEEDS COMMITTEE 3. There is hereby established a technical Committee to be known as the National Seeds Committee. Establi- shment of the Seeds commi- ttee 2003 No. 18 6 Seeds 4.-(l) The National Seeds Commitee shall be composed of the Commi- following members- ttee Member- (a) the Permanent Secretary to the Ministry for the time being ship responsible for agriculture who shall be the chairperson of the committee; (b) the officer responsible for co-ordination and supervision of the seeds industry in the Ministry and shall be the secretary to the Committee; (c) the head of the division in the Ministry for the time being responsible for crop research; (d) the head of the division in the Ministry for the time being responsible for crop development; (e) the Chief Seed Quality Controller; and (f) the Registrar of Plant Varieties. (2) The Minister shall appoint the following to be members of the National Seeds Committee- (a) a representative from the Tanzania Seed Trade Association; (b) a representative from higher learning institution responsible for agriculture; and (c) a representative from seed consumers'association;'' (3) The Chairperson of the Committee may after consultation with members co-op other members, to attend and speak on any matter at any meeting of the Committee, but a person so co-opted shall not have the right to vote. 5.-(1) The National Seeds Committee shall be a Stakeholders' Forum responsible for advising the Government on all matters relating to the Functions of the Committee development of the Tanzania seed industry.''; (2) Without prejedice to the generality of subsection (1), the functions of the National Seeds Committee shall include: - (a) to advise the Ministry on formulation and implementation of the seed industry policy and implementation of guidelines; (b) to advise the Ministry on the implementation and amendment of the seeds legislation; (c) to advise the Minister on all matters relating to seeds; (d) to give general advice in the co-ordination and supervision of the seed industry; (e) to advise the Minister on approval of plant varieties. No. 18 2003 7 Seeds 6. The Committee shall regulate its own procedures of conducting its Meetings of the meetings. Committee 7. The National Seeds Committee may, for the purpose of effective Establish- implementation of the functions of the Committee establish such number ment of Sub- of sub-Committees to perform specific functions as it may deem necessary. Committees 8.-(1) The Minister may, by notice published in the Gazette, appoint Appoint- or designate, from time to time, qualified persons to be Inspectors and ment of analysts who shall have and exercise powers generally respecting seeds other staff in accordance with the provisions of this Act or as may be prescribed. (2) The Director or any other person appointed by him shall be the Chief Seed Quality Controller and the head of the national seed quality control service. (3) Every person appointed or designated as Chief Quality Controller, analyst or Inspector under sub-section (1) shall be given a certificate, identity card or a document as a proof of his appointment or designation which shall be produced on entering any place in the exercise of his powers under this Act. (4) The Chief Seed Quality Controller may permit an analyst to perform internal seed quality control for a private specified producer, processor, seller or as the case may be, distributor of seed. (5) No person shall, while holding the office of Seed Quality Controller, Inspector, or Analyst engage in any business connected with the production, processing, sale or importation of seed. 9. The Chief Seed Quality Controller may permit a private specified producer, processor, seller or distributor to employ an analyst appointed under section 8 to effect the internal seed quality control. Issuance of permits Establish- 10.-(1) There is hereby established a body cooperate to be known as ment of the Tanzania Official Seeds Certification Institute (TOSCI), which shall- Seed (a) have perpetual succession and a common seal; (b) be capable of entering into contracts in its own name; Certifi- cation Institute 2003 8 No. 18 Seeds (c) be capable of purchasing or acquiring any movable and immovable property. (2) Any proceedings against the Institute in contract may only be instituted by or against the Government in accordance with the Government Proceedings Act, 1967. (3) The provisions of the First Schedule to this Act shall have effect as to the constitution, tenure of office, management and proceedings of and other matters relating to the Governing Council of the Institute. Delega- 11.-(1) The Minister may, with the exception of his power of tion of delegation, assign or delegate some or all of his powers under this Act to powers any competent institution or individual. of the Minister (2) Every assignment or delegation shall be revocable at will, and no delegation shall prevent the exercise of any power by the Minister. (3) In exercising the powers of delegation, assignment or appointment, the Minister may enter into contracts with competent institutions or individuals under such terms and conditions as the Minister may determine. 12. The Minister may make orders: Minister (a) prescribing the varieties of the seeds of which may be sold in to make orders Tanzania or imported into Tanzania; (b) classifying the species of plants the seeds of which he deems are weed seeds or noxious seed weed in relation to seed classes under this Act; (c) in respect of the detention of anything seized or placed under stop sale under the provisions of this Act and for the preservation or safeguarding anything so detained; (d) in respect of the disposition of anything forfeited to the Government under this Act. Seeds 2003 9 No. 18 PART III IMPORTATION, EXPORTATION AND SALES OF SEEDS 13.-(1) Any person, who intends to deal with importation, exportation, production, processing, distribution, sale or advertisement for sale of seeds shall obtain a permit from the Director or any other person authorized by the Director in that behalf Condi- tion for impor- tation, expor- tation and sale of seeds (2) The Director shall, before granting the permit or licence required under subsection(l) ensure that the standards and conditions for importation, production, processing, distribution sale or advertisement for sale of seeds, as provided for in the Plant Protection Act and in this Act, have been complied with. Act No.13 of 1997 (3) The Minister shall for the purpose of this Act, prescribe the plant varieties and standards of the seeds for importation, exportation, production, processing and distribution. (4) Any person who contravenes or fails to comply with a provision of this section, Orders or Regulations made under this Act in respect of matters specified in this section, commits an offence. 14.-(1) Any person who - (a) sells, import, exports any seed under a grade name or designation so closely resembling a grade name prescribed under the provision of this Act as likely to be mistaken therefor; or (b) applies, to any seed or package containing seed, a grade name prescribed under the provision of this Act as likely to be mistaken therefor, shall have the duty to ensure that, the seed meets the requirement prescribed for the grade and is marked, packed and labelled as required by Regulations or Orders made under this Act. (2) The Minister may prescribe classes of seeds which shall be exempted from the requirements of subsection (1). (3) Any person, who contravenes the provisions of subsection (1), commits an offence. Restri- ction on sale, importa- tion or exporta- tion of seeds Seeds 2003 No. 18 10 PART IV REGISTRATION OF SEEDS DEALERS 15.-(1) Any seed importer, exporter, producer, processor, distributor or seller shall, before operating, register with the Director or any other person appointed by him in that behalf Registra- tion of seeds dealers (2) Any owner or operator of a seed processing factory or seed testing laboratory shall be required to obtain registration of his factory or laboratory from the Director. (3) Every application for registration under subsection (1) shall be, submitted to the Director in the prescribed manner and shall be accompanied by the prescribed registration fee. (4) The Director may, after receiving an application for registration- (a) grant registration if he is satisfied with the contents of application; or (b) refuse an application. 16.-(l) The Director shall after granting the registration, issue a Issuance certificate of registration to a seed dealer subject to such terms and of certificate conditions as may be determined by the Minister. of registra- tion (2) A registration certificate granted shall be conspicuously displayed on the business premises of a registered seed dealer. 17.-(l) The Director may, if he is satisfied that any conditions subject to which a seed dealer was registered have not been complied with, cancel the certificate of registration issued to a seed dealer. Cancella- (2) The Director shall not cancel the registration of a seed dealer under this section unless the dealer has been given an opportunity to show cause as to why the registration should not be cancelled. 18. Any person who is not satisfied by the decision of the Director for refusal of registration, cancellation of registration or permit under the provisions of this Act may, within thirty days appeal to the Minister whose decision shall be final. Appeals tion of certificate of registra- tion No. 18 2003 11 Seeds 19.-(1) No person shall- Prohibi- . (a) import, export, produce, process, distribute or sell seeds unless he is registered as such under this Act; or (b) test, process or multiply seeds otherwise than in a registered laboratory seed processing factory or, as the case may be, a seed multiplication farm. (2) Notwithstanding subsection (1), nothing in this Act shall, be construed as preventing the sale of quality declared seeds as such to a neighbour fanner, whereby such seeds are grown by a smallholder fanner for use as seeds in his own farm. (3) Where a registered Seed Dealer contracts any person to import, export, produce, process, distribute or sell seeds, that person shall be bound by the terms and conditions provided for under this Act. 20.-(1) Every producer, processor, seller or distributor of seeds shall have the duty to keep within his premises, detailed records, by lot, of seed produced, purchased, sold, tested, and labelled or treated as the case may be and such records shall be provided to the Inspector whenever requested. (2) Any person who contravenes the provisions of this section, commits an offence and is liable on conviction to a fine not exceeding one million shillings or to imprisonment for a term not exceeding three months, or to both such fine and imprisonment. 21.-(l) The Minister shall upon advice by the National. Seeds Approval Committee approve any new plant variety. and listing of varieties (2) The Director shall establish and maintain a national catalogue of approved plant varieties and shall cause to be entered therein varieties imported, sold or distributed in Tanzania. (3) Subject to the recommendations of the National Seeds Committee, the Director shall publish in the Gazette the seed varietties entered in the national catalogue. 22.-(l) Any Inspector may, at any reasonable time, enter any place where he reasonably believes there is any seed to which this Act applies tion Duty to keeps records Re- consider- ation of dispute by the Public Service Joint Powers of Staff Inspectors Council Seeds 2003 12 No. 18 and may open any package found therein that he has reasons to believe contains such seed and may sample the same for the purpose of ensuring that the provisions of this Act, or of any regulations or orders made under this Act are being complied with. (2) An Inspector may, for the purposes of securing compliance with the provisions of this Act or of any Regulations or Orders made under this Act or for the purposes of detecting and establishing any breach of any such provisions - (a) conduct field inspection and or take samples of any seed found in any package or place and submit such samples to the official seeds testing laboratory for testing; or (b) require any person to produce for inspection or for the purpose of obtaining copies thereof or extracts therefrom, any books, shipping bills, bills of lading or other documents or papers relating to any seed to which this Act applies. (3) The owner or person in charge of any premises described under this section and every person found therein, shall give to an Inspector all reasonable assistance in his power to enable the Inspector to carry out his duties and functions under this Act. (4) An Inspector may if he has reasonable grounds, that any of the provisions of this Act, or Regulations or Orders made under this Act has been violated, seize, issue or stop sale of the seeds or package by means of or in relation to which the violation was committed. Provided that, any seeds or package seized or placed under stop sale pursuant to this subsection shall not be detained after- (a) the provisions of this Act and the regulations and orders have, in the opinion of the Inspector, been complied with; or (b) the expiration of three months from the day of seizure or stop sale, unless before that date proceedings have been instituted in respect of the violation, in which event the seeds or package may be detained until the proceedings are finally concluded. (5) An Inspector shall before inspection of the premises, take such steps as are reasonably practical to afford the owner of any seeds an opportunity to be present while an inspection under this Act is being carried out. Seeds No. 18 2003 13 Obstru- 23. Any person, being the owner or person entrusted with the charge ction of and custody of any seed lot who- Inspec- (a) refuses to allow the Inspector to take a sample of the seed tors from any premises which he is authorised under this Act to take a sample, or who otherwise wilfully delays or obstructs the Inspector; or (b) wilfully makes false or misleading statement either verbally or in writing to the Inspector or other official engaged in carrying out his duties or functions under this Act; commits an offence. 24. An analyst, who receives a sample taken under the provisions of Analysis of a this Act from an Inspector, shall as soon as is practicable analyse the same, and shall give a report in the prescribed form specifying the result of the analysis. sample Tempe- 25. Any person, who fraudulently tampers or interferes with any seed lot that any sample of it is taken or submitted for analysis under this Act does not correctly represent the seed lot, or fraudulently tampers or interferes with any sample taken or submitted for analysis under this Act, commits an offence. ring with samples PART V MISCELLANEOUS PROVISIONS 26.-(1) Any person, who contravenes a provision of this Actor of any subsidiary legislation made under this Act, commits an offence and shall, Penalties except as otherwise provided, be liable on conviction to a fine of not less than one million shillings but not exceeding five million shillings or to imprisonment for a term not exceeding one year, or to both such fine and imprisonment. (2) The court may in addition to any penalty imposed under this Act, order any article in respect of which such offence has been committed or which has been used for the commission of such offence to be forfeited. (3) The Minister shall be responsible for the disposal of anything forfeited to the Government under subsection (2). Offences and 2003 14 No. 18 Seeds (4) Where an offence has been committed and by reason of that commission a person has suffered a direct damage or loss of his property, the court may, in addition to the penalty provided for under subsection (1), order the offender to compensate the person who has suffered such loss or damage. (5) The court may in the case of a persistent offender, order, in addition to penalties provided for under this section, the withdrawal of any permit or, certificate of registration or any other right held by the offender under this Act. 27.-(1) Any act which if done by an individual would be an offence against this Act or any regulations or orders made under this Act shall, if done by a body corporate, be an offence by every Director, Secretary and Manager thereof unless he proves that the offence was committed without his consent or connivance and that he exercised all such diligence to prevent the commission of the offence as he ought to have exercised having regard to the nature of his functions in that capacity and to all circumstances. Offences by a body corporate or firm (2) Where an offence against this Act or any regulations or orders made under this Act has been committed by a partner in a firm, every person who at the time of the commission of the offence was partner in that firm, or was purporting to act in that capacity, shall be deemed to have committed that offence unless he proves that the offence was committed without his consent and or connivance and he exercised all such diligence to prevent the commission of the offence as he ought to have exercised having regard to the nature of his functions in that capacity and to all the circumstances. 28.-(l) Any document purporting to be a report under the hand of an analyst appointed under the provisions of this Act, on any sample duly submitted to him for analysis and report, may be admitted in evidence in any civil or criminal proceedings relating to the seed sampled without further proof, and shall be sufficient evidence of the facts stated therein unless the defendant or person charged requires that the analyst be called as a witness. Evidence (2) Where the defendant or person charged requires that the analyst be called as a witness he shall pay any reasonable costs incurred by such analyst in attending the trial. 15 2003 No. 18 Seeds (3) Any sample which has been taken in the prescribed manner by an Inspector shall, unless proved otherwise be deemed to be of the same composition, to have the same qualities and to possess in all other respects the same properties of the seed lot from which it was drawn. 29. No proceedings in respect of an offence under this Act or under Limita- any subsidiary legislation made under this Act shall be instituted after tion the expiry of two years from the date when the subject matter of the proceedings arose, if the offence is a misrepresentation of the plant variety name or purity of the plant variety. 30. Without prejudice to the provisions of section 284A of the Penal Code, no matter done by any person exercising or purporting to exercise any function under this Act or under any subsidiary legislation made under this Act shall, if done in good faith in the execution or purported execution of the functions under any of the provisions of this Act or such subsidiary legislation, subject any such person to any action liability, claim or demand whatsoever. Indemnity Cap. 16 31.-(l) The provisions of this Act shall not apply to a sale, offer or exposure for sell, where such sale is made by a bailiff, court broker or other officer in the course of executing any order or process of a court. Exempted sales (2) The term ''sell'' under sub-section (1) shall not be construed to mean selling of seeds or anything, which otherwise does not meet quality standards prescribed under this Act or Regulations made under this Act. 32.-(l) Subject to the provisions of subsection (2), the Seed (Regulations of Standards) Act, 1973, is hereby repealed. Repeal and savings Act,No.29 (2) Notwithstanding subsection (1), any applicable Regulations, Rules, Order or Notice made under the Seed (Regulation of Standards) Act, 1973, shall remain in force until such time as it is revoked cancelled or replaced. of 1973 33.-(l) The Minister may, after consultation with the Committee, make regulations for the better carrying into effect of the provisions of this Act. Power to make regula- tions 33.-(l) The Minister may, after consultation with the Committee, make regulations for the better carrying into effect of the provisions of this Act. 16 No. 18 Seeds 2003 (2) Without prejudice to the generality of subsection (1), the Minister may make regulations - (a) prescribing various forms to be applied under various provisions of this Act; (b) prescribing the manner in which - (i) returns and information shall be rendered or furnished; (ii) seeds intended for sale shall be packed, labelled, marked and sealed, and the manner in which seeds may be advertised or exposed for sale; (iii) seed samples are to be taken and dealt with; (c) prescribing the methods by which analyses are to be carried out by analysts under the provisions of this Act; (d) prescribing the terms and conditions and the manner in which seed may be inspected, classified and tested; (e) prescribing the minimum field and seed standards for breeders', basic, certified 1, certified 2, quality declared seed and also seed standards for standard seed class; (f) prescribing standards for a seed testing laboratory, processing factory, seed warehouses, seed selling or distribution points shops; (g) prescribing procedures for the establishment of quality declared seed production; (h) respecting the fees that may be charged for any services rendered under this Act; (i) generally prescribing anything which requires to be prescribed under this Act. (3) The Minister may restrict the application of any of the regulations made under the provisions of subsection (1) to specialised areas or to any group or groups of people or premises. (4) Regulations made under this section may provide for penalties for the breach thereof not in excess of the penalties mentioned in this Act. (5) All regulations made under this section shall be published in the Government Gazette. 2003 16 17 2003 No. 18 Seeds SCHEDULE (under section 10) CONSTITUTION, FUNCTIONS AND MANAGEMENT OF THE SEED CERTIFCATION INSTITUTE 1. The power to carry out the functions and management of the business and affairs of the Institute shall be vested in the Institute's Management Committee. Manage- ment of the Agency Constituion 2.-(1) The Management Committee of the Institute shall comprise of the following of the members- Manage- (a) one member from the Crop Development Division of the Ministry of ment Agriculture responsible for seed issues; Committee (b) the Head of the National Post-entry Plant Quarantine Station; (c) one member from the Reseach and Development Division of the Ministry of Agriculture, responsible for biotechnology issues; (d) the Chief Seed Certification Officer who is the head of the Tanzania Official Seed Certification Institute. (2) The Minister shall appoint the Chairperson of the Management Committee and one member from the Tanzania Seed Trade Association to be a member of the Management Committee: 3. Members of the Management Committee shall hold office for a period of three The Term of years and shall be eligible for re-appointment. 4.-(1) Three members of the Management Committee shall constitute a quorum at any meeting and all decisions to be arrived at by the Management Committee shall be decided by a simple majority of the members present. (2) Each member of the Management Committee shall have one vote and in the event of equality of votes, the Chairperson of the meeting shall have a second or casting vote in addition to his deliberative vote. 5. Minutes in proper form of each meeting of the Management Committee have to be property kept and shall be confirmed by the Management Committee at its next sitting and signed by the Chairperson of the meeting. 6. The Management Committee shall have power to regulate its procedures in respect of meetings and proper conduct of its business. 7.-(1) The Institute shall have the following duties: (a) to conduct seed field inspections; (b) to effect sampling and testing; the manage- ment Commi- ttee Members Quorum Minutes of Manage- ment Committee Procedures Functions of the Institution 18 No. 18 2003 Seeds (c) to conduct seed inspections; (d) to accredit seed sampling and seed testing laboratories; to charge fees or otherwise generate revenue from the services rendered; to ensure that the revenue accruing from the fees or any other charge (e) (f) guarantees sustainable and quality services; to train seed producers, seed inspectors and seed analysts; to liaise with other International Organizations such as the International Seed Testing Association (ISTA) on seed related issues; to carry out variety performance tests; and (g) (h) (i) (j) to carry out pre and post control tests. (2) The Institute shall not engage itself, directly or indirectly in any trade or business connected with the production, processing, importation, sale or distribution for sale of any seed. 8. The Minister in consultation with the Management Committee shall appoint the Chief Certification Officer. 9. The Management Committee may, appoint at such salaries and upon such terms and conditions such officers and employees, for the proper and efficient performance of necessary. 10.-(1) There shall be a Common Seal of the Institute which shall be of such shape, size and form as the Management Committee may determine. (2) The Seal of the Institute shall not be affixed to any instrument except in the presence of the Principal and one Management Committee member. 11. The Institute shall keep and maintain proper books of accounts and records relating to its transactions in accordance with acceptable accounting standards: (a) the financial year of the Institute shall end on 30th June of each year; (b) the books of accounts shall be audited at the end of each financial year by an authorized auditor duly registered under the Auditors and Accountants (Registration ) Act, 1972. The auditors shall be appointed by the Management Committee; (c) the accounts and reports of the auditors shall be submitted to the Management Committee not later than four months after the end of each financial year, and the Management Committee shall submit a copy of the audit report to the Institute within two months after they have been audited; Seal of the Institute Management Committee may appoint employees of the Institute Appoint - ment of the Institute's Chief Certification Officer Accounts and audit Act No. 33 of 1972"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":172,"cells":{"data":{"kind":"string","value":"# Extracted Content 1 GOVERNMENT NOTICE NO. 37 published on 9/2/2007 THE SEEDS ACT, 2003 (No. 18 of 2003) ______ THE SEEDS REGULATIONS, 2007 _______ Made under section 33 _______ ARRANGEMENT OF SECTIONS PART I PRELIMINARY PROVISIONS Regulation Title 1. Short title and commencement date. 2. Interpretation. PART II REGISTRATION OF SEED DEALERS 3. Submission of application PART III VARIETY REALEASE, REGISTRATION AND DEREGISTRATION 4. Restriction for variety release. 5. Establishment of the sub-Committees. 6. Composition and meeting of the NVRC and NPT-TC. 7. Application for the variety release and procedure for conducting NPT. 8. Variety registration. 9. Variety deregistration. PART IV SEED CLASSES AND STANDARD 10. Class name and standards. 11. Additional requirements with respect to standard. 2 PART V MARKING AND LABELING 12. Restriction to use variety name. 13. Necessary information in marking and labeling. 14. General labeling requirements. 15. Application of labeling requirements. 16. Labeling of the seeds specified in Tables of the First Schedule. 17. Labeling of mixture of seed. 18. Labeling of roots, tubers, and pyrethrum seed. 19. Labeling of onion sets and multiplier onions. 20. Labeling of forage seed. 21. Labeling of mixtures of seed specified in Tables 8 and 9 of the First Schedule. 22. Official Tag. 23. Inter-agency labels. 24. General provision with respect to official and inter-agency labels. 25. Chief Seeds Certification Officer to authorize use of official or interagency certification tags. PART VI SEED CERTIFICATION 26. Restriction on uncertified seed. 27. Seed crop inspection. 28. Appeal against results of field inspection. 29. Harvesting of seed. 30. Seed processing. 31. Storage of processed seed. 32. Seed for sale. 33. Seed importation. 34. Seed exportation. 35. Pre and post control plots. PART VII SEED SAMPLING AND TESTING 36. Sampling of seeds. 37. Sampling intensity. 38. Seeds testing. 39. Exemption. 40. Fees. 41. Appeals. 42. Authorization of Inspectors, Samplers and Analysts. 43. Suspension or cancellation of authorization. 44. Change of variety name. 45. Detention and stop sale order. 3 46. Offences. 47. Retention. 48. Prohibited, restricted and noxious seeds. 49. Revocation. 4 GOVERNMENT NOTICE NO. 37 published on 9/2/2007 THE SEEDS ACT, 2003 (No. 18 of 2003) ______ THE SEEDS REGULATIONS, 2006 _______ Made under section 33 _______ PART I PRELIMINARY PROVISIONS Short title and commencement date 1. These Regulations may be cited as the Seeds Regulations, 2006 and shall come into operation on the date of their publication. Interpretation 2. -(1) In these Regulations, unless the context otherwise requires – Act. No 18 “Act” means the Seed Act, 2003; “authentic sample” means a sample for the released variety kept or maintained by a recognized gene bank for future reference; “authorisation” means a formal of a person or organization as specified in these Regulations; \"authorized Analyst\" means a person who has been authorized to undertake testing of seeds by the Tanzania Official Seed Certification Institute for the purposes of analyzing seeds; \"authorized field Inspector \" means a person authorized to undertake field inspection by the Tanzania Official Seed Certification Institute; \"authorized Inspector \" means a person authorized to undertake inspection of seeds by the Tanzania Official Seed Certification Institute; \"authorized laboratory \" means a laboratory authorized by the Tanzania Official Seed Certification Institute for purposes of testing seeds; \"authorized sampler\" means a person who has been authorized to undertake sampling of seeds by the Tanzania Official Seed Certification Institute for purposes of sampling seeds; \"authorized seeds Inspector\" means a person authorized to undertake seeds inspection by the Tanzania Official Seed Certification Institute; Act No.22 of 2002 “breeder” shall have a meaning ascribed to it under the Plant Breeders’ Rights 5 Act; \"certificate of registration\" means a certificate issued by the Director certifying that the holder of the said certificate is registered as a seeds dealer pursuant to section 16 of the Act; “Chief Seed Certification Officer” means a person appointed and designated as Chief Seeds Certification Officer pursuant to paragraph 8 of the Schedule to the Act, and shall head the Tanzania Official Seed Certification Institute; “Chief Seed Quality Controller” means the Director or any other person appointed by him under section 8 (2) of the Act; “composite sample” means a combination of primary samples drawn from the same seed lot and placed in a suitable container; “DUS” means Distinctness, Uniformity and Stability; “fasten” with respect to package means sealing in such a manner that it is impossible to open the package, without leaving evidence of it having been opened; “germination in respect to seed” means the emergency and development of the seedling to a stage where the aspect of its essential structures indicates whether or not it is able to develop further into a satisfactory plant under favorable condition; “inert matter” means all seed-like structures from both crop and weed plants and other matter which is not defined as pure seed or other seeds; \"Institute\" means the Tanzania Official Seed Certification Institute established by section 10 of the Act; \"inter-agency certification tag\" means an official tag in respect of seeds that are certified by a Recognized Certification Agency; “ ISTA” refers to International Seed Testing Association; \"lot number or designation\" means a number, mark, symbol or test number that identifies a seeds lot; “Ministry” means the Ministry responsible for agriculture; “NPT” means the National Performance Trial; “NPT-TC” means the National Performance Trial Technical Committee; “NVRC” means the National Variety Release Committee; “OECD” means Organization of Economic Cooperation and Development; \"official laboratory\" means a seed testing laboratory under the management of the Tanzania Official Seed Certification Institute; \"official sample\" means a sample of seeds that has been drawn by an Inspector in the prescribed manner; \"official tag\" means a tag in respect of seed that is derived from a crop grown in Tanzania and classified by the Tanzania Official Seed Certification Institute; “ other seed” ,means seed units of any plant species other than that of pure seed ; “Permanent Secretary” means the permanent secretary in the Ministry for the time being responsible for agriculture; “primary sample” means each probe, handful of Seeds drawn from a seeds lot as a sample and when a seeds lot is sampled either in containers or bulk, several primary samples are drawn from different containers or from 6 different places in the bulk; “pure seed” means the species stated by applicant or found to predominate in the test and shall include all botanical varieties and cultivars of that species ; “ release” means discharge for commercial multiplication, production or sale of seed or plant varieties; \"seed conditioning” means preparation by cleaning, processing, packing, treating or changing in any other manner the nature of a seeds lot; \"seed lot\" means a specified quantity of seeds, each portion of which is within reasonable limits, uniform with respect to species, variety, purity, germination, and other quality requirements; \"Seed Testing Certificate\" means a document issued by Tanzania Official Seed Certification or authorized seeds testing laboratory or a recognized seeds certification agency, certifying that the seeds identified therein meets the specified laboratory standards; “seed certification” means a legally sanctioned system for quality control in the process of producing, processing and marketing of seed for the purposes of maintaining and ensuring quality and genetic purity; “seed processing” means treatment of seed other than testing which the seeds is subjected to after harvesting; “seed production” means operations leading up to and including harvesting of the seeds from the seeds field; “Seed Testing Report” means a document issued by an official or authorize seed testing laboratory stating the results of the laboratory analysis requested; “seed testing” means the examination of sample of seeds with a view to determine its quality; “submitted sample” means a composite sample or portion of a composite sample of a size appropriate for tests submitted to a testing station for quality tests; “TOSCI” means Tanzania Official Seed Certification Institute established under section 10 of the Act; “undesirable seed” means seeds that are light, undersized, off-colour, shrunken, immature, damaged, diseased, injured, sprouted or frosted seed; “UPOV” means Union for Convention on Protection for New Varieties; \"varietal blend\" means a mixture seed that contains two or more varieties of the same plant species; \"variety name\" includes a word, a number or a letter or combination of number and letter used to designate a variety; and “working sample” means a portion of a submitted sample on which a quality test is made. PART II REGISTRATION OF SEED DEALERS Submission of application 3.-(1) An application for the registration as seed dealer shall be submitted to the Director on Form SR I set out in the Fifth Schedule to these Regulations. 7 (2) Each application shall be accompanied by the appropriate fees as set out in the Sixth Schedule to these Regulations. (3) The Director shall register the applicant and issue a registration certificate contained as set out in Form SR II in the Fifth Schedule to these Regulations upon being satisfied that the applicant has complied with the requirements for registration. PART III VARIETY RELEASE, REGISTRATION AND DEREGISTRATION Restriction for variety release 4. No variety shall be released in Tanzania unless it has passed DUS test, evaluated through the National Performance Trial and recommended for release by the National Seed Committee. Establishment of sub- Committees 5.-(1) There are hereby established sub-Committees of the National Seed Committee to be known as the National Variety Release Committee (NVRC) and the National Performance Trial Technical Committee (NPT-TC). (2) The National Variety Release Committee shall be responsible for reviewing recommendations from the National Performance Trial Technical Committee and recommend for variety release to the National Seed Committee. Composition and meetings of the NVRC and NPT- TC 6.-(1) The National Variety Release Committee shall be composed of the following members:- (a) the Director for the time being responsible for crop development who shall be the Chairman; (b) the Director for the time being responsible for research in the Ministry; (c) one officer responsible for co-ordination and supervision of plant quarantine services in the country; (d) one officer responsible for co-ordination and supervision of seeds industry in the Ministry, who shall be the Secretary; (e) Chief Seed Certification Officer; (f) Curator of the gene bank at the National Plant Genetic Resources Centre; (g) head of section responsible for National Performance Trial within the TOSCI; (h) one plant breeder from agricultural universities to be appointed by the Permanent Secretary; (i) one pathologist from research institute within the Ministry responsible for agriculture to be appointed by the Permanent Secretary; (j) Registrar of Plant Breeders’ Rights; (k) a representative from Tanzania Seed Trade Association to be appointed by the Permanent Secretary upon recommendation by the respective association; (l) Chief Executive Officer responsible for Agricultural Seed Agency 8 (m) a representative from the Plant Breeders’ Association to be appointed by the Permanent Secretary upon recommendation by the respective association; and (n) a representative from farmers association to be appointed by the Permanent Secretary upon recommendation by the respective association. (2) The National Performance Trial Technical Committee shall be composed of the following members :- (a) Chief Seed Certification Officer, who shall be the Chairman; (b) one Seed technologist from department responsible for co- ordination and supervision of seeds industry in the Ministry to be appointed by the Permanent Secretary; (c) one plant breeder from the department responsible for research in the Ministry to be appointed by the Permanent Secretary; (d) head of section responsible for National Performance Trial within TOSCI, who shall be the Secretary; (e) one plant pathologist from an agricultural university to be appointed by the Permanent Secretary, upon consultation with agricultural universities; (f) one plant entomologist from any higher learning institution to be appointed by the Permanent Secretary, upon consultation with higher learning institutions; (g) one plant breeder from plantation crops research institution to be appointed by the Permanent Secretary, upon consultation with respective institutions; and (h) one seed producer representing Tanzania Seeds Trade Association to be appointed by the Permanent Secretary, upon consultation with respective associations; (3) The National Variety Release Committee and the National Performance Trial Technical Committee may co-opt any person to attend its meetings. (4) The National Variety Release Committee and the National Performance Trial Technical Committee shall regulate their own procedures for conducting meetings. Application for variety release and procedure for conducting NPT 7.-(1) Any person who intends to release a variety shall be required to submit to the Tanzania Official Seed Certification Institute an application for DUS test and NPT, on Form SR IIIA and SR IIIB respectively, as set out in the Fifth Schedule to these Regulations. (2) An application for DUS test shall be made one season prior to the application for NPT and shall be supported by the following:- (a) sufficient seed sample for the first season DUS test; (b) variety description; (c) application fees and DUS testing fees as set out in the Sixth Schedule to these Regulations; and (d) on-farm trial and farmers assessment data. 9 (3) Upon receiving the application and materials, TOSCI shall conduct a DUS test, repot the results to the applicant and issue the DUS test certificate for the qualified application on Form SR IV as set out in the Fifth Schedule to these Regulations. (4) The application for NPT test shall be supported with the following:- (a) a minimum of two recent previous seasons advanced yield trial data from not less than three recognized testing sites in Tanzania or any other country which is in agreement for harmonization of seeds policy and legislations with Tanzania, as set out in the Seventh Schedule to these Regulations; (b) sufficient seed sample for conducting NPT and second DUS test; (c) fees for the NPT and second DUS test; and (d) any other additional information that may be required for determination of the merits of the candidate variety. (5) TOSCI shall conduct NPT for a minimum of one season in at least three sites as set out in the Seventh Schedule to these Regulations, and shall conduct second DUS test and submit the report to NPT-TC for review. (6) TOSCI shall develop procedures and conditions for conducting DUS test and NPT for perennial crops. (7) Upon completion of review of the NPT report, NPT-TC Secretary shall report the results to the applicant and present the NPT data and the recommendations of the NPT-TC to the NVRC on Form SR V as set out in the Fifth Schedule to these Regulations. (8) The National Variety Release Committee shall review the recommendations of the NPT-TC and advise the National Seed Committee. (9) In order for a candidate variety to be recommended for release to the National Seeds Committee, a breeder shall be required to submit to TOSCI an authentic sample of pre- basic seed for reference purpose. (10) The amount of authentic sample referred to in sub- regulation (9) shall be:- (a) four kilograms for cereals, pulses or any other big seed crops; or (b) one hundred grams for small seed crops species (11) TOSCI shall have discretion to determine the amount of authentic sample needed for plant species other than those referred under sub-regulation (10). (12) A breeder shall be required to replenish the authentic sample as it may be required by TOSCI. Variety registration 8.-(1) The Director shall register and issue a Certificate of Registration to the Applicant once his variety is approved by Minister pursuant to Section 21 of the Act. (2) The Certificate of Registration of the varieties shall be on Form SR VI as set out in Fifth Schedule to these Regulations. (3) The Director shall enter the information hereunder in the National Variety Catalogue upon registration:- (a) name of registrant; (b) variety name; 10 (c) plant species; (d) registration number, (e) registration date; (f) date of release; (g) name of breeder; (h) origin of the variety; (i) any other characteristics; (j) area of adaptation; (k) duration of maturity; (l) yield potential; (m) tolerance to insect pest; (n) disease tolerance; (o) end use; (p) agency responsible for maintenance; and (q) any other information deemed necessary. Variety deregistration 9.-(1) the Director may, in consultation with the National Seeds Committee, deregister a variety upon proof that the variety is no longer conforming to its original description or has lost its qualitative and quantitative attributes for which it was released. (2) Authentic seed sample of deregistered variety shall be sent to the national gene bank for conservation. PART IV SEED CLASSES AND STANDARDS Class names and standards 10. Seed classes and standards for plant species for the purposes of these Regulations shall be as set out in the tables of class standard set out in the First Schedule to these Regulations. Additional requirements with respect to standards 11.-(1) In addition to conditions set out under regulation 10, requirements prescribed by sub- regulation, (2), (3) and (4) of this regulation shall apply with respect to the standards of the appropriate plant species specified in the tables of class standards set out in the First Schedule to these Regulations. (2) Seed of every plant species shall: - (a) not contain any objectionable weed seed as provided in the Eight Schedule to these Regulations; (b) if classified with the name of Tanzania seed class, not be mixed with any other seed class; and (c) for each seed lot sold as “Pre- basic seed”, “Basic seed”, ”Certified 1” or “Certified 2: (i) be uniform; (ii) not containing moisture in excess of thirteen percent or such greater percentage as the Chief Seed Certification Officer may, prescribe for seed of a specified plant species; and 11 (iii) be free from undesirable seed and inert matter within the percentage allowed under these Regulations. (3) Any seeds offered for sale shall be subjected to a test or tests after seven months from the date on which the last test was performed to determine the percentage of germination required to be shown on the label thereof; (4) Without prejudice to the provision of sub-regulation (3), the Chief Seed Certification Officer may, prescribe longer or shorter periods for re-testing. (5) It shall be the responsibility of seed dealer to call an Inspector for re- sampling for the purposes of re-testing and re-sealing of seed lots whose validity of germination test results have expired. (6) Any seed dealer who contravenes the provisions of this regulation commits an offence. PART V MARKING AND LABELING Restrictions to use variety name 12.-(1) No person shall mark or label a package of seed with a variety name unless that seed is of the variety to which the variety name refers. (2) No person shall alter the name of a variety on the label of any seed container. (3) Except for the mixture of lawn, turf grass or forage seed as specified in Tables 8, 9 and 11 set out in First Schedule to these Regulations, no person shall label a package of a mixture of seed with a variety name unless he is authorized in that behalf by the Chief Seed Certification Officer pursuant to Regulation 23, and the seeds to which the variety name refers is one of Tanzania seed class. Necessary information in marking and labeling 13.-(1) The information required by these Regulations on the label or outside of a package of seed shall be conspicuously, legibly and indelibly written or printed in both English and Swahili, and shall appear on one exposed face of the package or label and shall be of a size and colour that can be easily read. (2) No label shall contain any incorrect or misleading information, mark or brand name that might be construed as a variety name. (3) For purposes of these Regulations, the seed certification seal and the tag colours described under this sub- regulation shall be used as follows- (a) the seed certification seal shall be applied on all tags relating to seed of “Pre- basic”, “Basic”, “Certified 1” or “Certified 2” classes as classified in the Second Schedule to these Regulations; (b) in the case of tag on a package containing Pre- basic Seeds, white with diagonal violet colour shall be used, with the word “Pre-basic” conspicuously applied across one side of the tag; (c) in the case of tag on a package containing Basic seed, white colour shall be used, with the word “Basic” conspicuously applied across one side of the tag; (d) in the case of a tag on a package containing “Certified 1” seed, Blue colour shall be used, with the word ”Certified 1”or “C1” 12 conspicuously applied across one side of the tag; (e) in the case of a tag on a package containing “Certified 2” seed, Red colour shall be used, with the word “Certified 2” or “C2” conspicuously applied across one side of the tag; (f) in the case of label on a package containing standard seed, the tag shall be yellow with the word “ Standard” conspicuously applied across one side of the tag; (4) The seed certification seal referred to in sub- regulation (3), shall be printed words thereon “Tanzania Certified Seeds” and for standard seed, the seal shall be printed with the words “Tanzania Standard Seed” and shall be of such material, shape, size as the Minister may approve. General labeling requirements 14.-(1) Every package of seed marked with a class name shall have on its label a description that specifies the seed standard as provided for in these Regulations. (2) Where the seed is a mixture or blend of two or more original seed lot of certified seed, the word “BLEND” preceded by the two digit seed year designation; (3) Whenever seed is treated with a poisonous material it shall be thoroughly stained with a conspicuous contrasting colour to show that the seed has been treated and the container of such seed shall be marked or attached a conspicuous label reading as follows:- “POISONOUS: DO NOT USE AS FOOD, FEED OR OIL; or SUMU: MBEGU HIZI SIO KWA MATUMIZI YA CHAKULA CHA BINADAMU AU WANYAMA. “TREATED WITH………or “IMEWEKWA SUMU YA…….:- (Name of poisonous material or substance in bold letters in Swahili and English). (4) Seed for sale shall be packed in packages unless- (a) it is delivered in a bulk container that is labeled in accordance with these Regulations and accompanied with other relevant information for importation of seed as provided under regulation 33; or (b) it meets the following conditions:- (i) it is of one of the Tanzania seed classes and is on transit within Tanzania and accompanied by a transport order issued by Tanzania Official Seed Certification Institute or an authorized Inspector on Form SR IX as set out in the Fifth Schedule to these Regulations; and (ii) it bears an inter-agency certification label pursuant to Regulation 23. (5) No person, other than the ultimate user, shall remove label, seal or open mechanically sewn or closed package of the seed. (6) Where certified seed lots are re- packaged, the re-packing shall be done only with the approval of the Chief Seed Certification Officer. Application of labeling requirements 15. The labeling requirements prescribed under regulations, 10, 11, 12, 13 and 14 shall apply to seed of all plant species specified in these Regulations. Labeling of seed specified in 16.-(1) Every package of seed, offered for sale, of the plant species 13 Tables of the First Schedule specified in Tables 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, or 15, 18 and 19 set out in the First Schedule to these Regulations shall be labeled with the following information- (a) the name and address of the seed dealer; (b) the name of the plant species; (c) the name of the variety of the seed; (d) seed class; (e) lot number; (f) weight of the package; (g) month and year of germination test; (h) in the case of seed that is imported, the name of the country of production; and in the case of seed that is a blend of two or more varieties, the name of each of the component varieties. (2) For the purpose of sub - regulation (1), seeds provided hereunder shall be kind of seeds for purposes of these Regulations: (a) “open pollinated”, is a seed produced by means other than controlled and selective breeding; (b) “varietal cross”, is a seed of the first generation of a cross between two named open pollinated varieties, or an open pollinated variety and a hybrid; (c) “top cross”, being seed of the first generation of a controlled cross between a named open pollinated variety and an inbred line; (d) “hybrid”, is a seed of the first generation of a cross between two or more inbred lines or their combination including single crosses, double crosses and three-way crosses; (e) “composite variety”, is a seed derived from selected strains which have been allowed to freely inter-pollinate; (f) “inbred line”, is a seed derived from a relatively homogeneous line produced by inbreeding and selection; (g) “synthetic variety”, is a seed produced through a combination of several intercrosses of genotypes which have been previously tested for their combining ability; (h) “single cross hybrid”, is a seed obtained by crossing two unrelated homozygous strains to obtain uniform and enhanced trait expression in the first generation; (i) “a three way cross hybrid”, is a seed obtained by crossing three unrelated homozygous stains to obtain uniform and enhanced trait expression in the first generation heterozygote; and (j) “a double cross hybrid”, is a seed obtained by crossing four unrelated homozygous strains or two unrelated single cross hybrids to obtain uniform and enhanced trait expression in the first generation heterozygote. Labeling of mixtures of seed 17. Every package of a mixture of seed, offered for sale, of the specified in the Table 11 set out in the First Schedule of these Regulations shall be labeled with: (a) the name and address of the dealer; 14 (b) seed class; (c) the name and percentage by weight of each in the mixture, in order of its predominance; (d) the name of the variety of each plant species in the mixture. (e) germination percentage of each component of the mixture, in order of its predominance; (f) month and year of germination test; and (g) in the case of seed that is imported, the name of the country of production; Labeling of roots, tubers, and pyrethrum seed 18. Every package of seed, offered for sale, of the plant species specified on Table 16 set out in the First Schedule to these Regulations shall be labeled with: (a) the name and address of the dealer; (b) the name of the plant species; (c) the name of the variety roots or cuttings, as the case may be; (d) seed class and year of production; (e) germination or sprouting percentage if applicable; (f) month and year of germination or sprouting test; and (g) lot number. Labeling of onion sets and multiplier onions 19. Every package of onion sets and multiplier onions offered for sale shall be labeled with: (a) the name and address of the dealer; (b) the term “onion sets” or “multiplier onions”; (c) class of the onion sets and multiplier onions as set out in Table 17 of the First Schedule to these Regulations; (d) germination or sprouting percentage; (e) lot number; (f) month and year of germination test; and (g) in the case imported, the name of the country of production. Labeling of forage seed 20. Every package of seed, offered for sale, of plant species specified in Tables 8 and 9 set out in the First Schedule to these Regulations, shall be labeled with: (a) the name and address of the dealer; (b) the name of the plant species; (c) seed class; (d) variety name; (e) country of production if it is imported; (f) germination percentage; (g) lot number; and (h) month and year of germination test. Labeling mixtures of Seed specified in Tables 8 and 9 of First Schedule 21.-(1) Every package of a mixture of forage seed offered for sale, of the plant species specified in Tables 8 and 9 set out in First Schedule to these 15 Regulations shall be labeled with: (i) the name and address of the dealer; (ii) seed class; (iii) the name and percentage by weight of each in the mixture, in order of its predominance; (iv) the name of the variety of each plant species in the mixture. (v) germination percentage of each component of the mixture, in order of its predominance; (vi) month and year of germination test; and (vii) in the case of seed that is imported, the name of the country of production; (2) The information stated on a package or label pursuant to paragraphs (b), (c) and (d) of sub regulation (1) of this regulation shall be on the same face of the package or label and shall be of the same type of printing or lettering. Official tag 22.-(1) Every package of seed produced in Tanzania and classified with the name of one of the Tanzania seed class shall be fastened and tagged with an official tag authorized by the Chief Seed Certification Officer. (2) The domestic tag referred to under sub-regulation (1) shall contain the: (a) name of the plant species; (b) name of the variety; (c) seed class; (d) serial number of the label or tag; (e) seed certificate number; and (f) lot number. (3) The tags referred to under sub-regulation (1) shall be supplied only to seed dealers applying for these tags and furnishing an Inspector with- (a) a declaration of the grower declaring that the seed to which the tags are to be applied is derived from the crop in respect of which the final field inspection results specified in form SR VIII B set out in the Fifth Schedule to these Regulations; and (b) a declaration of the applicant, if the applicant is not the grower, declaring that the seed referred to in the grower’s declaration is the seed to which the labels are to be applied and that the seed has not been mixed or contaminated while in the possession of the applicant. (4) The tag for standard seed, shall contain the: (a) name of the seed; (b) name of the variety of the seed; (c) name of the class of the seed; (d) serial number of the tag; and (e) lot number. Inter-agency labels 23.–(1) Every package of seed of foreign origin classified with the name of the Tanzania seed class shall be fastened and tagged with an inter-agency certification tag authorized by the Chief Seed Certification Officer; 16 Provided that, for any package of seed which originates from an East African Community member country, grey colour shall be used. (2) The inter-agency certification tag referred under sub-regulation (1) shall contain the: (a) name of the plant specie; (b) name of the variety; (c) seed class; (d) name of the country of production; (e) serial number of the tag; and (f) lot number. (3) Inter-agency certification tags referred to under sub-regulation (1) shall be supplied only if the seed dealer applying for these tags furnishes an Inspector with- (a) seed inspection report from a certification agency recognized by the Tanzania Seed Certification Institute; and (b) particulars of the information on the tag of the foreign certification agency. General provisions with respect to official and inter-agency labels 24.-(1) An official tag or inter-agency certification tag shall only be applied to containers for which the tags were issued. (2) Except where the Chief Seed Certification Officer directs otherwise, an official or inter-agency certification tag shall not contain anything other than the information required by regulations 18 or 19. (3) An official tag or inter-agency certification label shall be affixed to a seed container by an Inspector Chief Seeds Certification Officer to authorize use of official or inter- agency certification tags 25.-(1) The Chief Seed Certification Officer may, authorize any seed dealer to affix an official tag to seed of one of the Tanzania seed class, if that person:- (a) has seed processing equipment and facilities adequate for the proper processing of seed; (b) has adequate facilities to maintain the identity of different seed lots; and shall return to the Chief Seed Certification Officer on request by him any label supplied pursuant to regulations 18 or 19. (2) Where the Chief Seed Certification Officer is of the opinion that the seed dealer authorized to affix official labels pursuant to sub-regulation (1) is not complying with the provisions of regulations 18, 19 and 20 of these Regulations, the Chief Seed Certification Officer may withdraw the authority granted under sub-regulation (1). PART VI SEED CERTIFICATION Restrictions 26.-(1) No seed shall be certified unless, it has been produced, inspected, 17 on uncertified seed sampled, tested, and complied with the standards set out in the First Schedule to these Regulations. (2) Varieties released in Tanzania pursuant to regulation 4 shall be eligible for certification. (3) Seed shall be classified in four classes as set out in the Second Schedule of these Regulations. (4) Minister may make rules and procedures for certification and control of Quality Declared Seed and tree seed. Seed crop inspection 27.-(1) Every seed grower or his agent shall, within thirty days after a seed crop is planted, apply for field inspection by completing Form SR VII set out in Fifth Schedule of these Regulations upon payment of fees set out in Sixth Schedule to these Regulations. (2) An application of field inspection may be refused by the Tanzania Official Seed Certification Institute if it is made thirty days after planting. (3) A field inspection for the purpose of certification shall be conducted by the field inspector or authorized Inspector and shall be confined to the field of a registered seed producer. (4) In inspecting the field, the Inspector or the authorized inspector shall ensure that all field standards as provided in Part II set out in the First Schedule to these Regulations are complied with. (5) The Field Inspector or authorized inspector shall have powers to enter into any field registered for inspection and shall not approve any field or part thereof if satisfied that it does not meet the prescribed field standards. (6) The Field Inspector or the Authorized Inspector shall visit each unit of certification and conduct at least a minimum number of inspections required for each seed crop. (7) The Field Inspector or Authorized Inspector shall make proper counts of plants or heads of plants as deemed necessary fit and the minimum counting shall be: (a) up to two hectares, five counts shall be used; and (b) for each addition of two hectares up to fifty hectares, one more count shall be needed, beyond fifty hectares, one additional count shall be needed for every four hectares. (8) The minimum number of plants or heads per count required for each crop shall be as set out in the Fourth Schedule to these Regulations. (9) Inspection may include pre-planting, nursery, pre-harvest, post harvest and storage facilities. (10) It shall be the responsibility of the seed grower to observe the recommended cultural practices at every stage of seed production for each unit of certification. (11) Upon completion of every field inspection, the Inspector or Authorised Inspector may advise the seed grower on any non- compliance of the inspection and in case there is a need to undertake re- inspection, the seed grower shall bear the cost of such re- inspection. (12) The result of each field inspection shall be issued on Form SR VIIIA set out in the Fifth Schedule to these Regulations; and shall be signed by both the 18 Inspector and the grower or his representative. (13) Upon completion of the field inspection, the Inspector shall accord appropriate class any seed crop which meets the standards and fill in a Final Inspection Result in Form SR VIIIB as set out in the Fifth Schedule to these Regulations and the results shall be signed by both field inspector and the grower or his dully authorized representative. Appeal against the result of field inspection 28-(1) Where a registered grower or his agent disagrees with the results of any field inspection, he may appeal within seven days from the date of the issuance of the results of the inspection to the Chief Seed Certification Officer. (2) The Chief Seed Certification Officer shall determine the appeal and issue his decision in writing within fourteen days from the date of receipt of the appeal. (3) Where the Chief Seed Certification Officer is satisfied with the grounds of appeal, he shall approve for a re-inspection. (4) Re-inspection shall be carried out by the team comprising of – (a) one senior Inspector; (b) one breeder; and (c) the aggrieved seed producer or his dully appointed representative. (5) The aggrieved grower shall pay the re- inspection fee which shall be refunded to him in case the re-inspection is proved to be in his favour. Harvesting of seed 29.-(1) The seed grower shall ensure that the seed quality is maintained during harvesting and transportation to the processing plants. (2) Where the processing plant is located far from the seed field, seed grower shall ensure that transportation of seed is done under close supervision of an Inspector or Authorised Field Inspector and after obtaining a transport order in Form SR IX as set out in the Fifth Schedule to these Regulations. (3) Before seeds are transported the Inspector or a person authorised shall mark the container with indelible ink. Seed processing 30.-(1) A registered seed processor shall processes only seeds from the approved fields or seeds permitted to be imported into Tanzania. (2) Every seed processor shall notify the Chief Seed Certification Officer or any authorized officer before processing any seed lots and upon such notification, the Chief Seed Certification Officer or authorized officer shall issue a work order to the dealer in Form SR X set out in the Fifth Schedule to these Regulations. (3) The Seed Inspector or authorized Seed Inspector may enter and inspect the premises for seed processing. (4) The processed seed shall be properly marked and stored separately in identifiable seed lots. Storage of processed seed 31.–(1) Each container or bag of processed seed in every lot shall be properly labeled and identified. (2) Seed lot shall be kept in a way to ensure the limits set for moisture and other quality attributes. Seed for sale 32.-(1) No seed shall be offered for sale unless it is certified in accordance to 19 these Regulations or rules made under regulation 26(4). (2) Every seed dealer shall be responsible for the quality of any seed he sells or offers for sale. (3) A seed dealer may appoint an agent or a stockist with knowledge, ability and appropriate facilities to maintain the quality and viability of the seed offered for sale. (4) The agent or stockist appointed pursuant to sub-regulation (3), shall have a valid registration certificate for dealing with seed business issued by the Director pursuant to Section 16 of the Act. (5) Where a Seed Inspector or an authorized inspector has reasonable grounds to believe that any seed or seed lots is being sold without having reached minimum prescribed standards or in violation of any provisions of the Act and these Regulations, may immediately issue a stop sale order on Form SR XI set out in the Fifth Schedule to these Regulations. Seed importation 33.-(1) Every seed dealer who, intends to import seed into Tanzania, shall submit to the Director a notice of intention to import such seed on Form SR XII set out in the Fifth Schedule to these Regulations. (2) the notice under sub-regulation (1) shall specify:- (a) name and address of importer; (b) country of origin; (c) name and address of importer; (d) the quantity of seed; (e) expected date of arrival of consignment; and (f) the species and the cultivar. (3) Upon receipt of such notice, the Director shall issue a seed import permit in Form SR XIII set out in the Fifth Schedule to these Regulations. (4) Any seed imported under this regulation shall not be sold unless its quality has been examined and approved by TOSCI or any other certification agency which is in bilateral agreement with Tanzania as regard to seed certification. (5) Any imported seed shall be accompanied by certificate of quality issued by a Recognized Certification Agency, phytosanitary certificate and shall meet Tanzanian quarantine requirements as provided in the Plant Protection Act. Seed exportation 34.-(1) Any seed dealer who intends to export seed from Tanzania, shall submit to the Director a notice of intention to export on Form SR XIV set out in the Fifth Schedule to these Regulations. (2) The notice under sub -regulation (1) shall be accompanied with an import permit from the country to which seed is exported and shall specify the quantity, plant species and variety to be exported. (3) Upon receipt of such notice, the Director shall issue seed export permit on Form SR XV set out in the Fifth Schedule to these Regulations. (4) The exporter shall ensure compliance with all conditions for export of seed as provided in the Plant Protection Act. Pre and post control plots 35.- (1) Any seed lots officially sampled and tested pursuant to these Regulations shall be grown in post control plots in accordance with OECD seed 20 scheme. (2) Control plots referred to under sub-regulations (1) shall be open for examination and assessment by all parties interested in the seed industry. (3) Upon completion of the examination and assessment of control plots, the Field Inspector or Authorized Inspector shall write a report on the number of off- types, other varieties, variety identity, purity, diseased plants and other diversions observed in the plots. PART VII SEED SAMPLING AND TESTING Sampling of Seeds 36.-(1) Any seed sample for testing shall be taken by a Seed Inspector or Authorised Inspector in accordance with the requirements prescribed under these Regulations. (2) The sample referred to under sub- regulation (1) shall be provided to the Seed Inspector or Authorized Inspector free of charge for purposes of laboratory seed testing and post control planting and examination. (3) Where an Inspector requires a larger amount of seed sample as he considers it necessary for satisfactory testing, re-testing or analysis, the size of each sample shall comply with the particulars set out in the Third Schedule to these Regulations. (4) Each seed sample shall bear a unique sample number for reference. (5) Seed lots shall be created at the time of sampling and shall not exceed the maximum weights prescribed in these Regulations. (6) Where automatic samplers have not been installed, a seed dealer shall arrange the packages in such a way to enable the seed Inspector or Authorized Inspector to reach all packages and draw samples. (7) Sampling of seed lots shall be conducted in accordance with the current Rules of ISTA. (8) Seed from different fields of the same class, species and variety which have passed field inspection and which can be traceable, may be blended and bulked to constitute one seed lot. (9) The seed dealer shall provide reliable scales for ascertaining the weight of a seed lot. (10) The seed dealer shall pay appropriate fees for seed sampling as set out in the Sixth Schedule to these Regulations. Sampling intensity 37.-(1) When sampling seed lots in a container that can be sealed, the sampling intensity hereunder shall be taken as the minimum requirements:- (a) seed not exceeding 500 kg.- five primary samples shall be taken except that for small lots not exceeding 50 kg. three or four samples may be taken; (b) seed exceeding 500 kg. – but not exceeding 3,000 kg. – one primary sample for every 300 kg. shall be taken, so however, that not less than five primary samples shall be taken; (c) seed exceeding 3,000 kg but not exceeding 20,000 kg. – one primary sample for every 500 kg. shall be taken, so however, that not less than 21 10 primary samples shall be taken; and (d) seed in bulk shall be sampled at random locations and the samples shall be drawn from varying depths. (2) For seeds lots in bags or other containers up to 100kg capacity, samples shall be taken at random locations and the intensity hereunder shall be taken as the minimum requirements:- (a) from 1 – 4 containers , three primary samples from each container; (b) from 5 – 8 containers, two primary samples from each container; (c) from 9 -15 containers, one primary sample from each container; (d) from 16 -30 containers, 15 primary samples total; (e) from 31 -59 containers, 20 primary samples total; (f) from 60 or more containers, 30 primary samples total. Seeds testing 38.-(1) Seed testing for the purpose of certification shall be conducted by an official seed testing laboratory or any authorized laboratory. (2) Any sample drawn or by the Seed Inspector or Authorized Inspector or taken by any private individual shall be submitted to the seed testing laboratory together with Form SR XVI set out in the Fifth Schedule to these Regulations. (3) Seed testing laboratory shall:- (a) test seed in accordance with the ISTA Rules; (b) in case for samples submitted by the Seed Inspector or Authorized Inspector, record results of the seed test on a certificate in Form SR XVII set out in the Fifth Schedule to these Regulations; (c) in case of samples submitted by the private individual, record results of seed testing report on Form SR XVIII set out in the same Schedule; and (d) store the sample under optimal storage conditions for at least twelve months from the date the test results certificate was issued. (4) Notwithstanding the provision of sub- regulation 3(d), the testing laboratory shall not be held responsible for any deterioration of the sample that may occur. PART VIII MISCELLANEOUS Exemption 39. The Minister may by order published in the Gazette, exempt some seed or class of seeds from the provisions of these Regulations. Fees 40.-(1) The fees set out in the Sixth Schedule to these Regulations shall be payable in respect of all services as provided therein. (2) The fee for any service shall be paid at the time when the application for a particular service is made. (3) The Minister may, by notice in the Gazette, remit in whole or in part any fees payable by any person in respect of any service, if he is satisfied that it is in the public interest to do so. Appeals 41.-(1) Any person who is aggrieved by the decision of any officer or the National Performance Trial-Technical Committee or National Variety Release Committee in the administration of the Act or these Regulations, may appeal to the 22 National Seed Committee. (2) Any person who is aggrieved by the decision of the National Seed Committee may appeal to the Minister within fourteen days upon receipt of such decision. (3) Any appeal whose time limit has not been specifically provided under the Act or these Regulations shall be made to the Minister within fourteen days from the date of receiving of a particular decision. Authorisatio n of Inspectors, Samplers and Analysts 42.-(1) Any person who wishes to be authorized as seed testing laboratory, an Inspector, Seed Sampler, or Analyst for the purposes of these Regulations, shall apply in writing to the Chief Seed Certification Officer to that effect. (2) The application made under sub-regulation (1) shall be accompanied with documentary evidence showing that the Applicant is knowledgeable of the principles and practices of seed testing, field or seed inspection, seed conditioning or seed sampling. (3) The application under sub-regulation (1) shall be accompanied with appropriate fees as set out in Sixth Schedule to these Regulations. (4) The Chief seed Certification Officer may after recommendation of the Management Committee of TOSCI and upon satisfied that the Applicant is capable to be authorised as an Inspector, Sampler or Analyst issue an authorisation Certificate on Form SR XIX set out in Fifth Schedule to these Regulations. (5) TOSCI shall from time to time issue guidelines and other requirements as regard to the authorisation of Inspectors, Samplers, Analysts and seed laboratories. (6) The Chief Seed Certification Officer shall renew annually the authorisation upon payment of the prescribed annual fees as set out in Sixth Schedule to these Regulations. (7) Authorisation referred under this regulation shall be limited to the activities for which the authority has been granted. Suspension or cancellation of authorisation 43.-(1) The Chief Seeds Certification Officer may suspend or cancel the authorisation issued under regulation 42, if:- (a) a false or misleading information has been submitted in support of the application for the authorisation; or (b) the authorised person has not complied with the provisions of the Act or these Regulations; or (c) the authorised person has not paid the applicable annual fee before 1st January of the year in respect of which the authorisation is to be renewed; or (d) the authorised person has provided or maintained false or misleading records or samples in respect of any seed. (2) The Chief Seed Certification Officer shall not suspend or cancel the authorisation under this regulation unless:- (a) the authorized person has been informed in writing the reasons for suspension or cancellation; (b) the authorized person has been given an opportunity to be heard, either 23 by written or oral representations, in respect of the suspension or cancellation; and (c) the authorized person has been issued with a fourteen days prior notice of intention to suspend or cancel the authorisation. (3) A suspension of an authorisation shall remain in effect until:- (a) the Chief Seeds Certification Officer has been satisfied that the suspended person has taken corrective measures; and (b) the Chief Seeds Certification Officer notifies the suspend person in writing that the suspension has been lifted. Change of variety name 44.-(1) The Director may after consultation with the National Seed Committee, approve change in variety name. (2) the variety name may be changed pursuant to this regulation, if the Director is satisfied by the information received from the breeder that justifies change in variety name. (3) Change of variety name shall come into effect on the date on which the Director approves. Detentions and stop sale order 45.-(1) Any seed or package seized pursuant to subsection (4) of section 22 of the Act may be detained by an Inspector at any place by attaching a detention tag or mark to:- (a) where only the seed is seized, the package provided by the institute and in which the seed is placed; (b) where only the package is seized, the package; (c) where the package and the seed are seized, the package; and (d) where a seed lot in packages is seized, at least one package of the seed lot. (2) On attaching a detention tag or mark to the appropriate package referred to in sub-regulation (1), the Seed Inspector or an authorised inspector shall issue a stop sale order as provide under regulation 32 (5) to the person entitled to possession, at the time of seizure, of the seed or package, as the case may be. (3) No person shall alter or remove a detention tag or mark attached to a package or sells any seed or package detained pursuant to these Regulations. (4) No person shall move any seed or package detained pursuant to sub- regulation (1), except where an inspector issues a written authorization indicating that the seed or package shall be placed in a safer or more convenient location. (5) Upon issuance of detention order, an inspector shall take or cause to be taken a sample of each seed lot that has been detained. (6) Where any seed has been placed under detention or stop sale by an inspector under this regulation, the owner or the person in possession of that seed may apply to the inspector for the release of the seed. (7) No seed under detention or stop sale order shall be released unless the person applying for the release has fulfilled to the satisfaction of the Chief Seed Certification Officer all the requirements of the Act and these Regulations. (8) On release from detention of the seed or package, an inspector shall issue a notice of release to the person who was in the possession of the detained seed. (9) Any Seeds or package forfeited to the Government under the provisions 24 of the Act or these Regulations shall be disposed of in such manner as the Chief Seeds Quality Controller may, with the approval of the Minister, direct. (10) Costs incidental to the detention shall be payable and recoverable from the person whose seed have been detained. Offence 46. Any person who contravenes the provision of these Regulations commits an offence, except as otherwise provided, be liable upon conviction to a fine not less than one million shillings but not exceeding five million shillings or to imprisonment for a term not exceeding one year or to both. Retention 47. The Minister may, after consulting the Minister for Finance determine the amount of money to be retained for TOSCI from collections made by TOSCI in discharging its duties under the Act and these Regulations. Prohibited, restricted and noxious seeds 48. The seeds set out in the Eighth Schedule to these Regulations shall be deemed as prohibited, restricted and noxious weed seeds for the purpose of these Regulations. Revocation of GN.No.29 of 1976 49. The Seed Regulations 1976, are hereby revoked 25 ____________ FIRST SCHEDULE ____________ (Made under Regulations 10) ____________ TABLES OF STANDARDS SEED ____________ PART I: LABORATORY STANDARDS TABLE 1 Applicable to: (a) Wheat including hybrid – Triticum aestivum L. and (b) Wheat durum – Triticum durum Desf. Factor Class Basic Certified1 Certified2” % % % Pure Seed (Minimum) … … … … … … … ……... 99.0 99.0 99.0 Other Seed (Maximum) … … … … …. ….. …… 0.9 0.9 0.9 Inert Matter (Maximum) … … … … … … …… .. 0.9 0.9 1.0 Moisture Content (Maximum) … … … … ... …… 13.0 13.0 15.0 Germination (Minimum) … … … … … … …... 85 85 85 Objectionable Weed Seed (Maximum) … … … … …. …. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… …. …… …. …. 4 per kg. 4 per kg. 4 per kg. TABLE 2 Applicable to: (a) Barley – Hordeum vulgare L, H. distichon L. (b) Oat – Avena sativa L.A. nuda L. Standard Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … .. .. … 99.0 99.0 99.0 Total Seed other (Maximum) … … … … …. … … 0.1 0.1 0.1 Other Crop Seed (Maximum) … … … … … … 0.0 0.0 0.0 Inert Matter (Maximum) … … … … … ... …… 0.9 0.9 0.9 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg Moisture Content (Maximum) … … … … … … ... 13.0 13.0 15.0 Germination (Minimum) … … … … … …. .. 85 85 85 26 TABLE 3 Applicable to: Rice (Paddy) – Oryza sativa L. TABLE 4 Applicable to: Sorghum (includes hybrid sorghum) – Sorghum bicolor (L.) Moench Factor Class Basic Certified 1 Certified 2 % % Pure seed(maximum) 98.0 98.0 98.0 Other Seed (Maximum) … … … … …. …. … …. 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … ….. …. 11.0 11.0 11.0 Germination (Minimum) … … … … … …. …. ... 75 75 75 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg Factor Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … … … 80 80 80 Blast – Pyricularia oryzae (Maximum) 1.0 0.2 0.2 Bacterial Leaf Blight – Xanthomonas oryzae (Maximum) 1.0 2.0 2.0 White Tip Nematode – Alphelenchoides besseyi (maximum) 0.0 0.0 0.0 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg 27 TABLE 5 Applicable to: (a) Maize open-pollinated - Zea mays L . (b) Maize (hybrid) TABLE 6 Applicable to: Soybean – Glycine max. Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 14.0 14.0 14.0 Germination (Minimum) …. …. ….. ….. … … … 75 75 75 Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... 0.9 0.9 0.9 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … … … 90.0 90 90 Factor Class Basic Certified 1 % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 Inert Matter (Maximum) … … … … … 0.9 0.9 Moisture Content (Maximum) … … … … 13.0 13.0 Germination (Minimum) … … … … … 90 90 28 TABLE 7 Applicable to: Millet (a) Pearl Millet,– Pennisetum glaucum (L.) R. Br. Emend Stuntz Standard Class Basic Certified 1 Certified 2” % % % Pure Seeds (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 12.0 12.0 12.0 Germination (Minimum) … … … … … 75 75 75 (b) Finger Millet, – Eleusine carocana Factor Standards for each Class Basic Certified 1 Certified2”” % % % Pure Seeds (Minimum) … … … … … 97.0 97.0 97.0 Other Seed (Maximum) … … … … 0.2 0.2 0.2 Inert Matter (Maximum) … … … … … ... 2.8 2.8 2.8 Germination (Minimum) … … … … … 75 75 75 Objectionable Weed Seed (Maximum) … … .. ... … 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … ….. 4 per kg. 4 per kg 4 per kg 29 TABLE 8 Applicable to: (a) Alfalfa – Medicago sativa (b) White Clover, incl. Ladino – Trifolium repens (c) Glycine – Glycine javanica (d) Lance Crotalaria – Crotalaria lanceolata. (e) Showy Crotalaria – Crotalaria spectabilis (f) Slender Crotalaria – Crotalaria intermedia (g) Striate Clotalaria – Crotalaria mucronata var. striata (h) Sunn Crotalaria - Crotalaria juncea (i) Kudzu – Pueraria phaseloides (j) Lupines – Lupinus spp. (k) Seradella – Ornithopus sativus. (l) Tall Tick Clover (Kuru vine) – Desmodium spp. (m) Siratro – Phaseolus atropurpureus. Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … 98.0 98.0 97.0 Other Seed (Maximum) … … … … 0.2 0.2 0.2 Inert Matter (Maximum) … … … … 1.8 1.8 2.8 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … 50 50 50 TABLE 9 STANDARDS FOR EACH SEED CLASS Applicable to: Forage Crops and Grasses Percent Inert Matter Percent Weed Seeds Percent Pure Seeds Percent Germination Basic and Certified1 Certi fied 2 Basic and Certified 1 Certifi ed2 Basic and Certifi ed1 Certified 2 Basic, “Certified1” and Certified2 Pennisetum clandestinum 3.8 4.5 0.2 0.5 96.0 95.0 75 Rhodes Grass – Chloris gayana 34.8 39.5 0.2 0.5 65.0 60.0 65 Dolichos spp. … … … 9.8 11.5 0.2 0.5 90.0 88.0 75 Stylo – Stylosanthos gracilis 2.8 3.5 0.2 0.5 97.0 96.0 65 Hypanheris rhufa … 4.8 6.5 0.2 0.5 95.0 93.0 75 African foxtail grass – Cenchrus ciliaris 9.8 14.5 0.2 0.5 90.0 85.0 65 Teff Grass – Eragrostis teff 1.8 2.5 0.2 0.4 98.0 97.0 75 Sand Lovegrass – Eragrostis trichoide … … 1.8 2.5 0.2 0.5 98.0 97.0 75 Euchleana mecinana … 7.8 9.5 0.2 0.5 92.0 90.0 75 Digitaria smutsii … … 2.8 4.5 0.2 0.5 97.0 95.0 65 Eragrostis chloromelas 1.8 2.5 0.2 0.5 98.0 97.0 75 Weeping Lovegrass – 1.8 2.5 0.2 0.5 98.0 97.0 75 30 Eragrostis urvula Bothriochloa insulpta … 9.8 14.5 0.2 0.5 90.0 85.0 60 Guines Grass – Panicum maximum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Blue panicgrass – Panicum antidotale … 4.8 7.5 0.2 0.5 95.0 92.0 60 Green panicgrass – Panicum maximum var trichoglume 4.8 7.5 0.2 0.5 95.0 92.0 60 Panicum coloratum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Vine mesquite – Panicum obtusum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Switchgrass – Panicum virgatum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Melinis minufiflora … … 4.8 9.5 0.2 0.5 95.0 90.0 60 Pennisetum typhoida … 3.8 4.5 0.2 0.5 96.0 95.0 75 Setaria sphacelate … … 9.8 14.5 0.2 0.5 90.0 85.0 60 Setaria splendida … … 9.8 14.5 0.2 0.5 90.0 85.0 60 Columbus grass – Sorghum alum … 3.8 7.5 0.2 0.5 96.0 92.0 75 Napier grass – Pennisetum purpureum … … 3.8 4.5 0.2 0.5 96.0 95.0 75 Bermuda grass – Cynodon dactylon … 3.8 4.5 0.2 0.5 96.0 95.0 75 Themeda triandra … … 4.8 7.5 0.2 0.5 95.0 92.0 60 Lovegrass – Eragrostis superba … 1.8 2.5 0.2 0.5 98.0 97.0 75 Cynodon plectostachyus … … 3.8 4.5 0.2 0.5 96.0 95.0 75 Lovegrass – Brachiaria brizantha … 4.8 7.5 0.2 0.5 95.0 92.0 70 Trypsacum laxum … … 4.8 7.5 0.2 0.5 95.0 92.0 70 Brachiaria ruziziensis … 4.8 7.5 0.2 0.5 95.0 92.0 70 Centro – Centrosema pubescens … 1.8 2.5 0.2 0.5 98.0 97.0 65 Stylosanthes humilis… … 2.8 3.5 0.2 0.5 97.0 96.0 65 Stylosanthes mucronata … 2.8 3.5 0.2 0.5 97.0 96.0 65 Clitoria ternatea … … 3.8 5.5 0.2 0.5 96.0 94.0 65 Note: Other crop seed contents shall not exceed as follows:- For Basic and”Certified1” class … … … … … 0.5 For Certified 2 class … … … … 1.0 31 TABLE 10 Applicable to: (a) Sunflower – Helianthus annuus. (b) Safflower – Carthamus tinctorius. Factor Class Basic Certified1 Certified2 % % % Pure Seed (Minimum) … … … … … … 99.0 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … 0.9 0.9 0.9 Moisture Content (Maximum) … … … … 10.0 10.0 10.0 Germination (Minimum) … … … … … 85 85 85 TABLE 11 Applicable to mixture of forage seed of two or more of the seed listed in Table 8 and 9 of this Schedule. “Mixture” means each component present in excess of 5 per cent of the whole. Maximum number of seed per Kg. except where otherwise stated Minimum percentage germination Class Name Objectionable Restricted Weed seed Each ingredient % % Certified 1, Certified 2 .… … None 4 per kg 1.5 60 Note:- 1. Mixtures of grass seed not designated by the sender as lawn or turf grass mixtures shall be classified under this table. 2. Percentage purity and germination of each component in the order of predominance shall be stated on the seed label. TABLE 12 Applicable to: (a) Cotton – Gossypium spp. (b) Kenaf – Hibiscus cannabinus (c) Roselle – Hibiscus sabdariffa Factor Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 98.0 Total Weed Seed (Maximum) … … … … None 0.0 0.1 Other Crop Seeds (Maximum) … … … … 0.0 0.1 0.1 Inert Matter (Maximum) … … … … … 2.0 0.9 0.9 Objectionable Weed Seed (Maximum) … … None None None 32 Restricted Noxious Weed Seed (Maximum) … … None None 4 per kg Moisture Content (Maximum) … … … … … 10.0 10.0 10.0 Germination (Minimum) … … … 70 70 70 Bacteria Blight – Xanthomonas malvacearum (Maximum) 0.5 1.0 2.0 TABLE 13 Applicable to: (a) Groundnut – Arachis hypogaea (b) Bambara Nut – Voandzeia subterranea Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … 98.0 97.0 97.0 Other Seeds (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (shelled) (Maximum) … … … … 1.9 2.9 2.9 Moisture Content (Maximum)… … … … … … 12.0 12.0 12.0 Germination (minimum) … … … … … … 75 75 75 TABLE 14 Applicable to: (a) Sesame – Sesamum indicum Factor Class Basic Certified1 Certified2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 97.0 Total Weed Seed (Maximum) … … … … 0.1 0.2 0.3 Other Crop Seed (Maximum) … … … … 0.1 0.2 0.3 Inert Matter (Maximum) … … … … … … 1.9 2.9 2.8 Objectionable Weed Seed (Maximum) … … … None None None Restricted Noxious Weed Seed (Maximum) … … 4 per kg 4 per kg 4 per kg Moisture Content (Maximum)… … … … … 10.0 10.0 10.0 Germination (Minimum). ……… …… ……. … 80 80 80 (b) Tobacco – Nicotiana tabacu - Nicotiana rustica. Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … … 98.0 97.0 97.0 Other Seed (Maximum) … … … … 0.1 0.1 0.2 Inert Matter (Maximum) … … … … … 2.0 2.0 3.0 Moisture Content (Maximum)… … … … … 12.0 12.0 12.0 Germination (Minimum) … … 80 80 80 Anthracnose (Maximum) … … … … … None None None Angullar Leaf Spot – Pseudomonas angulata (Maximum)… None None None Frog-Eye or Green Spot – Cercospora nicotianae (Maximum) None None None Tobacco Mosaic Virus (Maximum) … … … … … None None None TABLE 15 33 Applicable to: (a) Bean, common – Phaseolus vulgaris (b) Bean, broad – Vicia faba (c) Bean, Lima – Phaseolus lunatis var. macrocarpus (d) Bean, runner – Phaseolus cocecineus (e) Chick pea – Cicer arietinum (f) Cowpea – Vigna unguiculata (g) Mung Bean – Phaseolus aureus (h) Banavist Bean – Dolichos lablab (i) Hyacinth Bean –Lablab niger (j) Sword Bean – Canavalia ensiformis (k) Blackgram – Phaseolus mungo (l) Greengram – Phaseolus aureus (m) Pigeon pea – Cajanus cajan (n) Pea – perennial – Lathyrus spp (o) Castor bean – Ricinus communis 34 Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 99.0 Other Seeds (Maximum) … … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … … 0.9 0.9 0.9 Moisture Content (Maximum)… … … … … … … 10.0 10.0 10.0 Germination (Minimum) … … … 80 80 80 Common Bacteria Blight – Xanthomonas phaseoli (Maximum None None None Anthracnose – Coletotrichum lindemunthianum (Maximum)… None None None Bean Common Mosaic Virus (B.C.M.V.) … … … 0.1 0.1 0.1 Halo Blight – Pseudomonas phaseoli … … … … 0.1 0.1 0.1 TABLE 16 A: Applicable to: Irish potatoes - Solanum tuberosum Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … 99.0 98.0 97.0 Soft rot – Sclerotium rolfsii 0.0 0.1 0.1 Dry rot – Fusarium wilt … … … … … 0.5 1.0 1.0 Common scab – Streptomyes scabies*coverage of tuber in 50kg bag 1.0 2.0 2.0 Black scurf - Rhizoctonia solani** 1.0 5.0 5.0 1. *Even if a single tuber in a lot is detected to have standard scab the entire seed lot shall be treated with the recommended chemical before declaring it fit for certification. Any Seeds lot having more than 5% scabbed tubers will not be certified even after treatment. 2. **A tuber is considered having black scurfed if 10% or more of its surface in scurfed. If more than 5% of the tubers are scurfed the total lot is rejected. Seeds lots carrying scurf, should be treated with recommended chemicals before being considered fit for certification purposes. Seed potato shall be classified into 3 sizes for the different/classes of seeds***. Measurements in mm Hill seed potato Plain seed potato Small **** 30-40 25-35 Medium 41-50 36-45 Large Above 51 Above 46 3. ***Size of the tuber will be decided on the basis of mean of two width of tuber at the middle and that of length. 4. **** In a seed lot tuber not conforming to specific size of seed should not be more than 5% by number. The seed material shall be reasonably clean, health, firm and shall conform to the characteristics of the variety, cut, bruised, misshaped, cracked tubers or those damaged by insects, slugs or worms shall not exceed 1% by weight; Tubers showing greenish pigment are best for seed purposes. Total number of diseased tubers shall not be more than 5% by number in each case. B: Applicable to: (a) Ginger – Zingiber officinalis (b) Cardamom – Elittaria cardamomum (c) Pyrethrum – Chysanthemum cinerarieafolium Factor Class 35 Basic Certified1 Certified2’ % % % Pure Living splits or cuttings (Minimum) … … … 98 98 97 Total Weeds (Maximum) … … … … … None None None Other Living Plants (Maximum) … … … … 1.0 1.0 2.0 Germination (Minimum) … … … … … 95 95 95 Bacterial Fascial – Corynebacterium fascians … … 2.0 2.0 2.0 Bright Gray Mold – Botrytis cinerea … … … 2.0 2.0 2.0 Damping off – Gloesporium spp … … … … 2.0 2.0 2.0 Root Rot – Pythium spp 2.0 2.0 2.0 Phymatotrichum omnivorum (Text) or Rhizoctonia solani 2.0 2.0 2.0 Stem Rot – Sclerotinia screlerotiorum … … … … 2.0 2.0 2.0 Aster Yellow – Chlorogenus callistephi … … … 2.0 2.0 2.0 Leaf Nematode – Alphelenchoides ritzema – bosi … None None None Root Knot Nematode – Meloidogyne hapla … … None None None C: Applicable to: Cassava Manihot utilisima Sweet potato Ipomea batatas Factor Class Basic Certified1 Certified 2 % % % Other varieties (Maximum)… … … … 0.1 0.2 0.2 Storage rot… … … … … …. … … …… None None None Black rot - Ceratocystis fumbriata … … … … … None None None Pure living cutting (Minimum)… … … … … 95 95 95 Scurf - Monilochaetes unfuscans … … … … … None 0.1 0.1 Wilt (vascular wilt) - Fusarium oxysporum… … … None 0.1 0.1 Nematode … … … … … … … … …… 0.2 0.5 0.5 Wire worm … … … … … … … … … … 1 5 5 Sweet potato weevil - Cylasfor micarius … … None None None Foot rot – Plenodomus destruens … … …. …. …… …. None None None Leaf spot - Ercospora bataticala… …. ….. …… ….. …. None None None Soft rot - Rhizopus stoloniferi… … … … … …. .. None None None Cassava mealybug … … … … … …. …. …. None None None Cassava mosaic … ….. ….. …… … …. …. …… …. None None None TABLE 17 Applicable to: Onion Sets and Multiplier Onions (including Garlic). 1 2 3 4 Class Name Size in diameter Purity General Quality 1. Standard seeds 10 – 20 mm 98 per cent Mature, well cured sound, free from decay and dry, free from tops, dirt leaves, free from other foreign matter, disease, moulds, insect, mechanical, frost damage, sprouted and soft bulbs when classified. Note: The size standards under Column 2 do not apply to multiplier onions, 36 2. Onion sets may be labeled “pin-head” onion sets when they conform to the standards specified in this table and when the diameter of the sets is not more than 20 mm”. 3. The following are the generally accepted identification and distinction between onion sets and onion multipliers. Onion sets: (Allium cepa) small bulbs or “sets” grown from Seeds used to plant for the production of mature onions. Since A. cepa is perennial, in the temperate zone, the sets are produced one season for planting in the next season. They are in practical sense just very small onions. Onion multipliers: (A. cepa, var: varagratum). The example variety produces branching at the base of the bulb which, when divided, can be used as propagating material for planting. The practical example in Tanzania is the Spring onion. In the general Allium there are at least four basic means of propagation: Seeds, Cloves, Topsets, and Multipliers. Seeds: to produce mature onions, or for the production of transplants or sets. (Allium cepa). Bulb segments or cloves: (A. sativum) – Garlic. The separation of segments of the garlic bulb provides the usual propagation material. Seldom is garlic Seeds used. Top sets are the small bulb-like planting material produced in the flower cluster, sometimes in conjunction with Seeds. (A. cepa, var. vivaparum). Multipliers are the division of the branching at the base of the crown, which are used for propagation. (A cepa, var; aggregatum) Spring onions. 37 TABLE 18 Applicable to: Vegetable Crops. MINIMUM STANDARDS APPLICABLE TO SEED CLASSSES 1. Objectionable Weed Seed: None 2. Restricted Noxious Weed Seed: Maximum allowed shall be 4 Seed per kg 3. Total Weed Seed: The maximum by weight shall not exceed 1 per cent. Purity (Minimum) Germination (Minimum) % % African Cabbage… … … … … … … … … 98.0 70 African Eggplant… … … … … … … … … 98.0 70 Amaranths… … … … … … … … … … 95.0 70 Beans (all types) … … … … … … … … … 98.0 80 Beet (Incl. Swiss chard) … … … … … … … 98.0 65 Broccoli … … … … … … … … … … 98.0 75 Brussels Sprouts … … … … … … … … … 98.0 80 Cabbage … … … … … … … … … … 98.0 80 Carrot … … … … … … … … … … 98.0 60 Cauliflower… … … … … … … … … … 98.0 70 Celery … … … … … … … … … … … 99.0 60 Cucumber … … … … … … … … … … 98.0 70 Eggplant … … … … … … … … … … 98.0 70 Kale … … … … … … … … … … … 98.0 70 Kohlrabi … … … … … … … … … … 98.0 80 Leek … … … … … … … … … … 98.0 70 Lettuce … … … … … … … … … … 98.0 75 Marrow … … … … … … … … … … 98.0 75 Muskmelon … … … … … … … … … 98.0 75 Nightshade… … … … … … … … … … 98.0 60 Okra … … … … … … … … … … 98.0 70 Onion … … … … … … … … … … 98.0 70 Parsley … … … … … … … … … … 98.0 70 Parsnip … … … … … … … … … … 98.0 60 Peas … … … … … … … … … … … 99.0 80 Pepper … … … … … … … … … … 98.0 60 Pumpkin … … … … … … … … … … 99.0 60 Radish … … … … … … … … … … 98.0 70 Spinach … … … … … … … … … … 98.0 60 Squash … … … … … … … … … … 99.0 75 Sweet Corn … … … … … … … … … 98.0 80 Tomato … … … … … … … … … … 98.0 75 Turnip … … … … … … … … … … 98.0 70 Watermelon … … … … … … … … … 98.0 60 38 TABLE 19 Applicable to: Standard seed 1. Objectionable Weed Seed: None 2. Restricted Noxious Weed Seed: Maximum allowed shall be 10 Seed per kg 3. Total Weed Seed: The maximum by weight shall not exceed 1.5 per cent. 4. Minimum Seeds Standards shall be as follows:- Minimum Purity Minimum Germination % % A. CEREAL CROPS: Maize (open pollinated) … … … … … … 95.0 80 Wheat … … … … … … … … … … 95.0 80 Sorghum… … … … … … … … … … 95.0 65 Rice … … … … … … … … … … 95.0 70 Oats … … … … … … … … … … 95.0 80 Barley … … … … … … … … … … 95.0 80 Millet … … … … … … … … … … 95.0 65 B. GRAIN LEGUME AND PULSES: . Cow peas … … … … … … … … … 97.0 70 Bean, Mung … … … … … … … … … 97.0 70 Bean, Broad … … … … … … … … … 97.0 70 Bean, Banavist … … … … … … … … 97.0 70 Bean, Hyacinth … … … … … … … … 97.0 70 Bean, Sword … … … … … … … … … 97.0 70 Bean – Other s … … … … … … … … 97.0 70 Pigeon Pea … … … … … … … … … 97.0 70 Pea – Lathyrus spp. … … … … … … … 97.0 70 Pea – Field and Garden … … … … … … … 97.0 70 Bambara Nut … … … … … … … … ... 97.0 70 Greengram … … … … … … … … … 97.0 70 Blackgram … … … … … … … … … 97.0 70 Chickpea … … … … … … … … … 97.0 70 Lentil … … … … … … … … … 97.0 70 Lupines … … … … … … … … … 95.0 70 Minimum Purity Minimum Germination % % C. OIL CROPS: Soybean … … … … … … … … … 97.0 70 Groundnut … … … … … … … … … 97.0 70 Sesame… … … … … … … … … … 95.0 70 Sunflower … … … … … … … … … 95.0 65 Safflower … … … … … … … … … 95.0 65 Castor Bean … … … … … … … … … 97.0 75 Rape … … … … … … … … … 95.0 65 LinSeeds … … … … … … … … … 95.0 65 Cashew Nuts … … … … … … … … … 99.0 80 Macadamia Nuts… … … … … … … … … 99.0 80 Coconuts … … … … … … … … … 99.0 80 Oil Palm … … … … … … … … … 98.0 80 Dram Stick … … … … … … … … … 98.0 80 D. FIBRE CROPS: Cotton … … … … … … … … … 95.0 75 Kenaf … … … … … … … … … 95.0 75 Roselle… … … … … … … … … … 95.0 75 E. DRUG/STIMULANT CROPS: Pyrethrum … … … … … … … … … 97.0 85 39 Tobacco …… … … … … … … … ... Coffee … … … … … … … … … ….. Tea … … … … … … … … …. …. ….. .. 97.0 99.0 97.0 75 80 75 F. VEGETABLE CROPS: Tomato … … … … … … … … … 97.0 70 African Cabbage… … … … … … … … 97.0 70 African Eggplant… … … … … … … … 97.0 70 Amaranths… … … … … … … … … 95.0 70 Nightshade… … … … … … … … … .. 97.0 60 Onion … … … … … … … … … … 97.0 60 Eggplant … … … … … … … … … 97.0 65 Okra … … … … … … … … … 97.0 70 Cabbage … … … … … … … … … 95.0 75 Cauliflower … … … … … … … … … 95.0 75 Collards… … … … … … … … … 95.0 75 Broccoli… … … … … … … … … 95.0 75 Brussels Sprout … … … … … … … … 95.0 75 Pepper … … … … … … … … … … 97.0 55 Celery … … … … … … … … … … 95.0 50 Cucumber … … … … … … … … … 95.0 70 Squash, Pumpkin … … … … … … … … 95.0 70 Spinach … … … … … … … … … 95.0 55 Carrot … … … … … … … … … 95.0 55 Turnip … … … … … … … … … 95.0 75 Watermelon … … … … … … … … 95.0 60 Muskmelon … … … … … … … … 95.0 60 Radish (including beet) … … … … … … 95.0 65 Swiss Chard … … … … … … … … … 95.0 60 G. FRUIT CROPS Sweet Oranges – Citrus sinensis 98.0 80 Mandarine - C. reticulata 98.0 80 Lemon - C. limon 98.0 80 Lime - C. aurantifolia 98.0 80 Grapefruit - C. paradisi 98.0 80 Pummelo - C. grandis 98.0 80 Peaches - Prunus persica 98.0 75 Plums - P. domestica 98.0 75 Apricot - P. armenica 98.0 75 Custard Apple - Annona reticulata 98.0 80 Sweetsop A. squamosa 98.0 80 Mango - Mangifera indica 99.0 75 Avocado - Persea americana 99.0 80 Guava - Psidium guajava 97.0 75 Pineapple - Ananas comosus 98.0 70 Banana - Musa spp. 98.0 95 Apple - Malus sylvestris 98.0 90 Pears - Pyrus communis 98.0 90 Grapes - Vitis vinifera 98.0 90 Papaya - Carica papaya 95.0 70 Passion Fruit - Passiflora edulis 97.0 70 Jackfruit - Artocarpus heterophyllus 95.0 70 Breadfruit - A. altilis 95.0 70 Kumquat - Fortunella japonica 97.0 75 Litchi/Lychee - Litchi chinensis 95.0 70 Longan - Euphoria longana 90.0 70 Loquat - Eriobotrya japonica 90.0 70 Pomegranate – Punica granatum 95.0 80 Raspberry - Rubus spp. 95.0 80 Rose Apple - Syzygium jambos 95.0 80 Tree Tomato - Cyphomandra betacea 98.0 70 Tamarind - Tamarindus indica 98.0 70 Straw Berry - Fragaria ananassa 95.0 80 40 Carambora - Averrhoa carambola 90.0 70 Fig - Ficus spp. 95.0 70 H. GRASSES,FORAGE AND GREEN MANURE CROPS : African Foxtail Grass – Cenchrus ciliaris … … … 80.0 50 Centro – Centrsema pubescens … … … … … 950 50 Columbus Grass – Sorghum almum … … … … … 95.0 70 Guinea Grass – Panicum maximum … … … … … 90.0 50 Kuru vine – Desmodium intatum … … … … … 95.0 50 . Rhode Grass – Chloris gayana … … … … … 60.0 50 Siratro – Phaseolus atropurpureus … … … … 95.0 50 Stylo – Stylosanthes gayanensis … … … … … 95.0 50 Lance Crotalaria – Crotalaria lanceolata … … … … 95.0 70 Striate Crotalaria - Crotalaria mucronate var, Striata … 95.0 70 Showy Crotalaria – Crotalaria spectabilis … … … 95.0 70 Kudzu – Pueraria phaseoloides … … … … … 95.0 50 Teff Grass – Eragrostis teff … … … … … 95.0 50 Weeping – Eragrostis teff … … … … … … 95.0 50 Pennisetum clandestinum … … … … … … 95.0 60 Dolichos spp… … … ... … … … … … 85.0 60 Hyparenia rufa … … … … … … … … 90.0 50 Sand Lovegrass – Eragrostis trichoides … … 90.0 50 Euchleana mecinana … … … … … … … 90.0 50 Digitaria smutsii … … … … … … … 90.0 50 Eragrostis chloromelas … … … … … … … 90.0 50 Bothriochloa insulpta … … … … … … … 80.0 50 Blue panicgrass – Panicum antidotale … … … 90.0 50 Green Panicgrass – Panicum maximum var. trichoglume … 90.0 50 Panicum coloratum … … … … … … … 85.0 40 Vine Mesquite – Panicum obtusum … … … … ... 80.0 50 Switchgrass – Pancicum virgatum … … … … 85.0 50 Melinis minufiflora … … … … … … … .. . 85.0 50 Pennisetum typhoides … … … … … … 95.0 50 Setaria sphacelate … … … … … … … 80.0 50 Setaria splendida … … … … … … … 85.0 50 Napier Grass – Pennisetum purpureum … … … … 90.0 50 Bermuda Grass – Cynodon dactylon … … … … … 90.0 50 Cyndon plectostachyus … … … … … … … 90.0 50 Themeda triandra … … … … … … … 90.0 50 Lovegrass – Eragrostis superba … … … … 90.0 50 Brachiaria brizantha … … … … … … … 90.0 50 Trypsacum laxum … … … … … … … 90.0 50 Brachiaria ruziziensis … … … … … … … 90.0 50 Stylosanthes humilis … … … … … … … 90.0 50 Clitoria ternatea … … … … … … … … 90.0 50 Alfafa – Medicago sativa … … … … … … 95.0 70 Glycine – Glycine favanica … … … … … … 95.0 60 Lupine spp. … … … … … … … … … 95.0 70 White Clover incl. Ladino – Trifolium repens … … 95.0 70 Serradella – Ornithopus sativus … … … … … 95.0 70 Slender Leaf Crotalaria – Crotalaris intermedia … … 95.0 70 Sunn Crotalaria – Crotalaria juncea … … … … … 95.0 70 TABLE 20 CERTIFIED TREE AND SHRUB SEED Basic Seed of tree shall be Seed from trees of proven genetic superiority as defined under the Act and Rules made by the Minister under Regulation 26 (4) herein. (a) “Certified 1” tree and shrub Seed shall be the Seeds progeny grown from basic tree or trees and shrubs. 41 (b) “Certified 2” Seeds shall be the Seeds progeny grown from either “Certified1” or basic tree Seed. 42 PART II: FIELD STANDARDS TABLE 1 Applicable to: (a) Wheat including hybrid – Triticum aestivum L. (b) Wheat durum – Triticum durum Desf. (c) Barley – Hodeum vulgare L.H. distichon (d) Oats – Avena sativa L., A. nuda L. Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… … 2 2 2 Off- type (count in 100m2)… … … … …. ….. 1 6 6 Other crop (inseparable) (%) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … … …… 0 0 0 Diseases – (number per 100m2) - Kernel Bunt (plant) …. - Loose smut (plant) ….. - Ear cockle (percentage).... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 TABLE 2 Applicable to: Lowland Rice (Paddy) – Oryza sativa Factor Class Basic Certified1 Certified2 Land (seasons before) … … … …… … … 2 2 2 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… … 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.1 0.1 Other Crop (inseparable) (%) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … …… … 0 0 0 Red rice / Wild rice (%)… … … … …… … 0 0.1 0.1 Diseases – (number per 100m2) – Rice Blast (plant) …. - Bacterial leaf blight (plant) ….. - White tip Nematode (percentage) .... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 43 TABLE 3 Applicable to: Upland Rice (Paddy) – Oryza sativa Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.1 0.1 Other Crop (inseparable) (%.) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … … …… 0 0 0 Diseases – (number per 100m2) – Rice Blast (plant) …. - Bacterial leaf blight (plant) ….. - White tip Nematode (percentage).... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 TABLE 4 Applicable to: Sorghum (includes hybrid sorghum) – Sorghum bicolor (L.) Moench Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … …… … 2 2 2 Isolation (m) … … … …… … …… 400 200 200 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.0 0.5 0.5 Diseases -Bunt 1/1000plants 2/1000plants 2/1000plants -Mildew 1/1000plants 2/1000plants 2/1000plants -Ergot 0 0 0 -Head/covered smut 1/1000plants /2/1000plants 2/1000plants -Kernel smut 1/1000plants 2/1000plants 2/1000plants 44 TABLE 5 Applicable to: (a) Maize open-pollinated - Zea mays L. Factor Class Basic Certified1 Certifie2” Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 400 200 200 No. of inspection (minimum)… … … … …… 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 0.5 0.5 (b) Maize (hybrid) Factor Cross Class Certified1 Land (seasons before) ……. … … … …… … 1 1 Isolation (m) … … … …… … …… …. 400 200 No. of inspection (minimum) … … … …… ….. 5 3 Seeds parent shedding pollen (Selfing) (%) … … …. 0 1 Silk of first pollen control inspection (%)…. ….. … … … 2 2 Seeds parent at any one inspection (%)….. …. …. ….. … 0.5 Seeds parent at any three inspections (%)…. …. ….. … … 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0 0.1 TABLE 6 Applicable to: Soybean – Glycine max. Factor Basic Certified1 Certified2 Land (seasons before) … … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 5 4 4 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 1.0 1.0 Diseases – (number per 100 m2) – Soya Bean Mosaic….. ….. …. … ….. ... Bacterial Pustule (plant) ….. ….. …. … ….. Bacterial Blight (percentage) ….. ….. …. … Leaf spot (plants) ….. ….. …. … ….. ….. Anthracnose (plants) ….. ….. …. … ….. …. Charcoal rot (plant) ….. ….. …. … ….. … 0 1.0 2 0 0 0 0 0 0 1 2 2 1 2 2 1 2 2 45 TABLE 7 Applicable to: Millet (a) Millet, pearl – Pennisetum glaucum (L.) R. Br. Emend Stuntz Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 500 300 300 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.5 1.0 1.0 Diseases – (%) – Green ear…. … ... …. … - Ergot (plant) ….. … …. - Green smut (percentage) 0.05 0.1 0.1 0.02 0.05 0.05 0.05 0.1 0.1 (b) Millet, Finger – Eleusine carocana Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 25 10 10 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.05 0.1 0.1 TABLE 8 Applicable to: (n) Alfalfa – Medicago sativa (o) Clover, White, incl. Ladino – Trifolium repens (p) Glycine – Glycine javanica (q) Lance Crotalaria – Crotalaria lanceolata. (r) Showy Crotalaria – Crotalaria spectabilis (s) Slender Crotalaria – Crotalaria intermedia (t) Striate Clotalaria – Crotalaria mucronata var. striata (u) Sunn Crotalaria - Crotalaria juncea (v) Kudzu – Pueraria phaseloides (w) Lupines – Lupinus spp. (x) Seradella – Ornithopus sativus. (y) Tall Tick Clover (Kuru vine) – Desmodium spp. (z) Siratro – Phaseolus atropurpureus. Factor Basic Certified1 Certified2 % % % Land (seasons before) … … … … …… … … 2 1 1 Isolation (m) … … … …… … …… … 5 4 4 No. of inspection (minimum) … … … … …… …. 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 2.0 3.0 3.0 TABLE 9 STANDARDS FOR EACH SEED CLASS Applicable to: Forage Grasses and Crops Factor Basic Certified1 Certified2 46 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 400 200 200 No. of inspection (minimum) … … … … …… …. 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 2.0 3.0 3.0 TABLE 10 Applicable to: (a) Sunflower – Helianthus annuus. (b) Safflower – Carthamus tinctorius. Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 1700 1000 1000 No. of inspection (minimum) … … … … …. … 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 0.1 0.2 0.3 TABLE 11 Applicable to: (a) Cotton – Gossypium spp. (b) Kenaf – Hibiscus cannabinus (c) Roselle – Hibiscus sabdariffa Factor Class Basic Certified 1 Certified 2 Land (seasons before) … … … … … …… … 2 2 2 Isolation (m) (if contaminating source is of same species) ….. 200 100 100 Isolation (m) (if contaminating source is of different species) ….. ….. 450 300 300 No. of inspection (minimum) … … … … …… 3 3 3 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.02 0.05 Bacterial Blight (Minimum) ….. ….. …. …. …… ……… 0.5 1.0 2.0 47 TABLE 12 Applicable to: (a) Groundnut – Arachis hypogaea (b) Bambara Nut – Voandzeia subterranea Factor Class Basic Certified1 Certified2 Land (seasons before) . ……. …… ……. …… 1 1 1 Isolation (m) … …. … .. .. … … … … …. ….. …… 5 3 3 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … 0.1 0.5 0.5 TABLE 13 Applicable to: (a) Sesame – Sesamum indicum Factor Class Basic Certified1 Certified2 Land (seasons before) …. …… ……. …… … …. ….. 1 1 1 Isolation (m) ……. …… ……. …… … …. ….. 5 3 3 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … 0.2 0.5 0.5 (b) Tobacco – Nicotiana tabacum - Nicotiana rustica. Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … 1 1 1 Isolation (m) … … … …… … …… 100 50 50 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … none 0.05 0.1 TABLE 14 Applicable to: (a) Bean, Common – Phaseolus vulgaris (b) Bean, Broad – Vicia faba (c) Bean, Lima – Phaseolus lunatis var. macrocarpus (d) Bean, Runner – Phaseolus cocecineus (e) Chick Pea – Cicer arietinum (f) Cow Pea – Vigna unguiculata (L) walp. (g) Mung Bean – Phaseolus aureus (h) Banavist Bean – Dolichos lablab (i) Hyacinth Bean –Lablab niger (j) Sword Bean – Canavalia ensiformis (k) Blackgram –Phaseolus mungo (l) Greengram –Phaseolus aureus (m) Pigeon Pea – Cajanus cajan (n) Pea – perennial – Lathyrus spp (o) Castor Bean – Ricinus communis 48 Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 25 10 10 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 0.5 0.5 Diseases – (%) - Mosaic virus … …. ….. ….. …. … - Anthracnose ….. …. ….. ….. …. - Halo Blight .... …. ….. ….. …. … - Common Blight…. ….. ….. …. … 0.1 1.0 1.0 0.02 0.02 0.02 0.01 0.01 0.01 0.02 0.02 0.02 TABLE 15 A: Applicable to: Irish potatoes - Solanum tuberosum Factor Basic Certified 1 Certified2 Land (seasons before) … … … … … …… … … 5 3 3 Isolation (m) … … … …… … …… … 100 50 50 No. of inspection (minimum)… … … … …… 4 4 4 Off- type (number in 100 plants)… … … … …. 0 2 2 Diseases (%) Bacterial wilt …. …… … 0 0 0 Wart … ….. …. …. … …. 0 0 0 Golden Nematode …. 0 0 0 Ring rot ….. ….. …. … 0 0 0 Potato spindle … … … …. . 0 0 0 Mycoplasma… … … … 1:1000 1:100 1:100 Black leg …… …. …. . 0 0 0 Potato Virus Y …. …. ... 2 per 1000 plants 10 per 1000 plants 10 per 1000 plants Spindle Mottle Virus …… 13 per 100 plants 13 per 1000 plants 13 per 100 0plants Fusarium wilt …. … … 0 2 per 1000 plants 2 per 1000 plants Verticilium wilt ….. … .. 0 2 per 1000 plants 3 per 1000 plants 49 ___________ SECOND SCHEDULE ____________ (Made under Regulation 26(3)) ____________ SEED CLASSES Code Classes Seeds parents Colour of labels Pb Pre- basic Progeny of parent stock white with diagonal violet B Basic Progeny of certified pre- basic Seeds or certified pre- basic Seeds …. ….. ….. White C1 Cert.1st gen. Progeny of certified pre- basic Seeds or certified basic Seeds …. ….. ….. ….. … Blue C2 Cert. 2nd gen. Progeny of certified basic Seeds or certified 1st generation Seeds …. …. …. Red N.B: On authorization of the Minister, Standard seed may be labeled yellow and its code shall be Std. Seed THIRD SCHEDULE _____________ (Made under Regulation 36 (3)) _____________ (SAMPLE WEIGHTS FOR ALL CLASSES) Minimum weight for submitted sample (gm) Minimum weight for purity analysis(gm) Minimum weight for examination for other Seeds (gm) A CEREAL CROPS: Maize - Zea mays … … … … … … … 1,000 900 1,000 Wheat - Triticum aestivum … … … … 1,000 120 1,000 Wheat - Triticum durum … … … … … 1,000 120 1,000 Sorghum - Sorghum bicolor … … … … … 900 90 900 Rice - Oryza sativa … … … … … … … 700 70 700 Barley - Hordeum vulgare … … … … … 1,000 120 1,000 Millet- Eleusine carocana … … … … … 60 6 60 Oats - Avena sativa … … … … … … … 1,000 120 1,000 B GRAIN LEGUME AND PULSES: Cow peas- Vigna unguiculata … … … … … 1,000 400 1,000 -V. sinensis, V.catiag … … … 1,000 700 1,000 Field/ Common beans - Phaseolus vulgaris … … 1,000 700 1,000 Mung bean - Vigna aureus … … … … … 1,000 250 1,000 Phaseolus angularis … … … … … 1,000 400 1,000 Banavist beans - Dolichos lablab … … … 1,000 700 1,000 Hyacinth beans- Lablab niger … … … … 1,000 900 1,000 Sword beans - Canavalia ensiformis … … … 1,000 400 1,000 Pigeon pea - Cajanus cajan … … … … 1,000 300 1,000 Chickpea - Cicer arietinum … … … … 1,000 1,000 1,000 Broad beans - Vicia faba … … … … … 1,000 1000 1,000 50 Garden pea - Pisum sativum . … … … … 1000 900 1000 Bambara nut - Voandzeia subterranean … … 1,000 400 1,000 Greengram - Phaseolus aureus … … … 1,000 400 1,000 Blackgram - Phaseolus mungo … … … 1,000 700 1,000 C OIL CROPS: Soya beans - Glycine max … … … … … 1,000 500 1,000 Groundnut - Arachia hypogaea … … … … 1,000 1000 1,000 Sesame - Sesamum indicum … … … … … … 70 7 70 Sunflower - Helianthus annuus … … … … 1,000 200 1,000 Safflower - Carthamus tinctorius … … … … 900 90 900 Castor - Ricinus communis … … … … … 1,000 500 1,000 Cashew nuts – Anacardium occidentale 1,000 1,000 1,000 Macadamia nuts – Macadamia integrifolia … … … … . 1,000 1,000 1,000 Oil palm … … … … … … … …. … … …. … . 500 400 500 Coconuts …. … … … … … … … … … …. … … …. 20 15 20 Gram stick – Moringa oleifera…. … … … … … …... 200 150 200 D FIBRE CROPS: Cotton - Gossypium spp … … … … … 1,000 350 1,000 Kenaf - Hibiscus cannabinus … … … … … 700 70 700 Roselle - Hibiscus sabdariffa … … … … 700 70 700 E DRUG/STIMULANT CROPS: Pyrethrum - Chysanthemum cinerariaefolium … 100 10 100 Tobacco - Nicotiana tabacum … … … … 5 0.5 5 - Nicotiana rustica … … … … … 25 0.5 25 Coffee – Coffea spp. 1,000 400 1,000 Tea – Camellia sinensis Cocoa – Theobroma cacao … … … … …. … … …. 1,000 400 1,000 F VEGETABLE CROPS: African eggplant - Solanum macrocarpum… … … 15 7 10 Amaranth - Amaranthus spp. … … … … … 5 0.5 5 African cabbage – Brassica carinata… … … … 100 10 100 Nightshade - Solanum vilosum… … … … … 5 0.5 5 Tomato - Lycopersicon lycopersicum … … … 15 7 10 Onion - Allium cepa … … … … … 80 8 80 Egg plant - Solanum melongena … … … … … 150 15 150 Okra - Abelmoschus esculentus L. … … … 1,000 140 1,000 Cabbage - Brassica oleracea var. capitata … … … 100 10 100 Cauliflower - Brassica oleracea var. botrytis …. … 100 10 100 Sprouting brocoli -Brassica oleracea var. italica … ... 100 10 100 Brussels Sprout - Brassica oleracea var. germifera … 100 10 100 Chinese Cabbage - Brassica campestris sub-var. pekinensis … …… … … …. … 40 4 40 Chinese Cabbage Brassica campestris sub-var. chinensis … … … … … ….. …. …. …. 40 4 40 Pepper - Capsicum spp. … … … … … 150 15 150 Celery - Apium graveolens … … … … … … 25 2 25 Cucumber -Cucumis sativus… … … … … 150 70 150 Squash /Pumpkin -Cucurbita spp … … … … 1,000 700 1,000 Lettuce - Lectuca sativa … … … … … 30 3 30 Spinach - Spinach oleracea … … … … … … 250 25 250 Carrot - Daucus carota … … … … … 30 3 30 Turnip - Brassica campestris sub-var. rapa … … 70 7 70 Watermelon - Citrullus lanatus … … … … 1,000 250 1,000 Muskmelon - Cucumis melo … … … … … 150 15 150 Radish - Raphanus sativus … … … … … 300 30 300 Swiss chard - Beta vulgaris var, gilla … … … 500 50 500 51 G FRUIT CROPS Sweet oranges – Citrus sinensis 300 200 300 Mandarine - C. reticulata 300 200 300 Lemon - C. limon 300 200 300 Lime - C. aurantifolia 300 200 300 Grapefruit - C. paradisi 300 200 300 Pummelo - C. grandis 300 200 300 Peaches - Prunus persica 500 300 500 Plums - P. domestica 500 300 500 Apricot - P. armenica 500 300 500 Custard apple - Annona reticulata 300 200 300 Sweetsop A. squamosa 300 200 300 Mango - Mangifera indica 1,000 1,000 1,000 Avocado - Persea americana 1,000 1,000 1,000 Guava - Psidium guajava 200 200 200 Pineapple - Ananas comosus 10 (suckers) 10 (suckers) 10 (suckers) Banana - Musa spp. 10 (suckers) 10 (suckers) 10 (suckers) Apple - Malus sylvestris 30 (cuttings) 20 (cuttings) 30 (cuttings) Pears - Pyrus communis 30 (cuttings) 20 (cuttings) 30 (cuttings) Grapes - Vitis vinifera 30 (cuttings) 20 (cuttings) 30 (cuttings) Papaya - Carica papaya 300 300 300 Passion fruit - Passiflora edulis 200 200 200 Jackfruit - Artocarpus heterophyllus 500 300 500 Breadfruit - A. altilis 500 300 500 Kumquat - Fortunella japonica 500 200 500 Litchi/lychee - Litchi chinensis 20 (cuttings) 20 (cuttings) 20 (cuttings) Longan - Euphoria longana 20 (cuttings) 20 (cuttings) 20 (cuttings) Loquat - Eriobotrya japonica 20 (cuttings) 20 (cuttings) 20 (cuttings) Pomegranate – Punica granatum 300 200 300 Raspberry - Rubus spp. 20 (cuttings) 20 (cuttings) 20 (cuttings) Rose apple - Syzygium jambos 20 (cuttings) 20 (cuttings) 20 (cuttings) Tree tomato - Cyphomandra betacea 200 150 200 Tamarind - Tamarindus indica 200 150 200 Straw berry - Fragaria ananassa 30 (cuttings) 20 (cuttings) 30 (cuttings) Carambora - Averrhoa carambola 300 200 300 Fig - Ficus spp. 30 (cuttings) 20 (cuttings) 30 (cuttings) H GRASSES, FORAGE AND GREEN MANURE CROPS: Pennisetum clandestinum … … … … … 70 7 70 Desmodium spp. … … … … … … … 50 5 50 Glycine javanica … … … … … … … 250 20 200 Medicago sativa … … … … 50 5 55 Phaseolus atropurpure … … … … … … 75 7 75 Chloris gayana … … … … … … 25 1 20 Dolichos spp. … … … … … … … 75 7 75 Sylobanthas gracilis … … … … … … 25 5 25 Hyparenia rhufa … … … … … … 30 3 30 Cenchurus ciliaris … … … … … … 25 5 25 Eragrostis teff … … … … … … … 25 1 10 Eragrotis trichodes … … … … … … 25 1 10 Euchleana mecinana … … … … … … … 30 3 30 Digitoria smutsii … … … … … … … 25 2 20 Eragrostis chloromelas … … … … … 25 2 20 Eragrostics curvula … … … … … … 30 3 30 Bothriochloa insulpta … … … … … … 30 3 30 Panicum maximum … … … … … … … 25 2 20 Panicum antidotale … … … … … … 25 2 20 Panicum maximum va., trichoglume … … … 25 2 25 52 Panicum coloratum … … … … … … 25 2 25 Panicum obtusum … … … … … … 25 2 20 Panicum virgatum … … … … … … 30 3 30 Melinis minufilora … … … … … … 5 0.5 5 Lupinus spp. … … … … … … … 1,000 450 1,000 Pannisetum typhoides … … … … … … 60 6 60 Seteria splendida … … … … … … … 90 9 90 Seteria sphacelate … … … … … … 90 9 90 Sorghum alum … … … … … … 700 20 200 Pennisetum purpureum … … … … … … 60 6 60 Sorghum sudanense … … … … … … 250 25 250 Trifolium repens … … … … … … … 25 2 20 Ornithopusstivus spp. … … … … … … 90 9 90 Crotalaria intermedia … … … … … … 150 15 150 Crotalaria juncea … … … … … … … 700 70 700 Crotalaria lanceolata … … … … … … 70 7 70 Crotalaria mueronate … … … … … 150 15 150 Crotalaria spectabilis … … … … … … 350 35 350 Cynodon dactylon … … … … … … … 25 1 10 Themeda triandra … … … … … … … 25 2 25 Eragrostis superba … … … … … … 25 2 25 Cynodon plectostachyus … … … … … 25 1 10 Brachiaris brizantha … … … … … 30 3 30 Trysacum laxum … … … … … … 30 3 30 Brachiaria ruziziensis … … … … … … 30 3 30 Centrosema pubescens … … … … … 150 15 150 Pueraria phaseoloides … … … … … … 350 35 350 Stylosanthes humilis … … … … … 100 10 100 Stylosanthes mucronata … … … … … 50 5 50 Clitoria ternatea … … … … … … 100 10 100 H ROOT CROPS AND SPICES: Potato (Irish) - Solanum tuberosum.(no. of tubers) … 50 30 50 Garlic – Allium sativum(no. of sets)… … … … 50 20 50 Ginger – Zingiber officinalis(no. of rhizomes)… … 50 20 50 Cardamon –Elittalia cardamomum(gm) … … … 50 20 50 Cinnamon – Cinnamomum zeylanicum(cuttings)… … . 50 20 50 Cassava – Manihot esculentum (no. of cuttings) … 50 20 50 Sweet potatoes –Ipomea batatas (no. of vines) … 50 20 50 Yams – Dioscorea spp.(no. of tubers) 20 10 20 _________ FOURTH SCHEDULE ___________ (Made under Regulation 27 (8)) ____________ THE MINIMUM NUMBER OF PLANTS OR HEADS REQUIRED PER COUNT FOR EACH CROP ___________ S/no. Crop Number of counts required 1. Maize (hybrids/composite) … …. …. … …. 100 2. Sunflower castor… …. …. … … … … . 100 3. Beans and peas, cowpeas, groundnuts chickpeas and green gram … … .., …... 500 4. Sesame, groundnut, kenaf, cotton, okra, amaranths…. 500 53 5. Sorghum/millets… …. …. ….. … … . 1000 6. Wheat, rice, oats barley, critical … ….,. 2000 7. Peppers, eggplant, tomato … …………… 200 8. Cabbage, cauliflower … ………………… 200 9. Cucurbits… …. …. …… …. …. …… Almost every plant 10. Onions… …. …. …… …. …. …… ….. 2000 bulbs 54 ___________ FIFTH SCHEDULE ___________ (Made under regulation…..) ______________ APPLICATION FORMS/CERTIFICATES _____________ THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT (No. 18 of 2003) S/N………… Form SR I APPLICATION FOR RFGISTRATION AS A SEED DEALER (Made under Regulation 3(1)) (To be filled in Triplicate) To: Director for Crop Development Ministry of Agriculture, Food Security and Cooperatives P.O.Box 9192 DAR ES SALAAM. I/We hereby apply to be registered as seed dealer :- Name ………………………………………………………………………… Postal Address ……………………………………………………………….. Telephone Number ……………………………………………………….….. Email Address………………………………………………………………… Location of the premises …………………………………………….………. I/we wish to deal in (Please tick where applicable) ( i) Production (ii) Processing (iii) Importation (iv) Exportation (v) Distribution (vi) Sale * For a legal person like a company, please attach Memorandum/Articles of association/ registration certificate/ and or constitution _________________________________________________________________________________________________________ PART A: TO BE FILLED BY APPLICANTS WHO WISH TO PRODUCE/GROW SEED _________________________________________________________________________________________________________ 1. Mention class/class (s) of Seed to be produced: ……………………………………………………………………………………………… 2. What mode of production do you intend to use :- (fill where appropriate) (a) own land , hectares of production land ……………………………………………… Location:………………………………………….… (b) contract grower (c) give details of land and equipment:……………………………………………………………..………………………………….….....…..… 3. Provide number and qualification of the personnel who are conversant with Seeds production that are in your possession or possession of your contract grower ……………………………………………………………………………………………………………………….………….... 4. For how long have you been engaged in Seeds business?....................................................................................................................................... (attach business profile) 55 PART B: TO BE FILLED BY APPLICANTS WHO WISH TO PROCESS SEED 1. Do you have adequate equipments and machinery to process Seed? Yes /No If “ YES” provide the list and capacity of each equipment/machinery :………………………………………………………………………… 2. Are equipment/machinery own or hired?.................................................................................................................................................................. 3. Describe your storage facilities: …………………………………………………………………………………………………………………… 4. Do you have a capacity to mark or label packets /containers as required by Seed Regulations? Yes /No 5. Do you have adequate and knowledgeable personnel who are conversant with Seeds processing and storage? Yes/No. if “YES”, provide number and qualification of the said personnel ………………………………………………………………………………………………………………………………………………………….. ………………………………………………………………………………………………………………………………………………………….. ………………………………………………………………………………………………………………………………………………………….. _____________________________________________________________________________________________________________________ PART C: TO BE FILLED BY APPLICANTS WHO WISH TO IMPORT/ EXPORT SEED _____________________________________________________________________________________________________________________ 1. Mention class/class (s) of Seed to be imported/exported: ……………………… ……………………………………………………………… 2. Do you have adequate and knowledgeable personnel who are conversant with Seeds matters? Yes/No. if “YES”, provide number and qualification of the said personnel:…………………………………………………………………...…………………… 3. What is estimated tonnage of Seed to be imported/exported annually:…………………………………………………………………………… 4. Where are proposed sources for import/ export:…………………………………………………………………………………………………... 5. Describe your storage facilities:………………………………………………………………………….……………………………...………… _____________________________________________________________________________________________________________________ PART D: TO BE FILLED BY APPLICANTS WHO WISH TO SELL/DISTRIBUTE SEED _____________________________________________________________________________________________________________________ 1 What are your distribution centres in the country………………………………………………………………………………………………… 2 Do you have enough storage facilities? YES/ NO. If “YES” state their capacity and conditions…………………………………………….… 3 Do you have any agreements with agents or stockist to distribute Seed on your behalf ? YES/ NO . 4 If you have agents or stockist, do they have any identity to recognize them? YES/ NO if “YES” state their identity. ……………………………………………………………………………………………………………………………………………...… 5 Do your agents or stockist have any knowledge on Seeds business YES/ NO . 6 How will you ensure that your agents or stockist comply with the Seeds law?....................................................................................................... ……………………………………………………………………………………………………………………………………………………. _____________________________________________________________________________________________________________________ PART E: TO BE FILLED BY SEED STOCKIST _____________________________________________________________________________________________________________________ 1. location of shop …………………………………………village/street…………………………………………ward/town……………….…… 2. Do you have any agreements with any seed dealer to distribute seed on his behalf ? YES/ NO ………………………………………………... 3. if the answer in 2 is “YES”, mention them ……………………………………………………………,………………………………………… 4. If you have any identity ? YES/ NO if “YES” state the identity. ………………………………………………………………………………... 5. Do you have enough storage facilities? YES/ NO. If “YES” state their capacity and conditions?........................................................................ ………………………………………………………………………………………………………………………………………………………… …………………………………………………………………………………………………………………… 56 Declaration : I/We declare that all information provided herein above is true to the best of my/ our knowledge. Signed at……………………………………this…………..day of…………………20…… Signature:………………………………………………………………. _____________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY _______________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………..…………………… Fees Receipt No: …………………………………………………………………………………………………………………………………….. Date Approved/Rejected: …………………………………………………………………………………………………………..………………… If approved: Reg No.…………………........................................................................................................................................................................ If rejection, reasons for rejection….………………….................................................................................................................................................. Dated:……………………………….Signature of the responsible officer:………………………………...…………………………………………… 57 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR II Registration No. ………… CEERTIFICATE OF REGISTRATION AS SEEDS DEALER ( Made under Regulation 3(3)) This is to certify that……………………………………………………………………… of………………………………...……………………… (Name and address of Registrant ) has been registered as Seeds producer/processor/importer/exporter/ distributor ( delete where applicable) for category of……………………….. …………………………………………………………………………………………………………………………………………………………. (state of crop and class) his farm /premises for business is located at ……………………………………………………………………………………………………….…. (village/ town/district/ region) This registration shall be valid for the period of ……………………from………………………to …………………………and may be cancelled if the registrant fails to comply with terms and conditions for registration as set out in the Seeds Act, 2003 and Regulations made thereto. Issued at …………………………this………….day of …………………….200………. Signature:………………………………………………………….. Director of Crop Development. 58 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IIIA ______________ APPLICATION FOR DUS TEST ______________ (Made under Regulation 7(1)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute 1. Full name of the Applicant/Pre- basic: ………………………………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3. Tel. No. ……………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………………. 5.Name of the crop ………………………………………………………….6. Botanical Name:……………………………………………………... 7. Family Name:……………………………………………………………...8. Chromosome Number………………………………………………. 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:……………………………………………………………………………………………………………………………. 11.Name under which it is tested:………………………………………………………………………………………………………………………. 12. Proposed elevation:…………………………………………………………………………………………………………………………………. 13.Major distinguishing merits from other released varieties:……………………………………………………………………………………… 14. Variety descriptor attached/Not attached (cross where necessary) 15. Test fee paid by………………………………………P.O.BOX…………………………………………………………………..…………… Dated:……………………………………………………….Signed:………………………………………………………………....………………… ______________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY: ______________________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………………………………. Fees Receipt No: …………………………..…………………………………………………………………………………………………………… Amount of sample received for DUS test : first season:…………………………………………………second season…………………………….… Date Approved/Rejected: ………………………………………………………………………………………………………………………………. If rejection, reasons for rejection. …………………........................................................................................................................................................ Dated:……………………………….Signature of the responsible officer:……………………………………………………….…………………… 59 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IIIB ______________ APPLICATION FOR NATIONAL PERFORMANCE TRIAL ______________ (Made under Regulation 4(1)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute. 1. Full name of the Applicant: ………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3.Tel. No. ………………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………………. 5.Name of crop ………………………………………………………….…………………………………………………………………..………. 6. Botanical Name:…………………………………………………….. ……………………………………………………………………….……… 7. Family Name:……………………………………………………………... ………………………………………………………………………… 8. Chromosome Number……………………………………………….……………………………………………………………………………….. 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:………………………………………………………………………………………………………………..…………… 11. Proposed Name:……………………………………………………………………………………………………………………... ..…………… 12.Name under which it is tested:………………………………………………………………………………………………………. ..……………. 13. Agency responsible for development :……………………………………………………………………………………………… ..…………… 14.Cutivar Pedigree:…………………………………………………………………………………………………………………… ..…………….. 15. proposed area for release:………………………………………………………………………………………………………… ..…………….... 16.Proposed elevation:………………………………………………………………………………………………………………… ..……………... 17. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………. ..………… 18. Agency responsible for maintenance:………………………………………………… ..…………….……………………… ..……………. ..….. 19. Distinguishing characteristics (describe fully) (a)growth habit:………………………………..(b) leaf:…………………………………..(c) stem:………………………..……………………… (d) flower:……………………………………...(e) pods:…………………………………………………………………………………………... (f) Seeds:………………………………………...(g) Seed size:…………………………………………………………………………………..… (h)Seeds shape and colour:……………………...(i) time to flowering:…………………… (j) growth habit:…………………………………...... (k) others: ………………………………………………………………. 20. Major distinguishing merits from other released varieties:……………………………………………………………………………………... 21.Points of merits, drought tolerance, disease resistance, lodging resistance, etc…………………………………………………………………….. 22.Economical and quality attributes:…………………………………………………………………………………………………………………… 23.Agronomic characters (optimal):……………………………………………………………………………………………………........................ (a) Sowing date:………………………………………………..(b) Seeds rates:……………………...……...……………………………………... (c) Plant population :………………………………………….(d) Maturity:………………………………...........................................................… (e) Fertilizer:…………………………………………………...(f) Crop height:………………………..................................................................... (g) Irrigation need :…………………………………………………….……………..................................…………………………...…………….. (h Consumer acceptability :…………………………(i) Others:……………...……………………………………………………………………... 24. Yield data/comparison/trial (Attach) (a) Yield compared to check:……………………………………..(b) Yield in farmers field:………………………………………………………… 25. Name and address of Pre- basic if deferent from the Applicant…...…………………………………….................................................................. I/We certify that the information given above is correct to the best of my/our knowledge. I/We hereby enclose a cheque for:…………………………………………………………………………..being the payment of the application fee. 60 Date: ………………………………………… Signature: ………………………………………………………………………………………………..… * ______________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY ______________________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………………………………. Fees Receipt No: ………………………….. Advanced yield trial data (Accepted/Not accepted)………………………………….….. Amount of sample received:…………………………………………………………... Date Approved/Rejected: …………………………...……… If rejection, reasons for rejection. …………………........................................................................................................................................................ I………………………………… …………title………… …………………,certify that the information given above is correct to the best of my knowledge using the information and scientific data available to me. Date: ……………………………………………… Signature: …………………………………………………………………… 61 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IV ______________ CERTIFICATE FOR DISTINCTINESS,UNIFORMITY AND STABILITY TEST ______________ (Made under Regulation .7(3) This is to certify that the candidate variety whose particulars referred herein has been passed test for Distinctness, Uniformity and Stability (DUS) Name / number under which it was tested: …………………………………………………………………………….….. Plant species: ……………………………………………………………………………………………………….………. Botanical Name: ……………………………………………………………………………………….………………….... Name and Address of Applicant/ Certificate holder …………………………………………………………………….…. Certificate Number. ………………………………………………………………………………………….……………. Issued this……………………day of …………………………………………………200……. Signature & stamp: ……………………………………………. Chief Seed Certification Officer 62 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR V ______________ RE: RECOMMENDATION FOR THE RELEASE OF NEW VARIETY ______________ (Made under Regulation 7(7)) (To be filled in Triplicate) To: National Variety Release Committee This is to notify that the variety whose particulars set herein below had been submitted for NPT this ………………day of…………………….200………… The review of application was conducted by NPT- TC on ……………………day of…………………….200………… 1. Full name of the Applicant/Pre- basic: ………………………………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3.Tel. No. …………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………… 5.Name of crop ………………………………………………………….…………………………………………………………………..…… 6. Botanical Name:…………………………………………………….. ……………………………………………………………………….……… 7. Family Name:……………………………………………………………... …………………………………………………………………… 8. Chromosome Number……………………………………………….………………………………………………………………………… 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:…………………………………………………Pre- basic………………………………………………………………...... 11. Proposed Name:…………………………………………………………………………………………………………………...………………... 12.Name under which it is tested:………………………………………………………………………………………………………………… 13. Agency responsible for development:……………………………………………………………………………………………… ..……… 14. Cutivar pedigree:…………………………………………………………………………………………………………………… ..……… 15. Proposed area for release:…………………………………………………………………………………………………………………….. 16.Proposed elevation:………………………………………………………………………………………………………………… ..……………... 17. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………. ..……………. 18. Agency responsible for maintenance:………………………………………………… ..…………….……………………… ..……………. ..….. 19. Distinguishing characteristics (describe fully) (a) growth habit:……………………………….(b) leaf:………………………….(c) Stem:……………………………………………………... (d) flower:……………………………………...(e) pods:…………………………………………………………………………………………... (f) Seeds:………………………………………...(g) Seeds 63 size:…………………………………………………………………………………… (h) Seeds shape and colour:……………………...(i) time to flowering:………………………………………………………………………… 20. Major distinguishing characters from other released varieties:…………………………………………………………………………………….. 21.Points of merits, drought tolerance, disease resistance, lodging resistance, etc…………………………………………………………………….. 22.Economical and quality attributes:………………………………………………………………………………………………………………...… 23.Agronomic characters (optimal):……………………………………………………………………………………………………....................... (a) Sowing date:………………………………………………..(b) Seeds rates:……………………...……...………………………………….…... (c) Plant population :………………………………………….(d) maturity:………………………………...........................................................… (e) Fertilizer:…………………………………………………...(f) plant height:………………………..................................................................... (g) Irrigation need :……………………………………………………..……………..................................…………………………...……………. (h) Consumer acceptability :…………………………( i) Others:……………...……………………………………………………………………. 25. Yield data/comparison/trial (a)Yield compared to check:…………………………(b) Yield in farmers field :……………………….………… 26. Any other information:……………………………………………………………………........................................................................................ The following are the results of NPT:- 1: Mode of Pollination:…………………………………………………………………………………………………………………………………. 2. Proposed Name:………………………………………… 3.Name under which it is tested:………………………………………………………... 4. Agency responsible for development: ……………………………………………………………………………………………………………….. 5. Cultivar Pedigree: …………………………………………………………………………………………………………………………………… 6. Name of Pre- basic: ……………………………………………………………………………………………………………………………………. 7. Proposed area for Release:…………………………………………………………………………………………………………………………… 8.Proposed elevation:…………………………………………………………………………………………………………………………………… 9. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………………………... 10. Agency responsible for maintenance:………………………………………………………………………………………………………………. 11. Distinguishing characteristics: (a) growth habit:……………………………………….(b) leaf:…………………………………………….(c) Stem:…………………………… (d) flower:…………………………………………......(e)pods:…………………………………………………………………...……………….. (f) Seeds:……………………………………………… (g) Seeds size:…………………………………………………………...…………………. (h) Seeds shape and colour:……………………………..(i) time to flowering:………………………………………………………….…………. 12. Major distinguishing characters from other released varieties:…………………………………………………………………………………….. 14. Economical and quality attributes:………………………………………………………………………………………………………………… 15. Agronomic characters (optimal):………………………………………… (a) Sowing date:……………………………………..……………… (b) Seeds Rates:……………………...……...(c) Plant population:…………………………………….(d)Maturity:………………………………. 64 (e) Fertilizer:………………………………………………………..(f)crop height:………………………................................................................ (g) Irrigation need :…………………………………………………( h)Harvest index:…………….............................................................…......... (i) Consumer acceptability :………………………………………..( j)Others:……………...……………………………………………..………. 16. Yield data (a)Yield on NPT :…………………………………….(b) Yield on farm :…………………………………………………………… Based on the above results, NPT-TC recommends that:- (a) the variety be release (………)* (b) the variety should not be release (………)* Signature and Stamp:…………………………………………………… date:……………………………………………………………………………………….. *Please tick where applicable Secretary – NPT-TC ………………………………….. Attached: DUS results, NPT report, on farm trial report advanced yield trial 65 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR VI ______________ VARIETY REGISTRATION CERTIFICATE ______________ (made under Regulation 8(2)) This is to certify that the variety whose particulars referred herein has been approved and registered for use and commercialization in Tanzania. Name of Variety: …………………………………………………………………………….….. Plant species: ……………………………………………………………………………………. Botanical Name: ……………………………………………………………………………….... Name and Address of Registrant …………………………………………………………….…. Registration Number. …………………………………………………………………………… Issued this……………………day of …………………………………………………200……. Signature and Seal: ……………………………………………. Director 66 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR VII ______________ APPLICATION FOR INSPECTION OF SEED FIELD CROP ______________ (Made under Regulation 27(1)) (To be completed in triplicate) To: Tanzania Official Seed Certification Institute Note: Separate application form must be submitted for each crop and variety grown for certification and must be submitted within 30 days after planting. A map giving clear instruction on how to reach the farm as well as the location of the field unit within the farm must be drawn overleaf. 1. Full name of Applicant: .........................................................Address:................................................... Telephone: .............…………... 2. Name of Contract grower (if any)*:......................................................Address: ......................................Telephone: ............................. 3. Person to be Contacted for field inspection: ...........................……………Address: ................................. Telephone: ...............………. 4. Location of the field from the nearest town: ...................................… ………………………………………....................................... 5. Location of the field within the farm: ..................................................................................……………………………………….…...... 6. Details of crop to be produced/grown: Crop Variety Class Lot No. of Seeds used Hectarage: Source of Seeds use (Supplier/Seller Planting date 7. Estimated flowering/Tasselling date: ………………………….........................................................……………................................. 8. Quantity of Seeds Used: ...................... kgs No. of Containers:..............................................Weight of each container: .....................kgs 9. Estimated date of Harvesting (Approximate): ............................................……………………………………………………………… 10. Previous crops and varieties grown in this field for the last two growing seasons……………………………………………………… * a separate application form should be filled for each contract grower. Declaration: I hereby declare that all information provided here is true to the best of my knowledge and belief and I shall always observe all conditions governing Seeds production as provided in the Seeds Act and Regulations. Enclosed herewith is a cheque of the sum of shillings…………………… being payment of the inspection. Date: ................……... ………………………Signature of Applicant: ………………………..……………………….................................. Designation: ......................................................................................................................................................................................................... 67 FOR OFFICIAL USE ONLY Date received:…………………… ……..Appication No…………………………………………………………………………………..… Application accepted/rejected: ..................................................................……………....................................................................................... If rejected, state reasons for rejection:...................................................……………. .......................................................…............................... Field Registration No: ………………………………………………………….….…................................................................................... Date: ..................….... Signature: ...................……………...... Designation:.................................................................................................................... 68 Form SR. VIIIA THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… ______________ FIELD INSPECTION RESULTS ______________ (Made under Regulations 27(12)) (to be filled after every inspection) Applicant name………………………………………………………………….Address………………………………………………………..… Grower name………………………………………………………………….Address………………………………………………………..… Crop ………………………………………..Variety:…………………………………………………………………………………….. Class:……………………………………………...hectares:…………………………………………………………..……………………...… Does the crop have proper cutivar characteristics…………………………………………………………………………………………………….. Count Off - types Diseases Other features Objectionable weeds Other crop weeds 1. 2. 3. 4. 5. 6. Total Average percentage Identity The isolation distance /time of ……………………………………………………………days/meters is adquate/inadquate and should be corrected. General conditions of crop e.g drought, crop husbandry, etc…………………………………………………………………………………………... ………………………………………………………………………………………………………………………………………………………….. Further remarks…………………………………………………………………………………………………………………………………………. ………………………………………………………………………………………………………………………………………………………….. Estimated yield …………………………………………………………………………………bags/hectares……………………………………….. Comments: This crop is approved/rejected. If rejected state reasons:……………………………………………………………………………………………………………………………….... ………………………………………………………………………………………………………………………………………………………….. Signature of Seeds Grower or representative of the Grower ………………………Date…………………………...………………………………… Name of the Inspector: ………………………………………………………….……………………………………………………………………… Signature…………………………………………………………..Date………………………………………………………….…………………… Inspector 69 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR. VIIIB ______________ FINAL FIELD INSPECTION RESULT ______________ (Made under Regulation 27(13)) Applicant name………………………………………………………………….Address………………………………………………………..… Grower name………………………………………………………………….Address……………………………………………………..…..… Crop ………………………………………..Variety:…………………………………………………………………………………………….. Class:……………………………………………...hectares:…………………………………………………………..…………………….......… Factor 1st inspection 2nd Inspection 3rd Inspection Total No. or % Off - types Diseases Tassels Weeds Other crops Other (specify) Remarks………………………………………………………………………………………………………………………………………. ………………………………………………………………………………………………………………………………………………… ………………………………………………………………………………………………………………………………………………… This Crop is approved/rejected. If rejected, state reasons:…………………………………………………………………... Signature ……………………………………………………………………………………. Seed grower Signature…………………………………………………………..Date………………………………………………………….……………. Filed Inspector Copy to: Grower. Chief Seed Certification Officer 70 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR IX SEED TRANSPORT ORDER (Made under Regulation 29(2)) To:………………………………………………………….of …………………………………………………………………………... This order is issued to authorize transportation for processing of …………………………………bags/tones of seed crop from …………………to ………………………………………………on…………………….200……………………………. Crop : ……………………………………………………….…………. Variety: ………………………………………………………….....…. Class: ……………………………………………………………..…... Mode of transportation :…………………………………………….…. Vessel Registration No:. ……………………………………………… Type of the identification:………………………………………………………………………………………… ) ………………………………… Seeds Inspector 71 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR X ______________ WORK ORDER ______________ (Made under Regulation 30(2)) This work order is issued at …………………………………………this ……………………. day of ……………………………………200…………. Name and address of Seeds producer : ……………………………………………………… ……………………………………...................................... Crop : ……………………………………… variety ………………………………………………………………………………...…………………….. Name and address of Seeds processor: …………………………………………………………………….…...………………………...…………………. Location of processing plant………………… ……………………………………………………………………………………....................................… Class …………………………………………….Weight of lot before processing…………………………………………………kg Lot No…………………………………………………..Provisional germination………………………………………………… % No. of Labels Serial Nos. of labels Issued No. of unused Labels Date of Sealing Nos. of Seals used No. Container Sample No. Remarks if any ……………………………………………………………………………………………………………………………………….……… ………………………………………………………………………………………………………………………………………...… ………………………………………………………………………………………………………………………………………..……… ……………………………………………………………………………………………………………………………………………... Name of Inspector:………………………………… Signature: …………………………………………. Cc: Chief Seed Certification Officer 72 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEEDS CERTIFICATION INSTITUTE S/No FORM SR XI _________ STOP SALE ORDER _________ (Made under Regulation 32(5)) (to be filled in dublicate) Date:……………………………………….. To: .. ………………………………………………………………………………………………………………………………………………..……… (Name of Seeds Dealer) Address:………………………………………………………………………………………………………………………………………………… Businness Licence No……………………………………………………………………………………………............ You are hereby informed that the following lots of Seeds are found to be in violation of Seeds Act and Regulations : Crop Variety Lot No. No. of containers Quantity in Kg. Nature of violation Sampled Yes No By this Notice you are ordered to hold these lot/ lots of Seeds intact at:……………………………………………………………………………... until compliance with the law has been achieved and the Seeds has been released from this order . Once you comply with the relevant violated provision of the Seed Act or Regulations, please contact Chief Seeds Certification Office. Other instruction: ………………………………………………………………………………………………………….................................................. Name of Inspector: ……………………………………………………………… ..Name of seed dealer …………………………………....................... Signature: ………………………………………………………………………… Signature: ………………………....................................................... Date: ……………………………………………………………………………… Signature: ………………………………........................................... 73 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/No FORM SR XII ____________________ NOTICE TO IMPORT SEED ____________________ (Made under Regulation 33(1)) To: The Director, Ministry of Agriculture, Food Security and Cooperatives P.O.BOX 9192 Dar Es Salaam I/ We hereby apply to Import Seed described herein below in accordance with the terms and conditions laid down in the Seed Act and the Regulations made thereto. 1. Full Name of Applicant: ………………………………………………………………………………………………………………………. 2. Address:………………………………………………………………Tel:……………………………………………………………………. 3. Registration No………………………………………………………………………………………………………………………………… 4. Previous permit No. (if any )……………………Location of the store/godown where the Seeds will be kept after arrival :………………… 5. Quantity of the Seeds of the same variety in stock (if any)……………………………………………………………………………………. 6. Country of Origin………………………………………………………………………………………………………………………………. 7. Name and address of the Supplier:…………………………………………………………………………………………………………...… 8. Expected date of arrival of the consignment…………………………………………………………………………………………………… 9. Mode of transport ……………………………………………………………………………………………………………………………… 10.Point of entry…………………………………………………………………………………………………………………….…………….. 11.Particulars of seed ……………………………………………………………………………..………………………….…………………… Crop Variety Name Class Quantity in Kg. Declaration: I declare that all information provided herein is true and I do undertake to observe all terms and conditions for importation/ exportation as provided in the Seeds Act and its Regulations. Signed this……………………………day of ………………………………200……………………………………………… Signature:……………………………………………………………….. _________________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY Date Received:………………………………………………………….. Application Fees paid …………………………………………………………………………………………………………………………………….… Action taken : Considered for permit/ Not considered for Permit* Date: …………………………………………………………………….. Signature:………………………………………………………………… Director *please delete where necessary 74 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR XIII ____________________ SEED IMPORT PERMIT ____________________ (Made under Regulation 33(3)) Permit No. ……………………………………Date issued ………………………………………...………………………………...…….. Permission is hereby granted to …………………………………………………………… of Postal Address Office……………………... (Name and of the Seeds dealer) ………………………………………………………………………………, Registration No. ………………………………………….. to import from. …………………………………………………………………………………………………………………………….. the following Seed: _ Species Variety Class Weight in kg This permit is issued subject to the following conditions: 1. The consignment of Seeds shall be accompanied by- (a) Phytosanitary certificate. (b) Certificate of quality issued by a Recognized Certification Agency 2. The consignment shall be subjected to Tanzania Plant Protection Act and Regulations made thereof and on arrival in the country, the Seeds shall be inspected in accordance with the Seed Act and Regulations made thereto. 3. The Seed shall not be distributed prior to the outcome of the results of sample. 4. The Permit holder shall be required to pay all fees as stipulated in the Seeds Regulations. 5. The permit holder shall be required to fulfill all conditions for importation as provided in the relevant law of Tanzania. 6. This permit is not transferable and may be revoked if the holder fails to comply with the terms and condition for conditions as provide in the Seed Act and the Regulations made thereto. 7. The permit shall be for ………………………….months only. Signature : ……………………………………………………………………………………………………………………………….. Director cc. Chief Seeds Certification Officer. 75 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/No FORM SR XIV ____________________ NOTICE TO EXPORT SEED ____________________ (Made under Regulation 34(1)) To: The Director Ministry of Agriculture, Food Security and Cooperatives P.O.BOX 9192 Dar Es Salaam I/ We hereby apply to export Seed described herein below in accordance with the terms and conditions laid down in the Seed Act and the Regulations made thereto. 1. Full Name of Applicant: ………………………………………………………………………………………………………………………. 2. Address:……………………Tel:………………………………………………………………………………………………………………. 3. Registration No………………………………………………………………………………………………………………………………… 4. Previous permit No. (if any )……………………Location of the store/godown where the Seeds will be kept after arrival :………………… 5. Quantity of the Seeds of the same variety in stock (if any)……………………………………………………………………………………. 6. Country of Origin……………………………………………………………………………………………………………………………..…. 7. Name and address of the Supplier:…………………………………………………………………………………………………………...… 8. Expected date of arrival of the consignment…………………………………………………………………………………………………… 9. Mode of transport ……………………………………………………………………………………………………………………………… 10. .Point of entry…………………………………………………………………………………………………………………….…………….. 11. Particulars of seed ……………………………………………………………………………..………………………….…………………… Crop Variety Name Class Quantity in Kg. Declaration: I declare that all information provided herein is true and I do undertake to observe all terms and conditions for Importation/ exportation as provided in the Seeds Act and its Regulations. Signed this……………………………day of ………………………………200……………………………………………… Signature:……………………………………………………………….. _________________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY Date Received:………………………………………………………….. Application Fees paid …………………………………………………………………………………………………………………………………….… Action taken : Considered for permit/ Not considered for Permit* Date: …………………………………………………………………….. Signature:………………………………………………………………… Director *please delete where necessary 76 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR XV ____________________ SEED EXPORT PERMIT ____________________ (Made under Regulation 34(3)) Permit No. ……………………………………Date issued ………………………………………...………………………………...…….. Permission is hereby granted to …………………………………………………………… of Postal Address Office……………………... (Name and of the Seeds dealer) ………………………………………………………………………………, Registration No. ………………………………………….. to import from. …………………………………………………………………………………………………………………………….. the following Seed: _ Species Variety Class Weight in kg This permit is issued subject to the following conditions: 1. The consignment of Seeds shall be accompanied by- (a) Certificate of quality issued by Tanzania Official Seed Certification Institute. (b) Phytosanitary certificate and other relevant document governing exportation issued by relevant authorities. 2. The Permit holder shall be required to pay all fees as stipulated in the Seeds Regulations. 3. The permit holder shall be required to fulfill all conditions for exportation as provided in the relevant law of Tanzania and the country which seeds are exported. 4. This permit is not transferable and may be revoked if the holder fails to comply with the terms and condition for conditions as provide in the Seed Act and the Regulations made thereto. 5. The permit shall be for ………………………….months only. Signature : ……………………………………………………………………………………………………………………………….. Director cc. Chief Seeds Certification Officer. 77 FORM SR XVI THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… ______________ APPLICATION FOR SEED TESTING ______________ (Made under Regulation 38(2)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute1. Full name of the Applicant: …………………………............................... 2. Postal Address …………………………………………………………………………… (3) Tel. No. .......................................................... 4. Email. …..............................................Fax No……………………………………………............................................................................. 5. Crop …………………………………………………………………………………………………........................................................ 6. Variety .............................................................Class ………………………………………………………………………………...……. 7. Lot No. ………………………………………….Ref. ……………………………………………………………………...…………… 8. Seeds Import Permit No. ………………………………….. of ………………………………………Date ……………………………… 9. Weight of Lot……………………………………………………………………………………………………………………………… 10. Seeds dressing……………………………………………………………………………………………………………………...…….. 11. Date of Sampling:………………………………………………………………………………………………………………………………………… 12. Tests required……………………………………………………………………………………………………………………………… (purity/germination/moisture/injurious weeds/diseases/) * 13. Testing fee paid ………………………………………………………… Payment Voucher/ Cheque No ……………………………..). I certify that the sample was drawn by me in the prescribes manner this …………………………..day of ………………………………... Name of Sampler:…………………………………………….Address…………………………………………..………………………… Signature:…………………………………………………………………………… * delete as necessary ________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY: Application No: …………………………… Date Received:…………………………………………………………………………………… Fees Receipt No: ………………………….. Amount of sample received for testing :………………………………………………………………………..…. ………………………… Test requested:………………..………………………………………………………………………..…. …………………………………… Test results: Dated:……………………………….Signature of the responsible officer:……………………………………… 78 FORM SR XVII S/N………… THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE ______________ SEEDS TESTING CERTIFICATE ______________ (Made under Regulation 38(3)(b)) ((To be filled in Triplicate) OFFICIAL SAMPLE NO. Date received: TEST NUMBER Lot Number: Weight of lot: Crop and variety: Class of Seeds : Country of origin: RESULT OF ANALYSIS Purity Germination Pure Seeds (P) % Inert matter % Other Seed % Weed Seed % Capacity (G) Hard % Fresh ungerminated Seed % Abnormal Seedslings % Pure germinating Seed P x G 100 % Moisture % % Types of : (1) Inert matte ……………………………………………………………………………………………………………………………… (2) Other Seed……………………………………………………………………………………………………………………………… (3) Weed Seed: (a) objectionable …………………………………………………………………………………………………….………… (b) restricted ………………………………………………….……………………………………………………………… Special test:……………………………………………………………………………………………………………………………….. ………………………………………………………………………………………… ………………………………………………….. Remarks: It is hereby certified that the Seeds lot described above has met/ has not met minimum Seed standards for ……………………….class Signature……………………………………. Seeds Analyst Date:…………………………………………… Signature……………………………………. Chief Seeds Certification Officer 79 FORM XVIII S/N………… THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE ______________ SEED TESTING REPORT ______________ (Made under Regulation 38(3)(c)) PRIVATE SAMPLE NO. Date received: TEST NUMBER Lot Number: Weight of lot: Crop and variety: Class of Seeds: Country of origin: RESULT OF ANALYSIS Purity Germination Pure Seeds (P) % Inert matter % Other Seed % Weed Seed % Capacity (G) Hard % Fresh ungerminated Seed % Abnormal Seedslings % Pure germinating Seed P x G 100 % Moisture % % Types of : (1) Inert matte ……………………………………………………………………………………………………………………………………… (2) Other Seed………………………………………………………………………………………………………………………………………… Signature……………………………………. Seeds Analyst Date:…………………………………………… Signature……………………………………. Chief Seed Certification Office 80 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE AND FOOD SECURITY THE SEEDS ACT, 2003 (No. 18 of 2003) S/N………… Form SR - XIX Registration No. ………… ______________ CEERTIFICATE OF AUTHORISATION AS INSPECTOR/SAMPLER/ANALYST* ______________ ([Made under Regulation 42(4)) This is to certify that……………………………………………………………………… of………………………………...…………………… (Name and address of Registrant ) has been registered and authorized as … ………………………………………………..………………………………………………………. This authorization shall be valid for the period of ……………………from………………………to …………………………and may be cancelled if the registrant fails to comply with terms and conditions for authorisation and the provisions of the Seed Act and Regulations. Issued at ………………………………………this………………..………….….day of ……………….………………….200………. Signature and seal :………………………………………………………….. Chief Seed Certification Officer * delete where not applicable CC: Director 81 __________ SIXTH SCHEDULE __________ FEES FOR SERVICES ____________ (Made under Regulation 40 (1)) ____________ Service Fee in TShs. I. Charges based on the services rendered for each operation: A: Seed field inspection made to determine the eligibility of a crop for pedigree status for each inspection: (1) for hybrid maize per hectare inspected … … … … … … …… 3150 (2) vegetables/pastures, up to one hectare inspected … … … … … 5000 (3) vegetables/pastures, for every exceeding unit above one hectare inspected … 4000 (3) for all other s of Seeds crops, per hectare inspected … … …… … 2150 (4) minimum fee per field where inspected total field is less than 10 hectares,… …. 20,000 B: Seed inspection and sampling: (1) agricultural crops per 100kg or part thereof … … … …… …… … 1,500 (2) vegetable crops per 5 kg … …… … … …… …… …… … 2000 (3) root crops per hectare or part thereof … … … … … … … … 2000 (4) minimum fee for each lot inspected (maximum of 10 tones per lot) … … 10,000 C: Seed testing for germination, purity and moisture: (1). charges for one kg for field crops of pedigree class … … … … … .. ... 15 (2). charges for 100gm for vegetable crops of pedigree class … … … . …. … 20 (3). charges on one kg for standard class Seed… … … . .. …. …. …. …. … 5 (4). charges on one kg of Seed for export … … … . .. … … … . .. …. 20 D: Seed health testing: (1) charges per sample for local market Seed … … … . .. … … … . .. 20,000 (2) charges per sample for export Seed… … … . .. … … … . .. …. … 50,000 F: Certificate and Tags (1) registration of Seed dealer… … … … … … … ... …. …. … 2500 (2) variety registration … … … … … … … ... …. …. ……. … 10,000 (3) certificate of Seed testing … … … … … … … ... …. 1000 (4) certificate for Seed import/ export … … … … … … … … 10,000 (5) certified copy of a Seed testing certificate … … … … … … ….. 500 (6) label /seal per each label /seal … … … … … … …. …. …. ….. .. 500 (7) DUS test certificate… … … … … … … ... …. ….… … 5000 E: Non refundable fees for various application forms (1) Registration as a Seeds dealer… … … … ... …. ….… … … … 2000 (2) DUS test… … … … … … … ... …. ….… … … … 2000 (3) NPT … … … … … … … ... …. ….… … … … … 2000 (4) Seed field inspection… … … … … … … ... …. ….… … 3000 (5) Seed testing (per Seeds lot) … … … ... …. ….… … … … 1000 (6) Seed transport order… … … … … … … ... …. ….… … 2000 (7) Notice to import/export Seed… … … … … … … ... …. … 2000 F: Other charges (1) Conducting DUS test (for two seasons)… … … … ... …. ….… … 500,000 (2) Conducting NPT( for one season)… … … … … ... …. ….… … 600,000 (8) Authorisation / licensing of Seeds sampler or Analyst … … … … 20,000 Note: Fees for inspect, sampling , testing shall apply mutatis mutandis on re- inspection re- sampling or testing. 82 ___________ SEVENTH SCHEDULE ____________ (Made under Regulations 7(4)(a)) ____________ APPROVED TESTING SITES FOR NATIONAL PERFORMANCE TRIAL Crop Type High Altitude Mid Altitude Low Altitude A: Compulsory certification crops Hybrid Maize Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) ,Machame or Marangu AFSF or Selian, Lambo, Gairo, Mbimba, Babati, Laela Msimba or Ilonga, KATRIN, SUA, Maramba or Mwele, Uchira, Nachingwea Sweet Corn Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Miwaleni, Gairo Msimba or Ilonga, KATRIN, Kibaha, SUA, Maramba or Mwele Open Pollinated Maize Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Lambo, Gairo Ukiriguru Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA, Nachingwea Maramba or Mwele Common dry beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Lambo, Gairo, Mbimba Msimba or Ilonga, KATRIN, SUA Snap beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF, Horti-Tengeru Soya beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Horti- Tengeru, Laela (Sumbawanga), Maruku Msimba or Ilonga, KATRIN, Naliendele or Nachingwea, SUA Hybrid sorghum Uyole, Mbozi, Dabaga, Nkundi (Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA Open Pol. s or ghum AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA Wheat or Barley Dabaga, Njombe, Uyole, Basuto (Hanang) Nkundi(Sumbawanga) AFSF or Selian, Karatu, West Kilimanjaro Rice (Lowland) Ukiriguru, KATC (Moshi), Mbarali Dakawa, KATRIN, Ruvu, SUA, Kyela, Kitere, Kinyope (Lindi) Mkwaya (Lindi) Rice (Upland) Matombo, Mahenge Kyela,Kitaya Hybrid sunflower Dabaga, Njombe, Uyole, Nkundi(Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Maramba or Mwele Naliendele or Nachingwea, SUA Open pol. Sunflower Dabaga, Njombe, Uyole, Nkundi(Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Naliendele or Nachingwea SUA, Maramba or Mwele Irish potato Dabaga, Njombe, Uyole, Kifyulilo HORTI-Tengeru, Miwaleni, West Kilimanjaro Groundnuts Ukiriguru, Hombolo, Tumbi (Tabora), Gairo Naliendele or Nachingwea, Ilonga or Msimba, Chambezi, Masasi, Chambezi B:Voluntary certification crops Cassava* Ukiriguru, Hombolo Tumbi (Tabora) HORTI- Tengeru Kibaha, Mlingano, Chambezi, Naliendele or Nachingwea, Masasi, Mtopwa (Newala) Sweet potato Gairo, Hombolo, Miwaleni, Hort Tengeru, Ukiriguru, Tumbi (Tabora) SUA Naliendele or Nachingwea Carrots Dabaga, Njombe, Uyole HORTI-Tengeru, Miwaleni, West Kilimanjaro Green gram AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Tumbi (Tabora) Kibaha, Mlingano, Msimba or Ilonga , Maramba or Mwele Naliendele or Nachingwea, SUA, Msimba or Ilonga 83 Pigeon pea (Long duration) AFSF or Selian, Miwaleni, Ukiriguru, Isimani, Tumbi (Tabora) Hombolo Karatu Msimba or Ilonga, KATRIN, SUA, Masasi Pigeon pea (Mid. & short duration) AFSF or Selian, Miwaleni, Ukiriguru, Isimani, Tumbi (Tabora), Hombolo, Karatu Kibaha, Mlingano, Msimba or Ilonga, Naliendele or Nachingwea, SUA Cowpea AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Ismani, Tumbi (Tabora) Msimba or Ilonga, Naliendele or Nachingwea, SUA, Mlingano or Maramba, Masasi Sesame AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Kibaha, Mlingano, Msimba or Ilonga, Naliendele or Nachingwea, SUA,Kilwa Tomato Uyole, Dabaga, Njombe Seatondale (Iringa) HORTI-Tengeru, Ukiriguru, Lushoto, Makutop or a Dakawa or SUA, Kibaha, Mlingano, Maramba or Mwele Onion Uyole, Dabaga, Njombe, Seatondale (Iringa) HORTI-Tengeru, Ukiriguru, Mbarali Makutop or a, Karatu Dakawa or SUA, Kibaha, Mlingano, Maramba or Mwele Key to the abbreviations on the table: AFSF = Arusha Faundation Seeds farm SUA = Sokoine University of Agriculture KATC = Kilimanjaro agricultural Training Centre Horti - Tengeru = Horticultural Research Institute Tengeru KATRIN = Kilombero Agricultural Training and Research Institute EXPERIMENTAL DESIGNS AND DATA COLLECTION (a) Experimental design, plot size and number of replications for NPT CROP DESIGN MINIMUM GROSS PLOT SIZE MINIMUM REPLICATIONS ROW LENGTH (Meters) NUMBER OF ROWS Maize RCBD 5 4 3 Dry Beans RCBD 5 4 3 Snap Beans RCBD 5 4 3 S or ghum RCBD 5 4 3 Wheat or Barley RCBD 3 12 3 Rice RCBD 5 20 3 Sunflower RCBD 5 4 3 Irish Potato RCBD 5 4 3 Carrots RCBD 3 6 3 Cassava RCBD 5 4 3 Pigeon Peas RCBD 5 4 3 Cow peas RCBD 5 4 3 Green gram RCBD 5 4 3 Groundnut RCBD 5 4 3 Sweet potato RCBD 5 4 3 Sesame RCBD 5 4 3 Tomato RCBD 6 2 3 Onion RCBD 3 6 3 (b) BASIC INFORMATION ON MANAGEMENT OF NPTs 1. Planting Date 2. Fertilizer rate 3. Weeding regime or herbicide application 4. Plant spacing 5. Pesticides application (if any) 6. Weather (rainfall and temperature) 84 ________ EIGHTH SCHEDULE __________ PROHIBITED, RESTRICTED AND NOXIOUS WEED SEEDS __________ (Made under Regulation 48) The seed of the species of plants specified in this Schedule are hereby prescribed as weed seed for the purpose of establishing class standards under the Act. Class 1: Objectionable Weed Seed Objectionable weed seeds are weed seed not allowed in any seed at all, that is to say, a sample of seed may not contain any objectionable weed seed. However, if any objectionable weed seed is found in a sample, the tolerance shall be one seed per kilogram. If two or more seed are found in a kilogram the seed shall be placed under stop sale until it has been re-cleaned and retested. When one objectionable weed seed is found it will be considered within the tolerance none. The following are objectionable weed seed:- 1. Witch weed………………………………………………. Striga spp 2. Dodder…………………………………………………… Cascuta spp 3. Field bind wood…………………………………………. Convolvus arvensis L. 4. Hemp………………………………………… ….. ……. Marijuana spp. 5. True Hemp (in Swahili Bhangi) ………………… ……. Cannabis Sativa 6. Cocaine plant …………………………………… …….. Erythrosylum spp. 7. Sudan grass……………………………………… ……. Sorghum sudanese 8. Thorn apple…………………………………… ……….. Datura spramondum L. 9. Wild oats …………………………………………. …… Avena spp. Class 2: Restricted Noxious Weed Seed The following are restricted noxious weed seed:- 1. Couch grass …………………………………………… Digitaria scalarum (Schweinf.) Chiov. 2. Nutgrass, Watergrass…………………………………. Cyperus spp. 3. Perennial sowthistle…………………………………. Sonchus arvensis L. 4. Wild mustard…………………………………. . …… Brassica campestris L 5. Mexican poppy …………………………………. ….. Argemone mexicana L. 6. Darnel…………………………………. …………… Lolium temulentum L. 7. Guinea-fowl grass……………………………………. Rottboelia exaltata L.f. 8. Love grass …………………………………. ……… Setaria verticiltata (L.) Beauv. 9. Wild rice …………………………………. ………… Oryza barthii A. Chev. The presence of restricted noxious weed seed in any sample of seed shall be restricted. Where any restricted noxious weed seed are found in any sample of seed the maximum allowed shall not exceed four weed seed per kilogram, whether the four weed seed are of the same or a combination of two or more s of weed seed, the name and number of each must be stated on the label. Class 3: Common Noxious Weed Seed. Common Noxious Weed Seed are seed bulblets or tubers or pieces thereof specified as weed seed under the Seed, Regulations 2006 or recognized as weed seed by general usage. The presence of standard noxious weed seed in any sample of seed shall be restricted. Where any standard noxious weed Seed are found in any sample of seed the maximum allowed shall not exceed 1.5% by weight. Common noxious weed seed include, but not restricted to, the following seed:- 1. Cleavers…………………………………………… Galium spurium L. 2. Dock …………………………………. …………. Ramex crispus L. 3 Chickweed …………………………………. …… Stellaria media (L.) Vill. 4. Mexican marigold …………………………………. Tagetes minuta L. 5. Chinese lantern …………………………………… Nicandra physalodes (L.) Gaertn. 6. Oxalis ………………………………….………… Oxalis latifolia H.B.K. 7. Blackjack ………………………………….……… Bidens pilosa L. 8. Pigweed…………………………………. ………. Amaranthus spp.. 9. Goosefoot…………………………………. …….. Chenopodium spp. 10. Crabgrass………………………………………… Digitaria velutina (Forsk.) Beauv. 11. Macdonaldi, Gallant soldier …………………….. Galinsoga paarviflora. Cav. Dar Es Salaam, STEPHEN M. WASIRA (MP) ………, 2007 Minister for Agriculture Food Security and Cooperatives 85"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":173,"cells":{"data":{"kind":"string","value":"# Extracted Content SOURCES OF FUNDS DASIP BENEFICIARY BARIADI SOMANDA NYAUMATA Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 DUTWA MWAMONDI Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 SAPIWI NYAMIKOMA Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 MWAMAPALALA ISAKANG'HWALE Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 MHANGO NGALLA Rehabilitation of rural feeder roads 16,324 13,059 3,265 BUNAMHALA BUNAMHALA Construction of a market shed. 25,000 20,000 5,000 LUGURU NHOBOLA Rehabilitation of rural feeder roads 19,290 15,432 3,858 NKOLOLO MWASHAGATA Rehabilitation of a cattle dip. 15,000 12,000 3,000 SAKWE IBULYU Rehabilitation of a cattle dip. 15,000 12,000 3,000 MWASWALE LUG'WA Construction of a crop storage structure. 35,000 28,000 7,000 NKUYU Purchase of Oxen drawn implements 10,000 5,000 5,000 BUNAMHALA GIRIKU Construction of a cattle dip. 27,500 22,000 5,500 MWAUBINGI GASUMA Construction of a cattle dip. 27,500 22,000 5,500 MWADOBANA KILABELA Construction of a cattle dip. 27,500 22,000 5,500 LAGANGABILILI NG'HESHA Construction of a cattle dip. 27,500 22,000 5,500 305,614 241,491 64,123 BUKOMBE IYOGELO BUGELANGA Rehabilitation of rural feeder roads 26,000 20,800 5,200 USHIROMBO NGANZO Construction of a crop storage facility 33,200 26,560 6,640 Nyitundu Construction of a crop storage facility 33,200 26,560 6,640 92,400 73,920 18,480 KAHAMA MPUNZE IPONYAHOLO Construction of a crop storage structure. 28,180 22,544 5,636 Procurement of hulling machine 5,500 2,750 2,750 SABASABINI Procurement of hulling machine 5,500 2,750 2,750 KINAMAPULA BUNASANI Construction of a crop storage structure. 28,180 22,544 5,636 BUTIBU Procurement of hulling machine 5,500 2,750 2,750 NGONGWA NGULU Construction of a crop storage structure. 28,180 22,544 5,636 ISAGEHE MONDO Construction of a crop storage structure. 28,180 22,544 5,636 MWANDEKULIMA KISUKE Procurement of hulling machine 5,500 2,750 2,750 TOTAL BARIADI DISTRICT TOTAL BUKOMBE DISTRICT SHINYANGA REGION DISTRICT WARD VILLAGE NAME OF PROJECT TOTAL COST (in '000) DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ALLOCATION OF INVESTMENT FUNDS - 1st QRT 2008/09 KAGERA , SHINYANGA, MARA, KIGOMA AND MWANZA REGIONS BUGARAMA BUYANGE Procurement of hulling machine 5,500 2,750 2,750 UKUNE IGUNDA Rehabilitation of a cattle dip. 8,890 7,112 1,778 KUNDIKILI Construction of a charco dam. 28,536 22,829 5,707 KINAGU MWAKUHENGA Construction of a charco dam. 28,536 22,829 5,707 MALUNGA KITWANA Construction of a charco dam. 28,536 22,829 5,707 MHONGOLO NYASHIMBI Construction of a charco dam. 28,536 22,829 5,707 KILANGO WAME Construction of a charco dam. 28,536 22,829 5,707 291,790 225,182 66,608 KISHAPU MONDO MWIGUMBI Construction of a crop storage structure. 35,000 28,000 7,000 KABILA Procurement of a grain milling machine 10,000 5,000 5,000 SHAGIHILU MWALATA Construction of a charco dam. 35,000 28,000 7,000 TALAGA KIJONGO Construction of a charco dam. 35,000 28,000 7,000 LAGANA LAGANA Construction of a charco dam. 35,000 28,000 7,000 UKENYENGE BULIMBA Procurement of an agric processing machine 10,000 5,000 5,000 SONGWA MPUMBULA Construction of a cattle dip. 25,457 20,366 5,091 185,457 142,366 43,091 MASWA DAKAMA MWANDETE Construction of a cattle dip. 26,000 20,800 5,200 BUSILILI BUHUNGUKILA Construction of a crop storage facility 28,800 23,040 5,760 MPINDO SENANI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 Construction of 2 shallow wells for irrigation. 12,000 9,600 2,400 NGULIGULI MWASHEGESHI Construction of a crop storage facility 4,000 3,200 800 MALAMPAKA NYABUBINZA Procurement of rice hulling(grain milling) machine. 5,000 2,500 2,500 SUKUMA MWABAYANDA (m) Procurement of a ground nut sheller. 4,000 2,000 2,000 Construction of a shallow well for irrigation. 4,800 3,840 960 KULIMI MWABAYANDA (s) Construction of a shallow well for irrigation. 4,800 3,840 960 Construction of a crop storage facility 4,000 3,200 800 BADI IKUNGU Construction of a crop storage facility 4,000 3,200 800 NYASHIMBA Rehabilitation of a cattle dip. 15,000 12,000 3,000 Construction of a crop storage facility 4,000 3,200 800 ISANGA ISANGA Procurement of 2 ground nut shellers. 8,000 4,000 4,000 SHISHIYU IGUNYA Procurement of a paddy processing machine. 10,000 5,000 5,000 NYABUBINZA MWABAGALU Procurement of 20 oxen weeders 8,000 4,000 4,000 Construction of a shallow well for irrigation. 4,800 3,840 960 MASELA MANDELA Procurement of an oil processing machine. 5,000 2,500 2,500 Construction of a shallow well for irrigation. 4,800 3,840 960 TOTAL KAHAMA DISTRICT TOTAL KISHAPU DISTRICT 167,000 118,600 48,400 MEATU NG'HOBOKO MINYANDA/MWAFUGULI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 ITINJE ISENGWA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 LUBIGA LUBIGA Construction of a cattle dip. 35,000 28,000 7,000 MWAMALOLE USIULIZE Construction of a cattle dip. 35,000 28,000 7,000 MWAMANONGU MWAMANONGU Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 KIMALI PAJI Construction of a crop storage facility 35,000 28,000 7,000 KISESA KISESA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 SAKASAKA SAKASAKA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 MWAMISHALI MWAMBITI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 165,000 114,000 51,000 SHINYANGA SAMUYE NG'WANG'HALANGA Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 MWANTINI JIMONDOLL Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 IMESELA MWAMANYUDA Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 ITWANGI NYIDA Construction of a crop storage facility 35,000 28,000 7,000 MWAMALA BUGOGO Construction of a crop storage facility 35,000 28,000 7,000 TINDE WELEZO Construction of a crop storage facility 35,000 28,000 7,000 210,000 168,000 42,000 1,417,261 1,083,559 333,702 TOTAL SHINYANGA REGION TOTAL MASWA DISTRICT TOTAL MEATU DISTRICT TOTAL SHINYANGA DISTRICT"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":174,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vq: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 ACRONYMS i TABLE OF CONTENTS Table of contents........................................................................................................................................................... i Acronyms..................................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive summary.................................................................................................................................................... vii Illustrations................................................................................................................................................................. xii ENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION .................................................................................................... 1 1.1 Introduction.................................................................................................................................................. 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area..................................................................................................................................................... 1 1.4 Climate.......................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Population..................................................................................................................................................... 1 1.6 Socio-economic Indicators........................................................................................................................... 2 PART II: INTRODUCTION.................................................................................................................................. 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture........................................... 3 2.2 Census Objectives ........................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................ 4 2.4 Legal Authority of the National Sample Census of Agriculture.............................................................. 5 2.5 Reference Period.......................................................................................................................................... 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 5 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 7 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparations.............................................................................................. 9 - Data Quality............................................................................................................................. 10 2.7 Funding Arrangements........................................................................................................................ 10 PART III: CENSUS RESULTS AND ANALYSIS .............................................................................................. 11 3.1 Household Characteristics ........................................................................................................................ 11 3.1.1 Type of Household ........................................................................................................................ 11 3.1.2 Livelihood Activities/Source of Income........................................................................................ 11 3.1.3 Sex and Age of Heads of Households ........................................................................................... 11 3.1.4 Number and age of Household Members ...................................................................................... 15 3.1.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 - Literacy Rates for Heads of Households.................................................................................. 15 - Educational Status.................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................ 16 ACRONYMS ii 3.2 Land Use ................................................................................................................................................. 17 3.2.1 Area of Land Utilised .................................................................................................................... 17 3.2.2 Types of Land use.......................................................................................................................... 18 3.3 Annual Crops and Vegetable Production ................................................................................................ 18 3.3.1 Area Planted .................................................................................................................................. 18 3.3.2 Crop Importance............................................................................................................................ 20 3.3.3 Crop Types .................................................................................................................................... 20 3.3.4 Cereal Crop Production ................................................................................................................. 22 3.3.4.1 Maize ........................................................................................................................... 23 3.3.4.2 Paddy ........................................................................................................................... 23 3.3.4.3 Sorghum....................................................................................................................... 26 3.3.4.4 Other Cereals .................................................................................................................... 3.3.5 Roots and Tuber Crops Production................................................................................................ 26 3.3.5.1 Cassava........................................................................................................................ 27 3.3.5.2 Sweet Potatoes............................................................................................................. 28 3.3.6 Pulse Crops Production ................................................................................................................. 28 3.3.6.1 Chick Peas ................................................................................................................... 30 3.3.7 Oil Seed Production....................................................................................................................... 32 3.3.7.1 Groundnuts .................................................................................................................. 32 3.3.8 Fruits and Vegetables ..................................................................................................................... 33 3.3.8.1 Tomatoes ..................................................................................................................... 35 3.3.8.2 Onions.......................................................................................................................... 37 3.3.9 Other Annual Crops Production .................................................................................................... 40 3.3.9.1 Cotton ........................................................................................................................... 40 3.3.9.2 Tobacco ....................................................................................................................... 40 3.4 Permanent Crops....................................................................................................................................... 40 3.4.1 Mango ..................................................................................................................................... 43 3.5 Inputs/Implements Use.............................................................................................................................. 48 3.5.1 Methods of Land Clearing.............................................................................................................. 48 3.5.2 Methods of Soil Preparation.......................................................................................................... 48 3.5.3 Improved Seeds Use...................................................................................................................... 50 3.5.4 Fertilizers Use................................................................................................................................ 51 3.5.4.1 Farm Yard Manure Use ............................................................................................... 51 3.5.4.2 Inorganic Fertilizer Use ............................................................................................... 52 3.5.4.3 Compost Use................................................................................................................ 53 3.5.5 Pesticide Use ................................................................................................................................. 54 3.5.5.1 Insecticide Use............................................................................................................. 54 3.5.5.2 Herbicide Use .............................................................................................................. 55 3.5.5.3 Fungicide Use.............................................................................................................. 55 3.5.6 Harvesting Methods....................................................................................................................... 56 3.5.7 Threshing Methods ....................................................................................................................... 56 3.6 Irrigation ................................................................................................................................................. 56 3.6.1 Area Planted with Annual Crops and Under Irrigation.................................................................. 56 3.6.2 Sources of Water Used for Irrigation............................................................................................. 57 3.6.3 Methods of obtaining water for irrigation...................................................................................... 59 3.6.4 Methods of Water Application ..................................................................................................... 59 ACRONYMS iii 3.7 Crop Storage, Processing and Marketing................................................................................................ 59 3.7.1 Crop Storage.................................................................................................................................. 59 3.7.1.1 Method of Storage ....................................................................................................... 60 3.7.1.2 Duration of Storage...................................................................................................... 60 3.7.1.3 Purpose of Storage....................................................................................................... 62 3.7.1.4 The Magnitude of Storage Loss................................................................................... 62 3.7.2 Agro processing and By-products .................................................................................................. 63 3.7.2.1 Processing Methods..................................................................................................... 63 3.7.2.2 Main Agro-processing Products .................................................................................. 63 3.7.2.3 Main use of primary processed Products..................................................................... 64 3.7.2.4 Outlet for Sale of Processed Products.......................................................................... 64 3.7.3 Crop Marketing ............................................................................................................................. 65 3.7.3.1 Main Marketing Problems ........................................................................................... 65 3.7.3.2 Reasons for Not Selling............................................................................................... 65 3.8 Access to Crop Production Services......................................................................................................... 66 3.8.1 Access to Agricultural Credits....................................................................................................... 66 3.8.1.1 Source of Agricultural Credits..................................................................................... 66 3.8.1.2 Use of Agricultural Credits.......................................................................................... 66 3.8.1.3 Reasons for not using agricultural credits.................................................................... 67 3.8.2 Crop Extension .............................................................................................................................. 67 3.8.2.1 Sources of Crop Extension Messages.......................................................................... 67 3.8.2.2 Quality of Extension.................................................................................................... 69 3.9 Access to Inputs .......................................................................................................................................... 69 3.9.2 Inorganic Fertilizers ....................................................................................................................... 69 3.9.3 Improved Seeds .............................................................................................................................. 70 3.9.4 Insecticides and Fungicide.............................................................................................................. 70 3.10 Tree Planting............................................................................................................................................... 71 3.11 Irrigation and Erosion Control Facilities ............................................................................................... 72 3.12 Livestock Results........................................................................................................................................ 74 3.12.1 Cattle Production ........................................................................................................................... 74 3.12.1.1 Cattle Population ......................................................................................................... 74 3.12.1.2 Herd size...................................................................................................................... 74 3.12.1.3 Cattle Population Trend............................................................................................... 76 3.12.1.4 Improved Cattle Breeds ............................................................................................... 76 3.12.2 Goat Production............................................................................................................................. 76 3.12.2.1 Goat Population ........................................................................................................... 76 3.12.2.2 Goat Herd Size............................................................................................................. 78 3.12.2.3 Goat Breeds ................................................................................................................. 78 3.12.2.4 Goat Population Trend................................................................................................. 78 3.12.3 Sheep Production........................................................................................................................... 78 3.12.3.1 Sheep Population ......................................................................................................... 78 3.12.3.2 Sheep Population Trend............................................................................................... 80 3.12.4 Pig Production ............................................................................................................................... 80 3.12.4.1 Pig Population Trend ................................................................................................... 80 ACRONYMS iv 3.12.5 Chicken Production ....................................................................................................................... 82 3.12.5.1 Chicken Population...................................................................................................... 82 3.12.5.2 Chicken Population Trend ........................................................................................... 82 3.12.5.3 Chicken Flock Size...................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers) .......................................................... 84 3.12.6 Other Livestock ............................................................................................................................. 84 3.12.7 Pests and Parasites Incidences and Control ................................................................................... 84 3.12.7.1 Deworming .................................................................................................................. 86 3.12.8 Access to Livestock Services......................................................................................................... 86 3.12.8.1 Access to livestock extension Services........................................................................ 86 3.12.8.2 Access to Veterinary Clinic......................................................................................... 86 3.12.8.3 Access to village watering points/dam ........................................................................ 87 3.12.9 Animal Contribution to Crop Production ...................................................................................... 87 3.12.9.1 Use of Draft Power ...................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure........................................................................................... 88 3.12.9.3 Use of Compost ......................................................................................................... 88 3.12.10 Fish Farming.................................................................................................................................. 88 3.13 Poverty Indicators...................................................................................................................................... 91 3.13.1 Access to Infrastructure and Other Services.................................................................................. 91 3.13.2 Type of Toilets .............................................................................................................................. 91 3.13.3 Household’s Assets........................................................................................................................ 91 3.13.4 Sources of Light for Energy .......................................................................................................... 91 3.13.5 Sources of Energy for Cooking ..................................................................................................... 91 3.13.6 Roofing Materials.......................................................................................................................... 94 3.13.7 Access to Drink Water................................................................................................................... 94 3.13.8 Food Consumption Pattern ............................................................................................................ 95 3.13.8.1 Number of Meals per Day ........................................................................................... 95 3.13.8.2 Meat Consumption Frequencies .................................................................................. 95 3.13.8.3 Fish Consumption Frequencies.................................................................................... 95 3.13.9 Food Security................................................................................................................................. 97 3.13.10 Main Source of Cash Income ........................................................................................................ 97 PART IV: SHINYANGA PROFILES.................................................................................................................... 99 4.1 Region Profile.............................................................................................................................................. 99 4.2 District Profiles ......................................................................................................................................... 100 4.2.1 Bariadi .......................................................................................................................................... 100 4.2.2. Maswa .......................................................................................................................................... 102 4.2.3 Shinyanga Rural ........................................................................................................................... 104 4.2.4 Kahama......................................................................................................................................... 104 4.2.5 Bukombe....................................................................................................................................... 106 4.2.6 Meatu............................................................................................................................................ 108 4.2.7 Shinyanga Urban .......................................................................................................................... 110 4.2.8 Kishapu......................................................................................................................................... 111 ACRONYMS v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Wety Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Dry Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics, Tanzania Mainland and the Office of the Chief Government Statistician, Tanzania Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the President’s Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (data on household characteristics and livestock count were collected in 1993/1994 while data on crop area and production were collected in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Shinyanga region data disaggregated to district level. Due to numerous variables collected, the analysis is based on the most important smallholder variables. More variables can be found in the table of results annex. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Special thanks should go to all those who in one-way or the other contributed to the success of the survey. In particular, I would like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician, Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Finally, let me extend my sincere gratitude to all professional staff of the National Bureau of Statistics and Office of the Chief Government Statistician, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. I am also indepted to the respondents, particularly the heads of households, for spending much of their valuable time in providing data and all necessary information during enumeration. Certainly without their dedication, the census would not have been successful. Albina A. Chuwa Director General, National Bureau of Statistics EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Shinyanga region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Shinyanga region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Shinyanga region were 377,857 out of which 201,316 (53%) were involved in growing crops only, 2,310 (1%) rearing livestock only and 174,232 (46%) were involved in crop production as well as livestock keeping. In summary, Shinyanga region had 375,547 households involved in crop production and 176,542 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances. The region has a literacy rate of 59 percent. The highest literacy rate is in District Kishapu (65%), Shinyanga Urban (64%), Maswa (61%), Bukombe (60%), Shinyanga Rural (60%) and Meatu (60%). Kahama na Baridi districts have the lowest literacy rates of 59 and 56 percent Respectively. The literacy rate for the heads of households in the region was 59 percent. The number of heads of agricultural households with formal education in Shinyanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Shinyanga region 113,528 household members (59%) were involved in one off-farm income generating activity, 50,868 (26%) involved in two off-farm income generating activities and 28,310 (15%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 1,299,023 ha. The regional average land area utilised for crop production per crop growing household was only 3.4 ha. This figure is above the national average of 2.0 hectares. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ viii Planted Area The area planted with annual crops and vegetables was 960,250 hectares out of which 2,826 hectares (0.29%) were planted during Dry season and 957,423 hectares (99.71%) during Wety season. An estimated area of 591,416 ha (60% of the total planted area with annual and vegetable crops) was with cereals, followed by 67,809 hectares (7%) of pulses, 66,153 ha (7%) of oil seeds and nuts, 48,081 ha (5%) of roots and tubers, 1,421 ha (0.1%) of fruit and vegetables, 205,020 ha (21%) of cash crops. Maize Maize is the dominant annual crop grown in Shinyanga region and it had a planted area 3.4 times greater than Paddy, which had the second largest planted area. The area planted with maize constitutes 68 percent of the total area planted with annual food crops. Other crops in order of their importance (based on area planted) are Cotton, Paddy, Sorghum, Ground nuts, Beans, cassava, cowpeas, tomatoes, green gram, groundnuts and sweet potatoes. There was a decrease in maize production over the period 1995 to 1996 (52%), after which the production almost remained constant over the period 1996 to 97. Production gradually increased over the period 1997 to 1998 and remained constant over the period from 1998 to 1999 and thereafter declined over the period 1999 to 2003. The average area planted with maize per household was 1.06 hectares; however it ranged from 0.7 hectares in Shinyanga Urban district to 1.31 hectares in Bariadi district. Bariadi had the largest planted area of maize (101,952 ha) followed by Kahama (79,905 ha), Bukombe (64,833 ha), Shinyanga Rural (44,228 ha) , Maswa (35,159), Meatu (31,192) and Shinyanga Urban (7,505 ha) Paddy Paddy is the Second dominant cereal crop in terms of production in the region. The number of households growing Paddy in Shinyanga region during the wet season was 136,046 (36% of the total crop growing households in the region during the wet season). The total production of Paddy was 104,847 tonnes from a planted area of 118,916 hectares resulting in a yield of 0.88 t/ha • Sorghum Sorghum is the third most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Shinyanga region during the wet season was 59,619. This represents 16 percent of the total crop growing households in Shinyanga region. The total production of sorghum was 17,286 tonnes from a planted area of 65,868 hectares resulting in a yield of 0.26 t/ha. The district with the largest planted area of sorghum was Meatu (24,353 ha) followed by Kishapu (21,030 ha), Bariadi (9,971 ha) and Maswa (7,950 ha) (Map 3.15). The Largest planted area per household for sorghum was observed in Meatu (0.77 ha) and Kishapu (0.59 ha). There was a large reduction in the production of sorghum from 114,000 tonnes in 1995/96 to 17,000 tonnes in 2002/03 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ ix • Roots and Tuber Crops Production The Common Roots and Tuber Crops grown in Shinyanga Region were Sweet Potatoes and Cassava. The total production of both Cassava and Sweet Potatoes was 39,658 tonnes. Sweet Potatoes production was higher than that of Cassava in the region with a total production of 25,059 tonnes representing 63 percent of the total root and tuber crop production • Pulse Crops Production The total area planted with pulses was 66,153 hectares, of which 23,933ha were planted with Chick Peas (36% of the total area planted with pulses), followed by Beans (16,396 ha, 25%), Cow Peas (3,376 ha, 5%), Green Gram (2,898ha 4%) and Bambaranuts (1,382 ha, 2%). • Oil Seed Production The total production of oilseed crops was 31,568 tonnes, planted on an area of 65,985 hectares. Groundnuts was the most important oilseed crop with 64,188 ha (97% of the total area planted with oil seeds), followed by sunflower (2%) and simsim (1%). Fruit and Vegetables The total production of vegetables was 3,381 tonnes. The most cultivated vegetable crop was tomatoes with a production of 1,977 tonnes (58% of the total vegetables produced) followed by onions (503t, 15%) and Cabbages (461t, 14%). The production of the other vegetable crops was relatively small. Permanent Crops The planted area of smallholders with permanent crops was 53,420 hectares (5.2% of the area planted with annual and permanent crops in the region). The most important permanent crop in Shinyanga region is Mango which accounts for a planted area of 28,067.0 ha, (53% of the planted area of all permanent crops) followed by Pawpaw (6,337 ha, 12%), Sisal (5,719 ha, 11%), and Banana (3,763 ha, 11%). • Improved Seeds Use The planted area with improved seeds was 261,066 ha which represents 27 percent of the total area planted with the annual crops and vegetables. Cash Crops had the largest planted area with improved seeds (159,104 ha, 69% of the planted area with improved seeds) followed by Cereals crops (57,738 ha, 25%). Other crop types had insignificant area planted with improved seeds (Chart 3.42). Among the Cash Crops Cotton had the largest area of improved seeds application which was 155,842 ha 98% of area planted by cash crops. • Fertilizer Use The use of fertilisers on annual crops was very small with a planted area of only 171,943 ha (18% of the total planted area in the region). The planted area without fertiliser for annual crops was 785,481 hectares representing 82 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 137,161 ha which represents 14 percent of the total planted area (80% of the area planted with fertiliser application in the region). This was followed by Inorganic Fertilizers (20,380ha, 12% of the planted area with fertiliser and 2% of the total EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ x planted area in the region), Compost (14,404ha, 8% of the planted area with fertiliser and 2% of the total planted area in the region). The largest planted area with fertiliser (all types) was in Kahama district (60154 ha, 35.0% of the total planted area with fertilizer in the region, followed by Bariadi (27,350, 16%), Shinyanga Rural (20,901 12%), Bukombe (20,582 12%), Maswa (14,692 9%), Kishapu (14,010 8%) and Shinyanga Urban (4,188, 2%) Table 3.8 and (Charts 3.60 and 3.61). Irrigation The district with the highest proportion of area under irrigation with annual crops was Shinyanga Urban 5.5 percent of the planted area with annual crops in the District. This is followed by Kahama (3.2%), Shinyanga Rural (3.1%), Bariadi (2.7%) and Kishapu 2.1%. Other Districts had lower than 2% of the proportion of area under Irrigation Crop Storage The most important stored crop was maize with 284,899 households storing 101,693 tonnes as of 1st January 2004. This was followed by Paddy (112,839 households, 55,481t), Groundnuts/Bambaranuts (63,962 households, 10,223t) and Beans/Pulses (50,197 households, 5,247t). Other crops were stored in very small amounts Crop Marketing The number of households that reported selling crops was 219,317 which represents 58 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Maswa (79%) followed by Bariadi (66%), Meatu (59%), Kahama (59%), Bukombe (54%), Kishapu (59%), Shinyanga Rural (44%) and Shinyanga Urban (8%) (Chart 3.99 and Map 3.40). Agricultural Credit The census results shows that very few agricultural households (7,054, 2%) in Shinyanga region accessed credit, of which 5,402 (77%) were male-headed households and 1,651 (24%) were female headed households. The number of those who accessed credits was higher in Bariadi (31%) followed by Kahama (31%), Bukombe (12%) and Maswa (12%). Other Districts have less than 10% of those who accessed credits, ( Crop Extension Services The number of agricultural households that received crop extension was 104,252 (28% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Kishapu having a relatively high proportion of households that received crop extension messages (51%) followed by Meatu (47%), Kahama (36%), Shinyanga Urban (33%), Shinyanga Rural (27%), Bariadi (21%), and Bukombe (14%. Soil Erosion and Water Harvesting Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms in Shinyanga region was 15,199 which represent 4 percent of the total number of agricultural households in the region EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xi iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 2,604,105 which the largest population of Livestock in the Country regional wise. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 15.4 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Shinyanga region was 2,591,532 (92.6 % of the total number of cattle in the region), 1,375 cattle (0.1%) were dairy breeds and 11,198 cattle (7.3%) were beef breeds. Goats Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Shinyanga region ranked 11 out of the 21 regions with 4.4 percent of the total goats on the Mainland. The number of goat-rearing-households in Shinyanga region was 124,019 (33% of all agricultural households in the region) with a total of 1,277,929 goats giving an average of 10 head of goats per goat- rearing-household. Sheep Sheep rearing was the third important livestock keeping activity in Shinyanga region after cattle and goats. The region ranked 9 out of 21 Mainland regions and had 4 percent of all sheep on Tanzania Mainland. The number of sheep-rearing households was 58,545 (15% of all agricultural households in Shinyanga region) rearing 517,144 sheep, giving an average of 9 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 656 (0.2% of the total agricultural households) rearing about 3,266 pigs. This gives an average of 5 pigs per pig-rearing household. • Chicken The number of households keeping chicken was 257,044 raising about 2,979,590 chickens. This gives an average of 12 chickens per chicken-rearing household. In terms of total number of chickens in the country, Shinyanga region was ranked first for having the largest number of chicken out of the 21 Mainland regions. Use of Draft Power Use of draft animals to cultivate land in Shinyanga region is highly practiced with a total 246,196 (65%) agricultural households Practicing it. Kishapu, Shinyanga Rural and Bariadi Districts are the best in use of draft animals in farming practices with over 80% of all agricultural households in these districts using the method. The Percent of Agricultural households using this method in Maswa, Meatu and Shinyanga Urban was 79%, 78% and 86% respectively. The method is scarcely practiced in Kahama and Bukombe Districts. Fish Farming The number of households involved in fish farming in Shinyanga region was very small which was 430, representing 0.1 percent of the total agricultural households in the region. This Practice was only reported in Kahama District. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xii iv) Poverty Indicators • Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were Tarmac Road (68), Hospital (41), District Capital (39, Tertiary Market (34) Secondary School (19) Secondary Market (17), Primary Market (8), Health Clinic / Dispensary (8), All weather Road (7), Primary School (2), Feeder Road (2) Availability of Toilets A large number of rural agricultural households use traditional pit latrines (318,745 households, 84% of all rural agricultural households) 12,686 households (3%) use Flush Toilets and 2,450 households (1%) use Improved Pit Latrine. The remaining 474 household (0.13%) use other toilets facilities. However, 12,686 households (12%) in the region had no toilet facilities. Household Assets Bicycles are owned by most rural agricultural households in Shinyanga region with 246,531 households (65% of the agriculture households in the region) owning the asset. followed by Radios ( 192,251 households, 51%), iron (64,449 households, 17%), wheelbarrow (39,393 households, 10%), mobile phone (5,725 households, 2%), television/video (3,692 households, 0.96), vehicle (4,236 households, 1.1%) and landline phone (858 households, 0.23%) (Chart 3.152). • Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 81 percent of the total rural households using this source of energy followed by hurricane lamp (14%), Pressure lamp (3%), Firewood and Electricity (1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95 percent of all rural agricultural households in Shinyanga region. This is followed by charcoal (4%). The rest of energy sources accounted for 1 percent. These were bottled gas (0.05%), crop residues (0.64%), mains electricity (0.15%), livestock dung (0.26%), paraffin/kerosene (0.1%) and gas/biogas (0.05%) Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 35 percent of the rural agricultural households. This was closely followed by iron sheets (33%) and grass/mud (30%). Tiles (0.54%), (0.28%) and Concrete (0.06%) roofing style were scarcely used in the region. • Access to Drinking Water The main source of drinking water for rural agricultural households in Shinyanga region was unprotected Wells (33 percent of households use unprotected wells during the wet season and 31 percent of the households during the dry seasons). This is followed by protected wells (26% and 28% of households for wet and dry seasons respectively), Surface water (16% of households during the wet season and 19% in the dry season), Piped water (12% of households in the wet season and 13% EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xiii during dry season). Other sources of drinking water like uncovered rain water catchments, Unprotected/protected Spring, Bottled Water, Water vendor and Tank truck are scarcely used in the region Number of Meals per Day The majority of households in Shinyanga region normally have 3 meals per day (54 percent of the households in the region). This is followed by 2 meals per day (44 percent) and 1 meal per day (2 percent). A small number of Agricultural Households 0.27 percent normally have 4 meals per day. • Food Security In Shinyanga region, 134,001 households (35% of the total agricultural households in the region) said they seldom experienced problems in satisfying the household food requirement. However 55,062 (14%) said they often experience problems, 38,789 always experienced problems and 6.4 percent sometimes had problems in satisfying the household food requirement. About 33 percent of the agricultural households said they did not experience any food sufficiency problems. Main Source of Cash Income The main cash income of the households in Shinyanga region was from selling food crops (39.2 percent of smallholder households), followed by Sales of Cash Crops (31.8), Casual Cash earnings 13%), businesses income and Sales of Livestock each 4.9%. Other Means of income were Wages and Salaries (2.1%), Cash Remittances (1.1%), Sales of Forestry Products (1%), Sales of Livestock Products (1%) a and cash remittances (1%) and Fishing (1%)., ILLUSTRATIONS ________________________________________________________________________________________________________________________ xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size........................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season.................................................................................... 22 3.3 Area, Production and Yield of Root and Tuber Crops by Season.................................................................... 27 3.4 Area, Production and Yield of Pulse by Season .............................................................................................. 28 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season ................................................................. 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season..................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season........................................................................ 37 3.8 Land Clearing Methods.................................................................................................................................... 48 3.9 Planted Area by Type of Fertiliser Use and District – Long and Dry Season.................................................. 51 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Wety Season ................................................................................................................................... 51 3.11 Number of Households Storing Crops by Estimated Storage Loss and District.............................................. 62 3.12 Reasons for Not Selling Crop Produce ............................................................................................................ 65 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 66 3.14 Access to Inputs............................................................................................................................................... 69 3.15 Number of Households and Chickens Raised by Flock Size............................................................................82 3.16 Number of Other Livestock by Type of Livestock and District....................................................................... 84 3.17 Mean distances from dwellings to infrastructure and services by districts...................................................... 91 3.18 Number of Households by Number of meals the Household normally takes per Day and District................. 95 List of Charts 3.1 Agricultural Households by Type of Holdings ................................................................................................ 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ........................................... 11 3.3 Percentage Distribution of Population by Age and Sex in 2003...................................................................... 15 3.4 Percentage Literacy Level of Household Members by District ....................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District............................................................................ 15 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status ................................................................................................. 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment .................................................. 16 3.9 Number of Households by number of members with Off Farm Income – Shinyanga Region ........................ 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ................................ 17 3.11 Utilized and Usable Land per Household by District ...................................................................................... 17 3.12 Land Area by Type of Land Use...................................................................................................................... 18 3.13 Area Planted with Annual Crops (ha) by Season............................................................................................. 18 3.14 Area Planted with Annual Crops by Season and Region................................................................................. 18 3.15 Area Planted with Annual Crops per Household by Season and District ........................................................ 20 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................. 20 3.17a Planted Area per Household by Selected Crops................................................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type.................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season...................................................................... 22 3.19 Area Planted and Yield of Major Cereal Crops ............................................................................................... 22 3.20 Time Series Data on Maize Production – Shinyanga Region .......................................................................... 23 3.21 Maize: Total Area Planted and Planted Area per Household by District......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Shinyanga Region................................................................ 23 3.23 Total Planted Area and Area of Paddy per Household by District................................................................... 26 3.24 Time Series Data on Paddy Production – Shinyanga Region .......................................................................... 26 3.25 Time Series of Paddy Planted Area and Yield – Shinyanga Region................................................................ 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District ................................................................. 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................. 26 3.28 Area planted with Cassava during the census/survey years..............................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District ....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District.............................................................. 28 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xiii 3.31 Total Area Planted and Planted Area per Household by District..................................................................... 28 3.32 Area Planted and Yield of Major Pulse Crops................................................................................................. 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ........................................... 30 3.34 Area Planted per Bean Growing Household by District (Wety Season Only)................................................. 30 3.35 Time Series Data on Bean Production – Shinyanga Region............................................................................ 30 3.36 Time Series of Beans Planted Area and Yield - Shinyanga............................................................................. 32 3.37 Area Planted and Yield of Major Oil Seed Crops............................................................................................ 32 3.38 Time Series Data on Groundnut planted area – Shinyanga Region................................................................. 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Wety Season Only)........................................ 33 3.42 Area Planted and Yield of Fruit and Vegetables.............................................................................................. 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District .................................... 35 3.44 Area Planted per Tomato Growing Household by District (Dry Season Only) ............................................... 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District .................................... 37 3.47 Area planted with Annual Cash Crops............................................................................................................. 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District.................................. 40 3.49 Area Planted for Annual and Permanent Crops ............................................................................................... 40 3.50 Area Planted with the Main Permanent Crops................................................................................................. 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District ........................ 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District.......................... 45 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District ................. 48 3.56 Number of Households by Method of Land Clearing during the Wety Season............................................... 48 3.57 Area Cultivated by Cultivation Method............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District................................................................................... 50 3.59 Planted Area of Improved Seeds – Shinyanga..................................................................................................50 3.60 Planted Area with Improved Seed by Crop Type ............................................................................................ 50 3.61 Percentage of Crop Type Planted Area with Improved Seed – Annuals.......................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer........................................................................................ 51 3.63 Area of Fertilizer Application by Type of Fertilizer and District .................................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop Type - Wety Season.............................................................. 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District....................................................... 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals ...................................................................... 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type ............................................................... 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District ....................................................... 53 3.68a Planted Area with Compost by Crop Type ...................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type................................................................................ 53 3.68c Proportion of Planted Area Applied with Compost by District ....................................................................... 53 3.69 Planted area (ha) by Pesticide use.................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type..................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides.................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Wety Season............................. 54 3.73 Planted Area applied with herbicides by Crop Type........................................................................................ 55 3.74 Percentage of Crop Type Planted Area applied with herbicides...................................................................... 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Wety Season............................... 55 3.76 Planted Area applied with Fungicides by Crop Type ...................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides..................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Wety Season .............................. 56 3.79 Area of Irrigated Land ..................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District........................................................ 57 3.81 Time Series of Households with Irrigation – Shinyanga ................................................................................. 57 8.82 Number of Households with Irrigation by Source of Water ............................................................................ 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................. 57 3.84 Number of Households with Irrigation by Method of Field Application......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type ............................................................................ 59 3.86 Number of households by Storage Methods.................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xiv 3.88 Normal Length of Storage for Selected Crops................................................................................................. 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District................................................. 62 3.90 Number of Households by Purpose of Storage and Crop Type ....................................................................... 62 3.91a Percentage of Households Processing Crops by District ................................................................................. 63 3.91b Percent of Households Processing Crops by District....................................................................................... 63 3.92 Percent of Crop Processing Households by Method of Processing ................................................................. 63 3.93 Percent of Households by Type of Main Processed Product ........................................................................... 63 3.94 Number of Households by Type of By-product............................................................................................... 64 3.95 Use of Processed Product................................................................................................................................. 64 3.96 Percentage of Households Selling Processed Crops by District ...................................................................... 64 3.97 Location of Sale of Processed Products........................................................................................................... 64 3.98 Percent of Household selling Processed Products by Outlets for Sale and Distance........................................65 3.99 Number of Crop Growing Households Selling Crops by District.................................................................... 65 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 65 3.101 Percentage Distribution of Households Receiving Credit by Main Sources.................................................... 66 3.102 Number of Households Receiving Credit by Main Source of Credit and District........................................... 66 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit................................................... 66 3.104 Reasons for Not using Credit (% of Household).............................................................................................. 66 3.105 Number of Households Receiving Extension Advice...................................................................................... 67 3.106 Number of Households Receiving Extension by District ................................................................................ 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................ 67 3.108 Number of Households Receiving Extension by Quality of Services.............................................................. 67 3.109 Number of Households by Source of Inorganic Fertiliser ............................................................................... 69 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser................................................. 69 3.111 Number of Households by Source of Improved Seed...................................................................................... 70 3.112 Number of Households reporting Distance to Source of Improved Seed ........................................................ 70 3.113 Number of Households by Source of Insecticide/Fungicide............................................................................ 70 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides.......................................... 70 3.115 Number of Households with Planted Trees by District.................................................................................... 71 3.116 Number of Planted Trees by Species ................................................................................................................71 3.117 Number of Trees Planted by Smallholders by Species and District................................................................. 71 3.118 Number of Trees Planted by Location ............................................................................................................. 71 3.119 Number of Households by purpose of Planted Trees....................................................................................... 72 3.120 Number of Households with Erosion Control/Water Harvesting Facilities..................................................... 72 3.121 Number of Households with Erosion Control/Water Harvesting Facilities by District................................... 72 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................ 72 3.123 Total Number of Cattle ('000') by District ....................................................................................................... 74 3.124 Numbers of Cattle by Type and District .......................................................................................................... 74 3.125 Cattle Population Trend................................................................................................................................... 76 3.126 Improved Cattle Population Trend................................................................................................................... 76 3.127 Total Number of Goats ('000') by District ....................................................................................................... 76 3.128 Goat Population Trend..................................................................................................................................... 78 3.129 Total Number of Sheep by District.................................................................................................................. 78 3.130 Sheep Population Trend................................................................................................................................... 80 3.131 Total Number of Pigs by District..................................................................................................................... 80 3.132 Pig Population Trend ....................................................................................................................................... 80 3.133 Total Number of Chicken by District .............................................................................................................. 82 3.134 Chicken Population Trend ............................................................................................................................... 82 3.135 Number of Improved Chicken by Type and District.........................................................................................84 3.136 Improved Chicken Population Trend............................................................................................................... 84 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 84 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 86 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 86 3.140 Number of Households by Distance to Veterinary Clinic................................................................................ 87 3.141 Number of Households by Distance to Veterinary Clinic and District............................................................ 87 3.142 Number of Households by Distance to Village Watering Point ...................................................................... 87 3.143 Number of Households by Distance to Watering Point and District................................................................ 87 3.144 Number of Households using Draft Animals................................................................................................... 87 3.145 Number of Households using Draft Animals by District................................................................................. 87 3.146 Number of Households using Organic Fertiliser.............................................................................................. 88 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xv 3.147 Area of Application of Organic Fertiliser by District ...................................................................................... 88 3.148 Number of Households Practicing Fish Farming – Shinyanga ........................................................................ 88 3.149 Number of Households Practicing Fish Farming by District – Shinyanga ...................................................... 91 3.150 Fish Production................................................................................................................................................ 91 3.151 Agricultural Households by Type of Toilet Facility ........................................................................................ 92 3.152 Percentage Distribution of Households Owning the Assets............................................................................. 92 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting .............................................92 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................ 92 3.155 Percentage Distribution of Households by Type of Roofing Material............................................................. 94 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District................................................. 94 3.157 Percentage of Households by Main Source of Drinking Water and Season .................................................... 94 3.158 Percentage of Households by Distance to Main Source of Water and Season................................................. 94 3.159 Number of Agriculture Households by Number of Meals per day .................................................................. 95 3.160 Number of Households by Frequency of Meat and Fish Consumption............................................................95 3.161 Percentage Distribution of the Number of Households by Main Source of Income........................................ 97 List of Maps 3.1 Total Number of Agricultural Households by District..................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District........................................................ 12 3.3 Number of Crop Growing Households by District .......................................................................................... 13 3.4 Percent of Crop Growing Households by District ........................................................................................... 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District.......................................... 14 3.6 Percent of Crop and Livestock Households by District ................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ....................................................................... 22 3.8 Total Planted Area (annual crops) by District...................................................................................................22 3.9 Area planted and Percentage During the Dry Season by District .................................................................... 23 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.................................. 23 3.11 Planted Area and Yield of Maize by District................................................................................................... 26 3.12 Area Planted per Maize Growing Household .................................................................................................. 26 3.13 Planted Area and Yield of Beans by District ................................................................................................... 27 3.14 Area Planted per Beans Growing Household................................................................................................... 27 3.15 Planted Area and Yield of Sorghum by District .............................................................................................. 28 3.16 Area Planted per Sorghum Growing Household.............................................................................................. 28 3.17 Planted Area and Yield of Groundnuts by District .......................................................................................... 32 3.18 Area Planted per Groundnuts Growing Household.......................................................................................... 32 3.19 Planted Area and Yield of Tomato by District................................................................................................. 33 3.20 Area Planted per Tomato Growing Household................................................................................................ 33 3.21 Planted Area and Yield of Cassava by District................................................................................................ 35 3.22 Area Planted per Cassava Growing Household ............................................................................................... 35 3.23 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................ 49 3.24 Area Planted and Percent of Total Planted Area with Irrigation by District.................................................... 49 3.25 Percent of households storing crops for 3 to 6 weeks by district..................................................................... 50 3.26 Number of Households and Percent of Total Households Selling Crops by District....................................... 50 3.27 Number of Households and Percent of Total Households Receiving Crop Extension Services by District.... 57 3.28 Number and Percent of Crop Growing Households using Improved Seed by District ....................................57 3.29 Number and percent of smallholder planted trees by district........................................................................... 58 3.30 Cattle population by District as of 1st Octobers 2003 ......................................................................................62 3.31 Cattle Density by District as of 1st October 2003.............................................................................................62 3.32 Goat population by District as of 1st Octobers 2003 ....................................................................................... 63 3.33 Goat Density by District as of 1st October 2003 ............................................................................................. 63 3.34 Sheep population by District as of 1st Octobers 2003 ..................................................................................... 67 3.35 Sheep Density by District as of 1st October 2003 ........................................................................................... 67 3.36 Pig population by District as of 1st Octobers 2003.......................................................................................... 68 3.37 Pig Density by District as of 1st October 2003.................................................................................................68 3.38 Number of Chickens by District as of 1st October 2003 ................................................................................. 69 3.39 Density of Chickens by District as of 1st October 2003.................................................................................. 69 3.40 Number and Percent of Households Infected with Ticks by District............................................................... 74 3.41 Number and Percent of Households Using Draft Animals by District ............................................................ 74 3.42 Number and Percent of Households Using Farm Yard Manure by District..................................................... 75 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xvi 3.43 Number and Percent of Households using Compost by District...................................................................... 75 3.44 Number and Percent of Households Practicing Fish Farming by District ........................................................77 3.45 Number and Percent of Households without Toilets by District...................................................................... 77 3.46 Number and Percent of Households using Grass/Leaves for roofing material by District .............................. 83 3.47 Number and Percent of Households eating 3 meals per day by District...........................................................83 3.48 Number and Percent of Households eating Meat Once per Week by District ..................................................84 3.49 Number and Percent of Households eating Fish Once per Week by District................................................... 84 3.50 Number and percent of Households Reporting food insufficiency by District ................................................ 85 INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Shinyanga region is situated at the North of Tanzania between 20 and 30degrees below the Equator and 310 – 350 degrees East of the Greenwich Meridian. Shinyanga shares borders with Mwanza Region to the North, Tabora and Singida regions to the South, Kigoma region to the West and the Arusha region to the East. The region comprises eight districts namely Bariadi, Maswa, Kishapu, Shinyanga Rural, Shinyanga Urban, Meatu, Kahama, and Bukombe. The region headquarters is located in Shinyanga District. 1.3 Land Area The region has an area of 19,483 square kilometers 1.4 Climate 1.4.1 Temperature The dominant climate is tropical type of climate with clearly distinguished rainy and dry seasons. The average rainfall ranges from 600mm to 900mm. The rainy season usually starts between mid – October and December, and ends in May. 1.4.2 Rainfall Shinyanga Region has a tropical type of Climate with clearly distinguished rainy and dry seasons. The average rainfall ranged from 600mm to 900mm. The rainy season usually starts between mid October and December and ends in May. 1.5 Population According to the 2002 Population and Housing Census, there were 2,805,580 inhabitants in Shinyanga region. The population of Shinyanga region ranked 2nd of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The Economy of Shinyanga is predominantly based on subsistence agriculture and livestock rearing. The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 667,886 million with a per capita income of shillings 238,056. The region held 3rd position among regions on GDP and contributed about 6.80 percent to the national GDP1 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 2 Shinyanga region has mineral deposits of Diamond and Gold situated at Mwadui Village and Kahama District Respectively. The Main cash crops are cotton and tobacco while the main food crops are maize, paddy, sorghum, millet, Cassava, beans and sweet potatoes. Livestock reared are Cattle, sheep and goats, with chicken mostly dominated by indigenous bread. Modern diary farming and poultry keeping are confined to urban centers. Industrial activities mostly include cotton ginning, cotton seed oil extraction and small scale industries. Shinyanga Region is well served with communication network with the rest of the country by road and railway lines. There is an airport which is situated in shinyanga municipality. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 237 villages were from Shinyanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 5 • Livestock • Livestock products • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 6 Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 7 In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Shinyanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 8 training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff was used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 9 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 10 Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Household Characteristics _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 11 3. CENSUS RESULTS This part of the report presents the results of the census for Shinyanga region, based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results for establishment of trend and time series analysis. This include comparison with the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Survey, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation is divided into four main sections which are household characteristics, crop results, livestock results and Poverty indicators. Comparison to previous census and surveys has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Shinyanga region was 377,857. The largest number of agriculture households was in Kahama (81,217) followed by Bariadi (77,572), Bukombe (53,240), Shinyanga Rural (45,263) Maswa (43,252) Kishapu (35,624), Meatu (31,492) and Shinyanga Urban (10,198) (Map 3.1). Most households (201,316, 53.3%) were involved in growing crops only, 174,232 (46%) were involved in crop production as well as livestock keeping and 2,310 (0.6%) rearing livestock only (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Shinyanga region indicates that most of the agricultural households in all districts ranked annual crop farming as an activity that contributes to most of their livelihood followed by Livestock Keeping and Off-farm income (Table 3.1). Other activities with low contribution to livelihood were Tree/forest resources (4), Permanent crop Farming (5), Remittances (6) and Fishing/ Hunting (7) Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 1 6 3 2 4 7 5 Maswa 1 4 2 3 6 7 5 Shinyanga Ru 1 4 3 2 5 7 6 Kahama 1 5 2 3 6 7 4 Bukombe 1 4 2 3 5 7 6 Meatu 1 6 2 3 5 7 4 Shinyanga Urb 1 4 2 3 5 7 6 Kishapu 1 6 2 4 5 7 3 Total 1 5 2 3 6 7 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity Chart 3.1 Agriculture Households by Type - Shinyanga Crops and Livestock, 174,231.6, 46% Livestock Only, 2,310.1, 1% Crops Only, 201,315.6, 53% Shinyanga Urban Shinyanga Rural Bukombe Kishapu Bariadi Meatu Maswa Kahama 13 18 21 11 27 33 23 45 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Shinyanga Rural Shinyanga Urban Kahama Kishapu Bukombe Maswa Meatu Bariadi 81,217 45,263 53,240 35,624 31,492 43,252 77,572 10,198 64,000 > 48,000 to 64,000 32,000 to 48,000 16,000 to 32,000 0 to 16,000 Map 3.01 SHINYANGA Toatal Number of Agricultural Households by District Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.02 SHINYANGA Number of Agricultural Households Per Square Kilometer of Land by District RESULTS 12 Shinyanga Rural Shinyanga Urban Kishapu Kahama Maswa Bariadi Meatu Bukombe 46.8% 45.2% 52.7% 50.9% 43.9% 60.6% 64.9% 41.1% 60 to 80 45 to 60 30 to 45 15 to 30 0 to 15 Shinyanga Rural Shinyanga Urban Kishapu Maswa Kahama Meatu Bariadi Bukombe 21,182 16,108 13,820 22,774 39,487 34,546 49,208 4,190 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.03 SHINYANGA Number of Crop Growing Households by District Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.04 SHINYANGA Percent of Crop Growing Households by District RESULTS 13 Shinyanga Rural Shinyanga Urban Kishapu Bukombe 53% 48.9% 46.6% 56% 53.4% 39.2% 34.7% Kahama Maswa Meatu Bariadi 51.2% 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 Shinyanga Rural Shinyanga Urban Kahama Bariadi Maswa Kishapu Bukombe 15 11 14 5 8 14 8 Meatu 18 16 to 20 12 to 16 8 to 12 4 to 8 0 to 4 Map 3.05 SHINYANGA Number of Crop Growing Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Per square Km Percent of Crop and Livestock Households Percent of Crop and Livestock Households Map 3.06 SHINYANGA Percent of Crop and Livestock Households by District RESULTS 14 RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 15 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Shinyanga region was 323,921 (86%) of the total regional agricultural households) whilst the female-headed households were 53,936 (14%) of the total regional agricultural households). The mean age for household heads was 46 years (42 years for male heads and 51 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys ‘years shows that there has been no significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Shinganga region had a total rural agricultural population of 2,426,406 of which 1,240,1827 (51%) were males and 1,186,224 (49%) were females. Whereas age group 0-14 constituted 46 percent of the total rural agricultural population, age group 15–64 (active population) was only 50 percent. Shinyanga region had an average household size of 4 with Shinyanga Urban district having the lowest household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Chart 3.3 Percent Distribution of Population by Age and Sex - Shinyanga 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head - 25 50 75 100 Type of Holding (000') NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 Year Percent of Househol Male Headed (%) Female Headed (%) RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 16 Literacy Level for Household Members Shinyanga region had a total literacy rate of 59 percent. The highest literacy rate was found in Kishapu district (64.6%) followed by Shinyanga Urban district (64.2%) and Maswa district (61%). Bariadi and Kahama districts had the lowest literacy rates of 55 and 58 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 59 percent. The literacy rates for the male heads was 65 percent and that of female heads was 26 percent. Literacy rate of Male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Bariadi (68%) followed by Maswa (60%). Shinyanga Rural, Kahama and Bukombe had a literacy rate of 59%). The lowest literacy rates among heads of households were recorded in Kishapu (54%), Shinyanga Urban (54%) and Meatu (56%) districts (Chart 3.5). Chart 3.4 Percent Literatecy Level of Household Members by District - 10 20 30 40 50 60 70 80 90 100 Kishapu Shinyanga Urb Maswa Bukombe Shinyanga Rural Meatu Kahama Bariadi District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Shinyanga - 10 20 30 40 50 60 70 80 90 100 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percen Male Female Total Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent Attending School Completed Never Attended to School Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 36% Attending School 27% Never Attended to School 37% RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 17 Educational Status Information on educational status was collected from individual agricultural households. The results show that 36 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 27 percent were still attending school. Those who have never attended school were 37 percent (Chart 3.6). Agricultural households in Kishapu district had the highest percentage (38%) of population aged 5 years and above who had completed different levels of education. This was followed by Shinyanga Rural and Bukombe districts with 37.4 and 37.3 percent respectively. Meatu and Shinyanga Urban districts had the lowest percentages of 34.1 and 34.2 respectively (Chart 3.7). The number of heads of agricultural households with Primary education in Shinyanga region was 210,174 (56%), those with Post Primary education were 10,525 (3%) and those with only adult education were 4,332 (1%). The number of those who were reported to have no education at all was 152,825 (40%) (Chart 3.8). With regard to the heads of agricultural households with no education in Shinyanga Region, Kahama district had the highest percentages (22.6%). This was followed by Bariadi (20%), Maswa (13%), Shinyanga Rural (12%) and Bukombe, Meatu, Kishapu, both with (10%) of agricultural households with no education. The least number of households with no education was found in Shinyanga Urban (3%). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. In Shinyanga region 112,528 households (59%) had only one member aged 5 and above involved in off-farm income generating activity, 50,868 households (26%) had two members involved in off- Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment No Education, 152,826, 40% Primary Education, 210,174, 56% Post Primary Education, 10,525, 3% Adult Education, 4,332, 1% Chart 3.9 Number of Households by Number of Members with Off-farm income generating activities Two Members, 50,868 , 26% One Member 113,528 , 59% More than Two Members, 28,310 , 15% Chart 3.10 Percentage Distribution of Agricultural Households by Number of household members with Off- farm Activities 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Maswa Kahama Meatu Bariadi Shinyanga Urb Bukombe Kishapu Shinyanga Rur Percent More Than Two Two One None RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 18 Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Kishapu Meatu Maswa Bukombe Kahama Bariadi Shinyanga Rural Shinyanga Urban Districts Area/household (ha) 84 85 86 87 88 89 90 91 92 93 94 Percentage utilized Area utilised (Ha) Total usable area Percent Utilisation farm income generating activities and 28,310 households (15%) had more than two members involved in off-farm income generating activities (Chart 3.9). Shinyanga Rural district had the highest percentage of agriculture households with off-farm income (over 70% of total agriculture households in the district). Other districts with high percents of agriculture households with off-farm income were Kahama (60%), Bariadi (85%) and Shinyanga Urban (58%). Bukombe and Meatu districts had the lowest percent of agriculture households with off-farm income (31% and 33% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Kahama (30%). Kishapu and Bukombe districts had very few households with more than one member having off-farm income (14% and 13% respectively) (Chart (chart 3.10). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 1,468,142 ha. The regional average land area utilised for agriculture per household was 3.4 ha. This figure is above the national average which is estimated at 2.0 hectares. About ninety percent of the total land available to smallholders was utilised. Only 7.5 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 19 There were large differences in land area utilised per household between districts with Kishapu and Shinyanga Urban utilizing between 5.6 and 2.2 ha per household. The percentage utilized of the usable land per household was highest in Maswa (93%) and lowest in Kahama (87%). 3.2.2 Types of Land Use The area of land under temporary monocrop was 753,616 hectares (51% of the total land available to smallholders in Shinyanga), followed by temporary mixed crops (233,347 ha, 16%), area under pasture (121,381 ha, 8%), area of uncultivated usable land 108,572 ha, 7%) and area under fallow 105,297 ha 7%. The area under permanent mono and permanent mixed crops was very small about 1% of the total land area. (Chart 3.12) 3.3 Annual Crop and Vegetable Production Shinyanga region has a unimodal rainfall pattern with the rain starting in November and ending in March. With the exception of some irrigated annual crops and vegetables grown in the dry season, the rest of the crops are grown during the wet season. The quantity of crops produced in both seasons will be used as a basis for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 960,250 hectares out of which 957,423 hectares (99.71%) were planted during Wet season and 2,826 hectares (0.29%) during Dry season. The Wet Season is the most important agricultural season in the region for agricultural productivity. Because of this, the analysis in this report will be restricted to the information on Wet season, (Chart 3.13). The average area planted per household was 2.5 ha (Chart 3.14). Chart 3.12 Land Area by Type of Use 0.2 0.4 0.8 1.4 1.8 2.3 2.9 7.2 7.4 8.3 51.3 15.9 - 200,000 400,000 600,000 800,000 Area under P lanted Trees Area under P ermanent Mono Crops Area under P ermanent Mixed Crops Area Rented to Ot hers Area Unusable Area under Nat ural Bush Area under P ermanent / Annual Mix Area under Fallow Area of Uncultivat ed Usable Land Area under P asture Area under Temporary Mixed Crops Area under Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (Hectares) Wet Season, 957,423.30 , 99.71% Dry Season, 2,826.30 , 0.29% Chart 3.14 Average Area Planted per household by District 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Shinyanga Urban Kahama Bariadi Shinyanga Rural Meatu Bukombe Maswa Kishapu Planted Area (ha) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 20 The districts with the largest area planted per household were Kishapu (3.4 ha) followed by Maswa (3.0 ha), Bukombe (2.6 ha), Meatu (2.5 ha), Shinyanga Rural (2.4 ha), Bariadi (2.4 ha) and Kahama (2.2 ha). The district with the smallest average area planted per household was Shinyanga Urban (1.5 ha). The crop type with the largest planted area was cereals 591,416 ha (62% of the total area planted with annuals). This was followed by cash crops (205,020 hectares, 21%), oil Seeds and oil nuts (66,153 hectares, 6.7%), pulses (48,130 hectares, 5%), roots and tubers (48,081 hectares, 5%) and fruit and vegetables (1,421 hectares, 0.1%). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether it is annual or permanent. The second section contains a more detailed analysis of production based on crop types. 3.3.2 Crop Importance Maize was the dominant food crop grown in Shinyanga region and it had a planted area 3.4 times greater than Paddy. The area planted with maize constitutes 41.7 percent of the total area planted with annual crops in the region. Other annual crops in order of their relative importance in the region (based on area planted) include Cotton 199,390 ha, Sorghum 65,917 ha, Groundnuts 64,355 ha, and Beans 38,944 ha. Other crops planted in Shinyanga Region were Sweet Potatoes 27,601 ha, Chick Peas 23,933 ha, Cassava 19,235 ha, Bulrush Millet 6,024 ha, Tobacco 5,630 ha, Cowpeas 3,376 ha, Green Gram 2,898 ha, Sunflower 1,434 ha, Bambaranuts 1,382 ha. A small amount of Yams 641 ha, Irish Potatoes 562 ha, Tomatoes 524 ha, Simsim 364 ha, Finger Millet 289 ha, Onions 57 ha, Egg Plant 203 ha, Radish 199 ha, Cabbage 104 ha, Amaranths 74 ha, Mung Beans 64 ha, Cocoyam 41 ha, Pumpkins 26 ha, Chart 3.16 Planted Area (ha) for the Main Crops, SHINYANGA 0 100,000 200,000 300,000 400,000 Maize Cotton Paddy Sorghum Groundnuts Beans Sweet Potatoes Chich Peas Cassava Bulrush Millet Tobacco Cowpeas Sunflower Bambaranuts Crop Planted Area. (ha) Chart 3.18: Percentage Distribution of Area Planted with annual crops by Crop types Fruit & Vegetables 0% Cereals 60% Roots & Tubers 5% Oil Seeds & Oil Nuts 7% Pulses 7% Cash Crops 21% Chart 3.17 Planted Area (ha) per Household by Selected Crop - Shinyanga - 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 Chich Peas Bulrush Millet Cotton Maize Sorghum Tobacco Paddy Sunflower Cassava Groundnuts Green Gram Beans Cowpeas Bambaranuts Crop Planted Area (ha) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 21 Cucumber 23 ha and Chillies 10 ha are also grown in the region (Chart 3.16). Other annual crops are grown in minor quantities. Chart 3.17 shows the area planted per household growing selected crops. Households that grew Chick Peas, Bulrush Millet and Cotton have a larger planted area per household than those growing other crops. Vegetable crops have smaller planted areas per household than cereals, roots and tubers and oilseed crops. 3.3.3 Crop Types Cereals are the main crops grown in Shinyanga region. The area planted with cereals was 591,416 ha (60% of the total planted area), followed by Cash Crops with 205,898 ha (21%), Pulses 67,809 ha (6.9%), Oil Seeds & Nuts 66,153 (6.8%) and Roots and Tubers 48,081 ha (4.9%). Fruits and Vegetables were scarcely grown in Shinyanga, having 1,421 ha 0.1 % of the total Planted Area. The main cash crop was cotton but a small amount of tobacco (5,630 ha) was also grown (Chart 3.18). Almost all crops are grown in the wet season and only a few crops are also grown in dry season. The dry season production was therefore very small, it is inappropriate to make detailed comparisons between the two seasons. 3.3.4 Cereal Crop Production The total production of cereals was 316,187 tonnes. Maize was the dominant cereal crop at 191,402 tonnes which was 61 percent of total cereal crops produced, followed by paddy 104,847 tonnes (33%), sorghum 17,269 tonnes (5%), Bulrush Millet (0.8%) and finger millet (0.04%). The total area planted with cereals during the year was 591,416 ha, of which 589,543 ha (99.7%) was planted during the wet season and 1,873 ha (0.3%) was planted in dry season. The Wet season accounts for 99.6 percent of the total cereals produced in both seasons. Maize was dominant and it represented 67.6 percent of the total area planted with cereal crops, then followed by Paddy (20%), sorghum (11%), bulrush millet (1%) and finger millet (0.4%) (Chart 3.19A, Table 3.2). The yield of paddy was 882 kg/ha, followed by Finger Millet 481Kg/ha, Maize 478Kg/ha, Bulrush Millet 430kg/ha and Sorghum 262 kg/ha, (Chart 3.19B). Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 1,541 647 420 398,729 190,755 478 400,270 191,402 478 Paddy 244 439 1,802 118,673 104,408 880 118,916 104,847 882 Sorghum 63 14 228 65,854 17,255 262 65,917 17,269 262 Bulrush Millet 26 38 1,482 5,998 2,491 415 6,024 2,530 420 Finger Millet 0 0 0 289 139 481 289 139 481 Total 1,873 1,139 589,543 315,047 591,416 316,187 Chart 3.19A Area Planted of Major Cereal Crops 0 150,000 300,000 450,000 Maize Paddy Sorghum Bulrush Millet Finger Millet Area Planted (h Chart 3.19B Yield of Major Cereal Crops 0 300 600 900 Maize Paddy Sorghum Bulrush Millet Finger Millet Yield (Kg/ha) . Kahama Shinyanga Urban Meatu Maswa Kishapu Shinyanga Rural Bariadi Bukombe 86.9% 92.1% 92.7% 91.1% 89.7% 90.1% 90.2% 90.4% 91.7 to 92.7 90.5 to 91.7 89.3 to 90.5 88.1 to 89.3 86.9 to 88.1 Shinyanga Rural Maswa Bariadi Meatu Kishapu Kahama Shinyanga Urban Bukombe 197,060ha 94,952ha 182,648ha 134,521ha 121,691ha 101,227ha 112,392ha 15,759ha 160,000 to 200,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Map 3.07 SHINYANGA Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Area Tanzania Agriculture Sample Census Percent of Utilized Land Area Planted Area (ha) Planted Area (ha) Map 3.08 SHINYANGA Total Planted Area With Annual Crops by District RESULTS 22 Shinyanga Urban Kishapu Bariadi Maswa Shinyanga Rural Kahama Bukombe 11,720ha 66,491ha 119,017ha 55,971ha 53,105 65,240ha 109,652ha 86,432ha 2.1% 11.7% 21% 9.9% 11.5% 9.4% 19.3% 15.2% Meatu 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Shinyanga Rural Shinyanga Urban Maswa Kishapu Bariadi Meatu Kahama Bukombe 195ha 109ha 119,017ha 1,651ha 0ha 0ha 291ha 580ha 1.2% 0.1% 0% 1.2% 0% 0% 0.3% 0.5% 96,000 to 120,000 72,000 to 96,000 48,000 to 72,000 24,000 to 48,000 0 to 24,000 Map 3.09 SHINYANGA Area planted and Percentage During the Short Rainy Season by District Tanzania Agriculture Sample Census Area Planted (ha) Percent of Area Planted Planted Area (ha) Planted Area Cereal Crops Map 3.10 SHINYANGA Area Planted with Cereals and Percent of Total Land Planted With Cereals by District Area Planted (ha) Percent of Planted Area Cereal Crops RESULTS 23 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 24 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Shinyanga region during the wet season was 351,234 (93.7% of the total number of households growing annual crops in the region during the wet season). The total production of maize was 191,402 tonnes from a planted area of 400,270 hectares resulting in a yield of 0.48 t/ha. Chart 3.20 presents the maize production trend. The yield declined over the entire eight year period from 1995 to 2003. Alongside the decrease in yield the production also more or less declined over the entire period except in 1999 when production increased somewhat and remained the same level up to the year 2000 before declining over the remaining period up to the year 2003. The mentioned increase in production was due to a substantial increase in the planted area over the period 1997 to 2000 after which it also declined over the remaining period up to the year 2003, (Chart 3.20). The average area planted with maize per household was 1.1 hectares; however it ranged from 0.7 hectares in Shinyanga Urban district to 1.31 hectares in Bariadi district (Map 3.11). Bariadi had the largest planted area of maize (101,952 ha) followed by Kahama (79,905 ha), Bukombe (64,833 ha), Shinyanga Rural (44,228 ha), Kishapu (35,496 ha), Maswa (35,159), Meatu (31,192) and Shinyanga Urban (7,505 ha) (Chart 3.21 and Map 3.12) . 3.3.4.1 Paddy Paddy was the Second dominant cereal crop in terms of production in the region. The number of households growing Paddy in Shinyanga region during the wet season was 136,046 (36% of the total households growing annual crops in the region during the wet season). The total production of Paddy was 104,847 tonnes from a planted area of 118,916 hectares resulting in a yield of 0.88 t/ha. Chart 3.22 presents Paddy production trend. The chart shows that there was a decrease in Paddy production over the period 1996 to 1997, after which the production stabilized over the period 1997 to 2000. Production gradually increased sharply over the period 2000 to 2003 (Chart 3.22). Chart 3.22 Timeseries of Paddy Production, Area Planted and Yield - 50,000 100,000 150,000 200,000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 - 1.00 2.00 3.00 4.00 Paddy Yield (T/ha) Paddy Production (Tonnes) Paddy Planted Area (ha) Chart 3.21 Maize: Total Area Planted and Planted Area Per Household by District 0 30,000 60,000 90,000 120,000 Bariadi Bukombe Kishapu Meatu Kahama Shinyanga Rural Maswa Shinyanga Urban - 0.50 1.00 1.50 Planted Area (ha) Area Planted Per Household (ha) Chart 3.20 Timeseries of Maize Production, Area Planted and Yield - 100,000 200,000 300,000 400,000 500,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 - 0.50 1.00 1.50 2.00 Maize Yield Maize Production Maize Planted Area RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 25 Chart 3.22 also shows that the planted area of Paddy increased sharply between 1997 and 1998 and has remained almost constant since then. Conversely, the yield declined constantly between 1994 and 2002 and has remained at this low level since then. Whilst Chart 3.22 shows that, there has been a slight increase in the production of Paddy over the last 10 years, this can be explained by the increase in the planted area. (Chart 3.22). The average area planted with Paddy per household was 0.87 hectares; however it ranged from 1.19 hectares in Shinyanga Rural district to 0.27 hectares in Meatu district (Map 3.11). Kahama had the largest planted area of Paddy (53,283 ha) followed by Bukombe (21,371 ha), Shinyanga Rural (20,937 ha), Maswa (9,975 ha), Bariadi (6,914 ha), Kishapu (4,459 ha), Shinyanga Urban (1,628 ha) and Meatu (349 ha) (Chart 3.23 and Map 3.12). 3.3.4.3 Sorghum Sorghum was the third most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Shinyanga region during the wet season was 59,619. This represented 16 percent of the total households growing annual crops in Shinyanga region during the wet season. The total production of sorghum was 17,269 tonnes from a planted area of 65,917 hectares resulting in a yield of 0.26 t/ha. The district with the largest planted area of sorghum was Meatu (24,353 ha) followed by Kishapu (21,030 ha), Bariadi (9,971 ha) and Maswa (7,950 ha) (Map 3.15). The Largest planted area per household for sorghum was found in Meatu (0.77 ha) and Kishapu (0.59 ha). Shinyanga Rural had the smallest planted area per household (0.03 ha) (Chart 3.25 and Map 3.16). There was a large reduction in the production of sorghum from 114,000 tonnes in 1994/95 to 17,000 tonnes in 2002/03 (Chart 3.24). Chart 3.24 also shows that there was a gradual reduction in the area planted with sorghum and a persistent Chart 3.24 Timeseries of Sorghum Production, Area Planted and Yield - 50,000 100,000 150,000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 - 0.20 0.40 0.60 0.80 1.00 1.20 Sorghum Yield Sorghum Production Sorghum Area Chart 3.23 Paddy: Total Area Planted and Planted Area Per Household by District 0 15,000 30,000 45,000 Kahama Shinyanga Rural Bukombe Maswa Shinyanga Urban Kishapu Bariadi Meatu - 0.20 0.40 0.60 0.80 1.00 1.20 1.40 Planted Area (ha) Area Planted Per Household (ha) Chart 3.25 Sorghum: Total Area Planted and Planted Area Per Household by District 0 10,000 20,000 Meatu Kishapu Maswa Bariadi Shinyanga Urban Shinyanga Rural Bukombe Kahama 0.00 0.30 0.60 0.90 Planted Area (ha) Area Planted Per Household (ha) Shinyanga Urban Shinyanga Rural Maswa Bariadi Kishapu Meatu Bukombe 1 0.9 1.4 1.3 1.2 1 1.3 Kahama 0.9 1.3 to 1.4 1.2 to 1.3 1.1 to 1.2 1 to 1.1 0.9 to 1 Kishapu Shinyanga Urban Shinyanga Rural Maswa Bariadi Meatu Bukombe 35,494ha 7,505ha 44,228ha 79,905ha 35,159ha 101,952ha 31,193ha 64,833ha 0.2t/ha 0.3t/ha 0.4t/ha 0.4t/ha 0.4t/ha 0.3t/ha 0.6t/ha 0.7t/ha Kahama 80,000 to 110,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Map 3.11 SHINYANGA Planted Area and Yield of Maize by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.12 SHINYANGA Area Planted Per Maize Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 26 Shinyanga Rural Shinyanga Urban Maswa Kishapu Meatu Bariadi Kahama Bukombe 0.3ha 0.5ha 0ha 0ha 0.5ha 0.5ha 0.9ha 0.3ha 1.6 to 2 1.2 to 1.6 0.8 to 1.2 0.4 to 0.8 0 to 0.4 Maswa Shinyanga Rural Kishapu Bariadi Shinyanga Urban Kahama Bukombe 8,718ha 1ha 372ha 339ha 114ha 17ha 100ha 22ha 0.3t/ha 0.2t/ha 0.3t/ha 0.4t/ha 0.5t/ha 0t/ha 0.1t/ha 1.2t/ha Meatu 7,200 to 8,800 5,400 to 7,200 3,600 to 5,400 1,800 to 3,600 0 to 1,800 Map 3.13 SHINYANGA Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.14 SHINYANGA Area Planted per Beans Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 27 Shinyanga Rural Kishapu Shinyanga Urban Bukombe Maswa Bariadi 21,030ha 917ha 1,326ha 227ha 101ha 7,950ha 24,395ha 9,971ha 0t/ha 0t/ha 0t/ha 0.34t/ha 0.61t/ha 0t/ha 0.17t/ha 0.42t/ha Kahama Meatu 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Kishapu Shinyanga Urban Kahama Shinyanga Rural Bariadi Meatu Bukombe 1.5ha 0.8ha 0.5ha 0.7ha 1.6ha 0.2ha 0.4ha Maswa 0.7ha 1.4 to 1.7 1.1 to 1.4 0.8 to 1.1 0.5 to 0.8 0.2 to 0.5 Map 3.15 SHINYANGA Planted Area and Yield of Sorghum by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.16 SHINYANGA RESULTS 28 Area Planted per Sorghum Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 29 decline in yield. This implies that the dramatic reduction in the quantity of sorghum production over the reported period was due to both reductions in area planted as well as declining yields. 3.3.4.4 Other Cereals Other cereals that were produced in small quantities were Bulrush Millet and finger millet. The district with the largest area planted with Bulrush Millet was Kishapu (4,256 ha) and Shinyanga Urban (1,645 ha) with other districts having small planted areas. The largest area planted with finger millet was in Bariadi district (180 ha). Other districts had insignificant planted areas of finger millet. 3.3.5 Roots and Tuber Crops Production The Common Roots and Tuber Crops grown in Shinyanga Region were Sweet Potatoes and Cassava. The total production of both Cassava and Sweet Potatoes was 39,975 tonnes. Sweet Potatoes production was higher than that of Cassava in the region with a total production of 25,376 tonnes representing 63 percent of the total root and tuber crop production. (Chart 3.26 and Table 3.3). The area planted with Sweet Potatoes was the largest and therefore sweet potatoes was the most important root and tuber crop in Shinyanga in terms of planted area. 3.3.5.1 Sweet Potatoes The number of households growing Sweet Potatoes in the region was 95,342. This represented 25 percent of the total households growing crops during the wet season in the region. The total production of Sweet Potatoes during the census year was 25,376 tonnes from a planted area of 27,601 hectares resulting in a yield of 0.92t/ha. Previous censuses and surveys indicate that the area planted with Sweet Potatoes increased gradually over the period 1992/93 to 1997/98 (Chart 3.27) and thereafter decreased gradually up to 2002/03. The area planted with Sweet Potatoes accounted for 2.82 percent of the total area planted with annual crops and vegetables in the census year. Table 3.3: Area, Production and Yield of Roots and Tuber Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Cassava 0 0 0 19,235 14,599 759 19,235 14,599 759 Sweet Potatoes 45 317 7120 27,556 25,059 909 27,601 25,376 919 TOTAL 45 317 7120 46,791 39,658 800 46,836 39,975 800 Note: Cassava is produced in both the Wet and Dry Season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the Wet Season only. Chart 3.27 Area Planted with Sweet Potatoes during the Census/ Survey Year - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Sweet Potatoes Planted Area (ha) Chart 3.26 Area and Production for Major Root Crops in Shinyanga Region by type of Crop 0 5,000 10,000 15,000 20,000 25,000 30,000 Cassava Sweet Potatoes Crop Production/Area ' Area Planted (ha) Quantity Harvested (tons) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 30 Shinyanga Rural district had the largest planted area of Sweet Potatoes (6,310 ha, 23% of the Sweet Potatoes planted area in the region), followed by Kishapu (5,971 ha, 22%), Maswa (5,729 ha, 21%) , Kahama (2,471ha, 9%), Bariadi (2,384 ha, 9%), Meatu (2,378 ha, 9%) Shinyanga Urban (1,368 ha, 5%) and Bukombe (989 ha, 3%) (Map 3.17). However, the highest proportion of land planted with Sweet Potatoes, expressed as a percent of the total planted area was in Shinyanga Urban district (18.8%). This was followed by Kishapu (17%), Maswa (16%) Shinyanga rural (14%) and Meatu (7.6%) (Chart 3.28). The average Sweet Potatoes planted area per Sweet Potatoes growing households was 0.07 hectares. The area planted per Sweet Potatoes growing household was greatest in Kishapu (0.17 ha), followed by Shinyanga Rural (.17ha), Shinyanga Urban (0.13 ha), Maswa (0.13 ha), Meatu (0.08 ha), Bariadi (0.03 ha), Kahama (0.03 ha) and Bukombe (0.02 ha) (Map 3.18). 3.3.5 Pulse Crops Production The total area planted with pulses was 47,984 hectares, of which 23,933ha were planted with Chick Peas (50% of the total area planted with pulses), followed by Beans (16,396 ha, 34%), Cow Peas (3,376 ha, 7%), Green Gram (2,898ha 6%) and Bambaranuts (1,382 ha, 3%). The total production of pulses was 18,500 tonnes. Chick Peas was the highest producing pulse crop (10,315 tonnes) and accounted for 56 percent of the total pulse production. This was followed by Beans (5,408t, 29%), Bambaranuts (1,296t, 7%), Cowpeas (851t, 5%) and green gram (630t, 3%). The Highest Yield was recorded on Bambaranuts (938 kg/ha) followed by Chick Peas (431kg/ha,), Beans 330 Kg/ha, Cow Peas 252kg/ha and Green gram 217 kg/ha, (Table 3.4). 3.3.5.3 Chick Peas Chick Peas dominate the production of pulse crops in the region. The number of households growing Chick Peas in Shinyanga region was 15,333 (4% of all crop growing households in the region). The total production of Chick Peas in the region was 10,315 tonnes from a planted area of 23,933 hectares resulting in yield of 0.4 t/ha. The largest area planted with Table 3.4 Area, Production and Yield of Pulses by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 101 25 248 16,295 5,383 330 16,396 5,408 330 Cowpeas - - - 3,376 851 252 3,376 851 252 Green Gram - - - 2,898 630 217 2,898 630 217 Chich Peas - - - 23,933 10,315 431 23,933 10,315 431 Bambaranuts 3 2 533 1,379 1,295 939 1,382 1,296 938 Total 104 32 47,880 18,473 47,984 18,500 0 5 10 15 20 Proportion of Area Planted , Shinyanga Urban Kishapu Maswa Shinyanga Rural Meatu Kahama Bariadi Bukombe District . Chart 3.28 Propotion of Area Planted with Sweetpotatoes by District Chart 3.29 Area Planted with Chick Peas as a Percent of Area Planted with Oil Seeds & Nuts 0 20 40 60 80 100 Meatu Bukombe Kahama Maswa Shinyanga Urb Bariadi Kishapu Shinyanga Rur District Proportion of Area . RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 31 Chick Peas in the region was in Shinyanga Rural district with 8,927 ha (37% of the total area planted with Chick Peas in the region). Of the total area Planted with Pulses the highest proportion of area planted with chick peas was recorded in Shinyanga rural (77%), followed by Kishapu (76%) and Bariadi (69%) districts (Chart 3.29). 3.3.6 Oil Seed Production The total production of oilseed crops was 31,561 tonnes, planted on an area of 66,057 hectares. Groundnuts was the most important oilseed crop with 64,355 ha (97% of the total area planted with oil seeds), followed by sunflower (2%) and simsim (1%), (Table 3.5). The yield of Simsim was the highest for oil seed crops (578 kg/ha) followed by Ground nuts (481 kg/ha) and sunflower (317 kg/ha). The total production of groundnuts was 30,951 tonnes, accounting for 98 percent of the total production of oil seeds, followed by simsim and sunflower (1% each), (Chart 3.30). 3.3.7 Vegetables The collection of fruit and vegetable production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not for household consumption. Most fruit production is from permanent crops. Reliable historical data for time series analysis of fruit and vegetables was not available. The total production of vegetables was 3,381 tonnes. The most cultivated vegetable crop was tomatoes with a production of 1,977 tonnes (58% of the total vegetables produced) followed by onions (503t, 15%) and Cabbages (461t, 14%). The production of the other vegetable crops was relatively small (Chart 3.31, Table 3.6). Chillies had the highest yield (5,039 kg/ha) followed by Cabbages (4,443kg/ha), Tomatoes 3,773kg/ha and onions (1,956kg/ha). Pumpkins, Egg plant and Radish had the lowest yields of 55, 408 and 609 kg/ha respectively (Table 3.6). Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Sunflower 0 - 0 1,434 455 317 1,434 455 317 Simsim 0 - 0 268 155 578 268 155 578 Groundnuts 167 32 482 64,188 30,919 482 64,355 30,951 482 Total 167 32 65,890 31,529 66,057 31,561 Table 3.6: Area, Production and Yield of Fruit and vegetables by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Tomatoes 0 0 0 524 1,977 3,773 524 1,977 3,773 Onions 0 0 0 257 503 1,956 257 503 1,956 Egg Plant 0 0 0 203 83 408 203 83 408 Radish 0 0 0 199 121 609 199 121 609 Cabbage 0 0 0 104 461 4,443 104 461 4,443 Amaranths 0 0 0 74 140 1,880 74 140 1,880 Pumpkins 0 0 0 26 1 55 26 1 55 Cucumber 0 0 0 23 43 1,878 23 43 1,878 Chillies 0 0 0 10 51 5,039 10 51 5,039 Total 0 0 1,421 3,381 1,421 3,381 Chart 3.31 Area Planted with Vegetables by type of vegetable 0 100 200 300 400 500 600 Tomatoes Onions Egg Plant Radish Cabbage Amaranths Pumpkins Cucumber Chillies Type of Vegetable Area Chart 3.30 Area Planted with Ground Nuts as a Percent of Area Planted with Oil S eeds & Nuts 0 25 50 75 100 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Proportion of Area . Shinyanga Rural Maswa Kishapu Shinyanga Urban Kahama Bukombe Meatu Bariadi 0.4ha 0.5ha 0.3ha 0.6ha 0.5ha 0.6ha 0.4ha 0.5ha 0.6 to 0.7 0.6 to 0.7 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 Shinyanga Urban Kahama Bukombe Maswa Shinyanga Rural Kishapu Bariadi 1,547ha 19,995ha 11,299ha 6,427ha 2,845ha 3,035ha 9,441ha 9,766ha 0.6t/ha 0.6t/ha 0.6t/ha 0.4t/ha 0t/ha 0.2t/ha 0.2t/ha 0.6t/ha Meatu 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Map 3.17 SHINYANGA Planted Area and Yield of Groundnuts by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.18 SHINYANGA Area Planted per Groundnuts Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 32 Kishapu Shinyanga Urban Kahama Shinyanga Rural Bariadi Meatu Bukombe 0.3ha 0ha 0.2ha 0.1ha 0.2ha 0.2ha 0.1ha Maswa 0.3ha 0.24 to 0.3 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Shinyanga Urban Maswa Kishapu Shinyanga Rural Bariadi Bukombe 1,547ha 9,766ha 6,427ha 2,845ha 3,035ha 9,441ha 19,996ha 11,299ha 4t/ha 3.7t/ha 2.5t/ha 0t/ha 4.2t/ha 2.2t/ha 4.5t/ha 17.5t/ha Kahama Meatu 17,000 to 20,000 13,000 to 17,000 9,000 to 13,000 5,000 to 9,000 1,000 to 5,000 Map 3.19 SHINYANGA Planted Area and Yield of Tomatoes by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.20 SHINYANGA RESULTS 33 Area Planted per Tomatoes Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 34 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report, the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore time series analysis cannot be made in this section. For small holders the planted area with permanent crops was 53,420 hectares (5.2% of the area planted with annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as the physical planted land area. So the percentage of the physical area planted with permanent crops would be higher than indicated in Chart 3.34. The most important permanent crop in Shinyanga region is Mango which accounts for a planted area of 28,067.0 ha, (53% of the planted area of all permanent crops) followed by Pawpaw (6,337 ha, 12%), Sisal (5,719 ha, 11%), and Banana (3,763 ha, 11%). Each of the remaining permanent crops had an area of less than 5 percent of the total area planted with permanent crops (Chart 3.35). Kahama district had the largest area under smallholder permanent crops (41,573 ha, 78%). This is followed by Bukombe (6,738 ha, 13%). With the exception of these two districts, other districts have relatively low percentages, less than 5% of land allocated to permanent crops farming (Chart 3.36). Table 3.7 Land Clearing Methods Method of Land Clearing Number of Households Area Planted % Mostly Bush Clearance 25,886 73,450 8 Mostly Hand Slashing 306,419 786,468 82 Mostly Tractor Slashing 1,215 2,251 0 Mostly Burning 10,135 19,590 2 No Land Clearing 30,424 73,327 8 Total 374,078 955,086 100 Chart 3.34 Area Planted for Annual and Permanent Crops Permernent, 53,420 , 5% Annual, 960,219 , 95% Annual Permernent Chart 3.35 Area Planted with main Perennial Crops Other, 9,536, 18% Banana, 3,763, 7% Sisal, 5,719, 11% Pawpaw, 6,337, 12% Mango, 28,065, 52% Mango Pawpaw Sisal Banana Other 0 10,000 20,000 30,000 40,000 50,000 Planted Area Kahama Bukombe Bariadi Shinyanga Rural Maswa Kishapu Meatu Shinyanga Urban District . Chart 3.36 Planted Area with Permanent crops by District Shinyanga Urban Shinyanga Rural Meatu Bariadi Bukombe 0.3 0.3ha 0.5ha 0ha 0.5ha 0.5ha 0.9ha Kahama Maswa Kishapu 0ha 0.72 to 0.9 0.54 to 0.72 0.36 to 0.54 0.18 to 0.36 0 to 0.18 Shinyanga Rural Shinyanga Urban Kishapu Bariadi Meatu Kahama Bukombe 174ha 335ha 523ha 0ha 3,755ha 7,752ha 6,697ha 3.1t/ha 0t/ha 3t/ha 1.6t/ha 2.8t/ha 2.4t/ha 2.6t/ha 1.8t/ha Maswa 0ha 6,400 to 7,800 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 Map 3.21 SHINYANGA Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.22 SHINYANGA Area Planted per Cassava Growing Household by District Area Planted (ha) Planted Area Per Household ha RESULTS 35 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 36 0 40,000 80,000 120,000 160,000 200,000 Area Cultivated Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District . Chart 3.40 Area Cultivated by Method of Cultivation and District Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories; bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region was 786,468 ha which represents 82 percent of the total planted area. Burning, bush clearance and tractor slashing are less important methods of land clearing and they represent 2, 0.3 and 7.7 percents respectively (Table 3.7, Chart 3.38) 3.5.2 Methods of Soil Preparation Oxen Ploughing is mostly used for soil preparation as it has been used in an area of 629,516 ha which represents 66 percent of the total planted area, followed by Hand Cultivation (294,648 ha, 31%) and tractor ploughing (3,509 ha, 1%) (Chart 3.40). In Shinyanga region, Bariadi district has the largest planted area cultivated using oxen (164,355 hectares, 40.6%) followed by Kishapu (112,432 ha, 18%), Maswa (89,475 ha, 14%) and Shinyanga Rural (86,690 ha, 14%), Meatu (82,344 ha, 13%), Kahama (49,833 ha, 8%), Bukombe (32,312 ha, 5%) and Shinyanga Urban (12,077 ha, 2%) (Chart 3.40, 3.40A). Tractor ploughing was more prominent in Maswa district with 29 percent of the area cultivated using tractors in the region followed by Kahama District 19 %, Bariadi District 17%, Meatu District and Kishapu District 10%. Chart 3.38 Number of Households by Method of Land Claring in Shinyanga Region 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Method of Land Clear Number of Household Chart 3.40A Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 3509.1, 1% Mostly Hand Cultivation, 294,648, 31% Mostly Oxen Ploughing, 629,516, 66% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 37 3.5.3 Improved Seeds Use The planted area with improved seeds was 261,066 ha which represents 27 percent of the total area planted with the annual crops and vegetables. Cash Crops had the largest planted area with improved seeds (159,104 ha, 69% of the planted area with improved seeds) followed by Cereals crops (57,738 ha, 25%). Other crop types had insignificant area planted with improved seeds (Chart 3.41, 3.42). Among the Cash Crops Cotton had the largest area of improved seeds application which was 155,842 ha 98% of area planted by cash crops. 3.5.4 Fertilizer Use The use of fertilisers on annual crops was very small with a planted area of only 171,943 ha (18% of the total planted area in the region). The planted area without fertiliser for annual crops was 785,481 hectares representing 82 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 137,161 ha which represents 14 percent of the total planted area (80% of the area planted with fertiliser application in the region). This was followed by Inorganic Fertilizers (20,380ha, 12% of the planted area with fertiliser and 2% of the total planted area in the region), Compost (14,404ha, 8% of the planted area with fertiliser and 2% of the total planted area in the region), Chart 3.43. Chart3.42 Planted Area with Improved Seeds by Crop type Roots & Tubers, 2,701, 1% Cash Crops, 155,842, 69% Fruits & Vegetables, 652, 0% Oil Seeds & Oil Nuts, 4,554, 2% Pulses, 48,025, 5% Cereals, 57,738, 26% Chart 3.43 Area of Fertilizer Application by type of Fertlizer Mostly Compost, 14,402, 2% Mostly Farm Yard Manure, 137,161, 14% Mostly Inorganic Fertilizer, 20,380, 2% No Fertilizer Applied, 785,481, 82% Chart 3.41 Planted Area of Improved Seeds - Shinyanga Without Improved Seeds, 697,741, 73% With Improved Seeds, 261,066, 27% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 38 Table 3.8 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Area Planted with Fertilizer (ALL TYPES) Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Planted Area Number of Households Planted Area Bariadi 6,857 25,192 1,064 2,158 0 27,350 77,393 182,648 Maswa 4,374 13,327 420 1,190 216 175 14,692 42,935 111,811 Shinyanga Rural 8,776 20,436 569 465 0 20,901 45,161 100,937 Kahama 14,913 38,280 2,314 3,538 6,722 18,336 60,154 81,074 197,060 Bukombe 4,611 16,482 1,553 3,169 358 931 20,582 52,643 132,870 Meatu 2,335 9,394 83 671 0 10,065 31,111 94,843 Shinyanga Urban 2,584 3,252 294 826 32 110 4,188 9,260 15,564 Kishapu 3,266 10,798 567 2,386 79 827 14,011 35,124 121,691 Total 47,716 137,161 6,864 14,402 7,407 20,380 171,943 374,699 957,423 The largest planted area with fertiliser (all types) was in Kahama district (60,154 ha, 35.0% of the total planted area with fertilizer in the region, followed by Bariadi (27,350, 16%), Shinyanga Rural (20,901 12%), Bukombe (20,582 12%), Maswa (14,692 9%), Kishapu (14,010 8%) and Shinyanga Urban (4,188, 2%) Table 3.8 and (Charts 3.60 and 3.61). Most annual crop growing households in Shinyanga do not use any fertiliser (312,714 households, 83%) (Map 3.37). The percentage of the planted area with applied fertilizer was highest for Cereals (73% of the planted area with fertilizer application. This was followed by Cash Crops (17%), Oil seeds and Nuts (6%) and Pulses (3%), (Chart 3.44). Other Crop types had insignificant area under fertilizer application. 3.5.4.1 Farm Yard Manure Use The number of households that applied farm yard manure in their annual crops was 47,716 and it was applied to 137,161 ha representing 14 percent of the total area planted during that season and 80 percent of the total planted area with fertiliser in the region. Cereals had the highest percent of the planted area applied with farm yard manure (73%), followed by Cash Crops 16%), Oil Seeds (6%), pulses (3%), fruits & vegetables (0.4%) and roots and tubers (1%) (Chart 3.44). The Proportion of area planted with farm yard manure show that, farm yard manure is mostly used in Shunyanga Urban (21%), of the total planted area in the district), followed by Shinyanga Rural and 20% other districts have lower than 15% of their total area planted with farm yard manure (Chart 3.45). 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.44 Percent of Crop type Planted Area with Farm yard Manure - Annual Crops Chart 3 45 Propotion of Planted Area Applied with Farm Yard Manure by District - SHINYANGA 0 20 40 60 80 100 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 39 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Shinyanga region was 20,389 ha which represents 2 percent of the total planted area with annuals in the region and 2.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertiliser on their annual crops was 7,407. The largest area applied with inorganic fertilisers was on Cereals (51% of the total area applied with inorganic fertilisers), followed by Cash Crops (41%). The proportion of the area applied with Inorganic Fertilizer at district level was very low ranging from 0 to 9% in Kahama district; (Chart 3.49). Chart 3.47 Planted Area with Inorganic Fertilizer by Crop type - SHINYANGA Cereals, 7,541, 51% Fruits & Vegetables, 104, 1% Oil Seeds & Oil Nuts, 393, 3% Pulses, 587, 4% Cash Crops, 6,015, 41% Roots & Tubers, 33, 0% 0 20 40 60 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.48 Percent of Crop type Planted Area with Inorganic Fertilizer - Annual Crops Chart 3 49 Propotion of Planted Area Applied with Inorganic Fertilizer by District - SHINYANGA 0 20 40 60 80 100 Bariadi Maswa Shinyanga Ru Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 40 3.5.4.3 Compost Use The total planted area applied with compost was 14,402 ha which represents only 2 percent of the total planted area with annual crops in the region and 8 percent of the total planted area with fertiliser in the region. The number of households that applied Compost on their annual crops was 6,864 (Table 3.8). Cereals had the highest percent of the planted area applied with Compost (73%), followed by Cash Crops 13%), Oil Seeds (5%), roots and tubers (5%) pulses (3%) and fruits & vegetables (1%) (Chart 3.50, 3.51). The proportion of the area applied with compost was very low for each district ranging from 0.5% lowest in Shinyanga Rural to 5.3% highest in Shinyanga Urban Districts (Chart 3.52). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in Shinyanga region. Insecticides are the most common pesticide used in the region (85% of the total area applied with pesticides). This was followed by fungicides (11%) and herbicides (4%) (Chart 3.53). Chart 3.50 Planted Area with Compost by Crop type - SHINYANGA Cereals, 9,391, 73% Fruits & Vegetables, 100, 1% Oil Seeds & Oil Nuts, 668, 5% Pulses, 393, 3% Cash Crops, 1,609, 13% Roots & Tubers, 596, 5% 0 20 40 60 80 Percent of Planted Area . Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.51 Percent of Crop type Planted Area with Compost - Annual Crops Chart 3 52 Propotion of Planted Area Applied with Compost by District - SHINYANGA 0.0 20.0 40.0 60.0 80.0 100.0 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent ' Chart 3.53 Planted Area (ha) by Pesticides Use Fungicide, 42,435, 11% Herbicide, 17,521, 4% Insecticides, 330,893, 85% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 41 Chart 3.54 Area of Irrigated Land Un- Irrigated Area, 947,157, 99% Irrigated Area, 10,266, 1% Chart 3.55 Proportion of Planted Area with Irrigation by District 0.0 25.0 50.0 75.0 100.0 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Percentage . 3.5.6 Harvesting Methods The main harvesting method for cereals was by hand. All other cereals (Maize Paddy, Sorghum, Bulrush Millet, and Finger Millet) were mainly harvested by hand. Like cereals, other annual Crops were also mainly harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 96 percent of the total area planted with cereals being threshed by hand. Draft animals, human powered tools and engine driven machines were scarcely used on threshing crops and the percentage area utilized was 1,1 and 3 respectively. 3.6 Irrigation Water is the limiting fact or to crop prod uction in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Shinyanga region, the area of annual crops under irrigation was 10,266 ha representing 1.1 percent of the total area planted (Chart 3.54). The district with the highest proportion of area under irrigation with annual crops was Shinyanga Urban 2 percent of the planted area with annual crops in the District. This is followed by Maswa (1.7%) and Bariadi (1.5%). Other districts had insignificant areas planted under Irrigation. (Chart 3.55 and Map 3.38). RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 42 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The most important stored crop was maize with 284,899 households storing 101,693 tonnes as of 1st October 2003. This was followed by Paddy (112,839 households, 55,481t), Groundnuts/ Bambaranuts (63,962 households, 10,223t) and Beans/Pulses (50,197 households, 5,247t). Other crops were stored in very small quantities (Chart 3.60). 3.7.1.1 Methods of Storage The region had 172,157 crop growing households storing their produce in sacks and/or open drums (55% of households that stored crops in the region). The number of households that stored their produce in locally made traditional structures was 132,594 (42%). This was followed by improved locally made structure (4,668 households, 1.5%), airtight drum (204 households, 0.1%), unprotected piles (1,801 households, 0.6%) and modern stores (936 households, 0.3%) (Chart 3.61). Storage in sacks and/or open drum was the dominant storage method in most districts, with kahama having the highest percent of households using this method (36% of the total number of households storing crop products). This was followed by Shinyanga Rural (18%), Bukombe (17%), Bariadi (11%), Kishapu (7%), Maswa (5%), Meatu (4%) and Shinyanga Urban (3%). The highest percent of households using improved locally made structures was in Bariadi and Bukombe districts (57% and 20% of the total number of households storing crops respectively), other districts had relatively small numbers of households using the method, (less than 10% each). (Chart 3.61). . Chart 3.60 Number of Households and Quantity stored by by crop type - Shinyanga 0 50,000 100,000 150,000 200,000 250,000 300,000 Maize Paddy Groundnuts/Bambara Nu Beans & Pulses Sorghum & Mille Cottton Crop Quantity Stored Number of Households Quantity stored (tons) Chart 3.61 Number of Households by Method of Storage and District (Based on the Most important household Crop) 0 10 20 30 40 50 60 70 80 90 100 Kahama Shinyanga Rural Buko mbe Bariadi Kis hapu Mas wa Meatu Shinyanga Urban District Number of Households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 43 3.7.1.2 Duration of `Storage Most households stored their produce for a period of 3 to 6 months (52% of the households storing crops) followed by those who stored for a period of Less than three months (26%) and those who stored their crop for a period of more than six months (22%), Chart 3.62). Most households stored Maize for a period of 3 to 6 months (52% of the households storing crops) followed by those who stored crops for a period of less than three months and those who stored their for a period of more than six months. The proportion of number of households that stored their produce for the duration of 3 to 6 months was highest in Bukombe district (64%) followed by Shinyanga Urban (58%), Shinyanga Rural (57%), Bariadi (52%), Kahama (52%), Meatu (44%), Maswa (42%) and Kishapu (38%) (Chart 3.63, Map 3.39). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.64). However, households in Bariadi, Maswa and Bukombe Districts had proportionally stored little maize in comparison to the total quantity produced. Chart 3.62 Percent of Agricultural Households and Length of Storage of Crops by District 0 25 50 75 100 Less than 3 Months Between 3 and 6 Months Over 6 Months Length of Storage Percent Chart 3.63 Proportiont of Agricultural Households storing crops for a period of 3 to 6 Months by District 0 10 20 30 40 50 60 70 80 90 100 Bukombe Shinyanga Urba Shinyanga Rura Bariadi Kahama Meatu Maswa Kishapu District Percent Chart 3.64 Qunatity Stored and Propotion of Maize Stored to total production 0 10,000 20,000 30,000 40,000 50,000 60,000 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Quntity stored 0 10 20 30 40 50 60 70 80 90 100 Proportion Maize Production (tons) Proportion of Maize stored to Production ` RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 44 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet,) are mainly stored for household consumption. The percent of households that stored Crops for household consumption as the main purpose of storage was 95 percent, followed by seed for planting (3%) and selling at higher price (2%). A high percent of the households that stored pulses and groundnuts was for planting purpose (seeds) (8.5% and 12.8 respectively), Table 3.09. 3.7.1.4 The Magnitude of Storage Loss About 86 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are stored for seeds such as groundnut and bambara nuts. The proportion of households that reported a storage loss of more than a quarter was greatest for Maize and millets (4% of the total number of households that stored crops). This was followed by Beans & Pulses (2%), Paddy and Groundnuts both had scored 1% (Table 3.10). Table 3.09: Number of Households Storing Crops By Main Purpose of Storage and District Main Purpose District Food for the Household To Sell for Higher Price Seeds for Planting Other Total Bariadi 64,018 1,224 0 0 65,243 Maswa 24,475 209 1,188 0 25,873 Shinyanga Rural 40,721 203 605 0 41,528 Kahama 75,633 928 1,237 0 77,798 Bukombe 42,354 2,179 2,809 0 47,342 Meatu 23,048 273 388 81 23,791 Shinyanga Urban 6,216 52 250 32 6,550 Kishapu 22,398 0 3,003 0 25,401 Total 298,864 5,068 9,480 113 313,525 % 95 2 3 0 100 Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and Crop Estimated Storage Loss Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Crop Number of House holds % Number of House holds % Number of House holds % Number of House holds % Total Maize 243,033 85.3 31,313 11.0 8,708 3.1 1,845 0.6 284,899 Paddy 108,487 95.9 3,067 2.7 1,529 1.4 0 0.0 113,083 Sorghum & Millet 35,913 82.6 5,858 13.5 1,448 3.3 272 0.6 43,490 Beans & Pulses 47,291 92.6 2,828 5.5 677 1.3 251 0.5 51,047 Groundnuts/Bambara Nuts 60,951 94.9 2,344 3.6 840 1.3 95 0.1 64,230 Chart 3.91a Households Processing Crops Households not Processing, 49,026, 13% Households Processing, 328,832 , 87% Chart 3.91b Percentage of Households Processing Crops by District 0 20 40 60 80 100 120 Kahama Shinyanga Rural Bukombe Bariadi Meatu Kishapu Maswa Shinyanga Urban District Percent of Households Processing RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 45 3.7.2 Agro-processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Shinyanga region (328,832 households, 87% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high (above 80%) in most districts except Kishapu (79%), Maswa (75%) and Shunyanga Urban 42% (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines (221,237 households, 67% of households processing crops). This was followed by those processing on-farm by hand (51,589 households, 16%), by trader (42,017 households, 13%) and on farm by machine (10,071 households, 3%). Although processing by neighbours machine was the most common processing method in all districts in Shinyanga region, district differences existed. Kahama had a higher percent of hand processing on farm than other districts (43%), followed by Meatu (17%), Shinyanga Rural (13%) and Bariadi (12%). Processing by trader was mostly practised in Shinyanga Rural (39%) , Bukombe (32%), Bariadi (15%) and Maswa (12%), whilst processing on farm by machine though small, was more prevalent in Bariadi and Kishapu (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, main product and by-product. The main product is the major product after processing and the by- product is secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is the bran. Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District ' Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Chart 3.93 Percent of Households by Type of Main Processed Product Grain, 103,903 , 32% Oil, 2,929 , 1% Juice, 161 , 0% Other, 81 , 0% Pulp, 175 , 0% Flour / Meal, 218,022 , 67% Chart 3.94 Number of Households by Type of By- product Fiber, 362 , 0% Other, 313 , 0% Husk, 3,807, 8% Bran, 101,742 , 63% Pulp, 1,576, 3% Shell, 12,174 , 7% Oil, 473 , 0% Pulp, 590 , 0% Juice, 531 , 0% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 46 The main processed product was flour/meal with 218,022 households processing crops into flour (67%) followed by grain with 103,903 households (32%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 50 percent of the households processing crops. The most common by-product produced by crop processing households was bran (101,742) households 62%), followed by Husk (46,899 households, 29%), shell 12,174 households, 7%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were mainly used for household/human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which was reported by 98 percent of the total households that used primary processed product (Chart 3.95). Out of 15,132 households that sold processed products, 5,424 (36% of the total number of households selling processed products in the region) were from Kahama followed by Meatu (2,606 households, 17%), Bukombe (2,106 households, 14%), Maswa (1,826 Households, 12%), Shinyanga Rural (1,105 households, 7%), Bariadi districts (1,058 households, 7%), Kishapu (722 households, 5%) and Shinyanga Urban (403 households, 2%) (Chart 3.96). Compared to other districts in Shinyanga region, Meatu district had the highest proportion of households that sold processed products (10%). This is followed by Kahama, 7%, Shninyanga Urban, 7% and Maswa (6%). Other districts had lower that 5% of the number of agricultural households selling processed products.. 0.00 10.00 20.00 30.00 40.00 Percentage of household Kahama Meatu Bukombe Maswa Shinyanga Rural Bariadi Kishapu Shinyanga Urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.95 Number of Households and use of processed product Did Not Use, 1,806 , 1% Fuel for Cooking, 898 , 0% Animal Consumption, 819 , 0% Sale Only, 2,352 , 1% Household /Human Consumption, 322,958 , 98% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 47 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (5,874 households, 38% of households that sold processed crops). This was followed by selling to Local Markets/ Trade Store (3,453 households, 23%), Marketing Cooperatives (2,118 households, 14), Famers Association (1,091 households, 7%), Trade at Farm (1,020 households, 7%), Other unspecified Markets (594 households, 4%), Secondary Markets (531 households, 4%) and large scale farms (451 households, 3%) (Chart 3.97). There were large differences between districts in t he proportion of households selling processed products with Kahama district having the largest percent of households in the region selling to neighbours (51%) as well as selling to local markets or trade stores. Maswa district had a higher percent of households relying on secondary markets. (Chart 3.98). 3.7.3 Crop Marketing The number of households that reported selling crops was 219,317 which represents 58 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Maswa (79%) followed by Bariadi (66%), Meatu (59%), Kahama (59%), Bukombe (54%), Kishapu (59%), Shinyanga Rural (44%) and Shinyanga Urban (8%) (Chart 3.99 and Map 3.40). Chart 3.97 Location of Sale of Processed Products Farmers Association, 1,091 , 7% Trader at Farm, 1,020 , 7% Other, 594 , 4% Secondary Market, 531 , 4% Marketing Co- operative, 2,118 , 14% Local Market / Trade Store, 3,453 , 23% Neighbours, 5,874 , 38% Large Scale Farm, 451 , 3% Chart 3.98 Number of households Selling Processed Products by Main outlet sale and District 0 800 1,600 2,400 3,200 Kahama Bukombe Maswa Bariadi Shinyanga Rural Kishapu Shinyanga Urban Meatu District . Number of Households Neighbours Local Market / Trade Store Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 15,000 30,000 45,000 60,000 Bariadi Kahama Maswa Bukombe Shinyanga Rural Meatu Kishapu Shinyanga Urban District Number of Househo 0.0 20.0 40.0 60.0 80.0 100.0 Percent Number of Households Selling Crops Percent of Households Selling Crops RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 48 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketin g problem reported by households (75% of crop growing households that reported main marketing problems). Apart from low market prices, other problems were long distances to the markets (7%), high transport costs (6%), lack of transport (4%), lack of market information (2%), Trade union Problems (2%) and the government regulatory Boards problems (1%). Other marketing problems are minor, representing less than 1 percent of the total reported problems (Chart 3.100). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 87 percent of the smallholders. The proportion of households reporting other reasons for not selling were extremely low (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credits The census results shows that very few agricultural households (7,054, 2%) in Shinyanga region accessed credit, of which 5,402 (77%) were male-headed households and 1,651 (24%) were female headed households. The number of those who accessed credits was higher in Bariadi (31%) followed by Kahama (31%), Bukombe (12%) and Maswa (12%). Other Districts have less than 10% of those who accessed credits, (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 160,445 87 Other 12,481 7 Price Too Low 7,925 4 Trade Union Problems 1,503 1 Co-operative Problems 1,427 1 Government Regulatory Board Problems 905 0 Market Too Far 442 0 Total 149,005 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Bariadi 1,733 77 525 23 2,258 Maswa 650 75 217 25 867 Shinyanga Rural 100 25 302 75 401 Kahama 2,040 94 137 6 2,177 Bukombe 716 86 119 14 836 Meatu 81 33 165 67 246 Shinyanga Urban 0 0 23 100 23 Kishapu 82 33 164 67 245 Total 5,402 77 1,651 23 7,054 Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Open Market Price Too Low 74% Co-operative Problems 1% No Transport 4% Trade Union Problems 2% Market too Far 6% Transport Cost Too High 6% Other 4% Lack of Market Information 2% Farmers Association Problems 0% Government Regulatory Board Problems 1% Bukombe Kahama Shinyanga Urban Bariadi Maswa Kishapu Shinyanga Rural Meatu 299ha 291ha 302ha 1,505ha 157ha 66ha 646ha 589ha 96.9% 70.7% 91.3% 93.2% 50% 62.9% 84.8% 66.5% 1,200 > 900 to 1,200 600 to 900 300 to 600 0 to 300 Bariadi Maswa Shinyanga Rural Kishapu Meatu Shinyanga Urban Bukombe 155,298ha 97,119ha 11,430ha 86,259ha 107,681ha 80,035ha 136,906ha 112,530ha 85% 86.9% 89.4% 88.5% 73.1% 79.3% 69.5% 84.5% Kahama 120,000 > 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Map 3.23 SHINYANGA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Tanzania Agriculture Sample Census Planted Area with No Fertilizer Applied Percent of Planted Area with No Fertilizer Applied Planted Area With Irrigation Map 3.24 SHINYANGA RESULTS 49 Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area with No Fertilizer Applied Percent of Planted Area With Irrigation Planted Area With Irrigation Shinyanga Urban Bariadi Maswa Kishapu Shinyanga Rural Meatu Kahama Bukombe 770 51,136 34,296 18,658 17,952 19,829 47,924 28,751 7.6 65.9 79.3 59.2 50.4 43.8 59 54 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Selling Crops Map 3.25 SHINYANGA Number of Households and Percent of Total Households Selling Crops by District Percent of Total Households Selling Crops Number of Households Selling Crops RESULTS 50 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 51 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Shinyanga region were Family, Friends and relatives Religious which collectively provided credit to 2,233 agricultural households (32% of the total number of households that accessed credit), followed by Savings and Credit Society (21%), Religious Organisations (20%), Traders/ Trade Store (15%) and Commercial Banks (1%). (Chart 3.101). (Chart 3.102). 3.8.1.2 Use of Agricultural Credits A large proportion of the agricultural credit provided to agricultural households in the region was used on purchase of Agrochemicals (28%), followed by purchasing Seeds (21%), hiring labour (16%), Purchasing tools and Equipment (12%), and on purchasing fertilizers (12%) (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credits The main reason for not using agricultural credit as a source of finance was little credit awareness accounting for 57 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by “non-availability of credit” reported by 20 percent of households and “not wanting to go into debt” (11%), Credit not wanted (6%). The rest of the reasons collectively accounted for less than 10 percent of the agricultural households (chart 3.104). Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 27% Religious Organisation / NGO / Project 36% Family, Friend and Relative 30% Saving & Credit Society 7% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 16% Labour 35% Other 16% Agro-chemicals 4% Tools / Equipment 13% Seeds 16% Chart 3.104 Reasons for not Using Credit (% of Households) Did not know how to get credit, 132,023, 41% Don't know about credit, 69,551, 22% Not available, 64,325, 20% Did not w ant to go into debt, 27,138, 8% Difficult bureaucracy procedure, 7,190, 2% Not needed, 8,910, 3% Credit granted too late, 2,657, 1% Other, 2,465, 1% Interest rate/cost too high, 7,702, 2% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 52 3.8.2 Crop Extension The number of agricultural households that received crop extension was 104,252 (28% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Kishapu having a relatively high proportion of households that received crop extension messages (51%) followed by Meatu (47%), Kahama (36%), Shinyanga Urban (33%), Shinyanga Rural (27%), Bariadi (21%), and Bukombe (14%), (Chart 3.106 and Map 3.41). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (97%). NGOs provided 2.43 percent, large scale farms 0.33 percent and the remaining providers less than 0.24 percent (Chart 3.107), however district differences exist with the proportion of the households receiving advice from government services ranging from 98 percent in Shinyanga Urban, Kahama and Bukombe districts to 87 percent in Maswa district. 3.8.2.2 Quality of Extension29/01/2007 An assessment of the quality of extension indicates that 64 percent of the households receiving extension ranked the service as being “good” followed by “Average” (20%) and “very good (13%). Very few households reported the services to be “poor” (2.7%) and “no good” (0.3%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Receiving Extension , 132,389, 41% Households Not Receiving Extension , 191,331, 59% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 60,000 Dodoma Rural Kongwa Dodoma Urban Mpwapwa Kondoa District Number of Households 0 20 40 60 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Government 98.5% Other 0.6% NGO / Development Project 0.8% Large Scale Farm 0.2% Chart 3.108 Number of Households Receiving Extension by Quality of Services Very Good, 20,687, 15.8% No Good, 1,528, 1.2% Poor, 2,731, 2.1% Average, 19,865, 15.2% Good, 86,304, 65.8% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 53 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Shinyanga regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, the figures presented in this section may be different from the previous section on inputs (Section 2.6). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Shinyanga region, improved seeds is used by 118,404 households which represents 31 percent of the total number of crop growing households. This is followed by households using farm yard manure (23%), pesticide/fungicide (21%), compost (4%) and inorganic fertiliser (3%). The number of Households with access to herbicides was very small which is 3 for every 1000 agricultural households (Table 3.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Shinyanga region mostly purchase it from Cooperative Unions (59%) and local markets/trade stores (38% of the total number of households using inorganic fertiliser). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Most households access inorganic fertilizers from a distance of less than 1 kilometres (39%), followed by between 1 and 3 km (21%), between 3 and 10 km (18%), between 10 and 20 km (11%) and those who reside at distance of more than 20 km were 1,121 (10%), (Chart 3.110). Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 88,413 23 289,758 77 Improved Seeds 118,404 31 259,372 69 Pestcides/Fungicide 81,034 21 296,824 79 Compost 14,316 4 363,429 96 Inorganic Fertiliser 10,730 3 367,127 97 Herbicide 1,188 0 376,549 100 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 1,526 388 382 0 400 800 1,200 1,600 Local Market / Trade Store Locally Produced by Household Neighbour Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 54 Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “non available” (31%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using. Other reasons such as costs are more important with 60 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and fertiliser would become more accessible. More smallholders use inorganic fertilisers in Kahama than in other districts in Shinyanga region possibly because of the predominance of tobacco farming in the district, (79% of households using inorganic fertilisers). 3.9.3 Improved Seeds The percent of households that used improved seeds was 31 percent of the total number of crop growing households. Most of the improved seeds are from Cooperatives (41%). Other less important sources of improved seed are Local Market/ Store (27%) and Crop Buyers (22%). Other Sources of Improved Seeds are not significant (Chart 3.111). Access to improved seeds is equally same situation as access to chemical inputs with 35 percent of households obtaining the input within 1 km of the homestead (Chart 3.112) compared to 39 percent for chemical inputs. The higher use of improved seeds (31%) compared to other inputs is an indication that the availability is not the main prohibiting factor for the use of inputs but rather other factors such as cost. The district that mostly uses improved seeds is Bariadi with 29 percent of the total number of households using improved seeds in Shinyanga region, followed by Maswa (18%), Kahama (16%), and Kishapu (14%). Percents of the crop growing households in Bukombe, Meatu, Shinyanga Rural and Shinyanga Urban districts that used improved seeds were 9,4 and 1 percent respectively (Map 3.42). Chart 3.111 Number of Households by Source of Improved Seeds 57.5 22.0 12.9 3.3 1.9 1.1 0.7 0.6 0 5,000 10,000 15,000 20,000 Local Market / Trade Store Development Project Neighbour Locally Produced by Household Secondary Market Local Farmers Group Large Scale Farm Crop Buyers Source of Improved Seeds Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Improved Seeds 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 55 3.9.4 Insecticides and Fungicides The percent of households that used Insecticides/Fungicides was 21 percent of the total number of crop growing households. Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (60% of the total number of households using insecticides/fungicides), followed by Cooperatives (29%). Other sources of insecticides/Fungicides were not significant (Chart 3.113). Chart 3.114 shows that the number of agricultural households (31% of the crop growing households which used insecticides and fungicides) obtained the inputs from the distance of 3 to 20 kilometres. The small number of households using insecticides/fungicides coupled with the 8 percent of households responding to “non availability” as the reason for not using fungicides, may lead to the assumption that access is not the main reason for not using. Other reasons such as costs are more important with 76 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be improved. Fungicide is mostly used in Bariadi district with 36 percent of the total number of households using fungicide, followed by Kahama (22%), Bukombe (15%), Meatu (11%), Maswa (6%) and Kishapu (6%). Shinyanga Rural and Urban Districts had the smallest number of households using Insecticides/ Fungicides which was 3 and 1 Percent Respectively. Chart 3.113 Number of Households by Source of Insecticide/fungicide 58.5 34.0 6.0 1.4 0 2,000 4,000 6,000 Local Market / Trade Store Development Project Neighbour Secondary Market Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0.0 15.0 30.0 45.0 60.0 75.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 56 Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 5 4 3 4 28 0 5,000 10,000 15,000 20,000 25,000 Kondoa Mpwapwa Dodoma Urban Dodoma Rural Kongwa District Number of Households 0 6 12 18 24 30 Percent Number of Households Percent 3.10 Tree Planting The number of households involved in tree farming was 13,645 representing 4 percent of the total number of agriculture households (Chart 3.115). The Common tree species planted by smallholders on their allotted land were Leucena Sp (51%), Gravelli (21%), Acacia (12%) and Azadritachta Spp. In Shinyanga Region Smallholders plant trees mostly scattered on Field. The proportion of trees that are planted Scattered on field is 53 percent, followed by trees planted on field boundaries 38% and tress in Plantation accounted for 9% of all planted trees in the region. 3.11 Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms in Shinyanga region was 15,199 which represent 4 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Shinyanga Rural (7%) followed by Shyinyanga Urban (7%), Bariadi (5%), Kahama (4%), Kishapu (3%), Maswa (3%), Meatu (2%) and Bukombe (1%) (Chart 3.121 and Map 3.44). Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 33,336, 10% Households Without Facilities, 290,383, 90% Chart 3.115 Number of Households with Planted Trees - DODOMA Households without Planted Trees, 301,411, 93% Households withPlanted Trees, 22,308, 7% Bariadi Meatu Maswa Kishapu Shinyanga Rural Shinyanga Urban Kahama Bukombe 34,676 11,043 21,630 1,182 16,184 4,475 18,491 10,723 44.7% 35.1% 50% 45.5% 11.6% 9.9% 22.8% 20.1% 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Kishapu Meatu Bariadi Maswa Shinyanga Rural Shinyanga Urban Kahama Bukombe 18,190 3,364 14,761 16,641 2,469 12,421 29,021 7,386 51.1% 46.9% 21.5% 5.7% 33% 27.4% 35.7% 13.9% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.26 SHINYANGA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Tanzania Agriculture Sample Census Number of Households Percent of Households Receiving Crop Extension Services Crop Growing Households Using Improved Seed Map 3.27 SHINYANGA Number and Percent of Crop Growing Households using Improved Seed by District Percent of Crop Growing Households Using Improved Seed Growing Households Using Improved Seed Number of Households Receiving Crop Extension Services RESULTS 57 Maswa Kishapu Shinyanga Rural Bariadi Meatu Shinyanga Urban Kahama Bukombe 9 24 9 10 37 26 11 13 6.5% 17.3% 6.5% 7.2% 26.6% 18.7% 7.9% 9.4% Map 3.28 SHINYANGA Number and Percent of Smallholder Planted Trees by District Tanzania Agriculture Sample Census Number of Households Planted Trees Percent of Smallholder PlantedTrees Number of Smallholder Planted Trees 32 to 40 24 to 32 16 to 24 8 to 16 0 to 8 RESULTS 58 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 59 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 2,604,105 which has the largest cattle population in the Country regional wise. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region ranked 1st out of 21 Mainland regions and had 15.5 percent of all cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Shinyanga region was 2,591,532 (99.5 % of the total number of cattle in the region), 1,375 cattle (0.1%) were Beef breeds and 11,198 cattle (0.4%) were Diary breeds. The census results show that 148,216 agricultural households in the region (39% of total agricultural households) kept 2.6 million cattle. This was equivalent to an average of 17.6 heads of cattle per cattle-keeping- household. The district with the largest number of cattle was Bariadi which had about 544, 496 heads of cattle (21% of the total cattle in the region). This was followed by Kahama (409,991 cattle, 16%), Meatu (334,099 cattle, 13%), Bukombe (332,685 cattle, 13%), Shinyanga Rural (317,785 cattle, 12%), Maswa (312,274, 12%) and Kishapu (292,978 11%). Shinyanga Urban district with 59,788 cattle, 2% had the least number of cattle in the Region. However Shinyanga Urban district had the highest density (1,467 head per km2 ) (Chart 3.123, Map 3.48). The Region was mostly dominated by indigenous breeds and had a small number of improved cattle which was 12,573 (0.48%) or 5 in every 1,000 heads of cattle. A small number of improved dairy (3,039) and beef (537) cattle was found in Bariadi district. The number of dairy and beef cattle was insignificant in other Districts. (Chart 3.124). - 100 200 300 400 500 600 Number of Cattle ('000' Bariadi Kahama Meatu Bukombe Shinyanga Rural Maswa Kishapu Shinyanga Urban Districts Chart 3.123 Total Number of Cattle ('000') by District 0 100,000 200,000 300,000 400,000 500,000 600,000 Number of Cattle ('000') Bariadi Kahama Bukombe Meatu Shinyanga Rural Maswa Kishapu Shinyanga Urban Districts Chart 3.124 Total Number of Cattle ('000') by District Indigenous Beef Dairy RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 60 3.12.1.2 Herd Size Twenty three percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 27 percent of all cattle in the region. Only 13 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 87 percent of total cattle rearing households had herds of size 1- 30 cattle and owns 63 percent of total cattle in the region, resulting in an average of 11 cattle per cattle rearing household. There were about 610 households with a herd size of more than 151 cattle each (200,121 cattle in total) resulting in an average of 328 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Shinyanga increased during the eight years period from 2,262,809 in 1995 to 2,604,105 cattle in 2003. This trend depicts an overall annual positive growth rate of 1.77 percent (Chart 3.125). There was a very sharp increase in number of cattle for the period of four years from 1995 to 1999 at the rate of 13.67 percent whereby the number increased from 2,262,809 to 3,778,255. However, the number of cattle decreased from 3,778,255 in 1999 to 2,604,105 in 2003 at the negative decrease rate of - 8.88 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Shinyanga region was 12,573 (11,198 dairy and 1,375 improved beef). The diary cattle constituted 0.43 percent of the total cattle and 90 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 10 percent of the total number of improved cattle and 0.05 percent of the total cattle. The time series information to facilitate time series analysis for this category of cattle is not available. 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, the region ranked 2 out of 21 Mainland regions and had 11 percent of all Goat on Tanzania Mainland. 2,262,809 3,778,255 2,604,105 - 1,000,000 2,000,000 3,000,000 4,000,000 Number of Cattle ' 1995 1999 2003 Year Chart 3.125 Cattle Population Trend RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 61 3.12.2.1 Goat Population The number of goat-rearing-households in Shinyanga region was 124,019 (33% of all agricultural households in the region) with a total of 1,277,929 goats giving an average of 10 head of goats per goat-rearing-household. Bariadi had the largest number of goats (229,817 goats, 18% of all goats in the region), followed by Meatu (215,670 goats, 17%), Maswa (209,359 goats, 16%), Kishapu (189,543 goats, 15%), Shinyanga Rural (154,348 goats, 12%), Kahama (140,846 goats, 11%) and Bukombe (106,926, 8%). Shinyanga Urban district had the least number of goats (31,434 goats, 2%) (Chart 3.127 and Map 3.49). However Shinyanga Urban district had the highest density (471 head per km2 ) (Map 3.50). 3.12.2.2 Goat Herd Size Twenty nine percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Seventy eight percent of total goat-rearing households had herd size of 1-14 goats and owned 46 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 2,914 households (2.4%) with herd sizes of 40 goats or more each (183,695 goats in total), resulting in an average of 63 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 99.4 percent of the total goats in Shinyanga region. Improved goats for meat and diary goats constituted 0.5 and 0.1 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 0.92 percent. The positive rate of increase indicates goat population increase from 1,187,706 in 1995 to 1,277,929 in 2003. The number of goats increased from 1,187,706 in 1995 at an estimated annual rate of 14.30 percent to 2,026,929 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -10.89 percent (Chart 128). Chart 3.127 Total Number of Goats ('000') by District - 50 100 150 200 250 Bariadi Meatu Maswa Kishapu Shinyanga Rural Kahama Bukombe Shinyanga Urban District Number of Goats ('000') 1,187,706 2,026,845 1,277,929 - 1,000,000 2,000,000 3,000,000 Number of Goatas ' 1994/95 1998/99 2002/03 Year Chart 3.128 Goat Population Trend Bukombe Meatu Maswa Shinyanga Rural Bariadi Kishapu Shinyanga Urban Kahama 81.1 113.1 195.3 232.5 149.3 144.2 115.4 263.6 190,000 to 230,000 150,000 to 190,000 110,000 to 150,000 70,000 to 110,000 30,000 to 70,000 Maswa Bariadi Meatu Kishapu Shinyanga Urban Shinyanga Rural Bukombe Kahama 312,274 59,788 544,496 334,099 292,987 317,785 409,991 332,685 400,000 > 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Map 3.29 SHINYANGA Cattle population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Cattle Number of Cattle Number of Cattle Per Square Km Map 3.30 SHINYANGA Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km RESULTS 62 Shinyanga Urban Shinyanga Rural Maswa Bariadi Kishapu Kahama Bukombe 189,543 31,434 229,817 106,926 215,670 140,846 154,334 209,359 Meatu 184,000 to 230,000 138,000 to 184,000 92,000 to 138,000 46,000 to 92,000 0 to 46,000 Kahama Bukombe Bariadi Meatu Kishapu Shinyanga Urban Shinyanga Rural 43.4 51 63 66.9 73 69.3 23 Maswa 835.6 680 to 850 510 to 680 340 to 510 170 to 340 0 to 170 Map 3.31 SHINYANGA Goat population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Goat Number of Goat Number of Goat Per Square Km Map 3.32 SHINYANGA Goat Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 63 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 64 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Shinyanga region after cattle and goats. The region ranked 2 out of 21 Mainland regions and had 13 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 58,545 (15% of all agricultural households in Shinyanga region) rearing 517,144 sheep, giving an average of 9 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Kishapu with 131,296 sheep (25% of total sheep in Shinyanga region) followed by Maswa (106,969 sheep, 21%), Meatu (95,895 sheep, 19%), Bariadi (78,539 sheep, 15%), Shinyanga Rural (53,163 sheep, 10%), Kahama (30,133 sheep, 6%). Shinyanga Urban and Bukombe Districts had the least number of sheep in the region which was 12,403, 2% and 8,745, 2% sheep respectively (Chart 3.129 and Map 3.51). Maswa district also had the highest density (67 head per km2 ) (Map 3.52). Sheep rearing was dominated by indigenous breeds that constituted 100 percent of all sheep kept in the region. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the shee p population for the eight year period from 1995 to 2003 is estimated at 0.72 percent. The population increased at an annual rate of 14.11 percent from 488,267 in 1995 to 517,144 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -11.10 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 19 out of 21 Mainland regions and is 0.3 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Shinyanga region was 656 (1% of the total agricultural households in the region) rearing 3,266 pigs. This gives 488,267 827,930 517,144 - 200,000 400,000 600,000 800,000 1,000,000 Number of Sheep ' 1994/95 1998/99 2002/03 Year Chart 3.130 Sheep Population Trend Chart 3.129 Total Number of Sheep ('000') by District 0 30 60 90 120 150 Kishapu Maswa Meatu Bariadi Shinyanga Rural Kahama Shinyanga Urban Bukombe District Number of Sheep ('000') Chart 3.131 Total Number of Pigs by District 0 300 600 900 1,200 1,500 1,800 2,100 Bariadi Kahama Meatu Shinyanga Urban Kishapu District Number of Pigs RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 65 2,771,534 3,747,129 2,979,590 - 1,000,000 2,000,000 3,000,000 4,000,000 Number of Chicken 1994/95 1998/99 2002/03 Year Chart 3.134 Chicken Population Trend an average of 5 pigs per pig-rearing household. The district with the largest number of pigs was Shinyanga Urban with 1,931 pigs (59% of the total pig population in the region) followed by Meatu (736 pigs, 23%). Other District (Bariadi, Kahama and Kishapu) had insignificant number of Pigs. However, Shinyanga Urban district had the highest density (9 head per km2) (Map 3.54). The Sample Census could not enumerate any pigs from Maswa, Bukombe and Shinyanga Rural Districts, (chart 3.131). 3.12.5 Chicken Production The poultry sector in Shinyanga region was dominated by chicken. The region contributed 9 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 257 ,044 raising about 2,979,590 chickens. This gives an average of 12 chickens per chicken-rearing household. In terms of total number of chickens in the country, Shinyanga region was ranked first for having the largest number of chicken out of the 21 Mainland regions. The District with largest number of chickens was Bariadi (872,294 chickens, 29% of the total number of chickens in the region) followed by Shinyanga Rural (551,354, 19%), Maswa (405,569, 14%), Shinyanga Urban (383,126 13%), Meatu, (309,349, 10%), Bukombe, (229,146, 8%) and Kishapu, (187,361, 6%). Kahama district had the smallest number of chickens (40,890, 1%) (Chart 3.133 and Map 3.55). However Shinyanga Urban district had the highest density (1,689 head per km2) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 0.91 percent. The population increased at a rate of 7.83 percent from 1995 to 1999 after which it decreased to -5.57 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Shinyanga region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. Chart 3.133 Total Number of Chicken ('000') by District 0 100 200 300 400 500 600 700 800 900 1,000 Bariadi Shinyanga Rural Maswa Shinyanga Urban Meatu Bukombe Kishapu Kahama District Number of Chicken ('000') RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 66 3.12.5.3 Chicken Flock Size The results indicate that about 83 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 16.8 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 39 chickens per holder. Only 0.2 percent of holders kept the flock sizes of more than 100 chickens at an average of 117 chickens per holder (Table 3.14). 3.12.5.4 Improved Chickens (layers and broilers) The number of Layers and Broiler chicken population in Shinyanga Region was 11,276 and 32,934 respectively. In comparison to the total human population of the region the number of improved chicken is not significant. 3.12.6. Other Livestock There were 94,783 ducks, 708 turkeys, 5,263 rabbits and 4,421 donkeys raised by rural agricultural households in Shinyanga region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Bariadi District (56% of all ducks in the region), followed by Shinyanga Rural (14%), Maswa (10%), Kishapu (5%) and Kahama (5%). Meatu and Shinyanga Urban Districts district had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Meatu , Bariadi and Shinyanga Urban districts only. Rabbits were only reported in Bariadi District and the number was 5,263. Donkeys were mostly reported in Bariadi 49%, Kahama 22%, Shinyanga Rural 14% and the least number donkeys was found in Kishapu and Shinyanga Urban (Table 3.15). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 68 percent and 9 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Meatu district. (Map 3.57). The most practiced method of tick controlling was spraying with 77 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (2%), smearing (1%) and other traditional methods like hand picking (8%). However, 13 percent of livestock- keeping households did not use any method. Table 3.14 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 54,834 21 156,753 3 5-9 82,532 32 546,340 7 10-19 77,801 30 999,425 13 20-29 25,519 10 564,268 22 30-39 9,060 4 285,517 32 40-49 2,448 1 105,425 43 50-99 4,350 2 263,212 61 100+ 501 0.19 58,649 117 Total 257,044 100 2,979,590 12 Table 3.15 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Bariadi 53,587 179 5,263 2,170 . Maswa 9,193 . . . 1,734 Shinyanga Rural 13,516 . . 612 1,487 Kahama 5,165 . . 981 1,715 Bukombe 4,063 . . . 3,734 Meatu 2,249 497 . . 2,637 Shinyanga Urban 1,851 32 . 415 . Kishapu 5,160 . . 244 632 Total 94,783 708 5,263 4,421 11,938 Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Bariadi Kahama Shinyanga Rural Meatu Maswa Kishapu Shinyanga Urban Bukombe District P ercent Tick problems Tsetse flies problems Maswa Kishapu Shinyanga Urban Shinyanga Rural Bukombe Meatu Bariadi 5.5 14.8 9.1 26.1 15 32.5 21.5 Kahama 578.8 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Kishapu Maswa Shinyanga Rural Bariadi Shinyanga Urban Bukombe 30,133 131,296 8,745 78,539 95,895 12,403 53,163 106,969 Kahama Meatu 120,000 to 140,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Map 3.33 SHINYANGA Sheep Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Sheep Number of Sheep Number of Sheep Per Square Km Map 3.34 SHINYANGA Sheep Density by District as of 1st October 2003 Number of Sheep Per Square Km RESULTS 67 Bariadi Kishapu Shinyanga Urban Shinyanga Rural Kahama Bukombe 0.1 0.2 0 0 0 0.1 0 Maswa Meatu 8.5 6.8 to 8.5 5.1 to 6.8 3.4 to 5.1 1.7 to 3.4 0 to 1.7 Bariadi Kishapu Shinyanga Urban Shinyanga Rural Bukombe 296 736 0 82 0 221 0 Kahama Maswa Meatu 1,931 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Map 3.35 SHINYANGA Pig Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Pig Number of Pig Number of Pig Per Square Km Map 3.36 SHINYANGA Pig Density by District as of 1st October 2003 Number of Pig Per Square Km RESULTS 68 Kahama Shinyanga Urban Maswa Kishapu Shinyanga Rural Bukombe 11.5 253.7 239.2 104.7 92.2 403.4 55.8 Meatu Bariadi 1,689 26,000 to 30,000 20,000 to 26,000 14,000 to 20,000 8,000 to 14,000 2,000 to 8,000 Maswa Shinyanga Rural Bukombe Meatu Kishapu Shinyanga Urban 405,569 551,354 383,126 229,146 40,890 872,794 309,349 187,361 Kahama Bariadi Map 3.37 SHINYANGA Chicken Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken Number of Chicken Per Square Km Map 3.38 SHINYANGA Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km 800,000 to 1,000,000 600,000 to 800,000 400,000 to 600,000 200,000 to 400,000 0 to 200,000 RESULTS 69 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 70 The most common method used to control tsetse flies was spraying which was practiced by 42 percent of livestock-rearing households This was followed by dipping (9%) and trapping (3%). However, 36 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 72,356 (43% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 13 percent, goats (37%) and sheep (5%), (chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 49,733 representing 28 percent of the total livestock-rearing households and 13 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 94 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (4%), Cooperatives (2%) and large-scale farmers (2%),. About 62 percent of livestock rearing households described the general quality of livestock extension services as being good, 19 percent said they were average and 17 percent said they were very good. However, 1 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Veterinary clinics were located very far from livestock rearing households. About 84 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 16 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected district was Bariadi district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Shinyanga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.141). 0 10 20 30 Percen Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Poor 1% Average 19% Very Good 17% No Good 1% Good 62% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 71 Chart 3.142 Number of Households by Distance to Village Watering Points 15 or more Kms 2% Less than 5 Kms 85% 5 - 14 Kms 13% 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 84,182 (85% of livestock rearing households in Shinyanga region) whilst 12,569 households (13%) resided between 5 and 14 kms. However, 1,555 households (2%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Shinyaga Urban district had the best livestock water supply with the majority of livestock rearing households (97%) residing within 5 kms from the nearest watering point. This is followed by Kahama (93%), Maswa (92%), Bukombe (92%), Shinyanga Rural (90%). Kishapu (83%), Bariadi (75%) and Meatu (66%). In Kishapu, Bariadi and Meatu districts there is a considerable number of households accessing water points at a distance of more than five kilometers from their residences, which is about 17, 25 and 34 percent respectively (Chart 3.143). Chart 3.141 Number of households by Distance to Veterinary Clinic and District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Number of Households Less than 14 Km More than 14 Km Chart 3.140 Percent of households by Distance to Veterinary Clinic More than 14 Km 84% Less than 14 Km 16% Chart 3.143 Percent of households by Distance to Village Watering Points and District 0 10 20 30 40 50 60 70 80 90 100 Shinyanga Urb Kahama Maswa Bukombe Shinyanga Rur Kishapu Bariadi Meatu District Number of Households Less than 5 Kms 5 - 14 Kms 15 or more Kms RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 72 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Shinyanga region was highly practiced with a total 246,196 (65%) agricultural households Practicing it (Chart 3.144). Kishapu, Shinyanga Rural and Bariadi Districts are the best in use of draft animals in farming practices with over 80% of all agricultural households in these districts using the method. The Percent of Agricultural households using this method in Maswa, Meatu and Shinyanga Urban was 79%, 78% and 86% respectively. The method was scarcely practiced in Kahama and Bukombe Districts (Chart 3.145 and Map 3.58). The region had 1,247,888 oxen (Bariadi 344,077 oxen, Shinyanga Rural 205,171 oxen, Kishapu 164,453 oxen, Maswa 162,943 oxen, Kahama 156,129 oxen, Meatu 137,537 oxen, Bukombe 44,749 oxen, Shinyanga Urban 32,829 oxen). This represents only 27 percent of the total oxen found on the Mainland. The total Area Cultivated by using oxen was 630,546 hectares of land (Bariadi 157,648 ha, Kishapu 103,484 ha, Maswa 94,038 ha, Shinyanga Rural 80,035 ha, Meatu 77,393 ha, Kahama 69,368 ha, Bukombe 36,302 ha, Shinyanga Urban 12,277 ha). The largest area cultivated using oxen was found in Bariadi district (157,648 ha, 25% of the total area cultivated using oxen in the region). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Shinyanga region was 83,843 (22% of total crop growing households in the region) (Chart 3.146). 3.144 Number of Households Using Draft Amimals Using Draft Animals, 246,196, 65.2% Not Using Draft Animals, 131,662, 35% 0 10 20 30 40 50 60 70 80 90 Number of Households Kishapu Shinyanga Rural Bariadi Maswa Meatu Shinyanga Urban Kahama Bukombe Chart 3.145 Number of Households Using and NOT using Draft Animals by District - SHINYANGA Using Draft Animals Not Using Draft Animals ` Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 83,843, 22% Not Using Organic Fertilizer, 291,423, 78% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 73 The total area applied with organic fertiliser was 87,950 ha of which 82,243 hectares (94% of the total area applied with organic fertiliser) was applied with farm yard manure (Map 3.59). Farm Yard Manure was mostly applied in Kahama, Shinyanga Rural, Bariadi, Maswa and Bukombe Districts. 3.12.9.3 Use of Compost Only 5,707 ha (6% of the area of organic fertilizer application) was applied with compost. The largest area applied with Composit manure was found in Kahama district with 2,875 hectares followed by Bukombe (1,301 ha, 11%), (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Shinyanga region was very small (insignificant) which was 430, representing 0.1 percent of the total agricultural households in the region and fish farming was only reported in Kahama District. Chart 3.147 Area of Application of Organic Fertiliser by District - SHINYANGA 0 5,000 10,000 15,000 20,000 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Area of Fertiliser Applicatio Farm Yard Manure Compost Shinyanga Rural Bariadi Maswa Kishapu Meatu Shinyanga Urban Bukombe 39,760 6,894 67,493 34,293 31,630 32,470 8,972 87.8% 67.6% 87% 79.3% 78.4% 88.8% 40% 16.9% Kahama 24,684 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Bariadi Meatu Maswa Kishapu Shinyanga Rural Shinyanga Urban Kahama Bukombe 29,822 10,954 12,964 2,770 11,744 14,079 22,402 7,564 83.7% 70.8% 64% 60.9% 46.1% 70.9% 73.5% 42.1% 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.39 SHINYANGA Number and Percent of Households Infected with Ticks by District Tanzania Agriculture Sample Census Number of Households Infected with Ticks Number of Households Infected with Ticks Number of Households Using Draft Animals Map 3.40 SHINYANGA Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Percent of Households Infected with Ticks Percent of Households Using Draft Animals RESULTS 74 Shinyanga Urban Maswa Kishapu Shinyanga Rural Meatu Bariadi Kahama Bukombe 263ha 214ha 41ha 7ha 585ha 421ha 2,875ha 1,301ha 0.7% 4.6% 10.2% 3.7% 0.1% 7.4% 50.4% 22.8% 2,000 to 2500 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Bariadi Maswa Meatu Kishapu Shinyanga Urban Shinyanga Rural Kahama Bukombe 11,100ha 6,643ha 10,298ha 3,217ha 5,134ha 14,035ha 21,123ha 10,693ha 13.5% 8.1% 12.5% 6.2% 3.9% 17.1% 25.7% 13% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Map 3.41 SHINYANGA Planted Area and Percent of Total Planted Area with Farm Yard Manure Application by District Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure applied Planted Area with Farm Yard Manure applied Planted Area with Compost Manure Application Map 3.42 SHINYANGA Planted Area and Percent of Total Planted Area with Compost Manure Application by District Planted Area with Compost Manure Application Percent of Area Planted with Farm Yard Manure applied Percent of Area Planted with Compost Manure Application RESULTS 75 RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 76 Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 318,745 , 84% Flush Toilet, 12,686 , 3% No Toilet , 43,503 , 12% Other Type, 474 , 0% Improved Pit Latrine , 2,450 , 1% 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were Tarmac Road (68), Hospital (41), District Capital (39, Tertiary Market (34) Secondary School (19) Secondary Market (17), Primary Market (8), Health Clinic / Dispensary (8), All weather Road (7), Primary School (2), Feeder Road (2) Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 20 percent reported them to be average. Thirty percent of the agricultural households said the infrastructure and services were poor , and 25 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (318,745 households, 84% of all rural agricultural households) 12,686 households (3%) use Flush Toilets and 2,450 households (1%) use Improved Pit Latrine. The remaining 474 household (0.13%) use other toilets facilities. However, 12,686 households (12%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 37 percent of them were found in Kahama District and 1 percent were from Shinyanga Urban District. The percentages of households without toilets in other districts were as follows Bariadi (21%), Maswa (12%), Shinyanga Rural and Bukombe Districts (10%), Kishapu (6%), and Bukombe (2%). Table 3.17: Mean distance from household dwelings to Infrastructures and services by District District Primary School Secondary School Health Clinic / Dispensar y Hospital District Capital Regional Capital Feeder Road All weather Road Tarmac Road Primary Market Secondary Market Tertiary Market Bariadi 3.1 14.9 5.2 31.7 34.0 163.9 2.4 13.9 114.0 8.5 20.7 27.9 Maswa 2.4 16.3 6.1 32.5 32.0 102.4 3.3 3.5 98.8 6.5 14.1 22.6 Shinyanga Rur 1.8 19.5 4.4 46.7 47.1 49.1 1.4 5.8 43.0 7.5 12.4 43.5 Kahama 2.1 21.0 11.2 44.7 44.6 147.7 1.7 8.0 35.9 6.4 15.7 40.4 Bukombe 2.4 18.7 10.7 52.2 40.3 196.3 2.0 3.9 14.8 7.2 13.5 23.3 Meatu 2.9 22.1 8.3 42.7 46.1 174.7 2.3 5.6 169.4 9.1 13.7 54.1 Shinyanga Urb 1.7 7.6 5.1 10.0 11.1 14.9 1.3 2.7 13.1 6.2 9.0 9.4 Kishapu 2.1 23.2 7.4 45.2 38.3 52.8 2.8 3.6 43.9 12.6 26.1 41.3 Total 2.4 18.6 7.7 40.9 39.3 130.6 2.2 7.1 68.3 7.9 16.5 34.2 Meatu Kishapu Maswa Bariadi Shinyanga Rural Shinyanga Urban Kahama Bukombe 0 0 0 0 0 0 430 0 0% 0% 0% 0% 0% 0% 0.5% 0% 360 to 430 270 to 360 180 to 270 90 to 180 0 to 90 Kishapu Bariadi Maswa Shinyanga Rural Meatu Shinyanga Urban Kahama Bukombe 2,714 9,310 5,344 473 892 4,145 16,227 4,398 7.6% 12% 12.4% 2.8% 4.6% 9.2% 20% 8.3% 12,000 > 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Map 3.43 SHINYANGA Number and Percent of Households Practicing Fish Farming by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Number of Households Without Toilets Facilities Map 3.44 SHINYANGA Number and Percent of Households Without Toilets Facilities by District Number of Households Without Toilets Facilities Percent of Households Practicing Fish Farming Percent of Households Without Toilets Facilities RESULTS 77 RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 78 3.13.3 Household’s Assets Bicycles were owned by most rural agricultural households in Shinyanga region with 246,531 households (65% of the agriculture households in the region) owning the asset. followed by Radios ( 192,251 households, 51%), iron (64,449 households, 17%), wheelbarrow (39,393 households, 10%), mobile phone (5,725 households, 2%), television/video (3,692 households, 0.96), vehicle (4,236 households, 1.1%) and landline phone (858 households, 0.23%), (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting en ergy in the region. with 81 percent of the total rural households using this source of energy followed by hurricane lamp (14%), Pressure lamp (3%), Firewood and Electricity (1%). Other Means of lighting using Candles and Biogas are scarcely used in the region (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95 percent of all rural agricultural households in Shinyanga region. This is followed by charcoal (4%). The rest of energy sources accounted for 1 percent. These were bottled gas (0.05%), crop residues (0.64%), mains electricity (0.15%), livestock dung (0.26%), parrafin/kerosene (0.1%) and gas/biogas (0.05%), (Chart 3.154). 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 35 percent of the rural agricultural households. This was closely followed by iron sheets (33%) and grass/mud (30%), (Chart 3.155). Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Concrete 0.1% Asbestos 0.3% Other 0.4% Grass / Leaves 35.1% Iron Sheets 33.2% Grass & Mud 30.4% Tiles 0.5% Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 302,123 , 81% Firewood, 5,044 , 1% Solar, 443 , 0% Candles, 785 , 0% Gas (Biogas), 498 , 0% Mains Electricity, 2,485 , 1% Hurricane Lamp, 54,233 , 14% Pressure Lamp, 12,214 , 3% Chart 3.152 Percentage Distribution of Households Owning the Assets 10 2 1 1 0 17 51 65 0 20 40 60 Bicycle Radio Iron W heelbarrow M obile phone V ehicle Television / V ideo Landline phone Assets Percent RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 79 Tiles (0.54%), os (0.28%) and Concrete (0.06%) roofing style were scarcely used in the region (Chart 3.155). Kishapu district had the highest percentage of households with grass/leaves roofing (83%) followed by Shinyanga Rural district (82%), Shinyanga Urban (76%), Maswa (75%), Kahama (71%), Meatu (70%), Bukombe (65%) and Bariadi (34%) (Chart 3.156 and Map 3.63). Bariadi district had the highest percentage of households with Iron Sheets roofing (64%) followed by Bukombe district (34%), Kahama District (28%), Meatu (28%), Maswa (25%), Shinyanga Urban (24%), Shimyanga Rural (17%) and Kishapu (14%) (Chart 3.156B and Map 3.63) Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 0 20 40 60 80 100 Kishapu Shinyanga Rural Shinyanga Urban Maswa Kahama Meatu Bukombe Bariadi District Percen Chart 3.156B Percentage Distribution of Households with Iron Sheets Roofs by District - 20 40 60 80 100 Bariadi Bukombe Kahama Meatu Maswa Shinyanga Urban Shinyanga Rural Kishapu District Percen RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 80 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Shinyanga region was unprotected Wells (33 percent of households use unprotected wells during the wet season and 31 percent of the households during the dry seasons). This is followed by protected wells (26% and 28% of households for wet and dry seasons respectively), Surface water (16% of households during the wet season and 19% in the dry season), Piped water (12% of households in the wet season and 13% during dry season). Other sources of drinking water like uncovered rain water catchments, Unprotected/protected Spring, Bottled Water, Water vendor and Tank truck are scarcely used in the region Chart 3.157) Bukombe District had the highest percent of Agricultural Households whose main source of drinking water was Unprotected wells (61% of households during the wet season and same number during dry season), followed by Kahama District 47% of households during the wet season and 48% in the dry season). About 44 percent of the rural agricultural households in Shinyanga region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 56 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). Chart 3.157 Percent of Households by Main Source of Drinking Water and Season - 10 20 30 40 Uprotected Well Protected Well Surface Water Piped Water Uncovered Rainwater Unprotected Spring Protected / Covered Bottled Water Covered Rainwater Water Vendor Tanker Truck Main source Percent of Household Wet Dry Chart 3.158 Percentof Households by Distance to Main Source of Drinking Water and Season - 10 20 30 40 Less than 100m 500 - 999 m 5 - 9.99 Km 300 - 499 m 3 - 4.99 Km 2 - 2.99 Km 10Km and above 100 - 299 m 1 - 1.99 Km Distance Percent Wet Serason Dry Season RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 81 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Shinyanga region normally have 3 meals per day (54 percent of the households in the region). This is followed by 2 meals per day (44 percent) and 1 meal per day (2 percent). A small number of Agricultural Households 0.27 percent normally have 4 meals per day (Chart 3.159). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District One % Two % Three % Four % Total Bariadi 714 9 48,466 29 28,038 14 353 34 77,572 Maswa 1,607 20 13,758 8 27,886 14 - - 43,252 Shinyanga Rural 1,715 21 14,494 9 28,952 14 102 10 45,263 Kahama 561 7 34,903 21 45,609 23 144 14 81,217 Bukombe 956 12 38,793 23 13,492 7 - - 53,240 Meatu 2,310 28 9,744 6 19,229 10 209 20 31,492 Shinyanga Urban 71 1 2,537 2 7,527 4 64 6 10,198 Kishapu 239 3 4,352 3 30,870 15 163 16 35,624 Total 8,173 100 167,046 100 201,603 100 1,035 100 377,857 Number of Meals per day District Meatu district had the largest percent of households eating one meal per day whilst Kahama had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.64). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 214,120 (57% of the agricultural households in Shinyanga region) with 86,741 households (57% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31%). Very few households had meat three or more times during the respective week. About 43 percent of the agricultural households in Shinyanga region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). Chart 3.159 Number of Agricultural Housedholds by Number of Meals per Day Three, 201,603 , 54% Two, 167,046 , 44% One, 8,173 , 2% Four, 1,035 , 0% Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 25,000 50,000 75,000 100,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Househ Meat Fish RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 82 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 175,529 (46% of the total agricultural households in Shinyanga region) with 90,113 households (51 % of those who consumed fish) consuming fish only once during the respective week. This was followed by those who had fish twice (27%). In general, the percentage of households that consumed fish three times or more during the week in Shinyanga region was 38,375 (23% of the agricultural households that ate fish in the region during the respective period). About 54 percent of the agricultural households in Shinyanga region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66) 3.13.9 Food Security In Shinyanga region, 134,001 households (35% of the total agricultural households in the region) said they seldom experienced problems in satisfying the household food requirement. However 55,062 (14%) said they often experience problems, 38,789 always experienced problems and 6.4 percent sometimes had problems in satisfying the household food requirement. About 33 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main cash income of the households in Shinyanga region was from selling food crops (39.2 percent of smallholder households), followed by Sales of Cash Crops (31.8), Casual Cash earnings 13%), businesses income and Sales of Livestock each 4.9%. Other Means of income were Wages and Salaries (2.1%), Cash Remittances (1.1%), Sales of Forestry Products (1%), Sales of Livestock Products (1%) a and cash remittances (1%) and Fishing (1%)., (Chart 3.161) Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Fishing, 0.2, 0% Sales of Food Crops, 39.2, 39% Other Casual Cash Earnings, 13.3, 13% Sales of Cash Crops, 31.8, 32% Business Income, 4.9, 5% Sale of Livestock, 4.9, 5% Wages & Salaries in Cash, 2.1, 2% Sale of Livestock Products, 0.9, 1% Sale of Forest Products, 1.0, 1% not applicable, 0.5, 1% Cash Remittance, 1.1, 1% Shinyanga Rural Shinyanga Urban Bariadi Maswa Kishapu Kahama Bukombe 7,527 28,952 28,038 27,886 19,229 30,870 45,609 13,492 4% 14% 14% 10% 15% 14% 23% 7% Meatu 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Shinyanga Urban Kahama Shinyanga Rural Kishapu Maswa Bariadi Bukombe 2,405 7,831 23,036 5,055 10,796 8,751 49,428 18,127 23.6% 17.3% 28.4% 14.2% 25% 27.8% 63.7% 34% Meatu 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.45 SHINYANGA Number and Percent of Households Using Grass/Leaves for Roofing RESULTS 83 Material by District Tanzania Agriculture Sample Census Households Using Iron Sheets for Roofing Material Households Using Iron Sheets for Roofing Material Households Eating 3 Meals per Day Map 3.46 SHINYANGA Number and Percent of Households Eating 3 Meals per Day by District Households Eating 3 Meals per Day Percent of Households Using Iron Sheets for Roofing Material Percent of Households Eating 3 Meals per Day Shinyanga Urban Kahama Shinyanga Rural Kishapu Maswa Bukombe Meatu Bariadi 3,351 7,786 7,779 6,223 24,634 18,589 6,311 15,442 10.9% 11.9% 10.9% 13.5% 1.9% 1.8% 14.6% 45.4% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Shinyanga Urban Shinyanga Rural Bukombe 3,547 16,218 11,315 26,425 24,736 10,575 9,431 18,863 2.9% 13.4% 9.3% 20.4% 21.8% 8.7% 7.8% 15.6% Kahama Maswa Kishapu Meatu Bariadi 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.47 SHINYANGA Number and Percent of Households Eating Meat Once per Week by District Tanzania Agriculture Sample Census Number of Households eating Meat Once per Week Number of Households eating Meat Once per Week Number of Households eating Fish Once per Week Map 3.48 SHINYANGA Number and Percent of Households Eating Fish Once Per Week by District Number of Households eating Fish Once per Week Percent of Households eating Meat Once per Week Percent of Households eating Fish Once per Week RESULTS 84 Kishapu Shinyanga Urban Maswa Shinyanga Rural Bariadi Meatu Bukombe 1,093 43,252 77,572 31,492 35,624 45,263 81,217 53,240 11.4% 2.7% 20.5% 8.3% 9.4% 12% 21.5% 14.1% Kahama Map 3.49 SHINYANGA Number and Percent of Households Reporting Food Insufficiency by District Tanzania Agriculture Sample Census Number of Households Reporting food insufficiency Number of Households Reporting food insufficiency Percent of Households Reporting food insufficiency 80,000 to 90,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 85 DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 86 4 SHINYANGA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Shinyanga Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. Shinyanga has the largest rural agriculture population in Tanzania (2,426,406 persons of which 1,240,181 are male and 1,186,224 female). It also has the highest number of rural agriculture households (377,857) which represents 96.4 percent of the number of rural households and 84.9 percent of the total number of households in the region (includes urban households). The region has the highest number of persons per household (6.4 per household) and one of the lowest percent of female headed households (14%). The crop farming only and mixed crop and livestock farming are equally important. The region has no pastoralists, however it has a moderate number of households involved in livestock herding only. Shinyanga region has similar number of males and females (51% males and 49% females). The region has a normal population pyramid with a wider base compared to other regions. The region has an active agriculture population of 1,209,803 of which 608,972 are males and 600,832 are females resulting in a moderate difference between the percent of total male and female active population in the region 50.3% and 49.7% respectively). The region has the highest number of households in the country compared to other regions (377,857 out of which 323,921 are male headed and 53,936 are female headed) and it has the 3rd lowest percent of female headed households compared to other regions in the country. The average household size is larger than the National average (6.7 members per household for male headed households and 4.8 for female headed households), resulting in a difference in the household size of 1.9 more members in male headed households compared to female headed households. There is no difference in the dependency ratio between male and female headed households (111 dependants for every 100 active members in male headed households and 112 dependants for every 100 active members in female headed households). The region has a small difference in sex ratio of the active agriculture population between male and female headed households compared to most other regions (109:100 in male headed households compared to 57:100 in female headed households). Shinyanga has the 18th largest difference in illiteracy rate between male and female household heads with an illiteracy rate of 31 percent of male household heads and 70 percent of female household heads. Taking the overall population of male and female members in the region there are 13 percentage points more illiterate females than males and this is the 4th largest difference in the country. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 87 Shinyanga has a moderate percent of orphans in the country compared to other regions and it has a higher percent of orphans in male headed households compared to female headed households. No orphan headed households were detected in Shinyanga. Shinyanga has around 4 percent of children with off farm income and there is no difference between male and female headed households. Shinyanga has the largest area of land under cultivation (over 1,250,000 ha) and has the highest land utilisation per household (over 2.6 hectares for annual crops). Virtually no permanent crops are grown and it has the largest area of pasture to supports the high population of cattle in the region. A large proportion of smallholder households in the region felt that they did not have sufficient land. The region has the largest planted area of maize and second largest for paddy and sorghum than other regions in Tanzania, however it had one of the lowest yields for maize during the census year. During the Census year planting was largely during the Wet season. The region is not important for cassava, beans and fruit and vegetable production but, it has the third largest planted area of groundnuts in the Tanzania. In terms of cash crops, Shinyanga is the most important region for cotton production. Considering Shinyanga has the largest planted area of crops, it has one of the smallest areas of irrigation. It also has the largest planted area cleared by hand but most soil preparation is done by oxen. Most of the planted area is without fertiliser and the small area that has, it is with farm yard manure. Low fertiliser use and lack of irrigation facilities may have contributed to the low yields for this region. Although small, it has the largest planted area with insecticide and fungicide application. Over half of the crops stored are in sacks or open drums with the remainder in locally made traditional structures. Crop processing is predominantly done by neighbours’ machines and the processed production is for home consumption. Considering Shinyanga is one of the most important crop growing regions, it only has moderate contact with extension services. The region relies more on animal draft than most other regions. The region has one of the smallest areas of planted trees per household and lowest percent of erosion control facilities in Tanzania. Shinyanga has the largest population of livestock in the country. It has the highest number of cattle and second highest head of goats with small sheep numbers and virtually no pigs (very small number compared to actual number of agricultural households). The region has the second highest density of cattle and the density of goats is moderate compared to Mwanza, Arusha, Kilimanjaro and Mara. It is the second largest milk producing region in the country and it has one of the lowest farm gate prices for milk. Very low numbers of improved livestock are found in the region. Shinyanga region has the 6th highest percent of households keeping livestock and also the largest difference between male and female headed households, with 19 percentage point more male headed households keeping livestock compared to female headed households. It has the highest chicken population with the highest density in the country. Most of the chickens are indigenous with very few improved types and the number of layers is very low compared to many other regions. A small number of eggs are produced indicating that most of the chickens are used for meat. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 88 The area cultivated by draft animals in Shinyanga is much higher than in any other region which supports the predominance of mixed farming in the region. The region has one of the highest areas of organic fertiliser application and the area applied per household is comparatively high. Considering the high livestock population, the region had moderate to low rates of disease infection. In general the access to livestock infrastructure and services is poor to moderate. Practically all extension was provided by the government. A small amount of fish farming is practiced in the region. As with all regions, Shinyanga has more land per household in male headed households than in female headed households. It has a large difference between male and female headed households with 1.7ha more in male headed households compared to female headed households. Shinyanga region has a high percent of households reporting insufficiency of land (56%) and a slightly higher percent of female headed households have insufficient land compared to male headed households. Female headed households in the region have around 19 percentage points more female land holders compared to male headed households and this difference is one of the largest compared to other regions. In Shinyanga, 42 percent of female headed households have female land holders. Assuming that male household members of female headed households do not have rights to land, this would imply that 58 percent of female headed households have insecure access to land. Shinyanga has a higher percent of female headed households using land under customary law and bought compared to male headed households, whilst a higher percent of male headed households have bought land than female headed households. Shinyanga has a high percent of households keeping cattle (42%) and 19 percentage points more male headed households keep cattle than female headed households. Male headed households keep around 5 more cattle per household than female headed households. Goats are moderately important in the region with 34 percent of households keeping them and 11 percentage points more households keep goats compared to female headed households. Male headed households keep slightly more goats per household that female headed households. Shinyanga has the 3rd highest number of households with sheep and slightly more sheep are kept per household in male headed households than in female headed households. Compared to other regions, Shinyanga has a moderate to high percent of households using improved seeds (3rd highest) and there is little difference between male and female headed households. Compared to other regions Shinyanga, has a moderate to high percent of households using insecticides (15%) and 7 percentage points more male headed households use it compared to female headed households. The region has a moderate to high percent of households not using fertilisers (76%). It has a moderate to high percent of households using farm yard manure (17% of households in the region) with 7 percentage point more male headed households using farm yard manure than female headed households. Inorganic fertiliser is used by a small percent of households in the region and there is no difference between male and female headed households. The region has a very small area of land under irrigation (0.5%) and male headed households have a slightly higher percent of households with irrigation compared to female headed households. Shinyanga region has a low percent of households receiving extension advice and there is little difference between male headed households and female headed households. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 89 The region has a Wety season only. In the region, 99.2 percent of male headed households and 99.1 percent of female headed households plant crops. Shinyanga has the 7th lowest percent of its planted area with maize and a higher percent of female headed households planted area is with maize compared to male headed households. The yield of maize in the region is low (0.5t/ha) and male headed households have 0.15t/ha more than female headed households. A moderate to high percent of households grow paddy in the region (12%) and there is no difference between male and female headed households. Shinyanga has a moderate to high percent of households utilising secondary products (35 percent of households) and there is little difference in utilisation between male and female headed households. Shinyanga region has the highest percent of active agriculture household members working full time on farm (90% of active members) and there is no difference between male and female headed households. Of the most active agriculture population (18 to 44 years of age) 94 percent of males and 96 percent of females are mainly involved in agriculture. In male headed households, 94 percent of the male members and 96 percent of female members are mainly involved in agriculture, whilst in female headed households 90 percent of males and 95 percent of females are mainly involved in agriculture. Shinyanga region has one of the highest percent of boys and girls involved in agriculture (26% of boys and 21% of girls). A higher percent of boys are involved in female headed households compared to male headed households, however there is no difference in the percent of girls involved in agriculture between male and female headed households. Around 38 percent more elderly males are involved in agriculture compared to elderly females. Shinyanga region has one of the highest percent of households storing crops (85% of households) compared to other regions with more male headed households storing crops than female headed households. There is no difference between male and female headed households in the percent of households storing for consumption. The region has slightly more male headed households facing storage losses compared to female headed households. A higher percent of male headed households store crops in locally made traditional cribs, whilst more female headed households store crops in sacks/open drum. Shinyanga has a small percent of the households in the region receiving credit (2%) and more there is no difference between male and female headed households. The main reason for not using credit is that they do not know how to access it, followed by don’t know about credit and not available and there is no difference between male and female headed households. The region has a moderate percent of households with modern roofing material in the country (35% of households in the region) and there is little difference between male and female headed households. It has one of the lowest percent of households using hurricane/pressure lamps for lighting and there is little difference between male and female headed households. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 90 Compared to other regions, Shinyanga has a low percent of households using piped drinking water (11%) and there is no difference between male and female headed households. The region has a moderate percent of households without toilets compared to other regions and more female headed households have no toilets than male headed households. The difference in the ownership of assets (radio, iron and bicycle) between male and female households is high, in favour of male headed households, for all regions. Shinyanga has a moderate to low percent of households with radios, a moderate percent of households with irons, and one of the highest percent of households with bicycles in the country. Male headed households have 26 percentage points more radios, 9 percentage points more irons and 33 percentage points more bicycles than female headed households. Household members in Shinyanga region have a moderate to high number of meals per day in the country. And there is no difference between male and female headed households. The region has the fifth lowest number of time the household members eat meat in a week and this is lower in female headed households than in male headed households, with male headed households eating meat around 0.9 times per week, whilst female headed households eat meat 0.4 times per week. Shinyanga has a large difference in the percentage of male and female headed households facing food shortages. Eleven percentage points more female headed households often or always face food shortages compared to male headed households. Right to land is mostly by customary law (60% of total land area under agriculture), however a moderate to high proportion is bought land. It has one of the lowest percent of households with official certificates of ownership. Access to fields is moderate compared to other regions with 50% of the households having their nearest field less than 100m from the Homestead. However the distance from the field to the nearest road is one of the farthest in the country. Shinyanga has the fourth lowest percent of literate rural agriculture population in the country and the difference between the literacy rate of males and females is amongst the highest. It has a comparatively low percent of the rural agriculture population that have completed school and the third highest percent of household heads with no education. The most important livelihood activity is crop farming followed by remittances. The percent of the rural agriculture population working full time in farming is fifth lowest in the country, however it has one of the highest percent working part time in agriculture. The main source of cash is from the sale of food crops, the second most important source of cash income is from the sale of cash crops. Other sources are of minor importance. Very small amount of credit is available in the region. Around 30 percent of households have the roof of the main dwelling made of modern material (mainly iron sheets) and the rest is mainly with grass/leaves/mud and only 11 percent of the households have no toilet facility. Energy for lighting is mainly from wick lamps and a very small proportion from hurricane lamps. Shinyanga has one of the lowest percent of piped drinking water supply and most is from unprotected or protected wells Most rural agriculture smallholders are living a subsistence existence with only 5 percent of households using their livelihood activities for non subsistence purposes. The region has the highest percent of households that do not eat animal DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 91 protein in a week and the smallest number that eat animal protein every day. It has a low percent of households that never face food shortage and a high proportion that often or always face shortages. In general access to services is worse than most other regions. About 55.4 percent of the households in the region reported insufficiency of land which is relatively high when compared to some of the regions in the country. 4.2 District Profile The following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Kahama Kahama district has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kahama district is Annual Crop Farming, followed by Livestock Keeping/ Herding. However, the district has the second highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kahama has a relatively low levels of female headed households (14%) and it has one of the lowest average age of the household head. With an average household size of 6.1 members per household it is average for the region. Kahama has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household is also slightly higher than most of districts in the region. It has the moderate utilized land area per household (3.2 ha) and the allocated area is 87% utilized. The District has low area planted per household which is 2.2 compared to other districts. Paddy production is much higher than other districts with a planted area of 53,283 hectares and the area planted per household is 0.66 ha. The district is moderately important for maize production in the region with a planted area of 79,905ha and the planted area per household is 0.98ha. The Production of sorghum is very small. Cassava production is moderate accounting for 24 percent of the quantity harvested in the region. The district has a large planted area of Sweet Potatoes (2,471 ha) accounting for 9 percent of the area planted with the crop in the region. As with other districts in the region, most land clearing and preparation is done by hand, however there is also a moderate practice of using tractor and oxen in the district. The use of inputs in the region is very small, however district differences exist. Kahama has the moderate planted area with improved seed in Shinyanga region. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. The district has also the largest area planted with inorganic fertilizers (90%) probably because of tobacco which widely grown in the district. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 92 Compared to other districts in the region, Kahama district has the highest level of insecticide use, which records 7.1% of the total planted area in the district. Herbicides was also used in the district though not widely, recoding 1.4% of the total planted area in the district. Kahama district has larger area with irrigation compared to other districts with 6,309ha of irrigated land. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage is in sacks or open drums, however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. The highest percent of households processing crops in Shinyanga region is found in Kahama district and is is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 77% and the main sources of credits are Savings and Credit Society and family friends and relatives. Although a very small number of households receive extension service in the region (28%), Kahama district had a moderate proportion of households receiving the service (36%) and the main service provider was from the government. The quality of extension services was rated between Very good and average by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; however it has the smaller number of pigs and chicken in the region. The smallest number of households reporting Tsetse and tick problems was in Kahama district and it had the large number of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Kahama recording 74%. The use of draft animals in the district is moderate to lower having only 40% of households, second from lowest, A small number of households practice fish farming (0.5%), which is only found in the district. The District has amongst the worst access to secondary schools, health clinics, Hospitals, District and regional capitals, tarmac road and terially markets. However the district has amongst the beast access to and primary schools, feeder roads, all wealther roads and secondary markets. Saturday Kahama district has the highest proportion of households with no toilet facilities (20%) and it has the highest percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 0.17% or 17 out 0f 1000 households. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (6%) The district has the highest percent of households with grass roofs (65%) in the region, with 28 percent of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most of the households access source of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 93 drinking water within a distance of less than one kilometer. It has the moderate proportion of households having two or one meal per day compared to other districts. The district had higher percent of households that did not eat meat or fish during the week prior to enumeration, second from top; however about one third of households seldom had problems with food satisfaction. 4.2.2 Bariadi Bariadi district has the larger number of households in the region, second from the top and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bariadi district is Annual Crop Farming, followed by off-farm income. Compared to other districts in the region, Bariadi has a relatively low levels of female headed households (14%) and it has one of the lowest average age of the household head. With an average household size of 6.7 members per household it is highest for the region. Bariadi has a comparatively moderate literacy rate (75.3%) for agricultural household members and the number of heads of agricultural households who have never attended school was moderate (40%), equal to the regional proportion. The literacy rate for the heads of household is also moderate, about the same as the regional proportion (41%). Compared to other district in the region, Bariadi has lower utilized land area per household (2.7 ha) and the average usable land per household is 2.9 ha, which indicate an impeding land pressure. Allocated area is also 91% utilized in the district and the District has low area planted per household which is 2.4 marking a third position from bottom when compared to other districts. The district is important for maize production in the region with a planted area of 101,952ha and the planted area per household is 1.35ha. Paddy production is not very significant in the district when compared to other districts with a planted area of 6,914hectares and the area planted per household is 0.40 ha. Sorghum production is also important in the district with a planted area of 4,175 hectares and the district ranks third from top in the region in terms of area planted. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas and Chick Peas. The district has a large planted area of Cotton (53,882ha), and ranks first in the region in terms of area and production and the average planted are per cotton growing household is 1.1 hectare. About 90% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil prepararion (3%) which is about the same as regional average. The use of inputs in the region is very small, however district differences exist. Bariadi has the higher planted area with improved seed in Shinyanga region. The district has larger planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser) and it ranks second from top when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has smallest area, almost none planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 94 Compared to other districts in the region, Bariadi district has the highest level of insecticide use, which records 31% of the total planted area in the district. However looking at the propotions of area under insecticide use in the region Bariadi ranks first (56.55%). Herbicides was also used in the district though not widely, recoding 18% of the total planted area with herbicides in the district. Bariadi district has larger area with irrigation compared to other districts with 4,966 ha of irrigated land. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is 16% same as the regional proportion. The district has the higher number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (86%) of households processing crops is found in Bariadi district and is mostly all done by neighbouring machine. Although very small, access to credit in the district is mainly to male headed households, which is 77% and the main sources of credits are Religious Organisation / NGO / Project and family friends/ relatives. Although a very small number of households receive extension service in the region, Bariadi district had a lower proportion of households receiving the service (21%) and the main service provider was from the government. The quality of extension services was rated between Very good and Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 6% of all agricultural households reporting to have planted trees. The district has 12.2% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is highest compared to other districts; however a very small number of pigs was kept in rural agricultural households in Bariadi District. It has the highest number of chicken in the region. Higher number of households report Tsetse and tick problems in Bariadi district and it had the largest number of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Bariadi recording 84%. The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, All Weather Road, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, feeder roads, and Primary markets. Saturday Bariadi district has higher proportion of households with no toilet facilities (12%), which is second from highest when compared to other districts and it has higher percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 0.10% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (97%) and very few use charcoal (1%) The district has lower percent of households with grass roofs (23%) in the region, with 64 percent of households having iron sheets roofing. The most common source of drinking water is from Protected Well and most of the households access source of drinking water within a distance of less than two kilometer. It has very low (1%) proportion of households having one meal per day compared to other districts. The district had the DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 95 highest percent of households that did not eat meat or fish during the week prior to enumeration (62%); however about one third of households always and often had problems with food satisfaction. 4.2.3 Maswa Maswa district has larger number of households in the region, fifth from the top and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only, 1% (or 10 households in every 1000 households) households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Maswa district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Maswa has the highest levels of female headed households (20%) and it has one of the highest average age of the household head (48). With an average household size of 6.3 members per household it is moderate for the region, a bit lower than the regional average which is 6.4. Maswa has a comparatively moderate literacy rate (71.3%) for agricultural household members and the number of heads of agricultural households who have never attended school was moderate (45%), above the regional proportion. The literacy rate for the heads of household was 45, above the regional proportion (41%). Compared to other district in the region, Maswa has moderate utilized land area per household (3.7 ha) higher than the regional average which is 3.4. The total usable land per household is 4.0 ha, which indicate an impeding land pressure. Allocated area is also 93% utilized in the district and the District has higher area planted per household which is 3.0 marking a second position from top when compared to other districts. Production of maize is moderately to lower compared to other districts in the region with a planted area of 35,159ha and the planted area per household is 0.92ha. Paddy production is also not higher enough when compared to other districts with a total planted area of 9,975hectares and the area planted per household is 0.40 ha. Sorghum production is also lower in the district with a planted area of 3,098hectares and the district ranks fourth from top in the region in terms of area planted. Sorghum is also grown in the district with an area of 7,950 hectares and area planted per sorghum growing household being 0.8 hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a large planted area with Cotton (44,650ha), and ranks second in the region in terms of area and production and the average planted are per cotton growing household is 1.35 hectare a little higher than the regional average which is 1.31 ha. About 80% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil preparation (8%) which is considerably higher than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Maswa has the higher planted area with improved seed in Shinyanga region. The district has larger planted area with fertilizers (Farm yard manure, compost) and it ranks second from top when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has smaller area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 96 Compared to other districts in the region, Maswa district has lower level of insecticide use, which is 23% of the total planted area in the district , lower than the regional average which is 34.5%. Fungicides was used in the district though not widely, recoding 7.8% of the total planted area with Fungicides in the district. Herbicides was also used in the district though not widely, recoding 0.94% of the total planted area with herbicides in the district. Irrigation was also pracriced in the district though not widely applied on 1,580ha of irrigated land or 1.4% of total planted area. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is higher than other districts in the region. The district has the highest number of households selling crops (79%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (75%) of households processing crops is found in Maswa district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 75% and the main sources of credits is Family, Friend and Relative. Although a very small number of households receive extension service in the region, Maswa district had a lowest proportion of households receiving the service (6%) and the main service provider was from the government. The quality of extension services was rated to Good by the majority of the households (665) that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.0% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; however no pigs were kept in rural agricultural households in Maswa District. The District had moderate number of chicken (14%) in the region. Lower number of households (1%) report Tsetse and tick problems in Maswa district and it had lower proportion of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Maswa recording 64% which is a little bit lower than the regional average (68%). The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and terially markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Maswa district has higher proportion of households with no toilet facilities (12%), which is second from highest when compared to other districts and it has higher percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 100 households. Practically a large number of households use firewood for cooking (93%) and very few use charcoal (6%) The district has lower percent of households with grass roofs (15%) and higher percent of households with Mud Roofs (59%) in the region, low percent (25% ) of households having iron sheets roofing. The most common source of drinking water is from Protected Well and most households access source of drinking water within a distance of less than two kilometer. It has low (4%) proportion of households having one meal per day compared to other districts. The district had higher percent of households that did not eat meat or fish during the week prior to enumeration (57%); however about one third of households always and often had problems with food satisfaction. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 97 4.2.4 Meatu Meatu district has smaller number of households in the region, second from the lowest and the proportion of households involved in smallholder agriculture is 92%, lower than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. . The most important livelihood activity for smallholder households in Meatu district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Meatu has relatively lower levels of female headed households (13%), compared to the regional average, 14%, it has the moderate average age of the household head (46). With an average household size of 7.4 members per household, higher than the regional average which is 6.4. Meatu has a comparatively lower literacy rate (63.9%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was higher (46%), above the regional proportion, 40%. The literacy rate for the heads of household was 54, lower than the regional proportion (59%). Compared to other district in the region, Meatu has higher rate of utilized land area per household (5.1 ha) higher than the regional average which is 3.4. The total usable land per household is 5.6 ha, which indicate a scorching land pressure. Allocated area is also 92% utilized in the district and the District has moderate area planted per household which is 2.5 same as the regional average. Production of maize is lower compared to other districts in the region with a planted area of 31,193ha and the planted area per household is 0.29ha. Paddy production is also lowest when compared to other districts with a total planted area of 349hectares and the area planted per household is 0.27 ha. Sorghum production is highest in the district with a planted area of 24,395hectares and the district ranks First in the region in terms of area planted. The area planted per sorghum growing household is 1.57 hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a large planted area with Cotton (34,028ha), and ranks third in the region in terms of area and production and the average planted are per cotton growing household is 1.35 hectare a little higher than the regional average which is 1.31 ha. About 87% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil prepararion (5%) which is considerably higher than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Meatu has the low planted area with improved seed in Shinyanga region which is only 7% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) and it ranks second from bottom when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal or no area planted with inorganic fertilizers. Compared to other districts in the region, Meatu district has moderate level of insecticide use, which is 36% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 98 district, recoding 0.8% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 0.92% of the total planted area with herbicides in the district. Irrigation was also practiced in the district though not widely applied on 641ha of irrigated land or 0.7% of total planted area. The most common method of crop storage is in locally made traditional cribs, however the proportion of households not storing crops in the district is moderate. The district has the moderate number of households selling crops (59%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (84%) of households processing crops is found in Meatu district and is mostly all done by neighboring machine and by hand. Although very small, access to credit in the district is mainly to male headed households, which is 33% and the main sources of credits is Family, Friend and Relative, Commercial Bank and Trade store. Although a very small number of households receive extension service in the region, Meatu district had higher proportion of households receiving the service (47%), second from top and above from the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good and averge by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is higher compared to other districts; Very few pigs were reported in rural agricultural households (736) in Meatu District with an average of 4 pigs per pig rearing household. The District had moderate number of chicken (10%) in the region. Higher number of households (41%) report Tsetse fly problems in Meatu district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Meatu recording 71% which is a little bit lower than the regional average (68%). The District had moderate proportion of households (47%) de-worming livestock. The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Meatu district has the lowest proportion of households with no toilet facilities (3%), and it has moderate percent of households owning bicycles and radio and higher percent of households owning Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 100 households. Practically a large number of households use firewood for cooking (92%) and very few use charcoal (6%) and Crop Residues. The district has lower percent of households with grass roofs (12%) and higher percent of households with Mud Roofs (57%) and, low percent (28% ) of households having iron sheets roofing. The most common source of drinking water is from surface water (Lake/Dam/River/Stream) and most households access source of drinking water within a distance of less than three kilometer. It has the highest (7%) proportion of households having one meal per day compared to other districts. The district had Moderate percent of households that did not eat meat DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 99 or fish during the week prior to enumeration (42%); however about one third of households always and often had problems with food satisfaction. 4.2.5 Bukombe Bukombe district has moderate number of households in the region, and the proportion of households involved in smallholder agriculture is 99%, higher than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bukombe district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Bukombe has relatively the lowest levels of female headed households 9%, lower than the regional average, 14%, it has the moderate average age of the household head 42, lower than the regional average 46. the District has an average household size of 6.4 members per household, same as the regional average which is also 6.4. Bukombe has a comparatively higher literacy rate (76.5%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was higher (30%), below the regional proportion, 40%. The literacy rate for the heads of household was 68, higher than the regional proportion (59%). Compared to other district in the region, Bukombe has lower rate of utilized land area per household (3.2 ha) lower than the regional average which is 3.4. The total usable land per household is 3.6 ha, which indicate a scorching land pressure. Allocated area is also 90% utilized in the district and the District has moderate area planted per household which is 2.6 a little higher than the regional average which is 2.5. Production of maize is moderate compared to other districts in the region with a planted area of 64,833ha and the planted area per household is 1.25ha. Paddy production is also moderate when compared to other districts with a total planted area of 21,371hectares and the area planted per household is 1.19ha. Sorghum production is lowest in the district with a planted area of 227hectares and the district ranks last but one in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.38hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a moderate area planted area with Cotton (14,798ha), and ranks sixth in the region in terms of area and production and the average planted are per cotton growing household is 1.15 hectare lower than the regional average which is 1.31ha. About 74% of the total planted area was cleared and soil prepared by hand, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Bukombe has the higher planted area with improved seed in Shinyanga region which is 25% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) and it ranks second from bottom when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 100 Compared to other districts in the region, Bukombe district has moderate level of insecticide use, which is 35% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 4.6% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 1.23% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 641ha of irrigated land or 1% of total planted area. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the moderate number of households selling crops (59%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (93%) of households processing crops is found in Bukombe district and is mostly all done by neighboring machine and by trader. Although very small, access to credit in the district is mainly to male headed households, which is 86% and the main sources of credits is Family, Friend and Relative, Trade store. Although a very small number of households receive extension service in the region, Bukombe district had low proportion of households receiving the service (14%), second from bottom and lower than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 3% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is lowest compared to other districts; among enumerated rural agricultural households for Bukombe District no pigs were reported. The District had lower number of chicken (8%) in the region. Low number of households (5%) report Tsetse fly problems in Bukombe district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Bukombe recording 42% which is a little bit lower than the regional average (68%). The District had lower proportion of households (34%) de-worming livestock. The proportion of draft animals usage is lowest for the region recoding 17% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and terially markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Bukombe district has lower proportion of households with no toilet facilities (8%) as compared to the regional average which is 11%, and it has the highest percent of households owning bicycles and radio and lowest percent of households owning Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (3%) and Crop Residues. The district has moderate percent of households with grass roofs (44%) and lower percent of households with Mud Roofs (22%) and, moderate percent (34% ) of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most households access source of drinking water within a distance of half a kilometer to less than three kilometer. It has lower (2%) proportion of households having one meal per day compared to other districts. The district had lower DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 101 percent of households that did not eat meat or fish during the week prior to enumeration (24%); however about less than a quarter agricultural households always and often had problems with food satisfaction. 4.2.6 Shinyanga Rural Shinyanga Rural district has moderate number of households in the region, and the proportion of households involved in smallholder agriculture is 99%, higher than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Shinyanga Rural district is Annual Crop Farming, followed by Off farms income and Livestock keeping. Compared to other districts in the region, Shinyanga Rural has the moderate level of female headed households 14%, equal to the regional average, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 6.2 members per household, lower than the regional average which is also 6.4. Shinyanga Rural has a comparatively higher literacy rate (73.5%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 39%, below the regional proportion, 40%. The literacy rate for the heads of household was 59, same as the regional proportion. Compared to other district in the region, Shinyanga Rural has lower rate of utilized land area per household (2.5 ha) lower than the regional average which is 3.4. The total usable land per household is 2.8 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 2.4 a little lower than the regional average which is 2.5. Production of maize is moderate compared to other districts in the region with a planted area of 44,228ha and the planted area per household is 1.00ha. Paddy production is also moderate when compared to other districts with a total planted area of 20,937hectares and the area planted per household is 0.73ha. Sorghum production is lower with a planted area of 1,329hectares and the district ranks fifth in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.53hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Chick peas, Ground nuts and Chick Peas. The district has a lower cotton production with a total of 2,105hectares planted with cotton. About 86% of the total planted area was cleared and soil prepared by oxen ploughing, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Shinyanga Rural has the lower planted area with improved seed in Shinyanga region which is 11% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) . Most of the fertilizer under use is farm yard manure. The district has minimal or no area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 102 Compared to other districts in the region, Shinyanga Rural district has lower level of insecticide use, which is 10% of the total planted area in the district, lower than the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 3.5% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 2.71% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 3,152ha of irrigated land or 3.1% of total planted area. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the moderate number of households selling crops (43.8%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (94%) of households processing crops is found in Shinyanga Rural district and is mostly all done by neighboring machine and by trader. Although very small, access to credit in the district is mainly to female headed households, which is 75% and the main sources of credits are others or unspecified sources apart from family fried and relative, Commercial banks, Savings and credits, trade and religious organisations. Although a very small number of households receive extension service in the region, Shinyanga Rural district had a moderate proportion of households receiving the service (27%), a bit lower than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to very Good and Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 6% of all agricultural households reporting to have planted trees. The district has 12.2% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; Among enumerated households in rural agricultural households for Shinyanga Rural District no pigs were reported. The District had higher number of chicken (19%) in the region, second from top. No incidences of Tsetse fly problems were reported among the enumerated agricultural households.. The Incidence of Tick problem is almost commonly spread in all districts in the region with Shinyanga Rural recording 71% which is higher than the regional average (68%). The District had a moderate proportion of households (45%) de-worming livestock. The proportion of draft animals usage is lowest for the region recoding 17% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Shinyanga Rural district has lower proportion of households with no toilet facilities (9%) as compared to the regional average which is 11%, and it has the highest percent of households owning bicycles, radio and wheelbarrow. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (98%) and very few use charcoal (2%). The district has moderate percent of households with grass roofs (55%) and lower percent of households with Mud Roofs (28%) and, lower percent (17% ) of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most households access source of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 103 drinking water within a distance of half a kilometer to less than three kilometer. It has the highest (4%) proportion of households having one meal per day. The district had moderate number of households that did not eat meat or fish during the week prior to enumeration (44%); however about less than a quarter agricultural households always and often had problems with food satisfaction. 4.2.7 Shinyanga Urban Shinyanga Urban district has the smallest number of households in the region, and the proportion of households involved in smallholder agriculture is 92%, lower than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There is a small number of agricultural households with livestock only in the district (8%) and no pastoralists were recorded in the district. The most important livelihood activity for smallholder households in Shinyanga Urban district is Annual Crop Farming, followed by Livestock keeping and off farms income. Compared to other districts in the region, Shinyanga Urban has higher level of female headed households 19%, above the regional average which is 14%, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 5.4 members per household, lower than the regional average which is also 6.4. Shinyanga Urban has a comparatively lower literacy rate (52.2%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 45%, above regional proportion, 40%. The literacy rate for the heads of household was 56%, lower than the regional proportion which is 59%. Compared to other district in the region, Shinyanga Urban has lower rate of utilized land area per household (2.2 ha) lower than the regional average which is 3.4. The total usable land per household is 2.4 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 1.5 lower than the regional average which is 2.5. Production of maize is lower compared to other districts in the region with a planted area of 7,505ha and the planted area per household is 0.90ha. Paddy production is also lower when compared to other districts with a total planted area of 1,628hectares and the area planted per household is 0.48ha. Sorghum production is lower with a planted area of 917hectares and the district ranks fifth in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.72hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Cow peas, Chick peas, Ground nuts and Chick Peas. The district has the lowest cotton production in the region with a total of 385hectares planted with cotton. About 77% of the total planted area was cleared and soil prepared by hand, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Shinyanga Urban has the lower planted area with improved seed in Shinyanga region which is 14% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost). Most of the fertilizer under use is farm yard manure. The district has smaller area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 104 Compared to other districts in the region, Shinyanga Urban district has moderate level of insecticide use, which is 10% of the total planted area in the district, lower than the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 4.3% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 1.64% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 863ha of irrigated land or 5.5% of total planted area, higher number than that recorded on other districts. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the lowest number of households selling crops (7.6%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. The lowest proportion (42%) of households processing crops is found in Shinyanga Urban district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to female headed households, which is 100% and the main sources of credits is Trade store. Although a very small number of households receive extension service in the region, Shinyanga Urban district had a moderate proportion of households receiving the service (33%), higher than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated between Good and average by the majority of the households that received extension service. Tree farming was practiced in the district with 11% of all agricultural households reporting to have planted trees during the agricultural year this number is higher that that recorded for other districts. The district has 2.3% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is lowest compared to other districts. Very few pigs were reported in rural agricultural households (1,931) in Shinyanga Urban District with an average of 10 pigs per pig rearing household. The District had lower number of chicken (13%) in the region. Low number of households (3%) report Tsetse fly problems in Shinyanga Urban district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Shinyanga Urban recording 46% which is a lower than the regional average (68%). The District had lower proportion of households (33%) de-worming livestock. The proportion of draft animals usage is moderate for the region recoding 68% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to tarmac road. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, Primary markets, secondary schools, Hospitals, District and regional capitals, Secondary Market and tertiary markets. Shinyanga Urban district has lower proportion of households with no toilet facilities (5%) as compared to the regional average which is 12%, and it has higher number of households owning bicycles, radio, and Iron. The main source of energy for lighting in the district is Wick Lamp and hurricane lamp, very few households reported their main source of lighting being electricity which was 2% or 20 out of 1000 households. Practically a large number of households use firewood for cooking (88%) and very few use charcoal (10%) ,Crop Residues (1%) and bottled gas (1%). The district has a small number of households with grass roofs (15%) and higher percent of households with Mud Roofs (61%) and a small DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 105 percent (24%) of households having iron sheets roofing. The most common source of drinking water is from protected well and most households access source of drinking water within a distance of half a kilometer to less than two kilometer. It has lower (1%) proportion of households having one meal per day compared to other districts. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration (44%); however about one quarter of agricultural households always and often had problems with food satisfaction in the district. 4.2.8 Kishapu Kishapu district has smaller number of agricultural households compared to other districts in the in the region. The proportion of households involved in smallholder agriculture is 97%, above the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There is a small number of agricultural households with livestock only in the district (1%) and no pastoralists were recorded in the district. The most important livelihood activity for smallholder households in Kishapu district is Annual Crop Farming, followed by Livestock keeping. Compared to other districts in the region, Kishapu has moderate level of female headed households 15%, above the regional average which is 14%, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 6.4 members per household, same as the regional average which is also 6.4. Kishapu has a comparatively lower literacy rate (65%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 41%, above the regional proportion which is 40%. The literacy rate for the heads of household was 60%, a bit above the regional proportion which is 59%. Compared to other district in the region, Kishapu has the highest rate of utilized land per household (5.6 ha) above the regional average which is 3.4. The total usable land per household is 6.3 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 3.4 higher than the regional average which is 2.5 and is the highest average planted area for the region. Production of maize is moderate compared to other districts in the region with a planted area of 35,494ha and the planted area per household is 1.17ha. Paddy production is lower when compared to other districts with a total planted area of 4,459hectares and the area planted per household is 0.63ha. Sorghum production is higher with a planted area of 21,030hectares and the district ranks second from top in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 1.49hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a moderate area planted area with Cotton 32,748hectares, and ranks fourth in the region in terms of area and production and the average planted are per cotton growing household is 1.70 hectare higher than the regional average which is 1.31ha. About 92% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil preparation (3%) which is considerably a bit lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Kishapu has the higher planted area with improved seed in Shinyanga region which is 48% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 106 manure, compost) when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal area planted with inorganic fertilizers. Compared to other districts in the region, Kishapu district has moderate level of insecticide use, which is 33% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 2.8% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 4.15% of the total planted area with herbicides in the district. Irrigation was also practiced in the district though not widely applied on 2,597ha of irrigated land or 2.1% of total planted area. The most common method of crop storage is in locally made traditional cribs and in sacks or open drums; The district has the moderate number of households selling crops (50.4%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (97%) of households processing crops is found in Kishapu district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 33% and the main sources of credits is Family, Friend and Relative. Although a very small number of households receive extension service in the region, Kishapu district had higher proportion of households receiving the service (51%), ranking first from top and above the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good and average by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 11.3% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is higher compared to other districts; Very few pigs were reported in rural agricultural households (82) in Kishapu District with an average of 1 pigs per pig rearing household. The District had moderate number of chicken (6%) in the region. Low number of households (7%) report Tsetse fly problems in Kishapu district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Kishapu recording 61% which is a little bit lower than the regional average (68%). The District had the lowest proportion of households (26%) de-worming livestock. The proportion of draft animals usage is higher in the district recoding 89% of households. No rural agricultural households reported to practice fish farming. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Primary Market, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, and feeder roads. Kishapu district has the lower proportion of households with no toilet facilities (8%), and it is one of the districts with highest percent of households owning bicycles and radio. The main source of energy for lighting in the district is Wick Lamp and no households reported their main source of lighting being electricity. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (3%) and Crop Residues (1%). The district has lower percent of households with grass roofs (5%) and higher percent of households with Mud Roofs (79%) and, low percent (14% ) of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 107 households having iron sheets roofing. The most common source of drinking water is from surface water (Lake/Dam/River/Stream) and most households access source of drinking water within a distance of half a kilometer to less than three kilometer. It has lower (1%) proportion of households having one meal per day. The district had Moderate percent of households that did not eat meat or fish during the week prior to enumeration (35%); however about one third of households always and often had problems with food satisfaction. APPENDIX II 108 4. APPENDICES Appendix I Tabulation List...............................................................................................................................109 Appendix II Tables .............................................................................................................................................128 Appendix III Questionnaires...................................................................................................................................254 APPENDIX II 109 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD…………………………………...………………………………...128 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 129 2.2 Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year.......129 NUMBER OF AGRICULTURE HOUSEHOLDS .................................................................................................130 3.0 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year......................................................................................131 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District..................................................................................................................................131 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES............................................................................132 3.1a First Most Importance....................................................................................................................................133 3.1b Second Most Importance................................................................................................................................133 3.1c Third Most Importance ..................................................................................................................................133 3.1d Fourth Most Importance.................................................................................................................................133 HOUSEHOLDS DEMOGRAPHS............................................................................................................................134 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) .............................................................................................................................135 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) .......................................................................................................................135 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year.......136 3.5A Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year ......................................136 3.5B Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year.................................................136 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ............................................................................................................................136 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year.137 cont… Number of Agricultural Household Members By Main Activity and District.................................137 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ........................................................................................................138 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................ 138 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................139 APPENDIX II 110 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.................................................................................................140 3.11 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year..........................................................................................................................141 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year.............................................................................................................................141 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year..........................................................................................................................141 3.14 Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ............................................142 3.15A Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year........................................................................................142 3.15B Percent of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year .......................................................................................142 3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year.............................................................................................................................143 3.17 Time Series of Male and Female Headed Households: Shinyanga..........................................................................144 3.18 Literacy Rate of Heads of Households by Sex and District .....................................................................................144 LAND ACCESS/OWNERSHIP...........................................................................................................................................146 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year ..................................................................................................................................147 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year .....................147 LAND USE..............................................................................................................................................................................148 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ........149 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year.......................................149 5.3 Number of Households by type of household and District during 2002/03 Agricultural Year .............................150 5.4 Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year ......................................................................................150 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year ...............................................................150 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION LONG & SHORT SEASONS...................................152 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District......................................153 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District..................................................153 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Kahama District.............................................................................................................................154 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................................................155 APPENDIX II 111 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year..................................................................................................................155 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................155 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................155 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................156 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................157 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................157 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................157 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................158 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................158 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................158 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................158 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................159 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................159 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................159 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................160 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................160 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 APPENDIX II 112 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................162 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................163 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................163 7.1 & 7.2e Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Shinyanya Region ....................................................................................164 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Long & Short Season, Kagera..........................................................................................................164 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga.......................................................................164 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga Region ...............................................................164 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. ........................................................................................................165 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Kahama. ........................................................................................165 7.1 & 7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Shinyanga Region......................................................................................166 7.1 &7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Shinyanga Region..............................................166 ANNUAL CROP & VEGETABLES PRODUCTION LONG SEASON........................................................................168 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Kahama District .....................................................................169 7.2b ````Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season..............................................................................................................................................169 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama District .....................................................................169 7.2d Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON ..............................................................................................................................170 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region.....................................................................170 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region.....................................................................170 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON, Kahama Region...................................................................171 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................172 APPENDIX II 113 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................172 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................172 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................173 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................173 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................174 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................174 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................174 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................176 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................176 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................176 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................177 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................177 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................177 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................178 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................178 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................178 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................179 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................179 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................179 APPENDIX II 114 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................181 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................181 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................181 PERMANENT CROPS..................................................................................................................................................... 182 7.4 Total Area Planted with Coconut by District - Shinyanga Region......................................................................... 183 7.5 Total Area Planted with Oranges by District - Shinyanga Region ........................................................................ 183 7.6 Total Area Planted with Banana by District - Shinyanga Region.......................................................................... 183 AGROPROCESSING ....................................................................................................................................................... 184 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year......................................................................................................................... 185 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year District ........................................................................................................................................ 185 8.1.1a Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Kahama District ................................................................................................................ 186 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Use of Product and Crop, Kahama District................................................ 187 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Kahama District ...................................................... 188 8.1.1d Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Kahama District ......................................................................................................................... 188 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Kahama District............................................................................................... 189 8.1.1f Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Kahama District ......................................................................................................................... 189 8.1.1g Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Kahama District .............................................................................................. 189 MARKETING.................................................................................................................................................................... 190 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Kahama District................................................................................................................. 191 10.2 Number of Households who Reported Marketing Problems by District during 2002/03 Agricultural Year ................... 191 10.3 Proportion of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year.............................................................................................................................. 191 APPENDIX II 115 IRRIGATION/EROSION CONTROL........................................................................................................................... 192 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District..................................................................................................193 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year ...................................................................................................................193 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year .....................................................193 11.4 Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year ...............................................................................194 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year............................................194 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District .......................................................................................195 11.7 Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year.................................................................................195 ACCESS TO FARM INPUTS AND IMPLEMENTS ................................................................................................... 196 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District, 2002/03 Agricultural Year...................................................................................................................... 197 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year .................................................................................................................................... 197 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................... 198 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year .................................................................................................................................... 198 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year........................ 199 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year................ 199 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................................................................................... 200 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year, ................................................................................................................................... 200 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .................................................................................................................................... 201 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................... 201 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year........... 202 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year......... 203 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................................................................. 203 APPENDIX II 116 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Year ......................................................................................................204 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year..........................................................................................................205 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................205 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................................205 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year ............................................................................................206 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................206 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year..........................................................................................................207 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year...............................................................................................................207 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year ...............................................................................................208 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year.........................................................................................................208 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure By district 2002/03 Agricultural Year ...........................................................................................................209 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District 2002/03 Agricultural Year...........................................................................................................210 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District 2002/03 Agricultural Year...........................................................................................................210 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District 2002/03 Agricultural Year ............................................................................................................................211 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................212 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year.........................................................................................................212 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ............................................................................................................................213 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year..........................................................................................................213 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year......................................................................................................... 213 APPENDIX II 117 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year..........................................................................................................214 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................214 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year.............................................................................................................214 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year.............................................................................................................215 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year............................................................................................................215 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year.............................................................................................................216 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year.............................................................................................................216 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year..............216 12.2.1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03.......................................217 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year.............................................................................................................218 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District....218 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District .............................................................................................................................218 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District ...........219 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District....219 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District....................................................................................................................................219 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District .....220 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District ............................................................................................................................................220 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District....................................................................................................................................220 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District .............................................................................................................................221 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District.................................................................................................................221 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District ......................221 APPENDIX II 118 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District ....................................................................................................................................222 12.2.15 Number of Agricultural Households Owning OXEN by Source of Finance and District ............................222 12.2.16 Number of Agricultural Households Owning OX Plough by Source of Finance and District.................222 12.2.17 Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District.....223 12.2.18 Number of Agricultural Households Owning OX CART by Source of Finance and District ......................223 12.2.19 Number of Agricultural Households Owning TRACTOR by Source of Finance and District.....................223 12.2.20 Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District.....208 12.2.21 Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District ...223 AGRICULTURE CREDIT........................................................................................................................................224 13.1a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year............................................................................................................225 13.1b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year............................................................................................................225 13.2a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year........................................................................................209 13.2c Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year .......................................................................................................... 209 TREE FARMING AND AGROFORESTRY..........................................................................................................212 14.1 Number of Households Having Planted Trees By District............................................................................213 contNumber of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region..............................................................................................213 14.1 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Kagera Region……….....214 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Shinyanga Region .......................................214 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region ................................................................................................................214 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District........215 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Shinyanga Region..................................................................215 14 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Shinyanga Region ..........................................................................................................................................215 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region ................................................................................................................215 CROP EXTENSION...................................................................................................................................................216 15.1 Number of Agriculture Households Receiving Extension Messages by District APPENDIX II 119 During the 2002/03 Agriculture Year, Shinyanga Region............................................................................217 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region..........................................................................217 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region...........................................................................217 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................218 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................218 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................218 15.7 Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................219 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.10 Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................220 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................220 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region........................................................220 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................221 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................221 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................221 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................222 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................222 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region..............222 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region..............223 APPENDIX II 120 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region..............224 EXTENSION...............................................................................................................................................................226 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 AgricultureYear, Shinyanga Region.............................................................................224 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region .......................................................................................224 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................224 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................224 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region.......................................................218 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region....................................................... 218 15.7 Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................219 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.10 Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................220 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ..................................... 220 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region..............................................................220 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region................................................................. 21 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region................................................................. 21 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region........................................................221 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................222 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................222 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region..............222 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message APPENDIX II 121 and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region...........................................223 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region ...........................223 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region ...........................244 ANIMAL CONTRIBUTION TO CROP PRODUCTION.....................................................................................226 17.1 Number of Households Using Draft Animal to Cultivate Land By District.................................................227 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.................................................................................................................227 17.3 Number of Crop Growing Households Using Organic Fertilizer By Region During 2002/03 Agriculture Year ...............................................................................................227 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year ......228 CATTLE PRODUCTION..........................................................................................................................................229 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Shinyanga Region..............................................................................................................231 18.2 Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 .............................................................................................231 18.3 Total Number of Cattle by Category and Type of Cattle; on 1st October 2003...........................................231 18.4 Total Number of Cattle by Type and District As of 1st October 2003.........................................................232 18.5 Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003.................232 18.6 Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 ..........................232 18.7 Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003...........................233 18.8 Total Number of Cattle by Category and District as on 1st October 2003..................................................233 GOATS PRODUCTION............................................................................................................................................234 19.1 Total Number of Goats by goat type and District as on 1st October 2003...................................................235 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003................235 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003..............................................236 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003......................................236 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003.........................236 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 ............................237 19.7 Total Number of Goats by Category and District on 1st October 2003 .......................................................237 SHEEP PRODUCTION.............................................................................................................................................238 APPENDIX II 122 20.1 Total Number of Sheep by Breed Type on 1st October 2003.......................................................................239 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003................................239 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003........................................................239 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 ....................................239 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003.........................................240 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003................................240 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003................................244 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003...................................................240 PIGS PRODUCTION.................................................................................................................................................242 21.1 Number of Households Raising or Managing Pigs by District on 1st October 2003...................................243 21.2 Number of Households and Pigs by Herd Size on 1st October 2003 ...........................................................243 21.3 Number of Households and Pigs by District on 1st October 2003 ...............................................................243 LIVESTOCK PESTS AND PARASITE CONTROL ............................................................................................244 22.1 Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year .............................................................................................................................245 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year ..............................................................................................245 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year. ..................................245 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year .............................................................245 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year.................246 22.6 Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. .............................................................................................246 OTHER LIVESTOCK ...............................................................................................................................................248 23a Total Number of Other Livestock by Type as of 1st October 2003 .............................................................249 23b Number of Chicken by Category of chicken and District as of 1st October 2003 .......................................249 23d Total Number of households and chickens raised by flock size as of 1st October 2005 .............................249 23e Head Number of Other Livestock by Type of Livestock and District..........................................................249 23f LIVESTOCK/POULTRY POPULATION TREND: SHINYANGA REGION ..........................................249 LIVESTOCK PRODUCTS: .....................................................................................................................................249 25 Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year..............................................................................................249 APPENDIX II 123 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: ................................................................................250 27.1 Number of households by Distance to Nearest Cattle Dip and District.......................................................249 27.2 Number of households by Distance to Nearest Spray Raced and District...................................................249 27.3 Number of households by Distance to Nearest Hand Powered Sprayer and District..................................249 27.4 Number of households by Distance to Nearest Cattle Crush and District...................................................249 27.5 Number of households by Distance to Nearest Primary Market and District .............................................249 27.6 Number of households by Distance to Nearest Secondary Market and District .........................................249 27.7 Number of households by Distance to Nearest Abattoir and District..........................................................249 27.8 Number of households by Distance to Nearest Slaughter Slab and District................................................249 27.9 Number of households by Distance to Nearest Hide/ Skin Shade and District...........................................249 27.10 Number of households by Distance to Nearest Input Supply and District ..................................................249 27.11 Number of households by Distance to Nearest Veterinary Clinic and District...........................................249 27.12 Number of households by Distance to Nearest Village Holding Ground and District................................249 27.13 Number of households by Distance to Nearest Village Watering Point/ Dam and District........................249 27.14 Number of households by Distance to Nearest Drencher and District ........................................................249 FISH FARMING.........................................................................................................................................................250 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year..251 LIVESTOCK EXTENSION......................................................................................................................................252 29.1a Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year .............................................................................................................................253 29.1b Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District during the 2002/03 Agricultural Year........................................................................................253 29.1c Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year..............................................................................................................254 29.1d Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year......................................................................................254 29.1e Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year ......................................................................................254 29.1f Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year ......................................................................................254 29.1g Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year .....................................................................255 29.1h Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year.............................................................. 255 29.1i Number of Agricultural Households Receiving Extension Advice on Group Formation APPENDIX II 124 and Strengtherning By Source and District, 2002/03 Agricultural Year......................................................256 29.1j Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year...........................................................................................256 29.1k Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year......................................................................................257 29.1l Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .............................................................................................................................257 29.1m Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year ...........................................................................................................................258 29.13 Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year...............................................................................................................258 GOVERNMENT REGULATORY PROBLEMS: ..........................................................................................................258 30.1 Number of Agricultural Households by Whether Face Problems with Government Regulation During 2003/04 by District, 2002/03 Agricultural Year...................................................................................258 ACCESS TO INFRASRUCTURE AND OTHER SERVICES.............................................................................260 30.1 Number of Agricultural Households by Distance to Services by District, 2002/03 Agricultural Year ......261 30.2 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year..............................................................................................................................262 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural year ..............................................................................................................................262 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year .............................................................................................................................262 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year .............................................................................................................................263 33.6 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year .............................................................................................................................263 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year263 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year ............................................................................................................................264 33.9 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year .............................................................................................................................264 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year .............................................................................................................................264 33.11 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year ............................................................................................................................265 33.12 Number of Agricultural Households by Distance to Tertiary Market and District,....................................265 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................................................................265 33.14 Number of Agricultural Households by Distance to Extension Center.......................................................266 APPENDIX II 125 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year .............................................................................................................................266 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year .............................................................................................................................266 33.17 Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year .............................................................................................................................267 33.18 Number of Agricultural Households by Distance to Livestock Development Center ................................267 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year...............................................................................................................267 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year...............................................................................................................267 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year...............................................................................................................267 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ........................................................................................................267 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year...............................................................................................................267 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year ............................................................................................267 33.19g Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year............................................................................................................. 267 HOUSEHOLD FACILITIES ....................................................................................................................................268 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year ..............................................................................................................................269 34.2A Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District, 2002/03 Agricultural Year..........................................................................................269 34.2B Percent of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year.........................................................................................................269 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ....................................................................................................269 34.4a Number of Agriculture Households by Main Source of Energy Used for Lighting and during 2002/03 Agricultural Year..................................................................................................................270 34.4b Proportion of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year ...................................................................................................270 34.5a Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year.................................................................................................................270 34.5b Proportion of Agriculture Households by Main Source of Energy Used for Cooking and District during 2002/03 Agricultural Year ...................................................................................................270 34.6: Number of Agricultural Households by Main Source of Drinking Water by (wet and dry) and District during 2002/03 Agricultural Year.......................................................................271 APPENDIX II 126 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.......................................................................272 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year .......................................272 34.9: Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year ........................................273 34.10: Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year........................273 34.11: Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year........................273 34.12A Number of Households by Number of Meals the Household Normally Took per Day by District Normally Took per Day by District..............................................................................................................274 34.12B Number of Households by Number of Meals the Household Normally Took per Day by District............274 34.13A Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ...........................................................................................................................274 34.13B Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District .....................................................................................................................274 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District .....................................................................................................................275 34.15A: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.........................................................................................275 34.15B Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.........................................................................................275 34.16: Number of Households by Main Source of Cash Income and District during 2002/03 Agricultural Year .............................................................................................................................275 34.17: Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year .............................................................................................................................275 APPENDIX II: CROP TABLES APPENDIX II 127 Type of Agriculture Household.............................................................................................................................................. 128 Number of Agriculture Households ........................................................................................................................................ 130 Rank of Importance of Livelihood Activities ......................................................................................................................... 132 Households Demography......................................................................................................................................................... 134 Land Access/Ownership .......................................................................................................................................................... 146 Land Use……………….......................................................................................................................................................... 148 Total Annual Crop and Vegetable Production Long and short Seasons ............................................................................... 152 Annual Crop and Vegetable Production Long Rainy Seasons ............................................................................................... 168 Permanent Crop Production..................................................................................................................................................... 182 Agro-processing ............................................................................................................................................................. 184 Marketing ............................................................................................................................................................. 190 Irrigation/Erosion Control ....................................................................................................................................................... 192 Access to Farm Inputs ............................................................................................................................................................ 196 Agriculture Credit ............................................................................................................................................................. 208 Tree Farming and Agro-forestry.............................................................................................................................................. 212 Crop Extension ............................................................................................................................................................. 216 Animal Contribution to Crop Production................................................................................................................................ 226 Cattle Production ............................................................................................................................................................. 230 Goat Production ............................................................................................................................................................. 234 Sheep Production ............................................................................................................................................................. 238 Pig Production ............................................................................................................................................................. 242 Livestock Pests and Parasite Control ...................................................................................................................................... 244 Other Livestock ............................................................................................................................................................. 248 Fishing Farming ............................................................................................................................................................. 250 Livestock Extension ............................................................................................................................................................. 252 Access to Infrastructure and other services............................................................................................................................. 260 Household Facilities ............................................................................................................................................................. 268 Appendix II 128 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 129 Rural households involved in Agriculture % of Total rural house holds Rural households NOT involved in Agriculture % of Total Rural house - holds Total Rural Househol d % of Total house - holds Urban Households % of Total house - holds Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Kahama 81,217 94 4,979 6 86,196 85 14,657 15 100,853 Bariadi 77,572 96 2,955 4 80,527 94 5,032 6 85,559 Bukombe 53,240 99 528 1 53,768 88 7,503 12 61,271 Shinyanga Rural 45,263 100 126 0 45,389 100 128 0 45,517 Maswa 43,252 99 641 1 43,893 90 5,028 10 48,921 Kishapu 35,624 97 1,246 3 36,870 93 2,574 7 39,444 Meatu 31,492 93 2,261 7 33,753 96 1,485 4 35,238 Shinyanga Urban 10,198 92 939 8 11,137 39 17,080 61 28,217 Total 377,857 97 13,676 3 391,533 88 53,487 12 445,020 Number of households % Number of households % Number of househol ds % Bariadi 39,487 51 179 0 37,905 49 77,572 77,393 38,084 Maswa 22,774 53 317 1 20,160 47 43,252 42,935 20,478 Shinyanga Rural 21,182 47 102 0 23,979 53 45,263 45,161 24,081 Kahama 49,208 61 143 0 31,866 39 81,217 81,074 32,009 Bukombe 34,546 65 239 0 18,456 35 53,240 53,001 18,695 Meatu 13,820 44 47 0 17,625 56 31,492 31,445 17,672 Shinyanga Urban 4,190 41 783 8 5,226 51 10,198 9,415 6,009 Kishapu 16,108 500 1 19,015 53 35,624 35,124 19,515 Total 201,316 53 2,310 1 174,232 46 377,857 375,547 176,542 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households Crops & Livestock Total Number of Agriculture Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock District Crops Only 2. 2 TYPE OF AGRICULTURE HH: Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year District Livestock Only Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 130 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 131 Number % Average Household Size Number % Average Household Size Number % Bariadi 66,387 86 7 11,185 14 5 77,572 100 7 Maswa 34,626 80 7 8,625 20 5 43,252 100 6 Shinyanga Rural 38,841 86 6 6,422 14 5 45,263 100 6 Kahama 70,196 86 6 11,021 14 4 81,217 100 6 Bukombe 48,282 91 7 4,958 9 5 53,240 100 6 Meatu 27,272 87 8 4,220 13 5 31,492 100 7 Shinyanga Urban 8,214 81 6 1,984 19 5 10,198 100 5 Kishapu 30,103 85 7 5,520 15 5 35,624 100 6 Total 323,921 86 7 53,936 14 5 377,857 100 6 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 1 6 3 2 4 7 5 Maswa 1 4 2 3 6 7 5 Shinyanga Rural 1 4 3 2 5 7 6 Kahama 1 5 2 3 6 7 4 Bukombe 1 4 2 3 5 7 6 Meatu 1 6 2 3 5 7 4 Shinyanga Urban 1 4 2 3 5 7 6 Kishapu 1 6 2 4 5 7 3 Total 1 5 2 3 6 7 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity 3.0: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 132 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 133 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 65,962 0 370 10,875 0 0 696 Maswa 41,348 0 325 1,161 0 0 0 Shinyanga Rural 44,576 0 99 584 0 0 102 Kahama 77,801 135 972 1,982 428 282 141 Bukombe 52,762 0 0 358 0 0 119 Meatu 28,953 83 802 1,521 0 47 83 Shinyanga Urban 9,161 54 103 698 47 0 0 Kishapu 31,690 0 772 2,801 203 0 402 Total 352,253 272 3,444 19,980 678 329 1,544 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 9,512 1,549 30,753 21,952 2,144 0 1,753 Maswa 1,492 2,875 17,036 9,607 938 108 2,342 Shinyanga Rural 485 1,118 21,443 18,001 1,303 102 396 Kahama 2,843 4,993 25,587 21,139 1,522 133 7,248 Bukombe 478 2,507 18,911 10,340 2,142 119 1,075 Meatu 2,015 537 15,369 6,153 461 0 3,609 Shinyanga Urban 626 742 4,226 2,864 559 0 218 Kishapu 2,389 405 15,954 5,586 1,696 81 5,361 Total 19,840 14,726 149,279 95,643 10,764 544 22,003 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Shinyanga Rural 99 2,016 2,727 12,253 1,315 0 1,105 Kahama 0 4,691 5,623 9,663 1,910 0 4,670 Bukombe 0 1,189 4,052 4,179 1,550 0 358 Meatu 193 869 2,392 4,437 1,043 83 4,250 Shinyanga Urban 116 1,094 1,085 1,611 563 0 776 Kishapu 639 406 1,662 4,428 724 0 10,617 Total 2,097 16,836 26,635 55,960 14,759 192 28,021 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 170 3,921 714 1,055 1,439 0 1,952 Maswa 0 1,273 527 623 751 0 853 Shinyanga Rural 0 1,501 204 811 610 98 0 Kahama 0 1,729 1,089 556 907 0 2,348 Bukombe 0 478 597 239 239 0 0 Meatu 81 650 211 657 769 333 332 Shinyanga Urban 0 561 152 518 60 0 217 Kishapu 79 638 1,295 1,368 325 0 3,774 Total 330 10,751 4,790 5,826 5,099 431 9,477 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 134 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 135 Number % Number % Number % Less than 4 195,350 51 190,510 49 385,861 100 05 - 09 206,278 52 188,729 48 395,007 100 10 - 14 180,439 52 165,889 48 346,329 100 15 - 19 132,500 53 117,885 47 250,386 100 20 - 24 95,986 48 102,328 52 198,314 100 25 - 29 77,454 44 98,379 56 175,833 100 30 - 34 76,149 49 80,446 51 156,595 100 35 - 39 62,237 52 57,548 48 119,785 100 40 - 44 51,436 55 42,797 45 94,234 100 45 - 49 34,431 50 34,401 50 68,832 100 50 - 54 32,785 52 30,283 48 63,069 100 55 - 59 23,534 58 17,330 42 40,863 100 60 - 64 22,459 54 19,434 46 41,893 100 65 - 69 15,236 53 13,377 47 28,613 100 70 - 74 14,598 56 11,592 44 26,190 100 75 - 79 9,473 66 4,889 34 14,362 100 80 - 84 5,046 46 5,902 54 10,948 100 Above 85 4,790 52 4,503 48 9,293 100 Total 1,240,182 49 1,186,224 51 2,426,406 100 Number % Number % Number % Less than 4 82,018 13 88,990 13 171,007 13 05 - 09 104,818 17 102,672 16 207,490 16 10 - 14 101,601 16 92,510 14 194,111 15 15 - 19 68,064 11 61,926 9 129,989 10 20 - 24 40,272 6 61,291 9 101,563 8 25 - 29 43,942 7 51,603 8 95,544 7 30 - 34 35,049 6 38,261 6 73,310 6 35 - 39 28,872 5 37,812 6 66,684 5 40 - 44 25,932 4 30,220 5 56,152 4 45 - 49 23,468 4 23,258 4 46,726 4 50 - 54 19,919 3 19,937 3 39,856 3 55 - 59 13,381 2 10,934 2 24,315 2 60 - 64 13,033 2 12,749 2 25,782 2 65 - 69 11,024 2 9,540 1 20,565 2 70 - 74 10,535 2 10,146 2 20,681 2 75 - 79 4,869 1 3,763 1 8,632 1 80 - 84 4,058 1 3,400 1 7,458 1 Above 85 3,113 0 3,052 0 6,165 0 Total 633,967 100 662,064 100 1,296,031 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 136 Number % Number % Number % Bariadi 196,570 48 209,752 52 406,322 100 Maswa 112,681 49 115,135 51 227,816 100 Shinyanga Rural 113,667 49 116,950 51 230,617 100 Kahama 19,546 48 21,375 52 40,922 100 Bukombe 15,310 52 14,143 48 29,453 100 Meatu 123,622 48 132,669 52 256,291 100 Shinyanga Urban 52,570 50 52,040 50 104,610 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Number % % Bariadi 258,554 73.2 7,315 2.1 0 0.0 87,278 24.7 100 Maswa 140,665 68.9 5,004 2.5 0 0.0 58,514 28.7 100 Shinyanga Rural 143,330 71.2 4,205 2.1 283 0.1 53,363 26.5 100 Kahama 25,756 69.8 1,922 5.2 131 0.4 9,073 24.6 100 Bukombe 19,921 74.4 519 1.9 39 0.1 6,280 23.5 100 Meatu 128,671 59.7 6,330 2.9 750 0.3 79,943 37.1 100 Shinyanga Urban 44,615 51.2 668 0.8 243 0.3 41,651 47.8 100 Total 761,512 68 25,964 2 1,446 0.1 336,102 30 100 Number % Number % Number % Bariadi 87,278 24.7 265,869 75.3 353,147 100.0 Maswa 58,514 28.7 145,669 71.3 204,183 100.0 Shinyanga Rural 53,363 26.5 147,819 73.5 201,182 100.0 Kahama 9,073 24.6 27,809 75.4 36,882 100.0 Bukombe 6,280 23.5 20,479 76.5 26,758 100.0 Meatu 79,943 37.1 135,751 62.9 215,693 100.0 Shinyanga Urban 41,651 47.8 45,527 52.2 87,178 100.0 Total 336,102 29.9 788,922 70.1 1,125,024 100.0 Number % Number % Number % Number % Bariadi 132,142 37.4 162,461 46.0 58,544 16.6 353,147 100 Maswa 69,632 34.1 87,548 42.9 47,003 23.0 204,183 100 Shinyanga Rural 65,362 32.5 90,049 44.8 45,771 22.8 201,182 100 Kahama 11,636 31.5 17,439 47.3 7,807 21.2 36,882 100 Bukombe 9,276 34.7 13,161 49.2 4,322 16.2 26,758 100 Meatu 63,567 29.5 83,470 38.7 68,656 31.8 215,693 100 Shinyanga Urban 25,390 29.1 27,199 31.2 34,588 39.7 87,178 100 Total 377,006 33.5 481,327 42.8 266,691 23.7 1,125,024 100 3.5A HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total Cannot Read and Write Can Read and Write Total District 3.5B HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to STotal Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 137 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % % % Bariadi 152,752 43 1,866 1 144 0 143 0 1 8 Maswa 76,219 37 3,934 2 103 0 107 0 2 8 Shinyanga Rural 77,409 38 1,565 1 1,299 1 1,529 1 1 5 Kahama 9,867 27 898 2 23 0 987 3 2 4 Bukombe 8,770 33 45 0 0 0 942 4 1 5 Meatu 92,233 43 2,552 1 107 0 630 0 1 5 Shinyanga Urban 33,682 39 2,921 3 1,164 1 48 0 0 2 Total 450,932 40 13,782 1 2,839 0 4,387 0 1 6 cont… HOUSEHOLD DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Number % Bariadi 16,606 5 1,439 0 576 0 0 0 570 0 Maswa 7,418 4 919 0 200 0 103 0 1,556 1 Shinyanga Rural 18,315 9 1,566 1 708 0 736 0 2,515 1 Kahama 5,170 14 504 1 985 3 103 0 1,250 3 Bukombe 3,665 14 247 1 148 1 41 0 638 2 Meatu 17,355 8 2,481 1 615 0 216 0 837 0 Shinyanga Urban 14,306 16 98 0 0 0 192 0 582 1 Total 82,834 7 7,254 1 3,231 0 1,391 0 7,948 1 cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Bariadi 116,122 33 29,186 8 280 0 353,147 100 Maswa 63,908 31 23,480 11 809 0 204,183 100 Shinyanga Rural 63,082 31 16,832 8 1,957 1 201,182 100 Kahama 11,348 31 2,635 7 485 1 36,882 100 Bukombe 8,838 33 1,269 5 261 1 26,758 100 Meatu 55,470 26 21,768 10 7,226 3 215,693 100 Shinyanga Urban 24,417 28 7,202 8 716 1 87,178 100 Total 343,184 31 102,373 9 11,735 1 1,125,024 100 Livestock Keeping / Herding Livestock Pastoralist Fishing Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Housemaker / Housewife District Crop/Seaweed Farming Other Total Not Working & Available Student Not Working & Unavailable Main Activity District District Unable to Work / Too Old / Retired / Sick / Disabled Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 138 Number % Number % Number % Number % % Bariadi 153,483 43 11,754 3 143,275 41 44,635 13 100 Maswa 66,982 33 26,928 13 68,254 33 42,019 21 100 Shinyanga Rural 74,537 37 30,593 15 63,190 31 32,863 16 100 Kahama 8,995 24 5,515 15 9,496 26 12,877 35 100 Bukombe 8,093 30 1,458 5 12,725 48 4,483 17 100 Meatu 85,034 39 24,270 11 67,099 31 39,290 18 100 Shinyanga Urban 36,026 41 12,288 14 24,623 28 14,240 16 100 Total 433,150 39 112,805 10 388,661 35 190,408 17 100 Number % Number % Number % Number % % % Bariadi 146 0 288 0 2,314 1 2,450 2 10 2 Maswa - - 1,137 1 2,417 3 3,800 4 14 4 Shinyanga Rural - - 492 1 1,904 2 3,308 4 16 5 Kahama 111 1 167 1 448 3 681 4 12 3 Bukombe - - 23 0 301 2 518 4 14 4 Meatu 540 1 108 0 2,558 3 5,094 6 13 4 Shinyanga Urban 97 0 - - 731 3 925 3 13 1 Total 893 0 2,215 0 10,672 2 16,776 3 13 3 District District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year Education Level 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Under Standard One Standard One Standard Two Standard Three Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 139 Number % Number % Number % Number % Number % Bariadi 128,131 79 1,166 1 145 0 - - 146 0 Maswa 55,775 64 1,731 2 376 0 300 0 - - Shinyanga Rural 55,523 62 1,874 2 338 0 55 0 167 0 Kahama 10,589 61 360 2 30 0 23 0 91 1 Bukombe 8,465 64 250 2 35 0 19 0 67 1 Meatu 53,352 64 1,247 1 - - - - 217 0 Shinyanga Urban 20,391 75 98 0 - - - - - - Total 332,227 69 6,726 1 925 0 397 0 688 0 Number % Number % Number % Number % Number % Bariadi 582 0 144 0 2,588 2 - - 708 0 Maswa 596 1 191 0 2,305 3 - - 107 0 Shinyanga Rural 1,048 1 124 0 1,379 2 - - 84 0 Kahama 73 0 81 0 775 4 10 0 212 1 Bukombe 76 1 22 0 230 2 24 0 22 0 Meatu 520 1 217 0 944 1 - - 212 0 Shinyanga Urban 47 0 - - 433 2 - - 49 0 Total 2,942 1 779 0 8,654 2 34 0 1,393 0 Number % Number % Number % Bariadi - - 1,010 1 162,461 100 Maswa - - 725 1 87,548 100 Shinyanga Rural - - 1,532 2 90,049 100 Kahama 45 0 579 3 17,439 100 Bukombe - - 379 3 13,161 100 Meatu - - 1,253 2 83,470 100 Shinyanga Urban 47 0 386 1 27,199 100 Total 92 0 5,865 1 481,327 100 Training After Secondary Standard Seven Standard Eight ng After Primary Edu Pre Form One Form One Form Six Form Two Form Three Form Four cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District District District g Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year University & Other Tertiary Education Adult Education Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 140 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Bariadi 468,284 66,387 7 54,815 11,185 5 523,099 77,572 7 Maswa 227,390 34,626 7 43,540 8,625 5 270,930 43,252 6 Shinyanga Rural 248,001 38,841 6 31,458 6,422 5 279,459 45,263 6 Kahama 444,770 70,196 6 47,659 11,021 4 492,428 81,217 6 Bukombe 318,090 48,282 7 24,458 4,958 5 342,548 53,240 6 Meatu 210,253 27,272 8 21,603 4,220 5 231,856 31,492 7 Shinyanga Urban 46,129 8,214 6 9,099 1,984 5 55,228 10,198 5 Kishapu 204,861 30,103 7 25,997 5,520 5 230,858 35,624 6 Total 2,167,778 323,921 7 258,628 53,936 5 2,426,406 377,857 6 Number of Househod Members % Number of Househod Members % Number of Househod Members % Bariadi 468,284 86 54,815 14 523,099 100 Maswa 227,390 80 43,540 20 270,930 100 Shinyanga Rural 248,001 86 31,458 14 279,459 100 Kahama 444,770 86 47,659 14 492,428 100 Bukombe 318,090 91 24,458 9 342,548 100 Meatu 210,253 87 21,603 13 231,856 100 Shinyanga Urban 46,129 81 9,099 19 55,228 100 Kishapu 204,861 85 25,997 15 230,858 100 Total 2,167,778 86 258,628 14 2,426,406 100 Mean Median Mode Mean Median Mode Mean Median Mode Bariadi 46 42 40 52 53 60 46 42 40 Maswa 47 43 35 53 54 62 48 45 35 Shinyanga Rural 46 43 42 51 49 50 47 44 42 Kahama 45 42 30 50 50 55 46 44 30 Bukombe 42 38 38 48 50 45 42 39 38 Meatu 45 43 30 49 43 39 46 43 42 Shinyanga Urban 45 42 38 54 55 58 47 43 38 Kishapu 46 45 45 49 45 60 47 45 45 Total 45 42 30 51 50 60 46 43 30 3.10 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households by Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 141 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Bariadi 30,843 44,270 0 1,751 351 356 77,572 Maswa 19,779 22,228 0 1,031 0 214 43,252 Shinyanga Rural 17,623 24,537 303 683 303 1,814 45,263 Kahama 34,612 43,129 397 1,702 559 818 81,217 Bukombe 15,855 36,072 119 716 119 358 53,240 Meatu 14,773 15,403 0 830 156 331 31,492 Shinyanga Urban 4,662 5,083 30 156 46 222 10,198 Kishapu 14,680 19,453 0 1,028 243 219 35,624 Total 152,826 210,174 849 7,898 1,778 4,332 377,857 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Attending School 0 1,708 0 15 0 313 2,036 Completed 1,080 208,466 849 7,883 1,778 4,019 224,076 Never Attended to School 151,746 0 0 0 0 0 151,746 Total 152,826 210,174 849 7,898 1,778 4,332 377,857 Bariadi 22,815 34 43,572 66 66,387 100 Maswa 13,174 38 21,452 62 34,626 100 Shinyanga Rural 14,114 36 24,726 64 38,841 100 Kahama 25,482 36 44,714 64 70,196 100 Bukombe 13,265 27 35,017 73 48,282 100 Meatu 11,332 42 15,939 58 27,272 100 Shinyanga Urban 2,957 36 5,257 64 8,214 100 Kishapu 10,635 35 19,468 65 30,103 100 Total 113,776 35 210,146 65 323,921 100 Continued …. 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Bariadi 8,906 80 2,279 20 11,185 100 Maswa 6,489 75 2,137 25 8,625 100 Shinyanga Rural 4,625 72 1,797 28 6,422 100 Kahama 8,147 74 2,875 26 11,021 100 Bukombe 3,658 74 1,300 26 4,958 100 Meatu 3,089 73 1,131 27 4,220 100 Shinyanga Urban 1,501 76 483 24 1,984 100 Kishapu 3,673 67 1,847 33 5,520 100 Total 40,088 74 13,848 26 53,936 100 Continued …. 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Bariadi 31,721 41 45,851 59 77,572 100 Maswa 19,663 45 23,589 55 43,252 100 Shinyanga Rural 18,740 41 26,523 59 45,263 100 Kahama 33,629 41 47,588 59 81,217 100 Bukombe 16,923 32 36,317 68 53,240 100 Meatu 14,422 46 17,070 54 31,492 100 Shinyanga Urban 4,458 44 5,740 56 10,198 100 Kishapu 14,309 40 21,315 60 35,624 100 Total 153,864 41 223,994 59 377,857 100 Can Read and Write Total 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year Education Status Maximum Education Level Attained 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Male District 3.11 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained Cannot Read and Write Cannot Read and Write Can Read and Write Total District Female Cannot Read and Write Can Read and Write Total Total District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 142 Number Percent Number Percent Number Percent Number Percent Bariadi 27,319 59 12,360 27 6,560 14 46,239 100 Maswa 7,958 48 3,942 24 4,580 28 16,481 100 Shinyanga Rural 23,408 73 6,947 22 1,686 5 32,041 100 Kahama 24,544 51 15,981 33 8,003 16 48,528 100 Bukombe 9,994 60 4,157 25 2,506 15 16,657 100 Meatu 5,036 48 2,483 24 2,864 28 10,383 100 Shinyanga 3,725 63 1,646 28 538 9 5,908 100 Kishapu 11,545 70 3,352 20 1,573 10 16,470 100 Total 113,528 59 50,868 26 28,310 15 192,706 100 Attending School Completed Never Attended to School Total Completed Never Attended to School Total Attending School Completed Never Attended School Total Bariadi 356 43,745 22,286 66,387 2,627 8,557 11,185 356 46,372 30,843 77,572 Maswa 433 20,702 13,492 34,626 2,447 6,179 8,625 433 23,148 19,671 43,252 Shinyanga Rural 201 25,540 13,099 38,841 1,899 4,523 6,422 201 27,439 17,623 45,263 Kahama 828 43,188 26,179 70,196 3,018 8,003 11,021 828 46,206 34,182 81,217 Bukombe 119 35,964 12,198 48,282 1,420 3,538 4,958 119 37,384 15,737 53,240 Meatu 83 15,829 11,359 27,272 1,131 3,089 4,220 83 16,961 14,448 31,492 Shinyanga Urban 15 5,154 3,045 8,214 468 1,516 1,984 15 5,621 4,562 10,198 Kishapu 0 19,178 10,926 30,103 1,766 3,755 5,520 0 20,943 14,680 35,624 Total 2,036 209,301 112,585 323,921 14,775 39,161 53,936 2,036 224,076 151,746 377,857 Attending School Completed Never Attended to School Total Completed Never Attended to School Total Attending School Completed Never Attended School Total Bariadi 1 66 34 100 23 77 100 0 60 40 100 Maswa 1 60 39 100 28 72 100 1 54 45 100 Shinyanga Rural 1 66 34 100 30 70 100 0 61 39 100 Kahama 1 62 37 100 27 73 100 1 57 42 100 Bukombe 0 74 25 100 29 71 100 0 70 30 100 Meatu 0 58 42 100 27 73 100 0 54 46 100 Shinyanga Urban 0 63 37 100 24 76 100 0 55 45 100 Kishapu 0 64 36 100 32 68 100 0 59 41 100 Total 1 65 35 100 27 73 100 1 59 40 100 3.14 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm Income Total 3.15B Percent of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Male Female Total 3.15A Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 143 Bariadi 37,733 57 5,661 9 178 0 22,815 34 66,387 100 Maswa 19,797 57 1,438 4 217 1 13,174 38 34,626 100 Shinyanga Rural 23,243 60 1,483 4 0 0 14,114 36 38,841 100 Kahama 41,915 60 2,799 4 0 0 25,482 36 70,196 100 Bukombe 32,748 68 2,149 4 119 0 13,265 27 48,282 100 Meatu 14,562 53 1,294 5 83 0 11,332 42 27,272 100 Shinyanga Urban 4,806 59 451 5 0 0 2,957 36 8,214 100 Kishapu 17,322 58 2,146 7 0 0 10,635 35 30,103 100 Total 192,127 59 17,421 5 598 0 113,776 35 323,921 100 Bariadi 1,929 17 349 3 8,906 80 11,185 100 Maswa 1,921 22 216 3 6,489 75 8,625 100 Shinyanga Rural 1,797 28 0 0 4,625 72 6,422 100 Kahama 2,627 24 247 2 8,147 74 11,021 100 Bukombe 1,300 26 0 0 3,658 74 4,958 100 Meatu 993 24 138 3 3,089 73 4,220 100 Shinyanga Urban 391 20 92 5 1,501 76 1,984 100 Kishapu 1,766 32 81 1 3,673 67 5,520 100 Total 12,723 24 1,125 2 40,088 74 53,936 100 Bariadi 39,662 51 6,010 8 178 0 31,721 41 77,572 100 Maswa 21,718 50 1,655 4 217 1 19,663 45 43,252 100 Shinyanga Rural 25,040 55 1,483 3 0 0 18,740 41 45,263 100 Kahama 44,542 55 3,046 4 0 0 33,629 41 81,217 100 Bukombe 34,048 64 2,149 4 119 0 16,923 32 53,240 100 Meatu 15,555 49 1,432 5 83 0 14,422 46 31,492 100 Shinyanga Urban 5,197 51 543 5 0 0 4,458 44 10,198 100 Kishapu 19,088 54 2,227 6 0 0 14,309 40 35,624 100 Total 204,850 54 18,546 5 598 0 153,864 41 377,857 100 Cont….3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year 3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Ag Swahili & English Any Other Language District Female Swahili Swahili & English Don't Read / Write Total District Cont….3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year Male Swahili Don't Read / Write Total Swahili District Total Total Swahili & English Any Other Language Don't Read / Write Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 144 3.17 Time Series of Male and Female Headed Households: Shinyanga Type of Holding (000') NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed 175 179 192 204 205 200 Female Headed 38 51 63 64 56 64 Total 213 230 255 268 261 264 Male Headed (%) 82 78 75 76 78 76 Female Headed (%) 18 22 25 24 22 24 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Bariadi 43,572 2,279 45,851 22,815 8,906 31,721 66,387 11,185 77,572 Maswa 21,452 2,137 23,589 13,174 6,489 19,663 34,626 8,625 43,252 Shinyanga Rural 24,726 1,797 26,523 14,114 4,625 18,740 38,841 6,422 45,263 Kahama 44,714 2,875 47,588 25,482 8,147 33,629 70,196 11,021 81,217 Bukombe 35,017 1,300 36,317 13,265 3,658 16,923 48,282 4,958 53,240 Meatu 15,939 1,131 17,070 11,332 3,089 14,422 27,272 4,220 31,492 Shinyanga Urban 5,257 483 5,740 2,957 1,501 4,458 8,214 1,984 10,198 Kishapu 19,468 1,847 21,315 10,635 3,673 14,309 30,103 5,520 35,624 Total 210,146 13,848 223,994 113,776 40,088 153,864 323,921 53,936 377,857 3.18 Literacy Rate of Heads of Households by Sex and District District Literacy Know Don;t know Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 145 Appendix II 146 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 147 No of Households % No of Households % No of Household s % No of Households % No of Household s % No of Households % No of Households % Bariadi 3,028 4 58,544 75 14,987 19 19,782 26 3,867 5 1,317 2 2,567 3 77,572 Maswa 1,326 3 32,629 75 8,430 19 9,352 22 3,306 8 749 2 1,257 3 43,252 Shinyanga R 1,116 2 34,482 76 13,113 29 6,218 14 2,731 6 203 0 1,600 4 45,263 Kahama 1,208 1 54,984 68 32,559 40 11,152 14 6,411 8 699 1 2,852 4 81,217 Bukombe 1,314 2 26,297 49 22,658 43 8,444 16 2,963 6 239 0 1,314 2 53,240 Meatu 1,365 4 19,782 63 8,520 27 9,290 29 4,275 14 954 3 1,786 6 31,492 Shinyanga U 1,478 14 7,983 78 1,604 16 1,076 11 672 7 47 0 158 2 10,198 Kishapu 471 1 24,479 69 9,550 27 6,674 19 5,521 15 641 2 882 2 35,624 Total 11,307 3 259,181 69 111,422 29 71,989 19 29,748 8 4,800 1 12,417 3 377,857 Area Leased/ Certificate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Lushoto 3,414 156,403 40,942 23,467 2,095 1,170 3,837 231,328 Korogwe 4,449 121,175 30,595 11,944 3,910 1,869 807 174,749 Muheza 3,621 79,761 32,608 6,484 2,340 91 2,603 127,507 Tanga 1,767 176,703 103,481 12,537 5,841 458 3,129 303,915 Pangani 1,983 95,910 76,239 13,340 2,735 218 2,902 193,327 Handeni 4,225 98,128 47,843 16,285 8,402 1,787 4,185 180,855 Kilindi 2,172 17,236 4,109 1,298 493 7 56 25,371 Kishapu 690 165,863 40,800 13,683 10,261 1,439 1,123 233,859 Total 22,321 911,178 376,618 99,038 36,075 7,038 18,642 1,470,910 % 2 62 26 7 2 0 1 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure District Total Number of Households Land Access 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 148 LAND USE Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 149 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Bariadi 74,809 9,122 2,220 1,387 2,055 6,776 2,043 1,704 3,134 2,046 2,688 14,305 77,572 Maswa 38,868 16,151 521 906 4,620 7,605 4,032 837 325 1,484 1,799 6,217 43,252 Shinyanga Rural 41,156 22,882 1,632 711 1,890 2,226 2,423 908 702 805 1,918 11,403 45,263 Kahama 68,120 50,663 2,454 2,925 7,003 3,778 21,587 5,798 852 2,004 2,742 15,649 81,217 Bukombe 42,068 29,455 239 1,074 2,146 2,739 8,521 1,429 478 2,135 1,293 7,490 53,240 Meatu 30,566 11,904 324 1,384 1,593 8,028 4,250 2,005 1,030 1,512 3,084 4,952 31,492 Shinyanga Urban 8,755 5,737 158 244 414 633 769 381 515 96 177 1,070 10,198 Kishapu 33,193 8,061 322 163 558 7,554 7,438 798 473 1,344 2,491 6,131 35,624 Total 150,120 86,312 57,423 42,241 76,275 2,509 35,758 1,542 16,954 4,726 7,899 41,911 377,857 Districts Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Bariadi 168,804 16,893 1,108 1,787 3,927 9,027 1,991 1,899 1,143 3,659 2,751 18,339 231,328 Maswa 94,664 21,124 1,394 1,777 10,626 19,459 7,843 1,028 153 2,344 2,744 11,593 174,749 Shinyanga Rural 69,269 32,008 516 390 2,091 4,329 3,862 1,245 135 598 1,822 11,242 127,507 Kahama 123,882 69,243 1,877 1,811 15,477 6,789 37,778 16,341 362 3,839 3,557 22,960 303,915 Bukombe 88,015 48,751 242 399 3,797 8,631 18,578 3,825 121 3,970 1,986 15,012 193,327 Meatu 88,390 19,067 544 5,602 5,442 27,527 10,120 2,594 1,029 4,454 4,731 11,358 180,855 Shinyanga Urban 11,542 7,122 55 102 525 1,343 1,418 921 89 246 160 1,459 24,981 Kishapu 109,050 19,139 311 132 713 44,277 23,708 6,266 422 2,174 8,679 16,610 231,481 Total 753,616 233,347 6,046 11,999 42,598 121,381 105,297 34,118 3,454 21,284 26,429 108,572 1,468,142 % 51 16 0 1 3 8 7 2 0 1 2 7 100 Land use area Type of Land Use 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 150 Number % Number % Number % Number % Bariadi 75,031 87 11,404 13 86,435 Bariadi 35,993 42 50,442 58 86,435 Maswa 29,280 64 16,420 36 45,700 Maswa 26,375 58 19,325 42 45,700 Shinyanga Rural 32,598 67 16,218 33 48,815 Shinyanga Rural 28,327 58 20,488 42 48,815 Kahama 3,596 42 4,960 58 8,555 Kahama 5,945 69 2,611 31 8,555 Bukombe 4,147 59 2,930 41 7,076 Bukombe 4,694 66 2,382 34 7,076 Meatu 20,561 43 27,070 57 47,631 Meatu 31,637 66 15,994 34 47,631 Shinyanga Urban 10,561 55 8,753 45 19,314 Shinyanga Urban 13,381 69 5,933 31 19,314 Total 175,773 67 87,754 33 263,528 Total 146,353 56 117,175 44 263,528 Number % Number % Bariadi 12,284 14 74,151 86 86,435 Maswa 11,206 25 34,494 75 45,700 Rural 14,802 30 34,013 70 48,815 Kahama 3,459 40 5,097 60 8,555 Bukombe 1,739 25 5,337 75 7,076 Meatu 16,758 35 30,873 65 47,631 Urban 2,326 12 16,988 88 19,314 Total 62,574 24 200,954 76 263,528 No Total Table 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year District Do any Female Members of the Household own or have customary right to Land Yes No Total Table 5.3: Number of Households by type of household and District during 2002/03 Agricultural Year Table 5.4: Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year District Was all Land Available to the Hh Used during 2002/03? District Do you Consider that you have sufficient land for the Hh? Yes No Total Yes Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 151 Appendix II 152 TOTAL ANNUAL CROP & VEGETABLE PRODUCTION – LONG & SHORT RAINY SEASON Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 153 Number of Household Planted Area (hectare) Number of Household Planted Area (hectare) Bariadi 0 0 77,393 182,648 182,648 0.00 Bukombe 108 580 42,935 111,811 112,392 0.52 Kahama 0 291 45,161 100,937 101,227 0.29 Shinyanga Rural 144 0 81,074 197,060 197,060 0.00 Meatu 239 1,651 52,643 132,870 134,521 1.23 Maswa 915 109 31,111 94,843 94,952 0.12 Shinyanga Urban 156 195 9,260 15,564 15,759 1.24 Kishapu 0 0 35,124 121,691 121,691 0.00 Total 1,561 2,826 374,699 957,423 960,250 0.29 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Bariadi - 77,572 77,393 179 77,572 Maswa 108 43,144 42,935 317 43,252 Shinyanga Rural - 45,263 45,161 102 45,263 Kahama 144 81,073 81,074 143 81,217 Bukombe 239 53,001 52,643 597 53,240 Meatu 915 30,577 31,111 380 31,492 Shinyanga Urban 156 10,042 9,260 939 10,198 Kishapu - 35,624 35,124 500 35,624 Total 1,561 376,296 374,699 3,158 377,857 % Area planted in short rainy season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District District Total area planted (hectare) Short Rainy Season Long Rainy Season 7.1 & 7.2b TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of crop growing Households Planting Crops by Season and Region District Short Rainy Season Long Rainy Season Total Number of Crop Growing households Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 154 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) CEREALS 1,873 1,139 589,543 315,047 591,416 316,187 Maize 1,541 647 420 398,729 190,755 478 400,270 191,402 478 Paddy 244 439 1,802 118,673 104,408 880 118,916 104,847 882 Sorghum 63 14 228 65,854 17,255 262 65,917 17,269 262 Bulrush Millet 26 38 1,482 5,998 2,491 415 6,024 2,530 420 Finger Millet 0 0 0 289 139 481 289 139 481 ROOTS & TUBERS 45 317 48,036 40,253 48,081 40,570 Cassava 0 0 19,235 14,599 759 19,235 14,599 759 Sweet Potatoes 45 317 7,116 27,556 25,059 909 27,601 25,376 919 Irish Potatoes 562 89 158 562 89 158 Yams 641 424 662 641 424 662 Cocoyam 41 82 1,976 41 82 1976 PULSES 104 27 67,704 34,323 67,809 34,350 Mung Beans 0 0 0 64 145 2,274 64 145 2274 Beans 101 25 247 38,843 16,295 420 38,944 16,320 419 Cowpeas 0 0 0 2,731 3,376 1,236 2,731 3,376 1236 Green Gram 0 0 0 755 2,898 3,836 755 2,898 3836 Chich Peas 0 0 0 23,933 10,315 431 23,933 10,315 431 Bambaranuts 3 2 494 1,379 1,295 939 1,382 1,296 938 OIL SEEDS & OIL NUTS 167 32 65,985 31,568 478 66,153 31,601 478 Sunflower 0 0 0 1,434 455 317 1,434 455 317 Simsim 0 0 0 364 194 534 364 194 534 Groundnuts 167 32 194 64,188 30,919 482 64,355 30,951 481 FRUIT & VEGETABLES 0 0 1,421 3,381 1,421 3,381 2380 Tomatoes 0 0 0 524 1,977 3,773 524 1,977 3773 Onions 0 0 0 257 503 1,956 257 503 1956 Egg Plant 0 0 0 203 83 408 203 83 408 Radish 0 0 0 199 121 609 199 121 609 Cabbage 0 0 0 104 461 4,443 104 461 4443 Amaranths 0 0 0 74 140 1,880 74 140 1880 Pumpkins 0 0 0 26 1 55 26 1 55 Cucumber 0 0 0 23 43 1,878 23 43 1878 Chillies 0 0 0 10 51 5,039 10 51 5039 CASH CROPS 637 172 204,383 106,815 205,020 106,987 522 Cotton 637 172 270 198,753 101,423 510 199,390 101,595 510 Tobacco 0 0 0 5,630 5,392 958 5,630 5,392 958 Total 2,826 1,661 977,072 497,065 979,898 498,726 bein produced on the same land during the 2 seasons. Previous surveys have used the Long season to estimate physical land area under production to different crops * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to crops 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Kahama Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 155 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 75,299 101,952 42,799 0.42 101,952 42,799 0.42 1.35 Maswa 108 44 9 0.20 38,409 35,115 14,371 0.41 35,159 14,380 0.41 0.92 Shinyanga Rural - 44,046 44,228 19,359 0.44 44,228 19,359 0.44 1.00 Kahama 144 174 72 0.41 78,402 79,731 58,011 0.73 79,905 58,083 0.73 1.02 Bukombe 239 314 244 0.78 51,714 64,519 37,758 0.59 64,833 38,002 0.59 1.25 Meatu 665 909 273 0.30 24,634 30,284 8,922 0.29 31,193 9,195 0.29 1.27 Shinyanga Urban 124 99 50 0.50 8,372 7,405 2,356 0.32 7,505 2,406 0.32 0.90 Kishapu - - - - 30,359 35,494 7,179 0.20 35,494 7,179 0.20 1.17 Total 1,279 1,541 647 0.42 351,234 398,729 190,755 3.39 400,270 191,402 0.48 1.14 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 17,093 6,914 5,769 0.83 6,914 5,769 0.83 0.40 Maswa 0 . . - 14,438 9,975 11,033 1.11 9,975 11,033 1.11 0.69 Shinyanga Rural - 28,678 20,937 18,119 0.87 20,937 18,119 0.87 0.73 Kahama 144 116 194 1.67 46,180 53,166 46,923 0.88 53,283 47,117 0.88 1.15 Bukombe 239 121 239 1.98 17,924 21,250 18,738 0.88 21,371 18,977 0.89 1.19 Meatu 0 . . - 1,314 349 161 0.46 349 161 0.46 0.27 Shinyanga Urban 32 6 6 0.99 3,396 1,621 1,382 0.85 1,628 1,389 0.85 0.48 Kishapu 7,024 4,459 2,282 0.51 4,459 2,282 0.00 0.63 Total 415 244 439 1.80 136,046 118,673 104,408 6.40 118,916 104,847 0.88 0.87 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 15,252 9,971 4,175 - 9,971 4,175 0.42 0.65 Maswa 0 . . - 9,906 7,950 3,098 - 7,950 3,098 0.00 0.80 Shinyanga Rural - 2,511 1,326 492 - 1,326 492 0.00 0.53 Kahama 0 . . - 427 101 62 0.61 101 62 0.61 0.24 Bukombe 0 . . - 597 227 78 0.34 227 78 0.34 0.38 Meatu 167 51 8 0.16 15,563 24,344 4,244 - 24,395 4,252 0.17 1.57 Shinyanga Urban 30 12 6 0.49 1,273 905 332 - 917 338 0.00 0.72 Kishapu 14,090 21,030 4,775 - 21,030 4,775 0.00 1.49 Total 196 63 14 0.23 59,619 65,854 17,255 0.95 65,917 17,269 0.26 1.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 119 97 6 - 97 6 0.00 0.81 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 32 26 38 1.48 1,271 1,645 1,384 - 1,671 1,422 0.00 1.32 Kishapu 2,473 4,256 1,102 0.26 4,256 1,102 0.00 1.72 Total 32 26 38 1.48 3,864 5,998 2,491 0.26 6,024 2,530 0.42 1.56 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Bulrushmillet District 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District Short Rainy Season Long Rainy Season Total District Paddy Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 156 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 353 180 92 0.51 180 92 0.51 0.51 Maswa 0 . . - 108 22 7 - 22 7 0.00 0.20 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 358 53 32 - 53 32 0.00 0.15 Meatu 0 . . - 83 34 8 - 34 8 0.00 0.40 Shinyanga Urban 0 . . - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 902 289 139 0.51 289 139 0.48 0.32 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Bariadi - 1,159 523 1,513 1.58 523 1,513 1.57 0.45 Maswa - 1,080 335 148 3.44 335 148 3.05 0.31 Shinyanga Rural - 7,173 3,755 5,395 2.37 3,755 5,395 2.36 0.52 Kahama - 16,910 7,752 3,560 2.65 7,752 3,560 2.65 0.46 Bukombe - 7,448 6,697 3,943 1.85 6,697 3,943 1.83 0.90 Meatu - 0 . . 3.52 0 0 2.85 - Shinyanga Urban - 551 174 39 3.07 174 39 3.06 0.32 Kishapu - . . - Total 0 0 0 - 34,321 19,235 14,599 18.48 19,235 14,599 0.76 0.56 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 9,695 2,384 2,075 0.87 2,384 2,075 0.87 0.25 Maswa - 20,195 5,729 5,383 0.94 5,729 5,383 0.94 0.28 Shinyanga Rural - 22,326 6,310 7,634 1.21 6,310 7,634 1.21 0.28 Kahama - 8,261 2,471 2,216 0.90 2,471 2,216 0.90 0.30 Bukombe - 2,852 989 1,351 1.37 989 1,351 1.37 0.35 Meatu - 8,466 2,378 1,136 0.48 2,378 1,136 0.48 0.28 Shinyanga Urban - 4,694 1,324 1,479 1.12 1,324 1,479 1.12 0.28 Kishapu 18,853 5,971 3,785 0.63 5,971 3,785 0.00 0.32 Total 0 0 0 - 95,342 27,556 25,059 7.51 27,556 25,059 0.91 0.29 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 356 144 18 0.12 144 18 0.12 0.40 Maswa - 108 22 26 1.19 22 26 1.19 0.20 Shinyanga Rural - 302 75 31 - 75 31 0.00 0.25 Kahama - 273 299 9 - 299 9 0.00 1.09 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 87 22 5 - 22 5 0.00 0.25 Kishapu - . . - Total 0 0 0 - 1,127 562 89 1.31 562 89 0.16 0.50 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Finger Millet District Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 157 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 178 36 14 - 36 14 0.00 0.20 Maswa - 2,107 451 333 0.74 451 333 0.74 0.21 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 142 57 34 - 57 34 0.00 0.40 Bukombe - 119 24 12 - 24 12 0.00 0.20 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 32 7 2 - 7 2 0.00 0.20 Kishapu 81 65 29 0.44 65 29 0.00 0.81 Total 0 0 0 - 2,659 641 424 1.18 641 424 0.66 0.24 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 - - Maswa - 0 . . - 0 0 - - Shinyanga Rural - 102 41 82 1.98 41 82 1.98 0.40 Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 102 41 82 1.98 41 82 1.98 0.40 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 1,739 372 81 0.22 372 81 0.22 0.21 Maswa 0 . . - 217 22 26 1.20 22 26 1.20 0.10 Shinyanga Rural - 500 100 14 0.14 100 14 0.14 0.20 Kahama 0 . . - 21,864 6,714 2,381 0.35 6,714 2,381 0.35 0.31 Bukombe 0 . . - 21,050 8,718 2,772 - 8,718 2,772 0.32 0.41 Meatu 167 101 25 0.25 869 238 92 0.39 339 117 0.35 0.39 Shinyanga Urban 0 . . - 54 17 9 0.54 17 9 0.54 0.32 Kishapu 70 114 7 0.06 114 7 0.00 1.62 Total 167 101 25 0.25 46,363 16,295 5,383 2.89 16,397 5,408 0.33 0.35 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 158 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 1,916 538 144 - 0 0 0.00 0.00 Maswa 2,276 285 85 0.08 295 24 0.08 0.13 Shinyanga Rural 3,622 700 205 0.21 2,016 482 0.24 0.56 Kahama 2,013 414 88 0.13 383 77 0.20 0.19 Bukombe 1,075 249 100 0.14 998 167 0.17 0.93 Meatu 1,635 392 111 0.20 7,982 1,798 0.23 4.88 Shinyanga Urban 112 45 15 0.18 333 76 0.23 2.98 Kishapu 1,118 752 102 0.14 752 102 0.00 0.67 Total 0 0 0 - 13,767 3,376 851 1.08 12,759 2,726 0.21 0.93 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 350 84 7 0.08 84 7 0.08 0.24 Maswa - 0 . . 0 0 #DIV/0! - Shinyanga Rural - 4,549 1,503 340 0.23 1,503 340 0.23 0.33 Kahama - 286 90 11 0.13 90 11 0.13 0.32 Bukombe - 358 135 55 0.41 135 55 0.41 0.38 Meatu - 393 135 17 0.12 135 17 0.12 0.34 Shinyanga Urban - 62 25 10 0.40 25 10 0.40 0.40 Kishapu 1,585 925 191 0.21 925 191 0.21 0.58 Total 0 0 0 - 7,584 2,898 630 1.57 2,898 630 0.22 0.38 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 2,423 2,503 904 - 2,503 904 0.00 1.03 Maswa - 633 363 193 - 363 193 0.00 0.57 Shinyanga Rural - 5,438 8,927 4,379 - 8,927 4,379 0.00 1.64 Kahama - 987 3,154 1,552 - 3,154 1,552 0.00 3.20 Bukombe - 949 2,922 858 - 2,922 858 0.29 3.08 Meatu - 162 174 90 - 174 90 0.00 1.08 Shinyanga Urban - 220 134 53 - 134 53 0.00 0.61 Kishapu 4,521 5,755 2,286 0.40 5,755 2,286 0.40 1.27 Total 0 0 0 - 15,333 23,933 10,315 0.40 23,933 10,315 0.43 1.56 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 1,516 383 666 - 383 666 0.00 0.25 Shinyanga Rural - 1,203 315 143 - 315 143 0.00 0.26 Kahama 0 . . - 2,266 502 395 - 502 395 0.79 0.22 Bukombe 0 . . - 119 10 7 - 10 7 0.00 0.08 Meatu 0 . . - 0 . . - 0 0 0.00 - Shinyanga Urban 32 3 2 0.49 379 105 50 - 108 51 0.00 0.29 Kishapu 409 64 33 0.51 64 33 0.51 0.16 Total 32 3 2 0.49 5,893 1,379 1,295 0.51 1,382 1,296 0.94 0.23 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 159 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 . . - 0 0 0.00 - Maswa 0 . . - 101 123 55 - 123 55 0.00 1.21 Shinyanga Rural 0 . . - 300 141 45 - 141 45 0.00 0.47 Kahama 0 . . - 425 172 68 - 172 68 0.00 0.40 Bukombe 0 . . - 1,434 859 228 - 859 228 0.00 0.60 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 0 . . - 31 6 6 - 6 6 0.00 0.20 Kishapu 82 133 54 0.41 133 54 0.41 1.62 Total 0 0 0 - 2,373 1,434 455 0.41 1,434 455 0.32 0.60 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 336 83 66 - 83 66 0.00 0.25 Maswa 0 . . - 108 22 0 - 22 0 0.00 0.20 Shinyanga Rural - 190 138 83 0.60 138 83 0.60 0.73 Kahama 0 . . - 0 . . - 0 0 - - Bukombe 0 . . - 0 . . - 0 0 - - Meatu 0 . . - 81 25 7 0.26 25 7 0.26 0.30 Shinyanga Urban 0 . . - 0 . . - 0 0 - - Kishapu 79 96 39 0.41 96 39 0.41 1.21 Total 0 0 0 - 794 364 194 1.27 364 194 0.53 0.46 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 8,131 2,845 1,135 - 2,845 1,135 0.00 0.35 Maswa 0 . . - 14,132 6,427 2,388 0.37 6,427 2,388 0.37 0.45 Shinyanga Rural - 26,037 9,766 5,932 0.61 9,766 5,932 0.61 0.38 Kahama 0 . . - 44,313 19,995 11,691 0.58 19,995 11,691 0.58 0.45 Bukombe 119 97 30 0.31 19,917 11,202 6,512 0.58 11,299 6,542 0.58 0.57 Meatu 83 67 0 - 7,221 2,968 692 0.23 3,035 692 0.23 0.42 Shinyanga Urban 32 3 3 0.79 3,344 1,544 636 0.41 1,547 639 0.41 0.46 Kishapu 14,710 9,441 1,933 0.20 9,441 1,933 0.20 0.64 Total 235 167 32 0.19 137,805 64,188 30,919 3.00 64,355 30,951 0.48 0.47 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 160 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 147 20 14 0.68 20 14 0.68 0.14 Bukombe - 73 6 3 0.46 6 3 0.46 0.09 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 220 26 17 1.14 26 17 0.63 0.12 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 270 36 118 3.24 36 118 3.24 0.13 Kahama - 0 . . - 0 0 0.00 - Bukombe - 59 10 8 0.81 10 8 0.81 0.18 Meatu - 212 129 170 1.32 129 170 1.32 0.61 Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 541 176 296 5.37 176 296 1.69 0.32 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 161 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - . . 0 - 0 0 - - Maswa - . . 0 - 0 0 - - Shinyanga Rural - 171 392 0 - 392 0 0.00 2.29 Kahama - 28 28 0 - 28 0 0.00 0.99 Bukombe - . . 0 - 0 0 - - Meatu - . . 0 - 0 0 0.00 - Shinyanga Urban - . . 31 - 0 31 - - Kishapu 58 83 - - 83 0 0.00 1.43 Total 0 0 0 257 503 31 - 503 31 0.06 1.96 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 342 53 118 2.24 53 118 2.24 0.15 Maswa - 0 . . - 0 0 - - Shinyanga Rural - 101 10 15 - 10 15 1.48 0.10 Kahama - 285 22 307 13.98 22 307 13.98 0.08 Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 47 19 21 1.09 19 21 1.09 0.40 Kishapu - . . - Total 0 0 0 - 776 104 461 17.31 104 461 4.44 0.13 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 357 36 152 4.20 36 152 4.20 0.10 Maswa - 0 . . - 0 0 #DIV/0! - Shinyanga Rural - 805 165 619 3.74 165 619 3.74 0.21 Kahama - 851 160 398 2.48 160 398 2.48 0.19 Bukombe - 119 12 211 17.49 12 211 17.49 0.10 Meatu - 81 16 36 2.22 16 36 2.22 0.20 Shinyanga Urban - 341 93 373 4.04 93 373 4.04 0.27 Kishapu 163 41 188 4.54 41 188 4.54 0.25 Total 0 0 0 - 2,717 524 1,977 38.71 524 1,977 3.77 0.19 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 162 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 106 17 0 - 17 0 0.00 0.16 Shinyanga Rural - 86 5 0 - 5 0 0.00 0.06 Kahama - 54 2 2 0.87 2 2 0.87 0.04 Bukombe - 22 9 0 - 9 0 0.00 0.40 Meatu - 310 31 29 0.92 31 29 0.92 0.10 Shinyanga Urban - 0 . . - 0 0 - - Kishapu - Total 0 0 0 - 579 65 31 1.79 65 31 0.47 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 273 90 668 7.39 90 668 7.39 0.33 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 273 90 668 7.39 90 668 7.39 0.33 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 0.00 - Maswa 0 . . - 0 0 0.00 - Shinyanga Rural 79 8 8 1.04 8 8 1.04 0.10 Kahama 66 7 8 1.17 7 8 1.17 0.10 Bukombe 59 8 4 0.42 8 4 0.42 0.14 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 0.00 - Kishapu - Total 204 23 20 2.63 23 20 0.86 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 193 76 687 9.02 76 687 9.02 0.39 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 21 2 12 5.93 2 12 5.93 0.10 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 214 78 699 14.95 78 699 8.94 0.37 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 163 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 48,808 53,882 32,074 0.60 53,882 32,074 0.60 1.10 Maswa 108 66 15 0.23 32,967 44,575 22,036 0.49 44,640 22,051 0.49 1.35 Shinyanga Rural - 2,303 2,105 963 0.46 2,105 963 0.46 0.91 Kahama 0 . . - 14,316 16,803 12,165 0.72 16,803 12,165 0.72 1.17 Bukombe 119 48 10 0.20 12,882 14,750 12,560 0.85 14,798 12,570 0.85 1.15 Meatu 333 523 147 0.28 20,918 33,505 10,800 0.32 34,028 10,947 0.32 1.63 Shinyanga Urban 0 . . - 380 385 264 0.69 385 264 0.69 1.01 Kishapu 19,267 32,748 10,563 0.32 32,748 10,563 0.32 1.70 Total 561 637 172 0.27 151,840 198,753 101,423 4.45 199,390 101,595 0.51 1.31 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 - - Maswa 0 . . - 0 0 - - Shinyanga Rural 102 41 20 0.49 41 20 0.49 0.40 Kahama 5,406 5,413 5,241 - 5,413 5,241 0.00 1.00 Bukombe 358 109 123 1.13 109 123 1.13 0.30 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 - - Kishapu 82 66 8 0.12 66 8 0.12 0.81 Total 0 0 0 5,948 5,630 5,392 0.96 5,630 5,392 0.96 0.95 Average Planted Area Per household Average Planted Area Per household 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 164 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,671 5,315 65,617 164,355 10,104 12,527 77,393 182,196 Maswa 1,720 9,247 31,164 89,584 10,158 13,085 43,042 111,916 Shinyanga Rural 810 1,229 36,243 86,690 8,108 12,605 45,161 100,524 Kahama 1,520 6,167 16,219 49,833 63,478 140,776 81,218 196,776 Bukombe 1,427 2,240 5,727 32,312 45,727 98,898 52,882 133,450 Meatu 950 4,552 25,373 82,614 5,703 9,328 32,026 96,494 Shinyanga Urban 91 99 6,441 12,183 2,883 3,477 9,415 15,759 Kishapu 562 3,135 31,040 112,432 3,521 6,125 35,124 121,691 Total 8,753 31984.2 217,825 630,001 149,683 296,821 376,261 958,806 % 0.9 3.3 22.7 65.7 15.6 31.0 39.2 100.0 Total Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Planted Area Bariadi 6,857 25,192 1,064 2,158 0 0 69,472 155,298 182,648 Maswa 4,374 13,327 528 1,299 216 175 37,924 97,119 111,920 Shinyanga Rural 8,776 20,436 569 465 0 0 35,816 80,035 100,937 Kahama 15,057 38,570 2,314 3,538 6,722 18,336 57,126 136,906 197,351 Bukombe 4,611 16,482 1,673 3,507 358 931 46,239 112,530 133,450 Meatu 2,418 9,563 83 671 0 0 29,525 86,259 96,494 Shinyanga Urban 2,710 3,393 294 826 32 110 6,380 11,430 15,759 Kishapu 3,266 10,798 567 2,386 79 827 31,212 107,681 121,691 Total 48,069 137,761 7,091 14,850 7,407 20,380 313,694 787,259 960,250 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,921 4,966 74,472 177,682 77,393 182,648 2.7 Maswa 648 1,580 42,395 110,341 43,042 111,920 1.4 Shinyanga Rural 1,824 3,152 43,337 97,784 45,161 100,937 3.1 Kahama 1,830 6,309 79,387 191,042 81,218 197,351 3.2 Bukombe 712 1,338 52,170 132,113 52,882 133,450 1.0 Meatu 167 641 31,859 95,852 32,026 96,494 0.7 Shinyanga Urban 538 863 8,878 14,896 9,415 15,759 5.5 Kishapu 1,283 2,597 33,840 119,094 35,124 121,691 2.1 Total 9,922 21,445 366,339 938,804 376,261 960,250 2.2 % 2.6 2.2 97.4 97.8 100.0 100.0 2.2 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga Region District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Shinyanya Region District Soil Preparation y Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 165 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 32,717 103,285 44,676 79,362 77,393 182,648 56.55 Maswa 7,974 25,522 35,068 86,398 43,042 111,920 22.80 Shinyanga Rural 3,313 9,686 41,847 91,251 45,161 100,937 9.60 Kahama 22,480 68,787 58,737 128,564 81,218 197,351 34.86 Bukombe 12,997 47,075 39,885 86,376 52,882 133,450 35.28 Meatu 9,424 34,836 22,602 61,658 32,026 96,494 36.10 Shinyanga Urban 612 1,584 8,804 14,174 9,415 15,759 10.05 Kishapu 7,920 40,118 27,204 81,574 35,124 121,691 32.97 Total 97,437 330,893 278,824 629,357 376,261 960,250 34.5 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,599 3,171 75,794 179,477 77,393 182,648 1.74 Maswa 650 1,053 42,392 110,867 43,042 111,920 0.94 Shinyanga Rural 1,406 2,737 43,755 98,199 45,161 100,937 2.71 Kahama 1,264 2,721 79,954 194,629 81,218 197,351 1.38 Bukombe 597 1,645 52,284 131,806 52,882 133,450 1.23 Meatu 315 884 31,711 95,609 32,026 96,494 0.92 Shinyanga Urban 122 259 9,294 15,500 9,415 15,759 1.64 Kishapu 1,157 5,050 33,967 116,641 35,124 121,691 4.15 Total 7,109 17,521 369,151 942,729 376,261 960,250 1.82 % 2 2 98 98 100 100 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted area using Insecticide District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Herbicide 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Kahama. Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 166 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,446 5,872 74,947 176,775 77,393 182,648 3.2 Maswa 3,566 8,745 39,477 103,175 43,042 111,920 7.8 Shinyanga Rural 1,906 3,494 43,255 97,442 45,161 100,937 3.5 Kahama 4,007 13,910 77,210 183,441 81,218 197,351 7.0 Bukombe 1,668 6,191 51,214 127,259 52,882 133,450 4.6 Meatu 167 742 31,859 95,751 32,026 96,494 0.8 Shinyanga Urban 313 670 9,102 15,089 9,415 15,759 4.3 Kishapu 891 3,384 34,233 118,307 35,124 121,691 2.8 Total 14,963 7,220 423,390 393,090 430,102 400,310 1.8 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 17,809 48,537 59,584 133,659 77,393 182,196 26.64 Maswa 12,159 39,669 30,884 72,247 43,042 111,916 35.45 Shinyanga Rural 3,605 10,983 41,556 89,541 45,161 100,524 10.93 Kahama 13,945 37,903 67,272 158,873 81,218 196,776 19.26 Bukombe 4,293 16,328 48,588 117,122 52,882 133,450 12.24 Meatu 13,388 47,553 18,638 48,941 32,026 96,494 49.28 Shinyanga Urban 1,473 2,197 7,943 13,561 9,415 15,759 13.94 Kishapu 13,285 57,895 21,839 63,796 35,124 121,691 47.58 Total 79,957 261,066 296,304 697,741 376,261 958,806 27.23 % 21 27 79 73 100 100 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Improved Seeds % of Planted area using Fungicide 7.1 & 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Shinyanga Region 7.1 &7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Shinyanga Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census-2003 Shinyanga 167 Appendix II 168 ANNUAL CROP & VEGETABLE PRODUCTION – LONG RAINY SEASON Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 169 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Bariadi 1,671 5,315 65,617 164,355 10,104 12,527 77,393 182,196 Maswa 1,720 9,247 31,056 89,475 10,158 13,085 42,935 111,807 Shinyanga Rural 810 1,229 36,243 86,690 8,108 12,605 45,161 100,524 Kahama 1,520 6,167 16,219 49,833 63,335 140,485 81,074 196,485 Bukombe 1,427 2,240 5,727 32,312 45,488 98,318 52,643 132,870 Meatu 867 4,383 25,206 82,344 5,038 8,115 31,111 94,843 Shinyanga Urban 91 99 6,379 12,077 2,789 3,388 9,260 15,564 Kishapu 562 3,135 31,040 112,432 3,521 6,125 35,124 121,691 Total 8,670 31,815 217,488 629,516 148,541 294,648 374,699 955,980 % 2 3 58 66 40 31 100 100 No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area Bariadi 6,857 25,192 1,064 2,158 0 . 69,472 155,298 77,393 182,648 Maswa 4,374 13,327 420 1,190 216 175 37,924 97,119 42,935 111,811 Shinyanga Rural 8,776 20,436 569 465 0 . 35,816 80,035 45,161 100,937 Kahama 14,913 38,280 2,314 3,538 6,722 18,336 57,126 136,906 81,074 197,060 Bukombe 4,611 16,482 1,553 3,169 358 931 46,120 112,288 52,643 132,870 Meatu 2,335 9,394 83 671 0 . 28,693 84,777 31,111 94,843 Shinyanga Urban 2,584 3,252 294 826 32 110 6,350 11,376 9,260 15,564 Kishapu 3,266 10,798 567 2,386 79 827 31,212 107,681 35,124 121,691 Total 47,716 137,161 6,864 14,402 7,407 20,380 312,714 785,481 374,699 957,423 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Bariadi 2,921 4,966 74,472 177,682 77,393 182,648 2.7 Maswa 648 1,580 42,287 110,231 42,935 111,811 1.4 Shinyanga Rural 1,824 3,152 43,337 97,784 45,161 100,937 3.1 Kahama 1,830 6,309 79,244 190,751 81,074 197,060 3.2 Bukombe 712 1,338 51,931 131,532 52,643 132,870 1.0 Meatu 167 641 30,945 94,202 31,111 94,843 0.7 Shinyanga Urban 538 863 8,722 14,701 9,260 15,564 5.5 Kishapu 1,283 2,597 33,840 119,094 35,124 121,691 2.1 Total 9,922 21,445 364,778 935,978 374,699 957,423 2.2 % 3 2 97 98 100 100 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Kahama Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Irrigation Use % of area planted under irrigation in long rainy season Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 170 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 32,717 103,285 44,676 79,362 77,393 182,648 Maswa 7,974 25,522 34,960 86,289 42,935 111,811 Shinyanga Rural 3,313 9,686 41,847 91,251 45,161 100,937 Kahama 22,480 68,787 58,594 128,273 81,074 197,060 Bukombe 12,997 47,075 39,646 85,795 52,643 132,870 Meatu 9,424 34,836 21,687 60,007 31,111 94,843 Shinyanga Urban 612 1,584 8,648 13,980 9,260 15,564 Kishapu 7,920 40,118 27,204 81,574 35,124 121,691 Total 97,437 330,893 277,263 626,531 374,699 957,423 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,599 3,171 75,794 179,477 77,393 182,648 1.7 Maswa 650 1,053 42,284 110,758 42,935 111,811 0.9 Shinyanga Rural 1,406 2,737 43,755 98,199 45,161 100,937 2.7 Kahama 1,264 2,721 79,810 194,339 81,074 197,060 1.4 Bukombe 597 1,645 52,045 131,225 52,643 132,870 1.2 Meatu 315 884 30,796 93,958 31,111 94,843 0.9 Shinyanga Urban 122 259 9,138 15,305 9,260 15,564 1.7 Kishapu 1,157 5,050 33,967 116,641 35,124 121,691 4.2 Total 7,109 17,521 367,590 939,903 374,699 957,423 1.8 % 2 2 98 98 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,446 5,872 74,947 176,775 77,393 182,648 3.2 Maswa 3,566 8,745 39,369 103,066 42,935 111,811 7.8 Shinyanga Rural 1,906 3,494 43,255 97,442 45,161 100,937 3.5 Kahama 4,007 13,910 77,067 183,150 81,074 197,060 7.1 Bukombe 1,668 6,191 50,975 126,679 52,643 132,870 4.7 Meatu 83 169 31,028 94,674 31,111 94,843 0.2 Shinyanga Urban 313 670 8,946 14,894 9,260 15,564 4.3 Kishapu 891 3,384 34,233 118,307 35,124 121,691 2.8 Total 14,880 42,435 359,819 914,988 374,699 957,423 4.4 % 4.0 4.4 96.0 95.6 100.0 100.0 % of Planted area using Fungicide Households Not Using Herbicide 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region District Insecticide Use Households Using District Herbicide Use Households Using Herbicide Households Not Using Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total % of Planted area using Herbicide Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 171 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 17,809 48,537 59,584 133,659 77,393 182,196 27 Maswa 12,159 39,669 30,776 72,138 42,935 111,807 35 Shinyanga Rural 3,605 10,983 41,556 89,541 45,161 100,524 11 Kahama 13,945 37,903 67,129 158,582 81,074 196,485 19 Bukombe 4,174 15,989 48,469 116,880 52,643 132,870 12 Meatu 12,640 46,172 18,471 48,671 31,111 94,843 49 Shinyanga Urban 1,473 2,197 7,787 13,367 9,260 15,564 14 Kishapu 13,285 57,895 21,839 63,796 35,124 121,691 48 Total 79,089 259,346 295,610 696,634 374,699 955,980 27 % 21 27 79 73 100 100 District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON, Kahama Region Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 172 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 75,299 101,952 42,799 0.42 101,952 42,799 0.42 1.35 Maswa 108 44 9 0.20 38,409 35,115 14,371 0.41 35,159 14,380 0.41 0.92 Shinyanga Rural - 44,046 44,228 19,359 0.44 44,228 19,359 0.44 1.00 Kahama 144 174 72 0.41 78,402 79,731 58,011 0.73 79,905 58,083 0.73 1.02 Bukombe 239 314 244 0.78 51,714 64,519 37,758 0.59 64,833 38,002 0.59 1.25 Meatu 665 909 273 0.30 24,634 30,284 8,922 0.29 31,193 9,195 0.29 1.27 Shinyanga Urban 124 99 50 0.50 8,372 7,405 2,356 0.32 7,505 2,406 0.32 0.90 Kishapu - - - - 30,359 35,494 7,179 0.20 35,494 7,179 0.20 1.17 Total 1,279 1,541 647 0.42 351,234 398,729 190,755 3.39 400,270 191,402 0.48 1.14 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 17,093 6,914 5,769 0.83 6,914 5,769 0.83 0.40 Maswa 0 . . - 14,438 9,975 11,033 1.11 9,975 11,033 1.11 0.69 Shinyanga Rural - 28,678 20,937 18,119 0.87 20,937 18,119 0.87 0.73 Kahama 144 116 194 1.67 46,180 53,166 46,923 0.88 53,283 47,117 0.88 1.15 Bukombe 239 121 239 1.98 17,924 21,250 18,738 0.88 21,371 18,977 0.89 1.19 Meatu 0 . . - 1,314 349 161 0.46 349 161 0.46 0.27 Shinyanga Urban 32 6 6 0.99 3,396 1,621 1,382 0.85 1,628 1,389 0.85 0.48 Kishapu 7,024 4,459 2,282 0.51 4,459 2,282 0.00 0.63 Total 415 244 439 1.80 136,046 118,673 104,408 6.40 118,916 104,847 0.88 0.87 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 15,252 9,971 4,175 - 9,971 4,175 0.42 0.65 Maswa 0 . . - 9,906 7,950 3,098 - 7,950 3,098 0.00 0.80 Shinyanga Rural - 2,511 1,326 492 - 1,326 492 0.00 0.53 Kahama 0 . . - 427 101 62 0.61 101 62 0.61 0.24 Bukombe 0 . . - 597 227 78 0.34 227 78 0.34 0.38 Meatu 167 51 8 0.16 15,563 24,344 4,244 - 24,395 4,252 0.17 1.57 Shinyanga Urban 30 12 6 0.49 1,273 905 332 - 917 338 0.00 0.72 Kishapu 14,090 21,030 4,775 - 21,030 4,775 0.00 1.49 Total 196 63 14 0.23 59,619 65,854 17,255 0.95 65,917 17,269 0.26 1.11 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District Short Rainy Season Long Rainy Season Total District Paddy Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 173 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 119 97 6 - 97 6 0.00 0.81 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 32 26 38 1.48 1,271 1,645 1,384 - 1,671 1,422 0.00 1.32 Kishapu 2,473 4,256 1,102 0.26 4,256 1,102 0.00 1.72 Total 32 26 38 1.48 3,864 5,998 2,491 0.26 6,024 2,530 0.42 1.56 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 353 180 92 0.51 180 92 0.51 0.51 Maswa 0 . . - 108 22 7 - 22 7 0.00 0.20 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 358 53 32 - 53 32 0.00 0.15 Meatu 0 . . - 83 34 8 - 34 8 0.00 0.40 Shinyanga Urban 0 . . - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 902 289 139 0.51 289 139 0.48 0.32 Average Planted Area Per household Average Planted Area Per household 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Finger Millet District 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Bulrushmillet District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 174 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Bariadi - 1,159 523 1,513 1.58 523 1,513 1.57 0.45 Maswa - 1,080 335 148 3.44 335 148 3.05 0.31 Shinyanga Rural - 7,173 3,755 5,395 2.37 3,755 5,395 2.36 0.52 Kahama - 16,910 7,752 3,560 2.65 7,752 3,560 2.65 0.46 Bukombe - 7,448 6,697 3,943 1.85 6,697 3,943 1.83 0.90 Meatu - 0 . . 3.52 0 0 2.85 - Shinyanga Urban - 551 174 39 3.07 174 39 3.06 0.32 Kishapu - . . - Total 0 0 0 - 34,321 19,235 14,599 18.48 19,235 14,599 0.76 0.56 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 9,695 2,384 2,075 0.87 2,384 2,075 0.87 0.25 Maswa - 20,195 5,729 5,383 0.94 5,729 5,383 0.94 0.28 Shinyanga Rural - 22,326 6,310 7,634 1.21 6,310 7,634 1.21 0.28 Kahama - 8,261 2,471 2,216 0.90 2,471 2,216 0.90 0.30 Bukombe - 2,852 989 1,351 1.37 989 1,351 1.37 0.35 Meatu - 8,466 2,378 1,136 0.48 2,378 1,136 0.48 0.28 Shinyanga Urban - 4,694 1,324 1,479 1.12 1,324 1,479 1.12 0.28 Kishapu 18,853 5,971 3,785 0.63 5,971 3,785 0.00 0.32 Total 0 0 0 - 95,342 27,556 25,059 7.51 27,556 25,059 0.91 0.29 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 356 144 18 0.12 144 18 0.12 0.40 Maswa - 108 22 26 1.19 22 26 1.19 0.20 Shinyanga Rural - 302 75 31 - 75 31 0.00 0.25 Kahama - 273 299 9 - 299 9 0.00 1.09 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 87 22 5 - 22 5 0.00 0.25 Kishapu - . . - Total 0 0 0 - 1,127 562 89 1.31 562 89 0.16 0.50 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 175 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 178 36 14 - 36 14 0.00 0.20 Maswa - 2,107 451 333 0.74 451 333 0.74 0.21 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 142 57 34 - 57 34 0.00 0.40 Bukombe - 119 24 12 - 24 12 0.00 0.20 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 32 7 2 - 7 2 0.00 0.20 Kishapu 81 65 29 0.44 65 29 0.00 0.81 Total 0 0 0 - 2,659 641 424 1.18 641 424 0.66 0.24 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 - - Maswa - 0 . . - 0 0 - - Shinyanga Rural - 102 41 82 1.98 41 82 1.98 0.40 Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 102 41 82 1.98 41 82 1.98 0.40 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 1,739 372 81 0.22 372 81 0.22 0.21 Maswa 0 . . - 217 22 26 1.20 22 26 1.20 0.10 Shinyanga Rural - 500 100 14 0.14 100 14 0.14 0.20 Kahama 0 . . - 21,864 6,714 2,381 0.35 6,714 2,381 0.35 0.31 Bukombe 0 . . - 21,050 8,718 2,772 - 8,718 2,772 0.32 0.41 Meatu 167 101 25 0.25 869 238 92 0.39 339 117 0.35 0.39 Shinyanga Urban 0 . . - 54 17 9 0.54 17 9 0.54 0.32 Kishapu 70 114 7 0.06 114 7 0.00 1.62 Total 167 101 25 0.25 46,363 16,295 5,383 2.89 16,397 5,408 0.33 0.35 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 176 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 1,916 538 144 - 0 0 0.00 0.00 Maswa 2,276 285 85 0.08 295 24 0.08 0.13 Shinyanga Rural 3,622 700 205 0.21 2,016 482 0.24 0.56 Kahama 2,013 414 88 0.13 383 77 0.20 0.19 Bukombe 1,075 249 100 0.14 998 167 0.17 0.93 Meatu 1,635 392 111 0.20 7,982 1,798 0.23 4.88 Shinyanga Urban 112 45 15 0.18 333 76 0.23 2.98 Kishapu 1,118 752 102 0.14 752 102 0.00 0.67 Total 0 0 0 - 13,767 3,376 851 1.08 12,759 2,726 0.21 0.93 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 350 84 7 0.08 84 7 0.08 0.24 Maswa - 0 . . 0 0 0 - Shinyanga Rural - 4,549 1,503 340 0.23 1,503 340 0.23 0.33 Kahama - 286 90 11 0.13 90 11 0.13 0.32 Bukombe - 358 135 55 0.41 135 55 0.41 0.38 Meatu - 393 135 17 0.12 135 17 0.12 0.34 Shinyanga Urban - 62 25 10 0.40 25 10 0.40 0.40 Kishapu 1,585 925 191 0.21 925 191 0.21 0.58 Total 0 0 0 - 7,584 2,898 630 1.57 2,898 630 0.22 0.38 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 2,423 2,503 904 - 2,503 904 0.00 1.03 Maswa - 633 363 193 - 363 193 0.00 0.57 Shinyanga Rural - 5,438 8,927 4,379 - 8,927 4,379 0.00 1.64 Kahama - 987 3,154 1,552 - 3,154 1,552 0.00 3.20 Bukombe - 949 2,922 858 - 2,922 858 0.29 3.08 Meatu - 162 174 90 - 174 90 0.00 1.08 Shinyanga Urban - 220 134 53 - 134 53 0.00 0.61 Kishapu 4,521 5,755 2,286 0.40 5,755 2,286 0.40 1.27 Total 0 0 0 - 15,333 23,933 10,315 0.40 23,933 10,315 0.43 1.56 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 177 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 1,516 383 666 - 383 666 0.00 0.25 Shinyanga Rural - 1,203 315 143 - 315 143 0.00 0.26 Kahama 0 . . - 2,266 502 395 - 502 395 0.79 0.22 Bukombe 0 . . - 119 10 7 - 10 7 0.00 0.08 Meatu 0 . . - 0 . . - 0 0 0.00 - Shinyanga Urban 32 3 2 0.49 379 105 50 - 108 51 0.00 0.29 Kishapu 409 64 33 0.51 64 33 0.51 0.16 Total 32 3 2 0.49 5,893 1,379 1,295 0.51 1,382 1,296 0.94 0.23 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 . . - 0 0 0.00 - Maswa 0 . . - 101 123 55 - 123 55 0.00 1.21 Shinyanga Rural 0 . . - 300 141 45 - 141 45 0.00 0.47 Kahama 0 . . - 425 172 68 - 172 68 0.00 0.40 Bukombe 0 . . - 1,434 859 228 - 859 228 0.00 0.60 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 0 . . - 31 6 6 - 6 6 0.00 0.20 Kishapu 82 133 54 0.41 133 54 0.41 1.62 Total 0 0 0 - 2,373 1,434 455 0.41 1,434 455 0.32 0.60 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 336 83 66 - 83 66 0.00 0.25 Maswa 0 . . - 108 22 0 - 22 0 0.00 0.20 Shinyanga Rural - 190 138 83 0.60 138 83 0.60 0.73 Kahama 0 . . - 0 . . - 0 0 - - Bukombe 0 . . - 0 . . - 0 0 - - Meatu 0 . . - 81 25 7 0.26 25 7 0.26 0.30 Shinyanga Urban 0 . . - 0 . . - 0 0 - - Kishapu 79 96 39 0.41 96 39 0.41 1.21 Total 0 0 0 - 794 364 194 1.27 364 194 0.53 0.46 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 178 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 8,131 2,845 1,135 - 2,845 1,135 0.00 0.35 Maswa 0 . . - 14,132 6,427 2,388 0.37 6,427 2,388 0.37 0.45 Shinyanga Rural - 26,037 9,766 5,932 0.61 9,766 5,932 0.61 0.38 Kahama 0 . . - 44,313 19,995 11,691 0.58 19,995 11,691 0.58 0.45 Bukombe 119 97 30 0.31 19,917 11,202 6,512 0.58 11,299 6,542 0.58 0.57 Meatu 83 67 0 - 7,221 2,968 692 0.23 3,035 692 0.23 0.42 Shinyanga Urban 32 3 3 0.79 3,344 1,544 636 0.41 1,547 639 0.41 0.46 Kishapu 14,710 9,441 1,933 0.20 9,441 1,933 0.20 0.64 Total 235 167 32 0.19 137,805 64,188 30,919 3.00 64,355 30,951 0.48 0.47 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 147 20 14 0.68 20 14 0.68 0.14 Bukombe - 73 6 3 0.46 6 3 0.46 0.09 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 220 26 17 1.14 26 17 0.63 0.12 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 270 36 118 3.24 36 118 3.24 0.13 Kahama - 0 . . - 0 0 0.00 - Bukombe - 59 10 8 0.81 10 8 0.81 0.18 Meatu - 212 129 170 1.32 129 170 1.32 0.61 Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 541 176 296 5.37 176 296 1.69 0.32 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District Average Planted Area Per household Average Planted Area Per household 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 179 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - . . 0 - 0 0 - - Maswa - . . 0 - 0 0 - - Shinyanga Rural - 171 392 0 - 392 0 0.00 2.29 Kahama - 28 28 0 - 28 0 0.00 0.99 Bukombe - . . 0 - 0 0 - - Meatu - . . 0 - 0 0 0.00 - Shinyanga Urban - . . 31 - 0 31 - - Kishapu 58 83 - - 83 0 0.00 1.43 Total 0 0 0 257 503 31 - 503 31 0.06 1.96 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 342 53 118 2.24 53 118 2.24 0.15 Maswa - 0 . . - 0 0 - - Shinyanga Rural - 101 10 15 - 10 15 1.48 0.10 Kahama - 285 22 307 13.98 22 307 13.98 0.08 Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 47 19 21 1.09 19 21 1.09 0.40 Kishapu - . . - Total 0 0 0 - 776 104 461 17.31 104 461 4.44 0.13 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 357 36 152 4.20 36 152 4.20 0.10 Maswa - 0 . . - 0 0 0 - Shinyanga Rural - 805 165 619 3.74 165 619 3.74 0.21 Kahama - 851 160 398 2.48 160 398 2.48 0.19 Bukombe - 119 12 211 17.49 12 211 17.49 0.10 Meatu - 81 16 36 2.22 16 36 2.22 0.20 Shinyanga Urban - 341 93 373 4.04 93 373 4.04 0.27 Kishapu 163 41 188 4.54 41 188 4.54 0.25 Total 0 0 0 - 2,717 524 1,977 38.71 524 1,977 3.77 0.19 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 180 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 106 17 0 - 17 0 0.00 0.16 Shinyanga Rural - 86 5 0 - 5 0 0.00 0.06 Kahama - 54 2 2 0.87 2 2 0.87 0.04 Bukombe - 22 9 0 - 9 0 0.00 0.40 Meatu - 310 31 29 0.92 31 29 0.92 0.10 Shinyanga Urban - 0 . . - 0 0 - - Kishapu - Total 0 0 0 - 579 65 31 1.79 65 31 0.47 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 273 90 668 7.39 90 668 7.39 0.33 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 273 90 668 7.39 90 668 7.39 0.33 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 0.00 - Maswa 0 . . - 0 0 0.00 - Shinyanga Rural 79 8 8 1.04 8 8 1.04 0.10 Kahama 66 7 8 1.17 7 8 1.17 0.10 Bukombe 59 8 4 0.42 8 4 0.42 0.14 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 0.00 - Kishapu - Total 204 23 20 2.63 23 20 0.86 0.11 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 181 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 193 76 687 9.02 76 687 9.02 0.39 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 21 2 12 5.93 2 12 5.93 0.10 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 214 78 699 14.95 78 699 8.94 0.37 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 48,808 53,882 32,074 0.60 53,882 32,074 0.60 1.10 Maswa 108 66 15 0.23 32,967 44,575 22,036 0.49 44,640 22,051 0.49 1.35 Shinyanga Rural - 2,303 2,105 963 0.46 2,105 963 0.46 0.91 Kahama 0 . . - 14,316 16,803 12,165 0.72 16,803 12,165 0.72 1.17 Bukombe 119 48 10 0.20 12,882 14,750 12,560 0.85 14,798 12,570 0.85 1.15 Meatu 333 523 147 0.28 20,918 33,505 10,800 0.32 34,028 10,947 0.32 1.63 Shinyanga Urban 0 . . - 380 385 264 0.69 385 264 0.69 1.01 Kishapu 19,267 32,748 10,563 0.32 32,748 10,563 0.32 1.70 Total 561 637 172 0.27 151,840 198,753 101,423 4.45 199,390 101,595 0.51 1.31 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 - - Maswa 0 . . - 0 0 - - Shinyanga Rural 102 41 20 0.49 41 20 0.49 0.40 Kahama 5,406 5,413 5,241 - 5,413 5,241 0.00 1.00 Bukombe 358 109 123 1.13 109 123 1.13 0.30 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 - - Kishapu 82 66 8 0.12 66 8 0.12 0.81 Total 0 0 0 5,948 5,630 5,392 0.96 5,630 5,392 0.96 0.95 Average Planted Area Per household Average Planted Area Per household 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 182 PERMANENT CROPS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 183 7.4 Total Area Planted with Coconut by District - Kahama District 7.5 Total Area Planted with Oranges by District - Kahama District District Area planted with Mango Total Area planted (ha) % of Total Area Planted hh with Mango Average Planted Area per Household District Area planted with Banana (Ha) Total Area planted (ha) % of Total Area Planted hh with Banana Average Planted Area per Household Shinyanga Rural 979 101,952 1.0 1,114 0.88 Shinyanga Rural 101,952 0.00 0 0.00 Bukombe 5,335 35,159 15.2 3,699 1.44 Meatu 35,159 0.00 0 0.00 Maswa 318 44,228 0.7 951 0.33 Maswa 44,228 0.00 0 0.00 Kahama 20,919 79,905 26.2 12,307 1.70 Bukombe 526.0 79,905 0.66 1,553 0.34 Meatu 84 64,833 0.1 47 1.79 Shinyanga Urban 19.0 64,833 0.03 124 0.15 Bariadi 0 31,193 0.0 0 0.00 Kahama 3,197 31,193 10.25 1,689 1.89 Shinyanga Urban 268 7,505 3.6 464 0.58 Bariadi 7,505 0.00 0 0.00 Kishapu 164 35,494 0.5 243 0.67 Kishapu 21.0 35,494 0.1 70 0.30 Total 28,067.0 400,270 100.0 18,825 0.45 Total 3,763.0 364,775 10.94 3,436 1.10 7.6 Total Area Planted with Banana by District - Kahama District District Area planted with banana(Ha) Total Area planted (ha) % of Total Area Planted hh with bananas Average Planted Area per Household Shinyanga Rural 101,952 0.00 0.00 Maswa 35,159 0.00 217 0.00 Bariadi 30.0 44,228 0.07 528 0.06 Meatu 8.0 79,905 0.01 83 0.10 Shinyanga Urban 85.0 64,833 0.13 314 0.27 Bukombe 351.0 31,193 1.13 597 0.59 Kahama 5,635.0 7,505 75.09 2,932 1.92 Kishapu 167.0 35,494 0.47 406 0.41 Total 6,276.0 364,775 1.72 5,077 1.24 MANGO BANANA PAWPAW Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 184 AGROPROCESSING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 185 Number % Number % Number % Bariadi 66,411 86 11,160 14 77,572 100 Maswa 32,508 75 10,744 25 43,252 100 Shinyanga Rural 42,740 94 2,523 6 45,263 100 Kahama 79,018 97 2,199 3 81,217 100 Bukombe 49,297 93 3,943 7 53,240 100 Meatu 26,461 84 5,031 16 31,492 100 Shinyanga Urban 4,251 42 5,947 58 10,198 100 Kishapu 28,145 79 7,479 21 35,624 100 Total 328,832 87 49,026 13 377,857 100 On Farm by Hand On Farm by Machine y Neighbour Machine By Farmers Association y operative Union By Trader g Scale Farm Other Total Bariadi 6,158 4,444 49,488 0 0 6,322 - 0 81,783 Maswa 1,879 758 24,907 - 0 4,856 0 108 36,364 Shinyanga Rural 6,776 705 18,057 - 204 16,596 - 401 43,887 Kahama 22,398 945 55,392 0 139 - 0 144 6,162 Bukombe 3,332 836 31,595 0 0 13,534 0 - 5,133 Meatu 8,901 406 14,421 166 249 83 1988 247 43,919 Shinyanga Urban 936 56 2,744 0 0 485 31 0 18,537 Kishapu 1,209 1,922 24,634 0 0 141 82 157 Total 51,589 10,071 221,237 166 593 42,017 2,101 1,057 235,784 % 21.88 4.27 93.83 0.07 0.25 17.82 0.89 0.45 139.46 District 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year Method of Processing 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year District Households That Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 186 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other Total Bambaranut 1,499 0 0 0 0 0 0 31 1,530 Beans 7,823 0 1,282 0 0 0 0 128 9,234 Bulrush Millet 0 0 2,324 0 0 297 31 0 2,652 Cabbage 15 0 285 0 0 0 0 0 301 Cassava 5,433 0 3,964 0 0 0 0 260 9,657 Chick Peas 3,630 0 950 0 0 404 0 1,587 6,571 Cotton 1,392 0 1,366 2,368 1,882 201 6,799 0 14,008 Cowpeas 5,275 0 133 0 0 0 0 142 5,549 Finger Millet 0 0 83 0 0 0 0 0 83 Green Gram 1,792 0 0 0 0 0 0 0 1,792 Groundnut 73,472 157 2,945 0 82 1,081 83 7,675 85,495 Irish Potatoes 242 0 0 0 0 0 0 0 242 Maize 42,439 9,558 206,256 83 343 41,995 82 227 300,983 Mango 139 0 0 0 0 0 0 0 139 Paddy 28,780 2,592 69,238 119 102 14,671 0 174 115,678 Pigeon Peas 812 0 178 0 0 0 0 179 1,169 Pyrethrum 0 0 142 0 0 0 0 0 142 Simsim 81 0 0 0 0 99 0 0 180 Sorghum 7,636 1,149 33,510 0 179 2,211 0 0 44,686 Sunflower 141 0 0 0 0 200 99 0 441 Sweet Potatoes 15,592 0 83 83 0 0 0 2,509 18,267 Tobacco 0 0 1,631 0 0 0 0 0 1,631 Tomatoes 81 0 0 0 0 0 0 0 81 Yams 32 0 0 0 0 0 0 0 32 Crop Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 187 Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Maize 298,104 790 635 690 764 300,983 Paddy 111,647 295 2,458 857 420 115,678 Sorghum 44,428 0 0 83 175 44,686 Bulrush Millet 2,623 0 0 29 0 2,652 Finger Millet 83 0 0 0 0 83 Cassava 9,445 0 212 0 0 9,657 Sweet Potatoes 17,915 0 238 114 0 18,267 Irish Potatoes 242 0 0 0 0 242 Yams 32 0 0 0 0 32 Beans 8,971 119 143 0 0 9,234 Cowpeas 5,468 0 82 0 0 5,549 Green Gram 1,792 0 0 0 0 1,792 Pigeon Peas 991 0 178 0 0 1,169 Chick Peas 6,431 0 141 0 0 6,571 Bambaranut 1,530 0 0 0 0 1,530 Sunflower 100 0 341 0 0 441 Simsim 81 0 99 0 0 180 Groundnut 83,378 303 1,139 60 614 85,495 Cotton 2,529 83 9,948 287 1,161 14,008 Tobacco 1,520 0 110 0 0 1,631 Pyrethrum 142 0 0 0 0 142 Mango 139 0 0 0 0 139 Cabbage 301 0 0 0 0 301 Tomatoes 81 0 0 0 0 81 Total 597,975 1,590 15,724 2,121 3,135 620,545 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Product Use Crop Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 188 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 4,490 2,534 422 405 98 451 1,019 324 291,240 300,983 Paddy 7,635 7,019 141 282 250 209 1,001 1,391 97,750 115,678 Sorghum 722 0 54 187 95 81 329 0 43,218 44,686 Bulrush Millet 78 0 0 29 0 0 0 0 2,545 2,652 Finger Millet 0 0 0 0 0 0 0 0 83 83 Cassava 883 455 0 0 0 0 119 264 7,935 9,657 Sweet Potatoes 0 0 54 0 0 0 101 0 18,112 18,267 Irish Potatoes 0 0 0 0 0 0 0 0 242 242 Yams 0 0 0 0 0 0 0 0 32 32 Beans 304 119 0 0 0 0 0 0 8,810 9,234 Cowpeas 0 0 0 143 0 0 0 0 5,406 5,549 Green Gram 102 0 0 0 0 0 0 0 1,690 1,792 Pigeon Peas 0 178 0 0 0 0 0 0 991 1,169 Chick Peas 102 811 101 0 0 0 0 0 5,558 6,571 Bambaranut 0 285 0 0 0 0 0 0 1,245 1,530 Sunflower 0 0 0 101 0 0 0 0 340 441 Simsim 0 0 0 0 0 0 0 0 180 180 Groundnut 4,506 1,814 382 217 101 182 849 708 76,736 85,495 Cotton 95 187 0 7,002 4,016 0 0 235 2,473 14,008 Tobacco 110 0 0 0 0 0 0 0 1,520 1,631 Pyrethrum 142 0 0 0 0 0 0 0 0 142 Mango 0 0 0 0 0 0 0 0 139 139 Cabbage 0 0 0 0 0 0 0 0 301 301 Tomatoes 0 0 0 0 0 0 0 0 81 81 Total 19,169 13,403 1,155 8,366 4,558 923 3,418 2,922 566,630 620,545 Flour / Meal Grain Oil Juice Pulp Other Total Bariadi 63,408 2,118 351 0 0 534 66,411 Maswa 27,055 4,641 500 0 0 311 32,508 Shinyanga Rural 31,990 9,751 505 0 91 402 42,740 Kahama 3,865 74,837 86 0 0 230 79,018 Bukombe 41,670 7,627 0 0 0 0 49,297 Meatu 21,313 1,752 1,181 81 83 2,050 26,461 Shinyanga Urban 3,317 840 63 0 0 32 4,251 Kishapu 25,404 2,338 242 80 0 81 28,145 Total 218,022 103,903 2,929 161 175 3,641 328,832 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Crop Where Sold 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Kahama Region District Main Product Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 189 Household /Human C ti Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Bariadi 66,232 179 0 0 0 66,411 Maswa 32,090 108 310 0 0 32,508 Shinyanga Rural 41,945 102 298 193 201 42,740 Kahama 77,779 270 284 287 397 79,018 Bukombe 48,700 239 119 0 239 49,297 Meatu 24,101 0 1,309 165 886 26,461 Shinyanga Urban 4,129 0 31 92 0 4,251 Kishapu 27,982 0 0 81 82 28,145 Total 322,958 898 2,352 819 1,806 328,832 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Bariadi 529 174 176 0 0 179 0 0 65,353 66,411 Maswa 634 650 217 108 0 108 108 0 30,682 32,508 Shinyanga Rural 495 203 0 203 0 0 102 102 41,635 42,740 Kahama 2,999 1,344 0 144 98 0 571 269 73,594 79,018 Bukombe 914 953 0 0 0 0 239 0 47,191 49,297 Meatu 0 0 138 1,474 994 0 0 0 23,855 26,461 Shinyanga Urban 63 129 0 29 0 0 0 64 3,966 4,251 Kishapu 239 0 0 159 0 163 0 160 27,423 28,145 Total 5,874 3,453 531 2,118 1,091 451 1,020 594 313,699 328,832 Bran Cake Husk Juice Fiber Pulp Oil Shell No by-product Other Total Bariadi 2,813 178 10,625 178 179 0 0 4,035 48,403 0 66,411 Maswa 9,549 203 6,795 108 0 0 95 1,483 14,073 202 32,508 Shinyanga Rural 2,615 399 15,973 0 102 202 102 2,001 21,345 0 42,740 Kahama 72,791 141 2,691 0 0 144 0 733 2,408 110 79,018 Bukombe 9,917 119 7,238 0 0 0 0 1,061 30,961 0 49,297 Meatu 712 256 82 0 81 162 82 490 24,595 0 26,461 Shinyanga Urban 2,167 0 841 0 0 0 32 95 1,117 0 4,251 Kishapu 1,178 82 2,653 245 0 81 163 2,275 21,468 0 28,145 Total 101,742 1,379 46,899 531 362 590 473 12,174 164,368 313 328,832 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Kahama Region District Product Use 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Kahama Region 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Kahama Region District District Where Sold By Product Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 190 MARKETING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 191 Number % Number % Bariadi 51,136 65.9 26,436 34.1 77,572 Maswa 34,296 79.3 8,956 20.7 43,252 Shinyanga Rural 19,829 43.8 25,434 56.2 45,263 Kahama 47,924 59.0 33,293 41.0 81,217 Bukombe 28,751 54.0 24,489 46.0 53,240 Meatu 18,658 59.2 12,833 40.8 31,492 Shinyanga Urban 770 7.6 9,428 92.4 10,198 Kishapu 17,952 50.4 17,671 49.6 35,624 Total 219,317 58.0 158,540 42.0 377,857 District Open Market Price Too Low No Transport Transport Cost Too High Market too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Lack of Market Information Other Total Bariadi 3,795 358 174 537 0 177 0 0 0 - 5,041 Maswa 757 0 0 0 0 0 0 0 0 - 757 Shinyanga Rural 6,143 204 99 504 0 0 0 0 0 - 6,950 Kahama 11,651 826 1,264 1,394 142 98 0 0 286 408 16,068 Bukombe 11,778 239 1,434 597 0 0 113 239 239 352 14,991 Meatu 5,824 164 47 570 0 393 749 0 329 823 8,899 Shinyanga Urban 212 30 0 0 0 0 0 0 0 - 242 Kishapu 244 82 81 0 0 0 0 82 0 321 809 Total 40,404 1,903 3,099 3,602 142 667 862 321 854 1,903 53,757 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bariadi 884 27,922 169 342 534 - 2,960 43,552 76,363 Maswa 433 8,829 - - 433 - 2,968 30,371 43,035 Shinyanga Rural 300 23,259 99 303 - 102 1,194 19,200 44,457 Kahama 2,241 34,141 143 416 254 421 573 35,351 73,539 Bukombe 2,183 25,103 - 119 119 238 1,672 22,974 52,409 Meatu 924 13,118 - - - - 945 15,077 30,065 Shinyanga Urban 229 7,726 32 245 - 62 493 1,126 9,914 Kishapu 732 20,347 - - 163 81 1,675 12,229 35,227 Total 7,925 160,445 442 1,427 1,503 905 12,481 179,880 365,008 10.2 Number of Households who Reported Marketing Problems by District during 2002/03 Agricultural Year 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Kahama Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 192 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 193 Number of Household % Number of Household % Bariadi 1,569 2 76,003 98 77,572 Maswa 1,613 4 41,639 96 43,252 Shinyanga Rural 1,522 3 43,741 97 45,263 Kahama 1,559 2 79,658 98 81,217 Bukombe 468 1 52,772 99 53,240 Meatu 81 0 31,411 100 31,492 Shinyanga Urban 489 5 9,709 95 10,198 Kishapu 1,277 4 34,347 96 35,624 Total 8,578 2 369,279 98 377,857 District Irrigatable Area (ha) Irrigated Land (ha) % Bariadi 331 302 91 Maswa 1,615 1,505 93 Shinyanga Rural 886 589 67 Kahama 411 291 71 Bukombe 308 299 97 Meatu 131 66 50 Shinyanga Urban 186 157 85 Kishapu 1,044 646 Total 4,912 3,856 78 River Dam Well Borehole Canal Pipe water Total Bariadi 1,217 0 352 0 0 0 1,569 Maswa 101 108 0 0 1,404 0 1,613 Shinyanga Rural 713 102 401 0 306 0 1,522 Kahama 0 1,135 425 0 0 0 1,559 Bukombe 0 229 119 0 119 0 468 Meatu 81 0 0 0 0 0 81 Shinyanga Urban 193 0 188 23 0 85 489 Kishapu 1,195 82 0 0 0 0 1,277 Total 3,501 1,655 1,485 23 1,829 85 8,578 % 41 19 17 0 21 1 100 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.1 IRRIGATION: Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District District Households Practicing Irrigation Households not Practicing Irrigation Total Number of households 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 194 Gravity Hand Bucket Hand Pump Motor Pump Other Total Bariadi 179 1,212 178 0 0 1,569 Maswa 1,404 210 0 0 0 1,613 Shinyanga Rural 510 910 0 0 102 1,522 Kahama 143 1,416 0 0 0 1,559 Bukombe 348 119 0 0 0 468 Meatu 81 0 0 0 0 81 Shinyanga Urban 32 369 32 23 32 489 Kishapu 730 547 0 0 0 1,277 Total 3,427 4,783 211 23 134 8,578 % 39.9 55.8 2.5 0.3 1.6 100 Flood Sprinkler Water Hose Bucket / Watering Can Total Bariadi 0 0 178 1,391 1,569 Maswa 1,404 0 0 210 1,613 Shinyanga Rural 612 0 0 910 1,522 Kahama 428 0 0 1,131 1,559 Bukombe 348 0 0 119 468 Meatu 81 0 0 0 81 Shinyanga Urban 32 63 23 371 489 Kishapu 730 0 0 547 1,277 Total 3,635 63 202 4,678 8,578 % 42 1 2 55 100 District Method of Obtaining Water 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year District Method of field Application 11.4 IRRIGATION: Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 195 Number % Number % Bariadi 3,675 5 73,897 95 77,572 Maswa 1,500 3 41,752 97 43,252 Shinyanga Rural 4,022 9 41,241 91 45,263 Kahama 3,194 4 78,023 96 81,217 Bukombe 358 1 52,882 99 53,240 Meatu 577 2 30,915 98 31,492 Shinyanga Urban 754 7 9,444 93 10,198 Kishapu 1,119 3 34,504 97 35,624 Total 15,199 4 362,658 96 377,857 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Bariadi . 7,159 . . 18,685 4,871 887 . 31,603 Maswa . 11,757 325 . 108 759 . . 12,949 Shinyanga Rural . 102,581 1,327 . . 102 705 . 104,714 Kahama 131 3,155 . 4,274 . 14,160 1,815 . 23,535 Bukombe . 478 . 358 . . . . 836 Meatu . 8,858 . 83 333 826 . . 10,100 Shinyanga Urban . 4,224 . . . 152 124 . 4,500 Kishapu . 1,025 . . . 2,693 5,112 79 8,908 Total 131 139,237 1,652 4,716 19,127 23,561 8,643 79 197,146 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year District Type of Erosion Control 11.6 EROSION CONTROL: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District District Presence of Erosion Control/Water Harvesting Facilities Have facility Does Not Have Facility Total Number of households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 196 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tanga 197 District Number % Number % Number % Bariadi 535 1 77,036 99 77,572 100 Maswa 324 1 42,928 99 43,252 100 Shinyanga Rural 402 1 44,861 99 45,263 100 Kahama 8,437 10 72,779 90 81,217 100 Bukombe 597 1 52,643 99 53,240 100 Meatu 0 0 31,492 100 31,492 100 Shinyanga Urban 119 1 10,080 99 10,198 100 Kishapu 315 1 35,308 99 35,624 100 Total 10,730 3 367,127 97 377,857 100 District Number % Number % Number % Bariadi 12,383 16 65,188 84 77,572 100 Maswa 9,126 21 34,126 79 43,252 100 Shinyanga Rural 16,679 37 28,584 63 45,263 100 Kahama 27,407 34 53,931 66 81,337 100 Bukombe 9,019 17 44,221 83 53,240 100 Meatu 4,408 14 27,084 86 31,492 100 Shinyanga Urban 4,201 41 6,029 59 10,230 100 Kishapu 5,189 15 30,596 85 35,785 100 Total 88,413 23 289,758 77 378,171 100 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Chemical Fertilizers Number of Agricultural Households Using Chemical Fertilizers Total Number of Agricultural Households NOT Using Farm Yard Manure Number of Agricultural Households Using Farm Yard Manure 198 District Number % Number % Number % Bariadi 1,937 2 75,634 98 77,572 100 Maswa 1,056 2 42,196 98 43,252 100 Shinyanga Rural 862 2 44,401 98 45,263 100 Kahama 6,134 8 75,083 92 81,217 100 Bukombe 2,270 4 50,970 96 53,240 100 Meatu 83 0 31,409 100 31,492 100 Shinyanga Urban 514 5 9,652 95 10,166 100 Kishapu 1,460 4 34,084 96 35,544 100 Total 14,316 4 363,429 96 377,746 100 District Number % Number % Number % Bariadi 29,297 38 48,274 62 77,572 100 Maswa 5,212 12 38,040 88 43,252 100 Shinyanga Rural 2,216 5 43,047 95 45,263 100 Kahama 17,551 22 63,666 78 81,217 100 Bukombe 12,399 23 40,841 77 53,240 100 Meatu 8,754 28 22,737 72 31,492 100 Shinyanga Urban 408 4 9,791 96 10,198 100 Kishapu 5,196 15 30,427 85 35,624 100 Total 81,034 21 296,824 79 377,857 100 Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Pesticides/Fungicides Number of Agricultural Households Using Pesticides/Fungicides Total Number of Agricultural Households NOT Using COMPOST Manure Number of Agricultural Households Using COMPOST Manure 199 District Number % Number % Number % Bariadi 0 0 77,572 100 77,572 100 Maswa 325 1 42,927 99 43,252 100 Shinyanga Rural 0 0 45,263 100 45,263 100 Kahama 286 0 80,810 100 81,097 100 Bukombe 119 0 53,121 100 53,240 100 Meatu 81 0 31,410 100 31,492 100 Shinyanga Urban 0 0 10,198 100 10,198 100 Kishapu 376 1 35,247 99 35,624 100 Total 1,188 0 376,549 100 377,737 100 District Number % Number % Number % Bariadi 34,676 45 42,896 55 77,572 100 Maswa 21,630 50 21,622 50 43,252 100 Shinyanga Rural 4,475 10 40,788 90 45,263 100 Kahama 18,491 23 62,726 77 81,217 100 Bukombe 10,723 20 42,517 80 53,240 100 Meatu 11,043 35 20,449 65 31,492 100 Shinyanga Urban 1,182 12 9,017 88 10,198 100 Kishapu 16,184 46 19,358 54 35,542 100 Total 118,404 31 259,372 69 377,776 100 Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Herbicides Number of Agricultural Households Using Herbicides Total Number of Agricultural Households NOT Using Improved Seeds Number of Agricultural Households Using Improved Seeds 200 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 535 1 0 0 77,036 99 77,572 100 Maswa 108 0 0 0 216 1 0 0 42,928 99 43,252 100 Shinyanga Rural 0 0 0 0 302 1 100 0 44,861 99 45,263 100 Kahama 6,222 8 0 0 2,215 3 0 0 72,779 90 81,217 100 Bukombe 0 0 119 0 478 1 0 0 51,264 99 51,862 100 Meatu 0 0 0 0 0 0 0 0 31,077 100 31,077 100 Shinyanga Urban 0 0 0 0 119 1 0 0 10,080 99 10,198 100 Kishapu 0 0 0 0 235 1 80 0 35,308 99 35,624 100 Total 6,330 2 119 0 4,100 1 181 0 365,334 97 376,064 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 179 0 177 0 0 0 0 0 Maswa 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga Rural 0 0 0 0 200 0 102 0 0 0 0 0 Kahama 417 1 230 0 0 0 0 0 144 0 0 0 Bukombe 119 0 239 0 0 0 0 0 0 0 0 0 Meatu 0 0 0 0 0 0 0 0 0 0 82 0 Shinyanga Urban 30 0 94 1 62 1 157 2 0 0 0 0 Kishapu 0 0 81 0 0 0 0 0 0 0 0 0 Total 567 0 643 0 441 0 436 0 144 0 82 0 District Number % Number % Number % Number % Number % Bariadi 7,336 9 4,692 6 0 0 65,188 84 77,572 100 Maswa 5,798 13 3,005 7 323 1 34,126 79 43,252 100 Shinyanga Rural 10,568 23 5,202 11 606 1 28,584 63 45,263 100 Kahama 16,708 21 8,867 11 1,041 1 53,931 66 81,337 100 Bukombe 6,287 12 2,374 5 0 0 42,842 83 51,862 100 Meatu 2,168 7 2,074 7 83 0 26,836 86 31,243 100 Shinyanga Urban 2,455 24 1,247 12 157 2 6,029 59 10,230 100 Kishapu 3,019 8 2,089 6 0 0 30,596 85 35,785 100 Total 54,339 14 29,550 8 2,211 1 288,132 77 376,544 100 Cont…..Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Locally Produced by Household Total Not applicable Other Neighbour Local Market / Trade Store Co-operative Total Not applicable Neighbour Local Market / Trade Store Local Farmers Group Co-operative Large Scale Farm Crop Buyers Development Project Secondary Market 201 District Number % Number % Number % Number % Number % Bariadi 0 0 1,224 2 714 1 75,634 98 77,572 100 Maswa 0 0 839 2 217 1 42,196 98 43,252 100 Shinyanga Rural 0 0 679 2 183 0 44,401 98 45,263 100 Kahama 0 0 4,789 6 1,345 2 75,083 92 81,217 100 Bukombe 0 0 2,151 4 119 0 49,592 96 51,862 100 Meatu 0 0 83 0 0 0 30,994 100 31,077 100 Shinyanga Urban 0 0 115 1 400 4 9,652 95 10,166 100 Kishapu 81 0 483 1 895 3 34,084 96 35,544 100 Total 81 0 10,363 3 3,872 1 361,636 96 375,953 100 District Number % Number % Number % Number % Number % Bariadi 2,643 3 0 0 25,801 33 0 0 500 1 Maswa 2,340 5 108 0 2,113 5 542 1 108 0 Shinyanga Rural 204 0 595 1 1,112 2 0 0 306 1 Kahama 8,197 10 286 0 7,316 9 144 0 751 1 Bukombe 1,549 3 473 1 9,067 17 358 1 713 1 Meatu 5,827 19 537 2 1,431 5 629 2 330 1 Shinyanga Urban 32 0 0 0 343 3 0 0 0 0 Kishapu 2,368 7 162 0 1,612 5 0 0 973 3 Total 23,160 6 2,161 1 48,795 13 1,673 0 3,682 1 Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Co-operative Total Not applicable Neighbour Locally Produced by Household Local Market / Trade Store Crop Buyers Secondary Market Local Market / Trade Store Local Farmers Group 202 District Number % Number % Number % Number % Number % Bariadi 175 0 179 0 0 0 48,274 62 77,572 100 Maswa 0 0 0 0 0 0 38,040 88 43,252 100 Shinyanga Rural 0 0 0 0 0 0 43,047 95 45,263 100 Kahama 0 0 857 1 0 0 63,666 78 81,217 100 Bukombe 119 0 0 0 119 0 39,463 76 51,862 100 Meatu 0 0 0 0 0 0 22,487 72 31,242 100 Shinyanga Urban 0 0 32 0 0 0 9,791 96 10,198 100 Kishapu 0 0 81 0 0 0 30,427 85 35,624 100 Total 294 0 1,149 0 119 0 295,195 78 376,229 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 0 0 77,572 100 77,572 100 Maswa 216 1 0 0 108 0 0 0 42,927 99 43,252 100 Shinyanga Rural 0 0 0 0 0 0 0 0 45,263 100 45,263 100 Kahama 144 0 143 0 0 0 0 0 80,810 100 81,097 100 Bukombe 0 0 0 0 0 0 119 0 51,742 100 51,862 100 Meatu 81 0 0 0 0 0 0 0 30,995 100 31,077 100 Shinyanga Urban 0 0 0 0 0 0 0 0 10,198 100 10,198 100 Kishapu 215 1 162 0 0 0 0 0 35,247 99 35,624 100 Total 656 0 305 0 108 0 119 0 374,756 100 375,944 100 Cont…..Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Co-operative Total Not applicable Other Neighbour Locally Produced by Household Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Not applicable Locally Produced by Household Crop Buyers Local Market / Trade Store 203 District Number % Number % Number % Number % Number % Bariadi 4,532 6 0 0 12,022 15 0 0 1,229 2 Maswa 11,643 27 968 2 3,544 8 1,285 3 203 0 Shinyanga Rural 101 0 1,289 3 2,280 5 0 0 703 2 Kahama 10,657 13 0 0 6,379 8 0 0 0 0 Bukombe 4,649 9 1,553 3 2,613 5 0 0 119 0 Meatu 8,069 26 402 1 1,481 5 495 2 0 0 Shinyanga Urban 32 0 0 0 1,094 11 0 0 0 0 Kishapu 8,712 25 568 2 2,730 8 163 0 80 0 Total 48,394 13 4,779 1 32,143 9 1,943 1 2,335 1 District Number % Number % Number % Number % Number % Bariadi 16,383 21 179 0 332 0 42,896 55 77,572 100 Maswa 3,554 8 108 0 325 1 21,622 50 43,252 100 Shinyanga Rural 102 0 0 0 0 0 40,788 90 45,263 100 Kahama 644 1 123 0 688 1 62,726 77 81,217 100 Bukombe 1,191 2 358 1 239 0 41,139 79 51,862 100 Meatu 415 1 81 0 101 0 20,199 65 31,242 100 Shinyanga Urban 0 0 55 1 0 0 9,017 88 10,198 100 Kishapu 3,455 10 237 1 240 1 19,358 54 35,542 100 Total 25,743 7 1,142 0 1,925 1 257,744 69 376,147 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 178 33 357 67 535 100 Maswa 216 67 0 0 108 33 0 0 0 0 324 100 Shinyanga Rural 0 0 0 0 0 0 201 50 201 50 402 100 Kahama 3,744 44 2,251 27 1,305 15 575 7 563 7 8,437 100 Bukombe 119 20 0 0 358 60 119 20 0 0 597 100 Shinyanga Urban 0 0 23 20 31 26 64 54 0 0 119 100 Kishapu 79 25 0 0 156 50 80 25 0 0 315 100 Total 4,158 39 2,274 21 1,959 18 1,218 11 1,121 10 10,730 100 Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Cont…..Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Crop Buyers Locally Produced by Neighbour Not applicable Development Project Secondary Market Local Market / Trade Store Local Farmers Group Co-operative 204 District Number % Number % Number % Number % Number % Number % Bariadi 11,713 95 493 4 177 1 0 0 0 0 12,383 100 Maswa 8,390 92 420 5 317 3 0 0 0 0 9,126 100 Shinyanga Rural 15,177 91 600 4 101 1 702 4 99 1 16,679 100 Kahama 23,571 86 2,618 10 1,217 4 0 0 0 0 27,407 100 Bukombe 7,235 80 1,187 13 478 5 119 1 0 0 9,019 100 Meatu 3,744 85 414 9 250 6 0 0 0 0 4,408 100 Shinyanga Urban 3,773 90 352 8 45 1 31 1 0 0 4,201 100 Kishapu 4,394 85 714 14 81 2 0 0 0 0 5,189 100 Total 77,998 88 6,798 8 2,664 3 853 1 99 0 88,413 100 District Number % Number % Number % Bariadi 1,760 91 177 9 1,937 100 Maswa 947 90 108 10 1,056 100 Shinyanga Rural 862 100 0 0 862 100 Kahama 5,326 87 808 13 6,134 100 Bukombe 2,151 95 119 5 2,270 100 Meatu 83 100 0 0 83 100 Shinyanga Urban 514 100 0 0 514 100 Kishapu 1,460 100 0 0 1,460 100 Total 13,104 92 1,212 8 14,316 100 District Number % Number % Number % Number % Number % Number % Bariadi 5,402 18 4,938 17 7,197 25 3,709 13 8,051 27 29,297 100 Maswa 1,460 28 951 18 2,483 48 216 4 101 2 5,212 100 Shinyanga Rural 498 22 402 18 202 9 303 14 811 37 2,216 100 Kahama 4,978 28 4,088 23 3,535 20 2,198 13 2,752 16 17,551 100 Bukombe 1,909 15 2,504 20 6,434 52 956 8 596 5 12,399 100 Meatu 2,237 26 2,643 30 2,993 34 414 5 467 5 8,754 100 Shinyanga Urban 32 8 32 8 89 22 222 54 32 8 408 100 Kishapu 1,833 35 567 11 2,147 41 489 9 161 3 5,196 100 Total 18,349 23 16,126 20 25,080 31 8,507 10 12,972 16 81,034 100 Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Between 10 and 20 km 20 km and Above Total Less than 1 km Between 1 and 3 km Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 205 District Number % Number % Number % Number % Number % Number % Maswa 216 67 0 0 108 33 0 0 0 0 325 100 Kahama 144 50 143 50 0 0 0 0 0 0 286 100 Bukombe 0 0 0 0 0 0 0 0 119 100 119 100 Meatu 0 0 81 100 0 0 0 0 0 0 81 100 Kishapu 148 39 67 18 81 21 81 21 0 0 376 100 Total 508 43 291 24 189 16 81 7 119 10 1,188 100 District Number % Number % Number % Number % Number % Number % Bariadi 12,902 37 8,536 25 5,647 16 3,530 10 4,062 12 34,676 100 Maswa 6,488 30 5,877 27 7,651 35 758 4 857 4 21,630 100 Shinyanga Rural 1,293 29 682 15 906 20 594 13 1,002 22 4,475 100 Kahama 6,661 36 5,406 29 4,439 24 1,000 5 985 5 18,491 100 Bukombe 3,098 29 2,744 26 3,807 36 717 7 357 3 10,723 100 Meatu 2,612 24 2,865 26 3,945 36 467 4 1,154 10 11,043 100 Shinyanga Urban 63 5 247 21 491 42 285 24 95 8 1,182 100 Kishapu 8,065 50 2,362 15 4,145 26 1,124 7 489 3 16,184 100 Total 41,182 35 28,718 24 31,030 26 8,474 7 9,000 8 118,404 100 District Number % Number % Number % Number % Number % Bariadi 357 67 178 33 0 0 0 0 535 100 Maswa 0 0 324 100 0 0 0 0 324 100 Shinyanga Rural 0 0 302 75 100 25 0 0 402 100 Kahama 7,498 89 431 5 243 3 266 3 8,437 100 Bukombe 358 60 119 20 119 20 0 0 597 100 Shinyanga Urban 64 54 55 46 0 0 0 0 119 100 Kishapu 315 100 0 0 0 0 0 0 315 100 Total 8,592 80 1,409 13 463 4 266 2 10,730 100 Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year 20 km and Above Total Sale of Farm Products Other Income generating Bank Loan Other Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 206 District Number % Number % Number % Number % Bariadi 8,568 69 1,713 14 179 1 0 0 Maswa 6,883 75 526 6 432 5 0 0 Shinyanga Rural 12,667 76 1,195 7 403 2 0 0 Kahama 24,123 88 1,043 4 410 1 715 3 Bukombe 6,756 75 119 1 956 11 0 0 Meatu 2,684 61 379 9 83 2 0 0 Shinyanga Urban 3,710 88 277 7 0 0 31 1 Kishapu 4,702 91 324 6 0 0 0 0 Total 70,093 79 5,578 6 2,463 3 745 1 District Number % Number % Number % Bariadi 0 0 1,923 16 12,383 100 Maswa 0 0 1,285 14 9,126 100 Shinyanga Rural 0 0 2,414 14 16,679 100 Kahama 0 0 1,116 4 27,407 100 Bukombe 0 0 1,189 13 9,019 100 Meatu 62 1 1,199 27 4,408 100 Shinyanga Urban 0 0 183 4 4,201 100 Kishapu 0 0 163 3 5,189 100 Total 62 0 9,471 11 88,413 100 District Number % Number % Number % Number % Number % Bariadi 1,760 91 0 0 177 9 0 0 1,937 100 Maswa 839 79 0 0 0 0 217 21 1,056 100 Shinyanga Rural 559 65 0 0 0 0 303 35 862 100 Kahama 5,406 88 630 10 0 0 98 2 6,134 100 Bukombe 1,553 68 0 0 239 11 478 21 2,270 100 Meatu 83 100 0 0 0 0 0 0 83 100 Shinyanga Urban 483 94 0 0 0 0 31 6 514 100 Kishapu 1,297 89 81 6 0 0 81 6 1,460 100 Total 11,981 84 711 5 416 3 1,208 8 14,316 100 Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year Cont…..Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year Other Total Produced on form Other Total Sale of Farm Products Other Income generating Remittances Sale of Farm Products Other Income generating Remittances Bank Loan 207 District Number % Number % Number % Number % Number % Bariadi 22,199 76 6,580 22 0 0 0 0 0 0 Maswa 4,492 86 620 12 99 2 0 0 0 0 Shinyanga Rural 1,610 73 504 23 0 0 0 0 0 0 Kahama 15,473 88 1,383 8 144 1 133 1 0 0 Bukombe 10,608 86 1,552 13 0 0 119 1 0 0 Meatu 4,698 54 2,962 34 0 0 83 1 81 1 Shinyanga Urban 408 100 0 0 0 0 0 0 0 0 Kishapu 3,931 76 1,183 23 82 2 0 0 0 0 Total 63,419 78 14,784 18 325 0 336 0 81 0 District Number % Number % Bariadi 519 2 29,297 100 Maswa 0 0 5,212 100 Shinyanga Rural 102 5 2,216 100 Kahama 418 2 17,551 100 Bukombe 119 1 12,399 100 Meatu 930 11 8,754 100 Shinyanga Urban 0 0 408 100 Kishapu 0 0 5,196 100 Total 2,089 3 81,034 100 District Number % Number % Number % Maswa 216 67 108 33 325 100 Kahama 286 100 0 0 286 100 Bukombe 119 100 0 0 119 100 Meatu 81 100 0 0 81 100 Kishapu 148 39 229 61 376 100 Total 851 72 337 28 1,188 100 Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year Cont…. Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year Total Other Total Sale of Farm Products Other Income generating Sale of Farm Products Other Income generating Remittances Bank Loan Produced on form 208 District Number % Number % Number % Number % Bariadi 25,918 75 7,535 22 163 0 179 1 Maswa 17,398 80 3,054 14 315 1 108 1 Shinyanga Rural 2,686 60 1,489 33 98 2 0 0 Kahama 15,249 82 2,965 16 144 1 133 1 Bukombe 9,171 86 955 9 0 0 119 1 Meatu 5,771 52 4,101 37 81 1 0 0 Shinyanga Urban 815 69 304 26 62 5 0 0 Kishapu 14,111 87 1,831 11 161 1 81 0 Total 91,120 77 22,235 19 1,023 1 620 1 District Number % Number % Number % Bariadi 0 0 881 3 34,676 100 Maswa 0 0 755 3 21,630 100 Shinyanga Rural 0 0 202 5 4,475 100 Kahama 0 0 0 0 18,491 100 Bukombe 0 0 478 4 10,723 100 Meatu 136 1 954 9 11,043 100 Shinyanga Urban 0 0 0 0 1,182 100 Kishapu 0 0 0 0 16,184 100 Total 136 0 3,270 3 118,404 100 District Number % Number % Number % Number % Bariadi 28,725 37 43,811 57 348 0 0 0 Maswa 10,123 24 25,565 60 541 1 107 0 Shinyanga Rural 12,233 27 29,590 66 408 1 0 0 Kahama 22,117 30 44,752 61 422 1 572 1 Bukombe 10,476 20 36,095 69 1,195 2 119 0 Meatu 15,510 49 14,287 45 417 1 81 0 Shinyanga Urban 492 5 8,600 85 110 1 0 0 Kishapu 13,901 39 17,800 50 428 1 163 0 Total 113,577 31 220,499 60 3,868 1 1,042 0 Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year Not Available Price Too High No Money to Buy Too Much Labour Required Bank Loan Produced on form Other Total Cont…..Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year Sale of Farm Products Other Income generating Remittances 209 District Number % Number % Number % Number % Number % Bariadi 1,934 3 1,335 2 0 0 884 1 77,036 100 Maswa 1,936 5 3,358 8 216 1 1,082 3 42,928 100 Shinyanga Rural 1,406 3 1,121 2 0 0 102 0 44,861 100 Kahama 1,253 2 2,527 3 0 0 1,136 2 72,779 100 Bukombe 1,772 3 2,746 5 119 0 119 0 52,643 100 Meatu 326 1 448 1 0 0 422 1 31,492 100 Shinyanga Urban 268 3 519 5 0 0 92 1 10,080 100 Kishapu 1,455 4 1,187 3 0 0 373 1 35,308 100 Total 10,350 3 13,242 4 336 0 4,212 1 367,127 100 District Number % Number % Number % Number % Bariadi 1,951 3 1,592 2 42,580 65 10,355 16 Maswa 11,433 34 8,284 24 7,745 23 3,332 10 Shinyanga Rural 7,467 26 4,244 15 12,137 42 602 2 Kahama 18,154 34 12,632 23 17,539 33 1,491 3 Bukombe 16,054 36 16,183 37 7,353 17 836 2 Meatu 1,686 6 3,464 13 15,262 56 2,309 9 Shinyanga Urban 867 14 2,063 34 2,262 38 297 5 Kishapu 1,853 6 5,152 17 17,636 58 3,491 11 Total 59,464 21 53,614 19 122,514 42 22,713 8 District Number % Number % Number % Number % Number % Bariadi 6,152 9 867 1 0 0 1,692 3 65,188 100 Maswa 1,080 3 325 1 0 0 1,927 6 34,126 100 Shinyanga Rural 1,115 4 1,111 4 0 0 1,909 7 28,584 100 Kahama 364 1 2,623 5 123 0 1,002 2 53,931 100 Bukombe 936 2 2,262 5 0 0 597 1 44,221 100 Meatu 1,402 5 834 3 0 0 2,127 8 27,084 100 Shinyanga Urban 182 3 265 4 0 0 93 2 6,029 100 Kishapu 724 2 1,222 4 82 0 436 1 30,596 100 Total 11,955 4 9,509 3 205 0 9,783 3 289,758 100 Cont…,Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Cont….Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Total Do not Know How to Use Input is of No Use Locally Produced by Other Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Other 210 District Number % Number % Number % Number % Bariadi 1,948 3 1,935 3 28,193 37 8,135 11 Maswa 4,429 10 3,090 7 13,354 32 2,382 6 Shinyanga Rural 4,757 11 2,222 5 13,967 31 2,015 5 Kahama 8,355 11 6,832 9 38,905 52 3,207 4 Bukombe 11,201 22 9,917 19 17,345 34 2,748 5 Meatu 1,788 6 4,219 13 7,802 25 1,229 4 Shinyanga Urban 895 9 2,998 31 2,068 21 188 2 Kishapu 2,929 9 5,015 15 12,956 38 5,801 17 Total 36,302 10 36,229 10 134,592 37 25,706 7 District Number % Number % Number % Number % Number % Bariadi 34,023 45 874 1 0 0 527 1 75,634 100 Maswa 16,371 39 757 2 108 0 1,704 4 42,196 100 Shinyanga Rural 19,711 44 714 2 201 0 814 2 44,401 100 Kahama 13,253 18 3,163 4 656 1 712 1 75,083 100 Bukombe 6,778 13 2,263 4 0 0 717 1 50,970 100 Meatu 12,235 39 2,066 7 167 1 1,903 6 31,409 100 Shinyanga Urban 2,752 29 415 4 0 0 335 3 9,652 100 Kishapu 6,302 18 645 2 81 0 355 1 34,084 100 Total 111,425 31 10,897 3 1,213 0 7,066 2 363,429 100 District Number % Number % Number % Number % Bariadi 3,199 7 35,092 73 1,064 2 0 0 Maswa 4,391 12 27,937 73 756 2 0 0 Shinyanga Rural 4,842 11 31,863 74 1,014 2 987 2 Kahama 7,706 12 46,014 72 414 1 143 0 Bukombe 2,348 6 31,347 77 1,194 3 119 0 Meatu 937 4 19,155 84 325 1 83 0 Shinyanga Urban 301 3 7,667 78 446 5 0 0 Kishapu 1,361 4 26,728 88 489 2 81 0 Total 25,086 8 225,803 76 5,703 2 1,414 0 Cont….Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Other Not Available Price Too High No Money to Buy Too Much Labour Required Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year 211 District Number % Number % Number % Number % Bariadi 3,369 7 4,668 10 882 2 48,274 100 Maswa 3,020 8 975 3 960 3 38,040 100 Shinyanga Rural 2,823 7 1,416 3 102 0 43,047 100 Kahama 3,049 5 5,622 9 718 1 63,666 100 Bukombe 1,413 3 4,300 11 119 0 40,841 100 Meatu 579 3 658 3 999 4 22,737 100 Shinyanga Urban 389 4 805 8 184 2 9,791 100 Kishapu 651 2 886 3 230 1 30,427 100 Total 15,292 5 19,330 7 4,195 1 296,824 100 District Number % Number % Number % Number % Bariadi 30,447 39 22,816 29 866 1 0 0 Maswa 6,135 14 26,942 63 640 1 0 0 Shinyanga Rural 7,114 16 29,258 65 1,322 3 694 2 Kahama 22,937 28 33,166 41 548 1 0 0 Bukombe 11,607 22 29,369 55 1,539 3 239 0 Meatu 9,013 29 14,900 47 327 1 0 0 Shinyanga Urban 432 4 7,325 72 446 4 0 0 Kishapu 5,798 16 23,957 68 870 2 0 0 Total 93,483 25 187,732 50 6,558 2 933 0 District Number % Number % Number % Number % Bariadi 17,649 23 5,268 7 527 1 77,572 100 Maswa 5,991 14 1,921 4 1,298 3 42,927 100 Shinyanga Rural 5,049 11 1,520 3 306 1 45,263 100 Kahama 10,395 13 13,620 17 144 0 80,810 100 Bukombe 6,189 12 4,058 8 119 0 53,121 100 Meatu 4,250 14 2,380 8 539 2 31,410 100 Shinyanga Urban 668 7 1,206 12 122 1 10,198 100 Kishapu 3,093 9 1,177 3 352 1 35,247 100 Total 53,284 14 31,151 8 3,408 1 376,549 100 Cont…..Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year Cont….Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Other Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 212 District Number % Number % Number % Number % Bariadi 3,014 7 36,859 86 894 2 357 1 Maswa 3,548 16 16,666 77 433 2 108 1 Shinyanga Rural 7,490 18 31,887 78 509 1 0 0 Kahama 7,597 12 48,247 77 548 1 286 0 Bukombe 3,902 9 35,050 82 1,195 3 119 0 Meatu 1,902 9 17,291 85 244 1 164 1 Shinyanga Urban 381 4 7,800 87 338 4 0 0 Kishapu 1,936 10 16,534 85 327 2 0 0 Total 29,770 11 210,334 81 4,488 2 1,035 0 District Number % Number % Number % Number % Number % Bariadi 357 1 1,061 2 0 0 353 1 42,896 100 Maswa 217 1 217 1 0 0 433 2 21,622 100 Shinyanga Rural 303 1 599 1 0 0 0 0 40,788 100 Kahama 677 1 3,823 6 256 0 1,293 2 62,726 100 Bukombe 1,175 3 836 2 0 0 239 1 42,517 100 Meatu 411 2 62 0 0 0 376 2 20,449 100 Shinyanga Urban 120 1 196 2 0 0 182 2 9,017 100 Kishapu 82 0 163 1 0 0 316 2 19,358 100 Total 3,342 1 6,957 3 256 0 3,191 1 259,372 100 District Number % Number % Number % Number % Bariadi 0 0 535 100 0 0 535 100 Maswa 324 100 0 0 0 0 324 100 Shinyanga Rural 0 0 301 75 101 25 402 100 Kahama 3,715 44 4,219 50 504 6 8,437 100 Bukombe 358 60 239 40 0 0 597 100 Shinyanga Urban 55 47 63 53 0 0 119 100 Kishapu 78 25 237 75 0 0 315 100 Total 4,531 42 5,595 52 604 6 10,730 100 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Cont…….Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Total Excellent Good Average Total Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Locally Produced by Other Not Available Price Too High No Money to Buy Too Much Labour Required 213 District Number % Number % Number % Number % Number % Number % Bariadi 2,950 24 9,433 76 0 0 0 0 0 0 12,383 100 Maswa 5,246 57 3,447 38 433 5 0 0 0 0 9,126 100 Shinyanga Rural 9,463 57 7,011 42 204 1 0 0 0 0 16,679 100 Kahama 9,231 34 16,806 61 1,228 4 0 0 142 1 27,407 100 Bukombe 4,418 49 4,482 50 119 1 0 0 0 0 9,019 100 Meatu 659 15 3,541 80 208 5 0 0 0 0 4,408 100 Shinyanga Urban 941 22 2,685 64 124 3 452 11 0 0 4,201 100 Kishapu 1,913 37 2,625 51 651 13 0 0 0 0 5,189 100 Total 34,822 39 50,030 57 2,967 3 452 1 142 0 88,413 100 District Number % Number % Number % Number % Number % Bariadi 177 9 1,583 82 177 9 0 0 1,937 100 Maswa 202 19 636 60 217 21 0 0 1,056 100 Shinyanga Rural 191 22 397 46 274 32 0 0 862 100 Kahama 524 9 4,033 66 1,577 26 0 0 6,134 100 Bukombe 717 32 1,195 53 239 11 119 5 2,270 100 Meatu 83 100 0 0 0 0 0 0 83 100 Shinyanga Urban 30 6 484 94 0 0 0 0 514 100 Kishapu 321 22 1,058 72 81 6 0 0 1,460 100 Total 2,245 16 9,387 66 2,565 18 119 1 14,316 100 District Number % Number % Number % Number % Number % Number % Bariadi 6,245 21 21,827 75 1,048 4 0 0 178 1 29,297 100 Maswa 1,162 22 3,301 63 749 14 0 0 0 0 5,212 100 Shinyanga Rural 610 28 1,505 68 102 5 0 0 0 0 2,216 100 Kahama 8,279 47 8,855 50 273 2 142 1 0 0 17,551 100 Bukombe 4,059 33 6,907 56 836 7 477 4 119 1 12,399 100 Meatu 1,233 14 5,885 67 1,390 16 247 3 0 0 8,754 100 Shinyanga Urban 129 32 247 61 32 8 0 0 0 0 408 100 Kishapu 1,035 20 3,255 63 617 12 223 4 67 1 5,196 100 Total 22,751 28 51,782 64 5,047 6 1,089 1 365 0 81,034 100 Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Does not Work Total Excellent Good Average Poor Does not Work Total Excellent Good Average Poor Total Excellent Good Average Poor 214 District Number % Number % Number % Number % Number % Maswa 108 33 108 33 108 33 0 0 325 100 Kahama 144 50 143 50 0 0 0 0 286 100 Bukombe 0 0 119 100 0 0 0 0 119 100 Meatu 0 0 81 100 0 0 0 0 81 100 Kishapu 67 18 148 39 81 21 81 21 376 100 Total 319 27 599 50 189 16 81 7 1,188 100 District Number % Number % Number % Number % Number % Number % Bariadi 7,262 21 25,676 74 1,397 4 341 1 0 0 34,676 100 Maswa 9,965 46 10,690 49 758 4 217 1 0 0 21,630 100 Shinyanga Rural 1,407 31 2,968 66 101 2 0 0 0 0 4,475 100 Kahama 6,838 37 11,249 61 404 2 0 0 0 0 18,491 100 Bukombe 4,413 41 4,997 47 478 4 836 8 0 0 10,723 100 Meatu 1,430 13 8,036 73 1,415 13 83 1 79 1 11,043 100 Shinyanga Urban 251 21 822 70 78 7 30 3 0 0 1,182 100 Kishapu 4,406 27 8,029 50 1,890 12 1,860 11 0 0 16,184 100 Total 35,971 30 72,468 61 6,519 6 3,366 3 79 0 118,404 100 District Number % Number % Number % Bariadi 10,564 14 67,008 86 77,572 100 Maswa 2,940 7 40,312 93 43,252 100 Shinyanga Rural 5,952 13 39,311 87 45,263 100 Kahama 25,676 32 55,541 68 81,217 100 Bukombe 12,051 23 41,189 77 53,240 100 Meatu 2,148 7 29,344 93 31,492 100 Shinyanga Urban 1,198 12 9,000 88 10,198 100 Kishapu 2,933 8 32,691 92 35,624 100 Total 63,462 17 314,395 83 377,857 100 Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Does not Work Total Number of Agricultural Number of Agricultural Total Excellent Good Average Poor Excellent Good Average Poor Total 215 District Number % Number % Number % Bariadi 37,354 48 40,218 52 77,572 100 Maswa 16,721 39 26,531 61 43,252 100 Shinyanga Rural 33,702 74 11,561 26 45,263 100 Kahama 39,548 49 41,789 51 81,337 100 Bukombe 31,203 59 22,038 41 53,240 100 Meatu 17,781 56 13,710 44 31,492 100 Shinyanga Urban 5,374 53 4,857 47 10,230 100 Kishapu 13,950 39 21,834 61 35,785 100 Total 195,634 52 182,537 48 378,171 100 District Number % Number % Number % Bariadi 13,704 18 63,867 82 77,572 100 Maswa 3,456 8 39,796 92 43,252 100 Shinyanga Rural 9,941 22 35,322 78 45,263 100 Kahama 13,060 16 68,157 84 81,217 100 Bukombe 16,846 32 36,394 68 53,240 100 Meatu 6,705 21 24,787 79 31,492 100 Shinyanga Urban 993 10 9,173 90 10,166 100 Kishapu 3,780 11 31,764 89 35,544 100 Total 68,484 18 309,261 82 377,746 100 Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total 216 District Number % Number % Number % Bariadi 47,935 62 29,637 38 77,572 100 Maswa 11,592 27 31,660 73 43,252 100 Shinyanga Rural 7,173 16 38,090 84 45,263 100 Kahama 34,203 42 47,014 58 81,217 100 Bukombe 27,104 51 26,136 49 53,240 100 Meatu 19,853 63 11,639 37 31,492 100 Shinyanga Urban 1,430 14 8,768 86 10,198 100 Kishapu 12,271 34 23,352 66 35,624 100 Total 161,562 43 216,296 57 377,857 100 District Number % Number % Number % Bariadi 4,092 5 73,480 95 77,572 100 Maswa 2,260 5 40,992 95 43,252 100 Shinyanga Rural 2,438 5 42,825 95 45,263 100 Kahama 6,584 8 74,513 92 81,097 100 Bukombe 8,153 15 45,087 85 53,240 100 Meatu 1,532 5 29,960 95 31,492 100 Shinyanga Urban 662 6 9,536 94 10,198 100 Kishapu 3,456 10 32,168 90 35,624 100 Total 29,177 8 348,560 92 377,737 100 District Number % Number % Number % Bariadi 47,448 61 30,124 39 77,572 100 Maswa 25,091 58 18,161 42 43,252 100 Shinyanga Rural 21,196 47 24,067 53 45,263 100 Kahama 34,979 43 46,238 57 81,217 100 Bukombe 27,459 52 25,781 48 53,240 100 Meatu 20,064 64 11,427 36 31,492 100 Shinyanga Urban 2,777 27 7,421 73 10,198 100 Kishapu 20,865 59 14,677 41 35,542 100 Total 199,881 53 177,895 47 377,776 100 Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total 217 District Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Bariadi 299,108 876 6,146 15,127 166,411 166,575 41,515 39,254 0 178 7,307 16,680 Maswa 157,151 3,531 7,005 3,398 75,727 86,098 22,267 22,679 325 0 6,168 4,985 Shinyanga Rural 190,969 1,985 3,235 6,544 100,657 86,906 27,251 22,452 0 0 4,043 5,053 Kahama 342,361 14,502 6,467 7,918 89,667 45,568 26,188 14,101 144 0 6,879 3,762 Bukombe 244,232 2,703 6,195 6,088 33,940 8,933 7,529 3,106 0 239 1,413 478 Meatu 128,101 2,982 4,892 4,018 80,458 50,390 15,822 13,176 83 0 4,568 3,138 Shinyanga Urban 36,453 1,308 982 664 17,777 13,708 4,406 3,602 179 0 699 577 Kishapu 140,279 2,773 3,099 4,123 74,090 82,886 20,704 19,576 0 0 4,796 2,896 Total 1,538,653 30,659 38,021 47,880 638,727 541,062 165,681 137,946 731 417 35,873 37,569 District Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Bariadi 175 3,006 175 3,006 0 0 0 0 520,836 244,702 Maswa 0 406 0 406 202 0 0 0 268,845 121,503 Shinyanga Rural 102 204 0 102 0 102 0 0 326,257 123,348 Kahama 143 139 143 139 0 0 0 0 471,991 86,130 Bukombe 0 239 0 239 0 239 0 239 293,309 22,502 Meatu 333 891 250 1,141 0 0 0 0 234,505 75,735 Shinyanga Urban 120 0 0 0 0 0 0 0 60,616 19,859 Kishapu 0 245 0 245 569 0 0 0 243,538 112,743 Total 872 5,131 567 5,278 772 341 0 239 2,419,897 806,521 Cont…..Table 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Table 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Total Implement / Asset Name Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Hand Hoe Hand Powered Sprayer Oxen Implement / Asset Name Ox Plough Ox Seed Planter 218 District Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Tractor Plough Tractor Harrow Threshe rs / Shellers Bariadi 77,397 21,112 68,925 68,907 178 22,937 3,006 3,006 0 0 Maswa 42,617 6,842 35,057 32,307 325 9,637 406 406 101 0 Shinyanga Rural 45,263 7,849 39,770 39,575 0 8,382 204 102 102 0 Kahama 81,086 13,524 31,785 31,515 144 9,815 282 282 0 0 Bukombe 52,300 11,687 9,331 8,032 239 1,772 239 239 239 239 Meatu 31,069 6,880 25,962 22,737 83 7,056 1,141 1,141 0 0 Shinyanga Urban 9,964 876 7,018 6,386 30 1,276 30 0 0 0 Kishapu 35,242 5,312 31,885 30,294 0 7,449 245 245 81 0 Total 374,937 74,081 249,732 239,752 999 68,324 5,553 5,421 524 239 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 0 0 175 100 175 100 Maswa 0 0 318 60 216 40 0 0 0 0 534 100 Kahama 0 0 0 0 131 100 0 0 0 0 131 100 Bukombe 223 24 239 25 119 13 358 38 0 0 940 100 Meatu 0 0 256 61 0 0 167 39 0 0 423 100 Shinyanga Urban 15 7 157 77 0 0 32 16 0 0 205 100 Kishapu 0 0 239 80 61 20 0 0 0 0 300 100 Total 238 9 1,210 45 527 19 557 21 175 6 2,707 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 7,155 13 18,375 33 22,521 40 0 0 8,052 14 357 1 56,460 100 Maswa 3,628 10 18,417 51 10,903 30 0 0 3,029 8 432 1 36,410 100 Shinyanga Rural 4,839 13 14,192 38 9,250 25 199 1 8,630 23 303 1 37,414 100 Kahama 4,113 6 29,458 44 15,162 22 0 0 18,959 28 0 0 67,693 100 Bukombe 1,861 5 25,762 63 8,835 22 119 0 4,148 10 239 1 40,964 100 Meatu 3,398 14 9,476 38 7,425 30 0 0 4,147 17 332 1 24,778 100 Shinyanga Urban 387 4 5,846 63 1,847 20 62 1 1,057 11 122 1 9,322 100 Kishapu 2,677 9 18,953 62 5,236 17 82 0 3,363 11 81 0 30,392 100 Total 28,059 9 140,479 46 81,179 27 463 0 51,386 17 1,868 1 303,433 100 Table 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District Table 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District Total Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Not Available Price Too High No Money to Buy / Rent Equipment / Asset of No Use Implement / Asset Name Table 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultura Year 219 District Number % Number % Number % Number % Number % Number % Number % Bariadi 99 1 1,541 18 6,649 77 198 2 161 2 0 0 8,647 100 Maswa 107 1 5,105 62 2,780 34 95 1 108 1 0 0 8,195 100 Shinyanga Rural 0 0 2,016 37 3,374 61 0 0 0 0 102 2 5,493 100 Kahama 847 2 21,541 44 26,476 54 0 0 428 1 141 0 49,432 100 Bukombe 1,049 2 25,570 59 14,325 33 597 1 1,540 4 119 0 43,200 100 Meatu 0 0 2,427 45 2,504 46 164 3 164 3 188 3 5,447 100 Shinyanga Urban 64 2 1,592 50 1,267 40 62 2 195 6 0 0 3,181 100 Kishapu 0 0 2,035 54 1,703 46 0 0 0 0 0 0 3,739 100 Total 2,166 2 61,827 49 59,078 46 1,116 1 2,597 2 550 0 127,333 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 457 5 1,912 22 5,938 69 198 2 161 2 0 0 8,665 100 Maswa 108 1 5,732 52 4,901 45 95 1 108 1 0 0 10,945 100 Shinyanga Rural 0 0 2,418 43 3,270 57 0 0 0 0 0 0 5,688 100 Kahama 1,138 2 21,191 43 26,945 54 0 0 429 1 0 0 49,702 100 Bukombe 944 2 26,390 59 15,507 35 119 0 1,420 3 119 0 44,499 100 Meatu 62 1 3,111 36 4,981 57 164 2 164 2 271 3 8,754 100 Shinyanga Urban 93 2 1,853 49 1,472 39 62 2 301 8 32 1 3,812 100 Kishapu 158 3 3,013 57 2,080 39 0 0 79 1 0 0 5,330 100 Total 2,960 2 65,620 48 65,093 47 638 0 2,663 2 422 0 137,397 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 30,404 39 14,784 19 20,987 27 179 0 10,506 14 533 1 77,394 100 Maswa 12,820 30 15,541 36 13,266 31 0 0 1,192 3 108 0 42,927 100 Shinyanga Rural 16,939 38 16,703 37 8,692 19 0 0 2,826 6 0 0 45,161 100 Kahama 13,960 17 24,937 31 37,274 46 135 0 4,767 6 0 0 81,073 100 Bukombe 7,885 15 23,702 45 18,216 35 239 0 2,131 4 0 0 52,173 100 Meatu 10,946 35 8,671 28 9,937 32 0 0 1,726 6 47 0 31,327 100 Shinyanga Urban 2,156 21 4,458 44 2,977 29 95 1 513 5 0 0 10,198 100 Kishapu 6,740 19 19,023 53 7,430 21 0 0 2,430 7 0 0 35,624 100 Total 101,851 27 127,820 34 118,780 32 648 0 26,090 7 688 0 375,877 100 Table 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District Table 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Table 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District 220 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,276 2 15,413 28 29,886 55 179 0 7,712 14 169 0 54,634 100 Maswa 1,690 5 13,249 39 17,309 51 0 0 1,151 3 216 1 33,615 100 Shinyanga Rural 1,012 3 15,656 42 19,311 52 102 0 699 2 101 0 36,881 100 Kahama 794 1 25,123 35 42,857 60 98 0 2,410 3 120 0 71,402 100 Bukombe 2,066 4 25,623 50 21,179 42 239 0 1,653 3 0 0 50,760 100 Meatu 175 1 12,120 50 11,194 46 0 0 752 3 195 1 24,436 100 Shinyanga Urban 270 3 4,254 48 3,766 42 62 1 570 6 0 0 8,922 100 Kishapu 326 1 18,056 64 8,094 29 0 0 1,537 5 82 0 28,095 100 Total 7,608 2 129,496 42 153,595 50 680 0 16,483 5 883 0 308,745 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,588 2 32,834 44 34,915 47 0 0 5,061 7 169 0 74,566 100 Maswa 3,220 8 19,087 45 19,572 46 0 0 751 2 216 1 42,846 100 Shinyanga Rural 6,055 13 19,348 43 19,050 42 0 0 606 1 0 0 45,059 100 Kahama 8,569 11 32,609 40 34,101 42 278 0 5,378 7 0 0 80,935 100 Bukombe 4,882 9 17,363 33 27,904 53 119 0 2,025 4 0 0 52,293 100 Meatu 504 2 14,782 49 14,476 48 0 0 331 1 94 0 30,186 100 Shinyanga Urban 686 7 4,160 41 4,825 47 32 0 465 5 0 0 10,168 100 Kishapu 163 0 16,265 46 16,355 46 0 0 2,514 7 82 0 35,379 100 Total 25,666 7 156,448 42 171,197 46 429 0 17,130 5 560 0 371,431 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,942 3 32,474 44 33,491 45 0 0 6,312 8 347 0 74,566 100 Maswa 2,812 7 18,671 44 20,388 48 0 0 758 2 216 1 42,846 100 Shinyanga Rural 5,950 13 19,443 43 19,364 43 0 0 405 1 0 0 45,161 100 Kahama 8,734 11 33,046 41 33,099 41 141 0 5,915 7 0 0 80,935 100 Bukombe 5,206 10 16,659 32 28,396 54 0 0 2,031 4 0 0 52,293 100 Meatu 550 2 15,935 53 13,441 44 0 0 331 1 94 0 30,351 100 Shinyanga Urban 593 6 4,235 42 4,752 47 64 1 554 5 0 0 10,198 100 Kishapu 241 1 16,487 47 16,055 45 0 0 2,514 7 82 0 35,379 100 Total 26,028 7 156,951 42 168,985 45 205 0 18,821 5 739 0 371,728 100 Table 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District Table 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District Table 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required 221 District Number % Number % Number % Number % Number % Number % Number % Bariadi 15,614 20 24,492 32 26,617 34 0 0 10,685 14 163 0 77,572 100 Maswa 5,582 13 17,227 40 19,252 45 0 0 975 2 216 1 43,252 100 Shinyanga Rural 6,253 14 17,646 39 19,952 44 0 0 1,310 3 0 0 45,161 100 Kahama 12,083 15 30,072 37 32,331 40 141 0 6,589 8 0 0 81,217 100 Bukombe 5,672 11 15,986 31 27,905 53 0 0 2,729 5 0 0 52,293 100 Meatu 2,716 9 14,194 45 10,965 35 0 0 3,569 11 47 0 31,492 100 Shinyanga Urban 619 6 4,444 44 4,424 43 32 0 680 7 0 0 10,198 100 Kishapu 731 2 16,530 46 15,015 42 0 0 3,266 9 82 0 35,624 100 Total 49,271 13 140,592 37 156,460 42 173 0 29,804 8 508 0 376,808 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 23,919 31 16,968 22 22,115 29 354 0 13,693 18 523 1 77,572 100 Maswa 9,114 21 15,301 35 17,430 40 0 0 1,191 3 216 1 43,252 100 Shinyanga Rural 9,987 22 16,902 37 15,646 35 0 0 2,625 6 102 0 45,263 100 Kahama 13,431 17 28,483 35 32,424 40 0 0 6,633 8 247 0 81,217 100 Bukombe 18,922 36 17,645 34 13,820 26 0 0 1,905 4 0 0 52,293 100 Meatu 5,628 18 11,333 36 9,095 29 0 0 5,341 17 94 0 31,492 100 Shinyanga Urban 1,926 19 4,179 41 3,111 31 32 0 950 9 0 0 10,198 100 Kishapu 3,999 11 16,190 45 12,432 35 0 0 2,920 8 82 0 35,624 100 Total 86,927 23 127,001 34 126,074 33 386 0 35,258 9 1,264 0 376,910 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 52,198 67 21,152 27 1,067 1 178 0 169 0 2,634 3 77,397 100 Maswa 35,271 84 4,062 10 1,381 3 216 1 0 0 1,186 3 42,116 100 Shinyanga Rural 33,165 74 8,985 20 399 1 0 0 204 0 2,205 5 44,958 100 Kahama 64,828 80 12,916 16 1,242 2 144 0 282 0 1,544 2 80,956 100 Bukombe 44,112 85 5,581 11 351 1 119 0 239 0 1,777 3 52,180 100 Meatu 22,822 74 4,789 16 81 0 247 1 83 0 2,874 9 30,896 100 Shinyanga Urban 6,657 67 2,791 28 238 2 64 1 31 0 124 1 9,904 100 Kishapu 31,157 89 3,435 10 80 0 245 1 0 0 244 1 35,160 100 Total 290,210 78 63,709 17 4,840 1 1,213 0 1,008 0 12,588 3 373,568 100 Table 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District Table 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District Table 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District Equipment / Asset of No Other Total Sale of Farm Products Other Income Generating Remittances Bank Loan Credit Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total 222 District Number % Number % Number % Number % Number % Bariadi 3,523 59 2,462 41 0 0 0 0 5,985 100 Maswa 3,443 100 0 0 0 0 0 0 3,443 100 Shinyanga Rural 1,713 77 400 18 0 0 102 5 2,214 100 Kahama 5,614 89 567 9 0 0 144 2 6,325 100 Bukombe 5,240 90 358 6 239 4 0 0 5,837 100 Meatu 2,390 79 564 19 0 0 83 3 3,037 100 Shinyanga Urban 344 100 0 0 0 0 0 0 344 100 Kishapu 1,704 89 140 7 81 4 0 0 1,926 100 Total 23,971 82 4,491 15 320 1 328 1 29,111 100 District Number % Number % Number % Number % Number % Number % Bariadi 21,647 69 4,957 16 355 1 0 0 4,543 14 31,502 100 Maswa 14,080 92 433 3 325 2 0 0 528 3 15,365 100 Shinyanga Rural 15,423 78 2,106 11 918 5 0 0 1,416 7 19,863 100 Kahama 18,800 90 1,153 6 141 1 144 1 553 3 20,791 100 Bukombe 6,590 95 119 2 0 0 0 0 239 3 6,949 100 Meatu 9,992 67 954 6 83 1 0 0 3,774 25 14,804 100 Shinyanga Urban 3,111 84 423 11 0 0 0 0 154 4 3,687 100 Kishapu 12,134 86 716 5 158 1 0 0 1,042 7 14,048 100 Total 101,777 80 10,860 9 1,980 2 144 0 12,248 10 127,009 100 District Number % Number % Number % Number % Number % Number % Bariadi 24,773 78 5,935 19 177 1 0 0 1,058 3 31,942 100 Maswa 14,076 94 433 3 217 1 0 0 310 2 15,036 100 Shinyanga Rural 15,217 77 2,804 14 918 5 0 0 808 4 19,748 100 Kahama 17,908 89 1,338 7 141 1 134 1 686 3 20,207 100 Bukombe 4,931 93 234 4 0 0 119 2 0 0 5,284 100 Meatu 8,882 76 571 5 0 0 0 0 2,225 19 11,678 100 Shinyanga Urban 2,860 75 632 17 30 1 125 3 154 4 3,801 100 Kishapu 12,290 89 1,050 8 0 0 0 0 488 4 13,828 100 Total 100,938 83 12,997 11 1,483 1 378 0 5,729 5 121,525 100 Table 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District Table 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OXEN by Source of Finance and District Table 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District Total Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total Total Sale of Farm Products Other Income Generating Remittances Bank Loan Other Sale of Farm Products Other Income Generating Credit Other Appendix II 223 District Number % Number % Number % Maswa 325 100 0 0 325 100 Kahama 144 100 0 0 144 100 Meatu 83 100 0 0 83 100 Shinyanga Urban 0 0 30 100 30 100 Total 552 95 30 5 582 100 District Number % Number % Number % Number % Number % Bariadi 5,422 78 1,381 20 0 0 163 2 6,967 100 Maswa 5,086 96 0 0 0 0 216 4 5,302 100 Shinyanga Rural 2,720 77 303 9 306 9 204 6 3,533 100 Kahama 6,217 96 263 4 0 0 0 0 6,480 100 Bukombe 1,294 100 0 0 0 0 0 0 1,294 100 Meatu 3,542 80 323 7 0 0 538 12 4,402 100 Shinyanga Urban 575 82 63 9 0 0 61 9 699 100 Kishapu 3,909 83 647 14 0 0 162 3 4,717 100 Total 28,765 86 2,980 9 306 1 1,343 4 33,394 100 District District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 175 100 175 100 Maswa 101 100 101 100 Shinyanga Rural 102 100 0 0 0 0 102 100 Kishapu 81 100 81 100 Kahama 0 0 143 100 0 0 143 100 Total 183 100 183 100 Meatu 250 100 0 0 0 0 250 100 Shinyanga Urban 30 100 0 0 0 0 30 100 Total 382 55 143 20 175 25 699 100 District Number % Number % Number % Number % Bariadi 0 0 0 0 175 100 175 100 Kahama 0 0 143 100 0 0 143 100 Meatu 250 100 0 0 0 0 250 100 Total 250 44 143 25 175 31 567 100 Table 12.2.21 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District Sale of Farm Products Total Table 12.2.20 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District Table 12.2.19 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District Table 12.2.18 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX CART by Source of Finance and District Table 12.2.17 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District Sale of Farm Products Bank Loan Credit Total Other Total Sale of Farm Products Bank Loan Credit Total Sale of Farm Products Other Income Generating Total Sale of Farm Products Other Income Generating Activities Remittances Tanzania Agriculture Sample Census - 2003 Shinyanga Appendix II 224 AGRICULTURE CREDIT Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 225 Number % Number % Bariadi 1,733 77 525 23 2,258 Maswa 650 75 217 25 867 Shinyanga Rural 100 25 302 75 401 Kahama 2,040 94 137 6 2,177 Bukombe 716 86 119 14 836 Meatu 81 33 165 67 246 Shinyanga Urban 0 0 23 100 23 Kishapu 82 33 164 67 245 Total 5,402 77 1,651 23 7,054 % 77 23 District Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Bariadi 531 0 0 346 1,381 0 2,258 Maswa 542 0 0 108 0 217 867 Shinyanga Rural 0 0 0 0 0 401 401 Kahama 676 0 1,501 0 0 0 2,177 Bukombe 239 0 0 478 0 119 836 Meatu 81 83 0 82 0 0 246 Shinyanga Urban 0 0 0 23 0 0 23 Kishapu 163 0 0 0 0 82 245 Total 2,233 83 1,501 1,037 1,381 819 7,054 % 32 1 21 15 20 12 100 13.2c AGRICULTURE CREDIT: Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year 13.2a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year District Male Female Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 226 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Bariadi 3,128 15,731 4,887 3,112 28,173 333 175 0 19,776 75,314 Maswa 3,762 9,983 6,514 1,822 12,849 318 215 209 6,711 42,385 Shinyanga Rural 2,740 9,675 6,394 1,527 10,050 100 908 102 13,366 44,862 Kahama 6,180 12,761 14,721 1,474 20,417 1,163 266 0 22,058 79,040 Bukombe 2,609 20,415 3,564 1,054 11,791 239 358 0 12,374 52,404 Meatu 647 1,710 2,315 2,693 11,645 1,025 164 167 10,879 31,246 Shinyanga Urban 757 843 1,707 163 3,514 61 152 0 2,978 10,175 Kishapu 1,433 3,172 2,256 719 14,517 561 291 81 12,349 35,378 Total 21,257 74,290 42,359 12,564 112,955 3,798 2,529 560 100,492 370,804 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Bariadi 696 705 0 1,378 528 0 0 179 3,485 Maswa 217 434 0 108 217 0 0 434 1,409 Shinyanga Rural 100 102 100 0 199 0 0 0 502 Kahama 529 1,227 1,368 1,652 392 0 137 410 5,715 Bukombe 478 239 119 358 119 119 0 0 1433.4027 Meatu 0 0 0 163 82 0 83 0 328 Shinyanga Urban 0 0 0 0 0 0 0 23.301541 23.301541 Kishapu 164 82 0 82 82 0 0 0 408.46176 Total Credits 2,183 2,788 1,588 3,741 1,618 119 220 1,046 13,304 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Shinyanga 227 Appendix II 228 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 229 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Casurina Equisetfilia Tectona Grandis Terminalia Catapa Bariadi 10 43 . 181 17 25 . . . . Maswa 38 2,005 . . . 52 . . . . Shinyanga Rural 10 16 . 284 . . . 3 . . Kahama 5 . . . . . 30 . 1 . Bukombe . 125 9 4 . 4 . . . 7 Meatu . 93 . 120 . . . . . . Shinyanga Urban 3 68 . 77 . . . . . 1 Kishapu . 4 . 733 . . . . . . Total 66 2,354 9 1,399 17 81 30 3 1 8 % 0 10 0 6 0 0 0 0 0 0 District Terminalia Ivorensis Berchemoides Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Albizia Spp Calliandra Spp Moringa Spp TOTAL Bariadi . . . . . . . . . 11,261 Maswa . . 70 . 105 . 20 . . 48 Shinyanga Rural 10 . 146 2 499 . 4 . 9 0 Kahama . 32 . 1 91 . . . . 0 Bukombe . . . . . . . . . 0 Meatu . . 5,050 . 6 . . . . 11,261 Shinyanga Urban 2 . 136 . 398 7 . . 22 243 Kishapu . . 370 . 106 7 . 200 . 670 Total 12 32 5,772 3 1,205 14 24 200 31 23,483 % 0 0 25 0 5 0 0 1 0 100 cont…. ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 230 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Bariadi 8 85 10 88 6 83 24 256 Maswa 4 2,056 3 222 2 12 9 2,290 Shinyanga Rural 15 151 9 215 2 617 26 983 Kahama 7 79 4 81 0 . 11 160 Bukombe 7 36 5 13 1 100 13 149 Meatu 1 5 4 5,098 4 166 9 5,269 Shinyanga Urban 28 523 9 191 0 . 37 714 Kishapu 4 1,330 5 63 1 20 10 1,413 Total 74 4,265 49 5,971 16 998 139 11,234 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bariadi 3 1 18 8 0 0 30 Maswa 4 2 7 0 0 1 14 Shinyanga Rural 1 0 23 7 3 0 34 Kahama 7 2 0 1 1 2 13 Bukombe 4 0 3 2 0 3 12 Meatu 0 2 6 2 0 0 10 Shinyanga Urban 1 3 41 30 4 0 79 Kishapu 8 1 2 2 3 0 16 Total 28 11 100 52 11 6 208 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region District Main Use 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Shinyanga Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 231 1-9 10-19 20-29 30-39 40-49 Above 50 Total Bariadi 14,360 4,433 1,180 1,323 705 1,737 23,738 Maswa 297 325 108 425 756 540 2,451 Shinyanga Rural 2,804 808 813 509 714 408 6,057 Kahama 2,283 0 2,137 2,152 0 144 6,716 Bukombe Meatu 852 92 313 203 359 235 2,054 Shinyanga Urban 1,101 118 88 88 0 29 1,426 Kishapu 896 1,106 646 80 642 480 3,850 Total 22,593 6,882 5,286 4,781 3,176 3,574 46,292 % 49 15 11 10 7 8 100 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bariadi 3 1 18 8 0 0 30 Maswa 4 2 7 0 0 1 14 Shinyanga Rural 1 0 23 7 3 0 34 Kahama 7 2 0 1 1 2 13 Bukombe 4 0 3 2 0 3 12 Meatu 0 2 6 2 0 0 10 Shinyanga Urban 1 3 41 30 4 0 79 Kishapu 8 1 2 2 3 0 16 Total 28.0 11.0 100.0 52.0 11.0 6.0 208.0 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Bariadi 1 1 0 9 19 0 0 30 Maswa 1 4 0 6 1 0 2 14 Shinyanga Rural 2 6 3 8 11 3 1 34 Kahama 1 0 0 10 2 0 0 13 Bukombe 0 3 0 5 4 0 0 12 Meatu 0 0 0 1 2 4 3 10 Shinyanga Urban 1 3 1 23 38 7 2 75 Kishapu 1 8 1 4 0 2 0 16 Total 7 25 5 66 77 16 8 204 District Main Use 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region District Second Use 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Shinyanga Region District Distance to Community Planted Forest (km) 14 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 232 CROP EXTENSION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 233 Number % Number % Bariadi 16,641 21 60,931 79 77,572 Maswa 2,469 6 40,783 94 43,252 Shinyanga Rural 12,421 27 32,842 73 45,263 Kahama 29,021 36 52,195 64 81,217 Bukombe 7,386 14 45,854 86 53,240 Meatu 14,761 47 16,731 53 31,492 Shinyanga Urban 3,364 33 6,834 67 10,198 Kishapu 18,190 51 17,434 49 35,624 Total 104,252 28 273,606 72 377,857 Total Number % Number % Number % Number % Number % Number Bariadi 4,228 26 12,258 74 0 0 0 0 0 0 16,486 Maswa 324 13 1,617 66 527 21 0 0 0 0 2,469 Shinyanga Rural 3,330 27 7,503 60 1,388 11 200 2 0 0 12,421 Kahama 2,046 7 19,828 72 5,571 20 142 1 0 0 27,587 Bukombe 830 11 5361 74 836 12 239 3 0 0 7,266 Meatu 1,273 9 7,874 53 5,239 35 239 2 135 1 14,761 Shinyanga Urban 104 3 2,082 62 775 23 339 10 64 2 3,364 Kishapu 1,342 7 9,551 53 6,567 36 489 3 159 1 18,109 Total 13,478 13 66,075 64 20,903 20 1,648 2 358 0 102,463 Total Number % Number % Number % Number % Number % Number % Number Bariadi 15,757 95 357 2 348 2 0 0 0 0 179 1 16,641 Maswa 2,144 86.84807554 217 9 108 4 0 0 0 0 0 0 2,469 Bukombe 11,617 95 400 3 0 0 99 1 0 0 100 1 12,217 Kahama 27,094 98 634 2 0 0 0 0 0 0 0 0 27,729 Bukombe 7,028 98 119 2 0 0 0 0 0 0 0 0 7,147 Meatu 14,101 96 494 3 0 0 83 1 0 0 0 0 14,678 Shinyanga Urban 3,301 98 31 1 0 0 0 0 32 1 0 0 3,364 Kishapu 17,547 97 237 1 0 0 160 1 0 0 81 0 18,026 Total 98,589 96 2,489 2 456 0 343 0 32 0 361 0 102,269 Average 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region District Government NGO / Development Project Not Other Very Good Poor Good Cooperative Large Scale Farm 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region District 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Shinyanga Region District Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households No Good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 234 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Bariadi 15,043 357 348 0 0 0 15,748 77,572 20 Maswa 1,927 217 108 0 0 0 2,252 43,252 5 Shinyanga Rural 9,705 400 0 99 0 100 10,304 45,263 23 Kahama 26,219 634 0 0 0 0 26,854 81,217 33 Bukombe 6,192 119 0 0 0 0 6,311 53,240 12 Meatu 13,939 494 0 0 0 0 14,434 31,492 46 Shinyanga Urban 3,001 31 0 0 32 0 3,064 10,198 30 Kishapu 17,004 237 0 0 0 81 17,322 35,624 49 Total 93,030 2,489 456 99 32 182 96,288 377,857 25 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 12,303 179 169 0 179 12,830 77,572 17 Maswa 1,603 216 0 108 0 1,928 43,252 4 Shinyanga Rural 5,052 601 0 0 0 5,652 45,263 12 Kahama 23,762 770 133 0 0 24,665 81,217 30 Bukombe 4,062 119 0 0 358 4,540 53,240 9 Meatu 8,976 0 0 83 245 9,304 31,492 30 Shinyanga Urban 1,226 0 0 0 31 1,256 10,198 12 Kishapu 10,706 81 0 82 0 10,869 35,624 31 Total 67,690 1,966 302 273 814 71,044 377,857 18.8 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Use of Agrochemicals District Spacing Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 235 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 4,742 358 0 5,099 77,572 7 Maswa 325 108 0 433 43,252 1 Shinyanga Rural 5,834 402 0 6,236 45,263 14 Kahama 17,032 328 142 17,502 81,217 22 Bukombe 1,666 0 358 2,025 53,240 4 Meatu 7,638 247 83 7,968 31,492 25 Shinyanga Urban 1,189 0 0 1,189 10,198 12 Kishapu 7,672 0 160 7,832 35,624 22 Total 46,097 1,443 743 48,284 377,857 13 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 10,512 0 348 169 0 11,029 77,572 14 Maswa 1,400 527 0 217 0 2,144 43,252 5 Shinyanga Rural 9,025 900 0 0 0 9,925 45,263 22 Kahama 20,525 0 140 0 142 20,807 81,217 26 Bukombe 4,399 119 0 0 119 4,638 53,240 9 Meatu 10,085 410 0 0 83 10,578 31,492 34 Shinyanga Urban 2,764 0 0 0 62 2,826 10,198 28 Kishapu 12,008 79 0 81 242 12,410 35,624 35 Total 70,719 2,035 488 467 649 74,358 377,857 20 District Organic Fertilizer Use 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year Erosion Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 236 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 2,658 179 0 0 0 0 2,837 77,572 4 Maswa 216 325 0 0 0 0 541 43,252 1 Shinyanga Rural 3,128 701 0 0 0 201 4,030 45,263 9 Kahama 17,766 1,117 0 0 0 394 19,277 81,217 24 Bukombe 2,151 0 0 0 0 358 2,509 53,240 5 Meatu 4,355 165 0 0 0 0 4,519 31,492 14 Shinyanga Urban 539 0 0 0 32 0 571 10,198 6 Kishapu 3,751 237 80 160 0 162 4,390 35,624 12 Total 34,563 2,723 80 160 32 1,116 38,673 377,857 10 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 11,110 0 0 169 0 0 11,279 77,572 15 Maswa 1,291 528 0 0 0 0 1,819 43,252 4 Shinyanga Rural 6,822 1,003 0 102 0 202 8,129 45,263 18 Kahama 21,642 624 275 0 0 282 22,823 81,217 28 Bukombe 4,764 0 0 119 0 0 4,884 53,240 9 Meatu 11,409 416 0 0 0 83 11,909 31,492 38 Shinyanga Urban 2,284 0 0 0 63 31 2,377 10,198 23 Kishapu 12,891 238 0 0 0 644 13,773 35,624 39 Total 72,213 2,809 275 390 63 1,242 76,993 377,857 20 % 93.8 3.6 0.4 0.5 0.1 1.6 100 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seed 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Inorganic Fertilizer Use Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 237 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 2,259 0 179 0 0 2,438 77,572 3 Maswa 324 0 0 0 0 324 43,252 1 Shinyanga Rural 2,730 102 0 0 202 3,035 45,263 7 Kahama 1,407 98 0 0 282 1,787 81,217 2 Bukombe 597 119 0 119 239 1,075 53,240 2 Meatu 3,766 0 0 0 165 3,931 31,492 12 Shinyanga Urban 693 0 0 0 30 723 10,198 7 Kishapu 2,137 0 0 0 238 2,376 35,624 7 Total 13,914 319 179 119 1,157 15,688 377,857 4 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 4,048 0 179 0 0 4,227 77,572 5 Maswa 216 0 0 0 0 216 43,252 1 Shinyanga Rural 4,236 303 0 0 100 4,639 45,263 10 Kahama 7,134 240 0 0 142 7,516 81,217 9 Bukombe 1,912 0 0 0 239 2,151 53,240 4 Meatu 3,686 0 0 0 83 3,770 31,492 12 Shinyanga Urban 1,250 0 0 32 0 1,282 10,198 13 Kishapu 4,329 0 0 0 229 4,559 35,624 13 Total 26,812 543 179 32 794 28,359 377,857 8 District District 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Mechanisation / LST Irrigation Technology 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 238 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 10,470 178 0 348 0 0 10,996 77,572 14 Maswa 1,508 203 0 0 0 0 1,711 43,252 4 Shinyanga Rural 7,525 603 0 99 0 0 8,228 45,263 18 Kahama 21,309 647 275 0 0 0 22,230 81,217 27 Bukombe 2,748 0 0 0 0 119 2,868 53,240 5 Meatu 10,553 307 0 83 0 371 11,313 31,492 36 Shinyanga Urban 2,122 27 0 15 64 0 2,229 10,198 22 Kishapu 8,847 0 0 0 0 240 9,087 35,624 26 Total 65,082 1,965 275 545 64 730 68,660 377,857 18 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 3,512 179 169 0 0 0 3,860 77,572 5 Maswa 210 0 0 108 0 0 318 43,252 1 Shinyanga Rural 5,538 201 0 0 0 0 5,739 45,263 13 Kahama 10,730 240 142 0 0 250 11,362 81,217 14 Bukombe 836 0 0 0 0 358 1,195 53,240 2 Meatu 5,530 0 0 0 0 407 5,937 31,492 19 Shinyanga Urban 1,280 0 0 0 32 0 1,312 10,198 13 Kishapu 5,426 0 0 0 0 226 5,652 35,624 16 Total 33,062 620 311 108 32 1,242 35,375 377,857 9 % 93.5 1.8 0.9 0.3 0.1 3.5 100 Crop Storage Vermin Control 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region. District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 239 Government NGO / Development Project Large Scale Farm Not applicable Total Total Bariadi 5,513 356 174 179 6,222 6,222 77,572 8 Maswa 325 0 0 0 325 325 43,252 1 Shinyanga Rural 5,230 898 99 0 6,228 6,228 45,263 14 Kahama 11,217 0 0 569 11,786 11,786 81,217 15 Bukombe 1,075 0 0 358 1,434 1,434 53,240 3 Meatu 4,982 0 78 409 5,469 5,469 31,492 17 Shinyanga Urban 1,296 0 0 32 1,327 1,327 10,198 13 Kishapu 10,848 0 81 145 11,074 11,074 35,624 31 Total 40,484 1,255 433 1,692 43,864 43,864 377,857 11.6 Government NGO / Development Project Cooperative Not applicable Total Total Number of households % of total number of households Bariadi 1,043 0 0 0 1,043 77,572 1 Maswa 649 203 108 0 960 43,252 2 Shinyanga Rural 4,637 201 0 0 4,838 45,263 11 Kahama 12,406 98 0 283 12,787 81,217 16 Bukombe 956 0 0 239 1,195 53,240 2 Meatu 4,779 83 0 0 4,862 31,492 15 Shinyanga Urban 747 0 0 0 747 10,198 7 Kishapu 3,755 0 80 145 3,980 35,624 11 Total 28,972 584 188 668 30,412 377,857 8.0 % 95.3 1.9 0.6 2.2 100 Agro-progressing % of total number of households Total Number of households 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Agro-forestry District 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 240 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 532 0 0 532 77,572 1 Maswa 324 0 0 324 43,252 1 Shinyanga Rural 2,022 99 102 2,223 45,263 5 Kahama 426 110 276 812 81,217 1 Bukombe 0 0 358 358 53,240 1 Meatu 219 0 333 552 31,492 2 Shinyanga Urban 152 0 0 152 10,198 1 Kishapu 242 0 0 242 35,624 1 Total 3,917 210 1,070 5,196 377,857 1 % 75 4 21 100 Government NGO / Development Project Cooperative Not applicable Total Total Total Number of households % of total number of households Bariadi 179 0 0 0 179 179 77,572 0 Maswa 649 0 108 0 757 757 43,252 2 Shinyanga Rural 605 0 0 0 605 605 45,263 1 Kahama 280 0 0 276 556 556 81,217 1 Bukombe 0 0 0 358 358 358 53,240 1 Meatu 83 0 0 333 416 416 31,492 1 Shinyanga Urban 32 30 0 0 62 62 10,198 1 Kishapu 487 0 0 0 487 487 35,624 1 Total 2,313 30 108 968 3,419 3,419 377,857 0.9 District Fish Farming District 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Beekeeping Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 241 Received Adopted % Received Adopted % Received Adopted % Bariadi 15,748 13,816 88 12,830 9,117 71 4,925 2,638 54 Maswa 2,252 2,144 95 1,928 1,711 89 433 433 100 Shinyanga Rural 10,406 9,393 90 5,145 1,110 22 6,034 4,120 68 Kahama 26,717 23,855 89 24,528 18,669 76 17,510 12,586 72 Bukombe 6,311 4,882 77 4,062 2,628 65 1,666 1,308 78 Meatu 14,434 10,454 72 8,391 4,265 51 7,395 1,790 24 Shinyanga Urban 3,032 1,957 65 1,168 612 52 1,161 612 53 Kishapu 17,482 14,828 10,869 3,551 7,832 1,720 455 Total 96,382 81,330 84 68,920 41,663 60 46,957 25,207 54 Received Adopted % Received Adopted % Received Adopted % Bariadi 11,029 6,113 55 2,837 1,210 43 11,632 7,659 66 Maswa 2,144 1,718 80 649 216 33 1,711 1,710 100 Shinyanga Rural 10,026 8,010 80 3,422 1,414 41 8,229 3,715 45 Kahama 20,951 17,292 83 18,995 12,215 64 22,686 16,101 71 Bukombe 4,280 2,026 47 2,031 955 47 4,884 2,146 44 Meatu 10,578 3,678 35 4,031 1,659 41 11,993 7,160 60 Shinyanga Urban 2,917 1,924 66 556 239 43 2,377 984 41 Kishapu 12,407 4,861 4,228 478 13,936 8,834 Total 74,332 45,621 61 36,748 18,387 50 77,447 48,310 62 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District Spacing Use of Agrochemicals 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region Erosion Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 242 Received Adopted % Received Adopted % Received Adopted % Bariadi 2,438 1,896 78 3,359 1,925 57 11,353 9,930 87 Maswa 324 216 67 216 108 50 1,711 1,602 94 Shinyanga Rural 2,734 708 26 4,334 1,109 26 8,225 7,414 90 Kahama 945 562 60 7,099 5,299 75 22,502 19,834 88 Bukombe 478 1,433 300 1,195 717 60 2,748 2,390 87 Meatu 3,018 2,062 68 2,609 1,569 60 11,020 9,745 88 Shinyanga Urban 665 107 16 1,289 388 30 2,288 1,722 75 Kishapu 2,216 149 4,071 872 9,249 5,478 Total 12,818 7,133 56 24,173 11,987 50 69,096 58,115 84 Received Adopted % Received Adopted % Received Adopted % Bariadi 3,155 2,973 94 5,690 5,154 91 1,049 882 84 Maswa 318 318 100 216 325 150 960 311 32 Shinyanga Rural 5,433 4,840 89 5,919 5,430 92 4,838 3,837 79 Kahama 11,221 9,520 85 10,938 10,529 96 12,508 7,771 62 Bukombe 478 956 200 717 1,075 150 597 478 80 Meatu 5,032 5,609 111 4,313 5,388 125 4,779 2,136 45 Shinyanga Urban 1,344 707 53 1,264 891 70 689 401 58 Kishapu 5,162 3,811 10,911 9,643 3,898 481 Total 32,144 28,734 89 39,969 38,435 96 29,320 16,297 56 Received Adopted % Received Adopted % Received Adopted % Bariadi 1,049 882 84 175 175 100 0 0 0 Maswa 960 311 32 324 108 33 865 649 75 Shinyanga Rural 4,838 3,837 79 2,121 503 24 605 0 0 Kahama 12,508 7,771 62 395 393 100 143 143 0 Bukombe 597 478 80 0 0 0 0 0 0 Meatu 4,779 2,136 45 498 331 67 416 250 60 Shinyanga Urban 689 401 58 152 57 38 32 0 0 Kishapu 3,898 481 80 0 162 0 Total 29,320 16,297 56 3,744 1,567 42 2,223 1,220 55 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region District Agro-forestry Beekeeping Fish Farming 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region District Vermin Control Agro-progressing Agro-forestry 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region District Mechanisation / LST Irrigation Technology Crop Storage Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 243 Number % Number % Bariadi 16,641 21 60,931 79 77,572 Maswa 2,469 6 40,783 94 43,252 Shinyanga Rural 12,421 27 32,842 73 45,263 Kahama 29,021 36 52,195 64 81,217 Bukombe 7,386 14 45,854 86 53,240 Meatu 14,761 47 16,731 53 31,492 Shinyanga Urban 3,364 33 6,834 67 10,198 Kishapu 18,190 51 17,434 49 35,624 Total 104,252 28 273,606 72 377,857 Total Number % Number % Number % Number % Number % Number Bariadi 4,228 26 12,258 74 0 0 0 0 0 0 16,486 Maswa 324 13 1,617 66 527 21 0 0 0 0 2,469 Shinyanga Rural 3,330 27 7,503 60 1,388 11 200 2 0 0 12,421 Kahama 2,046 7 19,828 72 5,571 20 142 1 0 0 27,587 Bukombe 830.072222 11.4 5360.97405 74 836 12 239 3 0 0 7,266 Meatu 1,273 9 7,874 53 5,239 35 239 2 135 1 14,761 Shinyanga Urban 104 3 2,082 62 775 23 339 10 64 2 3,364 Kishapu 1,342 7 9,551 53 6,567 36 489 3 159 1 18,109 Total 13,478 13 66,075 64 20,903 20 1,648 2 358 0 102,463 Total Number % Number % Number % Number % Number % Number % Number Bariadi 15,757 95 357 2 348 2 0 0 0 0 179 1 16,641 Maswa 2,144 86.8 217 9 108 4 0 0 0 0 0 0 2,469 Bukombe 11,617 95 400 3 0 0 99 1 0 0 100 1 12,217 Kahama 27,094 98 634 2 0 0 0 0 0 0 0 0 27,729 Bukombe 7,028 98 119 2 0 0 0 0 0 0 0 0 7,147 Meatu 14,101 96 494 3 0 0 83 1 0 0 0 0 14,678 Shinyanga Urban 3,301 98 31 1 0 0 0 0 32 1 0 0 3,364 Kishapu 17,547 97 237 1 0 0 160 1 0 0 81 0 18,026 Total 98,589 96 2,489 2 456 0 343 0 32 0 361 0 102,269 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region District Government NGO / Development Cooperative Large Scale Other Not applicable District Households Receiving Extension Advice Households Not Receiving Extension Advice 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Total Number of Households Poor No Good 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region District Very Good Good Average Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 244 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Bariadi 15,043 357 348 0 0 0 15,748 77,572 20 Maswa 1,927 217 108 0 0 0 2,252 43,252 5 Shinyanga Rural 9,705 400 0 99 0 100 10,304 45,263 23 Kahama 26,219 634 0 0 0 0 26,854 81,217 33 Bukombe 6,192 119 0 0 0 0 6,311 53,240 12 Meatu 13,939 494 0 0 0 0 14,434 31,492 46 Shinyanga Urban 3,001 31 0 0 32 0 3,064 10,198 30 Kishapu 17,004 237 0 0 0 81 17,322 35,624 49 Total 93,030 2,489 456 99 32 182 96,288 377,857 25 % 97 3 0 0 0 0 100 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 12,303 179 169 0 179 12,830 77,572 17 Maswa 1,603 216 0 108 0 1,928 43,252 4 Shinyanga Rural 5,052 601 0 0 0 5,652 45,263 12 Kahama 23,762 770 133 0 0 24,665 81,217 30 Bukombe 4,062 119 0 0 358 4,540 53,240 9 Meatu 8,976 0 0 83 245 9,304 31,492 30 Shinyanga Urban 1,226 0 0 0 31 1,256 10,198 12 Kishapu 10,706 81 0 82 0 10,869 35,624 31 Total 67,690 1,966 302 273 814 71,044 377,857 18.8 % 95.3 2.8 0.4 0.4 1.1 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/ Agriculture Year, Shinyanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District District Spacing Use of Agrochemicals Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 245 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 4,742 358 0 5,099 77,572 7 Maswa 325 108 0 433 43,252 1 Shinyanga Rural 5,834 402 0 6,236 45,263 14 Kahama 17,032 328 142 17,502 81,217 22 Bukombe 1,666 0 358 2,025 53,240 4 Meatu 7,638 247 83 7,968 31,492 25 Shinyanga Urban 1,189 0 0 1,189 10,198 12 Kishapu 7,672 0 160 7,832 35,624 22 Total 46,097 1,443 743 48,284 377,857 13 % 95.5 3.0 1.5 100.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 10,512 0 348 169 0 11,029 77,572 14 Maswa 1,400 527 0 217 0 2,144 43,252 5 Shinyanga Rural 9,025 900 0 0 0 9,925 45,263 22 Kahama 20,525 0 140 0 142 20,807 81,217 26 Bukombe 4,399 119 0 0 119 4,638 53,240 9 Meatu 10,085 410 0 0 83 10,578 31,492 34 Shinyanga Urban 2,764 0 0 0 62 2,826 10,198 28 Kishapu 12,008 79 0 81 242 12,410 35,624 35 Total 70,719 2,035 488 467 649 74,358 377,857 20 % 95.1 2.7 0.7 0.6 0.9 100.0 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Erosion Control Organic Fertilizer Use Tanzania Agriculture Sample Census-2003 Tanga Appendix II 246 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 2,658 179 0 0 0 0 2,837 77,572 4 Maswa 216 325 0 0 0 0 541 43,252 1 Shinyanga Rural 3,128 701 0 0 0 201 4,030 45,263 9 Kahama 17,766 1,117 0 0 0 394 19,277 81,217 24 Bukombe 2,151 0 0 0 0 358 2,509 53,240 5 Meatu 4,355 165 0 0 0 0 4,519 31,492 14 Shinyanga Urban 539 0 0 0 32 0 571 10,198 6 Kishapu 3,751 237 80 160 0 162 4,390 35,624 12 Total 34,563 2,723 80 160 32 1,116 38,673 377,857 10 % 89.4 7.0 0.2 0.4 0.1 2.9 100.0 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 11,110 0 0 169 0 0 11,279 77,572 15 Maswa 1,291 528 0 0 0 0 1,819 43,252 4 Shinyanga Rural 6,822 1,003 0 102 0 202 8,129 45,263 18 Kahama 21,642 624 275 0 0 282 22,823 81,217 28 Bukombe 4,764 0 0 119 0 0 4,884 53,240 9 Meatu 11,409 416 0 0 0 83 11,909 31,492 38 Shinyanga Urban 2,284 0 0 0 63 31 2,377 10,198 23 Kishapu 12,891 238 0 0 0 644 13,773 35,624 39 Total 72,213 2,809 275 390 63 1,242 76,993 377,857 20 % 93.8 3.6 0.4 0.5 0.1 1.6 100 District 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 247 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 2,259 0 179 0 0 2,438 77,572 3 Maswa 324 0 0 0 0 324 43,252 1 Shinyanga Rural 2,730 102 0 0 202 3,035 45,263 7 Kahama 1,407 98 0 0 282 1,787 81,217 2 Bukombe 597 119 0 119 239 1,075 53,240 2 Meatu 3,766 0 0 0 165 3,931 31,492 12 Shinyanga Urban 693 0 0 0 30 723 10,198 7 Kishapu 2,137 0 0 0 238 2,376 35,624 7 Total 13,914 319 179 119 1,157 15,688 377,857 4 % 89 2 1 1 7 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 4,048 0 179 0 0 4,227 77,572 5 Maswa 216 0 0 0 0 216 43,252 1 Shinyanga Rural 4,236 303 0 0 100 4,639 45,263 10 Kahama 7,134 240 0 0 142 7,516 81,217 9 Bukombe 1,912 0 0 0 239 2,151 53,240 4 Meatu 3,686 0 0 0 83 3,770 31,492 12 Shinyanga Urban 1,250 0 0 32 0 1,282 10,198 13 Kishapu 4,329 0 0 0 229 4,559 35,624 13 Total 26,812 543 179 32 794 28,359 377,857 8 % 95 2 1 0 3 100 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Irrigation Technology District Mechanisation / LST 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 248 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 10,470 178 0 348 0 0 10,996 77,572 14 Maswa 1,508 203 0 0 0 0 1,711 43,252 4 Shinyanga Rural 7,525 603 0 99 0 0 8,228 45,263 18 Kahama 21,309 647 275 0 0 0 22,230 81,217 27 Bukombe 2,748 0 0 0 0 119 2,868 53,240 5 Meatu 10,553 307 0 83 0 371 11,313 31,492 36 Shinyanga Urban 2,122 27 0 15 64 0 2,229 10,198 22 Kishapu 8,847 0 0 0 0 240 9,087 35,624 26 Total 65,082 1,965 275 545 64 730 68,660 377,857 18 % 94.8 2.9 0.4 0.8 0.1 1.1 100.0 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 3,512 179 169 0 0 0 3,860 77,572 5 Maswa 210 0 0 108 0 0 318 43,252 1 Shinyanga Rural 5,538 201 0 0 0 0 5,739 45,263 13 Kahama 10,730 240 142 0 0 250 11,362 81,217 14 Bukombe 836 0 0 0 0 358 1,195 53,240 2 Meatu 5,530 0 0 0 0 407 5,937 31,492 19 Shinyanga Urban 1,280 0 0 0 32 0 1,312 10,198 13 Kishapu 5,426 0 0 0 0 226 5,652 35,624 16 Total 33,062 620 311 108 32 1,242 35,375 377,857 9 % 93.5 1.8 0.9 0.3 0.1 3.5 100 District 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region. District 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Crop Storage Vermin Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 249 Government NGO / Development Project Large Scale Farm Not applicable Total Total Bariadi 5,513 356 174 179 6,222 6,222 77,572 8 Maswa 325 0 0 0 325 325 43,252 1 Shinyanga Rural 5,230 898 99 0 6,228 6,228 45,263 14 Kahama 11,217 0 0 569 11,786 11,786 81,217 15 Bukombe 1,075 0 0 358 1,434 1,434 53,240 3 Meatu 4,982 0 78 409 5,469 5,469 31,492 17 Shinyanga Urban 1,296 0 0 32 1,327 1,327 10,198 13 Kishapu 10,848 0 81 145 11,074 11,074 35,624 31 Total 40,484 1,255 433 1,692 43,864 43,864 377,857 11.6 % 92.3 2.9 1.0 3.9 100.0 100.0 Government NGO / Development Project Cooperative Not applicable Total Total Number of households % of total number of households Bariadi 1,043 0 0 0 1,043 77,572 1 Maswa 649 203 108 0 960 43,252 2 Shinyanga Rural 4,637 201 0 0 4,838 45,263 11 Kahama 12,406 98 0 283 12,787 81,217 16 Bukombe 956 0 0 239 1,195 53,240 2 Meatu 4,779 83 0 0 4,862 31,492 15 Shinyanga Urban 747 0 0 0 747 10,198 7 Kishapu 3,755 0 80 145 3,980 35,624 11 Total 28,972 584 188 668 30,412 377,857 8.0 % 95.3 1.9 0.6 2.2 100 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source an District During the 2002/03 Agriculture Year, Shinyanga Regio District District Agro-progressing Total Number of households % of total number of households Agro-forestry 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 250 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 532 0 0 532 77,572 1 Maswa 324 0 0 324 43,252 1 Shinyanga Rural 2,022 99 102 2,223 45,263 5 Kahama 426 110 276 812 81,217 1 Bukombe 0 0 358 358 53,240 1 Meatu 219 0 333 552 31,492 2 Shinyanga Urban 152 0 0 152 10,198 1 Kishapu 242 0 0 242 35,624 1 Total 3,917 210 1,070 5,196 377,857 1 % 75 4 21 100 Government NGO / Development Project Cooperative Not applicable Total Total Total Number of households % of total number of households Bariadi 179 0 0 0 179 179 77,572 0 Maswa 649 0 108 0 757 757 43,252 2 Shinyanga Rural 605 0 0 0 605 605 45,263 1 Kahama 280 0 0 276 556 556 81,217 1 Bukombe 0 0 0 358 358 358 53,240 1 Meatu 83 0 0 333 416 416 31,492 1 Shinyanga Urban 32 30 0 0 62 62 10,198 1 Kishapu 487 0 0 0 487 487 35,624 1 Total 2,313 30 108 968 3,419 3,419 377,857 0.9 % 67.6 0.9 3.2 28.3 100.0 100.0 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District Durin the 2002/03 Agriculture Year, Shinyanga Region District District 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Beekeeping Fish Farming Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 251 Received Adopted % Received Adopted % Received Adopted % Bariadi 15,748 13,816 88 12,830 9,117 71 4,925 2,638 54 Maswa 2,252 2,144 95 1,928 1,711 89 433 433 100 Shinyanga Rural 10,406 9,393 90 5,145 1,110 22 6,034 4,120 68 Kahama 26,717 23,855 89 24,528 18,669 76 17,510 12,586 72 Bukombe 6,311 4,882 77 4,062 2,628 65 1,666 1,308 78 Meatu 14,434 10,454 72 8,391 4,265 51 7,395 1,790 24 Shinyanga Urban 3,032 1,957 65 1,168 612 52 1,161 612 53 Kishapu 17,482 14,828 10,869 3,551 7,832 1,720 455 Total 96,382 81,330 84 68,920 41,663 60 46,957 25,207 54 Received Adopted % Received Adopted % Received Adopted % Bariadi 11,029 6,113 55 2,837 1,210 43 11,632 7,659 66 Maswa 2,144 1,718 80 649 216 33 1,711 1,710 100 Shinyanga Rural 10,026 8,010 80 3,422 1,414 41 8,229 3,715 45 Kahama 20,951 17,292 83 18,995 12,215 64 22,686 16,101 71 Bukombe 4,280 2,026 47 2,031 955 47 4,884 2,146 44 Meatu 10,578 3,678 35 4,031 1,659 41 11,993 7,160 60 Shinyanga Urban 2,917 1,924 66 556 239 43 2,377 984 41 Kishapu 12,407 4,861 4,228 478 13,936 8,834 Total 74,332 45,621 61 36,748 18,387 50 77,447 48,310 62 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region District Spacing Use of Agrochemicals Erosion Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region District Organic Fertilizer Use Inorganic Fertilizer Use of Improved Seed Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 252 Received Adopted % Received Adopted % Received Adopted % Bariadi 2,438 1,896 78 3,359 1,925 57 11,353 9,930 87 Maswa 324 216 67 216 108 50 1,711 1,602 94 Shinyanga Rural 2,734 708 26 4,334 1,109 26 8,225 7,414 90 Kahama 945 562 60 7,099 5,299 75 22,502 19,834 88 Bukombe 478 1,433 300 1,195 717 60 2,748 2,390 87 Meatu 3,018 2,062 68 2,609 1,569 60 11,020 9,745 88 Shinyanga Urban 665 107 16 1,289 388 30 2,288 1,722 75 Kishapu 2,216 149 4,071 872 9,249 5,478 Total 12,818 7,133 56 24,173 11,987 50 69,096 58,115 84 Received Adopted % Received Adopted % Received Adopted % Bariadi 3,155 2,973 94 5,690 5,154 91 1,049 882 84 Maswa 318 318 100 216 325 150 960 311 32 Shinyanga Rural 5,433 4,840 89 5,919 5,430 92 4,838 3,837 79 Kahama 11,221 9,520 85 10,938 10,529 96 12,508 7,771 62 Bukombe 478 956 200 717 1,075 150 597 478 80 Meatu 5,032 5,609 111 4,313 5,388 125 4,779 2,136 45 Shinyanga Urban 1,344 707 53 1,264 891 70 689 401 58 Kishapu 5,162 3,811 10,911 9,643 3,898 481 Total 32,144 28,734 89 39,969 38,435 96 29,320 16,297 56 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region Crop Storage Irrigation Technology Mechanisation / LST District 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region District Vermin Control Agro-progressing Agro-forestry Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 253 Received Adopted % Received Adopted % Received Adopted % Bariadi 1,049 882 84 175 175 100 0 0 0 Maswa 960 311 32 324 108 33 865 649 75 Shinyanga Rural 4,838 3,837 79 2,121 503 24 605 0 0 Kahama 12,508 7,771 62 395 393 100 143 143 0 Bukombe 597 478 80 0 0 0 0 0 0 Meatu 4,779 2,136 45 498 331 67 416 250 60 Shinyanga Urban 689 401 58 152 57 38 32 0 0 Kishapu 3,898 481 80 0 162 0 Total 29,320 16,297 56 3,744 1,567 42 2,223 1,220 55 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region District Fish Farming Beekeeping Agro-forestry Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 254 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 255 Number % Number % Number % Bariadi 67,493 87 10,079 13 77,572 100 Maswa 34,293 79 8,959 21 43,252 100 Shinyanga Rural 39,760 88 5,503 12 45,263 100 Kahama 32,470 40 48,747 60 81,217 100 Bukombe 8,972 17 44,268 83 53,240 100 Meatu 24,684 78 6,808 22 31,492 100 Shinyanga Urban 6,894 68 3,305 32 10,198 100 Kishapu 31,630 89 3,994 11 35,624 100 Total 246,196 65 131,662 35 377,857 100 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Bariadi 164,800 325,542 152,258 11,115 8,374 3,985 15,399 10,160 1,405 . . . 191,314 344,077 157,648 Maswa 75,299 158,286 93,455 7,107 4,115 583 39,566 108 0 650 434 0 122,622 162,943 94,038 Shinyanga Rural 99,637 185,114 77,317 13,397 18,527 2,595 14,472 102 21 3,021 1,429 103 130,527 205,171 80,035 Kahama 85,893 131,266 64,232 15,017 18,681 5,136 26,283 4,732 0 2,025 1,450 0 129,219 156,129 69,368 Bukombe 33,230 40,729 33,883 7,126 4,020 2,419 12,166 0 0 0 0 0 52,522 44,749 36,302 Meatu 71,161 115,925 75,234 10,281 18,485 2,094 25,492 2,476 0 1,269 652 66 108,202 137,537 77,393 Shinyanga Urban 16,821 29,891 11,992 2,819 2,523 260 2,249 161 26 350 253 0 22,239 32,829 12,277 Kishapu 73,463 151,641 101,734 4,672 9,069 1,305 1,801 1,128 0 712 2,614 444 80,649 164,453 103,484 Total 620,304 1,138,393 610,105 71,535 83,794 18,377 137,428 18,868 1,451 8,027 6,832 613 837,294 1,247,888 630,546 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total 17 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District Use of Draft animals to cultivate land during 2002/03 agricultural Year Households Using Draft Animals Household Not Using Draft Animals Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 256 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Bariadi 164,800 325,542 376,077.6 11,115 8,374 9,842.6 15,399 10,160 3,469.4 . . . 191,314 344,077 389,389.6 Maswa 75,299 158,286 230,833.7 7,107 4,115 1,440.8 39,566 108 0.0 650 434 0.0 122,622 162,943 232,274.5 Shinyanga Rural 99,637 185,114 190,972.7 13,397 18,527 6,408.6 14,472 102 51.0 3,021 1,429 255.1 130,527 205,171 197,687.4 Kahama 85,893 131,266 158,652.4 15,017 18,681 12,685.9 26,283 4,732 0.0 2,025 1,450 0.0 129,219 156,129 171,338.3 Bukombe 33,230 40,729 83,691.4 7,126 4,020 5,974.2 12,166 0 0.0 0 0 0.0 52,522 44,749 89,665.7 Meatu 71,161 115,925 185,827.1 10,281 18,485 5,171.7 25,492 2,476 0.0 1,269 652 163.0 108,202 137,537 191,161.8 Shinyanga Urban 16,821 29,891 29,619.8 2,819 2,523 642.4 2,249 161 63.2 350 253 0.0 22,239 32,829 30,325.4 Kishapu 73,463 151,641 251,283.9 4,672 9,069 3,224.6 1,801 1,128 0.0 712 2,614 1,096.4 80,649 164,453 255,604.9 Total 620,304 1,138,393 1,506,958.6 71,535 83,794 45,390.8 137,428 18,868 3,583.6 8,027 6,832 1,514.5 837,294 1,247,888 1,557,447.6 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 257 Number % Number % Number % Bariadi 11,364 13.6 64,964 22.3 76,328 20.3 Maswa 7,883 9.4 35,369 12.1 43,252 11.5 Shinyanga Rural 14,532 17.3 30,221 10.4 44,753 11.9 Kahama 25,893 30.9 55,180 18.9 81,073 21.6 Bukombe 11,409 13.6 41,599 14.3 53,008 14.1 Meatu 3,941 4.7 27,089 9.3 31,030 8.3 Shinyanga Urban 3,527 4.2 6,672 2.3 10,198 2.7 Kishapu 5,295 6.3 30,329 10.4 35,624 9.5 Total 83,843 100.0 291,423 100.0 375,266 100.0 Area (Ha) % Area (Ha) % Area (Ha) % Bariadi 11,100 13.5 585 10.2 11,685 13.3 Maswa 10,298 12.5 263 4.6 10,561 12.0 Shinyanga Rural 14,035 17.1 421 7.4 14,456 16.4 Kahama 21,123 25.7 2,875 50.4 23,998 27.3 Bukombe 10,693 13.0 1,301 22.8 11,994 13.6 Meatu 6,643 8.1 7 0.1 6,650 7.6 Shinyanga Urban 3,217 3.9 41 0.7 3,257 3.7 Kishapu 5,134 6.2 214 3.7 5,348 6.1 Total 82,243 100.0 5,707 100.0 87,950 100.0 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Region During 2002/03 Agriculture Year District Organic fertilizer Application during 2002/03 Agriculture Year Households using Organic Fertilizer Households not Using Organic Fertilizer Total 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 258 CATTLE PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 259 Number % Number % Bariadi 34,951 45 42,621 55 77,572 38,084 Maswa 16,643 38 26,609 62 43,252 20,478 Shinyanga Rural 21,141 47 24,122 53 45,263 24,081 Kahama 27,522 34 53,695 66 81,217 32,009 Bukombe 13,120 25 40,120 75 53,240 18,695 Meatu 14,120 45 17,372 55 31,492 17,672 Shinyanga Urban 4,454 44 5,744 56 10,198 6,009 Kishapu 16,264 46 19,359 54 35,624 19,515 Total 148,216 39 229,641 61 377,857 176,542 Number % Number % 1-5 33,399 23 114,330 4 3 6-10 39,489 27 314,678 12 8 11-15 25,933 17 332,706 13 13 16-20 16,263 11 290,695 11 18 21-30 13,966 9 354,786 14 25 31-40 6,737 5 240,901 9 36 41-50 3,927 3 180,556 7 46 51-60 2,964 2 165,182 6 56 61-100 4,320 3 338,570 13 78 101-150 608 0 71,580 3 118 151+ 610 0 200,121 8 328 Total 148216 100 2,604,105 100 7 Number % Number % Number % Number % Regions Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total % Bulls 290,168 92.2 126 0.6 27 7.2 290,322 7.4 Cows 765,236 92.6 712 0.0 8,124 7.4 774,072 40.6 Steers 553,724 92.6 179 0.9 1,389 6.5 555,292 3.5 Heifers 406,859 93.5 . 0.0 618 6.5 407,477 22.9 Male Calves 215,035 91.8 358 0.0 403 8.2 215,796 12.5 Female Calves 360,510 91.8 . 0.0 636 8.2 361,146 13.1 Total 2,591,532 92.6 1,375 0.1 11,198 7.4 2,604,105 100.0 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year,Shinyanga Region Households Rearing Cattle Households Not Rearing Cattle 18.2: Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 District Total Agriculture households Total livestock keeping households Total Improved Beef Cattle Herd Size Cattle Rearing Households Heads of Cattle Average Number Per Household Table 18.3: Total Number of Cattle by Category and Type of Cattle; on 1st October 2003 Improved Dairy Cattle Category of cattle Indigenous Cattle Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 260 Meatu 34,772 540,920 99.3 179 537 0.0 715 3,039 0.6 35,666 544,496 20.9 Maswa 16,643 311,082 0 0.0 108 1,192 16,752 312,274 12.0 Bariadi 21,141 317,388 0 99 398 21,241 317,785 12.2 Shinyanga Rural 27,522 406,317 99.1 142 712 0.0 917 2,962 0.7 28,581 409,991 15.7 Shinyanga Urban 13,120 332,685 0 0.0 0 0.0 13,120 332,685 12.8 Kahama 14,120 332,464 0 326 1,635 14,446 334,099 12.8 Bukombe 4,201 58,903 98.5 32 126 0.0 337 759 1.3 4,570 59,788 2.3 Kishapu 16,264 291,773 0 162 1,214 16,426 292,987 11.3 Total 147,784 2,591,532 99.5 353 1,375 0.0 2,664 11,198 2 150,801 2,604,105 67 Number of Cattle Number of households Indigenous 18.4 CATTLE PRODUCTION: Total Number of Cattle by Type and District As of 1st October 2003 District % % % Number of Cattle Number of households Beef Total Cattle Dairy % Number of households Number of Cattle Number of Cattle Number of households Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 261 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi 63,559 159,166 143,830 85,604 45,127 43,634 540,920 Maswa 23,994 92,999 70,596 58,897 29,975 34,622 311,082 Shinyanga Rural 46,253 91,477 70,127 50,351 25,775 33,404 317,388 Kahama 45,137 126,373 88,913 65,366 35,447 45,080 406,317 Bukombe 29,617 69,637 30,449 46,004 18,505 138,473 332,685 Meatu 42,782 113,944 70,502 47,055 27,498 30,683 332,464 Shinyanga Urban 8,377 18,090 13,693 8,399 5,555 4,789 58,903 Kishapu 30,448 93,551 65,613 45,183 27,153 29,825 291,773 Total 290,168 765,236 553,724 406,859 215,035 360,510 2,591,532 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi . 1,430 536 537 179 358 3,039 Maswa . 1,192 . . . . 1,192 Shinyanga Rural . 398 . . . . 398 Kahama . 2,789 173 . . . 2,962 Bukombe . . . . . . . Meatu . 816 656 . . 162 1,635 Shinyanga Urban 27 286 23 81 225 116 759 Kishapu . 1,214 . . . . 1,214 Total 27 8,124 1,389 618 403 636 11,198 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi . . 179 . 358 . 537 Maswa . . . . . . . Shinyanga Rural . . . . . . . Kahama . 712 . . . . 712 Bukombe . . . . . . . Meatu . . . . . . . Shinyanga Urban 126 . . . . . 126 Kishapu . . . . . . . Total 126 712 179 0 358 0 1,375 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi 63,559 160,596 144,545 86,141 45,663 43,992 544,496 Maswa 23,994 94,191 70,596 58,897 29,975 34,622 312,274 Shinyanga Rural 46,253 91,874 70,127 50,351 25,775 33,404 317,785 Kahama 45,137 129,874 89,086 65,366 35,447 45,080 409,991 Bukombe 29,617 69,637 30,449 46,004 18,505 138,473 332,685 Meatu 42,782 114,760 71,159 47,055 27,498 30,845 334,099 Shinyanga Urban 8,531 18,376 13,716 8,480 5,780 4,905 59,788 Kishapu 30,448 94,765 65,613 45,183 27,153 29,825 292,987 Total 290,322 774,072 555,292 407,477 215,796 361,146 2,604,105 18.5: Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003 District Category - Indigenous 18.7: Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003 18.6: Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 District Number of Improved Dairy Cattle District Total Cattle District Number of Improved Beef 18.8: Total Number of Cattle by Category and District as on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 262 GOATS PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 263 Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats Bariadi 23,501 227,934 99 355 888 0 341 995 0.4 24,197 229,817 Maswa 14,269 207,202 99 215 2,157 1 0 0.0 14,484 209,359 Shinyanga Rural 15,628 154,135 100 0 0 99 199 0.1 15,727 154,334 Kahama 19,988 138,822 99 261 2,024 0 0 0.0 20,249 140,846 Bukombe 17,030 106,688 100 119 238 0 0 0.0 17,149 106,926 Meatu 13,099 214,466 99 245 984 0 137 220 0.1 13,480 215,670 Shinyanga Urban 3,654 31,171 99 81 201 1 62 62 0.2 3,797 31,434 Kishapu 14,936 189,543 100 0 0 0 0.0 14,936 189,543 Total 122,104 1,269,960 99 1,276 6,493 1 640 1,476 0.1 124,019 1,277,929 Number % Number % 1-4 34,804 28.5 98,352 7.7 2.8 5-9 41,317 33.8 270,967 21.2 6.6 10-14 19,156 15.7 216,643 17.0 11.3 15-19 9,619 7.9 158,851 12.4 16.5 20-24 9,161 7.5 192,083 15.0 21.0 25-29 2,000 1.6 51,810 4.1 25.9 30-39 3,308 2.7 105,529 8.3 31.9 40+ 2,914 2.4 183,695 14.4 63.0 Total 122,280 100.0 1,277,929.2 100.0 10.5 Total 19.1 GOAT PRODUCTION: Total Number of Goats by goat type and District as on 1st October 2003 District Indigenous Improved Dairy Improved for Meat Herd Size Goat Rearing Households Head of Goats Average per Household 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 264 Number % Number % Number % Number % Billy Goats 220,420 17 1,049 16 0 221,468 17 She Goats 63,142 5.0 1,545 23.8 115 7.8 64,802 5.1 Castrated Goat 678,195 53.4 2,552 39.3 312 21.1 681,058 53.3 Male Kid 152,433 12.0 308 4.7 177 12.0 152,919 12.0 She Kid 155,771 12.3 1,039 16.0 872 59.1 157,682 12.3 Total 1,269,960 100.0 6,493 100.0 1,476 100.0 1,277,929 100.0 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi 37,541 12,283 121,439 28,963 27,708 227,934 Maswa 31,554 10,467 108,817 26,450 29,914 207,202 Shinyanga Rural 27,369 3,714 84,206 18,521 20,324 154,135 Kahama 26,454 4,248 75,718 15,912 16,489 138,822 Bukombe 21,830 822 66,179 8,688 9,169 106,688 Meatu 41,576 18,921 103,426 25,918 24,625 214,466 Shinyanga Urban 6,403 1,815 16,494 3,171 3,288 31,171 Kishapu 27,693 10,872 101,915 24,810 24,254 189,543 Total 220,420 63,142 678,195 152,433 155,771 1,269,960 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi . . 357 . 531 888 Maswa 965 108 1,084 . . 2,157 Shinyanga Rural . . . . . . Kahama . 1,437 353 . 235 2,024 Bukombe . . 119 119 . 238 Meatu 83 . 485 166 250 984 Shinyanga Urban . . 155 23 23 201 Kishapu . . . . . . Total 1,049 1,545 2,552 308 1,039 6,493 District Type 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 Category of Goats Indigenous Goats Improved Meat Goats Improved Dairy Goats Total 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 District Number of Improved Meat Goats Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 265 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi . . . 177 817 995 Maswa . . . . . . Shinyanga Rural . . 199 . . 199 Kahama . . . . . . Bukombe . . . . . . Meatu . 83 83 . 54 220 Shinyanga Urban . 32 30 . . 62 Kishapu . . . . . . Total . 115 312 177 872 1,476 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi 37,541 12,283 121,796 29,140 29,057 229,817 Maswa 32,519 10,575 109,901 26,450 29,914 209,359 Shinyanga Rural 27,369 3,714 84,405 18,521 20,324 154,334 Kahama 26,454 5,685 76,071 15,912 16,725 140,846 Bukombe 21,830 822 66,298 8,807 9,169 106,926 Meatu 41,659 19,004 103,994 26,084 24,929 215,670 Shinyanga Urban 6,403 1,847 16,678 3,194 3,311 31,434 Kishapu 27,693 10,872 101,915 24,810 24,254 189,543 Total 221,468 64,802 681,058 152,919 157,682 1,277,929 19.7 Total Number of Goats by Category and District on 1st October 2003 District Total Goats 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 District Number of Improved Dairy Goats Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 266 SHEEP PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 267 Number % Number % Number % Ram 90,767 18 108 100 90,875 18 Castrated Sheep 34,925 7 0 34,925 7 She Sheep 285,032 55 0 285,032 55 Male Lamb 57,431 11 0 57,431 11 She Lamb 48,880 9 0 48,880 9 Total 517,036 100 108 100 517,144 100 Number % Number % Bariadi 10,251 13 67,321 87 77,572 38,084 Maswa 9,212 21 34,040 79 43,252 20,478 Shinyanga Rural 8,072 18 37,191 82 45,263 24,081 Kahama 6,923 9 74,294 91 81,217 32,009 Bukombe 2,482 5 50,758 95 53,240 18,695 Meatu 9,429 30 22,063 70 31,492 17,672 Shinyanga Urban 2,010 20 8,188 80 10,198 6,009 Kishapu 10,166 29 25,458 71 35,624 19,515 Total 58,545 15 319,312 85 377,857 176,542 Number % Number % Number % Bariadi 78,539 15 . 78,539 15 Maswa 106,861 21 108 100 106,969 21 Shinyanga Rural 53,163 10 . 53,163 10 Kahama 30,133 6 . 30,133 6 Bukombe 8,745 2 . 8,745 2 Meatu 95,895 19 . 95,895 19 Shinyanga Urban 12,403 2 . 12,403 2 Kishapu 131,296 25 . 131,296 25 Total 517,036 100 108 100 517,144 100 Number of Households Average Sheep Number of Households Average Sheep Bariadi 24,371 2 1,157 3 24,660 3 Maswa 5,569 4 188 55 5,569 6 Shinyanga Rural 3,027 8 81 1 3,027 8 Kahama 87 11 23 1 109 9 Bukombe 61 3 0 0 61 3 Meatu 640 31 0 0 640 31 Shinyanga Urban 1,314 14 97 3 1,314 14 Kishapu Total 35,068 4 1,547 10 35,381 5 Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003. Breed Number of Indigenous Sheep Number of Improved Mutton Sheep Total Sheep Total Households Raising Sheep Average number of Sheep per household Number of Improved for Mutton Sheep Total Sheep District Number of Indigenous Sheep Indigenous Sheep Improved for Mutton Sheep 20.1 Total Number of Sheep by Breed Type on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 268 Herd Size Number of Households % Number of Sheep % Average Number per Household 1-4 24,068 41 61,760 12 3 5-9 19,302 33 124,766 24 6 10-14 7,749 13 86,035 17 11 15-19 2,834 5 45,230 9 16 20-24 1,185 2 25,694 5 22 25-29 788 1 21,277 4 27 30-39 872 2 28,827 6 33 40+ 1,222 2 123,556 24 101 Total 58,021 100 517,144 100 9 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi 21,540 10,009 35,099 5,314 6,577 78,539 Maswa 15,115 7,369 49,691 23,289 11,396 106,861 Shinyanga Rural 10,997 4,574 24,802 6,953 5,837 53,163 Kahama 4,535 570 18,169 3,425 3,434 30,133 Bukombe 1,653 . 6,263 716 112 8,745 Meatu 22,200 9,071 43,529 9,635 11,462 95,895 Shinyanga Urban 2,230 534 7,815 1,003 821 12,403 Kishapu 12,497 2,799 99,663 7,097 9,241 131,296 Total 90,767 34,925 285,032 57,431 48,880 517,036 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi . . . . . 0 Maswa 108 . . . . 108 Shinyanga Rural . . . . . 0 Kahama . . . . . 0 Bukombe . . . . . . Meatu . . . . . . Shinyanga Urban . . . . . 0 Kishapu . . . . . Total 108 . . . . 108 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi 21,540 10,009 35,099 5,314 6,577 78,539 Maswa 15,223 7,369 49,691 23,289 11,396 106,969 Shinyanga Rural 10,997 4,574 24,802 6,953 5,837 53,163 Kahama 4,535 570 18,169 3,425 3,434 30,133 Bukombe 1,653 . 6,263 716 112 8,745 Meatu 22,200 9,071 43,529 9,635 11,462 95,895 Shinyanga Urban 2,230 534 7,815 1,003 821 12,403 Kishapu 12,497 2,799 99,663 7,097 9,241 131,296 Total 90,875 34,925 285,032 57,431 48,880 517,144 20.8: Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 269 Appendix II 270 PIGS PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 271 Number % Number % Bariadi 99 0 77,473 100 77,572 Maswa 0 0 43,252 100 43,252 Shinyanga Rural 0 0 45,263 100 45,263 Kahama 110 0 81,107 100 81,217 Bukombe 0 0 53,240 100 53,240 Meatu 164 1 31,328 99 31,492 Shinyanga Urban 202 2 9,974 98 10,176 Kishapu 81 0 35,542 100 35,623 Total 656 0 377,179 100 377,835 Number % Number % 1-4 521 79 1,254 38 2 5-9 112 17 684 21 6 40+ 23 4 1,328 41 57 Total 656 100 3,266 100 5 District Number of Households Number of Pigs Average per Household Bariadi 99 292 3 Kahama 110 221 2 Meatu 164 736 4 Shinyanga Urban 202 1,931 10 Kishapu 81 86 1 Total 656 3,266 5 Boars Castrated Males Sow / Gilt Male Piglets She Piglets Total Bariadi 99 . 198 . . 296 Kahama 110 . 110 . . 221 Meatu 245 . 328 163 . 736 Shinyanga Urban 272 466 451 341 402 1,931 Kishapu 82 . . . . 82 Total 807 466 1,087 503 402 3,266 21.3 Number of Households and Pigs by District on 1st October 2003 20.1 Number of Households Raising or Managing Pigs by District on 1st October 2003 District Pig Type Herd Size 21.2 Number of Households and Pigs by Herd Size on 1st October 2003 21.3 Number of Pigs by Type of Pig and District on 1st October 2003 Heads of pigs Average per Household Pig Rearing Households District Households Raising Pigs Households Not Raising Pigs Number of Agriculture Households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 272 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 273 No of Households % No of Households % Bariadi 20,832 55 17,253 45 38,084 Maswa 6,335 31 13,926 69 20,261 Shinyanga Rural 9,635 45 11,812 55 21,447 Kahama 14,856 52 13,753 48 28,609 Bukombe 6,287 34 12,407 66 18,695 Meatu 7,736 47 8,781 53 16,517 Shinyanga Urban 1,941 33 3,943 67 5,884 Kishapu 4,734 26 13,565 74 18,299 Total 72,356 43 95,440 57 167,796 No of Households % No of Households % No of Households % No of Households % Bariadi 5,643 25 18,241 29 1,943 24 679 13 Maswa 2,459 11 4,733 8 944 12 968 18 Shinyanga Rural 2,103 9 8,336 13 501 6 1,619 30 Kahama 3,473 16 13,504 22 1,091 14 541 10 Bukombe 1,759 8 5,575 9 0 0 0 0 Meatu 4,239 19 6,080 10 2,391 30 1,038 19 Shinyanga Urban 592 3 1,635 3 263 3 102 2 Kishapu 1,886 9 4,055 7 844 11 409 8 Total 22,155 100 62,159 100 7,977 100 5,355 100 No of Households % No of Households % Bariadi 29,822 84 5,793 16 35,615 Maswa 12,964 64 7,297 36 20,262 Shinyanga Rural 14,079 71 5,774 29 19,853 Kahama 22,402 74 8,068 26 30,470 Bukombe 7,564 42 10,421 58 17,985 Meatu 10,954 71 4,516 29 15,470 Shinyanga Urban 2,770 46 3,239 54 6,009 Kishapu 11,744 61 7,526 39 19,269 Total 112,299 68 52,634 32 164,933 22.1 PESTS AND PARASITES: Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year 22.3 PESTS AND PARASITE: 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year Cattle Goats Sheep Pigs District Deworming Livestock Not deworming Livestock Total District Tick problems No Tick problems Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 274 District No of Households age No of Households % No of Households % No of Households % No of Households % Bariadi 3,363 11 25,214 85 179 1 - - 1,066 4 29,822 Maswa 3,172 24 8,061 62 - - 540 4 1,190 9 12,964 Shinyanga Rural 2,207 16 8,321 59 304 2 305 2 2,941 21 14,079 Kahama 1,548 7 19,307 86 - - 286 1 1,261 6 22,402 Bukombe 478 6 6,251 83 239 3 119 2 478 6 7,564 Meatu 1,067 10 8,206 75 710 6 162 1 809 7 10,954 Shinyanga Urban 812 29 1,467 53 243 9 - - 248 9 2,770 Kishapu 1,795 15 9,224 79 82 1 162 1 481 4 11,744 Total 14,444 13 86,052 77 1,756 2 1,575 1 8,473 8 112,299 No of Households % No of Households % Bariadi 5,327 14 32,237 86 37,564 Maswa 108 1 19,722 99 19,830 Shinyanga Rural 101 0 20,232 100 20,334 Kahama 783 3 28,943 97 29,726 Bukombe 951 5 17,624 95 18,575 Meatu 6,548 41 9,430 59 15,977 Shinyanga Urban 182 3 5,674 97 5,856 Kishapu 1,297 7 17,076 93 18,374 Total 15,296 9 150,939 91 166,235 No of Households age No of Households % No of Households % No of Households % Bariadi 1,780 33 2,671 50 536 10 341 6 5,327 Maswa 108 100 0 0 0 0 0 0 108 Shinyanga Rural 101 100 0 0 0 0 0 0 101 Kahama 429 55 354 45 0 0 0 0 783 Bukombe 239 25 712 75 0 0 0 0 951 Meatu 3,502 53 2,048 31 914 14 83 1 6,548 Shinyanga Urban 86 47 96 53 0 0 0 0 182 Kishapu 734 57 564 43 0 0 0 0 1,297 Total 6,318 41 6,444 42 1,449 9 424 3 15,296 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, District Tsetse flies problems No Tsetse flies problems Total 22.6 PESTS AND PARASITE: Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. District Method of Tsetse Flies Control Total None Spray Dipping Trapping Total Method of Tsetse Flies Control Other None Spray Dipping Smearing 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 275 Appendix II 276 OTHER LIVESTOCK Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 277 Type Number % Type Number Indigenous Chicken 2,935,380 99 Ducks 94,783 Layer 11,276 0 Turkeys 708 Broiler 32,934 1 Rabbits 5,263 Donkeys 4,421 Total 2,979,590 100 105,175 Indigenous Chicken Layer Broiler Total number of chicken Shinyanga Rural 528,510 684 22,160 551,354 Meatu 304,689 4,660 . 309,349 Maswa 405,467 102 . 405,569 Bariadi 858,896 3,124 10,775 872,794 Shinyanga Urban 383,126 . . 383,126 Bukombe 227,622 1,524 . 229,146 Kahama 40,741 149 . 40,890 Kishapu 186,328 1,033 . 187,361 Total 2,935,380 11,276 32,934 2,979,590 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 23b OTHER LIVESTOCK: Number of Chicken by Category of chicken and District as of 1st October 2003 District Number of Chicken Chicken Others Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 278 Number % 1 - 4 54,834 21 156,753 3 5 - 9 82,532 32 546,340 7 10 - 19 77,801 30 999,425 13 20 - 29 25,519 10 564,268 22 30 - 39 9,060 4 285,517 32 40 - 49 2,448 1 105,425 43 50 - 99 4,350 2 263,212 61 100+ 501 0 58,649 117 Total 257,044 100 2,979,590 12 Ducks Turkeys Rabbits Donkeys Other Bariadi 53,587 179 5,263 2,170 . Maswa 9,193 . . . 1,734 Shinyanga Rural 13,516 . . 612 1,487 Kahama 5,165 . . 981 1,715 Bukombe 4,063 . . . 3,734 Meatu 2,249 497 . . 2,637 Shinyanga Urban 1,851 32 . 415 . Kishapu 5,160 . . 244 632 Total 94,783 708 5,263 4,421 11,938 1995 1999 2003 Cattle 653,549 277,000 378,338 Improved Dairy 20,420 25,675 28,127 Goats 736,727 317,924 514,620 Sheep 246,263 85,679 164,209 Pigs 1,072 2,715 6,281 Indigenous Chicken 1,670,790 735,916 1,751,278 Layers - 6,136 29,630 Broilers 2,986 22,327 7,859 Total Chickens 1,673,776 764,379 1,788,767 23f LIVESTOCK/POULTRY POPULATION TREND: SHINYANGA REGION Flock size District 23e Head Number of Other Livestock by Type of Livestock and District Type of livestock 23d OTHER LIVESTOCK: Total Number of households and chickens raised by flock size as of 1st October 2005 Chicken rearing Households Number of Chicken Average chicken by households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 279 Appendix II 280 LIVESTOCK PRODUCTS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 281 Sold Consumed / Utilised Sold Consumed / Utilised Sold Consumed / Utilised Bariadi 1,066,554 280,940 20,844 1,779 15,613 2,313 Maswa 288,733 160,572 9,891 217 10,466 2,708 Shinyanga Rural 316,508 198,516 6,162 1,222 7,237 611 Kahama 387,363 142,591 3,781 1,972 1,664 431 Bukombe 358,497 481,881 1,553 0 836 0 Meatu 77,085 66,516 28,611 1,717 34,582 1,954 Shinyanga Urban 167,661 35,079 1,730 0 1,697 94 Kishapu 484,980 104,223 15,202 800 19,027 562 Total 3,147,381 1,470,318 87,774 7,707 91,123 8,672 25.1 LIVESTOCK PRODUCTS: Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year District Product Name Eggs Hides Skins Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 282 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 283 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 4,335 0 0 0 0 0 0 4,335 Maswa 3,636 2,037 0 0 0 217 0 5,889 Shinyanga Rural 3,834 3,046 917 0 0 99 0 7,896 Kahama 3,489 3,436 144 849 1,868 1,922 0 11,707 Bukombe 119 0 0 0 0 0 0 119 Meatu 1,985 2,130 183 869 248 2,295 652 8,362 Shinyanga Urban 1,563 320 220 123 0 0 0 2,226 Kishapu 3,511 2,641 974 574 315 1,044 0 9,059 Total 22,470 13,610 2,438 2,414 2,431 5,576 652 49,592 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Bariadi 2,463 179 0 0 0 0 2,642 Maswa 1,934 108 0 0 0 0 2,042 Shinyanga Rural 2,243 204 0 0 0 0 2,447 Kahama 2,830 431 0 144 0 0 3,405 Meatu 2,417 415 167 0 220 934 4,153 Shinyanga Urban 964 127 0 0 0 0 1,090 Kishapu 4,073 78 0 0 0 0 4,152 Total 16,924 1,542 167 144 220 934 19,931 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 27,327 714 179 0 0 176 0 28,395 Maswa 6,610 1,405 541 216 0 0 0 8,772 Shinyanga Rural 8,151 1,321 404 99 296 0 99 10,371 Kahama 11,480 1,949 0 133 133 135 0 13,830 Bukombe 3,331 0 118 0 0 0 0 3,449 Meatu 9,270 576 0 0 165 79 0 10,089 Shinyanga Urban 1,578 158 0 32 0 0 32 1,800 Kishapu 8,659 82 158 0 79 0 0 8,977 Total 76,405 6,205 1,400 480 673 390 130 85,683 27.1 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Dip and District District Distance to Nearest Cattle Dip 27.2 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Spray Raced and District District Distance to Nearest Spray Raced 27.3 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hand Powered Sprayer and District District Distance to Nearest Hand Powered Sprayer Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 284 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Bariadi 3,164 3,662 0 0 179 537 7,542 Maswa 4,175 650 217 0 0 0 5,042 Shinyanga Rural 2,838 815 0 1,429 102 0 5,183 Kahama 4,098 120 0 287 0 0 4,505 Bukombe 597 118 0 0 0 0 715 Meatu 4,053 2,183 652 634 0 164 7,687 Shinyanga Urban 1,090 32 0 0 0 0 1,121 Kishapu 4,313 161 324 328 394 1,268 6,789 Total 24,328 7,740 1,193 2,678 675 1,969 38,584 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 4,134 6,261 878 2,315 3,307 5,613 163 22,672 Maswa 3,474 3,628 2,149 1,608 758 217 0 11,834 Shinyanga Rural 3,156 8,884 4,253 2,134 2,112 299 0 20,837 Kahama 4,432 8,367 1,950 5,877 3,732 1,219 137 25,714 Bukombe 2,258 2,714 2,020 358 1,785 464 0 9,600 Meatu 3,341 2,321 711 1,200 411 1,615 162 9,760 Shinyanga Urban 807 1,048 222 30 32 0 0 2,139 Kishapu 3,493 1,042 1,139 894 1,372 1,363 1,007 10,311 Total 25,096 34,266 13,322 14,416 13,509 10,789 1,469 112,868 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 2,730 1,205 2,299 708 7,064 11,347 1,609 26,962 Maswa 1,388 1,506 1,516 750 1,015 2,899 101 9,176 Shinyanga Rural 3,053 2,615 1,925 915 1,016 2,390 204 12,119 Kahama 1,387 1,272 992 1,577 2,845 2,573 1,777 12,423 Bukombe 948 836 836 119 239 119 119 3,218 Meatu 3,723 566 695 83 736 656 582 7,041 Shinyanga Urban 1,063 321 31 32 64 0 0 1,510 Kishapu 2,850 1,184 374 804 2,578 2,899 2,902 13,592 Total 17,142 9,505 8,670 4,989 15,557 22,883 7,295 86,041 27.4 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Crush and District District Distance to Nearest Cattle Crush 27.5 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Primary Market and District District Distance to Nearest Primary Market 27.6 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Secondary Market and District District Distance to Nearest Secondary Market Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 285 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 1,697 198 1,768 1,598 6,840 12,810 1,965 26,876 Maswa 1,280 2,055 1,516 750 912 1,816 860 9,190 Shinyanga Rural 2,545 102 99 816 204 1,829 3,309 8,903 Kahama 1,972 572 1,417 1,435 1,842 2,860 3,468 13,567 Bukombe 358 0 0 0 119 343 239 1,060 Meatu 2,945 0 0 0 250 2,288 304 5,787 Shinyanga Urban 1,241 390 475 186 32 0 0 2,324 Kishapu 4,242 788 372 231 407 2,654 797 9,491 Total 16,282 4,105 5,648 5,016 10,606 24,600 10,941 77,199 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 3,522 5,062 526 713 3,031 1,413 0 14,267 Maswa 5,487 1,915 1,734 430 862 1,407 108 11,942 Shinyanga Rural 2,582 7,287 4,144 99 1,187 99 0 15,398 Kahama 6,729 5,330 1,285 3,144 1,722 285 0 18,494 Bukombe 2,856 1,054 946 478 119 119 119 5,692 Meatu 2,805 1,125 498 162 1,027 4,113 539 10,268 Shinyanga Urban 1,669 489 194 0 0 0 0 2,352 Kishapu 5,268 1,664 483 888 570 565 315 9,754 Total 30,917 23,926 9,808 5,913 8,519 8,002 1,082 88,167 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 3,003 3,569 1,042 1,069 4,980 9,539 1,786 24,988 Maswa 1,403 2,704 2,167 750 921 3,020 528 11,491 Shinyanga Rural 3,815 4,330 4,139 0 1,196 1,724 0 15,204 Kahama 2,965 144 702 0 1,287 1,019 718 6,835 Bukombe 1,061 0 0 0 0 0 0 1,061 Meatu 1,029 1,338 348 162 1,435 4,910 766 9,988 Shinyanga Urban 1,263 303 285 0 0 0 0 1,851 Kishapu 4,385 710 236 492 164 816 632 7,434 Total 18,923 13,098 8,919 2,472 9,983 21,028 4,430 78,853 27.7 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Abattoir and District District Distance to Nearest Abattoir 27.8 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Slaughter Slab and District District Distance to Nearest Slaughter Slab 27.9 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hide/ Skin Shade and District District Distance to Nearest Hide/ Skin Shade Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 286 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 5,908 6,665 2,262 3,394 9,878 13,511 1,959 43,578 Maswa 1,726 2,811 3,029 430 930 2,695 101 11,722 Shinyanga Rural 3,232 3,135 3,049 408 1,212 1,809 1,590 14,436 Kahama 5,795 4,495 1,290 1,999 2,770 3,004 6,582 25,935 Bukombe 712 1,287 2,019 1,074 3,463 717 0 9,271 Meatu 1,716 655 416 0 1,036 4,164 1,433 9,420 Shinyanga Urban 1,072 710 474 284 97 0 0 2,637 Kishapu 4,793 1,276 967 1,625 408 1,770 1,035 11,873 Total 24,953 21,033 13,506 9,214 19,792 27,671 12,702 128,872 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 2,461 1,071 876 5,131 8,949 11,319 3,398 33,204 Maswa 742 3,127 2,807 433 643 3,786 434 11,971 Shinyanga Rural 2,637 502 1,918 918 605 3,120 3,412 13,112 Kahama 3,510 668 421 0 3,871 3,836 4,099 16,405 Bukombe 836 113 836 119 835 0 956 3,696 Meatu 923 404 83 0 553 4,026 1,735 7,725 Shinyanga Urban 824 392 253 0 0 0 0 1,470 Kishapu 2,863 391 480 0 327 3,056 1,951 9,067 Total 14,797 6,668 7,674 6,601 15,783 29,143 15,984 96,651 <5 5 - 9 15 - 19 30 - 49 50+ Total Bariadi 3,175 0 0 0 535 3,709 Maswa 2,158 324 0 0 0 2,482 Shinyanga Rural 2,602 0 0 0 0 2,602 Kahama 3,782 0 0 0 143 3,925 Bukombe 119 0 0 0 0 119 Meatu 1,742 0 0 1,200 0 2,942 Shinyanga Urban 963 22 32 0 0 1,017 Kishapu 4,880 0 0 952 0 5,832 Total 19,421 346 32 2,153 678 22,630 27.10 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Input Supply and District District Distance to Nearest Input Supply 27.11 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Veterinary Clinic and District District Distance to Nearest Veterinary Clinic 27.12 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Holding Gound and District District Distance to Nearest Village Holding Gound Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 287 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 18,056 5,605 175 178 0 0 0 24,014 Maswa 5,146 325 0 108 0 0 0 5,580 Shinyanga Rural 16,176 1,731 0 0 0 0 0 17,907 Kahama 27,349 1,610 131 0 144 137 0 29,371 Bukombe 4,171 358 0 0 0 0 0 4,530 Meatu 3,695 649 414 62 0 603 162 5,586 Shinyanga Urban 1,153 32 0 0 0 0 0 1,186 Kishapu 8,434 1,051 489 81 0 0 80 10,134 Total 84,182 11,361 1,208 429 144 740 242 98,306 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 7,472 1,899 530 175 178 0 0 10,254 Maswa 3,101 1,939 649 216 0 542 325 6,773 Shinyanga Rural 4,230 612 99 99 395 99 0 5,533 Kahama 4,270 991 421 0 429 144 0 6,255 Bukombe 955 0 0 0 0 0 0 955 Meatu 3,144 629 81 0 162 525 0 4,541 Shinyanga Urban 972 0 0 0 0 0 0 972 Kishapu 5,351 78 82 0 0 0 0 5,511 Total 29,494 6,148 1,862 490 1,165 1,310 325 40,794 District Distance to Nearest Drencher 27.13 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Watering Point/ Dam and District District Distance to Nearest Village Watering Point/ Dam 27.14 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Drencher and District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 288 FISH FARMING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 289 Number % Number % Number % Bariadi 0 0.0 77,572 100.0 77,572 100.0 Maswa 0 0.0 43,252 100.0 43,252 100.0 Shinyanga Rural 0 0.0 45,263 100.0 45,263 100.0 Kahama 430 0.5 80,787 99.5 81,217 100.0 Bukombe 0 0.0 53,240 100.0 53,240 100.0 Meatu 0 0.0 31,492 100.0 31,492 100.0 Shinyanga U b 0 0.0 10,198 100.0 10,198 100.0 Kishapu 0 0.0 35,624 100.0 35,624 100.0 Total 430 0.1 377,427 99.9 377,857 100.0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Number of Agricultural Households Doing Fish Farming Number of Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 290 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 291 Number % Number % Number % Bariadi 8,884 11 68,688 89 77,572 100 Maswa 1,942 4 41,310 96 43,252 100 Shinyanga Rural 6,848 15 38,415 85 45,263 100 Kahama 14,122 17 67,095 83 81,217 100 Bukombe 2,369 4 50,871 96 53,240 100 Meatu 6,208 20 25,283 80 31,492 100 Shinyanga Urban 1,403 14 8,795 86 10,198 100 Kishapu 7,957 22 27,667 78 35,624 100 Total 49,733 13 328,124 87 377,857 100 Government NGO / Development Project Bariadi 1,759 0 1,759 Maswa 434 0 434 Shinyanga Rural 2,013 0 2,013 Kahama 7,648 0 7,648 Bukombe 239 0 239 Meatu 1,202 0 1,202 Shinyanga Urban 815 23 839 Kishapu 3,146 0 3,146 Total 17,256 23 17,280 Government NGO / Development Project Bariadi 3,513 179 3,692 Maswa 650 0 650 Shinyanga Rural 3,434 298 3,732 Kahama 9,904 0 9,904 Bukombe 478 0 478 Meatu 2,686 0 2,686 Shinyanga Urban 559 82 641 Kishapu 3,539 0 3,539 Total 24,763 559 25,321 District 29.1b LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District 29.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year Source of Advice Source of Advice Total Total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year District g Households Receiving Advice g Households NOT Receiving Total Did Household receive livestock advice during 2002/03? Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 292 Government NGO / Development Project Bariadi 1,410 179 1,589 Maswa 108 0 108 Shinyanga Rural 1,611 199 1,809 Kahama 4,519 0 4,519 Bukombe 239 0 239 Meatu 1,389 0 1,389 Shinyanga Urban 323 116 439 Kishapu 2,252 0 2,252 Total 11,851 493 12,344 Government NGO / Development Project Other Bariadi 2,116 0 0 2,116 Maswa 108 0 0 108 Shinyanga Rural 2,418 199 0 2,617 Kahama 5,518 0 0 5,518 Bukombe 358 0 0 358 Meatu 2,183 0 0 2,183 Shinyanga Urban 327 143 32 502 Kishapu 2,501 0 0 2,501 Total 15,529 342 32 15,903 Government NGO / Development Project Bariadi 7,874 171 8,045 Maswa 867 0 867 Shinyanga Rural 4,726 301 5,026 Kahama 10,007 0 10,007 Bukombe 1,553 0 1,553 Meatu 5,134 0 5,134 Shinyanga Urban 1,097 54 1,151 Kishapu 6,346 0 6,346 Total 37,603 526 38,130 District Source of Advice Total Source of Advice Source of Advice Total 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District 29.1f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year Total 29.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 293 Government NGO / Development Project Other Bariadi 1,767 0 0 1,767 Maswa 434 0 0 434 Shinyanga Rural 1,914 99 0 2,014 Kahama 3,547 0 144 3,691 Bukombe 119 0 0 119 Meatu 2,666 0 79 2,745 Shinyanga Urban 360 23 0 383 Kishapu 4,106 0 81 4,187 Total 14,913 123 304 15,340 Government NGO / Development Project Large Scale Farmer Bariadi 3,698 0 0 3,698 Maswa 325 0 0 325 Shinyanga Rural 2,596 99 0 2,696 Kahama 6,321 0 0 6,321 Bukombe 358 0 0 358 Meatu 2,987 0 0 2,987 Shinyanga Urban 112 23 0 135 Kishapu 3,879 79 82 4,040 Total 20,277 202 82 20,560 Government NGO / Development Project Large Scale Farmer Bariadi 2,641 358 178 3,177 Maswa 217 108 0 325 Shinyanga Rural 1,707 298 0 2,006 Kahama 6,680 0 0 6,680 Bukombe 119 0 0 119 Meatu 1,380 0 0 1,380 Shinyanga Urban 307 54 0 361 Kishapu 2,821 0 0 2,821 Total 15,873 819 178 16,869 Source of Advice Source of Advice Source of Advice District 29.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Total Total Total 29.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year District 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 294 Government NGO / Development Project Other Bariadi 3,353 176 0 3,530 Maswa 434 0 0 434 Shinyanga Rural 2,504 199 0 2,703 Kahama 6,733 0 0 6,733 Bukombe 478 0 0 478 Meatu 1,861 83 0 1,945 Shinyanga Urban 477 82 0 559 Kishapu 2,576 0 78 2,654 Total 18,416 541 78 19,035 Government NGO / Development Project Bariadi 2,122 0 2,122 Maswa 426 108 534 Shinyanga Rural 1,314 200 1,514 Kahama 4,767 144 4,911 Bukombe 239 0 239 Meatu 2,664 0 2,664 Shinyanga Urban 602 55 657 Kishapu 2,661 0 2,661 Total 14,794 506 15,301 Source of Advice Total Source of Advice 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 295 Number % Number % Number % Number % Number % Number % Bariadi 1,223 13 7,856 85 169 2 0 0 0 0 9,248 100 Maswa 1,406 25 2,266 40 1,834 33 108 2 0 0 5,614 100 Shinyanga Rural 2,319 31 4,727 63 406 5 0 0 0 0 7,452 100 Kahama 1,899 14 10,177 75 1,116 8 393 3 0 0 13,585 100 Bukombe 239 11 1,424 67 358 17 0 0 119 6 2,141 100 Meatu 929 13 3,449 50 2,185 31 0 0 383 6 6,946 100 Shinyanga Urban 78 6 442 32 650 47 217 16 0 0 1,388 100 Kishapu 884 11 3,495 45 3,406 44 0 0 0 0 7,785 100 Total 8,979 17 33,835 62 10,125 19 719 1 503 1 54,160 100 Number % Number % Number % Number % Number % Number % Bariadi 8,884 20 8,884 20 8,884 20 8,884 20 8,884 20 44,419 100 Maswa 1,942 20 1,942 20 1,942 20 1,942 20 1,942 20 9,709 100 Shinyanga Rural 6,848 20 6,848 20 6,848 20 6,848 20 6,848 20 34,238 100 Kahama 14,122 20 13,981 20 13,981 20 13,981 20 13,981 20 70,047 100 Bukombe 2,369 20 2,369 20 2,369 20 2,369 20 2,369 20 11,847 100 Meatu 6,208 20 6,208 20 6,208 20 6,208 20 6,208 20 31,042 100 Shinyanga Urban 1,403 20 1,371 20 1,371 20 1,371 20 1,371 20 6,887 100 Kishapu 7,957 20 7,957 20 7,957 20 7,957 20 7,957 20 39,785 100 Total 49,733 20 49,560 20 49,560 20 49,560 20 49,560 20 247,974 100 29.1l LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year 29.lm LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year District Government NGO / Development Co-operative Large Scale Other Extension Provider Total District Quality of Service Total Very Good Good Average Poor No Good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 296 Number % Number % Number % Bariadi 3,996 5 73,576 95 77,572 100 Maswa 744 2 42,508 98 43,252 100 Shinyanga Rural 3,008 7 42,255 93 45,263 100 Kahama 4,687 6 76,530 94 81,217 100 Bukombe 597 1 52,643 99 53,240 100 Meatu 642 2 30,849 98 31,492 100 Shinyanga Urban 664 7 9,535 93 10,198 100 Kishapu 2,785 8 32,838 92 35,624 100 Total 17,123 5 360,735 95 377,857 100 Number % Number % Number % Bariadi 870 1 76,702 99 77,572 100 Maswa 542 1 42,710 99 43,252 100 Shinyanga Rural 102 0 45,161 100 45,263 100 Kahama 983 1 80,233 99 81,217 100 Bukombe 1,195 2 52,045 98 53,240 100 Meatu 993 3 30,498 97 31,492 100 Shinyanga Urban 140 1 10,059 99 10,198 100 Kishapu 623 2 35,001 98 35,624 100 Total 5,448 1 372,410 99 377,857 100 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Number of Agricultural Households WITH Contact Farmers / Group Members Number of Agricultural Households WITHOUT Contact Farmers / Group Members Total Did you face problems with Govt regulations during 02/03? Total 30.1 GOVERNMENT REGULATORY PROBLEMS: Number of Agricultural Households by Whether Face Problems with Governmet Regulation During 2003/04 by District, 2002/03 Agricultural Year District Yes No Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 297 Appendix II 298 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 299 Primary School Secondary School Health Clinic / Dispensar y Hospital District Capital Regional Capital Feeder Road All weather Road Tarmac Road Primary Market Secondary Market Tertiary Market Bariadi 3.1 14.9 5.2 31.7 34.0 163.9 2.4 13.9 114.0 8.5 20.7 27.9 Maswa 2.4 16.3 6.1 32.5 32.0 102.4 3.3 3.5 98.8 6.5 14.1 22.6 Shinyanga Ruralal 1.8 19.5 4.4 46.7 47.1 49.1 1.4 5.8 43.0 7.5 12.4 43.5 Kahama 2.1 21.0 11.2 44.7 44.6 147.7 1.7 8.0 35.9 6.4 15.7 40.4 Bukombe 2.4 18.7 10.7 52.2 40.3 196.3 2.0 3.9 14.8 7.2 13.5 23.3 Meatu 2.9 22.1 8.3 42.7 46.1 174.7 2.3 5.6 169.4 9.1 13.7 54.1 Shinyanga Urbanan 1.7 7.6 5.1 10.0 11.1 14.9 1.3 2.7 13.1 6.2 9.0 9.4 Kishapu 2.1 23.2 7.4 45.2 38.3 52.8 2.8 3.6 43.9 12.6 26.1 41.3 Total 2.4 18.6 7.7 40.9 39.3 130.6 2.2 7.1 68.3 7.9 16.5 34.2 Regional Capital 130.61 Tarmac Road 68.27 Hospital 40.88 District Capital 39.32 Tertiary Market 34.15 Secondary School 18.65 Secondary Market 16.48 Primary Market 7.90 Health Clinic / Dispensary 7.71 All weather Road 7.10 Primary School 2.39 Feeder Road 2.18 33.1a ACCESS TO SERVICES: Number of Agricultural Households by Distance to Services by District, 2002/03 Agricultural Year District Mean Distance to Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 300 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 17,755 23 36,621 47 22,933 30 0 0 262 0 77,572 3.1 Maswa 6,459 15 20,911 48 15,667 36 108 0 108 0 43,252 2.4 Shinyanga Rural 10,639 24 25,644 57 8,675 19 204 0 102 0 45,263 1.8 Kahama 14,915 18 43,020 53 22,433 28 848 1 0 0 81,217 2.1 Bukombe 6,541 12 29,156 55 17,304 33 0 0 239 0 53,240 2.4 Meatu 2,913 9 12,258 39 16,154 51 167 1 0 0 31,492 2.9 Shinyanga Urban 2,810 28 5,907 58 1,427 14 23 0 32 0 10,198 1.7 Kishapu 7,858 22 17,144 48 10,378 29 244 1 0 0 35,624 2.1 Total 69,889 18 190,660 50 114,971 30 1,594 0 743 0 377,857 2.4 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 178 0 4,946 6 20,598 27 30,164 39 21,686 28 77,572 14.9 Maswa 434 1 3,979 9 13,116 30 15,695 36 10,029 23 43,252 16.3 Shinyanga Rural 204 0 489 1 15,938 35 10,714 24 17,919 40 45,263 19.5 Kahama 570 1 3,669 5 17,108 21 26,228 32 33,643 41 81,217 21.0 Bukombe 232 0 239 0 13,355 25 18,767 35 20,647 39 53,240 18.7 Meatu 165 1 1,734 6 5,328 17 7,792 25 16,472 52 31,492 22.1 Shinyanga Urban 583 6 650 6 5,472 54 3,461 34 32 0 10,198 7.6 Kishapu 163 0 897 3 9,676 27 13,630 38 11,257 32 35,624 23.2 Total 2,527 1 16,603 4 100,591 27 126,451 33 131,684 35 377,857 18.6 Total Number of Households Mean Distance 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to Secondary School 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year Total Number of Households Mean District Distance to Primary School Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 301 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 5,897 8 21,799 28 43,822 56 4,808 6 1,245 2 77,572 5.2 Maswa 3,287 8 10,850 25 23,628 55 4,418 10 1,069 2 43,252 6.1 Shinyanga Rural 2,400 5 12,073 27 28,053 62 2,738 6 0 0 45,263 4.4 Kahama 5,069 6 11,141 14 44,142 54 10,552 13 10,312 13 81,217 11.2 Bukombe 1,309 2 2,390 4 28,505 54 15,547 29 5,489 10 53,240 10.7 Meatu 1,297 4 4,412 14 14,455 46 9,593 30 1,736 6 31,492 8.3 Shinyanga Urban 957 9 1,887 18 6,137 60 1,187 12 31 0 10,198 5.1 Kishapu 2,077 6 8,842 25 18,695 52 3,675 10 2,334 7 35,624 7.4 Total 22,293 6 73,393 19 207,436 55 52,519 14 22,216 6 377,857 7.7 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 177 0 338 0 4,233 5 6,795 9 66,029 85 77,572 31.7 Maswa 542 1 0 0 4,009 9 6,909 16 31,792 74 43,252 32.5 Shinyanga Rural 102 0 0 0 607 1 5,468 12 39,087 86 45,263 46.7 Kahama 0 0 133 0 6,428 8 14,535 18 60,121 74 81,217 44.7 Bukombe 717 1 0 0 2,146 4 8,014 15 42,363 80 53,240 52.2 Meatu 81 0 1,363 4 3,225 10 2,034 6 24,789 79 31,492 42.7 Shinyanga Urban 31 0 835 8 4,630 45 4,051 40 652 6 10,198 10.0 Kishapu 134 0 1,096 3 2,462 7 2,476 7 29,455 83 35,624 45.2 Total 1,784 0 3,765 1 27,740 7 50,283 13 294,286 78 377,857 40.9 Total Number of Households Mean Distance Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Distance (Kilometer) to Health Clinic Total Number of Households Mean Distance 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year 3 - 9 9 10 - 19.9 Above 20 District Distance (Kilometer) to Hospital District Less than 1 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year Above 20 1 - 2.9 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 302 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 0 0 99 0 2,623 3 6,896 9 67,955 88 77,572 34.0 Maswa 325 1 0 0 4,009 9 5,492 13 33,426 77 43,252 32.0 Shinyanga Rural 99 0 0 0 102 0 4,866 11 40,196 89 45,263 47.1 Kahama 0 0 0 0 5,858 7 10,811 13 64,548 79 81,217 44.6 Bukombe 478 1 118 0 696 1 10,544 20 41,404 78 53,240 40.3 Meatu 248 1 704 2 2,979 9 2,030 6 25,531 81 31,492 46.1 Shinyanga Urban 63 1 221 2 4,337 43 4,933 48 643 6 10,198 11.1 Kishapu 0 0 1,186 3 1,095 3 4,344 12 28,998 81 35,624 38.3 Total 1,213 0 2,329 1 21,699 6 49,916 13 302,701 80 377,857 39.3 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 715 1 0 0 178 0 709 1 75,970 98 77,572 163.9 Maswa 325 1 108 0 434 1 217 1 42,168 97 43,252 102.4 Shinyanga Rural 0 0 0 0 204 0 5,468 12 39,592 87 45,263 49.1 Kahama 948 1 133 0 143 0 144 0 79,849 98 81,217 147.7 Bukombe 2,502 5 478 1 119 0 471 1 49,670 93 53,240 196.3 Meatu 163 1 0 0 0 0 0 0 31,329 99 31,492 174.7 Shinyanga Urban 64 1 258 3 4,239 42 4,901 48 736 7 10,198 14.9 Kishapu 160 0 81 0 704 2 1,523 4 33,155 93 35,624 52.8 Total 4,877 1 1,058 0 6,022 2 13,432 4 352,468 93 377,857 130.6 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 30,610 39 24,685 32 17,464 23 4,456 6 356 0 77,572 2.4 Maswa 17,521 41 16,663 39 7,659 18 1,192 3 217 1 43,252 3.3 Shinyanga Rural 23,242 51 14,540 32 7,178 16 303 1 0 0 45,263 1.4 Kahama 43,588 54 24,624 30 10,707 13 2,155 3 144 0 81,217 1.7 Bukombe 17,091 32 28,159 53 6,920 13 956 2 114 0 53,240 2.0 Meatu 11,448 36 9,330 30 10,466 33 165 1 83 0 31,492 2.3 Shinyanga Urban 5,651 55 3,212 31 1,303 13 0 0 32 0 10,198 1.3 Kishapu 18,086 51 13,304 37 4,152 12 0 0 82 0 35,624 2.8 Total 167,236 44 134,517 36 65,849 17 9,226 2 1,029 0 377,857 2.2 Total Number of Households Mean Distance Distance (Kilometer) to Feeder Road Total Number of Households Mean Distance 10 - 19.9 Above 20 10 - 19.9 Above 20 Distance (Kilometer) to District Capital Total Number of Households Mean Distance 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to Districtal Capital District Less than 1 1 - 2.9 3 - 9 9 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 303 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 12,939 17 13,935 18 24,516 32 11,858 15 14,324 18 77,572 13.9 Maswa 10,038 23 15,504 36 13,351 31 3,935 9 424 1 43,252 3.5 Shinyanga Rural 12,094 27 7,004 15 20,110 44 3,648 8 2,408 5 45,263 5.8 Kahama 22,062 27 18,505 23 22,943 28 11,232 14 6,475 8 81,217 8.0 Bukombe 11,727 22 21,514 40 16,296 31 2,627 5 1,075 2 53,240 3.9 Meatu 5,719 18 6,806 22 13,006 41 5,795 18 166 1 31,492 5.6 Shinyanga Urban 3,222 32 3,118 31 3,278 32 580 6 0 0 10,198 2.7 Kishapu 11,200 31 10,364 29 12,021 34 1,320 4 718 2 35,624 3.6 Total 89,001 24 96,751 26 125,522 33 40,994 11 25,590 7 377,857 7.1 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 1,238 2 0 0 707 1 4,646 6 70,981 92 77,572 114.0 Maswa 2,709 6 0 0 434 1 95 0 40,014 93 43,252 98.8 Shinyanga Rural 2,162 5 101 0 0 0 4,143 9 38,858 86 45,263 43.0 Kahama 2,449 3 6,455 8 5,606 7 14,755 18 51,952 64 81,217 35.9 Bukombe 4,528 9 6,368 12 18,144 34 7,727 15 16,473 31 53,240 14.8 Meatu 1,235 4 0 0 0 0 0 0 30,256 96 31,492 169.4 Shinyanga Urban 571 6 336 3 4,207 41 4,210 41 875 9 10,198 13.1 Kishapu 5,692 16 639 2 5,636 16 1,696 5 21,960 62 35,624 43.9 Total 20,585 5 13,898 4 34,734 9 37,271 10 271,370 72 377,857 68.3 Mean Distance 10 - 19.9 Above 20 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to ALL Wealther Road Total Number of Households Mean Distance Distance (Kilometer) to Tarmac Road Total Number of Households District Less than 1 1 - 2.9 3 - 9 9 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 304 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 8,652 11 13,655 18 34,951 45 14,255 18 6,060 8 77,572 8.5 Maswa 2,231 5 10,686 25 25,149 58 3,885 9 1,300 3 43,252 6.5 Shinyanga Rural 1,882 4 7,045 16 22,495 50 12,045 27 1,795 4 45,263 7.5 Kahama 6,768 8 13,347 16 44,088 54 14,598 18 2,416 3 81,217 6.4 Bukombe 2,737 5 8,173 15 30,361 57 11,020 21 948 2 53,240 7.2 Meatu 2,070 7 2,242 7 18,891 60 5,811 18 2,477 8 31,492 9.1 Shinyanga Urban 650 6 1,725 17 6,047 59 1,554 15 223 2 10,198 6.2 Kishapu 2,186 6 4,886 14 10,003 28 10,666 30 7,882 22 35,624 12.6 Total 27,176 7 61,760 16 191,985 51 73,835 20 23,102 6 377,857 7.9 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 3,021 4 4,318 6 11,679 15 15,570 20 42,983 55 77,572 20.7 Maswa 1,244 3 4,822 11 15,383 36 13,785 32 8,017 19 43,252 14.1 Shinyanga Rural 183 0 4,166 9 18,716 41 17,095 38 5,104 11 45,263 12.4 Kahama 691 1 2,385 3 23,374 29 36,103 44 18,664 23 81,217 15.7 Bukombe 717 1 1,791 3 22,646 43 16,716 31 11,370 21 53,240 13.5 Meatu 479 2 1,746 6 11,071 35 11,143 35 7,053 22 31,492 13.7 Shinyanga Urban 633 6 715 7 5,479 54 2,531 25 840 8 10,198 9.0 Kishapu 1,379 4 2,695 8 3,032 9 6,807 19 21,711 61 35,624 26.1 Total 8,347 2 22,637 6 111,380 29 119,751 32 115,742 31 377,857 16.5 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 1,538 2 889 1 4,381 6 13,977 18 56,787 73 77,572 27.9 Maswa 650 2 1,841 4 11,117 26 8,957 21 20,687 48 43,252 22.6 Shinyanga Rural 295 1 1,278 3 3,156 7 6,080 13 34,453 76 45,263 43.5 Kahama 1,062 1 503 1 9,236 11 12,721 16 57,695 71 81,217 40.4 Bukombe 829 2 4,119 8 12,535 24 12,471 23 23,286 44 53,240 23.3 Meatu 463 1 1,451 5 1,967 6 1,791 6 25,819 82 31,492 54.1 Shinyanga Urban 556 5 273 3 5,056 50 3,483 34 831 8 10,198 9.4 Kishapu 328 1 1,920 5 3,296 9 3,817 11 26,262 74 35,624 41.3 Total 5,722 2 12,274 3 50,744 13 63,296 17 245,821 65 377,857 34.2 Total Number of Households Mean Distance District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Distance (Kilometer) to Tertiary Market Above 20 10 - 19.9 Above 20 3 - 9 9 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year 1 - 2.9 3 - 9 9 Distance (Kilometer) to Primary Market 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year Total Number of Households Mean Distance Distance (Kilometer) to Secondary Market Total Number of Households Mean Distance 10 - 19.9 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Less than 1 1 - 2.9 District Less than 1 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 305 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 0 0 1,993 3 178 0 1,071 1 7,639 10 5,800 7.8 57,562 78 74,244 151.8 Maswa 3,467 8 6,133 15 4,404 11 864 2 2,119 5 9,499 23.0 14,841 36 41,328 47.9 Shinyanga Rural 300 1 102 0 2,536 6 2,835 6 2,416 5 14,243 32.2 21,733 49 44,166 50.7 Kahama 4,927 6 7,181 9 4,708 6 6,768 9 9,181 12 11,074 14.0 35,517 45 79,356 50.1 Bukombe 4,894 9 453 1 1,912 4 0 0 3,100 6 118 0.2 41,336 80 51,813 100.1 Meatu 492 2 3,145 10 1,022 3 968 3 2,423 8 6,178 20.2 16,358 53 30,587 83.5 Shinyanga Urban 681 7 2,136 22 534 6 31 0 0 0 0 0.0 6,211 65 9,592 51.5 Kishapu 3,065 9 625 2 2,346 7 81 0 1,466 4 10,264 28.8 17,778 50 35,624 51.5 Total 17,825 5 21,767 6 17,641 5 12,617 3 28,345 8 57,177 15.6 211,337 58 366,709 80.8 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 520 1 2,767 4 4,227 6 3,735 5 22,289 31 25,035 34.8 13,346 19 71,919 49.3 Maswa 3,468 8 6,135 15 4,192 10 1,730 4 3,622 9 12,861 30.7 9,933 24 41,940 37.1 Shinyanga Rural 302 1 303 1 2,530 6 2,835 6 2,623 6 14,846 33.1 21,416 48 44,855 49.5 Kahama 3,262 5 13,711 19 4,371 6 5,549 8 3,291 5 2,239 3.1 38,770 54 71,193 50.1 Bukombe 1,553 3 3,748 7 4,439 8 5,239 10 6,327 12 8,421 16.1 22,690 43 52,416 85.3 Meatu 220 1 4,482 15 1,382 5 1,292 4 2,668 9 6,919 22.8 13,364 44 30,328 44.0 Shinyanga Urban 684 8 1,576 19 90 1 31 0 0 0 0 0.0 6,094 72 8,476 33.0 Kishapu 2,284 7 2,503 8 2,081 6 1,638 5 1,142 4 9,615 29.7 13,102 40 32,365 39.7 Total 12,294 3 35,225 10 23,312 7 22,048 6 41,962 12 79,937 22.6 138,715 39 353,493 51.4 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center District Distance (Kilometer) to Veterinary Clinic Mean Distance Mean Distance Distance (Kilometer) to Extension Center District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 306 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 179 0 0 0 0 0 178 0 179 0 0 0.0 77,036 99 77,572 192.1 Maswa 3,468 8 0 0 108 0 0 0 189 0 744 1.7 38,742 90 43,252 146.9 Shinyanga Rural 201 0 0 0 100 0 0 0 305 1 3,260 7.2 41,396 91 45,263 149.5 Kahama 427 1 0 0 0 0 0 0 0 0 133 0.2 80,657 99 81,217 263.6 Bukombe 358 1 0 0 0 0 0 0 0 0 0 0.0 52,882 99 53,240 318.7 Meatu 489 2 0 0 0 0 0 0 0 0 0 0.0 30,940 98 31,429 253.5 Shinyanga Urban 1,868 19 992 10 0 0 0 0 30 0 0 0.0 6,970 71 9,860 146.4 Kishapu 2,594 7 0 0 810 2 80 0 651 2 82 0.2 31,406 88 35,624 170.1 Total 9,584 3 992 0 1,019 0 258 0 1,355 0 4,219 1.1 360,030 95 377,457 216.8 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 178 0 177 0 0 0 348 0 353 0 76,516 99 77,572 192.8 Maswa 3,468 8 0 0 108 0 95 0 108 0 39,473 91 43,252 147.6 Shinyanga Rural 611 1 0 0 0 0 101 0 3,362 7 41,088 91 45,161 145.5 Kahama 571 1 0 0 0 0 0 0 418 1 80,228 99 81,217 258.3 Bukombe 358 1 0 0 118 0 238 0 0 0 52,526 99 53,240 312.2 Meatu 572 2 0 0 0 0 0 0 83 0 30,836 98 31,492 250.0 Shinyanga Urban 1,778 18 1,022 10 0 0 0 0 0 0 7,026 72 9,826 145.4 Kishapu 2,342 7 0 0 485 1 733 2 164 0 31,900 90 35,624 172.2 Total 9,878 3 1,200 0 711 0 1,513 0 4,488 1 359,592 95 377,383 214.4 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year Distance (Kilometer) to Plant Protection Lab 50 + 30 - 49 20 - 29 10 - 14 5 - 9 <5 Mean Distance District District Distance (Kilometer) to Research Station Mean Distance Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 307 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 346 0 1,082 1 3,698 5 3,556 5 22,834 30 36,025 47 8,573 11 76,113 33.5 Maswa 2,700 6 4,334 10 2,811 7 969 2 4,542 11 21,845 51 5,942 14 43,144 40.7 Shinyanga Rural 201 0 204 0 1,631 4 3,037 7 3,727 8 18,371 41 18,092 40 45,263 48.9 Kahama 417 1 2,716 3 3,110 4 7,640 9 13,550 17 24,131 30 29,281 36 80,846 44.0 Bukombe 239 0 119 0 7,545 14 3,568 7 9,546 18 9,803 18 22,420 42 53,240 40.7 Meatu 162 1 2,395 8 329 1 1,541 5 3,167 11 8,687 29 13,757 46 30,039 46.5 Shinyanga Urban 652 7 2,192 23 594 6 784 8 0 0 5,301 56 0 0 9,522 25.2 Kishapu 1,218 3 547 2 1,198 3 0 0 1,374 4 17,951 50 13,335 37 35,624 50.1 Total 5,935 2 13,589 4 20,916 6 21,095 6 58,741 16 142,115 38 111,401 30 373,792 41.9 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 163 0 10,367 14 5,904 8 11,208 15 7,102 10 533 1 39,127 53 74,405 91.1 Maswa 3,792 9 3,901 9 1,299 3 541 1 419 1 4,327 10 28,756 67 43,035 75.4 Shinyanga Rural 604 2 7,767 19 8,193 20 1,186 3 3,089 8 3,464 9 15,690 39 39,992 44.6 Kahama 10,620 13 565 1 110 0 566 1 2,378 3 1,998 2 64,980 80 81,217 127.3 Bukombe 5,490 10 119 0 236 0 1,314 2 119 0 0 0 45,841 86 53,121 164.6 Meatu 847 3 1,367 4 4,009 13 774 2 1,672 5 4,381 14 18,027 58 31,077 117.9 Shinyanga Urban 1,558 16 1,040 11 472 5 0 0 30 0 0 0 6,475 68 9,575 66.7 Kishapu 3,246 9 78 0 1,958 5 328 1 1,061 3 6,876 19 22,077 62 35,624 84.3 Total 26,320 7 25,205 7 22,181 6 15,917 4 15,871 4 21,578 6 240,972 65 368,045 102.8 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center 10 - 14 5 - 9 <5 Mean Distance Mean Distance Distance (Kilometer) to Livestock Development Center 50 + 30 - 49 20 - 29 15 - 19 10 - 14 5 - 9 <5 50 + 30 - 49 20 - 29 15 - 19 District District Distance (Kilometer) to Land Registration Office Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 308 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 2,110 8 10,808 40 7,582 28 3,934 15 2,311 9 26,745 Maswa 2,273 8 4,287 16 13,730 50 4,969 18 2,250 8 27,509 Shinyanga Rural 2,028 14 1,302 9 4,007 27 2,640 18 4,668 32 14,645 Kahama 1,350 1 24,852 25 11,230 11 29,070 30 31,959 32 98,461 Bukombe 1,538 5 3,784 13 3,565 13 16,353 57 3,215 11 28,455 Meatu 672 2 4,566 12 4,146 11 15,303 41 12,883 34 37,570 Shinyanga Urban 95 3 2,362 72 731 22 92 3 0 0 3,281 Kishapu 568 2 3,965 11 8,647 25 11,996 34 9,761 28 34,937 Total 10,634 4 55,927 21 53,637 20 84,358 31 67,047 25 271,602 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 884 9 6,752 69 1,411 14 452 5 357 4 9,855 Maswa 541 10 2,145 39 2,029 36 528 9 325 6 5,568 Shinyanga Rural 306 13 102 4 808 33 306 13 914 38 2,436 Kahama 787 5 6,226 38 2,826 17 1,786 11 4,688 29 16,312 Bukombe 358 5 2,647 35 1,432 19 2,744 36 357 5 7,538 Meatu 136 2 1,768 23 937 12 2,317 30 2,623 34 7,781 Shinyanga Urban 0 0 864 63 484 35 31 2 0 0 1,379 Kishapu 82 1 3,277 37 1,956 22 2,040 23 1,613 18 8,968 Total 3,094 5 23,780 40 11,883 20 10,203 17 10,877 18 59,838 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 529 17 154 5 1,237 39 889 28 357 11 3,166 Maswa 108 3 0 0 2,044 53 1,300 33 434 11 3,885 Shinyanga Rural 204 11 102 6 102 6 711 39 710 39 1,829 Kahama 141 1 4,147 26 2,475 15 4,937 31 4,398 27 16,098 Bukombe 0 0 119 3 474 12 2,747 70 596 15 3,936 Meatu 0 0 161 4 411 10 2,188 54 1,316 32 4,076 Shinyanga Urban 0 0 152 83 0 0 31 17 0 0 182 Kishapu 0 0 0 0 1,142 23 2,041 42 1,695 35 4,877 Total 982 3 4,836 13 7,884 21 14,842 39 9,505 25 38,049 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Very Good Good Average Poor No good Total number of households Satisfaction of Using Veterinary Clinic District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 309 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 350 14 179 7 1,058 43 536 22 357 14 2,479 Maswa 108 3 108 3 2,044 50 1,408 34 426 10 4,094 Shinyanga Rural 306 17 0 0 0 0 711 39 812 44 1,829 Kahama 141 1 4,061 25 2,648 16 4,850 30 4,398 27 16,098 Bukombe 112 3 119 3 354 9 2,747 70 596 15 3,929 Meatu 83 2 83 2 333 8 2,190 54 1,392 34 4,080 Shinyanga Urban 30 20 121 80 0 0 0 0 0 0 152 Kishapu 161 3 0 0 1,142 24 1,796 38 1,613 34 4,713 Total 1,291 3 4,671 12 7,579 20 14,238 38 9,594 26 37,374 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 174 4 1,060 27 1,408 36 710 18 531 14 3,885 Maswa 108 2 325 7 2,785 62 866 19 424 9 4,508 Shinyanga Rural 908 33 101 4 606 22 303 11 812 30 2,729 Kahama 0 0 7,788 37 1,694 8 4,946 23 6,762 32 21,191 Bukombe 239 5 540 11 593 13 2,866 61 477 10 4,715 Meatu 210 2 1,430 16 1,291 14 3,597 40 2,384 27 8,912 Shinyanga Urban 32 10 244 72 63 19 0 0 0 0 339 Kishapu 81 1 162 3 1,878 32 2,120 36 1,613 28 5,855 Total 1,753 3 11,650 22 10,318 20 15,409 30 13,004 25 52,134 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 0 0 715 27 1,233 46 357 13 357 13 2,661 Maswa 325 9 324 9 2,152 62 434 13 217 6 3,452 Shinyanga Rural 102 3 997 31 1,183 37 204 6 710 22 3,196 Kahama 282 3 1,145 12 566 6 1,700 17 6,205 63 9,897 Bukombe 232 6 119 3 354 9 2,627 69 477 13 3,809 Meatu 79 1 333 5 841 13 2,437 39 2,623 42 6,313 Shinyanga Urban 32 13 182 74 31 13 0 0 0 0 245 Kishapu 163 3 0 0 1,142 23 1,878 38 1,695 35 4,877 Total 1,214 4 3,816 11 7,502 22 9,637 28 12,283 36 34,451 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 310 No good No of Households % No of Households % No of Households % No of Households % No of Households 10,634 4 55,927 21 53,637 20 84,358 31 67,047 3,094 5 23,780 40 11,883 20 10,203 17 10,877 982 3 4,836 13 7,884 21 14,842 39 9,505 1,291 3 4,671 12 7,579 20 14,238 38 9,594 1,753 3 11,650 22 10,318 20 15,409 30 13,004 1,214 4 3,816 11 7,502 22 9,637 28 12,283 4 21.214 20.02 30.13 Extension Centre Veterinary Clinic OVERALL % Livestock Development Centre Land Registration Office Plant Protection Lab Research Station TYPE OF SERVICE LEVEL OF SATISFACTION OF THE SERVICE Very Good Good Average Poor 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 311 Appendix II 312 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 313 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Number of Households Bariadi 9,310 1,764 65,608 533 356 77,572 Maswa 5,344 851 36,651 405 - 43,252 Shinyanga Rural 4,145 2,920 38,005 91 102 45,263 Kahama 16,227 3,866 60,927 197 - 81,217 Bukombe 4,398 1,912 46,691 239 - 53,240 Meatu 892 897 29,353 350 - 31,492 Shinyanga Urban 473 76 9,244 390 15 10,198 Kishapu 2,714 400 32,266 244 0 35,624 Total 43,503 12,686 318,745 2,450 474 377,857 % 11.0 0.7 86.5 1.8 0.1 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Bariadi 3 49,428 333 0 0 17,850 8,371 1,590 77,572 Maswa 3 10,796 217 0 0 6,687 25,552 0 43,252 Shinyanga Rural 3 7,831 200 0 0 24,754 12,477 0 45,263 Kahama 2 23,036 381 123 0 53,009 4,557 110 81,217 Bukombe 2 18,127 239 119 0 23,166 11,588 0 53,240 Meatu 3 8,751 572 0 244 3,867 18,059 0 31,492 Shinyanga Urban 3 2,405 31 0 0 1,575 6,188 0 10,198 Kishapu 3 5,055 82 0 814 1,607 28,066 0 35,624 Total 3 125,429 2,054 243 1,058 132,516 114,858 1,700 377,857 % 33.2 0.5 0.1 0.3 35.1 30.4 0.4 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Bariadi 3 64 0 0 0 23 11 2 100 Maswa 3 25 1 0 0 15 59 0 100 Shinyanga Rural 3 17 0 0 0 55 28 0 100 Kahama 2 28 0 0 0 65 6 0 100 Bukombe 2 34 0 0 0 44 22 0 100 Meatu 3 28 2 0 1 12 57 0 100 Shinyanga Urban 3 24 0 0 0 15 61 0 100 Kishapu 3 14 0 0 2 5 79 0 100 Total 3 33 1 0 0 35 30 0 100 % 33.2 0.5 0.1 0.3 35.1 30.4 0.4 100.0 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year District Type of Toilet 34.2B Percent of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year 34.2A Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year District Average Number of Rooms per Household Type of Roofing Material District Type of Roofing Material Average Number of Rooms per Household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 314 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Radio 35,698 19,852 23,650 43,003 32,301 13,930 6,001 17,816 192,251 Landline phone 154 189 98 0 119 141 77 80 858 Mobile phone 1,352 297 788 1,541 0 1,186 317 244 5,725 Iron 12,880 6,915 5,969 16,974 6,289 6,936 2,096 6,390 64,449 Wheelbarrow 5,655 4,265 8,757 8,950 2,388 3,495 1,047 4,836 39,393 Bicycle 48,792 26,632 30,282 54,571 36,154 20,598 6,738 22,764 246,531 Vehicle 1,051 541 503 977 353 286 217 307 4,236 Television / Video 1,059 412 506 837 119 397 200 162 3,692 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Radio 46 46 52 53 61 44 59 50 Landline phone 0 0 0 0 0 0 1 0 Mobile phone 2 1 2 2 0 4 3 1 Iron 17 16 13 21 12 22 21 18 Wheelbarrow 7 10 19 11 4 11 10 14 Bicycle 63 62 67 67 68 65 66 64 Vehicle 1 1 1 1 1 1 2 1 Television / Video 1 1 1 1 0 1 2 0 Type of Owned Asset District Total District Type of Owned Asse 34.3 Propotion of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 315 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 792 290 301 137 478 329 158 0 2,485 Solar 175 0 0 0 119 0 0 149 443 Gas (Biogas) 179 108 100 0 0 0 30 81 498 Hurricane Lamp 11,469 6,820 4,262 12,961 6,049 5,340 2,206 5,125 54,233 Pressure Lamp 2,296 1,732 708 3,140 1,193 249 404 2,492 12,214 Wick Lamp 61,260 33,544 39,083 63,503 44,923 25,183 7,337 27,290 302,123 Candles 0 0 301 284 119 81 0 0 785 Firewood 1,402 757 508 1,192 358 310 32 486 5,044 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,491 10,166 35,624 377,825 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 1 1 1 0 1 1 2 0 1 Solar 0 0 0 0 0 0 0 0 0 Gas (Biogas) 0 0 0 0 0 0 0 0 0 Hurricane Lamp 15 16 9 16 11 17 22 14 14 Pressure Lamp 3 4 2 4 2 1 4 7 3 Wick Lamp 79 78 86 78 84 80 72 77 80 Candles 0 0 1 0 0 0 0 0 0 Firewood 2 2 1 1 1 1 0 1 1 Total 100 100 100 100 100 100 100 100 100 34.4a Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year District Main Source of Energy for Lighting Main Source of Energy for Lighting District 34.4b Proportion of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 316 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 349 0 101 0 0 0 31 82 562 Gas (Biogas) 178 0 0 0 0 0 0 0 178 Bottled Gas 0 0 102 267 119 83 92 0 663 Parraffin / Kerocine 154 95 0 0 0 83 47 0 379 Charcoal 1,142 2,737 888 5,213 1,431 1,193 990 1,056 14,650 Firewood 74,864 40,205 44,172 75,465 51,212 29,008 8,931 34,162 358,020 Crop Residues 0 215 0 273 478 1,125 78 245 2,413 Livestock Dung 885 0 0 0 0 0 30 79 993 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 377,857 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 0 0 0 0 0 0 0 0 0 Gas (Biogas) 0 0 0 0 0 0 0 0 0 Bottled Gas 0 0 0 0 0 0 1 0 0 Parraffin / Kerocine 0 0 0 0 0 0 0 0 0 Charcoal 1 6 2 6 3 4 10 3 4 Firewood 97 93 98 93 96 92 88 96 95 Crop Residues 0 0 0 0 1 4 1 1 1 Livestock Dung 1 0 0 0 0 0 0 0 0 Total 100 100 100 100 100 100 100 100 100 District 34.5b Proportion of Agriculture Households by Main Source of Energy Used for Cooking and District during 2002/03 Agricultural Year 34.5a Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Main Source of Energy for Lighting District District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 317 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatunyanga Urban Kishapu Wet 13,845 3,456 4,621 9,580 6,683 3,918 2,114 1,588 Dry 14,006 6,160 4,217 9,449 6,805 3,837 2,081 1,520 Wet 33,369 12,022 5,546 24,020 8,315 9,153 4,219 1,118 Dry 34,233 16,857 6,653 24,188 8,194 9,322 4,365 1,033 Wet 881 325 505 1,991 1,044 165 92 - Dry 704 433 507 1,989 924 249 184 632 Wet 14,145 11,025 14,113 38,002 32,544 3,855 1,605 11,085 Dry 11,505 5,408 15,316 38,990 32,424 4,388 1,747 8,902 Wet 5,605 1,081 3,916 2,849 597 700 278 399 Dry 4,723 1,183 4,418 4,080 956 83 278 1,198 Wet 8,503 9,824 12,315 1,884 357 13,028 1,423 14,941 Dry 11,867 10,829 12,837 1,466 357 13,188 1,452 17,933 Wet 175 95 0 131 239 166 32 1,534 Dry 0 108 101 0 239 166 0 1,122 Wet 1,049 4,412 4,046 2,512 1,314 250 406 4,959 Dry 534 2,274 1,018 697 1,075 83 32 3,284 Wet 0 0 0 247 0 94 30 - Dry 0 0 0 357 0 94 30 - Wet 0 0 0 0 0 81 0 - Dry 0 0 98 0 0 81 31 - Wet 0 1,013 201 0 2,147 81 0 - Dry 0 0 99 0 2,266 0 0 - Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 18 8 10 12 13 12 21 4 Dry 18 14 9 12 13 12 20 4 Wet 43 28 12 30 16 29 41 3 Dry 44 39 15 30 15 30 43 3 Wet 1 1 1 2 2 1 1 - Dry 1 1 1 2 2 1 2 2 Wet 18 25 31 47 61 12 16 31 Dry 15 13 34 48 61 14 17 25 Wet 7 3 9 4 1 2 3 1 Dry 6 3 10 5 2 0 3 3 Wet 11 23 27 2 1 41 14 42 Dry 15 25 28 2 1 42 14 50 Wet 0 0 - 0 0 1 0 4 Dry - 0 0 - 0 1 - 3 Wet 1 10 9 3 2 1 4 14 Dry 1 5 2 1 2 0 0 9 Wet - - - 0 - 0 0 - Dry - - - 0 - 0 0 - Wet - - - - - 0 - - Dry - - 0 - - 0 0 - Wet - 2 0 - 4 0 - - Dry - - 0 - 4 - - - Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Piped Water Protected Well Protected / Covered Spring District 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season Season Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well District 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Piped Water Other Tanker Truck Water Vendor Uncovered Rainwater Catchment Covered Rainwater Catchment Source Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 318 Bariadi Maswa Shinyanga R Kahama Bukombe Meatu Shinyanga UKishapu Wet 2,122 7,076 4,036 15,978 5,329 2,719 2,049 3,054 Dry 2,462 3,380 1,612 13,805 4,498 1,305 1,847 1,193 Wet 8,588 4,863 4,154 5,109 2,146 1,147 498 1,772 Dry 7,892 2,589 1,820 4,343 2,151 496 428 632 Wet 5,137 2,600 599 3,819 956 1,643 226 723 Dry 5,137 1,950 200 3,054 717 1,487 226 401 Wet 22,949 9,040 12,408 15,473 6,801 4,638 1,941 4,858 Dry 20,329 4,708 5,685 14,495 6,562 3,790 1,540 1,495 Wet 27,509 12,325 18,253 27,255 20,646 12,157 4,325 13,961 Dry 25,913 17,184 17,227 26,192 19,572 10,763 4,236 9,039 Wet 7,588 5,633 4,406 8,750 14,502 5,213 620 6,096 Dry 9,525 8,301 8,344 10,314 14,251 6,245 872 6,351 Wet 3,330 1,066 1,102 4,375 2,503 2,972 453 4,231 Dry 5,083 4,065 5,051 5,536 3,220 4,718 869 7,000 Wet 350 650 305 458 358 1,002 86 850 Dry 1,231 1,074 5,324 3,478 2,270 2,388 181 8,229 Wet - - - - - - - 80 Dry - - - - - 299 - 1,285 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga R Kahama Bukombe Meatu Shinyanga UKishapu Wet 3 16 9 20 10 9 20 9 Dry 3 8 4 17 8 4 18 3 Wet 11 11 9 6 4 4 5 5 Dry 10 6 4 5 4 2 4 2 Wet 7 6 1 5 2 5 2 2 Dry 7 5 0 4 1 5 2 1 Wet 30 21 27 19 13 15 19 14 Dry 26 11 13 18 12 12 15 4 Wet 35 28 40 34 39 39 42 39 Dry 33 40 38 32 37 34 42 25 Wet 10 13 10 11 27 17 6 17 Dry 12 19 18 13 27 20 9 18 Wet 4 2 2 5 5 9 4 12 Dry 7 9 11 7 6 15 9 20 Wet 0 2 1 1 1 3 1 2 Dry 2 2 12 4 4 8 2 23 Wet - - - - - - - 0 Dry - - - - - 1 - 4 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 319 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 347 1,703 502 3,116 1,424 737 774 1,129 Dry 844 581 505 2,701 1,190 162 729 233 Wet 14,526 7,415 6,404 18,498 7,824 3,762 1,140 6,305 Dry 10,690 3,631 2,788 13,888 6,156 2,480 954 3,136 Wet 9,781 4,535 6,337 12,756 3,778 2,323 1,089 3,981 Dry 8,546 3,455 3,125 10,587 3,181 1,543 868 1,636 Wet 26,034 11,048 15,193 26,116 20,944 7,041 3,943 10,150 Dry 21,313 8,789 10,558 23,480 18,435 5,434 3,369 6,300 Wet 8,561 2,922 4,645 4,607 3,323 4,100 1,232 1,977 Dry 7,466 2,491 4,245 5,188 3,437 3,536 1,202 1,008 Wet 2,573 3,438 3,736 2,416 1,307 1,528 243 857 Dry 2,768 2,356 1,191 2,609 2,496 1,894 273 553 Wet 15,750 12,190 8,445 13,708 14,641 12,001 1,777 11,224 Dry 25,945 21,949 22,851 22,764 18,344 16,443 2,804 22,759 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 0 4 1 4 3 2 8 3 Dry 1 1 1 3 2 1 7 1 Wet 19 17 14 23 15 12 11 18 Dry 14 8 6 17 12 8 9 9 Wet 13 10 14 16 7 7 11 11 Dry 11 8 7 13 6 5 9 5 Wet 34 26 34 32 39 22 39 28 Dry 27 20 23 29 35 17 33 18 Wet 11 7 10 6 6 13 12 6 Dry 10 6 9 6 6 11 12 3 Wet 3 8 8 3 2 5 2 2 Dry 4 5 3 3 5 6 3 2 Wet 20 28 19 17 27 38 17 32 Dry 33 51 50 28 34 52 27 64 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 320 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 714 9 1,607 20 1,715 21 561 7 956 12 2,310 28 71 1 239 3 8,173 2.2 Two 48,466 29 13,758 8 14,494 9 34,903 21 38,793 23 9,744 6 2,537 2 4,352 3 167,046 44.2 Three 28,038 14 27,886 14 28,952 14 45,609 23 13,492 7 19,229 10 7,527 4 30,870 15 201,603 53.4 Four 353 34 0 0 102 10 144 14 0 0 209 20 64 6 163 16 1,035 0.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 714 1 1,607 4 1,715 4 561 1 956 2 2,310 7 71 1 239 1 8,173 2.2 Two 48,466 62 13,758 32 14,494 32 34,903 43 38,793 73 9,744 31 2,537 25 4,352 12 167,046 44.2 Three 28,038 36 27,886 64 28,952 64 45,609 56 13,492 25 19,229 61 7,527 74 30,870 87 201,603 53.4 Four 353 0 0 0 102 0 144 0 0 0 209 1 64 1 163 0 1,035 0.3 Total 77,572 100 43,252 100 45,263 100 81,217 100 53,240 100 31,492 100 10,198 100 35,624 100 377,857 100.0 63 36 36 44 75 38 26 13 46 Bukombe Meatu Bariadi Maswa Shinyanga Rural Kahama One and Two Two Meals Per Day Bukombe Meatu Shinyanga Urban 34.12B Number of Households by Number of Meals the Household Normally Took per Day by District Kishapu Total Number of Meals per Day District Shinyanga Urban Kishapu 34.12A Number of Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day District Total Bariadi Maswa Shinyanga Rural Kahama Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 321 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 48,154 29 24,829 15 20,071 12 27,827 17 12,744 8 13,263 8 4,524 3 12,325 8 163,738 43.3 One 18,863 16 10,575 9 16,218 13 26,425 22 24,736 20 9,431 8 3,547 3 11,315 9 121,110 32.1 Two 7,940 12 5,003 8 7,083 11 19,653 30 10,688 16 6,828 10 1,383 2 7,879 12 66,457 17.6 Three 1,914 10 2,111 11 1,085 6 5,686 31 3,201 17 959 5 409 2 3,096 17 18,460 4.9 Four 353 8 521 11 302 7 829 18 1,407 30 589 13 266 6 362 8 4,629 1.2 Five 348 16 107 5 99 5 516 24 344 16 246 11 0 0 484 23 2,143 0.6 Six 0 0 0 0 102 38 0 0 119 45 0 0 46 17 0 0 268 0.1 Seven 0 0 107 10 303 29 280 27 0 0 177 17 23 2 163 15 1,052 0.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 48,154 62 24,829 57 20,071 44 27,827 34 12,744 24 13,263 42 4,524 44 12,325 35 163,738 43.3 One 18,863 24 10,575 24 16,218 36 26,425 33 24,736 46 9,431 30 3,547 35 11,315 32 121,110 32.1 Two 7,940 10 5,003 12 7,083 16 19,653 24 10,688 20 6,828 22 1,383 14 7,879 22 66,457 17.6 Three 1,914 2 2,111 5 1,085 2 5,686 7 3,201 6 959 3 409 4 3,096 9 18,460 4.9 Four 353 0 521 1 302 1 829 1 1,407 3 589 2 266 3 362 1 4,629 1.2 Five 348 0 107 0 99 0 516 1 344 1 246 1 0 0 484 1 2,143 0.6 Six 0 0 0 0 102 0 0 0 119 0 0 0 46 0 0 0 268 0.1 Seven 0 0 107 0 303 1 280 0 0 0 177 1 23 0 163 0 1,052 0.3 Total 77,572 100 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 34.13A Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Bariadi Shinyanga Urban Kishapu Maswa Number of Days District Bariadi Maswa Shinyanga Rural Meatu Shinyanga Rural Kahama Bukombe Meatu Total Kishapu Kahama Bukombe Shinyanga Urban 34.13B Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 322 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 40,053 47 33,048 11 30,037 11 47,995 1 7,625 1 19,647 20 4,819 9 19,103 9 202,328 53.5 One 15,442 45 6,223 13 7,786 12 18,589 2 24,634 2 6,311 15 3,351 11 7,779 11 90,113 23.8 Two 10,611 39 2,621 16 2,914 16 9,235 2 10,153 2 4,567 17 1,283 8 5,656 8 47,041 12.4 Three 7,104 28 511 18 2,214 20 3,770 3 5,835 3 419 21 458 7 2,146 7 22,457 5.9 Four 2,328 29 533 14 1,512 23 824 4 2,134 3 209 21 255 6 559 6 8,354 2.2 Five 974 16 208 26 295 25 669 6 2,268 4 127 16 0 7 230 7 4,772 1.3 Six 706 13 0 26 403 28 0 5 119 3 0 22 32 2 81 2 1,343 0.4 Seven 352 15 108 29 102 28 133 9 472 5 212 12 0 2 70 2 1,449 0.4 Total 77,572 33 43,252 17 45,263 19 81,217 3 53,240 3 31,492 18 10,198 7 35,624 7 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 15,693 12 8,379 7 17,625 14 42,528 34 17,954 14 7,041 6 3,360 3 13,306 11 125,885 33.3 Seldom 31,327 23 15,379 11 15,831 12 21,727 16 24,022 18 12,262 9 4,006 3 9,448 7 134,001 35.5 Sometimes 3,520 15 3,307 14 2,834 12 6,425 27 3,677 15 1,702 7 231 1 2,423 10 24,119 6.4 Often 13,496 25 11,129 20 6,962 13 3,643 7 4,855 9 5,706 10 1,508 3 7,763 14 55,062 14.6 Always 13,535 35 5,058 13 2,011 5 6,895 18 2,733 7 4,780 12 1,093 3 2,684 7 38,789 10.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 15,693 20 8,379 19 17,625 39 42,528 52 17,954 34 7,041 22 3,360 33 13,306 37 125,885 33.3 Seldom 31,327 40 15,379 36 15,831 35 21,727 27 24,022 45 12,262 39 4,006 39 9,448 27 134,001 35.5 Sometimes 3,520 5 3,307 8 2,834 6 6,425 8 3,677 7 1,702 5 231 2 2,423 7 24,119 6.4 Often 13,496 17 11,129 26 6,962 15 3,643 4 4,855 9 5,706 18 1,508 15 7,763 22 55,062 14.6 Always 13,535 17 5,058 12 2,011 4 6,895 8 2,733 5 4,780 15 1,093 11 2,684 8 38,789 10.3 Total 77,572 100 43,252 100 45,263 100 81,217 100 53,240 100 31,492 100 10,198 100 35,624 100 377,857 100.0 Bukombe Meatu Shinyanga Urban Kahama 34.15A Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Status of Food Satisfaction District Total Bariadi Maswa Shinyanga Rural Status of Food Satisfaction District Total Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Kishapu Total Maswa Shinyanga Rural Kahama Bukombe Shinyanga Urban Shinyanga Urban 34.15B Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Kishapu Number of Days District Bariadi Meatu Kishapu 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 323 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 5,082 3 9,064 6 14,711 10 53,745 36 38,424 26 7,814 5 6,410 4 12,748 9 147,998 39.2 Sale of Livestock 3,028 16 1,403 8 6,851 37 2,506 14 597 3 2,314 12 741 4 1,076 6 18,516 4.9 Sale of Livestock Products 535 15 311 9 402 11 982 27 587 16 356 10 97 3 318 9 3,588 0.9 Sales of Cash Crops 39,674 33 27,434 23 1,703 1 13,909 12 6,550 5 17,179 14 125 0 13,686 11 120,261 31.8 Sale of Forest Products 1,064 27 108 3 1,009 26 337 9 597 15 549 14 54 1 161 4 3,879 1.0 Business Income 4,022 22 741 4 7,062 38 2,166 12 2,259 12 791 4 434 2 1,139 6 18,613 4.9 Wages & Salaries in Cash 2,178 28 1,026 13 786 10 1,182 15 239 3 857 11 532 7 971 12 7,770 2.1 Other Casual Cash Earnings 21,098 42 2,530 5 11,530 23 5,430 11 2,706 5 1,171 2 1,580 3 4,351 9 50,395 13.3 Cash Remittance 892 22 635 15 706 17 820 20 470 11 0 0 85 2 526 13 4,133 1.1 Fishing 0 0 0 0 504 63 0 0 0 0 128 16 0 0 162 20 794 0.2 not applicable 0 0 0 0 0 0 139 7 810 42 333 17 141 7 486 25 1,910 0.5 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 49,428 234 10,796 427 7,831 68 23,036 424 18,127 670 8,751 748 2,405 152 5,055 116 125,429 248.9 Tiles 333 2 217 9 200 2 381 7 239 9 572 49 31 2 82 2 2,054 4.1 Concrete 0 0 0 0 0 0 123 2 119 4 0 0 0 0 0 0 243 0.5 Asbestos 0 0 0 0 0 0 0 0 0 0 244 21 0 0 814 19 1,058 2.1 Grass / Leaves 17,850 85 6,687 264 24,754 215 53,009 976 23,166 856 3,867 330 1,575 100 1,607 37 132,516 263.0 Grass & Mud 8,371 40 25,552 1,010 12,477 108 4,557 84 11,588 428 18,059 1,543 6,188 392 28,066 645 114,858 227.9 Other 1,590 8 0 0 0 0 110 2 0 0 0 0 0 0 0 0 1,700 3.4 Total Number of Households 77,572 21 43,252 1,710 45,263 393 81,217 1,496 53,240 1,967 31,492 2,690 10,198 645 35,624 819 377,857 749.8 Kahama Bukombe Shinyanga Urban Meatu Bukombe Meatu 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Cash Income District Total Bariadi Maswa Shinyanga Rural Kishapu Shinyanga Urban Kishapu 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year Roofing Materials District Total Bariadi Maswa Shinyanga Rural Kahama Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":175,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vm: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vm: REGIONAL REPORT: SINGIDA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents ........................................................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary......................................................................................................................................................... vi Illustrations.................................................................................................................................................................... xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Holding Characteristics................................................................................................................................ 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Litaracy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Sorghum.......................................................................................................................... 23 3.3.4.3 Other Cereals................................................................................................................... 24 3.3.5 Oil seeds and Oil nuts Production.................................................................................................... 24 3.3.5.1 Sunflower........................................................................................................................ 26 3.3.6 Pulse Crops Production ..................................................................................................................... 29 3.3.6.1 Beans............................................................................................................................... 29 3.3.7 Roots and Tuber Crops Production.................................................................................................. 30 3.3.7.1 Cassava........................................................................................................................... 30 3.3.7.2 Sweet potatoes............................................................................................................... 33 3.3.8 Fruits and Vegetables ........................................................................................................................ 34 3.3.8.1 Onions............................................................................................................................. 34 3.3.8.2 Tomatoes ........................................................................................................................ 34 3.4 Permanent Crops........................................................................................................................................... 36 3.4.1 Mango ......................................................................................................................................... 38 3.4.2 Banana ......................................................................................................................................... 39 3.3.9 Other Annual Crops Production....................................................................................................... 39 3.3.9.1 Cotton .............................................................................................................................. 39 3.3.9.2 Tobacco .......................................................................................................................... 39 3.5 Inputs/Implements Use................................................................................................................................. 42 3.5.1 Methods of land clearing................................................................................................................... 42 3.5.2 Methods of soil preparation............................................................................................................... 42 3.5.3 Improved seeds use........................................................................................................................... 43 3.5.4 Fertilizers use..................................................................................................................................... 44 3.5.4.1 Farm Yard Manure Use................................................................................................... 45 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 45 3.5.4.3 Compost Use .................................................................................................................. 45 3.5.5 Pesticide Use..................................................................................................................................... 48 3.5.5.1 Insecticide Use................................................................................................................ 49 3.5.5.2 Herbicide Use................................................................................................................. 50 3.5.5.3 Fungicide Use.................................................................................................................. 50 3.5.6 Harvesting Methods.......................................................................................................................... 50 3.5.7 Threshing Methods .......................................................................................................................... 50 3.6 Irrigation .................................................................................................................................................... 51 3.6.1 Area planted with annual crops and under irrigation........................................................................ 51 3.6.2 Sources of water used for irrigation................................................................................................. 53 3.6.3 Methods of obtaining water for irrigation......................................................................................... 54 3.6.4 Methods of water application .......................................................................................................... 54 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing .................................................................................................. 54 3.7.1 Crop Storage ..................................................................................................................................... 54 3.7.1.1 Method of Storage........................................................................................................... 55 3.7.1.2 Duration of Storage ......................................................................................................... 55 3.7.1.3 Purpose of Storage.......................................................................................................... 56 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 56 3.7.2 Agro processing and by-products...................................................................................................... 56 3.7.2.1 Processing Methods........................................................................................................ 57 3.7.2.2 Main Agro-processing Products...................................................................................... 57 3.7.2.3 Main use of primary processed Products........................................................................ 58 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 58 3.7.3 Crop Marketing.................................................................................................................................. 59 3.7.3.1 Main Marketing Problems............................................................................................... 59 3.7.3.2 Reasons for Not Selling................................................................................................... 59 3.8 Access to Crop Production Services............................................................................................................. 59 3.8.1 Access to Agricultural Credits .......................................................................................................... 60 3.8.1.1 Source of Agricultural Credits ....................................................................................... 60 3.8.1.2 Use of Agricultural Credits............................................................................................. 60 3.8.1.3 Reasons for not using agricultural credits...................................................................... 60 3.8.2 Crop Extension .................................................................................................................................. 61 3.8.2.1 Sources of crop extension messages.............................................................................. 61 3.8.2.2 Quality of extension ........................................................................................................ 61 3.9 Access to Inputs ............................................................................................................................................. 64 3.9.2 Inorganic Fertilisers .......................................................................................................................... 64 3.9.3 Improved Seeds ................................................................................................................................. 65 3.9.4 Insecticides and Fungicide ................................................................................................................ 65 3.10 Tree Planting................................................................................................................................................... 66 3.11 Irrigation and Erosion Control Facilities ................................................................................................... 66 3.12 Livestock Results........................................................................................................................................... 67 3.12.1 Cattle Production .............................................................................................................................. 67 3.12.1.1 Cattle Population............................................................................................................. 68 3.12.1.2 Herd size.......................................................................................................................... 68 3.12.1.3 Cattle Population Trend ................................................................................................. 68 3.12.1.4 Improved Cattle Breeds.................................................................................................. 68 3.12.2 Goat Production................................................................................................................................ 69 3.12.2.1 Goat Population.............................................................................................................. 69 3.12.2.2 Goat Herd Size ................................................................................................................ 69 3.12.2.3 Goat Breeds .................................................................................................................... 69 3.12.2.4 Goat Population Trend ................................................................................................... 69 3.12.3 Sheep Production.............................................................................................................................. 72 3.12.3.1 Sheep Population............................................................................................................ 72 3.12.3.2 Sheep Population Trend ................................................................................................. 72 3.12.4 Pig Production .................................................................................................................................. 73 3.12.4.1 Pig Population Trend...................................................................................................... 73 3.12.5 Chicken Production ........................................................................................................................... 73 3.12.5.1 Chicken Population ........................................................................................................ 73 3.12.5.2 Chicken Population Trend.............................................................................................. 73 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5.3 Chicken Flock Size.......................................................................................................... 73 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 73 3.12.6 Other Livestock ................................................................................................................................. 74 3.12.7 Pests and Parasites Incidences and Control ...................................................................................... 78 3.12.7.1 De-worming.................................................................................................................... 78 3.12.8 Access to Livestock Services ........................................................................................................... 78 3.12.8.1 Access to livestock extension Services.......................................................................... 78 3.12.8.2 Access to Veterinary Clinic ............................................................................................ 79 3.12.8.3 Access to village watering points/dam .......................................................................... 79 3.12.9 Animal Contribution to Crop Production......................................................................................... 80 3.12.9.1 Use of Draft Power......................................................................................................... 80 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 80 3.12.9.4 Use of Compost ............................................................................................................ 80 3.12.10 Fish Farming...................................................................................................................................... 80 3.13 Poverty Indicators......................................................................................................................................... 81 3.13.1 Access to Infrastructure and Other Services..................................................................................... 81 3.13.2 Type of Toilets................................................................................................................................... 81 3.13.3 Household’s assets............................................................................................................................. 82 3.13.4 Sources of Light Energy.................................................................................................................... 82 3.13.5 Sources of Energy for Cooking......................................................................................................... 82 3.13.6 Roofing Materials............................................................................................................................. 82 3.13.7 Access to Drinking Water ................................................................................................................. 84 3.13.8 Food Consumption Pattern................................................................................................................ 85 3.13.8.1 Number of Meals per Day.............................................................................................. 85 3.13.8.2 Meat Consumption Frequencies...................................................................................... 85 3.13.8.3 Fish Consumption Frequencies...................................................................................... 85 3.13.9 Food Security.................................................................................................................................... 88 3.13.10 Main Source of Cash Income........................................................................................................... 88 PART IV: SINGIDA PROFILES .............................................................................................................................. 90 4.1 Region Profile ................................................................................................................................................. 90 4.2 District Profiles............................................................................................................................................... 90 4.2.1 Iramba ................................................................................................................................................ 90 4.2.2. Singida Rural ..................................................................................................................................... 92 4.2.3 Manyoni............................................................................................................................................. 94 4.2.4 Singida Urban .................................................................................................................................... 96 ACRONYMS __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Singida region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in th e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Singida region that were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Singida region and indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Singida region was 179,915 out of which 06,837 (53.8%) were involved in growing crops only, 516 (0.3%) rearing livestock only and 82,563 (45.9%) were involved in crop production as well as livestock keeping. In summary, Singida region had 179,400 households involved in crop production and 83,079 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off farm income, livestock keeping/herding, remittances, permanent crop farming and fishing/hunting The region had a literacy rate of 73 percent. The highest literacy rate was in Singida Urban district (81%) followed by Singida Rural district (78%), Iramba district (71%) and Manyoni district (66%). The literacy rate for the heads of households in the region was 66 percent. The number of heads of agricultural households with formal education in Singida region was 116,473 (65%), those without formal education were 63,442 (35%) and those with only adult education were 2,235 (1%). The majority of heads of agricultural households (62%) had primary level education whereas only 3 percent had post primary education. In Singida region 92,591 (51%) households had one household member each involved in off-farm income generating activity, 49,008 (27%) households had two household members each involved in off-farm income generating activities and 17,437 (10%) households had more than two household members each involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 463,150 ha. The regional average land area utilised for crop production per crop growing household was only 2.2 ha. This figure was higher than the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 321,419 hectares out of which 2,292 hectares (0.71%) were planted during dry season and 319,128 hectares (99.29%) during long rainy season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii The planted area occupied by cereals was 243,745 ha (76.4% of the total area planted with annuals). This was followed by oil seeds and oil nuts (52,843 hectares, 16.6%), pulses (13,342 hectares, 4.2%), roots and tubers (5,724 hectares, 1.8%), cash crops (2,226 hectares, 0.7%) and fruit and vegetables (1,249 hectares, 0.4%). Maize Maize dominated the production of cereal crop in the region. The number of households growing maize in Singida region during the long rainy season was 132,667, (74% of the total crop growing households in the region during the long rainy season). The total production of maize during the long rainy season was 54,056 tonnes from a planted area of 135,482 hectares resulting in a yield of 0.4 t/ha. Other crops in order of their importance (based on area planted) were sorghum,bulrush millets,wheat, paddy and fingermillets. The average area planted with maize per maize growing household ranged from 0.84 hectares in Singida Rural district to 1.20 hectares in Iramba district. Iramba district had the largest planted area of maize (60,761 ha) followed by Singida Rural (42,787 ha), Manyoni (32,035 ha) and Singida Urban (1,694 ha). Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Singida region during the long rainy season was 82,809. This represented 46 percent of the total crop growing households in Singida region in the long rainy season. Oil Seeds The total production of oil seeds was 24,367 tonnes. The most cultivated oil seed crop was sunflower. The production for this crop was 21,002 tonnes, which constituted 86 percent of the total oil seeds production, followed by groundnuts 2,462 tonnes (10%) and simsim 887 tonnes (4%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 9,242 hectares which is 3 percent of the area planted with annual crops in the region. The most important permanent crop was mango which had a planted area of 3,784 ha (40 percent of the total area planted with permanent crops) followed by bananas 3,373 ha (36%) and guava 1,268 ha (14%). Improved Seeds The planted area using improved seeds was 62,511 ha which represents 20 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seeds was mainly in the long rainy season (95.5%) while in the short rainy season was only 0.5%. Use of Fertilizers The use of fertilizers on annual crops was very small with the application of fertilisers to a planted area of only 129,050 ha (40% of the total planted area in the region). The planted area without fertilizer for annual crops was 190,078 hectares representing 60 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 119,610 ha which represented 37.5 percent of the total planted area. This was followed by compost (5,952 ha, 4.6%). Inorganic fertilisers were used on a small area which represented only 2.7 percent of the area planted with fertilisers EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Irrigation In Singida region, the area of annual crops and vegetables under irrigation was 3,443 ha representing 1.1 percent of the total area planted. The district with the largest planted area under irrigation with annual crops was Manyoni (4,202 ha, 35% of the total irrigated planted area with annual crops in the region). This is closely followed by Singida Rural with (3,916 ha, 32%), Iramba (2,867 ha, 24%) and Singida Urban (1,113 ha, 9%). When expressed as a percentage of the total area planted in each district, Singida Urban had the highest with 10.2 percent of the planted area in the district under irrigation. This is followed by Manyoni (6.7%), Singida Rural (3.4%) and Iramba Crop Storage There were 179,391 crop growing households (14.7% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 115,361 households storing 8,366 tonnes as of 1st January 2004. This was followed by sorghum and millets (96,374 households, 5,413t), beans and pulses (15,765 households, 230t) and groundnuts/bambaranuts (4,894 households, 119t) and paddy (4,894 household, 387t). Other crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 81,720 which represented 45 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Manyoni (52%) followed by Singida Rural (50%) and Iramba (40%). Agricultural Credit In Singida region, few agricultural households (2,698, 1.5%) accessed credit, out of which 1,516 (56%) were male-headed households and 1,182 (44%) were female headed households. In Singida Urban district only female headed households got credit for agriculture purposes, whereas in Singida Rural district only male households accessed credit. In Manyoni and Iramba districts both male and female headed household’s accessed agricultural credit. Crop Extension Services The number of agricultural households that received crop extension was 86,702 (48% of total crop growing households in the region). Some districts have more access to extension services than others with Iramba district having a relatively high proportion of households that received crop extension messages (71.5%), followed by Singida Urban (36.9%), Singida Rural (36.8%) and Manyoni (33.8%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 15,529. This number represented 9 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Singida Rural district (11%) followed by Iramba (10%), Singida Urban (6%) and Manyoni (1%). (iii) Livestock and Poultry Production Cattle EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix The total number of cattle in the region was 1,257,159. Cattle were the dominant livestock in the region followed by goats, sheep and pigs. The region had 7.5 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 1,255,118 head (99.8% of the total number of cattle in the region), 1,115 (0.09%) were dairy breeds and only 925 (0.07%) were beef breeds. Goats The number of goat-rearing-households in the region was 60,387 (34% of all agricultural households) with a total of 684,420 goats giving an average of 11 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 39,179 (22% of all agricultural households) with a total of 309,938 sheep giving an average of 8 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,554 (1.4% of the total agricultural households) rearing about 6,375 pigs. This gave an average of 3 pigs per pig-rearing household. Chicken The number of households keeping chickens was 125,895 raising 1,658,178 chickens. This gives an average of 13 chickens per chicken-rearing household. In terms of total number of chickens in the country Singida ranked ninth out of the 21 Mainland regions. Use of Draft Power The region has 199,820 oxen that were used to cultivate 182,070 hectares of land. This represented only 8.9 percent of the total oxen found on the mainland. The largest area cultivated using oxen was found in Iramba district (105,194 ha, 58% of the total area cultivated using oxen). Fish Farming There was no fish farming in the region. iv) Poverty Indicators Availability of Toilets It was estimated that 88.7 percent of all rural agricultural households used the traditional pit latrines, 3.9 percent used flush toilets and 0.4 percent had improved pit latrines. The remaining 0.2 percent of households had other unspecified types of toilets. Households with no toilet facilities represented 6.8 percent of the total agriculture households in the region. Household Assets The radio was the most owned asset with 38.6% households owning it followed by bicycle (29.9%), iron (12.1%), wheelbarrow (4.4%), vehicle (0.8%), mobile phone (0.8%), television/video (0.4%), and landline phone (0.3%). Source of Lighting Energy EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x Wick lamp was the most common source of lighting energy in the region. About 72.8 percent of the total rural households used this source of energy followed by hurricane lamp (17.5%), firewood (4.9%), pressure lamp (3.9%), mains electricity (0.7%), solar (0.1%) and gas or biogas (0.6%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.1 percent of all rural agricultural households. The second most common source of energy for cooking was crop residues (2.3%) and charcoal (1.7%). The rest of energy sources accounted for 0.9 percent. These were solar energy (0.4%), mains electricity (0.2%), paraffin/kerosene (0.1%), bottled gas (0.1%) and livestock dung (0.1%). Roofing Materials The most used roofing material (for the main dwelling) was grass and mud and it was used by 73.2 percent of the rural agricultural households. This was followed by iron sheets (20.7%). Other roofing materials were grass/leaves (5.4%), asbestos (0.2%), tiles (0.1%) and others (0.3%). Number of Meals per Day About 66.5 percent of the holders in the region took two meals per day, 30.3 percent took three meals, 3.0 percent took one meal and 0.2 percent took four meals. Food Security In Singida region, 61,025 households (34% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 9,646 (5%) said they sometimes experience problems, 17 percent often experienced problems and 14 percent always had problems in satisfying the household food requirement. About 31 percent of the agricultural households said they did not experience any food sufficiency problems Main Source of Cash Income Casual cash earnings were the main cash income earning activity reported by 29.6 percent of all rural agricultural households. The second main cash income earning activity was sales of livestock (16.5%) followed by selling of cash crops (16.2%), businesses (10.7%) and sales of food crops (9.1%). Only 6.6% of smallholder households reported the cash remittances as their main source of income, followed by forest products (6.5%) and wages and salaries (3.1%) ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .............................................................................................................................................. 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 20 3.3 Area, Production and Yield of Oil seeds and Oil nuts by Season...................................................................... 24 3.4 Area, Production and Yield of Pulses by Season ................................................................................................26 3.5 Area, Production and Yield of Roots and Tuber Crops by Season.................................................................... 30 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 34 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 39 3.8 Land Clearing Methods....................................................................................................................................... 42 3.9 Planted Area by Type of Fertiliser Use and District – Long Rainy Season ...................................................... 43 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District - Long Rainy Season ............................................................................................................................................56 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ............................................... 59 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 59 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 59 3.14 Access to Inputs....................................................................................................................................................64 3.15 Number of Households and Chickens Raised by Flock Size..............................................................................74 3.16 Number of Other Livestock by Type of Livestock and District ........................................................................ 74 3.17 Mean distances from holders dwellings to infrastructure and services by districts ...........................................81 3.18 Number of Households by Number of meals the Household normally has per Day and District .................... 85 List of Charts 3.1 Agricultural Households by Type of Holdings................................................................................................... 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 11 3.3 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District.............................................................................. 15 3.6 Percentage of Person Aged 5 years and above by District and Educational Status .......................................... 16 3.7 Percentage of Population Aged 5 years and Above by District and Education Status.............................................................................................................................. 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off farm activities............................................................................................................. 17 3.10 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities............................................................................................................ 17 3.11 Utilized and Usable Land per Household by District......................................................................................... 17 3.12 Land Area by Type of Land Use......................................................................................................................... 18 3.13 Area Planted with Annual Crops by Season (hectares)...................................................................................... 18 3.14 Area Planted with Annual Crops during Long Rainy Season and District.........................................................18 3.15 Area Planted with Annual Crops per Household during Long Rainy Season and District............................... 19 3.16 Planted Area (ha) for the Main Annual Crops.................................................................................................... 19 3.17a Planted Area (ha) per Household by Selected Crops ......................................................................................... 19 3.17b Percentage Distribution of Area Planted with Annual Crops by Crop Type..................................................... 20 3.18 Area planted with Annual Crops by Crop Type and Season.............................................................................. 20 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 20 3.20 Time Series Data on Maize Production – Singida Region................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Singida Region...................................................................... 23 3.23 Total Planted Area and Area of Sorghum per Household by District ................................................................23 3.24 Time Series Data on Sorghum Production – Singida Region............................................................................ 23 3.25 Time Series of Sorghum Planted Area and Yield – SGD Region.......................................................................24 3.26 Area Planted With Bulrush millets, Finger Millet and Paddy by District ..........................................................24 3.27 Area Planted and Yield of Major Oil seeds and oil nuts.....................................................................................24 3.28 Time series data on Sunflower production – Singida Region.............................................................................24 3.29 Percent of Sunflower Planted Area and percent of Total Land with Sunflower by District..............................26 3.30 Area Planted per sunflower growing households by District (Long rainy Season Only) ................................. 26 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.31 Area Planted and Yield of Major Pulses crops................................................................................................... 29 3.32 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 29 3.33 Area Planted per Bean Growing Household by District (Long Rainy Season Only)........................................ 29 3.34 Time Series Data on Bean Production – Singida Region................................................................................... 29 3.35 Time Series of Beans Planted Area and Yield - Singida.....................................................................................30 3.36 Area Planted with Cassava during the Census/Survey Year.............................................................................. 30 3.37 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District.................................... 33 3.38 Cassava Planted Area per Cassava Growing Households by District ............................................................... 33 3.39 Sweet Potatoes: Total Area Planted and Planted Area per Household by District............................................ 33 3.40 Sweet Potatoes Planted Area per Sweet Potatoes Growing Households by District......................................... 33 3.41 Area Planted and Yield of Fruit and Vegetables................................................................................................ 34 3.42 Number of Households Growing Onion by District (Long Rainy Season) ...................................................... 34 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District ...........................................36 3.44 Area Planted per Onion Growing Household by District (Long Rainy Season Only)...................................... 36 3.45 Percent of Tomatoes Planted Area and Percent of Total Land with Tomatoes by District............................... 36 3.46 Area planted with Annual Cash Crops ............................................................................................................... 38 3.47 Area Planted (ha) with Main Perennial Crops.....................................................................................................38 3.48 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 38 3.49 Percent of Area Planted with Mango and Average Planted Area per Household by District........................... 38 3.50 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 39 3.51a Planted Area with Other Crops (Cash Crops.......................................................................................................39 3.51b Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District................................... 39 3.51c Area Planted with Annual Cops by Method of Land clearing During the Long Rainy Season........................ 42 3.52 Area Cultivated by Cultivation Method.............................................................................................................. 42 3.53 Area Cultivated by Method of Cultivation and District......................................................................................43 3.54 Planted Area with Improved Seed by Crop Type .............................................................................................. 43 3.55 Planted Area with Improved Seed by Crop Type............................................................................................... 43 3.56 Percentage of Crop Type Planted Area with Improved Seed – Annuals............................................................43 3.57 Area of Fertilizer Application by Type of Fertilizer ...........................................................................................44 3.58 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 44 3.59 Planted Area with Farm Yard Manure by Crop Type - Singida ........................................................................ 45 3.60 Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 45 3.61 Proportion of Planted Area Applied with Farm Yard Manure by District .........................................................45 3.62 Planted Area with Inorganic Fertiliser by Crop type – Singida......................................................................... 45 3.63 Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 48 3.64 Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 48 3.65 Planted Area with Compost by Crop Type......................................................................................................... 48 3.66 Percentage of Planted Area with Compost by Crop Type ................................................................................. 48 3.67 Proportion of Planted Area Applied with Compost by District......................................................................... 48 3.68 Planted area (ha) by Pesticide use....................................................................................................................... 49 3.69 Planted Area applied with Insecticides by Crop Type ........................................................................................49 3.70 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 49 3.71 Percent of Planted Area applied with Insecticides by District - Singida ........................................................... 49 3.72 Planted Area applied with herbicides by Crop Type...........................................................................................50 3.73 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 50 3.74 Proportion of Planted Area applied with Herbicides by District – Singida Region.......................................... 50 3.75 Planted Area applied with Fungicides by Crop Type......................................................................................... 50 3.76 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 51 3.77 Proportion of Planted Area applied with Fungicides by District – Singida region ........................................... 51 3.78 Area of Irrigated Land..........................................................................................................................................51 3.79 Irrigated Area and Percentage of Irrigated Area by District............................................................................ 53 3.80 Time Series of Households with Irrigation – Singida ........................................................................................ 53 8.81 Number of Households with Irrigation by Source of Water.............................................................................. 53 3.82 Number of Households by Method of Obtaining Irrigation Water.....................................................................54 3.83 Number of Households with Irrigation by Method of Field Application.......................................................... 54 3.84 Number of Households and Quantity Stored by Crop Type – Singida Region................................................. 54 3.85 Number of households by Storage Methods - Singida....................................................................................... 55 3.86 Number of households by method of storage and District (based on the most important household crop)......55 3.87 Normal Length of Storage for Selected Crops ................................................................................................... 55 3.88 Quantity of Maize Produced (tonnes), Stored (tones) and Percent Stored by District...................................... 56 3.89 Number of Households by Purpose of Storage and Crop Type......................................................................... 56 3.90 Percentage of Households Processing Crops by District ................................................................................... 56 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.91 Percent of Households Processing Crops by District......................................................................................... 56 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 57 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 57 3.94 Number of Households by Type of Bi-product.................................................................................................. 57 3.95 Use of Processed Product.....................................................................................................................................58 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 58 3.97 Location of Sale of Processed Products............................................................................................................ . 58 Percentage of Households Selling Processed Products by Outlet for Sale and District.................................... 58 3.99 Number of Crop Growing Households Selling Crops by District ..................................................................... 59 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 59 3.101 Percentage Distribution of Households Receiving Credit by Main Sources......................................................60 3.102 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 60 3.103 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 60 3.104 Reasons for not using Credit............................................................................................................................... 60 3.105 Number of Households Receiving Extension Advice.........................................................................................61 3.106 Number of Households that Received Extension by District............................................................................. 61 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 61 3.108 Number of Households Receiving Extension by Quality of Services ............................................................... 61 3.109 Number of Households by Source of Inorganic Fertiliser ..................................................................................64 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser...................................................64 3.111 Number of Households by Source of Improved Seed.........................................................................................65 3.112 Number of Households reporting Distance to Improved Seed .......................................................................... 65 3.113 Number of Households by Source of Insecticide/Fungicide.............................................................................. 65 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 65 3.115 Number of Households with Planted Trees by District...................................................................................... 66 3.116 Number of Planted Trees by Species...................................................................................................................66 3.117 Number of Trees Planted by Smallholders by Species and District ...................................................................66 3.118 Number of Trees Planted by Location................................................................................................................ 66 3.119 Number of Households by purpose of Planted Trees......................................................................................... 66 3.120 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 67 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............67 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 67 3.123 Total Number of Cattle ('000') by District.......................................................................................................... 68 3.124 Numbers of Cattle by Type and District............................................................................................................. 68 3.125 Cattle Population Trend ...................................................................................................................................... 68 3.126 Dairy Cattle Population Trend............................................................................................................................ 69 3.127 Total Number of Goats ('000') by District.......................................................................................................... 69 3.128 Goat Population Trend.........................................................................................................................................69 3.129 Total Number of Sheep by District..................................................................................................................... 72 3.130 Sheep Population Trend...................................................................................................................................... 72 3.131 Total Number of Pigs by District........................................................................................................................ 72 3.132 Pig Population Trend........................................................................................................................................... 73 3.133 Total Number of Chicken by District ................................................................................................................. 73 3.134 Chicken Population Trend .................................................................................................................................. 73 3.135 Number of Improved Chicken by Type and District...........................................................................................74 3.136 Layer Population Trend....................................................................................................................................... 74 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 78 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 78 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........78 3.140 Number of Households by Distance to Veterinary Clinic.................................................................................. 79 3.141 Number of Households by Distance to Veterinary Clinic and District.............................................................. 79 3.142 Number of Households by Distance to Village Watering Point ........................................................................ 79 3.143 Number of Households by Distance to Watering Point and District................................................................. 79 3.144 Number of Households using Draft Animals ..................................................................................................... 80 3.145 Number of Households using Draft Animals by District....................................................................................80 3.146 Number of Households using Organic Fertiliser................................................................................................ 80 3.147 Area of Application of Organic Fertiliser by District ........................................................................................ 80 3.148 Agricultural Households by Type of Toilet Facility .......................................................................................... 81 3.149 Percentage Distribution of Households Owning the Assets................................................................................82 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................82 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking ..............................................82 3.152 Percentage Distribution of Households by Type of Roofing Material .............................................................. 84 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.153 Percentage Distribution of Households With Grass/Mud Roofs by District......................................................84 3.154 Percentage of Households by Main Source of Drinking Water and Season...................................................... 84 3.155 Percentage of Households by Distance to Main Source of Water and Season...................................................84 3.156 Number of Agriculture Households by Number of Meals per day.................................................................... 85 3.157 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season... 85 3.158 Percent Distribution of the Number of Households by Main Source of Income............................................... 88 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 21 3.8 Total Planted Area (annual crops) by District.....................................................................................................21 3.9 Area planted and Percentage During the Short Rainy Season by District......................................................... 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................22 3.11 Planted Area and Yield of Maize by District ......................................................................................................25 3.12 Area Planted per Maize Growing Household..................................................................................................... 25 3.13 Planted Area and Yield of Sorghum by District..................................................................................................27 3.14 Area Planted per Sorghum Growing Household.................................................................................................27 3.15 Planted Area and Yield of Sunflower by District............................................................................................... 28 3.16 Area Planted per Sunflower Growing Household...............................................................................................28 3.17 Planted Area and Yield of Beans by District...................................................................................................... 31 3.18 Area Planted per Beans Growing Household..................................................................................................... 31 3.19 Planted Area and Yield of Cassava by District .................................................................................................. 35 3.20 Area Planted per Cassava Growing Household.................................................................................................. 35 3.21 Planted Area and Yield of Onion by District ..................................................................................................... 37 3.22 Area Planted per Onion Growing Household..................................................................................................... 37 3.25 Planted Area and Yield of Mango by District.................................................................................................... 40 3.26 Area Planted per Mango Growing Household ................................................................................................... 40 3.27 Planted Area and Yield of Banana by District ................................................................................................... 41 3.28 Area Planted per Banana Growing Household................................................................................................... 41 3.29 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 46 3.30 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 46 3.31 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 47 3.32 Number of Households and Percent of Total Households Selling Crops by District........................................ 47 3.33 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 52 3.34 Number and Percent of Crop Growing Households using Improved Seed by District .....................................52 3.35 Number and percent of smallholder planted trees by district............................................................................. 72 3.36 Number and Percent of Households with water Harvesting Bunds by District................................................. 72 3.37 Cattle population by District as of 1st Octobers 2003.........................................................................................62 3.38 Cattle Density by District as of 1st October 2003...............................................................................................62 3.39 Goat population by District as of 1st Octobers 2003 ..........................................................................................63 3.40 Goat Density by District as of 1st October 2003.................................................................................................63 3.41 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 73 3.42 Sheep Density by District as of 1st October 2003...............................................................................................73 3.43 Pig population by District as of 1st Octobers 2003.............................................................................................70 3.44 Pig Density by District as of 1st October 2003 ...................................................................................................70 3.45 Number of Chickens by District as of 1st October 2003 ....................................................................................75 3.46 Density of Chickens by District as of 1st October 2003.................................................................................... 75 3.47 Number and Percent of Households Infected with Ticks by District ................................................................ 83 3.48 Number and Percent of Households Using Draft Animals by District...............................................................76 3.49 Number and Percent of Households Using Farm Yard Manure by District...................................................... 76 3.50 Number and Percent of Households using Compost by District.........................................................................76 3.51 Number and Percent of Households without Toilets by District ........................................................................77 3.52 Number and Percent of Households using Grass/Leaves for roofing material by District ................................83 3.53 Number and Percent of Households eating 3 meals per day by District ............................................................83 3.54 Number and Percent of Households eating Meat Once per Week by District ...................................................86 3.55 Number and Percent of Households eating Fish Once per Week by District.................................................... 86 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.56 Number and percent of Households Reporting food insufficiency by District ..................................................87 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Singida region is situated in Central Tanzania. It lies between longitudes 330 27” 5’ and 350 26” east of Greenwich, and latitudes 30 52” and 70 34” south of the equator. Singida town is the regional headquarter. Arusha region bounds the region to the north, Dodoma region to the east, Mbeya and Iringa regions to the south, Tabora region to the west and Shinyanga to the northwest. The region comprises four districts namely Iramba, Singida Rural, Manyoni and Singida Urban. The region headquarters is located in Singida Urban District. 1.4 Land Area Singida region is divided into three administrative districts with three districts with three district councils and one town council namely: Iramba, Singida Rural, Manyoni and Singida Urban. The three districts cover an area of 49,341 square kilometers, equivalent to about six per cent of the total land area of Tanzania Mainland. 1.4 Climate 1.4.1 Temperature Temperature in the region ranges between 150C and 300C depending on season and altitude. The coldest period in the year is July while the hottest period is in October and November. 1.4.2 Rainfall The average annual rainfall ranges between 500-800 millimeters. In normal circumstances, rainfall usually takes place from mid-November ending in April or early May every year. 1.5 Population According to the 2002 Population and Housing Census, there were 1,090,758 inhabitants in Singida region. The population of Singida region ranked 17th out of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators • The contributed about 154,719 million shillings (4%) to Gross Domestic Product (GDP) at current prices in 1998. • Tha main cash crops in the region include cotton and tobacco. Cattle, Goats and Chicken have a significant contribution to GDP. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 • The road network is not well developed in Singida region despite the fact that, six regions around it. It has a road network with a total of 3,237.5 kms distributed in three criteria according to types of road surface. The tarmac road covers 15.5 kms, earth roads 2,534.5 kms and 687.5 kms. • The region is served by telephone, telefax and telex services. Also, the region has three post offices with some sub post offices. • The central railway line crosses the region in the southern part of Manyoni district. This line is very crucial economically to Singida region since it serves directly Kintiku, Makutopora, Saranda, Manyoni and itigi villages. Other villages served are Aghondi, Kitaraka and Kalangasi. This line serves passengers and transports goods and livestock (i.e cattle) to potential markets, particularly Dar es Salaam. There is also an extension of railway line from Manyoni to Singida region headquarters. • There is no airport in the region; hence there are no regular commercial flights. However, there are several privete airstrips, which cater for light air craft mainly for emergency cases such as flying doctors. There are three airstrips in Manyoni, two in Singida and one in Iramba district. The region is famous for producing both food and cash crops. The main food crops produced in Singida region include: maize, sorghum, bulrush Millets and finger Millets. The main cash crops include cotton and tobacco. Livestock keeping is also an important economic activity in the region. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from SINGIDA region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,SINGIDA, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the census results of the census data for Singida region which are based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Singida region was 179,915. The largest number of agriculture households was in Singida Rural 73,197 followed by Iramba 62,528, Manyoni 33,065 and Singida Urban 11,125. (Map 3.1) At district level, the highest density of Household (50/km2) was found in Singida Urban and Iramba for each district (Map 3.2). Most households 96,837 (53.8%) were involved in growing crops only, 516 (0.3%) rearing livestock only, 82,563 (45.9%) were involved in crop production as well as livestock keeping and pastoralist were not found in the region (Chart 3.1) (Maps 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Singida region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off farm income, livestock keeping/herding, remittances, permanent crop farming and fishing/hunting (Table 3.1). 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Singida region was 139,553 (78% of the total regional agricultural households) whilst the number of female-headed households it was 40,362 (22% of the total regional agricultural households). The mean age of household heads was 47 years (45 years for male heads and 51 years for female heads) (Chart 3.2). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 1 6 4 3 5 7 2 Singida R 1 5 4 3 6 7 2 Manyoni 3 6 4 1 5 7 2 Singida Urb 1 6 2 3 5 7 4 Total 1 6 4 3 5 7 2 Chart 3.1 Agriculture Households by Type - Singida Crops and Livestock 45.9% Crops Only 53.8% Livestock Only 0.3% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Singida Urban Singida Rural Manyoni 26 16 23 Iramba 3 21.4 to 26 16.8 to 21.4 12.2 to 16.8 7.6 to 12.2 3 to 7.6 Singida Urban Singida Rural Manyoni 11,125 73,197 62,528 33,065 Iramba 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS Tanzania Agriculture Sample Census Map 3.01 SINGIDA Total Number of Ariculture Households by District. Number of Ariculture Households Number of Ariculture Households Map 3.02 SINGIDA Number of Agriculture Households per Square Kilometer of Land by District. Number of Agriculture Households per Square Km Number of Agriculture Households per Square Km 12 Singida Urban Singida Rural 11,125 62,255 33,065 72,954 Manyoni Iramba 50,000 to 80,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 Singida Rural Singida Urban 100 99.7 100 99.6 Manyoni Iramba 99.9 to 100 99.8 to 99.9 99.7 to 99.8 99.6 to 99.7 99.5 to 99.6 13 Tanzania Agriculture Sample Census Map 3.03 SINGIDA Number of Crop Growing Households by District. Number of Crop Growing Households Number of Crop Growing Households Map 3.04 SINGIDA Percent of Crop Growing Household by District Percent of Crop Growing Households Percent of Crop Growing Households Iramba Singida Urban Singida Rural 51% 50% 54% 18% Manyoni 50 to 60 40 to 50 30 to 40 20 to 30 10 to 20 Singida Urban Singida Rural Manyoni 26 22 3 16 Iramba 21.4 to 26 16.8 to 21.4 12.2 to 16.8 7.6 to 12.2 3 to 7.6 14 Tanzania Agriculture Sample Census Map 3.05 SINGIDA Number of Crop Growing Households Per Square Kilometer of Land by District. Number of Crop Growing Households Per Square Km Number of Crop Growing Households Per Square Km Map 3.06 SINGIDA Percent of Crop and Livestock Households by District Percent of Crop and Livestock Households Percent of Crop and Livestock Households RESULTS RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Singida region had a total rural agricultural population of 936,792 of which 463,874 (49.5%) were males and 472,918 (50.5) were females. Whereas age group 0-14 constituted 45 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Singida region had an average household size of 5 with Iramba district having the highest household size of 6 whilst other districts had the regional average household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Singida region had a total literacy rate of 73 percent. The highest literacy rate was found in Singida Urban district (81%) followed by Singida Rural district (78%), Iramba district (71%) and Manyoni district (66%). (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 66.1 percent. The literacy rates among the male and female heads of households were 74 and 40 percent respectively. Male head of household literacy rate was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Manyoni (69.3%) followed by Singida Urban (67.9%), Singida Rural (66.2%), and Iramba (64%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - Singida 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 100 Singida Urb Singida Rur Iramba Manyoni District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Singida 0.0 25.0 50.0 75.0 100.0 Iramba Singida Rur Manyoni Singida Urb District Percent Male Female Total RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 38.5 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 34.9 percent were still attending school. Those who have never attended school were 26.6 percent (Chart 3.6). Agricultural households in Singida Urban district had the highest percentage (40.3%) of population aged 5 years and above who had completed different levels of education. This was followed by Singida Rural (39.4%), Iramba (37.8%) and Manyoni (37.1%). The number of heads of agricultural households with formal education in Singida region was 116,473 (65%), those without formal education were 63,442 (35%) and those with only adult education were 2,235 (1%). The majority of heads of agricultural households (62%) had primary level education whereas only 3 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Singida region, Singida Rural district had the highest percentages (40% for primary and 45% for secondary). This was followed by Iramba (34% primary and 29% secondary), Manyoni (19% primary and 18% secondary) and Singida Urban (6% primary and 8% secondary) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Singida with 88 percent of households having at least one member with off-farm income. In Singida region 92,591 households (51%) had only one member aged 5 and above involved in only one off-farm income generating activity, 49,008 households (27%) had two members involved in off-farm income generating activities and 17,437 households (10%) had more than two members involved in off-farm income generating activities. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.5% Never Attended 26.6% Attending School 34.9% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Iramba Singida Rur Manyoni Singida Urb District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 1% Post Primary Education 3% No Education 34% Primary Education 62% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 Manyoni district had the highest percentage of agriculture households with off-farm income (over 99.5% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Singida Rural (89.9%), Singida Urban (82.2%) and Iramba (81.9%). The district with the highest percentages of agriculture households with more than one member with off-farm income was Iramba (55%). Singida Rural district had very few households with more than one member having off-farm income (27%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country, however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 463,150 ha. The Regional average land area utilised for agriculture per household was only 2.2 ha. This figure is higher than the national average which is estimated at 2.0 hectares. Eighty nine percent of the total land available to smallholders was utilised. Only 11 percent of usable land available to smallholders was not used (Chart 3.11). Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Iramba Singida Rur Manyoni Singida Urb Districts Area/household 0 25 50 75 100 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.9 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities One Off Farm Income, 92591, 51% More than Tw o Off Farm Income, 17437, 10% Tw o Off Farm Income, 49008, 27% None, 20879, 12% Chart 3.10 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities 0% 20% 40% 60% 80% 100% Iramba Singida Rur Manyoni Singida Urb Districts Percent Mo re than Two Two One No ne RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 Large differences in land area utilised per household exist between districts with Manyoni (2.6ha), Iramba ((2.5ha), Singida Rural (2.0ha) and Singida Urban (1.3ha). The percentage utilized of the usable land per household is highest in Singida Rural (94%) and lowest in Manyoni (77%). Eighty nine percent of the total land available to smallholders was utilised. Only 11 percent of usable land available to smallholders was not used (Chart 3.11 and Map.7). 3.2.2 Types of Land Use The area of land under temporary mono crop was 273,971 hectares (59.2% of the total land available to smallholders in Singida), followed by temporary mixed crop (48,992 ha, 10.6%), area under fallow (37,900 ha, 8.2%), uncultivated usable land (37,134 ha, 8.0%), area under pasture (18,758 ha, 4.0%), area under natural bush (14,301 ha, 3.1%), unusable area (11,246 ha, 2.4%), permanent/annual mix (8,782 ha, 1.9%), area rented to others (5,344 ha, 1.2%), area under permanent mixed crops (3,488 ha, 0.8%), area under permanent mono crops (2,026 ha, 0.4%) and area planed trees (1,209 ha, 0.3%). 3.3 Annual Crops and Vegetable Production Singida region has one rainy season; however some crops were grown during the dry season of year by using irrigation/wet areas. A total of 2,292 ha were cultivated during dry season. The quantity of crops produced during the long rainy season will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 321,419 hectares out of which 2,292 hectares (0.71%) were planted during dry season and 319,128 hectares (99.29%) during long rainy season. The average areas planted per household during the dry and long rainy seasons were 1.1 and 0.8 ha respectively (Chart 3.13). The district with the largest area planted per household (during long rainy season) were Iramba (0.9 ha) followed by Manyoni (0.8 ha), Singida Rural (0.7 ha) and Singida Urban (0.5 ha) (Chart 3.14 and Map.8). The planted area occupied by cereals was 243,745 ha (76.4% of the total area planted with annuals). This was followed by oil seeds and oil nuts (52,843 hectares, Chart 3.12 Land Area by Type of Use 0.3 0.4 0.8 1.2 1.9 2.4 3.1 4.1 8.0 8.2 59.2 10.6 0 50000 100000 150000 200000 250000 300000 Planted Trees Permanent Mono Crops Permanent Mixed Crops Rented to Others Permanent / Annual Mix Unusable Natural Bush Pasture Uncultivated Usable Land Fallow Temporary Mixed Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.14 Area Planted with Annual Crops During Long Rainy Season and District 0 30000 60000 90000 120000 150000 Iramba Singida Rur Manyoni Singida Urb District Planted Area (ha) Long Rainy Season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 319128, 99.3% Dry Season, 2,292, 0.7% Dry Season Long Rainy Season RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 19 16.6%), pulses (13,342 hectares, 4.2%), roots and tubers (5,724 hectares, 1.8%), cash crops (2,226 hectares, 0.7%) and fruit and vegetables (1,249 hectares, 0.4%). The average area planted per household during the long rainy season in Singida region was 1.8 hectares, however, there were large district differences. Iramba had the largest planted area per household (2.1 ha) followed by Manyoni (1.9 ha), Singida Rural (1.6 ha) and Singida Urban (1.0 ha) (Chart 3.15 and Map.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Singida region and it had a planted area 2 times greater than Sorghum, which had the second largest planted area. The area planted with maize constitutes 43 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are sorghum, sunflower, bulrush Millets, groundnuts and beans (Chart 3.16). Chart 3.17 shows the area planted per household growing selected crops. Households that grow Irish potatoes, cotton and chick peas have larger planted areas per household than other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Singida region. The area planted with cereals was 243,745 ha (76.4% of the total planted area), followed by oil seeds and oil nuts with 52,843 ha (16.6%), pulses 13,342 ha (4.2%), roots and tubers 5,724 ha (1.8%), cash crops 2,226 ha (0.7%) and fruits and vegetables 1,249 ha (0.4%) (Chart 3.17b) Chart 3.15 Area Planted with Annual Crops per Household during Long Rainy Season and District 0.00 0.25 0.50 0.75 1.00 Iramba Manyoni Singida Rur Singida Urb District Area Planted (ha) Long Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops - Singida 0 30000 60000 90000 120000 150000 Maize Sorghum Sunflower Bulrush Millet Groundnuts Beans Finger Millet Paddy Chich Peas Cassava Sweet Potatoes Simsim Tobacco Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - Singida 0.00 0.50 1.00 1.50 2.00 2.50 Irish Potatoes Cotton Chick peas Maize Sunflower Sorghum Simsim Green Gram Bmillets Cauliflower Fmillets Paddy Cassava Beans Egg Plant Onions Groundnuts Crop Planted Area (ha) RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 20 Cereals and oil seeds and oil nuts are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because dry season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.4 Cereal Crop Production The total production of cereals was 89,468 tonnes. Maize was the dominant cereal crop at 54,396 tonnes which was 61 percent of total cereal crops produced, followed by sorghum (24%), bulrush millets (11%), paddy (2.2%), finger millets (1.5%) and wheat (0.02%) (Map. 10) The total area planted with cereals during the dry and long rainy seasons was 245,560 ha out of which 1,816 ha (0.7%) were planted in dry season and 243,744 ha (99.3%) were planted during the long rainy season. The long rainy season accounts for 99.6 percent of the total cereals produced in both seasons. The area planted with maize during the dry season was 98.8 percent of the total area planted with cereals in that season followed by sorghum (1.2%) (Table 3.2) The area planted with maize was large and it represented 55.9 percent of the total area planted with cereal crops, followed by sorghum (28.5%), bulrush millets (12.5%), finger millets (1.6%) and paddy (1.5%). The yield of paddy was 538 kg/ha, followed by wheat (483 kg/ha), maize (396 kg/ha), finger millets (348 kg/ha), bulrush millets (326 kg/ha and sorghum (310 kg/ha) (Chart 3.19). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Singida region during the long rainy season was 132,667, (74% of the total crop growing households in the region during the long rainy Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 1,795 340 190 135,482 54,056 399 137,277 54,396 396 Sorghum 21 11 533 69,884 21,692 310 69,905 21,703 310 Bulrush millets 0 0 0 30783 10,025 326 30,783 10,025 326 Finger Millet 0 0 0 3,901 1,357 348 3,901 1,357 348 Paddy 0 0 0 3,665 1,973 538 3,665 1,973 538 Wheat 0 0 0 29 14 483 29 14 483 Total 1,816 351 243,744 89,117 245,560 89,468 Chart 3.17 b: Percentage Distribution of Area planted with Annual Crops by Crop Type Cereals 76.4% Fruits and Vegetables 0.4% Oil seeds and Oil nuts 16.6% Cash crops 0.7% Pulses 4.2% Roots and Tubers 1.8% Cereals Oil seeds and Oil nuts Pulses Roots and Tubers Cash crops Fruits and Vegetables 1816 13342 0 5724 0 1249 197 52843 335 2226 0 0 100000 200000 300000 Area (hectares) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Dry Season Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 Maize Sorghum Bulrush millets Wheat Paddy Finger Millet Crop Area Planted (ha) 0.00 0.25 0.50 0.75 Yield (t/ha) Area Planted (ha) Yield (t/ha) Singida Urban Manyoni Iramba Singida Rural 132,986ha 10,943ha 63,160ha 114,330ha 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Manyoni Iramba Singida Urban 77% 91% 90% 94% Singida Rural 90.6 to 94 87.2 to 90.6 83.8 to 87.2 80.4 to 83.8 77 to 80.4 RESULTS 21 Tanzania Agriculture Sample Census Map 3.07 SINGIDA Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Area Percent of Utilized Land Area Map 3.08 SINGIDA Total Planted Area With Annual Crops by District Annual crops Planted Area Annual crops Planted Area Singida Urban Singida Rural Manyoni Iramba 9,438ha 44,688ha 98,190ha 93,244ha 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Manyoni Singida Rural Singida Urban Iramba 0ha 298ha 17ha 1,977ha 1.5% 0% 0.3% 0.2% 1,600 to 1,980 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 RESULTS 22 Tanzania Agriculture Sample Census Map 3.09 SINGIDA Area planted and Percentage During the Short Rainy Season by District Planted Area (ha) Planted Area (ha) Map 3.10 SINGIDA Area Planted with Cereals by District Planted Area (ha) Percentage of Area Planted Planted Area (ha) RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 season). The total production of maize was 54,056 tonnes from a planted area of 135,482 hectares resulting in a yield of 0.4 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tonnes) for the long rainy season. There was an increase in maize production 73% over the period of 1997 to 1999 after which the production remained constant until 2000. The average area planted with maize per household was 1.0 hectares however it ranged from 0.5 hectares in Singida Urban district to 1.2 hectares in Manyoni district. Iramba district had the largest area of maize (59,062 ha) followed by Singida Rural (42,699 ha), Manyoni (32,035 ha) and Singida Urban (1,686 ha). (Chart 3.21, Map 3.11 and map 3.12) Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 7 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 1999 and the area has remained constant ever since. However, the yield of maize has shown a gradual decline over the period 1995 to 1998 after which the yield remained almost steady to year 2002 then the yield dropped in 2003 (Chart 3.22). 3.3.4.2 Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Singida region during the long rainy season was 82,809. This represents 46 percent of the total crop growing households in Singida region in the long rainy season. The total production of sorghum was 21692 tonnes from a Chart 3.22 Time Series of Maize Planted Area and Yield - Singida 0 50000 100000 150000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area Yield Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 1686 32035 42699 59062 0 10000 20000 30000 40000 50000 60000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.0 0.3 0.6 0.9 1.2 1.5 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.23 Total Planted Area and Area of Sorghum per Household by District 29836 29315 8589 2143 0 10000 20000 30000 40000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.00 0.30 0.60 0.90 1.20 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Sorghum Production - Singida 22 60 59 59 71 75 0 20 40 60 80 1994/95 1995/96 1996/97 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.20: Time Series Data on Maize Production - Singida 88 114 123 54 88 51 66 0 25 50 75 100 125 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 24 planted area of 69,884 hectares resulting in a yield of 0.31 t/ha. The district with the largest area planted with sorghum was Iramba (29,836 ha) followed by Singida Rural (29,315 ha), Manyoni (8,589 ha) and Singida Urban (2,143 ha) (Map 3.13) There are significant variations in the average area planted per crop growing household among the districts ranging from 0.5 ha in Singida Urban district to 1.1 ha in Iramba district (Chart 3.23 and Map 3.14). There was a decreasing trend in the production of sorghum in 1995/96 to 2002/03. The production was almost steady from 1997 to 2000 at around 60,000 tonnes after which it dropped to 22,000 tonnes in the following year. Charts 3.24 and 3.25 shows that the yield and production of sorghum has dropped dramatically over the previous 7 years and the planted area decreased from 74,604 hectares in 1995 to 52,748 hectares in 1997, there after the area increased to 87,715 hectares in 2000 and then dropped to 69,905 hectares in 2003. The area planted with sorghum remained constant from 1999 to 2000 after which the area under production declined until 2003 (Chart 3.25). 3.3.4.3 Other Cereals Other cereals produced include bulrush millet, finger millet and paddy. Bulrush millets is produced in Singida Rural (16,562 ha), Iramba (6,949 ha), Singida Urban (5,156 ha) and Manyoni district (2,116 ha). Finger millet is produced in Singida Rural (3,428 ha), Singida Urban (399 ha) and Manyoni (75 ha). Paddy is produced in Manyoni (1,873 ha), Singida Rural (1,140 ha), Iramba (615 ha) and Singida Urban (39 ha) (Chart 3.26). 3.3.5 Oil seeds and Oil nuts Production The total production of oil seeds and oil nuts during the long rainy season was 24,367 tonnes. Sunflower production was higher than any other oil seed and oil nut crop in the region with a total production of 21,002 tonnes representing 86 percent of the total oil seeds and oil nuts production. This was followed by groundnut with 2,462 tonnes (10%), simsim (887 tonnes (4%) and soya beans 17 tonnes (0.1%) (Table 3.3) Table 3.3: Area, Production and Yield of Oil seeds and Oil nuts by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 279 335 1,201 40,590 21,002 517 40,728 21,281 522 Simsim 0 0 0 2,053 887 432 2,053 887 432 Groundnuts 0 0 0 10,146 2,462 243 25,662 10,146 243 Soyabeans 0 0 0 55 17 329 167 55 309 TOTAL 279 335 52,844 24,368 53,123 24,703 Chart 3.25 Time Series of Sorghum Planted Area and Yield - SGD 0 15000 30000 45000 60000 75000 90000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Yield (t/ha) Planted Area Yield Chart 3.26 Area Planted with Bulrush millets, Finger millets and Paddy by District 0 4000 8000 12000 16000 20000 Iramba Singida Rural Manyoni Singida Urban Bulrush millets Finger millets Paddy Chart 3.27 Area Planted and Yield of Major Oil seeds and Oil nuts 0 15000 30000 45000 Sunflower Simsim Groundnut Soyabeans Crop Area Planted (ha) 0.0 0.2 0.4 0.6 Yield (kg/ha) Yield (kg/ha) Singida Urban 1.2ha 0.5ha 1.2ha 0.8ha Singida Rural Manyoni Iramba 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Singida Urban Iramba Manyoni 59,062ha 1,686ha 32,035ha 42,699ha 0.3t/ha 0.4t/ha 0.5t/ha 0.5t/ha Singida Rural 48,000 to 60,000 36,000 to 48,000 24,000 to 36,000 12,000 to 24,000 0 to 12,000 Map 3.11 SINGIDA Planted Area and Yield of Maize by District Planted Area (ha) Planted Area (ha) Map 3.12 SINGIDA Area Planted per Maize Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 25 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 26 The area planted with sunflower was larger than any other oil seeds and oil nuts (12.7% of the total area planted with annual crops and vegetables) and it accounted for77 percent of the area planted with oil seeds and oil nuts, followed by groundnuts (19%), simsim (4%) and soya beans (0.1%). 3.3.5.1 Sunflower The number of households growing sunflower in Singida region was 45,857. The total production of sunflower in the region was 21,337 tonnes from a planted area of 40,869 hectares resulting in a yield of 0.5 t/ha. There has been a large decrease in production of sunflower over the period 1998/99 to 2002/03, from 40,046 tonnes in 1998/99 to 21,281 tonnes in 2002/03. Area planted increased from 32,495 hectares in 1998/99 to 40,590 hectares in 2002/03 (Chart 3.28) Fifty nine percent of the area planted with sunflower was located in Iramba district (23,946 ha) followed by Singida Rural (15,130 ha, 37%), Singida Urban (408 ha, 2.2%) and Manyoni (262 ha, 1.5%). The highest proportion of land with sunflower was found in Singida Urban followed by Singida Rural, Iramba and Manyoni (Chart 3.29 and Map 3.15). The largest area planted per sunflower growing household was found in Iramba district (1.04 ha) and the lowest was in Manyoni (0.45). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.30 and Map 3.16). Table 3.4: Area, Production and Yield of Pulses by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 2 9 4500 2 9 4500 Beans 0 0 0 8328 1645 198 8328 1645 198 Cowpeas 0 0 0 943 299 317 943 299 317 Green Gram 0 0 0 174 75 431 174 75 431 Chick Peas 0 0 0 3201 1624 507 3201 1624 507 Bambaranuts 0 0 0 695 169 243 695 169 243 TOTAL 0 0 13,343 3,821 13,343 3,821 Chart 3.28 Time Series Data on Sunflower Production - Singida 40046 21281 0 10,000 20,000 30,000 40,000 50,000 1998/99 2002/03 Year Production ( tonnes) Chart 3.29 Percent of Sunflower Planted Area and Percent of Total Land with Sunflower by District 0.0 15.0 30.0 45.0 60.0 Iramba Singida Rur Manyoni Singida Urb District Percent of Land 0.0 5.0 10.0 15.0 20.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.25 0.50 0.75 1.00 Area per Household (ha Iramba Singida Rur Singida Urb Manyoni District Chart 3.30 Area Planted per Sunflower Growing Households by District (Long Rainy Season Only) Singida Urban Singida Rural Iramba 0.5ha 1.1ha 0.7ha 0.8ha Manyoni 0.9 to 1.1 0.8 to 0.9 0.7 to 0.8 0.6 to 0.7 0.5 to 0.6 Manyoni Singida Urban Iramba 8,589ha 29,836ha 29,315ha 0.3t/ha 0.3t/ha 0.2t/ha 0.4t/hat/ha Singida Rural 2,143ha 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.13 SINGIDA Planted Area and Yield of Sorghum by District Planted Area (ha) Planted Area (ha) Map 3.14 SINGIDA Area Planted per Sorghum Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 27 Singida Urban Iramba Singida Rural Manyoni 905 23,946 15,130 609 0.45 0.52 0.53 0.43 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Singida Urban 0.72 1.04 0.75 0.45 Singida Rural Manyoni Iramba 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Map 3.15 SINGIDA Planted Area and Yield of Sunflower by District Planted Area (ha) Planted Area (ha) Map 3.16 SINGIDA Area Planted per Sunflower Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 28 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 3.3.6 Pulse Crops Production The total area planted with pulses was 13,343 hectares out of which 8,328 ha were planted with beans (62.4 percent of the total area planted with pulses), followed by chick peas (3,201 ha, 24.0%), cow peas (943 ha, 7.1%) bambaranuts 695 ha, (5.2%) and green gram (174 ha, 1.3%). pigeon peas, field peas and soya beans were not cultivated in the region. The total production of pulses was 3,821 tonnes. Beans were the most cultivated crop producing 1,645 tonnes which accounted for 43.1 percent of the total pulse production. This was followed by chick peas (1624t, 42.5%), cow peas (299t, 7.8%), bambaranuts (169t, 4.4%), green gram (75t, 2.0%) and mung beans (9t, 0.2%). Mung beans and chick peas had relatively higher yields of 4,500 and 507 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were green gram 431 kgs/ha, cowpeas 317 kgs/ha and beans 198 kgs/ha. (Chart 3,32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Singida region was 19,913. The total production of beans in the region was 1,645 tonnes from a planted area of 8,328 hectares resulting in a yield of 0.2 t/ha. The largest area planted with beans in the region was in Iramba (4,209 ha, 50.5%) (Chart 3.32 and Map 3.17), however, the largest area planted with beans per household was in Manyoni district (0.5 ha) (Chart 3.33), followed by Iramba district (0.4 ha), Singida Rural (0.3) and Singida Urban (0.2 ha). The average area planted per household in the region during the long rainy season was 0.4 ha (Map 3.18). Chart 3.31 Area Planted and Yield of Major Pulse Crops 0 2,000 4,000 6,000 8,000 10,000 Beans Chich Peas Cowpeas Bambaranuts Green Gram Mung Beans Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) Yield (kg/ha) Chart 3.32 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 Iramba Manyoni Singida Rur Singida Urb District Percent of Land 0 10 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.90 0.42 0.20 0.17 0.00 0.25 0.50 0.75 1.00 Area per Household Manyoni Iramba Singida Urb Singida Rur District Chart 3.33 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.34: Time Series Data on Beans Production - Singida 1,153 1,645 1,390 1,153 - 400 800 1,200 1,600 2,000 1997/98 1998/99 1999/2000 2002/03 Year Production tonnes RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 In Singida region, bean production has increased from 1,390 tonnes in 1997/98 to 1,645 tonnes in 2002/03 (Chart 3.34). Charts 3.35 and 3.36 show that, the yield of beans was high in 1996/96 (2.7 t/ha), Over the period 1998/99 to 1999/00 the yield of beans remained constant at around 0.3 t/ha (Chart 3.35). The quantity produced has increased and this has been due to a large increase in the area under production. The area planted with beans has increased erratically over the period from 1996 to 2003. 3.3.7 Roots and Tuber Crops Production The total production of roots and tubers was 5,597 tonnes. Sweet potatoes production was higher than any other root and tuber crop in the region with a total production of 2,807 tonnes representing 50.1 percent of the total root and tuber crops production. This was followed by cassava with 2,424 tonnes (43.3%), Irish potatoes (364t, 6.5%) and yams (2t, 0.04%). (Table 3.5). The area planted with cassava was larger than any other root and tuber crops and it accounted for 52.3 percent of the area planted with roots and tubers, followed by sweet potatoes (44.8%), Irish potatoes (2.8% and yams (0.1%). The yield was high for Irish potatoes (2.3 t/ha) and sweet potatoes (1.1 t/ha), followed by cassava (0.8 t/ha) and yams (0.7 t/ha). 3.3.7.1 Cassava The number of households growing cassava in the region was 6,610. This represents 3.7 percent of the total crop growing households in the region. The total production of cassava during the census year was 2,424 tonnes from a planted area of 2,995 hectares resulting in a yield of 0.8t/ha. Table 3.5: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 0 0 0 2995 2424 809 2995 2424 809 Sweet Potatoes 0 0 0 2564 2807 1095 2564 2807 1095 Irish Potatoes 0 0 0 161 364 2261 161 364 2261 Yams 0 0 0 3 2 667 3 2 667 Cocoyam 0 0 0 0 0 0 0 0 0 TOTAL 0 0 5,724 5,597 5,724 5,597 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.35 Time Series of Beans Planted Area and Yield - Singida 0 3000 6000 9000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.00 1.00 2.00 3.00 Yield (t/ha) Area Yield Chart 3.36 Area Planted with Cassava during the Census/Survey Years 0 12,000 24,000 36,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava Singida Urban 0.4hha 0.2ha 0.3ha 0.5ha Singida Rural Manyoni Iramba 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Iramba Singida Urban 4,208.54ha 17.22ha 1,051.14ha 3,050.75ha 0.1t/hha 0.3t/ha 0.4t/ha 0.3t/ha Singida Rural Manyoni 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.17 SINGIDA Planted Area and Yield of Beans by District Planted Area (ha) Planted Area (ha) Map 3.18 SINGIDA Area Planted per Beans Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 31 Singida Urban 6,294 8,080 488 6% 10% 11% 1% Singida Rural Manyoni Iramba 667 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Manyoni Singida Urban Iramba 1,252 4,606 4,902 3.8% 7.1% 7.4% 6.7% Singida Rural 792 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.35 SINGIDA Number and percent of smallholder Planted trees by district Number of smallholder Number of smallholder Planted trees Number of households With water harvesting Bunds Number of households With water harvesting Bunds Map 3.36 SINGIDA Number and percent of households With water harvesting Bunds by District Percent of households With water harvesting Bunds Tanzania Agriculture Sample Census Percent of smallholder Planted trees RESULT 32 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 33 Previous censuses and surveys indicate that the area planted with cassava increased from 1,532 in 1994/95 ha in 1994/95 to 30,783 ha in 2002/03 (Chart 3.36). The area planted with cassava accounted for 0.94 percent of the total area planted with annual crops and vegetables during the long rainy season. Manyoni district had the largest planted area of cassava (1,019 ha, 34% of the cassava planted area in the region), followed by Singida Rural (964 ha, 32%), Iramba (842 ha, 28%) and Singida Urban (171 ha, 0.6%) (Map 3.19). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Manyoni district (1.61%). This was followed by Singida Urban (1.56%), Singida Rural (0.84%) and Iramba district (0.64%) (Chart 3.37) The average planted area of cassava per cassava growing households was 0.5 hectares. However, there were small district variations. The area planted per cassava growing household was greatest in Singida Rural (0.8 ha). This was followed by Manyoni (0.6 ha), Iramba (0.27 ha) and Singida Urban (0.26 ha) (Chart 3.38 and Map 3.20). 3.3.7.2 Sweet potatoes The number of households growing sweet potatoes in Singida region was 8,432. This was 3 percent of the total root and tuber crop growing households during the long rainy season. The total production of sweet potatoes during the census year was 2,807 tonnes from a planted area of 2,564 hectares resulting in a yield of 1.1t/ha. Iramba district has the largest planted area for sweet potatoes (911 ha, 36%), followed by Singida Rural (755 ha, 29%), Manyoni (726 ha, 28%) and Singida Urban (171 ha, 7%) (Chart 3.39).Other root and tuber crops are of minor important in terms of area planted compared to cassava and sweet potatoes. The average planted area of sweet potatoes per sweet potatoes growing households was 0.30 hectares. However, there were small district variations. The area planted per sweet potatoes growing household was greatest in Manyoni (0.39 ha). This was followed by Singida Rural (0.33 ha), Singida Urban (0.28 ha) and Iramba (0.23 ha) (Chart 3.40) 0.8 0.6 0.3 0.3 0.0 0.2 0.4 0.6 0.8 Area per Household Singida Rur Manyoni Iramba Singida Urb District Chart 3.38 Cassava Planted Area per Cassava Growing Households by District Chart 3.37 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 34.0 32.2 28.1 5.7 - 10.00 20.00 30.00 40.00 Manyoni Singida Rur Iramba Singida Urb District Percent of Total Area Planted 0.0 0.6 1.2 1.8 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.39 0.33 0.28 0.25 0.00 0.20 0.40 Area per Household Manyoni Singida Rur Singida Urb Iramba District Chart 3.40 Sweet potatoes Planted Area per Sweet potatoes Growing Households by District Chart 3.39 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 911 755 726 171 0 250 500 750 1000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.00 0.10 0.20 0.30 0.40 Area Planted per Household Planted Area (ha) Area per hh RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 3.3.8 Fruits and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. The dry season is relatively important for production of tomatoes, spinach, cucumber and egg plant. However, most of fruit and vegetables are produced during long rainy season. The total production of fruits and vegetables was 1,797 tonnes. The most cultivated fruit and vegetable crop was onions with a production of 830 tonnes (46% of the total fruit and vegetables produced) followed by tomatoes (534t, 30%) and cauliflower (15t, 1%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of onions was 1,072 kg/ha, tomatoes (1,648 kg/ha) and cauliflower (185 kg/ha) (Chart 3.41). 3.3.8.1 Onion The number of households growing tomatoes in the region during the long rainy season was 1,928. This represented 1.2 percent of the total crop growing households in the region during the long rainy season. The highest number of households growing onion was found in Singida Rural followed by Iramba, Singida Urban and Manyoni. (Chart 3.42) Singida Rural district had the largest planted area of onions (84.8% of the total area planted with tomatoes in the region), followed by Iramba (12.9%), Singida Urban (1.5%) and Manyoni (0.7%) (Map 3.21). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 0 0 0 20 8 400 20 8 400 Radish 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 16 14 875 16 14 875 Onions 0 0 0 775 830 1,071 775 830 1,071 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 50 169 3380 50 169 3380 Tomatoes 109 266 2440 215 268 1,247 324 534 1,648 Spinnach 15 12 800 19 19 1000 34 31 912 Carrot 0 0 0 0 0 0 0 0 0 Chillies 0 0 0 4 5 1250 4 5 1250 Amaranths 0 0 0 36 60 1667 36 60 1667 Pumpkins 10 10 1000 0 0 0 10 10 1000 Cucumber 39 6 154 17 0 0 56 6 107 Egg Plant 24 96 4000 17 19 1118 41 115 2805 Cauliflower 0 0 0 80 15 188 80 15 188 Total 197 390 1,249 1,407 1,446 1,797 Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 200 400 600 800 Onions Tomatoes Cauliflower Cucumber Cabbage Egg Plant Others Crop A rea Planted (ha) 0 300 600 900 1200 Y ield (kg/ha) 0 500 1000 1500 Area per Household (ha). Singida Rur Iramba Singida Urb Manyoni District Chart 3.42 Number of households Growing Onion by District (Long Rainy Season Only) Singida Urban 0.3ha 0.3ha 0.8ha 0.6ha Singida Rural Manyoni Iramba 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Singida Urban Iramba Manyoni 842ha 964ha 1,019ha 0.9t/ha 1.3t/ha 0.4t/ha 0.8t/ha Singida Rural 171ha 1,000 to 1,250 750 to 1,000 500 to 750 250 to 500 0 to 250 Map 3.19 SINGIDA Planted Area and Yield of Cassava by District Planted Area (ha) Planted Area (ha) Map 3.20 SINGIDA Area Planted per Cassava Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 35 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 The highest percentage of land with onion was found in Singida Rural, followed by Singida Urban, Iramba and Manyoni districts (Chart 3.43). The largest area planted per onion growing household was found in Singida Rural district (0.45 ha) followed by Iramba (0.40 ha), Singida Rural (0.09 ha) and Manyoni (0.07 ha) (Chart 3.44 and Map 3.22). The total area planted with onion accounted for 0.6 percent of the total area planted with annual crops and vegetables during the long rainy seasons. 3.3.8.2 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 1,802. This represented one percent of the total crop growing households in the region in the long rainy season. Singida Rural district had the largest planted area of tomatoes during the long rainy season (108 ha, 50.5% of the total area planted with tomato in the region), followed by Singida Urban (82 ha, 38.3%), Manyoni (17 ha, 7.9%) and Iramba (7 ha, 3.3%) (Chart 3.45 and Map 3.23 and 2.24) The total area planted with tomatoes accounted for 0.07 percent of the total area planted with annual crops and vegetables during the long rainy seasons. 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once they mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature but survive for more than one year and are thus treated as a permanent crops. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 9,242 hectares (3% of the area planted with annual crops in the region). However, the area planted with crops is not the actual physical land area as it includes the area planted more than Chart 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District 0.0 15.0 30.0 45.0 60.0 75.0 90.0 Singida Rur Iramba Singida Urb Manyoni District Percent of Land 0.00 0.20 0.40 0.60 0.80 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha).. Singida Rur Iramba Singida Urb Manyoni District Chart 3.44 Area Planted per Onion Growing Household by District (Long Rainy Season Only) Chart 3.45 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Singida Rur Singida Urb Manyoni Iramba District Percent of Land 0.00 0.25 0.50 0.75 1.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.12 to 0.15 0.09 to 0.12 0.06 to 0.09 0.03 to 0.06 0 to 0.03 Singida Urban 0.14ha 0.05ha 0.13ha 0.07ha Singida Rural Manyoni Iramba Singida Urban 7ha 108ha 17ha 1.4t/ha 1.5t/ha 0.9t/ha 2.4t/ha Singida Rural Manyoni Iramba 82ha 88 to 110 66 to 88 44 to 66 22 to 44 0 to 22 Map 3.23 SINGIDA Planted Area and Yield of Tomatoes by District Planted Area (ha) Planted Area (ha) Map 3.24 SINGIDA Area Planted per Tomatoes Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 37 RESULT RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in Chart 3.46. The most important permanent crop in Singida region is Mango which had a planted area of 3,784 ha, (40% of the area planted with all permanent crops) followed by banana (3,373 ha, 36%), guava (1,268 ha, 14%) and sugarcane (541 ha, 6%). Each of the remaining permanent crops had an area of less than 2 percent of the total area planted with permanent crops (Chart 3.47). Manyoni district had the largest area under smallholder permanent crops (131,853 ha, 31.6%). This is followed by Singida Urban (117,667 ha, 28.2%), Iramba (97,731 ha, 23.4%) and Singida Rural (70,461 ha, 16.9%). However, Manyoni had the largest area per permanent crop growing household (1.8 ha) followed by Singida Rural (0.7 ha), Singida Urban (0.5 ha) and Iramba (0.4 ha) (Chart 3.48). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Singida Urban had the highest (6.0%) followed by Manyoni (4.8%), Singida Rural (3.3%) and Iramba (1.1%) 3.4.1 Mango The total production of mangoes by smallholders was 254 tonnes. In terms of area planted, mango was the most important permanent crop grown by smallholders in the region. They were grown by 2,599 households (26% of the total crop growing households). The average area planted with mango per mango growing households was moderate at around 1.5 ha per mango growing household and the average yield obtained by smallholders was 3,331 kg/ha from a harvest area of 76 hectares. Singida Rural had the largest area of mango in the region (3,940 ha, 43%) followed by Manyoni (3,159 ha, 34%), Iramba (1,449 ha, 16%) and Singida Urban (695 ha, 8%) (Map 3.25). However, the average area planted with mango per mango growing household was highest in Manyoni (1.8 ha) followed by Singida Rural (0.7 ha), Singida Urban (0.5 ha) and Iramba (0.4 ha) (Chart 3.49 and Map 3.26). Chart 3.47 Area Planted (ha) w ith Main Perennial Crops Orange, 50, 1% Guava, 1,268, 14% Other, 21, 0% Sugarcane, 541, 6% Star Fruit, 70, 1% Pigeon Pea, 65, 1% Mango, 3,784, 40% Paw paw , 72, 1% Banana, 3,373, 36% Guava Orange Banana Paw paw Mango Star Fruit Pigeon Pea Sugarcane Other Chart 3.48 Percent of Area Planted and Average Planted Area with Permanent Crops by District 28.2 23.4 16.9 31.6 0.0 9.0 18.0 27.0 36.0 Manyoni Singida Urban Iramba Singida Rural District % of Total Area Planted 0.0 0.5 1.0 1.5 2.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.49 Percent of Area Planted with Mango and Average Planted Area per Household by District 16 34 8 43 0 20 40 60 Singida Rural Manyoni Iramba Singida Urban District % of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.46 Area Planted for Annual and Permanent Crops Annual Crops, 319,143, 97% Permanent Crops, 9,242, 3% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 39 3.4.2 Bananas The total production of bananas by smallholders was 873 tonnes. In terms of area planted, banana was the second most important permanent crop grown by smallholders in the region. It was grown by 2,937 households (0.9% of the total crop growing households). The average area planted with bananas per household was moderate at around 1.1 ha per banana growing household and the average yield obtained by smallholders was 3,371 kg/ha from a harvest area of 259 hectares. Singida Rural had the largest area of bananas in the region (2,739 ha, 81.2%) followed by Iramba (503 ha, 14.9%), Manyoni (86 ha, 2.5%) and Singida Urban (45 ha, 1.3%) (Map 3.27) However, the average area planted with bananas per banana planting household was highest in Singida Rural (2.1 ha) followed by Iramba (0.5 ha), Manyoni (0.21 ha) and Singida Urban (0.18 ha). (Chart 3.50 and Map 3.28) 3.3.8 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 2,074 ha was planted with other annual crops and tobacco was the most prominent followed by cotton. Cash crops were grown in long rainy season only. 3.3.9.1 Tobacco Only 1,083 tonnes of tobacco were produced in Singida region on a planted area of 1,387 ha. It was produced during the long rainy season only. The crop is grown in Manyoni district only (Chart 3.51b) and only 1.0 ha was grown per household. 3.3.9.2 Cotton The quantity of cotton produced was 275 tonnes. Cotton had a planted area of 687 ha, all of which was planted in the long rainy season. Cotton was produced in Manyoni district only. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 687 275 400 687 275 400 Tobacco 0 0 0 1,387 1,083 780 1,387 1,083 780 Jute 0 0 0 0 0 0 0 0 0 TOTAL 0 0 2,074 1,358 2,074 1,358 Chart 3.50 Percent of Area Planted with Bananas and Average Planted Area per Household by District 14.9 1.3 81.2 2.5 0.0 30.0 60.0 90.0 Singida Rural Iramba Manyoni Singida Urban District % of Total Area Planted 0.0 0.5 1.0 1.5 2.0 2.5 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51a:Planted Area with Other Crops (Cash Crops) Tobacco, 1,387, 67% Cotton, 687, 33% Cotton Tobacco Chart 3.51b Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 80.0 100.0 Iramba Singida Rur Manyoni Singida Urb District Percent of Land 0.00 0.80 1.60 2.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Singida Urban 0.5 0.4 0.7 1.8 Singida Rural Manyoni Iramba 2 to 2.5 1.5 to 2 1 to 1.5 0.5 to 1 0 to 0.5 Singida Urban Singida Rural 1,449 695 3,940 3,159 Manyoni Iramba 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Map 3.25 SINGIDA Planted Area and Yield of Mango by District Planted Area (ha) Planted Area (ha) Map 3.26 SINGIDA Area Planted per Mango Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULT 40 Singida Urban Iramba 0.18ha 0.51ha 2.13ha 0.21ha Singida Rural Manyoni 2 to 2.5 1.5 to 2 1 to 1.5 0.5 to 1 0 to 0.5 Singida Urban 45ha 2,739ha 503ha 86ha 3.253t/ha 2.309t/ha 3.363t/ha 7.758t/ha Singida Rural Manyoni Iramba 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Map 3.27 SINGIDA Planted Area and Yield of Banana by District Planted Area (ha) Planted Area (ha) Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census Map 3.28 SINGIDA Area Planted per Banana Growing Household by District RESULT 41 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 42 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period and burning, hand slashing or tractor slashing, which is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 267,954 ha which represented 84.3 percent of the total planted area, followed by bush clearing (29,029 ha, 9.1%) and burning (13,722 ha, 4.3%). No land clearing, tractor slashing and other means are less important methods for land clearing and they represent 1.9, 0.2 and 0.04 percent respectively (Chart 3.51c and Table 3.8 ). 3.5.2 Methods of Soil Preparation Oxen ploughing is the most used method of preparation as it was used in an area of 207,558 ha which represented 65 percent of the total planted area, followed by hand cultivation (110,132 ha, 34%) and tractor ploughing (2,287 ha, 1%) (Chart 3.52). In Singida region, Iramba district had the largest planted area cultivated with oxen (118,470 hectares, 57.1%) followed by Singida Rural (68,074 ha, 2.8%), Manyoni (18,799 ha, 9.0%) and Singida Urban (2,215 ha, 1.1%). Table 3.8: Land Clearing Methods Long Rainy Season Dry Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 156,628 267,954 84.3 1,075 2,335 99.5 157,703 270,289 84.4 No Land Clearing 2,195 6,180 1.9 0 0 0 2,195 6,180 1.9 Mostly Bush Clearance 11,822 29,029 9.1 120 12 0.5 11,942 29,041 9.1 Mostly Burning 8,012 13,722 4.3 0 0 0 8,012 13,722 4.3 Mostly Tractor Slashing 556 684 0.2 0 0 0 556 684 0.2 Other 144 117 0 0 0 0 144 117 0 Total 179,357 317686 100 1,195 2,347 100 180,552 320,033 100 Chart 3.52 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 2,299 , 1% Mostly Hand Hoe Ploughing, 111,007, 34% Mostly Oxen Ploughing, 208,962, 65% Chart 3.51c Area Planted with Annual Crops by Method of Land Clearing During the Long Rainy Season 267,954 29,029 13,722 6,180 684 117 0 100,000 200,000 300,000 Mostly Hand S lashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor S lashing Ot her Plant e d A re a RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 During the long rainy season, 68.9 percent of the total area cultivated by using oxen was planted with cereals followed by oil seeds (18.8%), pulses (7.3%) roots and tubers (3.2%) fruit and vegetables (1.3%) and cash crops (0.5%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 62,511 ha which represents 20 percent of the total planted with the annual crops and vegetables area. Cereals had the largest area planted with improved seeds (43,089 ha, 73.3% of the planted area with improved seeds) followed by Oil seed (10,861 ha, 18.5%), pulses (2,159 ha, 3.7%), cash crops (1,797 ha, 3.1%), fruit and vegetables (550 ha, 0.9%) and root and tubers (341 ha, 0.6%) (Chart 3.55). However, the use of improved seed in cash crops and fruit and vegetables is much greater than in other crop types (81% and 44% respectively), only 8 percent of the planted area for roots and tubers used improved seeds (Chart 3.56). Table3.9 Planted Area by Type of Fertiliser Use and District - Long Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Iramba 62,040 2,569 93 64,702 66,307 Singida R 42,988 2,363 250 45,601 68,431 Manyoni 8,817 547 3,144 12,508 50,652 Singida U 5,765 473 0 6,238 4,688 Total 119,610 5,952 3,487 129,049 190,078 0 40000 80000 120000 Area Cultivated Iramba Singida Rural Manyoni Singida Urban District Chart 3.53 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.54 Planted Area of Improved Seeds - Singida With Improved Seeds, 62,511, 20% Without Improved Seeds, 255,174, 80% v Chart 3.55 Planted Area with Improved Seed by Crop Type Cereals, 43,089, 73.3% Pulses, 2,159, 3.7% Roots & Tubers, 341, 0.6% Oilseeds , 10,861, 18.5% Fruits & Vegetables, 550, 0.9% Cash Crops, 1,797, 3.1% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruit & Vegetables Cash Crops Crop Type Chart 3.56 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 44 3.5.4 Fertilizer Use The use of fertilisers on annual crops is moderate with a planted area of only 129,050 ha (40% of the total planted area in the region). The planted area without fertiliser for annual crops was 190,078 hectares representing 60 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 119,610 ha which represents 37.5 percent of the total planted area (92.7% of the area planted with fertiliser application in the region). This was followed by compost (5,952 ha, 4.6%). Inorganic fertilizers were used on a very small area and represented only 2.7 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Iramba district (50.1%) followed by Singida Rural (35.3%), Manyoni (9.7%) and Singida Urban (4.8%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 255,726 households, 64%) (Map 3.29). The percentage of the planted area applied with fertilisers was highest for cereals (88.1% of the area planted with fertilizers during the long rainy season). This was followed by oil seeds and oil nuts (8.1%), pulses (2.0%), cash crops (1.3%), fruit and vegetables (0.4%) and roots and tubers (0.1%) (Table 3.10). Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Cereals 111,345 106,556 6,471 5,137 2,126 1,984 153,358 130,068 273,300 243,745 Roots & Tubers 476 87 79 32 0 . 14,599 5,605 15,154 5,724 Pulses 6,661 2,412 370 91 74 72 21,641 10,767 28,746 13,342 Oil seeds & Oil nuts 10,060 9,727 879 680 190 90 63,321 42,346 74,450 52,843 Fruits & Vegetables 2,464 452 125 13 78 6 2,501 778 5,168 1,249 Cash Crops 283 376 0 . 1,278 1,335 306 515 1,867 2,226 Total 131,289 119,610 7,924 5,953 3,746 3,487 255,726 190,079 398,685 319,129 0 50,000 100,000 150,000 Area (ha) Iramba Singida R Manyoni Singida U District Chart 3.58 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.57 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 119,582, 37.5% Mostly Inorganic Fertilizer, 3,487, 1.1% Mostly Compost, 5,952, 1.9% No Fertilizer Applied, 190,122, 59.6% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 3.5.4.1 Farm Yard Manure Use The number of households that applied farm yard manure in their annual crops during the long rainy season was 131,289 and it was applied to 119,610 ha. The total planted area applied with farm yard manure in Singida region was 119,610 ha representing 37 percent of the total area planted with annual crops during that season (Table 3.10). Cereals had the highest percentage of the area applied with farm yard manure (89.1%), followed by oil seed and oil nuts (8.1%), pulses (2%), fruit and vegetables (0.4%), cash crop (0.3%) and roots and tubers (0.1%) However, cereals had the highest proportion of its planted area with farm yard manure (43.7% of the total area planted with cereals). This was followed by fruit and vegetables (36.2%), oil seeds (18.4%), pulses (18.1%), cash crop (16.9%) and roots and tubers (1.5%). (Charts 3.59 and 3.60). Farm yard manure was mostly used in Iramba (46.5% of the total planted area in the district), followed by Singida Rural (41.6%), Manyoni (38.2%) and Singida Urban (16.3%) (Chart 3.61) 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Singida region was 3,487 ha which represents 1.1 percent of the total planted area with annuals during the long rainy season and 2.7 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizers on their annual crops during the long rainy season was 3,746 (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (56.9% of the total area applied with inorganic fertilizers), followed by cash crop (38.3%), oil seeds (2.6%), and pulses (2.1%) (Chart 3.62). However, the proportion of cash crops with inorganic fertilizers was 60 percent higher than other crop types, followed by cereals (.8%), oil seeds (.2%) and fruit and vegetables (.5%) (Chart 3.63) Chart 3.59 Planted Area with Farm Yard Manure by Crop Type - Singida Cereals, 106,556, 89.1% Roots & Tubers, 87, 0.1% Pulses, 2,412, 2.0% Oilseeds, 9,727, 8.1% Fruits & Vegetables, 452, 0.4% Cash Crop, 376, 0.3% 0 15 30 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.60 Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.62 Planted Area with Inorganic Fertilizer by Crop Type - Singida Roots & Tubers, 0, 0.0% Pulses, 72, 2.1% Oilseeds, 90, 2.6% Fruit & Vegetables, 6, 0.2% Cereals, 1,984, 56.9% Cash Crop, 1,335, 38.3% Chart 3.61 Proportion of Planted Area Applied with Farm Yard Manure by District - Singida 0.0 10.0 20.0 30.0 40.0 50.0 Iramba Singida R Manyoni Singida U District Percent Manyoni Singida Urban Iramba 4,202 1,113 2,867 3,916 6.7 10.2 2.2 3.4 Singida Rural 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Singida Urban Iramba 68,634 69,760 52,847 51 52 61 84 Singida Rural Manyoni 5,611 60,000 to 75,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Map 3.29 SINGIDA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Planted Area (ha) Planted Area (ha) with No Application of Fertilizer Planted Area (ha) Percent of Planted Area (ha) with No Application of Fertilizer Planted Area (ha) with Irrigation Tanzania Agriculture Sample Census Map 3.30 SINGIDA Area Planted and Percent of Total Planted Area with Irrigation by District Percent of Planted Area (ha) with Irrigation RESULT 46 Iramba Singida Urban Manyoni 24,877 36,760 17,251 51% 45% 42% 46% Singida Rural 2,833 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Singida Urban Manyoni 51% 42% 46% Singida Rural Iramba 45% 50 to 52 48 to 50 46 to 48 44 to 46 42 to 44 Map 3.31 SINGIDA Percent of households Storing crops for 3 to 6 momths by district Percent of households Storing Crops Percent of households Storing Crops Number of Households Selling Crops Number of Households Selling Crops Map 3.32 SINGIDA Number of Households and Percent of Total Households Selling Crops by District Percent of Total Households Selling Crops Tanzania Agriculture Sample Census RESULT 47 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 Inorganic fertiliser is mostly used in Manyoni (5.0% of the total planted area in the district), followed by Singida Rural (0.2%) and Iramba (0.1%). Singida Urban district used virtually no inorganic fertiliser. (Chart 3.64). In permanent crops inorganic fertiliser were used mainly on cotton (100%). 3.5.4.3 Compost Use The total planted area applied with compost was 5,953 ha which represents only 1.9 percent of the total planted area with annual crops in the region and 4.6 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 7,924 The proportion of area applied with compost was very low for each type of crop (0 to 2%); however the distribution of the total area using compost manure shows that 86 percent of this area was cultivated with cereals, followed by oil seeds (11%), pulses (5%) and root and tubers (1%) (Chart 3.65) Compost is mostly used in Singida Urban (4.3% of the total planted area in the district), and this is closely followed by Singida Rural (2.1%), Iramba (2.0%) and Manyoni (0.9%) (Chart 3.67) 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 24,484 ha of annual crops and vegetables. 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.63 Percentage of Planted Area with Inorganic Fertilizer by Crop Type - Singida Chart 3.64 Proportion of Planted Area Applied with Inorganic Fertiliser by District - Singida 0.0 2.0 4.0 6.0 Manyoni Singida R Iramba Singida U District Percent Chart 3.65 Planted Area with Compost by Crop Type - Singida Roots & Tubers, 32, 1% Fruits & Vegetables, 13, 0% Pulses, 91, 2% Oilseeds, 680, 11% Cash Crop, 0, 0% 0 6 12 18 24 30 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.66 Percentage of Planted Area with Compost by Crop Type- Singida Chart 3.67 Proportion of Planted Area Applied with Compost by District - Singida 0.0 1.0 2.0 3.0 4.0 Singida U Singida R Iramba Manyoni District Percent RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 Insecticides are the most common pesticide in use in the region (58% of the total area applied with pesticides). This was followed by fungicides (29%) and herbicides (13%) (Chart 3.68). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 13,763 ha which represented 4.2 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (9,611 ha, 70.1% of the total planted area with insecticides) followed by cash crops (1,928 ha, 14.1%), oil seeds and oil nuts (886 ha, 6.5%), pulses (750 ha, 5.5%), fruit and vegetable (454 ha, 3.3%) and roots and tubers (86 ha, 0.6%) (Chart 3.69). However, the percent of insecticides used in cash crops and fruits and vegetables is much greater than in other crop types (86.6 and 36.4% respectively), while only 1.7 percent of oil seed crops were applied with insecticides (Chart 3.70). Manyoni had the highest percent of planted area with insecticides (16.7% of the total planted area with annual crops in the district). This was followed by Iramba (8.5%), Singida Rural (6.3%) and Singida Urban (4.7%) (Chart 3.71). Chart 3.68 Planted Area (ha) by Pesticide Use Fungicides, 7,220 , 29% Insecticides, 14,057 , 58% Herbicides, 3,207 , 13% Chart 3.69 Planted Area Applied with Insecticides by Crop Type Oil seeds & Oil nuts, 886, 6% Pulses, 750, 5% Roots & Tubers, 86, 1% Fruits & Vegetables, 454, 3% Cash crops, 1928, 14% Cereals, 9611, 71% 0.0 25.0 50.0 75.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.70 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.71 Percent of Planted Area Applied with Insecticides by District - Singida 0.0 6.0 12.0 18.0 Manyoni Iramba Singida Rural Singida Urban District Percent RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.5.2 Herbicide Use The planted area applied with herbicides was 2,868 ha which represented 0.9 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,777 ha, 62%) followed by oil seeds (856 ha, 30%), pulses (154 ha, 5%), and roots and tubers (49 ha, 2%) and cash crops (32ha, 1%) There was no herbicide use in fruit and vegetables (Chart 3.72). However, the percent of herbicide use on oil seeds, cash crops and pulses was much greater than in other crop types (1.6%, 1.4% and 1.2% respectively) while only 0.7 percent of cereals were applied with herbicides (Chart 3.73). The top six annual crops with highest percentage use of herbicides in terms of planted area were sunflower (28.0%), maize (22.2%), bulrush millet (21.8%), sorghum (16.6%), beans (5.4%) and groundnuts (1.8%). Singida Rural had the highest percent of planted area with herbicides (1.61% of the total planted area with annual crops in the district). This was followed by Manyoni (0.69%), Iramba (0.66%) and Singida Urban (0.32%) (Chart 3.74). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 3,487 ha which represented 1.1 percent of the total planted area for annual crops and vegetables. Cereals had the planted area applied with fungicide (2,513 ha, 72.6%) followed by cash crops (597 ha, 17.2%), oil seeds (167 ha, 4.8%), fruit and vegetables (85 ha, 2.4%), pulses (52ha, 1.5%) and roots and tubers (49 ha, 1.4%) (Chart 3.75) Chart 3.74 Proportion of Planted Area Applied with Herbicides by District - Singida 0.00 0.60 1.20 1.80 Singida Rural Manyoni Iramba Singida Urban District Percent Chart 3.75 Planted Area Applied with Fungicides by Crop Type Oil seeds, 167, 4.8% Fruits & Vegetables, 85, 2.4% Cash crops, 597, 17.2% Roots & Tubers, 49, 1.4% Pulses, 52, 1.5% Cereals, 2,513, 72.6% Chart 3.72 Planted Area Applied with Herbicides by Crop Type Pulses, 154, 5% Roots & Tubers, 49, 2% Cereals, 1777, 62% Cash crops, 32, 1% Oil seeds, 856, 30% 0.0 0.6 1.2 1.8 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruit & Vegetables Cash crops Crop Type Chart 3.73 Percentage of Crop Type Planted Area Applied with Herbicides RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 However, the percentage use of fungicide was mainly in cash crops (26.8%) (Chart 3.76). Annual crops with more than 20 percent fungicide use were sorghum (27%) and maize (26%) Manyoni had the highest percent of planted area with fungicides (4.6% of the total planted area with annual crops in the district). This was followed by Singida Rural (1.9%), Iramba (1.2%) and Singida Urban (1.0%) (Chart 3.77). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by draft animals (0.26%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 85.4 percent of the total area planted with cereals during the long rainy season was threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.2 percent, 5.2 percent and 0.6 percent of the total planted area respectively. The remaining 8.6 percent was under not applicable. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Singida region, the area of annual crops under irrigation was 3,443 ha representing 1.1 percent of the total area planted (Chart 3.78). The district with the largest planted area under irrigation with annual crops was Manyoni (4,202 ha, 35% of the total irrigated planted area with annual crops in the region). This is closely followed by Singida Rural with (3,916 ha, 32%), Iramba (2,867 ha, 24%) and Singida Urban (1,113 ha, 9%). When expressed as a percentage of the total area planted in 0.0 6.0 12.0 18.0 24.0 30.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.76 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.77 Proportion of Planted Area with Fungicides by District - Singida 0.0 1.0 2.0 3.0 4.0 5.0 Manyoni Singida Rural Iramba Singida Urban District Percent Chart 3.78 Area of Irrigated Land (hectares) Irrigated Area, 307,029, 98.9% Unirrigated Area, 3,443, 1.1% Singida Urban Iramba 11,020 12,344 6,970 7% 34% 38% 21% Singida Rural Manyoni 2,121 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Singida Urban Iramba 44,677 26,948 10,970 37% 71% 37% 33% Singida Rural Manyoni 4,107 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.33 SINGIDA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Number of Households of Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Number Households Using Improved Seeds Number Households Using Improved Seeds Map 3.34 SINGIDA Number and percent of Crop Growing Households Using Improved Seeds by District Percent of Households Crop Growig Using Improved Seeds Tanzania Agriculture Sample Census Percent of Total Households Receiving Crop Extension Services RESULT 52 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 each district, Singida Urban had the highest with 10.2 percent of the planted area in the district under irrigation. This is followed by Manyoni (6.7%), Singida Rural (3.4%) and Iramba (2.2%) (Chart 3.79 and Map 3.30). Of all the different crops and in terms of proportion of the irrigated planted area, cabbage, amaranths, okra, spinach, bitter Aubergine, chillies and mung beans were the most irrigated crops with 100 percent irrigation followed by tomatoes (72%). In terms of crop type, the area under irrigation with cereals was 3,512 ha (60% of the total area under irrigation), followed by roots and tubers with 1,467 ha (25.1%), oil seeds and oil nuts (459 ha, 7.8%), fruit and vegetables (368 ha, 6.3%) and pulses (44 ha, 0.8%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 368 ha which represents 29 percent of the total planted area with fruits and vegetables. Tomatoes, onion, and cabbages were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Singida region appears to have decreased over the 10 year intercensal period from 4,854 to 3,443 hectares. This may not be statically significant due to the small number of households sampled with irrigation (Chart 3.80). 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from canals (58% of households with irrigation). This was followed by well (29.2%), dam (8.7%) and river (4.1%) (Chart 3.81). Most households using irrigation in Singida Urban and Singida Rural get their irrigation water from well (7 3% and 54% respectively) Chart 3.79 Irrigated Area and Percentage of Irrigated Area by District 0 900 1,800 2,700 3,600 4,500 Manyoni Singida Rur Iramba Singida Urb District Irrigated Area (ha) 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Percentage with Irrigation Irrigated Area (ha) Percentage of Irrigated Area Chart 3.80 Time Series of Households with Irrigation - Singida 3,443 4,854 0 1,500 3,000 4,500 6,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Chart 3.81 Number of Households with Irrigation by Source of Water River, 259, 4.1% Well, 1,865, 29.2% Dam, 555, 8.7% Canal, 3,701, 58.0% Canal River Well Dam RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 63 percent of households using this method. This was followed by hand bucket with 35 percent of households and motor pump (2%) (Chart 3.82). Gravity was used by most households with irrigation in Manyoni (84%), followed by Singida Rural (12%) and Singida Urban (3%). Hand bucket was more common in Singida Rural with 37 percent of households using the method to get water for irrigation, followed by Singida Urban (36%), Manyoni (14%) and Iramba (13%). Motor pump was only used in Iramba district 3.6.4 Methods of Water Application Most households used flood irrigation (71% of households using irrigation) as a method of field application and bucket/watering can (29%). Other methods of field application for irrigation were not used in the region. (Chart 3.83) 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seeds for planting in the following season. The results for Singida region show that there were 179,391 crop growing households (14.7% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 115,361 households storing 8,366 tonnes as of 1st January 2004. This was followed by sorghum and millets (96,374 households, 5,413t), beans and pulses (15,765 households, 230t) and groundnuts/bambaranuts (4,894 households, 119t) and paddy (4,894 household, 387t). Other crops were stored in very small amounts. Chart 3.84 Number of Households and Quantity Stored by Crop Type - Singida 0 40,000 80,000 120,000 Maize Sorghum & Millet Beans & Pulses Gnuts/Bambara Nuts Paddy Cottton Crop Number of households 0 3,000 6,000 9,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.82 Number of Households by Method of Obtaining Irrigation Water Gravity, 3,977, 63% Motor Pump, 143, 2% Hand Bucket, 2,259, 35% Gravity Hand Bucket Motor Pump Chart 3.83 Number of Households with Irrigation by Method of Field Application Bucket / Watering Can, 1,845, 29% Flood, 4,534, 71% Flood Bucket / Watering Can RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.7.1.1 Methods of Storage The region had 105,564 crop growing households storing their produce in locally made traditional structures (64.7% of households that stored crops in the region). The number of households that stored their produce in sacks/open drum was 54,162 (33.5%). This was followed by improved locally made crib (1,172 households, 0.7%), other types of storage (940 households, 0.6%), air tight drums 537 households, 0.3%), modern store (293hh, 0.2%) and unprotected pile (85 households, 0.1%). Locally made traditional structures were the dominant storage methods in all districts, with the highest percent of households in Singida Rural using this method (73% of the total number of households storing crop products). This is followed by Iramba (69%), Manyoni (48%) and Singida Urban (35%) (Chart 3.86) The highest percent of households using sacks and open drum was in Singida Urban and Manyoni districts (57% and 49% of the total number of households storing crops respectively), followed by Iramba (30%) and Singida Rural (26%). 3.7.1.2 Duration of Storage Most households (46% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those that stored for a period of less than 3 months. The minority of households stored their crop for a period of over 6 months (17%). Most households that stored pulses stored for a period of between 3 to 6 months followed by less than 3 months. A small number of households stored pulses for the period of over 6 months (Chart 3.87). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Iramba district (51%) followed by Manyoni (46%), Singida Urban (45%) and Singida Rural (42%) (Map 3.31) Chart 3.86 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Iramba Singida Rural Manyoni Singida Urban District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.85 Number of households by Storage Methods - Singida Locally Made traditional Crib, 105019, 64.7% Improved Locally Made Crib, 1172, 0.7% Sacks / Open Drum, 54354, 33.5% Unprotected Pile, 85, 0.1% Airtight Drum, 537, 0.3% Other, 940, 0.6% Modern Store, 293, 0.2% 0 30,000 60,000 Number of households Maize Sorghum & Millet Beans & Pulses Crop Chart 3.87 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.88). However, households in Iramba district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 97.7 percent followed by seed for planting (Chart 3.89). 3.7.1.4 The Magnitude of Storage Loss About 86.1 percent of households that stored crops had little or no loss, followed by household with up to a quarter loss (7.9%), between a quarter and a half (5.2%) and over a half loss (0.8%). The proportion of households that reported a loss of more than a quarter was greatest for maize (9.6% of the total number of households that stored crops). This was followed by sorghum and millet (7.1%) and beans and pulses (1.3%). Most households storing groundnuts and bambara nuts had no storage loss (100%) (Table 3.11). 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Singida region (167,351 households, 93% of the total crop growing households) (Chart 3.90). The percent of households processing crops was very high in all the districts (above 80%) (Chart 3.91) Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba 65,209 5,262 8,832 645 79,948 Singida R 86,432 10,491 2,444 617 99,984 Manyoni 44,612 1,840 950 250 47,652 Singida U 11,100 539 128 42 11,809 Total 207,354 18,133 12,354 1,555 239,396 0% 25% 50% 75% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Gnuts/Bambara Nuts Crop Type Chart 3.89 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Chart 3.90 Households Processing Crops Households not Processing, 12,564, 7% Households Processing, 167,351, 93% 0 25 50 75 100 Percent of Households Processing Iramba Singida Rural Manyoni Singida Urban District Chart 3.91 Percentage of Households Processing Crops by District Chart 3.88 Quantity of Maize Produced (tonnes), Stored (tonnes)and Percent Stored by District 0 5,000 10,000 15,000 20,000 25,000 Iramba Singida Rur Manyoni Singida Urb District Quantity (tonnes) 0 7 14 21 % Stored Quantity harvested Quantity stored % stored RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 83 percent (138,352 households). This was followed by those processing on-farm by hand (17,013 households, 10%), trader (6,417 households, 4%) and on-farm by machine (4,468 households, 3%). The remaining methods of processing were used by very few households (less than 1%). Although processing by neighbours machine was the most common processing method in all districts in Singida region, however district differences existed. Singida Rural has a higher percent of hand processing than other districts (56%), followed by Manyoni (26%), Iramba (17%) and Singida Urban (1%). Processing by trader was more common in Singida Rural and Iramba (44% and 42% respectively), whilst processing on farm by machine was more prevalent in Singida Rural, Manyoni and Singida Urban (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 160,806 households processing crops into flour (96.1%) followed by grain with 3,473 households (2.1%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 20.6 percent of the households processing crops. The most common by-product produced by crop processing households was husk with bran 3,020 with households (60%) followed by husk (1,384 households, 27%), pulp (288 households, 6%) and cake (275 households, 5%). The remaining by- products were produced by a small number of households (Chart 3.94). Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Factory By Co-operative Union By Trader On Large Scale Farm Other Chart 3.93 Percent of Households by Type of Main Processed Product Grain 2.1% Oil 1.3% Other 0.5% Flour / Meal 96.1% Chart 3.94 Number of Households by Type of Bi-product Shell, 0, 0% Oil, 0, 0% Pulp, 288, 6% Other, 125, 2% Cake, 275, 5% Husk, 1,384, 27% Bran, 3,020, 60% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 99.6 percent of the total households that used primary processed product (Chart 3.95). Singida Rural was the only district that used primary products as fuel for cooking. Out of 167,351 households that sold processed products, 70,259 were from Singida Rural (42% of the total number of households selling processed products in the region), followed by Iramba with 56,039 households (33.5%), Manyoni with 31,583 households (18.9%) and Singida Urban with 9,469 households (5.7%). In Singida region, Iramba was the only district that sold processed products (Chart 3.96) 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (2,842 households, 60.8% of households that sold crops). This was followed by selling to local market/trade store (660 households, 14.1%), market cooperative (258 households, 5.5%), secondary market (169 households, 3.6%), trade at farm (168 households, 3.6%) and farmers association (165 households, 3.5%) (Chart 3.97). There are large differences between districts in the proportion of households selling processed products to neighbours with Singida Rural district having the largest percent of households in the district selling to neighbours (78%), whereas Singida Urban had only 54 percent. Iramba had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Manyoni had the highest percent of households selling processed products to traders at farm. In Singida Urban, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Singida Rural and Iramba. Chart 3.95 Use of Processed Product Household / Human Consumption, 166,761, 99.6% Fuel for Cooking, 120, 0.1% Sale Only, 285, 0.2% Animal Consumption, 143, 0.1% Did Not Use, 42, 0.0% 0.00 25.00 50.00 75.00 100.00 Percentage of households Iramba Singida Rural Manyoni Singida Urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Neighbours, 2,842, 60.8% Local Market / Trade Store, 660, 14.1% Marketing Co- operative, 258, 5.5% Other, 410, 8.8% Trader at Farm, 168, 3.6% Secondary Market, 169, 3.6% Farmers Association, 165, 3.5% Chart 3.98 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Secondary Market Trader at Farm Other RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.3 Crop Marketing The number of households that reported selling crops was 81,720 which represent 45 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Manyoni (52%) followed by Singida Rural (50%), Iramba (40%) and Singida Urban (25%) (Chart 3.99 and Map 3.32). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (80.4% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (6.9%), lack of transport (5%), lack of buyers (2.8%) and transport cost too high (2.3%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 95.8 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Singida region very few agricultural households (2,698, 1.5%) accessed credit out of the total number of agricultural households, out of those that received credit 1,516 (56%) were male-headed households and 1,182 (44%) were female headed households. In Singida Urban district only female headed households got agricultural credit whereas in Singida rural district only male households accessed credit. In Manyoni and Iramba districts both male and female headed households accessed agricultural credit (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Singida region were cooperatives which provided credit to 1,124 agricultural households (41.6% of the total number of households that accessed credit), followed by family, friends and relatives (33.8%), saving and credit society (8%), Religious Organizations/Non Governmental Organizations/ projects (7.5%), private individual (4.6%) and commercial bank (4.5%) (Chart 3.101). Commercial banks were the sole source of credit in Singida Rural district and cooperatives were found in Manyoni district only. Private individual was a major credit provider in Singida Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 101,154 95.8 Other 2,097 2.0 Price Too Low 1,243 1.2 Trade Union Problems 452 0.4 Co-operative Problems 263 0.2 Market Too Far 292 0.3 Government Regulatory Board Problems 125 0.1 Total 105,626 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Iramba 548 56 428 44 976 Singida R 246 100 0 0 246 Manyoni 723 50 712 50 1,435 Singida U 0 0 42 100 42 Total 1,517 56 1,182 44 2,699 Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 10,000 20,000 30,000 40,000 Singida Rural Iramba Manyoni Singida Urban District Number of Households 0 15 30 45 60 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Farmers Association Problems 0.5% Open Market Price Too Low 80.4% Government Regulatory Board Problems 0.7% Transport Cost Too High 2.3% Lack of Market Information 0.6% Market too Far 6.9% No Transport 5.0% No Buyer 2.8% Other 0.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 Rural district. Family, friends and relatives were more involved in funding a relatively great number of households in Iramba disrtict (Chart 3.102). 3.8.1.2 Use of Agricultural Credit The agricultural credit provided to agricultural households in the region was used as follows unspecified activities (37%), fertilizers (27%), agrochemicals (21%), labour (11%) and tools and equipment (2%). (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 66 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (13%), followed by “not wanting to go into debt” (12%) The rest of the reasons were collectively 9 percent of the households. Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households Family, Friend and Relative Commercial Bank Saving & Credit Society Co-operative Religious Organisation / NGO / Project Private Individual Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Other 37% Agro-chemicals 21% Tools / Equipment 2% Seeds 2% Fertilizers 27% Labour 11% Chart 3.104 Reasons for not Using Credit (% of Households) Did not know how to get credit, 74,405, 42% Don't know about credit, 43,336, 24% Not available, 23,298, 13% Did not w ant to go into debt, 21,358, 12% Difficult bureaucracy procedure, 2,315, 1% Not needed, 8,133, 5% Credit granted too late, 679, 0% Other, 909, 1% Interest rate/cost too high, 2,784, 2% Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Religious Organisation / NGO / Project 7.5% Commercial Bank 4.5% Private Individual 4.6% Family, Friend and Relative 33.8% Saving & Credit Society 8.0% Co-operative 41.6% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 86,702 (48% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Iramba district having a relatively high proportion of households (71.5%) that received crop extension messages followed by Singida Urban (36.9%), Singida Rural (36.8%) and Manyoni (33.8%). (Chart 3.106 and Map 4.33) 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (97.3%, 83,765 households). Large scale farm provided 1.0 percent, NGO/Development project 1 percent, cooperatives 0.3% and other providers 0.4 percent (Chart 3.107). 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 72.5 percent of the households receiving extension ranked the service as being good followed by average (13 %), very good (10.8%), poor (2.6%) and no good (1.1%) (Chart 3.108) However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 93,214, 52% Households Receiving Extension , 86,702, 48% Chart 3.106 Number of Households Receiving Extension by District 0 9,000 18,000 27,000 36,000 45,000 Iramba Singida Rural Manyoni Singida Urban District Number of Households 0 15 30 45 60 75 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Government 97.3% Other 0.4% NGO / Development Project 1.0% Cooperative 0.3% Large Scale Farm 1.0% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 62,764, 72.5% Average, 11,267, 13.0% Poor, 2,254, 2.6% No Good, 925, 1.1% Very Good, 9,349, 10.8% Singida Urban 163 103 127 16 Singida Rural Manyoni Iramba 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Singida Urban Manyoni 450,174 44,501 588,491 173,993 Singida Rural Iramba 480,000 to 600,000 360,000 to 480,000 240,000 to 360,000 120,000 to 240,000 0 to 120,000 Map 3.37 SINGIDA Cattle population by District as of 1st Octobers 2003 Number of Cattle Number of Cattle Number of Cattle Per Squre Km Map 3.38 SINGIDA Cattle Density by District as of 1st October 2003 Number of Cattle Per Squre Km Tanzania Agriculture Sample Census RESULT 62 Iramba Singida Urban Singida Rural Manyoni 92 86 7 67 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Singida Urban Iramba 313,502 37,409 255,680 77,829 Singida Rural Manyoni 400,000 to 500,0000 300,000 to 400,0000 200,000 to 300,0000 100,000 to 200,0000 0 to 100,0000 Map 3.39 SINGIDA Goat population by District as of 1st Octobers 2003 Number of Goat Number of Goat Number of Goat Per Squre Km Map 3.40 SINGIDA Goat Density by District as of 1st October 2003 Number of Goat Per Squre Km Tanzania Agriculture Sample Census RESULT 63 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs particularly the inputs that are not produced on the farm such as improved seeds, fungicides, inorganic fertiliser and herbicides. In Singida region farm yard manure was used by 83,259 households which represent 46 percent of the total number of crop growing households. This is followed by households using improved seeds (15%), compost (4%) fungicide (4%), inorganic fertiliser (1%), and herbicide (0.06%) (Table 2.14). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Singida mostly purchase from cooperative (53.4% of the total number of inorganic fertiliser users) followed by neighbours (28.4%) and local market/trade store (18.2 %) (Chart 3.109). Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing less than 1 km from the source (73%), followed by between 1 and 3 km (8%) and between 3 and 10 km (5%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available”(36%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 45 percent of households responding to cost factors as the main reason for not using inorganic fertilizers. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. Table 3.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 83,259 46 96,740 54 Improved Seeds 26,415 15 153,375 85 Pestcides/Fungicide 6,912 4 173,003 96 Compost 7,786 4 172,129 96 Inorganic Fertiliser 2,659 1 177,298 99 Herbicide 117 .06 179,799 100 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 53.4 28.4 18.2 0 300 600 900 1200 1500 Co-operative Neighbour Local Market / Trade Store Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 20.0 40.0 60.0 80.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 More smallholders use inorganic fertilisers in Manyoni than in other districts in Singida region (83% of households using inorganic fertilisers), followed by Iramba (10.8%), Singida rural (4.6%) and Singida Urban (1.6%). 3.9.3 Improved Seeds The proportion of households that used improved seeds was 15 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (56%). Other less important sources of improved seed are from neighbours (23.8%), locally produced by household (10.1%). Only 0.9 percent of households using improved seeds obtain them from large scale farms (Chart 3.111). Access to improved seed is better than access to chemical inputs with 46 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The district that used improved seeds are Singida Rural (38 percent of the total number of households used improved seeds), followed by Iramba (34%), Manyoni (21%) and Singida Urban (7). (Map 3.34). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (53.1% of the total number of fungicide users). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 17 percent of households responding to “not available” as the reason for not Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111 Number of Households by Source of Improved Seed 0.6 0.1 1.0 0.9 1.6 2.3 3.6 10.1 23.8 56.0 0 5000 10000 15000 Local Market / Trade Store Neighbour Locally Produced by Household Co-operative Development Project Crop Buyers Secondary Market Large Scale Farm Other Local Farmers Group Source of Im proved Seed Number of Households Chart 3.113 Number of Households by Source of Insecticide/fungicide 53.1 18.5 12.2 10.2 2.1 1.8 0.9 1.2 0 1000 2000 3000 4000 Local Market / Trade Store Co-operative Neighbour Other Secondary Market Local Farmers Group Crop Buyers Development Project Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 15 30 45 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 77 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Manyoni district (42.7 percent of the total number of households used fungicides), followed by Singida Rural (32.8%), Iramba (22.8%) and Singida Urban (1.6%). 3.10 Tree Planting The number of households involved in tree farming was 11,552 representing 6 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 186,395 trees. The average number of trees planted per household planting trees was 18 trees. The main species planted by smallholders is Eucalyptus spp (74,654 trees, 40.16%), followed by Gravellis (45,536, 24.4%), then senna spp (30683, 16.5%) and Moringa (8,976 trees, 4.8%). The remaining trees species are planted in comparatively small numbers (Chart116.). Singida Rural has the largest number of smallholders with planted trees than any other district (50%) which is dominated by Eucalypus species. This is followed by Iramba (29%) dominated by Gravellis species and to a lesser extent Leucena, then Singida Urban (12%) and Manyoni (9%) which are mainly planted with Eucalyptus and Senna species respectively (Chart 3.117 and Map 3.35.). Smallholders mostly plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 61.1 percent, followed by scattered around fields (29.5%) and then trees planted in a plantation or coppice (9.4%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (31.9%). This is followed by shade (21.5%), wood for fuel (15.8%) and poles (12.7%) (Chart 3.119). Chart 3.115 Number of Households with Planted Trees Not growing trees, 168,364, 94% hh growing trees, 11,552, 6% Chart 3.119 Number of Households by Purpose of Planted Trees 0 7 14 21 28 35 Planks / Timber Shade Fuel for Wood Poles Other Medicinal Use Percent of Households Chart 3.118 Number of Trees Planted by Location Field boundary, 79,550, 43% Scattered in field, 69,684, 37% Plantation, 37,160, 20% Chart 2.116 Number of Planted Trees by Species - Singida 0 20,000 40,000 60,000 80,000 Eucalyptus Spp Gravellis Senna Spp Moringa Spp Leucena Spp Azadritachta Spp Syszygium Spp Cyprus Spp Kyaya Spp Acacia Spp Calophylum Inophyllum Jakaranda Spp Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and District 0 150 300 450 600 750 900 Iramba Singida Rural Manyoni Singida Urban Region Number of Trees Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Moringa Spp Kyaya Spp RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 15,529 which represent 9 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Singida Rural district (11%) followed by Iramba (10%), Singida Urban (6%) and Manyoni (1%) (Chart 3.121). Erosion control bunds accounted for 61 percent of the total number of structures, followed by water harvesting bunds (17.4%), tree belts (11.9%), terraces (5.0%), drainage ditches (2.4%) and vetiver grass (2.1%) (Chart 3.122 and Map 3.36). Erosion control bunds, water harvesting bunds and tree belts together had 166,275 structures. This represented 90.4 percent of the total structures in the region. The remaining 9.6 percentages were shared among the rest of the erosion control methods mentioned above. Singida Rural and Iramba districts had 168,941 erosion control structures (91.8 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 1,257,159. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 7.5 percent of the total cat tle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Singida region was 1,255,118 (99.8 % of the total number of cattle in the region), 1,115 cattle (0.09%) were dairy breeds and 925 cattle (0.07%) were beef breeds. Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 15,529, 9% Households Without Facilities, 164,386, 91% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 11 6 1 10 0 3,000 6,000 9,000 Singida Rural Iramba Singida Urban Manyoni District Number of Households 0 3 6 9 12 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 61.0 17.4 11.9 5.0 2.4 2.1 0.0 0.0 0.0 20000.0 40000.0 60000.0 80000.0 100000.0 120000.0 Erosion Control Bunds Water Harvesting Bunds Tree Belts Terraces Drainage Ditches Vetiver Grass Gabions / Sandbag Dam Type of Facility Number of Structures RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 The census results show that 72,363 agricultural households in the region (40% of total agricultural households) kept 1.3 million cattle. This was equivalent to an average of 17 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Singida Rural which had about 588,491cattle (46.8% of the total cattle in the region). This was followed by Iramba (450,174 cattle, 35.8%), Manyoni (173,993 cattle, 13.8%) and Singida Urban (44,501 cattle, 3.5%) (Chart 3.123 and Map 3.37). However, Iramba district had the highest density (163 head per km2) (Map 3.38). Although Singida Rural district had the largest number of cattle in the region, most of then were indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant. Singida Rural was the only district with diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Thirteen percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 44 percent of all cattle in the region. Only 23 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 92 percent of total cattle rearing households had herds of size 1-30 cattle and owned 50 percent of total cattle in the region, resulting in an average of 10 cattle per cattle rearing household. There were about 705 households with a herd size of more than 151 cattle each (291,197 cattle in total) resulting in an average of 413 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Singida decreased during the period of eight years from 1,944,272 in 1995 to 1,257,159 cattle in 2003. This trend depicts an overall annual negative growth rate of -4.7 percent (Chart 3.125). There was a decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –4.6 percent whereby the number dropped from 1,944,272 to 1,538,463. The number of cattle further decreased from 1,538,463 in 1999 to 1,257,159 in 2003 at the rate of -4.9 percent. 1,944,272 1,538,463 1,257,159 - 500,000 1,000,000 1,500,000 2,000,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 0 100 200 300 400 500 600 Number of Cattle ('000') Singida Rural Iramba Manyoni Singida Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 44,501 433 493 - - - 1,115 - - 449,741 586,883 173,993 - 150,000 300,000 450,000 600,000 Iramba Singida Rural Manyoni Singida Urban Districts Number of Cattle Indigenous Improved Beef Total Cattle RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Singida region was 2,040 (1,115 dairy and 925 improved beef). The diary cattle constituted 0.09 percent of the total cattle and 55 percent of improved cattle in the region. The number of beef cattle in the region constituted 45 of the improved cattle in the region. The number of improved cattle increased from 1,662 in 1995 to 2,040 in 2003 at an annual growth rate of 3.21 percent. The growth rate was higher for the period from 1995 to 1999 (26.9%) then there was a sharp decrease from 1999 to 2003 (-16.1%) (Chart 126) 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Singida region ranked 8 out of the 21 regions with 6 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Singida region was 60,387 (34% of all agricultural households in the region) with a total of 684,420 goats giving an average of 11 head of goats per goat-rearing-household. Singida Rural had the largest number of goats (313,502 goats, 46% of all goats in the region), followed by Iramba (255,680 goats, 37%), Manyoni (77,829 goats, 11%) and Singida Urban (37,409 goats, 5%). (Chart 3.127 and Map 3.39). However, Iramba district had the highest density (92 head per km2) (Map 3.40). 3.12.2.2 Goat Herd Size Seven percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Seventy five percent of total goat-rearing households had herd size of 1-14 goats and owned 43 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 1,508 households (2.5%) with herd sizes of 40 or more goats each (104,321 goats in total), resulting in an average of 69 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.1 percent of the total goats in Singida region. Improved goats for beef and diary constituted of 0.5 and 1.4 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was -4.4 percent. This negative trend implies eight years of population decrease from 978,772 in 1995 to 684,420 in 2003. The number of goats increased from 978,772 in 1995 at an estimated annual rate of 1.8 percent to 1,052,716 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -10.2 percent (Chart 128). 1,662 4,314 2,040 - 1,500 3,000 4,500 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend 0 70 140 210 280 350 Number of Goats ('000'). Singida Rural Iramba Manyoni Singida Urban District Chart 3.127 Total Number of Goats ('000') by District 978,772 1,052,716 684,420 - 300,000 600,000 900,000 1,200,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend Singida Rural Singida Urban 3,464 0 2,508 403 Manyoni Iramba 2,760 to 3,470 2,070 to 2,760 1,380 to 2,070 690 to 1,380 0 to 690 Singida Rural Singida Urban 0 1 0 1 Manyoni Iramba 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Map 3.43 SINGIDA Pig population by District as of 1st Octobers 2003 Number of Pig Number of Pig Number of Pig Per Squre Km Map 3.44 SINGIDA Pig Density by District as of 1st October 2003 Number of Pig Per Squre Km Tanzania Agriculture Sample Census RESULT 70 Singida Urban Singida Rural Iramba 3,990 1,129 53,098 32,196 12.1% 84.9% 10.2% 44% Manyoni 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Singida Urban Singida Rural Iramba 20,152 3,419 28,370 4,434 65% 63% 77% 80% Manyoni 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.47 SINGIDA Number and Percent of households Infected with Ticks by District Number of households Number of Households Infected With Ticks Number of households Using Draft Animals Map 3.48 SINGIDA Number and Percent of Households Using Draft Animals by District Number of households Tanzania Agriculture Sample Census Percent of Households Infected With Ticks Percent of households Using Draft Animals RESULT 71 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Singida region after cattle and goats. The region ranked 4 out of 21 Mainland regions and had 8 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 39,179 (22% of all agricultural households in Singida region) rearing 309,938 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Singida Rural with 141,604 sheep (46%of total sheep in Singida region) followed by Iramba (119,704 sheep, 39%), Manyoni (31,901 sheep, 10%) and Singida Urban (16,729 sheep, 5%) and Map 3.41). Iramba district also had the highest density (43 head per km2 ) (Map 3.42). Sheep rearing was dominated by indigenous breeds that constituted 99 percent of all sheep kept in the region. Only 1 percent of the total sheep in the region was made up of improved breeds. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at - 4.9 percent. The population decreased at an annual rate of -23.2 percent from 246,263 in 1995 to 85,679 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 17.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 13 out of 21 Mainland regions and is 0.65 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Singida region was 2,554 (1.4% of the total agricultural households in the region) rearing 6,375 pigs. This gives an average of 3 pigs per pig-rearing household. The district with the largest number of pigs was Singida Rural with 3,464 pigs (54% of the total pig population in the region) followed by Iramba (2,508 pigs, 39%) and Manyoni (403 pigs, 6%) (Chart 3.131 and Map 3.44). However, Iramba district had the highest density (1 head per km2) (Map 3.43). There are no pigs were in Singida Urban district. 246,263 85,679 164,209 - 100,000 200,000 300,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 0 35000 70000 105000 140000 N um ber of sheep Singida Rural Iramba Manyoni Singida Urban District Chart 3.129 Total Number of Sheep by District 0 1,000 2,000 3,000 Number of Pigs Singida Rural Iramba Manyoni District Chart 3.131 Total Number of Pigs by District RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 24.7 percent. During this period the population grew from 1,072 to 6,281. The pig population increased from 1072 in 1995 to 22,093 in 1999 at a high rate of 26.2 percent. The growth rate dropped to 23.3 percent during the following four years from 1999 to 2003 in which pig population increased from 2,715 to 6,281(Chart 3.132). 3.12.5 Chicken Production The poultry sector in Singida region was dominated by chicken production. The region contributed 5.0 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 125,895 raising about 1,658,178 chickens. This gives an average of 13 chickens per chicken-rearing household. In terms of total number of chickens in the country, Singida region was ranked ninth out of the 21 Mainland regions. The District with largest number of chickens was Iramba (788,336 chickens, 47% of the total number of chickens in the region) followed by Singida Rural (644,898, 39%), Manyoni (163,332, 10%) and Singida Urban (61,610, 4%) (Chart 3.133 and Map 3.45) However Iramba district had the highest density (285 chikens per km2) (Map 3.46) 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 2.58 percent. The population decreased at a rate of -1.99 percent from 1995 to 1999 after which it increased at a rate of 7.37 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Singida region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 0 200,000 400,000 600,000 800,000 Number of Chickens Iramba Singida Rur Manyoni Singida Urb District Chart 3.133 Total Number of Chickens by District 1,351,988 1,247,658 1,658,178 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend - 22,093 6,375 - 7,000 14,000 21,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 74 3.12.5.3 Chicken Flock Size The results indicate that about 82 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 8 chickens per holder. About 18 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 32 chickens per holder. Only 0.32 percent of holders kept the flock sizes of more than 100 chickens at an average of 389 chickens per holder (Table 3.14). 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Singida Region decreased at an annual rate of 48.2 percent for the period of four years from 10,308 in 1995 to 7,558 in 2003. There were no layers in Iramba and Singida Urban districts (Chart 3.135). The overall annual growth rate for broilers during the four-year period from 1999 to 2003 was -14.18 percent during which the population dropped from 12,195 to 6,616. (Chart 3.136) 3.12.6. Other Livestock There were 35,013 ducks, donkeys, 16,649, turkeys, 7,501 and rabbits 840 raised by rural agricultural households in Singida region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Singida Rural District (57% of all ducks in the region), followed by Iramba (24%), Singida Urban (12%) and Manyoni (7%). Turkeys were reported in Singida Rural district only (Table 3.16). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 28,333 23 82,492 3 5 - 9 36,894 29 237,115 6 10 - 19 38,301 30 489,501 13 20 - 29 12,115 10 270,586 22 30 - 39 5,370 4 174,050 32 40 - 49 1,937 2 85,947 44 50 - 99 2,471 2 162,264 66 100+ 401 0 156,222 389 Total 125,823 100 1,658,178 13 Table 3.16 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Iramba 8,357 . . 12,295 1,142 Singida R 19,791 7,501 . 4,354 2,859 Manyoni 2,528 . . . . Singida U 4,336 . 840 . . Total 35,013 7,501 840 16,649 4,001 0 0 2099 3586 5490 0 0 3030 0 1000 2000 3000 4000 Number of Chickens Iramba Singida Rur Manyoni Singida Urb District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers 10,308 0 683 12,195 7,589 6,616 0 5000 10000 15000 Number of layers 1995 1999 2003 Year Chart 3.136 Layers Population Trend Singida Urban Singida Rural 142 285 15 139 Manyoni Iramba Singida Urban Singida Rural 61,611 788,337 163,332 644,898 Manyoni Iramba Map 3.45 SINGIDA Chicken population by District as of 1st Octobers 2003 Number of Chicken Number of Chicken Number of Chicken Per Squre Km Map 3.46 SINGIDA Chicken Density by District as of 1st October 2003 Number of Chicken Per Squre Km Tanzania Agriculture Sample Census 640,000 to 800,000 480,000 to 640,000 320,000 to 480,000 160,000 to 320,000 0 to 160,000 280 to 350 210 to 280 140 to 210 70 to 140 0 to 70 RESULT 75 Iramba Singida Urban 1,147 340 2,043 169 1.8% 3.1% 2.8% 0.5% Singida Rural Manyoni Singida Urban Iramba Singida Rural 4,786 26,267 25,451 3,460 43% 42% 34.8% 10.5% Manyoni Map 3.49 SINGIDA Number and Percent of households Using Farm Yard Manure by District Planted Area (ha) Number of households Using Farm Yard Manure Number of households Using Compost Manure Map 3.50 SINGIDA Number and Percent of households Using Compost by District Planted Area (ha) Tanzania Agriculture Sample Census Percent of households Using Farm Yard Manure Percent of households Using Compost Manure 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 RESULT 76 Singida Urban Singida Rural Iramba 4,860 833 1,183 5,363 14.7% 7.5% 1.9% 7.3% Manyoni 4,800 to 6,000 3,600 to 4,800 2,400 to 3,600 1,200 to 2,400 0 to 1,200 Map 3.51 SINGIDA Number and Percent of households Without Toilets by District Number of households Number of Households Without Toilets Tanzania Agriculture Sample Census Percent of Households Without Toilets RESULT 77 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 78 3.12.7 Pest and Parasite Incidence and Control The results indicate that 72 percent and 23 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Manyoni district but lowest in Singida Urban district (Map 3.47). The most practiced method of controlling ticks spraying with 41 percent of all livestock- rearing households in the region using the method. Other methods used were dipping (14%), smearing (3%) and other traditional methods like hand picking (13%). However, 29 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 47 percent of livestock-rearing households and dipping (6%). However, 46 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 34,103 (42 % of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 44.3 percent, goats (31.5%), sheep (14.3%) and pigs (9.9%) (Chart 3.138) 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 45,588, representing 55 percent of the total livestock- rearing households and 25 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 98.5 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (1.5%). About 61 percent of livestock rearing households described the general quality of livestock extension services as being good, 15 percent said they were very good and 12 percent said they were average. However, 7 percent of the livestock rearing households said the quality was not good whilst 5 percent described them as poor (Chart 3.139). Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Iramba Singida Rur Manyoni Singida Urb District Percent Ticks Tsetseflies 0 20 40 60 80 Percent Iramba Singida Rur Manyoni Singida Urb District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Average 12% No good 7% Poor 5% Very Good 15% Good 61% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 97 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 3 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). Almost all livestock rearing households accessing the services at a distance of less than 14 kms and the majority were within 5kms (Chart 3.141). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 24,573 (87% of livestock rearing households in Singida region) whilst 2,806 households (10%) resided between 5 and 14 kms. However, 848 households (3%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Iramba district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Singida Urban, Singida Rural and Manyoni districts. In Manyoni district about 20 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 1,725, 3% Less than 14km, 47,676, 97% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 40,000 Iramba Singida Rur Manyoni Singida Urb District Number of Households Less than 14km More than 14km Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 24,573, 87% 5-14 kms, 2,806, 10% 15 or more kms, 848, 3% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0.0 25.0 50.0 75.0 100.0 Iramba Singida Urb Singida Rur Manyoni District Number of Households Less than 5 kms 5-14 kms 15 or more kms RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Singida region is encouraging with 90,414 households (50.3% of the total households in the region) using them (Chart 3.144). The number of households that used draft animals in Iramba district was 53,098 (59% of the households using draft animals in the region). In Singida Rural the number of households using draft animals was 32,196 (36%). The use of draft animals was small in Manyoni and Singida Urban (Chart 3.145 and Map 3.48) The region had 199,820 oxen that were used to cultivate 182,070 hectares of land. This represents only 8.9 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Iramba district (105,194 ha, 58% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Singida region was 79,651 (44% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 180,367 ha or 37% of the area planted with annual crops and vegetables in Singida region during the long rainy season) was applied with farm yard manure (Map 3.49). 3.12.9.4 Use of Compost 0 20,000 40,000 60,000 Number of Households Iramba Singida Rural Manyoni Singida Urban District Chart 3.145 Number of Households Using Draft Animals by District - Singida Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 79,651, 45% Not Using Organic Fertilizer, 97,717, 55% Chart 3.147 Area of Application of Organic Fertiliser by District Singida 0 7,000 14,000 21,000 28,000 35,000 Iramba Singida Rural Manyoni Singida Urban District Area of Fertiliser Application (ha) Farm Yard Manure Compost 3.144 Number of Households Using Draft Amimals Using draft animal, 90,414, 50.3% Not using draft animal, 89,502, 49.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 81 Only 7,523 ha (4% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost was found in Iramba district with 32,951 hectares (47.1% of the total area applied with compost) followed by Singida Rural (27,618 ha, 39.5%), Manyoni (5,504 ha, 7.9%) and Singida Urban (3,905 ha, 5.6%) (Chart 3.147 and Map 3.50) 3.12.10 Fish Farming There was no fish farming in the region. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, tarmac road was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 154.6 kilometers from the agricultural household’s dwelling. Other services and their respective average distances in kilometers from the dwellings were feeder road (2.0), primary school (3.0), all weather road(6.0), health clinlcs (6.8), primary market (7.7), secondary market (11.6), secondary school (18.2), hospital (35.7) and tertiary market (42.2) (Table 3.17). Only 5 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 33 percent reported them to be ‘no good’. Twenty four percent of the agricultural households said the infrastructure and services were good. Those who said the infrastructures and services were poor were 21 percent while 17 percent said they were average. 3.13.2 Type of Toilet A large number of rural agricultural households use traditional pit latrines (159,503 households, 88.7% of all rural agricultural households) 7,005 households. This is followed by flush toilets (7,005 houeholds 3.9%), improved pit latrines (794 households, 0.4%) and other types of toilets (375 household, 0.2%). However, 12,238 households (6.8%) in the region had no toilet facilities (Chart 3.148). The distribution of the households without toilets within the region indicates that 44 percent of them were found in Singida Rural district followed by Manyoni (40%), Iramba (10%), and Singida Urban (7%) (Map 3.51) Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Iramba 14.9 1.8 4.5 2.4 37.0 6.3 167.4 6.5 9.2 41.1 186.6 Singida Rur 18.9 2.9 7.5 2.0 35.8 8.0 115.9 9.0 12.4 40.3 114.0 Manyoni 24.1 5.7 6.8 1.4 41.5 6.0 49.7 8.5 15.8 58.9 221.4 Singida Urb 14.5 2.1 2.4 1.2 11.2 4.3 16.6 3.7 7.4 11.0 44.1 Total 18.2 3.0 6.0 2.0 35.7 6.8 67.7 7.7 11.6 42.2 154.6 Chart 3.148 Agricultural Households by Type of Toilet Facility Flush Toilet, 7005, 3.9% No Toilet , 12238, 6.8% Improved Pit Latrine , 794, 0.4% Other Type, 375, 0.2% Traditional Pit Latrine, 159503, 88.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Singida region with 69,474 households (38.6% of the agriculture households in the region) owning the asset followed by bicycle (53864 households, 29.9%), iron (21,799 households, 12.1%), wheelbarrows (8,003 households, 4.4%), vehicles (1,464 households, 0.8%), mobile phones (1,463 households, 0.8%), television/videos (801 households, 0.4%) and landline phone (605 households, 0.3%) (Chart 3.149) 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region with 79.9 percent of the total rural households using this source of energy followed by hurricane lamp (12%), fire wood (5.3%), and pressure lamp (2.4%). The remaining sources of lighting were minor. (Chart 3.150) 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.1 percent of all rural agricultural households in Singida region. This is followed by crop residues (2.3%) and charcoal (1.7%). The rest of energy sources accounted for 0.9 percent. These were solar energy (0.4%), mains electricity (0.2%), paraffin/kerosene (0.1%), bottled gas (0.1%) and livestock dung (0.1%) (Chart 3.151). 3.13.6 Roofing Materials The most common material used for roofing the main dwelling was grass and mud and it was used by 73.2 Chart 3.149 Percentage Distribution of Households Owning the Assets 4.4 0.8 0.8 0.4 0.3 38.6 29.9 12.1 0.0 10.0 20.0 30.0 40.0 Radio Bicycle Iron Wheelbarrow Vehicle Mobile phone Television / Video Landline phone Assets Percent Chart 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting Solar, 269, 0.1% Other, 304, 0.2% Firew ood, 9499, 5.3% Gas (Biogas), 118, 0.1% Pressure Lamp, 4330, 2.4% Mains Electricity, 118, 0.1% Hurricane Lamp, 21581, 12.0% Wick Lamp, 143694, 79.9% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 171131, 95.1% Charcoal, 3104, 1.7% Bottled Gas, 103, 0.1% Mains Electricity, 448, 0.2% Solar, 641, 0.4% Livestock Dung, 143, 0.1% Parraffin / Kerocine, 143, 0.1% Crop Residues, 4202, 2.3% Singida Rural Singida Urban Iramba 11,014 10,744 1,306 31,405 15% 11.7% 32.5% 50.2% Manyoni 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Singida Urban Singida Rural Iramba 8,292 52,230 23,176 48,055 74.5% 71.4% 70.1% 76.9% Manyoni 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.52 SINGIDA Number and Percent of households Using Grass/mud for rooing materials by Distric Number of household Number of households Using Grass/Mud For Rooing Materials Number of Households Eating 3 Meals Per Day Map 3.53 SINGIDA Number and Percent of households Eating 3 meals per day by District Nuber of household Percent of Households Using Grass/Mud For Rooing Materials Percent of Households Eating 3 Meals Per Day Tanzania Agriculture Sample Census 83 RESULT RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 percent of the rural agricultural households. This was followed by iron sheets (20.7%), grass/leaves (5.4%), asbestos (0.2%), tiles (0.1%), and others (0.3%) (Chart 3.152) Singida Rural district had the highest percentage of households with grass and mud roofing (40%) followed by Iramba district (36%), Manyoni (18%) and Singida Urban (6%) (Chart 3.153 and Map 3.52) 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Singida region was unprotected well (31.3 percent of households using the source for both seasons. This is followed by piped water (17.7% of households in the wet season and 20.1 percent during dry season), lake/river (15.7% of households during the wet season and 14.2% in the dry season), protected well (15.2% of households in the wet season and 17.3% during dry season) and uncovered rain water catchments (10.1% of households in the wet season and 7.05 during dry season), unprotected spring (8.0% of household in the wet season and 8.8% during dry season), protected spring (0.9% of household for each season) and other sources (1.0% of household in the wet season and 0.4% during dry season) (Chart 3.154) Chart 3.152 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.2% Grass & Mud 73.2% Iron Sheets 20.7% Grass / Leaves 5.4% Tiles 0.1% Other 0.3% Chart 3.153 Percentage Distribution of Households with Grassy and Mud Roofs by District 40 36 18 6 0 10 20 30 40 Singida Rur Iramba Manyoni Singida Urb District Percent Chart 3.154 Percent of Households by Main Source of Drinking Water and Season 0.0 7.0 14.0 21.0 28.0 35.0 Uprotect - ed Well Piped Water Lake /River Protected Well Uncover -ed Rain Catchment Unprotect -ed Spring Other Main source Percent of Households Wet Season Dry Season Chart 3.155 Percent of Households by Distance to Main Source of Water and Season 0 10 20 30 40 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 About 45 percent of the rural agricultural households in Singida region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 55 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 500 meters and 1 km (Chart 3.155). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Singida region normally have 2 meals per day (66.5 percent of the households in the region). This is followed by 3 meals per day (30.3 percent) and 1 meal per day (3.0 percent). Only 0.2 percent of the households have 4 meals per day (Chart 3.156). Singida Rural district had the largest percent of households eating one meal per day whilst Iramba had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.53). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 118,687 (66% of the agricultural households in Singida region) with 62,773 households (52.9 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31.8%). Very few households had meat three or more times during the respective week. About 34 percent of the agricultural households in Singida region did not eat meat during the week preceding the census (Chart 3.157 and Map 3.54). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 91,646 (51% of the total agricultural households in Singida region) with 47,096 households (51 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (29%). In general, the percentage of households that consumed fish twice or more during the week in Singida region was 44,550 (49% of the agricultural Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Iramba 704 1.1 30420 48.6 31405 50.2 0 0.0 62529 Singida Rur 3474 4.7 58471 79.9 11014 15.0 237 0.3 73196 Manyoni 973 2.9 21265 64.3 10744 32.5 82 0.2 33064 Singida Urb 258 2.3 9519 85.6 1306 11.7 42 0.4 11125 Total 5409 3.0 119675 66.5 54469 30.3 361 0.2 179914 Chart 3.156 Number of Agriculural Households by Number of Meals per Day Three Meals, 54469, 30.3% Two Meals, 119676, 66.5% One Meal, 5409, 3.0% Four Meals, 361, 0.2% Chart 3.157 Number of Households by Frequency of Meat and Fish Cosumption 0 25000 50000 75000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Singida Urban Iramba Manyoni 3,064 23,590 3,541 16,901 9.3% 32.2% 31.8% 27% Singida Rural 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Manyoni Singida Urban Singida Rural Iramba 8,163 3,361 21,534 29,715 24.7% 30.2% 34.4% 40.6% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.54 SINGIDA Number and Percent of households eating Meat Once per Week by District Number of household Number of Households Eating Meat Once per Week Number of Households Eating Fish Once Per Week Map 3.55 SINGIDA Number and Percent of households eating Fish once per week by District Number of household Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once Per Week Tanzania Agriculture Sample Census RESULT 86 Singida Urban Singida Rural Iramba Manyoni 3,519 16,052 25,746 9,745 32% 26% 35% 29% 20,600 to 25,800 15,400 to 20,600 10,400 to 15,400 5,200 to 10,400 0 to 5,200 Map 3.56 SINGIDA Number and Percent of households Reporting food Insufficiency by District Number of household Number of households Reporting food Insufficiency Percent of households Reporting food Insufficiency Tanzania Agriculture Sample Census RESULT 87 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 households that ate fish in the region during the respective period). About 49 percent of the agricultural households in Singida region did not eat fish during the week preceding the census (Chart 3.157 and Map 3.55). 3.13.9 Food Security In Singida region, 61,025 households (34% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 9,646 (5%) said they sometimes experienced problems, 17 percent often experienced problems and 14 percent always had problems in satisfying the household food requirements. About 31 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.56). 3.13.10 Main Sources of Cash Income The main cash income of the households in Singida region was from other casual cash earnings (29.6 percent of smallholder households), followed by sales of livestock (16.5%), selling of cash crops (16.2%), businesses (10.7%) and sales of food crops (9.1%). Only 6.6% of smallholder households reported the cash remittances as their main source of income, followed by forest products (6.5%) and wages and salaries (3.1%) (Chart 3.158). Chart 3.158: Percentage Distribution of the Number of Households by Main Source of Income Fishing 0.7% Livestock Products 0.7% not applicable 0.0% Other 0.4% Forest Products 6.5% Food Crops 9.1% Other Casual Cash Earnings 29.6% Cash Crops 16.2% Livestock 16.5% Wages & Salaries 3.1% Remittance 6.6% Business Income 10.7% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 4 SINGIDA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Singida Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. 4.2.1 District Profiles Thee following district profiles highlight the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Iramba Iramba district had the second largest number of agricultural households in the region and it had among the highest percent of households involved in smallholder agriculture in the region. It was the third highest district with smallholders involved in crop farming only and those involved in crop and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Iramba district was annual crop farming, followed by tree forest resources and off farm income. However, the district had the highest percent of households with no off-farm activities and the least percent of households with more than one member with off-farm income. Compared to other districts in the region, Iramba had the least percent of female headed households (20.5%) and it had the highest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Iramba has the second highest literacy rate for agricultural household members (69.7%) and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household was the least in the region. It has the second highest utilized land area per household (2.5 ha) and the allocated area is not fully utilised indicating a low level of land pressure. The total planted area is the second greatest in the region due to the presence of good wet and dry seasons; however it has the second highest planted area per household as compared to other districts. The district was the most important for maize production in the region with a planted area of 60,761 ha; however the planted area per household was the highest in the region. Paddy production was very important with a planted area of 615 hectares and the production of sorghum was the second highest in the region. Iramba had no wheat production. Cassava production was the highest and accounted for 45 percent of the quantity harvested in the region. The district had no planted area of Irish potatoes. The production of beans in Iramba was the second highest in the region with a planted area of 4,209 ha. Oilseed crops are important in Iramba and had the highest production of sunflower in the region with a planted area of 24,225 ha. Vegetable production was important in the district. It had the second largest area planted with onions (214 ha) accounted for 25.8 percent of the onion production. Traditional cash crops were not grown in the district. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 Compared to other districts in the region, Iramba has a moderate planted area with permanent crops which were dominated by mango (806 ha), banana (503 ha) and star fruit (70 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Iramba had the largest area planted with improved seed in Singida region and this was due to the high planted area of vegetables. The district had the largest area planted with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Iramba district had the highest level of insecticide use. The use of fungicides was the third highest in the region. Also the district had the second highest use of herbicide in the region. It had the third largest irrigated area (2,867) ha. The most common source of water for irrigation was from dams and wells using hand bucket. Watering can and bucket were the most common means of water application. The most common method of crop storage was the locally made traditional crib. The proportion of households storing crops in the district was the least in the region. The district had the third largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. The third highest percent of households processing crops in Singida region was found in Iramba district, most of the processing was done by neighbours machine. The district had the highest percent of households selling processed crops to neighbours in the region and no sales were made to traders on farm, farmers association and secondary market. Although small, access to credit in the district was to both men and women headed households and the main sources of credits were family, friends, relatives and credit societies. A comparatively large number of households received extension services in Iramba and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Iramba (with 54,465 planted trees) and most of the trees were Senna, Gravellis with some Leucena species. The second highest proportion of households with erosion control and water harvesting structures was found in Iramba district and most of these were erosion control bunds, however it also had high number of tree belts, water harvesting bunds, vetiver grass and drainage ditches. The district had the second largest number of cattle in the region and most of them were indigenous. Goat production was the second largest in the region; however it was the second largest district with population of sheep in the region. It had the second largest number of pigs in the region and the largest number of chickens. The district had no layers. The district had high numbers of donkeys, ducks and moderate number of unspecified animals. It had third largest number of households that reported Tsetse and tick problems and also it had the third largest number of households de-worming livestock. The use of draft animals in the district was highest while fish farming was not practiced. It had amongst the best access to primary schools and feeder roads compared to other districts. However, it had one of the worst access to primary markets and tarmac roads. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 Iramba district had the least percent of households without toilet facilities and it had the highest percent of households owning bicycles, vehicles and television/video. It had no households using mains electricity in the district. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the smallest percent of households with grass roofs and 21 percent of households had iron sheet roofs. The most common source of drinking water was from surface water. It had the highest percent of households having three and two meals per day and the lowest percent having 1 meal per day. The district had the lowest percent of households that did not eat meat and the second highest percent of households that did not eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.2 Singida Rural Singida Rural district had the largest number of agricultural households in the region and it had the third highest percentage of households involved in smallholder agriculture. Most smallholders were involved in crop and livestock production, followed by crops only. It had a very small number of livestock only households and pastoralists were found in the district. The most important livelihood activity for smallholder households in Singida Rural district was annual crop farming, followed by off farm income. The district had the third highest percent of households with no off-farm activities and also the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Singida Rural had small percent of female headed households (23.2%) and it had one of the highest average age of the household head in the region. Its household size of 5 members per household was average for the region. Singida Rural had a comparatively high literacy rate for agricultural household members and this was reflected by the district having the highest level of school attendance in the region. It had a moderate utilized land area per household (2.0ha) and 94 percent of the allocated area was currently being utilised. The district had the second largest planted area in the region. The district was moderately important for maize production in the region with a planted area of 42,787 ha, and the planted area per maize growing household was also moderate for the region. Paddy was grown in the district with a planted area of 1,140 ha being the second in the region. The district had the second largest area planted with sorghum in the region with 29,328 hectares. Though small, cassava production is the second highest in the region with a planted area of 964 hectares. Irish potatoes are not grown in the district. The production of beans in Singida Rural district was the second highest in the region with a planted area of 1,051ha. Singida Rural district has the third largest groundnut planted area in Singida region with a planted area per groundnut growing household of 0.52 ha. Vegetable production was important in the district. It had the third largest planted area with tomatoes (218 ha). Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Singida Rural had the largest planted area with permanent crops which were dominated by bananas (2,739 ha), sugarcane (462 ha), guava (439 ha) and mango (154 ha). Other permanent crops were either not grown or were grown in very small quantities. As with most districts in the region, most land clearing and preparation was done by oxen, with the highest amount of land preparation in Singida Rural district being done by oxen. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 The use of inputs in the region was very small, however district differences existed. Singida Rural had the second largest area planted with improved seeds in the region and had the third highest proportion of households using improved seeds. The district had the second largest planted area with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of these were farm yard manure. Compared to other districts in the region, Singida Rural district had low level of insecticide use. The use of fungicides was the second highest in the region. Application of herbicides was the highest. It had the second largest irrigated area (7,832 ha). The most common source of water for irrigation was from well using hand bucket. Flood was the major means of water application. The most common method of crop storage in Singida rural district was the locally made traditional crib. The proportion of households storing crops in the district was relatively high. Singida Rural district was one of the districts with a moderate number of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. Singida Rural was among the districts with the highest percent of households processing crops in Singida region and most of the processing was done by neighbours machine. The district was among the two districts with households selling processed crops to marketing cooperatives and no sales were made to local market, secondary markets or trade at farm. Although very small, access to credit in the district was to men headed households and the main sources were commercial bank and private individuals. A comparatively small number of households received extension services in Singida Rural district and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not important in Singida Rural (with 93,465 planted trees) and most of the trees were Ecalyptus species and Gravellis. The district had the highest proportion of households with erosion control and water harvesting structures and most of these were erosion control bunds and water harvesting bunds; however it also had a number of terraces and drainage ditches. The district had the largest number of cattle in the region and almost all of them were indigenous. Goat production was the second largest in the region; however it had the largest population of sheep in the region. It had the largest number of pigs in the region and a large number of chickens. Many ducks, turkeys and donkeys but no rabbits were found in the district. A few households reported tsetse fly problems and many reported tick problems in Singida Rural district and it had the highest number of households de-worming livestock. The district had the second largest number of households using draft animals in the region. Fish farming was not practiced in the district. It has amongst the poorest access to secondary schools, hospitals, district capital and tertiary market compared to other districts. It also had one of the worst access to tarmac road. The percentage of households without toilet facility in Singida Rural district was 7.3 percent and was among the districts with the highest percent of households owning wheel barrows. Also, the district had the lowest percentage of households with vehicles, bicycles, tv/video and mobile phones. It was the only district with households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 94 for cooking. The roofing material for most of the households in the district was grass/mud (71.4%) and iron sheets (21.4%). The most common source of drinking water was from unprotected well. It was the second highest percent of households having two meals per day. The district had the third highest percent of households that did not eat meat and the least district in percentage of household that did not eat fish during the week prior to enumeration, however small number of households seldom had problems with food satisfaction. 4.2.3 Manyoni Manyoni district had the largest number of agricultural households in the region and it had amongst the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in production of crops only, followed by crops and livestock. Livestock only production and pastoralists were not found in the district. The most important livelihood activity for smallholder households in Manyoni district was annual crop farming, followed by off farm income. However, the district has the third highest percent of households with off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Manyoni had the third highest percent of female headed households (23.1%) and it had one of the least average age of the household head in the region. Its average household size of 5 members per household was average for the region. Manyoni has the least literacy rate for agricultural household members and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was the highest than in the region. It has a higher utilized land area per household (2.6ha) than the regional average of 2.2 ha and 77 percent of the allocated area is currently being utilised. The total planted area is lower than in other districts in the region, however it has the highest planted area per household (3.3ha) attributed to the low number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 32,035 ha, however the planted area per household was 1.18 ha which was the second highest in the region. Paddy production was important in the district with the highest area planted (1,873 ha). The district had the third highest production of sorghum (8,589 ha). Irish potatoes were produced in small quantities with no wheat production. The district had the largest planted area of cassava accounting for 34 percent of the cassava planted area in the region. The production of beans in Manyoni was the second highest in the region with a planted area of 3,051 ha. Oilseed crops were important in Manyoni district with the highest area planted with groundnut (5,897 ha) accounting for 58 percent of the total planted area in the region. Vegetable production was not important in the district. Traditional crops were mainly grown in the district with 1,387 ha of tobacco and 687 ha of cotton. Permanent crops were important in Manyoni district (34.2% of the total permanent crop planted area in Singida region was found in the district). The most prominent permanent crops in the district included mangos (2,770 ha) and guava (269 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand and small land preparation was done by oxen. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 95 The use of inputs in the region was small, however district differences existed. Manyoni had the third largest area planted with improved seeds in Singida region and this was due to the dominance of traditional crops which need improved seed for good harvest. The district had small area planted with the application of fertilizers (farm yard manure, compost and inorganic fertilizer), however most of these were farm yard manure. Compared to other districts in the region, Manyoni district had the second smallest area applied with herbicides and the largest area applied with fungicides. The use of pesticides was relatively moderate. It had the largest irrigated area (8,405 ha). The most common source of water for irrigation was from canal using gravity. Flood was the most common means of water application and bucket/watering can were also used. The most common method of crop storage in Manyoni was in sacks/open drum; however the proportion of households storing crops in the district was the highest in the region. The district had the highest percent of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. Manyoni district had the highest percent of households processing crops in the region and most of the processing was done to neighbours machine. However, the district had the second highest percent of households processing crops on farm by hand. The district had moderate percent of households selling processed crops. The district had the highest percent of households receiving credit with slightly more male headed household accessed credit than female headed households. A comparatively smaller number of households received extension services in Manyoni district and most of the service was from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming was important in Manyoni district (with 16,302 planted trees) and most of these were Moringa species with some Senna species. The least proportion of households with water harvesting bunds was found in Manyoni district and it also had the third largest number of erosion control bunds. The district had a moderate number of cattle in the region and most of these were indigenous. Goat and sheep production was small compared to other districts. It had the smallest number of pigs in the region and the third largest number of chickens, all of which are indigenous. The largest number of layers was found in Manyoni district. The district had small number of ducks; however it had no rabbits, turkeys and donkeys. The largest percent of households reported tsetse fly and tick problems. The district had the least number of household de-worming livestock. The use of draft animals in the district was low with (12%) of household using draft animals. Fish farming was not practiced in the district. It had amongst the best access to feeder roads, primary schools, and all weather roads compared to other districts. However, it had one of the worst accesses to tarmac roads, district capital and hospitals. Manyoni district had the highest percent of households with no toilet facilities and it had no households owning landline, mains electricity, solar, biogas and small percentage of households had vehicles, wheel barrows, Tv/video and mobile phones. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a high percent of households with grass/mud roofs (70.1%) with 18.2 percent of households having iron sheets. The most common source of drinking water was piped water. Sixty four point three percent of the households in the district reported having two meals per day and 32.5%only 0.2 percent of the household reported having DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 three meals per day with only 0.2 percent of households having more than four meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration; however few households seldom had problems with food satisfaction. 4.2.4 Singida Urban Singida Urban district had the least number of households in the region and it had the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. The district had no households with livestock only or pastoralists. The most important livelihood activity for smallholder households in Singida Urban district was annual crop farming, followed by off farm income and tree/forest resources. However, the district had the second lowest percent of households with off-farm activities and also, the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Singida Urban had the highest percent of female headed households (26.2%) and it had the third highest average age of the household head. Its average household size of 5 members per household was average for the region. Singida Urban had the highest literacy rate for agricultural household members and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was the second highest in the region. It had the smallest utilized land area per household (1.3ha) and the allocated area was almost fully utilized indicating a high level of land pressure. The total planted area was greater than in other districts in the region due to the presence of good wet and dry seasons, however it had the lowest planted area per household (1.4ha) attributed to the high number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 1,694 ha, however the planted area per household was the least in the region. Paddy production was not important with a planted area of only 39 hectares and the production of sorghum was very small. Singida Urban was among the districts that did not produce wheat and Irish potatoes. The production of beans in Singida Urban was the least compared to other districts in the region with a planted area of 17 hectares. Oilseed crops were not important in Singida Urban while simsim and groundnuts were not grown in the district. Vegetable production was less important in the district. It had the second largest area planted with tomatoes (82 ha) and the third largest area planted with onions (12 ha) in the region and accounted for 22 percent of the tomato production, 1.5 percent of the onion production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Singida Urban had the area smallest area planted with permanent crops which were dominated by guava (545 ha) and banana (45 ha) and mango (43 ha). Other permanent crops were either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Singida Urban had the smallest area planted with improved seeds in Singida region. The district had the smallest area planted with the application of fertilizers DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 (farm yard manure, compost and inorganic fertiliser), however most were farm yard manure. Compared to other districts in the region, Singida Urban district had low level of insecticides use. The use of fungicides and herbicides were low compared to other districts. It had the smallest area under irrigation in the region (1,113 ha). The most common source of water for irrigation was from well using hand bucket. Bucket/watering can was the most common means of water application. The most common method of crop storage was the locally made traditional crib; however the proportion of households not storing crops was the highest in the region. The district had the lowest number of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. The least percent of households processing crops in Singida region was found in Singida Urban district and most of the processing was done by neighbours machine. The district had a high percent of households selling processed crops to neighbours and no sales were made to traders on farm. Although very small, access to credit in the district was to women headed households and the main sources of credit were religious organisations, NGO and project. A comparatively large number of households received extension services in Singida district and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Singida Urban (with 22,410 planted trees) and most of these were Eucalyptus species with some Gravellis species and Syszygium species. The lowest proportion of households with erosion control and water harvesting structures was found in Singida Urban district and most of these were erosion control bunds; however it also has high number of water harvesting bunds and drainage ditches. The district has the least number of cattle in the region and most of them were indigenous. Goat and sheep production were the smallest in the region with a total number of 37,409 goats and 16,729 sheep; It had the smallest number of pigs and chicken in the region. The district had no layers and the second largest number of broilers in the region. The district had a moderate number of ducks and rabbits with no turkeys or donkeys. The smallest number of households reporting Tsetse fly and tick problems was in Singida Urban and it had the third largest number of households de-worming livestock. The use of draft animals in the district was very small and fish farming was practiced It was amongst the districts with the best access to feeder roads, primary schools and all weather roads compared to other districts. However, it had one of the worst accesses to tertiary market and tarmac roads. Singida Urban district had the second highest percent of households with no toilet facilities and it had the lowest percent of households owning pressing iron, vehicles, and land line. It had the no households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the second largest percent of households with grass/mud roofs (74.5%), with 23.2 percent of households having iron sheets. The most common source of drinking water was from protected well. It had the highest percent of households having two meals per day and the lowest percent with 3 meals per day. The district had the second highest percent of households that did not eat meat and was the third highest percent of household that did not eat fish during the week prior to enumeration, however very few households seldom had problems with food satisfaction. APPENDIX II 98 4. APPENDICES Appendix I Tabulation List................................................................................................................ 99 Appendix II Tables........................................................................................................................... 119 Appendix III Questionnaires .............................................................................................................. 310 APPENDIX II 99 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD........................................................................................ 199 2.1: Number of Agricultural Households by Type of Household and District, 2002/03 Agriculture Year ............................................................................................................... 120 2.2: Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year .............................................................................................................. 120 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES ......................................................... 121 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District ................................................................................................................. 122 3.1a First Most Importance.................................................................................................................. 122 3.1b Second Most Importance ............................................................................................................. 123 3.1c Third Most Importance................................................................................................................ 123 3.1d Fourth Most Importance .............................................................................................................. 123 3.1e Fifth Most Importance ................................................................................................................. 124 3.1f Sixth Most Importance ................................................................................................................. 124 3.1g Seventh Most Importance ............................................................................................................. 125 HOUSEHOLDS DEMOGRAPHS ........................................................................................................ 127 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) ......................................................................................... 128 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %)........................................................................................... 128 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year....................................................................................................... 128 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year............ 129 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year.................................................... 129 3.7 Number of Agricultural Household Members By Main Activity andDistrict, 2002/03 Agricultural Year........................................................................................................ 129 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ...................................................... 130 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year ............................................................... 130 APPENDIX II 100 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.................................. 131 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year................................................ 131 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year .................................................................... 131 3.13 Mean, Meadian, Mode of Age of Head of Agricultural Household and District ..................... 131 3.14 Time Series of Male and Female Headed Households............................................................. 132 3.15 Literacy Rates of Heads of Households by Sex and District.................................................... 132 LAND ACCESS/OWNERSHIP ............................................................................................................ 133 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year...................................................................................................................... 134 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year...................................................................................................................... 135 LAND USE .............................................................................................................................................. 137 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ............................................................................................ 138 5.2 Area of Land (Ha) by type of Land Use and District during 2002/03 Agricultural Year ........ 138 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.................................................................. 138 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District during 2002/03 Agricultural Year................. 139 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year................... 139 COMMUNIAL RESOURCES............................................................................................................... 141 6.1 Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year ................................... 142 6.2 Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District............................................................................. 142 6.3 Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year District............................................................................. 143 6.4: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District................................... 143 6.5 Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District................................... 144 APPENDIX II 101 6.6 Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District................................... 144 6.7 Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District................................................ 144 6.8 Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District................................... 145 6.9 Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District........................................ 145 6.10 Number of Agricultural Households with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year District................................... 145 TOTAL ANNUAL CROP & VEGE PRODUCTION - LONG AND SHORT RAINY SEASON .. 147 7.1 & 7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region..................................................................... 148 7.1 & 7.2d Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region..................................................................... 149 7.1 & 7.2e Total Number of Agriculture Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year- SHORT RAINY SEASON.................................................................................................... 150 7.1 1& 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Singida Region .............................................................................................. 150 7.1 Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 150 7.2 Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON...................................... 150 7.1 & 7.2h Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON................................ 151 7.1 & 7.2i Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 151 7.1 & 7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 151 7.1 & 7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON............................. 151 ANNUAL CROP AND VEGE PRODUCTION - SHORT RAINY SEASON................................... 153 7.1a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON ................... 154 7.1b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON ............................................. 154 APPENDIX II 102 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 154 7.1d Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON................................... 155 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 155 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 155 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - SHORT RAINY SEASON..................................... 156 ANNUAL CROP AND VEGE PRODUCTION-LONG RAINY SEASON....................................... 157 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON.............. 158 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON ............................................... 158 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON......................................... 158 7.2d Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON..................................... 159 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON......................................... 159 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District....................................................................................... 160 7.2g Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON................................................ 160 7.2h Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON....................................... 161 7.2i Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop......................................... 162 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 162 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 162 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District; 2002/03 Agricultural Year ................. 163 APPENDIX II 103 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 164 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 164 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year........................ 164 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year........................ 165 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 165 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 165 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 APPENDIX II 104 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 170 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year .................... 170 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 170 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year.......................... 174 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 174 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 174 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 175 PERMANENT CROPS.......................................................................................................................... 177 7.3 Production of Permanent Crops by Crop type and Region - Singida Region........................... 178 APPENDIX II 105 AGROPROCESSING ............................................................................................................................ 181 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District 2002/03 Agricultural Year........................................................................................................ 182 8.0b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year........................................................................................................ 182 8.1.1a Number of Crop Growing Households Processing Crops During 2002/03 agricultural Year by Location and Crop, Singida Region ........................................................ 183 8.1.1b Number of Crop Growing Households Reporting Farm Products Produced During 2002/03 Agricultural Year by Use of Products and Crop, 2002/03 ............................. 183 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop......................... 184 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District ................................................................................................... 184 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District......................................................................... 185 8.0f Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District ................................................................................................... 185 8.0g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District....................................................................................................................... 185 STORAGE............................................................................................................................................... 187 9.0 Number of Households Storing Crops By Estimated Storage Loss and Crop Type ................ 188 9.0a Number of Households Storing Crops By Main Purpose of Storage and Crop Type .............. 190 9.1 Number of Households and Current Quantity Stored (tons) by Crop Type and District ......... 194 9.2 Number of Households that Stored Crops By Length of Storage and Crop Type.................... 195 9.3 Number of Households Storing Crops By Method of Storage and District ............................. 196 MARKETING......................................................................................................................................... 197 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District...................................................................................................... 198 10.2: Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year .......................................................................... 198 10.3 Proportion of Household who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year .......................................................................... 198 \\ APPENDIX II 106 IRRIGATION ......................................................................................................................................... 199 11.1. Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District.......................................................................... 200 11.2 Area of Irrigated and Non Irrigatable (ha) Land By District.................................................... 200 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District......................................................................... 200 11.4 Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District...................................................................................................................... 200 11.5 Number of Households Using Irrigation By Method of Irrigation Application By District ................................................................................................................................ 200 11.6 Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District............................................................................................................... 201 11.7 Number of Erosion Control Harvesting Structures By Type and District................................ 201 ACCESS TO FARM INPUTS/ IMPLEMENTS.................................................................................. 203 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................... 205 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year.......................................................................................... 205 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year.......................................................................................... 206 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year.......................................................................................... 207 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year.......................................................................................... 207 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year.......................................................................................... 207 APPENDIX II 107 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.......................................................................................... 208 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................... 208 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ....................................................................... 208 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ....................................................................... 209 12.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 209 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year..................................................................................... 209 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................... 209 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year.................................................... 210 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year..................................................... 210 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year.................................................... 210 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 210 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year .................................................................. 211 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year.......................................................... 211 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year.................................................... 211 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year..................................................... 211 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year.................................................... 212 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 212 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .................................................................. 212 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year.......................................................... 212 APPENDIX II 108 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year........................................................................................................ 214 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year........................................................................................................ 214 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................... 214 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ....................................................................... 214 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ....................................................................... 215 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 215 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year..................................................................................... 215 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................... 215 12.2.1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 ................. 216 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year..................................................................................... 216 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District ............................................................................................................ 217 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District.......................................................................................... 217 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District...................................................................................................................... 217 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District ............................................................................................................ 217 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District.......................................................................................... 218 APPENDIX II 109 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District ............................................................................................................ 218 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District ............................................................................................................ 218 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District.......................................................................................... 218 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District.......................................................................................... 219 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District.......................................................................................... 219 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District.................................................................................................................. 219 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District ................................................................................................. 219 12.2.15 Number of Agricultural Households Owning OXEN by Source of Finance and District.................................................................................................................. 220 12.2.16 Number of Agricultural Households Owning OX Plough by Source of Finance and District.................................................................................................................. 220 12.2.17 Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District ................................................................................................. 220 12.2.18 Number of Agricultural Households Owning OX CART by Source of Finance and District.................................................................................................................. 221 12.2.19 Number of Agricultural Households Owning TRACTOR by Source of Finance and District.................................................................................................................. 221 12.2.21 Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District ................................................................................................. 221 AGRICULTURE CREDIT.................................................................................................................... 223 13.1a Number of Credit Received By Main Purpose of credit and District....................................... 224 13b Number of Agriculture household Received Credit By Sex .................................................... 224 13c Number of Agriculture household Received Credit By Source of Credit by District .............. 224 13d Number of Agriculture household Received Credit By Reason for not using Credit by District................................................................................................. 224 TREE FARMING AND AGROFORESTRY....................................................................................... 225 14.1 Number of Household having planted Tree by District........................................................... 226 14.2 Number of Household with planted tree on their land and number of tree by planting location226 14.3 Number of Planted tree by Species and District....................................................................... 266 APPENDIX II 110 14: Main Use of Trees By District.................................................................................................. 227 14 Second Use of Trees By District .............................................................................................. 227 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District .................................................................................................... 227 14.4 Number of Households By Distance to Community Planted Forest (Km) By District............ 228 14.5 Number of Households Involved in Community Tree Planting Scheme By Main Use and District......................................................................................................... 228 CROP EXTENSION .............................................................................................................................. 229 15.1 Number of Households Receiving Extension Messages By District........................................ 230 15.2 Number of Households By Quality of Extension Services By District.................................... 230 15.3 Number of Households By Source of Extension Messages By District................................... 230 15.4 Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District ............................................................................................... 231 15.5 Number of Households By Receiving Advice on Agrochemicals By Source of Messages By District ............................................................................................... 231 15.6 Number of Households By Receivingf Advice on Erosion Control By Source of Messages By District ............................................................................................... 231 15.7 Number of Households By Receiving Advice on Organic Fertiliser Use By Source of Messages By District.......................................................................................... 232 15.8 Number of Households By Receiving Advice on Inorganic Fertiliser Use By Source of Messages By District.......................................................................................... 232 15.9 Number of Households By Receivingf Advice on Use of Improved Seed By Source of Messages By District.......................................................................................... 232 15.10 Number of Households By Receiving Advice on Mechanisation / LST By Source of Messages By District.......................................................................................... 233 15.11 Number of Households By Receiving Advice on Irrigation Technology By Source of Messages By District.......................................................................................... 233 15.12 Number of Households By Receiving Advice on Crop Storage By Source of Messages By District............................................................................................................ 233 15.13 Number of Households By Receiving Advice on Vermin Control By Source of Messages By District ............................................................................................... 234 15.14 Number of Households By Receiving Advice on Agro-processing By Source of Messages By District ............................................................................................... 234 15.15 Number of Households By Receiving Advice on Agro-forestry By Source of Messages By District ............................................................................................... 234 APPENDIX II 111 15.16 Number of Households By Receiving Advice on Beekeeping By Source of Messages By District ............................................................................................... 235 15.17 Number of Households By Receiving Advice on Fish Farming By Source of Messages By District ............................................................................................... 235 5.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 1) During the 2002/03 Agriculture Year, Singida Region ......................................................................................................................... 236 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 2) During the 2002/03 Agriculture Year, Singida Region ......................................................................................................................... 236 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 3) During the 2002/03 Agriculture Year, Singida Region........... 236 LIVELIHOOD CONSTRAINTS .......................................................................................................... 237 16.1 Most Important Constraints By District ................................................................................... 238 16.2 Second Most Important Constraints By District....................................................................... 238 16.3 Third Important Constraints By District................................................................................... 239 16.4 Forth Important Constraints By District................................................................................... 239 16.5 Fifth Important Constraints By District.................................................................................... 240 16.6 Least Important Constraints By District................................................................................... 241 16.7 Second Least Important Constraints By District ...................................................................... 241 16.8 Third Least Important Constraints By District......................................................................... 242 16.9 Forth Least Important Constraints By District ......................................................................... 243 16.10 Fifth Least Important Constraints By District .......................................................................... 243 ANIMAL CONTRIBUTION TO CROP PRODUCTION.................................................................. 245 17.1 Number of Households Using Draft Animal to Cultivate Land By District ............................ 246 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.......................................................................... 246 17.3 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.......................................................................... 246 17.4 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year ............................................................................................ 247 17.5 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year....................................................................................................................... 247 APPENDIX II 112 CATTLE PRODUCTION...................................................................................................................... 249 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year....................................................................................................................... 250 18.2 Number of Cattle By Type and District as of 1st October, 2003 ............................................. 250 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 .................................................................................... 251 18.4 Number of Cattle by Category and Type of Cattle as of 1st October 2003.............................. 252 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 252 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 252 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 253 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 253 18.9 Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year ............................................................................................. 253 GOATS PRODUCTION........................................................................................................................ 255 19.1 Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year....................................................................................................................... 256 19.2 Total Number of Goats by Type and District as of 2st October, 2003..................................... 256 19.3 Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003....................................................................................... 257 19.4.1 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District ...................................................................................................................... 258 19.6 Number of Indigenous Goat by Category and District as of 1st October, 2003....................... 258 19.7 Number of Improved Meat Goat by Category and District as of 1st October, 2003................ 258 19.8 Number of Improved Dairy Goat by Category and District as of 1st October, 2003............... 258 19.4 Number of Total Goat by Category and District as of 1st October, 2003................................ 259 19.5 Goat Offtake By Type and District .......................................................................................... 259 19.6 Number of Goat Died and % of Offtake By Tpe and District.................................................. 259 19.7 Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year 260 SHEEP PRODUCTION......................................................................................................................... 261 20.1 Number of Households Rearing Sheep by District as of 1st October, 2002.0/Agriculture Year262 20.2 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03.......................... 262 APPENDIX II 113 20.3.1 Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03................................................................ 263 20.4.1 Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year....................... 264 20.5 Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year.......................................................................................... 264 20.6 Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year.......................................................................................... 264 20.7 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year....................................................................................................................... 265 20.8 Sheep Intake By Type and District........................................................................................... 265 20.9 Number of Sheep Died and % of Offtake By Type and District.............................................. 266 20.10 Number of Sheep Sold and Value (Tshs) by Category and District during 2002/03 Agriculture Year....................................................................................................................... 266 LIVESTOCK PESTS AND PARASITE CONTROL ......................................................................... 269 22.1 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ............................... 271 22.2 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock..................... 271 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ..................... 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year......................................... 271 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ............... 271 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year ............................. 271 OTHER LIVESTOCK ........................................................................................................................... 273 23.1 Total Number of Other Livestock by Breed and Type............................................................. 274 23.2 Number of Households Rearing and number of Other Livestock by Type and District .......... 274 23.3 Number of Chicken by Type and District ................................................................................ 274 23.4 Number of households with chicken and Category of Chicken by Flock Size ........................ 274 23.4 Number of households with chicken and Category of Chicken by District ............................. 274 LIVESTOCK PRODUCTS.................................................................................................................... 275 25.1 Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year......................................................................... 276 APPENDIX II 114 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES:.............................................................. 277 27.1 Number of households by Distance to Nearest Cattle Dip and District .................................. 278 27.2 Number of households by Distance to Nearest Spray Raced and District............................... 278 27.3 Number of households by Distance to Nearest Hand Powered Sprayer and District.............. 278 27.4 Number of households by Distance to Nearest Cattle Crush and District............................... 278 27.5 Number of households by Distance to Nearest Primary Market and District ......................... 278 27.6 Number of households by Distance to Nearest Secondary Market and District ..................... 279 27.7 Number of households by Distance to Nearest Abattoir and District ..................................... 279 27.8 Number of households by Distance to Nearest Slaughter Slab and District ........................... 279 27.9 Number of households by Distance to Nearest Hide/ Skin Shade and District....................... 279 27.10 Number of households by Distance to Nearest Input Supply and District.............................. 280 27.11 Number of households by Distance to Nearest Veterinary Clinic and District....................... 280 27.12 Number of households by Distance to Nearest Village Holding Gound and District ............. 280 27.13 Number of households by Distance to Nearest Village Watering Point/ Dam and District.... 280 27.14 Number of households by Distance to Nearest Drencher and District.................................... 280 FISH FARMING .................................................................................................................................... 281 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year........................................................................................................ 282 LIVESTOCK EXTENSION.................................................................................................................. 283 29.1 Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year .................................................................... 284 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year................................. 284 29.3 Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year ................................................................. 284 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year ................................................... 285 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year ................................................................. 285 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year.................................................... 285 APPENDIX II 115 29.7 Number of Agricultural Households Receiving Extension Advice on Herd / Flock Size and Selection By Source and District, 2002/03 Agricultural Year......................... 286 29.8 Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ................... 286 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year ................ 286 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.................................................... 287 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year ....................................... 287 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year.......................................................................................... 287 29.13 Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year.......................................................................................... 288 29.14 Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year ......................................................... 288 GOVERNMENT REGULATORY PROBLEMS:............................................................................... 289 30.1 Number of Agricultural Households by Whether Face Problems with Government Regulation During 2003/04 by District, 2002/03 Agricultural Year .......................................................... 290 LABOUR USE ........................................................................................................................................ 291 31.1 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year................................................................................................... 292 31.2 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year................................................................................................... 293 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES........................................................ 295 33.1 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.2 Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year...................................................................................................................... 296 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year........................................................................................................ 297 33.6 Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year........................................................................................................ 297 APPENDIX II 116 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year........................................................................................................ 297 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year........................................................................................................ 297 33.9 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year........................................................................................................ 298 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.11 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.12 Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year........................................................................................................ 299 33.14 Number of Agricultural Households by Distance to Extension Center................................... 299 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year........................................................................................................ 299 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year.......................................................................................... 299 33.17 Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year.......................................................................................... 300 33.18 Number of Agricultural Households by Distance to Livestock Development Center ............ 300 33.19 Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year................................................................................... 300 33.20 Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year................................................................................... 300 33.21 Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year................................................................................... 301 33.22 Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year............................................................................ 301 33.23 Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year........................................................................ 301 33.24 Number of Agricultural Households by Satisfaction of Using Livestock Development ........................................................................................................................... 301 HOUSEHOLD FACILITIES................................................................................................................. 303 34.1 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year..................................................................... 304 APPENDIX II 117 34.2 Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year........................................................................................................ 304 34.3 Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year...................................................................... 305 34.4: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year...................................................................... 305 34.5: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year.......................................... 305 34.6: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year .......................... 306 34.7: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year...................... 306 34.8: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .......................................... 306 34.9: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year........................... 306 34-10: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .......... 307 34-11: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year............................................................... 307 34-12: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year .................................................. 308 34-13 Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year ........... 308 34-14: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year............. 308 34-15: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year........................................ 309 34-16: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year........................................................................................................ 309 APPENDIX II 118 APPENDIX II: CROPS Number of Agriculture Households.......................................................................................................... 119 Rank of Importance of Livelihood activities ............................................................................................ 121 Households Demographs.......................................................................................................................... 127 Land access/ownership ............................................................................................................................. 133 Land Use .................................................................................................................................................. 137 Communial Resources.............................................................................................................................. 141 Total annual crop & vegetable production - long and short rainy season................................................. 147 Annual crop and vegetable production - short rainy season..................................................................... 153 Annual crop and vegetable production-long rainy season........................................................................ 157 Permanent Crops....................................................................................................................................... 177 Agroprocessing......................................................................................................................................... 181 Storage...................................................................................................................................................... 187 Marketing.................................................................................................................................................. 197 Irrigation ................................................................................................................................................... 199 Access to Farm Inputs/ Implements.......................................................................................................... 203 Agriculture Credit..................................................................................................................................... 223 Tree Farming and Agroforestry ................................................................................................................ 225 Crop Extension ......................................................................................................................................... 229 Livelihood Constraints.............................................................................................................................. 237 Animal Contribution to crop production .................................................................................................. 245 Cattle Production ...................................................................................................................................... 249 Goats Production ...................................................................................................................................... 255 Sheep Production...................................................................................................................................... 261 Pig Production .......................................................................................................................................... 267 Livestock Pests and Parasite Control........................................................................................................ 269 Other livestock.......................................................................................................................................... 273 Livestock Products.................................................................................................................................... 275 Access to functional livestock facilities: .................................................................................................. 277 Fish Farming............................................................................................................................................. 281 Livestock Extension.................................................................................................................................. 283 Government Regulatory Problems: .......................................................................................................... 289 Labour Use................................................................................................................................................ 291 Access to Infrastructure and Other services.............................................................................................. 295 Household Facilities ................................................................................................................................. 303 Appendix II 119 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 120 District Rural hosehold involved in Agriculture % of Total rural households Rural households NOT involed in Agriculture % of Total rural households Total rural households % of Total rural households Urban households Total number of Household (from 2002 pop. Census) Number % Number % Number % Number Number Iramba 62,255 96 2,408 4 64,663 90 7,014 71,677 Singida Rural 72,954 98 1,374 2 74,329 95 4,165 78,494 Manyoni 33,065 95 1,812 5 34,877 81 8,012 42,889 Singida Urban 11,125 97 375 3 11,500 47 13,012 24,512 Total 179,400 97 5,969 3 185,368 85 32,204 217,572 Number % Number % Number % Iramba 30,411 48.6 273 0.4 31,845 50.9 62,528 62,255 32,118 Singida Rural 33,761 46.1 242 0.3 39,193 53.5 73,197 72,954 39,436 Manyoni 27,088 81.9 0 0.0 5,977 18.1 33,065 33,065 5,977 Singida Urban 5,577 50.1 0 0.0 5,549 49.9 11,125 11,125 5,549 Total 96,837 53.8 516 0.3 82,563 45.9 179,915 179,400 83,079 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agriculture households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Crops Only Livestock Only Crops & Livestock Total Number of agriculture Household Total Number of Households Growing Crops Total Number of Households Rearing Livestock Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 121 RANK OF IMPORTANCE OFLIVELIHOOD ACTIVITIES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 122 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Iramba 172,336 50 6 173,435 50 5 345,770 100 6 Singida Rural 178,701 50 5 179,931 50 4 358,632 100 5 Manyoni 84,660 49 6 88,830 51 4 173,491 100 5 Singida Urban 28,177 48 6 30,722 52 4 58,899 100 5 Total 463,874 50 5 472,918 50 4 936,792 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 1 6 4 3 5 7 2 Singida Rural 1 5 4 2 6 7 3 Manyoni 1 6 4 2 5 7 3 Singida Urban 1 6 4 2 5 7 3 Total 1 6 4 3 5 7 2 Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Livelihood Activity 3.0: Number of Agriculture Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agriculture Year District Male Female Total Average Household Size Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 123 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 54,364 380,545 0 0 1,233 8,630 4,319 30,230 2,114 14,801 211 1,476 288 Singida Rural 45,408 317,857 124 866 6,616 46,313 18,818 131,727 991 6,940 0 0 744 Manyoni 8,817 61,720 255 1,786 2,950 20,648 14,970 104,791 1,403 9,823 0 0 4,074 Singida Urban 4,693 32,853 0 0 1,022 7,154 3,699 25,891 526 3,685 85 596 1,015 Total 113,282 792,975 379 2,652 11,821 82,745 41,806 292,639 5,036 35,250 296 2,072 6,121 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 7,064 42,383 419 2,514 23,487 140,925 16,355 98,131 3,783 22,699 316 1,898 10,155 Singida Rural 25,834 155,006 1,194 7,161 21,166 126,993 18,327 109,961 1,681 10,085 495 2,970 5,077 Manyoni 17,023 102,136 493 2,957 2,124 12,742 6,650 39,902 1,652 9,913 76 455 4,066 Singida Urban 4,783 28,697 84 505 2,912 17,470 2,112 12,669 402 2,412 0 0 909 Total 54,704 328,222 2,190 13,137 49,688 298,130 43,444 260,663 7,518 45,109 887 5,322 20,207 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 820 4,099 563 2,817 4,869 24,345 14,899 74,496 3,632 18,160 422 2,109 33,578 Singida Rural 1,464 7,318 1,542 7,710 10,417 52,083 15,984 79,921 2,431 12,153 246 1,228 38,204 Manyoni 5,566 27,829 501 2,504 2,778 13,892 4,399 21,994 652 3,259 162 811 16,303 Singida Urban 1,419 7,094 244 1,218 1,530 7,652 1,299 6,495 377 1,884 42 211 5,367 Total 9,268 46,341 2,850 14,248 19,594 97,971 36,581 182,906 7,091 35,457 872 4,358 93,452 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 1,703 6,811 3,664 14,658 8,656 34,625 5,089 20,356 245 980 14,933 Singida Rural 248 993 3,388 13,550 4,196 16,786 7,056 28,223 2,275 9,101 125 500 25,163 Manyoni 1,155 4,619 563 2,253 4,862 19,448 2,447 9,789 1,907 7,628 85 340 5,965 Singida Urban 230 922 1,132 4,527 296 1,182 1,286 5,144 212 848 43 170 2,481 Total 1,633 6,533 6,785 27,141 13,019 52,074 19,445 77,780 9,483 37,933 498 1,991 48,542 Table 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance Table 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance Table 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Table 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 124 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 144 433 852 2,555 1,279 3,836 988 2,965 1,704 5,112 0 0 2,053 Singida Rural 0 0 5,346 16,039 1,226 3,678 1,171 3,514 249 746 121 362 2,202 Manyoni 338 1,014 494 1,481 913 2,738 582 1,745 654 1,961 85 254 914 Singida Urban 0 0 659 1,978 43 128 168 504 170 510 0 0 169 Total 482 1,447 7,351 22,053 3,460 10,379 2,909 8,727 2,776 8,329 205 616 5,339 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 428 856 143 285 140 281 285 570 0 0 0 Singida Rural 0 0 614 1227 0 0 0 0 0 0 0 0 103 Manyoni 0 0 0 0 84 169 160 321 158 317 0 0 0 Singida Urban 0 0 0 0 0 0 43 85 0 0 42 84 0 Total 0 0 1,041 2083 227 454 343 687 444 887 42 84 103 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 0 0 0 0 144 144 0 0 0 0 141 Singida Rural 0 0 372 372 124 124 125 125 0 0 0 0 0 Manyoni 0 0 0 0 0 0 0 0 0 0 0 0 0 Singida Urban 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 372 372 124 124 269 269 0 0 0 0 141 Table 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Table 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance Table 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 125 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 427,460 0 15,552 0 192,678 144 240,871 0 81,699 0 6,463 141 Singida Rural 0 481,174 372 46,925 124 245,977 125 353,472 0 39,025 0 5,059 0 Manyoni 0 197,318 0 10,981 0 69,637 0 178,541 0 32,901 0 1,860 0 Singida Urban 0 69,566 0 8,228 0 33,586 0 50,788 0 9,339 0 1,061 0 Total 0 1,175,519 372 81,685 124 541,878 269 823,671 0 162,964 0 14,444 141 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 427,460 15,552 192,678 240,871 81,699 6,463 296,866 Singida Rural 481,174 46,925 245,977 353,472 39,025 5,059 334,149 Manyoni 197,318 10,981 69,637 178,541 32,901 1,860 161,033 Singida Urban 69,566 8,228 33,586 50,788 9,339 1,061 49,829 Total 1,175,519 81,685 541,878 823,671 162,964 14,444 841,878 Iramba 1 6 4 3 5 7 2 Singida Rural 1 5 4 2 6 7 3 Manyoni 1 6 4 2 5 7 3 Singida Urban 1 6 4 2 5 7 3 Total 1 6 4 3 5 7 2 Table 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Census Survey 2003 Singida Region 126 Appendix II 127 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 128 Number % Number % Number % Less than 4 61,961 50 62,486 50 124,446 100 05 - 09 75,426 50 76,808 50 152,234 100 10 - 14 74,260 52 67,770 48 142,030 100 15 - 19 52,220 52 48,907 48 101,127 100 20 - 24 33,478 47 37,248 53 70,726 100 25 - 29 28,086 47 31,119 53 59,205 100 30 - 34 24,456 44 31,590 56 56,046 100 35 - 39 22,415 47 25,255 53 47,670 100 40 - 44 20,633 51 19,597 49 40,230 100 45 - 49 15,963 47 17,899 53 33,862 100 50 - 54 13,061 47 14,689 53 27,750 100 55 - 59 10,044 52 9,171 48 19,215 100 60 - 64 10,146 53 8,999 47 19,145 100 65 - 69 6,745 47 7,714 53 14,459 100 70 - 74 6,297 52 5,740 48 12,036 100 75 - 79 4,014 51 3,839 49 7,853 100 80 - 84 2,704 58 1,990 42 4,694 100 Above 85 1,966 48 2,097 52 4,063 100 Total 463,874 50 472,918 50 936,792 100 Number % Number % Number % Less than 4 61,961 13 62,486 13 124,446 13 05 - 09 75,426 16 76,808 16 152,234 16 10 - 14 74,260 16 67,770 14 142,030 15 15 - 19 52,220 11 48,907 10 101,127 11 20 - 24 33,478 7 37,248 8 70,726 8 25 - 29 28,086 6 31,119 7 59,205 6 30 - 34 24,456 5 31,590 7 56,046 6 35 - 39 22,415 5 25,255 5 47,670 5 40 - 44 20,633 4 19,597 4 40,230 4 45 - 49 15,963 3 17,899 4 33,862 4 50 - 54 13,061 3 14,689 3 27,750 3 55 - 59 10,044 2 9,171 2 19,215 2 60 - 64 10,146 2 8,999 2 19,145 2 65 - 69 6,745 1 7,714 2 14,459 2 70 - 74 6,297 1 5,740 1 12,036 1 75 - 79 4,014 1 3,839 1 7,853 1 80 - 84 2,704 1 1,990 0 4,694 1 Above 85 1,966 0 2,097 0 4,063 0 Total 463,874 100 472,918 100 936,792 100 Number % Number % Number % Iramba 172,336 50 173,435 50 345,770 100 Singida Rural 178,701 50 179,931 50 358,632 100 Manyoni 84,660 49 88,830 51 173,491 100 Singida Urban 28,177 48 30,722 52 58,899 100 Total 463,874 50 472,918 50 936,792 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 129 Number % Number % Number % Number % Number % Iramba 189,432 65 15,025 5 0 0 88,988 30 293,445 100 Singida Rural 149,312 46 74,368 23 0 0 100,316 31 323,996 100 Manyoni 64,567 44 22,686 15 81 0 59,195 40 146,528 100 Singida Urban 30,065 62 5,842 12 0 0 12,470 26 48,377 100 Total 433,376 53 117,921 15 81 0 260,968 32 812,346 100 Number % Number % Number % Number % Iramba 96,219 33 110,939 38 86,287 29 293,445 100 Singida Rural 125,431 39 127,743 39 70,822 22 323,996 100 Manyoni 42,422 29 54,350 37 49,757 34 146,528 100 Singida Urban 19,666 41 19,488 40 9,222 19 48,377 100 Total 283,737 35 312,521 38 216,088 27 812,346 100 Number % Number % Number % Number % Iramba 129,780 44 26,453 9 289 0 1,054 0 Singida Rural 129,711 40 38,245 12 733 0 125 0 Manyoni 74,178 51 9,657 7 0 0 0 0 Singida Urban 19,257 40 5,402 11 0 0 84 0 Total 352,926 43 79,757 10 1,022 0 1,264 0 Number % Number % Number % Number % Iramba 2,626 1 2,525 1 144 0 2,689 1 Singida Rural 2,190 1 3,863 1 1,728 1 9,671 3 Manyoni 745 1 522 0 81 0 1,635 1 Singida Urban 169 0 414 1 184 0 428 1 Total 5,729 1 7,324 1 2,136 0 14,423 2 Number % Number % Number % Number % Iramba 1,141 0 562 0 144 0 417 0 Singida Rural 720 0 473 0 0 0 1,113 0 Manyoni 1,769 1 418 0 0 0 743 1 Singida Urban 305 1 43 0 0 0 43 0 Total 3,934 0 1,495 0 144 0 2,315 0 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Main Activity District Crop/Seaweed Farming p g Herding Livestock Pastoralist 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Fishing District Main Activity Self Employed (Non Farmimg) without Employees cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity District Government / Parastatal Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees p y p (Non Agriculture) Not Working & Available Not Working & Unavailable cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Housewife Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 130 Number % Number % Number % Number % Iramba 93,234 32 30,565 10 1,823 1 293,445 100 Singida Rural 121,979 38 12,710 4 735 0 323,996 100 Manyoni 41,288 28 14,601 10 892 1 146,528 100 Singida Urban 19,296 40 2,583 5 170 0 48,377 100 Total 275,798 34 60,458 7 3,619 0 812,346 100 Number % Number % Number % Number % Number % Iramba 97,961 33 11,322 4 64,715 22 119,447 41 293,445 100 Singida Rural 68,086 21 17,090 5 153,175 47 85,645 26 323,996 100 Manyoni 10,227 7 22,874 16 86,272 59 27,155 19 146,528 100 Singida Urban 9,116 19 2,371 5 23,013 48 13,877 29 48,377 100 Total 185,389 23 53,656 7 327,175 40 246,125 30 812,346 100 Number % Number % Number % Number % Iramba 431 0 392 0 1,670 2 1,128 1 Singida Rural 124 0 741 1 2,184 2 1,949 2 Manyoni 82 0 82 0 1,837 3 1,875 3 Singida Urban 42 0 42 0 211 1 210 1 Total 679 0 1,257 0 5,903 2 5,163 2 Number % Number % Number % Number % Iramba 9,843 9 2,619 2 1,898 2 87,460 79 Singida Rural 10,314 8 1,476 1 989 1 102,185 80 Manyoni 6,639 12 1,709 3 1,879 3 36,996 68 Singida Urban 1,803 9 212 1 422 2 15,536 80 Total 28,599 9 6,016 2 5,188 2 242,176 77 Number % Number % Number % Number % Iramba 1,131 1 143 0 139 0 143 0 Singida Rural 2,023 2 353 0 0 0 123 0 Manyoni 714 1 0 0 0 0 84 0 Singida Urban 170 1 248 1 0 0 0 0 Total 4,038 1 744 0 139 0 350 0 Number % Number % Number % Number % Iramba 959 1 0 0 1,838 2 0 0 Singida Rural 586 0 0 0 2,525 2 0 0 Manyoni 164 0 170 0 883 2 0 0 Singida Urban 83 0 0 0 381 2 43 0 Total 1,792 1 170 0 5,628 2 43 0 Main Activity cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Retired / Sick / Disabled Other Total Student District 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total Standard Two Education Level Form Two Form Three Form Four Pre Form One Form One Education Level Form Five District Education Level cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Standard Eight g y Education District Under Standard One Standard One 3.9 HOUSEHOLDS DEMOCRAPHS: Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Education Level District Standard Five Standard Six Standard Seven Standard Three Standard Four Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 131 Number % Number % Number % Number % Number % Iramba 0 0 137 0 0 0 1,009 1 110,939 100 Singida Rural 125 0 240 0 118 0 1,687 1 127,743 100 Manyoni 78 0 65 0 0 0 1,092 2 54,350 100 Singida Urban 0 0 0 0 0 0 85 0 19,488 100 Total 203 0 442 0 118 0 3,873 1 312,521 100 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Househol d Size Iramba 286,517 49,682 6 59,253 12,847 5 345,770 62,528 6 Singida Rural 288,561 56,246 5 70,071 16,951 4 358,632 73,197 5 Manyoni 143,554 25,418 6 29,937 7,647 4 173,491 33,065 5 Singida Urban 46,101 8,208 6 12,798 2,917 4 58,899 11,125 5 Total 764,733 139,553 5 172,059 40,362 4 936,792 179,915 5 Number Percent Number Percent Number Percent Number Percent Iramba 37,170 73 9,758 19 4,262 8 51,190 100 Singida Rural 43,622 66 17,787 27 4,395 7 65,804 100 Manyoni 6,210 19 18,821 57 7,870 24 32,901 100 Singida Urban 5,589 61 2,642 29 910 10 9,141 100 Total 92,591 58 49,008 31 17,437 11 159,036 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Attending School 0 871 33 0 0 0 0 903 Completed 185 111,065 326 3,876 185 118 2,257 118,012 Never Attended to School 61,000 0 0 0 0 0 0 61,000 Total 61,185 111,935 359 3,876 185 118 2,257 179,915 Mean Median Mode Mean Median Mode Mean Median Mode Iramba 46 43 30 52 52 65 48 45 40 Singida Rural 45 42 40 52 50 45 47 45 40 Manyoni 44 41 35 47 46 65 45 42 40 Singida Urban 46 42 31 47 46 50 46 44 30 Total 45 42 40 51 50 65 47 44 40 y y Education cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Adult Education Total District Education Level Form Six g y Education 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head Female Total District Male 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year Education Status Maximum Education Level Attained 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm Income Total 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 132 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 129,691 137,363 140,272 157,641 144,490 139,553 Female Headed (Number in Thousands) 39,069 34,361 34,302 42,722 50,926 40,362 Total 168,760 171,724 174,574 200,363 195,416 179,915 Male Headed (Percentage) 77 80 80 79 74 78 Female Headed (Percentage) 23 20 20 21 26 22 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Iramba 108,988 95,469 204,457 37,683 51,305 88,988 146,671 146,773 293,445 Singida Rural 117,335 106,345 223,680 43,807 56,509 100,316 161,142 162,854 323,996 Manyoni 45,720 41,614 87,334 25,400 33,795 59,195 71,120 75,409 146,528 Singida Urban 17,918 17,988 35,907 5,062 7,408 12,470 22,980 25,396 48,377 Total 289,961 261,417 551,378 111,952 149,016 260,968 401,913 410,433 812,346 District Literacy Know Don't know Total 3.15 Literacy Rate of Heads of Households by Sex and District 3.14 Time Series of male and Female Headed Households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 133 LAND ACCESS/OWNERSHIP Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 134 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Iramba 3,958 6 47,355 76 7,919 13 13,416 22 5,030 8 1,111 2 5,642 9 62,255 Singida Rural 5,544 8 63,662 87 4,873 7 3,162 4 3,385 5 1,209 2 3,062 4 72,954 Manyoni 649 2 29,948 91 2,627 8 633 2 1,846 6 222 1 829 3 33,065 Singida Urban 437 4 10,647 96 42 0 337 3 127 1 169 2 413 4 11,125 Total 10,588 6 151,612 85 15,461 9 17,549 10 10,388 6 2,711 2 9,946 6 179,400 Land Access Leased/Certificate of Ownership Households with Area under Other Forms of Tenure Total number of Households 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Area Owned Under Customary Law Bought Rented Borrowed Households with Area Shared Croped Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 135 Area Leased/Certif icate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Iramba 8,650 122,462 12,096 16,975 4,020 968 10,292 175,464 Singida Rural 9,065 123,211 8,085 5,215 4,509 2,653 2,801 155,538 Manyoni 931 91,144 19,564 819 2,102 102 1,635 116,296 Singida Urban 440 14,744 34 290 98 87 158 15,852 Total 19,086 351,560 39,779 23,298 10,730 3,811 14,887 463,150 District Land Access/ Ownership (Hectare) 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Singida 136 Appendix II 137 LAND USE Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 138 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Househ olds with Pasture Househ olds with Fallow Househ olds with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Household Iramba 56,073 12,116 990 144 1,405 1,831 7,339 432 1,497 1,230 1,570 13,796 98,424 Singida Rural 67,143 10,914 2,274 1,667 2,444 5,822 9,806 2,473 1,928 1,288 2,917 6,194 114,869 Manyoni 29,356 9,064 907 239 0 410 9,830 2,396 247 542 962 8,893 62,847 Singida Urban 10,271 1,596 211 572 117 635 1,226 210 423 169 506 1,620 17,557 Total 162,843 33,691 4,382 2,623 3,966 8,698 28,201 5,511 4,094 3,229 5,955 30,503 293,696 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Iramba 113,918 18,419 286 29 2,982 4,265 14,533 466 452 2,052 2,257 15,804 175,464 Singida Rural 99,977 15,723 1,220 3,093 5,777 8,280 8,734 3,763 494 1,151 2,502 4,824 155,538 Manyoni 50,153 13,247 490 153 . 5,168 13,834 9,758 100 2,021 6,022 15,350 116,296 Singida Urban 9,922 1,603 30 212 24 1,045 798 314 163 120 465 1,156 15,852 Total 273,971 48,992 2,026 3,488 8,782 18,758 37,900 14,301 1,209 5,344 11,246 37,134 463,150 % 59 11 0 1 2 4 8 3 0 1 2 8 100 Total Number Percent Number Percent Number Iramba 42,449 68 19,807 32 62,255 Singida Rural 50,629 69 22,326 31 72,954 Manyoni 15,093 46 17,972 54 33,065 Singida Urban 7,386 66 3,740 34 11,125 Total 115,556 64 63,844 36 179,400 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Land Use 5.2 LAND USE: Area of Land by type of Land Use and District during 2002/03 Agricultural Year District Size of Holding (Ha) Land Use 5.3 Number of Households by type of Hosehold and District During 2002/03 Agriculture Year District Yes No Was all Land Available to the Hh Used During 2002/03? Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 139 Total Number Percent Number Percent Number Iramba 35,016 56 27,240 44 62,255 Singida Rural 32,987 45 39,967 55 72,954 Manyoni 22,964 69 10,100 31 33,065 Singida Urban 3,652 33 7,473 67 11,125 Total 94,620 53 84,780 47 179,400 Total Number Percent Number Percent Number Iramba 11,015 18 51,240 82 62,255 Singida Rural 17,194 24 55,760 76 72,954 Manyoni 6,982 21 26,083 79 33,065 Singida Urban 2,663 24 8,463 76 11,125 Total 37,854 21 141,546 79 179,400 5.4 Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District, 2002/03 Agricultural Year 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Yes No Do you Consider that you have sufficient land for the Hh? District Yes No Do any Female Members of the Hh own or have customary right Tanzania Agriculture Census Survey 2003 Singida Region 140 Appendix II 141 COMMUNIAL RESOURCES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 142 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Iramba 0.8 1.5 1.3 2.2 2.2 3.0 2.3 3.1 Singida Rural 0.9 1.7 1.2 2.2 1.7 2.7 2.0 2.1 Manyoni 0.9 2.3 1.5 3.3 2.4 3.5 1.8 2.1 Singida Urban 0.8 1.0 1.2 1.5 1.8 2.7 2.5 2.5 Total 0.9 1.7 1.3 2.3 2.0 2.9 2.1 2.5 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Iramba 3.2 3.3 3.5 3.8 4.6 4.6 7.5 7.5 7.7 8.7 Singida Rural 2.6 2.6 3.4 3.6 4.7 4.6 7.8 7.8 7.3 8.1 Manyoni 3.3 3.3 3.4 3.6 7.2 7.3 8.1 8.1 7.7 8.7 Singida Urban 3.1 2.9 3.2 3.1 4.9 4.9 8.0 8.0 7.6 8.4 Total 3.0 3.0 3.5 3.6 5.1 5.1 7.8 7.8 7.5 8.5 District Communal Resource cont….COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Wood for Charcoal Building Poles Forest for Bees (Honey) Hunting (Animal Fishing (Fish) 6.1 COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Communal Resource District Water for Humans Water for Livestock Communal Grazing Communal Firewood Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 143 Home of Farm Consumptio n / Utilization Not Used by Household Total Iramba 62,528 0 62,528 Singida Rural 73,079 118 73,197 Manyoni 32,656 409 33,065 Singida Urban 11,125 0 11,125 Total 179,389 526 179,915 Home of Farm Consumptio n / Utilization Sold to Neighbours Not Used by Household Not Available Total Iramba 41,163 144 16,427 4,794 62,528 Singida Rural 49,403 243 21,109 2,441 73,197 Manyoni 7,418 85 25,400 162 33,065 Singida Urban 5,983 0 4,974 168 11,125 Total 103,967 473 67,911 7,565 179,915 Home of Farm Consumptio n / Utilization Sold to Neighbours Sold to Local Wholesale Market Not Used by Household Not Available Total Iramba 34,565 0 0 19,782 8,181 62,528 Singida Rural 39,989 118 122 20,757 12,211 73,197 Manyoni 6,074 0 0 22,421 4,570 33,065 Singida Urban 4,389 43 0 3,976 2,718 11,125 Total 85,018 161 122 66,936 27,679 179,915 District Water for Livestock 6.4: COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District Communal Grazing 6.2 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District Water for Humans 6.3 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 144 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 60,828 420 0 0 0 994 288 62,528 Singida Rural 65,766 3,034 248 1,584 0 1,964 601 73,197 Manyoni 31,317 370 74 0 0 1,303 0 33,065 Singida Urban 10,366 339 0 85 42 293 0 11,125 Total 168,276 4,163 322 1,669 42 4,554 889 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 11,228 2,813 280 0 276 289 20,136 27,506 62,528 Singida Rural 13,520 2,725 247 245 728 370 31,820 23,541 73,197 Manyoni 5,218 456 0 149 0 85 26,994 163 33,065 Singida Urban 1,259 635 42 0 0 419 6,754 2,016 11,125 Total 31,226 6,629 569 395 1,004 1,162 85,704 53,226 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 40,786 2,928 0 0 105 144 15,627 2,937 62,528 Singida Rural 47,169 2,048 0 369 1,698 0 13,146 8,766 73,197 Manyoni 26,962 238 139 0 0 0 5,323 402 33,065 Singida Urban 3,380 720 0 42 84 42 5,605 1,252 11,125 Total 118,297 5,935 139 411 1,888 187 39,701 13,357 179,915 6.5 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District Communal Firewood 6.6 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District Wood for Charcoal 6.7 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District Building Poles Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 145 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 2,450 1,587 144 0 0 0 5,562 52,785 62,528 Singida Rural 3,501 478 0 0 0 118 17,337 51,763 73,197 Manyoni 3,993 610 1,262 82 316 0 13,743 13,059 33,065 Singida Urban 33 209 83 0 0 0 159 10,642 11,125 Total 9,977 2,884 1,489 82 316 118 36,800 128,249 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Local Wholesale Market Not Used by Household Not Available Total Iramba 722 433 133 4,996 56,245 62,528 Singida Rural 120 0 0 2,302 70,774 73,197 Manyoni 82 0 0 2,408 30,575 33,065 Singida Urban 0 0 0 0 11,125 11,125 Total 924 433 133 9,706 168,719 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 0 0 0 1,054 0 1,711 59,763 62,528 Singida Rural 483 123 3,594 374 125 4,899 63,600 73,197 Manyoni 84 0 0 0 0 1,169 31,812 33,065 Singida Urban 42 85 0 42 0 1,380 9,575 11,125 Total 609 208 3,594 1,470 125 9,159 164,750 179,915 6.8 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District Forest for Bees Products District Fishing Resources 6.9 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District Hunting Grounds 6.10 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 146 Appendix II 147 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION - LONG AND SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 148 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cereal 1,816 352 194 243,745 89,117 366 245,560 89,468 364 Maize 1,795 340 190 135,482 54,056 399 137,277 54,396 396 Paddy 0 0 0 3,665 1,973 538 3,665 1,973 538 Sorghum 21 11 533 69,884 21,692 310 69,905 21,703 310 Bulrush Millet 0 0 0 30,783 10,025 326 30,783 10,025 326 Finger Millet 0 0 0 3,901 1,357 348 3,901 1,357 348 Wheat 0 0 0 29 14 494 29 14 494 Barley 0 0 0 0 0 0 0 0 0 Roots and Tubers 0 0 0 5,724 5,597 978 5,724 5,597 978 Cassava 0 0 0 2,995 2,424 809 2,995 2,424 809 Sweet Potatoes 0 0 0 2,564 2,807 1095 2,564 2,807 1095 Irish Potatoes 0 0 0 161 364 2253 161 364 2253 Yams 0 0 0 3 2 741 3 2 741 Cocoyam 0 0 0 0 0 0 0 0 0 Pulses 0 0 0 13,342 3,820 286 13,342 3,820 286 Mung Beans 0 0 0 2 9 4117 2 9 4117 Beans 0 0 0 8,328 1,645 198 8,328 1,645 198 Cowpeas 0 0 0 943 299 317 943 299 317 Green Gram 0 0 0 174 75 429 174 75 429 Pigeon Peas 0 0 0 0 0 0 0 0 0 Chich Peas 0 0 0 3,201 1,624 0 3,201 1,624 507 Bambaranuts 0 0 0 695 169 243 695 169 243 Field Peas 0 0 0 0 0 0 0 0 0 Oil Seeds and Oil nuts 279 335 1200 52,843 24,367 461 53,122 24,702 465 Sunflower 279 335 1200 40,590 21,002 517 40,869 21,337 522 Simsim 0 0 0 2,053 887 432 2,053 887 432 Groundnuts 0 0 0 10,146 2,462 243 10,146 2,462 243 Soya Beans 0 0 0 55 17 304 55 17 304 Castor Seed 0 0 0 0 0 0 0 0 0 Fruit and Vegetables 197 390 1982 1,249 1,406 1126 1,445 1,796 1243 Okra 0 0 0 20 8 398 20 8 398 Radish 0 0 0 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 16 14 884 16 14 884 Garlic 0 0 0 0 0 0 0 0 0 Onions 0 0 0 775 830 1072 775 830 1072 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 50 169 3355 50 169 3355 Tomatoes 109 266 2437 215 268 1247 324 534 1648 Spinnach 15 12 823 19 19 962 34 31 902 Carrot 0 0 0 0 0 0 0 0 0 Chillies 0 0 0 4 5 1067 4 5 1067 Amaranths 0 0 0 36 60 1692 36 60 1692 Pumpkins 10 10 988 0 0 0 10 10 988 Cucumber 39 6 154 17 0 20 56 6 113 Egg Plant 24 96 3952 17 19 1112 42 115 2772 Water Mellon 0 0 0 0 0 0 0 0 0 Cauliflower 0 0 0 80 15 185 80 15 185 Cash Crops 0 0 0 2,226 1,370 615 2,226 1,370 615 Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 687 275 400 687 275 400 Tobacco 0 0 0 1,387 1,083 780 1,387 1,083 780 Pyrethrum 0 0 0 152 13 0 152 13 0 Jute 0 0 0 0 0 0 0 0 0 Total 2,292 319,128 321,419 * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to being produced on the same land during the 2 seasons. Previous surveys have used the lpno season to estimate physical land area under production to different crops Table 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 149 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Cereals 899 1,816 7,121 3,901 5,717 32 Maize 733 1,795 132,667 135,482 137,277 1 Paddy 0 0 7,173 3,665 3,665 0 Sorghum 166 21 82,809 69,884 69,905 0 Bulrush Millet 0 0 43,386 30,783 30,783 0 Finger Millet 0 0 7,121 3,901 3,901 0 Wheat 0 0 0 0 0 0 Barley 0 0 0 0 0 0 Root and Tubers 0 0 15,155 5,724 5,724 0 Cassava 0 0 6,610 2,995 2,995 0 Sweet Potatoes 0 0 8,432 2,564 2,564 0 Irish Potatoes 0 0 80 161 161 0 Yams 0 0 33 3 3 0 Cocoyam 0 0 0 0 0 0 Pulses 0 0 28,746 13,342 13,342 0 Mung Beans 0 0 43 2 2 0 Beans 0 0 19,913 8,328 8,328 0 Cowpeas 0 0 2,579 943 943 0 Green Gram 0 0 242 174 174 0 Chich Peas 0 0 2,297 3,201 3,201 0 Bambaranuts 0 0 3,673 695 695 0 Field Peas 0 0 0 0 0 0 Oil Seeds and Oil nuts 138 279 74,450 52,843 53,122 1 Sunflower 138 279 45,857 40,590 40,869 1 Simsim 0 2,765 2,053 2,053 0 Groundnuts 0 0 25,662 10,146 10,146 0 Soya Beans 0 0 167 55 55 0 Castor Seed 0 0 0 0 0 0 Fruit and Vegetables 1,080 197 5,168 1,249 1,445 14 Okra 0 0 126 20 20 0 Bitter Aubergine 0 0 84 16 16 0 Onions 0 0 1,928 775 775 0 Cabbage 0 0 321 50 50 0 Tomatoes 600 109 1,802 215 324 34 Spinnach 120 15 265 19 34 43 Carrot 0 0 0 0 0 0 Chillies 0 0 42 4 4 0 Amaranths 0 0 350 36 36 0 Pumpkins 120 10 0 0 10 100 Cucumber 120 39 85 17 56 69 Egg Plant 0 0 43 17 17 0 Water Mellon 0 0 0 0 0 0 Cauliflower 0 0 123 80 80 0 Cash Crops 0 0 1,867 2,226 2,226 0 Cotton 0 0 399 687 687 0 Tobacco 0 0 1,343 1,387 1,387 0 Pyrethrum 0 0 125 152 152 0 Total 430,589 79,284 81,576 Table 7.1 and 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region Crop Short Rainy Season Long Rainy Season Total Area Planted Short and Long Rainy Season % Area Planted in Short Rainy Season Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 150 Number of Households Planted Area Number of Households Planted Area Number of Household s Planted Area Number of Households Planted Area Iramba 138 2,009 51,714 118,470 10,970 12,193 62,822 132,672 Singida Rural 483 234 31,959 68,074 41,237 45,569 73,679 113,877 Manyoni 0 0 3,838 18,799 29,226 43,685 33,065 62,485 Singida Urban 85 43 1,369 2,215 9,671 8,686 11,125 10,943 Total 706 2,287 88,881 207,558 91,104 110,132 180,691 319,977 % 0.2 0.7 27.8 64.9 28.5 34.4 56.5 100.0 Total Number of Households Planted Area Number of Households Planted Area Number of Household s Planted Area Number of Households Planted Area Planted Area Iramba 26,553 60,010 1,147 3,392 0 0 35,122 69,584 132,986 Singida Rural 25,695 42,261 2,043 2,161 0 0 45,940 69,908 114,330 Manyoni 3,460 6,546 169 171 1,422 3,595 28,014 52,847 63,160 Singida Urban 4,828 5,027 340 305 0 0 5,958 5,611 10,943 Total 60,536 113,845 3,699 6,029 1,422 3,595 115,034 197,951 321,419 Total Number of Household Planted Area Number of Household Planted Area Planted Area Iramba 0 0 567 1,977 1,977 Singida Rural 600 197 125 101 298 Manyoni 0 0 0 0 0 Singida Urban 0 0 41 17 17 Total 600 197 733 2,095 2,292 Total Number of Household Planted Area Number of Household Planted Area Planted Area Iramba 1,559 2,867 60,696 128,142 131,009 Singida Rur 1,584 3,916 71,371 110,116 114,032 Manyoni 2,157 4,202 30,908 58,957 63,160 Singida Urb 775 1,113 10,309 9,814 10,927 Total 6,076 12,098 173,283 307,029 319,128 7.1 and 7.2e: TOTAL ANNUAL CROP AND VEGETABLE: Total Number of Agriculture Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic No Fertilizer Applied District Households Using Irrigation Households Not Using Irrigation District 7.1 1nd 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Morogoro Region Fertilizer Use Irrigation Use 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON Irrigation Use 7.1 ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Households Using Irrigation Households Not Using Irrigation Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 151 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 4,702 11,306 58,120 121,680 62,822 132,986 8.50 Singida Rural 3,930 7,222 69,749 107,108 73,679 114,330 6.32 Manyoni 3,185 10,578 29,880 52,582 33,065 63,160 16.75 Singida Urban 512 515 10,613 10,428 11,125 10,943 4.71 Total 12,329 29,621 168,363 291,798 180,691 321,419 9.22 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 287 875 62,535 132,111 62,822 132,986 0.66 Singida Rural 1,343 1,839 72,336 112,491 73,679 114,330 1.61 Manyoni 210 434 32,855 62,726 33,065 63,160 0.69 Singida Urban 43 34 11,083 10,909 11,125 10,943 0.32 Total 1,882 3,182 178,809 318,237 180,691 321,419 0.99 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 564 1,551 62,258 131,435 62,822 132,986 1.17 Singida Rural 1,686 2,227 71,992 112,102 73,679 114,330 1.95 Manyoni 324 2,901 32,741 60,258 33,065 63,160 4.59 Singida Urban 85 112 11,040 10,832 11,125 10,943 1.02 Total 2,660 6,792 178,031 314,627 180,691 321,419 2.11 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 11,020 27,905 51,802 104,767 62,822 132,672 21.03 Singida Rural 13,069 19,766 60,610 94,111 73,679 113,877 17.36 Manyoni 6,970 12,880 26,136 49,622 33,106 62,501 20.61 Singida Urban 2,846 2,556 9,571 10,663 12,417 13,218 19.33 Total 32,456 62,511 146,902 255,174 179,359 317,685 19.68 Insecticide % of Planted area using Insecticide % of Planted area using Herbicide 7.1 and 7.2h TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON District Total Households Not Using Insecticide Households Using Insecticide % of Planted area using Fungicide % of Planted area using Improved Seed 7.1 and 7.2i TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON 7.1 and 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON 7.1 and 7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Herbicide Total Households Using Improved Seed Households Not Using Improved Seed Total Improved Seed Use Households Not Using Fungicide Total District Herbicide Use Households Using Herbicide District Tanzania Agriculture Census Survey 2003 Singida Region 152 Appendix II 153 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 0 . 429 1,363 138 614 567 1,977 Singida Rural 120 12 120 24 485 261 724 298 Singida Urban 0 . 41 17 0 . 41 17 Total 120 12 590 1,404 622 875 1,333 2,292 % 5 1 26 61 27 38 58 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 286 1,028 0 . 0 . 281 950 567 1,977 Singida Rural 245 150 0 . 0 . 480 148 724 298 Singida Urban 41 17 0 . 0 . 0 . 41 17 Total 572 1,194 0 . 0 . 761 1,098 1,333 2,292 % 43 52 0 . 0 . 57 48 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 600 197 125 101 724 298 66.08 Singida Urban 0 0 41 17 41 17 0.00 Total 600 197 733 2,095 1,333 2,292 8.58 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total % of Planted area using Irrigation Use 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON Total hh are indicative as a household may use more than one type of land preparation method for different crops District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 155 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Insecticide 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted area using Herbicide 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total % of Planted area using Fungicide 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 156 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 724 298 0 0 724 298 100.00 Singida Urban 0 0 41 17 41 17 0.00 Total 724 298 608 1,994 1,333 2,292 12.99 % 54.3 13 45.6 87 100.0 100 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 157 ANNUAL CROP AND VEGETABLE PRODUCTION- LONG RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 138 2,009 51,285 117,107 10,832 11,579 62,255 130,695 Singida Rural 363 222 31,839 68,050 40,753 45,307 72,954 113,579 Manyoni 0 0 3,838 18,799 29,226 43,685 33,065 62,485 Singida Urban 85 43 1,328 2,198 9,671 8,686 11,084 10,927 Total 586 2,274 88,291 206,154 90,482 109,257 179,359 317,685 % 0.3 0.7 49.2 64.9 50.4 34.4 100.0 100.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 26,267 58,982 1,147 3,392 0 . 34,841 68,634 62,255 131,009 Singida Rural 25,451 42,111 2,043 2,161 0 . 45,460 69,760 72,954 114,032 Manyoni 3,460 6,546 169 171 1,422 3,595 28,014 52,847 33,065 63,160 Singida Urban 4,786 5,011 340 305 0 . 5,958 5,611 11,084 10,927 Total 59,964 112,651 3,699 6,029 1,422 3,595 114,274 196,853 179,359 319,128 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 1,559 2,867 60,696 128,142 62,255 131,009 2.2 Singida Rural 1,584 3,916 71,371 110,116 72,954 114,032 3.4 Manyoni 2,157 4,202 30,908 58,957 33,065 63,160 6.7 Singida Urban 775 1,113 10,309 9,814 11,084 10,927 10.2 Total 6,076 12,098 173,283 307,029 179,359 319,128 3.8 % 3.4 4 96.6 96 100.0 100 Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Households Using Irrigation Households Not Using Irrigation Total 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied % of Planted area using Irrigation Use 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON District Irrigation Use Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 159 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 4,702 11,306 57,553 119,703 62,255 131,009 Singida Rural 3,810 7,173 69,144 106,859 72,954 114,032 Manyoni 3,185 10,578 29,880 52,582 33,065 63,160 Singida Urban 512 515 10,572 10,411 11,084 10,927 Total 12,209 29,573 167,150 289,555 179,359 319,128 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 287 875 61,968 130,134 62,255 131,009 0.67 Singida Rural 1,223 1,790 71,732 112,242 72,954 114,032 1.57 Manyoni 210 434 32,855 62,726 33,065 63,160 0.69 Singida Urban 43 34 11,042 10,892 11,084 10,927 0.32 Total 1,762 3,134 177,596 315,994 179,359 319,128 0.98 % 1 1 99 99 100 100 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Herbicide Use 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 160 Number % Number % Iramba 24,877 39.8 37,652 60.2 62,528 Singida Rural 36,760 50.2 36,437 49.8 73,197 Manyoni 17,251 52.2 15,814 47.8 33,065 Singida Urban 2,833 25.5 8,292 74.5 11,125 Total 81,720 45.4 98,195 54.6 179,915 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 564 1,551 61,691 129,458 62,255 131,009 1.2 Singida Rural 1,567 2,179 71,388 111,853 72,954 114,032 1.9 Manyoni 324 2,901 32,741 60,258 33,065 63,160 4.6 Singida Urban 85 112 10,999 10,815 11,084 10,927 1.0 Total 2,540 6,743 176,819 312,384 179,359 319,128 2.1 % 1 2 99 98 100 100 District Number of Households that Sold Number of Households that Did not Sell Households Using Fungicide Households Not Using Fungicide Total 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District Did the Hh Sell any Crops from the 2002/03 season? Total Number of Households 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON % of Planted area using Fungicide Use District Fungicide Use Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 161 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 11,020 27,905 51,235 102,790 62,255 130,695 21.4 Singida Rural 12,344 19,468 60,610 94,111 72,954 113,579 17.1 Manyoni 6,970 12,880 26,095 49,605 33,065 62,485 20.6 Singida Urban 2,121 2,258 8,963 8,669 11,084 10,927 20.7 Total 32,456 62,511 146,902 255,174 179,359 317,685 19.7 % 18 20 82 80 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0 Singida Rural 724 298 0 0 724 298 100 Singida Urban 0 0 41 17 41 17 0 Total 724 298 608 1,994 1,333 2,292 13 % 54.3 13 45.6 87 100 100 District Improved Seed Use % of Planted area using Improved Seed g Improved Seed g Improved Seed Total District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Fungicide Use 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 162 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 567 1,698 278 0.2 50,638 59,062 17,170 0.3 60,761 17,448 0.3 Singida Rural 125 88 52 0.6 51,194 42,699 21,146 0.5 42,787 21,198 0.5 Manyoni 0 0 0 0.0 27,194 32,035 15,102 0.5 32,035 15,102 0.5 Singida Urban 41 8 10 1.2 3,641 1,686 639 0.4 1,694 649 0.4 Total 733 1,795 340 0.2 132,667 135,482 54,056 0.4 137,277 54,396 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 845 615 186 0.3 615 186 0.3 Singida Rural 0 0 0 0.0 2,055 1,140 1,128 1.0 1,140 1,128 1.0 Manyoni 0 0 0 0.0 4,104 1,873 589 0.3 1,873 589 0.3 Singida Urban 0 0 0 0.0 169 39 70 1.8 39 70 1.8 Total 0 0 0 0.0 7,173 3,665 1,973 0.5 3,665 1,973 0.5 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0 27,844 29,836 6,296 0.2 29,836 6,296 0.2 Singida Rural 125 13 6 0.5 39,387 29,315 12,474 0.4 29,328 12,480 0.4 Manyoni 0 0 0 0 11,096 8,589 2,233 0.3 8,589 2,233 0.3 Singida Urban 41 8 5 0.6 4,483 2,143 689 0.3 2,151 694 0.3 Total 166 21 11 0.0 82,809 69,884 21,692 0.3 69,905 21,703 0.3 Table 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year District Maize Short Rainy bseason Long Rainy bSeason Total Table 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultura Year District Paddy Short Rainy bseason Long Rainy bSeason Total Table 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sorghum Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 163 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 5,906 3,428 1,216 0.0 3,428 1,216 0.0 Manyoni 0 0 0 0.0 243 75 21 0.3 75 21 0.3 Singida Urban 0 0 0 0.0 972 399 120 0.0 399 120 0.0 Total 0 0 0 0.0 7,121 3,901 1,357 0.0 3,901 1,357 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 6,475 6,949 1,600 0.2 6,949 1,600 0.2 Singida Rural 0 0 0 0.0 26,832 16,562 6,438 0.0 16,562 6,438 0.0 Manyoni 0 0 0 0.0 1,871 2,116 376 0.0 2,116 376 0.0 Singida Urban 0 0 0 0.0 8,207 5,156 1,610 0.0 5,156 1,610 0.0 Total 0 0 0 0.0 43,386 30,783 10,025 0.0 30,783 10,025 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Table 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District 2002/03 Agricultural Year District Fingemillet Short Rainy bseason Long Rainy bSeason Total Table 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bulrushmillets Short Rainy bseason Long Rainy bSeason Total Table 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/0 Agricultural Year District Wheat Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 164 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 3,116 842 1,100 1.3 842 1,100 1.3 Singida Rural 0 0 0 0.0 1,221 964 354 0.4 964 354 0.4 Manyoni 0 0 0 0.0 1,628 1,019 819 0.8 1,019 819 0.8 Singida Urban 0 0 0 0.0 646 171 151 0.9 171 151 0.9 Total 0 0 0 0.0 6,610 2,995 2,424 0.8 2,995 2,424 0.8 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 3,670 911 127 0.1 911 127 0.1 Singida Rural 0 0 0 0.0 2,300 755 1,845 2.4 755 1,845 2.4 Manyoni 0 0 0 0.0 1,848 726 681 0.9 726 681 0.9 Singida Urban 0 0 0 0.0 614 171 153 0.9 171 153 0.9 Total 0 0 0 0.0 8,432 2,564 2,807 1.1 2,564 2,807 1.1 Table 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year District Barley Short Rainy bseason Long Rainy bSeason Total Table 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cassava Short Rainy bseason Long Rainy bSeason Total Table 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sweet potatoes Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 165 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 80 161 364 0.0 161 364 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 80 161 364 0.0 161 364 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 33 3 2 0.0 3 2 0.0 Total 0 0 0 0.0 33 3 2 0.7 3 2 0.7 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Table 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year District Irish potatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year District Yams Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District 2002/03 Agricultural Year District Cocoyams Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 166 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 2 9 4.1 2 9 4.1 Total 0 0 0 0.0 43 2 9 4.1 2 9 4.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 10,124 4,209 469 0.1 4,209 469 0.1 Singida Rural 0 0 0 0.0 3,396 1,051 374 0.4 1,051 374 0.4 Manyoni 0 0 0 0.0 6,308 3,051 797 0.3 3,051 797 0.3 Singida Urban 0 0 0 0.0 85 17 5 0.3 17 5 0.3 Total 0 0 0 0.0 19,913 8,328 1,645 0.2 8,328 1,645 0.2 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 143 29 3 0.1 29 3 0.1 Singida Rural 0 0 0 0.0 860 237 63 0.3 237 63 0.3 Manyoni 0 0 0 0.0 1,468 653 230 0.4 653 230 0.4 Singida Urban 0 0 0 0.0 108 23 3 0.1 23 3 0.1 Total 0 0 0 0.0 2,579 943 299 0.3 943 299 0.3 Table 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Mungbeans Short Rainy bseason Long Rainy bSeason Total Table 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Beans Short Rainy bseason Long Rainy bSeason Total Table 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cowpeas Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 167 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 242 174 75 0.4 174 75 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 242 174 75 0.4 174 75 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 980 1,112 604 0.5 1,112 604 0.5 Singida Rural 0 0 0 0.0 495 274 123 0.5 274 123 0.5 Manyoni 0 0 0 0.0 822 1,815 896 0.5 1,815 896 0.5 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 2,297 3,201 1,624 0.5 3,201 1,624 0.5 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 1,697 321 71 0.2 321 71 0.2 Singida Rural 0 0 0 0.0 124 13 7 0.6 13 7 0.6 Manyoni 0 0 0 0.0 1,767 335 88 0.3 335 88 0.3 Singida Urban 0 0 0 0.0 85 26 2 0.1 26 2 0.1 Total 0 0 0 0.0 3,673 695 169 0.2 695 169 0.2 Table 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/0 Agricultural Year District Greengram Short Rainy bseason Long Rainy bSeason Total Table 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/0 Agricultural Year District Chick peas Short Rainy bseason Long Rainy bSeason Total Table 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/0 Agricultural Year District Bambanuts Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 168 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 138 279 335 1.2 23,115 23,946 12,364 0.5 24,225 12,699 0.5 Singida Rural 0 0 0 0.0 20,120 15,130 7,968 0.5 15,130 7,968 0.5 Manyoni 0 0 0.0 1,361 609 262 0.4 609 262 0.4 Singida Urban 0 0 0 0.0 1,261 905 408 0.5 905 408 0.5 Total 138 279 335 1.2 45,857 40,590 21,002 0.5 40,869 21,337 0.5 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 143 116 26 0.2 116 26 0.2 Singida Rural 0 0 0 0.0 121 49 18 0.4 49 18 0.4 Manyoni 0 0 0 0.0 2,501 1,888 843 0.4 1,888 843 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 2,765 2,053 887 0.4 2,053 887 0.4 Table 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/0 Agricultural Year District Fieldpeas Short Rainy bseason Long Rainy bSeason Total Table 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sunflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultura Year District Simsim Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 169 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) % of area Area per g growig hh Iramba 0 0 0 0.0 8,901 2,917 459 0.2 2,917 459 0.2 28.8 0.33 Singida Rural 0 0 0 0.0 2,549 1,332 355 0.3 1,332 355 0.3 13.1 0.52 Manyoni 0 0 0 0.0 14,211 5,897 1,648 0.3 5,897 1,648 0.3 58.1 0.41 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 0.0 0.00 Total 0 0 0 0.0 25,662 10,146 2,462 0.2 10,146 2,462 0.2 100.0 0.40 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 124 50 15 0.3 50 15 0.3 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 4 2 0.4 4 2 0.4 Total 0 0 0 0.0 167 55 17 0.3 55 17 0.3 Table 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Groundnuts Short Rainy bseason Long Rainy bSeason Total Table 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 District Castor oil Short Rainy bseason Long Rainy bSeason Total Table 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Soya beans Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 170 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 126 20 8 0.4 20 8 0.4 Total 0 0 0 0.0 126 20 8 0.4 20 8 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 84 16 14 0.9 16 14 0.9 Total 0 0 0 0.0 84 16 14 0.9 16 14 0.9 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 247 100 214 2.1 100 214 2.1 Singida Rural 0 0 0 0.0 1,473 657 601 0.9 657 601 0.9 Manyoni 0 0 0 0.0 80 5 4 0.7 5 4 0.7 Singida Urban 0 0 0 0.0 127 12 12 1.0 12 12 1.0 Total 0 0 0 0.0 1,928 775 830 1.1 775 830 1.1 Table 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year District Okra Short Rainy bseason Long Rainy bSeason Total Table 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bitter Aubergine Short Rainy bseason Long Rainy bSeason Total Table 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year District Onion Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 171 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 124 25 37 1.5 25 37 1.5 Manyoni 0 0 0 0.0 165 21 127 5.9 21 127 5.9 Singida Urban 0 0 0 0.0 33 4 5 1.3 4 5 1.3 Total 0 0 0 0.0 321 50 169 3.4 50 169 3.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 141 7 11 1.5 7 11 1.5 Singida Rural 600 109 266 2.4 841 108 102 0.9 218 368 1.7 Manyoni 0 0 0 0.0 237 17 39 2.4 17 39 2.4 Singida Urban 0 0 0 0.0 583 82 115 1.4 82 115 1.4 Total 600 109 266 2.4 1,802 215 268 1.2 324 534 1.6 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 141 7 6 0.8 7 6 0.8 Singida Rural 120 15 12 0.8 124 13 13 1.0 27 25 0.9 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 15 12 0.8 265 19 19 1.0 34 31 0.9 Table 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cabbage Short Rainy bseason Long Rainy bSeason Total Table 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tomatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/0 Agricultural Year District Spinnach Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 172 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 42 4 5 1.1 4 5 1.1 Total 0 0 0 0.0 42 4 5 1.1 4 5 1.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 158 9 4 0.4 9 4 0.4 Singida Urban 0 0 0 0.0 192 27 57 2.1 27 57 2.1 Total 0 0 0 0.0 350 36 60 1.7 36 60 1.7 Table 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year District Carrot Short Rainy bseason Long Rainy bSeason Total Table 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chillies Short Rainy bseason Long Rainy bSeason Total Table 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year District Amaranths Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 173 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 10 10 1.0 0 0 0 0.0 10 10 1.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 10 10 1.0 0 0 0 0.0 10 10 1.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 39 6 0.2 0 0 0 0.0 39 6 0.2 Manyoni 0 0 0 0.0 85 17 0 0.0 17 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 39 6 0.2 85 17 0 0.0 56 6 0.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 24 96 4.0 0 0 0 0.0 24 96 4.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 17 19 1.1 17 19 1.1 Total 120 24 96 4.0 43 17 19 1.1 42 115 2.8 Table 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year District Pumpkins Short Rainy bseason Long Rainy bSeason Total Table 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cucumber Short Rainy bseason Long Rainy bSeason Total Table 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/0 Agricultural Year District Eggplant Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 174 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 20 1 6 4.0 0 0 0 0.0 1 6 4.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 123 80 15 0.2 80 15 0.2 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 123 80 15 0.2 80 15 0.2 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 399 687 275 0.4 687 275 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 399 687 275 0.4 687 275 0.4 Table 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year District Water Mellon Short Rainy bseason Long Rainy bSeason Total Table 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cauliflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cotton Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 175 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 1,343 1,387 1,083 0.8 1,387 1,083 0.8 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 1,343 1,387 1,083 0.8 1,387 1,083 0.8 Table 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tobacco Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region 176 Appendix II 177 PERMANENT CROPS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 178 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Star Fruit 70 58 86 1482 Sugarcane 29 14 28 1976 Banana 503 92 213 2309 Mango 806 0 5 0 Pawpaw 26 0 33 0 Guava 14 0 13 0 Lime/Lemon 0 0 . 0 Total 1,449 164 378 2298 Pigeon Pea 65 65 14 217 Cashewnut . 0 6 0 Sugarcane 462 110 3,773 34236 Banana 2,739 129 433 3363 Mango 164 76 169 2218 Pawpaw 21 35 20 575 Orange 50 25 . 0 Guava 439 215 166 773 Lime/Lemon 1 0 12 0 Total 3,940 654 4,593 7024 Sugarcane 18 9 1,393 161834 Tamarin 7 0 . 0 Banana 86 23 180 7758 Mango 2,770 0 22 0 Pawpaw 3 1 12 12844 Guava 269 0 . 0 Lime/Lemon 7 0 . 0 Total 3,159 33 1,607 49001 Pigeon Pea . . . 0 Star Fruit . 0 10 0 Cashewnut . . 1 0 Sugarcane 33 11 63 5824 Nutmeg . . 1 0 Banana 45 14 46 3253 Mango 43 0 58 0 Pawpaw 22 9 7 841 Orange . . 2 0 Guava 545 6 28 4982 Lime/Lemon 2 2 8 4129 Bilimbi 4 4 10 2487 Total 695 45 234 5174 Pigeon Pea 65 65 14 217 Star Fruit 70 58 95 1652 Cashewnut . 0 7 0 Sugarcane 541 144 5,257 36522.005 Tamarin 7 0 . 0 Nutmeg . . 1 0 Banana 3,373 259 873 3375 Mango 3,784 76 254 3331 Pawpaw 72 44 72 1633 Orange 50 25 2 66 Guava 1,268 220 207 939 Lime/Lemon 10 2 20 10007 Bilimbi 4 4 10 2487 Total 9,242 896 6,812 7600 Manyoni Singida Urban Total Table 7.3 Production of Permanent Crops by Crop type and Region - Singida Region District/Crop Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 179 Cont…..7.3 Production of Permanent Crops by Crop type and Region - Singida Region Crop Area Planted % Mango 3,784 40.9 Banana 3,373 36.5 Guava 1,268 13.7 Sugarcane 541 5.9 Pawpaw 72 0.8 Star Fruit 70 0.8 Pigeon Pea 65 0.7 Orange 50 0.5 Lime/Lemon 10 0.1 Tamarin 7 0.1 Bilimbi 4 0.0 Cashewnut 0 0.0 Nutmeg 0 0.0 Total 9,242 100.0 Mostly Farm Yard Manure Mostly Compost No Fertilizer Applied Total Planted Area (ha) Planted Area (ha) Planted Area (ha) Planted Area (ha) Pigeon Pea 30 . 35 65 Star Fruit . . 70 70 Sugarcane 78 63 399 541 Tamarin . . 7 7 Banana 313 229 2,831 3,373 Mango 470 11 3,303 3,784 Pawpaw 23 0 49 72 Orange 50 . . 50 Guava 75 . 1,194 1,268 Lime/Lemon . . 10 10 Bilimbi . . 4 4 Total 1,037 303 7,901 9,242 Cont…. Planted Area with Fertiliser by type Crop Pigeon Pea 30 65 46.0 Star Fruit . 70 0.0 Sugarcane 78 541 14.5 Tamarin . 7 0.0 Banana 313 3,373 9.3 Mango 470 3,784 12.4 Pawpaw 23 72 31.4 Orange 50 50 100.0 Guava 75 1,268 5.9 Lime/Lemon . 10 0.0 Bilimbi . 4 0.0 Total 1,037 9,242 11.2 PERMANENT CROPS: Number of Households by Planted Area by Fertilizer Use by Crop by District Total % Crop Type Crop Type Mostly Farm Yard Manure Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 180 Mostly Compost Total Planted Area (ha) Planted Area (ha) Pigeon Pea . 65 0.0 Star Fruit . 70 0.0 Sugarcane 63 541 11.7 Tamarin . 7 0.0 Banana 229 3,373 6.8 Mango 11 3,784 0.3 Pawpaw 0 72 0.2 Orange . 50 0.0 Guava . 1,268 0.0 Lime/Lemon . 10 0.0 Bilimbi . 4 0.0 Total 303 9,242 3.3 Crop Type Cont…. Planted Area with Fertiliser by type Crop % Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 181 AGROPROCESSING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 182 Number % Number % Number % Iramba 56,039 90 6,489 10 62,528 100 Singida Rural 70,259 96 2,937 4 73,197 100 Manyoni 31,583 96 1,481 4 33,065 100 Singida Urban 9,469 85 1,657 15 11,125 100 Total 167,351 93 12,564 7 179,915 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Iramba 2,904 143 49,732 0 2,693 0 0 568 56,039 Singida Rural 9,483 2,337 55,266 125 2,801 123 125 0 70,259 Manyoni 4,416 1,339 25,744 0 0 0 84 0 31,583 Singida Urban 210 649 7,611 0 923 0 75 0 9,469 Total 17,013 4,468 138,352 125 6,417 123 284 568 167,351 8.0b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District 2002/03 Agricultural Year Households That Processed Crops Households That Did Not Process Crops Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 183 Number % Number % Number % Iramba 56,039 90 6,489 10 62,528 100 Singida Rural 70,259 96 2,937 4 73,197 100 Manyoni 31,583 96 1,481 4 33,065 100 Singida Urban 9,469 85 1,657 15 11,125 100 Total 167,351 93 12,564 7 179,915 100 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 117,228 0 143 143 0 0 117,514 Paddy 5,030 0 0 0 84 0 5,115 Sorghum 71,084 0 0 0 251 65 71,401 Bulrush Millet 39,601 120 123 0 202 0 40,047 Finger Millet 444 0 0 0 0 0 444 Cassava 2,288 0 0 0 0 0 2,288 Sweet Potatoes 1,659 0 0 0 0 0 1,659 Beans 2,524 0 0 0 0 0 2,524 Cowpeas 228 0 0 0 0 0 228 Pigeon Peas 122 0 0 0 0 0 122 Chick Peas 305 0 0 0 0 0 305 Bambaranut 831 124 0 0 0 0 955 Sunflower 4,588 0 142 0 80 0 4,810 Simsim 227 0 0 0 0 0 227 Groundnut 16,876 124 284 0 0 0 17,283 Banana 144 0 0 0 0 0 144 Total 263,179 367 693 143 618 65 265,064 Product Use Crop Table 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 agricultural Year by Location and Crop, Singida Region District Households That Processed Product Households That Did Not Process Product Total 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Farm Products Produced During 2002/03 Agricultural Year by Use of Products and Crop, 2002/03 Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 184 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Trader at Farm Other Did not Sell Total Maize 2,098 518 0 258 165 115 282 114,079 117,514 Paddy 189 0 169 0 0 291 0 4,465 5,115 Sorghum 803 42 0 0 42 121 108 70,286 71,401 Bulrush Millet 611 0 0 123 0 0 246 39,068 40,047 Finger Millet 125 0 0 0 0 0 0 319 444 Cassava 85 0 0 0 0 0 0 2,203 2,288 Sweet Potatoes 0 0 0 0 0 0 0 1,659 1,659 Beans 0 0 0 0 0 0 0 2,524 2,524 Cowpeas 0 0 0 0 0 0 0 228 228 Pigeon Peas 0 0 0 0 0 0 0 122 122 Chick Peas 0 0 0 0 0 80 0 225 305 Bambaranut 0 0 0 0 0 0 0 955 955 Sunflower 421 285 0 143 0 80 0 3,881 4,810 Simsim 0 0 0 0 0 0 0 227 227 Groundnut 414 0 83 0 0 150 0 16,636 17,283 Banana 144 0 0 0 0 0 0 0 144 Total 4,889 845 252 523 207 836 636 256,877 265,064 Flour / Mea Grain Oil Juice Other Total Iramba 53,784 574 843 0 838 56,039 Singida Rural 68,925 1,089 245 0 0 70,259 Manyoni 28,788 1,650 1,064 81 0 31,583 Singida Urban 9,309 160 0 0 0 9,469 Total 160,806 3,473 2,153 81 838 167,351 District Main Product 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultura Year By Location of Sale of Product and Crop Crop Where Sold Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 185 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Iramba 55,611 0 285 143 0 56,039 Singida Rural 70,139 120 0 0 0 70,259 Manyoni 31,583 0 0 0 0 31,583 Singida Urban 9,427 0 0 0 42 9,469 Total 166,761 120 285 143 42 167,351 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Trader at Farm Other Did not Sell Total Iramba 1,274 575 0 143 0 0 282 53,764 56,039 Singida Rural 859 0 0 115 123 0 0 69,164 70,259 Manyoni 506 85 169 0 0 168 0 30,656 31,583 Singida Urban 202 0 0 0 42 0 128 9,097 9,469 Total 2,842 660 169 258 165 168 410 162,680 167,351 Bran Cake Husk Pulp Oil Shell No by- product Other Total Iramba 1,964 2,018 0 0 0 0 52,058 0 56,039 Singida Rural 368 123 1,080 123 123 0 68,318 125 70,259 Manyoni 1,097 634 2,435 0 84 0 27,333 0 31,583 Singida Urban 124 126 85 165 0 85 8,884 0 9,469 Total 3,553 2,900 3,600 288 207 85 156,593 125 167,351 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use District By Product 8.0g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District 8.0f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold Tanzania Agriculture Census Survey 2003 Singida Region 186 Appendix II 187 STORAGE Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 188 No. of Househol ds % No. of Households % No. of Households % No. of Househ olds % No. of Househol ds % Maize 34,537 79.6 3,204 7.4 5,124 11.8 533 1.2 43,397 100.0 Paddy 143 100.0 0 0.0 0 0.0 0 0.0 143 100.0 Sorghum & Millet 21,296 80.0 2,059 7.7 3,151 11.8 112 0.4 26,619 100.0 Beans & Pulses 7,254 92.9 0 0.0 557 7.1 0 0.0 7,810 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 1,979 100.0 0 0.0 0 0.0 0 0.0 1,979 100.0 Total 65,209 81.6 5,262 6.6 8,832 11.0 645 0.8 79,949 100.0 Maize 36,140 80.1 6,426 14.2 2,082 4.6 492 1.1 45,140 100.0 Paddy 1,810 100.0 0 0.0 0 0.0 0 0.0 1,810 100.0 Sorghum & Millet 46,769 91.3 3,941 7.7 363 0.7 125 0.2 51,198 100.0 Beans & Pulses 1,587 92.7 125 7.3 0 0.0 0 0.0 1,712 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 125 100.0 0 0.0 0 0.0 0 0.0 125 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 86,432 86.4 10,491 10.5 2,444 2.4 617 0.6 99,985 100.0 Maize 22,223 91.5 1,342 5.5 479 2.0 250 1.0 24,294 100.0 Paddy 2,856 100.0 0 0.0 0 0.0 0 0.0 2,856 100.0 Sorghum & Millet 8,952 93.3 416 4.3 230 2.4 0 0.0 9,598 100.0 Beans & Pulses 5,769 94.7 83 1.4 240 3.9 0 0.0 6,092 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 79 100.0 0 0.0 0 0.0 0 0.0 79 100.0 Groundnuts/Ba mbara Nuts 4,648 100.0 0 0.0 0 0.0 0 0.0 4,648 100.0 Total 44,612 93.6 1,840 3.9 950 2.0 250 0.5 47,652 100.0 Maize 2,403 95.0 85 3.3 43 1.7 0 0.0 2,530 100.0 Paddy 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Sorghum & Millet 8,420 94.0 455 5.1 43 0.5 42 0.5 8,959 100.0 Beans & Pulses 108 71.8 0 0.0 43 28.2 0 0.0 151 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Total 11,100 94.0 539 4.6 128 1.1 42 0.4 11,809 100.0 9.0 CROP STORAGE: Number of Households Storing Crops By Estimated Storage Loss and Crop Type Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba Singida Rural Manyoni Singida Urban Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 189 No. of Househol ds % No. of Households % No. of Households % No. of Househ olds % No. of Househol ds % 9.0 CROP STORAGE: Number of Households Storing Crops By Estimated Storage Loss and Crop Type Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Maize 95,303 82.6 11,056 9.6 7,727 6.7 1,275 1.1 115,361 100.0 Paddy 4,894 100.0 0 0.0 0 0.0 0 0.0 4,894 100.0 Sorghum & Millet 85,438 88.7 6,870 7.1 3,787 3.9 279 0.3 96,374 100.0 Beans & Pulses 14,719 93.4 207 1.3 839 5.3 0 0.0 15,765 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 167 100.0 0 0.0 0 0.0 0 0.0 167 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 79 100.0 0 0.0 0 0.0 0 0.0 79 100.0 Groundnuts/Ba mbara Nuts 6,669 100.0 0 0.0 0 0.0 0 0.0 6,669 100.0 Total 207,354 86.6 18,133 7.6 12,354 5.2 1,555 0.6 239,395 100.0 Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 190 No. of Households % No. of House holds % No. of Households % No. of Households % No. of Househ olds % Maize 43,112 99.3 0 0.0 285 0.7 0 0.0 43,397 100.0 Paddy 143 100.0 0 0.0 0 0.0 0 0.0 143 100.0 Sorghum & Millet 26,189 98.4 0 0.0 430 1.6 0 0.0 26,619 100.0 Beans & Pulses 4,998 64.0 0 0.0 2,813 36.0 0 0.0 7,810 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 986 49.8 0 0.0 994 50.2 0 0.0 1,979 100.0 Total 75,428 94.3 0 0.0 4,521 5.7 0 0.0 79,949 100.0 Maize 43,546 96.5 0 0.0 1,594 3.5 0 0.0 45,140 100.0 Paddy 1,690 93.4 120 6.6 0 0.0 0 0.0 1,810 100.0 Sorghum & Millet 49,364 96.4 607 1.2 1,227 2.4 0 0.0 51,198 100.0 Beans & Pulses 971 56.7 0 0.0 741 43.3 0 0.0 1,712 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 125 100.0 0 0.0 0 0.0 0 0.0 125 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 95,696 95.7 728 0.7 3,562 3.6 0 0.0 99,985 100.0 Maize 23,572 97.0 253 1.0 470 1.9 0 0.0 24,294 100.0 Paddy 2,554 89.4 141 4.9 160 5.6 0 0.0 2,856 100.0 Sorghum & Millet 9,371 97.6 84 0.9 143 1.5 0 0.0 9,598 100.0 Beans & Pulses 4,121 67.6 234 3.8 1,737 28.5 0 0.0 6,092 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 79 100.0 79 100.0 Groundnuts/ Bambara Nuts 2,928 63.0 139 3.0 1,580 34.0 0 0.0 4,648 100.0 Total 42,631 89.5 851 1.8 4,090 8.6 79 0.2 47,652 100.0 Iramba Singida Rural Manyoni 9.0a CROP STORAGE: Number of Households Storing Crops By Main Purpose of Storage and Crop Type Crop Food for the Household To Sell for Higher Price Seeds for Planting Other Total Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 191 No. of Households % No. of House holds % No. of Households % No. of Households % No. of Househ olds % 9.0a CROP STORAGE: Number of Households Storing Crops By Main Purpose of Storage and Crop Type Crop Food for the Household To Sell for Higher Price Seeds for Planting Other Total Maize 2,488 98.3 42 1.7 0 0.0 0 0.0 2,530 100.0 Paddy 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Sorghum & Millet 8,876 99.1 83 0.9 0 0.0 0 0.0 8,959 100.0 Beans & Pulses 85 56.4 0 0.0 66 43.6 0 0.0 151 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Total 11,619 98.4 125 1.1 66 0.6 0 0.0 11,809 100.0 Maize 112,718 97.7 295 0.3 2,349 2.0 0 0.0 115,361 100.0 Paddy 4,473 91.4 261 5.3 160 3.3 0 0.0 4,894 100.0 Sorghum & Millet 93,801 97.3 774 0.8 1,799 1.9 0 0.0 96,374 100.0 Beans & Pulses 10,174 64.5 234 1.5 5,357 34.0 0 0.0 15,765 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 167 100.0 0 0.0 0 0.0 0 0.0 167 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 79 100.0 79 100.0 Groundnuts/ Bambara Nuts 3,956 59.3 139 2.1 2,574 38.6 0 0.0 6,669 100.0 Total 225,374 94.1 1,704 0.7 12,239 5.1 79 0.0 239,395 100.0 Total Singida Urban Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 192 No. of Households % No. of Households % No. of Households % Maize 43,397 81.5 9,858 18.5 53,255 100.0 Paddy 143 0.3 52,971 99.7 53,114 100.0 Sorghum & Millet 26,619 50.1 26,496 49.9 53,114 100.0 Beans & Pulses 7,810 14.7 45,304 85.3 53,114 100.0 Wheat 0 0.0 53,114 100.0 53,114 100.0 Coffee 0 0.0 53,114 100.0 53,114 100.0 Cashewnut 0 0.0 53,114 100.0 53,114 100.0 Tobacco 0 0.0 53,114 100.0 53,114 100.0 Cottton 0 0.0 53,114 100.0 53,114 100.0 Groundnuts/Ba mbara Nuts 1,979 3.7 51,135 96.3 53,114 100.0 Total 79,949 15.0 451,336 85.0 531,284 100.0 Maize 45,140 64.9 24,455 35.1 69,595 100.0 Paddy 1,810 2.6 67,785 97.4 69,595 100.0 Sorghum & Millet 51,198 73.6 18,397 26.4 69,595 100.0 Beans & Pulses 1,712 2.5 67,883 97.5 69,595 100.0 Wheat 0 0.0 69,595 100.0 69,595 100.0 Coffee 0 0.0 69,595 100.0 69,595 100.0 Cashewnut 125 0.2 69,470 99.8 69,595 100.0 Tobacco 0 0.0 69,595 100.0 69,595 100.0 Cottton 0 0.0 69,595 100.0 69,595 100.0 Groundnuts/Ba mbara Nuts 0 0.0 69,595 100.0 69,595 100.0 Total 99,985 14.4 595,964 85.6 695,950 100.0 Maize 24,294 80.1 6,053 19.9 30,347 100.0 Paddy 2,856 9.4 27,492 90.6 30,347 100.0 Sorghum & Millet 9,598 31.6 20,749 68.4 30,347 100.0 Beans & Pulses 6,092 20.1 24,255 79.9 30,347 100.0 Wheat 85 0.3 30,262 99.7 30,347 100.0 Coffee 0 0.0 30,347 100.0 30,347 100.0 Cashewnut 0 0.0 30,347 100.0 30,347 100.0 Tobacco 0 0.0 30,347 100.0 30,347 100.0 Cottton 79 0.3 30,268 99.7 30,347 100.0 Groundnuts/Ba mbara Nuts 4,648 15.3 25,699 84.7 30,347 100.0 Total 47,652 15.7 255,820 84.3 303,473 100.0 9.0c CROP STORAGE: Number of Households Storing Crops By Type of Crop Crop Households Storing Crop g Crop Total Iramba Singida Rural Manyoni Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 193 No. of Households % No. of Households % No. of Households % 9.0c CROP STORAGE: Number of Households Storing Crops By Type of Crop Crop Households Storing Crop g Crop Total Maize 2,530 26.1 7,148 73.9 9,678 100.0 Paddy 85 0.9 9,593 99.1 9,678 100.0 Sorghum & Millet 8,959 92.6 719 7.4 9,678 100.0 Beans & Pulses 151 1.6 9,527 98.4 9,678 100.0 Wheat 0 0.0 9,678 100.0 9,678 100.0 Coffee 0 0.0 9,678 100.0 9,678 100.0 Cashewnut 42 0.4 9,636 99.6 9,678 100.0 Tobacco 0 0.0 9,678 100.0 9,678 100.0 Cottton 0 0.0 9,678 100.0 9,678 100.0 Groundnuts/Ba mbara Nuts 42 0.4 9,636 99.6 9,678 100.0 Total 11,809 12.2 84,972 87.8 96,781 100.0 Maize 115,361 70.8 47,515 29.2 162,876 100.0 Paddy 4,894 3.0 157,841 97.0 162,735 100.0 Sorghum & Millet 96,374 59.2 66,361 40.8 162,735 100.0 Beans & Pulses 15,765 9.7 146,969 90.3 162,735 100.0 Wheat 85 0.1 162,650 99.9 162,735 100.0 Coffee 0 0.0 162,735 100.0 162,735 100.0 Cashewnut 167 0.1 162,567 99.9 162,735 100.0 Tobacco 0 0.0 162,735 100.0 162,735 100.0 Cottton 79 0.0 162,655 100.0 162,735 100.0 Groundnuts/Ba mbara Nuts 6,669 4.1 156,065 95.9 162,735 100.0 Total 239,395 14.7 1,388,092 85.3 1,627,487 100.0 Total Singida Urban Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 194 Number of Households Quantity stored (tons) Maize 43,397 1,323 Paddy 143 0 Sorghum & Millet 26,619 535 Beans & Pulses 7,810 11 Groundnuts/Bambara Nuts 1,979 25 Total 79,949 1,895 Maize 45,140 4,275 Paddy 1,810 261 Sorghum & Millet 51,198 3,965 Beans & Pulses 1,712 34 Cashewnut 125 0 Total 99,985 8,535 Maize 24,294 2,762 Paddy 2,856 126 Sorghum & Millet 9,598 804 Beans & Pulses 6,092 186 Wheat 85 0 Cottton 79 2 Groundnuts/Bambara Nuts 4,648 94 Total 47,652 3,974 Maize 2,530 6 Paddy 85 0 Sorghum & Millet 8,959 109 Beans & Pulses 151 0 Cashewnut 42 0 Groundnuts/Bambara Nuts 42 0 Total 11,809 115 Maize 115,361 8,366 Paddy 4,894 387 Sorghum & Millet 96,374 5,413 Beans & Pulses 15,765 230 Wheat 85 0 Cashewnut 167 0 Cottton 79 2 Groundnuts/Bambara Nuts 6,669 119 Total 239,395 14,518 Manyoni Singida Urban Total 9.1 CROP STORAGE: Number of Households and Current Quantity Stored (tons) by Crop Type and District District/Crop Type Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 195 Less than 3 Months Between 3 and 6 Months Over 6 Months Total Maize 13,364 21,648 8,386 43,397 Paddy 143 0 0 143 Sorghum & Millet 9,019 13,228 4,372 26,619 Beans & Pulses 2,835 4,403 572 7,810 Groundnuts/B ambara Nuts 420 1,559 0 1,979 Total 25,781 40,838 13,330 79,949 Maize 19,148 19,080 6,912 45,140 Paddy 122 368 1,321 1,810 Sorghum & Millet 20,790 21,663 8,745 51,198 Beans & Pulses 491 610 611 1,712 Cashewnut 125 0 0 125 Total 40,676 41,721 17,589 99,985 Maize 6,424 11,664 6,205 24,294 Paddy 1,168 1,226 462 2,856 Sorghum & Millet 4,424 3,877 1,297 9,598 Beans & Pulses 959 3,283 1,851 6,092 Wheat 85 0 0 85 Cottton 0 0 79 79 Groundnuts/B ambara Nuts 1,129 2,106 1,413 4,648 Total 14,188 22,156 11,308 47,652 Maize 1,481 964 85 2,530 Paddy 0 85 0 85 Sorghum & Millet 3,893 4,273 793 8,959 Beans & Pulses 43 33 75 151 Cashewnut 42 0 0 42 Groundnuts/B ambara Nuts 0 0 42 42 Total 5,458 5,355 995 11,809 Maize 40,417 53,356 21,588 115,361 Paddy 1,433 1,679 1,782 4,894 Sorghum & Millet 38,125 43,041 15,207 96,374 Beans & Pulses 4,328 8,329 3,109 15,765 Wheat 85 0 0 85 Cashewnut 167 0 0 167 Cottton 0 0 79 79 Groundnuts/B ambara Nuts 1,549 3,665 1,456 6,669 Total 86,104 110,070 43,221 239,395 Manyoni Singida Urban Total 9.2 CROP STORAGE: Number of Households that Stored Crops By Length of Storage and Crop Type Crop Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 196 In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotecte d Pile Other Total Iramba 36,688 255 0 15,885 0 0 284 53,113 Singida Rural 50,339 498 123 18,019 123 0 245 69,347 Manyoni 14,642 81 170 14,959 0 85 326 30,263 Singida Urban 3,350 338 0 5,491 414 0 85 9,678 Total 105,019 1,172 293 54,354 537 85 940 162,401 Less than 3 Months Between 3 and 6 Months Over 6 Months Total Iramba 16,833 27,120 9,160 53,113 Singida Rural 30,076 28,738 10,534 69,347 Manyoni 9,602 13,883 6,778 30,263 Singida Urban 4,499 4,504 676 9,678 Total 61,009 74,245 27,147 162,401 Food for the Household To Sell for Higher Price Seeds for Planting Other Total Iramba 52,400 0 712 0 53,113 Singida Rural 67,264 122 1,962 0 69,347 Manyoni 29,144 337 782 0 30,263 Singida Urban 9,553 125 0 0 9,678 Total 158,362 583 3,456 0 162,401 Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba 43,004 3,882 5,694 533 53,113 Singida Rural 59,629 7,027 2,199 492 69,347 Manyoni 28,109 1,425 479 250 30,263 Singida Urban 9,096 497 85 0 9,678 Total 139,838 12,830 8,457 1,275 162,401 9.3 CROP STORAGE: Number of Households Storing Crops By Method of Storage and District District Method of Storage 9.2 CROP STORAGE: Number of Households Storing 9.2 CROP STORAGE: Number of Households Storing Crops By District Estimate Storage Loss District Normal Duration of Storage 9.2 CROP STORAGE: Number of Households Storing Crops By Main District Main Purpose Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 197 MARKETING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 198 Number % Number % Number % Iramba 24,877 39.8 37,652 60.2 62,528 100.0 Singida Rural 36,760 50.2 36,437 49.8 73,197 100.0 Manyoni 17,251 52.2 15,814 47.8 33,065 100.0 Singida Urban 2,833 25.5 8,292 74.5 11,125 100.0 Total 81,720 45.4 98,195 54.6 179,915 100.0 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Iramba 137 35,741 0 0 138 287 0 1,136 25,090 62,528 Singida Rural 855 40,008 250 124 125 123 125 372 30,492 72,472 Manyoni 82 17,467 0 0 0 0 0 150 14,875 32,575 Singida Urban 170 7,938 42 0 0 43 0 439 2,409 11,041 Total 1,243 101,154 292 124 263 452 125 2,097 72,866 178,616 District Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Iramba 0.22 57.16 0.00 0.00 0.22 0.46 0.00 1.82 40.13 100.00 Singida Rural 1.18 55.20 0.35 0.17 0.17 0.17 0.17 0.51 42.07 100.00 Manyoni 0.25 53.62 0.00 0.00 0.00 0.00 0.00 0.46 45.66 100.00 Singida Urban 1.54 71.90 0.38 0.00 0.00 0.39 0.00 3.97 21.82 100.00 Total 0.70 56.63 0.16 0.07 0.15 0.25 0.07 1.17 40.79 100.00 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District Households that Sold Households that Did not Sell Total Number of Households 10.3 Proportion of Household who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year District Main Reasons for Not Selling Crops 10.2: Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 199 IRRIGATION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 200 Total Number of Household % Number of Household % Number of Household Iramba 426 0.7 62,102 99.3 62,528 Singida Rural 1,338 1.8 71,859 98.2 73,197 Manyoni 3,682 11.1 29,383 88.9 33,065 Singida Urban 933 8.4 10,192 91.6 11,125 Total 6,380 3.5 173,536 96.5 179,915 District Irrigated Area (ha) Irrigated Land (ha) % Iramba 230 46 20 Singida Rural 942 520 55 Manyoni 2,244 1,285 57 Singida Urban 167 167 100 Total 3,583 2,017 56 River Dam Well Canal Total Iramba 141 143 143 0 426 Singida Rural 0 370 720 249 1,338 Manyoni 76 0 322 3,283 3,682 Singida Urban 43 42 680 169 933 Total 259 555 1,865 3,701 6,380 % 4 9 29 58 100 Gravity Hand Bucket Motor Pump Total Iramba 0 283 143 426 Singida Rural 491 847 0 1,338 Manyoni 3,359 322 0 3,682 Singida Urban 127 806 0 933 Total 3,977 2,259 143 6,380 % 62 35 2 100 Flood Bucket / Watering Can Total Iramba 0 426 426 Singida Rural 1,091 247 1,338 Manyoni 3,359 322 3,682 Singida Urban 85 849 933 Total 4,534 1,845 6,380 % 71 29 100 District Households Practicing Irrigation Households not Practicing Irrigation 11.1.Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water 11.2 IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water District Method of Application 11.5: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 201 Total Number % Number % Number Iramba 6,294 10 56,234 90 62,528 Singida Rural 8,080 11 65,117 89 73,197 Manyoni 488 1 32,577 99 33,065 Singida Urban 667 6 10,458 94 11,125 Total 15,529 9 164,386 91 179,915 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Iramba 0 53,203 0 3,088 21,226 3,857 562 0 81,937 Singida Rural 8,497 46,270 . 862 736 26,956 3,685 . 87,004 Manyoni 792 7,898 . . . 820 . . 9,510 Singida Urban . 4,904 . . . 406 254 . 5,564 Total 9,289 112,275 0 3,950 21,962 32,039 4,500 0 184,015 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District District Have facility Does Not Have Facility Does the Household Have Any Erosion Control/Water Tanzania Agriculture Census Survey 2003 Singida Region 202 Appendix II 203 ACCESS TO FARM INPUTS/ IMPLEMENTS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 204 Number % Number % Number % Iramba 287 0 62,242 100 62,528 100 Singida Rural 123 0 73,074 100 73,197 100 Manyoni 2,208 7 30,857 93 33,065 100 Singida Urban 41 0 11,125 100 11,167 100 Total 2,659 1 177,298 99 179,957 100 Number % Number % Number % Iramba 36,163 58 26,365 42 62,528 100 Singida Rural 34,198 47 39,124 53 73,322 100 Manyoni 6,641 20 26,424 80 33,065 100 Singida Urban 6,257 56 4,827 44 11,084 100 Total 83,259 46 96,740 54 179,999 100 Number % Number % Number % Iramba 2,845 5 59,683 95 62,528 100 Singida Rural 3,471 5 69,726 95 73,197 100 Manyoni 660 2 32,404 98 33,065 100 Singida Urban 810 7 10,316 93 11,125 100 Total 7,786 4 172,129 96 179,915 100 Number % Number % Number % Iramba 3,155 5 59,373 95 62,528 100 Singida Rural 958 1 72,239 99 73,197 100 Manyoni 2,372 7 30,693 93 33,065 100 Singida Urban 427 4 10,699 96 11,125 100 Total 6,912 4 173,003 96 179,915 100 Number % Number % Number % Iramba 0 0 62,528 100 62,528 100 Singida Rural 117 0 73,080 100 73,197 100 Manyoni 0 0 33,065 100 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 117 0 179,799 100 179,915 100 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 205 Number % Number % Number % Iramba 5,295 8 57,233 92 62,528 100 Singida Rural 8,740 12 64,332 88 73,072 100 Manyoni 10,901 33 22,164 67 33,065 100 Singida Urban 1,479 13 9,647 87 11,125 100 Total 26,415 15 153,375 85 179,790 100 Number % Number % Number % Number % Number % Iramba 0 0 287 0 0 0 62,242 100 62,528 100 Singida Rural 0 0 123 0 0 0 73,074 100 73,197 100 Manyoni 1,421 4 74 0 712 2 30,857 93 33,065 100 Singida Urban 0 0 0 0 41 0 11,125 100 11,167 100 Total 1,421 1 484 0 754 0 177,298 99 179,957 100 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Neighbour Not applicable Total 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural Households Using Improved Seeds Number of Agricultural Households NOT Using Improved Seeds Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 206 Number % Number % Number % Number % Number % Number % Iramba 704 1 144 0 133 0 0 0 0 0 577 1 Singida Rural 0 0 0 0 0 0 370 1 122 0 0 0 Manyoni 0 0 0 0 0 0 0 0 0 0 0 0 Singida Urban 0 0 0 0 0 0 0 0 0 0 0 0 Total 704 0 144 0 133 0 370 0 122 0 577 0 Number % Number % Number % Number % Number % Number % Iramba 1,438 2 20,457 33 12,423 20 287 0 26,365 42 62,528 100 Singida Rural 0 0 28,669 39 5,036 7 0 0 39,124 53 73,322 100 Manyoni 0 0 2,810 8 3,831 12 0 0 26,424 80 33,065 100 Singida Urban 0 0 4,642 42 1,615 15 0 0 4,827 44 11,084 100 Total 1,438 1 56,578 31 22,905 13 287 0 96,740 54 179,999 100 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Neighbour Other Not applicable Total District Co-operative Local Farmers Group Secondary Market Development Project Crop Buyers District cont…. ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Large Scale Farm Locally Produced by Household Local Market / Trade Store Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 207 Number % Number % Number % Number % Number % Iramba 133 0 0 0 0 0 144 0 2,425 4 Singida Rural 642 1 103 0 207 0 0 0 2,396 3 Manyoni 0 0 0 0 0 0 79 0 581 2 Singida Urban 0 0 0 0 0 0 43 0 767 7 Total 775 0 103 0 207 0 266 0 6,170 3 Number % Number % Number % Iramba 143 0 59,683 95 62,528 100 Singida Rural 122 0 69,726 95 73,197 100 Manyoni 0 0 32,404 98 33,065 100 Singida Urban 0 0 10,316 93 11,125 100 Total 265 0 172,129 96 179,915 100 Number % Number % Number % Number % Number % Iramba 0 0 124 0 1,498 2 143 0 0 0 Singida Rural 0 0 0 0 958 1 0 0 0 0 Manyoni 1,278 4 0 0 787 2 0 0 65 0 Singida Urban 0 0 0 0 427 4 0 0 0 0 Total 1,278 1 124 0 3,670 2 143 0 65 0 Number % Number % Number % Number % Number % Iramba 0 0 684 1 706 1 59,373 95 62,528 100 Singida Rural 0 0 0 0 0 0 72,239 99 73,197 100 Manyoni 82 0 160 0 0 0 30,693 93 33,065 100 Singida Urban 0 0 0 0 0 0 10,699 96 11,125 100 Total 82 0 844 0 706 0 173,003 96 179,915 100 Number % Number % Number % Iramba 0 0 62,528 100 62,528 100 Singida Rural 117 0 73,080 100 73,197 100 Manyoni 0 0 33,065 100 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 117 0 179,799 100 179,915 100 District Co-operative Local Farmers Group Local Market / Trade Store Large Scale Farm Locally Produced by Household Neighbour Not applicable Total District Neighbour Not applicable Total 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District 2002/03 Agricultural Year 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Other Not applicable Total District Co-operative Local Farmers Group Development Project Crop Buyers Neighbour District Local Market / Trade Store District cont... ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Secondary Market Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 208 Number % Number % Number % Number % Number % Number % Iramba 143 0 0 0 3,736 6 143 0 0 0 0 0 Singida Rural 0 0 0 0 4,593 6 125 0 125 0 0 0 Manyoni 798 2 0 0 5,397 16 0 0 477 1 419 1 Singida Urban 0 0 33 0 1,063 10 0 0 0 0 0 0 Total 941 1 33 0 14,790 8 268 0 602 0 419 0 Number % Number % Number % Number % Number % Number % Iramba 0 0 143 0 1,131 2 0 0 57,233 92 62,528 100 Singida Rural 248 0 2,178 3 1,471 2 0 0 64,332 88 73,072 100 Manyoni 0 0 83 0 3,561 11 165 0 22,164 67 33,065 100 Singida Urban 0 0 255 2 128 1 0 0 9,647 87 11,125 100 Total 248 0 2,658 1 6,291 3 165 0 153,375 85 179,790 100 Number % Number % Number % Number % Number % Number % Iramba 0 0 143 50 143 50 0 0 0 0 287 100 Singida Rural 0 0 0 0 0 0 123 100 0 0 123 100 Manyoni 1,899 86 82 4 0 0 145 7 82 4 2,208 100 Singida Urban 41 100 0 0 0 0 0 0 0 0 41 100 Total 1,940 73 225 8 143 5 268 10 82 3 2,659 100 Number % Number % Number % Number % Number % Iramba 31,603 87 4,292 12 124 0 144 0 36,163 100 Singida Rural 32,477 95 1,104 3 0 0 618 2 34,198 100 Manyoni 5,594 84 804 12 243 4 0 0 6,641 100 Singida Urban 6,090 97 167 3 0 0 0 0 6,257 100 Total 75,763 91 6,367 8 367 0 762 1 83,259 100 District 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Neighbour Other Not applicable Total District Co-operative District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Crop Buyers Large Scale Farm Locally Produced by Household Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 209 Number % Number % Number % Number % Iramba 2,559 90 287 10 0 0 2,845 100 Singida Rural 2,997 86 228 7 245 7 3,471 100 Manyoni 660 100 0 0 0 0 660 100 Singida Urban 810 100 0 0 0 0 810 100 Total 7,026 90 515 7 245 3 7,786 100 Number % Number % Number % Number % Number % Number % Iramba 1,360 43 371 12 1,143 36 139 4 143 5 3,155 100 Singida Rural 0 0 0 0 249 26 243 25 466 49 958 100 Manyoni 1,503 63 82 3 622 26 165 7 0 0 2,372 100 Singida Urban 0 0 0 0 384 90 43 10 0 0 427 100 Total 2,863 41 453 7 2,398 35 590 9 608 9 6,912 100 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Number % Iramba 2,098 40 562 11 1,857 35 265 5 514 10 5,295 100 Singida Rural 3,523 40 861 10 1,114 13 738 8 2,503 29 8,740 100 Manyoni 6,031 55 1,184 11 1,516 14 1,147 11 1,024 9 10,901 100 Singida Urban 425 29 0 0 553 37 415 28 85 6 1,479 100 Total 12,076 46 2,607 10 5,041 19 2,566 10 4,126 16 26,415 100 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 10 and 20 km Total 12.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Yea District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Between 1 and 3 km Total 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 210 Number % Number % Number % Number % Iramba 287 100 0 0 0 0 287 100 Singida Rural 123 100 0 0 0 0 123 100 Manyoni 630 29 623 28 955 43 2,208 100 Singida Urban 41 100 0 0 0 0 41 100 Total 1,081 41 623 23 955 36 2,659 100 Number % Number % Number % Number % Number % Number % Number % Iramba 23,815 66 4,247 12 1,820 5 289 1 1,577 4 4,415 12 36,163 100 Singida Rural 22,627 66 3,580 10 862 3 0 0 0 0 7,128 21 34,198 100 Manyoni 3,887 59 1,774 27 326 5 74 1 0 0 580 9 6,641 100 Singida Urban 3,931 63 1,142 18 210 3 0 0 0 0 975 16 6,257 100 Total 54,260 65 10,742 13 3,219 4 363 0 1,577 2 13,099 16 83,259 100 Number % Number % Number % Number % Iramba 2,416 85 287 10 143 5 2,845 100 Singida Rural 2,500 72 476 14 495 14 3,471 100 Manyoni 497 75 85 13 78 12 660 100 Singida Urban 429 53 127 16 254 31 810 100 Total 5,842 75 975 13 969 12 7,786 100 Number % Number % Number % Number % Number % Iramba 1,788 57 943 30 143 5 282 9 3,155 100 Singida Rural 958 100 0 0 0 0 0 0 958 100 Manyoni 797 34 542 23 158 7 874 37 2,372 100 Singida Urban 384 90 43 10 0 0 0 0 427 100 Total 3,927 57 1,528 22 301 4 1,156 17 6,912 100 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Other Total 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Bank Loan Produced on form Other Total 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 211 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Iramba 3,754 71 1,541 29 0 0 0 0 5,295 100 Singida Rural 5,239 60 2,433 28 703 8 365 4 8,740 100 Manyoni 2,665 24 7,262 67 414 4 560 5 10,901 100 Singida Urban 546 37 763 52 42 3 127 9 1,479 100 Total 12,204 46 11,999 45 1,160 4 1,052 4 26,415 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 19,319 31 33,214 53 1,738 3 0 0 1,269 2 5,997 10 705 1 62,242 100 Singida Rural 25,679 35 28,673 39 730 1 0 0 4,176 6 12,964 18 852 1 73,074 100 Manyoni 16,193 52 12,025 39 254 1 83 0 798 3 1,420 5 85 0 30,857 100 Singida Urban 1,856 17 6,210 56 296 3 0 0 550 5 2,171 20 42 0 11,125 100 Total 63,046 36 80,121 45 3,019 2 83 0 6,794 4 22,551 13 1,685 1 177,298 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 7,261 28 6,375 24 3,133 12 1,285 5 1,031 4 5,715 22 1,564 6 26,365 100 Singida Rural 18,314 47 6,389 16 6,984 18 2,158 6 248 1 2,951 8 2,080 5 39,124 100 Manyoni 10,264 39 1,324 5 10,451 40 2,349 9 819 3 918 3 300 1 26,424 100 Singida Urban 3,769 78 486 10 286 6 0 0 41 1 117 2 127 3 4,827 100 Total 39,608 41 14,574 15 20,854 22 5,792 6 2,140 2 9,701 10 4,071 4 96,740 100 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year District Sale of Farm Products Total 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 212 Number % Number % Number % Number % Number % Number % Number % Number % Number % Iramba 9,052 15 8,443 14 12,785 21 3,998 7 17,711 30 6,707 11 136 0 851 1 59,683 100 Singida Rural 7,594 11 8,041 12 25,178 36 3,224 5 19,576 28 4,907 7 115 0 1,090 2 69,726 100 Manyoni 728 2 919 3 12,020 37 1,043 3 15,438 48 1,156 4 932 3 170 1 32,404 100 Singida Urban 2,720 26 991 10 3,169 31 127 1 2,122 21 686 7 0 0 500 5 10,316 100 Total 20,094 12 18,394 11 53,152 31 8,392 5 54,847 32 13,456 8 1,183 1 2,611 2 172,129 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Iramba 6,239 11 44,350 75 566 1 415 1 1,846 3 5,394 9 141 0 421 1 59,373 100 Singida Rural 13,391 19 39,415 55 728 1 123 0 12,172 17 5,687 8 0 0 722 1 72,239 100 Manyoni 9,365 31 16,748 55 415 1 165 1 3,440 11 474 2 0 0 85 0 30,693 100 Singida Urban 254 2 7,310 68 254 2 42 0 548 5 2,162 20 0 0 127 1 10,699 100 Total 29,250 17 107,824 62 1,964 1 746 0 18,007 10 13,717 8 141 0 1,355 1 173,003 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 11,470 18 36,390 58 1,232 2 143 0 2,270 4 10,881 17 143 0 62,528 100 Singida Rural 15,239 21 30,457 42 619 1 372 1 13,284 18 12,387 17 722 1 73,080 100 Manyoni 11,766 36 12,440 38 415 1 165 0 6,763 20 1,430 4 85 0 33,065 100 Singida Urban 338 3 5,474 49 424 4 42 0 486 4 4,192 38 170 2 11,125 100 Total 38,814 22 84,762 47 2,689 1 722 0 22,804 13 28,889 16 1,119 1 179,799 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 2,487 4 51,275 90 691 1 276 0 1,520 3 143 0 841 1 57,233 100 Singida Rural 17,733 28 43,047 67 614 1 990 2 985 2 240 0 722 1 64,332 100 Manyoni 5,304 24 15,708 71 167 1 570 3 164 1 82 0 168 1 22,164 100 Singida Urban 762 8 8,248 86 169 2 85 1 127 1 0 0 255 3 9,647 100 Total 26,287 17 118,278 77 1,641 1 1,921 1 2,797 2 465 0 1,987 1 153,375 100 Other Total Other Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Do not Know How to Use Other Input is of No Use Locally Produced by Household Other 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Total Do not Know How to Use Input is of No Use Input is of No Use Locally Produced by Household 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Total Locally Produced by Household Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 213 Number % Number % Number % Number % Iramba 143 50 143 50 0 0 287 100 Singida Rural 123 100 0 0 0 0 123 100 Manyoni 317 14 1,572 71 319 14 2,208 100 Singida Urban 0 0 41 100 0 0 41 100 Total 584 22 1,756 66 319 12 2,659 100 Number % Number % Number % Number % Number % Iramba 11,722 32 23,063 64 1,377 4 0 0 36,163 100 Singida Rural 19,497 57 13,884 41 817 2 0 0 34,198 100 Manyoni 2,697 41 3,777 57 84 1 83 1 6,641 100 Singida Urban 2,090 33 3,702 59 466 7 0 0 6,257 100 Total 36,006 43 44,426 53 2,744 3 83 0 83,259 100 Number % Number % Number % Number % Iramba 855 30 1,848 65 143 5 2,845 100 Singida Rural 1,672 48 1,678 48 121 3 3,471 100 Manyoni 0 0 236 36 424 64 660 100 Singida Urban 42 5 533 66 235 29 810 100 Total 2,569 33 4,295 55 923 12 7,786 100 Number % Number % Number % Number % Number % Iramba 571 18 1,909 61 390 12 285 9 3,155 100 Singida Rural 351 37 358 37 0 0 249 26 958 100 Manyoni 648 27 1,580 67 144 6 0 0 2,372 100 Singida Urban 117 27 277 65 33 8 0 0 427 100 Total 1,687 24 4,124 60 567 8 534 8 6,912 100 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 214 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Iramba 713 13 4,191 79 392 7 0 0 5,295 100 Singida Rural 3,841 44 4,419 51 480 5 0 0 8,740 100 Manyoni 2,829 26 7,492 69 496 5 84 1 10,901 100 Singida Urban 532 36 787 53 160 11 0 0 1,479 100 Total 7,914 30 16,889 64 1,528 6 84 0 26,415 100 Number % Number % Number % Iramba 1,961 3 60,567 97 62,528 100 Singida Rural 2,568 4 70,629 96 73,197 100 Manyoni 2,551 8 30,514 92 33,065 100 Singida Urban 0 0 11,167 100 11,167 100 Total 7,080 4 172,877 96 179,957 100 Number % Number % Number % Iramba 41,568 66 20,961 34 62,528 100 Singida Rural 49,814 68 23,507 32 73,322 100 Manyoni 14,922 45 18,143 55 33,065 100 Singida Urban 7,096 64 3,988 36 11,084 100 Total 113,400 63 66,599 37 179,999 100 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Farm Yard Manure Number of Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Chemical Fertilizers Number of Agricultural Households With NO Plan to use Next Year Chemica Fertilizers Total 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Good Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 215 Number % Number % Number % Iramba 5,406 9 57,123 91 62,528 100 Singida Rural 12,973 18 60,224 82 73,197 100 Manyoni 4,156 13 28,909 87 33,065 100 Singida Urban 961 9 10,165 91 11,125 100 Total 23,495 13 156,421 87 179,915 100 Number % Number % Number % Iramba 11,331 18 51,197 82 62,528 100 Singida Rural 16,046 22 57,151 78 73,197 100 Manyoni 7,329 22 25,736 78 33,065 100 Singida Urban 554 5 10,572 95 11,125 100 Total 35,260 20 144,655 80 179,915 100 Number % Number % Number % Iramba 2,248 4 60,280 96 62,528 100 Singida Rural 1,596 2 71,601 98 73,197 100 Manyoni 322 1 32,742 99 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 4,166 2 175,749 98 179,915 100 Number % Number % Number % Iramba 17,805 28 44,723 72 62,528 100 Singida Rural 30,914 42 42,158 58 73,072 100 Manyoni 16,732 51 16,333 49 33,065 100 Singida Urban 2,605 23 8,520 77 11,125 100 Total 68,057 38 111,734 62 179,790 100 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year COMPOST Manure Number of Agricultural Households With NO Plan to use Next Year COMPOST Manure Total 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides Number of Agricultural Households With NO Plan to use Next Year Pesticides/Fungicides Total 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Herbicides Number of Agricultural Households With NO Plan to use Next Year Herbicides Total 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Improved Seeds Number of Agricultural Households With NO Plan to use Next Year Improved Seeds Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 216 Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Iramba 203,512 4,441 3,961 1,950 103,723 109,170 27,669 29,955 423 141 Singida Rural 237,999 1,107 935 1,221 79,536 36,492 23,670 11,415 123 0 Manyoni 110,816 499 5,302 242 17,955 4,744 5,180 1,704 0 84 Singida Urban 35,192 333 308 33 2,648 1,031 1,047 581 0 0 Total 587,519 6,380 10,506 3,445 203,863 151,437 57,565 43,654 546 225 Owned Rented Owned Rented Owned Rented Owned Rented Owned Rented Owned Rented Iramba 4,906 3,745 138 412 0 829 0 0 0 0 344,332 150,643 Singida Rural 3,498 2,647 0 0 0 0 245 0 0 0 346,007 52,882 Manyoni 905 85 0 0 0 0 0 85 0 79 140,158 7,522 Singida Urban 338 338 0 0 0 0 0 0 0 0 39,533 2,316 Total 9,647 6,815 138 412 0 829 245 85 0 79 870,029 213,363 Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Iramba 61,826 2,303 52,565 48,948 421 7,703 406 545 0 0 Singida Rural 72,712 1,677 33,048 31,468 123 6,023 0 0 123 0 Manyoni 33,065 2,158 4,154 4,070 84 823 0 0 85 79 Singida Urban 11,125 341 1,173 1,331 0 371 0 0 0 0 Total 178,728 6,479 90,940 85,816 628 14,919 406 545 208 79 Total District Hand Hoe Hand Powered Sprayer Oxen 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Implement / Asset Name cont…. ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Implement / Asset Name Ox Plough Ox Seed Planter 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 District Implement / Asset Name Tractor Plough Tractor Harrow Threshers / Shellers District Ox Cart Tractor Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 217 Number % Number % Number % Number % Number % Iramba 137 19 0 0 565 81 0 0 702 100 Singida Rural 0 0 240 66 0 0 123 34 363 100 Total 137 13 240 23 565 53 123 12 1,065 100 Number % Number % Number % Number % Number % Number % Number % Iramba 3,195 5 26,951 45 22,333 37 143 0 6,747 11 857 1 60,225 100 Singida Rural 18,796 26 33,870 47 11,584 16 0 0 7,144 10 125 0 71,519 100 Manyoni 5,910 19 17,205 56 7,306 24 0 0 486 2 0 0 30,907 100 Singida Urban 1,357 13 3,696 34 2,364 22 0 0 3,368 31 0 0 10,785 100 Total 29,258 17 81,722 47 43,587 25 143 0 17,744 10 982 1 173,436 100 Number % Number % Number % Number % Number % Number % Number % Iramba 137 1 3,375 34 6,311 63 0 0 0 0 141 1 9,964 100 Singida Rural 1,345 3 12,571 31 25,372 63 124 0 247 1 489 1 40,148 100 Manyoni 954 3 5,394 19 22,349 77 139 0 0 0 74 0 28,911 100 Singida Urban 212 2 2,701 27 6,678 67 118 1 159 2 43 0 9,910 100 Total 2,648 3 24,041 27 60,711 68 381 0 406 0 747 1 88,933 100 Number % Number % Number % Number % Number % Number % Number % Iramba 428 3 4,158 31 7,595 56 133 1 1,124 8 143 1 13,581 100 Singida Rural 980 2 16,610 40 23,645 57 0 0 247 1 246 1 41,729 100 Manyoni 415 1 5,513 19 22,204 77 502 2 288 1 74 0 28,995 100 Singida Urban 329 3 2,324 24 6,813 70 43 0 244 2 43 0 9,794 100 Total 2,151 2 28,605 30 60,257 64 678 1 1,903 2 506 1 94,099 100 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Equipment / Asset of No Use Total 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 218 Number % Number % Number % Number % Number % Number % Number % Iramba 9,715 16 24,990 40 18,698 30 143 0 7,852 13 709 1 62,108 100 Singida Rural 25,626 35 27,702 38 12,886 18 0 0 6,364 9 496 1 73,074 100 Manyoni 3,489 11 12,911 39 16,154 49 0 0 428 1 0 0 32,981 100 Singida Urban 594 5 2,721 24 3,816 34 0 0 3,909 35 85 1 11,125 100 Total 39,423 22 68,324 38 51,554 29 143 0 18,553 10 1,290 1 179,287 100 Number % Number % Number % Number % Number % Number % Number % Iramba 573 1 21,184 39 28,529 52 143 0 4,111 7 286 1 54,825 100 Singida Rural 3,442 5 32,671 49 29,096 43 123 0 1,596 2 246 0 67,174 100 Manyoni 905 3 10,990 34 19,771 61 139 0 437 1 0 0 32,242 100 Singida Urban 211 2 3,662 34 5,128 48 0 0 1,583 15 170 2 10,754 100 Total 5,131 3 68,507 42 82,524 50 405 0 7,727 5 702 0 164,996 100 Number % Number % Number % Number % Number % Number % Number % Iramba 812 1 27,141 44 31,631 51 284 0 2,256 4 0 0 62,123 100 Singida Rural 9,849 13 44,463 61 12,033 16 0 0 6,852 9 0 0 73,197 100 Manyoni 1,130 3 22,317 67 9,321 28 0 0 297 1 0 0 33,065 100 Singida Urban 1,635 15 4,115 37 2,406 22 0 0 2,928 26 43 0 11,125 100 Total 13,425 7 98,035 55 55,391 31 284 0 12,333 7 43 0 179,510 100 Number % Number % Number % Number % Number % Number % Number % Iramba 953 2 26,973 44 31,374 51 143 0 2,541 4 0 0 61,983 100 Singida Rural 9,971 14 44,222 60 12,278 17 0 0 6,726 9 0 0 73,197 100 Manyoni 1,284 4 23,365 71 7,403 22 0 0 1,013 3 0 0 33,065 100 Singida Urban 1,593 14 4,196 38 2,407 22 0 0 2,886 26 43 0 11,125 100 Total 13,801 8 98,756 55 53,462 30 143 0 13,165 7 43 0 179,370 100 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 219 Number % Number % Number % Number % Number % Number % Number % Iramba 4,796 8 26,299 42 23,350 37 143 0 7,940 13 0 0 62,528 100 Singida Rural 10,212 14 43,838 60 11,797 16 0 0 7,232 10 118 0 73,197 100 Manyoni 1,363 4 23,054 70 7,465 23 159 0 938 3 0 0 32,980 100 Singida Urban 1,592 14 4,112 37 2,407 22 0 0 2,971 27 43 0 11,125 100 Total 17,964 10 97,303 54 45,019 25 302 0 19,082 11 160 0 179,830 100 Number % Number % Number % Number % Number % Number % Number % Iramba 8,867 14 24,883 40 17,048 27 143 0 11,444 18 143 0 62,528 100 Singida Rural 11,677 16 40,756 56 10,557 14 0 0 10,082 14 125 0 73,197 100 Manyoni 1,299 4 23,619 72 7,287 22 223 1 479 1 79 0 32,986 100 Singida Urban 380 3 2,973 27 2,084 19 0 0 5,604 50 85 1 11,125 100 Total 22,223 12 92,231 51 36,976 21 366 0 27,609 15 432 0 179,836 100 Number % Number % Number % Number % Number % Number % Number % Iramba 38,166 62 11,954 19 3,488 6 0 0 143 0 7,644 12 61,395 100 Singida Rural 47,163 65 21,689 30 1,920 3 118 0 122 0 1,452 2 72,464 100 Manyoni 12,287 37 19,544 59 920 3 80 0 85 0 149 0 33,065 100 Singida Urban 4,561 41 5,105 46 328 3 42 0 0 0 1,089 10 11,125 100 Total 102,177 57 58,292 33 6,656 4 240 0 350 0 10,334 6 178,049 100 Number % Number % Number % Number % Iramba 932 76 143 12 144 12 1,219 100 Singida Rural 709 85 123 15 0 0 832 100 Manyoni 989 52 926 48 0 0 1,916 100 Singida Urban 182 59 83 27 43 14 308 100 Total 2,812 66 1,276 30 187 4 4,275 100 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Remittances Bank Loan Credit Other Total 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 220 Number % Number % Number % Number % Number % Number % Iramba 16,998 64 3,674 14 1,422 5 0 0 4,492 17 26,586 100 Singida Rural 16,704 74 4,760 21 246 1 125 1 741 3 22,576 100 Manyoni 2,232 85 387 15 0 0 0 0 0 0 2,619 100 Singida Urban 666 76 126 14 0 0 0 0 84 10 876 100 Total 36,599 70 8,947 17 1,668 3 125 0 5,317 10 52,656 100 Number % Number % Number % Number % Number % Number % Iramba 15,078 64 4,394 19 850 4 0 0 3,205 14 23,527 100 Singida Rural 15,489 75 4,546 22 245 1 249 1 0 0 20,530 100 Manyoni 1,403 54 1,133 43 83 3 0 0 0 0 2,619 100 Singida Urban 455 61 168 22 0 0 0 0 126 17 750 100 Total 32,425 68 10,242 22 1,178 2 249 1 3,331 7 47,426 100 Number % Number % Number % Number % Iramba 0 0 137 49 143 51 280 100 Singida Rural 123 100 0 0 0 0 123 100 Total 123 31 137 34 143 35 403 100 12.2.17 ACCESS TO EQUIPMENT: Number of Agricultural Households District Sale of Farm Products Ot e co e Generating Activities Other Total 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District District Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OXEN by Source of Finance and District District Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 221 Number % Number % Number % Number % Number % Iramba 3,336 71 844 18 0 0 497 11 4,677 100 Singida Rural 2,451 73 821 24 103 3 0 0 3,375 100 Manyoni 489 66 249 34 0 0 0 0 738 100 Singida Urban 212 72 42 14 0 0 42 14 296 100 Total 6,488 71 1,955 22 103 1 539 6 9,086 100 Number % Number % Iramba 138 100 138 100 Total 138 100 138 100 Number % Number % Singida Rural 123 100 123 100 Total 123 100 123 100 12.2.18 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX CART by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Remittances Other Total 12.2.19 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District District Sale of Farm Total 12.2.21 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District District Other Income Generating Activities Total Tanzania Agriculture Census Survey 2003 Singida Region 222 Appendix II 223 AGRICULTURE CREDIT Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 224 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Other Total Credits Iramba 124 0 0 0 0 852 976 Singida Rural 246 0 0 0 0 0 246 Manyoni 76 76 1,117 883 74 646 2,872 Singida Urban 0 0 0 0 0 42 42 Total Credits 445 76 1,117 883 74 1,540 4,136 Number % Number % Number % Iramba 548 56 428 44 976 100 Singida Rural 246 100 0 0 246 100 Manyoni 723 50.4 712 49.6 1,435 100 Singida Urban 0 0 42 100 42 100 Total 1,516 56 1,182 44 2,698 100 Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Private Individual Religious Organisation / NGO / Project Total Iramba 837 0 0 139 0 0 976 Singida Rural 0 122 0 0 123 0 246 Manyoni 74 0 1,124 76 0 161 1,435 Singida Urban 0 0 0 0 0 42 42 Total 911 122 1,124 215 123 203 2,698 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Iramba 4,030 4,691 8,359 1,133 30,553 1,391 136 560 10,699 61,553 Singida Rural 2,318 11,084 8,061 853 27,783 490 250 242 21,871 72,951 Manyoni 985 6,352 3,700 564 12,180 327 251 65 7,207 31,630 Singida Urban 799 1,172 1,239 234 3,889 107 42 42 3,559 11,083 Total 8,133 23,298 21,358 2,784 74,405 2,315 679 909 43,336 177,217 District Male Female Total District Reason for Not Using Credit 13.1a AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District District Credit Use 13c AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District District Source of Credit 13d AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District 13b AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 225 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 226 Number % Number % Number % Iramba 4,606 7 57,922 93 62,528 100 Singida Rural 4,902 7 68,295 93 73,197 100 Manyoni 1,252 4 31,813 96 33,065 100 Singida Urban 792 7 10,333 93 11,125 100 Total 11,552 6 168,364 94 179,915 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Iramba 2,804 23,500 1,530 28,374 273 2,591 4,606 54,465 Singida Rural 3,315 30,500 988 36,724 598 25,993 4,902 93,217 Manyoni 490 5,432 762 10,871 0 . 1,252 16,302 Singida Urban 454 17,103 126 631 212 4,677 792 22,410 Total 7,063 76,535 3,406 76,598 1,083 33,261 11,552 186,395 61.1 41.1 29.5 41.1 9.4 17.8 District Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Leucena Spp Syszygium Spp Azadritacht a Spp Jakaranda Spp Kyaya Spp Moringa Spp Total Iramba 22,284 15,740 . 5,508 . . 8,149 1,134 1,507 143 . . 54,465 Singida Rural 3,315 23,396 613 53,783 1,850 243 749 2,824 4,743 . 974 728 93,217 Manyoni 4,474 930 . . 78 . . 255 2,402 . . 8,163 16,302 Singida Urban 610 5,470 . 15,363 . . . 883 . . . 85 22,410 Total 30,683 45,536 613 74,654 1,927 243 8,898 5,097 8,652 143 974 8,976 186,395 14.1 ON FARM TREE FARMING: Number of Households Having Planted Trees By District District Did your Hh have any Planted Trees on your land during 2002/ Households Having Planted Households Not Having Total 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Where Planted Mostly on Field / Plot Mostly Scattered in Field Mostly in Plantation / Total 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 227 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Iramba 1,422 832 1,345 1,277 143 1,836 6,856 Singida Rural 3,183 1,079 1,108 615 622 245 6,852 Manyoni 81 0 0 1,410 85 0 1,576 Singida Urban 530 170 125 210 0 42 1,078 Total 5,215 2,081 2,578 3,512 850 2,124 16,361 31.9 12.7 15.8 21.5 5.2 13.0 100.0 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Iramba 681 423 139 1,691 2,784 286 852 6,856 Singida Rural 1,238 608 0 3,775 863 368 0 6,852 Manyoni 85 85 0 0 165 754 487 1,576 Singida Urban 0 328 0 497 169 42 41 1,078 Total 2,004 1,444 139 5,963 3,981 1,450 1,380 16,361 Number % Number % Number % Iramba 30,810 49 31,718 51 62,528 100 Singida Rural 6,188 9 65,402 91 71,590 100 Manyoni 3,785 11 29,280 89 33,065 100 Singida Urban 4,363 39 6,762 61 11,125 100 Total 45,146 25 133,162 75 178,308 100 14 TREE FARMING: Main Use of Trees By District District Main Use 14 TREE FARMING: Second Use of Trees By District District Second Use 14.3 TREE FARMING: Number of Households By Whether Village Have a Community Tree Planting Scheme By District District does your village have a Community Tree Planting Scheme Have a Community Tree Does not Have a Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 228 0-9 1-19 05-29 30-39 40-49 60+ Total Iramba 5,908 6,439 5,958 4,515 2,852 5,138 30,810 Singida Rural 3,682 608 364 1,181 354 0 6,188 Manyoni 3,720 0 65 0 0 0 3,785 Singida Urban 1,440 1,493 301 831 127 170 4,363 Total 14,751 8,541 6,687 6,527 3,333 5,307 45,146 Poles Timber Logs Charcoal Firewood Not Ready to Use Not Allowed to Use Other Total Iramba 2,512 1,422 0 5,191 14,153 7,532 0 30,810 Singida Rural 2,222 2,851 0 235 123 0 1,768 7,198 Manyoni 0 84 505 505 2,610 80 0 3,785 Singida Urban 2,458 1,014 85 764 43 0 0 4,363 Total 7,191 5,371 590 6,695 16,929 7,612 1,768 46,157 District Main use during 2002/03 14.4 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) 14.5 TREE FARMING: Number of Households Involved in Community Tree Planting Scheme By Main Use and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 229 CROP EXTENSION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 230 Total Number % Number % Number Iramba 44,677 71.5 17,851 29 62,528 Singida Rural 26,948 36.8 46,249 63 73,197 Manyoni 10,970 33.2 22,095 67 33,065 Singida Urban 4,107 36.9 7,019 63 11,125 Total 86,702 48 93,214 52 179,915 Total Number % Number % Number % Number % Number % Number Iramba 4,865 10.9 31,473 70.7 6,357 14.3 1,277 2.9 562 1.3 44,534 Singida Rural 2,203 8.2 20,347 75.5 3,296 12.2 977 3.6 125 0.5 26,948 Manyoni 1,908 17.4 8,067 73.5 757 6.9 0 0.0 238 2.2 10,970 Singida Urban 372 9.1 2,878 70.1 856 20.8 0 0.0 0 0.0 4,107 Total 9,349 10.8 62,764 72.5 11,267 13.0 2,254 2.6 925 1.1 86,558 Total Number % Number % Number % Number % Number % Number Iramba 44,395 99.7 0 0.0 0 0.0 0 0.0 139 0.3 44,534 Singida Rural 24,980 94.0 368 1.4 250 0.9 855 3.2 125 0.5 26,576 Manyoni 10,452 95.8 453 4.2 0 0.0 0 0.0 0 0.0 10,905 Singida Urban 3,939 96.9 43 1.0 0 0.0 0 0.0 84 2.1 4,065 Total 83,765 97.3 863 1.0 250 0.3 855 1.0 348 0.4 86,081 15.3 EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District District Government NGO / Development Cooperative Large Scale Farm Other Source of Crop Extension 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services By District District Very Good Good Average Poor No Good Quality of service Households Receiving Extension Advice Households Not Receiving Extension Advice 15.1 CROP EXTENSION\" Number of Households Receiving Extension Messages By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 231 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Total Iramba 43,442 0 0 0 139 43,581 62,528 70 Singida Rural 23,521 368 250 855 0 24,993 73,197 34 Manyoni 9,951 453 0 0 0 10,404 33,065 31 Singida Urban 3,602 43 0 0 42 3,687 11,125 33 Total 80,516 863 250 855 181 82,665 179,915 46 Governme nt NGO / Development Project Cooperative Other Not applicable Total Iramba 25,744 0 0 281 424 26,449 62,528 42 Singida Rural 8,746 240 0 0 373 9,358 73,197 13 Manyoni 6,425 398 146 0 0 6,969 33,065 21 Singida Urban 1,862 0 0 117 42 2,021 11,125 18 Total 42,776 638 146 398 839 44,797 179,915 25 Governme nt NGO / Development Project Large Scale Farm Other Not applicable Total Iramba 29,272 0 0 139 0 29,411 62,528 47 Singida Rural 11,012 607 0 0 248 11,867 73,197 16 Manyoni 2,228 340 81 0 0 2,648 33,065 8 Singida Urban 2,220 43 0 0 0 2,263 11,125 20 Total 44,732 990 81 139 248 46,189 179,915 26 15.4 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District Spacing 15.6 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Erosion Control By Source of Messages By District Erosion Control Total Number of Households District % of total number of households Total Number of Households % of total number of households 15.5 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agrochemicals By Source of Messages By District % of total number of households Use of Agrochemicals Total Number of Households District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 232 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 40,414 0 0 0 139 0 40,553 62,528 65 Singida Rural 20,103 345 245 975 125 120 21,912 73,197 30 Manyoni 9,144 65 0 0 0 0 9,210 33,065 28 Singida Urban 3,474 43 0 0 169 0 3,686 11,125 33 Total 73,137 453 245 975 432 120 75,361 179,915 42 Governme nt NGO / Development Project Cooperative Not applicable Total Iramba 13,022 0 140 268 13,430 62,528 21 Singida Rural 1,480 121 0 250 1,851 73,197 3 Manyoni 4,027 889 161 0 5,078 33,065 15 Singida Urban 744 0 0 0 744 11,125 7 Total 19,273 1,011 302 518 21,104 179,915 12 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 35,152 136 0 0 139 696 36,124 62,528 58 Singida Rural 13,651 361 240 1,950 0 623 16,825 73,197 23 Manyoni 8,709 471 81 0 84 0 9,344 33,065 28 Singida Urban 3,021 85 0 0 75 85 3,266 11,125 29 Total 60,534 1,053 321 1,950 298 1,404 65,559 179,915 36 District District Total Number of Household s 15.7 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Organic Fertiliser Use By Source of Messages By District % of total number of households Total Number of Households 15.8 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Inorganic Fertiliser Use By Source of Messages By District 15.9 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Use of Improved Seed By Source of Messages By District % of total number of households Organic Fertilizer Use District % of total number of households Total Number of Households Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 233 Governme nt NGO / Development Project Not applicable Total Iramba 11,420 144 133 11,697 Singida Rural 245 245 370 860 Manyoni 2,187 163 0 2,350 Singida Urban 425 43 0 468 Total 14,277 594 504 15,375 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 9,841 859 0 0 0 267 10,966 62,528 18 Singida Rural 3,932 225 120 360 0 0 4,637 73,197 6 Manyoni 1,605 0 0 0 0 0 1,605 33,065 5 Singida Urban 999 33 108 33 286 0 1,458 11,125 13 Total 16,377 1,116 228 393 286 267 18,666 179,915 10 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 33,494 136 0 0 139 143 33,913 62,528 54 Singida Rural 19,093 592 240 1,595 125 373 22,017 73,197 30 Manyoni 9,017 240 65 0 0 0 9,322 33,065 28 Singida Urban 2,886 0 0 0 85 43 3,014 11,125 27 Total 64,491 969 305 1,595 348 558 68,266 179,915 38 District District Crop Storage District 15.12 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Crop Storage By Source of Messages By District Total Number of Households % of total number of households Mechanisation / LST Irrigation Technology 15.10 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Mechanisation / LST By Source of Messages By District 15.11 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Irrigation Technology By Source of Messages By District Total Number of Households % of total number of households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 234 Governme nt NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Iramba 21,387 0 0 0 144 21,531 62,528 34 Singida Rural 9,622 244 0 0 247 10,113 73,197 14 Manyoni 7,460 81 65 0 0 7,606 33,065 23 Singida Urban 1,914 43 0 159 33 2,149 11,125 19 Total 40,383 368 65 159 424 41,400 179,915 23 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 20,118 0 0 0 282 278 20,678 62,528 33 Singida Rural 12,907 494 120 2,570 0 125 16,215 73,197 22 Manyoni 4,570 85 406 65 0 0 5,126 33,065 16 Singida Urban 1,786 0 0 75 684 0 2,545 11,125 23 Total 39,380 579 526 2,710 966 403 44,564 179,915 25 Governme nt NGO / Development Project Cooperative Other Not applicable Total Iramba 18,553 0 0 139 0 18,692 62,528 30 Singida Rural 7,260 464 0 0 244 7,968 73,197 11 Manyoni 3,242 328 163 82 85 3,900 33,065 12 Singida Urban 2,310 43 43 43 0 2,437 11,125 22 Total 31,365 835 205 264 329 32,997 179,915 18 Vermin Control District 15.13 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Vermin Control By Source of Messages By District % of total number of households District Total Number of Households % of total number of households 15.14 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District Total Number of Households District 15.15 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-forestry By Source of Messages By District Agro-progressing Agro-forestry Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 235 Governme nt NGO / Development Project Cooperative Large Scale Farm Not applicable Total Iramba 5,850 266 0 0 0 6,116 62,528 10 Singida Rural 845 984 0 125 0 1,954 73,197 3 Manyoni 1,424 81 78 0 169 1,752 33,065 5 Singida Urban 43 0 0 0 0 43 11,125 0 Total 8,162 1,331 78 125 169 9,865 179,915 5 Governme nt NGO / Development Project Not applicable Total Iramba 2,990 0 0 2,990 62,528 5 Singida Rural 1,342 856 120 2,318 73,197 3 Manyoni 148 85 0 233 33,065 1 Singida Urban 0 0 0 0 11,125 0 Total 4,480 941 120 5,541 179,915 3 District Beekeeping District Total Number of Households % of total number of households 15.16 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Beekiping By Source of Messages By District 15.17 EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District Fish Farming Total Number of Household s % of total number of households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 236 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 43,576 38,311 88 26,466 7,452 28 29,145 14,298 49 40,698 29,560 73 12,712 2,159 17 Singida Rural 24,870 24,748 100 8,741 3,307 38 11,621 9,668 83 22,164 18,851 85 986 2,465 250 Manyoni 10,478 9,813 94 6,405 2,531 40 2,544 1,381 54 9,203 3,474 38 3,738 2,932 78 Singida Urban 3,687 3,644 99 2,021 365 18 2,263 1,679 74 3,686 2,579 70 702 75 11 Total 82,611 76,516 93 43,633 13,656 31 45,573 27,026 59 75,750 54,464 72 18,139 7,632 42 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 36,532 11,390 31 10,417 1,709 16 10,003 2,863 29 33,916 28,141 83 21,389 18,139 85 Singida Rural 17,193 10,103 59 618 740 120 2,537 3,423 135 22,266 19,421 87 9,003 10,237 114 Manyoni 9,344 5,231 56 2,200 0 0 1,605 464 29 9,237 8,602 93 7,614 7,021 92 Singida Urban 3,266 1,500 46 468 43 9 1,213 553 46 3,014 2,344 78 2,149 1,573 73 Total 66,335 28,223 43 13,703 2,492 18 15,358 7,304 48 68,433 58,508 85 40,155 36,971 92 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 20,293 18,874 93 18,548 6,645 36 5,317 2,453 46 2,730 0 0 2,203 1,360 62 Singida Rural 14,874 15,603 105 8,215 5,394 66 1,586 847 53 2,318 495 21 974 605 62 Manyoni 5,210 5,126 98 3,985 1,070 27 1,752 757 43 168 0 0 82 82 100 Singida Urban 2,460 2,386 97 2,470 927 38 43 43 100 0 0 0 42 42 100 Total 42,837 41,989 98 33,218 14,037 42 8,698 4,100 47 5,216 495 9 3,301 2,089 63 Use of Improved Seed Mechanisation / LST Irrigation Technology 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 2) During the 2002/03 Agriculture Year, Singida Region District Crop Storage Vermin Control 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 1) During the 2002/03 Agriculture Year, Singida Region Use of Agrochemicals Spacing Erosion Control Organic Fertilizer Use Inorganic Fertilizer Use District Other 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 3) During the 2002/03 Agriculture Year, Singida Region Agro-progressing Agro-forestry Beekeeping Fish Farming District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 237 LIVELIHOOD CONSTRAINTS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 238 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 10,333 1,697 29,436 2,187 3,461 698 0 2,303 429 0 0 Singida Rural 12,036 3,187 24,199 11,005 3,194 1,089 361 5,818 2,080 124 123 Manyoni 408 497 14,516 2,553 2,879 742 329 1,313 736 0 0 Singida Urban 2,316 566 2,920 2,451 836 85 43 419 127 85 0 Access to Potable Water Access to Credit Harvesting Storage Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 4,426 4,190 0 144 141 141 561 0 1,268 140 974 Singida Rural 2,171 1,277 124 353 0 123 3,630 124 1,564 0 613 Manyoni 2,002 823 0 0 85 81 4,341 238 1,286 0 236 Singida Urban 75 203 0 43 0 0 423 43 208 0 286 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 3,467 3,243 12,191 8,543 9,551 1,425 2,367 12,506 428 0 133 Singida Rural 2,776 4,599 17,327 11,522 12,576 2,330 2,338 6,485 3,176 0 0 Manyoni 0 0 6,025 2,912 7,610 568 1,998 3,183 1,144 0 0 Singida Urban 668 926 2,599 2,789 1,146 201 192 929 127 127 0 Access to Potable Water Access to Credit Threshing Storage Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Access to Off Farm Income Iramba 3,134 1,351 0 287 573 576 552 280 1,261 660 Singida Rural 1,954 1,690 124 124 369 0 2,785 122 2,531 369 Manyoni 474 1,873 0 255 0 170 2,485 243 3,880 247 Singida Urban 42 211 0 0 75 0 713 43 169 169 District 2nd Most Importance District 2nd Most Importance 16.2 LIVELIHOOD CONSTRAINTS: Second Most Important Constraints By District 16.1 LIVELIHOOD CONSTRAINTS: Most Important Constraints By District cont…. LIVELIHOOD CONSTRAINTS: Second Most Important Constraints By District 1st Most Importance cont…. LIVELIHOOD CONSTRAINTS: Most Important Constraints By District 1st Most Importance District District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 239 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Access to Potable Water Iramba 1,981 697 5,903 6,336 9,413 3,109 3,333 12,212 1,573 0 4,920 Singida Rural 1,480 1,729 6,185 6,350 12,619 1,723 8,330 10,775 5,661 0 2,425 Manyoni 0 84 2,112 639 5,945 1,812 4,515 5,753 1,213 0 1,370 Singida Urban 680 637 1,417 1,848 1,010 202 245 2,218 700 160 252 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Access to Off Farm Income Iramba 3,008 0 0 282 0 421 1,876 287 289 2,776 4,114 Singida Rural 3,513 220 125 1,540 123 2,033 609 3,034 598 3,767 359 Manyoni 2,044 0 0 590 0 84 819 3,437 167 2,139 340 Singida Urban 414 0 0 42 0 85 0 410 75 244 486 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 1,081 571 2,662 5,326 8,309 2,131 4,240 8,778 2,081 286 0 Singida Rural 858 725 2,921 2,542 8,103 1,606 4,277 13,806 5,155 122 0 Manyoni 0 82 1,983 489 3,359 554 3,315 6,147 1,719 0 0 Singida Urban 845 340 1,011 837 1,899 160 553 1,570 763 627 85 District 3rd Most Importance 16.3 LIVELIHOOD CONSTRAINTS: Third Important Constraints By District District cont…. LIVELIHOOD CONSTRAINTS: Third Important Constraints By District 3rd Most Importance District 4th Most Importance 16.4 LIVELIHOOD CONSTRAINTS: Forth Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 240 Access to Potable Water Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Iramba 8,788 5,502 286 0 714 143 1,685 1,268 429 0 5,951 144 Singida Rural 2,595 7,275 362 487 2,835 363 2,944 2,147 3,860 246 8,639 0 Manyoni 1,149 3,625 85 0 492 84 415 820 4,140 589 3,611 0 Singida Urban 319 583 43 0 117 0 84 169 578 65 116 33 Access to Off Farm Income Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Access to Potable Water Iramba 2,154 1,390 570 2,467 7,315 4,928 3,127 2,805 7,291 2,148 0 4,241 Singida Rural 1,328 1,239 1,481 3,426 1,548 5,159 1,845 4,054 8,156 8,715 369 1,351 Manyoni 406 0 160 1,462 743 1,419 648 3,085 4,295 2,302 0 989 Singida Urban 328 542 202 888 572 845 342 510 1,539 1,171 210 338 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 6,389 144 0 999 0 2,869 1,398 1,260 418 5,514 1,587 5,668 Singida Rural 5,988 247 231 2,684 243 5,357 2,189 6,283 124 8,987 0 2,785 Manyoni 3,230 0 0 330 0 491 905 4,658 331 6,804 0 1,215 Singida Urban 1,284 0 43 85 0 43 127 762 170 560 0 852 District cont LIVELIHOOD CONSTRAINTS: Fifth Important Constraints By District District 5th Most Importance 4th Most Importance cont…. LIVELIHOOD CONSTRAINTS: Forth Important Constraints By District 5th Most Importance 16.5 LIVELIHOOD CONSTRAINTS: Fifth Important Constraints By District District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 241 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 9,940 2,546 1,948 3,871 1,682 1,287 5,119 2,249 3,330 144 567 979 Singida Rural 6,194 5,623 2,196 4,663 3,565 3,148 4,397 1,229 4,529 1,472 611 2,206 Manyoni 2,495 668 1,652 3,674 2,084 409 2,603 1,000 1,566 83 0 997 Singida Urban 284 235 225 117 455 463 641 291 466 295 75 213 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,636 2,016 2,279 1,259 286 3,782 597 1,034 4,347 5,681 2,235 2,714 Singida Rural 2,824 2,353 3,029 3,271 871 3,160 589 3,069 3,339 2,820 5,363 2,677 Manyoni 2,463 329 326 801 251 811 981 1,714 4,121 2,313 330 1,396 Singida Urban 718 287 329 329 128 965 235 712 1,375 810 506 974 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 3,650 6,216 829 4,640 1,786 1,825 3,143 2,332 7,703 144 284 1,279 Singida Rural 1,162 4,500 1,334 2,324 3,084 3,634 4,286 4,133 5,969 2,103 3,311 2,957 Manyoni 248 1,006 887 2,278 1,479 1,064 3,402 2,455 2,773 0 0 1,633 Singida Urban 328 149 244 159 412 266 276 342 592 234 296 403 16.6 LIVELIHOOD CONSTRAINTS: Least Important Constraints By District 1st Least Importance District 16.7 LIVELIHOOD CONSTRAINTS: Second Least Important Constraints By District 2nd Least Importance District District 1st Least Importance cont…. LIVELIHOOD CONSTRAINTS: Least Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 242 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,879 2,849 1,279 3,729 853 5,337 2,056 2,150 1,313 3,475 713 2,065 Singida Rural 5,918 2,542 2,058 3,998 2,085 3,533 1,348 3,424 2,685 2,593 1,429 2,669 Manyoni 2,957 327 167 1,060 169 1,721 1,400 1,984 2,042 2,070 83 1,859 Singida Urban 742 541 383 659 255 794 296 680 1,333 732 506 502 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 4,879 1,236 834 3,094 1,121 858 4,946 1,542 5,425 288 0 3,147 Singida Rural 1,082 1,674 1,101 2,205 2,070 1,722 3,539 3,184 6,098 4,176 1,852 3,147 Manyoni 83 414 471 1,327 901 803 2,986 1,686 2,690 165 165 2,123 Singida Urban 267 381 242 149 549 320 463 520 792 404 337 340 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 3,554 2,549 3,301 3,828 1,562 4,318 1,567 1,499 3,353 4,564 1,275 3,789 Singida Rural 6,386 2,798 2,751 5,276 1,973 6,458 3,541 2,464 2,562 2,398 1,824 2,917 Manyoni 3,299 750 169 2,488 591 2,886 1,794 1,401 1,312 2,491 83 1,484 Singida Urban 606 552 382 253 85 489 297 1,146 913 930 253 456 District 2nd Least Importance District 16.8 LIVELIHOOD CONSTRAINTS: Third Least Important Constraints By District 3rd Least Importance 3rd Least Importance cont…. LIVELIHOOD CONSTRAINTS: Second Least Important Constraints By District District cont…. LIVELIHOOD CONSTRAINTS: Third Least Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 243 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 1,390 1,368 534 1,805 1,638 573 3,489 2,987 5,649 423 431 1,140 Singida Rural 2,329 1,694 865 1,095 1,570 1,415 2,914 3,027 3,594 2,339 2,103 1,592 Manyoni 247 336 983 1,484 806 1,129 2,025 1,725 1,872 579 0 970 Singida Urban 276 361 244 210 539 203 403 380 712 497 210 324 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 3,249 1,839 1,697 4,318 1,974 6,645 2,240 5,221 2,081 6,205 1,538 4,096 Singida Rural 5,232 4,479 1,832 5,515 3,045 5,640 5,023 3,450 2,547 4,933 3,319 3,644 Manyoni 2,073 757 331 1,977 839 3,068 1,536 2,403 1,743 2,822 333 1,607 Singida Urban 479 382 255 1,186 212 709 169 827 720 1,043 253 530 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 990 1,000 820 2,210 5,308 1,002 3,094 1,251 3,648 288 425 1,951 Singida Rural 1,827 3,420 1,187 843 2,143 1,207 3,288 2,294 3,188 1,225 1,592 869 Manyoni 332 837 993 1,671 824 575 1,705 1,019 2,595 249 0 1,488 Singida Urban 244 212 33 128 369 268 520 488 533 352 84 444 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,702 2,136 1,124 2,667 2,273 3,401 2,963 1,845 2,361 6,814 2,828 9,286 Singida Rural 4,940 1,609 1,573 3,503 1,943 4,367 2,082 4,522 4,667 10,367 3,183 5,876 Manyoni 2,785 583 669 1,311 336 1,204 1,668 1,725 3,129 1,739 419 3,377 Singida Urban 583 509 340 626 213 540 211 904 699 1,916 456 412 District District cont…. LIVELIHOOD CONSTRAINTS: Forth Least Important Constraints By District 16.9 LIVELIHOOD CONSTRAINTS: Forth Least Important Constraints By District 4th Least Importance 4th Least Importance 16.10 LIVELIHOOD CONSTRAINTS: Fifth Least Important Constraints By District 5th Least Importance cont…. LIVELIHOOD CONSTRAINTS: Fifth Least Important Constraints By District 5th Least Importance District District Tanzania Agriculture Census Survey 2003 Singida Region 244 Appendix II 245 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 246 Total Number % Number % Number Iramba 53,098 85 9,430 15 62,528 Singida Rural 32,196 44 41,001 56 73,197 Manyoni 3,990 12 29,075 88 33,065 Singida Urban 1,129 10 9,996 90 11,125 Total 90,414 50 89,502 50 179,915 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Iramba 103,723 212,893 105,194 7,145 6,617 3,696 44,071 3,896 467 4,375 3,950 2,006 159,315 227,356 111,363 Singida Rural 75,877 111,895 59,183 12,481 11,906 975 21,231 8,525 143 1,593 1,848 757 111,182 134,174 61,058 Manyoni 17,955 22,298 16,154 593 1,015 0 3,720 0 0 . . . 22,268 23,312 16,154 Singida Urban 2,265 3,296 1,539 338 85 43 168 0 0 . . . 2,770 3,381 1,582 Total 199,820 350,382 182,070 20,556 19,623 4,714 69,190 12,421 611 5,969 5,798 2,763 295,535 388,224 190,158 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Iramba 103,723 212,893 259,830.0 7,145 6,617 9,128.8 44,071 3,896 1,154.4 4,375 3,950 4,954.1 159,315 227,356 275,067.4 Singida Rural 75,877 111,895 146,181.6 12,481 11,906 2,408.5 21,231 8,525 353.6 1,593 1,848 1,869.9 111,182 134,174 150,813.7 Manyoni 17,955 22,298 39,900.7 593 1,015 0.0 3,720 0 0.0 . . . 22,268 23,312 39,900.7 Singida Urban 2,265 3,296 3,801.1 338 85 106.5 168 0 0.0 . . . 2,770 3,381 3,907.6 Total 199,820 350,382 449,713.4 20,556 19,623 11,643.8 69,190 12,421 1,508.0 5,969 5,798 6,824.1 295,535 388,224 469,689.3 Households Using Draft Animals Household Not Using Draft Animals Did you use Draft animals to cultivate your land during 2002/03 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total 17.3 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 247 Number % Number % Number % Iramba 34,394 43.2 28,134 28.8 62,528 35.3 Singida Rural 33,417 42.0 38,094 39.0 71,511 40.3 Manyoni 6,154 7.7 26,167 26.8 32,321 18.2 Singida Urban 5,686 7.1 5,322 5.4 11,008 6.2 Total 79,651 100.0 97,717 100.0 177,368 100.0 Area (%) % Area (%) % Area (%) % Iramba 32,951 47.1 1,731 56.8 34,682 47.5 Singida Rural 27,618 39.5 1,034 33.9 28,652 39.2 Manyoni 5,504 7.9 119 3.9 5,623 7.7 Singida Urban 3,905 5.6 161 5.3 4,067 5.6 Total 69,978 100.0 3,046 100.0 73,023 100.0 17.4 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total 17.5 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area applied with Organic Fertilisers Tanzania Agriculture Census Survey 2003 Singida Region 248 Appendix II 249 CATTLE PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 250 Number % Number % Number % Iramba 27,972 44.7 34,556 55.3 62,528 100.0 Singida Rural 35,272 48.2 37,925 51.8 73,197 100.0 Manyoni 4,522 13.7 28,543 86.3 33,065 100.0 Singida Urban 4,739 42.6 6,386 57.4 11,125 100.0 Total 72,505 40.3 107,410 59.7 179,915 100.0 Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Iramba 27,830 449,741 289 433 0 . 27,830 450,174 Singida Rural 35,272 586,883 123 493 372 1,115 35,272 588,491 Manyoni 4,522 173,993 0 . 0 . 4,522 173,993 Singida Urban 4,739 44,501 0 . 0 . 4,739 44,501 Total 72,363 1,255,118 412 925 372 1,115 72,363 1,257,159 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year District Households Rearing Cattle Households Not Rearing Cattle Total 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Beef Improved Dairy Total Cattle Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 251 Number of Household % Number of Cattle % Number Per Household 1-5 9,954 36 34,822 8 3 6-10 7,597 27 59,969 13 8 11-15 3,685 13 45,552 10 12 16-20 3,232 12 57,561 13 18 21-30 1,421 5 34,410 8 24 31-40 710 3 25,450 6 36 41-50 250 1 11,621 3 47 61-100 704 3 60,522 13 86 101-150 137 0 19,134 4 140 151+ 140 1 101,132 22 724 Total 27,830 100 450,174 100 16 1-5 10,541 30 36,680 6 3 6-10 11,813 33 92,445 16 8 11-15 5,970 17 75,972 13 13 16-20 1,987 6 36,638 6 18 21-30 2,928 8 73,104 12 25 31-40 830 2 31,021 5 37 41-50 123 0 6,135 1 50 61-100 476 1 43,912 7 92 101-150 123 0 18,405 3 150 151+ 481 1 174,179 30 362 Total 35,272 100 588,491 100 17 1-5 81 2 242 0 3 6-10 330 7 2,554 1 8 11-15 571 13 7,421 4 13 16-20 968 21 17,726 10 18 21-30 507 11 12,669 7 25 31-40 569 13 18,498 11 32 41-50 416 9 19,468 11 47 51-60 163 4 8,984 5 55 61-100 750 17 59,125 34 79 101-150 82 2 11,420 7 140 151+ 84 2 15,886 9 188 Total 4,522 100 173,993 100 38 1-5 1,499 32 5,373 12 4 6-10 1,622 34 13,245 30 8 11-15 836 18 11,359 26 14 16-20 614 13 10,803 24 18 21-30 169 4 3,721 8 22 Total 4,739 100 44,501 100 9 Manyoni Singida Urban 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 Herd Size Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 252 Type Number of Indigenous Number of Improved Beef Number of Improved Dairy Total Cattle Bulls 100,657 925 . 101,582 Cows 451,353 . 497 451,850 Steers 235,101 . 247 235,348 Heifers 213,743 . 124 213,866 Male Calves 121,206 . . 121,206 Female Calves 133,059 . 247 133,306 Total 1,255,118 925 1,115 1,257,159 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 37,586 203,723 96,473 51,275 28,101 32,583 449,741 Singida Rural 45,287 165,375 112,942 123,109 68,174 71,996 586,883 Manyoni 12,679 64,675 22,205 33,390 18,737 22,307 173,993 Singida Urban 5,104 17,580 3,480 5,970 6,194 6,173 44,501 Total 100,657 451,353 235,101 213,743 121,206 133,059 1,255,118 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 433 . . . . . 433 Singida Rural 493 . . . . . 493 Manyoni . . . . . . . Singida Urban . . . . . . . Total 925 . . . . . 925 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Beef Cattle Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 253 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba . . . . . . . Singida Rural . 497 247 124 . 247 1,115 Manyoni . . . . . . . Singida Urban . . . . . . . Total . 497 247 124 . 247 1,115 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 38,019 203,723 96,473 51,275 28,101 32,583 450,174 Singida Rural 45,780 165,872 113,189 123,232 68,174 72,243 588,491 Manyoni 12,679 64,675 22,205 33,390 18,737 22,307 173,993 Singida Urban 5,104 17,580 3,480 5,970 6,194 6,173 44,501 Total 101,582 451,850 235,348 213,866 121,206 133,306 1,257,159 Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Iramba 8,190 23,671 37,042 45,382 10,450 28,767 7,922 13,034 11,873 13,689 14,247 15,796 140,339 Singida Rural 13,143 33,773 13,881 25,202 2,078 16,458 3,703 9,657 3,560 4,302 4,616 6,581 95,972 Manyoni 3,408 13,668 3,571 10,325 82 4,061 170 2,626 750 2,322 991 2,230 35,232 Singida Urban 997 4,092 2,614 6,426 42 1,310 1,010 2,592 1,349 2,237 1,596 2,020 18,678 Total 25,738 75,204 57,108 87,334 12,652 50,595 12,805 27,910 17,533 22,550 21,450 26,627 290,220 Female Calves 18.7 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Total Cattle Offtake District Category - Total Cattle 18.9 CATTLE OFFTAKE: Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year District Bulls Cows Steers Heifers Male Calves Tanzania Agriculture Census Survey 2003 Singida Region 254 Appendix II 255 GOATS PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 256 Total Number % Number % Number Iramba 23,828 38 38,700 62 62,528 Singida Rural 27,499 38 45,698 62 73,197 Manyoni 5,714 17 27,351 83 33,065 Singida Urban 4,026 36 7,100 64 11,125 Total 61,067 34 118,849 66 179,915 Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Iramba 23,273 253,149 564 991 701 1,540 23,273 255,680 Singida Rural 27,375 303,892 601 2,669 851 6,941 27,375 313,502 Manyoni 5,629 77,574 0 . 85 255 5,714 77,829 Singida Urban 4,026 36,771 0 . 128 637 4,026 37,409 Total 60,302 671,387 1,165 3,659 1,765 9,374 60,387 684,420 Households Rearing Goats Households Not Rearing 19.1 GOAT PRODUCTION: Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year 19.2 GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Indigenous Improved for Meat Improved Dairy Total Goat Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 257 Number of Household % Number of Goat % Average Number 1-4 5,573 24 16,600 6 3 5-9 8,348 36 53,510 21 6 10-14 4,531 19 50,215 20 11 15-19 1,492 6 23,775 9 16 20-24 1,275 5 26,625 10 21 25-29 951 4 25,871 10 27 30-39 571 2 17,701 7 31 40+ 532 2 41,382 16 78 Total 23,273 100 255,680 100 11 1-4 7,648 28 22,249 7 3 5-9 7,533 28 48,705 16 6 10-14 4,880 18 55,795 18 11 15-19 2,938 11 48,616 16 17 20-24 2,332 9 48,968 16 21 25-29 955 3 24,846 8 26 30-39 366 1 12,300 4 34 40+ 724 3 52,023 17 72 Total 27,375 100 313,502 100 11 1-4 1,127 20 3,290 4 3 5-9 1,542 27 10,380 13 7 10-14 916 16 10,921 14 12 15-19 652 11 11,317 15 17 20-24 724 13 15,082 19 21 25-29 167 3 4,426 6 26 30-39 334 6 11,498 15 34 40+ 252 4 10,916 14 43 Total 5,714 100 77,829 100 14 1-4 1,251 31 3,945 11 3 5-9 1,010 25 6,863 18 7 10-14 1,088 27 11,893 32 11 15-19 297 7 5,054 14 17 20-24 211 5 4,465 12 21 25-29 84 2 2,103 6 25 30-39 85 2 3,087 8 37 Total 4,026 100 37,409 100 9 1-4 15,600 26 46,083 7 3 5-9 18,432 31 119,458 17 6 10-14 11,415 19 128,824 19 11 15-19 5,379 9 88,761 13 17 20-24 4,541 8 95,141 14 21 25-29 2,158 4 57,246 8 27 30-39 1,355 2 44,586 7 33 40+ 1,508 2 104,321 15 69 Total 60,387 100 684,420 100 11 Manyoni Singida Urban Total 19.3 GOAT PRODUCTION: Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003 Herd Size Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 258 District Number of Indigenous Number of Improved for Meat Number of Improved Dairy Total Goat Billy Goat 102,480 675 1,031 104,186 Castrated Goat 50,861 764 3,913 55,538 She Goat 333,822 1,418 1,736 336,975 Male Kid 93,271 114 1,227 94,613 She Kid 90,953 689 1,467 93,108 Total 671,387 3,659 9,374 684,420 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 41,075 22,266 128,344 31,862 29,601 253,149 Singida Rural 45,028 21,328 151,469 43,935 42,133 303,892 Manyoni 10,397 4,889 35,938 12,334 14,015 77,574 Singida Urban 5,980 2,378 18,071 5,140 5,203 36,771 Total 102,480 50,861 333,822 93,271 90,953 671,387 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 430 144 417 . . 991 Singida Rural 246 620 1,000 114 689 2,669 Manyoni . . . . . . Singida Urban . . . . . . Total 675 764 1,418 114 689 3,659 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba . 144 710 400 287 1,540 Singida Rural 861 3,769 601 743 968 6,941 Manyoni 170 . 85 . . 255 Singida Urban . . 339 85 213 637 Total 1,031 3,913 1,736 1,227 1,467 9,374 19.4.1 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District 19.6 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Number of Indigenous District Number of Improved Dairy 19.7 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat 19.8 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 259 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 41,505 22,555 129,471 32,262 29,888 255,680 Singida Rural 46,134 25,717 153,071 44,792 43,789 313,502 Manyoni 10,567 4,889 36,023 12,334 14,015 77,829 Singida Urban 5,980 2,378 18,410 5,225 5,416 37,409 Total 104,186 55,538 336,975 94,613 93,108 684,420 Ram Castrated Goat She Goat Male Kid She Kid Iramba 22,981 11,175 28,858 7,898 6,005 Singida Rural 32,313 15,696 27,613 7,846 7,488 Manyoni 9,797 1,474 6,295 1,350 7,188 Singida Urban 3,310 1,691 5,278 834 1,184 Total 68,400 30,036 68,043 17,927 21,864 Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Iramba 5,269 22,981 569 11,175 11,022 28,858 4,615 7,898 5,446 6,005 76,917 Singida Rural 4,265 32,313 1,855 15,696 8,326 27,613 3,962 7,846 5,514 7,488 90,955 Manyoni 4,072 9,797 . 1,474 2,637 6,295 1,017 1,350 6,520 7,188 26,103 Singida Urban 658 3,310 . 1,691 1,565 5,278 367 834 761 1,184 12,297 Total 14,264 68,400 2,424 30,036 23,550 68,043 9,961 17,927 18,241 21,864 206,271 District Goat Type 19.6 Goat OFFTAKE: Number of Goat Died and % of Offtake By Tpe and District District Ram Castrated Goat She Goat Male Kid She Kid Total Goat Offtake 19.4 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 District Total Goat 19.5 Goat OFFTAKE: Goat Offtake By Type and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 260 Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Iramba 13,570 9,229 89,960,894 7,097 12,869 65,961,329 14,035 7,151 67,952,958 Singida Rural 17,165 8,202 89,770,345 11,383 8,703 51,769,745 12,681 10,100 96,347,581 Manyoni 2,731 13,059 29,648,312 898 10,860 9,806,173 2,601 7,403 12,874,921 Singida Urban 1,593 11,389 14,710,229 1,245 9,188 7,046,845 1,981 7,470 13,193,881 Total 35,059 9,239 224,089,779 20,624 10,560 134,584,092 31,298 8,443 190,369,341 Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Iramba 3,004 4,286 7,220,097 283 4,612 8,378,602 37,989 8,590 239,473,879 Singida Rural 483 2,693 3,312,591 484 24,349 30,011,444 42,197 9,386 271,211,705 Manyoni . 5,053 3,651,056 330 4,142 2,416,375 6,561 9,391 58,396,836 Singida Urban 85 3,541 1,491,637 169 79,428 26,788,421 5,073 13,796 63,231,014 Total 3,572 3,862 15,675,381 1,266 17,026 67,594,842 91,819 9,357 632,313,435 Male Kid She Kid Total 19.7 Goat OFFTAKE: Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year District District Ram Castrated Goat She Goat cont…. Goat OFFTAKE: Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 261 SHEEP PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 262 Number % Number % Number % Iramba 14,969 24 47,559 76 62,528 100 Singida Rural 17,985 25 55,212 75 73,197 100 Manyoni 3,467 10 29,598 90 33,065 100 Singida Urban 2,758 25 8,367 75 11,125 100 Total 39,179 22 140,736 78 179,915 100 District Number of Indigenous Number of Improved Total Sheep Iramba 119,704 . 119,704 Singida Rural 139,366 2,238 141,604 Manyoni 31,901 . 31,901 Singida Urban 16,343 386 16,729 Total 307,314 2,624 309,938 20.2 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.1 SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002.0/ Agriculture Year District Did the household own, raise or manage any Sheep? Households Raising Sheep Households Not Raising Sheep Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 263 Number of Household % Number of Sheep % Average Number Per Household 1-4 7,081 48 19,561 16 3 5-9 4,923 33 31,734 27 6 10-14 961 6 10,568 9 11 15-19 768 5 12,588 11 16 20-24 526 4 10,797 9 21 25-29 140 1 3,911 3 28 30-39 143 1 4,286 4 30 40+ 284 2 26,258 22 92 Total 14,826 100 119,704 100 8 1-4 8,625 48 25,026 18 3 5-9 5,572 31 36,025 25 6 10-14 1,721 10 19,681 14 11 15-19 735 4 12,384 9 17 20-24 718 4 14,713 10 20 30-39 125 1 4,484 3 36 40+ 489 3 29,291 21 60 Total 17,985 100 141,604 100 8 1-4 984 28 2,847 9 3 5-9 1,316 38 8,401 26 6 10-14 500 14 5,651 18 11 15-19 329 10 5,274 17 16 20-24 170 5 3,729 12 22 30-39 169 5 5,999 19 36 Total 3,467 100 31,901 100 9 1-4 1,259 46 3,151 19 3 5-9 1,043 38 6,689 40 6 10-14 286 10 3,242 19 11 15-19 43 2 639 4 15 20-24 85 3 1,817 11 21 25-29 43 2 1,191 7 28 Total 2,758 100 16,729 100 6 1-4 17,949 46 50,586 16 3 5-9 12,854 33 82,849 27 6 10-14 3,468 9 39,141 13 11 15-19 1,875 5 30,886 10 16 20-24 1,498 4 31,056 10 21 25-29 182 0 5,102 2 28 30-39 436 1 14,769 5 34 40+ 773 2 55,550 18 72 Total 39,036 100 309,938 100 8 Singida Rural Manyoni Singida Urban Total 20.3.1 SHEEP PRODUCTION: Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03 Herd Size Total Sheep Iramba Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 264 Breed Number of Indigenous Number of Improved for Mutton Total Sheep Ram 46,334 368 46,703 Castrated Sheep 15,989 . 15,989 She Sheep 154,411 1,003 155,414 Male Lamb 52,662 379 53,040 She Lamb 37,918 873 38,792 Total 307,314 2,624 309,938 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 22,032 9,838 57,112 14,961 15,761 119,704 Singida Rural 16,642 4,749 72,517 30,541 14,916 139,366 Manyoni 5,306 1,168 16,292 4,051 5,084 31,901 Singida Urban 2,355 234 8,490 3,108 2,157 16,343 Total 46,334 15,989 154,411 52,662 37,918 307,314 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba . . . . . . Singida Rural 368 . 747 248 873 2,238 Manyoni . . . . . . Singida Urban . . 256 130 . 386 Total 368 . 1,003 379 873 2,624 20.4.1 SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year 20.5 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Number of Indigenous 20.6 SHEEP PRODUCTION: Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Improved for Mutton Number of Improved for Mutton Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 265 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 22,032 9,838 57,112 14,961 15,761 119,704 Singida Rural 17,010 4,749 73,265 30,790 15,790 141,604 Manyoni 5,306 1,168 16,292 4,051 5,084 31,901 Singida Urban 2,355 234 8,745 3,238 2,157 16,729 Total 46,703 15,989 155,414 53,040 38,792 309,938 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 3,651 286 571 17,036 20,296 Singida Rural 88,381 689 2,401 17,171 15,810 Manyoni 240 169 164 4,308 5,773 Singida Urban 441 126 932 2,155 1,903 Total 92,713 1,270 4,068 40,670 43,782 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 23,115 7,292 13,731 2,659 4,770 Singida Rural 13,056 5,067 10,025 744 1,971 Manyoni 1,909 74 2,538 169 894 Singida Urban 1,062 212 2,548 423 382 Total 39,142 12,645 28,843 3,995 8,018 District Sheep Type 20.8 SHEEP INTAKE: Sheep Intake By Type and District District Total Sheep Intake 20.9 SHEEP OFFTAKE: Sheep Offtake By Type and District 20.7 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep Total Sheep Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 266 Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Iramba 7,584 23,115 1,818 7,292 6,519 13,731 838 2,659 3,217 4,770 Singida Rural 861 13,056 1,237 5,067 2,945 10,025 620 744 616 1,971 Manyoni 159 1,909 . 74 589 2,538 . 169 304 894 Singida Urban 85 1,062 . 212 507 2,548 295 423 42 382 Total 8,688 39,142 3,055 12,645 10,560 28,843 1,753 3,995 4,179 8,018 Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Iramba 5,384 6,487 27,803,172 3,075 6,476 7,977,535 5,501 5,550 22,424,246 . 4,333 1,818,642 . 4,194 2,946,934 Singida Rural 8,674 5,904 30,366,061 1,472 5,886 7,926,491 3,562 5,840 23,571,069 . 10,939 2,716,542 740 2,667 989,103 Manyoni 846 9,508 7,932,457 74 10,000 742,862 930 7,154 4,226,175 169 5,000 422,798 . 3,727 596,701 Singida Urban 732 5,420 3,739,535 85 5,669 721,516 1,021 4,804 4,047,027 85 2,531 749,482 298 2,625 444,942 Total 15,636 6,376 69,841,225 4,706 6,248 17,368,405 11,013 5,707 54,268,517 254 5,442 5,707,464 1,038 3,548 4,977,681 20.9 SHEEP OFFTAKE: Number of Sheep Died and % of Offtake By Type and District District Ram Castrated Sheep She Sheep Male Lamb She Lamb 20.10 SHEEP OFFTAKE: Number of Sheep Sold and Value (Tshs) by Category and District during 2002/03 Agriculture Year District Ram Castrated Sheep She Sheep Male Lamb She Lamb Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 267 PIGS PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 268 Total Number % Number % Number Iramba 1,689 2.7 60,839 97.3 62,528 Singida Rural 703 1.0 72,493 99.0 73,197 Manyoni 161 0.5 32,903 99.5 33,065 Singida Urban 0 0.0 11,125 100.0 11,125 Total 2,554 1.4 177,362 98.6 179,915 District Number of Household Number of Pig g Number Per Household Iramba 1,546 2,508 2 Singida Rural 580 3,464 6 Manyoni 161 403 3 Total 2,288 6,375 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Iramba 0 144 1,546 273 545 2,508 Singida Rural 684 . 787 996 996 3,464 Manyoni . . 81 81 242 403 Total 684 144 2,414 1,350 1,784 6,375 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.2 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.3 PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Households Raising Pig Households Not Raising Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 269 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 270 Number % age Number % age Number % age Iramba 9,318 29 22,368 71 31,687 100 Singida Rural 20,721 55 16,782 45 37,503 100 Manyoni 1,625 27 4,352 73 5,977 100 Singida Urban 2,439 48 2,648 52 5,086 100 Total 34,103 42 46,150 58 80,253 100 Number % Number % Number % Number % Iramba 5,527 31 7,336 29 2,688 33 1,122 20 Singida Rural 9,755 55 15,223 61 4,251 53 4,125 74 Manyoni 745 4 1,042 4 328 4 314 6 Singida Urban 1,685 10 1,357 5 761 9 33 1 Total 17,712 100 24,959 100 8,029 100 5,593 100 Number % age Number % age Number % age Iramba 20,152 65 10,718 35 30,870 100 Singida Rural 28,370 77 8,515 23 36,885 100 Manyoni 4,434 80 1,079 20 5,513 100 Singida Urban 3,419 63 1,979 37 5,399 100 Total 56,375 72 22,292 28 78,667 100 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultura households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs Yes Yes Yes Yes 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 271 Number % age Number % age Number % age Number % age Number % age Number % age Iramba 2,785 14 8,539 42 5,305 26 855 4 2,667 13 20,152 100 Singida Rural 11,155 39 12,247 43 1,249 4 245 1 3,474 12 28,370 100 Manyoni 919 21 1,636 37 1,315 30 227 5 337 8 4,434 100 Singida Urban 1,425 42 679 20 254 7 298 9 763 22 3,419 100 Total 16,285 29 23,101 41 8,123 14 1,625 3 7,241 13 56,375 100 Number % age Number % age Number % age Iramba 7,565 23.6 24,553 76 32,118 100 Singida Rural 8,494 24.1 26,786 76 35,279 100 Manyoni 1,977 33.6 3,916 66 5,893 100 Singida Urban 85 1.7 5,012 98 5,096 100 Total 18,120 23.1 60,266 77 78,387 100 Number % age Number % age Number % age Number % age Iramba 2,566 34 4,423 58 576 8 7,565 100 Singida Rural 4,788 56 3,205 38 500 6 8,494 100 Manyoni 983 50 911 46 83 4 1,977 100 Singida Urban 42 50 43 50 0 0 85 100 Total 8,380 46 8,581 47 1,159 6 18,120 100 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tsetse Flies Control None Spray Dipping Total 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultura households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Yea District Number of Agricultural Number of Agricultural Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tick Control None Spraying Dipping Smearing Other Total Tanzania Agriculture Census Survey 2003 Singida Region 272 Appendix II 273 OTHER LIVESTOCK Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 274 Breed Type Current Number Indigenous Chicken 1,643,973 Layer 7,589 Broiler 6,616 Ducks 35,013 Turkeys 7,501 Rabbits 840 Donkeys 16,649 Horse 0 Other 4,001 Total 1,722,182 Number No of Househ olds Number No of Households Number No of Househ olds Number No of Households Number No of House holds Iramba 8,357 1,549 . 0 . 0 12,295 3,821 1,142 427 Singida Rural 19,791 2,093 7,501 125 . 0 4,354 1,694 2,859 370 Manyoni 2,528 483 . 0 . 0 . 0 . 0 Singida Urban 4,336 85 . 0 840 42 . 0 . 0 Total 35,013 4,209 7,501 125 840 42 16,649 5,516 4,001 797 Singida Rural 2,099 3,586 5,685 Manyoni 5,490 . 5,490 Singida Urban . 3,030 3,030 Total 7,589 6,616 14,205 1 - 4 81,920 449 123 82,492 5 - 9 233,377 2,229 1,510 237,115 10 - 19 487,816 1,684 . 489,501 20 - 29 268,123 . 2,463 270,586 30 - 39 174,050 . . 174,050 40 - 49 82,720 3,228 . 85,947 50 - 99 159,744 . 2,520 162,264 100+ 156,222 . . 156,222 Total 1,643,973 7,589 6,616 1,658,178 Indigenous Chicken Layer Broiler Total Iramba 788,337 . . 788,337 49,729 Singida Rur 639,213 2,099 3,586 644,898 55,299 Manyoni 157,842 5,490 . 163,332 13,274 Singida Urb 58,581 . 3,030 61,611 7,520 Total 1,643,973 7,589 6,616 1,658,178 125,823 Total 23.1 OTHER LIVESTOCK: Total Number of Other Livestock by Breed and Type Flock Size Chicken Type 23.3 OTHER LIVESTOCK: Number of Chicken by Type and District District Chicken Type Indigenous Chicken Layer Broiler Layer Broiler Total 23.4 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size 23.2 OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Ducks Turkeys Rabbits Donkeys Other 23.4 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District District Chicken Type Households Keeping Chicken Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 275 LIVESTOCK PRODUCTS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 276 Sold Consumed / Utilised Sold Consumed / Utilised Sold Consumed / Utilised Iramba 4,321,619 2,516,280 37,940 1,728 16,053 998 Singida Rural 5,377,708 2,562,195 32,443 4,844 32,860 4,464 Manyoni 1,175,075 712,768 7,538 3,169 8,763 1,876 Singida Urban 524,729 283,580 4,270 379 2,350 997 Total 11,399,132 6,074,824 82,192 10,119 60,025 8,335 25.1 LIVESTOCK PRODUCTS: Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year District Product Name Eggs Hides Skins Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 277 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 278 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 13,748 8,149 960 1,571 978 25,406 Singida Rural 4,311 1,779 0 497 124 6,711 Manyoni 3,993 739 84 0 0 4,816 Singida Urban 633 297 0 0 0 931 Total 22,686 10,964 1,044 2,068 1,102 37,864 <5 Total Iramba 1,546 1,546 Singida Rural 1,358 1,358 Manyoni 2,406 2,406 Total 5,311 5,311 <5 5 - 9 10 - 14 Total Iramba 4,909 140 1,287 6,336 Singida Rural 6,199 125 0 6,324 Manyoni 2,315 0 0 2,315 Singida Urban 42 0 43 85 Total 13,465 265 1,330 15,060 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 21,328 4,439 843 0 137 26,746 Singida Rural 27,631 3,533 233 123 125 31,644 Manyoni 2,662 254 80 0 0 2,996 Singida Urban 2,794 126 0 0 0 2,921 Total 54,415 8,353 1,155 123 261 64,307 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 8,875 12,342 2,283 2,993 3,513 484 0 30,490 Singida Rural 10,427 9,425 4,442 4,765 3,532 605 0 33,196 Manyoni 5,428 4,070 1,919 1,871 1,499 1,171 164 16,121 Singida Urban 972 548 363 84 426 42 0 2,436 Total 25,703 26,385 9,006 9,714 8,970 2,303 164 82,245 District Distance to Nearest Primary Market 27.4 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Crush and District District Distance to Nearest Cattle Crush 27.5 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Primary Market and District District Distance to Nearest 27.3 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hand Powered Sprayer and District District Distance to Nearest Hand Powered Sprayer 27.1 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Dip and District District Distance to Nearest Cattle Dip 27.2 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Spray Raced and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 279 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Iramba 1,508 398 289 424 0 0 2,619 Singida Rural 1,966 3,945 1,837 2,205 981 605 11,539 Manyoni 2,310 0 169 83 0 0 2,562 Singida Urban 0 0 0 0 0 43 43 Total 5,784 4,342 2,295 2,713 981 648 16,763 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 1,551 0 0 0 0 143 0 1,694 Singida Rural 2,956 980 0 0 0 457 593 4,986 Manyoni 2,068 0 170 0 0 0 0 2,238 Singida Urban 75 784 842 593 85 0 0 2,379 Total 6,650 1,764 1,012 593 85 600 593 11,297 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Iramba 7,687 1,848 0 1,287 141 0 10,963 Singida Rural 11,386 2,025 0 493 474 860 15,239 Manyoni 2,035 531 85 169 254 0 3,074 Singida Urban 792 794 1,167 170 85 0 3,009 Total 21,901 5,198 1,251 2,120 954 860 32,284 <5 5 - 9 10 - 14 15 - 19 20 - 29 50+ Total Iramba 3,121 279 0 0 0 0 3,400 Singida Rural 4,899 1,227 0 0 946 241 7,312 Manyoni 2,151 0 85 169 254 0 2,660 Singida Urban 183 1,489 1,060 551 127 0 3,410 Total 10,354 2,996 1,145 720 1,327 241 16,782 District Distance to Nearest Slaughter Slab 27.9 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hide/ Skin Shade and District District Distance to Nearest Hide/ Skin Shade 27.7 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Abattoir and District District Distance to Nearest Abattoir 27.8 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Slaughter Slab and District 27.6 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Secondary Market and District District Distance to Nearest Secondary Market Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 280 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 3,104 1,261 0 424 422 289 1,121 6,621 Singida Rural 2,785 2,229 373 867 6,267 4,972 8,305 25,798 Manyoni 1,697 506 420 488 959 574 239 4,884 Singida Urban 183 1,560 1,742 847 381 42 42 4,798 Total 7,770 5,556 2,535 2,626 8,029 5,876 9,707 42,101 <5 5 - 9 10 - 14 20 - 29 30 - 49 50+ Total Iramba 2,120 433 286 0 0 675 3,514 Singida Rural 1,366 859 115 1,083 2,440 949 6,812 Manyoni 2,087 0 0 0 0 0 2,087 Singida Urban 0 192 0 0 0 0 192 Total 5,573 1,484 401 1,083 2,440 1,625 12,606 <5 5 - 9 10 - 14 20 - 29 Total Iramba 1,695 142 0 0 1,837 Singida Rural 2,917 0 0 487 3,404 Manyoni 2,257 0 0 0 2,257 Singida Urban 33 108 43 0 183 Total 6,902 250 43 487 7,681 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 7,938 282 0 0 0 8,220 Singida Rural 13,167 1,941 457 728 120 16,413 Manyoni 2,334 0 84 0 0 2,419 Singida Urban 1,134 42 0 0 0 1,175 Total 24,573 2,264 542 728 120 28,227 <5 5 - 9 10 - 14 15 - 19 Total Iramba 1,694 144 0 1,144 2,982 Singida Rural 5,479 855 0 0 6,334 Manyoni 2,251 0 0 0 2,251 Singida Urban 255 127 43 43 467 Total 9,678 1,126 43 1,187 12,034 District Distance to Nearest Drencher 27.13 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Watering Point/ Dam and Distric District Distance to Nearest Village Watering Point/ Dam 27.14 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Drencher and Distric District Distance to Nearest Veterinary Clinic 27.12 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Holding Gound and District District Distance to Nearest Village Holding Gound 27.10 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Input Supply and District District Distance to Nearest Input Supply 27.11 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Veterinary Clinic and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 281 FISH FARMING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 282 Number % Number % Iramba 62,528 100.0 62,528 100.0 Singida Rural 73,197 100.0 73,197 100.0 Manyoni 33,065 100.0 33,065 100.0 Singida Urban 11,125 100.0 11,125 100.0 Total 179,915 100.0 179,915 100.0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District g Households NOT Doing Fish Farming Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 283 LIVESTOCK EXTENSION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 284 Number % Number % Number % Iramba 21,420 34 41,109 66 62,528 100 Singida Rural 9,465 13 63,732 87 73,197 100 Manyoni 2,831 9 30,234 91 33,065 100 Singida Urban 2,476 22 8,650 78 11,125 100 Total 36,191 20 143,724 80 179,915 100 Government Total Iramba 11,956 11,956 Singida Rural 2,691 2,691 Manyoni 1,340 1,340 Singida Urban 807 807 Total 16,795 16,795 Government NGO / Development Project Total Iramba 11,309 144 11,453 Singida Rural 3,988 123 4,111 Manyoni 1,593 0 1,593 Singida Urban 807 0 807 Total 17,697 267 17,965 District Source of Advice District Source of Advice 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year 29.1 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year District Did Household receive livestock advice during 2002/03? Number of Agricultural Number of Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 285 Government NGO / Development Project Total Iramba 9,938 0 9,938 Singida Rural 2,463 123 2,586 Manyoni 248 0 248 Singida Urban 807 0 807 Total 13,457 123 13,580 Government NGO / Development Project Large Scale Farmer Total Iramba 10,760 0 0 10,760 Singida Rural 2,592 246 125 2,964 Manyoni 248 0 0 248 Singida Urban 850 0 0 850 Total 14,450 246 125 14,822 Government NGO / Development Project Large Scale Farmer Total Iramba 17,890 705 0 18,594 Singida Rural 6,898 123 120 7,141 Manyoni 1,913 0 0 1,913 Singida Urban 2,306 0 0 2,306 Total 29,007 828 120 29,955 District Source of Advice 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 286 Government NGO / Development Project Large Scale Farmer Total Iramba 11,532 697 0 12,229 Singida Rural 2,565 0 125 2,690 Manyoni 918 0 0 918 Singida Urban 1,522 0 0 1,522 Total 16,537 697 125 17,359 Government NGO / Development Project Large Scale Farmer Total Iramba 12,060 417 0 12,477 Singida Rural 3,038 123 485 3,646 Manyoni 337 0 0 337 Singida Urban 1,084 0 0 1,084 Total 16,520 540 485 17,545 Government NGO / Development Project Total Iramba 12,342 849 13,191 Singida Rural 2,935 123 3,058 Manyoni 1,261 0 1,261 Singida Urban 797 0 797 Total 17,336 972 18,308 District Source of Advice 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 District Source of Advice 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 287 Government NGO / Development Project Total Iramba 8,722 280 9,003 Singida Rural 3,209 246 3,455 Manyoni 1,095 0 1,095 Singida Urban 1,147 0 1,147 Total 14,173 527 14,700 Government NGO / Development Project Total Iramba 8,458 0 8,458 Singida Rural 3,281 123 3,404 Manyoni 925 0 925 Singida Urban 1,307 0 1,307 Total 13,971 123 14,094 Number % Number % Number % Number % Number % Number % Iramba 3,716 15 17,657 70 3,547 14 287 1 143 1 25,349 100 Singida Rural 2,399 17 7,200 50 971 7 1,713 12 2,165 15 14,448 100 Manyoni 255 12 1,659 80 169 8 0 0 0 0 2,083 100 Singida Urban 255 7 1,608 43 657 18 298 8 892 24 3,709 100 Total 6,625 15 28,123 62 5,344 12 2,297 5 3,199 7 45,588 100 District Quality of Service Very Good Good Average Poor No Good Total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, District Source of Advice 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 288 Number % Number % Number % Number % Number % Number % Iramba 21,420 20 21,420 20 21,420 20 21,420 20 21,420 20 107,098 100 Singida Rural 9,465 20 9,465 20 9,465 20 9,465 20 9,465 20 47,324 100 Manyoni 2,831 20 2,746 20 2,746 20 2,746 20 2,746 20 13,815 100 Singida Urban 2,476 20 2,476 20 2,476 20 2,476 20 2,476 20 12,378 100 Total 36,191 20 36,106 20 36,106 20 36,106 20 36,106 20 180,614 100 Number % Number % Number % Iramba 9,462 25 27,840 75 37,301 100 Singida Rural 4,010 25 12,267 75 16,278 100 Manyoni 413 15 2,335 85 2,749 100 Singida Urban 457 8 5,103 92 5,561 100 Total 14,343 23 47,545 77 61,888 100 29.14LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Number of Agricultural Number of Total 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural District Extension Provider Government NGO / Co-operative Large Scale Farmer Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 289 GOVERNMENT REGULATORY PROBLEMS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 290 Number % Number % Number % Iramba 2,525 4 59,860 96 62,385 100 Singida Rural 3,439 5 66,649 95 70,089 100 Manyoni 240 1 32,825 99 33,065 100 Singida Urban 150 1 10,891 99 11,041 100 Total 6,355 4 170,225 96 176,580 100 30.1 GOVERNMENT REGULATORY PROBLEMS: Number of Agricultural Households by Whether Face Problems with Governmet Regulation During 2003/04 by District, 2002/03 Agricultural Year District Did you face problems with Govt regulations during 02/03? Yes No Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 291 LABOUR USE Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 292 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 54,565 19,376 6,538 69,970 1,247 0 586 21,120 3,097 176,501 Soil Preparation by Hand 35,810 9,866 9,908 79,982 779 84 270 25,089 1,772 163,560 Soil Preparation bu Oxen / Tractor 14,219 5,928 1,798 37,946 687 143 422 12,644 2,548 76,334 Planting 18,637 2,831 24,028 83,682 846 250 2,626 44,878 574 178,353 Weeding 13,748 2,297 5,653 89,692 764 84 349 60,636 4,419 177,643 Crop Protection 11,158 2,785 5,012 55,314 1,634 703 7,169 57,773 1,058 142,606 Harvesting 14,349 1,785 4,955 82,224 706 126 697 67,263 1,992 174,096 Crop Processing 15,379 2,752 80,060 31,703 1,452 5,092 6,710 11,388 125 154,659 Crop Marketing 64,776 6,159 4,293 28,363 787 0 370 3,207 125 108,080 Cattle Rearing 35,224 5,508 1,352 11,955 1,357 376 648 7,362 210 63,992 Cattle Herding 23,799 10,130 2,739 9,645 9,198 2,580 6,244 7,638 1,465 73,437 Cattle Marketing 37,537 5,531 924 5,591 433 0 261 694 0 50,971 Goat & Sheep Rearing 26,388 6,140 1,480 9,995 765 433 739 9,816 43 55,797 Goat & Sheep Herding 17,254 8,694 1,926 7,796 6,549 1,981 7,416 10,400 1,399 63,415 Goat & Sheep Marketing 31,570 4,950 1,005 5,239 539 0 342 841 140 44,626 Milking 3,297 1,561 37,336 4,593 1,035 388 2,060 3,726 0 53,996 Pig Rearing 1,622 582 282 691 125 43 123 633 0 4,099 Poultry Keeping 23,688 1,154 21,890 25,315 474 414 1,523 44,019 0 118,477 Collecting Water 13,802 3,209 104,317 16,505 1,475 7,846 11,485 16,225 269 175,134 Collecting Firewood 19,845 4,616 111,881 14,754 1,685 6,384 5,788 10,450 480 175,884 Pole Cutting 54,206 35,091 2,614 4,338 2,124 143 144 616 4,677 103,953 Timber Wood Cutting 2,885 4,472 0 735 0 0 0 0 168 8,260 Building / Maintaining Houses 62,937 32,313 3,062 19,233 1,754 267 185 7,864 5,586 133,200 Making Beer 7,653 1,571 48,381 1,901 42 208 0 143 0 59,899 Beekeeping 6,891 2,117 287 127 0 0 0 118 0 9,541 Fishing 5,449 351 0 271 461 0 43 0 0 6,574 Fish Farming 242 0 0 246 0 0 0 0 0 488 Off - farm Income Generation 60,093 3,460 22,367 42,522 3,511 1,733 955 2,532 155 137,328 31.1 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Activity Type of Household Member Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 293 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 31 11 4 40 1 0 0 12 2 100 Soil Preparation by Hand 22 6 6 49 0 0 0 15 1 100 Soil Preparation bu Oxen / Tractor 19 8 2 50 1 0 1 17 3 100 Planting 10 2 13 47 0 0 1 25 0 100 Weeding 8 1 3 50 0 0 0 34 2 100 Crop Protection 8 2 4 39 1 0 5 41 1 100 Harvesting 8 1 3 47 0 0 0 39 1 100 Crop Processing 10 2 52 20 1 3 4 7 0 100 Crop Marketing 60 6 4 26 1 0 0 3 0 100 Cattle Rearing 55 9 2 19 2 1 1 12 0 100 Cattle Herding 32 14 4 13 13 4 9 10 2 100 Cattle Marketing 74 11 2 11 1 0 1 1 0 100 Goat & Sheep Rearing 47 11 3 18 1 1 1 18 0 100 Goat & Sheep Herding 27 14 3 12 10 3 12 16 2 100 Goat & Sheep Marketing 71 11 2 12 1 0 1 2 0 100 Milking 6 3 69 9 2 1 4 7 0 100 Pig Rearing 40 14 7 17 3 1 3 15 0 100 Poultry Keeping 20 1 18 21 0 0 1 37 0 100 Collecting Water 8 2 60 9 1 4 7 9 0 100 Collecting Firewood 11 3 64 8 1 4 3 6 0 100 Pole Cutting 52 34 3 4 2 0 0 1 4 100 Timber Wood Cutting 35 54 0 9 0 0 0 0 2 100 Building / Maintaining Houses 47 24 2 14 1 0 0 6 4 100 Making Beer 13 3 81 3 0 0 0 0 0 100 Beekeeping 72 22 3 1 0 0 0 1 0 100 Fishing 83 5 0 4 7 0 1 0 0 100 Fish Farming 50 0 0 50 0 0 0 0 0 100 Off - farm Income Generation 44 3 16 31 3 1 1 2 0 100 Activity Type of Household Member 31.2 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Tanzania Agriculture Census Survey 2003 Singida Region 294 Appendix II 295 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 296 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 11,882 36,304 14,068 273 0 62,528 Singida Rural 9,510 35,326 25,735 1,791 835 73,197 Manyoni 8,195 10,762 11,131 2,000 978 33,065 Singida Urban 1,693 5,745 3,688 0 0 11,125 Total 31,280 88,137 54,621 4,064 1,813 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 1,232 5,718 23,977 11,408 20,193 62,528 Singida Rural 1,661 2,442 24,384 20,053 24,656 73,197 Manyoni 993 2,783 7,253 8,734 13,302 33,065 Singida Urban 681 282 3,928 5,686 549 11,125 Total 4,566 11,225 59,542 45,881 58,701 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 5,586 14,406 34,495 3,252 4,789 62,528 Singida Rural 3,748 15,517 39,001 8,044 6,887 73,197 Manyoni 6,948 7,009 11,943 5,193 1,972 33,065 Singida Urban 647 2,857 6,965 657 0 11,125 Total 16,929 39,790 92,403 17,146 13,648 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 282 255 9,151 8,931 43,909 62,528 Singida Rural 363 487 5,949 7,171 59,226 73,197 Manyoni 167 1,093 3,985 8,247 19,572 33,065 Singida Urban 0 108 4,051 6,118 848 11,125 Total 812 1,944 23,136 30,467 123,556 179,915 District Distance (Kilometer) to Hospital District Distance (Kilometer) to Health Clinic 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary School 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 297 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 144 0 2,291 1,978 58,115 62,528 Singida Rural 122 0 2,342 235 70,498 73,197 Manyoni 168 85 763 4,010 28,038 33,065 Singida Urban 85 98 3,425 6,543 974 11,125 Total 520 183 8,821 12,765 157,625 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 430 141 430 711 60,816 62,528 Singida Rural 740 0 2,341 235 69,882 73,197 Manyoni 80 0 165 247 32,573 33,065 Singida Urban 33 140 3,435 6,544 975 11,125 Total 1,282 281 6,370 7,737 164,245 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 26,122 24,111 11,603 137 556 62,528 Singida Rural 25,961 29,013 16,325 1,057 841 73,197 Manyoni 16,281 12,524 3,925 334 0 33,065 Singida Urban 4,519 5,101 1,505 0 0 11,125 Total 72,882 70,750 33,358 1,528 1,397 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 19,816 17,288 18,627 2,137 4,660 62,528 Singida Rural 13,508 18,074 27,299 7,712 6,603 73,197 Manyoni 9,449 4,995 11,963 4,571 2,087 33,065 Singida Urban 2,386 3,915 4,825 0 0 11,125 Total 45,159 44,271 62,714 14,420 13,351 179,915 District Distance (Kilometer) to Feeder Road District Distance (Kilometer) to ALL Wealther Road 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to Districtal Capital 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feede Road and District, 2002/03 Agricultural Yea 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to District Capital 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Distric Capital and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 298 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 15,128 144 429 0 46,827 62,528 Singida Rural 29,500 367 496 483 42,351 73,197 Manyoni 3,936 0 0 0 29,129 33,065 Singida Urban 8,034 151 587 590 1,764 11,125 Total 56,597 662 1,512 1,073 120,071 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 17,482 5,324 30,514 2,533 6,675 62,528 Singida Rural 11,921 13,204 26,607 9,016 12,449 73,197 Manyoni 3,030 3,977 17,925 5,279 2,853 33,065 Singida Urban 2,819 1,960 5,547 800 0 11,125 Total 35,253 24,465 80,593 17,628 21,977 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 3,303 3,008 38,308 10,099 7,811 62,528 Singida Rural 1,545 4,884 31,897 21,780 13,090 73,197 Manyoni 2,324 2,958 10,886 8,793 8,103 33,065 Singida Urban 4,055 0 2,759 3,310 1,001 11,125 Total 11,228 10,850 83,849 43,983 30,005 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 6,933 1,791 8,267 2,405 43,133 62,528 Singida Rural 1,956 539 3,752 3,205 63,746 73,197 Manyoni 495 734 2,409 5,856 23,571 33,065 Singida Urban 245 66 3,679 6,372 763 11,125 Total 9,629 3,129 18,107 17,839 131,212 179,915 District Distance (Kilometer) to Tertiary Market 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Primary Market District Distance (Kilometer) to Secondary Market 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tarmac Road 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 299 <5 5 - 9 10 - 14 15 - 19 30 - 49 50 + Total Iramba 2,443 0 143 0 0 124 2,710 Singida Rural 34,812 123 0 0 616 858 36,409 Manyoni 2,708 0 0 0 0 85 2,793 Singida Urban 7,404 42 0 43 0 0 7,489 Total 47,368 165 143 43 616 1,067 49,401 <5 5 - 9 10 - 14 15 - 19 30 - 49 50 + Total Iramba 2,429 0 0 143 0 0 2,572 Singida Rural 36,183 244 123 123 371 488 37,532 Manyoni 2,962 0 0 0 0 0 2,962 Singida Urban 7,522 0 0 0 0 0 7,522 Total 49,097 244 123 266 371 488 50,589 <5 20 - 29 30 - 49 50 + Total Iramba 2,306 143 0 124 2,572 Singida Rural 35,681 125 125 373 36,304 Manyoni 2,708 0 0 0 2,708 Singida Urban 7,479 0 0 0 7,479 Total 48,174 268 125 496 49,063 <5 30 - 49 50 + Total Iramba 2,306 0 124 2,429 Singida Rural 35,323 618 739 36,680 Manyoni 2,708 0 0 2,708 Singida Urban 7,564 0 0 7,564 Total 47,901 618 863 49,382 District Distance (Kilometer) to Plant Protection Lab District Distance (Kilometer) to Research Station 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultura Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultura Households by Distance to Research Station and District, 2002/03 Agricultural Year District Distance (Kilometer) to Veterinary Clinic District Distance (Kilometer) to Extension Center 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 300 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Iramba 256 2,149 2,253 0 4,914 11,370 41,444 62,386 Singida Rural 1,565 1,841 834 120 11,560 31,525 25,264 72,710 Manyoni 243 510 1,605 2,733 1,793 7,243 18,938 33,065 Singida Urban 84 3,337 4,606 1,777 849 42 74 10,769 Total 2,148 7,838 9,298 4,630 19,116 50,179 85,720 178,930 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Iramba 1,004 2,003 2,282 5,716 1,952 13,889 35,178 62,025 Singida Rural 35,556 246 246 0 125 36,044 610 72,827 Manyoni 2,723 0 0 0 0 30,342 0 33,065 Singida Urban 7,683 42 43 0 0 3,315 0 11,083 Total 46,965 2,292 2,571 5,716 2,077 83,590 35,788 179,000 Very Good Good Average Poor No good Not applicable Total Iramba 1,929 17,167 8,441 576 2,535 344,521 375,170 Singida Rural 1,570 1,213 3,643 13,580 21,515 397,660 439,181 Manyoni 723 417 587 254 0 196,408 198,389 Singida Urban 42 84 288 2,712 184 63,443 66,752 Total 4,264 18,881 12,960 17,121 24,234 1,002,032 1,079,492 Very Good Good Average Poor Total Iramba 105 124 0 0 229 Singida Rural 365 125 245 125 860 Manyoni 85 417 169 0 672 Total 556 666 414 125 1,761 District Satisfaction of Using Veterinary Clinic 33.20 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Extension Center District Distance (Kilometer) to Livestock Development Center 33.19 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center District Distance (Kilometer) to Land Registration Office 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 301 Very Good Poor Total Iramba 105 0 105 Singida Rural 241 249 491 Manyoni 78 0 78 Total 424 249 674 Very Good Good Poor No good Total Iramba 510 0 0 0 510 Singida Rural 471 123 722 123 1,439 Manyoni 255 0 0 0 255 Singida Urban 0 0 42 0 42 Total 1,236 123 764 123 2,246 Very Good Good Average Poor No good Total Iramba 527 9,226 4,363 144 1,268 15,529 Singida Rural 246 965 2,903 11,863 21,277 37,254 Manyoni 84 0 333 254 0 671 Singida Urban 42 84 245 2,627 141 3,139 Total 899 10,275 7,845 14,888 22,686 56,593 Very Good Good Average Poor No good Total Iramba 287 7,817 4,078 432 1,268 13,881 Singida Rural 122 0 370 0 0 493 Manyoni 143 0 0 0 0 143 Singida Urban 0 0 43 42 43 128 Total 552 7,817 4,491 474 1,310 14,644 33.24 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center District Satisfaction of Using Livestock Development Center District Satisfaction of Using Plant Protection Lab 33.23 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Satisfaction of Using Land Registration Office 33.21 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Satisfaction of Using Research 33.22 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 302 Appendix II 303 HOUSEHOLD FACILITIES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 304 District Number of rooms Iron Sheet Tiles Asbestos Grass/leaves Grass/mud Other Total Iramba 3 12,985 20.8 0 0.0 0 0.0 1,488 2.4 48,055 76.9 0 0.0 62,528 Singida Rural 3 15,651 21.4 125 0.2 236 0.3 4,343 5.9 52,230 71.4 612 0.8 73,197 Manyoni 3 6,031 18.2 81 0.2 167 0.5 3,610 10.9 23,176 70.1 0 0.0 33,065 Singida Urban 2 2,580 23.2 0 0.0 0 0.0 253 2.3 8,292 74.5 0 0.0 11,125 Total 3 37,246 21 206 0.1 403 0.2 9,695 5.4 131,753 73.2 612 0.3 179,915 Yes No Total Yes No Total Yes No Total Yes No Total Iramba 25,945 41 36,584 62,528 133 0.2 62,395 62,528 133 0.2 62,395 62,528 7,936 13 54,593 62,528 Singida Rural 23,577 32 49,620 73,197 364 0.5 72,833 73,197 1,096 1.5 72,101 73,197 8,958 12 64,239 73,197 Manyoni 16,050 49 17,015 33,065 0 0.0 33,065 33,065 84 0.3 32,981 33,065 3,758 11 29,307 33,065 Singida Urban 3,903 35 7,222 11,125 108 1.0 11,017 11,125 150 1.3 10,976 11,125 1,148 10 9,977 11,125 Total 69,474 39 110,441 179,915 605 0.3 179,310 179,915 1,463 0.8 178,452 179,915 21,799 12 158,116 179,915 Yes No Total Yes No Total Yes No Total Yes No Total Iramba 1,655 3 60,874 62,528 21,454 34 41,075 62,528 800 1.3 61,728 62,528 552 0.9 61,976 62,528 Singida Rural 4,665 6 68,532 73,197 18,667 26 54,530 73,197 366 0.5 72,830 73,197 121 0.2 73,075 73,197 Manyoni 1,280 4 31,785 33,065 10,909 33 22,156 33,065 255 0.8 32,810 33,065 85 0.3 32,980 33,065 Singida Urban 403 4 10,722 11,125 2,835 25 8,291 11,125 43 0.4 11,083 11,125 43 0.4 11,083 11,125 Total 8,003 4 171,912 179,915 53,864 30 126,051 179,915 1,464 0.8 178,451 179,915 801 0.4 179,114 179,915 cont….HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Bicycle District Television / Video Wheelbarrow Vehicle 34.1: HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year 34.2: HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Iron District Radio Mobile phone Landline phone Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 305 District Mains Electricity Solar Gas (Biogas) Hurricane Lamp Pressure Lamp Wick Lamp Firewood Other Total Iramba 0 0.0 144 0 10,745 22.3 2,386 48,118 992 1.6 143 62,528 Singida Rural 118 0.2 125 118 5,832 9.6 968 61,007 5,028 6.9 0 73,197 Manyoni 0 0.0 0 0 4,327 17.4 573 24,935 3,070 9.3 161 33,065 Singida Urban 0 0.0 0 0 678 7.0 403 9,635 410 3.7 0 11,125 Total 118 0.1 269 118 21,581 15.0 4,330 143,694 9,499 5.3 304 179,915 District Mains Electricity Solar Bottled Gas Parraffin / Kerocine Charcoal Firewood Crop Residues Livestock Dung Total Iramba 0 432 0 143 0.2 1,355 59,894 561 0.9 143 62,528 Singida Rural 373 124 103 0 0.0 1,228 67,855 3,513 4.8 0 73,197 Manyoni 0 85 0 0 0.0 412 32,483 85 0.3 0 33,065 Singida Urban 75 0 0 0 0.0 108 10,899 43 0.4 0 11,125 Total 448 641 103 143 0.1 3,104 171,131 4,202 2.3 143 179,915 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Other Total Iramba 12,223 7,144 285 20,133 1,566 16,574 286 18.2 2,749 1,568 62,528 Singida Rural 6,876 14,352 731 23,046 11,033 6,630 0 0.0 10,530 0 73,197 Manyoni 11,506 1,329 255 9,693 999 4,231 162 65.1 4,642 249 33,065 Singida Urban 1,156 4,437 277 3,421 762 735 0 0.0 337 0 11,125 Total 31,761 27,262 1,548 56,293 14,360 28,170 447 24.6 18,257 1,816 179,915 34.3: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year 34.4: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year 34.5: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 306 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Iramba 4,765 6,403 3,213 14,562 20,662 9,064 2,421 1,439 0 62,528 Singida Rural 5,153 5,007 2,686 19,011 30,124 7,304 3,416 495 0 73,197 Manyoni 735 5,516 2,754 7,141 10,045 4,387 1,825 579 83 33,065 Singida Urban 208 1,231 718 2,665 4,491 1,472 255 85 0 11,125 Total 10,861 18,157 9,370 43,379 65,322 22,227 7,917 2,598 83 179,915 District Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Iramba 3,085 11,438 3,863 22,796 3,487 1,689 16,169 62,528 Singida Rural 736 13,605 6,752 25,452 5,796 3,189 17,666 73,197 Manyoni 574 7,719 2,316 8,935 2,082 2,321 9,116 33,065 Singida Urban 124 1,706 1,605 4,461 1,047 126 2,056 11,125 Total 4,519 34,469 14,537 61,645 12,413 7,326 45,006 179,915 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Total HH Iramba 13,929 8,533 285 15,302 1,566 16,926 143 5,843 0 62,528 Singida Rural 8,236 16,787 608 25,727 12,065 4,658 363 4,633 120 73,197 Manyoni 12,676 1,327 332 11,845 1,466 3,363 78 1,979 0 33,065 Singida Urban 1,240 4,479 362 3,419 804 611 0 210 0 11,125 Total 36,081 31,126 1,587 56,292 15,900 25,559 584 12,666 120 179,915 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Iramba 2,066 5,684 2,357 10,999 22,113 8,486 7,822 3,002 0 62,528 Singida Rural 2,798 3,913 1,586 12,095 25,516 11,981 10,650 4,040 618 73,197 Manyoni 160 3,448 1,853 5,507 9,705 5,144 3,031 3,964 253 33,065 Singida Urban 168 1,062 845 2,338 4,407 1,680 424 200 0 11,125 Total 5,192 14,107 6,641 30,939 61,741 27,291 21,926 11,206 871 179,915 34.9: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34.6: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.7: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.8: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 307 District Less than 10 Minutes 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Iramba 1,107 7,107 3,008 16,109 3,037 1,407 30,754 62,528 Singida Rural 866 7,517 4,191 15,228 5,381 1,224 38,789 73,197 Manyoni 248 5,610 1,796 6,279 2,085 2,001 15,046 33,065 Singida Urban 41 902 1,104 3,267 1,379 259 4,173 11,125 Total 2,262 21,136 10,099 40,882 11,882 4,891 88,763 179,915 District No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Iramba 1,183 280 60,799 266 0 62,528 Singida Rural 5,363 5,607 61,728 248 250 73,197 Manyoni 4,860 328 27,643 152 82 33,065 Singida Urban 833 790 9,333 128 43 11,125 Total 12,238 7,005 159,503 794 375 179,915 34-10: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34-11: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 308 District One Two Three Four Total Iramba 704 30,420 31,405 0 62,528 Singida Rural 3,474 58,471 11,014 237 73,197 Manyoni 973 21,265 10,744 82 33,065 Singida Urban 258 9,519 1,306 42 11,125 Total 5,409 119,676 54,469 361 179,915 District Not Eaten One Two Three Four Five Six Seven Total Iramba 17,581 21,534 15,431 6,189 1,128 257 142 266 62,528 Singida Rural 22,390 29,715 14,543 4,252 1,213 719 120 245 73,197 Manyoni 16,771 8,163 5,570 1,674 245 569 0 74 33,065 Singida Urban 4,487 3,361 2,197 490 506 42 0 42 11,125 Total 61,228 62,773 37,741 12,604 3,092 1,587 262 628 179,915 District Not Eaten One Two Three Four Five Six Seven Total Iramba 28,811 16,901 13,224 1,558 603 520 316 596 62,528 Singida Rural 26,527 23,590 10,377 5,508 3,028 2,628 827 712 73,197 Manyoni 28,469 3,064 1,040 0 0 161 0 330 33,065 Singida Urban 4,463 3,541 2,069 701 202 107 0 42 11,125 Total 88,270 47,096 26,710 7,767 3,833 3,416 1,143 1,681 179,915 34-12: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year 34-13: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year 34-14: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 309 District Never Seldom Sometimes Often Always Total Iramba 16,052 23,248 3,497 8,186 11,545 62,528 Singida Rural 25,746 24,209 4,382 9,906 8,954 73,197 Manyoni 9,745 9,984 1,406 8,684 3,245 33,065 Singida Urban 3,519 3,585 361 2,928 733 11,125 Total 55,062 61,025 9,646 29,705 24,478 179,915 District Sales of Food Crops Sale of Livestock Sale of Livestock Products Sales of Cash Crops Sale of Forest Products Business Income Wages & Salaries in Cash Other Casual Cash Earnings Cash Remittance Fishing Other Total Iramba 2,577 12,554 557 13,065 2,393 3,935 2,735 16,918 6,445 633 717 62,528 Singida Rural 9,121 12,885 471 12,975 3,441 7,166 1,820 21,991 2,833 495 0 73,197 Manyoni 4,280 2,875 0 1,913 4,493 6,252 802 10,702 1,748 0 0 33,065 Singida Urban 411 1,316 211 1,149 1,429 1,819 170 3,670 822 85 42 11,125 Total 16,389 29,629 1,239 29,102 11,756 19,172 5,528 53,280 11,848 1,213 760 179,915 34-16: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year 34-15: HOUSEHOLD FACILITIES: Number of Agricultural Households Reportin the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 310 APPENDIX III QUESTIONNAIRES Appendix III 311 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 312 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 313 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 314 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 315 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 316 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 317 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 318 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 319 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 320 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 321 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 322 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 323 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 324 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 325 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 326 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 327 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 328 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 329 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 330 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 331 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 332 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 333 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source \"a\" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 334 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 335 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 336 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 337 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 338 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 339 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 340 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 341 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 342 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 343 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 344 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 345 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 346 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 347 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 348 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 349 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 350 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 351 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 352 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 353 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 354 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 355 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 356 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":176,"cells":{"data":{"kind":"string","value":"# Extracted Content Southern Maasai Agropastoral Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Southern Maasai Agro-Pastoral1 Livelihood Zone (TLZ 01) February, 20162 Zone Description The Southern Maasai Agropastoral Livelihood Zone covers an extensive area in north eastern Tanzania, including much of the traditional Maasai grazing lands. The administrative units that make up this zone include Simanjiro and Kiteto districts in Manyara Region; parts of Same and Mwanga districts in Kilimanjaro Region; and Kilindi District in Tanga Region3. The main ethnic group living here is the Maasai. The population density is only around 7 people per km2; so although this is a large zone geographically, the population that makes up the zone is relatively small compared to the rest of Tanzania. This livelihood zone consists of lowland plains, found between 400 and 600 meters, and covered with acacia- commiphora woodlands, grasslands and thickets. Extensive plains dotted with acacia trees are typical, and the Maasai who live here share their land with large herds of wildlife, concentrated especially in the Tarangire National Park and the Makame Wildlife Management Area. The Pangani River runs through the zone on its way to the Indian Ocean, providing year-round access to water for those who live close by. Tanzanite mines, found to the north of the zone, have been a source of cash income for some within the area over the past several decades; and there is some traditional mining of green tourmaline in isolated parts of Simanjiro District. This semi-arid expanse has been the home of Maasai pastoralists for centuries. The two rainy seasons – the vuli from November to January and the masika from March to May - generally bring no more than 500-650 mm of rainfall combined. Droughts are not uncommon, occurring on average once every three years. Crop production is a relatively new phenomenon here, dating back to the late 1970s when pastoralists were encouraged to settle and cultivate as part of the national villagisation programme, which came about as a result of the Ujamaa policies of the Arusha Declaration. Pastoralists began cultivating in earnest in the 1990s when terms of trade between livestock and grain became increasingly unfavourable, and when increasing land pressure related to a period of intense land grabbing by large multinational interests led the Maasai to 1 The original name of this zone was the Southern Maasai Pastoral Livelihood Zone; after the field work completed in this phase the team members have suggested re-naming it the Southern Maasai Agropastoral Livelihood Zone to convey the large role agriculture now has. 2 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 3 The livelihood zone boundaries should be redrawn to exclude some of the southern parts of the zone, in particular Sunya and Dongo wards, which do not share many of the characteristics described in this profile, and are more agricultural than pastoral. Southern Maasai Agropastoral Livelihood Zone Profile 2 stake their claims by beginning to cultivate large tracts of land. As it became more and more profitable to grow maize and beans on their land, the local population began to see this production as a means of protecting and increasing their herds, since the more of one’s own food one produced, the fewer animals needed to be sold to secure food4. Livestock production still forms the foundation of the local economy. Huge herds of cattle, goats and sheep are sustained here, grazing freely, and also benefitting from crop residues after the harvest. Households also grow maize and beans, both entirely rain-fed. The soils are fertile, consisting of sandy loams and clay, and people here do not use fertilizers or even manure. When clearing new fields all wealth groups use hand hoes and fires. Land is prepared by hand amongst the poorer wealth groups and using hired labour or by tractor for better off households. Ox ploughs are generally not used. The most labour intensive activities include land preparation, weeding, harvesting and fence making (with the branches of thorny acacia trees) to protect crops from wild animals. For these tasks middle and better off households hire members of poorer households to work for them in their much larger fields. Some labour (generally men from poor families) also migrates into the zone from Singida and Dodoma. Managing large herds in addition to large tracts of land creates a steady demand for seasonal labour. Livestock provide a critical source of food and cash for all households. Cattle are at the centre of the local economy and are critical to Maasai culture, binding families together through marriage and labour relations, and providing the currency by which people’s status is measured. Cattle provide milk for consumption and sale and they are a sort of bank account, drawn down on every year to provide cash for a range of basic necessities. Goats and sheep are also kept here, eaten especially during the festival season (from July through September) and when women give birth. They are also sold for cash income when smaller amounts of cash are needed. Chickens are used for eggs, eaten throughout the year, and they are sold whenever cash is needed. Rainy season water sources for livestock include seasonal ponds and rivers as well as shallow wells dug in seasonal river beds. In the dry season, livestock rely on village taps and shallow wells. Middle and better off households pay to keep the pumps going that keep this water flowing; and they also pay to transport water for their livestock. Men are responsible for taking care of cattle, goats and sheep, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots and fewer livestock, depend on seasonal agricultural labour - land clearing, ploughing, planting, weeding and harvesting - to generate cash income. They also piece together supplemental cash resources in the dry season collecting and selling poles for building, or engaging in petty trade – buying and selling small commodities like tobacco, soda, salt and sugar. This livelihood zone is far from urban centres and service provision here is poor. Water is obtained from open wells and ponds which are almost never clean or safe. Village taps, which require a fee, are used by some. In the dry season middle and better off households pay to pump and transport water from wells. Sanitation facilities consist of uncovered pit latrines; there is no organized garbage collection. There are very few health dispensaries, and even those that exist are not well stocked. People turn to traditional healers (called wakunga) in the absence of more modern alternatives. Primary schools are found in the villages, but these are 7-12 kilometres away for many people. Secondary schools are available in the ward centres, which are even more distant. There is no electricity in this zone. Households depend on battery-operated torches and solar lanterns for light. Households in all wealth groups have mobile phones, with better off households having multiple phones, although the cellular network is quite bad. People do not have access to credit here. In some villages, including Makame, Naberere, Emboret and Sukoro a savings scheme is available, providing households with a small return at the end of the year on weekly set-asides. A number of NGOs operate here, including Urban Crust Support, which provides a focus on education, health facilities and water infrastructure; UCTR, helping with land management; and the Heifer Project, supporting livestock production and especially poultry. 4 Boudreau, T., Household Food Economy Assessment, Arusha Region, Save the Children, 1999 Southern Maasai Agropastoral Livelihood Zone Profile 3 Markets The transportation infrastructure in this zone is relatively poor. The zone is far from urban centres and roads are few and far between. The main roads link the zone to Arusha via Simanjiro and Kiteto; further connections are made to Kijungu, Sunya and Songe in Kilindi. Rough dirt roads provide access to vehicles during the dry season, but these are washed away in the wet season, when even main roads become impassable. There are no bridges and rafts are used to cross the Pangani River in spots where people are unable to wade across. Well-worn dirt tracks take people by foot from villages to cultivated fields, pastures and water points. Donkeys are owned by all households, and these are used to carry goods and people. Motorbikes are the other main means of transportation, but these are owned by only better off households. Maize, beans, cattle, goats and sheep are the commodities sold by households in this zone. Crops are bought up at the farm gate by traders who flock to the area in the post-harvest months, from August to September. These traders arrange for crops to be transported out of the zone on trucks, which can travel on the dirt roads in the dry season. Maize makes its way to Kibaigwa in Dodoma Region and then on to other countries in the region, including Kenya, Uganda, Ethiopia, Rwanda and Sudan. Beans are transported to Arusha or Dodoma first and then on to Dar es Salaam. Cattle, goats and sheep are sold at small weekly ward- and sub-ward level markets within the zone throughout the year. Traders collect large numbers of animals near the road and then truck them on to their final destination. Dar es Salaam is the terminal market for most of the livestock. In addition to the market for commodities supplied by households from the zone, there is a market for food brought into the zone for consumption by local households. Poorer households need to buy maize grain to cover their needs for four to nine months of the year, even in good production years. Maize is the cheapest local staple, and most of this is locally sourced, procured from better off households who generally produce a large surplus. Rice, purchased almost exclusively by the upper wealth groups, is sourced from Shinyanga or Mbeya Region (Kyela) or Morogoro Region and distributed via the Dodoma market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks, often owned by poor or middle households. The labour market is almost entirely local. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms. An additional 5% of labour demand came from local towns and the final 5% came from outside the livelihood zone. Both men and women from poorer households take on paid agricultural work. There are three peak periods of labour demand: November through February for land clearing, land preparation and planting; February through April for weeding; and June through August for harvesting. Demand for labour is so high that there is some labour migration into the zone from other areas to help with ploughing and weeding. A small number of people also find work outside the zone, in the Tanzanite mines in Mereran. In bad years, the demand for local agricultural labour especially for weeding and harvesting, contracts. As a result, people try to find additional work in other zones, or in the mining area. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Southern Maasai Agropastoral Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the planting season in November/December and ends with the harvest in March-June of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average Southern Maasai Agropastoral Livelihood Zone Profile 4 rains, average crop yields and normal food prices. The reference year, however, followed three below average years, and so the baseline information presented in this profile, provides a view into how households in this livelihood zone make ends meet in an average year, but in the process of recovering from a series of below average years. Production Year Rank Critical Events 2014-2015 2 Below average crop and livestock production; high staple food prices and low livestock prices. Increased reliance on livestock sales, casual labour and labour migration. 2013-2014 3 Average rains, average crop yields, average food prices 2012-2013 3 Average rains, average crop yields, average food prices 2011-2012 2 Poor crop and livestock production, high staple food prices, low livestock prices. Increased livestock sales, increased reliance on casual labour and labour migration. 2010-2011 2 Poor crop and livestock production, high staple food prices, low livestock prices. Increased livestock sales, increased reliance on casual labour and labour migration. 2009 - 2010 1 Drought, high staple food prices, no crop harvest. Livestock diseases were rampant; livestock body condition was poor. Abnormal migrations took place, along with high livestock sales, reduced meals, and increased labour migration. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Rainy season r r r r r r r r r r r r Crops Maize - rainfed gh gh gh gh h h h h h h lp lp lp lp p p w w w w Beans w w gh h h h lp lp lp lp p p p p Livestock Cattle milk peak m m m m m m m m m m m m Goats milk peak m m m m m m Peak livestock sales salesalesalesalesalesale Peak livestock purchases 6 6 6 6 Livestock diseases 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 Petty trade peak 4 4 4 4 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Dec Jan Feb Mar Apr May Oct Jun Jul Aug Sep Nov Southern Maasai Agropastoral Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Arusha Region based on a recent 10-year period (2005 – 2014) Source: TZ Meteorology Department There is one long rainy season in this livelihood zone, starting in November and lasting through May, although a short dry spell in February often interrupts the rains. Milk production is highest in the wet season, when cattle and goats give birth, and when fresh pastures and water sources provide animals with the nutrients they need for lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Land preparation (clearing and ploughing), with poorer households cultivating by hand, using hand hoes, axes and machetes, and the upper wealth groups often using tractors, starts in November for maize and beans and lasts two months. Maize is planted in January, once the rains have been fully established and beans are planted in February and March. The weeding period begins in February for maize and as late as April for beans. January through March are especially labour-intensive times of the year and all poorer households have at least one member working on the larger farms of middle and better off households. The weeding period coincides with a time when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as October or November and by January none of the poorer households have their own food stocks left at home. These households need to purchase all of their staple foods just when the price of staple foods is highest (from November through February). This is one reason that livestock sales peak from December through February. Another reason is that households need to pay school fees in these months, and better off households need money to pay for labour and other productive inputs. Thus, demand for labourers from middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize comes in. The main harvest period starts in June for maize and June/July for beans. Crop sales are highest in the post- harvest months. June through October is the dry season. Early in the dry season is when the festival season occurs, since cash from crop sales and full granaries provide a sense of relative plenty. Poorer households take advantage of the post-harvest dry season, when they are no longer engaged in agricultural labour, to increase petty trade activities and the collection and sale of building poles. They also find odd jobs locally, helping repair huts or provide construction labour. People need to set aside money at this time to prepare for the costs associated with the coming agricultural season and to pay back any loans accrued in the past year. Wealth Breakdown In Maasai communities, cattle ownership and family size are the major determinants of wealth. The more cattle a man owns, the more wives he is likely to marry, the more children he tends to have and the bigger his boma.5 The Maasai term which applies to a rich boma, Orkasis, combines material wealth with status, and effectively means that you have a lot of cattle and a lot of children. Ortajiri is a term used for those who have a lot of cattle but a small family, in which case, although food secure, the boma is not really ‘rich’ in local terms, 5The boma is the fundamental economic unit in Maasai society. A boma is a physical settlement comprised of a man, his wives, their children and their associated livestock. Southern Maasai Agropastoral Livelihood Zone Profile 6 and is not viewed as prestigious by the community6. Not just status, but significant economy advantages can accrue with having a large family. Children provide an important pool of labour for the many tasks associated with both crop production and managing large herds of livestock. In addition, when girls marry, their parents are paid in cattle; and older sons may earn money through mining or other means that gets channelled back into the boma. Thus a better off boma may be comprised of up to six wives, each of whom has 7-9 members in her hut; whereas a very poor boma would have just one wife with 6-8 family members. Note: The percentage of household figures represent the mid-point of a range. The livestock numbers are per wife. The man owns the boma’s cattle and he distributes them among his wives, for her use. The livestock numbers in the chart above refer to the average number of livestock per wife. Thus, it is not surprising for a better off household to be in possession of over a thousand cattle if he has five wives, each with 200 cattle. Very poor households, on the other hand, have almost no livestock by Maasai standards, and are just barely scraping by. A secondary factor in determining wealth here is the total amount of land cultivated by the household. This is related largely to the amount of labour the household can draw on, both from within the household and by hiring. Only middle and better off households hire labour, and they are also in a position to rent or own tractors, which significantly increases the area under cultivation. Poorer households cultivate by hand and do not have the cash to hire extra labourers during the critical crunch periods, such as planting and weeding. As a result, poor households generally only cultivate around 1 -3 acres, whereas better off households cultivate 5 – 15 acres. The distribution of wealth in this zone is fairly even. Very poor (25%) and poor (30%) households together comprise just over half of the households in the zone. Middle (30%) and better off (15%) households combined represent just under half the population. However, as middle and better off households are larger, with multiple wives and more members per wife, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is much larger. Intra-community redistribution and support is an important aspect of Maasai culture. The redistribution that takes place via the local agricultural market is one way this support is channelled. Poorer households are also provided with gifts of food in the form of milk, meat and grain, even in good years. In bad years, this support can be life-saving. 6 Boudreau, T., Household Food Economy Assessment, Arusha Region, Save the Children, 1999 Southern Maasai Agropastoral Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Livestock, which are the basis In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. of the household economy, are also fundamental to the household diet in this zone. Milk and meat from households’ own livestock bring in a substantial portion of required calories over the year. Own crop production, purchased food and gifts (for those on the lower end of the wealth spectrum) provide the remaining calories. The traditional Maasai pastoral diet used to be comprised of milk, purchased grain, meat and (occasionally) blood. Over the past thirty years, the diet itself has not changed much, but the balance in how people source their food in years with relatively good rainfall has shifted away from purchased grains and towards their own production. In the reference year - which was deemed by community leaders to be an average year – the calories supplied by households’ own crops accounted for 35-65% of minimum food energy requirements. Most of this was from maize, planted during the masika season; and the rest was from beans. A typical very poor household, cultivating around two acres of land was able to produce around 870 kg of maize and 210 kg of beans. On the upper end, better off households, cultivating around 10 acres of land, generated around 3,180 kg of maize and 1,000 kg of beans. Households sold between 40% and 60% of the maize they produced, generating an important source of cash income. All three of the upper wealth groups also sold a good portion of their beans (50-70%), with this proportion increasing with wealth; it was more common for very poor households to consume rather than sell their beans. Whereas maize and beans provide a large proportion of the calories for households in this zone, milk is still a critical part of the diet, both in nutritional and in cultural terms. Milk provides a primary source of food for young children and all members of the household continue to drink large amounts of it (both fresh and curdled), especially in the wet season, when yields are high. The contribution of milk to the household food basket increases with wealth, since wealthier households are, by definition, those with larger herds. Food is managed at the household level, with each wife allocated a particular number of cattle which provides milk for her children and other household members. Very poor households rely on the milk from around 2 cows and 6-7 goats; poor households have around twice that number of cows; middle and better off households have between 12 and 18 cows milking, and 16 to 18 goats milking. On average, cows here (which are the Zebu variety) produce 2 litres of milk a day during the first rainy season (lasting around four months) and 1 litre of milk a day in the second season (which lasts around two months). Goats yield only around ¼ of a litre a day and lactate for a period of around 2 months. When added together, these sources of milk generated around 700 litres of milk for very poor households and as much as 5,640 litres of milk for better off households during the reference year. Some of this milk was sold by households in the top three wealth groups, but the milk that was consumed accounted for around 10-40% of the calories required by households. Meat (from animals that were either Southern Maasai Agropastoral Livelihood Zone Profile 8 slaughtered or died naturally throughout the year) contributed an additional source of food, especially for middle and better off households, for whom it covered 10-20% of their minimum food needs. The market accounted for almost all the remaining calorie needs of households, comprising around 17-47% of the reference year’s food basket. Those in the upper two wealth groups bought less (17-19% of minimum calories) than those in the bottom two wealth groups (34-47% of minimum calories). This is, in part, because the poorest wealth group did not produce enough of its own food – either in the form of crops or milk and meat, to cover all of its calorie needs, even though it was a relatively good year. Poor, middle and better off households, on the other hand, could have feasibly met all their calorie needs with their own crop production if they had not sold any of their harvests or milk. If very poor households had not sold any of their crops, (they generally do not sell milk) they would have been left with a deficit of over 20% of minimum calorie requirements (assuming no gifts). On the other hand, poor households in the same scenario would have had a surplus of over 20% of minimum food needs; and a typical middle household produced 135-140% of minimum calorie requirements in the form of food, with an additional 45% of minimum calorie requirements produced in the form of milk. Finally, a typical better off household produced 208% of minimum calorie requirements in the reference year in maize and beans and 68% of minimum calorie requirements in milk. Nevertheless, all households sell part of their harvests in average years in order to meet their cash needs, which means that those in the two bottom wealth groups, have a real food deficit (after sales) that needs to be met with purchased food. This is supported by the observation that these two wealth groups bought 18-35% of their calorie needs in the form of maize grain. Middle and better off households did not buy any maize at all, rather buying food to add variety to their diet, including rice, beans, sugar, and oil. Finally, providing assistance to poorer relatives is part of a long tradition of community assistance that forms a vital part of Maasai culture. Gifts of food (mainly milk and meat) made up 2-8% of minimum calorie needs for poor and very poor households during the reference year. Sources of Cash Income As shown in the graph to the right, there are two main sources of cash income in this livelihood zone: crop sales and livestock sales; and because poorer households do not have enough crops or livestock to meet all of their cash requirements, they supplement these by working on local farms and by engaging in various other self- employment activities. The income profiles for the better off and middle households are similar in terms of the relative importance of each source of cash. What differs is the absolute cash income, with the average better off The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 7 1,360,000 – 1,900,000 1,900,000 – 4,000,000 4,000,000 – 7,000,000 5,500,000 – 13,930,000 7 The average exchange rate from April 2014-March 2015 was 1 USD = 1,800 TZS Southern Maasai Agropastoral Livelihood Zone Profile 9 household’s annual income in the reference year around 50% higher than the average middle household’s. This is due mainly to a difference in livestock sales; better off households sold, on average, around 14 cattle during the reference year, whereas middle households sold around 9. Because it was an average (and not a bad) year, cattle were sold by the upper wealth groups primarily to maintain a desirable herd composition. A typical Maasai herd is composed of more than 50% adult females in order to maximize milk production and livestock reproduction rates. The majority of steers are sold off each year, along with old bulls and unproductive females. Thus, the larger the herd, the more cattle that need to be sold to maintain a balance in favour of productive females. This helps explain the high cash incomes seen in this livelihood zone, and it explains why better off households bring in much higher cash incomes than their poorer neighbours. In bad years, when more cash is needed, additional livestock may be sold to generate cash to balance out a loss in crops or to destock in the face of pasture loss. In addition to cattle, all households sell goats, sheep and chickens. The income from chickens is quite marginal, bringing in less than 5% of annual income from livestock for most households. But sheep and goats combined accounted for 17-35% of livestock income in the reference year. In relative terms, sheep and goats are more important for the poorer two wealth groups (making up 30-35% of livestock-based cash income) than for the upper two wealth groups (making up 17-19% of livestock-based cash income). Sales of goats and sheep allow poorer households to generate cash income without selling cattle, allowing these poorer households to focus on building their herds while still helping them meet basic needs. Owning cattle also provides households with the opportunity to generate cash income from milk sales. Milk sales alone accounted for around 14% of the annual cash income for middle households. Poor households benefitted far less from milk sales and better off households simply did not need to go to the trouble given their other income sources. Very poor households did not produce milk for sale, but they did sell eggs. The income from egg sales, however, was negligible, barely showing up on the graph above. All households also sold maize and most sold beans in the reference year. Crop sales combined accounted for 15%, 16%, 15% and 21% of annual cash income for very poor, poor, middle and better off households, respectively. Maize was the more important of the two crops sold, generating 55-100% of crop-based cash income. Very poor households sold no beans at all, consuming what they grew instead. Beans are more valuable on a per kilogram basis than maize, so this balance between maize and bean sales is something that is likely to shift in bad years, with a greater emphasis on sales of beans (a high value crop) in order to fund the purchase of maize when the maize crop fails. Very poor and poor households do not have enough livestock, nor do they generate enough of their own crop production to cover all of their cash needs during the year, so they fall back on seasonal agricultural labour and self-employment or petty trade to help them fill the remaining gap. Seasonal agricultural labour and self- employment combined accounted for around 40% of the annual cash earned by very poor households in the reference year; and agricultural labour and petty trade covered just under 30% of the cash earned by poor households in the reference year. Planting and weeding periods are quite labour intensive, and better off households, who have 5-15 acres under cultivation typically hire poorer household members to help them with these tasks. Poorer households typically had at least one, and sometimes two, members working in the fields of middle or better off households during three months of the cultivation and weeding months. They provided labour again during harvesting times. In addition, very poor households sold building poles, helped build huts and fences and found other ways to earn cash during the dry season. At the same time, poor households were more likely to be engaged in petty trading activities, buying and reselling commodities such as tobacco, soda or household goods, generating a small margin of profit in the process. Southern Maasai Agropastoral Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As indicated in the graph, households here need to spend money on a range of essential items and services throughout the year, including: food (both staple and non-staple), household items, productive The graph provides a breakdown of total annual cash expenditure according to category of expenditure inputs, social services, like schooling and health, as well as clothing and other miscellaneous items. The patterns shown in the graph above highlight a number of points. First, even in a normal year like the reference year, very poor households must devote a relatively large proportion of their annual cash to meeting immediate food needs, with the proportion of annual cash spent on staple foods highest for very poor households. In the reference year, households in the very poor wealth group bought around 35% of their minimum calories in the form of maize grain, the cheapest staple. The amount of maize grain purchased by poor households covered around 18% of their minimum calories; middle and better off households did not purchase any maize grain at all. What shows up on the graph as ‘staple food’ for these wealth groups is actually rice and some oil. Without this purchased maize grain, the two poorer wealth groups would have been facing a food deficit. All households also spent money on non-staple foods, such as sugar and rice. Sugar is used in relatively high amounts here, with around 1-2 kg of sugar purchased by all households every week. Second, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. Households tend to pay for these items week by week in incremental amounts. Within this category, poorer households spent the most money on payment for grinding, followed by soap. These two items alone comprised 50-55% of the inputs budget for poorer households in the reference year. Better off households spent the most on soap followed by grinding. On an annual basis, spending on basic household goods comprised 6-15% of total expenditure, generally decreasing as a proportion of annual expenditure as wealth increases. Third, poor middle and better off households, invest a large proportion of their annual cash in productive inputs. This investment is shown as ‘inputs’ on the expenditure graph above, and includes the following: livestock drugs, water for animals, ploughing, seeds and tools, labour, livestock purchase, and phone credit. Of these items, the poorer two wealth groups spent the majority of their money on livestock drugs, followed by livestock purchases. Poor households were distinct from very poor households in their heavy investment in ploughing (spending sixteen times more than very poor households on this item and 25% of their inputs budget), which highlights a determination to use their resources to maximum effect with the aim of moving up the wealth spectrum. More crop production ultimately translates into bigger herd sizes, since having more of one’s own- produced food reduces the need to sell cattle to buy food; and more crop sales can also fund livestock purchases. Again, this divide between very poor and poor households is highlighted with the difference made in livestock purchases, with poor households spending around four times more than very poor households on Southern Maasai Agropastoral Livelihood Zone Profile 11 buying new livestock in the reference year. Middle households spent the most on livestock purchases – even more than better off households. In relatively good years, like the reference year, the herds of better off households are big enough to ensure a rapid rate of increase through natural reproduction, so their livestock purchases are not as high; middle households, on the other hand, need to augment the rate of increase afforded by natural reproduction with purchases if they want to build herds quickly. Better off households had to invest large amounts of cash into livestock drugs (which took a full third of their inputs budget in the reference year), labour for their fields (which took a fifth of their inputs budget), and water for their livestock (accounting for an additional fifth of this budget). Having larger herds and more land generates a high income, but it also requires enormous investments. Fourth, spending on water for human consumption for middle and better off households is notable. These households in the upper two wealth groups incur costs associated with pumping from dams and shallow wells and paying others to transport water to their bomas by cart. The poorer two wealth groups fetch water themselves, and they generally do not incur costs for pumping because they get their water for free from better off and middle households. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, poor households spent around the same on education as very poor households, whereas middle households spent around 1.5 times more than very poor households, and better off households spent almost 2 times more than the poorer two wealth groups. This additional expenditure reflects the fact that poorer households are usually not able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school. Secondary schools are found only at ward level, which creates costs that are prohibitive for poorer households, including things like transportation, boarding, higher fees and more expensive uniforms and supplies. On health care, better off households spent more than three times as much as very poor households on a per capita basis, indicating that these households may have had access to better clinics. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation (including fuel and service for motorbikes) and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. Hazards There are a number of hazards that affect this zone on a regular basis. The first is crop pests and diseases. Stalk borers, which affect maize; and American bollworm, pollen beetles and yellow blight, which affect beans, cause problems throughout the zone almost every year. The second chronic hazard is livestock disease, such as East Coast fever anaplasmosis, babesiosis, ormillo and trypanosomosis, affecting cattle, sheep and goats, as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively8. Helminthiasis (worms) is also a common problem, along with New Castle Disease, which can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. Wild animals and human diseases are additional challenges faced every year in this zone. The main, and most devastating, periodic hazard is drought, which leads to severe crop failures, degradation of pastures, drying up of local water sources and spikes in food prices. Although pastoralists in this area have been coping with cyclical droughts throughout centuries, and build up herds in good years as a means of insurance 8 http://www.lrrd.org/lrrd26/8/swai26138.htm Southern Maasai Agropastoral Livelihood Zone Profile 12 during bad years, the loss of mobility and access to grazing areas over the past half century puts limits on the capacity of people here to manage droughts as effectively as they once did. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. One of the reasons the Maasai maintain large herds is so they have a buffer in bad years. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Better off households tend to be in a fairly comfortable position in this regard, with large numbers of excess livestock to draw down on. However, it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally (working in many cases in direct exchange for food) or migrating outside the zone. In particular, people may go to the Tanzanite mines to find more work in a bad year. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Poorer households also turn to better off relatives and neighbours for help. Community assistance is a vital part of Maasai culture and internal re-distribution mechanisms provide an important means for poorer households to make it through bad years. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Southern Maasai Agropastoral Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Beans – amount produced Maize – producer price Beans – producer price Livestock production Cow milk – yields Own meat – amount produced Cattle – herd size Goats – herd size Sheep – herd size Chickens – numbers Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Chickens – producer price Southern Maasai Agropastoral Livelihood Zone Profile 13 Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Demand for building poles Petty trade – volume of trade Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Prices of building poles Petty trade - margins Expenditure Maize grain – consumer price Vegetable oil – consumer price Sugar – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve access to and availability of safe and reliable water supplies for humans and animals 2) Improve access to more reliable supplies of drugs and improve health services 3) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 4) Offer subsidies to poorer households on agricultural and livestock inputs to enable them to invest more easily in their production. 5) Develop and implement land use policies that can help protect communal grazing and agricultural lands. 6) Develop and support the infrastructure to enable the proliferation of reliable and fair markets for crops and livestock 7) Improve road infrastructure and invest in maintenance of existing roads 8) Provide electric service throughout the zone 9) Facilitate access to agricultural loans with affordable interest rates for appropriate beneficiaries 10) Improve communication networks/infrastructure 11) Provide means for building cattle dip tank 12) Experiment with alternative income projects, such as bee hives, for poorer households 13) Improve security with establishment of a police post"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":177,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanga Maize and Cattle Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Tanga Maize and Cattle Livelihood Zone (TLZ 03) February, 20161 Zone Description The Tanga Maize and Cattle Livelihood Zone comprises a very small area in Tanga Region along the north eastern border with Kenya. The administrative units that make up this zone include Mkinga and Lushoto districts, encompassing Mwakijembe, Mng’aro and Lunguza wards. The main ethnic groups living here are the Maasai, Sambaa, Digo, Duruma, Taita, Kamba and Mbugu. The population density is only around 1.2 people per km2. This is a small zone both in geographical coverage and in terms of total population. Despite its small size, the zone is diverse in terms of livelihood patterns. In some villages, such as Mng’aro, Mazinde and Lunguza, there are irrigation schemes which allow households to cultivate rice and plant in three seasons (vuli, masika and utagata – recessional cropping). A further difference discerned by the field teams was that in Lushoto District the main season was associated with the vuli rains, whereas in Mkinga District the masika rains were primary. The profile below describes a generalized pattern for villages where there was no irrigation. The seasonal production shown below is balanced between both seasons, but it should be borne in mind that one harvest will be more prominent than the other depending on the district. It is likely that this zone is an extension of a larger zone in neighbouring Kenya. This livelihood zone consists of lowland plains, found between 100 and 200 meters, and covered with grasslands and thickets. The Umba River runs through the zone, originating in the Usambara Mountains and emptying into the Indian Ocean just across the border in Kenya. The mouth of the river marks the eastern- most point on the border between Kenya and Tanzania. Along the river, the Umba River Game Reserve is found, and the Mkomazi Game Reserve is also found in close proximity to the zone. Green granite is mined by a few households here, although it is not a typical source of cash income. Another natural resource found here – wood – is collected by most poorer households and sold either as firewood or turned into charcoal and sold. Rains come in two distinct seasons - the vuli from November to January and the masika from March to May; annual precipitation is around 600-1000 mm. Soil fertility is low, and although rainfall is generally adequate, production, which is almost entirely rain-fed, is not very high. Maize is the primary, and only, crop of any consequence grown by local households. Poorer households prepare the land with hand hoes, while middle and better off households generally use ox ploughs and sometimes tractors. All households cultivate maize 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in June 2014 and ended in May 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. Tanga Maize and Cattle Livelihood Zone Profile 2 in both seasons, staying busy throughout most of the year with farm-based activities. The most labour- intensive activities are land preparation and weeding. At these times as well as during the planting period, households with larger tracts of land hire those with less (both men and women) to work in their fields. Payment is made in cash. This provides an important source of cash to very poor households in the zone. Livestock production forms another crucial foundation of the local economy. Relatively large herds of cattle, goats and sheep are raised here, grazing freely, and also benefitting from crop residues after the harvest. Households also raise chickens, which are fed grain and food scraps. Cattle provide milk for consumption and sale and they also provide a means of savings, allowing households to convert them to cash when needed to cover a range of basic necessities. Goats and sheep are also kept here, used for cash income, but not for milk. All livestock are slaughtered and eaten, especially during the festival seasons. Livestock rely on water from rivers during both rainy and dry seasons. Men are responsible for taking care of cattle, goats and sheep, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots and fewer livestock, depend on seasonal agricultural labour - land clearing, planting, weeding and harvesting - to generate cash income. They also piece together supplemental cash resources throughout the year, collecting and selling firewood or charcoal, selling building poles, brewing or engaging in petty trade – buying and selling small commodities like tobacco, soda, salt and sugar. This livelihood zone is far from urban centres and service provision here is poor. As most villages are located along the river, both drinking water and water for other purposes comes from the river. It is free, but largely not safe. Sanitation facilities consist of uncovered temporary pit latrines for poorer households and improved pit latrines for better off households. Health dispensaries are found at village level, although for the most part they are not well-stocked. Primary schools are found in the villages as well. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and even college. Secondary schools are available in the ward centres. There is no electricity in this zone. Households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. Almost all households have mobile phones, with better off households having multiple phones. People do not have access to credit here; there are very limited options for savings (VICOBA for some of the wealthier households); and there are no NGOs or development agencies working in the area. Markets The transportation infrastructure in this zone is relatively poor and market access is considered quite bad. The zone is far from any of the main towns in Tanzania and roads are all dirt. They function in the dry season, but quickly deteriorate in the rainy season, leaving much of the area inaccessible by vehicle. The main road stretches from Horo Horo (in Tanzania but on the border with Kenya) to Daluni, Mng’aro and Lunguza. This zone is much more closely tied to the Kenyan market, via Mombasa, than the Tanzanian market, and most people depend on traders who come across the border to buy up local maize and cattle. Maize, cattle and goats are the main commodities sold by households in this zone. These transactions take place at the farm gate, or – in the case of maize – from house to house. Maize is sold in February, June and July, just after the harvest. Cattle and goats are sold throughout the year to traders who come to local villages and buy up livestock, transporting it to various end points, including Zanzibar (via Horohoro and Tanga); Mombasa (in Kenya); Korogwe (via Mombo); and Lushoto town. Chickens are also widely sold, again bought up by traders who take them to Tanga or Korogwe for sale. There is also a market for food brought into the zone for consumption by local households. Poorer households need to buy maize grain to cover their needs for a portion of the year, especially September through December and May to June, even in good production years. Maize is the cheapest local staple, and most of this is locally sourced, procured from better off households who generally produce a sizeable Tanga Maize and Cattle Livelihood Zone Profile 3 surplus. It is also sourced from Handeni via Tanga and Mkinga or via Mombo, Mnazi, Lunguza and Kikumbi. Rice, purchased almost exclusively by the upper wealth groups, is sourced from Morogoro, Kilimanjaro and Korogwe, distributed via the Tanga market or the Mnazi market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks. The labour market is largely local. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding. It was estimated that in the reference year, 70% of seasonal labour was found within the zone on local farms. An additional 30% of labour demand came from Maramba in a neighbouring livelihood zone where people travel every year during the lean season. Both men and women from poorer households take on paid agricultural work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Tanga Maize and Cattle Livelihood Zone the reference year covered the consumption period from June 2014 to May 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in November/December and ends with the masika harvest in July- August of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average rains, average crop yields and normal food prices. The incidence of crop pests was low, and livestock diseases were not widespread. In the past eight seasons, two were below average, and six were average. Production Year Season Rank Critical Events 2014-2015 Vuli 3 Average rainfall; average crop harvest Masika 3 Average rainfall; average crop harvest; no livestock diseases 2013-2014 Vuli 3 Average rainfall; average crop harvest; good prices for maize Masika 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases; no livestock diseases 2012-2013 Vuli 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases Masika 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases 2011-2012 Vuli 2 Below average rainfall; poor crop yield; high staple food prices; low livestock prices; people increased charcoal sales, migrated to Maramba; sold more livestock and chickens Masika 2 Below average rainfall; poor crop yield; high staple food prices; low livestock prices; food aid was distributed by the Government of Tanzania; people increased charcoal sales, migrated to Maramba; sold more livestock and chickens 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Tanga Maize and Cattle Livelihood Zone Profile 4 Seasonal Calendar for Reference Year In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until December or January; rains for the second season, called the masika, picks up in March or April and lasts through May or June. Households plant twice, taking advantage of both seasons’ precipitation to reduce the risks of failure in either one. Land preparation for the vuli season starts in September, soon after the masika harvest, and planting begins in November, when the rains are fully established. December and January are busy months, with households engaged in weeding; those at the lower end of the wealth spectrum work in both their own fields and the fields of those with bigger farms, earning cash during this labour intensive period. The green harvest for the vuli crop starts in February, with the main harvest occurring in March. As maize from the vuli crop is being harvested, fields are once again prepared for the next season, with planting for the masika maize taking place in April. May is when households are tied up with weeding activities, again followed by a green harvest in June. The main harvest of masika maize occurs in July and August. The whole cycle starts again in the following month, giving people very little time to enjoy any downtime associated with the post-harvest period. Milk production is highest throughout both rainy seasons (November through April), when cattle give birth, and when fresh pastures and water sources provide animals with the nutrients they need for lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging diseases, such as East Coast Fever and Black quarter, are likely to occur. Livestock sales, which represent the most important income source for many households in this zone, can take place at any time of the year, but cattle are sold in the largest quantities in November and December, to fund the end of year festival season. January is when school fees need to be paid, which helps explain why livestock are also sold at this time. Money is also needed for agricultural inputs in February, March and April, and again September, October and November. April and May is also when staple food prices tend to be highest, generating another requirement for extra cash. Rainy season r r r r r r r r r r r r r r Crops Maize - 1st season (vuli) lp lp lp lp p p w w w w gh gh h h Maize - 2nd season (masika) gh gh h h h h lp lp lp lp p p w w Livestock Cattle milk peak m m m m m m m m m m m m Cattle sales peak salesale salesalesalesalesalesalesalesalesalesalesalesalesalesale Goat sales peak salesalesalesale salesalesalesalesalesalesalesalesalesale salesale Livestock diseases 5 5 5 5 5 5 5 5 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Firewood sales 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp Human diseases 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 2 2 Lean season ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Feb Mar Apr May Jun Jul Dec Aug Sep Oct Nov Jan Tanga Maize and Cattle Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Lushoto District based on a 43 - year period (1971-2013) Source: TZ Meteorology Department People in this livelihood zone are busy throughout the year, juggling the many activities involved with managing two production seasons. Poorer households are especially busy during land preparation and weeding periods, splitting the household to work partly on their own farms and partly on others’ farms for cash. But when they are able, they take advantage of any drier days occurring from July through January to collect and sell firewood to supplement their cash income. Human diseases occur throughout the year as well, but respiratory infections tend to peak during the dry seasons, and malaria is highest in the wet seasons. Having a sick household member is extremely taxing, especially for poorer households who need as much labour on hand as possible to manage the demands of their own farms while taking advantage of changing seasonal employment opportunities. They are also more limited in being able to pay for medicines (where they are available) given the severe constraints on their budgets. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The livestock numbers are per wife. Maize and cattle are the engines of the economy in this zone, so it follows that wealth is determined both by the area of land cultivated and the number of livestock owned. Those at the top of the wealth breakdown cultivate between 6 and 10 acres of land and own 40-70 cattle, along with other livestock; those at the bottom cultivate 1.5 to 2.5 acres and may own no cattle at all, or one or two at most. The difference in access to food and cash income for households at these two ends of the spectrum is quite large, with better off households able to generate all their required food and cash from their own fields and livestock, whereas those at the bottom are just scraping by, needing to supplement their own production with various off-farm pursuits. Tanga Maize and Cattle Livelihood Zone Profile 6 A related factor in wealth differentiation is household size; those with more resources tend to have larger households and those with larger households tend to have more labour, which allows them to maintain more resources. Thus there is some indication that the lower two wealth groups have slightly smaller household sizes, suggesting less access to labour within the family unit. In any case, only middle and better off households hire labour, and they are also in a position to rent or own tractors, which significantly increases the area they have under cultivation. Poorer households cultivate by hand and do not have the cash to hire extra labourers during the critical crunch periods, such as planting and weeding. There is a certain amount of intra-community redistribution and support here. The local labour market acts as a mechanism for redistributing cash, giving poorer households access to needed cash income and better off households access to the labour they need. Some better off households also lend milking cows to poorer households, providing them with access to milk, and in return having the poorer household take responsibility for the care of the animal. The distribution of wealth in this zone is fairly even. Very poor (20%) and poor (33%) households together comprise just over half of the households in the zone. Middle (32%) and better off (15%) households combined represent just under half the population. However, as middle and better off households are larger, and some even have multiple wives, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is larger. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period June 2014 to May 2015. June represents the start of the consumption year because it is when people begin to consume green crops from the masika season (the main season) and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. What is striking about livelihood patterns in this zone is the In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. overwhelming reliance on maize. It is the only crop of any significance grown by all households. Maize is grown in two season, with both seasons of almost equal importance. In the reference year, for example, a typical poor household produced around 840 kg of maize in the vuli season and 1,260 kg in the masika season. A typical middle household produced around 1,000 kg in the vuli season, and 1,400 kg in the masika. It was common for better off households to produce twice that much. Over half of the maize produced is sold, leaving an amount that does not meet the minimum calorie requirements of any wealth group. Sales of maize are critical here, providing households with a portion of the cash they need to cover their expenditure requirements. However, with maize the only crop of any note grown for both consumption and sale, people’s livelihood and food security are highly vulnerable to any hazard that affects maize production, be it a stoppage in rain, damage caused by monkeys (which is pervasive in this area), or any of a wide range of potential crop diseases affecting maize. The risk is countered to some degree by the fact that there are two seasons, however even if rainfall fails in one Tanga Maize and Cattle Livelihood Zone Profile 7 season this wipes out up to half of the annual food and cash supply, a shock that only the better off would be able to withstand. The lack of alternative crops, and the reliance on maize for both consumption and sale means that all households, but especially the poorer two wealth groups, are highly dependent on purchased food, even in an average year, like reference year. It is important to note that, even with these purchases the typical very poor household does not cover its minimum calorie needs. Very poor households purchased around 40-45% of their minimum calorie requirements and poor households purchased 35-40% of minimum calories in the form of maize grain - the cheapest staple - in the reference year. Middle and better off households generally did not purchase maize grain, instead buying wheat flour and rice along with a number of other more expensive non- grain items, such as beans, sugar, meat, oil, and dried fish. The purchase bar on the graphs above, therefore, represents a different basis for decision making: poorer households bought food because they had to fill a real food gap that they were unable to meet through their own production; middle and better off households, on the other hand, tended to buy food to diversify their food basket. This is further supported by the fact that if better off households had consumed all of their own maize production rather than selling half of it, they would have been able to cover over 250% of their minimum food needs with maize alone. Very poor households, on the other hand, given the same assumptions, would only have gleaned 105% of minimum calories from their own production. Even though this appears to be more than enough, it is not, because maize plays a critical role in covering household cash needs. Thus, households need to sell off maize to meet cash flow requirements after the harvest, putting them at a deficit later in the year. Milk contributes substantially to the diet of middle and better off households and to poor households as well to a lesser degree, covering 10%, 18% and 4% of minimum calorie needs in the reference year, respectively. Meat from the households’ own livestock also accounts for 5-10% of calorie needs for better off households. Poor households rely on the milk from around 2 cows; middle have around 7 cows milking, and better off households have, on average, 18 cows milking. On average, cows here produce 1.5 litres of milk a day during the first rainy season (lasting around four months) and 1 litre of milk a day in the second season (which lasts around three months). When added together, the milk from both seasons amounted to around 495 litres for poor households, over 1700 litres for middle households, and almost 4,500 litres for better off households during the reference year. Around 45-55% of this was sold, providing some cash income (shown in the section below) for these three wealth groups. Very poor households, who generally do not own cattle, benefitted neither in food nor in cash terms from milk. It is important to note that the milk from just two cows could have helped very poor households to close the calorie gap (of around 3% of minimum needs) they had in the reference year. Sources of Cash Income As shown in the graph to the right, there are five sources of cash income in this livelihood zone: crop sales, milk sales, livestock sales, agricultural labour, and self-employment. The latter two options are the domain (mainly) of poorer households. Better off households are the only wealth group that can cover all of their cash needs from their own farms, relying exclusively on their crop and livestock production. The bottom two groups rely Tanga Maize and Cattle Livelihood Zone Profile 8 heavily on agricultural labour and self-employment; and middle households need to take on some self- employment activities as well to cover all of their cash needs. What stands out in this The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 2 1,295,000 – 1,640,000 1,640,000 – 2,355,000 3,600,000 – 4,800,000 4,800,000 – 9,650,000 livelihood zone with reference to cash income is the importance of livestock sales, which dominate the income for middle and better off households. If maize was central to the story on the food side, then livestock (and especially cattle) are central to the story on the cash income side. It is no wonder, then, that the name of the zone features both maize and cattle, as these provide the engine for the local economy. Livestock sales make up around 65-70% of annual cash income for middle and better off households; and only around 10-20% for very poor and poor households. In absolute terms, better off households earn from livestock sales almost twice as much as middle households and over 27 times more than very poor households. This is largely due to the sale of cattle; better off households sold 7-8 cattle during the reference year, at around 500,000 Tanzanian Shillings each, providing them with around 3,750,000 Tsh from cattle sales alone. Middle households sold around 4 cattle, and poor households usually sell a single steer once every two years. Very poor households sold no cattle. Goats, worth around only 50,000 Tsh each (or a tenth of a cow), were sold by all wealth groups, ranging from around 2 goats sold by very poor households up to 19 goats sold by better off households. Chickens, which were worth around 9,000 Tsh per hen, were sold most intensively by very poor households, who typically cashed in on around 9 chickens in the reference year. Chickens provided very poor households with almost half of their livestock-based cash income, small as that income may be. Goats and chickens, therefore, are the only source of livestock-based cash for very poor households, whereas the other three wealth groups sell sheep and cattle as well. Having cattle affords the upper three wealth groups with access not just to a larger pool of money from the sale of live animals, but also cash earned from sales of milk. As noted above, households with milking cows sold 45- 55% of the milk they generated in the reference year. This resulted in substantial income for especially middle and better off households, bringing in, on average, 126,500, 433,400, and 1,375,000 Tsh for poor, middle and better off households respectively, or 7%, 11% and 19% of their annual cash income, respectively. Crop sales – which, in this livelihood zone means maize sales – accounted for 12-22% of total cash income for households in the reference year. In absolute terms, better off households earned around four times more from selling maize than very poor households, and twice as much as middle households. Maize is sold in both seasons, and better off households usually sell their maize for a higher price per unit than poor and very poor households. For example, the masika season maize, which is harvested in July and August, was sold by very poor households for around 278 Tsh/kg; better off households sold their maize for 400 Tsh/kg. This is mainly due to the timing of these sales; better off households store their grain and sell it when prices are highest, whereas poorer households usually need to sell right at harvest time, when prices are lowest. The result is that not only do better off households earn more cash from crop sales because they sell more maize, but also because they get significantly more money per unit of maize. Very poor and poor households, because their cash income from crop and livestock sales is so limited, must turn to other sources of cash to make ends meet. Agricultural labour is the most important alternative source for very poor households, making up just over 40% of their annual cash income in the reference year. For poor households, agricultural labour accounted for around 20% of their annual cash income. Land clearing is an especially arduous task, and poorer households are routinely hired throughout the two months when this work is undertaken, bringing them over half of their agricultural labour income. Planting, weeding and harvesting times also see an increase in the demand for seasonal labour, and these three periods bring in the rest of the 2 The average exchange rate from June 2014-May 2015 was 1 USD = 2,000 TZS Tanga Maize and Cattle Livelihood Zone Profile 9 cash income in this category. Most of the labour is performed for local middle and better off households, but some people also go to a neighbouring livelihood zone (the Tanga Maize, Orange and Jackfruit Midlands Livelihood Zone) to find work. The other source of cash income on the graph above is ‘self-employment’. This covers a range of activities that households undertake to try to earn cash at different times of the year. For very poor households this represents around a third of cash income and includes mainly firewood and charcoal sales. For poor households these activities also make up around 30% of cash income, but in addition to firewood and charcoal sales, these households earn cash from pole sales, brick sales and brewing. Middle households also supplement their crop and livestock sales with self-employment activities, but instead of firewood and charcoal, they focus mainly on mining, ox hire, petty trade, prepared food sales and some with motorcycles pursue boda boda (motorcycle transport). An additional point to make is that there is a large spread in income distribution, with those at the upper end of the wealth spectrum generating, on average, seven times more than those at the bottom. Owning livestock is the critical differentiator in this zone, with cattle sales alone for the better off equivalent to more than the total cash income of middle households and over twice the total annual cash income of both very poor and poor household. Expenditure Patterns The graph presents expenditure patterns for the reference year June 2014 to May 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. Households here, as in other areas of Tanzania, need to spend money throughout the year on a range of goods and services. These include: staple and non- staple food, household items, productive inputs, social services The graph provides a breakdown of total annual cash expenditure according to category of expenditure like schooling and health, as well as clothing and other miscellaneous items. There are three main points that emerge when delving into the data that supports the graph above. First, relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum. Even in a normal year like the reference year, very poor households must devote large proportion of their annual cash to meeting food needs, with the proportion of annual cash spent on staple foods highest for very poor households. In the reference year, households in the very poor wealth group bought around 44% of their minimum calories in the form of maize grain, the cheapest staple, and poor households bought 36% of their calories in the form of maize grain. This was the equivalent of around 560 kg and 450 kg of maize, respectively. Middle and better off households did not purchase any maize grain at all3. All households also spent money on other foods, such as dried fish, oil, sugar, rice, meat, vegetables and potatoes. These items are more expensive, and thus take up a larger proportion of annual cash for all wealth groups. In absolute terms, better off 3 What appears on the graph as ‘staple’ purchase for middle and better off households is beans, oil and dried fish. Tanga Maize and Cattle Livelihood Zone Profile 10 households spend more than twice as much as very poor households on these other foods, but because their cash income is more than seven times higher, in relative terms their expenditure is lower than poorer households. Second, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. Within this category, the two poorer wealth groups spent the most money on payment for grinding (taking up anywhere between 34% and 55% of the household items budget) followed by kerosene and soap. Kerosene and soap combined comprised 30-44% of the inputs budget for poorer households in the reference year. Better off households spent the most on kerosene followed by utensils. On an annual basis, spending on basic household goods, which occurred in weekly or daily incremental outlays, comprised 12-18% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Third, it is striking that the investment in productive inputs increases markedly with wealth group. Very poor households generally devote only 0-5% of their annual budget to productive inputs, either unable or unwilling to spend more. Better off households, on the other hand, invest almost 40% of their annual cash back into their production. In absolute terms, better off households spend over 80 times more than very poor households on productive inputs. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, ploughing, seeds and tools, labour, livestock purchase, and phone credit. Households here generally do not buy pesticides or fertilizers. Of these items, the poorer two wealth groups spent the majority of their money on phone credit, followed by livestock drugs and seeds and tools. Poor households were distinct from very poor households in that they also invested in livestock purchases. Middle households spent the most on labour, spending more than two-thirds of their inputs budget on hiring people to help on their farm. Phone credit was the next most important investment for these households, followed by livestock drugs, livestock purchases and then seeds and tools. Better off households invested large amounts of their budget into buying additional livestock, spending around a third of their inputs cash on this category. The next most important expenditure was labour hire, followed by livestock drugs, ploughing (effectively hiring tractors to help till their land), phone credit and then seeds and tools. The priority of better off households is clear from these numbers, and it is in line with the engine of growth here: the accumulation of cattle. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Better off households spent around 1.5 times as much as middle households; middle households spent around 1.5 times as much as poor households; and poor households spent around 1.5 times as much as very poor households. As you move up wealth groups, households are spending more on stationery, books, uniforms and, ultimately, the costs that are associated with secondary school. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to college. With respect to health costs, better off households spent more than six times as much as very poor households on a per capita basis; it is likely that these households sought treatment, when necessary, at facilities other than the village dispensary. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, bicycle service, savings, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. Tanga Maize and Cattle Livelihood Zone Profile 11 Hazards There are a number of hazards that affect this zone on a regular basis. The first is livestock disease, such as Food and Mouth disease (FMD), East Coast fever, trypanosomiases, affecting cattle, sheep and goats, as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively. Helminthiasis (worms) is also a common problem, along with New Castle Disease, which can wipe out an entire flock of chickens The second is crop pests and diseases. Stalk borers, which affect maize; and American bollworm, pollen beetles and yellow blight, which affect beans, cause problems throughout the zone almost every year. Wild animals pose additional challenges, ruining crops and causing damage in fields on a regular basis. The main, and most devastating, periodic hazard is drought, which leads to severe crop failures, degradation of pastures, drying up of local water sources and spikes in food prices and severe declines in livestock prices. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Better off households tend to have larger numbers of excess livestock to draw down on. However, it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through increasing self-employment, especially making more charcoal and collecting and selling more firewood. This option is limited because as the year worsens, the number of people attempting to increasing their income in this way rises, increasing supplies on the market and pushing down prices. The amount of wood available locally is also limited. Poorer households also try to find more work, either locally (working in many cases in direct exchange for food) or migrating outside the zone to Maramba, to the Tanga Maize, Orange and Jackfruit Midlands Livelihood Zone, where labour demand is higher, or even to Kenya. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Tanga Maize and Cattle Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Tanga Maize and Cattle Livelihood Zone Profile 12 Item Key Parameter - Quantity Key Parameter – Price Crops Maize - vuli – amount produced Maize – masika – amount produced Maize - vuli – producer price Maize - masika – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Sheep – herd size Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Firewood/charcoal – amount collected Self-employment – level of activity Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Firewood/charcoal - prices Self-employment – return on activities Expenditure Maize grain – consumer price Wheat flour – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Construct dam to create water source for irrigation 2) Provide affordable loans for agricultural inputs and livestock purchase 3) Improve access to and availability of safe and reliable water supplies for humans and animals 4) Improve access to more reliable supplies of drugs and improve health services 5) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 6) Provide electric service throughout the zone 7) Improve road infrastructure and invest in maintenance of existing roads 8) Develop and support the marketing infrastructure to enable the proliferation of reliable and fair markets for crops and livestock 9) Provide more affordable access to agricultural and livestock inputs 10) Improve communication networks/infrastructure"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":178,"cells":{"data":{"kind":"string","value":"# Extracted Content Western Usambara-Pare Highlands Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Western Usambara-Pare Highlands Livelihood Zone (TLZ 05) February, 20161 Zone Description The Western Usambara-Pare Highlands Livelihood Zone comprises a mountainous highland area in parts of Tanga and Kilimajaro regions. The administrative units that make up this zone include the wards of Kwai, Malibwi, Rangwi, Mwangoi, Mbaramo, Mtae, Soga, Soni, Mlalo, Shume, Malindi, Hamtoye, Ngweo, Lushoto, Gare, Baga, Mgwashi, Mwamboi, Ubiri, Mbuzii, Mayo, Bumbuli, Vuga, Mponde, Funta, and Tamota, all of which are found in Lushoto District2. The main ethnic groups living here are the Sambaa and the Pare. The population density here is high: 141 people per km2 in the western part of the zone and 104 per km2 in the eastern part, although around Korogwe the density is much lower, around 68 people per km2. This livelihood zone consists of a mountainous areas containing some of the only rain forests in East Africa. The Usambaras are part of a mountain range that stretches from the Taita Hills in southern Kenya to Morogoro and the southern highlands of Tanzania. The Usambaras are commonly split into two sub-ranges, the West Usambara Mountains and the East Usambara Mountains. The East Usambara are closer to the coast, receive more rainfall, and are smaller than the West Usambara. Natural resources include timber and a range of fruit trees, which are exploited for cash by a large proportion of the population. Since the late 19th century, a mix of cash crops like coffee, tea, and timber have been harvested from this area. A range of fruit trees are also found here. In the eastern parts, bananas, mangoes, jackfruit and avocado are grown. In the western part apples, peaches, and avocados are found. Tea plantations can be found in both the eastern and western areas, but most small-holder households do not grow tea. There are two rainy seasons – the masika rains, from March to June, and the vuli rains, from October to December. Total precipitation can be as high as 2,000 mm or as low as 500 mm depending on the year, but on average, based on a 43-year series of data, annual rainfall is around 1,036 mm. Temperatures are cool, ranging from 150C to 30ºC. The soils are fertile here, but there are severe constraints on land, with some of the highest population pressure in the country. Therefore, plot sizes are small, and production per household is low. All households cultivate maize, beans and Irish potatoes, all of which are rain-fed. Those with more land also cultivate a range of horticultural crops, such as cabbages, tomatoes and sweet peppers. These are grown in both seasons and bring in substantial cash income. Because of the mountainous terrain, tractors and ox ploughs are not 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in February 2014 and ended in January 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2 Although the map shows a zone that includes Korogwe and Muheza, these areas are considered to be a separate zone because the masika season is the main season here (rather than the vuli) and there are different fruits cultivated in smaller amounts. Cassava is found in the east not the west; people work on tea estates in the east but not the west. Potatoes are important in the west but not the east. Therefore, a re-zoning exercise is necessary along with a new map. Western Usambara-Pare Highlands Livelihood Zone Profile 2 feasible; therefore, all households – even the better off – use hand hoes to cultivate. Horticultural production is labour intensive, requiring arduous land preparation, planting, weeding, spraying, watering and harvesting. Middle and better off households pay poor household members in cash to help them complete these activities. Both men and women from poorer households work as labourers, helping provide their families with an important source of cash. Livestock are raised here in small numbers. Because of the severe limitations on land, people are unable to keep more than a few cattle and goats or sheep per household. Chickens are also kept by all households Zero grazing is the norm here, and animals are hand fed with grasses and crop residues. Cattle provide milk for consumption and sale and those who have them can convert them into cash when needed to cover a range of basic necessities. Goats and sheep are also kept here, used for cash income, but not for milk. Goats, sheep and chickens slaughtered and eaten throughout the year, but especially during the festival seasons. Livestock rely on water from seasonal rivers during the rainy seasons and shallow wells and springs during the dry season. Men are responsible for taking care of the cattle; both men and women take care of the goats and sheep, whereas women and children manage the chicken flocks. Poorer households depend heavily on seasonal agricultural labour - land clearing, planting, watering, spraying, weeding and harvesting - to generate cash income. Some also piece together supplemental cash by collecting and selling firewood, selling building poles, or brewing. Middle and better off households earn extra cash from petty trade, running small kiosks, and – if they have a motorcycle – boda boda (motorcycle taxi hire). Services in this zone are on a par with much of rural Tanzania. Drinking and washing water is sourced from springs and taps, usually not farther than 1 km from the village. Tap water is not free, costing 1,000 Tsh per household per month. Sanitation facilities consist of pit latrines, most of which are constructed with brick and mud and covered with aluminium sheets. Better off households may have improved concrete floors instead of mud floors. Health dispensaries are found within a 5-6 kilometre radius of most villages. Primary schools also available in villages, with secondary schools found at the ward level. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and vocational college. There is no electricity in this zone so households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. In general, all households have at least one mobile phone and better off households having multiple phones. People do not have access to credit here and there are no options for savings. A few NGOs operate here, including the Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services; Oxfam, which promotes vegetable crop marketing; TwoAfrica, which provides improved yellow bean seeds; and ASARECA, which promotes soil conservation and provides seeds. Markets In this mountainous zone, roads are mostly made of dirt and often in poor repair. One major tarmac road runs through the zone from Lushoto to Korogwe. In the dry season vehicles make it through on all the roads; but during the rains, the more difficult areas to reach, such as Kwai village in Lushoto District, become inaccessible. The majority of bridges are in good condition, although this can change rapidly in the wet season. Motorcycles, bicycles and foot traffic are the means by which most people get around in any case, and people sell their goods to traders who come into the zone to buy directly from farmers. Vegetables, such as cabbage, tomatoes and sweet peppers, along with fruits and livestock are the main commodities sold by households in this zone. These transactions take place at the farm gate. Vegetables are sold in the largest quantities after both harvests, from January to February and June to July, but there are vegetables harvested throughout the year in valleys where water pools, and sales can take place at any time. Traders buy vegetables from farmers and then transport them to Lushoto, where they are sold on to Tanga, Western Usambara-Pare Highlands Livelihood Zone Profile 3 Arusha or Dar es Salaam. Fruits are sold mainly in December and January. They follow the same trade route. Cattle, goats and chickens are sold in small numbers throughout the year at local markets. Given the high requirement for purchased food in this zone, the route by which maize enters the zone is important to understand. Demand for purchased maize grain is high from April to July in Korogwe (the eastern part of the zone) and from August to January in Lushoto (the western part of the zone). All households need to buy maize grain to cover their needs for a large portion of the year. Maize is the cheapest local staple, and this is sourced from Handeni or from Dar es Salaam. It is trucked into the area by local traders and better off households (who own trucks and bring back maize after their sell their vegetables in Dar es Salaam). This helps to moderate maize prices and ensures a fairly steady supply. Beans are sourced from Kilindi and are distributed via local markets from October through December. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks. The labour market is almost entirely local seasonal agricultural work. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms, with middle and better off households hiring poorer household members to work on their land. An additional 10% of labour demand came from Lushoto town, where people regularly go to seek work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Western Usambara-Pare Highlands Livelihood Zone the reference year covered the consumption period from February 2014 to January 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in October/November and ends with the April through July harvest of the following calendar year. Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average rains, average crop yields and normal food prices. In the past eight seasons, three were below average, three were just below average and two were average. Production Year Season Rank Critical Events 2014-2015 Vuli 2.5 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. Masika 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. 2013-2014 Vuli 3 Average rainfall; average crop production average prices Masika 3 Average rainfall; average crop production average prices 2012-2013 Vuli 2.5 Average rainfall; average crop production average prices Masika 2.5 Average rainfall; average crop production average prices 2011-2012 Vuli 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. Masika 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Western Usambara-Pare Highlands Livelihood Zone Profile 4 Seasonal Calendar for Reference Year The graph to the right shows average monthly rainfall (mm) in Lushoto District based on a 43 - year period (1971-2013) Source: TZ Meteorology Department In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until January; the second, called the masika, occurs from March through May. Households in the western part of the zone consider the vuli rains to be the main production season, whereas those in the eastern part consider the masika rains to be the main production season. The seasonal calendar below shows the pattern for the western part of the zone, but even here, there is production in both the vuli and masika seasons, and many crops rely on irrigation which, while supported by the rains, is not entirely dependent on them. Land preparation takes place twice a year: from August to October (for the vuli season) and February and March (for the masika season). This is a time of intense labour demand and those at the lower end of the wealth spectrum are working in both their own fields and in the fields of those with bigger farms, earning much of their annual cash during this period. Maize is grown in only one season, but beans and Irish potatoes Rainy season r r r r r r r r r r r r Crops Land preparation lp lp lp lp lp lp lp lp lp lp Maize - (vuli) gh gh gh gh h h h h p p p p w w w w Beans h h p p w w w w h h p p p p w w w w Irish potatoes h h p p w w w w h h h h p p p p w w w w h h Vegetables/fruit h h p p p p w w h h h h p p p p w w h h Livestock Cattle milk peak m m m m m m m m m m Cattle sales peak salesalesalesalesalesale Other Agricultural labor peak 4 4 4 4 4 4 4 4 4 4 Non-agricultural labor peak 4 4 4 4 4 4 4 4 Firewood sales 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp Human diseases 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Oct Nov Dec Jan Feb Mar Aug Apr May Jun Jul Sep Vuli Masika Western Usambara-Pare Highlands Livelihood Zone Profile 5 are planted twice. Maize, beans and horticultural crops are planted in October and November, once the rains are fully established. Irish potatoes are planted before this, starting in September, since they need slightly less water to get started. Weeding takes place from November to January, and once again poorer households are hired by those with larger farms to help with this activity. Irish potatoes and some of the horticultural crops start to get harvested as early as January, and households begin to harvest maize green, and beans, starting in February. The main harvest of vuli maize is in April and March. As maize from the vuli crop is being harvested green, fields are once again prepared for the next season, with planting for the masika beans, Irish potatoes and vegetables taking place in March and April. May is when households are tied up with weeding activities, again followed by a harvest of the second season crops in June and July. The whole cycle starts again in the following month, in August. Milk production is highest from February through June since conceptions are highest in May and cattle give birth around nine months later. This is a time when the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging diseases, such as East Coast Fever and Blackquarter, are likely to occur. Livestock sales can also take place at any time of the year, but November through January tends to be a time of especially high sales, when households need extra cash for food since staple prices are highest in these pre-harvest months. Poorer households in this zone are especially busy during land preparation and weeding periods, splitting the household to work partly on their own farms to grow their own food and cash crops, and partly on others’ farms for cash. February and March, and August through October are periods of intense agricultural labour demand. During the months when there is more time for off-farm work (from April through July), poorer households may seek temporary jobs in town, or they collect and sell firewood to supplement their cash income. June through September is the festival season. This brief period between the masika harvest and the start of the vuli season is when people have slightly more cash available from their cash crop sales, and the break in agricultural labour gives people a time to rest. Human diseases occur throughout the year as well, but respiratory infections tend to peak during the dry seasons, and malaria is highest in the wet seasons. Having a sick household member is extremely taxing, especially for poorer households who need as much labour on hand as possible to manage the demands of their own farms while taking advantage of changing seasonal employment opportunities. They are also more limited in being able to pay for medicines (where they are available) given the severe constraints on their budgets. Wealth Breakdown Given that crop production is the main source of cash income in this zone, it follows that wealth is determined largely by the area of land cultivated by a household. In addition, ownership of productive assets, like motorcycles (which enable households to make money from boda boda), livestock and fruit trees contributes to the basis on which differences of wealth are determined. These other productive assets are relatively more important in this zone than in many others because the population is dense, land is very limited and, thus, the land areas cultivated are severely constrained. No land is left uncultivated, and even better off households are unable to plant on more than 5 acres. Very poor households plant on less than an acre, concentrating mainly on food crops rather than horticulture. Poor households cultivate 1-2 acres and middle households cultivate 2-3 acres. The difference between these two amounts of land seems minor, but there is a critical divide between poor and middle households: poor and very poor households need to work for others to earn enough cash to live on and middle households generally do not. In part this is because middle households have that extra acre that allows them to plant Western Usambara-Pare Highlands Livelihood Zone Profile 6 vegetables for sale and also allows them to cultivate – importantly – a significant number of fruit trees, which provide another source of cash income that poor households do not have. Note: The percentage of household figures represent the mid-point of a range. All asset numbers are per wife (in the case of polygamous households). Another difference between poor and middle households is the number of livestock owned. Although livestock are not a major source of cash income in this zone – limited in numbers because of the lack of land for grazing and maintenance - they still help provide milk for consumption and sale, and the cash from live animal sales is not insubstantial. A middle household with up to 3 cattle has different prospects for cash income than a poor household with none. There is a certain amount of intra-household redistribution in this livelihood zone. All households cultivate with hand hoes, which means that those with more land need extra help, unable to rely exclusively on their intra-household labour to complete all their agricultural tasks throughout the year. Thus, households on the upper end of the wealth spectrum hire those on the lower end, especially during land preparation and weeding. The local labour market acts mechanism for redistributing cash, giving poorer households access to needed cash income and better off households access to the labour they need. In addition, there are some share-cropping arrangements in place, in which middle households provide land, fertilizers and seeds to poorer households in exchange for a portion of the crop that is harvested by the poor household. The distribution of wealth in this zone is fairly even. Very poor (23%) and poor (32%) households together comprise just over half of the households in the zone. Middle (30%) and better off (15%) households combined represent just under half the population. Western Usambara-Pare Highlands Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period February 2014 to January 2015. February represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. What is striking about livelihood patterns in this zone is the heavy reliance on the market for all In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. wealth groups. All households needed to purchase food to cover a production gap – even better off households generally do not produce enough to meet their minimum calorie needs. In the reference year, an average year, very poor households bought almost 60% of their minimum calories in the form of maize grain (the cheapest staple) and better off households bought around 30% of their calories in the form of maize grain. All households also bought some rice, with middle and better off households buying more of this expensive grain than poorer households; and middle and better off households also bought wheat flour, which was around twice as expensive as maize grain. Sugar, meat, oil, Irish potatoes, beans and dried fish also contributed to the purchased food basket. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 70-85% of their minimum calorie requirements in the reference year. It is important to note that, even with these purchases the typical very poor and poor households were left with a gap. In addition to the market, households depended on two other sources of food: their own crop production and their own milk production. All households grow a range of crops, including maize, beans, Irish potatoes and vegetables, such as cabbage, sweet peppers. Better off households also cultivate fruit trees; in the eastern part of the zone, where the altitude is not as high, bananas, mangoes, jackfruit and avocados are grown; in the western, higher altitude part of the zone, apples, peaches, avocados and futari (matunda damu) are grown. Despite this large variety, households do not grow enough to meet their own consumption requirements, even in an average year like the reference year. People have relatively small plots, and only one season of maize is grown. In that one season (the vuli season in the western part of the zone and the masika season in the eastern part), total production of maize was quite low in the reference year, ranging on average from 175 kg for very poor households up to 430 kg for better off households. All of the maize was consumed, but this amount accounted only around 10-30% of minimum calorie requirements. Beans are grown in both seasons, and a large portion of the bean harvest is sold. Given that beans fetch a higher price than maize grain, selling this crop to generate cash for purchased maize makes economic sense. The beans that households retained for consumption covered an additional 4-7% of minimum food needs. Irish potatoes, grown in the masika season, provide an additional 2-5% of minimum calorie needs for households. When combined, own crops accounted for only around 20-40% of households’ annual food needs in the reference year. Milk makes up the last component of the diet for households in this zone, although it does not make a large contribution in calorie terms, providing only 1-6% of minimum calorie needs in the reference year, increasing Western Usambara-Pare Highlands Livelihood Zone Profile 8 with wealth. Middle households typically have around 1 cow milking, and better off households have, on average, 2 cows milking. Very poor and poor households may borrow a cow, or share in the milk from a neighbour. Yields are relatively high, at 3-4 litres a day in the first rainy season (lasting around four months) and 1.5-2 litres a day in the second rainy season (lasting around three months). When added together, the milk from both seasons amounted to around 660 litres for middle households, and 1,300 litres for better off households during the reference year. Around 50-65% of this was sold, providing some cash income (shown in the section below) for these three wealth groups. Sources of Cash Income The graph to the right highlights six main sources of cash income in this livelihood zone: own crop sales, milk/egg sales, livestock sales, agricultural labour, petty trade and boda boda. All households need to depend on sources of cash from off- farm activities, although the majority of cash income for middle and better off households is generated on the farm (from crop and livestock-related sales.) The bottom two groups rely quite heavily on agricultural labour to supplement their crop and livestock-related sales. Their on-farm production is much too low to meet all of their cash needs The importance of vegetable The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 3 1,157,000 – 1,760,000 1,760,000 – 2,355,000 2,600,000 – 5,600,000 5,600,000 – 7,000,000 and fruit sales stands out in this livelihood zone, especially for the upper two wealth groups. For these households, the purchased food that dominated the ‘Sources of Food’ graphs is funded in large part by these sales of vegetables and fruits. All the crop sales combined (including beans, Irish potatoes, vegetables and fruit) accounted for (on average) 9%, 43%, 64% and 65% of annual cash income for very poor, poor, middle and better off households, respectively. Middle and better off households derived over 80% of their crop-based cash income from vegetable and fruit sales. As noted above, in the eastern part of the zone, where the altitude is not as high, bananas, mangoes, jackfruit and avocados are grown; in the western, higher altitude part of the zone, apples, peaches, avocados and futari (matunda damu) are grown. Fruit sales made up 25-30% of the crop- based cash income for middle and better off households in the reference year. Tomatoes, cabbages and sweet peppers are the main horticultural crops grown and sold; better off households marketed as much as 5,400 kg of cabbage, 1,500 kg of sweet peppers and 2,100 kg of tomatoes. Poor households also benefitted from vegetable sales, deriving over 60% of their crop-based cash from horticulture. Very poor households, on the other hand, sold only beans and Irish potatoes, and in only very small quantities. In many ways the main distinction between poor and very poor households is that very poor households are unable to cultivate vegetables, whereas poor households do; the cash incomes of very poor households suffer as a result. 3 The average exchange rate from February 2014-January 2015 was 1 USD = 1,776 TZS Western Usambara-Pare Highlands Livelihood Zone Profile 9 Two other sources of on-farm cash income (milk/egg sales and livestock sales) are less important, making up only 7-19% of annual cash income combined for all wealth groups. People keep small number of cattle, sheep and chickens and use them to generate milk, eggs and cash income from sales of live animals. Poorer households generated around 74,000 Tsh from milk and egg sales in the reference year; this was enough to cover the agricultural inputs budget of very poor households, or at least part of the school fees for their children. So although this does not compare to the 400,000 Tsh generated by better off households from milk and egg sales, it is nevertheless a meaningful amount. Sales of live animals (sheep and chickens for all households and cattle in addition to the sheep and chickens for middle and better off households) brought in around the same amount of money as milk and egg sales did for the poorer two wealth groups, and around twice as much as milk and egg income for better off households. In any case, livestock are not the major engine of the local economy in this livelihood zone, providing a relatively small supplement to other more important sources. Far more important for very poor and poor households than either crop sales or livestock-based income is the cash derived from agricultural labour. Agricultural labour is the single most important source of cash for both of these wealth groups, accounting for almost 85% of annual cash income for very poor households, and 50% of annual cash income for poor households in the reference year. Land preparation for vegetables is an especially arduous task, as everyone is forced to use hand hoes in this highland zone. There are no tractors or ox ploughs. Poorer households are routinely hired throughout the four months when this work is undertaken; land preparation alone accounts for over half of the agricultural labour income for very poor households. Watering, spraying, weeding and harvesting times also see an increase in the demand for seasonal labour, and these activities bring in the rest of the cash income in this category. All of the labour is performed for local middle and better off households. There is no seasonal agricultural labour migration to other areas. The other sources of cash income on the graph above are ‘petty trade’ and ‘boda boda’, both the domains of middle and better off households. Petty trade requires households here to have a means of transporting goods and some extra cash to purchase goods for re-sale. Boda boda requires the ownership of a motorcycle – something only the better off households have. These extra sources of cash make up between 15% and 25% of the cash income for these upper two wealth groups. The spread in income distribution is fairly large here, with those at the upper end of the wealth spectrum generating, on average, four times more than those at the bottom. Being able to cultivate vegetables is large quantities, and fruit trees, is the critical differentiator in this zone, with fruit and vegetable sales alone for the better off equivalent to 175% of the total cash income of poor households and 225% of the total annual cash income of very poor households. Expenditure Patterns The graph presents expenditure patterns for the reference year February 2014 to January 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. Households here, as in other areas of Tanzania, need to spend money throughout the year on a range of goods and services. These include: staple and non- Western Usambara-Pare Highlands Livelihood Zone Profile 10 staple food, household items, productive inputs, social services The graph provides a breakdown of total annual cash expenditure according to category of expenditure like schooling and health, as well as clothing and other miscellaneous items. A number of conclusions can be drawn from the expenditure data for this zone. First, the amount of cash spent on staple food is higher here for the top two wealth groups than in many other zones. This reflects the high purchase requirement for all wealth groups discussed in the ‘Sources of Food’ section. While relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum, in absolute terms, expenditure on food increases with wealth. Very poor households spent, on average, around 608,500 Tsh on staple food in the reference year; better off households spent 781,800 Tsh. Even in a normal year like the reference year, all households must devote a large sum of money to meeting food needs, with the proportion of annual cash spent on staple foods highest for very poor households because their total income is lowest, as discussed in the section above. In the reference year, households in the very poor wealth group bought around 58% of their minimum calories in the form of maize grain, the cheapest staple; better off households bought 31% of their calories in the form of maize grain and the other wealth groups fell somewhere in between. This was the equivalent of around 850 kg and 455 kg of maize, respectively. Middle and better off households also purchased wheat flour, which was twice as expensive as maize. All households also spent money on other foods, such as rice, sugar, meat, dried fish and oil. Very poor households also purchased cassava, as well as some Irish potatoes (along with poor households). These are all included in the non-staple food basket. Second, it is clear from the graph above that middle and better off households are investing heavily in their agricultural production, spending 30 - 40% of their annual cash income on inputs. Very poor and poor households, on the other hand, devoted only 4-8% of their annual budget to productive inputs in the reference year, either unable or unwilling to spend more. In absolute terms, better off households spent over 36 times more than very poor households on productive inputs. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, seeds and tools, pesticides and fertilizers, labour, and phone credit. All households spend part of their inputs budget on seeds and tools, and on phone credit. Very poor households, in fact, spend three-quarters of their inputs budget on phone credit and the rest on seeds and tools. Middle and better off households spend the majority of their inputs budget (60-65%) on hiring labour. Pesticides and fertilizers also account for a sizeable portion of the budget, taking up 35% of poor households’ inputs budget in the reference year and around 16% of middle and better off households’. Only middle and better off households spent money on livestock drugs and house repairs, but combined these took up less than 10% of their inputs budget. Another category of expenditure (‘hh items’) includes all of the items bought by households over the year – often in small incremental amounts - to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils. Within this category, the highest expenditure was on grinding, kerosene and soap; very poor households devoted 55% of their ‘hh items’ budget to grinding in the reference year; better off households spent around 45% of this budget on kerosene; and for middle households, grinding and soap together comprised almost 50% of this same budget. On an annual basis, spending on basic household goods comprised 7-12% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Finding ways to reduce the relatively high costs of grinding for poorer households could help them free us some money for other productive uses. ‘Social services’ includes the money spent on education and medical services. Education covers school fees, uniforms, stationery and transportation, where relevant. Absolute spending on school during the reference year was about the same for very poor and poor households (approximately 125,000 Tsh per year per household). Middle households spent more than double this amount, and better off households spent three times the amount spent by poorer households. As you move up wealth groups, households are spending more on stationery, books, uniforms, school fees and transportation. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to vocational school. Better off and Western Usambara-Pare Highlands Livelihood Zone Profile 11 middle households also spend more on medicine and health care, with each wealth group spending on average 30-50% more than the one below it. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget. Hazards There are a number of hazards that affect this zone on a regular basis. The first is inadequate and erratic rainfall. All households rely heavily on crop production from one season to at least partially meet their food needs. If rains in this season are poor, if they are interrupted at the growing stage, or if they end early, households are at risk of losing their maize, beans and Irish potato crops, all of which are rain-fed. Horticultural crops can also be damaged because, although they rely on irrigation, they are also partially rain-dependent. Thus the food and cash income of households here is substantially reduced when rains are poor. Second, livestock diseases, such as Food and Mouth disease (FMD) and East Coast fever – both of which affect cattle - and New Castle Disease, which can wipe out an entire flock of chickens, are serious problems. Third, crop pests and diseases are a constant threat. Stalk borers, which affect maize; American bollworm and late blight, which affect tomatoes and sweet peppers are among the worst. A new crop pest, known locally as kanitangaze, has been causing problems for tomatoes, African eggplants and sweet peppers. Fourth, human diseases, like malaria and typhoid, undermine the most important livelihood capital held by poorer households – their labour pool. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to find more work, either locally or migrating outside the zone, or sometimes into towns. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Middle and better off households try to increase their livestock sales. The value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Therefore, this option has quite severe limitations in this zone, where people do not have many livestock to begin with. Middle and better off households take their crops directly to markets to try to get a better price, cutting out the middlemen traders in order to increase their cash income. Middle and better off households try to increase their reliance on small businesses, buying and selling goods to make as much cash as they can with which to buy food. Western Usambara-Pare Highlands Livelihood Zone Profile 12 Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Western Usambara-Pare Highlands Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize - vuli – amount produced Beans – vuli – amount produced Beans – masika – amount produced Irish potatoes – masika – amount produced Tomatoes – amount produced Cabbage – amount produced Sweet peppers – amount produced Fruits – amount produced Beans - vuli – producer price Beans - masika – producer price Irish potatoes – masika – producer price Tomatoes – producer price Cabbage – producer price Sweet peppers – producer price Fruits – producer price Livestock production Cow milk – yields Cattle – herd size Cow milk – price Cattle – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, watering, spraying, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Petty trade – amount of trade Boda boda – level of activity Agricultural wage rates (land clearing and preparation, planting, watering, spraying, weeding) Agricultural labour rates (harvesting) Petty trade – margins on trade Boda boda – fares Expenditure Maize grain – consumer price Rice – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Provide subsidized and improved agricultural inputs, especially for seeds and fertilizers 2) Provide affordable loans 3) Improve health services and increase the availability of medicines 4) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 5) Improve road infrastructure and invest in maintenance of existing roads 6) Construct irrigation infrastructure and provide pumps 7) Develop soil water conservation systems through construction of terraces 8) Improve access to and availability of safe and reliable water supplies for humans 9) Provide electric service throughout the zone 10) Provide support for expansion of dairy cattle industry"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":179,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanga-Pwani Coastal Belt Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Tanga-Pwani Coastal Belt Livelihood Zone (TLZ 07) April, 20161 Zone Description The Tanga-Pwani Coastal Belt Livelihood Zone comprises a very narrow strip of land along the coast of the Indian Ocean, including parts of Tanga Municipal, Muheza, Mkinga, Pangani, Rufiji, Bagamoyo and Mkuranga districts2. The main ethnic groups residing here include the Zigua, Digo, Bondei, Sambaa, Pemba, Makonde, Tumbatu and Wadoe. The population density is 38 people per square kilometre3. Warm, lowland, flat plains characterise this zone. Villages are located within a narrow strip of land along the coast, interspersed with agricultural land and mangrove forests. The Pangani and Zigi rivers flow through on their way to the Indian Ocean, providing a source of fresh water to those who live in close proximity. The Saadani National Park is located at the southern end of the zone. Fish are the main natural resource, and they provide all households living here with significant food and cash income. Annual rainfall levels vary quite a bit, ranging from 600-1400 mm depending on the year and the location. The average annual precipitation for Pangani, based on a 43-year time series, is 1,176 mm. Rains fall in two seasons, the vuli from October to December and the masika from March to May. The masika rains are far more reliable and plentiful, and crop production relies heavily on these second rains. Soil fertility is relatively high, and this is a moderately productive zone despite inconsistent and unreliable rains. The household economy rests on two main pillars: crop production and fishing. Cassava and maize are the main food crops, although paddy is also produced in small quantities, along with cowpeas and green gram. These crops are all harvested only once a year, because the vuli rains are not sufficient for planting two cycles. Maize is produced almost entirely for home consumption, whereas cassava is grown both for consumption and sale, as are the other crops. Oranges, coconuts and cashews provide additional income for households who own fruit and nut trees. Ox ploughs and tractors are not used here and all households cultivate by hand. The most labour-intensive activities are land preparation and weeding and for these tasks, households with larger tracts of land hire those with less (both men and women) to work in their fields. 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in June 2014 and ended in May 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 Only a very narrow strip of coastal land is included in the zone. The coastal parts of the following wards are included in the zone: Moa, Manza, Kwale, Chongoleani, Mzizima, East Chumbageni, East Nguvumali, East Mzingani, Mabawa, Tangasisi, Tongoni, Kirare, Kigombe, Kimang’a, Pangani, Mashariki, Mwera, Mikunguni, East Tungamaa, and Mkwaja. The following wards are not part of the zone: Madanga, Marungu, Maweni, Mwanzange, Mabokweni, and Duga. 3 District Socio-economic profiles, 2014 Tanga-Pwani Coastal Belt Livelihood Zone Profile 2 People are also hired for planting and harvesting, but the demand is not as high for these tasks. Payment is made in cash, providing an important source of income to poorer households. In addition to crop production, people from all households are engaged in fishing in one way or another throughout the year. The degree to which fishing contributes to a household’s income is related to its ownership of fishing equipment – especially boats – and its ability to hire others to help fish. Poorer households work on the boats of better off households, or absentee urban boat owners, who hire local residents to manage their boats. They are paid in both cash and in fish, some of which is used for household consumption, and some of which is sold. Households with more fishing equipment use nets and bring in much larger quantities of fish, most of which is sold to generate cash income. Fishing is done mostly at night in the Indian Ocean, although some also dive for shell fish during the day. Only men are engaged in fishing. All households own small numbers of livestock, although the types and numbers owned vary by wealth. Very poor households, for example, only have chickens, whereas better off households own cattle, goats and chickens. Even better off households do not have large herds, however, because the demands of fishing and crop production already take most of a household’s time, and adequate grazing areas (and water resources) are not available to sustain large numbers of cattle. Cattle and goats graze (and browse) freely and are also given crop residues after the harvest. Chickens are fed grain and food scraps. Those who own cattle use them for milk, which is consumed at the household level and also sold, and they also sell live animals, especially young bulls, for cash. Goats are also sold for cash, and slaughtered for meat during festivals and other important occasions. Livestock rely on water from small rivers, shallow wells and seasonal pools during the rainy season; in the dry season, water from deep wells is purchased by the bucket for livestock. The expense of keeping livestock watered during the dry season is another reason that people do not keep large herds of cattle. Men are responsible for taking care of cattle and goats, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots, minimal fishing equipment and fewer livestock, earn cash from seasonal labour - clearing land, planting, weeding, harvesting and working on fishing boats. Some find work in local towns on construction projects. During times of low agricultural demand, they also collect and sell firewood or burn and sell charcoal, and produce and sell sea salt. Better off households may own small kiosks or otherwise engage in petty trade, buying and selling household goods like soap, kerosene and tobacco. Service provision here is on a par with much of rural Tanzania. Each village has tap-water, which households purchase for drinking purposes. Water for washing and laundry comes from open wells at no cost. All households use pit latrines, and some better off households use improved pit latrines. Health dispensaries are found at village level and health centres are located in ward centres. Health facilities are not well-staffed, however, and dispensaries are often poorly stocked. Primary schools are found in the villages as well and secondary schools are at ward level. Most poorer households send their children through primary school but not to secondary school because they cannot afford the extra expenses involved with secondary school, including transportation (and sometimes boarding), uniforms, stationery and books. Middle and better off households, on the other hand, typically send their children to secondary school and even college. Electricity is available in only a few villages; most households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. Almost all households have mobile phones, with better off households having multiple phones. Only better off households have access to credit through SACCOS, and options for savings are not available. There are no NGOs or development agencies working in the area. Markets The transportation infrastructure in this zone is not well developed. The zone comprises a narrow strip along the coast with rough dirt roads. The only main towns are Pangani and Tanga. Vehicles can access villages in the dry season, but in the rainy season much of the area is inaccessible. Tanga-Pwani Coastal Belt Livelihood Zone Profile 3 Fish, cassava, sesame, oranges, coconuts and cashews are the main food items produced and sold in this zone. Cattle, goats and chickens are the main livestock sold. All crops are sold at the farm gate to traders who transport them on to urban markets. Cassava is collected by traders in large bags and taken by truck to Tanga from October to March. Oranges (sold from June to August and then December to January) and coconuts (sold from December to March) are likewise taken to Tanga and then trucked onwards to Dar es Salaam, or to Arusha. Sesame has a longer journey, making its way overseas to terminal markets in India via the Dar es Salaam or Mombasa ports. Sesame sales take place in August, after the harvest. The local demand for fish comes from inland villages and nearby towns, like Tanga; but there is also a wider network of distribution, and traders come from Dar es Salaam and Arusha town to buy up local supplies. Dried fish is transported by truck, but fresh fish is taken by vehicle or boats installed with special freezers. The peak trade in fish occurs from February through April, when winds are calm and fishing is most productive. Chickens are sold within villages and to nearby towns like Pangani and Tanga, as are goats. The most common time for these animals to be sold is February through May, at the peak of the lean season. Traders go village to village buying up cattle, which get transported to urban centres for consumption. December and February through May are both peak times for cattle sales. Local households buy food throughout much of the year, with the demand for staple grains increasing during the lean season from January through May, even in years of good production. Maize is the cheapest local staple, and most of this is sourced from Handeni, Dodoma, or Kilimanjaro. Tanga acts as the main distribution point for maize that comes into the zone. Rice, a more expensive grain, is sourced from Morogoro or Mbeya and distributed via the Tanga market. Beans come from Kilimanjaro, Handeni, and Iringa, making their way to village shops via Tanga. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks, often by better off households. The labour market is mostly local, either in the agricultural sector, where seasonal jobs are found, or the fishing sector, where people find work as daily labourers on boats. Middle and better off households hire additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding, and people are needed almost year-round on fishing boats. It was estimated that in the reference year, 80% of seasonal labour was found within the zone. An additional 20% of labour demand came from local towns. While men and women both engage in seasonal agricultural labour, only men are involved in fishing labour. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Tanga-Pwani Coastal Belt Livelihood Zone the reference year covered the consumption period from June 2014 to May 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in October/November and ends with the masika harvest in June-August/September of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, rainfall during the production year corresponding to the reference year was relatively good in the masika season and below average during the vuli season. Harvests of food and cash crops were relatively good. In the past eight seasons, four were below average, three were average and one was above average. Production Year Season Rank Critical Events 2014-2015 Vuli 2 Poor rainfall distribution and poor maize yields; average cassava yields; high food prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food crops; lower prices for cash crops Tanga-Pwani Coastal Belt Livelihood Zone Profile 4 2013-2014 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 4 Good rainfall distribution; good harvest of food and cash crops; lower cash crop prices; good prices for sesame 2012-2013 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food crops; lower prices for cash crops; striga affected crops in some areas 2011-2012 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food and cash crops; wild animals destroyed crops in some areas 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Tanga-Pwani Coastal Belt Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Bagamoyo District based on a 43 - year period (1968-2010) Source: TZ Meteorology Department In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until December or January; rains for the second season, called the masika, start in March and last through May. The main food crops are only planted and harvested once, in the masika season, because the vuli rains cannot support a full production cycle. However, fruit and nut tree crops, which do not require the same consistent distribution of rains, are typically harvested twice a year. January through May are busy months in this livelihood zone. Land preparation begins after the vuli rains have softened the ground, usually starting in January and continuing through February. Maize and paddy are planted in March as soon as the masika rains are well-established. New cassava cuttings are planted as needed a month later, in April. April and May are the weeding months, requiring long days of work in the field. During these first five months of the year, very poor and poor households divide up their intra-household labour pool, with some family members working in their own fields and others hired to work in the fields of middle and better off households. For these households, much of the year’s cash is earned during this time, as shown below in the section on ‘Sources of Cash Income’. The green harvest begins in June along with the orange and mango harvest. The green harvest is particularly important for poorer households who buy the majority of their food when their own stocks run out, usually starting in February or March. Being able to eat maize green helps them to reduce their expenditure requirements. The main harvest for maize and paddy begins in July. Cassava can be harvested throughout the year, but a concerted harvest and sale takes place in August and September, helping households raise revenues to buy inputs for the next year’s agricultural season. December, January and February are months when middle and better off households benefit from the coconut and cashew harvests, along with a second season of mangoes and oranges. This helps them raise the cash they need to hire poorer household members who work for them during the agricultural season. The post-harvest period (August, September, October) is when the majority of petty trade takes place, which benefits middle and better off households who earn money from trading crops and processed foods, or who sell household goods to other households who have newly-earned income from their crop sales. October is also a time when festivals occur, as it is a relative down-period before the peak fishing season starts, and it coincides with a time when people have more cash on hand. Other festival months are July, as harvests are brought in from the fields, and December. The main fishing season is from January through April, when winds are minimal and seas are relatively calm. This coincides with much of the agricultural season, which means that families divide their labour, sending some men to work on fishing boats while women and older children work the fields, or working some evenings on fishing boats and others in their fields. Either way, it is a very busy time and people are fully engaged with productive tasks. Milk production is highest from April through July. This is when fresh pastures and water sources, fed by the masika rains, provide animals with the nutrients they need for birth and lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging ones, such as East Coast Fever, Contagious Caprine Pleuropneumonia (CCPP), and Black quarter, are likely to occur. Cattle sales peak in December, February and April and May. December sales help fund the end of year festival season as well as school fees, which are due in January. Money is also needed for agricultural inputs in February and labour hire Tanga-Pwani Coastal Belt Livelihood Zone Profile 6 in April and May. April and May is also when staple food prices tend to be highest, generating another requirement for extra cash. Human diseases have a seasonal pattern as well, with respiratory infections peaking during the dry seasons, and malaria highest in the wet seasons. Having a sick household member creates hardships on a number of levels, especially for poorer households who need as much labour on hand as possible to manage the competing demands of their own farms, seasonal agricultural labour, fishing labour and income generating activities like firewood sales, salt processing and sales, and charcoal sales. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. In this coastal zone, differences in wealth are determined in part by the area of land cultivated by a household and in part by its ownership of fishing equipment. Livestock numbers are a third differentiating factor. Those at the top of the wealth breakdown cultivate between 4 and 8 acres of land, own 1-2 boats as well as nets and other fishing equipment, and own 5-10 cattle, along with other smaller livestock. Those at the bottom cultivate 0.5 to 1.5 acres, own no cattle, and only a small number of goats (if any) and chickens. The difference in access to food and cash income for households at these two ends of the spectrum is quite large, with better off households able to generate all their required food and cash from their own fields, boats and livestock; whereas those at the bottom need to supplement their own production with various off-farm activities. All households have cell phones and bicycles, although those at the upper end have more than one of each. Bicycles act as a key means of transporting people and goods. Cell phones have become an essential means of staying connected to people and information, and there are both productive as well as social reasons for having them. The distribution of wealth in this zone is fairly even. Very poor (17%) and poor (34%) households together comprise just over half of the households in the zone. Middle (33%) and better off (16%) households combined represent just under half the population. Amongst these groups there is a fair amount of re-distribution and intra- community links are strong; better off and middle households hire poorer household members to work in their fields and on their boats. Without the labour of the lower groups, the production that better off groups generate would not be possible. Likewise, without the cash income supplied from agricultural labour, poorer households would not be able to survive. Tanga-Pwani Coastal Belt Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period June 2014 to May 2015. June represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Households in this zone obtain their food in four ways: they grow it themselves, they buy it, they get it from fishing, and they derive it from In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. their livestock (in the form of milk and meat). The differences in relative reliance on these four sources shown in the graph reflect the differences in wealth discussed above in the ‘Wealth Breakdown’ section. Better off households cultivate more land, and therefore have a higher reliance on own crops; they also have more livestock, which gives them access to milk and meat; and they have fishing equipment, which means they consume more of their own catch. Poorer households, on the other hand, with less land, less livestock and less fishing equipment, must buy more of their food to make up for gaps in their capacity to produce it. A range of different crops are grown for consumption, including maize and cassava, the main staples, along with small amounts of paddy, cowpeas, green grams, sesame and coconut. Maize is grown in the masika season, and cassava can be harvested throughout the year as needed. In the reference year a typical poor household produced around 260 kg of maize, a typical middle household produced around 480 kg of maize, and a typical better off household produced around 670 kg. Between 20% and 40% of the maize produced was sold, with poorer households selling a higher proportion than better off households. Thus home-grown maize contributed 15-35% of the minimum calories needed by households. Cassava is produced in higher quantities than maize, and in the reference year very poor and better off households harvested around 480 kg and 2,300 kg of cassava, respectively. Because of its lower calorie per kg contribution, however, cassava accounted for only 10-20% of the minimum calories needed by households, after sales. The other crops provided an additional 5-10% of annual calories, along with maize eaten green, which provided less than 5% of minimum calories. Most of the calories that people did not grow in their own fields, they purchased instead, and the purchase category as a whole accounted for 50-65% of minimum food requirements in the reference year, decreasing in value as you move up the wealth spectrum. Within this category, purchased maize, the cheapest staple, was most important for very poor and poor households (making up 25-35% of minimum calorie needs) and less important for middle and better off households (contributing only 10-15% of minimum calories). Middle and better off households bought wheat flour and rice (more expensive grains) along with fresh fish, beans, sugar, meat, oil and potatoes. The poorer two wealth groups also bought these more expensive non-staple items, but usually in smaller quantities. The ‘purchase’ bar on the graphs above, therefore, represents a different set of priorities, depending on wealth group: poorer households bought food because they had to fill a real food gap; middle and better off households, on the other hand, bought food in order to diversify their food basket. This is further supported by the fact that if better off households had consumed all of their own maize, cassava and bean production rather than selling much of it, they would have been able to cover over 133% of their minimum food needs. Very poor Tanga-Pwani Coastal Belt Livelihood Zone Profile 8 households, on the other hand, given the same assumptions, would have only been able to obtain 50% of minimum calorie requirements from their own production; and poor households also produced less than the amount needed. (Middle households, if they consumed everything they grew in the reference year could have covered 105-110% of minimum calorie needs.) Crops are grown not just for food, but also to generate cash, however, so all households needed to sell some of their production. The poorer the household, the bigger the post-crop-sale gap for the market to address. Milk and meat contributed a small amount to the diet of middle and better off households, covering 2-5% of minimum calorie needs in the reference year. A typical middle household had 1 cow milking, and better off households had, on average, 2 cows milking. Cows here produce approximately 2.5 litres of milk a day during the first rainy season (lasting around four months) and 1.5 litres of milk a day in the second season (which lasts around three months). When added together, the milk from both seasons amounted to around 435 litres for middle households and 870 litres for better off households during the reference year. Over two-thirds of this was sold, providing some cash income (shown in the section below) for these wealth groups, leaving them with enough to cover 2-4% of their calorie needs. Meat from goats slaughtered throughout the year provides better off households with an additional 1% of minimum calories. Poor households may or may not benefit from milk, depending on their livestock profile. Very poor households, who generally do not own cattle, did not have access to this source of food or cash. It is worth noting that the milk from just one cow could have helped very poor households to close the calorie gap (of around 1% of minimum needs) they had in the reference year. Fish caught by the household provide an additional source of calories. All households fish here, some using lines, hooks and baskets, others using boats and nets. Very poor households brought in around 270 kg of fish in the reference year, whereas better off households got around 840 kg. Much of this was sold, but the part retained for home consumption covered 1-4% of annual calorie needs. Although this is quite minor in terms of calories, the protein contribution is nevertheless important, especially for poorer households who do not have access to milking cows. Sources of Cash Income The graphs to the right highlight the unique importance of fishing in the local economy. Households here take advantage of their coastal location to make the most of this plentiful natural resource. In addition, a range of other income sources are drawn on, including crop sales (both food and perennial tree crops), milk sales, livestock sales, petty trade, self employment and local seasonal labour. A fundamental difference in wealth is demonstrated in The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. Tanga-Pwani Coastal Belt Livelihood Zone Profile 9 these graphs: those in the top two groups were able to generate sufficient cash amounts in the reference year from their on-farm and fishing activities alone; but. those in the bottom two groups needed to supplement their on-farm and fishing sources with casual labour sales (in seasonal construction and agriculture) and self- employment activities. This relates back to the differences in productive assets owned and utilized by the different wealth groups. Poorer households are not able to cultivate enough land, do not own enough livestock, and do not have the means to exploit fishing to the extent that enables them to be ‘self- sufficient’ in terms of their production. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,800,000 – 2,200,000 2,200,000 – 3,000,000 3,000,000 – 4,000,000 4,000,000 – 6,700,000 As shown in the graphs, 30-45% of the annual cash income for households in this livelihood zone is generated through fishing. In absolute terms, better off households earn 2.5 to 3 times more from fishing than poor and very poor households. Fishing takes place in the Indian Ocean, mostly at night, using fishing nets, hooks and lines, and on dhows, canoes, and bigger fishing boats. People from very poor and poor households may act as labourers on fishing boats owned by better off households, or on the bigger fishing vessels owned by urban dwellers. They are paid in cash, but also sometimes with a share of the fish they catch. Part of this is used for home consumption, and part is sold. They also devote some time to catching fish on their own using lines and hooks, or baskets. Those on the upper end of the wealth scale own their own boats, or manage larger boats owned by urban elite from Dar es Salaam, Zanzibar or Tanga. The cash generated from these activities is included in the graphs above under ‘fish sales’, and it helps provide households here with access to a source of cash almost all year round that is not available in neighbouring inland zones. Crop sales are equally important as a source of cash for the top three wealth groups, accounting for 35-40% of annual cash income, but they comprise just over 10% of cash income for very poor households, a much smaller share. Middle and better off households cultivate 4 to 6 times more than poor and very poor households, which allows them to sell more of their production while still meeting a large portion of their food needs. Maize is sold in all quantities by all wealth groups, but this is not the main income earner. Cassava, sold in much larger quantities, provides the bulk of the food crop income. Better off households sold over 1,500 kg of cassava (on average) in the reference year, generating as much as 770,000 TZS. Cassava is more valuable per kilo than maize (450 TZS/kg compared to 350-390 TZS/kg for maize) and it is easier for households to grow larger quantities of this drought- resistant perennial than it is to grow maize, which is more sensitive to rainfall irregularities. Very poor households also depend most heavily on cassava, supplementing this with small amounts of cash from pulses, like cowpeas and green grams. However, their total income from crop sales is quite low most years, even in a relatively good year like the reference year. Another reason for their low cash income in this category is that, unlike the top three wealth groups, very poor households do not own any fruit trees or cashew trees. They gather and sell small 4 The average exchange rate from June 2014-May 2015 was 1 USD = 2,000 TZS Tanga-Pwani Coastal Belt Livelihood Zone Profile 10 amounts of coconuts, but other households sell large quantities of oranges, mangoes and cashew nuts, which helps them to almost double the income derived from food crops alone. In addition to fishing and crop sales, the top two wealth groups depended on livestock sales and milk sales to make up almost all their remaining cash income in the reference year, and combined, these two sources accounted for almost 20% of their cash income. These sources comprised only 5-10% of cash income for poor and very poor households. In absolute terms, middle and better off households earned from livestock sales over 3 ½ times more than poor and very poor households. Middle and better off households typically sell a cow (at around 500,000 TZS) once every two years and they sell 3-4 goats (at 55,000 TZS each) every year. Very poor and poor households sell no cattle, and sell only around 1 goat a year. Chickens, which were worth around 10,000 TZS per hen in the reference year, were also sold by all wealth groups, averaging 5-7 hens sold per household. Chickens provided very poor households with almost half of their livestock-based cash income, small as that income may be. Having cattle affords the upper two wealth groups access to milk as well, much of which gets sold. As noted above, households with milking cows sold over two-thirds of the milk they generated in the reference year. This resulted in almost as much cash for better off households as live animal sales. Very poor and poor households, because they have much less crop-based and livestock-based cash income, and because they earn less from fishing, turn instead to manual labour. Land preparation is a particularly difficult task as it is all done by hand; at least two members from poorer households work for middle and better off households during the months before the rains start getting fields ready to plant. They stay on to help with planting and weeding activities as needed, and some are even employed during the harvest months. Seasonal agricultural labour is the most important source of cash for very poor households outside of fishing, and it provided them with around a quarter of their cash income in the reference year. During the off season, when demand for agricultural labour dries up, poorer households seek daily employment in local towns, helping with house construction. Another source of cash, under ‘self-employment’ comes from ‘harvesting’ salt from the sea. None of these alternative sources of cash comes easy; they all require a large investment of time away from one’s own fields and/or fishing, and they are not a guaranteed stream of income, dependent on the vagaries of the weather as well as their neighbours’ demand. Finally, middle and better off households also run small businesses and engage in petty trade, such as owning kiosks, selling prepared foods, and some with motorcycles pursue boda boda (motorcycle hire/transport). Expenditure Patterns The graph presents expenditure patterns for the reference year June 2014 to May 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other areas of Tanzania, households need to spend money throughout the year on a range of goods and services. These include: staple and non-staple food, household items, productive inputs, social services like schooling and health as well as clothing and other The graph provides a breakdown of total annual cash expenditure according to category of expenditure Tanga-Pwani Coastal Belt Livelihood Zone Profile 11 miscellaneous items. There are three main points that emerge when delving into the data that supports the graph above. First, relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum. In other words, poorer households have to spend a larger portion of their annual cash just to meet basic food needs. Even in a normal year like the reference year, very poor households devoted over a quarter of their income to staple foods, which consisted almost entirely of maize grain, the cheapest staple, along with small amounts of rice, beans, oil and dried fish. They spent the same amount on non-staple foods, which included wheat, sugar, fresh fish, meat, and potatoes. The three upper wealth groups spent more on non-staple foods than they did on staple foods, in part because they grew (or caught) more of their own staple foods, and in part because the non-staple foods were preferred commodities, so with more income available, spending on these increased. Second, investments in productive inputs increase substantially as you move up the wealth spectrum. This category includes spending on livestock drugs, seeds and tools, labour, phone credit and fishing equipment. Very poor households generally devoted only 4-8% of their annual budget to productive inputs, either unable or unwilling to spend more. Middle and better off households spent 25-30% of their cash on their various productive pursuits. In absolute terms, better off households spent almost 24 times more on inputs than very poor households. In the reference year, two categories of spending were particularly high for middle and better off households: fishing equipment and labour hire. Middle households devoted around 50% of their inputs budget to hiring seasonal agricultural labour, and 25% to fishing equipment, similar to better off households. The amount that better off households spent on just hiring labour was equivalent to around ten times the amount very poor households spent on all of their inputs combined. Poorer households spent money on livestock drugs, seeds and tools and fishing equipment. Much of their inputs budget was devoted to phone credit. Only better off households invested in buying livestock. Third, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services, firewood and utensils. Within this category, the two poorer wealth groups spent the most money on soap and kerosene. Soap alone comprised 20-30% of this budget, and kerosene took up an additional 24% in the reference year. Better off households spent the most on kerosene. On an annual basis, spending on basic household goods, which occurred in weekly or daily incremental outlays, accounted for around 10% of total expenditure for all wealth groups. Another point to note is that unlike in many rural zones of Tanzania, all wealth groups spent money on water for human consumption, with very poor households spending around 4,500 TZS a month on water and better off households spending around 12,500 TZS a month on water. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, absolute spending on school during the reference year increased as you moved up the wealth spectrum. Better off households spent around 1.5 times as much as very poor households although the difference between middle and better off households was not significant. Very poor households are generally only able to afford to send their children to primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to college. With respect to health costs, better off households again spent around 1.5-2 times as much as very poor households on a per capita basis; it is likely that these households sought treatment, when necessary, at facilities other than the village dispensary. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, bicycle service, savings, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In absolute terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. But in relative terms this category is fairly constant across all wealth groups. Tanga-Pwani Coastal Belt Livelihood Zone Profile 12 Hazards There are a number of hazards that affect this zone on a regular basis. The first is wild animals, which damage crops and reduce production. Crop pests and diseases, such as stalk borers and striga (or witch weed), which affect maize, and fruit flies, which damage oranges and mangoes, reduce yields on a regular basis, affecting access to both food and cash income. New Castle Disease, which can wipe out an entire flock of chickens, is also a regular concern, especially for very poor households who have no other livestock of note. Finally, conflict between livestock keepers and farmers is a fairly common occurrence in this zone. Pastoralists from other districts come to the coast to find grazing and water resources in the December to March period. Large herds of cattle destroy standing crops and conflict can erupt. The main, and most devastating, periodic hazard is unreliable or inconsistent rainfall, occurring once every three years, and leading to serious declines in crop production. Heavy winds and storms are a problem for fishermen who find their fishing income decline in these circumstances. Less a hazard than a constraint, unfavourable market conditions for local farmers mean they are often forced to accept unfair prices for their commodities and this lowers the income for local residents every year. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer, or eliminating clothing purchases. Poorer households try to increase their labour income from fishing, working more hours on fishing boats and more days, if possible. This strategy is limited by the demand for fishing labour, which can be quickly saturated given the finite number of fishing boats. All households also try to increase their livestock sales. Poorer households have less protection, because they only have chickens and a few goats. Livestock herds are not large for any wealth group in this area, however, and it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through increasing self-employment, especially making more charcoal and collecting and selling more firewood. They also try to process and sell more salt. This option is limited because as the year worsens, the number of people attempting to increasing their income in this way rises, increasing supplies on the market and pushing down prices. The amount of wood available locally is also limited. Better off households try to increase their fishing income by spending more hours at sea. Better off households also may reduce their spending on agricultural labour, which has knock-on effects for poorer households. Better off households with relatives outside the zone might increase their request for remittances, relying on this external source of funds to get them through the year. Tanga-Pwani Coastal Belt Livelihood Zone Profile 13 Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Tanga-Pwani Coastal Belt Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika – amount produced Paddy – amount produced Cassava – amount produced Sesame – amount produced Coconut– amount produced Oranges– amount produced Cassava – producer price Sesame – producer price Coconut – producer price Oranges – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Cow milk – price Cattle – producer price Goats – producer price Other food and cash income Fishing - yields Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Construction – number of jobs Firewood/charcoal – amount collected Self-employment – level of activity Petty trade – level of activity Fishing – producer prices Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Construction – labour rates Firewood/charcoal - prices Self-employment – return on activities Petty trade – return on activities Expenditure Maize grain – consumer price Fish – consumer price Rice – consumer price Beans – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below, prioritized by wealth group, include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. Very poor Poor Middle Better off Improve access to and availability of safe and reliable water supplies Provide affordable and timely access to agricultural inputs Provide affordable access to modern fishing equipment Improve access to and availability of safe and reliable water supplies Tanga-Pwani Coastal Belt Livelihood Zone Profile 14 Increase access to land for crop production Provide affordable access to modern fishing equipment Improve market infrastructure to ensure fair producer prices for both crop and fish produce Provide electric services throughout the zone. Provide affordable access to modern fishing equipment Improve market infrastructure to ensure fair producer prices Improve market infrastructure to ensure fair producer prices Provide affordable and timely access to agricultural inputs Improve road infrastructure"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":180,"cells":{"data":{"kind":"string","value":"# Extracted Content Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone (TLZ 18) April, 20161 Zone Description The Mbulu-Karatu Midlands Maize, Beans and Livestock Livelihood Zone encompasses parts of Mbulu and Hanang districts in Manyara Region and part of Karatu District in Arusha Region2. This mid-altitude zone is relatively cool, with flat plains broken up by hills and valleys, extending from 1,000 to 2,400 metres above sea level. Most of the zone is covered by agricultural land, which has taken over much of the previously forested areas. The Kilimapunda and Endamaksi mountains are the highest points in the zone. The lowest points are found along the Endagikot River and the Yaeda River valley, which extends from Lake Eyasi. These waterways provide seasonal access to water for people living in close proximity to them. The zone has a relatively well-developed network of roads, although only one is paved. The main arteries connect Mbulu to Babati, Singida and Arusha; and Karatu to Mang’ola and the Serengeti. The main ethnic group residing here is the Iraqw. The population density is 32-45 people per square kilometre3, with higher densities found in Arusha Region and lower densities found in Manyara. There is one long rainy season, from November through April, although this is typically interrupted in February by a stoppage in the rains. Annual precipitation ranges from 700-1,200 mm, and temperatures are cool, averaging 15 - 240 C, dropping as you move up in elevation. Fertile, silt clays and sandy soils are the norm, and the combination of relatively high rainfall and good soils makes this a moderately productive zone. The household economy is built around crop and livestock production. Maize, beans and pigeon peas are the main food crops. A few households grow sunflower as a cash crop. All production is rain-fed. Households use oxen to plough the earth; some households on the upper end of the wealth spectrum also use tractors. The use of improved seeds is common here, and people fertilize their fields with manure from their own livestock. The use of industrial fertilizers is not customary. Weeding is one of the most labour-intensive activities and middle and better off households hire men and women from poorer households during 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 The wards in Mbulu District are: Maretadu, Haydom, Maghang, Dongobesh, Bashay, Tlawi, Mbulu Mjini, Bargish, Sanu and Masieda. The wards in Karatu District are Baray, Daa, Endabash, Kansay, Endamarariek, Qurus and Karatu. 3 Based on the 2012 national census. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 2 weeding periods, and to a lesser extent for harvesting. Some people also migrate seasonally to coffee estates in Karatu District. Livestock provide a source of food and cash for all households. Cattle are the most valuable livestock, providing milk for consumption and sale and acting as a bank account, drawn down on every year to provide cash for a range of basic necessities. Bulls also get converted into plough oxen, providing a critical source of agricultural labour. Goats and sheep are also kept, eaten especially during festivals and sold for cash income. Chickens are used for eggs, eaten throughout the year, and sold whenever cash is needed, especially by poorer households. Pigs are kept by some households as well. The larger livestock migrate during the dry season, taken to areas within 20 or 30 kilometres from the villages, where better access to pasture and water can be found, such as Yaeda Chini or the Eyasi Basin. Rainy season water sources for livestock include charcoal dams, the perennial rivers, seasonal rivers, shallow wells and seasonal ponds. In the dry season, livestock use reservoirs and dams, the perennial rivers and wells. Men manage the cattle, goats and sheep; women are responsible for the chickens and pigs. In addition to crop and livestock production, brick sales and firewood and charcoal sales bring income to poorer households. These sources of cash, along with seasonal agricultural labour, are of critical importance to households who do not have enough land and livestock to make ends meet. Service provision in this zone is basic. Water for all purposes comes from seasonal rivers, ponds, open wells, boreholes and tap water. There is some payment expected for tap water, but the other sources are free. The quality of water is quite poor in most villages, with the exception of villages where tap water is the main source, such as Endagem, Changarawe and Qurus in Karatu. Sanitation facilities consist of pit latrines with no covers. Waste is collected and burned. Health dispensaries are found in many villages, or at the ward centre, although these are often poorly stocked and under-staffed. Better off households have access to private hospitals if they can make their way to Mbulu, Karatu or Arusha. Primary schools are found in the villages and secondary schools are available in the ward centres, which are often too far for children to reach on a daily basis. Poorer households only send their children to primary, or at most secondary school. Better off households usually manage to send their children to at least secondary school and often to college. There is electricity in only a few villages; in most villages households depend on solar lamps and solar panels. Households in all wealth groups have mobile phones, with better off households having multiple phones. Better off households have access to credit through VICOBA, SILC and SACCOS. Savings facilities are provided through VICOBA and SILC. A number of NGOs and government agencies operate here, including TASAF (Tanzania Social Action Fund), which supports poorer households by providing funds to cover food, education and health as well as helping build hospitals, schools and bridges, etc.; the Diocese of Mbulu Development Department, which undertakes the construction of improved toilets and toilet seat covers for schools; the Roman Catholic church, which supports the construction of bore holes; and HELVETORS, which undertakes actions to prevent post-harvest losses. Markets The transportation infrastructure in this zone is variable, with relatively good access in the dry season, but serious problems during the wet season. Mbulu and Karatu are the main intermediate markets and Arusha is a central terminal market. There is only one tarmac road in the zone, connecting Karatu to Arusha and Ngorongoro gate. The others, from Singida to Haydom and Mbulu; and from Babati to Mbulu are not paved. The more remote villages are hard to reach, accessed via rough dirt roads, many with deep eroded gullies. In the dry season these roads are passable, but they become difficult to traverse in the wet season. Most of the bridges are in relatively good condition. Well-worn dirt tracks take people by foot from villages to cultivated fields, pastures and water points, and walking is the most common means of transportation. Maize, beans, pigeon peas, sunflower, cattle, goats and sheep are the commodities sold by households in this zone. Locally-produced crops are purchased by small traders at the farm gate. August and September are when traders come to villages in order to buy up maize harvests, and any pigeon peas that local Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 3 households might want to sell. The traders arrange for crops to be bundled and transported to larger market hubs during the post-harvest dry season months, when trucks can still travel on the dirt roads. Haydom, in Mbulu, is one of these market hubs; Karatu is another. Arusha is the terminal market for maize, but pigeon peas are often exported after being transported to Dar es Salaam via Arusha. Beans are sold in March and April, following the same trade route used for maize. Sunflower, sold mostly by better off households, is collected in Haydom or Karatu, where it is processed into oil for local consumption. Cattle, goats and sheep are sold at small weekly ward- and sub-ward level markets within the zone throughout the year. Traders generally do not come to the villages for livestock, with the exception of pigs. From the livestock markets, traders collect and transport livestock to Duka Bovu in Arusha, and then on to Weruweru in Kilimanjaro, Korogwe in Tanga and finally the Pugu market in Dar es Salaam. Much of this trade takes place from August to November, just before the rains start in earnest. This is a time when households need extra cash in order to pay for agricultural inputs; and it is also a time when roads throughout the zone are still accessible. In addition to local commodities that are sold for ‘export’ from the zone, there is an active importation of food and other basic goods for consumption by local households. Poorer households need to buy maize grain to cover their needs for seven to nine months of the year, especially from November to March, even in relatively good production years. Maize is the cheapest local staple, and all of this is locally sourced, procured from better off households who generally produce a large surplus. Rice, purchased mostly by the upper wealth groups, is sourced from Magugu and Shinyanga, collected in Mbulu and Karatu and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local markets. The labour market is almost entirely local seasonal agricultural labour. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, especially weeding and harvesting. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms. An additional 5% of labour demand came from local towns and the other 5% came from outside the livelihood zone, mainly from the Oldeani coffee estates in Karatu District. Both men and women from poorer households take on paid agricultural work. The coffee estates are a primary place for seeking work in bad years, when poor rains reduce local production. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the planting season in December and ends with the harvest in June through August of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year of 2014- 2015 was average, with average rainfall, a decent harvest, average staple food prices, and average livestock prices. The reference year followed an average year and a below average year. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an average year after a fairly normal sequence of years. Production Year Season Rank Critical Events 2014-2015 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 2013-2014 Masika 3 Average rainfall, good crop yields, average staple food and livestock prices. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 4 2012-2013 Masika 3 Average rainfall, good crop yields, average staple food and livestock prices. 2011-2012 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 2010-2011 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year The seasonal calendar below highlights the competing demands of livestock raising and crop production in this agro-pastoral zone. The rains determine the timing of productive activities here, signalling the start and stop of a range of crop and livestock management tasks. There is one long rainy season, which begins in November and continues through April, although it is common for rains to stop for a while in February. People begin to prepare lands in October and continue this through November, as the new rains help to soften the ground. The November rains also provide a welcome boost to pastures. All crops are planted in December and January, followed by a period of weeding that lasts from mid-January through April. Maize, beans and pigeon peas are inter-cropped; sunflower is planted as a single stand around the edges of fields. The green harvest of maize starts in April, although beans can be harvested green as early as March. June marks the start of the main maize harvest, which lasts through August. This coincides with the sunflower harvest, which is relevant mainly for better off households. Pigeon peas are harvested as late as September and October. As planting activities are in full swing, in January, milk production begins to increase as a result of fresh pastures and renewed sources of water that come with the rains. The rains also bring livestock diseases. Contagious Bovine Pleura-pneumonia (CBPP), Contagious Caprine Pleura-pneumonia (CCPP) and Black Quarter occur with higher frequency during the rains. Thus, as people are busy in their fields, they also must contend with more work related to milking and caring for livestock. Livestock sales are highest from July to October, a time when households are putting together the cash they need for the coming agricultural season. The peak agricultural labour period is during weeding time. Land preparation is not as arduous here as in many areas because ploughing is done with ox ploughs, not hand hoes. Poorer households who do not own oxen themselves obtain access to oxen and ploughs by exchanging their labour for it. This reduces the effort involved in land preparation and ploughing, and it means that poorer households are generally not paid in cash for any work related to land preparation. Weeding, however, is done entirely by hand, and poorer households are hired throughout the weeding period to work on the larger farms of middle and better off households. At the same time, poorer households need to weed their own fields, which leads them to split their labour pool, sending some members to work for cash, while others work in their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. They often also miss the best times for ploughing and planting because they must wait for plough oxen to finish cultivating the farms of the oxen’s owners before being deployed to their farms. The weeding period coincides with a time when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as September or October, but by November none of the poorer households have their own food stocks left at home. These households need to purchase all of their staple foods Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 5 just when the price of staple foods is highest (from December through March). Thus, the paid work offered up by middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize begins. The rainy season is also when most human illnesses occur. Malaria is a serious problem here, and the rains bring about a new influx of mosquitoes and a greater incidence of sickness. This increases the expenditure requirements for medical treatment at a time of year when other outlays (on staple food and education – in January) are already high. Remittances from relatives living outside the zone are most commonly sent in January and February to help cover school fees and also to help cover the costs of staple foods. The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35 -year period (1980-2014). Source: TZ Meteorology Department Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 6 May through October is the dry season. At this time, poorer household members earn extra cash by collecting and selling firewood, or making charcoal. Brick making also peaks at this time. It is often women and children who collect the firewood; men are involved in charcoal and brick production. People need to set aside money at this time to prepare for the costs associated with the coming agricultural season and to pay back any loans accrued in the past year. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The main determinants of wealth in this zone are, first, the amount of land a household cultivates and, second, the number of livestock, particularly cattle, a household owns. In important ways these two things are inter- related: bigger herds generate more cash, which enables people to buy or rent tractors and hire labourers to expand the area they have under cultivation. On the other side, the more land a household has under cultivation, the larger its harvests; and with more crop production, a household is able to reduce the money it spends on food for survival, and – with the proceeds from crop sales - invest more in the health and growth of its livestock herd. A typical better off household, therefore, cultivates around 7-9 acres and owns 15-25 cattle, 20-40 goats, 5-20 sheep and 6-8 oxen. These are slightly bigger households, with around 7-9 members. In addition to land and livestock, other assets, like ploughs, ox carts and cell phones are commonly owned. Of all the households, these are the most likely to have a motorcycle as well, which can provide additional cash through boda boda (motorcycle taxi or transport hire). Better off households benefit from surplus crop production and sizeable supplies of milk. These households hire very poor and poor household members to help with weeding and harvesting activities, because they do not have enough intra-household labour to manage their fields on their own. A typical very poor household, on the other hand, cultivates only 1.5-2 acres of land, working in exchange for access to plough oxen. These households have no cattle, and small numbers of goats (2-6), sheep (0-2) and pigs (0-2). They have 5-15 chickens which are, relatively speaking, significant to them as a source of cash. Very poor households tend to be smaller in size, with only 5-7 members. This means that they have a difficult time managing the many competing labour requirements associated with the cropping season, especially since they need to work on both their own fields and the fields of better off households, where they earn cash that is critical to their survival. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 7 The distribution of wealth in this zone is weighted towards poorer households, with very poor (30%) and poor (32%) households together comprising over 60% of households in the zone. Middle (26%) and better off (12%) households combined represent just over a third of the population. However, as middle and better off households are slightly larger, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is larger than this. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12- month period. This was considered an average year, with average rains, crop yields and prices. Own crops, own milk and meat, and purchased food are the three In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. sources of food in this livelihood zone. Households’ own crop production made up 45-65% of minimum calorie requirements for very poor and poor households in the reference year, with maize, beans and pigeon peas the only food crops grown. This means that even in an average year, poorer households do not depend on their own crop production to cover all of their own food needs. Middle and better off households produced considerably more, meeting the vast majority (90-98%) of their minimum calorie needs with their own crops; in addition, what they consume is only a portion of the total they grow, since a good deal of their crops are sold in a year like the reference year. In fact, if households did not sell any of the crops they produced, consuming them instead, all except for the very poor would well exceed their minimum calorie requirements. The reference year production of maize for typical very poor, poor, middle and better off households was 970 kg, 1,800 kg, 3,200 kg, and 5,050 kg, respectively. For beans and pigeon peas combined it was 210 kg, 315 kg, 495 kg, and 910 kg, respectively. In calorie terms, the total production of maize and beans together represented 90%, 150%, 230% and 330% of minimum calorie requirements, respectively. All households, however, sold at least half of their production for cash (with sales as a proportion of production increasing as you move up with wealth scale) to meet a range of expenditure requirements throughout the year, which means that their own crop production covered less of their food needs than it could have. Milk, and to a much lesser degree meat, provided additional calories in the reference year, but only for the top three wealth groups. Very poor households own neither cattle nor substantial numbers of goats, and do not benefit from this source of food. A typical poor household had around 1 cow milking throughout much of the year, middle households had around 3 cows milking, and better off households had 5 cows milking. Milk yields are not very high in this livelihood zone due to limitations on pasture, but the 1.25 litres per cow per day during the rainy season, and 0.5 litres a day in the dry season accumulated over the year to total around 220 litres for poor households, 660 litres for middle and 1,100 litres for better off households. The upper two wealth groups sold 15-30% of this in the reference year, leaving them with enough milk to cover around 6% of their annual calorie needs; poor households did not sell any of their milk, using it all for home consumption. For them, milk covered around 3% of their food needs. There was also a small contribution (only around 1% of calorie needs) from goat meat for middle and better off households. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 8 Food purchased from the market made up all of the remaining food needs for all wealth groups, comprising around 20-45% of minimum calorie requirements. Those in the upper two wealth groups bought less (20-21% of minimum calories) and those in the bottom two wealth groups bought more (35-45% of minimum calories). This is because, as explained above, poorer households produced less of their own food in the reference year and needed to buy food to make up for the gap. What poorer households purchased supports this argument: 28-36% of their minimum calories were comprised of purchased maize grain, the cheapest staple. Middle households bought only 5% of their calories in the form of maize grain, and better off households purchased no maize grain at all. The ‘purchase’ component for better off households was comprised of high-value, preferred foods, such as rice, wheat, sweet potatoes, meat, oil, sugar, Irish potatoes and dried fish. Thus, the 20% of minimum calories purchased by these households diversified their diets and added nutrients and protein they otherwise could not produce themselves. Poorer households, on the other hand, purchased only around 8-9% of their minimum calories for the sake of diversity, and most of this was oil. The largest portion of their ‘purchase’ component was devoted to filling a real calorie gap and meeting their minimum food needs for the year. Sources of Cash Income The graphs to the right present the sources of cash income in the reference year by wealth group, first in terms of absolute values, and next as a proportion of annual cash income. They reveal a number of points about the local household economy. First, livestock- related income is clearly important for the top three wealth groups. Thus, even in a year of decent crop production, cash income depends more on livestock than on crops. Second, there is a noticeable difference between the sources of cash income for those in the upper three wealth groups and those in the bottom wealth group. Very poor households derived more than half of their annual cash income from off their own farms, working for others, or generating income from self- employment activities. The top three wealth groups, on the other hand, obtained 80- 100% of their cash income from their own farms – both from crops and from livestock – in the reference year. The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 9 There were five main sources of cash income in the reference year: own crop sales, own milk/egg sales, livestock sales, seasonal agricultural labour, and self-employment. On average, better off households’ annual cash income was over four times higher than very poor households’. In the reference year, crop sales accounted for 27-46% of cash income for households. Maize, beans, pigeon peas and sunflower are sold, although sunflower is only sold by better off households. Maize provides the majority of crop-based cash income, accounting for over two-thirds of the cash earnings from crop sales. Beans and pigeon peas garner a higher price than maize, sold at an average of 2 ½ times more per kilogramme, but far larger quantities of maize are sold. In the reference year, beans brought in 30-40% of the crop-sale income for local households. In years when rains are inconsistent, beans become even more important, as they have a higher tolerance to drought than maize, and their price tends to increase in bad years. Better off households grow and sell a small amount of sunflower as well, although this is not crucial income when viewed on an annual basis. In absolute terms, better off households generated over 7 times more from their crop sales than very poor households, which is proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 4.5 times more land than very poor households, but are able to derive more per acre from their efforts, investing more in terms of labour and inputs, and able to time their ploughing, labour and inputs applications for more effective outcomes. Sales of live animals (fattened oxen, cattle, goats, sheep, chickens, and pigs), milk and eggs provided an additional source of earnings in the reference year, making up around 15% of very poor household annual cash income, and 45-65% of middle and better off cash income. Poor, middle and better off households sold, on average, 0-1, 1-2, and 2-3 oxen (at 500,000-600,000 TZS per head), respectively, in the reference year; along with 1-2 heads of cattle (at around 300,000 TZS per head); 2-5 goats (at 35,000 TZS each) and 1-3 sheep (at 25,000-30,000 TZS each). Of these, very poor households sold only goats and sheep, 0-2 in total. All households also sold chickens, averaging around 8 hen sales per year at 8,000 each. Although households sell a number of livestock species, cattle are the most important, and the cash that better off households generated with their cattle and oxen sales alone exceeded the average annual cash income (all sources combined) of both very poor and poor households. Cattle are also important because of the milk they provide, and the upper two wealth groups both benefitted from milk income, accounting for around 4-8% of their total cash earnings. In addition, egg sales contributed a small amount of cash for all four wealth groups. While better off households obtained almost all of their cash income from livestock- and crop-based sources, poorer households needed to supplement their farm-based cash income with other options. Seasonal agricultural labour and self-employment both provided additional cash for poorer households, and these are especially important sources for very poor households. Weeding is a busy time, and very poor and poor households split their efforts between their own farms and the farms of middle and better off households, where they work for a daily fee. As mentioned previously, because middle and better off households use ox ploughs and tractors, land preparation activities are not as labour-intensive, and people are not usually hired for land preparation and planting. But weeding is done entirely by hand and occupies people’s time for three months of the year. People also get hired for harvesting work, but this lasts only for around a month. Seasonal agricultural labour provided very poor households with around a quarter of their cash income in the reference year, and it provided poor households with around 10% of their cash income. In the dry season, after the harvest ends but before the next agricultural season begins (July to December), poorer households rely on making and selling bricks as a source of earnings. Very poor households also gather and sell firewood and make charcoal. These self-employment activities account for around 35% of annual cash income for very poor households and around 5% of poor households’ cash income. Finally, better off households obtained a small amount of their cash during the reference year from credit. Technically this is not ‘income’ in the same sense as other sources, because it must be paid back with interest; but it does provide these upper households with additional financial resources with which to fund their productive activities. None of the other wealth groups had access to credit in the reference year. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. There are a number of essential goods and services that households in this zone need to spend their money on each year. These include: staple and non-staple food, household items, productive inputs, social services, like schooling and health, in addition to clothing and The graph provides a breakdown of total annual cash expenditure according to category of expenditure other miscellaneous items. The graph illustrates a general trend in rural Tanzania: poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. These trends are discussed in more detail below. In an average year, like the reference year, all wealth groups buy staple foods, however the composition of the staple food basket is not the same for all wealth groups. In this zone, staple foods were defined as maize grain, sweet potatoes, wheat flour and rice. Very poor households devoted almost all of their expenditure on staple foods to maize grain, the cheapest staple, spending nothing on sweet potatoes or wheat, and only a very small amount on rice. Better off households, on the other hand, bought no maize grain, but did spend money on sweet potatoes, wheat flour and rice, all of which are preferred higher-priced foods. (For example, rice costs 2,000 TZS per kg on average, whereas maize grain costs around 555 TZS per kg.) Thus, poorer households bought staple foods to fill a calorie gap, whereas better off households bought staple foods to fill a diversity gap. This is an important point, because without the purchase of staple foods, the very poor wealth group would have been facing a food deficit, but the same cannot be said for the two upper wealth groups. The same motivation extended to non-staple food purchases, a category in which better off households spent over three times more than very poor households. The non-staple foods category includes money spent on beans, sugar, meat, oil, fried fish, vegetables and Irish potatoes. Sugar and oil comprised 50-60% of the non-staple food budget for all wealth groups; sugar is used in relatively high amounts here, with around 1.5-1.75 kg of sugar purchased and consumed by the upper two wealth groups every week, and closer to ½ kg per week consumed by the lower two wealth groups. The lower two wealth groups did not buy vegetables and Irish potatoes, mainly buying sugar, oil and dried fish, along with small amounts of beans. Their spending on meat was quite minimal. Middle and better off households spent substantially more on meat, but tended not to buy beans (since they produced enough of these on their own). They also devoted more cash income to vegetables and Irish potatoes, although the latter was purchased only by better off households. The dark blue bar on the graph above represents spending on productive inputs, including the following: livestock drugs, spare parts for fixing ploughs, seeds and tools, labour hire, livestock purchase, house repair, phone credit and loan repayment. Of these items, very poor households spent money only on seeds/tools and phone credit, with a roughly equal amount spent on each. Poor households spent most of their money on seeds/tools (30% of their inputs budget), livestock purchase (28% of their inputs budget) and phone credit (26% of their inputs budget). They also spent some cash on livestock drugs and house repairs. Middle and better off households spent the majority of their inputs budget on labour hire and livestock purchases. In absolute terms, better off households Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 11 spent more than 20 times the amount spent by very poor households and double the amount spent by middle households. Better off households had to invest large amounts of cash into hiring labour (which took almost a third of their inputs budget in the reference year), and livestock purchase (which took around a quarter their inputs budget). A typical better off household spent around 502,200 TZS on hiring labour in the reference year. When we compare this to the amount of seasonal labour income very poor households obtained in the reference year (around 234,000 TZS) we see that every better off household supported around 2 households in the very poor wealth group. This highlights the particular importance of this intra-community exchange of labour and cash: very poor households could not survive without this income; and better off households need the labour from very poor households to generate their surplus production. One final point is that better off households are the only ones who have to spend money repaying loans: this takes up around 10% of their inputs budget. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor households spent the most money on payment for grinding, which took up around 40% of their spending in this category, followed by soap. Poor households also spent the most money on these two categories, with the combined spending on these two items alone comprising around 60% of their inputs budget in the reference year. Middle and better off households spent the most on soap followed by grinding and utensils. On an annual basis, spending on basic household goods comprised 7-13% of total expenditure, decreasing as a proportion of annual expenditure as wealth increases (although increasing in absolute terms). ‘Social services’ includes schooling and health costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, middle and better off households spent around the same amount on education, and these two wealth groups spent around 2 times more than very poor households, although not much more than poor households. Very poor households are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent three times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute and relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was a relatively good year, even the very poor wealth group had more in this budget than it would in a bad year. Hazards There are a number of hazards that affect this zone on a regular basis. The first is livestock disease, such as Foot and Mouth Disease (FMD), tick-borne diseases and East Coast Fever. Contagious Bovine Pleuropneumonia (CBPP) and Contagious Caprine Pleuropneumonia (CCPP) affect cattle and goats, respectively4. Helminthiasis (worms) is a common problem, as well as New Castle Disease, which can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. The second is crop pests and diseases. Stalk borers, which affect maize; and aphids and rust fungus, which reduce yields for beans, cause lossees throughout the zone almost every year. Birds can also ruin crops. The main, and most devastating, periodic hazard is inadequate rainfall, which leads to serious declines in crop production, degradation of pastures, drying up of local water sources and spikes in food prices. This occurs once 4 http://www.lrrd.org/lrrd26/8/swai26138.htm Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 12 every three years. Army worms devastate local maize harvests once every five years. Floods also cause damage to crops once every five years, on average. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. Poorer households sell more goats, sheep and chickens, and some sell pigs. Middle and better off households sell more cattle, oxen, goats, sheep and chickens. This strategy is far more successful for middle and better off households than for poorer households. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Also, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people go to the Oldeani coffee estates in Karatu District. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Better off households decrease the amount of money they pay (wage rates) for agricultural labour. This directly contradicts the attempts made by poorer households to increase their casual labour income. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika – amount produced Beans – amount produced Pigeon peas – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Livestock production Cow milk – yields Fattened oxen – numbers per household Cattle – herd size Goats – herd size Sheep – herd size Pigs – numbers per household Cow milk – price Fattened oxen - price Cattle – producer price Goats – producer price Sheep – producer price Pigs – producer price Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 13 Chickens – flock size Chickens – producer price Other food and cash income Agricultural labour (weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Brick production – numbers produced Firewood/charcoal – bundles collected Self-employment – level of activity Credit – amount of credit issued Agricultural wage rates (weeding) Agricultural labour rates (harvesting) Bricks – prices Firewood/charcoal – price per bundle Self-employment – return on activities Credit – terms/rates of repayment Expenditure Maize grain – consumer price Sugar – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than credit, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Timely and affordable provision of crop and livestock inputs to all households Access to affordable and safe sources of water for humans and animals Provision of health services at village level, including qualified health professionals and sufficient and affordable supplies of medicines Improved maintenance of existing road networks and increased construction of new roads Provision of electricity at village level Improved livestock health infrastructure, including dip tanks, charcoal dams and crushes Targeted capital investments in agricultural activities and entrepreneurship"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":181,"cells":{"data":{"kind":"string","value":"# Extracted Content Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone (TLZ 25) April, 20161 Zone Description The Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone2 is found in the central-northern part of Tanzania, and it includes parts of Babati, Hanang and Singida districts. The zone sits at a relatively high altitude, with elevation ranging from 1,000 to 2,000 metres above sea level. Mt. Hanang, which is found here, rises to 3,420 meters above sea level. The topography is made up of rolling plains and valleys, and mountainous terrain around Mt. Hanang. Agricultural fields surround villages, and outside of these areas one finds bush-covered savannahs and some marshlands in the Bubu River catchment. This river, along with a number of seasonal waterways, such as the Bagara, Endasaki and Dirma rivers, provide water for people living nearby. Other open water sources include Kisisi and Matumbo lakes, along with a number of smaller seasonal ponds. Bassotu, Gendabi, and Balandalalu are salt lakes, providing occasional opportunities for salt mining. The zone’s road network is fairly extensive, with a tarmac road connecting Babati and Singida, and dirt or marram roads connecting Katesh to Kondoa via Dirma; Katesh to Hydom via Basutu; and Singida to Meatu via Mudida and Mkalama. The main ethnic groups found here are the Iraqw, Gorowa and Barabaig in Babati and Hanang; and the Nyaturu in Singida. The population density is 28-78 people per square kilometre3, with higher densities found in Manyara Region and lower densities found in Singida. The rains here fall from mid-November to April, interrupted for one month in February by a dry spell. Annual precipitation ranges from 350-1,2004 mm and temperatures average 20-300 C in the hot season, and 16-200 C in the cooler months. The soils are fertile red and black loams, and when rains are good, this zone can expect high levels of crop production. In years when the rains are insufficient or poorly distributed, production drops substantially and households have trouble covering their food needs. The household economy is based on crop production and livestock husbandry. Maize, sorghum, beans, pigeon peas, and sunflower are all grown, with maize and beans the central food crops; and sunflower the 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2013 and ended in March 2014. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 The zonal boundaries for TLZ25, as drawn during the 2008 FEWS NET livelihood zoning, need to be revised as follows: Qash, Bonga and Gidas are not in this zone, but in TLZ16; and Nkaiti, Mwada, Magugu and part of Kiru wards should form a separate zone as this area benefits from irrigation and grows maize, cotton, sesame, rice, sugarcane and watermelon, and there are more cattle per household. 3 Based on the 2012 national census. 4 Hanang DC gets 350-900 mm; Babati DC gets 500-1200 mm; Singida DC gets 500-850 mm. Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 2 main cash crop. However, it is misleading to think of the food crops as being grown just for consumption, since all food crops are also sold, with pulses especially important in terms of cash earnings. All production is rain-fed. Ploughing is done using oxen for the most part, although some households on the upper end of the wealth spectrum use tractors, and those at the bottom end may use hand hoes. Some poorer households work for better off households in exchange for use of their plough oxen. Most households buy improved seeds but they do not buy industrial fertilisers. People either fertilise their fields with manure from their own livestock or they do not use it. The agricultural season involves periods of intense labour; weeding is especially arduous, done using hand hoes, and threshing is also done by hand. Middle and better off households have more land under cultivation than they can manage with just their intra-household labour, so they hire members from poor and very poor households to work for them during these labour-heavy times of the year. This provides important cash for poorer households, who could not survive without this seasonal work. This zone is distinct from neighbouring livelihood zones like TLZ16 and TLZ55 in that these other zones rely on different crops, like bulrush millet, sesame and groundnuts. Livestock is a secondary, but vital, source of food and cash for all households. Cattle are the most prized of the livestock, and they are owned in the greatest numbers by households at the upper end of the wealth spectrum. Cattle provide milk for consumption and young bulls are sold for substantial amounts of cash when needed. Select bulls also get converted into plough oxen. Goats are also sold for cash income, and slaughtered for meat during festivals or special events. Chickens are eaten and sold whenever cash is needed, especially by poorer households. The larger livestock migrate during the driest months of September, October and November, taken to grazing areas in Singida around a national forest in south- eastern Ngimu, or to the southern parts of Hanang, where better pasture and water sources can be found. Wet season water sources for livestock include seasonal and perennial rivers and seasonal ponds. In the dry season, livestock use water from deep wells. There is payment for tap water for use by livestock in some villages. Men manage the cattle and goats; women are responsible for the chickens. If households are unable to find enough work locally, they may also send members to work in towns or to sugar plantations in Moshi or flower plantations in Arusha. A few individuals also find work mining salt or sand and gravel, but this is not typical for all households. A minority of households near the lakes engage in fishing but this is not typical for the zone. In bad years, poorer households also collect and sell firewood to earn extra cash. The services in this zone are similar to many rural areas in Tanzania. Water for all purposes comes from open wells, charcoal dams, local shallow wells, boreholes and village taps. People usually pay a small fee to use the tap water, but all other sources are free. However, there is no guarantee that these other sources are safe to drink. Sanitation facilities consist of pit latrines, most without covers. Health dispensaries are found in many villages, or at the ward centre, but they are not always well-stocked or staffed with qualified medical professionals. Traditional healers are sought out in many cases. Primary schools are found in the villages and secondary schools are available in the ward centres. It is common for all households to send their children through primary school, but only middle and better off households are able to afford the extra costs of secondary school. There is no electricity, so poorer households depend on kerosene lamps, battery-operated torches and some solar lamps; better off households generally use solar lamps. Households in all wealth groups have mobile phones, with better off households owning multiple phones. Telecommunications services are provided by Airtel and Vodacom networks. Credit facilities do not exist for the most part. Households can take part in VICOBA savings schemes, which provide a rotating mechanism that allows each member to contribute cash on a regular basis throughout the year and receive annual disbursements. No NGOs of note are working in this zone. Markets The transportation infrastructure is relatively good. A main inter-regional tarmac road, from Babati to Singida, passes through the zone and there are other decent dirt roads connecting Katesh to Kondoa, and Kateshi to Highdom. Access to more remote, interior villages is not ensured during the rainy season, when Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 3 roads become muddy and impassable; but in the dry season, vehicles are able to get around with relative ease. People travel by foot from villages to cultivated fields, pastures and water points, and walking is the most common means of transportation for most. Babati, Katesh and Singida are the main intermediate markets, along with Arusha. Dar es Salaam, Mwanza and Nairobi are all terminal markets. Market information is conveyed through relatively good mobile phone networks, and there are emerging small business centres at the village and ward levels. Locally-grown maize, beans, pigeon peas, and sunflower are sold by all households, providing the most important source of cash for many. Livestock, cattle, goats and chickens, provide a secondary source of income. Sheep and pigs are not commonly kept here. Transactions around crops occur at the farm gate; traders circulate from village to village and buy up crops and then transport them to either Babati, Katesh or Singida. The traders arrange for crops to be bundled and transported to larger market hubs during the post-harvest dry season months, when trucks can still travel on the dirt roads. Maize typically remains in these terminal markets for regional consumption, whereas beans, pigeon peas and sunflowers continue onwards. These crops are taken either to Arusha or Singida and then to Dar es Salaam or Nairobi (from Arusha) or Mwanza (from Singida). Maize is traded from July to September; sunflower is traded from May to August; and beans are traded from August to October. Livestock are sold at small mobile ward- and sub-ward level markets within the zone throughout the year. From the livestock markets, traders collect and transport livestock to one of the intermediate markets (Babati, Katesh or Singida) and then on to Arusha or Dar es Salaam. Cattle are sold most frequently from July to August; this is a time when livestock body condition is good, with animals fattened on recent crop residues, and roads are still accessible before the heavier rains in March and April. Middle and better off households need money at this time to cover school fees, uniforms and stationery for the second term. They also are putting cash together to pay for the many cash needs associated with the agricultural season. Also, traditional festivals, marriages and religious ceremonies occur in this period. Peak months for selling goats are July, December and March, the first two of which are associated with school fees, festival or holidays seasons and the last of which is associated with peak staple food expenditures, weeding payment and livestock drugs. Poorer households need to buy maize grain, the cheapest staple, to cover their needs for five to seven months of the year, especially from December to March, even in relatively good production years. Most maize is locally sourced, procured from better off households who generally produce a large surplus. In bad years, maize comes into the zone from Arusha. Rice is purchased as well, most commonly by the upper wealth groups, and this is sourced from Igunga, Magugu and Shinyanga and comes into the zone via Babati, Katesh and Singida and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local markets. The labour market is mostly local and consists of seasonal agricultural labour. There is also a sizeable demand from local towns and some work is found outside the livelihood zone. It was estimated that in the reference year, 70% of seasonal labour was found within the zone on local farms. An additional 20% of labour demand came from local towns, especially Singida town, and the other 10% came from outside the livelihood zone, mainly from sugar plantations in Moshi or flower plantations in Arusha. The balance shifts in bad years, with more people traveling to local towns or to areas outside the zone to find work. A certain amount of casual labour is also found in the salt mining areas of Gendabi, Balangidalalu, and Basutu, or from sand and gravel mining, but this is not typical for most households. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Manyara- Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone the reference year covered the consumption period from April 2013 to March 2014. This followed on the production year of 2012-2013. The production year starts with the planting season in November/December and ends with the harvest in June through Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 4 August/September of the following calendar year. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the responses of the community leaders, shows year quality by production year. The reason that the consumption year of 2014-2015 (following the 2013- 2014 production year) could not be used as a reference year is because it was an excellent year, which would not have been representative of livelihoods in this zone. Thus, the production year of 2012-2013, which corresponds to the consumption year of 2013-2014 was used, as this was an average year. In the past five years most have been average, with one excellent year and one below average year. This most recent production year (2014-2015) is the worst of the past five years. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an average year. Production Year Season Rank Critical Events 2014-2015 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, the top three wealth groups sold more livestock; there was increased attempt to find work among very poor and poor households, with migration to other areas 2013-2014 Masika 5 Excellent amount and distribution of rainfall leading to bumper harvest and low staple prices 2012-2013 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 2011-2012 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 2010-2011 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year There is one long rainy season which begins in November and lasts through April. A dry spell occurs most years in February, and the rains that follow, in March and April, are usually heavier than those from November through January. The rains determine the timing of all the productive activities, signalling the start and stop of a range of crop-related and livestock management tasks. People begin to prepare their fields just after all of the crops from the previous year have been harvested, starting in September, and continuing through November. The November rains help to soften the ground enough to allow for planting of maize to begin part way through November. Pulses and sunflower are planted in December. Maize is often inter-cropped with the other crops, with combinations of maize and beans, maize and pigeon peas and maize and sunflower found throughout the zone. The green harvest of maize starts at the end of March or the beginning of April, although beans can be harvested green as early as February. June marks the start of the main maize harvest for maize and sorghum, which lasts through August. Beans can be planted and harvested twice, with March and July the main harvesting months for this crop. The sunflower harvest occurs from May through June. Pigeon peas, a long cycle crop, are harvested as late as August and September. A period of threshing and sales follows the harvest of each crop. Livestock activities occur in tandem with many agricultural tasks. Milk production begins to peak in January, just as households are in the midst of planting and weeding. Milk yields increase as a result of fresh pastures and renewed sources of water that come with the rains. Milk is consumed almost exclusively by the upper wealth groups, although some poor households may also benefit from this boost in nutrition. On the downside, the rains Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 5 also bring livestock diseases, such as Contagious Bovine Pleura-pneumonia (CBPP) and Contagious Caprine Pleura-pneumonia (CCPP) and Black Quarter, which occur with higher frequency during wet season. Thus, as people are busy in their fields, they also must contend with more work related to milking and caring for sick livestock. Livestock sales peak from October through February. In October, better off households are putting together the cash they need for the coming agricultural season; and later in the year, especially in January and February, households need cash both for school fees and for staple food expenditures, which peak during the lean season from January through March. The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35-year period (1980-2014) Source: TZ Meteorology Department The peak agricultural labour periods are from January through March and then June through August. The first period is associated with planting and weeding; the second is when harvesting occurs. Land preparation is not as arduous here as in many areas because ploughing is done with ox ploughs, not hand hoes. Poorer households who do not own oxen themselves obtain access to oxen and ploughs by exchanging their labour for it. This reduces the effort involved in land preparation and ploughing, but some poorer households are still paid to help with land clearing and ploughing. Weeding, however, is done entirely by hand, and this is when poorer Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 6 households are hired in the highest numbers and for the most money. The weeding period lasts 2-3 months, and during this time members of poor and very poor households work on the larger farms of middle and better off households, while, at the same time, tending to their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. They often also miss the best times for ploughing and planting because they must wait for plough oxen to finish cultivating the farms of the oxen’s owners before being deployed to their farms. The weeding period coincides with the lean season, which is when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as October or November, but by January none of the poorer households have any of their own food stocks left at home. They need to purchase all of their staple grains just when the price of staple foods is highest (from December through March). Thus, the paid work offered up by middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize is available. The rainy season is also when most human illnesses occur. Malaria is brought about by an influx of mosquitoes that come with the wet season. Upper respiratory illnesses also occur at this time. This increases the expenditure requirements for medical treatment at a time of year when other outlays (on staple food and education – in January) are already high. It is also worth keeping in mind that the most important livelihood capital that poorer households have is their own labour; when an active labourer is sick in a poor household, the income for this household rapidly drops. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. Remittances from relatives living outside the zone are most commonly sent in January and February to help cover school fees and also to help cover the costs of staple foods. Petty trade and other off-farm activities peak from June through September. This is also a time of relative plenty, when people are able to take a break before the next agricultural season. Most festivals and weddings occur at this time, making the most of new harvests to supply the grain for brewing activities and the cash to fund large gathering. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. There are two factors that determine wealth in this livelihood zone: first, the amount of land a household cultivates, and second, the number of livestock it owns. How much land a household cultivates is, in turn, governed by the amount of land it owns and/or is able to rent in; the amount of labour it has available within the household alongside its capacity to hire additional labour; and the number of plough oxen and ploughs it has. A Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 7 relatively large pool of intra-household labour is also essential for managing larger livestock herds, as is having access to sufficient grazing, and the financial resources to buy veterinary medicines and, occasionally, water. Typical better off households own around 8-13 acres of land and cultivate all of it, using hired labour as well as intra-household labour. They have 6-10 oxen and 2 ox ploughs, which they use to prepare their land for planting. They harvest a sizeable surplus of crops which get used for both home consumption and sale. Alongside their crop production, they own 10-20 cattle, 10-20 goats, a few sheep; 2-3 donkeys and 10-20 chickens. Their household sizes are usually a little bigger than poor and very poor households, with around 7-9 members. These households also own other assets, like an ox cart for transporting crops, a bicycle and a motorcycle for transporting people, and several cell phones. Typical very poor households, on the other hand, own only 1-3 acres of land and cultivate only around 1-2 acres. They do not produce enough in any year to cover all of their food and cash needs. They have no oxen or ploughs of their own and, in order to get their fields ploughed, work in the fields of better off households. These households have no cattle, and only a small number of goats, if any (0-5), as well as some chickens (2-10), sheep (0-2) and pigs (0-2). Very poor households tend to be slightly smaller in size, with 6-8 members. They face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone. The distribution of wealth in this zone is weighted slightly towards the top. Very poor (10-15%) and poor (25-40%) households together make up around 40-50% of households in the zone. Middle (35-45%) and better off (10-20%) households combined represent around 55% of the households. In addition, since middle and better off households are slightly larger, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is even larger than this. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2013 to March 2014. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12- month period. This was considered an average year, with average rains, crop yields and prices. There are three sources of food in this livelihood zone: own crops, milk In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. and meat from the household’s own livestock, and purchased food. The contribution of own crops increases with wealth; inversely, the reliance on purchased food increases as you become poorer. Maize, sorghum, beans, and sunflower are the main food crops grown; collectively, these accounted for 45-85% of the minimum calorie requirements for households in the reference year. Very poor and poor households covered 45-57% of their food needs with their own crops, which means that even in an average year, very poor households cannot even meet half of their annual food needs from crop production. Middle and better off households, on the Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 8 other hand, derived around 85% of their required calories from their fields. The majority of the own crop contribution is from maize; the importance of green maize is especially notable for poorer households. It is also important to recognize that what households consume is only a portion of the total they grow, since a large proportion of crops are sold in a year like the reference year. In fact, if households did not sell any of the crops they produced, consuming them instead, all except for the very poor would exceed their minimum calorie requirements. The reference year production of maize for typical very poor, poor, middle and better off households was around 700 kg, 1,120 kg, 4,000 kg, and 6,900 kg, respectively. For beans and pigeon peas combined it was 175 kg, 520 kg, 1,500 kg, and 2,500 kg, respectively. Sorghum added 100-200 kilos across the board. Hypothetically, if households kept all of their production for consumption, the total production of maize, sorghum and beans would have covered 75%, 125%, 320% and 535% of minimum calorie requirements for very poor, poor, middle and better off households, respectively. This is not to suggest that households should not have sold their production, but rather to highlight the large difference in the choices that better off households have, compared to very poor households: very poor households have no choice but to purchase food in order to fill a production gap, whereas better off households could have easily covered all of their food needs with their own crop production alone if they decided that was more beneficial to them. The top two wealth groups also consumed milk from their own livestock, and to a much lesser degree meat. Very poor households do not own cattle or substantial numbers of goats, and do not benefit from this source of food. A typical middle household had 1-2 cows milking throughout part of the reference year and better off households had 3-4 cows milking. Milk yields are relatively low here, but the 1 litres per cow per day during the rainy season, and .05 litres a day in the dry season accumulated over the year to total around 270 litres for middle households and 630 litres for better off households. All of this is consumed within the households, contributing 3-7% of annual calorie needs. There was also a small contribution (only around 1-2% of calorie needs) from meat for better off households. The market accounted for all of the remaining food needs for all wealth groups. For very poor and poor households, food purchases met 48-52% of calorie requirements; for middle and better off households, purchased food comprised 23-27% of minimum food needs. As explained above, poorer households produced less of their own food in the reference year and needed to buy food to make up for the gap, as demonstrated by what they purchased: most of what poorer households purchased was in the form of maize grain, the cheapest staple. While very poor households bought 43% of their calories in the form of maize grain and poor households purchased 37% of their calories as maize grain, middle households bought only 10% of their calories in the form of maize grain, and better off households purchased no maize grain at all. The ‘purchase’ component for better off households was comprised of high-value, preferred foods, such as rice, beans, sugar, meat, oil, and dried fish. Thus, these households used the market to diversify their diets and add nutrients and protein they otherwise could not produce themselves. Poorer households, on the other hand, purchased only around 10% of their minimum calories in the form of these more nutritious items. Sources of Cash Income The graphs below present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. They convey a number of points about the local household economy. As a general statement, there are three core sources of cash in this zone: crop sales, livestock sales and seasonal agricultural labour. Better off households also earn cash renting out their oxen, and all wealth groups earn an insignificant amount of money selling eggs. Crop sales provided the most important source of revenue for the upper two wealth groups. Maize, beans, pigeon peas, and sunflower are all sold, along with small amounts of sorghum. The pulses, and especially pigeon peas, are a particularly important cash source. In the reference year, typical middle and better off households sold around 2,800 kg and 5,500 kg of maize; and 1,300 kg and 2,200 kg of pulses, respectively. At 700 TZS/kg, pulses are worth almost 2 ½ times more than maize, so although much larger quantities of maize were sold, pulses brought in almost as much, and sometimes more, cash. Sunflower, the other cash crop, provided around 5-10% of the cash income of local households. Overall, crop sales accounted for 25-40% of the annual cash income of very poor and poor Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 9 households; and 65-70% of the cash income of middle and better off households. In absolute terms, better off households generated around 13 times more from their crop sales than very poor households, which is proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 5.25 times more land than very poor households, but are able to derive substantially more value per acre from their efforts. They invest more in terms of labour and inputs, and are able to better time their ploughing, labour and inputs applications, enabling them to produce more in absolute terms; but their emphasis on growing more of the high value crops also means that what they produce is more valuable in cash terms. Livestock-related income made up the remainder of cash income for the top two wealth groups in the reference year. Sales of live animals (cattle, goats, chickens, and pigs) and eggs covered around 6% of very poor household annual cash income, and 18-23% of poor, middle and better off cash income. Middle and better off households sold, on average, The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 5 855,000 – 1,600,000 1,600,000 – 2,000,000 2,000,000 – 3,200,000 3,200,000 – 6,5000,000 1-2 cattle at 525,000-700,000 TZS per head in the reference year; along with 2-4 goats (at 35,000-40,000 TZS each). Poor households sold around 2 goats, and might also sell a cow once every two years. Better off households were able to get a better price per head than middle and poor households because their animals were in better condition and they chose the best times of year and the best markets in which to sell. For example, a typical better off household sold its goats for 40,000 per head, whereas poor households only brought in 30,000 per head. Very poor households had neither cattle nor goats to sell. All households also sold chickens, averaging around 11-12 hen sales per year at 5,000-5,200 each. In addition, regular egg sales contributed a small amount of cash for all four 5 The average exchange rate from April 2013-March 2014 was 1 USD = 1,600 TZS Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 10 wealth groups. Middle and better off households also took advantage of their oxen ownership to generate cash from renting them out to poorer households for ploughing at the beginning of the agricultural season. While middle and better off households obtained all of their cash income from on-farm sources, poorer households needed to supplement their farm-based income by pursuing activities that took them away from their own fields. Seasonal agricultural labour provides a critical source of cash for both of the bottom two wealth groups. Seasonal agricultural labour provided very poor households with around 70% of their cash income in the reference year, and it provided poor households with around 45% of their cash income. Because this source of cash is so critical to poorer households, it is important to monitor this casual labour market (including changes in demand and the availability of jobs, and changes in the daily wage rate) in order to understand changes in the well-being of these households. Expenditure Patterns The graph presents expenditure patterns for the reference year April 2013 to March 2014. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in all parts of rural Tanzania, households here need to spend cash on a number of essential goods and services, including: staple and non-staple food, household items, productive inputs, social services, like schooling and health, as well as clothing and other miscellaneous The graph provides a breakdown of total annual cash expenditure according to category of expenditure items. The graph illustrates a general trend in rural Tanzania: poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. These trends, as well as number of other points, are discussed in more detail below. Even in an average year, like the reference year, all wealth groups buy staple foods, however the composition of the staple food basket is not the same for all wealth groups. In this zone, the items included in staple food expenditure were maize grain and rice. Very poor and poor households devoted almost all of their expenditure on staple foods to maize grain, the cheapest staple, spending only a small amount on rice. For example, a typical very poor household spent around 277,200 TZS on maize grain in the reference year, and 44,800 TZS on rice, which was four times more expensive. The three bottom wealth groups bought around 400-440 kg of maize grain in the reference year, but no more than 55 kg of rice. Better off households, on the other hand, bought no maize grain at all and devoted their entire staple food expenditure to rice, with a typical better off household spending around 230,400 TZS for around 145 kg of rice. Without the purchase of staple foods, the two bottom wealth groups would have been facing a food deficit, but the same cannot be said for the two upper wealth groups. In the reference year, the proportion of cash income spent on staple foods for very poor, poor, middle and better off households was around 27%, 17%, 5%, and 5%, respectively. While, in both absolute and relative terms, poorer households spent more on staple foods than any other wealth group, better off households spent the most in absolute terms on non-staple foods, expending three time more than very poor households. The non-staple food category included beans, sugar, meat, oil, fried fish, vegetables and fruit. The lower two wealth groups did not buy fruits, but their spending on all the other non-staple foods was Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 11 relatively even. Middle and better off households spent substantially more on meat, along with sugar and oil. These three food items together comprised 70-75% of their non-staple expenditure. In the reference year, the proportion of cash income spent on non-staple foods for very poor, poor, middle and better off households was around 21%, 19%, 17%, and 16%, respectively. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 7%, 9%, 10% and 18%, respectively. Thus, better off households are able to buy a much more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less. Moving up the graph, the ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor and poor households spent the most money on payment for grinding, and soap, which took around 60-70% of their inputs budget in the reference year. Middle and better off households spent the most on soap followed by grinding and utensils. On an annual basis, spending on basic household goods comprised 6-12% of total expenditure, decreasing as a proportion of annual expenditure as wealth increases (although increasing in absolute terms). The graph makes it clear that middle and better off households spend heavily on productive inputs, as represented by the dark blue bar. Included in this category are the following: livestock drugs, water for animals, seeds and tools, pesticides, labour hire, livestock purchase, and phone credit. Very poor households spent most of their money on seeds/tools (75% of their inputs budget), and phone credit (25% of their inputs budget). Poor households also spent some cash on livestock drugs and livestock purchase. Middle and better off households spent money on all items within the category; the majority of their inputs budget was spent on labour hire (45-55% of their inputs budget), livestock purchases (13-16% of their inputs budget) and seeds and tools (12-17% of their inputs budget). In absolute terms, the amount spent by better off households on inputs was more than 35 times the amount spent by very poor households, around 10 times the amount spent by poor households, and double the amount spent by middle households. Better off households had to invest large amounts of cash into hiring labour (which took over half of their inputs budget in the reference year). A typical better off household spent around 1,200,000 TZS on hiring labour in the reference year. Very poor and poor households could not survive without this income; and better off households could not generate their surplus production without this labour. Next on the graph, ‘social services’ includes schooling and health costs. Households spent 5-10% of their annual cash on these costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, middle and better off households spent around the same amount on education, and these two wealth groups spent around 2 times more than very poor households, although not much more than poor households. Very poor households usually are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent three times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Better off households spent around 15-25% more than middle and poor households on health. Spending on clothes and other miscellaneous items are the last two categories included here. Clothes accounted for 5-8% of the annual budget for all households. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation and festivals, and in the reference year households devoted 15-20% of their cash to these items. This budget can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 5 times more in this category than very poor households); and because the reference year was an average year, even the very poor wealth group had more in this budget than it would in a bad year. Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 12 Hazards There are a number of hazards that affect this zone on a regular basis. The first is intermittent or poorly distributed rains. If crops do not receive the moisture they need at the right time of year, this reduces crop yields, which has knock on effects throughout the local economy. The second is crop pests and diseases. Elegant grasshoppers, which affect both maize and sorghum; leaf hoppers and stem rot, which affect beans; and quelea quelea birds, which affect sorghum, cause problems throughout the zone almost every year. The third is livestock disease, such as Foot and Mouth Disease (FMD), as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively. New Castle Disease can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. Human diseases are also endemic, especially malaria and upper respiratory diseases. Because household labour is so critical to income generation, especially for poorer households, losing this labour at a critical time of year can translate into significant drops in income. The main periodic hazard is flooding, which can cause damage to crops in lowland areas every other year, or three years out of six. Floods also create transportation difficulties, and market access problems. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Middle and better off households try to increase their livestock sales. Poorer households are not as able to turn to this option because they can afford to sell only a few animals and still maintain viable herds. Also, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people may go to Singida town, sugar plantations in Moshi, and flower plantations in Arusha. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 13 Crops Green maize – amount produced Maize – amount produced Sorghum – amount produced Beans – amount produced Pigeon peas – amount produced Sunflower – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Sunflower – producer price Livestock production Cattle – herd size Goats – herd size Chickens – flock size Cattle – producer price Goats – producer price Chickens – producer price Other food and cash income Agricultural labour (land preparation, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Firewood/charcoal – bundles collected Agricultural wage rates (land preparation, weeding) Agricultural labour rates (harvesting) Firewood/charcoal – price per bundle Expenditure Maize grain – consumer price Oil - consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than pasture improvement, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Improved maintenance of existing road networks and increased construction of new roads Provision of electricity at village level Access to affordable and safe sources of water for humans and animals Timely and affordable provision of crop and livestock inputs or subsidies, especially seeds Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines Improved security at village level Improved markets for crops and livestock, including market infrastructure, market information, and standardisation of weights and measures Improved livestock health infrastructure, including dip tanks Construction of dams for irrigation and flood dikes and terraces to protect fields Construction of warehouses for storage Provision of land right titles Access to credit facilities and affordable loans Improvement of educational services, including construction of teachers’ houses, primary schools, and curriculum development Resolution of land conflicts with national reserves Development of phone networks Sunflower oil extraction facilities Provision of agricultural and livestock extension work Access to affordable construction materials, especially iron sheets Improvement of pasture lands"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":182,"cells":{"data":{"kind":"string","value":"# Extracted Content Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Chalinze-Ngerengere Maize, Sesame & Cattle1 Livelihood Zone (TLZ 41) February, 20162 Zone Description The Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone is a warm lowland to midland zone found in parts of Pwani and Morogoro regions. In Morogoro District, the wards included in this zone are Bwakila, Chini, Ngerengere and Kidugalo; in Kibaha District, the wards included are Gwata and Magindu; and in Bagamoyo District, the wards included are Lugoba, Msoga, Talawanda, Pera and Bwilingu.3 The main ethnic groups living here are the Kwere in Bagamoyo, Chalinze and Kibaha; and the Luguru and Kutu in Morogoro District. The Uluguru Mountains border the zone to the southwest, and major rivers, like the Ruvu, Ngerengere, Mvuha and Bwakila provide a source of water for local residents. The main towns found here include Chalinze, Ngerengere, Lugoba and Mvuha, and the zone is well connected to Dar es Salaam via a major tarmac road between Morogoro and the coastal capital as well as the central railway. This is a low- to mid-altitude area, ranging from 100 to 480 metres above sea level, with undulating plains and forested areas interspersed with agricultural land. The forests are an important source of charcoal, firewood and timber. The Selous Game Reserve also borders this zone, stretching southwards to cover an expanse larger than the country of Switzerland. The population density is approximately 23 people per km2. This zone has two rainy seasons – the masika rains, from March to June, and the short vuli rains, from November to December. The long masika rains are the most reliable and the most important for crop production. Total precipitation ranges from 800 to 1,000 mm, and the temperatures are hot and humid, typically hovering around 300 C from October to March, the summer months. Winter is cooler, with temperatures dropping to around 250 C between May and August. The soils are sandy loams, moderately fertile and suitable for cultivation. 1 The previous name of this zone was Chalinze-Tununguo Maize, Cassava & Cattle, but after the current field work, team members proposed a new name that reflects livelihood patterns in the zone. It should be noted that within the same geographical area there are households practicing pastoralism, agro-pastoralism and cropping. This profile covers the livelihood patterns of the agro-pastoralists and cropping households. 2 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in May 2014 and ended in April 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 3 The southern part of the zone shown on the map should be separated from the current zone because it has a different economic base, dependent on irrigated crops along the rivers, including paddy, water melons, tomatoes and bananas. The three wards that should be separated from this zone are Tununguo, Mvuha and Bwakila in Morogoro District. The information contained in this profile does not apply to these wards. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 2 This zone is considered self-sufficient in the sense that rarely do people need external assistance. This does not mean that households grow all of their own food; they do not, relying heavily on the market to meet food needs every year, especially on the poorer end of the wealth spectrum. The foundation of the household economy in this livelihood zone is two-fold: people grow crops for consumption and sale; but just as importantly they raise livestock. Livestock are more important in cash terms than crops, and milk is consumed by those in the top two wealth groups. Maize, sorghum and cassava - all of which are rain-fed - are the main food crops grown, along with some pulses; households sell part of these food crops for cash. Sesame is grown as a cash crop, sold to markets as far away as India. Cassava used to be more important in this zone, but in recent years a number of factors have led to its diminished role; wild pigs, for one, root up cassava, creating a year-round requirement to scare them off. Also, cattle numbers have increased, which has elevated the labour requirements around livestock and reduced the time available for households to manage cassava throughout the year. An additional factor is the growth in importance of sesame; households prefer to focus on this high-value crop over cassava. Hand hoes are the dominant form of cultivation; ox ploughs are not used, although a few better off households hire tractors. Land clearing/preparation and weeding are the most labour-intensive activities and for these tasks middle and better off households hire members from poor and very poor households to help them. It is mostly the men from poorer households who work as seasonal labourers, helping provide their families with an important source of cash. Livestock are the second important pillar of the economy. Cattle, goats, sheep and chickens are raised, relying on free grazing/browsing and some crop residues. During the wet season, livestock find water in rivers and seasonal streams. In the dry season they turn also to shallow wells and dams, and cattle are moved to rivers within the zone towards the end of the dry season. Cattle are the most important livestock from an economic viewpoint; they provide significant amounts of milk for consumption and sale and those who have them are able to sell young steers or other unproductive animals to generate cash when needed. Goats and sheep are used for meat, slaughtered especially during the festival season, and also sold when needed. Very poor households own only chickens, also sold throughout the year when cash is required. Men are responsible for taking care of the cattle, goats and sheep; women and children manage the chicken flocks. To earn additional cash, poorer households depend heavily on seasonal agricultural labour - all of it local - and on selling charcoal. Charcoal is produced by cutting down and burning trees from local forests. The charcoal then gets bundled and sold to local urban areas. This practice, carried out especially during the hunger season (February to April) and in the dry season (July to October) is having a devastating effect on the local environment. Middle and better off households earn extra cash from petty trade and running small kiosks. Services in this zone are on a par with much of rural Tanzania. Drinking water is obtained from government- run taps, which require payment of around 50-100 Tsh per household per day. Water for washing comes from rivers and wells (both shallow and deep). Sanitation facilities consist of pit latrines, most of which are constructed with brick and mud and covered with aluminium sheets. Better off households may have improved concrete floors instead of mud floors. Most villages have a health dispensary, although these may not be well-stocked. Better off households typically travel to health facilities in the ward centre, or hospitals in regional centres when necessary. Primary schools also available in villages, with secondary schools found at the ward level. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and vocational college. There is no electricity in this zone so households depend on battery-operated torches and kerosene lanterns for light; most better off households use solar lanterns. In general, all households have at least one mobile phone and better off households have multiple phones. People do not have access to credit here; VICOBA offers an opportunity to save money, but this is done only by better off households. A few NGOs operate here, including the Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services; CAMFED, which supports girls’ education; MUVI, which helps support sesame production. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 3 Markets The transportation infrastructure in this zone is relatively good. There is a tarmac road from Dar es Salaam to Morogoro and Tanga which passes along the zone; and feeder roads extend throughout the zone, from Chalinze to Ngerengere, Chalinze to Magindu, and Chalinze to Talawanda. For the most part roads are accessible throughout the year and bridges are all in good condition, although some of the more remote areas can be difficult to traverse in the peak of the rainy season. The zone is close to urban centres, which provide a steady demand for local commodities. Morogoro is the main intermediary market, providing ready access to Dar es Salaam, the main terminal market for most goods. Maize, sorghum and cassava are the main food crops sold by households in this livelihood zone. Sesame, however, is the most important cash crop. Food crops are sold from August through October. Traders come to the farm gate, traveling from village to village to buy up local commodities. They transport crops to Morogoro, where they are sold at retail; or on to Dar es Salaam. Sesame is also purchased by traders directly from local households in June and July; the terminal market for sesame is India. It transported by traders to Morogoro and then on to Dar es Salaam, from where it is shipped on freighters headed east. Livestock and milk are a more important commodity (in terms of cash earned per household) than crops. Cattle – the biggest earner – and goats and sheep are sold at local markets called mnada or gulio twice a month. The urban population in Dar es Salaam ensures a relatively constant demand for livestock; traders purchase the animals locally and then truck them on to the city. Chickens are also sold at local markets throughout the year, but consumed within the region. Households in all wealth groups also buy some maize grain during the year, especially from October through April, when local stocks are low and the new harvest has not yet come in. Maize is the cheapest local staple, and most of this is sourced from Ruvuma and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks owned by better off households. The labour market is entirely local seasonal agricultural work. It was estimated that in the reference year, 100% of seasonal labour was found within the zone on local farms, with middle and better off households hiring poorer household members to work on their land. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Chalinze- Ngerengere Maize, Cattle & Cassava Livelihood Zone the reference year covered the consumption period from May 2014 to April 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli rains in October/November and ends with the May through July harvest of the following calendar year. Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was relatively good, with good rainfall, good harvests and average food prices. In the past nine seasons, including the recent vuli season, five were below average, three were average and one was slightly above average. Production Year Season Rank Critical Events 2015-2016 Vuli 3 Fairly good vuli rains; farmers have planted 2014-2015 Masika (2015) 1.5 Inadequate rainfall, high food prices; normal livestock migration; increased livestock sales and charcoal sales Vuli 1 No vuli rains Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 4 2013-2014 Masika (2014) 3.5 Good rainfall, good harvest and average food prices Vuli 1 No vuli rains 2012-2013 Masika (2013) 3 Average rainfall; average crop production average prices Vuli 2 Below average rains 2011-2012 Masika (2012) 3 Mixed picture by village – some average and some inadequate rainfall, poor harvest with high food prices; normal livestock migration; people increased livestock sales and charcoal sales Vuli 1.5 Poor rains 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Rainy season r r r r r r r r r r r r Crops Maize gh gh gh gh h h h h lp lp p p w w gh gh h h lp lp p p w w Sorghum h h h h lp lp lp lp p p w w Sesame h h h h lp lp lp lp p p w w Cassava h h h h h h h lp p p w w w w Livestock Cattle milk peak m m m m m m m Cattle sales peak salesalesalesalesalesale Goat sales peak salesale salesalesalesalesalesale salesalesalesale Livestock diseases 5 5 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 4 4 Charcoal sales 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp sp sp Human diseases 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Jan Feb Mar Apr May Jun Nov Jul Aug Sep Oct Dec Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Kibaha for a 50-year period from 1964 to 2013. Source: TZ Meteorology Department This livelihood zone benefits from two rainy seasons. The first, called the vuli, is short, starting in October and lasting until the end of December; the second, called the masika, occurs from March through May. Masika rains are when the main planting takes place here because vuli rains do not provide enough precipitation and they are not as reliable. Nevertheless, as shown on the calendar above, most households attempt to plant a vuli crop of maize, taking what comes from it if it succeeds. Most maize, however, is planted in March, when the masika rains are fully established. Sorghum, sesame and cassava are also planted at this time, following a month of land preparation in February. January through April is when seasonal agricultural labour is most intense. Within that period, April is an especially challenging month, with weeding the main focus of agricultural activities. Poorer households need to buy food at this time of year as they tend to have none of their own food stocks left from February through April. This is the worst month of the lean period, when prices are high and food stocks are low; human and livestock diseases (especially malaria for people and East Coast Fever and Blackquarter – both highest in the rainy season) are starting to peak at this time too, imposing additional expenditure requirements on already- stretched households. Poorer households, in need of extra cash to buy food, medicines and possibly livestock drugs, find work on the farms of middle and better off households, paid to weed their larger fields. They also burn and sell charcoal or collect and sell firewood at this time to shore up their cash income. Middle and better off households, who own cattle, see their milk production peak from April through June, as the condition of cows improves with replenished pastures from the recent rains, and with plentiful supplies of water. Milk helps boost the nutritional content of the diet for these households, and especially for children, while at the same time improving the income flows, since households sell at least half of their milk. Cattle and goat sales peak from August through October. Body condition is highest at this time, which brings in the best prices. There is also higher demand locally since people have extra money from crop sales, and the dry season facilitates the movement of trucks which are deployed to transport livestock to Dar es Salaam. Goats are also sold in higher quantities in the lean season – but mainly by poorer households. May marks the beginning of the consumption year as households begin to eat maize from the masika harvest. At first, maize is eaten green – especially by poorer households, who cannot afford to wait the additional month or two for the dried harvest. In July and August the main maize harvest is taken in from the fields and August and September are when sales of maize are highest. Cassava and sesame can be harvested starting in June. Sales of sesame – the main cash crop - are highest in July. People sell cassava for months afterwards, with peak sales occurring from October through December. The festival season occurs from September through December, when harvests are in, cash flow is a bit higher and people have a chance to rest before delving into the next production year. Meat consumption is highest during these months as goats are slaughtered; and expenditures on weddings or other celebrations is highest at this time as well. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. Both crop and livestock production are central in this zone, and so it follows that the area of land cultivated by a household along with the number of livestock it owns are the two key determinants of wealth. Households with smaller areas of land and fewer livestock are generally poorer, whereas those with larger plots also have more livestock and are considered better off. In addition, ownership of productive assets, like motorcycles (which enable households to make money from trading activities), contributes to the basis on which differences of wealth are determined. Very poor households plant on 1.5-2.5 acres and have no livestock other than chickens. Poor households cultivate 2.5-3.5 acres and own 0-10 goats and 0-5 sheep along with a few chickens. A jump occurs between poor and middle households, with middle households typically cultivating 4-5 acres and owning 30-50 cattle, 20-40 goats, possibly some sheep and 10-20 chickens. The difference between these two wealth groups is seen more in the livestock than in the land. Middle households cultivate just an acre or two more than poor households, but they own twenty to thirty times more cattle. Better off households cultivate 4-8 acres (not much different from middle households) and own 40-80 cattle, 30-70 goats and 20-50 sheep. Cattle are critical because they bring in significant amounts of cash income from live animal and milk sales; and they provide extra nutrition and calories in the form of milk. The other critical divide between poor and middle households is that poor and very poor households need to work for others to earn enough cash to live on and middle households do not. Thus, middle and better off households hire labour to work for them; very poor and poor households are the labour that gets hired. Middle and better off households are engaged in trade activities, providing them with another source of cash. This trade is enabled by their ownership of motorcycles. Almost all better off households own at least one motorcycle and some middle households do as well. Bicycles are another common means of transport, and all wealth groups except for the very poor own at least one bicycle. Almost all households also own at least one cell phone. Over the last decade, cell phone ownership has become ubiquitous throughout rural Africa. There are more households falling into the very poor and poor categories than into the middle and better off categories. Very poor (30%) and poor (33%) households together comprise just under two-thirds of the households in the zone. Middle (25%) and better off (13%) households combined represent just over a third of the population. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period May 2014 to April 2015. May represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Households in this livelihood zone depended on three main sources of food in the reference In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. year: their own crop production; their own milk and meat production; and the market. A range of crops are grown here, including maize, sorghum, cassava, pulses (like pigeon peas and cowpeas) and sesame. Only the top two wealth groups are able to produce enough from their own fields to come close to meeting all of their own food needs, even in a good year like the reference year. Better off households harvested around 1,200 kg of maize, 250 kg of sorghum and 320 kg of cassava in the reference year along with small amounts of pulses for consumption. Very poor households, on the other end of the wealth spectrum, produced only around 390 kg of maize, 390 kg of sorghum, and 100 kg of cassava along with small amounts of pulses. If these poorer households had consumed all the maize, sorghum and cassava they produced, they could have covered around 65-70% of their minimum calorie needs, leaving a fairly sizeable gap. Better off households could have covered closer to 125% of their minimum calorie needs. However, all households here sell some of their crops for cash, which means that even better off households are left with a staple grain gap that needs to be filled with purchased food. When combined, the contribution of own crops (after sales and seed) accounted for around 40-68% of households’ annual food needs in the reference year, increasing with wealth. The upper two wealth groups fill in a good portion of the remaining gap with milk and meat. Middle households typically had around 12 cows milking during much of the reference year, and better off households had, on average, 15 cows milking. Very poor and poor households did not own any cattle and were not able to benefit from this source of food. Yields are relatively low, at 1.5 litres a day in the first rainy season (lasting around four months) and 0.75 litres a day in the second rainy season (lasting around two months). When added together, the milk from both seasons amounted to around 2,700 litres for middle households, and 3,375 litres for better off households during the reference year. Around 50-70% of this was sold, providing some cash income (shown in the section below) for these two wealth groups. The remainder was consumed, providing 8-18% of the minimum calories for these households. Meat from cattle and goats consumed throughout the year contributed an additional 4% of minimum food needs for the upper two wealth groups. Goats are the main livestock slaughtered, usually in April, June, July and December during festivals; but cattle that die from natural causes are also eaten. Given the remaining gap, all households needed to purchase staple grain to cover a production gap – even better off households. In the reference year, an average year, very poor households bought almost 600 kg of maize grain, the cheapest staple, which is equivalent to 45-50% of their minimum calories; poor, middle and better off households bought around 40%, 12%, 6% of their calories in the form of maize grain, respectively. All households also bought some rice, with middle and better off households buying more of this expensive grain Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 8 than poorer households. Beans, sugar, meat, oil, Irish potatoes, and dried fish also contributed to the purchased food basket. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 30-60% of their minimum calorie requirements in the reference year. Sources of Cash Income The graph to the right highlights six main sources of cash income in this livelihood zone: own crop sales, milk/egg sales, livestock sales, agricultural labour, petty trade and firewood/charcoal sales. The majority of cash income for middle and better off households is generated on the farm (from crop and livestock-related sales.) The bottom two groups rely heavily on agricultural labour and firewood and charcoal sales to supplement their crop and livestock-related cash income. Their on-farm production meets less than half of their annual cash needs. The importance of livestock sales and milk sales is striking The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,140,000 – 1,640,000 1,640,000 – 2,10,000 3,000,000 – 5,000,000 5,000,000 – 6,000,000 for the upper two wealth groups. Combined, these two sources of income account for around 55-65% of annual cash for middle and better off households; for very poor and poor households, on the other hand, they only make up 3-12% of annual cash income. The difference is due almost entirely to cattle, owned by the upper two groups but not by the lower two. Cattle are worth 300,000 – 350,000 Tsh per head. Typical middle and better off households each sold 4-5 head of cattle in the reference year, bringing in 1,200,000-1,750,000 Tsh. This stream of income alone is more than the total annual income of some poor households. In addition, these households also sold goats, sheep and chickens. Their total income from livestock sales ranged from 1,565,000 Tsh to 2,207,000 Tsh. Poor households sold only goats, sheep and chickens in the reference year, averaging around 200,000 Tsh from livestock sales; very poor households had only chickens to sell, which brought them around 40,000 Tsh. Cattle also afforded middle and better off households with cash income from milk sales, adding another 825,000 – 950,000 Tsh. Comparing livestock-based cash income (including both the sale of live animals and milk) across wealth groups we see that better off households had a total that 75 times higher than very poor households’ and 15 times higher than poor households’. Without cattle this difference would have been only 11 times higher (better off vs very poor) and 2 times higher (better off vs poor) respectively. Crop sales generated 15-30% of cash income for households in this zone in the reference year. It is worth remembering that the reference year was a good year, so the contribution from crop sales is as high as it would ever be. In a bad year the share will decrease. This suggests that crops are more important as a source of food than cash here. Maize, sorghum, cassava and sesame were the main crops sold; sesame generated 34-56% of crop-based cash income, with middle households making the most of this crop. Sorghum sales were most 4 The average exchange rate from May 2014-April 2015 was 1 USD = 1,810 TZS Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 9 important for very poor households who generated around half of their crop-based cash income from this crop alone. Better off households generated around 2 ½ times as much cash from crop sales as very poor households. Although crops contribute to the local economy, they are not as important as livestock. Poorer households depend on two main sources of cash other than crop and livestock sales: agricultural labour and charcoal/firewood sales. Middle and better off households hire men and women from poorer households to help with land preparation and weeding activities. January and February are especially busy months for agricultural labour, when land preparation occurs, as well as April, when weeding takes place. The wage rate for land preparation is higher than for weeding, but weeding generates more revenue for very poor households, who may send additional people to work during this time and/or spend more days working. Agricultural labour accounts for around a third of annual cash income for the bottom two wealth groups. Selling charcoal and/or firewood brought in even more money for very poor households in the reference year, making up around 45% of their cash income. Middle households may also be engaged in charcoal sales. Men are responsible for charcoal production and sales; women gather and sell firewood. Local towns are the main source of demand. Wood for both is found in the forests within the zone and environmental degradation is clearly a serious problem given the high reliance on this income source. Petty trade is very important for better off households, and also for middle households. This trade is done mainly by middle and better off households who have motorcycles and extra money and can buy up local produce, selling in more profitable markets to make a small margin. Better off or middle households may also have small kiosks where they sell salt, soap, kerosene or other household goods. Better off households relied on petty trade to make up around a third of their cash income in the reference year. Those at the upper end of the wealth spectrum generated, on average, three and a half times more than those at the bottom. Owning cattle is the critical differentiator in this zone, affording the two upper wealth groups with cash income from the sales of cattle as well as milk. Having the means to trade provides a further advantage, with petty trade bringing in – for better off households – almost as much on its own as very poor households made from all of their sources combined. Expenditure Patterns The graph presents expenditure patterns for the reference year May 2014 to April 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. There are a range of essential goods and services that households here need to spend money on, including: staple and non-staple food, household items, productive inputs, social services, clothing and other The graph provides a breakdown of total annual cash expenditure according to category of expenditure miscellaneous items. There are four main points to make about the information displayed in the graph. First, both absolute and relative expenditure on staple foods decreases as we move up the wealth spectrum, but the opposite is true for non-staple foods. Very poor households spent, on average, around 390,000 Tsh on Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 10 staple foods5 in the reference year; better off households spent around 220,000 Tsh. But if we look just at spending on maize grain it becomes clear that poorer households spent far more on ensuring they had sufficient calories and better off households spent more on diversifying their diet: very poor households spent around 360,000 Tsh (of the 390,000 Tsh) on just maize grain, whereas better off households spent 62,400 Tsh (of the 220,000 Tsh) on maize grain. The rest of the staple expenditure was on beans, oil and dried fish. All households also spent money on other foods, such as rice, sugar, meat, and potatoes. These are all included in the non- staple food basket. Better off households spent almost twice as much on non-staple foods as very poor households, again using the market to help diversify their diets. Second, expenditure on basic household goods (‘hh items’), including all of the items bought by households over the year – often in small incremental amounts - to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils, ate up a large amount of the cash earned by the two poorer groups. Within this category, the highest expenditure was on grinding; very poor households devoted 45-50% of their ‘hh items’ budget to grinding in the reference year; no wealth group devoted less than 30% of their ‘hh items’ budget on grinding. Soap took up the next largest chunk. On an annual basis, spending on basic household goods comprised 7-16% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Finding ways to reduce the relatively high costs of grinding for poorer households could help them free us some money for other productive uses. Third, productive inputs accounts for a much larger portion of the budget for middle and better off households than for the poorer two wealth groups. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, seeds and tools, labour, livestock purchase and phone credit. Very poor households spent all of their inputs budget on phone credit. Poor households, in addition to phone credit, spent a small amount on seeds and tools. Middle and better off households spent the majority of their inputs budget (58-68%) on two items: labour and livestock purchase. Livestock drugs took up almost all of the rest of their budget. On the whole, middle and better off households devoted 30 - 40% of their annual cash income to productive inputs whereas very poor and poor households devoted only 5-6% of their annual budget to productive inputs in the reference year. In absolute terms, better off households spent almost 20 times more than very poor households on productive inputs. Fourth, this is one of the livelihood zones where households need to spend a noticeable proportion of their budget on water. An average household buys 80-100 buckets of water from village taps every month throughout the year, spending 100-250 Tsh per bucket. In annual terms this adds up to around 5-6% of total expenditure. Water can also be obtained from local rivers and streams, but this is not safe for drinking and is used only for washing. ‘Social services’ includes the money spent on education and medical services. Education covers school fees, uniforms, stationery and transportation. Absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Very poor households spent around 76,000 Tsh on schooling compared to 240,000 Tsh spent by better off households. As you move up, households are spending more on stationery, books, uniforms, school fees and transportation. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to vocational school. Better off and middle households also spend more on medicine and health care, with each wealth group spending on average 20-50% more than the one below it. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. There is also some savings included here for the better off wealth group. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget. 5 The team included maize grain, beans, oil and dried fish in the staple food basket. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 11 Hazards There are a number of hazards that affect this zone on a regular basis. The first is inadequate and erratic rainfall and occasional drought. All households rely heavily on crop production from one season to at least partially meet their food and cash needs. If rains in this season are poor, if they are interrupted at the growing stage, or if they end early, households are at risk of losing their crops, all of which are rain-fed. Thus the food and cash income of households here is substantially reduced when rains are poor. Pastures and water supplies are also affected when droughts occur, reducing milk yields and leading to a deterioration in livestock body condition and value. Second, conflict between farmers and pastoralists is high in this zone. Competition over scarce pasture and cropping lands as well as prime water sources has resulted in contested access to resources crucial for both farmers and livestock keepers. Third, livestock diseases, such as Food and Mouth disease (FMD) and East Coast fever – both of which affect cattle - and New Castle Disease, which can wipe out an entire flock of chickens, are serious problems. Fourth, crop pests and diseases are a constant threat. Elegant grasshoppers and army worms are especially problematic as well as quelea quelea, which threaten the sorghum harvest. Wild animals also cause damage to crops. Finally, poor markets for cash crops are a consistent constraint on the income of households here. With better market infrastructure and ensured access to markets that offer good producer prices, households here would have higher and more assured incomes. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to increase the sale of charcoal, intensifying the burning and selling of wood products. The expandability of this option is limited in bad years because as more people turn to this option, supplies of charcoal on the market increase, thereby reducing the price of each bag. There are also serious environmental downsides to this strategy. More must be done to provide poor households with an alternative to charcoal as an income source, both in normal and bad years. Poorer households also try to increase their production and sale of handicrafts. Again, this is an option with limited expansion since the market for handicrafts is limited, and the more households pursuing this option, the lower the returns on each sale. Poorer households also sell more chickens. However, as the number of chickens owned by very poor and poor households does not exceed 10-15, and each chicken is worth only around 8,000 Tsh in a good year, this option will only go so far in terms of raising cash income. Middle and better off households try to increase their livestock sales. The value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. However, middle and better off households have relatively large herds of cattle here, so this option could provide people with a substantial amount of additional cash. Middle and better off households try to increase their reliance on petty trade and small businesses, buying and selling goods to make as much cash as they can with which to buy food. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 12 Middle and better off households also use some of their savings in bad years, buying food and other necessities with money saved from the previous good year. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika - amount produced Sorghum – masika – amount produced Cassava – amount produced Sesame – amount produced Maize – masika – producer price Sorghum - masika – producer price Cassava – producer price Sesame – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Sheep – herd size Chickens - numbers Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Chickens – producer price Other food and cash income Agricultural labour (land clearing and preparation, weeding) – number of jobs Petty trade – amount of trade Firewood/Charcoal – bundles/bags sold Agricultural wage rates (land clearing and preparation, weeding) Petty trade – margins on trade Firewood/Charcoal – prices Expenditure Maize grain – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve health services and increase the availability of medicines 2) Provide agricultural extension services 3) Provide affordable loans for agriculture 4) Improve road infrastructure and invest in maintenance of existing roads 5) Resolve conflict between farmers and pastoralists 6) Develop market infrastructure 7) Improve access to and availability of safe and reliable water supplies for humans 8) Provide subsidized and improved agricultural inputs, for example, access to a village tractor for rental 9) Provide access to mechanized agriculture 10) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":183,"cells":{"data":{"kind":"string","value":"# Extracted Content Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone (TLZ 42) February, 20161 Zone Description The Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone is a unique zone found in Morogoro Region, and geographically separated into two parts – one at the north eastern boundary of the Kilosa-Mvomero Maize and Paddy Lowlands Livelihood Zone (TLZ 44) and one on the southern boundary of the same zone. Most of the zone is found in three districts: Kilombero (Sanje and Mkula wards); Kilosa (Kidodi and Ruhembe wards); and Mvomero (Sungaji, Kanga, Mtibwa and Djongoya wards). The main ethnic groups living here are the Pogoro, Wavidunda, Nguu and Zigua. The Nguu, Udzungwa, and Kanga mountains are found here, and major rivers, like the Ruaha and Mjonga flow through the zone, providing a source of water for local residents. This warm zone is situated at around 270-500 meters above sea level, and has a mix of flat plains, river valleys and mountainous areas, covered with forests and agricultural land. The Ruaha River provides some with access to fishing, but this is not a typical source of food or cash for most households. The Mikumi and Udzungwa national parks are found nearby. This zone is unique due to the existence of sugarcane estates and factories, which are surrounded by outgrower farmers who supply sugarcane via producer associations to the factories. The profile describes the livelihoods of these outgrowers, who work, essentially, as contract farmers for the sugarcane factories. Many households own or rent farm plots far from their homes, where they grow paddy and maize. Plots near the homestead have been converted into sugarcane fields, which makes land for farming crops scarce. With the expansion of sugarcane, food crops have been exposed to fires and pests that are associated with sugarcane fields, which makes it difficult to grow food crops near the sugarcane fields. This means many households are juggling various demands from different agricultural plots as well as the care of home and children.2 Poorer households concentrate more on food crop production, unable to manage the heavy demands of both sugar cane and food crops. Better off households use the proceeds from sugarcane to help support their food crop production, essentially reducing the risks of failure from either their food or cash 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in May 2014 and ended in April 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2http://www.plaas.org.za/blog/tanzanias-commuter-farmers-facing-livelihoods-challenges#sthash.X4ckdtvf.dpuf Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 2 sources. Cash incomes are, relatively speaking, higher than in neighbouring zones, and there is a noticeably higher investment in schooling as a result. There are two rainy seasons – the masika rains, from March to June, and the short vuli rains, from November to December. Maize is grown in two seasons, but the other crops are long cycle varieties, depending on the rains from both seasons to reach maturity. Total precipitation ranges from 600 to 1,200 mm, and the temperatures can be as low as 18 oC in the winter and as high as 30 oC in the summer. The soils are fertile clay loams with a high potential for good crop production. Maize and paddy are the main food crops, but portions of both are also sold for cash by all households. Maize is rain fed; paddy is both rain fed and irrigated. Pigeon peas and sesame are also grown, primarily as cash crops, but partially consumed as well. Hand hoes are the dominant form of cultivation for poorer households, whereas better off households use tractors. Sugar cane and paddy are both very labour- intensive crops, especially at planting, weeding and harvesting times. During these periods, middle and better off households hire members from poor and very poor households to help them. Other than chickens, which are widely kept, livestock are not a source of either food or cash income in this livelihood zone, unlike many zones in rural Tanzania. There is not enough land to raise livestock, and it is not a part of the traditional livelihood patterns of the local inhabitants. To earn additional cash, poorer households depend heavily on seasonal agricultural labour on both the farms of local outgrowers as well as at the larger sugarcane estates. They also engage in a range of other income generating activities, such as brick making, brewing and petty trade. Middle and better off households earn extra cash from petty trade and from boda boda (motorcycle taxi hire). There are serious constraints to production in this zone, including severe limitations on the amount of land available for food crop production. As more and more land is taken over for sugarcane production, people are forced to rent plots farther and farther away from their villages in order to grow food. Crop diseases and pests, such rice blast fungus, army worms and rodents, are a constant challenge. Local outgrowers claim that their income is limited by unfair practices on the part of the sugarcane companies, which has led to a climate of distrust and frustration. In addition, there is ongoing conflict between local cropping residents and pastoralists who migrate into the zone to access pasture and water resources. Services in this zone are good compared to much of rural Tanzania, especially for better off households. Drinking water is obtained from rivers and wells that are all fairly close to villages. Tap water, which is found in the village centres, requires a monthly contribution to maintain the pumps. Better off households generally have tap water in their houses. Poorer households use pit latrines and maintain separate pits for garbage disposal; better off households have improved flush toilets in their houses. Most villages have a health dispensary, although these may not be well-stocked. Better off households typically travel to health facilities in the ward centre, or hospitals in regional centres when necessary. Primary schools also available in villages, with secondary schools found at the ward level. Almost all households send their children through secondary school, even poorer households. Middle and better off households send their children through to the university level. There is no electricity in this zone so households depend on battery-operated torches, kerosene lanterns and solar lamps for light. In general, all households have at least one mobile phone and better off households have multiple phones. VICOBA provides access to loans and to savings schemes. The Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services, operates here. Markets The transportation infrastructure in this zone is relatively good. The zone is split into two parts, as discussed above, with one section found in Mvomero, in the north of Morogoro, and the other in Kilombero, in the central western part of Morogoro. The Kilombero part of the zone is very close to a major junction in Tanzania’s railway line, with one arm extending from Mbeya to Dar es Salaam and the other heading north Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 3 to Dodoma. This part of the zone has ready access to the tarmac road that goes from Morogoro to Iringa. The other part of the zone is close to Tanga and Morogoro town. Feeder roads extend throughout the zone, from Dumila to Kilindi, Dumila to Kilosa, and Mikumi to Kilombero. Almost all roads are accessible throughout the year (even in the wet season) and most bridges are in good condition, with the exception of the Mjonga bridge to reach Digoma village. The zone is close to urban centres, which provide a steady demand for local commodities, and good roads make the movement of goods and services relatively easy. Morogoro is the main intermediary market, providing ready access to Dar es Salaam, the main terminal market for most goods. Paddy, maize, pigeon peas and sesame are the main food crops sold by households in this livelihood zone. Sugar cane is the most important cash crop, but this is grown and sold only by middle and better off households. Poorer households rely on maize, pigeon peas, sesame and paddy to generate their crop-based cash income. Maize is sold after both harvests: in February (from the vuli harvest) and June to September (from the masika harvest). Maize is sold locally and generally does not get transported out of the zone. Sesame is sold from June through September and pigeon peas are sold in September. Paddy is sold at its lowest price from July through September and at higher prices from November through April. Only better off households are able to sell at higher prices because they produce surplus paddy and store it until prices peak. Traders come to the farm gate, traveling from village to village to buy up local commodities. They transport crops to Morogoro, where they are sold at retail; or on to Dar es Salaam. The terminal markets for sesame are India and China. It transported by traders to Morogoro and then on to Dar es Salaam, from where it is shipped eastwards on freighters. Pigeon peas follow the same route, but are usually exported only to India, not China. Sugarcane is sold to local sugarcane plantations where it is processed into sugar and sold for national consumption as well as export. There are numerous issues with the marketing of sugarcane that have led to a sense that local farmers are being treated unfairly. These include a lack of transparency with respect to the measurement of sucrose levels (which determines payment to the farmers), lack of representation when it comes to disputes, lack of awareness about rights, concerns about the deductions taken from the farmers’ payments, and suspicion of corruption and exploitation on the part of the sugarcane executives. Households in all wealth groups also buy some maize grain during the year, especially in the lean season, from January through April, when local stocks are low. Maize is the cheapest local staple, and most of this is sourced locally from traders who buy up maize at harvest time and store it for sale later in the year. Beans are also purchased throughout the year; these originate from Mbeya and come into the zone via the main Morogoro market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks owned by better off households. The labour market is almost entirely local, with seasonal agricultural work taking place on the sugar plantations as well as on the farms of middle and better off households. It was estimated that in the reference year, 95% of seasonal labour was found within the zone. A very small percentage of work (around 5% of the total) is also found in local towns. There is some in-migration to this livelihood zones; people from other areas come to work on the sugar plantations. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Kilombera- Mvomero Paddy, Maize & Sugarcane Livelihood Zone the reference year covered the consumption period from May 2014 to April 2015. During community leader interviews, informants were asked to rank the last four years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli rains in October/November and ends with the May through September harvest of the following calendar year.) Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was relatively good, with heavy rainfall, average yields and good crop prices. The past four Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 4 years have all been relatively good in terms of rainfall, with the exception of last year; although the incidence of pests and crop diseases is a limiting factor every year. Production Year Rank Critical Events 2014-2015 2.8 Poor rainfall distribution; average crop yields; average staple food prices; occurrence of Rice Yellow Mottle Virus (RYMV) and quelea quelea birds 2013-2014 3 Heavy rainfall; average crop yields; good crop prices; rodents and grasshoppers 2012-2013 3 Good rainfall distribution; good yields; rodents and army worms 2011-2012 3 Average rainfall; average yields; average staple food prices; rodents 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Kilosa for a 50-year period from 1968 to 2008. Source: TZ Meteorology Department There are two rainy seasons in this livelihood zone. The first, called the vuli, is short, starting in October and ending in December; the second, called the masika, takes place from March through May. Because many of the crops grown here are medium- to long-cycle varieties, both rains play a role in the agricultural production season. However, it is after the masika season that the main harvests occur, with the exception of vuli maize, which is harvested in February. There are two maize harvests: the first is planted with the vuli rains in October and harvested in February; the second is planted in March, at the onset of the masika rains, and harvested in July. Pigeon peas are inter-cropped with maize in October, when the vuli rains are fully established. They are harvested seven to nine months later, with the green crop coming in July and the main harvest occurring in September. Sugar cane, another long cycle crop, is planted as a single stand in October and harvested seven to eight months later, from June to August. The paddy production cycle depends on both irrigation and the rains. The vuli rains help soften the ground to prepare for planting. Land preparation for paddy takes place in December, followed by planting in January and February. The green harvest is in May, and the main harvest takes place from June through August. Sesame is also planted in single stands, planted and harvested at the same time as paddy. Given the long production season, and the intensity of labour required for the paddy and sugar cane crops, people here are busy with agricultural activities almost year-round. Land preparation activities begin as early as September and harvests end the following August. The peak labour requirements, however, occur from January through July. In some months, like January, paddy and sesame are being planted at the same time that fields for masika maize are being prepared, vuli maize is being harvested, and sugarcane needs to be weeded. This is a month when poorer household food stocks are low and staple food prices are high. It is the start of the lean season, which lasts through April; a time of relative hardship, when people are working hard and food is harder to come by. Two months of the lean season coincide with a higher incidence of human disease (March and April), which means that household expenditure requirements (to buy medicines) – already stretched from the need to buy more food at higher prices – are even higher. Poorer households, in need of extra cash at this time of year, work on sugarcane plantations and in the fields of middle and better off households, who need extra labour, especially to manage their paddy and sugarcane crops. Most of the cash that poorer households earn throughout the year comes from this seven-month period. The seasonal calendar also shows that chicken sales are highest at this time of year, helping supplement the cash from labour and crop sales. May marks the beginning of the consumption year as households begin to eat paddy green, followed in June by the consumption of green maize and the main paddy harvest. Both access to food and cash flow starts to increase in June as a number of crops are harvested and sold, including sugar cane, paddy, and sesame. The harvest of pigeon peas in September finishes off the production cycle and brings in additional cash for all households. The festival season follows the harvest period, because this is a time when all households have a bit more cash and there is a brief respite before the next production season begins. Petty trade activities are at a peak in these months (July through September) as wealthier households buy up local produce to sell in central markets, and re-stock their kiosks full of basic commodities to be sold locally. Off-farm labour, like brick making and selling, also peaks at this time as poorer households take advantage of the dry season and a break in agricultural labour demand. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. Differences in wealth in this livelihood zone are determined by the amount of land a household cultivates. This, in turn, is related to how much land the household owns along with how much it can rent; and how much labour the household can draw on, both within the household and through hiring. Sugar cane and paddy – the most important cash crops - are both highly labour intensive crops, requiring extra labour investments (relative to the requirements for maize and other crops) at planting, weeding and harvesting times. In addition, ownership of productive assets, like motorcycles (which enable households to make money from boda boda - motorcycle taxi hire), contributes to the basis on which differences of wealth are determined. Livestock ownership is not an important differentiating factor. The graph and table above summarizes the percentage of households falling into each wealth group along with its associated productive assets. One thing to note about the information in the table above is the difference between ‘land area owned’ and ‘land area cultivated’. The existence of large sugar cane plantations limits the amount of land that people can use for planting food and cash crops. Many people start with inherited land or land allocated by the village government to plant sugarcane, but they add to that area by purchasing or renting more land for paddy and maize production. For the most part, the three lower wealth groups own less land than they cultivate, which means they need to rent extra land from either better off households within the zone or from non-resident land owners. The market for rented land has grown enormously in recent years as the squeeze on available arable land increases. Very poor households plant on 1-3 acres, poor households cultivate 3-4 acres, middle households cultivate 5- 8 acres, and better off households cultivate 8-15 acres. Thus, the typical better off households is cultivating more than five times the amount cultivated by the typical very poor household. The other critical divide between poor and middle households is that poor and very poor households need to work for others to earn enough cash to live on and middle households do not work for others. In other words, middle and better off households hire labour to work for them; very poor and poor households provide the labour that gets hired by these upper two wealth groups. Middle and better off households are engaged in trade activities, providing them with another source of cash. This trade is enabled by their ownership of motorcycles. Almost all better off households own at least one motorcycle and some middle households do as well. Bicycles are another common means of transport, and all Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 7 wealth groups except for the very poor own at least one bicycle. Almost all households also own at least one cell phone. Over the last decade, cell phone ownership has become ubiquitous throughout rural Africa. There are more households falling into the very poor and poor categories than into the middle and better off categories. Very poor (29%) and poor (32%) households together comprise just under two-thirds of the households in the zone. Middle (27%) and better off (12%) households combined represent just over a third of the population. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period May 2014 to April 2015. May represents the start of the consumption year because it is when people begin to consume green crops - especially paddy - and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. There are only two sources of food in this livelihood zone: own In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. crop production and the market. The relative importance of own crops increases as you move up the wealth spectrum, and the opposite is true for market purchases; poorer households need to buy more food than better off households. However, all households bought a substantial portion of their food in the reference year, which was an average (not a bad) year. This is generally not because households do not produce enough food to cover their own consumption needs: in fact, if households did not sell any of their crops, and consumed them instead, they would meet 140-520% of their minimum calorie requirements.3 Even very poor households could have met their minimum food needs with their own crop production alone, which highlights the productive nature of this zone. However, because there are no other substantive sources of cash income – no livestock, for example – crops are the means for generating both food and cash requirements. Therefore, households needed to sell over half of their crops to fund all the other cash-related expenses in their lives, leaving them with a gap that got filled by the market. In the reference year maize, grown and harvested in two seasons, was the dominant food crop. Although paddy generated more output on a seasonal basis in the one season it was grown, it is used more heavily as a cash crop. The average production reported for maize by households in the reference year was 800-1200 kg per acre, with most poorer households growing maize without the use of industrial fertilizers or pesticides. Combining both seasons, very poor and poor households harvested around 1,130 and 1,930 kg of maize, respectively, in the reference year. Over half of this was sold, leaving these households with enough to cover 29-36% of their minimum calorie requirements. The green maize (fresh maize) harvest covered an additional 2-4% of calorie needs. Middle and better off households produced around 2,350 kg and 4,680 kg of maize respectively, with a balance of approximately 70-80% grown in the masika season. After selling the majority of this, these households retained enough maize to cover 40-55% of their minimum calorie needs during the reference year. 3 Very poor, poor, middle and better off households would have been able to cover 140%, 210%, 315%, and 520% of minimum calorie needs respectively in the reference year with their own crop production alone. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 8 Paddy is the second-most important food crop, although it functions more as a source of cash than food. The average production per acre for paddy during the reference year was 1000-1200 kg per acre. Thus, household production ranged from around 950 kg for very poor households up to 3,700 kg for better off households; 75- 85% of this was sold, leaving households with enough paddy to cover 10-20% of minimum calorie needs. A very small contribution was also made from the sesame grown by the top three wealth groups, although again, most of this was sold. As a whole, own crops accounted for around 43-77% of households’ minimum food needs in this zone during the reference year. To fill the gap, all households purchased food. Poorer households bought mainly maize grain – the cheapest staple. They purchased maize for four to six months of the year, meeting 20-25% of their food needs this way; whereas middle and better off households bought maize for only one to three months of the year, covering 7- 14% of their calorie requirements. All households also purchased rice, although at 1.6 times the price of maize, poorer households limited their expenditure on this grain. Nevertheless, purchased rice accounted for around 10% of household food needs for very poor households and around half of that for better off households. Other purchased foods, like beans, sugar, meat, oil, dried fish, sweet potatoes and vegetables, contributed an additional 23-33% of minimum calories for all wealth groups. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 45-57% of their minimum calorie requirements in the reference year. Sources of Cash Income The graph to the right provides a detailed breakdown of the income sources in this livelihood zone. The main source of cash for the two upper wealth groups is crop sales. The main source of cash for the bottom two wealth groups is agricultural labour. Other sources of cash, depending on the wealth group, include brick sales, petty trade and boda boda (taxi hire). The income table below the graph summarizes absolute cash income ranges in Tanzanian Shillings for each wealth group in the reference year. The average income of better off households is at least three times higher than the average income of very poor households. The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 2,220,000 – 2,700,000 2,700,000 – 3,800,000 3,800,000 – 6,000,000 6,000,000 – 9,900,000 It is clear from the income graph that crops are the main driver of the local economy in this livelihood zone. Of particular importance are paddy and maize sales (for all wealth groups) and sugar cane sales (for the upper two wealth groups). As noted in the section above, households sell the majority of their crop production, retaining less than half for consumption. It is here – in this graph – that we see the economic value of that decision. For 4 The average exchange rate from May 2014-April 2015 was 1 USD = 1,810 TZS Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 9 the upper two wealth groups, these sales are especially important, generating 60-75% of their cash income in the reference year. The bottom two wealth groups, with less to sell, derive 25-45% of their annual cash income from crop sales. Maize and paddy sales combined bring in over 90% of the crop-based cash income for very poor households; the other three wealth groups depend also on sesame sales (not grown by the very poor); and the top two wealth groups grow sugar cane. Maize is sold in both seasons, but the maize from the masika season brings in substantially more in terms of cash income, contributing – for example – 23% of crop-based cash income in the reference year for better off households, compared to the 4% brought in by vuli maize. In addition to maize from both seasons, paddy, sesame and sugar cane, pigeon peas are also sold, providing 4-9% of crop-based cash income in the reference year. An even more important source of cash for very poor households than crop sales is seasonal agricultural labour. This source alone accounted for around 60% of cash income in the reference year for very poor households and around 36% for poor households. Sugar cane and paddy are highly labour-intensive crops, especially at planting and weeding times. Many people are also required to harvest sugar cane, and people are hired to scare birds from paddy fields in the weeks before the harvest as well. Better off and middle households, who cultivate fields that are larger than their household labour can manage on their own, hire members of very poor and poor households to help throughout the year. In the reference year, a typical very poor household sent 1-2 people to work on others’ farms during land preparation, planting and weeding periods, bringing in, on average, over 1,000,000 Tsh from cultivation labour. Harvest labour (including harvesting, threshing and bird scaring) generated an additional 395,000 Tsh. Poor households, who had more of their own land to look after, brought in slightly less than this: around 800,000 Tsh from cultivation labour and 320,000 Tsh from harvest labour. In the off season, when households have finished harvesting and before the rains start again, poorer households seek additional cash earning opportunities, making and selling bricks, preparing and selling food, brewing or gathering and selling firewood. Brick production was especially wide-spread in the reference year, bringing in around 10% of annual cash income for very poor and poor households. Some poor households also engage in small amounts of petty trade, although they are limited by a lack of transportation and investment capital. Petty trade is more important for middle and better off households. These households have some extra money and some means of transport, allowing them to buy up sizeable quantities of local produce and sell it in more profitable markets to make a small margin. Better off or middle households may also have small kiosks where they sell salt, soap, kerosene or other household goods. In addition, many middle and almost all better off households have a motorcycle, which they hire out for a fee (called boda boda) to transport people or goods. These two sources of cash income (petty trade and boda boda,) combined, provided middle and better off households with (on average) 35-40% and 20-25%, respectively, of their cash income in the reference year. Finally, all households derive a very small amount of cash by selling chickens. These are sold throughout the year when cash needs arise, but the total sales on an annual basis do not make up more than 3% of cash income. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year May 2014 to April 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other parts of Tanzania, households in this livelihood zone have to buy a number of essential goods throughout the year, and they need to pay for basic services. These include food (both staple and non- The graph provides a breakdown of total annual cash expenditure according to category of expenditure staple), household items, productive inputs, social services (school and health), clothes and miscellaneous items. The graph highlights a number of points. First, the two poorer wealth groups spend more money on staple food, in both absolute and relative terms; but the two upper wealth groups spend more in absolute terms on non-staple foods. As explained above in the section on ‘Sources of Food’, very poor and poor households bought maize grain for 4-6 months of the year. They spent between 260,000 and 290,000 Tsh on maize alone, taking up 15-20% of their cash income. Middle and better off households, on the other hand, spent 90,000 – 185,000 Tsh and had to devote less than 10% of their annual cash to maize. The rest of the staple expenditure was on a very small amount of cassava, beans, oil and dried fish. All households also spent money on other foods, such as rice, sugar, meat, sweet potatoes and vegetables. These are all included in the non-staple food basket. Better off households spent twice as much on non-staple foods as very poor households; the market helps middle and better off households increase their dietary diversity and provides access to preferred foods. Because these non-staple foods are generally more expensive, poorer households can afford to buy less of them, but what they do buy takes a larger chunk of their budget. For example, very poor and poor households spent around 30% of their annual cash on non-staple foods, whereas better off households (who actually spent more in absolute terms in this category) devoted around 20% of their annual cash to non-staple foods. Second, middle and better off households spent a lot more money on productive inputs than the poorer two wealth groups. ‘Inputs’ on the expenditure graph above includes the following: house repairs, land rental, seeds and tools, pesticides and fertilizers, labour, small business investment, and phone credit. Very poor and poor households did not spend any money on pesticides and fertilizers, labour or small business, devoting the majority of their inputs budget to phone credit, followed by house repairs and then land rental. The least is spent on seeds and tools. Middle and better off households spent the majority of their inputs budget (60-70%) on labour. This reflects the high-labour requirements of sugar cane and paddy and highlights the fact that, although better off households make more than three times what very poor households make, this comes at a cost. Business investment and phone credit are the next most important input costs for these households. In absolute terms, better off households spent around 13 times more than very poor households on productive inputs. In relative terms, the poorer two wealth groups allocated around 10% of their annual cash to productive inputs and the top two wealth groups spent 30-40% of their annual income on this category. Third, ‘social services’, which includes the money spent on education and health services, accounted for a significant proportion of annual expenditure. Education covers school fees, uniforms, stationery and Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 11 transportation. Absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Very poor households spent around 245,700 Tsh on schooling compared to 735,300 Tsh spent by better off households. This is much higher than in neighbouring zones, where spending on school is less than half of this amount. In this zone, the poorer two wealth groups are typically sending their children to both primary and secondary school, whereas in other zones poorer households only sent children as far as primary school. This is, in large part, because of the cash income derived from sugarcane outgrowing5. Better off households are funding their children’s education all the way through university. Also, as you move up the wealth spectrum, households are spending more on stationery, books, uniforms, school fees and transportation. Better off and middle households also spend more on medicine and health care; the poorer two wealth groups spent around 80,000 – 86,000 Tsh on health in the reference year, whereas middle and better off households spent 155,000 – 188,000 Tsh. Of course, these are general statements and individual households will have had very different requirements depending on whether or not a household member became sick and whether or not medical treatment was sought. Fourth, expenditure on basic household goods (‘hh items’), including all of the items bought by households over the year to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils, took up 5-10% of the expenditure basket for all households. Within this category, very poor and poor households spent the most on soap (28% and 26% of the ‘HH items’ budget, respectively), followed by grinding (20% and 23% of the ‘HH items’ budget, respectively). Middle and better off households spent the most within this category on kerosene and firewood; these two items combined accounted for 45-50% of the ‘HH items’ budget in the reference year. Soap took up the next largest chunk. Finding ways to reduce the relatively high costs of soap and grinding for poorer households could help them free us some money for other productive uses. Spending on clothes and other miscellaneous items are the last two categories included here. These two categories combined made up 18-22% of the expenditure basket for all wealth groups in this livelihood zone. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. As a reminder, the reference year was a relatively good year, so this discretionary category is higher here than it would be in bad years. Hazards There are a number of hazards that affect this zone on a regular basis. The first is crop pests and diseases, especially army worms, which affect maize and rice, rice blast and quelea quelea birds, which threaten the rice harvest, and rodents. Second, less of a hazard than a constraint, is a scarcity of land for agricultural production. This is a particular problem in the areas around the sugarcane plantations and near the national park (in the south). Third, conflict between farmers and pastoralists is high in this zone. Competition over scarce pasture and cropping lands as well as prime water sources has resulted in contested access to resources crucial for both farmers and livestock keepers. There are also occasional floods that can seriously undermine production during one or both seasons two out of every five years. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: 5 “Study of Sugarcane Outgrowing at Kilombero”, May 2015, page 4, http://dspace.africaportal.org/jspui/bitstream/123456789/35492/1/Kilombero%20stakeholder%20report_English%20Version.pdf?1 Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 12 All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to increase their local agricultural labour, working more days per month and sending more household members to work. There are limits on this strategy in a bad year since an increase in labour supply will inevitably drive down wages after a while. Thus, although more hours of work might be obtained by the household, the payment per day is likely to be reduced. Poorer households also try to sell more chickens. However, as the number of chickens owned by very poor and poor households does not exceed 20, and each chicken is worth only around 9,000 Tsh in a good year, this option will only go so far in terms of raising cash income, especially since the price is likely to drop in bad years. Middle and better off households try to reduce the amount they pay for agricultural labour, freeing up some of their cash income to spend on other essentials. This works in direct counterpoint to poorer households’ strategy of attempting to increase their agricultural labour income. Middle and better off households try to increase their sales of crops, selling their surplus at a higher price given the limited supplies on the market. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – vuli – amount produced Maize - masika - amount produced Pigeon peas – amount produced Paddy – amount produced Sesame – amount produced Sugar cane – amount produced Maize – vuli – producer price Maize - masika – producer price Pigeon peas – producer price Paddy – producer price Sesame – producer price Sugar cane – producer price Livestock production Chickens - numbers Chickens – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (bird scaring, harvesting, threshing) – number of jobs Petty trade – amount of trade Bricks – numbers produced Agricultural labour (land clearing and preparation, planting, weeding) – wage rates Agricultural labour (bird scaring, harvesting, threshing) – wage rates Petty trade – margins on trade Bricks – prices Expenditure Maize grain – consumer price Rice – consumer price Beans – consumer price Sugar – consumer price Oil – consumer price Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 13 Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve education services, ensuring that each school has an adequate number of qualified teachers 2) Provide access to affordable loans for agriculture 3) Set aside reserved areas of land for dedicated crop cultivation 4) Provide affordable agricultural inputs with adequate lead time for cultivation period 5) Improve health services by providing well-equipped dispensaries with affordable medicines at village level 6) Improve market infrastructure to ensure local households receive the best prices for their crops 7) Resolve conflict between farmers and pastoralists In addition, there are specific problems related to the payment for sugarcane which lead to households receiving less payment than they should. These could be addressed as follows: Identify which policies of the sugarcane cooperative create unfair conditions for the local farmers. Reduce the deduction take from the payment received by farmers. Create a more open and transparent system of standard measurement so that systems for weighing, sucrose measurement and payment calcuation are more open and fair and involve representation from outgrowers. Rotate district agricultural officers who are responsible for farmers in sugarcane plantations to reduce potential for corruption. Regularly assess the amount paid per ton of sugarcane in relation to the economic situation facing the farmers and producers."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":184,"cells":{"data":{"kind":"string","value":"# Extracted Content Morogoro Highland Maize & Vegetable Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Morogoro Highland Maize & Vegetable Livelihood Zone (TLZ 47) April, 20161 Zone Description The Morogoro Highland Maize and Vegetable Livelihood Zone is a small zone found in Mvomero District in Morogoro Region, including seven wards: Mlali, Bunduki, Mgeta, Langali, Nyandira, Tchenzema and Kikeo. At 2,000 to 2,300 metres above sea level, this is a highland area overlooking the town of Morogoro. The topography is made up of mountainous terrain, with hills and valleys following the contours of two main rivers: the Mgeta and Mbakana. The rivers are part of the Ruvu sub-basin, which is found at the base of the Uluguru mountains. They provide a year-round source of water for irrigation. This was originally a heavily forested area, much of which has been cleared for agriculture. Only a third of the forest cover that existed here in 1900 remained by the mid-1990s2. Rainforests in on the high mountain slopes have been declared forest reserves, but enforcement of the protections associated with this status are not easily imposed. Agricultural lands, surrounded by forests, are the main ground cover. The population density is around 42 people per square kilometre3. The rains here fall in two periods, from October to January, and then March through May. Annual precipitation ranges from 700-2,300 mm, with higher amounts found at higher elevations. Temperatures average around 180 C in the cool season and 300 C in the warmer months. The soils are well-drained, moderately deep to deep, reddish and yellowish sandy clay loams and sandy clays. Soil fertility is low, and land is hard to come by. The local economy rests on the cultivation and sale of vegetable crops. Households here generally do not produce enough food crops to cover their annual consumption needs. Thus, the strategy is to grow higher value vegetable crops throughout the year using both rain-fed and irrigated plots, and to use the cash from the sales of these crops to fund essential food and non-food purchases. This strategy depends on households’ access to markets, which is not always assured during the rainy season. Livestock are not a central part of the household economy, but provide small amounts of supplemental income. Households cultivate on small plots of land, constrained by the mountainous terrain and a growing population density. They use these small plots to maximum effect, however, growing a large array of crops, 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in February 2014 and ended in January 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2 Nobert, Joel, et al, Investigating the effects of landuse change on the streamflows of upper Ruvu River Subbasin, Tanzania, www.waternetonline.ihe.nl/symposium/10/.../Nobert-%20J.doc 3 Based on the 2012 national census. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 2 including maize, beans, pigeon peas, green peas, tomatoes, cabbages, sweet peppers, cow peas, carrots, eggplants and bananas. Maize and beans, as well as small amounts of Irish potatoes, green peas and bananas, are grown for household consumption; a portion of these crops is also sold. All the vegetable crops are grown almost exclusively for sale. Tomatoes and cabbages are especially important cash crops, and these tend to be grown mainly by middle and better off households, who can afford the expensive inputs associated with these crops. The vegetable crops are irrigated during the dry season, or when rainfall distribution is poor; maize, beans and bananas are entirely rain-fed. All cultivation is done by hand, using hand hoes and machetes. It is not possible to use oxen because of the mountainous terrain. All households use improved seeds, as well as fertilisers and pesticides, although the quantities vary by wealth group. The agricultural season extends throughout the year, and people are busy almost every month with one task or another. Land preparation, planting and transplanting tomatoes, and weeding are especially arduous, and for these tasks middle and better off households hire members from poor and very poor households to work for them. This provides important cash for poorer households, who could not survive without this seasonal work. It also provides critical labour for middle and better off households, without which they could not produce their surplus crops. Livestock is a minor source of cash for all households. Goats, pigs and chickens are raised. Chickens are the only animals owned by all wealth groups; very poor households do not own significant numbers of goats or pigs. Goats graze and browse freely; pigs are stall-fed on crop residues, maize husks and green leaves; chickens range freely, subsisting on maize husks and food scraps. The main water sources for livestock are minor rivers and streams; water is not purchased for animals. In addition to vegetable sales and local agricultural labour, households here earn cash through self- employment activities (such as brick making, brewing, and firewood/charcoal sales for poorer households) and petty trade (such as owning kiosks, or boda boda for middle and better off households). The services in this zone are similar to many rural areas in Tanzania, with the exception of access to water, which is better here than in most places. Fresh, potable water is obtained from rivers, streams and mountain springs. Sanitation facilities consist of pit latrines, most without covers and of poor quality. Health dispensaries are found in many villages, or at the ward centre, but they are not always well-stocked or staffed with qualified medical professionals. Most people use Community Health Funds (CHF). Primary schools are found in the villages and secondary schools are available in the ward centres. It is common for all households to send their children through primary school, but only middle and better off households are able to afford the extra costs of secondary school. Some better off households also send their children to college. There is no electricity, so poorer households depend on kerosene lamps, while better off households also use battery-operated torches. Households in all wealth groups have mobile phones, with better off households having multiple phones. There are no sources of credit, nor are there savings schemes available. Markets Market access is especially important in this zone, because household depend heavily on the sale of fresh vegetables throughout the year. On the one hand, the transportation infrastructure in this zone is good: trucks can always reach Nyandira, the central vegetable market, where households bring their commodities for sale; and from Nyandira there is a good tarmac road to Morogoro, which has easy access to the terminal market in Dar es Salaam or Dodoma. Therefore, if people reach Nyandira, they are almost guaranteed to have a market for their goods. On the other hand, the road access for farmers living in remote villages is not always secure. In the rainy season vehicles get stuck in the mud or are blocked by seasonal streams or boulders that get washed into roads. Households sell a range of food crops and vegetables, including maize, beans, pigeon peas, green peas, Irish potatoes, tomatoes, cabbages, onions, carrots, sweet peppers, eggplants and cucumbers. Tomatoes and cabbages are particularly important cash crops. All locally-grown food crops and vegetables follow the same trade route. After harvesting, farmers must transport their goods to Nyandira, and from there they are sold Morogoro Highland Maize & Vegetable Livelihood Zone Profile 3 on to Morogoro, Dar es Salaam and/or Dodoma. Tomatoes are sold throughout the year, but the peak sales occur in January, from the vuli harvests. The peak selling time for beans is in February; for cabbages it is November; and for green peas it is July. People reach the central market on foot, by bicycle or motorcycle. Unlike in many parts of Tanzania, traders do not buy up vegetables at the farm gate. Vegetables need to be transported to market soon after harvesting, and there is a short window of opportunity for selling them. Many are vulnerable to bruising and rotting, especially in hot weather, so care needs to be taken during transport. Traders do not want to take on the risks involved, preferring to transfer these to local farmers. Traders buy up commodities once they reach the central market of Nyandira, where vegetables are collected and bundled for onward sale to Morogoro, Dar es Salaam and Dodoma. Thus all the risks of transporting fresh vegetables to market rest on the farmers, who must traverse rocky, mountainous dirt roads that often become inaccessible in the rainy season. From interior villages like Kikeo, Tchenzema, Tandari, Luale and Bumu, these risks are not insubstantial. Livestock are sold at small mobile ward- and sub-ward level markets within the zone throughout the year. Most livestock are for local consumption and do not get sold onwards. Sales occur throughout the year, when people need extra cash for school fees, medical expenses, festivals, or unexpected emergencies. All households also buy food during much of the year. Poorer households buy maize grain, the cheapest staple, to cover their needs for nine to ten months of the year, starting in August, even in relatively good production years. Most maize is sourced from Morogoro and Kibaigwa, and sold through the Nyandira market. Rice, purchased mostly by better off households, comes from Turiani and Kilosa via Morogoro to the Nyandira market. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local kiosks that are owned by middle and better off households. The labour market is mostly local and consists of seasonal agricultural labour. There is also a small demand from local towns and some seasonal employment is found outside the livelihood zone. It was estimated that in the reference year, 85% of seasonal labour was found within the zone on local farms. An additional 10% came from local towns, and the other 5% came from outside the livelihood zone, mainly from Mbigiri and Magole, in Kilosa District, where there is often work to be found on tomato and paddy farms. The balance shifts in bad years, with more people traveling to local towns or to areas outside the zone to find work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Morogoro Highland Maize & Vegetable Livelihood Zone the reference year covered the consumption period from February 2014 to January 2015. The production year starts with the planting season in October/November and ends with the harvest in February through April of the following calendar year. Thus, the 2014-2015 consumption year corresponds to the production year that starts with the 2013-2014 vuli season. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the responses of the community leaders, shows year quality by production year. The production year of 2013-2014, which corresponds to the consumption year of 2014-2015 was considered an average year. In the past 10 seasons, there have been 5 average seasons, 2 below average seasons, and 3 above average seasons. The baseline information presented in this profile provides a view into how households in this livelihood zone make ends meet in an average year. Production Year Season Rank Critical Events 2014-2015 Masika 4 Above average rainfall, good crop yields, good producer prices, low staple food prices 2014-2015 Vuli 4 Above average rainfall, good crop yields, good producer prices, low staple food prices 2013-2014 Masika 4 Above average rainfall, good crop yields, good producer prices, low staple food prices Morogoro Highland Maize & Vegetable Livelihood Zone Profile 4 2013-2014 Vuli 3 Average rainfall, normal harvest, decent producer prices 2012-2013 Masika 3 Average rainfall, normal harvest, decent producer prices 2012-2013 Vuli 3 Average rainfall, normal harvest, decent producer prices 2011-2012 Masika 3 Average rainfall, normal harvest, decent producer prices 2011-2012 Vuli 3 Average rainfall, normal harvest, decent producer prices 2010-2011 Masika 2 Below average rains, with below average harvest and high staple food prices; received food aid from the government 2010-2011 Vuli 2 Below average rains, with below average harvest and high staple food prices 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year This is a bi-modal area: the first rains occur from October through December (vuli) and the second are from March through May (masika). The masika rains are usually heavier and more reliable. Agricultural activities are linked to the timing of the rains, but because irrigation is also used, households here are busy year-round with different crop-based activities. Land preparation occurs in September for the vuli crops, and in February for the masika crops. The October rains soften the ground enough so that people start to plant maize towards the end of October. Tomatoes are planted towards the beginning of October, often with the use of irrigation from streams. Beans are planted at the same time as these two crops, inter-cropped with both maize and tomatoes. Cabbage and Irish potatoes are planted as single stands. Cabbages are grown in two main seasons; the first corresponds to the masika season, planted in March and harvested in May and June; the second season relies on irrigation and is planted just after the first harvest and harvested two months later in September. Irish potatoes are planted in June, also irrigated using the water from streams and rivers, and harvested in October and November. Most maize is harvested in March and April, preceded by a month of green consumption. A period of sales follows the harvest of each crop. The peak agricultural labour periods are, first, from October through February, corresponding to planting of the first maize crop, and planting and transplanting of the first tomato crop; weeding for both crops; the first tomato harvest; the tomato harvest and land preparation for cabbages. And, second, from June through July, which is when cabbages are harvest, tomatoes are re-planted, Irish potatoes are planted, and all the irrigated vegetables are weeded. All activities are done by hand, and land preparation, transplanting tomatoes and weeding are especially arduous. Even though middle and better off households do not cultivate large areas of land, they need extra help to manage the intensive periods of the year, and so they hire members of very poor and poor households to work for them on all of these tasks. Land preparation takes place over 2.5-4 months (at different times of year); planting/transplanting occurs for 3 months (although not consecutively); and weeding also is being undertaken for 3 months at different times of year depending on the crop and the season. The harvesting periods also take place for around 2 ½ months of the year. During these times, members of poor and very poor households work on the larger farms of middle and better off households, while, at the same time, tending to Morogoro Highland Maize & Vegetable Livelihood Zone Profile 5 their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. The graph to the right shows average monthly rainfall (mm) in Morogoro District based on a 20 -year period (1994-2013) Source: TZ Meteorology Department December and January is when the lean season occurs. These are the months that households have run out of their maize stocks from the previous year’s harvest. Poorer households, in fact, run out as early as June or July, but by December, all households have depleted their stocks. They need to purchase all of their staple grains just when the price of staple foods is highest (from December through January). Thus, the paid work for weeding maize and harvesting tomatoes, which is offered up by middle and better off households at this time, helps provide needed cash to poorer households, allowing them to bridge the gap until February, when the green harvest of maize is available. The dry season starts in earnest in June and lasts through September. This is a time when most human illnesses, especially pneumonia and upper respiratory diseases, occur. The weather during this period in this high, mountainous zone is quite cold, creating the conditions for these sicknesses. It is worth keeping in mind that the most important livelihood capital that poorer households have is their own labour; when an active labourer is sick in a poor household, the income for this household rapidly drops. Because this coincides with one of the peak labour periods, it can be especially damaging for a productive household member to be sick at this time. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. The festival season takes place in September and October, when the proceeds from the previous year are available to spend, and before the intensive work of the coming agricultural season has kicked into high gear. It is a rare moment of relative downtime in the otherwise very busy schedules of people living here. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The main determinant of wealth in this livelihood zone is how much land a household cultivates, and related to this, the type and quantity of vegetable crops grown. How much land a household cultivates is, in turn, governed by the amount of land it owns and/or is able to rent in; the size of its intra-household labour pool as well as its capacity to hire additional labour; and the amount of cash it has available to buy seeds, fertilizers and pesticides, which are especially important when it comes to the success of vegetable crops. Arable land is not easy to come by in this mountainous terrain, and plot sizes are small; even better off households do not cultivate more than 4 acres. All households use hand hoes, as the terrain is not amenable to ox ploughing. Typical better off households cultivate around 2.5-4 acres of land, using hired labour as well as intra-household labour. They devote as much of their land as possible to tomatoes and cabbages, which offer up the highest returns. These crops also demand high investments, and better off households buy the most pesticides, fertilizers and improved seeds. They also hire the most seasonal agricultural labourers. Better off households have more livestock than other households, usually keeping a herd of around 10-18 goats and a few pigs, alongside 10-30 chickens. Their household sizes are a little smaller than poor and very poor households, with around 4-6 members. These households may also own other assets, like a motorcycle for boda boda, or they may operate a kiosk. They typically own several cell phones, which are used to gather price and market information as well as to keep in touch with far-away relatives. Typical very poor households, on the other hand, cultivate only 0.5-1.5 acres of land. They do not produce enough in any year to cover all of their food and cash needs. These households have very few goats, if any (0-2), and pigs (0-2) as well as some chickens (4-8). Very poor households tend to be slightly bigger in size, with 5-7 members. They face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone. The distribution of wealth in this zone is weighted towards the bottom. Very poor (30-40%) and poor (20-40%) households together make up around 50-80% of households in the zone. Middle (20-30%) and better off (8-15%) households combined represent around 28-45% of the households. In addition, since middle and better off households are slightly smaller, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is even smaller than this. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period February 2014 to January 2015. February represents the start of the consumption year because it is when people begin to harvest green maize and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year, with average rains, crop yields and prices. There are only two sources of food In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. in this livelihood zone: own crops and purchased food. Own milk and meat do not contribute to the food basket, as they do in many other zones. As you move up the wealth spectrum, reliance on own crops increases. Food purchases are important for all wealth groups, but especially for poorer households. Maize, along with very small amounts of beans, pigeon peas, green peas, cassava and Irish potatoes, provide the calories shown in the ‘own crops’ bar on the graph above. Collectively, these accounted for 44-67% of the minimum calorie requirements for households in the reference year. The majority of these came from maize, which contributed (including green maize) 36%, 36% 48%, and 61% of minimum food needs for very poor, poor, middle and better off households, respectively. The other crops accounted for only around 7-11% of food needs. Thus, even in an average year, very poor and poor households are meeting, at most, only half of their annual food needs with crop production. Taking a closer look at production, typical middle and better off households produced around 600 kg and 1,000 kg of maize, respectively, in the reference year, along with 430 kg and 480 kg of pulses, respectively, and around 350-400 kg of Irish potatoes. With the exception of maize, the production values for food crops do not vary much between middle and better off households. Very poor and poor households produced around 450 kg and 540 kg of maize, respectively, 150 kg and 250 kg of pulses, respectively, and 190 kg of Irish potatoes (for both). These are not high levels of production, reflecting the fact the households have very small agricultural plots. The only households that could cover all of their food needs with their own production alone, if they consumed all (rather than selling part) of their food crops would be the better off households. (Even then, they would only be able meet around 135% of their calorie needs, which does not represent a large surplus.) The vast majority of households here produce significantly less than they need for survival in an average year. The market is, therefore, especially important in this livelihood zone, accounting for around 47-48% of minimum food needs for all households. The poorer two wealth groups purchased mostly maize grain, the cheapest staple. Of the 47-48% of minimum calories these households bought, 32-36% were in the form of maize grain, or in other words, around three-quarters of their purchased food (in calorie terms) was made up of maize grain. Middle and better off households, on the other hand, purchased only around 14% and 9% of their minimum calories in the form of maize grain. In other words, less than a third of their purchased food (in calorie terms) was made up of maize grain. For middle and better off households, the ‘purchase’ component was comprised of more high-value, preferred foods, such as wheat flour (2% of minimum calories), rice (13% of minimum calories), sugar (6% of minimum calories), meat (1-2% of minimum calories), oil (8-11% of minimum calories), dried fish (2% of minimum calories), and sweet potatoes (1% of minimum calories). By comparison, very poor and poor households purchased only around 11-15% of their minimum calories in the form of these higher-value food items, and much of this was oil. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 8 Sources of Cash Income The graphs to the right present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. Because households need to purchase at least half of their food every year in this zone, it is especially important to know where the cash to fund those purchases comes from. Crop sales provide the most important source of revenue for all but the bottom wealth group. Especially striking is the contribution made by sales of tomatoes and vegetables. With smaller areas under cultivation, households here choose to use a good portion of their available land for high-value vegetable production. In the reference year, the combined value of tomato and vegetable sales accounted for 16%, 28%, 38%, and 42% of the annual cash income of typical very poor, poor, middle and better off households, respectively. Maize, beans, pigeon peas, green peas, Irish potatoes and bananas are also sold. The pulses, and especially beans and pigeon peas, garner the highest price (around 1,500/kg in the reference The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,500,000 – 2,000,000 2,000,000 – 3,000,000 3,000,000 – 4,000,000 4,000,000 – 6,500,000 year) so even small amounts can earn households a meaningful amount of cash. Typical middle and better off households sold 270-410 kg of pulses, generating around 425,000 – 535,000 TZS, or 11-12% of annual cash income. Sales of maize and the other food crops brought in substantially less than this. Overall, crop sales accounted for 28% of the annual cash income of typical very poor households, 53% of the annual cash income of typical poor households; and 65-70% of the cash income of middle and better off households. In absolute terms, better off households generated around 7 times more from their crop sales than very poor households, which is 4 The average exchange rate from February 2014 - January 2015 was 1 USD = 1,777 TZS Morogoro Highland Maize & Vegetable Livelihood Zone Profile 9 proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 3.25 times more land than very poor households, but are able to derive substantially more value per acre from their efforts. They invest more in terms of labour and inputs, and are able to better time their ploughing, labour and inputs applications, enabling them to produce more in absolute terms; and they can also grow more of the higher- value crops, which allows them to make the most of their investments. For middle and better off households, small business and trade (shown as ‘petty trade’ on the graphs) was the next most important source of cash income in the reference year, comprising 17% and 24% of their annual cash income, respectively. These households are able to use some of their cash to buy household goods and commodities, like salt, soap, kerosene and batteries in bulk; they set up kiosks in the villages and generate extra income through this business. Some also make money from boda boda, or motorcycle hire, which is especially important for transporting agricultural commodities and people from the villages to the central vegetable market in Nyandira. Very poor and poor households do not have the financial means to set up shops or buy motorcycles for transporting goods, so they turn instead to casual labour as a means of securing needed cash. Casual labour is, in fact, the most important source of cash income for very poor households, accounting for 45-50% of their cash income in the reference year. Poor households derived around a third of their cash income from this source. Agricultural activities take place throughout the year in this zone, and poorer households provide a good portion of the labour pool for middle and better off households. Labour is hired for land preparation, planting, weeding and harvesting. Very poor households derived a relatively even amount of their annual cash from each of these activities (around a quarter of their labour-based cash income from each). Poor households earned the most from land preparation, followed by weeding. In a bad year, harvest-related labour may be eliminated, and demand for the other activities would be much reduced. Livestock sales provided the remainder of cash income for the top three wealth groups in the reference year. Overall, livestock sales accounted for only around 5-15% of cash income for households in this livelihood zone. Goats, pigs and chickens are sold. A typical better off household sold around 4 goats (at 45,000 TZS per head), 8 chickens (at 8,000 TZS per head) and 1 pig (at 10,000 TZS) in the reference year; middle households sold more pigs – around 4 – because they have less in the way of crop income, so try to make up for that through pig ownership. They also sold around 2-3 goats and 6 chickens. Very poor and poor households sold only around 4 chickens, along with 0-2 goats and 0-2 pigs. The price of animals did not vary much by wealth group. Livestock are not a significant differentiator in this zone, and although better off households did earn around 3 times more than very poor households from livestock sales, they actually earned less than middle households and almost the same as poor households. Vegetable sales are crucial here, not livestock sales. One final source of cash income for very poor households was self-employment, which included mainly brick production, but also brewing and firewood/charcoal sales. These activities contributed almost a fifth of the annual cash income for these households in the reference year. Expenditure Patterns The graph below presents expenditure patterns for the reference year February 2014 to January 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. The goods and services on which households in this zone spend their cash include: staple and non-staple food, household items, productive inputs, social services, like schooling and health, clothing and other non-essential items, such as tobacco, cosmetics and festivals. As in many other areas of rural Tanzania, poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. All wealth groups spent some of their available cash on staple foods, which includes (in this case) maize grain, wheat and rice. In both absolute and relative terms, very poor households spent more than any other wealth group Morogoro Highland Maize & Vegetable Livelihood Zone Profile 10 on staple foods. In the reference year, very poor and poor households spent around 28-33% of their annual cash on staple foods; and middle and better off households spent 8%-13% on this category. The make-up of the staple food basket is not the same for all wealth groups. Very poor and poor households spent a total of 530,000-539,000 TZS on staple food; 405,000-459,000, or 75-85% of this was, on maize grain, the cheapest staple. Middle and better off households spent around 460,000 and 407,000 TZS, respectively, on staple foods, but only 144,000 and 90,000 TZS, or The graph provides a breakdown of total annual cash expenditure according to category of expenditure around 20-30%, on maize grain. They concentrated their spending on rice, first, which is a preferred food, and then wheat. Unlike in many zones, where middle and better off households do not need to spend cash on staple grain, in this zone all households, with the exception of some better off households, need to buy staples to fill a calorie gap, although this gap decreases as you move up the wealth spectrum. Poorer households spent more in absolute terms on staple foods, but middle and better off households spent more in absolute terms on non-staple foods. The non-staple food category included beans, Irish potatoes, sugar, meat, oil, dried fish, sweet potatoes and vegetables. Of these, the lower two groups spent the most on meat and dried fish, supplementing their heavily grain-based diet with protein, followed by oil and then sugar. Middle and better off households spent the most on meat. After this, relatively equal amounts were spent on sugar, oil and dried fish. In the reference year, the proportion of cash income spent on non-staple foods for very poor, poor, middle and better off households was around 22%, 21%, 19%, and 17%, respectively. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 9%, 10%, 19% and 23%, respectively. Thus, better off households are able to buy a more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less. Middle and better off households both spent the largest portion of their annual cash income on productive inputs, as represented by the dark blue bar in the graph. In proportional terms, their spending on productive inputs (27- 34% of annual expenditure) is similar to very poor and poor household spending on staple foods (28-33% of annual expenditure). The following are included in this category: livestock drugs, land rental, seeds/tools, pesticides/fertiliser, labour hire, business investment, and phone credit. Within this set, very poor households spent money only on seeds/tools, pesticides/fertilisers and phone credit, with the most spent on seeds/tools, followed by phone credit and finally pesticides/fertilisers. Middle and better off households spent money on all items within the category (with the exception of land rental, which only applies to better off households); the majority of their inputs budget was on seeds, tools, pesticides and fertilisers (35-39% of their inputs budget), and labour hire (27-32% of their inputs budget). Fertilisers and pesticides are more important in this zone than they are in other zones because of the dependence on vegetables and tomatoes for cash income. In many zones there is no spending at all on those items, but here all households devote at least part of their budget to these goods. In absolute terms, the amount spent by better off households on productive inputs was 9-10 times the amount spent by very poor and poor households, and almost 2 times the amount spent by middle households. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services, firewood and utensils. Within this category, very poor and poor households spent the most money on soap, which took up around a third of this budget, followed by payment for lighting and grinding, each of which made up around 15-20% of the ‘hh items’ budget. Middle and better off households spent the most on lighting. Middle households spent the next most on soap, whereas better off households spent the next most on firewood. Neither very poor nor poor households spent money on firewood, Morogoro Highland Maize & Vegetable Livelihood Zone Profile 11 collecting it themselves, and selling extra bundles to the top two wealth groups. All households spent the least on salt and tea. On an annual basis, spending on basic household goods made up 12-13% of annual expenditure. ‘Social services’, shown in orange on the graph, includes schooling and health costs. Households spent 9-11% of their annual cash on these costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, better off households spent on education around 1 ½ times more than middle households and 2-2 ½ times more than poor and very poor households. Very poor and poor households usually are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent 3 ½ times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Spending on clothes and other miscellaneous items are the last two categories included here. Spending on clothes accounted for 5% of the annual budget for all households. The ‘other’ category includes things like cosmetics, hair, beer, tobacco, cigarettes, community obligations, transportation and festivals; in the reference year households devoted 7-15% of their cash to these items. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was an average year, even the very poor wealth group had more in this budget than it would in a bad year. Hazards Two hazards affect this zone on a regular basis. The first is crop pests and diseases. Tomato leaf miner (tuta absoluta) is especially destructive, as it can destroy a whole season’s crop. Elegant grasshoppers, which affect maize and leaf hoppers and stem rot, which affect beans cause problems throughout the zone almost every year. The second is livestock disease, such as contagious caprine pleuropneumonia (CCPP) for goats, worms for pigs, and New Castle Disease, which can wipe out an entire flock of chickens. Human diseases are also endemic, especially malaria and upper respiratory diseases. Because household labour is so critical to income generation, especially for poorer households, losing this labour can translate into significant drops in income. The main periodic hazards are drought, which can seriously damage crop production once every three years. Droughts result in a series of inter-related shocks, such as rapid increases in staple food prices, declines in livestock production, reduced labour income and reduced returns on self-employment. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Middle and better off households try to increase their irrigation activities. When the rains fail, households who have the means to do so attempt to increase their production of irrigated crops. In years when rain-fed crops fail, irrigated crops fetch even higher prices than normal, so if the strategy succeeds, it can be quite effective. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 12 Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people may go to Mbigiri and Kilosa districts, where they find work on tomato and paddy farms. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Morogoro Highland Maize & Vegetable Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Beans – amount produced Pigeon peas – amount produced Green peas – amount produced Irish potatoes – amount produced Sweet potatoes – amount produced Bananas – amount produced Tomatoes – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Green peas – producer price Irish potatoes – producer price Tomatoes – producer price Livestock production Goats – herd size Pigs - numbers Goats – producer price Pigs – producer price Other food and cash income Agricultural labour (land preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Bricks – numbers produced Petty trade – volume of trade Agricultural wage rates (land preparation, planting, weeding) Agricultural labour rates (harvesting) Bricks – price per brick Petty trade – returns on trade Expenditure Maize grain – consumer price Rice – consumer price Sugar – consumer price Oil - consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than pasture improvement, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Timely and affordable provision of crop inputs Improved maintenance of existing road networks and increased construction of new roads Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":185,"cells":{"data":{"kind":"string","value":"# Extracted Content Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone (TLZ 56) April, 20161 Zone Description The Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone2 is found in Dodoma Region, in central Tanzania, and includes parts of Bahi, Dodoma Municipal and Chamwino districts.3 This is a warm, semi-arid, lowland area, interspersed with hills and valleys, and located on a broad plateau ranging between 900 and 1,200 metres above sea level. The vegetation is largely semi-desert and bush with areas of savannah grassland. There are no mountains or permanent rivers of note. This zone is relatively well-connected to other parts of Tanzania owing to its central location. A major highway connects Dodoma with Dar es Salaam via Morogoro to the east. To the west, there are roads to Mwanza and Kigoma through Tabora. The Great North Road links the area to Arusha via Kondoa to the north. The central railway line also connects Dodoma to Dar es Salaam to the east, Kigoma to the west, and Mwanza to the north-west. The population density is around 38 people per square kilometre. There is one rainy season, starting in December and lasting until April or May. Annual precipitation is quite limited, ranging from 500 to 600 mm. Poorly distributed rains are a regular occurrence, with dry spells particularly common in January, when most of the crops are sown. Average temperatures vary from 180 C in July to 310 C in November. The cool dry season begins in June and ends in early September. The soils are loamy sands and reddish loamy sands. The household economy is based on both crop production and livestock raising. Food crops are all rain-fed, and because of poorly distributed and inadequate rainfall, there are frequent bad years, leading to deficits among poorer households that need to be filled with food aid. Grapes are the main cash crop, and they provide a meaningful source of income, but only for households in the upper two wealth groups. 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 In the 2008 FEWS NET Livelihood Zoning, this zone was called the Dodoma Lowland Sorghum, Bulrush Millet, Sunflower & Grape Livelihood Zone, but because oilseed crops (like sesame) are important, and sorghum and sunflower are less important, the name has been changed. 3 The wards included in the zone are Mtitaa, Mwitikira and Chibelela in Bahi District; Mpunguzi, Mbabala, Zuzu, Nala, Hombolo, Chihanga, Ipala, Buigiri, Msalato, Nzuguni, Miyuji, Kizota, Mkonze, Mbalawala, Makole, Hazina, Uhuru, Chamwino, Kikuyu North, Kikuyu South, Dodoma Makulu, Kilimani, Tambuka Reli, and Makutupora in Dodoma Municipal; Makang’wa, Mvumi Mission, Mvumi Makulu, Mlowa Bwawani and Iringa Mvumi in Chamwino District. There are some wards originally included in this zone that should be removed and put into Dodoma urban because they are more urban in nature. These include: Kizota, Msalato, Nzuguni, Makole, Miyuji, Hazina, Uhuru, Chamwino, Kikuyu North, Kikuyu South, Dodoma Makulu, Klimani and Tambuka Reli. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 2 Households cultivate bulrush millet, sorghum and maize, with bulrush millet (a relatively successful drought- resistant crop) the most important of the cereal crops for home consumption. Bambara nuts and groundnuts are the main pulses grown for food, and they are grown just as importantly for sale as for consumption. Sesame and sunflowers are two other crops grown principally for sale, but also consumed in small amounts. Grapes, the main cash crop, are grown only by the upper two wealth groups, but they provide an important source of cash, indirectly, to poorer households, who get hired within the vineyards to help prune, spray and harvest. Oxen are used widely for ploughing. Some at the upper end also use tractors, and poorer households use hand hoes when they are unable to get access (through labour exchange) to plough oxen. Most households do not use improved seeds or industrial fertilizers and pesticides. However, middle and better off households do buy pesticides for use in their vineyards, and they may use animal manure to fertilise their fields. The peak agricultural labour period is from December through March, corresponding to planting and weeding periods; but other times of year are also busy. Extra labour is required in the vineyards for land preparation, pruning, spraying and harvesting; and it is also needed for land preparation, harvesting and threshing of the food and oil crops, in addition to planting and weeding. Middle and better off households hire members of very poor and poor households to work for them during the labour-intensive times of the year. This provides the most important source of cash for poorer households, who could not survive without this seasonal work. It also provides essential labour for middle and better off households, without which they could not produce their surplus crops. Livestock is also a vital source of cash (and a minor source of food) for some. Cattle, goats, sheep and chickens are raised. All of these animals are sold live throughout the year when cash is needed and milk from cattle is sold for cash and consumed at home. Chickens are the only animals owned by all wealth groups; very poor households do not own cattle, goats or sheep. All livestock graze and/or browse freely, and also eat crop residues at harvest time. None of the livestock are stall-fed. The main water sources for livestock during the wet season are seasonal rivers, open wells, boreholes, seasonal ponds and dams. In the dry season, they turn to shallow wells and boreholes, and there is payment for tap water in some villages. In addition, the larger livestock are taken to areas in Morogoro, where pastures and water sources are more reliable. Men are usually in charge of taking care of the cattle; boys, and sometimes girls, are responsible for taking care of goats, sheep and calves. In addition to crop and livestock-related income, and – for poorer households – casual employment income, households earn cash through self-employment activities (such as firewood/charcoal sales for poorer households) and petty trade (such as prepared food sales for poorer households, or owning kiosks, renting out oxen, or boda boda for middle and better off households). The services in this zone are very basic. Access to water in this semi-arid zone is more limited here than in many other areas of the country. Open wells, shallow wells, boreholes, and seasonal ponds are the main sources of water. In some villages, payment for water is typical. Access to clean, potable water is not guaranteed throughout the zone. Health dispensaries are found at the ward centre, health centres are found at each division, and every district has a hospital; however, these are not always well-stocked or fully-staffed with qualified medical professionals. Primary schools are found in the villages and secondary schools are present in the ward centres. It is common for all households to send their children through primary school, and some (but not all) poorer households also send their children to secondary school; however, only middle and better off households are able to afford the extra costs of vocational schools or colleges. There is no electricity, so poorer households depend on kerosene lamps and battery-operated torches, whereas better off households also use solar panels. Households in all wealth groups have mobile phones, with better off households having multiple phones. There are no sources of credit, nor are there savings schemes available. There are no NGOs operating in this zone. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 3 Markets The transportation infrastructure in this livelihood zone is mixed. There are tarmac roads connecting the central market of Dodoma to Morogoro, to Iringa, to Singida and to Arusha via Kondoa. From all of these points it is possible to reach terminal markets like Kenya and Dar es Salaam. However, the many feeder roads that connect villages to Dodoma are made of dirt or marram, and most are in poor condition. They function adequately during the dry season, but in the wet season access becomes challenging. Inundation by seasonal streams during the wet season is a common occurrence, requiring long waiting periods until waters recede and vehicles are able to make their way through. Bridges are few and far between; most passages over rivers are not bridges at all, but cemented portions of the river bed. Nevertheless, the zone is well-connected to other urban centres and market access, once commodities reach Dodoma town, is good. Households sell a range of food and cash crops, as well as livestock. Maize, sorghum, bulrush millet, groundnuts, Bambara nuts and sesame are grown for both home consumption and sale. The cash income generated from sesame and pulses (groundnuts and Bambara nuts) is especially important, as discussed below in the section on ‘Sources of Cash Income’. Sunflowers and grapes are the main cash crops, grown almost exclusively for sale. Whereas the cereal crops are sold locally, rarely leaving the region, the other crops are exported to other regions. Traders purchase bulrush millet or maize at the farm gate and take it by truck to markets and stocking facilities in Dodoma and Dar es Salaam. Traders from village shops also go to farmsteads to buy maize or bulrush millet. Some farmers carry bulrush millet by bicycle or head-lots to ward markets (in Kiswahili known as minadas) or village shops. Most maize and bulrush millet farmers in the zone do not have storage facilities and must sell all bulrush millet or maize immediately after harvest. If local grain storage facilities were improved, many farmers would not need to sell their grain at a low price directly after harvest only to buy bulrush millet or maize later in the season at a high price. Sunflowers are transported to Dodoma and then on to Dar es Salaam and other regional centres for processing into oil. Sesame and groundnuts get exported to Dar es Salaam and then on to distant markets in Asia. Some groundnuts are also destined for Nairobi. Groundnuts are sold from April to August; sesame and sunflowers have a more limited window of sale, from June to August. Grapes have a number of different terminal points: some are used within Dodoma Region for wine production; some are sent via Dodoma to Dar es Salaam as fruit for direct consumption; others are transported via Dodoma to Arusha and then on to Kenya for both consumption and wine production. The two periods of peak grape sales are February to March and August to September. The first period coincides with the rainy season, when road access is often compromised, which means some grapes never make it to market before rotting. Cattle, goats and sheep are sold to traders at mobile markets within the zone, from where they get transported to Dodoma and then on to Dar es Salaam. Chickens are sold locally. Sales occur throughout the year, when people need extra cash for school fees, medical expenses, festivals, or unexpected emergencies. However, peak sales are from January through March, the lean season, when most households need extra cash to purchase food; and in the harvest season, from June through August, when livestock prices are high after animals have been fattened on crop residues. (See ‘Seasonal Calendar’ section, below.) Poorer households buy maize grain, the cheapest staple, to cover their needs for two to three months of the year (December through February), even in relatively good production years. Most maize is sourced from Iringa and sold through the Dodoma market. Rice, purchased by middle and better off households, comes from Shinyanga and Morogoro to the Dodoma market. The labour market is mostly local and consists of seasonal agricultural labour. There is also a small demand from local towns and some seasonal employment is found outside the livelihood zone. It was estimated that in the reference year, 80% of seasonal labour was found within the zone on local farms. An additional 15% of the casual employment opportunities were from local towns, and the other 5% came from outside the livelihood zone, mainly from Kongwa (in Dodoma), Kiteto (in Manyara), Mvomero and Kilosa (both in Morogoro) and Kilindi (in Tanga). The balance shifts in bad years, with more people traveling to local towns Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 4 or to areas outside the zone to find work, especially from December to February. There is no labour migration into this zone. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. The production year starts with the planting season in November/December and ends with the harvest in April through July of the following calendar year. Thus, the 2014-2015 consumption year corresponds to the production year that starts with the 2013-2014 agricultural season. During community leader interviews, informants were asked to rank the last five production years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below summarizes the responses of the community leaders. The production year of 2013-2014, which corresponds to the consumption year of 2014-2015, was considered an above average year. In the past 5 years, there have been 2 average or above average years; 2 slightly below average years; and 1 well-below average year. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an above-average year. Production Year Season Rank Critical Events 2014-2015 Masika 1.4 Poor rainfall distribution, low crop yields, poor pastures, high staple food prices, low livestock prices, higher livestock mortality; unusual migration of livestock; food aid was distributed; extra livestock sales; more charcoal sales. 2013-2014 Masika 3.7 Good rainfall distribution; good crop yields; good pastures; low staple food prices; good livestock prices. 2012-2013 Masika 3.1 Average rainfall distribution; average crop harvests; average pastures; average food prices; average livestock prices. 2011-2012 Masika 2.4 Average rainfall distribution, below average crop yields; average pastures; average staple food prices; average livestock prices. 2010-2011 Masika 2.5 Average rainfall distribution; average crop harvests; average pastures; average food prices; average livestock prices. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year There is one long rainy season in this zone, starting in December and lasting partway through April. Agricultural activities are linked to the timing of the rains, but because irrigation is also used in the vineyards, households here are occupied year-round with different crop-based and livestock-rearing activities. Land preparation starts in September – a full two months before the planting period – as the cereal and oilseed crops are all planted in November and December, with some planting extending into the beginning of January. Sorghum, maize and groundnuts are inter-cropped, while Bambara nuts, grapes, sesame, sunflower and bulrush millet are grown as single stands. From late December through March, people are busy with weeding. The main harvests occur in May and last through July; however, sesame is harvested as early as March; and part of the maize, groundnut and Bambara nut harvests are eaten green, beginning mid-way through March. Grapes are harvested twice a year, once in March and once in August/September. A period of threshing (where applicable) and sales follows the harvest of each crop. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35-year period (1980-2014). Source: TZ Meteorology Department The peak agricultural labour period is from December through March, corresponding to planting and weeding of the cereal and oil seed crops; but that does not mean that the other times of year are not busy. Extra labour is required in the vineyards almost year-round for land preparation, pruning, spraying and harvesting; and it is also needed for the land preparation, harvesting and threshing of food and oil crops. Middle and better off households cultivate large areas of land, which they cannot manage without extra help. They hire members of very poor and poor households to work for them during these labour-intensive times of the year. Thus, poorer households are busy working for others while, at the same time, tending to their own fields. The ultimate result Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 6 is that poorer households have lower yields due to less-intensive management on their own fields during critical management times. One reason that poorer households seek work off their own farms is that they run out of their own food stocks from the previous year’s harvest before the next harvest is available. This means they need to buy a good bit of their food every year, and they need cash to do that. Local agricultural labour offers them the best means for earning cash without having to migrate away from the villages. Very poor households can deplete their stocks as early as December, but by February and March (the lean season) almost all households in the lower two wealth groups are buying food. Thus, the paid work for weeding helps provide needed cash, allowing them to bridge the gap until mid-March or April, when green harvests are available. Unfortunately, this is also a time of year when human diseases, and especially malaria, peaks. The most important livelihood capital that poorer households have is their own labour, so when an active labourer is sick in a poor household, income for this household is lost. Because the months of peak human illness coincide with one of the peak labour periods, it can be especially damaging for a productive household member to be sick at this time. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. People in this zone are not only busy with cropping activities, but also with livestock-related work. Milk sales peak from January through March (as pastures and water sources regenerate with the rains) and again from June through August (as livestock benefit from harvest residues). Milking animals is a time-consuming task, competing with the demands of weeding and harvesting in these months, but it brings with it the reward of extra nutrition for the household and cash income from milk that is sold. These same two periods (January through March and June through August) are when livestock sales are highest. In January through March, livestock are sold (by poorer households) in response to the need for cash to pay for food during the lean season, and (for middle and better off households) to cover the cost of hiring labour during the agricultural season. The June to August period of peak sales corresponds to the fact that livestock are in good condition at this time and garner high prices, and this is also when middle and better off households are putting aside cash for the coming agricultural season. In September, as the dry season deepens, livestock are taken to areas in Morogoro, where pasture and water sources are more reliable, returning to the villages in January or February. Those without livestock are busy with other activities in the dry season, especially collecting and selling firewood. Wild foods are also available at this time. Petty trade peaks in the harvest months, with some households transporting and re-selling local commodities, and others transporting goods into the zone for sale to local households that have new cash from crop sales. The festival season also takes place at this time, when the proceeds from the harvest are available to spend, and before the intensive work of the coming agricultural season has kicked into high gear. Wealth Breakdown The main determinants of wealth in this zone are, first, the amount of land a household cultivates and, second, the number of livestock - particularly oxen and cattle – it owns. In important ways these two things are inter- related: ownership of oxen allows people to increase the area they cultivate; and bigger herds generate more cash, which enables people hire labourers to carry out the many tasks associated with having more land. On the other side, the more land a household has under cultivation, the larger its harvests; and with more crop production, a household is able to generate proceeds from crop sales that can be invested in the health and growth of its livestock herd. Additional factors that determine how much land a household cultivates include the amount of land they own, the intra-household labour they have on hand, and their ability to hire additional help. Typical better off households own around 12-28 acres of land and cultivate 10-16 acres of these, using several teams of their own oxen for ploughing, or tractors in some cases. They also hire seasonal agricultural labourers. Better off households have more livestock than other households, usually keeping a herd of around 4-6 oxen, 25- 40 cattle, 15-35 goats and 0-15 sheep, alongside 15-25 chickens. Their household sizes are a little bigger than the other wealth groups. These households also own other assets, such as 1-3 ox-ploughs, an ox cart, a bicycle or two, Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 7 and possibly a motorcycle for boda boda. They typically own several cell phones, which are used to gather price and market information as well as to keep in touch with far-away relatives. Typical very poor households, on the other hand, own around 3-5 acres and cultivate only 2-3 acres, usually by hand, although they may exchange labour for access to plough oxen from better off households. They do not produce enough in any year to cover all of their food and cash needs. Very poor households have no livestock at all, except for 2-12 chickens. They have around 5-7 household members and face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of middle and better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone and a bicycle, but many do not even have these. Note: The percentage of household figures represent the mid-point of a range. Another distinction between the wealth groups is that middle and better off households grow grapes, whereas very poor and poor households do not, lacking the financial means to invest in the inputs and labour required to manage successful vineyards. In addition, the upper two wealth groups grow more sesame and sunflower, the other main cash crops, and they hire people to work for them, whereas the lower two wealth groups are the hired labourers. The distribution of wealth in this zone is weighted towards the bottom. Very poor (20-38%) and poor (25-35%) households together make up around 45-70% of households in the zone. Middle (20-35%) and better off (10-20%) households combined represent around 30-55% of the households. Sources of Food The graph below presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to harvest green maize and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an above-average year, with good rains, good crop yields, and low staple food prices. There are two main sources of food in this livelihood zone, and two supplemental sources: own crops and purchased food make up the majority of calories, while those in the upper two wealth groups also benefitted from their own milk and meat; and all households received a small amount of food aid. As you move up the wealth spectrum, reliance on own crops increases and the importance of the market decreases. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 8 Own crops covered 44-95% of minimum calorie needs in the reference year, increasing with wealth. In this lowland, semi-arid zone, maize is not the primary food crop; a more drought-tolerant crop – bulrush millet – is. Alongside maize and bulrush millet, households grow sorghum, groundnuts, Bambara nuts, and sunflower. Bulrush millet provides the most calories of any single crop, accounting for 20-44% of minimum food needs in the reference year. Maize, on the other hand, contributed 15-25% of minimum calories (including eaten green). In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. The other crops, which were mainly pulses, made up 8-14% of reference year food needs. Taking a closer look at production, typical very poor, poor, middle and better off households produced around 400 kg, 630 kg, 750 kg and 1,240 kg of bulrush millet, respectively, in the reference year; along with 150 kg, 400 kg, 500 kg and 840 kg of maize; 40 kg, 120 kg, 330 kg and 450 kg of sorghum; 80 kg, 140 kg, 210 kg and 300 kg of groundnuts; 50 kg, 100 kg, 130 kg and 150 kg of Bambara nuts; as well as 65 kg, 80 kg, 320 kg and 500 kg of sesame, all respectively. In the reference year, households sold a sizeable portion of all of these crops, but if they had consumed, rather than sold, all of their maize, sorghum, groundnuts, bulrush millet and Bambara nuts, all but the very poor group would have been able to cover their minimum calorie requirements. In fact, in pure calorie terms, these crops could be converted into 60%, 108%, 150% and 205% of minimum calorie needs for very poor, poor, middle and better off households, respectively. The point here is not that households should not have sold their crops: crop sales offer a necessary means for generating the cash required to cover a range of essential goods and services. But it is important to note that households in the top two categories are able to produce substantially more than those in the bottom two categories, and this has implications for their ability to survive in bad years. Even if half of their crop production is wiped out in a bad year, better off households still have enough to cover their minimum needs, whereas very poor households would be left with a deficit of over 70% of minimum calories. It also explains differences in what these households purchased in the reference year, as discussed below. Purchased food accounts for most of the remaining calories consumed by all households in the reference year, covering 20-52% of minimum calorie requirements, decreasing with wealth. The poorer two wealth groups purchased mostly maize grain and bulrush millet, the cheapest staples. Purchased maize grain and bulrush millet together accounted for around 44% of minimum calories (for typical very poor households) and 32% of minimum calories (for poor households) in the reference year, or over three-quarters of their purchased calories. Middle households, on the other hand, purchased only around 4% of their minimum calories in the form of maize grain and no millet; and better off households purchased no maize or millet at all. For middle and better off households, the ‘purchase’ component was comprised of more high-value, preferred foods, such as wheat flour, rice, beans, sugar, meat, oil and dried fish. Thus, almost the entire value of their purchased calories came from high-value preferred foods. By comparison, very poor and poor households purchased only around 8% of their minimum calories in the form of these higher-value food items, and did not buy meat or wheat flour in meaningful amounts. The final two sources of food are own milk/meat and food aid. Only middle and better off households obtain significant quantities of milk and meat from their livestock. In the reference year a typical middle household had around 4 cows milking, and better off households had around 6 cows milking. Milk yields vary over the year, reaching their peak of around 1.75 litres per day in the rainy season, and dropping off to around 0.5 litres per day in the dry season. Given this variation and the period of time that cows here continue to lactate, households obtained a total of around 1,085-1,630 litres over the year. Approximately 45-50% of the milk got sold, leaving middle and poor households with enough to cover 6-8% of their minimum calorie needs in the reference year. An Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 9 additional 3% or so of minimum calories accrued to better off households in the form of meat from slaughtered cattle and goats. While only the upper two wealth groups benefitted from milk (and meat), all households who sent their children to school received some help in the form of school feeding, shown as ‘food aid’ on the graph. Most households have at least 1 child attending school, and this household member was fed one meal a day during the school term, helping to add to the required calories for the household in the reference year. Sources of Cash Income The graphs to the right present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. It is immediately clear that households in the upper two wealth groups have a very different income profile from those in the bottom two wealth groups. Although ‘grapes’ is in the title of this zone, the income from this source only benefits middle and better off households directly. The land, labour and pesticides required to grow a successful crop of grapes puts this crop out of reach for very poor and poor households. The other major difference is that middle and better off households round out their cash income with livestock- related income, relying on milk sales and live animal sales to meet almost all of the rest of their needs. Poorer households, on the other hand, do not have enough livestock to make this possible, and rely instead on casual labour and self- employment. Neither of these provide guaranteed income in any year, and both sources The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 900,000 – 1,400,000 1,400,000 – 2,500,000 2,500,000 – 5,500,000 5,500,000 – 7,500,000 4 The average exchange rate from April 2014 - March 2015 was 1 USD = 1,800 TZS Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 10 are linked to the surpluses held by those at the upper end of the wealth spectrum. Poor households also depend to a small extent on petty trade, as do middle and better off households, but the nature of this trade is different, as discussed below. In the reference year, the combined value of crop sales accounted for 19%, 27%, 50% and 51% of the annual cash income of typical very poor, poor, middle and better off households, respectively. Maize, sorghum, groundnuts, Bambara nuts, Bulrush millet, sunflower, and sesame are all sold, as well as grapes, the main cash crop. Sesame, Bambara nuts and groundnuts are the highest value crops, sold at around 850-1,500 TZS/kg in the reference year. The lower end of the range corresponds to the price that poorer households got for their groundnuts. Middle and better off households are able to get a higher price for their groundnuts (1,200 TZS/kg) because the quality of their produce is higher and they sell at more advantageous times of the year and/or to markets where they get a better price. The upper end of the range applies to sesame. Either way, these prices compare favourably with the cereal crops, which are valued at around 400-500 TZS/kg. Therefore, even small amounts of pulses and sesame can earn households a meaningful amount of cash. For example, in the reference year, typical middle and better off households sold 300-450 kg of sesame, 150-185 kg of groundnuts and 130-150 kg of Bambara nuts. The combined total for these three crops represented around 16-18% of annual cash income for the upper wealth groups. The poorer two wealth groups only sold 50-90 kg of groundnuts, 60-70 kg of sesame and 0-40 kg of Bambara nuts but still earned around 132,500-221,500 TZS, or approximately 10-13% of their annual cash from these relatively small quantities. Cereal crop sales (maize, sorghum and bulrush millet) contributed around 5-11% of annual cash income for all wealth groups. Sunflowers only earned households 2-4% of their annual cash. The real cash earner was grapes, but these were only grown by the top two wealth groups. Grape sales alone provided middle and better off households with 20-25% of their annual cash income. Better off households earned from grapes alone more than very poor households earned from all of the cash sources combined in the reference year. As a whole, better off households generated 13 times more from crop sales than very poor households, despite only having, on average, 5 times more land under cultivation. This is explained, at least in part, by the capacity of better off households to buy sufficient inputs and to apply timely management practices. Poorer households cannot afford to buy many inputs, and their labour pool is split during key times of the year, partly on their own farms and partly working for others, but never fully devoted to their own fields. The resulting difference in yields is apparent in these figures. For middle and better off households, livestock sales and livestock product sales (including milk, meat and eggs) are the next most important income earner, making up 40-45% of annual cash income; on the other hand, very poor and poor households only derived 3-14% of their annual cash from these sources. As discussed in the ‘Sources of Food’ section, middle and better off households both own milking cows. Around half of the milk produced in the reference year was sold. In addition, better off households sell eggs and meat. The total income from livestock product sales accounted for 10-15% of cash income for the two upper wealth groups. Poor households also sold a very small amount of milk, but this resulted in an insignificant amount of cash. More important than the livestock product sales were sales of live animals, which made up 25-35% of cash income for middle and better off households, and 3-13% of annual cash for very poor and poor households. Cattle, goats, chickens, and a few sheep, are sold. Cattle bring in the most cash per animal (at around 95,000-1,320,000 per head); in contrast goats are sold for around 40,000 TZS and chickens for 6,500-8,000. Better off households typically sold around 3 cattle, 6 goats, 1 sheep and 7 chickens in the reference year; very poor households only sold around 6 chickens. The other two wealth groups fell in between these two extremes. Casual labour is the most important source of income for very poor and poor households. In the reference year, this stream of earnings accounted for 60% of a typical very poor household’s annual cash income and 40-45% of poor households’ cash income. Middle and better off households cultivate more land than they can manage with their own household labour, so they hire members of these poorer households to help throughout the agricultural season. People are hired to prepare land, to plough, to plant, weed, harvest and thresh. The majority of the cash income is associated with pre-harvest tasks, which account for 60-70% of the agricultural labour income. It is important to keep in mind that this income, as critical as it is in an average year, shrinks in a bad year because Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 11 losses in production translate into losses in the demand for labour, especially for harvest and threshing labour. This leaves poorer households struggling to find ways to fill this large gap. The last source of cash income for very poor households is self-employment, which means, primarily firewood and charcoal sales. Both women and men from the poorer wealth groups engage in this activity, with women focusing more on firewood, and men focusing on charcoal burning and sale. July to October, the dry season, is when these sales are concentrated. The environmental damage that ensues from this cash income is of concern, especially as the population grows and especially given the large proportion of the population already depending on this income. Self-employment made up almost a fifth of the cash income of very poor households in the reference year. Poor, middle and better off households also engage in ‘petty trade’ to earn extra cash. This may take the form of prepared food sales (for poorer households), or sales of household items, which middle and better off households are able to buy in bulk; they set up kiosks in the villages and generate extra income through this business. Some also make money from boda boda, or motorcycle hire, which can be used to transport goods and people, or ox plough and/or ox cart hire. Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other areas of the country, households need to spend cash on a range of goods and services throughout the year, including: staple and non-staple food, household items, productive inputs, social services, like schooling and health, clothing and other non- The graph provides a breakdown of total annual cash expenditure according to category of expenditure essential items, such as tobacco, cosmetics and festivals. As shown in the graph to the right, two common trends appear in this zone, mirroring the findings in other rural areas: first, the poorer you are, the more cash you have to spend on securing basic staple foods; second, the richer you are, the more money you need to spend on productive inputs. The fact that typical households here need to buy water sets this zone apart from many other rural areas of the country; and the relatively large amount of cash in the ‘other’ category is also notable. All wealth groups spend some of their available cash on staple foods, which includes (in this case) maize grain, millet, wheat and rice. In both absolute and relative terms, very poor households spent more than the other wealth groups on staple foods. In the reference year, very poor and poor households spent around 16-26% of their annual cash on staple foods; and middle and better off households spent only 3-4%. The make-up of the staple food basket is not the same for all wealth groups. Typical very poor and poor households spent a total of 265,000-340,000 TZS on staple food, and 220,000-305,000 TZS (or 80-90%) of this was on maize grain and millet, the cheapest staples. Middle and better off households spent around 160,000-180,000 TZS, respectively, on staple foods, but only middle households spent a small amount on maize grain and neither bought millet at all. They spent money on rice, first, which is a preferred food, and better off households also bought a small amount of wheat flour. Thus, middle and better off households did not need to buy staple grains to fill a calorie gap; but rather to fill a preference gap. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 12 Although middle and better off households spent much less in both absolute and relative terms on staple food, on non-staple foods, they spent 2 ½ to 3 ½ times more in absolute terms than very poor households. The non-staple food category included beans, sugar, meat, oil, dried fish, and vegetables. Of these, the lower two groups spent the most on beans, dried fish, and oil, supplementing their heavily grain-based diet with proteins and fats. They spent the least on vegetables. Middle and better off households spent the most on meat and sugar. In the reference year, the proportion of cash income spent on non-staple foods was around 16% for very poor and poor households, and around 11-12% for middle and better off households. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 6-8% (for very poor and poor households) and 13-15% (for middle and better off households). Thus, middle and better off households are able to buy a more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less than the other two wealth groups. In the reference year, middle and better off households both spent the largest portion of their annual cash income on productive inputs, as represented by the dark blue bar in the graph. In proportional terms, their spending on productive inputs (37-41% of annual expenditure) is larger than any other wealth group spends on any of the other categories. The following are included in this category: livestock drugs, seeds/tools, pesticides/fertiliser, livestock purchases, labour hire, business investment, phone credit and house repairs. Within this set, very poor households spent money only on seeds/tools and phone credit, with the most spent on phone credit. Poor households, in addition to these two categories, spent on money on livestock drugs. Middle and better off households spent money on all items within the category (with the exception of business investment, which only applies to better off households). The majority of their inputs budget was devoted to labour hire (47-57% of their inputs budget), followed by livestock purchase (15-19% of their inputs budget). Collectively, seeds, tools, pesticides and fertilisers comprised only around 11-12% of their inputs budget. In absolute terms, better off households spent 44 times more on productive inputs than very poor households, 17 times more than poor households, and 1 ½ times more than middle households. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services, firewood and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor and poor households spent the most money on grinding, which took up around a quarter to a third of this budget, followed by payment for lighting. Middle and better off households spent the most on utensils, followed by lighting and soap. All households spent the least on salt and tea. On an annual basis, spending on basic household goods made up 7-13% of annual expenditure. Somewhat unusually, households in this zone also needed to spend money regularly on water, especially during the dry season, highlighting the particularly poor access people have to fresh, potable water. ‘Social services’, shown in orange on the graph, includes schooling and health costs. In the reference year, households spent 8-11% of their annual cash on these services. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, better off households spent around 25% more than middle households and around 2-3 times more than poor and very poor households on schooling. In addition, better off households spent up to 11 times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Spending on clothes and other miscellaneous items are the last two categories included here. Spending on clothes accounted for 3-5% of the annual budget for all households. The ‘other’ category includes things like cosmetics, hair, beer, tobacco, cigarettes, community obligations, transportation and festivals; in the reference year households devoted 24-26% of their cash to these items. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was an above average year, even the very poor wealth group had more in this budget than it would in a bad year. In fact, this discretionary Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 13 budget, in relative terms, is larger than in most other zones, which is related to the fact that in many other zones the reference year was average, not above average. Hazards Three hazards affect this zone on a regular basis. The first is poor rainfall distribution. All the food crops in this zone are rain-fed; only grapes benefit from irrigation. Crops require an even, reliable distribution of rain to perform well. When too much or not enough rain falls during critical development periods, especially the vegetative and reproductive stages, yields can drop dramatically. Thus even if overall seasonal precipitation is normal, poor distribution can cause crop losses of 50-60%. The second chronic hazard is crop and livestock pests and diseases. Quelea quelea birds are especially problematic, damaging both the sorghum and bulrush millet crops. Army worm, which affects all cereal crops, and fungal diseases, which affect grapes, also reduce yields on a regular basis. The most commonly-occurring livestock diseases are contagious bovine pleuropneumonia (CBPP) for cattle, caprine pleuropneumonia (CCPP) for goats, and Foot and Mouth Disease (FMD). Newcastle Disease is also common and can wipe out an entire flock of chicken. Livestock diseases reduce the value of animals, lowering income levels, while at the same time increasing expenditure requirements related to livestock drugs. In the worst case, animals die, reducing the productive asset holdings of a household. The third chronic hazard is human diseases, especially malaria and typhoid fever. Because household labour is so critical to income generation, especially for poorer households, having a household member sick at a critical time of year can translate into significant drops in income, while at the same time increasing the medical expenditure requirements. The main periodic hazards are drought, which can seriously damage crop production once every three years. Droughts result in a series of inter-related shocks, such as rapid increases in staple food prices, declines in livestock production, reduced labour income and reduced returns on self-employment. Floods occur once every three years as well. Floods can damage standing crops and wash away roads, making it difficult for people to reach markets, and usually causing a spike in staple food prices. Less of a hazard, and more of a structural constraint, poor marketing infrastructure means that households are selling their agricultural commodities are prices that barely cover their production costs. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple instead, or cutting down on festivals, tobacco and beer. Very poor and poor households try to increase cash income through finding more agricultural labour and casual employment, either locally or migrating outside the zone. In particular, people may go to Kongwa in Dodoma, Kiteto in Manyara, Mvomero and Kilosa districts in Morogoro, and Kilindi in Tanga. The expandability of this option is limited in bad years because the labour market gets saturated as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. This problem is somewhat mitigated if the bad year is localised. All households also try to increase their self-employment income. Poorer households try to increase cash income from charcoal and firewood sales. However, as more and more households try to do the same thing in a bad year, the value of each bundle of wood or charcoal decreases, which makes it difficult to expand this source of income substantially. The environmental damage that accumulates from this pursuit should be a cause for serious concern. Middle and better off households try to increase income from petty trade. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 14 Middle and better off households also try to increase their livestock sales. However, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Dodoma Lowlands Cereals, Oilseeds & Grapes Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Sorghum – amount produced Groundnuts – amount produced Sunflower – amount produced Sesame – amount produced Bulrush millet – amount produced Bambara nut – amount produced Grapes – amount produced Maize– producer price Sorghum – producer price Groundnuts – producer price Sunflower – producer price Sesame – producer price Bulrush millet – producer price Bambara nut – producer price Grapes – producer price Livestock production Cows’ milk – yields Meat – amount sold Cattle – herd size Goats – herd size Chickens - numbers Cows’ milk – producer price Meat – producer price Cattle – producer price Goats – producer price Chickens – producer price Other food and cash income Agricultural labour (land preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Bricks – numbers produced Firewood/charcoal – amount sold Petty trade – volume of trade Agricultural wage rates (land preparation, planting, weeding) Agricultural labour rates (harvesting) Bricks – price per brick Firewood/charcoal – price per bundle Petty trade – returns on trade Expenditure Maize grain – consumer price Rice – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. Very poor/poor households Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines Improved maintenance of existing road networks Timely and affordable provision of crop and livestock inputs Access to safe and sufficient water at all times of year Provision of school buildings, qualified teachers and appropriate teaching materials for all children Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 15 Development of fair, standardised and efficient agricultural markets Construction of dam for irrigation Middle/better off households Timely and affordable provision of crop and livestock inputs Development of livestock health infrastructure, including affordable veterinary services and dip tanks, etc. Access to safe and sufficient water at all times of year Provision of school buildings, qualified teachers and appropriate teaching materials for all children Development of fair, standardised and efficient agricultural markets Provision of electricity at village level Construction of dam for irrigation"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":186,"cells":{"data":{"kind":"string","value":"# Extracted Content"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":187,"cells":{"data":{"kind":"string","value":"# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA WIZARA YA KILIMO Simu ya Upepo: “KILIMO” Dodoma Idara ya Utawala, Simu: +255 (026) 2321407 Mji wa Serikali - Mtumba, Nukushi: +255 (026) 2320037 S.L.P. 2182, Barua Pepe: ps@kilimo.go.tz DODOMA. Tovuti: www.kilimo.go.tz TAARIFA KWA VYOMBO VYA HABARI SERIKALI YAPANGA KURASIMISHA BIASHARA YA MAZAO YA KILIMO NCHINI Dodoma, 14 Julai 2023 Waziri wa Kilimo, Mhe. Hussein Bashe (Mb) amefanya kikao cha pamoja na wafanyabiashara na wadau wanaouza mazao ya kilimo ndani na nje ya nchi kujadili mwenendo wa usafirishaji wa mazao, jitihada za Serikali katika kuondoa vikwazo vya biashara na urasimishaji wa biashara ya mazao ya kilimo. Waziri Bashe ameeleza kuwa takwimu zinaonesha mchango wa kilimo katika uchumi ni asilimia 26.1 ambapo mauzo ya mazao ya kilimo nje ya nchi yameongezeka kutoka Dola za Marekani milioni 994.5 mwaka 2021 hadi Dola za Marekani bilioni 1.38 kufikia Aprili 2023. Serikali imepanga kurasimisha biashara ya mazao ya kilimo ambapo malengo mahususi ya urasimishaji huo ni kuongeza thamani ya mazao ya kilimo ili kumlinda mkulima na mfanyabiashara wa ndani dhidi ya usumbufu na utapeli unaotokea katika biashara ya mazao ya kilimo. Aidha, Mhe. Bashe amesema kuwa Tanzania ina hali nzuri ya chakula kutokana na mavuno yaliyopatikana na kupelekea utoshelevu wa chakula kwa asilimia 114 . Vile vile, aliwakumbusha kauli ya Mhe. Dkt. Samia Suluhu Hassan, Rais wa Jamhuri ya Muungano wa Tanzania umuhimu wa nchi kulinda akiba ya chakula na kuwahasa wakulima kuuza ziada ya chakula popote pale duniani kwa kufuata utaratibu uliowekwa na Serikali. Mhe. Bashe amesema kuwa Serikali inawezesha NFRA kuhifadhi tani 3,000,000 ifikapo mwaka 2030 ikiwa sehemu ya kuimarisha usalama wa chakula na lishe. Hatua nyingine ni kuiongezea Wakala wa Taifa wa Uhifadhi wa Chakula (National Food Reserve Agency) uwezo wa kununua mazao ya wakulima ili kuongeza hifadhi hadi kufikia tani 500,000 na kwa msimu huu Mhe. Bashe ameagiza Wakala wa Taifa wa Hifadhi ya Chakula kununua mahindi kwa shilingi 1,000 kwa kilo kwa mkulima yeyote anayetaka kuwauzia NFRA ofisi za Dodoma. Kuhusu jitihada za kurahisisha usajili wa ghala za Sekta ya Umma, Sekta Binafsi na Vyama vya Ushirika, Serikali imebuni mfumo wa kidijitali unaoitwa Crop Stock Dynamics System. Vile vile, Mhe. Bashe amewaahidi wafanyabiashara kuwa ataimarisha mfumo wa kidigitali wa upatikanaji wa vibali kwa njia ya mtandao ili wafanyabiashara wapate vibali kwa urahisi. Waziri Bashe ameongeza kuwa Tanzania imekuwa katika maandalizi ya kuwa mwenyeji wa Mkutano wa Mifumo ya Chakula Afrika - 2023 (Africa’s Food Systems Forum), ambao ni sehemu ya hatua za kuimarisha usalama wa chakula. Mkutano huo umepangwa kufanyika tarehe 5 hadi 8 Septemba 2023 na utahusisha wadau mbalimbali wa kilimo na biashara kutoka ndani ya nchi, wadau kutoka Jumuiya ya Maendeleo Kusini mwa Afrika (SADC) na Jumuiya ya Afrika Mashariki (EAC). Imetolewa na: Kitengo cha Mawasiliano Serikalini"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":188,"cells":{"data":{"kind":"string","value":"# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO YA CHAKULA 21 - 25 Juni, 2021 Jedwali1: Wastani wa bei za jumla kitaifa (TZS/ Kilo100) Jedwali 2: Wastani wa bei za jumla za mahindi kwa wiki (TZS/kilo 100) Mazao Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Mahindi 43,100 42,122 43,000 ▲2 Mchele 135,240 133,500 136,260 ▲2 Mtama 97,070 98,469 94,500 ▼4 Maharage 175,700 173,684 174,150 ►0 Viazi mviringo 69,500 70.647 67,800 ▼4 Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 44,000 44,000 46,500 ▲6 Dar - Kinondoni 42,500 42,500 42,500 ►0 Dodoma (Majengo) 50,000 53,500 51,500 ▼4 Bukoba 47,500 46,500 46,500 ►0 Babati 39,000 40,500 40,500 ►0 Musoma 52,500 52,500 52,500 ►0 Morogoro 46,297 46,297 46,297 ►0 Mpanda 30,000 30,000 30,000 ►0 Mtwara DC 40,000 40,000 40,000 ►0 Mwanza 50,000 50,000 56,500 ▲13 Sumbawanga 33,000 31,500 31,500 ►0 Shinyanga 45,000 42,500 45,000 ▲6 Songea 45,000 35,000 36,500 ▲4 Tabora 36,000 36,000 36,000 ►0 Tanga/Mgandini 43,518 43,518 48,570 ▲2 Ujumbe Mkuu ✓ Wastani wa bei kitaifa umebadilika kwa viwango tofauti tofauti. Bei za mahindi na mchele zimeongezeka kwa asilimia 2, bei za maharage hazijabadilika, wakati bei mtama na viazi mviringo zimepungua kwa asilimia 4. ✓ Mboga na Matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za nanasi, na vitunguu zimeongezeka kwa asilimia 1, wakati bei za tikiti maji, pilipili hoho na tango, zimepungua kwa asilimia 5, 3 na 2 mtawalia. ✓ Tumbaku: Hadi kufikia tarehe 20 Juni, 2021 kiasi cha tumbaku kilichouzwa ni Kilo 29,122,687 zenye thamani ya Dola za Kimarekeni za 44,633,382. ✓ Kahawa: Hadi kufikia tarehe 27 Mei, 2021 kahawa iliyouzwa kwa msimu wa mauzo 2020/21 ni tani 70,043 zenye thamani ya Dola za Kimarekani milioni 137.6. ✓ Ufuta: Hadi kufikia tarehe 24 Juni, 2021 ufuta uliouzwa kwa msimu wa mauzo 2021/22 ni Kilo 19,741,410 zenye thamani ya shilingi 45,632,860,313. 2 Jedwali 3. Wastani wa bei za jumla za mchele kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 152,500 152,500 152,500 ►0 Dar – Kinondoni 150,000 150,000 140,000 ▼7 Dar – Ilala 170,000 170,000 170,000 ►0 D'Salaam – Tandika 150,000 150,000 150,000 ►0 Dodoma (Majengo) 162,500 160,000 165,000 ▲3 Bukoba 129,000 129,000 129,000 ►0 Babati 150,000 145,000 145,000 ►0 Morogoro 125,000 125,000 125,000 ►0 Mwanza 132,500 132,500 180,000 ▲36 Sumbawanga 100,000 100,000 105,000 ▲5 Shinyanga 105,000 105,000 105,000 ►0 Songea 165,000 170,000 175,000 ▲3 Tabora 110,000 110,000 110,000 ►0 Tanga/Mgadini 135,000 135,000 135,000 ►0 Jedwali 4. Wastani wa bei za jumla za mtama kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 72,500 72,500 72,500 ►0 Dar - Kinondoni 90,000 90,000 70,000 ▼22 Dar - Ilala 85,000 85,000 85,000 ►0 D'Salaam – Tandika 95,000 95,000 95,000 ►0 Dodoma (Majengo) 51,000 65,500 65,000 ▼1 Bukoba 135,000 135,000 135,000 ►0 Babati 70,000 70,000 70,000 ►0 Morogoro 150,000 150,000 150,000 ►0 Mpanda 82,500 82,500 82,500 ►0 Mtwara DC 95,000 95,000 95,000 ►0 Mwanza 165,000 165,000 165,000 ►0 Shinyanga 82,500 82,500 65,000 ▼21 Tabora 145,000 145,000 145,000 ►0 Tanga/Mgandini 90,000 90,000 85,000 ▼4 Jedwali 5. Wastani wa bei za jumla za maharage kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07- 11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 152,500 155,000 152,500 ▼2 Dar – Kinondoni 210,000 210,000 210,000 ►0 Dar – Ilala 210,000 210,000 210,000 ►0 D'Salaam – Tandika 205,000 205,000 205,000 ►0 Dodoma (Majengo) 195,000 210,000 211,500 ▲1 Bukoba 132,500 132,500 130,000 ▼2 Babati 165,000 165,000 165,000 ►0 Morogoro 187,500 187,500 187,500 ►0 Mpanda 175,000 175,000 175,000 ►0 Mtwara DC 177,500 177,500 175,000 ▼1 Sumbawanga 97,500 97,500 132,500 ▲36 Shinyanga 175,000 175,000 175,000 ►0 Songea 180,000 170,000 190,000 ▲12 Tabora 185,000 185,000 185,000 ►0 Tanga/Mgandini 185,000 185,000 175,000 ▼5 Jedwali 6. Wastani wa bei za jumla za viazi mviringo kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 75,000 75,000 75,000 ►0 Dar - Kinondoni 52,000 52,500 55,000 ▲5 Dar – Ilala 64,800 64,800 64,800 ►0 D'Salaam – Tandika 72,500 75,000 75,000 ►0 Dodoma (Majengo) 62,000 63,000 63,000 ►0 Babati 65,000 60,000 52,500 ▼13 Musoma 90,000 90,000 90,000 ►0 Morogoro 75,500 75,500 75,500 ►0 Mtwara DC 57,500 57,500 57,500 ►0 Mwanza 75,000 75,000 75,000 ►0 Sumbawanga 67,500 67,500 67,500 ►0 Songea 72,500 77,500 77,500 ►0 Tabora 72,500 72,500 67,500 ▼7 Tanga/Mgandini 59,000 56,500 56,500 ►0 3 Jedwali 7: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Uganda (bei za jumla) 1,824 1,955 489 512 Uganda (bei za rejareja) 1,955 2,281 847 912 Chanzo: https://farmgainafrica.org/ Tarehe 25 Juni, 2021 Jedwali 8A: Wastani wa bei za mazao ya horticulture kwa wiki ya tarehe (6-12) Mei, 2021 Zao Wiki ya nyuma (23-28 Aprili, 2021) Wiki iliyopita (30 Apr- 5 Mei, 2021) Wiki hii (6-12 Mei, 2021) Badiliko wiki iliyopita na wiki hii (%) Nyanya (40 Kg kreti) 53,475 45,913 45,437 ▼1 Vitunguu (100 Kg Gunia) 153,200 176,714 177,902 ▲1 Tikiti maji (Kilo) 539 551 523 ▼5 Nanasi (Kilo) 729 762 770 ▲1 Pilipili hoho (50 Kg Gunia) 53,770 56,945 55,070 ▼3 Tango (100 Kg Gunia) 72,806 73,513 72,015 ▼2 Chanzo: TAHA, 2021 Jedwali 8B: Bei za mazao ya Horticulture katika masoko mbalimbali kwa wiki la tarehe (6-12) Mei, 2021 Soko Nyanya (40kg kreti) Vitunguu (100 Kg Gunia) Tikiti maji (Kilo) Nanasi (Kilo) Pilipili hoho (50 Kg Gunia) Tango (100 Kg Gunia) Nairobi 46,933 161,333 777 660 70,400 99,000 Mombasa 50,600 177,833 660 66,000 66,000 Zanzibar 70,000 250,000 767 800 108,333 73,333 Dar es salaam 45,000 190,000 350 400 91,667 90,000 Morogoro 38,667 168,333 417 1,000 41,667 69,667 Dodoma 48,333 150,000 317 533 38,889 66,667 Shinyanga 35,000 126,389 500 500 29,333 40,000 Mwanza 38,333 155,556 467 1,067 33,333 47,333 Arusha 40,000 220,000 550 517 50,833 70,000 Tanga 43,000 132,000 671 1,000 45,500 77,000 Lindi 45,000 210,000 500 567 40,000 56,667 Mtwara 50,000 208,333 500 600 75,000 75,000 Mbeya 46,000 147,500 690 1,500 49,333 125,000 Chanzo: TAHA, 2021 4 Jedwali 9A: Mauzo ya tumbaku katika msimu wa 2021/2022 hadi kufikia tarehe 20 Juni, 2021 kwa kampuni AINA YA TUMBAKU KAMPUNI KILO ZA MKATABA MASOKO YALIYOTHAMINISHWA MPAKA SASA (CUMMULATIVE) BELO KG THAMANI(USD) BEI YA WASITANI (USD/KG) (USD) VFC Alliance One Tobacco Tanzania Ltd 20,040,000 269,378 12,732,539 18,868,592 1.48 JTI Leaf Services Ltd 14,460,000 153,195 7,433,245 12,722,387 1.71 Premium Active Tanzania Ltd 16,000,000 83,479 4,076,237 6,149,241 1.51 Pachtec Company Ltd 4,461,838 43,888 2,024,662 2,832,423 1.40 Mo Green International Company Limited 2,800,000 5,377 255,084 359,362 1.41 Naile Leaf (T) Co. Ltd 2,535,000 27,295 1,230,743 1,869,755 1.52 Magefa Growers Ltd 4,400,000 20,198 927,521 1,218,853 1.31 Jespan Company Ltd 760,000 6,990 357,097 484,028 1.36 ENV Services Ltd 800,000 1,743 85,560 128,742 1.50 SUB TOTAL VFC 68,071,838 611,543 29,122,687 44,633,382 1.53 DFC Premium Active Tanzania Ltd 500,000 - - - GRAND TOTAL 68,571,838 611,543 29,122,687 44,633,382 1.53 Jedwali 9B: Mauzo ya tumbaku (kimkoa) katika msimu wa masoko 2021/2022 hadi kufikia tarehe 20 Juni, 2021 Mkoa Kilo za Mkataba Kiasi cha tumbaku kilichonunuliwa Belo Kilo Katavi 7,350,000 51,767 2,434,695 Mbeya 10,280,000 32,418 1,596,321 Songwe 670,000 4,108 209,278 Kigoma 4,705,000 46,454 2,225,923 Tabora 32,546,838 380,284 17,980,725 Shinyanga 9,930,000 83,260 3,981,547 Geita 1,070,000 10,858 546,263 Kagera 70,000 1,180 58,557 Iringa 200,000 1,214 89,377 Singida 1,250,000 Jumla ya VFC 68,071,838 611,543 29,122,687 Ruvuma (DFC) 500,000 JUMLA KUU (DFC+VFC) 68,571,838 611,543 29,122,687 5 Jedwali 10A: Mauzo ya kahawa kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 27 Mei, 2021 Mkoa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 18,900,851 51,340,876 9,449,747 30,391,503.67 54,881 132,565.16 28,405,409 81,864,945.03 Arabika ngumu 145,527 291,691 2,143,620 3,453,241.00 16,620 15,972.00 2,305,767 3,760,903.98 Robusta 1,524,910 2,539,431 37,431,848 48,952,780.96 375,192 441,839.32 39,331,950 51,934,051.20 Jumla 20,571,288 54,171,998 49,025,215 82,797,525.63 446,623 590,376.48 70,043,126 137,559,900.21 Chanzo: Bodi ya Kahawa, 2021 Jedwali 10B: Mauzo ya kahawa (kimkoa) kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 27 Mei, 2021 Mkoa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD KAGERA 1,631,070 2,739,386.60 39,426,488 52,098,305.96 391,812 457,811.32 41,449,370 55,295,503.88 SONGWE 6,859,673 18,411,063.41 2,710,804 7,948,200.71 - - 9,570,477 26,359,264.13 RUVUMA 8,688,220 23,073,124.19 3,480,035 10,028,372.23 10,076 28,618.80 12,178,331 33,130,115.22 MBEYA 1,754,341 5,219,692.24 576,889 1,749,402.94 29,963 74,742.56 2,361,193 7,043,837.75 KILIMANJARO 573,990 1,749,557.79 1,030,571 3,854,232.40 4,515 10,853.70 1,609,076 5,614,643.88 KIGOMA 476,042 1,288,566.78 230,143 661,727.00 - - 706,185 1,950,293.78 TANGA 122,241 317,481.42 - - - - 122,241 317,481.42 ARUSHA 361,727 1,108,443.28 1,355,255 5,956,817.25 10,257 18,350.10 1,727,239 7,083,610.63 IRINGA 21,210 50,225.82 - - - - 21,210 50,225.82 MANYARA 1,936 5,950.05 - - - - 1,936 5,950.05 MOROGORO 314 1,030.39 - - - - 314 1,030.39 MARA 39,367 91,735.30 147,060 298,116.00 - - 186,427 389,851.30 NJOMBE 41,157 115,740.83 67,970 202,351.13 - - 109,127 318,091.96 TOTAL 20,571,288 54,171,998.10 49,025,215 82,797,525.63 446,623 590,376.48 70,043,126 137,559,900.21 Chanzo: Bodi ya Kahawa, 2021 6 Jedwali 11: Mauzo ya ufuta kwa msimu wa 2021/22 hadi kufikia tarehe 24 Juni, 2021 NA HALMASHAURI MAKISIO KIASI (KG) THAMANI (TZS) 1 MTAMA (LINDI VIJIJINI) 8,000,000 4,305,358 9,912,231,853.00 2 LINDI MC 3,500,000 3,169,073 7,320,953,838.00 3 KILWA 19,000,000 6,743,479 15,617,491,613.00 4 NACHINGWEA 12,000,000 2,152,176 4,982,211,930.00 5 RUANGWA 13,000,000 2,289,082 5,293,607,396.00 6 LIWALE 13,000,000 1,082,242 2,506,363,683.00 JUMLA 68,500,000 19,741,410 45,632,860,313.00 Chanzo: Mrajisi Lindi Jedwali 12: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati mzuri wa kuvuna Wakati mbaya wa kuvuna Muda sahihi wa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA 2021 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ Bei elekezi za mbolea ni za rejareja na zinatofautiana kwenye mikoa kulingana na umbali. ✓ N/A bei haikupatikana ✓ Chanzo cha takwimu: Wizara ya Kilimo/Wizara ya Viwanda na Biashara/TAHA. Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo,"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":189,"cells":{"data":{"kind":"string","value":"# Extracted Content 1 05 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO YA CHAKULA 26-30 Oktoba 2020 Jedwali1: Wastani wa bei za jumla kitaifa (TZS/ Kilo100) Jedwali 2. Wastani wa bei za jumla za mahindi kwa wiki (TZS/Kilo 100) Mazao Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Mahindi 58,000 58,000 57,000 ▼2 Mchele 139,600 141,500 142,300 ▲1 Maharage 202,000 202,900 197,600 ▼3 Mtama 89,000 86,200 95,100 ▲10 Viazi mviringo 75,500 71,000 70,100 ▼1 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26- 30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha -Mjini 51,500 51,500 51,000 ▼1 Bukoba 62,500 63,500 62,500 ▼2 Dar es Salaam - Ilala 60,500 62,000 57,000 ▼8 Dar es Salaam- Kinondoni 72,500 72,500 57,000 ▼21 Dodoma Majengo 62,000 61,500 64,000 ▲4 Dodoma-Kibaigwa 61,000 53,500 56,500 ▲6 Mpanda 51,000 52,500 52,500 ►0 Musoma 60,000 67,500 67,500 ►0 Babati 64,000 64,000 64,000 ►0 Morogoro 55,500 55,500 57,800 ▲4 Mtwara DC 58,000 57,000 57,000 ►0 Tabora 51,500 51,000 51,500 ►0 Tanga/Mgandini 62,500 60,700 60,600 ▼0 Ujumbe Mkuu ✓ Wastani wa bei za mazao makuu ya chakula kitaifa zimeongezeka na kupungua kwa viwango tofauti ambapo bei za mtama zimeongezeka kwa asilimia 10 na mchele kwa asilimia 1 na bei za maharage, mahindi, na viazi mviringo zimepungua kwa asilimia 3, 2 na 1 mtawalia. ✓ Mahindi: Bei zimeonekana kuwa za juu zaidi katika soko la Musoma, Dodoma-majengo na Babati. Bei za chini zimeonekana katika soko la Arusha Mjini, Tabora na Mpanda. ✓ Mchele: Bei zimeonekana kuwa za juu zaidi katika soko la Dar es Salaam-Ilala, Dar es Salaam Kinondoni na soko la Babati ambapo bei ya chini imeonekana katika soko la Mpanda na soko la Musoma. ✓ Maharage Bei zimeonekana kuwa za juu zaidi katika soko la Mpanda na soko la Tabora ambapo bei za chini zimeonekana katika soko la Morogoro na Iringa Mjini. ✓ Korosho: Kwa msimu wa 2020/21 wa mauzo, mahitaji mpaka sasa yamezidi korosho iliyopo kwa tani 234,733. 2 Jedwali 3: Wastani wa bei za jumla za mchele kwa wiki (TZS/kilo 100) Jedwali 4: Wastani wa bei za jumla za maharage kwa wiki (TZS/kilo 100) Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha- mjini 160,000 165,000 165,000 ►0 Dar es Salaam - Ilala 220,000 220,000 220,000 ►0 Dar es Salaam-Kinondoni 220,000 220,000 220,000 ►0 Dodoma -majengo 220,000 216,000 217,500 ▲1 Bukoba 207,500 195,000 195,000 ►0 Babati 186,000 186,000 186,000 ►0 Morogoro 182,500 182,500 182,500 ►0 Iringa- mjini 180,000 180,000 185,000 ▲3 Mpanda 210,000 240,000 240,000 ►0 Mtwara DC 210,000 215,000 215,000 ►0 Tabora 225,000 225,000 225,000 ►0 Tanga/Mgandini 205,000 215,000 215,000 ►0 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha - Mjini 145,000 140,000 135,000 ▼4 Dar es Salaam - Ilala 170,000 170,000 170,000 ►0 Dar es Salaam-Kinondoni 165,000 165,000 165,000 ►0 Dodoma - majengo 135,000 136,500 142,500 ▲4 Bukoba 134,000 136,000 136,000 ►0 Babati 160,000 160,000 160,000 ►0 Morogoro 130,000 130,000 130,000 ►0 Mpanda 85,000 85,000 85,000 ►0 Mtwara DC 150,000 145,000 145,000 ►0 Musoma 97,500 97,500 97,500 ►0 Iringa Mjini 160,000 160,000 160,000 ►0 Tabora 145,000 145,000 145,000 ►0 Tanga/Mgandini 170,000 155,000 155,000 ►0 3 Jedwali 5: Wastani wa bei za jumla za mtama kwa wiki (TZS/Kilo100) Jedwali 6: Wastani wa bei za jumla za viazi mviringo kwa wiki (TZS/Kilo 100) Table 7: Wastani wa bei za mazao ya Horticulture kwa tarehe 23-28 October 2020 Eneo la Soko (Mji) Nyanya (40 Kg Crate) Vitunguu (100 Kg Sack) Tikiti maji (Kilo) Nanasi (Kilo) Green Pepper (50 Kg Sack) Cucumber (100 Kg Sack) Nairobi 44,000 74,800 719 609 52,800 96,800 Mombasa 33,293 80,667 550 - 51,333 77,000 Zanzibar 44,250 98,333 767 833 39,167 76,667 Dar es Salaam 21,667 80,000 300 400 36,111 100,000 Morogoro 37,500 73,000 425 - 45,000 83,333 Dodoma 24,000 70,000 267 333 35,000 60,000 Shinyanga 25,000 75,000 533 500 33,333 31,667 Mwanza 18,000 70,833 400 550 16,500 35,000 Mbeya 35,333 64,444 433 1,167 54,333 130,667 Arusha 24,500 80,000 530 475 30,000 75,000 Tanga 25,500 90,000 633 800 40,000 70,000 Lindi 19,000 90,000 300 350 30,000 55,000 Mtwara - 100,000 400 - 30,000 75,000 Chanzo: TAHA, 2020 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt26-30) Badiliko Wiki iliyopita na wiki hii (%) Arusha- mjini 72,500 72,500 72,500 ►0 Dar es Salaam –Kinondoni 55,000 55,000 57,500 ▲5 Dar es Salaam – Ilala 62,000 62,000 62,000 ►0 Dodoma - majengo 62,500 63,000 63,500 ▲1 Bukoba 95,000 97,500 97,500 ►0 Babati 67,500 67,500 67,500 ►0 Morogoro 76,000 76,500 76,500 ►0 Musoma 105,000 105,000 105,000 ►0 Mpanda 95,000 95,000 95,000 ►0 Mtwara DC 95,000 67,500 67,500 ►0 Tabora 77,500 72,500 72,500 ►0 Tanga/mgandini 58,900 58,900 58,900 ►0 Soko Wiki ya nyuma (Okt 12- 16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita na wiki hii (%) Arusha -mjini 65,000 62,500 65,000 ▲4 Dar es Salaam - Kinondoni 80,000 80,000 80,000 ►0 Dar es Salaam - Ilala 105,000 105,000 105,000 ►0 Dodoma - Majengo 47,500 49,000 50,500 ▲3 Dodoma-Kibaigwa 54,500 54,000 54,500 ▲1 Bukoba 140,000 145,000 145,000 ►0 Babati 60,000 60,000 60,000 ►0 Morogoro 95,000 95,000 95,000 ►0 Mtwara DC 80,000 80,000 80,000 ►0 Tabora 145,000 145,000 145,000 ►0 Tanga - mgandini 90,000 95,000 95,000 ►0 4 Jedwali 8: Mauzo ya korosho kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 30 Oktoba, 2020 Tarehe ya mnada Jina la chama Kikuu Kiasi kilichokusanywa (kilo) Mahitaji ya wanunuzi (kilo) Idadi ya wanunuzi Bei (Sh/kilo) Kiasi kilichouzwa (kilo) Ya chini Ya juu 9/10/2020 TANECU 3,109,568 15,952,000 22 2,421 2,707 3,109,568 9/10/2020 MAMCU 6,975,897 31,215,783 25 2,439 2,607 5,526,113 10/10/2020 MWAMBAO 7,143,773 21,247,546 19 2,329 2,470 7,143,773 11/10/2020 RUNALI 2,854,008 16,128,868 21 2,345 2,555 2,854,008 16/10/2020 TANECU 4,109,347 17,883,000 22 2,404 2,459 4,109,347 16/10/2020 MAMCU 9,603,182 32,910,536 21 2,265 2,459 9,602,982 17/10/2020 MWAMBAO 4,755,685 11,994,166 17 2,242 2,395 4,738,653 18/10/2020 RUNALI 7,225,504 16,149,454 17 2,301 2,435 7,225,504 23/10/2020 TANECU 4,726,622 17,333,000 26 2,351 2,415 3,759,000 23/10/2020 MAMCU 8,074,188 39,483,656 22 2,271 2,450 8,074,188 24/10/2020 MWAMBAO 3,180,884 11,051,522 15 1,7501 2,412 3,180,884 25/10/2020 RUNALI 4,989,359 20,974,022 18 1,630 2,410 4,989,359 29/10/2020 TAMCU 2,729,158 11,114,118 16 2,245 2,369 2,729,158 30/10/2020 TANECU 4,761,780 14,293,000 21 2,380 2,459 4,761,780 30/10/2020 MAMCU 5,978,692 34,844,966 21 2,290 2,479 5,978,692 Jumla 80,217,647 312,575,637 77,783,009 Chanzo: Bodi ya Korosho Tanzania, 2020 ✓ Kwa msimu wa 2020/21 wa mauzo, hadi kufikia tarehe 30 Oktoba, 2020, jumla ya tani 77,783 zilikuwa zimeuzwa kwa njia ya minada kati ya tani 80,218 zilizokuwa zimekusanywa na wakulima ambapo mahitaji ya wanunuzi yalikuwa ni jumla ya tani 312,576. 1 Bei ya korosho ya daraja la chini (Undergrade) ni Shilingi 1,750 na bei ya chini ya korosho ya daraja la juu (standard grade) ni shilingi 2,305, ambapo bei ya juu ya korosho daraja la juu ni shilingi 2,412. 5 Jedwali 9: Bei elekezi (shilingi) ya mbolea iliyotangazwa tarehe 11 Agosti, 2020 Kituo cha Mauzo DAP UREA Kilo 50 Kilo 25 Kilo 50 Kilo 25 Arusha 55,539 28,770 47,757 24,879 Dodoma 54,109 28,054 46,321 24,161 Dar es Salaam 48,892 25,446 41,462 21,731 Geita 58,496 30,248 50,709 26,355 Iringa 54,746 28,373 46,959 24,480 Kagera 59,378 30,689 52,337 27,168 Katavi 59,614 30,807 52,595 27,297 Kigoma 58,653 30,326 51,546 26,773 Kilimanjaro 54,499 28,250 46,712 24,356 Lindi 54,226 28,113 46,439 24,219 Manyara 56,643 29,321 48,856 25,428 Mara 59,510 30,755 52,481 27,240 Mbeya 56,476 29,238 48,689 25,344 Morogoro 53,211 27,606 45,424 23,712 Mtwara 54,963 28,482 47,176 24,588 Mwanza 58,370 30,185 50,583 26,291 Njombe 55,571 28,785 47,784 24,892 Pwani 51,819 26,909 44,032 23,016 Rukwa 59,439 30,719 52,403 27,202 Ruvuma 57,585 29,793 49,798 25,899 Shinyanga 57,716 29,858 49,929 25,964 Simiyu 57,727 29,864 49,940 25,970 Singida 55,134 28,567 47,347 24,673 Songwe 57,663 29,832 49,876 25,938 Tabora 56,863 29,432 49,594 25,797 Tanga 53,206 27,603 45,419 23,709 Wastani 55,756 28,878 48,126 25,063 Chanzo: Wizara ya Kilimo, 2020 6 Jedwali 10: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati mzuri wa kuvuna Wakati mbaya wa kuvuna Muda sahihi wa kupanda Vitunguu Feb- Julai Julai- Novemba Sept- Des Nyanya Jan- Mei Juni- Desemba Sept- Des Hoho kijani Feb- Aprili Juni- Januari Okt- Nov Karoti Okt- Machi April- Sept Julai- Okt Matango Feb- Mei Mei- Jan Des- Jan Viazi mviringo Machi- Juni Julai- Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba-Desemba Mei- Sept, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Des- Mei Feb- Machi Tangawizi Aprili- Julai Agosti - Machi Des- Feb Chanzo: TAHA 2020 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ Bei elekezi za mbolea ni za rejareja na zinatofautiana kwenye mikoa kulingana na umbali. ✓ Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara. Kwa maelezo zaidi wasiliana na: Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: benitho.kavenuke@kilimo.go.tz Simu: +255 786 465 121 au +255 754 419 813"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":190,"cells":{"data":{"kind":"string","value":"# Extracted Content Juni, 2021 WIZARA YA KILIMO Idara ya Usalama wa Chakula – Sehemu ya Uratibu wa Mazao na Tahadhari ya Awali TAARIFA YA TATHMINI YA AWALI YA UZALISHAJI WA MAZAO YA CHAKULA MSIMU 2020/2021 NA UPATIKANAJI WA CHAKULA 2021/2022 Sehemu ya Uratibu wa Mazao ya Chakula na Tahadhari ya Awali © Julai, 2021 JAMHURI YA MUUNGANO WA TANZANIA i YALIYOMO YALIYOMO ....................................................................................................................................... i ORODHA YA JEDWALI ................................................................................................................ ii ORODHA YA VIELELEZO ........................................................................................................... ii VIFUPISHO ..................................................................................................................................... iii SURA YA KWANZA ...................................................................................................................... 1 1.0 UTANGULIZI ............................................................................................................................ 1 SURA YA PILI ................................................................................................................................. 3 2.0 LENGO LA TATHMINI ............................................................................................................ 3 2.1 Malengo Mahsusi ..................................................................................................................... 3 SURA YA TATU.............................................................................................................................. 4 3.0 METHODOLOJIA ..................................................................................................................... 4 SURA YA NNE ................................................................................................................................ 6 4.0 MATOKEO YA TATHMINI ...................................................................................................... 6 4.1 Mwenendo wa Unyeshaji wa mvua katika Msimu wa Uzalishaji wa Mazao ya Chakula 2020/2021 na Athari zake kwenye Kilimo ................................................................................... 6 4.2 Mvua za Vuli, Oktoba – Desemba, 2020 na Mchango wake katika Uzalishaji wa Mazao ya Chakula .......................................................................................................................... 6 4.3 Mwenendo wa unyeshaji wa mvua za msimu Novemba, 2020 – Aprili, 2021 ............... 7 4.4 Mwenendo wa Unyeshaji wa Mvua za Masika, Machi – Mei, 2021................................. 9 4.5 Ulinganifu wa unyeshaji mvua Msimu wa 2020/2021 na 2019/2020: ........................... 10 4.6 Uzalishaji wa Mazao ya Chakula ......................................................................................... 11 4.7 Mahitaji ya chakula kwa Mwaka 2021/2022 Ikilinganishwa na Uzalishaji .................... 12 4.8 Mchango wa Uzalishaji wa Mazao ya Chakula ................................................................. 15 4.9 Mtiririko wa viwango vya SSR ............................................................................................. 15 4.10 Hali ya Uzalishaji wa Mazao ya Chakula na Viwango vya Uwiano (SSR) Kimkoa ... 16 4.11 Maeneo yenye Dalili za kuwa na Upungufu wa Chakula Nchini .................................. 18 SURA YA TANO ........................................................................................................................... 19 5.0 MWENENDO WA BEI KWA BAADHI YA MAZAO YA CHAKULA HADI KUFIKIA TAREHE 31 MEI, 2021 ................................................................................................................ 19 SURA YA SITA ............................................................................................................................. 21 ii 6.0 ATHARI ZA UGONJWA WA VIRUSI VYA KORONA (UVIKO-19) KATIKA UZALISHAJI WA MAZAO YA CHAKULA ................................................................................. 21 SURA YA SABA ........................................................................................................................... 22 7.0 CHANGAMOTO ..................................................................................................................... 22 SURA YA NANE ........................................................................................................................... 23 8.0 HITIMISHO NA USHAURI .................................................................................................... 23 VIAMBATISHO ............................................................................................................................. 25 Kiambatisho Na:1a. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Nafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei, 2021 .................................................................. 25 Kiambatisho Na:1b. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Yasiyonafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei,2021 ............................................. 26 Kiambatisho Na:2. Kiwango cha mvua na mtawanyiko wake kwa kila mwezi katika msimu wa mvua 2020/2021. .................................................................................................................... 27 Kiambatisho Na:3. Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (SSR) Msimu wa 2020/2021 .................................................................................................................. 30 ORODHA YA JEDWALI Jedwali Na: 1. Matarajio ya Uzalishaji wa Mazao ya Chakula Kimkoa ................................ 12 Jedwali Na: 2. Uzalishaji mazao ya Chakula kwa Msimu wa 2020/2021 Zao kwa zao na Mahitaji ya Chakula kwa Mwaka 2021/2022 (Tani) Kwa Mlinganisho ................................. 13 Jedwali Na: 3. Uwiano wa Uzalishaji na Mahitaji ya Mazao ya Chakula kwa Mwaka 2020/2021 ...................................................................................................................................... 17 Jedwali Na: 4. Halmashauri zenye Maeneo yenye Dalili ya Upungufu wa Chakula kwa Mwaka 2021/2022 ......................................................................................................................... 18 ORODHA YA VIELELEZO Kielelezo Na: 1. Viwango vya Unyeshaji mvua na Mtawanyiko wake kwa Kipindi cha Kuanzia Tarehe 1 Oktoba – 31 Desemba, 2020 ....................................................................... 7 Kielelezo Na: 2. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Novemba, 2020 – 30 Aprili, 2021 ................................................................. 8 Kielelezo Na: 3. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Machi – 31 Mei, 2021. .................................................................................... 9 Kielelezo Na: 4. Ulinganifu wa Viwango vya unyeshaji mvua (Anomalia) na mtawanyiko wake kwa kipindi cha kuanzia Tarehe Septemba 1, 2020 – Mei 31, 2021 na kuanzia Tarehe Septemba 1, 2019 – Mei 31, 2020. ............................................................................. 10 Kielelezo Na: 5. Asilimia ya uzalishaji ya mazao makuu ya chakula nchini ....................... 15 Kielelezo Na: 6. Mtiririko wa Uwiano wa Uzalishaji na Mahitaji (SSR) Kuanzia Mwaka 2002/2003 hadi 2021/2022 .......................................................................................................... 16 Kielelezo Na: 7. Mwenendo wa bei za mahindi, mchele na maharage kwa gunia la kilo 100 (Juni 2019-Mei 2021). ........................................................................................................... 19 iii VIFUPISHO ARDS: Agriculture Routine System CMEWs: Crop Monitoring and Early Warning System CPB: Cereal and other Produce Board HYC: Hali ya Chakula M&E: Monitoring and Evaluation NFRA: National Food Reserve Authority SSR: Self Sufficiency Ratio TMA: Tanzania Meterogical Authority UVIKO-19: Ugonjwa wa Virusi vya Korona 1 SURA YA KWANZA 1.0 UTANGULIZI Tathmini ya Uzalishaji wa Mazao ya Chakula na Upatikanaji wa Chakula nchini ni ya muhimu katika kupata taarifa ya uzalishaji wa mazao ya chakula na upatikanaji wa chakula nchini. Tathmini hizi huiwezesha Serikali kuchukua maamuzi stahiki katika utekelezaji wa jukumu la hali endelevu ya utengamano wa usalama wa chakula na lishe nchini kwa wakati wote. Tathmini hii hufanyika mara mbili katika msimu wa uzalishaji (Tathmini ya Awali na ya Mwisho). Tathmini ya Awali hufanyika kila mwaka mwezi Mei/Juni na Tathmini ya Mwisho mwezi Novemba/Desemba. Tathmini hizo huratibiwa na Idara ya Usalama wa Chakula Sehemu ya Uratibu wa Mazao na Tahadhari ya Awali. Sehemu hii hufanya shughuli za ufuatiliaji na ukusanyaji wa takwimu na taarifa mbalimbali zinazohusiana na Usalama wa Chakula nchini. Takwimu na taarifa hizo ni pamoja na: - hali ya unyeshaji wa mvua, ukuaji wa mazao mashambani, athari katika ukuaji wa mazao zinazoweza kusababishwa na visumbufu, mwenendo wa bei na upatikanaji wa chakula sokoni, hali ya biashara ya mazao ya chakula (export & import) na akiba ya mazao (stocks). Takwimu za uzalishaji wa mazao ya chakula hukusanywa kwa kutumia Mfumo wa Uratibu wa Mazao na Tahadhari ya Awali (Crop Monitoring and Early Warning System – CMEWs) sambamba na Mfumo wa Ukusanyaji na Utoaji wa Taarifa na Takwimu za Sekta ya Kilimo nchini (Agriculture Routine Data System - ARDS) ambapo nyenzo (tools) mbalimbali hutumika katika ukusanyaji wa takwimu na taarifa hizo. Katika tathmini hizo, mazao makuu ya chakula yanayoratibiwa kwa sasa ni mahindi, mpunga, mtama, uwele, ulezi, ngano, ndizi, muhogo, viazi vitamu, viazi mviringo, maharage, soya, mbaazi, kunde, choroko, karanga, njegere na njugumawe. Katika msimu wa 2020/2021 mazao haya yamelimwa katika eneo la ukubwa wa hekta 10,264,339 kati ya takriban hekta 44,000,000 zinazofaa kwa kilimo Tanzania Bara. Katika kipindi cha mwezi Juni 2021, timu ya wataalam wa Idara ya Usalama wa Chakula kwa kushirikiana na Idara ya Sera na Mipango - Sehemu ya Uratibu na 2 Tathmini (M&E) Wizara ya Kilimo, Ofisi ya Rais – Ikulu, Ofisi ya Rais –TAMISEMI, Ofisi ya Waziri Mkuu na Ofisi ya Taifa ya Takwimu ilifanya Tathmini ya Awali ya Uzalishaji wa Mazao ya Chakula kwa msimu wa 2020/20211. Katika tathmini hiyo, takwimu na taarifa mbalimbali za uzalishaji, upatikanaji wa mazao makuu ya chakula na mwenendo wa unyeshaji mvua kutoka Halmashauri zote za Tanzania Bara zilikusanywa na kufanyiwa uchambuzi wa kina na kutolewa taarifa. 1 Hapa nchini, msimu wa uzalishaji huanza kuhesabiwa kuanzia katikati ya mwezi Septemba ya mwaka husika hadi katikati ya mwezi Agosti ya mwaka unaofuata (Mfano Septemba, 2020 hadi Agosti, 2021), Aidha, kila msimu hupata unyeshaji wa mvua kama inavyoonesha yaani mvua za Vuli –Septemba-Desemba, Msimu –Desemba-Mei, na Masika-Machi –Mei. 3 SURA YA PILI 2.0 LENGO LA TATHMINI Lengo kuu ni kupata takwimu na taarifa za hali ya uzalishaji wa mazao ya chakula inayotarajiwa katika msimu wa 2020/2021 na upatikanaji wa chakula nchini kwa mwaka 2021/2022 ili kuiwezesha Serikali na wadau wa masuala ya usalama wa chakula kuchukua maamuzi stahiki katika utekelezaji wa jukumu la hali endelevu ya utengamano wa usalama wa chakula na lishe nchini. 2.1 Malengo Mahsusi Malengo mahsusi ni pamoja na; 1. Kukusanya takwimu za malengo ya uzalishaji wa mazao ya chakula kwa msimu wa 2020/2021 na utekelezaji wake kufikia Mei 31, 2021 ; 2. Kukusanya takwimu na taarifa za visumbufu na mwenendo wa unyeshaji wa mvua katika maeneo ya uzalishaji wa mazao ya chakula; 3. Kukusanya na kufuatilia taarifa za mwenendo wa bei za mazao ya chakula na mifugo, hali ya maji na malisho na upatikanaji wa chakula katika Halmashauri zote Tanzania bara ;na 4. Kufuatilia na kukusanya takwimu na taarifa za akiba ya mazao ya chakula katika maghala ya wafanya biashara na wakulima. 4 SURA YA TATU 3.0 METHODOLOJIA Tathmini hii ilihusisha jumla ya timu 9 za Wataalam ambapo takwimu na taarifa mbalimbali za uzalishaji wa mazao ya chakula zilikusanywa katika Halmashauri 184 katika Mikoa 26 ya Tanzania Bara. Takwimu na taarifa hizo zilikusanywa kwa kutumia mfumo wa CMEWs na ARDS. Timu hizo zilirejea na kuhakiki takwimu na taarifa mbalimbali za uzalishaji wa mazao ya chakula katika msimu wa 2020/2021. Aidha, timu ya wataalam walikutana Mkoani Morogoro kuendelea na kazi ya kuchambua, kuchakata na kuandaa taarifa ya awali ya uzalishaji wa mazao ya chakula katika msimu wa 2020/2021 na matarajio ya upatikanaji wa chakula kwa mwaka 2021/2022. Katika uchambuzi na uchakataji wa takwimu, vigezo vifuatavyo vilizingatiwa: - 1. Kigezo cha Upimaji wa Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (Self Sufficiency Ratio – SSR): Kigezo hiki hukokotolewa kwa kulinganisha uzalishaji na mahitaji (kutafsiriwa kwa kuzingatia asilimia - %) , ambapo Kiwango cha asilimia 0 - 99 inaashiria Upungufu wa chakula; asilimia 100 – 119 inaashiria Utoshelevu wa chakula na asilimia 120 na zaidi inaashiria Ziada ya chakula; 2. Ukokotoaji wa Mahitaji ya Chakula: Mahitaji ya chakula kwa mwaka hukokotolewa kwa kuzingatia idadi ya watu kwa mwaka wa chakula2 (mid-year population),3 mahitaji ya chakula (food consumption requirement) na mahitaji mengine yasiyokuwa ya chakula cha binadamu (non-food requirement) kama vile mbegu, chakula cha mifugo, biashara na upotevu wa mazao ambayo ni sehemu ya asilimia ya chakula kilichozalishwa; na 2 Hapa nchini, mwaka wa chakula huanzia tarehe 1 Juni hadi tarehe 31 Mei ya mwaka unaofuata, mfano Juni, 2021 hadi tarehe 31 Mei, 2022 kwa msimu wa uzalishaji 2020/2021. 3 ‘Mid-Year Population’ ni Idadi ya watu watakao kuwepo katikati ya mwaka husika wa chakula. Hii hukokotolewa kwa kutumia viwango vya ukuaji wa idadi ya watu (population growth rate) kulingana na Sensa ya idadi ya watu inayotolewa na NBS. 5 3. Ukokotoaji wa Ziada/Upungufu: Ziada au uhaba hukokotolewa kutokana na uzalishaji wa msimu husika baada ya kutoa mahitaji ya chakula ya mwaka husika (Production less Requirement) ambapo jibu linaweza kuwa chanya (+) inayoashiria ziada au hasi (-) inayoashiria upungufu kulingana na uzalishaji ulivyokuwa na; 4. Athari za visumbufu vya mazao na mwenendo wa unyeshaji wa mvua katika msimu husika. 6 SURA YA NNE 4.0 MATOKEO YA TATHMINI Matokeo ya tathmini hii ya awali yanaonesha kuwa, hali tarajiwa ya upatikanaji wa chakula kwa mwaka 2021/2022 itaendelea kutengamaa kutokana na uzalishaji wa kuridhisha wa mazao ya chakula katika mikoa yote ya Tanzania Bara. Aidha, kutokana na sababu mbalimbali zilizoleta athari katika baadhi ya mazao hususan nafaka, uzalishaji huu unatarajiwa kushuka kidogo ikilinganishwa na msimu wa 2019/2020. 4.1 Mwenendo wa Unyeshaji wa mvua katika Msimu wa Uzalishaji wa Mazao ya Chakula 2020/2021 na Athari zake kwenye Kilimo Uzalishaji wa mazao ya kilimo hutegemea kwa kiasi kikubwa unyeshaji wa mvua za kutosha na mtawanyiko wa kuridhisha. Unyeshaji wa mvua hapa nchini umegawanyika katika sehemu mbili, ambapo kuna maeneo yanayopata msimu mmoja wa mvua kwa mwaka (Msimu) na maeneo yanayopata misimu miwili ya mvua kwa mwaka (Vuli na Masika). 4.2 Mvua za Vuli, Oktoba – Desemba, 2020 na Mchango wake katika Uzalishaji wa Mazao ya Chakula Katika msimu wa mvua za Vuli 2020/2021, mvua zilianza mapema mwezi Septemba katika maeneo ya mikoa ya Mara na Kagera, na kutawanyika katika maeneo mengine ya Kanda ya Ziwa Viktoria pamoja na maeneo machache ya mikoa ya Pwani na Dar es Salaam katika kipindi cha mwezi Oktoba. Mvua hizi ziliendelea kunyesha kwa kiwango cha juu ya wastani katika maeneo mengi hasa ya Kanda ya Ziwa Viktoria. Katika maeneo mengine ya Pwani ya Kaskazini na Kanda ya Kaskazini Mashariki, mvua zilichelewa kuanza (zilianza mwezi Novemba, 2020) na ziliendelea kwa mtawanyiko hafifu. Mvua hizi ziliendelea kunyesha hadi katika kipindi cha mwezi Januari, 2021 na hivyo kuisha nje ya msimu. Hali hii ilisababisha athari kidogo kwenye mazao yaliyokuwa yamekomaa katika baadhi ya maeneo. Hata hivyo, uzalishaji wa mazao kwa ujumla ulikuwa mzuri Kielelezo Na. 1. 7 Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Vuli, 2020 ikilinganishwa na wastani Asilimia ya unyeshaji mvua za Vuli, 2020 (wastani ni 75 – 125%) Kielelezo Na: 1. Viwango vya Unyeshaji mvua na Mtawanyiko wake kwa Kipindi cha Kuanzia Tarehe 1 Oktoba – 31 Desemba, 2020 Chanzo: TMA, GeoWRSI 2020 4Anomalia 4.3 Mwenendo wa unyeshaji wa mvua za msimu Novemba, 2020 – Aprili, 2021 Mvua za Msimu zilianza kwa wakati katika wiki ya pili ya mwezi Novemba, 2020 katika maeneo mengi yanayopata mvua hizo isipokuwa maeneo ya mikoa ya Dodoma, Iringa, Njombe, Ruvuma, Mtwara, Lindi na Morogoro-kusini. Katika maeneo hayo, mvua zilianza kati ya wiki ya pili na wiki ya tatu ya mwezi Desemba, 2020. Ziliendelea vizuri katika miezi ya Januari na Februari, 2021 katika maeneo yote. Kipindi cha Mwezi Machi, 2021 kilitawaliwa na vipindi vya ukosefu wa mvua (prolonged dry spells) katika maeneo mengi isipokuwa kusini mwa nchi. Mvua hizi ziliwahi kuisha mapema zaidi katika wiki ya kwanza ya mwezi Aprili, 2021 katika maeneo ya mkoa wa Ruvuma na maeneo ya kanda ya kati. Maeneo mengine 4 Anomalia: Kiwango cha wa unyeshaji mvua mwenendo wa kawaida 8 yaliyosalia, mvua hizo ziliendelea mpaka kufikia wiki ya kwanza ya mwezi Mei, 2021. Aidha, mvua chache zilinyesha katika maeneo ya magharibi na kusini mwa mkoa wa Morogoro katika wiki ya kwanza ya mwezi Mei, 2021 na maeneo ya Pwani ya kusini katika wiki ya mwisho ya mwezi Mei, 2021. Mvua hizi zimechangia uharibifu kiasi wa mazao yaliyokuwa yamefikia hatua ya kukomaa na pia menejimenti ya ukaushaji wa mazao yaliyokuwa yanavunwa. Hata hivyo, kwa ujumla mvua za wastani hadi juu ya wastani zilinyesha katika maeneo yote yanayopata mvua za Msimu, lakini mtawanyiko wake haukuwa mzuri katika baadhi ya maeneo na hivyo kupunguza tija ya uzalishaji katika maeneo mengi yanayopata mvua hizo za Msimu hasa kwa mazao ya nafaka Kielelezo Na. 2. Chanzo: TMA, GeoWRSI 2021 Kiasi cha mvua (mm) iliyonyesha kwenye kipindi cha Msimu Novemba, 2020 – Aprili, 2021 Asilimia ya unyeshaji mvua za Msimu Novemba, 2020 – Aprili, 2021 (wastani ni 75 – 125%) Kielelezo Na: 2. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Novemba, 2020 – 30 Aprili, 2021 9 4.4 Mwenendo wa Unyeshaji wa Mvua za Masika, Machi – Mei, 2021 Kwa mwaka 2021, mvua za Masika zilichelewa sana kuanza. Mvua hizo zilianza katika wiki ya nne katika maeneo machache badala ya wiki ya pili ya mwezi Machi kama ilivyokawaida na kuendelea kwa wingi katika mwezi Aprili. Hata hivyo, mvua hizo hazikuwa na mtawanyiko mzuri kimaeneo (spatial distribution) na kwa kipindi cha unyeshaji (temporal distribution). Aidha, mvua hizo ziliwahi kuisha katika baadhi ya maeneo na kusababisha mazao kukosa unyevunyevu wa kutosha hasa mazao ya mahindi na mpunga. Hata hivyo, uchache wa mvua hizi uliwezesha mazao ya mizizi kustawi vizuri na hivyo kuongeza uzalishaji wa mazao hayo. Kwa ujumla, mvua zilikuwa za wastani hadi juu ya wastani katika maeneo mengi isipokuwa maeneo ya mkoa wa Tanga na kaskazini mwa mkoa wa Pwani na hivyo kusababisha uzalishaji wa mazao kiujumla kuwa wa wastani Kielelezo Na.3. Chanzo: TMA, GeoWRSI 2021 Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Masika, 2021 ikilinganishwa na wastani Asilimia ya unyeshaji mvua za Masika, 2021 (wastani ni 75 – 125%) Kielelezo Na: 3. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Machi – 31 Mei, 2021. 10 4.5 Ulinganifu wa Unyeshaji mvua Msimu wa 2020/2021 na 2019/2020: Mvua katika msimu wa 2020/2021 ilinyesha katika kiwango cha wastani hadi juu ya wastani kama ilivyokuwa katika msimu uliopita wa 2019/2020 katika maeneo mengi ya nchi. Hata hivyo, katika msimu wa 2020/2021 mvua ilinyesha kwa kiwango pungufu ikilinganishwa na msimu wa 2019/2020. Aidha, Maeneo machache ya Kaskazini hasa mikoa ya Kilimanjaro, Tanga, Dar es Salaam na kaskazini mwa mkoa wa Pwani mvua zimenyesha kwa kiwango cha wastani hadi chini ya wastani, hali hii ni pungufu zaidi ikilinganishwa na msimu uliopita Kielelezo Na. 4 na Kiambatisho Na. 2. Chanzo: TMA, GeoWRSI 2021 & 2020 Mtawalia Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Kilimo kuanzia Septemba 1, 2020 – Mei 31, 2021 ikilinganishwa na wastani Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Kilimo kuanzia Septemba 1, 2019 – Mei 31, 2020 ikilinganishwa na wastani Kielelezo Na: 4. Ulinganifu wa Viwango vya unyeshaji mvua (Anomalia) na mtawanyiko wake kwa kipindi cha kuanzia Tarehe Septemba 1, 2020 – Mei 31, 2021 na kuanzia Tarehe 1 Septemba, 2019 – 31 Mei, 2020. 11 4.6 Uzalishaji wa Mazao ya Chakula Tathmini ya Awali ya hali ya Uzalishaji wa Mazao ya Chakula Msimu wa 2020/2021 na Upatikanaji wa Chakula kwa Mwaka 2021/2022 imeonesha kuwa, hali ya uzalishaji wa chakula inatarajiwa kufikia kiasi cha tani 18,425,250 kwa mlinganisho wa nafaka (Grain Equivalent). Ikilinganishwa na tani 18,196,733 msimu wa 2019/2020 uzalishaji huu umeongezeka kwa kiasi cha tani 228,517 sawa na asilimia 1.3. Kwa msimu wa uzalishaji wa 2020/2021, uzalishaji wa mazao ya nafaka unatarajiwa kufikia tani 10,639,990. Uzalishaji huu umepungua kwa tani 229,606 sawa na asilimia 2.1 ikilinganishwa na uzalishaji wa tani 10,869,596 kwa msimu wa 2019/2020. Aidha, kwa mazao yasiyo nafaka uzalishaji unatarajiwa kufikia tani 7,785,260. Ikilinganishwa na uzalishaji wa tani 7,327, 137 msimu wa 2019/2020, uzalishaji huu umeongezeka kwa tani 458,123 sawa na ongezeko la asilimia 6.2. Uzalishaji wa mahindi unatarajiwa kufikia kiasi cha tani 6,908,318 ikilinganishwa na tani 6,711,002 za uzalishaji msimu wa 2019/2020. Uzalishaji wa mchele unatarajiwa kufikia kiasi cha tani, 2,629, 519 ikilinganishwa na tani 3,038,080 kwa msimu wa 2019/2020. Uzalishaji wa mahindi umeongezeka kwa tani 197,316 na mchele umepungua kwa tani 408,561 sawa na asilimia 3.0 na 13.5 mtawalia. Uzalishaji wa mazao ya chakula kwa kuzingatia mkoa ulioongoza katika uzalishaji wa mazao hayo ni kama inavyoonekana katika Jedwali Na.1. 12 Jedwali Na: 1. Matarajio ya Uzalishaji wa Mazao ya Chakula Kimkoa 1 Ruvuma 352,796 998,550 Kagera 364,220 972,960 Ruvuma 509,976 1,341,740 Ruvuma 2 Mbeya 303,434 865,715 Kigoma 350,816 693,780 Mbeya 452,090 1,253,699 Mbeya 3 Morogoro 410,843 770,966 Mwanza 244,547 550,806 Kigoma 599,633 1,215,621 Kigoma 4 Rukwa 329,706 768,033 Mbeya 148,656 387,985 Kagera 489,866 1,139,154 Kagera 5 Songwe 255,162 595,429 Tanga 283,096 385,144 Rukwa 514,207 1,041,067 Rukwa 6 Tabora 337,520 573,624 Mara 130,175 371,093 Mwanza 482,779 978,820 Mwanza 7 Kigoma 248,817 521,841 Ruvuma 157,180 343,190 Morogoro 510,529 973,508 Morogoro 8 Manyara 302,889 514,471 Geita 231,561 340,944 Tabora 598,952 892,093 Tabora 9 Dodoma 423,517 455,012 Mtwara 200,227 323,845 Songwe 394,432 843,847 Songwe 10 Mwanza 238,232 428,014 Tabora 261,432 318,469 Tanga 571,407 741,809 Tanga 11 Simiyu 309,655 396,602 Kilimanjaro 117,755 300,237 Dodoma 604,175 715,512 Dodoma 12 Arusha 207,728 361,570 Rukwa 184,500 273,033 Geita 445,974 699,841 Geita 13 Singida 313,055 360,965 Dodoma 180,658 260,499 Manyara 443,849 655,780 Manyara 14 Geita 214,413 358,897 Arusha 113,510 253,675 Mara 293,094 628,399 Mara 15 Tanga 288,311 356,666 Pwani 80,028 248,513 Arusha 321,238 615,245 Arusha 16 Shinyanga 246,209 356,427 Songwe 139,270 248,418 Simiyu 517,353 585,422 Simiyu 17 Iringa 160,427 322,132 Morogoro 99,686 202,542 Kilimanjaro 241,858 569,184 Kilimanjaro 18 Njombe 143,195 280,960 Shinyanga 181,882 189,499 Shinyanga 428,090 545,926 Shinyanga 19 Kilimanjaro 124,103 268,947 Simiyu 207,699 188,820 Singida 398,457 523,665 Singida 20 Katavi 132,452 268,286 Njombe 115,818 175,863 Iringa 261,667 471,490 Iringa 21 Mara 162,919 257,306 Katavi 78,684 165,541 Njombe 259,013 456,824 Njombe 22 Kagera 125,646 166,194 Singida 85,402 162,700 Katavi 211,136 433,827 Katavi 23 Lindi 143,240 156,983 Iringa 101,240 149,358 Mtwara 297,546 417,908 Mtwara 24 Pwani 110,052 151,553 Manyara 140,960 141,308 Pwani 190,080 400,066 Pwani 25 Mtwara 97,319 94,063 Lindi 80,197 128,185 Lindi 223,437 285,168 Lindi 26 Dar es Salaam 926 818 Dar es Salaam 2,573 8,852 Dar es Salaam 3,499 9,670 Dar es Salaam Jumla 5,982,567 10,639,990 Jumla 4,239,083 7,785,260 Jumla 10,264,339 18,425,250 Jumla Matarajio ya Mavuno Yote (Tani) Mkoa Eneo (Hekta) Mkoa Mavuno (Tani) Mavuno (Tani) Mkoa Mkoa Mavuno (Tani) Matarajio ya Mazao ya Nafaka (Tani) Eneo (Hekta) Matarajio ya Mazao yasiyo Nafaka (Tani) Eneo (Hekta) Chanzo: Tathmini ya HYC 2020/2021 4.7 Mahitaji ya chakula kwa Mwaka 2021/2022 Ikilinganishwa na Uzalishaji Mahitaji ya chakula kwa mwaka 2021/2022 ni kiasi cha tani 14,796, 751 ambapo tani 9,417,888 ni za mazao ya nafaka na tani 5,378,864 ni mazao yasiyo nafaka. Kutokana na mahitaji haya yakilinganishwa na uzalishaji, nchi inategemewa kuwa na ziada ya tani 3,628,499 za chakula ambapo tani 1,222,103 ni mazao ya nafaka na tani 2,406,396 ni mazao yasiyo nafaka. Aidha, mahitaji ya mahindi ni kiasi cha tani 5,956,814, ikilinganishwa na uzalishaji, nchi inatarajiwa kuwa na ziada ya tani 951,504 za mahindi. 13 Mahitaji ya mchele ni tani 1,091,778, kiasi hiki kikilinganishwa na uzalishaji, nchi itakuwa na ziada ya tani 1,537,741. Kulingana na uzalishaji unaotarajiwa, nchi itaendelea kuwa na utengamano wa usalama wa chakula, ambapo uwepo na upatikanaji wa chakula nchini utaendelea kuwa wa kuridhisha Jedwali Na. 2. Jedwali Na: 2. Uzalishaji mazao ya Chakula kwa Msimu wa 2020/2021 Zao kwa zao na Mahitaji ya Chakula kwa Mwaka 2021/2022 (Tani) Kwa Mlinganisho wa Nafaka (Grain Equivalent). Nafaka Mahindi Mtama&Malezi Mchele Ngano Nafaka Uzalishaji 6,908,318 1,031,865.0 2,629,519 70,288 10,639,990 Mahitaji 5,956,814 2,087,357.8 1,091,778 281,938 9,417,888 Uhaba (-)/Ziada(+) 951,504 -1,055,493 1,537,741 -211,650 1,222,103 SSR (%) 116 49 241 25 113 Sinafaka Mikunde Ndizi Muhogo Viazi Yasiyonafaka Uzalishaji 2,135,522 1,392,970 2,643,915 1,612,852 7,785,260 Mahitaji 859,337 990,670 2,473,437 1,055,420 5,378,864 Uhaba (-)/Ziada(+) 1,276,185 402,300 170,478 557,433 2,406,396 SSR (%) 249 141 107 153 145 JUMLA Nafaka Yasiyonafaka Uzalishaji 10,639,990 7,785,260 Mahitaji 9,417,888 5,378,864 Uhaba (-)/Ziada(+) 1,222,103 2,406,396 SSR (%) 113 145 125 JUMLA 18,425,250 14,796,751 3,628,499 Chanzo: Tathmini ya HYC 2021 14 4.7.1 Mahitaji ya Ngano ikilinganishwa na Uzalishaji Tathmini ambazo zimekuwa zikifanyika hapa nchini, zimeendelea kubainisha uzalishaji wa kiwango kidogo cha ngano. Mahitaji ya ngano kwa majumbani na viwandani hapa nchini ni takribani tani 1, 000,000 kwa mwaka. Kupitia tathmini hii, jumla ya tani 70,288 za ngano zinatarajiwa kuzalishwa ambapo kiasi hiki ni sawa na asilimia 7 ya mahitaji ya ngano kwa mwaka 2021/2022. Kwakuwa kiasi kinachozalishwa hakikidhi mahitaji, nchi imeendelea kuagiza ngano kutoka nje kutoka nchi za Canada, India, Uturuki, Urusi, Argentina na Australia kama inavyoonekana kwenye Jedwali Na.3. Jedwali Na. 3. Mtiririko wa Uagizaji wa Ngano kutoka Nje kwa Kipindi cha Miaka 3. Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Buck wheat HS CODE 10081000 Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Buck wheat HS CODE 10081000 CANADA 5,000.00 - 5,000.00 INDIA 6.27 - 5.36 1.60 116.67 129.90 UTURUKI - 7.08 17.41 21.32 45.80 URUSI 40,000.00 10,000.00 50,000.00 ARGENTINA 8,960.00 8,960.00 AUSTRALIA 27,319.77 27,319.77 91,455.47 50,022.77 36,419.36 JUMLA 5,013.35 JUNI 2019 - MEI 2020 JUNI 2020-MEI 2021 JUNI 2018 - MEI 2019 JUMLA NCHI INAPOTOKA Chanzo: Mamlaka ya Mapato Tanzania 15 4.8 Mchango wa Uzalishaji wa Mazao ya Chakula Matarajio ya uzalishaji wa mazao ya chakula katika msimu wa 2020/2021 unaonesha kuwa, mahindi yatachangia asilimia 37.5, mchele asilimia 14.3, muhogo asilimia 14.3, mikunde asilimia 11.6 na mazao mengine yamechangia asilimia 22.3 kwa pamoja Kielelezo Na.5: Chanzo: Tathmini ya HYC 2020/2021 Kielelezo Na: 5. Asilimia ya uzalishaji ya mazao makuu ya chakula nchini 4.9 Mtiririko wa viwango vya SSR Kwa kuzingatia Kigezo cha Upimaji wa Uwiano wa Uzalishaji na Mahitaji (Self Sufficiency Ratio – SSR), kwa kipindi cha miaka 7 nchi imeendelea kuwa na viwango vya ziada kati ya asilimia 120 na 126. Katika mwaka 2021/2022 nchi inatarajia kuwa na ziada kwa uwiano wa asilimia 125 16 Kielelezo Na.6. Chanzo: Tathmini za HYC – Wizara ya Kilimo Kielelezo Na: 6. Mtiririko wa Uwiano wa Uzalishaji na Mahitaji (SSR) Kuanzia Mwaka 2002/2003 hadi 2021/2022 Ufunguo: Ziada: SSR ≥120 Utoshelevu: SSR 100-119 Upungufu: SSR≤100 4.10 Hali ya Uzalishaji wa Mazao ya Chakula na Viwango vya Uwiano (SSR) Kimkoa Hali ya chakula inatarajiwa kuwa ya kiwango cha: Ziada kati ya asilimia 240 na 120 katika mikoa 13 ambayo ni Ruvuma, Rukwa, Songwe, Katavi, Njombe, Mbeya, Kigoma, Iringa, Kagera, Morogoro, Geita, Manyara na Mtwara. Utoshelevu kati ya asilimia 119 na 104 kwenye mikoa 12 ya Pwani, Simiyu, Singida, Lindi, Tabora, 17 Shinyanga, Tanga, Mara, Kilimanjaro, Dodoma, Arusha na Mwanza na Upungufu kwa asilimia 1 katika mkoa wa Dar es Salaam Jedwali Na.3, Kiambatisho Na.1 a, 1 b na 3. Jedwali Na: 3. Uwiano wa Uzalishaji na Mahitaji ya Mazao ya Chakula kwa Mwaka 2020/2021 Chanzo: Tathmini ya HYC 2020/2021. * Pamoja na kwamba Mkoa wa Dar es Salaam unaonesha upungufu, mkoa huu siyo wa uzalishaji. Ufunguo: Ziada: SSR ≥120 Utoshelevu: SSR 100-119 Upungufu: SSR≤100 18 4.11 Maeneo yenye Dalili za kuwa na Upungufu wa Chakula Nchini Wakati hali ya chakula Kitaifa inatarajiwa kuwa ya kiwango cha Ziada (SSR ya 125), Halmashauri 17 katika mikoa 8 ina maeneo yenye dalili za upungufu wa chakula kwa mwaka 2021/2022 katika vipindi tofauti. Upungufu huo umechangiwa na sababu mbalimbali ikiwemo mtawanyiko mbaya wa mvua, visumbufu vya mimea kama vile wanyama pori, ndege aina ya kwelea kwelea na viwavijeshi vamizi. Maeneo yanayotarajiwa kuwa na upungufu huo ni kama inavyoonekana katika Jedwali Na.4. Jedwali Na: 4. Halmashauri zenye Maeneo yenye Dalili ya Upungufu wa Chakula kwa Mwaka 2021/2022 Na Jina La Mkoa Idadi ya Halmashauri Jina la Halmashauri Kipindi cha Upungufu 1 Tanga 6 Korogwe DC, Korogwe TC, Handeni DC, Handeni TC, Kilindi, Mkinga Sept 2021-Machi 2022 2 Manyara 1 Mbulu DC Des 2021 -Machi 2022 3 Arusha 2 Monduli, Longido Okt 2021-Machi 2022 4 Kilimanjaro 2 Same, Mwanga Okt 2021-Machi 2022 5 Mara 2 Rorya, Musoma DC Okt 2021 - Feb 2022 6 Singida 2 Manyoni na Mkalama Sept 2021-Machi 2022 7 Simiyu 1 Meatu Jan 2022 -Machi 2022 8 Dodoma 1 Bahi Sept 2021-Machi 2022 JUMLA = 8 17 Chanzo: Tathmini ya HYC 2020/2021 NB: Pamoja na kwamba Mkoa wa Dar es Salaam unaonesha upungufu, Halmashauri zake hazioneshwi katika jedwali hili kwa kuwa siyo mkoa wa uzalishaji. Mkoa huo unapokea vyakula kutoka katika mikoa mingine. *Tahadhari inatolewa dhidi ya upungufu wa chakula unaoweza kujitokeza katika maeneo hayo katika kipindi cha 2021/2022. 19 SURA YA TANO 5.0 MWENENDO WA BEI KWA BAADHI YA MAZAO YA CHAKULA HADI KUFIKIA TAREHE 31 MEI, 2021 Hadi kufikia tarehe 31 Mei, 2021, upatikanaji wa chakula sokoni umeendelea kuwa mzuri ambapo bei za mazao ya chakula hususan mahindi, mchele na maharage zimeendelea kushuka ikilinganishwa na bei za mazao hayo katika kipindi kama hicho kwa mwaka 2020 Kielelezo Na: 7. Chanzo:Wizara ya Viwanda na Biashara, 2020 Kielelezo Na: 7. Mwenendo wa bei za mahindi, mchele na maharage kwa gunia la kilogramu 100 (Juni 2019-Mei 2021). Mlinganisho wa bei za mazao haya umezingatia mwaka wa chakula husika ambapo katika uchambuzi huu miaka iliyozingatiwa ni Juni 2019 hadi Mei 2020 na Juni, 2020 hadi Mei, 2021. Kwa kuzingatia mlinganisho huo, bei ya wastani kwa mazao ya mahindi na mchele haijatofautiana sana. Bei ya wastani ya mahindi kwa gunia la kilogramu 100 kwa mwaka wa chakula 2019/2020 ilikuwa juu ikilinganishwa na mwaka wa chakula 2020/2021. Mfano, hadi kufikia mwezi Mei 2020, bei ya mahindi kwa gunia la kilogramu 100 ilikuwa shilingi za kitanzania 56,355 ikilinganishwa na shilingi za kitanzania 43,466 kwa mwezi Mei, 2021. 20 Bei ya wastani ya mchele kwa gunia la kilogramu 100 kwa mwaka wa chakula 2019/2020 ilikuwa juu ikilinganishwa na mwaka wa chakula 2020/2021. Hadi kufikia, Mei 2020, bei ya mchele kwa gunia la kilogramu 100 ilikuwa shilingi za kitanzania 165,294 ikilinganishwa na shilingi za kitanzania 136,666 kwa mwezi Mei, 2021. Kwa ujumla, mwenendo wa bei ya maharage kwa kipindi cha kuanzia Juni, 2020 hadi Novemba, 2020 ilikuwa juu ikilinganishwa na bei ya kipindi kama hicho kwa mwaka 2019. Bei ya gunia la kilogramu 100 liliuzwa kuanzia shilingi 205,234 mwezi Juni 2020 hadi shilingi 207,382 mwezi Novemba 2020 ikilinganishwa na shilingi 164,587 Juni 2019 hadi shilingi 196,527 mwezi Novemba 2019. Hali hii ilichangiwa na mvua nyingi katika msimu wa uzalishaji wa 2019/2020 zilizosababisha zao hilo kuharibikia shambani na hivyo kuathiri uzalishaji wa zao hilo katika maeneo mengi ya nchi. Aidha, kuanzia kipindi cha mwezi Desemba 2020 hadi Mei 2021, mwenendo wa bei ya maharage ulikuwa chini ikilinganishwa na bei ya kipindi kama hicho kwa mwaka 2019/2020. Hali hii ilichangiwa na uzalishaji mzuri wa maharage katika msimu wa vuli wa 2020. Kutokana na mwelekeo mzuri wa uzalishaji wa mazao ya chakula ikiwemo mahindi, mchele na maharage, bei inatarajiwa kuendelea kushuka na hivyo kuimarisha utengamano wa upatikanaji wa chakula nchini. 21 SURA YA SITA 6.0 ATHARI ZA UGONJWA WA VIRUSI VYA KORONA (UVIKO-19) KATIKA UZALISHAJI WA MAZAO YA CHAKULA Ugonjwa wa UVIKO umekuwa tishio kubwa katika shughuli mbalimbali za kiuchumi ikiwemo shughuli za uzalishaji na usafirishaji wa mazao ya chakula duniani. Ugonjwa huo unaweza kuleta athari hasi katika masuala ya usalama wa chakula nchini hususan katika ngazi ya kaya. Taarifa mbalimbali zilizopatikana kutoka katika mikoa yote ya Tanzania bara, zimeonesha kuwa uzalishaji wa mazao ya chakula kwa msimu wa 2020/2021 haujaathiriwa na uwepo wa mlipuko wa ugonjwa huo hapa nchini. Hata hivyo, iwapo hali hii ya uwepo wa ugonjwa wa UVIKO-19 itaendelea katika nchi zinazozalisha pembejeo, shughuli za kilimo kwa msimu wa 2021/2022 zinaweza kuathiriwa katika upatikanaji wa pembejeo muhimu za kilimo kama vile mbegu, mbolea, viuatilifu na zana za kilimo. Hivyo basi, mikakati madhubuti inatakiwa ili kukabiliana na changamoto yoyote itakayoweza kujitokeza. 6.1 Mikakati ya Kuimarisha Uhakika wa Usalama wa Chakula katika kipindi cha UVIKO-19 (i) Kuboresha mifumo ya uhifadhi wa mazao ya chakula katika ngazi zote; (ii) Kuimarisha mfumo wa stakabadhi za mazao ghalani ili kuongeza viwango vya mazao kupunguza uharibifu; (iii) Kuendelea kuimarisha miundombinu ya umwagiliaji ili kuongeza upatikanaji wa chakula; (iv) Kufanya maandalizi mapema ya ununuzi wa pembejeo za kilimo kwa ajili ya msimu wa uzalishaji wa 2021/2022; (v) Kuendelea kuelimisha wananchi juu ya matumizi sahihi ya chakula katika ngazi ya kaya na; (vi) Kuendelea kujenga mazingira rafiki na wezeshi ya usafirishaji wa mazao ya chakula na bidhaa zake kwenda nje ya nchi. 22 SURA YA SABA 7.0 CHANGAMOTO Katika msimu wa uzalishaji 2020/2021, changamoto mbalimbali zilijitokeza na kusababisha kutofikiwa kwa malengo ya uzalishaji katika baadhi ya maeneo nchini. Changamoto hizo ni kama zilivyofafanuliwa hapo chini: (i) Mvua kuchelewa kunyesha na kuisha mapema katika baadhi ya maeneo na hivyo kusababisha kupungua kwa uzalishaji hususan mazao ya nafaka; (ii) Unyeshaji wa mvua juu ya kiwango uliosababisha kutokea kwa mafuriko na kutuama kwa maji katika baadhi ya maeneo hususan katika mikoa ya Kilimanjaro, Morogoro, Mbeya na Kagera. Hali hii imechangia kushuka kwa uzalishaji wa mazao hususan mpunga, jamii ya mikunde na mizizi katika maeneo hayo; (iii) Kuongezeka kwa gharama za uzalishaji uliotokana na upotevu wa mbolea ardhini (leaching) katika baadhi ya maeneo; (iv) Mvua za nje ya msimu zilisababisha uharibifu wa mazao yaliokuwa yamefikia hatua ya kukomaa hasa mpunga na maharage; (v) Hali ya vipindi virefu vya ukosefu wa mvua ilisababisha kupungua kwa uzalishaji hasa katika baadhi ya maeneo ya mikoa ya Morogoro, Katavi, Lindi, Arusha, Tanga, Mara, Mtwara na Kilimanjaro; (vi) Bei kubwa za pembejeo hasa mbolea na mbegu bora zimechangia kushuka kwa matumizi ya pembejeo na hivyo kuchangia kushuka kwa uzalishaji katika baadhi ya maeneo na; (vii) Uvamizi wa visumbufu hususan batobato kali, kwelea kwelea, tembo, kiboko na nguruwe pori kwenye baadhi ya mashamba nchini. 23 SURA YA NANE 8.0 HITIMISHO NA USHAURI Hali ya uzalishaji na upatikanaji wa mazao ya chakula nchini imeendelea kuwa nzuri katika kipindi cha zaidi ya miaka saba mfululizo kufuatia uzalishaji mzuri wa mazao ya chakula ikilinganishwa na mahitaji ya chakula nchini. Katika kipindi cha miaka ya chakula 2013/2014 na 2021/2022, nchi imekuwa na SSR kati ya asilimia 118 hadi 126 na imekuwa ikizalisha ziada kati ya tani 2,234,725 hadi tani 3,792,562. Mafanikio hayo yanatokana na sababu mbalimbali ikiwemo hali ya hewa nzuri pamoja na usimamizi na utekelezaji mzuri wa sera na mikakati mbalimbali ya Serikali pamoja na wadau wengine wa masuala ya kilimo na usalama wa chakula. Kwa mwaka wa uzalishaji 2020/2021, hali ya uzalishaji wa mazao ya chakula ni ya kuridhisha ambapo kwa mwaka wa chakula 2021/2022, nchi inatarajia kujitosheleza kwa asilimia 125. Kwa kuzingatia vigezo vya upimaji wa upatikanaji na mahitaji, kiwango hiki kinaashiria nchi itakuwa na ziada. Uzalishaji wa msimu huu haujatofautiana sana na msimu wa 2019/2020 ambapo kwa mwaka wa chakula wa 2020/2021 nchi ilifikia kiwango cha asilimia 126. Kutokana na matokeo ya Tathmini hii, ushauri ufuatao unapendekezwa: - (i) Kuendelea kuboresha Mfumo wa Uratibu wa Mazao na Tahadhari ya Awali ili kuwezesha upatikanaji wa takwimu na taarifa sahihi za usalama wa chakula nchini kwa wakati; (ii) Kuendelea kuwajengea uwezo wataalam wa kilimo katika ngazi ya Taifa, Mkoa na Halmashauri katika masuala ya takwimu za usalama wa chakula na kilimo; (iii) Kuboresha na kuhuisha vituo vya mvua ili kupata takwimu za unyeshaji wa mvua katika maeneo ya kilimo; (iv) Wananchi waendelee kuhamasishwa kuhifadhi chakula cha kutosha kwa ajili ya kaya zao; 24 (v) Ili kuongeza tija katika uzalishaji wa mazao ya kilimo, ruzuku iwekwe kwenye pembejeo ili kurahisisha upatikanaji na kuongeza matumizi sahihi; (vi) Biashara ya mazao ya chakula ndani na nje ya nchi iendelee kwa kufuata sheria na taratibu zilizopo; (vii) Wakala wa Taifa wa Hifadhi ya Chakula (NFRA), waanze ununuzi wa mazao mapema kwa ajili ya usalama wa chakula wa nchi; (viii) Bodi ya Nafaka na Mazao Mchanganyiko (CPB), iongeze kasi ya kufungua vituo vipya vya uuzaji wa mazao ya chakula ndani na nje ya nchi; (ix) Mamlaka za Mikoa na Halmashauri za pembezoni mwa nchi ziendelee kuimarisha udhibiti wa utoroshaji wa chakula nje ya nchi kupitia mipaka isiyo rasmi; (x) Kuendelea kuimarisha mfumo wa upatikanaji na usambazaji wa pembejeo na zana za kilimo katika ngazi zote; (xi) Kuendelea kuimarisha na kuongeza miundombinu ya umwagiliaji; (xii) Kufanya maandalizi mapema ya ununuzi wa pembejeo za kilimo kwa ajili ya msimu wa uzalishaji wa 2021/2022; (xiii) Wafanyabiashara waendelee kuhamasishwa kuwekeza katika viwanda vya kuchakata mazao ya chakula ili kuyaongezea thamani na kupata bei nzuri ndani na nje ya nchi na; (xiv) Kuendelea kuhamasisha sekta binafsi kuwekeza katika ujenzi wa maghala katika ngazi zote. VIAMBATISHO Kiambatisho Na:1a. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Nafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei, 2021 Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Uzalishaji (Tani) Mkoa Arusha 122,974 1.6 196,758 23,613 0.8 19,339 534 1.4 739 52,847 2.4 126,833 4,000 2.8 11,259 3,760 1.8 6,642 207,728 361,570 Arusha Pwani 73,980 1.4 103,571 2,743 1.7 4,653 33,330 1.3 43,328 110,052 151,553 Pwani Dar es Salaam 388 1.0 388 538 0.8 430 926 818 Dar es Salaam Dodoma 125,858 1.0 125,858 169,992 1.1 185,414 4,012 1.0 3,820 118,442 1.1 125,846 5,213 2.7 14,075 423,517 455,012 Dodoma Iringa 130,008 2.0 260,016 7,414 0.7 5,133 3,627 1.0 3,688 17,577 2.8 49,214 1,802 2.3 4,081 160,427 322,132 Iringa Njombe 127,578 2.0 255,156 1,301 1.2 1,549 1,605 1.2 1,922 904 2.0 1,808 11,807 1.7 20,525 143,195 280,960 Njombe Kagera 93,765 1.4 131,271 9,789 1.1 10,480 2,498 1.2 2,931 452 1.0 456 19,142 1.1 21,056 125,646 166,194 Kagera Kigoma 215,754 2.1 453,083 5,230 2.5 13,320 600 1.6 969 27,234 2.0 54,468 248,817 521,841 Kigoma Kilimanjaro 106,726 2.1 224,124 663 0.7 449 529 1.0 523 13,489 2.7 36,420 1,087 3.9 4,211 1,610 2.0 3,220 124,103 268,947 Kilimanjaro Lindi 90,665 1.2 108,798 29,719 1.1 32,186 22,856 0.7 15,999 143,240 156,983 Lindi Manyara 270,694 1.7 460,180 13,213 1.7 22,396 4,065 1.5 5,977 1,138 1.4 1,596 6,578 2.2 14,472 7,115 1.4 9,679 86 2.0 172 302,889 514,471 Manyara Mara 88,680 1.7 150,756 57,010 1.5 85,553 5,400 0.7 3,644 686 0.9 639 11,143 1.5 16,715 162,919 257,306 Mara Mbeya 205,831 2.7 555,744 4,401 11,012 1,152 1,226 87,604 3.3 289,093 4,446 8,640 303,434 865,715 Mbeya Songwe 178,289 2.5 445,723 29,160 39,033 8,393 13,581 650 1,020 38,277 2.5 95,693 393 380 255,162 595,429 Songwe Morogoro 100,567 1.6 160,907 14,778 0.9 13,394 100 0.8 76 141 1.2 169 295,257 2.0 596,420 410,843 770,966 Morogoro Mtwara 54,578 1.1 60,036 15,748 1.0 15,115 439 0.7 324 26,554 0.7 18,588 97,319 94,063 Mtwara Mwanza 109,868 1.7 186,776 16,349 1.2 19,138 26 0.7 18 3,078 1.4 4,260 108,911 2.0 217,822 238,232 428,014 Mwanza Geita 99,543 1.7 169,223 7,200 1.0 7,514 413 0.9 386 1,032 1.2 1,189 106,227 1.7 180,585 214,413 358,897 Geita Rukwa 256,503 2.5 641,258 9,230 1.2 11,040 17,785 1.2 20,850 7 1.1 8 41,282 2.1 86,692 4,900 1.7 8,185 329,706 768,033 Rukwa Katavi 58,910 1.7 100,147 860 1.3 1,114 103 1.2 120 19 0.9 17 72,560 2.3 166,888 132,452 268,286 Katavi Ruvuma 290,488 3.2 929,560 875 1.0 859 7,000 0.8 5,928 51,652 1.1 58,874 2,782 1.2 3,328 352,796 998,550 Ruvuma Shinyanga 91,764 1.4 128,470 27,177 1.5 41,530 10,614 1.1 11,447 116,654 1.5 174,981 246,209 356,427 Shinyanga Simiyu 187,055 1.3 243,172 62,157 1.3 81,340 1,200 0.8 999 59,242 1.2 71,090 309,655 396,602 Simiyu Singida 179,453 1.1 197,398 71,840 1.2 88,607 9,968 1.7 16,539 40,621 1.1 45,013 11,173 1.2 13,408 313,055 360,965 Singida Tabora 200,614 1.5 300,920 22,137 1.4 31,884 148 0.8 113 114,622 2.1 240,706 337,520 573,624 Tabora Tanga 265,855 1.2 319,025 12,082 1.1 13,780 - - 10,374 2.3 23,860 288,311 356,666 Tanga Jumla 3,726,386 1.7 6,908,318 614,681 1.2 755,832 68,395 1.1 83,374 178,079 1.1 192,659 1,351,239 1.9 2,629,519 38,331 2.1 70,288 5,456 1.9 10,034 5,982,567 10,639,990 Jumla Uwele Mchele Ngano Jumla Tathmini ya Awali ya Uzalishaji (Tani) Kimkoa kwa Msimu wa 2020/2021 (Kufikia Tarehe 31 Mei 2021) Nafaka ( Eneo (Hekta), Tija na Uzalishaji (Tani) kwa Hekta) Mkoa Mahindi Shayiri Mtama Ulezi Chanzo: Tathmini ya HYC 2020/2021 24 26 Kiambatisho Na:1b. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Yasiyonafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei,2021 Chanzo: Tathmini ya HYC 2020/2021 Kiambatisho Na:2. Kiwango cha mvua na mtawanyiko wake kwa kila mwezi katika msimu wa mvua 2020/2021. 28 29 Chanzo: TMA, GeoWRSI 2020/2021 30 Kiambatisho Na:3. Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (SSR) Msimu wa 2020/2021 Chanzo: Tathmini ya Awali ya Uzalishaji wa Mazao ya Chakula Msimu wa 2019/2020 na Upatikanaji wa Chakula kwa Mwaka 2020/2021."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":191,"cells":{"data":{"kind":"string","value":"# Extracted Content 1 Sehemu ya Masoko ya Mazao ya Kilimo Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO Septemba 06-10, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/Kilo 100) Wiki iliyopita Agost 30-Septemba 03 Wiki hii Septemba 06-10 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 41,700 134,000 162,100 86,600 106,600 154,000 59,700 Wiki iliyopita 41,900 133,100 163,400 87,100 102,600 145,900 59,800 Badiliko ▼0.5% ▲0.7% ▼0.8% ▼0.6% ▲3.8% ▲5.3% ▼0.2% Wastani wa Nchi Ujumbe Mkuu Kwa ujumla, zimebadilika kiasi kidogo ikilinganishwa na viwango vya bei wiki iliyopita. Bei za mahindi, maharage, mtama, na viazi zimepungua kwa asilimia 0.5, 0.8, 0.6 na 0.2 mtawalia. Hata hivyo, bei ya mchele,uwele na ulezi iliongezeka kwa kiasi cha asilimia 0.7,3.8 na 5.3 mtawalia. Bei za mazao makuu ya chakula zinategemewa kubadilika kwa viwango vidogo wiki inayofuata. Upatikanaji wa mazao katika masoko ni wa kuridhisha kutokana na kuendelea kwa msimu wa mavuno. Tumbaku: Hadi kufikia tarehe 22 Agosti, 2021 kiasi cha tumbaku kilichouzwa ni Kilo 55,722,247 zenye thamani ya Dola za Marekeni Milioni 86.4. Pamba: Hadi kufikia tarehe 29 Agosti, 2021, pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 138, 482,490. Mbaazi: Hadi kufikia tarehe 02 Septemba, 2021, mbaazi zilizouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,572,532 zenye thamani ya Shilingi Bilioni 4.68 2 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/Kilo 100) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 38,700 142,500 185,000 50,200 49,500 122,500 62,000 Wiki iliyopita 39,300 142,500 182,500 48,500 48,500 120,000 63,000 Badiliko ▼1.6% ►0.0% ▲1.4% ▲3.4% ▲2.0% ▲2.0% ▼1.6% Arusha Wiki hii 47,000 160,000 155,000 67,500 70,000 NA 42,500 Wiki iliyopita 47,500 160,000 155,000 69,000 71,000 NA 42,500 Badiliko ▼1.1% ►0.0% ►0.0% ▼2.2% ▼1.4% ►0.0% Dar es Salaam Wiki hii 50,300 155,000 211,700 85,000 80,000 157,500 52,300 Wiki iliyopita 51,200 155,000 211,700 82,500 76,300 160,000 51,700 Badiliko ▼1.8% ►0.0% ►0.0% ▲2.9% ▲4.6% ▼1.6% ▲1.1% Morogoro Wiki hii 39,500 170,000 180,000 120,000 120,000 160,000 70,000 Wiki iliyopita 39,500 150,000 182,500 120,000 115,000 160,000 74,000 Badiliko ►0.0% ▲11.8% ▼1.4% ►0.0% ▲4.2% ►0.0% ▼5.7% Tanga Wiki hii 44,000 145,000 165,000 85,000 100,000 170,000 45,000 Wiki iliyopita 43,100 145,000 160,000 95,000 100,000 NA 45,500 Badiliko ▲2.0% ►0.0% ▲3.0% ▼11.8% ►0.0% ▼1.1% Ruvuma Wiki hii 26,000 170,000 120,000 NA NA NA 73,500 Wiki iliyopita 27,000 175,000 130,000 NA NA NA 73,800 Badiliko ▼3.8% ▼2.9% ▼8.3% ▼0.4% Iringa Wiki hii 34,000 160,000 145,000 90,000 NA 150000 50,000 Wiki iliyopita 34,000 160,000 145,000 90,000 NA 150000 50,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Njombe Current 36,500 145,000 152,000 NA NA 125,500 31,300 Previous week 36,500 145,000 152,000 NA NA 125,500 31,300 Change ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 31,500 105,000 170,000 NA NA 175,000 65,000 Wiki iliyopita 34,300 105,000 173,800 NA NA 142,500 65,000 Badiliko ▼8.9% ►0.0% ▼2.2% ▲18.6% ►0.0% 3 Sehemu ya Masoko ya Mazao ya Kilimo Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Katavi Wiki hii 33,000 90,000 175,000 60,000 NA 165,000 45,000 Wiki iliyopita 31,300 90,000 175,000 60,000 NA 165,000 45,000 Badiliko ▲5.2% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tabora Wiki hii 35,500 102,500 170,000 145,000 NA 175,000 62,500 Wiki iliyopita 35,500 102,500 170,000 145,000 NA 175,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Kigoma Wiki hii 47,200 93,500 125,000 80,000 NA 145,000 55,000 Wiki iliyopita 47,200 88,500 135,000 80,000 NA 150,000 55,000 Badiliko ►0.0% ▲5.3% ▼8.0% ►0.0% ▼3.4% ►0.0% Kagera Wiki hii 55,000 130,000 130,000 125,000 155,000 155,000 60,000 Wiki iliyopita 54,500 135,000 130,000 125,000 127,500 150,000 60,000 Badiliko ▲0.9% ▼3.8% ►0.0% ►0.0% ▲17.7% ▲3.2% ►0.0% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 125,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲34.2% ►0.0% Manyara Wiki hii 45,000 150,000 135,000 70,000 90,000 125,000 65,000 Wiki iliyopita 45,000 150,000 135,000 70,000 90,000 125,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲3.8% Shinyanga Wiki hii 43,500 110,000 175,000 115,000 105,000 115,000 85,000 Wiki iliyopita 43,500 110,000 177,500 115,000 105,000 115,000 85,000 Badiliko ►0.0% ►0.0% ▼1.4% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 40,000 145,000 167,500 57,500 NA 180,000 57,500 Wiki iliyopita 40,000 145,000 167,500 57,500 NA 180,000 57,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Uganda (bei za jumla) 1,750 1,900 470 500 Uganda (bei za rejareja) 1,900 2,185 820 900 Chanzo: https://farmgainafrica.org/ Tarehe 10 Septemba, 2021 Jedwali 4A: Mauzo ya tumbaku katika msimu wa 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 kwa kampuni AINA YA TUMBAKU KAMPUNI KILO ZA MKATABA MASOKO YALIYOTHAMINISHWA MPAKA SASA (CUMMULATIVE) BELO KG THAMANI(USD) BEI YA WASITANI (USD/KG) (USD) VFC Alliance One Tobacco Tanzania Ltd 20,040,000 410,978 18,857,569 28,307,316 1.50 JTI Leaf Services Ltd 14,460,000 297,865 14,074,601 24,034,375 1.71 Premium Active Tanzania Ltd 16,000,000 287,194 13,488,012 20,740,505 1.54 Pachtec Company Ltd 4,461,838 57,284 2,609,127 3,627,934 1.39 Mo Green International Company Limited 2,800,000 36,017 1,677,408 2,545,870 1.52 Naile Leaf (T) Co. Ltd 2,535,000 43,336 1,851,806 2,775,124 1.50 Grand Tobacco Limited 1,815,000 Magefa Growers Ltd 4,400,000 40,179 1,755,989 2,414,887 1.38 Jespan Company Ltd 760,000 9,865 486,296 661,391 1.36 ENV Services Ltd 800,000 7,932 360,503 520,860 1.44 Biexen Company Limited 29,145 717 29,145 40,041 1.37 JUMLA NDOGO 68,071,838 1,191,367 55,190,456 85,668,303 1.55 DFC Premium Active Tanzania Ltd 500,000 11,022 531,792 698,768 1.31 JUMLA KUU 68,571,838 1,202,389 55,722,247 86,367,071 1.55 5 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 4B: Mauzo ya tumbaku (kimkoa) katika msimu wa masoko 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 Mkoa Kilo za Mkataba Kiasi cha tumbaku kilichonunuliwa Belo Kilo Katavi 7,350,000 141,785 6,229,618 Mbeya 10,280,000 167,660 8,067,643 Songwe 670,000 12,953 624,655 Kigoma 4,705,000 93,825 4,194,878 Tabora 32,546,838 575,479 26,682,758 Shinyanga 9,930,000 162,321 7,648,131 Geita 1,070,000 17,809 871,093 Kagera 70,000 1,180 58,557 Iringa 200,000 2,446 157,631 Singida 1,250,000 15,909 655,493 Jumla ya VFC 68,071,838 1,191,367 55,190,456 Ruvuma (DFC) 500,000 11,022 531,791.96 JUMLA KUU (DFC+VFC) 68,571,838 1,202,389 55,722,247 Jedwali 5: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 16 kuishia tarehe 29Agosti, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 133,918,964 4,563,526 138, 482,490 133,918,964 4,563,526 138, 482,490 Chanzo: Bodi ya Pamba, 2021 6 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali :6 Mauzo ya mbaazi hadi tarehe 25 Agosti 2021 Tarehe Wilaya Chama cha Ushirika Kampuni Kilo Shilingi/Kilo Jumla Ndogo (Shilingi) 11/08/2021 Namtumbo Ushirika B Afrisian Ginning 41,428 1,280 53,027,840 12/08/2021 Tunduru Mtetesi MeTL 150,000 1,300 195,000,000 Mtetesi RBST 210,251 1,290 271,223,790 18/08/2021 Namtumbo Ushirika B MeTL 206,517 1,320 272,602,440 Ushirika B LENIC 200,000 1,320 264,000,000 19/08/2021 Tunduru Asema LENIC 300,000 1,344 403,200,000 Asema LENIC 845,498 1,340 1,132,967,320 25/08/2021 Namtumbo Namtumbo LENIC 819,149 1,380 1,130,425,620 02/09/2021 Tunduru Naluwale MeTL 280,000 1,203 336,840,000 Naluwale LENIC 519,689 1,200 623,626,800 JUMLA KUU 3,572,532 4,682,913,810 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb 7 Sehemu ya Masoko ya Mazao ya Kilimo Habari Muhimu ✓ Mwezi Agosti, Serikali ya Tanzania imetoa jumla ya shilingi bilioni 19 kwa Wakala wa Taifa wa Hifadhi ya Chakula (NFRA) na Bodi ya Nafaka na Mazao Mchanganyiko (CPB) kwa ajili ya ununuzi wa mahindi. ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority Kwa maelezo zaidi wasiliana na: Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: masoko@kilimo.go.tz Simu: +255 686 107 673 / +255 713 309 122"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":192,"cells":{"data":{"kind":"string","value":"# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vr: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vn: REGIONAL REPORT: TABORA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar September 2006 TOC i ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census TABLE OF CONTENTS Table of contents................................................................................................................................................................i Acronyms.......................................................................................................................................................................... v Preface..............................................................................................................................................................................vi Executive summary.........................................................................................................................................................vii Illustrations......................................................................................................................................................................xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION........................................................................................................ 1 1.1 Introduction ...................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................. 1 1.3 Land Area.......................................................................................................................................................... 1 1.4 Climate............................................................................................................................................................... 1 1.4.1 Temperature......................................................................................................................................... 1 1.4.2 Rainfall................................................................................................................................................. 1 1.5 Population ......................................................................................................................................................... 1 1.6 Socio-economic Indicators............................................................................................................................... 1 PART II: INTRODUCTION...................................................................................................................................... 2 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................. 2 2.2 Census Objectives............................................................................................................................................. 2 2.3 Census Coverage and Scope............................................................................................................................ 3 2.4 Legal Authority of the National Sample Census of Agriculture................................................................. 4 2.5 Reference Period .............................................................................................................................................. 4 2.6 Census Methodology........................................................................................................................................ 4 2.6.1 Census Organization............................................................................................................................ 5 2.6.2 Tabulation Plan.................................................................................................................................... 5 2.6.3 Sample Design..................................................................................................................................... 5 2.6.4 Questionnaire Design and Other Census Instruments ........................................................................ 6 2.6.5 Field Pre-Testing of the Census Instruments...................................................................................... 6 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................... 6 2.6.7 Information, Education and Communication (IEC) Campaign.......................................................... 6 2.6.8 Household Listing................................................................................................................................ 7 2.6.9 Data Collection .................................................................................................................................... 7 2.6.10 Field Supervision and Consistency Checks ........................................................................................ 7 2.6.11 Data Processing ................................................................................................................................... 8 - Manual Editing............................................................................................................................... 8 - Data Entry ...................................................................................................................................... 8 - Data Structure Formatting ............................................................................................................. 8 - Batch Validation ............................................................................................................................ 8 - Tabulations..................................................................................................................................... 8 - Analysis and Report Preparations ................................................................................................. 9 - Data Quality................................................................................................................................... 9 2.7 Funding Arrangements.............................................................................................................................. 9 PART III: CENSUS RESULTS AND ANALYSIS.................................................................................................. 10 3.1 Holding Characteristics................................................................................................................................. 10 3.1.1 Type of Holdings............................................................................................................................... 10 3.1.2 Livelihood Activities/Source of Income........................................................................................... 10 3.1.3 Sex and Age of Heads of Households............................................................................................... 14 3.1.4 Number of Household Members....................................................................................................... 14 3.1.5 Level of Education............................................................................................................................. 14 - Literacy ........................................................................................................................................ 14 - Literacy Level for Household Members ..................................................................................... 14 - Literacy Rates for Heads of Households..................................................................................... 15 - Educational Status........................................................................................................................ 15 3.1.6 Off-farm Income................................................................................................................................ 16 TOC ii ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.2 Land Use ...................................................................................................................................................... 16 3.2.1 Area of Land Utilised ........................................................................................................................ 17 3.2.2 Types of Land use.............................................................................................................................. 17 3.3 Annual Crops and Vegetable Production.................................................................................................... 17 3.3.1 Area Planted....................................................................................................................................... 18 3.3.2 Crop Importance................................................................................................................................ 18 3.3.3 Crop Types......................................................................................................................................... 19 3.3.4 Cereal Crop Production..................................................................................................................... 19 3.3.4.1 Maize ............................................................................................................................... 19 3.3.4.2 Paddy ............................................................................................................................... 22 3.3.4.3 Other Cereals................................................................................................................... 23 3.3.5 Roots and Tuber Crops Production................................................................................................... 23 3.3.5.1 Cassava............................................................................................................................ 23 3.3.5.2 Sweet Potatoes................................................................................................................. 26 3.3.6 Pulse Crops Production ..................................................................................................................... 27 3.3.6.1 Beans................................................................................................................................ 27 3.3.7 Oil Seed Production........................................................................................................................... 30 3.3.7.1 Groundnuts ...................................................................................................................... 30 3.3.8 Fruits and Vegetables ........................................................................................................................ 31 3.3.8.1 Onions.............................................................................................................................. 33 3.3.8.2 Tomatoes ......................................................................................................................... 33 3.3.8.3 Amaranths........................................................................................................................ 34 3.3.8.4 Cabbage ........................................................................................................................... 34 3.3.9 Other Annual Crops Production........................................................................................................ 34 3.3.9.1 Tobacco ........................................................................................................................... 34 3.3.9.2 Cotton .............................................................................................................................. 39 3.4 Permanent Crops............................................................................................................................................ 39 3.4.1 Mango ......................................................................................................................................... 40 3.4.2 Palm Oil ......................................................................................................................................... 40 3.4.3 Banana ......................................................................................................................................... 40 3.4.4 Pawpaw ......................................................................................................................................... 41 3.5 Inputs/Implements Use.................................................................................................................................. 42 3.5.1 Methods of land clearing................................................................................................................... 42 3.5.2 Methods of soil preparation............................................................................................................... 42 3.5.3 Improved seeds use............................................................................................................................ 48 3.5.4 Fertilizers use..................................................................................................................................... 48 3.5.4.1 Farm Yard Manure Use................................................................................................... 49 3.5.4.2 Inorganic Fertilizer Use................................................................................................... 50 3.5.4.3 Compost Use ................................................................................................................... 51 3.5.5 Pesticide Use...................................................................................................................................... 51 3.5.5.1 Insecticide Use................................................................................................................. 52 3.5.5.2 Herbicide Use.................................................................................................................. 52 3.5.5.3 Fungicide Use.................................................................................................................. 53 3.5.6 Harvesting Methods........................................................................................................................... 54 3.5.7 Threshing Methods .......................................................................................................................... 54 3.6 Irrigation .................................................................................................................................................... 54 3.6.1 Area planted with annual crops and under irrigation........................................................................ 54 3.6.2 Sources of water used for irrigation.................................................................................................. 55 3.6.3 Methods of obtaining water for irrigation......................................................................................... 55 3.6.4 Methods of water application ........................................................................................................... 56 TOC iii ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.7 Crop Storage, Processing and Marketing ................................................................................................... 56 3.7.1 Crop Storage ...................................................................................................................................... 56 3.7.1.1 Method of Storage........................................................................................................... 56 3.7.1.2 Duration of Storage ......................................................................................................... 58 3.7.1.3 Purpose of Storage........................................................................................................... 58 3.7.1.4 The Magnitude of Storage Loss...................................................................................... 59 3.7.2 Agro processing and by-products...................................................................................................... 59 3.7.2.1 Processing Methods......................................................................................................... 59 3.7.2.2 Main Agro-processing Products...................................................................................... 60 3.7.2.3 Main use of primary processed Products........................................................................ 60 3.7.2.4 Outlet for Sale of Processed Products............................................................................. 61 3.7.3 Crop Marketing.................................................................................................................................. 61 3.7.3.1 Main Marketing Problems............................................................................................... 62 3.7.3.2 Reasons for Not Selling................................................................................................... 62 3.8 Access to Crop Production Services............................................................................................................. 62 3.8.1 Access to Agricultural Credits .......................................................................................................... 62 3.8.1.1 Source of Agricultural Credits ........................................................................................ 63 3.8.1.2 Use of Agricultural Credits............................................................................................. 63 3.8.1.3 Reasons for not using agricultural credits....................................................................... 63 3.8.2 Crop Extension .................................................................................................................................. 65 3.8.2.1 Sources of crop extension messages............................................................................... 65 3.8.2.2 Quality of extension ........................................................................................................ 66 3.9 Access to Inputs ............................................................................................................................................. 66 3.9.1 Inorganic Fertilisers .......................................................................................................................... 66 3.9.2 Improved Seeds ................................................................................................................................. 67 3.9.3 Insecticides and Fungicide ................................................................................................................ 67 3.10 Tree Planting................................................................................................................................................... 68 3.11 Irrigation and Erosion Control Facilities ................................................................................................... 69 3.12 Livestock Results............................................................................................................................................ 72 3.12.1 Cattle Production .............................................................................................................................. 72 3.12.1.1 Cattle Population............................................................................................................. 72 3.12.1.2 Herd size.......................................................................................................................... 72 3.12.1.3 Cattle Population Trend .................................................................................................. 73 3.12.1.4 Improved Cattle Breeds................................................................................................... 73 3.12.2 Goat Production................................................................................................................................. 73 3.12.2.1 Goat Population............................................................................................................... 73 3.12.2.2 Goat Herd Size ................................................................................................................ 74 3.12.2.3 Goat Breeds ..................................................................................................................... 74 3.12.2.4 Goat Population Trend .................................................................................................... 74 3.12.3 Sheep Production............................................................................................................................... 74 3.12.3.1 Sheep Population............................................................................................................. 74 3.12.3.2 Sheep Population Trend .................................................................................................. 75 3.12.4 Pig Production ................................................................................................................................... 75 3.12.4.1 Pig Population Trend....................................................................................................... 75 3.12.5 Chicken Production ........................................................................................................................... 75 TOC iv ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.12.5.1 Chicken Population ......................................................................................................... 76 3.12.5.2 Chicken Population Trend............................................................................................... 76 3.12.5.3 Chicken Flock Size.......................................................................................................... 76 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................. 82 3.12.6 Other Livestock ................................................................................................................................. 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming...................................................................................................................... 83 3.12.8 Access to Livestock Services ............................................................................................................ 83 3.12.8.1 Access to livestock extension Services........................................................................... 83 3.12.8.2 Access to Veterinary Clinic ............................................................................................ 84 3.12.8.3 Access to village watering points/dam ........................................................................... 84 3.12.9 Animal Contribution to Crop Production.......................................................................................... 85 3.12.9.1 Use of Draft Power.......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure .............................................................................................. 85 3.12.9.4 Use of Compost ............................................................................................................. 86 3.12.10 Fish Farming...................................................................................................................................... 86 3.13 Poverty Indicators......................................................................................................................................... 87 3.13.1 Access to Infrastructure and Other Services..................................................................................... 87 3.13.2 Type of Toilets................................................................................................................................... 87 3.13.3 Household’s assets............................................................................................................................. 87 3.13.4 Sources of Light Energy.................................................................................................................... 91 3.13.5 Sources of Energy for Cooking......................................................................................................... 91 3.13.6 Roofing Materials.............................................................................................................................. 91 3.13.7 Access to Drinking Water ................................................................................................................. 92 3.13.8 Food Consumption Pattern................................................................................................................ 92 3.13.8.1 Number of Meals per Day............................................................................................... 92 3.13.8.2 Meat Consumption Frequencies...................................................................................... 93 3.13.8.3 Fish Consumption Frequencies....................................................................................... 93 3.13.9 Food Security..................................................................................................................................... 93 3.13.10 Main Source of Cash Income............................................................................................................ 94 PART IV: TABORA PROFILES ............................................................................................................................... 98 4.1 Region Profile ................................................................................................................................................. 98 4.2 District Profiles............................................................................................................................................... 98 4.2.1 Nzega ................................................................................................................................................. 98 4.2.2. Igunga ..............................................................................................................................................100 4.2.3 Uyui..................................................................................................................................................102 4.2.4 Urambo ............................................................................................................................................104 4.2.5 Sikonge ............................................................................................................................................106 4.2.6 Tabora Urban...................................................................................................................................108 ACRONYMS v __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ____________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics, Tanzania Mainland and the Office of the Chief Government Statistician, Tanzania Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the President’s Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (data on household characteristics and livestock count were collected in 1993/1994 while data on crop area and production were collected in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Tabora region data disaggregated to district level. Due to numerous variables collected, the analysis is based on the most important smallholder variables. More variables can be found in the table of results annex. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Special thanks should go to all those who in one-way or the other contributed to the success of the survey. In particular, I would like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician, Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Finally, let me extend my sincere gratitude to all professional staff of the National Bureau of Statistics and Office of the Chief Government Statistician, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. I am also indepted to the respondents, particularly the heads of households, for spending much of their valuable time in providing data and all necessary information during enumeration. Certainly without their dedication, the census would not have been successful. Albina A. Chuwa Director General, National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Tabora region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings on agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Tabora region. Included are activities’ indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Tabora region were 235,917 out of which 148,046 (62.8%) were involved in growing crops only, 296 (0.1%) rearing livestock only, and 87,575 (37.1%) were involved in crop production as well as livestock keeping. In summary, Tabora region had 235,621 households involved in crop production and 87,871 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock keeping/herding ,permanent crop farming, remittances and fishing/hunting and gathering. The region had a literacy rate of 52.5 percent. The highest literacy rate was in Tabora Urban district (67.4%) followed by Urambo district (56.0%) and Sikonge district (55.7%). Igunga, Uyui and Nzega districts had the lowest literacy rates of 53.3 percent, 51.8 percent and 46.0 percent respectively. The literacy rate for the heads of households in the region was 58.9 percent. The number of heads of agricultural households with formal education in Tabora region was 135,084 (57.3%), those without formal education were 97,767 (41.4%) and those with only adult education were 3,066 (1.3%). The majority of heads of agricultural households (54%) had primary level education whereas only 3 percent had higher than post primary level education. In Tabora region, of the households with at least one household member engaged in off-farm income generating activity, 117,453 household members (50%) had only one member engaged in an off-farm income generating activity, 52,284 (22%) had two members involved in off-farm income generating activities and 37,162 (16%) had more than two members involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 899,225 ha. The regional average land area utilised for crop production per crop growing household was only 2.6 ha. This figure is slightly above the national average of 2.0 hectares. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Planted Area The area planted with annual crops and vegetables was 532,615 hectares. The area planted with permanent crops was 9,929 hectares (1.8% of the total planted area). An estimated area of 347,455 ha (65.2% of the total planted area with annual and vegetable crops) was with cereals, followed by 69,862 hectares (13.1%) of oil seeds, 54,948 ha (10.3%) of cash crops, 31,535 ha (5.9%) of root and tuber crops, 25,911 ha (4.9%) of pulses and 2,904 ha (0.5%) of fruits and vegetables. Maize Maize was the dominant annual crop grown in Tabora region and it had a planted area 3.4 times greater than groundnuts, which had the second largest planted area. The area planted with maize constitutes 44 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were paddy, sorghum, tobacco, cotton, cassava, beans, sweet potatoes, bulrush millet, finger millet, simsim and sunflower. There was 62 percent decrease in maize production in 1996/97 followed by a 36 percent increase in maize production the following year (1997/98). The total production of maize in 2002/03 was 143,122 tonnes. The average area planted with maize per household ranged from 0.8 hectares in Nzega and Tabora Urban to 1.3 hectares in Igunga District. Igunga district had the largest planted area for maize (56,579 ha) followed by Nzega (52,986 ha), Uyui (46,418 ha), Urambo (46,076 ha), Sikonge (22,958 ha) and Tabora (7,844 ha). Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tabora region during the long rainy season was 92,037. This represented 39 percent of the total crop growing households in Tabora Region in the long rainy season. Cassava The area planted with cassava was larger than that of any other root and tuber crop in Tabora region accounted for 4 percent of the total area planted with annual crops and vegetables and accounted for 68 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 5,847 tonnes. The most cultivated fruit and vegetable crop was onions with a production of 2,550 tonnes (44% of the total fruits and vegetables produced) followed by tomatoes 2,522 tonnes (43%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The smallholders’ planted area with permanent crops was 9,929 hectares which was 1.9 percent of the area planted with crops in the region. The most important permanent crop was mango which accounted for 38 percent of the total area planted with permanent crops followed by palm oil (22%), banana (16%) and pawpaw (7%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix Improved Seeds The planted area using improved seeds was 88,125 ha which represented 17 percent of the total area planted with annual crops and vegetables. Use of Fertilizers Most annual crop growing households did not use any fertilisers. The area planted without fertiliser for annual crops was 352,800 hectares representing 66 percent of the total area planted with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 101,423 ha which represented 56% of the planted area applied with fertilisers. This was followed by inorganic fertilizers (64,675 ha, 36%). Compost manure was used on a small area which represented only 8 percent of the area planted with fertilizers. Irrigation In Tabora region, the area of annual crops and vegetables under irrigation was 34,866 ha representing 7 percent of the total planted area. Crop Storage There were 217,899 crop growing households (92.4% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 206,605 households storing 28,060 tonnes as of 1st January 2004. This was followed by paddy (76,850 households and 11,758 tonnes), groundnuts /bambara nuts (111,290 households and 6,695 tonnes) and sorghum and millet (21,828 households and 6,195 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 131,403 which represent 55.7 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Urambo (80.3%) followed by Sikonge (62.2%), Uyui (53.0%), Igunga (47.9%), Tabora Urban (45.5%) and Nzega (42.1%). Agricultural Credit In Tabora region, few agricultural households (25,655, 10.9%) accessed credit, out of which 24,679 (96%) were male- headed households and 977 (4%) were female headed households. In Nzega, Igunga and Urambo districts only male headed households got credit for agriculture purposes, whereas in Sikonge and Tabora Urban both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 62,956 (27% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.108). Tabora Urban had a relatively high proportion of households that received crop extension messages (73%), followed by Uyui (30%), Sikonge (27%), Urambo (25%), Nzega (24%) and Igunga (19%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 5,399. This number represented 2.3 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Tabora Urban District (7.1%) followed by Uyui (4.9%), Nzega (2.5%), Urambo (1.8%), Sikonge (1.8%) and Igunga (0.2%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 1,568,691. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region had 9.1 percent of the total cattle population on Tanzanian Mainland. The number of indigenous cattle was 1,566,169 head (98.8% of the total number of cattle in the region), 1,851 (0.12 %) were dairy breeds and only 671 (0.04 %) were beef breeds. Goats The number of goat-rearing-households in the region was 65,167 (27.6 % of all agricultural households) with a total of 718,996 goats giving an average of 11 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 28,126 (12% of all agricultural households) with a total of 235,213 sheep giving an average of 8 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,614 (1.2% of the total agricultural households) rearing about 6,286 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 168,339 raising 2,507,469 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country Tabora ranked fourth out of the 21 Mainland regions. Use of Draft Power The region had 370,495 oxen and they were found in all districts as follows: Igunga (162,466), Nzega (120,742), Uyui (42,341), Urambo (25,202), Sikonge (15,992) and Tabora Urban (3,752). Tabora region has 6 percent of the total 4,195,100 head of oxen found on the Mainland and were used to cultivate 223,878 hectares of land. Fish Farming The number of households involved in fish farming was 222 (0.1 percent of the total agricultural households in the region). Sikonge and Uyui were the leading districts each with 98 agricultural households involved in fish farming (44%) followed by Tabora Urban 26 (2%). Fish farming was not practiced in Nzega, Igunga and Urambo districts. iv) Poverty Indicators Availability of Toilets It was estimated that 81.2 percent of all rural agricultural households used the traditional pit latrines, 1.0 percent used flush toilets and 0.8 percent used improved pit latrines. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represented 16.9 percent of the total agriculture households in the region. Household Assets Out of all assets bicycle were owned by most households (69.7% of households) followed by radio (53.7%), iron (17.8%), wheelbarrow (5.4%), vehicle (1.4%), mobile phone (1.0%), television/video (0.9 and landline phone (0.2%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xi Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 84 percent of the total rural households used this source of energy followed by hurricane lamp (10.1%), pressure lamp (3.4%), firewood (2.0%), mains electricity (0.5%), candle (0.2%), solar (0.15%), and gas or biogas (0.06%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.8 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.7%). The rest of energy sources accounted for 2.9 percent. These were parrafin/kerosene (1.2%), crop residues (0. 8%), bottled gas (0.2%), livestock dung (0.13%), mains electricity (0.11%), solar (0.06%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 70.1 percent of the rural agricultural households followed by grass/mud (14.9%). This was closely followed by iron sheets (13.8%). Other roofing materials are tiles (0.6%), asbestos (0.3%), concrete (0.1%) and others (0.3%). Number of Meals per Day About 58.2 percent of the holders in the region took three meals per day, 37.7 percent took two meals, 3.2 percent took one meal and 0.9 percent took four meals. Food Security Households which had never experienced food shortage represented 44.8 percent of the total number of agriculture households in the region. Households which seldom had problems in satisfying their food needs represented 32.4 percent and the households which were often faced with food shortage represented 8.7 percent. Those with little problems represented 7.2 percent and whilst about 6.9 percent of agriculture households always faced food shortages problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 22.8 percent of all rural agricultural households. The second main cash income earning activity was casual labor (20.9%) followed by selling of cash crops (16.0%), businesses (11.0%), sale of livestock (10.3%) and sale of forest products (7.5%). Other income earning activities were cash remittances (5.0%), employment (2.2%), sale of livestock products (1.1%) and fishing (0.2%). ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ...........................................................................................................................................…5 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 10 3.2 Area, Production and Yield of cereal crops.........................................................................................................19 3.3 Area Planted and Quantity Harvested and Yield of Root and Tuber Crop.........................................................23 3.4 Area, Quantity Harvested and Yield of Pulses....................................................................................................26 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops......................................................................................30 3.6 Area, Production and Yield of Fruits and Vegetables.........................................................................................31 3.7 Land Clearing Methods........................................................................................................................................42 3.8 Planted Area by Type of Fertiliser Use and District ...........................................................................................49 3.9 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District.......................... 49 3.10 Number of Households Storing Crops by Estimated Storage Loss and District ................................................59 3.11 Reasons for Not Selling Crop Produce................................................................................................................62 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 62 3.13 Access to Inputs....................................................................................................................................................66 3.14 Total Number of Households and Chickens Raised by Flock Size ....................................................................76 3.15 Head Number of Other Livestock by Type of Livestock and District................................................................82 3.16 Mean distances from holders dwellings to infrastructure and services by districts ...........................................87 3.17 Number of Households by Number of meals the Household normally has per Day and District .................... 93 List of Charts 3.1 Agricultural Households by Type....................................................................................................................... 10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 14 3.3 Percentage Distribution of Population by Age and Sex – Tabora Region..........................................................14 3.4 Percentage Literacy Level of Household Members by District..........................................................................14 3.5 Literacy Rates for Heads of Household by Sex and District – Tabora Region ..................................................15 3.6 Percentage of Persons Aged 5 years and above by Educational Status..............................................................15 3.7 Percentage of Population Aged 5 years and Above by District and Education Status.......................................15 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 15 3.9 Number of Households by Number of Members with Off Farm Income...........................................................16 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities..................................16 3.11 Utilized and Usable Land per Household by District..........................................................................................17 3.12 Percentage Distribution of Land Area by Type of Land Use..............................................................................17 3.13 Area Planted with Annual Crops (ha)..................................................................................................................17 3.14 Area Planted with Annual Crops by District.......................................................................................................18 3.15 Area Planted with Annual Crops per Household by District ..............................................................................18 3.16 Planted Area (ha) for the Main Annual Crops (ha) – Tabora Region.................................................................18 3.17 Planted Area (ha) per Household by Selected Crops – Tabora Region..............................................................18 3.20 Area Planted and Yield of Major Cereal Crops...................................................................................................19 3.21 Time Series Data on Maize Production – Tabora Region...................................................................................19 3.22 Maize: Total Area Planted and Planted Area per Household by District ...........................................................19 3.23 Time Series of Maize Planted Area and Yield – Tabora Region........................................................................22 3.24 Total Planted Area and Area of Paddy per Household by District .....................................................................22 3.25 Time Series Data on Paddy Production – Tabora Region...................................................................................22 3.26 Time Series of Paddy Planted Area and Yield – Tabora Region........................................................................22 3.27 Area Planted With Sorghum, Bulrush Millet and Finger Millet District............................................................23 3.28 Area Planted and Yield of Major Root and Tuber Crops....................................................................................23 3.29 Area planted with Cassava during the census/survey years................................................................................23 3.30 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................26 3.31 Cassava Planted Area per Cassava Growing Households by District ................................................................26 3.32 Total Area Planted with Sweet Potatoes and Planted Area per Household by District......................................26 3.33 Area Planted and Yield of Major Pulse Crops ....................................................................................................27 3.34 Percent of Bean Planted Area and Percent of Total Land with Beans by District .............................................27 3.35 Area Planted with Beans per Household by District...........................................................................................27 3.36 Time Series Data on Bean Production – Tabora Region.....................................................................................27 3.37 Time Series of Beans Planted Area and Yield - Tabora......................................................................................30 3.38 Area Planted and Yield of Major Oil Seed Crops...............................................................................................30 3.39 Time Series Data on Groundnut production – Tabora Region............................................................................30 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.40 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District .........................31 3.41 Area Planted per Groundnut Growing Household by District (Long Rainy Season).........................................31 3.42 Area Planted and Yield of Fruit and Vegetables.................................................................................................31 3.43 Percent of Onions Planted Area and Percent of Total Land with Onions by District ........................................33 3.44 Area Planted per Onions Growing Household by District..................................................................................33 3.45 Percent of Tomatoes Planted Area and Percent of Total Land with tomato by District ....................................33 3.46 Area Planted per Tomato Growing Household by District.................................................................................33 3.47 Percent of Amaranths Planted Area and Percent of Total Land with Amaranths by District............................34 3.48 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ...................................34 3.49 Area planted with Annual Cash Crops ................................................................................................................34 3.50 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................34 3.51 Area Planted Annual and Permanent Crops ........................................................................................................39 3.52 Area Planted with the Main Permanent Crops ....................................................................................................39 3.53 Percent of Area Planted and Average Planted Area with Permanent Crops by District ....................................39 3.54 Percent of Area Planted with Mango and Average Planted Area per Household by District............................40 3.55 Percent of Area Planted with Palm Oil and Average Planted Area per Household by District.........................40 3.56 Percent of Area Planted with Banana and Average Planted Area per Household by District ...........................41 3.57 Percent of Area Planted with Pawpaw and Average Planted Area per Household by District..........................41 3.58 Number of Households by Method of Land Clearing.........................................................................................41 3.59 Area Cultivated by Cultivation Method...............................................................................................................42 3.60 Area Cultivated by Method of Cultivation and District......................................................................................42 3.61 Planted Area of Improved Seeds – Tabora Region .............................................................................................48 3.62 Planted Area with Improved Seed by Crop Type................................................................................................48 3.63 Percentage of Crop Type Planted Area with Improved Seed – Annuals............................................................48 3.64 Area of Fertilizer Application by Type of Fertilizer ...........................................................................................48 3.65 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 48 3.66 Planted Area with Farm Yard Manure by Crop Type – Tabora Region.............................................................49 3.67a Percent of crop type planted with Farm Yard Manure – Annuals ......................................................................49 3.67b Proportion of Planted Area Applied with Farm Yard Manure by District – Tabora Region.............................50 3.68 Planted Area with Inorganic Fertilizer by Crop type – Tabora Region..............................................................50 3.69a Percentage of Planted Area with Inorganic Fertilizer by Crop Type – Tabora Region .....................................50 3.69b Proportion of Planted Area Applied with Inorganic Fertilizer by District – Tabora Region.............................50 3.70a Planted Area with Compost Manure by Crop Type – Tabora Region................................................................51 3.70b Percentage of Planted Area with Compost by Crop Type ..................................................................................51 3.70c Proportion of Planted Area Applied with Compost by District..........................................................................51 3.71 Planted area (ha) by Pesticide use........................................................................................................................51 3.72 Planted Area applied with Insecticides by Crop Type ........................................................................................52 3.73 Percentage of Crop Type Planted Area applied with insecticides ......................................................................52 3.74 Percentage of Planted Area applied with Insecticides by District ......................................................................52 3.75 Planted Area applied with herbicides by Crop Type...........................................................................................52 3.76 Percentage of Crop Type Planted Area applied with herbicides.........................................................................53 3.77 Proportion of Planted Area applied with Herbicides by District – Tabora Region............................................53 3.78 Planted Area applied with Fungicides by Crop Type..........................................................................................53 3.79 Percentage of Crop Type Planted Area applied with Fungicides .......................................................................53 3.80 Proportion of Planted Area applied with Fungicides by District – Tabora Region............................................54 3.81 Area of Irrigated Land..........................................................................................................................................54 3.82 Planted Area and Percentage of Planted Area with Irrigation by District..........................................................54 3.83 Time Series of Households with Irrigation – Tabora..........................................................................................55 8.84 Number of Households with Irrigation by Source of Water...............................................................................55 3.85 Number of Households by Method of Obtaining Irrigation Water.................................................................... 55 3.86 Number of Households with Irrigation by Method of Field Application...........................................................55 3.87 Number of Households and Quantity Stored by Crop Type – Tabora Region...................................................56 3.88 Number of households by Storage Methods – Tabora Region .......................................................................... 56 3.89 Number of households by method of storage and District (based on the most important household crop)..... 56 3.90 Normal Length of Storage for Selected Crops ....................................................................................................58 3.91 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ...................................................58 3.92 Number of Households by Purpose of Storage and Crop Type..........................................................................58 3.93a Households Processing Crops by District............................................................................................................59 3.93b Percent of Households Processing Crops by District..........................................................................................59 3.94 Percent of Crop Processing Households by Method of Processing................................................................... 60 3.95 Percent of Households by Type of Main Processed Product ..............................................................................60 3.96 Number of Households by Type of By-product..................................................................................................60 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.97 Use of Processed Product.....................................................................................................................................60 3.98 Percentage of Households Selling Processed Crops by District.........................................................................61 3.99 Location of Sale of Processed Products...............................................................................................................61 3.100 Percentage of Households Selling Processed Products by Outlet for Sale and District ....................................61 3.101 Number of Crop Growing Households Selling Crops by District ......................................................................61 3.102 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ....................62 3.103 Percentage Distribution of Households Receiving Credits by Main Source......................................................63 3.104 Number of Households Receiving Credits by Main Source of Credits and District..........................................63 3.105 Proportion of Households Receiving Credit by Main Purpose of the Credit .....................................................63 3.106 Reasons for Not using Credit...............................................................................................................................63 3.107 Number of Households Receiving Extension Advice.........................................................................................65 3.108 Number of Households that Received Extension by District..............................................................................65 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider..................................65 3.110 Number of Households that Received Extension by Reported Quality of Services...........................................65 3.111 Number of Households by Source of Inorganic Fertilizer ..................................................................................66 3.112 Number of Households Reporting Distance to Source of Inorganic Fertilizer...................................................66 3.113 Number of Households by Source of Improved Seed.........................................................................................67 3.114 Number of Households reporting Distance to source of Improved Seed ...........................................................67 3.115 Number of Households by Source of Insecticide/Fungicide...............................................................................67 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides............................................67 3.117 Number of Households with Planted Trees.........................................................................................................68 3.118 Number of Planted Trees by Species...................................................................................................................68 3.119 Number of Trees Planted by Smallholders by Species and District ...................................................................68 3.120 Number of Trees Planted by Location.................................................................................................................68 3.121 Number of Households by purpose of Planted Trees..........................................................................................69 3.122 Number of Households with Erosion Control/Water Harvesting Facilities .......................................................69 3.123 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............69 3.124 Number of Erosion Control/Water Harvesting structures by Type of Facility...................................................69 3.125 Total Number of Cattle by District......................................................................................................................72 3.126 Numbers of Cattle by Type and District..............................................................................................................72 3.127 Cattle Population Trend .......................................................................................................................................73 3.128 Improved Cattle Population Trend.......................................................................................................................73 3.129 Total Number of Goats by District .....................................................................................................................73 3.130 Goat Population Trend.........................................................................................................................................74 3.131 Total Number of Sheep by District......................................................................................................................74 3.132 Sheep Population Trend.......................................................................................................................................75 3.133 Total Number of Pigs by District.........................................................................................................................75 3.134 Pig Population Trend............................................................................................................................................75 3.135 Total Number of Chicken by District ..................................................................................................................76 3.136 Chicken Population Trend ...................................................................................................................................76 3.137 Number of Improved Chicken by Type and District...........................................................................................82 3.138 Improved Chicken Population Trend...................................................................................................................82 3.139 Percentage Keeping Households that Reported Tsetse flies and Ticks Problems by District............................82 3.140 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............83 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........83 3.142 Number of Households by Distance to Veterinary Clinic...................................................................................84 3.143 Number of Households by Distance to Veterinary Clinic and District...............................................................84 3.144 Number of Households by Distance to Village Watering Point .........................................................................84 3.145 Number of Households by Distance to village Watering Point and District......................................................84 3.146 Number of Households using Draft Animals ......................................................................................................85 3.147 Number of Households using Draft Animals by District....................................................................................85 3.148 Number of Households using Organic Fertilizer.................................................................................................85 3.149 Area of Application of Organic Fertilizer by District .........................................................................................85 3.150 Number of Households Practicing Fish Farming – Tabora.................................................................................86 3.151 Number of Households Practicing Fish Farming by District – Tabora ..............................................................86 3.152 Fish Production.....................................................................................................................................................86 3.153 Agricultural Households by Type of Toilet Facility .......................................................................................... 87 3.154 Percentage Distribution of Households Owning the Assets................................................................................87 3.155 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................91 3.156 Percentage Distribution of Households by Main Source of Energy for Cooking ..............................................91 3.157 Percentage Distribution of Households by Type of Roofing Material ...............................................................91 3.158 Percentage Distribution of Households With Grass/Leaves Roofs by District ..................................................91 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.159 Percentage Distribution of the Number of Households by Main Source of Income..........................................92 3.160 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season....92 3.161 Number of Agriculture Households by Number of Meals per day.....................................................................92 3.162 Number of Households by Frequency of Meat and Fish Consumption..............................................................93 3.163 Number of Households by level of Food Availability ........................................................................................93 3.164 Percentage of Households reporting food availability Status by District...........................................................94 3.165 Percentage Distribution of the Number of Households by Main Source of Income..........................................94 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 11 3.2 Number of Agricultural Households per Square Km of Land by District..........................................................11 3.3 Number of Crop Growing Households by District..............................................................................................12 3.4 Percent of Crop Growing Households by District...............................................................................................12 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................13 3.6 Percent of Crop and Livestock Households by District ......................................................................................13 3.7 Utilized Land Area Expressed as a Percent of Available Land ..........................................................................20 3.8 Total Planted Area (annual crops) by District.....................................................................................................20 3.9 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................21 3.10 Planted Area and Yield of Maize by District ......................................................................................................24 3.11 Area Planted per Maize Growing Household......................................................................................................24 3.12 Planted Area and Yield of Paddy by District ......................................................................................................25 3.13 Area Planted per Paddy Growing Household......................................................................................................25 3.14 Planted Area and Yield of Cassava by District ...................................................................................................28 3.15 Area Planted per Cassava Growing Household...................................................................................................28 3.16 Planted Area and Yield of Beans by District.......................................................................................................29 3.17 Area Planted per Beans Growing Household......................................................................................................29 3.18 Planted Area and Yield of Groundnuts by District .............................................................................................32 3.19 Area Planted per Groundnuts Growing Household.............................................................................................32 3.20 Planted Area and Yield of Onions by District.....................................................................................................35 3.21 Area Planted per Onions Growing Household ....................................................................................................35 3.22 Planted Area and Yield of Tomatoes by District.................................................................................................36 3.23 Area Planted per Tomatoes Growing Household................................................................................................36 3.24 Planted Area and Yield of Amaranths by District...............................................................................................37 3.25 Area Planted per Amaranths Growing Household ..............................................................................................37 3.26 Planted Area and Yield of Tobacco by District...................................................................................................38 3.27 Area Planted per Tobacco Growing Household..................................................................................................38 3.28 Area Planted per Cotton Growing Household.....................................................................................................43 3.29 Planted Area and Yield of Cotton by District......................................................................................................43 3.30 Planted Area and Yield of Mango by District.................................................................................................... 44 3.31 Area Planted per Mango Growing Household ....................................................................................................44 3.32 Planted Area and Yield of Palm Oil by District..................................................................................................45 3.33 Area Planted per Palm Oil Growing Household .................................................................................................45 3.34 Planted Area and Yield of Banana by District ....................................................................................................46 3.35 Area Planted per Banana Growing Household....................................................................................................46 3.36 Planted Area and Yield of Pawpaw by District...................................................................................................47 3.37 Area Planted per Pawpaw Growing Household ..................................................................................................47 3.38 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..................................57 3.39 Area Planted and Percent of Total Planted Area with Irrigation by District ......................................................57 3.40 Percent of households storing crops for 3 to 6 weeks by district........................................................................64 3.41 Number of Households and Percent of Total Households Selling Crops by District........................................ 64 3.42 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .....70 3.43 Number and Percent of Crop Growing Households using Improved Seed by District .....................................70 3.44 Number and percent of smallholder planted trees by district..............................................................................71 3.45 Number and Percent of Households with water Harvesting Bunds by District..................................................71 3.46 Cattle population by District as of 1st Octobers 2003.........................................................................................77 3.47 Cattle Density by District as of 1st October 2003...............................................................................................77 3.48 Goat population by District as of 1st Octobers 2003 ..........................................................................................78 3.49 Goat Density by District as of 1st October 2003.................................................................................................78 3.50 Sheep population by District as of 1st Octobers 2003 ........................................................................................79 3.51 Sheep Density by District as of 1st October 2003...............................................................................................79 3.52 Pig population by District as of 1st Octobers 2003.............................................................................................80 3.53 Pig Density by District as of 1st October 2003 ...................................................................................................80 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.54 Number of Chickens by District as of 1st October 2003 ....................................................................................81 3.55 Density of Chickens by District as of 1st October 2003.....................................................................................81 3.56 Number and Percent of Households Infected with Ticks by District .................................................................88 3.57 Number and Percent of Households Using Draft Animals by District...............................................................88 3.58 Planted Area and Percent of Planted are with Farm Yard Manure application by District................................89 3.59 Planted Area and Percent of Planted are with Compost application by District ................................................89 3.60 Number and Percent of Households Practicing Fish Farming by District..........................................................90 3.61 Number and Percent of Households Without Toilets by District .......................................................................90 3.62 Number and Percent of Households using Grass/Leaves for roofing material by District ................................95 3.63 Number and Percent of Households eating 3 meals per day by District ............................................................95 3.64 Number and Percent of Households eating Meat Once per Week by District ...................................................96 3.65 Number and Percent of Households eating Fish Once per Week by District.....................................................96 3.66 Number and percent of Households Reporting food insufficiency by District ..................................................97 INTRODUCTION Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Tabora region is situated at the Midwest part of Tanzania between 40 and 70degrees below the Equator and 310 – 430 degrees East of the Greenwich Meridian. The region lies on the central plateau whereby in the north east it shares the border with Shinyanga region, on the western side it borders Kigoma while in the south it shares the border with Rukwa and Mbeya regions. The region comprises six districts of Nzega, Igunga, Uyui, Urambo, Sikonge, and Tabora Urban. The region headquarters is located in Tabora Urban. 1.3 Land Area The region has an area of 76,151 square kilometers, of which 194.3 square kilometers (1,943,280 ha) are arable land. 1.4 Climate 1.4.1 Temperature The dominant climate is warm with temperatures reaching the peak during September and October just before the long rainy season starts. The Central Plateau has the average temperature of 230C with the minimum temperature of 17oC and maximum temperature of 280C. 1.4.2 Rainfall The region has one rainy season, the long rainy seasons. The season falls almost entirely between November and May. The total annual precipitation decreases from West to East. In the west the rainfall total over 1,000mm while in the East it drops to 700mm or less 1.5 Population According to the 2002 Population and Housing Census, there were 1,717,908 inhabitants in Tabora region. The population of Tabora region ranked 7th out of the 21 regions on Tanzania Mainland. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 1998 was estimated to be TShs 196,803 million with a per capita income of 151,208 shillings. Tabora region is famous for forestry industry and game reserves. The region has 34,698 square kilometers of forestry reserves and 17,122 square kilometers of game reserves. The region is also famous for producing both food and cash crops. The main food crops produced in Tabora region include: maize, paddy, sorghum and finger millet. The main cash crops include cotton and tobacco. Livestock keeping is also a very important economic activity. The main livestock raised are cattle, goats and sheep. INTRODUCTION Tanzania Agriculture Sample Census 2 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION Tanzania Agriculture Sample Census 3 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION Tanzania Agriculture Sample Census 4 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION Tanzania Agriculture Sample Census 5 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION Tanzania Agriculture Sample Census 6 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION Tanzania Agriculture Sample Census 7 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION Tanzania Agriculture Sample Census 8 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations INTRODUCTION Tanzania Agriculture Sample Census 9 Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS This part of the report presents the results of the census for Tabora region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Tabora region was 235,917. The largest number of agricultural households was in Nzega (65,566) followed by Urambo (54,120), Igunga (45,141), Uyui (41,318), Sikonge, (19,514) and Tabora Urban (10,258) (Map 3.1). The highest density of households was found in Nzega (27/km2) followed by Igunga (17/km2) (Map 3.2). Most households (148,046, 62.8%) were involved in growing crops only, 296 (0.1%) rearing livestock only, and 87,575 (37.1%) were involved in crop production as well as livestock keeping (Chart 3.1) (Maps 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Tabora region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock keeping/herding, permanent crop farming, remittances and fishing/hunting and gathering (Table 3.1). Annual crop farming was the most important source of livelihood for all districts while fishing/hunting and gathering was the least important source of income to all districts. Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permane nt Crop Farming Livestock Keeping / Herding Off Farm Income Remitta nces Fishing / Hunting & Gathering Tree / Forest Resources Nzega 1 5 3 4 6 7 2 Igunga 1 5 4 2 6 7 3 Uyui 1 4 3 2 6 7 5 Urambo 1 5 4 2 6 7 3 Sikonge 1 5 2 3 6 7 4 Tabora Urban 1 4 3 2 6 7 5 Total 1 5 4 2 6 7 3 Chart 3.1 Agriculture Households by Type - Tabora Crops & Livestock 37% Crops Only 63% Livestock Only 0% Tabora Urban Uyui Urambo Sikonge Igunga Nzega 15 9 7 2 17 27 24 to 30 18 to 24 12 to 18 6 to 12 0 to 6 Igunga Nzega Tabora Urban Uyui 45,141 65,566 41,318 10,258 19,514 54,120 Urambo Sikonge 56,000 to 70,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.01 TABORA Total Number of Agriculture Households by District Map 3.02 TABORA Number of Agricultural Households Households Per Square Kilometer of Land by District RESULTS 11 Tabora Urban Uyui Sikonge Igunga Nzega Urambo 99.8% 99.7% 99.7% 99.7% 100% 100% 99.94 to 100 99.88 to 99.94 99.82 to 99.88 99.76 to 99.82 99.7 to 99.76 Sikonge Tabora Urban Uyui Igunga Nzega 19,464 10,233 41,212 45,025 65,566 54,120 Urambo 56,000 to 70,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Tanzania Agriculture Sample Census Number of crop Growing Households Number of crop Growing Households Percent of crop Growing Households Percent of crop Growing Households Map 3.3 TABORA Number of crop Growing Households by District Map 3.4 TABORA Percent of crop Growing Households by District RESULTS 12 Tabora Urban Uyui Sikonge Igunga Nzega 22.2 35.5 29.7 52 42.2 25.4 Urambo 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 Tabora Urban Sikonge Urambo Igunga Nzega Uyui 15 2 7 17 27 9 24 to 30 18 to 24 12 to 18 6 to 12 0 to 6 Tanzania Agriculture Sample Census Number of Crop Growing Households Per Square Km Number of crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.05 TABORA Number of Crop Growing Households Per Square Kilometer of Land by District Map 3.06 TABORA Percent of Crop and Livestock Households by District RESULTS 13 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 14 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Tabora region was 202,097 (86% of the total regional agricultural households) whilst the female-headed households it were 33,820 (14% of the total regional agricultural households). The mean age of household heads was 46 years (46 years for male heads and 52 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys’ years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Tabora region had a total rural agricultural population of 1,420,300 of which 732,811 (52%) were males and 687,489 (48%) were females. Whereas age group 0-14 constituted 44 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Tabora region had an average household size of 6 persons per household with Nzega and Tabora Rural districts having the lowest household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Tabora region had a total literacy rate of 52.5 percent. The highest literacy rate was found in Tabora Urban district (67.4%) followed by Urambo district (56.0%) and Sikonge district (55.7%). Igunga, Uyui and Nzega districts had the lowest literacy rates of 53.3, 51.8 and 46.0 percent respectively (Chart 3.4). Chart 3.3 Percent Distribution of Population by Age and Sex - TABORA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85+ Age Group Percent Male Female Chart 3.4 Percent Literacy Level of Household Members by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Tabora Urb Urambo Sikonge Igunga Uyui Nzega District Percent Chart 3.2: Percentage Distribution of Agricultural Households by Sex of Household Head 0 10 20 30 40 50 60 70 80 90 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/96 NSCA 2002/03 Year Percent of Households Male Headed Households Female Headed Households RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 58.9 percent. The literacy rate for the male heads was 63.0 percent and that of female heads of households has 34.1 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst for all heads of households was Sikonge (69.2%) followed by Tabora Urban (68.9%), Urambo (67.6%), Uyui (62.0%), Igunga (52.3%) and Nzega (49.7%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 34 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 21 percent were still attending school. Those who have never attended school were 45 percent (Chart 3.6). Agricultural households in Tabora Urban district had the highest percentage (42%) of population aged 5 years and above who had completed different levels of education. This was followed by Sikonge and Urambo districts with 41 and 35 percent respectively. Igunga, Uyui and Nzega districts had the lowest percentages of 33, 33 and 30 respectively. The number of heads of agric ultural households with formal education in Tabora region was 135,084 (57.3%), those without formal education were 97,767 (41.4%) and those with only adult education were 3,066 (1.3%). The majority of heads of agricultural households (54.2%) had primary level education whereas only 3.1 percent had higher than primary level education. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 34% Attending School 21% Never Attended 45% Chart 3.5 Literacy Rates of Heads of Household by Sex and District - TABORA 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Sikonge Tabora Urb Urambo Uyui Igunga Nzega District P ercent Male Female Total Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Tabora Urban Sikonge Urambo Igunga Uyui Nzega District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Primary Education 54.2% No Education 41.4% Post Primary Education 3.1% Adult Education 1.3% RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 With regard to the heads of agricultural households with primary or secondary education in Tabora region, Sikonge district had the highest percentages (64.6% for primary and 3.8% for secondary). This was followed by Tabora Urban (62.3% primary and 4.0% secondary), Urambo (60.8% primary and 2.8% secondary) and Uyui (57.3% primary and 3.0% secondary), Igunga (48.9% primary and 1.0% secondary) and Nzega (46.1% primary and 2.1% secondary). Tabora Urban had the highest percentage of heads of agricultural households with secondary school education while Igunga had the lowest. (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or laborers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Tabora with 87.7 percent of households having at least one member with off-farm income. In Tabora region, there were 206,899 households with at least one household member engaged in off-farm income generating activity 117,453 households (50%) had only one member aged 5 years and above engaged in an off-farm income generating activity, 52,284 households (22%) had two members involved in off-farm income generating activities and 37,162 households (16%) had more than two members involved in off-farm income generating activities. Igunga and Nzega district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Urambo (89%) and Tabora Urban (86%). Uyui and Sikonge districts had the lowest percent of agriculture households with off-farm income (77% and 74% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Nzega (54%). Uyui district had few households with more than one member having off-farm income (17%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income More than Two,37,162, 16% None, 29,018, 12% One , 117,453, 50% Two, 52,284, 22% Chart 3.10 Percentage Distribution of Agricultural Household by Number of Off-farm Activities 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Nzega Igunga Uyui Urambo Sikonge Tabora Urb District P ercent One Two More than Two None RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 country, but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 899,225 ha. The regional average land area utilised for agriculture per household was only 2.9 ha. This figure is above the national average which is estimated at 2.0 hectares. Large differences in land area utilised per household exist between districts with Igunga and Nzega utilizing between 3.8 and 1.9 ha per household. The percentage utilized of the usable land per household was highest in Igunga (92%) and lowest in Urambo (69%) (Map 3.7). Seventy eight percent of the total land available to smallholders was utilised. Twenty two percent of usable land available to smallholders was not used (Chart 3.11, Map 3.7) 3.2.2 Types of Land Use The area of land under temporary mono-crops was 336,318 hectares (37.4% of the total land available to smallholders in Tabora), followed by temporary mix (182,793 ha, 20.3%), uncultivatable usable land (122,977, 13.7%), natural bush (63,072 ha, 7%), area under fallow (62,016 ha, 6.9%), unusable land (33,763 ha, 3.8), pasture (33,264 ha, 3.7%), permanent annual mix (25,917 ha, 2.9%), permanent mono-crops (15,179 ha, 1.7%), area rented to others (10,553 ha, 1.2%), permanent mixed crops (10,136 ha, 1.1%) and area planted with trees (3,237 ha, 0.4%). 3.3 Annual Crop and Vegetable Production Tabora region has only one rainy season, namely the long rainy season (November to May). The quantity of crops produced in that season will be used as a base for comparison with the past surveys and censuses. Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Districts Area/household 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.12 Land Area by Type of Use 20.3 37.4 13.7 7.0 6.9 3.8 3.7 2.9 1.7 1.2 1.1 0.4 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 Planted Trees Permanent Mixed Crops Rented to Others Permanent Mono Crops Permanent / Annual Mix Pasture Unusable Fallow Natural Bush Uncultivated Usable Land Temporary Mixed Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops Long Rainy Season, 532,615, 100% Planted Area - Long Rainy Season RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 3.3.1 Area Planted The area planted with annual crops and vegetables was 532,615. The average areas planted per household was 0.7. The district with the largest area planted per household was Igunga (1.1 ha) followed by Sikonge (0.9 ha) and Uyui (0.8 ha). The district with the smallest average area planted per household was Tabora Urban (0.5ha). (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 347,455 ha (65.2% of the total area planted with annuals). This was followed by oil seeds (69,862 hectares, 13.1%), cash crops (54,948 hectares, 10.3%), root and tuber crops (31,535 hectares, 5.9%), pulses (25,911 hectares, 4.9%) fruits and vegetables (2,904 hectares, 0.5%). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Tabora region and it had a planted area 3.4 times greater than groundnuts, which had the second largest planted area. The area planted with maize constituted 44 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are paddy, sorghum, tobacco, cotton, cassava and beans (Chart 3.16). Households that grow bulrush millet, cotton, sorghum, maize and tobacco have larger planted areas per household than those growing other crops (Chart 3.17). Chart 3.14 Area Planted with Annual Crops by District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Igunga Urambo Nzega Uyui Sikonge Tabora Urban District Planted Area (Ha) Chart 3.15 Area Planted with Annual Crops per Household by District 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Igunga Sikonge Uyui Urambo Nzega Tabora Urb District A rea pe r H o u seh o ld (H a ) Chart 3.16 Planted Area (ha) for the Main Crops - TABORA 0 100,000 200,000 300,000 Maize Groundnuts Paddy Sorghum Tobbaco Cotton Cassava Beans Sweet Potatoes Bambaranuts Cowpeas Bulrush Millet Onion Crop Area Planted (ha) Chart 3.17 Planted Area (ha) per Household by Selected Crop - TABORA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Bulrush Millet Cotton Sorghum Maize Tobacco Paddy Simsim Groundnuts Onions Cassava Beans Sunflower Sweet Potatoes Bambatanuts Tomatoes Cowpeas Greemgram Crop Planted Area (ha) RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 19 3.3.3 Crop Types Cereals are the main crops grown in Tabora region. The area planted with cereals was 347,455 ha (65.% of the total area planted with annuals), followed by oil seeds (69,862 hectares, 13.%), cash crops (54,948 hectares, 10%), root and tuber crops (31,535 hectares, 6%), pulses (25,911 hectares, 5%) fruits and vegetables (2,904 hectares, 1%). Cereals and oil seeds and oil seeds are the dominant crops and other crop types are of minor importance in comparison (Chart 18). 3.3.4 Cereal Crop Production The total production of cereals was 222,315 tonnes. Maize was the dominant cereal crop at 143,122 tonnes which was 64.4 percent of total cereal crops produced, followed by paddy (26.4%) sorghum (8.5%), finger millet (0.4%) and bulrush millet (0.3%). Production of wheat and barley was very small. Igunga district had the largest planted area of Cereals in the region (101,943ha) followed by Nzega, (79,731ha), Uyui (64,269ha), Urambo (59,115), Sikonge (32,371ha) and Tabora Urban (10,025ha) (Map 3.9). Maize had the largest planted area which represented 67 percent of the total area planted with cereal crops. It was followed by paddy (19%), sorghum (13%), bulrush millet (0.4%) and finger millet 0.3%). Areas planted with wheat and barley were very small. Paddy had the largest yield at 893 kg/ha, followed by finger millet (873 kg/ha), maize (615 kg/ha), bulrush millet (453 kg/ha) and sorghum (409 kg/ha) (Chart 3.20). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Tabora region was 229,901, (65% of the total annual crop growing households in the region). The total production of maize was 143,122 tonnes from a planted area of 232,860 hectares resulting in a yield of 0.6 t/ha. Chart 3.21 indicates maize production trend (in thousand metric tonnes). There was a sharp decrease in maize production by 62 percent in 1996/97 followed by a steady increase in production until 2002/03. The average area planted with maize Table 3.2: Area, Production and Yield of Cereal Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Maize 232,860 143,122 615 Paddy 65,657 58,661 893 Sorghum 46,379 18,959 409 Bulrush Millet 1,545 700 453 Finger Millet 881 769 873 Wheat 33 15 455 Barley 100 89 889 Total 347,455 222,315 Chart 3.20 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 200,000 250,000 Maize Paddy Sorhum Bulrush Millet Finger Millet Crop Area Planted (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Yield (T/Ha) Area Planted (Ha) Yield (T/Ha) Chart 3.21: Time Series Data on Maize Production - TABORA 143 126 126 98 72 191 186 0 50 100 150 200 250 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Agriculture Year Production ('000') Chart 3.22 Maize: Total Area Planted and Planted Area per Household by District 7,844 22,958 46,076 46,418 52,986 56,579 0 10,000 20,000 30,000 40,000 50,000 60,000 Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Acre (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Area Planted per Household Area Planted (Ha) Area Planted / Household Sikonge Tabora Urban Uyui Igunga Nzega 142,453 52,716 17,606 95,654 109,322 114,863 Urambo 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tabora Urban Uyui Sikonge Igunga Nzega 70.4% 73.2% 90.1% 69.9% 69.1% 92.1% Urambo Tanzania Agriculture Sample Census Percent of Utilized Land Area Percent of Utilized Land Area Annual crops Planted Area Annual crops Planted Area Map 3.7 TABORA Utilized Land Area Expressed as a Percent of Available Land by District Map 3.8 TABORA Total Planted Area with Annual crops by District 87.5 to 92.2 82.9 to 87.5 78.3 to 82.9 73.7 to 78.3 69.1 to 73.7 RESULTS 20 Nzega Tabora Urban Igunga Uyui Sikonge 79,731ha 59,115ha 10,025ha 101,943ha 64,269ha 32,371ha 72.9% 51.5% 56.9% 71.6% 67.2% 61.4% Urambo 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) Map 3.09 TABORA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Percent of Planted Area With Cereal Crops RESULTS 21 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 per household was 1.0 hectare, however it ranged from 0.8 hectares in Tabora Urban and Nzega districts to 1.3 hectares in Igunga district (Map 3.11). Igunga district had the largest area of maize (56,579 ha) followed by Nzega (52,986 ha), Uyui (46,418 ha), Urambo (46,076 ha), Sikonge (22,958 ha) and Tabora Urban (7,844 ha) (Chart 3.22 and Map 3.10). Charts 3.21 and 3.23 show that, over the period of 8 years from 1994/95 to 2002/03 both the yield and production decreased during the first half of the period and increased gradually during the remaining half. The area planted with maize remained constant but low over the period from 1994 to 1996 after which the area expanded rapidly 1997/98 and remained constant up to the year 2002/03. During the period 1997/98 to 2002/03, the yield increased gradually from 0.3 t/ha in 1997/98 to 0.6 t/ha in 2002/03 (Chart 3.23). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tabora region was 92,037. This represents 39 percent of the total annual crop growing households in Tabora region. The total production of paddy was 58,661 tonnes from a planted area of 65,657 hectares resulting in a yield of 0.9 t/ha. The district with the largest area planted with Paddy was Nzega (25,289 ha) followed by Uyui (14,587 ha), Urambo (11,904 ha), Igunga (6,560 ha), Sikonge (5,193 ha), and Tabora Urban (2,124 ha) (Map 3.12). There were variations in the average area planted per crop growing household among the districts ranging from 0.5 ha in Tabora Urban to 1.1 ha in Sikonge (Chart 3.24 and Map 3.13) There was a sharp rise in the production of paddy in 1997/98 and in 2002/03 compared to 1996/97 and 1999/2000 respectively. The production rose from 3,861 tonnes in 1996/97 to 46,601 tonnes in 1997/98 after which it dropped to 24,370 tonnes in the following year. Also, the production rose from 24,370 tonnes in 1999/00 to 58,661 tonnes in 2002/03. Charts 3.25 and 3.26 show that, whilst the yield of paddy has been erratic over the 8 year period from 1994/95 to 2002/03, the quantity produced increased due to a large increase of the planted area. From 1997/98 to 2002/03 the yield Chart 3.23 Time Series Data of Maize Planted Area and Yield - TABORA 0 100,000 200,000 300,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Yield (t/ha) Planted Area (Ha) Yield Chart 3.24: Total Planted Area and Area of Paddy per Household by District 2,124 5,193 6,560 11,904 14,587 25,289 0 5,000 10,000 15,000 20,000 25,000 30,000 Nzega Uyui Urambo Igunga Sikonge Tabora Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Area Planted per Household Area Planted (Ha) Area Planted / Household Chart 3.25: Time Series Data on Paddy Production - TABORA 47 59 24 24 4 6 9 0 10 20 30 40 50 60 70 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Agriculture Year Production ('000') tones Chart 3.26 Time Series Data of Paddy Area and Yield - TABORA 0 20000 40000 60000 80000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Yield (t/ha) Planted Area (Ha) Yield RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 has not dropped. The area planted with paddy and the production dropped drastically from 1994/95 to 1996/97 followed by rapid increase in 1997/98 after which the area planted and the production dropped rapidly in 1998/99. From 1999/2000 to 2002/03 the area planted and the production has been increasing (Chart 3.26). 3.3.4.3 Other Cereals Other cereals are produced in small quantities except sorghum of which the planted areas were as follows: Igunga (38,804 ha) followed by Uyui (3,162 ha), Sikonge (2,665 ha), Nzega (1,347 ha), Urambo (345 ha) and Tabora Rural (57 ha). Bulrush millet is produced in Sikonge (1,436 ha), Urambo (70 ha) and Uyui (39 ha) while finger millet was produced in Urambo (722 ha), Nzega (98 ha), Uyui (43 ha) and Sikonge (19 ha). The production of wheat and barley were very small. 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 41,380 tonnes. Cassava production was the highest being 28,416 tonnes, representing 68.7 percent of the total root and tuber crops production. This was followed by sweet potatoes with 12,351 tonnes (29.8%), Irish potatoes (329 tonnes, 0.8%) and yams (283 tonnes, 0.7%) (Table 3.3). The area planted with cassava was the largest in the region root and tuber crops. It accounted for 67.8 percent of the area planted with roots and tubers, followed by sweet potatoes (29.1%), Irish potatoes (2.3%) and yams (0.8%). There was a significant increase in area planted with cassava in the eight year period from 1994/95 to 2002/03. The area for sweet potato and yams remained more or less constant. The estimated yield was highest for sweet potatoes (1.34 t/ha) and cassava (1.32 t/ha), followed by yams (1.14 t/ha) and Irish potatoes 0.5 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 47,395. This represents 20 percent of the total crop growing households in the region. The total production of cassava during the census year was 28,416 tonnes from a planted area of 21,391 hectares resulting in a yield of 1.3 t/ha. Table 3.3: Area, Quantity Harvested and Yield of Root and Tuber Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Cassava 21,391 28,416 1,328 Sweet Potatoes 9,173 12,351 1,346 Irish Potatoes 723 329 455 Yams 248 283 1,143 Total 31,535 41,380 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Area (Ha) Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.27 Area Planted with Sorghum, Bulrush Millet and Finger Millet by District Sorghum Finger Millet Bulrush Millet Chart 3.28 Area Planted and Yield of Major Root and Tuber Crops 0 5,000 10,000 15,000 20,000 25,000 Cassava Sweet Potatoes Irish Potatoes Yams Crop Area Planted (Ha) 0 500 1,000 1,500 Yield (Kg/Ha) Area Planted (Ha) Yield (Kg/Ha) Chart 3.29 Area Planted with Cassava during the Census/Survey Year 0 15000 30000 45000 1994/95 1995/96 1997/98 1998/99 2002/03 Agriculture Year Area (Ha) Cassava Tabora Urban Urambo Igunga Sikonge Uyui Nzega 0.8ha 0.9ha 1.3ha 1.2ha 1.1ha 0.8ha 1.2 to 1.3 1.1 to 1.2 1 to 1.1 0.9 to 1 0.8 to 0.9 Sikonge Urambo Uyui Tabora Urban Nzega Igunga 22,958ha 46,076ha 46,418ha 7,844ha 52,986ha 56,579ha 0.8t/ha 0.8t/ha 0.6t/ha 0.5t/ha 0.7t/ha 0.3t/ha 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 24 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.10 TABORA Planted Area and Yield of Maize by District Map 3.11 TABORA Area Planted per Maize Growing Household by District Yield(t/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.5ha 0.8ha 0.7ha 0.7ha 0.6ha 1.1ha Tabora Urban Uyui Urambo Nzega Igunga Sikonge 2,124ha 14,587ha 11,904ha 25,289ha 6,560ha 5,193ha 0.8% 0.9% 0.9% 1.2% 0.9 0.5% Tanzania Agriculture Sample Census RESULTS 25 Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.12 TABORA Planted Area and Yield of Paddy by District Map 3.13 TABORA Area Planted per Paddy Growing Household by District Yield(t/ha) 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 0.98 to 1.11 0.86 to 0.98 0.74 to 0.86 0.62 to 0.74 0.5 to 0.62 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 26 Previous censuses and surveys indicate that the area planted with cassava increased for the period 1994/95 to 1998/99. Since 1998/99 the area planted with cassava dropped from 40,582 ha in 1998/99 to 21,391 ha in 2002/03 (Chart 3.29). The area planted with cassava accounted for 7 percent of the total area planted with annual crops and vegetables in the census year. Urambo district had the largest planted area of cassava (8,795 ha, 41% of the cassava planted area in the region), followed by Nzega (4,388 ha, 21%), Uyui (3,316 ha, 16%), Tabora Urban (2,326 ha, 11%), Sikonge (1,829 ha, 9%) and Igunga (736 ha, 3%) (Map 3.14). However, the district with the highest proportion of land planted with cassava was Tabora Urban (13.2%). This was followed by Urambo (7.7%), Nzega (4.0%), Uyui and Sikonge (3.5% each) and Igunga (0.5%) (Chart 3.30). The average cassava planted area per cassava growing household was 0.5 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Tabora Urban (0.6 ha). This was followed by Sikonge (0.5 ha), Uyui (0.5 ha), Urambo (0.5 ha), Nzega (0.4 ha) and Igunga (0.4 ha) (Chart 3.31 and Map 3.15). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Tabora region was 27,635. The total production of sweet potatoes during the census year was 12,351 tonnes from a planted area of 9,173 hectares resulting in a yield of 1.3t/ha. Igunga District has the largest planted area for sweet potatoes (3,639 ha, 39.7%), followed by Urambo (1,483 ha, 16.2%), Uyui (1,440 ha, 15.7%), Sikonge (1,166 ha, 12.7%), Tabora Urban (772 ha, 8.4%) and Nzega (673 ha, 7.3%). Other root and tuber crops are of minor importance in terms of area planted compared to cassava and sweet potatoes. Table 3.4: Area, Quantity Harvested and Yield of Pulse Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Beans 19,331 7,143 369.5 Bambara nuts 3,593 1,424 396.4 Cowpeas 1,802 544 301.7 Chick Peas 682 437 640.4 Green Gram 436 91 209.2 Mung Beans 66 19 287.9 Pigeon Peas 0 0 0.0 Field Peas 0 0 0.0 Total 25,910 9,658 Chart 3.30 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 41.1 20.5 15.5 10.9 3.4 8.6 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 Urambo Nzega Uyui Tabora Urban Sikonge Igunga District Percent of Total Area Planted 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.6 0.5 0.5 0.5 0.4 0.4 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Area per Household Tabora Urban Sikonge Uyui Urambo Nzega Igunga District Chart 3.31 Cassava Planted Area per Cassava Growing Households by District Chart 3.32 Total Area Planted with Sweet Potatoes and Planted Area per Household by District 673 772 1,166 1,440 1,483 3,639 0 1,000 2,000 3,000 4,000 Igunga Urambo Uyui Sikonge Tabora Urban Nzega District Area (H a) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Area Planted per H ousehod Area Planted (Ha) Area Planted/Hh RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 3.3.6 Pulse Crops Production The total area planted with pulses was 25,910 hectares representing 5 percent of total area planted with annual crops out of which 19,3318 ha were planted with beans (74.6 percent of the total area planted with pulses), followed by bambara nuts (3,593 ha, 13.9%), cowpeas (1,802 ha, 7.0%), chick peas (682 ha, 2.6%), green gram (436 ha, 1.7%) and mung beans (66 ha, 0.3%). Pigeon peas and field peas were not cultivated in the region. The total production of pulses was 9,658 tonnes. The production of beans was 7,143 tonnes and it accounted for 74 percent of the total pulse production. This was followed by bambara nuts (1,424t, 14.7%), cow peas (544t, 5.6%), chick peas (437t, 4.5%), green gram (91t, 0.9%) and mung beans (19t, 0.2%). Chick peas had a relatively higher yield of 640 kgs/ha than other pulses. The yields of the rest of the pulses in kilograms per hectare were bambara nuts 396 kgs/ha, beans 370 kgs/ha, cow peas 302 kgs/ha, mung beans 288 kgs/ha and green gram 209 kgs/ha (Chart 3,33). 3.3.6.1 Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Tabora region was 56,189. The total production of beans in the region was 7,143 tonnes from a planted area of 19,331 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Urambo (10,308 ha, 53.3% of the area planted with beans in the region) (Chart 3.34 and Map 3.16), however, the largest area planted with beans per household was in Igunga district (0.7 ha) (Chart 3.35). With exception of Igunga district, the variations in area planted with beans per household for the rest of the districts were small ranging from 0.2 ha in Nzega districts to 0.4 ha in Urambo and Sikonge districts (Map 3.17). In Tabora region, bean production has increased over the period 1995 to 2003 from 1,423 tonnes in 1995 to 7,143 tonnes in 2003 (Chart 3.36). Chart 3.33 Area Planted and Yield of Major Pulse Crops 0 5,000 10,000 15,000 20,000 25,000 Beans Bambaranuts Cowpeas Chick Peas Green GramMung Beans Crop Area Planted (Ha) 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 Yield (Kg/Ha) Area Planted Yield(Kg/Ha) Chart 3.34 Percent of Bean Planted Area and Pecent of Total Land with Beans by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Urambo Uyui Sikonge Tabora Urban Nzega Igunga District Percent of Land 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.7 0.4 0.4 0.3 0.3 0.2 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Area per Household Igunga Urambo Sikonge Uyui Tabora Urban Nzega District Chart 3.35 Area Planted per Household by District Chart 3.36 Time Series Data on Beans Production - TABORA 1.4 3.6 10.4 1.1 24.3 7.1 0.0 5.0 10.0 15.0 20.0 25.0 30.0 1994/95 1995/96 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Tabora Urban Nzega Sikonge Urambo Igunga Uyui 4,388ha 2,326ha 3,316ha 1,829ha 8,795ha 736ha 0.9t/ha 0.8t/ha 0.9t/ha 1.1t/ha 1.9t/ha 1.5t/ha 8,000 to 9,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Sikonge Uyui Nzega Igunga Tabora Urban Urambo 0.5ha 0.5ha 0.4ha 0.4ha 0.6ha 0.5ha 0.56 to 0.61 0.52 to 0.56 0.48 to 0.52 0.44 to 0.48 0.4 to 0.44 Area Planted per Household Map 3.14 TABORA Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.15 TABORA Area Planted per Cassava Growing Household by District Yield(t/ha) RESULTS 28 Tabora Urban Uyui Nzega Igunga Urambo Sikonge 0.3ha 0.2ha 0.7ha 0.4ha 0.4ha 0.3ha 0.6 to 0.7 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 1,439ha 3,654ha 10,308ha 1,064ha 319ha 2,547ha 0.2t/ha 0.3t/ha 0.4t/ha 1.5t/ha 0.2t/ha 0.3t/ha 8,000 to 11,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.16 TABORA Planted Area and Yield of Beans by District Map 3.17 TABORA Area Planted per Beans Growing Household by District Yield(t/ha) RESULTS 29 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 Charts 3.36 and 3.37 show that, whilst the area under beans production remained fairly constant the previous 4 years the quantity produced and the yield were fluctuating. The production increased rapidly in 1999/2000 due to the high yield of that year whilst the production decreased in the 2002/03 due to rapid decrease of yield (Chart 3.37). 3.3.7 Oil Seed Production The total production of oilseed crops was 31,877 tonnes planted on an area of 69,863 hectares representing 13 percent of the total area planted with annual crops. Groundnuts were the most important oilseeds with 68,730 ha (98.4% of the total area planted with oil seeds), followed by simsim (0.8%), sunflower (0.7%) and soya beans (0.1%) (Chart 3.38). The yield of groundnuts was 460 kg/ha. Sunflower had a yield of 292 kg/ha, soya beans of 213 kg /ha and simsim 172 kg/ha. In terms of production, groundnuts at 31,618 tonnes, accounted for 99.2 percent of the total production of oil seeds, followed by sunflower (0.5%) and simsim (0.3%). The production of soya beans was very small while castor seeds were not produced at all. 3.3.7.1 Groundnuts The number of households growing groundnuts in Tabora region was 143,462. The total production of groundnuts in the region was 31,618 tonnes from a planted area of 68,730 hectares resulting in a yield of 0.5 t/ha. There was a large increase in the production of groundnuts over the period 1995 to 2003, from 9,876 tonnes in 1994/95 to 31,618 tonnes in 2002/03. The area planted increased from 12,120 hectares in 1994/95 to 32,184 hectares in 1995/96 and 68,730 hectares in 2002/03 (Chart 3.39). Twenty nine percent of the area planted with groundnuts was located in Nzega District (19,722 ha) followed by Urambo (17,001 ha, 25%), Uyui (11,660 ha, 17%), Igunga (10,391 ha, 15%), Sikonge (7,863 ha, 11%) and Tabora Urban (2,093 ha, 3%). (Chart 3.40 and Map 3.18). Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Groundnuts 68,730 31,618 460.0 Simsim 548 94 171.9 Sunflower 510 149 291.8 Soya Beans 75 16 213.3 Total 69,863 31,877 Chart 3.37 Time Series of Beans Planted Area and Yield - TABORA 0 10000 20000 30000 40000 50000 1995/96 1998/99 1999/00 2002/03 Agriculture Year Area (Hectares) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Yield (T/Ha) Area Yield Chart 3.38 Area Planted and Yield of Major Oil Seed Crops 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Groundnuts Simsim Sunflower Soya Beans Crop Area Planted (Ha) 0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.5 Yield (Kg/Ha) Area Yield Chart 3.39 Time Series Data on Groundnut Production - TABORA 0 10000 20000 30000 40000 1994/95 1995/96 2002/03 Year Production (Tonnes) RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 The highest proportion of land with groundnuts was found in Nzega followed by Sikonge, Urambo, Uyui, Tabora Urban and Igunga. planted per household depicts small variations in area planted among the districts (Chart 3.41 and Map 3.19). The largest area planted per groundnut growing household was found in Sikonge District (0.6 ha) and the lowest was in Tabora Urban with 0.36 ha. The range between the district with the highest and the lowest area 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. Reliable historical data for time series analysis of fruit and vegetables were not available.The total production of fruits and vegetables was 5,847 tonnes. The most cultivated fruit and vegetable crop was onion with a production of 2,550 tonnes (44% of the total fruit and vegetables produced) followed by tomatoes (2,522t, 43%), radish (419t, 7%), amaranths (98t, 1.7%), bitter aubergine (85t, 1.4%) and cabbage (55t, 0.9%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 3,048 kg/ha, onions (1,692 kg/ha), amaranths (1,632 kg/ha) and radish (1,480 kg/ha). Cabbages and bitter aubergine had yields of 1,140 kg/ha and 872 kg/ha respectively (Chart 3.42). Table 3.6: Area, Quantity Harvested and Yield of Fruit and Vegetable Crops Crops Area Planted (ha) Quantity Harvested (tonnes) Yield (kg./ha) Onion 1,507 2,550 1,692 Tomatoes 827 2,522 3,048 Radish 283 419 1,480 Bitter Aubergine 97 85 872 Amaranths 60 98 1,632 Cabbage 48 55 1,140 Pumpkins 38 53 1,408 Okra 21 31 1,469 Egg Plant 12 11 865 Ginger 5 13 2,371 Cucumber 3 2 790 Chillies 1 7 5,558 Total 2,904 5,847 Chart 3.40 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Nzega Urambo Uyui Igunga Sikonge Tabora Urban District Percent of Land 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.0 0.2 0.4 0.6 0.8 Area per Household ((Ha) Sikonge Igunga Urambo Uyui Nzega Tabora Urban District Chart 3.41 Area Planted per Groundnut Growing Households by District Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 200 400 600 800 1,000 1,200 1,400 1,600 Onion Tomotoes Radish Bitter Aubergine Amaranths Cabbage Others Crop Area Planted (ha) 0 500 1000 1500 2000 2500 3000 3500 Yield (kg/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.4ha 0.5ha 0.5ha 0.4ha 0.5ha 0.6ha 0.56 > 0.52 to 0.56 0.48 to 0.52 0.44 to 0.48 0.4 to 0.44 Uyui Sikonge Tabora Urban Nzega Urambo Igunga 11,660ha 7,863ha 19,722ha 2,093ha 17,001ha 10,391ha 0.5t/ha 0.3t/ha 0.5t/ha 0.4t/ha 0.3t/ha 0.6t/ha 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.18 TABORA Planted Area and Yield of Groundnuts by District Map 3.19 TABORA Area Planted per Groundnuts Growing Household by District Yield(t/ha) RESULTS 32 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 33 3.3.8.1 Onions The number of households growing onion in the region was 3,250. This represented 1.4 percent of the total crop growing households. Igunga district had the largest planted area of onions (80.4% of the total area planted with tomatoes in the region), followed by Nzega (10%), Urambo (4.8%), Tabora Rural (2.7%) and Uyui (2%) (Map 3.20). The district with the highest proportion of land under onions was Igunga, followed by Tabora Urban. With exception of Igunga district, the rest of the districts had relatively small percentages of land under onion (Chart 3.43). The largest area planted per onion growing household was found in Igunga district (0.8 ha) followed by Nzega and Tabora Urban (0.2 ha) and Uyui and Urambo (0.1 ha each) (Chart 3.44 and Map 3.21). The total area planted with onion accounted for 0.3 percent of the total area planted with annual crops in the region. 3.3.8.2 Tomatoes The number of households growing tomatoes in the region was 5,471. This represented 2.3 percent of the total crop growing households. Uyui district had the largest planted area for tomatoes (31% of the total area planted with tomatoes in the region), followed by Tabora Urban (27%), Urambo (21%), Nzega (14%), Igunga (6%) and Sikonge (1%) (Map 3.22). The highest proportion of land with onion was found in Tabora Urban, followed by Uyui. All the districts had relatively low percentage of land used for tomatoes production (Chart 3.45). The largest area planted per onion growing household was found in Tabora Urban district (0.19 ha) followed by Nzega (0.16 ha), Uyui (0.15 ha), Igunga (0.13 ha) Urambo (0.12 ha) and Sikonge (0.1 ha) (Chart 3.46 and Map 3.23). The total area planted with tomatoes accounted for 0.2 percent of the total area planted with annual crops in the region. Chart 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 Igunga Nzega Urambo Tabora Urban Uyui Sikonge District Percent of Land 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.0 0.2 0.4 0.6 0.8 1.0 A rea per H o useho ld (H a ) Igunga Nzega Tabora Urban Uyui Urambo Sikonge District Chart 3.44 Area Planted per Household by DistrictArea/Hh Chart 3.45 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 10.0 20.0 30.0 40.0 Uyui Tabora Urban Urambo Nzega Igunga Sikonge District Percent of Land 0.0 0.5 1.0 1.5 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.04 0.08 0.12 0.16 0.20 Area per H ousehold Tabora Urban Nzega Uyui Igunga Urambo Sikonge District Chart 3.46 Area Planted per Tomato Growing Household by District RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.8.3 Amaranths The number of households growing amaranths in the region was 568. This represented 0.07 percent of the total crop growing households. Urambo district had the largest planted area of amaranths (36 ha, 60% of the total area planted with amaranths in the region), followed by Tabora Urban (24 ha, 40%). The rest of the districts did not plant amaranths (Chart 3.47 and Map 3.24 and 3.25). The total area planted with amaranths accounted for 0.01 percent of the total area planted with annual crops in the region. 3.3.8.4 Cabbage The number of households growing cabbage in the region was 246. This represented 0.10 percent of the total crop growing households. Uyui district had the largest planted area for cabbage (42 ha, 86% of the total area planted with amaranths in the region), followed by Tabora Urban (7 ha, 14%). Rest of the districts had not planted cabbages (Chart 3.48). The total area planted with cabbage accounted for 0.01 percent of the total area planted with annual crops in the region. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. Of the 54,948 ha planted with other annual crops, tobacco was the most prominent followed by cotton. Pyrethrum was also planted but area planted was very small. 3.3.9.1 Tobacco The quantity of tobacco produced was 29,613 tonnes. Tobacco had a planted area of 32,490 ha. Tobacco production was concentrated in three districts with Urambo having the largest planted area (15,565 ha, 48% of total area planted with tobacco in the region), followed by Uyui (9,635 ha, 29%), Sikonge (5,735 ha, 18%), Nzega (1,078 ha 3%), Tabora Urban (246 ha, 0.8%) and Igunga (230 ha, 0.7%) (Chart 3.50) (Map 3.26 and 3.37). Chart 3.47 Percent of Amaranthus Planted Area and Percent of Total Land with Amaranths by District 0 20 40 60 80 Urambo Tabora Urban Nzega Igunga Uyui Sikonge District P ercent of Land 0.00 0.04 0.08 0.12 0.16 Percent Area Pla nted of Total Land Area Percent of Land Proportion of Land Chart 3.48 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 75.0 100.0 Uyui Tabora Urban Nzega Igunga Urambo Sikonge District Percent of Land 0.00 0.01 0.02 0.03 0.04 0.05 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted with Annual Cash Crops Cotton, 22,409, 41% Pyrethrum, 49, 0% Tobacco, 32,490, 59% Chart 3.50 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Urambo Uyui Sikonge Nzega Tabora Urban Igunga District Percent of Land 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Sikonge Urambo Tabora Urban Uyui Nzega Igunga 0ha 0.1ha 0.2ha 0.1ha 0.2ha 0.8ha 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Tabora Urban Uyui Igunga Nzega Urambo Sikonge 41ha 30ha 1,212ha 151ha 72ha 0ha 1.2t/ha 5.5t/ha 1.2t/ha 2t/ha 8.2t/ha 0t/ha Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.20 TABORA Planted Area and Yield of Onions by District Map 3.21 TABORA Area Planted per Onions Growing Household by District Yield(t/ha) 1,200 to 1,300 900 to 1,200 600 to 900 300 to 600 0 to 300 RESULTS 35 Sikonge Tabora Urban Uyui Urambo Nzega Igunga 0.1ha 0.2ha 0.2ha 0.1ha 0.2ha 0.1ha 0.18 to 0.2 0.16 to 0.18 0.14 to 0.16 0.12 to 0.14 0.1 to 0.12 Tabora Urban Uyui Sikonge Urambo Nzega Igunga 221 255 5ha 173ha 120ha 54ha 3.4% 2.5t/ha 1.5t/ha 2.4t/ha 3.5t/ha 3% 200 to 260 150 to 200 100 to 150 50 to 100 0 to 50 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.22 TABORA Planted Area and Yield of Tomatoes by District Map 3.23 TABORA Area Planted per Tomatoes Growing Household by District Yield(t/ha) RESULTS 36 Sikonge Tabora Urban Uyui Urambo Igunga Nzega 0ha 0.1ha 0.1ha 0ha 0 ha 0ha Area Planted per Household 0.08 to 0.1 0.06 to 0.08 0.04 to 0.06 0.02 to 0.04 0 to 0.02 Urambo Igunga Tabora Urban Nzega Uyui 0ha 36ha 0ha 0ha 24ha 0ha 0t/ha 0.9t/ha 0t/ha 0t/ha 2.8t/ha 0t/ha Sikonge 28 > 21 to 28 14 to 21 7 to 14 0 to 7 Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.24 TABORA Planted Area and Yield of Amaranths by Map 3.25 TABORA Area Planted per Amaranths Growing Household by District Yield(t/ha) District RESULTS 37 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 246ha 9,635ha 15,565ha 1,078ha 230ha 5,735ha 0.8t/ha 0.9t/ha 0.8t/ha 0.4t/ha 0.9t/ha 1.1t/ha 12,000 to 16,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tabora Urban Uyui Urambo Igunga Sikonge 0.8ha 1ha 1.2ha 1ha 1ha 1.2ha Nzega 1.12 to 1.21 1.04 to 1.12 0.96 to 1.04 0.88 to 0.96 0.8 to 0.88 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.26 TABORA Planted Area and Yield of Tobacco by Map 3.27 TABORA Area Planted per Tobacco Growing Household by District Yield(t/ha) District RESULTS 38 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 3.3.9.2 Cotton Only 9,932 tonnes of cotton were produced in Tabora Region on a planted area of 22,409 ha. The crop was grown in four districts only (Igunga, Urambo, Nzega and Uyui). Igunga had the largest area planted with cotton (21,751 ha, 97.1%) followed by Urambo district (494 ha, 2.2%), Nzega (145 ha, 0.6%) and Uyui (19 ha, 0.1%) (Map 3.28) and an average of 1.7 ha was grown per household (Map 3.29). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 9,931 hectares (2% of the area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops would be higher than indicated in Chart 3.51. The most important permanent crop in Tabora region is mango which accounts for a planted area of 3,807 ha, (38.3% of the planted area of all permanent crops) followed by palm oil (2,159 ha, 21.7%), banana (1,599 ha, 16.1%), pawpaw (670 ha, 6.7%) and guava (656 ha, 6.6%). All the remaining permanent crops accounted for 10.5 percent of the total area planted with permanent crops (Chart 3.52). Urambo district had the largest area under smallholder permanent crops (5,820 ha, 58.6%). This is followed by Nzega (1,429 ha, 14.4%), Uyui (1,287 ha, 13%), Tabora Urban (932 ha, 9.4%), Igunga (327 ha, 3.8%) and Sikonge (85 ha, 0.9%). However, Tabora Urban had the largest area per permanent crop growing household (0.8 ha) followed by Urambo and Uyui (0.4 ha), Nzega (0.3 ha) and Sikonge (0.1 ha) (Chart 3.53). Chart 3.53 Percent of Area Planted and Average Planted Area with Permanent Crops by District 58.6 0.9 3.8 9.4 13.0 14.4 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Urambo Nzega Uyui Tabora Urban Igunga Sikonge District % of Total Area Planted 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Average Panted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51 Area Planted Annual and Permanent Crops Annual Crops, 532,615, 98% Permanent Crops, 9,931, 2% Chart 3.52 Area Planted with Main Permanent Crops Palm Oil, 2,159, 22% Banana, 1,599, 16% Mango, 3,807, 38% Pawpaw, 670, 7% Guava, 656, 7% Orange, 440, 4% Others, 132, 1% Coconut, 54, 1% Lime/Lemon, 110, 1% Sugarcane, 303, 3% RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Tabora Urban had the highest percent (5.0%) followed by Urambo (4.8%), Igunga (1.3%), Uyui (1.3%), Nzega (0.3%) and Sikonge (0.2%). 3.4.1 Mango The total production of mangoes by smallholders was 20,763 tonnes. In terms of area planted, mango was the most important permanent crop grown by smallholders in the region. They were grown by 9,338 households (4% of the total crop growing households). The average area planted with mangoes per household was relatively small at around 0.4 ha per mangoes growing household and the average yield obtained by smallholders was 45,600 kg/ha from a harvest area of 455 hectares. Urambo had the largest area of mangoes in the region (1,618 ha, 42.5%) followed by Tabora Urban (788 ha, 20.7%), Nzega (649 ha, 17.0%), Uyui (432 ha, 11.3%), Igunga (268 ha, 7.0%) and Sikonge (53 ha, 1.4%) (Map3.30). However, the average area planted with mangoes per mango growing household was highest in Tabora Urban (1.9 ha) followed by Urambo, Uyui and Igunga (0.4 ha each), Nzega (0.3 ha) and Sikonge (0.1 ha) (Chart 3.54 and Map 3.31). 3.4.2 Palm Oil The total production of palm oil by smallholders was 416 tonnes. In terms of area planted, palm oil was the second most important permanent crop grown by smallholders in the region. It was grown by 3,425 households (1.5% of the total crop growing households). The average area planted with palm oil per household was at around 0.6 ha per palm oil growing household and the average yield obtained by smallholders was 3,525 kg/ha from a harvest area of 118 hectares. Urambo had the largest area of palm oil in the region (1,858 ha, 86.1%) followed by Uyui (291 ha, 13.5%) and Tabora Urban (10 ha, 0.4%). Palm oil production was not reported in the rest of the districts (Map 3.32). However, the average area planted with palm oil per palm oil planting household was highest in Uyui (0.7 ha) followed by Urambo (0.6 ha) and Tabora Urban (0.4 ha) (Chart 3.55 and Map 3.33). 3.4.3 Banana The total production of banana by smallholders was 2,616 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 5,058 households (2.1% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.32 ha per banana growing household and the average yield obtained by smallholders was 5,300 kg/ha from a harvested area of 490 hectares. Chart 3.54 Percentage of Area Planted with Mango and Average Planted Area per Household by District 1.4 7.0 11.3 17.0 20.7 42.5 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 Urambo Tabora Urban Nzega Uyui Igunga Sikonge District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Average Area Planted per Household % of Total Area Planted Average Planted Area per Household Chart 3.55 Percent of Area Planted with Palm Oil and Average Planted Area per Household by District 0.0 0.0 0.0 0.4 13.5 86.1 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Uyui Tabora Urban Nzega Igunga Sikonge District % of Total Area Planted 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 Urambo had the largest planted area of bananas in the region (1,362 ha, 85.2%) followed by Nzega (92 ha, 5.7%), Uyui (70 ha, 4.4%), Tabora Urban (56 ha, 3.5%) and Sikonge (19 ha, 1.2%). Banana was not planted in Igunga (Map 3.34). However, the area planted with banana per banana growing household was highest in Sikonge (0.40 ha), followed by Urambo (0.36 ha), Tabora Urban (0.24 ha), Uyui (0.17 ha) and Nzega (0.15 ha) (Chart 3.56 and Map 3.35). 3.4.4 Pawpaw The total production of pawpaw by smallholders was 926 tonnes. In terms of area planted, pawpaw was the fourth most important permanent crop grown by smallholders in the region. It was grown by 2,745 households (0.4% of the total crop growing households). The average area planted with pawpaw per household was relatively small at around 0.2 ha per pawpaw growing household and the average yield obtained by smallholders was 4,700 kg /ha from a harvest area of 197 hectares. Urambo has the largest area of pawpaw in the region (516 ha, 77.1%) followed by Nzega (84 ha, 12.6%), Igunga (40 ha, 6.0%), Uyui (25 ha, 3.7%) and Tabora (4 ha, 0.6%) (Map 3.36). The average area planted per pawpaw growing household was highest in Urambo (0.34 ha), followed by Nzega (0.30 ha), Igunga (0.09 ha), Uyui (0.06 ha) and Tabora Urban (0.04 ha) (Map 3.37). Sikonge district reported no pawpaw production. Chart 3.57 Percent of Area Planted with Pawpaw and Average Planted Area per Household by District 77.0 12.5 6.0 3.8 0.6 0.0 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Nzega Igunga Uyui Tabora Urban Sikonge District % of Total Area Planted 0.00 0.10 0.20 0.30 0.40 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.58 Number of Households by Method of Land Clearing 208,502 19,557 3,262 2,361 670 150 0 50,000 100,000 150,000 200,000 250,000 Mostly Hand Slashing Mostly Bush Clearance No Land Clearing Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.56 Percent of Area Planted with Banana and Average Planted Area per Household 0.0 1.2 3.5 4.4 5.7 85.1 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Nzega Uyui Tabora Urban Sikonge Igunga District % of Total Area Planted 0.00 0.10 0.20 0.30 0.40 0.50 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 42 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region was 451,452 ha which represented 88.5 percent of the total planted area. Burning and tractor slashing are less important methods for land clearing and they represented 0.9 and 0.3 percent respectively (Table3.7). 3.5.2 Methods of Soil Preparation Ox-ploughing is the most method used for soil preparation and was used in an area of 261,638 ha which represented 51 percent of the total planted area, closely followed by hand cultivation (244,900 ha, 48%) and tractor ploughing (5,117 ha, 1%). In Tabora region, Igunga district had the largest planted area cultivated with oxen (129,795 hectares, 25.4%) followed by Nzega (64,739 ha, 12.7%), Uyui (31,866 ha, 6.2%), Sikonge (18,060 ha, 3.5%), Urambo (15,290 ha, 2.44%), and Tabora Urban (1,888 ha, 0.4%). Table 3.7: Land Clearing Methods Method of Land Clearing Number of Households Area Planted % Mostly Hand Slashing 208,502 451,452 88.5 Mostly Bush Clearance 19,557 46,763 9.2 No Land Clearing 3,262 5,635 1.1 Mostly Burning 2,361 4,611 0.9 Mostly Tractor Slashing 670 1,535 0.3 Other 150 122 0.0 Total 234,501 510,117 100.0 Chart 3.59 Area Cultivated by Cultivation Method Mostly Hand Cultivation, 244,900, 48% Mostly Tractor Ploughing, 5,117, 1% Mostly Oxen Ploughing, 261,638, 51% 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 A r ea C u ltiv a te d ( h a ) Igunga Nzega Uyui Sikonge Urambo Tabora Urban District Chart 3.60 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostly Tractor Ploughing Igunga Tabora Urban Nzega Uyui Sikonge 21,751ha 145ha 0ha 494ha 0ha 19ha 0.4t/ha 0.4t/ha 0t/ha 0.8t/ha 0t/ha 1.5t/ha Urambo 16,000 to 22,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tabora Urban Uyui Nzega Igunga Sikonge 0ha RESULTS 43 0.6ha 0.2ha 1.7ha 1.3ha 0ha Urambo Planted Area (ha) Map 3.28 TABORA Planted Area and Yield of Cotton by District Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Map 3.29 TABORA Area Planted per Cotton Growing Household by District Yield(t/ha) 1.2 to 1.7 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Tabora Urban Uyui Urambo Igunga Nzega Sikonge 1.9ha 0.4ha 0.4ha 0.4 0.3ha 0.1ha 1.7 > 1.3 to 1.7 0.9 to 1.3 0.5 to 0.9 0.1 to 0.5 Igunga Nzega Tabora Urban Urambo Uyui Sikonge 268ha 649ha 1,618ha 788ha 432ha 53ha 17.9t/ha 50.8t/h 72.5t/ha 19.1t/ha 31.1t/ha 9.8t/ha 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Planted Area (ha) Map 3.30 TABORA Planted Area and Yield of Mango by District Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Map 3.31 TABORA Area Planted per Mango Growing Household by District Yield(t/ha) RESULTS 44 Tabora Urban Urambo Nzega Igunga Uyui Sikonge 0.4ha 0.6ha 0ha 0ha 0.7ha 0ha 0.56 to 0.7 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Tabora Urban Uyui Sikonge Nzega Igunga 10ha 0ha 1,858ha 0ha 0ha 291ha 1t/ha 0t/ha 0t/ha 3.6t/ha 0t/ha 0t/ha Urambo 1,600 to 1,900 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.32 TABORA Planted Area and Yield of Palm Oil by District Map 3.33 TABORA Area Planted per Palm Oil Growing Household by District RESULTS 45 Yield(t/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.2ha 0.4ha 0.2ha 0ha 0.2ha 0.4ha RESULTS 46 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Sikonge Tabora Urban Uyui Nzega Igunga 19ha 56ha 70ha 1,362ha 0ha 4.1% 9.3% 0.8% 0% 5.5% 7.3% Urambo Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.34 TABORA Planted Area and Yield of Banana by District Map 3.35 TABORA Area Planted per Banana Growing Household by District Yield(t/ha) 1,200 to 1,400 900 to 1,200 600 to 900 300 to 600 0 to 300 Tabora Urban Uyui Sikonge Urambo Nzega Igunga 0.04ha 0.09ha 0.06ha 0ha 0.34ha 0.3ha 0.28 to 0.34 0.21 to 0.28 0.14 to 0.21 0.07 to 0.14 0 to 0.07 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 4ha 516ha 84ha 40ha 26ha 0ha 0.6t/ha 0t/ha 8.8t/ha 5.1t/ha 3.4t/ha 0.5t/ha 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.36 TABORA Planted Area and Yield of Pawpaw by District Map 3.37 TABORA Area Planted per Pawpaw Growing Household by District Yield(t/ha) RESULTS 47 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 88,125 ha which represents 17 percent of the total area planted with the annual crops and vegetables area. Cash crops had the largest area planted with improved seeds (47,636 ha, 62% of the planted area with improved seeds) followed by cereals (24,144 ha, 31%), Oil seeds (2,568 ha, 3%), pulses (1,550 ha, 2%), fruits and vegetables (1,526 ha, 2%) and roots and tubers (236 ha, 0.3%) (Chart 3.62). However, the use of improved seed in cash crops and fruits and vegetables is much greater than in other crop types (87% and 53% respectively), only 2.2 percent of the planted area for root and tuber crops used improved seed (Chart 3.63). 3.5.4 Fertilizer Use The use of fertilisers on annual crops is small with a planted area of only 179,816 ha (34% of the total planted area in the region) having been applied with fertilizers. The planted area without fertiliser for annual crops was 352,800 hectares representing 66 percent of the total area planted with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 101,423 ha which represented 56 percent of the planted area applied with fertilisers in the region. This was followed by inorganic fertilizers (64,676 ha, 36%). Compost manure was used on a very small area which represented only 8 percent of the area planted with fertilizers. Chart 3.62 Planted Area with Improved Seed by Crop Type Cash Crops, 47,636, 62% Cereals, 24,144, 31% Pulses, 1,550, 2% Oilseeds , 2,568, 3% Roots & Tubers, 236, 0% Fruits & Vegetables, 1,526, 2% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.63 Percent of Crop Type Planted with Improved Seed - Annuals Chart 3.61 Planted Area of Improved Seeds - TABORA Without Improved Seeds, 444,490, 83% With Improved Seeds, 88,125, 17% 0 50,000 100,000 150,000 Area (ha) Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.65 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.64 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 352,800, 66% Mostly Compost, 13,717, 3% Mostly Inorganic Fertilizer, 64,675, 12% Mostly Farm Yard Manure, 101,423, 19% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 The highest percentage of the area planted with fertilizer (all types) was in Nzega (26.4%) followed by Urambo (24.2%), Igunga (12.6%), Sikonge (12.6%) and Tabora Rural (3.6%) (Table 3.8 and Charts 3.64 and 3.65). Most annual crop growing households do not use any fertiliser (approximately 170,306 households, 72.3%) (Map 3.38). Table 3:9 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Nzega 12,860 38,652 3,087 6,086 1,413 2,767 48,206 61,817 65,566 109,322 Igunga 3,998 20,436 460 625 862 1,562 39,705 119,830 45,025 142,453 Uyui 3,850 16,464 1,124 2,750 8,428 17,736 27,811 58,704 41,212 95,654 Urambo 3,102 12,782 1,364 3,716 13,908 27,027 35,746 71,339 54,120 114,863 Sikonge 1,943 9,520 47 331 5,258 12,859 12,217 30,005 19,464 52,716 Tabora Urban 1,228 3,570 160 209 2,197 2,724 6,622 11,104 10,206 17,606 Total 26,982 101,423 6,240 13,717 32,066 64,676 170,306 352,800 235,594 532,615 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Tabora region was 101,423 ha. The number of households that applied farm yard manure in their annual crops was 26,982 (Table 3.9). Cereals had the highest percent of the total area planted with applied farm yard manure (87.0%), followed by oil seeds (8.0%), pulses (2.7%), root and tuber (1.0%), cash crops (1.0%) and fruits and vegetables (0.4%). Also, cereals had the highest proportion of the planted area with farm yard manure (25% of the total area of cereals in Tabora). This was followed by fruits and vegetables (15%), oil seeds (12%), pulses (11%), roots and tubers (3%) and cash crops (2%) (Chart 3.67a). Table3.8 Planted Area by Type of Fertilizer Use and District Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Nzega 38,652 6,086 2,767 47,505 61,817 Igunga 20,436 625 1,562 22,623 119,830 Uyui 16,464 2,750 17,736 36,950 58,704 Urambo 12,782 3,716 27,027 43,525 71,339 Sikonge 9,520 331 12,859 22,710 30,005 Tabora Urban 3,570 209 2,724 6,503 11,104 Total 101,423 13,717 64,675 179,816 352,800 Chart 3.66 Planted Area with Farm Yard Manure by Crop Type - TABORA Pulses, 2,789, 3% Roots & Tubers, 975, 1% Cash Crop, 902, 1% Oilseeds, 8,118, 8% Fruits & Vegetables, 433, 0% Cereals, 88,206, 87% 0 5 10 15 20 25 30 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.67a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 Farm yard manure was mostly used in Nzega (35.4% of the total planted area in the district), followed by Tabora Urban (24.0%), Sikonge (22.4%), Uyui (17.2%), Igunga (14.3%) and Urambo (11.1%) (Chart 3.67b). For permanent crops, most farm yard manure was used in the production of palm oil (32.%), followed by mango (25.%), banana (23.%), pawpaw (12%) oranges (2%), sugar cane (1.3%), coconut (1.1%), mandarine/tangerine, lemon/lime (1.3%), guava (0.3%) and jack fruits (0.2%) 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Tabora region was 64,676 ha which represents 12.1 percent of the total area planted with annuals in the region and 36 percent of the total planted area with fertilizers. The number of households that applied inorganic fertilizer on their annual crops was 32,066 representing 13.6 percent of the total household planted annual crops (Table 3.10). The largest area applied with inorganic fertilizers was on cash crops (47.4% of the total area applied with inorganic fertilizers) followed by cereals (47.0), fruits and vegetables (2.6%), oil seeds (1.5%), pulses (1.1%) and root and tubers (0.4%) (Chart 3.68). However, the proportion of planted area applied with inorganic fertilizer for fruit and vegetables was 57 percent. This was followed by cash crops (56%), cereals (9%), pulses (23%), oil seeds (1%) and roots and tubers (1%) (Chart 3.69a). Inorganic fertiliser was mostly used in Urambo (23.5% of the total planted area in the district), followed by Uyui (18.5%), Sikonge (6.4%), Nzega (2.5%) and Igunga (1.1%). Tabora Urban reported to have used no inorganic fertilisers (Chart 3.67b). In permanent crops inorganic fertilizers were used in orange (76.2%), followed by sugar cane (22.0%) and mango (1.8%). Chart 3.68 Planted Area with Inorganic Fertilizer by Crop Type - TABORA Cereals, 30,409, 47% Pulses, 712, 1% Cash Crop, 30,634, 47% Oilseeds, 993, 2% Fruits & Vegetables, 1,661, 3% Roots & Tubers, 267, 0% Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop 0 10 20 30 40 50 60 Percent of Planted A rea Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 69a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - TABORA Chart 3.69b Proportion of Planted Area Applied with Inorganic Fertilizer by District - TABORA 0.0 10.0 20.0 30.0 Urambo Uyui Sikonge Nzega Igunga Tabora Urban District P ercent Chart 3.67b Proportion of Planted Area with Farm Yard Manure by District - TABORA 0.0 10.0 20.0 30.0 40.0 Nzega Tabora Urban Sikonge Uyui Igunga Urambo District Percent RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 3.5.4.3 Compost Use The total planted area applied with compost was 13,717 ha which represents only 2.6 percent of the total area planted with annual crops in the region and 7.6 percent of the total planted area applied with fertiliser in the region. The number of households that applied compost manure on their annual crops was 6,240 representing 2.6 percent of the total households that planted annual crops (Table 3.9 and Chart 3.70a). The proportion of area applied with compost was very low for each type of crop (1 to 3%) (Chart 3.70b); however the distribution of the total area using compost manure shows that 67 percent of this area was cultivated with cereals, followed by oil seeds (16%), cash crops (7%) roots and tubers (5%), pulses (5%) and fruits and vegetables (0.1%) (Chart 3.70a). Compost was mostly used in Nzega (5.6% of the total planted area in the district) followed by Tabora Urban (3.2%). Other districts used very little compost (Chart 3.70c). In permanent crops, compost was mostly used in the production of orange (23.1%) followed by mango (22.3%), banana (20.5%), avocado (5.3%) palm oil (11.1%) lime/lemon (7.4%), pawpaw (7.3%), guava (7.3%) and sugar cane (1.0%). 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 115,141 ha of annual crops and vegetables. Insecticides are the most common pesticides used in the region (74% of the total area applied with pesticides). This was followed by fungicides (18%) and herbicides (8%) (Chart 3.71). 0 1 2 3 4 Percent of Planted Area Cereals Ro o ts & Tubers P uls es Oils eeds Fruits & Vegetables Cas h Cro p Crop Type Chart 3.70b Percentage of Planted Area with Compost by Crop Type - TABORA Chart 3.70c Proportion of Planted Area Applied with Compost by District - TABO RA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Nzega Urambo Uyui Tabora Urban Sikonge Igunga D is t ric t Chart 3.71 Planted Area (ha) by Pesticide Use Fungicides, 20,875, 18% Herbicides, 9,327, 8% Insecticides, 84,939, 74% Chart 3.70a Planted Area with Compost Manure by Crop Type - TABORA Pulses, 639, 5% Roots & Tubers, 685, 5% Oilseeds, 2,127, 16% Fruits & Vegetables, 15, 0% Cash Crop, 974, 7% Cereals, 9,276, 67% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 84,939 ha which represented 16 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with insecticides (42,110 ha, 49.6% of the total planted area with insecticides) followed by cash crops (36,819 ha, 43.3%), oil seeds (2,169 ha, 2.6%), pulses (1,629 ha, 1.9%), fruits and vegetables (1,588 ha, 1.9%) and roots and tubers (626 ha, 0.7%) (Chart 3.72). However, the percent of insecticides used in cash crops and fruits and vegetables is much greater than in other crop types (67.0% and 54.7% respectively), while only 2 percent of roots and tubers were applied with insecticides (Chart 3.73). Annual Crops with more than 50 percent insecticide use were cabbage (100%), ginger (100%), radish (92.2%), tobacco (85.3%) and onions (61.3%). Sikonge had the highest percent of planted area applied with insecticides (25.5% of the total planted area with annual crops in the district). This was closely followed by Uyui (23.6%) then Urambo (22.3%), Tabora Urban (21.3%), Igunga (9.7%) and Nzega (5.2%) (Chart3.74). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 9,327 ha which represented 1.8 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with herbicides (4,871 ha, 51%) followed by cash crops (2,761 ha, 30%), oil crops (738 ha, 8%), pulses (451 ha, 5%) and roots and tubers (340 ha, 4%) and fruits and vegetables (166 ha, 2%) (Chart 3.75). Chart 3.74 Percent of Planted Area Applied with Insecticide by District - TABORA 0.0 10.0 20.0 30.0 Sikonge Uyui Urambo Tabora Urban Igunga Nzega District Percent Chart 3.75 Planted Area Applied with Herbicide by Crop Type Roots & Tubers, 340, 4% Pulses, 451, 5% Oil Seeds & Oil Nuts, 738, 8% Cereals, 4,871, 51% Cash Crops, 2,761, 30% Fruits & Vegetables, 166, 2% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 P ercent o f P la nted A rea Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.73 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Planted Area Applied with Insecticides by Crop Type Roots & Tubers, 625, 1% Pulses, 1,629, 2% Oil Seeds & Oil Nuts, 2,169, 3% Fruits & Vegetables, 1,588, 2% Cereals, 42,110, 49% Cash Crops, 36,819, 43% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 However, the percent of herbicide use on fruits/ vegetables and cash crops was much greater than in other crop types (5.7% and 5.0% respectively) while only 1.1 percent of roots and tubers and 1.1 percent of oil seeds was applied with herbicides (Chart 3.76). The top six annual crops with highest percentage use of herbicides in terms of planted area were tomatoes (11.3%), tobacco (6.7%), yams (6.1%), onions (4.8%), cotton (2.6%) and beans (2.1%). Urambo had the highest percent of planted area applied with herbicides (3.1% of the total planted area with annual crops in the district). This was followed by Tabora Urban (2.2%) then Sikonge (1.9%), Uyui (1.7%) and Igunga (1.2%). The smallest percentage use was recorded in Nzega district (0.9%) (Chart 3.77). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 20,875 ha which represented 3.9 percent of the total area planted with annual crops and vegetables. Cash crops had the largest planted area applied with fungicides (9,013ha, 44%) followed by cereals (8,548 ha, 41%), fruits and vegetables (1,343 ha, 6%), oil seeds (1,011 ha, 5%) roots and tubers (508 ha, 2%) and pulses (451 ha, 2%) (Chart 3.78). However, the percentage use of fungicide in cash crops and cereals was much greater than in other crop types (8.2% and 7.4% respectively), while only 0.9 percent of fruits and vegetables was applied with fungicides (Chart 3.79). Annual crops with more than 40 percent fungicide use were ginger (100%), cucumber (100%), radish (92.2%) and onion (56.8%). Chart 3.77 Proportion of Planted Area Applied with Herbicides by District - TABORA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Urambo Tabora Urban Sikonge Uyui Igunga Nzega District P ercent Chart 3.78 Planted Area Applied with Fungicide by Crop Type Roots & Tubers, 508, 2% Pulses, 451, 2% Oil Seeds & Oil Nuts, 1,011, 5% Fruits & Vegetables, 1,343, 6% Cereals, 8,548, 41% Cash Crops, 9,013, 44% 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.79 Percentage of Crop Type Planted Area Applied with Fungicide 0.0 2.0 4.0 6.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.76 Percentage of Crop Type Planted Area Applied with Herbicides RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 Urambo had the highest percent of planted area with fungicides (7.4% of the total planted area with annual crops in the district). This was followed by Sikonge (5.5%), Tabora Urban (4.2%), Uyui (3.4%), Igunga (2.9%) and Nzega (1.2%) (Chart 3.80). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by draft animals (0.3%) and by powered tools (0.1%) while paddy was harvested by draft animals (0.1%) and powered animal (0.1) percent. All other cereals and annual crops were harvested by hand except small amount of oil seeds and cash crops which were harvested by machines (oil seeds - groundnuts were harvested by draft animals (0.3%) and powered tools (0.3%), cash crops – tobacco was harvested by draft animals (0.7%), powered tools (0.9%) and driven machine (0.9%). 3.5.7 Threshing Methods Hand threshing was the most common method used, with 99.1 percent of the total area planted with cereals being threshed by hand. Human powered tools and engine driven machines were used on cereal crops harvested from 0.1 percent and 0.8 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Tabora region, the area of annual crops under irrigation was 34,866 ha representing 7 percent of the total area planted (Chart 3.81). The area under irrigation during the dry season was not reported. The district with the largest planted area under irrigation for annual crops was Urambo (9,624 ha, 27.6% of the total irrigated planted area with annual crops in the region). This is followed by Uyui (7,037 ha, 20.2%), Igunga (6,822 ha,19.6%), Nzega (6,125 ha, 17.6%), Tabora Urban (2,738 ha, 7.9%) and Sikonge (2,520 ha, 7.2%). When expressed as a percentage of the total area planted in each district, Tabora Urban had the higher percentage with 15.6 percent under irrigation. This was followed by Urambo (8.4%), Uyui (7.4%), Nzega (5.6%), Igunga (4.8%) and Sikonge (4.8%) (Chart 3.82) and Map 3.39). Chart 3.81 Area of Irrigated Land Unirrigated Area, 497,749, 93% Irrigated Area, 34,866, 7% Chart 3.82 Planted Area with Irrigation by District - TABORA 0 2,000 4,000 6,000 8,000 10,000 12,000 Urambo Uyui Igunga Nzega Tabora Urban Sikonge District Irrig a ted A rea (ha ) 0.0 4.0 8.0 12.0 16.0 20.0 P ercenta g e Irrig a tio n Irrigated Area Percent of Irrigated Land Chart 3.80 Proportion of Planted Area with Fungicide by District - TABORA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 Urambo Sikonge Tabora Urban Uyui Igunga Nzega District Percent RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 Of all the different crops and in terms of proportion of the irrigated planted area, ginger, chillies and cucumber were the most irrigated crops with 100 percent irrigation followed by tomatoes (79.6%), onions (73.8%), amaranths (57.9%) and cabbages (44.2%). In terms of crop type, the area under irrigation for roots and tubers was 19,713 ha (56.5% of the total area under irrigation), followed by cereals with 10,780 ha (30.9%), fruit and vegetables (1,836 ha, 5.3%), cash crops (1,701 ha, 4.9%), oil seeds (741 ha, 2.1%) and pulses (94 ha, 0.3%). All of the irrigation on cereals was applied to maize, paddy and sorghum. The number of households practicing irrigation in Tabora region appears to have increased over the eight year intercensal period from 9,000 to 17,181 households. This may not be statically significant due to the small number of households sampled. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from dams (43% of households with irrigation). This was followed by wells (41%) and rivers (7%). Proportions of households that used boreholes and canals as a source of water for irrigation were very small being 4% and 5% respectively (Chart 3.84). Most households using irrigation in Uyui, Nzega and Igunga get their irrigation water from dams (79%, 61% and 60 % respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common method of getting water for irrigation with 69 percent of households using this method. This was followed by gravity with 29 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.85). Most households that used the hand bucket for irrigation were Urambo (38.7%), followed by Uyui (23.6%), Nzega (11.1%), Sikonge (9.9%), Tabora Chart 3.84 Number of Household with Irrigation by Source of Water Well, 7,054, 41% Dam, 7,418, 43% Borehole, 654, 4% Canal, 859, 5% River, 1,196, 7% Canal River Well Dam Borehole Chart 3.85 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 11,828, 69% Gravity, 4,987, 29% Other, 293, 2% Hand Pump, 46, 0% Motor Pump, 26, 0% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.86 Number of Households with Irrigation by Method of Field Application Water Hose, 99, 1% Flood, 5,926, 34% Bucket / Watering Can, 10,821, 63% Sprinkler, 334, 2% Flood Bucket / Watering Can Sprinkler Water Hose Chart 3.83 Time Series of Households with Irrigation - TABORA 17,181 9,000 0 5,000 10,000 15,000 20,000 1995/96 2002/03 Agriculture Year Number of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 (9.0%) and Igunga (7.7%). Gravity was more common in Igunga with 49 percent of households using the method to get water for irrigation, followed by Nzega (32.5), Uyui (8.2%), Sikonge (6.2%), Urambo (2.5%) and Tabora Urban (1.6%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Tabora Urban used some hand and motor pumps for obtaining water. 3.6.4 Methods of Water Application Most households used bucket/watering can (63% of households using irrigation) as a method of field application. This was followed by flood irrigation (34%). Sprinklers and water hose were not widely used (2% and 1% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Tabora region show that there were 217,899 crop growing households (92.5% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 206,605 households storing 28,060 tonnes as of 1st January 2004. This was followed by groundnuts/bambaranuts (111,290 households, 6,695t), paddy (76,850 households, 11,758t), Pulses (50,527 households, 1,995t) and sorghum/millet (21,828 households, 6,195t). Other crops were stored in very small quantities. 3.7.1.1 Methods of Storage The region had 120,421 crop growing households storing their produce in sacks and/or open drums (55% of households that stored crops in the region). The number of households that stored their produce in locally made traditional cribs was 93,554 (43%). This was followed by improved locally made structure (2,312 households, 1%), unprotected piles (685 households, 0.3%), other methods (575 households, 0.3%) and airtight drums (351 households, 0.2 (Chart 3.88). Sacks and/or open drums were the dominant storage method in all districts, with the highest percent of households in Urambo using this method (70% of the total number of households storing crop products in the district). This was followed by Uyui (68%), Tabora Urban (59%), Nzega (54%), Sikonge (46%) and Igunga (27%) (Chart 3.89). Chart 3.87 Number of Households and Quantity Stored by Crop Type - TABORA 0 50,000 100,000 150,000 200,000 250,000 Maize Gnuts/Bamb Nuts Paddy Pulses Sorghum & Millet Cotton Tobacco Crop Number of Household 0 5,000 10,000 15,000 20,000 25,000 30,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.89 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.88 Number of households by Storage Methods - TABORA Locally Made traditional Crib, 93,554, 43% Sacks / Open Drum, 120,421, 56% Modern Store, 0, 0% Airtight Drum, 351, 0% Other, 575, 0% Improved Locally Made Structure, 2,312, 1% Unprotected Pile, 685, 0% Sikonge Igunga Tabora Urban Nzega Urambo Uyui 2,520ha 6,822ha 6,125ha 9,624ha 2,738ha 7,037ha 4.8% 4.8 5.6% 8.4% 15.6% 7.4% 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Uyui Sikonge Igunga Tabora Urban Nzega Urambo 46,116ha 51,227ha 59,851ha 76,141ha 84,091ha 1,725 86% 91.2% 80% 91.1% 93.7% 78.5% 80,000 to 90,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Percent of Planted Area (ha) with Irrigation Planted Area (ha) Planted Area (ha) Planted Area With No Application of Fertilizer Map 3.38 TABORA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Map 3.39 TABORA Area Planted and Percent of Total Planted Area With Irrigation by District Percent of Planted Area (ha) with No Application of Fertilizer Planted Area (ha) With Irrigation RESULTS 57 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 The highest percent of households using locally made traditional cribs was in Igunga (72% of the total number of households storing crops) followed by Sikonge (50%), Nzega (45%), Tabora Rural (39%), Uyui (31%) and Urambo (27%). 3.7.1.2 Duration of Storage Most households (56.7% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (24.6%). The minority of households stored their crop for a period of less than 3 months (18.8%). Most households that stored pulses stored them for a period of 3 to 6 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.90). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Tabora Urban (77.6%) followed by Urambo (57.4%), Nzega (57.2%), Uyui (56.7%), Igunga (52.9%) and Sikonge (49.1%) (Map 3.40). District comparison of duration of storage cannot be done for all crops combined. The analysis has therefore been done for maize only as it is the most commonly stored crop. In general, the quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st January 2004 (Chart 3.91). However, households in Igunga district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 90.8 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at a higher price (Chart 3.92). 0 30,000 60,000 90,000 120,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.90 Normal Length of Storage for Selected Crops Less than 3 Months Between 3 and 6 Months Over 6 Months 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Wheat Cotton Tobacco Gnuts Bamb Nuts Crop Type Chart 3.92 Number of Household by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Chart 3.91 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 Nzega Urambo Igunga Uyui Sikonge Tabora Urban District Quantity (tonnes) 0 5 10 15 20 % Stored Quantity harvested Quantity stored % stored RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.1.4 The Magnitude of Storage Loss About 78.5 percent of households that stored crops had little or no loss. The proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as cotton, tobacco and paddy. The proportion of households that reported a loss of more than a quarter was greatest for maize (6.4% of the total number of households that stored maize). This was followed by sorghum and millet (3.4%), beans and pulses (2.4%), groundnuts/bambaranuts (1.3%) and paddy (0.7%). 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Tabora region (223,896 households, 95% of the total crop growing households) (Chart 3.93a). The percent of households processing crops was very high in all districts (above 80%). Igunga had the lowest percent of households processing crops (80% of crop growing households respectively) (Chart 3.93b). 3.7.2.1 Processing Methods Most households processed their crops using neighbour’s machines representing 85.8 percent (192,153 households). This was followed by those processing on-farm by hand (21,628 households, 9.7%) and farm machines (9,031 households, 4.0%). The remaining methods of processing were used by very few households (less than 1%). Table 3.10: Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Nzega 48,747 9,664 3,076 729 62,216 Igunga 31,956 3,628 1,041 114 36,739 Uyui 27,605 7,179 2,486 735 38,004 Urambo 38,296 10,218 3,083 488 52,084 Sikonge 16,937 1,215 684 335 19,172 Tabora Urban 7,518 1,479 405 282 9,684 Total 171,060 33,383 10,774 2,683 217,899 80 100 Percent of Households Processing Sikonge Tabora Rural Nzega Uyui Urambo Igunga District Chart 3.93b Percentage of Households Processing Crops by District Chart 3.93a Households Processing Crops Households not Processing, 11,725, 5% Households Processing, 223,896, 95% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 Although processing by machine was the most common processing method in all districts in Tabora region, however district differences existed. Nzega has the highest percent of hand processing (30.8%), followed by Urambo (22.2%), and Uyui (18.3%). Processing by trader was more common in Igunga and Nzega (71% and 25% respectively), whilst processing on farm by machine was more prevalent in Nzega, Urambo and Uyui (Chart 3.94). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely the main product and the by-product. The main product is the major product after processing and the by-product is the secondary after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 201,164 households processing crops into flour (90%) followed by grain with 18,970 households (8%). The remaining products were produced by a small number of households (Chart 3.95). The number of households producing by-products accounted for 69 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 126,638 households (81%) followed by husks (23,999 households, 16%) and pulp (1,483 households, 1%). The remaining by-products were produced by a small number of households (Chart 3.96). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 99 percent of the total households that used primary processed product (Chart 3.97). Tabora Urban was the only district that used primary products as fuel for cooking. Chart 3.94 Percent of Crop Processing Households by Methods of Processiong 0 25 50 75 100 125 Sikonge Nzega Uyui Urambo Igunga Tabora Rural District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Factory By Co-operative Union By Trader Other Chart 3.95 Percent of Households by Type of Main Processed Product Grain 8% Oil 1% Juice 0.1% Rubber 0% Pulp 0.9% Flour / Meal 90% Chart 3.96 Number of Households by Type of By-product Oil, 265, 0% Juice, 123, 0% Shell, 832, 1% Other, 97, 0% Pulp, 1,483, 1% Cake, 1,023, 1% Bran, 126,638, 81% Husk, 23,999, 16% Chart 3.97 Use of Processed Product Did Not Use, 268, 0% Fuel for Cooking, 54, 0% Animal Consumption, 1,141, 1% Sale Only, 628, 0% Household / Human Consumption, 221,805, 99% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 Out of 10,955 households that sold processed products, 2,981were from Igunga (27.2% of the total number of households selling processed products in the region), followed by Sikonge with 2,809 households (25.6%), Nzega with 2,098 households (19.1%), Urambo with 1,523 households (13.9%), Uyui with 1,103 household (10.1%) and Tabora Urban with 434 households (4.0%) (Chart 3.98). 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold them to unspecified markets (4,976 households, 45% of households that sold crops). This was followed by selling to neighbours (3,175 households, 29%), local markets and trade stores (1,194 households, 11%), trader at farm (993 households, 9%), marketing co-operatives (231 households, 2%), large scale farm (173 households, 2%) farmers associations (114 households, 1%) and secondary markets (99 households, 1%) (Chart 3.99). There were large differences between districts in the proportion of households selling processed products to unspecified markets with Sikonge district having the largest percent of households in the district selling to those markets (46.7%), whereas Tabora Urban had only 0.5 percent. In Nzega and Urambo no sales were made to unspecified markets. Tabora Urban and Urambo had a higher percent of households relying on neighbours than other outlets. In Nzega, the sale of processed produce to local markets/trade stores and traders at farm were most prominent compared to other districts. The district that had the highest proportion of households selling processed products to marketing cooperative was Uyui. 3.7.3 Crop Marketing The number of households that reported selling crops was 131,403 which represent 55.7 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Urambo (80.3%) followed by Sikonge (62.2%), Uyui (53.0%), Igunga (47.9%), Tabora Urban (45.5%) and Nzega (42.1%) (Chart 3.101 and Map 3.41). 0.0 10.0 20.0 30.0 Percentage of Household Igunga Sikonge Nzega Urambo Uyui Tabora Urban District Chart 3.98 Percentage of Household Selling Processed Crops by District Chart 3.99 Location of Sale of Processed Products Farmers Association, 114, 1% Large Scale Farm, 173, 2% Trader at Farm, 993, 9% Other, 4,976, 45% Marketing Co- operative, 231, 2% Local Market / Trade Store, 1,194, 11% Neighbours, 3,175, 29% Secondary Market, 99, 1% Chart 3.100 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Urambo Tabora Urban Igunga Nzega Sikonge Uyui District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Secondary Market Chart 3.101 Number of Crop Growing Households Selling Crops by Districts 0 10,000 20,000 30,000 40,000 50,000 Urambo Nzega Uyui Igunga Sikonge Tabora Urban District Number of Households 0.0 20.0 40.0 60.0 80.0 100.0 Percent Number of Households Selling Crops Percentage of Households Selling Crops RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (76% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (11%), lack of transport (7%), high transport costs (4%) and lack of market information (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems (Chart 3.102). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 93.3 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts. 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Tabora region few agricultural households (25,655, 10.9%) accessed agricultural credit out of which 24,679 (96%) were male-headed households and 977 (4%) were female headed households. In Nzega, Igunga and Tabora Urban districts only male headed households got agricultural credit whereas in Uyui, Urambo and Sikonge districts both male and female headed households accessed agricultural credit (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 121,210 93.3 Other 4,094 3.2 Price Too Low 3,635 2.8 Trade Union Problems 614 0.5 Co-operative Problems 248 0.2 Market Too Far 100 0.1 Government Regulatory Board Problems 25 0.0 Total 129,925 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Nzega 1,411 100 0 0 1,411 Igunga 336 100 0 0 336 Uyui 7,629 96 309 4 7,938 Urambo 11,186 95 618 5 11,803 Sikonge 3,985 99 50 1 4,034 Tabora Urban 132 100 0 0 132 Total 24,679 96 977 4 25,655 Chart 3.102 Percentage Distribution of Household that Reported Marketing Problems by Type of Problem Market to o Far 11% Open Market P rice To o Lo w 76% No Transpo rt 7% Transpo rt Cos t To o High 4% Other 0% Co -o perative P ro blems 0% Lack o f Market Info rmatio n 1% No Buyer 1% Farmers Ass o ciatio n P ro blems 0% Go vernment Regulato ry Bo ard P ro blems 0% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Tabora region were Cooperatives which provided credit to 22,049 agricultural households (85.9% of the total number of households that accessed credit), followed by family, friends and relatives (5.6%), religious organizations/NGO/projects (4.2%), commercial bank (1.5%), traders / trade stores (1.3%), savings and credit society (1.0%) and other sources (0.5%) (Chart 3.103). Cooperatives were the sole credit providers in Tabora Urban while other credit providers were found in Urambo district only. Religious organizations, NGOs and projects were the major credit providers in Nzega district (Chart 3.104). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region was used on fertilizers (40%) and other agro-chemicals (30%) followed by seeds (14%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment and hiring labour was very low (Chart 3.105). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 57 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (23%), followed by “not wanting to get into debt” (10%) and ‘credit not needed’ (4%). The rest of the reasons were collectively reported by less than 8 percent of the households. Chart 3.103 Percentage Distribution of Households Receiving Credit by Main Source Co-operatives, 86, 85% Other, 1, 1% Trader / Trade Store, 1, 1% Commercial Bank, 2, 2% Saving & Credit Society, 1, 1% Family, Friend and Relative, 6, 6% Religious Organisation / NGO / Project, 4, 4% Chart 3.104 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Percent of Households Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Co-operative Chart 3.105 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 1% Seeds 14% Tools / Equipment 5% Irrigation Structures 2% Agro-chemicals 30% Other 6% Fertilizers 40% Labour 2% Chart 3.106 Reasons for not Using Credit (% of Households) Did not know how to get credit, 66,223, 31% Don't know about credit, 54,206, 26% Not available, 47,318, 23% Did not want to go into debt, 21,580, 10% Difficult bureaucracy procedure, 5,730, 3% Not needed, 8,744, 4% Credit granted too late, 1,418, 1% Other, 275, 0% Interest rate/cost too high, 4,768, 2% Tabora Urban Uyui Nzega Igunga Sikonge 77.6% 57.2% 56.7% 57.4% 52.9% 49.1% Urambo Uyui Urambo Igunga Sikonge Tabora Urban Nzega 21,884 43,449 21,622 12,147 4,669 27,633 53% 80.3% 47.9% 62.2% 45.5% 42.1% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 71.9 > 66.2 to 71.9 60.5 to 66.2 54.8 to 60.5 49.1 to 54.8 Tanzania Agriculture Sample Census Percent of Total Households Selling Crops Number of Households Selling Crops Percent of Households Storing Crops Percent of Households Storing Crops Map 3.40 TABORA Percent of Households Storing Crops for 3 to 6 Months by District Map 3.41 TABORA Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops RESULTS 64 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 62,956 (27% of total crop growing households in the region) (Chart 3.107). Some districts had more access to extension services than others, with Tabora Urban having a relatively high proportion of households (73%) that received crop extension messages in the district followed by Uyui (30%), Sikonge (27%), Urambo (25%), Nzega (24%) and Igunga (19%). (Map 3.42) 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (80%, 49,275 households). NGOs provided 13.8 percent, cooperatives (4.8%), large scale farms (0.9%) and the remaining providers (0.5%) (Chart 3.109). District differences existed with the proportion of the households receiving advice from government services ranging from between 54.2 percent in Urambo to 98.6 percent in Igunga. Chart 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider Government 80.0% Other 0.5% NGO / Development Project 13.8% Cooperative 4.8% Large Scale Farm 0.9% Chart 3.108 Number of Households Receiving Extension by District 0 10,000 20,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District N um ber of Households 0 20 40 60 80 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.110 Number of Households Receiving Extension by Quality of Services Very Good, 9,547, 15.4% No Good, 358, 0.6% Poor, 1,361, 2.2% Average, 10,282, 16.6% Good, 40,449, 65.2% Chart 3.107 Number of Households Receiving Extension Advice Households Receiving Extension Advice, 62,956, 27% Households Not Receiving Extension Advice, 172,665, 73% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.8.2.2 Quality of Extension On the quality of extension, 65.2 percent of the households receiving extension ranked the service as being good followed by average (16.6 %), very good (15.4%), poor (2.2%) and no good (0.6%) (Chart 3.110). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tabora region regardless of whether the households grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm eg., improved seeds, inorganic fertilizers, insecticides, fungicides and herbicides. In Tabora region farm yard manure was used by 65,279 households which represent 28 percent of the total number of crop growing households. This was followed by households using insecticides/fungicides (20%), inorganic fertilizers (20%), improved seeds (19%), compost manure (7%) and herbicides (1%) (Table 2.13). 3.9.1 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Tabora mostly purchased them from the local cooperatives (57.3% of the total number of inorganic fertiliser users), from the local markets (33.7%) and from local farmers groups (5%). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.111). Access to inorganic fertiliser was mainly less than 10 km from the household with most households residing less than 1 km from the source (30.5%), followed by between 3 and 10 km (21.9%) and between 1 and 3 km (21%) (Chart 3.112). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (20% ) as the reason for not using, it may be assumed that access is not the main reason for not using them. Other reasons such as cost are more important with 73 percent of households responding to cost factors as the main reason for not using the fertilizers. Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 65,279 28 170,342 72 Improved Seeds 45,706 19 189,914 81 Insecticides/Fungicide 47,859 20 187,761 80 Compost Manure 15,368 7 220,253 93 Inorganic Fertilizers 46,287 20 189,334 80 Herbicides 2,056 1 233,565 99 Chart 3.111 Number of Households by Source of Inorganic Fertiliser 0.1 0.2 0.1 0.3 0.9 2.5 5.0 33.7 57.3 0 10,000 20,000 30,000 Co-operative Local market/Trade Local Farmers Group Neighbour Crop Buyers Locally Produced by Household Secondary Market Development Project Large Scale Farm Source of Inorganic Fertiliser Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 In other words, if the cost was affordable the demand would be higher and inorganic fertiliser would be made more available.More smallholders use inorganic fertilisers in Urambo than in other districts in Tabora region (46.1% of households using inorganic fertilisers), followed by Uyui (23.8%) and Sikonge (14.6%). Other districts use very little inorganic fertiliser. 3.9.2 Improved Seeds The percent of households that used improved seeds was 19.4 percent of the total number of crop growing households. Most of the improved seeds were obtained from the cooperatives (55.1%) followed by from local markets/trade stores (29%). Other less important sources of improved seeds were from local farmers group (5.1%), locally produced by households (3.3%), neighbours (2.6%), crop buyers (2.5%) and development projects (1.7%). Only 0.6 percent and 0.1 percent of households using improved seeds were from secondary markets and other sources respectively (Chart 3.113). Access to improved seeds was mainly less than 10 km from the household with most households residing less than 1 km from the source (33%), followed by between 1 and 3 km (21%) and between 3 and 10 km (21%) (Chart 3.114). The districts that used improved seeds most were Igunga (35.7 percent of the total number of households in the district), followed by Urambo (20.1%). Use of improved seeds in other districts is of minor importance (Map 3.42). 3.9.3 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchased them from cooperatives (55.2% of the total number of fungicides users) and local markets/trade stores (32.9%). Other sources of insecticides/ fungicides were of minor importance (Chart 3.115). Chart 3.116 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticides/fungicides. Chart 3.115 Number of Household by Source of Insecticide/fungicide 55.2 32.9 4.2 3.4 1.9 1.4 0.7 0.4 0.1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Co-operative Local Market/Trade Local Farmers Group Neighbour Crop Buyers Secondary Market Locally Produced by Household Development Project Large Scale Farms Source of Insecticide/fungicide Number of Households Chart 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.113 Number of Households by Source of Improved Seed 0.1 0.6 1.7 2.5 2.6 3.3 5.1 29.0 55.1 0 5,000 10,000 15,000 20,000 25,000 30,000 Co-operative Local Market / Trade Store Local Farmers Group Locally Produced by Household Neighbour Crop Buyers Development Project Secondary Market Other Source of Improved Seeds Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 The small number of households using insecticides/fungicides coupled with the 18 percent of households responding to “not available” as the reason for not using them, it may be assumed that access is not the main reason for not using them. Other reasons such as cost are more important with 72 percent of households responding to cost factor as the main reason for not using them. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were mostly used in Urambo district (33.7 percent of the total number of households that use fungicide in the region), followed by Uyui (24.7%), Igunga (12.9%) and Sikonge (12.7%). Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 4,619 representing 2 percent of the total number of agriculture households (Chart 3.117). The number of trees planted by smallholders on their allotted land was 190,349 trees. The average number of trees planted per household planting trees was 41. The main species planted by smallholders was Moringa spp (52,394 trees, 27.5%), followed by Albizia Spp (34,292, 18.0%), then Acacia Spp (32,393, 17.0%) and Eucalyptus Spp (29,003 trees, 15.2%). The remaining trees species were planted in comparatively small numbers (Chart118.). Uyui has the largest numbers of smallholders with planted trees than any other district (44.0%) and the trees were dominated by Moringa Spp. and Eucalyptus Spp. This is followed by Urambo (40.0%) with the trees dominated by Albizia Spp and Acacia Spp and Nzega (7.3%) where the trees were mainly Gravellis Spp. (Chart 3.119 and Map 3.45.). Smallholders mostly plant trees on plantation or coppice. The proportion of households that plant on plantation is 58 percent, followed by scattered around fields (32%) and then trees planted on the field boundaries (10%) (Chart 3.120). Chart 2.118 Number of Planted Trees by Species - TABORA 0 10,000 20,000 30,000 40,000 50,000 60,000 Moringa Spp Albizia Spp Acacia Spp Eucalyptus Spp Leucena Spp Senna Spp Gravellis Azadritachta Spp Pinus Spp Terminalia Ivorensis Syszygium Spp Others Tree Species Number of Trees Chart 3.119 Number of Trees Planted by Smallholders by Species and District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Uyui Urambo Sikonge Igunga Nzega Tabora Urban District Number of Trees Moringa Spp Albizia Spp Acacia Spp Eucalyptus Spp Leucena Spp Senna Spp Gravellis Azadritachta Spp Pinus Spp Terminalia Ivorensis Syszygium Spp Others Chart 3.120 Number of Trees Planted by Location Plantation/Copp- ice, 109,041, 58% Scattered in field, 61,461, 32% Field boundary, 19,847, 10% Chart 3.117 Number of Households with Planted Trees Growing Trees, 4,619, 2% Not Growing Trees, 231,298, 98% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 The main purpose of planting trees was to obtain wood for fuel (42.57%). This was followed by shade (25.9%), planks/timber (6.3%), poles (4.1%) and medicinal (1.7%). Other purposes were reported by 19.4 percent of the households (Chart 3.121, Map 3.44). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 5,399 which represented 2 percent of the total number of agricultural households in the region (Chart 3.122). The proportion of households with soil erosion control and water harvesting facilities was highest in Tabora Urban (7.1%) followed by Uyui (4.9%), Nzega (2.5%), Urambo (1.8%), Sikonge (1.8%) and Igunga (0.2%) (Chart 3.123). Erosion control bunds accounted for 50 percent of the total number of structures, followed by dam (16.1%), tree belts (14.7%), water harvesting bunds (11.4%), drainage ditches (3.4%), terraces (1.9%), vetiver grass (1%) and gabions / sandbag (1.1%) (Chart 3.124 and Map 3.45). Erosion control bunds, dam and tree belts together had 23,131 structures. This represented 81 percent of the total structures in the region. The remaining 19 percentages were shared among the rest of the erosion control methods mentioned above. Urambo and Uyui districts had 16,859 erosion control structures (59 percent of the total erosion structures in the region). Chart 3.122 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 230,518, 98% Households with facilities, 5,399, 2% Chart 3.123 Number of Households with Erosion Control/Water Harvesting Facilities 0 500 1,000 1,500 2,000 2,500 Tabora Urban Uyui Nzega Urambo Sikonge Igunga District Number of Households 0.0 2.0 4.0 6.0 8.0 Percent Number of Households Percent Chart 3.124 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Erosion Control Bunds Dam Tree Belts Water Harvesting Bunds Drainage Ditches Terraces Vetiver Grass Gabions / Sandbag Type of Faciliy Number of Structures Chart 3.121 Number of Households by Purpose of Planted Trees 0.0 15.0 30.0 45.0 Wood for Fuel Shade Other Planks / Timber Poles Medicinal Use Percent of Households Tabora Urban Uyui Nzega Igunga Urambo Sikonge 1,700 21,710 2,416 29,712 8,173 5,370 45.4% 2.9% 34.4% 14.9% 29.1% 11.4 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 236 5,692 11,036 570 21,533 1,066 6.3% 0.7% 24.9% 20.1% 7.6% 2.3% 16,000 to 22,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Percent of Crop Growing HouseholdsUsing Improved Seeds Number Households Using Improved Seeds Number of Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services Map 3.42 TABORA Number of Households and Percent of Total HouseholdsReceiving Crop Extension Services by District Map 3.43 TABORA Number and Percent of Crop Growing Households Using Improved Seeds by District Number Households Using Improved Seeds Number of Households Receiving Crop Extension Services % RESULTS 70 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 727 2,209 965 1,041 115 343 7.1% 2.5% 1.8% 0.2% 4.9% 1.8% 2,000 to 3,000 2,000 to 2,000 2,000 to 2,000 1,000 to 2,000 0 to 1,000 Tabora Urban Uyui Sikonge Urambo Igunga Nzega 555,548 2,438,158 2,685,052 643,721 2,642,671 5,361,219 3.9% 37.4% 18.7% 4.5% 17% 18.4% 4,000,000 to 6,000,000 3,000,000 to 4,000,000 2,000,000 to 3,000,000 1,000,000 to 2,000,000 0 to 1,000,000 Tanzania Agriculture Sample Census Percent of Households with Water Harvesting Bunds Number of Smallholder Number of Smallholder Planted Trees Map 3.44 TABORA Number and Percent of Smallholder Planted Trees by district Map 3.45 TABORA Number and Percent of Households With Water Harvesting Bunds by District Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Number of Households with Water Harvesting Bunds RESULTS 71 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 1,568,691. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 9.3 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Tabora region was 1,566,169 (99.8 % of the total number of cattle in the region), 1,851 cattle (0.12%) were dairy breeds and 671 cattle (0.04%) were beef breeds. The census results show that 65,925 agricultural households in the region (27.9% of total agricultural households) kept 1.6 million cattle. This was equivalent to an average of 24 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Igunga which had about 466,892 cattle (29.8% of the total cattle in the region). This was followed by Nzega (425,021 cattle, 27.1%), Sikonge (272,100 cattle, 17.3%), Uyui (205,865 cattle, 13.1%) and Urambo (131,000 cattle, 8.4%). Tabora Urban had the least number of cattle (67,812 cattle, 4.3%) (Chart 3.126 and Map 3.46). Igunga district had the highest density (176 head per km2 ) (Map 3.47). Although Igunga district had the largest number of cattle in the region, most of it was indigenous. Also the district had the largest number of dairy cattle but it had no beef cattle. In general, the number of beef cattle in the region was insignificant (Chart 3.126). 3.12.1.2 Herd Size Twenty four percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 38 percent of all cattle in the region. Only 15.4 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 82.5 percent of total cattle rearing households had herds of size 1-30 cattle and owns 41 percent of total cattle in the region, resulting in an average of 12 cattle per cattle rearing household. There were about 782 households with herd sizes of more than 151 cattle each (278,198 cattle in total) resulting in an average of 356 cattle per household. 0 100 200 300 400 500 Number of Cattle ('000') Igunga Nzega Sikonge Uyui Urambo Tabora Urban District Chart 3.125 Total Number of Cattle ('000') by District Chart 3.126 Number of Cattle by Type and District 0 100,000 200,000 300,000 400,000 500,000 Igunga Nzega Sikonge Uyui Urambo Tabora Urban District Num ber of Cattle Indigenous Beef Dairy RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 3.12.1.3 Cattle Population Trend Cattle population in Tabora increased during the period of eight years from 1,009,571 in 1995 to 1,568,691 cattle in 2003. This implies an overall annual positive growth rate of 5.7 percent (Chart 3.127). However, there was a very sharp increase in number of cattle for the period of four years from 1995 to 1999 at the rate of 12.7 percent whereby the number increased from 1,009,571 to 1,626,130. The number of cattle is estimated to have decreased from 1,626,130 in 1999 to 1,568,691 in 2003 at the rate of -0.9 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Tabora region was 2,522 (1,851 dairy and 671 improved beef). The diary cattle constituted 0.11 percent of the total cattle and 73.4 percent of improved cattle in the region. The number of beef cattle in the region was small constituting 26.6 percent of the total number of the improved cattle and 0.04 percent of the total cattle. The number of improved cattle increased from zero in 1995 to 2,522 in 2003 whilst the number increased from 904 in 1999 to 2,522 in 2003 at the growth rate of 29%. 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Tabora region ranked 6 out of the 21 regions with 6.1 percent of the total number goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Tabora region was 65,487 (28% of all agricultural households in the region) with a total of 718,996 goats giving an average of 11 head of goats per goat-rearing-household. Igunga had the largest number of goats (234,077 goats, 32.6% of all goats in the region), followed by Nzega (185,172 goats, 25.8%), Uyui (124,998 goats, 17.4%) and Urambo (93,826 goats, 13.0). Sikonge and Tabora Urban had the least number of goats (54,087 goats, 7.5% and 26,836 goats, 3.7% respectively) (Chart 3.129 and Map 3.48). Igunga district had also the highest density of goats (88 head per km2 ) (Map 3.49). 1,009,571 1,626,130 1,568,691 0 500,000 1,000,000 1,500,000 2,000,000 Number of Cattle 1995 1999 2003 Year Chart 3.127 Cattle Population Trend 0 904 2,522 0 1000 2000 3000 Number of Cattle 1995 1999 2003 Year Chart 3.128 Improved Cattle Population Trend 0 50 100 150 200 250 Number of Goats Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Chart 129 Total Number of Goats ('000') by District RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12.2.2 Goat Herd Size Twenty four percent of the goat-rearing households had herd sizes of 1-4 goats with an average of 3 goats per goat rearing household. Seventy seven percent of total goat-rearing households had herd size of 1-14 goats and owned 47 percent of the total goats in the region resulting in an average of 7 goats per goat-rearing households. The region had 2,188 households (3%) with herd sizes of 40 or more goats each (113,118 goats in total), resulting in an average of 52 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.4 percent of the total goats in Tabora region. Improved goats for meat and diary goats constituted 0.83 and 0.81 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 5.6 percent. This positive trend implies eight years of population increase from 464,327 in 1995 to 718,996 in 2003. The number of goats increased from 464,327 in 1995 at an estimated annual rate of 18.1 percent to 903,652 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -5.5 percent (Chart 130). 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Tabora region after cattle and goats. The region ranked 6 out of 21 Mainland regions and had 6 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 28,126 (12% of all agricultural households in Tabora region) rearing 235,213 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Igunga with 101,570 sheep (43.2% of total sheep in Tabora region) followed by Uyui (60,347 sheep, 25.7%), Nzega (42,118 sheep, 17.9%) and Sikonge (19,838 sheep, 8.4%). Urambo and Tabora Urban had the least number of sheep [6,019 sheep (2.6%) and 5,321 sheep (2.3%) respectively] (Chart 3.131 and Map 3.50). Igunga district also had the highest density of sheep (38 head per km2 ) (Map 3.51). Sheep rearing was dominated by indigenous breeds that constituted 88 percent of all sheep kept in the region. Only 12 percent of the total sheep in the region were improved breeds. 0 20,000 40,000 60,000 80,000 100,000 120,000 Number of Sheep Igunga Uyui Nzega Sikonge Urambo Tabora Urban District Chart 3.131 Total Number of Sheep by District 464,327 903,652 718,996 0 200,000 400,000 600,000 800,000 1,000,000 Number of Goats 1995 1999 2003 Year Chart 3.130 Goat Population Trend RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 75 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated to be 5.7 percent. The population increased at an average annual rate of 13 percent from 151,034 in 1995 to 245,723 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -1.1 percent (Chart 3.132). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 16 out of 21 Mainland regions and had 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Tabora region was 2,719 (1.2% of the total agricultural households in the region) rearing 6,286 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Urambo with 4,172 pigs (66.4% of the total pig population in the region) followed by Nzega (1,083 pigs, 17.2%), Uyui (739 pigs, 11.8%) and Tabora Urban (292 pigs, 4.6%) (Chart 3.133 and Map 3.52). However Urambo district had the highest density of pigs (0.5 head per km2 ) (Map 3.53). There were no pigs in Igunga and Sikonge districts. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population over the eight-year period from 1995 to 2003 was 5.6 percent. During this period the population grew from 4,071 to 6,286. The pig population increased very much from 4,071 in 1995 to 30,406 in 1999 at a rate of 65.3 percent. The growth rate dropped to -32.6 percent during the following four years from 1999 to 2003 in which pig population decreased from 30,406 to 6,286 (Chart 3.134). 3.12.5 Chicken Production The poultry sector in Tabora region was dominated by chicken production. The region contributed 7.5 percent to the total chicken population on Tanzania Mainland. 151,034 245,723 235,213 0 100,000 200,000 300,000 Number of Sheep 1994/95 1998/99 2002/03 Year Chart 3.132 Sheep Population Trend 0 1,000 2,000 3,000 4,000 5,000 Number of Pigs Urambo Nzega Uyui Tabora Urban District Chart 3.133 Total Number of Pigs by District 4,071 30,406 6,286 0 10,000 20,000 30,000 40,000 N um ber o f P ig s 1995 1999 2003 Year Chart 3.134 Pig Population Trend RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.5.1 Chicken Population The number of households keeping chicken was 168,339 raising about 2,507,469 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country, Tabora region was ranked fourth out of the 21 Mainland regions. The District with largest number of chickens was Urambo with 647,562 chickens (25.8% of the total number of chickens in the region) followed by Uyui (582,803, 23.2%), Nzega (496,490, 19.8%), Igunga (360,864, 14.4%) and Sikonge (341,572, 13.6%). Tabora Urban had the smallest number of chickens (78,178, 3.1%) (Chart 3.135 and Map 3.54). However Nzega district had the highest density of chickens (201 chickens per km2 ) (Map 3.55). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 5.1 percent. The population increased at a rate of 11.4 percent from 1995 to 1999 after which it decreased by -0.7 percent for the remaining four years from 1999 to 2003 (Chart 3.136). About 99.6 percent of all chicken in Tabora region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 74.6 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 8 chickens per holder. About 25.0 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 31 chickens per holder. Only 0.3 percent of holders kept the flock sizes of more than 100 chickens at an average of 366 chickens per holder (Table 3.14). Table 3.14 Number of Household and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 28,432 17 83,765 3 5 - 9 46,552 28 309,940 7 10 - 19 50,056 30 645,709 13 20 - 29 23,087 14 517,953 22 30 - 39 9,792 6 312,264 32 40 - 49 4,126 2 173,702 42 50 - 99 4,771 3 289,704 61 100+ 477 0 174,432 365 Total 167,294 100 2,507,469 15 1,679,258 2,584,112 2,507,469 0 1,000,000 2,000,000 3,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.136 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Number of Chicken Urambo Uyui Nzega Igunga Sikonge Tabora Urban District Chart 3.135 Total Number of Chicken by District Tabora Urban Uyui Urambo Nzega Igunga Sikonge 96.2 16.4 172.2 175.5 42.9 24.8 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Uyui Tabora Urban Igunga Nzega Sikonge Urambo 205,865 466,892 425,021 272,100 131,000 67,812 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Tanzania Agriculture Sample Census Number of Cattle Map 3.46 TABORA Cattle population by District as of 1st Octobers 2003 Map 3.47 TABORA Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km Number of Cattle Number of Cattle Per Square Km RESULTS 77 Tabora Urban Uyui Urambo Sikonge Igunga Nzega 38.1 11.8 4.9 26 88.3 75.1 80 to 90 60 to 80 40 to 60 20 to 40 0 to 20 Uyui Sikonge Igunga Tabora Urban Nzega Urambo 124,998 54,087 234,077 185,172 93,826 26,836 200,000 to 250,000 150,000 to 200,000 100,000 to 150,000 50,000 to 100,000 0 to 50,000 Tanzania Agriculture Sample Census Number of Goats Map 3.48 TABORA Goat population by District as of 1st Octobers 2003 Map 3.49 TABORA Goats Density by District as of 1st October 2003 Number of Goats Per Square Km Number of Goats Number of Goats Per Square Km RESULTS 78 Tabora Urban Uyui Urambo Sikonge Nzega Igunga 7.6 0.8 1.8 12.6 17.1 38.3 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tabora Urban Urambo Nzega Igunga Uyui Sikonge 5,321 6,019 42,118 101,570 60,347 19,838 Tanzania Agriculture Sample Census Number of Sheep Map 3.50 TABORA Sheep population by District as of 1st Octobers 2003 Map 3.51 TABORA Sheep Density by District as of 1st October 2003 Number of Sheep Per Square Km Number of Sheep Number of Sheep Per Square Km 80,000 to 110,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 79 Nzega Igunga Sikonge Tabora Urban Urambo Uyui 0 0 0 0 1 0 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Igunga Sikonge Uyui Nzega Urambo Tabora Urban 0 0 739 1,083 4,172 292 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Number of Pig Map 3.52 TABORA Pig population by District as of 1st Octobers 2003 Map 3.53 TABORA Pig Density by District as of 1st October 2003 Number of Pig Per Square Km Number of Pig Number of Pig Per Square Km RESULTS 80 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 111 81.3 201.3 136.1 121.4 31.2 Urambo Igunga Tabora Urban Nzega Uyui Sikonge 647,562 360,864 496,490 78,178 582,803 341,572 Tanzania Agriculture Sample Census Number of Chicken Map 3.54 TABORA Chicken population by District as of 1st Octobers 2003 Map 3.55 TABORA Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km Number of Chicken Number of Chicken Per Square Km 400,000 to 700,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 RESULTS 81 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.5.4 Improved Chickens (layers and broilers) The overall annual growth rate for layers during the eight-year period from 1995 to 2003 decreased at an annual rate of - 6.1 percent during which the population decreased from 6,507 to 3,949. For the last four year period layers chicken population decreased at an annual rate of -5.5 percent from 4,950 in 1999 to 3,949 in 2003. The number of improved chicken was most significant in Nzega District followed by Uyui (Chart 3.137). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 9.0 percent during which the population grew from 2,675 to 5,330. The average annual growth rate was higher (65.7%) during the period of four years from 1995 to 1999. The broiler population exhibited a decreasing trend at the rate of -28.3 percent per annum for the period of four years resulting at decrease from 20,142 in 1999 to 5,330 2003 (Chart 3.138). 3.12.6. Other Livestock There were 57,565 ducks, 1,830 turkeys, 7,171 rabbits and 26,294 donkeys raised by rural agricultural households in Tabora region. Table 3.15 shows the number of livestock kept in each district. The biggest number of ducks in the region was found in Uyui District (47% of all ducks in the region), followed by Nzega (22%), Urambo (16%), Igunga (9%) and Sikonge (4%). Tabora Urban had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Nzega, Igunga and Sikonge districts only (Table 3.15). 3.12.7 Pest and Parasite Incidence and Control According to the results indicate that 59 percent and 37 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.139 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidence of ticks’ problem was highest in Igunga district whilst the incidence of tsetse flies problem was highest in Sikonge district. The incidences of both problems were lowest in Tabora Urban. (Map 3.56). Table 3.15 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Nzega 12,653 890 0 1,197 901 Igunga 5,420 656 0 11,055 341 Uyui 27,042 0 633 13,896 1,019 Urambo 9,171 0 6,438 0 2,552 Sikonge 2,129 285 99 146 0 Tabora Urban 1,151 0 0 0 0 Total 57,565 1,830 7,171 26,294 4,813 3,522 438 109 811 317 2,740 0 1,242 0 99 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Number of Chickens Nzega Igunga Uyui Urambo Sikonge District Chart 3.137 Number of Improved Chicken by Type and District Layer Broiler Chart 3.139 PercentageKeeping Households Reporting Tsetseflies and Tick Problems by District 0 20 40 60 80 Igunga Nzega Sikonge Uyui Urambo Tabora Urb District Percent Ticks Tsetseflies 6,507 2,675 4,950 20,142 3,949 5,330 0 5,000 10,000 15,000 20,000 25,000 Number of Improved Chickens 1995 1999 2003 Year Chart 3.138 Improved Chicken Population Trend Layers Broilers RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 83 The most practiced method of tick control was spraying with 49 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (10%), smearing (5%) and other traditional methods like hand picking (9%). However, 25 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 29 percent of livestock- rearing households. This was followed by dipping (6%) trapping (6%) and smearing (3%). However, 41 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 30,028 (34% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 34, goats (17%) and sheep (15%) (Chart 3.140). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 16,853, representing 19.2 percent of the total livestock- rearing households and 7.1 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 83.8 percent of all households receiving livestock extension services followed by co-operatives (11.1%). The rest of the households got services from NGOs/development projects (4.1%) and large- scale farmers (0.5%). About 45 percent of livestock rearing households described the general quality of livestock extension services as being good, 10 percent said they were average and 16 percent said they were very good. However, 25 percent of the livestock rearing households said the quality was not good whilst 4 percent described them as poor (Chart 3.141). 0 10 20 30 40 50 Percent Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.140 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good 45% Very Good 16% Poor 4% No Good 25% Average 10% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 75 percent of the livestock rearing households accessed the services, at a distance of more than 14 km. Only 25 percent of them accessed the services within 14 km from their dwellings (Chart 3.142). The most affected district was Sikonge district with 91 percent of all livestock rearing households accessing the services at a distance of more than 14 km. Tabora Urban was the least affected because about 60 percent of the households could access the service within a distance of 14 kilometers. (Chart 3.143). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 km from the nearest watering point was 52,689 (86% of livestock rearing households in Tabora region) whilst 7,597 households (12%) resided between 5 and 14 km. However, 1,282 households (2%) had to travel a distance of 15 or more km to f the nearest watering point (Chart 3.144). Uyui district had the best livestock water supply with the majority of livestock rearing households residing within 5 km from the nearest watering point. This is followed by Urambo, Sikonge, Nzega and Tabora Urban districts. In Igunga district about 32 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.145) Chart 3.142 Number of Households by Distance to Veterinary Clinic Less than 14km, 19,482, 25% More than 14km, 59,848, 75% Chart 3.144 Number of Households by Distance to Village Watering Points 15 or more kms, 1,282, 2% 5-14kms, 7,597, 12% Less than 5kms, 52,689, 86% Chart 3.143 Number of Households by Distance to Veterinary Clinic and District 0 5,000 10,000 15,000 20,000 25,000 30,000 Nzega Uyui Urambo Igunga Sikonge Tabora Urban District Number of Households Less than 14km More than 14km Chart 3.145 Number of Households by Distance to Village Watering Point and District 0 5,000 10,000 15,000 20,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District N um ber o f H o useho lds Less than 5kms 5-14kms 15 or more kms RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Tabora region is limited in some districts while it is common in other districts. Draft animals were used by 88,862 households (38% of the total agricultural households in the region) (Chart 3.146). The number of households that used draft animals in Igunga was 34,913 representing 39.3 percent of the households using draft animals in the region followed by Nzega (34,629 households, 39.0%), Uyui (9,192 households, 10.3%), Urambo (5,525 households, 6.2%) and Sikonge (3,754 households, 4.2%). In Tabora Urban only 849 households (1%) used draft animals. (Chart 3.147 and Map 3.57). The region had 370,495 oxen (162,466 oxen in Igunga, 120,742 oxen in Nzega, 42,341 oxen in Uyui, 25,202 oxen in Urambo, 15,992 oxen in Sikonge and 3,752 oxen in Tabora Urban) that were used to cultivate 223,878 hectares of land. This represents 8.8 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Igunga district (162,466 ha, 44% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Tabora region was 68,504 (29% of total crop growing households in the region) (Chart 3.148). The total area applied with organic fertilizer was 176,963 ha of which 159,104 hectares (90% of the total area applied with organic fertilizer or 29.9% of the area planted with annual crops and vegetables in Tabora region during the long rainy season) was applied with farm yard manure. The largest area applied with farm yard manure was found in Nzega district with 26,328 hectares (40.9% of the total area applied with farm yard manure) followed by Igunga (11,737 ha, 18.2%), Urambo (8,972 ha, 13.9%), Uyui (8,880 ha, 13.8%), Sikonge (5,695 ha, 8.8%) and Tabora Urban (2,803 ha, 4.4%) (Chart 3.149 and Map 3.58). 3.146 Number of Households Using Draft Amimals Not Using Draft Animals, 147,055, 62% Using Draft Animals, 88,862, 38% 0 10,000 20,000 30,000 40,000 N um ber o f H o useho lds Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Chart 3.147 Number of Households Using Draft Animals by District - TABORA T Chart 3.148 Number of Household Using Organic Fertilizer Using Organic Fertilizer, 68,504, 29% Not Using Organic Fertilizer, 167,117, 71% Chart 3.149 Area of Application of Organic Fertilizer by District - TABORA 0 10,000 20,000 30,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Area of Fertilizer Application (ha) Farm Yard Manure Compost Manure RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 3.12.9.4 Use of Compost Only 7,230 ha (10.% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost manure was found in Urambo district with 4,104 hectares (56.8% of the total area applied with compost manure) followed by Nzega (1,713 ha, 23.7%), Uyui (732 ha, 10.1%), Igunga (537 ha, 7.4%), Sikonge (84 ha, 1.2%) and Tabora Urban (60 ha, 0.8%) (Chart 3.149 and Map 3.59). 3.12.10 Fish Farming The number of households involved in fish farming in Tabora region was 222, representing 0.1 percent of the total agricultural households in the region (Chart 3.150 and Map 3.60). Sikonge and Uyui districts were the leading districts each with 98 households involved in fish farming. This was followed by Tabora Urban (26 households). Fish farming was not practiced in Nzega, Igunga and Urambo districts (Chart 3.151). The main source of fingerings was the neighbours which provided fingering to 49 percent of the fish farming households. About 38 percent of households practicing fish farming got fingerings from the government and 12 percent got them from non-governmental organizations and projects. All fish farming households in the region used the dug-out-pond system and the main fish specie planted was Carp. The number of fish harvested in Tabora region was 76,689, of which 55,768 fish (73%) were carp and 15,767 (21%) were tilapia whilst 5,153(7%) were other types (Chart 3.152) . All households (100%) did not sell fish. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. Chart 3.150 Number of Households Practicing Fish Farming - TABORA Households Not Practicing Fish Farming, 235,694, 100% Households Practicing Fish Farming, 222, 0% 0 20 40 60 80 100 N u m b er o f H o u seh o ld s Sikonge Uyui Tabora Urban Nzega Igunga Urambo District Chart 3.151 Number of Households Practicing Fish Farming by District - TABORA Chart 3.152 Fish Production Number of Others, 5,153, 6.7% Number of Carp, 55,768, 72.7% Number of Tilapia, 15,767, 20.6% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 113 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (88), hospital (44), tertiary market (43), secondary school (27), all weather road (14), primary market (12), health clinic (10), primary school (4) and feeder road (3) (Table 3.17). Table 3.16: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Nzega 19.4 2.7 6.7 3.2 31.4 9.8 41.9 105.8 8.5 15.9 26.6 69.2 Igunga 13.6 2.4 9.1 2.1 25.2 6.4 46.3 163.9 7.0 14.9 27.0 107.1 Uyui 43.7 5.8 11.8 4.5 61.1 18.1 70.5 68.5 13.1 32.4 64.4 68.6 Urambo 22.4 5.7 19.0 3.2 58.4 8.9 63.5 125.8 13.3 19.4 48.3 115.8 Sikonge 67.3 3.5 47.1 2.0 67.0 7.8 76.8 133.4 28.6 25.8 86.0 119.4 Tabora Urban 14.6 4.1 3.8 0.8 13.5 8.2 14.0 14.5 9.4 13.3 13.9 5.0 Total 27.0 4.0 14.1 3.0 43.8 10.1 54.4 113.3 11.8 20.1 42.6 88.4 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (191,542 households, 81.2% of all rural agricultural households) 1,987 households (0.8%) use improved pit latrine and 2,357 households (1.0%) use flush toilets. The remaining 118 household (0.0%) use other toilets facilities. However, 39,914 households (16.9%) in the region had no toilet facilities (Chart 3.153). The distribution of the households without toilets within the region indicates that 32.8 percent of them were found in Nzega District and 0.6 percent was from Tabora Urban. The percentages of households without toilets in other districts were as follows Igunga (27.1%), Uyui (14.4%), Urambo (14.1%), and Sikonge (11.0%) Map 3.61). 3.13.3 Household’s Assets Bicycles are owned by most rural agricultural households in Tabora region with 164,536 households (69.7% of the agriculture households in the region) owning the asset followed by radio (126,723 households, 53.7%), iron (42,071 households, 17.8%), wheelbarrow (12,671 households, 5.4%), vehicles (3,214 households, 1.4%), mobile phone (2,336 households, 1.0%), television/video (2,127 households, 0.9%) and landline phone (368 households, 0.2%) (Chart 3.154). Chart 3.53 Agricultural Households by Type of Toilet Facility Other Type, 118, 0% Improved Pit Latrine - hh Owned, 1,987, 1% No Toilet , 39,914, 17% Flush Toilet, 2,357, 1% Traditional Pit Latrine, 191,542, 81% Chart 3.154 Percentage Distribution of Households Owning the Assets 17.8 69.7 53.7 0.2 0.9 1.0 1.4 5.4 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Bicycle Radio Iron Wheelbarrow Vehicle Mobile phone Television/Video Landline phone Assets Percent Urambo Sikonge Tabora Urban Uyui Igunga Nzega 5,525 3,754 849 9,192 34,913 34,629 10.2% 19.2% 8.3% 22.2% 77.3% 52.8% 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Uyui Tabora Urban Igunga Nzega Sikonge 3,754 5,525 9,192 34,629 34,913 849 19.2% 10.2% 22.2% 52.8% 77.3% 8.3% Urambo 16,000 to 18,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Number of Households Map 3.56 TABORA Number and Percent of Households Infected With Ticks by District Map 3.57 TABORA Number and Percent of HouseholdsUsing Draft Animals by District Percent of Households Using Draft Animals Number of Households Infected with Ticks Number of Households Using Draft Animals Percent of Households Infected with Ticks Number of Households Using Draft Animals RESULTS 88 Igunga Nzega Uyui Sikonge Tabora Urban Urambo 11,737ha 26,328ha 8,880ha 5,695ha 2,803ha 8,972ha 12.1% 18.4% 8% 10.8% 15.1% 7.4% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Igunga Nzega Tabora Urban Urambo Sikonge 732ha 537ha 1,713ha 60ha 84ha 4,104ha 0.66% 0.55% 1.2% 0.33% 0.16% 3.4% Tanzania Agriculture Sample Census Planted Area (ha) Map 3.58 TABORA Planted Area and Percent of Total Planted Area With Farm Yard Manure application by District Map 3.59 TABORA Planted Area and Percent of Total Planted Area with Compostapplication by District Planted Area (ha) with Compost applied Planted Area (ha) with Farm Yard Manure applied Planted Area (ha) Percent Planted Area (ha) with Farm Yard Manure applied Percent of Planted Area (ha) with Compost applied 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 RESULTS 89 Nzega Tabora Urban Uyui Sikonge Urambo Igunga 13,083 10,807 5,764 4,406 229 5,625 20% 23.9% 14% 22.6% 2.2% 10.4% 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Urambo Uyui Sikonge Tabora Urban Igunga Nzega 0 98 98 26 0 0 0%% 0.24% 0.5% 0.26% 0% 0% Tanzania Agriculture Sample Census Number of Households Map 3.60 TABORA Number and Percent of Households Practicing Fish Farming by District Map 3.61 TABORA Number and Percent of Households Without Toilets by District Number Households Without Toilets Number of Households Practicing Fish Farming Number of Households Percent of Households Practicing Fish Farming Percent of Households Without Toilets 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 RESULTS 90 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region. with 83.6 percent of the total rural households using this source of energy followed by hurricane lamp (10.1%), pressure lamp (3.4%), fire wood (2.0%), mains electricity (0.5%), candles (0.2%), solar and gas or biogas (0.1% each). Other source of lighting energy accounted for 0.1 percent (Chart 3.155). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.84 percent of all rural agricultural households in Tabora region. This is followed by charcoal (2.67%). The rest of energy sources accounted for 2.49 percent. These were paraffin/kerosene (1.19%), crop residue (0.77%), bottled gas (0.24%), livestock dung (0.13%), mains electricity (0.11%) and solar (0.06%) (Chart 3.156). 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 70.1 percent of the rural agricultural households. This was followed by grass and mud (14.9%) which was closely followed by iron sheets (13.8%), tiles (0.6%), asbestos (0.3%) concrete (0.1%) and others (0.3%) (Chart 3.157). Urambo district had the highest percentage of households with grass/leaves roofing material (83%) and was followed by Uyui district.(81%), Nzega (77%), Sikonge (75%), Tabora Urban (72%) and Igunga (31%) (Chart 3.158 and Map 3.62). Chart 3.155 Percentage Distribution Of Households by Main Source of Energy for Lightining Solar, 346, 0% Candles, 484, 0% Pressure Lamp, 8,051, 3% Mains Electricity, 1,075, 0% Gas (Biogas), 151, 0% Other, 149, 0% Firewood, 4,687, 2% Wick Lamp, 197,211, 85% Hurricane Lamp, 23,763, 10% Chart 3.156 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 562, 0% Crop Residues, 1,814, 1% Mains Electricity, 250, 0% Solar, 152, 0% Livestock Dung, 300, 0% Parraffin / Kerocine, 2,807, 1% Charcoal, 6,299, 3% Firewood, 223,732, 95% Chart 3.157 Percentage Distribution of Households by Type of Roofing Material Other 0% Grass & Mud 15% Grass / Leaves 70% Tiles 1% Concrete 0% Asbestos 0% Iron Sheets 14% Chart 3.158 Percentage Distribution of Households with Grass/Lafy by District 77 31 72 75 81 83 11 16 12 21 23 13 0 10 20 30 40 50 60 70 80 90 Urambo Uyui Nzega Sikonge Tabora Urb Igunga District P e r c e n t %Grass/Leaves % Iron Sheets RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Tabora region was unprotected wells (67.5 percent of households use unprotected wells during the wet season and 68.2 percent of the households during the dry seasons). This was followed by protected wells (8.2 % of households during wet season and 7.8 % in dry season), unprotected springs (5.3% of households during the wet season and 9.3% in the dry season), surface water (5.5% of households in the wet season and 8.6% during dry season), uncovered rain water (8.1% of households during the wet season and 1.9% in the dry season), piped water (2.2% of households during the wet season and 1.8% in the dry season) and protected / covered springs (1.1% of households during the wet season and 1.3% in the dry season). Covered rain water was used as a main source by 0.3 percent of the households in the wet season and by 0.1 percent in the dry season and other services accounted for 1.9 percent in wet season and 1.3 percent in dry season Chart 3.159). About 59 percent of the rural agricultural households in Tabora region obtained drinking water within a distance of less than one kilometer during wet season compared to 43 percent of the households during the dry season. However, 41 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 57 percent of households in the dry season. The most common distance from the source of drinking water was between 500m and 2 km (Chart 3.160). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Tabora region normally had 3 meals per day (58 percent of the households in the region). This was followed by 2 meals per day (38 percent) and 1 meal per day (3 percent). Only 1 percent of the households had 4 meals per day (Chart 3.161). Chart 3.160 Percent of Households by Distance to Main Source of Drinking Water and Season 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance Percent Wet Season Dry Season Chart 3.159 Percent of Households by Main source of Drinking Water and Season 0.0 20.0 40.0 60.0 80.0 Pip ed W ater Pro tected W ell Pro tected / Co v ered Sp rin g U p ro tected W ell U n p ro tected Sp rin g Su rface W ater (L ak e / D am / Riv er / Stream ) Co v ered Rain w ater Catch m en t U n co v ered Rain w ater Catch m en t O th er Main Source P ercent o f H o useho lds Wet Season Dry Season Chart 3.161 Number of Agriculural Households by Number of Meals per Day Three, 137,213, 58% One, 7,492, 3% Four, 2,159, 1% Two, 89,052, 38% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 Tabora Urban had the largest percent of households eating one meal per day whilst Igunga had the highest percent of households eating three and four meals per day. (Table 3.17 and Map 3.63). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 156,187 (66.2% of the agricultural households in Tabora region) with 77,552 households (49.7 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31.3%). Very few households had meat three or more times during the respective week. About 33.8 percent of the agricultural households in Tabora region did not eat meat during the week preceding the census (Chart 3.162 and Map 3.64). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 117,195 (49.7% of the total agricultural households in Tabora region) with 54,881 households (46.8% of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish twice (29,025 households, 24.8 %), those who had fish three times (13.8%). In general, the percentage of households that consumed fish twice or more times during the week in Tabora region was 62,314 (53.2% of the agricultural households that ate fish in the region during the respective period). About 50.3 percent of the agricultural households in Tabora region did not eat fish during the week preceding the census (Chart 3.162 and Map 3.65). 3.13.9 Food Security In Tabora region, 76,446 households (32.4% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement while 20,610 (8.7%) said they often experienced problems. However 7.2 percent sometimes experienced problems and 6.9 percent always had problems in satisfying the household food requirements. About 44.8 percent of the agricultural households said they did not experience any food insufficiency. (Map 3.66). Table 3.17: Number of Households by Number of Meals the Household Normally District One % Two % Three % Four % Total Nzega 1,190 1.8 19,042 29.0 44,886 68.5 447 0.7 65,566 Igunga 2,202 4.9 8,983 19.9 33,151 73.4 804 1.8 45,141 Uyui 1,934 4.7 14,990 36.3 23,789 57.6 605 1.5 41,318 Urambo 733 1.4 32,149 59.4 21,130 39.0 109 0.2 54,120 Sikonge 914 4.7 8,737 44.8 9,669 49.5 194 1.0 19,514 Tabora Urban 519 5.1 5,151 50.2 4,589 44.7 0 0.0 10,258 Total 7,492 3.2 89,052 37.7 137,213 58.2 2,159 0.9 235,917 Chart 3.162 Number of Households by Frequency of Meat and Fish Consuption 0 25,000 50,000 75,000 100,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Chart 3.163: Number of Households by Level of Food Availability Always, 16,249, 7% Often, 20,610, 9% Sometimes, 16,953, 7% Seldom, 76,446, 32% Never, 105,659, 45% Never Seldom Sometimes Often Always RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 Tabora Urban had the highest percent of households that had problems in satisfying their household food requirements (35% of the agricultural households always or often having food problems). The percentage of households with food problems is also high in Igunga, Sikonge and Uyui. Urambo and Nzega districts had the lowest percentages of households that always or often faced food problems being between 20 and 21% of the agricultural households (Chart 3.164). 3.13.10 Main Sources of Cash Income The main cash income of the households in Tabora region came from the selling of food crops (22.8 percent of smallholder households), followed by casual labour (20.9%), selling of cash crops (16.0%), businesses (11.8%), sale of livestock (10.3%) and cash remittances (6.0%). Only 2.2 percent of smallholder households reported the wages and salaries in cash were their main source of income followed by livestock products (1.1%) and fishing (0.2%) (Chart 3.165). Chart 164: Percentage of Household Reporting Food Availability Status by District 0% 25% 50% 75% 100% Sikonge Urambo Uyui Nzega Igunga Tabora Urban District Percentage of Households Never Seldom Sometimes Often Always Chart 3.165: Percentage Distribution of the Number of Households by Main Source of Income Remittance, 6.0, 6% not applicable, 0.2, 0% Other, 0.9, 1% Wages & Salaries, 2.2, 2% Livestock Products, 1.1, 1% Forest Products, 7.5, 8% Livestock, 10.3, 10% Business Income, 11.8, 12% Other Casual Cash Earnings, 20.9, 21% Cash Crops, 16.0, 16% Food Crops, 22.8, 23% Fishing, 0.2, 0% Uyui Tabora Urban Nzega Urambo Sikonge Igunga 23,789 9,669 4,589 44,886 21,130 33,151 57.6% 49.5% 44.7% 68.5% 39% 73.4% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Uyui Tabora Urban Igunga Urambo Sikonge Nzega 14,622 33,359 13,968 50,779 7,367 45,166 75% 81% 31% 77% 72% 83% 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Map 3.62 TABORA Number and Percent of Households Using Grass/leaves for Roofing Material by District Map 3.63 TABORA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Practicing Fish Farming Number of Households Using Grass/ Leaves for Roofing Material Number of Households Percent of Households Using Grass/Leaves for Roofing Material Percent of Households Practicing Fish Farming RESULTS 95 Igunga Nzega Tabora Urban Uyui Sikonge Urambo 13,859 29,694 3,777 RESULTS 96 10,558 4,649 15,015 30.7% 45.3% 36.8% 25.6% 23.8% 27.7% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Tabora Urban Sikonge Nzega Igunga 7,331 2,712 2,769 11,844 23,718 6,506 17.7% 26.4% 14.2% 21.9% 14.45 36.2% Urambo Tanzania Agriculture Sample Census Number of Households Map 3.64 TABORA Number and Percent of Households Eating Meat Once per Week by District Map 3.65 TABORA Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Number of Households Eating Meat Once per Week Number of Households Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once per Week 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Tabora Urban Nzega Sikonge Urambo Igunga 33,897 7,519 56,827 16,516 47,380 36,920 82% 73.3% 86.7% 84.6% 87.5% 81.8% 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Map 3.66 TABORA Number and percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency RESULTS 97 TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 4 TABORA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Region Profile The region profile describes the status of the agriculture sector in the region and compares it with other regions in the country. Tabora has a land area of around 600,000 hectares under cultivation. It is characterised by annual cropping with a very small amount of permanent crops. The percent of land available to smallholders that was utilised during the census year is one of the lowest in the country. This, coupled with its having one of the lowest number of crop growing households per square kilometre in Tanzania may indicate that there is more than sufficient accessible land in the region to satisfy the needs of the smallholder households. This is reflected by the low number of households responding to insufficiency of land. The region has only one planting season (the long rainy season). Tabora has the fourth largest planted area of maize and rice in the country, however the yields during the census year were low. Although not the largest sorghum producing region, it has one of the largest area planted per household. It is a predominant tobacco growing region and has the second largest planted areas of groundnuts and onions in the country. Cassava and beans are of moderate to low importance in the region. Permanent crops consist of small areas of mangos and oil palm. Although small, the region has a moderate planted area under irrigation and the number of households using irrigation has remained stable over a 10 year period. Wells and dams are the most common source of water for irrigation. Land clearing is predominantly by hand, however around half of the households use oxen for cultivation while the other half cultivates by hand. Tabora is one of the four regions in the country that uses noticeable quantities of inorganic fertilisers however, as with all other regions most of the planted area has no fertiliser application. Small amounts of insecticides and fungicides were used and the region is placed second in the use of these inputs. Crops are either stored unprotected or in traditional cribs. Compared to other regions, the percent of households selling crops was low. Practically all crop processing was done on neighbours machines, with small amounts sold to neighbours. A low percent of households received extension services in Tabora compared to other regions. Smallholders do not plant trees in Tabora and there are virtually no erosion control/water harvesting structures in the region. 4.2 District Profiles The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Nzega Nzega district had the largest number of households in the region and it had one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. The district had no households keeping livestock only and no pastoralists were found in the district. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 The most important livelihood activity for smallholder households in Nzega district was annual crop farming, followed by tree / forestry resources and livestock keeping. However, the district had the second lowest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Nzega had the highest percent of female headed households (17.1%) and it had one of the highest average age of the household head. With an average household size of 5 members per household it had about the same average as the region. Nzega has a comparatively low literacy rate among smallholder households and this was reflected by the concomitant relatively low level of school attendance in the region.. The literacy rate for the heads of household is also lower than other districts in the region. It had the smallest utilized land area per household (1.9ha) and the allocated area was almost fully utilized indicating a high level of land pressure. The total planted area was greater than in some other districts in the region, however it had the lowest planted area per household (1.7ha) attributed to the high number of smallholders in the district. The district is important for maize production in the region and had a planted area of over 52,000ha; however the planted area per household was the lowest in the region. Paddy production was also very important with a largest planted area of 25,289 hectares but the production of sorghum is small. Cassava production was moderate accounting for 14.2 percent of the quantity harvested in the region. The district had the smallest planted area of sweet potatoes (673 ha) and it was one of the two districts in the region which didn’t grow Irish potatoes. The district was among the lowest beans producer in the region with a planted area of 1,064ha. Oilseed crops were very important in Nzega and the district had the largest area planted with groundnuts (19,722ha). Vegetable production was moderately important in the district. It had moderate area planted with tomatoes and onion (120 ha and 151 ha respectively). Traditional cash crops (e.g. tobacco and cotton) were grown in small quantities. Compared to other districts in the region, Nzega had the second smallest area planted with permanent crops which were dominated by mango (649 ha), guava (279 ha) and oranges (234 ha). Other permanent crops were either not grown or were grown in very small quantities. In Nzega district most land clearing and preparation was done by oxen followed by hand cultivation, however slightly more land preparation was done by tractor compared to most other districts. The use of inputs in the region is very small, however district differences exist. Nzega has the second smallest planted area with improved seed in Tabora region. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is farm yard manure. Compared to other districts in the region, Nzega district has a small level of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. The use of herbicides is also small. The district has the fourth largest area with 6,125 ha of irrigated land. The most common source of water for irrigation is from dams using gravity and hand bucket. Flood and bucket are the most common means of irrigation water application. The most common method of crop storage is in sacks / open drums followed by storing in locally made traditional structures, however the district has the second largest proportion of households storing crops in sacks / open drums compared to other districts in the region. The district has the second largest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The highest percent of households TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 processing crops in Tabora region is found in Nzega district and is almost all done by neighbor machines. The district also has a higher percent of households selling processed crops to local markets/trade stores than other districts and no sales are to secondary markets, marketing cooperatives, farmers association or large scale farms. Although small, access to credit in the district is to men only and the main sources are religious organisations/NGO projects and traders/trade stores. A comparatively larger number of households receive extension services in Nzega and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Nzega (with 98 planted trees) and is mostly Gravellis with some Azadirachta and leucena spp. The second highest proportion of households with erosion control and water harvesting structures is found in Nzega district and are mostly erosion control bunds; however it also has moderate number of dams and drainage ditches compared to other districts. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has a moderate number of pigs in the region and has the third highest number of chickens. Although small, the district has the highest number of layers in the region. Nzega district has moderate to small numbers of ducks, turkeys and donkeys are also found in the district. The smallest number of households reporting Tsetse and tick problems was in Nzega district and it had the second largest number of households de-worming livestock. The use of draft animals in the district is high. Fish farming is virtually absent in the district. It has amongst the best access to primary schools, all weather roads and primary and secondary markets compared to other districts. However, it has one of the worst accesses to health clinics and regional capital. Nzega district has the third highest percent of households with no toilet facilities. The district has the highest percent of households owning bicycles, the second highest number of households owning vehicles and the third highest number of households owning TV/Video sets. It has small number of households using mains electricity. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the third highest percent of households with grass roofs with 12 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. The district is among the districts with the lowest percent of households having one meal per day. It has the moderate percent of households having two meals per day compared to other districts and amongst the highest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat during the week prior to enumeration and amongst the district with highest percent of household that did not eat fish in the same week; however most households never had problems with food satisfaction. 4.2.2 Igunga Igunga district had the third largest number of households in the region and was among the districts with the highest percentages of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock production, followed by crop farming only. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Igunga district was annual crop farming, followed by off farm income. The district had the lowest percent of households with no off-farm activities although it had the second TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Igunga had a lowest percent of female headed households (11.3%) and it had one of the moderate average age of the household head in the region. With an average household size of 7 members per household it was above the average for the region. Igunga has a comparatively moderate literacy rate among smallholder households and this was reflected by the district having the moderate level of school attendance in the region. The literacy rate for the heads of household was lower than most districts in the region. It has a largest utilized land area per household (3.8ha) and 92.1 percent of the allocated area was being utilized. The district had the largest planted area in the region, and the largest planted area per household (3.2ha). The district is important for maize production in the region and had the largest planted area of over 56,000 ha, and the planted area per household was also large for the region. The district had moderate planted area of paddy in the region with 6,560 hectares. Igunga had the largest planted area for sorghum (38,804ha) whilst cassava production was low, accounting for 3.9 percent of the quantity harvested in the region. The district had the largest area planted with sweet potatoes (3,639ha) but a very small planted area of Irish potatoes (112 ha). The production of beans in Igunga was very small compared to other districts in the region with a planted area of 319ha. Igunga district had a moderate planted area for groundnuts and an area planted per household of 0.5 ha. Vegetable production was important in the district. It had the largest planted area for onions in the region accounting for 80.4 percent of the onions planted area. Other vegetables were grown in small quantities. Cotton and tobacco were the cash crops grown in the district. The district had the largest area planted with cotton (21,751ha). Tobacco was very small. Compared to other districts in the region, Igunga had the third largest area planted with permanent crops which were dominated by mango (2,069 ha), coconuts (268 ha), sugar cane (47 ha) and pawpaw (40 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by oxen ploughing followed by hand cultivation, however a very small amount of land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Igunga has the fifth largest planted area with improved seed in Tabora region. Also, the district has the fifth largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), most of these are farm yard manure and inorganic fertilizers. Compared to other districts in the region, Igunga district has the third largest area of insecticide use and has the second largest area of fungicide and herbicide use. It has the third largest area with irrigation compared to other districts with 6,822 ha of irrigated land. The most common source of water for irrigation is from dams using gravity. Flood irrigation is the most common means of irrigation water application and a small amount of bucket / watering can is used. The most common method of crop storage in Igunga is locally made traditional structures, however the proportion of households storing crops in the district is lower compared to other districts in the region. The district has the fourth highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Igunga district is one of the districts in Tabora region with moderate percent of households processing crops and is almost all done by neighbor machines. There is no agro-processing carried out by co-operatives. The district has the second largest number of households selling primary processed products. Although very small, access to credit in the district is to men (100% of those who accessed credit) and the main sources are family friends and relatives. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 A comparatively small number of households receive extension services in Igunga district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming is not very important in Tabora region. Igunga district has the smallest number of planted trees in the region (with 32 planted trees) and is mostly Moringa Spp with some Sena Spp and Azadirachta Spp. Igunga has the lowest number of households with water control bunds. The district has a largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is also highest compared to other districts. Pigs were virtually absent in the district and has the third largest number of chickens, almost all are indigenous. Igunga has the fourth largest number of improved chickens in the region. The district has the largest number of ducks and donkeys, however small numbers of rabbits are also found in the district. Turkeys are virtually not found in the district. A number of households reported tsetse and tick problems in Igunga district. De- worming of livestock is also practiced in Igunga. The use of draft animals in the district exists. A small number of households’ practice fish farming, however the district has the second largest number in the region. The district has the second largest number of donkeys and turkeys. Some ducks are also found in the district. A number of households reported tsetse problem. Igunga district had the second largest number of households reported of ticks and it had the second largest number of households de-worming livestock. The district has the largest number of households using draft animals in the region. Fish farming is virtually absent in the region. It has amongst the best access to secondary schools, primary schools, all feeder roads, health clinics and primary, secondary and tertiary markets compared to other districts. However, it has one of the worst access to regional capital and tarmac roads. Igunga district has the highest percentage of households without toilet facility (23.9%) and it is among the districts with the lowest percent of households owning radios and iron. The district has the second percent of households owning bicycles and has third percent of households owning mobile phones and vehicles. It has the largest percent of households owning wheelbarrows and televisions/videos. The most common source of drinking water is from unprotected wells and uncovered rainwater catchments. It is one of the districts with the highest percent of households having three meals per day. The district had the second highest percent of households that did not eat meat and has the highest percent of households that did not eat fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.3 Uyui Uyui district had the forth largest number of households in the region and it had the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. It had a small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Uyui district was annual crop farming, followed by off-farm income. The district had the second highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Uyui had a relatively low percent of female headed households (13.8%) and it had one of the moderate average age of the household head in the region. With an average household size of 7 members per household it was above the average for the region. Uyui had a comparatively low literacy rate among smallholder households and this was reflected by the TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 concomitant relatively high level of population not attended schools in the region. The literacy rate for the heads of household was moderate compared with other districts in the region. It had higher utilized land area per household (3.2ha) than the regional average of 2.9 ha and 73.2 percent of the allocated area was being utilized. The district had the fourth largest total planted area as compared to other districts in the region. Also, the district had the third largest planted area per household (2.3ha). The district is moderately important for maize production in the region and had a planted area of over 46,418 ha, however the planted area per household was 1.1 ha which was moderate in the region. Paddy production was also important with a planted area of 14,587 hectares. Sorghum was less important with a planted area of 3,162 hectares. Irish potatoes and wheat were not produced in the district. The district had a moderately large planted area of cassava accounting for 15.5 percent of the cassava planted area in the region. The production of beans in Uyui was much lower than Urambo district but higher than other districts in the region with a planted area of 3,654ha. Oilseed crops were important in Uyui with 98.2 percent of the groundnuts grown in the district. Uyui district had the largest area planted with vegetable in the region. A very small quantity of cotton was planted in the district. The district had the second largest planted area for tobacco. Permanent crops were less important in Uyui district (12.9% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district include mango (432 ha), guava (329 ha) and palm oil (291 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, only very small land preparation was done by tractors. The use of inputs in the region is very small, however district differences exist. Uyui has the second largest planted area with improved seed in Tabora region. The district has the third largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), most of these are inorganic fertilizers and farm yard manure. Compared to other districts in the region, Uyui district has the second largest area of insecticide use and has the third largest area of fungicide and herbicide use. It has the second largest area with irrigation compared to other districts with 7,037 ha of irrigated land. The most common source of water for irrigation is from dams using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Uyui is sacks and open drums, however the proportion of households storing crops in the district is moderate compared to other districts in the region. The district has the third highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Uyui district is one of the districts in Tabora region with a high percent of households processing crops and is almost all done by neighbor machines. In the district the agro-processing is not carried out neither by traders, co-operatives nor factories. The district has the smallest number of households selling primary processed products. Although very small, access to credit in the district is mostly to men (96% of those who accessed credit) and the main sources are cooperatives, family friends and relatives. A comparatively moderate number of households receive extension services in Uyui district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 Tree farming is not very important in Tabora region. However, Uyui district has the largest number of planted trees in the region (with 793 planted trees) and is mostly Moringa Spp with some Eucalyptus Spp. Uyui has the highest number of households with dams, tree belts and water harvesting bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the third largest number of pigs in the region and the second largest number of chickens. Most of them are indigenous. Uyui has the second largest number of improved chickens in the region. The district has the largest number of ducks and donkeys, however small numbers of rabbits are also found in the district. Turkeys are virtually not found in the district. A number of households reported tsetse and tick problems in Uyui district. De-worming of livestock is also practiced in Uyui. The use of draft animals in the district exists. A small number of households’ practice fish farming, however the district has the second largest number in the region. Uyui district is not amongst the best access to any infrastructure compared to other districts. However, it has one of the worst access to secondary schools, primary schools, feeder roads, hospitals, health clinics, district capital, secondary markets and tertiary markets. Uyui district has a moderate percent of households with no toilet facilities and it has the highest percent of households owning vehicles and has the second highest percent of households owning land lines, TV/Video and mobile phones. It has the third lowest number of households owning wheelbarrows, radios and bicycles. Uyui district has the third highest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (80.7%) with 16.2 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Forty one percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district had a highest percent of households that did not eat meat compared to other districts and moderate percent of households that did not eat fish during the week prior to enumeration, however most households reported to have no food satisfaction. 4.2.4 Urambo Urambo district had the second largest number of households in the region and it had the fifth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Urambo district there were no households involved in livestock only. Also, no pastoralists were found. The most important livelihood activity for smallholder households in Urambo district was annual crop farming followed by off-farm income. It had the third lowest percent of households with no off-farm activities and the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Urambo district had a relatively low percent of female headed households (13.7%) and it had one of the lowest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Urambo district had a comparatively high literacy rate among smallholder households and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the female heads of household was lower than that of Sikonge district but slightly higher than those of other districts in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 It has the third largest utilized land area per household (3.0 ha) and only 69.1 percent of the allocated land area had been utilized. The total planted area was moderate compared to other districts in the region, however it had the second lowest planted area per household (2.2 ha) attributed to the high number of smallholders in the district. Urambo district is more or less important for maize production in the region and had a planted area of 46,076 ha, however the planted area per household was among the lowest in the region. Paddy production was also more or less important with a planted area of only 11,904 hectares but the production of sorghum was small. The production of cassava and beans in Urambo district was much higher than in other districts. The district had the second largest area planted with oil seeds especially groundnuts. Vegetable production was not very important in the district. The most important vegetable produced was tomatoes followed by amaranths and onions. Other vegetables were produced in very small quantities. Urambo district had the largest area planted with tobacco (15,565 ha). Cash crops such as cotton were grown in small quantities. Urambo district had the largest area planted with permanent crops (58.6% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district include palm oil (1,859 ha), mango (1,618 ha), banana (1,362 ha) and pawpaw (516 ha). Other permanent crops were either not grown or were grown in small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Urambo has the largest planted area with improved seed in Tabora region. The district has the second largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are inorganic fertilizers followed by farm yard manure. Compared to other districts in the region, Urambo district has the largest area of insecticide use and has the largest area of fungicide and herbicide use. It has the largest area with irrigation compared to other districts with 9,624 ha of irrigated land. The most common source of water for irrigation is from wells using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Urambo is sacks and open drums, however the proportion of households storing crops in the district is high compared to most of other districts in the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Urambo district is one of the districts in Tabora region with a high percent of households processing crops and is almost all done by neighbor machines. However, the agro-processing is not done by traders, co- operatives or by factories. The district has no households selling primary processed products. Although small, access to credit in the district is mostly to men (99% of those who accessed credit) and the main sources are co-operatives. Sikonge district has the third largest number of households received agricultural credits in the region. A comparatively high number of households receive extension services in Urambo district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 Tree farming is not very important in Tabora region. However, Urambo district has the second largest number of planted trees in the region (with 608 planted trees) and is mostly Albizia Spp with some Acacia Spp. Urambo has the highest number of households with dams, tree belts and water harvesting bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate to low compared to other districts. It has the largest number of pigs in the region and the largest number of chickens, all of which are indigenous. Urambo has the third largest number of improved chickens in the region. The district has the largest number of rabbits and has the third largest number of ducks. Turkeys and donkeys are virtually not present in the district. A number of households reported tick problem is relatively small but the district has the largest number of households reported tsetse problems in the region. De-worming of livestock is also practiced in Urambo. The use of draft animals in the district exists. Fish farming is virtually absent in the district. Urambo district is not amongst the best access to any infrastructure compared to other districts. However, it has one of the worst accesses to primary schools, hospitals, district capital, regional capital and tarmac road. Urambo district has relatively low percent of households with no toilet facilities and it has the highest percent of households owning radio and has the second highest percent of households owning iron. It has the third lowest number of households owning bicycle. Urambo district has the lowest percent of households owning vehicles and the use of is vrtuall absent. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a highest percent of households with grass roofs (83.3%) with 10.9 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Sixty one percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district was amongst the districts with the lowest percent of households that did not eat meat or fish the week prior to enumeration, however most households reported to have food satisfaction. 4.2.5 Sikonge Sikonge district had the lowest number of households in the region and it had the fourth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Sikonge district, very few households were involved in livestock only. Also, pastoralists were virtually absent. The most important livelihood activity for smallholder households in Sikonge district was annual crop farming followed by livestock keeping / herding. It had the highest percent of households with no off-farm activities and the forth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sikonge district had a relatively low percent of female headed households (13.5%) and it had one of the lowest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Sikonge district has a comparatively high literacy rate among smallholder households and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the female heads of household was the highest in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 It had the third largest utilized land area per household (3.0 ha) and only 69.9 percent of the allocated land area had been utilized. The total planted area was small compared to other districts in the region, however it had the second largest planted area per household (2.7 ha) attributed to the low number of smallholders in the district. Sikonge district was more or less important for maize production in the region with a planted area of 22,958 ha and had the second largest planted area per household in the region. Paddy, cassava and groundnuts production were more or less important with a planted area of only 5,193 hectares, 1,829 hectares and 7,863 hectares respectively. The production of sorghum and beans in Sikonge district was also more or less important in the region for which it had the third largest planted area in the region. Vegetable production was not very important in the district. The most important vegetable produced is radish followed by okra. Other vegetables were produced in very small quantities. Sikonge district had a moderate planted area of tobacco (5,735 ha) compared to other districts in the region. Sikonge district had the smallest area planted with permanent crops (0.9% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district was mango (53 ha) followed by banana (19 ha) and oranges (8 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Sikonge has the forth largest planted area with improved seed in Tabora region. The district has the third largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are inorganic fertilizers followed by farm yard manure. Compared to other districts in the region, Sikonge district has the forth largest area of insecticide use, fungicide and herbicide use. It has the smallest area with irrigation compared to other districts with 2,520 ha of irrigated land. The most common source of water for irrigation is from wells using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Sikonge is locally made traditional structures followed by sacks and open drums. The proportion of households storing crops in the district is highest compared to most of other districts in the region. The district has the second highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Sikonge district is one of the districts in Tabora region with a highest percent of households processing crops and is almost all done by neighbor machines. However, the agro-processing is not done by traders or by factories. The district has small number of households selling primary processed products. Most of the products are sold to neighbours. Although small, access to credit in the district is mostly to men (99% of those who accessed credit) and the main sources are co-operatives. Sikonge district has the third largest number of households received agricultural credits in the region. A comparatively low number of households receive extension services in Sikonge district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 Tree farming is not very important in Tabora region. However, Sikonge district has the second smallest number of planted trees in the region (with 226 planted trees) and is mostly Moringa Spp with some Pinus Spp. and Acacia Spp. Sikonge is among the districts with the highest number of households water harvesting bunds and a moderate number of households with erosion control bunds. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate to small compared to other districts. Pig rearing in Sikonge district is virtually absent. Sikonge has the second smallest number of chickens and very small number of improved chickens. Also, the district has very small number of ducks, turkeys, rabbits and donkeys. A number of households reported tick problem is relatively small but the district has the moderate number of households reported tsetse problems in the region. De-worming of livestock is also practiced in Urambo. The use of draft animals in the district exists. Very small number of households’ practice fish farming; however the district has the largest number of harvested fish in the region. Sikonge district is amongst the worst access to some infrastructure compared to other districts. It is one amongst districts with the worst access to secondary schools, primary schools, all weather roads, hospitals, district capital, regional capital, primary markets, secondary markets tertiary markets and tarmac road. Sikonge district has a high percent of households with no toilet facilities and it has the highest percent of households owning iron. It has the second highest percent of households owning radio and wheelbarrow and has the third, forth and fifth percent of households owning television/video, mobile telephones and bicycle respectively. Sikonge district has the lowest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (74.9%) with 20.5 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Fifty percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district had the second smallest percent of households that did not eat meat during the week prior to enumeration and among the district with moderate percent of household that did not eat fish in the same week; however most households never had problems with food satisfaction. 4.2.6 Tabora Urban Tabora Urban district had the second lowest number of households in the region and it had the smallest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Tabora Urban, very few households were involved in livestock only. Also, pastoralists were virtually absent. The most important livelihood activity for smallholder households in Tabora Urban district was annual crop farming followed by off-farm income. It had the third highest percent of households with no off-farm activities and the fifth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tabora Urban had a relatively high percent of female headed households (16.75%) and it had one of the highest average age of the household head. Its average household size of 5 members per household was about the same as the average for the region. Tabora Urban has a highest literacy rate among smallholder households. The literacy rate for the female heads of household was moderate as compared to other districts in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 It had the fifth largest utilized land area per household (2.3 ha) and only 70.4 percent of the allocated land area had been utilized. The total planted area was the smallest in the region, it also had the smallest planted area per household (1.7 ha) attributed to the large number of smallholders in the district. Tabora Urban is almost important for maize production in the region and had a planted area of 7,844 ha and has the least planted area per household in the region. Paddy production was also more or less important with a planted area of 2,124 ha. A very small area was planted with sorghum while the production of bulrush millet and finger millet was virtually absent. Cassava production was low accounting for 6.4 percent of the quantity harvested in the region. The district had a small planted area of sweet potatoes (772 ha). The production of beans in Tabora Urban was smaller than in other districts in the region with a planted area of 1,439ha. Oilseed crops were not important in Tabora Urban and it had the sixth groundnuts planted area in the region. Vegetable production was not very important in the district. It had the second largest planted area for tomatoes (221ha) and a small planted area of onions (41ha) and amaranths (24ha). The production of tomatoes and amaranths accounted for 30.1 percent and 67.6 percent respectively in the region. Traditional cash crops (especially tobacco) were grown in very small quantities. Tabora Urban has the third smallest planted area for permanent crops (9.4% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district was mango (788 ha) followed by banana (56 ha) and sugar cane (62 ha). Oil palm was grown in small quantities (10ha) whilst other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractors. The use of inputs in the region is very small, however district differences exist. Tabora Urban has the smallest planted area with improved seed in Tabora region. The district has the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are farm yard manure followed by inorganic fertilizers. Compared to other districts in the region, Tabora Urban district has the smallest area of insecticide use, fungicide and herbicide use. It has the second smallest area with irrigation compared to other districts with 2,738 ha of irrigated land. The most common source of water for irrigation is from dams using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of water hose irrigation is used. The most common method of crop storage in Tabora Urban is sacks and open drums followed by locally made traditional structures. The proportion of households storing crops in the district is higher compared to some other districts in the region. The district has the fifth highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Tabora Urban is one of the districts in Tabora region with a highest percent of households processing crops and most of them are done by neighbor machines. However, the agro-processing done by factories is virtually absent. The district has small number of households selling primary processed products. Most of the products are sold to neighbours. Although small, access to credit in the district is to men (100% of those who accessed credit) and the main sources are co-operatives. Tabora Urban has the smallest number of households received agricultural credits in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 A comparatively low number of households receive extension services in Tabora Urban and most of this is from the government. The quality of extension services was rated between average and good by the majority of the households. Tree farming is not very important in Tabora region. Tabora Urban has the smallest number of planted trees in the region (with 108 planted trees) and is mostly Albizia Spp with some Moringa Spp. and Leucena Spp. Tabora Urban is among the districts with moderate to small number of households with erosion control bunds, drainage ditches and terraces. The district has the smallest number of cattle, goats, sheep and pigs in the region and they are almost all indigenous. It has the least number of chickens in the region and rearing of improved chicken is virtually absent. The district has the smallest number of ducks in the region and it has no turkeys, rabbits or donkeys. A number of households reported tsetse and tick problems in Tabora Urban district is small. De-worming of livestock is also practiced in Tabora Urban. The use of draft animals in the district exists. Very small number of households’ practice fish farming; however the district has the largest number of harvested fish in the region. Tabora Urban is the best access to most infrastructures compared to other districts. It is the best district with the best access to all weather roads, feeder roads, district capital, regional capital, secondary markets, tertiary markets and tarmac roads. Also, the district is amongst the districts with best access to primary and secondary schools, health clinics, hospitals and primary markets. Tabora Urban has a lowest percent of households with no toilet facilities and it has the highest percent of households owning mobile phones. It has the second highest percent of households owning radio and has the third highest percent of households owning landline phones and wheelbarrows. The district has the fourth percent of households owning iron and has the smallest percent of households owning bicycles. Tabora Urban has the second highest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a second lowest percent of households with grass roofs (71.8%) and a highest percent of households having iron sheets (22.8%). The most common source of drinking water is from unprotected wells. Fifty five percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. The district had the third largest percent of households that did not eat meat during the week prior to enumeration and among the district with lowest percent of household that did not eat fish in the same week; however most households seldom had problems with food satisfaction. Appendix II 129 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 130 Rural Household Involved in Agriculture % of Total Rural House- hold Rural Households NOT Involved in Agriculture % of Total Rural House- hold Total Rural Household % of Total Rural House- hold Urban Households % of Total Urban House- holds Total Number of Households (From 2002 Population Census) Number % Number % Number % Number % Number Nzega 65,566 97.0 2,001 22.5 67,567 27.6 6,012 12.9 73,579 Igunga 45,141 96.2 1,771 19.9 46,912 19.2 4,264 9.2 51,176 Uyui 41,318 96.6 1,439 16.2 42,757 17.5 409 0.9 43,166 Urambo 54,120 95.1 2,800 31.4 56,920 23.2 5,713 12.3 62,633 Sikonge 19,514 97.7 466 5.2 19,980 8.2 2,269 4.9 22,249 Tabora Urban 10,258 96.1 421 4.7 10,679 4.4 27,887 59.9 38,566 Total 235,917 96.4 8,908 100.0 244,824 100.0 46,545 100.0 291,369 Number Percent Number Percent Number Percent Number Percent Nzega 37,921 26 0 0 27,645 32 65,566 28 65,566 27,645 Igunga 21,553 15 116 39 23,472 27 45,141 19 45,025 23,588 Uyui 26,559 18 105 36 14,653 17 41,318 18 41,212 14,758 Urambo 40,380 27 0 0 13,740 16 54,120 23 54,120 13,740 Sikonge 13,677 9 50 17 5,787 7 19,514 8 19,464 5,837 Tabora Urban 7,956 5 25 9 2,276 3 10,258 4 10,233 2,302 Total 148,046 100 296 100 87,575 100 235,917 100 235,621 87,871 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Crops Only Livestock Only Total Number of Agricultural Households Rearing Livestock Agriculture, Non Agriculture and Urban Households 2.1: TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by Type of Household and District, 2002/03 Agriculture Year District Crops & Livestock Total District Type of Agriculture Household Total Number of Agricultural Households Growing Crops Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 131 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 132 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Average Household Size Nzega 54,327 83 6 11,239 17 3 65,566 100 5 Igunga 40,038 89 7 5,103 11 4 45,141 100 7 Uyui 35,609 86 7 5,708 14 5 41,318 100 7 Urambo 46,691 86 6 7,429 14 4 54,120 100 6 Sikonge 16,882 87 6 2,631 13 3 19,514 100 6 Tabora Urban 8,549 83 6 1,709 17 4 10,258 100 5 Total 202,097 86 6 33,820 14 4 235,917 100 6 3.0 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 133 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 134 Nzega 1 5 3 4 6 7 2 Igunga 1 5 4 2 6 7 3 Uyui 1 4 3 2 6 7 5 Urambo 1 5 4 2 6 7 3 Sikonge 1 5 2 3 6 7 4 Tabora Urban 1 4 3 2 6 7 5 Total 1 5 4 2 6 7 3 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 58,722 601 1,952 3,004 718 296 138 Igunga 18,172 110 7,535 16,131 1,751 114 996 Uyui 35,913 0 404 3,485 505 0 801 Urambo 48,593 125 821 3,307 1,273 107 247 Sikonge 15,991 0 438 2,032 329 0 723 Tabora Urban 7,505 126 326 1,249 438 78 436 Total 184,896 962 11,476 29,208 5,014 596 3,340 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 6,278 2,340 23,383 19,320 4,503 0 9,747 Igunga 22,496 627 10,573 7,580 1,304 0 3,018 Uyui 4,992 2,880 9,984 18,350 2,678 0 2,334 Urambo 4,797 5,084 10,962 23,948 2,252 466 6,270 Sikonge 3,182 781 5,435 5,601 776 142 3,591 Tabora Urban 2,396 1,051 1,414 3,485 490 13 1,228 Total 44,142 12,762 61,751 78,283 12,003 622 26,187 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 426 3,944 10,453 13,602 4,464 136 27,639 Igunga 3,370 2,015 5,050 9,123 2,727 0 20,420 Uyui 307 5,137 9,280 8,018 1,656 0 2,837 Urambo 361 12,827 10,026 8,296 2,526 232 15,799 Sikonge 291 2,021 5,069 3,339 828 337 3,108 Tabora Urb 286 2,312 1,963 2,484 544 0 1,168 Total 5,041 28,256 41,840 44,863 12,745 705 70,971 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Livelihood Activity Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tanzania Agriculture Census - 2003 Tabora Appendix II 135 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 6,347 6,074 6,735 2,317 0 16,906 Igunga 773 5,083 2,997 4,859 2,161 110 16,197 Uyui 0 1,635 3,874 1,647 701 106 811 Urambo 0 6,905 5,801 2,080 1,093 327 19,025 Sikonge 49 1,486 2,802 1,485 489 148 1,688 Tabora Urban 0 2,038 1,686 940 123 51 413 Total 822 23,493 23,233 17,746 6,885 742 55,040 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 4,465 1,754 750 1,113 0 4,123 Igunga 224 3,836 2,078 952 547 112 1,234 Uyui 0 100 208 701 301 106 0 Urambo 0 2,259 1,924 867 733 126 7,281 Sikonge 0 1,068 476 384 147 0 291 Tabora Urban 0 450 1,118 159 27 0 106 Total 224 12,178 7,559 3,813 2,868 344 13,035 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 1,908 119 0 150 0 0 Igunga 0 115 109 0 110 0 0 Uyui 0 0 0 0 0 203 0 Urambo 0 121 487 125 473 0 853 Sikonge 0 0 146 43 49 0 0 Tabora Urban 0 49 54 0 27 0 27 Total 0 2,193 915 168 809 203 880 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Igunga 0 0 110 0 0 0 0 Uyui 0 0 0 0 0 0 105 Urambo 120 0 0 0 0 0 0 Sikonge 0 0 0 0 0 50 50 Tabora Urb 0 0 27 0 0 0 0 Total 120 0 137 0 0 50 155 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Census - 2003 Tabora 136 Appendix II 137 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 138 Number % Number % Number % Less than 4 97,618 51 92,435 49 190,053 100 05 - 09 121,677 51 114,599 49 236,276 100 10 - 14 105,672 54 91,793 46 197,465 100 15 - 19 84,870 55 70,772 45 155,643 100 20 - 24 57,246 47 64,992 53 122,237 100 25 - 29 53,708 47 60,021 53 113,729 100 30 - 34 43,396 50 42,548 50 85,944 100 35 - 39 35,393 54 30,611 46 66,004 100 40 - 44 28,093 53 24,554 47 52,647 100 45 - 49 19,436 47 21,691 53 41,127 100 50 - 54 18,516 52 17,093 48 35,608 100 55 - 59 15,504 51 14,624 49 30,128 100 60 - 64 13,585 48 14,514 52 28,099 100 65 - 69 13,941 60 9,131 40 23,073 100 70 - 74 9,608 50 9,539 50 19,147 100 75 - 79 7,796 68 3,634 32 11,430 100 80 - 84 4,414 61 2,841 39 7,255 100 Above 85 2,338 53 2,097 47 4,435 100 Total 732,811 52 687,489 48 1,420,300 100 Number % Number % Number % Less than 4 97,618 13 92,435 13 190,053 13 05 - 09 121,677 17 114,599 17 236,276 17 10 - 14 105,672 14 91,793 13 197,465 14 15 - 19 84,870 12 70,772 10 155,643 11 20 - 24 57,246 8 64,992 9 122,237 9 25 - 29 53,708 7 60,021 9 113,729 8 30 - 34 43,396 6 42,548 6 85,944 6 35 - 39 35,393 5 30,611 4 66,004 5 40 - 44 28,093 4 24,554 4 52,647 4 45 - 49 19,436 3 21,691 3 41,127 3 50 - 54 18,516 3 17,093 2 35,608 3 55 - 59 15,504 2 14,624 2 30,128 2 60 - 64 13,585 2 14,514 2 28,099 2 65 - 69 13,941 2 9,131 1 23,073 2 70 - 74 9,608 1 9,539 1 19,147 1 75 - 79 7,796 1 3,634 1 11,430 1 80 - 84 4,414 1 2,841 0 7,255 1 Above 85 2,338 0 2,097 0 4,435 0 Total 732,811 100 687,489 100 1,420,300 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Census - 2003 Tabora Appendix II 139 Number % Number % Number % Nzega 187,171 54 158,195 46 345,366 100 Igunga 157,202 51 153,059 49 310,261 100 Uyui 135,903 51 133,076 49 268,979 100 Urambo 168,695 51 159,259 49 327,955 100 Sikonge 56,742 50 56,159 50 112,900 100 Tabora Urban 27,098 49 27,741 51 54,839 100 Total 732,811 52 687,489 48 1,420,300 100 Number % Number % Number % Number % Number % Nzega 134,146 42 11,184 4 136 0 170,905 54 316,371 100 Igunga 127,922 50 9,149 4 215 0 120,066 47 257,353 100 Uyui 111,264 47 9,758 4 300 0 112,963 48 234,284 100 Urambo 141,661 51 13,348 5 0 0 121,964 44 276,972 100 Sikonge 51,852 54 1,893 2 43 0 42,807 44 96,596 100 Tabora Urban 31,541 65 1,228 3 54 0 15,848 33 48,671 100 Total 598,385 49 46,560 4 748 0 584,554 48 1,230,247 100 Number % Number % Number % Number % Nzega 57,727 18 94,452 30 164,192 52 316,371 100 Igunga 55,993 22 84,604 33 116,756 45 257,353 100 Uyui 49,696 21 76,825 33 107,763 46 234,284 100 Urambo 66,043 24 97,841 35 113,088 41 276,972 100 Sikonge 16,951 18 39,365 41 40,280 42 96,596 100 Tabora Urban 12,700 26 20,449 42 15,521 32 48,671 100 Total 259,109 21 413,537 34 557,601 45 1,230,247 100 Number % Number % Number % Number % Number % Nzega 194,747 62 13,916 4 136 0 146 0 1,403 0 Igunga 104,449 41 23,567 9 338 0 222 0 910 0 Uyui 130,995 56 5,783 2 310 0 211 0 713 0 Urambo 164,093 59 5,094 2 1,001 0 222 0 1,052 0 Sikonge 61,918 64 3,991 4 0 0 0 0 390 0 Tabora Urban 20,136 41 1,943 4 199 0 0 0 627 1 Total 676,338 55 54,294 4 1,984 0 802 0 5,095 0 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Crop/Seaweed Farming Livestock Keeping / Livestock Pastoralist Fishing Government / Parastatal 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 District School Attendancy Attending Completed Never Attended Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Census - 2003 Tabora Appendix II 140 Number % Number % Number % Number % Number % Nzega 1,691 1 1,028 0 272 0 1,027 0 299 0 Igunga 1,968 1 663 0 12,566 5 1,290 1 444 0 Uyui 2,786 1 1,622 1 5,083 2 2,472 1 184 0 Urambo 1,996 1 734 0 1,218 0 1,070 0 326 0 Sikonge 198 0 490 1 393 0 764 1 99 0 Tabora Urban 473 1 148 0 7,203 15 52 0 697 1 Total 9,112 1 4,684 0 26,734 2 6,676 1 2,049 0 Number % Number % Number % Number % Number % Number % Nzega 0 0 6,016 2 52,014 16 40,187 13 3,490 1 316,371 100 Igunga 116 0 9,482 4 52,575 20 48,089 19 675 0 257,353 100 Uyui 317 0 1,210 1 43,676 19 38,503 16 418 0 234,284 100 Urambo 126 0 1,314 0 61,673 22 32,377 12 4,675 2 276,972 100 Sikonge 0 0 197 0 15,397 16 11,847 12 913 1 96,596 100 Tabora Urban 26 0 77 0 11,757 24 5,172 11 160 0 48,671 100 Total 585 0 18,296 1 237,091 19 176,175 14 10,331 1 1,230,247 100 Number % Number % Number % Number % Number % Nzega 195,227 62 7,110 2 61,660 19 52,374 17 316,371 100 Igunga 114,990 45 7,672 3 79,772 31 54,919 21 257,353 100 Uyui 124,460 53 8,156 3 58,994 25 42,674 18 234,284 100 Urambo 161,836 58 5,255 2 64,371 23 45,511 16 276,972 100 Sikonge 62,408 65 3,901 4 14,186 15 16,101 17 96,596 100 Tabora Urban 19,269 40 5,663 12 16,694 34 7,045 14 48,671 100 Total 678,190 55 37,757 3 295,677 24 218,623 18 1,230,247 100 Total Main Activity 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full- time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Other Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Private - NGO / Mission / etc p y (Non Farmimg) p y (Non Farmimg) without p y Helper (Non Agriculture) Not Working & Available Main Activity Tanzania Agriculture Census - 2003 Tabora Appendix II 141 Number % Number % Number % Number % Number % Nzega 0 0 878 1 3,213 3 2,726 3 10,289 11 Igunga 224 0 228 0 1,132 1 1,466 2 6,476 8 Uyui 200 0 1,320 2 3,077 4 2,128 3 9,351 12 Urambo 1,099 1 600 1 2,600 3 4,069 4 11,318 12 Sikonge 50 0 434 1 1,263 3 1,444 4 4,012 10 Tabora Urban 27 0 523 3 670 3 973 5 2,446 12 Total 1,599 0 3,984 1 11,955 3 12,806 3 43,893 11 Number % Number % Number Number % Number % Nzega 2,483 3 2,555 3 68,074 72 708 1 574 1 Igunga 2,112 2 1,812 2 66,602 79 887 1 562 1 Uyui 1,921 2 2,937 4 50,751 66 1,536 2 103 0 Urambo 4,454 5 4,258 4 63,770 65 357 0 124 0 Sikonge 672 2 877 2 28,387 72 439 1 292 1 Tabora Urban 748 4 748 4 12,612 62 633 3 37 0 Total 12,389 3 13,186 3 290,195 70 4,560 1 1692 0 Number % Number % Number % Number % Number % Nzega 0 0 119 0 445 0 291 0 1,536 2 Igunga 0 0 0 0 109 0 109 0 973 1 Uyui 0 0 310 0 504 1 0 0 1,537 2 Urambo 0 0 0 0 349 0 375 0 1,845 2 Sikonge 148 0 95 0 244 1 46 0 913 2 Tabora Urban 27 0 52 0 103 1 25 0 416 2 Total 175 0 576 0 1756 0 847 0 7,220 2 Number % Number % Number % Number % Number % Nzega 0 0 147 0 124 0 290 0 94,452 100 Igunga 330 0 204 0 0 0 1,378 2 84,604 100 Uyui 208 0 0 0 0 0 942 1 76,825 100 Urambo 0 0 126 0 0 0 2,497 3 97,841 100 Sikonge 0 0 0 0 0 0 49 0 39,365 100 Tabora Urban 27 0 0 0 27 0 355 2 20,449 100 Total 566 0 476 0 151 0 5,511 1 413,537 100 District Education Level Education Level Education Level Education Level Form Six Training After Secondary University & Other Adult Education Total 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont….HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District District Form Four Pre Form One Form One Form Two Form Three Standard Three Standard Four Standard Five Standard Six Standard Seven Standard Eight Training After District Under Standard One Standard One Standard Two Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 142 Number % Average Household Size Number % Average Household Size Number % Average Household Size Nzega 54327 83 6 11239 17 3 65566 100 5 Igunga 40038 89 7 5103 11 4 45141 100 7 Uyui 35609 86 7 5708 14 5 41318 100 7 Urambo 46691 86 6 7429 14 4 54120 100 6 Sikonge 16882 87 6 2631 13 3 19514 100 6 Tabora Urban 8549 83 6 1709 17 4 10258 100 5 Total 202097 86 6 33820 14 4 235917 100 6 Number % Number % Number % Number % Nzega 26,082.13 43 18,726.87 31 16,469.31 27 61,278.31 100 Igunga 23,285.70 55 10,971.36 26 8,205.83 19 42,462.89 100 Uyui 24,801.56 78 4,545.28 14 2,431.98 8 31,778.82 100 Urambo 28,648.95 59 12,552.49 26 6,983.64 14 48,185.08 100 Sikonge 8,709.02 60 3,459.75 24 2,240.38 16 14,409.15 100 Tabora Urb 5,925.18 67 2,028.46 23 831.00 9 8,784.64 100 Total 117,452.54 57 52,284.21 25 37,162.14 18 206,898.89 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Nzega 32,985 30,197 300 1,383 147 124 431 65,566 Igunga 21,763 22,085 340 450 94 0 409 45,141 Uyui 15,801 23,665 103 1,223 0 0 526 41,318 Urambo 18,012 32,915 124 1,516 126 0 1,427 54,120 Sikonge 6,018 12,610 98 740 0 0 49 19,514 Tabora Urban 3,190 6,393 13 412 0 27 224 10,258 Total 97,767 127,864 979 5,724 367 151 3,066 235,917 Mean Median Mode Mean Median Mode Mean Median Mode Nzega 47.39448261 45 60 54.28974015 54 50 48.57643073 48 60 Igunga 45.7464136 42 40 51.20685666 49 55 46.36371093 43 40 Uyui 45.40639926 42 30 52.5523658 52 70 46.39364742 44 30 Urambo 43.54515626 40 35 49.0763008 50 55 44.30442272 41 40 Sikonge 43.07979649 40 30 50.72944103 49 45 44.11132617 41 30 Tabora Urb 48.88210258 48 65 52.06704642 52 50 49.41278829 49 65 Total 45.5308498 42 30 51.99676421 52 70 46.45777754 44 30 District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Off farm income One Two More than Two Total 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 143 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 151 159 158 175 174 209 Female Headed (Number in Thousands) 25 34 36 32 29 52 Total 176 193 194 207 203 261 Male Headed (Percentage) 86 82 81 84 86 80 Female Headed (Percentage) 14 18 19 16 14 20 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Nzega 28867 3715 32582 25460 7524 32985 54,327 11,239 65,566 Igunga 22287 1315 23602 17751 3788 21539 40,038 5,103 45,141 Uyui 24097 1522 25618 11513 4186 15699 35,609 5,708 41,318 Urambo 33820 2757 36577 12871 4672 17543 46,691 7,429 54,120 Sikonge 11838 1658 13496 5044 974 6018 16,882 2,631 19,514 Tabora Urban 6487 581 7068 2062 1128 3190 8,549 1,709 10,258 Total 127396 11548 138944 74701 22272 96973 202,097 33,820 235,917 3.14 Time Series of Male and Female Headed Households Know Don't Know Total Literacy District 3.15 Literacy Rates of Heads of Households by Sex and District Tanzania Agriculture Sample Census - 2003 Tabora 144 Appendix II 145 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 146 Households with Area Leased/Certif icate of Ownership % Households with Area Owned Under Customary Law % Households with Area Bought From Others % Households with Area Rented From Others % Households with Area Borrowed From Others % Households with Area Shared Croped From Others % Households with Area under Other Forms of Tenure % Total Number of Households Nzega 150 0 55,082 84 13,660 21 4,482 7 4,400 7 585 1 1,008 2 65,566 Igunga 1,437 3 33,952 75 10,720 24 10,393 23 4,139 9 2,265 5 1,344 3 45,141 Uyui 909 2 28,668 69 11,291 27 3,011 7 5,011 12 616 1 1,675 4 41,318 Urambo 1,546 3 39,267 73 11,302 21 3,413 6 6,455 12 477 1 2,961 5 54,120 Sikonge 341 2 16,462 84 2,398 12 830 4 1,762 9 99 1 615 3 19,514 Tabora Urban 674 7 8,346 81 2,016 20 577 6 630 6 113 1 244 2 10,258 Total 5,057 2 181,777 77 51,387 22 22,706 10 22,397 9 4,155 2 7,847 3 235,917 Area Leased/Certif icate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Nzega 213 116,954 22,792 2,620 2,539 179 611 145,908 Igunga 3,681 126,635 35,872 15,382 6,634 3,853 1,021 193,077 Uyui 5,193 130,792 37,005 4,406 5,781 1,470 3,447 188,093 Urambo 4,078 171,784 49,247 5,171 6,405 1,644 13,350 251,678 Sikonge 1,285 69,040 9,810 1,246 1,955 241 2,597 86,174 Tabora Urb 1,497 25,164 5,666 826 629 235 300 34,318 Total 15,946 640,369 160,392 29,651 23,943 7,622 21,326 899,248 Land Access 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 147 LAND USE Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 148 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Nzega 51,560 39,574 7,994 1,898 5,295 124 9,862 738 676 882 3,284 15,156 65,566 Igunga 40,335 19,440 1,284 1,349 1,356 5,977 2,066 749 114 1,919 1,774 10,258 45,141 Uyui 31,741 27,979 5,696 1,933 2,707 3,479 8,536 3,283 822 1,320 3,557 19,013 41,318 Urambo 42,042 29,079 11,415 2,309 9,542 2,959 15,591 12,325 876 1,328 7,253 18,972 54,120 Sikonge 13,358 13,330 3,470 484 1,060 1,112 4,162 2,266 288 291 625 7,601 19,514 Tabora Urban 7,066 7,730 4,013 659 1,659 497 2,473 736 79 186 775 5,155 10,258 Total 186,102 137,132 33,871 8,631 21,619 14,147 42,690 20,096 2,855 5,927 17,268 76,155 235,917 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Nzega 61,148 44,348 3,144 636 4,578 125 12,225 512 131 1,126 4,406 13,528 145,908 Igunga 113,001 27,521 327 2,970 4,315 16,095 3,319 1,592 46 5,710 4,851 13,330 193,077 Uyui 57,360 43,216 2,484 2,609 3,194 7,704 12,261 11,085 606 2,280 8,076 37,219 188,093 Urambo 73,930 36,474 5,904 2,636 10,490 6,589 25,353 41,471 2,241 688 13,910 31,968 251,655 Sikonge 24,826 22,518 1,310 414 1,652 2,012 5,930 7,130 188 388 1,433 18,373 86,174 Tabora Urban 6,053 8,716 2,009 871 1,688 739 2,928 1,283 24 361 1,087 8,560 34,318 Total 336,318 182,793 15,179 10,136 25,917 33,264 62,016 63,072 3,237 10,553 33,763 122,977 899,225 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year District Land Use Area Land Use District 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District during 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 149 Number % Number % Number % Number % Nzega 40,492 62 25,074 38 65,566 Nzega 40,042 61 25,524 39 65,566 Igunga 28,055 62 16,970 38 45,025 Igunga 21,242 47 23,783 53 45,025 Uyui 13,245 32 27,968 68 41,212 Uyui 27,506 67 13,706 33 41,212 Urambo 14,588 27 39,532 73 54,120 Urambo 36,872 68 17,248 32 54,120 Sikonge 6,808 35 12,656 65 19,464 Sikonge 13,666 70 5,799 30 19,464 Tabora Urban 3,372 33 6,861 67 10,233 Tabora Urban 7,819 76 2,413 24 10,233 Total 106,559 45 129,061 55 235,621 Total 147,147 62 88,474 38 235,621 Total Number % Number % Number Nzega 10,308 16 55,258 84 65,566 Igunga 2,223 5 42,802 95 45,025 Uyui 4,076 10 37,137 90 41,212 Urambo 4,245 8 49,875 92 54,120 Sikonge 2,827 15 16,637 85 19,464 Tabora Urban 1,009 10 9,224 90 10,233 Total 24,688 10 210,933 90 235,621 Total 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District during 2002/03 Agricultural Year Do you Consider that you have sufficient land for the Hh? District Yes No Total 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year Was all Land Available to the Hh Used During 2002/03? 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Yes No District Yes No Do any Female Members of the Hh own or have Tanzania Agriculture Sample Census - 2003 Tabora 150 Appendix II 151 ANNUAL CROP & VEGETABLE PRODUCTION - LONG RAIN SEASON Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 152 District Number of Households Planted Area (hectare Nzega 65,566 109,322 Igunga 45,141 142,453 Uyui 41,318 95,654 Urambo 54,120 114,863 Sikonge 19,514 52,716 Tabora Urban 10,258 17,606 Total 235,917 532,615 Number of Households Growing Crops Number of Households NOT Growing Crops Total Number of Crop Growing Households Number Number Number Nzega 65,428 138 65,566 Igunga 45,025 116 45,141 Uyui 41,212 105 41,318 Urambo 54,120 0 54,120 Sikonge 19,464 50 19,514 Tabora Urban 10,206 52 10,258 Total 235,456 461 235,917 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) By District - LONG RAINY SEASON District Long Rainy Season 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District-LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 153 Planted area (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 347455 222315 Maize 232860 143122 615 Paddy 65657 58661 893 Sorghum 46379 18959 409 Bulrush Millet 1545 700 453 Finger Millet 881 769 873 Wheat 33 15 468 Barley 100 89 889 ROOTS & TUBERS 31535 41380 Cassava 21391 28416 1328 Sweet Potatoes 9173 12351 1346 Irish Potatoes 723 329 455 Yams 248 283 1143 PULSES 25911 9659 Mung Beans 66 19 295 Beans 19331 7143 370 Cowpeas 1802 544 302 Green Gram 436 91 209 Chich Peas 682 437 640 Bambaranuts 3593 1424 396 OIL SEEDS & OIL NUTS 69862 31877 456 Sunflower 510 149 292 Simsim 548 94 172 Groundnuts 68730 31618 460 Soya Beans 75 16 211 FRUITS & VEGETABLES 2904 5847 Okra 21 31 1469 Radish 283 419 1480 Turmeric 0 0 0 Bitter Aubergine 97 85 872 Garlic 0 0 0 Onions 1507 2550 1692 Ginger 5 13 2371 Cabbage 48 55 1140 Tomatoes 827 2522 3048 Chillies 1 7 5558 Amaranths 60 98 1632 Pumpkins 38 53 1408 Cucumber 3 2 790 Egg Plant 12 11 865 CASH CROPS 54948 39604 Seaweed 0 0 0 Cotton 22409 9932 443 Tobacco 32490 29613 911 Pyrethrum 49 58 1186 Jute 0 1 3088 Total 532615 7.1c CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the Year 2002/03 Agriculture Year, Tabora Region Crop Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 154 Number of Households Planted area (ha) Area Planted per Household (ha/hh) CEREALS 353280 347455 Maize 229901 232860 1.0 Paddy 92037 65657 0.7 Sorghum 28207 46379 1.6 Bulrush Millet 554 1545 2.8 Finger Millet 2311 881 0.4 Wheat 221 33 0.1 Barley 49 100 2.0 ROOTS & TUBERS 77055 31535 Cassava 47395 21391 0.5 Sweet Potatoes 27635 9173 0.3 Irish Potatoes 1193 723 0.6 Yams 832 248 0.3 PULSES 79687 25911 Mung Beans 163 66 0.4 Beans 56189 19331 0.3 Cowpeas 7792 1802 0.2 Green Gram 2015 436 0.2 Chich Peas 948 682 0.7 Bambaranuts 12580 3593 0.3 OIL SEEDS & OIL NUTS 146161 69862 Sunflower 1525 510 0.3 Simsim 976 548 0.6 Groundnuts 143462 68730 0.5 Soya Beans 198 75 0.4 FRUITS & VEGETABLES 10815 2904 Okra 76 21 0.3 Radish 258 283 1.1 Bitter Aubergine 240 97 0.4 Onions 3250 1507 0.5 Ginger 27 5 0.2 Cabbage 246 48 0.2 Tomatoes 5471 827 0.2 Chillies 25 1 0.0 Amaranths 568 60 0.1 Pumpkins 476 38 0.1 Cucumber 26 3 0.1 Egg Plant 150 12 0.1 CASH CROPS 44413 54948 Cotton 13395 22409 1.7 Tobacco 30946 32490 1.0 Pyrethrum 48 49 1.0 Jute 24 0 0.0 Total 711411 532615 Long Rainy Season Crop 7.1d CROP AND VEGETABLE PRODUCTION: Number of Agriculture Household by Area Planted (ha) and Crop for the Agricuture Year 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 155 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 571 1,353 29,292 64,739 35,566 38,842 65,428 104,934 Igunga 901 1,875 37,154 129,795 6,970 10,112 45,025 141,782 Uyui 412 749 8,794 31,866 32,007 59,899 41,212 92,515 Urambo 126 115 4,950 15,290 49,043 90,783 54,120 106,188 Sikonge 589 983 3,041 18,060 15,835 31,873 19,464 50,916 Tabora Urban 51 42 670 1,888 9,485 13,391 10,206 15,321 Total 2,650 5,117 83,901 261,638 148,905 244,900 235,456 511,655 % 0.5 1.0 16.4 51.1 29.1 47.9 46.0 100.0 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 12,860 24,016 3,087 6,515 1,413 3,154 48,206 75,637 65,566 109,322 Igunga 3,998 8,517 460 1,792 862 3,136 39,705 129,008 45,025 142,453 Uyui 3,850 12,907 1,124 1,993 8,428 24,771 27,811 55,984 41,212 95,654 Urambo 3,102 9,090 1,364 1,549 13,908 38,531 35,746 65,694 54,120 114,863 Sikonge 1,943 8,234 47 66 5,258 15,973 12,217 28,443 19,464 52,716 Tabora Urb 1,228 2,843 160 258 2,197 4,618 6,622 9,888 10,206 17,606 Total 26,982 65,605 6,240 12,173 32,066 90,184 170,306 364,654 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 10,673 23,021 54,893 86,301 65,566 109,322 21.1 Igunga 3,227 8,425 41,799 134,028 45,025 142,453 5.9 Uyui 6,708 14,011 34,505 81,643 41,212 95,654 14.6 Urambo 12,546 24,666 41,574 90,197 54,120 114,863 21.5 Sikonge 2,540 11,910 16,924 40,805 19,464 52,716 22.6 Tabora Urban 3,009 6,457 7,197 11,149 10,206 17,606 36.7 Total 38,702 88,491 196,892 444,124 235,594 532,615 16.6 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 5,747 12,895 59,819 96,428 65,566 109,322 Igunga 6,710 32,343 38,315 110,111 45,025 142,453 Uyui 12,766 39,897 28,447 55,758 41,212 95,654 Urambo 18,095 52,083 36,025 62,780 54,120 114,863 Sikonge 6,670 23,218 12,795 29,498 19,464 52,716 Tabora Urb 3,939 8,474 6,267 9,133 10,206 17,606 Total 53,927 168,908 181,667 363,707 235,594 532,615 % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation 7.1h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing and Planted Area By Insecticide Use and District for the 2002/03 Crop Year - LONG RAINY SEASON District Insecticide Use Households Using Pesticide Households Not Using Pesticide Total Households Not Using Irrigation Total District Mostly Farm Yard Mostly Compost Mostly Inorganic Fertilizer Use Total No Fertilizer Applied 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION:Number of Crop Growing Households and Planted Area By Irrigation Use and District for the 2002/03 Crop Year - LONG RAINY SEASON 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District for the 2002/03 Crop Year-LONG RAINY SEASON 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Tabora Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 156 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 601 1,350 64,965 107,973 65,566 109,322 Igunga 569 1,544 44,456 140,909 45,025 142,453 Uyui 726 1,882 40,486 93,772 41,212 95,654 Urambo 2,568 7,520 51,552 107,343 54,120 114,863 Sikonge 99 542 19,365 52,174 19,464 52,716 Tabora Urb 287 492 9,919 17,114 10,206 17,606 Total 4,850 13,330 230,744 519,285 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 900 3,249 64,666 106,073 65,566 109,322 Igunga 1,589 7,215 43,436 135,238 45,025 142,453 Uyui 1,565 4,017 39,648 91,637 41,212 95,654 Urambo 6,436 17,503 47,684 97,361 54,120 114,863 Sikonge 1,134 4,185 18,331 48,531 19,464 52,716 Tabora Urb 620 1,510 9,586 16,096 10,206 17,606 Total 12,244 37,680 223,350 494,935 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 4,630 7,588 60,799 97,346 65,428 104,934 Igunga 3,815 17,066 41,210 124,716 45,025 141,782 Uyui 6,237 19,024 34,976 73,490 41,212 92,515 Urambo 12,950 31,224 41,170 74,964 54,120 106,188 Sikonge 3,057 10,548 16,407 40,368 19,464 50,916 Tabora Urban 1,788 2,675 8,418 12,646 10,206 15,321 Total 32,477 88,125 202,980 423,530 235,456 511,655 Number % Number % Nzega 27633 42 37933 58 65566 Igunga 21622 48 23519 52 45141 Uyui 21884 53 19434 47 41318 Urambo 43449 80 10671 20 54120 Sikonge 12147 62 7367 38 19514 Tabora Urban 4669 46 5589 54 10258 Total 131403 56 104514 44 235917 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON 7.1j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total 7.1i ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total 7.2a Number of Crop Producing Households Reporting Selling Agricultural Produce by District; 2003/04 Agriculture Year District Households that Sold Produce Households that Did not Sell Produce Total Number of Households Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area CEREALS 29743 303639 1124 5669 5594 122 345891 Maize 18,660 20,329 204,004 205,806 670 795 2,110 1,758 3,352 3,152 150 122 228,946 231,963 Paddy 5,347 5,607 77,445 53,189 256 73 4,889 3,708 3,656 2,442 0 . 91,592 65,020 Sorghum 3,034 3,807 24,805 42,268 114 231 108 44 0 . 0 . 28,060 46,349 Bulrush Millet 0 . 554 1,545 0 . 0 . 0 . 0 . 554 1,545 Finger Millet 0 . 1,702 697 125 25 484 159 0 . 0 . 2,311 881 Wheat 0 . 221 33 0 . 0 . 0 . 0 . 221 33 Barley 0 . 49 100 0 . 0 . 0 . 0 . 49 100 ROOTS & TUBERS 1,356 8,670 125 115 309 . 10,575 Cassava 0 . 1,429 431 0 . 0 . 0 . 0 . 1,429 431 Sweet Potatoes 4,038 1,274 21,780 7,397 232 103 222 90 1,362 309 0 . 27,635 9,173 Irish Potatoes 145 59 940 642 109 22 0 . 0 . 0 . 1,193 723 Yams 114 23 595 200 0 . 123 25 0 . 0 . 832 248 Cocoyam 0 . 0 . 0 . 0 . 0 . 0 . 0 . PULSES 5,899 2,397 71,672 22,533 267 69 1,198 696 624 195 0 . 79,661 25,889 Mung Beans 114 46 49 20 0 . 0 . 0 . 0 . 163 66 Beans 3,215 1,347 51,280 17,127 267 69 1,198 696 229 93 0 . 56,189 19,331 Cowpeas 969 305 6,728 1,465 0 . 0 . 95 32 0 . 7,792 1,802 Green Gram 476 129 1,539 307 0 . 0 . 0 . 0 . 2,015 436 Pigeon Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chich Peas 0 . 948 682 0 . 0 . 0 . 0 . 948 682 Bambaranuts 1,125 569 11,128 2,933 0 . 0 . 300 70 0 . 12,553 3,571 Field Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . OIL SEEDS & OIL NUTS 6,010 61,568 3 572 1,169 . 69,320 Sunflower 341 116 1,184 394 0 . 0 . 0 . 0 . 1,525 510 Simsim 244 94 732 453 0 . 0 . 0 . 0 . 976 548 Groundnuts 11,082 5,800 127,899 60,645 27 3 1,075 572 2,727 1,169 0 . 142,810 68,188 Soya Beans 0 . 198 75 0 . 0 . 0 . 0 . 198 75 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 439 2,407 21 22 15 . 2,904 Okra 50 20 27 1 0 . 0 . 0 . 0 . 76 21 Radish 149 261 0 . 0 . 109 22 0 . 0 . 258 283 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 240 97 0 . 0 . 0 . 0 . 240 97 Garlic 0 . 0 . 0 . 0 . 0 . 0 . 0 . Onions 741 110 2,359 1,381 0 . 0 . 150 15 0 . 3,250 1,507 Ginger 0 . 27 5 0 . 0 . 0 . 0 . 27 5 Cabbage 0 . 246 48 0 . 0 . 0 . 0 . 246 48 Tomatoes 242 46 5,052 760 177 21 0 . 0 . 0 . 5,471 827 Spinnach 0 . 0 . 0 . 0 . 0 . 0 . 0 . Carrot 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chillies 0 . 25 1 0 . 0 . 0 . 0 . 25 1 Amaranths 26 1 542 60 0 . 0 . 0 . 0 . 568 60 Pumpkins 27 1 449 37 0 . 0 . 0 . 0 . 476 38 Cucumber 0 . 26 3 0 . 0 . 0 . 0 . 26 3 Egg Plant 0 . 150 12 0 . 0 . 0 . 0 . 150 12 Water Mellon 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 6,929 47,710 181 67 20 . 54,908 Seaweed 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cotton 1,909 2,252 11,262 19,951 114 139 110 67 0 . 0 . 13,395 22,409 Tobacco 3,970 4,677 26,772 27,710 106 43 0 . 50 20 0 . 30,897 32,450 Pyrethrum 0 . 48 49 0 . 0 . 0 . 0 . 48 49 Jute 0 . 24 0 0 . 0 . 0 . 0 . 24 0 Total 46,875 446,526 1,523 7,140 7,302 122 509,488 Total Crop 7.2b ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households During the Long Rainy Season by Method of Land Clearing and Crop; 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning No Land Clearing Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 158 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 64,428 52,986 36,466 0.7 Igunga 42,764 56,579 18,821 0.3 Uyui 40,700 46,418 28,017 0.6 Urambo 52,445 46,076 37,839 0.8 Sikonge 19,375 22,958 17,841 0.8 Tabora Urban 10,189 7,844 4,138 0.5 Total 229,901 232,860 143,122 0.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 36,736 25,289 22,484 0.9 Igunga 10,553 6,560 7,924 1.2 Uyui 17,627 14,587 13,713 0.9 Urambo 17,943 11,904 10,422 0.9 Sikonge 4,627 5,193 2,470 0.5 Tabora Urban 4,551 2,124 1,648 0.8 Total 92,037 65,657 58,661 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 2,176 1,347 712 0.5 Igunga 20,424 38,804 15,621 0.4 Uyui 2,899 3,162 1,660 0.5 Urambo 1,152 345 100 0.3 Sikonge 1,381 2,665 850 0.3 Tabora Urban 176 57 15 0.3 Total 28,207 46,379 18,959 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 97 39 29 0.7 Urambo 115 70 5 0.1 Sikonge 341 1,436 666 0.5 Tabora Urban 0 0 0 0.0 Total 554 1,545 700 0.5 7.2.5 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.3 Number of Households by Planted Area (ha) and Quantity of Sorghum Harvested (tons) by District and Crop-Long Rainy Season District Bulrush Millet 7.2.1 Number of Households by Planted Area (ha) and Quantity of Maize Harvested (tons) by District and Crop-Long Rainy Season Maize Sorghum Paddy District 7.2.2 Number of Households by Planted Area (ha) and Quantity of Paddy Harvested (tons) by District and Crop-Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 159 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 432 98 152 1.6 Igunga 0 0 0 0.0 Uyui 106 43 76 1.8 Urambo 1,726 722 513 0.7 Sikonge 48 19 28 1.5 Tabora Urban 0 0 0 0.0 Total 2,311 881 769 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 49 100 89 0.9 Tabora Urban 0 0 0 0.0 Total 49 100 89 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 119 12 0 0.0 Igunga 0 0 0 0.0 Uyui 102 21 15 0.7 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 221 33 15 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 10,904 4,388 4,024 0.9 Igunga 2,088 736 1,114 1.5 Uyui 7,176 3,316 3,115 0.9 Urambo 19,146 8,795 16,274 1.9 Sikonge 3,906 1,829 2,062 1.1 Tabora Urban 4,175 2,326 1,827 0.8 Total 47,395 21,391 28,416 1.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 1,602 673 490 0.7 Igunga 11,500 3,639 2,590 0.7 Uyui 4,234 1,440 3,715 2.6 Urambo 5,546 1,483 3,396 2.3 Sikonge 2,299 1,166 923 0.8 Tabora Urban 2,453 772 1,237 1.6 Total 27,635 9,173 12,351 1.3 District District 7.2.6 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.7 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.8 Number of Households by Planted Area (ha) and Quantity of Cassava Harvested (tons) by District and Crop-Long Rainy Season Barley Wheat District 7.2.9 Number of Households by Planted Area (ha) and Quantity of Sweet Potatoes Harvested (tons) by District and Crop-Long Rainy Season District 7.2.4 Number of Households by Planted Area (ha) and Quantity of Finger Millet Harvested (tons) by District and Crop-Long Rainy Season Finger Millet Sweet Potatoes Cassava Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 160 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 444 112 81 0.7 Uyui 105 21 17 0.8 Urambo 618 579 218 0.4 Sikonge 0 0 0 0.0 Tabora Urban 27 11 13 1.2 Total 1,193 723 329 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 419 129 247 1.9 Igunga 114 23 3 0.1 Uyui 0 0 0 0.0 Urambo 123 25 0 0.0 Sikonge 149 60 25 0.4 Tabora Urban 27 11 9 0.8 Total 832 248 283 1.1 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 6612 1064 300 0.3 Igunga 451 319 493 1.5 Uyui 10854 3654 912 0.2 Urambo 26666 10308 4318 0.4 Sikonge 6669 2547 870 0.3 Tabora Urban 4936 1439 250 0.2 Total 56189 19331 7143 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 5487 1353 691 0.5 Igunga 1903 659 112 0.2 Uyui 2020 782 305 0.4 Urambo 1324 294 103 0.3 Sikonge 918 327 133 0.4 Tabora Urban 928 177 81 0.5 Total 12580 3593 1424 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 2,024 560 135 0.2 Igunga 1,306 187 62 0.3 Uyui 1,125 236 76 0.3 Urambo 1,852 444 169 0.4 Sikonge 713 245 55 0.2 Tabora Urban 772 130 47 0.4 Total 7,792 1,802 544 0.3 7.2.12 Number of Households by Planted Area (ha) and Quantity of Beans Harvested (tons) by District and Crop-Long Rainy Season Beans District District 7.2.14 Number of Households by Planted Area (ha) and Quantity of Cowpeas Harvested (tons) by District and Crop-Long Rainy Season District 7.2.11 Number of Households by Planted Area (ha) and Quantity of Irish Potatoes Harvested (tons) by District and Crop-Long Rainy Season Yams District District 7.2.13 Number of Households by Planted Area (ha) and Quantity of Bambaranuts Harvested (tons) by District and Crop-Long Rainy Season Bambaranuts 7.2.10 Number of Households by Planted Area (ha) and Quantity of Irish Potatoes Harvested (tons) by District and Crop-Long Rainy Season Irish Potatoes Cowpeas Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 161 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 150 16 9 0.6 Igunga 798 667 428 0.6 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 948 682 437 0.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 450 86 12 0.1 Uyui 407 85 10 0.1 Urambo 1101 258 68 0.3 Sikonge 43 1 1 0.6 Tabora Urb 13 6 1 0.1 Total 2015 436 91 0.2 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 114 46 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 49 20 19 1.0 Tabora Urban 0 0 0 0.0 Total 163 66 19 0.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 46,773 19,722 9,820 0.5 Igunga 19,892 10,391 2,972 0.3 Uyui 25,553 11,660 5,422 0.5 Urambo 32,741 17,001 10,343 0.6 Sikonge 12,635 7,863 2,298 0.3 Tabora Urban 5,869 2,093 763 0.4 Total 143,462 68,730 31,618 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 147 179 0 0.0 Igunga 0 0 0 0.0 Uyui 399 211 48 0.2 Urambo 244 94 35 0.4 Sikonge 186 64 12 0.2 Tabora Urban 0 0 0 0.0 Total 976 548 94 0.2 District 7.2.17 Number of Households by Planted Area (ha) and Quantity of Mung Beans Harvested (tons) by District and Crop-Long Rainy Season Mung Beans 7.2.16 Number of Households by Planted Area (ha) and Quantity of Green Gram Harvested (tons) by District and Crop-Long Rainy Season Green Gram District 7.2.18 Number of Households by Planted Area (ha) and Quantity of Groundnuts Harvested (tons) by District and Crop-Long Rainy Season Groundnuts District 7.2.15 Number of Households by Planted Area (ha) and Quantity of Chick Peas Harvested (tons) by District and Crop-Long Rainy Season Chich Peas District District 7.2.19 Number of Households by Planted Area (ha) and Quantity of Simsim Harvested (tons) by District and Crop-Long Rainy Season Simsim Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 162 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 998 328 74 0.2 Uyui 0 0 0 0.0 Urambo 252 77 45 0.6 Sikonge 194 77 23 0.3 Tabora Urban 80 28 6 0.2 Total 1525 510 149 0.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 198 75 16 0.2 Tabora Urban 0 0 0 0.0 Total 198 75 16 0.2 District District 7.2.20 Number of Households by Planted Area (ha) and Quantity of Sunflower Harvested (tons) by District and Crop-Long Rainy Season 7.2.21 Number of Households by Planted Area (ha) and Quantity of Soya Beans Harvested (tons) by District and Crop-Long Rainy Season Soya Beans Sunflower Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 163 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 747 151 298 2.0 Igunga 1488 1212 1446 1.2 Uyui 203 30 166 5.5 Urambo 598 72 591 8.2 Sikonge 0 0 0 0.0 Tabora Urban 215 41 49 1.2 Total 3250 1507 2550 1.7 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 743 120 304 2.5 Igunga 417 54 80 1.5 Uyui 1658 255 767 3.0 Urambo 1417 173 599 3.5 Sikonge 49 5 12 2.4 Tabora Urb 1187 221 760 3.4 Total 5471 827 2522 3.0 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 109 22 5 0.2 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 149 261 413 1.6 Tabora Urban 0 0 0 0.0 Total 258 283 419 1.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 116 47 65 1.4 Uyui 0 0 0 0.0 Urambo 124 50 20 0.4 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 240 97 85 0.9 District District Bitter Aubergine 7.2.22 Number of Households by Planted Area (ha) and Quantity of Onion Harvested (tons) by District and Crop-Long Rainy Season 7.2.23 Number of Households by Planted Area (ha) and Quantity of Tomatoes Harvested (tons) by District and Crop-Long Rainy Season 7.2.24 Number of Households by Planted Area (ha) and Quantity of Radish Harvested (tons) by District and Crop-Long Rainy Season 7.2.25 Number of Households by Planted Area (ha) and Quantity of Bitter Aubergine Harvested (tons) by District and Crop-Long Rainy Season Radish Onions Tomatoes District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 164 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 358 36 32 0.9 Sikonge 0 0 0 0.0 Tabora Urban 211 24 67 2.8 Total 568 60 98 1.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 206 42 46 1.1 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 40 7 9 1.4 Total 246 48 55 1.1 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 476 38 53 1.4 Total 476 38 53 1.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 50 20 30 1.5 Tabora Urban 27 1 1 1.2 Total 76 21 31 1.5 District District District Okra 7.2.26 Number of Households by Planted Area (ha) and Quantity of Amaranths Harvested (tons) by District and Crop-Long Rainy Season 7.2.27 Number of Households by Planted Area (ha) and Quantity of Cabbage Harvested (tons) by District and Crop-Long Rainy Season 7.2.28 Number of Households by Planted Area (ha) and Quantity of Pumpkins Harvested (tons) by District and Crop-Long Rainy Season District 7.2.29 Number of Households by Planted Area (ha) and Quantity of Okra Harvested (tons) by District and Crop-Long Rainy Season Pumpkins Cabbage Amaranths Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 165 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 150 12 11 0.9 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 150 12 11 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 27 5 13 2.4 Total 27 5 13 2.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 26 3 2 0.8 Total 26 3 2 0.8 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 25 1 7 5.6 Total 25 1 7 5.6 District Chillies 7.2.30 Number of Households by Planted Area (ha) and Quantity of Egg Plant Harvested (tons) by District and Crop-Long Rainy Season 7.2.31 Number of Households by Planted Area (ha) and Quantity of Ginger Harvested (tons) by District and Crop-Long Rainy Season 7.2.32 Number of Households by Planted Area (ha) and Quantity of Cucumber Harvested (tons) by District and Crop-Long Rainy Season 7.2.33 Number of Households by Planted Area (ha) and Quantity of Chillies Harvested (tons) by District and Crop-Long Rainy Season Cucumber Ginger Egg Plant District District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 166 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 1,101 1,078 889 0.8 Igunga 221 230 85 0.4 Uyui 8,363 9,635 8,286 0.9 Urambo 16,304 15,565 13,758 0.9 Sikonge 4,637 5,735 6,401 1.1 Tabora Urban 320 246 194 0.8 Total 30,946 32,490 29,613 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 260 145 61 0.4 Igunga 12,674 21,751 9,438 0.4 Uyui 95 19 28 1.5 Urambo 367 494 404 0.8 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 13,395 22,409 9,932 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 48 49 58 1.2 Tabora Urban 0 0 0 0.0 Total 48 49 58 1.2 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0.0 0.0 0.0 Igunga 0 0.0 0.0 0.0 Uyui 0 0.0 0.0 0.0 Urambo 0 0.0 0.0 0.0 Sikonge 0 0.0 0.0 0.0 Tabora Urban 24 0.4 1.2 3.1 Total 24 0.4 1.2 3.1 District 7.2.37 Number of Households by Planted Area (ha) and Quantity of Jute Harvested (tons) by District and Crop-Long Rainy Season Jute District 7.2.36 Number of Households by Planted Area (ha) and Quantity of Pyrethrum Harvested (tons) by District and Crop-Long Rainy Season Pyrethrum District 7.2.35 Number of Households by Planted Area (ha) and Quantity of Cotton Harvested (tons) by District and Crop-Long Rainy Season Cotton District 7.2.34 Number of Households by Planted Area (ha) and Quantity of Tobacco Harvested (tons) by District and Crop-Long Rainy Season Tobacco Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 167 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 168 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/Ha) Malay Apple 29 9 7 823 Sugarcane 0 0 . 0 Jack Fruit 7 0 . 0 Banana 92 52 42 822 Mango 649 105 5,320 50,756 Pawpaw 84 0 201 0 Orange 234 15 83 5,620 Guava 279 0 153 0 Lime/Lemon 56 0 3 0 Total 1,429 180 5,809 32,263 Sugarcane 47 23 145 6,175 Tamarin 5 0 . 0 Mango 268 9 165 17,883 Pawpaw 40 22 191 8,766 Guava 17 10 60 5,709 Total 377 65 560 8,633 Palm Oil 291 0 22 0 Coconut 1 0 2 0 Sugarcane 64 0 . 0 Jack Fruit 0 . 16 0 Banana 70 17 123 7,323 Avocado 0 . 59 0 Mango 432 129 4,028 31,123 Pawpaw 26 25 86 3,408 Orange 74 52 147 2,828 Guava 329 171 71 416 Total 1,285 394 4,555 11,552 Pigeon Pea 39 31 9 278 Malay Apple 0 0 126 0 Palm Oil 1,858 106 382 3,609 Coconut 53 0 . 0 Sugarcane 125 49 1,872 37,824 Jack Fruit 0 . 7 0 Banana 1,362 360 1,983 5,502 Mango 1,618 141 10,186 72,476 Pawpaw 516 80 406 5,078 Orange 119 78 2,175 27,886 Mandarine/Tangerine 51 . 6 0 Guava 28 28 16 589 Lime/Lemon 51 . 20 0 Total 5,820 873 17,188 19,686 Sugarcane 5 5 5 988 Jack Fruit 0 . 1 0 Banana 19 19 78 4,056 Mango 53 32 311 9,802 Pawpaw 0 4 2 497 Orange 8 8 40 5,055 Guava 0 0 3 0 Total 86 67 440 6,523 7.3.1 Production of Permanent Crops by Crop Type and District - Tabora Region Uyui Urambo Sikonge District/Crop Nzega Igunga Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 169 Palm Oil 10 12 12 992 Coconut 0 . 21 0 Sugarcane 62 40 1,527 37,975 Banana 56 42 390 9,343 Avocado 1 0 . 0 Mango 788 39 753 19,144 Pawpaw 4 66 40 613 Orange 6 8 192 22,609 Guava 3 2 57 26,391 Plums 0 . . 0 Lime/Lemon 3 17 186 10,999 Total 933 227 3,178 14,026 Pigeon Pea 39 31 9 278 Malay Apple 29 9 134 15,285 Palm Oil 2,158 118 416 3,538 Coconut 53 0 23 0 Sugarcane 303 118 3,549 30,031 Tamarin 5 0 . 0 Jack Fruit 7 0 24 0 Banana 1,600 490 2,616 5,341 Avocado 1 0 59 0 Mango 3,807 455 20,762 45,630 Pawpaw 670 197 926 4,712 Orange 440 161 2,637 16,352 Mandarine/Tangerine 51 . 6 0 Guava 656 211 360 1,706 Plums 0 . . 0 Lime/Lemon 110 17 209 12,325 Total 9,929 1,806 31,730 17,566 7.3.2: Area Planted by Crop Type - Tabora Region Crop Area Planted % Mango 3,807 38.3 Palm Oil 2,158 21.7 Banana 1,600 16.1 Pawpaw 670 6.7 Guava 656 6.6 Orange 440 4.4 Sugarcane 303 3.0 Lime/Lemon 110 1.1 Coconut 53 0.5 Mandarine/Tangerine 51 0.5 Pigeon Pea 39 0.4 Malay Apple 29 0.3 Jack Fruit 7 0.1 Tamarin 5 0.0 Avocado 1 0.0 Plums 0 0.0 Total 9,929 100.0 Cont…. Production of Permanent Crops by Crop Type and District - Tabora Region Tabora Urban Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 170 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Hh with Banana Average Planted Area per Household District Area Planted with Palm Oil Total Area Planted (Ha) % of Total Area Planted Hh with Palm Oil Average Planted Area per Household Urambo 1,618 120,683 1.3 3,953 0.4 Urambo 1,858 120,683 1.5 2,983 0.0 Tabora Urban 788 18,539 4.2 416 1.9 Uyui 291 110,751 0.3 419 0.0 Nzega 649 142,830 0.5 2,490 0.3 Tabora Urban 10 18,539 0.1 24 0.0 Uyui 432 110,751 0.4 1,221 0.4 Nzega 0 142,830 0.0 0 0.0 Igunga 268 96,939 0.3 669 0.4 Igunga 0 96,939 0.0 0 0.0 Sikonge 53 52,801 0.1 590 0.1 Sikonge 0 52,801 0.0 0 0.0 Total 3,807 542,544 0.7 9,338 0.4 Total 2,158 542,544 0.4 3,425 0.0 District Area Planted with Banana Oil Total Area Planted (Ha) % of Total Area Planted Hh with Banana Oil Average Planted Area per Household District Area Planted with Pawpaw Total Area Planted (Ha) % of Total Area Planted Hh with Pawpaw Average Planted Area per Household Urambo 1,362 120,683 1.1 3,767 0.4 Urambo 516 120,683 0.43 1,517 0.34 Nzega 92 142,830 0.1 601 0.2 Nzega 84 142,830 0.06 275 0.30 Uyui 70 110,751 0.1 404 0.2 Igunga 40 96,939 0.04 448 0.09 Tabora Urban 56 18,539 0.3 239 0.2 Uyui 26 110,751 0.02 400 0.06 Sikonge 19 52,801 0.0 47 0.4 Tabora Urban 4 18,539 0.02 105 0.04 Igunga 0 96,939 0.0 0 0.0 Sikonge 0 52,801 0.00 0 0.00 Total 1,600 542,544 0.3 5,058 0.3 Total 670 542,544 0.12 2,745 0.24 BANANA PAWPAW 7.3.3 Total Area Planted with Mango by District - Tabora Region 7.3.6 Total Area Planted with Pawpaw by District - Tabora Region 7.3.4 Total Area Planted with Palm Oil by District - Tabora Region 7.3.5 Total Area Planted with Banana by District - Tabora Region MANGO PALM OIL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 171 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Pigeon Pea 0 0 0 39 39 Malay Apple 0 0 0 29 29 Palm Oil 1,282 84 0 782 2,148 Coconut 51 0 0 2 53 Sugarcane 53 8 13 230 303 Tamarin 0 0 0 5 5 Jack Fruit 7 0 0 0 7 Banana 911 157 0 531 1,600 Avocado 0 0 0 1 1 Mango 998 170 1 2,638 3,807 Pawpaw 479 56 0 110 645 Orange 72 176 43 149 440 Mandarine/Tangerine 51 0 0 0 51 Guava 12 56 0 588 656 Plums 0 0 0 0 0 Lime/Lemon 51 57 0 2 110 Total 3,968 764 57 5,106 9,895 Crop Mostly Farm Yard Manure Total % Jack Fruit 7 7 100.0 Mandarine/Tangerine 51 51 100.0 Coconut 51 53 96.0 Pawpaw 479 645 74.3 Palm Oil 1,282 2,148 59.7 Banana 911 1,600 57.0 Lime/Lemon 51 110 46.5 Mango 998 3,807 26.2 Sugarcane 53 303 17.4 Orange 72 440 16.3 Guava 12 656 1.9 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Tamarin 0 5 0.0 Avocado 0 1 0.0 Plums 0 0 0.0 Total 3,968 9,895 40.1 7.3.7 Planted Area with Fertiliser by Fertiliser Type and Crop - Tabora Region Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Fertilizer Use Crop Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 172 Crops Mostly Inorganic Fertilizer Total % Orange 43 440 9.9 Sugarcane 13 303 4.1 Mango 1 3,807 0.0 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Palm Oil 0 2,148 0.0 Coconut 0 53 0.0 Tamarin 0 5 0.0 Jack Fruit 0 7 0.0 Banana 0 1,600 0.0 Avocado 0 1 0.0 Pawpaw 0 645 0.0 Mandarine/Tangerine 0 51 0.0 Guava 0 656 0.0 Plums 0 0 0.0 Lime/Lemon 0 110 0.0 Total 57 9,895 0.6 Crops Mostly Compost Total % Lime/Lemon 57 110 51.6 Orange 176 440 40.1 Banana 157 1,600 9.8 Pawpaw 56 645 8.6 Guava 56 656 8.5 Mango 170 3,807 4.5 Palm Oil 84 2,148 3.9 Sugarcane 8 303 2.5 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Coconut 0 53 0.0 Tamarin 0 5 0.0 Jack Fruit 0 7 0.0 Avocado 0 1 0.0 Mandarine/Tangerine 0 51 0.0 Plums 0 0 0.0 Total 764 9,895 7.7 Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 173 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 174 Number % Number % Number % Nzega 63,856 97 1,710 3 65,566 100 Igunga 39,049 87 6,093 13 45,141 100 Uyui 39,991 97 1,326 3 41,318 100 Urambo 51,694 96 2,426 4 54,120 100 Sikonge 19,273 99 241 1 19,514 100 Tabora Urban 10,032 98 226 2 10,258 100 Total 223,896 95 12,021 5 235,917 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Others By Factory Total Nzega 6,670 4,605 52,292 138 150 0 0 63,856 Igunga 2,858 215 35,432 0 432 0 110 39,049 Uyui 3,951 1,210 34,831 0 0 0 0 39,991 Urambo 4,805 1,996 44,893 0 0 0 0 51,694 Sikonge 2,817 835 15,474 147 0 0 0 19,273 Tabora Urban 526 169 9,231 26 27 54 0 10,032 Total 21,628 9,031 192,153 311 609 54 110 223,896 % 9.66 4.03 85.82 0.14 0.27 0.02 0.05 100.00 Crops On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 14,399 9,146 9,146 311 495 0 54 0 33,552 Paddy 25,839 1,549 49,294 26 0 0 0 0 76,708 Sorghum 585 617 20,577 0 0 0 0 0 21,779 Bulrush Millet 0 50 313 0 0 0 0 0 363 Finger Millet 0 123 364 0 0 0 0 0 486 Cassava 4,167 224 10,599 0 0 150 50 0 15,190 Sweet Potatoes 270 0 0 0 0 0 0 0 270 Beans 427 0 50 0 0 0 0 0 477 Cowpeas 594 0 0 0 0 0 0 0 594 Chick Peas 112 0 0 0 0 0 0 0 112 Green Gram 0 0 98 0 0 0 0 0 98 Bambaranut 987 150 0 0 150 0 0 1,288 Groundnut 100,253 599 3,492 126 717 0 616 0 105,802 Sunflower 0 49 101 0 0 0 0 110 260 Simsim 49 0 0 0 0 0 0 0 49 Tobacco 0 0 0 0 0 0 0 27 27 Pawpaw 102 0 0 0 0 0 0 0 102 Orange 102 0 0 0 0 0 0 0 102 Oil Palm 1,682 0 230 0 0 0 0 0 1,912 8.0a: AGROPROCESSING: Number of Crops Growing Households Reported to have Processed Farm Products by District; 2002/03 Agriculture Year District Households That Processed Product Households That Did Not Process Product Total 8.0b AGRO PROCESSING: Number of Crop Growing Households by Method Processing and District; 2002/03 Agriculture Yearof Farm Products Produced During 2002/03 Agriculture Year District Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agriculture Year by Location and Crop, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 175 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Other Total Maize 211,896 54 50 1,141 268 0 213,408 Paddy 74,695 121 685 471 498 237 76,708 Sorghum 21,779 0 0 0 0 0 21,779 Bulrush Millet 363 0 0 0 0 0 363 Finger Millet 486 0 0 0 0 0 486 Cassava 14,940 0 249 0 0 0 15,190 Sweet Potatoes 270 0 0 0 0 0 270 Beans 477 0 0 0 0 0 477 Cowpeas 594 0 0 0 0 0 594 Green Gram 98 0 0 0 0 0 98 Chick Peas 112 0 0 0 0 0 112 Bambaranut 987 0 300 0 0 0 1,288 Sunflower 211 0 49 0 0 0 260 Simsim 49 0 0 0 0 0 49 Groundnut 104,419 161 671 0 525 27 105,802 Oil Palm 1,794 0 118 0 0 0 1,912 Tobacco 0 0 27 0 0 0 27 Pawpaw 102 0 0 0 0 0 102 Orange 102 0 0 0 0 0 102 Total 433,375 336 2,149 1,613 1,291 263 439,027 Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 2,455 744 99 231 114 173 1,245 4,544 203,803 213,408 Paddy 2,200 1,329 126 27 0 250 1,475 1,684 69,617 76,708 Sorghum 232 114 0 0 0 0 0 1,175 20,259 21,779 Bulrush Millet 0 0 0 0 0 0 0 0 363 363 Finger Millet 0 0 0 0 0 0 0 0 486 486 Cassava 27 401 0 0 0 0 125 198 14,439 15,190 Sweet Potatoes 0 0 0 0 0 0 0 0 270 270 Beans 0 0 0 0 0 0 0 0 477 477 Cowpeas 0 0 0 0 0 0 0 0 594 594 Green Gram 0 0 0 0 0 0 0 0 98 98 Chick Peas 0 0 0 0 0 0 0 0 112 112 Bambaranut 0 0 0 0 0 0 0 0 1,288 1,288 Sunflower 49 0 0 0 0 0 0 0 211 260 Simsim 0 0 0 0 0 0 0 0 49 49 Groundnut 945 641 0 228 0 0 539 2,945 100,504 105,802 Oil Palm 469 0 0 0 0 0 0 0 1,443 1,912 Tobacco 0 0 0 0 27 0 0 0 0 27 Pawpaw 0 0 0 0 0 0 102 0 0 102 Orange 0 0 0 0 0 0 102 0 0 102 Total 6,375 3,229 225 485 141 423 3,588 10,547 414,013 439,027 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop, Tabora Region 8.1.c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop, Tabora Region Product Use Crop Where Sold Crops Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 176 Flour / Meal Grain Oil Juice Pulp Rubber Total Nzega 56,063 7,210 147 149 286 0 63,856 Igunga 35,784 2,256 110 0 789 110 39,049 Uyui 36,402 3,189 97 0 303 0 39,991 Urambo 46,450 4,260 621 126 115 121 51,694 Sikonge 17,045 1,550 147 0 532 0 19,273 Tabora Urban 9,421 505 27 0 54 27 10,032 Total 201,164 18,970 1,148 276 2,079 258 223,896 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Total Nzega 62,988 0 300 300 268 63,856 Igunga 38,401 0 230 418 0 39,049 Uyui 39,889 0 0 102 0 39,991 Urambo 51,449 0 0 245 0 51,694 Sikonge 19,126 0 98 49 0 19,273 Tabora Urban 9,952 54 0 27 0 10,032 Total 221,805 54 628 1,141 268 223,896 Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Nzega 451 899 0 0 0 0 748 0 61,758 63,856 Igunga 688 116 0 0 114 0 232 1,837 36,062 39,049 Uyui 106 0 0 204 0 0 0 794 38,888 39,991 Urambo 1,273 126 0 0 0 124 0 0 50,171 51,694 Sikonge 340 0 99 0 0 49 0 2,322 16,463 19,273 Tabora Urban 317 54 0 27 0 0 13 24 9,598 10,032 Total 3,175 1,194 99 231 114 173 993 4,976 212,941 223,896 Bran Cake Husk Juice Pulp Oil Shell No by-product Other Total Nzega 49,205 0 7,851 0 294 147 0 6,360 0 63,856 Igunga 5,718 110 4,178 0 570 0 229 28,244 0 39,049 Uyui 18,887 106 7,022 0 499 0 0 13,380 97 39,991 Urambo 33,547 464 3,040 123 0 118 334 14,069 0 51,694 Sikonge 11,583 343 978 0 97 0 243 6,029 0 19,273 Tabora Urban 7,697 0 931 0 24 0 27 1,354 0 10,032 Total 126,638 1,023 23,999 123 1,483 265 832 69,436 97 223,896 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year - Tabora Region District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Tanga Region District Product Use 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year - Tabora Region District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Type of By-Product and District During 2002/03 Agriculture Year, Tabora Region District By Product Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 177 MARKETING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 178 Number % Number % Nzega 27,633 42 37,933 58 65,566 Igunga 21,622 48 23,519 52 45,141 Uyui 21,884 53 19,434 47 41,318 Urambo 43,449 80 10,671 20 54,120 Sikonge 12,147 62 7,367 38 19,514 Tabora Urban 4,669 46 5,589 54 10,258 Total 131,403 56 104,514 44 235,917 Open Market Price Too Low No Transport Transport Cost Too High No Buyer Market too Far Farmers Association Problems Co- operative Problems Government Regulatory Board Problems Lack of Market Information Other Not applicable Total Nzega 10,860 1,332 741 0 1,030 0 0 0 0 0 13,670 27,633 Igunga 2,859 116 0 0 444 116 114 0 319 0 17,655 21,622 Uyui 6,769 512 410 100 1,136 0 0 0 102 0 12,854 21,884 Urambo 15,504 1,481 980 458 2,252 0 0 124 248 121 22,282 43,449 Sikonge 4,849 344 244 49 494 50 0 0 96 0 6,022 12,147 Tabora Urban 596 40 40 27 210 0 0 25 0 0 3,730 4,669 Total 41,437 3,825 2,415 634 5,565 165 114 149 764 121 76,214 131,403 District Open Market Price Too Low No Transport Transport Cost Too High No Buyer Market too Far Farmers Association Problems Co- operative Problems Government Regulatory Board Problems Lack of Market Information Other Not applicable Total Nzega 39.30 4.82 2.68 0.00 3.73 0.00 0.00 0.00 0.00 0.00 49.47 100.00 Igunga 13.22 0.54 0.00 0.00 2.05 0.54 0.53 0.00 1.47 0.00 81.65 100.00 Uyui 30.93 2.34 1.88 0.46 5.19 0.00 0.00 0.00 0.47 0.00 58.74 100.00 Urambo 35.68 3.41 2.25 1.05 5.18 0.00 0.00 0.29 0.57 0.28 51.28 100.00 Sikonge 39.92 2.83 2.01 0.41 4.06 0.41 0.00 0.00 0.79 0.00 49.58 100.00 Tabora Urban 12.77 0.86 0.85 0.57 4.50 0.00 0.00 0.54 0.00 0.00 79.89 100.00 Total 31.53 2.91 1.84 0.48 4.24 0.13 0.09 0.11 0.58 0.09 58.00 100.00 District Households that Sold Households that Did not Sell 10.1 MARETING: Number of Crop Growing Households Reported to have Sold Agricultural Produce by District During 2003/04 Agriculture Year, Tabora Region Total Number of Household 10.3 Proportion of Households who Reported Main Reason for Not Selling their Crops by District During 2002/03 Agriculture Year 10.2 MARKETING: Number of Households who Reported Main Reason for Not Selling their Crops by District during 2002/03 Agriculture Year, Tabora Region District Main Problem Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 179 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 180 Total Number of Households Number of Households % Number of Households % Number Nzega 2,938 4 62,628 96 65,566 Igunga 3,350 7 41,791 93 45,141 Uyui 3,310 8 38,008 92 41,318 Urambo 4,701 9 49,419 91 54,120 Sikonge 1,479 8 18,034 92 19,514 Tabora Urban 1,403 14 8,855 86 10,258 Total 17,181 7 218,736 93 235,917 District Irrigatable Area (ha) Irrigated Land (ha) % Nzega 1,641 1,241 76 Igunga 2,865 2,782 97 Uyui 1,977 1,709 86 Urambo 1,607 810 50 Sikonge 740 531 72 Tabora Urban 541 408 75 Total 9,371 7,480 80 River Dam Well Borehole Canal Total Nzega 0 1,798 570 0 571 2,938 Igunga 966 2,037 346 0 0 3,350 Uyui 106 2,607 597 0 0 3,310 Urambo 0 125 3,971 605 0 4,701 Sikonge 97 93 979 50 261 1,479 Tabora Urban 27 758 591 0 27 1,403 Total 1,196 7,418 7,054 654 859 17,181 Gravity Hand Bucket Hand Pump Motor Pump Other Total Nzega 1,622 1,316 0 0 0 2,938 Igunga 2,445 904 0 0 0 3,350 Uyui 407 2,797 0 0 105 3,310 Urambo 125 4,576 0 0 0 4,701 Sikonge 309 1,171 0 0 0 1,479 Tabora Urban 79 1,063 46 26 188 1,403 Total 4,987 11,828 46 26 293 17,181 11.4 IRRIGATION: Number of Agriculture Households by Method Used to obtain Water and District During 2002/03 Agriculture Year District Method of Obtaining Water 11.2 IRRIGATION: Area (ha) of Irrigatable and NON Irrigated Land by District During 2002/03 Agriculture Year 11.3 IRRIGATION: Number of Agriculture Households Using Irrigation By Source of Irrigation Water by District During the 2003/04 Agricultural Year District Source of Irrigation Water District Household Practicing Irrigation Household Not Practicing Irrigation 11.1 IRRIGATION: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year by District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 181 Flood Sprinkler Water Hose Bucket / Watering Can Total Nzega 1,622 0 0 1,316 2,938 Igunga 2,775 114 0 461 3,350 Uyui 618 0 0 2,692 3,310 Urambo 378 0 0 4,323 4,701 Sikonge 507 195 0 778 1,479 Tabora Urban 27 25 99 1,252 1,403 Total 5,926 334 99 10,821 17,181 Total Number of Household Number % Number % Number Nzega 1,041 2 64,525 98 65,566 Igunga 115 0 45,026 100 45,141 Uyui 2,209 5 39,109 95 41,318 Urambo 965 2 53,155 98 54,120 Sikonge 343 2 19,171 98 19,514 Tabora Urban 727 7 9,531 93 10,258 Total 5,399 2 230,518 98 235,917 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Nzega 0 3,857 0 0 0 0 281 901 5,039 Igunga 0 230 0 0 0 0 0 0 230 Uyui 0 619 317 0 3,058 1,372 204 3,679 9,248 Urambo 0 7,034 0 385 193 0 0 0 7,612 Sikonge 99 1,501 0 0 446 1,239 0 0 3,286 Tabora Urban 455 1,068 0 0 520 646 487 26 3,202 Total 554 14,309 317 385 4,217 3,258 971 4,606 28,616 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District as of 2002/03 Agriculture Year District Type of Erosion Control District Method of Field Application District Have facility Does Not Have Facility Presence of Erosion Control/Water Harvesting Facilities 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Tabora 182 Appendix II 183 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 184 No. of Households % No. of Households % Nzega 2,887 4 62,679 96 65,566 Igunga 1,206 3 43,935 97 45,141 Uyui 11,025 27 30,293 73 41,318 Urambo 21,354 39 32,766 61 54,120 Sikonge 6,773 35 12,741 65 19,514 Tabora Urban 3,042 30 7,216 70 10,258 Total 46,287 20 189,630 80 235,917 No. of Households % No. of Households % Nzega 29,333 45 36,233 55 65,566 Igunga 12,244 27 32,897 73 45,141 Uyui 8,020 19 33,297 81 41,318 Urambo 8,576 16 45,545 84 54,120 Sikonge 4,202 22 15,312 78 19,514 Tabora Urban 2,903 28 7,355 72 10,258 Total 65,279 28 170,638 72 235,917 No. of Households % No. of Households % Nzega 6,580 10 58,986 90 65,566 Igunga 459 1 44,682 99 45,141 Uyui 2,973 7 38,345 93 41,318 Urambo 4,696 9 49,425 91 54,120 Sikonge 295 2 19,219 98 19,514 Tabora Urb 365 4 9,893 96 10,258 Total 15,368 7 220,549 93 235,917 No. of Households % No. of Households % Nzega 4,294 7 61,272 93 65,566 Igunga 6,162 14 38,979 86 45,141 Uyui 11,823 29 29,494 71 41,318 Urambo 16,130 30 37,990 70 54,120 Sikonge 6,095 31 13,419 69 19,514 Tabora Urban 3,355 33 6,903 67 10,258 Total 47,859 20 188,057 80 235,917 District Using Insecticide/Fungicides NOT Using Insecticide/Fungicides Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Insecticide/Fungicides by District, 2002/03 Agricultural Year Total District Using Compost Not Using Compost Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Total District Using Farm Yard Manure NOT Using Farm Yard Manure Total Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year Total Number of Crop Growing Households Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Using Chemical Fertilizers NOT Using Chemical Fertilizers Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 185 No. of Households % No. of Households % Nzega 149 0 65,417 100 65,566 Igunga 345 1 44,797 99 45,141 Uyui 306 1 41,012 99 41,318 Urambo 973 2 53,148 98 54,120 Sikonge 248 1 19,266 99 19,514 Tabora Urban 37 0 10,221 100 10,258 Total 2,056 1 233,861 99 235,917 No. of Households % No. of Households % Nzega 5,774 9 59,792 91 65,566 Igunga 10,971 24 34,170 76 45,141 Uyui 6,679 16 34,639 84 41,318 Urambo 16,300 30 37,820 70 54,120 Sikonge 3,730 19 15,784 81 19,514 Tabora Urban 2,253 22 8,005 78 10,258 Total 45,706 19 190,210 81 235,917 District Using Improved Seeds NOT Using Improved Seeds Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Total District Using Herbicides NOT Using Herbicides Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 186 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 0 0 543 1 1,922 3 0 0 0 0 272 0 0 0 0 0 150 0 62,679 96 65,566 Igunga 106 0 0 0 1,100 2 0 0 0 0 0 0 0 0 0 0 0 0 43,935 97 45,141 Uyui 7,630 18 211 1 2,977 7 0 0 0 0 0 0 0 0 102 0 106 0 30,293 73 41,318 Urambo 14,360 27 1,099 2 5,661 10 109 0 0 0 0 0 0 0 0 0 126 0 32,766 61 54,120 Sikonge 4,288 22 343 2 1,205 6 0 0 49 0 149 1 0 0 0 0 739 4 12,741 65 19,514 Tabora Urban 134 1 99 1 2,732 27 0 0 0 0 0 0 26 0 26 0 25 0 7,216 70 10,258 Total 26,518 11 2,296 1 15,595 7 109 0 49 0 420 0 26 0 128 0 1,146 0 189,630 80 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 150 0 149 0 150 0 0 0 0 0 0 0 23,679 36 5,055 8 150 0 36,233 55 65,566 Igunga 0 0 114 0 204 0 0 0 114 0 109 0 6,932 15 4,772 11 0 0 32,897 73 45,141 Uyui 0 0 0 0 106 0 196 0 98 0 0 0 5,797 14 1,718 4 106 0 33,297 81 41,318 Urambo 0 0 0 0 126 0 0 0 124 0 0 0 4,916 9 1,966 4 1,443 3 45,545 84 54,120 Sikonge 98 1 0 0 0 0 0 0 0 0 740 4 2,727 14 587 3 50 0 15,312 78 19,514 Tabora Urban 53 1 0 0 53 1 27 0 27 0 0 0 1,438 14 1,281 12 24 0 7,355 72 10,258 Total 302 0 262 0 639 0 223 0 362 0 849 0 45,489 19 15,380 7 1,772 1 170,638 72 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 149 0 149 0 0 0 0 0 0 0 0 0 5,989 9 294 0 58,986 90 65,566 Igunga 0 0 0 0 0 0 0 0 116 0 0 0 344 1 0 0 44,682 99 45,141 Uyui 1,354 3 98 0 104 0 98 0 0 0 0 0 1,221 3 98 0 38,345 93 41,318 Urambo 0 0 124 0 0 0 0 0 236 0 0 0 4,335 8 0 0 49,425 91 54,120 Sikonge 0 0 0 0 0 0 0 0 0 0 99 1 196 1 0 0 19,219 98 19,514 Tabora Urban 0 0 0 0 0 0 27 0 0 0 0 0 292 3 46 0 9,893 96 10,258 Total 1,503 1 371 0 104 0 125 0 352 0 99 0 12,377 5 438 0 220,549 93 235,917 Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Development Project Crop Buyers Large Scale Farm Neighbour Other Not applicable Total Development Project Crop Buyers Large Scale Farm Locally Produced by Household District Co-operative Local Farmers Group Local Market / Trade Store Neighbour Not applicable Total Locally Produced by Household Neighbour Not applicable Total Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households by Source of COMPOST Manure by District, 2002/03 Agricultural Year District Co-operative Crop Buyers Large Scale Farm Locally Produced by Household Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 187 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 124 0 543 1 3,055 5 150 0 150 0 272 0 0 0 0 0 0 0 61,272 93 65,566 Igunga 3,992 9 115 0 1,825 4 114 0 0 0 0 0 0 0 0 0 116 0 38,979 86 45,141 Uyui 7,418 18 211 1 3,383 8 193 0 0 0 197 0 0 0 105 0 317 1 29,494 71 41,318 Urambo 11,340 21 730 1 3,187 6 124 0 0 0 124 0 0 0 126 0 499 1 37,990 70 54,120 Sikonge 3,361 17 294 2 1,369 7 50 0 49 0 246 1 0 0 47 0 678 3 13,419 69 19,514 Tabora Urban 161 2 99 1 2,939 29 26 0 0 0 53 1 26 0 51 0 0 0 6,903 67 10,258 Total 26,395 11 1,993 1 15,758 7 657 0 200 0 891 0 26 0 330 0 1,610 1 188,057 80 235,917 Number % Number % Number % Number % Number % Number % Number % Nzega 0 0 0 0 149 0 0 0 0 0 0 0 65,417 100 65,566 Igunga 0 0 0 0 345 1 0 0 0 0 0 0 44,797 99 45,141 Uyui 0 0 105 0 102 0 98 0 0 0 0 0 41,012 99 41,318 Urambo 864 2 0 0 0 0 0 0 109 0 0 0 53,148 98 54,120 Sikonge 149 1 50 0 50 0 0 0 0 0 0 0 19,266 99 19,514 Tabora Urban 0 0 0 0 17 0 0 0 0 0 20 0 10,221 100 10,258 Total 1,013 0 155 0 662 0 98 0 109 0 20 0 233,861 99 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 124 0 282 0 4,374 7 0 0 721 1 136 0 0 0 138 0 0 0 59,792 91 65,566 Igunga 8,632 19 223 0 1,086 2 116 0 0 0 340 1 115 0 459 1 0 0 34,170 76 45,141 Uyui 4,072 10 628 2 1,662 4 0 0 0 0 317 1 0 0 0 0 0 0 34,639 84 41,318 Urambo 10,622 20 855 2 2,845 5 118 0 0 0 233 0 1,385 3 241 0 0 0 37,820 70 54,120 Sikonge 1,694 9 245 1 1,354 7 49 0 49 0 50 0 0 0 289 1 0 0 15,784 81 19,514 Tabora Urban 54 1 119 1 1,935 19 0 0 0 0 67 1 0 0 51 0 27 0 8,005 78 10,258 Total 25,198 11 2,352 1 13,256 6 282 0 771 0 1,142 0 1,500 1 1,179 0 27 0 190,210 81 235,917 Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Other Not applicable Total District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Locally Produced by Household Neighbour Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households by Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Development Project Locally Produced by Household Neighbour Not applicable Neighbour Not applicable Large Scale Farm Locally Produced by Household Total Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 188 Number % Number % Number % Number % Number % Nzega 996 34 150 5 858 30 737 26 146 5 2,887 Igunga 110 9 106 9 459 38 114 9 416 35 1,206 Uyui 2,207 20 3,444 31 1,872 17 936 8 2,566 23 11,025 Urambo 7,982 37 4,899 23 4,477 21 2,843 13 1,154 5 21,354 Sikonge 2,601 38 1,018 15 1,505 22 1,066 16 582 9 6,773 Tabora Urban 211 7 87 3 953 31 1,582 52 209 7 3,042 Total 14,107 30 9,704 21 10,124 22 7,279 16 5,073 11 46,287 Number % Number % Number % Number % Number % Nzega 29,183 99 0 0 0 0 0 0 150 1 29,333 Igunga 11,361 93 666 5 217 2 0 0 0 0 12,244 Uyui 7,630 95 292 4 0 0 0 0 98 1 8,020 Urambo 8,223 96 227 3 0 0 126 1 0 0 8,576 Sikonge 3,907 93 295 7 0 0 0 0 0 0 4,202 Tabora Urban 2,347 81 424 15 53 2 53 2 27 1 2,903 Total 62,650 96 1,904 3 270 0 179 0 275 0 65,279 District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Number Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 189 Number % Number % Number % Number % Nzega 6,580 100 0 0 0 0 0 0 6,580 Igunga 459 100 0 0 0 0 0 0 459 Uyui 2,973 100 0 0 0 0 0 0 2,973 Urambo 4,076 87 0 0 115 2 505 11 4,696 Sikonge 295 100 0 0 0 0 0 0 295 Tabora Urban 312 86 26 7 0 0 26 7 365 Total 14,696 96 26 0 115 1 531 3 15,368 Number % Number % Number % Number % Number % Nzega 1,230 21 0 0 1,337 23 2,324 40 883 15 5,774 Igunga 4,438 40 3,515 32 2,162 20 440 4 417 4 10,971 Uyui 1,790 27 2,088 31 933 14 205 3 1,663 25 6,679 Urambo 6,260 38 3,318 20 3,594 22 2,225 14 903 6 16,300 Sikonge 1,167 31 531 14 858 23 780 21 394 11 3,730 Tabora Urban 184 8 156 7 676 30 1,102 49 133 6 2,253 Total 15,069 33 9,608 21 9,560 21 7,077 15 4,393 10 45,706 Number % Number % Number % Number % Number % Nzega 1,080 25 0 0 1,158 27 860 20 1,197 28 4,294 Igunga 1,476 24 1,712 28 2,407 39 115 2 452 7 6,162 Uyui 2,815 24 3,230 27 2,167 18 830 7 2,781 24 11,823 Urambo 5,496 34 4,062 25 3,110 19 2,632 16 830 5 16,130 Sikonge 2,003 33 928 15 1,210 20 782 13 1,171 19 6,095 Tabora Urban 157 5 149 4 1,052 31 1,851 55 146 4 3,355 Total 13,028 27 10,081 21 11,103 23 7,071 15 6,576 14 47,859 Between 10 and 20 km 20 km and Above Total Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 20 km and Above Total Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Between 10 and 20 km Total Number Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 190 Number % Number % Number % Number % Number % Number % Number % Nzega 8,849 14 51,521 82 0 0 281 0 2,029 3 0 0 0 0 62,679 Igunga 20,332 46 17,655 40 693 2 904 2 4,124 9 0 0 228 1 43,935 Uyui 3,591 12 24,391 81 413 1 502 2 1,197 4 0 0 200 1 30,293 Urambo 3,420 10 27,367 84 107 0 373 1 1,373 4 125 0 0 0 32,766 Sikonge 2,160 17 10,062 79 95 1 0 0 331 3 0 0 93 1 12,741 Tabora Urban 0 0 7,032 97 27 0 39 1 92 1 0 0 25 0 7,216 Total 38,352 20 138,027 73 1,335 1 2,099 1 9,147 5 125 0 546 0 189,630 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 19,964 55 10,334 29 4,529 12 0 0 119 0 863 2 0 0 424 1 36,233 Igunga 6,114 19 3,019 9 13,396 41 1,258 4 4,364 13 2,940 9 108 0 1,697 5 32,897 Uyui 19,353 58 4,170 13 4,460 13 2,493 7 920 3 1,020 3 0 0 880 3 33,297 Urambo 27,577 61 4,877 11 8,877 19 1,655 4 1,571 3 626 1 123 0 240 1 45,545 Sikonge 10,394 68 2,291 15 1,709 11 343 2 246 2 230 2 50 0 50 0 15,312 Tabora Urban 4,515 61 806 11 1,823 25 67 1 66 1 53 1 0 0 25 0 7,355 Total 87,917 52 25,497 15 34,794 20 5,817 3 7,285 4 5,733 3 280 0 3,315 2 170,638 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,806 10 10,547 18 19,735 33 1,175 2 20,097 34 425 1 0 0 1,201 2 58,986 Igunga 2,453 5 2,780 6 14,008 31 1,250 3 21,375 48 2,602 6 108 0 106 0 44,682 Uyui 4,616 12 3,056 8 10,766 28 1,796 5 17,184 45 927 2 0 0 0 0 38,345 Urambo 6,290 13 3,903 8 26,931 54 1,842 4 8,886 18 876 2 698 1 0 0 49,425 Sikonge 2,522 13 1,706 9 9,826 51 756 4 3,980 21 330 2 0 0 99 1 19,219 Tabora Urban 239 2 794 8 7,428 75 61 1 1,174 12 120 1 0 0 77 1 9,893 Total 21,926 10 22,785 10 88,694 40 6,879 3 72,696 33 5,279 2 806 0 1,484 1 220,549 Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, Other Total Total Total District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other District Not Available Price Too High No Money to Buy Do not Know How to Use Input is of No Use Locally Produced by Household Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 191 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,930 10 51,565 84 150 0 0 0 2,906 5 571 1 0 0 150 0 61,272 Igunga 8,462 22 24,258 62 793 2 0 0 4,797 12 668 2 0 0 0 0 38,979 Uyui 6,070 21 21,185 72 707 2 104 0 804 3 414 1 106 0 105 0 29,494 Urambo 11,099 29 23,289 61 1,081 3 0 0 1,187 3 1,123 3 96 0 115 0 37,990 Sikonge 2,762 21 9,300 69 444 3 198 1 479 4 140 1 0 0 96 1 13,419 Tabora Urban 53 1 6,379 92 188 3 0 0 125 2 80 1 0 0 79 1 6,903 Total 34,376 18 135,975 72 3,362 2 302 0 10,299 5 2,996 2 202 0 545 0 188,057 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,296 8 50,658 77 451 1 0 0 6,072 9 2,817 4 0 0 124 0 65,417 Igunga 10,186 23 21,012 47 1,599 4 0 0 9,289 21 2,711 6 0 0 0 0 44,797 Uyui 7,631 19 20,425 50 918 2 104 0 8,693 21 3,137 8 106 0 0 0 41,012 Urambo 20,861 39 20,973 39 1,170 2 0 0 6,392 12 3,424 6 109 0 219 0 53,148 Sikonge 4,536 24 10,665 55 591 3 149 1 2,416 13 810 4 0 0 99 1 19,266 Tabora Urban 256 3 2,819 28 262 3 0 0 6,778 66 81 1 0 0 25 0 10,221 Total 48,765 21 126,552 54 4,991 2 253 0 39,639 17 12,979 6 214 0 468 0 233,861 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 13,186 22 45,270 76 150 0 0 0 140 0 744 1 0 0 300 1 59,792 Igunga 13,850 41 17,577 51 461 1 0 0 1,951 6 217 1 0 0 114 0 34,170 Uyui 11,091 32 21,699 63 821 2 0 0 403 1 626 2 0 0 0 0 34,639 Urambo 15,048 40 21,575 57 825 2 0 0 373 1 0 0 0 0 0 0 37,820 Sikonge 4,616 29 9,542 60 198 1 149 1 99 1 146 1 985 6 50 0 15,784 Tabora Urban 26 0 7,510 94 206 3 0 0 65 1 146 2 0 0 52 1 8,005 Total 57,818 30 123,173 65 2,661 1 149 0 3,030 2 1,879 1 985 1 516 0 190,210 Input is of No Use Locally Produced by Household Price Too High No Money to Buy Other Total Total Total Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Too Much Labour Required Do not Know How to Use Locally Produced by Household Other District Not Available Other District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 192 Number % Number % Number % Number % Number % Nzega 1,033 36 1,568 54 286 10 0 0 0 0 2,887 Igunga 686 57 519 43 0 0 0 0 0 0 1,206 Uyui 3,882 35 6,104 55 724 7 315 3 0 0 11,025 Urambo 10,928 51 8,556 40 1,495 7 376 2 0 0 21,354 Sikonge 2,376 35 4,052 60 345 5 0 0 0 0 6,773 Tabora Urban 578 19 2,013 66 290 10 134 4 27 1 3,042 Total 19,484 42 22,812 49 3,140 7 825 2 27 0 46,287 Number % Number % Number % Number % Nzega 15,446 53 12,461 42 1,426 5 0 0 29,333 Igunga 4,681 38 6,553 54 1,010 8 0 0 12,244 Uyui 2,571 32 4,354 54 994 12 102 1 8,020 Urambo 5,193 61 2,846 33 537 6 0 0 8,576 Sikonge 1,814 43 2,294 55 94 2 0 0 4,202 Tabora Urban 692 24 1,973 68 238 8 0 0 2,903 Total 30,398 47 30,480 47 4,299 7 102 0 65,279 Number % Number % Number % Number % Nzega 1,285 20 4,999 76 296 5 0 0 6,580 Igunga 0 0 230 50 230 50 0 0 459 Uyui 1,459 49 1,221 41 294 10 0 0 2,973 Urambo 602 13 2,240 48 1,853 39 0 0 4,696 Sikonge 48 16 198 67 50 17 0 0 295 Tabora Urban 73 20 239 66 26 7 27 7 365 Total 3,466 23 9,127 59 2,748 18 27 0 15,368 District Excellent Excellent Good Total Total Good Average Poor Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Average Poor Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Total District Excellent Good Average Poor Does not Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 193 Number % Number % Number % Number % Number % Nzega 1,126 26 2,901 68 124 3 144 3 0 0 4,294 Igunga 1,266 21 4,450 72 224 4 222 4 0 0 6,162 Uyui 5,110 43 6,510 55 203 2 0 0 0 0 11,823 Urambo 6,837 42 8,421 52 747 5 125 1 0 0 16,130 Sikonge 2,093 34 3,668 60 241 4 43 1 50 1 6,095 Tabora Urban 732 22 2,396 71 200 6 27 1 0 0 3,355 Total 17,163 36 28,345 59 1,739 4 562 1 50 0 47,859 Number % Number % Number % Nzega 0 0 149 100 0 0 149 Igunga 115 33 230 67 0 0 345 Uyui 0 0 306 100 0 0 306 Urambo 505 52 468 48 0 0 973 Sikonge 149 60 50 20 50 20 248 Tabora Urban 0 0 37 100 0 0 37 Total 769 37 1,238 60 50 2 2,056 Number % Number % Number % Number % Number % Number % Number % Nzega 2,724 47 2,613 45 438 8 0 0 0 0 5,774 Nzega 14,192 22 51,374 78 65,566 Igunga 3,652 33 5,522 50 1,569 14 114 1 114 1 10,971 Igunga 4,918 11 40,224 89 45,141 Uyui 2,527 38 4,152 62 0 0 0 0 0 0 6,679 Uyui 15,651 38 25,667 62 41,318 Urambo 8,976 55 6,973 43 227 1 124 1 0 0 16,300 Urambo 32,925 61 21,195 39 54,120 Sikonge 1,165 31 2,370 64 195 5 0 0 0 0 3,730 Sikonge 9,732 50 9,782 50 19,514 Tabora Urban 560 25 1,494 66 172 8 27 1 0 0 2,253 Tabora Urban 3,825 37 6,433 63 10,258 Total 19,603 43 23,123 51 2,601 6 265 1 114 0 45,706 Total 81,242 34 154,675 66 235,917 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Agricultural Households With NO Plan to use Next Year District Total Poor Does not Work Total Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Good Average Poor Average Total District Excellent Good Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 District Excellent Does not Total Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 194 Number % Number % Number % Number % Nzega 47,418 72 18,148 28 65,566 Nzega 20,760 32 44,806 68 65,566 Igunga 31,132 69 14,009 31 45,141 Igunga 2,519 6 42,622 94 45,141 Uyui 12,879 31 28,438 69 41,318 Uyui 3,804 9 37,514 91 41,318 Urambo 15,250 28 38,870 72 54,120 Urambo 7,485 14 46,635 86 54,120 Sikonge 6,507 33 13,006 67 19,514 Sikonge 740 4 18,774 96 19,514 Tabora Urban 3,533 34 6,725 66 10,258 Tabora Urban 1,027 10 9,231 90 10,258 Total 116,720 49 119,197 51 235,917 Total 36,336 15 199,581 85 235,917 Number % Number % Number % Number % Nzega 25,067 38 40,499 62 65,566 Nzega 3,391 5 62,175 95 65,566 Igunga 22,236 49 22,905 51 45,141 Igunga 6,510 14 38,631 86 45,141 Uyui 18,136 44 23,182 56 41,318 Uyui 2,896 7 38,422 93 41,318 Urambo 22,444 41 31,676 59 54,120 Urambo 4,108 8 50,012 92 54,120 Sikonge 8,259 42 11,255 58 19,514 Sikonge 775 4 18,739 96 19,514 Tabora Urban 3,672 36 6,586 64 10,258 Tabora Urban 149 1 10,109 99 10,258 Total 99,814 42 136,103 58 235,917 Total 17,829 8 218,088 92 235,917 Number % Number % Nzega 29,068 44 36,498 56 65,566 Igunga 29,364 65 15,777 35 45,141 Uyui 12,035 29 29,283 71 41,318 Urambo 27,331 51 26,789 49 54,120 Sikonge 6,411 33 13,102 67 19,514 Tabora Urban 2,729 27 7,529 73 10,258 Total 106,937 45 128,979 55 235,917 District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Insecicides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 195 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 196 Number % Number % Nzega 1,411 100 0 0 1,411 Igunga 336 100 0 0 336 Uyui 7,629 96 309 4 7,938 Urambo 11,186 95 618 5 11,803 Sikonge 3,985 99 50 1 4,034 Tabora Urban 132 100 0 0 132 Total 24,679 96 977 4 25,655 District Family, Friend and Relative Commercial Bank Co- operative Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Nzega 150 0 0 146 286 829 0 1,411 Igunga 230 0 0 0 0 106 0 336 Uyui 306 210 7,318 104 0 0 0 7,938 Urambo 503 125 11,051 0 0 0 125 11,803 Sikonge 245 48 3,548 0 47 145 0 4,034 Tabora Urban 0 0 132 0 0 0 0 132 Total 1,434 384 22,049 250 333 1,080 125 25,655 % 6 1 86 1 1 4 0 100 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit grante d too late Other Don't know about credit Total Nzega 2,835 9,141 7,727 1,316 22,339 854 150 0 19,793 64,155 Igunga 1,581 16,372 3,082 1,376 10,589 1,031 226 0 10,548 44,805 Uyui 1,091 6,299 4,338 616 11,904 1,113 105 0 7,913 33,379 Urambo 1,926 10,437 3,627 952 12,812 2,052 690 126 9,694 42,317 Sikonge 920 3,446 2,180 294 3,956 331 247 149 3,956 15,480 Tabora Urban 391 1,622 626 213 4,621 350 0 0 2,302 10,126 Total 8,744 47,318 21,580 4,768 66,223 5,730 1,418 275 54,206 210,261 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livest ock Other Total Credits Nzega 282 418 975 829 407 0 150 446 3,508 Igunga 336 106 106 106 106 0 106 106 972 Uyui 0 3,043 7,419 5,028 105 206 105 308 16,214 Urambo 446 4,580 11,438 9,447 2,309 757 0 2,189 31,166 Sikonge 96 537 3,750 2,868 143 242 0 544 8,179 Tabora Urban 0 0 107 107 25 0 25 107 372 Total Credits 1,159 8,684 23,795 18,386 3,095 1,205 386 3,701 60,410 13.2a AGRICULTURE CREDIT: Number of Households Reported Main Reasons for Not Using Credit By District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District During the 2002/03 Agriculture Year 13.1a AGRICULTURE CREDIT: Number of Agriculture Households Receiving Credit By Sex of Household Head Receiving Credit and District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District Total District Male Female Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 197 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 198 District Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Terminalia Ivorensis Leucena Spp Syszygium Spp Azadritachta Spp Albizia Spp Moringa Spp Total Nzega 1,201 5,599 119 . . . . . 576 144 1,474 751 3,068 . 895 13,828 Igunga 695 547 . . . . . . . . 342 . 683 . 1,366 3,633 Uyui . . 98 633 29,003 633 197 . . . 10,557 . 308 0 42,229 83,659 Urambo 3,915 . 30,087 . . . . . . . 4,352 . 241 32,717 4,819 76,131 Sikonge 1,168 297 2,088 2,424 . . . 495 . 1,636 . . . . 2,909 11,018 Tabora Urban 134 . . . . . . . . . 197 . . 1,575 175 2,081 Total 7,114 6,443 32,393 3,058 29,003 633 197 495 576 1,780 16,922 751 4,300 34,292 52,394 190,349 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees 0-9 1-19 05-29 30-39 40-49 60+ Total Nzega 1,280 8,485 291 5,343 0 . 1,570 13,828 Nzega 4,115 1,197 0 296 0 0 5,609 Igunga 223 888 344 2,744 0 . 567 3,633 Igunga 693 1,839 2,072 577 0 106 5,288 Uyui 204 1,562 418 50,425 211 31,672 833 83,659 Uyui 626 0 98 0 0 0 724 Urambo 483 7,005 0 . 741 69,127 1,224 76,131 Urambo 5,532 829 2,040 1,070 251 1,374 11,096 Sikonge 50 198 198 2,577 97 8,242 345 11,018 Sikonge 149 744 727 98 0 99 1,817 Tabora Urban 47 1,709 33 372 0 . 80 2,081 Tabora Urba 692 507 157 105 157 367 1,984 Total 2,285 19,847 1,284 61,461 1,049 109,041 4,619 190,349 Total 11,807 5,116 5,094 2,146 408 1,946 26,518 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Planks / Timber Poles Charcoal Fuel for Wood Shade Medicina l Other Total Nzega 288 147 1,248 419 0 294 2,397 Nzega 150 0 0 297 942 588 419 2,397 Igunga 0 0 0 453 0 114 567 Igunga 0 0 0 453 0 114 0 567 Uyui 0 106 210 295 103 422 1,135 Uyui 0 106 0 415 207 197 106 1,030 Urambo 0 0 983 241 0 241 1,465 Urambo 126 371 126 120 362 241 118 1,465 Sikonge 98 0 97 149 0 98 442 Sikonge 0 50 0 48 196 48 99 442 Tabora Urban 0 0 47 20 0 13 80 Tabora Urba 0 0 0 20 47 13 0 80 Total 386 252 2,585 1,576 103 1,183 6,085 Total 277 526 126 1,353 1,754 1,202 742 5,980 14.5 TREE FARMING: Number of Responses by Second Use of Planted Trees and District for the 2002/03 Agriculture Year, Tabora RegionSecond Use of Trees By District District Second Use 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Tabora Region 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Tabora District District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total 14.4 TREE FARMING: Number of Agriculture Households Classified By Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Tabora Region District Distance to Community Planted Forest (km) 14.3 TREE FARMING: Number of Responses by Main Use of Trees By District and District for the 2002/03 Agriculture Year, Tabora Region District Main Use Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 199 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 200 Number % Number % Nzega 15,560 24 50,006 76 65,566 Igunga 8,662 19 36,479 81 45,141 Uyui 12,311 30 29,006 70 41,318 Urambo 13,710 25 40,411 75 54,120 Sikonge 5,173 27 14,341 73 19,514 Tabora Urban 7,539 73 2,719 27 10,258 Total 62,956 27 172,961 73 235,917 Number % Number % Number % Number % Number % Nzega 1,862 12 9,464 61 3,339 21 749 5 147 1 15,560 Igunga 1,608 19 5,819 67 1,125 13 0 0 109 1 8,662 Uyui 2,533 21 7,914 64 1,656 13 106 1 102 1 12,311 Urambo 2,540 20 7,746 60 2,296 18 242 2 0 0 12,824 Sikonge 719 14 3,596 70 760 15 50 1 0 0 5,124 Tabora Urban 284 4 5,910 79 1,107 15 214 3 0 0 7,516 Total 9,547 15 40,449 65 10,282 17 1,361 2 358 1 61,997 Total Number % Number % Number % Number % Number % Number % Number Nzega 14,157 91 984 6 119 1 150 1 0 0 150 1 15,560 Igunga 8,436 99 0 0 0 0 116 1 0 0 0 0 8,552 Uyui 8,845 72 2,199 18 1,267 10 0 0 0 0 0 0 12,311 Urambo 6,885 54 4,119 32 1,483 12 96 1 118 1 0 0 12,701 Sikonge 3,716 72 1,125 22 93 2 192 4 0 0 46 1 5,173 Tabora Urban 7,237 97 40 1 0 0 26 0 160 2 25 0 7,488 Total 49,275 80 8,468 14 2,962 5 581 1 278 0 222 0 61,785 15.1 CROP EXTENSION\" Number of Agriculture Households Receiving Extension Messages By District During the 2002/03 Agriculture Year, Tabora Region Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District District During the 2002/03 Agriculture Year, Tabora Region Households Receiving Households Not Not applicable Very Good Good Average Poor No Good 15.3 CROP EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Tabora Region Total Number of Households District Government NGO / Development Cooperative Large Scale Farm Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 201 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Received Advice Total Number of Household % of Total Number of Household Nzega 13,888 844 0 150 0 150 15,032 65,566 23 Igunga 8,321 0 0 116 0 0 8,436 45,025 19 Uyui 8,113 2,095 1,267 0 0 0 11,475 41,212 28 Urambo 6,297 4,119 1,483 96 118 0 12,113 54,120 22 Sikonge 3,474 978 93 143 0 0 4,688 19,464 24 Tabora Urban 6,400 40 0 0 26 25 6,492 10,233 63 Total 46,493 8,075 2,843 505 144 175 58,236 235,621 25 % 80 14 5 1 0 0 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 6,243 1,088 0 150 0 0 7,481 65,566 11 Igunga 5,511 106 0 0 0 0 5,617 45,025 12 Uyui 6,046 2,614 1,161 0 0 0 9,821 41,212 24 Urambo 1,759 4,926 222 96 590 126 7,719 54,120 14 Sikonge 2,329 1,023 99 148 0 50 3,649 19,464 19 Tabora Urban 4,079 40 0 0 239 27 4,385 10,233 43 Total 25,967 9,798 1,483 394 829 202 38,673 235,621 16 % 67 25 4 1 2 1 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 3,083 571 0 0 0 150 3,804 65,566 6 Igunga 1,453 0 0 0 0 106 1,559 45,025 3 Uyui 3,011 1,048 211 0 0 0 4,270 41,212 10 Urambo 1,422 1,095 115 0 0 251 2,882 54,120 5 Sikonge 2,021 149 50 50 0 50 2,319 19,464 12 Tabora Urban 2,713 0 0 52 53 27 2,845 10,233 28 Total 13,703 2,862 376 102 53 583 17,680 235,621 8 % 78 16 2 1 0 3 100 15.4 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Plant Spacing By Source and District During the 2002/03 Agriculture Year, Tabora Region 15.5 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Agrochemical By Source and District During the 2002/03 Agriculture Year, Tabora Region District 15.6 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Erosion Control By Source and District During the 2002/03 Agriculture Year, Tabora Region Spacing District District Erosion Control Use of Agrochemicals Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 202 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 11,085 150 119 269 0 0 11,623 65,566 18 Igunga 6,951 0 0 116 0 343 7,410 45,025 16 Uyui 5,410 940 106 0 0 106 6,560 41,212 16 Urambo 4,433 973 193 0 244 251 6,093 54,120 11 Sikonge 2,069 333 50 149 0 50 2,650 19,464 14 Tabora Urban 3,379 25 0 26 266 54 3,751 10,233 37 Total 33,326 2,421 467 560 511 802 38,087 235,621 16 % 88 6 1 1 1 2 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 5,445 690 0 150 0 0 6,285 65,566 10 Igunga 4,358 212 0 0 0 220 4,790 45,025 11 Uyui 5,329 3,253 1,267 0 0 0 9,849 41,212 24 Urambo 2,462 6,101 96 332 590 244 9,826 54,120 18 Sikonge 1,590 1,415 149 149 0 146 3,449 19,464 18 Tabora Urban 3,446 67 0 0 293 25 3,831 10,233 37 Total 22,631 11,739 1,512 631 883 635 38,030 235,621 16 % 60 31 4 2 2 2 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 8,453 1,941 0 150 0 0 10,544 65,566 16 Igunga 6,051 106 0 0 0 231 6,387 45,025 14 Uyui 5,900 2,722 950 106 0 211 9,889 41,212 24 Urambo 3,891 4,546 220 96 236 126 9,115 54,120 17 Sikonge 2,899 636 50 98 0 0 3,683 19,464 19 Tabora Urban 3,014 67 27 0 400 0 3,508 10,233 34 Total 30,207 10,018 1,247 450 636 568 43,126 235,621 18 % 70 23 3 1 1 1 100 Inorganic Fertilizer Use District 15.7 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Tabora Region 15.8 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Tabora Region Organic Fertilizer Use Use of Improved Seed District 15.9 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Use of Improved Seeds By Source and District During the 2002/03 Agriculture Year, Tabora Region District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 203 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 738 0 0 0 150 888 65,566 1 Igunga 1,026 0 0 0 115 1,141 45,025 3 Uyui 418 0 0 0 211 629 41,212 2 Urambo 613 124 96 0 363 1,197 54,120 2 Sikonge 245 0 50 50 0 344 19,464 2 Tabora Urban 926 0 0 0 0 926 10,233 9 Total 3,966 124 146 50 839 5,124 235,621 2 % 77 2 3 1 16 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,519 147 300 0 0 2,966 65,566 5 Igunga 1,838 0 0 0 115 1,953 45,025 4 Uyui 2,715 104 0 0 211 3,030 41,212 7 Urambo 797 738 0 0 125 1,660 54,120 3 Sikonge 594 198 50 0 50 891 19,464 5 Tabora Urban 1,665 0 0 134 54 1,853 10,233 18 Total 10,128 1,187 350 134 554 12,353 235,621 5 % 82 10 3 1 4 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 6,739 1,096 0 1,170 300 149 9,455 65,566 14 Igunga 6,034 575 0 0 0 114 6,723 45,025 15 Uyui 7,188 419 528 0 0 0 8,134 41,212 20 Urambo 3,597 1,831 230 0 0 118 5,776 54,120 11 Sikonge 2,454 438 0 50 0 99 3,040 19,464 16 Tabora Urban 6,092 13 0 79 133 0 6,317 10,233 62 Total 32,104 4,373 758 1,298 433 480 39,445 235,621 17 % 81 11 2 3 1 1 100 15.10 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Mechanization/LST By Source and District During the 2002/03 Agriculture Year, Tabora Region District District District 15.11 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Irrigation Technology By Source and District During the 2002/03 Agriculture Year, Tabora Region Mechanisation / LST 15.12 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Crop Storage By Source and District During the 2002/03 Agriculture Year, Tabora Region Irrigation Technology Crop Storage Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 204 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Household % of Total Number of Household Nzega 1,034 0 0 0 269 1,303 65,566 2 Igunga 1,213 0 0 0 0 1,213 45,025 3 Uyui 4,992 103 106 0 0 5,200 41,212 13 Urambo 986 1,101 96 347 369 2,900 54,120 5 Sikonge 1,162 0 0 198 50 1,410 19,464 7 Tabora Urban 2,418 27 0 27 103 2,575 10,233 25 Total 11,805 1,230 202 572 791 14,601 235,621 6 % 81 8 1 4 5 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,114 300 0 2,904 269 0 5,588 65,566 9 Igunga 1,110 0 0 0 0 0 1,110 45,025 2 Uyui 1,215 105 211 0 0 317 1,848 41,212 4 Urambo 483 377 0 251 0 356 1,467 54,120 3 Sikonge 680 385 50 50 0 50 1,213 19,464 6 Tabora Urban 4,777 27 0 79 267 24 5,173 10,233 51 Total 10,380 1,194 260 3,283 536 746 16,400 235,621 7 % 63 7 2 20 3 5 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,900 928 0 0 0 0 3,829 65,566 6 Igunga 1,757 0 0 0 0 0 1,757 45,025 4 Uyui 2,918 312 106 0 0 0 3,336 41,212 8 Urambo 1,093 471 220 118 472 240 2,614 54,120 5 Sikonge 682 96 0 99 0 50 927 19,464 5 Tabora Urban 1,725 54 0 0 54 0 1,832 10,233 18 Total 11,076 1,861 326 217 526 290 14,295 235,621 6 % 77 13 2 2 4 2 100 District 15.13 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Vermin Control By Source and District During the 2002/03 Agriculture Year, Tabora Region District 15.14 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Agro-processing By Source and District During the 2002/03 Agriculture Year, Tabora Region District Vermin Control Agro-forestry Agro-progressing 15.15 CROP EXTENSION MESSAGES: Number of Agriculture Households Receivingf Advice on Agro-forestry By Source and District During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 205 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 297 0 0 0 0 297 65,566 0 Igunga 116 0 0 0 0 116 45,025 0 Uyui 838 211 0 0 0 1,049 41,212 3 Urambo 357 239 0 244 243 1,083 54,120 2 Sikonge 694 140 99 0 0 934 19,464 5 Tabora Urban 239 75 27 0 0 341 10,233 3 Total 2,541 665 126 244 243 3,819 235,621 2 % 67 17 3 6 6 100 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Household % of Total Number of Household Nzega 447 519 0 0 0 966 65,566 1 Igunga 106 115 0 0 0 221 45,025 0 Uyui 0 0 0 0 0 0 41,212 0 Urambo 249 0 124 0 243 615 54,120 1 Sikonge 446 92 0 99 50 687 19,464 4 Tabora Urban 105 0 0 26 0 131 10,233 1 Total 1,353 726 124 125 292 2,620 235,621 1 % 52 28 5 5 11 100 15.16 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Beekeeping By Source and District During the 2002/03 Agriculture Year, Tabora Region District District Fish Farming Beekeeping 15.17 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Fish Farming By Source and District During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 206 Received Adopted e % Received Adopted % Received Adopted % Received Adopted % Nzega 14,612 10,942 75 7,031 4,465 64 3,322 1,397 42 11,337 8,274 73 Igunga 8,436 7,308 87 5,617 2,500 45 1,339 671 50 7,296 4,277 59 Uyui 11,577 10,733 93 9,821 7,345 75 4,165 2,193 53 6,349 3,139 49 Urambo 12,231 12,001 98 7,837 6,464 82 2,635 1,200 46 5,605 2,630 47 Sikonge 4,688 3,918 84 3,649 2,916 80 2,175 1,410 65 2,650 1,549 58 Tabora Urban 6,547 5,915 90 4,331 3,349 77 2,820 2,312 82 3,672 2,558 70 Total 58,092 50,816 87 38,287 27,040 71 16,455 9,183 56 36,909 22,427 61 Received Adopted % Received Adopted % Received Adopted % Received Adopted % Nzega 6,144 2,303 37 10,544 5,763 55 738 0 0 2,816 1,779 63 Igunga 4,456 1,681 38 6,387 2,373 37 1,035 221 21 1,721 1,606 93 Uyui 9,951 7,137 72 9,995 4,712 47 312 0 0 2,721 2,087 77 Urambo 9,708 8,984 93 8,993 7,708 86 707 118 17 1,535 1,330 87 Sikonge 3,399 2,917 86 3,585 3,090 86 198 50 25 744 545 73 Tabora Urban 3,772 2,271 60 3,482 1,946 56 900 27 3 1,641 1,112 68 Total 37,431 25,294 68 42,985 25,592 60 3,890 415 11 11,177 8,460 76 Received Adopted % Received Adopted % Received Adopted % Received Adopted % Nzega 9,455 7,937 84 884 587 66 5,469 4,962 91 3,829 1,030 27 Igunga 6,609 5,485 83 1,213 780 64 994 765 77 1,749 983 56 Uyui 7,923 7,398 93 4,989 4,472 90 1,326 1,856 140 3,230 938 29 Urambo 5,654 4,566 81 2,539 2,646 104 1,106 1,111 100 2,386 731 31 Sikonge 3,040 2,524 83 1,361 1,113 82 1,164 732 63 976 739 76 Tabora Urban 6,237 6,054 97 2,190 2,323 106 5,117 4,856 95 1,324 583 44 Total 38,918 33,964 87 13,175 11,920 90 15,177 14,281 94 13,494 5,004 37 District Erosion Control Crop Storage Vermin Control 15.18 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tabora Region 15.19 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tabora Region 15.20 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tabora Region Spacing Use of Agrochemicals District District Agro-progressing Agro-forestry Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 207 Received Adopted % Received Adopted % Nzega 297 0 0 966 0 0 Igunga 0 0 0 0 0 0 Uyui 421 316 75 0 0 0 Urambo 598 598 100 124 0 0 Sikonge 934 643 69 492 248 50 Tabora Urban 128 77 60 53 26 50 Total 2,378 1,635 69 1,634 274 17 District Beekeeping Fish Farming 15.21 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora 208 Appendix II 209 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 210 Number of Households % Number of Households % Nzega 34,629 53 30,937 47 65,566 Igunga 34,913 77 10,228 23 45,141 Uyui 9,192 22 32,126 78 41,318 Urambo 5,525 10 48,595 90 54,120 Sikonge 3,754 19 15,760 81 19,514 Tabora Urban 849 8 9,409 92 10,258 Total 88,862 38 147,055 62 235,917 Number Owned Number Used Area Cultivated (Acres) Number Owned Number Used Area Cultivated (Acres) Nzega 83,769 120,742 155,244 83,769 120,742 155,244 Igunga 102,641 162,466 277,122 102,641 162,466 277,122 Uyui 34,417 42,341 63,200 34,417 42,341 63,200 Urambo 14,865 25,202 24,585 14,865 25,202 24,585 Sikonge 12,227 15,992 28,100 12,227 15,992 28,100 Tabora Urban 3,381 3,752 4,728 3,381 3,752 4,728 Total 251,299 370,494 552,978 251,299 370,494 552,978 Number % Number % Nzega 30,698 45 34,868 21 65,566 Igunga 11,351 17 33,791 20 45,141 Uyui 8,867 13 31,727 19 40,594 Urambo 10,884 16 42,391 26 53,275 Sikonge 3,959 6 15,555 9 19,514 Tabora Urban 2,746 4 7,407 4 10,154 Total 68,504 100 165,739 100 234,244 Area (Ha) % Area (Ha) % Area (Ha) (%) Nzega 26,328 41 1,713 24 28,042 39 Igunga 11,737 18 537 7 12,274 17 Uyui 8,880 14 732 10 9,612 13 Urambo 8,972 14 4,104 57 13,075 18 Sikonge 5,695 9 84 1 5,779 8 Tabora Urban 2,803 4 60 1 2,863 4 Total 64,415 100 7,230 100 71,645 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year, Tabora Region District Farm Yard Manure Area Applied Compost Area Applied Total Area Applied with Organic Fertilizers 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft Animal By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year, Tabora Region Total Type of Craft District Oxen District Using Organic Fertilizer Not Using Organic Fertilizer 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By District During 2002/03 Agriculture Year, Tabora Region Total Number of Crop Growing Households District Using Draft Animals Not Using Draft Animals 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Agriculture Households Using Draft Animal to Cultivate Land By District During 2002/03 Agriculture Year, Tabora Region Total Households Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 211 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 212 Number % Number % Nzega 22,876 35 42,690 65 65,566 27,645 Igunga 21,452 48 23,689 52 45,141 23,588 Uyui 9,429 23 31,889 77 41,318 14,758 Urambo 6,624 12 47,496 88 54,120 13,740 Sikonge 4,275 22 15,238 78 19,514 5,837 Tabora Urban 1,269 12 8,989 88 10,258 2,302 Total 65,925 28 169,992 72 235,917 87,871 Number % Number % 1-5 15,840 24 52,711 3 3 6-10 12,660 19 100,927 6 8 11-15 9,495 14 121,805 8 13 16-20 7,284 11 133,088 8 18 21-30 9,097 14 234,411 15 26 31-40 3,459 5 129,682 8 37 41-50 2,359 4 108,258 7 46 51-60 839 1 47,044 3 56 61-100 3,506 5 288,935 18 82 101-150 605 1 73,633 5 122 151+ 782 1 278,198 18 356 Total 65,925 100 1,568,691 100 24 Number % Number % Number % Number % Bulls 204,261 100.0 0 0.0 46 0.0 204,307 13.0 Cows 488,048 99.8 0 0.0 1,089 0.2 489,137 31.2 Steers 259,614 99.7 671 0.3 0 0.0 260,285 16.6 Heifers 274,899 99.9 0 0.0 345 0.1 275,243 17.5 Male Calves 150,648 100.0 0 0.0 46 0.0 150,694 9.6 Female Calves 188,699 99.8 0 0.0 325 0.2 189,024 12.0 Total 1,566,169 99.8 671 0.0 1,851 0.1 1,568,691 100.0 Total Cattle 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 Category of Cattle Catle Rearing Households Heads of Catle Average Number per Household Herd Size 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size; on 1st October 2003 Indigenous Cattle Improved Beef Cattle 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Tabora Region Total Number of Agricultural Households Rearing Livestock Total Agriculture Households Improved Dairy Cattle District Households Rearing Cattle Households Not Rearing Cattle Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 213 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Nzega 22,876 424,721 99.9 150 300 0.1 0 0 0.0 22,876 425,021 27.1 Igunga 21,452 465,399 99.7 0 0 0.0 115 1,493 0.3 21,452 466,892 29.8 Uyui 9,429 205,865 100.0 0 0 0.0 0 0 0.0 9,429 205,865 13.1 Urambo 6,624 130,629 99.7 124 371 0.3 0 0 0.0 6,624 131,000 8.4 Sikonge 4,229 271,820 99.9 0 0 0.0 96 279 0.1 4,275 272,100 17.3 Tabora Urban 1,244 67,734 99.9 0 0 0.0 52 79 0.1 1,269 67,812 4.3 Total 65,854 1,566,169 99.8 274 671 0.0 262 1,851 0.1 65,925 1,568,691 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega 49,505 130,919 82,744 72,958 38,799 49,797 424,721 Igunga 40,747 160,218 102,951 64,432 45,213 51,839 465,399 Uyui 25,178 65,451 34,556 32,588 22,476 25,615 205,865 Urambo 16,505 40,744 20,445 20,860 15,359 16,716 130,629 Sikonge 67,715 64,890 13,808 66,392 23,469 35,547 271,820 Tabora Urban 4,611 25,827 5,111 17,669 5,333 9,184 67,734 Total 204,261 488,048 259,614 274,899 150,648 188,699 1,566,169 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega . . 300 . . . 300 Igunga . . . . . . . Uyui . . . . . . . Urambo . . 371 . . . 371 Sikonge . . . . . . . Tabora Urban . . . . . . . Total . . 671 . . . 671 Total Cattle 18.6 CATTLE PRODUCTION: Number of Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle 18.2 CATTLE PRODUCTION: Total Number of Cattle By Type and District as of 1st October, 2003 District 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Improved Beef Improved Dairy Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 214 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega . . . . . . . Igunga . 919 . 345 . 230 1,493 Uyui . . . . . . . Urambo . . . . . . . Sikonge 46 92 . . 46 96 279 Tabora Urban . 79 . . . . 79 Total 46 1,089 . 345 46 325 1,851 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega 49,505 130,919 83,044 72,958 38,799 49,797 425,021 Igunga 40,747 161,137 102,951 64,776 45,213 52,069 466,892 Uyui 25,178 65,451 34,556 32,588 22,476 25,615 205,865 Urambo 16,505 40,744 20,816 20,860 15,359 16,716 131,000 Sikonge 67,761 64,982 13,808 66,392 23,515 35,642 272,100 Tabora Urban 4,611 25,905 5,111 17,669 5,333 9,184 67,812 Total 204,307 489,137 260,285 275,243 150,694 189,024 1,568,691 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Total Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 215 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 216 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Nzega 17,692 183,820 99 150 901 0.5 300 451 0.2 17,692 185,172 Igunga 17,664 230,075 98 338 1,825 0.8 453 2,177 0.9 17,664 234,077 Uyui 11,852 121,592 97 516 1,558 1.2 512 1,849 1.5 11,852 124,998 Urambo 11,777 91,975 98 370 1,349 1.4 126 502 0.5 11,777 93,826 Sikonge 3,998 53,445 99 99 347 0.6 49 296 0.5 3,998 54,087 Tabora Urban 2,184 26,288 98 0 . 0.0 104 547 2.0 2,184 26,836 Total 65,167 707,195 98 1,473 5,979 0.8 1,543 5,821 0.8 65,167 718,996 Number % Number % Average Per Household 1-4 15,561 23.9 43,747 6 3 5-9 21,112 32.4 138,722 19 7 10-14 13,399 20.6 154,144 21 12 15-19 5,930 9.1 98,153 14 17 20-24 4,395 6.7 92,037 13 21 25-29 930 1.4 25,191 4 27 30-39 1,651 2.5 53,884 7 33 40+ 2,188 3.4 113,118 16 52 Total 65,167 100.0 718,996 100 11 Number % Number % Number % Number % Billy Goat 118,728 98.7 793 0.7 766 0.6 120,287 17 Castrated Goat 35,905 88.4 2,192 5.4 2,505 6.2 40,602 6 She Goat 361,261 99.4 1,019 0.3 1,338 0.4 363,619 51 Male Kid 88,817 98.2 1,146 1.3 522 0.6 90,485 13 She Kid 102,484 98.5 828 0.8 691 0.7 104,003 14 Total 707,195 98.4 5,979 0.8 5,821 0.8 718,996 100 19.1 GOAT PRODUCTION: Total Number of Goats by Goat Type and District as on 1st October, 2003 District 19.3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat on 1st October, 2003 Total Goat 19.2 GOAT PRODUCTION: Number of Households Rearing Goats and Head of Goats by Herd Size on 1st October 2003 Goat Rearing Households Head of Goats Herd Size Category of Goats Total Goat Improved Dairy Improved for Meat Indigenous Indigenous Goats Improved Meat Goats Improved Dairy Goats Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 217 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega 29,304 10,183 96,015 20,218 28,099 183,820 Igunga 35,784 13,767 117,179 30,866 32,478 230,075 Uyui 21,994 5,629 59,806 17,051 17,112 121,592 Urambo 17,784 3,378 48,730 10,071 12,013 91,975 Sikonge 10,210 2,007 25,555 7,205 8,468 53,445 Tabora Urban 3,651 941 13,977 3,405 4,315 26,288 Total 118,728 35,905 361,261 88,817 102,484 707,195 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega . 901 . . . 901 Igunga 695 . 914 216 . 1,825 Uyui 98 616 105 633 106 1,558 Urambo . 626 . . 723 1,349 Sikonge . 50 . 297 . 347 Tabora Urban . . . . . . Total 793 2,192 1,019 1,146 828 5,979 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega 150 300 . . . 451 Nzega 29,455 11,385 96,015 20,218 28,099 185,172 Igunga . 1,838 . . 338 2,177 Igunga 36,479 15,606 118,094 31,082 32,816 234,077 Uyui 512 205 632 199 299 1,849 Uyui 22,604 6,450 60,543 17,884 17,516 124,998 Urambo . . 502 . . 502 Urambo 17,784 4,003 49,232 10,071 12,735 93,826 Sikonge . . . 296 . 296 Sikonge 10,210 2,056 25,555 7,798 8,468 54,087 Tabora Urban 103 161 204 26 53 547 Tabora Urban 3,754 1,102 14,180 3,431 4,368 26,836 Total 766 2,505 1,338 522 691 5,821 Total 120,287 40,602 363,619 90,485 104,003 718,996 19.7 GOAT PRODUCTION: Total Number of Goat by Category and District as of 1st October, 2003 District Total Goat 19.5 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District on 1st October, 2003 194 GOAT PRODUCTION: Number of Indigenous Goat by Category and District on 1st October, 2003 District Number of Indigenous Goats District Number of Improved Meat Goats 19.6 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 District Number of Improved Dairy Goats Tanzania Agriculture Sample Census - 2003 Tabora 218 Appendix II 219 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 220 Number % Number % Number % Ram 37,225 62 22,459 38 59,684 25 Castrated Sheep 3,721 82 828 18 4,549 2 She Sheep 110,926 98 2,042 2 112,969 48 Male Lamb 25,454 93 1,841 7 27,295 12 She Lamb 29,269 95 1,448 5 30,717 13 Total 206,595 88 28,618 12 235,213 100 Number % Number % Nzega 7,912 12 57,654 88 65,566 27,645 Igunga 10,454 23 34,687 77 45,141 23,588 Uyui 5,082 12 36,235 88 41,318 14,758 Urambo 1,826 3 52,294 97 54,120 13,740 Sikonge 2,016 10 17,498 90 19,514 5,837 Tabora Urban 836 8 9,422 92 10,258 2,302 Total 28,126 12 207,790 88 235,917 87,871 Number % Number % Number % Nzega 40,616 96 1,502 4 42,118 18 Igunga 98,197 97 3,373 3 101,570 43 Uyui 38,240 63 22,107 37 60,347 26 Urambo 5,076 84 943 16 6,019 3 Sikonge 19,410 98 428 2 19,838 8 Tabora Urban 5,056 95 265 5 5,321 2 Total 206,595 88 28,618 12 235,213 100 District Number of Indigenous Number of Improved for Mutton Total Number of Sheep Total Household Raising Sheep Average Sheep Nzega 40,616 1,502 42,118 7,912 5 Igunga 98,197 3,373 101,570 10,454 10 Uyui 38,240 22,107 60,347 5,082 12 Urambo 5,076 943 6,019 1,826 3 Sikonge 19,410 428 19,838 2,016 10 Tabora Urban 5,056 265 5,321 836 6 Total 206,595 28,618 235,213 28,126 8 Breed 20.1 SHEEP PRODUCTION: Total Number of Sheep By Breed Type on 1st October 2002/03 Total Sheep Number of Indigenous Sheep Number of Improved Mutton Sheep 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.4 Number of Sheep per Household by District as of 1st October 2003 Number of Indigenous Number of Improved for Mutton Total Sheep District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 221 Head Size Number of Households % Number of Sheep % Average Number Per Household 1-4 12,999 46 32,772 14 3 5-9 8,550 31 55,667 24 7 10-14 2,781 10 31,232 13 11 15-19 1,496 5 24,471 10 16 20-24 863 3 18,294 8 21 25-29 486 2 12,873 5 26 30-39 485 2 16,330 7 34 40+ 367 1 43,573 19 119 Total 28,028 100 235,213 100 8 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 7,539 892 24,122 3,213 4,850 40,616 Igunga 14,347 1,535 53,264 13,999 15,052 98,197 Uyui 9,314 943 18,042 4,475 5,465 38,240 Urambo 844 . 3,268 474 490 5,076 Sikonge 4,091 138 9,916 2,484 2,781 19,410 Tabora Urban 1,089 213 2,314 809 631 5,056 Total 37,225 3,721 110,926 25,454 29,269 206,595 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 300 . 150 1,051 . 1,502 Igunga 927 232 1,288 232 695 3,373 Uyui 21,115 317 . 190 486 22,107 Urambo 118 . 472 236 118 943 Sikonge . 279 . . 149 428 Tabora Urban . . 132 133 . 265 Total 22,459 828 2,042 1,841 1,448 28,618 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 7,840 892 24,272 4,264 4,850 42,118 Igunga 15,274 1,767 54,552 14,230 15,747 101,570 Uyui 30,429 1,259 18,042 4,665 5,952 60,347 Urambo 962 . 3,740 710 608 6,019 Sikonge 4,091 418 9,916 2,484 2,930 19,838 Tabora Urban 1,089 213 2,446 942 631 5,321 Total 59,684 4,549 112,969 27,295 30,717 235,213 20.5 Number of Households and Heads of Sheep by Head Size on 1st October 2003 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2002 District Number of Indigenous 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2002 District Total Sheep 20.7 Total Number of Mutton Sheep by Sheep Type and District on 1st October 2002 District Number of Improved for Mutton Tanzania Agriculture Sample Census - 2003 Tabora 222 Appendix II 223 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 224 Number % Number % 1-4 2,386 91 4,076 65 2 5-9 106 4 739 12 7 10-14 123 5 1,471 23 12 Total 2,614 100 6,286 100 2 District Number of Household Number of Pig Average Number Per Household Nzega 532 1,083 2 Uyui 106 739 7 Urambo 1,844 4,172 2 Tabora Urban 132 292 2 Total 2,614 6,286 2 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Nzega 413 119 551 . . 1,083 Uyui 317 0 422 0 0 739 Urambo 1,612 . 1,098 729 733 4,172 Tabora Urban 54 . 81 106 52 292 Total 2,395 119 2,152 835 785 6,286 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type of Pigs and District on 1st October, 2003 Pig Rearing Households Heads of Pigs g Number Per Household Herd Size Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 225 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 226 Number % Number % Nzega 8,133 29 19,512 71 27,645 Igunga 10,622 46 12,621 54 23,243 Uyui 3,511 26 10,122 74 13,634 Urambo 5,587 41 7,910 59 13,497 Sikonge 1,070 19 4,668 81 5,738 Tabora Urban 1,103 49 1,162 51 2,265 Total 30,028 35 55,995 65 86,022 Number % Number % Number % Number % Nzega 6,237 28 3,085 28 868 21 720 19 Igunga 9,316 42 2,918 27 1,212 29 972 26 Uyui 1,440 6 1,235 11 737 18 1,468 39 Urambo 3,865 17 2,224 20 489 12 360 10 Sikonge 732 3 683 6 396 10 48 1 Tabora Urban 581 3 767 7 426 10 150 4 Total 22,172 100 10,913 100 4,127 100 3,717 100 No. of Households % No. of Households % Nzega 17,269 63 9,955 37 27,224 Igunga 16,662 75 5,609 25 22,271 Uyui 7,612 55 6,127 45 13,739 Urambo 6,805 50 6,688 50 13,493 Sikonge 3,081 56 2,432 44 5,513 Tabora Urban 847 39 1,323 61 2,171 Total 52,275 62 32,135 38 84,410 Number % Number % Number % Number % Number % Nzega 3,857 22 7,993 46 2,605 15 300 2 2,514 15 17,269 Igunga 4,094 25 9,841 59 1,718 10 114 1 894 5 16,662 Uyui 2,115 28 3,357 44 632 8 890 12 617 8 7,612 Urambo 1,903 28 3,340 49 96 1 855 13 611 9 6,805 Sikonge 1,154 37 714 23 297 10 634 21 280 9 3,081 Tabora Urban 187 22 502 59 106 13 53 6 0 0 847 Total 13,310 25 25,747 49 5,455 10 2,847 5 4,916 9 52,275 22.1 PESTS AND PARASITES: Number of Livestock Rearing Households deworming Livestock by District During the 2002/03 Agriculture Year District Demworming Livestock NOT Demworming Livestock Total 22.3 PESTS AND PARASITE: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year 22.2 PESTS AND PARASITES: Number of Livestock Rearing Households dewormed Livestock byType of Livestock and District During the 2002/03 Agriculture Year District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs District Tick Problems No Tick Problems Total Method of Tick Control 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District None Spraying Dipping Smearing Other Total Tanzania Agriculture Sample Census Appendix II 227 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 228 Number % Type Number Indigenous Chicken 2,498,191 99.63 Ducks 57,565 Layer 3,949 0.16 Turkeys 1,830 Broiler 5,330 0.21 Rabbits 7,171 0.00 Donkeys 26,294 0.00 Total 2,507,469 100.00 92,861 Indigenous Chicken Layer Broiler Total Number of Chicken Ducks Turkeys Rabbits Donkeys Other Nzega 492,529 3,522 438 496,490 Nzega 12,653 890 0 1,197 901 Igunga 359,944 109 811 360,864 Igunga 5,420 656 0 11,055 341 Uyui 579,747 317 2,740 582,803 Uyui 27,042 0 633 13,896 1,019 Urambo 646,320 . 1,242 647,562 Urambo 9,171 0 6,438 0 2,552 Sikonge 341,473 . 99 341,572 Sikonge 2,129 285 99 146 0 Tabora Urban 78,178 . . 78,178 Tabora Urban 1,151 0 0 0 0 Total 2,498,191 3,949 5,330 2,507,469 Total 57,565 1,830 7,171 26,294 4,813 Flock Size Number of Households % Number of Chicken Average Chicken by Households 1995 1999 2003 1 - 4 28,432 17 83,765 3 Cattle 1,009,571 1,626,130 1,568,691 5 - 9 46,552 28 309,940 7 Improved Dairy 0 947 1,851 10 - 19 50,056 30 645,709 13 Goats 464,327 930,652 718,996 20 - 29 23,087 14 517,953 22 Sheep 151,034 245,723 235,213 30 - 39 9,792 6 312,264 32 Pigs 4,071 30,406 6,286 40 - 49 4,126 2 173,702 42 Indigenous Chicken 1,670 2,559,020 2,498,191 50 - 99 4,771 3 289,704 61 Layers 6,507 4,950 3,949 100+ 477 0 174,432 365 Broilers 2,675 20,142 5,330 Total 167,294 100 2,507,469 15 Total Chicken 1,679,258 2,584,112 2,507,469 Chicken Others Type 23c OTHER LIVESTOCK: Total Number of Households and Chickens raised by Flock Size as of 1st October 2003 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 District Chicken Type 23b OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District Type of Livestock 23e OTHER LIVESTOCK/POULTRY POPULATION TREND District 23d OTHER LIVESTOCK: Head Number of Other Livestock by Type of Livestock and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 229 FISH FARMING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 230 Yes % No % Nzega 0 0 65,566 100 65,566 Igunga 0 0 45,141 100 45,141 Uyui 98 0 41,220 100 41,318 Urambo 0 0 54,120 100 54,120 Sikonge 98 1 19,416 99 19,514 Tabora Urban 26 0 10,232 100 10,258 Total 222 0 235,694 100 235,917 Dug out Pond Total Uyui 196 196 Sikonge 148 148 Tabora Urban 53 53 Total 396 396 Government Institution NGOs / Project Other (Neighbour) Uyui 0 0 196 Sikonge 99 48 0 Tabora Urban 53 0 0 Total 152 48 196 Did not Sell Number Uyui 196 196 Sikonge 148 148 Tabora Urban 53 53 Total 396 396 District Number of Tilapia Number of Carp Number of Others Uyui 3,424 196 196 Sikonge 9,697 0 4,958 Tabora Urban 2,646 55,573 0 Total 15,767 55,768 5,153 District Total 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District During 2002/03 Agricultural Year Was Fish Farming Carried Out by this Household During 2002/03 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District During the 2002/03 Agricultural Year District System of Fish Farming District 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year Total District 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerings and District During the 2002/03 Agricultural Year Source of Fingerlings 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District During the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 231 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 232 Number % Number % Nzega 5,387 8 60,179 92 65,566 27,645 19 Igunga 4,180 9 40,961 91 45,141 23,588 18 Uyui 1,780 4 39,538 96 41,318 14,758 12 Urambo 2,877 5 51,244 95 54,120 13,740 21 Sikonge 764 4 18,750 96 19,514 5,837 13 Tabora Urban 1,866 18 8,392 82 10,258 2,302 81 Total 16,853 7 219,063 93 235,917 87,871 19 Government NGO / Development Project Large Scale Farmer Nzega 3,827 421 138 Igunga 2,270 0 0 Uyui 1,261 0 0 Urambo 1,652 0 126 Sikonge 471 96 0 Tabora Urban 1,135 51 0 Total 10,614 567 263 District Source of Advice 29.1b LIVESTOCK EXTENSION PROVIDERS: Number of Households By Source of Extension and District during the 2002/03 Agriculture Year % 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice By District During 2002/03 Agricultural Year District Received Livestock Advice Did Not Receive Livestock Advice Total Total Number of Households Raising Livestock Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 233 Government NGO / Development Project Total Nzega 447 0 447 27,645 1.6 Igunga 681 0 681 23,588 2.9 Uyui 317 0 317 14,758 2.1 Urambo 0 0 0 13,740 0.0 Sikonge 195 0 195 5,837 3.3 Tabora Urban 263 27 290 2,302 12.6 Total 1,903 27 1,930 87,871 2.2 % 98.6 1.4 100.0 Government NGO / Development Project Total Nzega 1,198 0 1,198 27,645 4.3 Igunga 681 0 681 23,588 2.9 Uyui 422 0 422 14,758 2.9 Urambo 104 0 104 13,740 0.8 Sikonge 195 0 195 5,837 3.3 Tabora Urban 448 27 474 2,302 20.6 Total 3,048 27 3,075 87,871 3.5 % 99.1 0.9 100.0 % Receiving Advice out of Total 29.1c LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking By Source and District 29.1d LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene By Source and District District Source of Advice on Milk Hygene Total Number of Households Raising Livestock Total Number of Households Raising Livestock District Source of Advice opn Proper Milking % Receiving Advice out of Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 234 Government NGO / Development Project Large Scale Farmer not applicable Total Nzega 3,841 150 0 0 3,991 27,645 14.4 Igunga 3,623 0 0 0 3,623 23,588 15.4 Uyui 1,472 0 0 0 1,472 14,758 10.0 Urambo 1,566 0 126 0 1,691 13,740 12.3 Sikonge 474 0 0 0 474 5,837 8.1 Tabora Urban 925 27 26 27 1,006 2,302 43.7 Total 11,901 177 152 27 12,257 87,871 13.9 % 97.1 1.4 1.2 0.2 100.0 Government NGO / Development Project Total Nzega 1,457 150 1,607 27,645 5.8 Igunga 2,269 0 2,269 23,588 9.6 Uyui 317 0 317 14,758 2.1 Urambo 126 0 126 13,740 0.9 Sikonge 237 0 237 5,837 4.1 Tabora Urban 608 24 631 2,302 27.4 Total 5,015 174 5,188 87,871 5.9 % 96.7 3.4 100.0 Total Number of Households Raising Livestock % Receiving Advice out of Total Total Number of Households Raising Livestock % Receiving Advice out of Total District Source of Advice on Herd/Flock Size $ Selection 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control By Source and District District Source of Advice on Disease Control (Dipping/Spraying) 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection By Source and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 235 Government NGO / Development Project Total Nzega 1,042 124 1,166 27,645 4.2 Igunga 663 0 663 23,588 2.8 Uyui 211 0 211 14,758 1.4 Urambo 0 0 0 13,740 0.0 Sikonge 50 99 149 5,837 2.5 Tabora Urban 131 0 131 2,302 5.7 Total 2,096 223 2,319 87,871 2.6 % 90.4 9.6 100.0 Government NGO / Development Project Co-operative Total Nzega 2,061 721 0 2,783 27,645 10.1 Igunga 2,484 0 566 3,050 23,588 12.9 Uyui 947 0 0 947 14,758 6.4 Urambo 930 0 0 930 13,740 6.8 Sikonge 333 0 0 333 5,837 5.7 Tabora Urban 471 51 0 522 2,302 22.7 Total 7,227 772 566 8,565 87,871 9.7 % 84.4 9.0 6.6 100.0 % Receiving Advice out of Total 291h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengtherning By Source and District Total Number of Households Raising Livestock Total Number of Households Raising Livestock % Receiving Advice out of Total District Source of Advice on Group Formation & Strenthening District Source of Advice on Pasture Establishment 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment By Source and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 236 Government NGO / Development Project Total Nzega 2,608 150 2,759 27,645 10.0 Igunga 2,371 0 2,371 23,588 10.1 Uyui 528 0 528 14,758 3.6 Urambo 125 0 125 13,740 0.9 Sikonge 287 0 287 5,837 4.9 Tabora Urb 334 27 361 2,302 15.7 Total 6,254 177 6,431 87,871 7.3 % 97.2 2.8 100.0 Government NGO / Development Project Total Nzega 721 150 871 27,645 3.2 Igunga 912 0 912 23,588 3.9 Uyui 106 0 106 14,758 0.7 Urambo 0 0 0 13,740 0.0 Sikonge 145 50 195 5,837 3.3 an 209 27 236 2,302 10.2 Total 2,093 227 2,319 87,871 2.6 % 90.2 9.8 100.0 Number % Number % Number % Number % Number % Nzega 1,135 18 3,956 64 566 9 570 9 0 0 6,227 Igunga 1,130 14 2,916 35 797 10 110 1 3,325 40 8,279 Uyui 739 19 936 24 106 3 0 0 2,097 54 3,877 Urambo 1,061 25 1,896 45 242 6 0 0 978 23 4,177 Sikonge 0 0 633 53 464 39 0 0 92 8 1,189 Tabora Urban 116 5 1,339 61 341 15 386 18 25 1 2,207 Total 4,182 16 11,676 45 2,516 10 1,066 4 6,517 25 25,956 Quality of Service Total District Very Good Good Average Poor No Good 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year 29.1j LIVESTOCK EXTENSION: Number of Households Receiving Advice on Use of Improved Bulls By Source and District District Source of Advice on Improved Bulls Total Number of Households Raising Livestock % Receiving Advice out of Total 29.1i LIVESTOCK EXTENSION: Number of Households Receiving Advice on Calf Rearing By Source and District District Source of Advice on Calf Rearing Total Number of Households Raising Livestock % Receiving Advice out of Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 237 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Total Number of Households Raising Livestock % Nzega 5,387 5,387 5,387 5,387 5,387 26,933 27,645 97 Igunga 4,180 4,180 4,180 4,180 4,180 20,899 23,588 89 Uyui 1,780 1,780 1,780 1,780 1,780 8,901 14,758 60 Urambo 2,877 2,877 2,877 2,877 2,877 14,383 13,740 105 Sikonge 764 718 569 569 569 3,189 5,837 55 Tabora Urban 1,866 1,866 1,866 1,866 1,866 9,332 2,302 405 Total 16,853 16,807 16,659 16,659 16,659 83,637 87,871 95 % 20.2 20.1 19.9 19.9 19.9 100.0 29.1l LIVESTOCK EXTENSION: Number of Households Receiving Advice on Other Extension Messages by Source and District Other Livestock Extension District Tanzania Agriculture Sample Census - 2003 Tabora 238 Appendix II 239 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 240 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Nzega 19.4 2.7 6.7 3.2 31.4 9.8 41.9 105.8 8.5 15.9 26.6 69.2 Igunga 13.6 2.4 9.1 2.1 25.2 6.4 46.3 163.9 7.0 14.9 27.0 107.1 Uyui 43.7 5.8 11.8 4.5 61.1 18.1 70.5 68.5 13.1 32.4 64.4 68.6 Urambo 22.4 5.7 19.0 3.2 58.4 8.9 63.5 125.8 13.3 19.4 48.3 115.8 Sikonge 67.3 3.5 47.1 2.0 67.0 7.8 76.8 133.4 28.6 25.8 86.0 119.4 Tabora Urban 14.6 4.1 3.8 0.8 13.5 8.2 14.0 14.5 9.4 13.3 13.9 5.0 Total 27.0 4.0 14.1 3.0 43.8 10.1 54.4 113.3 11.8 20.1 42.6 88.4 Regional Capital 113.3 Tarmac Roads 88.4 District Capital 54.4 Hospitals 43.8 Tertiary Market 42.6 Secondary Schools 27.0 Secondary Market 20.1 All weather roads 14.1 Primary Markets 11.8 Health Clinics 10.1 Primary Schools 4.0 Feeder Roads 3.0 33 01a Mean Distances from Holders Dwellings to Infrastructures and Services by District District Mean Distance to Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 241 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 297 0.5 1,216 1.9 11,463 17.5 26,739 40.8 25,850 39.4 65,566 19.4 Igunga 1,097 2.4 2,200 4.9 16,608 36.8 13,312 29.5 11,924 26.4 45,141 13.6 Uyui 2,589 6.3 1,233 3.0 5,154 12.5 5,404 13.1 26,937 65.2 41,318 43.7 Urambo 346 0.6 869 1.6 14,530 26.8 13,718 25.3 24,657 45.6 54,120 22.4 Sikonge 99 0.5 99 0.5 2,201 11.3 3,991 20.5 13,124 67.3 19,514 67.3 Tabora Urban 54 0.5 227 2.2 3,127 30.5 5,054 49.3 1,796 17.5 10,258 14.6 Total 4,482 1.9 5,845 2.5 53,082 22.5 68,218 28.9 104,289 44.2 235,917 27.0 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 10,622 16.2 17,491 26.7 20,752 31.7 13,415 20.5 3,286 5.0 65,566 6.7 Igunga 12,436 27.5 9,625 21.3 10,961 24.3 4,915 10.9 7,204 16.0 45,141 9.1 Uyui 9,128 22.1 5,959 14.4 13,617 33.0 7,098 17.2 5,515 13.3 41,318 11.8 Urambo 12,171 22.5 8,898 16.4 15,351 28.4 5,021 9.3 12,680 23.4 54,120 19.0 Sikonge 5,194 26.6 1,753 9.0 5,536 28.4 2,346 12.0 4,686 24.0 19,514 47.1 Tabora Urban 4,947 48.2 3,104 30.3 1,819 17.7 361 3.5 26 0.3 10,258 3.8 Total 54,498 23.1 46,830 19.9 68,036 28.8 33,157 14.1 33,397 14.2 235,917 14.1 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 28,747 43.8 23,782 36.3 11,558 17.6 883 1.3 596 0.9 65,566 3.2 Igunga 22,550 50.0 12,717 28.2 8,292 18.4 1,365 3.0 217 0.5 45,141 2.1 Uyui 24,633 59.6 9,627 23.3 5,846 14.1 208 0.5 1,004 2.4 41,318 4.5 Urambo 23,105 42.7 15,973 29.5 10,717 19.8 3,086 5.7 1,239 2.3 54,120 3.2 Sikonge 10,413 53.4 4,242 21.7 4,125 21.1 637 3.3 97 0.5 19,514 2.0 Tabora Urban 6,462 63.0 3,094 30.2 675 6.6 27 0.3 0 0.0 10,258 0.8 Total 115,910 49.1 69,435 29.4 41,213 17.5 6,205 2.6 3,154 1.3 235,917 3.0 1 - 2.9 km 3 - 9 9 km District District Distance to ALL Wealther Road Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km 33.01d: Number of Households by Distance to Feeder Road and District for 2002/03 Agriculture Year Total Number of Households Mean Distance Total Mean Distance Distance to Feeder Road 10 - 19.9 km Above 20 km District Less than 1 km 33.01b: Mean distances from holders dwellings to Secondary Schools by District for 2002/03 Agriculture Year 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 Agriculture Year Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Mean Distance Total Number of Households Distance to Secondary School Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 242 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 1,414 2.2 689 1.1 6,271 9.6 17,180 26.2 40,012 61.0 65,566 31.4 Igunga 788 1.7 210 0.5 8,632 19.1 11,104 24.6 24,408 54.1 45,141 25.2 Uyui 712 1.7 0 0.0 0 0.0 2,597 6.3 38,010 92.0 41,318 61.1 Urambo 0 0.0 422 0.8 6,731 12.4 6,137 11.3 40,829 75.4 54,120 58.4 Sikonge 0 0.0 0 0.0 2,003 10.3 4,338 22.2 13,173 67.5 19,514 67.0 Tabora Urban 157 1.5 122 1.2 2,751 26.8 5,305 51.7 1,922 18.7 10,258 13.5 Total 3,071 1.3 1,443 0.6 26,388 11.2 46,661 19.8 158,354 67.1 235,917 43.8 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 5,039 7.7 15,275 23.3 27,239 41.5 13,233 20.2 4,780 7.3 65,566 9.8 Igunga 4,983 11.0 7,712 17.1 20,363 45.1 11,855 26.3 229 0.5 45,141 6.4 Uyui 2,826 6.8 5,916 14.3 18,084 43.8 8,807 21.3 5,684 13.8 41,318 18.1 Urambo 5,100 9.4 8,378 15.5 26,816 49.5 9,863 18.2 3,963 7.3 54,120 8.9 Sikonge 2,257 11.6 2,304 11.8 8,625 44.2 5,002 25.6 1,326 6.8 19,514 7.8 Tabora Urban 688 6.7 1,838 17.9 6,539 63.7 1,122 10.9 71 0.7 10,258 8.2 Total 20,894 8.9 41,423 17.6 107,666 45.6 49,881 21.1 16,052 6.8 235,917 10.1 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 8,610 13.1 30,783 46.9 25,136 38.3 1,037 1.6 0 0.0 65,566 2.7 Igunga 7,097 15.7 23,066 51.1 14,641 32.4 221 0.5 116 0.3 45,141 2.4 Uyui 7,023 17.0 14,164 34.3 15,643 37.9 3,162 7.7 1,325 3.2 41,318 5.8 Urambo 10,824 20.0 21,594 39.9 18,316 33.8 2,651 4.9 735 1.4 54,120 5.7 Sikonge 5,911 30.3 6,191 31.7 5,199 26.6 1,792 9.2 420 2.2 19,514 3.5 Tabora Urban 2,532 24.7 4,571 44.6 2,915 28.4 186 1.8 54 0.5 10,258 4.1 Total 41,996 17.8 100,369 42.5 81,851 34.7 9,050 3.8 2,650 1.1 235,917 4.0 Above 20 km Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Total Number of Households Mean Distance District 33.01g: Number of Households by Distance to Primary School by District for 2002/03 Agriculture Year Distance to Primary School Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 Agriculture Year Total Number of Households Mean Distance District Distance to Health Clinic Distance to Hospital Less than 1 km 1 - 2.9 km 33.01e Number of Households by Distance to Hospital by District for 2002/03 Agriculture Year Total Number of Households Mean Distance District 3 - 9 9 km 10 - 19.9 km Above 20 km Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 243 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 150 0.2 150 0.2 296 0.5 268 0.4 64,702 98.7 65,566 105.8 Igunga 114 0.3 0 0.0 338 0.7 0 0.0 44,689 99.0 45,141 163.9 Uyui 600 1.5 0 0.0 0 0.0 203 0.5 40,515 98.1 41,318 68.5 Urambo 757 1.4 0 0.0 126 0.2 623 1.2 52,613 97.2 54,120 125.8 Sikonge 0 0.0 0 0.0 195 1.0 96 0.5 19,224 98.5 19,514 133.4 Tabora Urban 107 1.0 53 0.5 2,766 27.0 5,407 52.7 1,925 18.8 10,258 14.5 Total 1,729 0.7 203 0.1 3,721 1.6 6,595 2.8 223,668 94.8 235,917 113.3 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 10,836 16.5 150 0.2 3,869 5.9 2,045 3.1 48,665 74.2 65,566 69.2 Igunga 9,442 20.9 223 0.5 112 0.2 107 0.2 35,257 78.1 45,141 107.1 Uyui 1,008 2.4 0 0.0 308 0.7 97 0.2 39,904 96.6 41,318 68.6 Urambo 10,046 18.6 0 0.0 126 0.2 0 0.0 43,949 81.2 54,120 115.8 Sikonge 2,812 14.4 0 0.0 99 0.5 0 0.0 16,603 85.1 19,514 119.4 Tabora Urb 7,290 71.1 60 0.6 1,309 12.8 1,001 9.8 598 5.8 10,258 5.0 Total 41,434 17.6 433 5,824 2.5 3,250 1.4 184,976 78.4 235,917 88.4 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 6,595 10.1 9,070 13.8 30,342 46.3 15,123 23.1 4,437 6.8 65,566 8.5 Igunga 5,997 13.3 7,247 16.1 22,044 48.8 8,035 17.8 1,818 4.0 45,141 7.0 Uyui 4,108 9.9 5,465 13.2 15,503 37.5 8,341 20.2 7,901 19.1 41,318 13.1 Urambo 5,628 10.4 5,384 9.9 22,498 41.6 9,163 16.9 11,446 21.1 54,120 13.3 Sikonge 2,588 13.3 1,902 9.7 8,732 44.7 3,561 18.2 2,732 14.0 19,514 28.6 Tabora Urb 1,807 17.6 289 2.8 3,525 34.4 3,522 34.3 1,115 10.9 10,258 9.4 Total 26,723 11.3 29,357 12.4 102,643 43.5 47,745 20.2 29,449 12.5 235,917 11.8 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 715 1.1 4,614 7.0 14,443 22.0 28,418 43.3 17,376 26.5 65,566 15.9 Igunga 2,329 5.2 3,251 7.2 18,272 40.5 7,248 16.1 14,040 31.1 45,141 14.9 Uyui 1,620 3.9 1,014 2.5 5,269 12.8 5,844 14.1 27,571 66.7 41,318 32.4 Urambo 2,468 4.6 4,689 8.7 18,748 34.6 14,118 26.1 14,098 26.0 54,120 19.4 Sikonge 632 3.2 1,227 6.3 6,456 33.1 4,212 21.6 6,987 35.8 19,514 25.8 Tabora Urb 284 2.8 273 2.7 2,989 29.1 4,648 45.3 2,065 20.1 10,258 13.3 Total 8,048 3.4 15,068 6.4 66,176 28.1 64,487 27.3 82,137 34.8 235,917 20.1 33.01h Number of Households by Distance to Regional Capital and District for 2002/03 Agriculture Year Distance to Regional Capital Total Mean Distance Distance to Secondary Market District District District District 33.01k Number of Households by Distance to Secondary Marketand District for 2002/03 Agriculture Year 33.01j Number of Households by Distance to Primary Market and District for 2002/03 Agriculture Year 33.01i Number of Households by Distance to Tarmac Road and District for 2002/03 Agriculture Year Distance to Tarmac Road Distance to Primary Market Total 10 - 19.9 km Mean Distance Total Mean Distance Total Mean Distance 3 - 9 9 Less than 1 km 1 - 2.9 km 3 - 9 9 km 3 - 9 9 Above 20 km Above 20 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Less than 1 1 - 2.9 10 - 19.9 10 - 19.9 Above 20 Less than 1 1 - 2.9 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 244 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 1,389 2.1 1,676 2.6 10,153 15.5 13,920 21.2 38,428 58.6 65,566 26.6 Igunga 1,921 4.3 2,349 5.2 8,900 19.7 9,505 21.1 22,467 49.8 45,141 27.0 Uyui 1,112 2.7 202 0.5 1,536 3.7 368 0.9 38,099 92.2 41,318 64.4 Urambo 2,867 5.3 978 1.8 7,368 13.6 6,246 11.5 36,661 67.7 54,120 48.3 Sikonge 828 4.2 294 1.5 3,879 19.9 1,835 9.4 12,678 65.0 19,514 86.0 Tabora Urb 242 2.4 78 0.8 2,807 27.4 5,127 50.0 2,004 19.5 10,258 13.9 Total 8,359 3.5 5,576 2.4 34,643 14.7 37,001 15.7 150,337 63.7 235,917 42.6 Total Mean Distance 33.01l Number of Households by Distance to Tertiary Marketand District for 2002/03 Agriculture Year Distance to Tertiary Market District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 245 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 689 1.4 7,815 16.2 6,894 14.3 4,277 8.9 28,498 59.2 48,173 Igunga 1,265 1.8 6,963 9.7 6,389 8.9 56,429 78.6 771 1.1 71,817 Uyui 2,074 16.0 4,533 35.0 1,336 10.3 2,585 20.0 2,414 18.7 12,942 Urambo 1,125 10.2 4,099 37.3 1,966 17.9 2,678 24.4 1,112 10.1 10,980 Sikonge 1,299 14.1 2,608 28.2 1,307 14.2 3,208 34.8 809 8.8 9,231 Tabora Urban 365 8.4 2,770 63.4 809 18.5 373 8.5 53 1.2 4,371 Total 6,818 4.3 28,787 18.3 18,702 11.9 69,550 44.2 33,657 21.4 157,514 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 689 4.9 5,246 37.0 3,219 22.7 290 2.1 4,718 33.3 14,163 Igunga 919 5.3 4,154 24.1 4,403 25.5 7,548 43.8 217 1.3 17,242 Uyui 1,146 18.9 3,596 59.2 916 15.1 209 3.4 211 3.5 6,078 Urambo 624 11.2 3,357 60.0 875 15.6 425 7.6 315 5.6 5,597 Sikonge 244 6.2 2,082 53.1 960 24.5 591 15.1 43 1.1 3,922 Tabora Urban 73 3.2 1,857 82.8 232 10.4 80 3.6 0 0.0 2,242 Total 3,696 7.5 20,293 41.2 10,605 21.5 9,144 18.6 5,506 11.2 49,243 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 424 7.8 431 7.9 4,566 84.2 5,421 Igunga 0 0.0 0 0.0 108 1.0 10,605 99.0 0 0.0 10,713 Uyui 200 9.7 417 20.2 0 0.0 1,132 54.8 317 15.3 2,066 Urambo 0 0.0 248 25.4 124 12.7 508 52.0 96 9.9 976 Sikonge 97 7.1 142 10.4 50 3.6 940 68.6 142 10.3 1,371 Tabora Urban 106 25.3 132 31.4 102 24.2 54 12.8 27 6.4 421 Total 404 1.9 939 4.5 808 3.9 13,670 65.2 5,148 24.5 20,968 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total Number of Households Very Good Good Average Poor No good Satisfaction of Using Extension Center Good Average Poor No good Total Number of Households 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year Satisfaction of Using Research Station Total Number of Households Very Good Good Average Poor No good Very Good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 246 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 424 7.8 290 5.4 4,707 86.8 5,421 Igunga 0 0.0 0 0.0 216 2.0 10,487 96.0 224 2.0 10,927 Uyui 204 17.8 106 9.2 0 0.0 413 36.1 422 36.9 1,145 Urambo 0 0.0 0 0.0 96 12.1 412 51.6 289 36.3 797 Sikonge 518 91.3 0 0.0 0 0.0 50 8.7 0 0.0 567 Tabora Urban 53 29.0 26 14.3 50 27.4 54 29.3 0 0.0 183 Total 775 4.1 132 0.7 787 4.1 11,706 61.5 5,642 29.6 19,041 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 398 5.6 1,642 22.9 5,126 71.5 7,166 Igunga 116 1.1 115 1.1 223 2.1 10,259 94.8 108 1.0 10,820 Uyui 106 6.8 97 6.3 209 13.5 310 20.0 830 53.5 1,552 Urambo 126 6.5 247 12.8 501 26.0 738 38.3 315 16.4 1,927 Sikonge 50 3.1 191 11.8 198 12.3 1,032 64.0 142 8.8 1,612 Tabora Urban 27 9.0 20 6.7 169 57.5 79 26.8 0 0.0 294 Total 424 1.8 669 2.9 1,698 7.3 14,059 60.2 6,521 27.9 23,372 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 1,444 18.8 1,231 16.1 422 5.5 4,566 59.6 7,663 Igunga 116 1.2 0 0.0 217 2.2 9,607 95.5 114 1.1 10,055 Uyui 208 22.0 106 11.2 0 0.0 209 22.2 422 44.7 945 Sikonge 50 33.8 0 0.0 0 0.0 0 0.0 97 66.2 147 Tabora Urban 0 0.0 13 11.3 78 66.0 27 22.7 0 0.0 118 Total 373 2.0 1,563 8.3 1,526 8.1 10,266 54.2 5,200 27.5 18,928 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % 6818 4 28787 18 18702 12 69550 44 33657 21 3696 8 20293 41 10605 22 9144 19 5506 11 404 2 939 5 808 4 13670 65 5148 25 775 4 132 1 787 4 11706 62 5642 30 424 2 669 3 1698 7 14059 60 6521 28 373 2 1563 8 1526 8 10266 54 5200 28 3 6 8 47 23 Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year Satisfaction of Using Plant Protection Lab Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year Satisfaction of Using Land Registration Office Very Good Good Average Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center Very Good Good District District District Total Total Satisfaction of Using Livestock Development Center Total Extension Centre Research Station Land Registration Office 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and Type of Servive, 2002/03 Agricultural Year Veterinary Clinic Livestock Development Centre OVERALL % Plant Protection Lab Satisfaction of Using Livestock Development Center Very Good Good Average Poor No good Type of Service Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 247 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 248 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Nzega 13,083 446 51,613 424 0 65,566 Igunga 10,807 558 33,323 453 0 45,141 Uyui 5,764 708 34,114 731 0 41,318 Urambo 5,625 253 47,921 204 118 54,120 Sikonge 4,406 247 14,761 99 0 19,514 Tabora Urban 229 144 9,810 75 0 10,258 Total 39,914 2,357 191,542 1,987 118 235,917 % 16.9 1.0 81.2 0.8 0.0 100.0 District Number of rooms Iron Sheets Tiles Concrete Asbestos Grass/ Leaves Grass & Mud Other Total Nzega 2 7,644 447 0 0 50,779 6,695 0 65,566 Igunga 2 5,935 201 0 445 13,968 24,269 323 45,141 Uyui 3 6,684 300 92 106 33,359 587 190 41,318 Urambo 3 5,875 253 0 0 45,166 2,701 124 54,120 Sikonge 2 4,006 99 46 96 14,622 645 0 19,514 Tabora Urban 3 2,336 39 104 95 7,367 317 0 10,258 Total 2 32,481 1,339 243 741 165,263 35,213 637 235,917 % 13.8 0.6 0.1 0.3 70.1 14.9 0.3 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 34,533 27 21,466 17 21,841 17 31,874 25 11,363 9 5,645 4.5 126,723 35.8 Landline Phone 0 0 0 0 201 55 0 0 147 40 20 5.4 368 0.1 Mobile Phone 300 13 444 19 1,135 49 0 0 146 6 310 13.3 2,336 0.7 Iron 10,079 24 5,435 13 8,412 20 11,467 27 4,856 12 1,822 4.3 42,071 11.9 Wheelbarrow 2,470 19 4,941 39 2,571 20 568 4 1,425 11 696 5.5 12,671 3.6 Bicycle 47,255 29 32,427 20 27,587 17 38,059 23 12,612 8 6,597 4.0 164,536 46.5 Vehicle 1,045 32 452 14 1,305 41 222 7 98 3 93 2.9 3,214 0.9 Television/Video 574 27 780 37 503 24 0 0 193 9 77 3.6 2,127 0.6 Total Number of Households 96,257 27 65,945 19 63,554 18 82,190 23 30,840 9 15,260 4.3 354,046 100.0 Sikonge Tabora Urban 34.1: Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year Type of Toilet District 34.2: Number of hoseholds Reporting AverageNumber of Rooms and Type of Roofing Materials by District, 2002/03 Agricultural Year 34.3: Number of Agricultural Households by Type of Owned Assets and District During 2002/03 Agricultural Year District Total Type of Owned Asset Nzega Igunga Uyui Urambo Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 249 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 147 13.7 648 60.3 205 19.0 0 0.0 0 0.0 75 7.0 1,075 0.5 Solar 150 43.4 0 0.0 98 28.3 0 0.0 98 28.3 0 0.0 346 0.1 Gas (Biogas) 0 0.0 0 0.0 102 67.6 0 0.0 49 32.4 0 0.0 151 0.1 Hurricane Lamp 7,474 31.5 4,126 17.4 3,237 13.6 5,276 22.2 2,257 9.5 1,392 5.9 23,763 10.1 Pressure Lamp 2,368 29.4 1,466 18.2 1,243 15.4 1,223 15.2 1,409 17.5 342 4.3 8,051 3.4 Wick Lamp 54,399 27.6 36,769 18.6 35,935 18.2 46,530 23.6 15,270 7.7 8,308 4.2 197,211 83.6 Candles 438 90.5 0 0.0 0 0.0 0 0.0 0 0.0 46 9.5 484 0.2 Firewood 441 9.4 2,132 45.5 499 10.6 1,091 23.3 430 9.2 94 2.0 4,687 2.0 Other 149 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 149 0.1 Total 65,566 27.8 45,141 19.1 41,318 17.5 54,120 22.9 19,514 8.3 10,258 4.3 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 148 59.2 0 0.0 102 40.8 0 0.0 0 0.0 0 0.0 250 0.1 Solar 0 0.0 0 0.0 103 67.6 0 0.0 49 32.4 0 0.0 152 0.1 Bottled Gas 149 26.4 0 0.0 211 37.6 126 22.5 49 8.7 27 4.8 562 0.2 Parraffin / Kerocine 2,553 91.0 107 3.8 98 3.5 0 0.0 49 1.7 0 0.0 2,807 1.2 Charcoal 1,655 26.3 1,296 20.6 1,186 18.8 1,219 19.4 685 10.9 258 4.1 6,299 2.7 Firewood 60,187 26.9 43,391 19.4 39,303 17.6 52,418 23.4 18,487 8.3 9,947 4.4 223,732 94.8 Crop Residues 574 31.7 347 19.1 315 17.3 357 19.7 195 10.7 27 1.5 1,814 0.8 Livestock Dung 300 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 300 0.1 Total 65,566 27.8 45,141 19.1 41,318 17.5 54,120 22.9 19,514 8.3 10,258 4.3 235,917 100.0 Sikonge 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting and District During 2002/03 Agriculture Year Nzega Igunga Uyui Urambo Uyui Urambo Sikonge Tabora Urb District District Total 34.5: Number of Agricultural Households by Main Source of Energy for Cooking and District During 2002/03 Agriculture Year Tabora Urban Main Source of Energy for Lighting District Nzega Igunga Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 250 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 1,489 224 1,932 742 144 602 Dry 1,489 0 1,228 867 0 609 Wet 5,422 2,240 3,501 4,419 1,388 2,460 Dry 5,332 1,677 3,489 4,062 1,340 2,462 Wet 989 457 92 370 335 255 Dry 1,135 564 0 617 335 328 Wet 41,951 15,651 34,815 45,514 14,834 6,477 Dry 42,294 15,909 35,052 45,998 15,175 6,382 Wet 6,175 1,813 102 1,677 2,423 265 Dry 11,940 5,202 206 1,706 2,571 292 Wet 1,886 9,542 668 613 142 79 Dry 2,174 16,038 1,241 623 92 159 Wet 409 0 106 235 0 27 Dry 150 0 0 0 0 0 Wet 6,342 11,881 102 549 50 93 Dry 0 4,017 102 248 0 26 Wet 901 3,333 0 0 198 0 Dry 1,051 1,734 0 0 0 0 Total Agricultural Households per District 65,566 45,141 41,318 54,120 19,514 10,258 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 2 0 5 1 1 6 Dry 2 0 3 2 0 6 Wet 8 5 8 8 7 24 Dry 8 4 8 8 7 24 Wet 2 1 0 1 2 2 Dry 2 1 0 1 2 3 Wet 64 35 84 84 76 63 Dry 65 35 85 85 78 62 Wet 9 4 0 3 12 3 Dry 18 12 0 3 13 3 Wet 3 21 2 1 1 1 Dry 3 36 3 1 0 2 Wet 1 0 0 0 0 0 Dry 0 0 0 0 0 0 Wet 10 26 0 1 0 1 Dry 0 9 0 0 0 0 Wet 1 7 0 0 1 0 Dry 2 4 0 0 0 0 District District 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District During 2002/03 Agriculture Year Source District 34.7: Proportion of Agricultural Households by Maion Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Season Season Other Uncovered Rainwater Catchment Covered Rainwater Catchment Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well Protected Well Piped Water Piped Water Other Uncovered Rainwater Catchment Covered Rainwater Catchment Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 251 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 5,690 3,253 4,659 15,745 2,690 1,698 Dry 3,957 1,231 3,440 11,882 1,809 1,616 Wet 10,551 4,716 10,067 9,635 2,811 1,335 Dry 6,184 3,005 8,018 7,223 2,415 1,203 Wet 3,516 2,822 2,955 2,679 1,744 207 Dry 2,642 1,961 3,047 2,651 1,746 206 Wet 18,155 7,637 8,720 9,823 5,771 2,942 Dry 11,117 2,969 6,922 8,632 5,232 2,765 Wet 20,922 16,694 10,372 11,084 4,184 2,677 Dry 23,335 9,913 10,743 15,224 4,625 2,747 Wet 5,118 5,749 3,180 3,446 1,924 1,150 Dry 10,641 7,540 3,806 5,294 2,709 1,097 Wet 1,014 2,926 943 1,353 241 212 Dry 4,182 9,924 4,244 2,244 832 453 Wet 599 1,345 422 355 99 37 Dry 2,922 6,090 1,098 970 97 171 Wet 0 0 0 0 49 0 Dry 587 2,507 0 0 49 0 Season Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 9 7 11 29 14 17 Dry 6 3 8 22 9 16 Wet 16 10 24 18 14 13 Dry 9 7 19 13 12 12 Wet 5 6 7 5 9 2 Dry 4 4 7 5 9 2 Wet 28 17 21 18 30 29 Dry 17 7 17 16 27 27 Wet 32 37 25 20 21 26 Dry 36 22 26 28 24 27 Wet 8 13 8 6 10 11 Dry 16 17 9 10 14 11 Wet 2 6 2 3 1 2 Dry 6 22 10 4 4 4 Wet 1 3 1 1 1 0 Dry 4 13 3 2 0 2 Wet 0 0 0 0 0 0 Dry 1 6 0 0 0 0 34.8: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agriculture Year 34.9: Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year 3 - 4.99 Km 2 - 2.99 Km 1 - 1.99 Km 500 - 999 m 300 - 499 m 100 - 299 m Less than 100m Season 1 - 1.99 Km 500 - 999 m 300 - 499 m Source 100 - 299 m Less than 100m 10Km and above 5 - 9.99 Km 3 - 4.99 Km 2 - 2.99 Km District 10Km and above 5 - 9.99 Km District Distance to Main Source of Drinking Water Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 252 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 2,814 447 1,026 6,457 446 304 Dry 1,939 116 1,012 4,390 198 271 Wet 15,112 4,483 9,898 16,552 4,468 3,061 Dry 8,706 1,020 7,744 13,906 3,772 2,741 Wet 13,653 3,391 5,222 6,413 2,749 1,132 Dry 8,891 1,004 4,726 5,678 2,701 1,157 Wet 17,693 11,726 10,768 11,221 5,733 3,085 Dry 13,704 4,688 10,268 9,877 4,949 3,027 Wet 5,818 5,627 3,329 1,084 634 517 Dry 6,651 3,286 2,363 1,443 779 568 Wet 3,822 2,219 3,255 6,723 1,597 545 Dry 2,922 1,211 2,867 6,271 1,105 443 Wet 6,654 17,248 7,819 5,670 3,887 1,614 Dry 22,752 33,816 12,336 12,555 6,009 2,052 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 4 1 2 12 2 3 Dry 3 0 2 8 1 3 Wet 23 10 24 31 23 30 Dry 13 2 19 26 19 27 Wet 21 8 13 12 14 11 Dry 14 2 11 10 14 11 Wet 27 26 26 21 29 30 Dry 21 10 25 18 25 30 Wet 9 12 8 2 3 5 Dry 10 7 6 3 4 6 Wet 6 5 8 12 8 5 Dry 4 3 7 12 6 4 Wet 10 38 19 10 20 16 Dry 35 75 30 23 31 20 34.10: Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year 34.11: Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year District Season above one Hour 50 - 59 Minutes 40 - 49 Minutes 30 - 39 Minutes 20 - 29 Minutes 10 - 19 Minutes Less than 10 District Season District Less than 10 10 - 19 Minutes 20 - 29 Minutes District 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 253 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 1,190 16 2,202 29 1,934 26 733 10 914 12 519 7 7,492 3.2 Two 19,042 21 8,983 10 14,990 17 32,149 36 8,737 10 5,151 6 89,052 37.7 Three 44,886 33 33,151 24 23,789 17 21,130 15 9,669 7 4,589 3 137,213 58.2 Four 447 21 804 37 605 28 109 5 194 9 0 0 2,159 0.9 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 19,244 24 16,501 21 16,334 20 17,902 22 6,179 8 3,570 4 79,730 33.8 One 29,694 38 13,859 18 10,558 14 15,015 19 4,649 6 3,777 5 77,552 32.9 Two 11,603 24 8,669 18 8,546 17 13,197 27 4,870 10 1,952 4 48,837 20.7 Three 2,921 17 2,824 16 3,154 18 5,920 34 2,053 12 632 4 17,504 7.4 Four 1,538 21 1,825 25 1,725 23 1,349 18 771 10 204 3 7,411 3.1 Five 290 10 778 27 693 24 361 13 658 23 96 3 2,876 1.2 Six 0 0 579 70 0 0 125 15 95 12 26 3 825 0.3 Seven 277 23 107 9 308 26 251 21 240 20 0 0 1,182 0.5 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 34.12: Number of Agricultural Households by Number of Meals the Household NormallyTook by District District Tabora Urban Sikonge Urambo 34-13: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District Uyui Igunga Nzega District Number of Days Number of Meals per Day Total Total Tabora Urban Uyui Igunga Nzega Sikonge Urambo Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 254 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 37,526 32 31,863 27 17,811 15 20,445 17 8,961 8 2,116 2 118,722 50.3 One 23,718 43 6,506 12 7,331 13 11,844 22 2,769 5 2,712 5 54,881 23.3 Two 2,182 8 4,320 15 8,515 29 8,381 29 3,043 10 2,584 9 29,025 12.3 Three 696 4 1,774 11 4,455 28 5,680 35 2,088 13 1,448 9 16,141 6.8 Four 1,298 13 678 7 1,649 17 3,881 39 1,525 15 834 8 9,865 4.2 Five 146 3 0 0 1,029 21 2,697 54 786 16 353 7 5,011 2.1 Six 0 0 0 0 211 26 379 46 98 12 133 16 822 0.3 Seven 0 0 0 0 315 22 813 56 244 17 77 5 1,450 0.6 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 29,554 28 16,357 15 19,873 19 27,117 26 10,285 10 2,473 2 105,659 44.8 Seldom 22,394 29 17,097 22 11,882 16 16,042 21 4,819 6 4,212 6 76,446 32.4 Sometimes 4,879 29 3,466 20 2,143 13 4,221 25 1,411 8 834 5 16,953 7.2 Often 4,761 23 3,742 18 4,970 24 3,799 18 1,748 8 1,591 8 20,610 8.7 Always 3,978 24 4,480 28 2,450 15 2,942 18 1,251 8 1,148 7 16,249 6.9 Total 65,566 45,141 41,318 54,120 19,514 10,258 235,917 100.0 Igunga Nzega 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceeding Week by District 34.15: Number of Households Reporting the status of Food ASatisfaction of the Household during the Preceeding Year by District District District Status of Food Satisfaction Number of Days Tabora Urb Sikonge Total Uyui Igunga Nzega Total Tabora Urb Sikonge Urambo Urambo Uyui Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 255 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 17,562 33 6,988 13 8,802 16 14,250 27 4,926 9 1,225 2 53,753 22.8 Sale of Livestock 9,875 41 8,774 36 2,725 11 1,316 5 1,155 5 383 2 24,229 10.3 Sale of Livestock Products 300 12 223 9 414 17 718 29 390 16 444 18 2,489 1.1 Sales of Cash Crops 985 3 8,719 23 7,402 20 16,197 43 4,013 11 412 1 37,727 16.0 Sale of Forest Products 7,218 41 1,551 9 3,147 18 1,328 7 2,884 16 1,658 9 17,786 7.5 Business Income 5,611 20 3,765 13 6,044 22 8,801 31 1,507 5 2,223 8 27,950 11.8 Wages & Salaries in Cash 1,705 32 998 19 727 14 794 15 489 9 576 11 5,288 2.2 Other Casual Cash Earnings 14,834 30 12,347 25 8,586 17 8,037 16 3,239 7 2,265 5 49,309 20.9 Cash Remittance 5,555 39 1,433 10 3,158 22 2,332 16 770 5 930 7 14,177 6.0 Fishing 296 57 0 0 0 0 107 21 92 18 26 5 522 0.2 Other 1,175 53 343 15 313 14 239 11 49 2 117 5 2,236 0.9 not applicable 451 100 0 0 0 0 0 0 0 0 0 0 451 0.2 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Total Main Source of Cash Income 34.16: Number of Households by Main Source of Income and District During 2002/03 Agriculture Year District Tabora Urban Sikonge Urambo Uyui Igunga Nzega Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 256 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 7,644 24 5,935 18 6,684 21 5,875 18 4,006 12 2,336 7 32,481 13.8 Tiles 447 33 201 15 300 22 253 19 99 7 39 3 1,339 0.6 Concrete 0 0 0 0 92 38 0 0 46 19 104 43 243 0.1 Asbestos 0 0 445 60 106 14 0 0 96 13 95 13 741 0.3 Grass / Leaves 50,779 31 13,968 8 33,359 20 45,166 27 14,622 9 7,367 4 165,263 70.1 Grass & Mud 6,695 19 24,269 69 587 2 2,701 8 645 2 317 1 35,213 14.9 Other 0 0 323 51 190 30 124 19 0 0 0 0 637 0.3 Total Number of Households 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 34.17: Number of Households by Type of Roofing Materials and District During 2002/03 Agriculture Year Total Roofing Materials District Tabora Urb Sikonge Urambo Uyui Igunga Nzega Tanzania Agriculture Sample Census - 2003 Tabora 257 APPENDIX III QUESTIONNAIRES Appendix III 258 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 259 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 260 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 261 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 262 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 263 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 264 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 265 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 266 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 266 267 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 268 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 269 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 270 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 271 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 272 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 273 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 274 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 275 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 276 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 277 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 278 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 279 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 280 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source \"a\" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 281 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 282 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 283 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 284 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 285 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 286 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 287 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 288 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 289 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 290 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 291 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 292 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 293 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 294 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 295 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 296 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 297 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 298 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 299 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 300 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 301 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 302 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 303 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":193,"cells":{"data":{"kind":"string","value":"# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA WIZARA YA KILIMO MAOMBI YA MAFUNZO YA KILIMO KWA VIJANA Serikali kupitia Wizara ya Kilimo inatekeleza Programu ya Kuwezesha Ushiriki wa Vijana katika Kilimo Biashara (Building a Better Tomorrow Youth Initiative for Agribusiness (BBT-YIA). Programu hii inatarajiwa kuongeza ajira kwa vijana kufikia milioni tatu (3) na kuongeza ukuaji wa sekta ya kilimo hadi kufikia asilimia10 ifikapo mwaka 2030 (Ajenda 10/30). Kupitia BBT, Wizara inaratibu uanzishwaji wa mashamba makubwa ya pamoja (Block Farms) kwa ajili ya vijana. Mradi huu utatekelezwa nchi nzima na vijana wote wenye sifa watapata fursa ya kufanya kilimo biashara katika mnyororo wa thamani. Kwa kuanzia, Wizara imetambua mashamba yenye jumla ya ekari 162,492 katika Wilaya ya Chunya (Mbeya); Bahi na Chamwino (Dodoma); na Misenyi na Karagwe (Kagera); na Uvinza na Kasulu (Kigoma). Wizara inatangaza fursa za mafunzo ya kilimo biashara kwa awamu ya kwanza kwa vijana katika Kituo cha Mafunzo ya Kilimo Bihawana mkoani Dodoma. Mafunzo hayo yanatarajiwa kuanza tarehe 15 Februari 2023 ambapo vijana watapatiwa mafunzo kwa muda wa miezi mitatu. Baada ya mafunzo hayo, wahitimu watakabidhiwa mashamba kwa ajili ya kilimo kwa taratibu na masharti yatakayoainishwa Maombi yote yatumwe kupitia kiunganishi cha bbt.kilimo.go.tz kuanzia leo tarehe 10 Januari, 2023. Mwisho wa kutuma maombi ni tarehe 30 Januari 2023 Sifa za vijana wanaotakiwa kuomba ni pamoja na:- i. Awe Mtanzania; ii. Awe na umri kati ya miaka 18 - 40; iii. Awe anapenda kufanya kilimo biashara; na iv. Awe anashiriki kwenye shughuli za kilimo. Imetolewa na: KATIBU MKUU WIZARA YA KILIMO"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":194,"cells":{"data":{"kind":"string","value":"# Extracted Content T.O.C. Tanzania Agriculture Sample Census i United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vd: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar September 2006 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vd: REGIONAL REPORT:TANGA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents........................................................................................................................................................... i Acronyms..................................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive summary.................................................................................................................................................... vii Illustrations................................................................................................................................................................. xii ENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION .................................................................................................... 1 1.1 Introduction.................................................................................................................................................. 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area..................................................................................................................................................... 1 1.4 Climate.......................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Population..................................................................................................................................................... 1 1.6 Socio-economic Indicators........................................................................................................................... 2 PART II: INTRODUCTION.................................................................................................................................. 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture........................................... 3 2.2 Census Objectives ........................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................ 4 2.4 Legal Authority of the National Sample Census of Agriculture.............................................................. 5 2.5 Reference Period.......................................................................................................................................... 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 5 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 7 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparations.............................................................................................. 9 - Data Quality............................................................................................................................. 10 2.7 Funding Arrangements........................................................................................................................ 10 PART III: CENSUS RESULTS AND ANALYSIS .............................................................................................. 11 3.1 Holding Characteristics............................................................................................................................. 11 3.1.1 Type of Holdings........................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income........................................................................................ 11 3.1.3 Sex and Age of Heads of Households ........................................................................................... 11 3.1.4 Number of Household Members ................................................................................................... 15 3.1.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 - Literacy Rates for Heads of Households.................................................................................. 15 - Educational Status.................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................ 16 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.2 Land Use ................................................................................................................................................. 17 3.2.1 Area of Land Utilised .................................................................................................................... 17 3.2.2 Types of Land use.......................................................................................................................... 18 3.3 Annual Crops and Vegetable Production ................................................................................................ 18 3.3.1 Area Planted .................................................................................................................................. 18 3.3.2 Crop Importance............................................................................................................................ 20 3.3.3 Crop Types .................................................................................................................................... 20 3.3.4 Cereal Crop Production ................................................................................................................. 22 3.3.4.1 Maize ........................................................................................................................... 23 3.3.4.2 Paddy ........................................................................................................................... 23 3.3.4.3 Other Cereals ............................................................................................................... 26 3.3.5 Roots and Tuber Crops Production................................................................................................ 26 3.3.5.1 Cassava........................................................................................................................ 27 3.3.5.2 Irish Potatoes ............................................................................................................... 28 3.3.6 Pulse Crops Production ................................................................................................................. 28 3.3.6.1 Beans ........................................................................................................................... 30 3.3.7 Oil Seed Production....................................................................................................................... 32 3.3.7.1 Groundnuts .................................................................................................................. 32 3.3.8 Fruits and Vegetables ..................................................................................................................... 33 3.3.8.1 Tomatoes ..................................................................................................................... 35 3.3.8.2 Cabbage ....................................................................................................................... 37 3.3.8.3 Chillies......................................................................................................................... 37 3.3.9 Other Annual Crops Production .................................................................................................... 40 3.3.9.1 Cotton ........................................................................................................................... 40 3.3.9.2 Tobacco ....................................................................................................................... 40 3.4 Permanent Crops....................................................................................................................................... 40 3.4.1 Coconuts ..................................................................................................................................... 43 3.4.2 Oranges ..................................................................................................................................... 45 3.4.3 Banana ..................................................................................................................................... 45 3.4.4 Cashew Nuts.................................................................................................................................. 45 3.5 Inputs/Implements Use.............................................................................................................................. 48 3.5.1 Methods of land clearing ................................................................................................................ 48 3.5.2 Methods of soil preparation........................................................................................................... 48 3.5.3 Improved seeds use........................................................................................................................ 50 3.5.4 Fertilizers use................................................................................................................................. 51 3.5.4.1 Farm Yard Manure Use ............................................................................................... 51 3.5.4.2 Inorganic Fertilizer Use ............................................................................................... 52 3.5.4.3 Compost Use................................................................................................................ 53 3.5.5 Pesticide Use ................................................................................................................................. 54 3.5.5.1 Insecticide Use............................................................................................................. 54 3.5.5.2 Herbicide Use .............................................................................................................. 55 3.5.5.3 Fungicide Use.............................................................................................................. 55 3.5.6 Harvesting Methods....................................................................................................................... 56 3.5.7 Threshing Methods ....................................................................................................................... 56 3.6 Irrigation ................................................................................................................................................. 56 3.6.1 Area planted with annual crops and under irrigation..................................................................... 56 3.6.2 Sources of water used for irrigation............................................................................................... 57 3.6.3 Methods of obtaining water for irrigation...................................................................................... 59 3.6.4 Methods of water application ....................................................................................................... 59 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing................................................................................................ 59 3.7.1 Crop Storage.................................................................................................................................. 59 3.7.1.1 Method of Storage ....................................................................................................... 60 3.7.1.2 Duration of Storage...................................................................................................... 60 3.7.1.3 Purpose of Storage....................................................................................................... 62 3.7.1.4 The Magnitude of Storage Loss................................................................................... 62 3.7.2 Agro processing and by-products ................................................................................................... 63 3.7.2.1 Processing Methods..................................................................................................... 63 3.7.2.2 Main Agro-processing Products .................................................................................. 63 3.7.2.3 Main use of primary processed Products..................................................................... 64 3.7.2.4 Outlet for Sale of Processed Products.......................................................................... 64 3.7.3 Crop Marketing ............................................................................................................................. 65 3.7.3.1 Main Marketing Problems ........................................................................................... 65 3.7.3.2 Reasons for Not Selling............................................................................................... 65 3.8 Access to Crop Production Services......................................................................................................... 66 3.8.1 Access to Agricultural Credits....................................................................................................... 66 3.8.1.1 Source of Agricultural Credits..................................................................................... 66 3.8.1.2 Use of Agricultural Credits.......................................................................................... 66 3.8.1.3 Reasons for not using agricultural credits.................................................................... 67 3.8.2 Crop Extension .............................................................................................................................. 67 3.8.2.1 Sources of crop extension messages............................................................................ 67 3.8.2.2 Quality of extension..................................................................................................... 69 3.9 Access to Inputs .......................................................................................................................................... 69 3.9.2 Inorganic Fertilisers ....................................................................................................................... 69 3.9.3 Improved Seeds .............................................................................................................................. 70 3.9.4 Insecticides and Fungicide.............................................................................................................. 70 3.10 Tree Planting............................................................................................................................................... 71 3.11 Irrigation and Erosion Control Facilities ............................................................................................... 72 3.12 Livestock Results........................................................................................................................................ 74 3.12.1 Cattle Production ........................................................................................................................... 74 3.12.1.1 Cattle Population ......................................................................................................... 74 3.12.1.2 Herd size...................................................................................................................... 74 3.12.1.3 Cattle Population Trend............................................................................................... 76 3.12.1.4 Improved Cattle Breeds ............................................................................................... 76 3.12.2 Goat Production............................................................................................................................. 76 3.12.2.1 Goat Population ........................................................................................................... 76 3.12.2.2 Goat Herd Size............................................................................................................. 78 3.12.2.3 Goat Breeds ................................................................................................................. 78 3.12.2.4 Goat Population Trend................................................................................................. 78 3.12.3 Sheep Production........................................................................................................................... 78 3.12.3.1 Sheep Population ......................................................................................................... 78 3.12.3.2 Sheep Population Trend............................................................................................... 80 3.12.4 Pig Production ............................................................................................................................... 80 3.12.4.1 Pig Population Trend ................................................................................................... 80 3.12.5 Chicken Production ....................................................................................................................... 82 3.12.5.1 Chicken Population...................................................................................................... 82 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5.2 Chicken Population Trend ........................................................................................... 82 3.12.5.3 Chicken Flock Size...................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers) .......................................................... 84 3.12.6 Other Livestock ............................................................................................................................. 84 3.12.7 Pests and Parasites Incidences and Control ................................................................................... 84 3.12.7.1 Deworming .................................................................................................................. 86 3.12.8 Access to Livestock Services......................................................................................................... 86 3.12.8.1 Access to livestock extension Services........................................................................ 86 3.12.8.2 Access to Veterinary Clinic......................................................................................... 86 3.12.8.3 Access to village watering points/dam ........................................................................ 87 3.12.9 Animal Contribution to Crop Production ...................................................................................... 87 3.12.9.1 Use of Draft Power ...................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure........................................................................................... 88 3.12.9.3 Use of Compost ......................................................................................................... 88 3.12.10 Fish Farming.................................................................................................................................. 88 3.13 Poverty Indicators...................................................................................................................................... 91 3.13.1 Access to Infrastructure and Other Services.................................................................................. 91 3.13.2 Type of Toilets .............................................................................................................................. 91 3.13.3 Household’s assets......................................................................................................................... 91 3.13.4 Sources of Light Energy................................................................................................................ 91 3.13.5 Sources of Energy for Cooking ..................................................................................................... 91 3.13.6 Roofing Materials.......................................................................................................................... 94 3.13.7 Access to Drink Water................................................................................................................... 94 3.13.8 Food Consumption Pattern ............................................................................................................ 95 3.13.8.1 Number of Meals per Day ........................................................................................... 95 3.13.8.2 Meat Consumption Frequencies .................................................................................. 95 3.13.8.3 Fish Consumption Frequencies.................................................................................... 95 3.13.9 Food Security................................................................................................................................. 97 3.13.10 Main Source of Cash Income ........................................................................................................ 97 PART IV: TANGA PROFILES.............................................................................................................................. 99 4.1 Region Profile.............................................................................................................................................. 99 4.2 District Profiles ......................................................................................................................................... 100 4.2.1 Lushoto......................................................................................................................................... 100 4.2.2. Korogwe ....................................................................................................................................... 102 4.2.3 Muheza ......................................................................................................................................... 104 4.2.4 Tanga............................................................................................................................................ 106 4.2.5 Pangani ......................................................................................................................................... 108 4.2.6 Handeni ........................................................................................................................................ 110 4.2.7 Kilindi........................................................................................................................................... 111 ACRONYMS Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Tanga region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Cletus P. B. Mkai The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Tanga region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Tanga region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Tanga region were 265,198 out of which 178,406 (67.3%) were involved in growing crops only, 1,477 (0.6%) rearing livestock only, 194 (0.1%) were pastoralist, and 85,121 (32%) were involved in crop production as well as livestock keeping. In summary, Tanga region had 263,527 households involved in crop production and 86,792 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances. The region has a literacy rate of 70 percent. The highest literacy rate is in Pangani district (70%) followed by Tanga district (68%) and Lushoto district (65%). Kilindi and Handeni districts have the lowest literacy rates of 44 and 53 percent respectively. The literacy rate for the heads of households in the region was 73.6 percent. The number of heads of agricultural households with formal education in Tanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Tanga region 46,351 household members (76%) were involved in one off-farm income generating activity, 34,169 (18%) involved in two off-farm income generating activities and 12,023 (6%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 524,451 ha. The regional average land area utilised for crop production per crop growing household was only 1.7 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 428,533 hectares out of which 160,820 hectares (37.5%) were planted during short rainy season and 267,713 hectares (62.5%) during long rainy season. An estimated area of 295,529 ha (69.0% of the total planted area with annual and vegetable crops) was with cereals, followed by 77,017 hectares (18.0%) of pulses, 47,614 ha (11.1%) of roots and tubers, 5,346 ha (1.2%) of fruit and vegetables, 2,564 ha (0.6%) of oil seed and 465 ha (0.1%) of cash crops. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Maize Maize is the dominant annual crop grown in Tanga region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 67 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) are cassava, Irish potatoes, cowpeas, paddy, tomatoes, green gram, groundnuts and sweet potatoes. There was a sharp increase in maize production (122%) over the period of 1997 to 1999, whereas there was a sharp decrease in maize production (46%) over the period from 2000 to 2003. The total production of maize in 2002/03 was 173,602 tonnes. The average area planted with maize per household ranged from 0.5 hectares in Lushoto District to 1.3 hectares in Kilindi District. Handeni district had the largest planted area of maize (95,688 ha) followed by Lushoto (51,118 ha), Muheza (50,778 ha), Korogwe (46,369 ha), Kilindi (32,536 ha), Pangani (7,042 ha) and Tanga (3,946 ha). Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tanga region during the long rainy season was 15,443. This represented 66 percent of the total crop growing households in Tanga Region in the long rainy season. Cassava The area planted with cassava was larger than any other root and tuber crop in Tanga in terms of planted area (7.2% of the total area planted with annual crops and vegetables) and it accounted for 64.5 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 10,852 tonnes, which amounts to 55 percent of the total fruit and vegetable production, followed by cabbage 3,472 tonnes (18%) and chilies 1,973 tonnes (10%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 62,403 hectares which is 13 percent of the area planted with annual crops in the region. The most important permanent crop is coconuts which accounts for 24 percent of the total area planted with permanent crops followed by oranges (15%), banana (13%) and cashew (13%). Improved Seeds The planted area using improved seeds was 52,089 ha which represents 13 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was 13.4 percent which is slightly higher than the corresponding percentage use for the long rainy season (12.73%). Use of Fertilizers Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 367,237 hectares representing 85.6 percent of the total planted area with annual crops. Of the planted area with fertiliser EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix application, farm yard manure was applied to 45,411 ha which represented 10.6 percent of the total planted area (73.3 % of the area planted with fertiliser application). This was followed by compost (12,491 ha, 20.1%). Inorganic fertilizers were used on a very small area and represented only 6.6 percent of the area planted with fertilizers. Irrigation In Tanga region, the area of annual crops and vegetables under irrigation was 41,089 ha representing 9.6 percent of the total area planted. The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 12.3 percent compared with 5 percent in the short rainy season. Crop Storage There were 228,187 crop growing households (87% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and pulses (104,155 households and 1,914 tonnes), paddy (14,828 households and 827 tonnes) and groundnuts and bambara nuts (1,674 households and 54 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 197,168 which represent 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Tanga (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%). Agricultural Credit In Tanga region, few agricultural households (1,022, 0.4%) accessed credit, out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got credit for agriculture purposes, whereas in Korogwe, Tanga and Handeni districts only male households accessed credit. In Muheza district both male and female headed household’s accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.96). Korogwe district had a relatively high proportion of households that received crop extension messages (84%), followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Tanga (14%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 30,288. This number represents 11 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Lushoto District (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Tanga (1%) Pangani (0.5%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 378,338. Cattle rearing are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on the Tanzanian Mainland. The number EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x of indigenous cattle was 350,210 head (92.6% of the total number of cattle in the region), 27,829 (7%) were dairy breeds and only 298 (1.4%) were beef breeds. Goats The number of goat-rearing-households in the region was 68,764 (26% of all agricultural households) with a total of 514,620 goats giving an average of 7 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 35,381 (13% of all agricultural households) with a total of 164,209 sheep giving an average of 5 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 176,806, raising 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Tanga ranked eighth out of the 21 Mainland regions. Use of Draft Power The region has 738 oxen and they were only found in two districts, Korogwe and Kilindi with 592 and 146 head respectively. Tanga region has 0.03 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 2,653 hectares of land. Fish Farming The number of households involved in fish farming was 1,423 (0.5 percent of the total agricultural households in the region). Korogwe was the leading district with 634 agricultural households involved in fish farming (1.4%) followed by Lushoto 430 (0.5%), Muheza 336 (0.7%) and Tanga 23 (0.3%). Fish farming was not practiced in Pangani and Handeni districts. iv) Poverty Indicators Availability of Toilets It was estimated that 86.5 percent of all rural agricultural households used the traditional pit latrines, 1.8 percent used improved pit latrine and 0.7 percent had flush toilets. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 11 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (61.3% of households) followed by bicycle (32.1%), iron (18.9%), wheelbarrow (3.4%), mobile phone (1.9%), television/video (1.0%), vehicle (0.9%) and landline phone (0.5%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. About 77 percent of the total rural households used this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), paraffin/kerosene (0.03%) and gas/biogas (0.01%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households however, this was closely followed by iron sheets (43.6%). Other roofing materials are grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%). Number of Meals per Day About 72.3 percent of the holders in the region took three meals per day, 25.2 percent took two meals, 2.4 percent took one meal and 0.1 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 42 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 8.3 percent whereas those with little problems represent 7.6 percent. About 7 percent of agriculture households always faced food shortages whilst 35 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 25.5 percent of all rural agricultural households. The second main cash income earning activity was casual labor (20.9%) followed by selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Other income earning activities were employment (5.0%), sale of livestock (4.0%), sale of forest products (2.5%), sale of livestock products (1.7%) and fishing (0.9%). ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size........................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season.................................................................................... 22 3.3 Area, Production and Yield of Root and Tuber Crops by Season.................................................................... 27 3.4 Area, Production and Yield of Pulse by Season .............................................................................................. 28 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season ................................................................. 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season..................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season........................................................................ 37 3.8 Land Clearing Methods.................................................................................................................................... 48 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season..................................... 51 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Long Rainy Season......................................................................................................................... 51 3.11 Number of Households Storing Crops by Estimated Storage Loss and District.............................................. 62 3.12 Reasons for Not Selling Crop Produce ............................................................................................................ 65 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 66 3.14 Access to Inputs............................................................................................................................................... 69 3.15 Number of Households and Chickens Raised by Flock Size............................................................................82 3.16 Number of Other Livestock by Type of Livestock and District....................................................................... 84 3.17 Mean distances from dwellings to infrastructure and services by districts...................................................... 91 3.18 Number of Households by Number of meals the Household normally takes per Day and District................. 95 List of Charts 3.1 Agricultural Households by Type of Holdings ................................................................................................ 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ........................................... 11 3.3 Percentage Distribution of Population by Age and Sex in 2003...................................................................... 15 3.4 Percentage Literacy Level of Household Members by District ....................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District............................................................................ 15 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status ................................................................................................. 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment .................................................. 16 3.9 Number of Households by number of members with Off Farm Income – Tanga Region ............................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ................................ 17 3.11 Utilized and Usable Land per Household by District ...................................................................................... 17 3.12 Land Area by Type of Land Use...................................................................................................................... 18 3.13 Area Planted with Annual Crops (ha) by Season............................................................................................. 18 3.14 Area Planted with Annual Crops by Season and Region................................................................................. 18 3.15 Area Planted with Annual Crops per Household by Season and District ........................................................ 20 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................. 20 3.17a Planted Area per Household by Selected Crops................................................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type.................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season...................................................................... 22 3.19 Area Planted and Yield of Major Cereal Crops ............................................................................................... 22 3.20 Time Series Data on Maize Production – Tanga Region................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Tanga Region ...................................................................... 23 3.23 Total Planted Area and Area of Paddy per Household by District................................................................... 26 3.24 Time Series Data on Paddy Production – Tanga Region................................................................................. 26 3.25 Time Series of Paddy Planted Area and Yield – Tanga Region ...................................................................... 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District ................................................................. 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................. 26 3.28 Area planted with Cassava during the census/survey years..............................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District ....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District.............................................................. 28 3.31 Total Area Planted and Planted Area per Household by District..................................................................... 28 3.32 Area Planted and Yield of Major Pulse Crops................................................................................................. 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ........................................... 30 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only)....................................... 30 3.35 Time Series Data on Bean Production – Tanga Region................................................................................... 30 3.36 Time Series of Beans Planted Area and Yield - Tanga.................................................................................... 32 3.37 Area Planted and Yield of Major Oil Seed Crops............................................................................................ 32 3.38 Time Series Data on Groundnut planted area – Tanga Region........................................................................ 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only).............................. 33 3.42 Area Planted and Yield of Fruit and Vegetables.............................................................................................. 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District .................................... 35 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) .................................. 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District .................................... 37 3.47 Area planted with Annual Cash Crops............................................................................................................. 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District.................................. 40 3.49 Area Planted for Annual and Permanent Crops ............................................................................................... 40 3.50 Area Planted with the Main Permanent Crops................................................................................................. 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District ........................ 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District.......................... 45 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District ................. 48 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season..................................... 48 3.57 Area Cultivated by Cultivation Method............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District................................................................................... 50 3.59 Planted Area of Improved Seeds – Tanga.........................................................................................................50 3.60 Planted Area with Improved Seed by Crop Type ............................................................................................ 50 3.61 Percentage of Crop Type Planted Area with Improved Seed – Annuals.......................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer........................................................................................ 51 3.63 Area of Fertilizer Application by Type of Fertilizer and District .................................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season.................................................... 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District....................................................... 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals ...................................................................... 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type ............................................................... 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District ....................................................... 53 3.68a Planted Area with Compost by Crop Type ...................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type................................................................................ 53 3.68c Proportion of Planted Area Applied with Compost by District ....................................................................... 53 3.69 Planted area (ha) by Pesticide use.................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type..................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides.................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season................... 54 3.73 Planted Area applied with herbicides by Crop Type........................................................................................ 55 3.74 Percentage of Crop Type Planted Area applied with herbicides...................................................................... 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season .................... 55 3.76 Planted Area applied with Fungicides by Crop Type ...................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides..................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season .................... 56 3.79 Area of Irrigated Land ..................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District........................................................ 57 3.81 Time Series of Households with Irrigation – Tanga ........................................................................................ 57 8.82 Number of Households with Irrigation by Source of Water ............................................................................ 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................. 57 3.84 Number of Households with Irrigation by Method of Field Application......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type ............................................................................ 59 3.86 Number of households by Storage Methods.................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 3.88 Normal Length of Storage for Selected Crops................................................................................................. 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District................................................. 62 3.90 Number of Households by Purpose of Storage and Crop Type ....................................................................... 62 3.91a Percentage of Households Processing Crops by District ................................................................................. 63 3.91b Percent of Households Processing Crops by District....................................................................................... 63 3.92 Percent of Crop Processing Households by Method of Processing ................................................................. 63 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.93 Percent of Households by Type of Main Processed Product ........................................................................... 63 3.94 Number of Households by Type of By-product............................................................................................... 64 3.95 Use of Processed Product................................................................................................................................. 64 3.96 Percentage of Households Selling Processed Crops by District ...................................................................... 64 3.97 Location of Sale of Processed Products........................................................................................................... 64 3.98 Percent of Household selling Processed Products by Outlets for Sale and Distance........................................65 3.99 Number of Crop Growing Households Selling Crops by District.................................................................... 65 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 65 3.101 Percentage Distribution of Households Receiving Credit by Main Sources.................................................... 66 3.102 Number of Households Receiving Credit by Main Source of Credit and District........................................... 66 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit................................................... 66 3.104 Reasons for Not using Credit (% of Household).............................................................................................. 66 3.105 Number of Households Receiving Extension Advice...................................................................................... 67 3.106 Number of Households Receiving Extension by District ................................................................................ 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................ 67 3.108 Number of Households Receiving Extension by Quality of Services.............................................................. 67 3.109 Number of Households by Source of Inorganic Fertiliser ............................................................................... 69 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser................................................. 69 3.111 Number of Households by Source of Improved Seed...................................................................................... 70 3.112 Number of Households reporting Distance to Source of Improved Seed ........................................................ 70 3.113 Number of Households by Source of Insecticide/Fungicide............................................................................ 70 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides.......................................... 70 3.115 Number of Households with Planted Trees by District.................................................................................... 71 3.116 Number of Planted Trees by Species ................................................................................................................71 3.117 Number of Trees Planted by Smallholders by Species and District................................................................. 71 3.118 Number of Trees Planted by Location ............................................................................................................. 71 3.119 Number of Households by purpose of Planted Trees....................................................................................... 72 3.120 Number of Households with Erosion Control/Water Harvesting Facilities..................................................... 72 3.121 Number of Households with Erosion Control/Water Harvesting Facilities by District................................... 72 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................ 72 3.123 Total Number of Cattle ('000') by District ....................................................................................................... 74 3.124 Numbers of Cattle by Type and District .......................................................................................................... 74 3.125 Cattle Population Trend................................................................................................................................... 76 3.126 Improved Cattle Population Trend................................................................................................................... 76 3.127 Total Number of Goats ('000') by District ....................................................................................................... 76 3.128 Goat Population Trend..................................................................................................................................... 78 3.129 Total Number of Sheep by District.................................................................................................................. 78 3.130 Sheep Population Trend................................................................................................................................... 80 3.131 Total Number of Pigs by District..................................................................................................................... 80 3.132 Pig Population Trend ....................................................................................................................................... 80 3.133 Total Number of Chicken by District .............................................................................................................. 82 3.134 Chicken Population Trend ............................................................................................................................... 82 3.135 Number of Improved Chicken by Type and District.........................................................................................84 3.136 Improved Chicken Population Trend............................................................................................................... 84 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 84 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 86 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 86 3.140 Number of Households by Distance to Veterinary Clinic................................................................................ 87 3.141 Number of Households by Distance to Veterinary Clinic and District............................................................ 87 3.142 Number of Households by Distance to Village Watering Point ...................................................................... 87 3.143 Number of Households by Distance to Watering Point and District................................................................ 87 3.144 Number of Households using Draft Animals................................................................................................... 87 3.145 Number of Households using Draft Animals by District................................................................................. 87 3.146 Number of Households using Organic Fertiliser.............................................................................................. 88 3.147 Area of Application of Organic Fertiliser by District ...................................................................................... 88 3.148 Number of Households Practicing Fish Farming – Tanga............................................................................... 88 3.149 Number of Households Practicing Fish Farming by District – Tanga............................................................. 91 3.150 Fish Production................................................................................................................................................ 91 3.151 Agricultural Households by Type of Toilet Facility ........................................................................................ 92 3.152 Percentage Distribution of Households Owning the Assets............................................................................. 92 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting .............................................92 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................ 92 3.155 Percentage Distribution of Households by Type of Roofing Material............................................................. 94 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District................................................. 94 3.157 Percentage of Households by Main Source of Drinking Water and Season .................................................... 94 3.158 Percentage of Households by Distance to Main Source of Water and Season................................................. 94 3.159 Number of Agriculture Households by Number of Meals per day .................................................................. 95 3.160 Number of Households by Frequency of Meat and Fish Consumption............................................................95 3.161 Percentage Distribution of the Number of Households by Main Source of Income........................................ 97 List of Maps 3.1 Total Number of Agricultural Households by District..................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District........................................................ 12 3.3 Number of Crop Growing Households by District .......................................................................................... 13 3.4 Percent of Crop Growing Households by District ........................................................................................... 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District.......................................... 14 3.6 Percent of Crop and Livestock Households by District ................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ....................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................. 19 3.9 Area planted and Percentage During the Short Rainy Season by District........................................................ 21 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.................................. 21 3.11 Planted Area and Yield of Maize by District................................................................................................... 24 3.12 Area Planted per Maize Growing Household .................................................................................................. 24 3.13 Planted Area and Yield of Paddy by District................................................................................................... 25 3.14 Area Planted per Paddy Growing Household .................................................................................................. 25 3.15 Planted Area and Yield of Cassava by District................................................................................................ 29 3.16 Area Planted per Cassava Growing Household ............................................................................................... 29 3.17 Planted Area and Yield of Beans by District ................................................................................................... 31 3.18 Area Planted per Beans Growing Household................................................................................................... 31 3.19 Planted Area and Yield of Groundnuts by District .......................................................................................... 34 3.20 Area Planted per Groundnuts Growing Household.......................................................................................... 34 3.21 Planted Area and Yield of Tomato by District................................................................................................. 36 3.22 Area Planted per Tomato Growing Household................................................................................................ 36 3.23 Planted Area and Yield of Cabbage by District................................................................................................38 3.24 Area Planted per Cabbage Growing Household .............................................................................................. 38 3.25 Planted Area and Yield of Chillies by District................................................................................................. 39 3.26 Area Planted per Chillies Growing Household................................................................................................ 39 3.27 Planted Area and Yield of Cotton by District .................................................................................................. 41 3.28 Area Planted per Cotton Growing Household ................................................................................................. 41 3.29 Planted Area and Yield of Tobbaco by District............................................................................................... 42 3.30 Area Planted per Tobacco Growing Household............................................................................................... 42 3.31 Planted Area and Yield of Coconuts by District.............................................................................................. 44 3.32 Area Planted per Coconuts Growing Household ............................................................................................. 44 3.33 Planted Area and Yield of Oranges by District................................................................................................ 46 3.34 Area Planted per Orange Growing Household................................................................................................. 46 3.35 Planted Area and Yield of Banana by District................................................................................................. 47 3.36 Area Planted per Banana Growing Household ................................................................................................ 47 3.37 Planted Area and Yield of Cashew nut by District .......................................................................................... 49 3.38 Area Planted per Cashew nut Growing Household.......................................................................................... 49 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................ 58 3.40 Area Planted and Percent of Total Planted Area with Irrigation by District.................................................... 58 3.41 Percent of households storing crops for 3 to 6 weeks by district..................................................................... 61 3.42 Number of Households and Percent of Total Households Selling Crops by District....................................... 61 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District.... 68 3.44 Number and Percent of Crop Growing Households using Improved Seed by District ....................................68 3.45 Number and percent of smallholder planted trees by district........................................................................... 73 3.46 Number and Percent of Households with water Harvesting Bunds by District ............................................... 73 3.47 Cattle population by District as of 1st Octobers 2003 ......................................................................................75 3.48 Cattle Density by District as of 1st October 2003.............................................................................................75 3.49 Goat population by District as of 1st Octobers 2003 ....................................................................................... 77 3.50 Goat Density by District as of 1st October 2003 ............................................................................................. 77 3.51 Sheep population by District as of 1st Octobers 2003 ..................................................................................... 79 3.52 Sheep Density by District as of 1st October 2003 ........................................................................................... 79 3.53 Pig population by District as of 1st Octobers 2003.......................................................................................... 81 3.54 Pig Density by District as of 1st October 2003................................................................................................ 81 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.55 Number of Chickens by District as of 1st October 2003 ................................................................................. 83 3.56 Density of Chickens by District as of 1st October 2003.................................................................................. 83 3.57 Number and Percent of Households Infected with Ticks by District............................................................... 85 3.58 Number and Percent of Households Using Draft Animals by District ............................................................ 85 3.59 Number and Percent of Households Using Farm Yard Manure by District..................................................... 89 3.60 Number and Percent of Households using Compost by District...................................................................... 89 3.61 Number and Percent of Households Practicing Fish Farming by District ....................................................... 90 3.62 Number and Percent of Households without Toilets by District...................................................................... 90 3.63 Number and Percent of Households using Grass/Leaves for roofing material by District .............................. 93 3.64 Number and Percent of Households eating 3 meals per day by District.......................................................... 93 3.65 Number and Percent of Households eating Meat Once per Week by District ................................................. 96 3.66 Number and Percent of Households eating Fish Once per Week by District................................................... 96 3.67 Number and percent of Households Reporting food insufficiency by District ................................................ 98 INTRODUCTION _________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Tanga region is situated at the North-East corner of Tanzania between 40 and 60degrees below the Equator and 370 – 39010’ degrees East of the Greenwich Meridian. Tanga shares borders with Kenya to the North, Morogoro and Coast regions to the South, Kilimanjaro and Arusha regions to the West and the Indian Ocean to the East. The region comprises seven districts namely Lushoto, Korogwe, Muheza, Tanga, Pangani, Handeni and Kilindi. The region headquarters is located in Tanga District. 1.3 Land Area The region has an area of 26,808 square kilometers, of which 17,000 square kilometers are arable land. 1.4 Climate 1.4.1 Temperature The dominant climate is warm and wet along the coast and inland of the Tanga region. The Western Plateau of Handeni district has a hot and dry climate and in the Usambara Mountain range a temperate climate is found. In most cases, there is no big variation of temperature at the coast due to the influence of the Indian Ocean. The coolest month is June with minimum temperature of 200C. The hottest month is December with maximum temperature of 320C. 1.4.2 Rainfall The region has two rainy seasons, the short and the long rainy seasons. The short rainy season (Vuli) is from October to November and the Long rainy season (Masika) from April to May. In Tanga region, most areas get rainfall of at least 750mm per year. The amount of rainfall is about 1,100 to 1,400mm along the coast, decreasing inland with the exception of the Usambara Mountains, where, depending upon the slope position and height, the amount of rainfall may exceed 2000mm per year. In the Maasai Plains (North West of Handeni) and in the dry plains of Korogwe, the average rainfall is below 600mm. 1.5 Population According to the 2002 Population and Housing Census, there were 1,642,015 inhabitants in Tanga region. The population of Tanga region ranked 10th of the 21 regions in Tanzania. INTRODUCTION _________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 418,816 million with a per capita income of shillings 236,115. The region held 10th position among regions on GDP and contributed about 4.3 percent to the national GDP1 Tanga region is famous for limestone and gypsum mineral deposits, all of which are used in the cement factory situated in the region. It has many tourist attractions such as Mkomazi Game Reserve, Amboni Caves, Totten Islands, Tongoni Ruins, Pangani Beach and Hot Water Baths in Amboni and Amani Nature Reserve and has first class hotels (including Mkonge Hotel and Baobab Tree Inn) with conference facilities. The region is famous for producing both food and cash crops. The main food crops produced in Tanga region include: maize, paddy, beans and sorghum. The main cash crops include sisal and tea. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: Identification (i.e. region, district, ward and village) Household and holding characteristics Household information Land ownership/tenure Land use Access and use of resources Crop and vegetable production Agro processing and by-Products Crop storage and marketing On-farm investment Access to farm inputs and implements Use of credit for agricultural purposes Tree farming/agro-forestry Crop extension services Livelihood constraints Animal contribution to crop production Livestock INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 Livestock products Fish farming Livestock extension Labour use Access to infrastructure and other services Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: Where feasible all variables were extensively coded to reduce post enumeration coding error. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. Skip patterns were used to avoid asking unnecessary questions Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff was used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: Manual editing Data entry Data structure formatting Batch validation Tabulation Illustration production Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census data for Tanga region. Which are based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and Maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and Poverty indicators. More effort has been placed in analyzing the results in order to formulate solid conclusions than in previous censuses and surveys. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Tanga region was 265,198. The largest number of agriculture households was in Lushoto (86.580) followed by Muheza (49,195), Handeni (47739), Korogwe (45,990) Kilindi, (19,654) Tanga (8,914) and Pangani (7,128) (Map 3.1). The highest density of households was found in Tanga (74/km2) and Lushoto (63%) (Map 3.2). Most households (178,406, 67.2%) were involved in growing crops only, 1,477 (0.6%) rearing livestock only, 194 (0.1%) pastoralists, and 85,121 (32.1%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Tanga region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm Income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances (Table 3.1). Tanga and Pangani districts are the only ones whereby annual crop farming was not the most important source of livelihood, being replaced by Off-farm income 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Tanga region was 200,432 (76% of the total regional agricultural households) whilst in female-headed households it was 64,766 (24% of the total regional agricultural households). The mean age of household heads is 45 years (44 years for male heads and 49 years for female heads) (Chart 3.2) Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1 3 6 2 7 4 5 Korogwe 1 5 6 2 7 3 4 Muheza 1 2 6 5 7 4 3 Tanga 3 2 5 1 6 7 4 Pangani 2 5 6 1 7 4 3 Handeni 1 6 5 2 7 3 4 Kilindi 1 6 5 2 7 3 4 Total 1 5 6 2 7 3 4 Chart 3.1 Agriculture Households by Type - Tanga Pastoralists 0.1% Livestock Only 0.6% Crops Only 67.3% Crops and Livestock 32.1% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Handeni Muheza Pangani Lushoto Kilindi 8,914 47,739 49,195 45,990 Tanga Korogwe 19,654 7,128 86,580 Total Number of Agricultural Households by District 70,700 to 86,600 54,800 to 70,700 38,900 to 54,800 23,000 to 38,900 7,100 to 23,000 Number of Agriculture Households MAP 3.1 TANGA 74 30 30 63 14 9 11 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 61 to 74 48 to 61 35 to 48 22 to 35 9 to 22 Agricultural Households per Square Km MAP 3.2 TANGA Number of Agricultural Households per Square Kilometer of Land by District Tanzania Agriculture Sample Census RESULTS 12 37,830 48,594 14,833 32,853 6,216 6,974 31,105 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto Number of Crop Growing Households by District MAP 3.3 TANGA 40,200 to 48,600 31,700 to 40,200 23,200 to 31,700 14,700 to 23,200 6,200 to 14,700 Crops Growing Households 75% 87% 78% 69% 68% 77% 56% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.4 TANGA Percent of Crop Growing Households by District 80.8 to 87 74.6 to 80.8 68.4 to 74.6 62.2 to 68.4 56 to 62.2 Percent of Crop Growing Households Tanzania Agriculture Sample Census RESULTS 13 9 58 23 35 20 10 6 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.5 TANGA Number of Crop Growing Households per Square Kilometer of Land by District 47.6 to 58 37.2 to 47.6 26.8 to 37.2 16.4 to 26.8 6 to 16.4 Crop Growing Households per Sq Km 18% 12% 23% 31% 32% 22% 44% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.6 TANGA Percent of Crop and Livestock Households by District 37.6 to 44 31.2 to 37.6 24.8 to 31.2 18.4 to 24.8 12 to 18.4 Percent of Crop and Livestock Households Tanzania Agriculture Sample Census RESULTS 14 RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Tanga region had a total rural agricultural population of 1,296,031 of which 633,967 (49%) were males and 662,064 (51%) were females. Whereas age group 0-14 constituted 44 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Tanga region had an average household size of 5 with Pangani district having the lowest household size of 4 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Tanga region had a total literacy rate of 70 percent. The highest literacy rate was found in Pangani district (70%) followed by Tanga district (68%) and Lushoto district (65%). Kilindi and Handeni districts had the lowest literacy rates of 44 and 53 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 73.6 percent. The literacy rates among the male and female heads of households were 82 and 48 percent respectively. Male head of household literacy rate was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Pangani (79.4%) followed by Lushoto (76.4%), Muheza (75.4%), Korogwe (74.8%), Tanga (73.5%), Handeni (71.3%) and Kilindi (58.4%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - TANGA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 Pangani Tanga Lushoto Muheza Korogwe Handeni Kilindi District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - TANGA 0.0 25.0 50.0 75.0 100.0 Pangani Lushoto Muheza Korogwe Total Tanga Handeni Kilindi District Percent Male Female Total RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 42.8 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 33.5 percent were still attending school. Those who have never attended school were 23.7 percent (Chart 3.6). Agricultural households in Korogwe district had the highest percentage (49.2%) of population aged 5 years and above who had completed different levels of education. This was followed by Muheza and Pangani districts with 47.3 and 46 percent respectively. Kilindi and Handeni districts had the lowest percentages of 31.2 and 38.7. The number of heads of agricultural households with formal education in Tanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Tanga region, Lushoto district had the highest percentages (34% for primary and 26% for secondary). This was followed by Muheza (19% primary and 20% secondary), Korogwe (18% primary and 26% secondary) and Handeni (17% primary and 11% secondary). Pangani had the lowest percentage of heads of agricultural households with both primary education (3%) and secondary education (3%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Tanga with 73 percent of households having at least one member with off-farm income. In Tanga region 146,351 households (55%) had only one member aged 5 and above involved in only one off-farm income generating activity, 34,169 households (13%) had two members involved in off-farm income generating activities and 12,023 households (5%) had more than two members involved in off-farm income generating activities. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 42.8% Never Attended 23.7% Attending School 33.5% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Korogwe Muheza Pangani Lushoto Tanga Handeni Kilindi District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 1% Post Primary Education 3% No Education 27% Primary Education 69% RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 Tanga district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Pangani (85%), Korogwe (85%), Kilindi (82%) and Handeni (80%). Muheza and Lushoto districts had the lowest percent of agriculture households with off-farm income (63% and 60% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Tanga (50%). Lushoto district had very few households with more than one member having off-farm income (9%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 524,451 ha. The regional average land area utilised for agriculture per household was only 1.7 ha. This figure is below the national average which is estimated at 2.0 hectares. Eighty eight percent of the total land available to smallholders was utilised. Only 11.1 percent of usable land available to smallholders was not used (Chart 3.11). Large differences in land area utilised per household exist between districts with Handeni and Kilindi utilizing between 2.5 and 2.6 ha per household. The smallest land area utilised per household is found in Lushoto (1.1 ha). The percentage utilized of the usable land per household is highest in Lushoto (99%) Chart 3.9 Number of Household by Number of Members with Off-farm Income One, 146,351, 55% Two, 34,169, 13% More than Two, 12,023, 5% None, 72,655, 27% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Tanga Handeni Pangani Korogwe Kilindi Muheza Lushoto Districts Percent Mo re than Two Two One No ne Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Handeni Kilindi Pangani Muheza Tanga Korogwe Lushoto Districts Area/household 0 20 40 60 80 100 120 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 and lowest in Tanga (76%). Eighty eight percent of the total land available to smallholders was utilised. Only 11.1 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 167,575 hectares (32% of the total land available to smallholders in Tanga), followed by permanent/annual mix (81,938 ha, 15.6%), temporary mixed crops (78,356 ha, 14.9%), uncultivatable usable land (57,053 ha, 10.9%), area under fallow (43,926 ha, 8.4%), permanent mixed crop (40,080 ha, 7.6%), permanent monocrop (33,108 ha, 6.3%), unusable area (9,597 ha, 1.8%), area rented to others (4,236 ha, 0.8%), area planted with trees (3,959 ha, 0.8%), area under natural bush (2,771 ha, 0.5%) and area under pasture (1,852 ha, 0.4%). 3.3 Annual Crop and Vegetable Production Tanga region has two rainy seasons, namely the short rainy season (October to November) and the long rainy season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 428,533 hectares out of which 160,820 hectares (37.5%) were planted during short rainy season and 267,713 hectares (62.5%) during long rainy season. The average areas planted per household during the short and long rainy seasons was 0.8 and 1.0 ha respectively (Chart 3.13). The districts with the largest area planted per household (the average of the two seasons) were Kilindi (1.5 ha) followed by Handeni (1.3 ha). The district with the smallest average area planted was Tanga (0.77ha). While in Lushoto district the average area planted during the short rainy season in higher than that of the long rainy season the reverse is true in the rest of the districts (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 295,529 ha (69.0%of the total area planted with annuals). This was followed by pulses (77,017 hectares, 18.0%), roots and tubers (47,614 hectares, 11.1%), fruit and vegetables (5,346 hectares, 1.2%), oil seeds (2,564 hectares, 0.6%) and cash Chart 3.12 Land Area by Type of Use 0.4 0.5 0.8 0.8 1.8 6.3 7.6 8.4 10.9 14.9 32.0 15.6 0 50,000 100,000 150,000 200,000 Pasture Natural Bush Planted Trees Rented to Others Unusable Permanent Mono Crops Permanent Mixed Crops Fallow Uncultivated Usable Land Temporary Mixed Crops Permanent / Annual Mix Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 267,714, 62% Short Rainy Season, 160,820, 38% Long Rainy Season Short Rainy Season Chart 3.14 Area Planted with Annual Crops by Season and Region 0 20,000 40,000 60,000 80,000 Lushoto Pangani Tanga Muheza Handeni Korogwe Kilindi Region Area Planted (ha) 0.00 20.00 40.00 60.00 80.00 Percentage Planted Short Rainy Season Long Rainy Season % Area planted in short rainy season 89% 89% 84% 84% 76% 89% 99% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.7 TANGA Utilized Land Area Expressed as a Percent of Available Land by Distrct 94.4 to 99 89.8 to 94.4 85.2 to 89.8 80.6 to 85.2 76 to 80.6 Percent of Utilized Land Area Pangani 8,198ha 10,260ha 111,249ha 43,153ha 69,468ha 61,078ha 125,020ha Kilindi Handeni Tanga Korogwe Muheza Lushoto MAP 3.8 TANGA Total Planted Area (Annual Crops) by District 104,000 to 126,000 80,000 to 104,000 56,000 to 80,000 32,000 to 56,000 8,000 to 32,000 Total Planted Area Tanzania Agriculture Sample Census RESULTS 19 RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 Crops (465 hectares, 0.1%). The average area planted per household during the long rainy season in Tanga region was 0.82 hectares, however, there were large district differences. Kilindi had the largest planted area per household (2.8 ha) followed by Pangani (2.5 ha) and Korogwe (1.7 ha). The smallest planted area per household is in Muheza (1.1 ha). In Lushoto the area planted per household in the short rainy season represents 58 percent of the total planted area per household, whereas in Kilindi the corresponding figure is 24 percent (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Tanga region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 67 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are cassava, Irish potatoes, cowpeas, paddy and tomatoes (Chart 3.16). Households that grow sorghum, maize and cowpeas have larger planted areas per household than for other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Tanga region. The area planted with cereals was 295,529 ha (69.0% of the total planted area), followed by pulses with 77,017 ha (18.0%), root and tubers 47,614 ha (11.1%), fruits and vegetables 5,346 ha (1.2%) and oil seeds 2,564 ha (0.6%). Annual cash crops that are mainly constituted of cotton and tobacco had got the least planted area of about 465 ha (0.1%) (Chart 3.17b). Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 1.00 2.00 3.00 Kilindi Pangani Handeni Korogwe Tanga Lushoto Muheza District Area Planted (ha) Long Rainy Season Short Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops Tanga 0 100,000 200,000 300,000 Maize Beans Cassava Irish Potatoes Cowpeas Paddy Tomatoes Green Gram Groundnuts Sweet Potatoes Cabbage Simsim Chillies Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - TANGA 0.00 0.50 1.00 1.50 2.00 Sorghum Maize Cowpeas Water Mellon Sunflower Beans Simsim Irish Potatoes Carrot Green Gram Cotton Tomatoes Yams Cocoyam Chillies Paddy Groundnuts Crop Planted Area (ha) Tanga 3,902ha 2,335ha 24,062ha 34,643ha 9,928ha 16,755ha 69,194ha 28% 35% 27% 31% 23% 55% 38% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.9 TANGA Area Planted and Percentage During the Short Rainy Season by District 55,900 to 69,200 42,500 to 55,900 29,100 to 42,500 15,700 to 29,100 2,300 to 15,700 Area Planted During Short Rain Season Area Planted (ha) Percent of Area Planted Tanzania Agriculture Sample Census RESULTS 21 Tanga Korogwe 7,565ha 4,504ha 97,042ha 52,422ha 49,028ha 32,678ha 52,289ha 74% 55% 75% 87% 80% 76% 42% Kilindi Handeni Pangani Muheza Lushoto MAP 3.10TANGA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District 78,500 to 97,100 60,000 to 78,500 41,500 to 60,000 23,000 to 41,500 4,500 to 23,000 Area Planted (ha) Planted Area With Cereal Crops Percent of Total Land Planted With Cereals RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 Cereals and pulses are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.4 Cereal Crop Production The total production of cereals was 180,987 tonnes. Maize was the dominant cereal crop at 173,602 tonnes which was 96 percent of total cereal crops produced, followed by paddy (4%) sorghum (0.19%), wheat (0.03%) and finger millet (0.01%).Handeni district had the largest planted area of Cereals in the region (97,042ha) followed by Lushoto, (51,118ha), Muheza (50,778ha) and Korogwe 46,369) (Map 3.10). The total area planted with cereals during the short and long rainy seasons was 295,529 ha out of which 111,875 ha (37.8%) were planted in short rainy season and 183,654 ha (62.1%) were planted during the long rainy season. The long rainy season accounts for 64 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 98.4 percent of the total area planted with cereals in that season followed by Paddy (1.6%) and Sorghum (0.1%) (Table 3.2). The area planted with maize was dominant and it represented 97.3 percent of the total area planted with cereal crops, then followed by paddy (2.59%), wheat 0.07%), Sorghum 0.04%) and finger millet 0.02%). The yield of paddy was 908 kg/ha, followed by maize (604 kg/ha), finger millet (346 kg/ha) and wheat (280 kg/ha). Bulrush millet and barley were not grown in the region (Chart 3.19). Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 110,043 61,910 563 177,433 111,692 629 287,476 173,602 604 Paddy 1,735 3,488 2,010 5,930 3,472 585 7,665 6,960 908 Sorghum 97 338 3,485 19 7 357 116 345 2969 Finger Millet 0 0 0 66 23 346 66 23 346 Wheat 0 0 0 205 57 280 205 57 280 Total 111,875 65,736 183,654 115,251 295,529 180,987 111,875 42,393 34,624 36,856 10,759 2,525 2,821 1,839 725 448 17 0 100,000 200,000 300,000 Area (hectares) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 100,000 200,000 300,000 Maize Paddy Wheat Sorghum Finger Millet Crop Area Planted (ha) 0.00 1.00 2.00 3.00 4.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.17b: Percentage Distribution of Area planted w ith Annual Crops by Crop Type Oil seeds & Oil nuts, 0.6% Roots & Tubers, 11.1% Fruits & Vegetables, 1.2% Cash crops, 0.1% Pulses, 18.0, % Cereals, 69.0% RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Tanga region during the long rainy season was 189,772, (81% of the total crop growing households in the region during the long rainy season). The total production of maize was 173,602 tonnes from a planted area of 287,476 hectares resulting in a yield of 0.6 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. There was a sharp increase in maize production (122%) over the period of 1998 to 1999 after which the production remained constant until 2003. The average area planted with maize per household was 0.91 hectares; however it ranged from 0.4 hectares in Lushoto district to 1.4 hectares in Kilindi district (Map 3.12). Handeni district had the largest area of maize (95,688 ha) followed by Lushoto (51,118 ha), Muheza (50,778 ha), Korogwe (46,369 ha), Kilindi (32,536 ha), Pangani (7,042 ha) and Tanga (3,946 ha) (Chart 3.21 and Map 3.11). Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 2000 and the area has remained constant ever since. However, the yield of maize has shown a gradual decline over the period 1996 to 2003 (from 1.3t/ha in 1995 to 0.6 t/ha in 2003) (Chart 3.22). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tanga region during the long rainy season was 15,443. This represents 66 percent of the total crop growing households in Tanga region in the long rainy season. The total production of paddy was 6,960 tonnes from a planted area of 7,665 hectares resulting in a yield of 0.91 t/ha. The district with the largest area planted with Paddy was Korogwe (2,659 ha) followed by Muheza (1,644 ha), Handeni (1,245 ha), Lushoto (931 ha), Tanga (545 ha), Pangani (500 ha) and Kilindi (142 ha) (Map 3.13). There are small insignificant variations in the average area planted per crop growing household among the districts ranging from 0.32 ha in Muheza to 0.45 ha in Handeni (Chart 3.23 and Map 3.14) Chart 3.20: Time Series Data on Maize Production - TANGA 320 166 126 174 306 138 197 0 100 200 300 400 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 3,946 7,042 32,536 46,369 50,778 51,118 95,688 0 20,000 40,000 60,000 80,000 100,000 120,000 Handeni Lushoto Muheza Korogwe Kilindi Pangani Tanga District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.22 Time Series of Maize Planted Area & Yield -TANGA 0 100000 200000 300000 400000 500000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area Yield Korogwe Tanga 46,369ha 7,042ha 3,946ha 95,688ha 32,536ha 50,778ha 51,118ha 0.5t/ha 0.4t/ha 0.8t/ha 0.7t/ha 0.5t/ha 0.3t/ha 0.6t/ha Kilindi Handeni Pangani Muheza Lushoto MAP 3.11 TANGA Planted Area and Yield of Maize by District 79,000 to 96,000 60,000 to 79,000 41,000 to 60,000 22,000 to 41,000 3,000 to 22,000 Maize Planted Area (ha) Planted Area Yield (t/ha) (ha) Tanzania Agriculture Sample Census RESULTS 24 Tanga Korogwe 0.8ha 0.5ha 0.7ha 1.5ha 1.4ha 0.8ha 0.4ha Kilindi Handeni Pangani Muheza Lushoto MAP 3.12 TANGA Area Planted per Maize Growing Household by District 1.2 to 1.5 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 Area Planted Per Household Planted Area Per Household (ha) Tanga Korogwe 545ha 500ha 1,644ha 931ha 2,659ha 1,245ha 142ha 0.2t/ha 0.9t/ha 0.5t/ha 0.3t/ha 0.5t/ha 1.3t/ha 1.5t/ha Kilindi Handeni Pangani Muheza Lushoto Planted Area and Yield of Paddy by District MAP 3.13 TANGA 2,140 to 2,660 1,640 to 2,140 1,140 to 1,640 640 to 1,140 140 to 640 Paddy Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 25 Korogwe 0.43ha 0.38ha 0.45ha 0.39ha 0.31ha 0.42ha 0.38ha Kilindi Handeni Pangani Tanga Muheza Lushoto MAP 3.14 TANGA Area Planted Per Paddy Growing Household by District 0.43 to 0.45 0.4 to 0.43 0.37 to 0.4 0.34 to 0.37 0.31 to 0.34 Area Planted Per Household Area Planted Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 26 There was a sharp rise in the production of paddy in 1996/97 compared to 1995/96. The production rose from 8,000 tons in 1995/96 to 26,000 tonnes in 1996/97 after which it dropped to 5,000 tonnes in the following year. Thereafter the yield increased gradually to 16,000 tonnes in 1999/2000 and this was followed by another decline in 2002/03 to 7,000 tonnes. Charts 3.23 and 3.25 show that, whilst the yield of paddy has dropped dramatically over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with paddy remained constant over the period from 1995 to 2003 after which the area under production expanded rapidly until 1999 after which it declined to 7,500 ha in 2003. Over the period 1995 to 1997 the yield of paddy fluctuated at around 3t/ha. However, there was a sharp decline in yield over the period 1996 to 1998 (down to 0.5 t/ha) and it has remained at this low level since then (Chart 3.25). 3.3.4.3 Other Cereals Other cereals are produced in small quantities. A small quantity of Sorghum is produced in Handeni (43 ha), Lushoto (35 ha), Pangani (24 ha) and Tanga (14 ha). Fingermillet is produced in Handeni district only (66 ha) and wheat is produced in Lushoto district only (205 ha) (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 66,967 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 44,500 tonnes representing 67.5 percent of the total root and tuber crops production. This was followed by Irish potatoes with 20,736 tonnes (30%), sweet potatoes (1,002t, 1.4%), coco yams (675t, 1.0%) and yams (55t, 0.1%) (Table 3.3). The area planted Chart 3.23 Total Planted Area and Area of Paddy per Household by District 2,659 1,644 1,245 931 545 500 142 0 500 1,000 1,500 2,000 2,500 3,000 Korogwe Muheza Handeni Lushoto Tanga Pangani Kilindi District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - TANGA 8 7 7 13 5 26 16 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons 0 50 100 150 200 250 Area (Ha) Handeni Lushoto Pangani Tanga Korogwe Muheza Kilindi District Chart 3.26 Area Planted with Sorghum, Fingermillet and Wheat by District Sorghum Fingermillet Wheat Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10,000 20,000 30,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Chart 3.25 Time Series of Paddy Planted Area and Yield - TANGA 0 2500 5000 7500 10000 12500 15000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Yield (t/ha) Planted Area Yield RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 with cassava was larger than any other root and tuber crops and it was the most important root and tuber crop in Tanga in terms of planted area accounting for 64.5 percent of the area planted with roots and tubers, followed by Irish potatoes (32.3%), sweet potatoes (2.3%), cocoyams (0.6%) and yams (0.3%). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava was reported under the long rainy season. However, excluding cassava, 54 percent of the area planted with roots and tubers was during the short rainy season. Cocoyams and Irish potatoes had a larger planted area in the short rainy season (68 percent and 54 respectively). However sweet potatoes had a larger planted area in the long rainy season (55.3%). The percentage planted area of yams during the short rainy season was estimated at 39 percent. There was a significant increase in area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potato and yams remained more or less constant. The total production of roots and tubers was estimated at 66,966 tonnes. Cassava with an estimate of 44,500 tonnes was the most important root and tuber crop. It accounted for 66.9 percent of the total roots and tubers production, followed by Irish potatoes with 20,736 tonnes (30.5%), sweet potatoes with 1,002 tonnes (1.5%), cocoyams with 675 tonnes (1.0%) and yams with 55 tonnes (0.1%). The estimated yield was high for cocoyams (2.5 t/ha) and cassava (2.3 t/ha), followed by Irish potatoes (1.3 t/ha), sweet potatoes (0.9 t/ha) and yams (0.4 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 78,627. This represents 30 percent of the total crop growing households in the region. The total production of cassava during the census year was 45,499 tonnes from a planted area of 30,732 hectares resulting in a yield of 2.4t/ha. Previous censuses and surveys indicate that the area planted with cassava increased for the period 1996 to 1999. Since 1999 the area planted with cassava dropped from 43,000 ha to 30,732 ha (Chart 3.28). The area planted with cassava accounted for 7 percent of the total area planted with annual crops and vegetables in the census year. Muheza district had the largest planted area of cassava (11,772 ha, 38% of the cassava planted area in the region), followed by Lushoto (6,457 ha, 21%), Korogwe (4,020 ha, 13%), Handeni (3,162 ha, 10%) Tanga (2,730 ha, 9%), Kilindi (1,475 ha, 5%) and Pangani (1,117 ha, 4%) (Map Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 1,725 2,131 1,235 29,007 43,368 2,358 30,732 45,499 2,358 Sweet Potatoes 480 537 1,119 593 465 784 1,073 1,002 934 Irish Potatoes 8,314 11,973 1,440 7,089 8,763 1,236 15,402 20,736 1,346 Yams 51 0 0 80 55 684 132 55 417 Cocoyam 188 574 3,045 86 101 1,169 275 675 2,455 TOTAL 10,759 15,214 36,856 52,752 47,614 67,966 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 28 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Tanga district (33%). This was followed by Muheza (17%), Pangani (11%), Korogwe (7%), Lushoto (5%), Handeni (3%) and Kilindi (3%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.4 hectares. However, there were small district variations. The area planted per cassava growing household was greatest in Kilindi (0.6 ha). This was followed by Muheza (0.5 ha), Tanga (0.5 ha), Handeni (0.5 ha), Pangani (0.4 ha), Korogwe (0.3 ha) and Lushoto (0.2 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Irish Potatoes The number of households growing Irish potatoes in Tanga region was 52,200. This was 2.5 percent of the total root and tuber crop growing households during the long rainy season. The total production of Irish potatoes during the census year was 20,736 tonnes from a planted area of 15,402 hectares resulting in a yield of 1.3t/ha. Lushoto District has the largest planted area for Irish potatoes (15,309 ha, 99.39%), followed by Korogwe (90 ha, 0.58%) and Pangani (4 ha, 0.02%). Irish potatoes were not grown in the other districts of Tanga region(Chart 3.31).Other root and tuber crops are of minor important in terms of area planted compared to cassava and Irish potatoes. 3.3.6 Pulse Crops Production The total area planted with pulses was 77,017 hectares out of which 63,028 ha were planted with beans (82 percent of the total area planted with pulses), followed by cow peas (12,007 ha, 15.6%), green gram (1,863 ha, 2.4%), mung beans (64 ha, 0.1%) and field peas (50 ha, 0.1%). Pigeon peas and soya beans were not cultivated in the region. Table 3.4: Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 64 88 1,385 64 88 1,385 Beans 24,185 8,699 360 38,843 15,325 395 63,028 24,023 381 Cowpeas 9,276 2,125 229 2,731 499 183 12,007 2,624 219 Green Gram 1,108 288 260 755 248 329 1,863 536 288 Chich Peas 2 0 198 0 0 0 2 0 198 Bambaranuts 2 1 296 0 0 0 2 1 296 Field Peas 50 109 2,159 0 0 0 50 109 2,159 TOTAL 34,624 11,221 42,393 16,160 77,017 27,381 Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 38.3 21.0 13.1 10.3 8.9 4.8 3.6 0 15 30 45 Muheza Lushoto Korogwe Handeni Tanga Kilindi Pangani District Percent of Total Area Planted 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.57 0.50 0.50 0.47 0.43 0.34 0.25 0.00 0.20 0.40 0.60 Area per Household Kilindi Muheza Tanga Handeni Pangani Korogwe Lushoto District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.21 Irish Potatoes: Total Area Planted and Planted Area per Household by District 15,309 90 0 0 4 0 0 0 4,000 8,000 12,000 16,000 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Area (Ha) 0.00 20.00 40.00 60.00 80.00 100.00 120.00 Area Planted per Household Planted Area (ha) Area per hh Tanga 1,117ha 2,730ha 3,162ha 11,772ha 1,475ha 4,020ha 6,457ha 1.8t/ha 2.6t/ha 2.8t/ha 3.1t/ha 2.4t/ha 3t/ha 1.6t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.15 TANGA Planted Area and Yield of Cassava by District 9,500 to 11,800 7,400 to 9,500 5,300 to 7,400 3,200 to 5,300 1,100 to 3,200 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 29 Korogwe 0.4ha 0.5ha 0.4ha 0.6ha 0.5ha 0.5ha 0.2ha Kilindi Handeni Pangani Tanga Muheza Lushoto MAP 3.16 TANGA Area Planted Per Cassava Growing Household by Distrct 0.52 to 0.61 0.44 to 0.52 0.36 to 0.44 0.28 to 0.36 0.2 to 0.28 Area Planted Per Households RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 The area planted with pulses in the short rainy season was 34,624 ha which represented 45 percent of total area planted with pulses during the year. Beans was the most dominant crop during long rainy season with 38,843 ha (91.2 % of the total area planted with pulses in that particular season), followed by cow peas (2,731 ha, 6.4%), green gram (755 ha, 1.8%) and mung beans 64 ha (0.2%). The total production of pulses was 27,381 tonnes. Beans were the most cultivated crop producing 24,023 tonnes which accounted for 88 percent of the total pulse production. This was followed by cow peas (2,624t, 10%), green gram (536t, 1.9%), field peas (109t, 0.4%), mung beans (88t, 0.3%), bambaranuts (1t, 0.002%) and chick peas (0.4t, 0.002%). Field peas and mung beans had relatively higher yields of 2,159 and 1,385 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were beans 381 kgs/ha, bambaranuts 296 kgs/ha, green gram 288 kgs/ha, cowpeas 219 kgs/ha and chick peas 198 kgs/ha (Chart 3,32). 3.3.6.1 Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Tanga region was 166,192. The total production of beans in the region was 24,023 tonnes from a planted area of 63,028 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Lushoto (46,981 ha, 74.5%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per household was in Kilindi district (0.92 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.4 ha. With exception of Kilindi district, the variations in area planted with beans for the rest of the districts were small ranging from 0.2 ha in Tanga and Pangani districts to 0.4 ha in Lushoto district (Map 3.18). Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 20,000 40,000 60,000 80,000 Beans Cowpeas Green Gram Mung Beans Field Peas Bambaranuts Chich Peas Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 80 Lushoto Kilindi Korogwe Muheza Handeni Tanga Pangani District Percent of Land 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.92 0.40 0.35 0.25 0.24 0.19 0.00 0.00 0.25 0.50 0.75 1.00 Area per Household Kilindi Lushoto Korogwe Muheza Handeni Tanga Pangani District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.35: Time Series Data on Beans Production - TANGA 12 4 13 21 24 2 11 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Tanga 4ha 13ha 1,374ha 5,979ha 432ha 46,981ha 8,245ha 0.2t/ha 0.1t/ha 0.4t/ha 0.1t/ha 0.3t/ha 0.6t/ha 0.4t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.17 TANGA Planted Area and Yield of Beans by District 36,000 to 47,000 27,000 to 36,000 18,000 to 27,000 9,000 to 18,000 0 to 9,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 31 0.2ha 0.2ha 0.3ha 0.5ha 0.7ha 0.3ha 0.3ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.18 TANGA Area Planted per Beans Growing Household by District. Area Planted Per Household 0.6 to 0.8 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 In Tanga region, bean production has increased steadily over the period 1995 to 2003 from 2,000 tonnes in 1995 to 24,000 tonnes in 2003 (Chart 3.35). Charts 3.35 and 3.36 show that, whilst the yield of beans remained fairly constant the previous 8 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with beans has increased erratically over the period from 1986 to 2003. Over the period 1997 to 2003 the yield of beans remained constant at around 0.4 t/ha. (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 1,516 tonnes planted on an area of 2,564 hectares... The total planted area of oilseeds in the long rainy season was 1,839 ha representing 72 percent of the total area planted with oil seeds. Groundnuts were most important oilseed crop with 1,645 ha (64% of the total area planted with oil seeds), followed by simsim (32%), sunflower (3%) and castor seed (0.8%) (Chart 3.37). The yield of groundnuts was moderate (714 kg/ha). Castor seed had a yield of 498 kg/ha, sunflower of 451 kg /ha and simsim 362 kg/ha. In terms of production, groundnuts were 1,174 tonnes and accounted for 77 percent of the total production of oil seeds, followed by simsim (20%), sunflower (2%) and castor seed (1%). 3.3.7.1 Groundnuts The number of households growing groundnuts in Tanga region was only 5,645. The total production of groundnuts in the region was 1,174 tonnes from a planted area of 1,645 hectares resulting in a yield of 0.7 t/ha. Area planted dropped from 310 hectares in 1994/95 to 196 hectares in 1995/96 after which it increased to 1,645 hectares in 2002/03 (Chart 3.38) Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 78 35 451 78 35 451 Simsim 92 26 281 729 271 372 822 297 362 Groundnuts 613 212 346 1,032 961 932 1,645 1,174 714 Castor Seed 20 10 494 0 0 0 20 10 494 Total 725 248 1,839 1,268 2,564 1,516 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 500 1,000 1,500 2,000 Groundnuts Simsim Sunflower Castor Seed Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) Chart 3.36 Time Series of Beans Planted Area & Yield - TANGA 0 20000 40000 60000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 0.8 Yield (t/ha) Area Yield 310 196 1400 1645 0 400 800 1200 1600 Planted Area 1994/95 1995/96 1998/99 2002/03 Year Chart 3.38 Time Series Data on Groundnut Planted area RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 33 There has been a large increase in production of groundnuts over the period 1995 to 2003, from 310 tonnes in 1994/95 to 1,174 tonnes in 2002/03. Area planted dropped from 310 hectares in 1994/95 to 196 hectares in 1995/96 after which it increased to 1,645 hectares in 2002/03 (Chart 3.38). Fifty percent of the area planted with groundnuts was located in Muheza District (828 ha) followed by Korogwe (359 ha, 21.8%), Handeni (228 ha, 13.8%), Tanga (104 ha, 6.3%), Pangani (93 ha, 5.6%) and Kilindi (34 ha, 2.0%). Groundnuts were not grown in Lushoto district (Map 3.19). The highest proportion of land with groundnuts was found in Tanga followed by Muheza, Pangani, Korogwe, Handeni and Kilindi (Chart 3.39 and Map 3.20). The largest area planted per groundnut growing household was found in Tanga District (0.43 ha) and the lowest was in Handeni (0.27). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short rainy season is relatively important for fruit and vegetables production since 53 percent of the total area planted with fruit and vegetables was during the short rainy season. For tomatoes, water Mellon, ginger, spinach and radish over 60 percent of the planted area of each crop was during the short rainy season. The planted area for cucumber in the long rainy season was abnormally large (100% of the total planted area was in the long rainy season). Reliable historical data for time series analysis of fruit and vegetables were not available. Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 60.0 Muheza Korogwe Handeni Tanga Pangani Kilindi Lushoto District Percent of Land 0.0 0.5 1.0 1.5 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 Area per Household (ha Tanga Kilindi Pangani Korogwe Muheza Handeni Lushoto District Chart 3.40 Area Planted per Groundnut Growing Households by District (Long Rainy Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 1,000 2,000 3,000 Tomatoes Cabbage Chillies Water Mellon Bitter Aubergine Carrot Others Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) Tanga 0ha 104ha 828ha 93ha 228ha 34ha 359ha 0t/ha 0.6t/ha 0.4t/ha 0.3t/ha 1.8t/ha 0.5t/ha 0.4t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.19 TANGA Planted Area and Yield of Groundnuts by District- 680 to 830 510 to 680 340 to 510 170 to 340 0 to 170 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 34 0.5ha 0.4ha 0.3ha 0.3ha 0.2ha 0.3ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.20 TANGA Area Planted Per Groundnuts Growing Household by District. 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Planted Area Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 The total production of fruits and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 10,852 tonnes (55% of the total fruit and vegetables produced) followed by cabbage (3,472t, 18%) and chilies (1,973t, 10%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 4,225 kg/ha, cabbage (4,105 kg/ha), water melon (3,634 kg/ha) and pumpkins (3,384 kg/ha). Radish and spinach had yields of 529 and 251 kg/ha respectively (Chart 3.42). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 4,100 and 7,462 households in the short rainy season. This represented 1.7 percent of the total crop growing households in the region during the long rainy season and 3.8 percent during the short rainy season. Lushoto district had the largest planted area of tomatoes (65.4% of the total area planted with tomatoes in the region), followed by Korogwe (17.8%), Kilindi (4.7%), Muheza (4.2%), Pangani (3.6%), Tanga (2.5%) and Handeni (1.9%) (Map 3.21). The highest percentage of land with tomatoes was found in Lushoto, followed by Pangani district. With exception of Lushoto district, the rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Pangani district (0.34 ha) followed by Tanga (0.25 ha), Lushoto (0.23 ha), Korogwe (0.21 ha), Kilindi (0.20 ha), Muheza (0.11 ha) and Handeni (0.08 ha) (Chart 3.44 and Map 3.22). The total area planted with tomatoes accounted for 0.6 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 9 13 1,422 26 17 629 35 29 831 Radish 4 2 529 0 0 0 4 2 529 Bitter Aubergine 18 216 11,856 176 296 1,685 194 512 2641 Onions 18 85 4,681 100 279 2,782 119 364 3072 Ginger 88 66 746 0 0 0 88 66 746 Cabbage 344 1,410 4,099 502 2,062 4,109 846 3,472 4105 Tomatoes 1,621 7,220 4,455 948 3,632 3,832 2,569 10,852 4225 Spinnach 30 8 251 0 0 0 30 8 251 Carrot 51 182 3,584 143 145 1,017 194 328 1691 Chillies 414 1,054 2,549 307 919 2,990 721 1,973 2737 Amaranths 65 140 2,153 66 59 886 131 199 1515 Pumpkins 13 234 17,324 65 31 475 78 265 3384 Cucumber 0 0 0 90 668 7,390 90 668 7390 Egg Plant 9 11 1,227 23 20 856 32 31 960 Water Mellon 137 82 599 78 699 8,936 215 781 3634 Total 2,821 10,723 2,525 8,827 5,346 19,550 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 80.0 Lushoto Korogwe Kilindi Muheza Pangani Tanga Handeni District Percent of Land 0.00 0.50 1.00 1.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha). Pangani Tanga Lushoto Korogwe Kilindi Muheza Handeni District Chart 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) Tanzania Agriculture Sample Census RESULTS 36 Tanga 63ha 92ha 108ha 456ha 49ha 120ha 1,680ha 2.2t/ha 1.7t/ha 1.7t/ha 1.9t/ha 6.4t/ha 1.8t/ha 5.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.21 TANGA Planted Area and Yield of Tomatoes by District 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Planted Area (ha) Planted Area (ha) Yield (t/ha) 0.3ha 0.2ha 0.3ha 0.1ha 0.1ha 0.2ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.22 TANGA Area Planted Per Tomatoes Growing Household by District 0.28 to 0.33 0.23 to 0.28 0.18 to 0.23 0.13 to 0.18 0.08 to 0.13 Area Planted Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 3.3.8.2 Cabbage The number of households growing cabbages in the region during the long rainy season was 2,277 and 1,582 in the short rainy season. This represented 0.97 percent of the total crop growing households in the region in the long rainy season and 0.8 percent in the short rainy season. Lushoto district had the largest planted area of cabbage (751 ha, 88.8% of the total area planted with cabbage in the region), followed by Korogwe (35 ha, 4.1%), Handeni (32 ha, 3.8%), Kilindi (17 ha, 2.0%), Muheza (9 ha, 1.1%) and Tanga (2 ha, 0.2%) (Chart 3.45 and Map 3.23 and 2,24). The total area planted with cabbages accounted for 0.2 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Chillies The number of households growing chillies in the region during the long rainy season was 1,367 households and 1,691 in the short rainy season. This represents 0.58 percent of the total crop growing households in the region in the long rainy season and 0.86 percent in the short rainy season. Lushoto district had the largest planted area of chillies (438 ha, 60.8% of the total area planted with chillies in the region), followed by Korogwe (237 ha, 32.9%), Tanga (23 ha, 3.2%), Muheza (18ha, 2.5%), Kilindi (2 ha, 0.3%) and Pangani (2 ha, 0.3%) districts (Map 3.25 and 3.26). Chillies are not produced in Handeni district. The largest proportion of the area planted with chillies was found in Korogwe district (0.39%), followed by Lushoto (0.35%), Tanga (0.28%), Muheza (0.03%), Pangani (0.02%) and Kilindi (0.005) (Chart 3.46). The total area planted with chillies accounted for 0.17 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. able 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 2 7 2,964 0 0 0 2 7 2,964 Cotton 0 0 0 264 165 625 264 165 625 Tobacco 15 3 198 166 70 422 180 73 404 Jute 0 0 0 18 12 642 18 12 642 TOTAL 17 10 448 247 465 256 Chart 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 75.0 100.0 Lushoto Korogwe Handeni Kilindi Muheza Tanga Pangani District Percent of Land 0.00 0.20 0.40 0.60 0.80 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 80.0 Lushoto Korogwe Tanga Muheza Kilindi Pangani Handeni District Percent of Land 0.00 0.10 0.20 0.30 0.40 0.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Tanzania Agriculture Sample Census RESULTS 38 0.2ha 0ha 0ha 0.3ha 0.1ha 0.1ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.24 TANGA Area Planted Per Cabbage Growing Household by District 0.24 to 0.3 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Area Planted Per Household Tanga 0ha 2ha 32ha 17ha 9ha 751ha 35 0t/ha 1.7t/ha 2.1t/ha 1.3t/ha 0t/ha 2.7t/ha 4.5t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.23 TANGA Planted Area and Yield of Cabbage by District 600 to 760 450 to 600 300 to 450 150 to 300 0 to 150 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanga 23ha 2ha 0ha 18ha 237ha 2ha 438ha 0t/ha 0.4t/ha 1.2t/ha 3.9t/ha 2.9t/ha 7t/ha 2.7t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.25 TANGA Area Planted Per Chillies Growing Household by District 352 to 438 264 to 352 176 to 264 88 to 176 0 to 88 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 39 Tanga 0.1ha 0.4ha 0ha 0.1ha 0.2ha 0.1ha 0.3ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.26 TANGA Area Planted per Chillies Growing Household by District 0.28 to 0.35 0.21 to 0.28 0.14 to 0.21 0.07 to 0.14 0 to 0.07 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 465ha was planted with other annual crops and cotton was the most prominent followed by tobacco, jute and seaweed. The area planted with annual cash crops in short rainy season was 17 ha which represents 3.6 percent of the total area planted with other annual cash crops in short and long rainy season. 3.3.9.1 Cotton Only 165 tonnes of cotton was produced in Tanga Region on a planted area of 264 ha it was produced during the long rainy season only. The crop is grown in Handeni district only (Map 3.27) and only 0.6 ha was grown per household (Map 3.28). 3.3.9.2 Tobacco The quantity of tobacco produced was 73 tonnes. Tobacco had a planted area of 180 ha, most of which was planted in the long rainy season. Tobacco production is concentrated in 4 districts with Kilindi having the largest planted area (46.1% of total area planted with tobacco in the region), followed by Muheza (25.6%), Korogwe (15.0%), Lushoto (8.3%) and Pangani (5.0%) (Chart 3.43) (Map 3.29 and 3.30). 3.4 Permanent Crops Permanent crops (sometimes referred as permanent crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore any time series analysis is made in this section. The area of smallholders planted with permanent crops was 62,403 hectares (13% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area planted more than once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in Chart 3.49. Chart 3.47 Area planted with Annual Cash Crops Seaweed, 2, 0% Cotton, 264, 57% Tobacco, 180, 39% Jute, 18, 4% Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 Kilindi Muheza Korogwe Lushoto Pangani Tanga Handeni District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted for Annual and Permanent Crops Annual , 428,533, 87% Permanent , 62,402 13% 0ha 0ha 0ha 0ha 264ha 0ha 0ha 0t/ha 0t/ha 0.6t/ha 0t/ha 0t/ha 0t/ha 0t/ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.27 TANGA Planted Area and Yield of Cotton by District 200 to 270 150 to 200 100 to 150 50 to 100 0 to 50 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 41 0ha 0.6ha 0ha 0ha 0ha 0ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.28 TANGA Area Planted Per Cotton Growing Household by District 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household Tanga 0ha 0ha 9ha 46ha 83ha 27ha 15ha 0t/ha 0t/ha 0.9t/ha 0t/ha 0.2t/ha 0.6t/ha 0.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.29 TANGA Planted Area and Yield of Tobbaco by District 80 to 90 60 to 80 40 to 60 20 to 40 0 to 20 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 42 0ha 0.4ha 0.3ha 0ha 0.6ha 0.1ha 0.1ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.30 TANGA Area Planted Per Tobacco Growing Household by Distrct 0.48 to 0.58 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 43 The most important permanent crop in Tanga region is coconuts which accounts for a planted area of 14,765 ha, (23.7% of the planted area of all permanent crops) followed by orange (9,342 ha, 15%), banana (8,125 ha, 13%), cashew nuts (7,905 ha, 12.7%), mango 4,268 ha, 6.8%) and coffee (3,199 ha, 5.1%). Each of the remaining permanent crops had an area of less than 5 percent of the total area planted with permanent crops (Chart 3.50). Muheza district had the largest area under smallholder permanent crops (28,263 ha, 45%). This is followed by Korogwe (9,357 ha, 15%), Lushoto (6,808 ha, 11%), Handeni (6,360 ha, 10%), Kilindi (4,914 ha, 8%), Pangani (4,623 ha, 7%) and Tanga (2,078 ha, 3%). However, Pangani had the largest area per permanent crop growing household (0.9 ha) followed by Muheza (0.7 ha), Kilindi (0.5 ha), Korogwe (0.4 ha), Handeni (0.3 ha), Tanga (0.3 ha) and Lushoto (0.1 ha) (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Pangani had the highest (31%) followed by Muheza (29%), Tanga (20%), Korogwe (13%), Kilindi (10%), Handeni (5%) and Lushoto (5%). 3.4.1 Coconuts The total production of coconuts by smallholders was 26,328 tonnes. In terms of area planted, coconut was the most important permanent crop grown by smallholders in the region. They were grown by 32,814 households (12.4% of the total crop growing households). The average area planted with coconuts per household was relatively small at around 0.45 ha per cashew nut growing household and the average yield obtained by smallholders was 3,479 kg/ha from a harvest area of 7,568 hectares. Muheza had the largest area of coconuts in the region (9,380 ha, 63.5%) followed by Pangani (2,417 ha, 16.4%), Korogwe (1,682.1 ha, 11.4%), Tanga (964.6 ha, 6.5%), Handeni (248.1 ha, 1.7%) and Lushoto (72.4 ha, 0.5%). There was no coconut production in Kilindi district (Map 3.31). However, the average area planted with coconuts per coconut growing household was highest in Pangani (0.69 ha) followed by Muheza (0.58 ha), Korogwe (0.38 ha), Tanga (0.22 ha), Lushoto (0.18 ha) and Handeni (0.07 ha) (Chart 3.52 and Map 3.32). Chart 3.50 Area Planted with the Main Perennial Crops Tea, 1,941, 3% Sugarcane, 2,356, 4% Pigeon Pea, 2,484, 4% Cardamon, 2,952, 5% Coffee, 3,200, 6% Mango, 4,268, 7% Cashewnut, 7,905, 14% Banana, 8,125, 14% Orange, 9,342, 16% Coconut, 14,765, 27% Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 15.0 10.9 10.2 7.9 7.4 3.3 45.3 0.0 20.0 40.0 Muheza Korogwe Lushoto Handeni Kilindi Pangani Tanga District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District 0.0 1.7 0.5 11.4 16.4 6.5 63.5 0.0 20.0 40.0 60.0 80.0 Muheza Pangani Korogwe Tanga Handeni Lushoto Kilindi District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 965ha 9,380ha 2,418ha 248ha 0ha 1,682ha 72ha 3.8t/ha 7.2t/ha 2t/ha 7.1t/ha 1.6t/ha 7.3t/ha 1.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.31 TANGA Planted Area and Yield of Coconuts by District 6,400 to 9,380 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 44 0.2ha 0.7ha 0.6ha 0.1ha 0ha 0.4ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.32 TANGA Area Planted per Coconuts Growing Households by District 0.56 to 0.69 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 45 3.4.2 Oranges The total production of oranges by smallholders was 65,210 tonnes. In terms of area planted, orange was the second most important permanent crop grown by smallholders in the region. It was grown by 9,342 households (3.5% of the total crop growing households). The average area planted with oranges per household was relatively small at around 0.39 ha per orange growing household and the average yield obtained by smallholders was 10,952 kg/ha from a harvest area of 5,954 hectares. Muheza had the largest area of oranges in the region (6,433 ha, 68.9%) followed by Handeni (2,201 ha, 23.6%), Korogwe (404 ha, 4.3%), Pangani (158 ha, 1.7%), Kilindi (79 ha, 0.9%), Tanga (63 ha, 0.7%) and Lushoto (4.3ha, 0.1%) (Map 3.33). However, the average area planted with oranges per orange planting household was highest in Muheza (0.6 ha) followed by Handeni (0.3 ha), Korogwe (0.3 ha), Pangani (0.1 ha), Kilindi (0.07 ha), Tanga (0.04 ha) and Lushoto (0.03 ha) (Chart 3.53 and Map 3.34). 3.4.3 Banana The total production of banana by smallholders was 34,126 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 61,464 households (23.3% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.13 ha per banana growing household and the average yield obtained by smallholders was 6,311 kg/ha from a harvested area of 5,408 hectares. Muheza had the largest planted area of bananas in the region (2,281 ha, 28%) followed by Korogwe (2,069 ha, 25%), Lushoto (1,751 ha, 22%), Handeni (1,143 ha, 14%), Kilindi (662 ha, 8%), Pangani (152 ha, 2%) and Tanga (68 ha, 1%) (Map 3.35). However, the area planted with banana per banana growing household was highest in Kilindi (0.22 ha), followed by Handeni (0.21 ha), Korogwe (0.20 ha), Muheza (0.16 ha), Pangani (0.13 ha), Lushoto (0.07 ha) and Tanga (0.06 ha) (Chart 3.49 and Map 3.36). 3.4.4 Cashew Nuts The total production of cashew nuts by smallholders was 4,557 tonnes. In terms of area planted, cashew nut was the fourth most important permanent crop grown by smallholders in the region. It was grown by 16,074 households (6.1% of the total crop growing households). The average area planted with cashew nuts per household was relatively small at around 0.49 ha per cashew nut growing household and the average yield obtained by smallholders was 977 kg /ha from a harvest area of 4,664 hectares. Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 0.68 0.05 23.56 1.69 68.86 0.85 4.33 0.00 20.00 40.00 60.00 Muheza Handeni Korogwe Pangani Kilindi Tanga Lushoto District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District 21.55 8.15 28.07 14.07 25.46 1.87 0.83 0.00 10.00 20.00 30.00 Muheza Korogwe Lushoto Handeni Kilindi Pangani Tanga District % of Total Area Planted 0.00 0.10 0.20 0.30 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 63ha 79ha 2,201ha 158ha 6,433ha 404ha 4ha 35.5t/ha 4.1t/ha 11.4t/ha 7.4t/ha 11.7t/ha 2.5t/ha 6.1t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.33 TANGA Planted Area and Yield of Oranges by District 5,200 to 6,500 3,900 to 5,200 2,600 to 3,900 1,300 to 2,600 0 to 1,300 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 46 Tanga Pangani Kilindi Handeni Korogwe Muheza Lushoto 0ha 0.1ha 0.6ha 0.3ha 0.3ha 0.1ha 0ha MAP 3.34 TANGA Area Planted per Orange Growing Households by District 0.4 to 0.6 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Households Tanga 68ha 152ha 1,143ha 2,281ha 2,069ha 662ha 1,751ha 18t/ha 7.6t/ha 6t/ha 3.6t/ha 7.4t/ha 6.9t/ha 13.3t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP3.35 TANGA Planted Area and Yield of Banana by District 2,000 to 2,300 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Planted Area (ha) Tanzania Agriculture Sample Census RESULTS 47 Tanga 0.1ha 0.1ha 0.2ha 0.21ha 0.2ha 0.2ha 0.1ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.36 TANGA Area Planted per Banana Growing Household by District 0.18 to 0.22 0.15 to 0.18 0.12 to 0.15 0.09 to 0.12 0.06 to 0.09 Area Planted Per Household RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 Muheza has the largest area of cashew nuts in the region (4,600 ha, 58%) followed by Pangani (1,766 ha, 22%), Tanga (950 ha, 12%), Korogwe (578 ha, 7%) and Lushoto (11 ha, 0.1%) (Map 3.37). However, the average area planted per cashewnut growing household was highest in Pangani (0.87 ha), followed by Muheza (0.54 ha), Tanga (0.43 ha), and Korogwe (0.25 ha) (Map 3.38). Handeni and Kilindi districts reported no cashew nuts production. 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 172,247 ha which represented 72.2 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 3.6, 0.8 and 0.4 percent respectively (Chart 3.56 and Table 3.8 ). 3.5.2 Methods of Soil Preparation Hand cultivation is mostly used for soil preparation as it has been used in an area of 379,283 ha which represented 95 percent of the total planted area, followed by ox-ploughing (17,519 ha, 4%) and tractor ploughing (3,509 ha, 1%) (Chart 3.57). Table 3.8: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 266,868 172,247 72.2 288,964 127,858 79.7 555,831 300,105 75.2 No Land Clearing 70,212 54,961 23.0 48,698 25,488 15.9 118,910 80,450 20.2 Mostly Bush Clearance 8,438 8,584 3.6 8,307 4,180 2.6 16,745 12,764 3.2 Mostly Burning 3,014 1,896 0.8 2,579 1,682 1.0 5,593 3,577 0.9 Mostly Tractor Slashing 1,684 875 0.4 1,267 457 0.3 2,951 1,332 0.3 Other 98 56 0.0 998 691 0.4 1,096 747 0.2 Total 350,314 238,619 100.0 350,812 160,357 100.0 701,126 398,976 100.0 Chart 3.57 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 3,509, 1% Mostly Hand Hoe, 379,283, 95% Mostly Oxen Ploughing, 17,519, 4% Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 266,868 70,212 8,438 3,014 1,684 98 0 100,000 200,000 300,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.55 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.00 0.00 12.01 0.14 58.19 7.31 22.34 0.00 20.00 40.00 60.00 Muheza Pangani Tanga Korogwe Lushoto Handeni Kilindi District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 950ha 1,766ha 4,600ha 0ha 0ha 578ha 11.1ha 12.3t/ha 1.7t/ha 0t/ha 0t/ha 0.7t/ha 1.5t/ha 0t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.37 TANGA Planted Area and Yield of Cashewnut by District 3,680 to 4,600 2,760 to 3,680 1,840 to 2,760 920 to 1,840 0 to 920 Planted Area (ha) 0.9ha 0.5ha 0ha 0ha 0.4ha 0.3ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.38 TANGA Area Planted Per Cashewnut Growing Household by District 0.68 to 0.87 0.51 to 0.68 0.34 to 0.51 0.17 to 0.34 0 to 0.17 Area Planted Per Household Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 49 RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 Slightly more hand cultivation was used during short rainy season at 96 percent against 94 percent for the long rainy season, whereas, oxen and tractor ploughing was more common in the long rainy season with 5 percent and 1 percent respectively. For the short rainy season the corresponding percentages are 3 and 1 respectively. In Tanga region, Handeni district has the largest planted area cultivated with oxen (9,515 hectares, 8.8%) followed by Kilindi (1,570 ha, 3.8%), Muheza (1,830 ha, 3.2%), Pangani (244 ha, 2.7%), Lushoto (2,919 ha, 2.44%), Korogwe (1,386 ha, 2.4%) and Tanga (55 ha, 1%). During the long rainy season, 91.7 percent of the total area cultivated by using oxen was planted with cereals followed by pulses (5.0%), fruit and vegetables (1.1%), roots and tubers (1.0%), oil seeds (0.6%) and cash crops (0.5%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 52,089 ha which represents 13 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the short rainy season was 13.4 percent, slightly higher than the corresponding percentage use for the long rainy season (12.73%). Cereals had the largest planted area with improved seeds (35,171 ha, 67% of the planted area with improved seeds) followed by pulses (8,748 ha, 17%), fruit and vegetables (4,291 ha, 8%), roots and tubers (3,415 ha, 7%), cash crops (280 ha, 1%) and Oil seed (185 ha, 0.3%) (Chart 3.54). However, the use of improved seed in fruit and vegetables and cash crops is much greater than in other crop types (80% and 60% respectively), only 7 percent of the planted area for oil seed crops used improved seed (Chart 3.55). 0 20,000 40,000 60,000 80,000 100,000 120,000 Area Cultivated Handeni Lushoto Muheza Kilindi Korogwe Pangani Tanga District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.59 Planted Area of Improved Seeds - TANGA With Improved Seeds, 52,089, 13% Without Improved Seeds, 348,221, 87% Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 3,415, 7% Pulses, 8,748, 17% Oilseeds , 185, 0% Fruits & Vegetables, 4,291, 8% Cereals, 35,171, 67% Cash Crops, 280, 1% 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 3.5.4 Fertilizer Use The use of fertilisers on annual crops is very small with a planted area of only 57,966 ha (15.6% of the total planted area in the region). The planted area without fertiliser for annual crops was 370,460 hectares representing 86.5 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 40,772 ha which represents 9.5 percent of the total planted area (70.3% of the area planted with fertiliser application in the region). This was followed by compost (12,226 ha, 21.1%). Inorganic fertilizers were used on a very small area and represented only 8.6 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Lushoto district (54.3%) followed by Korogwe (18%), Handeni (14%), Muheza (6%), Kilindi (5%), Tanga (1.4%) and Pangani (0.7%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 27,847 households, 11.5%) (Map 3.39). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (78% of the area planted with these fruit and vegetables during the long rainy season had an application of fertilizers). This was followed by roots and tubers (17%), pulses (13%), cereals (12%) and oil seeds (6%). There was no fertiliser application in cash crops (Table 3.10). 3.5.4.1 Farm Yard Manure Use Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 12,690 9,955 2,039 1,259 1,153 817 58,902 43,795 74,784 55,826 Korogwe 3,590 4,259 2,243 1,944 403 379 36,599 37,741 42,835 44,323 Muheza 1,411 1,549 79 32 0 43,881 43,825 45,371 45,406 Tanga 523 291 174 121 52 7 6,959 5,445 7,708 5,863 Pangani 99 123 44 110 0 5,779 6,125 5,922 6,357 Handeni 1,491 4,772 632 1,570 204 366 44,453 69,898 46,779 76,606 Kilindi 243 629 729 1,933 49 30 17,273 30,633 18,294 33,225 Total 20,047 21,577 5,939 6,968 1,861 1,598 213,846 237,462 241,693 267,605 Table3.9 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Lushoto 24,102 3,971 3,386 31,459 93,561 Korogwe 5,830 3,677 913 10,419 50,659 Muheza 3,226 248 95 3,570 65,898 Tanga 656 142 22 819 7,379 Pangani 209 182 0 391 9,869 Handeni 6,051 1,810 482 8,343 102,906 Kilindi 699 2,197 69 2,965 40,188 Total 40,772 12,226 4,968 57,966 370,460 0 50,000 100,000 150,000 Area (ha) Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 40,772, 10% Mostly Inorganic Fertilizer, 4,968, 1% Mostly Compost, 12,226, 3% No Fertilizer Applied, 370,460, 86% RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 The total planted area applied with farm yard manure in Tanga region was 45,375 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 20,047 and it was applied to 25,286 ha representing 7.5 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (56%), followed by roots and tubers (22%), pulses (17%) and fruit and vegetables (8%). However, fruit and vegetables had the highest percent of the planted area with farm yard manure (65.8% of the total area of fruit and vegetables in Tanga). This was followed by roots and tubers (21%), cereals (9%), pulses (8.0%) and oil seeds (4%) (Charts 3.64 and 3.65a). Farm yard manure is mostly used in Lushoto (18.5% of the total planted area in the district), followed by Korogwe (9.5%), Tanga (7.5%), Handeni (5.0%), Muheza (4.5%), Pangani (2.0%) and Kilindi (1.6%) (Chart 3.65b). For permanent crops, most farm yard manure is used for the production of passion fruits (40.8%), followed by apples (31.8%) and coffee (25.7%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Tanga region was 4,071 ha which represents 0.95 percent of the total planted area with annuals in the region and 6.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 1,861 and it was applied to 1,687 ha representing 0.6 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (53% of the total area applied with inorganic fertilizers), followed by pulses (16%), fruit and vegetables (16%) and roots and tubers (15%) (Chart 3.66). However, the proportion of fruit and vegetables with inorganic fertilizers was 12.7 percent higher than other crop types, followed by roots and tubers (1.1%), Pulses (0.8%) and cereals (0.3%) (Chart 3.67a). Inorganic fertiliser is mostly used in Lushoto (2.7% of the total planted area in the district), followed 0 25 50 75 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - TANGA 0.0 5.0 10.0 15.0 20.0 Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Percent Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - TANGA Roots & Tubers, 10,203, 22% Pulses, 3,407, 17% Oilseeds, 111, 0% Fruits & Vegetables, 3,458, 8% Cereals, 25,344, 56% Cash Crops, 0, 0% Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - TANGA Pulses, 638, 16% Oilseeds, 0, 0% Cash Crop, 0, 0% Cereals, 2,168, 53% Roots & Tubers, 594, 15% Fruit & Vegetables, 671, 16% RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 by Korogwe (1.5%). Other districts used virtually no inorganic fertiliser and Pangani recorded zero inorganic fertiliser use (Chart 3.67b). In permanent crops inorganic fertiliser were used on tea (5.2%), followed by sugarcane (1.1%), coconut (0.3%), mangoes (0.15%) and oranges (0.14%). 3.5.4.3 Compost Use The total planted area applied with compost was 12,490 ha which represents only 2.9 percent of the total planted area with annual crops in the region and 20 percent of the total planted area with fertiliser in the region. The number of households that applied compost on their annual crops during the long rainy season was 6,818 and it was applied to 7,650 ha representing 3.0 percent of the total area planted (Table 3.10 and Chart 3.68a). The proportion of area applied with compost was very low for each type of crop (0 to 4%); however the distribution of the total area using compost shows that 71 percent of this area was cultivated with cereals, followed by pulses (17%), roots & tubers (9%) and fruit and vegetables (0.5%)(Chart 3.68b). Compost is mostly used in Lushoto (6% of the total planted area in the district), and this is closely followed by Korogwe (5%). Other districts, like Kilindi used the least compost (0.2%) (Chart 3.67b). In permanent crops, compost was mostly used to durian (100.0%) followed by cloves (8.6%), pears (7.8%), avocado (5.3%) cinnamon (4.7%) and mango (4.0%). 0 5 10 15 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - TANGA Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - TANGA 0.0 1.0 2.0 3.0 Lushoto Korogwe Handeni Tanga Kilindi Muheza Pangani District Percent Chart 3.68a Planted Area with Compost by Crop Type - TANGA Roots & Tubers, 1,073, 9% Cereals, 9,067, 72% Fruits & Vegetables, 86, 1% Pulses, 2,265, 18% Oilseeds, 0, 0% Cash Crop, 0, 0% Chart 3.68c Proportion of Planted Area Applied with Compost by District - TANGA 0.0 2.0 4.0 6.0 8.0 Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Percent 0 5 10 15 20 25 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type- TANGA RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 25,121 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (56% of the total area applied with pesticides). This was followed by fungicides (29%) and herbicides (14%) (Chart 3.69). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 14,175 ha which represented 3.3 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (7,762 ha, 54% of the total planted area with insecticides) followed by fruit and vegetables (3,642 ha, 26%), pulses (1,379 ha, 10%), roots and tubers (1,100 ha, 8%), cash crops (273 ha, 2%) and oil seed (18 ha, 0.1%) (Chart 3.70). However, the percent of insecticides used in fruits and vegetables and cash crops is much greater than in other crop types (68 and 59% respectively), while only 0.7 percent of oil seed crops were applied with insecticides (Chart 3.71). Annual Crops with more than 50 percent insecticide use were spinach (100%), cucumber (100%), cotton (100%), water mellon (85.4%), tomatoes (83.3%), onions (75.7%), cabbage (71.3%), field peas (56.6%) and chillies (52.2%). Handeni had the highest percent of planted area with insecticides (5.4% of the total planted area with annual crops in the district). This was closely followed by Pangani (5%) then Lushoto (3.8%), Tanga (3.3%) and Korogwe (3.2%). The smallest percentage use was recorded in Muheza district (0.3%) (Chart 3.72). Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 7346, 29% Herbicides, 3600, 14% Insecticides, 14175, 56% Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 273, 1.9% Cereals, 7,762, 54.8% Fruits & Vegetables, 3,642, 25.7% Oil seeds & Oil nuts, 18, 0.1% Pulses, 1,379, 9.7% Roots & Tubers, 1,100, 7.8% 0.0 25.0 50.0 75.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - TANGA 0.0 2.0 4.0 6.0 Handeni Pangani Lushoto Tanga Korogwe Kilindi Muheza District Percent RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 3.5.5.2 Herbicide Use The planted area applied with herbicides was 3,207 ha which represented 0.8 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (2,119 ha, 59%) followed by roots and tuber (636 ha, 18%), pulses (383 ha, 11%), fruits and vegetables (310 ha, 9%) and oil seed (153 ha, 4%) (Chart 3.73). However, the percent of herbicide use on oil seeds and fruit and vegetables was much greater than in other crop types (6.0% and 5.8% respectively) while only 0.5 percent of pulses was applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were amaranths (13.0%), eggplant (10.3%), groundnuts (9.3%), onions (9.2%), tomatoes (8.2%) and cabbages (5.6%). Tanga had the highest percent of planted area with herbicides (3.3% of the total planted area with annual crops in the district). This was followed by Kilindi (1.5%) then Lushoto (0.9%), Muheza (0.6%) and Korogwe (0.6%). The smallest percentage use was recorded in Pangani district (0.2%) (Chart 3.75). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 7,346 ha which represented 1.7 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (2.5%) was higher than the corresponding percentage for the long rainy season (1.2%). Fruits and vegetables had the largest planted area applied with fungicides (3,005ha, 40.9%) followed by cereals (2,851 ha, 38.8%), roots and tubers (664 ha, 9.0%), pulses (590 ha, 8.0%), cash crops (218 ha, 3.0%) and oil seeds (18 ha, 0.2%) (Chart 3.76). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cash crops, 0, 0% Cereals, 2,119, 59% Fruits & Vegetables, 310, 9% Oil seeds & Oil nuts, 153, 4% Pulses, 383, 11% Roots & Tubers, 636, 18% 0.0 2.0 4.0 6.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 664, 9% Pulses, 590, 8% Oil seeds, 18, 0.2% Fruits & Vegetables, 3,005, 41% Cereals, 2,851, 39% Cash crops, 218, 3% Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - TANGA 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Tanga Kilindi Lushoto Muheza Korogwe Handeni Pangani District Percent RESULTS – Irrigation __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 However, the percentage use of fungicide in fruits and vegetables and cash crops was much greater than in other crop types (0.562% and 0.470% respectively), while only 0.008 percent of pulses was applied with fungicides (Chart 3.77). Annual crops with more than 40 percent fungicide use were field peas (100%), tomatoes (81%), cotton (79%), cucumber (78%), Onions (74%), chillies (43%) and egg plants (42%). Pangani had the highest percent of planted area with fungicides (3.8% of the total planted area with annual crops in the district). This was closely followed by Tanga (3.4%) and Lushoto (3.0%). The smallest percentage use was recorded in Muheza district (0.3%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.2%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 89 percent of the total area planted with cereals during the long rainy season was threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1%, 0.1 percent and 0.2 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other cultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Tanga region, the area of annual crops under irrigation was 41,089 ha representing 9.6 percent of the total area planted (Chart 3.79). The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season, 84 percent of the area planted with vegetables was irrigated, whilst 74 percent of the vegetables were irrigated in the long rainy season. 0.0 0.2 0.4 0.6 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - TANGA 0.0 1.0 2.0 3.0 4.0 Pangani Tanga Lushoto Korogwe Handeni Kilindi Muheza District Percent Chart 3.79 Area of Irrigated Land Unirrigated Area, 387,336, 90% Irrigated Area, 41,089, 10% RESULTS – Irrigation __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 The district with the largest planted area under irrigation with annual crops was Lushoto (13,424 ha, 33% of the total irrigated planted area with annual crops in the region). This is closely followed by Muheza with (11,336 ha, 28%) and then Korogwe (6,600 ha, 16%). When expressed as a percentage of the total area planted in each district, Tanga had the highest with 34 percent of the planted area in the district under irrigation. This is followed by Muheza (16%), Pangani (13%), Korogwe (11%), Lushoto (11%), Kilindi (4%) and Handeni (4%) (Chart 3.80 and Map 3.40). Of all the different crops and in terms of proportion of the irrigated planted area, field peas and spinach were the most irrigated crops with 100 percent irrigation followed by cabbage (96%), onions (96%), Amaranths (89%) and tomatoes (89%). In terms of crop type, the area under irrigation with roots and tubers was 47,505 ha (71% of the total area under irrigation), followed by cereals with 5,858 ha (14%), fruit and vegetables (4,218 ha,10%) and pulses (1,754 ha, 4%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 4,218 ha which represents 79 percent of the total planted area with fruit and vegetables. Tomatoes, cabbages and chillies were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Tanga region appears to have decreased over the 10 year intercensal period from 18,109 to 13,555 hectares. This may not be statically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from canals (45% of households with irrigation). This was followed by river (43%) and wells (8%). Only 0.5 percent of the households used water from boreholes and the proportion of households that used wells, dams and pipe water as a source of water for irrigation were very few (8.4%, 3.3% and 1.1% respectively). Most households using irrigation in Lushoto and Korogwe get their irrigation water from rivers (90 and 92 % respectively) Chart 3.82 Number of Households with Irrigation by Source of Water Canal, 10,176, 45% River, 10,052, 43% Well, 1,965, 8% Dam, 774, 3% Pipe water, 258, 1% Borehole, 113, 0% Canal River Well Dam Pipe water Borehole Chart 3.80 Planted Area with Irrigation by District - TANGA Region 0 4,000 8,000 12,000 16,000 Lushoto Muheza Korogwe Handeni Tanga Kilindi Pangani Region Irrigated Area (ha) 0 10 20 30 40 Percentage Irrigation Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation - TANGA 13,555 18,109 0 5,000 10,000 15,000 20,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Tanga 9,888ha 7,179ha 49,019ha 102,660ha 39,912ha 64,350ha 93,481ha 96% 88% 93% 92% 92% 80% 75% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 2.39 TANGA Planted Area and Percent of Planted Area with No Application of Fertilizer by District 83,500 to 102,700 64,400 to 83,500 45,300 to 64,400 26,200 to 45,300 7,100 to 26,200 Area Planted and Percent of Planted Area with no Fertilizer Applied Area Planted Percent of Planted Area with no Fertilizer Applied Tanzania Agriculture Sample Census RESULTS 58 Tanga Pangani 6,600ha 3,927ha 2,767ha 1,337ha 1,699ha 11,336ha 13,424 ha 4% 34% 13% 4% 16% 11% 11% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.40 TANGA Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area (ha) Percent of Total Planted Area with Irrigation Planted Area (ha) 13,400 to 13,500 11,300 to 13,400 6,600 to 11,300 2,800 to 6,600 1,300 to 2,800 RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 55.2 percent of households using this method. This was closely followed by hand bucket with 43.4 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.76). Gravity was used by most households with irrigation in Lushoto (65.8%), followed by Korogwe (32.2%), Muheza (1.3%), Kilindi (0.4%), Tanga (0.2%) and Pangani (0.1%). Hand bucket was more common in Lushoto with 68.3 percent of households using the method to get water for irrigation, followed by Korogwe (13.2), Muheza (7.6%), Kilindi (4.3%), Handeni (3.2%), Tanga (2.4%) and Pangani (1.1%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Tanga and Korogwe districts used some hand and motor pumps for obtaining water. 3.6.4 Methods of Water Application Most households used flood irrigation (52% of households using irrigation) as a method of field application. This was closely followed by hand bucket/watering can (45%). Sprinklers and water hose were not widely used (2.2% and 0.9% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices and as seed for planting in the following season. The results for Tanga region show that there were 228,187 crop growing households (87% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and other pulses (104,155 households, 1,914t), paddy (14,828 households, 827t) and groundnuts and bambara nuts (1,674 households, 54t). Other crops were stored in very small amounts. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 12,883, 55.2% Hand Bucket, 10,123, 43.4% Motor Pump, 36, 0.2% Hand Pump, 84, 0.4% Other, 212, 0.9% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 521, 2% Bucket / Watering Can, 10,588, 45% Flood, 12,006, 52% Water Hose, 222, 1% Flood Bucket / Watering Can Sprinkler Water Hose Chart 3.85 Number of Households and Quantity Stored by Crop Type - TANGA 0 50,000 100,000 150,000 200,000 250,000 Maize Pulses Paddy Gnuts/Bamb Nuts Cloves Sorghum & Millet Seaweed Tobacco Cashewnut Crop Number of households 0 5,000 10,000 15,000 20,000 25,000 30,000 Quantity (t) Number of households Quantity stored (Tons) RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 3.7.1.1 Methods of Storage The region had 171,393 crop growing households storing their produce in locally made traditional structures (74% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 43,125 (19%). This was followed by : unprotected piles (6,288 households, 3%), improved locally made structures (3,918 households, 2%), air tight drums (2,136 households, 1%) and modern stores (134 households, 0.1%). Locally made traditional structures were the dominant storage method in all districts, with the highest percent of households in Handeni using this method (88% of the total number of households storing crop products). This is followed by Lushoto (78%), Korogwe (73.5%), Muheza (71.3%), Pangani (67%), Tanga (57%) and Kilindi (52.4%) (Chart 3.80). The highest percent of households using sacks and open drum was in Tanga and Kilindi districts (37% and 36% of the total number of households storing crops), followed by Pangani (24.7%), Korogwe (21.5%), Muheza (18.6%), Lushoto (17.4%) and Handeni (9.6%). 3.7.1.2 Duration of Storage Most households (52% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of less than 3 months. The minority of households stored their crop for a period of over 6 months (17%). Most households that stored pulses stored for a period of less than 3 months followed by 3 to 6 months. A small number of households stored pulses for the period of over 6 months (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Korogwe district (67%) followed by Kilindi (60%), Muheza (59%), Handeni (58%), Pangani (47%), Tanga (38%) and Lushoto (37%) (Map 3.41). Chart 3.86 Number of households by Storage Methods - TANGA Unprotected Pile, 6,288, 3% Improved Locally Made Crib, 3,918, 2% Other, 1,193, 1% Airtight Drum, 2,136, 1% Modern Store, 134, 0% Sacks / Open Drum, 43,125, 19% Locally Made traditional Crib, 171,393, 74% Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Lushoto Handeni Muheza Korogwe Kilindi Pangani Tanga District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 30,000 60,000 90,000 120,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Tanga Pangani 37.6% 47.3% 58.2% 60% 59.3% 66.8% 37% Kilindi Handeni Korogwe Muheza Lushoto Tanga 4,977 6,605 41,149 69,510 29,751 30,492 14,684 70% 74% 80% 65% 84% 64% 75% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.42 TANGA Number of Households and Percent of Total Households Selling Crops by District 56,000 to 70,000 43,000 to 56,000 30,000 to 43,000 17,000 to 30,000 4,000 to 17,000 Number of Households Sells Crops Number of Households Sells Crops Percent of Total Households Selling Crops MAP 2.41 TANGA Percent of Households Storing Crops for 3 to 6 Months by District Percent of Households Storing Crops 70 to 70 60 to 70 50 to 60 40 to 50 30 to 40 Tanzania Agriculture Sample Census RESULTS 61 RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Lushoto district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 93.4 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at higher price. A high percent of the stored permanent crops was used for household consumption as was the case of cloves and cashew nuts (73.5% and 62% respectively). This is followed by selling at a higher price (26,5% and 38% respectively) (Chart 3.90). 3.7.1.4 The Magnitude of Storage Loss About 69 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (9.3% of the total number of households that stored crops). This was followed by maize (9.1%), groundnuts and bambaranut (5.4%), beans and pulses (2.9%) and paddy (1.1%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (94%) (Table 3.10). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Lushoto 72,408 8,108 1,276 426 82,219 Korogwe 31,199 4,146 693 213 36,251 Muheza 21,120 15,921 3,756 792 41,589 Tanga 3,641 800 213 0 4,654 Pangani 2,870 1,713 140 66 4,788 Handeni 15,611 17,138 7,113 968 40,831 Kilindi 10,642 4,920 1,953 340 17,855 Total 157,491 52,746 15,145 2,806 228,187 Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Handeni Muheza Kilindi Korogwe Pangani Lushoto Tanga District Quantity (tonnes) 0 5 10 15 20 25 30 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Sea weed Cloves Cashew nut Tobacco Gnuts Bamb Nuts Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Tanga region (235,784 households, 89% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 80%). Tanga amd Pangani had the lowest percent of households processing crops (69% and 72% of crop growing households respectively) (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 86 percent (202,137 households). This was followed by those processing on-farm by hand (16,189 households, 6.9%), trader (9,495 households, 4%) and on-farm by machine (7,094 households, 3%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Tanga region, however district differences existed. Pangani has a higher percent of hand processing than other districts.(27.2%), followed by Tanga (13.4%), and Handeni (13.2%). Processing by trader was more common in Muheza and Kilindi (10% and 6% respectively), whilst processing on farm by machine was more prevalent in Tanga, Pangani and Handeni (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, main product and by-product. The main product is the major product after processing and the by- product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 218,715 Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Pangani Tanga Handeni Kilindi Korogwe Muheza Lushoto District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal 92% Pulp 0.1% Other 1% Juice 0.3% Oil 1% Grain 6% Chart 3.91a Households Processing Crops Households not Processing, 29,414, 11% Households Processing, 235,784, 89% 0 20 40 60 80 100 Percent of Households Processing Lushoto Kilindi Handeni Muheza Korogwe Pangani Tanga District Chart 3.91b Percentage of Households Processing Crops by District RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 households processing crops into flour (93%) followed by grain with 13,494 households (5.7%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 20.6 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 40,044 households (82%) followed by Husks (3,807 households, 8%), cake (1,765 households, 4%) and pulp (1,576 households, 3%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Korogwe was the only district that used primary products as fuel for cooking. Out of 1,768 households that sold processed products, 871 were from Lushoto (49% of the total number of households selling processed products in the region), followed by Korogwe with 636 households (36%), Tanga with 115 households (6.5%), Pangani with 98 households (5.5%) and Kilindi with 49 households (2.8%) (Chart 3.96). Compared to other districts in Tanga region, Pangani had the highest percent of households that sold processed products. This is followed by Tanga (1.86), Korogwe (1.75%), Lushoto (1.06%) and Kilindi (0.28%). 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold to local market and trade stores (9,180 households, 41% of households that sold crops). This was followed by selling to neighbours (7,582 households, 35%), trader at farm (2,374 households, 11%), marketing co-operatives (1,334 households, 6%), large scale farm (595 households, 2.7%) and Farmers Associations (568 households, 2.6%) (Chart 3.97). Chart 3.94 Number of Households by Type of By-product Juice, 99, 0% Shell, 352, 1% Other, 879, 2% Cake, 1,765, 4% Pulp, 1,576, 3% Bran, 40,044, 82% Husk, 3,807, 8% Chart 3.95 Use of Processed Product Household/ human consumption, 277,966, 98% Fuel for Cooking, 218, 0% Sale Only, 4,194, 1% Did Not Use, 984, 0% Animal Consumption, 278, 0% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of households Lushoto Korogwe Tanga Pangani Kilindi Muheza Handeni District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Neighbours, 7,582, 35% Local Market / Trade Store, 9,180, 41% Marketing Co- operative, 1,334, 6% Other, 169, 1% Trader at Farm, 2,374, 11% Large Scale Farm, 595, 3% Farmers Association, 568, 3% RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 There are large differences between districts in the proportion of households selling processed products to neighbours with Tanga district having the largest percent of households in the district selling to neighbours (65%), whereas Lushoto had only 24 percent. Lushoto had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Pangani had the highest percent of households selling processed products to traders at farm. In Muheza, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Lushoto and Korogwe. 3.7.3 Crop Marketing The number of households that reported selling crops was 197,168 which represent 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Tanga (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%) (Chart 3.99 and Map 3.42). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (82% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (8%), lack of transport (4%), high transport costs (4%), lack of buyers (1%) and lack of market information (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 86 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts except for Pangani and Korogwe where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (16% and 12% respectively). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 72,966 86.3 Other 6,735 8.0 Price Too Low 2,253 2.7 Trade Union Problems 1,668 2.0 Co-operative Problems 491 0.6 Market Too Far 284 0.3 Government Regulatory Board Problems 146 0.2 Total 84,543 100.0 Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Lushoto Muheza Handeni Korogwe Kilindi Tanga Pangani District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Open Market Price Too Low 82% Co-operative Problems 0% Transport Cost Too High 4% Lack of Market Information 1% Market too Far 8% No Transport 4% No Buyer 1% Chart 3.98 Percent of Households Selling Pro cessed Pro ducts by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Tanga Muheza Pangani Handeni Kilindi Korogwe Lushoto District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other RESULTS – Access to Crop Production Services __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Tanga region very few agricultural households (1,022, 0.4%) accessed credit out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got agricultural credit whereas in Korogwe, Tanga and Handeni districts only male households accessed credit. In Muheza district both male and female headed households accessed agricultural credit (Table 3.12). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Tanga region were Religious Organizations/Non Governmental Organizations/ projects which collectively provided credit to 382 agricultural households (38% of the total number of households that accessed credit), followed by family, friends and relatives (21%), saving and credit society (20%), trader/trade store (8%), commercial bank (3%) and other sources (10%) (Chart 3.101). Commercial banks were the sole source of credit in Tanga district and savings and credit societies were found in Handeni district only. Trader/trader store was a major credit provider in Muheza district. Religious organization, NGO and projects were more involved in funding a relatively great number of households in Lushoto disrtict (Chart 3.102). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on unspecified activities (24%), followed by hiring labour (22%), fertilizers (16%) and seeds (12%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment and agro-chemicals was very low (Chart 3.103). Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Lushoto 0 0 404 100 404 Korogwe 107 100 0 0 107 Muheza 78 32 165 68 243 Tanga 61 100 0 0 61 Handeni 208 100 0 0 208 Total 453 44 569 56 1,022 Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Lushoto Korogw e Muheza Tanga Handeni District Percent of Households Family, Friend and Relative Commercial Banks Saving & Credit Society Trader/Trade Store Religious Organisation/NGO/Project Other Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Trader / Trade Store 8% Other 10% Saving & Credit Society 20% Family, Friend and Relative 21% Religious Organisation / NGO / Project 38% Commercial Bank 3% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Seeds 12% Tools / Equipment 7% Irrigation Structures 7% Agro-chemicals 7% Other 27% Fertilizers 17% Labour 23% Chart 3.104 Reasons for not Using Credit (% of Households) Interest rate/cost too high, 4,097, 2% Other, 659, 0% Credit granted too late, 684, 0% Not needed, 4,490, 2% Difficult bureaucracy procedure, 9,470, 4% Did not w ant to go into debt, 15,787, 6% Not available, 27,302, 10% Don't know about credit, 50,220, 19% Did not know how to get credit, 151,467, 57% RESULTS – Access to Crop Production Services __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 76 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (10.3%), followed by “not wanting to go into debt” (6.0%) The rest of the reasons were collectively less than 8 percent of the households. 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Korogwe having a relatively high proportion of households (84%) that received crop extension messages in the district followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Tanga (14%) (Chart 3.106 and Map 4.43). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (98.9%, 119,592 households). NGOs provided 0.4 percent, large scale farms 0.4 percent and the remaining providers less than 0.3 percent (Chart 3.107), however district differences exist with the proportion of the households receiving advice from government services ranging from between 94.0 percent and 100 percent in Handeni and Lushoto respectively. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 143,711, 54% Households Receiving Extension , 121,487, 46% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Number of Households 0 20 40 60 80 100 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 0.4% Cooperative 0.1% NGO / Development Project 0.4% Other 0.2% Government 98.9% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 75,884, 62.5% Average, 32,287, 26.6% Poor, 1,505, 1.2% No Good, 1,594, 1.3% Very Good, 10,217, 8.4% Pangani Tanga Korogwe 737 14,855 8,835 1,166 818 5,183 1,907 17.2% 19.2% 13.1% 4% 10.3% 10.9% 3.9% Kilindi Handeni Muheza Lushoto 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanga 2,807 1,266 21,091 42,132 38,500 10,334 5,356 39% 14% 49% 84% 43% 22% 27% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.43 TANGA Number of Households and Percent of Total Households Receiving Crop Extension Services by District 33,000 to 43,000 25,000 to 33,000 17,000 to 25,000 9,000 to 17,000 1,000 to 9,000 Number Households Receiving Crop Extension Services Number Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services MAP 3.44 TANGA Number and Percent of Crop Growing Households Using Improved Seeds by District Number of Households Growing Crops Using Improved Seeds Number of Households Growing Crops Using Improved Seeds Percent of Total Households Selling Crops Tanzania Agriculture Sample Census RESULTS 68 RESULTS – Access to Inputs __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 63 percent of the households receiving extension ranked the service as being good followed by average (27 %), very good (8%), no good (1%) and poor (1%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Tanga region farm yard manure is used by 51,812 households which represents 19.7 percent of the total number of crop growing households. This is followed by households using improved seeds (12.7%), compost (5.5%) fungicide (5.3%), inorganic fertiliser (3%), and herbicide (0.3%) (Table 2.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Tanga mostly purchase from the local market/trade store (90.5% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing between 3 and 10 km from the source (39%), followed by between 1 and 3 km (30%) and less than 1 km (20%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 70 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. Table 2.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 51,812 19.7 211,716 80.3 Improved Seeds 33,500 12.7 230,028 87.3 Pestcides/Fungicide 13,971 5.3 249,557 94.7 Compost 14,580 5.5 248,948 94.5 Inorganic Fertiliser 8,223 3.1 255,304 96.9 Herbicide 835 0.3 262,692 99.7 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 90.5 3.1 1.9 1.8 1.6 1.2 0 2,000 4,000 6,000 8,000 Local Market / Trade Store Co-operative Large Scale Farm Locally Produced by Household Neighbour Development Project Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Access to Inputs __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 More smallholders use inorganic fertilisers in Lushoto than in other districts in Tanga region (72% of households using inorganic fertilisers), followed by Korogwe (17%) and Muheza (6.2%). Other districts use very little inorganic fertiliser. 3.9.3 Improved Seeds The percent of households that use improved seeds was 13 percent of the total number of crop growing households. Most of the improved seeds are from the local market/trade store (77.4%). Other less important sources of improved seed are from development partners (6.5%), neighbours (6.3%) and locally produced by household (6.3%). Only 0.9 percent of households using improved seed obtain them from large scale farms (Chart 3.111). Access to improved seed is better than access to chemical inputs with 30 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly use improved seeds are Lushoto (44.3 percent of the total number of households using improved seeds in Tanga region), followed by Korogwe (26.4%) and Handeni (15.5%). Use of improved seeds in other districts is of minor importance (Map 3.44). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (91% of the total number of fungicide users). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 7 percent of Chart 3.111 Number of Households by Source of Improved Seed 0.4 0.1 0.6 0.6 0.9 1.0 6.3 6.3 6.5 77.4 0 10,000 20,000 30,000 Local Market / Trade Store Development Project Neighbour Locally Produced by Household Co-operative Large Scale Farm Crop Buyers Local Farmers Group Other Secondary Market Source of Improved Seed Number of Households Chart 3.113 Number of Households by Source of Insecticide/fungicide 91.0 1.5 1.4 1.3 1.2 1.2 0.8 0.9 0.1 0.8 0 3,000 6,000 9,000 12,000 Local Market / Trade Store Crop Buyers Locally Produced by Household Development Project Co-operative Neighbour Large Scale Farm Other Secondary Market Local Farmers Group Source of Insecticide/fungicide Number of Households Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Tree Planting __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 74 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Lushoto district (60.9 percent of the total number of households that use fungicide in the region), followed by Korogwe (15.8%) and Handeni (15%). ,Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 28,110 representing 11 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 1,215,222 trees. The average number of trees planted per household planting trees was 43 trees. The main species planted by smallholders is Gravellia spp (648,235 trees, 53%), followed by Tectona grandis (313,570, 26%), then Eucalyptus (91,754, 7%) and Cyprus spp (72,130 trees, 6%). The remaining trees species are planted in comparatively small numbers (Chart116.). Lushoto has the largest number of smallholders with planted trees than any other district (49.3%) and is dominated by Gravellia species. This is followed by Muheza (32.9%) which is dominated by Tectona grandis and to a lesser extent Gravellia, then Korogwe (17%) and Kilindi (0.4%) which is mainly planted with Moringa (Chart 3.117 and Map 3.45.). Chart 2.116 Number of Planted Trees by Species - TANGA 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp Leucena Spp Others Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and Region 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Lushoto Korogw e Muheza Tanga Pangani Handeni Kilindi Region Number of Trees Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp Leucena Spp Other Chart 3.118 Number of Trees Planted by Location Field boundary, 482,086, 40% Scattered in field, 427,672, 35% Plantation, 305,464, 25% Chart 3.115 Number of Households w ith Planted Trees Growing trees, 28,110, 11% Not growing trees, 235,417, 89% RESULTS –Irrigation and Erosion Control Facilities __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 Smallholders mostly plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 40 percent, followed by scattered around fields (35%) and then trees planted in a plantation or coppice (25%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (45.9%). This is followed by wood for fuel (29.8%), shade (11.0%) and poles (10.7%) (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 30,288 which represents 11 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Lushoto district (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Tanga (1%) and Pangani (0.5%) (Chart 3.121). Terraces accounted for 28 percent of the total number of structures, followed by vetiver grass (21%), water harvesting bunds (20%), erosion control bunds (14%), tree belts (12%), drainage ditches (4%) gabions/sandbags (1%) and dams (0.5%) (Chart 3.122 and Map 3.46). Erosion control by terraces, vetiver grass and water harvesting bunds together had 207,920 structures. This represented 69 percent of the total structures in the region. The remaining 31 percentages were shared among the rest of the erosion control methods mentioned above. Lushoto and Korogwe districts had 258,206 erosion control structures (86 percent of the total erosion structures in the region). Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Wood for Fuel Shade Poles Other Medicinal Use Percent of Households Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 234,910, 89% Households with facilities, 30,288, 11% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 23 10 8 3 2 1 0.5 0 5,000 10,000 15,000 20,000 25,000 Lushoto Korogwe Muheza Kilindi Handeni Tanga Pangani District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 28.0 21.0 19.9 14.1 12.0 3.8 1.0 0.2 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Terraces Vetiver Grass Water Harvesting Bunds Erosion Control Bunds Tree Belts Drainage Ditches Gabions / Sandbag Dam Type of Facility Number of Structures Tanga Handeni Kilindi 68 0 0 925 13,571 1,587 43,906 0.8% 0% 27.6% 50.7% 3.5% 0% 5% Pangani Korogwe Muheza Lushoto 77 424 5,277 143 5,902 16,093 195 0.9% 0.9% 11.5% 2% 1% 12% 18.6% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.45 TANGA Number and Percent of Smallholder Planted Trees by District Number of Smallholder Planted Trees Number of Smallholder Planted Trees Percent of Smallholder Planted Trees MAP 3.46 TANGA Number and Percent of Households with Water Harvesting Bunds by District Number of Households with Water Harvesting Bunds Number of Households with Water Harvesting Bunds Percent of Households with Water Harvesting Bunds 12,800 to 16,100 9,600 to 12,800 6,400 to 9,600 3,200 to 6,400 0 to 3,200 35,200 to 44,000 26,400 to 35,200 17,600 to 26,400 8,800 to 17,600 0 to 8,800 Tanzania Agriculture Sample Census RESULTS 73 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 378,338. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Tanga region was 350,210 (92.6 % of the total number of cattle in the region), 27,829 cattle (7%) were dairy breeds and 298 cattle (1.4%) were beef breeds. The census results show that 86,792 agricultural households in the region (32.7% of total agricultural households) kept 0.4 million cattle. This was equivalent to an average of 7 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Handeni which had about 106,901cattle (28.3% of the total cattle in the region). This was followed by Lushoto (75,911 cattle, 20.1%), Korogwe (74,238 cattle, 19.6%), Muheza (63,355 cattle, 16.7%), Kilindi (46,019 cattle, 12.2%) and Tanga (11,012 cattle, 2.9%). Pangani district had the least number of cattle (901 cattle, 0.2%) (Chart 3.123 and Map 3.47). However Tanga district had the highest density (92 head per km2 ) (Map 3.48). Although Handeni district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant. Lushoto district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Eighty one percent of the cattle-rearing households had herds of size 1-5 cattle with an average of two cattle per household. Herd sizes of 6-30 accounted for about 30 percent of all cattle in the region. Only 3 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 97.5 percent of total cattle rearing households had herds of size 1-30 cattle and owns 59 percent of total cattle in the region, resulting in an average of 4 cattle per cattle rearing household. There were about 280 households with a herd size of more than 151 cattle each (95,883 cattle in total) resulting in an average of 342 cattle per household. 0 20 40 60 80 100 120 Number of Cattle ('000') Handeni Lushoto Korogwe Muheza Kilindi Tanga Pangani Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 40,000 80,000 120,000 Handeni Korogwe Lushoto Muheza Kilindi Tanga Pangani Districts Number of Cattle Indigenous Beef Dairy 11,012 63,355 901 46,019 106,901 74,238 75,911 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 48 1 92 39 20 32 55 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.48 TANGA Cattle Density by District as of 1st October 2003 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Cattle per Square Km MAP 3.47 TANGA Cattle population by District as of 1st Octobers 2003 84,000 to 107,000 63,000 to 84,000 42,000 to 63,000 21,000 to 42,000 0 to 21,000 Number of Cattle Tanzania Agriculture Sample Census RESULTS 75 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.1.3 CattlePopulation Trend Cattle population in Tanga decreased during the period of eight years from 653,549 in 1995 to 378,337 cattle in 2003. This trend depicts an overall annual negative growth rate of -6.6 percent (Chart 3.125). However, there was a very sharp decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –19.3 percent whereby the number dropped from 653,549 to 276,739. However, the number of cattle is estimated to have increased from 276,739 in 1999 to 378,337 in 2003at the rate of 8.13 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in tanga region was 28,127 (27,829 dairy and 298 improved beef). The diary cattle constituted 7.4 percent of the total cattle and 99 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 1 percent of the total number of the improved cattle and 0.1 percent of the total cattle The number of improved cattle increased from 20,420 in 1995 to 28,127 in 2003 at an annual growth rate of 4.1 percent. The growth rate was higher for the period from 1995 to 1999 (5.9%) than from 1999 to 2003 (2.3%) (Chart 126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Tanga region ranked 11 out of the 21 regions with 4.4 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Tanga region was 68,227 (26% of all agricultural households in the region) with a total of 514,620 goats giving an average of 8 head of goats per goat-rearing-household. Handeni had the largest number of goats (170,860 goats, 33% of all goats in the region), followed by Muheza (96,195 goats, 19%), Korogwe (86,441 goats, 17%), Lushoto (73,449 goats, 14%) and Kilindi (66,928 goats, 13%). Tanga and Pangani districts had the least number of goats (10,390 goats, 2% and 10,357 goats, 2% respectively) (Chart 3.127 and Map 3.49). However Tanga district had the highest density (87 head per km2 ) (Map 3.50). 653,549 277,000 378,338 - 200,000 400,000 600,000 800,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 0 40 80 120 160 200 Number of Goats ('000'). Handeni Muheza Korogwe Lushoto Kilindi Tanga Pangani District Chart 3.127 Total Number of Goats ('000') by District 20,420 25,675 28,127 - 20,000 40,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Improved Cattle Population Trend Pangani 10,357 10,390 96,195 66,928 170,860 86,441 73,449 Kilindi Handeni Tanga Korogwe Muheza Lushoto 15 87 60 29 51 56 54 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.50 TANGA Goat Density by District as of 1st October 2003 71 to 87 57 to 71 43 to 57 29 to 43 15 to 29 Number of Goats per Square Km MAP 3.49 TANGA Goat Population by District as of1st Octobers 2003 138,000 to 171,000 106,000 to 138,000 74,000 to 106,000 42,000 to 74,000 10,000 to 42,000 Number of Goats Tanzania Agriculture Sample Census RESULTS 77 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 3.12.2.2 Goat Herd Size Forty eight percent of the goat-rearing households had herd size of 1-4 goats with an average of 2 goats per goat rearing household. Eighty seven percent of total goat-rearing households had herd size of 1-14 goats and owned 57 percent of the total goats in the region resulting in an average of 5 goats per goat-rearing households. The region had 765 households (1.1%) with herd sizes of 40 or more goats each (53,587 goats in total), resulting in an average of 70 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 95 percent of the total goats in Tanga region. Improved goats for meat and diary goats constituted 3 and 2 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was -4.4 percent. This negative trend implies eight years of population decrease from 736,727 in 1995 to 514,620 in 2003. The number of goats decreased from 736,727 in 1995 at an estimated annual rate of -18.9 percent to 317,924 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 12.8 percent (Chart 128). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Tanga region after cattle and goats. The region ranked 9 out of 21 Mainland regions and had 4 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 35,381 (13% of all agricultural households in Tanga region) rearing 164,209 sheep, giving an average of 5 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Lushoto with 64,742 sheep (39%of total sheep in Tanga region) followed by Korogwe (35,367 sheep, 22%), Muheza (25,140 sheep, 15%), Handeni (19,570 sheep, 12%), Kilindi (18,222 sheep, 11%) and Tanga (1,010 sheep, 0.6%). Pangani District had the least number of sheep (158 sheep) (Chart 3.129 and Map 3.51). Lushoto district also had the highest density (47 head per km2 ) (Map 3.52). Sheep rearing was dominated by indigenous breeds that constituted 91 percent of all sheep kept in the region. Only 9 percent of the total sheep in the region were improved breeds. 736,727 317,924 514,620 - 200,000 400,000 600,000 800,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 20,000 40,000 60,000 80,000 Number of sheep Lushoto Korogwe Muheza Handeni Kilindi Tanga Pangani District Chart 3.129 Total Number of Sheep by District 35,367 25,140 1,010 158 18,222 19,570 64,742 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto Lushoto 0 8 8 6 23 16 47 Kilindi Handeni Pangani Tanga Korogwe Muheza MAP 3.52 TANGA Sheep Density by District as of 1st October 2003 37.6 to 47 28.2 to 37.6 18.8 to 28.2 9.4 to 18.8 0 to 9.4 Number of Sheep per Square Km MAP 3.51 TANGA Sheep population by District as of 1st Octobers 2003 51,700 to 64,800 38,800 to 51,700 25,900 to 38,800 13,000 to 25,900 100 to 13,000 Number of Sheep Tanzania Agriculture Sample Census RESULTS 79 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 80 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at -4.9 percent. The population decreased at an annual rate of -23.2 percent from 246,263 in 1995 to 85,679 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 17.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 16 out of 21 Mainland regions and is 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Tanga region was 2,601 (1% of the total agricultural households in the region) rearing 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Korogwe with 2,886 pigs (46% of the total pig population in the region) followed by Muheza (1,582 pigs, 25%), Handeni (759 pigs, 12%), Kilindi (389 pigs, 6%), Tanga (373 pigs, 6%) and Lushoto (292 pigs, 5%) (Chart 3.131 and Map 3.53). However Tanga district had the highest density (3.1 head per km2 ) (Map 3.54). There are no pigs were in Pangani district. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 24.7 percent. During this period the population grew from 1,072 to 6,281. The pig population increased from 1072 in 1995 to 2, in 1995 a higher rate of 26.2 percent. The growth rate dropped to 23.3 percent during the following four years from 1999 to 2003 in which pig population increased from 2,715 to 6,281(Chart 3.132). 246,263 85,679 164,209 - 100,000 200,000 300,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 0 1,000 2,000 3,000 Number of Pigs Korogwe Muheza Handeni Kilindi Tanga Lushoto District Chart 3.131 Total Number of Pigs by District 1,072 2,715 6,281 - 4,000 8,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 373 1,582 389 759 2,886 292 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 0.2 0.2 0 3.1 1 1.9 0.2 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.54 TANGA Pig Density by District as of 1st October 2003 2.48 to 3.1 1.86 to 2.48 1.24 to 1.86 0.62 to 1.24 0 to 0.62 Number of Pigs per Square Km MAP 3.53 TANGA Pig Population by District as of 1st Octobers 2003 2,890 to 2,890 1,580 to 2,890 760 to 1,580 370 to 760 0 to 370 Number of Pigs Tanzania Agriculture Sample Census RESULTS 81 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.5 Chicken Production The poultry sector in Tanga region was dominated by chicken production. The region contributed 5.4 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 176,806 raising about 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Tanga region was ranked eighth out of the 21 Mainland regions. The District with largest number of chickens was Muheza (468,300 chickens, 26% of the total number of chickens in the region) followed by Handeni (430,586, 24%), Korogwe (264,547, 15%), Lushoto (247,867, 14%), Kilindi (162,907, 9%) and Pangani (121,397 chickens, 7%). Tanga district had the smallest number of chickens (93,168, 5%) (Chart 3.133 and Map 3.55). However Tanga district had the highest density (776 head per km2 ) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 0.8 percent. The population decreased at a rate of -17.8 percent from 1995 to 1999 after which it increased to 23.7 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety two percent of all chicken in Tanga region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 85 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 6 chickens per holder. About 16 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 31 chickens per holder. Only 0.13 percent of holders kept the flock sizes of more than 100 chickens at an average of 208 chickens per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 66,036 37 164,365 2 5-9 47,677 27 308,323 6 10-19 36,365 21 461,035 13 20-29 15,520 9 345,418 22 30-39 4,980 3 157,343 32 40-49 3,245 2 137,272 42 50-99 2,760 2 168,679 61 100+ 223 0 46,333 208 Total 176,806 100 1,788,767 10 1,673,776 764,379 1,788,767 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 Number of Chickens Muheza Handeni Korogwe Lushoto Kilindi Pangani Tanga District Chart 3.133 Total Number of Chickens by District 121,393 93,168 468,300 430,586 162,907 264,547 247,867 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 181 776 290 71 127 170 181 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.56 TANGA Density of Chicken by District as of 1st October 2003 630 to 780 490 to 630 350 to 490 210 to 350 70 to 210 Number of Chickens per Square Km MAP 3.55 TANGA Number of Chicken by District as of 1st October 2003 393,000 to 469,000 318,000 to 393,000 243,000 to 318,000 168,000 to 243,000 93,000 to 168,000 Number of Chickens Tanzania Agriculture Sample Census RESULTS 83 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Tanga Region increased at an annual rate of 48.2 percent for the period of four years from 6,136 in 1999 to 29,630 in 2003. The number of improved chicken was most significant in Tanga District followed by Lushoto District (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 12.9 percent during which the population grew from 2,986 to 7,859. The annual growth rate was higher (65.4%) for the period of four years from 1995 to 1999. The broiler population exhibited a decreasing trend at the rate of -23 percent per annum for the period of four years resulting at increase from 22,327 in 1999 to 7,859 2003 (Chart 3.136). 3.12.6. Other Livestock There were 117,486 ducks, 503 turkeys, 16,611 rabbits and 17,502 donkeys raised by rural agricultural households in Tanga region. Table 3-32 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Muheza District (37% of all ducks in the region), followed by Korogwe (24%), Handeni (22%), Lushoto (7%), Tanga (5%) and Kilindi (4). Pangani district had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Muheza and Tanga districts only (Table 3.14). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 40 percent and 25 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Kilindi district but lowest in Lushoto district (Map 3.57). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Lushoto 7,722 0 12,558 8,764 0 Korogwe 28,561 0 2,024 643 0 Muheza 42,980 322 674 0 0 Tanga 5,556 182 416 25 239 Pangani 1,822 0 0 48 22 Handeni 25,758 0 940 6,082 530 Kilindi 5,088 0 0 1,940 773 Total 117,486 503 16,611 17,502 1,563 8,764 1,022 533 1,172 0 78 20,332 5,381 0 205 0 0 0 0 0 5,000 10,000 15,000 20,000 25,000 Number of Chickens Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers - 2,986 6,136 22,327 29,630 7,859 - 10,000 20,000 30,000 Number of layers 1995 1999 2003 Year Chart 3.136 Layers Population Trend Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Kilindi Handeni Tanga Korogwe Muheza Pangani Lushoto District Percent Ticks Tsetseflies Pangani 0 0 0 0 395 49 0 0% 0% 0% 0% 0% 0.2% 0.9% Kilindi Handeni Tanga Korogwe Muheza Lushoto Tanga 4,554 8,775 6,130 339 8,442 3,653 814 43% 24% 43% 38% 60% 82% 45% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.57 TANGA Number and Percent of Households Infected with Ticks by District Number of Households Infected with Ticks Number of Households Infected with Ticks Percent of Households Infected with Ticks MAP 3.58 TANGA Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Number of Households Using Draft Animals Percent of Households Using Draft Animals 7,100 to 8,800 5,400 to 7,100 3,700 to 5,400 2,000 to 3,700 300 to 2,000 320 to 400 240 to 320 160 to 240 80 to 160 0 to 80 Tanzania Agriculture Sample Census RESULTS 85 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 The most practiced method of tick controlling was spraying with 64 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (9%), smearing (1%) and other traditional methods like hand picking (10%). However, 15 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 50 percent of livestock-rearing households This was followed by dipping (13%) and trapping (1%). However, 36 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 48,587 (57% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 38 percent, goats (32%), sheep (17%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 53,666, representing 62 percent of the total livestock- rearing households and 20.2 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 98.6 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (1.1%) and large-scale farmers (0.3%). About 63 percent of livestock rearing households described the general quality of livestock extension services as being good, 19 percent said they were average and 15 percent said they were very good. However, 2 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 70 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 30 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected district was Pangani district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Tanga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.141). 0 20 40 60 Percent Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 2% Very Good 15% Good, 63% Average, 19% Poor, 1% RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 26,350 (92% of livestock rearing households in Tanga region) whilst 1,587 households (6%) resided between 5 and 14 kms. However, 597 households (2%) had to travel a distance of 15 or more kms to f the nearest watering point (Chart 3.142). Korogwe district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Tanga, Handeni and Lushoto districts. In Kilindi district about 37 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Tanga region is very limited with only 443 households (0.17% of the total households in the region) using them (Chart 3.144). Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 26,350, 92% 5-14 kms, 1,587, 6% 15 or more kms, 597, 2% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 2,500 5,000 7,500 10,000 Korogwe Handeni Lushoto Muheza Kilindi Pangani Tanga District Number of Households Less than 5 kms 5-14 kms 15 or more kms Chart 3.140 Number of Households by Distance to Verinary Clinic Less than 14km, 37,901, 30% More than 14km, 87,316, 70% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 Lushoto Handeni Korogwe Muheza Kilindi Tanga Pangani District Number of Households Less than 14 kms More than 14kms 3.144 Number of Households Using Draft Amimals Using draft animal, 443, 0.2% Not using draft animal, 264,755, 100% 0 100 200 300 400 Number of Households Korogwe Kilindi Lushoto Muheza Tanga Pangani Handeni District Chart 3.145 Number of Households Using Draft Animals by District - TANGA RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 88 The number of households that used draft animals in Korogwe was 395 representing 89 percent of the households using draft animals in the region were from Korogwe whilst in Kilindi only 49 households (11%) used draft animals. Use of draft animals was not reported in the other districts (Chart 3.145 and Map 3.58). The region had 1,132 oxen (987 oxen in Korogwe and 146 in Kilindi) that were used to cultivate 2,653.3 hectares of land. This represents only 0.03 perce nt of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Korogwe district (1,973.4 ha, 74.4% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Tanga region was 51,503 (20% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 27,331 ha of which 21,954 hectares (80% of the total area applied with organic fertiliser or 9.4% of the area planted with annual crops and vegetables in Tanga region during the long rainy season) was applied with farm yard manure (Map 3.59). 3.12.9.3 Use of Compost Only 5,377 ha (20% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Lushoto district with 13,238 hectares (60% of the total area applied with farm yard manure) followed by Korogwe (4,160 ha, 19%), Muheza (2,467 ha, 11%), Handeni (896 ha, 4%), Tanga (657 ha, 3%), Kilindi (389 ha, 2%) and Pangani (147 ha, 1%) (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Tanga region was 1,423, representing 0.5 percent of the total agricultural households in the region (Chart 3.148 and Map 3.61). Korogwe was the leading district with 634 households (1.4% of agricultural households) involved in fish farming. This was followed by Lushoto (430 households, 0.5%), Muheza (336 households, 0.7%) and Tanga (23 households, 0.3%). Fish farming was not practiced in Pangani and Handeni districts (Chart 3.149). Chart 3.148 Number of Households Practicing Fish Farming - TANGA Households Prcticing Fish Farming, 1,423, 1% Households Not Prcticing Fish Farming, 263,775, 99% Chart 3.147 Area of Application of Organic Fertiliser by District TANG A 0 5,000 10,000 15,000 Lushoto Korogwe Muheza Handeni Tanga Kilindi Pangani District Area of Fertiliser Application (ha) Farm Yard Manure Compost Chart 3.146 Number of Households Using Organic Fertiliser Not Using O rganic Fertilizer, 212,025, 80% Using Organic Fertilizer, 51,503, 20% Tanga Pangani 1,668ha 772ha 17ha 1,440ha 105ha 340ha 1,035ha 0% 0.01% 0.01% 0.02%% 0% 0.01% 0% Kilindi Handeni Korogwe Muheza Lushoto Tanga 4,160ha 147ha 389ha 896ha 657ha 2,467ha 13,238ha 6.4% 10% 1% 0.8% 5.9% 1% 2.5% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.59 TANGA Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District Planted Area with Farm Yard Manure Application Planted Area with Farm Yard Manure Application Percent of Total Planted Area with Farm Yard Manure Application MAP 3.60 TANGA Planted Area and Percent of Total Planted Area with Compost Manure Application by District Planted Area with Compost Manure Application Planted Area with Compost Manure Application Percent of Total Planted Area with Compost Manure Application 10,500 to 13,300 7,900 to 10,500 5,300 to 7,900 2,700 to 5,300 100 to 2,700 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Tanzania Agriculture Sample Census RESULTS 89 Tanga 1,661 7,747 723 1,883 1,679 12,191 3,310 18.6% 23.6% 15.7% 4.1% 25.5% 17% 0.8% Kilindi Handeni Pangani Korogwe Muheza Lushoto Tanga 105 1,035 1,440 340 17 772 1,668 1.4% 0.7% 0.3% 0.5% 0% 0% 0% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.61 TANGA Number and Percent of Households Practicing Fish Farming by District Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming MAP 3.62 TANGA Number and Percent of Households Without Toilets by District Number of Households Without Toilets Number of Households Without Toilets Percent of Households Without Toilets 520 to 640 390 to 520 260 to 390 130 to 260 0 to 130 9,900 to 12,200 7,600 to 9,900 5,300 to 7,600 3,000 to 5,300 700 to 3,000 Tanzania Agriculture Sample Census RESULTS 90 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 The main source of fingerings was the non governmental organizations and/or projects which provided fingering to 55 percent of the fish farming households. About 28 percent of households practicing fish farming got fingerings from their neighbours and 11 percent got them from government institutions. All fish farming households in the region used the dug-out- pond system and the main fish specie planted is Tilapia. The number of fish harvested in Tanga region was 249,570, of which 248,888 fish (99.7%) were tilapia and 682 (0.3%) were carp (Chart 3.150). About 75 percent of the fish farming households sold their fish while 25 percent did not sell. All fish were sold to their neighbours. ] 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were all weather road (38), tarmac road (38), hospital (36), tertiary market (32), secondary market (28), secondary school (17), primary market (9), health clinic (6), primary school (2) and feeder road (1) (Table 3.15). Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 29 percent reported them to be average. Twenty four percent of the agricultural households said the infrastructure and services were poor were , and 20 percent said they were ‘no good’. Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Lushoto 10.9 2.0 38.1 2.3 34 6.0 167.4 5.7 20.8 27.8 38.1 Korogwe 12.6 1.8 23.1 0.8 35 7.0 115.9 9.6 20.6 24.3 23.1 Muheza 13.1 2.2 24.5 1.1 28 5.6 49.7 12.3 23.8 29.2 24.5 Tanga 15.1 2.9 12.3 1.2 17 7.6 16.6 26.2 62.8 18.8 12.3 Pangani 21.4 2.3 48.7 0.7 24 4.7 67.7 10.6 56.1 27.3 48.7 Handeni 26.9 2.2 30.7 0.8 39 7.6 134.9 8.4 43.8 40.4 30.7 Kilindi 32.2 3.0 131.1 2.0 75 6.2 276.1 8.1 27.0 61.3 131.1 Total 16.5 2.2 38.0 1.5 36 6.4 131.1 9.1 28.3 31.9 38.0 0 100 200 300 400 500 600 700 Number of Households KorogweLushoto Muheza Tanga Pangani Handeni Kilindi District Chart 3.149 Number of Households Practicing Fish Farming by District - Tanga Chart 3.150 Fish Production Number of Tilapia, 248,888, 99.7% Number of Carp, 682, 0.3% RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (229,330 households, 86.5% of all rural agricultural households) 4,663 households (1.8%) use improved pit latrine and 1,733 households (0.7%) use flush toilets. The remaining 279 household (0.1%) use other toilets facilities. However, 29,194 households (11%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 41.8 percent of them were found in Handeni District and 2.5 percent were from Lushoto. The percentages of households without toilets in other districts were as follows Muheza (26.5%), Kilindi (11.3%), Korogwe (6.4%), Pangani (5.8) and Tanga (2.5%) Map 3.62). 3.13.3 Household’s Assets Radios are owned by most rural agricultural households in Tanga region with 162,610 households (61.3% of the agriculture households in the region) owning the asset. followed by bicycle ( 85,039 households, 32.1%), iron (50,029 households, 18.9%), wheelbarrow (8,928 households, 3.4%), mobile phone (5,112 households, 1.9%), television/video (2,714 households, 1.0%), vehicle (2,319 households, 0.9%) and landline phone (1,337 households, 0.5%) (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 77.3 percent of the total rural households using this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households in Tanga region. This is followed by charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), parrafin/kerosene (0.03%) and gas/biogas (0.01%) (Chart 3.154) Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 229,330, 86.5% Flush Toilet, 1,733, 0.7% No Toilet , 29,194, 11.0% Other Type, 279, 0.1% Improved Pit Latrine , 4,663, 1.8% Chart 3.152 Percentage Distribution of Households Owning the Assets 3.4 1.9 1.0 0.9 0.5 61.3 32.1 18.9 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 915, 0.35% Solar, 383, 0.14% Candles, 321, 0.12% Hurricane Lamp, 44,098, 16.63% Pressure Lamp, 11,043, 4.16% Mains Electricity, 3,315, 1.25% Gas (Biogas), 137, 0.05% Wick Lamp, 204,986, 77.30% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 736, 0.28% Crop Residues, 735, 0.28% Mains Electricity, 378, 0.14% Solar, 278, 0.10% Livestock Dung, 106, 0.04% Charcoal, 7,210, 2.72% Firewood, 255,643, 96.4% Parraffin / Kerocine, 90, 0.03% Gas (Biogas), 21, 0.01% Tanga Pangani 5,845 5,638 41,120 40,232 37,482 48,899 12,543 65.6% 79.1% 83.6% 84.3% 64% 81.5% 56.5% Kilindi Handeni Korogwe Muheza Lushoto Pangani Tanga 5,973 7,300 20,191 19,973 33,362 31,471 12,227 43.4% 83.8% 81.9% 67.8% 23.3% 65.9% 62% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.63 TANGA Number and Percent of Households Using Grass /Leaves for Roofing Material by District Number of Households Using Grass/Leaves for Roofing Material Number of Households Using Grass/ Leaves for Roofing Material Percent of Households Using Grass/ Leaves for Roofing Material MAP 3.64 TANGA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day Percent of Households Eating 3 Meals per Day 27,900 to 33,400 22,400 to 27,900 16,900 to 22,400 11,400 to 16,900 5,900 to 11,400 40,400 to 48,900 31,700 to 40,400 23,000 to 31,700 14,300 to 23,000 5,600 to 14,300 Tanzania Agriculture Sample Census RESULTS 93 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households. This was closely followed by iron sheets (43.6%), grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%) (Chart 3.155). Pangani district had the highest percentage of households with grass/leaves roofing (84%) followed by Tanga district (82%), Muheza (68%), Handeni (66%), Kilindi (62%), Korogwe (43%) and Lushoto (23%) (Chart 3.156 and Map 3.63). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Tanga region was unprotected spring (26 percent of households use unprotected wells during the wet season and 24 percent of the households during the dry seasons. This is followed by piped water (22% of households for each season), unprotected wells (20% of households during the wet season and 21% in the dry season), surface water (17% of households in the wet season and 18% during dry season) and protected wells with 9 percent of households using the source for both seasons. Covered spring was used as a main source by 3 percent of the households in the wet season and by 4 percent in the dry season Chart 3.157) About 55 percent of the rural agricultural households in Tanga region obtained drinking water within a distance of less than one kilometer during wet season compared to 46 percent of the households during the dry season. However, 45 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 54 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). Chart 3.155 Pe rce ntage Distribution of H ous e holds by Type of Roofing M ate rial Asbestos 1.1% Grass & Mud 4.8% Iron Sheets 43.6% Grass / Leaves 49.2% Tiles 1.0% Other 0.2% Concrete 0.1% Chart 3.156 Percentage Distribution of Households w ith G rassy/Leafy Roofs by District 23 43 62 66 68 82 84 0 25 50 75 100 Pangani Tanga Muheza Handeni Kilindi Korogwe Lushoto District Percent Chart 3.157 Percent of Households by M ain Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Unprotected Spring Piped Water Uprotected Well Lake /River Protected Well Protected Spring Other M ain source Percent of Households Wet Season Dry Season Chart 3.158 Percentof Households by Distance to M ain Source of Water and Season 0 10 20 30 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Tanga region normally have 3 meals per day (72.3 percent of the households in the region). This is followed by 2 meals per day (25.2 percent) and 1 meal per day (2.4 percent). Only 0.1 percent of the households have 4 meals per day (Chart 3.159). Lushoto district had the largest percent of households eating one meal per day whilst Handeni had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.64). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 177, 887 (67% of the agricultural households in Tanga region) with 86,741 households (48.8 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (33.4%). Very few households had meat three or more times during the respective week. About 32.9 percent of the agricultural households in Tanga region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 225, 800 (85% of the total agricultural households in Tanga region) with 52,958 households (23.5 % of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish three times (21.1%). In general, the percentage of households that consumed fish twice or more during the week in Tanga region was 191,435 (84.8% of the agricultural households that ate fish in the region during the respective period). About 14.9 percent of the agricultural households in Tanga region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66) Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Lushoto 4,337 5.0 33,209 38.4 48,899 56.5 135 0.2 86,580 Korogwe 615 1.3 7,894 17.2 37,482 81.5 0 0.0 45,990 Muheza 525 1.1 7,550 15.3 41,120 83.6 0 0.0 49,195 Tanga 133 1.5 2,926 32.8 5,845 65.6 10 0.1 8,914 Pangani 68 1.0 1,408 19.8 5,638 79.1 14 0.2 7,128 Handeni 523 1.1 6,878 14.4 40,232 84.3 106 0.2 47,739 Kilindi 146 0.7 6,964 35.4 12,543 63.8 0 0.0 19,654 Total 6,346 2.4 66,829 25.2 191,758 72.3 265 0.1 265,198 Chart 3.159 Number of Agriculural Households by Number of Meals per Day . Three Meals, 191,758, 72.3% Two Meals, 66,829, 25.2% Four Meals, 265, 0.1% Chart 3.160 Number of Households by Frequency of M eat and Fish Cosumption 0 25,000 50,000 75,000 100,000 O nce Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Pangani Tanga 660 622 4,623 3,741 5,023 4,089 15,606 9% 7% 10% 11% 19% 8% 18% Kilindi Handeni Korogwe Muheza Lushoto 33,590 1,613 17,868 10,811 1,841 14,692 6,327 38.8% 18.1% 36.3% 23.5% 25.8% 30.8% 32% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.65 TANGA Number and Percent of Households Eating Meat Once per Week by District Number of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week MAP 3.66 TANGA Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week Percent of Households Eating Fish Once per Week 27,200 to 33,600 20,800 to 27,200 14,400 to 20,800 8,000 to 14,400 1,600 to 8,000 12,600 to 15,700 9,600 to 12,600 6,600 to 9,600 3,600 to 6,600 600 to 3,600 Tanzania Agriculture Sample Census RESULTS 96 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 3.13.9 Food Security In Tanga region, 111,515 households (42% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 20,029 (7.6%) said they sometimes experience problems, 8.3 often experienced problems and 7.1 percent always had problems in satisfying the household food requirement. About 35 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main cash income of the households in Tanga region was from selling food crops (25.5 percent of smallholder households), followed by casual labour (20.9%), selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Only 4% of smallholder households reported the sale of livestock as their main source of income, followed by forest products (2.5%), livestock products (1.7%) and fishing (0.9%) (Chart 3.161). Chart 3.161: Percentage Distribution of the Number of Households by M ain Source of Income not applicable, 0.0, 0% Food Crops, 25.5, 26% Cash Crops, 16.8, 17% Other Casual Cash Earnings, 20.9, 21% Business Income, 14.3, 14% Remittance, 7.4, 7% Wages & Salaries, 5.0, 5% Livestock Products, 1.7, 2% Forest Products, 2.5, 3% Fishing, 0.9, 1% Other, 0.0, 0% Livestock, 4.0, 4% Tanga Pangani 1,960 1,556 10,168 12,979 9,825 19,078 5,410 22% 21.8% 22.1% 22% 20% 27.2% 28% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.67 TANGA Number and Percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 15,500 to 19,100 12,000 to 15,500 8,500 to 12,000 5,000 to 8,500 1,500 to 5,000 Tanzania Agriculture Sample Census RESULTS 98 DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 4 TANGA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Tanga Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. Tanga region has a land area of around 470,000 hectares under crop production and it has a relatively large number of crop growing households compared to other regions. It has the fifth largest number of crop growing households per square kilometer. The available land area per household is low (1.8 ha/household) with a utilized land area of 1.5 ha per crop growing households. Whilst most of the region is under annual crop production, it has significant areas of permanent crops mainly planted as a mixture with annual crops. It has the sixth largest planted area of cereals with maize having the third largest planted area in the country. The region has the third largest planted area of beans in the country and vegetable production is important with the exception of onions. Paddy and cassava production are low and sorghum is almost absent in the region. Important permanent crops are oranges having the largest planted area in the country and coconuts and sugar cane having the second largest planted area. Small quantities of bananas, cashew nut, mangoes, coffee and pigeon peas are produced. Compared to other regions, Tanga has a moderate planted area with irrigation and the number of households practicing irrigation has remained more or less unchanged over the a period of 10 years prior to the census. The source of irrigation water is equally split between rivers and canals. Gravity is the most common method of obtaining irrigation water closely followed by buckets/watering cans. Irrigation application is equally split between buckets/watering cans and flood. The method of cultivation in Tanga is almost entirely by hand. A very small quantity of fertilizer is used and is mostly farm yard manure and compost to a lesser extent. Virtually no pesticides are used. Compared to other regions, smallholder households in Tanga store moderate quantities of maize. Most of the storage is mostly in locally made traditional cribs, with small amounts stored in sacks or open drums. A relatively high number of households sell crops compared to other regions. The large majority of households process their crops by neighbours machines and very few households sell their processed produce. Compared to other regions, the number of smallholders in Tanga receiving extension services is moderate to high. Tanga has a small number of planted trees by smallholders and the species is mainly gravellis. Compared to other regions, the percent of households with erosion control/water harvesting facilities is moderate to high with terraces being one of the most prominent. Tanga has a low livestock population compared to other regions. It has a similar number of cattle and goats as Kilimanjaro; however it has a moderate to low density. Most of the cattle kept are indigenous, however there are more dairy cattle kept than in most other regions. Milk production is moderate and the farm gate price of milk is average. Goat numbers are moderate to low and there is a small population of sheep and pigs. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 Tanga has a moderate to high population of chickens, almost entirely made up of indigenous types. Egg production is moderate to low compared to other regions. The use of organic fertilizer is comparatively low and draft animals are not used for cultivation. The disease infection rate is moderate to high for most diseases. Access to livestock infrastructure and services is between average and poor. In relation to livestock population Tanga receives disproportionately more extension advice compared to other regions with much higher livestock populations. Tanga has moderate number of fish farmers. 4.2 District Profile The following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Lushoto Lushoto district has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Lushoto district is Annual Crop Farming, followed by Off farm Income and Permanent crop farming. However, the district has the highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Lushoto has a relatively high percent of female headed households (26%) and it has one of the lowest average age of the household head. With an average household size of 4.7 members per household it is average for the region. Lushoto has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region.. The literacy rate for the heads of household is also slightly higher than most of districts in the region. It has the smallest utilized land area per household (1.1ha) and the allocated area is fully utilised indicating a high level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (1.5ha) attributed to the high number of smallholders in the district. The district is moderately important for maize production in the region with a planted area of over 51,000ha, however the planted area per household is the lowest in the region. Paddy production is not important with a planted area of only 900 hectares and the production of sorghum is very small. Lushoto is the only district in the region that produces wheat (200ha). Cassava production is moderate accounting for 21 percent of the quantity harvested in the region. The district has a large planted area of Irish potatoes (15,000 ha) and it is the only district in the region that grows this crop. The production of beans in Lushoto is much higher than in other districts in the region with a planted area of 25,000ha. Oilseed crops are not important in Lushoto and no groundnuts were grown in the district. Vegetable production is important in the district. It has the largest planted area with tomatoes, cabbage and chilies (1,600 ha, 750 ha and 450 ha respectively) than other districts in DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 the region and accounts for 65 percent of the tomato production, 89 percent of the cabbage production and 60 percent of the chilly production in the region. Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. Compared to other districts in the region, Lushoto has a moderate planted area with permanent crops.which is dominated by coffee (2,000 ha), tea (1,000 ha) and bananas (1,000 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is very small, however district differences exist. Lushoto has the largest planted area with improved seed in Tanga region and this is due to the higher planted area of vegetables. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Lushoto district has a moderate level of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. Virtually no herbicide was used. It has the largest area with irrigation compared to other districts with 13,500 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage is in locally made traditional cribs, however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the largest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The highest percent of households processing crops in Tanga region is found in Lushoto district and is almost all done by hand. The district also has a higher percent of households selling processed crops to local markets/trade stores than other districts and no sales are to traders on farm. Although very small, access to credit in the district is to women only and the main sources are religious organisations/NGO projects and family friends and relatives. A comparatively larger number of households receive extension services in Lushoto and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Lushoto (with 600,000 planted trees) and is mostly Gravellis with some Cyprus and eucalyptus. The highest proportion of households with erosion control and water harvesting structures is found in Lushoto district and is mostly terraces, however it also has the highest number of vetiver grass strips, water harvesting bunds and tree belts than other districts. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts, however it has the largest population of sheep in the region. It has the smallest number of pigs in the region and a moderate number of chickens. Although small, the district has the second highest number of layers in the region. Small numbers of ducks, rabbits and donkeys are also found in the district. The smallest number of households reporting Tsetse and tick problems was in Lushoto district and it had the largest number of households de- worming livestock. The use of draft animals in the district is very small, A small number of households practice fish farming, however the district has the second largest number in the region. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 It has amongst the best access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to all weather roads and regional capital. Lushoto district has the second highest percent of households with no toilet facilities and it has the lowest percent of households owning bicycles, vehicles and tv/video and mobile phones. It has the second lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the smallest percent of households with grass roofs with 70 percent of households having iron sheets. The most common source of drinking water is from unprotected springs. It has the highest percent of households having two or one meal per day compared to other districts and the lowest percent with 3 meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.2 Korogwe Korogwe district has the fourth largest number of households in the region and it has a high percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Korogwe district is Annual Crop Farming, followed by Off farm Income. The district has the fourth highest percent of households with no off-farm activities although it has the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Korogwe has a relatively high percent of female headed households (25%) and it has one of the highest average age of the household head in the region. With a household size of 5 members per household it is average for the region. Korogwe has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. It has a moderate utilized land area per household (1.6ha) and 89 percent of the allocated area is currently being utilised. The district has the fourth largest planted area in the region, and the third largest planted area per household (1.8ha in the long rainy season and 1.1ha in the short rainy season). The district is moderately important for maize production in the region with a planted area of over 46,369 ha, and the planted area per maize growing household is also moderate for the region. The district has the largest planted area of paddy in the region with 2,659 hectares. Sorghum is not grown in the district. Cassava production is moderate to low, accounting for 13 percent of the quantity harvested in the region. The district has a very small planted area of Irish potatoes (90 ha). The production of beans in Korogwe, district is moderate to low with a planted area of 5,979ha. Korogwe district has the second largest groundnut planted area in Tanga region with a planted area per groundnut growing household of 0.34 ha. Vegetable production is moderately important in the district. Although small, it has the second largest planted area with tomatoes, cabbage and chilies (456 ha, 35 ha and 237 ha respectively)Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 Compared to other districts in the region, Korogwe has the second largest planted area with permanent crops which is dominated by bananas (2,069 ha), coconuts (1,682 ha), Mango (1,487 ha) and Cardamon (1,232 ha). Cashewnuts, coffee, tea, sugarcane, oranges and jack fruit are also grown in smaller quantities. As with other districts in the region, most land clearing is done by hand slashing, however there is a substantial area with no land clearing indicating bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Korogwe has the second largest planted area with improved seed in the region as well as the highest proportion of households using improved seeds. Though small, the district has the second highest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with farm yard manure. Compared to other districts in the region, Korogwe district has a moderate level of insecticide use. The use of fungicides and herbicides is low. It has the second largest area with irrigation compared to other districts with 6,600 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity methods. Flood is the most common means of irrigation water application followed by bucket/watering can and a very small amount of sprinkler irrigation is used. The most common method of crop storage in Korogwe district is in locally made traditional cribs, however the proportion of households not storing crops is average for the region. Korogwe has moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Korogwe is among the districts with the lowest percent of households processing crops in Tanga region and is almost all done by neighbours machine. The district also has the second highest percent of households selling processed crops to marketing cooperatives than other districts and no sales are to farmers associations or large scale farms. Access to credit in the district is extremely small. A comparatively larger number of households receive extension services in Korogwe district and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Korogwe (with 207,720 planted trees) and is mostly Gravellis and Eucalyptus. The second highest proportion of households with erosion control and water harvesting structures is found in Korogwe district and is mostly erosion control bunds and vertiver grass, however it also has the a number of tree belts and drainage ditches. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts, however it has the second largest population of sheep in the region. It has the largest number of pigs in the region and a moderate number of chickens. Some ducks, rabbits and donkeys are also found in the district. A number of households reported tsetse and tick problems and it has the second largest number of households de- worming livestock. A small number of households use draft animals, however it is the highest in the region. A small number of households practice fish farming, however the district has the largest number in the region. It has amongst the best access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to regional capital. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 The percentage of households without toilet facility in Korogwe district is comparatively low. It is amongst the districts with the lowest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the third largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is grass/leaves (43%), however it has a high percent of households with iron sheet roofing (42%) compared to most other districts. The most common source of drinking water is from unprotected springs. It is one of the districts with the highest percent of households having three meals per day. The district had one of the lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Muheza Muheza district has the second largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Muheza district is Annual Crop Farming, followed by Permanent Crop Farming. However, the district has the second highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Muheza has a relatively high percent of female headed households (26%) and it has one of the highest average age of the household head in the region. With an average household size of 4.7 members per household it is slightly below average for the region. Muheza has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The land area utilized per household (1.8ha) is around average for the region and 89 percent of the allocated area is currently being utilized which is moderate to high for the region. The district has the third largest planted area in the region and the forth largest planted area per household (0.92ha in the long rainy season and 0.84ha in the short rainy season). The planted area in the long rainy season is almost the same as that of the short rainy season. The district is moderately important for maize production in the region with a planted area of over 50,778 ha and the planted area per household is 0.7 ha which average for the region is. Paddy production is not important with a planted area of only 1,644 hectares; however it is the second highest in the region. Sorghum, Irish potatoes and wheat are not produced in the district. The district has the largest planted area of cassava accounting for 38 percent of the cassava planted area in the region. The production of beans in Muheza is much lower than in other districts in the region with a planted area of 875ha. Oilseed crops are important in Muheza with 50 percent of the groundnuts grown in the district. Vegetable production is not important and very small quantities of tobacco are grown in the district. Permanent crops are very important in Muheza district (45% of the total permanent crop planted area in Tanga region) and are more important than any other district in the region. The most prominent permanent crops in the district include coconuts (9,380 ha), cashew nuts (4,600 ha) bananas (2,281 ha) and cardamom (1,466 ha). It is the only district that produces black pepper (1,521 ha) and it has the highest area with oranges in the region (6,433 ha). Other permanent crops are either not grown or are grown in very small quantities. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is very small, however district differences exist. Muheza has the smallest planted area with improved seed in Tanga region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and practically all is with farm yard manure. Compared to other districts in the region, Muheza district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively small. It has the second largest area with irrigation in the region with 21,896ha of irrigated land. The most common source of water for irrigation is from wells and rivers and almost all water application is by using hand bucket. The most common method of crop storage is in Muheza is locally made traditional cribs, and the proportion of households not storing crops in the district is moderate to low for the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Muheza district has a high percent of households processing crops in the region and is almost all done by hand; however, the district has the highest percent of households processing crops by trader. Small quantities of processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Muheza district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Muheza district (with 403,112 planted trees) and is mostly Tectona Grandis with some Gravellis and Sienna Spp. The second highest proportion of households with water harvesting bunds is found in Muheza district and it also has the third highest number of erosion control bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the second largest number of pigs in the region and the largest number of chickens, all of which are indigenous. Virtually no improved chicken are found in the district. The district has the largest number of ducks, and a small number of rabbits and turkeys are found in the district. A small number of households reported tsetse and tick problems in Muheza district. A small amount of de-worming of livestock is practiced in the district No draft animals are used. Fish farming is practiced by a small number of households; however the district has the third largest number in the region. It has amongst the best access to secondary schools, primary schools, health clinics, feeder roads and primary markets compared to other districts. However, it has one of the worst accesses to tertiary markets and the regional capital. The percentage of households without toilet facility in Muheza district is average for the region; however it has the second highest percent of households with no toilet facilities. It has the lowest percent of households owning land line phones, vehicles and TV/video. It has the third lowest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (68%) and only 29 percent of households have iron sheet roofing. The DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 most common source of drinking water is from unprotected wells. Sixteen percent of the households in the district reported having one or two meals per day and virtually no household reported having more than three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Tanga Tanga district has an average number of households for the region and it has the smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Tanga district is off-farm income followed by Permanent crop farming. It has the lowest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tanga district has a relatively high percent of female headed households (28%) and it has one of the highest average ages of the household head. With an average household size of 4.6 members per household it is average for the region. Tanga district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. It has the second smallest utilized land area per household (1.4 ha) and only 76 percent of the allocated land area is utilised. The total planted area is the smallest in the region however it has the second lowest planted area per household (0.78ha in the long rainy season and 0.664ha in the short rainy season. Tanga district is not important for maize production in the region with a planted area of only 3,946 ha, and the planted area per household is among the lowest in the region. Paddy production is also not important with a planted area of only 545 hectares and the production of sorghum is small. Cassava and bean production in Tanga district was small and Irish potato and wheat is not grown. Oilseed crops and vegetables are not important in the district however, whist the district has one of the smallest planted areas with tomatoes it is the second in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Tanga district has the smallest planted area with permanent crops (3.3% of total permanent crop planted area) which is dominated by cashew nuts (959 ha), coconuts (964 ha), A small area of bananas and oranges are grown. Apart from a minor amount of sugarcane no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 The use of inputs in the region is very small, however district differences exist. Tanga district has the smallest planted area with improved seed; however it has the highest planted area per household in the region. The district also has the smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with farm yard manure. Compared to other districts in the region, Tanga district has the lowest area planted with insecticide but has the second highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the highest for herbicides. It has one of the smallest areas of irrigation 2679 ha. The most common source of water for irrigation is from rivers using hand buckets/Bucket. Watering cans are the most common means of irrigation water application. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in Tanga district is the highest in the region. The number of households selling crops in the district is among the smallest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The smallest percent of households processing crops in the region is found in Tanga district and processing is mostly done by neighbor’s machine. The district has the largest number of households processing crops on farm by machine. It also has the second largest number of households processing crops on farm by hand. Most households that sell crops sell to neighbors and no sales are to traders on neither farm nor large scale farms. Access to credit in the district is very small. A very small number of households receive extension services in Tanga district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Tanga district (with only 296 planted trees) and all of them are Sienna Spp. The largest proportion of households in Tanga district use terraces for erosion control. Tanga district has the second smallest number of cattle in the region and most of them are indigenous. It is one of the districts with the least number of goats in the region, however the district has the highest density (87 head per km2) Tanga is also one of the districts with the smallest number of sheep, pigs and chicken, however it has the largest number of improved chickens (both layers and broilers) in the region. Small numbers of ducks, rabbits, turkeys and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Tanga district and it had one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and very few households practice fish farming. It is amongst the districts with the best access to secondary schools, primary schools, feeder roads, all weather roads, health clinics, hospitals, regional capital, tarmac roads and tertiary markets compared to other districts. However, it has the worst access to primary and secondary markets. Tanga district has a small number of households with no toilet facilities. The district has the highest percent of households owning wheel barrows, vehicles and television/video, land line and mobile phones and it has the second highest percent of households with radio, bicycles and irons. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the second largest percent of households with grass roofs with only 16 percent of households having iron sheets. The most common source of drinking water is piped water and it has the second highest percent of households having two or one meal per day compared to other districts and the third lowest percent with 3 meals per day. The district had the highest DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 percent of households that did not eat meat during the week prior to enumeration but has the lowest percent of households that did not eat fish. Most households seldom had problems with food satisfaction. 4.2.5 Pangani Pangani district has the smallest number of households in the region and it has the second lowest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Pangani district is off farm income followed by Annual Crop Farming, Tree/Forest Resources and Fishing/Hunting and Gathering. The district has the third lowest percent of households with no off-farm activities and the second largest percent of households with more than one member with off- farm income. Compared to other districts in the region, Pangani has a moderate percent of female headed households (24%) and it has one of the highest average ages of the household head. With an average household size of 4.1 members per household it is slightly lower than the regional average. Pangani has the highest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the lowest in the region. It has one of the smallest utilized land area per household (1.4 ha) which is slightly lower than the regional average of 1.7 ha per household. The district has smallest planted area in the region, however it has the second largest planted area per household (1.6 ha) in the long rainy season. The district is not important for maize production with a planted area of 7,042 ha, however the planted area per household is moderate compared to other districts in the region. Paddy production is also not important with a planted area of only 500 hectares and the production of sorghum is very small. Wheat and finger millet are not grown in the district. The district has among the lowest percent of cassava planted area in the region and it has virtually no Irish or sweet potatoes. The production of beans in Pangani district is the smallest in the region with a planted area of only 4 ha and oil crops are not important in the district. Vegetable production is also not important in the district; however the district has largest planted area per tomato growing household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Pangani has a small planted area with permanent crops (4,623 ha) which is dominated by coconuts (2,418 ha) and cashew nuts (1,766 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Pangani has one of the smallest planted areas with improved seed in Tanga region however it has one of the highest percent of planted area using improved seed. The district has the smallest planted area with fertilizers and most of this is with farm yard manure with no inorganic fertiliser. Compared to other districts in the region, Pangani district has the second highest percent of its planted area with DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 insecticides in the region. The use of fungicides was the was one of the lowest in the region and virtually no herbicide was used. It has the smallest planted area with irrigation in the region with only 2310 ha of irrigated land. Rivers, wells boreholes and canals is used as the source of irrigation water and hand bucket was mainly used. Buckets/Water cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is the second highest in the region. The district has the smallest number of households selling crops and the main reason for not selling is insufficient production. Pangani district has the highest percent of households processing crops on farm by hand and a small percent of households selling processed crops mainly to neighbours and trader at farm. No sales were made to farmers associations, marketing cooperatives or large scale farms. Access to credit is non existent in the district and the main reason for not using credit is lack of awareness. A comparatively small number of households receive extension services in Pangani district and all of this is from the government. The quality of extension services was rated between good and average by most of the households. Tree farming is not important in Pangani (with only 3,229 planted trees) and is mostly with Tectona Grandis with some Azadritachta Spp, Moringa Spp and Gravellis. The smallest number of erosion control and water harvesting structures is found in Pangani district and they are tree belts only. The district has the smallest number of cattle in the region and they are mostly all indigenous. Goat and sheep production is smallest in the region, and no pigs are found in the district. It has a comparatively smallest number of chickens. Small numbers of ducks and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Pangani district and has the smallest number of households de-worming livestock. The use of draft animals in the district is non existent and no fish farming is practiced in the district. It is amongst the districts with the best access to primary schools, feeder roads, health clinics and primary markets; however it has one of the worst accesses to all weather roads, regional capital, secondary markets and tarmac roads. Pangani district has a low percent of households with no toilet facilities. The district has the largest percent of households owning radios and bicycles and no ownership of land line phones was reported. Very small number of households reported ownership of vehicles, mobile phones, wheel barrows and televisions/videos. It has the second largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the largest percent of households with grass roofs and only 13 percent of households having iron sheets. The most common source of drinking water is from piped water, unprotected wells and surface water... It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a high percent of households with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration; however it is among the districts with low percent of households that did not eat fish during the week. Most households in the district seldom had problems with food satisfaction. 4.2.6 Handeni DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 Handeni district has a moderate number of households in the region and it has one of the highest percents of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Handeni district is Annual Crop Farming, followed by off farm Income, Fishing/Hunting and Gathering and Tree/Forest resources. The district has a high percent of households with no off-farm activities however it has the forth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Handeni has the second lowest percent of female headed households (21%) and it has one of the lowest average ages of the household head. With an average household size of 5.4 members per household it is the largest for the region. The literacy rate among smallholder households in Handeni is low compared to other districts in the region and associated with this is a number of household members who have never attended school. It has the largest utilized land area per household (2.6 ha) in Tanga region. The total planted area is the second largest in the region and has the largest planted area in the long rainy season. However the planted area per household in the long rainy season the district had the fifth largest planted area per household with 0.63 ha per household in the short rainy season and 0.98 ha in the long rainy season. The district is the most important for maize production in the region with a planted area of 95,688 ha and the planted area per household is the second largest in the region. Paddy production is moderate for the region with a planted area of 1,245 hectares and the district has the largest planted area per paddy growing household. Production of sorghum and finger millet is very small. The district also has the largest planted area of cow peas (7,982) and green grams (817 ha), however very little beans and field peas are produced. Cassava production is relatively low accounting for 10.3 percent of the total cassava planted area in the region. Oilseed crops are important in Handeni with the largest planted area of simsim in the region (680 ha) and the third largest planted area of groundnuts. Vegetable production is not important in the district; however tomatoes, cabbage, water melon, bitter aubergine, pumpkins and amaranths are produced in very small quantities. Handeni is the only district that cultivates cotton although the planted area is small. Compared to other districts in the region, Handeni has a moderate planted area with permanent crops which is dominated by oranges (2,201 ha), Mango (1,271 ha), bananas (1,143 ha) and Jack fruit (904 ha). Other permanent crops are either not grown or are grown in small quantities. Most land clearing is done by hand slashing, however it has the highest Planted Area with “no land clearing” indicating the presence of a large area of bare land before cultivation. It has also the largest area of bush clearance in the region. Most land preparation is done by hand, however a it has the highest planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Handeni has a moderate planted area with improved seed in Tanga region. The use of fertilizer is very small and is mostly farm yard manure and compost. No inorganic fertilizer is used. Compared to other districts in the region, Handeni district has a small percentage of the planted area in the district with fungicides application and a small amount of herbicide was used. It has the third largest area with irrigation with a planted area of 5,380 ha under irrigation. The most common source of water for irrigation is from wells using hand buckets. Buckets/Watering cans are the only means of irrigation water application in the district. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 111 The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is moderate to low when compared to other districts in Tanga region. The district has a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Handeni is among the districts in Tanga region with a high percent of households processing crops and is mostly done using neighbors machines. The district also has a small percent of households selling processed crops mostly to neighbours and traders on farm. Access to credit in the district small. A comparatively small number of households receive extension services in Handeni and mostly from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Handeni (with only 2,014 planted trees) and is mostly Senna Spp with some Saraca Spp and Gravellis. A small proportion of households with erosion control and water harvesting structures is found in Handeni district and is mostly drainage ditches, terraces and erosion control bunds, It also has a small number of tree belts for erosion control. The district has the largest number of cattle in the region and they are almost all indigenous. Goat population is also the largest in the region; however it has one of the smallest populations of sheep in the region. The district has a comparatively moderate to low number of pigs in the region but it has the second largest chicken population, all of which are indigenous. A moderate numbers of ducks, donkeys and rabbits are also found in the district. It has the second highest proportion of households reporting Tsetse and tick problems in the region and it had a moderate to low number of households de-worming livestock compared to other districts. Draft animals are not used and fish farming is not practiced. It is amongst the districts with the best access to primary schools, feeder roads, health clinics and primary markets, however it has one of the worst access to regional capital, secondary and tertiary markets, tarmac roads and all weather roads. Handeni district has the highest percent of households with no toilet facilities. Though small, it has the second highest percent of households with wheel barrows and mobile phones, however and it among the districts with a low percent of households owning vehicles and land line phones. It has a small number of households using mains electricity. The most common source of energy for lighting is the wick lamp and almost all households use firewood for cooking. The district has a moderate to high percent of households with grass roofs with and 29 percent of households have iron sheet roofing. The most common sources of drinking water are from unprotected wells and piped water. It has the highest percent of households having three meals per day compared to other districts and moderate percent with one or two meals per day. The district has a moderate to high percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.7 Kilindi Kilindi district has the second smallest number of households in the region; it has however it has of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and though small, it is the only district with pastoralists. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 112 The most important livelihood activity for smallholder households in Kilindi district is Annual Crop Farming, followed by off farm Income/ Fish/hunting and Gathering and tree/Forest Resources. However, the district has a moderate to high percent of households with no off-farm activities and a moderate percent of households with more than one member with off-farm income compared to other districts in the region, Kilindi has the lowest percent of female headed households (18%) in the region and it has the lowest average age of the household head. With an average household size of 5.3 members per household it is the second largest for the region. Kilindi has the lowest literacy rate among smallholder households in and this is reflected by the relatively high level of never attended school in the region... The literacy rates for the heads of household are the lowest in the region. It has the second largest utilized land area per household (2.5 ha) in the region. The total planted area is moderate compared to other districts in the region due to the presence of good wet and dry seasons, however it has the largest planted area per household (1.8 ha during the long rainy season and 1.1 ha in the short rainy season). The district is moderately important for maize production in the region with a planted area of over 32,536 ha and the planted area per maize growing household is the largest in the region. The district has the smallest planted area of paddy (142 ha) and sorghum, finger millet and wheat are not produced in the district. Cassava production is small accounting for only 5 percent of the cassava planted area in the region. The production of beans in Kilindi though comparatively small (8,245 ha) is higher than in most other districts in the region. Other pulses produced in the district are of minor importance. Oilseed crops are not important in Kilindi, however it is the only district in the region which grows castor seeds. Vegetable production is not important in the district; however tomatoes, cabbage, onions and other vegetables are grown in small quantities. Tobacco is the only traditional cash crop grown in the district in small quantities. Compared to other districts in the region, Kilindi has a moderate planted area with permanent crops which is dominated by pigeon peas (2,417 ha) and mangoes (1,320 ha). Small quantities of banana, sugar cane, cardamom and jack fruit are also grown and other permanent crops are either not grown or are grown in very small quantities. Most land clearing is done by hand slashing, however it has a high planted area with “no land clearing” indicating the presence of a large area of bare land before cultivation. Most land preparation is done by hand, however it has a very small planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Kilindi has a one of the smallest percentaqge of its planted area with improved seed and fertilizers (compost and Farm yard manure, however most of this is compost). The district has a relatively small level of insecticide and fungicides use, however the use of herbicides, though small, was the second highest in the region. It has the second smallest area of irrigation with only 2,927 ha of irrigated land. The most common source of water for irrigation is from wells using hand buckets. Buckets/Watering cans are the most common means of irrigation water application and a very small amount of food irrigation is used. The most common method of crop storage is in locally made traditional cribs and sacks/open drums. The proportion of households not storing crops in the district is the second lowest in the region. The district has a small number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The second highest percent of households processing crops in Tanga region is found in Kilindi district and is mostly done using DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 113 neighbors machines, virtually no processing as done on farm by machine... The district has a small percent of households selling processed crops mostly to neighbours and local markets/trade stores. There is no access to credit in the district. A comparatively small number of households receive extension services in Kilindi district and almost all of this is from the government. The quality of extension services was rated bet ween good and average by the majority of the households. Tree farming is not important in Kilindi (with only 4,326 planted trees) and is mostly Morringa and Gravellis with some Eucalyptus Spp, Terminala Catapa and Syszygium Spp. A relatively small proportion of households with erosion control and water harvesting structures is found in Kilindi district and is mostly tree belts and erosion control bunds; however it also has a number of water harvesting bunds, drainage ditches and vetiver grass. The district has a moderate to low number of cattle in the region and they are all indigenous. Goat production is also moderate to low compared to most other districts, however it has a relatively small population of sheep compared to other districts in the region. It has one of the smallest numbers of pigs in the region and a moderate to low number of chickens, with no improved chicken. Small numbers of ducks and donkeys are also found in the district. The largest number of households reporting tsetse and tick problems was in Kilindi district; however it has one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and no fish farming is practiced in the district. It is amongst the districts with the best access to primary schools, feeder roads, health clinics, and primary markets, however it has one of the worst access to the regional capital, tarmac roads, all weather roads, tertiary markets, secondary markets and secondary schools. Kilindi district has the third highest percent of households with no toilet facilities and it has one of the lowest percent of households owning landline and mobile phones, vehicles and televisions/video. It has no access to mains electricity. The most common source of energy for lighting is the wick lamp and most of the households use firewood for cooking. The district has a moderate percent of households with grass roofs with 26 percent of households having iron sheet roofing. The most common source of drinking water is from unprotected well. It has the second highest percent of households having two or one meal per day compared to other districts and the second lowest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat during the week prior to enumeration; however it has the second highest percent of households that did not eat fish during the respective period. Most households seldom had problems with food satisfaction. APPENDIX II 114 4. APPENDICES Appendix I Tabulation List.................................................................................................. 115 Appendix II Tables ................................................................................................................ 130 Appendix III Questionnaires ................................................................................................. 301 APPENDIX II 115 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD 2.1 Number of Agricultural Households by type of Household and District during 2002/03 Agriculture Year.......... 131 2.2.1 Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year.................. 131 NUMBER OF AGRICULTURE HOUSEHOLDS.......................................................................................................... 133 3.0 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year ..................................................................................................................................... 134 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District ........................................................................................................................................... 134 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES..................................................................................... 135 3.1a First Most Importance............................................................................................................................................ 136 3.1b Second Most Importance ....................................................................................................................................... 136 3.1c Third Most Importance .......................................................................................................................................... 136 3.1d Fourth Most Importance ........................................................................................................................................ 136 3.1e Fifth Most Importance ........................................................................................................................................... 136 3.1f Sixth Most Importance........................................................................................................................................... 136 3.1g Seventh Most Importance ...................................................................................................................................... 136 HOUSEHOLDS DEMOGRAPHS.................................................................................................................................... 139 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) .......................................................................................................................................................... 140 3.3 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (col %) .......................................................................................................................................................... 140 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year ................. 141 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year............................................................................. 141 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ..................................................................................................................................... 141 3.7 Number of Agricultural Household Members by Main Activity and District ....................................................... 141 Cont… Number of Agricultural Household Members by Main Activity and District.......................................... 142 Cont… Number of Agricultural Household Members by Main Activity and District.......................................... 142 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ..................................................................................................................................... 142 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ..................................................................................................................................... 143 APPENDIX II 116 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year................................................................................................................. 144 3.11 Number of Agricultural Households Involved in Off Farm Income Generating Activity by Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ................................................................... 144 3.12 Number of Heads of Agricultural Households by Maximum Education Level Attained and District, 2002/03 Agricultural Year ................................................................................................................................................... 144 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District..................................................... 144 3.14 Time Series of Male and Female Headed Households .......................................................................................... 145 3.15 Literacy Rate of Heads of Households by Sex and District................................................................................... 145 LAND ACCESS/OWNERSHIP........................................................................................................................................ 147 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year .......................................................................................................................................................... 148 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year..................... 148 LAND USE .......................................................................................................................................................... 149 5.1 Number of Agricultural Households by Type of Land Use and District for the 2002/03 Agricultural Year......... 150 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year ...................................... 150 5.3 Number of Households by type of household and District during 2002/03 Agricultural Year.............................. 151 5.4 Number of Agricultural Households by whether they consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year.................................................................................... 151 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year ......................................................................................... 151 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION- LONG & SHORT RAINY SEASON ................. 153 7.1&7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District ........................................ 154 7.1&7.2b Number of crop growing Households Planting Crops by Season and Region ..................................................... 154 7.1&7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Tanga Region .......................................................................................................................................................... 155 7.1&7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03- Short and Long Season, Tanga Region.................................................................................................................. 156 7.1&7.2e Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Tanga .................................................................................................................. 157 APPENDIX II 117 7.1&7.2f Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 Agriculture Year - LONG & SHORT RAINY SEASON, Tanga ......................................................................... 157 7.1&7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 Agriculture Year - LONG & SHORT RAINY SEASON, Tanga Region.............................................................. 157 7.1&7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture year - LONG & SHORT RAINY SEASON....................................................................................... 158 7.1&7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture year - LONG & SHORT RAINY SEASON, Tanga........................................................................... 158 7.1&7.2j Number of Crop Growing Households and Planted Area by Fungicide Use and District during 2002/03 Crop Year LONG & SHORT RAINY SEASON, Tanga Region .......................................................................... 159 7.1&7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Tanga Region........................................................................ 159 ANNUAL CROP AND VEGETABLE PRODUCTION – SHORT RAINY SEASON ................................................ 161 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Tanga Region........................................................................................................................................ 162 7.1b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON, Tanga Region ................................................................................................... 162 7.1c Number of Crop Growing Households and Planted Area by Irrigation Use and District during 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region........................................................................................... 162 7.1d Number of Crop Growing Households and Planted Area by Insecticide Use and District during 2002/03 Crop Year in SHORT RAINY SEASON............................................................................................................... 163 7.1e Number of Crop Growing Households and Planted Area by Herbicide Use and District during 2002/03 Crop Year SHORT RAINY SEASON.................................................................................................................. .163 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON............................................................................................................................ 164 . 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region............................................................................. 164 ANNUAL CROP AND VEGETABLE PRODUCTION – LONG RAINY SEASON .................................................. 165 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District during 2002/03 Crop Year-LONG RAINY SEASON, Tanga Region...................................................... 166 7.2b Number of Crop Growing Households and Planted Area by Fertilizer Use and District during the Long Rainy Season ................................................................................................................................................ 166 7.2c Number of Crop Growing Households and Planted Area by Irrigation Use and District during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................ 166 7.2d Number of Crop Growing Households & Planted Area by Insecticide Use and District – LONG RAINY SEASON....................................................................................................................................... 167 7.2e Number of Crop Growing Households and Planted Area by Herbicide Use and District during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................. 167 APPENDIX II 118 7.2J Number of Crop Selling Households and Reported Agriculture Products during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................. 167 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region ..................................................................................................... 168 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON, Tanga Region ............................................................................ 168 7.2h Planted Area and Number of Crop Growing Households during the Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agricultural Year ................................................................................................... 169 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 170 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 170 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................................. 170 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 170 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................................. 171 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 171 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 171 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 171 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 172 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyam Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 172 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 172 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 172 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 173 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 APPENDIX II 119 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Field peas Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 174 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 175 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 175 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 175 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District 2002/03 Agricultural Year ...................................................................................... 175 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 176 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 176 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 176 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 177 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District 2002/03 Agricultural Year ..................................................................................... 177 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Jute Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 APPENDIX II 120 PERMANENT CROPS ......................................................................................................................................................... 179 7.3.1 Production of Permanent Crops by crop type and Region – Tanga ....................................................................... 180 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 181 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 182 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 183 Cont…Production of Permanent Crops by crop type and Region – Tanga ........................................................... 184 Cont…Area planted and area per Household by Region – Tanga ......................................................................... 185 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 186 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 187 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 188 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 189 AGROPROCESSING........................................................................................................................................................ 191 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year ................................................................................................................................................... 192 8.0b Number of Crops Growing Households by Method of Processing and District 2002/03 Agricultural Year- Tanga Region ............................................................................................................................................... 192 8.1.1a Number of Crop Growing Households Processing Crops during 2002/03 Agricultural Year by Location and Crop, Tanga Region ......................................................................................................................... 192 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced during 2002/03 Agricultural Year By Use of Product and Crop, Tanga Region............................................................................. 193 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced during 2002/03 Agricultural Year By Location of Sale of Product and Crop, Tanga Region......................................................... 193 8.1.1d Number of Crop Growing Households by Main Product and District during 2002/03 Agriculture Year, Tanga Region ......................................................................................................................................................... 193 8.1.1e Number of Crop Growing Households by Use of Primary Processed Product and district during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................ 194 8.1.1f Number of Crop Growing Households by Where Product Sold and District during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................................... 194 8.1.1g Number of Crop Growing Households By type of By-Product and District during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................................... 194 MARKETING .......................................................................................................................................................... 195 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Tanga Region.................................................................................................................. 196 10.2 Number of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year.......................................................................................................................... 196 10.3 Proportion of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year ................................................................................................................................................... 196 APPENDIX II 121 IRRIGATION /EROSION CONTROL ........................................................................................................................... 197 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural Year by District.................................................................................................................................................... 198 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year................................ 198 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year..................................................................................................................... 198 11.4 Number of Agriculture Households by method of used to obtain water and district during 2002/03 Agriculture Year .......................................................................................................................................................... 198 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year ..................................................................................................................................... 199 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land by District................... 199 11.7 Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 Agriculture Year .................................................................................................................................................... 199 ACCESS TO FARM INPUTS/IMPLEMENTS .............................................................................................................. 201 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year .......... 202 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District during 2002/03 Agricultural Year .......................................................................................................................................................... 202 12.1.3 Number of Agricultural Households Using COMPOST Manure by District during 2002/03 Agricultural Year .......................................................................................................................................................... 202 12.1.4 Number of Crop Growing Households Using Insecticides/Fungicides by District during 2002/03 Agricultural Year ................................................................................................................................................... 203 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year.............. 203 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year............ 203 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.9 Number of Agricultural Households by Source of COMPOST Manure and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.10 Number of Agricultural Households by Source of Pesticides/Fungicides and District, 2002/03 Agricultural Year ................................................................................................................................................... 205 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year............... 205 12.1.12 Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year ................................................................................................................................................... 205 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ................................................................................................................................................... 206 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 206 APPENDIX II 122 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................................... 209 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .......................................................................................................................................................... 209 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ................................................................................................................................................... 209 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................................................... 211 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year.............. 211 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................................................................................................... 211 12.1.37 Number of Agricultural Households with Plan to use Chemical Fertilizers Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 211 12.1.38 Number of Agricultural Households with Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.39 Number of Agricultural Households with Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.40 Number of Agricultural Households with Plan to use Pesticides/Fungicides Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.41 Number of Agricultural Households with Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.42 Number of Agricultural Households with Plan to use Improved Seeds next year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 APPENDIX II 123 AGRICULTURE CREDIT ............................................................................................................................................... 213 13.1a Number of Households Reporting the Main reasons for Not Using Credit by District during the 2002/03 Agriculture Year..................................................................................................................................................... 215 13.1b Number of Credits Received by Main Purpose of Credit and District during the 2002/03 Agriculture Year........ 215 13.2a Number of Agriculture Households receiving Credit by sex of household head and District during the 2002/03 Agriculture Year....................................................................................................................................... 214 13.2b Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year..................................................................................................................................................... 214 TREE FARMING AND AGROFORESTRY .................................................................................................................. 217 14.1 Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region ............. 218 Cont…. Number of Planted Trees by Species and District during the 2002/03 Agriculture Year, Tanga Region ......................................................................................................................................................... 218 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 219 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region ......................................................................................................................................................... 219 14.4 Number of Households with planted trees on their land and Number of Trees by Planting Location and District during the 2002/03 Agriculture Year, Tanga Region ........................................................................ 220 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Tanga Region......................................................................................................................................................... 220 14.6 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region ......................................................................................................................................................... 221 CROP EXTENSION .......................................................................................................................................................... 223 15.1 Number of Agriculture Households Receiving Extension Messages by District during the 2002/03 Agriculture Year, Tanga Region ........................................................................................................................... 224 15.2 Number of Households by Quality of Extension Services and District during the 2002/03 Agricultural Year, Tanga Region ......................................................................................................................................................... 224 15.3 Number of Agriculture Households by Source of Crop Extension Messages and District during the 2002/03 Agriculture Years, Tanga Region........................................................................................................................... 224 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 225 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District during the 2002/03 Agriculture Year, Tanga Region .............................................................................................................. 225 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District during the 2002/03 Agriculture Year, Tanga Region .............................................................................................................. 225 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 226 APPENDIX II 124 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................... 226 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District during the 2002/03 Agriculture Year ........................................................................................................ 226 15.10 Number of Agriculture Households Receiving Advice on Mechanization /LST by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 227 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................... 227 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 227 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 228 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 228 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 228 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 229 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region............................................................................................ 229 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) during the 2002/03 Agriculture Year, Tanga Region ......................................... 229 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) during the 2002/03 Agriculture Year, Tanga Region ............................................. 230 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) during the 2002/03 Agriculture Year, Tanga region............................................... 230 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) during the 2002/03 Agriculture Year, Tanga Region ............................................. 231 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) during the 2002/03 Agriculture Year, Tanga region............................................... 231 ANIMAL CONTRIBUTION TO CROP PRODUCTION .................................................................................................................. 247 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Tanga Region .......................................................................................................................................................................... 248 17.2 Type of Draft by Number Owned, Used and Area Cultivated (acres) By District during 2002/03 agriculture year, Tanga Region .......................................................................................................................................................................... 248 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Tanga region .......................................................................................................................................................................... 248 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Tanga Region .................. 248 CATTLE PRODUCTION...................................................................................................................................................................... 249 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Tanga Region..................................... 250 APPENDIX II 125 18.2 Total Number of Cattle by Type and District as of 1st October 2003....................................................................................... 250 18.3 Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 ................................................................................................................................................ 250 18.4 Total Number of Cattle by Category and Type of Cattle; on 1st October 2003........................................................................ 250 18.5 Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003............................................... 251 18.6 Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003........................................................ 251 18.7 Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003......................................................... 252 18.8 Total Number of Cattle by Category and District as on 1st October 2003............................................................................... 252 GOAT PRODUCTION .......................................................................................................................................................................... 253 19.1 Total Number of Goats by goat type and District as on 1st October 2003................................................................................ 254 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003............................................... 254 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 ........................................................................... 255 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 ................................................................... 255 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003....................................................... 255 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003.......................................................... 256 19.7 Total Number of Goats by Category and District on 1st October 2003 .................................................................................... 256 SHEEP PRODUCTION......................................................................................................................................................................... 257 20.1 Total Number of Sheep by Breed Type on 1st October 2003 ................................................................................................... 258 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 ............................................................. 258 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003..................................................................................... 258 20.4 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Tanga Region. ............................................. 258 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003...................................................................... 259 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003............................................................. 259 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ............................................................. 259 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003................................................................................ 259 PIG PRODUTION .......................................................................................................................................................................... 261 21.1 Number of Households and Pigs by Herd Size on 1st October 2003........................................................................................ 262 21.2 Number of Households and Pigs by District on 1st October 2003............................................................................................ 262 21.3 Number of Pigs by Type of Pig and District on 1st October 2003............................................................................................ 262 LIVESTOCK PESTS AND PARASITE CONTROL.......................................................................................................................... 263 22.1 Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year .............. 264 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year ...................................................................................................................................................................... 264 APPENDIX II 126 22.3 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year............................................................................................ 264 22.4 Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. .......................................................................................................................................................................... 264 OTHER LIVESTOCK .......................................................................................................................................................................... 265 23a Total Number of Other Livestock by Type as of 1st October 2003 .......................................................................................... 266 23b Number of Chicken by Category of chicken and District as of 1st October 2003..................................................................... 266 23c Head Number of Other Livestock by Type of Livestock and District ...................................................................................... 266 23d Total Number of households and chickens raised by flock size as of 1st October 2005........................................................... 266 23e Livestock / Poultry Population Trend ....................................................................................................................................... 266 FISH FARMING .......................................................................................................................................................................... 267 28.1a Number of Agriculture Households by Fish Farming and District during the 2002/03 Agriculture Year................................. 268 28.2a Number of Agriculture Households by System of Fish Farming and District during the 2002/03 Agriculture Year................ 268 28.2b Number of Agriculture Households by Source of Fingerling and District during the 2002/03 Agriculture Year ..................... 268 28.2c Number of Agriculture Households by Location of Selling Fish and District during the 2002/03 Agriculture Year................ 268 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year ................................................................. 268 LIVESTOCK EXTENSION .................................................................................................................................................................. 269 29.1a Number of households receiving extension advice by District during the 2002/03 agriculture year ....................................... 270 29.1b Livestock Extension Service Providers: Number of Households by Source of Extension and District during the 2002/03 Agriculture year .......... ............................................................................................................................................................. 270 29.1c Number of Households Receiving Advice on Proper Milking by Source and Region.............................................................. 271 29.1d Number of Households Receiving Advice on Milk Hygiene by Source and District................................................................ 271 29.1e Number of Households Receiving Advice on Disease Control by Source and District ............................................................ 272 29.1f Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District........................................ 273 29.1g Number of Households Receiving Advice on Pasture Establishment by Source and District................................................... 273 29.1h Number of Households Receiving Advice on Group Formation and Strengthen by Source and District ................................. 273 29.1i Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District during the 2002/03 Agriculture Year.......... ............................................................................................................................................................. 274 29.1j Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District during the 2002/03 Agriculture Year.......... ............................................................................................................................................................. 274 29.1k Number of Households Receiving Advice on Milk Hygiene by Source and District................................................................ 274 29.1l Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year .................... 274 29.1m Number of Households Receiving Advice on Other Extension Message by Source and District............................................. 274 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES ........................................................................................................ 283 33.01a Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 284 APPENDIX II 127 33.01b Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 285 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 agriculture year......................................... 285 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year ................................................ 285 33.01e: Number of Households by Distance to Hospital by District for 2002/03 agriculture year........................................................ 286 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year............................................... 286 33.01g : Number of Households by distance to Primary School for 2002/03 agriculture year ............................................................. 286 33.01h Number of Households by Distance to Feeder Road by District............................................................................................... 287 33.01i Number of Households by Distance to Regional Capital.......................................................................................................... 287 33.01j Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 288 33.01k Number of Households by Level of Satisfaction Using Infrastructure and Service by Region................................................. 288 33.01l Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year ..................................... 288 33.01m Number of Households by Distance to Primary Market and District for the 2002/03 Agricultural Year.................................. 288 33.01n Number of Households by Distance to Tertiary Market and District for the 2002/03 Agricultural Year.................................. 288 33.01o Number of Households by Distance to Secondary Market and District for the 2002/03 Agricultural Year.............................. 288 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 289 33.19b: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year ................ 289 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 289 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 290 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 290 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year ........ ............................................................................................................................................................. 290 33.19g Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year............ 290 HOUSEHOLD FACILITIES... ............................................................................................................................................................. 291 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year.............................. 292 34.2 Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year ....... ............................................................................................................................................................. 292 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year District......... 292 34.4 Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year ............ ............................................................................................................................................................. 293 34.5 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year..................... 293 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ............................................................................................................................................. 294 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ............................................................................................................................................. 295 APPENDIX II 128 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year.......................................................................................................................... 295 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year........................................................................................................................... 296 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year.......................................................................................................................... 296 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year................................................................................................. 296 34.12 Number of Households by Number of Meals the Household Normally Took per Day by District........................................... 297 34.13 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ............ 297 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District.............. 298 34.15 Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District ........................................................................................................................................................ 298 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year................................. 299 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year........... 300 34.18 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year..................... 300 APPENDIX II 129 APPENDIX II: CROP TABLES Type of Agriculture Household........................................................................................................................................... 131 Number of Agriculture Households ..................................................................................................................................... 134 Livelihood Activities .......................................................................................................................................................... 136 Households Demography..................................................................................................................................................... 140 Land Access/Ownership....................................................................................................................................................... 148 Land Use .......................................................................................................................................................... 150 Total Annual Crop and Vegetable Production – LONG and SHORT Rainy Seasons ......................................................... 154 Annual Crop and Vegetable Production – SHORT Rainy Season....................................................................................... 162 Annual Crop and Vegetable Production – LONG Rainy Season......................................................................................... 166 Permanent Crop Production ................................................................................................................................................. 180 Agro-processing .......................................................................................................................................................... 192 Marketing .......................................................................................................................................................... 196 Irrigation/Erosion Control.................................................................................................................................................... 198 Access to Farm Inputs and Implements ............................................................................................................................... 202 Agriculture Credit .......................................................................................................................................................... 214 Tree Farming and Agro-forestry .......................................................................................................................................... 218 Crop Extension .......................................................................................................................................................... 224 Animal Contribution to Crop Production............................................................................................................................. 248 Cattle Production .......................................................................................................................................................... 250 Goat Production .......................................................................................................................................................... 254 Sheep Production .......................................................................................................................................................... 258 Pig Production .......................................................................................................................................................... 262 Livestock Pests and Parasite Control ................................................................................................................................... 264 Other Livestock .......................................................................................................................................................... 266 Fishing Farming .......................................................................................................................................................... 268 Livestock Extension .......................................................................................................................................................... 272 Access to Infrastructure and other services.......................................................................................................................... 284 Household Facilities .......................................................................................................................................................... 292 Appendix II 130 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 131 District Rural households involved in Agriculture % of Total rural house - holds Rural households NOT involved in Agriculture % of Total Rural house - holds Total Rural Household % of Total house - holds Urban Households % of Total house - holds Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Lushoto 86,580 99 1062 1 87,642 97 2,621 3 90,263 Korogwe 45,990 95 2252 5 48,242 82 10,270 18 58,512 Muheza 49,195 89 5929 11 55,124 89 7,059 11 62,183 Tanga 8,914 70 3895 30 12,809 24 40,295 76 53,104 Pangani 7,128 82 1526 18 8,653 77 2,630 23 11,283 Handeni 47,739 98 1074 2 48,813 93 3,427 7 52,240 Kilindi 19,654 99 130 1 19,784 67 9,624 33 29,408 Total 265,198 94 15,869 6 281,067 79 75,926 21 356,993 Number of households % Number of households % Number of household % Number of households % Lushoto 48,594 56 144 0 0 0 37,841 44 86,580 86,435 37,986 Korogwe 31,105 68 290 1 0 0 14,596 32 45,990 45,700 14,885 Muheza 37,830 77 379 1 0 0 10,985 22 49,195 48,815 11,365 Tanga 6,974 78 358 4 0 0 1,581 18 8,914 8,555 1,939 Pangani 6,216 87 51 1 0 0 860 12 7,128 7,076 911 Handeni 32,853 69 108 0 0 0 14,777 31 47,739 47,631 14,886 Kilindi 14,833 75 146 1 194 1 4,481 23 19,654 19,314 4,820 Total 178,406 67 1,477 1 194 0 85,121 32 265,198 263,528 86,792 Livestock Only Pastoralist 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households 2. 2 TYPE OF AGRICULTURE HH: Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year Crops & Livestock Total Number of Agriculture Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock District Crops Only Tanzania Agriculture Sample Census - 2003 Tanga 132 Appendix II 133 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 134 Number % Average Household Size Number % Average Household Size Number % Lushoto 63,785 74 5 22,795 26 4 86,580 100 5 Korogwe 34,421 75 5 11,569 25 4 45,990 100 5 Muheza 36,415 74 5 12,779 26 4 49,195 100 5 Tanga 6,424 72 5 2,490 28 4 8,914 100 5 Pangani 5,402 76 4 1,726 24 4 7,128 100 4 Handeni 37,875 79 6 9,864 21 4 47,739 100 5 Kilindi 16,111 82 6 3,543 18 4 19,654 100 5 Total 200,432 76 5 64,766 24 4 265,198 100 5 3.0: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size District Male Female Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 135 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 136 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 27,825 11,033 3,462 38,782 5,331 292 292 Korogwe 9,061 5,880 4,955 18,040 6,534 365 1,139 Muheza 10,236 16,697 1,419 14,876 3,474 891 659 Tanga 511 2,499 347 4,136 345 948 157 Pangani 911 1,537 66 3,439 231 590 430 Handeni 19,300 3,027 1,920 17,279 2,217 107 2,825 Kilindi 6,819 676 1,461 9,484 825 0 341 Total 74,663 41,349 13,630 106,035 18,958 3,192 5,842 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 50,682 17,863 12,699 4,054 275 3,478 2,898 Korogwe 24,066 5,472 2,865 6,947 2,442 2,265 2,783 Muheza 27,576 10,719 1,923 4,337 1,254 1,239 1,975 Tanga 3,103 2,634 566 1,652 586 112 219 Pangani 3,550 1,435 314 920 180 230 454 Handeni 23,112 2,457 6,333 6,758 1,046 4,489 4,064 Kilindi 8,607 1,849 1,511 3,504 729 2,433 923 Total 140,696 42,430 26,211 28,171 6,513 14,246 13,316 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 5,328 14,399 21,672 4,933 1,600 15,877 15,373 Korogwe 5,680 5,240 5,635 5,254 3,934 10,668 8,155 Muheza 5,843 4,846 5,532 5,887 1,669 8,614 17,231 Tanga 2,361 1,325 779 1,110 1,009 516 1,344 Pangani 1,141 661 533 706 292 1,052 2,686 Handeni 4,050 3,469 6,275 5,139 1,676 18,046 9,075 Kilindi 2,334 1,799 2,193 1,600 1,119 7,062 3,546 Total 26,737 31,739 42,620 24,630 11,300 61,834 57,411 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1 3 6 2 7 4 5 Korogwe 1 5 6 2 7 3 4 Muheza 1 2 6 5 7 4 3 Tanga 3 2 5 1 6 7 4 Pangani 2 5 6 1 7 4 3 Handeni 1 6 5 2 7 3 4 Kilindi 1 6 5 2 7 3 4 Total 1 5 6 2 7 3 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 137 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1,587 7,205 10,952 1,011 3,485 28,555 31,168 Korogwe 1,807 1,927 3,749 3,468 3,047 14,714 14,569 Muheza 1,473 1,759 3,362 3,108 1,154 20,397 16,910 Tanga 1,019 612 1,393 386 645 588 2,813 Pangani 448 365 453 559 351 2,519 2,298 Handeni 644 3,310 4,582 3,517 1,388 14,289 17,344 Kilindi 729 1,851 1,511 879 781 6,229 7,044 Total 7,707 17,029 26,004 12,928 10,851 87,291 92,146 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 433 5,755 11,521 1,565 3,297 24,711 24,521 Korogwe 2,845 2,247 2,105 1,405 3,109 10,986 11,360 Muheza 1,153 3,952 3,504 1,790 590 14,351 8,230 Tanga 269 221 866 205 333 515 2,205 Pangani 280 691 641 371 442 1,739 741 Handeni 432 5,124 4,350 1,912 925 7,230 9,763 Kilindi 534 1,456 2,337 487 824 3,540 4,925 Total 5,946 19,445 25,324 7,736 9,519 63,071 61,745 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 144 6,178 5,630 1,740 1,127 11,203 5,784 Korogwe 1,229 989 1,883 832 411 4,989 3,576 Muheza 479 964 2,490 893 911 2,835 2,395 Tanga 0 55 274 18 223 235 409 Pangani 207 395 225 162 164 472 400 Handeni 93 2,958 2,582 952 1,254 1,374 2,767 Kilindi 340 1,071 1,507 239 292 242 2,534 Total 2,492 12,609 14,591 4,838 4,384 21,351 17,866 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 292 870 289 869 835 862 144 Korogwe 408 0 827 316 0 206 525 Muheza 248 426 639 255 0 260 167 Tanga 0 32 30 29 41 33 0 Pangani 14 35 35 0 155 257 14 Handeni 0 414 489 216 315 108 430 Kilindi 0 243 385 244 195 49 243 Total 963 2,021 2,696 1,928 1,541 1,774 1,524 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Tanga 138 Appendix II 139 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 140 Number % Number % Number % Less than 4 82,018 48 88,990 52 171,007 100 05 - 09 104,818 51 102,672 49 207,490 100 10 - 14 101,601 52 92,510 48 194,111 100 15 - 19 68,064 52 61,926 48 129,989 100 20 - 24 40,272 40 61,291 60 101,563 100 25 - 29 43,942 46 51,603 54 95,544 100 30 - 34 35,049 48 38,261 52 73,310 100 35 - 39 28,872 43 37,812 57 66,684 100 40 - 44 25,932 46 30,220 54 56,152 100 45 - 49 23,468 50 23,258 50 46,726 100 50 - 54 19,919 50 19,937 50 39,856 100 55 - 59 13,381 55 10,934 45 24,315 100 60 - 64 13,033 51 12,749 49 25,782 100 65 - 69 11,024 54 9,540 46 20,565 100 70 - 74 10,535 51 10,146 49 20,681 100 75 - 79 4,869 56 3,763 44 8,632 100 80 - 84 4,058 54 3,400 46 7,458 100 Above 85 3,113 51 3,052 49 6,165 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Less than 4 82,018 13 88,990 13 171,007 13 05 - 09 104,818 17 102,672 16 207,490 16 10 - 14 101,601 16 92,510 14 194,111 15 15 - 19 68,064 11 61,926 9 129,989 10 20 - 24 40,272 6 61,291 9 101,563 8 25 - 29 43,942 7 51,603 8 95,544 7 30 - 34 35,049 6 38,261 6 73,310 6 35 - 39 28,872 5 37,812 6 66,684 5 40 - 44 25,932 4 30,220 5 56,152 4 45 - 49 23,468 4 23,258 4 46,726 4 50 - 54 19,919 3 19,937 3 39,856 3 55 - 59 13,381 2 10,934 2 24,315 2 60 - 64 13,033 2 12,749 2 25,782 2 65 - 69 11,024 2 9,540 1 20,565 2 70 - 74 10,535 2 10,146 2 20,681 2 75 - 79 4,869 1 3,763 1 8,632 1 80 - 84 4,058 1 3,400 1 7,458 1 Above 85 3,113 0 3,052 0 6,165 0 Total 633,967 100 662,064 100 1,296,031 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 141 Number % Number % Number % Lushoto 196,570 48 209,752 52 406,322 100 Korogwe 112,681 49 115,135 51 227,816 100 Muheza 113,667 49 116,950 51 230,617 100 Tanga 19,546 48 21,375 52 40,922 100 Pangani 15,310 52 14,143 48 29,453 100 Handeni 123,622 48 132,669 52 256,291 100 Kilindi 52,570 50 52,040 50 104,610 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Number % % Lushoto 258,554 73.2 7,315 2.1 0 0.0 87,278 24.7 100 Korogwe 140,665 68.9 5,004 2.5 0 0.0 58,514 28.7 100 Muheza 143,330 71.2 4,205 2.1 283 0.1 53,363 26.5 100 Tanga 25,756 69.8 1,922 5.2 131 0.4 9,073 24.6 100 Pangani 19,921 74.4 519 1.9 39 0.1 6,280 23.5 100 Handeni 128,671 59.7 6,330 2.9 750 0.3 79,943 37.1 100 Kilindi 44,615 51.2 668 0.8 243 0.3 41,651 47.8 100 Total 761,512 68 25,964 2 1,446 0.1 336,102 30 100 Number % Number % Number % Number % Lushoto 132,142 37.4 162,461 46.0 58,544 16.6 353,147 100 Korogwe 69,632 34.1 87,548 42.9 47,003 23.0 204,183 100 Muheza 65,362 32.5 90,049 44.8 45,771 22.8 201,182 100 Tanga 11,636 31.5 17,439 47.3 7,807 21.2 36,882 100 Pangani 9,276 34.7 13,161 49.2 4,322 16.2 26,758 100 Handeni 63,567 29.5 83,470 38.7 68,656 31.8 215,693 100 Kilindi 25,390 29.1 27,199 31.2 34,588 39.7 87,178 100 Total 377,006 33.5 481,327 42.8 266,691 23.7 1,125,024 100 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % % % Lushoto 152,752 43 1,866 1 144 0 143 0 1 8 Korogwe 76,219 37 3,934 2 103 0 107 0 2 8 Muheza 77,409 38 1,565 1 1,299 1 1,529 1 1 5 Tanga 9,867 27 898 2 23 0 987 3 2 4 Pangani 8,770 33 45 0 0 0 942 4 1 5 Handeni 92,233 43 2,552 1 107 0 630 0 1 5 Kilindi 33,682 39 2,921 3 1,164 1 48 0 0 2 Total 450,932 40 13,782 1 2,839 0 4,387 0 1 6 Main Activity 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total Fishing District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 142 cont… HOUSEHOLD DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Number % Lushoto 16,606 5 1,439 0 576 0 0 0 570 0 Korogwe 7,418 4 919 0 200 0 103 0 1,556 1 Muheza 18,315 9 1,566 1 708 0 736 0 2,515 1 Tanga 5,170 14 504 1 985 3 103 0 1,250 3 Pangani 3,665 14 247 1 148 1 41 0 638 2 Handeni 17,355 8 2,481 1 615 0 216 0 837 0 Kilindi 14,306 16 98 0 0 0 192 0 582 1 Total 82,834 7 7,254 1 3,231 0 1,391 0 7,948 1 cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Lushoto 116,122 33 29,186 8 280 0 353,147 100 Korogwe 63,908 31 23,480 11 809 0 204,183 100 Muheza 63,082 31 16,832 8 1,957 1 201,182 100 Tanga 11,348 31 2,635 7 485 1 36,882 100 Pangani 8,838 33 1,269 5 261 1 26,758 100 Handeni 55,470 26 21,768 10 7,226 3 215,693 100 Kilindi 24,417 28 7,202 8 716 1 87,178 100 Total 343,184 31 102,373 9 11,735 1 1,125,024 100 Number % Number % Number % Number % % Lushoto 153,483 43 11,754 3 143,275 41 44,635 13 100 Korogwe 66,982 33 26,928 13 68,254 33 42,019 21 100 Muheza 74,537 37 30,593 15 63,190 31 32,863 16 100 Tanga 8,995 24 5,515 15 9,496 26 12,877 35 100 Pangani 8,093 30 1,458 5 12,725 48 4,483 17 100 Handeni 85,034 39 24,270 11 67,099 31 39,290 18 100 Kilindi 36,026 41 12,288 14 24,623 28 14,240 16 100 Total 433,150 39 112,805 10 388,661 35 190,408 17 100 District District Too Old / Retired / Sick / Disabled Not Working & Unavailable Student 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Housemaker / Housewife Other Total Not Working & Available District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 143 Number % Number % Number % Number % % % Lushoto 146 0 288 0 2,314 1 2,450 2 10 2 Korogwe - - 1,137 1 2,417 3 3,800 4 14 4 Muheza - - 492 1 1,904 2 3,308 4 16 5 Tanga 111 1 167 1 448 3 681 4 12 3 Pangani - - 23 0 301 2 518 4 14 4 Handeni 540 1 108 0 2,558 3 5,094 6 13 4 Kilindi 97 0 - - 731 3 925 3 13 1 Total 893 0 2,215 0 10,672 2 16,776 3 13 3 Number % Number % Number % Number % Number % Lushoto 128,131 79 1,166 1 145 0 - - 146 0 Korogwe 55,775 64 1,731 2 376 0 300 0 - - Muheza 55,523 62 1,874 2 338 0 55 0 167 0 Tanga 10,589 61 360 2 30 0 23 0 91 1 Pangani 8,465 64 250 2 35 0 19 0 67 1 Handeni 53,352 64 1,247 1 - - - - 217 0 Kilindi 20,391 75 98 0 - - - - - - Total 332,227 69 6,726 1 925 0 397 0 688 0 Number % Number % Number % Number % Number % Lushoto 582 0 144 0 2,588 2 - - 708 0 Korogwe 596 1 191 0 2,305 3 - - 107 0 Muheza 1,048 1 124 0 1,379 2 - - 84 0 Tanga 73 0 81 0 775 4 10 0 212 1 Pangani 76 1 22 0 230 2 24 0 22 0 Handeni 520 1 217 0 944 1 - - 212 0 Kilindi 47 0 - - 433 2 - - 49 0 Total 2,942 1 779 0 8,654 2 34 0 1,393 0 Number % Number % Number % Lushoto - - 1,010 1 162,461 100 Korogwe - - 725 1 87,548 100 Muheza - - 1,532 2 90,049 100 Tanga 45 0 579 3 17,439 100 Pangani - - 379 3 13,161 100 Handeni - - 1,253 2 83,470 100 Kilindi 47 0 386 1 27,199 100 Total 92 0 5,865 1 481,327 100 District District District g Secondary Form Six Under Standard One Standard One Standard Two Standard Three y Tertiary Education Adult Education Total Form Two Form Three Form Four cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Standard Seven Standard Eight Training After Primary Education Pre Form One Form One 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 144 Number % Average Household Size Number % Average Household Size Number % Lushoto 63,785 74 5 22,795 26 4 86,580 100 5 Korogwe 34,421 75 5 11,569 25 4 45,990 100 5 Muheza 36,415 74 5 12,779 26 4 49,195 100 5 Tanga 6,424 72 5 2,490 28 4 8,914 100 5 Pangani 5,402 76 4 1,726 24 4 7,128 100 4 Handeni 37,875 79 6 9,864 21 4 47,739 100 5 Kilindi 16,111 82 6 3,543 18 4 19,654 100 5 Total 200,432 76 5 64,766 24 4 265,198 100 5 Number % Number % Number % Number % Tanga 3,664 45 3,047 37 1,521 18 8,232 100 Handeni 27,704 73 6,445 17 3,604 10 37,753 100 Pangani 3,999 67 1,475 25 539 9 6,013 100 Korogwe 27,323 70 9,037 23 2,926 7 39,286 100 Kilindi 12,256 76 2,872 18 1,019 6 16,147 100 Muheza 25,227 78 5,388 17 1,552 5 32,168 100 Lushoto 46,179 87 5,904 11 862 2 52,945 100 Total 146,351 76 34,169 18 12,023 6 192,543 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Lushoto 20,754 62,658 145 1,734 427 144 718 86,580 Korogwe 11,060 32,741 209 1,681 - - 299 45,990 Muheza 12,223 34,685 164 1,318 84 - 720 49,195 Tanga 2,448 5,410 10 605 77 45 319 8,914 Pangani 1,450 5,183 11 201 - - 282 7,128 Handeni 14,564 31,725 - 721 106 - 623 47,739 Kilindi 8,319 10,614 - 287 49 47 338 19,654 Total 70,819 183,016 539 6,548 742 236 3,298 265,198 Mean Median Mode Mean Median Mode Mean Median Mode Lushoto 42 40 30 49 48 40 44 41 40 Korogwe 47 44 35 50 47 65 47 45 35 Muheza 46 45 30 50 48 60 47 45 60 Tanga 49 48 45 55 55 70 51 50 70 Pangani 46 44 25 49 46 70 47 45 65 Handeni 43 40 30 47 45 30 44 40 30 Kilindi 42 40 30 45 42 50 42 40 30 Total 44 42 30 49 47 40 45 43 30 District Male Female Total 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year District Off farm income Total One Two More than Two Average Household Size 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 145 3.14 Time Series of Male and Female Headed Households Male Female Total Male Female Total Male Female Total Lushoto 55,415 10,703 66,117 8,370 12,092 20,462 63,785 22,795 86,580 Korogwe 28,146 6,252 34,399 6,274 5,317 11,591 34,421 11,569 45,990 Muheza 30,491 6,580 37,071 5,924 6,200 12,124 36,415 12,779 49,195 Tanga 5,430 1,123 6,554 994 1,367 2,360 6,424 2,490 8,914 Pangani 4,598 1,058 5,656 803 668 1,472 5,402 1,726 7,128 Handeni 29,694 4,337 34,031 8,181 5,527 13,708 37,875 9,864 47,739 Kilindi 10,220 1,261 11,481 5,891 2,282 8,172 16,111 3,543 19,654 Total 163,994 31,314 195,308 36,438 33,452 69,890 200,432 64,766 265,198 3.15 Literacy Rate of Heads of Households by Sex and District District Literacy Know Don;t know Total Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed ( Number in Thousands) 175 179 192 204 205 200 Female Headed ( Number in Thousands) 38 51 63 64 56 64 Total 213 230 255 268 261 264 Male Headed (Percentage) 82 78 75 76 78 76 Female Headed (Percentage) 18 22 25 24 22 24 Total 100 100 100 100 100 100 Tanzania Agriculture Sample Census - 2003 Tanga 146 Appendix II 147 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 148 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 2,451 3 81,583 94 14,865 17 2,127 2 3,002 3 863 1 1,304 2 86,435 Korogwe 7,554 17 28,457 62 12,194 27 7,104 16 6,613 14 1,326 3 1,999 4 45,700 Muheza 9,683 20 26,895 55 12,370 25 1,838 4 10,581 22 697 1 2,860 6 48,815 Tanga 3,652 43 2,266 26 1,639 19 384 4 1,740 20 131 2 347 4 8,555 Pangani 272 4 5,228 74 1,423 20 41 1 1,100 16 72 1 359 5 7,076 Handeni 17,106 36 24,959 52 7,298 15 428 1 3,813 8 1,662 3 1,936 4 47,631 Kilindi 1,824 9 14,670 76 1,307 7 438 2 873 5 49 0 2,827 15 19,314 Total 42,541 16 184,058 70 51,095 19 12,361 5 27,721 11 4,800 2 11,632 4 263,528 District Total Number of Households Land Access 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Area Leased/ Certificate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Lushoto 2,370 82,638 9,649 734 1,321 264 566 97,543 Korogwe 10,034 37,725 18,227 6,229 4,395 1,343 3,159 81,111 Muheza 15,746 46,914 24,133 1,238 9,938 272 3,666 101,907 Tanga 7,653 3,743 3,283 525 1,711 156 600 17,671 Pangani 517 10,141 2,556 17 931 80 560 14,803 Handeni 52,143 63,069 20,618 581 4,236 4,605 5,494 150,746 Kilindi 5,471 41,526 3,238 463 973 79 8,865 60,614 Total 93,934 285,756 81,704 9,786 23,506 6,800 22,910 524,396 % 18 54 16 2 4 1 4 100 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 149 LAND USE Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 150 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Lushoto 27,522 41,392 21,570 4,613 33,010 421 7,063 289 9,902 581 730 1,167 86,580 Korogwe 34,049 13,313 7,128 8,922 8,549 423 6,000 0 2,097 2,089 914 8,675 45,990 Muheza 27,406 13,807 15,007 15,586 15,868 988 6,832 400 4,382 566 1,589 8,090 49,195 Tanga 3,286 1,481 2,036 2,952 3,337 191 158 0 0 95 529 2,943 8,914 Pangani 5,032 1,401 2,365 1,953 1,454 125 470 18 121 90 277 1,418 7,128 Handeni 41,619 8,302 6,447 6,219 9,544 216 12,319 641 210 1,160 2,309 13,687 47,739 Kilindi 11,205 6,617 2,870 1,996 4,514 146 2,916 194 243 146 1,552 5,931 19,654 Total 150,120 86,312 57,423 42,241 76,275 2,509 35,758 1,542 16,954 4,726 7,899 41,911 265,198 Districts Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Lushoto 15,136 31,558 7,664 2,611 33,082 71 4,729 117 1,621 186 296 473 97,543 Korogwe 35,542 11,038 3,122 6,396 7,707 162 4,857 0 654 2,200 562 8,871 81,111 Muheza 21,727 11,289 12,593 17,539 16,691 663 6,620 893 1,362 430 1,619 10,481 101,907 Tanga 1,799 1,085 1,343 4,038 3,884 429 91 0 0 138 727 4,137 17,671 Pangani 4,350 1,316 2,480 2,685 1,599 84 478 20 19 51 254 1,522 14,859 Handeni 68,474 9,664 4,486 5,385 11,126 304 22,534 1,565 222 1,093 3,628 22,267 150,746 Kilindi 20,547 12,408 1,419 1,427 7,848 138 4,616 176 83 138 2,511 9,303 60,614 Total 167,575 78,356 33,108 40,080 81,938 1,852 43,926 2,771 3,959 4,236 9,597 57,053 524,451 % 32 15 6 8 16 0 8 1 1 1 2 11 100 Land use area Type of Land Use 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 151 Number % Number % Number % Number % Lushoto 75,031 87 11,404 13 86,435 Lushoto 35,993 42 50,442 58 86,435 Korogwe 29,280 64 16,420 36 45,700 Korogwe 26,375 58 19,325 42 45,700 Muheza 32,598 67 16,218 33 48,815 Muheza 28,327 58 20,488 42 48,815 Tanga 3,596 42 4,960 58 8,555 Tanga 5,945 69 2,611 31 8,555 Pangani 4,147 59 2,930 41 7,076 Pangani 4,694 66 2,382 34 7,076 Handeni 20,561 43 27,070 57 47,631 Handeni 31,637 66 15,994 34 47,631 Kilindi 10,561 55 8,753 45 19,314 Kilindi 13,381 69 5,933 31 19,314 Total 175,773 67 87,754 33 263,528 Total 146,353 56 117,175 44 263,528 Number % Number % Lushoto 12,284 14 74,151 86 86,435 Korogwe 11,206 25 34,494 75 45,700 Muheza 14,802 30 34,013 70 48,815 Tanga 3,459 40 5,097 60 8,555 Pangani 1,739 25 5,337 75 7,076 Handeni 16,758 35 30,873 65 47,631 Kilindi 2,326 12 16,988 88 19,314 Total 62,574 24 200,954 76 263,528 No Total Table 5.5: LAND SUFFICIENCY Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year District Do any Female Members of the Household own or have customary right to Land Yes No Total Table 5.3 : LAND SUFFICIENCY Number of Households by type of household and District during 2002/03 Agricultural Year Table 5.4: LAND SUFFICIENCYNumber of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year District Was all Land Available to the Hh Used during 2002/03? District Do you Consider that you have sufficient land for the Hh? Yes No Total Yes Tanzania Agriculture Sample Census - 2003 Tanga 152 Appendix II 153 TOTAL ANNUAL CROP & VEGETABLE PRODUCTION – LONG & SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 154 Number of Household Planted Area (hectare) Number of Household Planted Area (hectare) Lushoto 78,808 69,194 72,230 50,351 119,544 57.88 Pangani 4,631 3,902 5,730 5,260 9,162 42.59 Tanga 4,586 2,335 5,675 3,173 5,508 42.39 Muheza 36,437 24,062 43,558 33,883 57,945 41.53 Handeni 36,056 34,643 46,671 74,099 108,742 31.86 Korogwe 26,637 16,755 41,687 40,899 57,655 29.06 Kilindi 9,345 9,928 18,050 31,825 41,754 23.78 Total 196,502 160,820 233,601 239,490 400,310 40.17 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Lushoto 78,808 7,771 72,230 14,349 86,435 Korogwe 26,637 19,353 41,687 4,303 45,700 Muheza 36,437 12,757 43,558 5,637 48,815 Tanga 4,586 4,328 5,675 3,239 8,555 Pangani 4,631 2,496 5,730 1,397 7,076 Handeni 36,056 11,682 46,671 1,068 47,631 Kilindi 9,345 10,309 18,050 1,604 19,314 Total 196,502 68,697 233,601 31,597 263,528 7.1 & 7.2b TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of crop growing Households Planting Crops by Season and Region District Short Rainy Season Long Rainy Season Total Number of Crop Growing households % Area planted in short rainy season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District District Total area planted (hectare) Short Rainy Season Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 155 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) CEREALS 111,875 65,736 183,654 115,251 295,529 180,987 Maize 110,043 61,910 563 177,433 111,692 629 287,476 173,602 604 Paddy 1,735 3,488 2,010 5,930 3,472 585 7,665 6,960 908 Sorghum 97 338 3,485 19 7 357 116 345 2969 Finger Millet 0 0 0 66 23 346 66 23 346 Wheat 0 0 0 205 57 280 205 57 280 ROOTS & TUBERS 10,759 15,214 36,856 52,752 47,614 67,966 Cassava 1,725 2,131 1,235 29,007 43,368 2,358 30,732 45,499 2358 Sweet Potatoes 480 537 1,119 593 465 784 1,073 1,002 934 Irish Potatoes 8,314 11,973 1,440 7,089 8,763 1,236 15,402 20,736 1346 Yams 51 0 0 80 55 684 132 55 417 Cocoyam 188 574 3,045 86 101 1,169 275 675 2455 PULSES 34,624 11,221 42,393 16,160 77,017 27,381 Mung Beans 0 0 0 64 88 1,385 64 88 1385 Beans 24,185 8,699 360 38,843 15,325 395 63,028 24,023 381 Cowpeas 9,276 2,125 229 2,731 499 183 12,007 2,624 219 Green Gram 1,108 288 260 755 248 329 1,863 536 288 Chich Peas 2 0 198 0 0 0 2 0 198 Bambaranuts 2 1 296 0 0 0 2 1 296 Field Peas 50 109 2,159 0 0 0 50 109 2159 OIL SEEDS & OIL N 725 248 1,839 1,268 2,564 1,516 Sunflower 0 0 0 78 35 451 78 35 451 Simsim 92 26 281 729 271 372 822 297 362 Groundnuts 613 212 346 1,032 961 932 1,645 1,174 714 Castor Seed 20 10 494 0 0 0 20 10 494 FRUIT & VEGETAB 2,821 10,723 2,525 8,827 5,346 19,550 Okra 9 13 1,422 26 17 629 35 29 831 Radish 4 2 529 0 0 0 4 2 529 Bitter Aubergine 18 216 11,856 176 296 1,685 194 512 2641 Onions 18 85 4,681 100 279 2,782 119 364 3072 Ginger 88 66 746 0 0 0 88 66 746 Cabbage 344 1,410 4,099 502 2,062 4,109 846 3,472 4105 Tomatoes 1,621 7,220 4,455 948 3,632 3,832 2,569 10,852 4225 Spinnach 30 8 251 0 0 0 30 8 251 Carrot 51 182 3,584 143 145 1,017 194 328 1691 Chillies 414 1,054 2,549 307 919 2,990 721 1,973 2737 Amaranths 65 140 2,153 66 59 886 131 199 1515 Pumpkins 13 234 17,324 65 31 475 78 265 3384 Cucumber 0 0 0 90 668 7,390 90 668 7390 Egg Plant 9 11 1,227 23 20 856 32 31 960 Water Mellon 137 82 599 78 699 8,936 215 781 3634 CASH CROPS 17 10 448 247 465 256 Seaweed 2 7 2,964 0 0 0 2 7 2964 Cotton 0 0 0 264 165 625 264 165 625 Tobacco 15 3 198 166 70 422 180 73 404 Jute 0 0 0 18 12 642 18 12 642 Total 160,820 91,930 267,714 178,344 428,534 270,274 * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual ar bein produced on the same land during the 2 seasons. Previous surveys have used the Long season to estimate physical land area u production to different crops 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Tanga Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 156 Number of Households Planted Area (Ha) Number of Households Planted Area (Ha) CEREALS 190,720 111,875 205,932 183,654 295,529 37.9 Maize 186,153 110,043 189,772 177,433 287,476 38.3 Paddy 4,247 1,735 15,443 5,930 7,665 22.6 Sorghum 320 97 66 19 116 83.5 Finger Millet 0 0 217 66 66 0.0 Wheat 0 0 433 205 205 0.0 ROOTS & TUBERS 38,281 10,759 27,925 36,856 47,614 22.6 Cassava 5,155 1,725 2,315 29,007 30,732 5.6 Sweet Potatoes 2,041 480 2,468 593 1,073 44.7 Irish Potatoes 29,786 8,314 22,414 7,089 15,402 54.0 Yams 213 51 213 80 132 39.0 Cocoyam 1,085 188 515 86 275 68.6 PULSES 106,989 34,624 100,762 42,393 77,017 45.0 Mung Beans 0 0 133 64 64 0.0 Beans 77,157 24,185 89,035 38,843 63,028 38.4 Cowpeas 25,741 9,276 8,833 2,731 12,007 77.3 Green Gram 3,798 1,108 2,760 755 1,863 59.5 Chich Peas 22 2 0 0 2 100.0 Bambaranuts 23 2 0 0 2 100.0 Field Peas 248 50 0 0 50 100.0 OIL SEEDS & OIL N 2,546 725 4,608 2,871 3,596 20.2 Sunflower 0 0 96 78 78 0.0 Simsim 202 92 1,163 729 822 11.2 Groundnuts 2,296 613 3,350 1,032 1,645 37.3 Castor Seed 48 20 0 1,032 1,051 1.9 FRUITS & VEGETA 13,080 2,821 11,089 2,525 5,346 52.8 Okra 56 9 220 26 35 25.5 Radish 14 4 0 0 4 100.0 Bitter Aubergine 90 18 541 176 194 9.4 Onions 203 18 399 100 119 15.3 Ginger 291 88 0 0 88 100.0 Cabbage 1,582 344 2,277 502 846 40.7 Tomatoes 7,462 1,621 4,100 948 2,569 63.1 Spinnach 107 30 0 0 30 100.0 Carrot 286 51 286 143 194 26.3 Chillies 1,691 414 1,367 307 721 57.4 Amaranths 890 65 628 66 131 49.6 Pumpkins 92 13 579 65 78 17.3 Cucumber 0 0 273 90 90 0.0 Egg Plant 88 9 204 23 32 28.1 Water Mellon 227 137 214 78 215 63.6 CASH CROPS 166 17 1,075 448 465 3.6 Seaweed 23 2 0 0 2 100.0 Cotton 0 0 419 264 264 0.0 Tobacco 143 15 565 166 180 8.1 Jute 0 0 91 18 18 0.0 Total 351,782 351,391 268,745 429,566 0.0 % Area Planted in Short Rainy Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the agriculture year 2002/03- Short and Long Season, Tanga Region Crop Short Rainy Season Long Rainy Season Total Area Planted Short & Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 157 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,011 847 3,448 2,919 146,579 115,779 151,039 119,544 Korogwe 591 1,063 912 1,386 66,821 55,206 68,324 57,655 Muheza 320 273 2,675 1,830 77,000 55,842 79,995 57,945 Tanga 43 83 168 55 10,051 5,370 10,261 5,508 Pangani 424 510 287 244 9,651 8,409 10,361 9,162 Handeni 210 428 5,541 9,515 76,976 98,798 82,728 108,742 Kilindi 243 305 1,069 1,570 26,082 39,879 27,395 41,754 Total 2,843 3509.1 14,101 17,519 413,159 379,283 430,102 400,310 % 0.7 0.9 3.5 4.4 103.2 94.7 107.4 100.0 Total Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Planted Area Lushoto 28,758 25,274 5,361 3,389 4,607 2,649 112,313 88,233 119,544 Korogwe 9,005 7,108 4,652 3,922 1,199 793 53,467 45,831 57,655 Muheza 5,714 4,410 580 307 340 226 73,362 53,001 57,945 Tanga 1,504 747 364 184 104 29 8,289 4,548 5,508 Pangani 316 259 107 64 0 . 9,938 8,839 9,162 Handeni 3,199 6,104 1,035 2,090 192 350 78,301 100,197 108,742 Kilindi 488 951 1,405 2,231 49 20 25,453 38,552 41,754 Total 48,984 44,853 13,504 12,187 6,491 4,068 361,124 339,202 400,310 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 8,304 8,065 142,734 111,480 151,039 119,544 6.7 Korogwe 3,414 3,177 64,910 54,478 68,324 57,655 5.5 Muheza 493 480 79,502 57,465 79,995 57,945 0.8 Tanga 217 120 10,044 5,388 10,261 5,508 2.2 Pangani 253 276 10,109 8,886 10,361 9,162 3.0 Handeni 1,076 1,447 81,652 107,295 82,728 108,742 1.3 Kilindi 389 383 27,006 41,371 27,395 41,754 0.9 Total 14,145 13,947 415,958 386,363 430,102 400,310 3.5 % 3.3 3.5 96.7 96.5 100.0 100.0 3.5 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Tanga District Soil Preparation y Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Tanga District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 158 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 7,050 6,054 146,543 118,966 153,593 125,020 4.84 Korogwe 2,380 2,918 67,093 58,160 69,472 61,078 4.78 Muheza 413 259 81,395 69,210 81,808 69,468 0.37 Tanga 327 246 11,967 7,952 12,294 8,198 3.00 Pangani 380 581 10,173 9,678 10,554 10,260 5.66 Handeni 2,293 6,490 80,543 104,759 82,836 111,249 5.83 Kilindi 919 1,309 26,719 41,844 27,639 43,153 3.03 Total 13,762 17,857 424,433 410,568 438,195 428,425 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. % of Planted area using Herbicide Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,143 1,094 149,895 118,450 151,039 119,544 0.92 Korogwe 497 336 67,827 57,319 68,324 57,655 0.58 Muheza 226 345 79,769 57,599 79,995 57,945 0.60 Tanga 264 183 9,997 5,325 10,261 5,508 3.32 Pangani 11 21 10,350 9,141 10,361 9,162 0.23 Handeni 703 578 82,024 108,164 82,728 108,742 0.53 Kilindi 390 650 27,005 41,104 27,395 41,754 1.56 Total 3,235 3,207 426,867 397,103 430,102 400,310 0.80 % 1 1 99 99 100 100 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Tanga. Total % of Planted area using Insecticide District Insecticide Use g Insecticide g Insecticide Total 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. District Herbicide Use Households Using Herbicide Households Not Using Herbicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 159 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 3,035 3,609 148,003 115,936 151,039 119,544 3.0 Korogwe 1,297 1,069 67,027 56,586 68,324 57,655 1.9 Muheza 349 202 79,646 57,743 79,995 57,945 0.3 Tanga 347 185 9,914 5,323 10,261 5,508 3.4 Pangani 156 338 10,206 8,824 10,361 9,162 3.7 Handeni 1,140 1,348 81,588 107,394 82,728 108,742 1.2 Kilindi 388 469 27,006 41,285 27,395 41,754 1.1 Total 6,713 7,220 423,390 393,090 430,102 400,310 1.8 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 21,528 19,826 129,510 99,718 151,039 119,544 16.58 Korogwe 13,961 15,465 54,362 42,190 68,324 57,655 26.82 Muheza 2,883 2,145 77,112 55,799 79,995 57,945 3.70 Tanga 1,554 1,048 8,706 4,461 10,261 5,508 19.02 Pangani 2,026 2,150 8,335 7,013 10,361 9,162 23.46 Handeni 6,421 9,090 76,307 99,652 82,728 108,742 8.36 Kilindi 1,108 2,365 26,287 39,388 27,395 41,754 5.66 Total 49,482 52,089 380,620 348,221 430,102 400,310 13.01 % 12 13 88 87 100 100 % of Planted area using Improved Seeds % of Planted area using Fungicide 7.1 & 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Tanga Region 7.1 &7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Tanga Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Tanga 160 Appendix II 161 ANNUAL CROP & VEGETABLE PRODUCTION – SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 866 614 1,868 1,800 76,074 66,779 78,808 69,194 Korogwe 301 415 103 161 26,233 16,179 26,637 16,755 Muheza 236 162 1,194 716 35,007 23,185 36,437 24,062 Tanga 8 24 61 26 4,516 2,286 4,586 2,335 Pangani 132 140 176 137 4,323 3,625 4,631 3,902 Handeni 0 . 2,461 1,846 33,595 32,798 36,056 34,643 Kilindi 0 . 244 292 9,101 9,636 9,345 9,928 Total 1,544 1,355 6,107 4,978 188,850 154,487 196,502 160,820 % 1 1 3 3 96 96 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 15,223 15,178 3,327 2,118 3,031 1,684 57,227 50,214 78,808 69,194 Korogwe 2,789 1,508 2,302 1,642 709 482 20,837 13,124 26,637 16,755 Muheza 2,482 1,588 331 189 79 80 33,546 22,206 36,437 24,062 Tanga 701 366 73 21 42 12 3,770 1,936 4,586 2,335 Pangani 172 91 63 51 0 . 4,397 3,760 4,631 3,902 Handeni 1,493 1,290 203 261 96 116 34,264 32,975 36,056 34,643 Kilindi 98 69 387 254 49 10 8,811 9,595 9,345 9,928 Total 22,959 20,089 6,686 4,537 4,005 2,383 162,852 133,811 196,502 160,820 % 12 12 3 3 2 1 83 83 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 4,267 4,735 74,541 64,459 78,808 69,194 7 Korogwe 2,409 1,767 24,228 14,988 26,637 16,755 11 Muheza 336 296 36,101 23,767 36,437 24,062 1 Tanga 101 87 4,485 2,248 4,586 2,335 4 Pangani 135 88 4,496 3,814 4,631 3,902 2 Handeni 864 1,028 35,193 33,615 36,056 34,643 3 Kilindi 193 87 9,152 9,841 9,345 9,928 1 Total 8,306 8,088 188,196 152,732 196,502 160,820 5 % 4 5 96 95 100 100 Total hh figures are indicative as a household may use more than one type of Land preparation method for different crops District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation in short rainy season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON, Tanga Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Tanga Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 163 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 2,437 1,675 76,371 67,518 78,808 69,194 Korogwe 794 739 25,844 16,016 26,637 16,755 Muheza 172 86 36,266 23,976 36,437 24,062 Tanga 261 179 4,324 2,156 4,586 2,335 Pangani 143 162 4,488 3,740 4,631 3,902 Handeni 1,057 1,944 34,999 32,699 36,056 34,643 Kilindi 242 191 9,103 9,737 9,345 9,928 Total 5,106 4,977 191,395 155,843 196,502 160,820 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 716 617 78,092 68,576 78,808 69,194 0.9 Korogwe 291 243 26,346 16,513 26,637 16,755 1.4 Muheza 167 155 36,270 23,908 36,437 24,062 0.6 Tanga 166 127 4,419 2,209 4,586 2,335 5.4 Pangani 0 . 4,631 3,902 4,631 3,902 - Handeni 324 196 35,733 34,447 36,056 34,643 0.6 Kilindi 147 89 9,198 9,839 9,345 9,928 0.9 Total 1,811 1,427 194,690 159,394 196,502 160,820 0.9 % 1 1 99 99 100 100 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON. District Herbicide Use % of Planted area using Herbicide Households Using Herbicide Households Not Using Herbicide Total 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON. District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 164 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,878 2,327 76,930 66,867 78,808 69,194 3.4 Korogwe 497 486 26,140 16,270 26,637 16,755 2.9 Muheza 167 109 36,270 23,954 36,437 24,062 0.5 Tanga 228 129 4,358 2,206 4,586 2,335 5.5 Pangani 87 144 4,544 3,758 4,631 3,902 3.7 Handeni 745 693 35,312 33,950 36,056 34,643 2.0 Kilindi 193 125 9,152 9,803 9,345 9,928 1.3 Total 3,796 4,012 192,706 156,808 196,502 160,820 2.5 % 1.9 2.5 98.1 97.5 100.0 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 10,823 11,394 67,986 57,800 78,808 69,194 16 Korogwe 6,606 4,918 20,031 11,838 26,637 16,755 29 Muheza 1,758 1,106 34,679 22,956 36,437 24,062 5 Tanga 774 512 3,812 1,823 4,586 2,335 22 Pangani 1,063 983 3,569 2,919 4,631 3,902 25 Handeni 2,438 1,957 33,618 32,686 36,056 34,643 6 Kilindi 484 729 8,861 9,200 9,345 9,928 7 Total 23,945 21,599 172,556 139,221 196,502 160,820 13 % 12 13 88 87 100 100 District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region District Fungicide Use % of Planted area using Fungicide Households Using Fungicide Households Not Using Fungicide Total 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON. Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 165 ANNUAL CROP & VEGETABLE PRODUCTION – LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 166 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Lushoto 146 233 1,580 1,118 70,504 49,000 72,230 50,351 Korogwe 290 648 809 1,225 40,588 39,027 41,687 40,899 Muheza 84 112 1,481 1,114 41,993 32,657 43,558 33,883 Tanga 35 59 106 30 5,535 3,084 5,675 3,173 Pangani 291 369 111 106 5,328 4,785 5,730 5,260 Handeni 210 428 3,080 7,670 43,381 66,001 46,671 74,099 Kilindi 243 305 825 1,278 16,981 30,242 18,050 31,825 Total 1,299 2,154 7,993 12,541 224,309 224,795 233,601 239,490 % 1 1 3 5 96 94 100 100 No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area Lushoto 13,534 10,096 2,033 1,270 1,576 965 55,086 38,019 72,230 50,351 Korogwe 6,216 5,601 2,351 2,280 490 311 32,630 32,708 41,687 40,899 Muheza 3,232 2,822 249 119 261 147 39,816 30,795 43,558 33,883 Tanga 803 381 291 163 62 17 4,520 2,612 5,675 3,173 Pangani 144 168 44 13 0 . 5,542 5,079 5,730 5,260 Handeni 1,706 4,814 832 1,829 96 234 44,037 67,221 46,671 74,099 Kilindi 390 882 1,018 1,976 0 10 16,642 28,957 18,050 31,825 Total 26,025 24,764 6,818 7,650 2,485 1,684 198,272 205,392 233,601 239,490 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Lushoto 4,037 3,330 68,193 47,021 72,230 50,351 6.6 Korogwe 1,004 1,410 40,682 39,489 41,687 40,899 3.4 Muheza 157 184 43,401 33,698 43,558 33,883 0.5 Tanga 116 33 5,559 3,141 5,675 3,173 1.0 Pangani 117 188 5,613 5,073 5,730 5,260 3.6 Handeni 212 418 46,459 73,680 46,671 74,099 0.6 Kilindi 195 296 17,854 31,530 18,050 31,825 0.9 Total 5,839 5,859 227,762 233,631 233,601 239,490 2.4 % 2 2 98 98 100 100 District Irrigation Use % of area planted under irrigation in long rainy season Households Using Irrigation Households Not Using Irrigation Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Tanga Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 167 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 4,613 4,378 70,172 51,448 74,784 55,826 Korogwe 1,586 2,179 41,249 42,143 42,835 44,323 Muheza 242 173 45,129 45,233 45,371 45,406 Tanga 65 66 7,643 5,796 7,708 5,863 Pangani 237 419 5,685 5,938 5,922 6,357 Handeni 1,236 4,546 45,544 72,059 46,779 76,606 Kilindi 678 1,118 17,616 32,107 18,294 33,225 Total 8,656 12,880 233,037 254,725 241,693 267,605 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 428 477 71,803 49,874 72,230 50,351 0.9 Korogwe 205 94 41,481 40,806 41,687 40,899 0.2 Muheza 59 191 43,499 33,692 43,558 33,883 0.6 Tanga 98 56 5,577 3,117 5,675 3,173 1.8 Pangani 11 21 5,719 5,239 5,730 5,260 - Handeni 380 382 46,292 73,717 46,671 74,099 0.5 Kilindi 243 561 17,806 31,265 18,050 31,825 1.8 Total 1,424 1,781 232,177 237,709 233,601 239,490 0.7 % 1 1 99 99 100 100 Number % Number % Lushoto 69,510 80 17,069 20 86,580 Korogwe 29,751 65 16,240 35 45,990 Muheza 41,149 84 8,045 16 49,195 Tanga 6,605 74 2,309 26 8,914 Pangani 4,977 70 2,151 30 7,128 Handeni 30,492 64 17,247 36 47,739 Kilindi 14,684 75 4,970 25 19,654 Total 197,168 74 68,030 26 265,198 District Insecticide Use g Insecticide District Herbicide Use Households Using Herbicide Households that Sold Produce Households that Did not Sell Produce Total Number of households % of Planted area using Herbicide Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region g Insecticide Total 7.2j: Number of Crops Producing Households Reporting Selling Agricultural Produce by District; 2002/03 Agricultural Year District Households Not Using Herbicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 168 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,157 1,282 71,073 49,069 72,230 50,351 2.5 Korogwe 800 583 40,887 40,316 41,687 40,899 1.4 Muheza 182 93 43,376 33,789 43,558 33,883 0.3 Tanga 119 56 5,556 3,117 5,675 3,173 1.8 Pangani 69 194 5,661 5,066 5,730 5,260 3.7 Handeni 395 654 46,276 73,444 46,671 74,099 0.9 Kilindi 195 344 17,855 31,481 18,050 31,825 1.1 Total 2,917 3,208 230,684 236,282 233,601 239,490 1.3 % 1.2 1.3 98.8 98.7 100.0 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 10,706 8,432 61,525 41,919 72,230 50,351 17 Korogwe 7,356 10,547 34,331 30,352 41,687 40,899 26 Muheza 1,124 1,039 42,433 32,844 43,558 33,883 3 Tanga 781 535 4,895 2,638 5,675 3,173 17 Pangani 964 1,166 4,766 4,094 5,730 5,260 22 Handeni 3,982 7,133 42,689 66,965 46,671 74,099 10 Kilindi 624 1,637 17,425 30,189 18,050 31,825 5 Total 25,537 30,490 208,064 209,000 233,601 239,490 13 % 11 13 89 87 100 100 District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON, Tanga Region % of Planted area using Fungicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 169 Number of House - holds Planted Area Number of House -holds Planted Area Number of House - holds Planted Area Numbe r of House - holds Planted Area Number of House - holds Planted Area Numbe r of House - holds Planted Area Number of House - holds Planted Area CEREALS 6,895 7,865 153,422 129,869 1,032 677 2,299 1,739 41,404 42,651 66 53 205,117 182,855 Maize 6,475 7,718 142,137 125,559 903 564 1,865 1,592 37,598 41,165 66 53 189,044 176,651 Paddy 420 147 10,700 4,046 129 113 434 147 3,675 1,459 0 . 15,357 5,913 Sorghum 0 . 44 15 0 . 0 . 22 5 0 . 66 19 Finger Millet 0 . 108 44 0 . 0 . 108 22 0 . 217 66 Wheat 0 . 433 205 0 . 0 . 0 . 0 . 433 205 ROOTS & TUBERS 0 . 23,431 7,311 59 12 0 . 4,435 1,309 0 . 27,925 8,632 Cassava 0 . 1,993 628 59 12 0 . 263 143 0 . 2,315 783 Sweet Potatoes 0 . 1,718 349 0 . 0 . 749 244 0 . 2,468 593 Irish Potatoes 0 . 19,351 6,283 0 . 0 . 3,063 806 0 . 22,414 7,089 Yams 0 . 0 . 0 . 0 . 213 80 0 . 213 80 Cocoyam 0 . 369 51 0 . 0 . 146 35 0 . 515 86 PULSES 1,544 719 77,819 31,433 571 183 535 124 20,137 9,883 0 . 100,606 42,342 Mung Beans 46 29 0 . 87 35 0 . 0 . 0 . 133 64 Beans 1,109 532 70,361 29,291 107 22 284 56 17,125 8,903 0 . 88,986 38,803 Cowpeas 388 159 5,409 1,650 140 61 165 42 2,624 810 0 . 8,727 2,720 Green Gram 0 . 2,049 493 237 66 87 26 388 171 0 . 2,760 755 OIL SEEDS & OIL NU 0 . 2,874 1,222 0 . 180 33 1,448 562 0 . 4,502 1,817 Sunflower 0 . 0 . 0 . 0 . 96 78 0 . 96 78 Simsim 0 . 942 570 0 . 90 18 131 141 0 . 1,163 729 Groundnuts 0 . 1,932 652 0 . 90 15 1,221 344 0 . 3,243 1,010 FRUITS & VEGETABL 0 . 8,509 1,995 21 2 0 . 2,526 525 33 3 11,089 2,525 Okra 0 . 160 19 21 2 0 . 39 5 0 . 220 26 Bitter Aubergine 0 . 239 38 0 . 0 . 302 138 0 . 541 176 Onions 0 . 300 80 0 . 0 . 99 20 0 . 399 100 Cabbage 0 . 1,963 429 0 . 0 . 315 73 0 . 2,277 502 Tomatoes 0 . 3,441 823 0 . 0 . 659 125 0 . 4,100 948 Carrot 0 . 140 121 0 . 0 . 146 22 0 . 286 143 Chillies 0 . 1,025 253 0 . 0 . 342 54 0 . 1,367 307 Amaranths 0 . 573 62 0 . 0 . 23 1 33 3 628 66 Pumpkins 0 . 119 5 0 . 0 . 460 59 0 . 579 65 Cucumber 0 . 174 70 0 . 0 . 99 20 0 . 273 90 Egg Plant 0 . 182 18 0 . 0 . 22 5 0 . 204 23 Water Mellon 0 . 193 76 0 . 0 . 21 2 0 . 214 78 CASH CROPS 0 . 813 416 0 . 0 . 262 32 0 . 1,075 448 Cotton 0 . 313 253 0 . 0 . 107 11 0 . 419 264 Tobacco 0 . 409 145 0 . 0 . 156 21 0 . 565 166 Jute 0 . 91 18 0 . 0 . 0 . 0 . 91 18 Total 8,438 8,584 266,868 172,247 1,684 875 3,014 1,896 70,212 54,961 98 56 350,314 238,619 % 4 72 0 1 23 0 100 7.2h: Planted Area and Number of Crop Growing Households During the Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agricultural Year Crop Land Clearing Method Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Other Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 170 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 77,511 35,639 21,772 0.611 34,582 15,479 8,971 0.580 51,118 30,743 0.601 Korogwe 24,375 12,945 4,224 0.326 40,827 33,425 11,484 0.344 46,369 15,709 0.339 Muheza 35,248 21,126 13,574 0.643 42,339 29,652 25,753 0.869 50,778 39,327 0.774 Tanga 3,744 1,774 811 0.457 4,310 2,171 946 0.436 3,946 1,757 0.445 Pangani 4,040 2,950 1,428 0.484 5,205 4,092 2,126 0.520 7,042 3,554 0.505 Handeni 32,034 26,149 14,467 0.553 46,454 69,539 50,471 0.726 95,688 64,938 0.679 Kilindi 9,201 9,460 5,635 0.596 16,053 23,076 11,940 0.517 32,536 17,575 0.540 Total 186,153 110,043 61,910 0.563 189,772 177,433 111,692 0.629 287,476 173,602 0.604 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1,650 557 1,094 1.963 994 374 263 0.703 931 1,356 1.457 Korogwe 2,102 972 2,226 2.290 4,039 1,686 1,178 0.699 2,659 3,405 1.281 Muheza 424 171 141 0.825 4,738 1,472 1,282 0.871 1,644 1,424 0.866 Tanga 0 . . 0.000 1,443 545 112 0.205 545 112 0.205 Pangani 23 5 12 2.470 1,156 495 224 0.452 500 235 0.471 Handeni 0 . . 0.000 2,781 1,245 361 0.290 1,245 361 0.290 Kilindi 48 29 15 0.494 291 113 52 0.463 142 67 0.470 Total 4,247 1,735 3,488 2.010 15,443 5,930 3,472 0.585 7,665 6,960 0.908 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 146 35 321 9.057 0 . . 0.000 35 321 9.057 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 33 14 6 0.445 14 6 0.445 Pangani 68 18 0 0.024 33 6 1 0.145 24 1 0.053 Handeni 107 43 16 0.371 0 . . 0.000 43 16 0.371 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 320 97 338 3.485 66 19 7 0.357 116 345 2.969 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 217 66 23 0.346 66 23 0.346 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 217 66 23 0.346 66 23 0.346 Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Short Rainy Season Long Rainy Season Total District Paddy 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Fingermillet District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 171 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 433 205 57 0.280 205 57 0.280 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 433 205 57 0.280 205 57 0.280 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Lushoto 3,066 862 1,273 1.477 22,490 5,595 8,549 1.581 6,457 9,822 1.566 Korogwe 593 216 96 0.443 10,005 3,804 4,388 3.439 4,020 4,484 3.046 Muheza 678 196 396 2.023 22,608 11,576 16,155 2.373 11,772 16,551 2.363 Tanga 0 0 . 0.000 5,479 2,730 5,041 2.648 2,730 5,041 2.648 Pangani 44 7 0 0.000 2,513 1,110 844 1.855 1,117 844 1.829 Handeni 726 440 356 0.809 5,628 2,722 4,695 3.519 3,162 5,051 2.847 Kilindi 49 5 10 1.976 2,434 1,470 3,697 3.068 1,475 3,707 3.064 Total 5,155 1,725 2,131 1.235 71,157 29,007 43,369 2.358 30,732 45,500 2.264 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1154 223 372 1.673 1,154 311 122 0.392 533 494 0.927 Korogwe 0 . . 0.000 209 32 21 0.657 32 21 0.657 Muheza 259 26 23 0.859 91 18 12 0.642 45 34 0.769 Tanga 134 39 65 1.665 187 69 145 2.096 108 210 1.940 Pangani 22 9 2 0.247 103 18 25 1.401 27 27 1.009 Handeni 422 171 55 0.322 431 76 16 0.213 247 71 0.288 Kilindi 49 12 20 1.647 292 69 124 1.801 81 144 1.778 Total 2041 480 537 1.119 2,468 593 465 0.784 1,073 1,002 0.934 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 29593 8270 11875 1.436 22,184 7,039 8,662 1.231 15,309 20,537 1.341 Korogwe 194 44 98 2.227 194 46 98 2.122 90 195 2.173 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 37 4 4 0.988 4 4 0.988 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 29786 8314 11973 1.440 22,414 7,089 8,763 1.236 15,402 20,736 1.346 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Wheat District 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 172 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 213 51 0 0.000 213 80 55 0.684 132 55 0.417 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 213 51 0 0.000 213 80 55 0.684 132 55 0.417 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 437 88 127 1.444 437 78 101 1.287 166 228 1.370 Korogwe 213 22 365 16.916 0 . . 0.000 22 365 16.916 Muheza 435 79 82 1.038 79 8 0 0.000 87 82 0.944 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 1,085 188 574 3.045 515 86 101 1.169 275 675 2.455 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 87 35 52 1.482 35 52 1.482 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 46 29 36 1.265 29 36 1.265 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 133 64 88 1.385 64 88 1.385 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 68309 21587 7885 0.365 63,635 25,394 9,396 0.370 46,981 17,280 0.368 Korogwe 6409 1850 663 0.358 11,917 4,129 2,711 0.656 5,979 3,374 0.564 Muheza 1977 499 119 0.239 3,478 875 424 0.485 1,374 543 0.396 Tanga 31 6 1 0.084 31 6 0 0.079 13 1 0.082 Pangani 22 4 1 0.198 0 . . 0.000 4 1 0.198 Handeni 312 170 22 0.129 1,076 261 40 0.154 432 62 0.144 Kilindi 97 69 8 0.120 8,898 8,176 2,753 0.337 8,245 2,761 0.335 Total 77157 24185 8699 0.360 89,035 38,843 15,325 0.395 63,028 24,023 0.381 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Mung beans 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans Tanzania Agriculture Sample Census-2003 Tanga Appendix II 173 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.00 0 . . 0.000 0 0 0.000 Korogwe 799 141 12 0.083 614 154 12 0.080 295 24 0.081 Muheza 4,138 1,174 306 0.261 2,996 842 176 0.209 2,016 482 0.239 Tanga 1,137 239 58 0.245 705 144 19 0.129 383 77 0.201 Pangani 1,812 633 115 0.181 1,239 365 52 0.144 998 167 0.167 Handeni 16,732 6,823 1,571 0.230 3,087 1,159 227 0.196 7,982 1,798 0.225 Kilindi 1,122 266 63 0.238 194 66 12 0.183 333 76 0.227 Total 25,741 9,276 2,125 0.229 8,833 2,731 499 0.183 12,007 2,624 0.219 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 139 56 83 1.482 56 83 1.482 Korogwe 103 42 10 0.247 107 22 1 0.035 64 11 0.174 Muheza 1,064 226 74 0.329 1,579 355 69 0.194 582 143 0.246 Tanga 561 97 13 0.130 264 52 10 0.186 149 22 0.149 Pangani 349 123 47 0.384 190 53 15 0.282 176 62 0.354 Handeni 1,721 620 143 0.231 433 197 68 0.343 817 211 0.258 Kilindi 0 . . 0.000 49 20 3 0.150 20 3 0.150 Total 3,798 1,108 288 0.260 2,760 755 248 0.329 1,863 536 0.288 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 22 2 0 0.198 0 . . 0.000 2 0 0.198 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 22 2 0 0.198 0 . . 0.000 2 0 0.198 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 23 2 1 0.296 0 . . 0.000 2 1 0.296 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 23 2 1 0.296 0 . . 0.000 2 1 0.296 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 174 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 140 28 84 2.964 0 . . 0.000 28 84 2.964 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 108 22 24 1.112 0 . . 0.000 22 24 1.112 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 248 50 109 2.159 0 . . 0.000 50 109 2.159 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 96 78 35 0.451 78 35 0.451 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 96 78 35 0.451 78 35 0.451 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 90 18 12 0.642 18 12 0.642 Tanga 26 21 2 0.099 64 18 6 0.326 39 8 0.203 Pangani 67 27 8 0.279 45 27 3 0.124 54 11 0.201 Handeni 108 44 16 0.371 867 636 246 0.387 680 262 0.386 Kilindi 0 . . 0.000 97 30 4 0.148 30 4 0.148 Total 202 92 26 0.281 1,163 729 271 0.372 822 297 0.362 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 206 53 3 0.060 903 306 640 2.092 359 643 1.790 Muheza 1657 448 166 0.370 1,289 380 158 0.416 828 324 0.391 Tanga 254 52 34 0.666 117 52 29 0.547 104 63 0.606 Pangani 70 38 9 0.235 143 54 16 0.300 93 25 0.273 Handeni 108 22 0 0.000 753 206 104 0.506 228 104 0.457 Kilindi 0 . . 0.000 144 34 14 0.425 34 14 0.425 Total 2296 613 212 0.346 3,350 1,032 961 0.932 1,645 1,174 0.714 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Field peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Field Peas 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 175 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 48 20 10 0.494 0 . . 0.000 20 10 0.494 Total 48 20 10 0.494 0 . . 0.000 20 10 0.494 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 56 9 13 1.422 147 20 14 0.683 29 26 0.913 Pangani 0 . . 0.000 73 6 3 0.458 6 3 0.458 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 56 9 13 1.422 220 26 17 0.629 35 29 0.831 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 14 4 2 0.529 0 . . 0.000 4 2 0.529 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 14 4 2 0.529 0 . . 0.000 4 2 0.529 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 90 18 216 11.856 270 36 118 3.236 55 334 6.109 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 59 10 8 0.813 10 8 0.813 Handeni 0 . . 0.000 212 129 170 1.317 129 170 1.317 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 90 18 216 11.856 541 176 296 1.685 194 512 2.641 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Castor oil District 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Radish District 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine Tanzania Agriculture Sample Census-2003 Tanga Appendix II 176 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 146 59 146 2.470 59 146 2.470 Korogwe 107 11 11 0.988 186 38 126 3.359 48 137 2.827 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 19 2 4 1.976 2 4 1.976 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 95 7 74 10.246 49 2 4 1.902 9 78 8.448 Total 203 18 85 4.681 399 100 279 2.782 119 364 3.072 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 291 88 66 0.746 0 . . 0.000 88 66 0.746 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 291 88 66 0.746 0 . . 0.000 88 66 0.746 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1285 302 1349 4.475 2,013 449 2,013 4.481 751 3,362 4.479 Korogwe 87 18 . 0.000 87 18 0 0.000 35 0 0.000 Muheza 92 9 20 2.134 0 . . 0.000 9 20 2.134 Tanga 23 1 2 1.976 23 1 1 1.482 2 3 1.729 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 106 32 42 1.317 32 42 1.317 Kilindi 95 15 39 2.662 49 2 5 2.717 17 44 2.669 Total 1582 344 1410 4.099 2,277 502 2,062 4.109 846 3,472 4.105 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 5062 1176 6116 5.199 1,742 504 2,569 5.099 1,680 8,685 5.169 Korogwe 1137 240 433 1.805 1,000 216 389 1.800 456 822 1.803 Muheza 430 47 105 2.221 343 60 80 1.319 108 184 1.714 Tanga 190 48 121 2.516 148 15 17 1.148 63 139 2.192 Pangani 131 44 98 2.247 265 49 61 1.247 92 159 1.720 Handeni 323 27 21 0.774 217 22 70 3.211 49 91 1.866 Kilindi 191 38 326 8.483 387 82 446 5.435 120 772 6.406 Total 7462 1621 7220 4.455 4,100 948 3,632 3.832 2,569 10,852 4.225 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Ginger 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 177 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 106 17 0 0.000 17 0 0.000 Muheza 0 . . 0.000 86 5 0 0.000 5 0 0.000 Tanga 21 2 6 2.964 54 2 2 0.874 4 8 1.886 Pangani 22 9 223 24.700 22 9 0 0.000 18 223 12.350 Handeni 0 . . 0.000 310 31 29 0.916 31 29 0.916 Kilindi 49 2 4 1.853 0 . . 0.000 2 4 1.853 Total 92 13 234 17.324 579 65 31 0.475 78 265 3.384 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 273 90 668 7.390 90 668 7.390 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 273 90 668 7.390 90 668 7.390 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 96.849 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 79 8 8 1.037 8 8 1.037 Tanga 66 7 10 0.000 66 7 8 1.171 13 17 1.307 Pangani 22 2 1 24.037 59 8 4 0.425 11 5 0.461 Handeni 0 . . 106.178 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 88 9 11 227.064 204 23 20 0.856 32 31 0.960 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 97 10 0 0.000 193 76 687 9.018 86 687 7.990 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 21 2 12 5.928 2 12 5.928 Pangani 24 19 29 1.482 0 . . 0.000 19 29 1.482 Handeni 106 107 53 0.494 0 . . 0.000 107 53 0.494 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 227 137 82 0.599 214 78 699 8.936 215 781 3.634 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon Tanzania Agriculture Sample Census-2003 Tanga Appendix II 178 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 23 2 7 2.964 0 . . 0.000 2 7 2.964 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 23 2 7 2.964 0 . . 0.000 2 7 2.964 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 419 264 165 0.625 264 165 0.625 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 419 264 165 0.625 264 165 0.625 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 143 15 3 0.000 0 . . 0.000 15 3 0.198 Korogwe 0 . . 96.849 214 27 15 0.549 27 15 0.549 Muheza 0 . . 0.000 183 46 42 0.909 46 42 0.909 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 24.037 22 9 0 0.000 9 0 0.000 Handeni 0 . . 106.178 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 146 83 13 0.157 83 13 0.157 Total 143 15 3 227.064 565 166 70 0.422 180 73 0.404 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 91 18 12 0.642 18 12 0.642 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 91 18 12 0.642 18 12 0.642 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Seaweed 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Jute Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Jute Tanzania Agriculture Sample Census-2003 Tanga Appendix II 179 PERMANENT CROPS Tanzania Agriculture Sample Census-2003 Tanga Appendix II 180 Area planted(Ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Cassava 5,500.3 5,314 8,519.17 1603 Coconut 72.4 72 85.96 1187 Cashewnut 11.1 11 0.00 0 Coffee 477 Tea 2338 Wattle 147.8 0 0.00 0 Sugarcane 686.1 392 9,924.73 25340 Cardamon 115.3 115 25.83 224 Jack Fruit 0.0 . 67.75 0 Mpesheni 0.0 . 35.74 0 Banana 1,750.7 1,096 3,977.66 3630 Avocado 0.0 . 34.97 0 Mango 0.0 . 211.10 0 Pawpaw 0.0 . 26.07 0 Pineapple 0.0 . 0.73 0 Orange 4.3 6 14.47 2470 Mandarine/Tangerine 0.0 . 14.54 0 Plums 29.2 29 494.52 16913 Apples 0.0 6 849.71 146796 Pears 146.7 93 62,845.52 672846 Pitches 0.0 . 8.61 0 Lime/Lemon 0.0 0 0.00 0 Total 12,308.9 10,623 90,879.21 8555 Cassava 3,449.3 921 4,166.31 4525 Star Fruit 0.7 0 133.45 0 Coconut 1,682.1 539 3,912.58 7254 Cashewnut 578.2 73 110.94 1511 Coffee 453.5 2,878 34.72 12 Tea 455.3 338 1,148.74 3402 Kapok 20.9 21 0.00 0 Sugarcane 564.5 2,983 5,566.85 1866 Cardamon 1,231.5 721 111.72 155 Mshelisheli 0.1 0 0.00 0 Jack Fruit 262.1 127 2,321.44 18344 Banana 2,069.1 1,416 10,409.51 7353 Avocado 38.0 34 2,723.65 79218 Mango 1,487.0 1,350 13,879.09 10284 Pineapple 0.0 . 7.99 0 Orange 404.2 68 499.57 7379 Mandarine/Tangerine 10.8 0 4.26 0 Guava 1.0 0 31.96 0 Lime/Lemon 97.9 0 31.04 0 Total 12,806.1 11,468 45,093.82 3932 7.3 Production of Permanent Crops by crop type and Region - Tanga Lushoto Korogwe Tanzania Agriculture Sample Census-2003 Tanga Appendix II 181 Black Pepper 1,520.6 470 686.52 1460 Cassava 11,523.5 6,757 16,137.28 2388 Star Fruit 35.8 36 13.25 371 Palm Oil 18.3 18 9.02 494 Coconut 9,380.0 4,722 9,349.80 1980 Cashewnut 4,599.6 3,527 2,361.91 670 Coffee 47.4 0 2.42 0 Tea 339.9 340 1,655.56 4871 Cocoa 306.2 312 232.55 746 Sugarcane 407.6 410 12,877.44 31446 Cardamon 1,487.8 1,273 197.07 155 Tamarin 47.4 47 4.50 95 Cinamon 105.4 32 122.00 3793 Cloves 361.5 74 351.76 4755 Jack Fruit 260.3 245 4,194.57 17119 Mpesheni 0.0 . 0.00 0 Banana 2,280.9 1,930 11,511.85 5966 Avocado 32.7 16 183.73 11197 Mango 145.4 153 4,309.18 28151 Pawpaw 110.3 117 196.51 1680 Pineapple 188.6 514 242.01 470 Orange 6,432.8 3,993 45,425.51 11376 Grape Fruit 35.7 36 81.06 2268 Mandarine/Tangerine 0.0 . 46.53 0 Guava 0.0 . 87.27 0 Pitches 15.8 . 3.12 0 Lime/Lemon 103.0 95 320.52 3391 Total 39,786.4 25,117 110,602.95 4404 Sour Soup 0.0 . 0.57 0 Cassava 2,689.4 1,863 5,025.41 2698 Pigeon Pea 0.0 0 0.00 0 Star Fruit 0.0 . 83.29 0 Coconut 964.6 837 3,171.02 3789 Cashewnut 949.7 23 288.73 12310 Sugarcane 23.8 24 139.67 5871 Mshelisheli 0.0 . 0.68 0 Jack Fruit 0.0 0 103.03 0 Banana 67.6 34 612.56 18032 Avocado 0.0 . 71.76 0 Mango 6.2 6 2,498.04 408339 Pawpaw 0.0 . 125.02 0 Pineapple 0.0 0 69.82 0 Orange 63.3 49 1,741.18 35517 Mandarine/Tangerine 0.0 0 23.02 0 Guava 0.0 . 1.86 0 Lime/Lemon 1.1 1 125.83 118823 Total 4,765.7 2,837 14,081.49 4964 Muheza Tanga cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 182 Cassava 1,097.1 442 843.85 1910 Pigeon Pea 44.2 18 15.87 883 Star Fruit 4.3 4 107.09 25001 Palm Oil 0.0 . 0.14 0 Coconut 2,417.8 1,043 7,508.51 7198 Cashewnut 1,766.1 1,029 1,795.16 1745 Sugarcane 6.8 7 46.90 6918 Jack Fruit 2.2 0 313.66 0 Mpesheni 3.3 . 0.90 0 Banana 151.7 82 624.67 7609 Mango 38.4 0 739.18 0 Pawpaw 0.0 . 6.70 0 Pineapple 14.6 18 9.16 504 Orange 157.7 443 1,833.55 4139 Mandarine/Tangerine 0.0 . 3.56 0 Guava 0.0 . 44.66 0 Lime/Lemon 16.2 0 156.35 0 Durian 0.0 . 55.35 0 Total 5,720.5 3,086 14,105.26 4571 Sour Soup 64.5 21 106.18 4940 Cassava 2,565.3 1,177 4,564.91 3878 Pigeon Pea 21.8 22 8.09 371 Coconut 248.1 315 2,238.68 7103 Cashewnut 0.0 0 23.32 0 Kapok 4.4 4 243.66 55575 Sugarcane 471.9 205 5,320.73 25948 Jack Fruit 904.0 496 3,191.32 6428 Mpesheni 8.5 . 361.00 0 Banana 1,143.1 670 4,587.48 6852 Mango 1,271.2 911 9,151.86 10051 Pawpaw 21.5 19 310.13 15989 Orange 2,200.7 1,278 14,980.37 11725 Lime/Lemon 0.0 . 0.00 0 Total 8,925.1 5,119 45,087.73 8809 Cassava 1,399.4 1,134 3,660.84 3229 Pigeon Pea 2,417.4 1,490 450.05 302 Malay Apple 0.0 . 81.29 0 Coconut 0.0 39 62.01 1582 Sugarcane 195.1 196 5,810.68 29632 Cardamon 117.6 118 10.04 85 Cinamon 0.2 0 0.73 0 Jack Fruit 118.9 40 366.43 9265 Banana 662.1 181 2,401.84 13259 Avocado 0.0 . 0.59 0 Mango 1,319.9 332 4,852.79 14607 Pawpaw 0.0 . 0.34 0 Orange 79.3 118 715.46 6086 Mandarine/Tangerine 0.1 0 0.29 0 Guava 4.0 . 4.36 0 Total 6,313.9 3,647 18,417.71 5050 Kilindi Pangani Handeni cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 183 Sour Soup 64.5 21 106.75 4966 Black Pepper 1,520.6 470 686.52 1460 Cassava 28,224.4 17,607 42,917.77 2438 Pigeon Pea 2,483.5 1,530 474.01 310 Malay Apple 0.0 . 81.29 0 Star Fruit 40.7 40 337.08 8417 Palm Oil 18.3 18 9.16 502 Coconut 14,765.1 7,568 26,328.55 3479 Cashewnut 7,904.7 4,664 4,580.07 982 Coffee 3,199.5 5,250 1,168.37 223 Tea 1,941.3 1,794 5,415.18 3018 Cocoa 306.2 312 232.55 746 Wattle 147.8 0 0.00 0 Kapok 25.3 25 243.66 9642 Sugarcane 2,356.0 4,216 39,687.01 9414 Cardamon 2,952.1 2,227 344.66 155 Tamarin 47.4 47 4.50 95 Cinamon 105.6 32 122.74 3815 Cloves 361.5 74 351.76 4755 Mshelisheli 0.1 0 0.68 0 Jack Fruit 1,547.3 908 10,558.20 11633 Mpesheni 11.8 . 397.65 0 Banana 8,125.1 5,408 34,125.57 6311 Avocado 70.7 51 3,014.69 59356 Mango 4,268.1 2,751 35,641.24 12953 Pawpaw 131.9 136 664.78 4874 Pineapple 203.2 533 329.70 619 Orange 9,342.3 5,954 65,210.11 10952 Grape Fruit 35.7 36 81.06 2268 Mandarine/Tangerine 10.9 0 92.20 0 Guava 4.9 0 170.10 0 Plums 29.2 29 494.52 16913 Apples 0.0 6 849.71 146796 Pears 146.7 93 62,845.52 672846 Pitches 15.8 . 11.73 0 Lime/Lemon 218.2 96 633.74 6631 Durian 0.0 . 55.35 0 Total 90,626.6 61,896 338,268.16 5465 Total cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 184 cont… Area Planted by crop type - Tanga Region Crop Area planted % Coconut 14,765.1 23.7 Orange 9,342.3 15.0 Banana 8,125.1 13.0 Cashewnut 7,904.7 12.7 Mango 4,268.1 6.8 Coffee 3,199.5 5.1 Cardamon 2,952.1 4.7 Pigeon Pea 2,483.5 4.0 Sugarcane 2,356.0 3.8 Tea 1,941.3 3.1 Jack Fruit 1,547.3 2.5 Black Pepper 1,520.6 2.4 Cloves 361.5 0.6 Cocoa 306.2 0.5 Lime/Lemon 218.2 0.3 Pineapple 203.2 0.3 Wattle 147.8 0.2 Pears 146.7 0.2 Pawpaw 131.9 0.2 Cinamon 105.6 0.2 Avocado 70.7 0.1 Sour Soup 64.5 0.1 Tamarin 47.4 0.1 Star Fruit 40.7 0.1 Grape Fruit 35.7 0.1 Plums 29.2 0.0 Kapok 25.3 0.0 Palm Oil 18.3 0.0 Pitches 15.8 0.0 Mpesheni 11.8 0.0 Mandarine/Tangerine 10.9 0.0 Guava 4.9 0.0 Mshelisheli 0.1 0.0 Malay Apple 0.0 0.0 Apples 0.0 0.0 Durian 0.0 0.0 Total 62,402.2 100.0 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 185 7.4 Total Area Planted with Coconut by District - Tanga Region 7.5 Total Area Planted with Oranges by District - Tanga Region District Area planted with coconuts Total Area planted (ha) % of Total Area Planted hh with coconuts Average Planted Area per Household District Area planted with oranges(Ha) Total Area planted (ha) % of Total Area Planted hh with oranges Average Planted Area per Household Muheza 9,380.0 69,468 63.5 16,250 0.58 Muheza 6,432.8 69,468 68.86 10,742 0.60 Pangani 2,417.8 111,307 16.4 3,525 0.69 Handeni 2,200.7 111,307 23.56 7,449 0.30 Korogwe 1,682.1 0.38 Korogwe 404.2 61,104 4.33 1,346 0.30 Tanga 964.6 0.22 Pangani 157.7 10,260 1.69 1,501 0.11 Handeni 248.1 43,153 1.7 3,402 0.07 Kilindi 79.3 43,153 0.85 1,122 0.07 Lushoto 72.4 8,198 0.5 412 0.18 Tanga 63.3 8,198 0.68 1,662 0.04 Kilindi 0.0 125,045 0.0 341 0.00 Lushoto 4.3 125,045 0.05 145 0.03 Total 14,765.1 357,171 100.0 32,814 0.45 Total 9,342.3 428,535 100.00 23,967 0.39 7.6 Total Area Planted with Banana by District - Tanga Region 7.7 Total Area Planted with Cashewnuts by District - Tanga Region District Area planted with banana(Ha) Total Area planted (ha) % of Total Area Planted hh with bananas Average Planted Area per Household District Area planted with cashewnuts(Ha ) Total Area planted (ha) % of Total Area Planted hh with cashewnuts Average Planted Area per Household Muheza 2,280.9 69,468 0.53 14,380 0.16 Pangani 4,599.6 69,468 3031.51 8,508 0.54 Korogwe 2,069.1 61,104 0.48 10,403 0.20 Tanga 1,766.1 10,260 1164.03 2,042 0.87 Lushoto 1,750.7 125,045 0.41 26,066 0.07 Muheza 949.7 8,198 625.93 2,213 0.43 Handeni 1,143.1 111,307 0.27 5,325 0.21 Korogwe 578.2 61,104 381.06 2,350 0.25 Kilindi 662.1 43,153 0.15 2,966 0.22 Lushoto 11.1 125,045 7.29 427 0.03 Pangani 151.7 10,260 0.04 1,133 0.13 Handeni 0.0 111,307 0.00 534 0.00 Tanga 67.6 8,198 0.02 1,193 0.06 Kilindi 0.0 43,153 0.00 0 0.00 Total 8,125.1 428,535 1.90 61,464 0.13 Total 7,904.7 428,535 5209.82 16,074 0.49 COCONUTS Oranges CASHEWNUTS Banana Tanzania Agriculture Sample Census-2003 Tanga Appendix II 186 7.8 Production of Permanent Planted Crops with Fertiliser by Fertiliser Use - Tanga Region Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Apples 1,005 0 0 2,153 3,159 Avocado 0 180 0 3,235 3,415 Banana 6,551 1,047 0 53,040 60,637 Black Pepper 0 86 0 3,434 3,520 Cardamon 214 173 0 7,207 7,594 Cashewnut 547 0 0 15,118 15,665 Cinamon 92 92 0 1,763 1,946 Cloves 92 178 0 1,809 2,079 Cocoa 0 0 0 249 249 Coconut 1,202 183 101 30,572 32,058 Coffee 2,838 146 0 8,051 11,035 Durian 0 22 0 0 22 Grape Fruit 0 0 0 90 90 Guava 97 0 0 561 658 Jack Fruit 106 86 0 13,434 13,626 Kapok 0 0 0 211 211 Lime/Lemon 314 0 0 3,872 4,185 Malay Apple 0 0 0 98 98 Mandarine/Tangerine 0 0 0 766 766 Mango 616 1,294 49 30,404 32,363 Mpesheni 143 0 0 207 350 Mshelisheli 23 0 0 203 226 Orange 826 447 32 21,631 22,935 Palm Oil 0 0 0 113 113 Pawpaw 168 0 0 2,266 2,434 Pears 578 584 0 6,349 7,511 Pigeon Pea 0 0 0 1,873 1,873 Pineapple 88 0 0 1,896 1,984 Pitches 143 0 0 1,234 1,377 Plums 143 0 0 873 1,016 Plums 143 0 0 873 1,016 Sour Soup 23 0 0 106 129 Star Fruit 0 0 0 357 357 Sugarcane 401 476 146 11,971 12,993 Tamarin 0 0 0 90 90 Tea 0 0 247 4,467 4,714 Wattle 0 0 0 730 730 Total 17,668 5,690 606 297,600 321,564 Fertilizer Use Tanzania Agriculture Sample Census-2003 Tanga Appendix II 187 7.9 Production of Permanent Planted Crops with Fertiliser by Farm Yard Manure - Tanga Region Mostly Farm Yard Manure Total % Mpesheni 143 350 40.8 Apples 1,005 3,159 31.8 Coffee 2,838 11,035 25.7 Sour Soup 23 129 17.6 Guava 97 658 14.7 Plums 143 1,016 14.1 Plums 143 1,016 14.1 Banana 6,551 60,637 10.8 Pitches 143 1,377 10.4 Mshelisheli 23 226 10.1 Pears 578 7,511 7.7 Lime/Lemon 314 4,185 7.5 Pawpaw 168 2,434 6.9 Cinamon 92 1,946 4.7 Pineapple 88 1,984 4.5 Cloves 92 2,079 4.4 Coconut 1,202 32,058 3.8 Orange 826 22,935 3.6 Cashewnut 547 15,665 3.5 Sugarcane 401 12,993 3.1 Cardamon 214 7,594 2.8 Mango 616 32,363 1.9 Jack Fruit 106 13,626 0.8 Avocado 0 3,415 0.0 Black Pepper 0 3,520 0.0 Cocoa 0 249 0.0 Durian 0 22 0.0 Grape Fruit 0 90 0.0 Kapok 0 211 0.0 Malay Apple 0 98 0.0 Mandarine/Tangerine 0 766 0.0 Palm Oil 0 113 0.0 Pigeon Pea 0 1,873 0.0 Star Fruit 0 357 0.0 Tamarin 0 90 0.0 Tea 0 4,714 0.0 Wattle 0 730 0.0 Total 16,353 253,227 6.5 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 188 7.10 Production of Permanent Planted Crops with Fertiliser by Inorganic Fertiliser - Tanga Region Mostly Inorganic Fertilizer Total % Tea 247 4,714 5.25 Sugarcane 146 12,993 1.12 Coconut 101 32,058 0.32 Mango 49 32,363 0.15 Orange 32 22,935 0.14 Apples 0 3,159 0 Avocado 0 3,415 0 Banana 0 60,637 0 Black Pepper 0 3,520 0 Cardamon 0 7,594 0 Cashewnut 0 15,665 0 Cinamon 0 1,946 0 Cloves 0 2,079 0 Cocoa 0 249 0 Coffee 0 11,035 0 Durian 0 22 0 Grape Fruit 0 90 0 Guava 0 658 0 Jack Fruit 0 13,626 0 Kapok 0 211 0 Lime/Lemon 0 4,185 0 Malay Apple 0 98 0 Mandarine/Tangerine 0 766 0 Mpesheni 0 350 0 Mshelisheli 0 226 0 Palm Oil 0 113 0 Pawpaw 0 2,434 0 Pears 0 7,511 0 Pigeon Pea 0 1,873 0 Pineapple 0 1,984 0 Pitches 0 1,377 0 Plums 0 1,016 0 Plums 0 1,016 0 Sour Soup 0 129 0 Star Fruit 0 357 0 Tamarin 0 90 0 Wattle 0 730 0 Total 575 253,227 0.23 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 189 7.11 Production of Permanent Planted Crops with Fertiliser by Inorganic Fertiliser - Tanga Region Mostly Compost Total % Durian 22 22 100.0 Cloves 178 2,079 8.6 Pears 584 7,511 7.8 Avocado 180 3,415 5.3 Cinamon 92 1,946 4.7 Mango 1,294 32,363 4.0 Sugarcane 476 12,993 3.7 Black Pepper 86 3,520 2.5 Cardamon 173 7,594 2.3 Orange 447 22,935 1.9 Banana 1,047 60,637 1.7 Coffee 146 11,035 1.3 Jack Fruit 86 13,626 0.6 Coconut 183 32,058 0.6 Apples 0 3,159 0.0 Cashewnut 0 15,665 0.0 Cocoa 0 249 0.0 Grape Fruit 0 90 0.0 Guava 0 658 0.0 Kapok 0 211 0.0 Lime/Lemon 0 4,185 0.0 Malay Apple 0 98 0.0 Mandarine/Tangerine 0 766 0.0 Mpesheni 0 350 0.0 Mshelisheli 0 226 0.0 Palm Oil 0 113 0.0 Pawpaw 0 2,434 0.0 Pigeon Pea 0 1,873 0.0 Pineapple 0 1,984 0.0 Pitches 0 1,377 0.0 Plums 0 1,016 0.0 Plums 0 1,016 0.0 Sour Soup 0 129 0.0 Star Fruit 0 357 0.0 Tamarin 0 90 0.0 Tea 0 4,714 0.0 Wattle 0 730 0.0 Total 5,690 321,564 Tanzania Agriculture Sample Census-2003 Tanga 190 Appendix II 191 AGROPROCESSING Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 192 Number % Number % Number % Lushoto 81,783 94 4,796 6 86,580 100 Korogwe 36,364 79 9,627 21 45,990 100 Muheza 43,887 89 5,308 11 49,195 100 Tanga 6,162 69 2,752 31 8,914 100 Pangani 5,133 72 1,995 28 7,128 100 Handeni 43,919 92 3,820 8 47,739 100 Kilindi 18,537 94 1,117 6 19,654 100 Total 235,784 89 29,414 11 265,198 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other Total Lushoto 1,875 1,131 75,285 0 0 3,348 144 0 81,783 Korogwe 1,901 1,051 32,787 213 0 411 0 0 36,364 Muheza 2,241 760 36,316 78 78 4,327 86 0 43,887 Tanga 827 659 4,476 0 0 201 0 0 6,162 Pangani 1,396 441 3,010 0 0 18 0 268 5,133 Handeni 5,809 2,954 35,155 0 0 0 0 0 43,919 Kilindi 2,140 98 15,109 0 0 1,190 0 0 18,537 Total 16,189 7,094 202,137 291 78 9,495 231 268 235,784 % 6.87 3.01 85.73 0.12 0.03 4.03 0.10 0.11 100.00 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 11,403 6,575 199,258 291 78 9,479 86 0 0 227,170 Paddy 1,836 260 11,381 0 0 188 0 0 0 13,665 Sorghum 33 0 107 0 0 0 0 0 0 140 Finger Millet 0 0 108 0 0 0 0 0 0 108 Wheat 143 0 146 0 0 0 0 0 0 290 Cassava 10,367 596 17,445 0 0 335 90 283 0 29,117 Sweet Potat 0 0 146 0 0 0 0 0 0 146 Beans 857 0 1,356 0 0 142 0 0 0 2,355 Cowpeas 235 0 0 0 0 0 0 0 0 235 Green Gram 43 0 0 0 0 0 0 0 0 43 Groundnut 760 108 0 0 0 0 0 0 0 868 Oil Palm 23 0 0 0 0 0 0 0 0 23 Coconut 5,828 18 24 0 0 0 0 380 0 6,250 Cashewnut 85 0 0 0 0 0 0 0 0 85 Coffee 0 872 903 0 0 0 0 0 0 1,774 Tea 0 0 0 0 0 0 144 0 146 291 Sugarcane 422 262 0 0 0 0 0 0 0 685 Pineapple 180 0 0 0 0 0 0 0 0 180 Tomatoes 108 0 0 0 0 0 0 0 0 108 Amaranths 108 0 0 0 0 0 0 0 0 108 Crop Method of Processing 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Tanga Region 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year District Households That Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 193 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Total Maize 226,323 107 171 127 441 227,170 Paddy 13,141 89 225 0 210 13,665 Sorghum 140 0 0 0 0 140 Finger Millet 108 0 0 0 0 108 Wheat 290 0 0 0 0 290 Cassava 28,546 0 266 81 224 29,117 Sweet Potat 146 0 0 0 0 146 Beans 2,065 0 290 0 0 2,355 Cowpeas 235 0 0 0 0 235 Green Gram 43 0 0 0 0 43 Groundnut 369 0 391 0 108 868 Oil Palm 23 0 0 0 0 23 Coconut 6,056 22 102 70 0 6,250 Cashewnut 85 0 0 0 0 85 Coffee 0 0 1,774 0 0 1,774 Tea 0 0 291 0 0 291 Sugarcane 0 0 685 0 0 685 Pineapple 180 0 0 0 0 180 Tomatoes 108 0 0 0 0 108 Amaranths 108 0 0 0 0 108 Total 277,966 218 4,194 278 984 283,641 Neighbours Market / Trade Store Secondary Market Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 6,956 8,169 0 646 277 450 2,113 82 208,477 227,170 Paddy 385 1,745 0 0 93 105 14 175 11,148 13,665 Sorghum 0 0 0 0 0 0 0 0 140 140 Finger Millet 0 0 0 0 0 0 0 0 108 108 Wheat 0 0 0 0 0 0 0 0 290 290 Cassava 319 5,179 142 0 0 91 0 0 23,387 29,117 Sweet Potat 0 0 0 146 0 0 0 0 0 146 Beans 0 340 0 0 0 0 144 0 1,870 2,355 Cowpeas 106 0 0 0 0 0 0 0 129 235 Green Gram 0 0 0 0 0 0 0 0 43 43 Groundnut 0 198 0 0 0 0 175 108 387 868 Oil Palm 0 0 0 0 0 0 0 0 23 23 Coconut 653 0 0 0 0 0 55 0 5,543 6,250 Cashewnut 0 0 0 0 0 0 0 0 85 85 Coffee 0 0 0 979 583 0 0 0 213 1,774 Tea 0 0 0 0 0 144 146 0 0 291 Sugarcane 107 49 0 0 0 0 214 0 316 685 Pineapple 0 0 0 0 0 0 90 0 90 180 Tomatoes 0 0 0 0 0 0 0 0 108 108 Amaranths 0 0 0 0 0 0 0 0 108 108 Total 8,525 15,679 142 1,771 953 792 2,951 365 252,464 283,641 Flour / Meal Grain Oil Juice Pulp Other Total Lushoto 74,995 6,644 0 0 144 0 81,783 Korogwe 33,525 2,310 0 528 0 0 36,364 Muheza 41,503 1,099 1,095 146 0 43 43,887 Tanga 5,348 741 64 0 0 8 6,162 Pangani 3,442 349 78 39 0 1,225 5,133 Handeni 42,000 1,812 107 0 0 0 43,919 Kilindi 17,902 537 0 48 0 49 18,537 Total 218,715 13,494 1,344 762 144 1,325 235,784 District Main Product 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Tanga Region Crop Where Sold 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Tanga Region 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Use of Product and Crop, Tanga Region Crop Product Use Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 194 Household /Human Consumption Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Total Lushoto 80,767 0 871 0 146 81,783 Korogwe 35,415 107 636 0 205 36,364 Muheza 43,722 0 0 79 86 43,887 Tanga 6,047 0 115 0 0 6,162 Pangani 5,012 0 98 23 0 5,133 Handeni 43,814 0 0 0 105 43,919 Kilindi 18,440 0 49 48 0 18,537 Total 233,217 107 1,768 150 542 235,784 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Lushoto 2,899 7,147 1,017 291 291 0 0 70,139 81,783 Korogwe 641 416 107 0 0 321 0 34,879 36,364 Muheza 332 0 0 76 91 90 87 43,210 43,887 Tanga 174 54 0 0 0 0 33 5,900 6,162 Pangani 182 54 0 0 0 136 0 4,760 5,133 Handeni 2,818 972 210 201 214 1,729 0 37,776 43,919 Kilindi 535 538 0 0 0 97 48 17,318 18,537 Total 7,582 9,180 1,334 568 595 2,374 169 213,982 235,784 Bran Cake Husk Juice Pulp Shell No by- product Other Total Lushoto 851 0 825 0 872 144 79,091 0 81,783 Korogwe 1,871 0 1,598 99 626 101 32,069 0 36,364 Muheza 14,914 1,160 399 0 78 0 27,336 0 43,887 Tanga 1,462 73 713 0 0 57 3,857 0 6,162 Pangani 1,563 533 164 0 0 0 2,103 770 5,133 Handeni 18,802 0 108 0 0 0 24,901 108 43,919 Kilindi 581 0 0 0 0 49 17,907 0 18,537 Total 40,044 1,765 3,807 99 1,576 352 187,263 879 235,784 District By Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Tanga Region District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Tanga Region 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Tanga Region District Product Use Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 195 MARKETING Tanzania Agriculture Sample Census-2003 Tanga Appendix II 196 Number % Number % Lushoto 69,510 80.3 17,069 19.7 86,580 Korogwe 29,751 64.7 16,240 35.3 45,990 Muheza 41,149 83.6 8,045 16.4 49,195 Tanga 6,605 74.1 2,309 25.9 8,914 Pangani 4,977 69.8 2,151 30.2 7,128 Handeni 30,492 63.9 17,247 36.1 47,739 Kilindi 14,684 74.7 4,970 25.3 19,654 Total 197,168 74.3 68,030 25.7 265,198 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Lushoto 292 17,772 0 143 721 146 874 65,760 85,708 Korogwe 512 15,936 105 204 189 0 2,311 23,561 42,819 Muheza 514 11,287 0 0 635 0 703 35,102 48,241 Tanga 87 2,891 0 26 26 0 325 5,315 8,670 Pangani 94 2,309 21 118 0 0 500 4,085 7,128 Handeni 755 17,509 108 0 0 0 1,389 23,814 43,575 Kilindi 0 5,261 49 0 97 0 632 13,419 19,458 Total 2,253 72,966 284 491 1,668 146 6,735 171,056 255,599 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Lushoto 0.34 20.74 0.00 0.17 0.84 0.17 1.02 76.73 100.00 Korogwe 1.19 37.22 0.25 0.48 0.44 0.00 5.40 55.02 100.00 Muheza 1.06 23.40 0.00 0.00 1.32 0.00 1.46 72.76 100.00 Tanga 1.01 33.34 0.00 0.30 0.30 0.00 3.75 61.30 100.00 Pangani 1.32 32.40 0.30 1.65 0.00 0.00 7.02 57.31 100.00 Handeni 1.73 40.18 0.25 0.00 0.00 0.00 3.19 54.65 100.00 Kilindi 0.00 27.04 0.25 0.00 0.50 0.00 3.25 68.97 100.00 Total 0.88 28.55 0.11 0.19 0.65 0.06 2.64 66.92 100.00 10.2 Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Tanga Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census-2003 Tanga Appendix II 197 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census-2003 Tanga Appendix II 198 Number of Household % Number of Household % Lushoto 15,391 18 71,188 82 86,580 Korogwe 5,673 12 40,317 88 45,990 Muheza 929 2 48,266 98 49,195 Tanga 306 3 8,608 97 8,914 Pangani 129 2 6,998 98 7,128 Handeni 427 1 47,312 99 47,739 Kilindi 482 2 19,172 98 19,654 Total 23,338 9 241,860 91 265,198 District Irrigatable Area (ha) Irrigated Land (ha) % Lushoto 4,819 4,011 83 Korogwe 2,817 2,276 81 Muheza 229 156 68 Tanga 237 181 77 Pangani 150 149 99 Handeni 289 202 70 Kilindi 119 103 87 Total 8,660 7,079 82 River Dam Well Borehole Canal Pipe water Total Lushoto 4,731 718 433 0 9,375 135 15,391 Korogwe 4,539 0 422 0 609 103 5,673 Muheza 354 0 418 79 78 0 929 Tanga 133 56 96 0 0 21 306 Pangani 41 0 36 34 18 0 129 Handeni 108 0 319 0 0 0 427 Kilindi 147 0 240 0 95 0 482 Total 10,052 774 1,965 113 10,176 258 23,338 % 43 3 8 0 44 1 100 Gravity Hand Bucket Hand Pump Motor Pump Other Total Lushoto 8,480 6,911 0 0 0 15,391 Korogwe 4,149 1,334 84 0 106 5,673 Muheza 164 764 0 0 0 929 Tanga 23 248 0 36 0 306 Pangani 18 111 0 0 0 129 Handeni 0 321 0 0 106 427 Kilindi 49 433 0 0 0 482 Total 12,883 10,123 84 36 212 23,338 % 55.2 43.4 0.4 0.2 0.9 100 11.1 IRRIGATION: Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District District Households Practicing Irrigation Households not Practicing Irrigation Total Number of households 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year District Method of Obtaining Water 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.4 IRRIGATION: Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 199 Flood Sprinkler Water Hose Bucket / Watering Can Total Lushoto 7,898 434 0 7,060 15,391 Korogwe 3,941 87 186 1,459 5,673 Muheza 78 0 0 851 929 Tanga 23 0 36 248 306 Pangani 18 0 0 111 129 Handeni 0 0 0 427 427 Kilindi 49 0 0 433 482 Total 12,006 521 222 10,588 23,338 % 51 2 1 45 100 Number % Number % Lushoto 20,308 23 66,271 77 86,580 Korogwe 4,540 10 41,450 90 45,990 Muheza 3,815 8 45,380 92 49,195 Tanga 55 1 8,859 99 8,914 Pangani 33 0 7,095 100 7,128 Handeni 952 2 46,787 98 47,739 Kilindi 585 3 19,069 97 19,654 Total 30,288 11 234,910 89 265,198 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Lushoto 77,536 11,978 0 46,100 24,407 43,906 578 146 204,651 Korogwe 1,825 21,794 2,203 14,657 6,957 1,587 4,112 421 53,555 Muheza 1,654 5,956 919 2,290 1,433 13,571 2,104 . 27,925 Tanga 2,388 227 45 91 205 68 114 45 3,183 Pangani 0 0 0 0 410 0 0 0 410 Handeni 644 321 . . 192 . 3,963 . 5,120 Kilindi 436 2,243 . 245 2,710 925 582 . 7,141 Total 84,481 42,520 3,167 63,382 36,312 60,056 11,453 613 301,985 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year District Type of Erosion Control 11.6 EROSION CONTROL: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District District Presence of Erosion Control/Water Harvesting Facilities Have facility Does Not Have Facility Total Number of households 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year District Method of field Application Tanzania Agriculture Sample Census-2003 Tanga 200 Appendix II 201 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 202 NOT Using Chemical Fertilizer No of households % No of households % Lushoto 5,915 7 80,665 93 86,580 Korogwe 1,388 3 44,602 97 45,990 Muheza 509 1 48,686 99 49,195 Tanga 158 2 8,756 98 8,914 Pangani 0 0 7,086 100 7,086 Handeni 204 0 47,535 100 47,739 Kilindi 49 0 19,605 100 19,654 Total 8,223 3 256,933 97 265,156 No of households % No of households % Lushoto 33,587 39 53,285 61 86,872 Korogwe 8,623 19 37,367 81 45,990 Muheza 5,103 10 44,092 90 49,195 Tanga 1,449 16 7,465 84 8,914 Pangani 275 4 6,963 96 7,238 Handeni 2,238 5 45,501 95 47,739 Kilindi 537 3 19,117 97 19,654 Total 51,812 20 213,789 80 265,601 No of households % No of households % Lushoto 5,932 7 80,647 93 86,580 Korogwe 5,434 12 40,556 88 45,990 Muheza 688 1 48,507 99 49,195 Tanga 442 5 8,471 95 8,914 Pangani 85 1 7,021 99 7,106 Handeni 935 2 46,804 98 47,739 Kilindi 1,063 5 18,590 95 19,654 Total 14,580 5 250,597 95 265,177 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer Total Number of Crop growing households 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 203 No of households % No of households % Lushoto 8,505 10 77,929 90 86,434 Korogwe 2,214 5 43,776 95 45,990 Muheza 469 1 48,725 99 49,195 Tanga 201 2 8,713 98 8,914 Pangani 201 3 6,903 97 7,104 Handeni 2,093 4 45,646 96 47,739 Kilindi 289 1 19,365 99 19,654 Total 13,971 5 251,058 95 265,029 No of households % No of households % Lushoto 721 1 86,150 99 86,871 Korogwe 103 0 45,887 100 45,990 Muheza 0 0 49,195 100 49,195 Tanga 0 0 8,914 100 8,914 Pangani 11 0 7,092 100 7,104 Handeni 0 0 47,739 100 47,739 Kilindi 0 0 19,654 100 19,654 Total 835 0 264,630 100 265,466 No of households % No of households % Lushoto 14,855 17 71,433 83 86,288 Korogwe 8,835 19 37,155 81 45,990 Muheza 1,907 4 47,288 96 49,195 Tanga 1,166 13 7,748 87 8,914 Pangani 737 10 6,391 90 7,128 Handeni 5,183 11 42,556 89 47,739 Kilindi 818 4 18,836 96 19,654 Total 33,500 13 231,407 87 264,907 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticides/Fungicides by District during 2002/03 Agricultural Year District Using Insecticide/Fungicide Not Using Insecticide/Fungicide Total Number of Crop growing households 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 204 Number % Number % Number % Number % Number % Number % Number % Lushoto 146 0 5,623 6 0 0 0 0 146 0 0 0 80,665 93 86,580 Korogwe 107 0 1,175 3 0 0 0 0 0 0 107 0 44,602 97 45,990 Muheza 0 0 352 1 0 0 156 0 0 0 0 0 48,686 99 49,195 Tanga 0 0 135 2 0 0 0 0 0 0 23 0 8,756 98 8,914 Pangani 0 0 0 0 0 0 0 0 0 0 0 0 7,086 100 7,086 Handeni 0 0 108 0 96 0 0 0 0 0 0 0 47,535 100 47,739 Kilindi 0 0 49 0 0 0 0 0 0 0 0 0 19,605 100 19,654 Total 253 0 7,443 3 96 0 156 0 146 0 129 0 256,933 97 265,156 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 582 1 0 0 0 0 0 0 20,335 23 12,524 14 146 0 53,285 61 86,872 Korogwe 103 0 107 0 0 0 0 0 4,456 10 3,957 9 0 0 37,367 81 45,990 Muheza 0 0 91 0 92 0 0 0 2,158 4 2,761 6 0 0 44,092 90 49,195 Tanga 21 0 0 0 18 0 23 0 428 5 926 10 33 0 7,465 84 8,914 Pangani 0 0 0 0 0 0 0 0 110 2 128 2 37 1 6,963 96 7,238 ACCESS TO 106 0 0 0 0 0 0 0 1,169 2 963 2 0 0 45,501 95 47,739 Kilindi 0 0 0 0 0 0 0 0 243 1 293 1 0 0 19,117 97 19,654 Total 812 0 199 0 110 0 23 0 28,900 11 21,552 8 216 0 213,789 80 265,601 Number % Number % Number % Number % Lushoto 146 0 5,202 6 584 1 80,647 93 86,580 Korogwe 0 0 5,125 11 309 1 40,556 88 45,990 Muheza 0 0 688 1 0 0 48,507 99 49,195 Tanga 0 0 442 5 0 0 8,471 95 8,914 Pangani 0 0 41 1 44 1 7,021 99 7,106 Handeni 0 0 935 2 0 0 46,804 98 47,739 Kilindi 0 0 1,063 5 0 0 18,590 95 19,654 Total 146 0 13,497 5 937 0 250,597 95 265,177 Total Total Total 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households by Source of COMPOST Manure and District, 2002/03 Agricultural Year District Co-operative Locally Produced by Household Neighbour Not applicable 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Local Market / Trade Store Secondary Market Development Project Large Scale Farm Locally Produced by Household Neighbour Other Not applicable 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Development Project Large Scale Farm Locally Produced by Household Neighbour Not applicable Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 205 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 146 0 0 0 8,358 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 77,929 90 86,434 Korogwe 0 0 0 0 1,896 4 105 0 107 0 0 0 0 0 105 0 0 0 0 0 43,776 95 45,990 Muheza 0 0 0 0 384 1 0 0 0 0 0 0 0 0 85 0 0 0 0 0 48,725 99 49,195 Tanga 0 0 0 0 201 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8,713 98 8,914 Pangani 21 0 11 0 63 1 0 0 72 1 0 0 22 0 0 0 11 0 0 0 6,903 97 7,104 Handeni 0 0 0 0 1,566 3 0 0 0 0 204 0 106 0 0 0 108 0 108 0 45,646 96 47,739 Kilindi 0 0 0 0 242 1 0 0 0 0 0 0 0 0 0 0 47 0 0 0 19,365 99 19,654 Total 167 0 11 0 12,711 5 105 0 179 0 204 0 128 0 190 0 166 0 108 0 251,058 95 265,029 Number % Number % Number % Lushoto 577 1 144 0 86,150 99 86,871 Korogwe 103 0 0 0 45,887 100 45,990 Muheza 0 0 0 0 49,195 100 49,195 Tanga 0 0 0 0 8,914 100 8,914 Pangani 0 0 11 0 7,092 100 7,104 Handeni 0 0 0 0 47,739 100 47,739 Kilindi 0 0 0 0 19,654 100 19,654 Total 679 0 156 0 264,630 100 265,466 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 292 0 0 0 13,846 16 0 0 0 0 0 0 0 0 430 0 286 0 0 0 71,433 83 86,288 Korogwe 0 0 192 0 5,950 13 0 0 881 2 0 0 0 0 1,217 3 597 1 0 0 37,155 81 45,990 Muheza 0 0 0 0 1,379 3 0 0 0 0 0 0 91 0 171 0 265 1 0 0 47,288 96 49,195 Tanga 0 0 0 0 979 11 21 0 57 1 0 0 0 0 35 0 43 0 31 0 7,748 87 8,914 Pangani 0 0 0 0 581 8 0 0 72 1 0 0 0 0 30 0 54 1 0 0 6,391 90 7,128 Handeni 0 0 0 0 2,416 5 0 0 1,168 2 204 0 212 0 214 0 859 2 108 0 42,556 89 47,739 Kilindi 48 0 0 0 769 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18,836 96 19,654 Total 341 0 192 0 25,921 10 21 0 2,178 1 204 0 303 0 2,097 1 2,104 1 140 0 231,407 87 264,907 Total Other Not applicable Neighbour Other Not applicable 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households by Source of Pesticides/Fungicides and District, 2002/03 Agricultural Year Neighbour 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Total Development Project Crop Buyers Large Scale Farm Total District Local Market / Trade Store Neighbour Not applicable Locally Produced by Household District Co-operative Local Farmers Group Local Market / Trade Store Locally Produced by Household Development Project Crop Buyers Large Scale Farm 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year Secondary Market Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 206 Number % Number % Number % Number % Number % Lushoto 1,297 22 1,443 24 3,029 51 145 2 0 0 5,915 Korogwe 107 8 779 56 0 0 101 7 401 29 1,388 Muheza 78 15 169 33 79 15 0 0 183 36 509 Tanga 10 6 0 0 93 59 55 35 0 0 158 Handeni 96 47 0 0 0 0 0 0 108 53 204 Kilindi 0 0 0 0 0 0 0 0 49 100 49 Total 1,587 19 2,392 29 3,201 39 302 4 741 9 8,223 Number % Number % Number % Number % Lushoto 31,565 94 1,735 5 143 0 144 0 33,587 Korogwe 7,930 92 492 6 202 2 0 0 8,623 Muheza 4,511 88 500 10 91 2 0 0 5,103 Tanga 1,114 77 264 18 62 4 8 1 1,449 Pangani 275 100 0 0 0 0 0 0 275 Handeni 1,707 76 531 24 0 0 0 0 2,238 Kilindi 390 73 147 27 0 0 0 0 537 Total 47,492 92 3,668 7 498 1 153 0 51,812 Between 10 and 20 km Total Number 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 207 Number % Number % Lushoto 5,932 100 0 0 5,932 Korogwe 5,237 96 197 4 5,434 Muheza 598 87 90 13 688 Tanga 409 92 33 8 442 Pangani 85 100 0 0 85 Handeni 935 100 0 0 935 Kilindi 1,063 100 0 0 1,063 Total 14,259 98 321 2 14,580 Number % Number % Number % Number % Number % Lushoto 5,481 37 4,178 28 4,473 30 291 2 431 3 14,855 Korogwe 2,626 30 1,300 15 1,201 14 2,383 27 1,325 15 8,835 Muheza 556 29 92 5 160 8 398 21 701 37 1,907 Tanga 154 13 53 5 569 49 234 20 156 13 1,166 Pangani 113 15 0 0 67 9 108 15 448 61 737 Handeni 846 16 1,269 24 743 14 638 12 1,687 33 5,183 Kilindi 238 29 47 6 49 6 144 18 341 42 818 Total 10,013 30 6,939 21 7,263 22 4,197 13 5,088 15 33,500 Number % Number % Number % Number % Number % Number % Lushoto 2021 24 2731 32 3169 37 437 5 146 2 8505 100 Korogwe 0 0 364 16 522 24 713 32 615 28 2214 100 Muheza 0 0 85 18 0 0 0 0 384 82 469 100 Tanga 0 0 0 0 104 52 66 33 31 16 201 100 Pangani 82 41 0 0 11 6 0 0 108 54 201 100 Handeni 321 15 210 10 430 21 0 0 1132 54 2093 100 Kilindi 142 49 0 0 0 0 49 17 98 34 289 100 Total 2565 18 3389 24 4236 30 1265 9 2515 18 13971 100 District Less than 1 km Between 1 and 3 km Total Number 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 208 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 4,053 5 70,581 87 4,580 6 0 0 583 1 726 1 0 0 142 0 80,665 Korogwe 4,222 9 33,146 74 825 2 305 1 1,229 3 3,851 9 0 0 1,024 2 44,602 Muheza 3,853 8 34,042 70 617 1 0 0 2,464 5 7,448 15 0 0 262 1 48,686 Tanga 543 6 5,867 67 47 1 0 0 656 7 1,564 18 45 1 33 0 8,756 Pangani 1,678 24 3,706 52 289 4 0 0 199 3 1,192 17 0 0 22 0 7,086 Handeni 9,209 19 19,831 42 428 1 0 0 6,849 14 10,358 22 0 0 860 2 47,535 Kilindi 6,388 33 4,581 23 95 0 0 0 775 4 7,523 38 0 0 243 1 19,605 Total 29,946 12 171,754 67 6,880 3 305 0 12,756 5 32,663 13 45 0 2,586 1 256,933 Number % Number % Number % Number % Number % Number % Number % Lushoto 5,555 10 9,733 18 28,458 53 7,676 14 711 1 1,151 2 0 0 53,285 Korogwe 3,023 8 2,953 8 25,114 67 1,865 5 1,114 3 2,374 6 924 2 37,367 Muheza 10,410 24 1,484 3 22,556 51 3,370 8 1,794 4 4,298 10 180 0 44,092 Tanga 2,441 33 323 4 2,646 35 739 10 270 4 1,013 14 32 0 7,465 Pangani 2,525 36 2,020 29 1,494 21 381 5 131 2 366 5 46 1 6,963 Handeni 5,880 13 1,165 3 25,498 56 935 2 3,147 7 8,230 18 647 1 45,501 Kilindi 2,629 14 2,245 12 5,989 31 98 1 1,119 6 6,795 36 243 1 19,117 Total 32,464 15 19,922 9 111,756 52 15,063 7 8,286 4 24,228 11 2,071 1 213,789 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 6,831 8 13,925 17 39,102 48 9,281 12 5,020 6 6,488 8 0 0 0 0 80,647 Korogwe 1,785 4 3,676 9 25,266 62 2,198 5 3,390 8 3,422 8 0 0 820 2 40,556 Muheza 1,804 4 1,248 3 24,437 50 5,196 11 10,654 22 4,282 9 268 1 618 1 48,507 Tanga 1,006 12 378 4 3,398 40 213 3 2,151 25 1,163 14 0 0 163 2 8,471 Pangani 553 8 2,043 29 2,315 33 396 6 1,232 18 328 5 0 0 154 2 7,021 Handeni 3,087 7 1,912 4 19,665 42 520 1 13,602 29 7,267 16 106 0 647 1 46,804 Kilindi 1,216 7 2,583 14 4,869 26 195 1 2,782 15 6,360 34 245 1 340 2 18,590 Total 16,282 6 25,764 10 119,052 48 17,999 7 38,831 15 29,310 12 618 0 2,741 1 250,597 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 209 Number % Number % Number % Number % Number % Number % Number % Lushoto 1,599 2 72,257 93 584 1 146 0 1,162 1 2,182 3 0 0 77,929 Korogwe 2,975 7 32,004 73 1,047 2 300 1 2,170 5 4,568 10 712 2 43,776 Muheza 2,417 5 34,766 71 403 1 0 0 2,713 6 8,072 17 355 1 48,725 Tanga 306 4 5,308 61 92 1 21 0 1,216 14 1,707 20 63 1 8,713 Pangani 1,105 16 4,812 70 369 5 36 1 257 4 259 4 65 1 6,903 Handeni 3,805 8 25,653 56 205 0 108 0 11,384 25 3,950 9 541 1 45,646 Kilindi 4,243 22 9,480 49 290 1 0 0 1,021 5 4,039 21 291 2 19,365 Total 16,449 7 184,281 73 2,990 1 611 0 19,923 8 24,777 10 2,027 1 251,058 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 5,101 6 66,833 78 728 1 0 0 3,930 5 9,558 11 0 0 0 0 86,150 Korogwe 3,607 8 33,365 73 419 1 302 1 3,173 7 3,680 8 107 0 1,234 3 45,887 Muheza 1,522 3 34,018 69 407 1 0 0 4,969 10 7,927 16 0 0 351 1 49,195 Tanga 336 4 4,507 51 66 1 24 0 2,402 27 1,517 17 0 0 63 1 8,914 Pangani 1,134 16 4,790 68 411 6 0 0 373 5 361 5 0 0 22 0 7,092 Handeni 5,261 11 23,281 49 309 1 0 0 12,776 27 5,466 11 0 0 647 1 47,739 Kilindi 4,535 23 8,747 45 387 2 0 0 1,116 6 4,625 24 0 0 243 1 19,654 Total 21,496 8 175,541 66 2,727 1 327 0 28,740 11 33,132 13 107 0 2,560 1 264,630 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 2,744 4 68,105 95 146 0 0 0 292 0 146 0 0 0 0 0 71,433 Korogwe 2,024 5 31,981 86 522 1 195 1 613 2 693 2 107 0 1,020 3 37,155 Muheza 5,726 12 38,231 81 404 1 0 0 356 1 1,920 4 357 1 250 1 47,245 Tanga 1,282 17 5,446 70 18 0 0 0 181 2 676 9 45 1 100 1 7,748 Pangani 1,640 26 4,263 67 356 6 0 0 23 0 87 1 0 0 22 0 6,391 Handeni 6,653 16 31,820 75 0 0 105 0 1,714 4 1,616 4 108 0 540 1 42,556 Kilindi 5,987 32 9,059 48 341 2 48 0 436 2 2,625 14 49 0 291 2 18,836 Total 26,054 11 188,905 82 1,787 1 349 0 3,617 2 7,762 3 667 0 2,223 1 231,364 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Other Total Too Much Labour Required Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 210 Number % Number % Number % Number % Lushoto 1,019 17 3,616 61 1,139 19 140 2 5,915 Korogwe 879 63 316 23 193 14 0 0 1,388 Muheza 157 31 261 51 91 18 0 0 509 Tanga 41 26 63 40 54 34 0 0 158 Handeni 108 53 96 47 0 0 0 0 204 Kilindi 0 0 49 100 0 0 0 0 49 Total 2,205 27 4,400 54 1,478 18 140 2 8,223 Number % Number % Number % Number % Lushoto 6,246 19 23,720 71 3,622 11 0 0 33,587 Korogwe 1,957 23 5,956 69 710 8 0 0 8,623 Muheza 2,151 42 2,260 44 691 14 0 0 5,103 Tanga 368 25 924 64 128 9 29 2 1,449 Pangani 104 38 159 58 11 4 0 0 275 Handeni 216 8 2,135 83 213 8 0 0 2,564 Kilindi 98 18 439 82 0 0 0 0 537 Total 11,140 21 35,593 68 5,375 10 29 0 52,137 Number % Number % Number % Number % Lushoto 859 14 4,791 81 142 2 140 2 5,932 Korogwe 835 15 4,296 79 304 6 0 0 5,434 Muheza 173 25 254 37 260 38 0 0 688 Tanga 129 29 280 63 33 7 0 0 442 Pangani 18 22 67 78 0 0 0 0 85 Handeni 105 11 734 78 96 10 0 0 935 Kilindi 243 23 774 73 47 4 0 0 1,063 Total 2,363 16 11,195 77 881 6 140 1 14,580 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Excellent Good Average Poor 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 211 Number % Number % Number % Number % Lushoto 1,452 17 5,185 61 1,727 20 140 2 8,505 Korogwe 382 17 1,536 69 190 9 106 5 2,214 Muheza 235 50 235 50 0 0 0 0 469 Tanga 32 16 136 68 32 16 0 0 201 Pangani 21 11 180 89 0 0 0 0 201 Handeni 0 0 1,709 82 383 18 0 0 2,093 Kilindi 98 34 191 66 0 0 0 0 289 Total 2,220 16 9,171 66 2,332 17 247 2 13,971 Number % Lushoto 721 100 721 Korogwe 103 100 103 Pangani 11 100 11 Total 835 100 835 Total Number % Number % Number % Number % Number % Number % Number % Lushoto 2,478 17 10,523 71 1,854 12 0 0 0 0 14,855 Lushoto 19,382 22 67,197 78 86,580 Korogwe 2,248 25 5,651 64 723 8 107 1 106 1 8,835 Korogwe 10,738 23 35,252 77 45,990 Muheza 778 41 1,069 56 59 3 0 0 0 0 1,907 Muheza 1,804 4 47,391 96 49,195 Tanga 422 36 694 60 49 4 0 0 0 0 1,166 Tanga 717 8 8,197 92 8,914 Pangani 118 16 573 78 22 3 23 3 0 0 737 Pangani 474 7 6,611 93 7,086 Handeni 638 12 4,332 79 432 8 107 2 0 0 5,508 Handeni 1,912 4 45,827 96 47,739 Kilindi 244 30 525 64 49 6 0 0 0 0 818 Kilindi 633 3 19,020 97 19,654 Total 6,925 20 23,369 69 3,188 9 237 1 106 0 33,825 Total 35,660 13 229,496 87 265,156 District Excellent Good Average District Good Total 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Does not Work Total Number Total Poor District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizers Next Year by District, 2002/03 Agricultural Year 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 212 District Number % Number % Number % Number % Lushoto 52,735 61 34,136 39 86,872 Lushoto 18,205 21 68,374 79 86,580 Korogwe 25,606 56 20,384 44 45,990 Korogwe 16,446 36 29,544 64 45,990 Muheza 10,943 22 38,251 78 49,195 Muheza 3,869 8 45,325 92 49,195 Tanga 3,675 41 5,239 59 8,914 Tanga 1,716 19 7,198 81 8,914 Pangani 820 11 6,418 89 7,238 Pangani 589 8 6,517 92 7,106 Handeni 14,829 31 32,910 69 47,739 Handeni 4,126 9 43,613 91 47,739 Kilindi 3,753 19 15,900 81 19,654 Kilindi 3,157 16 16,497 84 19,654 Total 112,362 42 153,239 58 265,601 Total 48,108 18 217,069 82 265,177 District Total Number Number % Number % Number % Number % Lushoto 16,325 19 70,109 81 86,434 Lushoto 3,455 4 83,416 96 86,871 Korogwe 12,094 26 33,896 74 45,990 Korogwe 5,668 12 40,322 88 45,990 Muheza 2,918 6 46,277 94 49,195 Muheza 916 2 48,278 98 49,195 Tanga 1,110 12 7,804 88 8,914 Tanga 267 3 8,646 97 8,914 Pangani 1,023 14 6,081 86 7,104 Pangani 318 4 6,785 96 7,104 Handeni 6,690 14 41,048 86 47,739 Handeni 3,729 8 44,010 92 47,739 Kilindi 3,704 19 15,950 81 19,654 Kilindi 1,751 9 17,903 91 19,654 Total 43,864 17 221,165 83 265,029 Total 16,104 6 249,361 94 265,466 Number % Number % Lushoto 28,186 33 58,103 67 86,288 Korogwe 25,581 56 20,409 44 45,990 Muheza 14,687 30 34,507 70 49,195 Tanga 3,657 41 5,257 59 8,914 Pangani 1,733 24 5,395 76 7,128 Handeni 18,984 40 28,755 60 47,739 Kilindi 7,961 41 11,693 59 19,654 Total 100,788 38 164,118 62 264,907 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households with Plan to use Improved Seeds next year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Pesticides/Fungicides Next Year by District, 2002/03 Agricultural Year 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Total District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 213 AGRICULTURE CREDIT Tanzania Agriculture Sample Census-2003 Tanga Appendix II 214 Number % Number % Lushoto 0 0 404 100 404 Korogwe 107 100 0 0 107 Muheza 78 32 165 68 243 Tanga 61 100 0 0 61 Handeni 208 100 0 0 208 Total 453 44 569 56 1,022 % 44 56 District Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Lushoto 135 0 0 0 270 0 404 Korogwe 0 0 0 0 0 107 107 Muheza 79 0 0 78 86 0 243 Tanga 0 35 0 0 26 0 61 Handeni 0 0 208 0 0 0 208 Total 213 35 208 78 382 107 1,022 % 21 3 20 8 37 10 100 13.2a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year District Male Female Total 13.2c AGRICULTURE CREDIT: Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 215 District Did not know how to get credit Don't know about credit Not available Did not want to go into debt Difficult bureaucracy procedure Not needed Interest rate/cost too high Credit granted too late Other Total Lushoto 54,575 13,490 12,226 3,326 1,156 291 975 135 0 86,175 Korogwe 26,004 11,093 2,914 2,459 1,161 603 1,275 281 94 45,883 Muheza 27,538 7,663 2,894 5,247 3,511 1,298 721 80 0 48,952 Tanga 4,076 1,293 689 1,459 500 418 265 32 121 8,853 Pangani 2,994 1,803 527 424 650 190 356 0 183 7,128 Handeni 26,688 10,207 4,021 2,336 2,299 1,253 409 107 212 47,531 Kilindi 9,591 4,671 4,031 536 193 436 97 49 49 19,654 Total 151,467 50,220 27,302 15,787 9,470 4,490 4,097 684 659 264,176 District Total Credits Other Labour Fertilizers Seeds Tools / Equipment Irrigation Structures Agro- chemicals Livestock Lushoto 404 404 0 0 0 0 0 0 0 Korogwe 533 0 0 107 107 107 107 107 0 Muheza 400 0 79 157 79 0 0 0 86 Tanga 61 0 61 0 0 0 0 0 0 Handeni 208 0 208 0 0 0 0 0 0 Total Credits 1,606 404 347 263 185 107 107 107 86 13.1b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga 216 Appendix II 217 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census-2003 Tanga Appendix II 218 Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp 430,520 983 51,640 72,130 1,156 19,121 10,639 8,516 5,014 2,808 157,977 . 37,210 . 4,080 . . . 872 1,612 58,367 311,076 2,758 . 25,285 . . . . . . . . . 296 . . . . . 361 1,511 . . 290 . . . . . 424 . . . 1,060 . . . . . 587 . 147 . . . . . 196 . 648,235 313,570 91,754 72,130 32,166 19,121 10,639 8,516 6,082 4,420 3 53 2 7 6 0 26 0 0 0 Leucena Spp Azadritachta Spp Terminalia Catapa Terminalia Ivorensis Saraca Spp Sesbania Spp Jakaranda Spp Syszygium Spp Total . . . . . . 584 . . 603,112 . . 2,270 2,000 1,301 . . 206 194 207,720 4,052 . 504 336 . 734 . . . 403,112 . . . . . . . . . 296 . 447 576 . . . . 45 . 3,229 . . . . . 531 . . . 2,014 . 3,200 . 147 . . . . 49 4,326 4,052 3,646 3,350 2,483 1,301 1,265 584 251 243 1,223,809 0 0 0 1 0 0 0 0 1 100 cont…. ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 219 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Lushoto 10,157 277,992 4,338 227,967 1,597 89,302 16,093 595,261 Korogwe 3,269 36,615 1,698 61,283 310 109,625 5,277 207,523 Muheza 3,878 163,425 1,495 133,151 529 106,536 5,902 403,112 Tanga 77 296 0 . 0 . 77 296 Pangani 121 1,900 22 1,328 0 . 143 3,229 Handeni 318 1,271 106 743 0 . 424 2,014 Kilindi 98 587 97 3,200 0 . 195 3,787 Total 17,917 482,086 7,757 427,672 2,436 305,464 28,110 1,215,222 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Lushoto 8,931 1,148 9,152 1,595 144 0 20,971 Korogwe 3,685 425 845 945 0 504 6,403 Muheza 3,305 2,002 424 834 0 87 6,653 Tanga 0 0 0 77 0 0 77 Pangani 40 112 0 101 0 46 299 Handeni 106 0 106 318 0 0 530 Kilindi 147 98 0 0 49 97 391 Total 16,214 3,785 10,527 3,870 193 735 35,324 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region District Main Use 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Tanga Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 220 1-9 10-19 20-29 30-39 40-49 Above 50 Total Lushoto 10,235 3,878 3,905 1,746 0 146 19,909 Korogwe 854 522 736 852 213 103 3,279 Muheza 81 0 1,183 79 0 0 1,343 Tanga 458 0 0 0 0 0 458 Pangani 59 0 0 0 0 0 59 Handeni 0 0 485 862 192 0 1,539 Kilindi 0 97 0 0 0 390 487 Total 11,687 4,497 6,309 3,539 405 638 27,073 % 43 17 23 13 1 2 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Lushoto 6,154 3,008 0 10,678 1,277 0 0 21,117 Korogwe 535 814 0 4,222 531 203 97 6,403 Muheza 601 1,079 90 4,375 253 84 260 6,742 Tanga 0 77 0 0 0 0 0 77 Pangani 0 0 0 176 22 78 0 277 Handeni 0 106 0 318 106 0 0 530 Kilindi 98 0 0 49 196 48 0 391 Total 7,388 5,084 90 19,818 2,384 414 357 35,536 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Tanga Region District Distance to Community Planted Forest (km) District Second Use 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 221 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total 8,931 1,148 9,152 1,595 144 0 20,971 3,685 425 845 945 0 504 6,403 3,305 2,002 424 834 0 87 6,653 0 0 0 77 0 0 77 40 112 0 101 0 46 299 106 0 106 318 0 0 530 147 98 0 0 49 97 391 16,214 3,785 10,527 3,870 193 735 35,324 14 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region Main Use Tanzania Agriculture Sample Census-2003 Tanga 222 Appendix II Tanzania Agriculture Sample Census – 2003 Tanga 223 CROP EXTENSION Appendix II 224 Number % Number % Lushoto 42,132 49 44,448 51 86,580 Korogwe 38,500 84 7,490 16 45,990 Muheza 21,091 43 28,103 57 49,195 Tanga 1,266 14 7,648 86 8,914 Pangani 2,807 39 4,321 61 7,128 Handeni 10,334 22 37,405 78 47,739 Kilindi 5,356 27 14,298 73 19,654 Total 121,487 46 143,711 54 265,198 Total Number % Number % Number % Number % Number % Number Lushoto 3,038 7 23,310 55 14,941 35 140 0 702 2 42,132 Korogwe 4,187 11 26,875 70 6,943 18 495 1 0 0 38,500 Muheza 2,093 10 13,998 66 3,703 18 406 2 892 4 21,091 Tanga 63 5 841 66 234 18 127 10 0 0 1,266 Pangani 54 1,141 41 35 1 0 0 2,807 Handeni 538 5 5,684 55 3,909 38 203 2 0 0 10,334 Kilindi 194 4 3,647 68 1,417 26 98 2 0 0 5,356 Total 10,217 8 75,884 62 32,287 27 1,505 1 1,594 1 121,487 Total Number % Number % Number % Number % Number % Number % Number Lushoto 42,132 100 0 0 0 0 0 0 0 0 0 0 42,132 Korogwe 37,886 99 321 1 0 0 104 0 0 0 97 0 38,407 Pangani 104 4 1,527 0 0 0 0 0 0 0 89 0 21,001 Tanga 1,194 94 10 1 0 0 21 2 10 1 32 3 1,266 Pangani 2,677 96 18 1 0 0 24 1 22 1 47 2 2,788 Handeni 9,624 94 0 0 107 1 284 3 215 2 0 0 10,231 Kilindi 5,258 98 0 0 0 0 0 0 49 1 49 1 5,356 Total 119,592 99 438 0 107 0 433 0 296 0 313 0 121,180 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Tanga Region District Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Tanga Region District Good No Good 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Tanga Region District Government NGO / Development Project Cooperative Large Scale Farm Other Not Very Good Average Poor Tanzania Agriculture Sample Census-2003 Tanga Appendix II 225 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Lushoto 41,406 0 0 0 0 0 41,406 86,580 48 Korogwe 37,461 321 0 0 0 97 37,878 45,990 82 Muheza 20,606 0 0 0 0 89 20,695 49,195 42 Tanga 1,148 0 0 21 0 32 1,201 8,914 13 Pangani 2,538 18 0 24 22 47 2,649 7,128 37 Handeni 9,520 0 107 284 215 0 10,127 47,739 21 Kilindi 5,160 0 0 0 49 49 5,258 19,654 27 Total 117,838 339 107 329 287 313 119,213 265,198 45 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 31,324 2,439 145 0 432 34,340 86,580 39.7 Korogwe 19,453 720 0 107 307 20,587 45,990 44.8 Muheza 9,849 630 0 0 214 10,693 49,195 21.7 Tanga 340 0 0 0 323 663 8,914 7.4 Pangani 665 142 0 0 95 901 7,128 12.6 Handeni 1,574 217 0 0 2,253 4,044 47,739 8.5 Kilindi 926 49 0 0 489 1,464 19,654 7.5 Total 64,130 4,197 145 107 4,113 72,692 265,198 27.4 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Tanga Region District Spacing 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 226 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 23,282 146 0 146 2,171 25,745 86,580 29.7 Korogwe 12,384 194 0 107 1,918 14,602 45,990 31.8 Muheza 7,325 0 0 0 986 8,311 49,195 16.9 Tanga 246 0 21 0 381 647 8,914 7.3 Pangani 862 0 0 0 164 1,027 7,128 14.4 Handeni 1,033 217 0 0 2,559 3,809 47,739 8.0 Kilindi 586 0 0 0 637 1,222 19,654 6.2 Total 45,718 557 21 253 8,815 55,363 265,198 20.9 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Organic Fertilizer Use 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Tanga Region District Inorganic Fertilizer Use 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seeds Tanzania Agriculture Sample Census-2003 Tanga Appendix II 227 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 3,304 0 0 146 1,441 4,891 86,580 6 Korogwe 8,660 107 0 107 1,225 10,098 45,990 22 Muheza 1,972 0 0 0 215 2,187 49,195 4 Tanga 338 0 23 0 321 681 8,914 8 Pangani 494 65 24 0 167 750 7,128 11 Handeni 3,331 108 188 0 2,351 5,979 47,739 13 Kilindi 975 0 0 49 832 1,857 19,654 9 Total 19,073 280 235 302 6,552 26,443 265,198 10 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 25,905 708 436 27,049 86,580 31 Korogwe 17,626 506 1,227 19,360 45,990 42 Muheza 4,716 0 584 5,300 49,195 11 Tanga 250 0 350 600 8,914 7 Pangani 254 72 164 490 7,128 7 Handeni 1,055 0 2,350 3,405 47,739 7 Kilindi 534 49 734 1,317 19,654 7 Total 50,340 1,335 5,846 57,521 265,198 22 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 39,553 0 0 144 146 39,844 86,580 46.0 Korogwe 28,076 210 204 0 495 28,986 45,990 63.0 Muheza 15,724 59 0 0 322 16,106 49,195 32.7 Tanga 607 0 0 0 248 855 8,914 9.6 Pangani 1,789 73 0 0 143 2,004 7,128 28.1 Handeni 6,176 213 0 107 971 7,467 47,739 15.6 Kilindi 3,364 146 49 49 146 3,755 19,654 19.1 Total 95,290 701 253 301 2,472 99,017 265,198 37.3 District Crop Storage 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Tanga Region. 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Tanga Region District Mechanisation / LST District Irrigation Technology 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 228 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Lushoto 36,643 140 0 0 581 37,364 86,580 43.2 Korogwe 19,470 84 107 0 599 20,260 45,990 44.1 Muheza 8,033 183 0 0 213 8,429 49,195 17.1 Tanga 254 0 0 0 445 699 8,914 7.8 Pangani 499 177 0 0 143 818 7,128 11.5 Handeni 1,353 0 0 643 2,125 4,121 47,739 8.6 Kilindi 2,590 0 0 0 49 2,639 19,654 13.4 Total 68,840 584 107 643 4,156 74,331 265,198 28.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Vermin Control 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Tanga Region District Agro-progressing Total Number of households % of total number of households 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga Region District Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 229 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 3,025 710 859 4,594 86,580 5.3 Korogwe 2,031 958 1,017 4,007 45,990 8.7 Muheza 927 0 59 986 49,195 2.0 Tanga 36 0 404 440 8,914 4.9 Pangani 162 48 167 377 7,128 5.3 Handeni 212 316 2,774 3,302 47,739 6.9 Kilindi 293 48 783 1,125 19,654 5.7 Total 6,685 2,082 6,064 14,831 265,198 6 % 12,337 3,841 11,190 27,368 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 2,877 713 0 0 433 4,022 86,580 4.6 Korogwe 2,478 1,384 0 0 1,124 4,986 45,990 10.8 Muheza 1,843 720 59 78 0 2,701 49,195 5.5 Tanga 0 0 0 0 440 440 8,914 4.9 Pangani 0 48 0 0 191 239 7,128 3.4 Handeni 106 418 0 0 2,672 3,196 47,739 6.7 Kilindi 97 0 0 0 734 832 19,654 4.2 Total 7,400 3,284 59 78 5,594 16,415 265,198 6.2 Received Adopted % Received Adopted % Received Adopted % Lushoto 41,407 38,827 94 26,611 5,749 22 33,324 11,795 35 Korogwe 37,795 36,111 96 14,048 1,391 10 20,486 4,442 22 Muheza 20,695 16,121 78 7,189 824 11 10,493 4,477 43 Tanga 1,169 1,061 91 565 213 38 308 153 50 Pangani 2,625 2,533 97 1,626 637 39 764 372 49 Handeni 10,231 9,919 97 2,925 812 28 1,477 427 29 Kilindi 5,209 4,476 86 2,193 191 9 1,073 293 27 Total 119,130 109,047 92 55,156 9,817 18 67,925 21,958 32 District 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Tanga Region Beekeeping District District Spacing Use of Agrochemicals 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tanga Region Fish Farming Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 230 Received Adopted % Received Adopted % Received Adopted % Lushoto 39,095 20,744 53 23,283 4,031 17 36,633 12,112 33 Korogwe 30,635 9,858 32 11,666 1,073 9 30,299 8,881 29 Muheza 13,699 4,629 34 7,145 553 8 16,716 2,664 16 Tanga 839 494 59 168 51 30 892 447 50 Pangani 1,459 529 36 884 172 19 1,941 1,065 55 Handeni 4,923 1,270 26 625 213 34 8,085 3,666 45 Kilindi 1,661 341 21 537 195 36 3,553 726 20 Total 92,312 37,865 41 44,307 6,288 14 98,120 29,562 30 Received Adopted % Received Adopted % Received Adopted % Lushoto 1,713 714 42 25,453 9,346 37 39,697 37,242 94 Korogwe 8,438 793 9 16,525 4,665 28 28,757 20,086 70 Muheza 1,876 85 5 4,165 585 14 15,888 10,513 66 Tanga 291 32 11 240 51 21 607 528 87 Pangani 583 176 30 254 145 57 1,909 1,697 89 Handeni 3,419 511 15 851 428 50 6,500 4,500 69 Kilindi 1,024 97 9 485 193 40 3,804 2,436 64 Total 17,344 2,408 14 47,974 15,413 32 97,163 77,002 79 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tanga Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tanga region District Mechanisation / LST Irrigation Technology Crop Storage District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Sample Census-2003 Tanga Appendix II 231 Received Adopted % Received Adopted % Received Adopted % Lushoto 7,975 5,521 69 36,200 34,752 96 28,547 15,683 55 Korogwe 27,020 22,813 84 19,441 16,567 85 13,222 2,949 22 Muheza 11,855 9,030 76 8,370 6,197 74 6,810 3,120 46 Tanga 801 685 86 254 297 117 274 241 88 Pangani 2,031 1,843 91 652 520 80 534 470 88 Handeni 3,300 3,086 94 1,357 1,678 124 3,231 1,252 39 Kilindi 2,735 2,540 93 2,639 2,493 94 1,317 195 15 Total 55,716 45,519 82 68,912 62,505 91 53,935 23,909 44 Received Adopted % Received Adopted % Received Adopted % Lushoto 28,547 15,683 55 2,282 718 31 2,131 0 0 Korogwe 13,222 2,949 22 2,354 178 8 3,336 531 16 Muheza 6,810 3,120 46 596 0 0 2,530 449 18 Tanga 274 241 88 36 0 0 0 0 0 Pangani 534 470 88 138 162 117 0 0 0 Handeni 3,231 1,252 39 102 0 0 204 104 51 Kilindi 1,317 195 15 341 147 43 97 0 0 Total 53,935 23,909 44 5,849 1,205 21 8,297 1,085 13 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Agro-progressing Agro-forestry 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Tanga region District Agro-forestry Beekeeping Fish Farming Tanzania Agriculture Sample Census-2003 Tanga Appendix II 232 Number % Number % Number % Number % Number % Lushoto 3,038 7 23,310 55 14,941 35 140 0 702 2 Korogwe 4,187 11 26,875 70 6,943 18 495 1 0 0 Muheza 2,093 10 13,998 66 3,703 18 406 2 892 4 Tanga 63 5 841 66 234 18 127 10 0 0 Pangani 104 4 1,527 54 1,141 41 35 1 0 0 Handeni 538 5 5,684 55 3,909 38 203 2 0 0 Kilindi 194 4 3,647 68 1,417 26 98 2 0 0 Total 10,217 8 75,884 62 32,287 27 1,505 1 1,594 1 Total Number % Number % Number % Number % Number % % Number Lushoto 42,132 100 0 0 0 0 0 0 0 0 0 42,132 Korogwe 37,886 99 321 1 0 0 104 0 0 0 0 38,407 Muheza 20,822 99 90 0 0 0 0 0 0 0 0 21,001 Tanga 1,194 94 10 1 0 0 21 2 10 1 3 1,266 Pangani 2,677 96 18 1 0 0 24 1 22 1 2 2,788 Handeni 9,624 94 0 0 107 1 284 3 215 2 0 10,231 Kilindi 5,258 98 0 0 0 0 0 0 49 1 1 5,356 Total 119,592 99 438 0 107 0 433 0 296 0 0 121,180 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During th 2002/03 Agriculture Year, Tanga Region District Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable 15.1 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Tanga Region District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 233 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Lushoto 41,406 0 0 0 0 0 41,406 86,580 48 Korogwe 37,461 321 0 0 0 97 37,878 45,990 82 Muheza 20,606 0 0 0 0 89 20,695 49,195 42 Tanga 1,148 0 0 21 0 32 1,201 8,914 13 Pangani 2,538 18 0 24 22 47 2,649 7,128 37 Handeni 9,520 0 107 284 215 0 10,127 47,739 21 Kilindi 5,160 0 0 0 49 49 5,258 19,654 27 Total 117,838 339 107 329 287 313 119,213 265,198 45 % 99 0 0 0 0 0 100 Government NGO / Development Project Large Scale Farm Other Not applica ble Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 % 91.8 1.1 0.0 0.2 6.9 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Tanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals District Spacing Tanzania Agriculture Sample Census-2003 Tanga Appendix II 234 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 31,324 2,439 145 0 432 34,340 86,580 39.7 Korogwe 19,453 720 0 107 307 20,587 45,990 44.8 Muheza 9,849 630 0 0 214 10,693 49,195 21.7 Tanga 340 0 0 0 323 663 8,914 7.4 Pangani 665 142 0 0 95 901 7,128 12.6 Handeni 1,574 217 0 0 2,253 4,044 47,739 8.5 Kilindi 926 49 0 0 489 1,464 19,654 7.5 Total 64,130 4,197 145 107 4,113 72,692 265,198 27.4 % 88.2 5.8 0.2 0.1 5.7 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 % 93.8 2.3 0.2 0.1 3.6 100.0 Erosion Control 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Organic Fertilizer Use 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 235 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 23,282 146 0 146 2,171 25,745 86,580 29.7 Korogwe 12,384 194 0 107 1,918 14,602 45,990 31.8 Muheza 7,325 0 0 0 986 8,311 49,195 16.9 Tanga 246 0 21 0 381 647 8,914 7.3 Pangani 862 0 0 0 164 1,027 7,128 14.4 Handeni 1,033 217 0 0 2,559 3,809 47,739 8.0 Kilindi 586 0 0 0 637 1,222 19,654 6.2 Total 45,718 557 21 253 8,815 55,363 265,198 20.9 % Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 District Use of Improved Seeds 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Tanga Region District Inorganic Fertilizer Use 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 236 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 3,304 0 0 146 1,441 4,891 86,580 6 Korogwe 8,660 107 0 107 1,225 10,098 45,990 22 Muheza 1,972 0 0 0 215 2,187 49,195 4 Tanga 338 0 23 0 321 681 8,914 8 Pangani 494 65 24 0 167 750 7,128 11 Handeni 3,331 108 188 0 2,351 5,979 47,739 13 Kilindi 975 0 0 49 832 1,857 19,654 9 Total 19,073 280 235 302 6,552 26,443 265,198 10 % 72 1 1 1 25 100 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 25,905 708 436 27,049 86,580 31 Korogwe 17,626 506 1,227 19,360 45,990 42 Muheza 4,716 0 584 5,300 49,195 11 Tanga 250 0 350 600 8,914 7 Pangani 254 72 164 490 7,128 7 Handeni 1,055 0 2,350 3,405 47,739 7 Kilindi 534 49 734 1,317 19,654 7 Total 50,340 1,335 5,846 57,521 265,198 22 % 88 2 10 100 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Tanga Region District Irrigation Technology District Mechanisation / LST 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 237 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 39,553 0 0 144 146 39,844 86,580 46.0 Korogwe 28,076 210 204 0 495 28,986 45,990 63.0 Muheza 15,724 59 0 0 322 16,106 49,195 32.7 Tanga 607 0 0 0 248 855 8,914 9.6 Pangani 1,789 73 0 0 143 2,004 7,128 28.1 Handeni 6,176 213 0 107 971 7,467 47,739 15.6 Kilindi 3,364 146 49 49 146 3,755 19,654 19.1 Total 95,290 701 253 301 2,472 99,017 265,198 37.3 % 96.2 0.7 0.3 0.3 2.5 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 District Crop Storage 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Tanga Region. District Vermin Control 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 238 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,643 140 0 0 581 37,364 86,580 43.2 Korogwe 19,470 84 107 0 599 20,260 45,990 44.1 Muheza 8,033 183 0 0 213 8,429 49,195 17.1 Tanga 254 0 0 0 445 699 8,914 7.8 Pangani 499 177 0 0 143 818 7,128 11.5 Handeni 1,353 0 0 643 2,125 4,121 47,739 8.6 Kilindi 2,590 0 0 0 49 2,639 19,654 13.4 Total 68,840 584 107 643 4,156 74,331 265,198 28.0 % 92.6 0.8 0.1 0.9 5.6 100.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 Agro-progressing Agro-forestry 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Tanga Region District 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga region District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 239 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 3,025 710 859 4,594 86,580 5.3 Korogwe 2,031 958 1,017 4,007 45,990 8.7 Muheza 927 0 59 986 49,195 2.0 Tanga 36 0 404 440 8,914 4.9 Pangani 162 48 167 377 7,128 5.3 Handeni 212 316 2,774 3,302 47,739 6.9 Kilindi 293 48 783 1,125 19,654 5.7 Total 6,685 2,082 6,064 14,831 265,198 5.6 % 45.1 14.0 40.9 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 2,877 713 0 0 433 4,022 86,580 4.6 Korogwe 2,478 1,384 0 0 1,124 4,986 45,990 10.8 Muheza 1,843 720 59 78 0 2,701 49,195 5.5 Tanga 0 0 0 0 440 440 8,914 4.9 Pangani 0 48 0 0 191 239 7,128 3.4 Handeni 106 418 0 0 2,672 3,196 47,739 6.7 Kilindi 97 0 0 0 734 832 19,654 4.2 Total 7,400 3,284 59 78 5,594 16,415 265,198 6.2 % 45.1 20.0 0.4 0.5 34.1 100.0 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Tanga Region Beekeeping Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region District District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 240 Received Adopted % Received Adopted % Received Adopted % Lushoto 41,407 38,827 94 26,611 5,749 22 33,324 11,795 35 Korogwe 37,795 36,111 96 14,048 1,391 10 20,486 4,442 22 Muheza 20,695 16,121 78 7,189 824 11 10,493 4,477 43 Tanga 1,169 1,061 91 565 213 38 308 153 50 Pangani 2,625 2,533 97 1,626 637 39 764 372 49 Handeni 10,231 9,919 97 2,925 812 28 1,477 427 29 Kilindi 5,209 4,476 86 2,193 191 9 1,073 293 27 Total 119,130 109,047 92 55,156 9,817 18 67,925 21,958 32 Received Adopted % Received Adopted % Received Adopted % Lushoto 39,095 20,744 53 23,283 4,031 17 36,633 12,112 33 Korogwe 30,635 9,858 32 11,666 1,073 9 30,299 8,881 29 Muheza 13,699 4,629 34 7,145 553 8 16,716 2,664 16 Tanga 839 494 59 168 51 30 892 447 50 Pangani 1,459 529 36 884 172 19 1,941 1,065 55 Handeni 4,923 1,270 26 625 213 34 8,085 3,666 45 Kilindi 1,661 341 21 537 195 36 3,553 726 20 Total 92,312 37,865 41 44,307 6,288 14 98,120 29,562 30 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tanga Region District Use of Improved Seed Inorganic Fertilizer Use Organic Fertilizer Use 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tanga Region District Spacing Use of Agrochemicals Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 241 Received Adopted % Received Adopted % Received Adopted % Lushoto 1,713 714 42 25,453 9,346 37 39,697 37,242 94 Korogwe 8,438 793 9 16,525 4,665 28 28,757 20,086 70 Muheza 1,876 85 5 4,165 585 14 15,888 10,513 66 Tanga 291 32 11 240 51 21 607 528 87 Pangani 583 176 30 254 145 57 1,909 1,697 89 Handeni 3,419 511 15 851 428 50 6,500 4,500 69 Kilindi 1,024 97 9 485 193 40 3,804 2,436 64 Total 17,344 2,408 14 47,974 15,413 32 97,163 77,002 79 Received Adopted % Received Adopted % Received Adopted % Lushoto 7,975 5,521 69 36,200 34,752 96 28,547 15,683 55 Korogwe 27,020 22,813 84 19,441 16,567 85 13,222 2,949 22 Muheza 11,855 9,030 76 8,370 6,197 74 6,810 3,120 46 Tanga 801 685 86 254 297 117 274 241 88 Pangani 2,031 1,843 91 652 520 80 534 470 88 Handeni 3,300 3,086 94 1,357 1,678 124 3,231 1,252 39 Kilindi 2,735 2,540 93 2,639 2,493 94 1,317 195 15 Total 55,716 45,519 82 68,912 62,505 91 53,935 23,909 44 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Agro-progressing Agro-forestry 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tanga region Crop Storage Irrigation Technology Mechanisation / LST District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 242 Received Adopted % Received Adopted % Received Adopted % Lushoto 28,547 15,683 55 2,282 718 31 2,131 0 0 Korogwe 13,222 2,949 22 2,354 178 8 3,336 531 16 Muheza 6,810 3,120 46 596 0 0 2,530 449 18 Tanga 274 241 88 36 0 0 0 0 0 Pangani 534 470 88 138 162 117 0 0 0 Handeni 3,231 1,252 39 102 0 0 204 104 51 Kilindi 1,317 195 15 341 147 43 97 0 0 Total 53,935 23,909 44 5,849 1,205 21 8,297 1,085 13 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Tanga region District Fish Farming Beekeeping Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 243 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 % 91.8 1.1 0.0 0.2 6.9 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 % 93.8 2.3 0.2 0.1 3.6 100.0 District Organic Fertilizer Use 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 244 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seeds Tanzania Agriculture Sample Census-2003 Tanga Appendix II 245 Government NGO / Developmen t Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga region District Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 246 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 247 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 248 Using draft animal Not using draft animal No of households % No of households % Korogwe 395 1 45,595 99 45,990 Kilindi 49 0 19,605 100 19,654 Lushoto 0 0 86,580 100 86,580 Muheza 0 0 49,195 100 49,195 Tanga 0 0 8,914 100 8,914 Pangani 0 0 7,128 100 7,128 Handeni 0 0 47,739 100 47,739 Total 443 0 264,755 100 265,198 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Korogwe 592 987 1,973.4 592 987 1,973.4 Kilindi 146 146 679.9 146 146 679.9 Total 738 1,132 2,653.3 738 1,132 2,653.3 Using Organic Fertilizer Not Using Organic Fertilizer Number % Number % Lushoto 31,882 37 54,406 63 86,288 Korogwe 9,889 22 34,951 78 44,841 Muheza 5,076 10 44,040 90 49,116 Tanga 1,302 15 7,576 85 8,878 Pangani 245 3 6,883 97 7,128 Handeni 1,894 4 45,526 96 47,420 Kilindi 1,215 6 18,439 94 19,654 Total 51,503 20 211,820 80 263,323 Area (Ha) % Area (Ha) % Area (%) % Lushoto 13,238 60 1,035 19 14,273 52 Korogwe 4,160 19 1,440 27 5,600 20 Muheza 2,467 11 340 6 2,807 10 Tanga 657 3 105 2 762 3 Pangani 147 1 17 0 164 1 Handeni 896 4 772 14 1,668 6 Kilindi 389 2 1,668 31 2,057 8 Total 21,954 100 5,377 100 27,331 100 Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (acres) By District during 2002/03 agriculture year, Tanga Region 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculoture households using draft animal to cultive land by District during 2002/03 agriculture year, Tanga Region District Type of Craft Oxen Total 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Tanga region District Did you apply organic fertilizer during 2002/03? Total number of crop growing households 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Tanga Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census-2003 Tanga Appendix II 249 CATTLE PRODUCTION Tanzania AgricultureSample Census-2003 Tanga Appendix II 250 Number % Number % Lushoto 33,672 39 52,908 61 86,580 37,986 Korogwe 9,314 20 36,676 80 45,990 14,885 Muheza 3,778 8 45,416 92 49,195 11,365 Tanga 1,093 12 7,821 88 8,914 1,939 Pangani 191 3 6,936 97 7,128 911 Handeni 5,231 11 42,508 89 47,739 14,886 Kilindi 2,484 13 17,170 87 19,654 4,820 Total 55,762 21 209,436 79 265,198 86,792 Number % Number % 1-5 45,258 81 107,005 28 2 6-10 4,931 9 37,621 10 8 11-15 1,310 2 16,539 4 13 16-20 1,632 3 30,286 8 19 21-30 1,253 2 30,831 8 25 31-40 389 1 14,253 4 37 41-50 49 0 2,448 1 50 51-60 374 1 21,053 6 56 61-100 286 1 22,417 6 78 151+ 280 1 95,883 25 342 Total 55,762 100 378,338 100 7 Number % Number % Number % Number % Regions Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total % Bulls 25,822 92.2 175 0.6 2,022 7.2 28,018 7.4 Cows 142,064 92.6 0 0.0 11,357 7.4 153,421 40.6 Steers 12,100 92.6 123 0.9 846 6.5 13,069 3.5 Heifers 81,149 93.5 0 0.0 5,654 6.5 86,803 22.9 Male Calves 43,500 91.8 0 0.0 3,862 8.2 47,362 12.5 Female Calves 45,576 91.8 0 0.0 4,088 8.2 49,664 13.1 Total 350,210 92.6 298 0.1 27,829 7.4 378,338 100.0 18.3: Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 Total Improved Beef Cattle Herd Size Cattle Rearing Households Heads of Cattle Average Number Per Household Table 18.4: Total Number of Cattle by Category and Type of Cattle; on 1st October 2003 District Total Agriculture households Total livestock keeping households 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Tanga Region Households Rearing Cattle Households Not Rearing Cattle Improved Dairy Cattle Category of cattle Indigenous Cattle Tanzania AgricultureSample Census-2003 Tanga Appendix II 251 Handeni 5,125 106,690 99.8 0 0 0.0 106 212 0.2 5,231 106,901 28.3 Korogwe 8,895 72,264 97.3 0 0 0.0 720 1,975 2.7 9,314 74,238 19.6 Lushoto 27,444 60,120 79.2 143 143 0.2 8,264 15,648 20.6 33,672 75,911 20.1 Muheza 2,235 57,618 90.9 0 0 0.0 1,800 5,736 9.1 3,778 63,355 16.7 Kilindi 2,484 46,019 100.0 0 0 0.0 0 0 0.0 2,484 46,019 12.2 Tanga 663 7,003 63.6 52 155 1.4 526 3,854 35.0 1,093 11,012 2.9 Pangani 101 497 55.1 0 0 0.0 114 405 44.9 191 901 0.2 Total 46,947 350,210 92.6 195 298 0.1 11,529 27,829 7.4 55,762 378,338 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 3,603 22,614 1,004 15,192 7,762 9,945 60,120 Korogwe 4,149 30,262 1,544 14,027 10,130 12,153 72,264 Muheza 3,372 30,612 244 10,920 5,637 6,833 57,618 Tanga 772 2,805 570 1,272 793 792 7,003 Pangani 37 74 37 242 70 37 497 Handeni 7,938 38,925 5,146 31,644 12,872 10,164 106,690 Kilindi 5,951 16,771 3,556 7,852 6,237 5,652 46,019 Total 25,822 142,064 12,100 81,149 43,500 45,576 350,210 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 727 6,523 . 3,622 2,750 2,026 15,648 Korogwe 422 720 97 320 107 308 1,975 Muheza 301 2,475 227 1,072 496 1,165 5,736 Tanga 550 1,394 481 544 484 400 3,854 Pangani 21 138 42 96 24 84 405 Handeni . 106 . . . 106 212 Kilindi . . . . . . . Total 2,022 11,357 846 5,654 3,862 4,088 27,829 18.6: Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 District Number of Improved Dairy Cattle Number of Cattle Number of households Indigenous 18.2 CATTLE PRODUCTION: Total Number of Cattle by Type and District As of 1st October 2003 % Number of Cattle Number of households % Number of households Number of Cattle Number of Cattle Total Cattle Dairy District % % Number of households Beef 18.5: Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003 District Category - Indigenous Tanzania AgricultureSample Census-2003 Tanga Appendix II 252 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 143 . . . . . 143 Korogwe . . . . . . . Muheza . . . . . . . Tanga 32 . 123 . . . 155 Pangani . . . . . . . Handeni . . . . . . . Kilindi . . . . . . . Total 175 . 123 . . . 298 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 4,473 29,138 1,004 18,814 10,512 11,971 75,911 Korogwe 4,570 30,982 1,640 14,347 10,237 12,461 74,238 Muheza 3,673 33,087 471 11,992 6,133 7,998 63,355 Tanga 1,354 4,199 1,174 1,816 1,277 1,192 11,012 Pangani 58 212 78 338 94 121 901 Handeni 7,938 39,031 5,146 31,644 12,872 10,269 106,901 Kilindi 5,951 16,771 3,556 7,852 6,237 5,652 46,019 Total 28,018 153,421 13,069 86,803 47,362 49,664 378,338 18.8: Total Number of Cattle by Category and District as on 1st October 2003 District Total Cattle District Category - Number of Improved Beef 18.7: Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003 Tanzania AgricultureSample Census-2003 Tanga Appendix II 253 GOATS PRODUCTION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 254 Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats Lushoto 18,308 60,498 82 280 9,049 12 283 3,901 5.3 18,447 73,449 Korogwe 12,551 85,858 99 99 99 0 291 484 0.6 12,648 86,441 Muheza 11,478 94,480 98 246 1,222 1 121 493 0.5 11,478 96,195 Tanga 1,445 10,287 99 0 . 0 51 103 1.0 1,445 10,390 Pangani 839 10,278 99 0 . 0 80 80 0.8 839 10,357 Handeni 18,159 163,482 96 204 1,529 1 845 5,849 3.4 18,159 170,860 Kilindi 5,212 65,615 98 97 1,166 2 49 147 0.2 5,212 66,928 Total 67,991 490,499 95 925 13,064 3 1,720 11,057 2.1 68,227 514,620 Number % Number % 1-4 684,045 50.1 2,742,006 23.2 4.0 5-9 412,350 30.2 3,268,273 27.7 7.9 10-14 143,889 10.5 1,890,115 16.0 13.1 15-19 52,541 3.8 957,755 8.1 18.2 20-24 31,066 2.3 721,644 6.1 23.2 25-29 13,098 1.0 395,397 3.3 30.2 30-39 13,013 1.0 480,002 4.1 36.9 40+ 16,615 1.2 1,351,536 11.4 81.3 Total 1,366,618 100.0 11,806,728 100.0 8.6 Improved for Meat Herd Size Goat Rearing Households Head of Goats Average per Household 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003 Total 19.1 GOAT PRODUCTION: Total Number of Goats by goat type and District as on 1st October 2003 District Indigenous Improved Dairy Tanzania Agriculture Sample Census-2003 Tanga Appendix II 255 Number % Number % Number % Number % Billy Goats 62,759 82.5 9,164 12.0 4,180 5.5 76,102 15 She Goats 256,571 99.1 331 0.1 1,884 0.7 258,786 50 Castrated G 28,226 98.5 0.0 423 1.5 28,649 6 Male Kid 65,381 96.3 2,234 3.3 258 0.4 67,873 13 She Kid 77,562 93.2 1,335 1.6 4,312 5.2 83,209 16 Total 490,499 95.3 13,064 2.5 11,057 2.1 514,620 100 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 6,879 437 36,646 7,997 8,539 60,498 Korogwe 8,660 1,856 41,725 13,967 19,650 85,858 Muheza 11,368 6,186 51,204 13,261 12,461 94,480 Tanga 1,613 1,301 5,019 1,319 1,035 10,287 Pangani 1,497 179 5,647 1,672 1,283 10,278 Handeni 22,561 11,839 87,103 16,701 25,278 163,482 Kilindi 10,181 6,428 29,226 10,465 9,315 65,615 Total 62,759 28,226 256,571 65,381 77,562 490,499 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 8,347 . . 702 . 9,049 Korogwe . . . 99 . 99 Muheza 156 . 234 413 418 1,222 Tanga . . . . . . Pangani . . . . . . Handeni 611 . . . 917 1,529 Kilindi 49 . 97 1,020 . 1,166 Total 9,164 . 331 2,234 1,335 13,064 District Number of Improved Meat Goats 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 Category of Goats Indigenous Goats Improved Meat Goats Improved Dairy Goats Total 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 District Type 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 256 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 3,609 292 . . . 3,901 Korogwe . . 484 . . 484 Muheza . . 258 78 156 493 Tanga . 23 23 57 . 103 Pangani 43 . . 19 18 80 Handeni 528 108 1,070 104 4,039 5,849 Kilindi . . 49 . 98 147 Total 4,180 423 1,884 258 4,312 11,057 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 18,835.52 729.41 36,646.29 8,698.66 8,539.13 73,449.01 Korogwe 8,660.33 1,855.64 42,209.41 14,065.41 19,650.27 86,441.06 Muheza 11,524.54 6,186.39 51,696.48 13,752.16 13,034.94 96,194.52 Tanga 1,612.70 1,323.78 5,041.44 1,376.74 1,034.97 10,389.63 Pangani 1,539.24 178.62 5,647.18 1,690.63 1,301.64 10,357.32 Handeni 23,700.82 11,947.11 88,172.98 16,804.35 30,235.00 170,860.25 Kilindi 10,229.16 6,427.91 29,372.40 11,484.89 9,413.38 66,927.74 Total 76,102.31 28,648.85 258,786.17 67,872.86 83,209.33 514,619.53 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 District Number of Improved Dairy Goats District Total Goats 19.7 Total Number of Goats by Category and District on 1st October 2003 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 257 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 258 Number % Number % Number % Ram 16,121 61 10,275 39 26,396 16 Castrated Sheep 11,043 100 . 0 11,043 7 She Sheep 87,623 98 1,400 2 89,023 54 Male Lamb 15,318 84 2,945 16 18,262 11 She Lamb 19,292 99 194 1 19,485 12 Total 149,396 91 14,813 9 164,209 100 Number % Number % Lushoto 24,660 28 61,919 72 86,580 37,986 Korogwe 5,569 12 40,421 88 45,990 14,885 Muheza 3,027 6 46,168 94 49,195 11,365 Tanga 109 1 8,804 99 8,914 1,939 Pangani 61 1 7,067 99 7,128 911 Handeni 640 1 47,099 99 47,739 14,886 Kilindi 1,314 7 18,340 93 19,654 4,820 Total 35,381 13 229,817 87 265,198 86,792 Number % Number % Number % Lushoto 60,715 94 4,028 6 64,742 39 Korogwe 24,975 71 10,391 29 35,367 22 Muheza 25,059 100 81 0 25,140 15 Tanga 988 98 23 2 1,010 1 Pangani 158 100 0 0 158 0 Handeni 19,570 100 0 0 19,570 12 Kilindi 17,932 98 290 2 18,222 11 Total 149,396 91 14,813 9 164,209 100 Number of Households Average Sheep Number of Households Average Sheep Lushoto 24,371 2 1,157 3 24,660 3 Korogwe 5,569 4 188 55 5,569 6 Muheza 3,027 8 81 1 3,027 8 Tanga 87 11 23 1 109 9 Pangani 61 3 0 0 61 3 Handeni 640 31 0 0 640 31 Kilindi 1,314 14 97 3 1,314 14 Total 35,068 4 1,547 10 35,381 5 20.1 Total Number of Sheep by Breed Type on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 District Number of Indigenous Sheep Indigenous Sheep Improved for Mutton Sheep Breed Number of Indigenous Sheep Number of Improved Mutton Sheep District Total Sheep Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003. Total Households Raising Sheep Average Sheep Number of Improved for Mutton Sheep Total Sheep Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 259 Herd Size Number of Households % Number of Sheep % Average Number per Household 1-4 27,110 77 57,107 35 2 5-9 5,431 15 33,298 20 6 10-14 1,649 5 19,175 12 12 15-19 296 1 4,636 3 16 20-24 227 1 4,764 3 21 25-29 91 0 2,559 2 28 30-39 233 1 7,559 5 32 40+ 344 1 35,111 21 102 Total 35,381 100 164,209 100 5 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 6,070 1,722 40,668 5,750 6,504 60,715 Korogwe 3,741 643 14,093 3,295 3,204 24,975 Muheza 2,684 604 14,765 2,384 4,622 25,059 Tanga 64 33 614 97 179 988 Pangani 61 . 98 . . 158 Handeni 1,067 5,357 10,269 1,600 1,277 19,570 Kilindi 2,436 2,684 7,116 2,191 3,506 17,932 Total 16,121 11,043 87,623 15,318 19,292 149,396 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 144 . 1,296 2,588 . 4,028 Korogwe 10,130 . . 261 . 10,391 Muheza . . 81 . . 81 Tanga . . 23 . . 23 Pangani . . . . . . Handeni . . . . . . Kilindi . . . 96 194 290 Total 10,275 . 1,400 2,945 194 14,813 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 6,214 1,722 41,964 8,338 6,504 64,742 Korogwe 13,871 643 14,093 3,556 3,204 35,367 Muheza 2,684 604 14,846 2,384 4,622 25,140 Tanga 64 33 636 97 179 1,010 Pangani 61 . 98 . . 158 Handeni 1,067 5,357 10,269 1,600 1,277 19,570 Kilindi 2,436 2,684 7,116 2,287 3,699 18,222 Total 26,396 11,043 89,023 18,262 19,485 164,209 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8: Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Tanga 260 Appendix II Tanzania Agriculture Sample Census – 2003 Tanga 261 PIGS PRODUCTION Appendix II 262 Number % Number % 1-4 2,118 81 3,336 53 2 5-9 467 18 2,694 43 6 10-14 8 0 117 2 14 15-19 8 0 134 2 16 Total 2,601 100 6,281 100 2 District Number of Households Number of Pigs Average per Household Lushoto 146 292 2 Korogwe 1,160 2,886 2 Muheza 972 1,582 2 Tanga 58 373 6 Handeni 217 759 4 Kilindi 49 389 8 Total 2,601 6,281 2 Boars Castrated Males Sow / Gilt Male Piglets She Piglets Total Lushoto 146 . 146 . . 292 Korogwe 633 796 942 300 215 2,886 Muheza 347 181 873 90 90 1,582 Tanga 27 . 68 87 192 373 Handeni 108 . 434 217 . 759 Kilindi 49 . 146 97 97 389 Total 1,310 977 2,609 791 594 6,281 District Pig Type Herd Size 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 21.3 Number of Pigs by Type of Pig and District on 1st October 2003 21.2 Number of Households and Pigs by District on 1st October 2003 Heads of pigs Average per Household Pig Rearing Households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 263 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 264 No of Households % No of Households % Lushoto 22,075 59 15,180 41 37,255 Korogwe 6,784 46 7,908 54 14,692 Muheza 6,064 55 4,973 45 11,037 Tanga 961 51 934 49 1,895 Pangani 411 46 478 54 889 Handeni 9,176 63 5,495 37 14,671 Kilindi 3,116 65 1,656 35 4,772 Total 48,587 57 36,624 43 85,210 No of Households % No of Households % No of Households % No of Households % Lushoto 19,044 58 8,100 30 10,263 69 1,004 29 Korogwe 4,329 13 3,463 13 1,640 11 1,356 39 Muheza 2,765 8 3,519 13 1,310 9 543 16 Tanga 679 2 434 2 90 1 86 2 Pangani 87 0 365 1 0 0 0 0 Handeni 4,044 12 8,322 31 529 4 424 12 Kilindi 1,703 5 2,676 10 973 7 49 1 Total 32,653 100 26,881 100 14,805 100 3,463 100 No of Households % No of Households % Lushoto 3,047 8 34,500 92 37,547 Korogwe 3,823 26 10,764 74 14,587 Muheza 3,014 27 8,264 73 11,278 Tanga 633 34 1,254 66 1,887 Pangani 396 45 493 55 889 Handeni 7,054 48 7,723 52 14,777 Kilindi 3,167 69 1,410 31 4,577 Total 21,134 25 64,409 75 85,543 No of Households age No of Households % No of Households % No of Households % Lushoto 2,760 91 287 9 0 0 0 0 3,047 Korogwe 1,191 31 2,113 55 305 8 215 6 3,823 Muheza 1,042 35 1,892 63 80 3 0 0 3,014 Tanga 260 41 373 59 0 0 0 0 633 Pangani 143 36 165 42 41 10 46 12 396 Handeni 1,615 23 3,630 51 1,809 26 0 0 7,054 Kilindi 585 18 2,049 65 533 17 0 0 3,167 Total 7,595 36 10,510 50 2,768 13 261 1 21,134 22.4 PESTS AND PARASITE: Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. District Method of Tsetse Flies Control Total None Spray Dipping Trapping Not deworming Livestock Total District Tsetse flies problems No Tsetse flies problems Total 22.1 PESTS AND PARASITES: Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year Cattle Goats Sheep Pigs District Deworming Livestock Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 265 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 266 Type Number % Type Number Indigenous Chicken 1,751,278 98 Ducks 117,486 Layer 29,630 2 Turkeys 503 Broiler 7,859 0 Rabbits 16,611 Donkeys 17,502 Total 1,788,767 100 152,103 Indigenous Chicken Layer Broiler Total number of chicken Ducks Turkeys Rabbits Donkeys Other Muheza 468,222 . 78 468,300 Lushoto 7,722 0 12,558 8,764 0 Handeni 430,586 . . 430,586 Korogwe 28,561 0 2,024 643 0 Korogwe 262,842 533 1,172 264,547 Muheza 42,980 322 674 0 0 Lushoto 238,080 8,764 1,022 247,867 Tanga 5,556 182 416 25 239 Kilindi 162,907 . . 162,907 Pangani 1,822 0 0 48 22 Pangani 121,187 . 205 121,393 Handeni 25,758 0 940 6,082 530 Tanga 67,454 20,332 5,381 93,168 Kilindi 5,088 0 0 1,940 773 Total 1,751,278 29,630 7,859 1,788,767 Total 117,486 503 16,611 17,502 1,563 1995 1999 2003 Number % Cattle 653,549 277,000 378,338 1 - 4 66,036 37 164,365 2 Improved Dairy 20,420 25,675 28,127 5 - 9 47,677 27 308,323 6 Goats 736,727 317,924 514,620 10 - 19 36,365 21 461,035 13 Sheep 246,263 85,679 164,209 20 - 29 15,520 9 345,418 22 Pigs 1,072 2,715 6,281 30 - 39 4,980 3 157,343 32 Indigenous Chicken 1,670,790 735,916 1,751,278 40 - 49 3,245 2 137,272 42 Layers - 6,136 29,630 50 - 99 2,760 2 168,679 61 Broilers 2,986 22,327 7,859 100+ 223 0 46,333 208 Total Chickens 1,673,776 764,379 1,788,767 Total 176,806 100 1,788,767 10 23f LIVESTOCK/POULTRY POPULATION TREND Chicken Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 District 23e Head Number of Other Livestock by Type of Livestock and District Type of livestock 23d OTHER LIVESTOCK: Total Number of households and chickens raised by flock size as of 1st October 2005 Chicken rearing Households Number of Chicken Average chicken by households 23b OTHER LIVESTOCK: Number of Chicken by Category of chicken and District as of 1st October 2003 District Number of Chicken Flock size Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 267 FISH FARMING Tanzania Agriculture Sample Census-2003 Tanga Appendix II 268 Yes % No % Total Korogwe 634 1.4 45,356 98.62 45,990 Lushoto 430 0.5 86,149 99.50 86,580 Muheza 336 0.7 48,858 99.32 49,195 Tanga 23 0.3 8,891 99.74 8,914 Pangani 0 0.0 7,128 100.00 7,128 Handeni 0 0.0 47,739 100.00 47,739 Kilindi 0 0.0 19,654 100.00 19,654 Total 1,423 0.5 263,775 99.5 265,198 Natural Pond Dug out Pond Natural Lake Water Resevoir Other Lushoto 0 576 0 0 0 Korogwe 0 532 0 0 0 Muheza 0 336 0 0 0 Tanga 0 23 0 0 0 Total 0 1,467 0 0 0 Own Pond Government Institution NGOs / Project Neighbour Private Trader Other Lushoto 0 0 576 0 0 0 Korogwe 0 0 213 319 0 0 Muheza 0 156 0 90 0 90 Tanga 0 0 23 0 0 0 Total 0 156 812 409 0 90 District Neighbour Local Market Large Scale Farm Trader at Farm Did not Sell Other Lushoto 576 0 0 0 0 0 Korogwe 319 0 0 0 213 0 Muheza 180 0 0 0 156 0 Tanga 23 0 0 0 0 0 Total 1,098 0 0 0 369 0 District Number of Tilapia Number of Carp Number of Others Lushoto 124.4 0 0 Korogwe 95.9 0 0 Muheza 28.2 0 0 Tanga 0.5 0.7 0 Total 248,888 682 0 Source of fingerlings District Where sold 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.1a FISH FARMING: Number of Agriculture Households By Fish Farming And District during the 2002/03 Agriculture Year 28.2b FISH FARMING: Number of Agriculture Households by Source of Fingerling and District During the 2002/03 Agriculture Year 28.2c FISH FARMING: Number of Agriculture Households by Location of Selling Fish and District During the 2002/03 Agriculture Year District 28.2a FISH FARMING: Number of Agriculture Households by System of Fish Farming and District during the 2002/03 Agriculture Year Was Fish farming carried out by this household during 2002/03 System of fish farming District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 269 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 270 No of households % No of households % Lushoto 15,548 18.0 71,031 82.0 86,580 37,986 41 Korogwe 16,976 36.9 29,014 63.1 45,990 14,885 114 Muheza 9,898 20.1 39,296 79.9 49,195 11,365 87 Tanga 608 6.8 8,305 93.2 8,914 1,939 31 Pangani 1,064 14.9 6,064 85.1 7,128 911 117 Handeni 7,485 15.7 40,254 84.3 47,739 14,886 50 Kilindi 2,086 10.6 17,567 89.4 19,654 4,820 43 Total 53,666 20.2 211,532 79.8 265,198 86,792 62 Government NGO / Development Project Co-operative Large Scale Farmer Other(former coding) Other Lushoto 10,493 140 0 0 0 0 Korogwe 13,369 0 0 0 0 0 Muheza 6,219 85 0 89 0 0 Tanga 212 40 0 0 0 0 Pangani 567 0 0 0 0 0 Handeni 1,057 104 0 0 0 0 Kilindi 582 0 0 0 0 0 Total 32,500 370 0 89 0 0 29.1a LIVESTOCK EXTENSION: Number of households receiving extension advice by District during the 2002/03 agriculture year District % Source of extension advice District 29.1b Livestock Extension Service Providers: Number of Households By Source of Extension and District during the 2002/03 agriculture year Received livestock advice Did Not receive livestock advice Total Total Number of households raising livestock Tanzania Agriculture Sample Census-2003 Tanga Appendix II 271 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,885 562 0 0 0 8,447 37,986 22.2 Korogwe 2,899 107 0 0 0 3,006 14,885 20.2 Muheza 1,777 0 0 0 0 1,777 11,365 15.6 Tanga 168 76 0 0 0 243 1,939 12.6 Pangani 135 0 0 0 0 135 911 14.9 Handeni 520 104 0 0 0 624 14,886 4.2 Kilindi 242 0 0 0 0 242 4,820 5.0 Total 13,626 849 0 0 0 14,475 86,792 16.7 % 94.1 5.9 0.0 0.0 0.0 100.0 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 29.1c LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking by Source and Region District Source of Advice Proper Milking Total Number of households raising livestock % receiving advice out of total 29.1d LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 272 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 11,368 0 0 0 146 11,514 37,986 30.3 Korogwe 11,807 107 0 0 0 11,914 14,885 80.0 Muheza 5,060 0 0 89 0 5,148 11,365 45.3 Tanga 234 76 0 0 0 310 1,939 16.0 Pangani 492 0 0 0 22 515 911 56.5 Handeni 5,711 104 0 0 0 5,815 14,886 39.1 Kilindi 1,359 0 0 0 0 1,359 4,820 28.2 Total 36,031 286 0 89 169 36,574 86,792 42.1 % 41.5 0.3 0.0 0.1 0.2 42.1 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 6,578 146 0 0 0 6,724 37,986 17.7 Korogwe 3,001 107 0 0 0 3,107 14,885 20.9 Muheza 1,570 0 0 0 0 1,570 11,365 13.8 Tanga 95 76 0 0 0 170 1,939 8.8 Pangani 269 0 0 0 0 269 911 29.5 Handeni 961 104 0 0 0 1,065 14,886 7.2 Kilindi 290 0 0 0 48 338 4,820 7.0 Total 12,764 433 0 0 48 13,245 86,792 15.3 % 14.7 0.5 0.0 0.0 0.1 15.3 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control by Source and District District Source of Advice on Disease control (dipping/spraying) Total Number of households raising livestock % receiving advice out of total 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District District Source of Advice on Herd / Flock Size & Selection Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 273 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 3,088 146 0 0 0 3,234 37,986 8.5 Korogwe 2,057 0 0 0 0 2,057 14,885 13.8 Muheza 2,025 0 0 0 0 2,025 11,365 17.8 Tanga 39 32 0 0 0 71 1,939 3.7 Pangani 111 0 0 0 0 111 911 12.2 Handeni 637 104 0 0 0 741 14,886 5.0 Kilindi 580 0 0 0 0 580 4,820 12.0 Total 8,537 282 0 0 0 8,819 86,792 10.2 % 9.8 0.3 0.0 0.0 0.0 10.2 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment by Source and District District Source of Advice on Pasture Establishment Total Number of households raising livestock % receiving advice out of total 29.1h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengthing by Source and District District Source of Advice on Group Formation & Strengthening Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 274 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,169 281 0 0 0 8,449 37,986 22.2 Korogwe 4,330 107 0 0 0 4,436 14,885 29.8 Muheza 3,328 92 0 0 0 3,509 11,365 30.9 Tanga 236 40 0 0 0 277 1,939 14.3 Pangani 386 0 0 0 0 386 911 42.3 Handeni 1,363 104 0 0 0 1,467 14,886 9.9 Kilindi 533 0 0 0 0 533 4,820 11.1 Total 18,345 624 0 0 0 19,057 86,792 22.0 % 98.8 3.4 0.0 0.0 0.0 102.6 Number % Number % Number % Number % Number % Lushoto 4,946 27 9,088 50 3,927 22 146 1 0 0 18,108 Korogwe 2,107 12 12,024 68 2,431 14 619 4 405 2 17,586 Muheza 1,773 10 12,265 70 3,431 20 0 0 0 0 17,469 Tanga 32 6 209 41 144 28 117 23 11 2 513 Pangani 39 3 470 37 744 59 17 1 0 0 1,270 Handeni 305 5 3,861 69 847 15 0 0 614 11 5,626 Kilindi 341 13 1,749 65 194 7 0 0 391 15 2,675 Total 9,543 15 39,666 63 11,718 19 899 1 1,421 2 63,247 29.1i LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District During the 2002/03 Agriculture Year District Source of Advice on Calf Rearing Total Number of households raising livestock % receiving advice out of total 29.1l LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Quality of Service Total Very Good Good Average Poor No Good 29.1j LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District During the 2002/03 Agriculture Year District Source of Advice on Use of Improved Bulls Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 275 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,885 562 0 0 0 8,447 37,986 22.2 Korogwe 2,899 107 0 0 0 3,006 14,885 20.2 Muheza 1,777 0 0 0 0 1,777 11,365 15.6 Tanga 168 76 0 0 0 243 1,939 12.6 Pangani 135 0 0 0 0 135 911 14.9 Handeni 520 104 0 0 0 624 14,886 4.2 Kilindi 242 0 0 0 0 242 4,820 5.0 Total 13,626 849 0 0 0 14,475 86,792 16.7 % 94.1 5.9 0.0 0.0 0.0 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 Total Number of households raising livestock % receiving advice out of total 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking by Source and Region 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District District Source of Advice on Milk Hygene Source of Advice Proper Milking Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 276 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 11,368 0 0 0 146 11,514 37,986 30.3 Korogwe 11,807 107 0 0 0 11,914 14,885 80.0 Muheza 5,060 0 0 89 0 5,148 11,365 45.3 Tanga 234 76 0 0 0 310 1,939 16.0 Pangani 492 0 0 0 22 515 911 56.5 Handeni 5,711 104 0 0 0 5,815 14,886 39.1 Kilindi 1,359 0 0 0 0 1,359 4,820 28.2 Total 36,031 286 0 89 169 36,574 86,792 42.1 % 98.5 0.8 0.0 0.2 0.5 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 6,578 146 0 0 0 6,724 37,986 17.7 Korogwe 3,001 107 0 0 0 3,107 14,885 20.9 Muheza 1,570 0 0 0 0 1,570 11,365 13.8 Tanga 95 76 0 0 0 170 1,939 8.8 Pangani 269 0 0 0 0 269 911 29.5 Handeni 961 104 0 0 0 1,065 14,886 7.2 Kilindi 290 0 0 0 48 338 4,820 7.0 Total 12,764 433 0 0 48 13,245 86,792 15.3 % 96.4 3.3 0.0 0.0 0.4 100.0 Total Number of households raising livestock % receiving advice out of total 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control by Source and District 29.1h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District District District Source of Advice on Herd / Flock Size & Selection Source of Advice on Disease control (dipping/spraying) Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 277 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 3,088 146 0 0 0 3,234 37,986 8.5 Korogwe 2,057 0 0 0 0 2,057 14,885 13.8 Muheza 2,025 0 0 0 0 2,025 11,365 17.8 Tanga 39 32 0 0 0 71 1,939 3.7 Pangani 111 0 0 0 0 111 911 12.2 Handeni 637 104 0 0 0 741 14,886 5.0 Kilindi 580 0 0 0 0 580 4,820 12.0 Total 8,537 282 0 0 0 8,819 86,792 10.2 % 96.8 3.2 0.0 0.0 0.0 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Source of Advice on Group Formation & Strengthening Total Number of households raising livestock % receiving advice out of total 29.1i LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment by Source and District 29.1j LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengthing by Source and District District District Source of Advice on Group Formation & Strengthening Source of Advice on Pasture Establishment Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 278 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 8,169 281 0 0 0 8,449 37,986 22.2 Korogwe 4,330 107 0 0 0 4,436 14,885 29.8 Muheza 3,328 92 0 0 0 3,509 11,365 30.9 Tanga 236 40 0 0 0 277 1,939 14.3 Pangani 386 0 0 0 0 386 911 42.3 Handeni 1,363 104 0 0 0 1,467 14,886 9.9 Kilindi 533 0 0 0 0 533 4,820 11.1 Total 18,345 624 0 0 0 19,057 86,792 22.0 % 98.8 3.4 0.0 0.0 0.0 102.6 Total Number of households raising livestock % receiving advice out of total 29.1k LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District During the 2002/03 Agriculture Year 29.1l LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District During the 2002/03 Agriculture Year District District Source of Advice on Use of Improved Bulls Source of Advice on Calf Rearing Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 279 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 280 Number % Number % Number % Number % Number % Lushoto 4,946 27 9,088 50 3,927 22 146 1 0 0 18,108 Korogwe 2,107 12 12,024 68 2,431 14 619 4 405 2 17,586 Muheza 1,773 10 12,265 70 3,431 20 0 0 0 0 17,469 Tanga 32 6 209 41 144 28 117 23 11 2 513 Pangani 39 3 470 37 744 59 17 1 0 0 1,270 Handeni 305 5 3,861 69 847 15 0 0 614 11 5,626 Kilindi 341 13 1,749 65 194 7 0 0 391 15 2,675 Total 9,543 15 39,666 63 11,718 19 899 1 1,421 2 63,247 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Total Quality of Service No Good Very Good Good Average Poor Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 281 Government NGO / Developme nt Project Co- operative Large Scale Farmer Other(form er coding) Other Total Total Number of households raising livestock % Lushoto 15,548 14,975 14,975 14,975 14,975 75,446 37,986 50 Korogwe 16,976 16,274 16,331 16,331 16,331 82,244 14,885 18 Muheza 9,898 9,898 9,898 9,898 9,898 49,492 11,365 23 Tanga 608 608 608 608 608 3,042 1,939 64 Pangani 1,088 1,040 1,064 1,064 1,064 5,318 911 17 Handeni 7,485 7,389 7,389 7,389 7,389 37,041 14,886 40 Kilindi 2,086 2,038 2,038 2,038 2,038 10,237 4,820 47 Total 53,690 52,221 52,303 52,303 52,303 262,821 86,792 33 % 20 20 20 20 0 20 100 29.1 LIVESTOCK EXTENSION: Number of Households Receiving Advice on Other Extension Message by Source and District District Other Livestock Extension Tanzania Agriculture Sample Census - 2003 Tanga 282 Appendix II 283 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census-2003 Tanga Appendix II 284 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Lushoto 10.9 2.0 38.1 2.3 34 6.0 167.4 5.7 20.8 27.8 38.1 Korogwe 12.6 1.8 23.1 0.8 35 7.0 115.9 9.6 20.6 24.3 23.1 Muheza 13.1 2.2 24.5 1.1 28 5.6 49.7 12.3 23.8 29.2 24.5 Tanga 15.1 2.9 12.3 1.2 17 7.6 16.6 26.2 62.8 18.8 12.3 Pangani 21.4 2.3 48.7 0.7 24 4.7 67.7 10.6 56.1 27.3 48.7 Handeni 26.9 2.2 30.7 0.8 39 7.6 134.9 8.4 43.8 40.4 30.7 Kilindi 32.2 3.0 131.1 2.0 75 6.2 276.1 8.1 27.0 61.3 131.1 Total 16.5 2.2 38.0 1.5 36 6.4 131.1 9.1 28.3 31.9 38.0 Regional Capital 131.09 All weather roads 37.98 Tarmac roads 37.98 Hospitals 36.08 Tertiary Market 31.90 Secondary Market 28.29 Secondary Schools 16.50 Primary Markets 9.06 Health Clinics 6.40 Primary Schools 2.17 Feeder roads 1.45 District Mean Distance to 33.01a Mean distances from holders dwellings to infrustructures and services by districts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 285 No of households % No of households % No of households % No of households % No of households % Lushoto 1,603 1.9 12,147 14.0 43,017 49.7 18,432 21.3 11,381 13.1 86,580 10.9 Korogwe 312 0.7 4,078 8.9 16,012 34.8 15,625 34.0 9,963 21.7 45,990 12.6 Muheza 1,372 2.8 5,077 10.3 14,786 30.1 16,467 33.5 11,491 23.4 49,195 13.1 Tanga 4 0.0 166 1.9 3,007 33.7 3,277 36.8 2,460 27.6 8,914 15.1 Pangani 169 2.4 112 1.6 2,060 28.9 2,495 35.0 2,292 32.2 7,128 21.4 Handeni 1,478 3.1 2,094 4.4 8,771 18.4 14,018 29.4 21,378 44.8 47,739 26.9 Kilindi 569 2.9 1,738 8.8 4,239 21.6 1,417 7.2 11,690 59.5 19,654 32.2 Total 5,507 2.1 25,413 9.6 91,893 34.7 71,731 27.0 70,655 26.6 265,198 16.5 No of households % No of households % No of households % No of households % No of households % Lushoto 23,935 27.6 22,413 25.9 28,563 33.0 5,654 6.5 5,113 5.9 86,580 38.1 Korogwe 20,979 45.6 11,323 24.6 11,459 24.9 10,668 23.2 1,289 2.8 45,990 23.1 Muheza 27,694 56.3 8,466 17.2 8,984 18.3 6,661 13.5 528 1.1 49,195 24.5 Tanga 4,815 54.0 1,578 17.7 2,347 26.3 2,175 24.4 35 0.4 8,914 12.3 Pangani 3,183 44.7 1,120 15.7 2,399 33.7 463 6.5 77 1.1 7,128 48.7 Handeni 21,142 44.3 9,232 19.3 11,998 25.1 4,632 9.7 650 1.4 47,739 30.7 Kilindi 6,103 31.1 1,165 5.9 4,436 22.6 0 0.0 5,268 26.8 19,654 131.1 Total 107,852 40.7 55,298 20.9 70,187 26.5 30,254 11.4 12,959 4.9 265,198 38.0 No of households % No of households % No of households % No of households % No of households % Lushoto 42,213 48.8 31,134 36.0 11,637 13.4 1,451 1.7 144 0.2 86,580 2.3 Korogwe 31,404 68.3 11,037 24.0 3,441 7.5 107 0.2 0 0.0 45,990 0.8 Muheza 37,686 76.6 5,864 11.9 4,574 9.3 981 2.0 90 0.2 49,195 1.1 Tanga 7,355 82.5 1,198 13.4 227 2.6 104 1.2 29 0.3 8,914 1.2 Pangani 4,994 70.1 1,720 24.1 372 24 0.3 17 0.2 7,128 0.7 Handeni 31,037 65.0 13,082 27.4 3,620 7.6 0 0.0 0 0.0 47,739 0.8 Kilindi 13,074 66.5 3,409 17.3 2,879 14.6 97 0.5 195 1.0 19,654 2.0 Total 167,764 63.3 67,444 25.4 26,750 10.1 2,764 1.0 476 0.2 265,198 1.5 Distance to All Weather Road Total number of households Mean Distance Total number of households Mean Distance Distance to Feeder Road Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01c: Number of Households By Distance to All Weather Road by Distcrict for 2002/03 agriculture year 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Above 20 km Total number of households 33.01b Mean distances from holders dwellings to infrustructures and services by districts Distance to Secondary School District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 286 No of households % No of households % No of households % No of households % No of households % Lushoto 291 0.3 6,465 7.5 14,370 16.6 11,611 13.4 53,842 62.2 86,580 34 Korogwe 107 0.2 174 0.4 3,860 8.4 10,759 23.4 31,090 67.6 45,990 35 Muheza 608 1.2 0 0.0 9,467 19.2 9,016 18.3 30,103 61.2 49,195 28 Tanga 0 0.0 96 1.1 2,010 22.6 3,670 41.2 3,137 35.2 8,914 17 Pangani 0 0.0 102 1.4 1,691 23.7 2,939 41.2 2,396 33.6 7,128 24 Handeni 408 0.9 713 1.5 2,984 6.3 16,990 35.6 26,644 55.8 47,739 39 Kilindi 145 0.7 0 0.0 0 0.0 2,001 10.2 17,507 89.1 19,654 75 Total 1,560 0.6 7,550 2.8 34,383 13.0 56,986 21.5 164,720 62.1 265,198 36 No of households % No of households % No of households % No of households % No of households % Lushoto 2,685 3.1 28,612 33.0 43,991 50.8 10,127 11.7 1,164 1.3 86,580 6.0 Korogwe 6,139 13.3 10,583 23.0 21,926 47.7 2,963 6.4 4,380 9.5 45,990 7.0 Muheza 3,792 7.7 9,381 19.1 27,967 56.9 7,290 14.8 764 1.6 49,195 5.6 Tanga 1,432 16.1 2,740 30.7 3,975 44.6 709 8.0 58 0.7 8,914 7.6 Pangani 1,198 16.8 2,509 35.2 2,716 605 8.5 99 1.4 7,128 4.7 Handeni 4,227 8.9 7,551 15.8 22,103 46.3 11,941 25.0 1,917 4.0 47,739 7.6 Kilindi 4,262 21.7 3,301 16.8 8,966 45.6 1,466 7.5 1,658 8.4 19,654 6.2 Total 23,734 8.9 64,679 24.4 131,644 49.6 35,101 13.2 10,040 3.8 265,198 6.4 No of households % No of households % No of households % No of households % No of households % Lushoto 17,016 19.7 53,745 62.1 14,944 17.3 291 0.3 584 0.7 86,580 Korogwe 18,721 40.7 19,165 41.7 7,680 16.7 213 0.5 212 0.5 45,990 Muheza 12,612 25.6 21,399 43.5 14,582 29.6 515 1.0 87 0.2 49,195 Tanga 3,633 40.8 3,556 39.9 1,632 18.3 0 0.0 93 1.0 8,914 Pangani 1,983 27.8 3,462 48.6 1,516 21.3 95 1.3 72 1.0 7,128 Handeni 12,777 26.8 18,614 39.0 15,824 33.1 418 0.9 105 0.2 47,739 Kilindi 7,289 37.1 8,031 40.9 4,141 21.1 48 0.2 145 0.7 19,654 Total 74,029 27.9 127,973 48.3 60,319 22.7 1,579 0.6 1,298 0.5 265,198 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year Distance to Primary Schools District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Total number of households 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year Distance to hospital Above 20 km District 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km District Total number of households Mean Distance Total number of households Mean Distance Health clinic Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 287 Region Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Total Mean Distance Lushoto 1,157 144 135 0 85,143 86580 167.4 Korogwe 202 0 285 107 45,395 45990 115.9 Muheza 426 87 176 1,221 47,284 49195 49.7 Tanga 0 73 1,800 4,220 2,820 8914 16.6 Pangani 108 40 17 65 6,897 7128 67.7 Handeni 105 0 0 0 47,634 47739 134.9 Kilindi 49 0 0 49 19,556 19654 276.1 Total 2,047 345 2,414 5,662 254,730 265198 131.1 District Very Good Good Average Poor No good Dodoma 20,709 90,132 31,607 31,297 3,761 Arusha 16,615 45,509 26,865 15,292 7,340 Kilimanjaro 26,187 99,001 121,096 66,003 21,901 Tanga 5,679 64,192 49,751 29,061 7,120 Morogoro 8,272 43,910 26,476 88,592 28,157 Pwani 4,978 17,948 10,989 9,970 12,308 Dar es Salaam 745 4,045 5,935 6,606 936 Lindi 4,100 10,064 7,053 20,340 2,727 Mtwara 5,602 22,341 35,140 88,342 18,229 Ruvuma 10,629 59,679 45,037 19,278 7,838 Iringa 21,138 89,479 34,882 20,547 11,705 Mbeya 15,987 62,374 44,200 114,683 20,802 Singida 4,264 18,881 12,960 17,121 24,234 Tabora 6,818 28,787 18,702 69,550 33,657 Rukwa 1,358 6,158 7,035 7,494 7,751 Kigoma 11,644 16,820 34,718 29,280 1,304 Shinyanga 10,634 55,927 53,637 84,358 67,047 Kagera 9,677 59,292 28,756 35,937 5,897 Mwanza 13,417 43,860 48,127 71,684 58,486 Mara 11,188 23,922 17,080 27,217 21,643 Manyara 8,114 35,656 43,539 22,040 35,506 Total 217,754 897,977 703,585 874,695 398,349 33.01h Number of Households by Distance to Regional Capital 33.01i Number of Households By Level of Satisfaction Using Infrastructure and Service by Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 288 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 0 1,845 10,506 5,654 68,574 86580 38.1 Korogwe 3,891 4,807 8,106 10,668 18,518 45990 23.1 Muheza 4,447 3,475 8,730 6,661 25,881 49195 24.5 Tanga 519 572 3,705 2,175 1,943 8914 12.3 Pangani 619 72 32 463 5,942 7128 48.7 Handeni 5,483 4,214 6,390 4,632 27,021 47739 30.7 Kilindi 95 49 196 0 19,314 19654 131.1 Total 15,054 15,034 37,664 30,254 167,192 265198 38.0 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 13,940 28,206 31,217 8,863 4,353 86580 5.7 Korogwe 9,883 8,124 17,879 5,941 4,164 45990 9.6 Muheza 2,805 4,196 19,683 12,040 10,471 49195 12.3 Tanga 324 105 1,205 2,067 5,213 8914 26.2 Pangani 987 858 2,019 2,441 821 7128 10.6 Handeni 8,400 6,077 16,587 11,208 5,467 47739 8.4 Kilindi 4,099 2,381 7,113 4,009 2,052 19654 8.1 Total 40,438 49,948 95,703 46,569 32,540 265198 9.1 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 1,880 6,185 20,040 13,491 44,983 86580 27.8 Korogwe 1,465 2,810 9,029 13,126 19,561 45990 24.3 Muheza 403 59 6,928 9,780 32,024 49195 29.2 Tanga 28 91 1,568 4,347 2,880 8914 18.8 Pangani 345 92 1,488 2,812 2,391 7128 27.3 Handeni 108 0 4,733 13,962 28,936 47739 40.4 Kilindi 1,825 333 1,413 2,733 13,350 19654 61.3 Total 6,055 9,569 45,198 60,250 144,126 265198 31.9 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 8,536 10,288 14,620 21,564 31,572 86580 20.8 Korogwe 5,065 1,475 7,122 13,835 18,493 45990 20.6 Muheza 4,125 1,049 7,053 14,030 22,939 49195 23.8 Tanga 202 14 790 1,272 6,636 8914 62.8 Pangani 1,085 61 583 908 4,489 7128 56.1 Handeni 2,164 0 1,939 10,499 33,137 47739 43.8 Kilindi 1,064 580 6,141 5,076 6,792 19654 27.0 Total 22,243 13,466 38,248 67,183 124,058 265198 28.3 33.01jNumber of Households By Distance toTarmac Road and Distric for the 2002/03 Agricultural Year 33.01k Number of Households By Distance to Primary Market and Distric for the 2002/03 Agricultural Year 33.01l Number of Households By Distance to Tertiary Market Market and Distric for the 2002/03 Agricultural Year 33.01m Number of Households By Distance to Secondary Market Market and Distric for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 289 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 1,314 2 28,724 42 21,083 31 16,013 23 1,011 1 68,145 Korogwe 2,752 8 19,800 60 9,095 28 1,160 4 0 0 32,807 Muheza 59 0 5,971 37 2,513 16 2,450 15 5,203 32 16,197 Tanga 199 6 869 26 1,572 48 645 20 0 0 3,285 Pangani 180 5 335 9 970 27 2,141 59 0 0 3,626 Handeni 836 4 6,408 29 9,743 44 4,846 22 418 2 22,251 Kilindi 340 4 2,085 22 4,775 50 1,806 19 487 5 9,492 Total 5,679 4 64,192 41 49,751 32 29,061 19 7,120 5 155,804 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 584 2 16,456 58 9,370 33 1,602 6 146 1 28,159 Korogwe 1,161 8 10,195 70 3,202 22 107 1 0 0 14,665 Muheza 0 0 3,092 54 1,517 26 450 8 706 12 5,765 Tanga 23 2 320 35 361 206 23 0 0 910 Pangani 101 8 268 21 881 70 0 0 0 0 1,250 Handeni 203 2 3,463 40 4,363 50 619 7 0 0 8,649 Kilindi 242 7 1,020 30 1,857 54 244 7 49 1 3,412 Total 2,314 4 34,816 55 21,550 34 3,228 5 901 1 62,810 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 4 146 4 144 4 3,060 84 146 4 3,643 Korogwe 215 50 215 50 0 0 0 0 0 0 430 Muheza 0 0 863 36 405 17 359 15 794 33 2,421 Tanga 0 0 27 12 176 79 19 9 0 0 222 Pangani 0 0 0 0 0 0 503 100 0 0 503 Handeni 96 5 108 5 973 46 824 39 107 5 2,109 Kilindi 0 0 49 6 390 50 293 38 48 6 780 Total 457 5 1,407 14 2,088 21 5,059 50 1,095 11 10,106 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Very Good Good Average Poor No good Total number of households Satisfaction of Using Veterinary Clinic District 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 290 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 4 0 0 436 12 2,765 76 282 8 3,629 Korogwe 107 50 0 0 0 0 107 50 0 0 215 Muheza 0 0 90 6 91 6 355 25 879 62 1,416 Tanga 0 0 8 2 227 66 107 31 0 0 342 Pangani 0 0 0 0 23 24 73 76 0 0 95 Handeni 214 10 108 5 867 39 824 37 216 10 2,230 Kilindi 0 0 49 10 145 30 293 60 0 0 487 Total 468 6 256 3 1,789 21 4,524 54 1,377 16 8,414 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 0 0 281 5 2,604 47 2,476 45 146 3 5,506 Korogwe 215 3 1,884 27 4,216 60 741 11 0 0 7,056 Muheza 0 0 304 12 260 10 852 33 1,146 45 2,561 Tanga 7 1 47 8 434 71 119 20 0 0 607 Pangani 18 3 18 3 67 11 527 84 0 0 631 Handeni 106 5 542 25 529 24 924 42 96 4 2,197 Kilindi 0 0 194 12 725 45 390 24 293 18 1,603 Total 347 2 3,271 16 8,834 44 6,029 30 1,680 8 20,161 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 1 6,535 50 3,621 28 2,621 20 146 1 13,069 Korogwe 101 11 484 54 210 23 103 11 0 0 898 Muheza 0 0 323 21 240 16 87 6 885 58 1,535 Tanga 53 12 165 39 157 37 48 11 0 0 422 Pangani 42 7 24 4 0 0 521 89 0 0 587 Handeni 217 10 108 5 1,183 53 714 32 0 0 2,222 Kilindi 0 0 0 0 586 60 293 30 97 10 975 Total 559 3 7,639 39 5,996 30 4,386 22 1,128 6 19,708 No of Households % No of Households % No of Households % No of Households % No of Households % Veterinary Clinic 5,679 4 64,192 41 49,751 32 29,061 19 7,120 0 Extension Centre 2,314 4 34,816 55 21,550 34 3,228 5 901 1 Research Station 457 5 1,407 14 2,088 21 5,059 50 1,095 11 Plant Protection Lab 468 6 256 3 1,789 21 4,524 54 1,377 16 Land Registration Office 347 2 3,271 16 8,834 44 6,029 30 1,680 8 Livestock Development Centre 559 3 7,639 39 5,996 30 4,386 22 1,128 6 OVERALL % 3 19.83 29.37 23.58 3 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good TYPE OF SERVICE LEVEL OF SATISFACTION OF THE SERVICE Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 291 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census-2003 Tanga Appendix II 292 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Number of Households Lushoto 723 566 84,273 1,017 - 86,580 Korogwe 1,883 301 43,200 607 - 45,990 Muheza 7,747 322 39,502 1,345 279 49,195 Tanga 1,661 296 6,590 367 - 8,914 Pangani 1,679 47 5,286 115 - 7,128 Handeni 12,191 202 34,519 826 - 47,739 Kilindi 3,310 - 15,959 385 - 19,654 Total 29,194 1,733 229,330 4,663 279 265,198 % 11.0 0.7 86.5 1.8 0.1 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Lushoto 2 60,726 1,022 0 1,308 20,191 3,187 146 86,580 Korogwe 2 19,288 300 0 980 19,973 5,449 0 45,990 Muheza 2 14,233 519 43 323 33,362 626 89 49,195 Tanga 3 1,451 112 0 52 7,300 0 0 8,914 Pangani 3 918 171 21 0 5,973 44 0 7,128 Handeni 2 13,821 401 106 108 31,471 1,724 108 47,739 Kilindi 2 5,193 146 98 146 12,227 1,747 97 19,654 Total 2 115,628 2,671 268 2,917 130,497 12,778 440 265,198 % 43.6 1.0 0.1 1.1 49.2 4.8 0.2 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 52,670 32 25,596 16 32,362 20 6,032 4 5,415 3 29,309 18 11,227 7 162,610 61.3 Landline phone 427 32 181 14 356 27 110 8 0 0 214 16 49 4 1,337 0.5 Mobile phone 987 19 982 19 1,060 21 551 11 86 2 1,254 25 191 4 5,112 1.9 Iron 20,307 41 9,144 18 9,181 18 1,956 4 832 2 6,380 13 2,229 4 50,029 18.9 Wheelbarrow 2,720 30 809 9 1,583 18 812 9 146 2 2,275 25 584 7 8,928 3.4 Bicycle 12,641 15 12,226 14 19,009 22 4,602 5 4,098 5 24,042 28 8,420 10 85,039 32.1 Vehicle 282 12 562 24 380 16 222 10 155 7 427 18 291 13 2,319 0.9 Television / Video 285 10 562 21 520 19 286 11 81 3 738 27 241 9 2,714 1.0 Total Number of Households 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict Type of Owned Asset District 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year District Type of Toilet 34.2 Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year Type of Roofing Material Average Number of Rooms per Household District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 293 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 561 17 1,088 480 14 482 15 198 6 506 15 0 0 3,315 1.3 Solar 146 38 0 0 0 0 0 22 6 215 56 0 0 383 0.1 Gas (Biogas) 137 100 0 0 0 0 0 0 0 0 0 0 0 137 0.1 Hurricane Lamp 20,468 46 4,465 9,198 21 1,382 3 1,553 4 4,704 11 2,328 5 44,098 16.6 Pressure Lamp 2,747 25 1,677 3,557 32 282 3 179 2 1,824 17 776 7 11,043 4.2 Wick Lamp 62,374 30 38,655 35,653 17 6,719 3 5,131 3 39,953 19 16,501 8 204,986 77.3 Candles 146 45 0 0 0 49 15 21 6 105 33 0 0 321 0.1 Firewood 0 0 105 306 33 0 0 23 3 432 47 49 5 915 0.3 Total 86,580 33 45,990 49,195 19 8,914 3 7,128 3 47,739 18 19,654 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 0 190 0 0 64 17 22 6 102 27 0 0 378 0.1 Solar 278 100 0 0 0 0 0 0 0 0 0 0 0 278 0.1 Gas (Biogas) 0 0 0 0 0 0 0 21 100 0 0 0 0 21 0.0 Bottled Gas 289 39 0 267 36 52 7 79 11 0 0 49 7 736 0.3 Parraffin / Kerocine 0 0 0 90 100 0 0 0 0 0 0 0 0 90 0.0 Charcoal 572 8 1,564 650 9 515 7 123 2 3,302 46 484 7 7,210 2.7 Firewood 85,151 33 44,027 48,188 19 8,283 3 6,743 3 44,226 17 19,024 7 255,643 96.4 Crop Residues 289 39 103 0 0 0 0 138 19 108 15 97 13 735 0.3 Livestock Dung 0 0 106 0 0 0 0 0 0 0 0 0 0 106 0.0 Total 86,580 45,990 49,195 8,914 3 7,128 47,739 19,654 7 265,198 100.0 Pangani 34.4 Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year Main Source of Energy for Lighting District Total Lushoto Korogwe Muheza Tanga Handeni Kilindi Pangani 34.5 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Main Source of Energy for Cooking District Total Korogwe Muheza Handeni Kilindi Lushoto Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 294 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 17,828 10,171 6,667 4,415 2,244 16,269 917 Dry 15,090 9,737 7,152 4,961 2,247 17,675 1,698 Wet 4,777 6,271 8,074 1,108 1,097 1,399 1,941 Dry 4,628 6,551 6,906 1,115 1,252 1,399 2,281 Wet 2,874 2,887 2,120 154 83 531 535 Dry 3,159 2,774 2,526 253 39 642 633 Wet 4,057 3,737 11,539 2,530 1,681 21,080 9,286 Dry 3,913 6,062 12,566 1,906 1,504 18,276 11,335 Wet 41,372 13,741 7,910 224 422 751 3,314 Dry 42,086 12,133 7,766 400 433 320 829 Wet 14,959 8,715 11,377 210 1,534 4,920 3,660 Dry 17,129 8,380 11,132 191 1,630 6,967 2,684 Wet 424 174 429 0 0 108 0 Dry 285 84 349 0 0 108 0 Wet 290 197 818 145 66 2,149 0 Dry 146 99 239 26 23 1,716 194 Wet 0 0 258 32 0 0 0 Dry 0 171 474 32 0 108 0 Wet 0 0 0 8 0 0 0 Dry 142 0 84 8 0 105 0 Wet 0 0 0 21 0 0 0 Dry 0 0 0 21 0 0 0 Wet 0 97 0 68 0 533 0 Dry 0 0 0 0 0 424 0 Total Agricultural Households per District 86,580 45,990 49,195 8,914 7,128 47,739 19,654 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 21 22 14 50 31 34 5 Dry 17 21 15 56 32 37 9 Wet 6 14 16 12 15 3 10 Dry 5 14 14 13 18 3 12 Wet 3 6 4 2 1 1 3 Dry 4 6 5 3 1 1 3 Wet 5 8 23 28 24 44 47 Dry 5 13 26 21 21 38 58 Wet 48 30 16 3 6 2 17 Dry 49 26 16 4 6 1 4 Wet 17 19 23 2 22 10 19 Dry 20 18 23 2 23 15 14 Wet 0 0 1 0 0 0 0 Dry 0 0 1 0 0 0 0 Wet 0 0 2 2 1 5 0 Dry 0 0 0 0 0 4 1 Wet 0 0 1 0 0 0 0 Dry 0 0 1 0 0 0 0 Wet 0 0 0 0 0 0 0 Dry 0 0 0 0 0 0 0 Wet 0 0 0 0 0 0 0 Dry 0 0 0 0 0 0 0 Wet 0 0 0 1 0 1 0 Dry 0 0 0 0 0 1 0 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year District Piped Water Other Bottled Water Tanker Truck Water Vendor Uncovered Rainwater Catchment Covered Rainwater Catchment Source 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season Season Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well Piped Water Protected Well Protected / Covered Spring District Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Other Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Tanzania Agriculture Sample Census-2003 Tanga Appendix II 295 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 29,092 6,397 9,918 1,181 1,339 5,307 2,507 Dry 27,073 4,295 4,837 943 961 1,794 1,308 Wet 5,632 8,608 10,895 2,746 987 6,313 2,786 Dry 5,345 8,500 8,959 2,395 907 4,928 1,563 Wet 1,018 911 4,224 835 334 0 976 Dry 1,018 830 4,378 646 384 0 880 Wet 13,736 9,344 9,195 1,796 1,087 7,122 2,388 Dry 13,584 8,597 7,683 1,460 947 5,203 2,244 Wet 26,671 14,901 10,830 982 2,036 15,087 7,294 Dry 27,251 14,129 10,293 683 1,733 8,743 6,601 Wet 7,245 3,153 3,336 889 1,004 7,928 2,387 Dry 8,260 3,986 5,229 1,084 1,196 9,942 3,304 Wet 2,757 1,973 564 395 319 5,018 682 Dry 3,339 3,910 2,966 1,111 842 9,825 1,998 Wet 428 703 233 91 21 965 634 Dry 708 1,742 4,602 526 158 6,111 1,660 Wet 0 0 0 0 0 0 0 Dry 0 0 247 67 0 1,193 97 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 34 14 20 13 19 11 13 Dry 31 9 10 11 13 4 7 Wet 7 19 22 31 14 13 14 Dry 6 18 18 27 13 10 8 Wet 1 2 9 9 5 0 5 Dry 1 2 9 7 5 0 4 Wet 16 20 19 20 15 15 12 Dry 16 19 16 16 13 11 11 Wet 31 32 22 11 29 32 37 Dry 31 31 21 8 24 18 34 Wet 8 7 7 10 14 17 12 Dry 10 9 11 12 17 21 17 Wet 3 4 1 4 4 11 3 Dry 4 9 6 12 12 21 10 Wet 0 2 0 1 0 2 3 Dry 1 4 9 6 2 13 8 Wet 0 0 0 0 0 0 0 Dry 0 0 1 1 0 2 0 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Source Season District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 296 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 2,947 866 5,389 592 474 1,485 243 Dry 2,384 589 3,609 497 320 523 97 Wet 16,553 13,128 13,140 2,759 2,423 8,474 4,670 Dry 15,669 9,466 9,318 1,915 2,051 6,353 2,732 Wet 9,829 7,670 5,492 511 441 2,948 3,207 Dry 8,661 7,155 3,565 447 423 1,149 1,696 Wet 33,306 12,275 11,633 1,964 1,470 14,536 5,257 Dry 33,440 10,961 8,868 1,326 1,097 8,521 5,049 Wet 4,928 1,735 3,353 289 480 3,710 1,121 Dry 5,501 2,227 4,066 239 510 1,468 1,412 Wet 5,026 2,750 4,687 1,452 45 3,154 1,507 Dry 5,330 2,543 3,887 1,331 59 2,189 1,119 Wet 13,991 7,567 5,502 1,348 1,795 13,433 3,650 Dry 15,596 13,049 15,882 3,159 2,667 27,537 7,547 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 3 2 11 7 7 3 1 Dry 3 1 7 6 4 1 0 Wet 19 29 27 31 34 18 24 Dry 18 21 19 21 29 13 14 Wet 11 17 11 6 6 6 16 Dry 10 16 7 5 6 2 9 Wet 38 27 24 22 21 30 27 Dry 39 24 18 15 15 18 26 Wet 6 4 7 3 7 8 6 Dry 6 5 8 3 7 3 7 Wet 6 6 10 16 1 7 8 Dry 6 6 8 15 1 5 6 Wet 16 16 11 15 25 28 19 Dry 18 28 32 35 37 58 38 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 297 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 4,337 68 615 10 525 8 133 2 68 1 523 8 146 2 6,346 2.4 Two 33,209 50 7,894 12 7,550 11 2,926 4 1,408 2 6,878 10 6,964 10 66,829 25.2 Three 48,899 26 37,482 20 41,120 21 5,845 3 5,638 3 40,232 21 12,543 7 191,758 72.3 Four 135 51 0 0 0 0 10 4 14 5 106 40 0 0 265 0.1 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 29,863 34 12,020 14 18,561 21 4,870 6 2,922 3 15,141 17 3,934 5 87,311 32.9 One 33,590 39 10,811 12 17,868 21 1,613 2 1,841 2 14,692 17 6,327 7 86,741 32.7 Two 17,538 29 13,673 23 9,011 15 1,440 2 1,661 3 10,416 17 6,271 10 60,009 22.6 Three 3,443 18 6,028 32 2,465 13 328 2 277 1 4,644 24 1,806 10 18,992 7.2 Four 722 12 1,883 30 764 12 258 4 227 4 1,690 27 683 11 6,227 2.3 Five 566 19 829 29 264 9 68 2 158 5 628 22 390 13 2,903 1.1 Six 719 51 430 31 90 6 8 1 0 0 106 8 49 3 1,402 0.5 Seven 139 9 315 20 171 11 329 20 43 3 422 26 194 12 1,613 0.6 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Total 34.13 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District 34.12 Number of Households by Number of Meals the Household Normally Took per Day by District Kilindi Total Number of Meals per Day District Lushoto Korogwe Muheza Tanga Pangani Handeni Number of Days District Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Tanzania Agriculture Sample Census-2003 Tanga Appendix II 298 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 18,417 47 4,517 11 4,189 11 311 1 496 1 7,824 20 3,644 9 39,398 14.9 One 15,606 45 4,623 13 4,089 12 622 2 660 2 5,023 15 3,741 11 34,365 13.0 Two 20,754 39 8,321 16 8,621 16 1,270 2 1,033 2 8,779 17 4,180 8 52,958 20.0 Three 13,112 28 8,743 18 9,394 20 1,577 3 1,327 3 10,048 21 3,457 7 47,658 18.0 Four 10,499 29 4,988 14 8,188 23 1,264 4 1,198 3 7,494 21 2,245 6 35,877 13.5 Five 4,017 16 6,652 26 6,519 25 1,546 6 1,077 4 4,055 16 1,852 7 25,718 9.7 Six 1,291 13 2,607 26 2,773 28 521 5 330 3 2,205 22 244 2 9,971 3.8 Seven 2,884 15 5,539 29 5,421 28 1,802 9 1,006 5 2,310 12 292 2 19,254 7.3 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 26,975 29 18,422 20 22,501 24 3,211 3 3,392 4 11,013 12 7,194 8 92,707 35.0 Seldom 40,527 36 17,400 16 16,869 15 3,743 3 2,180 2 23,747 21 7,049 6 111,515 42.0 Sometimes 6,508 32 2,935 15 4,374 22 544 3 716 4 2,955 15 1,998 10 20,029 7.6 Often 6,493 29 3,572 16 3,424 15 920 4 441 2 5,438 25 1,850 8 22,138 8.3 Always 6,078 32 3,661 19 2,027 11 497 3 399 2 4,586 24 1,562 8 18,810 7.1 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 34.15 Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Number of Days District Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Total Status of Food Satisfaction District Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Tanzania Agriculture Sample Census-2003 Tanga Appendix II 299 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 27,232 40 6,905 10 9,047 13 553 1 602 1 17,694 26 5,498 8 67,531 25.5 Sale of Livestock 3,321 31 4,294 40 412 4 33 0 0 0 1,281 12 1,313 12 10,655 4.0 Sale of Livestock Products 720 16 1,040 23 1,009 23 340 8 48 1 1,067 24 244 5 4,468 1.7 Sales of Cash Crops 11,767 26 6,876 15 17,481 39 2,421 5 1,739 4 3,133 7 1,073 2 44,491 16.8 Sale of Forest Products 433 6 1,338 20 735 11 222 3 431 6 3,161 47 438 6 6,758 2.5 Business Income 13,747 36 6,318 17 5,077 13 2,621 7 1,247 3 6,985 18 1,800 5 37,795 14.3 Wages & Salaries in Cash 2,843 21 4,345 33 2,227 17 936 7 702 5 2,066 16 190 1 13,308 5.0 Other Casual Cash Earnings 20,467 37 8,440 15 8,063 15 596 1 1,345 2 8,788 16 7,789 14 55,488 20.9 Cash Remittance 5,613 29 6,434 33 3,523 18 246 1 290 1 2,641 13 873 4 19,620 7.4 Fishing 0 0 0 0 891 37 913 37 633 26 0 0 0 0 2,437 0.9 not applicable 0 0 0 0 0 0 0 0 0 0 0 0 97 100 97 0.0 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Handeni 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Cash Income District Total Lushoto Korogwe Muheza Kilindi Tanga Pangani Tanzania Agriculture Sample Census-2003 Tanga Appendix II 300 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 60,726 53 19,288 17 14,233 12 1,451 1 918 1 13,821 12 5,193 4 115,628 43.6 Tiles 1,022 38 300 11 519 19 112 4 171 6 401 15 146 5 2,671 1.0 Concrete 0 0 0 0 43 16 0 0 21 8 106 40 98 36 268 0.1 Asbestos 1,308 45 980 34 323 11 52 2 0 0 108 4 146 5 2,917 1.1 Grass / Leaves 20,191 15 19,973 15 33,362 26 7,300 6 5,973 5 31,471 24 12,227 9 130,497 49.2 Grass & Mud 3,187 25 5,449 43 626 5 0 0 44 0 1,724 13 1,747 14 12,778 4.8 Other 146 33 0 0 89 20 0 0 0 0 108 25 97 22 440 0.2 Total Number of Households 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 190 0 64 22 102 0 378 0.1 Solar 278 0 0 0 0 0 0 278 0.1 Gas (Biogas) 0 0 0 0 21 0 0 21 0.0 Bottled Gas 289 0 267 52 79 0 49 736 0.3 Parraffin / Kerocine 0 0 90 0 0 0 0 90 0.0 Charcoal 572 1,564 650 515 123 3,302 484 7,210 2.7 Firewood 85,151 44,027 48,188 8,283 6,743 44,226 19,024 255,643 96.4 Crop Residues 289 103 0 0 138 108 97 735 0.3 Livestock Dung 0 106 0 0 0 0 0 106 0.0 Number of Households 86,580 45,990 49,195 8,914 7,128 47,739 19,654 265,198 100.0 Main Source of Energy for Cooking District Handeni Kilindi Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year 34.18 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Roofing Materials District Total Lushoto Korogwe Muheza Tanga Pangani Tanzania Agriculture Sample Census-2003 Tanga 301 APPENDIX III QUESTIONNAIRES Appendix III 302 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 303 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a \" 3\" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 304 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 305 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 306 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 307 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 308 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vemen Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farmin No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 309 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 310 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area \"owned\" by the household in the 2002/03 agricultural year. Give area reported by the respondent in \"acres\". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in \"acres\". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 310 311 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code \"Not available\" means that the resource does not exist. The code \"Not Used\" means that the resource does exist but is not used by the hh. 312 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 313 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 314 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 315 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 316 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert HerbFun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 317 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 318 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 319 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter \"0\" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter \"0\" in columns 8 & 14. 4. If no bi-product was produced enter \"0\" in columns 10, 11, 12, 13 &14. 320 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 321 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 322 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method ofMethod of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 323 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 324 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source \"a\" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source \"b\" Source \"c\" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 325 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using \"too much labour required\" as this code generally refers to hand hoes only. The codes for this should \"NOT\" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns \"a\" , \"b\" and \"c\" for the different sources of credit. Start with the main source of credit in column \"a\". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 326 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 327 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a \"0\" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter \"0\" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 328 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importanceConstraint Order of least importanc Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 329 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 330 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 331 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 332 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 333 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 334 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 335 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 336 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 337 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 338 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 339 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter \"0\" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a \"X\". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 340 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Sourcefrequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 341 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter \"0\" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 342 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick i Main Tick if Activity carrie respo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used forused for noCheck hh -ility in activitysubsistancesubsistenceTotal (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 343 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 344 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 345 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 346 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 347 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":195,"cells":{"data":{"kind":"string","value":"# Extracted Content UNITED REPUBLIC OF TANZANIA TANZANIA CLIMATE SMART AGRICULTURE PROGRAMME COORDINATED BY MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES AND VICE PRESIDENT’S OFFICE 2015 – 2025 Tanzania Climate Smart Agriculture Program 2015 - 2025 i Contents LIST OF TABLES ................................................................................................................................ iv LIST OF FIGURES .............................................................................................................................. iv FOREWORD ..................................................................................................................................... vi ACKNOWLEDGEMENT .................................................................................................................. viii ACRONYMS AND ABBREVIATIONS ................................................................................................ ix EXECUTIVE SUMMARY .................................................................................................................. xii 1.0 INTRODUCTION ....................................................................................................................... 1 1.1 Background ......................................................................................................................... 1 1.2 Alignment with the Comprehensive African Agriculture Development Programme, National Development Goal, Agriculture Sector Strategies, National Climate Change Strategy and Action Plans, Water Resources Management Strategic Interventions and Action Plan for Climate Change Adaptation ........................................................................ 2 1.3 Preparation Process ........................................................................................................... 3 2.0 SITUATION ANALYSIS ............................................................................................................. 4 2.1 General Trends ................................................................................................................... 4 2.2 Agricultural Production Trends ....................................................................................... 4 2.2.1 Crop Production .......................................................................................................... 4 2.2.2 Livestock Production ................................................................................................. 7 2.2.3 Fisheries Production .................................................................................................. 8 2.2.4 Forest Resources ........................................................................................................ 9 2.3 Food Consumption and Nutrition Trends ....................................................................... 9 2.3.1 Levels of food consumption...................................................................................... 9 2.3.2 Nutrition trends ........................................................................................................ 10 2.4 Enabling Policy Environment ......................................................................................... 10 Agricultural Sector ............................................................................................................. 12 National Agricultural Policy .............................................................................................. 12 Tanzania Climate Smart Agriculture Program 2015 - 2025 ii National Climate Change Strategy (NCCS) ..................................................................... 13 2.5 Constraints to Agriculture Development and Growth ............................................... 13 2.5.1 Land Degradation and Soil Health ......................................................................... 13 2.5.2 Climate Change and Variability ............................................................................. 14 2.5.3 Agricultural Finance and Investments .................................................................. 19 2.6 Agricultural Growth Potential and Sources of Growth .............................................. 20 3.0 VISION AND OBJECTIVES ..................................................................................................... 21 3.1 Vision ................................................................................................................................. 21 3.2 Objectives ......................................................................................................................... 21 4.0 PROGRAMATIC RESULT AREAS ............................................................................................ 23 4.1 Result Area 1: Improved Productivity and Incomes ................................................... 23 4.1.1 Component 1: Improved productivity and nutrition .......................................... 23 4.1.2 Component 2: Irrigation and agricultural water management ........................ 24 4.1.3 Component 3: Improved Food Storage and Distribution ................................... 25 4.1.4 Component 4: Increased Growth of Incomes ...................................................... 26 4.2 Result Area 2: Building resilience and associated mitigation co-benefits............. 28 4.2.1 Component 1: Improve soil health, and restore degraded lands .................... 28 4.2.2 Component 2: Conservation of Natural Resources and Catchments ............... 29 4.2.3 Component 3: Insurance and Other Safety Nets ................................................. 31 4.2.4 Component 4: Early Warning System and Emergency Preparedness .............. 31 4.2.5 Component 5: Synergies in adaptation and mitigation enhanced ................... 32 4.3 Result Area 3: Value Chain Integration ........................................................................ 33 4.3.1 Component 1: Value addition process for agricultural products ..................... 33 4.3.2 Component 2: Increased competitiveness and enhanced integration into domestic, regional and international markets .............................................................. 33 4.4 Result Area 4: Research for Development and Innovations ..................................... 35 Tanzania Climate Smart Agriculture Program 2015 - 2025 iii 4.4.1 Component 1: Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain .................................................. 35 4.4.2 Component 2: Research Extension Linkage strengthened and made functional by 2018 ..................................................................................................................................... 36 4.5 Result Area 5: CSA Knowledge, Extension and Agro-weather Services .................. 36 4.5.1 Component 1: CSA knowledge generation and dissemination.......................... 36 4.5.2 Component 2: Enhance extension, climate information services and agro- weather advisories ............................................................................................................. 37 4.6 Result Area 6: Improved Institutional Coordination .................................................. 38 4.6.1 Component 1: Improve Inter-Ministerial and Local Government Coordination ............................................................................................................................................... 38 4.6.2 Component 2: Partnerships with private sector and civil society organizations ....................................................................................................................... 39 4.6.3 Component 3: Programmatic Coordination with Development Partners strengthened ....................................................................................................................... 40 5.0 COORDINATION FRAMEWORK ............................................................................................. 41 5.1 Institutional Arrangements ............................................................................................ 41 5.2 Coordination of Activities ......................................................................................... 41 6.0 ROLES AND RESPONSIBILITIES OF DIFFERENT SECTORS ............................................ 43 6.1 MAFC and MANR Divisions and Units ........................................................................ 43 6.2 Ministries, Departments and Agencies (MDAs) ...................................................... 43 6.3 Non-State Actors ......................................................................................................... 43 6.4 Sub-National Entities ................................................................................................. 44 7.0 MONITORING AND EVALUATION .................................................................................... 46 8.0 TEN - YEAR PROGRAMME FINANCING FRAMEWORK ................................................... 47 8.1 Cost Estimates and indicative Financing Plan ............................................................ 47 ANNEXES ....................................................................................................................................... 49 Annex I: Tanzania Map ........................................................................................................... 49 Annex IIa: Tanzania Agricultural Zones .............................................................................. 50 Tanzania Climate Smart Agriculture Program 2015 - 2025 iv Annex IIb: Tanzania Agricultural Map ................................................................................. 53 Annex III: Agricultural production ....................................................................................... 54 Annex IV: Agriculture Sector Financing Gap (TShs) 2010/2011 – 2014/2015 ............... 56 Annex V: Resource Requirement for Zanzibar................................................................... 56 Annex VI: Wood Fuel Demand and Consumption .............................................................. 57 Annex VII: Logical Framework Matrix or Program Design Matrix ............................... 58 Annex VIII: Budget Estimates for 2015 - 2025 ................................................................... 66 LIST OF TABLES Table 1: Share of Agriculture in the National Gross Domestic Product: 2005 - 2013 ..................... 4 Table 2: Production of livestock products 2008/2009 to 2013/2014 ............................................. 7 Table 3: Trends in per capita supply of major foods groups (in g/per day) .................................... 9 Table 4: The prevalence of various forms of nutrient deficiencies in Tanzania according to population groups ......................................................................................................................... 10 Table 5: Key policies relevant for CSA implementation and scale out in Tanzania ....................... 11 Table 6: Roles and Responsibilities of Different Sectors ............................................................... 44 Table: 7. Summary of CSA Cost Estimates for 10 Years ................................................................ 48 LIST OF FIGURES Figure 1: Food Crop Yield 2004 – 2013............................................................................................ 5 Figure 2: Industrial Crop Yield 2004 – 2014 .................................................................................... 5 Figure 3: Sugarcane Yield 2004 – 2013. .......................................................................................... 6 Figure 4: Horticultural Crops Yield 2004 – 2013.............................................................................. 6 Figure 5: Livestock Population Trend. ............................................................................................. 7 Figure 6: Aquaculture Production Trend in Tanzania (2010-2014) ................................................. 8 Figure 7: Climate change impacts in Tanzania with respect to temperature under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios.................................................... 14 Figure 8: Climate change impacts in Tanzania with respect to precipitation in Tanzania under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios ................................. 15 Tanzania Climate Smart Agriculture Program 2015 - 2025 v Figure 9: Percent change in precipitation in 2080 under the higher RCP 8.5 greenhouse gas emissions scenario based on an ensemble of 19 climate models from the IPCC Fifth Assessment Report. ........................................................................................................................................... 16 The darker bars represent months with greater average precipitation (from Climate Wizard, CIAT, 2015). Climate Impacts to Crops .......................................................................................... 16 Figure 10: Percent change in suitable area for major crops in Tanzania due to climate change. 17 Figure 11: Projected changes Above ground Net Primary Productivity (ANPP) in Tanzania’s rangelands ANPP by 2050s and RCP8.5 (high-end emissions) in relation to the mean value of 1971-1980. .................................................................................................................................... 17 Figure 12: Future emission projections 2007 – 2030 Source: The Economics of Climate Change in Tanzania ........................................................................................................................................ 18 Figure 13: Trend in Agricultural Financing (2001/02 - 2010/11). .................................................. 19 Figure 14: Coordination mechanism among the different implementers of CSA practices ......... 42 Tanzania Climate Smart Agriculture Program 2015 - 2025 vi FOREWORD In Sub-Saharan Africa, heavy reliance on rain-fed agriculture renders farming communities more vulnerable to effect of climate change and variability resulting in widespread food insecurity and poverty. Climate change and variability present new challenges particularly for smallholder farmers whose main stay is agriculture. Providing food for the future will require a holistic approach in order to produce on less land and by using appropriate methods. Farming communities and researchers are obliged to re-evaluate mainstreaming of farming practices and techniques and look for ways of securing food through adoption of conservation agriculture, integrated livestock keeping, fish farming and agro-forestry. High dependence on rain-fed agriculture and poor soil health increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience to external shocks. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are therefore needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. The most affected will be the rural poor, who are dependent on farming as a livelihood. Because of their poverty status, they have less ability to accumulate and protect assets and have the least adaptive capacity to respond to climatic shocks occasioned through extreme events as well as variability in weather during the cropping seasons. Changes in climate may be faster and more intense than in the past and existing knowledge on approaches and practices in agriculture may not be sufficient to address the adaptation needs. To ensure that the country is food secure and for food producers to improve their livelihoods, climate smart agriculture (CSA) is the most appropriate approach. The CSA approach would ensure sustainable increase in agricultural productivity; build resilience in food systems and adapt to climate change; Tanzania Climate Smart Agriculture Program 2015 - 2025 vii reduce food losses and waste; and contribute to the reduction and removal of greenhouse gas emissions, where possible. I believe that this CSA Programme, which is the result of a collective, sector- wide consultation effort, places Tanzania firmly on a new and ambitious growth trajectory for the future. We recognise the vital role that agriculture must play in growing the economy and creating decent jobs. In this respect, the agriculture sector as a whole is determined to optimise its contribution. The successful implementation of this programme will require multi-level partnerships between the public and private sector, civil society and citizens. I acknowledge with appreciation the constructive and cooperative relationships we have already built in this regard with all parties involved. I believe that agriculture in this country will grow from strength to strength. This, however, will require a shift in the way we do things, in line with the new strategic approach. Finally, I would like to thank the many people who have contributed to the development of this programme. Our thanks to the panel of 10 experts from across all stakeholder groups in the sector, chaired by Ms. Shakwaanande Natai, for the pivotal role they played in guiding the development of the Programme, and for their commitment to the process. I would also like to express our appreciation for those who submitted comments and made inputs that tmade the document better. We are grateful for your commitment and dedication to walk this path with our Ministry. Steven Masatu Wassira (MP) MINISTER FOR AGRICULTURE FOOD SECURITY AND COOPERATIVES Tanzania Climate Smart Agriculture Program 2015 - 2025 viii ACKNOWLEDGEMENT The preparation of the Tanzania Climate Smart Agriculture (CSA) Program has been spearheaded by a multi-disciplinary and multi-stakeholders National Expert Team from relevant Ministries, Departments, Agencies, Researchers and Academia, Civil Society Organization (CSOs) and Private Sector under the auspices of the Ministry of Agriculture Food Security and Cooperatives (MAFC) and the Vice President’s Office (VPO). Following the development of National Adaptation Program of Action (NAPA), adoption of the National Climate Change Strategy (NCCC) and Agriculture Climate Resilience Plan (ACRP), it was found necessary to prepare the Tanzania Climate Smart Agriculture (CSA) Program to guide implementation of the identified interventions. Preparation of the Tanzania CSA Program would not have been possible without the financial and technical support from the New Partnership for Africa’s Development Agency (NEPAD), Southern African Development Cooperation (SADC), Common Market for Eastern and Southern Africa (COMESA), East African Community (EAC) and the Consultative Group for International Agricultural Research Program on Climate Change, Agriculture and Food Security (CCAFS). Special thanks are due to National Team of Experts led by Shakwaanande Natai (Chairperson, National CSA Program Task Force), Eng. Isaria Mwende, Ombaeli Lemweli, Elirehema Swai, Mary Majule, Tereza Massoy, (MAFC), Joseph Kihaule (VPO), Dr. Lucy Ssendi (PMO-RALG), Lucia Chacha (MLFD), Nassor Mkarafuu (MANR - Zanzibar), Dr. Fadhila Hemed (NEMC), Mathew Ndaki (TMA) Prof. Salim Maliondo (SUA) and Mary Swai (TaTEDO) for their expertise and valuable inputs in the development of the program. Special gratitude is extended to the Tanzania government officials in relevant ministries, Development Partners, NGOs, Private Sector and other stakeholders who went through the draft and shared their ideas and opinions. We would also like to acknowledge tireless support of Dr. George Wamukoya (Climate Advisor, COMESA Secretariat) and Dr. James Kinyangi (Regional Program Leader - CCAFS) during the process of developing the CSA program. Finally, we appreciate the constructive contributions received from National Stakeholder’s Validation Workshop participants. Sophia Elias Kaduma PERMANENT SECRETARY MINISTRY OF AGRICULTURE FOOD SECURITY AND COOPERATIVES Tanzania Climate Smart Agriculture Program 2015 - 2025 ix ACRONYMS AND ABBREVIATIONS ACRP Agriculture Climate Resilience Plan AEZ Agro-ecological zone AfDB African Development Bank AGOA Africa Growth Opportunity Act ANSAF Agricultural Non State Actors Forum ARI Agricultural Research Institutes AR5 Fifth Assessment Report ASDP Agriculture Sector Development Programme ASDP-2 Second Agriculture Sector Development Programme ASLM Agriculture Sector Lead Ministries AU African Union BFSC Basket Fund Steering Committee BRN Big Results Now CA Conservation Agriculture CAADP Comprehensive Africa Agriculture Development Programme CBF Community Based Forest Management CARE CARE International CBO Community Based Organization CCAFS Climate Change, Agriculture and Food Security CGIAR Consultative Group for International Agricultural Research COMESA Common Market for Eastern and Southern Africa (COMESA) CSA Climate Smart Agriculture CSO Civil Society Organization DALDO District Agricultural and Livestock Officer DADP District Agriculture Development Plan DPP Department of Policy and Planning DRD Department of Research and Development DRTE Department of Research, Training and Extension DRM Disaster Risk Management EAC East African Community EEZ Exclusive Economic Zone EMU Environment Management Unit FANR Food, Agriculture and Natural Resources Division FAO Food and Agriculture Organization FSDP Fishery Sector Development Program GDP Gross Domestic Product HEMU Head, Environment Management Unit ICRAF International Center for Research in Agroforestry ICT Information and Communication Technology IFAD International Fund for Agricultural Development IPCC Intergovernmental Panel on Climate Change KR Key result area LDCs Least Developed Countries LGA Local Government Authority LSDS Livestock Sector Development Strategy Tanzania Climate Smart Agriculture Program 2015 - 2025 x MAFC Ministry of Agriculture Food Security and Cooperatives MANR Ministry of Agriculture and Natural Resources - Zanzibar MDAs Ministries/Departments/Agencies MDGs Millennium Development Goals MEM Ministry of Energy and Minerals MICCA Mitigation of Climate Change in Agriculture Programme MITM Ministry of Industries, Trade and Marketing MIVARF Marketing, Infrastructure, Value Addition and Rural Finance MJUMITA Mtandao wa Jamii wa Usimamizi wa Misitu Tanzania MKUKUTA National Strategy for Growth and Reduction of Poverty MLDF Ministry of Livestock Development and Fisheries MLHHS MNRT Ministry of Natural Resources and Tourism MoFEP Ministry of Finance and Economic Planning MNRT Ministry of Natural Resource and Tourism MoW Ministry of Water MT Metric Tones MTEF Medium Term Expenditure Framework NAFORMA National Forest Resource Monitoring and Assessment NAPA National Adaptation Plan of Action NARS National Agricultural Research System NCCFP National Climate Change Focal Point NCCS National Climate Change Strategy NCCSC National Climate Change Steering Committee NCCTC National Climate Change Technical Committee NCSATF National Climate Smart Agriculture Task Force NEMC National Environmental Management Council NEPAD New Partnership for Africa’s Development (NEPAD) NGOs Non-Governmental Organizations NPS National Panel Survey NSGRP National Strategy for Growth and Reduction of Poverty PMORALG Prime Minister’s Office Regional Administration and Local Government PPP Public Private Partnership PPVA Postharvest Process and Value Addition REDD Reduced Emissions from Deforestation and Degradation RCP Representative Concentration Pathways SACCOs Savings and Credit Cooperative Societies SADC Southern African Development Community (SADC) SAGCOT Southern Agricultural Growth Corridor of Tanzania SECAP Soil Erosion Control and Agro forestry Project SRI Sustainable Rice Intensification SUA Sokoine University of Agriculture TaCRI Tanzania Coffee Research Institute TADB Tanzania Agricultural Development Bank TDV Tanzania Development Vision TAFIRI Tanzania Fisheries Research Institute TAFORI Tanzania Forest Research Institute Tanzania Climate Smart Agriculture Program 2015 - 2025 xi TAFSIP Tanzania Agriculture and Food Security Investment Plan TASAF Tanzania Social Action Fund TaTEDO Tanzania Traditional Energy Development and Environment Organisation TCCIA Tanzania Chamber of Commerce, Industry and Agriculture TFCG Tanzania Forest Conservation Group TIB Tanzania Investment Bank TMA Tanzania Meteorological Agency TNA Training Needs Assessment TORITA Tobacco Research Institute of Tanzania TPRI Tropical Pesticide Research Institute TRIT Tea Research Institute of Tanzania TV Television TWG Technical Working Group UDSM University of Dar es Salaam UN United Nations UNDP United Nations Development Programme UNFCCC United Nations Framework Convention on Climate Change UNEP United Nations Environmental Programme URT United Republic of Tanzania USAID United States Agency for International Development VPO-DoE Vice President's Office - Division of Environment WARC Ward Agricultural Resource Centre WB World Bank WG I Working Group I WG II Working Group I WUE Water Use Efficiency Tanzania Climate Smart Agriculture Program 2015 - 2025 xii EXECUTIVE SUMMARY Tanzania, an East African country, is endowed with important land and water resources that have a high agricultural potential. Agriculture is a key sector of Tanzania’s economy, as it accounts for 24.1 percent of GDP and is the source of livelihoods for more than three-quarters of the population. Majority of the population still live in rural areas although urbanization has increased in the last three decades to reach 38 percent. The population is very young, as the youth (18-35 years) accounts for 65 percent. High dependence on rain-fed agriculture and poor soil health increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience to external shocks. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are therefore needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. Given that over 90.4 percent of active women in Tanzania are engaged in agricultural activities, producing about 70 percent of the country’s food requirements, and that youth who constitute about 65 percent of the total labor force in Tanzania are less engaged in agricultural activities and emerging opportunities, it is imperative that transformation and growth in the agriculture sector target both women and the youth. To address these challenges and to harmonize and enhance CSA initiatives being undertaken by different stakeholders throughout the country, the Government of Tanzania through the CSA programme, has identified six strategic priorities as sources of Tanzania’s agricultural development and growth in a changing climate. The six strategic priorities are as follows: Improved Productivity and incomes – a pro-growth and pro-poor development agenda that supports agricultural sustainability and includes better targeting to climate change impacts will improve resilience and climate change adaptation. Because climate change has a negative impact on agricultural production, achieving any given food and nutrition security target will require greater investments in agricultural productivity. It is important that Agricultural growth Tanzania Climate Smart Agriculture Program 2015 - 2025 xiii does not jeopardize soil quality or groundwater resources. Public and private sectors as well as public-private partnerships will play a critical role. Building resilience and associated mitigation co-benefits - CSA practices that will help reduce vulnerability of Tanzania’s agriculture sector by increasing productivity, enhancing adaptation and resilience of the farming systems and reducing emissions intensity in the context of achieving food and nutrition security, sustainable development and poverty reduction. Value Chain Integration - This approach is holistic in that considers input supply, production, agricultural services, traceability, marketing and business support services as necessary building blocks. Under the approach, both public and private sectors are seen as critical actors in the value chain. Knowledge and capacity building are critical strategic priorities to leverage innovations and increase efficiencies. The approach also provides enabling framework for integrating gender and the needs of the youth. Research for Development and Innovations - Although Tanzania has a well- developed agricultural research system, use of modern science and climate smart technologies in agricultural production is still limited. Inadequate research–extension–farmer linkages to facilitate demand-driven research and increased use of improved technologies continue to constrain efforts to increase agricultural productivity as farmers continue to use outdated and ineffective technologies. The role of research will be reoriented to support innovations that facilitate the transition to climate-smart agriculture by smallholder farmers. New and emerging agricultural research partnerships will identify technological advances that respond to the impacts of climate change and climate variability. A major thrust will be on the use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and aquaculture intensification, in order to bolster farmers’ adaptive capacity and support the national vision of achieving food security. Improving and Sustaining Agricultural Advisory Services - Agro-advisory services that include climate applications for agriculture will help farmers to better make informed decisions in the face of risks and uncertainties, in addition to the integrated management of present and emerging pests and disease challenges. Climate knowledge applications include seasonal weather forecasts, monitoring and early warning products for drought, floods and pests and disease surveillance. These products and services would increase the preparedness of the farmers, well in advance, to cope with risks and Tanzania Climate Smart Agriculture Program 2015 - 2025 xiv uncertainties. In this regard, dissemination of agro-weather advisories and other climate-smart agricultural practices will be enhanced through Public Private Partnerships. Furthermore, robust agro-advisory services are expected to catalyze private sector investment in priority areas such as weather-based index insurance and associated infrastructure. Further, insurance instruments shall be linked to incentives for adaptation (or risk prevention and reduction, e.g. by introducing drought resistant crops, drip irrigation, or similar measures). Improved Institutional Coordination – Improved institutional coordination is crucial for achievement of horizontal and vertical integration required for effective discharge of the CSA Programme. The achievement of horizontal integration requires a framework that provides for high-level guidance while vertical integration is instrumental in determining the roles of various sector institutions and devolved governments in performing CSA mandates. The proposed coordination framework will improve Inter-Ministerial and Local Government coordination, enhance partnerships with private sector and civil society organizations, and strengthen coordination with development partners. Tanzania Climate Smart Agriculture Program 2015 - 2025 1 1.0 INTRODUCTION 1.1 Background The agriculture sector is key to overall economic growth and development of Tanzania. It provides livelihoods to over 80 per cent of the population, generates about 24.1 percent of GDP, contributes 30 percent of export earnings and employs 75 percent of the total labor force (URT, 2013). In the national development agenda, agriculture is expected to lead the growth and structural transformation of the economy and maximize the benefits of accelerated growth. Significant improvements in the productivity of the agriculture sector are required to raise the average real incomes of Tanzanians. The food and agriculture sector also has direct impact on the attainment of at least five of the Millennium Development Goals (MDGs) and the emerging sustainable development goals (SDGs) that include poverty reduction. Agricultural growth is a proven driver of poverty reduction. When agriculture stimulates growth in Africa, the growth is twice as effective in reducing poverty as growth based in other sectors. Thus, agricultural growth also means more production, improved food security and economic growth. Tanzania depends largely on agriculture, which is strongly dependent on natural resources such as land, forests, air, and water. Sustainable utilization of these resources is vital for the growth and sustainability of the sector. However, agriculture is vulnerable to the effects of climate change associated with global warming. Smallholder farmers dominate the agricultural sector with average farm sizes of between 0.2 and 2.0 hectares, depending on the location. Yields have been mostly stagnant for the last ten years and agricultural productivity gains have been based more on the expansion of cultivated land, which is one of the major drivers of deforestation and land degradation in the country. Studies by the Tanzania Meteorological Agency (TMA) have shown that some of the previously known highly productive areas such as the Southern and Northern Highlands will continue to be affected by declining rainfall, frequent droughts and significant increase in spatial and temporal variability of rainfall with long term implications in the agricultural sector planning and resources allocation, such as improved seeds -, pesticides and even the shifts in types of agricultural produce (URT, 2009). Tanzania’s National Adaptation Program of Action (NAPA, 2007) ranked agriculture and food security as the most vulnerable and important sector that is severely impacted by climate change and advocated that studies on the impact of climate change in the sector and on food security be a priority activity. Despite the uncertainty and recognizing the potential risks, climate challenges for agriculture are reflected in Tanzania’s development plans at the highest levels. For example, the Five-Year Development Plan (FYDP 2011/12 – Tanzania Climate Smart Agriculture Program 2015 - 2025 2 2015/16), MKUKUTA-II, National Climate Change Strategy (NCCS, 2012) and Agriculture Climate Resilience Plan (ACRP, 2014-2019) include climate change as a threat to economic growth and an “underlying pre-requisite” which must be addressed to ensure success of agriculture as a core growth priority. The NCCS highlights agriculture as a key climate-sensitive sector where impacts of climate variability are already experienced by farmers, including declines in agricultural productivity, shifting Agro Ecological Zones (AEZ), increased incidents of pests and diseases, and increasingly unreliable rainfall. This CSA Program will support climate change adaptation and mitigation initiatives in the agricultural sector. Climate-smart agriculture, forestry and fisheries (CSA), as defined by FAO 2010, - contributes to the achievement of sustainable development goals and integrates the three dimensions of sustainable development (economic, social and environmental) by jointly addressing food security and climate challenges. CSA has three main pillars: Sustainably increasing agricultural productivity and incomes. Adapting and building resilience to climate change. Reducing and/or removing greenhouse gases emissions, where possible. CSA is an approach to developing the technical, policy and investment conditions to achieve sustainable agricultural development for food security under climate change. In this context, the CSA approach in Tanzania is designed to identify and operationalize sustainable agricultural development within the explicit parameters of climate change and variability 1.2 Alignment with the continental, regional and national agriculture and climate change policies, strategies and plans This CSA Programme is aligned with the national economic blue print – Tanzania Vision 2025 and the National Development Plan. The Programme is also in line with the broad national objectives of the agricultural sector of contributing towards attainment and maintenance of domestic supply of main food items, production of raw materials for industries and creation of gainful employment of men, women and the youth. Similarly, the CSA Programme is aligned with the Water Resources Management Strategic Interventions and Action Plan for Climate Change Adaptation. The programme is further aligned with National REDD+ Strategy and Action Plan as it addresses the main drivers of deforestation and forest degradation. At the regional level, the CSA Program enhances the implementation of the Comprehensive African Agriculture Development Programme (CAADP) and responds to the 23rd Ordinary African Union Assembly – Decisions and Declaration (Malabo Declaration), in particular: Assembly/AU/Dec. 538 (XXIII) on Climate Change and agriculture; Assembly/AU/Decl.1 (XXIII) on Accelerated agricultural growth and transformation; and Assembly/AU/Decl.4 (XXIII) on Nutrition security for Inclusive economic Growth and Sustainable Development. At the national level, Tanzania Climate Smart Agriculture Program 2015 - 2025 3 the CSA Program will contribute to Tanzania’s efforts to adapt and build resilience in - agriculture under the National Adaptation plan of Action (NAPA), The National Climate Change Strategy (NCCS), Agriculture Climate Resilient Plan (ACRP) and The National REDD+ Strategy and Action Plan. The CSA Program is intended to harmonize and enhance CSA initiatives being undertaken by different stakeholders. 1.3 Preparation Process In preparation of this CSA Program, the Ministry of Agriculture Food Security and Cooperatives and the Vice President’s Office pursued a consultative approach under the guidance of a Multi-disciplinary Team of Experts drawn from relevant Ministries and Departments, Agencies, Civil Society Organization (CSOs), Private Sectors, Researchers and Academia. The Program was developed through a four-step procedure as follows: 1. conducting technical working sessions that took stock of the sector’s programmes, strategies and performance from a historical perspective, as well as an analysis of options for agricultural sector growth in a changing climate; 2. consultative sessions were carried out with interested groups, particularly the National Designated Authority (NDA) for Green Climate Fund (GCF), Global Environment Facility (GEF) Focal Point, Planning Commission, Revolutionary Government of Zanzibar, CSOs, umbrella private sector organizations such as the Tanzania private sector association and farmer organizations, Local Government Authority and Development Partners; 3. National stakeholder validation workshop where comments from stakeholders were discussed and incorporated; and 4. Resource mobilization to support implementation of Tanzania CSA Programme. Tanzania Climate Smart Agriculture Program 2015 - 2025 4 2.0 SITUATION ANALYSIS 2.1 General Trends The agriculture sector in Tanzania provides livelihoods to over 80 percent of the population, generates about 24.1 percent of GDP (Table 1), contributes 30 percent of export earnings and employs 75 percent of the total labor force (URT, 2013). Tanzania is endowed with 44 million hectares (46 percent of total land) suitable for agriculture. However, part of this arable land is only marginally suitable for agricultural production due to a combination of factors including infertile soils, soil erosion, degradation and likelihood of drought. Moreover, about 28% of the land area is inaccessible to agriculture as it is under protection as Forest reserves and Wildlife protected areas. Currently, only 32 percent of the available arable land is cultivated. Tanzania also has significant potential for irrigated agriculture, with the area suitable for irrigation estimated to be about 29.4 million ha. Yet only 1.5 percent (441,000 ha) of potential irrigated areas is currently under irrigation. Smallholder agriculture is predominantly rain fed especially in arid and semi-arid regions that depend entirely on subsistence livestock and food crop production for their livelihoods. Table 1: Share of Agriculture in the National Gross Domestic Product: 2005 - 2013 YEAR SECTOR (percent) Agriculture Industry Services Other (Net Indirect Taxes) 2005 26.9 20.8 42.5 9.8 2006 25.3 20.8 43.3 10.6 2007 25.0 21.2 43.3 10.5 2008 24.9 21 43.8 10.3 2009 23.8 22 43.6 10.6 2010 24.1 21 49.5 5.4 2011 24.7 21 50 4.3 2012 24.8 21 50 4.2 2013 24.7 25 47.7 24.7 Source: URT (2013). The Economic Survey, Ministry of Finance. 2.2 Agricultural Production Trends 2.2.1 Crop Production Smallholder farmers dominate the agricultural sector with average farm sizes of between 0.2 and 2.0 hectares, depending on the location. Yields have been Tanzania Climate Smart Agriculture Program 2015 - 2025 5 mostly stagnant for the last ten years and agricultural productivity gains have been based more on the expansion of cultivated land, which is one of the major drivers of deforestation and land degradation in the country. The major food crops include maize, sorghum, rice, pulses, cassava and potatoes (Figure 1). Figure 1: Food Crop Yield 2004 – 2013 Source: FAOSTAT 28/03/2015 Industrial crops (Figures 2 & 3), commonly referred to as cash crops, are mainly grown as a source of income. These include tea, coffee, pyrethrum, tobacco, sisal, cashew and sugarcane among others. Figure 2: Industrial Crop Yield 2004 – 2014 Source: FAOSTAT 28/03/2015 Tanzania Climate Smart Agriculture Program 2015 - 2025 6 Figure 3: Sugarcane Yield 2004 – 2013. Source: FAOSTAT 28/03/2015 The horticulture sub-sector is one of the fastest growing sectors contributing to food security, nutrition improvements and economic growth (Figure 4). It has been identified as one of the priority sub-sectors in the National Export Strategy (2008), the Kilimo Kwanza Resolution and a key component in the diversification of the agricultural sector from over dependence on traditional primary agricultural products. The sub-sector has a potential to become one of the main sources of foreign exchange earnings and a significant driver of economic growth. For instance, indigenous fruits, vegetables, spices and flowers have been cultivated in Tanzania for generations and traded throughout the region and internationally (e.g. the country is thought to have started exporting bean seed to Europe in the 1950s). Horticulture is mainly practised by small-scale farmers with a few large-scale operators. Local and foreign investors endow the floriculture and export vegetables sub-sector. Figure 4: Horticultural Crops Yield 2004 – 2013 Source: FAOSTAT 28/03/2015 Tanzania Climate Smart Agriculture Program 2015 - 2025 7 2.2.2 Livestock Production The country has an estimated population of 22.8 million cattle, 15.6 million goats, 7 million sheep, 35.5 million local chickens; 24.5 million improved chicken breed and 2.1 million pigs1. However, 97 percent of all livestock are indigenous breeds which are kept by rural farmers and are grazed under natural pasture, while only 3 percent are improved breeds either grazed and or fed in cut and carry systems with minimal supplements. Figure 5: Livestock Population Trend. Source: Ministry of Livestock and Fisheries Development, 2014 Table 2: Production of livestock products 2008/2009 to 2013/2014 Source: Ministry of Livestock and Fisheries Development (2014) 1 Budget Speech 2014/2015 Product 2008/09 2009/10 2010/11 2011/12 2012/13 2013/2014 Meat Production (Tonnes) Cattle 225,178 243,943 262,606 289,835 299,581 309,353 Goats/sheep 82,884 86,634 103,709 111,106 115,652 120,199 Pig 36,000 38,180 43,647 47,246 50,814 79,174 Chicken 78,168 80,916 93,534 84,524 87,408 54,360 Total 422,230 449,673 503,496 532,711 553,455 563,086 Milk Production ('000' litres) Local Cattle 1,012,436 997,261 1,135,422 1,255,938 1,297,775 1,339,613 Modern Cattle 591,690 652,596 577,962 597,161 623,865 650,570 Total 1,604,126 1,649,857 1,713,384 1,853,098 1,921,640 1,990,183 Egg Production ('000') Eggs 2,806,350 2,917,875 3,339,566 3,494,584 3,725,200 3,899,568,750 Tanzania Climate Smart Agriculture Program 2015 - 2025 8 Despite the large livestock population size, its contribution to the national economy (GDP) has persistently been declining from 18 percent in 2001 to 4.4 percent (TBS, 2013). Major challenges include recurring droughts which reduce pasture productivity and water availability; alien invasive species, pests and diseases. Furthermore, uncontrolled livestock mobility brings about conflicts between crop farmers and livestock keepers. 2.2.3 Fisheries Production Tanzania has total water area of 62,000 km2 potential currently employing more than 4 million people. In Zanzibar, the fisheries sector is largely artisanal currently employing about 20 percent of the island population with mariculture activities such as seaweed and prawn farming also supplementing the incomes of - island households. Climate change impacts on fisheries are mainly associated with degradation of fish areas and fish stock. For instance, sea level rise, which is associated with global warming, may cause sea water to rise above optimal levels, and increased sea water acidification bleaching corals, causing degradation of fish nursery grounds, breeding and feeding areas. Moreover, drought and frequent floods increases sedimentation in freshwaters, negatively affecting fisheries in fresh water bodies. Aquaculture in Tanzania has a huge potential but yet untapped for widespread household and commercial use. The high potential for development of aquaculture is due to availability of water resources and diversified species in the wild potentially suitable for aquaculture. Currently, the total number of people involved in the aquaculture is about 17,100 (with 14,100 involved in freshwater fish farming and about 3,000 in seaweed farming). Youths play an important role in aquaculture in pond construction, management and distribution of fish. Figure 6: Aquaculture Production Trend in Tanzania (2010-2014) Source: Ministry of Livestock and Fisheries Development Tanzania Climate Smart Agriculture Program 2015 - 2025 9 2.2.4 Forest Resources The total forest area in Tanzania is 48 million ha, of which 93 percent of this is woodlands and only 7 percent are classified as forest reserves (mangroves, coastal forests, humid montane forests and plantations). Forest ecosystems in Tanzania are major sources of various ecosystem goods and services. They cover and protect most of the water catchments in the country and serve as a link in the agriculture-water-energy nexus. Besides timber and other non- timberforest products, the most important use of wood in Tanzania is provision biomass energy (fuel wood and charcoal) used by over 90% of the population. Some forest areas also support agriculture and livestock keeping. 2.3 Food Consumption and Nutrition Trends 2.3.1 Levels of food consumption Cereals and roots and tubers serve as staples for the majority of the population in rural as well as in urban areas. Maize is consumed in all regions, especially in rural areas while rice is mostly consumed in urban and coastal regions. Other staples include plantain, potatoes, rice, cassava and sorghum. Other cereals such as sorghum and millet; roots and tubers such as yams and sweet potatoes are known but contribute less to the diet, as they are less preferred. The main dish is a stiff porridge (known in Kiswahili as ugali) made from maize flour, sorghum or cassava. The staple is eaten with a relish either made of vegetables, sardines, pulses or meat. The diet is often monotonous with a limited diversity of foods; it is based on starchy foods with high fibre content. Frequency of vegetable consumption is high, especially among rural communities where they are included in every meal, but generally quantities are small. Therefore, vegetables do not contribute substantially to nutrient intake. Table 3: Trends in per capita supply of major foods groups (in g/per day) Major food groups Supply for human consumption in g/day 1966-68 1973-75 1980-82 1987-89 1994-96 2001-2003 Starchy roots 742 755 691 494 592 518 Cereals (excl. beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oil crops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Tanzania Climate Smart Agriculture Program 2015 - 2025 10 Source: FAOSTAT In rural areas and among the low-income section of the urban population, the quantity of food consumed can be limited and meal frequency varies with the season. It is limited to one meal per day during the wet season (lean months) and to two meals during the dry or harvest season. Frequency of meat and milk consumption is extremely low, on average once a week or even less. Among certain communities these products are consumed very rarely, for example once a month or less. 2.3.2 Nutrition trends Under-nutrition and malnutrition are still highly prevalent in Tanzania. More than a third of children under five years are affected by chronic malnutrition (stunting). In the Southern zone prevalence surpasses 50 percent. Stunting is due to a combination of factors including maternal malnutrition, inadequate infant feeding practices, low quality of health care and poor hygiene. Breastfeeding is widely practiced but exclusive breastfeeding is not widespread and complementary feeding practices are inadequate. At the same time, the country is undergoing a nutrition transition due to changes in dietary habits, especially among middle and high-income groups living in urban areas who consume energy dense and processed foods. The prevalence of overweight and obesity is noticeable among women (almost one woman out of five). Table 4: The prevalence of various forms of nutrient deficiencies in Tanzania according to population groups Category of population affected Type of deficiency and percent affected PED Anaemia IDD VAD Children under-five years 52.0 45.0 13.0 30.0 Pregnant and lactating women 13.0 80.0 52.0 0.7 Remaining groups 20.0 20.0 40.0 0.1 General population 28.0 32.0 25.0 6.1 Source: Kavishe F.P (1987), TFNC Report no. 1215 2.4 Enabling Policy Environment Policy reforms are cited as one of the drivers of productivity gains experienced in the agriculture sector. These policy reforms substantially improve the economic environment for agriculture through improvements in better policies on pricing -, trade, exchange rates, institutions and markets. The Government of the United Republic of Tanzania has over the years developed policies and strategies to enhance agricultural growth, natural resource management and climate change interventions. The Table 5 below summarizes the key policies and strategies that the GoT ratified and implemented in the country, and which, through their objectives and action plans, have an impact on CSA Tanzania Climate Smart Agriculture Program 2015 - 2025 11 implementation (Table 3). The summary of the enabling and (potentially) obstructing policies are provided in Table 5. Table 5: Key policies relevant for CSA implementation and scale out in Tanzania Regional Comprehensive Africa Agriculture Development Programme (CAADP) Based on four reinforcing pillars for investment in agriculture to improve performance through strengthening country presence, focused lending program based on coordinated sector plans, enhanced capacity for policy, analytical work, and knowledge/partnership management: 1. Expanding the areas under sustainable land management and reliable water control systems. 2. Improving rural infrastructure and trade related capacities for market access 3. Increasing food supply and reducing hunger 4. Expanding agricultural research and technology transfer and dissemination East Africa Community Food Security Action Plan Developed to address food insecurity in the region. It forms the initial step of implementing the provisions of the EAC Treaty as set out in Chapter 18 Articles 105 -110. One of the main objectives of the EAC as set out in the Treaty is the achievement of food security and rational agricultural production. The EAC- Food Security Action Plan will guide coordination and implementation of the joint programmes and projects emanating from this plan. East Africa Community Climate Change Policy The purpose is to guide EAC Partner States and other stakeholders on the implementation of collective measures to address climate change impacts and causes in the region through adaptation and mitigation actions while assuring sustainable social and economic development. Macro economics Tanzania Development Vision (TDV) 2025 Developed with the intention of coordinating and directing national’s efforts and resources towards economic and social development by 2025. 1. Achieving quality life for all, 2. Good governance and the rule of law, and 3. Building a strong and resilient economy that can effectively withstand global competition. Tanzania Climate Smart Agriculture Program 2015 - 2025 12 The National Strategy for Growth and Reduction of Poverty II Sets targets and goals on accelerating economic growth, reducing poverty and improving living standards and social welfare of Tanzanians. Agricultural Sector National Agricultural Policy Aims at setting instruments for the development of an efficient, competitive and profitable agricultural industry that contributes to nation’s economic growth and wellbeing of Tanzanians. Tanzania Agriculture and Food Security Investment Plan (TAFSIP) Ten-year investment plan, which maps the investments, needed to achieve the CAADP target of six percent annual growth in agricultural sector GDP. It aims to contribute to the national economic growth, household income and food security in line with national and sectoral development aspirations. Agricultural Sector Development Programme (ASDP) Main objectives are to enable farmers to have better access to and use of agricultural knowledge, technologies, marketing systems and infrastructures for higher productivity and profitability; and to promote involvement of the private sector in agricultural transformation under improved regulatory and policy frameworks. Livestock Sector Development Strategy (LSDS) Aims at developing a competitive and more efficient livestock industry that contributes to the improvement of the livelihoods of all livestock keepers and the national economy. Fisheries Sector Development Programme (FSDP) Designed to develop a sustainable, competitive and more efficient fisheries and aquaculture industry that contribute to the sustainable livelihood improvement and the national economy. Tanzania Agriculture Climate Resilience Plan (ACRP) Developed to implement strategic adaptation and mitigation actions in the crops sub-sector. It presents a wide range of adaptation options including, but not limited to: improving agricultural land and water management, accelerating uptake of CSA, reducing impacts of climate-related shocks through risk management, and strengthening knowledge and systems to targeted climate action. Southern Agricultural Growth Corridor of Tanzania (SAGCOT) The goal is to expand investment in agribusiness leading to income growth among smallholders and employment generation across agribusiness value chains in the Southern Corridor Tanzania Climate Smart Agriculture Program 2015 - 2025 13 Big Result Now (BRN) The objective is to address critical sector constraints and challenges and to speed-up agriculture GDP, improve smallholder incomes and ensure food security by 2015, mainly through smallholder aggregation models for main cereals and high potential crops contributing to import substitution, farm income and food security. Environment and Climate Change National Environmental Policy (NEP) Aims at ensuring sustainable and equitable use of resources for meeting basic needs, preventing and controlling degradation of land, water, vegetation and air, and improving the condition and productivity of degraded rural and urban areas National Climate Change Strategy (NCCS) Sets out strategic interventions for climate change adaptation measures and greenhouse gas emissions reductions. It has outlined objectives for all sectors and proposed strategic interventions in those sectors and themes that are highly vulnerable to climate change such as agriculture. Land, Land use and Forestry The National Strategy (and Action Plan) for Reduced Emissions from Deforestation and Forest Degradation (REDD+) The strategy (and plan) aims to facilitate effective and coordinated framework for reducing deforestation and forest degradation. It guides the implementation and coordination of mechanisms required for Tanzania to benefit from a post-2012 internationally approved system for forest carbon trading, based on demonstrated emission reductions from deforestation and forest degradation and other aspects of REDD+ 2.5 Constraints to Agriculture Development and Growth 2.5.1 Land Degradation and Soil Health Demands on the land for economic development and pressures from a growing population are leading to unprecedented land use change. In turn, unsustainable land use is driving land degradation. The result is - loss of land productivity with impacts on livelihoods and the economy. The impacts of land degradation and desertification include a reduction in crop and pasture productivity and fuel-wood and non-timber forest products, which are closely linked to poverty and food insecurity. The damage to soil, loss of habitat, water shortages, and siltation reduce biodiversity and ecosystem services and has wider economic consequences. Land degradation manifests itself in many forms; among them are soil erosion, increased sediment loading of water bodies, loss of soil fertility, increased salinity, reduced ground cover, and the reduced carrying capacity of pastures. To address this challenge, the Tanzania Climate Smart Agriculture Program 2015 - 2025 14 government launched the National Strategy on Urgent Actions to Combat the Degradation of Land and Water Catchment Areas in Tanzania (URT, 2006) that has not yet been fully implemented. 2.5.2 Climate Change and Variability Agriculture in Tanzania is acutely vulnerable to the impacts of climate change due to dependency on climate. Unreliable rainfall, extreme weather events and poor rainfall distribution are the most damaging risks of production among smallholder farmers and fisher-folks. Drought and floods are the major natural disasters in Tanzania accounting for up to 70 percent of all recorded natural calamities causing large-scale famine, diseases and deaths for human beings, plants and animals. A range of Global Circulation Models (GCM) and emission scenarios projections indicate future changes in rainfall and increases in average annual temperatures of 1ºC to 3ºC above the baseline period (1961-1999) by the 2050s, with the latest projections indicating a high certainty of a 1 ºC rise across the country. Figures 7 and 8 show Climate change impacts in Tanzania with respect to temperature and rainfall respectively under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios. Figure 7: Climate change impacts in Tanzania with respect to temperature under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios Tanzania Climate Smart Agriculture Program 2015 - 2025 15 The thick black lines represent the average of 29 different climate models, whereas the grey box and dashed lines represent the range of climate models. Although precipitation is projected to increase by most climate models, the timing of precipitation is also changing with some months projected to decrease. Figure 8: Climate change impacts in Tanzania with respect to precipitation in Tanzania under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios Although climate change is projected to bring more rain to Tanzania in some areas, models show that this increase in rainfall is only during the middle of the rainy season (November-April rain season) with all other months projected to decrease in precipitation (see Figure 9). This would result in the rainy season becoming shorter but more intense, and the dry season becoming drier. Increased intensity in frequency of storms, drought, flooding, may alter the hydrological cycles while variable precipitation may have implications for food, pasture and water availability. Tanzania Climate Smart Agriculture Program 2015 - 2025 16 Figure 9: Percent change in precipitation in 2080 under the higher RCP 8.5 greenhouse gas emissions scenario based on an ensemble of 19 climate models from the IPCC Fifth Assessment Report. The darker bars represent months with greater average precipitation (from Climate Wizard, CIAT, 2015). Climate Impacts to Crops Agricultural crop modeling shows that climate change has impacts depending on the crop. Maize is expected to have 25 to 75 percent decreases in area suitable for cultivation (Figure 10). Likewise, sorghum is expected to have a moderate decrease in area suitable for cultivation. However other crops such as beans, cassava and banana are expected to increase in area suitable. While forage for livestock grazing is very important to Tanzania, climate change is projected to decrease rangeland productivity (Figure 11 below). Tanzania Climate Smart Agriculture Program 2015 - 2025 17 Figure 10: Percent change in suitable area for major crops in Tanzania due to climate change. The red line represents the average projected change and the blue box and dashed lines represent uncertainty associated with the crop modeling. Analysis provide by J. Vargas, CIAT Figure 11: Projected changes Above ground Net Primary Productivity (ANPP) in Tanzania’s rangelands ANPP by 2050s and RCP8.5 (high-end emissions) in relation to the mean value of 1971-1980. This provides a good proxy for climate change impacts to livestock productivity. Tanzania Climate Smart Agriculture Program 2015 - 2025 18 Tanzania currently has very low emissions of Greenhouse Gases (GHG), in total and per capita. The published inventory for 1994 puts per capita emissions at 1.3 tones of CO2e (all GHGs) and 0.1 tCO2 (CO2 only). However, if land use changes and forestry (including deforestation) are included, the per capita emission estimates rise to 2.67 (all GHGs) and 1.65 (CO2 only). The key emitting sectors are forestry, due to deforestation, and agriculture, primarily from livestock (CH4 from enteric fermentation) and soils (N2O from fertilizers, animal manure, etc.). These two sectors accounted for 93percent of emissions in 1994 (forests 70percent, agriculture 23percent). In the future, it is inevitable that GHG emissions in Tanzania will increase under the planned current development baseline. For example, between 2005 and 2030 under the current projected baseline, per capita emissions are set to increase to 1.5 tCO2e and 0.5 tCO2 (CO2 only). The future emission projections (excluding LUCF sector) are shown in Figure below Figure 12: Future emission projections 2007 – 2030 Source: The Economics of Climate Change in Tanzania Building resilience and adaptation in the agriculture sector is very crucial due to the vulnerability and the observed impacts of climate change in the country. With a vulnerable rainfed agricultural sector, a well-functioning early warning system is a key factor in risk reduction and enhancing productivity. The institution responsible for provision of early warning information in Tanzania include Tanzania Meteorological Agency (TMA), in collaboration with international partners and national partners such as Ministry of Agriculture Food Security and Cooperatives (MAFC), Ministry of Livestock and Fisheries Development - and Ministry of Natural Resources and Tourism. However, these early warning systems are inefficient in terms of the means of communicating the intended information. The common means of communicating the information is via radio and Television broadcasting, newspapers, websites and Tanzania Climate Smart Agriculture Program 2015 - 2025 19 emails. With this method, the information is not delivered on time, and thus difficult to integrate it into farming decisions. 2.5.3 Agricultural Finance and Investments The Government through the national budget is the main funder of the agricultural sector, supplemented by Development Partners (DPs), private sector and civil society organizations thus making significant contributions to the sector. According to the Maputo Declaration of the African Union in 2003, it was agreed that all African countries, including Tanzania strive to commit at least 10 percent of the national budgets to agriculture. Although Tanzania has not attained the annual target of 10 percent, over the years, there has been a remarkable increase in investments in agriculture currently standing at about 8 percent. Figure 13: Trend in Agricultural Financing (2001/02 - 2010/11). In addition, the Government in collaboration with DPs and private sector have put in place measures aimed at improving the flow of finance and investment to the agriculture sector such as: the Export Credit Guarantee Scheme, USAID Guarantee for Input Scheme, Private Agriculture Sector Support (PASS), the Agro-Dealers Scheme and the Agriculture Input Trust Fund (AGIFT). Other initiatives that enhance Public Private Partnerships include the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) and Big Results Now (BRN). One of the main constraints to private sector investment in agriculture is lack of appropriate financing arrangement, particularly considering the high risks associated with investments in the agriculture as compounded by the impacts of climate change and climate variability. Tanzania Climate Smart Agriculture Program 2015 - 2025 20 2.6 Agricultural Growth Potential and Sources of Growth Agriculture in Tanzania has a huge potential and opportunities for development. About 44 million hectares are suitable for agricultural production and only 10.8 million hectares (25%) are cultivated mostly under subsistence agriculture (i.e., smallholders operating between 0.2 and 2 hectares with low productivity). The potential therefore exists for expansion and intensification. In addition, the area with irrigation potential is 29.4 million hectares, but only 1.5 % (440,000 ha) so far utilized. Tanzania has a dual agricultural economy: smallholder farmers on one side dominate the agricultural sector, carrying out rainfed agriculture, producing a variety of subsistence crops, such as maize, sorghum, millet, cassava, sweet potatoes, pulses, paddy, wheat, fruits and vegetables. On the other side, cash crops like sisal, sugarcane and tea are grown on large-scale commercial farms and cashew nut, coffee, cotton and tobacco are grown on small-scale farms. Peri-urban agriculture (mainly horticultural crops) for household food consumption is rapidly increasing. High dependence on rainfed agriculture and poor soil health largely due to land mismanagement increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. Over 90.4 percent of active women in Tanzania are engaged in agricultural activities, producing about 70 percent of the country’s food requirements. Moreover, youth who constitute about 65 percent of the total labor force in Tanzania, are less engaged in agricultural activities and emerging opportunities. It is imperative that transformation and growth in the agriculture sector target both women and the youth. Tanzania Climate Smart Agriculture Program 2015 - 2025 21 3.0 VISION AND OBJECTIVES 3.1 Vision The Vision for the CSA Program is to have an “Agricultural sector that sustainably increases productivity, enhances climate resilience and food security for the national economic development in line with Tanzania National Development Vision 2025.” 3.2 Objectives The five core objectives of the Country CSA Programme are: 1. Increase productivity of the agricultural sector through (appropriate) climate smart agriculture practices that consider gender. 2. Enhance climate resilience of agricultural and food systems. 3. Strengthen policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture. 4. Improve infrastructure to support value addition, marketing, trade and postharvest management. 5. Develop financing mechanisms to solicit resources through national, international and public private partnerships to support climate smart agriculture. The Programme, therefore, aims to build resilience of agricultural farming systems for enhanced food and nutrition security through six Programmatic Result Areas, namely: Improved Productivity and incomes – a pro-growth and pro-poor development agenda that supports agricultural sustainability and includes better targeting to climate change impacts will improve resilience and climate change adaptation. Because climate change has a negative impact on agricultural production, achieving any given food and nutrition security target will require greater investments in agricultural productivity. It is important that Agricultural growth does not jeopardize soil quality or groundwater resources. Public and private sectors as well as public-private partnerships will play a critical role. Building resilience and associated mitigation co-benefits - CSA will help reduce vulnerability of Tanzania’s agriculture sector by increasing productivity, enhancing adaptation and resilience of the farming systems and reducing emissions intensity in the context of achieving food and nutrition security, sustainable development and poverty reduction. Value Chain Integration - This approach is holistic in that it considers input supply, production, agricultural services, traceability, marketing and business support services as necessary building blocks. Under the approach, both public and private sectors are seen as critical actors in the value chain. Knowledge Tanzania Climate Smart Agriculture Program 2015 - 2025 22 and capacity building are critical strategic priorities to leverage innovations and increase efficiencies. The approach also provides enabling framework for integrating gender and the needs of the youth. Research for Development and Innovations - Although Tanzania has a well- developed agricultural research system, use of modern science and climate smart technologies in agricultural production is still limited. Inadequate research–extension–farmer linkages to facilitate demand-driven research and increased use of improved technologies continue to constrain efforts to increase agricultural productivity as farmers continue to use outdated and ineffective technologies. The role of research will be reoriented to support innovations that facilitate the transition to climate-smart agriculture by smallholder farmers. New and emerging agricultural research partnerships will identify technological advances that respond to the impacts of climate change and climate variability. A major thrust will be on the use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and fisheries intensification, in order to bolster farmers’ adaptive capacity and support the national vision of achieving food security. Improving and Sustaining Agricultural Advisory Services - Agro-advisory services that include climate applications for agriculture will help farmers to better make informed decisions in the face of risks and uncertainties, in addition to the integrated management of present and emerging pests and disease challenges. Climate applications include seasonal weather forecasts, monitoring and early warning products for drought, floods and pests and disease surveillance. These products and services would increase the preparedness of the farmers, well in advance, to cope with risks and uncertainties. In this regard, dissemination of agro-weather advisories and other climate-smart agricultural practices will be enhanced through Public Private Partnerships. Furthermore, robust agro-advisory services would catalyze private sector investment in priority areas such as weather-based index insurance and associated infrastructure. Improved Institutional Coordination – Improved institutional coordination is crucial for achievement of horizontal and vertical integration required for effective discharge of the CSA Programme. The achievement of horizontal integration requires a framework that provides for high-level guidance while vertical integration is instrumental in determining the roles of various sector institutions and devolved governments in performing CSA mandates. The proposed coordination framework will improve Inter-Ministerial and Local Government coordination; enhance partnerships with private sector and civil society organizations; and strengthen coordination with development partners. Tanzania Climate Smart Agriculture Program 2015 - 2025 23 4.0 PROGRAMATIC RESULT AREAS 4.1 Result Area 1: Improved Productivity and Incomes 4.1.1 Component 1: Improved productivity and nutrition Development issues: Low use of CSA technologies and practices in crops, livestock and fisheries by men and women farmers/fisher-folk. Low use of inputs by smallholder men and women farmers. High levels of stunting and high mineral deficiency levels. High poverty levels. Low capacity for adaptation to climate change and variability Poor knowledge on CSA technologies 4.1.1.1 Output 1: Sustainable CSA technologies adopted by smallholder farmers and yields of staple crops (such as maize, rice, sorghum, cassava, potatoes and beans) increased by 50 percent by 2025. Actions: 1. Identify, upgrade, disseminate and practice climate smart technological packages. 2. Introduce improved crop varieties (high yielding, early maturing, disease and pest resistant and nutrient fortified). 3. Increase access to farm inputs (fertilizers/pesticides/seeds/vet drugs) and its wise application/use 4. Strengthen surveillance of agricultural input trade and use. 5. Identification of best indigenous knowledge and its interaction with scientific knowledge to enhance climate change adaptation 6. Train farmers on CSA agronomic practices 4.1.1.2 Output 2: Production of poultry, cattle, small ruminants and pigs increased by 30 percent through adoption of sustainable CSA technologies Actions: 1. Introduce improved livestock breeds (increased productivity, disease resistant and drought tolerant). 2. Undertake genetic characterization and improvement of local livestock breeds. 3. Identify, upgrade, disseminate and practice livestock technological packages. 4. Train farmers on livestock husbandry and disease management. Tanzania Climate Smart Agriculture Program 2015 - 2025 24 4.1.1.3 Output 3: Productivity of aquaculture increased by 50 percent by 2025. Actions: 1. Develop and disseminate best management practices of aquaculture throughout the country. 2. Train fisher folks in good fishing practices. 3. Strengthen fish health and disease surveillance. 4. Strengthen and increase fingerlings breeding and multiplication centers 5. Strengthen integrated fish farming (e.g. in paddy farms) 6. Sensitize and support private sector involvement in fingerling and feed production and distribution 4.1.1.4 Output 4: Stunting and underweight in children as well as micronutrient deficiencies in children and women of reproductive age reduced by 50 percent by 2025. Actions: 1. Promote production and consumption of high quality protein cereals, orange fleshed sweet potatoes (for vitamin A) and leafy vegetables. 2. Develop other high quality staples through breeding – cassava, rice, potatoes etc. 3. Promote fortification of staples during processing (micronutrient fortification and blending products). 4. Educate and train consumers on appropriate food combination 4.1.2 Component 2: Irrigation and agricultural water management Development issues: Overdependence of agriculture on inadequate and erratic rainfall (rain- fed agriculture). Inadequate infrastructure development for irrigation, drainage and water storage Inefficient water use of existing irrigation systems. Low productivity on existing irrigation schemes. Inadequate and un-coordinated information in irrigation research, science and technology. Inadequate operation and maintenance practices of existing irrigation schemes. Limited knowledge on the role of in-situ rainwater harvesting technologies through tillage and Conservation Agriculture. Tanzania Climate Smart Agriculture Program 2015 - 2025 25 4.1.2.1 Output 1: Irrigation schemes productivity increased by 25 percent and integrated farming systems increased by 50 percent by 2025. Actions: 1. Promote development and diffusion of appropriate efficient small-scale irrigation technological packages. 2. Train extension workers on irrigation and water management technologies and skills. 3. Build the capacity of Irrigators Organizations in agricultural water management and their obligations 4. Undertake comprehensive management needs assessment of existing large scale irrigation schemes. 4.1.2.2 Output 2: 1.5 million ha of irrigation developed by 2025 to benefit 2.3 million households. Actions: 1. Review of the National Irrigation Master Plan (2002) and update irrigation potential areas for small scale irrigation systems. 2. Train farmers in the installation, operation and maintenance of recommended irrigation technologies. 3. Establish links to input and output markets and service providers (strengthen value chain and technical backstopping). 4.1.2.3 Output 3: 500,000 ha of integrated farming systems with sustainable water harvesting and management systems developed by 2025 to benefit 700,000 households. Actions: 1. Identify suitable areas for rainwater harvesting and agricultural water management systems. 2. Train farmers/household members in water harvesting and agricultural water management technologies. 3. Facilitate the construction of water harvesting structures at household and community levels. 4. Introduce and promote in-situ rainwater harvesting technologies (e.g. Conservation agriculture) 4.1.3 Component 3: Improved Food Storage and Distribution Development issues: High post-harvest losses along the value chain. Tanzania Climate Smart Agriculture Program 2015 - 2025 26 Low integration of agricultural commodity markets Inadequate cold storage and cool trucks for perishable produce Inadequate agro-processing industries 4.1.3.1 Output 1: Post harvest losses for staple food crops (such as maize, rice, sorghum, cassava, potatoes and beans), horticultural crops, livestock and fish value chains reduced by 30 percent by 2025. Actions: 1. Invest in improved appropriate storage facilities and technologies along the value chain. 2. Promote small scale agro-processing industries in rural areas. 3. Train producers, processers and marketers in post-harvest management. 4. Provide regular market information (deficit/surplus areas) to improve distribution of agricultural commodities/food stuffs. 5. Facilitate establishment of market centres in rural areas with the appropriate infrastructure. 6. Link Region and District by feeder roads to various market centres and highways. 4.1.3.2 Output 2: Private sector capacity enhanced to store 5000 Mt of grain annually and to process and package 50 percent of cereals, cassava and sorghum products annually by 2025. Actions: 1. Strengthen and link the smallholder farmers to the Warehouse Receipt System (WRS) in the grain supply chain. 2. Rehabilitate existing warehouses and silos and establish Public-Private- Partnerships. 3. Support private sector to invest in food processing as well as value addition, including packaging and branding. 4. Facilitate linkages with relevant service providers and markets (inputs and outputs). 4.1.4 Component 4: Increased Growth of Incomes Development issues: Low levels of income from food and cash crop production by smallholder farmers (men, women and youth). Low productivity of animal breeds and low production of improved breeds to meet demand. Tanzania Climate Smart Agriculture Program 2015 - 2025 27 High levels of animal diseases and inadequate feed and water for animals. Limited market linkages for livestock and livestock products. Low production of aquaculture to meet the increasing demand. Limited adoption of integrated farming production systems with potential high incomes. Limited access to input and output markets. Potential for urban and peri-urban agriculture as a source of food and income is under exploited. 4.1.4.1 Output 1: Income from food and cash crop production by men and women increased by 20 percent and 30 percent, respectively by 2025. Actions 1. Build capacity of nursery operators in all crop growing areas and support them to expand and improve quality of seedlings. 2. Build capacity of Quality Declared Seed producers and support them to expand and improve quality of seed. 3. Build capacity of food and cash crop farmers to improve productivity and produce quality. 4. Facilitate contractual arrangements between food and cash crop producers and market/industry. 5. Develop and promote innovative micro-financing packages to facilitate food and cash crop farmers to access credit. 4.1.4.2 Output 2: Income from livestock production by men and women increased by 20 percent and 25 percent respectively by 2025. Actions 1. Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. 2. Facilitate and support the acquisition of improved breeding stocks by men and women farmers. 3. Provide adequate and effective extension knowledge and agro-weather information. 4. Strengthen and/or establish efficient and sustainable animal health and artificial insemination services. 5. Develop and support innovative micro-financing packages to support livestock keepers’ access to credit and markets. 6. Identify areas with acute problem of water for livestock and construct water infrastructures. 7. Facilitate improvement of demarcated grazing lands. 8. Promote use of crop residues and agro-industry byproducts. Tanzania Climate Smart Agriculture Program 2015 - 2025 28 9. Promote value addition for livestock products. 4.1.4.3 Output 3: Income from aquaculture production by men and women increased by 20 percent by 2025. Actions 1. Facilitate and support acquisition of fingerlings by men and women fish farmers. 2. Promote value addition for fish products. 3. Facilitate contractual arrangements between fish farmers and market. 4. Establish and support innovative micro-financing packages to support fisherfolks access to credit. 4.1.4.4 Output 4: Output for Urban and peri-urban agriculture increased by 30 percent by 2025. Actions 1. Support Local Governments to identify and demarcate potential areas within urban and peri-urban areas for agricultural activities. 2. Train urban and peri-urban producers in CSA Practices. 3. Monitor the safety of outputs from urban and peri-urban agriculture. 4. Enforce laws and bylaws related to urban and peri-urban sustainable land use. 4.2 Result Area 2: Building resilience and associated mitigation co- benefits 4.2.1 Component 1: Improve soil health, and restore degraded lands Development issues: Land degradation Soil and water conservation. Soil erosion and nutrient depletion Loss of biodiversity Low capacity at all levels for implementation CSA and SLM practices Low adoption of CSA and SLM technologies and practices at community level Most CSA and SLM activities are of pilot in nature Weak collaboration of relevant ministries and agencies to ensure CSA and SLM up scaling. Tanzania Climate Smart Agriculture Program 2015 - 2025 29 4.2.1.1 Output 1: Adoption of sustainable climate smart technologies and sustainable land management practices by 5 million households by 2025. Actions 1. Promote integrated soil fertility and water management interventions. 2. Establish CSA/SLM knowledge hubs across the country to support adoption of CSA and SLM technologies and practices by men and women that improve soil health and restore degraded lands. 3. Enhance the capacities of private sector service providers and farmer- based organizations to support farmers’ adoption of existing/new/improved CSA and SLM technologies and practices. 4. Develop and integrate CSA and SLM principles into farmer-field schools, primary, secondary and tertiary curriculum. 5. Establish mechanisms for joint planning and implementation of CSA and SLM at the local level. 4.2.1.2 Output 2: Technology dissemination and adoption for scaling up of CSA and SLM promoted by 2025. Actions: 1. Develop and implement sustained awareness creation program on CSA and SLM in addressing soil health and land degradation challenges. 2. Facilitate the development and implementation of at least five (5) small scale CSA Projects annually. 3. Facilitate the dissemination and adoption of CSA and SLM technologies and practices at the farm level across the country through Local Government’s CSA Projects. 4.2.1.3 Output 3: CSA and SLM knowledge to support policy and investment decision making generated and adequately managed by 2025 Actions 1. Establish CSA/SLM Knowledge Platform with disaggregated data on men and women. 2. Document and publicize successful CSA/SLM technologies, practices and interventions. 4.2.2 Component 2: Conservation of Natural Resources and Catchments Development issues: High Deforestation and Forest Degradation Poor Natural forest management including low adoption of Participatory Forest Management Low Forest Plantation area to meet the high wood demand Tanzania Climate Smart Agriculture Program 2015 - 2025 30 Low adoption of Agroforestry/Community Forestry Extensive Land degradation, Soil erosion and siltation High loss of natural and agro- biodiversity Unsustainable Biomass Energy Production and use 4.2.2.1 Output 1: The National REDD+ Strategy implemented in 25 percent of Natural forests in the country by 2025 Actions 1. Upscale Natural Forest Conservation through Participatory Forest Management (PFM) 2. Protect water catchment areas through integrated watershed management. 3. Increase forest cover through natural regeneration, Agroforestry, Reforestation. and Afforestation. 4. Promote best management practices for natural resources management to improve and maximize net benefits for the farmers and other downstream users (e.g. power generation and urban water supply). 5. Promote and support on farm soil conservation activities 6. Promote sustainable production and marketing of charcoal from miombo woodlands 7. Promote sustainable land use management. 4.2.2.2 Output 2: Farm/community forest cover increased by 20 percent by 2025 Actions 1. Develop a business model for ecosystem management in order to facilitate payment for ecosystem services (e.g. tourism revenue used to motivate farmers to conserve wildlife and payment for water in urban areas used to pay farmers for conservation of water catchments). 2. Develop and implement management plans for ecosystems in order to encourage sustainable use 3. Document biodiversity in the ecosystems including below ground biodiversity and develop eco-tourism opportunities in such areas 4. Undertake natural resources accounting for ecosystem services. 5. Identify agroforestry species for different agro-ecological zones and support farmers to increase tree cover 6. Undertake afforestation and reforestation through Public-Private Partnerships. Tanzania Climate Smart Agriculture Program 2015 - 2025 31 4.2.3 Component 3: Insurance and Other Safety Nets Development issues: Vulnerability and increasing risks to climate change. Shifting spatial distribution of events High incidence of poverty making it difficult for small scale farmers to recover after experiencing extreme weather events and climate variability Inadequacy of traditional approaches to risk transfer and risk management. 4.2.3.1 Output 1: Crop and livestock weather-indexed insurance increased by 30 percent by 2025. Actions 1. Develop and implement varied innovative crop and livestock weather- indexed insurance packages. 2. Develop agro-meteorological infrastructure to support weather-indexed insurance and to use them for improved weather and climate information services for farmers. 3. Enhance the capacity of micro-finance institutions to act as agents to deliver innovative crop and livestock weather-indexed insurance packages. 4. Raise awareness within the insurance industry of extreme weather and climate risks and communicate actions and opportunities. 5. Undertake farmer education to address their concerns regarding insurance products with a view to gain their trust 6. Establish livestock insurance schemes and use of insured livestock as collateral 7. Explore ways of using existing and other safety nets such as cash transfers or workfare programmes. 4.2.4 Component 4: Early Warning System and Emergency Preparedness Development issues: Susceptibility of crops, livestock and fisheries to extreme weather events, pests and diseases. Fragmented and inefficient early warning systems. Inadequate systems, knowledge and capacity at household, LGAs and national levels to respond to emergencies. Lack of contingency plans at district level. Tanzania Climate Smart Agriculture Program 2015 - 2025 32 4.2.4.1 Output 1: A Comprehensive Early Warning System and Contingency Plan developed and implemented by 2017 Actions: 1. Prepare vulnerability maps for targeting food security and emergency preparedness interventions. 2. Develop tools to support vulnerable households and communities to establish household community systems that can respond to emergencies (with regards to food insecurity) 3. Monitor crops, livestock and fish pests and diseases. 4. Integrate scientific weather forecasting and indigenous knowledge for early warning and to inform farmer decisions. 5. Establish a National Seed Emergency stock. 6. Improve EWS messages (clear, consistent) that include risk information; designed to link threat levels. 7. Capacity development to farmers on early warning systems and emergency preparedness. 8. Improve mass delivery system particularly on content development and communication channels. 9. Establish a feedback and evaluation process of messages delivered. 10. Develop an effective frame-work for collaboration emergency communication centres/stakeholders. 11. The explicit development of contingency plans on district level is not mentioned as an activity. 4.2.5 Component 5: Synergies in adaptation and mitigation enhanced Development issues: Agriculture sector is a source of GHG emissions Some adaptation actions have mitigation as co-benefits Increased soil carbon has beneficial effects on soil fertility 4.2.5.1 Output 1: Reduction of GHG emissions intensity from the agriculture sector Actions 1. Promote adoption of low cost climate smart technologies that minimize emission of carbon dioxide and enhance soil carbon sequestration. 2. Develop a national carbon accounting and measurement, reporting and verification system. Tanzania Climate Smart Agriculture Program 2015 - 2025 33 4.3 Result Area 3: Value Chain Integration 4.3.1 Component 1: Value addition process for agricultural products Development issues: Most agricultural commodities are sold on the farm as a result the quality is compromised and the farmers obtain low prices. Most of agricultural produce are sold raw and thus bulky with short shelf lives. Lack of supportive infrastructure for agricultural value chain. Disjointed value chains with regards to most agricultural commodities. 4.3.1.1 Output 1: At least two new commercially viable products developed from each of the staple crops, horticultural crops, livestock and fisheries by 2025. Actions 1. Solicit funds for research and innovation into agricultural value chains. 2. Develop improved infrastructure for agricultural value chains. . 3. Institute competitive grant scheme for agriculture value chains. 4. Identify existing value addition technologies and incentivize the private sector to promote them. 4.3.1.2 Output 2: Efficient pilot value chains developed for two selected commodities in each agro-ecological zone. Actions 1. Establish regional hubs (a cluster of livelihood zones in the same AEZ) for value chain development and backstopping. 2. Identify and build capacity of actors in value chain processes. 3. Undertake advanced market feasibility studies to promote demand for the selected commodities. 4. Facilitate linkages to markets for the selected commodities. 4.3.2 Component 2: Increased competitiveness and enhanced integration into domestic, regional and international markets Development issues Low levels of local market penetration by smallholder men and women farmers. Low capitalization of bulk traders. Poor grading and standardization system. Tanzania Climate Smart Agriculture Program 2015 - 2025 34 High consumer preference of imported commodities that have local substitutes. Inadequate volumes with the required specifications and quality to supply the international market. Limited capacity to fully comply with international sanitary and phytosanitary (SPS) standards. 4.3.2.1 Output 1: Marketed output of food and cash crops, livestock and fish products by smallholders increased by 50 percent by 2025. Actions: 1. Create agricultural, livestock and fish commodity hubs through participation of private sector especially micro-financiers and apply viable models of linkage with smallholders. 2. Facilitate capacity building of farmers on demand- and market-driven production. 3. Design and launch a market promotion program for import substitution commodities. 4. Work with supermarkets, hotels and restaurants to participate in selected commodity value chains with a smallholder production base. 4.3.2.2 Output 2: Export of non-traditional agricultural commodities by men and women smallholders increased by 50 percent by 2025 Actions: 1. Identify successful lead private sector firms with access to assured markets and apply viable models of linkage with smallholders. 2. Design sustainable programmes to support the certification of smallholders for export markets. 3. Develop branding of Tanzania produce for regional and international markets. 4.3.2.3 Output 3: Grading and standardization systems of agricultural commodities (crops, livestock and fish) developed and improved. Actions: 1. Develop grading and standardization systems for agricultural commodities that do not have grades and standards 2. Promote the adoption of grading and standardization systems for all agricultural commodities for both domestic and export markets. Tanzania Climate Smart Agriculture Program 2015 - 2025 35 4.4 Result Area 4: Research for Development and Innovations 4.4.1 Component 1: Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain Development issues: Low public expenditure funding into agricultural research. Limited participation of private sector in funding agricultural research and innovations. Poor dissemination and management of agricultural research information. Poor coordination and collaboration among the institutions involved in research. 4.4.1.1 Output 1: Increased funding in research and development and innovations by 50percent by 2025. Actions: 1. Increase public expenditure into research and development and innovations through national budget. 2. Incentivize private sector investments in research and development and innovations. 4.4.1.2 Output 2: Adoption of improved CSA technologies and practices by men and women along the value chain increased by 30 percent by 2025. Actions 1. Conduct participatory research work on improved technologies and practices that is informed by needs of users and agro-ecological zones along the value chain. 2. Conduct on-farm research into low-cost appropriate technologies and practices and deliver them as packages. 3. Build the capacity of extension, producers and other stakeholders in the use of existing/new/improved CSA technologies and practices. 4. Support development of private sector input and appropriate CSA technologies outreach and distribution networks. 5. Intensify field demonstration/field days/study tours to enhance adoption of existing/new/improved CSA technologies and practices. Tanzania Climate Smart Agriculture Program 2015 - 2025 36 4.4.2 Component 2: Research Extension Linkage strengthened and made functional by 2018 Development issues: Poor management and sharing of agricultural research information. Poor packaging of research information for the benefit of farmers. Lack of appropriate platforms for researchers and farmers to interact and share knowledge and experiences. 4.4.2.1 Output 1: Research Extension Linkage and made functional by 2018 Actions: 1. Establish a platform through which researchers will have regular contacts with stakeholders and other users at the national, local and farm levels. 2. Prepare CSA information packages and disseminate them to interested stakeholders using ICT. 4.5 Result Area 5: CSA Knowledge, Extension and Agro-weather Services 4.5.1 Component 1: CSA knowledge generation and dissemination Development issue Fragmented CSA knowledge and understanding of what CSA is. Lack of CSA knowledge Management System across the country. 4.5.1.1 Output 1: Robust CSA Knowledge Management System (Platform/Hub) across the country Actions 1. Undertake a CSA knowledge mapping, audit and analysis. 2. Build CSA knowledge Resource Centre. 3. Develop and maintain a robust and functional CSA knowledge management system. 4. Build capacity to different stakeholders in the agricultural value chain at the national and local levels. Tanzania Climate Smart Agriculture Program 2015 - 2025 37 4.5.1.2 Output 2: Synthesis reports and case studies on CSA best approaches and guidelines prepared and disseminated Actions: 1. Undertake analyses and provide tools to support CSA decision-making. 2. Bundle and provide synthesized information on CSA approaches and case studies on CSA best approaches. 3. Develop and test CSA guidelines and decision-making support tools. 4.5.1.3 Output 3: Multimedia CSA knowledge products, training and communications packages produced Actions: 1. Produce regular CSA information and communication materials for influential stakeholders to support and inform policies, planning and agricultural advisory services. 2. Produce CSA information and communication materials to strengthen capacity of researchers, private sector, CSOs and farmer organizations to influence policy and decision makers. 3. Develop practical guides and applied training materials and packages for training on best practices for CSA. 4.4.5.4 Output 4: CSA knowledge networks and partnerships strengthened Actions: 1. Strengthen CSA knowledge and information sharing networks/forums. 2. Develop a portfolio of information sharing technology tools to support sharing of CSA information and learning resources. 3. Establish CSA knowledge partnerships on knowledge generation, sharing and mobilization with governments, international organizations, research institutions, farmer organizations, private sector and civil society organizations. 4.5.2 Component 2: Enhance extension, climate information services and agro- weather advisories Development issues Low use of climate information services and agro-weather advisories in agricultural planning and farm management decision making (Highly inadequate agro-climate information services and inappropriate agro- weather products) Low reliability and availability of climate information Tanzania Climate Smart Agriculture Program 2015 - 2025 38 Role of climate change and weather variability in the increased post- harvest losses, and increased energy use, along value chains are not clearly known Low integration of climate research with agricultural research, Poor knowledge on weather data processing, packaging and timely dissemination. 4.5.2.1 Output 1: Agro-climate information services and timely-use of agro- weather products increased by 40 percent by 2025. Actions: 1. Identify appropriate climate/weather services and products for small scale farmers 2. Apply user friendly software such as INSTAT to generate products for improving smallholder decision making. 3. Promote integrated weather observation for improving availability and reliability of climate information. 4. Digitize historical climate data to enhance availability and accessibility of climate information. 5. Downscaling forecasted weather to various localities to promote the appropriate climate/weather services and products for small scale farmers, and pre-season dissemination of agro weather advisories 6. In-season community agro-weather monitoring and post-season agro- weather review 7. Upscale the mobile phone based early warning system. 8. Strengthen integration of climate research with agricultural research 9. Training of Regional Coordinators on CSA 4.6 Result Area 6: Improved Institutional Coordination 4.6.1 Component 1: Improve Inter-Ministerial and Local Government Coordination Development issue: Inadequate inter-ministerial coordination including collaboration with PMO Disaster Management Department. Inadequate coordination between national and local governments on agriculture related issues. Low capacity for cross-sectoral planning. Ineffective communication within and between ministries. Tanzania Climate Smart Agriculture Program 2015 - 2025 39 4.6.1.1 Output 1: A joint platform for collaboration between ministries responsible agriculture, livestock, fisheries, environment, forestry, water, finance and planning established and strengthened by end of 2015. Actions: 1. Develop and implement an inter-ministerial communications strategy with respect to inter-ministerial coordination on matters relating to climate smart agriculture. 2. Introduce a biannual joint planning and review session between inter- ministerial team and the country government officials responsible for agriculture. 3. Train national and local government staff in cross-sectoral planning and implementation. 4. Build policy review and analytical capacity at the national and local levels. 5. Strengthen the planning, implementation, monitoring and evaluation at the national and local levels. 6. Establish a framework for disseminating CSA programmatic planning and implementation as well as annual reports and studies and receiving feedback at national and local levels. 4.6.2 Component 2: Partnerships with private sector and civil society organizations Development issue: Lack of structured framework for private sector and CSOs to engage national and local governments on CSA issues. Inadequate incentives for private sector to invest in CSA. 4.6.2.1 Output 1: A platform for private sector and CSOs engagement with national and local governments established and strengthened by end of 2017. Actions: 1. Engage private sector to identify opportunities for increased investments in CSA. 2. Organize regular consultative meetings with private sector and CSOs on the planning and implementation of the CSA Program. 3. Identify appropriate incentives to catalyze private sector and CSO investments in CSA activities. 4. Publicize the Country CSA Program to private sector and CSOs with a view to identifying areas for their participation. Tanzania Climate Smart Agriculture Program 2015 - 2025 40 5. Establish communication channels for consultations between private sector and CSOs in the programmatic planning and implementation of CSA activities at the national and local levels 4.6.3 Component 3: Programmatic Coordination with Development Partners strengthened Development issue: Fragmented projects/programmes on CSA or CSA-related initiatives. Varied financial management, procurement, monitoring and evaluation systems. Weak ownership of intervention at the national and local levels. 4.6.3.1 Output 1: GoT – Development Partner Coordination and Collaboration strengthened and Development Partners fund a common Country CSA Program by end of 2015 Actions: 1. Harmonize GoT and development partners’ investments in climate smart agriculture through a common Country (National) CSA Program. 2. Strengthen collaboration between GoT and the Development Partners’ Agriculture Coordination Group (with a standing agenda item programmatic planning and implementation of CSA Program). Tanzania Climate Smart Agriculture Program 2015 - 2025 41 5.0 COORDINATION FRAMEWORK 5.1 Institutional Arrangements The National Climate Change Technical Committee (NCCTC) and National Climate Change Steering Committee (NCCSC) will guide the coordination and implementation of the CSA Program. The NCCTC shall provide technical advice to the National Climate Change Focal Point (NCCFP) in the Vice President’s Office – Division of Environment, while the NCCSC shall provide policy guidance and ensure coordination of Programmatic Result Areas as well as cross-sectorial participation. The MAFC Environment Management Unit (EMU) will be the implementation Sector focal point for the Country CSA Program. In that case Head of EMU is responsible and accountable for ensuring the smooth implementation of the Country CSA Program. The main constraint is that EMU does not currently have a budget allocation for climate change activities including CSA. The National Climate Smart Agriculture Task Force (NCSATF) formed under the EAC directives with a broad range of government and non-governmental stakeholders will have an overall responsibility for coordination and delivery of the expected Programmatic Result Areas outcomes. Hence, NCSATF will monitor implementation of the Country CSA Program, serve as a vital coordination function between MAFC, MDAs, NSAs, and regional entities such as the EAC, SADC, COMESA and issue directives to all relevant MAFC departments and units for implementing Programmatic Result Areas. 5.2 Coordination of Activities Coordination mechanism of different activities that will be implemented by different sectors involved in the promotion of CSA practices is highlighted in Figure 10. Tanzania Climate Smart Agriculture Program 2015 - 2025 42 Figure 14: Coordination mechanism among the different implementers of CSA practices Tanzania Climate Smart Agriculture Program 2015 - 2025 43 6.0 ROLES AND RESPONSIBILITIES OF DIFFERENT SECTORS The implementing partners of the Country CSA Program will have different roles and responsibilities as highlighted in the following table: 6.1 MAFC and MANR Divisions and Units All MAFC and MANR Divisions/Units will be instrumental in implementing the Country CSA Program as well, and include technical and research units at the national and sub-national levels. Of particular importance is the Department of Policy and Planning (DPP) under MFC– as the entity with responsibility for strategic planning and policy development, will need to assist with ensuring that resources are allocated for the program implementation. The ICT unit will have a key role in managing the developed ACRP website where all the information and communication- on CSA will be done. Technical divisions/departments will have a key role in implementing Programmatic Result Areas. Importantly MAFC will work closely with major agricultural programmes and initiatives related to agriculture as well as climate change, including the ASDP-2 Secretariat, the Big Results Now Presidential Delivery Bureau- and the SAGCOT Centre to promote the implementation of the Programmatic Result Areas. Large agriculture programmes and initiatives are well placed to promote climate resilience, pilot innovations, and reduce the environmental impacts of the sector that can drive climate vulnerability. 6.2 Ministries, Departments and Agencies (MDAs) Several other MDAs are linked with agricultural activities and necessary for implementation of CSA activities for building resilience in the agriculture sector. MAFC will be responsible for forging links with these MDAs and incentives to coordinate. It will be important for other sectors with linked activities to coordinate with MAFC, as their action plans are developed to identify opportunities to link activities, since climate change is an issue that cuts across sectors. 6.3 Non-State Actors Non-State Actors, including research institutions, universities, the private sector, NGO and CSOs, and Development Partners include key stakeholders that can contribute to fulfilling research needs, providing financial resources, and technical assistance toward implementation of the Country CSA Program. MAFC will need to coordinate closely especially with NGOs who are working in the field and are on the front line of practices that can be scaled up with additional support. Tanzania Climate Smart Agriculture Program 2015 - 2025 44 6.4 Sub-National Entities Sub-national entities will be key recipients of Programmatic Result Areas, including training, finance, and technical assistance, but much of the Result Areas implementation will rest at the sub-national level as well. Entities such as District-level Local Government Authorities, District Irrigation Development Teams, Zonal Plant Health Centres, regional Agricultural Research Institutes, and River Basin Offices will all play a role in each of the Programmatic Result Areas actions. Table 6: Roles and Responsibilities of Different Sectors ORGANIZATION/ STAKEHOLDER ROLES/ RESPONSIBILITY COMPARATIVE ADVANTAGE TARGET WHAT THEY CAN DO FOR CSA COUNTRY PROGRAMME VPO / 1st VP (Zanzibar) Climate Change Focal Point Climate Change Expertise Climate Change adaptation and mitigation Technical support by Climate Change Secretariat MAFC Coordination Monitoring and Evaluation Technical Expertise Productivity and food security Technical and financial support Monitoring and Evaluation MANR (Zanzibar) Co-coordination Technical Expertise Productivity and food security Technical and financial support National Climate Smart Agriculture Taskforce (NCSATF) Solicit funds, information sharing Technical Expertise Climate Smart Agriculture adoption Mainstreamin g and adoption MoF Climate financing Financial Expertise Climate finance Technical and financial support MNRT, MLFD, PMO- RALG, NEMC, TMA, MITM, MoW, MEM, Planning Commission, MLHHS, Policy formulation, capacity building, monitoring and evaluation, technical backstopping on CSA - Technical Expertise - Physical and financial resources Service provision, CC adaptation and mitigation Enabling environment Regional Secretariat Coordination of LGAs Linkage between Sector Ministries and LGAs Monitoring and evaluation Coordination mechanism Provide linkage Coordination and reporting LGAs Policies / strategies / programmes Nationwide coverage in implementation Adoption of CSA technologies Dissemination Tanzania Climate Smart Agriculture Program 2015 - 2025 45 ORGANIZATION/ STAKEHOLDER ROLES/ RESPONSIBILITY COMPARATIVE ADVANTAGE TARGET WHAT THEY CAN DO FOR CSA COUNTRY PROGRAMME implementers Formulation of by - laws and practices Research Institutions / Academia Research and technology development High tertiary level Training (short and long-term) Scientific knowledge management Scientific expertise Training capacity Access to new scientific knowledge Infrastructure International collaboration Identification and development of sustainable CSA technologies Research on improving CSA technologies Technology evaluation, improvement and validation, Disseminatio n of innovative CSA technologies to different to agro- ecological zones NGOs, CBOs, FBOs Dissemination of CSA extension packages/ awareness raising Close to the community, lobbying and advocacy on CSA related matters Adoption of CSA technologies and practices, awareness creation Dissemination Private Sector (TCCIA, ANSAF, etc.) Resource mobilization Entrepreneursh ip investment facility, input supply, credit facility Investment and business opportunities Financial support Development Partners Resource mobilization, technical assistance Technical expertise Financial resources Climate Change adaptation and mitigation Financial and technical support Regional initiatives (CCAFS, COMESA, EAC and SADC) Resource mobilization, technical assistance Technical expertise Financial resources Climate Change adaptation and mitigation Financial and technical support Tanzania Climate Smart Agriculture Program 2015 - 2025 46 7.0 MONITORING AND EVALUATION Participatory Monitoring and Evaluation (PM&E) framework that ensures the project targets are met and learning achieved will be an emphasis of the proposed investment plan. Capacity building in PM&E and mentoring process for site team and other core members will be done in each target area. The process will include participatory monitoring and tracking of major outcomes for each specific objective. The PM&E will serve several functions such as tracking progress, learning and change as well as collecting data for answering key questions, and for project management. Technical and financial reports will be delivered on an agreed-upon schedule to communicate progress to the different stakeholders. The reporting framework including the content of reports, frequency of submission, responsible parties and target recipients will be developed and agreed between parties involved. As mentioned in the previous sections this is a multi-partner programme involving the central government, local government, private sector and non-governmental organisations. The tools for M&E will include the programme log frame and annual work plan and budget. Audit of project activities constitutes part of M&E system. Activity Based Result framework is attached as annex VII. Tanzania Climate Smart Agriculture Program 2015 - 2025 47 8.0 TEN - YEAR PROGRAMME FINANCING FRAMEWORK The CSA programme document is mainly intended to be a guiding document that will be used to leverage financial support from the Government of Tanzania and various Development Partners. It is in particular anticipated that most of the activities will carried out as separate projects with detailed operationalization narratives and budgets. Prior to, and during the Stakeholders’ Validation workshop, different Development Partners have expressed interest in funding various components depending on their priorities. As such the document therefore broadly identify focus areas where funding during the next 10-years should be directed. The sustainability of CSA programme is mainly based on the premise that activities under different focus areas will be mainstreamed in various plans of the different ministries and other stakeholders. 8.1 Cost Estimates and indicative Financing Plan Table 7 shows cost estimates of US $32.158 Million projected over ten years in nominal terms. Budget for first three years are higher due the needed investment in terms of infrastructure and equipment. However, this figure is only indicative and does not prescribe a limit. Tanzania Climate Smart Agriculture Program 2015 - 2025 48 Table: 7. Summary of CSA Cost Estimates for 10 Years Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total A: Investment 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 B: Components 1.1 Improved productivity and nutrition 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 1.2 Irrigation and water management 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 1.3 Improved Food Storage and Distribution 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 1.4 Increased Growth of Incomes 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 2.1 Improve soil health and restore degraded lands 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 2.2 Conservation of Natural Resources and Catchments 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 2.3 Insurance and Other Safety Nets 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.4 Early Warning System and Emergency Preparedness 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 2.5 Synergies in adaptation and mitigation enhanced 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 3.1 Development of new agricultural products 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 3.2 Increased competitiveness and enhanced integration into domestic, regional and international markets 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 4.2 Research Extension Linkage strengthened and made functional by 2018 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 5.1 CSA knowledge generation and dissemination 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 5.2 Enhance extension, climate information services and agro- weather advisories 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 6.1 Improve Inter-Ministerial and Local Government Coordination 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 6.2 Partnerships with private sector and civil society organizations 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 6.3 Programmatic Coordination with Development Partners strengthened 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 GRAND TOTAL 6,347,000 5,272,000 5,364,000 3,979,000 3,284,000 2,521,000 2,194,000 2,154,000 1,904,000 1,889,000 32,158,000 BASE COSTS IN US$ Summary Cost by Component Tanzania Climate Smart Agriculture Program 2015 - 2025 49 ANNEXES Annex I: Tanzania Map Tanzania showing regional and international boundaries Tanzania Climate Smart Agriculture Program 2015 - 2025 50 Annex IIa: Tanzania Agricultural Zones Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season COAST North: Tanga (except Lushoto), Coast and Dar- es- Salaam Infertile sands on gently rolling uplands, Alluvial soils in Rufiji, Sand and infertile soils Under 3000 North: Bimodal, 750- 1200mm October- December and March- June South: Eastern Lindi and Mtwara (except Makonde Plateau) Fertile clays on uplands and river flood plains South: Unimodal, 800- 1200mm December- April ARID LANDS North: Serengeti, Ngorongoro Parks, Part of Masai land North: Volcanic ash and sediments. Soils variable in texture and very susceptible to water erosion 1300- 1800 North: Unimodal, unreliable, 500-600mm March- May Masai Steppe, Tarangire Park, Mkomazi Reserve, Pangani and Eastern Dodoma South: Rolling plains of low fertility. Susceptible to water erosion. Pangani river flood plain with saline, alkaline soil 500-1500 South: Unimodal and Unreliable, 400-600mm SEMI-ARID LANDS Central Dodoma, Singida, Northern Iringa, some of Arusha, Shinyanga Central: Undulating plains with rocky hills and low scarps. Well drained soils with low fertility. Alluvial hardpan and saline soils in Eastern Rift Valley and lake Eyasi. Black cracking soils in Shinyanga. 1000- 1500 Central: unimodal and unreliable: 500-800mm December - March Tanzania Climate Smart Agriculture Program 2015 - 2025 51 Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season Southern: Morogoro (except Kilombero and Wami Basins and UluguruMts).Also Lindi and Southwest Mtwara Southern: Flat or undulating plains with rocky hills, moderate fertile loams and clays in South (Morogoro), infertile sand soils in centre 200-600 South-eastern: Unimodal 600- 800mm PLATEAUX Western: Tabora, Rukwa (North and Centre), Mbeya Western: Wide sandy plains and Rift Valley scarps 800-1500 Western: unimodal, 800- 1000mm November- April North: Kigoma, Part of Mara Flooded swamps of Malagarasi and Ugalla rivers have clay soil with high fertility 1,500- 1,700 Southern: Ruvuma and Southern Morogoro Southern: upland plains with rock hills. Clay soils of low to moderate fertility in south, infertile sands in North. 500- 2,000 Southern: unimodal, very reliable, 900- 1300mm SOUTHERN AND WESTERN HIGHLANDS Southern: A broad ridge of from N. Morogoro to N. Lake Nyasa, covering part of Iringa, Mbeya Southern: Undulating plains to dissected hills and mountains. Moderately fertile clay soils with volcanic soils in Mbeya 1200- 1500 Unimodal, reliable, local rain shadows, 800-1400 December – April South-western: Ufipa plateau in Sumbawanga South-western: Undulating plateau above Rift Valleys and sand soils of low fertility 1400- 2300 Unimodal, reliable, 800- 1000 November- April Western: Along the shore of Lake Tanganyika in Kigoma and Kagera Western: North-south ridges separated by swampy valleys, loam and clay soils of low fertility in hills, with alluvium and ponded clays in the valleys 100-1800 Bimodal, 1000- 2000 October- December and February- May Tanzania Climate Smart Agriculture Program 2015 - 2025 52 Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season NOTHERN HIGHLANDS Northern: foot of Mt. Kilimanjaro and Mt. Meru. Eastern Rift Valley to Eyasi Northern: Volcanic uplands, volcanic soils from lavas and ash. Deep fertile loams. Soils in dry areas prone to water erosion. 1,000- 2,500 Bimodal, varies widely 1000- 2000 November- January and March-June Granite MtsUluguru in Morogoro, Pare Mts in Kilimanjaro and UsambaraMts in Tanga, Tarime highlands in Mara Granite steep Mountain side to highland plateaux. Soils are deep, arable and moderately fertile on upper slopes, shallow and stony on steep slopes 1,000- 2,000 Bimodal and very reliable 1000-2000 October- December and March- June ALLUVIAL PLAINS Kilombero (Morogoro) Cental clay plain with alluvial fans east and west 750-1200 Unimodal, very reliable, 900- 1300 November- April Rufiji (Coast) Wide mangrove swamp delta, alluvial soils, sandy upstream, loamy down steam in floodplain <500 Unimodal, often inadequate 800-1200 December- April Usangu (Mbeya) Seasonally Flooded clay soils in North, alluvial fans in South 2,400- 5,000 Unimodal, 500- 800 December- March Wami (Morogoro) Moderately alkaline black soils in East, alluvial fans with well drained black loam in West 400- 1,000 Unimodal, 600- 1800 December- March Source: Modified from de Pawn, 1984 Tanzania Climate Smart Agriculture Program 2015 - 2025 53 Annex IIb: Tanzania Agricultural Map Source: SUA Tanzania Climate Smart Agriculture Program 2015 - 2025 54 Annex III: Agricultural production ‘000 Metric Tons Year 2003/0 4 2004/0 5 2005/0 6 2006/0 7 2007/0 8 2008/0 9 2009/1 0 2010/1 1 2011/1 2 2012/1 3 2013/14 * Maize 3,157 3,219 3,423 3,302 3,556 3,326 4,475 4,341 5,104 5,288 6,734 Sorghum 757 714 712 971 861 709 789 807 839 782 883 Millets 201 221 228 194 203 220 372 312 214 292 363 Rice 688 759 805 872 875 868 1,700 1,461 1,170 1,342 1,681 Wheat 67 102 110 83 92 95 62 113 109 102 167 Pulses 879 886 1,050 1,156 1,126 1,116 1,254 1,632 1,827 1,871 1,697 Cassava 1,480 1,846 2,053 1,733 1,797 1,972 1,464 1,549 1,821 1,878 1,664 Bananas 734 991 1,169 1,028 982 1,073 975 1,048 842 1,317 1,064 Potatoes 874 931 1,396 1,322 1,379 1,392 1,231 1,710 1,418 1,808 1,761 Crop Metric Tons 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 Tea 32,000 30,000 34,446 32,698 34,165 33,160 35,000 33,000 33,700 33,000 Sugarcane 229,620 263,317 192,535 265,434 276,605 279,850 317,000 260,055 286,380 293,011 Tobacco 51,970 56,500 65,299 55,567 58,702 60,900 78,000 126,624 74,240 100,000 Cotton 344,210 376,591 130,565 200,662 368,229 267,004 260,000 225,938 351,151 246,767 Pyrethrum 1,000 2,800 1,500 2,800 3,280 3,320 5,000 5,700 6,100 7,000 Sisal 26,800 27,794 30,934 33,039 33,208 26,363 35,000 33,406 23,344 41,104 Coffee 54,000 34,334 48,869 43,000 62,345 40,000 60,575 33,219 71,200 48,599 Cashew 81,600 77,158 92,232 99,107 79,068 74,169 121,070 160,00 121,704 127,939 Tanzania Climate Smart Agriculture Program 2015 - 2025 55 Crop 2008/2009 2009/10 2010/11 2011/12 2012/13 2013/14 Fruits 557,400 3,297,910 3,751,170 3,938,730 4,096,280 4,416,690 Vegetables 602,000 766,570 858,740 901,680 937,750 1,005,305 Flower 8,670 9,100 9,850 10,200 10,790 Spices 6,865 7,150 7,370 8,125 8,377 Source: BEST, 2014 Tanzania Climate Smart Agriculture Program 2015 - 2025 56 Annex IV: Agriculture Sector Financing Gap (TShs) 2010/2011 – 2014/2015 Annex V: Resource Requirement for Zanzibar Tanzania Climate Smart Agriculture Program 2015 - 2025 57 Annex VI: Wood Fuel Demand and Consumption Wood Fuel Demand (2012) Woodfuel Demand Firewood Charcoal Total Charcoal & Firewood in m3 Fuel Wood (mi) Tonnes (mi) M3 Fuel wood (mi) Tonnes (mi) M3 Fuel wood equiv (mi) Rural 20.97 29.96 0.52 3.88 33.83 Urban 1.64 2.34 1.51 11.38 13.72 Total 22.60 32.29 2.03 15.26 47.55 Source: Adapted from BEST, 2014 Tanzania Fuel Wood Consumption by household (2012) Area Total Population percent Population using wood No. using wood Dar es Salaam 4,364,541 3.0 percent 130,936 Other Urban 7,316,739 19 percent 1,381,334 Rural 33,246,720 90.0 percent 29,922,048 Total 44,928,000 70.0 percent 31,434,318 Sources: National Bureau of Statistics 2002 and 2012 Census, and 2007 Household Budget Survey, and Tanzania Commission for AIDS, Tanzania HIV/AIDS and Malaria Indicator Survey 2011-12 (NBS, 2007, NBS, 2009, NBS, 2013b and TACACIDS, 2013) Tanzania Climate Smart Agriculture Program 2015 - 2025 58 Annex VII: Logical Framework Matrix or Program Design Matrix Verifiable Indicators Source of Verification Assumptions Overall Goal Tanzania achieves enhanced sustainable productivity, climate resilience and food security for the agricultural sector growth CSA Policy index (CSA-Pol) CSA Results index (CSA-Res) Specialized targeted surveys End of Program evaluation Report Available policies to support CSA Available services and infrastructure to support CSA Governments continue to support agriculture and poverty reduction as priorities Equitable distribution of benefits occurs PDO (Purpose) The PDO is: A: Enhanced climate resilience of agricultural and food systems B: CSA Program - Strengthens policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture C: Enhance collaboration in CSA related activities among ministries, agencies institutions and private sector service providers % of farming communities practicing CSA (disaggregated by gender) Rate of change of adoption of sustainable climate smart technologies and sustainable land management practices (disaggregated by type) – (in %) Rate of increase in CSA information and knowledge transfer among stakeholders Rate for adaptation to climate change and variability End of Program evaluation Report Mid-Term Reports Quarterly Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 59 Verifiable Indicators Source of Verification Assumptions Tanzania CSA programs accesses climate financing and uses it effectively to support climate change resilience and low carbon sustainable growth Level of stakeholder satisfaction with the CSA technologies and innovations (%) by number of products users (by gender, age, and location) Transparent national Climate Change financing mechanism established Intermediate Outcomes Component 1: Improved Productivity and incomes CSA Program has enhanced use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and fisheries intensification New CSA practices developed relative to plan (%) Number of Sustainable CSA technologies adopted by smallholder farmers Increased annual yields of targeted crops (such as maize, rice, sorghum, cassava, potatoes and beans, aquaculture and livestock Percent of farmers using improved inputs. Number of extension officers and management of Irrigators Evaluation Reports Annual Reports Communication priority setting document Annual survey reports. Mid Term Reports Review Missions Implementation support Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 60 Verifiable Indicators Source of Verification Assumptions Organization trained. Number of farmers trained on irrigation technologies % increase in irrigated land Number of irrigation schemes constructed to its full potentiality. % increase in Income from crop, livestock, aquaculture production by men and women Component 2: Building resilience and associated mitigation co-benefits Strengthened policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture in identified priority areas. Number of evidence based policy responses to food insecurity adopted Number of established CSA/SLM Knowledge Platforms with disaggregated data on men and women. Number of villages with land use plan. Number of small scale CSA projects implemented annually. % change in Farm/community forest cover Quarterly Reports Annual survey reports. Evaluation Reports CSA Program Annual Reports Specialized survey Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 61 Verifiable Indicators Source of Verification Assumptions Rate of Adoption of sustainable climate smart technologies and sustainable land management practices Number of generated CSA and SLM knowledge to support policy and investment decision making % change in Crop and livestock weather-indexed insurance Reduction of GHG emissions intensity from the agriculture sector (%) Component 3: Value Chain Integration Availability of infrastructure to support value addition, marketing, trade and postharvest management. Number of new commercially viable products developed from each of the staple crops, horticultural crops, livestock and fisheries Number of Efficient pilot value chains developed for selected commodities in each agro-ecological zone Value and Quantity of Marketed output of food and cash crops, livestock and fish products by smallholders Quarterly Reports Evaluation Reports Annual Reports Mid Term Reports Review Missions Implementation support Reports TRA data. Annual survey reports Partnerships and platforms with adequate capacity for generation and uptake of technologies and innovations exist Government, non- government, regional and national organizations operate effectively at appropriate levels. Tanzania Climate Smart Agriculture Program 2015 - 2025 62 Verifiable Indicators Source of Verification Assumptions Value of Export of non-traditional agricultural commodities by men and women smallholders Established Grading and standardization systems of agricultural commodities Component 4: Research for Development and Innovations Generated and disseminated improved land management and gender sensitive climate resilient agricultural practices and technologies in targeted areas Hectares of land managed under climate-resilient practices Number of CSA technologies developed Increased funding in research and development and innovations % adoption of improved CSA technologies and practices by men and women along the value chain Quarterly Reports Publications Mass media Evaluation Reports Annual survey reports Annual Reports Mid Term Reports Review Missions Implementation support Reports Diagnostic Survey Reports Agricultural research in support of CSA Conducive policy environment maintained Component 5: Improving and Sustaining Agricultural Advisory Services Knowledge on Climate Smart Agriculture documented and scaled up and out in targeted areas. Number of existing and new CSA practices disseminated targeted areas Number of Ward Resource Centres equipped with CSA knowledge. Quarterly Reports Publications Mass media Annual survey reports. Evaluation Reports Annual Reports Mid Term Reports Government, non- government, regional and national organizations operate effectively at appropriate levels. Conducive policy environment maintained Partnerships and platforms Tanzania Climate Smart Agriculture Program 2015 - 2025 63 Verifiable Indicators Source of Verification Assumptions Number of demand-driven gender- responsive CSA made available to uptake pathways Number of technology uptake pathways (e.g. web-based information platform, radio, TV program, etc.) compared to plan. Established robust CSA Knowledge Management System (Platform/Hub) across the country Number of synthesis reports and case studies on CSA best approaches and guidelines prepared and disseminated % increase in agro-climate information services and timely-use of agro-weather products Level of satisfaction of stakeholders with the technology uptake pathways (%) Number of stakeholders whose capacity building needs have been addressed Number of networks and stakeholder Review Missions Implementation support Reports with adequate capacity for generation and uptake of technologies and innovations exist Primary schools leavers with CSA knowledge and practice Tanzania Climate Smart Agriculture Program 2015 - 2025 64 Verifiable Indicators Source of Verification Assumptions platforms Number of staff trained (short-term and study tours) and applying skills acquired in conducting CSA practices Component 6: Improved Institutional Coordination Coordination and management of CSA activities and initiatives in all implementing agencies enhanced Number of Climate Change plans developed in key sector ministries, private sector Percent of CSA Program activities implemented according to plan. Harmonized M&E system for CSA Program developed, adopted, and implemented according to plan (%). Established effective joint platform for collaboration between ministries responsible agriculture, livestock, fisheries, environment, forestry, water, finance and planning Number of relevant policies, laws, regulations, and/or procedures reviewed for harmonization Level of compliance with the Environment and Social Safeguards. Evaluation Reports Annual Reports Mid Term Reports Review Missions Implementation support Reports Quarterly Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 65 Footnote: 1. The CSA-Pol reflects the most significant aspects of the enabling environment for implementing CSA at the national level. 2. The CSA-Res indicators provide an understanding about the short-term to medium-term results of a CSA intervention which may relate to food security, poverty reduction and environmental sustainability. Tanzania Climate Smart Agriculture Program 2015 - 2025 66 Annex VIII: Budget Estimates for 2015 - 2025 Activities Expendit ure Account Unit of measure Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Unit Cost (in US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total Rehabilitate existing warehouses and silos Works Set 0 2 2 1 0 30,000 0 60,000 60,000 30,000 0 0 0 0 0 0 150,000 Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. Works Set 1 1 1 0 0 100,000 100,000 100,000 0 0 0 0 0 0 0 0 200,000 Develop agro-meteorological infrastructure to support weather-indexed insurance Works Unit 0 2 2 0 0 150,000 0 300,000 300,000 0 0 0 0 0 0 0 600,000 Construction of water harvesting structures at household and community levels. Works Unit 5 5 5 5 5 5 5 50,000 0 250,000 250,000 250,000 250,000 250,000 250,000 250,000 100,000 710,000 610,000 280,000 250,000 250,000 250,000 250,000 0 0 950,000 Procurement of office equipment/a Goods Unit 24 0 12 0 0 15 50,000 1,200,000 0 600,000 0 0 0 0 0 0 1,800,000 Procurement of vehicles Goods Unit 10 0 0 5 0 10 50,000 500,000 0 0 250,000 0 0 0 0 0 0 750,000 1,700,000 0 600,000 250,000 0 0 0 0 0 0 2,550,000 Short term courses Study tour Tour Lump sum 60 50 50 50 0 5,000 300,000 250,000 250,000 250,000 0 0 0 0 0 0 1,050,000 short-term training Training Lump sum 50 50 50 50 50 20 20 20 20 3,000 150,000 150,000 150,000 150,000 150,000 0 0 0 0 0 750,000 0 0 0 0 0 0 0 0 0 0 0 450,000 400,000 400,000 400,000 150,000 0 0 0 0 0 1,800,000 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 ** Footnotes: a/ Computer set= computer, printer, scanner and accessories, photocopiers, GPS Total Cost Physical and Human Resources BASE COSTS US$ 1.1. Physical resources Quantities A: Investment 1.2: Human resources Sub Total Civil Works Sub Total Office Equipments Sub Total Human Resources 1.1.2: Office equipments 1.1.1: Civil works 1.2.2: Trainings and tours Tanzania Climate Smart Agriculture Program 2015 - 2025 67 4.1 Improved Productivity and Incomes Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total Identify, upgrade, disseminate and practice climate smart technological packages service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Introduce improved crop varieties (high yielding, early maturing, disease and pest resistant and nutrient fortified) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Increase access to farm inputs (fertilizers/pesticides/seeds/vet drugs) and its wise application Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen surveillance of agricultural input trade and use Service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 600,000 Identification of best indigenous knowledge and its interaction with scientific knowledge to enhance climate change adaptation Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Train farmers on CSA agronomic practices Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Introduce improved livestock breeds (increased productivity, disease resistant and drought tolerant) Service Lumpsum 1 2 2 1 1 0 0 0 0 0 30,000 30,000 60,000 60,000 0 0 0 0 0 0 0 150,000 Undertake genetic characterization and improvement of local livestock breeds Service Lumpsum 1 1 1 1 1 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 200,000 Identify, upgrade, disseminate and practice improved livestock technological packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 40,000 40,000 40,000 40,000 0 0 0 0 0 0 0 120,000 Train farmers on livestock husbandry and disease management Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Develop and disseminate best management practices of aquaculture throughout the country Service Lumpsum 1 1 1 1 1 1 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 210,000 Train fisher folks in good fishing practices Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Strengthen fish health and disease surveillance Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Strengthen and increase fingerlings breeding and multiplication centers Service Lumpsum 1 1 1 1 0 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 0 160,000 Sensitize and support private sector involvement in fingerling and feed production and distribution Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Strengthen integrated fish farming (e.g. in paddy farms) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote production and consumption of high quality protein cereals, orange fleshed sweet potatoes (for vitamin A) and leafy vegetables Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Develop other high quality staples through breeding – cassava, rice, potatoes etc Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote fortification of staples during processing (micronutrient fortification and blending products) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Educate and train consumers on appropriate food combination Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 Unit Cost (in US$) Sub Total BASE COSTS IN US$ Component Activities Quantities 4.1.1 Improved productivity and nutrition Expenditure Account Unit of measure Tanzania Climate Smart Agriculture Program 2015 - 2025 68 Promote development and diffusion of appropriate efficient small-scale irrigation technological packages. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Train extension workers on irrigation and water management technologies and skills. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Build the capacity of Irrigators Organizations in agricultural water management and their obligations Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Undertake comprehensive management needs assessment of existing large scale irrigation schemes. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Review of the National Irrigation Master Plan (2002) and update irrigation potential areas for small scale irrigation Service Lumpsum 1 1 0 0 0 0 0 0 0 0 35,000 35,000 35,000 0 0 0 0 0 0 0 0 70,000 Train farmers in the installation, operation and maintenance of recommended irrigation technologies Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Establish links to input and output markets and service providers (strengthen value chain and technical backstopping). Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Identify suitable areas for rainwater harvesting and agricultural water management systems. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Train farmers/household members in water harvesting and agricultural water management technologies. Service Lumpsum 1 1 1 1 1 1 1 1 1 0 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 0 135,000 Facilitate the construction of water harvesting structures at household and community levels. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Introduce and promote in-situ rainwater harvesting technologies (e.g. Conservation agriculture) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 450,000 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 4.1.2 Irrigation and water management Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 69 Invest in improved appropriate storage facilities and technologies along the value chain. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 200,000 Promote small scale agro-processing industries in rural areas. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Train producers, processers and marketers in post-harvest management. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Provide regular market information (deficit/surplus areas) to improve distribution of agricultural commodities/food stuffs. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Facilitate establishment of marketing centres in rural areas with the appropriate infrastructure. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Link Region and District by feeder roads to various marketing centres and highways. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Strengthen and link the smallholder farmers to the Warehouse Receipt System (WRS) in the grain supply chain. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 180,000 Establish Public-Private-Partnerships management. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Support private sector to invest in food processing, pasture and pasture seed production as well as value addition, Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Facilitate linkages with relevant service providers and markets (inputs and outputs). Service Lumpsum 1 1 1 1 1 1 0 0 0 0 12,000 12,000 12,000 12,000 12,000 12,000 12,000 0 0 0 0 72,000 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 4.1.3 Improved Food Storage and Distribution Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 70 Build capacity of nursery operators in all crop growing areas and support them to expand and improve quality of seedlings. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Build capacity of Quality Declared Seed producers and support them to expand and improve quality of seed. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Build capacity of food and cash crop farmers to improve productivity and produce quality. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Facilitate contractual arrangements between food and cash crop producers and market/industry. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Develop and promote innovative micro- financing packages to facilitate food and cash crop farmers to access credit. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Facilitate and support the acquisition of improved breeding stocks by men and women farmers. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Provide adequate and effective extension knowledge and agro-weather information Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen and/or establish efficient and sustainable animal health and artificial insemination services. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Develop and support innovative micro- financing packages to support livestock keepers’ access to credit and markets. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Identify areas with acute problem of water for livestock and construct water infrastructures. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Facilitate improvement of demarcated grazing lands Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Promote use of crop residues and agro- industry byproducts Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Promote value addition for livestock products Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Facilitate and support acquisition of fingerlings by men and women fish farmers Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Promote value addition for fish products Service Lumpsum 1 1 1 1 1 0 0 0 0 0 20,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Facilitate contractual arrangements between fish farmers and market Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Establish and support innovative micro- financing packages to support fisherfolks access to credit. Service Lumpsum 1 1 1 1 0 0 0 0 0 0 20,000 15,000 15,000 15,000 15,000 0 0 0 0 0 0 60,000 Support Local Governments to identify and demarcate potential areas within urban and peri-urban areas for agricultural activities. Service Lumpsum 1 1 1 1 0 0 0 0 0 0 30,000 20,000 20,000 20,000 20,000 0 0 0 0 0 0 80,000 Train urban and peri-urban producers in Good Agricultural Practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Monitor the safety of outputs from urban and peri-urban agriculture. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Enforce laws and bylaws related to urban and peri-urban land use. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 6,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 1,707,000 1,737,000 1,702,000 1,447,000 1,372,000 1,062,000 850,000 850,000 850,000 835,000 12,412,000 4.1.4 Increased Growth of Incomes Sub Total TOTAL RESULT AREA 1 : IMPROVED PRODUCTIVITY AND INCOMES Tanzania Climate Smart Agriculture Program 2015 - 2025 71 4.2. Building resilience and associated mitigation co-benefits Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Unit Cost (in US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Promote integrated soil fertility and water management interventions. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Establish CSA/SLM knowledge hubs across the country to support adoption of CSA and SLM technologies and practices by men and women that improve soil health and restore degraded lands. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Enhance the capacities of private sector service providers and farmer-based organizations to support farmers’ adoption of existing/new/improved CSA and SLM technologies and practices. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Develop and integrate CSA and SLM principles into farmer-field schools, primary, secondary and tertiary curriculum. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 0 100,000 Establish mechanisms for joint planning and implementation of CSA and SLM at the local level. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Develop and implement sustained awareness creation program on CSA and SLM in addressing soil health and land degradation challenges. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Facilitate the development and implementation of at least five (5) small scale CSA Projects annually. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Facilitate the dissemination and adoption of CSA and SLM technologies and practices at the farm level across the country through Local Government’s CSA Projects. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 1,000,000 Establish CSA/SLM Knowledge Platform with disaggregated data on men and women. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Document and publicize successful CSA/SLM technologies, practices and interventions Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 Total BASE COSTS IN US$ Component Activities Unit of measure Expenditure Account Quantities Sub Total 2.1 Improve soil health and restore degraded lands Tanzania Climate Smart Agriculture Program 2015 - 2025 72 Upscale Natural Forest Conservation through Participatory Forest Management (PFM) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 Protect water catchment areas through integrated watershed management. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Increase forest cover through natural regeneration, Agroforestry, Reforestation. and Afforestation Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote best management practices for natural resources management to improve and maximize net benefits for the farmers and other downstream users (e.g. power generation and urban water supply). Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Promote and support on farm soil conservation activities Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Promote sustainable production and marketing of charcoal from miombo woodlands Service Lumpsum 1 1 1 1 1 1 1 1 1 1 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 130,000 Promote sustainable land use management Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Develop a business model for ecosystem management in order to facilitate payment for ecosystem services (e.g. tourism revenue used to motivate farmers to conserve wildlife and payment for water in urban areas used to pay farmers for conservation of water catchments). Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Develop and implement management plans for ecosystems in order to encourage sustainable use Service Lumpsum 1 1 1 1 1 0 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 0 0 0 0 0 75,000 Document biodiversity in the ecosystems including below ground biodiversity and develop eco-tourism opportunities in such areas Service Lumpsum 1 1 1 1 1 0 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 0 0 0 0 0 75,000 Undertake natural resources accounting for ecosystem services. Service Lumpsum 0 0 0 0 1 1 1 1 1 1 15,000 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 90,000 Identify agroforestry species for different agro-ecological zones and support farmers to increase tree cover Service Lumpsum 1 1 1 0 0 0 0 0 0 0 12,000 12,000 12,000 12,000 0 0 0 0 0 0 0 36,000 Undertake afforestation and reforestation through Public-Private Partnerships. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 Sub Total 2.2 Conservation of Natural Resources and Catchments Tanzania Climate Smart Agriculture Program 2015 - 2025 73 Develop and implement varied innovative crop and livestock weather-indexed insurance packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Develop agro-meteorological infrastructure to support weather-indexed insurance and to use them for improved weather and climate information services for farmers. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Enhance the capacity of micro-finance institutions to act as agents to deliver innovative crop and livestock weather- indexed insurance packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Raise awareness within the insurance industry of extreme weather and climate risks and communicate actions and opportunities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Undertake farmer education to address their concerns regarding insurance products with a view to gain their trust Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Establish livestock insurance schemes and use of insured livestock as collateral Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Explore ways of using existing and other safety nets such as cash transfers or workfare programmes. Service Lumpsum 0 0 1 1 1 0 0 0 0 0 6,000 0 0 6,000 6,000 6,000 0 0 0 0 0 18,000 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.3 Insurance and Other Safety Nets Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 74 Prepare vulnerability maps for targeting food security and emergency preparedness interventions. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Develop tools to support vulnerable households and communities to establish household community systems that can respond to emergencies (with regards to food insecurity). Service Lumpsum 1 1 0 0 0 0 0 0 0 0 20,000 20,000 20,000 0 0 0 0 0 0 0 0 40,000 Monitor crops, livestock and fish pests and diseases. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Integrate scientific weather forecasting and indigenous knowledge for early warning and to inform farmer decisions. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 Establish a National Seed Emergency stock. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 60,000 60,000 60,000 0 0 0 0 0 0 0 0 120,000 Improve EWS messages (clear, consistent) that include risk information; designed to link threat levels. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Capacity development to farmers on early warning systems and emergency preparedness. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Improve mass delivery system particularly on content development and communication channels. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Establish a feedback and evaluation process of messages delivered. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Develop an effective frame-work for collaboration emergency communication centres/stakeholders. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 The explicit development of contingency plans on district level Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 Promote adoption of low cost climate smart technologies that minimize emission of carbon dioxide and enhance soil carbon t ti Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Develop a national carbon accounting and measurement, reporting and verification Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 829,000 829,000 705,000 463,000 478,000 402,000 402,000 402,000 402,000 402,000 5,314,000 2.4 Early Warning System and Emergency Preparedness 2.5 Synergies in adaptation and mitigation enhanced Sub Total Sub Total TOTAL RESULT AREA 2 : BUILDING RESILIENCE AND ASSOCIATED MITIGATION CO-BENEFITS Tanzania Climate Smart Agriculture Program 2015 - 2025 75 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Solicit funds for research and innovation into agricultural value chains service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Develop improved infrastructure for agricultural value chains. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 Institute competitive grant scheme for agriculture value chains. Service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Identify existing value addition technologies and incentivize the private sector to promote them. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 16,000 16,000 16,000 16,000 16,000 16,000 0 0 0 0 0 80,000 Establish regional hubs (a cluster of livelihood zones in the same AEZ) for value chain development and backstopping. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Identify and build capacity of actors in value chain processes. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 Undertake advanced market feasibility studies to promote demand for the selected commodities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Facilitate linkages to markets for the selected commodities. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 16,000 16,000 16,000 16,000 16,000 16,000 0 0 0 0 0 80,000 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 Unit of measure Expenditure Account Total Unit Cost (in US$) BASE COSTS IN US$ 4.3.1 Development of new agricultural products Component Activities Quantities Sub Total 3. Value Chain Integration Tanzania Climate Smart Agriculture Program 2015 - 2025 76 Create agricultural, livestock and fish commodity hubs through participation of private sector especially micro-financiers and apply viable models of linkage with smallholders Service Lumpsum 1 1 1 0 0 0 0 0 0 0 16,000 16,000 16,000 16,000 0 0 0 0 0 0 0 48,000 Facilitate capacity building of farmers on demand- and market-driven production. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Design and launch a market promotion program for import substitution commodities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 12,000 12,000 12,000 12,000 0 0 0 0 0 0 0 36,000 Work with supermarkets, hotels and restaurants to participate in selected commodity value chains with a smallholder production base. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Identify successful lead private sector firms with access to assured markets and apply viable models of linkage with smallholders. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 5,000 5,000 5,000 0 0 0 0 0 0 0 0 10,000 Design sustainable programmes to support the certification of smallholders for export markets. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 10,000 10,000 10,000 0 0 0 0 0 0 0 0 20,000 Develop branding of Tanzania produce for regional and international markets. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 20,000 20,000 20,000 0 0 0 0 0 0 0 0 40,000 Develop grading and standardization systems for agricultural commodities that do not have grades and standards Service Lumpsum 1 1 0 0 0 0 0 0 0 0 26,000 26,000 26,000 0 0 0 0 0 0 0 0 52,000 Promote the adoption of grading and standardization systems for all agricultural commodities for both domestic and export markets. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 245,000 245,000 184,000 116,000 116,000 74,000 74,000 74,000 74,000 74,000 1,276,000 Sub Total TOTAL RESULT AREA 3 : VALUE CHAIN INTEGRATION 4.3.2 Increased competitivenes s and enhanced integration into domestic, regional and international markets Tanzania Climate Smart Agriculture Program 2015 - 2025 77 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Increase public expenditure into research and development and innovations through national budget. service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Incentivize private sector investments in research and development and innovations. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 35,000 35,000 35,000 35,000 0 0 0 0 0 0 0 105,000 Conduct participatory research work on improved technologies and practices that is informed by needs of users and agro- ecological zones along the value chain. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 55,000 55,000 55,000 55,000 55,000 55,000 55,000 0 0 0 0 330,000 Conduct on-farm research into low-cost appropriate technologies and practices and deliver them as packages. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 60,000 60,000 60,000 60,000 60,000 60,000 60,000 0 0 0 0 360,000 Build the capacity of extension, producers and other stakeholders in the use of existing/new/improved CSA technologies and practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 600,000 Support development of private sector input and appropriate CSA technologies outreach and distribution networks. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 54,000 54,000 54,000 54,000 54,000 54,000 0 0 0 0 0 270,000 Intensify field demonstration/field days/study tours to enhance adoption of existing/new/improved CSA technologies and practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 Establish a platform through which researchers will have regular contacts with stakeholders and other users at the national, local and farm levels. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 30,000 30,000 30,000 0 0 0 0 0 0 0 0 60,000 Prepare CSA information packages and disseminate them to interested stakeholders using ICT. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 369,000 369,000 339,000 304,000 304,000 250,000 135,000 135,000 135,000 135,000 2,475,000 Total Unit Cost (in US$) 4: Research for Development and Innovations Sub Total TOTAL RESULT AREA 4 : RESEARCH FOR DEVELOPMENT AND INNOVATIONS 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 4.2 Research Extension Linkage strengthened and made functional by 2018 Expendit ure Account Unit of measure BASE COSTS IN US$ Quantities Component Activities Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 78 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Undertake a CSA knowledge mapping, audit and analysis. service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Equip Ward Resource Centres with CSA knowledge. service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Develop and maintain a robust and functional CSA knowledge management system. service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Build capacity to different stakeholders in the agricultural value chain at the national and local levels. service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Undertake analyses and provide tools to support CSA decision-making. service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Bundle and provide synthesized information on CSA approaches and case studies on CSA best approaches. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Develop and test CSA guidelines and decision- making support tools. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Produce regular CSA information and communication materials for influential stakeholders to support and inform policies, planning and agricultural advisory services. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Produce CSA information and communication materials to strengthen capacity of researchers, private sector, CSOs and farmer organizations to influence policy and decision makers. service Lumpsum 1 1 1 1 1 1 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 180,000 Develop practical and applied training materials and packages for training on CSA. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Strengthen CSA knowledge and information sharing networks/forums. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Develop a portfolio of information sharing technology tools to support sharing of CSA information and learning resources. service Lumpsum 1 1 1 1 1 1 1 1 1 1 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 330,000 Establish CSA knowledge partnerships on knowledge generation, sharing and mobilization with governments, international organizations, research institutions, farmer organizations, private sector and civil society organizations. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen curriculum and put emphasis on practical experience. service Lumpsum 1 1 1 35,000 35,000 35,000 35,000 0 0 0 0 0 0 105,000 Sub total 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 BASE COSTS IN US$ Unit Cost (in US$) Component Activities Quantities 4.5.1 CSA knowledge generation and dissemination 5: CSA Knowledge, Extension and Agro-weather Services Total Unit of measure Expenditure Account Tanzania Climate Smart Agriculture Program 2015 - 2025 79 Identify appropriate climate/weather services and products for small scale farmers service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Promote integrated weather observation for improving availability and reliability of climate information. service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Digitize historical climate data to enhance availability and accessibility of climate information. service Lumpsum 1 1 1 1 1 0 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Downscaling forecasted weather to various localities to promote the appropriate climate/weather services and products for small scale farmers, and pre-season dissemination of agro weather advisories service Lumpsum 1 1 1 1 0 0 0 0 0 0 45,000 45,000 45,000 45,000 45,000 0 0 0 0 0 0 180,000 Promote in-season community agro-weather monitoring and post-season agro-weather review service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Improve dissemination channels of climate information (e.g. use of mobile phone based early warning system). service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Generate user friendly and tailor made products for improving smallholder farmers ‘decision making. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Strengthen integration of climate research with agricultural research service Lumpsum 1 1 1 1 1 0 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Training of Regional Coordinators on CSA. service Lumpsum 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 280,000 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 463,000 498,000 458,000 458,000 378,000 283,000 283,000 243,000 243,000 243,000 3,550,000 Sub Total TOTAL RESULT AREA 5 : CSA KNOWLEDGE, EXTENSION AND AGRO-WEATHER SERVICES 4.5.2 Enhance extension, climate information services and agro- weather advisories Tanzania Climate Smart Agriculture Program 2015 - 2025 80 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Develop and implement an inter- ministerial communications strategy with respect to inter-ministerial coordination on matters relating to climate smart agriculture. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Introduce a biannual joint planning and review session between inter-ministerial team and the country government officials responsible for agriculture. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 150,000 Train national, regional and local government staff in cross-sectoral planning and implementation. service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 300,000 Build policy review and analytical capacity at the national and local levels. service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Strengthen the planning, implementation, monitoring and evaluation at the national and local levels. service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 200,000 Establish a framework for disseminating CSA programmatic planning and implementation as well as annual reports and studies and receiving feedback at national and local levels. service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 Total 6: Improved Institutional Coordination Expenditure Account Unit of measure Unit Cost (in US$) BASE COSTS IN US$ 4.6.1 Improve Inter-Ministerial and Local Government Coordination Component Activities Quantities Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 81 Engage private sector to identify opportunities for increased investments in CSA. service Lumpsum 1 1 1 1 0 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 0 100,000 Organize regular consultative meetings with private sector and CSOs on the planning and implementation of the CSA Program. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 150,000 Identify appropriate incentives to catalyze private sector and CSO investments in CSA activities. service Lumpsum 1 1 1 0 0 0 0 0 0 0 30,000 30,000 30,000 30,000 0 0 0 0 0 0 0 90,000 Publicize the Country CSA Program to private sector and CSOs with a view to identifying areas for their participation. service Lumpsum 1 1 0 0 0 0 0 0 0 0 33,000 33,000 33,000 0 0 0 0 0 0 0 0 66,000 Establish communication channels for consultations between private sector and CSOs in the programmatic planning and implementation of CSA activities at the national and local levels. service Lumpsum 1 1 0 0 0 0 0 0 0 0 45,000 45,000 45,000 0 0 0 0 0 0 0 0 90,000 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 Harmonize GoT and development partners’ investments in climate smart agriculture through a common Country (National) CSA Program. service Lumpsum 1 1 1 1 1 0 0 0 0 0 36,000 36,000 36,000 36,000 36,000 36,000 0 0 0 0 0 180,000 Strengthen collaboration between GoT and the Development Partners’ Agriculture Coordination Group (with a standing agenda item programmatic planning and implementation of CSA Program). service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 200,000 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 484,000 484,000 366,000 261,000 236,000 200,000 200,000 200,000 200,000 200,000 1,831,000 Sub Total 6.3 Programmatic Coordination with Development Partners strengthened TOTAL RESULT AREA 6 : IMPROVED INSTITUTIONAL COORDINATION 4.6.2 Partnerships with private sector and civil society organizations Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 82 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total A: Investment 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 B: Components 1.1 Improved productivity and nutrition 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 1.2 Irrigation and water management 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 1.3 Improved Food Storage and Distribution 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 1.4 Increased Growth of Incomes 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 2.1 Improve soil health and restore degraded lands 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 2.2 Conservation of Natural Resources and Catchments 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 2.3 Insurance and Other Safety Nets 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.4 Early Warning System and Emergency Preparedness 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 2.5 Synergies in adaptation and mitigation enhanced 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 3.1 Development of new agricultural products 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 3.2 Increased competitiveness and enhanced integration into domestic, regional and international markets 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 4.2 Research Extension Linkage strengthened and made functional by 2018 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 5.1 CSA knowledge generation and dissemination 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 5.2 Enhance extension, climate information services and agro- weather advisories 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 6.1 Improve Inter-Ministerial and Local Government Coordination 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 6.2 Partnerships with private sector and civil society organizations 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 6.3 Programmatic Coordination with Development Partners strengthened 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 GRAND TOTAL 6,347,000 5,272,000 5,364,000 3,979,000 3,284,000 2,521,000 2,194,000 2,154,000 1,904,000 1,889,000 32,158,000 BASE COSTS IN US$ Summary Cost by Component"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":196,"cells":{"data":{"kind":"string","value":"# Extracted Content THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL JULY, 2017 CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | iii TABLE OF CONTENTS TABLE OF CONTENTS iii ACKNOWLEDGEMENT vi LIST OF ABBREVIATION AND SYMBOLS vii INTRODUCTION viii 1. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1 1.1 DEFINITION OF TERMS 1 1.2 THE CONCEPT OF CLIMATE CHANGE 1 1.3 THE IMPACTS OF CLIMATE CHANGE ON AGRICULTURE 2 1.4 THE IMPACTS OF AGRICULTURE ON CLIMATE CHANGE 3 1.5 CLIMATE CHANGE RISKS AND VULNERABILITIES IN AGRICULTURE 3 1.6 ADAPTATION AND MITIGATION OF CLIMATE CHANGE 4 1.6.1 Adaptation Options 4 1.6.2 Mitigation Actions 5 2 CLIMATE-SMART AGRICULTURE 6 2.1 INTRODUCTION 6 2.2 THE THREE PILLARS OF CSA 6 2.2.1 Productivity 6 2.2.2 Adaptation 6 2.2.3 Mitigation 7 2.3 CSA PRACTICES AND TECHNOLOGIES 7 2.3.1 Key characteristics of CSA 7 2.4 CROP SUB SECTOR PRACTICES AND TECHNOLOGIES 8 2.4.1 Rain Water Harvesting and Storage 8 2.4.2 Irrigation Practices and Technologies 9 2.4.3 Soil and Water Conservation Practices and Technologies 11 2.4.4 Agro forestry Practices and Technologies 13 2.4.5 Conservation Agriculture (CA) 15 2.4.6 Common CA practices and technologies 16 2.4.7 Soil Fertility Management Practices and Technologies 18 TABLE OF CONTENTS iv | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4.8 Crop Management Practices and Technologies 19 2.5 LIVESTOCK SUBSECTOR PRACTICES AND TECHNOLOGIES 21 2.5.1 Improved Livestock Breeds 21 2.5.2 Improved Feeds 21 2.5.3 Livestock Improved Feedings 21 2.5.4 Pasture and Grazing Land Management 22 2.5.5 Improved Grazing Land Management 23 2.5.6 Manure Management 24 2.6 FISHING AND AQUACULTURE ACTIVITIES 25 2.6.1 Pond Aquaculture/Fish Ponds 25 2.6.2 Integrated Aquaculture and Cage Culture 26 2.6.3 Sustainable Fishing 26 2.6.4 Seaweed Farming 26 2.7 OTHER CSA PRACTICES AND TECHNOLOGIES 27 2.7.1 Bee-keeping 27 2.8 UPSCALING CSA PRACTICES AND TECHNOLOGIES 28 2.8.1 The challenges in upscaling CSA 28 3: CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 29 3.1 INTRODUCTION 29 3.2 IDENTIFICATION OF STAKEHOLDERS 29 3.3 ROLES OF DIFFERENT STAKEHOLDERS ON IMPLEMENTATION AND UPSCALING OF CSA 29 3.3.1 Government 29 3.3.2 NGOs 30 3.3.3 Research partners 31 3.3.4 Private Sector 31 3.3.5 Farmers 31 3.3.6 Media 32 3.3.7 Development Partners/Inter-governmental Institutions 32 3.3.8 Religious institutions and communities 32 3.4 STAKEHOLDERS ENGAGEMENT MECHANISMS 32 3.5 APPROACHES FOR CSA INTEGRATION 32 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 34 4.1 INTRODUCTION 34 4.2 AWARENESS CREATION AND SENSITIZATION ON CSA 34 4.2.1 Meaning of awareness 34 4.2.2 Meaning of sensitization 34 4.2.3 How to create awareness 34 TABLE OF CONTENTS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | v 4.2.4 Target for Awareness Creation 35 4.3 CSA RELATED ACTIVITIES AND THEIR JUSTIFICATION 35 4.3.1 CSA Related Activities 36 4.3.2 Justification for CSA activities 36 4.4 PLANNING CSA ACTIVITIES WITH GENDER CONSIDERATION 37 4.4.1 Mainstreaming Gender into CSA Planning Process 37 4.4.2 Gender Analysis 37 4.5 BUDGETING FOR CSA RELATED ACTIVITIES 37 4.5.1 Gender responsive budgeting 38 4.5.2 Potential Costs of Maladaptation 38 4.5.3 Source of Finance for CSA 38 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS 41 5.1 INTRODUCTION 41 5.2 BASELINE INDICATORS FOR CSA RELATED 41 5.3 PERFORMANCE INDICATORS 41 5.4 MONITORING TOOLS AND RECORD KEEPING 42 5.5 CREATION OF EVIDENCE FOR CSA INTERVENTIONS 42 CONCLUSION 43 REFERENCES 44 TABLE OF CONTENTS vi | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL ACKNOWLEDGEMENT The preparation of the Climate-Smart Agriculture (CSA) Training of Trainers (ToT) Manual involved a number of individuals who worked to ensure that the document captures essential details. In a very special way, I would like to thank all the Technical Team Members from the Ministry of Agriculture Livestock and Fisheries who actively participated in the preparation of this Training of Trainers Manual especially from Department of Crop Development (DCD), Department of Training (DT), Livestock Training Agency (LIT A) and Environment Management Unit (EMU). I acknowledge and appreciate the valued contributions from World Vision, Sokoine University of Agriculture (SUA) and VUNA Climate Smart Agriculture programme for their great efforts in the development of the CSA Training of Trainers Manual. Finally, I do acknowledge and appreciate the technical and financial support provided by the Food and Agriculture Organization of the United Nations (FAO). We appreciate and value their cooperation and support. Shakwaanande Natai Head - Environment Management Unit Ministry of Agriculture Livestock and Fisheries AKNOWLEDGEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | vii LIST OF ABBREVIATION AND SYMBOLS ASDP Agriculture Sector Development Programme BRN Big Results Now CAADP Comprehensive African Agriculture Development Programme CH4 Methane CO2 Carbon dioxide CSA Climate-Smart Agriculture CSO Civil Society Organization ERPP Expanding Rice Production Project FAO Food and Agriculture Organizations of United Nations GHGs Green House gases IPCC Intergovernmental Panel on Climate Change M & E Monitoring and Evaluation N2O Nitrogen oxide NAMA National Appropriate Mitigation Actions NAPs National Adaptation Plans NGOs Non-Government Organizations RWH Rain Water Harvesting SUA Sokoine University of Agriculture SRI System of Rice Intensification URT United Republic of Tanzania LIST OF ABBREVIATION AND SYMBOLS viii | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL INTRODUCTION Climate-smart agriculture is “Agriculture that sustainably increases productivity, resilience (adaptation), reduces or removes Greenhouse Gases (GHGs) (mitigation) where possible, and enhances achievement of national food security and development goals” (FAO, 2010). However, in the Tanzanian context, the adapted definition of Climate- Smart Agriculture is “agriculture that sustainably increases productivity and income, increases the ability to adapt and build resilience to Climate Change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” (National Task Force Planning Workshop Report, 2016). CSA aims to achieve food security and broader development goals under a changing climate and increasing food availability using different practices and technologies. CSA practices and technologies on crop, livestock and fisheries aims at addressing tradeoffs and synergies between the three pillars: productivity, adaptation, and mitigation. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies also embrace priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. In understanding the importance of CSA in crops, livestock and fisheries production; practices and technologies were identified and mapped according to Agro-Climatic Zones of Tanzania. These Practices and technologies may serve as tool for deciding options within which the three pillars of CSA can be achieved. It is because of the importance of CSA in the Tanzanian context that this Training of Trainers (ToT) Manual has been developed, in order to guide agricultural stakeholders on how to accelerate the uptake of CSA practices and technologies within the agricultural sector. This manual is divided into five chapters where by chapter 1 aims at helping users to understand some of the potential impacts of climate change and possible solutions for addressing climate related risks with regard to agriculture. It also provides an understanding of how changes in climate can affect agriculture and subsequently identifies best practices that will help farmers to adapt in their respective agro- climatic zones. Chapter 2 introduces in detail the concept of CSA practices and technologies in crop, livestock and fisheries production. Chapter 3 provides guidance on identification, roles and engagement mechanisms of different stakeholders on implementation of CSA related activities. Chapter 4 helps elaborate on issues related to mainstreaming of CSA into agricultural plans, programmes and budgets. Lastly, chapter 5 give guidance on how to carry out monitoring and evaluation of CSA related activities and interventions. INTRODUCTION CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 1 CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1.1 DEFINITION OF TERMS Climate change and climate variability Climate change is defined as the long-term continuous change to average weather conditions. Specifically, it is the rise in average surface temperatures on earth. The way climate fluctuates yearly above or below a long-term average value is climate variability Risk Risk can be defined as a probability or threat of damage, injury, liability, loss, or any other negative occurrence that is caused by external or internal vulnerabilities, and that may be avoided through pre-emptive action. Vulnerability Vulnerability is the state of being open to injury, or susceptibility to harm and lack of capacity to cope and adapt Adaptation Adaptation is defined as an adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities. Mitigation Mitigation refers to effort that seek to prevent or slow down the increase of atmospheric Green House Gases (GHGs) Concentration by limiting current and future emission and enhancing their potential sinks . 1.2 THE CONCEPT OF CLIMATE CHANGE Climate refers to the average weather conditions in a certain place over many years. Climate encompasses temperature, humidity, atmospheric pressure, wind, rainfall, atmospheric particle count and other meteorological elements in a given region. The average climate around the world is called global climate. Rising global temperatures lead to other changes around the world, such as melting glaciers, submerging of islands, rising of sea levels and the loss of wildlife habitats. Many places have seen changes in rainfall, resulting in more floods, droughts, or intense rain, as well as more frequent and severe heat waves. That’s because the Earth’s air, water, and land are all related to one another and to the climate. This means a change in one place can lead to other changes somewhere else. For example, when air temperatures rise, the oceans absorb more heat from the atmosphere and become warmer. Warmer oceans, in turn, can cause stronger storms. As these and other changes become more pronounced in the coming decades, they will likely present challenges to our society and our environment. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1| 2 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Climate change is largely caused by human activities, and it presents a serious threat to nature and people now, and in the future. It affects the plants and animal populations and distributions of species, the composition of ecological communities, and nature’s provision of goods and services – such as food, fuel and clean water. Climate change also compounds other major threats to biodiversity, such as invasive alien species, habitat fragmentation and over exploitation. The principal drivers of climate change are variations in atmospheric concentrations of greenhouse gasses (GHG, including water vapour, carbon dioxide, methane, nitrous oxide, and ozone) and aerosols, as well as changes in land cover and solar radiation, all of which alter the energy balance of the Earth’s climate. Terrestrial and marine ecosystems currently sequester carbon, acting as ‘sinks’. Changes to atmospheric carbon dioxide (CO2) concentrations could shift the global carbon cycle towards annual net emissions, turning these ecosystems into ‘sources’. Concentrations of other greenhouse gasses, including methane (CH4) and Nitrogen Oxide (N2O), which have similar effects, have also increased markedly as a result of human activities. Without ambitious mitigation efforts, global temperature rise this century could exceed four (4) degrees Celsius above pre-industrial levels, with catastrophic impacts. 1.3 THE IMPACTS OF CLIMATE CHANGE ON AGRICULTURE There are several impacts associated with Climate change in Agriculture: • Lowering crop production This is due to either erratic rains prolonged drought, changing temperatures, and nutrient constraints due to erosion or leaching. This may counteract the potential increases in yield. For example, if temperature exceeds a crop’s optimal level, if sufficient water and nutrients are not available, yield may be adversely affected. Extreme events, especially flooding and drought, can harm crops and reduce yields. • Lowering livestock production Climate change is expected to further shrink rangelands which are important for livestock production. Climate change and variability are expected to lead to pasture and water shortages. • Persistent Poverty The majority of rural poor farmers depend on seasonal rainfall that could be unreliable for agricultural production causing them to get low yields that perpetuate the cycle of poverty. • The prevalence of crop and livestock pests and diseases This situation has been exacerbated by a conducive environment influenced by the change in climate. Many pests and diseases thrive under warmer temperatures, wetter climates, and increased CO2 levels. Farmers will spend more money to fight pests and diseases. The spatial and temporal distribution of pests and diseases is likely to increase with climate change. This could cause new problems for farmers’ crops previously unexposed to these species. • Water stress affecting agriculture This is due to changes in temperature and rainfall patterns. Although increased irrigation might be possible in some places, in other places water supplies may also be reduced, leaving less water available for irrigation. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 3 • Reduced nutritional value of most food crops Some laboratory experiments suggest that elevated CO2 levels can increase plant growth. Though rising CO2 can stimulate plant growth, it also reduces the nutritional value of most food crops. Rising levels of atmospheric carbon dioxide reduce the concentrations of protein and essential minerals in most plant species, including wheat, soybeans, and rice. This direct effect of rising CO2 on the nutritional value of crops represents a potential threat to human health. Human health is also threatened by increased pesticide use due to increased pest pressures and reductions in the efficacy of pesticides. 1.4 THE IMPACTS OF AGRICULTURE ON CLIMATE CHANGE • Industrial agriculture is a huge carbon contributing factor. It has a hugely negative impact on global warming. Figures from the Intergovernmental Panel on Climate Change (IPCC) say that agricultural land use contributes 12 percent of global greenhouse gas emissions. Supporting industrial agriculture perpetuates these disturbing practices. • Greenhouse gas emissions from fertilizer and pesticide use; manufacture and use of pesticides and fertilizers, fuel and oil for tractors, equipment, trucking and shipping, electricity for lighting, cooling, and heating, and emissions of carbon dioxide, methane, nitrous oxide and other greenhouse gases significantly bumps the impact to the climate. • Land use changes significantly contribute to climate change. Large-scale changes such as deforestation contribute to increased carbon dioxide concentrations in the atmosphere. Soil erosion by water, wind and tillage affects both agriculture and the natural environment. Soil loss, and its associated impacts, is one of today’s most important environmental problems. 1.5 CLIMATE CHANGE RISKS AND VULNERABILITIES IN AGRICULTURE The Agriculture sector faces many risks that could pose potentially serious consequences for all stakeholders. Volatility in the prices of agricultural commodities and “inputs” such as fertilizer, pesticides and equipment, as well as impact from pests, diseases, droughts and floods which have become more frequent and severe due to climate change—can negatively affect farmers and others involved in the agriculture industry. They can also put a severe fiscal strain on government. Malnutrition, gender inequality and bad governance also curb productivity and raise vulnerability over the long term. The extent of vulnerability can be determined by undertaking assessments. Agricultural risk and vulnerability assessment helps identify appropriate risk management strategies, which often include: • Mitigation such as Improved water management; Use of drought and flood tolerant seeds, Early warning systems and other activities that reduce the likelihood of adverse events and the severity of losses • Risk transfer: Insurance and other arrangements • Coping: Savings and targeted safety net programs, risk financing These are accompanied by appropriate agricultural investments, policy support, and technical assistance activities to make the agriculture sector more resilient. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 4 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 1.6 ADAPTATION AND MITIGATION OF CLIMATE CHANGE Climate change and its associated impacts on agriculture sectors is a major concern in Tanzania. It has far-reaching consequences for agriculture that keeps disproportionately affect the poor. Greater risks of crop failures and livestock deaths are already imposing economic losses and undermining food security and they are likely to get far more severe as global warming continues. More than 80% of the population in Tanzania depends on climate sensitive rain fed agriculture as source of livelihood. Reducing vulnerability of agriculture to climate change will significantly contribute to socio-economic development and ensure food security. Adaptation measures are needed urgently to reduce the adverse impacts of climate change, facilitated by concerted international action and strategic country planning. The National Climate Change Strategy (URT, 2012) sets out strategic interventions for climate change adaptation measures and greenhouse gas emissions reductions. The goal is to enable Tanzania to effectively adapt to and participate in global efforts to mitigate climate change with a view to achieving sustainable economic growth in the context of the Tanzania’s national development blueprint, Vision 2025; Five Years National Development Plan; and national cross-sectoral policies in line with established international policy frameworks. The National Climate Change Strategy has outlined objectives for all sectors and proposed strategic interventions in those sectors and themes that are highly vulnerable to climate change such as agriculture. The Agriculture Climate Resilience Plan (URT, 2014) has been developed to implement strategic adaptation and mitigation actions in the crops sub-sector. The Climate-smart Agriculture Programme for Tanzania (2015 – 2025) aims to build resilience of agricultural farming systems for enhanced food and nutrition security through six programmatic result areas namely: Improved Productivity and incomes; Building resilience and associated mitigation co-benefits; Value Chain Integration; Research for Development and Innovations; Improving and Sustaining Agricultural Advisory Services; and Improved Institutional Coordination. The Climate change agriculture (CSA) programme enhances the implementation of the Comprehensive African Agriculture Development Programme (CAADP) and responds to the 23rd Ordinary African Union Assembly Decisions and Declaration (Malabo Declaration), This CSA guideline has therefore been developed to support the implementation of Tanzania CSA programme. 1.6.1 Adaptation Options Potential adaptation options that can help to integrate resilience in agricultural policy decisions, influence planning processes, and implement investments on the ground include: • Improving agricultural land and water use and management through proper land use planning and management • Accelerating uptake of climate-smart agriculture • Strengthening knowledge on Early warning and community preparedness and establish early information systems • The potential adaptation in the livestock sector include promoting climate change resilient traditional and modern knowledge on sustainable pasture and range management systems; enhancing development of livestock infrastructure and services; promoting development of livestock insurance strategies; strengthening weather forecast information sharing for pastoralists; promoting livelihood diversification of livestock keepers; and promoting improved traditional livestock keeping systems • In fisheries promote aquaculture and enhance protection and conservation of aquatic ecosystems. • In forests and ecosystems; application of best practices in soil and water conservation; promotion of fast growing tree species; farmer and pastoralist managed natural regenerations and use of alternative sources of energy CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 5 CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE • As a major source of greenhouse gas (GHG) emissions, agriculture also has much untapped potential to reduce emissions through reduced deforestation and changes in land use and agricultural practices • Better climate information is another potentially cost-effective way of adapting to climate change. • The greater uncertainty from climate change can be best addressed through contingency planning across sectors and identify immediate priorities to improve preparedness for climate change. • Mainstreaming climate change in the broader economic agenda, rather than taking a narrow agricultural perspective • Devise new mechanisms to provide climate information and forecasting, research and development of diverse crops adapted to new weather patterns, and techniques to reduce land degradation. • Diversify livestock types and varieties to address the environmental variations and economic risks associated with climate change. • Change the intensification of production to address the environmental variations and economic risks associated with climate change. • Change timing of farm operations to address the changing duration of growing seasons and associated changes in temperature and moisture. • Diversify source of household income in order to address the risk of climate-related income loss. 1.6.2 Mitigation Actions • Agriculture is also a major contributor of lowering carbon sequestration (storage) through land use change (the loss of soil organic matter in cropland and pastures, and forest conversion to agriculture), although quantitative estimates are uncertain. Emissions of carbon dioxide from changes in agricultural land use can be reduced by slowing deforestation. • Promote carbon trading to reduce emission of Green House Gases this will motivate communities living adjacent to forest reserves to conserve trees and other biota. Carbon financing can support mitigation; the emerging market for trading carbon emissions offers new possibilities for agriculture to benefit from land uses that sequester carbon. • Changes in agricultural land management (conservation tillage, agroforestry, and rehabilitation of degraded crop and pasture land, promoting afforestation and reforestation), overall improvement of nutrition and genetics of ruminant livestock • Storage and capture technologies for manure, and conversions of emissions into biogas (production of valuable by-products, such as bio energy) is a better management of natural resources • Development of low-emission crop varieties and livestock breeds. Therefore, it is important to put in place strategies aiming at adapting to climate change and reducing its impacts through research, awareness raising, advocacy, mobilization and empowerment of most vulnerable communities. Adaptive strategies have to be implemented from household, community, and national levels in order to enhance already existing adaptation strategies while designing new ones. One of these strategies is to promote Climate- Smart Agriculture. 6 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.1 INTRODUCTION Climate-Smart Agriculture (CSA) addresses climate change related risks. Contrary to conventional agricultural development, systematically integrates climate change into the planning and development of sustainable agricultural systems (Lipper et al., 2014). Also, CSA integrates multiple goals and manages trade-offs. Frequently, when it comes time to implement CSA, trade-offs must be made. This requires identification of synergies and weighs the costs and benefits of different options based on intended objectives (CSA guide, 2016). By definition (FAO, 2010) CSA defined as “agriculture that sustainably increases productivity, enhances resilience (adaptation), reduces/removes GHGs (mitigation) where possible, and enhances achievement of national food security and development goals”. In this definition, the principal goal of CSA is identified as food security and development; while productivity, adaptation, and mitigation are identified as the three interlinked pillars necessary for achieving this goal. However, in Tanzanian context the adopted definition of Climate-Smart Agriculture is “agriculture that sustainably increases productivity and income (profitability), increases the ability to adapt and build resilience to Climate Change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” as defined at the National Climate-Smart Agriculture Task Force Planning Workshop Report of 2016. 2.2 THE THREE PILLARS OF CSA 2.2.1 Productivity CSA aims to sustainably increase agricultural productivity and incomes from crops, livestock and fish, without having a negative impact on the environment. This, in turn, will raise food and nutritional security. A key concept related to raising productivity is sustainable intensification. 2.2.2 Adaptation CSA aims to reduce the exposure of farmers to short-term risks, while also strengthening their resilience by building their capacity to adapt and prosper in the face of shocks and longer-term stresses. Attention is given to protect the ecosystem services, whereby these services are essential for farmers on maintaining productivity and enhances our ability to adapt climate changes. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE 2| CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 7 CLIMATE-SMART AGRICULTURE 2.2.3 Mitigation Wherever and whenever possible, CSA should help to reduce and/or remove greenhouse gas (GHG) emissions. This implies that we reduce emissions for each calorie or kilo of food, fibre and fuel that we produce and that we avoid deforestation from agriculture, we manage soils, crops, livestock and vegetation in ways that maximizes their potential to acts as carbon sinks and absorb CO2 from the atmosphere. 2.3 CSA PRACTICES AND TECHNOLOGIES In agriculture practices refer to management activities at the farm and landscape level while technologies are highly productive, high quality, efficient and resource-saving (water, energy, labour) techniques and expertise for agricultural production. It also refers to techniques appropriate for the protection and improvement of the environment In view of the observed climate change impacts, different strategies are being employed to adapt to the changing climate. These strategies vary from place to place and includes early land preparation, early planting, dry planting, planting of drought tolerant crops, planting of early maturing crops, mulching, irrigation, tree planting, and the use of indigenous knowledge. Other strategies include re-planting, intercropping, crop rotation, minimum tillage, use of water harvesting technologies, digging irrigation trenches and terracing. Livestock farmers also adapt by growing grasses and perennial fodders, using farm by-products and doing additional activities such as crop farming. Fish farmers uses practices and technologies such as Pond Aquaculture/Fish Ponds, Integrated fish farming, Cage culture, Seaweed Farming and Mariculture. 2.3.1 Key characteristics of CSA • CSA maintains ecosystems services: Ecosystems provide essential services, including clean air, water, food and materials. • CSA has multiple entry points at different levels: CSA has multiple entry points, ranging from the development of technologies and practices to the elaboration of climate change models and scenarios, information technologies, insurance schemes, value chains and strengthening of institutional and political enabling environments. As such, it goes beyond single technologies at the farm level and includes the integration of multiple interventions at the food system, landscape, and value chain or policy level. • CSA is context specific: What is climate-smart in one-place may not be climate-smart in another, and no interventions are climate-smart everywhere or every time. Interventions must take into account how different elements interact at the landscape level, within or among ecosystems and as a part of different institutional arrangements and political realities. The fact that CSA often strives to reach multiple objectives at the system level makes it particularly difficult to transfer experiences from one context to another. • CSA engages women and marginalized groups: To achieve food security goals and enhance resilience, CSA approaches must involve the poorest and most vulnerable groups. These groups often live on marginal lands which are most vulnerable to climate events like drought and floods. Gender is another central aspect of CSA. Women typically have less access and legal right to the land which they farm, or to other productive and economic resources which could help build their adaptive capacity to cope with events like droughts and floods. • Stakeholder Involvement: CSA strives to involve stakeholders at local, regional and national stakeholders in decision-making. Only by doing so, it is possible to identify the most appropriate interventions, form of partnerships and alliances needed to enable sustainable development. 8 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4 CROP SUB SECTOR PRACTICES AND TECHNOLOGIES 2.4.1 Rain Water Harvesting and Storage Rain water harvesting (RWH) involves collecting, storing and conserving local surface runoff for agriculture (Boers and Ben-Asher, 1982). In crop production systems, RWH is composed of a runoff producing area normally called the Catchment Area (CA) and a runoff utilization area normally called Cropped Basin (CB) as explained by Hatibu and Mahoo (1999). The Rain water Harvesting and Storage Practices are highly recommended in semi-arid regions where there is limited water availability and storage capacities such as Dodoma, Singida and parts of Manyara and Shinyanga. Water shortage affects more rural women since it is their cultural role to provide water for the family. They are more concerned with rainwater harvesting as compared to men. Therefore, small-scale rainwater harvesting can ensure a significant and steady supply of water for farming even in times of drought, and permit year-round vegetable cultivation with significant nutritional impacts on families. 2.4.1.1 Types of rain water harvesting practices and technologies • In-situ rain water harvesting Is a method of increasing the amount of water stored in the soil profile by trapping or holding the rain where it falls such as bunded basin (Majaluba). In essence, in situ rainwater harvesting technologies are soil management strategies that aim at maximum infiltration and minimize surface runoff to achieve better yields where soil moisture is a constraint. This technology often serves primarily to recharge soil water for crop and other vegetation growth in the landscape. CLIMATE-SMART AGRICULTURE Farmers learning how to prepare bunds (Majaluba) Transplanted rice in bunds – Mbarali, Mbeya • Chololo pits This is harvesting technology initiated by a farmer in Chololo village, Dodoma. They are made during land preparation (before rains) and the soil is heaped below the pit. Crop seeds (millet seeds) are planted in the pits and part of the soil (sometimes mixed with manure) is returned to cover the seeds. The pit holds and conserves runoff water during the growing season. Contour bunds are constructed on the upper side of the farm to control excessive runoff’. CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 9 CLIMATE-SMART AGRICULTURE Chololo pits consist of pits of about 0.2 – 0.25m deep and 0.2-0.25m diameter dug in a line across the slope spaced at 0.5m within line and about 1.0m between lines. The adjacent line of pits is set such that the pits are dug in a middle position to the above ones so as to tap runoff that has drained through the first line of pits. 2.4.2 Irrigation Practices and Technologies • Irrigation canal lining Canal lining is a process of reducing seepage loss of irrigation water by adding an impermeable layer to the edges of the trench. Seepage can result in losses of 30 to 50 percent of irrigation water from canals, so adding lining can make irrigation systems more efficient. Canal linings are also used to prevent weed growth, which can spread throughout an irrigation system and reduce water flow. Lining a canal can also prevent water logging around low lying areas of the canal. The most commonly used types of lining include: concrete, concrete blocks, bricks or stone masonry, sand cement, plastic; and compacted clay. Rain water harvesting at Mbigiri Village in Kilolo District, Iringa • Dam Construction of dam is a system that involves the collection of runoff from large areas, which are at an appreciable distance from where it is being used. This may involve traditional water harvesting technologies e.g. Ndiva system in Pare Mountains, or Kitivo in Usambara Mountains. 10 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Lined canals at Lower Moshi irrigation scheme • Drip/trickle irrigation Drip irrigation is a technology of using water efficiently, reducing evaporation and enhancing infiltration and moisture retention in the soil profile through soil organic matter (SOM) management combined with the use of more drought-resilient species Drip irrigation, also known as trickle irrigation, is an irrigation method that saves water and fertilizer by allowing water to drip slowly to the plant roots, either onto the soil surface or directly onto the root zone, through a network of valves, pipes, tubing, and emitters. It is easy to design, install and much less water is wasted during irrigation. The farmers can use low cost drip irrigation system, which will enable them to produce high value crops especially vegetables. • System of Rice Intensification (SRI) SRI is a technology of increasing productivity of irrigated rice by changing the management of plants, soil, water and nutrients. It is a water saving technology for lowland (paddy) rice farmers, it involves controlled irrigation, (rice fields are alternately flooded and dried and fields monitored via simple, perforated tube). SRI Drip irrigation system CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 11 technology allows weed control by using hand tools such as push-weeders. It improves farmers’ livelihoods; decreases costs of (water-related) inputs and increases resilience to both price shocks (e.g. increased energy costs) and weather variability. Paddy rice cultivation is a primary source of non-CO2 GHG emissions from the agriculture sector Therefore, SRI is widely accepted as climate-smart technology for its potential to significantly reduce methane emissions and increasing yields. SRI is now well used by farmers in Mcholi 1 ward in Ruvuma River Basin and Dakawa in Wami River Basin. Farmers at KATC practicing on use of push-weeder ERPP SRI Demonstration plot at Kigugu, Morogoro 2.4.3 Soil and Water Conservation Practices and Technologies Soil and water conservation practices and technologies reduce run-off and eventually soil erosion, conserve the soil productivity and therefore help to increase yields, especially on sloping farmlands. There are different types of soil and water conservation practices, which can be used under specific conditions such as low rainfall, high rainfall, steep slopes, gentle slopes, deep soil, shallow soil etc. • Ridging Ridging is the farming practice of ploughing or placing stones across the slope following its contour line for the purpose of controlling soil erosion and enhancing water infiltration. This practice is mostly adopted in gentle slopes to control run-off and retain moisture and nutrients. Ridging creates a water break, which reduces the formation of rills and gullies during the times of heavy water runoff which is a major cause of soil erosion. The ridges should traverse the slope to capture the rainfall rather than running downhill, channelling water and soil away. The ridges can be tied (Tie-ridging) with small earth ties within the ridge/furrow to collect and store runoff in the soil to be used by crops planted on the ridges. CLIMATE-SMART AGRICULTURE 12 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Contour Ridges in Kibwaya village, Morogoro • Water Retaining/Harvesting Pits A series of pits are dug into the ground where runoff normally occurs to allow seepage, minimize soil erosion and nutrient loss to improve soil fertility. The soil from the pit is used to make banks around the pits where by four ridges are tied together. Furrows carry excess water from one pit to the next. Traditionally, this system is mainly practiced by the Matengo tribe of Mbinga District, living on the steep slopes of the Matengo highlands. The pits are locally called Matengo pits or Ngoro. The system is suitable for steep slopes of 20% - 50%, which are prone to erosion. Matengo (Ngoro)pits in Ruvuma CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 13 Terraces Terrace farming is a method of farming using “steps” that are built into the side of a mountain or hill. On each level, various crops are planted. When it rains, instead of washing away all of the nutrients in the soil, the nutrients are carried down to the next level. Terraced fields decrease both erosion and surface runoff, and may be used to support growing crops that require irrigation. Small terraces with the size of a ladder are dug on steep slopes for the purpose of breaking the slope and controlling soil erosion. They are used for growing mainly vegetable crops such as cabbage, onions, green pea and beans. • Fanya Juu terraces Fanya juu terraces are made by digging a trench along the contour and throwing the soil uphill to form an embankment. The embankments are stabilized with fodder grasses and in between cultivated portions. Over time, the Fanya Juu develops into bench terraces. FanyaJuu is a very versatile technology - ideally suited to smallholder farms, especially in sub-humid areas where the land is sloping and erosion a threat Fanya juu terraces are useful in semi-arid areas in harvesting and conserving water. The measure is suitable for soil too shallow for level bench terracing and moderate slopes below 20%. Fodder grasses may be planted on the bunds and fed to livestock. In the dry areas, water harvested from roads is directed into the trenches which allow production of bananas and fruits. However, they are not applicable on stony soils. • Fanya chini terraces Fanya chini terraces are made by digging a trench along the contour and the soil is put on the lower side of the contour trench. It is used to conserve soil and divert water. The embankment can be used to grow fodder. This is applicable on slopes of up to 20%. • Bench terraces Bench terraces are level or nearly level steps constructed or formed on the contour and separated by embankments known as risers. They are formed by excavation or developed from grass strips or Fanya Juu terraces. They are suitable on slopes up to 55%. • Stone terraces Stone terraces are useful in areas with steep slopes but high population density and scarce land. The terrace risers are made of stones collected from the land. Stone terraces are suitable where there is abundant availability of stones. 2.4.4 Agro forestry Practices and Technologies It is a dynamic, ecologically based, natural resource management system that, through integration of trees on farms and in the agricultural landscape, diversifies and sustains production for increased social, economic and environmental benefits. Agroforestry systems include both traditional and modern land-use systems where trees are managed together with crops and/or animal production systems in agricultural settings. Agroforestry play important roles in increasing the resilience to climate change impacts for small scale farmers and CLIMATE-SMART AGRICULTURE 14 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL in larger landscape approaches. Trees help fight climate change by storing carbon. Carbon, sequestered by trees intercropped with food and fodder crops and stored in above ground biomass and soil, contributes to reducing greenhouse gas concentrations in the atmosphere. Trees buffer against weather-related production losses, such as reducing soil erosion through e.g. hedgerow and contour planting - thus enhancing resilience against climate impacts. Trees bring nutrients from deeper soil layers, or in case of legume trees, through nitrogen fixation, and decomposition of leaf litter into fertilizer for crops. Trees on farms provide additional income and diversity of food sources through tree-based products. Agroforestry with Indigenous fruits trees can provide women with significant income. The combination of trees, crops and livestock mitigates environmental risk, creates a permanent soil cover against erosion and minimizes damage from flooding and acts as water storage, benefitting crops and pastures. Agroforestry serves to enrich farmers through the harvesting of diverse products at different times of the year. It also brings job opportunities from the processing of tree products, expanding the economic benefits to rural communities and national economies. Planting of heavy feeder trees (e.g. some of Eucalyptus spps) is discouraged in crop lands. 2.4.4.1 Common Agroforestry Practices • Tree in crop land This is the practice of growing crops in association with trees left during land preparation or planted for their economic, social or cultural value. Among the common values include production of fruits, fuel wood, timber, medicine, fodder and shade or soil fertility improvement. Some of the common species found on cropped lands include Leucaena spps. Faidherbia albida agroforestry in Mbarali (Source – ICRAF Tanzania) • Rotational woodlot The rotational woodlot is an agroforestry practice which involves alternating arable crops with improved tree fallow on the same piece of land over time. The practice is intended to simulate the effects of shifting cultivation systems, with tree species carefully selected for their fast growth rates, high wood yields, and/or soil enrichment capacity. The practice involves three phases namely; tree establishment phase (crop and young trees), fallow phase (woodlot) and the post-fallow phase (clearing for cultivation). CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 15 • Improved fallow This is a practice of improving a farm which after continuous cultivation is rested (fallowed) for one or two seasons to regain fertility by introducing fast growing, high fertility enriching plants normally herbaceous legumes, grasses and/or shrubs. Some of the species used to improve fallow land are Sesbania sesban (sesbania), fish poisoning plant (utupa), Chick Peas (Cajanus cajan/mbaazi), Marejea (Crotalaria ochroleuca) and herbaceous legumes like Lablab. • Fodder bank The practice involves growing of high quality fast-growing and high-yielding trees, shrubs, grass and herbaceous legumes in small homestead plots in order to provide low cost fodder supply to alleviate shortages of fodder and nutrition deficiencies to sustain livestock production. The animals are given supplements of protein-rich feedstuffs during the dry season when other good-quality fodder is scarce. The fodder may be cut, carried and fed to livestock in their enclosure (kraal). The kraal manure in turn is applied to crops thus enhancing nutrient cycle (soil resilience). The amount and quality of manure increase with good feeding of the animals. Some species used in fodder bank include; Leucaena leucocephala, Panicum maximum and Acacia spp. • Tree planting / afforestation It involves planting seedlings over an area of land where the forest has been harvested or damaged by fire or disease or insects. Trees contribute to climate change adaption by reducing wind speed, and decreasing damage to crops and degradation/erosion to the soil. They contribute to climate change mitigation by removing CO2 from the atmosphere. Trees provide shades to mitigate the impact of climate induced temperature rise. Reforestation provides other benefits by reducing land degradation and soil erosion, and improving water infiltration. Also forests provide multiple benefits for local communities such as wood and non-wood products, timber, fruits, fibre, medicines and honey, all of which can be important for the livelihood. 2.4.5 Conservation Agriculture (CA) Conservation Agriculture is a set of soil management practices that minimize the disruption of the soil structure, composition and natural biodiversity and has a potential to improve crop yields, while improving the long-term environmental and financial sustainability of farming. It encompasses farming practices which have three key characteristics: • First, minimal mechanical soil disturbance (i.e. no tillage and direct seeding); • Second, maintenance of a mulch of carbon-rich organic matter covering and feeding the soil (e.g. straw and/ or other crop residues including cover crops); and • Third, rotations or sequences and associations of crops including trees and legumes which are nitrogen-fixing. CA offers climate change adaptation and mitigation solutions while improving food security through sustainable production intensification and enhanced productivity of resource use. Management of soil fertility and organic matter, and improvement of the efficiency of nutrient inputs, enable more to be produced with proportionally less fertilizers. It also saves on energy use in farming and reduces emissions from the burning of crop residues. Moreover, it helps to sequester carbon in soil. CA contributes to adaptation to climate change by reducing crop vulnerability and protects crops from extreme temperatures. Hence, CA offers opportunities for climate change adaptation and mitigation solutions, while improving food security through sustainable production intensification and enhanced productivity. CLIMATE-SMART AGRICULTURE 16 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4.6 Common CA practices and technologies • Cover cropping Cover cropping is a technology that aims to maintain or cover soil surface during and between cropping operations. It is well known by farmers and extension agents. It can be achieved by planting leafy legumes between the plants of the main crop, providing shade, suppressing weeds, reducing ground temperature and evapo-transpiration, and thereby retaining soil moisture. It has also been used for reducing effects of raindrop impact and aggregate disintegration from slaking. Ground cover also prevents raindrops from directly striking the soil surface and allows rainfall to slowly penetrate the soil surface. Ground cover helps to sequester carbon dioxide in the soils but also control soil erosion. • Mulching Mulching is a technology of applying a protective covering, usually of organic matter such as grass, leaves, straw, or peat, around plants or on the surface of the soil. Mulching helps to conserve moisture, improve the fertility and health of the soil and reduce weed growth. When applied correctly, mulching can dramatically improve soil productivity. Maintenance of a mulch layer provides a substrate for soil-inhabiting microorganisms which helps to improve and maintain water and nutrients in the soil. This also contributes to net increase of soil organic matter - derived from carbon dioxide captured by photosynthesis in plants, whose residues above and below the surface are subsequently transformed and sequestered by soil biota. • Crop Rotation Crop rotation is a practice of growing different crops in a field each year or season. The new crop planted during the succeeding season will be from a different family. The idea behind this is to change what soil nutrients the crop uses, and the insects it attracts. So, the pests never get used to one field because crops are constantly changed. In terms of soils, each crop needs different nutrients. Changing the crop every year prevents depletion of any one nutrient in the field. Crop rotation is also effective in suppressing weeds because of regular changes in the root zone composition and patterns of nutrient absorption. Rotations and crop associations that include legumes are capable of hosting nitrogen-fixing bacteria in their roots, which contributes to optimum plant growth without increased gas emissions induced by fertiliser’s production. Crop rotation over several seasons also minimises the outbreak of pests and diseases. • Intercropping Intercropping is a multiple cropping technology involving growing two or more crops in proximity in the same field. The farmers commonly use a cereal-legume intercrop, mixing of crops for example millet, sorghum or maize with cowpeas or groundnuts. Farmers acknowledge leguminous crops such as beans, cowpeas, lablab and pigeon peas are suitable for intercropping as they contribute nutrients to the soils by biological nitrogen fixation. In this case, intercropping reduces depletion of individual soil nutrients. It can also involve new crop varieties (e.g. drought resistant). CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 17 Maize-Pigeon pea intercropping in Babati, Manyara The most common goal of intercropping is to produce higher yields on a given piece of land by making use of resources that would otherwise not be utilized by a single crop. It provides a family with a balanced diet of staple grains, protein-rich beans, and green leaves for essential vitamins. It also reduces risk of total crop failure by having two crops instead of one. Also intercropping increase resilience to drought and reduced pest and diseases • Minimum / Zero Tillage Minimum Tillage means reducing tillage operations required to plant a crop that usually involves scratching or ripping along the row where the crop is to be planted and leaving the rest of the land untouched until weeding is required. Alternatively, farmers may just dig holes or pits where the seed will be sown (such as chololo pits in Dodoma and basins in Newala). It is a practice that minimizes run-off and increases infiltration rates. It actually ensures enough moisture is stored in the soil for plant growth. Avoidance of tillage minimises occurrence of net losses of carbon dioxide by microbial respiration and oxidation of the soil organic matter and builds soil structure and bio-pores through soil biota and roots. Zero tillage has many advantages among others including minimal soil disturbance; retention of crop residues; seeds planted directly into previous crop’s residue; and crop rotation. It reduces erosion; improves soil quality and structure, soil biota; reduces evaporation of water, helps retain nutrients. In addition, depending on rotation, no-till reduces greenhouse gas emissions of nitrous oxides. • Crop Residue Management Crop residues management is the practice where by crop residues are left in the field /farm after the crops have been harvested. These residues include sticks and stubble/stems, leaves and seed pots. Crop residues can also be used as animal feed outside the crop field. The protective soil cover of leaves stems and stalks from the previous crop protect the soil surface from heat, wind and rain, keeps the soil cooler and reduces moisture losses by evaporation. In drier conditions, it reduces crop water requirements, makes better use CLIMATE-SMART AGRICULTURE 18 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL of soil water and facilitates deeper rooting of crops. In extremely wet conditions, crop residues management facilitates rain water infiltration, reducing soil erosion and the risk of downstream flooding. 2.4.7 Soil Fertility Management Practices and Technologies A healthy soil is fundamental for sustained agricultural productivity and the maintenance of other vital soil- mediated ecosystem processes. To cope with climate change, specific management practices need to be adapted. Management practices that increase soil organic carbon (SOC) content from year to year through organic matter management will bring benefits. Soil Fertility Management Practices and Technologies include: • Manure Application Farm Yard Manure (FYM) - is an appropriate technology to enhance nutrient availability for ensuring high yields. FYM is also good for improving soil structure and control evaporation. Use of FYM increases crop– livestock integration such that crop residues from well managed crops are fed to livestock. The livestock manure is then returned to the fields at the start of the cropping season. A large proportion of the mitigation potential of agriculture (excluding bio-energy) arises from soil carbon sequestration, which has strong synergies with sustainable agriculture and generally reduces vulnerability to climate change. With regard to CO2 sequestration in soils, use of FYM can achieve high carbon and improve soil structure and quality, because the accumulated carbon is in the organic form of humus. This will improve climate adaptation by reducing the impacts of flooding, droughts, water shortages and desertification, thereby also improving food and water security. Compost manure - refers to a mixture of organic matter, from leaves and manure that has decayed or has been digested by organisms, and can be used to improve soil structure and provide nutrients. It helps dry soil to absorb and retain more water, compacted soils to regain their elasticity and poor soils to bring forth abundant farm produce; they provide plants with nutrients which they require to grow to their full potential. Harvesting crops removes carbon from the soil that would otherwise return to the soil when the plant dies and decomposes. Compost returns organic matter to the soil. The nitrogen in compost can increase soil productivity, which can lead to increased crop residues and an increased return of carbon to the soil. Composting increases the formation of stable carbon that remains bound in the soil for long periods of time. Applying organic matter to soils is one of the most effective ways to divert CO2 from the atmosphere and convert it into organic carbon in the soil. Compost use can supply at least some of the mineral nitrogen that would otherwise have to be provided through mineral fertilisers, as well as most, if not all, of the crop’s phosphorous, potassium and trace element requirements. Substituting the use of mineral fertiliser through compost use offers an opportunity of reducing GHG emissions caused by the manufacturing and transportation of fertilisers. Efficient Use of Fertilizer (Micro Dosing) - involves the application of small and affordable, quantities of fertiliser onto or close to the seed at planting time, or a few weeks after emergence. This can be done by filling a soda bottle cap with fertiliser and applying it directly to the root of the crop. The micro-dosing technique increases the efficiency of fertilizer use, and helps improve productivity. For efficient use of Fertilizer soil status need to be known through soil testing. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 19 Integrated Soil Fertility Management (ISFM) - aims to make available required soil nutrients by balancing different on-farm soil organic sources (amendments) with nutrients from mineral fertilizers (to address deficiencies) and reducing nutrient losses through soil and water conservation. It is advised that use of fertilizers should be under the concept of ISFM which is a set of agricultural practices adapted to local conditions to optimise the efficiency of nutrient and water use and improve agricultural productivity. ISFM aims to optimise the use of organic matter that provides nutrients, sequesters C and enhances water storage (e.g. compost, animal manures or green manures); and enhance nutrient efficiency through crop rotations or intercropping with nitrogen-fixing crops and judicious/precision use of inorganic fertilizer to reduce losses. Also ISFM minimize GHGs emissions (reduced traffic and tillage and efficient use of organic and inorganic fertilizers). ISFM strategies centre on the combined use of mineral fertilizers and locally available soil amendments (such as lime and rock phosphate) and organic matter (crop residues, compost and green manure) to replenish lost soil nutrients. This improves both soil quality and the efficiency of fertilizers and other agro-inputs. In addition, ISFM promotes improved germ-plasm, agroforestry and the use of crop rotation and/or intercropping with legumes (a crop which also improves soil fertility). Farmers who have adopted ISFM technologies have more than doubled their agricultural production and increased their farm-level incomes. ISFM improves resilience of soils and agricultural production to weather variability; increases soil organic matter and soil organic carbon; improves soil health and fertility leading to increased yields and; lowers potential for nitrogen leaching and greenhouse gas emissions, potentially increases soil carbon. Other soil fertility management practices include; mulching, crop rotation (see under CA). 2.4.8 Crop Management Practices and Technologies • Adapted crops and crop varieties Adapted crops and crop varieties involves improved seeds for high yielding, fast maturing, drought tolerant, salinity tolerant and flood tolerant. Climate change affects the agricultural yield directly through changes in temperature and precipitation, and indirectly through changes in soil quality, pests and diseases. One key technology is improved seeds which are early maturing and drought tolerant crop varieties. It is noted that farmers understand and are using improved seeds in their crop production with the main objective to grow high yielding varieties as an adaptation strategy to climate change. Improved, high-yielding varieties include grain, legume, fruit and vegetable varieties that have been bred to improve and increase yields. Early maturing crop varieties enable the crop to escape stress at the end of the season and are ideal for intercropping as they provide less competition for moisture, light and nutrients as compared to late maturing varieties. In addition, they offer flexibility in planting dates, which enables multiple plantings in a season to avoid risk of losing a single crop due to drought and avoidance of known terminal drought periods during the cropping season. These advantages make the early maturing crop varieties more remunerative and less risky to climate change impacts. Drought tolerant crops bred specifically to be adapted to climate challenges in a particular region escape drought through early maturity. CLIMATE-SMART AGRICULTURE 20 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL • Integrated Pest Management (IPM) Integrated Pest Management (IPM) is a broad-based approach that integrates practices for economic control of pests. It aims to suppress pest populations below the Economic Injury Level (EIL). It is a strategy that promotes a safer and more sustainable management of pesticides. IPM lies at the centre of insect, disease and weed control. The combination of farming strategies, biological control agents, and necessary pesticide (e.g. herbicide, fungicides and insecticides) use can help farmers address pest problems using a variety of methods. IPM reduces the need for pesticides by using several pest management methods; shields the environment from excessive or unnecessary pesticide applications; fosters clean water supplies; and promotes sound structures and healthy plants. IPM contributes to climate change adaptation by providing a healthy and balanced ecosystem in which the vulnerability of plants to pests and diseases is decreased. By promoting a diversified farming system, the practice of IPM builds farmers’ resilience to potential risks posed by climate change, such as damage to crop yields caused by newly emerging pests and diseases. However, the multiple impacts of climate change could significantly reduce the effectiveness of current IPM strategies, leading to higher crop losses. Better knowledge and understanding of pest behaviour under different projected scenarios are required to adopt and develop new IPM technologies to respond to threats resulting from climate change. • Timely or early planting/sowing Timely or early planting/sowing (in some places also dry sowing) is a practice of adapting to climate change. The practice ensures optimal use of the short rain season and makes efficient use of accumulated nutrients from organic sources during the dry season (nitrogen flush). The use of this practice can be strengthened by climate services through timely provision of weather information. • Crop Insurance and Safety Nets Crop insurance is purchased by agricultural producers, including farmers, ranchers, and others to protect themselves against either the loss of their crops due to natural disasters, such as hail, drought, and floods, or the loss of revenue due to declines in the prices of agricultural commodities. The two general categories of crop insurance are called crop-yield insurance and crop-revenue insurance. Safety nets are a form of social insurance comprising programmes supported by the public sector or NGOs that provide transfers to prevent the poor from falling below a certain poverty level. These programmes include cash transfers, food distribution, seeds and tools distributions, or conditional cash transfers (Devereaux, 2002). Safety net programmes can actually be a form of social investment into human capital (e.g. nutrition, education) and productive capital (e.g. allowing households to adopt higher risk and higher productivity strategies; (SOFI, 2010). Safety nets are increasingly being linked to rights based approaches to food security moving from a charity to entitlements. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 21 2.5 LIVESTOCK SUBSECTOR PRACTICES AND TECHNOLOGIES 2.5.1 Improved Livestock Breeds One key technology in livestock production is improving the genetic potential of cattle, poultry, pigs, sheep and goats to produce livestock which grow bigger and faster and at the same time resistant to stress (e.g. water, heat , diseases stress etc). This can be achieved by combining the desirable traits of the exotic breeds with the hardiness, and disease resistance of local breeds through cross-breeding or upgrading. The aim of cross-breeding is to improve local breeds to improve production (e.g. meat, milk and eggs), maturity time, resistant to stress etc. In this way, livestock keepers increase incomes by selling more Livestock products and by-products. Different livestock types and breeds require specific environmental conditions. Climate determines the type and quality of pasture, availability of water, livestock pests and diseases and therefore overall livestock types and their productivity. Adapted livestock types and breeds often survive and do well under extreme climatic conditions. Under the changing climate, care should be taken in deciding the appropriate livestock enterprise for any particular area. 2.5.2 Improved Feeds Improved feeds includes pastures, concentrates formulated using agro industry by products (molasses, brewers waste, maize/rice/wheat bran, oilseed cake). These feeds can be altered to improve its digestibility and provide needed nutrients. Addition of feed additive can also be used to improve digestibility and nutritive value of feeds. Such Feed improvement aims at reducing methane (CH4) emissions. Climate change mitigations result from a more efficient absorption of nutrients, with a consequent reduction in gaseous losses, and the ability to produce comparable amounts of dairy and meat with fewer animals. Feed supplements are required in small amount but are very important in enhancing productivity of livestock. Examples of feed supplements are urea–molasses multi-nutrient blocks, low bypass protein, lipids, and calcium hydroxide. Succulent plants can offer an alternative source of water as well as feed to grazing animals especially during the dry season. Example of succulent plants includes Commelina spps, Pyrenacantha malvifolia and Water melons (Citrullus vulgaris) locally known as “mahikwi”. 2.5.3 Livestock Improved Feedings Improved feeding strategies include; cut and carry; rotational grazing by paddocks, fodder crops, and grassland restoration and conservation may be adopted to improve Livestock productivity. This entails storing animal feeds (stover, grass, grain) and making better use of feed (by combining types of feed), growing grass varieties specifically suited to the agro-ecological zone, and many other practices, such as fodder conservation and animal fattening. The strategies also involve managing paddocks and/or pastures for ensuring enough fodder for livestock feeding at home, especially under zero grazing. Keeping livestock under zero grazing and in paddocks helps in improving manure management practices. CLIMATE-SMART AGRICULTURE 22 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.5.4 Pasture and Grazing Land Management • Pasture Management Pasture management is a practice of growing healthy grass and related plants to profitably sustain forage availability and livestock production while ensuring ecological health. Pasture management can provide significant benefits including improved forage yields, lower feed costs and improve livestock performance. Pasture spps African fox tail grass (left) and Elephant grass (right) Good pasture management tends to decrease carbon release to the atmosphere. The key to reducing GHG emission is to maintain healthy and high quality pastures. High quality feed means higher feed efficiency and more nutrients absorbed by the animal. The rate of consumption by animal (e.g. cattle) is influenced with high quality forage, increasing the efficiency of digestion and reducing the amount of time needed to graze. Faster digestion and greater feed use efficiency means less production of methane. Improved pastures also have numerous indirect benefits to reduce GHG production from animal production. Perennial forages trap atmospheric CO2 with their extensive root systems, storing carbon meters below the ground. Grasses and alfalfa not only improve the soil by increasing organic carbon, but are capable of absorbing excess water, lowering the water table and helping to control soil salinity. Reducing soil moisture also limits the risk of N losses by de-nitrification, cutting down the amount of nitrous oxide (N2O) creation. Pastures also provide soil cover, protecting against erosion, and maintain or improve water quality. • Grazing Land Management Different methods can be employed to manage grazing land depending on indigenous knowledge in regard to natural resources management, human and animal diseases relative to their environment. Both traditional and improved grazing land systems can be employed managing grazing lands. Under, traditional grazing land Management system, the communities control resource use pattern, and conservation using the traditional knowledge of the ecosystem and the biological diversity of the areas. Some of the traditional grazing land Management systems are Ngitili and Olelii. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 23 Ngitili - is a traditional fodder conservation system that was developed by the Sukuma agro-pastoralists (Shinyanga) as a means of alleviating acute dry season fodder shortage. Ngitili encompasses retaining of an area of standing hay until the rainy season ends, the area remains closed to livestock and other activities at the onset of the rainy season and is opened up at the peak of the dry season to allow the livestock get dry season fodder. Grazing under ngitili normally starts from July/August after crop residues and forage in fallow areas has been depleted.Animals also removed from ngitili after all the fodder is exhausted or when fodder becomes available outside the ngitili. Ngitili System in Shinyanga Olelii -is a traditional fodder conservation system developed by the Maasai pastoralists (Arusha) as means of conserving fodder for the dry season or for the calves, sick animals and/or milking herd. The vegetation is left to grow and regenerate during wet season and livestock are allowed to graze in dry season. The elder groups oversee and directs on management and use of resources such as grazing pattern and conservation of fodder for dry season grazing. The Traditional ecological and farming knowledge (TEK) systems such as grassland and forest conservation and use, uses of biological diversity (including ethno-veterinary, nutritional and medicinal uses) is practiced and passed from one generation to another through the traditional institutions 2.5.5 Improved Grazing Land Management • Zero Grazing A zero-grazing system is where grass is mechanically mown and brought to livestock. Its appeal is that it allows livestock to consume forages from fields that are too far away, or are separated by busy road, to be included in the grazing rotation. Zero-grazing can also play a role when utilizing fields too wet for grazing, provided the machines employed have sufficiently wide wheels to safely distribute their load. This system increases productivity to livestock due to minimum energy utilization, also there is no land trampling so controlling soil erosion realization. CLIMATE-SMART AGRICULTURE 24 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Livestock kept under zero grazing 2.5.6 Manure Management Major emissions from manure come in the form of methane (CH4) from anaerobic decomposition of manure during storage as well as N2O formed during storage and application. The creation of these gases is influenced by a variety of factors: temperature, oxygen level, moisture or amount of nutrients. In turn, these factors are affected by manure type, animal diet, the type of manure storage and handling and manure application techniques. To help reduce GHGs creation and work with large amounts of excess manure, it is important that manure management in the area concentrates on disposing manure in an environmentally and economically friendly manner. One of the economic and environmental friendly systems of managing manure is the use of Biogas digester On Farm Biogas Production This aims at reduce Greenhouse Gases (GHGs) emissions and develop more sustainable livestock operations. The GHGs are reduced by production of renewable energy as a substitute for fossil fuels via reduction of fugitive GHGs emissions from stored and land applied manures, as well as by reduction in use of chemical fertilizers in crop production. Utilization of livestock droppings (residue) in this way is important for preventing environmental pollution, also decomposed manure (slurry) is rich in nutrients and hence applied to crops be it food crops and pasture increases productivity. Biogas plant Cooking using biogas CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 25 2.6 FISHING AND AQUACULTURE ACTIVITIES The main elements of climate change that could potentially impact fishing and aquaculture production are mostly associated with water level changes in water bodies and temperature fluctuations. These changes are triggered by the impacts of climate change such as changes in rain seasons and patterns, an increase in extreme events such as prolonged dry spell periods, drought and flood, water stress which results in changes of oxygen levels, solute concentration and water pollution through algae proliferation. However, there some fishing and aquaculture practices which are considered climate-smart based on their ability to ensure sustainable productivity in the face of climate change. 2.6.1 Pond Aquaculture/Fish Ponds It is a common technology which uses pond to raise fish for domestic or market purposes. It is commonly practiced in areas with easy access to water, though it can also be practiced in dry areas where water can be harvested and stored for fish farming. Inland finfish culture which uses ponds is a dominant form of aquaculture in Tanzania. The Size of pond used in this type of aquaculture ranges from a few hundred square meters to a few hectares and are often shallow ponds. CLIMATE-SMART AGRICULTURE Cement Fish pond Earth fish ponds in Kalenga, Iringa The practice of culturing more than one species of fish in the same pond is known as Polyculture and is known to have higher yield through proper food utilization, because different species of fish exploit food at different trophic levels in the pond. Proper management of fish pond is critical to reduce production of noxious gases and mitigate risks of disease outbreak. It is advised to consider species of fish which are adaptable to changes in oxygen, temperature and saline species such as Nile Tilapia and catfish. In Marine milk fish is known to be tolerant to oxygen, temperature and poor water quality. Planning of pond management based on the knowledge of climate change impact such as water availability, temperature changes, flooding events and periods of prolonged dry spell are critical on ensuring sustainable fish production. 26 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL CLIMATE-SMART AGRICULTURE 2.6.2 Integrated Aquaculture and Cage Culture Integrated aquaculture practice involves an integration of fish with another production system such as rice which is known as rice cum fish culture or integration of aquaculture with animal husbandry. In this way, the integrated aquaculture practice may exist in different forms. Though, in most cases fish species cultured are those which feed at low trophic levels of food chain. The practice is mostly practiced by a single-family unit, conducted at small-scale level and takes various traditional forms. The practice is considered climate-smart as it contributes to food security and diversification, fish species are less susceptible to temperature changes and contribute on carbon sequestration Integrated fish farming with crops 2.6.3 Sustainable Fishing This include fishing practices which uses passive fishing gears such as gill nets, pots, hook, lines and traps with minimal destruction to aquatic environment, fish reproduction sites and ensure sustainability in productivity. Such practices may involve use of bio-degradable materials and use of innovative technologies such as echo-sounders in vulnerable or sensitive habitats. The practices are climate-smart because they focus on increasing productivity and sustainability of production systems even under the impact of climate change. 2.6.4 Seaweed Farming Seaweed farming is the practice of cultivating and harvesting seaweed. In its simplest form, it consists of the management of naturally found batches. In its most advanced form, it consists of fully controlling the life cycle of the algae. It is practiced mainly along the sea shores and in Tanzania is practiced widely in Zanzibar and along the shore. The culture of seaweed requires minimal energy inputs and, therefore, has a relatively small carbon footprint. The rapid turnover in seaweed culture of approximately three months per crop (in the tropics) makes one of the climate-smart practices. This is because its carbon uptake potential far exceeds that obtained through other agricultural activity of the same comparable area. Additionally, sea weed farming systems can filter nutrients and provide a “cleaning service” to coastal marine environments and thus contributing on enhancing ecosystem service. CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 27 Seaweed farming 2.7 OTHER CSA PRACTICES AND TECHNOLOGIES 2.7.1 Bee-keeping Beekeeping or apiculture is the maintenance of honey bee colonies, commonly in man-made hives. A beekeeper (or apiarist) keeps bees in order to collect their honey and other products that the hive produces (including beeswax, propolis, pollen, and royal jelly), to pollinate crops, or to produce bees for sale to other beekeepers. Hence, bee keeping contributes in increasing agricultural productivity through pollination, protection of surrounding environments as bee keepers need to maintain vegetation or forest cover and enhance resilience as source of income. CLIMATE-SMART AGRICULTURE Beekeeping in Iringa Traditional beehives are hung on trees close to a nearby forest. They are made by cutting a cylindrical log, carefully scooping inner content to make a hollow structure and sealing the two ends with small holes for exit and entry. Contrast to traditional hives, modern hives have straws to test honey is readiness before harvesting. By opening the hive and taking out the straw, the farmer will know whether the honey is ready to harvest. This method helps beekeepers to increase productivity. 28 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL CLIMATE-SMART AGRICULTURE 2.7.2 Climate Information Services Timely communication of climate information helps prevent the economic setbacks and humanitarian disasters that can result from climate extremes and long term climate change. Climate information also plays a crucial role in national development planning, for managing development opportunities and risks as well as for mitigation and adaptation. Efficient application of climate services requires that climate information become available to stakeholders. Availability of climate information services offers great potential to enable farmers to make informed decisions, better manage risk, take advantage of favourable climate conditions, and adapt to change. 2.7.3 Improved Post-Harvest Appropriate post-harvest practices and technologies are important on ensuring sustainable applications of CSA practices by ensuring produces are sold in good quality and condition. Practices and technologies such as winnowing, drying, improved storage facilities, cold room transportation vans and other processing methods are key for sustainable productivity and market linkages of agricultural produce. This in turn increases community resilience to the impact of climate change by ensuring food and nutrition security. 2.8 UPSCALING CSA PRACTICES AND TECHNOLOGIES Agriculture is considered climate-smart when it sustainably increases agricultural productivity and incomes, builds resilience to climate change and reduces greenhouse gas emissions. To achieve this, there is urgent need to upscale CSA practices which can be facilitated through; • Proof of concept at sites/field established based on clear objectives set by farmers, extension officers and possibly researcher where possible using inclusive and participatory multi stakeholder planning approach. • Creation of innovative CSA practices toolbox customized to an area, will allow farmers extension officer, researchers and other relevant stakeholders to identify CSA technologies and practices prioritized based on yield, resilience potential and other beneficial features customized to an area. • Promotion of holistic approaches which are cross-sectoral will foster linkages between relevant stakeholders across value chain for sustainable and profitable CSA practice adoption at all levels and scales by farmers. • Promotion of climate-smart agricultural innovative CSA financing arrangements and business models needs to be encouraged by policy and decision makers such that agribusinesses, SACCOS, banks and farmers based organization can spread risk and develop substitutes for collateral through multi-party financing mechanisms (PWC, 2012). • Ensure equitable land access to men and women alike, increase investment in agriculture, promote sustainable use of inputs and ensure availability of reliable markets of the produce. • Improve knowledge management system –by strengthening farmers knowledge of CSA practices, facilitate sharing the techniques and provide the greatest support to local knowledge system 2.8.1 The challenges in upscaling CSA While CSA technologies and practices are generating significant benefits, their adoption often faces a variety of challenges or barriers by famers such as:- • Insufficient information on potential gains of adopting new technologies, training and extension • Limited availability and access to inputs • Limited capacities on implementing improved practices • Significant upfront expenditure required on adopting new technology • Limited number of CSA projects CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 29 CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 3.1 INTRODUCTION Successful CSA implementation requires strong institutional support to: promote inclusivity in decision making; improve the dissemination of information; provide financial support and access to markets; provide insurance to cope with risks associated with climate shocks and the adoption of new practices; and support farmers’ collective actions. In this regard, there are specific roles to be fulfilled by different stakeholders, also there are series of approaches and methods that should be considered based on local situation and the characteristics of the target group. 3.2 IDENTIFICATION OF STAKEHOLDERS Multi-stakeholders’ participation and active community involvement in projects/program design and development are critical for successful climate-smart agriculture implementation and upscaling. Different stakeholders have been identified with different roles to play in the CSA implementation among them are; Government, NGOs, Development and Research Partners, Private Sector, Farmers and Media. 3.3 ROLES OF DIFFERENT STAKEHOLDERS ON IMPLEMENTATION AND UPSCALING OF CSA Different institutions have different roles to play in order to make CSA Implementation successful and sustainable for agriculture development. The following are some of the roles of stakeholders in different levels; 3.3.1 Government • Sensitization and Awareness Creation at all levels This can be done using various means such as Policy briefs, mass media (radio, TV, newspapers, social media and drama groups), farmers’ exhibitions and resource centers (demonstrations), workshops, incorporating CSA concept in curriculums at different levels of education. • Amendment and enforcement of related agriculture policies Climate-Smart Agriculture is an initiative adopted from abroad, and it has got specific principles, practices and technologies, but also it is globally implemented under UN agencies such as FAO. Due to that, the need for the Government to amend Agricultural related Policies to accommodate CSA concepts where it is found necessary to speed up CSA up-take, is a core responsibility, and ensures their enforcement. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 3| 30 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL • Capacity Building of Extension agents The Government has to organize and conduct workshops and meeting for capacity building for the extension agents to enable them understand and then engage in disseminating and promoting the CSA guideline appropriately • Establish Partnership with Other Institutions The government should establish partnership/collaboration with institutions and the private sector that will help and improve access of required implements/equipment including promoting local manufacturing of equipment and maintenance/service of equipment or facilitating purchase of that equipment such as rippers and biogas plants, for upscaling identified CSA technologies and practices • Distribution on incentivizing agricultural subsidies The government has to help the implementation of CSA by providing subsidies to agricultural inputs that support CSA practices and technologies to open a door for economic disadvantaged farmers to adopt CSA. • Establish Monitoring and Evaluation Systems To ensure CSA good performance and sustainability, the Government, in relation with other CSA stakeholders has to develop monitoring systems which will help to evaluate CSA achievements basing on the temporal and spatial scales, but also will merge a door for mistake correction towards higher CSA achievements • To establish link to connect farmers with markets and service providers In relation with other CSA stakeholders the Government has to provide suitable atmosphere on legal and policy aspects which will allow farmers to be linked easily and assuredly with markets and other service providers. To have Investments that support agricultural marketing and the food system, including roads and market infrastructure • To Develop and provide improved early warning information (weather and climate) The concept of Climate-Smart Agriculture, refers, agriculture activities to be carried out with great achievements by making farmers smart by being aware and make adaptation of the on-going changes of weather and climate. This requires developing reliable and trusted systems of early warning information 3.3.2 NGOs NGOs are typically strong in providing social services, especially when supporting poor communities. For example, building social capital by organizing farmer groups to articulate their own needs and formulate solutions collaboratively, brings immediate positive effects at the local level. • To fast up-take of CSA technologies by Improving the quality and relevance of research on CSA through local participation. • Promote Indigenous CSA Knowledge, Practices and Technologies which are identified as CSA practices and technologies. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 31 3.3.3 Research partners Research Institutions can help in bringing together different stakeholders using Learning and Practice Alliance (LPA) approach which engages key stakeholders including policy makers, practitioners and farmers to join and work together in addressing existing problems and identify potential solutions. The LPA approach has the capacity to influence change in attitude, strategies, planning and resource allocations for upscaling CSA best technologies and practices. Some of the roles of research partners include; • Participatory Research on Improved Technologies and Practices • Strengthening capacity of agricultural research systems for linking with other actors (e.g. through stakeholder platforms, alliances and consortia, technology transfer and commercialization • Bring Together Stakeholders Through Learning and Practice Alliance 3.3.4 Private Sector As markets become increasingly important in developing economies, private sector actors also become significant providers of research and development, education and extension services. When seeking private sector support for CSA initiatives, it is important to bear in mind that the private sector’s main priorities are profit and public perception. CSA works to establish a ‘triple win’ scenario in which innovative practices produce higher yields, build resilience to climate change (reducing long-term risks) and lower carbon emissions all along the supply chain. By contributing to CSA, private businesses can enhance their brand recognition among key suppliers and consumers. Key private sector actors and the possible support they might provide to CSA initiatives include; • Strengthening of informal agricultural Markets (e.g. certification and training of traders) • Develop and Implement Risk Management Strategies such as productive social safety nets (e.g. cash transfers, food distribution, and seed and tool distribution, conditional cash transfers, food for work 3.3.5 Farmers Farmers should form groups but also identify champion farmers who are very effective in obtaining and disseminating knowledge of CSA technologies and practices. Establishing farmers’ groups and champion farmers should of course consider social dimensions due to the fact that the preferences of dissemination pathways always differ among gender groups Farmers should engage in farmer field schools (FFS), which will include demo plots to help learn and disseminate practical knowledge on CSA packages. Learning visits and/or farmer field days/shows should be organized and facilitated for farmers. In addition, extension staff, private sector and policy and decision makers should learn by seeing. This will help farmers share knowledge and experiences of CSA practices among themselves, but also with policy and decision makers, extension agents and private sector Knowledge sharing products (KSPs) should be designed to suit each category of stakeholder. Those with low education level, field days could be more appropriate mode of dissemination; farmers with small farm size prefer fellow farmer/trainers field visits; while young and educated farmers, print materials, electronic knowledge sharing such as use of media and mobile phones could be appropriate CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 32 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 3.3.6 Media Mass media can reach large audiences with messages about CSA. Broadcast and electronic media include radio, television, film and the internet; print media includes newspapers, journals, publications; outdoor media includes posters, billboards and other materials placed in public view. An important channel for disseminating informative and educational contents, media can both reflect public opinion and shape it. In recent years, more and more people, even in rural areas have gained access to media hardware such as radios, televisions, computers and smart phones. Innovative technologies, such as solar-powered electronic devices, are also becoming increasingly important in mobilizing the media for development purposes. 3.3.7 Development Partners/Inter-governmental Institutions Development partners are very crucial stakeholders in CSA implementation in Tanzania. They help in changing the mind-set of policy makers, practitioners and also farmers by emphasizing the importance of Indigenous Knowledge (IK) that is compatible with best CSA technologies and practices, and supported with scientific knowledge in scaling up through communicating research findings on IK and through training. Some of their roles are; Provide technical assistance, Provision of sourcebook, Provide financial assistance in promoting CSA and facilitate capacity building to increase knowledge and skills on upscaling best CSA technologies and practices 3.3.8 Religious institutions and communities The term ‘institutions’ does not merely refer to types of organizations; it also encompasses cultural and social norms and conventions. An awareness of public opinions and values is therefore important when formulating a CSA strategy. While religious institutions or issue groups are unlikely to provide CSA-related advisory services, they can offer indispensable insights into prevailing beliefs and values. They can be mobilized as powerful tools for advocacy and endorsement 3.4 STAKEHOLDERS ENGAGEMENT MECHANISMS Basing on the provided roles of stakeholders, mechanisms for implementation are very important; hence the need to identify stakeholders’ engagement mechanisms is crucial for effective implementation of Climate-Smart Agriculture. Establishment of different platforms at all levels will be used as the main mechanism to engage different stakeholders to be involved in the CSA implementation, for example creation of CSA Networks and convening for national/regional events. Also the stakeholders have to be aware on how they engage in the implementation of CSA basing on their roles. For example Government through mainstreaming of CSA initiative in policies and strategy is one of the mechanisms for its engagement. 3.5 APPROACHES FOR CSA INTEGRATION The agricultural extension approach in Tanzania involves farmers’ groups in the planning and implementation process. It is also integrating different extension providers, allowing room for pluralistic extension approaches and empowering farmers organizationally and financially to demand for appropriate services. The extension services use a combination of dissemination pathways such as • Gender responsive approach Social inequality and social inclusion, particularly in reference to gender, have been recognized as a CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 33 foundational issue in development .The successful of CSA practices requires institutional and behavioral change, which is not possible without social analysis (including gender analysis) influencing policies, projects, and other interventions aimed at achieving sustainable CSA. • Community Based Approach This is the approach whereby a practicing farmer or livestock keeper selected by their community and trained to a standard where they can offer credible advice and services in a specific area of production. A sizeable proportion of those trained 5-10 years ago have built a loyal client base by charging affordable fees for their services, and plan to continue in the role indefinitely • Farmer Field School Approach It is used throughout the country and is incorporated within DADPs. It uses experiential learning and group approach and currently its successes have been seen especially in smallholder’s irrigated rice farms where production has increased, key farmers train others. The impact of the approach is an increase in production seen in FFS members compared to non-FFS. Agricultural resource centres are permanently established in each District/ward used for demonstration of good agricultural technologies/practices. • Farming System Approach This is the approach where by farmers priorities are incorporated into the research agenda & user-friendly technologies are developed. • Farmer to Farmer Extension Approach This is the approach whereby there are trained farmers who can train others. • Champion Farmer Approach This is the approach whereby extension services choose farmers to work with them in implementing their programs. Those farmers selected to lead “farmer-to-farmer” extension are often called model, master, or lead farmers and are chosen according to their agricultural expertise • Landscape and Ecosystem Services Approach This approach deals with large-scale processes in an integrated and multidisciplinary manner, combining natural resources management with environmental and livelihood considerations, It is also factors in human activities and their institutions, viewing them as an integral part of the system rather than as external agents • Payment of Ecosystem Services Approach These are incentives offered to farmers or landowners in exchange for managing their land to provide some sort of ecological service. They have been defined as “a transparent system for the additional provision of environmental services through conditional payments to voluntary providers. • Nucleus and Out Growers Approach Formal arrangement between agriculture companies and farmers (contract farming), the private sector facilitates farmers’ access to credit, improved inputs, pooling of farmers’ produce, processing and developing market links. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 34 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 4.1 INTRODUCTION This topic addresses the issue of mainstreaming Climate-Smart Agriculture (CSA) into development plans at different levels. The first part of the topic looks at awareness and sensitization on CSA. The second part addresses the CSA related activities. Finally, the third part focuses on budgeting for CSA activities and how climate change affects investment needs for agricultural development to support food security, poverty reduction and economic growth. 4.2 AWARENESS CREATION AND SENSITIZATION ON CSA 4.2.1 Meaning of awareness Awareness is having knowledge that something exists, or understanding of a situation or subject at a given time based on information or experience (in simple term is knowing what is going on). Creating awareness is letting the right people know that the information/service exists and is available. To raise awareness is to inform and educate people about a topic or issue with the intention of influencing their attitudes, behaviours and beliefs towards the achievement of a defined purpose or goal. 4.2.2 Meaning of sensitization Is the process of making someone react to something that previously had no effect. Basing on CSA dissemination, sensitization aims at making all stake holders to be responsive to their roles and contributions on the implementation of CSA practices and technologies 4.2.3 How to create awareness Many African smallholder farmers and farm communities experience low crop and animal yields but they are not aware that, this is partly a result of climate change. Most of them are not aware of what to do to remedy the situation. The current climate change discourse is very much promoted by international NGOs and some CSOs with little contribution from local farmers and communities. Other stakeholders such as CSOs can be consulted to be involved in awareness creation. Awareness raising is an important stage for effective dissemination of knowledge and technologies, to be successful, it needs to use all appropriate communication channels such as radio, television, print media, leaflets, brochures, oral communication, and traditional communication. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 4| MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 35 MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS • Training Training of key stakeholders in climate change and climate-smart agriculture is important in order to increase knowledge and understanding, which eventually contribute to change or shape their mind-sets in their undertakings. Training should therefore be done based on the roles of the stakeholders at different levels. Training can be offered through different ways such as; technology-based learning, on field training, coaching, lectures, group discussion, films and videos. Likewise, training should also take into account the specific role of each target group (stakeholders). Relevant training manuals should be prepared for the target group, which will also serve as a reference during the implementation stage. • Integration of CSA in the Syllabus Educational institutions actually prepare and shape future working force of different professionals including the rural agrarian community. Most of the agrarian communities use knowledge and skills acquired at different stages of their education. Introduction of CSA in the syllabus would therefore help building capacity of not only future farmers but also future stakeholders of CSA (Policy maker, Researcher, Planner, Economist, Engineer, and Doctor etc.). The government should take up the agenda and oversee possibilities of mainstreaming it in the curriculum or syllabus. 4.2.4 Target for Awareness Creation Awareness raising targets different groups such as, government authorities, central and local administrative authorities, religious, traditional leaders, opinion leaders, NGOs, civil society, donors, media and community. Planning for awareness raising strategy should therefore take into account the target group, the message for each target group (preferably specific to the group), and the appropriate channels for communicating those messages. 4.3 CSA RELATED ACTIVITIES AND THEIR JUSTIFICATION CSA activities can range over a very broad range, depending on the relative importance of its three pillars – food security (productivity), adaptation, and GHG mitigation. 36 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 4.3.1 CSA Related Activities The table below shows some of the CSA related projects/activities together with the Practices and its related pillar(s); CSA RELATED ACTIVITIES CSA PRACTICES OR INTERVENTION RELATED CSA PILLAR(s) Soil and water Management • Water use efficient (drip irrigation, lining of canals) • Rain water harvesting and storage • Land and catchment management • System of Rice Intensification • Conservation agriculture( Cover cropping, Crop residue management, crop rotation, agro forest and Mulching • Productivity • adaptation Research • Resilient crop varieties (Drought tolerant varieties, Early maturing varieties and Water efficient varieties) • Productivity • Adaptation crop production & land preparation • Resilient crop varieties • Pest and diseases control • Post harvest and storage facilities • Productivity • Adaptation • Mitigation Livestock • Improved livestock breed • Improved Feeding • Efficient manure management; • Productivity • Adaptation • Mitigation Fisheries and aquaculture • Pond aquaculture • integrated aquaculture • cage aquaculture, • seaweed farming • Productivity • mitigation Disaster and risk reduction • crop insurance • productive social safety nets • Adaptation 4.3.2 Justification for CSA activities The changes in agricultural systems needed to achieve agricultural growth for food security, nutrition, and economic development under climate change are largely built upon sustainable agricultural intensification activities. Building an evidence base to identify the most suitable activities is an essential part of developing CSA strategies, investments and financing plans. Innovative financing mechanisms that link and blend climate and agricultural finance and investments from public and private sectors are a key means of implementing CSA. New climate financing instruments such as the Green Climate Fund are currently under development and could be a way of spurring sustainable agricultural development. Strong and all-encompassing Nationally Appropriate Mitigation Actions (NAMAs) and National Adaptation Plans (NAPs) are key national policy instruments important in creating links to national and international sources of finance. National sector budgets will continue to be the main sources of funding, climate integration into LGAs planning and budgeting is therefore a prerequisite for successfully addressing climate change. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 37 4.4 PLANNING CSA ACTIVITIES WITH GENDER CONSIDERATION Gender is pertinent to CSA, hence the need to put emphasis on the importance and ultimate goal of integrating gender in CSA activities is inevitable. The aim for integration is to reduce gender inequalities and ensure that men, youth and women can equally benefit from CSA related interventions in the agricultural sectors, so that to reduce risks linked to climate change. Taking a gender responsive approach to CSA, means that particular needs, priorities and realities of youth, men and women are recognized and adequately addressed in the design and application of CSA activities. Gender transformative CSA interventions seek to transform gender roles and promote more gender- equitable relationships between men and women. Planning of CSA activities must be flexible enough to reflect gender priorities and needs (specific to women). The active participation of women in the planning process, development of funding criteria and allocation of resources for climate change initiatives is critical, particularly at local levels. Gender analysis of all plans, budget lines and financial instruments for CSA is needed to ensure gender-sensitive investments in programmes for adaptation, mitigation, technology transfer and capacity building. 4.4.1 Mainstreaming Gender into CSA Planning Process The adverse impacts of climate change have disproportionate bearing on youth, men and women. It is therefore important to consider gender specific concerns and subsequent solutions in climate change adaptation planning processes. Women are not only differently vulnerable to climate change but they are also crucial in implementing adaptation solutions and building resilience. Similar to mainstreaming climate change adaptation development activities, gender integration in climate change can be internalized through systematic integration in policies, programmes, projects and activities. 4.4.2 Gender Analysis In order to support women’s and men’s equal uptake of and benefit in site-specific CSA practice or technology, gender analysis as well as equal participation and engagement of women and men are the key actions to be taken at the outset of any CSA intervention. In the longer term, broader changes are needed in order to reduce the constraints women and men may face in terms of accessing resources, services and information. Gender analysis of how women are differently affected by climate change and identification of gender specific responses during the planning stage can help make CSA activities and outputs gender sensitive. Socio-economic vulnerability assessments, assessing the CSA activities to address woman’s access to resources (e.g. finance, information, etc.) can help to set up gender specific objectives at an initial stage of the planned CSA related activity, project or programme. 4.5 BUDGETING FOR CSA RELATED ACTIVITIES Significant progress in addressing climate change in the agricultural sectors can only be achieved if climate concerns are considered in the context of all agricultural investment decisions, rather than in climate change specific projects. The need of adaptation to climate change in the near, medium and long term implies that, changes in agricultural investment needs, ranging from the farm scale up to the national and international levels. Current agricultural investment flows are insufficient to adequately finance sustainable agricultural development. This financing deficit is due not only to a lack of overall funds, but also to the fact that, the activities which are currently allocated resources do not generate the highest returns for sustainable agricultural growth. The main sources of agricultural investment MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 38 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL finance are the farmers, herders, fishers and foresters themselves. For this reason, public investment that enables agricultural producers to make investments in CSA is a priority. 4.5.1 Gender responsive budgeting Gender-responsive budgeting aims to address the lack of resources for gender mainstreaming activities by translating gender commitments into fiscal commitments through the application of a gender lens to the entire budgeting process. In addition to making the work undertaken by women economically visible, gender-responsive budgeting is advocated as a means of increasing transparency and accountability by delineating the amount of the budget allocated to women that is actually spent. Gender budgeting can be used as an important tool to allocate resources for implementing gender specific adaptation actions. Adequate financial resource allocation is key to the achievement in the gender mainstreaming process, and is one of the biggest challenges in efforts to implement gender mainstreaming across climate change related and other activities. 4.5.2 Potential Costs of Maladaptation Important issue to consider is the potential costs of maladaptation (e.g. agricultural investments that increase vulnerability to climate change or increase risks of economic losses associated with unsustainable and unprofitable investments). Investments, particularly large fixed capital investments with significant lifetimes, are particularly vulnerable to being maladaptive if climate risks are not considered. An example that is likely to be maladaptive and essentially add to the adaptation deficit is a case where major capital expenditures on irrigation systems use out- dated estimates of water demand and supply in areas where climate change is predicted to have major impacts. Screening agricultural investment plans for their degree of “climate smartness” is a simple first step that can be taken to identify the potential overlap between adaptation and development investments, as well as potential maladaptive agricultural investments. The screening methodology considers the potential contribution of planned activities to various aspects of adaptation as well as mitigation. This suggests that climate-smart agricultural investments with mitigation co-benefits should be identified within the context of existing agricultural investment strategies developed for the purposes of agricultural growth for a specific context. 4.5.3 Source of Finance for CSA Financing options specifically targeting CSA are still limited, necessitating a strategic use and combination of existing funding sources. The basis for any CSA activity should be the identification of a country’s opportunities and vulnerabilities, corresponding needs and preferred options for CSA activities. After priorities have been defined, a strategic approach to sources of finance based on an understanding of available channels will not only increase the chances for approval, but also enhance the fit between the finance option and the country’s overall approach to climate change in agriculture. • Internal Finance The Government through the national budget is the main funder of the agricultural sector, supplemented by Development Partners (DPs), private sector and CSOs thus making significant contributions to the sector. In addition, the Government in collaboration with DPs and private sector have put in place measures MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 39 aimed at improving the flow of finance and investment to the agriculture sector such as: the Export Credit Guarantee Scheme, USAID Guarantee for Input Scheme, Private Agriculture Sector Support (PASS), the Agro- Dealers Scheme and the Agriculture Input Trust Fund (AGIFT). Other initiatives that enhance Public Private Partnerships include the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) and Big Results Now (BRN). ASDP2 is the potential source for funding especially at the local level as it aims to increase resilience of agricultural systems to climate change and variability. ASDP-2 interventions will be undertaken with climate change considerations factored into the interventions, including Climate-Smart Agriculture in sustainable landscapes and appropriate climate change mitigation strategies. Farmers’ adaptive capacities will be strengthened to ensure the impact is understood and integrated into their farming systems/activities. Capacity building programmes for FFSs, extension officers and subject matter specialists on current climate related issues will be developed, implemented and periodically updated • External Finance Main sources of external public financing for climate change adaptation and mitigation include the following: i. Financing mechanisms directly under the UNFCCC; ii. United Nations (UN) organizations or programmes; UN Agencies and Programmes play a central role as implementing agencies for the activities financed through the funding channels under the UNFCCC. In addition, UN Agencies also provide climate financing directly, primarily through multi-donor trust funds financed by member states e.g. the UN REDD programme. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 40 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL iii. Multilateral Development Banks (MDBs); The primary function of MDBs is to provide loans under conditions and objectives based on their overall principles as well as the specific agreements between a specific country and the respective development bank. The agricultural sector remains one of the primary target sectors of MDB loans. As MDBs are increasingly incorporating environmental sustainability criteria into their agricultural lending practices, their loans play an increasing role as a financing option for CSA activities iv. Bilateral public financing channels Bilateral instruments remain one of the primary sources of climate finance. Bilateral Financial Institutions play a central role as intermediaries disbursing climate funding to developing countries. Examples include Japan International Cooperation Agency (JICA) v. Compliance and voluntary carbon markets Compliance carbon markets are marketplaces through which regulated entities obtain and surrender emissions permits (allowances) or offsets in order to meet predetermined regulatory targets. The voluntary carbon markets function outside of the compliance market. They enable businesses, governments, NGOs, and individuals to offset their emissions by purchasing offsets that were created either through the CDM or in the voluntary market vi. Private sector actors and philanthropy. Looking at the entire landscape of climate finance, the private sector is an international private sector funding that contributes to catalysing this transition. It is in fact the single largest source of financing. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 41 5.1 INTRODUCTION Monitoring and Evaluation (M&E) aims at evaluation of CSA interventions in order to understand their performance, challenges, potentials and opportunities for upscaling and adoption. Also helps to determine the extent to which a CSA intervention has been achieved, its effectiveness and provide recommendation for consideration in other endeavour. Through M&E framework it is easier to track progress at different levels of the CSA implementation by looking at: • Impact on people’s livelihood and the environment • Effect on behavior and institutional change, and CSA mainstreaming in plans • Output reflecting on the CSA pillars • Multidisciplinary involvement of the stakeholder and gender mainstreaming 5.2 BASELINE INDICATORS FOR CSA RELATED A baseline indicator is a value of a performance before the implementation of projects or activities, while targeting a specific level of result to be achieved within an explicit timeframe. In order to monitor and evaluate an impact of CSA intervention a baseline indicator(s) needs to be identified. The process of identifying indicator(s) is always done at the early CSA intervention planning stage to get knowledge of the current status of an item. For CSA interventions this is important because baseline result will show how different aspects have changed as a result of implementing CSA Practices and Technologies. Baseline indicators is recommended to come from officially recognized sources of information national statistics, policy documents, budget speeches, local plans, comparison between seasons, food reserve and market price. Targets need to be established and agreed against the selected baseline indicators. The classification of baseline indicators for CSA interventions can be set according to the three CSA pillars which are Productivity, Adaptation and Mitigation or mitigation co-benefit. 5.3 PERFORMANCE INDICATORS A Key Performance Indicator (KPI) is a measurable value that will demonstrates how CSA intervention has been achieved considering key objectives of the intervention and respective baseline indicator(s). The key characteristics of the indicator is that; it should be SMART, specific to the objective, Measurable either quantitatively or qualitatively, Available at an acceptable cost, Relevant to the information needs and Time-bound so that it is easier to monitor and evaluate against expected objective or targets to be achieved. MONITORING AND EVALUATION OF CSA INTERVENTIONS 5| MONITORING AND EVALUATION OF CSA INTERVENTIONS 42 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL The Performance indicators in most cases differ between project and interventions based on set targets or goals. However, the process of indicators identification is similar by starting with clear identification of goals to be achieved, mechanism to reach the goal and metrics to achieve. Contrary to baseline indicators, the key performance indicators are extracted from the intervention plan to correlate with baseline indicator(s) identified. 5.4 MONITORING TOOLS AND RECORD KEEPING Monitoring tools are continuously used to keep track of the status of agreed plan on implementing CSA intervention in order to identify defects or problems and give early warning signs on failure or successes. Selection of monitoring tools for a certain project depends on the nature and type of indicators, also type of metric data needed. In the case of CSA interventions, the tools are such as record keeping data sheet, Checklist, field observation and documentation of evidence. 5.5 CREATION OF EVIDENCE FOR CSA INTERVENTIONS This is the process by which evidence of project succession or failures are compiled together in an easy manner with the aim of sharing lessons learnt with others. The effectiveness on compiling the evidence depends on the baseline and key performance indicators identified in the intervention plan. However the monitoring tool identified, quality of data collected and analysis will determine the influencing power of evidence created. Hence, for effective upscaling or sharing of lesson learnt from implementing CSA intervention, identification of baseline indictor, KPI and appropriate monitoring tools are essential. For example, a farmer in Kiroka Village in Morogoro after receiving high-yielding and early-maturing banana cultivars he managed to document (see picture below) landscape transformation before and after. This is one way of creating evidence which would allow sharing of lessons learnt with others for upscaling and adoption. The farm BEFORE The farm AFTER (Source: Henry Mahoo - SUA) MONITORING AND EVALUATION OF CSA INTERVENTIONS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 43 CONCLUSION CSA practices and technologies aims at achieving food security and broader development goals under a changing climate and increasing food demand. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies can coordinate priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. Effective use of this ToT Manual is an important step toward the achievement of the national goals of sustainable agriculture production in a changing climate through application of CSA practices and technologies. This manual compliments Government efforts and initiatives on implementation of sustainable development goals by creating awareness, identifying CSA practices and technologies and mainstreaming of CSA in plans and programmes. CONCLUSION 44 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL REFERENCES Boers, T.M. and Ben-Asher, J. (1982) A review of rainwater harvesting: In Agriculture Water Management, 5:145-158 Food and Agriculture Organization (2010) “Climate-Smart” Agriculture Policies, Practices and Financing for Food Security, Adaptation and Mitigation: Food and Agriculture Organization of the United Nations. Hatibu, N. and Mahoo H., (1999): Rainwater harvesting technologies for agricultural production: A case for Dodoma, Tanzania. In: Kaumbutho P G and Simalenga T E (eds.), 1999. Conservation tillage with animal traction: a resource book of the Animal Traction Network for Eastern and Southern Africa (ATNESA). Harare. Zimbabwe. 173p. A publication supported by French Cooperation, Namibia. http://www.atnesa.org. United Republic of Tanzania (2017) Climate-Smart Agriculture Guideline. Ministry of Agriculture Livestock and Fisheries. United Republic of Tanzania (2014) Agriculture Climate Resilience Plan. Ministry of Agriculture Food Security and Cooperatives. United Republic of Tanzania (2008).Study on strategies for addressing negative effects of climate change in food insecure areas of Tanzania. Dar-es-Salaam, Tanzania: Ministry of Agriculture, Food Security and Cooperatives. United Republic of Tanzania (2015) Climate-smart Agriculture Program. Ministry of Agriculture Food Security and Cooperatives. REFERENCES"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":197,"cells":{"data":{"kind":"string","value":"# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE AND FOOD SECURITY Participatory Agricultural Development and Empowerment Project (PADEP) ENVIRONMENTAL AND SOCIAL FRAMEWORK Environmental Guidelines for PADEP March 2003 TABLE OF CONTENTS 1. BACKGROUND .............................................................................................................1 1.1 Introduction..........................................................................................................1 1.2 Project description ...............................................................................................1 2 SUBPROJECT TYPOLOGIES AND THEIR POTENTIAL ENVIRONMENTAL IMPACTS AND MITIGATION MEASURES ...............................................................3 2.1 Introduction and Background ..............................................................................3 2.2 Benefits of PADEP Subprojects ..........................................................................5 2.3 Environmental impacts of PADEP subprojects and proposed measures.............7 3. THE ENVIRONMENTAL ASSESSMENT AND APPROVAL PROCESSES FOR PADEP SUBPROJECTS.................................................................................................21 4. GUIDLENES FOR INSTITUTIONAL ARRANGEMENTS, TRAINING NEEDS AND COST ESTIMATES FOR MITIGATION MEASURES – PROCEDURES FOR COST ESTIMATE..................................................................................................34 5. PADEP SENSITIZATION MEETINGS AND LAUNCHING WORKSHOPS TO ADDRESS ENVIRONMENTAL ISSUES .....................................................................35 6. COMPLIANCE OF PADEP ACTIVITIES WITH BOTH WORLD BANK AND TANZANIA’S POLICIES, GUIDELINES, LEGISLATION AND REGULATIONS..............................................................................................................37 6.1 Compliance with World Bank safeguard policies ...............................................37 6.2 Compliance with Tanzania’s environmental management policies.....................39 7. PUBLIC CONSULTATION PROCESS.........................................................................41 Annex 1: Sample check lists for sub-projects.......................................................................43 i LIST OF ABBREVIATIONS AG Attorney General ASDS Agricultural Sector Development Strategy CADS Community Development Subprojects CIS Community Investment Subprojects CSC Community Subproject Committee DC District Commissioner DED District Executive Officer DFT District Facilitation Team DMT District Management Team DoE Division of Environment DPO District Project Officer DPO District Project Officer EIA Environmental Impact Assessment EMP Environmental Management Plan EP Environmental Permit EP Environmental Profile ESMP Environmental Social Management and Plans EU European Union FAO Food and Agricultural organization FGIS Farmer Group Investment Subprojects GDP Gross Domestic Product GoT Government of Tanzania IPM Integrated Pest Management IPNS Integrated Plant Nutrition Techniques/Strategies IRA Institute of Resource Management LEAT Legal Environmental Action Team MAC Ministry of Agriculture and Cooperatives MAFS Ministry of Agricultural and Food Security MNRT Ministry o f Natural Resources and Tourism MRALG Ministry of Regional Administration and Local Government MRP Minjingu Rock Phosphate MW Ministry of Water MWLD Ministry of Water and Livestock Development NEMC National Environmental Management Council NEP National Environment Policy NGOs Non-Governmental Organizations NPSC National Technician Steering Committee NRT National Resource Team NSSF National Social Security Fund NTSC Natural Technician Steering Committee OD Operational Directive PADEP Participatory Agricultural Development and Empowerment Project PCU Project Coordinating Unit PEP Provisional Environmental Permit PLUM Participatory Land Use planning and Management PM Prime Minister POM PADEP Operation Manual PPP Policy, Plan or Programme PRA Participatory Rural Assessment ii RC Regional Commissioner RDS Rural Development Strategy RPF Resettlement Policy Framework SC Subproject Committee SEA Strategic Environmental Assessment SPC Subproject Cycle T.S.A.E Tanzania Society of Agricultural Engineers TASAF Tanzania Social Action Fund TRC Technical Review Committee UN United Nations UNCHS United Nations Commission for Housing and human settlements VEOs Village Executive Officers WB World Bank WEO Ward Executive Officer iii EXECUTIVE SUMMARY This report provides guidelines for assessing possible environmental and social impacts of the subprojects to be funded under the Participatory Agricultural Development and Empowerment Project (PADEP). The guidelines provide a framework for screening community and farmer groups subprojects to determine their environmental and social impacts. The guidelines furthermore show how determination should be made and appropriate mitigating measures incorporated into the subprojects report. The main objective of PADEP is to raise the production of food, incomes, and assets of participating households and groups in a sustainable manner through the implementation of small agricultural development sub-projects planned and managed by groups of community members and farmers. The project has two components: (i) Community Agricultural Development Sub-projects; and (ii) Capacity Building and Institutional Strengthening. The total project cost is estimated to be US$ 70.6 million equivalent, of which IDA will finance US$ 56.0 million, beneficiaries will contribute US$ 12.0 million, and Government (national and district councils) will provide US$ 2.6 million. The project will provide grants to communities and farmer groups for investment in agricultural development subprojects, focusing primarily on improving soil fertility and land management, adopting sustainable agricultural technologies and increasing efficiency in inputs and outputs marketing. The soil fertility and land management subprojects will included watershed management for soil and water conservation, conservation tillage and efficient use of inorganic fertilizers. Similarly, under the adoption of sustainable agricultural technologies, subprojects such as integrated plant nutrition techniques/strategies (IPNS), integrated pest management, water harvesting techniques, improvement of traditional irrigation schemes, improved livestock production, introduction of non-traditional crops and rehabilitation of rural infrastructure will be undertaken. Finally, subprojects aiming at increasing efficiency in input and output marketing like supply of farm inputs, rural processing of agricultural and livestock products as well as improvement of products marketing will be funded. There are several positive socio-economic and environmental impacts that are expected due to implementation of subprojects which are eligible for PADEP funding. Amongst them are: improved skills for farmers; improved soil fertility and better land management; higher degree of environmental awareness; increased productivity; increased land, soil and water conservation; improved soil structure due to the use of manure and organic fertilizers; value added due to processing; and reduced post harvest losses through improvement of rural storage facilities. While beneficial subprojects are likely to represent a substantial portion of overall PADEP funded subprojects, it is recognised that negative environmental and social impacts are also likely to be generated in the course of implementation of the aforementioned subprojects. In this report, the typical environmental and social impacts for each of the likely subprojects have been analysed, and mitigation measures to be deployed have been proposed. Overall, PADEP which is a community driven development (CDD) project is classified as Category B project. However, since the subprojects to be supported by PADEP are small and because rural people will be the drivers of the subprojects, the process of environmental and social screening has been made simple and informative. The process will consist of the following steps: preparation of environmental profiles; assigning category to a subproject; scooping and public consultations; conducting environmental assessment; review and approval of environmental assessment reports; and disclosure and appeal procedures. These steps have been described in details to enable districts and communities understand the process involved. An environmental and social checklist by subproject types has been included to assist district facilitation teams, communities and farmer groups in the screening process. The environmental screening process, therefore, will include questions pertaining to safeguard policy requirements. The subsequent EA work will be carried out based on the screening results and related recommendations on subproject’s category. For example, as a result of the environmental screening process, the resulting EA work may also require a subproject-specific Pest Management Plan based on Integrated Pest Management approaches, or Resettlement Action Plan. If the later is being prepared as a result of the EA work, the RAP will be a separate document and disclosed separately after being cleared by NEMC and the Bank. The environmental assessment (including social and socio-economic aspects) itself will follow a number of steps, including impact assessment - based on screening and scoping exercise; analysis of alternatives - to enhance the design of a subproject, including do nothing alternative; predictions – to provide information on the potential implication of the proposed subproject; evaluation of significance – to determine the predicted or measured change in an environment and social attributes; identify mitigation measures – to reduce adverse environmental and social impacts; and public consultations – with affected or interested groups and NGOs during screening, scooping and preparation of ToR and EA report. iv The review and approval of Category B environmental assessment report, which includes social aspects will be done by the National Environmental Management Council (NEMC), or an agency accredited by NEMC, which is responsible for EIA clearance in Tanzania. The EA report will include a section on the Environmental and Social Management Plan (ESMP). For subprojects which are likely to increase pest problems, a subproject- specific Pest Management Plan (PMP) based on Integrated Pest Management (IPM) will be prepared. In subprojects that are expected to introduce changes in access to land or changes in ownership and use of land and property, a concise Resettlement Action Plan (RAP) will be prepared according to the Resettlement Policy Framework (RPF), which has been disclosed separately. The institutional arrangements will seek to promote and enhance efficiency, effectiveness, transparency and accountability, reduce red tape and bureaucracy. Instead, they will aim at strengthening community participation, empowerment and ownership of processes leading to the subprojects. The Community Subproject Committee (CSC) and Farmer Groups Subproject Committee (FGSC) will be responsible for overseeing the preparation of EA reports and implementation of agreed mitigation measures for community investments (CIS) and farmer groups investments (FGIS) subprojects, according to the environmental and social plan (ESMP), Resettlement Action Plan (RAP) and project-specific Pest Management Plan (PMP). The District Facilitation Team (DFT) will be responsible for assisting the communities in preparing their specific ToRs and EA reports and developing ESMP and RAP plans. The DFT will also monitor and supervise the implementation of these plans and report progress back to PADEP. At national level, PADEP/Ministry of Agriculture and Food Security (MAFS) Environmental Assessment Unit will be responsible for developing the generic Terms of Reference (ToRs) for EA, capacity building and backstopping of districts and supervision of implementation of ESMP, RAP and project-specific PMP based on IPM. Resources will be made available for training of MAFS EU staff, DFT and communities to identify and address environmental and social issues of the subprojects. The costs of capacity building for environmental assessment and social aspects shall be part of the component 2 of the project. The estimated costs of undertaking training in environmental and social assessment will be determined according to the needs assessment. The Environmental Assessment and Social aspects training manual prepared by NEMC will provide the basis for developing project-specific modules. Training on Bank safeguards will be added into the modules prepared by PADEP consultant. Public understanding about the proposed subprojects and their possible environmental and social impacts will be key to their successful implementation. These environmental and social issues shall therefore be fully covered in the participatory assessment leading up to selection of the proposed subprojects, and in subsequent design. The District Facilitation Team (DFT) shall be fully prepared to lead public discussion of environmental and social issues. In order to raise awareness of communities about the potential environmental and social impacts of PADEP funded activities, a number of sensitisation meetings will be held. These will include meeting with village leaders, village assembles, workshops to launch implementation of mitigation plans and seminars to discuss various environmental and social assessment themes. PADEP will design communication strategy to enhance consultations. This will include the right choices of the agenda of meetings, launching workshops and seminars, media for message delivery; cultural considerations; and publicity or advocacy activities. PADEP will ensure that the World Bank environmental and social safeguard polices are adhered to. The safeguard policies that are triggered by the proposed PADEP project are: OP/BP 4.01 Environmental Assessment, OP 4.09 Pest Management, OP 4.12 Involuntary Resettlement, and OP 7.50 Projects on International Waterways. To the extent that subprojects trigger World Bank safeguard policies, subproject- specific safeguard documentation, such as subproject PMPs, subproject Dam Safety Measures and subproject RAP will be prepared. v PADEP Environmental Assessment 1. INTRODUCTION AND BACKGROUND 1.1 Introduction Environmental Assessment (EA) is a process used to evaluate projects’ potential environmental risks and impacts in the area of influence; examines project alternatives; identifies ways of improving project selection, siting, planning, design, and implementation by preventing, minimizing, mitigating, or compensating for adverse environmental impacts and enhancing positive impacts; and includes the process of mitigating and managing adverse environmental impacts throughout project implementation. Whenever feasible, preventive measures are favoured over mitigatory or compensatory measures. This report provides guidelines for assessing possible environmental and social impacts of the subprojects. The guidelines indicate how projects should be screened to determine their environmental and social impacts. The guidelines furthermore show how determination should be made and appropriate mitigating measures incorporated into the subprojects report. The guidelines specify institutional responsibilities for undertaking environmental assessment including the social aspects, implementation of preventive, mitigatory or compensatory measures, and monitoring and evaluation. The guidelines also set out the criteria according to which a project would be disqualified for support as a result of likely environmental or social impact. 1.2 Project description The Government of Tanzania with assistance from the World Bank has prepared the “Participatory Agricultural Development and Empowerment Project (PADEP)”. The main objective of the project is to raise the production of food, incomes, and assets of participating households and groups in at least 840 villages in a sustainable manner through the implementation of small agricultural development sub-projects planned and managed by groups of community members and farmers. This objective will be achieved by: (i) empowering self-selected rural communities and farmers' groups to make decisions regarding choice of sustainable and remunerative productive technology; (ii) sharing of costs by the public sector and participants, and hence sharing the risk of adoption of improved technologies, again for self-selected participants; (iii) enhancing demand for products and services provided by the private sector in rural areas by increasing the purchasing power of participating groups and encouraging the growth of savings; (iv) promoting improved land and crop husbandry practices by participants; (v) supporting the ongoing decentralization process at the district level; and (vi) partially financing maintenance and/or construction of roads, bridges, and other small sub-projects to improve access to markets. The project has two components: (i) Community Agricultural Development Sub-projects; and (ii) Capacity Building and Institutional Strengthening. The total project cost is estimated to be US$ 70.6 million equivalent, of which IDA will finance US$ 56.0 million, beneficiaries will contribute US$ 12.0 million, and Government (national and district councils) will provide US$ 2.6 million. Component 1: Community Agricultural Development Sub-projects This project component will consist of (a) Community Investment Sub-projects (CIS); and (b) Farmer Group Investment Sub-projects (FGIS). The aim of this component is to empower rural communities and farmer groups to make decisions to improve their economic well-being and to act on them. Village Councils and organized farmers’ groups will have the primary responsibility for using participatory approaches in implementing small-scale investment activities supported by the project, including identification, undertaking environmental assessment, planning of subprojects, implementation of technical recommendations, local procurement of inputs, contracting of service providers and monitoring and evaluation. The project will build capacity of local authorities, communities and farmers' groups by conducting tailor-made basic training in participatory methodologies (PRA), sub-project cycle, basic financial and procurement skills, participatory monitoring and evaluation (PM&E), environmental and social assessments, and HIV/AIDS awareness and prevention. A community is defined as a single village, or a significant portion thereof, with a common investment interest. Thus a community sub-project would be any investment that draws public 1 PADEP Environmental Assessment interest and brings common benefits. A \"Farmer Group\" is defined as a small group (10 - 40 households) of the same village in which members have voluntarily agreed, with endorsement of their Village Council, to engage in an investment sub-project that introduces technological innovation. Possible sub-projects include: soil fertility and better land management (watershed management for soil and water conservation, restoration of soil fertility using rock phosphate, conservation and no tillage techniques, and fuel efficiency technologies - biogas); agricultural investments and technologies (integrated plant nutrition strategy (IPNS), integrated pest management (IPM), rainwater harvesting, improvement of traditional schemes, production of non-traditional crops and improved livestock); and input-output marketing (production of organic fertilizers, primary processing of crop and livestock products, contract farming etc.). Criteria for approval of sub-projects will include gender balance, sustainability and empowerment of rural communities. In order to share risks involved in adopting new improved technologies, efforts of communities and farmers' groups will be complemented with direct transfers of financial resources to them (through local governments) on a matching-grant basis. This will allow them to shop and compare prices among several suppliers of goods and services needed to implement their sub-projects. Mechanisms for community-driven development will be introduced in a phased manner, to allow for improvements in the course of project implementation. Before implementing the sub-projects, each Village Council or farmer group committee will undergo a participatory planning process to identify key challenges and practical ways to overcome them. The sub-projects thus derived will then be costed and the implied share of the cost to the beneficiaries, including mitigation measures for the likely environmental problems made clear. If the beneficiaries wish to undertake the project, it will be submitted for approval to the District Facilitation Team (DFT) of the District Authority. With each participating community or farmers group, the cycle of sub- projects will unfold over three years. The initial year will be devoted to capacity building, PRA, and identification of the sub-projects. The second and third years will be devoted to implementation. For CIS, beneficiaries will contribute (labour, materials or in cash) at least 20% of total sub-project costs and the project will contribute the difference up to a maximum of US$ 35,000 equivalent per village. For FGIS, the project will contribute in cash 50% of the cost of consumable inputs (seeds, fertilizers, and plant protection chemicals) up to US$ 25 equivalent per household per year for a maximum of 2 years, and up to US$ 11,000 equivalent per village. The total project contribution for CIS and FGIS subprojects per village will be US$ 46,000 equivalent. This amount includes all costs related to preventive or mitigation measures of environmental and social problems due to implementation of the chosen subprojects. The project will also contribute up to 80% of other costs, up to a maximum of US$ 750 equivalent per FGIS. Other costs might cover, for example, advisory services for effective marketing, repair of access roads, small infrastructure for grading or sorting, and other activities. Farmers participating in the group investment sub-projects will be required to have a savings account and to deposit their 50% share into the account prior to receiving the matching grant. At the end of the first year, they will be required to deposit a portion of the value of the initial grant, plus another 50% down payment on the second year's cost of consumable inputs. In this way, farmers will build up savings adequate to sustain use of the technology at the completion of the sub-project cycle. They will also build up a relationship with a local bank and with input dealers. Component 2: Capacity Building and Institutional Strengthening This component enhances the institutional and human capacity to ensure that the sub-projects chosen are adequately considered in key dimensions, including environmental, economic, and social, and implemented with acceptable quality. At the community/village level the project will finance technical assistance and training to village/farmer groups committee members with the aim to support preparation, implementation, monitoring and evaluation of sub-projects. Specific training needs will be identified during the PRA process, and will include environmental and social assessment, and managerial and technical issues relevant to the success of the subprojects. Basic business skills, such as bookkeeping and management of business relations with providers of services and inputs will be included. Grants of up to US$ 5,000 equivalent would be provided for capacity building to communities after they complete 2 PADEP Environmental Assessment the PRA exercise. Resources will be used for need-based and \"just in time\" technical assistance and training, particularly at the local levels, and to hire in advisory services as needed. In all participating district councils the project will support training to upgrade capacities in participatory planning methodologies, project implementation, monitoring and evaluation, financial and procurement management skills, environmental and social assessments, and public-private partnership in service delivery. Staff of the district councils will also undergo training to enable them guide communities and farmers' groups as needed. Technical assistance will be provided in the preparation of District Agricultural Development Plans (DADPs), which are integral part of the overall District Development Plans (DDPs). Under this component conditional block grants to the districts will be in cash in the amount of US$ 175,000 equivalent for three years. The District Councils will contribute 10% (US$ 17,500 equivalent). Planning for the use of these funds will be the responsibility of the District Councils through the DFTs. Support of the project at national level will include funding for capacity building in key entities and for additional analytical work to underpin ongoing reforms. The capacities of national institutions responsible for policy analysis and regulatory functions, such as planning, monitoring and evaluation, seed agency and plant protection units will be strengthened through training, technical assistance and provision of required equipment. The project will also finance various policy studies aiming at reviewing, harmonizing and rationalizing agricultural taxes, levies and fees on crop and livestock sub- sectors. Other studies to be supported will cover surveys of sectoral performance and beneficiary assessments. The project will support further development and updating of the agricultural sector monitoring and evaluation system, and improvement of its management information system (MIS). In addition, the project will support the implementation of the Seed Act (2000) and the Plant Breeders Right Act (2002), which provide the regulatory framework for seed industry, including the establishment of Seed Executive Agency. The project will carry out the rehabilitation of four strategically located soil testing laboratories, provide the required laboratory chemicals and equipment, including soil-testing kits for on-site soil diagnosis. Finally, the project will finance the national coordination and facilitation unit operating costs. Overall, the national level capacity building and institutional strengthening support budget amounts to US$ 8.9 million equivalent. The framework for environmental and social management under the PADEP project is intended to safeguard the health and resources of rural people in a way that is simple enough to be implemented within the context of a community driven developmental initiative. The administrative procedures are therefore simple but sufficient to accomplish the desired objective. 2. SUBPROJECT TYPOLOGIES AND THEIR POTENTIAL ENVIRONMENTAL IMPACTS AND MITIGATION MEASURES 2.1 Subproject Typologies In the PADEP Guidelines for Preparation and Implementation of Community Agricultural Development Subprojects it is indicated that community and farmer group agricultural investments would focus on the following thematic areas: • Soil fertility and better land management • Agricultural technologies • Inputs and outputs marketing The types of likely projects eligible for financing under this categorization, with some examples, are presented in Table 2.1. This list is not exhaustive. 3 PADEP Environmental Assessment Table 2.1: Types of possible projects eligible for financing by PADEP Type Possible subprojects Examples Soil fertility and better land management Watershed management for soil and water conservation Conservation tillage Efficient use of inorganic fertilizers Fuel efficient technology Construction of contours, protection of gullies, construction of terraces, agro-forestry, establishing and enforcing by-laws, bulking of seed/plant materials required for agro-forestry, woodlot establishment, promotion of gender awareness in soil and water conservation Improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion, use of green manure Use of rock phosphate, use of high analysis fertilizers Biogas technology that utilizes manure and reduces use of fuel to safeguard forests Agricultural technologies Increase productivity Integrated plant nutrition techniques/strategies (IPNS) Integrated pest management (IPM) Increased use of labour saving technologies Use of organic manure in combination with mineral fertilizers, production and use of bio- fertilizers Use of organic manure in combination with mineral fertilizers, production and use of bio- fertilizers Observation, preventive and intervention methods in crops, particularly vegetable and fruit production Safe use of pesticides in combinations with improved management related to IPM approaches Use of farm implements, such as ox-drawn ploughs, ridgers, rippers, weeders, power tillers and use of herbicides, etc Use of rainwater harvesting techniques Improvement of traditional irrigation schemes Improvement in livestock production Production of non-traditional crops Rehabilitation of infrastructure Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc Rehabilitation of weirs, irrigation canals and construction of division boxes Dairy animals, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dips, etc Production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture Rehabilitation of soil testing laboratories, rural roads, bridges, storage facilities and other rural infrastructure 4 PADEP Environmental Assessment Input/output marketing Supply of farm inputs Initial processing of agricultural and livestock products Improvement of crop produce marketing Input shops at farm level, etc Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, processing of dairy products, etc Establishment of village marketing centres, construction of market yards, grain storage, group- led grain marketing, etc Source: PADEP – Guidelines for Preparation and Implementation of Community Agricultural Development Projects (draft) Many subprojects funded by PADEP can have positive impacts on the surrounding environment if they are well designed and implemented. Watershed management, for example, can enhance soil and water conservation; Integrated Pest Management (IPM) can prevent increased use of pesticides through use of other measures to keep pest populations low. For example, breeding and cultural practices are used to make the environment less hospitable to pests and to keep the crop healthy and resistant or tolerant to attack. Other subprojects are also expected to produce positive socio-economic and environmental impacts, which include, based on the type of projects eligible for PADEP funding: • Improved skills for farmers • Improved soil fertility and better land management in general • Higher degree of environmental awareness • Increased production per unit area, with reduced pressure to expand area • Expected increased income and higher living standards, including better housing, better nutrition • Strengthened farmers’ groups and organizations • Improved gender awareness • Improved Land, soil and water conservation practices • Increase in soil fertility through use of livestock manure and other organic matter • Value added produce through processing and better marketing strategies • Forest conservation through use of fuel efficient technologies 2.2 Benefits of PADEP Subprojects Environmentally beneficial projects are likely to represent a substantial portion of PADEP subprojects. The benefits of this type of subprojects are long-term rather than short-term, and will not be limited to the members of village community. Below are a few examples of environmentally beneficial subprojects that will be financed by PADEP: • Watershed management for soil and water conservation: The primary advantage of watershed based management for soil and water conservation is that it provides the link between the resources and the system that generates and modifies them. Watershed forms a nested hierarchical system of units, which link the smallest hill slop to the local, district and regional watershed. The linkages of the watershed to runoff generation also provide for the necessary integration of water quantity management with planning for water quality and erosion and sedimentation control. • Conservation tillage: This offers numerous benefits. Added crop residue and minimal tillage both provide the effect of drastically reducing runoff of soil and agrochemicals. The result is to minimize impact on the water ecosystem. Conservation tillage main benefits are: decreased erosion, improved water quality, better long term production, higher soil moisture, improved water infiltration, decreased soil compaction, improved soil tilt, more biological activity, reduced release of carbon gases and reduced air pollution. Reducing and eliminating tillage helps increase soil fertility. Residue left on the soil not only serves in the capacity of soil conservation it also adds organic matter to the soil as it decomposes. Soil fertility, tilt, and structure are improved by conservation tillage practices. 5 PADEP Environmental Assessment • Fuel efficient technology: Biogas is one of the fuel-efficient technologies, which will be promoted by PADEP as one of the subprojects. The main positive impacts of biogas technology include: (i) conservation of the forest resource as a result of decreased use of fuel wood which will also result in carbon sequestration by reduction in the cutting of the forest, (ii) renewable source of energy, (iii) reduces workload on the part of women to collect fuel wood, (iv) cheaper when compared to kerosene, (iv) promotes a nutrient cycling strategy. Considering the biogas technology as gas generation and slurry production for soil conditioning purposes, it becomes apparent that it produces positive impacts at farm and public levels as shown in Table 2.2. below. Table 2.2: Positive impacts from biogas at farmer and public levels Farmers’ interests Public interests Reduction of pollutants Quality improvement of organic fertilizer/reduction of mineral fertilizer Reduction of odour Risk of increased NH4 Positive impact on resource protection Reduction of the use of pesticides Positive impact on climate protection Stabilization & improvement of soil fertility/reduction of desertification Compared to other fuels positive emission behaviour of biogas • Integrated plant nutrition techniques/strategies (IPNS): The strategy optimises all aspects of nutrient cycling – supply, uptake, and loss to the environment – to improve food production. At farm level, IPNS aims to optimise the productivity of nutrient flows that pass through the farming system during a crop rotation. This means application of external plant nutrient sources and amendments, efficient processing, and recycling of crop residues and on-farm organic wastes that limit plant nutrient losses. In the process, IPNS empower farmers by increasing their technical know-how and decision-making capacity, and promote changes in land use, crop rotation, and interactions among forestry, livestock and cropping systems in support of agricultural intensification. At village or farming community level, IPNS take into account plant nutrient sources outside cropped areas, including those in irrigation water and flood sediments, livestock manure, and forest litter and organic material that is physically transferred from forest and pastures. IPNS promotes rationalization in the transfer of organic matter and plant nutrients from non-cropped to cropped areas, and the mobilization of unused nutrient resources or the saving of valuable nutrient sources diverted as domestic fuel, raw materials for building or for industrial purposes. • Integrated pest management (IPM): This has broad application since it integrates management of all pests, it is a holistic approach, ecologically based and can be applied to any ecosystem. IPM integrates multiple pest management tactics (chemical, biological, cultural, mechanical) and management of multiple pests (insects, weeds, disease pathogens, nematodes, vertebrates, etc). IPM incorporates environmental and social concerns. The main goals of IPM are: sustain resource (agricultural and natural over the long term), more rational use of pesticides, reduce environmental contamination and costs, utilize natural biological controls, minimize pesticides resistance problems, food safety (reduce residues of pesticides on food products) and worker safety (rely on pest management tactics that are safe for workers). • Use of rain harvesting techniques: High intensity rains commonly cause devastating effects on the environment particularly in areas of low or no vegetation. Runoff arising from rainwater often causes erosion with subsequent land degradation and sometimes sets the desertification process in motion. Preventing and mitigating soil erosion may achieve environmental conservation. One method to achieve this is through runoff control by rainwater harvesting methods. Surface catchment is the most effective among the rainwater harvesting methods that could mitigate the possible environmental hazards caused by rain. • Rehabilitation of infrastructure: High marketing costs are partly related to the poor rural infrastructure, including poor condition of roads, lack of bridges on some rivers and streams and poor storage facilities. By supporting the rehabilitation of these rural infrastructure, PADEP will be able to reduce transaction costs, through linking rural producer to the urban markets, and reducing post harvest losses. Reduced transportation costs due to accessibility of 6 PADEP Environmental Assessment rural areas will increase profit margins of various crops produced by farmers, hence contribute to reduction of rural poverty. Loss of soil fertility has been identified by the Soil Fertility Initiative document as the biggest threat to smallholder agricultural development. By supporting rehabilitation of strategically located soil testing laboratories, technical services would be readily available to districts and communities, on demand-driven basis. The PADEP may also generate environmental benefits through a variety of other mechanisms, including: • Improved awareness and concern for environmental issues on the part of beneficiaries, local communities and districts • Training of environmental specialists, thus increasing the availability of staff conversant with environmental issues within PADEP and districts • Generation of environmental assessment guidelines that are then used by other institutions or line ministries and districts, or are adopted by the National Environmental Management Council (NEMC) for enhancing environmental procedures. • Improvement of tradition irrigation schemes • Improved livestock production • Introduction of non-traditional crops 2.3 Environmental impacts of PADEP subprojects and proposed mitigation measures Subprojects may have impacts that change environmental characteristics of the project area, and these impacts may be ambiguous or negative in their effects. The environmental screening process, therefore, will include questions pertaining to safeguard policy requirements. The subsequent EA work will be carried out based on the screening results and related recommendations on subproject’s category. For example, as a result of the environmental screening process, the resulting EA work may also require a subproject-specific Pest Management Plan based on Integrated Pest Management approaches. 2.3.1 Watershed management of soil and water conservation The project will support watershed management for soil and water conservation subprojects, including construction of contours and terraces, protection of gullies, bulking of seed/planting materials required for agro-forest, establishment of woodlot, enforcement of catchment management by-laws and creation of awareness in soil and water resources conservation. Watershed management subprojects are undertaken for purposes consistent with sound environmental management, but they may also generate environmental impacts that warrant mitigation. These include changes in land, water, morphological and physical characteristics, as well as quality and quantity of these resources; changes in natural habitats, loss of biodiversity or changes in biodiversity characteristics of both fauna and flora, infringement of property rights and possible intrusion on social/cultural resources, such as archaeological sites and religious shrines. 2.3.2 Conservation tillage Examples of conservation tillage subprojects include improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion and use of green manure. Impacts during conservation tillage are usually associated with management aspects. While conservation tillage offers many advantages, it does require a change in agricultural practice. If certain elements are not managed correctly, impact can occur. Amongst these are: soil and ground water contaminations, river pollution, increased herbicide use, weed infested fields, increased use of fertilizers, increased diseases, soil compaction, etc. Table 2.4 summarizes possible impacts and their mitigation measures. The most important mitigation measures related to conservation tillage are developing subproject-specific PMP based on IPM approaches, integrated weed management, proper fertilization management, residue management, etc. 7 PADEP Environmental Assessment Table 2.3: Typical Impacts and Mitigation Measures of Watershed Management for Soil and Water Conservation Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Changes in Land, Water, morphological and physical characteristic as well as quality and quantity of resources Awareness raising Participatory land use planning and management (PLUM) By-laws and their effective enforcement Joint management programmes Biological Environment Natural Habitats Fauna and Flora Changes in natural habitats Loss of biodiversity Changes in biodiversity characteristics of both fauna/ flora and ecosystems Careful site selection Use of indigenous plant species Biodiversity Assessment and monitoring Developing subproject-specific EA and related Environmental Management Plan (EMP) Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Infringement on property rights Possible intrusion on physical/cultural resources e.g. archaeological and religions shrines Awareness raising Provision of alternative income sources Enforcement of by-laws Compensation as per provisions of the resettlement policy framework Table 2.4: Typical impacts and mitigation measures of conservation tillage Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Contamination of ground water table and river pollution Soil conservation measures Fertilization management Proper residue management Enforcement of air quality standards Awareness raising Biological Environment Fauna and Flora Disturbance on ecological functioning of farming systems Integrated weed management Promote Integrated pest management approaches Proper residue management Biodiversity assessment and monitoring Subproject-specific PMP based on IPM approaches “Social Environment” Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Loss of historical/cultural sites Reluctance to reduce ploughing Proper site selection Propose disease management Awareness raising 8 PADEP Environmental Assessment 2.3.3. Efficient use of inorganic fertilizers There are three examples of possible subprojects on efficient use of fertilizers among the PADEP's possible subproject types. These are use of rock phosphate, use of high analysis fertilizers and use of organic manure. Table 2.5 summarizes the most frequently encountered environmental impact, particularly for rock phosphate, related to mining and processing. In phosphorus-deficient soils, Minjingu rock phosphate (MRP) exploited from Manyara Region near Lake Manyara is as effective and profitable as imported triple super phosphate (TSP). Farmers are applying 125-250 kg P/Ha as a capital investment, and expect a five-year residual effect. A particular important environmental consideration in the case of Minjingu rock phosphate is dust, presence of heavy metals and radionuclides. MRP like other Rock Phosphate (RP) mines contains heavy metals. Of the metals contained in MRP, Cadmium (Cd) represents the greatest concern because of the potential human risks via transfers within the food chain. The Cd level is considered low (9 mg/kg) and within the same range as those reported from other RP mines. Despite this, there is a need to monitor the Cd levels in soils as phosphate fertilizers are continuously being applied to soils. With regard to radioactive materials, the levels of radionuclides are not much different from the levels found in other RP mines. Table 2.5: Typical impacts and mitigation measures of efficient use of inorganic fertilizers Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Stalinization of soils Contamination of groundwater Pollution of surface water Heavy metals Dust Air pollution Conduct training on safe use and handling Use of high grade fertilizers Salinity monitoring Use of masks to prevent inhaling of dust Stored and transported in closed containers Bringing the moisture content to 7-8 percent Enforce air quality standards Biological Environment Fauna and Flora Promoting weed growth Loss of natural plant and wildlife habitats and species Increased pest problems Conduct training on safe use of fertilizers Weed control, e.g. through lining of irrigation canals Biodiversity assessment and monitoring Promoting Integrated Pest Management (IPM) approaches Developing subproject- specific Pest Management Plans (PMP) Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Loss of natural recreational, historical and archaeological sites Health risks Increased use of labour- saving technologies Land reclamation Disease surveillance Provision of protective gear Proper screening of herbicides Training on IPM approaches 9 PADEP Environmental Assessment 2.3.4 Fuel efficient technology Fuel efficient (e.g. biogas technology subprojects) do not usually result in major impacts. Table 2.6 summarizes the most frequently encountered environmental impacts of these types of subprojects. PADEP fuel-efficient technology subprojects will finance construction of biogas plants. Biogas subprojects are likely to increase ammonia content of digested manure. Combined with a slightly increased pH will a higher risk of ammonia losses in treated slurry compared to untreated manure. Therefore, digested slurry must be handled more carefully and farmers have to follow manure-handling instructions given by the extension service officers. Table 2.6: Typical impacts and mitigation measures of fuel-efficient technology Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Ground water pollution Ammonia losses Control surpluses of slurry Cover the soil Biological Environment Natural Habitats Fauna and Flora Effect on vegetables and fodder Locate far from residential settings Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Odour complaints Lost income opportunity, e.g. for charcoal traders Different design concept Build far from residential houses Provision of alternative income sources 2.3.5 Increasing productivity Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers are subproject activities supported by PADEP. Table 2.7 shows some typical impacts of these subprojects. All studies conducted in the country have indicated that the application of organic manures in combination with mineral fertilizer gives higher crop yield increases than when both are applied separately. In addition, studies have concluded that Nitrogen and phosphorous applied in combination have resulted in significantly high yield. The potential impacts from these subprojects are salinization of soil, contamination of surface and ground water, loss of plant species. 2.3.6 Integrated plant nutrition techniques/strategies (IPNS) PADEP will support IPNS subprojects with the aim to address nutrient management, including improving organic matter in the soil, increasing plant available nitrogen, and combining organic and inorganic fertilizers. These interventions have the potential to increase and sustain production levels, increase the economic potential of a production system, and counteract and minimize environmental pollution. However, the interactions between nutrient applications and other agricultural activities and the likelihood of unforeseen problems such as environmental contamination of soil, surface and ground water should be a great concern and a monitoring system with key indicators should be developed. Table 2.8 summarizes typical impacts and mitigation measures of IPNS. 10 PADEP Environmental Assessment Table 2.7: Typical impacts and mitigation measures of increasing productivity through use of organic manure in combination with mineral fertilizers and bio-fertilizers Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Salinization of soils Contamination/pollution of surface and groundwater Conduct training on safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility management Public awareness raising Biological Environment Fauna and Flora Loss of plant species Promoting weed growth Increased pest problems Weed control measures, e.g. lining of irrigation canals Biodiversity assessment and monitoring Promoting IPM approaches Developing PMP which are subproject-specific Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Change of scenery Health risks Increased use of labour- saving technologies Awareness and training on safe use Promote high value crops Provision of protective gear Proper screening of herbicides Training in IPM approaches Table 2.8: Typical impacts and mitigation measures of integrated plant nutrition techniques / strategies (IPNS) Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Salinization of soils Contamination/pollution of surface & groundwater Conduct training on safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility Management Biological Environment Fauna and Flora Loss of some plant species Scientific studies on plant nutrition Promoting weed growth Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks Awareness and training on safe use Promote high value crops Provision of protective gear 2.3.7 Integrated pest management (IPM) PADEP will finance subprojects aimed at promoting safe use of pesticides in combinations with observation, preventive and intervention methods in crops, particularly vegetable and fruit production. According to FAO definition, an IPM is a pest management that in the context of the associated environment and the population dynamics of pest species, utilizes all suitable techniques and methods in as compatible a manner as possible and maintains pest population at levels below those causing economically unacceptable damage or loss. Therefore, an IPM involves a combination of various measures to ensure effective pest management without disturbing the ecosystem, reduce environmental pollution and eliminate direct and indirect health hazards to human beings. Due to changes in project 11 PADEP Environmental Assessment design, PADEP has now become demand-driven, hence subsequent to the screening procedures, each subproject will have its own case-specific Pest Management Plan based on IPM approaches. The PMP prepared in 2001 will be re-formulated and used as a guide/reference document in the preparation of subproject-specific PMPs. Table 2.9 summarizes typical impacts and mitigation measures of IPM. Most of IPM methods have little or no impacts at all, especially use of botanical pesticides like neem trees, biological control, such as concinellid beetles, intercropping, resistance varieties, etc. Typical negative impacts include soil contamination, water resources pollution, loss of animal and plant species. Table 2.9: Typical impacts and mitigation measures of Integrated Pest Management (IPM) Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Soil contamination Water resources pollution Adherence to provisions of the subproject-specific pest management plan Awareness and training Treatment/purification of water for domestic use Provision of safe watering points/structures for livestock Adopt leaching techniques Biological Environment Fauna and Flora Loss of animal and plant species Aggravating pest problems due to increased pesticides resistance Conduct Biodiversity assessment and monitoring Effective screening of pesticides entering the market Promoting and adopting IPM approaches to pest control Developing PMPs which are subproject-specific Enhanced research and extension support services Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks Awareness and training on safe handling of pesticides Pesticide-related hazards adequately addressed Enforcement of by-laws Clean-up and disposal to appropriate land fills 2.3.8 Increased use of labour saving technologies PADEP will support labour saving technologies, such as use of farm implements, such as ox-drawn ploughs, ridgers, rippers, weeders, power tillers, etc. The objective of supporting these subprojects is to increase the marginal labour productivity in the existing smallholder farms. The project will not support use of labour saving technologies to open up new areas. Table 2.10 summarizes typical impacts and mitigation measures of increased use of labour saving technologies. The potential impacts of the inappropriate use of labour saving technologies are loss of soil fertility, loss of water sources and air and noise pollution. There is also loss of plant and animal species due to the use of non-selective herbicides, accidents to human beings and potential land use conflicts. 2.3.9 Use of rainwater harvesting techniques Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc are interventions supported by PADEP. Table 2.11 summarizes typical impacts and mitigation measures of increased use of rainwater harvesting techniques. Potential environmental impacts of rainwater harvesting techniques are: land degradation at livestock watering points, 12 PADEP Environmental Assessment contamination of stored water, water and land use conflicts, loss of natural habitats, loss of fauna and flora, etc. Table 2.10: Possible impacts and mitigation measures of increased use of labour-saving technologies Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Loss of soil fertility Soil compaction, deterioration of structure Soil and water contamination due to herbicides use Employ farm management principles Use of appropriate technology Awareness raising and training in herbicides use and handling methods Effective screening of herbicides used by farmers Biological Environment Fauna and Flora Loss of plants species due to use of non-selective weed killers/herbicides Biodiversity assessment and monitoring Participatory land - use planning from the grass root levels Training on proper use and handling of herbicides Use of selective herbicides Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Gender inappropriateness, e.g. increasing of women’s burden Land use conflicts Accidents due to farm machinery operations Accidents due to unsafe handling of herbicides Participatory land-use planning at all levels Recognition of indigenous knowledge Adherence to safety regulations on herbicides handling Enforcement of by-laws governing screening of herbicides Gender awareness in selection of technology 2.3.10 Improvement of traditional irrigation schemes PADEP will finance the rehabilitation of weirs, irrigation canals, drainage systems and construction of diversion boxes. PADEP will not finance the construction of new irrigation schemes. Irrigation and drainage systems will be designed to manage water for enhancing agriculture production. There is a wide range of irrigation schemes, which can accommodate many variations in the source, and availability of water, types of climate, and form of agriculture (e.g. rivers and streams, underground water, rainwater, reservoirs etc.). However, since most of the traditional irrigation schemes in Tanzania draw water from rivers and streams, PADEP support primarily the improvement of open irrigation and drainage canals. Rehabilitation of weirs will involve appropriately designed system to provide effective and efficient supply of water. Rehabilitation of earth canals will include excavation and earthworks. If subprojects will involve rehabilitation of chacos or small dams, subproject-specific dam safety analysis in addition to subproject-specific EA will be carried out consistent with the Bank’s safeguard policy. Table 2.12 summarizes the most frequently encountered environmental impacts of small-scale irrigation and minor civil works subprojects. Irrigation subprojects often intensify agricultural production in the irrigation zone and environmental problems may result from increasing use and concentrations of agrochemicals. Such agricultural intensification can also cause accelerated nutrient loading of receiving waters, resulting in algae blooms, proliferation of aquatic weeds, and 13 PADEP Environmental Assessment deoxygenation. Other impacts from irrigation subprojects include water logging and salinization of soils, degradation of downstream surface water systems, and biotic and chemical changes to aquatic ecosystems. Abstractions of water from dams or reservoirs have the potential to cause significant hydrological disturbances. Diverting water from river systems, especially during seasonal low flows, can cause changes to riverine ecology, fisheries, and aquatic vegetation. Irrigation schemes may also cause an increase in waterborne diseases, because disease vectors proliferate in irrigation canals under some circumstances. If canals are not properly maintained, animal and human waste may be deposited into irrigation systems and spread communicable diseases. The incidence of schistosomiasis, malaria, and onchocerciasis has increased in some irrigation schemes in Tanzania due to poor drainage systems. Social problems may arise because of multiple demands for limited water resources. Water right issues cause disruption of historical land use practices. Conflicting demands for water and inequities in distribution can also cause problems. Table 2.11: Typical impacts and mitigation measures of increased use of rainwater harvesting techniques Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Siltation due to erosion Land degradation at livestock watering points Contamination of stored water Water and land use conflicts Potential floods during heavy rains Awareness & training on safe handling and storage of water Disinfection of water sources By-laws and their effective enforcement Adherence to water rights by irrigators associations Enforcement of water rights by Basin Water Officers Provision of safe watering points/structures for livestock Participatory planning Erosion control measures at the watering points. Prepare and have in place contingency/emergency plans Dam safety analysis in addition to EA of subproject Biological Environment Fauna and Flora Loss of natural habitats Loss of Fauna and Flora species Increased pest problems Introduction of alien weeds species Awareness & training on safe handling and storage Careful site selection Planting trees and other vegetation around chaco dams Biodiversity assessment and monitoring Developing subproject-specific EA and related Environmental Management Plan (EMP) Develop weed monitoring plan and control measures Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Change of scenery Health hazards e.g. malaria, schistosomiasis and other related diseases. Child accidents Infringement on property and access rights Participatory planning Alternative income sources Awareness raising to avoid accidents and provide basic knowledge on methods of preparing clean water Use of treated mosquito nets Improved drainage systems Compensation as per provisions of the RPF 14 PADEP Environmental Assessment Table 2.12: Typical impacts and mitigation measures of improvement of traditional irrigation schemes Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Introducing salinity Soil acidification Land and water use conflicts Secondary water uses (domestic, livestock) Water logging Poor water quality for downstream users caused by irrigation return flow quality Flooding and siltation of irrigation canals Reduction in irrigation water quality Contamination of water sources by agro- chemicals Dust pollution Noise pollution Construction wastes Provide drainage including disposal of water Analyse soils and monitor changes so that potential problems can be managed Participatory land and water use planning and management, e.g. WUAs and dialogues. Provide water for leaching as a specific operation Provide water for domestic and livestock water supply Include access crossings at convenient locations for people and livestock Provide for drainage of tail waters Salinity monitoring Provision of flood control and de- silting structures in subproject designs Provide plans for disposal of construction wastes Provide protective gear against dust and noise Biological Environment Fauna and Flora Loss of fauna and flora species Loss of habitat Proliferation of aquatic weeds Increased pest problems Effective screening of agro-chemicals Training in proper use and handling of agro-chemicals Adopting IPM approaches to pest management Preparing subprojects-specific PMP based on IPM approach Biodiversity assessment and monitoring and evaluation of fauna and flora species Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Increase incidence of water-borne diseases Infringement on property and access rights Increased inequity Weaker community infrastructure Educate about cause of diseases Improve health facility Disease surveillance Awareness and training By-laws and enforcement Allow sufficient time and money for extensive public participation that all affected groups are considered and that district and village institutions are involved to sustain irrigated agriculture, particularly in respect of land and water rights Include economic activity like household vegetables, fodder or growing trees for firewood Compensation as per provisions of the RPF 15 PADEP Environmental Assessment 2.2.11 Rehabilitation of rural infrastructure The project will also support small civil works including the rehabilitation of rural roads, bridges and other small infrastructure, such as, storage facilities. Rehabilitation of soil testing laboratories, marketing yards and dipping facilities will also be supported by the project. The objective of supporting small scale civil works will be to open up inaccessible rural areas and improve rural infrastructure so that marketing costs an post harvest losses are reduced. In terms of rehabilitation of the soil testing laboratories, the aim will be to enable research institutes to immediately respond to the demands for soil analyses from districts within the given ecological zone. Negative impact of minor civil works include noise pollution, generation of construction wastes and dust during the construction phase. In some cases, open pits could be left behind after the excavation of sand and aggregate materials. Loss of vegetation and habitat from excavation sites. A summary of likely impacts and mitigation measures is given in Table 2.13. Table 2.13: Typical impacts and mitigation measures of rehabilitation of rural infrastructure Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Open pits Dust pollution Noise pollution Construction wastes Contract conditions defining working practices and monitoring Consultation with stakeholders Provide plans for disposal of construction wastes Provide protective gear against dust and noise Biological Environment Fauna and Flora Loss of fauna and flora species Loss of habitat Loss of crops or livestock grazing land Provision of landfill requirement in the contracts Biodiversity assessment and monitoring and evaluation of fauna and flora species Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Infringement on access and movement for humans and livestock Health problems due to dust inhalation and noise Accidents from construction sites Improve health facilities Occupational disease surveillance Awareness and training on safety measures Subproject-specific EA required Compensation of lost plants, land or displacement according to RPF 2.3.12 Improvement in livestock production The PADEP project will also finance subprojects related to improvement of dairy farming, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dip, etc. Table 2.14 summarizes the most frequently encountered environmental impacts of improvement in livestock production. The potential impacts of improved in livestock production are overgrazing, degradation of land and vegetation, soil erosion, gas emissions, loss of natural habitats through overgrazing, 16 PADEP Environmental Assessment Table 2.14: Typical impacts and mitigation measures of improvement in livestock production Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Overgrazing Degradation of land and vegetation Soil erosion Gas emissions Awareness & training Observing land carrying capacity Establishment of stock routes Combine with biogas technology Market research Rotational grazing Zero grazing Biological Environment Fauna and Flora Loss of natural habitats through overgrazing Wildlife displacement Biodiversity assessment and monitoring Joint wildlife management i.e. integrated management Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks from use of acaricides in dips Conflicts between pastoralists and wildlife management areas Environmental risks from emptying water from dips into rivers/water sources Infringement of property and access rights Provision of protective gear Training on safe handling of chemicals and animal drugs Participatory planning and management. By-law enforcement on disposal of waste waters from the dips Compensation as per provisions of the RPF 2.3.13 Production of non-traditional crops PADEP will support subprojects that are related to the production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture. Table 2.15 summarizes the most frequently encountered environmental impacts of production of non-traditional crops subprojects. The potential impacts of production of non-traditional crops are contamination of soil, fruits and mushrooms (quality control). 17 PADEP Environmental Assessment Table 2.15: Typical impacts and mitigation measures of production of non-traditional crops Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Soil contamination by agro- chemicals Water sources contamination Treatment/purification of water for domestic use Provision of safe watering points/structures for livestock Training on agro-chemicals handling and safety measures Biological Environment Fauna and Flora Introduction of new pests Introduction of new diseases in the farming systems Quarantine / screening of imported varieties Adherence to phytosanitary regulations of Ministry of Agriculture and Food Security Biodiversity assessment and monitoring Development of subproject- specific PMP based on IPM approaches Enhanced research and extension services support to farmers growing new crops Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Fruits might be contaminated if watered by streams loaded with industrial effluents Lack of reliable markets Awareness and promotional campaigns Market research and products promotion Enforcement of by-laws Adherence to environmental quality standards. 2.3.14 Supply of farm inputs The project will support farmer groups intending to stock agricultural inputs in the rural areas. Table 2.16 summarizes the most frequently encountered environmental impacts of supply of farm inputs. Table 2.16: Typical impacts and mitigation measures of supply of farm inputs Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes from packaging materials plastics, tins and cans Awareness campaigns Proper disposal of wastes By-laws enforcement Design alternative packaging materials. Biological Environment Natural Habitats Fauna and Flora Livestock and wildlife might consume the plastic materials which are deadly to their health Ecological disruption due to overuse of pesticides and herbicides Raise awareness and training farmers in IPM approaches Enforcement of by-laws governing use and handling of agrochemicals Promoting an IPM approaches Screening / inspection of approved agrochemical 18 PADEP Environmental Assessment Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks from agro- chemicals especially if repackaging is undertaken Awareness and training Provision of protective gear 2.3.15 Initial processing of agricultural and livestock products Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, and processing of dairy products, are typical examples of subprojects under this category. Table 2.17 summarizes the most frequently encountered environmental impacts of improvement in livestock production. The potential environmental impacts of initial processing of agricultural and livestock products are wastes from processing, contamination of products, noise pollution, vibrations and dust. Table 2.17: Typical impacts and mitigation measures of initial processing of agricultural and livestock products Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes from processing Contamination of products Noise pollution Vibrations Dust Provide for proper waste disposal Ensure hygienic conditions Careful site selection O & M strategies Biological Environment Natural Habitats Fauna and Flora Solid and liquid wastes from the processing might affect plant and animal species Conduct Biodiversity assessment and monitoring Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Gender concerns in ownership and operation Workers’ health in the processing plants might be affected Increased pesticides residue in foodstuff Strategic group targeting Provision of protective gears, health insurance, awareness raising Adherence to Industrial and occupational health regulations Promoting IPM approaches 2.3.16 Improvement of crop produce marketing Establishment of village marketing centers, construction of market yards, grain storage and group-led grain marketing are typical examples of subprojects to be supported by PADEP under this category. Table 2.18 summarizes the most frequently encountered environmental impacts of improvement of crop produce marketing. The potential environmental impacts of improved crop produce marketing include wastes at markets, smells and odour, change of aesthetic values, air pollution and soil contamination, etc. 19 PADEP Environmental Assessment Table 2.18: Typical impacts and mitigation measures of improvement of crop produce marketing Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes at markets Smells and odour Change of aesthetic values Air pollution Soil contamination Waste management strategies Careful site selection Monitoring Biological Environment Fauna and Flora Livestock might consume hazardous materials from the damp sites Spread of storage pests to other locations Design an appropriate sanitary land-fill Developing subproject- specific Environmental Management Plan (EMP) Develop subproject-specific PMP based on integrated approaches Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Poor sanitation due to absence of sanitation facilities Infringement on property and access rights Provide for water supply and sanitation facilities Consensus building through participatory site selection and planning Compensation as per provisions of the RPF 3. THE ENVIRONMENTAL ASSESSMENT AND APPROVAL PROCESSES FOR PADEP SUBPROJECTS Since the sub-projects supported by PADEP are small and because rural people will be the drivers of the projects, the process of environmental screening must be simple and informative. The process will consist of the following steps: Step 1: Preparation of environmental profiles The preparation of an environmental profile of subprojects is an important phase in subproject planning in general and in the environmental assessment of subprojects in particular. An environmental profile is a description of the socio-economic, physical and environmental characteristics of the subproject area. The EP describes the subproject area’s development-environment situation and relationships, giving recognition to the relationship among resources, resource users, institutions, socio-economic and cultural setting. The preparation of an EP should be as participatory as possible, drawing on the knowledge of and involving the local people. Step 2: Assigning category to a subproject After basic information is collected in the profile, projects should be screened and categorized according to their likely environmental and social impact. Screening serves two purposes: • To determine which projects, of all those proposed at the identification phase of the project cycle of PADEP, need further environmental consideration, and to eliminate those likely to have harmful environmental impacts • To indicate the level of environmental appraisal that a project will require 20 PADEP Environmental Assessment Assignment of project categories at screening EA process is indicated in Box.3.1. stage of Box 3.1 Assignment of Project Categories at Screening Stage of Environmental Impact Assessment (OD. 4.01) Category A: Environmental Assessment is normally required as projects may have diverse and significant environmental impacts Category B: More limited environmental analysis is appropriate as projects may have specific environmental impacts Category C: Projects in this category are likely to have minimal or no adverse environmental impacts Environmental screening of each proposed subproject to be financed under PADEP will be done to determine the appropriate extent and type of environmental assessment required. PADEP subprojects will be classified as A, B or C depending on the type, location, sensitivity, and scale of the subproject and the nature and magnitude of its potential environmental impacts. The process for identification and approval of PADEP subprojects is elaborated in the GUIDELINES FOR PREPARATION AND IMPLEMENTATION OF COMMUNITY AGRICULTURAL DEVELOPMENT SUBPROJECTS. In brief, the PADEP process with regard to environmental and social assessment is as follows. During the first year of project participation, a village undergoes capacity building and PRA to assess opportunities and identify possible sub-projects to be supported within the envelope of resources available to the community. The District Facilitation Team guides this process, and is well trained to assure that environmental and social considerations form an integral part of the PRA process. Once the community has identified one or several possible subprojects, the proposals are categorized as A, B, or C according to criteria summarized below. Category A projects are those with significant adverse environmental impacts that are sensitive, diverse, or unprecedented. The impacts may affect an area broader than the sites or facilities subject to physical works. For example, direct pollutant discharges large enough to cause degradation of air, water, or soil; large-scale physical disturbance of the site or surroundings; extraction, consumption, or conversion of substantial amounts of forest and other natural resources, measurable modification of hydrological cycles; use of hazardous materials in more than incidental quantities; and involuntary displacement of people and other significant social disturbances. EA for Category A project examines the project’s potential negative and positive environmental impacts, compares them with those of feasible alternatives (including the “without project” option), and recommends any measures needed to prevent, minimize, mitigate, or compensate for adverse impacts and improve environmental performance. The PADEP process is not likely to generate these, but if such proposals surface they should be rejected during the PRA process because PADEP, which is a Community Driven Development project is not equipped to finance the environmental remediation that would be needed to make them acceptable. Category B projects are those with potential adverse environmental impacts on human populations or environmentally important areas - including wetlands, forests, grasslands, and other natural habitats – are less adverse than those of Category A projects. These impacts are normally site-specific; few if any of them are irreversible; and in most cases mitigatory measures can be designed more readily than for Category A projects. The scope of EA for Category B project may vary from project to project, but it is narrower than that of Category A’s. Category B EA examines the project’s potential negative and positive environmental impacts, compares them with those of feasible alternatives (including the “without project” option), and recommends any measures needed to prevent, minimize, mitigate, or compensate for adverse impacts and improve environmental performance. Category C projects are those which are likely to have minimal or no adverse environmental impacts. Beyond screening, no further EA action is required for a Category C project. However, PADEP financed Category C subprojects will have to show clearance from NEMC with regard to their classification. 21 PADEP Environmental Assessment All subproject proposals will be required to include an environmental categorization with justification and clearance by NEMC. Category B subprojects will require an environmental assessment. Subprojects which are likely to result in a significant conversion of natural habitats or the destruction of cultural property will not be supported by PADEP. Changes in access to land or changes in ownership and use of land and property that may be detrimental to the society will be addressed according to the Resettlement Policy Framework, which is disclosed separately. Communities and farmer groups wishing to prepare subprojects will have access to grants to hire technical assistance, primarily through contracting services to private sector/NGOs to undertake the environmental and social assessment. The generic ToRs for the EA will be prepared by the PADEP/MAFS EA unit and customized to suit specific subproject needs by the District Facilitation Team (DFT), which also helps communities/farmer groups with the preparation of EA reports for their respective subprojects. The ToRs and the resulting EA reports shall be approved by NEMC (or an agency accredited by NEMC). Final approval of category B subprojects by the District Management Team (DMT) will require evidence of NEMC (or accredited agency) clearance of the EA report. Evidence that appropriate mitigatory measures, such as, Environmental Management Plan are included and costed in the project proposal will be required. Environmental and social indicators will be included among those monitored to assess progress in implementation of the project. The implementation of the preventive or mitigation measures, will be the responsibility of communities and farmer groups undertaking the subproject. PCU in collaboration with the District Facilitation Teams will undertake regular monitoring and evaluation of the mitigation measures implementation by communities and farmer groups. Any project that entails changes in access to land or changes in use of land that may be detrimental to interests of current land holders or users will be subject to provisions of the Resettlement Policy Framework (separately disclosed). Provisions for treatment of agricultural chemicals, particularly pesticides, will be included in the subproject-specific Pest Management Plan based on Integrated Pest Management approaches. Tanzania EIA Procedure and Guidelines also categorize projects according to impact magnitudes i.e., “Mandatory list of projects requiring EIA” and “List of small scale activities and enterprises that require registration” (may or may not require EIA) . According to “Tanzania EIA Procedure and Guidelines”, the screening procedure can lead to one of the following decisions: • Environmental Impact Assessment is required where the project is known to have significant adverse environmental impacts. • Preliminary environmental assessment is required where the project may have environmental impacts • Environmental Impact Assessment is not necessary where the project is unlikely to cause significant environmental impacts. • No further consideration at all for projects contravening Government policies or other global obligations. Within Tanzanian EIA Procedure and Guidelines, the following criteria need to be taken into account while conducting screening to determine whether EIA is required or not: • Key project parameters • Affected area • Importance and scale of impacts on the environment • The likely degree of public opposition i.e. controversial issues which raise public concern as a result of type and scale of the undertaking, sensitivity of the site location, technology used, conflict of interest in land issues and any other factor related to a particular project may required detailed scrutiny and assessment. Step 3: Scoping and public consultations Scoping is defined as a consultative procedure that culminates in the determination of the extent and approach to an Impact Assessment study for category B sub-projects requiring assessments. The procedure follows upon classification of the project into an environmental category. It is an early and 22 PADEP Environmental Assessment an open process for determining the scope of issues related to the proposed action. The objective of consulting communities is to determine how their concerns will be addressed in the EA study. When a proposed subproject is classified as category B, the PADEP project will provide funds for the group to consult as needed with NEMC and Environmental Units in relevant sectoral authorities, as well as affected or interested parties, and to hire consultants to undertake an assessment. All the concerned parties shall be given adequate opportunities to participate in the Scoping exercise. Draft Terms of Reference (ToRs) for the EA study and the scoping report should be submitted to NEMC for review with assistance of the Technical Review Committee (TRC) for some projects for approval. Since most of these projects will be similar in nature, standard ToRs could be developed in consultation with NEMC. The standard TORs can be customized for the specific subprojects using information collected during the Environmental Profile preparation stage of the EA process and additional comments received from the key stakeholders. Step 4: Conducting an environmental assessment Where necessary NEMC will conduct a visit to the site(s). The outcome of the study, which could be a rejection or revision/modification or approval should be communicated by NEMC to the project group in a period not exceeding 30 days. When a subproject is classified as Category B, a partial (preliminary) environmental assessment (EA) should be undertaken, resulting in a brief EA report. As part of an EA report, an environmental and social management and monitoring plan (ESMP) should be incorporated. If Resettlement Action Plans (RAP) are being prepared as a result of the EA work, the RAPs will be separate documents and disclosed separately. The responsibility for assuring that the EIA report is done lies with the proposing group and or consultants hired by the group. The main items included in the environmental assessment study are; baseline survey and inventory, development of proposal options, potential impact identification and prediction, mitigation consideration and cost estimates, environmental management plans and other issues specified in the ToRs. The following steps should be adopted in this procedure for environmental assessment: Impact Assessment: Based on the screening and scoping, the EA shall identify and assess positive and negative impacts likely to result from the proposed subproject. This uses a variety of methods including checklists, questionnaires, matrices, overlays, modelling, network analysis and simulations. Opportunities for environmental enhancement should be explored. The extent and quality of available data, key gaps in data, and uncertainties associated with predictions shall be identified or estimated. Topics that do not require further attention should be specified. • • • • Analysis of alternatives: Assessment of subprojects from an environmental perspective. This is a key purpose of EA work and the more proactive side of EA – enhancing the design of a project through consideration of alternatives, as opposed to the more defensive task of reducing the adverse impacts of a given design. This provides a detailed review of alternative approaches and prioritises them into a feasible approach. For each alternative, the environmental costs and benefits should be quantified to the extent possible. The do nothing alternative should always be included, with a discussion of it being adopted; that is what would the future look like without the proposal? The do nothing (or no project) alternative is always feasible and gives a “base case” against which the performance of other alternatives can be compared in terms of environmental impact, economic effects and other performance measures indicated by the objectives. Predictions: The principal function of EA is to provide predictive information on the potential implication of projects. Prediction should determine the cause and effect relationship of direct and indirect impacts based on data and information from a wide number of sources on the physical, social, biological, institutional, economic and cultural issues. The quality and availability of data and the analytical techniques and assumptions frequently limit the reliability of prediction. In this context open dialogue with key stakeholders and the public is vital. Evaluation of significance: This determines the significance at subproject and influence area levels. Within specified time and space a significant impact is the predicted or measured 23 PADEP Environmental Assessment change in an environmental attribute that should be considered in project design, depending on the reliability and accuracy of the prediction and the magnitude of the change. Mitigation: This identifies measures to avoid and/or to reduce adverse impacts. It also assesses how to plan and manage environmental enhancement. The identified measures need to be undertaken early enough to embed ideas thoroughly into the basic design of a proposed subproject and show how future monitoring and evaluation would be carried out. These measures are drawn together into coherent Environmental and Social Management and Monitoring Plans. • • • Public consultation: Consultation throughout EA preparation is generally encouraged, particularly for subprojects like those to be supported by PADEP that affect people’s livelihoods. Public consultation can be undertaken during screening, scoping and preparation of ToR, EA report, review of EA report by the NEMC and other stakeholders and during preparation of terms and conditions for EA acceptance or approval. All the information gathered during the impact assessment is compiled in the format given in the NEMC Reporting Procedure and Guidelines and submitted to NEMC for review. In all cases the documentation should be kept as brief and simple as possible. Step 5: Review and approval of environmental assessment report The EA report prepared for each subproject (Category B) should be reviewed by district facilitation team and NEMC as appropriate and public consultations should be undertaken during the review period. The outcome of the review is of the EA is one of the following: • EA accepted • EA not accepted Acceptance and clearance of the EA (for Category B projects) or the checklist (for Category C projects) by NEMC will serve as a sufficient environmental permit to proceed with further consideration for approval of the project by district council and PADEP. The review of the environmental assessment report should also include the determination of whether or not any people have been identified as owners/users of the land upon which or where the sub-project will be located or if the sub-project in any other way will affect people/ property and access so that there is a negative impact (loss) as a result of the sub-project. If that is found to be the case, the appropriate measures need to be taken in accordance with the Resettlement Policy Framework. The environmental assessment report should be short and clear, so that project participants can understand it. It should state clearly the main environmental issues, both positive and negative, likely impacts, potentially affected people, mitigating measures, and costs of mitigation. The report should include a section called the Environmental and Social Management Plan (ESMP). The ESMP should be a practical, action oriented plan specifying measures to be taken to address the negative environmental impacts. It should also specify the actions, resources and responsibilities needed to implement the agreed actions and details on key social and environmental management and monitoring performance indicators. Further, ESMP should ensure that the costs of implementing the EA report recommendations are budgeted into the total subprojects costs. Responsibility for preparation of the ESMP will be with the group under guidance of the DFT. The DFT will supervise the implementation of action plans in close cooperation with communities. The PADEP/MAFS EA unit in consultation with NEMC will undertake periodic monitoring and evaluation. The ESMP should be formulated in such a way that it easy to use. The ESMP should cover the following aspects: Summary of impacts, description of mitigation measures, description of monitoring programme, institutional arrangements, implementation schedule and reporting procedures, cost estimate and sources of funds, and capacity development for implementation of the environmental and social management plan. The contents of an ESMP are further elaborated below. Summary of Impacts: The predicted adverse environmental and social impacts for which mitigation is required should be established and briefly summarized. Cross-referencing the 24 PADEP Environmental Assessment ESMP report to RPF and subproject-specific PMP, so that additional detail can readily be accessed. Description of mitigation measures: Cost-effective and feasible mitigation measures are often detailed and technical in nature. The mitigation measure proposed for PADEP’s subprojects should draw on findings from identified impacts and analysis of compliance with the GoT policies, legislation and administrative matters, and WB Safeguard Policies. Each mitigation (or enhancement) measure should be briefly described with reference to the impact to which it relates and the conditions under which it is required. • • • • • • • Description of monitoring plan: Environmental monitoring should be designed to ensure that mitigation measures are implemented. The ESMP should demonstrate that all identified impacts are matched with mitigation measures and monitoring plans. The monitoring plan will use the findings of existing baseline data, as the means to measure the progress in compliance with the GoT and WB Safeguard Policies. In a nutshell, an effective monitoring plan should consist of the following elements: - Monitoring objectives - Description of performance indicators, which provide linkages to impacts and mitigation measures identified in EA - Description of parameters to be measured, methods to be employed, sampling locations, frequency of measurements, detection limits (where appropriate) and definition of thresholds that will signal the need for remedial actions - Institutional responsibilities, timing and timescales for monitoring - Reporting arrangements (to the NEMC) - Cost and financing provisions - As part of monitoring plan for PADEP's subprojects a table format should be presented with performance indicators, monitoring site and frequency, responsible institution, time frame and provisional cost for each subproject. Institutional arrangements: Responsibilities for mitigation and monitoring should be clearly defined. The ESMP should identify arrangements for coordination between the various government institutions and environmental agencies responsible for mitigation impacts of subprojects. Environmental management in Tanzania involves many government institutions and other agencies, and links between the various actors are often complex. Capacity Development and Training: This comprises a plan for improving institutional environmental management capabilities in the PADEP’s subprojects, based on findings of a rapid training needs assessment and review of the existing capacities and institutional roles. Capacity building would be undertaken for staff of PADEP’s environmental unit, districts for raising their awareness about environmental issues and for upgrading of skills related to environmental management of subprojects. The ESMP will detail the resources needed and the timing of these staff. Specifically, the ESMP provides a specific description of institutional arrangements – who is responsible for carrying out the mitigatory and monitoring measures (e.g. for operation, supervision, enforcement, monitoring of implementation, remedial actions, financing, reporting, and staff training). Implementation schedule and cost estimates: The ESMP should provide the timing, frequency, and duration of mitigation measures, specified in an implementation schedule, showing links with the overall subprojects project implementation plans (PIP). Moreover, the capital and recurrent cost estimates and sources of funds for implementing the ESMP should be considered and also integrated into the total subproject cost. Integration of ESMP with Subprojects: In a nutshell, the ESMP should be specific in its description of the individual mitigation and monitoring measures and its assignment of institutional responsibilities, and it must be integrated into the subprojects overall planning, design, budget, and implementation arrangements Approval: As mentioned earlier, most of the potential subprojects to be supported by PADEP are not expected to generate significant adverse environmental impacts. If it is confirmed 25 PADEP Environmental Assessment through the screening process that the subproject is of Category C, which means no EA is necessary, District Facilitation Team should, on behalf of the community or farmer group request clearance of the subproject from NEMC, or agency accredited by NEMC to clear EA reports. Subprojects classified as Category B would require an EA, and would undergo the formal approval process, in which case the NEMC will review and approve the EA report. In case RAP has been prepared, it should first be cleared by NEMC (or agency accredited by NEMC) before the District Facilitation Team seeking clearance from the Bank through PADEP. According to WB policy on resettlement (OP 4.12), all RAPs should be reviewed and approved of by the Bank, before resettlement activities are implemented. Upon receiving clearance from NEMC, District Facilitation Team shall request PADEP to proceed with funding of the subproject. Supervision: Once the approval process is completed, the supervision becomes part and parcel of the normal subproject cycle management, including monitoring, evaluation and reporting. Environmental monitoring and supervision should be undertaken by all implementing agencies. The DFT should bear the responsibility of supervision at district level and reporting to the PADEP. The PADEP environmental unit staff in consultation with NEMC should be undertaking periodical field visits as part of their supervisory responsibilities. In the process they should also participate in the process of developing and appraising new subproject proposals, which is the prime responsibility of communities, assisted by the DFT. • Step 6: Disclosure and appeal process As project proposals are finalized, the complete proposal shall include the environmental category of the subproject. For category B subprojects, the proposal shall include the EA report and proof of its approval by NEMC. For category C subprojects, the environmental checklist shall be included, together with a list of mitigating measures. The checklist will include an enumeration of possible environmental impact (such as those listed above for the various projects and/or others) and planned mitigating measures. Sample templates for the checklist are included in Annex 1. Box 3.2 Contents of an Environmental and Social Management Plan (ESMP) • Identification and summary of major anticipated adverse environmental impacts • Description of mitigation measure • Description of elements of monitoring program • Institutional arrangement • Implementation schedule for mitigation measures • Performance monitoring and reporting procedures designed to ensure early detection of conditions necessitating corrective actions, and provide information on progress and results of mitigation and institutional strengthening measures • Cost estimates and sources of funds The EA reports of subprojects should be disclosed to the public by presenting the findings and recommendations to the village assembly and distributing copies to PADEP, district and village government. NGOs and other civil societies in the community should be informed of the meeting and copies of report should be made available to them if needed. A summary of findings should be posted at the village government and political parties’ offices. The Community Subproject Committees will be responsibility for disclosing the EA reports for community subprojects, while the Farmer Groups Committees will be responsible for disclosing EA report for farmer groups subprojects. The village governments will be responsible for taking minutes of EA disclosure on behalf of the village councils. PADEP groups or any affected/interested party, has the right of appeal. If dissatisfied with the decision reached at any stage in the EA process, the affected party has the right of appeal to the Minister responsible for Environment. The Minister shall appoint a panel of five people to hear the appeals. The 26 PADEP Environmental Assessment Chairman of the panel shall be the Director of Environment in the Vice President’s Office and the remaining members shall be three (3) environmental management experts and one member from the general public. The results of appeal shall be communicated to NEMC for action. A summary of institutional responsibilities for key steps in the environmental and social management process is given in Table 3.1 below. Table 3.1: Institutional responsibilities for environmental and social management process Subproject Cycle Process Outputs EA Process Outputs Responsible agency Community participation Approval and Clearance 1. Subproject plan prepared Sub-Project Environmental Profile Environmental Screening Report (Full and partial for Category B. No EA required for Category C). District Management Team (DMT), Environmental Unit (EU), and District Facilitation Team (DFT) District Management Team (DMT), Environmental Unit (EU), and District Facilitation Team (DFT) Participated actively in examining and analysing environmental problems related to subproject Provide input to subprojects classification, and EA and subproject- specific PMP and RPF reports District Council NEMC 2. Desk Appraisal of Subproject proposal Scoping and TOR for Category B EU with external consultant / NGOs Consulted interested and affected parties NEMC 3. Field Appraisal of Subproject report EA draft report for Category B subprojects, RAP and ESMP DFT with external consultant / NGO Participated in disclosure workshops NEMC/Bank 4. Subprojects approved ESMP agreed for subprojects implementation EU, monitoring, evaluation and PADEP supervision Partner in implementation of ESMP NEMC 27 PADEP Environmental Assessment Table 3.2: Environmental checklist by subproject types Eligible subprojects Examples Environmental checklist Watershed management for soil and water conservation Construction of contours, protection of gullies, construction of terraces, agro-forestry, establishing and enforcing by-laws, bulking of seed/plant materials required for agro-forestry, woodlot establishment, promotion of gender awareness in soil and water conservation Is there likelihood of biodiversity loss? Will there be infringement on property and access rights? Are the necessary by-laws in place? Conservation tillage Improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion, use of green manure Are herbicides going to be used to control weeds? Have they (herbicides) been screened and approved by the authorized plant protection agency? Have cover crops been screened by research? Has an IMP approach been adopted? Has a project-specific PMP been prepared? Is the PMP prepared based on IPM approaches? Are herbicides-related hazards adequately addressed? Efficient use of fertilizers Use of rock phosphate, use of high analysis fertilizers, organic manure What measures are in place to prevent health risks to farmers? Are there signs of salinity in the area? Will the fertilizer be stored safely prior to use? Is there a likelihood of polluting surface and groundwater? Are requisite soil and water quality control measures in place? Have soil tests been done? Are there any recommendations on application rates? Fuel efficient technology Biogas technology that utilizes manure and reduces use of fuel to safeguard forests Is there a segment of the community depending on current energy source for income, e.g. charcoal selling? If yes, what alternative is proposed for the lost opportunity? Increase productivity Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers Are there health risks to farmers? Has an IMP approach been adopted? Has a project-specific PMP been prepared? Is the PMP prepared based on IPM approaches? Are herbicides-related hazards adequately addressed? Is training on IPM approaches required by farmers? 28 PADEP Environmental Assessment Integrated plant nutrition techniques/strategies (IPNS) Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers Are there any health risks to farmers? Do the farmers have the necessary knowledge and skills? Integrated pest management (IPM) Safe use of pesticides in combinations with observation, preventive and intervention methods in crops, particularly vegetable and fruit production What pests are found in the area? Which pesticides are effective against the pests? Are there alternative control methods? Is it safe to use pesticides? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Are there any measures to prevent health risks to farmers? Will special protective gear be required and is it available locally? Are the farmers competent enough to handle the pesticides? If not, what kind of training will be required on how to apply the pesticides? What equipment will be used? Is there likelihood of polluting the soils, surface and groundwater? Is there likelihood of the pesticides concentrating in the food chains? Is the activity consistent with the pest management plan? Increased use of labour saving technologies Use of farm implements, such as ox- drawn ploughs, ridgers, rippers, weeders, power tillers, etc Are the implements appropriate for use by women and men? Have the herbicides been screened and approved for use by farmers? Are herbicides-related hazards adequately addressed? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Has training on IPM approaches, and safe use and handling of herbicides been conducted? Is research and extension technical support on IPM and use of herbicides adequate? 29 PADEP Environmental Assessment Use of rainwater harvesting techniques Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc Are measures in place to avoid contamination of stored water? Is there a segment of the community depending on water vending for their income? If yes, what alternative is proposed for the lost opportunity? Are measures in place against child accidents? Are water and land use conflicts likely to emerge? Are measures in place against land degradation at livestock watering points? Will there be infringement on property and access rights? Improvement of traditional irrigation schemes Rehabilitation of weirs, irrigation canals and construction of division boxes Will the subproject cause land and water use conflicts? What measures will be put in place to avoid water logging and poor water quality especially for downstream users? What measures will be used to prevent scouring and clogging of canals? Will there be infringement on property and access rights? Will it cause salinity problems? Will it cause changes in gender relations? Has provision been made for domestic and livestock water supply? Which water-borne diseases are prevalent in the village? Will the subproject lead to an increase in disease incidences? Will the subproject lead to an increase in pest problems? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Is salinity a problem? If yes, is the subproject likely to increase the salinity problem? What measures will be put in place to prevent or control salinity? Will the improvement lead to expansion of the irrigated area? If yes, would this encroach on ecologically sensitive areas? 30 PADEP Environmental Assessment Livestock production Improvement Rehabilitation of infrastructure Dairy animals, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dips, etc Rehabilitation of soil testing laboratories, rural roads, bridges, storage facilities and other rural infrastructure Is land currently enough for existing livestock herds? Are signs of overgrazing and soil erosion? Will the subproject contribute to degradation of land and vegetation through overgrazing? Are their dips in the village? If yes, who operates them? What measures are in place against health risks from use of acaricides in dips? What is done with animal manure? Is it used for biogas production? What measures will be put in place to prevent degradation of vegetation and soil at water points? Is there wildlife in the vicinity of the village? If yes, what measures will be instituted to avoid conflicts between livestock and wildlife? Will there be infringement on property and access rights? Will the subproject cause land conflict? Is it likely to cause dust and/or noise pollution? What measures are in place for disposal of construction wastes? Will it result in open pits? If yes, how are they going to be filled? Have the communities and stakeholders been consulted? Is the construction site going to be protected? Will the contract provide protective gear to workers? Is the construction contract include working practices and monitoring of environmental impacts? Are there plans to monitor biodiversity and evaluate fauna and flora species? How is compensation for lost crops or grazing land going to be effected? Is there a mechanism to monitor occupational diseases? Is there any training plan for safety and precautionary measures? 31 PADEP Environmental Assessment Production of non- traditional crops Production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture Do the farmers have the necessary knowledge and skills? What measures are in place for control of potential new pests? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Supply of farm inputs Input shops at farm level, etc What measures are in place against health risks from agro-chemicals? Initial processing of agricultural and livestock products Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, processing of dairy products, etc Are there any crop processing facilities in the village? If yes, who owns and operates them? Are women involved in the processing and do they own any of the facilities? Will addition of new facilities cause any conflicts? How will the operations be sustained? What will be done with the by- products from processing facilities? How will waste management be organized? How will the hygiene of processed products be controlled? Will the subproject cause adverse changes in gender relationships? Improvement of crop produce marketing Establishment of village marketing centres, construction of market yards, grain storage, group-led grain marketing, etc How will waste management be organized? Is there a provision for water supply and sanitation facilities at market places? Who will operate these facilities? What are the roles of women and men? Will there be infringement on property and access rights? Environmental supervision will be an important activity to assure successful implementation of projects. For category B subprojects that require environmental assessment, the key indicators of the Environmental and Social Management Plan will become indicators that are monitored regularly to assess performance of the subproject. For category C subprojects, the general areas highlighted on the checklist should be reported on in the supervision reports, with measures of indicators where relevant. 32 PADEP Environmental Assessment 4. GUIDELINES FOR INSTITUTIONAL ARRANGEMENTS, TRAINING NEEDS AND COST ESTIMATES FOR MITIGATION MEASURES Institutional arrangements should seek to promote and enhance efficiency, effectiveness, transparency and accountability, reduce red tape and bureaucracy. They should also aim at strengthening participation, empowerment and ownership of stakeholders. At community/village level: The community subproject committee (CSC) will have direct oversight for preparation of EA reports and implementation of agreed mitigation measures, according to environmental and social management plan (ESMP), as part of the overall subproject cycle management and monitoring at community/village level. . Communities and farmer groups will report on the environmental indicators as part of their regular reporting process for implementation of the subproject. The CSC will communicate implementation progress of the ESMP to the district, through their village government, with copies of such correspondence to the Ward Executive Officer (WEO) for information. The periodic reports on implementation of the PADEP project will include a section on achievement of environmental objectives as shown by the indicators. At district level: The District Executive Director (DED), should assign the task of monitoring the implementation of the ESMP at district level to the DFT, which is lead by District Agricultural and Livestock Development Officer (DALDO). Again, this should be part and parcel of the overall management/monitoring function for the subproject cycle at district level, which is the responsibility of the DMT/DFT. The subproject EA reports, including their ESMPs, should be forwarded by DFT to NEMC (or an agency accredited by NEMC) for their clearance, before sending to PADEP for funding. On behalf of DED, the DALDO should send progress reports on implementation of the ESMP to the PADEP/MAFS EA unit, with copy to the Regional Secretariat for information. DFT should be responsible for ensuring that DALDO sends the reports on regular basis, as required by PADEP’s operational guidelines. At national or project level: A decision has been made to build capacity of the EA unit of MAFS, and earmark two individuals to be directly responsible for EA aspects of PADEP during its implementation. The mainstreaming of EA function into the Ministry’s EA unit has an advantage of ensuring sustainability of environmental screening beyond the project life. Environmental assessment should be taken as an integral part of the technical evaluation of subprojects proposal. The environmental audit function needs to be taken into consideration at every step of subprojects cycle. In view of this, PADEP should allocate funding for building capacity of EA unit of MAFS, both in terms of required human resources, office equipment and logistical support. The EA unit of MAFS should be responsible for preparing generic TORs for EA, have an oversight on the overall implementation of ESMPs by communities and farmer groups, and provide technical backstopping to districts. Resources are available under the project for training of MAFS EU staff, DFT and communities to identify and address environmental and social issues. The costs of capacity building for environmental assessment including social aspects should be part of the component 2 of the project. The estimated costs of undertaking training in environmental and social assessment is summarized in Table 4.1 below. The Environmental Assessment training manual prepared by NEMC should provide the basis for developing project specific modules. Training on Bank safeguards will be added into the modules prepared by PADEP consultant. Table 4.1: Estimated costs of training in environmental assessment Area of activity Responsible Target Outcomes Proposed timing Cost Estimates US$ Conduct training needs assessments for PADEP/MAFS, districts, Villages PADEP – PCU, District authorities & Village governments MAFS/PAD EP staff, District staff, villagers Training needs identified and documented 2003 for MAFS/PADEP & pilot districts & villages, yearly for new districts and villages come on board 50,000 33 PADEP Environmental Assessment Arrange for & coordinate training in environment in general & EA, WB & GoT policies MAFS/PADE P staff, district authorities MAFS/PAD EP staff, District staff, villagers Increased environmental awareness, appreciation of EA, skills for EA 2003 for MAFS/PADEP & pilot districts & villages, yearly for new districts and villages come on board 100,000 Ensure initial PRAs in villages contain EA messages PADEP – PCU, DMTs, DFTs, DFTs, (DMTs) PRA reports address environ- mental concerns, incliner impacts, mitigation, ESMP at subproject level 2003 for pilot districts/villages, yearly for new districts and villages come on board 20,000 Monitoring and follow-up PADEP – PCU, DMTs & DFTs Village governments, subproject committees Subproject EMPs successfully implemented Continuously 30,000 5. PADEP SENSITIZATION MEETINGS AND LAUNCHING WORKSHOPS TO ADDRESS ENVIRONMENTAL ISSUES Public understanding about the proposed subprojects and their possible environmental and social impacts is key to successful implementation. These issues should therefore be fully covered in the participatory assessment leading up to selection of the proposed subproject, and in subsequent design. The District Facilitation Team (DFT) should be fully prepared to lead public discussion of environmental and social issues. When DFT visits a village and hold meetings with the village Government leaders to discuss project concepts, objectives and types of eligible subproject etc., and process to be followed to evolve subprojects, they should introduce environmental issues. In order to raise awareness of communities about the potential environmental and social impacts of PADEP funded activities, a number of sensitisation meetings are proposed. These will enhance stakeholders participation in EA processes. Sensitisation should also target the National Resource Team and District Authorities in order to raise their awareness and understanding of the major environmental issues/concepts, such as: EIA; impact identification and prediction methods/techniques; social-cultural dimension of EIA; impact mitigation; and inspection and monitoring of environmental standards. Having been sensitised the District authorities, will in turn sensitise communities when they contact them to introduce and discuss the project concepts, objectives, components and focus through the DFT. When orienting the DFT on project objectives, implementation procedures and roles of teams in facilitating the communities the NRT should also include importance of assessing environment impact on each activity to be undertaken especially during implementation stage. Meeting village leaders: When DFT visits a village and hold meetings with the village Government leaders to discuss project concepts, objectives and types of eligible subproject etc, and process to be followed to evolve subprojects, they should introduce environmental issues concerning resource management and environmental conservation. • 34 PADEP Environmental Assessment First Village Meeting: The purpose should be to create awareness about the project. In this meeting DFT members should emphasize on the importance of observing natural impact on resource management, including soils, trees, sources of water etc., • • • • • • • • • • Village Meeting for prioritisation of problems: After prioritising their problems, the villagers and their facilitators should point out environmental issues related to the prioritised problem. Launching Workshop: Implementation processes will commence with the project launch workshop. The aim of launch workshop is to bring together stakeholders to revisit the project objectives, activities, work plans and each stakeholders responsibilities. This is a good opportunity for DFT to emphasize on the environmental impacts of the different activities to be undertaken and ways to avoid or mitigate. Other meetings: Meetings should be held on a regular basis with district authorities and communities at which PADEP activities in general, and their environmental consequences in particular are explained in simple and easily understandable terms. Depending on the prevailing social and cultural norms, there may be need to arrange separate meetings for different groups. For example, meeting with elders, women and youths. Workshops and seminars: These should be arranged for district authorities and communities around relevant environmental and social assessment themes. Plays and songs: Use/hire school children and drama groups to sing and play/act with messages related to environmental management and social protection. In order to enhance the effectiveness of these campaigns, the following strategies are recommended: Content: It is important to make sure that the contents of the launching workshops; seminars and meetings are relevant to the situation in village. Build speeches around real environmental problems within the village. Delivery strategy: The messages should be delivered in simple and easily understandable language. In order to facilitate understanding of the messages, use of visual aids – films, videos, placards etc is recommended. The occasions should include events like tree planting (season permitting or with watering) and study tours. As far as is feasible, the events should involve local government and national leaders. Cultural considerations: It is important to consider cultural and norms prevailing in the community. If free mixing is not possible due to social and cultural norms, there may be need to form groups according to age, gender and maybe wealth status. Publicity/advocacy: The launching ceremonies should be covered in local media – radio, newspapers, TV. Invite representatives from other communities to participate and let them say a word on their experiences. A training team should consist of an environmental specialist familiar with environmental assessment issues of PADEP subprojects, an agriculturalist familiar with PADEP’s subprojects, and an experienced training facilitator, who should be responsible for logistical planning and facilitation. 35 PADEP Environmental Assessment 6. COMPLIANCE OF PADEP ACTIVITIES WITH BOTH WORLD BANK AND TANZANIA’S POLICIES, GUIDELINES, LEGISLATION AND REGULATIONS 6.1 Compliance with World Bank safeguard policies A list of World Bank environmental and social safeguard polices is summarized in Box 6.1. The following safeguard policies are triggered by the proposed PADEP project: OP/BP 4.01 Environmental Assessment, OP 4.09 Pest Management, OP 4.12 Involuntary Resettlement, and OP 7.50 Projects on International Waterways. To the extent that sub-projects trigger World Bank safeguard policies, sub-project-specific safeguard documentation such as sub-project PMPs or sub-project Dam Safety Measures will be prepared. OP 4.01 Environmental Assessment: The Bank requires environmental assessment (EA) of projects proposed for Bank financing to help ensure that they are environmentally sound and sustainable, and thus to improve decision making. EA takes into account the natural environment (air, water, land); human and safety; social aspects (involuntary resettlement, indigenous peoples, and cultural property); and transboundary and global environmental aspects. EA considers natural and social aspects in an integrated way. It also takes into account the variations in project and country conditions; the findings of country environmental studies; national environmental action plans; the country’s overall policy framework, national legislation, and institutional capabilities related to the environment and social aspects; and obligations of the country, pertaining to project activities, under relevant international environmental treaties and agreements. The Bank does not finance project activities that would contravene such country obligations, as identified during the EA. OP 4.09 Pest Management: In assisting Borrowers to manage pests that affect either agriculture or public health, the Bank supports a strategy that promotes the use of biological or environmental control methods and reduces reliance on synthetic chemical pesticides. In Bank-financed projects, the Borrower addresses pest management issues in the context of the project’s environmental assessment. In appraising a project that will involve pest management, the Bank assesses the capacity of the country’s regulatory framework and institutions that promote and support safe, effective, and environmentally sound pest management. As necessary, the Bank and the Borrower incorporate in the project components to strengthen such capacity. OP 7.50 Projects on International Waterways: This policy applies to the following types of international waterways: (a) any river, canal, lake, or similar body that forms a boundary between, or any river or body of surface water that flows through, two or more states, whether Bank members or not, (b) any tributary or other body of surface water that is a component of any waterway describe in (a) above; and (c) any bay, gulf, strait, or channel bounded by two or more states, or, if within one state, recognized as a necessary channel of communication between the open sea and other states – any river flowing into such waters. This policy applies to the following types of projects (a) hydroelectric, irrigation, flood control, navigation, drainage, water and sewerage, industrial, and similar projects that involve the use or potential pollution of international waterways as described above and (b) detailed design and engineering studies of these projects, including those to be carried out by the Bank as executing agency or in any other capacity. Due to the use of international waters by future sub-projects, this safeguard policy is triggered, and the relevant riparians (Kenya, Uganda, Rwanda, Malawi and Mozambique) are being notified. Involuntary Resettlement (OP 4.12). The resettlement policy is triggered when people are affected by loss of land, loss of property and/or loss of access to resources. It is therefore irrelevant whether or not the impact will entail physically relocation of the affected people, the policy is triggered in all such cases. This means that the impact may be of such kind that only compensation in cash or kind is necessary. For this purpose, the Government of Tanzania has prepared a Resettlement Policy Framework which is a document that explains the procedures for resettlement and/or compensation, which must be followed once the Environmental Assessment has determined that people will be adversely affected by a project activity\". 36 PADEP Environmental Assessment The PADEP project will not cause involuntary resettlement, but some of the sub-projects may require changes in land use or changes in access to land. For that reason a Resettlement Policy Framework has been prepared. 37 PADEP Environmental Assessment Box6 6.1 World Bank Environmental and Social Safeguard Policies • Environmental Assessment (OP 4.01). Outlines Bank policy and procedure for the environmental assessment of Bank lending operations. The Bank undertakes environmental screening of each proposed project to determine the appropriate extent and type of EA. The Bank classifies the proposed project into one of four categories, depending on the type, location, sensitivity , and the scale of the project and the nature and magnitude of its potential environmental impacts. This environmental screening process will apply to all sub- projects to be funded by PADEP; sub-projects may be classified as category A, B, or C (category FI will not be applicable in this context). As indicated in the EA report, subsequent EA work for sub-projects will depend on the environmental classification of the sub-project. . • Natural Habitats (OP 4.04). The conservation of natural habitats, like other measures that protect and enhance the environment, is essential for long-term sustainable development. The Bank does not support projects involving the significant conversion of natural habitats unless there are no feasible alternatives for the project and its siting, and comprehensive analysis demonstrates that overall benefits from the project substantially outweigh the environmental costs. If the environmental assessment indicates that a project would significantly convert or degrade natural habitats, the project includes mitigation measures acceptable to the Bank. Such mitigation measures include, as appropriate, minimizing habitat loss (e.g. strategic habitat retention and post-development restoration) and establishing and maintaining an ecologically similar protected area. The Bank accepts other forms of mitigation measures only when they are technically justified. Should the sub-project-specific EAs indicate that natural habitats might be affected negatively by the proposed sub-project activities, such sub-projects will not be funded under the proposed PADEP project. • Pest Management (OP 4.09). The policy supports safe, affective, and environmentally sound pest management. It promotes the use of biological and environmental control methods. An assessment is made of the capacity of the country’s regulatory framework and institutions to promote and support safe, effective, and environmentally sound pest management. As outlined in the EA report, sub-projects will prepare sub-project specific pest management plans as required. A revised PMP for the PADEP project will serve as a guidance/reference document for the preparation of sub-project PMPs. • Involuntary Resettlement (OP 4.12). The resettlement policy is triggered when people are affected by loss of land, loss of property and/or loss of access to resources. It is therefore irrelevant whether or not the impact will entail physically relocation of the affected people, the policy is triggered in all such cases. This means that the impact may be of such kind that only compensation in cash or kind is necessary. For this purpose, the Government of Tanzania has prepared a Resettlement Policy Framework which is a document that explains the procedures for resettlement and/or compensation, which must be followed once the Environmental Assessment has determined that people will be adversely affected by a project activity\". This policy has been revised in FY 99/00 with the direct participation of technical Bank staff representing various networks. It also benefited from a four month external consultation process, in which the drafting team received and reviewed nearly 300 comments from NGO representatives, resettlement researchers, and government officials from around the world. This draft was approved in December 2001. The Resettlement Sourcebook, which will synthesize best practices in resettlement and provide guidance to staff in application of the policy, is now available. • Indigenous Peoples (OD 4.20). This directive provides guidance to ensure that indigenous people benefit from development projects, and to avoid or mitigate adverse effects of Bank-financed development projects on indigenous people. Measures to address issues pertaining to indigenous peoples must be based on the informed participation of the indigenous people themselves. Sub-projects that would have negative impacts on indigenous people will not be funded under the proposed PADEP project. • Forests (OP 4.36). This policy applies to the following types of Bank-financed investment projects: (a) projects that have or may have impacts on the health and quality of forests; (b) projects that affect the rights and welfare of people and their level of dependence upon or interaction with forests; and (c) projects that aim to bring about changes in the management, protection, or utilization of natural forests or plantations, whether they are publicly, privately, or communally owned. The Bank does not finance projects that, in its opinion, would involve significant conversion or degradation of critical forest areas or related critical habitats. If a project involves the significant conversion or degradation of natural forests or related natural habitats that the Bank determines are not critical, and the Bank determines that there are no feasible alternatives to the project and its siting, and comprehensive analysis demonstrates that overall benefits from the project substantially outweigh the environmental costs, the Bank may finance the project provided that it incorporates appropriate mitigation measures. Sub-projects that are likely to have negative impacts on forests will not be funded under the proposed PADEP project. • Cultural Property (OPN 11.03). The term “cultural property” includes sites having archaeological (prehistoric) , paleontological, historical, religious, and unique natural values. The Bank’s general policy regarding cultural property is to assist in their preservation, and to seek to avoid their elimination. 38 PADEP Environmental Assessment Specifically, the Bank (i) normally declines to finance projects that will significantly damage non-replicable cultural property, and will assist only those projects that are sited or designed so as to prevent such damage; and (ii) will assist in the protection and enhancement of cultural properties encountered in Bank-financed projects, rather than leaving that protection to chance. The management of cultural property of a country is the responsibility of the government. The government’s attention should be drawn specifically to what is known about the cultural property aspects of the proposed project site and appropriate agencies, NGOs, or university departments should be consulted; if there are any questions concerning cultural property in the area, a brief reconnaissance survey should be undertaken in the field by a specialist. The proposed PADEP project will not fund sub-projects that will have negative impacts on cultural property. • Safety of Dams (OP 4.37). For the life of any dam, the owner is responsible for ensuring that appropriate measures are taken and sufficient resources provided for the safety to the dam, irrespective of its funding sources or construction status. The Bank distinguishes between small and large dams. Small dams are normally less than 15 m in height; this category includes, for example, farm ponds, local silt retention dams, and low embankment tanks. For small dams, generic dam safety measures designed by qualified engineers are usually adequate. Sub-projects that will include small dams, i.e. chaco dams and other water management structures will prepare a generic dam safety analysis. • International waterways (O 7.50). The Bank recognizes that the cooperation and good will of riparians is essential for the efficient utilization and protection of international waterways and attaches great importance to riparians making appropriate agreements or arrangement for the entire waterway or any part thereof. Projects that trigger this policy include hydroelectric, irrigation, flood control, navigation, drainage, water and sewerage, industrial, and similar projects that involve the use or potential pollution of international waterways. The riparians are being notified in accordance with this policy; no additional steps need to be taken at the level of the sub-projects. • Disputed Areas (OP/BP/GP 7.60). Project in disputed areas may occur the Bank and its member countries as well as between the borrower and one or more neighbouring countries. Any dispute over an area in which a proposed project is located requires formal procedures at the earliest possible stage. The Bank attempts to acquire assurance that it may proceed with a project in a disputed area if the governments concerned agree that, pending the settlement of the dispute, the project proposed can go forward without prejudice to the claims of the country having a dispute. This policy is not expected to be triggered by sub-projects. This policy is unlikely to be triggered by sub-projects to be funded by the proposed PADEP project. 6.2 Compliance with Tanzania’s environmental management policies Implementation of the PADEP project will be undertaken in conformity to provisions of the Tanzanian National Environment Policy (NEP) of 1997 and The National Land Policy of 1995. Also relevant is the National Environment Management Council Act (no. 19 of 1983) which principally provided establishment of the National Environment Management Council (NEMC). Among others; the Act also stipulated the following functional roles and responsibilities for NEMC: • To advise government on all environmental-related issues (i.e. including impacts of PADEP activities) • To formulate environment policy • To establish multisectoral/multidisciplinary coordination among both institutions as well as respective individuals dealing with environmental issues. In other words, this incorporates aspects of community participation/involvement as required by PADEP. Also relevant are the Land Acts especially both no, 4 and 5 of 1999. These make far-reaching provisions for environmental management and natural resources because they provide for categorization of lands into three areas: namely: (a) general (i.e. unreserved or public lands) (b) reserved ( i.e. protected/conserved lands) (c) village lands (i.e. lands to be administered by village government authorities; as opposed to lands to be administered by central government) Other pertinent Land Acts (among several) are: • Land Acquisition Act no. 47 of 1967: which provides for compulsory acquisition of land in the interest of the public. 39 PADEP Environmental Assessment • National Land use Planning Commission Act; 1984 which mainly provides for establishment of the National Land use Planning Commission, but more importantly together with the Rural Lands (planning and utilization) Act no 22 of 1979 establishes the need for ensuring proper land use through e.g. multisectoral/multidisciplinary/coordination as well as cooperation, both of which are in the spirit of PADEP. • Town and Country Planning Ordinance Cap 378 of 1956, which provides for both methodology and approach to land use planning in both urban and rural areas. Local authorities will be essential to successful implementation of the PADEP project, and the powers of these are specified in several relevant pieces of legislation. The key legislations are as follows: • Local Government District Authorities Act no. 7 of 1982 duly amended in Act no. 8 of 1992, Act no.4 of 1985 and Act no, 13 of 1988 • Decentralization of government administration (interim provisions Act no. 27 of 1972, duly amended among several others in Act 26 of 1975, Act no. 12 of 1982 as well as in Act no. 19 of 1992. • There is a long list of district by-laws, most of which pertain to agriculture, for example the following: ♦ Manyoni District Development Council (Cultivation of Agricultural lands by-laws) ♦ Kilosa District Development Council (Cultivation of Agricultural lands by-laws) ♦ Bagamoyo District Development Council (Cultivation of Agricultural lands by-laws), etc., Several pieces of legislation govern use of specific resources. Key among them are: (i) Range Development and Management Ordinance (Cap 569), which provides for among others demarcation and improvement of range areas for livestock grazing. (ii) Wildlife Conservation Act no. 12 of 1974, which provides for protection of wildlife reserved areas from human activities. (iii) Forests Ordinance (Cap 389), which similar to Wildlife Act also provides for protection of forestry related reserved areas from human activities. (iv) Among several others; the following acts/ordinance in their totality provide for proper agricultural practices and thence products: • Grass-fires (control) Ordinance (Cap 13) • Plant protection Ordnance (Cap 133) • Food (control) of quality Act no. 10 of 1978 • Pharmaceuticals and poisons Act no. 9 of 1978 • Penal Code (Cap 16) • Section: 179: Negligent Spreading of diseases • Sections:180-81: Adulteration and sale of noxious food • Tropical Pesticides Research Institute Act no, 18 of 1979 • Water utilization (control and regulations) Act no. 42 of 1974 as duly amended in Act no 10 of 1981 as well as Act no 17 of 1989 Acts which promote/control industrial production and trade: • Small Industries Development Organization Act no 28 of 1973 • National Industries (Licensing and Registration Act) no 10 of 1967 with its amendments in Act 13 of 1982, no. 13 of 1991 and also amended by Investment Promotion Centre Act no 10 of 1992 • Penal code Cap 16; Section 186: on Trade 40 PADEP Environmental Assessment 7. PUBLIC CONSULTATION PROCESS As mentioned earlier, PADEP will not support subprojects classified as Category A because of limited capacity, both in terms of technical and financial resources, to implement preventive or mitigation measures required for this type of subprojects. According to Bank’s OP 4.01, all Category A and B subprojects proposed for PADEP financing, during the EA process, the implementing agencies (PCU, districts councils and communities/farmer groups) shall be required to consult subprojects-affected groups and local non-governmental organizations (NGOs) about the subproject’s environmental aspects and shall take their views into account. PADEP implementing agencies shall initiate such consultations as early as possible. PADEP should consult these groups at least twice: shortly after environmental screening and before the terms of reference for the EA are finalized; and once a draft EA report is prepared. In addition, the PADEP should consult with such groups throughout project implementation as necessary to address EA-related issues that affect them. For meaningful consultations between the implementing agencies and subproject-affected groups and local NGOs, relevant material shall be provided in a timely manner prior to consultation, and in a form and language that are understandable and accessible to the groups being consulted. Any Category B report for a subproject proposed for PADEP financing shall be made available to subproject-affected groups and local NGOs. For Category B subprojects, public availability of EA reports in Country is a prerequisite to PADEP funding of these subprojects. The consultation process with the subproject-affected groups will be as follows: Stakeholder identification: There should be an explicitly designed consultation strategy based upon NEMC guidelines and the Bank’s safeguard policies. Key stakeholders should be defined. The means for identifying and weighing the relative participation in the consultations of “affected communities” “beneficiaries” and other “stakeholders” should be considered. These should included representatives of government agencies, NGOs, religious groups, and village and community leaders. Gender and ethnicity should be considered in stakeholder identification and consultation process. • • • Information dissemination: A range of means for information dissemination is available, such as posters, radio reports, and public meetings and hearings. Key stakeholders should be targeted for information campaigns prior to meetings or hearings. Information materials for communities affected by subprojects should be translated into Kiswahili language. Consultation mechanism: The types of consultation mechanisms to be used in PADEP should include public meetings and workshops and seminars. A systematic survey to elicit opinions of persons affected directly by the subprojects could be considered. There are a wide variety of other effective techniques, which could be used for consultation, but apparently they are not tested in the country. These include public hearings, citizen advisory groups, focus groups, community opinion survey and expert panels discussions. According to the NEMC guidelines, public consultations are paramount during impact assessment, especially at the stage of scoping, ToR preparation and EA preparation. DFT should identify the main issues of concern and the affected or interested parties during the scoping exercise. To ensure satisfactory public (affected and/or interested people) involvement, DFT should initiate a public information programme of the area likely to be affected by the proposed subprojects. Any concern raised by the public should be recorded and addressed in the process of categorization of proposals. Public notice of the scoping process for the subprojects should be issued by NEMC (or accredited agency) through village leaders and/or other appropriate mechanisms. . NEMC requires that a summary of the draft EA conclusions, including the ESMP, be presented to affected communities and interested NGOs in a form and language meaningful to the groups being consulted. Comments made by the communities and NGOs must be incorporated into the EA report submitted to NEMC (or accredited agency) and subsequently PADEP for funding. Under the PADEP implementation procedures, public consultation will begin with the PRA on environmental issues in the communities. During the PRA, the subproject will be defined and, through 41 PADEP Environmental Assessment the screening process, its associated potential environmental impacts and category of the EA will be determined. During the subsequent scoping stages, if the project will be classified as category B, another public consultation will be held with the communities affected by the proposed subproject. Involvement of the public will continue throughout the EA process, using the community and farmer group subcommittees and village and community leaders. Once the draft EA report has been prepared, another consultation involving as many community members as possible, will be held to review the findings and recommendations of the draft EA report. Comments and observations shall be incorporated into the final EA report and the resulting ESMP report. 42 PADEP Environmental Assessment Annex 1 Sample check list for watershed management for soil and water conservation sub- project Name of Sub-project: _________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Reduce biodiversity? 3. Adversely affect downstream users? 4. Affect areas of water sources extraction? 5. Affect wetland/swamps areas? 6. Affect rare/endangered species? 7. Adversely effect human health? 8. Provide benefits to both men and women? 9. Cause changes in land, water morphology and physical characteristics as well as quality and quantity of resources? 10. Reduce quality of land, water, or health of plants or animals? Mitigation 11. Awareness raising? measures: 12. Improved designing and construction method. 13. Compensation if appropriate. 14. Are IPM approaches being adopted? 15. Have subproject-specific PMP been developed? 16. Are agro-chemical-related hazards being addressed? 17. Have PMP based on IPM approaches been developed? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 43 PADEP Environmental Assessment Annex 1 Sample check list for conservation tillage sub-project Name of Sub-Project: _________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to soil erosion? 2. Provide benefits to both men and women? 3. Entail loss of access to or use of land by current users? 4. Increase ability of soil to retain water? 5. Require use of unfamiliar agricultural chemicals? 6. Enable water resources conservation? 7. Affect groundwater table? 8. Introduce new pests? 9. Require storage of manure? 10. Lead to use of new implements? 11. Lead to appropriate management of residue? 12. Are IPM approaches being adopted? 13. Have subproject-specific PMP been developed? 14. Have agro-chemical-related hazards been addressed? 15. Have PMPs based on IPM approaches been developed? 16. Is training in IPM approaches planned? Comments by DFO: I recommend the proposal: Signature: (DFO Date: (clearance by NEMC and date) 44 PADEP Environmental Assessment Annex 1 Sample check list for fuel-efficient technology subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Provide benefits for both men and women? 2. Result in loss of access to or use of land by present landholders and users? 3. Increased cutting of trees or bushes? 4. Lead to loss of land cover and soil disturbances? 5. Lead to unsightly or foul smelling storage of compost or other matter? 6. Leaching of contaminants into water supply? 7. Lead to land degradation and soil disturbance? Mitigation 9. Are public awareness and training in biogas technology planned? 10. Are safe disposal methods of slurry in place? measures: 10. Siting of storage areas Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 45 PADEP Environmental Assessment Annex 1 Sample check list to increase productivity subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to application of organic manure? 2. Require significantly increased use of water? 3. Lead to loss of access to or use of land by present landholders or users? 4. Require use of new or unfamiliar agricultural chemicals? 5. Lead to salinization of soils? 6. Lead to contamination/pollution of surface and/or groundwater? 7. Lead to benefits for both men and women? 8. Introduction of new pests? Mitigation 9. Soil testing. measures: 10. Are public awareness and training in IPM approaches being considered? 11. Are soil, water and pests being monitored?. 12. Are IPM approaches being adopted? 13. Are subproject-specific PMP being developed? 14. Have agro-chemical-related hazards being addressed? 15. Are PMPs based on IPM approaches in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 46 PADEP Environmental Assessment Annex 1 Sample check list for integrated plant nutrition techniques/strategies (IPNS) sub- projects Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to application of organic manure, mineral fertilizers, bio-fertilizers? 2. Entail loss of access to or change in use of land by present landholders and/or users? 3. Provide benefits to both men and women? 4. Adversely affect quality of surface and ground water? 5. Increase weeds or pests? 6. Lead to salinization of soils? 7. Lead to loss of some plant species? Mitigation 8. Public awareness and training on IPM approaches? measures: 9. Are soil and water quality being monitored? 10. Are IPM approaches being adopted? 11. Have subproject-specific PMPs been developed? 12. Have agro-chemical-related hazards been addressed? 13. Is PMP based on IPM approaches being used? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 47 PADEP Environmental Assessment Annex 1 Sample check list for integrated pest management (IPM) subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Provide benefit to both men and women? 2. Entail loss of access to or use of land by current land holders and/or users? 3. Entail use of new or unfamiliar agricultural chemicals? 4. Adversely affect micro organisms in soil? 5. Adversely affect surface and groundwater (terrestrial or aquatic ecosystems)? 6. Adversely affect consumers crops (residues in vegetables and fruits)? 7. Soil contamination? 8. Water resources pollution? Mitigation 9. Has awareness campaign and training in IPM approaches been done? measures: 10. Is there adequate capacity for proper handling and storage of agrochemicals? 14. Have IPM approaches been adopted? 15. Are subproject-specific PMP developed? 16. Are agro-chemical-related hazards addressed? 17. Is the PMP based on IPM approaches? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 48 PADEP Environmental Assessment Annex 1 49 Sample check list for increased use of labour saving technology subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to loss of access to or use of land by present landholders or users? 2. Provide benefits to both men and women? 3. Entail production of more manure? 4. Introduce increased risk of accidents to humans? Mitigation 5. Awareness and training on safe use and handling of herbicides available? measures: 6. Proper storage and use of manure in place? 7. Are IPM approaches adopted? 9. Are herbicides-related hazards addressed? 10. Are PMP based on IPM approaches in place? 7. Compensation if appropriate Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 50 Sample check list for use of rainwater harvesting techniques subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Lead to increased incidence of water-borne disease? 3. Lead to land degradation at livestock watering points? 4. Provide benefits to men and women? 5. Increase risk of flooding during heavy rain? 6. Lead to siltation due to erosion? Mitigation 7. Is awareness and training plan in place? measures: 8. Are there plans to plant protective vegetation? 9. Are design specifications able to withstand reasonable risks of flooding? 10. Are IPM approaches adopted? 11. Are agrochemicals-related hazards addressed? 12. Are PMP based on IPM approaches in place? 13. Is there a need for the preparation of generic dam safety measures? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 51 Sample check list for improvement of traditional irrigation schemes subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Provide benefits to both men and women? 3. Result in increased salinity of soil or water? 4. Increase incidence of water borne disease? 5. Adverse impact on downstream users? 6. Land and water use conflicts? Mitigation 7. Provide drainage including disposal of water. measures: 8. Monitoring of soil and water 9. Is salinity monitoring plan in place? 10. Is awareness and training plan in place? 11. Are there plans to plant protective vegetation? 12. Are design specifications able to withstand reasonable risks of flooding? 13. Are IPM approaches adopted? 14. Are agrochemicals-related hazards addressed? 15 Are PMP based on IPM approaches in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 52 Sample check list for improvement in livestock production subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Create conflicts with customs/traditions of local communities with respect to livestock keeping? 3. Increase quantities of manure? 4. Lead to overgrazing? 5. Increase exposure of humans to animal borne disease? 6. Increase exposure to agricultural chemicals (dips)? Mitigation 7. Are the grazing arrangements rotational? measures: 8. Is public awareness and training planned? 9. Are the arrangements for handling and storage of manure and chemicals in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 53 Sample check list for production of non-traditional crops subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Entail loss of access to or use of land by present landholders and/or users? 2. Provide benefits to men and women? 3. Contribute to deterioration in soil quality? 4. Entail introduction of new pests? Mitigation measures: 5. Is public awareness and training program in place? 6. Is a pest monitoring and surveillance in plan in place? 7. Are PMP based on IPM approaches in place? 8. Are IPM approaches adopted? 9. Are agrochemicals-related hazards addressed? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 54 Sample check list for supply of farm inputs subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Entail loss of access to or use of land by present land holders and or users? 2. Entail local storage of agricultural chemicals? 3. Provide benefits to both men and women? 4. Enhance risk of robbery or theft? 5. Increase population of vermin or rats? Mitigation 6. Has security for money and goods (locks) been provide? measures: 7. Has public awareness been raised? 8. Is there good storage facility of agricultural chemicals and seeds? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 55 Sample check list for initial processing of agricultural and livestock products subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Increase production of by-products? 2. Entail loss of access to or use of land by present land holders and/or users? 3. Contribute to soil contamination? 4. Create unpleasant odours? 5. Affect water quality 6. Lead to benefits for men and women? 7. Lead to contamination of products? Mitigation 8. Is there proper disposal of wastes planned? measures: 9. Is the site appropriate?. 10. Is training and public awareness plan in place?. Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 56 Sample check list for improvement of crop produce marketing subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Provide benefits to men and women? 3. Create plant waste requiring disposal? 4. Create needs for latrines to accommodate gatherings of people? 5. Unpleasant odours? Mitigation 6. Is the plan for disposal of waste in place?. measures: 7. Has the site been carefully selected? . 8. Are the water supply and sanitation facilities provided? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 57 Sample check list for rehabilitation of infrastructure sub-projects Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Will it cause land use conflicts? 2. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 3. Generates excessive dust and noise? 4. Leads to creation of open pits? 5. Reduces biodiversity? 6. Leads to construction wastes? 7. Leads to loss of vegetation? Mitigation measures: 8. How is compensation for lost crops or grazing land going to be done? 9. Are protective gear provided? 10. Landfill arrangements in place? 11. Construction wastes management in place? 12. Biodiversity monitoring plan available? 13. Training on safety and precautionary measures planned? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 58"},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":198,"cells":{"data":{"kind":"string","value":"# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE AND FOOD SECURITY Participatory Agricultural Development and Empowerment Project (PADEP) RESETTLEMENT POLICY FRAMEWORK February 2003 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP TABLE OF CONTENTS A. Introduction ………………………………………………………………… 1 B. Policy Principles and Objectives Government Resettlement Preparation and Implementation …………………………………………………………… 2 C. Description of the Process for Preparing and Approving Resettlement Plans 4 D. Subprojects Identified Categories of Potential Impacts ……………………… 11 E. Eligibility Criteria for Defining various Categories of Affected Persons …… 15 F. A Legal Framework comparing the Borrower Laws and Regulations with the Bank Policy Requirements and Measures proposed to Bridge any Gaps between them ……………………………………………………………… 17 G. Methods of Valuing Affected Assets ……………………………………… 18 H. Organizational Procedures for Delivery of Entitlements, Including, for Projects Involving Private Sector Intermediaries, the Responsibilities of the Financial Intermediary, the Government, and the Private Developer …………………… 24 I. A Description of the Implementation Process, Linking Resettlement Implementation to Civil Works ……………………………………………… 25 J. A Description of Grievance Redress Mechanisms …………………………. 25 K. A Description of Mechanisms for Consultations with, and Participation of, Displaced Persons in Planning, Implementation and Monitoring …………….. 27 L. Arrangements for Monitoring by the Implementing Agency and, if Required, By Independent Monitors …………………………………………………….. 28 i WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP A. INTRODUCTION Tanzania is essentially an agricultural country. Over 80% of its population lives in rural areas and depends mostly on traditional agricultural and related activities. Agriculture contributes approximately 50% of GDP. The envisaged PADEP project seeks to increase productivity of smallholder farmers, to increase farm incomes, to reduce food insecurity, and to enhance management of soil fertility. The PADEP project will benefit 840 villages in 28 participating districts (out of a total of 121 in mainland Tanzania, and additional areas in Zanzibar. Specifically, it is planned that through the Community Investment Subprojects and Farmer Group Investment Subprojects of PADEP communities and farmer groups will request financing for sub-projects. Some of these sub projects may involve the construction of irrigation infrastructure, such as small dams, water retention ponds and other water management schemes, as well as those related to improved agricultural technology and marketing of inputs and output. Tanzania's average population density is relatively low at about 32 people /km2, and therefore population pressure on scarce land resources is not a major problem theoretically, but it is important in some localities, particularly semi-arid areas. Nonetheless, efforts should be made in the design and screening stages of the sub projects to avoid negative impacts on people, land, and property, including people’s access to natural and other economic resources, as far as possible. The necessity for land acquisition, compensation and resettlement of people may arise for certain categories of sub projects. When that occurs, the World Bank Operational Policy, OP 4.12 on Involuntary Resettlement and the Government of Tanzania's relevant policies and acts especially Land Acquisition Act of 1967 will be triggered. The preparation of a Resettlement Plan is not required at this stage since the sub projects, to be created on a demand driven basis have not yet been defined. Resettlement plans, when required, will be specific to particular sub-projects. Notwithstanding, in line with the Bank's Involuntary Resettlement Policy OP 4.12, the Government of Tanzania is required to prepare a resettlement policy framework to be disclosed before appraisal. The resettlement framework establishes the resettlement and compensation principles, organizational arrangements and design criteria to be applied to the sub-projects that will be prepared during project implementation in compliance with the laws of Tanzania and the Bank’s safeguards policy on involuntary resettlement. The subproject resettlement/compensation plans will be subsequently prepared consistent with this policy framework and will be submitted to the Bank for approval after specific planning information becomes available. All efforts will be deployed to minimize the need for resettlement in the project design stage. According to World Bank Operation Policy 4.12 on involuntary resettlement this resettlement policy framework will cover the following: • Policy principles and objectives governing resettlement preparation and implementation 1 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP • A description of the process for preparing and approving resettlement plans • Land acquisition and likely categories of impact. • Eligibility criteria for defining various categories of project affected persons • A Legal framework comparing the borrower laws and regulations and Bank policy requirements and measures proposed to bridge any gaps between them • Methods of valuing affected assets • Organizational procedures for delivery of entitlements, including, for projects involving private sector intermediaries, the responsibilities of the financial intermediary, the government, and the private developer • A description of the implementation process, linking resettlement implementation to civil works • Description of grievance redress mechanisms • A description of mechanisms for consultations with, and participation of, displaced persons in planning, implementation, and monitoring • Arrangements for monitoring by the implementing agency and, if required, by independent monitors. B. POLICY PRINCIPLES AND OBJECTIVES GOVERNING RESETTLEMENT PREPARATION AND IMPLEMENTATION The impacts due to involuntary resettlement from development projects, may give rise to economic, social and environmental risks resulting in production systems being dismantled, people facing impoverishment when their productive assets or income sources are lost, people being relocated to environments where their productive skills may be less applicable and the competition for resources increases; community institutions and social networks being weakened; kin groups being dispersed; and cultural identity, traditional authority, and the potential for mutual help being diminished or lost. The resettlement policy may be triggered because the project activity causes land acquisition, namely: a physical piece of land is needed and people may be affected because they are cultivating that land, they may have buildings on the land, they will use the land for watering and grazing of animals or they may otherwise access the land economically, spiritually or in any other way which may not be possible during and after the project is implemented. Therefore people will appropriately be compensated for their loss (of land, property or access) either in kind or in cash, of which the former is preferred. The Land Act No.4 and Village Land Act No.5 of 1999 have set clear procedures for full, fair and prompt compensation while acquiring land from citizens,. These procedures should be adhered to, especially the Land (assessment of the value of compensation) Regulations – made under S.179 of Land Act No. 4 of 1999. GN 78 published on 4/5/2001. 2 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Therefore, the objectives of this policy are the following: i) Involuntary resettlement and land acquisition should be avoided where feasible, or minimized, exploring all viable alternative sub projects design. ii) Where involuntary resettlement and land acquisition is unavoidable, resettlement and compensation activities should be conceived and executed as sustainable development programs, providing sufficient investment resources to give the persons displaced by the project the opportunity to share in project benefits. Displaced and compensated persons should be meaningfully consulted and should have opportunities to participate in planning and implementing resettlement programs. iii) Displaced and compensated persons should be assisted in their efforts to improve their livelihoods and standards of living or at least to restore them, in real terms, to pre-displacement levels or to levels prevailing prior to the beginning of project implementation, whichever is higher. Here, the affected people, according to the Bank policy, refer to people who are directly affected socially and economically by the Bank assisted investment projects, caused by: (a) the involuntary taking of land and other assets resulting in : (i) relocation or loss of shelter; (ii) loss of assets or access to assets; (iii) loss of income sources or means of livelihood, whether or not the affected persons must move to another location; or (b) the involuntary restriction of access to legally designated parks and protected areas results in adverse impacts on the livelihood of the displaced persons. The resettlement policy applies to all components under the project, whether or not they are directly funded in whole or in part by the Bank. The policy applies to all displaced persons regardless of the total number affected, the severity of impact and whether or not they have legal title to land. Particular attention should be paid to the needs of vulnerable groups among those displaced; especially those below the poverty line, the landless, the elderly, women and children, indigenous groups and ethnic minorities or other displaced persons who may not be protected through Tanzania land compensation legislation. In particular for PADEP, the policy requires that resettlement plans be developed for sub projects that entail acquisition of land and for which displacement or restriction of access may result. Determination of which sub-projects require resettlement plans will be made during the PRA process leading to the decision to formulate a proposal for a sub-project. Sub-projects that entail acquisition of land and for which displacement or restriction of access may result will require resettlement plans; others will not. Implementation of the sub-projects requiring resettlement plans cannot commence before necessary measures for resettlement and compensation are in place according to steps identified in the resettlement plan. These measures will include provision for compensation and other assistance required for relocation, prior to displacement, and preparation and provision of resettlement sites with adequate facilities, where required. In 3 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP particular, the taking of land and related assets may take place only after compensation has been paid and, where applicable, resettlement sites, new homes, related infrastructure, public services and moving allowances have been provided to displaced persons. For sub projects requiring relocation or loss of shelter, the policy further requires that measures to assist the displaced persons be implemented in accordance with the sub project’s resettlement plan of action. The policy aims to have the affected persons perceive the process and any compensation to be full, fair and prompt. C. DESCRIPTION OF THE PROCESS FOR PREPARING AND APPROVING RESETTLEMENT PLANS. To address the impacts under this policy, sub projects resettlement plans must include measures to ensure that the displaced persons are; a) informed about their options and rights pertaining to resettlement b) consulted on, offered choices among, and provided with technically and economically feasible resettlement alternatives c) and provided prompt and effective compensation at full replacement cost for losses of assets and access attributable to the sub project. Before implementation of the subproject, three interrelated documents will have to be prepared, namely, a) A socio-economic study (this study will include determination of impacts) b) Resettlement plan c) A valuation report of land and landed properties of the site 4 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP The purpose of the socio-economic study is to collect base line data within the project targeted areas thereby enabling the social assessment of potentially affected populations/communities. Under this study a comprehensive census would be carried out to identify potentially affected people on the individual and household levels, vulnerable groups (women, children, the elderly, female headed households, etc.). The social assessment would focus on identification of stakeholders (demographic data), the participation process, identification of affected people and impact on their property and their production systems, the institutional analysis and the system for monitoring and evaluation. Detailed calculation of household economies and identification of all impacts will be necessary in the social assessment and be the determinant in the potential compensation process. The components of the sub project resettlement/compensation plan will be: • Description of the Sub project • Potential Impacts • Sub project Objectives • Relevant findings of the socio-economic study • Legal framework • Institutional framework • Eligibility • Valuation of and compensation of losses • Resettlement measures • Site selection, site preparation, and relocation • Housing, infrastructure and social services • Environmental protection and management • Community participation • Integration with host populations • Grievance procedures • Organizational responsibilities • Implementation schedule • Costs and budget • Monitoring and evaluation The local communities who are to be assisted by PADEP, will be advised during the subproject identification/preparation stage whether of not the resettlement policy will be triggered. At that stage the local community may decide to drop the sub project on that basis. If they chose to continue with the sub project, however, then they will be advised to prepare a resettlement plan, and will be assisted to do so. The resettlement plan will then be forwarded for screening and approval through the District Council in compliance with the project institutional administrative arrangements. The Ministry responsible for Agriculture and Food Security will have representatives to provide the necessary technical support required at this level. Sub projects requiring resettlement plans that are approved at the district level will be subject to final screening by the PADEP Project Coordination Unit. The EA and resettlement plans would also be reviewed and approved by the Bank to ensure compliance with Bank Safeguards, thereby 5 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP ensuring that before the sub project is approved for funding by the Bank, the resettlement plans are consistent with this framework policy. Therefore, each sub project that is proposed to be included would be screened and classified according to its environmental and social impact. The screening and classification process should follow certain criteria already established and the mitigation measures that will be proposed vis a vis environmental and social issues should be in compliance with all Government of Tanzania environmental policies and World Bank Safeguard policies. Certain activities will not be funded by the project, including those likely to trigger selected safeguards for e.g. disputed areas, cultural property, indigenous peoples and natural habitats. The DMT will screen the proposed sub projects that it receives from the beneficiaries. The Screening Process The screening process would take the form of: General sub project sub sector classification: a. Dam construction b. Expand irrigated areas c. Expanded land areas or consolidation in order to make more rational use of land Agro-ecological zonal location of Sub project • Coastal zone • Semi-arid zone • Highland zone • Mountainous zones 1.) Classifying the sub projects by activity into the following categories; Identification of the type of sub-project, and determination of whether the sub- project will entail repair/ rehabilitation or new construction. In general sub- projects that repair and/or rehabilitate existing infrastructure will not trigger the resettlement policy. Those that entail new construction are more likely to trigger the policy if the activity involves acquisition of land and if displacement or restriction of access may result. Types of activity might require resettlement plans include the following, inter alia; e.g., i) Dam construction ii) Expanded irrigated areas iii) Expansion or consolidation of land areas to improve use 2.) Identifying and evaluating potential impacts for each proposed sub project according to whether land is acquired and whether displacement or loss of access may result. 3.) Triggering of the resettlement policy will be one criterion by which sub projects can be rejected. 6 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 4.) Alternatively, triggering of the resettlement policy would require further a preliminary determination of whether the sub project should be proposed or not, based on an assessment of the intensity of the impact and on the mitigation measures that would need to be developed and proposed. The communities and/or farmer groups may then determine whether or not to proceed to present the proposal to the DMT even where extensive/cumbersome mitigation measures are deemed necessary in the sub project. Determining the need for land acquisition and, if so, whether it is necessary to obtain legal title to the land. Under the right-of-occupancy land tenure system, legal title as expressed in a property deed is not always necessary. 5.) Use of the Socio Economic Studies to identify affected people on the household level and vulnerable groups in the sub project impact area(s) and to calculate household economies. 6.) Using the environmental assessments 7.) Ensuring that land required/acquired is not, (i) in disputed areas, (ii) cultural property, (iii) negatively affecting indigenous peoples and (iv) is not in natural habitats. This is a pre-condition for approval. The above screening process should be used by the local communities assisted by technical personnel in the district in the preparation of their sub projects to enhance likelihood approval. At the level of the DMT, project proposals will be reviewed according to the same criteria. The DMT would also review the sub project Environmental Assessment (EA) reports. Furthermore, the DMT should as a guideline consider the cumulative factor and not approve sub projects that have individual high impact intensity. For example, where land acquisition is required to such an extent that it would require more than 20% of a community’s or individual household’s total land under cultivation or when the mitigation measures are so cumbersome that their efficacy cannot be ensured or they cost more than 20% of the investment budget, district authorities should in general reject such proposals. Before a decision to approve a sub project requiring a resettlement plan is taken, the DMT will need to approve the resettlement plan of the sub project together with the overall environmental and social screening process that has been applied for each sub project and to also approve or disapprove of the proposed mitigation measures, if any. With respect to PADEP in Tanzania the following is a sample of possible sub projects that may be proposed by the communities and/or farmer groups that would trigger the involuntary resettlement policy with probable environmental and social impact; Sub project Impact OP 4.12 Construction of Dams for Irrigation and water supply Land acquisition, lack of access, loss of shelter. Risk of flooding. Yes Expansion of areas under irrigation -as above -as above 7 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Expansion of area or consolidation of parcels for improved agricultural production -as above -as above The sub projects are expected to be small in scale. The cumulative effect of hundreds of sub projects, however, may be significant and a review must be made at a level higher than the community level on the possible cumulative impact of the sub projects. If the impact is significant, individual mitigation measures per sub project should be assessed to determine their adequacy relative to the cumulative impact. When the cumulative impact of sub projects is being considered at the local, regional and/or national levels, additional mitigation measures may be deemed necessary. These would have to be integrated into the resettlement plans of sub projects and the monitoring and evaluation plan of the project. Capacity will be built at the community levels by providing technical assistance to allow communities to screen their sub-project ideas for environmental and social concerns. This training will also include the capacity to develop mitigation measures to meet environmental and social impacts and to prepare implementation of such measures. Capacity will also be built at the decentralized (departmental) levels of the district authorities as well as at national level of the Ministry of Agriculture and Food Security to assist them effectively to carry out their role at both the district levels and at the central levels. District Facilities Teams that are required to work with local communities should be targeted for training to enhance their skills and to produce more of them. This would build capacity at the local level, which is crucial for the success of this project. Communities and/or farmer groups may use the templates below during the PRA process to determine whether or not proposed sub-projects will entail acquisition of land, and if so, who may be among the affected people. 8 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP PARTICIPATORY AGRICULTURAL DELOPMENT AND EMPOWERMENT PROJECT SUBPROJECT LAND REQUIREMENT AND ACQUISITION FORMS (a); Existing land resources 1. Name of Village:……………………………………. Postal Address: P. O. Box…………………District ……………….Region ……………………. 2. Current land tenure/ownership in the village Ha. • Individual land...……………………………………………………………....……. • Household land …………………………………………………..… ……………... • Community land, e.g. belonging to religious organizations, • CBOs, other (specify) .………………………………………… ….………...……. • Village land (under Village Government) ………………… … …….………...….. • Government land (under Central Government) ………………….. ……...……….. TOTAL LAND RESOURCES …………………………..…….. 3. Subproject land requirement..….…….. 4. Agreement to meet subproject land requirement, as per Village Government Meeting of (day/month/year) and confirmed by Village Assembly of (day/month/year) Sample form for agreement regarding identification of land needed for a sub-project: With compensation Ha Without compensation Ha Sub- total Ha Wholly from village land Partly as follows: From individual land From household land From community land From village land From government land Grand-total allocation Assessment of overall current land use 9 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Tenure system Current land use in ha. Remarks Fallow Cropped Grazing/ pasture Forest Mixed (specify) Individual land Household land Community land Village land Government land TOTAL Assessing current use of earmarked land Tenure system Current land use in ha. Remarks Fallow Cropped Grazing/ pasture Forest Mixed (specify) Individual land Household land Community land Village land Government land TOTAL 10 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 11 Analyzing Subproject land allocation from individual land with corresponding compensation Name of individual With compensa tion Ha Compens ation rate /ha TShs. Compensat ion per individual TShs. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. Total The first table above gives an overview of the land resources available in the village. The next table shows the current land use in overall terms while the next gives the current land use of that land which is earmarked for allocation to the development project. The last specifies the contribution of individuals to the land earmarked for the subproject, and the agreed compensation. D. SUBPROJECTS IDENTIFIED CATEGORIES OF POTENTIAL IMPACTS Generally, the subprojects, which are likely to be proposed by community, are individually not expected to generate major negative environmental impacts to the human and natural environment. However, their cumulative impacts could be significant. Again, based the types of possible projects to be funded by PADEP, potential negative social and environmental impacts are presented in the Table below, together with their mitigation measures. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 12 Table 2.1: Potential negative impacts & mitigation measures by PADEP possible subproject types Subproject type Potential impacts Mitigation measures Watershed management for soil and water conservation Land use conflicts, loss of land and property Illegal harvesting Encroachment Lost opportunities Infringement on property rights Awareness raising Participatory land use planning and management Application of the Resettlement Policy Framework (resettlement and compensation) By-laws and their effective enforcement Joint management programmes Provision of alternatives Conservation tillage Contamination of ground water table and river pollution Disturbance on ecological functioning of farming systems Loss of historical/cultural sites Reluctance to reduce plowing Soil conservation measures Fertilization management Proper residue management Awareness raising IPM Proper site selection Efficient use of fertilizers Health risks Salinization Surface & groundwater contamination/pol lution Dust Air pollution Promoting weed growth Conduct training of safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility management Provision of protective gear Bringing the moisture content to 7-8 percent Biodiversity assessment and monitoring Fuel efficient technology Ground water pollution Ammonia losses Effect on vegetables and fodder Control surpluses of slurry Cover the soil Locate far from residential settings Different design concepts WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 13 Increasing productivity through use of organic manure in combination with mineral fertilizers, bio-fertilizers Salinization of soils Contamination of surface and groundwater Loss of plant species Awareness and training Promote high value crops Use of high grade fertilizers Integrated plant nutrition techniques/strategies (PNS) Salinization of soils Pollution of surface and groundwater Loss of some plant Health risks Awareness and training Salinity monitoring Integrated soil fertility management Promoting weed growth Integrated pest management (IPM) Soil contamination Water resources pollution Loss of animal and plant species Awareness and training High value crops Conduct biodiversity assessment and monitoring Increased use of labour saving technologies Loss of soil fertility Loss of water sources Loss of plant and animal species Potential land conflicts Employ farm management principles Use of appropriate technology Awareness raising Participatory land-use planning Gender awareness in selection of technology Use of rainwater harvesting techniques Contamination of stored water Siltation due to erosion Potential floods during heavy rains Water and land use conflicts Land degradation at livestock watering points Awareness & training on safe handling and storage Disinfections By-laws and their effective enforcement Provision of safe watering points/structures for livestock Participatory planning Improvement of traditional irrigation schemes Land and water use conflicts Loss of land and property Water-borne diseases Secondary water uses (domestic, Awareness & training Participatory land and water use planning & management, e.g. WUAs Application of the Resettlement Policy Framework (resettlement and compensation). By-laws and enforcement Provide for domestic and livestock WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 14 livestock) Infringement on access and movement for humans and livestock Water logging Poor water quality esp. for downstream users water supply Include access crossings at convenient locations for people and livestock Provide for drainage of tail waters Improvement in livestock production Overgrazing Land degradation Health risks from use of acaricides in dips Gas emissions Awareness & training Observing land carrying capacity Combine with biogas technology Production of non- traditional crops Soil contamination Introduction of new pests Loss of habitats and species Quarantine Adherence to regulations Awareness & training Biodiversity assessment and monitoring Supply of farm inputs Wastes from packaging materials plastics, tins and cans Livestock and wildlife might consume the plastic materials Health risks from agro-chemicals Proper disposal of wastes Institute by-laws Awareness & training Provision of protective gear Initial processing of agricultural and livestock products Wastes from processing Contamination of products Vibrations Soil and liquid wastes from processing might affect plant and animal species Provide for proper waste disposal Ensure hygienic conditions Conduct biodiversity assessment and monitoring Provision of protective gears, health insurance, awareness raising Adherence to industrial health regulations Improvement of crop produce marketing Wastes at markets Contamination of products Soil contamination Poor sanitation Waste management strategies Design an appropriate sanitary land- fill Provide for water supply and sanitation facilities WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 15 E. ELIGIBILITY CRITERIA FOR DEFINING VARIOUS CATEGORIES OF AFFECTED PERSONS At this stage it would not be possible to attempt to quantify the estimated likely number of people who may be affected since the sub projects have not been created. However, the likely displaced persons can be categorized into three groups, namely; i) Affected Individual - An individual who suffers loss of assets or investments, land and property and/or access to natural and/or economical resources as a result of the sub- projects and to whom compensation is due. For example, an affected individual is a person who farms, or who has built a structure on land that is now required by a sub project for purposes other than farming or residence by the initial individuals. ii) Affected Household - A household is affected if one or more of its members is affected by project activities, either by loss of property, land, loss of access or otherwise affected in any way by project activities. This provides for: a) any members in the households, men, women, children, dependent relatives and friends, tenants. b) vulnerable individuals who may be too old or ill to farm along with the others c) relatives who depend on one another for their daily existence. d) any members in the households, men, women, children, dependent relatives and friends, tenants, and e) Other vulnerable people who cannot participate for physical or cultural reasons in production, consumption, or co-residence. Compensation will not be limited to people who live together in a co-resident group, since this might leave out people whose labor contributions are critical to the functioning of the “household”. iii) Affected local community – A community is affected if project activities affect their socio-economic and/or social-cultural relationships or cohesion. For example project activities could lead into such improvement of socio-economic welfare that class- consciousness arises coupled with cultural erosion etc. iv) Vulnerable Households - vulnerable households may have different land needs from most households or needs unrelated to the amount of land available to them.: a) unmarried women b) Non-farming c) Elderly d) The infirm or ill e) Orphans Each category of vulnerable person or household must be compensated according to the nature of the economic loss suffered by loss of access to or use of the land acquired by the sub-project. The Bank’s OP4.12 suggests the following three criteria for eligibility; WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 16 a) Those who have formal legal rights to land (including customary and traditional rights recognized under the laws of Tanzania); b) Those who do not have formal legal rights to land but have a claim to such land or assets- provided that such claims are recognized under the laws of Tanzania or become recognized through a process identified in the resettlement plan. c) Those who have no recognizable legal right or claim to the land they are occupying. Those covered under a) and b) above are to be provided compensation for the land they lose, and other assistance in accordance with the policy. Persons covered under c) above are to be provided with resettlement assistance in lieu of compensation for the land they occupy, and other assistance, as necessary, to achieve the objectives set out in this policy, if they occupy the project area prior to a cut-off date established by the Government of Tanzania and acceptable to the Bank. Persons who encroach on the area after the cut-off date are not entitled to compensation or any other form of resettlement assistance. All persons included in a), b) or c) above are to be provided with compensation for loss of assets other than land. Therefore, it is clear that all affected persons irrespective of their status or whether they have formal titles, legal rights or not, are eligible for some kind of assistance if they occupied the land before the entitlement cut-off date. The entitlement cut-off date refers to the time when the assessment of persons and their property in the project area is carried out, i.e. the time when the project area has been identified and when the socio-economic study is taking place. Thereafter, no new cases of affected people will be considered. Persons who encroach the area after the socio-economic survey (census and valuation) are not eligible for compensation or any form of resettlement assistance. Eligibility for Community Compensation Local Communities (villages, cantons wards; divisions etc) permanently losing land and/or access to assets on under customary rights will be eligible for compensation. F. A LEGAL FRAMEWORK COMPARING THE BORROWER LAWS AND REGULATIONS WITH THE BANK POLICY REQUIREMENTS AND MEASURES PROPOSED TO BRIDGE ANY GAPS BETWEEN THEM. LAND TENURE AND OWNERSHIP Land in Tanzania is owned by the state, and ownership is vested with the President. It is categorized as follows: general/public land on which socio-economic activities are permitted; reserved/restricted lands for national parks; protected areas; and forest/wildlife reserves. About 25% of Tanzania falls into the category of reserved/ restrictive. By international standards this is a high proportion of land under restriction.. Only about 20% of potentially arable land is actually cultivated. Communities and individuals are not permitted to use reserved or restricted land for economic activities. Land is so designated by order of the President or the Minister charged with conservation of natural resources. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 17 Tenure rights to land in the first category can be held by individuals and by communities. Village communities are allowed to hold land and to manage it, although they do not formally own the land. Holdings of individuals can be as follows:- • By leasehold right of occupancy for varying periods; e.g. for 33,66,99 years • By customary lands i.e. in usufruct in perpetuity. Tenure rights are defined by the Land Act and the Village Act. The Land Act No. 5 of 1999 provides for village land to be administered and managed by the local communities. Land that is not village land can be allocated by the state to users under specified tenure regimes. In addition, Participatory Land Use Planning and Management (PLUM) is explicitly recognized in the Land Policy of 1995. The adjudication function on village lands is assigned to the village government. Taxation is the prerogative of local authorities. Villagers hold rights of occupancy and use for an indefinite (i.e., unlimited) period. Village lands do not have to be titled for rights of users and occupants to be recognized, and are not subject to rental payments. Security of tenure is not a major issue at the village level. In accordance with provisions of the Tanzanian legal framework, a process for preparing and approving resettlement plans should be based on PLUM (with technical assistance of relevant district functional officers). The Village government should therefore be able to: • Review the proposal to prepare a resettlement plan • Discuss the proposal in its village organs • Prepare and agree on proposals of the resettlement plan • Approve the resettlement plan subject national legislations esp. Land Act no. 4 of 1999 and Land Acquisition Act of 1967. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 18 Land Tenure for Sub Projects Village government has administrative control over the village land and acts as a liaison between the government and the inhabitants of the village. Within villages, use of land is controlled by various committees of village government. At present, local communities are operating on their own land. However, if their sub projects require more land, extension of their existing land or new land, they would have to acquire the land through the village government. G. METHODS OF VALUING AFFECTED ASSETS The valuation of affected assets will be carried out by estimation of the market value, when it is known, and/or by estimation of the replacement cost. Graves are valued separately – under the Graveyard Removal Act of 1968.. Valuations methods for affected land and assets would depend on the type of asset. The land asset types identified under Tanzania law in this policy framework are; i) State Land not within the jurisdiction of a village ii) Village Land, including customary rights of villagers State owned land would be allocated free (perhaps except for surveying and registration fees), and the sub project would be expected to pay to acquire land in this category in cases where the state-owned land is being used by individual farmers. This is because, although state owned, the land may be used by individuals and/or household farmers. The guiding principle is that whoever was using the land to be acquired by the sub project, would be provided other land of equal size and quality. Assets held under customary rights on state owned land would have to be valued according to the following method and compensation paid for. The sub projects would value and duly compensate for assets and investments, including land, crops, buildings, and other improvements, according to the provisions of the resettlement plan. Compensation rates would be market rates as of the date and time that the replacement is to be provided. The current prices for cash crops would have to be determined. Compensation would be based on valuation at or before the entitlement cut off date in compliance with this policy. Homestead sites such as bush are community property. Only structures on the site belong to individuals. The permanent loss of any homestead site will be covered by community compensation which will be in-kind only. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 19 Compensation for Land Compensation is intended to provide a farmer whose land is acquired and used for sub project purposes with compensation for land, labor, and crop loss. For this reason, and for transparency, land is defined as an area: • In cultivation • Being prepared for cultivation, or • Cultivated during the last agricultural season This definition recognizes that the biggest investment a farmer makes in producing a crop is his or her labor. A farmer works in his/her land ,most of the months of the year. The major input for producing a crop is not seed or fertilizer, but the significant labor put into the land each year by the farmer. As a result, when land acquired has a standing crop, the farmer will be compensated in full for the expected market value of the crop. This compensation will cover loss of investment of labor and purchased inputs for the production year in question. FORMS OF COMPENSATION Cash Payments Compensation will be calculated and paid in the national currency. Rates will be based on the market value of land when known, or estimated when not known, plus compensation for the value of standing crops. In-Kind Compensation Compensation may include items such as land, houses, other buildings, building materials, seedlings, agricultural inputs and financial credits for equipment. Assistance Assistance may include moving allowance, transportation and labor Because land market transactions are not recorded in Tanzania, market values may not be observable, and will have to be imputed through simple estimation of discounted loss of the stream of future income derived from land. As an approximate rule in a country with ample land and labor-intensive agriculture, the contribution of land can be imputed as about 25% of the gross market value of output. The present value of this future income stream in perpetuity, when discounted back to the present at a discount rate of 12% amounts to approximately twice the average annual value of output. Therefore a person who gives up a parcel of agricultural land for use by a sub-project could be adequately compensated in cash in the amount of twice the average value of gross annual output (plus the additional value of the standing crop, if any). Compensation in kind would take the form of provision of an alternative parcel of equal size and quality. If cash compensation is used, financial institutions should encourage the use of their facilities to reduce likelihood of loss or theft when beneficiaries are compensated in cash. Each recipient in consultation with the project implementation unit will decide upon the time and place for in-kind compensation payments. A subproject that interferes with pastoralists or grazing land will not be approved for financing by the Project unless the affected people have been offered alternative land as compensation in kind and acceptable to the affected people. Compensation for buildings and Structures. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 20 Compensation will be paid by replacing structures such as huts, houses, farm outbuildings, latrines, and fences on alternative land provided as in-kind compensation. Cash compensation would be available as a preferred option for structures (i.e. extra buildings) lost, that are not the main house or house in which someone is living. The going market prices for construction materials will be determined. Alternatively, compensation will be paid in-kind for the replacement cost without depreciation of the structure. Compensation will be made for structures that are: • Abandoned because of relocation or resettlement of an individual or household, or • Directly damaged by construction activities. Replacement values will be based on: • Related structures and support services • Average replacement costs of different types of homestead buildings and structures based on collection of information on the numbers and types of materials used to construct different types of structures (e.g. bricks, rafters, bundles of straw, doors etc.), • Prices of these items collected in different local markets, • Costs for transportation and delivery of these items to acquired/ replacement land or building site, • Estimates of construction of new buildings including labor required. Compensation for Sacred Sites The use of sacred sites, ritual sites, tombs and cemeteries is not permitted under this project. Compensation for vegetable gardens and beehives. These are planted primarily for use within the household. Until a replacement garden starts to bear, the family losing gardens or beehives will have to purchase vegetables and honey in the market. The replacement costs therefore, will be calculated based on the local market rates for these products at the time. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 21 Beehives are placed in various locations in the bush by some individuals that specialize in honey gathering. If such hives would be disturbed by the sub project activities, or access to the hives denied, beekeepers can move them, and the bees will adapt to the new locations. Activities of beekeepers would be valued and duly compensated based on value of one season’s production costs of honey for each hive that is moved and any reasonable costs associated with moving the hive. Large fruit and crop trees Large fruit/trees e.g. mangoes and coconut important as a source of: • Subsistence food for families • Petty market income in some areas, and • Shade Given their significance to the local subsistence economy, which this project intends to enhance, mango and coconut trees will be compensated on a combined replacement/market value. Mango and coconut trees used for commercial purposes will be compensated at market value based on historical production records. If households chose to resettle, they will be compensated for the labor invested in the trees they leave behind. The compensation rate will be based on information obtained from the socio-economic study. From this study, a compensation schedule for trees can be developed incorporating the following goals: • Replace subsistence mango and coconut production yields as quickly as possible. • Provide subsistence farmers with trees to extend the number of months of the year during which fruit is produced and can be harvested as a supplemental source of food for their families during their “hungry season”. • Provide farmers with the opportunity to derive additional production income from trees bearing more valuable fruits at off-season periods. • Provide cash payments to farmers to replace pre-subproject income derived from the sale of excess production until replacement trees produce the equivalent (or more) in projected cash income. It should be pointed out the Valuation Division in the Ministry of Lands and Human Settlements Development has developed crop compensation rates. These rates are to be reviewed every year. Compensation assessment must be approved by Chief Government Valuer. Displaced people have to be issued with land form 59 and 70 which allows them to indicate what they expect to be compensated. The compensation schedule is based on providing a combination of new grafted and local trees to farmers, as well as cash payments to offset lost yearly income. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 22 Proposed Schedule for Mango and Coconut Trees Cut Down Type/Age of Tree Est. Years In-kind replacement for Local Mangoes Sapling Trees planted after sub project cut-off date in area will not be eligible for compensation 0-1 Deliver to Farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade. Sapling/Young Tree First minor production 12-50 fruits occurs about age 4-5 1-6 Deliver to farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade Mango Trees Fruit Producing 6-30+ Deliver to farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade Mature Trees – Low or Non- Fruit Producing 30+ Same as for mature trees above No compensation will be paid for minor pruning of trees. Compensation for removal of limbs will be prorated on the basis of the number of square metres of surface area removed. The total surface area of the tree will be calculated using the following formula: (½ diameter of canopy) 2 x 3.14. Other domestic fruit and shade trees. These trees have recognized local market values. Depending upon the species and age. Individual compensation for wild trees “owned” by individuals, who are located in lands as defined in this policy, will be paid. Note that wild, productive trees belong to the community when they occur in the true bush as opposed to a fallow land. These trees will be compensated under the umbrella of the village or community compensation. Examples include: avocado, bananas, lemon, guava, lime, oranges, grapefruits, papaya, tamarind etc. INDIVIDUAL COMPENSATION Sub-Category Unit Compensation Value (TSHS) WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 23 Foodstuffs & others Domestic Fruit Trees Avocado Non-productive productive 13,000 Banana Non-productive productive 11,000 Lemon Non-productive productive 5,000 Guava Non-productive Productive 6000 Lime Non-productive Productive 5,000 Orange Non-productive Productive 14,000 Grapefruit Non-productive Productive 2,000 Papaya Non-productive productive 4,000 Shade Trees Young 2,000 adult 5,000 Individual Owned Wild Productive Trees Non-productive 13,000 Tamarind productive Crops Yield/ha 1,200 110,000 Maize Rice Yield/ha 1,000 180,000 Beans Yield/ha 500 87,000 Vegetables Yield/ha 8,300 220,000 Tomatoes Water melon Yield/ha 8,300 860,000 Lettuce Yield/ha 3,500 305,000 Cauliflower Yield/ha 5,000 275,000 Carrot Yield/ha 10,000 880,000 H. ORGANIZATIONAL PROCEDURES FOR DELIVERY OF ENTITLEMENTS, INCLUDING, FOR PROJECTS INVOLVING PRIVATE SECTOR INTERMEDIARIES, THE RESPONSIBILITIES OF THE FINANCIAL INTERMEDIARY, THE GOVERNMENT, AND THE PRIVATE DEVELOPER. Compensation (and resettlement) will be funded like any other activity eligible under the projects’ administrative and financial management rules and manuals. Payments will be included WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 24 in the costing of the project, and finances for the payments will be made available to the communities and/or farmer groups through the usual flow of funds. For sub-projects involving payment of compensation, monitoring activities will include confirmation that payments were received by those entitled to them. The compensation process will involve several steps and would be in accordance with the sub- project resettlement plans, significantly; • Public Participation: Local communities would initiate assessment of the appropriateness of compensation at the concept stage of the sub project. Affected individual/households will be invited to become involved in design activities. • Notification Affected individuals and households will be identified during the PRA process and notified. The user will be informed through both a formal notification in writing and, as many as people are illiterate, by verbal notification delivered in the presence of the village chief or his or her representative. In addition, the chairman, village chiefs committees individuals who control fishing areas, wild trees, or beehives will accompany the survey teams to identify sensitive areas. • Documentation of Holdings and Assets – village officials and District Project Officer to arrange meetings with affected individuals and/or households to discuss the compensation process. For each individual or household affected, the District Project Officer completes a compensation dossier containing necessary personal information on, the affected party and those that s/he claims as household members, total land holdings, inventory of assets affected, and information for monitoring their future situation. This information is confirmed and witnessed by village officials; Dossiers will be kept current and will include documentation of lands surrendered. This is necessary because it is possible that an individual will surrender several parcels of land over time and will eventually become eligible for resettlement. All claims and assets will be documented in writing. • Agreement on Compensation and Preparation of Contracts – All types of compensation are clearly explained to the individual or household. The District Project Officer (DPO) draws up a contract listing all property and land being surrendered, and the types of compensation (cash and/or in-kind) selected. A person selecting in-kind compensation has an order form, which is signed and witnessed. The compensation contract is read aloud in the presence of the affected party and the village Chairman and other village leaders prior to signing. • Compensation Payments – All payments and transfers in kind will be made in the presence of the affected party and the village authorities. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 25 Community Compensation Payments Community compensation will be in-kind only for a community as a whole in the form of reconstruction of the facility to at least the same standard or better standard to that being built by local NGO’s. Examples of community compensation include, • School Building (public) • Public Toilets • Well or Pump • Market Place • Road • Storage warehouse I. A DESCRIPTION OF THE IMPLEMENTATION PROCESS, LINKING RESETTLEMENT IMPLEMENTATION TO CIVIL WORKS. Before any project activity is implemented, people who are affected and have been determined to be entitled to compensation will need to be compensated in accordance to the policy and the resettlement policy framework. For sub projects involving land acquisition, it is further required that these measures include provision of compensation and of other assistance required for relocation, prior to displacement, and preparation and provision of resettlement sites with adequate facilities, where required. In particular, the taking of land and related assets may take place only after compensation has been paid and, where applicable, resettlement sites and moving allowances have been provided to displaced persons. For sub projects requiring relocation or loss of shelter, the policy further requires that measures to assist the displaced persons be implemented in accordance with the sub project’s resettlement plan of action. The measures to ensure compliance with this policy directive would be included in the resettlement plans that would be prepared for each sub project involving resettlement or compensation. The timing mechanism of these measures would ensure that no individual or affected household would be displaced due to civil works activity before compensation is paid and resettlement sites with adequate facilities are prepared and provided for to the individual or household affected. Once the resettlement plan is approved by the local and national authorities, the resettlement plan should be sent to the World Bank for review and approval. J. A DESCRIPTION OF GRIEVANCE REDRESS MECHANISMS. At the time the resettlement plan is approved and individual compensation contracts are signed, affected individuals would have been informed of the process for expressing dissatisfaction and to seek redress. The grievance procedure will be simple, administered as far as possible at the local level to facilitate access, flexible and open to various proofs taking into cognizance the fact most people are illiterate requiring a speedy, just and fair resolution of their grievances. Communities and/or farmer groups will in general be a party to the contract would not be the best organizations to receive, handle and rule on disputes. Therefore, taking these concerns into account, all grievances concerning non-fulfillment of contracts, levels of compensation, or seizure of assets without compensation should be addressed to the district authorities either in writing or in person. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 26 In the local cultures it takes people time to decide that they are aggrieved and want to complain. Therefore, the grievance procedures will give people up to the end of the next full agricultural season after surrendering their assets to set forth their case. All attempts would be made to settle grievances. It is anticipated that the PRA process in land acquisition would avoid, or at least minimize complaints arising from the loss of land and resources as a result of implementing any subproject. However, should any complaint still arise, it addressed as follows: • The Community or Farmer Group Subproject Committee would discuss the matter as the case may be. • The outcome would be reported to the Village Government for records, if it is resolved or for further action if it were not resolved at the Subproject Committee level. If the Village Council cannot settle the complaint, a special Village Assembly should be convened to make a final decision on the fate of the subproject. Individual and household compensation will be made in cash, in kind, and/or through assistance. The type of compensation will be an individual choice although efforts will be made to encourage in kind compensation if the loss amounts to more than 20% of the total loss of subsistence assets. Depending on the nature and significance of grievances; PADEP's redressing mechanisms will incorporate interrelated approaches, which are based on the following two different legal institutional structures: - (a) central/local government legal- institutional structures: i.e. fully utilizing existing laid down legal institutional mechanisms e.g. the following: - • Local government acts and organizational structure • District council organizational structures i.e. including their laid down committees • Ward/ Village council organizational structures i.e. again including their laid down committees (b) PADEP institutional structure as stipulated Chapter 3 of the project Operational Manual: namely the following: - Community- level: village as a whole or farmer group levels which will implement PADEP subprojects through Subproject Committees (SC) duly elected by village Community Assemblies and Farmer Group Assembles. Aggrieved parties can air grievances either through central/ local government organs i.e. through village on to wards, divisions, districts and up to central government organic or strictly through PADEP’s institutional structure i.e. starting through farmers groups on to village/ community level, and their forward to District Project Officer, District Facilitation Team, District Executive Director, National Technical Steering Committee, ever as far as National Project Steering Committee. K. A DESCRIPTION OF MECHANISMS FOR CONSULTATIONS WITH, AND PARTICIPATION OF, DISPLACED PERSONS IN PLANNING, IMPLEMENTATION AND MONITORING. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 27 Public consultation and participation are essential because they afford potential displaced persons the opportunity to contribute to both the design and implementation of the sub projects. This fits perfectly with the demand driven nature of the PADEP project. The sub projects would be initiated, planned, designed, implemented and operated (i.e. demand driven) by communities and/or farmer groups who by their very nature are members of the rural community and therefore, are an integral part of and play a crucial role in the community that may be effected. Furthermore, it is the local communities who are to claim ownership of this project for it to be successful and their wealth of knowledge of local conditions are invaluable assets to the project. In recognition of this, particular attention would be paid to public consultation with potentially affected individuals/households when resettlement concerns are involved. Public consultation has taken place at the identification of the sub projects during the PRA process and EA. The participation strategy would evolve around the provision of a full opportunity for involvement. This process would not be an isolated one because of the very nature of the project, which through its implementation and design ensures continuous public participation and involvement at the local level. Therefore, as a matter of strategy, public consultation would be an on-going activity taking place through out the entire project cycle. For example, public consultation would also occur during the preparation of the; (i) the socio- economic study, (ii) the resettlement plan and (ii) the environmental assessment and (iv) during the drafting and reading of the compensation contract. Public participation and consultation would take place through meetings, radio programmes, request for written proposals/comments, filling in of questionnaires/forms, public readings and explanations of sub project ideas and requirements, making public documents available at the regional, district, canton and village levels at suitable locations like the official residences/offices of local leaders/elders. These measures would take into account the low literacy levels prevalent in these communities by allowing enough time for responses and feedback. Notwithstanding, the best guarantor for public interest is the communities and farmer groups who are responsible members of their local communities and are very likely to be knowledgeable about the likely impact of the project. Monitoring of this process would be through the overall monitoring and evaluation mechanism of the entire PADEP project. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 28 L. ARRANGEMENTS FOR MONITORING BY THE IMPLEMENTING AGENCY AND, IF REQUIRED, BY INDEPENDENT MONITORS. The arrangements for monitoring would fit the overall monitoring plan of the entire PADEP project which would be through the PCU and decentralized to the DMT and DFT which is expected to have monitoring and evaluation guides established and functional by end of year one in the project cycle. The objective will be to make a final evaluation in order to determine if the people who were affected by the project have been affected in such a way that they are now living at a higher standard than before, living at the same standard as before, or they are they are actually poorer than before. For sub-projects triggering the resettlement safeguard, indicators tracking the households affected by the acquisition of land will be assessed in comparison to those of households not affected. The resettlement plans will indicate parameters to be monitored, institute monitoring milestones and provide resources necessary to carry out the monitoring activities. In order to access whether these goals are met, the resettlement plans will indicate parameters to be monitored, institute monitoring milestones and provide resources necessary to carry out the monitoring activities. For example the following parameters and verifiable indicators will be used to measure the resettlement plans performance; • Questionnaire data will be entered into a database for comparative analysis at the DMT and PCU levels, • Each individual will have a compensation dossier recording his or her initial situation, all subsequent sub project use of assets/improvements, and compensation agreed upon and received. • The project will maintain a complete database on every individual impacted by the project land use requirements including relocation/resettlement, land impacts or damages • Percentage of individuals selecting cash or a combination of cash and in-kind compensation, • Proposed use of payments • The number of contention cases out of the total cases • The number of grievances and time and quality of resolution • Ability of individuals and families to re-establish land and crops or other alternative incomes • Agricultural productivity of new lands • Number of impacted locals in the workforce • Seasonal or inter annual fluctuation on key foodstuffs • General relations in the local communities WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 29 The following indicators will be used to monitor and evaluate the implementation of resettlements plans; VERIFIABLE INDICATORS Monitoring Evaluation Outstanding compensation or resettlement contracts not completed before next agricultural season. Outstanding individual compensation or resettlement contracts. Communities unable to set village-level compensation after two years. Outstanding village compensation contracts. Grievances recognized as legitimate out of all complaints lodged. All legitimate grievances rectified Pre-sub project production and income (year before land used) versus present production and income of resettlers, off- farm-income trainees, and users of improved agricultural techniques. Affected individuals and/or households compensated or resettled in first year that have maintained their previous standard of living at final evaluation. Pre- subproject production versus present production (crop for crop, land/land for land/land). Equal or improved production per household. Financial records will be maintained by the DMT/PCU to enable calculation of the final cost of resettlement per individual or household. Each individual receiving compensation will have a dossier containing; • Individual bio-data information, • Number of people s/he claims as household dependents • Amount of land available to the individual or household when the dossier is opened. Additional information will be acquired for individuals eligible for resettlement/compensation: • Level of income and of production • Inventory of material assets and improvements in land, and • Debts. Each time land is used by the project; the dossier will be updated to determine if the individual or household is being affected to the point of economic non-viability and eligibility for compensation/resettlement or its alternatives. These dossiers will provide the foundation for monitoring and evaluation, as well as documentation of compensation agreed to, received, and signed for. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 30 It is normal that some compensation procedures and rates may require revision at some time during the project cycle. PCU and DMT will implement changes through the Change Management Process in the Monitoring and Evaluation manuals of the project, which will require feed back from: • Indicators monitored by the DMT to determine whether goals are being met, and a grievance procedure for the local community to express dissatisfaction about implementation of compensation and resettlement."},"rejected":{"kind":"string","value":"false"}}},{"rowIdx":199,"cells":{"data":{"kind":"string","value":"# Extracted Content TRAINING GUIDE FOR CLIMATE SMART AGRICULTURE PRACTICES AND TECHNOLOGY PRACTITIONERS UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES TRAINING GUIDE FOR CLIMATE SMART AGRICULTURE PRACTICES AND TECHNOLOGY PRACTITIONERS UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES ii TABLE OF CONTENTS TABLE OF CONTENTS .................................................................................................................. ii ACRONYMS .................................................................................................................................. iii INTRODUCTION .......................................................................................................................... v CHAPTER ONE ............................................................................................................................. 1 1. TOPIC 1: CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE .................................................. 1 CHAPTER TWO ............................................................................................................................. 3 2. TOPIC 2: CLIMATE SMART AGRICULTURE ............................................................................................. 3 2.1 PERIOD 1: Concept of Climate Smart Agriculture ........................................................................ 3 2.2 PERIOD 2: Soil and Water Conservation Practices and Technologies...................................... 5 2.3 PERIOD 3: Conservation agriculture (CA) Practices and Technologies.................................... 6 2.4 PERIOD 4: Rain Water Harvesting and Irrigation Practices ........................................................ 7 2.5 PERIOD 5: Soil Fertility Management Practices ............................................................................. 8 2.6 PERIOD 6: Crop Management Practices and Technologies ....................................................... 9 2.7 PERIOD 7: Agroforestry Practices and Technologies ................................................................. 11 2.8 PERIOD 8: Adaptation Practices and Technologies in Livestock Keeping ............................. 12 2.9 PERIOD 9: Manure Management Practices .................................................................................. 14 2.10 Period 10: Climate Smart Agriculture in Fishing and Aquaculture ........................................ 15 2.11 PERIOD 11: Upscaling of Climate Smart Agriculture ................................................................. 17 CHAPTER THREE ......................................................................................................................... 19 3. TOPIC 3: CSA STAKEHOLDERS INVOLVEMENT ................................................................................... 19 CHAPTER FOUR .......................................................................................................................... 21 4. TOPIC 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS ............................................... 21 CHAPTER FIVE ............................................................................................................................ 23 5.TOPIC 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS ........................................... 23 iii ACRONYMS CSA Climate Smart Agriculture SUA Sokoine University of Agriculture FAO Food and Agriculture Organization of the United Nations MIN Minutes UNFCCC United Nations Framework Convention for Climate Change M&E Monitoring and Evaluation SACCOs Savings and Credit Cooperatives iv AKNOWLEDGEMENT This Training Guide has been prepared by a technical team from various Departments, Units and Agencies within the Ministry of Agriculture Livestock and Fisheries with a wealth of valuable information sourced from different stakeholders around the country including Sokoine University of Agriculture and World Vision. The Ministry is highly indebted to The Food and Agriculture Organization of the United Nations and DFID funded Vuna Climate Smart Agriculture Programme for the technical and financial support that enabled the preparation of this training Guide. Shakwaanande Natai Head - Environment Management Unit Ministry of Agriculture Livestock and Fisheries v INTRODUCTION Climate-Smart Agriculture is “agriculture that sustainably increases productivity, resilience (adaptation), reduces or removes Greenhouse Gases (GHGs) (mitigation) where possible, and enhances achievement of national food security and development goals” (FAO, 2010). However, in Tanzanian context, the adapted definition of Climate-Smart Agriculture is “agriculture that sustainably increases productivity and income, increases the ability to adapt and build resilience to climate change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” (National Task Force Planning Workshop Report, 2016). CSA aims to achieve food security and broader development goals under a changing climate and increasing food availability using different practices and technologies. CSA practices and technologies on crop, livestock and fisheries aim at addressing tradeoffs and synergies between the three pillars; productivity, adaptation, and mitigation. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies also embrace priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. In understanding the importance of CSA in crops, livestock and fisheries production practices and technologies were identified and mapped according to Agro-Climatic Zones of Tanzania. These Practices and technologies serve as tools for deciding options within which the three CSA pillars can be achieved. It is because of the importance of CSA in the Tanzanian context that this Training Guide has been developed, in order to guide trainers on how to equip relevant stakeholders on the uptake of CSA practices and technologies within the agricultural sector. This guide is divided into five chapters whereby chapter 1 aims at helping users to understand some of the impacts of climate change and possible solutions for addressing climate related risks with regard to agriculture. It also provides an understanding of how changes in climate can affect agriculture and subsequently identifies best practices that will help farmers to adapt in their respective agro-climatic zones. Chapter 2 introduces in detail the concept of CSA practices and technologies in crop, livestock and fisheries production. Chapter 3 provides guidance on identification, roles and engagement mechanisms of different stakeholders on implementation of CSA related activities. Chapter 4 helps elaborate on issues related to mainstreaming of CSA into agricultural plans, programmes and budgets. Lastly, chapter 5 give guidance on how to carry out monitoring and evaluation of CSA related activities and interventions. It is important to note that, the effective use of this guide requires to go hand in hand with the use of CSA manual, Guideline document and other relevant materials as may be recommended in this training guide. The supplementary documents have detailed explanations and elaborations to help the trainer on preparation and development of the lessons. In this way, it is expected for the trainer to achieve intended learning objectives to the trainees. 1 1. TOPIC 1: CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE VENUE: Classroom DURATION: 60 Min SUB-TOPICS • Definition of terms • The Concept of Climate change • The impacts of climate change on agriculture • The impacts of agriculture on climate change • Climate change risks and vulnerabilities in agriculture • Adaptation and mitigation of climate change MAIN OBJECTIVE The main objective of the lesson is to enable participants to understand what climate change is, as well as its impact in agriculture so that they can be able to facilitate targeted group on appropriate measures for effective adaptation and mitigation of climate change in their respective agro-ecological zones. SPECIFIC OBJECTIVES It is expected that at the end of the lesson participants will be able to:- • Define key terms commonly used in explaining the impact of Climate Change in agriculture (Climate change, Risks, Vulnerability, Adaptation, and Mitigation) • Understand the concept of Climate Change • List at least five impacts of Climate Change on agriculture and three impacts of agriculture on climate change • Explain potential Climate Change risks and vulnerabilities in agriculture • Explain at least three potential adaptation actions and two mitigation actions LESSON DEVELOPMENT Start the lesson by giving a general introduction followed by explaining the main objective as well as specific objectives of the lesson. Ask participants few questions related to the subject matter in order to know their level of understanding of the subject, while listing all their answers on the writing board. Write proper answers on the writing board so that participants can compare. Continue with the lesson by defining five key terms commonly used when explaining the impact of Climate Change in agriculture. Explain clearly the concept of Climate Change by giving examples. Divide participants into groups depending on their number and ask each group to list five impacts of Climate CHAPTER ONE 2 Change on agriculture and three impacts of agriculture on Climate Change for 15 minutes. Ask each group to present their work while listing the results on the writing board. Thereafter, explain the impacts of climate change on agriculture and the impacts of agriculture on Climate Change and then conclude the lesson by summarizing and ask participant if they have any questions. TEACHING METHODS Lecturing, Plenary discussions, Question & Answers and group work/discussion TEACHING AIDS Video for Climate Smart Agriculture, internet access to play the video in real time or embed it in a PowerPoint ahead of time, writing board, marker pen/chalks, Posters, Flip Chart 3 2. TOPIC 2: CLIMATE SMART AGRICULTURE 2.1 PERIOD 1: Concept of Climate Smart Agriculture SUB TOPICS • Introduction to Climate Smart Agriculture • CSA Pillars • Characteristics of CSA Practice and Technologies VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand the concept of Climate Smart Agriculture. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain Climate Smart Agriculture • Identify Pillars of Climate Smart Agriculture • Characterize CSA Practices and Technologies LESSON DEVELOPMENT Start by probing the understanding of Climate Smart Agriculture (CSA) by asking participants the question “who can tell the meaning of CSA?” Write down answers from participants on a flip chart. Thereafter, give participants the definition of CSA as defined by FAO and make them aware of keywords (pillars of CSA) which are Productivity, Adaptation and Mitigation. Start with global definition followed by Tanzania definition which has emphasis on increased income, food and nutrition security, achievement of mitigation co-benefits through adaptation, but all should be in line with national development priorities. Explain in details, the need to practice CSA in light of climate change adaptation while achieving mitigation co-benefits because in Tanzania, adaptation is the key priority followed by mitigation. Examples should be given such as Tanzania and other developing countries are more vulnerable to the impact of Climate Change as compared to developed countries with ability to adapt and at the same time to mitigate the impact of climate change can be given to make the lesson more understood. Explain the three pillars of CSA (Productivity, Adaptation and Mitigation). Elaborate each pillar to the participants by explaining their actual meaning and what they intend to achieve through CSA. Give examples on how each pillar can be achieved through CSA to enhance understanding. Use illustrations or short relevant videos where possible. Then ask participants to form groups and allow them to discuss CHAPTER TWO 4 for 10 minutes if the aforementioned practices in their local area adhere to the three pillars of CSA and how. Allow groups to present their findings in plenary and let the groups ask two or three questions after each presentation. After all groups have presented, give overall feedback by emphasizing that, sometimes it’s hard to have all three pillars attained in one practice. Ask participants to give examples of CSA practices and technologies based on the definitions of CSA and the three CSA pillars. Note down the examples on the flip chart or writing board, and then give definition of CSA practices and technologies. Expand the definitions given by sharing examples of CSA practices and technologies readily available in the local areas, or by emphasizing on the ones already mentioned and move on to mention others which are not practiced in the geographical area but relevant. Lastly, discuss with the participants on the key characteristics of CSA. End the training session by asking questions to the participants about their understanding of CSA, CSA pillars, CSA practices and technologies. Give them training manuals/notes for further reading and referencing. TEACHING METHODS Plenary/group/group discussion questions and answers and lecture TEACHING AIDS Projector, Posters, Video on CSA, stationary (Flip chart, Exercise books, pens, marker pen), loud speaker 5 2.2 PERIOD 2: Soil and Water Conservation Practices and Technologies SUB TOPICS: • Meaning of soil and water conservation practices and technologies • Types of soil and water conservation practices and technologies • Suitable Soil and water conservation Practices and technologies in different agro-climatic zones VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe soil and water conservation practices and technologies that are used in the country, and in the different agro-climatic zones. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Comprehensively define the meaning of soil and water conservation practices and technologies • Mention different types of soil and water conservation practices and technologies • Describe the types of soil and water conservation practices and technologies and its suitability in different agro-climatic zones and for their localities. LESSON DEVELOPMENT Start by asking the participants what they know about the meaning and importance of soil and water conservation. Write on flip chart the answers and allow five minutes for plenary discussion. Thereafter write down on flip chart or project the meaning and importance of soil and water conservation. Ask participants to write on the card different types of soil and water conservation practices they know (each participant should write only one), place the card on board by grouping cards with the same answers together. Thereafter finish by projecting different types of soil and water conservation practices. Provide group work to the participants to write down on flip charts, the types of soil and water conservation practices and their suitability in different agro-climatic zones. Afterwards, groups should present their work and discuss. Thereafter project the types of soil and water conservation practices in different agro-climatic zones. Finish the lesson, by asking participants (sampling at two) questions on soil and water conservation practices and technologies. TEACHING METHODS Groups and Plenary discussion, Questions & Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Manila cards, Projector and Computer/laptop. 6 2.3 PERIOD 3: Conservation agriculture (CA) Practices and Technologies SUB TOPICS: • Meaning of Conservation agriculture • Types of conservation agriculture practices and technologies • Suitable conservation agriculture practices in different agro-climatic zones VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training participants will be able to understand conservation agriculture practices and technologies, their uses and suitability in different agro-climatic zones. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain the meaning of conservation agriculture • Mention different types of conservation agriculture practiced in the country • Identify different types of conservation agriculture practices suitable for their localities. LESSON DEVELOPMENT Introduce the subject by projecting a picture of CA practice/technology and allow five minutes for discussion. Thereafter, project on the board the meaning of conservation agriculture and explain the projected picture. Afterward, allow participants to discuss in groups and write on flip chart different types of conservation practices and their advantage to the environment. Then group representatives present their answers, and allow other group members to contribute and ask questions. Thereafter, write down on a flip chart or project different types of conservation agriculture and explain their importance. Then, provide manila cards to the participants to write conservation agriculture practices from their localities. Place the card on the board by grouping them based on similarities, this will help to know commonly used CA practices to allow the trainer to emphasize on the potential practices to be introduced or perfected in the area. At the end of the session, ask questions to the participants on conservation practices and technologies. TEACHING METHODS Brainstorming, Group discussion, questions & answers, Lecture. TEACHING AIDS Picture/Photo, Flip Chart, Maker Pen, Manila cards, Projector, Blackboard and Compute 7 2.4 PERIOD 4: Rain Water Harvesting and Irrigation Practices SUB TOPICS: • Meaning and Importance of rain water harvesting • Rain water harvesting technologies • Irrigation practices and technologies VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe the concept of rainwater harvesting and irrigation practices. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the rain water harvesting concept • Identify types of rain water harvesting techniques suitable in their localities • Explain CSA irrigation practices • Describe rain water harvesting and irrigation practices LESSON DEVELOPMENT Start by asking the participants what they know about rainwater harvesting and irrigation practices. Write on flip chart the answers and allow 10 minutes for plenary discussion. Thereafter, write down on flip chart or project the answers from the participants. Ask participants to write on the card different types of rain water harvesting techniques and irrigation practices suitable in their localities then place the card on board by grouping cards with the same answers together. Thereafter, finish by projecting on the board different types of rain water harvesting techniques and irrigation practices suitable in their localities. At the end of the lesson, finish by asking participants (sampling at four) questions on rain water harvesting and irrigation practices. TEACHING METHODS Group and Plenary discussion, Questions & Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Manila cards, Projector and Computer/laptop, chart/drawings showing recommended CSA practices in different Agro-climatic zones of Tanzania 8 2.5 PERIOD 5: Soil Fertility Management Practices SUB TOPICS: • Meaning and importance of soil fertility management practices • Manure application • Efficient use of fertilizer (micro dozing) • Integrated soil fertility management VENUE: Classroom DURATION: Classroom 75 Min MAIN OBJECTIVE At the end of the training session, participants will be able to describe soil management practices which are relevant on addressing impact of climate change in agriculture. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of soil fertility management practices • Define the efficient use of fertilizers • Identify soil management practices in line with CSA pillars • Explain soil fertility in line with CSA pillars LESSON DEVELOPMENT Start by asking the participants what they know about the meaning and importance of soil fertility management practices. Write on flip chart the answers and allow five minutes for plenary discussion. Thereafter, write down on flip chart or project on the board the meaning and importance of soil fertility management practices. Provide group work to the participants to write down on flip chart types of soil fertility management practices. Afterward, the groups should present their work and discuss in plenary. Later on, finish by projecting the types of soil fertility management practices and its importance on CSA. Ask question and discuss in plenary the soil fertility and its contribution on CSA pillars. Write the answers on flip chart and finish by providing the notes. TEACHING METHODS Group and Plenary discussion, Questions and Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Projector and Computer/laptop, manila sheets 9 2.6 PERIOD 6: Crop Management Practices and Technologies SUB TOPICS: • Meaning of crop management • Management practices and technologies in crops • Adaptable crops and crop varieties • Integrated Pest and Diseases Management (IPM) • Timely/early planting/sowing VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand crop management practices and technologies in relation to CSA pillars SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of crop management • Explain different crop management practices and technologies • Identify desirable adapted crop and crop varieties • Explain the benefit of using Integrated Pest Management (IPM) • Explain the importance of timely/early planting/sowing practices LESSON DEVELOPMENT Start the lesson by asking the participants what they know about crop management and their importance. Write answers on flip chart and allow five minutes for plenary discussion. Thereafter, write down on flip chart or project the meaning and importance of crop management. Continue the session by asking the participants to mention different crop management practices and technologies available in their locality and continue plenary discussion. Then, let participants mention characteristics of adaptable crop and crop varieties. Write their answers on the board and allow plenary discuss, then continue by displaying different types of adaptable crops and crop varieties. Afterward, stress the link between different crop management practices and technologies, improved seeds and crop productivity in relation to Climate Change adaptation strategies. Ask participants the methods used to manage pest in their areas. Note down their answers on the board. Emphasize on the ones which are related to Integrated Pest Management and concur with CSA pillars. Continue by defining the term Integrated Pest Management as a broad-based approach that integrates practices for economic control of pests with minimal impact to human health and environment. Stress the point by saying that IPM aims to suppress pest populations below the Economic Injury Level and promotes a safer and more sustainable management and control of pests in agriculture. Tell participants that IPM lies at the centre of insect, disease, and weed control. Later, explain the combination of farming strategies and biological control agents as necessary methods to pesticide and herbicide use that can help farmers to address pest problems. 10 Explain to participants that IPM can provide a healthy and balanced ecosystem in which the vulnerability of plants to pests and diseases is decreased; hence it contributes to climate change adaptation. Give emphasis by telling the participants that it is important to diversify farming system by using IPM as it builds farmers’ resilience to potential risks posed by climate change such as proliferation of pests. Make it clear that it is important to understand pest behavior indifferent agro ecological zones because it helps on adopting and developing new IPM technologies to respond to threats resulting from Climate Change. Ask participants about the importance of timely land preparation and early planting/sowing advantages and disadvantages? Write down their answers on the board and later on give them the right answer, tell them that early land preparation and planting is the practice that ensures optimal use of the short rains and increases efficient use of organic nutrient accumulated in the soil dry season (nitrogen flush). Make it clear to the participants that the use of this practice can be more effective when supplemented with timely of weather information provided by relevant authorities. Conclude the lesson by questions and answers session and by distributing to the participants handouts for further reading. TEACHING METHODS Lecturing, question and answers, brain storming TEACHING AIDS Flip chart, marker pens, pictures 11 2.7 PERIOD 7: Agroforestry Practices and Technologies SUB TOPICS: • Meaning and importance of agroforestry • Common agroforestry practices and technologies VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe agroforestry practices and technologies in their respective agro-climatic zone. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain the meaning and importance of agroforestry • Describe the common agroforestry practices and technologies in their respective agro-climatic zone. LESSON DEVELOPMENT Start by asking participants what they know about the meaning and importance of agroforestry. Write on flip chart answers and allow 10 minutes for plenary discussion. Thereafter write down on flip chart or project the meaning and importance of agroforestry. Provide group work to the participants to write down on flip chart common agroforestry practices and Technologies in their respective agro-climatic zone. Afterward, the groups should present their work and discuss. Conclude the training session by projecting common agroforestry practices and technologies. TEACHING METHODS Group and plenary discussion, Questions and Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Projector, Computer/laptop, note book, real plant materials. 12 2.8 PERIOD 8: Adaptation Practices and Technologies in Livestock Keeping SUB TOPICS: • Climate change and livestock keeping • Improved Livestock Breeds • Improved feeds and feeding • Pasture and grazing land management • Alternative source of water for livestock VENUE: Classroom DURATION: 120 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand adaptation practices and technologies in livestock keeping in relation to climate change. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Understand the relationship between climate change and livestock keeping • Identify desirable livestock breeds adaptable to a agro-ecological zone • Outline methods used to improve livestock breeds • Identify available feeds and methods of improving them for different livestock breeds available in a given area • Identify different methods of conserve and manage forage/pasture • Identify alternative water sources for livestock LESSON DEVELOPMENT Start the lesson by asking participants to mention the impacts of climate change in livestock production. Write answers on the board so that are clearly seen and make the necessary corrections on plenary discussion. Afterward ask participants if they think livestock keeping has any contribution to the impacts of Climate Change. Based on their responses, explain the relationship between Climate Change and livestock keeping. Emphasize on the effect of the release of methane from enteric fermentation of livestock keeping, manure management and land degradation. Ask few questions on the relationship between livestock keeping and Climate Change. Divide participants in small groups and ask them to differentiate between Local and exotic breeds, let them present their answers later on summaries the answers. Prepare slideshow of different breeds, select few and explain their adaptation capacity to climate change. A local based example of the breed would be better if present. Ask participants the way they do conserve forage in their areas. Note down the answers on the board. Emphasize the desirable forage conservation methods as described in the CSA guideline or CSA Manual. Continue the lesson by showing pictures and explaining few pastures and grazing land management practices which are regarded as climate smart as elaborated in the CSA Guideline and summarized in the CSA manual. Ask participants if there are any alternative sources of water for livestock production in their area. Write the answers on the board. Show them the common alternative sources of water for livestock production. Emphasis should be given on how to make them available for use during the periods of prolonged dry spell as projected by climate change models. 13 TEACHING METHODS Group discussion, Lecturing, Presentation, demonstration TEACHING AIDS Flip chart, laptop, projector, pictures, illustration and demonstration area, real materials 14 2.9 PERIOD 9: Manure Management Practices SUB TOPICS: • Meaning and importance of manure • Source of manure • Manure management VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand different forms of utilizing manure in relation to climate change. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of manure • Outline different ways of proper manure utilization LESSON DEVELOPMENT Ask participants what they understand about manure and different sources of manure in their area. Write the answers on the board and make the necessary corrections on plenary discussion. Afterward ask participants how do they handle and dispose manure from their locality. Note down the answers on the board and stress the desirable ways of disposing and handling manure especially those environmentally/Climate Change friendly technologies or practices. Ask participants if there is any person with environmentally/climate change friendly technologies. Emphasis on the mentioned technologies in relation to the three pillars of CSA. Finalize by associating environmentally/Climate Change friendly technologies and soil management practices (nutrient losses). Stress that all these are essential for building resilience and mitigating to Climate Change impacts. TEACHING METHODS Group discussion, Lecturing, Presentation TEACHING AIDS Flip chart, laptop, projector, pictures, illustration and demonstration area, real materials 15 2.10 Period 10: Climate Smart Agriculture in Fishing and Aquaculture SUB TOPICS: • Impact of Climate Change on Fishing and Aquaculture enterprises • Climate Smart Fishing and Aquaculture practices • Sustainable Fishing • Seaweed Farming VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand the Climate-Smart agriculture practices in Fishing and Aquaculture enterprises. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain impacts of climate change on fishing and aquaculture enterprise • Identify Climate-Smart Fishing and Aquaculture practices • Explain sustainable fishing in the context of climate smart fishing • Describe seaweed farming in the context of mitigating Climate Change impact LESSON DEVELOPMENT The trainer start by probing participants’ understanding on the meaning of aquaculture by asking a question such as “what comes into minds when someone says Aquaculture?” After a little discussion on its meaning, then the trainer summarizes the discussion by giving the actual meaning of Aquaculture. Thereafter, the trainer ask participants to think of any ways by which weather variability or climate change can impact fishing enterprises and aquaculture. Thereafter, the trainer writes answers obtained on the flip chart or writing board. After that the trainer explains each of the mentioned response with emphasize on the impact of temperature on oxygen availability, biophysical characteristics of the aquatic organisms, water pollution through formation of algae bloom and increase of solute concentration triggered by evaporation. On giving explanation the trainer may use video or demonstrate by drawings on the writing boards. Afterward, the trainer introduces the concept of sustainable fishing by giving few examples of sustainable fishing practices aided by pictures. In the end the trainer give an explanation on how sustainable fishing is related to Climate-Smart agriculture by associating with CSA pillar of increase of agricultural productivity. The concept of seaweed farming is then introduced as another CSA practice mostly practiced along the sea coast. The trainer explain seaweed farming as a practice which has bigger contribution on sequestrating atmospheric carbon compared to similar area under terrestrial agricultural activity. This explanation should be related to the third pillar of CSA which is target on mitigation of GHG by reducing GHG in the atmosphere. 16 Then the trainer concludes the lesson by encouraging participants to visit any nearby place where aquaculture or seaweed farming is practiced. The trainer should also provide manual for further reading at the end of the session. TEACHING METHODS Plenary discussion, questions and answers and lecture TEACHING AIDS Flip Chart, Maker Pen, Projector and Computer and pictures 17 2.11 PERIOD 11: Upscaling of Climate Smart Agriculture SUB TOPICS: • CSA practices and technologies • Challenges on upscaling practices and technologies • Ways for upscaling CSA practices and technologies VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand on how to upscale Climate- Smart Agriculture practices and technologies in their localities. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Define CSA practices and technologies • Understand challenges on upscaling CSA practices and technologies • Explain ways for upscaling CSA practices and technologies LESSON DEVELOPMENT At the beginning present to participants the main concept of CSA practices and technologies in relation to three CSA pillars. Then ask the participants a question such as“ is there a need to upscale CSA in their localities?” Write down answers obtained from the participants on the flip chart. Afterward, arrange participants in groups of livestock keepers, crop farmers, fisheries and let them discuss common CSA practices applicable to them. While still in their groups ask them to pick one practice and describe how they can be able to upscale in other areas and within their communities. Let this discussion last for about 20 minutes. Then, allow groups to present their findings in plenary and take two or three question after each presentation. After all the group have presented give overall feedback and elaborate more on methods they could further consider for upscaling of the CSA practices. Then discuss with the participants on common challenges associated with the upscaling of CSA. Let participants share their experience and on the same time the trainer will have to be presenting possible solution on overcoming the challenges. Based on the discussion and solutions presented, list down various ways which can be considered for upscaling of CSA practices. In the end, ask general questions about CSA upscaling and their relevance in the respective area and emphasize on the possible solutions to overcome CSA upscaling challenges in the respective area. Then give them the training manual/notes for further reading and referencing. TEACHING METHODS Plenary discussion questions and lecture TEACHING AIDS Projector, standby generator, stationaries (Flip chart, Exercise books, pens, marker pen) 19 3. TOPIC 3: CSA STAKEHOLDERS INVOLVEMENT SUB TOPICS: • Identification of stakeholders • Roles of different stakeholders on implementation and upscaling of CSA • Stakeholders engagement mechanisms • Approaches for CSA integration VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of training session participants will be able to identify CSA stakeholders and their roles in the implementation and scaling up of CSA practices and technologies SPECIFIC OBJECTIVES At the end of the session, Participant will be able to; • Identify CSA Stakeholders • Explain roles of different CSA stakeholders • Describe different mechanisms for stakeholder engagement • Identify different approaches for CSA implementation LESSON DEVELOPMENT Start session by asking participants if they can mention stakeholders that they think are important in implementation of CSA. After that, mention other stakeholders that were not mentioned and describe why they are important. Thereafter, group participants in groups which represent major categories of stakeholders such as policy makers, planners, farmers, private sectors, NGOs, youth, women and men and let them discuss their roles on any CSA intervention of their choice. Afterward, ask the groups to present their discussed roles, allow plenary discussion for twenty minutes after presentation from each group. Then ask participants if there is necessity for the different stakeholder to work together. If the answer is yes, ask them to mention mechanisms which can allow them to work together. Ask them to discuss those mechanisms briefly on how they are effective on engaging different stakeholders on implementing CSA intervention. Afterward, present and describe other mechanisms which were not mentioned and how they can be used adopted to help bring and engage CSA stakeholders on implanting CSA intervention. Then introduce different approaches which should be considered on implementing different mechanisms for engaging stakeholder such as gender inclusive and participatory approach. Emphasis should be given on issues such as gender, inclusion of the three CSA pillars and evolvement of multi- CHAPTER THREE 20 stakeholders. In the end, present summary on key stakeholder to be considered on implementing CSA intervention and their roles, give summary of different mechanisms of stakeholder engagement; briefly give emphasis on approaches to be considered and their application in the respective area. TEACHING METHODS; Lecturing, group discussion, questions and answers, TEACHING AIDS; Projecting board, projector, laptop, notebooks, pens, flip chat, marker pens 21 4. TOPIC 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS SUB TOPICS: • Awareness creation and sensitization of CSA • CSA related activities and their relevant justifications • Planning of CSA activities with gender consideration • Budgeting for CSA related activities VENUE: Classroom DURATION: 120 Min MAIN OBJECTIVE To teach participants on mainstreaming of CSA in agricultural related plans in order to increase agriculture resilience to the impact of climate change, increase agricultural productivity, sustainability and farmers’ income. SPECIFIC OBJECTIVES At the end of the training session participants will be able to: • Define CSA awareness creations • Create awareness to stakeholders • Identify at least three target groups for CSA awareness creation • Mainstream CSA activities into agricultural plans Explain CSA related activities in a given area • Plan CSA activities with gender considerations • Budget for CSA activities LESSON DEVELOPMENT Start the lesson by asking participants to define the word awareness by associating it to CSA. Take a note of the answers and write them on the board. Later ask participants what they understand about awareness creation and sensitization. Assist participants to give the right definitions of the words awareness and awareness creation in relation to Climate Smart Agriculture (CSA). Give clarifications on the meaning of Climate Change and how it affects agriculture and livelihood. Show participants the impacts of Climate Change using power point slides or pictures/photos. Then ask participants to explain at least five methods of creating awareness. Take note of the answers. Afterward, give more elaboration on the method of awareness creation and give examples on their failure or success. CHAPTER FOUR 22 Ask participants to give example of few target groups which can be considered for awareness creation purpose. Note down their responses and then tell the participants that the target groups for CSA awareness creation include government authorities, central and local administrative authorities, religious, traditional leaders, opinion leaders, NGOs, civil society, donors and media. On mentioning the target group, give more elaboration and examples in relation to awareness creation methods. Emphasize the points by saying that a successful awareness raising strategy takes into account the type of target group, type of message to be reached out for each particular target group and selection of appropriate awareness creation method for communicating the messages. Now divide participants into four groups and let them discuss how they may create CSA awareness activities to the target group of their choice. Go around the groups to see whether they have understood the assignment and assist them accordingly. Then, allow a representative member from each group to a make brief presentation and allow others to contribute to the presentation after its done. Ask participants to mention main sources of finance to agricultural investments in Tanzania. Write down their responses and later give them the more sources those from the farmers, herders, fishers and foresters, development partners, central and local government as well as NGOs. Emphasize by saying that for successive public investment, it is better to consider potential stakeholders in a given locality and identify the most suitable activities when developing CSA strategies, investments and financing plans. Explain to participants’ things that have to be considered when budgeting for CSA related activities. Give elaborations by saying that large fixed capital investments with significant lifetimes are particularly vulnerable to being maladaptive if climate risks are not considered. Continue by telling participants that for successful investment they must screen agricultural investment plans for their degree of “climate smartness”. The screening methodology considers potential contribution of planned activities to the three pillars of CSA and other aspects of adaptation as well as mitigation. This suggests that Climate- Smart agricultural investments with mitigation co-benefits should be identified within the context of existing agricultural investment strategies developed for the purposes of agricultural growth. Start by pointing out that financing options specifically targeting CSA are still limited, necessitating for a strategic use and combination of funding sources in existence. Ask participants to mention sources of funds they thought could be used for CSA activities in their respective areas. Moderate and remind them to include internal and external sources. The internal sources are: Local Government Authorities (LGAs), budgets, National budgets and Agricultural Sector Development Programme (ASDP), while the external sources include United Nations Framework Convention for Climate Change (UNFCC), United Nations (UN) organizations, Multilateral Development Banks (MDBs); bilateral public financing channels; Compliance and voluntary carbon markets; and Private sector actors and philanthropy. Tell participants the roles played by each financing agencies on CSA activities and how they may get access to such funds. Conclude the session by asking different questions to participants and tell them what is expected to be done in the next training session. TEACHING METHODS Question and answers, brainstorming, group discussion, questions at the end of the period, TEACHING AIDS Flip charts, black/white board, marker pens, projector 23 5.TOPIC 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS SUB TOPICS: • The meaning of Monitoring and evaluation (M&E) • Identification of baseline indicators for CSA • Performance Indicators for CSA interventions • Monitoring tools and Record keeping • Creation of evidence for CSA practices performance VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: In the end of the lesson, participants will be able to know how to monitor and evaluate CSA interventions or related projects in their respective areas. SPECIFIC OBJECTIVES: At the end of the subject Participants will be able to: • Explain the meaning and importance of M&E • Describe and identify the baseline indicators • Describe and identify key performance indicators and their uses • Distinguish between baseline and key performance indicators • Identify different M&E tools • Explain importance of records keeping for evidence based creation • Describe how CSA evidence can be created LESSON DEVELOPMENT Start lesson by asking the participants if they know anything about Monitoring and evaluation. Thereafter, provide the proper definition of M&E so that there is common understanding among participants. Then, explain the importance of Monitoring and Evaluation for CSA interventions or related projects. Then, introduce the concept of baseline indicator, describe its characteristics and lead them to identify sources of the indicators. After that introduce the concept of key performance indicators, describe their characteristic and explain how they can be obtained. Then, ask the participants to briefly reflect on the main differences between the two types of indicators. After that, divide participants into groups and give them simple CSA intervention for them to develop baseline indicators and key performance indicator. Then let them discuss their outputs in the plenary. CHAPTER FIVE 24 Then continue by introducing participants on different tools for monitoring and evaluation. Explain the importance of these different tools including their usefulness in record keeping for monitoring and evaluation. Then give emphasis of record keeping for evidences creating with the purpose of sharing lessons learnt with others during project or activity implementation. Describe various ways by which participants can be able to document their M&E data and create evidence for sharing with other in an easy and customizable way. Finally, end the training session by providing the summary of the topics and emphasis on the importance of M&E, the two types of indicators, tools for M&E and their importance. TEACHING METHODS Group work, lecture, plenary discussions, questions and answers TEACHING AIDS Flip charts, writing board, marker pens, notebooks, laptop and projector Ministry of Agriculture Livestock and Fisheries P.O. 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# Extracted Content KARAGWE DISTRICT COUNCIL P.O. BOX 20, KARAGWE. REF.NO. KGR/HWK/T.29/…. 2nd July 2010 DASIP Project Coordinator, Nyanza Cooperative Union Ltd Building, 3rd Floor, P.O. Box 11185 MWANZA. Ref: IMPLEMENTATION PROGRESS REPORT FOR THE YEAR 2009-10 ANNUAL REPORT 2009-10 The above heading refers. Find herewith attached DASIP ANNUAL IMPLEMENTATION PROGRESSIVE REPORT 2009/2010. It shows briefly on what the project have supported in collaboration with other stakeholders in the District The report includes - General Information & Background. - Introduction. - Planned Activities - Physical performance - Financial status - Challenges faced - Lessons learnt - Recommendations - Future plans - Annexes. C.M. Kamuhabwa DISTIRICT EXECUTIVE DIRECTOR KARAGWE DISTRICT COUNCIL C.C. Regional Administrative Secretary, P.O. Box 299 BUKOBA LIST OF ABBREVIATION AfDB African Development Bank ASDS Agriculture sector Development Strategy DASIP District Agricultural Sector Investment Project DADP District Agricultural Development Plan DALDO District Agriculture and Livestock Development Officer DED District Executive Director DFT District Facilitation Team DMEO District Monitoring and Evaluation Officer DPLO District Planning Officer DPO District Project Officer DTC District Training Coordinator FFS Farmer Field School FP Farmers Practice FY Financial Year PFG Participatory farmer group PFSC Participatory farmer Supervision Committee O&OD Obstacles and Opportunity for Development WTF Ward training facilitators WFT Ward facilitation team TABLE OF CONTENTS 1.0 List of Abbreviations………………………………………………………………3 2.0 Table Of contents…………………………………………………………………4 3.0 General information and Background..…..……………………………………5 3.1 Introduction ………………………..……………………………………………5 4.0 Overview of planned interventions……………………………………………...6 4.1 Planned activities 2008/ 2009 ( carried Over )……………………………….6 4.2 Planned activities 2009/10..………………………………………………….6 5.0 Implementation status of planned interventions ..……………………………7 5.1 Physical perfomances..............................................................................7 5.2 Financial Status……………………………………………………………….9 6. Issues and Constraints………………………………………………………….10 6.1 Challenges faced…………………………………………………………….10 6.2 Lessons learnt……………………………………………..…………………10 6.3 Recommendations…………………………………………………………..10 6.4 Future plans…………………………………………………………………10 ANNEX 1A: PHYSICAL PROGRESS FOR THE BALANCE OF 2007/08 CARRIED FORWARD TO 2008/09……………………………………………..7-8 ANNEX 1B: PHYSICAL ANNUAL PROGRESS FOR THE YEAR 2009/10 ............ 8-9 ANNEX 2. FINANCIAL PROGRESS FOR THE YEAR 2009/2010……………9-10 ANNEX 3: SUMMARY AND NUMBER OF GROUPS ACTIVITIES DONE ..............12 1.0 General information and Background Karagwe District is characterized by mountains ranges, which are separated by swampy valley bottoms and wet lands. The altitude ranges between 1500-1800 meters above sea level while valley bottoms and wet lands are 1150 meters to 1450 meters above sea level. Most of the District has a tropical highland climate. The annual average temperature is 26 0C Rainfall distribution is bi-modal with peak rains from September to December and from March to May. This type of climate makes the District very potential for most of Agricultural crops. 2.0 INTRODUCTION The government of Tanzania through a loan from the African Development Bank is implementing the District Agriculture sector Investment Project (DASIP).The Project aims at increasing productivity and income of the rural households in the project area within a frame work of the Agriculture Sector Development Strategy (ASDS).The project is being implemented for a period of six years starting from January 2006. It covers a total of 30 villages in 20 wards. Project components are; o Farmers capacity Building. o Community planning and investment in Agriculture. o Support to Rural financial services and marketing. o Project coordination and management. Karagwe District Council in collaboration with other stakeholders is implementing Agricultural Sector Development Programme (ASDP) through its District Agricultural Development Plan (DADP). The Council is receiving grants from the Central Government and Other donors for the development of the Agriculture sector. DASIP being part of DADPs is receiving grants from AfDB to implement different activities including Community Planning &Investment projects, Farmers capacity building as well as Marketing and Micro financial services. This report gives overview of the district implementation status of both Community projects and groups activities for the year 2009/2010 from July to June respectively. 3.0 District Development Goal The district development goal is to improve the quality of the lives of the population by alleviating poverty through sustained economic growth, meeting basic human needs and rights and reinforcing peoples own development capabilities. The District strives for a balanced growth of several and productive sectors, integrating all development efforts both public and private. The DDP underlines that participation of all stakeholders is an essential element to achieve sustainable development with long term impact. 4.0 IMPLEMENTATION LOCATION Names of Wards and Villages REGION DISTRICT WARD VILLAGE Kyerere Kamuli Kitwe Businde Mabira Kibimba Iteera Rwabwere Rwabwere Kihanga Isingiro Katera Kibona KAGERA KARAGWE Igurwa Igurwa Murongo Masheshe Kayanga Kayanga Bweranyange Chamchuzi Kakuraijo Kibondo Kibondo Ihembe Ihembe ii Nyabiyonza Nyabiyonza Bukangara Nyakakika Nyakakika Kayungu Kihinda Kibingo Kibingo Kiruruma Nyakagoyagoye Lukale Nyaishozi Nyakayanja Bugene Bujuruga Ndama Nyabwegira Nyakahanga Omurusimbi Nyakasimbi Bujara Bugomora Nyamiyaga The Project has three major field practical components and one project management component as follows: 1. Farmers Capacity Building: 2. Community Planning and Investment in Agriculture 3. Support to Rural Micro-finance and Marketing 4. Project Co-ordination 5.0 District Development Objectives: During 2009/10 the district main objectives as been; A. Improve the Socio Economic status of the vulnerable people to HIV/AIDS and impoverished groups of people as the results of pandemic HIV/AIDS and STI’s in Karagwe District through increased knowledge communication and support. B. To increase quality and quantity of the production and marketing of agricultural and livestock products in order to achieve self-sufficiency in food, increase foreign exchange, increased rural incomes and protecting environment. C. Improved delivery of timely and quality of social services and good governance to the people of Karagwe. D. To improve infrastructure and services related to development of trade, industry and private sector. The DDP – 2009/10 development objectives have been reviewed to ensure they are in line with economic reforms and district development goal. In line with the planning guidelines rationalization of the DDP – 2009/10 is formulated to ensure greater efficiency and productivity in utilizing the available meager resources. The available resources for DDP – 2009/10 as been used to support development clusters which are made by interrelated sectors complementing each other in their development objectives. The district recognizes the need to involve the community and other development partners in planning and decision making if local development is to be successful and sustainable. The members of development clusters are multi- discipline team with members from government departments and private sector. Cluster planning teams have been responsible in providing technical support to VFCs, WFCs and district council Facilitation team. The district is already working closely and will continue to do so with other development actors in the district. The capacity of the district to plan and implement has been further enhanced by the government (local and Central), NGOs, CBOs, faith-based organizations, the private sector and concerned individuals (CBIs). Participation of all these development actors has increased the level of performance of the district in implementing development activities. The government mainly performs supervisory and supportive role and actual implementation is done by the community, NGOs, CBOs and private sector. 6.0 OVERVIEW OF PLANNED INTERVENTIONS Different activities have been planned to be implemented this year as shown in the list below starting with carried forward activities followed by current year projects. 6.1 Planned interventions for the balance of 2008/09 Planned interventions for the balance of 2008/09 carried forward to 2009/10 includes:- Community Planning and Investment in Agriculture • To construct 8 storage facilities at Omurusimbi, Kibondo, Kakuraijo, Nyabiyonza, Rwabwere, Iteera, Kibona, Katera. • To construct 6 water troughs at Chamchuzi and Bukangara • To construct 2 permanent cattle crushes at Businde and Ihembe II. • To rehabilitate 1 slaughter slab at Kayanga. • To rehabilitate 12 km of feeder roads and 3 culverts. • To construct 1 SACCOS building at Nyamiyaga. To support 60 participatory farmer groups on micro- project investments 6.2 Physical performances ( carried over projects ) Status of the carried forward projects is as shown by the Annex A attached here with the Report. All in all carried over projects have been implemented as intended. Most of the projects have been completed, remaining few are at final stages. The last year’s groups have continued with implementation of their projects. Attached here with is status of groups in action. 6.3 Planned activities – 2009/10 Different activities have been planned to be implemented this year 2009/10 as shown in the list below; i) To construct 7 storage facilities. ii) To add value of grains in 23 villages by using milling machines. iii) To add value of Banana produce through agro processing in one village. iv) To construct 7 culverts. v) To rehabilitate 24 km of feeder roads. vi) To increase production area by using power tillers in 4 villages vii) To increase productivity in irrigated areas by using irrigation pump in one village. viii) To construct one char co dam. ix) To improve breeding of indigenous cattle by using artificial insemination in one village. 6.4 Farmers capacity Building • To train 180 Participatory farmer groups. • To train Farmer facilitators. • To continue training PFG’s supervision committees. • To continue training Ward training facilitators. 7.0 IMPLEMENTATION STATUS OF PLANNED INTERVENTION 7.1 Physical performances Implementation of Community projects have been going as planned though there some planned projects which have been changed due community priority change, for example Community in Kyerere-cattle dip, Bukangara-Cattle water trough, Chamchuzi- Cattle trough, Nyamiyaga-Construction of SACCOS building and Nyakagoyagoye- Construction of cattle char co dam, changed to Godown rehabilitation. During implementation some projects achieved more than were planned for example we planned to rehabilitate 12 km of feeder roads instead we achieved 20.27km for the same allocation of funds. All 3 Culverts achieved as planned, All cattle crush were completed, 1 Slaughter slab is completed, 1 cattle dip is under construction, 10 Godowns is under construction and other 2 are at contract signing stage. The groups have continued with implementation of their projects. There are 180 participatory farmer groups in place with a total of 4138 members in which 2369 are males and 1769 are females. Farmers have shown interest in receiving new technologies but the adoption rate is still low, more mechanism on adoptability methods should be applied. Groups trained on crops adopted a bit at higher rate compared to groups trained on livestocks. To date the adoption stands at average of 30%. Groups growing banana and cereal crops have adopted at around 65%. Poultry and goat keepers are still receiving training we hope they will adopt in the near future after getting the first products. Table 1: A table showing adoption per crop Crop Total trained Adoption Male Female Total Male Female Total Banana 148 102 250 96 66 162 Coffee 155 106 261 101 69 170 Maize 190 120 310 124 78 202 Beans 52 35 87 34 51 85 Total 545 363 908 355 264 619 7.2 FINANCIAL STATUS Funds for planned community projects and groups activities have been disbursed to respective villages through their Bank accounts. Total of TAS 353,634,000 for community projects disbursed to respect village banks accounts and total of TAS 90,000,000 for groups transferred to respective group accounts. Also TAS 2,300,000 for facilitating formation of participatory farmer groups, Tshs 5,853,000 for WTF and Tshs 3,815,000 for FFs Training on agribusiness entrepreneurship, also 72,000,000 for PFG Mini grant and 208,000,000 received for Agriculture technologies. The financial status for the period under review is as indicated in the table format attached with the report. Annex B Beneficiaries of the project are the community at large in respective villages, participatory farmer groups and their grassroots institutions such as Savings and Credit Associations (SACAs) and Savings and Credit Co- operative Societies (SACCOS); households benefits directly and indirectly, of which 23% are to be female – headed households. Beneficiaries have shown appreciation of the project intervention. The participatory approach applied by the project gives more understanding and sense of ownership to participants. O&OD system, planning, Budgeting and Procurement style, have lead farmers to appreciate what as been done to date. FINANCIAL SITUATION AS AT 30th July 2010 S/No ACTIVITY AMOUNT DISBURSED EXPENDITURE BALANCE 1. Construction of 8 storage facilities 140,000,000 140,000,000 0 2. Construction of 2 permanent cattle crushes 15,000,000 15,000,000 0 3. Construction of 6 water 14,400,000 14,400,000 0 troughs 4. Rehabilitation of slaughter slab 16,000,000 16,000,000 0 5. Establishment of medium irrigation scheme in the district 0 0 0 6. Rehabilitation of 12 km of feeder roads and 3 culverts 120,000,000 120,000,000 0 7. Construction of SACCOS building 28,000,000 28,000,000 0 8. Season long training of PFG 90,000,000 90,000,000 0 9. Formation of 120 PFGs 2,300,000 2,300,000 0 10. O &OD planning 5,200,000 5,200,000 0 11. Min-Projects of participatory farmer groups 24,000,000 11,200,000 12,800,000 12 Training of Farmer facilitators 10,041,000 10,041,000 0 13 Supervision of activities 5,203,000 3,450,000 1,753,000 Total 470,144,000 455,591,000 14,553,000 8.0 PROBLEMS With all this achievements realized still there are drawbacks encountered in the due course of implementation. ¾ Long tendering process delays the project implementation. ¾ Shortage of extension staffs at wards and village level. ¾ Slow response in implementing project activities by villages, especially local contribution. ¾ Previous year BOQ were not timely prepared. ¾ Lack of transport, especially a car, hinders quick response of officers to supervise activities in the field. ¾ Slow understanding of supervision committee members and other village leaders when implementing community projects. ¾ Low productivity of agricultural and livestock products because of inadequate extension services and low level of application of appropriate technology in agriculture and livestock sector. ¾ High agricultural input costs. ¾ Low prices for agricultural products. 9.0. RECOMMENDATION DASIP approach of Farmer Field schools geared by Farmer Facilitators has lessened the gap created by the scarcity of extension services. During village meeting and group training, sensitization and elaboration is being done to create sense of ownership and stop total dependence on support, hence sensitization should be a continuous process for permanent adoptability. 9 More staff needed at village level to make sure farmers are technically supported accordingly. 9 Village supervision committees need regular training especially in the initial stages of new projects implementation. 9 Vehicle is of great need at District level for smooth learning of planned activities. 10.0 ACTIVITIES FOR THE COMING SEASON For the following quarter started activities will be accomplished as shown in the table attached with this report. Most of the projects have undergone preliminary process ensuring successes within scheduled period. Major activities being; Micro Investment Projects implementation. Agricultural Investment Technologies support. PFGs training and support. Monitoring and Evaluation. DISTRICT AGRICULTURE INVESTMENT PROJECT (DASIP) VILLAGE MICRO AND AGR. TECHNOLOGY IMPROVEMENT – PROJECTS PLANNED IN 2009/2010 KARAGWE DISTRICT COUNCIL S/n Ward Village Inv.project Cost Tsh. '000' Train.needs Cost Tsh. '000' Agr.Inv Tech Tsh.'000' Cost Tsh. '000' Kitwe Road rehab. 13,000 Banana, coffee 6,000 Milling machine 10,000 1 Kamuli Kyerere - 0 Cassava product. 6,000 Milling machine 10,000 Businde Crop storage 28,000 Banana, coffee 6,000 Milling machine 10,000 2 Mabira Kibimba charco dam 35,000 Poultry,Maize , banana. 6,000 Milling machine 10,000 Iteera - 0 Beans, goat 6,000 Power tiller 10,000 3 Rwabwere Rwabwere - 0 Maize, Banana 6,000 Banana wine processing machine 10,000 Kihanga Crop storage 35,000 Poultry, Maize, Vegetable, goat 6,000 Milling machine 10,000 4 Isingiro Katera - 0 Maize, beans 6,000 Milling machine 10,000 Kihinda Road rehab. 30,200 Diary goat, maize 6,000 Milling machine 10,000 5 Kibingo Kibingo Road rehab. 13,000 diary goat, poultry 6,000 Milling machine 10,000 6 Murongo Masheshe Road rehab. 7,000 Banana, coffee,maize 6,000 Milling machine 10,000 7 Bugomora Nyamiyaga - 0 Banana, coffee 6,000 Milling machine 10,000 8 Kiruruma Nyakagoyag oye - 0 Poultry,Maize 6,000 Milling machine 10,000 Kibona - 0 Banana, maize, beans 6,000 Milling machine 10,000 9 Igurwa Igurwa Crop storage 24,000 Sunflower, maize, beans 6,000 Milling machine 10,000 10 Ndama Nyabwegira Road rehab. 13,000 Beans, goat 6,000 Milling machine 10,000 11 Kayanga Kayanga Road rehab. 15,000 Maize, Beans 6,000 Artificial Insemination 10,000 12 Bugene Bujuruga Road rehabilitation 3,731 Maize, Beans 6,000 Power tillers 10,000 13 Nyakahanga Omurusimbi - 0 Onions, beans 6,000 Power tillers 10,000 Nyakayanja Road rehab/culvert 20,800 Vegetables, Maize, beans, coffee product. 6,000 Irrigation pumping machine unit 10,000 Culvert 10,000 14 Nyaishozi Rukale Road rehab. 20,000 Onions, beans 6,000 Milling machine 10,000 15 Ihembe Ihembe II Road rehab. 13,000 Coffee nursery, maize,beans 6,000 Milling machine 10,000 16 Nyakasimbi Bujara - 0 Maize, Poultry 6,000 Milling machine 10,000 Nyakakika Crop storage 35,000 Maize, Coffee 6,000 Milling machine 10,000 17 Nyakakika Kayungu Crop storage 24,000 Maize, Beans 6,000 Milling machine 10,000 Kakuraijo - 0 Maize, beans, 6,000 Milling machine 10,000 18 Kibondo Kibondo - 0 Maize,beans, coffee 6,000 Milling machine 10,000 Bukangara Crop storage 26,000 Maize, beans 6,000 Milling machine 10,000 19 Nyabiyonza Nyabiyonza - 0 Maize, beans 6,000 Power tillers 10,000 20 Bweranyange Chamchuzi Crop storage 26,000 Maize,poultry , beans 6,000 Milling machine 10,000 20 WARDS 30 VILLAGES Sub total 391,731 Sub total 180,000 Sub total 300,000 2: Status of carried forward projects for the year 2008/09 No Name of project Status Remarks 1. Construction of 10 storage facilities at Omurusimbi, Kibondo, Kakuraijo, Nyabiyonza, Rwabwere, Kibona, Katera, Chamchuzi, Bukangara, Nyamiyaga -Construction is at final different stages. Currently Chamchuzi, Kibona, Kyerere, Rwabwere, Omurusimbi and Katera are completed; Kibondo, Kakuraijo, Bukangara, Nyabiyonza at finishing stage; Finishing is going on 2. Construction of 2 permanent cattle crushes at Businde & Ihembe II -Construction of Cattle crushes at Ihembe II and Businde are completed. The structure in use 4. Rehabilitation of slaughter slab at Kayanga - Completed The structure in use 5. Establishment of medium irrigation scheme in the district Not yet started Awaiting Consultants from DASIP 6. Rehabilitation of 12 km of feeder roads;- 3 culverts at Bujara, Masheshe , Kibingo, Kayungu , Igurwa, Kitwe, Nyabwegira and Nyakayanja village. -20.35km of feeder road have been rehabilitated, 32culverts and 2Reinforced box culverts have been constructed as below shown: 3 culverts(900mm dia), 2culverts(750mm dia) 4.05km road at Bujara village, 4culverts(900mm dia), 2km road at Masheshe village, 2culverts(900mm dia), 2culverts(1200mm dia), To rise Embankment 700m, Gravel 490m3, 2km road at Kibingo village, 1culvert(900mm dia), 2.70km road at Kayungu village, 2Culverts(750mm dia), 1culvert(1200mm) 2.20km road at Igurwa village, 5culverts(900mm dia), 3.70km road at Kitwe village and 5culverts(900mm dia), 3.70km road at Nyabwegira village, 2culverts(1500mm dia) at Nyakayanja village, 1Reinforced box Culvert(2000mmx2000mmx6000mm) at Lukale village and 1Reinforced Box culvert (2000mmx2000mmx6000mm) at Ihembe II Village. The structures are in use. 8. Season long training of PFG -Training of 180 groups, some have conducted graduation ceremony and some are under way Training completed 9. Formation of 120 PFGs -120 PFGs formed Training completed 10 O &OD planning -30 VADPs have been prepared VADPs are being implemented in 2009/10 11 Training of Farmer facilitators -Training of Farmer facilitators; 27 farmer facilitators trained Training done 12 Min-Projects of participatory farmer groups -60 groups have opened accounts and; Funds transferred to 32 PFGs phase II is in process DISTRICT AGRICULTURE INVESTMENT PROJECT (DASIP) STATUS OF VILLAGE MICRO -PROJECTS 2009/2010 KARAGWE DISTRICT COUNCIL S/n Ward Village Inv.project Cost Tsh. ' 000' Funds Receive d ‘000’ Project status Remarks 1 Kamuli Kitwe Road rehab. 13,000 10,400 1culvert(900mm dia), 1culvert(1500mmdia) and 1.50km road Structures is in use Businde Crop storage 28,000 22,400 The building is completed Construction completed 2 Mabira Kibimba charco dam 35,000 28,000 Detail structural design and preparation of tender document Detail structural design and preparation of tender document are going on. 3 Isingiro Kihanga Crop storage 35,000 28,000 The building is completed Construction completed Kihinda Road rehab. 30,200 24,160 2culverts(900mm dia), 1culvert(1500mmdia), 3.40km road The rehabilitation is completed 4 Kibingo Kibingo Road rehab. 13,000 10,400 Construction of 2culverts(900mm dia), 1.50km road not yet started Funds not received 5 Murongo Masheshe Road rehab. 10,000 5,600 Completed The structure in use 6 Igurwa Igurwa Crop storage 24,000 19,200 The building is at linter stage Construction is going on 7 Ndama Nyabwegira Road rehab. 13,000 10,400 1culverts(1500mm dia), 1.50km road rehabilitated The structure in use 8 Kayanga Kayanga Road rehab. 15,000 12,000 Completed The structure in use 9 Bugene Bujuruga Road rehabilitation 3,731 2,985, Completed The structure in use Nyakayanja Road rehab/culvert 20,800 0 Not started Funds not received Culvert 10,000 0 Not started Funds not received 10 Nyaishozi Rukale Road rehab. 20,000 16,000 Not started Funds not received 11 Ihembe Ihembe II Road rehab. 13,000 0 Not started Funds not received. Nyakakika Crop storage 35,000 28,000 The building is at roofing stage Construction is going on 12 Nyakakika Kayungu Crop storage 24,000 19,200 The building is at roofing stage Construction is going on 13 Nyabiyonza Bukangara Crop storage 26,000 20,800 The construction is roofing stage Construction is going on 14 Bweranyang e Chamchuzi Crop storage 26,000 20,800 The construction is Completed The structure is ready for use 15 Kayanga Kayanga Artificial insemination 10,000 8,000 Procurement process going on On track 16 Rwabwere Rwabwere Banana wine processing unit 10,000 8,000 Procurement process going on On track 17 Nyaishozi Nyakayanja Purchase of irrigation pumping machines 10,000 8,000 Procurement process going on On track 18 All wards All villages Season long PFGs training 90,000 90,000 Transfer of funds to village accounts On track 19 All wards All villages PFGs Mini grant 72,000 72,000 Transfer of funds to village accounts On track 20 23 villages Procurement of 23 milling machines 230,000 184,000 Transfer of funds to village accounts On track 20 WARDS 30 VILLAGES Sub total 816,731 648,345 | false |
# Extracted Content KARAGWE DISTRICT COUNCIL P.O. BOX 20, KARAGWE. REF.NO. KGR/HWK/T.29/26 2 January 2009 Project Coordinator , DASIP, Nyanza Cooperative Union Ltd Building, 3rd Floor, P.O. Box 11185 MWANZA. Ref: IMPLEMENTATION PROGRESS REPORT FOR THE SECOND QUARTER OCTOBER –DECEMBER 2008/09 The above heading refers. Find herewith attached DASIP IMPLEMENTATION PROGRESSIVE REPORTSECOND QUARTER 2008/2009. The report includes - General Information & Background. - Introduction. - Planned Activities - Physical performance - Financial status - Challenges faced - Lessons learnt - Recommendations - Future plans - Annex. C.M. Kamuhabwa DISTIRICT EXECUTIVE DIRECTOR KARAGWE DISTRICT COUNCIL KARAGWE DISTRICT COUNCIL DISTRICT AGRICULTURAL DEVELOPMENT PLAN 2008/2009 Implementation report for 2nd Quarter OCTOBER-DECEMBER DASIP P.O. BOX. 20, Tel. 028 – 2227140 KARAGWE. Fax: 028 – 2227148 1.1 General information and Background Karagwe District is characterized by mountains ranges, which are separated by swampy valley bottoms and wet lands. The altitude ranges between 1500-1800 meters above sea level while valley bottoms and wet lands are 1150 meters to 1450 meters above sea level. Most of the District has a tropical highland climate. The annual average temperature is 26 0C Rainfall distribution is bi-modal with peak rains from September to December and from March to May. This type of climate makes the District very potential for most of Agricultural crops. 1.2 INTRODUCTION The government of Tanzania through a loan from the African Development Bank is implementing the District Agriculture sector Investment Project (DASIP).The Project aims at increasing productivity and income of the rural households in the project area within a frame work of the Agriculture Sector Development Strategy (ASDS).The project will be implemented over a period of six years starting from January 2006. It will cover a total of 30 villages in 20 wards. Project components are; o Farmers capacity Building. o Community planning and investment in Agriculture. o Support to Rural financial services and marketing. o Project coordination and management. Karagwe District Council in collaboration with other stakeholders is implementing Agricultural Sector Development Programme (ASDP) through its District Agricultural Development Plan (DADP). The Council is receiving grants from the Central Government and Other donors for the development of the Agriculture sector. DASIP being part of DADPs is receiving grants from AfDB to implement different activities including Community Planning &Investment projects, Farmers capacity building as well as Marketing and Micro financial services. 2.0 PLANNED ACTIVITIES Different activities have been planned to be implemented this year as shown in the list below starting with carried forward activities. Activities planned in 2007/08 Community Planning and Investment in Agriculture • To construct 1 cattle dip at Kyerere village. • To construct 1 cattle dip at Bujuruga village. • To construct 1 char co dam at Nyakagoyagoye village. • To rehabilitate 5 km of feeder roads at Kihinda village. • To rehabilitate 4 km of feeder road at Masheshe village. Farmers capacity Building • To train 60 participatory farmer groups (PFGs). • To train 30 participatory farmer supervision committees (PFSCs). • To train 24 ward training facilitators (WTFs). • Annual follow up training in O&OD methods. Activities planned in 2008/09 Community Planning and Investment in Agriculture • To construct 8 storage facilities. • To construct 6 water troughs. • To construct 3 permanent cattle crushes. • To rehabilitate 1 slaughter slab. • To purchase 6 coffee hullers. • To establish large irrigation scheme in the district. • To construct one fish pond. • To rehabilitate 11 km of feeder roads and 3 culverts. • To purchase 240,000 of cassava cuttings. • To purchase 200 piglets. • To support 60 participatory farmer groups on micro-project investments. Farmers capacity Building • To train 180 Participatory farmer groups. • To train Farmer facilitators. • To continue train PFG’s supervision committees. • To continue train Ward training facilitators. 3.0 Physical performances Funds for planned activities have been disbursed to respective villages through their Bank accounts. The last year’s groups have continued with implementation of their projects. Formation of new Groups, four in each village is completed; appointment of leadership; Bank account opening and other necessary procedures are being performed. Groups formed so far are as indicated in Annex 6 4.0 FINANCIAL STATUS Community & group projects have been supported especially those which commenced in 2007/08. Newly found groups will be supported this financial year. Financial position of group community projects are as shown in Annex 1, 2 & 4 5.0 CHALLENGES FACED With all efforts endeavored still we are facing some challenges in the due course of implementation. Major ones being; • Slow response in implementing project activities by villages. • BOQ not timely prepared. • Slow rate of local community contribution. • Little amount of money allocated for supervision to DTCs. • Lack of transport like a car hinders quick response of officers to supervise activities in the field. • Lack of funds allocated for fuels. • Poor understanding of supervision committee members and other village leaders. 6.0 LESSONS LEARNT • The project should have its vehicle at District level for smooth learning of activities. • Fuel cost should be incorporated in project funds. • More sensitization to the society is needed to have community contribution at the required time. 7.0 RECOMMENDATIONS More staff is needed at village level to make sure farmers are technically supported accordingly. Village supervision committees need regular training especially in the initial stages of project implementation. 8.0 FUTURE PLANS • Completion of previous year projects. • Implement this year projects as scheduled. • More concentration on project activities for all focal persons. • Continue sensitizing community on contribution of projects. CARRIED FORWARD COMMUNITY INVESTMENT PROJECTS Name of District: KARAGWE Reporting Date: 2 Jan, 2009 Quarter: SECOND Name of Reporting Officer: Samuel Stambuli Financial year: 2008/09 Annex. 1 Project Cost Contributions by Source DASIP Village Number of Households Investment Type Total(Tshs) Community Total Disbursed Balance Unallocated Remarks KYERERE 521` Construction of Cattle dip 16,000,000 3,200,000 12,800,000 12,800,000 - - Changed the project to godown BUJURUGA 415 Construction of Cattle dip 16,000,000 3,200,000 12,800,000 12,800,000 - - Tender advertisement NYAKAGOYAG OYE 916 Construction of Char co dam 16,000,000 3,200,000 12,800,000 12,800,000 - - BOQ preparation MASHESHE 709 Rehabilitation of 4 km of feeder roads 4,800,000 960,000 3,840,000 3,840,000 - - Completed KIHINDA 595 Rehabilitation of 5 km of feeder roads 6,000,000 1,200,000 4,800,000 4,800,000 - - Completed TOTAL 2635 58,800,000 11,760,000 47,040,000 47,040,000 SUMMARY OF COMMUNITY INVESTMENT PROJECTS Name of District: KARAGWE Reporting Date: 2 Jan, 2009 Quarter; SECOND Name of Reporting Officer: Samuel Stambuli Financial year: 2008/09 Annex. 2 Project Cost Contributions by Source DASIP Village Number of Households Investment Type Total(Tshs) Community Total Disbursed Balance Unallocated Remarks KYERERE 521 Purchase of two coffee hullers 15,000,000 7,500,000 7,500,000 - - - Not received KITWE 795 Rehabilitation of 2 km feeder road 22,000,000 4,400,000 17,600,000 - - - Not received KIBIMBA 991 Purchase two coffee hullers 15,000,000 7,500,000 7,500,000 - - - Not received BUSINDE 830 Construction of permanent clash 7,000000 1,400,000 5,600,000 - - - Tender in process ITEERA 971 Establishment of cassava farms (10 ha) 500,000 100,000 400,000 - - - Not received RWABWERE 762 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process KIHANGA 577 Improved Pig production 2,000,000 400,000 1,600,000 - - - Not received KATERA 844 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process KIBONA 509 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process IGURWA 317 Road rehabilitation 11,000,000 2,200,000 8,800,000 - - - Tender in process MASHESHE 709 Road rehabilitation 22,000,000 4,400,000 17,600,000 - - - Not received KAYANGA 2096 Rehabilitation of slaughter slab 20,000,000 4,000,000 16,000,000 - - - Tender in process CHAMCHUZI 1825 Construction of 3 water troughs 9,000,000 I,800,000 7,200,000 - - - Tender in process KAKURAIJO 594 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process KIBONDO 484 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process Construct permanent crush 7,000,000 1,400,000 5,600,000 - - - Tender in process IHEMBE II 395 Rehabilitation of culvert 6,000,000 1,200,000 4,800,000 - - - Tender in process NYABIYONZA 761 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process BUKANGARA 353 Construct three water troughs 9,000,000 1,800,000 7,200,000 - - - Tender in process NYAKAKIKA 2337 Establish medium scale Irrigation Scheme 225,000,000 45,000,000 180,000,00 0 - - - Not received KAYUNGU 797 Road rehabilitation 11,000,000 2,200,000 8,800,000 - - - Tender in process KIHINDA 595 Construction of one fish pond 20,000,000 4,000,000 16,000,000 - - - Not received KIBINGO 1095 Rehabilitation of two km feeder 22,000,000 4,400,000 17,600,000 - - - Not received Project Cost Contributions by Source DASIP Village Number of Households Investment Type Total(Tshs) Community Total Disbursed Balance Unallocated Remarks road Purchase two coffee hullers 15,000,000 7,500,000 7,500,000 - - - Not received NYAKAGOYAGOYE 916 Establishment of cassava farms (10 ha) 500,000 100,000 400,000 - - - Not received BUJURUGA 415 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process LUKALE 264 Rehabilitate one culvert 6,000,000 1,200,000 4,800,000 - - - Tender in process NYAKAYANJA 757 Rehabilitate one culvert 6,000,000 1,200,000 4,800,000 - - - Tender in process NYABWEGIRA 538 Rehabilitate two kms of feeder road 22,000,000 4,400,000 17,600,000 - - - Not received OMURUSIMBI 343 Godown construction 25,000,000 5,000,000 20,000,000 - - - Tender in process BUJARA 343 Rehabilitate two kms of feeder road 22,000,000 4,400,000 17,600,000 - - - Not received NYAMIYAGA 1078 Establishment of SACCOs premises 10,000,000 5,000,000 5,000,000 - - - Not received TOTAL 23812 705,000,000 108,800,000 547,500,00 0 DISTRICT AGRICULTURAL SECTOR INVESTMEN T PROJECT (DASIP) DISTRICT SUMMARY FOR PARTICIPATORY FARMER GROUPS (PFG) NAME OF DISTRICT: KARAGWE QUARTER ; SECOND REPORTING DATE: 2 Jan, 2009 YEAR: 2008/09 NAME OF REPORTING OFFICER: SAMUEL STAMBULI Annex. 3 YEAR NUMBER OF MEMBERS WARD VILLAGE NAME OF PFG FORMED GRADUATED Male Female Total ENTERPRISE REMARKS KAMULI KYERERE JUHUDI 2007/08 NOT GRADUATED 10 15 25 Improved Banana production Under operation BARAKA 2007/08 GRADUATED 16 9 25 Resistant cassava production - KITWE NYOTA 2007/08 GRADUATED 14 11 25 Improved coffee production - MAENDELEO 2007/08 NOT GRADUATED 23 2 25 Improved banana production Under operation MABIRA KIBIMBA NYABIHARA 2007/08 GRADUATED 17 8 25 Improved maize production - KIBIMBA “A” 2007/08 NOT GRADUATED 10 15 25 Improved Banana production Under operation BUSINDE MSHIKAMANO 2007/08 GRADUATED 23 2 25 Improved coffee production - NYARUGONGO 2008/08 GRADUATED 21 4 25 Improved maize production - RWABWERE ITEERA RUKIKI 2007/08 GRADUATED 11 14 25 Maize Production - UPENDO 2007/08 GRADUATED 15 10 25 Maize Production - RWABWERE NYANGOYE 2007/08 GRADUATED 14 11 25 Improved maize production - UWAKAKI 2007/08 GRADUATED 16 9 25 Horticultural crop production - ISINGIRO KIHANGA JUHUDI 2007/08 GRADUATED 15 10 25 Improved coffee production - MUUNGANO 2007/08 NOT GRADUATED 13 12 25 Improved Banana production Under operation KATERA TUPENDANE 2007/08 NOT GRADUATED 13 12 25 Improved Banana production Under operation NEEMA 2007/08 GRADUATED 0 25 25 Improved coffee production - IGURWA KIBONA UJAMAA 2007/08 NOT GRADUATED 25 7 32 Improved Banana production Under operation TUMAINI 2007/08 GRADUATED 20 13 33 Improved Beans production - IGURWA FAIDA 2007/08 GRADUATED 20 10 30 Improved Beans production - LENGO LETU 2007/08 GRADUATED 22 8 30 Improved coffee production - MURONGO MASHESHE MGOMBA 2007/08 NOT GRADUATED 14 11 25 Improved Banana production Under operation USHIRIKA 2007/08 NOT GRADUATED 16 9 25 Improved coffee production Under operation KAYANGA KAYANGA UMOJA NSHESHE 2007/08 GRADUATED 22 10 32 Improved coffee production - RWAMBALE 2007/08 NOT GRADUATED 15 15 30 Improved poultry production Under operation BWERANYANGE CHAMCHUZI UMOJA 2007/08 GRADUATED 11 13 24 Improved coffee production - TEGEMEO 2007/08 GRADUATED 16 8 24 Improved cassava production - KIBONDO KAKURAIJO UWAKAKA 2007/08 NOT GRADUATED 12 13 25 Improved Banana production Under operation JUHUDI 2007/08 NOT GRADUATED 11 14 25 Improved poultry production Under operation KIBONDO UKIKIA 2007/08 NOT GRADUATED 17 8 25 Improved Banana production Under operation MAENDELEO 2007/08 NOT GRADUATED 16 9 25 Improved Banana production Under operation IHEMBE IHEMBE II MAHAGE 2007/08 GRADUATED 10 15 25 Improved poultry production - UMANO 2007/08 NOT GRADUATED 18 6 24 Tree seedling nursery Under operation NYABIYONZA NYABIYONZA KAYANGO 2007/08 GRADUATED 17 8 25 Improved maize production - JITEGEMEE 2007/08 GRADUATED 16 9 25 Improved coffee production - BUKANGARA NYOTA 2007/08 NOT GRADUATED 17 8 25 Improvement of goat production Under operation NYABIRIZI 2007/08 NOT GRADUATED 18 7 25 Tree seedling nursery Under operation NYAKAKIKA NYAKAKIKA TUINUANE 2007/08 GRADUATED 16 9 25 Improved maize production - TWEYAMBE 2007/08 GRADUATED 17 9 26 Improved poultry production - KAYUNGU UPENDO 2007/08 GRADUATED 18 7 25 Improved Banana production - BORESHA 2007/08 GRADUATED 18 7 25 Improved maize production - KIBINGO KIBINGO TUINUANE 2007/08 GRADUATED 13 12 25 Diary zero grazing - TUSAIDIANE 2007/08 GRADUATED 14 11 25 Vegetable production - KIHINDA JUHUDI 2007/08 GRADUATED 13 17 30 Maize production - ABAGAMBAKA MO 2007/08 GRADUATED 16 14 30 Maize production - KIRURUMA NYAKAGOYAGOYE MUUNGANO 2007/08 GRADUATED 13 12 25 Improved Banana production - MAPAMBANO 2007/08 GRADUATED 16 9 25 Improved coffee production - BUGENE BUJURUGA KIJIUMA 2007/08 GRADUATED 14 11 25 Improved Banana production - TUKOMBOAN E 2007/08 GRADUATED 16 9 25 Improved maize production - NYAISHOZI NYAKAYANJA UMOJA NI NGUVU 2007/08 GRADUATED 26 12 38 Vegetable production - MSHIKAMAN O 2007/08 GRADUATED 4 16 20 Improved poultry production - LUKALE OMURWERE 2007/08 NOT GRADUATED 19 8 27 Improved Diary Goat production - NGUVUKAZI 2007/08 GRADUATED 16 13 29 Carrot Production - NDAMA NYABWEGIRA NYAKIRU 2007/08 GRADUATED 14 11 25 Improved Banana production - UWAWANYA 2007/08 GRADUATED 13 12 25 Diary zero grazing - NYAKAHANGA OMURUSIMBI MKOMBOZI 2007/08 GRADUATED 14 11 25 Improved maize production - PAMAO 2007/08 GRADUATED 15 10 25 Improved poultry production - NYAKASIMBI BUJARA JIKOMBOE 2007/08 GRADUATED 12 12 24 Improved Beans production - JUHUDI 2007/08 GRADUATED 14 10 24 Vegetable production - BUGOMORA NYAMIYAGA MWANAKWE TU 2007/08 NOT GRADUATED 13 12 25 Improved poultry production Under operation UMOJA 2007/08 NOT GRADUATED 14 11 25 Improved Banana production Under operation TOTAL OF MEMBERS 922 635 1557 DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) FINANCIAL STATUS OF PARTICIPATORY FARMER GROUPS (PFGs) NAME OF DISTRICT: KARAGWE QUARTER; SECOND REPORTING DATE: 2 Jan 2009 YEAR: 2008/09 NAME OF REPORTING OFFICER: SAMUEL STAMBULI Annex 4 Contribution from DASIP (Tsh. ‘000) Number of PFG Members Village Male Female Total Type of Enterprise Total Cost (Tsh. ‘000) Group Contribution (Tsh. ‘000) Total Disbursed Balance Unallocated Balance (Tsh. ‘000) KYERERE 10 15 25 Improved Banana production 1200 700 500 500 0 0 0 16 9 25 Resistant cassava production 800 300 500 500 0 0 0 KITWE 14 11 25 Improved coffee production 1300 900 500 500 0 0 0 23 2 25 Improved banana production 900 400 500 500 0 0 0 KIBIMBA 17 8 25 Improved maize production 900 400 500 500 0 0 0 10 15 25 Improved Banana production 1000 500 500 500 0 0 0 BUSINDE 23 2 25 Improved coffee production 1300 800 500 500 0 0 0 21 4 25 Improved maize production 1000 500 500 500 0 0 0 ITEERA 11 14 25 Improved Banana production 1000 500 500 500 0 0 0 15 10 25 Improved poultry production 1200 800 400 400 0 0 0 RWABWERE 14 11 25 Improved maize production 1000 500 500 500 0 0 0 16 9 25 Vegetable production 950 450 500 500 0 0 0 KIHANGA 15 10 25 Improved coffee production 1100 600 500 500 0 0 0 13 12 25 Improved Banana production 900 500 400 400 0 0 0 KATERA 13 12 25 Improved Banana production 1000 500 500 500 0 0 0 15 10 25 Improved coffee production 1000 500 500 500 0 0 0 KIBONA 25 7 32 Improved Banana production 1000 500 500 500 0 0 0 20 13 33 Improved Beans production 1000 500 500 500 0 0 0 IGURWA 21 11 32 Diary zero grazing 1000 500 500 500 0 0 0 22 9 31 Improved coffee production 1000 500 500 500 0 0 0 MASHESHE 14 11 25 Improved Banana production 1000 500 500 500 0 0 0 16 9 25 Improved coffee production 1000 500 500 500 0 0 0 NYAMIYAGA 13 12 25 Improved poultry production 1100 600 500 500 0 0 0 14 11 25 Improved Banana production 1000 500 500 500 0 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members BUJARA 12 12 24 Improved beans production 1000 500 500 500 0 0 0 14 10 24 Vegetable production 1000 500 500 500 0 0 0 14 11 25 Improved maize production 1000 500 500 500 0 0 0 OMURUSIMBI 15 10 25 Improved poultry production 900 500 400 400 0 0 0 14 11 25 Improved Banana production 1000 500 500 500 0 0 0 NYABWEGIRA 13 12 25 Diary zero grazing 1000 500 500 500 0 0 0 19 8 27 Improved Banana production 1000 500 500 500 0 0 0 LUKALE 16 13 29 Improved coffee production 1000 500 500 500 0 0 0 26 12 38 Vegetable production 1000 500 500 500 0 0 0 NYAKAYANJA 4 16 20 Maize Production 900 500 400 400 0 0 0 22 10 32 Improved coffee production 1000 500 500 500 0 0 0 KAYANGA 15 15 30 Improved poultry production 900 400 500 500 0 0 0 11 13 24 Improved coffee production 1000 500 500 500 0 0 0 CHAMCHUZI 16 8 24 Improved cassava production 1200 700 500 500 0 0 0 12 13 25 Improved banana production 1000 500 500 500 0 0 0 KAKURAIJO 11 14 25 Improved poultry production 1000 500 500 500 0 0 0 17 8 25 Improved banana production 1000 500 500 500 0 0 0 KIBONDO 16 9 25 Improved banana production 1000 500 500 500 0 0 0 10 15 25 Improved poultry production 1000 500 500 500 0 0 0 IHEMBE II 18 6 24 Tree nursery 1000 500 500 500 0 0 0 17 8 25 Improved coffee production 1000 500 500 500 0 0 0 NYABIYONZA 16 9 25 Improved maize production 1000 500 500 500 0 0 0 BUKANGARA 17 8 25 Diary goat production 1000 500 500 500 0 0 0 18 7 25 Tree nursery production 1000 500 500 500 0 0 0 16 9 25 Improved maize production 1000 500 500 500 0 0 0 NYAKAKIKA 17 9 26 Improved poultry production 900 500 400 400 0 0 0 18 7 25 Improved banana production 1000 500 500 500 0 0 0 KAYUNGU 18 7 25 Improved maize production 1000 500 500 500 0 0 0 13 12 25 Diary zero grazing 1000 500 500 500 0 0 0 KIBINGO 14 11 25 Vegetable production 1000 500 500 500 0 0 0 KIHINDA 13 17 30 Improved maize production 1000 500 500 500 0 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members 16 14 30 Improved maize production 1000 500 500 500 0 0 0 13 12 25 Improved banana production 1000 500 500 500 0 0 0 NYAKAGOYAGO YE 16 9 25 Improved coffee production 1000 500 500 500 0 0 0 14 11 25 Improved banana production 1000 500 500 500 0 0 0 BUJURUGA 16 9 25 Improved maize production 1000 500 500 500 0 0 0 60,450 31,050 29,500 29,500 DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) DISTRICT SUMMARY FOR ALL PROJECTS NAME OF DISTRICT: KARAGWE QUARTER: SECOND REPORTING DATE: 2 Jan 2009 YEAR: 2008/09. NAME OF REPORTING OFFICER: SAMUEL STAMBULI Annex 5 Number of Projects Type of Project and its Description Community Investment Group Total Improved Livestock Husbandry – Improved goat and Diary zero grazing, Improved piggery and poultry keeping, cattle dips construction and rehabilitation, water troughs, slaughter slabs, cattle crushes. 8 11 19 Improved Crop Husbandry- Improved Banana production, Improved Cassava resistant varieties production, Improved Maize production, Improved Coffee production, Improved Beans production, Improved horticultural crops production and Tree nursery establishment. 2 49 51 Improved Post-harvest technique- Storage facilities construction, Coffee value added equipments, 11 0 11 Improved Rural Infrastructure- Improved feeder roads and culverts, Construction of char co dam &fish pond, Established irrigation scheme 13 0 13 Total 34 60 94 DISTRICT AGRICULTURAL SECTOR INVESTMEN T PROJECT (DASIP) DISTRICT SUMMARY FOR PARTICIPATORY FARMER GROUPS (PFG) NAME OF DISTRICT: KARAGWE QUARTER: SECOND REPORTING DATE: 2 Jan 2009 YEAR: 2008/09 NAME OF REPORTING OFFICER: SAMUEL STAMBULI Annex 6 YEAR NUMBER OF MEMBERS WARD VILLAGE NAME OF PFG FORMED GRADUATED Male Female Total ENTERPRISE REMARKS KUJITEGEMEA 2008/09 NEW 15 11 26 Banana Production Newly formed MUUNGANO 2008/09 NEW 16 9 25 Maize production Newly formed MAFANIKIO 2008/09 NEW 14 10 24 Maize production Newly formed KYERERE TWEYAMBE 2008/09 NEW 19 11 30 Maize production Newly formed MAENDELEO 2008/09 NEW 15 9 24 Banana Production Newly formed NYOTA 2008/09 NEW 16 13 29 Horticulture Crop Prod. Newly formed KWETU 2008/09 NEW 13 12 25 Goat production Newly formed KAMULI KITWE TUJENGANO 2008/09 NEW 15 11 26 Poultry production Newly formed TWEMANYE 2008/09 NEW 16 9 25 Banana Production Newly formed SONGAMBELE 2008/09 NEW 18 8 26 Maize production Newly formed USHIRIKA 2008/09 NEW 14 11 25 Poultry Production Newly formed KIBIMBA TUSAIDIANE 2008/09 NEW 18 9 27 Coffee Production Newly formed KAZI KWETU 2008/09 NEW 16 8 24 Banana Production Newly formed JUHUDI 2008/09 NEW 17 9 26 Poultry Production Newly formed MAVUNO 2008/09 NEW 15 7 22 Maize production Newly formed MABIRA BUSINDE MAJARIWA 2008/09 NEW 11 14 25 Beans production Newly formed AKILIMALI 2008/09 NEW 18 9 27 Maize production Newly formed UJAMAA 2008/09 NEW 10 14 24 Beans production Newly formed MAFANIKIO 2008/09 NEW 14 13 27 Maize production Newly formed ITEERA TUELEKEZANE 2008/09 NEW 16 10 26 Banana Production Newly formed MUUNGANO 2008/09 NEW 18 9 27 Horticulture Crop Prod. Newly formed AZIMIO 2008/09 NEW 16 9 25 Banana Production Newly formed MAFANIKIO 2008/09 NEW 13 14 27 Horticulture Crop Prod. Newly formed RWABWERE RWABWERE MAPINDUZI 2008/09 NEW 18 7 25 Banana Production Newly formed UPENDO 2008/09 NEW 15 6 21 Poultry Production Newly formed HEKIMA 2008/09 NEW 15 10 25 Coffee Production Newly formed MAENDELEO KIJARWE 2008/09 NEW 14 15 25 Banana Production Newly formed KIHANGA FARAJA 2008/09 NEW 7 9 16 Coffee Production Newly formed MAARIFA 2008/09 NEW 8 3 11 Banana Production Newly formed TUPENDANE 2008/09 NEW 13 11 24 Tomato production Newly formed TUJIINUE 2008/09 NEW 12 3 15 Goat production Newly formed ISINGIRO KATERA AKINA MAMA NA MAENDELEO 2008/09 NEW 0 18 18 Poultry production Newly formed UJAMAA 2008/09 NEW 14 7 21 Poultry production Newly formed TUMAINI 2008/09 NEW 5 7 12 Maize production Newly formed WEKEZA 2008/09 NEW 18 9 27 Beans production Newly formed KIBONA UKOMBOZI 2008/09 NEW 10 5 15 Maize production Newly formed TWENDENI 2008/09 NEW 15 10 25 Beans production Newly formed TUSHIRIKIANE 2008/09 NEW 18 8 26 Banana Production Newly formed RWAMBAIZI 2008/09 NEW 11 15 26 Banana Production Newly formed IGURWA IGURWA MTU KWAO 2008/09 NEW 17 7 24 Maize Production Newly formed MWONGOZO 2008/09 NEW 14 15 29 Maize Production Newly formed MWOKOZI 2008/09 NEW 12 14 26 Banana Production Newly formed FANIKISHA 2008/09 NEW 17 9 26 Coffee Production Newly formed MURONGO MASHESHE VUMILIA 2008/09 NEW 12 13 25 Poultry production Newly formed WARD VILLAGE NAME OF PFG YEAR NUMBER OF ENTERPRISE REMARKS MEMBERS FORMED GRADUATED Male Female Total KAYANGA KAYANGA RUZINGA 2008/09 NEW 4 14 18 Maize production Newly formed UMOJA NI NGUVU 2008/09 NEW 16 9 25 Beans production Newly formed OMUKATOMA GROUP 2008/09 NEW 14 12 26 Poultry production Newly formed ELIMISHA 2008/09 NEW 18 9 27 Bean Production Newly formed BWERANYANGE CHAMCHUZI TUKUMBUKANE 2008/09 NEW 7 9 16 Maize production Newly formed JITIHADA 2008/09 NEW 8 3 11 Beans production Newly formed WEKEZA 2008/09 NEW 13 11 24 Maize production Newly formed AZIMIA 2008/09 NEW 12 3 15 Beans production Newly formed KIBONDO KAKURAIJO TEGEMEO 2008/09 NEW 0 18 18 Maize production Newly formed JIKOMBOE 2008/09 NEW 14 10 24 Beans production Newly formed MWANGAZA 2008/09 NEW 19 11 30 Maize production Newly formed TUJENGE 2008/09 NEW 15 9 24 Beans production Newly formed KIBONDO UJASIRIAMALI 2008/09 NEW 16 13 29 Banana Production Newly formed TUSHEMERERWE 2008/09 NEW 7 9 16 Bean Production Newly formed TULIZA 2008/09 NEW 8 3 11 Banana Production Newly formed ZALISHA 2008/09 NEW 7 9 16 Bean Production Newly formed IHEMBE IHEMBE II MAENDELEO 2008/09 NEW 8 3 11 Beans production Newly formed HEKIMA 2008/09 NEW 13 11 24 Poultry production Newly formed MAPINDUZI 2008/09 NEW 12 3 15 Beans production Newly formed SAIDIA 2008/09 NEW 13 11 24 Poultry production Newly formed NYABIYONZA NYABIYONZA UMOJA 2008/09 NEW 8 3 11 Maize production Newly formed TUMAINI 2008/09 NEW 13 11 24 Beans production Newly formed SAIDIANA 2008/09 NEW 7 9 16 Maize production Newly formed UMOJA NI NGUVU 2008/09 NEW 8 3 11 Beans production Newly formed BUKANGARA UPENDO 2008/09 NEW 13 11 24 Maize production Newly formed TWEJUNE 2008/09 NEW 12 3 15 Beans production Newly formed TWIMANYE 2008/09 NEW 10 6 16 Maize production Newly formed ENDELEZA 2008/09 NEW 11 19 30 Beans production Newly formed NYAKAKIKA NYAKAKIKA MILENIUM 2008/09 NEW 16 9 25 Beans production Newly formed BUANGA 2008/09 NEW 16 9 25 Poultry production Newly formed KOMESHA 2008/09 NEW 14 11 25 Beans production Newly formed TAJIRIKA 2008/09 NEW 14 11 25 Poultry production Newly formed KAYUNGU TUELIMISHE 2008/09 NEW 13 12 25 Beans production Newly formed TWENDENI 2008/09 NEW 8 3 11 Banana Production Newly formed MAENDELEO 2008/09 NEW 8 3 11 Banana Production Newly formed CHAPAKA KAZI 2008/09 NEW 13 11 24 Maize Production Newly formed KIBINGO KIBINGO TUJIAJIRI 2008/09 NEW 7 9 16 Maize Production Newly formed UKAKAMAVU 2008/09 NEW 8 3 11 Maize production Newly formed MWANZO MGUMU 2008/09 NEW 13 11 24 Maize production Newly formed UMOJA 2008/09 NEW 12 3 15 Maize production Newly formed KIHINDA AMANI 2008/09 NEW 16 9 25 Maize production Newly formed FAGILIA 2008/09 NEW 16 9 25 Maize production Newly formed UMOJA 2008/09 NEW 13 4 17 Maize production Newly formed MWANGAZA 2008/09 NEW 19 11 30 Maize production Newly formed KIRURUMA NYAKAGOYAGOYE MAENDELEO 2008/09 NEW 15 9 24 Maize production Newly formed MAPAMBANO 2008/09 NEW 16 13 29 Maize production Newly formed MUUNGANO 2008/09 NEW 7 9 16 Poultry production Newly formed JITIHADA 2008/09 NEW 8 3 11 Poultry production Newly formed BUGENE BUJURUGA FARIJIKA 2008/09 NEW 14 11 25 Bees keeping Newly formed TUSAIDIANE 2008/09 NEW 14 11 25 Piggery production Newly formed KUJIAJIRI 2008/09 NEW 13 12 25 Maize production Newly formed YEAR NUMBER OF MEMBERS WARD VILLAGE NAME OF PFG FORMED GRADUATED Male Female Total ENTERPRISE REMARKS UMOJA NI NGUVU 2008/09 NEW 10 15 25 Maize production Newly formed LUKALE TWEKAZE 2008/09 NEW 0 23 23 Bean Production Newly formed AZIMIO 2008/09 NEW 10 10 20 Maize Production Newly formed TEGEMEO 2008/09 NEW 15 10 25 Horticultural Crops Newly formed TUJIKOMBOE 2008/09 NEW 10 6 16 Banana Wine Newly formed NDAMA NYABWEGIRA MABORESHO 2008/09 NEW 11 19 30 Banana Production Newly formed TUKOMBOANE 2008/09 NEW 18 9 27 Banana Production Newly formed DUNDULIZA 2008/09 NEW 14 11 25 Maize Production Newly formed SHIRIKIANA 2008/09 NEW 8 3 11 Maize Production Newly formed NYAKAHANGA OMURUSIMBI KAZIKAZI 2008/09 NEW 13 11 24 Banana Production Newly formed CHANGAMUKA 2008/09 NEW 13 12 25 Banana Production Newly formed TWENDE KAZI 2008/09 NEW 9 16 25 Maize Production Newly formed SHIRIKIANA 2008/09 NEW 14 11 25 Maize Production Newly formed NYAKASIMBI BUJARA OMURUBALE 2008/09 NEW 10 13 23 Beans production Newly formed CHAIBUMBA 2008/09 NEW 10 15 25 Maize production Newly formed TWEJUNE 2008/09 NEW 7 17 24 Beans production Newly formed KAINA 2008/09 NEW 9 16 25 Maize production Newly formed BUGOMORA NYAMIYAGA FANIKISHA 2008/09 NEW 14 11 25 Poultry Production Newly formed MAENDELEO 2008/09 NEW 8 3 11 Banana production Newly formed UMOJA 2008/09 NEW 13 11 24 Beans Production Newly formed IMARISHA 2008/09 NEW 14 11 25 Maize production Newly formed TOTAL 20 30 120 1447 1134 2577 DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) FINANCIAL STATUS OF NEWLY FORMED PARTICIPATORY FARMER GROUPS (PFGs) NAME OF DISTRICT: KARAGWE QUARTER; SECOND REPORTING DATE: 2 Jan 2009 YEAR: 2008/09 NAME OF REPORTING OFFICER: SAMUEL STAMBULI Annex 4 Contribution from DASIP (Tsh. ‘000) Number of PFG Members Village Male Female Total Type of Enterprise Total Cost (Tsh. ‘000) Group Contribution (Tsh. ‘000) Total Disbursed Balance Unallocated Balance (Tsh. ‘000) 15 11 26 Improved Banana production 938 438 500 0 500 0 0 14 10 24 Improved poultry production 938 438 500 0 500 0 0 16 9 25 Improved poultry production 938 438 500 0 500 0 0 KYERERE 19 11 30 Improved poultry production 938 438 500 0 500 0 0 14 11 25 Improved Onion production 1090 590 500 0 500 0 0 16 13 29 Improved Onion production 1402 902 500 0 500 0 0 15 9 24 Improved banana production 1208 708 500 0 500 0 0 KITWE 23 2 25 Improved poultry production 900 400 500 0 500 0 0 17 8 25 Improved maize production 900 400 500 0 500 0 0 10 15 25 Improved Banana production 1000 500 500 0 500 0 0 18 9 27 Improved poultry production 780 280 500 0 500 0 0 KIBIMBA 14 11 25 Improved poultry production 780 280 500 0 500 0 0 16 8 24 Improved banana production 1300 800 500 0 500 0 0 15 7 22 Improved maize production 1000 500 500 0 500 0 0 17 9 26 Improved poultry production 1000 500 500 0 500 0 0 BUSINDE 11 14 25 Improved beans production 1000 500 500 0 500 0 0 16 10 26 Improved Banana production 1000 500 500 0 500 0 0 18 9 27 Improved maize production 1300 800 500 0 500 0 0 10 14 24 Improved beans production 1000 500 500 0 500 0 0 ITEERA 14 13 27 Improved maize production 1300 800 500 0 500 0 0 16 9 25 Improved Banana production 1000 500 500 0 500 0 0 18 7 25 Improved Banana production 950 450 500 0 500 0 0 RWABWERE 18 9 27 Improved Tomato 1000 500 500 0 500 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members production 13 14 27 Improved Tomato production 1000 500 500 0 500 0 0 15 6 21 Improved coffee production 1100 600 500 0 500 0 0 14 15 29 Improved Banana production 900 500 500 0 500 0 0 7 9 16 Improved coffee production 1000 500 500 0 500 0 0 KIHANGA 15 10 25 Improved Poultry production 1000 500 500 0 500 0 0 8 3 11 Improved Banana production 1000 500 500 0 500 0 0 13 11 24 Improved Tomato production 1000 500 500 0 500 0 0 12 3 15 Improved Goat production 1000 500 500 0 500 0 0 KATERA 0 18 25 Improved poultry production 1000 500 500 0 500 0 0 14 7 21 Improved poultry production 1000 500 500 0 500 0 0 18 9 27 Improved Beans production 1000 500 500 0 500 0 0 5 7 12 Improved maize production 1000 500 500 0 500 0 0 KIBONA 10 5 15 Improved maize production 1000 500 500 0 500 0 0 15 10 25 Improved Beans production 1000 500 500 0 500 0 0 18 8 26 Improved Beans production 1000 500 500 0 500 0 0 11 15 26 Improved Banana production 1000 500 500 0 500 0 0 IGURWA 17 7 24 Improved maize production 1000 500 500 0 500 0 0 14 15 29 Improved maize production 1000 500 500 0 500 0 0 17 9 26 Improved coffee production 1000 500 500 0 500 0 0 12 13 25 Improved poultry production 1000 500 500 0 500 0 0 MASHESHE 12 14 26 Improved Banana production 1000 500 500 0 500 0 0 14 11 25 Improved poultry production 1100 600 500 0 500 0 0 8 3 11 Improved Banana production 1000 500 500 0 500 0 0 14 11 25 Improved maize production 1000 500 500 0 500 0 0 NYAMIYAGA 13 11 24 Improved Beans production 1000 500 500 0 500 0 0 10 13 23 Improved beans production 1000 500 500 0 500 0 0 10 15 25 Improved maize production 1000 500 500 0 500 0 0 7 17 24 Improved beans production 1000 500 500 0 500 0 0 BUJARA 9 16 25 Improved maize 1000 500 500 0 500 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members production 13 11 24 Improved Banana production 1000 500 500 0 500 0 0 13 12 25 Improved Banana production 1000 500 500 0 500 0 0 9 16 25 Improved maize production 1000 500 500 0 500 0 0 OMURUSIMBI 14 11 25 Improved maize production 1000 500 500 0 500 0 0 11 19 30 Improved Banana production 1000 500 500 0 500 0 0 18 9 27 Improved Banana production 1000 500 500 0 500 0 0 14 11 25 Improved maize production 1000 500 500 0 500 0 0 NYABWEGIRA 8 3 11 Improved maize production 1000 500 500 0 500 0 0 0 23 23 Improved Beans production 670 170 500 0 500 0 0 10 10 20 Improved maize production 640 140 500 0 500 0 0 15 10 25 Improved Onion production 775 275 500 0 500 0 0 LUKALE 10 6 16 Banana wine 829.5 329.5 500 0 500 0 0 26 12 38 Vegetable production 1000 500 500 0 500 0 0 4 16 20 Maize Production 1000 500 500 0 500 0 0 13 12 25 Improved poultry production 1000 500 500 0 500 0 0 NYAKAYANJA 10 8 18 Vegetable production 1000 500 500 0 500 0 0 4 14 18 Improved Maize production 1000 500 500 0 500 0 0 16 9 25 Improved Beans production 1000 500 500 0 500 0 0 14 12 26 Improved poultry production 900 400 500 0 500 0 0 KAYANGA 18 9 25 Improved Beans production 1000 500 500 0 500 0 0 7 16 13 Improved Maize production 1000 500 500 0 500 0 0 8 3 11 Improved Beans production 1200 700 500 0 500 0 0 13 11 24 Improved Maize production 1000 500 500 0 500 0 0 CHAMCHUZI 12 3 15 Improved Beans production 1000 500 500 0 500 0 0 0 15 15 Improved Tree Nursery 750 250 500 0 500 0 0 14 10 24 Improved Poultry production 1000 500 500 0 500 0 0 19 11 30 Improved Poultry production 753 253 500 0 500 0 0 KAKURAIJO 15 9 14 Improved Beans production 1000 500 500 0 500 0 0 16 13 29 Improved banana production 1000 500 500 0 500 0 0 KIBONDO 7 9 16 Improved Beans 1000 500 500 0 500 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members production 8 3 11 Improved banana production 1000 500 500 0 500 0 0 12 14 26 Improved Beans production 1000 500 500 0 500 0 0 8 3 11 Improved Beans production 1000 500 500 0 500 0 0 13 11 24 Improved poultry production 1000 500 500 0 500 0 0 12 3 15 Improved Beans production 1000 500 500 0 500 0 0 IHEMBE II 13 11 24 Improved poultry production 1000 500 500 0 500 0 0 8 3 11 Improved maize production 1000 500 500 0 500 0 0 13 11 24 Improved Beans production 1000 500 500 0 500 0 0 7 9 16 Improved maize production 1000 500 500 0 500 0 0 NYABIYONZA 8 3 11 Improved Beans production 1000 500 500 0 500 0 0 13 11 24 Improved maize production 1000 500 500 0 500 0 0 12 11 23 Improved Beans production 1000 500 500 0 500 0 0 10 24 24 Improved maize production 1000 500 500 0 500 0 0 BUKANGARA 15 10 25 Improved Beans production 1000 500 500 0 500 0 0 16 9 25 Improved Beans production 1000 500 500 0 500 0 0 17 9 26 Improved poultry production 1000 500 500 0 500 0 0 20 10 30 Improved Beans production 1000 500 500 0 500 0 0 NYAKAKIKA 13 13 26 Improved pig production 1000 500 500 0 500 0 0 13 12 25 Improved banana production 1000 500 500 0 500 0 0 8 15 23 Improved maize production 1000 500 500 0 500 0 0 10 11 21 Improved banana production 1000 500 500 0 500 0 0 KAYUNGU 13 11 24 Improved Beans production 1000 500 500 0 500 0 0 13 12 25 Improved maize production 1000 500 500 0 500 0 0 14 11 25 Improved maize production 1000 500 500 0 500 0 0 12 14 26 Improved maize production 1000 500 500 0 500 0 0 KIBINGO 8 15 23 Improved maize production 1000 500 500 0 500 0 0 16 9 25 Improved maize production 1000 500 500 0 500 0 0 16 9 25 Improved maize production 1000 500 500 0 500 0 0 KIHINDA 13 4 Improved maize production 1000 500 500 0 500 0 0 Contribution from DASIP (Tsh. ‘000) Number of PFG Members 13 17 30 Improved maize production 1000 500 500 0 500 0 0 15 9 24 Improved poultry production 1000 500 500 0 500 0 0 16 13 29 Improved poultry production 1000 500 500 0 500 0 0 7 9 15 Improved maize production 1000 500 500 0 500 0 0 NYAKAGOYAGO YE 15 10 25 Improved maize production 1000 500 500 0 500 0 0 14 11 25 Improved bees keeping 1000 500 500 0 500 0 0 16 9 25 Improved piggery production 1000 500 500 0 500 0 0 13 12 25 Improved maize production 1000 500 500 0 500 0 0 BUJURUGA 10 15 25 Improved maize production 1000 500 500 0 500 0 0 1529 1262 223 122,527.5 179,653 60,000 60,000 | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA PRIME MINISTERS OFFICE REGIONAL ADMINISTRATION AND LOCAL GOVERNMENT KIGOMA REGION KASULU DISTRICT COUNCIL DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ANNUAL PROGRESS REPORT:- JULY,2009 – JUNE, 2010 PREPARED BY: Justinian K. Muchunguzi. DMEO 15th JULY, 2010 KIL3/Annual report 2009-10- Kasulu 1 DASIP KIL3/Annual report 2009-10- Kasulu 2 DASIP 1.0 TABLE OF CONTENT CONTENTS PAGE 1. Table of contents…………………………………………………………………..2 2. Executive summary …………..……………………………………………………3 3. Introduction………………………………..……..………………………………….4-5 4. List of abbreviations/Acronyms .…………………………………………………..6 5. Planned activities……………………………………………………………………7 6. Implementation status…………………………………………………………….7-11 7. Output and Results………………………………………………………………. ..11 8. Challenges and Problems ………………………………………………………….12 9. Lesson Learnt…………………………………………………………………………13 10. Recommendation…………………………………………………………………....13 11. The way forward……………………………………………………………………..13-14 12. Annex: Matrix of the status of village micro Projects ……………………………..15-16 Matrix of Resource (financial) Utilization………………………………….17 Matrix of Farmer Field Schools status……………………………………..18 KIL3/Annual report 2009-10- Kasulu 3 DASIP 2.0 EXECUTIVE SUMMARY During the year 2009/10 Kasulu District council planned to implement 6 activities under farmer capacity building component which are; formation of 180 Participatory Farmer Group (PFGs), training of 20 and 30 farmer facilitators in business planning and management, facilitation of the so formed 180 PFGs in undergoing a season long training on various crop and livestock enterprises, to organize and facilitate selected farmers and extension staff participate in Nane Nane show at district level. Other activities under the same component included ;facilitation of 146 PFGs which graduated in the 2008/9 season establish and manage min income generating activities and facilitation of 15 selected PFGs acquire 15 power tillers. Almost all of the above mentioned activities were successfully implemented except facilitation of PFGs to initiate min income generating projects whose performance reached 35% and for the case of power tillers none of the groups acquired one. Activities planned under the component of community planning and investment in Agriculture are; follow up backstopping on planning using O&OD method at ward and village levels aiming at producing quality VADPs and construction of market shed in seven villages. Backstopping of the 2010/11 planning process was carried out in all DASIP supported villages and then processed and compiled to form the district plan. The national team that assessed the 2010/11 DADPs ranked Kasulu district above average with a score of 66.25%. The status of market shed at the end of June, 2010 was at different stages of construction; Kalela,Kwaga,and Nyankoronko village were still mobilizing local building materials, in Kabanga and Migunga village the construction work was at foundation stage, in Karunga and Muhunga village construction work was at ring beam and roofing stage respectively. During the year under review, Kasulu district received a total of Tsh. 349,390,000/= out of which Tsh.306, 188,500/= was spent and the balance at the of the year was Tsh. 43,201,500/= Major challenges experienced during the year are slow pace of the community in mobilizing local building materials and stringent conditions put by the bank in opening group account. These challenges made it difficult for the district to attain its annual target of constructing seven market sheds and facilitating 146 PFGs establish min income generating projects. The district responded to these challenges by undertaking community sensitization sessions in villages which lagged behind in mobilization of building materials. For the PFGs which experienced difficulties in raising Tsh.100, 000/= (one hundred thousand) which is a minimum amount to open bank account have been assisted by allowing them to spend a part of their Tsh.4000/= min grant in opening a bank account. The project is at its third year of implementation which is its half life time thus a right time for being reviewed. The review for Kasulu district was held in March, 2010 at Kigoma municipal council hall. The review concentrated on assessing our adherence to laid down procurement procedures. The district presented samples of procurement documents for sixteen randomly selected civil works implemented in a three year DASIP life span. The result of the review indicated that the performance was satisfactory. As away forward the district intends to implement the following activities in the year 2010/11; to complete all infrastructures which were not completed in previous years, to construct additional/missing structures such as toilets and tables, support 180 PFGs which graduated in 2009/10 season undertake min income generating activities, Construction of market shed in Muzye/Mutala,Mubanga and Munanila village, and KIL3/Annual report 2009-10- Kasulu 4 DASIP construction of a crop storage structure in Kurugongo village. Other activities include; to facilitate the development of Kabanga irrigation scheme, facilitate the 2011/12 planning process in the 30 DASIP supported villages, sensitization of PFG members on the importance of SACCAS and SACCOS and training of SACCAS and SACCOS leaders on saving and credit policy, leadership and management skills 3.0 INTRODUCTION The District Agriculture Sector Investment Project (DASIP) has the goal of reducing poverty among smallholder farmers in the project area. Its specific objective is to increase productivity and incomes of rural households, within the framework of the Agricultural Sector Development Strategy (ASDS). Kasulu district council is implementing DASIP in thirty villages well distributed in the two agro ecological zones of the district. The low land zone which is a maize/cassava dominated zone has 16 villages and the plateau/highland zone dominated by banana/coffee farming system has 16villages implementing DASIP supported activities. The project has three major field components and one project management component which are: • Farmer Capacity Building component • Community Planning and Investment in Agriculture • Support to Rural Micro-finance and Marketing • Project monitoring and supervision/Project Coordination. However, Kasulu District Council is so far implementing two field components namely; (i) Farmer Capacity Building and (ii) Community Planning and Investment in Agriculture. The component; Support to rural micro-finance and marketing has not yet been implemented at district level, the only activity implemented since project inception is training of District cooperative officer on how to strengthen SACCOS in DASIP supported villages The training was organized and implemented by Project Coordination Unit in which each district was represented by one cooperative officer. The Farmer Capacity Building component deals with training of farmers through Participatory Farmer Groups (PFGs) in which each group is comprised of 25 farmers on average. They are trained in technical, organizational and managerial subject matters through participatory adult learning methods whereby Farmer Field School is the dominant extension method applied. Under the component of Community planning and Investment in Agriculture, the project facilitates village and district level planning process, implementation of agriculture related micro projects, small infrastructure and agricultural technology investments. In order to achieve the above stated goal and objective the project has been financing a number of activities for the last three consecutive financial years whose progress have been reported in the previous reports. KIL3/Annual report 2009-10- Kasulu 5 DASIP Activities planned for the year 2009/2010 are: • Formation of 180 Participatory Farmer Groups in 30 DASIP supported villages • Training of 20 WTFs and 30 Farmer Facilitators in business planning and management • Facilitation of the so formed 180 PFGs in undergoing a season long training • Facilitation of the 2009 Nane Nane show • Facilitation of 146 PFGs which graduated in 2008/9 to establish and manage mini income generating projects • Facilitate farmer groups acquire 15 power tillers • Construction of market shed in the following villages; Kwaga(1); Kalela(1); Kabanga(1);Karunga(2); Muhunga(2); Nyankoronko(1); and Migunga(2)m accomplished in Kalela,Karunga,Muhunga,Nyankoronko,and Migunga. • Regular monitoring and supervision of field activities During the financial year 2009/2010; Kasulu District Council received a total of Tsh 349,390,000/=(three hundred forty nine million, three hundred ninety thousand only) out of which Tsh. 306,188,500/= (three hundred and six thousand million, one hundred eighty eight thousand five hundred only) was spent and the balance at the end of June is Tsh.43,201,500/=( forty three million, two hundred and one thousand five hundred only). About 90% of the balance is the money meant for supporting PFGs to invest in mini income generating activities .Farmers in participatory farmer groups ex These difficulties led to a delay in opening bank accounts so a delay in transferring funds into PFGs’ bank accounts. This report reflects on planned activities and corresponding achievements by component, brief description of results and output so far realized, it ends by giving highlights on challenges encountered and some recommendations. At the end of the report there are three annexes; Matrix indicating the current status of village micro projects; Number Farmer Field Schools formed per year, and Matrix of resource/finance Utilization KIL3/Annual report 2009-10- Kasulu 6 DASIP 4.0 LIST OF ABBREVIATIONS AfDB African Development Bank DALDO District Agriculture and Livestock Development DPLO District Planning Officer DDP District Development Plans DADP District Agricultural Development Plan DASIP District Agriculture Sector Investment Project DFTs District Facilitation Team DMEO District Monitoring and Evaluation Officer DPO District Project Officer FFS Farmer Field School FFs Farmer Facilitators FP Farmers Practices IPM Integrated Pest Management ICM Improved Crop Management M & E Monitoring and Evaluation MAFC Ministry of Agriculture Food Security and Co-operatives DMEO District Monitoring and Evaluation Officer O & OD Opportunities and Obstacles to Development PC Project Coordinator PCU Project Co-Ordination Unit PFGs Participatory Farmer Groups VADPs Village Agricultural Development Plans WFTs Ward Facilitation Team SACCOS Saving and Credit Cooperative Society KIL3/Annual report 2009-10- Kasulu 7 DASIP 5.0 PLANNED ACTIVITIES FOR 2009/2010 5.1 Farmers Capacity Building • Formation of 180 Participatory Farmer Groups in 30 DASIP supported villages • Training of 20 WTFs and 30 Farmer Facilitators in business planning and management • Facilitation of the so formed 180 PFGs in undergoing a season long training • Facilitation of the 2009 Nane Nane show • Facilitation of 146 PFGs which graduated in 2008/9 establish and manage mini income generating projects • Facilitate graduation of 171 PFGs formed in 2008/9 • Facilitate farmer groups acquire 15 power tillers 5.2 Community Planning and Investment in Agriculture • Construction of market shed in the following villages; Kwaga(1); Kalela(1); Kabanga(1);Karunga(2); Muhunga(2); Nyankoronko(1); and Migunga(2) • Follow up backstopping on planning using O & OD method at ward and village levels aiming at producing quality VADPs/DADPS for 2010/11) • Monitoring and supervision of completed, on going and new project activities 6.0 IMPLEMENTATION STATUS 6.1Farmers Capacity Building component Formation of Participatory Farmer Groups for 2009/10 season The annual target was to form 180 Participatory Farmer Groups (PFG), with an average of six groups in each of the thirty DASIP supported villages. All 180 targeted groups have been formed during the year under review. The 180 PFGs consist of 4,551 members, out of which 2,088 are male and 2,463 female. They are involved in 86 crop and 94 livestock enterprises. While Livestock enterprises of interest are piggery and poultry (chicken), crops are maize, cassava and beans. Training of 20 WTFs and 30 Farmer Facilitators in business planning and management. The objective of the training was to equip both Ward Training Facilitators and Farmer Facilitators with knowledge and skills which will enable them facilitate graduate members of PFGs prepare sound business plans to qualify for DASIP min grant worthy Tsh.400,000/= per farmer group. Training of Ward Training Facilitators (WTFs) and Farmer Facilitators were conducted at Kabanga Teachers Training College at two different sessions. The first session included 30 Farmer Facilitators (25 male and 5 female) and lasted for six days from 19/10/2009 - 24/10/2009. Participants were drawn from the 30 DASIP supported villages, one participant from each of village. All targeted participants attended as intended. The district Training coordinators were the full time trainers. Topics covered included; Farming as a business, Enterprise Analysis and selection, Guidelines for preparing a business plan and Brief introduction to National Input Subsidy Program. Training of ward training facilitators was conducted for six consecutive days from 26/10/2009 to 31/10/2009. A total number of participants attended were 22 out of 20 KIL3/Annual report 2009-10- Kasulu 8 DASIP targeted, the additional costs was partly met by DALDO’s office. Out 22 participants attended, 20 were male and 2 female. Trainers were the two District Training Coordinators (DTCs) one with specialty in crops and another one in livestock. Topics covered included; Farming as a business, Enterprise Analysis and selection, Guidelines for preparing a business plan and Brief introduction to National Input Subsidy Program The major challenge encountered was inadequate budget allocated to this activity, for instance there was no budget for venue and no consideration for lactating mothers who attended along with their young children and care takers. Facilitation of PFGs in undergoing a season long training This activity started soon after the completion of an exercise that led to the formation of 180 groups. Processing of funds meant for the group’s inputs, stationeries and other associated cost has been done for all 180 groups. The fund has been remitted into the respective PFG’s bank account. The groups are being facilitated by staff and farmer facilitators in organizational and technical knowledge and skills depending on the nature of enterprise the group is dealing with. Facilitation of 146 graduate PFGs establish and manage mini income generating projects Implementation of this activity is confronted with difficulties experienced by PFGs in opening bank accounts. They are required to have a written constitution, opening cash of not less than Tsh.100, 000/= and to be legally registered at least as a community based organization. These conditions are met by a few groups. During the period under review it is only 51 (fifty one) groups out of 146 have managed to fulfill the said conditions and hence able to open bank account to date. Therefore processing and transferring of funds for mini income generating activities have been done for 51 (fifty one) groups only. The amount of funds transferred into PFG’s account up to the end of June, 2010 is Tsh.20, 400,000/= out of Tsh.58, 400,000/= received by the council for this activity. Extra efforts are being done to facilitate the remaining groups to meet the set conditions. The district authority decided to use part of the grant (Tsh.100, 000/= for each group) to be used by the respective groups to open bank account. Other efforts include facilitating group leaders on how to write constitutions and where to register their groups. Facilitate graduation of Participatory Farmer Groups formed in 2008/9 season A total of 171 groups were formed and under went a season long training during the 2008/09 season. At the end of season only 146 PFGs with 2,519 farmers qualified and have been awarded certificates of attendance. This is equivalent to about 70% achievement, the 30% drop out included those who joined the groups for direct personal benefits like farm inputs, cash, etc. KIL3/Annual report 2009-10- Kasulu 9 DASIP Facilitate farmer groups acquire 15 power tillers Sensitization was conducted in all 30 DASIP supported villages to introduce the community on the importance of power tiller, available DASIP financial support and farmer’s 20% contribution towards the cost of this farm implement. Interested groups submitted their requests to DALDO’s office; the requests were evaluated and short listed. As an output of this activity the following participatory farmer groups qualified for being given power tiller upon payment of Tsh.1, 600, 000/= per power tiller as a group contribution. However most groups requested to pay the 20% at least in two installments. Table: 1 Participatory Farmer Groups ready to receive Power tiller S/NO VILLAGE NAME OF PFG No OF P.TILLER 01 Kabanga Boresha 1 02 Migunga Juhudi 1 03 Murufiti Chapa Kazi 1 04 Rungwe Mpya Juhudi Youth Group 1 05 Asante Nyerere Ajira 1 06 Bugaga Tugeze 1 07 Muzye/Mutala Kazamwendo 1 08 Kalela Fanikio 1 09 Buhoro Kimabu 1 10 Kitema Upendo 1 11 shunga Tujikomboe 1 12 Kibwigwa Umuntu Kuundi 1 13 Kitambuka Lete baraka 1 14 Mubanga kapfunya 1 15 Janda omaka 1 TOTAL 15 5.2 Community Planning and Investment in Agriculture 5.2.1 Construction of market shed in the following villages; Kwaga(1); Kalela(1); Kabanga(1);Karunga(2); Muhunga(2); Nyankoronko(1); and Migunga(2) Construction of one market shed at Kwaga village No construction work has taken place to date due to two major reasons namely failure to receive competitive bidders and low pace of community in mobilizing local building materials. The village advertised the tender several times without response from bidders, at last two bidders responded in May, 2010 and the tender was awarded to one of the two bidders. The community has already mobilized local building materials, the construction work is scheduled to commence early July, 2010. Construction of one market shed at Kalela village The village experienced similar problems mentioned above (Kwaga village) thus no construction work was done during the reporting period. As it was a case in Kwaga village, a tender was at last awarded in late June, 2010. The contractor is scheduled to KIL3/Annual report 2009-10- Kasulu 10 DASIP begin construction work in early July, 2010.The community is still mobilizing local building materials. Construction of one market shed at Kabanga village Kabanga village decided to use quotation method after advertising twice without response. The contract between the contractor and village project supervision committee was signed in late May, 2010 and construction began in mid June, 2010. The civil works completed include site clearance, setting out, excavation of foundation trench and construction of foundation wall. Construction of a two sheds market at Karunga village The civil works completed so far include site clearance, setting out, excavation of foundation trench, construction of foundation wall, vertical columns and hard core. The work on progress are setting form work and casting ring beam. Construction of a two sheds market at Muhunga village Generally the work is progressing well, completed works include; site clearance, setting out, excavation of foundation trench, construction of foundation wall, vertical and horizontal(ring beam) columns and hard core. The contractor is progressing with roofing. Construction of a two sheds market at Migunga village Although procurement procedures and awarding of the work was completed on time, the contractor did not begin on time because the community took time to mobilize local building materials. The contractor started the work in mid June, 2010,the works done so far include site clearance, setting out, excavation of foundation trench and construction of foundation wall. Construction of a one shed market at Nyankoronko village Like other villages with a budget for a one market shed, Nyankoronko village experienced dump hear from the bidders. The village advertised twice without response, three bidders appeared during the third tender re advertisement out of which the work was awarded to M/s Sumiye building contractors. Surprisingly the company did not turn up to sign the contract, thus the village project committee decided to go for quotation but the approach was also not successful. The district authority is thinking of using force account. As a result of this problem even the community has failed to complete mobilization of the required local building materials. 5.2.2 Backstopping planning exercise at ward and village levels using O & OD method aiming at producing quality VADPs/DADPS for the year 2010/11) This activity was undertaken at two levels; it started with facilitating /training members of the district and ward facilitation teams. This training was attended by twenty five ward facilitators and six district facilitators. A national facilitator facilitated this training which lasted for two days on 11/2/2010 and 12/2/2010. This training equipped participants with knowledge on how to prepare a quality VADP and then DADPs After the training members of the district and ward facilitation teams back stopped planning exercise in fifteen (15) DADP and thirty (30) DASIP villages. Since 26 villages KIL3/Annual report 2009-10- Kasulu 11 DASIP out of 30 have already consumed its budget for micro projects, therefore the 2010/11 budget has included four villages which have not yet spent their budget. The villages include; Munanila (2 markert shed), Mubanga(2 market sheds), Muzye/Mutala(1 market shed),and Kurugongo( crop storage structure). 5.2.3 Mid term review of the District Agriculture Investment project The project is at its third year of implementation which is its half life time thus a right time for being reviewed. The review for Kasulu district was held in March, 2010 at Kigoma municipal council hall. The review concentrated on assessing our adherence to laid down procurement procedures. The district presented samples of procurement documents for sixteen randomly selected civil works implemented in a three year DASIP life span. At the time of writing this report the results of the review was not yet communicated to the district authority. 5.2.4 Monitoring and supervision of the Project activities Monitoring and supervision of new project activities (2009/10), completed and on going projects whose implementation started in the previous years was undertaken as planned. At least two supervisory visits were done to most of civil work projects and one visit to each Participatory Farmer Group. As usual, the above mentioned activity was carried out in a participatory manner in which the monitoring and evaluation team not only included technical staff but also farmers, members of the village project committee and village leaders. In most cases the district team comprised of DALDO, DPO, DMEO, DTCs, internal auditor/project accountant and district civil engineer. 7.0 OUTPUT AND RESULTS SO FAR ACHIEVED All 30 DASIP supported villages have been able to prepare Village Agricultural Plans for the three consecutive years of its existence Cattle morbidity and mortality rates due to tick born diseases have gone down in seven villages where dips have been constructed The project has so far enabled 780 farmers in 13 villages acquire conducive environment/market shed where they display their agricultural produce for marketing(selling) The number of households adopting poultry and piggery enterprise is increasing in DASIP supported villages. This is exemplified by the number of PFGs which have opted to take livestock as their study enterprise in the 2009/10 season. Out of 176 PFGs which were registered during the July-December period,94 are livestock enterprises and the remaining 82 are crop enterprises The number of farmers practicing cross breeding to improve local breeds of chicken in DASIP supported and neighboring villages has increased by five percent in one season. It has been noted that the number of farmers adhering to improved practices like vaccination of local chicken is also increasing. Following good results of some PFGs in the previous seasons, more farmers came forward to form farmer groups. Although each village is allowed to register a maximum of six farmer groups per year, above 30% of DASIP supported villages have registered more than six groups by the end of December, 2009. KIL3/Annual report 2009-10- Kasulu 12 DASIP The number of farmers joining PFGs has tremendously increase from 3,193(2008/9) in 171 groups to 4,439(2009/10) in 176 farmer groups The number of female farmers joining PFGs has also increased from 1,475(2008/9) in 171 groups to 2,351(2009/10) in 176 farmer groups Some farmer groups have acquired permanent land by buying plots in their villages. This will automatically reduce tendency of being tenants which in most cases results in acquiring marginal land. Example of such groups is Eden which bought a two acre plot in Munzeze village at a cost of Tsh five hundred thousand. 8.0 CHALLENGES AND PROBLEMS A number of challenges and problems were encountered during the period under review. While some challenges were within the capacity of beneficiaries and the district council to adequately address them others were not. Some of the challenges met during the year under review include the following. The community does not acknowledge that procurement of community projects like construction of infrastructures such as cattle dips, market sheds and the like is guided by established rules (laws) and procedures that have to be complied with. The community would like to see that the power of awarding tenders be accorded to them and hence finalized at community level. They don’t easily accept that it is only the accounting officer(DED) who has experts and procurement instruments recognized by the law such as TCB and PMU and hence has the power of awarding the tender. In most villages mobilization of community contribution for civil works is done at a very slow pace thus significantly contributing to delay in completing civil works We experienced a few or no response from civil companies for the civil works which are located in remote areas and with small in terms of value (one shed). As we go along implementing project activities we are experiencing a drop out of Ward Training Facilitators who are being replaced by new staff with no knowledge on how DASIP operates. A condition that each PFG has to open its own bank account is confronted with lack of legally recognized financial institutions (micro finance) in rural areas. All groups have to open bank account at the sole NMB located at the district head quarter, this not only adds the cost to the group but also is time consuming. During PFG formation exercise we experienced a challenge of female farmers in some villages preferring to form groups which are solely women Although the project insists on PFGs to invest in agricultural related projects/activities, we have observed some PFGs suggesting to invest the min grant fund in non agricultural related income generating projects which they think are quickly rewarding and more profitable. It is taking too long from when one initiates application of funds to a time when a cheque is released. This is also slowing down the implementation and some times leading to poor performance of crop enterprises as farmers find themselves not matching with the season 9.0 LESSON LEARNT • Use of participatory approach in monitoring and supervision of project activities built KIL3/Annual report 2009-10- Kasulu 13 DASIP Procurement procedures under community based projects are not clearly understood by members of the village micro project supervisory committees and the village governments on how tendering process is being undertaken. They would like to see the tender evaluation and awarding being finalized at village level unlike the current situation whereby tenders are awarded at district level • Participatory monitoring approach which involved technical staff ,farmers, members of the village project supervision committee and village leaders facilitated the implementation and strengthened the capacity of the community to supervise, monitor and own project activities • Some farmer facilitators have proved to effective in organizing and constantly facilitating farmers in their learning process • Awarding certificates to farmers who successfully attended a season long training together with good performance of the study enterprises really impressed other farmers as a result more farmer showed interest and came forward to field schools in the 2009/10 season • The infrastructures and capacity built among farmers by DASIP have laid down a good base for other projects operating in the area. 10.0 RECOMMENDATIONS More community sensitization on the procedures governing procurement of community based projects is very necessary. Use of local radio (FM radio) such as Kwizera and radio Free Africa can assist to diffuse the information to a wider community Recruitment of farmer facilitators as means of bridging the gap of inadequacy of field staff should go hand in hand with provision of incentives. Farmers and staff exchange visits (study tour) within and outside the district should be promoted to speed up adoption of improved technologies Refresher training to Ward Training Facilitators on FFS methodology should be undertaken as a 20 days training done was not adequate. Project review meeting that will involve farmer representatives, implementers at lower and higher levels and other stakeholders should be done as the project has reached half life time. 11. WAY FORWARD During the year 2010/11, Kasulu district council envisages to undertake the following activities under the support of DASIP: To complete all infrastructures which were not completed within scheduled period of implemented To construct additional/missing structures such as toilets, tables and accaricide disposal pits which were not budgeted for in the previous years Support 180 PFGs which graduated in 2009/10 season undertake min income generating activities Construction of one market shed in Muzye/Mutala village Construction of a two shed market in Mubanga and Munanila village Construction of a crop storage structure in Kurugongo village Facilitate the development of Kabanga irrigation scheme Facilitate the 2011/12 planning process in the 30 DASIP supported villages Sensitization of PFG members on the importance of SACCAS and SACCOS KIL3/Annual report 2009-10- Kasulu 14 DASIP Training of SACCAS and SACCOS leaders on saving and credit policy, leadership and management skills Conduct a five days refresher training to Ward Training Facilitators and Farmer Facilitators on preparation of business plans KIL3/Annual report 2009-10- Kasulu 15 DASIP ANNEX 1; MATRIX OF VILLAGE MICRO PROJECTS STATUS UP TO THE END OF JUNE,2010 PROJECT COST (FUNDS Tsh’000) NAME OF PROJECT DASIP BENEF. TOTAL Tsh.’000 STATUS WARD MUNYEGERA VILLAGE MUGANZA Charcoal dam 10,000 Nil 10,000 Not yet completed To be completed Using DADPs funds BUHIGWE BUHIGWE Market shed(1) 14,982 Nil 14,982 Completed MSAMBARA KABANGA Rehabilitation of cattle dip 8,000 Nil 8,000 Completed YEAR MUNZEZE MUNZEZE Cattle dip rehabilitation 12,933,355 Nil 12,933 Completed 2007/8 KWAGA KWAGA Cattle dip rehabilitation 9,508,848 2,399,71 2 11,908,560 Completed BUHORO SHUNGA Market shed(2) 28,000 7,000 35,000 completed BUHIGWE BUHIGWE Market shed(1) 13,000 3,250 16,250 Finishing stage NYAMUNYUSI KITEMA Go down 28,000 7,000 35,000 Completed BUHIGWE NYANKORONKO Cattle dip 13,000 3,250 16,250 Completed MUNZEZE MUNZEZE Market shed(2) 15,000 3,750 18,750 Completed JANDA JANDA Market shed(2) 28,000 7,000 35,000 Finishing stage RUSABA RUSABA Market shed(2) 28,000 7,000 35,000 Tables not yet built MUNANILA KIBWIGWA Market shed(2) 28,000 7,000 35,000 Completed MUNANILA KITAMBUKA Go down 28,000 7,000 35,000 Completed R/MPYA R/MPYA Market shed(2) 28,000 7,000 35,000 Completed MUZYE MUZYE/MUTALA Cattle dip 13,000 3,250 16,250 Completed MURUFITI MURUFITI Market she(2) 28,000 7,000 35,000 Completed KIL3/Annual report 2009-10- Kasulu 16 DASIP MUZYE BUGAGA Market shed(2) 28,000 7,000 35,000 Tables no yet built KWAGA KALELA Cattle dip 13,000 3,250 16,250 Completed KIGONDO KIDYAMA Cattle dip 27,700,000 6,925 34,625 Completed MUNANILA MWAYAYA Go down 28,000 7,000 35,000 Ring beam stage RUSESA RUSESA Market shed(2) 28,000 7,000 35,000 Completed R/MPYA A/ NYERERE Market shed(2) 28,000 7,000 35,000 Completed BUHORO BUHORO Market shed(2) 28,000 7,000 35,000 Completed KASULU MJINI KUMSENGA/MU RUBONA Market shed(2) 28,000 7,000 35,000 Completed 2008/9 TITYE SHUNGULIBA Market shed(2) 28,000 7,000 35,000 Completed KALELA Market shed(1) 15,000 3,750 18,750 Foundation stage KWAGA KWAGA Market shed(1) 15,000 3,750 18,750 Mobilization of building material MSAMBARA KABANGA Market shed(1) 15,000 3,750 18,750 Foundation stage KARUNGA Market shed(2) 28,000 7,000 35,000 Ring beam stage MUHUNGA MUHUNGA Market shed(2) 28,000 7,000 35,000 Roofing stage BUHIGWE NYANKORONKO Market shed(1) 15,000 3750 18,750 Tender already awarded 2009/10 RUHITA MIGUNGA Market shed(2) 28,000 7,000 35,000 Foundation stage KIL3/Annual report 2009-10- Kasulu 17 DASIP ANNEX; II: MATRIX OF RESOURCE (FINANCIAL) UTILIZATION JULY,2009-JUNE, 2010 DISTRICT- KASULU, REPORTING PERIOD- JULY-JUNE, 2009/10 COMPO NENT SUB COMPONE NT ACTIVITY FUND FROM DASIP EXPENDITU RE BALANCE COMMENTS Formation of PFGs for 2009/10 2,300,000 2,300,000 - Season long training of 180 PFGs 90,000,000 90,000,000 - Training of Farmer Facilitators 3,935,000 3,935,000 - Training of WTF on business plan 5,407,000 5,407,000 Min grants for 146 PFGs 58,400,000 20,400,000 38,000,000 Farmers’ capacity building Sub Total 160,042,000 122,042,000 38,000,000 Market shed- Kalela village 15,000,000 15,000,000 - Market shed-Kwaga village 15,000,000 15,000,000 - Market shed-Kabanga village 15,000,000 15,000,000 - Market shed-Karunga village 28,000,000 28,000,000 - Market shed-Muhunga village 28,000,000 28,000,000 - Market shed-Nyankoronko village 15,000,000 15,000,000 - Market shed-Migunga village 28,000,000 28,000,000 - Sub Total 144,000,000 144,000,000 000,000 Storage structure-Kitema 6,846,000 6,846,000 - Storage structure-Kitambuka 6,846,000 6,846,000 - Storage structure-Mwayaya 6,846,000 6,846,000 - Community micro projects Sub Total 20,538,000 20,538,000 000,000 2010/11 DADP planning process 8,220,000 7,166,000 1,054,000 Commu nity Plannin g and Investm ent in Agricult ure Community Planning Sub Total 8,220,000 7,166,000 1,054,000 Funds was transferred into the respective village project account Office operating expenses(DTCs) 1,200,000 900,000 300,000 M/cycle operating & maintenance 1,920,000 1,440,000 480,000 Field allowances(DTCs) 1,300,000 975,000 325,000 Sub Total(DTCs) 4,420,000 3,315,000 1,105,000 Office operation (DMEO/DPO) 1,500,000 1,125,000 375,000 M/cycle operating /maintenance 1,920,000 1,440,000 480,000 Field allowances(District staff) 8,750,000 6,562,500 2, 187,500 Project Coordin ation Monitoring and supervision Sub Total(DMEO/DPO) 12,170,000 9,127,500 3,042,500 TOTAL 349,390,000 306,188,500 43,201,500 KIL3/Annual report 2009-10- Kasulu 18 DASIP ANNEX III: NUMBER OF FARMER FIELD SCHOOLS FORMED SINCE PROJECT INCEPTION TO JULY,2010 DISTRICT; KASULU - REPORTING PERIOD; JULY, 2009-JUNE,2010 NUMBER OF FFS (PFGs) NUMBER OF MEMBERS YEAR WARD VILLAGE CROPS LIVESTOCK OTHERS TOTAL F/MALE MALE TOTAL 2007/8 20 28 40 14 - 54 2008/9 20 30 136 35 - 171 1,475 1,718 3,193 2009/10 20 30 86 94 - 180 2,463 2,088 4,551 | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA PRIME MINISTERS OFFICE REGIONAL ADMINISTRATION AND LOCAL GOVERNMENT KIGOMA REGION KASULU DISTRICT COUNCIL DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) SEMI ANNUAL PROGRESS REPORT - JULY – DECEMBER, 2008 PREPARED BY: Justinian Mchunguzi. – DMEO 15th December,2008 KIL2/Kasulu dasip progres report qt2 08-09 1 DASIP CONTENTS PAGE 1. Basic Data………………………………………………………………………3 2. Introduction…………………………………………………………………….4 3. List of Abbreviations………………………………………………………….. 5 4. Changes in the Action Environment………………………………………….6 5. Fulfillment of loan conditions………………………………………………6-9 6. Progress of on going projects…………………………………………… 10-12 7. Progress of completed projects…………………………………………..13-14 8. Routine monitoring and supervision……………………………………..14-15 9. Financial status………………………………………………………………..16 10. Planned activities for January - March 2008/2009……………………17-18 11. challenges and Problems ………………………………………………….18 12. Recommendation…………………………………………………………18-19 KIL2/Kasulu dasip progres report qt2 08-09 2 DASIP 1. BASIC DATA DISTRICT NAME :Kasulu District Council PROJECT TITLE :District Agricultural Sector Investment Project (DASIP) EXECUTING AGENCY :Ministry of Agriculture, Food and Cooperative (MAFC) REPORT NO. :IV REPETING PERIODO :July-September,, 2008 PROJECT LOAN NUMBER :2100150008694 PROJECT LOAN AMOUNT : UA 36.00 Million – ADF (loan) OTHER SOURCES OF FINANCE FOR PROJECT: ♦ ADF (Grant) :UA 7.00 Million ♦ GOT :UA 6.64 Million ♦ Beneficiaries :UA 8.37 Million ♦ TOTAL :UA 58.01 Million DATE OF APPROVAL :November 2004 PROJECT LAUNCHING DATE :17th January 2005 PROJECT EXECUTING PERIOD : July 2005 for 6 years. LOAN CLOSING DATE :June 2012 PROJECT COMPONENTS: (i) Farmers capacity Building (ii) Community planning and Investment in Agriculture (iii) Support to Rural Financial Services and Marketing (iv) Project Coordination and Management PROJECT AREA: Twenty eight (28) District in Kagera, Kigoma, Mara, Mwanza and Shinyanga Region of Tanzania. KIL2/Kasulu dasip progres report qt2 08-09 3 DASIP 2. INTRODUCTION Although the period under review is from July to December, 2008, this report sheds light on all investment projects supported by DASIP since its inception to December, 2008. The reason behind is that some projects started in previous years are still on progress, we also need to track the progress of completed projects. The report therefore covers 31 projects which include; 19 markets sheds, 3 crop storage structures, 2 central pulp lies, 1 charcoal dam and 6 cattle dips. The 19 markets shed include 5 sheds for the 2008/9 financial year meant to be constructed in five villages. Out of 31 investment projects 23 are on going at different construction stages and 8 have been completed. Completed investment projects are 6 cattle dips and 2 central pulp lies, among the 6 cattle dips, 3 are providing intended services and the remaining 3 are still under curing period. Both central pulp lies are functioning and being maintained by beneficiary community. Under farmer capacity building component, the report covers achievement on the formation of 180 PFGs for 2008/9 season, facilitation of the 55 PFGs which graduated in 2007/8 in establishment of economic min projects, and training of 30 farmer facilitators. It also reports on monitoring and supervision of project activities by highlighting how the activity was undertaken and key findings during supervisory visits. The report also covers financial status for the period of July-December, 2008 in which the district received a total of TShs 309,725,848 whose expenditure and balance is given in the report. Planned activities for the third quarter (January-March) are also indicated. It ends by highlighting problems and challenges encountered during the implementation process. Major challenges that merit a mention include sharp increase in prices for industrial building materials, failure of some civil contractors to meet prescribed BOQ for the civil work given to them, and inadequate resources that made supervision and monitoring of field activities difficult. Lastly the report gives a few recommendations. KIL2/Kasulu dasip progres report qt2 08-09 4 DASIP 3. LIST OF ABBREVIATIONS AfDB African Development Bank DADP’s District Agricultural Development Plans DASIP District Agriculture Sector Investment Project DFTs District Facilitation Team DMEO District Monitoring and Evaluation Officer DPO District Project Officer FFS Farmer Field School M & E Monitoring and Evaluation MAFC Ministry of Agriculture Food Security and Co-operatives MEO Monitoring and Evaluation Officer O & OD Opportunities and Obstacles to Development PC Project Coordinator PCU Project Co-Ordination Unit PFGs Participatory Farmer Groups WFTs Ward Facilitation Team KIL2/Kasulu dasip progres report qt2 08-09 5 DASIP 4 CHANGES IN THE ACTION ENVIRONMENT As of now there has been no external event that has seriously caused irreversible negative effect to the project implementation. However sharp increase of industrial building materials is the only remarkable external event that has some how affected implementation of civil works. As was reported in the last quarter’s report brick making around the Muzye/Mutala cattle dip destroyed the environment. Village government leaders have been instructed by the district engineer to ensure that all the pit holes around the cattle dip are appropriately filled otherwise they will not be allowed to embark on building health facility they made bricks for. To conserve the environment around all cattle dips, a waste discharge tank is being excavated around each dip constructed. 5. FULFILLMENT OF LOAN CONDITIONS. NA PROJECT PROJECT AREA WORK DONE CONDITION FULLFILLED CONDITION NOT FULFILLED REMARKS 1 Procurement and installation of 2 coffee central pulperies Mwayaya & Munanila Construction of central pulperies building, Toilets and sewage system The facilities providing intended service Funds transferred to farmer groups bank account for implementation - Procurement of 2 central pulperies funded by sustainable harvest project. DASIP facilitated installation of the machines and accessories 2 Construction of market shed Buhigwe /Mulera Completed,finishi ng works on progress Tender advertisement and invitation Opening bank account Funds transfer to village bank account Project implemented at District level as it was quick win project 3 Construction of cattle dip Nyankolonko Construction completed Opening bank account Tender advertisement Funds transfer to village bank account - Dip committee will be trained in Jan.2009 on dip management 4 Expansion of market shed Buhigwe/ Mulera Training Mobilization of building maderials Foundation completed Opening bank account Tender advertisement and invitation Funds transfer to village bank account - - 5 Construction of cattle dip Kalela Construction completed Opening bank account Tender - Dip committee KIL2/Kasulu dasip progres report qt2 08-09 6 DASIP advertisement Funds transfer to village bank account will be trained in jan. 2009 using DADP funds 6 Construction of market shed Munzeze Ring beam level Opening bank account Tender advertisement Funds transfer to village bank account - - 7 Construction of godown Kitambuka Roofing stage Opening bank account Tender advertisement Funds transfer to village bank account - - 8 Construction of market shed Kibwigwa Training Mobilization of building materials Excavation of foundation completed Opening bank account Tender advertisement Funds transfer to village bank account - The first contractor was terminated, the work re advertised then awarded to a new contractor 9 Construction of godown Mwayaya Foundation and concrete floor construction stage Opening bank account Tender advertisement Funds transfer to village bank account - The first contractor has sub contracted another contractor 10 Construction of market shed Muganza Completed,finishi ng work in progress Opening bank account Tender advertisement Funds transfer to village bank account - - 11 Construction of Godown Kitema Ring beam level Opening bank account Tender advertisement Funds transfer to village bank account - Inadequate bricks hence community insisted to fulfill its obligation - 12 Construction of market shed Shunga Roofing completed Construction of tables and finishing works on progress Opening bank account Tender advertisement Funds transfer to village bank account - - 13 Construction of market shed Bugaga Roofing stage Opening bank account Tender advertisement Funds transfer to village bank account - - KIL2/Kasulu dasip progres report qt2 08-09 7 DASIP 14 Construction of market shed Rusaba Ring beam constructed, Roofing structure on progress Opening bank account Tender advertisement Funds transfer to village bank account - - 15 Construction of market shed Murufiti Ring beam setting on progress after demolishing the first one Opening bank account Tender advertisement Funds transfer to village bank account - The contractor was instructed to demolish the ring beam and re do the same as per prescribed BOQ 16 Construction of market shed Janda Foundation and external walls completed Opening bank account Tender advertisement Funds transfer to village bank account - - 17 Construction of market shed Rungwe Mpya Roofing stage Opening bank account Tender advertisement Funds transfer to village bank account The contractor instructor instructed to do some improvement on the roofing structure 18 Construction of cattle dip Kidyama Construction work complete. The dip tank is under curing period Training Opening of bank account Tender advertisement Fund transferred to village bank account Training of dip committee will be done in Jan. 2009 19 Rehabilitation of cattle dip Kwaga Rehabilitation has been completed Opening bank account Tender advertisement Funds transferred to village account Training of dip committee will be done in Jan. 2009 20 Construction of charcoal dam Muganza 50% of work completed The remaining work will be financed by DADP 21 Construction of a two shed market Rusesa Mobilizing local building materials Opening bank account Funds will be transferred to village bank account upon fulfillment of community contribution KIL2/Kasulu dasip progres report qt2 08-09 8 DASIP 22 Construction of a two shed market Kumsenga/M urubona Mobilizing local building materials Funds will be transferred to village bank account upon fulfillment of community contribution 23 Construction of a two shed market Buhoro Mobilizing local building materials Opening bank account Funds will be transferred to village bank account upon fulfillment of community contribution 24 Construction of a two shed market Asante Nyerere Mobilizing local building materials Funds will be transferred to village bank account upon fulfillment of community contribution 25 Construction of a two shed market in village Shunguliba Mobilizing local building materials Funds will be transferred to village bank account upon fulfillment of community contribution 20 PFG’S training supervision 30 DASIP villages in the District A total of 55 PFG’S were well trained. 888 farmers from 28 PFGs have graduated - - KIL2/Kasulu dasip progres report qt2 08-09 9 DASIP 6. PROGRESS OF ON GOING PROJECTS Projects under this section started in (i) Construction of one market shed at Buhigwe/Mulera village. Construction has been completed. There are still minor finishing works which a contractor is working on as directed by the District Engineer. (ii) Expansion of market shed at Buhigwe/Mulera village. Setting out, excavation and construction of foundation has been completed. (iii) Construction of market shed at Munzeze village. Constructions of tables in the market shed have been completed. The building is at ring beam level. (iv) Construction of godown at Kitambuka village. Setting out, excavation, construction of foundation, laying hard core and casting over site concrete have been completed. Walls have been erected and ring beam set. Roofing structure on progress (v) Construction of two markets sheds at Kibwigwa village. The first contractor who did excavation of foundation was terminated following his absenteeism at the site for more than two months since he completed foundation excavation. The work was re-advertised and awarded to a new contractor. The new contractor has requested a review of the bill of quantities as the prices of building materials has sharply gone up. The district Engineer is reviewing the BOQ (vi) Construction of godown at Mwayaya village. Due to poor performance the contractor was instructed to demolish the over site concrete and repeat the same as per given bill of quantities. However, the contractor has never responded for the last two months, at last he decided to officially sub contract the work. The sub contractor will start by demolishing the over site concrete the proceed under the site supervisor from district engineer’s office (vii) Construction of market shed at Muganza village. The construction has been completed. The contractor is working on some finishing works as directed by the district engineer. (viii) Construction of Godown at Kitema village. The building is at ring beam level.The community is mobilizing bricks and bringing them to the site. (ix) Construction of a two sheds market in Shunga village. Roofing completed, construction of tables and finishing works on progress KIL2/Kasulu dasip progres report qt2 08-09 10 DASIP (x) Construction of two market shed at Bugaga village. The contractor is re fixing new 28G C.I.S as it was revealed that at the first time did not utilize the recommended C.I.S (xi) Construction of market shed at Rusaba village. The building is at roofing stage, super structure completed. The contractor is mobilizing other roofing materials (xii) Construction of two markets shed at Murufiti village. Construction had reached at roofing stage, however it was realized that the ring beam was poorly done. District engineer instructed the contractor to demolish the beam and set it following recommended standards. The roofing structure and ring beam have been demolished, recasting of ring beam is on progress. (xiii) Construction of market shed at Janda village. Setting out, excavation and construction of foundation have been completed. Construction of external walls on progress The beneficiary community is fully involved in mobilizing and colleting stones for hard core and bricks for walls and table construction. (xiv) Construction of market shed at Rungwe Mpya. The market shed had reached at roofing stage but it was realized that there was poor workmanship on the roofing structure. The contractor was ordered to remove the roof structure and accommodate engineer’s instructions The contractor is working on engineer’s instructions (xv) Construction of market shed at Rusesa village Village project bank account has been opened. Construction has not started; community is still mobilizing local building materials (xvi) Construction of market shed at Kumsenga/Murubona village Construction has not started; the community is still mobilizing local building materials (xvii) Construction of market shed at Buhoro village Village project bank account has been opened. Construction has not started; community is still mobilizing local building materials (xviii) Construction of market shed at Asante Nyerere village Construction has not started; the community is still mobilizing local building materials (xix) Construction of market shed at Shunguliba village Construction has not started; the community is still mobilizing local building materials (xx) Formation of 180 participatory farmer groups for 2008/2009 season. A total of one hundred forty five (145) participatory farmer groups have been formed within a period under review. The formed groups have registered a total of 3665 members out of whom 1927 are males and 1738 female KIL2/Kasulu dasip progres report qt2 08-09 11 DASIP The remaining 35 PFGs are expected to be formed in the third quarter, 2007/2008. The PFGs formation exercise was undertaken by WTFs with technical back stopping from the district training coordinators in collaboration with district monitoring and evaluation officer. Farmer facilitators participated in their respective villages. A summary of selected enterprises is as follows: S/NO ENTERPRISE NO. OF PFGs 01 Tomato production 26 02 Onion production 05 03 Local chicken improvement(low to high genetic potential) 18 04 Improved practices on coffee production 6 05 Maize production 25 06 Bean production 23 07 Improved cassava varieties 2 08 Ground nut production 13 09 Piggery 16 10 Cotton production 01 11 Round Potatoes 01 12 Banana Production 08 TOTAL 145 (xxi) Facilitation of 55 PFGs undertake economic mini-project All 55 PFGs have identified their min economic enterprises Forty four (44) PFGs have submitted their investment proposal to DALDO’s office for appraisal and approval. Twety (20) PFGs have opened bank accounts using funds from own contribution or accrued from FFs plots’ harvests. (xxii)Training of 30 farmer facilitators The training has been organized into three phases as follows:- (i) 1/12/08- 4/12/2008 (ii) 15/12/08- 19/12/08 (iii) 5/1/2009- 7/1/2009 The first session was implemented as scheduled, attended by 27 participants out of 30 expected. Out of 27 participants attended only 2 were female The training was facilitated by the two district training coordinators who covered principles of crop and livestock production and the district monitoring and evaluation officer facilitated topics on facilitation skill of adult learners with special emphasis on Farmer Field school methodology. Practical took over 60% of the overall training days. The next session was not implemented as trainers were out of their duty station attending a training which was organized by higher authority. KIL2/Kasulu dasip progres report qt2 08-09 12 DASIP 7. PROGRESS OF COMPLETED PROJECTS (i)Two coffee central pulperis for Munanila and Mwayay village. The two pulperis are functioning well. They have assisted the intended community to maintain the quality of the coffee because they have made it possible to pulp all the coffee brought to the central pulpery within recommended time. The quantity of coffee pulped per season in the catchment area has gradually increased from less than 400 tones to 500 tones this season. (ii)Cattle dip at Kabanga village The cattle dip is functioning and providing the service to the intended community. Beneficiaries have started a cattle dip maintenance fund where by for each immersed animal a sum of Tshs 100 is contributed to the fund. (iii) Cattle dip at Munzeze. It is providing the intended services. Livestock keepers do the daily management of the dip under the supervision of dip committee. Also the dip committee has been advised to establish a cattle dip maintenance fund. (iv)Cattle dip at Nyankolonko village. The cattle dip is functioning and providing the intended service to the community (v)Cattle dip at Muzye/Mutala. The construction has just been completed livestock keepers are organizing themselves to secure fund for accaricide. (vi)Cattle dip at Kidyama village. Setting out, leveling of water pipe trench, excavation of water pipe trench from the water source to the cattle dip, excavation of cattle dip tank, construction of cattle dip tanks, installation of water pipes and other finishing works have been completed. The dip tank is still under curing period beyond which the dip will start to serve its purpose. Livestock keepers are mobilizing funds to purchase accaricide. (vii) Cattle dip at Kalela village The cattle dip is operating and providing intended service to the community. (viii) Rehabilitation of cattle dip in Kwaga village Rehabilitation work has been finished. The dip tank is still under curing period The beneficiary community is mobilizing funds for purchase of accaricide KIL2/Kasulu dasip progres report qt2 08-09 13 DASIP (ix)Participatory farmer groups graduation and certification. The 55 PFGs which underwent a season long training using FFs methodology in the year 2007/2008 graduated within the period under review. A total of 1,592 farmers out of 1,650 who registered at the beginning of the season PFGs graduated. Among 1,592 graduates, 670 are female and 912 male. Graduation ceremonies were conducted in their respective villages on the dates set by PFG members but within the district planed schedule. The inauguration ceremony was conducted in Bugaga village attended by District facilitation team and some Ward Leaders as invitees. Most PFGs had an opinion that they would like to continue to study other crops or livestock which were not studied in the season in question while others want to study the same crop/live stock on other practices that were not covered during their study 8. ROUTINE MONITORING AND SUPERVISION This activity was accomplished by visiting project sites to ascertain what is happening in relation to what was planned. A team comprised of multidisciplinary professionals made a total of eleven supervisory visits during the period under review. In most cases the team was composed of DALDO, DPLO, DPO, DMEO, DTCs, internal auditor/project accountant and district engineer. The supervision is done twice per month in which each session lasts for a minimum of three days (night out) During field visit, the team meets with members of the village project supervision committee, village government leaders, PFG members and when necessary some villagers are also met to seek their views and perception A total of eleven(11) back to office reports highlighting on the progress achieved, bottlenecks and suggestions to eliminate the observed bottlenecks have been written and submitted to DED for feed back, action and assistance where needed. The field supervisory visits made during the period under review revealed following: ¾ In some villages members of the village project committee are playing shrinking role ¾ Most villages have not yet developed a sense of formulating strategies that will sustain their project KIL2/Kasulu dasip progres report qt2 08-09 14 DASIP ¾ Some (a few) civil contractors are not abiding to the bill of quantities provided for a given civil work. This has led to demolishing some of the civil works that were considered as completed ones. ¾ Absence of permanent site supervisor from DED’s office makes certification of construction works difficult ¾ Most civil contractors tend to ignore advises/instructions given by members of the village project committee in this case the committee become redundant ¾ A delay in disbursing min grants to PFG graduates has helped to eliminate input driven participants ¾ Almost all members of the ward facilitation team except agricultural/livestock extension officers are not playing their roles in DASIP supported activities KIL2/Kasulu dasip progres report qt2 08-09 15 DASIP 9. FINANCIAL STATUS Within the period of July-December, 2008 PCU transferred a total of TShs 320,725,848 into DASIP Kasulu Bank Account to facilitate implementation of DASIP supported activities. The financial status for the period under review is indicated in the table format below. COMPONENT DISBURSMEN T DATE COST ITEM DISBURSED AMOUNT (TSHS) EXPENDITURE (TSHS) BALANCE (TSHS) 31/07/2008 Rehabilitation of Kwaga village cattle dip 9,508,848 9,508,848 - Community investment 31/07/2008 Construction of cattle dip at Kidyama village 27,700,000 27,700,000 - Motor cycle allowance for DTCs 900,000 900,000 - Office operation and maintenance DTCs 600,000 600,000 - Farmer capacity building 08/08/2008 Field allowance DTC 650,000 650,000 - 5/11/2008 Training of farmer facilitators 10,042,000 10,042,000 - Office operation and maintenances 750,000 700,000 50,000 DPO & DMEO motor cycle allowance 900,000 900,000 - 08/08/2008 District staff allowance 4,375,000 4,200,000 175,000 Community planning and Investment in Agriculture 9/10/2008 Construction of five village micro projects(market shed) 140,000,000 - 140,000,000 28/11/2008 Procurement of a milk processor for Kunsenga/Murubona group 3,000,000 - 3,000,000 28/11/2008 Procurement of 2 milling machine- Kumsenga/Murubona 2,000,000 - 2,000,000 28/11/2008 Procurement of 4 milling machine for Kidyama group 4,000,000 - 4,000,000 28/11/2008 Procurement of 2 milling machine for Munzeze 2,000,000 2,000,000 22/8/2008 Economic mini-projects for 55 PFGs 22,000,000 - 22,000,000 04/09/2008 Formation of 180 PFGs for 2008/2009 2,300,000 2,274,000 26,000 Farmer capacity building TOTAL 320,725,848 122,723,798 198,002,050 KIL2/Kasulu dasip progres report qt2 08-09 16 DASIP 10.PLANNED ACTIVITIES FOR THE NEXT PERIOD: JANUARY – MARCH 2008 TIME FRAME S/N ACTIVITIES INDICATOR RESPONSIBLE JAN FEB. MARCH 1 Construction of a two sheds market in each of the following villages, Rusesa, Kumsenga/Murubona, Buhoro, Asante Nyerere and Shunguliba Number of market shed constructed. Number of market sheds providing services (Operational) to the community DALDO, DPO, DMEO 2 Facilitation of 55 PFGs undertake economic mini- projects Number of economic mini-projects undertaken. Number of PFGs with and operating bank account. DTCs DMEO 3 Season long training of 180 PFGs Number of PFGs undergoing season long training. Number of farmers participating in a season long training DTCs, DMEO, DPO 4 Training of 30 farmer facilitators on principles of crop and livestock production; facilitation skill with special emphasis on FFS methodology, farming as a business Number of participants attended Number of topics covered Training report produced DTC, DPO 5 Training of dip committee members for all completed dips(DADP funds will support this activity) Number of participants trained Number of dip committee trained Training report produced DALDO, DPO, DLO 6 Monitoring and supervision of completed, on going and new project activities Number of monitoring and supervisory visits made. Number of back to office reports written Number of quality projects completed and functional DPF, DMEO,DALDO 7 Quarterly report writing Quarterly reports produced and distributed to the respective authorities DMEO KIL2/Kasulu dasip progres report qt2 08-09 17 DASIP 11. CHALLENGES AND PROBLEMS ENCOUNTERED Inadequate/Lack of qualified/registered civil contractors in rural areas. Some civil contractors not adhering to building standard (BOQ). This resulted in demolishing some of the works and instructing them to repeat the same under close supervision of district engineer. Inadequate resources (transport facilities, fuel and field allowance) is a bottle net to monitoring and supervision of field activities. Increase in prices of building materials has negative implication in civil works. A buddle of corrugated iron sheet whose price was Tshs 200,000/= in February 2008 shifted to TShs 300,000 in September 2008.Most civil contractors have requested revision of the bill of quantities following sky rocketing prices Some of the graduate farmers are eager to go back learn some technologies which were not part of the just ended season long training but the project does not provide for the second season long training for the same farmers. A pre requisite that requires each PFG to open a bank account before receiving a grant for economic mini project is limited by lack of financial institutions in rural areas. Some villages are located as far as over 70 kms away from the district headquarter where the only bank is situated. To meet the said requirement PFG leaders are incurring a lot of money for transport and general up keep when traveling to open bank account. PCU has been allocating the same quantity of resources like field allowance etc to districts irrespective of geographical location and number of activities the district is handling. In a district like Kasulu who is supposed to supervise over 31 investment projects which are sparsely distributed finds it difficult to meet her role using allocated resources. 12. RECOMMENDATIONS (i) Following a sharp increase in the cost of living in the country, the cost of industrial materials and even field allowances rates have also been raised. The project should consider increasing the budget allocated to the district in order to bridge the gap. (ii) The newly appointed DMEO has little knowledge and skills on data processing, analysis, report writing and lack the same on computer application (spread sheet, power point and Internet). We therefore recommend PCU to allocate modest amount of money that can support him to acquire the said knowledge and skills. (iii) In order to speed up the diffusion of new innovations (technologies) studied and demonstrated in FFS, farmer field days are important venues that we need to promote. KIL2/Kasulu dasip progres report qt2 08-09 18 DASIP ANNEX 1; SUMMARY OF INVESTIMENT PROJECTS IN DASIP SUPPORTED VILLAGE UP TO DECEBER, 2008 S/NO VILLAGE YEAR PROJECT IMPLEMENTED STATUS 2006/2007 charcoal dam Partially done, DADP will top up 1 MUGANZA 2007/2008 market shed(1) At finishing stage 2 BUHORO 2008/9 Market sheds(2) Mobilizing local materials 3 SHUNGA 2007/8 Market shed(2) Finishing stage 4 KUMSENGA/ MURUBONA 2008/2009 Market shed(2) Mobilizing local materials 5 JANDA 2007/2008 Market shed(2) Wall erecting stage 6 KIDYAMA 2007/2008 Cattle dip Completed 2007/8 Go down Foundation stage 7 MWAYAYA 2006/2007 Central pulpury Operating 8 MUBANGA ? Not identified 9 RUSESA 2008/2009 Market shed(2) Mobilizing local materials 10 RUSABA 2007/2008 Market shed(2) Roofing stage 11 BUGAGA 2007/2008 Market shed(2) Roofing stage 12 MUZE/MUTALA 20072008 Cattle dip completed 13 MURUFITI 2007/2008 Market shed(2) Ring beam stage 14 KITEMA 2007/2008 Go down Ring beam stage 15 KWAGA 2007/2008 Cattle dip Completed 16 KALELA 2007/2008 Cattle dip Completed 17 SHUNGULIBA ? Not identified 2006/2007 Market shed(1) Finishing stage 18 BUHIGWE/MULERA 2007/2008 Market shed(1) Foundation and hard core concrete completed 19 NYANKORONKO 2006/2007 Cattle dip completed 2006/2007 Cattle dip operating 20 MUNZEZE 2007/2008 Market shed(1) Roofing stage 2006/2007 Central pulpury operating 21 MUNANILA ? Not identified 22 KIBWIGWA 2006/2OO8 Market shed(2) Foundation KIL2/Kasulu dasip progres report qt2 08-09 19 DASIP stage 23 KITAMBUKA 2007/2008 Go down Ring beam stage 24 KURUGONGO ? Not yet identified 25 MIGUNGA ? Not yet identified 26 KARUNGA ? Not yet identified 27 MUHUNGA ? Not yet identified 28 KABANGA 2006/2007 Market shed(2) Operating 29 RUNGWE MPYA 2007/2008 Market shed(2) Roofing stage 30 ASANTE NYERERE 2008/2009 Market shed(2) Mobilizing local building materials KIL2/Kasulu dasip progres report qt2 08-09 20 DASIP | false |
# Extracted Content KATIBA YA CHAMA CHA MAPINDUZI 1977 TOLEO LA 2017 Imetolewa na Makao Makuu ya CCM S.L.P. 50, DODOMA 2017 BEI SH. 3,000/= Katiba ya Chama Cha Mapinduzi i KATIBA YA CHAMA CHA MAPINDUZI 1977 TOLEO LA 2017 Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi ii iii YALIYOMO 1. Azimio la Mkutano Mkuu wa Taifa wa pamoja wa TANU na ASP iv 2. SEHEMU YA KWANZA Jina, Imani na Madhumuni 1 3. SEHEMU YA PILI Wanachama na Viongozi 5 4. SEHEMU YA TATU (i) Vikao vya Shina 13 (ii) Vikao vya Tawi 19 (iii) Vikao vya Kata/ Wadi 35 (iv) Vikao vya Jimbo 50 (v) Vikao vya Wilaya 65 (vi) Vikao vya Mkoa 83 (vii) Vikao vya Taifa 102 5. SEHEMU YA NNE Wazee na Jumuiya za Wananchi 136 6. SEHEMU YA TANO Mengineyo 137 7. Nyongeza ‘A’ Ahadi za Wanachama wa Chama cha Mapinduzi 143 8. Nyongeza “B” 144 Toleo hili limezingatia na kuweka pamoja marekebisho yote yaliyofanywa katika Katiba ya Chama Cha Mapinduzi ya 1977 hadi kufikia mwaka 2017. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi iv v Kwa kuwa tunatambua pia kwamba kuweko kwa Vyama viwili katika mazingira ya Chama kimoja cha Siasa kunapunguza upeo wa Nguvu na Umoja wetu katika kuendeleza mapambano ya kujenga Ujamaa nchini na kushiriki kwa pamoja kwa ukamilifu katika harakati za Mapinduzi ya Tanzania, ya Afrika na ya Dunia na; Kwa kuwa, kihistoria, tumeongozwa na kumbukumbu ya kitendo kama hiki cha kimapinduzi na busara ambacho Waanzilishi wa TANU, chini ya Uongozi wa Mwalimu Julius K. Nyerere walikifanya hapo awali cha kuvunja Chama cha African Association na kuunda TANU, na waanzilishi wa ASP chini ya uongozi wa Marehemu Abeid Amani Karume, walikifanya hapo awali cha kuvunja Vyama vya African Association na Shiraz Association na kuunda ASP, shabaha yao wote ikiwa ni kuunda Chama kipya madhubuti na cha kimapinduzi chenye uwezo mkubwa zaidi wa kuongoza mapambano ya wananchi wetu katika mazingira mapya ya wakati huo; Kwa hiyo basi: (1) Sisi wajumbe wa Mkutano Mkuu wa Taifa wa pamoja wa TANU na ASP tuliokutana leo tarehe 21 Januari, 1977 mjini Dar es Salaam, chini ya uongozi wa pamoja wa Mwalimu Julius K. Nyerere Rais wa TANU na Ndugu Aboud Jumbe, Rais wa ASP, kwa kauli moja tunaamua na kutamka rasmi kuvunjwa kwa Tanganyika African National Union (TANU) KATIBA YA CHAMA CHA MAPINDUZI AZIMIO LA MKUTANO MKUU WA TAIFA WA PAMOJA WA TANU NA ASP Kwa kuwa Mkutano Mkuu wa Taifa wa pamoja, kwa niaba ya Wana-TANU na Wana-ASP, kwa pamoja unaelewa na kukubali kwamba jukumu letu katika Historia ya Taifa ni kuimarisha Umoja, kuleta Mapinduzi ya Kijamaa Tanzania na kuendeleza mapambano ya Ukombozi katika Afrika na kote Duniani; Kwa kuwa tunatambua kuwa Mapambano ya Kujenga Ujamaa katika Tanzania na kushiriki kwetu kwa ukamilifu katika harakati za Mapinduzi ya Afrika na Dunia kunahitaji Chombo madhubuti cha uongozi kinachounganisha fikira na vitendo vya Wafanyakazi na Wakulima; Kwa kuwa tunazingatia na kuthamini kazi nzuri ya kimapinduzi na ya mafanikio makubwa iliyokwishafanywa na TANU na ASP katika kumwondoa Mwafrika kutoka kwenye unyonge wa kunyonywa, kunyanyaswa na kudharauliwa na kumfikisha kwenye uhuru na kuheshimiwa; Kwa kuwa tunatambua kuwa Umoja wa TANU na ASP unatokana na ushirikiano wetu wa miaka mingi tangu wakati wa Mapambano ya kupigania Uhuru hadi sasa, na unatokana pia na Siasa yetu moja ya Ujamaa na Kujitegemea; Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi vi vii Chama tunachokiunda tunataka kiwe chombo madhubuti katika muundo wake na hasa katika fikra zake na vitendo vyake vya kimapinduzi vya kufutilia mbali aina zote za unyonyaji nchini, na kupambana na jaribio lolote lile la mtu kumuonea mtu au shirika au chombo cha nchi kuonea na kudhalilisha wananchi, kudhoofisha uchumi au kuzorotesha maendeleo ya Taifa; Chama tunachokiunda tunataka kishike barabara hatamu za uongozi wa shughuli zote za umma kwa maslahi ya Wafanyakazi na Wakulima wa Taifa letu; Chama tunachokiunda tunataka kiwe kiungo kati ya Wanamapinduzi wa Tanzania na Wanamapinduzi wenzetu kokote waliko. na Afro Shirazi Party (ASP) ifikapo tarehe 5 Februari, 1977 na wakati huo kuundwa kwa Chama kipya cha pekee na chenye uwezo wa mwisho katika mambo yote kwa mujibu wa Katiba. (2) Vyama vya TANU na ASP vinavunjwa kwa taadhima kubwa. TANU na ASP havikuamua kujivunja kama vyama kwa kuwa vimeshindwa kutekeleza jukumu lao. Kwa hakika TANU na ASP ni Vyama vilivyopata mafanikio ya kipekee katika Afrika katika kulitekeleza jukumu la kihistoria na mafanikio hayo ndiyo leo yamewezesha kitendo hiki cha Vyama viwili kujivunja vyenyewe. TANU na ASP vitaheshimiwa siku zote kama viungo muhimu katika Historia ya Mapambano ya Ukombozi wa Taifa letu na wa Bara la Afrika, na waanzilishi wa TANU na ASP watakumbukwa daima kama mashujaa wa taifa letu waliotuwezesha leo kupiga hatua hii ya kufungua ukurasa mpya katika Historia ya Tanzania. (3) Tumeamua kwa pamoja kuunda Chama kipya cha kuendeleza mapinduzi ya kijamaa nchini Tanzania na Mapambano ya Ukombozi wa Afrika juu ya misingi iliyojengwa na TANU na ASP. Katiba ya Chama Cha Mapinduzi viii Katiba ya Chama Cha Mapinduzi 1 SEHEMU YA KWANZA JINA, IMANI NA MADHUMUNI 1. Jina la Chama litakuwa CHAMA CHA MAPINDUZI, kwa kifupi CCM. 2. Makao Makuu ya CCM yatakuwa Dodoma na kutakuwa na Afisi Kuu ya Chama Cha Mapinduzi Zanzibar na Ofisi Ndogo ya Makao Makuu Dar es Salaam. 3. Bendera ya CCM itakuwa na rangi ya kijani kibichi, ambayo itakuwa na alama ya Jembe (alama ya Mkulima) na Nyundo (alama ya Mfanyakazi) kwenye pembe ya juu upande wa mlingoti. 4. Chama Cha Mapinduzi kinaamini kwamba: (1) Binadamu wote ni sawa. (2) Kila mtu anastahili heshima ya kutambuliwa na kuthaminiwa utu wake. (3) Ujamaa na Kujitegemea ndiyo njia pekee ya kujenga jamii ya watu walio sawa na huru. 5. Kwa hiyo Malengo na Madhumuni ya CCM yatakuwa yafuatayo: (1) Kushinda katika Uchaguzi wa Serikali Kuu na Serikali za Mitaa Tanzania Bara na Zanzibar ili kuunda na kushika Serikali Kuu na Serikali za Mitaa katika Jamhuri ya Muungano wa Tanzania kwa upande mmoja na Zanzibar kwa upande wa pili. Jina la Chama Makao Makuu ya Chama Bendera ya CCM Imani ya CCM Malengo na Madhumuni ya CCM Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 2 3 (9) Kuona kwamba Nchi yetu inatawaliwa kwa misingi ya kidemokrasia na ya kijamaa. (10) Kuhifadhi, kukuza na kudumisha imani na moyo wa kimapinduzi miongoni mwa Watanzania pamoja na ushirikiano na wanamapinduzi wenzetu kokote waliko. (11) Kuweka na kudumisha heshima ya binadamu kwa kufuata barabara Kanuni za Tangazo la Dunia la Haki za Binadamu. (12) Kuona kwamba Dola inakuwa Mhimili wa Uchumi wa Taifa. (13) Kuona kwamba Serikali na Vyombo vyote vya Umma vinasaidia kwa vitendo kuanzishwa na kuendeleza shughuli za Ushirika na za ujamaa, na shughuli nyinginezo halali za wananchi za kujitegemea. (14) Kuona kwamba matumizi ya utajiri wa Taifa yanatilia mkazo maendeleo ya Wananchi na hasa jitihada za kuondosha umasikini, Ujinga na Maradhi. (15) Kuona kwamba Serikali na vyombo vyote vya umma vinatoa nafasi zilizo sawa kwa raia wote, wanawake na wanaume bila kujali rangi, kabila, Dini, au hali ya mtu. (16) Kuona kwamba katika nchi yetu hakuna aina yoyote ya dhuluma, vitisho, ubaguzi, rushwa, uonevu na/au upendeleo. (17) Kuendelea kupiga vita Ukoloni Mamboleo, Ubeberu na Ubaguzi wa aina yoyote. (2) Kulinda na kudumisha Uhuru wa Nchi yetu na raia wake. (3) Kuhimiza ujenzi wa Ujamaa na Kujitegemea kwa mujibu wa Azimio la Arusha. (4) Kusimamia utekelezaji wa Siasa ya CCM pamoja na kuendeleza fikra za viongozi waasisi wa vyama vya TANU na ASP, kama zilivyofafanuliwa katika maandiko mbalimbali ya Vyama hivyo. (5) Kuona kwamba kila mtu anayo haki ya kupata kutoka katika Jamii hifadhi ya maisha yake na mali yake kwa mujibu wa sheria. (6) Kuona kwamba katika Nchi yetu kila mtu aliye na uwezo wa kufanya kazi anafanya kazi; na kazi maana yake ni shughuli yoyote halali inayompatia mtu riziki yake. (7) Kusimamia haki na maendeleo ya Wakulima, Wafanyakazi na wananchi wengine wenye shughuli halali za kujitegemea; na hasa kuona kwamba kila mtu ana haki ya kupata malipo yanayostahili kutokana na kazi yake. (8) Kuona kwamba kwa kutumia Vikao vilivyowekwa, raia anayo haki ya kushiriki kwa ukamilifu katika kufikia uamuzi wa mambo ya Taifa na yanayomhusu, na kwamba anao uhuru wa kutoa mawazo yake, wa kwenda anakotaka, wa kuamini Dini anayotaka na kukutana na watu wengine, maadamu havunji Sheria au Taratibu zilizowekwa. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 4 5 SEHEMU YA PILI WANACHAMA NA VIONGOZI FUNGU LA 1 WANACHAMA 6. Kila mtu aliyekuwa Mwanachama wa TANU au wa ASP mara kabla ya kuvunjwa kwa Vyama hivyo, na aliyekuwa anatimiza masharti ya Uanachama wake, atakuwa mwanachama wa Chama Cha Mapinduzi, isipokuwa kama atakataa mwenyewe. 7. Raia yeyote wa Tanzania mwenye umri usiopungua miaka 18, anaweza kuwa Mwanachama wa Chama Cha Mapinduzi iwapo anakubali Imani, Malengo na Madhumuni ya CCM. 8. Mtu atakayekubaliwa kuingia katika CCM, au kuendelea kuwa Mwanachama, ni yule anayetimiza Masharti yafuatayo: (1) Kuwa mtu anayeheshimu watu. (2) Kuwa mtu anayefanya juhudi ya kuielewa, kuieleza, kuitetea na kuitekeleza Itikadi na Siasa ya CCM. (3) Kuwa mtu mwenye kuamini kuwa kazi ni kipimo cha Utu, na kuitekeleza imani hiyo kwa vitendo. (4) Kuwa mtu anayependa kushirikiana na wenzake. (18) Kuimarisha uhusiano mwema na Vyama vyote vya Siasa vya Nchi nyingine vyenye itikadi kama ya CCM ambavyo kweli vinapinga Ukoloni, Ukoloni Mamboleo, Ubeberu na Ubaguzi wa aina yoyote. (19) Kushirikiana na Vyama vingine katika Afrika, kwa madhumuni ya kuleta Umoja wa Afrika, na kuona kwamba Serikali inaendeleza na kuimarisha ujirani mwema. 5 A. Katika Katiba hii, maneno yafuatayo yatakuwa na maana inayoonyeshwa kwa kila neno linalohusika ‘Wabunge wa aina nyingine’ maana yake ni Wabunge wa Viti Maalum, Wabunge wa kuteuliwa pamoja na Wabunge wa Bunge la Afrika Mashariki, wanaotokana na CCM. ‘Wawakilishi’ maana yake ni Wajumbe wa Baraza la Wawakilishi la Zanzibar wanaotokana na CCM. ‘Kanuni zinazohusika’ maana yake ni Kanuni za CCM zinazohusika, zilizoorodheshwa katika Nyongeza ‘B’ ya Katiba hii. Kwa ajili ya kuondoa utata unaoweza kujitokeza, inafafanuliwa zaidi kwamba endapo Kanuni yoyote itaonekana kuwa inapingana na Masharti ya Katiba hii, masharti ya Katiba ndiyo yatakayofuatwa. Wanachama Waasisi Wanachama Wapya Masharti ya Uanachama Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 6 7 (c ) Atalipa ada ya Uanachama kila mwezi, isipokuwa kama akipenda anaweza kulipa ada ya mwaka mzima mara moja. (d) Atatoa michango yoyote itakayoamuliwa. (2) Viwango vya kiingilio, ada na michango vitawekwa na Halmashauri Kuu ya Taifa. 13 (1) Uanachama wa mwanachama utakwisha kwa:- (a) Kufariki. (b) Kujiuzulu mwenyewe. (c) Kuachishwa kwa mujibu wa Katiba. (d) Kufukuzwa kwa mujibu wa Katiba. (e) Kutotimiza masharti ya Uanachama. (f) Kujiunga na Chama kingine chochote cha siasa. (2) Mwanachama ambaye uanachama wake unakwisha kwa sababu yoyote ile hatarudishiwa kiingilio alichokitoa, ada aliyotoa wala michango yoyote aliyoitoa. (3) Mwanachama aliyeachishwa au kufukuzwa Uanachama akitaka kujiunga tena katika CCM, itabidi aombe upya, na atapeleka maombi yake hayo ama katika Halmashauri Kuu ya Wilaya ama kikao kilichomwachisha au kumfukuza Uanachama. (4) Mwanachama aliyejiuzulu akitaka kujiunga tena katika CCM ataomba upya kwa kufuata utaratibu wa kuomba Uanachama kwa mujibu wa Katiba ya CCM. (5) Kuwa mtu ambaye siku zote yuko mstari wa mbele katika utekelezaji wa mambo yote ya Umma, kulingana na Miongozo ya CCM. (6) Kuwa wakati wote ni mfano wa tabia nzuri kwa vitendo vyake na kauli yake, kuwa mwaminifu na kutokuwa mlevi au mzururaji. (7) Kuwa ama Mkulima, Mfanyakazi, au mwenye shughuli nyingine yoyote halali ya kujitegemea. 9. Mtu atakayetaka kuwa Mwanachama atajaza fomu ya maombi na kuipeleka kwa Katibu wa Tawi anapoishi. 10. Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi itafikiria na kutoa uamuzi wa mwisho kuhusu maombi ya Uanachama. 11. CCM itakuwa na Mpango wa kutoa mafunzo kwa wanachama wake juu ya Imani, Malengo na Madhumuni ya Siasa ya CCM kwa jumla. 12. (1) Mtu akikubali kuwa Mwanachama itabidi atekeleze haya yafuatayo:- (a) Atatoa ahadi zilizoorodheshwa katika NYONGEZA “A” ya Katiba hii. Atazitoa katika mfumo wa kiapo, mbele ya Kiongozi aliyemkabidhi Kadi ya Uanachama. (b) Atatoa kiingilio cha Uanachama. Utaratibu wa kuomba Uanachama Utaratibu wa kufikiria maombi ya uanachama Mafunzo kwa Wanachama Kiingilio na Ada za Wanachama Kuondoka katika Chama Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 8 9 15. Kila Mwanachama atakuwa na wajibu ufuatao:- (1) Kujua kwamba Chama Cha Mapinduzi ndicho chenye nguvu, uwezo na kwamba nguvu hizo zinatokana na umoja wa Wanachama, fikra sahihi za CCM na kukubalika kwake na umma. Kwa hiyo kulinda na kuendeleza mambo hayo ni Wajibu wa kwanza wa kila Mwanachama. (2) Kutumikia Nchi yake na watu wake wote kwa kutekeleza wajibu wake bila hofu, chuki wala upendeleo wa nafsi yake, rafiki au jamaa. (3) Kujitolea nafsi yake kuondosha Umasikini, Ujinga, Maradhi na Dhuluma, na kwa jumla kushirikiana na wenzake wote katika kujenga Nchi yetu. (4) Kuwa wakati wote mkweli, mwaminifu na raia mwema wa Tanzania. (5) Kukiri kwa imani na kutekeleza kwa vitendo Siasa ya CCM ya Ujamaa na Kujitegemea. (6) Kujielimisha kwa kadiri ya uwezo wake, na kutumia elimu hiyo kwa faida ya wote. (7) Kuwa tayari kujikosoa na kukosolewa ili kuweza kuwa na msimamo sahihi wa siasa ya CCM. (8) Kuwa wakati wowote hadaiwi ada zozote za Uanachama. (9) Kuhudhuria mikutano ya CCM inayomhusu. (5) Mwanachama wa CCM aliyehama Chama na kujiunga na Chama kingine cha siasa, akitaka kujiunga tena na CCM atapeleka maombi yake kwenye Tawi lake analoishi, atajadiliwa na vikao vinavyohusika na uamuzi wa mwisho wa kukubaliwa au kukataliwa utafanywa na Kamati ya siasa ya Halmashauri kuu ya CCM ya Wilaya inayohusika, baada ya kujiridhisha kuwa kurejea kwake kwenye Chama kuna manufaa kwa Chama na hakutakuwa na madhara. 14. Mwanachama yeyote atakuwa na haki zifuatazo:- (1) Haki ya kushiriki katika shughuli zote za CCM kwa kufuata utaratibu uliowekwa. (2) Haki ya kuhudhuria na kutoa maoni yake katika mikutano ya CCM pale ambapo anahusika kwa mujibu wa Katiba. (3) Haki ya kuomba kuchaguliwa kuwa Kiongozi wa CCM na ya kuchagua viongozi wake wa CCM kwa mujibu wa Katiba, Kanuni na Taratibu za CCM. (4) Haki ya kujitetea au kutoa maelezo yake mbele ya Kikao cha CCM kinacho husika katika mashtaka yoyote yaliyotolewa juu yake, pamoja na haki ya kukata rufani ya kwenda katika Kikao cha juu zaidi cha CCM kama kipo endapo hakuridhika na hukumu iliyotolewa. (5) Haki ya kumuona kiongozi yeyote wa CCM maadam awe amefuata utaratibu uliowekwa. Haki ya Mwanachama Wajibu wa Mwanachama Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 10 11 19. (1) Uongozi wa kiongozi utakoma kwa:- (a) Kufariki (b) Kujiuzulu mwenyewe. (c) Kuachishwa kwa mujibu wa Katiba. (d) Kufukuzwa kwa mujibu wa Katiba. (e) Kung’atuka /kuacha kazi. (f) Kujiunga na chama kingine chochote cha siasa. (2) Kiongozi aliyeachishwa au kufukuzwa uongozi anaweza kuomba tena nafasi ya uongozi wowote na maombi yake yatafikiriwa na kutolewa uamuzi na kikao kilichomwachisha au kumfukuza uongozi. (3) Kiongozi wa CCM aliyehama Chama na kujiunga na Chama kingine cha siasa, anaweza kuomba tena uongozi baada ya kuchunguzwa kwa muda wa miaka mitatu toka alipojiunga tena na CCM baada ya muda huo kumalizika, vikao vinavyohusika vitafikiria maombi yake na kuyatolea uamuzi. Kamati Kuu ya Halmashauri kuu ya Taifa ina uwezo wa kuamua kwa kadiri itakavyoona inafaa juu ya utekelezaji wa kifungu hiki kwa manufaa ya Chama. 20. (1) Mwanachama anayeomba nafasi ya uongozi wa aina yoyote katika CCM hatakubaliwa kuwa amechaguliwa mpaka awe amepata zaidi ya nusu ya kura halali zilizopigwa. FUNGU LA PILI VIONGOZI 16. Kiongozi wa CCM ni kila Mwanachama mwenye dhamana yoyote katika CCM aliyechaguliwa au kuteuliwa kwa mujibu wa Katiba. 17. Pamoja na kutimiza masharti ya Uanachama kama yalivyoelezwa katika Katiba, Kiongozi sharti pia awe na sifa zifuatazo:- (1) Awe ni mtu aliyetosheka na asiwe mtu aliyetawaliwa na tamaa. (2) Awe ni mtu anayependa kueneza matunda ya Uhuru kwa wananchi wote kwa ajili ya manufaa yao na maendeleo ya Taifa kwa jumla. (3) Awe na sifa nyingine kama zilivyowekwa katika Kanuni zinazohusika. 18. Ni mwiko kwa kiongozi: - (1) Kutumia madaraka aliyopewa ama kwa ajili ya manufaa yake binafsi au kwa upendeleo, au kwa namna yoyote ambayo ni kinyume cha lengo lililokusudiwa madaraka hayo. (2) Kupokea mapato ya kificho, kutoa au kupokea rushwa, kushiriki katika mambo yoyote ya magendo au mambo mengine yaliyo kinyume cha lengo lililokusudiwa madaraka hayo. (3) Miiko mingine ya Viongozi itakuwa kama ilivyowekwa kati ka Kanu ni zinazohusika. Maana ya Kiongozi Sifa za Kiongozi Miiko ya Kiongozi Kuondoka katika Uongozi Kiwango cha kura katika Uchaguzi wa Viongozi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 12 13 SEHEMU YA TATU VIKAO VYA CCM FUNGU LA 1 VIKAO VYA SHINA 21. Kikao cha mwanzo kabisa cha CCM kitakuwa ni kikao cha Shina. Hapa ndipo kila mwanachama atadhihirisha uanachama wake kwa kutekeleza kwa vitendo wajibu wake wa uanachama. Aidha hapa ndipo alama zinazo kitambulisha Chama kama vile bendera, zitakapoanzia kutumika. 22. (1) Kutakuwa na aina zifuatazo za Mashina:- (i) Mashina ya Ndani ya Nchi:- (a) Mashina yaliyoundwa katika maeneo ya makazi Mijini na Vijijini. (b) Mashina ya Wakereketwa/ Maskani yaliyoundwa na wanachama wa CCM katika maeneo husika, baada ya kupata idhini ya Kamati ya Siasa ya Wilaya. (ii) Mashina ya Nje ya Nchi: - Mashina yaliyoundwa Nje ya Nchi katika maeneo wanakoishi wanachama wa CCM, baada ya kupata idhini ya Kamati Kuu ya Halmashauri Kuu ya Taifa. (2) Katika uchaguzi wa kujaza nafasi nyingi kwa pamoja, ushindi utahesabiwa kwa kufuata wingi wa kura alizopata mwombaji wa nafasi hiyo zaidi ya wenzake, bila kujali kama kura hizo zinafikia nusu ya kura halali zilizopigwa. Shina Aina za Mashina Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 14 15 (2) Kuona kwamba unakuwepo ulinzi na usalama wa umma katika eneo lake. (3) Kueneza itikadi na Siasa ya CCM katika Shina. (4) Kutekeleza ipasavyo maamuzi na maagizo ya ngazi za juu ya CCM na ya Serikali pamoja na shughuli nyinginezo za umma. 24. Kutakuwa na vikao vifuatavyo vya CCM katika kila Shina:- (1) Mkutano wa Mwaka wa CCM wa Shina. (2) Mkutano wa Wanachama wote wa Shina. (3) Kamati ya Uongozi ya Shina. 25. (1) Mkutano wa Mwaka wa CCM wa Shina utakuwa na wajumbe wafuatao:- (a) Balozi/Mwenyekiti wa Shina. (b) Wajumbe wa Kamati ya Uongozi ya Shina. (c) Wanachama wengine wote wa Shina hilo. (2) Mkutano wa Mwaka wa CCM wa Shina ndicho kikao kikuu cha CCM katika Shina. (3) Mkutano wa Mwaka wa CCM wa Shina utafanyika kwa kawaida mara moja kwa mwaka, lakini unaweza kufanyika wakati wowote mwingine endapo itatokea haja ya kufanya hivyo, au kwa maagizo ya vikao vya juu. (2) (a) KWA TANZANIA BARA, lli Wanachama waweze kuunda shina, idadi yao isiwe chini ya Hamsini kwa maeneo ya mijini na isiwe chini ya Thelathini kwa maeneo ya vijijini na wanachama hao wasiwe zaidi ya miamoja na hamsini. (b) KWA UPANDE WA ZANZIBAR, ili wanachama waweze kuunda Shina idadi yao isiwe chini ya Ishirini na isiwe zaidi ya mia moja. (3) Kila Shina la eneo la makazi au lililo nje ya nchi litachagua Kiongozi wa Shina kwa mujibu wa utaratibu uliowekwa, ambaye atajulikana kama Balozi wa Shina. Aidha kila Shina la Wakereketwa/ Maskani litachagua Kiongozi wa Shina kwa utaratibu uliowekwa ambaye atajulikana kama Mwenyekiti wa Shina la Wakereketwa au la Maskani. (4) Kila Shina litachagua Kamati itakayoitwa Kamati ya Uongozi ya Shina yenye wajumbe watano akiwemo Balozi/ Mwenyekiti wa Shina hilo. Katibu wa Shina atachaguliwa na Kamati ya Uongozi ya Shina. 23. Pamoja na wajibu mwingine wowote unaowahusu wanachama kwa jumla, kila Shina litakuwa na wajibu ufuatao:- (1) Kulinda na kuendeleza Siasa ya CCM katika Shina. Wajibu wa Shina Vikao vya CCM vya Shina Mkutano wa mwaka wa CCM wa Shina Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 16 17 Usalama, maendeleo katika Shina na kufikisha mapendekezo ya wanachama katika vikao vya juu. (3) Mkutano wa kawaida wa Wanachama wote utafanyika mara moja katika kila miezi mitatu, lakini mkutano usiokuwa wa kawaida unaweza kufanyika wakati wowote inapotokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (4) Kiwango cha mahudhurio katika mikutano ya wanachama wote katika Shina kitakuwa ni zaidi ya theluthi moja ya wajumbe walio na haki ya kuhudhuria kikao hicho. (5) Balozi/Mwenyekiti wa Shina ataongoza Mkutano wa wanachama wote wa Shina lakini asipoweza kuhudhuria, Mkutano utamchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 28. (1) Kamati ya Uongozi ya Shina itakuwa na wajumbe wafuatao: (i) Balozi/Mwenyekiti wa Shina (ii) Wajumbe wanne wa Kamati ya Uongozi ya Shina. (2) Kamati ya uongozi ya shina itafanya mikutano yake ya kawaida mara moja kila mwezi. (4) Balozi/Mwenyekiti wa Shina ataongoza Mkutano wa Mwaka wa CCM wa Shina. Lakini Balozi/ Mwenyekiti wa Shina asipoweza kuhudhuria, Mkutano unaweza kumchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 26. Kazi za Mkutano wa Mwaka wa CCM wa Shina zitakuwa zifuatazo: (1) Kufikiria taarifa ya kazi za CCM katika Shina na kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuzungumzia mambo yote yanayohusu maendeleo kwa jumla katika Shina. (3) Kuhakikisha kwamba maazimio na maagizo ya ngazi za juu yanatekelezwa ipasavyo. (4) Unapofika wakati wa uchaguzi, Mkutano wa Mwaka wa CCM wa Shina utashughulikia mambo yafuatayo:- (a) Kumchagua Balozi / Mwenyekiti wa Shina. (b) Kuwachagua wajumbe wa Kamati ya Uongozi ya Shina pale panapohusika. 27. (1) Kutakuwa na Mkutano wa Wanachama wote wa Shina kwa kila Shina. (2) Mkutano wa wanachama wote wa Shina utazungumzia mambo yenye maslahi ya CCM na ya wananchi mahali pale Shina lilipo, kama vile shughuli za Ulinzi na Kazi za Mkutano wa mwaka wa CCM wa Shina Mkutano wa Wanachama wote wa CCM wa Shina Kamati ya Uongozi ya Shina Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 18 19 (6) Atakuwa na wajibu wa kufuatilia utekelezaji wa mambo yote ya siasa katika Shina lake. (7) Atakuwa na wajibu wa kujenga uhusiano mwema wa wakazi wa Shina lake kwa lengo la kuunda mazingira ya amani na utulivu. (8) Ataongoza Kamati ya Uongozi ya Shina pale panapohusika. (9) Atakuwa Mwenyekiti wa Mkutano wa Mwaka wa CCM wa Shina, na Mkutano wa Wanachama wote wa Shina. (10) Katika Mikutano anayoongoza zaidi ya kuwa na kura yake ya kawaida, atakuwa pia na kura ya uamuzi, endapo kura za wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama Kikao anachokiongoza ni Kikao cha Uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za Wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. FUNGU LA II VIKAO VYA TAWI 31. (1) Kutakuwa na aina tatu za Matawi ya CCM kama ifuatavyo: - (a) Matawi yaliyoundwa vijijini ambayo yataitwa Matawi ya Vijijini. 29. Kazi za Kamati ya Uongozi ya Shina zitakuwa zifuatazo:- (1) Kuongoza na kusimamia utekelezaji wa maamuzi yote ya CCM na utendaji kazi katika shina. (2) Kuandaa shughuli za vikao vyote vya CCM vya shina. (3) Kutambua na kutunza kumbukumbu za wanachama wa CCM. (4) Kuhimiza ulipaji wa ada za wanachama (5) Unapofika wakati wa uchaguzi, Kamati ya uongozi ya Shina itaunda Kamati ya kampeni. 30. (1) Balozi/Mwenyekiti wa Shina atachaguliwa na Mkutano wa Mwaka wa CCM wa Shina. Atakuwa katika nafasi ya Uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na madaraka ya Kuangalia mambo ya CCM na utendaji kazi katika Shina. (3) Atakuwa kiungo cha wanachama wote katika Shina. (4) Atakuwa ndiye mwenezi na mhamasishaji mkuu wa Siasa ya CCM katika eneo lake. (5) Atakuwa na wajibu wa kuwaeleza Wanachama maamuzi yote ya CCM, kuwaongoza na kuwashirikisha katika utekelezaji wa maamuzi hayo, na kufikisha mapendekezo ya wanachama katika vikao vya juu. Kazi za Kamati ya Uongozi ya Shina Balozi wa Shina Aina za Matawi ya CCM Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 20 21 (e) Tawi jipya litaanzishwa baada ya kupata kibali cha kamati maalum ya Halmashauri kuu ya Taifa. 32. Kutakuwa na vikao vifuatavyo vya CCM katika kila Tawi:- (1) Mkutano Mkuu wa CCM wa Tawi. (2) Mkutano wa Wanachama wote wa Tawi. (3) Mkutano wa Halmashauri Kuu ya CCM ya Tawi. (4) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi. (5) Sekretarieti ya Halmashauri Kuu ya CCM ya Tawi. 33. (1) Mkutano Mkuu wa CCM wa Tawi utakuwa na Wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Tawi. (b) Katibu wa CCM wa Tawi. (c) Katibu wa Siasa na Uenezi wa Tawi. (d) Wajumbe wote wa Halmashauri Kuu ya CCM ya Tawi. (e) Mwenyekiti wa Serikali ya Kijiji/Mji mdogo/Mtaa/Kitongoji anayetokana na CCM anayeishi katika Tawi hilo. (f) Wajumbe wote wa mkutano mkuu wa CCM wa Kata/Wadi waliomo katika Tawi hilo. (g) Wajumbe wote wa Mkutano Mkuu wa CCM wa Wilaya waliomo katika Tawi hilo. (b) Matawi yaliyoundwa katika maeneo wanayoishi watu mijini ambayo yataitwa Matawi ya Mitaani. (c) Matawi ambayo yameundwa nje ya nchi yenye wanachama wa CCM wengi wanaoishi katika sehemu mbalimbali za nchi hiyo na ambao wana Mashina yao. Matawi haya yatafunguliwa kwa idhini ya Kamati Kuu. (2) (a) KWA TANZANIA BARA, Katika maeneo ya vijijini Tawi litafunguliwa tu iwapo mahali hapo panapohusika kuna Wanachama wasiopungua Mia moja na hamsini (150) na wasiozidi Elfu moja (1000). Pamoja na sharti hilo, sifa muhimu zitakazozingatiwa kufungua tawi ni jiografia na umbali wa kati ya tawi na tawi jingine la jirani. (b) Kwa matawi ya mitaani sehemu za mijini, Tawi litafunguliwa iwapo mahali hapo kuna wanachama wasiopungua mia mbili hamsini (250) na wasiozidi elfu moja (1000). (c) Tawi jipya litaanzishwa baada ya kupata kibali cha kamati kuu ya Halmashauri kuu ya Taifa. (d) KWA UPANDE WA ZANZIBAR, Tawi litafunguliwa iwapo mahali hapo kuna wanachama wasiopungua mia moja (100). Vikao vya CCM vya Matawi Mkutano Mkuu wa CCM wa Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 22 23 kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuhakikisha kwamba maazimio na maagizo ya ngazi za juu yanatekelezwa ipasavyo. (3) Kuzungumzia mambo yote yanayohusu Ulinzi na Usalama na Maendeleo kwa jumla katika Tawi hilo. (4) Unapofika wakati wa uchaguzi, Mkutano Mkuu wa CCM wa Tawi utashughulikia mambo yafuatayo:- (a) Kumchagua Mwenyekiti wa CCM wa Tawi. (b) Kuwachagua wajumbe watano wa kuhudhuria Mkutano Mkuu wa CCM wa Kata/Wadi. (c ) Kumchagua mjumbe mmoja wa kuhudhuria Mkutano Mkuu wa CCM wa Jimbo na wa Wilaya. (d) Kuwachagua wajumbe kumi wa kuingia katika Halmashauri Kuu ya CCM ya Tawi. (5) Kuunda Kamati za Mkutano Mkuu wa CCM wa Tawi kwa kadri itakavyoonekana inafaa. 35. (1) Kutakuwa na Mkutano wa Wanachama wote wa CCM katika kila Tawi. (2) Mkutano huo utazungumzia mambo yaliyo na maslahi ya CCM na ya wananchi mahali pale Tawi lilipo, kama vile shughuli za Ulinzi na Usalama, na maendeleo katika Tawi. (h) Mabalozi wa Mashina wa Tawi hilo. (i) Wenyeviti wa Mashina ya Wakereketwa/Maskani ya Tawi hilo. (j) Mwenyekiti na Katibu wa Tawi wa Jumuiya za CCM, na Mjumbe mmoja mwingine ambaye ni Mwanachama wa CCM aliyechaguliwa na kila Jumuiya iliyomo katika Tawi hilo. (k) Diwani anayetokana na CCM anayeishi katika Tawi hilo. (l) Wanachama wengine wote wa Tawi hilo. (2) Mkutano Mkuu wa CCM wa Tawi ndicho kikao kikuu cha CCM katika Tawi. (3) Mkutano Mkuu wa CCM wa Tawi utafanyika kwa kawaida mara moja kwa mwaka, lakini unaweza kufanyika wakati wowote mwingine endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (4) Mwenyekiti wa CCM wa Tawi ataongoza Mkutano Mkuu wa CCM wa Tawi. Lakini Mwenyekiti asipoweza kuhudhuria, Mkutano huo unaweza kumchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 34. Kazi za Mkutano Mkuu wa CCM wa Tawi zitakuwa zifuatazo: (1) Kupokea na kujadili Taarifa ya Kazi za CCM katika Tawi, iliyotolewa na Halmashauri Kuu ya CCM ya Tawi na Kazi za Mkutano Mkuu wa CCM wa Tawi Mkutano wa Wanachama wote wa Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 24 25 (d) Wajumbe kumi waliochaguliwa na Mkutano Mkuu wa CCM wa Tawi. (e) Wajumbe watatu wa Mkutano Mkuu wa CCM wa Kata/Wadi waliochaguliwa na Mkutano Mkuu wa CCM wa Tawi hilo. (f) Mwenyekiti wa Serikali ya Kijiji/Mtaa anayetokana na CCM anayeishi katika Tawi hilo. (g) Mjumbe mmoja wa Mkutano Mkuu wa CCM wa Wilaya aliyechaguliwa na Mkutano Mkuu wa CCM wa Tawi hilo. (h) Mwenyekiti na Katibu wa Tawi wa Jumuiya za CCM, na Mjumbe mmoja mwingine ambaye ni Mwanachama wa CCM aliyechaguliwa na kila Jumuiya inayohusika iliyomo katika Tawi hilo. (i) Wenyeviti wa Vitongoji wanaotokana na CCM wanaoishi katika Tawi hilo. (j) Diwani anayetokana na CCM anayeishi katika tawi hilo (k) Mabalozi/Wenyeviti wote wa Mashina katika Tawi hilo. (2) Halmashauri Kuu ya CCM ya Tawi itafanya Mikutano yake ya kawaida mara moja katika kila miezi sita lakini inaweza kufanya Mkutano usiokuwa wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo. (3) Mkutano wa Wanachama wote utafanyika kwa kawaida mara moja katika kila miezi mitatu, lakini unaweza kufanyika wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (4) Kiwango cha mahudhurio katika Mikutano ya Wanachama wote katika Tawi kitakuwa zaidi ya theluthi moja ya Wajumbe wake wenye haki ya kuhudhuria kikao hicho. (5) Mwenyekiti wa CCM wa Tawi ataongoza Mkutano wa Wanachama wote wa Tawi, lakini Mwenyekiti asipoweza kuhudhuria, Mkutano utamchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. (6) Siku ya kupiga Kura za maoni kwa wagombea wa ngazi za Kijiji na Mtaa, wana CCM wote watapiga Kura zao za maoni wakiwa katika Matawi ya Vijijini au Mitaani ambako wanaishi na ambako wao ni wanachama. Katika ngazi ya kitongoji, Kura za maoni zitapigwa na Wanachama wote wa CCM wanaoishi katika kitongoji kinachohusika. 36. (1) Halmashauri Kuu ya CCM ya Tawi itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Tawi. (b) Katibu wa CCM wa Tawi. (c) Katibu wa Siasa na Uenezi wa Tawi. Halmashauri Kuu ya CCM ya Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 26 27 (8) Unapofika wakati wa Uchaguzi, Halmashauri Kuu ya CCM ya Tawi itashughulikia mambo yafuatayo:- (a) Kufikiria na kufanya Uteuzi wa Mwisho wa wanachama wanaoomba nafasi za uongozi wa Shina la CCM. (b) Kumchagua Katibu wa CCM wa Tawi; (c) Kumchagua Katibu wa Siasa na Uenezi wa Tawi. (d) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Kata/Wadi juu ya Wanachama wa CCM wanoomba kugombea Uenyekiti wa Vitongoji kwa mujibu wa Sheria za uchaguzi wa Serikali za Mitaa. (e) Kuwachagua wajumbe watatu wa kuingia katika Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi kutoka miongoni mwao. (9) Kujaza nafasi wazi za uongozi zinazotokea katika Tawi isipokuwa nafasi ya Mwenyekiti wa CCM wa Tawi. (10) Kuunda Kamati Ndogo za Utekelezaji kama itakavyoonekana inafaa kwa ajili ya utekelezaji bora zaidi wa Siasa na kazi za CCM katika Tawi. (11) Kupokea na kujadili taarifa za Kamati Ndogo za utekelezaji wa kazi za CCM katika Tawi. (3) Mwenyekiti wa CCM wa Tawi ataongoza Mkutano wa Halmashauri Kuu ya CCM ya Tawi, lakini Mwenyekiti asipoweza kuhudhuria, Katibu wa CCM wa Tawi atakuwa Mwenyekiti wa muda wa Mkutano huo. 37. Kazi za Halmashauri Kuu ya CCM ya kila Tawi zitakuwa zifuatazo:- (1) Kuongoza na kusimamia Ujenzi wa Ujamaa na Kujitegemea katika eneo la Tawi. (2) Kueneza Siasa na kueleza mipango ya CCM kwa Wanachama wote wa Tawi na kutafuta kila njia inayofaa ya kuimarisha CCM katika eneo la Tawi. (3) Kutoa msukumo wa utekelezaji wa Ilani ya Uchaguzi ya CCM na kufanya kampeni za uchaguzi na kampeni nyinginezo katika Tawi. (4) Kuona kwamba unakuwepo Ulinzi na Usalama katika eneo la Tawi. (5) Kuangalia mwenendo na vitendo vya wanachama na viongozi wa CCM katika Tawi na inapolazimu kutoa taarifa kwa vikao vya CCM vinavyohusika. (6) Kuongoza Mashina ya Tawi hilo katika vitendo na njia zinazofaa za kuimarisha CCM. (7) Kufikisha maazimio na maagizo ya Vikao vya CCM vya juu kwa Wanachama, na kufikisha mapendekezo ya Wanachama katika vikao vya juu. Kazi za Halmashauri Kuu ya CCM ya Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 28 29 Katibu wa CCM wa Tawi atakuwa Mwenyekiti wa muda wa Mkutano huo. 39. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika eneo lake. (2) Kueneza itikadi na Siasa ya CCM katika Tawi. (3) Kuandaa mikakati ya kampeni za uchaguzi na kampeni nyinginezo katika Tawi. (4) Kusimamia Utekelezaji wa kila siku wa Siasa na maamuzi ya CCM chini ya Uongozi wa Halmashauri Kuu ya CCM ya Tawi. (5) Kupanga mipango ya kukipatia Chama mapato, kusimamia kwa dhati utekelezaji wa mipango hiyo, kudhibiti mapato na kusimamia matumizi bora ya fedha na mali za Chama katika Tawi. (6) Unapofika wakati wa Uchaguzi, Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi itashughulikia mambo yafuatayo: - (a) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya Kata/Wadi juu ya wanachama wanaoomba kugombea nafasi za uongozi wa Tawi hilo; na uongozi wa jumuiya za CCM kupitia Tawi hilo. (12) Kupokea, kuzingatia na kuamua juu ya mapendekezo ya vikao vya CCM vilivyo chini yake. (13) Kuunda Kamati ya Usalama na Maadili ya CCM ya Tawi. 38. (1) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Tawi. (b) Katibu wa CCM wa Tawi. (c) Katibu wa Siasa na Uenezi wa Tawi. (d) Wajumbe watatu waliochaguliwa na Halmashauri Kuu ya CCM ya Tawi kutoka miongoni mwao. (e) Mwenyekiti wa Serikali ya Kijiji/Mtaa anayetokana na CCM anayeishi katika Tawi hilo. (f) Diwani anayetokana na CCM anayeishi katika Tawi hilo. (g) Mwenyekiti wa Tawi wa kila Jumuiya ya CCM iliyomo katika Tawi hilo. (2) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi itakutana si chini ya mara moja katika kila miezi mitatu, lakini inaweza kufanya mkutano usiokuwa wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Tawi ataongoza Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya Tawi. Lakini Mwenyekiti asipoweza kuhudhuria, Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi Kazi za Kamati ya Siasa ya Halmashauri Kuu ya Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 30 31 40. Sekretarieti ya Halmashauri Kuu ya CCM ya Tawi itakuwa na wajumbe wafuatao: - (a) Katibu wa CCM wa Tawi ambaye atakuwa Mwenyekiti. (b) Katibu wa Siasa na Uenezi wa Tawi. (c) Makatibu wa Matawi ya Jumuiya za CCM. 41. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Tawi yatakuwa yauatayo:- (a) Kuongoza na kusimamia shughuli za Chama katika Tawi. (b) Kuandaa Vikao vyote vya CCM katika Tawi. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Tawi yatagawanyika ifuatavyo:- (a) Katibu wa CCM wa Tawi. (b) Idara ya Siasa na Uenezi ya Tawi. (c) Idara ya Organaizesheni ya Tawi. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya Tawi isipokuwa kwamba Katibu wa CCM wa Tawi atakuwa ndiye Katibu wa Organaizesheni katika Tawi. 42. Kutakuwa na Wakuu wa CCM wafuatao katika Tawi:- (a) Mwenyekiti wa CCM wa Tawi (b) Katibu wa CCM wa Tawi (b) Kufikiria na kutoa mapendekezo kwa Halmashauri Kuu ya CCM ya Tawi juu ya Wanachama wanaoomba nafasi ya uongozi wa Shina la CCM katika Tawi hilo. (c) Kufikiria na kutoa mapendekezo kwa Halmashauri Kuu ya CCM ya Tawi juu ya wanachama wa CCM wanaoomba nafasi ya Mwenyekiti wa Kitongoji wakati wa Uchaguzi wa Serikali za Mitaa. (d) Kufikiria na kutoa mapendekezo kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi juu ya Wanachama wanaoomba nafasi ya Ujumbe wa Halmashauri Kuu ya Tawi, Ukatibu wa Siasa na Uenezi wa Tawi, Uenyekiti wa Mtaa, Ujumbe wa Kamati ya Mtaa, Uenyekiti wa Kijiji na Ujumbe wa Halmashauri ya kijiji kupitia Tawi hilo kwa mujibu wa sheria za uchaguzi wa Serikali za Mitaa. (7) Kufikiria na kutoa uamuzi wa mwisho maombi ya Uanachama. (8) Kuandaa mikutano ya Halmashauri Kuu ya CCM katika Tawi. (9) Kuona kwamba unakuwepo Ulinzi na Usalama wa umma katika Tawi. Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Tawi Wakuu wa CCM katika Tawi Sekretarieti ya Halmashauri Kuu ya Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 32 33 (2) Atakuwa ndiye Mtendaji Mkuu wa CCM katika Tawi, na atafanya kazi chini ya uongozi wa Halmashauri kuu ya CCM ya Tawi lake. majukumu yake ni haya yafuatayo:- (a) Kuratibu kazi zote za CCM katika Tawi. (b) Kuitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya Tawi kwa madhumuni ya kushauriana, kuandaa agenda za Kamati ya Siasa ya Tawi na kuchukua hatua za utekelezaji wa maamuzi ya CCM. (c) Kusimamia kazi za Utawala na Uendeshaji wa Chama katika Tawi. (d) Kufuatilia na kuratibu masuala ya Usalama na Maadili ya Chama katika Tawi. (e) Kusimamia Udhibiti wa Fedha na Mali ya Chama katika Tawi. ( f ) Kuitisha mikutano ya Kamati ya Siasa ya Tawi, Halmashauri Kuu ya Tawi na Mkutano Mkuu wa Tawi baada ya kushauriana na Mwenyekiti wa CCM wa Tawi. (3) Atakuwa ndiye Mkurugenzi wa Uchaguzi katika Tawi. (4) Atashughulikia masuala yote ya Organaizesheni ya CCM katika Tawi, ambayo ni:- (a) Masuala yote ya wanachama. 43. (1) Mwenyekiti wa CCM wa Tawi atachaguliwa na Mkutano Mkuu wa Tawi. Atakuwa katika nafasi hiyo ya uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na madaraka ya kuangalia mambo yote ya CCM katika Tawi. (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Tawi, Mkutano wa Wanachama wote wa Tawi, Mkutano wa Halmashauri Kuu ya Tawi na Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Tawi. (4) Katika Mikutano anayoiongoza, zaidi ya kuwa na kura yake ya kawaida, Mwenyekiti wa CCM wa Tawi atakuwa pia na kura ya uamuzi, endapo kura za wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama Kikao anachokiongoza ni Kikao cha Uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za Wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 44. (1) Katibu wa CCM wa Tawi atachaguliwa na Halmashauri Kuu ya CCM ya Tawi lake. Atakuwa katika nafasi hiyo ya uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. Mwenyekiti wa CCM wa Tawi Katibu wa CCM wa Tawi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 34 35 FUNGU LA III VIKAO VYA KATA/WADI 46. Kutakuwa na Vikao vya CCM vifuatavyo katika kila Kata ya Tanzania Bara yenye Matawi ya CCM yasiyopungua mawili, na katika kila Wadi ya Zanzibar (1) Mkutano Mkuu wa CCM wa Kata/Wadi. (2) Halmashauri Kuu ya CCM ya Kata/Wadi. (3) Kamati ya Siasa ya Halmashauri Kuu ya Kata/Wadi. (4) Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/Wadi. 47. (1) Mkutano Mkuu wa CCM wa Kata/Wadi utakuwa na Wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Kata/Wadi. (b) Katibu wa CCM wa Kata/Wadi. (c) Katibu wa Siasa na Uenezi wa Kata/Wadi. (d) Mbunge na Mwakilishi wa Jimbo linalohusika anayetokana na CCM anayeishi katika Kata/Wadi hiyo, au katika Kata/Wadi ambayo atakuwa ameichagua mwenyewe kwa madhumuni hayo. (e) Wenyeviti wote wa CCM wa Matawi ya Kata/Wadi hiyo. (f) Makatibu wote wa CCM wa Matawi ya Kata/Wadi hiyo. (g) Makatibu wa Siasa na Uenezi wa CCM wa Matawi ya Kata/Wadi hiyo. (b) Kufuatilia vikao na maamuzi ya vikao vya Chama. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. (d) Uchaguzi wa ndani ya CCM ngazi ya Shina na Tawi, na ule wa Uwakilishi katika vyombo vya Dola, (e) Kusimamia masuala yote ya Kusimamia Muundo, Katiba, Kanuni na Taratibu za Chama na Jumuiya za CCM. 45. Katibu wa Siasa na Uenezi wa Tawi atachaguliwa na Halmashauri Kuu ya CCM ya Tawi na atashughulikia masuala yote ya Siasa na Uenezi katika Tawi. Majukumu yake ni haya yafuatayo:- (a) Kusimamia, kueneza na kufafanua masuala yote ya Itikadi, Siasa na Sera za CCM katika Tawi. (b) Kushughulikia mafunzo na maandalizi ya Makada na Wanachama katika Tawi. (c) Kufuatilia utekelezaji wa Sera za CCM za kijamii na Ilani za uchaguzi za CCM katika Tawi. (d) Kuwa na mipango ya mawasiliano na uhamasishaji wa Umma katika Tawi. (e) Kufuatilia hali ya kisiasa na harakati za Vyama vya Siasa katika Tawi. (f) Kufuatilia mwenendo wa Jumuiya za Kijamii katika Tawi. Katibu wa Siasa na Uenezi wa Tawi Vikao vya CCM Kata Mkutano Mkuu wa CCM wa Kata/Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 36 37 (p) Mwenyekiti na Katibu wa Kata/ Wadi wa jumuiya za CCM na mjumbe mmoja mwingine ambaye ni mwanachama wa CCM aliyechaguliwa na kila Jumuiya inayohusika iliyomo katika Kata/ Wadi hiyo. (2) Mkutano Mkuu wa CCM wa Kata/Wadi ndicho kikao kikuu cha CCM katika Kata/ Wadi. Mkutano Mkuu wa CCM wa Kata/ Wadi utafanyika kwa kawaida mara moja kwa mwaka, lakini unaweza kufanyika wakati wowote mwingine endapo kutatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Kata/Wadi ataongoza Mkutano Mkuu wa CCM wa Kata/Wadi lakini Mwenyekiti asipoweza kuhudhuria, Mkutano huo utamchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 48. Kazi za Mkutano Mkuu wa CCM wa Kata/Wadi zitakuwa zifuatazo:- (1) Kupokea na kujadili taarifa ya kazi za CCM katika Kata/Wadi iliyotolewa na Halmashauri Kuu ya CCM ya Kata/Wadi na kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuhakikisha kwamba maazimio na maagizo ya ngazi ya juu yanatekelezwa ipasavyo. (h) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa CCM wa kila Tawi kuhudhuria Mkutano Mkuu wa Kata/Wadi. (i) Mjumbe mmoja anayewakilisha Tawi la CCM kwenye Mkutano Mkuu wa Jimbo na wa Wilaya. (j) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa CCM wa Kata/ Wadi kuingia katika Halmashauri Kuu ya CCM ya Kata/Wadi. (k) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa CCM wa Kata/Wadi wa kuhudhuria Mkutano Mkuu wa CCM wa Wilaya na wajumbe watano wa kuhudhuria Mkutano Mkuu wa Jimbo Zanzibar. (l) Wajumbe waliochaguliwa na Mkutano Mkuu wa CCM wa Kata/ Wadi wa kuhudhuria Mkutano Mkuu wa CCM wa Mkoa, mmoja kutoka kila Kata ya Tanzania Bara na watano kutoka kila Wadi ya Zanzibar. (m) Wenyeviti wote wa Serikali za Vijiji/Mitaa wa Kata/Wadi hiyo wanaotokana na CCM. (n) Diwani wa Kata/Wadi anayetokana na CCM anayewakilisha Kata/Wadi hiyo, na Madiwani wa aina nyingine wanaoishi katika Kata/Wadi hiyo. (o) Wajumbe wa Halmashauri Kuu ya Wilaya wanaoishi katika Kata/Wadi hiyo. Kazi za Mkutano Mkuu wa CCM wa Kata/Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 38 39 (c) Katibu wa Siasa na Uenezi wa Kata/Wadi. (d) Mbunge na Mwakilishi wa Jimbo linalohusika anayetokana na CCM anayeishi katika Kata/Wadi hiyo, au katika Kata/Wadi ambayo ameichagua mwenyewe kwa madhumuni hayo. (e) Diwani anayetokana na CCM anayewakilisha Kata/Wadi husika, na Madiwani wa aina nyingine wanaoishi katika Kata/Wadi hiyo. (f) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa Kata/Wadi hiyo. (g) Wenyeviti wote wa CCM wa Matawi ya Kata/Wadi hiyo. (h) Makatibu wote wa CCM wa Matawi ya Kata/Wadi hiyo. (i) Makatibu wote wa Siasa na Uenezi wa Matawi yaliyomo katika Kata/ Wadi hiyo. (j) Wenyeviti wote wa Serikali za vijiji/ Mitaa wanaotokana na CCM katika Kata/Wadi hiyo. (k) Wajumbe wa Halmashauri Kuu ya Wilaya waliomo katika Kata/Wadi hiyo. (l) Mwenyekiti na Katibu wa Kata/Wadi wa Jumuiya na mjumbe mmoja mwingine ambaye ni mwanachama wa CCM aliyechaguliwa na kila Jumuiya ya CCM iliyomo katika Kata/Wadi hiyo. (3) Kuzungumzia mambo yote yanayohusu Ulinzi na Usalama, na maendeleo kwa jumla katika Kata/Wadi. (4) Unapofika wakati wa Uchaguzi, Mkutano Mkuu wa CCM wa Kata/Wadi utashughulikia mambo yafuatayo: - (a) Kumchagua Mwenyekiti wa CCM wa Kata/Wadi. (b) Kuwachagua wajumbe watano wa kuingia katika Halmashauri Kuu ya CCM ya Kata/Wadi. (c) Kuwachagua wajumbe watano wa kuhudhuria Mkutano Mkuu wa Jimbo kwa upande wa Zanzibar na wajumbe watano wa kuhudhuria Mkutano Mkuu wa CCM wa Wilaya. (d) Kuwachagua wajumbe wa kuhudhuria Mkutano Mkuu wa CCM wa Mkoa, mmoja kutoka kila Kata ya Tanzania Bara na watano kutoka kila Wadi ya Zanzibar. (e) Kupiga kura za maoni za kumpendekeza mwanachama mmoja atakayesimama kugombea Udiwani katika kata/Wadi hiyo. (5) Kuunda Kamati za Mkutano Mkuu wa CCM wa Kata/Wadi kwa kadri itakavyoonekana inafaa. 49. (1) Halmashauri Kuu ya CCM ya Kata/Wadi itakuwa na wajumbe wafuatao: - (a) Mwenyekiti wa CCM wa Kata/Wadi. (b) Katibu wa CCM wa Kata/Wadi. Halmashauri Kuu ya CCM ya Kata/ Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 40 41 hiyo kuhusu vitendo na njia zinazofaa za kuimarisha CCM. (7) Kuangalia mwenendo na vitendo vya wanachama pamoja na viongozi wa CCM na inapolazimu kutoa taarifa kwa vikao vinavyohusika. (8) Kufikisha Matawini maazimio na maagizo ya vikao vya juu na kufikisha kwenye Vikao vya juu mapendekezo kutoka Matawini. (9) Unapofika wakati wa Uchaguzi Halmashauri Kuu ya CCM ya Kata/Wadi itashughulikia mambo yafuatayo:- (a) Kumchagua Katibu wa CCM wa Kata/Wadi. (b) Kumchagua Katibu wa Siasa na Uenezi wa Kata/Wadi. (c) Kuwachagua wajumbe watatu wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi kutoka miongoni mwao. (d) Kwa Tanzania Bara itafikiria na kufanya uteuzi wa mwisho wa wanachama wanaoomba kugombea Uenyekiti wa Vitongoji vya Kata hiyo. (e) Kufikiria na kufanya uteuzi wa mwisho wa Wanachama wanaoomba Ujumbe wa Halmashauri Kuu ya Tawi, Wajumbe wa Mkutano Mkuu wa CCM wa Kata/Wadi, Jimbo na Wilaya wanaotoka katika Tawi hilo. (2) Halmashauri Kuu ya CCM ya Kata/ Wadi itafanya Mikutano yake ya kawaida mara moja kila baada ya miezi sita, lakini inaweza kufanya mikutano isiyo ya kawaida wakati wowote endapo kutatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Kata/Wadi ataongoza Mkutano wa Halmshauri Kuu ya CCM ya Kata/Wadi; lakini Mwenyekiti asipoweza kuhudhuria, Katibu wa CCM wa Kata/Wadi atakuwa Mwenyekiti wa muda wa Mkutano huo. 50. Kazi za Halmashauri Kuu ya CCM ya Kata/ Wadi zitakuwa zifuatazo:- (1) Kuongoza na kusimamia ujenzi wa Ujamaa na Kujitegemea katika eneo lake la Kata/Wadi. (2) Kusimamia uenezi wa Itikadi na Siasa ya CCM, na kueleza mipango ya CCM kwa Matawi yote ya Kata/Wadi na kubuni mbinu zinazofaa za kuimarisha CCM katika eneo la Kata/Wadi inayohusika. (3) Kupanga mikakati ya kampeni za uchaguzi na kampeni nyinginezo. (4) Kutoa msukumo wa utekelezaji wa Ilani ya CCM na kusimaia utekelezaji wa siasa na maazimio ya CCM kwa jumla. (5) Kuona kwamba unakuwepo Ulinzi na Usalama katika eneo la Kata/Wadi hiyo. (6) Kuziongoza Halmashauri Kuu za CCM za Matawi yaliyomo kati ka Kata/Wadi Kazi za Halmashauri Kuu ya CCM ya Kata/ Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 42 43 51. (1) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Kata/Wadi. (b) Katibu wa CCM wa Kata/Wadi. (c) Katibu wa Siasa na Uenezi wa Kata/Wadi. (d) Diwani anayetokana na CCM anayewakilisha Kata/Wadi hiyo, na Madiwani wa aina nyingine wanaotokana na CCM wanaoishi katika Kata/Wadi hiyo. (e) Wajumbe watatu waliochaguliwa na Halmashauri Kuu ya CCM ya Kata/ Wadi hiyo. (f) Mwenyekiti wa Kata/Wadi wa kila Jumuiya ya CCM katika Kata/Wadi hiyo. (2) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi itafanya mikutano yake ya kawaida mara moja katika kila miezi mitatu, lakini inaweza kufanya mikutano isiyo ya kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Kata/Wadi ataongoza Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/ Wadi. Lakini Mwenyekiti asipoweza kuhudhuria Katibu wa CCM wa Kata/ Wadi atakuwa Mwenyekiti wa muda wa Mkutano huo. (f) Kufanya uteuzi wa mwisho wa majina ya wanachama wa CCM watakaosimama katika uchaguzi wa Mwenyekiti na Katibu wa Tawi wa kila Jumuiya ya CCM na wajumbe wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Matawi yaliyomo katika Kata/Wadi hiyo (10) Kujaza, kwa niaba ya Mkutano Mkuu wa CCM wa Kata/Wadi, nafasi za uongozi zinazokuwa wazi, isipokuwa ya Mwenyekiti wa CCM wa Kata/Wadi. (11) Kupokea, kuzingatia na kuamua juu ya mapendekezo ya vikao vya CCM vilivyo chini yake. (12) Kumsimamisha uanachama mwanachama yeyote wa ngazi ya Tawi au Shina ambaye mwenendo na tabia yake vinamuondolea sifa za uanachama. (13) Kuunda Kamati Ndogo za Utekelezaji kwa kadri itakavyoonekana inafaa kwa ajili ya utekelezaji bora zaidi wa kazi za CCM katika Kata/Wadi hiyo. (14) Kupokea na kujadili taarifa za Kamati Ndogo za Utekelezaji wa kazi za CCM za Kata/Wadi na Kamati za Mkutano Mkuu wa CCM wa Kata/Wadi. (15) Kuunda Kamati ya Usalama na Maadili ya CCM ya Kata/Wadi. Kamati ya Siasa ya Halmashauri kuu ya CCM ya Kata/ Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 44 45 (b) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya juu ya wanachama wanaoomba Udiwani, Uenyekiti wa Mtaa, Ujumbe wa Kamati ya Mtaa, Uenyekiti wa Kijiji na Ujumbe wa Halmashauri ya Kijiji kwa mujibu wa sheria za uchaguzi wa Serikali za Mitaa. (c) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya Kata/Wadi juu ya Wanachama wa CCM wanaoomba Uenyekiti na Ukatibu wa Tawi wa Jumuiya za CCM, na Ujumbe wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Kata/Wadi hiyo. (d) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Wilaya juu ya Wanachama wanaoomba nafasi ya Mwenyekiti na Katibu wa Jumuiya za CCM wa Kata/Wadi. (8) Kuandaa mikutano ya Halmashauri Kuu ya CCM ya Kata/Wadi. (9) Kuona kwamba masuala ya Ulinzi na Usalama katika Kata/Wadi yanazingatiwa. 53. Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/Wadi itakuwa na wajumbe wafuatao: - (a) Katibu wa CCM wa Kata/Wadi ambaye atakuwa Mwenyekiti. 52. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/ Wadi zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika Kata/ Wadi hiyo. (2) Kueneza Itikadi na Siasa ya CCM katika Kata/Wadi hiyo. (3) Kuandaa mikakati ya kampeni za uchaguzi na kampeni nyinginezo katika Kata/Wadi hiyo. (4) Kusimamia utekelezaji wa shughuli za kila siku za CCM katika Kata/Wadi chini ya uongozi wa Halmashauri Kuu ya CCM ya Kata/Wadi hiyo. (5) Kumsimamisha uongozi kiongozi yeyote wa ngazi ya Tawi au Shina endapo itaridhika kwamba tabia na mwenendo wake vinamuondolea sifa ya uongozi. (6) Kupanga mipango ya kukipatia Chama mapato, kusimamia kwa dhati utekelezaji wa mipango hiyo, kudhibiti mapato na kusimamia matumizi bora ya fedha na mali za Chama katika Kata/Wadi. (7) Unapofika wakati wa Uchaguzi Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi itashughulikia mambo yafuatayo:- (a) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya juu ya wanachama wanaoomba nafasi ya uongozi wa CCM kupitia Kata/Wadi hiyo. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata / Wadi Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/ Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 46 47 uongozi kwa muda wa miaka mitano lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na madaraka ya kuangalia mambo yote ya CCM katika Kata/Wadi. (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Kata/Wadi, Mkutano wa Halmashauri Kuu ya CCM ya Kata/Wadi na Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Kata/Wadi. (4) Katika mikutano anayoiongoza, zaidi ya kuwa na kura yake ya kawaida, Mwenyekiti wa CCM wa Kata/Wadi pia atakuwa na kura ya uamuzi endapo kura za Wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama kikao anachokiongoza ni kikao cha uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za Wajumbe zimelingana. Wajumbe wa Kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 57. (1) Katibu wa CCM wa Kata/Wadi atachaguliwa na Halmashauri Kuu ya CCM ya Kata/Wadi. (2) Atakuwa ndiye Mtendaji Mkuu wa CCM katika Kata/Wadi na atafanyakazi chini ya uongozi wa Halmashauri Kuu ya Kata/Wadi yake. Majukumu yake ni haya yafuatayo:- (a) Kuratibu kazi zote za CCM katika Kata/Wadi. (b) Katibu wa Siasa na Uenezi Kata/Wadi. (c) Makatibu wa Kata/Wadi wa Jumuiya za CCM. 54. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/Wadi yatakuwa yafuatayo:- (a) Kuongoza na kusimamia shughuli za Chama katika Kata/Wadi. (b) Kuandaa Vikao vyote vya Chama vya Kata/Wadi. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Kata/Wadi yatagawanyika ifuatavyo:- (a) Katibu wa CCM wa Kata/Wadi. (b) Idara ya Siasa na Uenezi ya Kata/ Wadi. (c) Idara ya Organaizesheni ya Kata/ Wadi. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya CCM ya Kata/Wadi isipokuwa kwamba Katibu wa CCM wa Kata/Wadi atakuwa ndiye Katibu wa Organaizesheni katika Kata/Wadi. 55. Kutakuwa na Wakuu wa CCM wafuatao katika Kata/Wadi:- (1) Mwenyekiti wa CCM wa Kata/Wadi. (2) Katibu wa CCM wa Kata/Wadi. 56. (1) Mwenyekiti wa CCM wa Kata/Wadi atachaguliwa na Mkutano Mkuu wa CCM wa Kata/Wadi. Atashika nafasi hiyo ya Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/ Wadi Wakuu wa CCM wa Kata/Wadi Mwenyekiti wa CCM wa Kata/Wadi Katibu wa CCM wa Kata/Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 48 49 (e) Kusimamia Muundo, Katiba, Kanuni na Taratibu za Chama na Jumuiya za CCM. 58. Katibu wa Siasa na Uenezi wa Kata/Wadi atachaguliwa na Halmashauri Kuu ya CCM ya Kata/Wadi na atashughulikia masuala yote ya Siasa na Uenezi katika Kata/Wadi. Majukumu yake ni haya yafutayo:- (a) Kusimamia, kueneza na kufafanua masuala yote ya Itikadi, Siasa na Sera za Chama katika Kata/Wadi. (b) Kupanga na kusimamia mafunzo na maandalizi ya Makada na wanachama katika Kata/Wadi. (c) Kufuatilia utekelezaji wa Sera za Chama za Kijamii na Ilani za Uchaguzi za Chama katika Kata/Wadi. (d) Kuwa na mipango ya Mawasiliano na Uhamasishaji wa Umma katika Kata/ Wadi. (e) Kufuatilia hali ya kisiasa na harakati za Vyama vya Siasa katika Kata/Wadi. (f) Kufuatilia mwenendo wa Jumuiya za Kijamii katika Kata/Wadi (b) Kuitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya CCM ya Kata/Wadi kwa madhumuni ya kushauriana, kuandaa agenda za Kamati ya Siasa ya Kata/Wadi na kuchukua hatua za utekelezaji wa maamuzi ya CCM. (c) Kusimamia kazi zote za Utawala na Uendeshaji wa Chama katika Kata/ Wadi. (d) Kufuatilia na kuratibu masuala ya Usalama na maadili ya Chama katika Kata/Wadi. (e) Kusimamia Udhibiti wa Fedha na Mali ya Chama katika Kata/Wadi. (3) Ataitisha Mikutano ya Kamati ya Siasa ya Kata/Wadi, Halmashauri Kuu ya Kata/ Wadi na Mkutano Mkuu wa Kata/Wadi baada ya kushauriana na Mwenyekiti wa CCM wa Kata Wadi. (4) Atakuwa ndiye Mkurugenzi wa Uchaguzi katika Kata/Wadi. (5) Atashughulikia masuala yote ya Organaizesheni ya CCM katika Kata/ Wadi, ambayo ni:- (a) Masuala yote ya wanachama. (b) Kufuatilia vikao na maamuzi ya Vikao vya Chama. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. (d) Kusimamia masuala yote ya Uchaguzi ndani ya Chama na ule wa uwakilishi katika vyombo vya Dola, Katibu wa Siasa na Uenezi wa CCM wa Kata/Wadi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 50 51 (e) Makatibu wa Jumuiya za CCM, wa Kata zote zilizomo katika Jimbo la Uchaguzi linalohusika (f) Mbunge wa CCM wa Jimbo hilo la Uchaguzi na Wabunge wa CCM wa aina nyingine wanaoishi katika Jimbo la Uchaguzi linalohusika. Isipokuwa kwamba, katika Wilaya ambazo Wilaya nzima ni Jimbo la Uchaguzi, Mkutano Mkuu wa CCM wa Wilaya uliotajwa katika Ibara za 72(1) na 73(1)(a)-(v) za Katiba ndio utakaowapigia Kura za Maoni wanaoomba kugombea Ubunge. (3) Mkutano huu utakuwa na kazi moja tu ya kupiga Kura za Maoni kwa Wagombea Ubunge kwa Tiketi ya CCM. Kwa sababu hiyo, Mkutano huu utafanya vikao vyake katika nyakati zile tu ambapo kuna zoezi la Kura za Maoni. 59B. Kwa upande wa Tanzania Zanzibar kutakuwa na vikao vifuatavyo katika kila Jimbo:- (1) Mkutano Mkuu wa CCM wa Jimbo. (2) Halmashauri Kuu ya CCM ya Jimbo. (3) Kamati ya Siasa ya Halmashauri Kuu ya Jimbo. (4) Sekretarieti ya Halmashauri Kuu ya CCM ya Jimbo. 60. (1) Mkutano Mkuu wa CCM wa Jimbo utakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Jimbo. FUNGU LA IV VIKAO VYA JIMBO 59. Kutakuwa na Vikao vya CCM vifuatavyo katika kila Jimbo:- 59A. (1) Kwa upande wa Tanzania Bara, kutakuwa na Mkutano Mkuu wa Jimbo kwa kila Jimbo la Uchaguzi wa Wabunge. (2) Wajumbe wa Mkutano Mkuu wa Jimbo watakuwa ni hawa wafuatao (a) Wajumbe wa Mkutano Mkuu wa Wilaya waliotajwa katika Ibara ya 73(1)(a)-(v) ya Katiba ya CCM ambao ni Mwenyekiti wa CCM Wilaya, Katibu wa CCM wa Wilaya, Mjumbe wa Halmashauri Kuu ya Taifa nafasi ya Mkoa, na Wajumbe wa Halmashauri Kuu ya Taifa wa aina nyingine wanaoishi katika Wilaya hiyo, Mkuu wa Wilaya anayetokana na CCM, Katibu wa Siasa na Uenezi wa Wilaya. (b) Viongozi wote wa CCM wa Wilaya wanaoishi katika Jimbo la Uchaguzi linalohusika. (c) Wajumbe wa Mkutano Mkuu wa Wilaya waliotajwa katika Ibara ya 73(1)(a)-(v) wanaoishi katika Jimbo la Uchaguzi linalohusika. (d) Wajumbe wote wa Kamati za Siasa za Kata zilizomo katika Jimbo la Uchaguzi linalohusika Vikao vya CCM vya Jimbo Mkutano Mkuu wa CCM wa Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 52 53 (n) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa CCM wa kila Jimbo wa kuhudhuria Mkutano Mkuu wa CCM wa Wilaya. (o) Wajumbe watatu waliochaguliwa na Mkutano Mkuu wa CCM wa Jimbo wa kuhudhuria Mkutano Mkuu wa CCM wa Mkoa, (p) Madiwani wanaotokana na CCM wanaowakilisha Wadi zilizomo katika Jimbo husika, na Madiwani wa aina nyingine wanaoishi katika Wadi za Jimbo hilo. (q) Mjumbe mmoja wa kuhudhuria Mkutano Mkuu wa CCM wilaya kutoka kila Tawi la Jimbo hilo. (r) Wajumbe wa Halmashauri Kuu ya Wilaya na Mkoa waliomo katika Jimbo hilo. (s) Mwenyekiti na Katibu wa Jimbo wa jumuiya ya CCM, na mjumbe mmoja mwingine ambaye ni mwanachama wa CCM aliyechaguliwa na kila Jumuiya iliyomo katika Jimbo hilo. (2) Mkutano Mkuu wa Jimbo ndicho kikao kikuu cha CCM katika Jimbo. (3) Mkutano Mkuu wa Jimbo utafanya mikutano yake ya kawaida mara moja kwa mwaka, lakini unaweza kufanyika wakati wowote mwingine endapo itatokea haja ya kufanya hivyo, au kwa maagizo ya vikao vya juu. (b) Katibu wa CCM wa Jimbo. (c) Katibu wa Siasa na Uenezi wa Jimbo. (d) Mbunge au Mwakilishi anayetokana na CCM, na Wabunge au Wawakilishi wa aina nyingine wanaoishi katika Jimbo hilo. (e) Wenyeviti wote wa CCM wa Matawi ya Jimbo hilo. (f) Makatibu wote wa CCM wa Matawi ya Jimbo hilo. (g) Makatibu wa Siasa na Uenezi wa CCM wa Matawi yote ya Jimbo hilo. (h) Mwenyekiti na Katibu wa CCM wa kila Wadi ya Jimbo. (i) Makatibu wa siasa na Uenezi wa CCM wa Wadi zote za Jimbo. (j) Wenyeviti na Makatibu wa Jumuiya za CCM wa Wadi zote za Jimbo. (k) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa Jimbo kuingia katika Halmashauri Kuu ya CCM ya Jimbo. (l) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa kila Wadi kuhudhuria mkutano Mkuu wa CCM wa Mkoa (m) Wajumbe watano waliochaguliwa na Mkutano Mkuu wa CCM wa kila Wadi iliyomo katika Jimbo hilo Kuingia katika mkutano Mkuu wa Jimbo. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 54 55 (e) Kupiga kura za maoni ya awali kwa waombaji wa nafasi ya Ubunge na Uwakilishi katika Jimbo husika. (5) Kuunda kamati za Mkutano Mkuu wa CCM wa Jimbo kwa kadri itakavyoonekana inafaa. 62. (1) Halmashauri Kuu ya CCM ya Jimbo itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Jimbo. (b) Katibu wa CCM wa Jimbo. (c) Katibu wa Siasa na Uenezi wa Jimbo. (d) Mbunge na Mwakilishi wanaotokana na CCM wanaowakilisha Jimbo husika, na Wabunge au Wawakilishi wa aina nyingine wanaoishi katika Jimbo hilo. (e) Madiwani wanaotokana na CCM wanaowakilisha Kata/Wadi zilizomo katika Jimbo husika, na Madiwani wa aina nyingine wanaoishi katika Kata/Wadi za Jimbo hilo. (f) Wajumbe watano waliochaguliwa na Mkutano wa Jimbo kuingia katika Halmashauri Kuu ya Jimbo. (g) Wenyeviti wote wa CCM wa Wadi za Jimbo hilo. (h) Makatibu wote wa CCM wa Wadi za Jimbo hilo. (i) Makatibu wote wa Siasa na Uenezi wa Wadi za Jimbo hilo. (4) Mwenyekiti wa CCM wa Jimbo ataongoza Mkutano Mkuu wa CCM wa Jimbo. Lakini Mwenyekiti asipoweza kuhudhuria, Mkutano utamchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 61. Kazi za Mkutano Mkuu wa CCM wa Jimbo zitakuwa zifuatazo:- (1) Kupokea na kujadili taarifa ya kazi za CCM katika Jimbo iliyotolewa na Halmashauri Kuu ya CCM ya Jimbo na kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuhakikisha kwamba maazimio na maagizo ya ngazi ya juu yanatekelezwa ipasavyo. (3) Kuzungumzia mambo yote yanayohusu Ulinzi na Usalama na maendeleo kwa jumla katika Jimbo. (4) Unapofika wakati wa uchaguzi, Mkutano Mkuu wa CCM wa Jimbo utashughulikia mambo yafuatayo:- (a) Kumchagua Mwenyekiti wa CCM wa Jimbo. (b) Kuwachagua wajumbe watano wa kuingia katika Halmashauri Kuu ya CCM ya Jimbo. (c) Kuwachagua wajumbe watano wa kuhudhuria Mkutano Mkuu wa CCM wa Wilaya. (d) Kuwachagua wajumbe watatu wa kuhudhuria Mkutano Mkuu wa CCM wa Mkoa. Kazi za Mkutano Mkuu wa CCM Wa Jimbo Halmashauri Kuu ya CCM ya Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 56 57 (4) Kutoa msukumo wa utekelezaji wa Ilani ya CCM na kusimamia utekelezaji wa Siasa na maazimio ya CCM kwa jumla katika Jimbo. (5) Kuona kwamba unakuwepo Ulinzi na Usalama katika eneo la Jimbo. (6) Kuziongoza Halmashauri Kuu za CCM za Wadi za Jimbo kuhusu vitendo na njia zinazofaa za kuimarisha CCM. (7) Kuangalia mwenendo na vitendo vya Wanachama pamoja na Viongozi wa CCM waliomo katika Jimbo hilo, na inapolazimu, kutoa taarifa kwa vikao vinavyohusika. (8) Kufikisha kwenye Wadi maazimio na maagizo ya vikao vya juu na kufikisha kwenye Vikao vya juu mapendekezo kutoka Wadi. (9) Unapofika wakati wa Uchaguzi, Halmashauri Kuu ya CCM ya Jimbo itashughulikia mambo yafuatayo:- (a) Kumchagua Katibu wa CCM wa Jimbo. (b) Kumchagua Katibu wa Siasa na Uenezi wa Jimbo. (c) Kuwachagua Wajumbe watatu wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Jimbo kutoka miongoni mwao. (d) Kufanya uteuzi wa mwisho wa majina ya wanachama wa CCM watakaosimama katika uchaguzi wa Mwenyekiti na Katibu wa Wadi wa kila Jumuiya ya CCM na wajumbe (j) Wajumbe wa Halmashauri Kuu ya Wilaya ya CCM waliomo katika Jimbo hilo. (k) Mwenyekiti na Katibu wa Jimbo wa Jumuiya za CCM, na Mjumbe mmoja mwingine ambaye ni mwanachama wa CCM aliyechaguliwa na kila Jumuiya inayohusika iliyomo katika Jimbo hilo. (2) Halmashauri Kuu ya CCM ya Jimbo itafanya mikutano yake ya kawaida nara moja katika kila miezi sita, lakini inaweza kufanya mikutano isiyo ya kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Jimbo ataongoza Mkutano wa Halmashauri Kuu ya Jimbo; lakini Mwenyekiti asipoweza kuhudhuria, Katibu wa CCM wa Jimbo atakuwa Mwenyekiti wa muda wa Mkutano huo. 63. Kazi za Halmashauri Kuu ya CCM ya Jimbo zitakuwa zifuatazo:- (1) Kuongoza na kusimamia ujenzi wa Ujamaa na Kujitegemea katika eneo lake la Jimbo. (2) Kusimamia uenezi wa Itikadi na Siasa ya CCM, na kueleza mipango ya CCM kwa Wadi zote za Jimbo na kubuni mbinu zinazofaa za kuimarisha CCM katika eneo la Jimbo. (3) Kupanga mikakati ya kampeni za uchaguzi na kampeni nyinginezo. Kazi za Halmashauri Kuu ya CCM ya Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 58 59 (e) Madiwani wanaotokana na CCM wanaowakilisha Wadi husika na Madiwani wa aina nyingine wanaoishi katika Wadi za Jimbo hilo (f) Wajumbe watatu waliochaguliwa na Halmashauri Kuu ya CCM ya Jimbo hilo. (g) Mwenyekiti wa Jimbo wa kila Jumuiya ya CCM iliyopo katika Jimbo hilo. (2) Kamati ya Siasa ya Halmashauri Kuu ya Jimbo itafanya mikutano yake ya kawaida mara moja katika kila miezi mitatu, lakini inaweza kufanya mkutano usio wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Jimbo ataongoza Mkutano wa Kamati ya Siasa ya Jimbo. Lakini Mwenyekikti asipoweza kuhudhuria, Katibu wa CCM wa Jimbo atakuwa Mwenyekiti wa muda wa Mkutano huo. 65. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Jimbo zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika Jimbo. (2) Kusimamia utekelezaji wa shughuli za kila siku za CCM Jimboni chini ya uongozi wa Halmashauri Kuu ya CCM ya Jimbo. (3) Kueneza Itikadi na Siasa ya CCM katika Jimbo. wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Wadi zote za Jimbo hilo. (10) Kujaza kwa niaba ya Mkutano Mkuu wa CCM wa Jimbo nafasi za uongozi zinazokuwa wazi, isipokuwa ya Mwenyekiti wa Jimbo. (11) Kupokea, kuzingatia na kuamua juu ya mapendekezo ya vikao vya CCM vilivyo chini yake. (12) Kuunda Kamati Ndogo za Utekelezaji kwa kadri itakavyoonekana inafaa kwa ajili ya utekelezaji bora zaidi wa kazi za CCM katika Jimbo. (13) Kupokea na kujadili taarifa za Kamati Ndogo za Utekelezaji wa Kazi za CCM za Jimbo na Kamati za Mkutano Mkuu wa CCM wa Jimbo. (14) Kuunda Kamati ya Usalama na Maadili ya CCM ya Jimbo. 64. (1) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Jimbo itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Jimbo. (b) Katibu wa CCM wa Jimbo. (c) Katibu wa Siasa na Uenezi wa CCM wa Jimbo. (d) Mbunge na Mwakilishi wanaotokana na CCM wanaowakilisha Jimbo linalohusika na Wabunge au Wawakilishi wa aina nyingine wanaoishi katika Jimbo hilo. Kazi za Kamati ya Siasa ya Halmashauri kuu ya CCM ya Jimbo Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 60 61 (7) Kuandaa mikutano ya Halmashauri Kuu ya CCM ya Jimbo. (8) Kuona kwamba masuala ya Ulinzi na Usalama katika Jimbo yanazingatiwa. 66. Sekretarieti ya Halmashauri Kuu ya CCM ya Jimbo itakuwa na wajumbe wafuatao:- (a) Katibu wa CCM wa Jimbo ambaye atakuwa Mwenyekiti, (b) Katibu wa Siasa na Uenezi wa Jimbo. (c) Makatibu wa Jimbo wa Jumuiya za CCM. 67. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Jimbo yatakuwa yafuatayo:- (a) Kuongoza na kusimamia shughuli za Chama katika Jimbo. (b) Kuandaa vikao vyote vya Chama vya Jimbo. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Jimbo yatagawanyika ifuatavyo:- (a) Katibu wa CCM wa Jimbo. (b) Idara ya Siasa na Uenezi ya Jimbo. (c) Idara ya Organaizesheni ya Jimbo. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya Jimbo isipokuwa kwamba Katibu wa CCM wa Jimbo atakuwa ndiye Katibu wa Organaizesheni katika Jimbo. 68. Kutakuwa na Wakuu wa CCM wafuatao katika Jimbo:- (1) Mwenyekiti wa CCM wa Jimbo. (2) Katibu wa CCM wa Jimbo. (4) Kuandaa mikakati ya kampeni za uchaguzi na kampeni nyinginezo katika Jimbo. (5) Kupanga mipango ya kukipatia Chama mapato, kusimamia kwa dhati utekelezaji wa mipango hiyo, kudhibiti mapato na kusimamia matumizi bora ya fedha na mali za chama katika Jimbo. (6) Unapofika wakati wa Uchaguzi, Kamati ya Siasa ya Jimbo itashughulikia mambo yafuatayo:- (a) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Wilaya juu ya wanachama wanaoomba nafasi za Uenyeketi na Ukatibu wa CCM wa Wadi, Ukatibu wa Siasa na Uenezi wa Wadi, na Wanachama wanaoomba Uongozi wa CCM wa Jimbo kupitia Jimbo hilo. (b) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Wilaya juu ya wanachama wanaoomba Udiwani au Uwakilishi wa aina nyingine katika Serikali za Mitaa kwa mujibu wa Sheria zilizopo. (c) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya Jimbo juu ya wanachama wa CCM wanaoomba Uenyekiti na Ukatibu wa Wadi wa Jumuiya za CCM; na ujumbe wa kuiwakilisha Jumuiya katika vikao vya CCM vya Kata/ Wadi. Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Jimbo Wakuu wa CCM katika Jimbo Sekretarieti ya Halmashauri Kuu ya CCM ya Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 62 63 (a) Kuratibu kazi zote za CCM katika Jimbo. (b) Kuitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya Jimbo kwa madhumuni ya kushauriana, kuandaa agenda za Kamati ya Siasa ya Jimbo na kuchukua hatua za utekelezaji wa maamuzi ya CCM. (c) Kusimamia kazi za Utawala na Uendeshaji wa Chama katika Jimbo. (d) Kufuatilia na kuratibu masuala ya Usalama na Maadili ya Chama katika Jimbo. (e) Kusimamia Udhibiti wa fedha na mali ya Chama katika Jimbo. (3) Ataitisha Mikutano ya Kamati ya Siasa ya Jimbo, Halmashauri Kuu ya Jimbo na Mkutano Mkuu wa Jimbo baada ya kushauriana na Mwenyekiti wa CCM wa Jimbo. (4) Atakuwa ndiye Mkurugenzi wa Uchaguzi katika Jimbo. (5) Atashughulikia na kusimamia masuala yote ya Organaizesheni ya CCM katika Jimbo, ambayo ni:- (a) Masuala yote ya wanachama. (b) Kufuatilia vikao na maamuzi ya vikao vya CCM. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. 69. (1) Mwenyekiti wa CCM wa Jimbo atachaguliwa na Mkutano Mkuu wa CCM wa Jimbo. Atashika nafasi hiyo ya uongozi kwa muda wa miaka mitano lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na madaraka ya kuangalia mambo yote ya CCM katika Jimbo. (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Jimbo, Mkutano wa Halmashauri Kuu ya CCM ya Jimbo na Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Jimbo. (4) Katika mikutano anayoiongoza zaidi ya kuwa na kura yake ya kawaida, Mwenyekiti wa CCM wa Jimbo pia atakuwa na kura ya uamuzi endapo kura za Wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama kikao anachokiongoza ni kikao cha uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 70. (1) Katibu wa CCM wa Jimbo atachaguliwa na Halmashauri Kuu ya CCM ya Jimbo. (2) Atakuwa ndiye Mtendaji Mkuu wa CCM katika Jimbo na atafanya kazi chini ya Halmashauri Kuu ya Jimbo lake. Majukumu yake ni haya yafuatayo:- Mwenyekiti wa CCM wa Jimbo Katibu wa CCM wa Jimbo Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 64 65 FUNGU LA V VIKAO VYA WILAYA 72. Kutakuwa na Vikao Vifuatavyo vya CCM katika kila Wilaya:- (1) Mkutano Mkuu wa CCM wa Wilaya. (2) Halmashauri Kuu ya CCM ya Wilaya. (3) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya. (4) Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya. (5) Kamati ya Madiwani wote wa CCM. 73. (1) Mkutano Mkuu wa CCM wa Wilaya utakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Wilaya. (b) Katibu wa CCM wa Wilaya. (c) Wajumbe wa Halmashauri Kuu ya Taifa wanaoishi katika wilaya hiyo. (d) Mkuu wa Wilaya ambaye anatokana na CCM. (e) Katibu wa Siasa na Uenezi wa Wilaya. (f) Mbunge au Wabunge wanaotokana na CCM, wanaowakilisha Majimbo yaliyomo katika Wilaya hiyo, na Wabunge wa aina nyingine wanaoishi katika Wilaya hiyo. (g) Wawakilishi wanaotokana na CCM, wanaowakilisha Majimbo yaliyomo katika Wilaya hiyo, na Wawakilishi wa aina nyingine wanaoishi katika Wilaya hiyo. (d) Kusimamia masuala yote ya Uchaguzi wa ndani ya Chama na ule wa Uwakilishi katika Vyombo vya Dola. (e) Kusimamia Katiba, Muundo, Kanuni na Taratibu za Chama na Jumuiya za CCM. 71. Katibu wa Siasa na Uenezi wa Jimbo atachaguliwa na Halmashauri Kuu ya CCM ya Jimbo na atashughulikia masuala yote ya Siasa na Uenezi katika Jimbo. Majukumu yake ni haya yafuatayo:- (a) Kusimamia, kueneza na kufafanua masuala yote ya Itikadi, Siasa na Sera za CCM katika Jimbo. (b) Kupanga na kusimamia Mafunzo na maandalizi ya Makada na Wanachama katika Jimbo. (c) Kufuatilia utekelezaji wa Sera za Chama za Kijamii na Ilani ya Uchaguzi ya CCM katika Jimbo. (d) Kudumisha uhusiano mzuri na vyombo vya habari na kuwa na mipango ya mawasiliano na uhamasishaji wa Umma katika Jimbo. (e) Kufuatilia hali ya kisiasa na harakati za Vyama vya Siasa Jimboni. (f) Kufuatilia mwenendo wa Jumuiya za Kijamii katika Jimbo. Katibu wa Siasa na Uenezi wa CCM wa Jimbo Vikao vya CCM vya Wilaya Mkutano Mkuu wa CCM Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 66 67 (q) Mjumbe mmoja aliyechaguliwa na Mkutano Mkuu wa kila Tawi la Wilaya hiyo. (r) Wenyeviti wote wa CCM wa Matawi katika Wilaya hiyo. (s) Makatibu wote wa CCM wa Matawi katika Wilaya hiyo. (t) Makatibu wa Siasa na Uenezi wote wa Matawi ya CCM yaliyomo katika Wilaya hiyo. (u) Wajumbe wengine wote wa Mkutano Mkuu wa Mkoa wanaoishi katika Wilaya hiyo. (v) Wajumbe wengine wa Mkutano Mkuu wa Wilaya ni hawa wafuatao: (ii) Wenyeviti na Makatibu wote wa CCM wa Majimbo. (i) Makatibu wa Siasa na Uenezi wa Majimbo. (iii) Wenyeviti na Makatibu wa Majimbo wa Jumuiya zinazoongozwa na CCM. (iv) Wajumbe wa Mkutano Mkuu wa Wilaya na Mkoa kupitia kila Jimbo linalohusika. (2) Mkutano Mkuu wa Wilaya ndicho kikao kikuu cha CCM katika Wilaya. (3) Mkutano mkuu wa wilaya utafanya mikutano yake ya kawaida mara moja kila mwaka, lakini unaweza kukutana wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya vikao vya juu. (h) Wajumbe wote wa Mkutano Mkuu wa CCM wa Taifa waliochaguliwa na Mkutano Mkuu wa CCM wa Wilaya hiyo. (i) Wajumbe wa Halmashauri Kuu ya CCM ya Mkoa wanaoishi katika W ilaya hiyo. (j) Mwenyekiti na Katibu wa Wilaya wa kila jumuiya ya CCM, na mjumbe mwingine mmoja ambaye ni mwanachama wa CCM aliyechaguliwa na kila Jumuiya inayohusika iliyomo katika Wilaya hiyo. (k) Wajumbe wote ambao ni wanachama wa CCM kutoka kila Jumuiya ya CCM wanaowakilisha Jumuiya hizo katika Mkutano Mkuu wa CCM wa Taifa wanaoishi katika Wilaya hiyo. (l) Madiwani wanaotokana na CCM wanaowakilisha Kata/Wadi zilizomo katika Wilaya husika na Madiwani wa CCM wa aina nyingine wanaoishi katika Wilaya hiyo. (m) Meya wa Manispaa au Mwenyekiti wa Halmashauri ya Wil aya anayetokana na CCM. (n) Makatibu wa Siasa na Uenezi wa Kata/Wadi za Wilaya hiyo. (o) Wenyeviti na Makatibu wa CCM wa kila Kata ya Wilaya hiyo. (p) Wajumbe watano waliochaguliwa na Kata ya Wilaya hiyo. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 68 69 (5) Kuunda Kamati za Mkutano Mkuu wa CCM wa Wilaya kwa kadri itakavyoonekana inafaa. (6) Mkutano Mkuu wa Wilaya waweza kukasimu madaraka yake kwa Halmashauri Kuu ya Wilaya kuhusu utekelezaji wa kazi zake kwa kadri utakavyoona inafaa. 75. (1) Halmashauri Kuu ya CCM ya Wilaya itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Wilaya. (b) Katibu wa CCM wa Wilaya. (c) Mjumbe wa Halmashauri kuu ya Taifa wa mkoa huo iwapo anaishi katika wilaya hiyo. (d) Mkuu wa Wilaya ambaye anatokana na CCM. (e) Katibu wa Siasa na Uenezi wa Wilaya. (f) Mbunge au Wabunge wanaotokana na CCM wanaowakilisha Majimbo yaliyomo katika Wilaya husika, na Wabunge wa aina nyingine wanaoishi katika Wilaya hiyo. (g) Wawakilishi wanaotokana na CCM wanaowakilisha Jimbo husika, na Wawakilishi wa aina nyingine wanaoishi katika Wilaya hiyo. (h) Wajumbe kumi waliochaguliwa na Mkutano Mkuu wa CCM wa Wilaya. (4) Mwenyekiti wa CCM wa Wilaya ataongoza Mkutano Mkuu wa CCM wa Wilaya; lakini Mwenyekiti asipoweza kuhudhuria Mkutano utamchagua mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo. 74. Kazi za Mkutano Mkuu wa CCM wa Wilaya zitakuwa zifuatazo:- (1) Kupokea na kujadili taarifa ya kazi za CCM iliyotolewa na Halmashauri Kuu ya CCM ya Wilaya, na kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuhakikisha kwamba maazimio na maagizo ya ngazi za juu yanatekelezwa ipasavyo. (3) Kuzungumzia mambo yote yanayohusu ulinzi na usalama na maendeleo kwa jumla katika Wilaya. (4) Unapofika wakati wa uchaguzi Mkutano Mkuu wa CCM wa Wilaya utashughulikia mambo yafuatayo:- (a) Kumchagua Mwenyekiti wa CCM wa Wilaya. (b) Kuwachagua Wajumbe kumi kuingia katika Halmashauri Kuu ya CCM ya Wilaya. (c) Kuwachagua Wajumbe wawili kuhudhuria Mkutano Mkuu wa CCM wa Mkoa. (d) Kuwachagua Wajumbe watatu kuhudhuria Mkutano Mkuu wa CCM wa Taifa. Halmashauri Kuu ya CCM ya Wilaya Kazi za Mkutano Mkuu wa CCM wa Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 70 71 (2) Halmashauri Kuu ya CCM ya Wilaya itafanya mikutano yake ya kawaida mara moja kila baada ya miezi Sita, Lakini inaweza kufanya mkutano usiokuwa wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mkutano wa Halmashauri Kuu ya CCM Wilaya utakaofanyika katika kipindi cha miezi sita ya kwanza ya kila mwaka utakuwa pia na Kazi Maalum ya kupokea na kujadili Taarifa ya Utekelezaji wa Ilani ya CCM unaofanywa na mamlaka za Serikali za Mitaa katika Wilaya hiyo, katika mwaka wa Fedha uliopita wa mamlaka hizo, uliomalizika tarehe 30 Juni ya mwaka unaohusika. Isipokuwa kwamba kwa Halmashauri ya Jiji, ambalo mipaka yake inaunganisha Wilaya zaidi ya moja, Taarifa zake zitapokelewa na kujadiliwa na Halmashauri Kuu ya Mkoa unaohusika na Mamlaka hiyo. (4) Mwenyekiti wa CCM wa Wilaya ataongoza Mkutano wa Halmashauri Kuu ya CCM ya Wilaya, lakini Mwenyekiti asipoweza kuhudhuria, Katibu wa CCM wa Wilaya atakuwa Mwenyekiti wa muda wa Mkutano huo. 76. Kazi za Halmashauri Kuu ya CCM ya Wilaya zitakuwa zifuatazo:- (1) Kuongoza na kusimamia ujenzi wa Ujamaa na Kujitegemea katika eneo la Wilaya. (i) Mwenyekiti, Katibu wa Wilaya na Mjumbe mmoja ambao ni wanachama wa CCM kutoka kila Jumuiya ya CCM iliyopo Wilayani wanaowakilisha Jumuiya hiyo kwenye Mkutano Mkuu wa CCM wa Wilaya. (j) Wenyeviti wa CCM wa Majimbo yaliyomo katika Wilaya hiyo. (k) Makatibu wa CCM wa Majimbo yaliyomo katika Wilaya hiyo. (l) Makatibu wa Siasa na uenezi wa Majimbo yaliyomo katika Wilaya hiyo. (m) Wenyeviti wa CCM wa Kata/Wadi zilizomo katika Wilaya hiyo. (n) Makatibu wa CCM wa Kata/Wadi zilizomo katika Wilaya hiyo. (o) Makatibu wa Siasa na Uenezi wa CCM wa Kata/Wadi zilizomo katika Wilaya hiyo. (p) Mwenyekiti wa Halmashauri ya Mji, Manispaa au Mwenyekiti wa Halmashauri ya Wilaya hiyo anayetokana na CCM. (q) Madiwani wanaotokana na CCM wanaowakilisha Kata/Wadi zilizomo katika Wilaya husika, na Madiwani wa aina nyingine wanaoishi katika Wilaya hiyo. (r) Wajumbe wengine wote wa Halmashauri Kuu ya CCM ya Mkoa wanaoishi katika Wilaya hiyo. Kazi za Halmashauri Kuu ya CCM ya Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 72 73 (a) Kuwachagua kutoka miongoni mwao Wajumbe watatu kuingia katika Kamati ya Siasa ya Halmashauri Kuu ya Wilaya. (b) Kwa Wilaya za Zanzibar, kuchagua Wabunge wasiozidi wawili kutoka miongoni mwa Wabunge wanaotokana na CCM wanaowakilisha Majimbo ya Uchaguzi yaliyomo katika Wilaya inayohusika, pamoja na Wabunge wa aina nyingine wanaoishi katika Wilaya hiyo; wa kuingia katika Kamati ya Siasa ya Wilaya. (c) Kwa Wilaya za Zanzibar, kuchagua Wawakilishi wasiozidi wawili kutoka miongoni mwa Wawakilishi wanaotokana na CCM wanaowakilisha Majimbo ya Uchaguzi yaliyomo katika Wilaya inayohusika, pamoja na wawakilishi wa aina nyingine wanaoishi katika Wilaya hiyo; wa kuingia katika Kamati ya Siasa ya Wilaya. (d) Kumchagua Katibu wa Siasa na Uenezi wa CCM waWilaya. (e) Kufikiria na kufanya uteuzi wa mwisho wa wanachama wanaoomba Uenyekiti na Ukatibu wa CCM wa Tawi, Ukatibu wa Siasa na Uenezi wa Tawi, Ujumbe wa Halmashauri Kuu ya CCM ya Kata/ Wadi, Uenyekiti wa Mtaa, Ujumbe (2) Kusimamia Uenezi wa Itikadi na Siasa ya CCM na kueleza mipango ya CCM kwa Kata/Wadi na Majimbo yote ya Wilaya, na kubuni mbinu zinazofaa za kuimarisha CCM katika Wilaya. (3) Kupanga mikakati ya kampeni za uchaguzi na kampeni nyinginezo katika Wilaya. (4) Kutoa msukumo wa utekelezaji wa Ilani ya CCM na kusimamia utekelezaji wa Siasa na Maazimio ya CCM kwa jumla. (5) Kuona kwamba shughuli za maendeleo ya Ulinzi na Usalama zinazingatiwa katika Wilaya. (6) Kuziongoza Halmashauri Kuu za CCM za Kata zote upande wa Tanzania Bara; na za Wadi na Majimbo upande wa Zanzibar, kuhusu njia zinazofaa za kuimarisha CCM na kuleta maendeleo Wilayani. (7) Kuangalia mwenendo na vitendo vya wanachama pamoja na viongozi wa CCM katika Wilaya na inapolazimu kutoa taarifa kwa vikao vinavyohusika. (8) Kufikisha kwenye Kata, Wadi, Jimbo maazimio na maagizo ya vikao vya juu na kufikisha kwenye Vikao vya juu mapendekezo kutoka kwenye Kata/Wadi na Jimbo. (9) Unapofika wakati wa uchaguzi, Halmashauri Kuu ya CCM ya Wilaya itashughulikia mambo yafuatayo:- Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 74 75 kuimarisha Chama katika Jimbo hilo, pamoja na kupanga mikakati inayofaa ya Kampeni za uchaguzi kwa lengo la kuipatia CCM ushindi. (13) Kupokea na kujadili taarifa za utekelezaji wa Kazi za CCM za Wilaya na Kamati ya Madiwani wa CCM wa Wilaya. (14) Kumwachisha au kumfukuza uongozi Mwenyekiti au Katibu wa CCM wa Tawi. (15) Kuunda Kamati ya Usalama na Maadili ya CCM ya Wilaya. (16) Halmashauri Kuu ya Wilaya yaweza kukasimu madaraka yake kwa Kamati ya Siasa ya Wilaya kuhusu utekelezaji wa kazi zake kwa kadri itakavyoona inafaa. 77. (1) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Wilaya. (b) Katibu wa CCM wa Wilaya. (c) Mkuu wa Wilaya ambaye anatokana na CCM. (d) Katibu wa Siasa na Uenezi wa Wilaya. (e) Mbunge au Wabunge wanaotokana na CCM. wanaowakilisha Wilaya hiyo au Wabunge wa aina nyingine wanaoishi katika Wilaya hiyo. (f) Kwa upande wa Zanzibar wabunge wawili kutoka miongoni mwa wabunge wanaotokana na CCM wanaowakilisha majimbo ya wa Kamati ya Mtaa, Uenyekiti na Ujumbe wa Halmashauri ya Kijiji. (f) Kufanya uteuzi wa mwisho wa majina ya wanachama wa CCM watakaosimama katika uchaguzi wa Mwenyekiti na Katibu wa Kata na Jimbo kwa upande wa Zanzibar wa kila Jumuiya ya CCM na Ujumbe wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Kata na Majimbo katika Wilaya inayohusika. (10) Kujaza kwa niaba ya Mkutano Mkuu wa CCM wa Wilaya nafasi za Uongozi zinazokuwa wazi isipokuwa ya Mwenyekiti wa CCM wa Wilaya. (11) Kupokea, kuzingatia na kuamua juu ya mapendekezo ya vikao vya CCM vilivyo chini yake. (12) Kuunda Kamati Ndogo za Utekelezaji kama itakavyoonekana inafaa kwa ajili ya utekelezaji bora zaidi wa kazi za CCM katika Wilaya. Isipokuwa kwamba Halmashauri Kuu ya Wilaya itaunda Kamati Ndogo kwa kila Jimbo la Uchaguzi wa Wabunge/Wawakilishi lililomo katika Wilaya hiyo, ambayo itaitwa Kamati ya Jimbo. Kamati hiyo itakuwa na Wajumbe wote wa Halmashauri Kuu ya Wilaya wanaotoka katika Jimbo la Uchaguzi linalohusika, na itakuwa na uwezo wa kuchagua Mwenyekiti na Katibu wake. Kazi kubwa ya Kamati ya Jimbo la Uchaguzi itakuwa ni kubuni mbinu za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 76 77 (3) Mwenyekiti wa CCM wa Wilaya ataongoza Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya. Lakini Mwenyekiti asipoweza kuhudhuria Katibu wa CCM wa Wilaya atakuwa Mwenyekiti wa muda wa Mkutano huo. 78. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika Wilaya. (2) Kusimamia utekelezaji wa shughuli za kila siku za CCM Wilayani chini ya uongozi wa Halmashauri Kuu ya CCM ya Wilaya. (3) Kueneza Itikadi ya CCM katika Wilaya. (4) Kuandaa mikakati ya kampeni za uchaguzi na kampeni nyinginezo. (5) Kupanga mipango ya kukipatia Chama mapato, kusimamia kwa dhati utekelezaji wa mipango hiyo, kudhibiti mapato na kusimamia matumizi bora ya fedha na mali za Chama katika Wilaya. (6) Unapofika wakati wa uchaguzi, Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya itashughulikia mambo yafuatayo:- (a) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa juu ya wanachama wanaoomba nafasi za uongozi wa CCM kupitia Wilaya hiyo. (b) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya uchaguzi yaliyomo kwenye wilaya inayohusika, wakuingia katika Kamati ya siasa ya wilaya. (g) Kwa upande wa Zanzibar Wawakilishi wasiozidi wawili kutoka miongoni mwa wawakilishi wanaotokana na CCM wanaowakilisha majimbo ya uchaguzi yaliyomo kwenye wilaya inayohusika, pamoja na wawakilishi wa aina nyingine wanaoishi katika wilaya hiyo wa kuingia katika kamati ya siasa ya wilaya. (h) Wajumbe watatu waliochaguliwa na Halmashauri Kuu ya CCM ya Wilaya kuingia katika Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya. (i) Mwenyekiti wa Halmashauri ya Mji, Manispaa au Mwenyekiti wa Halmashauri ya Wilaya hiyo anayetokana na CCM. (j) Mwenyekiti wa Wilaya wa kila Jumuiya ya CCM iliyomo katika Wilaya hiyo. (k) Mwenyekiti wa Kamati ya Madiwani wa CCM. (2) Kamati ya Siasa ya Halmashauri Kuu ya Wilaya itafanya mikutano yake yakawaida mara moja katika kila miezi mitatu lakini inaweza kufanya mkutano usiokuwa wakawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. Kazi za Kamati ya Siasa ya Halmashauri Kuu CCM ya Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 78 79 (e) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya Wilaya juu ya wanachama wa CCM wanaoomba Uenyekiti na Ukatibu wa Kata na Jimbo kwa upande wa Zanzibar wa kila Jumuiya ya CCM na wanaoomba Ujumbe wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Kata na Majimbo katika Wilaya inayohusika. (f) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Mkoa juu ya wanachama wa Jumuiya za CCM wanaoomba kuwa Wajumbe wa Mkutano Mkuu wa CCM wa Mkoa na kuwakilisha Jumuiya katika vikao vya Mkoa huo. (7) Kumsimamisha uongozi kiongozi yeyote wa Kata/Wadi na Jimbo endapo itadhihirika kwamba tabia na mwenendo wake vinamwondolea sifa za uongozi. (8) Kuandaa mikutano ya Halmashauri Kuu ya CCM ya Wilaya. (9) Kuona kwamba masuala ya Ulinzi na Usalama yanazingatiwa katika Wilaya 79. Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya itakuwa na wajumbe wafuatao:- (1) Katibu wa CCM wa Wilaya ambaye atakuwa Mwenyekiti. (2) Katibu wa Siasa na Uenezi wa Wilaya. (3) Makatibu wa Wilaya wa Jumuiya za CCM. CCM ya Wilaya juu ya wanachama wanaoomba Uenyekiti na Ukatibu wa CCM wa Tawi; Ukatibu wa Siasa na Uenezi wa Tawi; Ujumbe wa Halmashauri Kuu ya CCM ya Kata/ Wadi; Uenyekiti wa Mtaa, Uenyekiti wa kijiji na Ujumbe wa Halmashauri ya Kijiji. (c ) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa juu ya Wanachama wanaoomba Uenyekiti na Ukatibu wa CCM wa Jimbo; Katibu wa Siasa na Uenezi wa Jimbo, Ujumbe wa Mkutano Mkuu wa Jimbo, Wilaya na Mkoa, Ujumbe wa Halmashauri Kuu ya CCM ya Jimbo, Uenyekiti na Ukatibu wa CCM wa Kata/Wadi, Katibu wa Siasa na Uenezi wa Kata/Wadi; na wagombea Udiwani wa CCM kwa mujibu wa sheria zilizopo za uchaguzi wa Serikali za Mitaa. (d) Kufikiria na kutoa mapendekezo yake kwa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa, juu ya Wanachama wanaoomba nafasi za Mwenyekiti na Makamu Mwenyekiti wa Halmashauri ya Wilaya na Mji, Meya na Naibu Meya wa Manispaa zilizomo katika Mkoa huo na wanachama wanaoomba nafasi za Ubunge na Uwakilishi. Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 80 81 (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Wilaya, Halmashauri Kuu ya CCM ya Wilaya na Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Wilaya. (4) Katika mikutano anayoiongoza zaidi ya kuwa na kura yake ya kawaida, Mwenyekiti wa CCM wa Wilaya pia atakuwa na kura ya uamuzi endapo kura za wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama kikao anachokiongoza ni kikao cha Uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 83. (1) Katibu wa CCM wa Wilaya atakuwa ndiye Mtendaji Mkuu wa CCM Wilayani na atafanya kazi chini ya uongozi wa Halmashauri Kuu ya CCM ya Wilaya. Majukumu yake ni haya yafuatayo:- (a) Kuratibu kazi zote za CCM katika Wilaya. (b) Kuitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya kwa madhumuni ya kushauriana, kuandaa agenda za Kamati ya Siasa ya Halmashauri Kuu ya Wilaya na kuchukua hatua za utekelezaji wa maamuzi ya CCM. 80. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya yatakuwa yafuatayo:- (a) Kuongoza na kusimamia shughuli za Chama katika Wilaya. (b) Kuandaa shughuli za vikao vyote vya Chama vya Wilaya. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Wilaya yatagawanyika ifuatavyo:- (a) Katibu wa CCM wa Wilaya. (b) Idara ya Siasa na Uenezi ya Wilaya. (c) Idara ya Organaizesheni ya Wilaya. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya Wilaya isipokuwa kwamba Katibu wa CCM wa Wilaya atakuwa ndiye Katibu wa Organaizesheni katika Wilaya. 81. Kutakuwa na Wakuu wa CCM wafuatao katika Wilaya:- (1) Mwenyekiti wa CCM wa Wilaya. (2) Katibu wa CCM wa Wilaya. 82. (1) Mwenyekiti wa CCM wa Wilaya atachaguliwa na Mkutano Mkuu wa CCM wa Wilaya. Atashika nafasi hiyo kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na wajibu wa kuangalia mambo yote ya CCM katika Wilaya. Majukumu ya Sekretarieti ya Halmashauri kuu ya CCM ya Wilaya Wakuu wa CCM katika Wilaya Mwenyekiti wa CCM wa Wilaya Katibu wa CCM wa Wilaya Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 82 83 84. Katibu wa Siasa na Uenezi wa Wilaya atachaguliwa na Halmashauri Kuu ya CCM ya Wilaya na atashughulikia masuala yote ya Siasa na Uenezi katika Wilaya. Majukumu yake ni haya yafuatayo:- (a) Kushughulikia masuala yote ya Itikadi, Siasa na Sera za CCM katika Wilaya, (b) Kupanga na kusimamia Mafunzo na maandalizi ya Makada na Wanachama katika Wilaya. (c) Kufuatilia utekelezaji wa Sera za Chama za Kijamii na Ilani ya Uchaguzi ya CCM katika Wilaya. (d) Kudumisha uhusiano mzuri na Vyombo vya Habari na kuwa na mipango ya mawasiliano na uhamasishaji wa umma kwa ujumla katika Wilaya. (e) Kufuatilia hali ya Kisiasa na harakati za Vyama vya Siasa Wilayani. (f) Kufuatilia mwenendo wa Jumuiya za kijamii katika Wilaya. FUNGU LA VI VIKAO VYA MKOA 85. (1) Kutakuwa na Vikao vifuatavyo vya CCM katika kila Mkoa: - (a) Mkutano Mkuu wa CCM wa Mkoa. (b) Halmashauri Kuu ya CCM ya Mkoa. (c) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa. (c) Kusimamia kazi za Utawala na Uendeshaji wa Chama katika Wilaya, (d) Kufuatilia na kuratibu masuala ya Usalama na Maadili ya Chama katika Wilaya. (e) Kusimamia Udhibiti wa Fedha na Mali ya Chama Katika Wilaya. (2) Kuitisha mikutano ya Kamati ya Siasa ya Wilaya, Halmashauri Kuu ya Wilaya na Mkutano Mkuu wa Wilaya baada ya kushauriana na Mwenyekiti wa CCM wa Wilaya. (3) Atakuwa ndiye Mkurugenzi wa Uchaguzi katika Wilaya. (4) Atashughulikia na kusimamia masuala yote ya Organaizesheni ya CCM katika Wilaya, ambayo ni:- (a) Masuala yote ya wanachama. (b) Kufuatilia vikao na maamuzi ya vikao vya Chama. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. (d) Kusimamia masuala yote ya Uchaguzi wa ndani ya Chama na ule wa Uwakilishi katika Vyombo vya Dola. (6) Kusimamia Katiba, Muundo, Kanuni na Taratibu za Chama na Jumuiya zinazoongozwa na CCM. Katibu wa Siasa na Uenezi wa Wilaya Vikao vya CCM vya Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 84 85 (j) Mwenyekiti, Katibu, Mjumbe wa Mkutano Mkuu wa Taifa wa Mkoa na Mjumbe mwingine mmoja aliyechaguliwa na kila Jumuiya ya CCM iliyomo Mkoani. (k) Meya wa Jiji au Mji wenye hadhi ya Jiji. (l) Wajumbe wawili waliochaguliwa kutoka kila Wilaya. (m) Wenyeviti na Makatibu wote wa CCM wa Wilaya za Mkoa huo. (n) Wakuu wote wa Wilaya ambao wanatokana na CCM katika Mkoa huo. (o) Makatibu wa Siasa na Uenezi wa Wilaya za Mkoa huo. (p) Wenyeviti wa Halmashauri za Miji, Meya wa Manispaa na Wenyeviti wa Halmashauri za Wilaya katika Mkoa huo. (q) Wajumbe watatu wa Mkutano Mkuu wa CCM wa Taifa, wanaowakilisha kila Wilaya ya Mkoa huo. (r) Wenyeviti na Makatibu wa CCM wa Majimbo ya Mkoa unaohusika, wa Zanzibar. (s) Wenyeviti na Makatibu wa CCM wa Kata/Wadi zilizomo katika Mkoa huo. (t) Makatibu wa Siasa na Uenezi wa Majimbo ya CCM ya Mkoa unaohusika wa Zanzibar. (d) Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa. 86. (1) Mkutano Mkuu wa CCM wa Mkoa utakuwa na Wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Mkoa. (b) Katibu wa CCM wa Mkoa. (c) Mjumbe/Wajumbe wa Halmashauri kuu ya Taifa wa Mkoa huo na Wajumbe wa Halmashauri kuu ya Taifa wa aina nyingine waishio katika Mkoa huo. (d) Mkuu wa Mkoa ambaye anatokana na CCM. (e) Katibu wa Siasa na Uenezi wa Mkoa. (f) Wabunge wote wanaotokana na CCM wanaowakilisha Majimbo yaliyomo katika Mkoa husika, na Wabunge wa aina nyingine wanaoishi katika Mkoa huo. (g) Wawakilishi wote wanaotokana na CCM wanaowakilisha Majimbo yaliyomo katika Mkoa husika na Wawakilishi wa aina nyingine wanaoishi katika Mkoa huo. (h) Wajumbe wote wa Halmashauri Kuu ya CCM ya Mkoa. (i) Mwenyekiti na Katibu wa Wilaya wa Jumuiya za CCM zilizomo katika Mkoa huo; na Mjumbe mwingine mmoja aliyechaguliwa na kila Jumuiya kutoka kila Wilaya zilizomo katika Mkoa huo. Mkutano Mkuu wa CCM wa Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 86 87 (4) Mwenyekiti wa CCM wa Mkoa ataongoza Mkutano Mkuu wa CCM wa Mkoa, lakini asipoweza kuhudhuria mkutano huo utamchagua Mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa mkutano huo. 87. Kazi za Mkutano Mkuu wa CCM wa Mkoa zitakuwa zifuatazo:- (1) Kupokea na kujadili taarifa ya kazi za CCM iliyotolewa na Halmashauri Kuu ya CCM ya Mkoa na kutoa maelekezo ya utekelezaji wa Siasa ya CCM kwa kipindi kijacho. (2) Kuhakikisha kwamba maazimio na maagizo ya ngazi za juu yanatekelezwa ipasavyo. (3) Kuzungumzia mambo yote yanayohusu Ulinzi na Usalama, na maendeleo kwa jumla katika Mkoa huo. (4) Unapofika wakati wa uchaguzi, Mkutano Mkuu wa CCM wa Mkoa utashughulikia mambo yafuatayo:- (a) Kumchagua Mwenyekiti wa CCM wa Mkoa. (b) Kuwachagua wajumbe wa Halmashauri Kuu ya CCM Taifa wa nafasi ya Mkoa, mmoja (1) kwa kila Mkoa wa Tanzania Bara na wanne (4) kwa kila Mkoa wa Zanzibar. (c) Kuwachagua Wajumbe wawili kutoka kila Wilaya ya Tanzania Bara na Wajumbe watano kutoka (u) Madiwani wote wanaotokana na CCM wanaowakilisha Kata/ Wadi zilizomo katika Mkoa husika, na Madiwani wa aina nyingine wanaoishi katika Mkoa huo. (v) Makatibu wa Siasa na Uenezi wa Kata/Wadi zilizomo katika Mkoa huo. (w) Mjumbe mmoja kutoka kila Kata kwa upande wa Tanzania Bara na Wajumbe watano kutoka kila Wadi kwa upande wa Zanzibar waliochaguliwa na Mkutano Mkuu wa CCM wa kila Kata/Wadi iliyomo katika Mkoa huo. (x) Wajumbe watatu waliochaguliwa kutoka kila Jimbo la Mkoa unaohusika wa Zanzibar. (y) Wajumbe wa Baraza Kuu la Taifa ambao ni wanachama wa CCM wa kila Jumuiya ya CCM iliyomo Mkoani. (2) Mkutano Mkuu wa CCM wa Mkoa ndicho kikao kikuu cha CCM katika Mkoa. (3) Mkutano Mkuu wa CCM wa Mkoa utafanya mikutano yake ya kawaida mara tatu katika kipindi cha miaka mitano. Mikutano miwili itakuwa ya uchaguzi na mmoja wa kazi. Lakini mkutano usio wa kawaida unaweza kufanyika wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. Kazi za Mkutano Mkuu wa CCM Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 88 89 (k) Wawakilishi wanaotokana na CCM wanaowakilisha majimbo ya uchaguzi yaliyomo katika Mkoa husika, na Wawakilishi wa aina nyingine wanaoishi katika Mkoa huo. (l) Meya wa Jiji au Meya wa Mji wenye hadhi ya Jiji anayetokana na CCM. (m) Wenyeviti wa Halmashauri za Miji, Meya wa Manispaa au Wenyeviti wa Halmashauri za Wilaya katika Mkoa huo wanaotokana na CCM. (n) Wajumbe wa Halmashauri Kuu ya Mkoa wanaochaguliwa na Mkutano Mkuu wa CCM wa Mkoa, wawili kutoka kila Wilaya ya Tanzania Bara na watano kutoka kila Wilaya ya Zanzibar. (o) Mwenyekiti na Katibu wa Kamati ya Madiwani wa CCM ya Mkoa wenye Jiji au Mji wenye hadhi ya Jiji. (p) Mwenyekiti, Katibu wa Mkoa na Mjumbe au wajumbe ambao ni Wanachama wa CCM wa Baraza Kuu la Taifa wa kila Jumuiya ya CCM iliyopo Mkoani. (2) Halmashauri Kuu ya CCM ya Mkoa itafanya mikutano yake ya kawaida mara moja katika kila miezi sita lakini inaweza kufanya mkutano usiokuwa wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya Kikao cha juu. kila Wilaya ya Zanzibar kuingia katika Halmashauri Kuu ya CCM ya Mkoa. (5) Kuunda Kamati za Mkutano Mkuu wa CCM wa Mkoa kwa kadri itakavyoonekana inafaa. (6) Mkutano Mkuu wa Mkoa waweza kukasimu madaraka yake kwa Halmashauri Kuu ya Mkoa kuhusu utekelezaji wa kazi zake kwa kadri utakavyoona inafaa. 88. (1) Halmashauri Kuu ya CCM ya Mkoa itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Mkoa. (b) Katibu wa CCM wa Mkoa. (c) Mjumbe/Wajumbe wa Halmashauri kuu ya Taifa wa Mkoa huo. (d) Mkuu wa Mkoa ambaye anatokana na CCM. (e) Katibu wa Siasa na Uenezi wa Mkoa. (f) Wenyeviti wote wa CCM wa Wilaya za Mkoa huo. (h) Makatibu wa CCM wa Wilaya za Mkoa huo. (i) Makatibu wa Siasa na Uenezi wa Wilaya zaMkoa huo. (j) Wabunge wote wanaotokana na CCM wanaowakilisha Majimbo ya Uchaguzi yaliyomo katika Mkoa husika, na Wabunge wa aina nyingine wanaoishi katika Mkoa huo. Halmashauri Kuu ya CCM Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 90 91 (8) Kuangalia mwenendo na vitendo vya Wanachama na viongozi wa CCM katika Mkoa na inapolazimu kutoa taarifa kwa vikao vinavyohusika. (9) Kufikisha maazimio na maagizo ya vikao vya juu kwa ngazi za chini yake, na kufikisha mapendekezo kutoka ngazi hizo kwa vikao vya juu. (10) Unapofika wakati wa Uchaguzi, Halmashauri Kuu ya CCM ya Mkoa itashughulikia mambo yafuatayo: (a) Kuwachagua Wajumbe watatu wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa kutoka miongoni mwao. (b) Kumchagua Katibu wa Siasa na Uenezi wa Mkoa. (c) Kwa upande wa Tanzania Bara, itafikiria na kufanya uteuzi wa mwisho wa wanachama wanaoomba Uenyekiti wa CCM wa Kata, Ukatibu wa CCM wa Kata, Ukatibu wa Siasa na Uenezi wa Kata, Udiwani, Ukatibu wa Siasa na Uenezi wa Wilaya, Ujumbe wa Halmashauri Kuu ya CCM ya Wilaya na Mkoa, Ujumbe wa Mkutano Mkuu wa CCM wa Wilaya, Mkoa, na Taifa. (d) Kwa upande wa Tanzania Zanzibar, itafikiria na kufanya uteuzi wa mwisho wa wanachama wanaoomba Uenyekiti wa CCM wa (3) Mwenyekiti wa CCM wa Mkoa ataongoza Mkutano wa Halmashauri Kuu ya CCM ya Mkoa. Lakini Mwenyekiti asipoweza kuhudhuria, Mjumbe wa Halmashauri kuu ya CCM ya Taifa wa Mkoa huo atakuwa Mwenyekiti wa muda wa mkutano huo. 89. Kazi za Halmashauri Kuu ya CCM ya Mkoa zitakuwa zifuatazo:- (1) Kuongoza na kusimamia ujenzi wa Ujamaa na Kujitegemea katika Mkoa. (2) Kusimamia Uenezi wa Itikadi na Siasa ya CCM, kueleza Mipango ya CCM kwa Wilaya za CCM za Mkoa huo, na kubuni mbinu zinazofaa za kuimarisha CCM katika Mkoa. (3) Kupanga mikakati ya Kampeni za Uchaguzi na kampeni nyinginezo katika Mkoa. (4) Kutoa msukumo wa utekelezaji wa Ilani ya CCM na kusimamia utekelezaji wa Siasa na maazimio yaliyopitishwa na Mkutano Mkuu wa CCM wa Taifa na Mkutano Mkuu wa CCM wa Mkoa. (5) Kuona kwamba shughuli za Maendeleo na za Ulinzi na Usalama katika Mkoa zinazingatiwa. (6) Kupokea, kuzingatia na kuamua juu ya mapendekezo ya vikao vya CCM vilivyo chini yake. (7) Kuziongoza Halmashauri Kuu za CCM za Wilaya katika njia zinazofaa za kuimarisha CCM, na za kuleta maendeleo katika Mkoa. Kazi za Halmashauri Kuu ya CCM Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 92 93 Mwanachama anayeachishwa au kufukuzwa Uanachama anaweza kukata rufaa kwa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. (15) Kumwachisha au kumfukuza uongozi kiongozi yeyote ambaye uteuzi wake wa mwisho unafanywa na Halmashauri Kuu ya CCM ya Mkoa. Isipokuwa kwa suala la kumvua uanachama au uongozi Diwani lisifanyike hadi Kamati Kuu imearifiwa na kutoa maelekezo. (16) Kuunda Kamati ya Usalama na Maadili ya CCM ya Mkoa. (17) Halmashauri Kuu ya CCM ya Mkoa yaweza kukasimu madaraka yake kwa Kamati ya Siasa ya Mkoa kuhusu utekelezaji wa Kazi zake kwa kadri itakavyoona inafaa. 90. (1) Kutakuwa na Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa katika kila Mkoa ambayo itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM wa Mkoa. (b) Katibu wa CCM wa Mkoa. (c) Mjumbe/Wajumbe wa Halmashauri kuu ya Taifa wa Mkoa huo. (d) Mkuu wa Mkoa ambaye anatokana na CCM. (e) Katibu wa Siasa na Uenezi wa Mkoa. (f) Mwenyekiti wa Mkoa wa kila Jumuiya ya CCM katika Mkoa huo. Wadi; Ukatibu wa CCM wa Wadi; Ukatibu wa Siasa na Uenezi wa Wadi, Udiwani; Uenyekiti wa CCM na Ukatibu wa CCM wa Jimbo, Ukatibu wa Siasa na Uenezi wa Jimbo; Ukatibu wa Siasa na Uenezi wa Wilaya, Ujumbe wa Halmashauri Kuu ya CCM ya Jimbo, Wilaya na Mkoa, Ujumbe wa Mkutano Mkuu wa CCM wa Wilaya, Mkoa na Taifa. (e) Kufanya uteuzi wa mwisho wa majina ya wanachama wa CCM wanaogombea Uenyekiti wa Wilaya wa kila Jumuiya ya CCM; na majina ya wagombea wa kuiwakilisha kila Jumuiya katika vikao vya CCM vya Wilaya; Mkoa; na Taifa. (11) Kujaza kwa niaba ya Mkutano Mkuu wa CCM wa Mkoa nafasi za uongozi zitakazokuwa wazi isipokuwa ya Mwenyekiti wa CCM wa Mkoa. (12) Kuunda Kamati Ndogo kwa kadri itakavyoonekana inafaa kwa ajili ya utekelezaji bora zaidi wa kazi za CCM katika Mkoa. (13) Kupokea na kujadili taarifa za Kamati Ndogo za utekelezaji wa kazi za CCM za Mkoa na Kamati ya Madiwani wa CCM ya Mkoa pale panapohusika. (14) Kumwachisha au kumfukuza Uanachama Mwanachama yeyote endapo itaridhika kwamba tabia na mwenendo wake vinamwondolea sifa za Uanachama. Kamati ya Siasa ya Halmashauri Kuu ya Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 94 95 (4) Kusimamia utekelezaji wa shughuli za kila siku za CCM na maamuzi yote ya CCM chini ya Uongozi wa Halmashauri Kuu ya CCM ya Mkoa. (5) Kupanga mipango ya kukipatia Chama mapato, kusimamia kwa dhati utekelezaji wa mipango hiyo, kudhibiti mapato na kusimamia matumizi bora ya fedha na mali za Chama katika Mkoa. (6) Unapofika wakati wa Uchaguzi, Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa itashughulikia mambo yafuatayo:- (a) Kwa upande wa Tanzania Bara, itafikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Mkoa juu ya wanachama wanaoomba nafasi ya Mwenyekiti wa CCM wa Kata, Katibu wa Siasa na Uenezi wa Kata, na Wilaya; Ujumbe wa Halmashauri Kuu ya CCM ya wilaya na Mkoa. Ujumbe wa Mkutano Mkuu wa CCM wa Wilaya na Mkoa na Ujumbe wa Mkutano Mkuu wa CCM wa Taifa. (b) Kwa upande wa Tanzania Zanzibar, itafikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Mkoa juu ya wanachama wanaoomba nafasi ya Mwenyekiti wa CCM wa Jimbo, Katibu wa CCM wa Jimbo, Mwenyekiti wa CCM wa Wadi, Katibu wa CCM wa Wadi, Katibu wa Siasa na Uenezi wa (g) Wajumbe watatu waliochaguliwa na Halmashauri Kuu ya Mkoa kuingia katika Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa. (h) Meya wa Jiji ambalo mipaka yake inaunganisha zaidi ya Wilaya moja anayetokana na CCM. (i) Mwenyekiti wa Kamati ya Madiwani wote wa CCM wa Jiji au Mji wenye hadhi ya Jiji. (2) Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa itafanya mikutano yake ya kawaida mara moja katika kila miezi mitatu lakini inaweza kufanya mikutano isiyo ya kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM wa Mkoa ataongoza Mkutano wa Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa, Iakini Mwenyekiti asipoweza kuhudhuria, Mjumbe wa Halmashauri kuu ya CCM ya Taifa wa Mkoa huo atakuwa Mwenyekiti wa muda wa Mkutano huo. 91. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika Mkoa. (2) Kueneza Itikadi na Siasa ya CCM katika Mkoa. (3) Kuandaa mikakati ya kampeni za uchaguzi na kampeni nyinginezo katika Mkoa. Kazi za Kamati ya Siasa ya Halmashauri Kuu ya Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 96 97 (f) Kwa upande wa Tanzania Bara, itafikiria na kutoa mapendekezo yake kwa Kamati Kuu ya Halmashauri Kuu ya CCM juu ya Wanachama wanaoomba nafasi za Umeya wa Jiji na Ubunge. (g) Kwa upande wa Zanzibar, itafikiria na kutoa mapendekezo yake kwa Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa juu ya Wanachama wanaoomba nafasi za Umeya wa Jiji, au Manispaa yenye hadhi ya Jiji, Ubunge na Uwakilishi. (h) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Mkoa juu ya Wanachama wa CCM wanaoomba nafasi za uongozi katika Jumuiya za CCM, ngazi ya Wilaya, ambazo uteuzi wake wa mwisho hufanywa na Halmashauri Kuu ya CCM ya Mkoa unaohusika. Vile vile itafikiria na kutoa mapendekezo yake kwa Kamati Kuu na Kamati Maalum ya Halmashauri Kuu ya Taifa kuhusu Wanachama wa CCM wanaoomba nafasi za uongozi wa kila Jumuiya ya CCM ngazi ya Mkoa. (i) Kufikiria na kufanya uteuzi wa mwisho wa majina ya wanachama wa CCM watakaogombea nafasi za Mwenyekiti na Makamu Mwenyekiti wa Halmashauri za Wilaya, na Wadi na Jimbo, Katibu wa Siasa na Uenezi wa Wilaya, Mjumbe wa Halmashauri kuu ya CCM ya jimbo, Wilaya na Mkoa, na Mjumbe wa Mkutano Mkuu wa Wilaya, Mkoa na Taifa. (c) Kwa upande wa Diwani itafikiria na kuteua majina ya wana CCM wasiozidi watatu kwa kila kata, walioomba kugombea udiwani ili wakapigiwe kura za maoni. Baada ya kura za maoni itafikiria na kutoa mapendekezo yake kwa Halmashauri kuu ya Mkoa juu ya wanachama wanaopendekezwa kuteuliwa kugombea udiwani kwa mujibu wa sheria za Uchaguzi zilizopo. (d) Kufikiria na kutoa mapendekezo yake kwa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa juu ya wanachama wanaoomba nafasi ya uongozi katika kila Wilaya na Mkoa wa Tanzania Bara ambao uteuzi wao wa mwisho hufanywa na vikao vya juu. (e) Kufikiria na Kutoa mapendekezo yake kwa Kamati Maalum ya Halmashauri Kuu ya Taifa juu ya Wanachama wanaoomba nafasi za uongozi katika kila Wilaya na Mkoa wa Zanzibar ambao uteuzi wao wa mwisho hufanywa na vikao vya juu. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 98 99 (a) Katibu wa CCM wa Mkoa. (b) Idara ya Siasa na Uenezi ya Mkoa. (c) Idara ya Organaizesheni ya Mkoa. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya CCM ya Mkoa isipokuwa kwamba Katibu wa CCM wa Mkoa atakuwa ndiye Katibu wa Organaizesheni katika Mkoa. 94. Kutakuwa na Wakuu wa CCM wafuatao katika Mkoa:- (1) Mwenyekiti wa CCM Mkoa (2) Katibu wa CCM wa Mkoa (3) Mjumbe/Wajumbe wa Halmashauri kuu ya Taifa wa Mkoa huo. 95. (1) Mwenyekiti wa CCM Mkoa atachaguliwa na Mkutano Mkuu CCM Mkoa na atashika nafasi hiyo ya uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Atakuwa na madaraka ya kuangalia mambo yote ya CCM katika Mkoa. (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Mkoa, Halmashauri Kuu ya CCM ya Mkoa na Kamati ya Siasa ya Halmashauri Kuu ya CCM ya Mkoa. (4) Katika Mikutano anayoiongoza zaidi ya kuwa na kura yake ya kawaida, Mwenyekiti wa CCM wa Mkoa atakuwa pia na kura ya uamuzi iwapo kura za wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama kikao Naibu Meya wa Halmashauri za Manispaa na Miji. (7) Kumsimamisha uongozi kiongozi yeyote wa ngazi ya Wilaya endapo itaridhika kwamba tabia na mwenendo wake vinamwondolea sifa za uongozi, isipokuwa kwamba haitakuwa na uwezo wa kumsimamisha uongozi Kiongozi ambaye uteuzi wake wa mwisho haukufanywa na Halmashauri Kuu ya CCM ya Mkoa. (8) Kuandaa mikutano ya Halmashauri Kuu ya CCM ya Mkoa. (9) Kuona kwamba masuala ya Ulinzi na Usalama na ya Maendeleo yanazingatiwa katika Mkoa. 92. Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa itakuwa na wajumbe wafuatao:- (1) Katibu wa CCM wa Mkoa ambaye atakuwa Mwenyekiti. (2) Katibu wa Siasa na Uenezi wa Mkoa. (3) Makatibu wa Mkoa wa Jumuiya za CCM. 93. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa yatakuwa yafuatayo:- (a) Kuongoza na kusimamia shughuli za Chama katika Mkoa. (b) Kuandaa shughuli za vikao vyote vya Chama vya Mkoa. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Mkoa yatagawanyika ifuatavyo:- Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa Wakuu wa CCM katika Mkoa Mwenyekiti wa CCM wa Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 100 101 (3) Atakuwa ndiye Mkurugenzi wa Uchaguzi katika Mkoa. (4) Atashughulikia na kusimamia masuala yote ya Organaizesheni ya CCM katika Mkoa, ambayo ni:- (a) Masuala yote ya wanachama. (b) Kufuatilia vikao na maamuzi ya vikao vya Chama. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. (d) Kusimamia na kuratibu masuala yote ya Uchaguzi wa ndani ya Chama na ule wa Uwakilishi katika vyombo vya Dola. (e) Kusimamia Katiba, Muundo, Kanuni na Taratibu za Chama na Jumuiya za CCM. 97. Katibu wa Siasa na Uenezi wa Mkoa atachaguliwa na Halmashauri Kuu ya CCM ya Mkoa na atashughulikia masuala yote ya Siasa na Uenezi katika Mkoa. Majukumu yake ni haya yafuatayo:- (a) Kusimamia, kueneza na kufafanua masuala yote ya Itikadi, Siasa na Sera za CCM katika Mkoa. (b) Kupanga na kusimamia Mafunzo na Maandalizi ya Makada na Wanachama katika Mkoa. (c) Kufuatilia utekelezaji wa Sera za Chama za Kijamii na Ilani za Uchaguzi za CCM katika Mkoa. (d) Kudumisha uhusiano mzuri na Vyombo vya Habari na kuwa na mipango ya mawasiliano na Uhamasishaji wa Umma kwa jumla katika Mkoa. anachokiongoza ni kikao cha Uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 96. (1) Katibu wa CCM wa mkoa atakuwa Mtendaji Mkuu wa shughuli zote za CCM katika Mkoa na atafanya kazi chini ya uongozi wa Halmashauri Kuu ya CCM ya Mkoa wake. Majukumu yake ni haya yafuatayo:- (a) Kuratibu kazi zote za CCM katika Mkoa. (b) Kuitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya CCM ya Mkoa kwa madhumuni ya kushauriana, kuandaa agenda za Kamati ya Siasa ya Mkoa na kuchukua hatua za utekelezaji wa maamuzi ya CCM. (c) Kusimamia kazi za Utawala na Uendeshaji wa Chama katika Mkoa. (d) Kufuatilia na kuratibu masuala ya Usalama na Maadili ya Chama katika Mkoa. (e) Kusimamia Udhibiti wa Fedha na Mali ya Chama katika Mkoa. (2) Ataitisha Mikutano ya Kamati ya Siasa ya Mkoa, Halmashauri Kuu ya Mkoa na Mkutano Mkuu wa Mkoa baada ya kushauriana na Mwenyekiti wa CCM wa Mkoa. Katibu wa CCM wa Mkoa Katibu wa Siasa na Uenezi wa Mkoa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 102 103 (g) Waziri Mkuu wa Jamhuri ya Muungano wa Tanzania na Makamu wa Rais wa Zanzibar anayetokana na CCM. (h) Katibu wa Halmashauri Kuu ya Taifa wa Organaizesheni. (i) Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi. (j) Katibu wa Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa. (k) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha. (l) Mwenyekiti na Makamu Mwenyekiti wa kila Jumuiya ya CCM (m) Katibu Mkuu na manaibu wa Katibu Mkuu wa kila Jumuiya ya CCM (n) Wajumbe wote wa Halmashauri kuu ya CCM Taifa. (o) Mwenyekiti na Katibu wa Kamati ya Wabunge wote wa CCM (p) Mwenyekiti na Katibu wa Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM. (q) Wenyeviti wote wa CCM wa Mikoa. (r) Makatibu wote wa CCM wa Mikoa (s) Makatibu wa Siasa na Uenezi wa mikoa (t) Mwenyekiti, Katibu wa Mkoa na mjumbe mwingine mmoja aliyechaguliwa kutoka kila Mkoa wa Tanzania Bara na Zanzibar kwa kila Jumuiya ya CCM. (e) Kufuatilia hali ya Kisiasa Mkoani. (f) Kufuatilia mwenendo wa Jumuiya za Kijamii Mkoani. FUNGU LA VII VIKAO VYA TAIFA 98. Kutakuwa na Vikao vifuatavyo vya CCM vya Taifa:- (1) Mkutano Mkuu wa CCM wa Taifa. (2) Halmashauri Kuu ya CCM ya Taifa. (3) Kamati Kuu ya Halmashauri Kuu ya Taifa. (4) Kamati Maalum ya Halmashauri Kuu ya Taifa ya CCM (Zanzibar). (5) Sekretarieti ya Halmashauri Kuu ya CCM Taifa. (6) Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa. (7) Kamati ya Wabunge wote wa CCM. (8) Kamati ya Wajumbe wa Baraza la Wawakilishi wote wa CCM (Zanzibar). 99. (1) Mkutano Mkuu wa CCM wa Taifa utakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM. (b) Makamu wawili wa Mwenyekiti wa CCM. (c) Katibu Mkuu wa CCM. (d) Rais na Makamu wa Rais wa Jamhuri ya Muungano wa Tanzania. (e) Manaibu wa Katibu Mkuu wa CCM. Vikao vya CCM vya Taifa Mkutano Mkuu wa CCM wa Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 104 105 unaweza kufanyika wakati wowote ukiitishwa na Mwenyekiti wa CCM au ukiombwa na theluthi mbili ya wajumbe wote wa Halmashauri Kuu ya CCM ya Taifa. (4) Taarifa ya kukutana Mkutano Mkuu wa CCM wa Taifa ni lazima itolewe si chini ya miezi mitatu kabla ya tarehe ya kukutana. Lakini inaweza kutolewa taarifa ya muda mfupi zaidi ya huo ikiwa unafanyika mkutano usiokuwa wa kawaida. (5) Mkutano Mkuu wa CCM wa Taifa unaweza kukiagiza kikao chochote cha CCM kufanya kazi zozote ambazo ni za Mkutano huo bila Mkutano Mkuu wa CCM wa Taifa wenyewe kuathiri uwezo wake wa kufanya kazi hizo. (6) Kiwango cha mahudhurio ya Mkutano Mkuu wa CCM wa Taifa kitakuwa ni theluthi mbili ya Wajumbe kutoka Tanzania Bara na theluthi mbili ya Wajumbe kutoka Zanzibar. (7) Mwenyekiti wa CCM atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Taifa na asipoweza kuhudhuria, mmoja wa Makamu wa Mwenyekiti wa CCM ataongoza Mkutano huo. Iwapo itatokea kwamba wote watatu hawawezi kuhudhuria Mkutano fulani, Halmashauri Kuu ya CCM ya Taifa itamchagua Mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa Mkutano huo kwa ajili ya (u) Wenyeviti wote wa CCM wa Wilaya. (v) Makatibu wote wa CCM wa Wilaya. (w) Makatibu wa siasa na uenezi wa Wilaya (x) Wabunge wote wanaotokana na CCM au kama Bunge limevunjwa wale wanachama wote waliokuwa Wabunge mara kabla ya kuvunjwa Bunge; na Wabunge wote wa Bunge la Afrika Mashariki wanaotokana na CCM. (y) Wajumbe wote wa Baraza la Wawakilishi wanaotokana na CCM au kama Baraza hilo limevunjwa wale wanachama wote waliokuwa Wajumbe wa Baraza la Wawakilishi mara kabla ya kuvunjwa kwa Baraza hilo. (z) Wajumbe watatu waliochaguliwa na Mkutano mkuu wa CCM wa kila Wilaya. (2) Mkutano Mkuu wa CCM wa Taifa utakuwa ndicho Kikao Kikuu cha CCM kupita vyote na ndicho kitakachokuwa na madaraka ya mwisho. (3) Mkutano Mkuu wa CCM wa Taifa utafanya mikutano yake ya kawaida mara tatu katika kipindi cha miaka mitano. Mikutano miwili kati ya hiyo itakuwa ya uchaguzi na mmoja utakuwa wa kazi. Kalenda ya vikao vya Chama itaonyesha ni lini mikutano hiyo mitatu itafanyika. Lakini mkutano usiokuwa wa kawaida Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 106 107 (c) Kuchagua jumla ya Wajumbe Thelathini (30): kumi tano kutoka Tanzania Bara, na kumi tano kutoka Zanzibar wa kuingia katika Halmashauri Kuu ya CCM ya Taifa kutoka orodha ya Taifa. (6) Kuunda Kamati za Mkutano Mkuu wa CCM wa Taifa kwa kadri itakavyoonekana inafaa. (7) Mkutano Mkuu wa CCM wa Taifa waweza kukasimu madaraka yake kwa Halmashauri Kuu ya Taifa kuhusu utekelezaji wa kazi zake kwa kadri itakavyoona inafaa. 101. (1) Halmashauri Kuu ya CCM ya Taifa itakuwa na wajumbe wafuatao:- (a) Mwenyekiti wa CCM. (b) Makamu mwenyekiti wa CCM (Zanzibar) (c) Makamu mwenyekiti wa CCM (Bara) (d) Katibu Mkuu wa CCM (e) Rais na Makamu wa Rais wa Jamhuri ya Muungano wa Tanzania wanaotokana na CCM. (f) Rais wa Zanzibar anayetokana na CCM. (g) Manaibu wa Katibu Mkuu wa CCM (h) Waziri Mkuu wa Jamhuri ya Muungano wa Tanzania, na Makamu wa Rais wa Serikali ya Mapinduzi Zanzibar wanaotokana na CCM. shughuli hiyo. Kutokana na hali hiyo Halmashauri Kuu ya CCM ya Taifa inaweza kukutana hata kama Mwenyekiti na Makamu wote wawili wa Mwenyekiti hawapo. 100. Kazi za Mkutano Mkuu wa CCM wa Taifa zitakuwa zifuatazo:- (1) Kupanga Siasa ya CCM na kusimamia utekelezaji wa shughuli zote za CCM. (2) Kupokea na kufikiria taarifa ya kazi za CCM iliyotolewa na Halmashauri Kuu ya CCM ya Taifa na kutoa maelekezo ya mipango na utekelezaji wa Siasa ya CCM Kwa kipindi kijacho. (3) Kuthibitisha, kubadili, kukataa au kuvunja uamuzi wowote uliotolewa na kikao chochote cha chini yake au na Kiongozi yeyote wa CCM. (4) Kubadili sehemu yoyote ya Katiba ya CCM kwa uamuzi wa theluthi mbili za Wajumbe walio na haki ya kupiga kura kutoka Tanzania Bara na theluthi mbili kutoka Zanzibar. (5) Unapofika wakati wa uchaguzi, Mkutano Mkuu wa CCM wa Taifa utashughulikia mambo yafuatayo:- (a) Kuwachagua Mwenyekiti wa CCM na Makamu wa Mwenyekiti wa CCM. (b) Kuchagua jina moja la Mwanachama atakayesimama katika uchaguzi wa Rais wa Jamhuri ya Muungano wa Tanzania. Kazi za Mkutano Mkuu wa CCM wa Taifa Halmashauri Kuu ya CCM wa Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 108 109 (t) Wajumbe watano kutoka kila Jumuiya ya CCM, waliochaguliwa na Mkutano Mkuu wa Jumuiya. (u) Wajumbe saba waliochaguliwa na Halmashauri kuu ya Taifa kutokana na mapendekezo ya Mwenyekiti wa CCM. (v) Wajumbe watano waliochaguliwa na Wabunge wote wa CCM. (w) Wajumbe watatu waliochaguliwa na Wajumbe wa Baraza la Wawakilishi wa CCM kutoka miongoni mwao. (2) Halmashauri Kuu ya CCM ya Taifa itafanya mikutano yake ya kawaida mara moja katika kila miezi sita (6), lakini inaweza kufanya mkutano usiokuwa wa kawaida wakati wowote endapo itatokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. Mkutano wa Halmashauri Kuu ya Taifa utakaofanyika katika kipindi cha miezi sita ya mwisho wa kila mwaka utakuwa pia na kazi maalum ya kupokea na kujadili taarifa ya utekelezaji wa Ilani ya CCM unaofanywa na Serikali ya Jamhuri ya Muungano wa Tanzania pamoja na Serikali ya Mapinduzi ya Zanzibar katika mwaka wa fedha uliopita wa Serikali hizo ambao ulimalizika tarehe 30 Juni ya mwaka unaohusika. (i) Katibu wa Halmashauri Kuu ya Taifa wa Organaizesheni. (j) Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi. (k) Katibu wa Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa. (l) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha. (m) Mwenyekiti, Makamu Mwenyekiti na Katibu Mkuu wa kila Jumuiya ya CCM (n) Mwenyekiti na Katibu wa Kamati ya Wabunge wa CCM (o) Mwenyekiti na Katibu wa Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM. (p) Spika wa Bunge la Jamuhuri ya Muungano wa Tanzania anaye tokana na CCM, na Spika wa Baraza la Wawakilishi anayetokana na CCM (q) Wenyeviti wote wa CCM wa Mikoa. (r) Wajumbe wa Halmashauri Kuu ya Taifa mmoja kutoka kila mkoa wa Tanzania Bara na wanne kutoka kila mkoa wa Zanzibar waliochaguliwa na Mkutano Mkuu wa Mkoa. (s) Wajumbe kumi na tano kutoka Tanzania Bara na Wajumbe kumi na tano kutoka Zanzibar waliochaguliwa na Mkutano Mkuu wa CCM wa Taifa kutoka Orodha ya Taifa. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 110 111 (2) Kueneza Itikadi na Siasa ya CCM, kuongoza mafunzo ya Siasa ya CCM na kukuza nadharia na Itikadi ya CCM ya Ujamaa na Kujitegemea. (3) Kuongoza na kusimamia ujenzi wa Ujamaa na Kujitegemea nchini. (4) Kuandaa Ilani ya CCM ya Uchaguzi na kutoa msukumo wa utekelezaji wa Ilani hiyo. (5) Kufikisha maazimio na maagizo ya CCM katika Mikoa na kufikiria na kutoa uamuzi juu ya mapendekezo kutoka vikao vya CCM vya chini. (6) Kuona kwamba shughuli za Maendeleo na za Ulinzi na Usalama wa Taifa zinazingatiwa. (7) Kuandaa mikakati na mbinu za kampeni za uchaguzi na kampeni nyinginezo za kitaifa. (8) Kudumisha uangalizi juu ya vitendo vya Wanachama na Viongozi wa CCM na endapo itadhihirika kwamba tabia na mwenendo wa Mwanachama fulani vinamwondolea sifa za Uanachama au Uongozi itakuwa na uwezo wa kumwachisha au kumfukuza Uanachama au Uongozi alionao. Kuhusu mtu aliyeachishwa au kufukuzwa Uanachama, Halmashauri Kuu ya CCM ya Taifa ndiyo itakayokuwa na uwezo wa mwisho wa kumrudishia Uanachama wake kwa mujibu wa Katiba, endapo itaridhika kuwa amejirekebisha. (3) Katika mikutano yote ya Halmashauri Kuu ya CCM ya Taifa, uamuzi utafikiwa kwa makubaliano ya jumla, au kwa wingi wa kura za Wajumbe waliohudhuria na kupiga kura. Lakini ukitokea uamuzi unaohitajika kutolewa kuhusu vyombo vya Serikali ya Jamhuri ya Muungano wa Tanzania au vyombo vya Serikali ya Mapinduzi ya Zanzibar au kuhusu muundo wa Serikali ya Jamhuri ya Muungano wa Tanzania na Serikali ya Mapinduzi ya Zanzibar, uamuzi huo ni lazima upitishwe kwa azimio lililoungwa mkono na theluthi mbili ya kura za Wajumbe kutoka Tanzania Bara na theluthi mbili ya kura za Wajumbe kutoka Zanzibar. (4) Mwenyekiti wa CCM atakuwa Mwenyekiti wa Mkutano wa Halmashauri Kuu ya CCM ya Taifa, lakini Mwenyekiti wa CCM asipoweza kuhudhuria, mmoja wa Makamu wa Mwenyekiti wa CCM atakuwa Mwenyekiti wa muda wa Mkutano huo. 102. Kazi za Halmashauri Kuu ya CCM ya Taifa zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa ya CCM kwa jumla kwa Tanzania nzima. Kwa hiyo itakuwa na uwezo wa kubuni, kujadili, kuamua na kutoa Miongozo ya Siasa ya CCM katika mambo mbalimbali. Kazi za Halmashauri Kuu ya CCM wa Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 112 113 Halmshauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa na Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha na Katibu wa Halmashauri Kuu ya Taifa Organaizesheni kutoka miongoni mwa wajumbe wa Halmashauri Kuu ya Taifa. (e) Kuwachagua Wanachama wasiozidi saba (7) kuwa Wajumbe wa Halmashauri Kuu ya CCM ya Taifa kutokana na mapendekezo ya Mwenyekiti wa CCM. (f) Kuwachagua Wajumbe sita (6) wa Kamati Kuu ya Halmashauri Kuu ya Taifa watatu (3) kutoka Tanzania Bara na watatu (3) kutoka Zanzibar, wakiwemo wanawake wasiopungua wawili mmoja kutoka Tanzania Bara na mmoja kutoka Zanzibar. (g) Kufikiria na kufanya uteuzi wa mwisho wa majina ya Wanachama wanaoomba nafasi ya Ubunge na majina ya Wanachama wanaoomba nafasi ya Ujumbe wa Baraza la Wawakilishi kwa mujibu wa sheria zilizopo za uchaguzi huo. (h) Kufikiria na kufanya uteuzi wa mwisho wa majina ya Wanachama wanaoomba nafasi ya Ujumbe wa Halmashauri Kuu ya CCM ya Taifa; Uenyekiti wa CCM wa Wilaya na Mikoa na Ukatibu wa Siasa na Uenezi wa Mkoa. (9) Kuziongoza Halmashauri Kuu za CCM za Mikoa kuhusu vitendo na njia zinazofaa za kuimarisha CCM na za kuleta maendeleo. (10) Kuandaa Katiba, Kanuni na kuweka taratibu za kuongoza shughuli mbalimbali za CCM. (11) Kuandaa Mkutano Mkuu wa CCM wa Taifa. (12) Unapofika wakati wa Uchaguzi, Halmashauri Kuu ya CCM ya Taifa itashughulikia mambo yafuatayo:- (a) Kuteua jina la Mwanachama atakayesimama katika uchaguzi wa Mwenyekiti wa CCM, na majina mawili ya Wanachama watakaosimama katika uchaguzi wa Makamu wa Mwenyekiti wa CCM. (b) Kupendekeza kwa Mkutano Mkuu wa CCM wa Taifa majina yasiyozidi matatu ya Wanachama wanaogombea nafasi ya Rais wa Jamhuri ya Muungano wa Tanzania na kuyawasilisha mbele ya Mkutano Mkuu wa CCM wa Taifa. (c) Kuchagua jina moja la Mwanachama atakayesimama katika uchaguzi wa Rais wa Zanzibar. (d) Kuwachagua Katibu Mkuu wa CCM, Manaibu Katibu Mkuu wa CCM, Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi, Katibu wa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 114 115 hivyo Halmashauri Kuu ya CCM ya Taifa itafikisha uamuzi wake mbele ya Mkutano Mkuu wa CCM wa Taifa kwa uamuzi wa mwisho. (18) Kushughulikia uhusiano kati ya CCM na Jumuiya mbalimbali za wananchi na kuziorodhesha Jumuiya za CCM. (19) Kutengeneza na kurekebisha Muundo wa CCM katika maeneo na nyanja mbalimbali kwa kadri itakavyoonekana inafaa. (20) Kumsimamisha Mwenyekiti wa CCM au Makamu Mwenyekiti wa CCM iwapo mwenendo na utendaji wake wa kazi vinamwondolea sifa za uongozi. Hata hivyo Halmashauri Kuu ya CCM ya Taifa itafikisha mapendekezo yake mbele ya Mkutano Mkuu wa CCM wa Taifa kwa uamuzi wa mwisho. (21) Kumwachisha au kumfukuza Uongozi kiongozi yeyote ambaye uteuzi wake wa mwisho ulifanywa na Halmashauri Kuu ya CCM ya Taifa. (22) Kuunda Kamati ya Usalama na Maadili. (23) Kuidhinisha Kanuni za Kamati za Wabunge wote wa CCM, Wawakilishi wote wa CCM, Madiwani wote wa CCM; Katiba/Kanuni za Jumuiya za CCM na kuidhinisha marekebisho ya Katiba/ Kanuni hizo. (24) Halmashauri Kuu ya Taifa yaweza kukasimu madaraka yake kwa Kamati Kuu kuhusu utekelezaji wa kazi zake kwa kadri itakavyoona inafaa. (i) Kufanya uteuzi wa mwisho wa majina ya Wanachama wa CCM wanaogombea Uenyekiti wa Mkoa, Uenyekiti na Makamu Wenyeviti wa Taifa wa kila Jumuiya ya CCM. (j) Kuwachagua Wajumbe wanane wa Baraza la Wadhamini kutoka Tanzania Bara na Zanzibar. (13) Kujaza kwa niaba ya Mkutano Mkuu wa CCM wa Taifa, nafasi za uongozi zitakazokuwa wazi, isipokuwa ya Mwenyekiti wa CCM na Makamu wa Mwenyekiti wa CCM. (14) Kuunda Kamati au Tume kwa shughuli maalum bila kuathiri majukumu ya Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. (15) Kupokea na kujadili taarifa za Tume na Kamati Maalum za CCM, Kamati ya Wabunge wa CCM, na Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM. (16) Kuweka kiwango cha kiingilio katika CCM, ada za Uanachama na michango maalum. (17) Kusimamisha kwa maslahi ya CCM utumiaji wa kifungu chochote cha Katiba ya CCM au kuruhusu kifungu kutumika kabla ya kuingizwa ndani ya Katiba. Uamuzi huo sharti uungwe mkono na theluthi mbili ya Wajumbe kutoka Tanzania Bara na theluthi mbili za Wajumbe kutoka Zanzibar. Hata Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 116 117 (o) Mwenyekiti wa Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM. (p) Spika wa Bunge la Jamhuri ya Muungano anayetokana na CCM, na Spika wa Baraza la Wawakilishi la Zanzibar anayetokana na CCM. (q) Wajumbe Sita waliochaguliwa na Halmashauri Kuu ya CCM ya Taifa watatu (3) kutoka Tanzania Bara na watatu (3) kutoka Zanzibar, wakiwemo wanawake wasiopungua wawili mmoja kutoka Tanzania Bara na mmoja kutoka Zanzibar. (2) Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa itafanya mikutano yake ya kawaida mara moja katika kila miezi minne lakini inaweza kufanya mkutano usio wa kawaida wakati wowote itakapotokea haja ya kufanya hivyo au kwa maagizo ya kikao cha juu. (3) Mwenyekiti wa CCM atakuwa Mwenyekiti wa Mkutano wa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa, lakini Mwenyekiti wa CCM asipoweza kuhudhuria, mmoja wa Makamu wa Mwenyekiti atakuwa Mwenyekiti wa muda wa Mkutano huo. 104. Kazi za Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa zitakuwa zifuatazo:- (1) Kutoa uongozi wa Siasa katika nchi. (2) Kusimamia utekelezaji wa shughuli za kila siku za CCM. 103. (1) Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa itakuwa na wajumbe wafuatao: - (a) Mwenyekiti wa CCM. (b) Makamu wawili wa Mwenyekiti wa CCM (c) Katibu Mkuu wa CCM. (d) Rais na Makamu wa Rais wa Jamhuri ya Muungano wa Tanzania wanaotokana n a CCM. (e) Rais wa Zanzibar anayetokana na CCM. (f) Makamu wa Rais wa Serikali ya Mapinduzi ya Zanzibar anayetokana na CCM. (g) Manaibu Katibu Mkuu wa CCM. (h) Waziri Mkuu wa Jamhuri ya Muungano wa Tanzania anayetokana na CCM na Makamu wa pili wa Rais wa Zanzibar anayetokana na CCM. (i) Katibu wa Halmashauri Kuu ya Taifa wa Organaizasheni. (j) Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi. (k) Katibu wa Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa. (l) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha. (m) Mwenyekiti wa Taifa wa kila Juimuiya ya CCM. (n) Mwenyekiti wa kamati ya Wabunge wa CCM. Kamati Kuu ya Halmashauri Kuu ya Taifa Kazi za Kamati Kuu ya Halmashauri Kuu ya Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 118 119 (e) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Taifa juu ya Wanachama wanaoomba nafasi za uongozi katika CCM na Jumuiya za CCM ambao uteuzi wao wa mwisho unafanywa na Halmashauri Kuu ya CCM ya Taifa. (f) Kufikiria na kuteua majina ya wana CCM wasiozidi watatu kwa kila jimbo la uchaguzi walioomba nafasi ya Ubunge na Ujumbe wa Baraza la Wawakilishi ili wakapigiwe kura za maoni, na baada ya kura za maoni itafikiria na kutoa mapendekezo yake kwa Halmashauri kuu ya Taifa juu ya wanachama wanaoomba nafasi ya Ubunge na Wanachama wanaoomba nafasi ya Ujumbe wa Baraza la Wawakilishi kwa uteuzi wa mwisho. (g) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu yaTaifa juu ya Wanachama wa CCM wanaoomba nafasi za uongozi katika Jumuiya za CCM, ngazi ya Mkoa na Taifa, ambazo uteuzi wake wa mwisho hufanywa na Halmashauri Kuu ya CCM Taifa. (h) Kufikiria na Kufanya uteuzi wa mwisho wa wanachama wa CCM wanaoomba kugombea nafasi ya Spika wa Bunge/Baraza la Wawakilishi, Meya wa Halmashauri ya Jiji/Manispaa. (3) Kueneza Itikadi na Siasa ya CCM nchini. (4) Kusimamia kampeni za Uchaguzi na kampeni nyinginezo. (5) Kuteua Katibu wa Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa. (6) Kuteua Makatibu wakuu wa Jumuiya za CCM (7) Unapofika wakati wa Uchaguzi Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa itashughulikia mambo yafuatayo:- (a) Kufikiria na kutoa mapendekezo kwa Halmashauri Kuu ya CCM ya Taifa juu ya Wanachama watakaosimama katika uchaguzi wa Mwenyekiti wa CCM. (b) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Taifa juu majina ya Wanachama wasiozidi watano wanaoomba kugombea kiti cha Rais wa Jamhuri ya Muungano wa Tanzania. (c ) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Taifa juu ya Wanachama watakaosimama katika uchaguzi wa Makamu wa Mwenyekiti wa CCM. (d) Kufikiria na kutoa mapendekezo yake kwa Halmashauri Kuu ya CCM ya Taifa juu ya majina ya Wanachama wasiozidi watatu ambao wanaomba kugombea kiti cha Rais wa Zanzibar. Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 120 121 (9) Katibu wa Kamati ya Wajumbe wa Baraza la wawakilishi wote wa CCM 106. (1) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Taifa yatakuwa yafuatayo:- (a) Kusimamia shughuli zote za utendaji za Chama kitaifa. (b) Kuandaa shughuli za vikao vya Chama ngazi ya Taifa. (c ) Kuwateua Makatibu Wasaidizi Wakuu na Wakuu wa Vitengo vya Makao Makuu ya Chama. (d) Kuwateua Manaibu wa Katibu Mkuu wa kila Jumuiya CCM (e) Kuwateua Makatibu wa CCM wa Mikoa, Makatibu wa CCM wa Wilaya na watumishi wengine wa CCM. (2) Majukumu ya Sekretarieti ya Halmashauri Kuu ya Taifa yatagawanyika ifuatavyo:- (a) Katibu Mkuu wa CCM. (b) Idara ya Organaizesheni. (c) Idara ya Itikadi na Uenezi. (d) Idara ya Mambo ya Siasa na Uhusiano wa Kimataifa. (e) Idara ya Uchumi na Fedha. (3) Kila Idara itaongozwa na Katibu wa Halmashauri Kuu ya Taifa ya CCM. Idara ya Utawala na Uendeshaji Bara au Zanzibar itaongozwa na Naibu Katibu Mkuu wa CCM. (8) Kumsimamisha uongozi kiongozi yeyote isipokuwa Mwenyekiti wa CCM na Makamu wa Mwenyekiti wa CCM endapo itaridhika kwamba tabia na mwenendo wake vinamwondolea sifa za uongozi. (9) Kuona kwamba masuala ya Ulinzi na Usalama wa Taifa na Maendeleo yanazingatiwa. (10) Kuandaa mikutano ya Halmashauri Kuu ya CCM ya Taifa. (11) Kuwa na mikakati endelevu ya kuimarisha Chama kimapato, kudhibiti mapato na mali za Chama na kuthibitisha matumizi ya Chama katika ngazi ya Taifa. 105. Kutakuwa na Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa ambayo itakuwa na wajumbe wafuatao:- (1) Katibu Mkuu wa CCM ambaye atakuwa Mwenyekiti. (2) Manaibu Katibu Mkuu wa CCM. (3) Katibu wa Halmashauri Kuu ya Taifa wa Organaizesheni. (4) Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi. (5) Katibu wa Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa. (6) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha. (7) Makatibu Wakuu wa Jumuiya za CCM. (8) Katibu wa Kamati ya wabunge wote wa CCM Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa Majukumu ya Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 122 123 (d) Kusimamia Vyombo vya Habari vya Chama, Mawasiliano na Uhamasishaji wa Umma kwa Jumla. (e) Kuongoza na kusimamia maandalizi ya Sera, Programu na Ilani za Uchaguzi za CCM. (f) Kusimamia Utafiti, Maktaba na Nyaraka za Chama. (3) Idara ya Mambo ya Siasa na Uhusiano wa Kimataifa:- (a) Kufuatilia hali ya kisiasa nchini. (b) Kufuatilia utekelezaji wa Ilani ya Uchaguzi na Sera za Kijamii za CCM. (c) Kufuatilia harakati za Vyama vya Siasa nchini. (d) Kufuatilia maendeleo ya Jumuiya za Kijamii nchini. (e) Kuratibu uhusiano na ushirikiano wa CCM na vyama vya siasa vya kidugu, kirafiki na vya kimapinduzi. (f) Kufuatilia hali ya kisiasa katika nchi jirani na nchi nyinginezo duniani. (g) Kufuatilia maendeleo ya Kamati za Urafiki na mshikamano kati ya Watanzania na wananchi wa nchi rafiki. (h) Kushughulikia masuala ya Itifaki ndani ya Chama. (4) Kila Idara ya Makao Makuu ya Chama itakuwa na Kamati ya Ushauri yenye Wajumbe wasiozidi watano akiwemo na Katibu wa Halmashauri Kuu ya Taifa. Wajumbe hao watateuliwa na Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. 107. Kazi za Idara za Sekretarieti ya Halmashauri Kuu ya Taifa:- (1) Idara ya Organaizesheni:- (a) Kushughulikia masuala yote ya wanachama wa CCM. (b) Kufuatilia vikao na maamuzi ya vikao vya Chama. (c) Kusimamia Jumuiya za CCM na Wazee wa Chama. (d) Kusimamia masuala yote ya Uchaguzi wa ndani ya CCM na ule wa Uwakilishi katika Vyombo vya Dola. (e) Kusimamia Katiba, Muundo, Kanuni na Taratibu za Chama na Jumuiya za CCM. (2) Idara ya Itikadi na Uenezi:- (a) Kushughulikia masuala ya msingi ya Itikadi na Sera za Chama Cha Mapinduzi. (b) Kueneza na kufafanua Itikadi na Sera za CCM. (c) Kupanga na kusimamia Mafunzo na Maandalizi ya Makada na Wanachama. Kazi za idara ya Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 124 125 (2) Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa itafanya mikutano yake ya kawaida mara moja kila miezi mitatu. (3) Mwenyekiti wa Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa atakuwa Makamu Mwenyekiti wa CCM kutoka Zanzibar. Katibu wa Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa atakuwa Naibu Katibu Mkuu wa CCM kutoka Zanzibar. (4) Mwenyekiti wa Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa ataongoza mikutano ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa. Lakini Mwenyekiti asipoweza kuhudhuria, Mkutano huo utamchagua Mjumbe mwingine yeyote miongoni mwao kuwa Mwenyekiti wa muda wa mkutano huo. 109. Kazi za Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa zitakuwa zifuatazo:- (1) Kusaidia Kamati Kuu kutoa Uongozi wa Siasa Zanzibar. (2) Kueneza Itikadi na Siasa ya CCM Zanzibar. (3) Kuisaidia Kamati Kuu katika kusimamia utekelezaji wa shughuli za kila siku za CCM Zanzibar. (4) Kutafuta na kubuni njia au mbinu mbalimbali zinazoweza kukifanya Chama kujitegemea kimapato Zanzibar. (4) Idara ya Uchumi na Fedha:- (a) Kufuatilia utekelezaji wa Sera za CCM za Uchumi. (b) Kuratibu mapato ya fedha za Chama nchini kote kwa ajili ya maamuzi ya uwekezaji wa Chama. (c) Kusimamia vitega uchumi na uwekezaji katika Chama. (d) Kusimamia Mali za Chama nchini kote. (e) Kusimamia mapato na matumizi ya Chama katika ngazi zote za uongozi wa CCM. 108. (1) Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa Zanzibar itakuwa na Wajumbe wafuatao:- (a) Makamu Mwenyekiti wa CCM Zanzibar. (b) Naibu Katibu Mkuu wa CCM Zanzibar. (c) Rais wa Zanzibar anayetokana na CCM. (d) Makamu wa Rais wa Zanzibar anayetokana na CCM. (e) Wajumbe wa Kamati Kuu ya Halmashauri Kuu ya CCM Taifa kutoka Zanzibar. (f) Wenyeviti wa CCM wa Mikoa ya Zanzibar. (g) Wajumbe wote wa Halmashauri Kuu ya CCM ya Taifa wanaotoka Zanzibar. Kamati maalum ya Halmashauri Kuu ya CCM ya Taifa Kazi za Kamati maalum ya Halmashauri Kuu ya CCM ya Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 126 127 Aidha, inaweza kujiwekea utaratibu wake wa kufanyakazi kwa kadri itakavyoona inafaa kwa ajili ya kufanikisha shughuli za CCM Zanzibar. (e) Kuwachagua Katibu wa Kamati Maalum ya Halmashauri Kuu ya Taifa wa Organaizesheni Zanzibar, Katibu wa Kamati Maalum ya Halmashauri kuu ya Taifa wa Itikadi na Uenezi Zanzibar, Katibu wa Kamati Maalum ya Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa Zanzibar na Katibu wa Kamati Maalum ya Halmashauri Kuu ya Taifa wa Uchumi na Fedha, Zanzibar, kutoka miongoni mwao. (f) Kupokea na kujadili taarifa za Kamati Ndogo za CCM. (g) Kufikiria na kutoa mapendekezo yake kwa Kamati Kuu juu ya Wanachama wa CCM wanaoomba nafasi za uongozi katika Jumuiya za CCM, ngazi ya Mkoa na Taifa kwa upande wa Zanzibar, ambazo uteuzi wake wa mwisho hufanywa na Halmashauri Kuu ya Taifa. 110. Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa itakuwa na wajumbe wafuatao:- (1) Naibu Katibu Mkuu wa CCM (Zanzibar) ambaye atakuwa Mwenyekiti. (5) Kuandaa mikakati na mbinu za kampeni za uchaguzi na kampeni nyinginezo. (6) Kuona kwamba masuala ya Ulinzi na Usalama na ya Maendeleo yanazingatiwa. (7) Unapofika wakati wa Uchaguzi Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa itashughulikia mambo yafuatayo:- (a) Kufikiria na kutoa mapendekezo yake kwa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa juu ya Wanachama wanaoomba nafasi za uongozi katika CCM kutoka Zanzibar, ambao uteuzi wao wa mwisho unafanywa na Halmashauri Kuu ya CCM ya Taifa. (b) Kufikiria na kutoa mapendekezo yake kwa Kamati Kuu ya Halmashauri Kuu ya Taifa juu ya Wanachama wanaoomba nafasi ya Rais wa Zanzibar, Ubunge na Ujumbe wa Baraza la Wawakilishi Zanzibar. (c) Kupendekeza kwa Kamati Kuu kumsimamisha uongozi kiongozi yeyote wa CCM wa Zanzibar isipokuwa Makamu Mwenyekiti wa CCM endapo itaridhika kwamba tabia na mwenendo wake vinamwondolea sifa za uongozi. (d) Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa inaweza kuunda Kamati Ndogo za CCM . Sekretarieti ya kamati maalum ya Halmashauri Kuu ya CCM ya Taifa Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 128 129 (e) Idara ya Uchumi na Fedha, Zanzibar. (3) Kila Idara ya Zanzibar itaongozwa na Katibu wa Kamati Maalum ya Halmashauri Kuu ya Taifa ambaye atateuliwa na Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa. (4) Idara za Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa zitatekeleza kazi na majukumu ambayo kwa upande wa Bara yanatekelezwa na Idara za Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa. 112. Chama cha Mapinduzi kitakuwa na Wakuu wa CCM wafuatao:- (1) Mwenyekiti wa CCM. (2) Makamu wawili wa Mwenyekiti wa CCM. (3) Katibu Mkuu wa CCM. 113. Mwenyekiti wa CCM ndiye kiongozi mkuu na ndiye msemaji mkuu wa CCM (1) Atachaguliwa na Mkutano Mkuu wa CCM wa Taifa na atakuwa katika nafasi hiyo ya uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (2) Anaweza kuondolewa katika uongozi kwa azimio litakalopitishwa katika Mkutano Mkuu wa CCM wa Taifa na kuungwa mkono na theluthi mbili za Wajumbe kutoka Tanzania Bara na theluthi mbili za W ajumbe kutoka Zanzibar. (2) Katibu wa Kamati Maalum wa Idara ya Organaizesheni. (3) Katibu wa Kamati Maalum wa Idara ya Itikadi na Uenezi. (4) Katibu wa Kamati Maalum wa Idara ya Mambo ya Siasa na Uhusiano wa Kimataifa. (5) Katibu wa Kamati Malum wa Uchumi na Fedha. (6) Manaibu Katibu Mkuu wa Jumuiya za CCM wanaoishi na kufanya kazi Zanzibar. (7) Katibu wa Kamati ya Wajumbe wa Baraza la Wawakilishi wote wa CCM 111. (1) Majukumu ya Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa yatakuwa yafuatayo:- (a) Kusimamia na kuratibu shughuli zote za utendaji za Chama Zanzibar. (b) Kuandaa shughuli za vikao vya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa Zanzibar. (2) Majukumu ya Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya Taifa Zanzibar yatagawanyika ifuatavyo:- (a) Naibu Katibu Mkuu wa CCM (Zanzibar). (b) Idara ya Organaizesheni, Zanzibar. (c) Idara ya Itikadi na Uenezi, Zanzibar. (d) Idara ya Mambo ya Siasa na Uhusiano wa Kimataifa, Zanzibar. Majukumu ya Sekretarieti ya kamati maalum ya Halmashauri Kuu ya CCM ya Taifa Wakuu wa CCM Mwenyekiti wa CCM Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 130 131 (3) Makamu wa Mwenyekiti wa CCM anaweza kuondolewa katika madaraka hayo kwa azimio litakalopitishwa na Mkutano Mkuu wa CCM wa Taifa na kuungwa mkono na theluthi mbili za Wajumbe kutoka Tanzania Bara, na theluthi mbili za Wajumbe kutoka Zanzibar. (4) Makamu wa Mwenyekiti watakuwa ndiyo wasaidizi wakuu wa Mwenyekiti wa CCM na watafanya kazi zote za CCM watakazopewa na Mwenyekiti wa CCM. 115. (1) Katibu Mkuu wa CCM atachaguliwa na Halmashauri Kuu ya CCM ya Taifa. (2) Atakuwa Katibu wa Mkutano Mkuu wa CCM wa Taifa, Halmashauri Kuu ya CCM ya Taifa, na Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. (3) Atakuwa ndiye Mtendaji Mkuu wa CCM na atafanya kazi chini ya uongozi wa Halmashauri Kuu ya CCM ya Taifa. (4) Atakuwa na wajibu wa kuitisha Mikutano yote ya Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa, Halmashauri Kuu ya CCM ya Taifa na Mkutano Mkuu wa CCM wa Taifa. (5) Ataitisha na kuongoza vikao vya Sekretarieti ya Halmashauri Kuu ya CCM ya Taifa kwa madhumuni ya kushauriana, kuandaa agenda za Kamati Kuu, na kuchukua hatua za utekelezaji wa maamuzi ya CCM. (3) Atakuwa Mwenyekiti wa Mkutano Mkuu wa CCM wa Taifa, Halmashauri Kuu ya CCM ya Taifa na Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. (4) Katika mikutano anayoiongoza zaidi ya kuwa na kura yake ya kawaida Mwenyekiti atakuwa pia na kura ya uamuzi endapo kura za Wajumbe wanaoafiki na wasioafiki zitalingana. Isipokuwa kwamba kama kikao anachokiongoza ni kikao cha Uchaguzi, Mwenyekiti atakuwa na kura yake ya kawaida tu. Hatakuwa na haki ya kutumia kura yake ya uamuzi endapo kura za wajumbe zimelingana. Wajumbe wa kikao wataendelea kupiga kura mpaka hapo mshindi atakapopatikana. 114. (1) Kutakuwa na Makamu wa Mwenyekiti wa CCM wawili watakaochaguliwa na Mkutano Mkuu wa CCM wa Taifa. Kutakuwa na Makamu wa Mwenyekiti anayeishi na kufanyia kazi zake Tanzania Bara; na kutakuwa na Makamu wa Mwenyekiti wa CCM anayeishi na kufanyia kazi zake Zanzibar. Isipokuwa kwamba kuishi kwao hivyo hakutapunguza upeo wa madaraka yao ya kushughulikia kazi za CCM kwa Tanzania nzima. (2) Makamu Mwenyekiti wa CCM atakuwa katika madaraka hayo kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. Makamu Mwenyekiti wa CCM Katibu Mkuu wa CCM Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 132 133 na kufanyia kazi zake Zanzibar. Isipokuwa kwamba kuishi kwao hivyo hakutapunguza upeo wa madaraka yao ya kushughulikia kazi za CCM kwa Tanzania nzima. (3) Naibu Katibu Mkuu wa CCM atakayefanya kazi Zanzibar atakuwa na wajibu wa kuandaa na kuitisha mikutano ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa Zanzibar na ataitisha na kuongoza vikao vya Sekretarieti ya Kamati Maalum ya Halmashauri Kuu ya CCM ya Taifa Zanzibar. (4) Manaibu Katibu Mkuu wa CCM watakuwa ndio wasaidizi wakuu wa Katibu Mkuu wa CCM na watafanya kazi zozote za CCM watakazopangiwa na Katibu Mkuu wa CCM. 118. (1) Katibu wa Halmashauri Kuu ya Taifa wa Organaizesheni atachaguliwa Halmashauri Kuu ya CCM Taifa. (2) Atakuwa ndiye Msimamizi Mkuu wa Organaizesheni ya CCM. (3) Atakuwa Naibu Mkurugenzi wa Uchaguzi wa Chama nchini na atafanya kazi hii chini ya uongozi wa Katibu Mkuu wa CCM ambaye ndiye Mkurugenzi wa Uchaguzi wa Chama. 119. (1) Katibu wa Halmashauri Kuu ya Taifa wa Itikadi na Uenezi atachaguliwa na Halmashauri Kuu ya CCM ya Taifa. (6) Atakuwa ndiye Mkurugenzi wa Uchaguzi wa Chama nchini (7) Kazi na majukumu ya Katibu Mkuu wa CCM:- (a) Kuratibu kazi zote za Chama Cha Mapinduzi. (b) Kusimamia kazi za Utawala na Uendeshaji katika Chama. (c) Kufuatilia na kuratibu masuala ya Usalama na Maadili katika Chama. (d) Kusimamia Udhibiti wa Fedha na Mali za Chama. 116. Kutakuwa na Viongozi wengine wa CCM wa Kitaifa wafuatao:- (1) Naibu Katibu Mkuu Bara na Naibu Katibu Mkuu Zanzibar. (2) Katibu wa Halmashauri Kuu ya Taifa wa Organaizesheni. (3) Katibu wa Halmashauri Kuu ya Taifa wa itikadi na Uenezi (4) Katibu wa Halmashauri Kuu ya Taifa wa mambo ya Siasa na Uhusiano wa Kimataifa. (5) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha 117. (1) Kutakuwa na Manaibu Katibu Mkuu wa CCM wawili. (2) Kutakuwa na Naibu Katibu MKuu wa CCM atakayeishi na kufanyia kazi zake Tanzania Bara, na kutakuwa na Naibu Katibu Mkuu wa CCM atakayeishi Viongozi wengine wa Kitaifa wa CCM Manaibu Katibu Mkuu wa CCM Katibu wa Halmashauri kuu ya Taifa wa Organizesheni Katibu wa Halmashauri kuu ya Taifa wa wa Itikadi na Uenezi Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 134 135 (a) Marais wastaafu wa Jamhuri ya Muungano wa Tanzania, ambao pia walikuwa ni Wenyeviti wa CCM. (b) Marais wastaafu wa Zanzibar, ambao pia walikuwa ni Makamu Wenyeviti wa CCM. (c) Makamu wa Mwenyekiti wa CCM wa wastaafu. (2) Baraza hilo litafanya vikao vyake kulingana na mahitaji kama itakavyooamuliwa na Baraza lenyewe. (3) Kazi za Baraza hilo zitakuwa ni kutoa ushauri kwa Chama Cha Mapinduzi na Serikali zinazoogozwa na CCM, kwa namna ambayo Baraza lenyewe litaona kuwa inafaa. Isipokuwa kwamba kwa madhumuni ya kutoa ushauri katika jambo mahsusi, Wajumbe wa Baraza hilo wanaweza pia kualikwa, ama wote kwa pamoja au kwa Mwakilishi wao, kuhudhuria Vikao vya Chama ngazi za Taifa pale ambapo busara zao zitahitajika hususan katika masuala Muhimu na nyeti. (2) Atashughulikia masuala ya msingi ya Itikadi na Sera za CCM. (3) Atakuwa ndiye Msimamizi Mkuu wa shughuli za Uenezi wa Itikadi, Siasa na Sera za CCM. 120. (1) Katibu wa Halmashauri Kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa atachaguliwa na Halmashauri Kuu ya CCM ya Taifa. (2) Atakuwa ndiye Msimamizi Mkuu wa Mambo ya Siasa na Uhusiano wa Kimataifa ndani ya Chama. (3) Atashughulikia masuala ya kuimarisha uhusiano mwema baina ya CCM na vyama vya siasa vya nchi nyingine; na harakati za vyama vya siasa na maendeleo ya Jumuiya za Kijamii nchini. 121. (1) Katibu wa Halmashauri Kuu ya Taifa wa Uchumi na Fedha atachaguliwa na Halmas hauri Kuu ya CCM ya Taifa. (2) Atakuwa ndiye Msimamizi Mkuu wa masuala ya Uchumi, Fedha na Mali za Chama. (3) Atafuatilia utekelezaji wa Sera za CCM za Uchumi na ataratibu mapato ya fedha za Chama nchini kote kwa ajili ya maamuzi ya uwekezaji wa Chama 122. (1) Kutakuwa na Baraza la Ushauri la Viongozi Wakuu Wastaafu. Baraza hilo litakuwa na Wajumbe wafuatao: - Katibu wa Halmashauri kuu ya Taifa wa Mambo ya Siasa na Uhusiano wa Kimataifa Katibu wa Halmashauri kuu ya Taifa wa Uchumi na Fedha Baraza la Ushauri la Viongozi Wakuu Wastaafu Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 136 137 SEHEMU YA TANO MENGINEYO 125. (1) Kutakuwa na Baraza la Wadhamini wa CCM (2) Baraza hilo litakuwa na Wajumbe wafuatao:- (a) Mwenyekiti ambaye atateuliwa na Mwenyekiti wa CCM kutoka miongoni mwa Wajumbe wa Baraza. (b) Wajumbe wanane waliochaguliwa na Halmashauri Kuu ya CCM ya Taifa. (3) Baraza la Wadhamini la CCM litafanya Vikao vyake kila baada ya miezi minne, yaani si chini ya mara tatu kwa mwaka. (4) Baraza hili litakuwa na uwezo wote ule wa wadhamini kwa mujibu wa Sheria. (5) Baraza la Wadhamini wa CCM litasimamia Mali zote za CCM na Jumuiya za CCM, zinazoondosheka na zisizoondosheka. Baraza ndilo litakuwa na mamlaka ya kuingia mikataba yote inayohusu mali za CCM na Jumuiya zake, isipokuwa kwamba Baraza laweza kukasimu madaraka yake kwa Kamati za Siasa za Mikoa. SEHEMU YA NNE WAZEE NA JUMUIYA ZA WANANCHI 123. Kutakuwa na Baraza la Wazee wanaotokana na CCM katika kila ngazi ya Uongozi isipokuwa ngazi ya Taifa. Wajumbe wa mabaraza hayo watakuwa Wazee wote (kuanzia miaka sitini) wanaokubali imani, malengo na madhumuni ya CCM. 124. Chama Cha Mapinduzi kitakuwa na uhusiano na Jumuiya mbalimbali za Wananchi:- (1) Kutakuwa na Jumuiya za CCM ambazo kwa sasa ni:- (a) Umoja wa Vijana wa CCM (UVCCM), (b) Umoja wa Wanawake Tanzania (UWT). (c) Umoja wa Wazazi (WAZAZI). (2) Kutakuwa na Jumuiya nyingine zilizojishirikisha na CCM. (3) Halmashauri Kuu ya CCM ya Taifa inaweza kuongeza na kupunguza katika orodha, Jumuiya zinazoongozwa au zilizojishirikisha na CCM. (4) Halmashauri Kuu ya CCM ya Taifa itakuwa na uwezo wa kushauri, kutoa maagizo ya jumla, na maelekezo maalum kwa Jumuiya zinazoongozwa na CCM. (5) Halmashauri Kuu ya Taifa itathibitisha Kanuni/Katiba ya kila Jumuiya inayoongozwa na CCM na marekebisho yake kabla hazijatumika. Sehemu ya Wazee Jumuiya za Wananchi Baraza la Wadhamini Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 138 139 126. Isipokuwa kama imeagizwa vingine katika Katiba hii ya CCM, kiwango cha mahudhurio katika mikutano ya CCM kitakuwa ni zaidi ya nusu ya Wajumbe walio na haki ya kuhudhuria katika kikao kinachohusika. 127. Isipokuwa kama imeagizwa vingine katika Katiba hii ya CCM uamuzi utafikiwa katika vikao vyote vya CCM kwa kufuata makubaliano ya jumla au wingi wa kura za Wajumbe waliohudhuria na kupiga kura. Lakini katika shughuli zozote za uchaguzi wa Viongozi, kura zitakuwa za Siri. 128. Wakati wowote kunapotokea nafasi wazi miongoni mwa viti vyovyote vya CCM, kikao kinachohusika kitajaza nafasi hiyo bila kuchelewa kwa kufuata utaratibu uliowekwa. 129. (1) Mwanachama anayetaka kujiuzulu atafanya hivyo kwa kuandika barua ya kujiuzulu kwake na kuipeleka kwa Katibu wa Tawi lake. (2) Kiongozi anayetaka kujiuzulu atafanya hivyo kwa kuandika barua ya kujiuzulu kwake na kuipeleka kwa Katibu wa Kikao kilichomchagua au kumteua. 130. (1) Kiongozi anayetaka kung’atuka atafanya hivyo kwa kuandika barua ya kung’atuka kwake na kuipeleka kwa Katibu wa kikao kilichomchagua au kumteua, au (6) Kazi za Baraza hilo zitakuwa zifuatazo; (a) Kusimamia Mali zote za CCM na Jumuiya za CCM zinazoondosheka na zisizoondosheka. (b) Kufanya tathmini ya mara kwa mara ya mali za CCM na Jumuiya za CCM. (c) Kutoa ushauri juu ya mabadiliko yoyote yanayohitajika katika umiliki wa mali za CCM na Jumuiya za CCM kwa mfano kuhusu mali zinazostahili kuuzwa. (d) Kutekeleza majukumu mengine yoyote ambayo yatakabidhiwa kwake na Kamati Kuu ya Halmashauri Kuu ya Taifa. (7) Baraza hili litafanya kazi chini ya uongozi wa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa na litawajibika kutoa taarifa yake kwa kikao hicho. (8) Mdhamini atashika nafasi hiyo ya uongozi kwa muda wa miaka mitano, lakini anaweza kuchaguliwa tena baada ya muda huo kumalizika. (9) Iwapo Mwenyekiti wa Baraza hili hataweza kuhudhuria Mkutano wowote, Baraza lenyewe litachagua Mjumbe mwingine miongoni mwao atakayekuwa Mwenyekiti wa muda wa Mkutano huo. Kiwango cha Mahudhurio katika kufikia uamuzi Kiwango cha kura katika kufikia maamuzi Nafasi zikiwa wazi Kujiuzulu Kung’atuka Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 140 141 136. Unapofika wakati wa uchaguzi, Kamati ya Wabunge wote wa CCM itachagua Wajumbe watano (5) kutoka miongoni mwao, kuwa Wajumbe wa Halmashauri Kuu ya Taifa. 137. Wajumbe wote wa Baraza la Wawakilishi wanaotoka na CCM kwa pamoja watakuwa ni Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM ambayo kazi yake itakuwa ni kusimamia kwa jumla utekelezaji wa Ilani ya CCM na Siasa ya CCM katika shughuli zote zinazoendeshwa na Baraza la Wawakilishi, pamoja na kutekeleza kazi nyingine ambazo zimeainishwa katika Kanuni zake zinazohusika. Vikao vya Kamati hii vitafanyika kwa mujibu wa Kanuni zake hizo. 138. Mwenyekiti wa CCM anaweza kuitisha vikao vya pamoja baina ya Halmashauri Kuu ya Taifa na Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM kwa ajili ya kushughulikia mambo kama itakavyoonekana inafaa. 139. Mwenyekiti wa Kamati ya Wajumbe wa Baraza la Wawakilishi wa CCM atakuwa mjumbe wa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. 140. Unapofika wakati wa uchaguzi, Wajumbe wote wa Baraza la Wawakilishi wanaotokana na CCM watachagua Wajumbe watatu (3) kutoka miongoni mwao kuwa Wajumbe wa Halmashauri Kuu ya CCM Taifa. (2) Kwa kutangaza uamuzi wa kung’atuka kwake mbele ya kikao kilichomchagua. 131. Mjumbe yeyote wa kikao chochote kilichowekwa na Katiba hii ataacha kuwa Mjumbe wa kikao hicho iwapo hatahudhuria mikutano mitatu mfululizo ya kikao chake isipokuwa kama ni kwa sababu zinazokubaliwa na kikao chenyewe. 132. Wabunge wote wanaotokana na CCM kwa pamoja watakuwa ni Kamati ya Wabunge wa CCM ambao kazi yake itakuwa ni kusimamia kwa jumla utekelezaji wa Ilani ya CCM na Siasa ya CCM katika shughuli zote zinazoendeshwa na Bunge, pamoja na kutekeleza kazi nyingine ambazo zimeainishwa katika Kanuni zake zinazohusika. Vikao vya Kamati hii vitafanyika kwa mujibu wa Kanuni zake hizo. 133. Kamati hii itakuwa na uwezo wa kutunga Kanuni zake kwa ajili ya uendeshaji bora wa shughuli zake. Kanuni hizo itabidi ziidhinishwe na Halmashauri kuu ya Taifa kabla hazijaanza kutumika. 134. Mwenyekiti wa CCM anaweza kuamua kuitisha vikao vya pamoja baina ya Halmashauri Kuu ya Taifa ya CCM na Kamati ya Wabunge wote wa CCM kwa ajili ya kushughulikia mambo kama itakavyoonekana inafaa. 135. Mwenyekiti wa Kamati ya Wabunge wote wa CCM atakuwa mjumbe wa Kamati Kuu ya Halmashauri Kuu ya CCM ya Taifa. Kuacha Ujumbe wa Kikao Kamati ya Wabunge wa CCM Kamati ya Wawakilishi wa CCM Katiba ya Chama Cha Mapinduzi Katiba ya Chama Cha Mapinduzi 142 143 NYONGEZA ‘A’ AHADI ZA WANACHAMA WA CHAMA CHA MAPINDUZI (1) Binadamu wote ni ndugu zangu na Afrika ni Moja. (2) Nitaitumikia nchi yangu na watu wake wote. (3) Nitajitolea nafsi yangu kuondosha umaskini, ujinga,magonjwa na dhuluma. (4) Rushwa ni adui wa haki, sitapokea wala kutoa rushwa. (5) Cheo ni dhamana, sitatumia cheo changu wala cha mtu mwingine kwa faida yangu. (6) Nitajielimisha kwa kadri ya uwezo wangu na kuitumia elimu yangu kwa faida ya wote. (7) Nitashirikiana na wenzangu wote kujenga nchi yetu. (8) Nitasema kweli daima, fitina kwangu mwiko. (9) Nitakuwa mwanachama mwaminifu wa CCM na raia mwema wa Tanzania na Afrika. 141. Madiwani wote wanaotokana na CCM kwa pamoja watakuwa Kamati ya Madiwani wa CCM ambayo kazi yake itakuwa ni kusimamia kwa jumla utekelezaji wa ilani zinazotekelezwa na Halmashauri za Wilaya, pamoja na kutekeleza kazi nyingine ambazo zimeainishwa katika kanuni zake.Vikao vya Kamati hii vitafanyika kwa mujibu wa Kanuni zake zinazohusika. Kwa upande wa Wilaya za Zanzibar, kwa kuwa Wilaya hizo zina Wabunge wengi pamoja na Wawakilishi wengi wanaotokana na CCM wanaowakilisha Majimbo ya Uchaguzi yaliyomo katika Wilaya husika, pamoja na Wabunge na Wawakilishi wa aina nyingine wanaoishi katika Wilaya hizo, utaratibu utakuwa kwamba Wabunge wanaohusika watachagua wajumbe wawili kutoka miongoni mwao, na Wawakilishi wanaohusika pia watachagua wajumbe wawili kutoka miongoni mwao, ambao ndio watakuwa Wajumbe wa Kamati ya Madiwani wote wa CCM katika Halmashauri inayohusika. 142. Madiwani wote wanaoishi katika Jiji au Mji wenye hadhi ya Jiji wanaotokana na CCM kwa pamoja watakuwa ni Kamati ya Madiwani wa CCM ya Mkoa katika Jiji au Mji unaohusika. Kazi yake itakuwa ni kusimamia kwa jumla utekelezaji wa Ilani ya CCM na Siasa ya CCM katika shughuli zote zinazoendeshwa na Halmashauri ya Jiji au Halmashauri ya Mji wenye hadhi ya Jiji, pamoja na kutekeleza kazi nyingine ambazo zimeainishwa katika kanuni zake zinazohusika. Kamati ya Madiwani wa CCM Katiba ya Chama Cha Mapinduzi 144 NYONGEZA “B” Katiba, Kanuni na Taratibu za utekelezaji zilizotungwa katika kuongoza shughuli mbalimbali za CCM ni hizi zifuatazo: (1) Taratibu za Sehemu ya Wazee. (2) Kanuni za Uchaguzi wa CCM. (3) Kanuni za Utendaji kazi za Uongozi katika Chama Cha Mapinduzi. (4) Kanuni za Fedha na Mali za Chama. (5) Kanuni za Umoja wa Vijana wa CCM. (6) Katiba ya Umoja wa Wanawake wa Tanzania. (7) Kanuni za Umoja wa Wazazi. (8) Kanuni za Uongozi na Maadili. (9) Kanuni za Uteuzi wa Wagombea Uongozi katika Vyombo vya Dola. (10) Kanuni za Kamati ya Wabunge wote wa CCM. (11) Kanuni za Wajumbe wa Baraza la Wawakilishi wote wa CCM. (12) Kanuni za Madiwani wote wa CCM. (13) Kanuni za Utumishi wa Chama Cha Mapinduzi. (14) Kanuni za Tume ya Udhibiti na Nidhamu. | false |
# Extracted Content KIBONDO DISTRICT COUNCIL District Executive Director Office, P.o Box 43, KIBONDO. Tel. 028-2820084 Fax. 028-2820473 Ref. P/DASIP/VOL.III/18 Agricultural Department, P.o Box 9, KIBONDO. Tel. 028-2820287 District Agricultural Sector Investment Project (DASIP) SEMI-ANNUAL REPORT JULY – DECEMBER, 2008/2009 2 List of abbreviations DASIP District Agriculture Sector Investment Project FFS Farmer Field School PFG Participatory Farmer Group FP Farmer Practice VADP Village agriculture development Plans PCU Project Coordinating Unity FCB Farmers Capacity Building CP Community Planning FF’s Farmers Facilitators BOQ Bill of Quantities KIWOSA Kibondo Women SACCOS O & OD Opportunity and Obstacle for Development July – December DASIP progress report 2008/09 KIBONDO DISTRICT Introduction This report gives the status of project implementation of the past six(6) months from July 2008 to December 2008. The report starts by listing the activities carried out in the period and goes on giving both physical and financial status of their respective implementation. It should be noted that activities done so far includes implementation of the carried over activities from the fourth quarter of financial year 2007/2008. The report also explains the performance of the FFS`s for the past cropping season by comparing yields under FP and IPPM and all the important information from FFS`s. The component of monitoring and evaluation/verification of the planned activities were carried out in all DASIP target villages in the district. At the end, the report cites problems encountered during the period. These quarters verification of implementation of the past and activities plans for the financial year 2008/2009 was conducted under field appraisal, which was carried by PCU staff in collaboration with district DASIP staff and the beneficiaries. - 3 - - 4 - 2.0 Plan and implementation status 2.1 Farmers capacity building • Senstization and formation of six more PFG’s for each village under DASIP. 135 PFG’s out of 180 target in 2008/ 2009 have been formed. • Trainig of farmer facilitators. 28 FF’s out of 30 targeted have received train on the major principles of crops and livestock production. • Distribution of agricultural inputs/training materials to villages under DASIP. 135 PFG’s formed 2008/2009 have been supplied 2.2 Community planning and investment Table 1. Community investments 2006/2007/2008: FUNDS ISSUED 2006/2007/2008Tsh. (000 ) WARD VILLAGE PROJECT NAME BENEF. DASIP TOTAL IMPLEMENTA TION STATUS REMARKS Kibondo Kibondo Rehabilitation of rural feeder road. 2,400 9,600 12,000 Completed Kibondo Kibondo Rice mill & Flour packaging machine. 5,000 5,000 10,000 Co-funded and procurement process begin Co-funded by KIWOSA and DASIP after the former Kabwigwa Women Association failed to do so. Misezero Twabagondo zi Construction of 4 box culverts for rural feeder road 2,400 9,600 12,000 Completed Misezero Twabagondo zi Construction of rural feeder road 1,600 6,400 8,000 BOQ prepared Due to delayed opening Bank A/C Misezero Twabagondo zi Construction of Cattle dip 3,000 12,000 15,000 At initial stage of implementation (Construction) Due to delayed opening Bank A/C Busagara Kasaka Rehabilitation of a Cattle dip 1,340 5,360 6,700 Completed Muhange Muhange Coffee pulpier machine- MUCUPA 5,000 5,000 10,000 Co-funded and it is at procurement stage Due to delayed opening Bank A/C - 5 - Kasanda Kasanda Rehabilitation of rural feeder road 1,200 4,800 6,000 BOQ prepared and it is at tender stage Due to delayed opening Bank A/C Kasanda Kasanda Construction of Cattle dip 3,000 12,000 15,000 Construction is at 80% of implementation Due to delayed opening Bank A/C Kasuga Kinonko Rehabilitation of rural feeder road at Katengera Irrigation scheme 800 3,200 4,000 Tender processing Due to delayed opening Bank A/C Rugongwe Kichananga Rehabilitation of rural feeder road 5,800 23,200 29,000 Tender processing Due to delayed opening Bank A/C Nyabibuye Nyabibuye Construction of a Slaughter slab 800 3,200 4,000 Completed Gwanumpu Bukirilo Construction of a Slaughter slab 800 3,200 4,000 Tender processing Due to delayed opening Bank A/C 33,140 102,560 135,700 - 6 - - 7 - Table 2. Community investments 2008/2009: WARD VILLAGE NAME OF PROJECT BEN.CONTR. TSHS.`000’ DASIP FUNDS TSHS.`000’ TOTAL TSHS.`000” IMPLEMENTATION STATUS REMARKS 1 Kibondo Kibondo Rural feeder road 3,680 14,720 18,400 Transfer of money to respective project a/c Compliance delay of VADP action plan to district head quarter 2 Gwanumpu Bukirilo Rural feeder road 5,000 20,000 25,000 Transfer of money to respective project a/c Compliance delay of VADP action plan to district 3 Itaba Kigogo Crop storage facility 6,900 27,600 34,500 Transfer of money to respective project a/c Compliance delay of VADP action plan to district 4 Kakonko Kanyonza Rural feeder road 5,600 22,400 28,000 Transfer of money to respective project a/c Compliance delay of VADP action plan to district 5 Kakonko Kabingo Rural feeder road 5,020 20,080 25,100 At BOQ stage Compliance delay of VADP action plan to district 6 Kakonko Itumbiko Rural feeder road 3,000 12,000 15,000 At BOQ stage Compliance delay of VADP action plan to district 7 Nyamtukuza Churazo Crop storage facility 6,900 27,600 34,500 Transfer of money to respective project a/c Compliance delay of VADP action plan to district TOTAL 36,100 144,400 180,500 - 8 - 3.0 Training of DASIP stakeholders There was no any training conducted to DASIP staff on first quarter. However, the Project Officers, the District Agriculture and livestock Development Officers, The District Planning Officers and the District Executive Directors from all 28 districts implementing DASIP had a workshop in Mwanza. The objective of the workshop was to review the performance of DASIP in the project area for the past two years. They reviewed the performance and find solution to those problems which seemed to be common in the project area in hindering effective implementation of the project. At the end strategies to improve and fasten the speed of implementation were put. On the second quarter training of farmers facilitators were conducted, 28 FF’s from 28 villages under DASIP project were involved. 4.0 Supervision Supervision activities carried were to monitor and to verify the implementation of the above-mentioned projects. Project beneficiaries were advised open bank accounts, forming six more PFG`s and their respective selected farming enterprises for each village under the DASIP project, handing over of their business/project plans attached with the minutes to the DASIP district head quarter for further action before disbursement this project financial year. The Training Project Coordinator from PCU recommended on these during his visit in the district at the end of this first quarter. 5.0 Out put results so far achieved 5.1 Farmers capacity building • Farmers have shown greater interest in farmers’ field school, extension methodology. They have recognized that, training through FFS have more impact than the previous approach. Learning by doing sticks more, and is easier to practice the skills to their field. The Umoja PFG - 9 - of Kichananga village under FFS succeeded to produce and yield 336 Kgs of groundnuts alongside the 180 Kgs under prior farmers practices. Tumaini PFG of Kigogo village under FFS also succeeded to produce and yield 15 bags of maize grains alongside the 3 bags under prior farmers practices. Maendeleo PFG of Mugunzu village under FFS also succeeded to produce and yield 14 bags of maize grains alongside the 3 bags under prior farmers practices. 5.2 Community planning investment • Completion of Rehabilitation of rural feeder road at Kibondo village. There after, accessibility to and from Twabagondozi-Kilalangona have been made easier to be accessible throughout a year by project beneficiaries and other stakeholders in agricultural sector. • Construction of box culverts for rural feeder road also completed. This has made the feeder road free from been damaged by randomly running water across the feeder road. 5.3 Lesson learned and experience gained • Village leaders show more commitment in project activities if facilitated (trained in project management as well as monitoring and evaluation). • Farmers have appreciated FFS methodology as a means of disseminating knowledge to them. They said it is an enjoyable, funny methodology especially when referring to AESA 6.0 Project to date 6.1 Farmers capacity building • The total of 43 PFG’s formed last financial year (2007/2008) having a total of 978 farmers of which 568 be males and 410 be females have been trained on the major principles of some different crops through FFS’s accordingly. • PFG’s in each village under the DASIP project for 2008/2009 financial year have been done, so far 135 out 180 FPG’s targeted have been formed. • 28 FF’s out of 30 have been trained on the major principles of crop and livestock production. - 10 - 6.2 Community planning and investments • Among 13 micro projects for 2006/2007/2008, 4 have been completed and 9 at different levels of implementation not yet completed as described on table 1 above. • In this 2008/2009 financial year, 7 village micro projects under DASIP have been planed and financed as shown in table 2 above. Below is a success story from Kibondo village, regarding the Rehabilitated Farm access road about 10 Km. Kibondo village is among the four villages of Kibondo ward. The village is important for various economic activities such as Food crops production. Most of these activities to the large extent are carried out faraway distance (North-east) from the Village head quarter. According to Mzee Hamisi Omari who is a resident of Kibondo village and is among farmers working at Kilalangona area, said that “Before rehabilitation of the farm access road in the village, accessibility to and from the production area was difficult due to water logging along the way especially during rainy season which made transportation cost of the agricultural produce to be relatively high because initially it was not possible to hire a motor car to carry the products and instead the product was been carried by using human power, which generally was expensive and also too laborious compared to nowadays where the products are easily carried by motor cars”. He continued to explain that “Time spent to reach to the farm has been reduced since the road has made a short cut resulting into increased working time and hence working area and production. After completion of feeder road, accessibility to and from the field has became easier and throughout the year. We give much thanks to the project, donor and Tanzania government as a whole”. Mzee Hamisi Omari ended that. - 11 - 7.0 Financial status of budget and disbursement 2008/2009 7.0 Financial status of budget and disbursement 2008/2009 In these 1st two quarters the money transferred into Kibondo DASIP account was meant for, as described in the table below:- In these 1 Kibondo – Kilalangona road after completion of rehabilitation. . Farm products are nowadays easily carried by motorcars st two quarters the money transferred into Kibondo DASIP account was meant for, as described in the table below:- SN Amount disbursed Activity Expenditure Balance Remarks 1. 24,000,000.00 Mini -projects of participatory farmer groups 11,200,000.00 12,800,000.00 Delay in opening bank a/c- Activity is going on 2. 90,000,000.00 Season long Training of PFG’s 5,602,400.00 84,397,600.00 Activity is going on 3. 2,300,000.00 PFG’s formation for 2008/2009 2,300,000.00 Nil 4. 1,800,000.00 Motorcycle allowances 1,800,000.00 Nil 5. 1,350,000.00 Office operation & maintenance costs- FCB&CP 640,000.00 710,000.00 On going activity 6. 5,025,000.00 District Staff field allowances 280,000.00 4,745,000.00 On going activity 7. 144,400,000.00 Village Micro Project implementation 144,400,000.00 Nil 8. 10,042,000.00 Training Farmer Facilitators(FF’s) 5,102,000.00 4,940,000.00 Activity is going on Total 278,917,000.00 171,324,400.00 107,592,600.00 - 12 - Table 3: Summary of disbursement and expenditure of funds Source: Disbursement record and expenditure report 2008/2009 8.0 Problems and Challenges The following are the challenges/problems so far encountered. Most farmers have low purchasing power the fact that makes them unable to budgets for their farms in the aspect of farm inputs. This made most farmers fail to apply what they learned from FFS in 2007/2008 cropping season. However, they have taken this as a challenge and promised to budget for the farm inputs ready to practice the skill they acquired in FFS in this 2008/2009 cropping season. Transport for execution of project activities is still a problem despite the fact that project staffs have been provided with motorcycles. When there is a need to travel as a team the vehicle is highly needed, since we some time need to work as a team with other staffs like, engineers, community development staffs, cooperative officers etc. The procurement procedures take so long time, the fact that leads/contributes to delayed implementation of planned activities. Most farmers have low income in such that can not afford to organize themselves and ask for 50% Co-funding Micro projects as a DASIP precondition. Inflation has interfered with DASIP budgets- rapid raise of farming inputs e.g. Pesticides/ insecticides, fertilizers and building/ construction materials e.g. Cements. 9.0 Way Forward • To emphasize training and community sensitization so that they can contribute where required and implement their activity planned. • To facilitate capacity building training to all stakeholders for project sustainability. • To base on contract, efficiency and time specific to complete implementation of planned activities for 2007/2008 and 2008/2009 financial years. • To carry on monitoring and evaluation of project activities. 10.0 Recommendation • We recommend the money provided as motorcycle maintenance and fuel allowance to be increased from the current seventy five thousand per month to one hundred fifty thousand due to the fact that, the cost of maintenance as well as the price of fuel increases. The fund allocated as field allowance for staff doubled the current amount. This is because the execution of DASIP activities needs multi-disciplinary technocrats (i.e. engineers, technicians, cooperative officers, etc.) of which the current budget cannot suffice. • Since that most of the farming enterprises especially crop productions are seasonal, timely need and rain fed, if possible procurement procedures for DASIP activities implementation to be revised by PCU. • The 50% Co-funding precondition to be revised at least to be 20%. 11.0 Conclusion Provision of vehicles to the districts under DASIP, reviewing of some preconditions and procurement procedures may increase the adoption and efficiency rates of Implementation of DASIP activities plans. The district has planned to do much better on implementation and supervision of the ongoing village micro projects for the past as well as this financial year. On top of that, monitoring and evaluation for the project activities need to be of paramount importance to charter for efficiency, effective, economical and timely implementation of the planned activities. 14 | false |
# Extracted Content KIGOMA DISTRICT COUNCIL DASIP IMPLEMENTENTION REPORT 4th Quarter 2010 District Executive Director Kigoma District Council P.O.Box 332, Fax Tel KIGOMA INTRODUCTION AND BACK GROUND INFORMATION Kigoma District Council (KDC) is among 28 district councils funded by The District Agriculture Sector Investment Project (DASIP). The objective of the project is mainly crop productivity and income enhancement to rural farming community. The Project covers 30 villages in 22 wards in the district. At the district level the project has three main components namely:- (i) Farmer’s capacity building component. (ii) Community planning and investment in Agriculture component. (iii) Support to Rural Financial Services and Agriculture Marketing component (Not yet started). This report explains progress made, component-wise, including carried over activities of FY 2008/2009 up to the end of the 3nd quarter (March 31st, 2010 of FY 2009/10). The report winds up by summarizing problems and challenges and ways of addressing them. PROJECT IMPLEMENTATION STATUS 1. Physical status 1.1 Farmers Capacity building component. Under this component, major activity planned for this quarter were • Facilitation of PFGs in opening bank account for implementing economic mini-projects and criteria of selection of those projects. • Monitoring of PFGs under seasonal long training. 1.2 Community planning and Investment in Agriculture The plan during the period under review was to finalize implementation of carried over activities FY2008/09 and first quarter activities FY 2009/10. Carried over activities include:- Construction of eight (8) market shades at Nyarubanda, Nyangabo, Msimba, Ilagala, Matendo, Kaparamsenga, Igalula and Sibwesa villages. Construction of livestock market at Chagu village. Planned activities for the first quarter FY 2009/10 were:- • Construction of five (5) market shades at Chakulu, Mgaraganza, Mgambazi, Buhingu and Kashagulu villages. • Rehabilitation of rural feeder roads (15 km) at Kidahwe and Kasisi villages. • To construct one (1) cattle dip tank at Kaseke village. • To construct (1) farm road bridge at Nkonkwa village. • To construct (1) bore hole at Itebula village. • Monitoring and supervision of village/group micro projects. 2.0 IMPLEMENTATION STATUS FOR ACTIVITIES UNDER FARMER CAPACITY BUILDING AND COMMUNITY PLANNING AND INVESTMENT • Training of 13 District Facilitators Team (DFT), 10 district staff and 30 WAEO on DADP planning and implementation for the 2010/2011. 2.1 Community planning and Investment in Agriculture implementation status 2.1.1 Carried over activities FY 2007/08 and 2008/09 (i) Improvement of market infrastructures. Under the improvement of market infrastructures achievements made so far includes three market shades at Kaparamsenga, Msimba, Matendo, Nyarubanda and Ilagala villages have been constructed (100% completed). Nyangabo and Igalula market shade is in the roofing stage (making; 85% completed). Cattle market at Chagu village is in the finishing stage of plastering of collection yards, market office and toilets (85%). 2.2 Implementation status of planned First quarter activities FY 2009/2010 • Construction of five market shades at Chakulu, Mgaraganza, Mgambazi, Buhingu and Kashagulu villages • Rehabilitation of rural feeder roads (15 km) at Kidahwe and Kasisi villages. • To construct one (1) cattle dip tank at Kaseke village • To construct (1) farm road bridge at Nkonkwa village • To construct (1) bore hole at Itebula village Implementation status as up to June 2010 (Attached). 2.3 Support to rural financial services and marketing Training of Cooperative Officer for rural financing within the DASIP village was conducted in Shinyanga. 3.0 FINANCIAL STATUS 3.1 Funds received For the 2009/2010 financial year Kigoma District Council has received a total amount of Tshs. 425,445,000/=/= as a budget for the following activities:- Farmers Capacity building component (i) Formation of 180 PFGs……………………Tshs. 4,300,000 /= (ii) Training of 29 Ward Training Facilitators and 30 Farmer Training Facilitors………………………................Tshs. 11,143,000/= (iii) Expenditure for DASIP activities….….Tshs. 17,390,000/= Community planning and Investment in Agriculture (i) Village Micro-projects………………….Tsh. 265,012,000/= (ii) DADP planning and implementation….Tsh. 8,200,000/= (iii) Investment in 148 2008/09 PGFs……….Tsh. 59,200,000/= (iv) Agro technology…………………………Tsh. 60,200,000/= Grand total …………………………. Tshs. 425,445,000/= 3.2 Funds spent as at 30th June, 2010 See attached DASIP consolidated/cashbook analysis. 4.0 PROBLEMS AND CHALLENGES (ISSUES AND CONSTRAINTS) • Slow pace of community in mobilizing local building materials for construction activities for both community and group investments. • Slow pace of project supervision communities and groups in opening bank project accounts for quick implementation of micro projects funded by DASIP. • Presence of many socio economic activities such as construction of Dispensaries, secondary schools infrastructures etc which requires community contributions. • Limited fund for supervision of project which especially villages along lake Tanganyika. • Increase in price of the industrial products such as cement, iron bars coffee pulper • Lack of road communication with wards in the East of the district as result of flooding at Malagarasi valley 5.0 REMEDIAL ACTIONS • To continue sensitize community on the importance of adherence to work plans and enforcement of village by-Laws to laxity community members. • To continue on educating the community on the importance of implementing their projects within the planed time frame. KIGOMA DISTRICT COUNCIL COMMUNITY PROJECT IMPLEMENTATION STATUS AS AT END OF JUNE 2010 KIGOMA RURAL DISTRICT FUNDS ISSUED 2006/07/08/09/10 IMPLEMENTATION STATUS No WARD VILLAGE PROJECT NAME BEN. DASIP TOTAL complete on going not started Remarks 1 Uvinza Basanza Construction of a market shed 7,000 28,000 35,000 Chakulu Construction of a market shed 7,000 28,000 35,000 Tender re-advertised 2 Nguruka Itebula Completion of a cattle dip construction 600 3,000 3,600 Construction of bore hole for irrigation 6,250 25,000 31,250 Under tender process Nyangabo Construction of a crop marketing shed 7,000 28,000 35,000 3 Ilagala Ilagala Construction of a matket shed. 7,000 28,000 35,000 Cereal processing machine 1,800 7,200 9,000 The farmer/group have already been informed and their cheque is raedy Mwakizega Rehabilitation of rural feeder road . 2,795 11,180 13,975 The community demanded construction of market and not feeder road. We have already sent a request of 16,820,000/= as an additional fund for market shed construction Cereal processing machine 1,800 7,200 9,000 The farmer/group have already been informed and their cheque is raedy 4 Kalinzi Mkabogo Construction of a coffee washing station 2,800 11,200 14,000 The fund is not enough for purchase of washing wachine. The additional funds Tsh. 16,800,000/= is still needed 5 Kalya Sibwesa Oxen drawn implements 1,000 1,000 2,000 Construction of a market shed. 7,000 28,000 35,000 Kashagulu Construction of a market shed. 7,000 28,000 35,000 6 Matendo Matendo Construction of a matket shed. 7,000 28,000 35,000 Cereal processing machine 1,800 7,200 9,000 The farmer / group have already been informed . Kidahwe Rehabilitation of rural feeder road . 7,000 28,000 35,000 Cereal processing machine 1,800 7,200 9,000 The farmer/group have already been informed. 7 Mganza Malagarasi Oxen drawn implements 1,000 1,000 2,000 Construction of slaughter slab 720 2,880 3,600 Environmental conservation 345 1,381 1,726 Cereal processing machine 1,750 7,000 9,000 The farmer/group have already been informed. Kasisi Rehabilitation of rural feeder road . 7,000 28,000 35,000 8 Sunuka Sunuka Construction of a matket shed. 7,000 28,000 35,000 Cereal processing machine 1,800 7,200 9,000 The farmer/group have already been informed. 9 Igalula Igalula Construction of a matket shed. 7,000 28,000 35,000 Mgambazi Construction of a matket shed. 7,000 28,000 35,000 Render re-advertised 10 Sigunga Kaparamsenga Construction of a matket shed. 7,000 28,000 35,000 Kernel processing machine 1,250 5,000 6,125 The funds have already been deposited in group/farmers account. 11 Bitale Nyamhoza Rehabilitation of rural feeder road . 7,000 28,000 35,000 12 Kandaga Mlela Rehabilitation of rural feeder road . 7,000 28,000 35,000 Cereal processing machine 1,800 7,200 9,000 The farmer/group have already been informed. Kandaga Rehabilitation of rural feeder road . 7,000 28,000 35,000 Purchase of a cereals processing machine 3,500 3,500 7,000 13 Mtegowanoti Chagu Construction of a cattle market. 7,000 28,000 35,000 14 Mkigo Nyarubanda Construction of a crop marketing shed 7,000 28,000 35,000 15 Mungonya Msimba Construction of a matket shed. 7,000 28,000 35,000 Rehabilitation of rural feeder road . 1,747 6,988 8,735 The fund was re-allocated to Kasisi and Kidahwe community projects according to your letter with Ref.No. DASIP/PC/KIG/DC/09/16 of 18 August, 2009 16 Simbo Kaseke Construction of a cattle dip. 5,750 23,000 28,750 Nyamori Rehabilitation of rural feeder road . 3,494 13,976 17,470 The community demanded construction of market and not feeder road. We have already sent a request of 14,024,000/= as an additional fund for market shed construction 17 Buhingu Nkonkwa Purchase of a kernel processing machine 5,000 5,000 10,000 Nkonkwa Rehabilitation of rural feeder road . 7,000 28,000 35,000 Buhingu Construction of a matket shed. 7,000 28,000 35,000 Tender re- advertised Oil palm processsing machine 1,250 5,000 6,125 The farmer/group have already been informed. 18 Mwandiga Kibingo Construction of a crop marketing shed 7,000 28,000 35,000 19 Mahembe Nkungwe Rehabilitation of rural feeder road . 7,000 28,000 35,000 Under tender process 20 Kagongo Mgaraganza Construction of a crop marketing shed 7,000 28,000 35,000 Evaluation process TOTAL KIGOMA DISTRICT 218,051 841,305 1,059,356 | false |
# Extracted Content SOURCES OF FUNDS DASIP BENEFICIARY KASULU BUHORO BUHORO Construction of a market shed. 35,000 28,000 7,000 KASUKU MJINI KUMSENGAMurubona Construction of a market shed. 35,000 28,000 7,000 RUNGWE MPYA ASANTE NYERERE Construction of a market shed. 35,000 28,000 7,000 RUSESA RUSESA Construction of a market shed. 35,000 28,000 7,000 TITYE SHUNGULIBA Construction of a market shed. 35,000 28,000 7,000 175,000 140,000 35,000 KIBONDO Kibondo Kibondo Rehabilitation of rural feeder roads 18,400 14,720 3,680 Gwanumpu Bukililo Rehabilitation of rural feeder roads 25,000 20,000 5,000 Itaba Kigogo Construction of a crop storage facility 34,500 27,600 6,900 Kakonko Kanyonza Rehabilitation of rural feeder roads 28,000 22,400 5,600 Kakonko Kabingo Rehabilitation of rural feeder roads 25,100 20,080 5,020 Kakonko Itumbiko Rehabilitation of rural feeder roads 15,000 12,000 3,000 Nyamtukuza Churazo Construction of a crop storage facility 34,500 27,600 6,900 180,500 144,400 36,100 KIGOMA BITALE NYAMHOZA Rehabilitation of rural feeder road . 35,000 28,000 7,000 KANDAGA MLELA Rehabilitation of rural feeder road . 35,000 28,000 7,000 MTEGOWANOTI CHAGU Construction of a cattle market. 35,000 28,000 7,000 MKIGO NYARUBANDA Construction of a crop marketing shed 35,000 28,000 7,000 NGURUKA NYANGABO Construction of a crop marketing shed 35,000 28,000 7,000 Mungonya Msimba Construction of a matket shed. 35,000 28,000 7,000 210,000 168,000 42,000 565,500 452,400 113,100 TOTAL COST (in '000) DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ALLOCATION OF INVESTMENT FUNDS - 1st QRT 2008/09 KAGERA , SHINYANGA, MARA, KIGOMA AND MWANZA REGIONS KIGOMA REGION DISTRICT WARD VILLAGE NAME OF PROJECT TOTAL KASULU DISTRICT TOTAL KIBONDO DISTRICT TOTAL KIGOMA DISTRICT TOTAL KIGOMA REGION | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vp: REGIONAL REPORT: 1 National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vp: REGIONAL REPORT:KIGOMA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 ACRONYMS ________________________________________________________________________________________________________________________ i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms ......................................................................................................................................................................... v Preface..............................................................................................................................................................................vi Executive summary........................................................................................................................................................ vii Illustrations.................................................................................................................................................................... xiv CENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 1 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period.............................................................................................................................................. 5 2.6 Census Methodology ....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 6 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 6 2.6.5 Field Pre-Testing of the Census Instruments ..................................................................................... 6 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 6 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 6 2.6.8 Household Listing............................................................................................................................... 7 2.6.9 Data Collection ................................................................................................................................... 7 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 7 2.6.11 Data Processing................................................................................................................................... 8 - Manual Editing.............................................................................................................................. 8 - Data Entry ..................................................................................................................................... 8 - Data Structure Formatting ............................................................................................................ 8 - Batch Validation ........................................................................................................................... 8 - Tabulations.....................................................................................................................................8 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality.................................................................................................................................. 9 2.7 Funding Arrangements............................................................................................................................. 9 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 10 3.1 Household Characteristics............................................................................................................................ 10 3.1.1 Type of Household ........................................................................................................................... 10 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number and age of Household Members......................................................................................... 11 3.1.5 Level of Education............................................................................................................................ 11 - Literacy ....................................................................................................................................... 11 - Literacy Level for Household Members .................................................................................... 15 - Literacy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 15 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 17 ACRONYMS ________________________________________________________________________________________________________________________ ii 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance ............................................................................................................................... 19 3.3.3 Crop Types........................................................................................................................................ 19 3.3.4 Cereal Crop Production .................................................................................................................... 20 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 25 3.3.4.3 Other Cereals...................................................................................................................25 3.3.5 Roots and Tuber Crops Production .................................................................................................. 27 3.3.5.1 Cassava ........................................................................................................................... 28 3.3.5.2 Sweet Potatoes................................................................................................................ 28 3.3.6 Pulse Crops Production .................................................................................................................... 31 3.3.6.1 Beans............................................................................................................................... 32 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts ..................................................................................................................... 34 3.3.8 Fruits and Vegetables ........................................................................................................................36 3.3.8.1 Tomatoes......................................................................................................................... 37 3.3.8.2 Cabbage .......................................................................................................................... 37 3.3.8.3 Chilies............................................................................................................................. 40 3.3.9 Other Annual Crop production..........................................................................................................40 3.3.9.1 Cotton ............................................................................................................................. 41 3.3.9.2 Tobacco........................................................................................................................... 41 3.4 Permanent Crops........................................................................................................................................... 41 3.4.1 Palm oil........................................................................................................................... 42 3.4.2 Orange............................................................................................................................. 42 3.4.3 Banana ............................................................................................................................ 43 3.4.4 Pigear pea ....................................................................................................................... 43 3.5 Inputs/Implements Use ................................................................................................................................. 45 3.5.1 Methods of Land Clearing.................................................................................................................45 3.5.2 Methods of Soil Preparation............................................................................................................. 45 3.5.3 Improved Seeds Use ......................................................................................................................... 46 3.5.4 Fertilizers Use................................................................................................................................... 47 3.5.4.1 Farm Yard Manure Use.................................................................................................. 49 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 50 3.5.4.3 Compost Use................................................................................................................... 51 3.5.5 Pesticide Use..................................................................................................................................... 52 3.5.5.1 Insecticide Use............................................................................................................... 52 3.5.5.2 Herbicide Use ................................................................................................................ 54 3.5.5.3 Fungicide Use................................................................................................................ 55 3.5.6 Harvesting Methods.......................................................................................................................... 55 3.5.7 Threshing Methods ..........................................................................................................................55 3.6 Irrigation .....................................................................................................................................................56 3.6.1 Area Planted with Annual Crops and Under Irrigation ................................................................... 56 3.6.2 Source of water used for Irrigation ................................................................................................. 57 3.6.3 Methods of obtaining water for Irrigation........................................................................................ 57 3.6.4 Methods of water for Application .................................................................................................... 57 3.7 Crop Storage, Processing and Marketing .................................................................................................. 58 3.7.1 Crop Storage ......................................................................................................................................58 3.7.1.1 Method of Storage.......................................................................................................... 58 ACRONYMS ________________________________________________________________________________________________________________________ iii 3.7.1.2 Duration of Storage ........................................................................................................ 59 3.7.1.3 Purpose of Storage.......................................................................................................... 59 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 59 3.7.2 Agro processing and By-products.....................................................................................................60 3.7.2.1 Processing Methods........................................................................................................ 60 3.7.2.2 Main Agro-processing Products..................................................................................... 61 3.7.2.3 Main use of primary processed Products....................................................................... 62 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 62 3.7.3 Crop Marketing................................................................................................................................. 63 3.7.3.1 Main Marketing Problems.............................................................................................. 63 3.7.3.2 Reasons for Not Selling.................................................................................................. 65 3.8 Access to Crop Production Services............................................................................................................ 65 3.8.1 Access to Agricultural Credits.......................................................................................................... 65 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits ............................................................................................ 66 3.8.1.3 Reasons for not using agricultural credits...................................................................... 66 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of Crop Extension Messages............................................................................ 67 3.8.2.2 Quality of Extension....................................................................................................... 67 3.9 Access to Inputs .............................................................................................................................................67 3.9.1 Use of Inputs .....................................................................................................................................67 3.9.2 Inorganic Fertilizers ..........................................................................................................................68 3.9.3 Improved Seeds..................................................................................................................................69 3.9.4 Insecticides and Fungicide ................................................................................................................69 3.10 Tree Planting...................................................................................................................................................70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 74 3.12.1 Cattle Production ..............................................................................................................................74 3.12.1.1 Cattle Population ............................................................................................................ 76 3.12.1.2 Herd size......................................................................................................................... 76 3.12.1.3 Cattle Population Trend ..................................................................................................76 3.12.1.4 Improved Cattle Breeds.................................................................................................. 76 3.12.2 Goat Production................................................................................................................................ 76 3.12.2.1 Goat Population.............................................................................................................. 76 3.12.2.2 Goat Herd Size ................................................................................................................77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 80 3.12.4 Pig Production................................................................................................................................... 80 3.12.4.1 Pig Population ................................................................................................................ 80 3.12.4.2 pig Population Trend...................................................................................................... 80 3.12.5 Chicken Production ...........................................................................................................................80 3.12.5.1 Chicken Population .........................................................................................................82 3.12.5.2 Chicken Population Trend.............................................................................................. 82 ACRONYMS ________________________________________________________________________________________________________________________ iv 3.12.5.3 Chicken Flock Size......................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers) .............................................................84 3.12.6 Other Livestock................................................................................................................................. 84 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 85 3.12.7.1 Deworming..................................................................................................................... 85 3.12.8 Access to Livestock Services ........................................................................................................... 85 3.12.8.1 Access to livestock extension Services.......................................................................... 85 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 86 3.12.8.3 Access to village watering points/dam .......................................................................... 86 3.12.9 Animal Contribution to Crop Production......................................................................................... 87 3.12.9.1 Use of Draft Power......................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure ..............................................................................................89 3.12.9.3 Use of Compost .............................................................................................................89 3.13 Fish Farming..................................................................................................................................... 89 3.14 Access to infrastructure and other services...................................................................................... 90 3.15 Poverty Indicators......................................................................................................................................... 90 3.15.1 Type of Toilets.................................................................................................................................. 90 3.15.2 Household’s Assets........................................................................................................................... 90 3.15.3 Sources of Light for Energy ............................................................................................................. 92 3.15.4 Sources of Energy for Cooking........................................................................................................ 92 3.15.5 Roofing Materials ............................................................................................................................. 93 3.15.6 Access to Drink Water...................................................................................................................... 93 3.15.7 Food Consumption Pattern............................................................................................................... 94 3.15.7.1 Number of Meals per Day.............................................................................................. 94 3.15.7.2 Meat Consumption Frequencies..................................................................................... 94 3.15.7.3 Fish Consumption Frequencies.......................................................................................95 3.15.8 Food Security.................................................................................................................................... 95 3.15.9 Main Source of Cash Income ........................................................................................................... 95 PART IV: KIGOMA PROFILES.............................................................................................................................. 99 4.1 Region Profile..................................................................................................................................................99 4.2 District Profiles.............................................................................................................................................100 4.2.1 Kibondo............................................................................................................................................100 4.2.2. Kasulu ..............................................................................................................................................101 4.2.3 Kigoma Rural...................................................................................................................................103 4.2.4 Kigoma Urban..................................................................................................................................104 ACRONYMS ________________________________________________________________________________________________________________________ v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department for International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ________________________________________________________________________________________________________________________ vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Kigoma region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Kigoma region who were selected using statistical sampling techniques. The results presented in this report do not cover urban areas and large-scale farmers. Highlighted are important findings regarding agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural and related activities and poverty in Kigoma region, the aim being to present an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural activities. i) Household Characteristics The number of agricultural households in Kigoma region was 195,756 out of which 135,655 (69.3%) were involved in growing crops only, 911 (0.5%) rearing livestock only, 160 (0.1%) were pastoralist and 59,040 (30.2%) were involved in crop production as well as livestock keeping. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, livestock keeping\ heading, off farm income, tree/forest resource, remittances and fishing\hunting & gathering. The region had a literacy rate of 66.8 percent. The highest literacy rate was in Kasulu district (69.0%) followed by Kibondo district (66.2%), Kigoma urban district (65.5%), and Kigoma rural have the lowest literacy rates of 64.9%. The literacy rate for the heads of households in the region was 69.9%. The number of heads of agricultural households with formal education in Kigoma region was 128,834 (65.8%), those without formal education were 59,307 (30.3%) and those with only adult education were 7,624 (3.9% percent). The majority of heads of agricultural households (63.9) percent had primary level education whereas only 0.4 percent had post primary education. In Kigoma region 93,401 households (71.9% of households with off-farm income) had each one household member engaged in off-farm income generating activities. Another 26,675 households (20.5%) had two household members engaged in off farm income generating activities and 9,848 households (7.6%) had each more than two members engaged in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 373,576 ha. The regional average land area utilised for crop production per crop growing household was only 1.3 ha. This figure was below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 264,9746 hectares out of which 145,143 hectares (54.5%) were planted during short rainy season and 119,831 hectares (45.4%) during long rainy season. An estimated area of 94,282 ha (35.6% of the total planted area with annual and vegetable crops) was planted with cereals, followed by 78,510 hectares (29.6%) of root and tubers, 77,848 ha (29.4%) of pulses, 11,202 ha (4.2 percent) of oil seeds and oil nuts, 12,039 ha (0.8%) of fruits & vegetables and 1,090 ha (0.4%) of cash crops. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ viii Maize Maize was the dominant annual crop grown in Kigoma region and it had a planted area 1.08 times greater than beens, which had the second largest planted area. The areas planted with maize constitute 31.7 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were cassava, groundnuts,paddy, sorghum, sweet potatoes and finger millet Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Kigoma region during the short rainy season was 11,298. This represented 6.1% of the total crop growing households in Kigoma Region in the short rainy season. Cassava The area planted with cassava was larger than any other root and tuber crop in Kigoma region in terms of planted area (28.7% of the total area planted with annual crops and vegetables) and it accounted for 97.0% of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 5,704 tonnes. The most cultivated fruit and vegetable crop was the tomatoe. The production for this crop was 3,208 tonnes, which accounted to 56.2% of the total fruits and vegetables production, followed by cabbage (1256 tonnes, 22.0%) and onion (238 tonnes, 12.6%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 42,852 hectares which was 12%t of the area planted with crops in the region. The most important permanent crop was banana which accounted for 47.8% of the total area planted with permanent crops followed by palm oil (24.0%) and mango (17.2%) Improved Seeds The planted area using improved seeds was 11,216 ha which represented 4.2 percent of the total area planted with annuals. The percentage use of improved seed in the short rainy season was 6.1 percent and higher than the corresponding percentage use for the long rainy season (2.0%). Use of Fertilizers Most annual crop growing households did not use any fertilisers. The area planted without fertilisers for annual crops was 107,921 hectares representing 74.4% of the total area planted with annual crops. Of the area planted with fertiliser application, farm yard manure was applied to 27,982 ha which represented 19.3% of the total planted area (77.4% of the area planted with fertiliser application). This was followed by compost (6,271 ha 4.3%) Inorganic fertilizers were used on a very small area and represented only 2.0 percent of the area planted with fertilizers. Irrigation In Kigoma region, the area of annual crops and vegetables under irrigation was 7,835 ha representing 3% of the total area planted. The area under irrigation during the short rainy season was 5,532 ha accounting for 2.1 percent of the total EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ ix area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 32.8% Crop Storage There were 186,533 crop growing households (95.8% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 172,631 households storing 18,093 tonnes as of 1st January 2004. This was followed by beans & pulses (162,195 households and 7,788 tonnes) Paddy (1,803 households and 1,389 tonnes), and ground nuts/bambara nuts (15,702 households and 712 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crops was 167,633 which represent 86.1% of the total number of crop growing households. The percent of crop growing households selling crops was highest in Kasulu (94%) followed by Kigoma rural (92%), Kigoma urban (87%), and Kibondo (65%). Agricultural Credit In Kigoma region, few agricultural households (3,403, 1.7%) accessed credit, out of which 3,211 (94%) were male- headed households and 192 (6%) were female headed households. In Kibondo and Kigoma rural only female headed households got credit for agriculture purposes, in Kasulu and Kigoma urban districts both male and female headed households’ accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 118,407 (61% of total crop growing households in the region). Some districts had more access to extension services than others (Chart 3.106). Kigoma urban district had a relatively high proportion of households that received crop extension messages (94.7%), followed by Kigoma rural (87.9%), Kibondo (47.0%) and Kasulu (46.6%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 19,370. This number represented 10% of the total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Kigoma rural district (13%) followed by Kasulu (9%), Kibondo (8%), and Kigoma urban (3%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 422,361. Cattle were the most dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.5 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 421,613 head (99.8% of the total number of cattle in the region), and 748 (0.2%) were dairy breeds. There were no beef breeds. Goats The number of goat-rearing households was 74,496 (38.6%) of all agricultural households) with a total of 425,604 goat giving an average of 6 heads of goats per goats-rearing household. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ x Sheep The number of sheep-rearing-households in the region was 12,111 (6.2 percent of all agricultural households) with a total of 51,805 sheep giving an average of 4 head of sheep per sheep-rearing-households. Pigs The number of pig-rearing households in the region was 5,221 (2.6 percent of the total agricultural households) rearing about 23,698 pigs. This gives an average of 5 pigs per pig-rearing household. Chicken The number of households keeping chickens was 81,952, raising 797,537 chickens. This gave an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Kigoma ranked eighteenth out of the 21 Mainland regions. • Use of Draft Power The region has 5,071 oxen and they were found in Kigoma rural. Kigoma region has 0.2 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 1,811 hectares of land. Fish Farming The number of households involved in fish farming was 193 (0.1 percent of the total agricultural households in the region). Kasulu was the only district with households involved in fish farming. iv) Poverty Indicators Availability of Toilets The results show that 94.5% of all rural agricultural households used traditional pit latrines, 0.6 percent used improved pit latrines and 2.1 percent had flush toilets. Households with no toilet facilities represented 2.8 percent of the total agriculture households in the region. Household Assets Out of all assets, the radio was the most common household assets and was owned by 58.5% of the households, followed by bicycle (44.4%), iron (12.0%), wheelbarrow (2.8%), mobile phone (0.6%), television/video (0.5%), and vehicle (0.3%) and there was no landline phone. Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 78.5 percent of the total rural households used this source of energy followed by hurricane lamp (12.0%), fire wood (5.0 percent), pressure lamp (4.2 percent), fire wood 5.0 percent, mains electricity (0.2%), , solar (0.1%), Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.0 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (3.0 percent). The rest of energy sources accounted for 0.7 percent. These were crop residues (0.5 percent), living dung (0.1 percent) and mains electricity (0.1) Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and was used by 61.5% of the rural agricultural households. It was followed by iron sheets (27.4%). Other roofing materials were grass/mud (8.0 percent), asbestos and concrete both had (0.5 percent), tiles (0.2 percent) and others (0.1 percent). EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xi Number of Meals per Day About 80.5% of the households in the region took two meals per day, 16% took two meals, 3.3 percent took one meal and 0.2 percent took four meals • Food Security Households which never had problems in satisfying their food needs represented 63.4% of the total number of agricultural households in the region. Households which often experienced problems represented 3.4 percent whereas those with little problems represented 7.6 percent. About 3.9 percent of the agricultural households always faced food shortages whilst 21.7%seldom experienced food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 64.7% of all rural agricultural households. The second main cash income earning activity was casual labour (9.5 percent) followed by selling of cash crops (5.3 percent), businesses (6.0 percent) and fishing (2.3 percent), cash and remittance (2.3 percent), other income earning activities were sales of livestock (1.8 percent), employment (9.3 percent) sale of forest products (2.7percent) and sale of livestock product (0.8 percent) EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .................................................................................................................................................. 5 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District....... 10 3.2 Area, Production and Yield of Cereal Crops by Season ........................................................................................ 20 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop........................................... 27 3.4 Area, Quantity Harvested and Yield of Pulses by Season ..................................................................................... 31 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season....................................................................... 34 3.6 Area, Production and Yield of Fruits and Vegetables by Season .......................................................................... 36 3.7 Area, Production and Yield of Annual Cash Crops by Season.............................................................................. 40 3.8 Land Clearing Methods........................................................................................................................................... 45 3.9 Number of Crop Growing Households and Planted Area (ha) by Type of Fertilizer Used and District DurintheLong Rainy Season ................................................................................................................................. 47 3.10 Number of Households Storing Crops by Estimated Storage Loss and District ................................................... 60 3.11 Reasons for Not Selling Crop Produce................................................................................................................... 65 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District ................... 65 3.13 Access to Inputs....................................................................................................................................................... 67 3.14 Total Number of Households and Chickens Raised by Flock Size ....................................................................... 82 3.15 Head Number of Other Livestock by Type of Livestock and District................................................................... 84 3.16 Mean Distances from Holders Dwellings to Infrastructures and Services by Districts ........................................ 90 3.17 Number of Households by Number of Meals the Household Normally Has per Day and District...................... 94 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings........................................................... 10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head................................................. 11 3.3 Percentage Distribution of Population by Age and Sex in 2003............................................................................ 11 3.4 Percentage Literates Level by District.................................................................................................................... 15 3.5 Literacy Rates of Heads of Household by Sex and District................................................................................... 15 3.6 Percentage of Person Aged 5 years and Above by District and Educational Status ............................................. 15 3.7 Percentage Distribution of Persons Aged 5 Years and Above in Agricultural Households by Education Status and District.................................................................................... 15 3.8 Percentage Distribution of Heads of Household by Educational Attainment........................................................ 16 3.9 Number of Households by Number of Members with Off-farm Activities........................................................... 16 3.10 Percentage Distribution of Agricultural Households by Number of Members with Off-farm Activities and District .............................................................................................................................................................. 16 3.11 Utilized and Usable Land per Household by District............................................................................................. 17 3.12 Percentage Distribution of Land Area by Type of Land Use................................................................................. 17 3.13 Area Planted with Annual Crops per household and Vegetables by Season........................................................ 18 3.14 Area Planted with Annual Crops (ha) by Season and District ............................................................................... 18 3.15 Area Planted with Annual Crops per household by Season and District............................................................... 18 3.16 Planted Area for the Main Annual Crops (ha)........................................................................................................ 19 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xiii 3.17 Planted Area (ha) per Household for Selected Crops............................................................................................. 19 3.18 Percentage Distribution of Area Planted with Annual Crops by Crop Type......................................................... 19 3.19 Area Planted with Annual Crops by Type of Crops and Season ........................................................................... 19 3.20 Area Planted and Yield of Major Cereal Crops...................................................................................................... 20 3.21 Maize: Total Area Planted and Planted Area per Household by District .............................................................. 23 3.22 Maize Production Trend as per Agriculture Censuses and Surveys ...................................................................... 23 3.23 Time Series of Maize Planted Area and yield ........................................................................................................ 23 3.24 Paddy: Total Area and Area of Paddy per Household by District ......................................................................... 25 3.25 Paddy: Production Trend as per Agriculture Censuses and Surveys.................................................................... 25 3.26 Time Series of Paddy Planted Area and Yield ....................................................................................................... 25 3.27 Area planted with Sorghum, Finger Millet and Wheat by District........................................................................ 25 3.28 Area Planted and Yield of Major Root and Tuber Crops....................................................................................... 27 3.29a Area Planted with Cassava during the Census/Survey Years ................................................................................ 27 3.29b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District........................................ 28 3.30 Cassava Planted Area per Cassava Growing Households by District.................................................................... 28 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District................................................ 28 3.32 Area Planted and Yield of Major Pulse Crops........................................................................................................ 31 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ................................................ 32 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only)............................................ 32 3.35 Time Series Data on Bean Production.................................................................................................................... 32 3.36 Time Series of Bean Planted Area and Yield......................................................................................................... 32 3.37 Area Planted and Yield of Major Oil Seed Crops .................................................................................................. 34 3.38 Time Series Data on Groundnuts Production......................................................................................................... 34 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District ........................... 34 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) ................................. 34 3.41 Area Planted and Yield of Fruits and Vegetables.................................................................................................. 36 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ........................................ 37 3.43 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) ...................................... 37 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ..................................... 37 3.45 Percent of Chilies Planted Area and Percent of Total Land with Chillies by District.......................................... 40 3.46 Area planted with Annual Cash Crops .................................................................................................................. 40 3.47 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District...................................... 41 3.48 Area Planted for Annual and Permanent Crops..................................................................................................... 41 3.49 Area Planted with the Main Permanent Crops ...................................................................................................... 41 3.50 Percent of Area Planted with Permanent crops and Average Planted Area per Household by District .............. 42 3.51 Percent of Area Planted with Coconuts and Average Planted Area per Household by District .......................... 42 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District .......................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District............................ 43 3.54 Percent of Area Planted with Bananas and Average Planted Area per Household by District............................ 43 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District..................... 45 3.56 Number of Households by Method of Land Clearing During the Long Rainy Season........................................ 45 3.57 Area Cultivated by Cultivation Method................................................................................................................. 46 3.58 Area Cultivated by Method of Cultivation and District........................................................................................ 46 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xiv 3.60 Area Planted with Improved Seed by Crop Type.................................................................................................. 46 3.59 Area Planted with Improved Seeds......................................................................................................................... 46 3.61 Percentage of Crop Type Area Planted with Improved Seed – Annuals.............................................................. 46 3.62 Area of Fertilizer Application by Type of Fertilizer ............................................................................................. 47 3.63 Area of Fertilizer Application by Type of Fertilizer and District ......................................................................... 47 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season........................................................ 49 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals ....................................................... 50 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District............................................................. 50 3.66 Planted Area with Inorganic fertilizers by Crop Type ......................................................................................... 50 3.67a Percentage of Planted Area with Inorganic Fertilizers by Crop Type– Annuals.................................................. 51 3.67b Proportion of Planted Area Applied with Inorganic Fertilizers by District........................................................... 51 3.68a Planted Area with Compost by Crop Type - Long Rainy Season......................................................................... 51 3.68b Percentage of Planted Area with Compost by Crop Type...................................................................................... 51 3.68c Proportion of Planted Area Applied with Compost by District ............................................................................. 52 3.69 Planted Area (ha) by Pesticide Use........................................................................................................................ 52 3.70 Planted Area Applied with Insecticides by Crop Type ......................................................................................... 52 3.71 Percentage of Crop Type Planted Area Applied with Insecticides....................................................................... 52 3.72 Percentage of Planted Area Applied with Insecticides by District ...................................................................... 54 3.73 Planted Area Applied with Herbicides by Crop Type........................................................................................... 54 3.74 Percentage of Crop Type Planted Area Applied with Herbicides......................................................................... 54 3.75 Proportion of Planted Area Applied with Herbicides by District ........................................................................ 54 3.76 Planted Area Applied with Fungicides by Crop Type........................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides.......................................................................... 55 3.78 Proportion of Planted Area Applied with Fungicides by District ........................................................................ 55 3.79 Area of Irrigated Land............................................................................................................................................ 56 3.80 Planted Area with Irrigation by District................................................................................................................ 56 3.81 Time Series OF Households with Irrigation........................................................................................................... 56 3.82 Number of Households with Irrigation by Source of Water ................................................................................. 57 3.83 Number of Households by Method of Obtaining Irrigation Water....................................................................... 57 3.84 Number of Households with Irrigation by Method of Field Application ............................................................. 57 3.85 Number of Households and Quantity Stored by Crop .......................................................................................... 58 3.86 Number of Households by Storage Method .......................................................................................................... 58 3.87 Number of Households by method of Storage and District (based on the most important household crop)....... 58 3.88 Normal Length of Storage for Selected Crops ...................................................................................................... 59 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ..................................................... 59 3.90 Number of Households by Purpose of Storage and Crop .................................................................................... 59 3.91a Households processing Crops ............................................................................................................................... 60 3.91b Households Processing Crops by District.............................................................................................................. 60 3.92 Percent of Crop Processing Households by Method of Processing...................................................................... 61 3.93 Number of Households by Type of Main Processed Product ............................................................................... 61 3.94 Number of Households by Type of By-product .................................................................................................... 61 3.95 Use of Processed Product....................................................................................................................................... 62 3.96 Percentage of Households Selling Processed Crops by District ........................................................................... 62 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xv 3.97 Location of Sale of Processed Products................................................................................................................. 62 3.98 Percent of Households Selling Processed Products by Outlet and District .......................................................... 63 3.99 Number of Crop Growing Households that selling Crops by District.................................................................. 63 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ...................... 63 3.101 Percentage Distribution of Households that Received Credit by Main Source.................................................... 65 3.102 Proportion of Households who Received Credits by Main Source of the Credit................................................. 65 3.103 Proportion of Households Receiving credit by Main Purpose of the Credit ......................................................... 66 3.104 Reason for nit Using Credit (%of Households)...................................................................................................... 66 3.105 Number of Households Receiving Extension Advice........................................................................................... 66 3.106 Number of Households Receiving Extension by District ..................................................................................... 66 3.107 Number of Households Receiving Extension by Quality of Service.................................................................... 67 3.108 Number of Households by Source of Inorganic Fertilizers.................................................................................... 68 3.109 Number of Households Reporting Distance to Source of Inorganic Fertilizers.................................................... 68 3.110 Number of Households by Source of Improved Seeds .......................................................................................... 68 3.111 Number of Households Reporting Distance to Source of Improved Seeds........................................................... 69 3.112 Number of Households by Source of Insecticides/Fungicides............................................................................... 68 3.113 Number of Households reporting Distance to Source of Insecticides/Fungicides ................................................ 69 3.114 Number of Households with Planted Trees............................................................................................................ 70 3.115 Number of Planted Trees by Species...................................................................................................................... 70 3.116 Number of Trees Planted by Smallholders by Species and District ...................................................................... 70 3.117 Number of Trees Planted by Location.................................................................................................................... 71 3.118 Number of Households by Purpose of Planted Trees............................................................................................. 71 3.119 Number of Households with Erosion Control/Water Harvesting Facilities ......................................................... 71 3.120 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District.............. 71 3.121 Number of Erosion Control/Water Harvesting Structures by Type of Facility.................................................... 74 3.122 Total Number of Cattle ('000') by District............................................................................................................. 74 3.123 Numbers of Cattle by Type and District................................................................................................................ 74 3.124 Cattle Population Trend ......................................................................................................................................... 76 3.125 Dairy Cattle Population Trend ............................................................................................................................... 76 3.126 Total Number of Goats ('000') by District............................................................................................................. 76 3.127 Goat Population Trend ........................................................................................................................................... 77 3.128 Total Number of Sheep by District........................................................................................................................ 77 3.129 Sheep Population Trend ......................................................................................................................................... 80 3.130 Total Number of Pigs by District........................................................................................................................... 80 3.131 Pig Population Trend.............................................................................................................................................. 80 3.132 Total Number of Chicken by District .................................................................................................................... 82 3.133 Chicken Population Trend...................................................................................................................................... 82 3.135 Layers Population Trend......................................................................................................................................... 84 3.134 Number of Improved Chicken by Breed Type and District.................................................................................. 84 3.136 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District......... 85 3.137 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District.............. 85 3.138 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........... 86 3.139 Number of Households by Distance to veterinary clinic ...................................................................................... 86 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xvi 3.140 Percentage of households by Distance to veterinary clinic and District............................................................... 86 3.141 Number of Households by Distance to Village Watering point............................................................................ 86 3.142 Number of Households by Distance to Village Watering point and District ....................................................... 87 3.143 Number of Households using Draft Animal.......................................................................................................... 87 3.144 Number of Households using Draft Animal by District........................................................................................ 87 3.145 Number of Households using organic Fertilizers................................................................................................. 89 3.146 Area of Application of organic Fertilizers by District........................................................................................... 89 3.147 Number of Households Practicing Fish Farming ................................................................................................ 89 3.148 Fish Productiono...................................................................................................................................................... 89 3.149 Percentage Distribution of Agricultural Households by type of Toilet ................................................................. 90 3.150 Percentage Distribution of Household Owning the Assets...................................................................................... 92 3.151 Percentage Distribution of Household by Main Source of Energy for lighting .................................................... 92 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking.................................................. 92 3.153 Percentage Distribution of Households by Type of Roofing Material................................................................... 93 3.154 Percentage Distribution of Households with Grass/ Leaves Roofs by District...................................................... 93 3.155 Percentage of Households by main source of Drinking water and season............................................................ 93 3.156 Percentage of Households Distance to Main Source of Drinking Water by Season .............................................. 93 3.157 Number of Households Agricultural by Number of Meals per Day ....................................................................... 94 3.158 Number of Households by Frequence of Meat and Fish Consuption .................................................................... 94 3.159 Percentage Distribution of the Number of Households by Main source of income .............................................. 95 List of Maps 3.1 Total Number of Agricultural Households by District........................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District............................................................. 12 3.3 Number of Crop Growing Households by District................................................................................................. 13 3.4 Percent of Crop Growing Households by District.................................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................... 14 3.6 Percent of Crop and Livestock Households by District ......................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ............................................................................. 21 3.8 Total Planted Area (annual crops) by District........................................................................................................ 21 3.9 Area planted and Percentage During the Short Rainy Season by District............................................................. 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District....................................... 22 3.11 Planted Area and Yield of Maize by District.......................................................................................................... 24 3.12 Area Planted per Maize Growing Household ........................................................................................................ 24 3.13 Planted Area and Yield of Paddy by District.......................................................................................................... 26 3.14 Area Planted per Paddy Growing Household ........................................................................................................ 26 3.15 Planted Area and Yield of Cassava by District ...................................................................................................... 29 3.16 Area Planted per Cassava Growing Household ..................................................................................................... 29 3.17 Planted Area and Yield of Sweet Potatoes by District........................................................................................... 30 3.18 Area Planted per Sweet Potatoes Growing Household ......................................................................................... 30 3.19 Planted Area and Yield of Beans by District.......................................................................................................... 33 3.20 Area Planted per Beans Growing Household ........................................................................................................ 33 3.21 Planted Area and Yield of Groundnuts by District................................................................................................. 35 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xvii 3.22 Area Planted per Groundnuts Growing Household ............................................................................................... 35 3.23 Planted Area and Yield of Tomatoes by District.................................................................................................... 38 3.24 Area Planted per Tomatoes Growing Household .................................................................................................. 38 3.25 Planted Area and Yield of Cabbage by District ..................................................................................................... 39 3.26 Area Planted per Cabbage Growing Household .................................................................................................... 39 3.27 Planted Area and Yield of Banana by District........................................................................................................ 44 3.28 Area Planted per Banana Growing Household ...................................................................................................... 44 3.29 Planted Area and Percent of Planted Area with Application of Fertilizer by District.......................................... 48 3.30 Area Planted and Percent of Total Planted Area with Irrigation by District ......................................................... 48 3.31 Planted Area and Percent of Planted Area with Farm Yard Manure application by District................................ 53 3.32 Planted Area and Percent of Planted Area with Compost application by District ................................................ 53 3.33 Percent of Hhd storeing crops 3-6 month by district.............................................................................................. 64 3.34 Number of Households and Percent of Total Households Selling Crops by District............................................ 64 3.35 Number of Households and Percent of Total Households Receiving Crop Extension Services by District ........ 72 3.36 Number and Percent crop growing hhdsusing improved seeds by district............................................................ 72 3.37 Number and percent of smallholder planted trees by district................................................................................. 73 3.38 Number and Percent of Households with water Harvesting Bunds by District..................................................... 73 3.39 Cattle population by District as of 1st Octobers 2003............................................................................................ 75 3.40 Cattle Density by District as of 1st October 2003.................................................................................................. 75 3.41 Goat population by District as of 1st Octobers 2003 ............................................................................................. 78 3.42 Goat Density by District as of 1st October 2003.................................................................................................... 78 3.43 Sheep population by District as of 1st Octobers 2003 ........................................................................................... 79 3.44 Sheep Density by District as of 1st October 2003.................................................................................................. 79 3.45 Pig population by District as of 1st Octobers 2003................................................................................................ 81 3.46 Pig Density by District as of 1st October 2003 ...................................................................................................... 81 3.47 Number of Chicken by District as of 1st October 2003......................................................................................... 83 3.48 Density of Chicken by District as of 1st October 2003.......................................................................................... 83 3.49 Number and Percent of Households Infected with Ticks by District..................................................................... 88 3.50 Number and Percent of Households Using Draft Animals by District.................................................................. 88 3.51 Number and Percent of Households Practicing Fish Farming by District............................................................. 91 3.52 Number and Percent of Households Without Toilets by District........................................................................... 91 3.53 Number and Percent of Households using grass/leaves for roofing material by District...................................... 96 3.54 Number and Percent of Households eating 3 meals per day by District................................................................ 96 3.55 Number and Percent of Households eating Meat Once per Week by District....................................................... 97 3.56 Number and Percent of Households eating Fish Once per Week by District........................................................ 97 3.57 Number and percent of Households Reporting food insufficiency by District ..................................................... 98 BACKGROUND _____________________________________________________________________________________ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on its geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information is intended to provide the user of this report a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Kigoma region lies on the western part of Tanzania along Lake Tanganyika and borders Kagera region to the north,Shinyanga region to the Northeast, Tabora region to the east and Rukwa region to the south. Kigoma region also shares borders with two neighbouring countries of Zaire to the west and Burundi to the northwest Kigoma region is allocated at approximately 30 degrees east and 5 degrees south. It lies at an altitude between 800 and 2400 meters above sea level. The region is divided into four districts which are Kibondo,Kasulu, Kigoma rural and Kigoma urban. The region headquarters is located in Ujiji/Kigoma urban District and has the largest port of Lake Tanganyika. 1.3 Land Area The region has an area of 45,066 sq. kilometers. Out of this area, 37,037 (82%) sq.kms (82%) is land. Ujiji/Kigoma town is the regional headquarters as well as largest port of Lake Tanganyika. 1.4 Climate 1.4.1 Temperature The coolest month is July (16.1 0C) and October is the hottest month (32.3 o C). 1.4.2 Rainfall Kigoma region has two types of rain seasons namely: Long rainfall season (Masika) which starts from March to May and Short rainfall season, (Vuli) which starts from October to December the average rainfall is over 1000mm. 1.5 Population In 2002, Kigoma had a population of 1,674,046 according to the 2002 population census 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 357,088 million with a per capita income of shillings 205,045 . The region held 14th position among regions on GDP and contributed about 3.6 percent to the national GDP. Kigoma region has many tourist attractions such as Ujiji town, which is very famous due to Arab slave caravans from this town to the coast of Dar es Salaam. There is also a Mountain National Park called Mhale where Chimpanzees can be seen. Moreover, it is a town where the explorer Henry Stanley found Dr. David Livingsstone. The region has two tourist hotels which are Hill Top Hotel and Zanzibar Hotel all of them situated within the township area. Ujiji/Kigoma town is linked with the Dar es Salaam city by the railway line, which is about 1254 kilometres in length. The region’s main cash crops are –Tobacco and Coffee, the region is also famous for small sardines called ‘’ Dagaa Kigoma’’ which are used as food INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 2 INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro- processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Kigoma region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: Identification (i.e. region, district, ward and village) Household and holding characteristics Household information Land ownership/tenure Land use Access and use of resources Crop and vegetable production Agro processing and by-Products Crop storage and marketing On-farm investment Access to farm inputs and implements Use of credit for agricultural purposes Tree farming/agro-forestry Crop extension services Livelihood constraints Animal contribution to crop production Livestock Livestock products Fish farming INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 Livestock extension Labour use Access to infrastructure and other services Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation Sample design Design of census questionnaires and other instruments. Field pretesting of the census instruments Training of trainers, supervisors and enumerators Information Education and Communication (IEC) campaign Data Collection Field supervision and consistency checks Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. - Report preparation using Word and Excel. INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: Where feasible all variables were extensively coded to reduce post enumeration coding error. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. Skip patterns were used to avoid asking unnecessary questions Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during than training Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Kigoma, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2.6.11 Data Processing Data processing consisted of the following processes: Manual editing Data entry Data structure formatting Batch validation Tabulation Illustration production Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR Extraction Technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch Validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 Analysis and Report Preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS This part of the report presents the census results for Kigoma region, based on the statistical data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Kigoma region was 195,765.The largest number of agricultural households was in Kasulu (79,396) followed by Kigoma rural (62,470), Kibondo (51,407) Kigoma Urban (2,492). The highest density of households was found in Kasulu (221km2) (Map 3.2). Most households (135,655 69.3%) were involved in growing crops only, (911, 0.5%) were rearing livestock only, and (59,040, 30.2%) were involved in crop production as well as livestock keeping. There were only (160, 0.1% pastoralist in Kigoma Region. (Chart 3.1 and Map 3.1, 3.2,3.3,3.4,3.5 and 3.6) Table 3.1: The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kibondo 1 2 4 3 6 7 5 Kasulu 1 2 3 4 6 7 5 Kigoma Rural 1 2 5 3 7 6 4 Kigoma Urban 2 3 4 1 5 6 7 Total 1 2 3 4 6 7 5 Chart 3.1 Agriculture Households by Type -Kigoma Pastoralists 0.1% Livestock Only 0.5% Crops Only 69.3% Crops and Livestock 30.2% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3.1.2 Livelihood Activities/Source of Income The census results for Kigoma region indicates that most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, livestock keeping/herding, off farm income, tree/forest resources, remittances, fishing hunting & gathering (Table 3.1) Kigoma Urban district was the district where annual crop farming was not the most important livelihood activity and was replaced by permanent crop farming. 3.1.3 Sex and Age of Heads of Households The number of male-headed agriculture households in Kigoma region was 167,324 (85.5% of the total regional agricultural households) whilst the female- headed households it were 28,442 (14.5% of the total regional agricultural households). The mean age of household heads was 44 years (43 years for male heads and 49 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Kigoma region had a total rural agricultural Population of 1,076,658 of which 528,004, (49%) were males and (548,654 51%) were females. Whereas age group 0-14 constituted 46.3 percent of the total rural agricultural population, age group 15-64 (active population) was 50.5 percent. Kigoma region had an average household size of 5 with Kibondo and Kasulu district having the lowest households’ size of 5. (Chart 3.3) 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Chart 3.3 Percent Distribution of Population by Age and Sex - Kigoma. 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percen t Male Female Kigoma Urban Kigoma Rural 2,492 62,470 79,396 51,407 Kasulu Kibondo Map 3.01 KIGOMA Toatal Number of Agricultural Households by District Kigoma Urban Kigoma Rural 8 22 7 9 Kasulu Kibondo Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.02 KIGOMA Number of Agricultural Households Per Square Kilometer of Land by District 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 RESULTS 12 Kigoma Urban Kigoma Rural 34.2 39.3 25.1 Kasulu Kibondo 1.4 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Kigoma Urban Kasulu Kigoma Rural 1,887 53,306 46,422 34,041 Kibondo Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.03 KIGOMA Number of Crop Growing Households by District Map 3.04 KIGOMA Number of Agricultural Households Per Square Kilometer of Land by District 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 13 Kigoma Urban Kigoma Rural 6 5 6 15 Kasulu Kibondo 12 to 15 9 to 12 6 to 9 3 to 6 0 to 3 Kigoma Rural Kigoma Urban 25.9% 44.2% 29% 1% Kasulu Kibondo 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tanzania Agriculture Sample Census Number of Crop Growing Households Per Square Km Number of Crop Growing Households Per Square Km Percent of Crop and Livestock Households Percent of Crop and Livestock Households Map 3.05 KIGOMA Number of Crop Growing Households per Square Kilometer of Land by District Map 3.06 KIGOMA Percent of Crop and Livestock Households by District RESULTS 14 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 Literacy Level for Household Members Kigoma region had a total literacy rate of 66.8 percent. The highest literacy rate was found in Kasulu district (69.0%) followed by Kibondo district (66.2%), Kigoma urban district (65.5%) and lastly Kigoma rural district (64.87) thus Kigoma urban and Kigoma rural had the lowest literacy rates. Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 69.9 percent. The literacy rate for the male heads was 76.7% and that of female heads of households was 29.7%. Literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Kigoma urban (73.3%) followed by Kasulu (71.1%), Kibondo (69.9%) and Kigoma rural (67.7%). (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 38.4 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 31.4 percent were still attending school. Those who have never attended school were 30.2 percent (Chart 3.6). Chart 3.4 Percent Literatecy Level of Household Members by District 0 40 80 Kasulu Kibondo Kigoma Urb Kigoma Rur District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Kigoma 0 50 100 Kibondo Kasulu Kigoma rural Kigoma Urban District Percent Male Female Total Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.4% Never Attended 30.2% Attending School 31.4% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Kigoma Urban Kibondo Kasulu Kigoma rural District Percent Attending School Completed Never Attended RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Agricultural households in Kigoma Urban district had the highest percentage (73.3%) of population aged 5 years and above who had completed different levels of education. This was followed by Kasulu district (71.1%), Kibondo district (69.9%) and Kigoma rural district with the lowest percentage of 67.7. The number of heads of agricultural households with formal education in Kigoma region was 128,834 (65.8%), those without formal education were 59,307 (30.3%) and those with only adult education were 7,624 (3.9%). The majority of heads of agricultural households (63.9%) had primary level education whereas only 0.4% had post secondary education (Chart 3.8). With regard to the heads of agricultural households with primary or secondary education in Kigoma region, Kibondo district had the highest percentages (66.4% for primary and 1.3% for secondary). It was followed by Kasulu (65.9% primary and 1.5% secondary), Kigoma Urban (62.6% primary and 2.7% secondary) and Kigoma rural (59.5% primary and 1.2% secondary). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Kigoma with 66.4% of households with at least one household member engaged in off-farm income generating activities, 93.401 households (71.9%) had only one member aged 5 years and above involved in off-farm income generating activities 26,675 households (20.5%) had two members involved in off-farm income generating activities and 9,848 households (7.6%) had more than two members involved in off-farm income generating activities. The districts with highest percentage of households with off-farm income was Kigoma urban followed by Kigoma rural, Kibondo and Kasulu.The district with the highest percent of agriculture households with more than two members Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Secondary Education 1.4% Post Secondary School 0.4% Adult Education 3.9% Post Primary Education 0.1% No Education 30.3% Primary Education 63.9% Chart 3.9 Percentage Distribution of Household Members of Five Years and Above by Number of Off-farm Activities Two Off Farm Income 21% One Off Farm Income 71% More than Two Off Farm Income 8% Chart 3.10: Number of Household Members with off-farm Activities 0% 20% 40% 60% 80% 100% Kibondo Kasulu Kigoma Rural Kigoma Urban Districts Percen t One Off Farm Inco me Two Off Farm Income Mo re than Two Off Farm Inco me RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 with off-farm income was Kigoma urban (23%), other districts had very few households with more than two members having off-farm income. 3.2 Land Use Land area and planted area are different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total of all areas planted with crops in a year and the areas are summed if there were more than one crop on the same year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that had been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agricultural land in the country; Instead it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused through designated of agricultural land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 373,576 ha, including 1,738 of unusable land. At Regional level the average land area utilised for agriculture per household was only 3.1 ha. This figure is below to the national average which was estimated at 2.0 hectares. The percent utilized of the land available to smallholders was 71%. There were large differences in land utilization per household between districts with Kigoma urban utilizing 9.6 ha per household. The smallest land area utilised per household was found in Kigoma rural (1.3ha). The percentage utilized of the usable land per household is highest in Kigoma urban (100%) and lowest in Kasulu where 79% of the total land available to smallholders was utilised and only 19.7% of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary mono crops was 82,089 hectares (22.0% of the total land available to smallholders in Kigoma), followed by area of uncultivated usable land (80,144 ha, 21.5%), area under permanent mono crops (60,037 ha, 16.1%), area under temporary mixed crops (58,605 ha, 15.7%), area under permanent annual mix (50,073 ha, 13.4%), under Chart 3.11 Utilized and Usable Land per Household by District 0.0 2.0 4.0 6.0 8.0 10.0 Kibondo Kasulu Kigoma Rur Kigoma Urb Districts Area/household 0 10 20 30 40 50 60 70 80 90 100 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.12 Percentage Distribution of Land Area by Type of Land Use 0.2 0.2 0.5 0.6 0.7 2.6 6.7 13.4 15.7 16.1 21.5 22.0 0.0 5.0 10.0 15.0 20.0 25.0 Area under pasture Natural Bush Area unusable area rented Planted trees Permanent mixed crops Under fallow Permanent annual mix Temporary mixed crops Permanent mono crops Uncultivated usable land Temporary mono crops Type of Land Use Percent RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 fallow (24,995 ha, 6.7%), area under permanent mixed crops (9,865 ha, 2.6%), (planted trees 2744 ha, 0.7%), area rented (2,076 ha, 0.5%), Area unsuble (1,738 ha, 0.5%), natural bush (643 ha, 0.2%), area under pasture (569 ha, 0.2%) 3.3 Annual Crops and Vegetable Production Kigoma region has two rainy seasons, which are the short rainy season (October to December) and the long rainy season (March to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 264,974 hectares out of which 145,143 hectares (55%) were planted during short rainy season and 119,831 hectares (45%) during long rainy season. The average areas planted per household during the short and long rainy seasons were 0.8 ha and 1.0 ha respectively (Chart 3.13). The district with the largest area planted for both two seasons was Kasulu while the district with the smallest area planted was Kigoma urban and the percentage planted during short rainy season was highest in Kibondo district (77%), followed by Kasulu (55%), Kigoma rural (39%) and Kigoma urban (37%) (Chart 3.14 and Map 3.8 ). The planted area occupied by cereals was 94,282 ha, (35.6 %of the total area planted with annuals). This was followed by root and tubers 78,510 hectares, (29.6%), pulses 77,848 hectares, (29.5%), oil seeds 11,202 hectares, (4.2%), fruits and vegetables (2,039 hectares (0.8%) and cash crops 1,090 (0.4%) The average area planted per household during the long rainy season in Kigoma region was 1.4 hectares, however, there were small district differences. Kigoma rural had the largest planted area per household (0.4 ha) followed by Kasulu (0.42 ha), Kigoma urban (0.4) and Kibondo had (0.3 ha.) In Kibondo the area planted per household in the short rainy season represents 77 percent of the total planted area per household, whereas in Kigoma urban the corresponding figure is 37 per cent. (Chart 3.15 and Map 3.9). Chart 3.14 Area Planted with Annual Crops by Season and District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Kibondo Kasulu Kigoma Rural Kigoma Urban District Planted Area (ha) 0 10 20 30 40 50 60 70 80 90 Percentage Planted in Short Rainy Season Short Rainy Season Long Rainy Season Percent Planted in Short Rainy Season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 1.00 2.00 3.00 Kibondo Kasulu Kigoma Rural Kigoma Urban District A rea P la nted (ha ) Long Rainy Season Short Rainy Season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 119,831, 45% Short Rainy Season, 145,143, 55% Long Rainy Season Short Rainy Season RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 19 Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of all crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize was the dominant annual crop grown in Kigoma region and it had a planted area 83,896 ha, followed by beans which had the second largest planted area of 77,486 ha. Of the area planted with annuals, maize constitutes 31.7. Other crops in order of their importance (based on area planted) were, maize, beans, groundnuts, cassava, paddy, sorghum, sweetpotatoes, fingermillet, tobacco,amaranths, cocoyams and cotton (Chart 3.16). Households that grow cassava, cotton, maize, simsim, paddy and beans have larger planted areas per household than other crops (Chart 3.16). 3.3. 3 Crop Types Cereals are the main crops grown in Kigoma region. The area planted with cereals was 94,282 ha (35.6 % of the total area planted with annual crops), followed by root & tubes with 78,510 ha (29.6%), pulses 77,848 ha (29.5%), oilseeds & oil nuts 11,202 ha (4.2%) fruits & vegetables 2,039 ha (0.8%) and cash crops had got the least planted area of about 1090 ha (0.4%), (Chart 3.17). Cereals and root and tubers are the dominant crops and other crop types are of minor importance in comparison. There is difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season especial for cereal and it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.17 Planted Area (ha) per Household for Selected Crop 0.00 0.50 1.00 Cassava Cotton Maize Simsim Paddy Beans Cowpeas Sorghum Groundnuts Cocoyam Sweet Potatoes Yams Tomatoes Cabagge Sunflower Irish Potatoes Chillies Crop Planted Area (ha) Chart 3.16 Planted Area (ha) for the Main Crops Tanga 0 20,000 40,000 60,000 80,000 100,000 Maize Beans Groundnuts Cassava Paddy Sorghum Sweet Potatoes Finger Millet Tobbaco Tomatoes Amaranths Cocoyam Cotton Crop Planted Area (ha) 7,862 86,420 30,804 47,044 78,509 1,745 3,258 7,944 1,132 507 8 1,082 0 20,000 40,000 60,000 80,000 A r e a (h e c ta r e s) Cereals Pulses Roots & Tubers Oil seeds & Oil nuts Fruits &Vegetables Cash Crops Crop Type Chart 3.19 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season Chart 3.18: Percentage Distribution of Area planted with Annual Crops by Crop Type Oil seeds & Oil nuts, 4.2% Roots & Tubers, 30.1% Fruits & Vegetables, 0.6% Cash crops, 0.4% Pulses, 29.2, % Cereals, 35.4% Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 3. 3. 4 Cereal Crop Production The total production of cereals was 119,398 tonnes. Maize was the dominant cereal crop at 106,175 tonnes which was (88.9%) of total cereal crops produced, followed by paddy 7,860 tonnes (6.6 %) sorghum 4,530 tonnes (3.8%) , finger millet 742 tonnes (0.6 %) and bulrush millet 71 tonnes (0.05 %), (Map 3.10). The total area planted with cereals was 94,282 ha out of which 86,419 ha (91.7%) were planted in short rainy season and 7,863 ha (8.3%) were planted during the long rainy season. The long rainy season accounted for 8.6 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 90.0% of the total area planted with cereals in that season followed by paddy (4.5%) and sorghum (3.8%), finger millet (1.2%) and bulrush millet (0.1%) (Table 3.2). The area planted with maize was dominant and it represented 89.0% of the total area planted with cereal crops, was followed by paddy (5.1%), sorghum (4.7%), finger millet (1.1%) and bulrush millet with (0.1%).. The yield of paddy was 1,619 kg/ha, followed by bulrush millet (1340 kg/ha), maize (1266 kg/ha), sorghum (1029 kg/ha) and finger millet (709 kg /ha) Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 77,797 98,592 1,267 6,099 7,583 1,243 83,896 106,175 1266 Paddy 4,235 6,820 1,610 620 1,040 1,679 4,855 7,860 1619 Sorghum 3,260 2,890 886 1,144 1,640 1,434 4,404 4,530 1029 Finger Millet 1,074 762 709 0 0 0 1,074 762 709 Bulrush Millet 53 71 1,340 0 0 0 53 71 1340 Total 86,419 109,135 7,863 10,263 94,282 119,398 Chart 3.20 Area Planted and Yield of Major Cereal Crops 0 20,000 40,000 60,000 80,000 100,000 Maize Paddy Sorghum Finger Millet Bulrush millet Crop Area Planted (ha) 0.00 1.00 2.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Kasulu Kigoma Urban Kibondo Kigoma Rural 119,085 2,692 59,744 83,307 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Kigoma Rural Kigoma Urban 64.7% 94.2% 79.2% 99.9% Kasulu Kibondo Tanzania Agriculture Sample Census Percent of Utilized Land Area Percent of Utilized Land Area Annual Crops Planted Area Annual Crops Planted Area Map 3.07 KIGOMA Utilized Land Area Expressed as a Percent of Available Land by District Map 3.08 KIGOMA Total Planted Area with Annual crops by District 92.7 to 99.9 85.7 to 92.7 78.7 to 85.7 71.7 to 78.7 64.7 to 71.7 RESULTS 21 Kasulu Kigoma Rural Kibondo Kigoma Urban 31,792ha 40,776ha 20,872ha 843ha 33.7% 43.2% 22.1% 0.9% Kigoma Urban Kasulu Kigoma Rural 1,004ha 65,520ha 46,202ha 32,417ha 37.3% 55% 77.3% 38.9% Kibondo Tanzania Agriculture Sample Census Planted Area (ha) Percent of Planted Area During the Short Rainy Season Planted Area (ha) Percent of Planted Area With Cereals Crops Map 3.09 KIGOMA Area planted and Percentage During the Short Rainy Season by District Map 3.10 KIGOMA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Planted Area (ha) Planted Area (ha) 40,000 to 70,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 22 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3. 3. 4. 1 Maize Maize dominated the production of cereal crops in the region. The number of households growing maize in Kigoma region during the short rainy season was 168,082 (91.5% of the total annual crops growing households in the region during the short rainy season). The total production of maize was 106,175 tonnes from a planted area of 83,896 hectares resulting in a yield of 1.3 t/ha. (Chart 3.22 Map 3.11) gives maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. There was a continuous increase in maize production over the five year period from 1995 to 2000 followed by a drop in production from 120,000 tonnes to 106,000 tones in 2002.. The average area planted with maize per household was 0.4 hectares; Kasulu district had the largest area of maize (36,958 ha) followed by Kibondo (27,195 ha), Kigoma rural (18,983 ha) and Kigoma Urban (760 ha). (Chart 3.21 and Map 3.12). Chart 3.23 shows that, the yield of maize remained stable from 1995 to 2000 but by year 2003 it had dropped. On the other hand the area planted with maize increased over the entire eight –year period from 1995 to 2003. (Chart 3.23 and 3.14) Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 36,958 27,195 18,983 760 0 10,000 20,000 30,000 40,000 50,000 60,000 Kasulu Kibondo Kigoma rural Kigoma Urban District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.22: Time Series Data on Maize Production 120 47 39 106 84 67 58 0 20 40 60 80 100 120 140 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.23 Time Series of Maize Planted Area & Yield 0 20000 40000 60000 80000 100000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 2 4 Yield (t/ha) Area Yield Kigoma Rural Kibondo Kasulu Kigoma Urban 0.4 0.5 0.5 0.3 0.46 to 0.5 0.42 to 0.46 0.38 to 0.42 0.34 to 0.38 0.3 to 0.34 Kigoma Rural Kibondo Kasulu Kigoma Urban 18,983ha 27,195ha 36,958ha 760ha 1.4% 1.2% 1.3% 0.9% Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Households Map 3.11 KIGOMA Planted Area and Yield of Maize by District Map 3.12 KIGOMA Area Planted per Maize Growing Household by District Planted Area (ha) Planted Area per Households 28,000 > 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 RESULTS 24 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 25 3. 3. 4. 2 Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Kigoma region during the short and long season were 11,298 and 2,510 respectively. These represented 0.1% and 2.1% of the total annual crop growing households in the respective seasons. The total production of paddy was 7,860 tonnes from a planted area of hectare 4,855 resulting in a yield of 1.6 t/ha. The district with the largest area planted with paddy was Kasulu (1,959 ha) followed by Kigoma rural (1,859 ha), Kibondo (954 ha), and Kigoma urbana (83 ha). (Chart 3.24 and Map 3.13 and map 3.14) There was a sharp rise in the production of paddy in 1995/96, 1997/98, 1998/1999 and 1999/00, but by the 2002/03 production had dropped significantly. On the other hand the area planted with paddy kept increasing over the period from 1995/96 to 2003. 3.3.4.3 Other Cereals In terms of area planted with other cereals, bulrush millet and finger millet were less important crops compared to sorghum. The district with the largest area planted with sorghum was Kibondo (2,875ha) and Kasulu (1,499 ha) and Kigoma rural (30 ha) There was no bulrush and finger millet production reported in Kigoma rural and Kigoma urban districts. (Chart 3.27). 0 500 1,000 1,500 2,000 2,500 3,000 Area (H a) Kibondo Kasulu Kigoma Rural Kigoma Urban District Chart 3.27 Area Planted with Sorghum, Finger Millet and Bulrush Millet Sorghum Fingermillet Bulrush millet Chart 3.24 Paddy: Total Area Planted and Planted Area per Household by District 83 954 1,859 1,959 0 500 1,000 1,500 2,000 2,500 Kasulu Kigoma rural Kibondo Kigoma urban District Area (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.25 Time Series Data on Paddy Production 5 1 2 4 4 0 1 0 2 4 6 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year P ro ductio n ('0 0 0 ') to ns Chart 3.26 Time Series of Paddy Planted Area & Yield 0 2000 4000 6000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 1 2 Yield (t/ha) Area Yield Kigoma Urban Kigoma Rural Kibondo Kasulu 83ha 1,859ha 954ha 1,959ha 0.8% 1.3% 1.2% 2.2% 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Kigoma Urban Kasulu Kibondo Kigoma Rural 2.7 4.2 3.5 1.1 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Households Map 3.13 KIGOMA Planted Area and Yield of Paddy by District Map 3.14 KIGOMA Area Planted per Paddy Growing Household by District Planted Area (ha) Planted Area per Households RESULTS 26 3.5 > 2.9 to 3.5 2.3 to 2.9 1.7 to 2.3 1.1 to 1.7 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 135, 912 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 129,744 tonnes representing 95 percent of the total root and tuber crops production. This was followed by sweet potatoes with 5,312 tonnes (4%), the remaining other crops contribute less than 1% of the total production. The estimated yield was highest for Irish potatoes (4.1 t/ha) followed by yams (2.5 t/ha), sweet potatoes (2.4t/ha), cassava (1.7 t/ha) and cocoyams (0.9 t/ha). The area planted with cassava was larger than any other root and tuber crops and it was the second most important annual crop in Kigoma in terms of planted area Note: Cassava is produced in both the long and short rainy seasons. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported mainly under the long rainy season. It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava has been reported under the long rainy season. Table 3.3: Area planted and quantity harvested by season and type of root and tuber crop Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 178 165 927 75,497 129,579 1,716 75,675 129,744 1,714 Sweet Potatoes 1,193 3,103 2,601 1,046 2,209 2,112 2,239 5,312 2,372 Irish Potatoes 49 90 1,837 39 270 6,923 88 360 4,091 Yams 87 200 2,299 27 80 2,963 114 280 2,456 Cocoyam 238 175 735 10 41 4,100 248 216 871 TOTAL 1,745 3,733 76,619 132,179 78,364 135,912 Chart 3.28 Area Planted and Yield of Major Root and Tuber Crops 0 20,000 40,000 60,000 80,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) Yield (kg/ha) Chart 3.29a Area Planted with Cassava during the Census/Survey Years 0 20,000 40,000 60,000 80,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 28 3.3.5.1 Cassava The number of households growing cassava in the region was 137,943. This represented about 70 percent of the total crop growing households in the region. The total production of cassava during the census year was 129,744 tonnes from a planted area of 75,675 hectares resulting in a yield of 1.7t/ha. Previous censuses and surveys indicate that the area planted with cassava increased over the period 1995 to 2002/03. (Chart 3.29a) The area planted with cassava accounted for 53 percent of the total area planted with annual crops and vegetables in the census year. Kasulu district had the largest planted area of cassava (33,553 ha, 44.3%) of cassava planted area in the region). followed by Kigoma rural (33,178 ha, 43.8%), Kibondo (8,503 ha, 11.2%) and Kigoma urban (441 ha, 0.6%) (Chart 3.29a and Map 3.15) However, the district with the highest proportion of its land planted with cassava was in Kigoma Urban (77.6%). This was followed by Kibondo (68.9%), Kigoma rural (24.5%), and Kasulu (10.6%) (Chart 3.29 b). The average cassava planted area per cassava growing household was 0.5 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Kigoma rural (0.6 ha). This was followed by Kasulu (0.5 ha), Kibondo (0.4 ha) and Kigoma urbana (0.3 ha) (Chart 3.30), Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Kigoma region was 8,100 and 4,928 during short and long rainy seasons. This was 8.5% of the total root and tuber crop growing households during both seasons. The total production of sweet potatoes during the census year was 5,312 tonnes from a planted area of 2,238 hectares resulting in a yield of 2.4t/ha. Kigoma rural district has the largest planted area for sweet potatoes (1,210 ha, 54.1%), followed by Kasulu (696 ha, 31.1%), Kigoma urban (200 ha 8.9%) and Kibondo (132 ha, 5.9%) (Chart 3.31 and Map 3.17 and 3.18). Other root and tuber crops are of minor important in terms of area planted compared to cassava and sweet potatoes. Chart 3.29 b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 44.3 43.8 0.6 11.2 0.0 15.0 30.0 45.0 Kasulu Kigoma rural Kibondo Kigoma urban District Percent of Total Area Planted 0 10 20 30 40 50 60 70 80 90 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.64 0.53 0.34 0.23 0.00 0.20 0.40 0.60 0.80 Area per Household Kigomarural Kasulu Kigoma urban Kibondo District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 1,2 10 6 96 20 0 1 3 2 0 200 400 600 800 1,000 1,200 1,400 Kigoma Rur Kasulu Kigoma Urb Kibondo District A rea (Ha) 0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 A rea Planted per Household Area planted (ha) Area planted/hh Kigoma Rural Kibondo Kigoma Urban 0.6 0.5 0.4 0.3 Kasulu 0.54 > 0.48 to 0.54 0.42 to 0.48 0.36 to 0.42 0.3 to 0.36 Kigoma Rural Kibondo Kasulu Kigoma Urban 33,178ha 8,503 33,553 441 1.9t/ha 1.1t/ha 1.7t/ha 3.2t/ha 28,000 to 34,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.15 KIGOMA Planted Area and Yield of Cassava by District Map 3.16 KIGOMA Area Planted per Cassava Growing Household by District Planted Area (ha) RESULTS 29 Planted Area per Households Planted Area per Households Kigoma Urban Kigoma Rural 0.1 0.2 0.2 Kasulu Kibondo 0.3 0.26 to 0.3 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 Kigoma Rural Kigoma Urban Kibondo Kasulu 1,210ha 200ha 132ha 696ha 2.8t/ha 0.7t/ha 0.5t/ha 2.5t/ha 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.17 KIGOMA Planted Area and Yield of Sweet Potatoes by District Map 3.18 KIGOMA Area Planted per Sweet Potatoes Growing Household by District Planted Area (ha) Planted Area per Households Planted Area per Households RESULTS 30 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 3.3.6 Pulse Crops Production: The total area planted with pulses was 77,848 hectares out of which 77,486 ha were planted with beans (99.5 percent of the total area planted with pulses), other pulse crops were of minor importance in terms of area planted, The area planted with pulses in the short rainy season was 47,044 ha which represented 60 percent of total area planted with pulses during the year. Beans was the most dominant pulse crop during short rainy season with 46,723 ha (99.3 % of the total area planted with pulses in that particular season), followed by cowpeas 214 ha, (0.5%) field peas (0.2%) and bambaranuts 16 ha (0.03%). The total production of pulses was 40,521 tonnes. Beans production constituted 99.5 percent of the total pulse production. It was followed by cowpeas (128t, 0.3%), field peas (70t, 0.2%) and bambaranuts (19t, 0.05%) (Chart 3.32). Table 3.4: Area, Quantity Harvested and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 46,723 24,588 526 30,764 15,716 511 77,486 40,304 520 Cowpeas 214 121 56 10 7 731 224 128 571 Bambaranuts 16 13 809 10 6 625 26 19 731 Field peas 91 50 549 20 20 1000 111 70 630 TOTAL 47,044 24,772 30,804 15,749 77,848 40,521 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 10,000 20,000 30,000 40,000 Beans Cowpeas Bambaranuts Crop Area Planted (ha) 0 250 500 750 1,000 Yield (kg/ha) Yield (kg/ha) RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Kigoma region in the short and long rainy seasons was 156,692 and 100,196 respectively. The total production of beans in the region was 40,304 tonnes from a planted area of 77,486 hectares resulting in a yield of 0.52 t/ha. Kasulu with 39351 ha of beans had the largest planted area in the region, (Chart 3.33), it also had the largest area planted with beans per household (0.33 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.5 ha. The variations in area planted with beans per household among the districts were small ranging from 0.33 to 0.24 ha, (Chart 3.34 and Map 3.20) In Kigoma region, bean production has increased steadily over the period 1994/95 to 1997/98 from 35000 tonnes in 1995 to 50,000 tonnes in 1998 but thereafter it started dropping and by 2001 ha dropped to 40,000 tonnes (Chart 3.35). 3.3.7 Oil Seed Production The total production of oilseed crops was 8,577 tonnes planted on an area of 11,202 hectares. The total planted area of oilseeds during the short rainy season was 7,944 ha representing 70.9 percent of the total area planted with oil seeds. The groundnuts was the most important oilseed crop with 10,972 ha (98.0 % of the total area planted with oil seeds), followed by simsim (1.7%) and sunflower (0.3%). (Table 3.5) The yield for simsim was 1057 kg/ha. The yield for ground nuts was 761 kg/ha and the yield for sunflower was 519 kg/ha. Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 Kasulu Kigoma rural Kibondo Kigoma urban District Percent of Land -100 50 200 350 500 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.33 0.29 0.24 0.31 0.00 0.25 0.50 Area per H ousehold Kasulu Kigoma rural Kibondo Kigoma urban District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.35: Time Series Data on Beans Production 45 48 50 43 40 35 37 0 10 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Prod u ction ('000') ton s Chart 3.36 Time Series of Beans Planted Area & Yield 0 20000 40000 60000 80000 1996/97 1998/99 1999/00 2002/03 Agriculture Year A rea (hectares) 0 0.5 1 1.5 2 2.5 3 Y ield (t/ha) Area Yield Kigoma Urban Kigoma Rural 3.7 3.7 3.4 3.1 Kasulu Kibondo 3.58 to 3.7 3.46 to 3.58 3.34 to 3.46 3.22 to 3.34 3.1 to 3.22 Kigoma Rural Kasulu Kigoma Urban 23,214ha 14,293ha 39,351ha 628ha 0.6t/ha 0.5t/ha 0.5t/ha 0.4t/ha Kibondo 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.19 KIGOMA Planted Area and Yield of Beans by District Map 3.20 KIGOMA Area Planted per Beans Growing Household by District Planted Area (ha) Planted Area per Households Planted Area per Households RESULTS 33 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.7.1 Groundnuts The number of households growing groundnuts in Kigoma region was 30,879 and 14,008 during short and long rainy seasons. The total production of groundnuts in the region was 8,354 tonnes from a planted area of 10,972 hectares resulting in a yield of 0.8 t/ha. There was a decrease in production of groundnuts over the period 2001 to 2003, from 10,560 tonnes in 2001/02 to 8,353 tonnes in 2002/03. The district with the largest groundnuts planted area was Kigoma rural with 3743 hectares (34.1 percent of the total area planted with groundnuts in the region) followed by Kibondo (3738 ha, 34.1%), Kasulu (3,470 ha, 31.6%) and Kigoma urban (21 ha, 0.2%), (Chart 3.39 and Map 3.21). The largest area planted per groundnut growing household was found in Kigoma urban (1.1 ha) and the lowest was in Kibondo (0.7 ha.) The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). Map 3.22 Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 37 19 514 0 0 0 37 19 514 Simsim 140 163 774 53 41 774 193 204 1,057 Groundnuts 7,767 5,615 723 3,205 2,739 855 10,972 8,354 761 Total 7,944 5,797 3,258 2,780 11,202 8,577 Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 Kigoma rural Kibondo Kasulu Kigoma Urban District Percent of Land 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.38 Time Series Data on Groundnut Production 9560 8360 8356 10560 0 5,000 10,000 15,000 1994/95 1995/96 1998/99 2002/03 Year Production ( tonnes) Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 5,000 10,000 15,000 Groundnuts Simsim Sunflower Crop Area Planted (ha) -100 100 300 500 700 900 1,100 Yield (kg/ha) 761 1,054 497 0.00 0.20 0.40 0.60 Area per Household (ha) Kibondo Kasulu Kigoma rural Kigoma Urban District Chart 3.40 Area Planted per Groundnut Growing Households by District (Long Rainy Season Only) Kigoma Rural Kigoma Urban 0.2 0.3 0.2 Kasulu Kibondo 0.1 0.26 to 0.3 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 Kigoma Urban Kigoma Rural Kibondo Kasulu 3,738ha 21ha 3,743ha 3,470ha 0.7t/ha 0.8t/ha 0.8t/ha 0.9t/ha 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.21 KIGOMA Planted Area and Yield of Groundnuts by District Map 3.22 KIGOMA Area Planted per Groundnuts Growing Household by District Planted Area (ha) RESULTS 35 Planted Area per Households Planted Area per Households RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 36 3.3.8 Fruits and Vegetables The collection of fruits and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. Reliable historical data for time series analysis of fruits and vegetables are not available the short rainy season is relatively important for fruits and vegetables production since 56 percent of the total area planted with fruits and vegetables was during the short rainy season. For tomatoes, onion, cabbage, water mellon, ginger, and pumkins over 50 percent of the planted area was during the short rainy season. The total production of fruits and vegetables was 5704 tonnes. The most cultivated fruit and vegetable crop was tomatoe with a production of 3,208 tonnes (56.2% of the total fruits and vegetables produced) followed by cabbage (1,256t, 22.0%), onion (508t, 8.9%), amaranths (388t, 6.8%), egg plant (128t, 2.2%) and aubergine (120t, 2.1%) The production of the other fruits and vegetables crops was relatively small (Table 3.6). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 0 0 0 25 13 203 25 13 520 Bitter Aubergine 41 60 683 48 60 1,250 89 120 1,348 Onions 179 372 481 58 136 2,345 237 508 2,143 Cabbage 122 449 3,680 115 807 7,017 237 1,256 5,300 Tomatoes 384 1,285 3,346 396 1,923 4,856 780 3,208 4,113 Spinnach 3 15 5,000 5 7 1,400 8 22 2,750 Carrot 8 16 2,000 0 0 0 8 16 2,000 Chillies 4 29 7,250 3 16 5,333 7 45 6,429 Amaranths 109 372 3,413 470 16 34 579 388 670 Egg Plant 57 95 1,667 12 33 0 69 128 1,855 Total 907 2,683 1,132 3,011 2,039 5,704 Chart 3.41 Area Planted and Yield of Fruits and Vegetables 0 400 800 Tomatoes Cabbage Bitter Aubergine Egg Plant Carrot Chillies Crop A rea P la n ted (h a ) 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 Y ield (k g /h a ) RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 The yield of chillies was 6,429 kg/ha, cabbage (5300 kg/ha), tomatoes (4113 kg/ha) and spinach (2,750 kg/ha), onion and carrot had yields of 2143 and 2000 kg/ha respectively (Chart 3.42 and Map 3.22). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 2,836 and in the short rainy season the number was 2.956. This represented 2.4 percent of the total crop growing households in the region during the long rainy season and 1.2 percent during the short rainy season. Kigoma rural district had the largest planted area of tomatoes (45.4% of the total area planted with tomatoes in the region), followed by Kasulu (25.6%), Kibondo (24.7%) and Kigoma urban (4.2%). (Map 3.23) The highest proportion of land with tomatoes was found in Kigoma rural followed by Kibondo, Kasulu district, the remaining of the district had relatively low percentage of land used for tomato production (Chart 3.42). The largest area planted per tomato growing household was found in Kigoma urban district (0.25 ha) followed by Kigoma rural (0.16 ha), Kibondo (0.13 ha) and Kasulu (0.10 ha) (Chart 3.43) and Map 3.24). The total area planted with tomatoes accounted for 0.3 percent of the total area planted with annual crops and vegetables during the census year. 3.3.8.7 Cabbage The number of households growing cabbages in the region during the long rainy season was 750 and 1010 in the short rainy season. This represented 0.6 percent of the total crop growing households in the region in the long rainy season and 0.5 percent in the short rainy season. Kigoma rural district had the largest planted area of cabbage (87 ha, 34.3% of the total area planted with cabbage in the region), followed by Kasulu (78 ha, 30.7%), Kibondo (72 ha, 28.3%) and Kigoma urban (17 ha, 6.7%). (Chart 3.45 and Map 3.25) map 3.26. The total area planted with cabbages accounted for 0.09 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Chart 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Kigoma rural Kasulu Kibondo Kibondo rural District Percen t of L an d 0.00 0.50 Percen t A rea Plan ted of T otal L an d A rea Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha) Kigoma urban Kigoma rural Kibondo Kasulu District Chart 3.43 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) Chart 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 Kigoma rural Kasulu Kibondo Kigoma Urban District Percent of Land 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Kibondo Kasulu Kigoma Rural Kigoma Urban 0.1 0.1 0.2 0.2 0.18 to 0.2 0.16 to 0.18 0.14 to 0.16 0.12 to 0.14 0.1 to 0.12 Kasulu Kigoma Urban Kigoma Rural Kibondo 200ha 33ha 354ha 193ha 5.8t/ha 4.1t/ha 3t/ha 4.4t/ha 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.23 KIGOMA Planted Area and Yield of Tomatoes by District Map 3.24 KIGOMA Area Planted per Tomatoes Growing Household by District Planted Area (ha) Planted Area per Households Planted Area per Households RESULTS 38 Kigoma Urban Kigoma Rural Kibondo 0.3 0.1 0.1 Kasulu 0 0.24 to 0.31 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Kigoma Urban Kigoma Rural Kibondo Kasulu 0ha 72ha 78ha 87ha 2.5t/ha 6t/ha 7t/ha 0t/ha 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.25 KIGOMA Planted Area and Yield of Cabbage by District Map 3.26 KIGOMA Area Planted per Cabbage Growing Household by District Planted Area (ha) RESULTS 39 Planted Area per Households Planted Area per Households RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 3.3.8.3 Chillies The number of households growing chillies in the region during both the long and short rainy season was 34. This represented 0.03 percent of the total crop growing households in the region. Kigoma Urban district had the only planted area of chillies (7 ha, 100% of the total area planted with chillies in the region), Chillies were not reported in the remaining districts. The largest proportion of the area planted with chillies. (Chart 3.45). The total area planted with chillies accounted for 0.002 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 1090 ha was planted with other annual crops and Tobacco was the most prominent followed by cotton. The area planted with tobacco was 843 ha which represented 77 percent of the total area planted with annual cash crops in short and long rainy season. Cotton Only 89 tonnes of cotton were produced in Kigoma Region on a planted area of 247 ha. All of it was produced during the short rainy season. The crop only grown in Kibondo district, Table 3.6: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 0 0 0 0 0 0 0 0 0 Cotton 247 89 360 0 0 0 247 89 360 Tobacco 835 473 566 8 6 750 843 479 568 Jute 0 0 0 0 0 3 0 0 3 TOTAL 1,082 562 8 6 1,090 568 Chart 3.46 Area planted with Annual Cash Crops Cotton, 247, 23% Tobacco, 843, 77% Chart 3.45 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Kigoma Urban Kibondo Kasulu Kigoma rural District Percen t of L an d 0.00 0.05 0.10 Percen t A rea Plan ted of T otal L an d A rea Percent of Land Proportion of Land RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 Tobacco The quantity of tobacco produced was 479 tonnes. Tobacco had a planted area of 843 ha, most of which was planted in the short rainy season. Tobacco production was concentrated in 3 districts with Kibondo having the largest planted area (49.8% of total area planted with tobacco in the region), followed by Kigoma rural (31.6%) and Kasulu (18.6%). Kigoma urban had no production of Tobacco. (Chart 3.47). 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature they can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of planted area, production and yield. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 42,852 hectares (14% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it doubles counts the area planted more than once during the year, whilst the planted area for permanent crops is the same as physical land area. So the percentage of physical area planted with permanent crops may be higher than indicated in Chart 3.49. Chart 3.47 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 Kibondo Kigoma rural Kasulu Kigoma Urban District Percent of Land 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.48 Area Planted for Annual and Permanent Crops Annual , 264,828 86% Permanent, 42,852 14% Chart 3.49 Area Planted with the Main Perennial Crops Guava, 40, 0.1% Pawpaw, 200, 0.5% Orange, 909, 2.1% Sugarcane, 943, 2.2% Pigeon Pea, 956, 2.3% Coffee, 1,093, 2.6% Mango, 7,376, 17.4% Palm oil, 10,287, 24.3% Banana, 20,503, 48.4% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 42 The most important permanent crop in Kigoma region was banana which had a planted area of 20,503 ha, (47.8% of the planted area of all permanent crops) followed by palm oil (10,287 ha, 24.0%), mango (7,376 ha, 17.2%). The remaining permanent crops collectively had a planted area of 4688 ha (11.0%) (Chart 3.50 and Map 3.26 and 3.27). Kasulu district had the largest area under smallholder permanent crops (20,389 ha, 47.6%). This was followed by Kigoma rural (12,945 ha, 30.2%), Kibondo (9,073 ha, 21.2%) and Kigoma urban (446 ha, 1.0%). Kasulu had the largest area per permanent crop growing household (0.51 ha) followed by Kigoma rural (0.47 ha), Kibondo (0.42 ha) and Kigoma urban (0.0.36 ha). (Chart 3.50). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Kasulu had the highest (17.1%) followed by kigoma urban (16.6%), Kigoma rural (15.5%) and Kibondo (15.2%),. 3.4.1 Palm Oil The total production of palm oil by smallholders was 40,507 tonnes. In terms of area planted, palm oil was the second important permanent crop grown by smallholders in the region. They were grown by 15,819 households (8.1% of the total crop growing households). The average area planted with palm oil per household was relatively big at around 0.65 ha per palm oil growing households Kigoma rural had highest percentage in region region with (12,016 ha, 76.3%), followed by Kasulu (2,922 ha, 18.6%) , There was small amount of palm oil production in the remaining districts (Chart 3.52). 3.4.2 Oranges The total production of oranges by smallholders was 5,559 tonnes. In terms of area planted, orange was the seventh most important permanent crop grown by smallholders in the region. It was grown by 2132 households (1.1% of the total crop growing households). The average area planted with oranges per household was relatively small at around 0.43 ha per orange growing household and the average yield obtained by smallholders was 9,422 kg/ha from a harvest area of 590 hectares. Chart 3.51 Percent of Area Planted with Permanent crops and Average Planted Area per Household by District 21.2 1.0 30.2 47.6 0.0 20.0 40.0 Kasulu Kigoma rural Kibondo Kigoma urban District % o f T o ta l A r e a P la n te d 0.00 0.20 0.40 0.60 A v e r a g e P la n te d A r e a p e r H o u s e h o ld % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Palm oil and Average Planted Area per Household by District 4.8 18.6 0.3 76.3 0.0 20.0 40.0 60.0 80.0 100.0 Kigoma rural Kasulu Kigoma urban Kibondo District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 43 Kigoma rural had the largest area of oranges in the region (543 ha, 59.7%) followed by Kasulu (294 ha, 32.3%), Kibondo (72 ha, 7.9%) and Kigoma urban had no production. The average area planted with oranges per orange planting household was highest in Kigoma Urban (0.49 ha) (Chart 3.53). 3.4.3 Banana The total production of banana by smallholders was 95,828 tonnes. In terms of area planted, banana was the first most important permanent crop grown by smallholders in the region. It was grown by 44,445 households (22.8% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.5 per banana growing household and the average yield obtained by smallholders was 1077 kg/ha kg/ha from a harvested area of 8891 hectares Map 3.27. Kasulu had the largest planted area of bananas in the region (10,136 ha, 49.4%) followed by Kibondo (7,586 ha, 37.0%), Kigoma rural (2,762 ha, 13.5%), and Kigoma urban (18 ha, 0.1%). However, the area planted with banana per banana growing household was highest in Kibondo (0.53 ha), followed by Kasulu (0.46 ha), Kigoma rural (0.35 ha) and Kigoma urban (0.11 ha) (Chart 3.54 and Map 3.28). 3.4.4 Pigeon Pea In terms of area planted, pigeon pea was the sixth most important permanent crop grown by smallholders in the region. It was grown by 6,214 households (3.2% of the total crop growing households). The average area planted with pigeon pea per household was relatively small at around 0.2 ha per pigeon pea growing household. Kasulu had the largest planted area of pigeon pea in the region (604 ha, 63.3%) followed by Kigoma rural (243 ha, 25.5%), Kibondo (103 ha, 10.8%), and Kigoma urban (5 ha, 0.5%). (Chart 3.55) Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 32.34 0.00 59.74 7.92 0.00 20.00 40.00 60.00 Kigoma rural Kasulu Kibondo Kigoma urban District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.54 Percent of Area Planted with Bananas and Average Planted Area per Household by District 13.47 49.44 0.09 37.00 0.00 20.00 40.00 60.00 Kasulu Kibondo Kigoma rural Kigoma urban District % of Total Area Planted 0.00 0.20 0.40 0.60 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.55 Percent of Area Planted with Pigeon peas and Average Planted Area per Household by District 10.79 63.25 0.52 25.45 0.00 20.00 40.00 60.00 80.00 Kasulu Kigoma rural Kibondo Kigoma urban District % of T otal A rea Plan ted 0.00 0.10 0.20 0.30 A verage Plan ted A rea p er H ou seh old % of Total Area Planted Average Planted Area per Household Kigoma Urban Kigoma Rural Kibondo 0.1 0.4 0.5 4.8 Kasulu 3.7 > 2.8 to 3.7 1.9 to 2.8 1 to 1.9 0.1 to 1 Kigoma Urban Kibondo Kigoma Rural Kasulu 18ha 7,586ha 2,762ha 10,136ha 2.7t/ha 10t/ha 5.2t/ha 4.7t/ha 8,000 to 10,200 6,000 to 8,000 4,000 to 8,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Map 3.27 KIGOMA Planted Area and Yield of Banana by District Map 3.28 KIGOMA Area Planted per Banana Growing Household by District Planted Area (ha) RESULTS 44 Planted Area per Households Planted Area per Households RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 45 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method used for land clearing. Table 3.8: Land Clearing Methods 3.5.2 Methods of Soil Preparation Hand cultivation is the most used method for soil preparation and was used on an area of 182,959 ha which represented 69.0 percent of the total planted area, followed by ox-ploughing (5,481 ha, 2.6%) and tractor ploughing (1197 ha, 0.5%). More hand cultivation was used during short rainy season at 77.1% against 22.9% for the long rainy season, similarly oxen ploughing was more common in the short rainy season with 67.6% against 32.4% in the long rainy season. On the otherhand tractor ploughing was used more during the long rainy season of 74.4% during the short rainy season. Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Area Planted % Mostly Hand Slashing 130,331 37,155 23.4 156,202 121,821 76.6 158,976 100.0 Mostly Burning 11,306 3,716 24.2 13,576 11,613 75.8 15,329 100.0 No Land Clearing 4,702 1,292 24.7 5,124 3,945 75.3 5,237 100.0 Mostly Bush Clearance 4,200 1,621 18.4 7,956 7,206 81.6 8,827 100.0 Mostly Tractor Slashing 331 50 19.5 290 207 80.5 257 100.0 Total 150,870 43,834 23.2 183,148 160,357 76.8 188,626 100.0 Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 130,331 11,306 4,702 4,200 331 0 50,000 100,000 150,000 Mostly Hand Slashing Mostly Burning No land clearance Mostly Bush clearance Mostly Tractor Slashing Method of Land Clearing Number of Households Chart 3.57 Area Cultivated by Cultivation Method No preparation, 75,337, 28.4% Mostly Oxen Ploughing, 5,481, 2.1% Mostly Hand Hoe Ploughing, 182,959, 69.0% Mostly Tractor Ploughing, 1197 0.5% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 In Kigoma region, Kasulu district had the largest planted area cultivated by hand hoe oxen (82,402 hectares, 44.9%) followed by Kibondo (50,757 ha, 27.7%), Kigoma rural (49,223, 26.8%) and Kigoma Urban (1,173 ha, 0.6%), 3.5.3 Improved Seeds Use The planted area using improved seeds was estimated at 11,216 ha which represented 4.2 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the short rainy season was 6.1 percent, and higher than the corresponding percentage uses for the long rainy season at 2.0 percent Cereals had the largest area planted with improved seeds (6754 ha, 62% of the area planted with improved seeds) followed by pulses (1888 ha, 17%), fruits and vegetables (1196 ha, 11%), cash crops (743 ha, 7%), roots and tubers (201 ha, 2%) and oil seeds and nuts (161 ha, 1.0%) (Chart 3.60). However, the use of improved seed in cash crops and fruits and vegetables is much greater than in other crop types (68.2% and 63.5% respectively). Only 0.3 percent of the planted area for roots and tubers used improved seed (Chart 3.61). Chart 3.60 Area Planted with Improved Seed by Crop Type Cash Crops, 743, 7% Cereals, 6,754, 62% Fruits & Vegetables, 1,196, 11% Oilseeds , 161, 1% Pulses, 1,888, 17% Roots & Tubers, 201, 2% 0.0 20.0 40.0 60.0 80.0 Crop Type Chart 3.61 Percentage of Crop Type Area Planted with Improved Seed - Annuals Chart 3.59 Planted Area of Improved Seeds Without Improved Seeds, 253,758, 95.8% With Improved Seeds, 11,216, 4.2% 0 45,000 90,000 Area Cultivated Kibondo Kasulu Kigoma rural Kigoma Urban District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 47 3.5.4 Fertilizer Use The use of fertilisers on annual crops is very small with a planted area of only 45,273 ha (17.1 of the total planted area in the region). The planted area without fertilisers for annual crops was 219,555 hectares representing 82.9 percent of the total planted area with annual crops. Of the area planted with fertiliser application, farm yard manure was applied to 31,802 ha which represents 12 percent of the total planted area (70.9% of the area planted with fertiliser application in the region). This was followed by mostly compost (7,557 ha, 3%) and mostly inorganic (5,913) representing only 2 percent of the total planted area The highest percentage of the area planted with fertilizer (all types) was in Kasulu district (48.9%) followed by Kibondo (27.9%), Kigoma rural (20.8%) and Kigoma urban (2.4%) (Table 3.9) Map 3.29 Table 3.9 Number of Crop Growing Households and Planted Area by Fertilizer use and District during Long and Short Rainy Season Most annual crop growing households do not use any fertiliser (approximately 406,797 households, 86.1%). The percentage of the planted area with applied fertiliser was highest for root and tubers (70% of the area planted with these Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 12,518 10,779 1,716 918 1,640 1,188 77,696 46,859 93,571 59,744 Kasulu 20,039 14,854 7,074 6,834 2,153 934 177,089 96,462 206,355 119,085 Kigoma Rural 8,360 6,294 4,597 1,450 5,776 1,876 147,825 73,687 166,558 83,307 Kigoma Urban 1,338 875 272 133 266 114 4,186 1,570 6,062 2,692 Total 42,254 32,803 13,659 9,335 9,835 4,113 406,797 218,578 472,546 264,828 Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 31,803, 12% Mostly Inorganic Fertilizer, 5,913, 2% Mostly Compost, 7,557, 3% No Fertilizer Applied, 219,555, 83% 0 50,000 100,000 150,000 Area (ha) Kibondo Kasulu Kigoma Rural Kigoma Urban Dis t ric t Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Kigoma Urban Kigoma Rural Kasulu 1,524ha 43,810ha 11,692ha 50,572ha 52.6% 56.6% 19.6% 42.5% Kibondo 50,000 to 60,000 50,000 to 50,000 40,000 to 50,000 10,000 to 40,000 0 to 10,000 Kigoma Rural Kigoma Urban Kibondo Kasulu 5,793ha 361ha 5,582ha 10,625ha 25.9% 1.6% 25% 47.5% 8,000 to 11,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Planted Area (ha) Map 3.29 KIGOMA Planted Area and Percent of Planted Area with Application of Fertilizer by District Map 3.30 KIGOMA Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area (ha) with No Application of Fertilizer Planted Area (ha) Planted Area (ha) with Irrigation Percent of Planted Area (ha) with No Fertilizer Applied Percent of Planted Area (ha) with Irrigation RESULTS 48 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 root and tubers during the long rainy season had an application of fertilizers). This was followed by cereals (19%), pulses (8%), fruits and vegetables (2.1%) cash crops and oil seeds (0.3%). (Table 3.10). Table 3.10 Number of Crop Growing Households and Planted Area by Fertilizer use and District- LONG RAINY SEASON Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 3,342 846 658 139 753 103 37,677 12,454 42,429 13,542 Kasulu 5,917 2,348 2,559 1,968 1,177 179 118,092 49,070 127,745 53,565 Kigoma Rural 3,261 960 3,340 835 3,900 831 103,978 48,265 114,478 50,890 Kigoma Urban 906 667 203 123 199 30 2,821 868 4,130 1,688 Total 13,425 4,820 6,760 3,064 6,029 1,144 262,568 110,656 288,782 119,685 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Kigoma region was 32,803 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 13,425 and it was applied to 4,820 ha representing 14.7 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (61.2%), followed by Pulses (29.0%), Fruits & Vegetables (4.2%), Roots & Tubers (3.9%), Oil seeds (1.4%) and Cash crops (0.3%). However, pulses had the highest percent of the proportion of planted area with farm yard manure (34.1% of the total area of pulses in Kigoma). Chart 3.64 Planted Area with Farm Yard Manure by Crop Type Roots & Tubers, 1,038, 3.9% Pulses 7,736 29.0% Oilseeds, 379, 1.4% Fruits & Vegetables, 1,124, 4.2% Cereals, 16,300, 61.2% Cash Crops, 73, 0.3% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 This was followed by cereals (23.0%), fruits & vegetables (17.2%), roots & vegetables (15.7%), oil seeds (5.4%) and cash crops (4.6%) (Chart 3.65a). Farm yard manure is mostly used in Kigoma urban (32.5% of the total planted area in the district), followed by Kibondo (18.0%), Kasulu (12.5%) and Kigoma rural (7.6%) (Chart 3.65b). map 3.81 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Kigoma region was 3,649 ha which represents 1.3 percent of the total planted area with annuals in the region and 9.3 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 6,029 and it was applied to 1,144 ha representing 0.9 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (66% of the total area applied with inorganic fertilizers), followed by fruits & vegetables (29%), pulses (8%), roots and tubers (3%), pulses (7%) and oil seeds (1%). (Chart 3.66). 0.0 10.0 20.0 30.0 40.0 Percen t of Plan ted A rea Pulses Cereals Fruits & Vegetables Roots & Tubers Oilseeds Cash Crop Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District 0.0 20.0 40.0 Kigoma Urban Kibondo Kasulu Kigoma Rural District Percent Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type Pulses, 273, 8% Oilseeds, 42, 1% Cereals, 2,124, 66% Roots & Tubers, 107, 3% Fruit & Vegetables, 763, 29% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 However, the proportion of fruit and vegetables with inorganic fertilizers was 39.1 percent higher than other crop types, followed by roots & tubers (10.5%), oil seeds (7.6%), cereals (6.6%) and pulses (1.5%) (Chart 3.67a). Inorganic fertiliser is mostly used in Kigoma urban (6.0% of the total planted area in the district), followed by Kigoma rural (3.8%), Kibondo (2.0%) and Kasulu (1.1%) (Chart 3.67b). 3.5.4.3 Compost Use The total planted area applied with compost was 12,491 ha which represents only 4.7 percent of the total planted area with annual crops in the region and 31.9 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 6,760 and it was applied to 3064 ha representing 2.5 percent of the total area planted (Table 3.10 and Chart 3.68a). The proportion of area applied with compost was low for each type of crop; however the distribution of the total area using compost manure shows that 32 percent of this area was cultivated with pulses, followed by roots & tubers (26%), oil seeds (24%), cereals (20%) and fruits & vegetables (3%). (Chart 3.68b). 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 P ercen t o f P la n ted A rea Fruits & Vegetables Roots & Tubers Oilseeds Cereals Pulses Cash Crop Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type -Annuals Chart 3.68a Planted Area with Compost by Crop Type Roots & Tubers, 432, 5% Cereals, 4,377, 50% Fruits & Vegetables, 64, 1% Pulses, 3,803, 43% Oilseeds, 130, 1% 0 5 10 15 20 25 Percen t of Plan ted A rea Pulses Roots & Tubers Oilseeds Cereals Fruits & Vegetables Cash Crop Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertilisers by District 0.0 2.0 4.0 6.0 8.0 Kigoma Urban Kigoma Rural Kibondo Kasulu District Percent ` RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 Compost is mostly used in Kasulu (4.6% of the total planted area in the district), followed by Kibondo (1.5%), Kigoma rural (1.4%) and Kigoma urban (0.9%) (Chart 3.68c). Map 3.32 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 21,818 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (60% of the total area applied with pesticides). This was followed by fungicides (24%) and herbicides (16%) (Chart 3.69). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 13,092 ha which represented 60 percent of the total planted area for annual crops and vegetables. Cereal crops had the largest planted area applied with insecticides (4358 ha, 50%) of the total planted area with insecticides) followed by pulses (2,420 ha, 27%), fruits & vegetables (962 ha, 11%), cash crops (559 ha, 6%) roots & tubers (385 ha, 4%) and oil seeds &oil (204 ha, 2%). (Chart 3.70). However, the proportion of planted area applied with insecticides was largest for cash crops( 51%), fruits/vegetables (47%), cereals (5%), pulses (3%), Only 2 percent the area planted with oil seeds & tubers was applied with insecticides (Chart 3.71). Chart 3.69 Planted Area (ha) of Annual Crops Pesticide Use Fungicides, 5,234, 24% Herbicides, 3,492, 16% Insecticides, 13,092, 60% Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 559, 6% Cereals, 4358, 50% Fruits & Vegetables, 962, 11% Oil seeds & Oil nuts, 204, 2% Pulses, 2,420, 27% Roots & Tubers, 385, 4% 0 20 40 60 Percent of Planted Area Cash crops Fruits & Vegetables Cereals Pulses Oil seeds & Oil nuts Roots & Tubers Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.68c Proportion of Planted Area Applied with Compost by District -1.0 1.0 3.0 5.0 Kasulu Kibondo Kigoma Rural Kigoma Urban District Percent Kigoma Rural Kasulu Kigoma Urban 4,496ha 4,655ha 6,665ha 260ha 28% 29% 41.5% 1.6% Kibondo 4,000 to 7,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Kigoma Rural Kasulu Kigoma Urban Kibondo 1,297ha 927ha 3,960ha 101ha 20.6% 14.7% 63% 1.6% 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Planted Area (ha) Map 3.31 KIGOMA Planted Area and Percent of Total Planted Area with Farm Yard Manure Application by District Planted Area and Percent of Total Planted Area with Compost Application by District Planted Area (ha) with Farm Yard Manure Applied Planted Area (ha) Planted Area (ha) with Compost Applied Map 3.32 KIGOMA Percent of Planted Area (ha) with Farm Yard Manure Applied Percent of Planted Area (ha) with Compost Applied RESULTS 53 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 Annual crops with more than 50 percent insecticide use were spinach, cucumber , cotton , water mellon, tomatoes, onions, cabbage, field peas, and chillies. Kibondo had the highest percent of planted area with insecticides (7.7% of the total planted area with annual crops in the district). This was followed by Kigoma rural and Kigoma urban both had (6.5%) and the smallest percentage use was recorded in Kasulu district (2.5%) (Chart 3.72) 3.5.5.2 Herbicide Use The planted area applied with herbicides was 2,544 ha which represented 0.9 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1176 ha, 47%) followed by roots & tubers (872 ha, 34%), pulses (233 ha, (9%), oil seeds (128 ha, 5%), fruits & vegetables (127 ha, 5%) and cash crops (54 ha, 2%) (Chart 3.73). However, the proportion of the planted area applied with herbicides was greater for fruits/vegetables being 8.0%, cereals (1.2%), oil seeds and root & tubers both had (1.1%) and only 0.3 percent of pulses were applied with herbicides Kigoma urban had the highest percent of planted area with herbicides (3.8% of the total planted area with annual crops in the district). This was followed by Kibondo (3.0%), Kasulu (1.0%) and Kigoma rural district had less than (1%). 3.75). Chart 3.72 Percentage of Planted Area Applied with Insecticides by District 0.0 2.0 4.0 6.0 8.0 10.0 Kibondo Kigoma Rural Kigoma Urban Kasulu District Percent Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cash crops, 54, 2% Cereals, 1,176, 47% Fruits & Vegetables, 127, 5% Oil seeds & Oil nuts, 128, 5% Pulses, 233, 9% Roots & Tubers, 872, 34% Chart 3.75 Proportion of Planted Area Applied with Herbicides by District 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Kigoma Urb Kibondo Kasulu Kigoma Rur District Percent 0.0 2.0 4.0 6.0 8.0 Percen t of Planted A rea Fruits & Vegetables Cereals Oil seeds Roots & Tubers Pulses Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 3.5.5.3 Fungicides Use The planted area applied with fungicides was 3,507 ha which represented 1.3 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (0.6%) was higher than the corresponding percentage for the long rainy season (0.4%). Cereals had the largest planted area applied with fungicides (1,145 ha, 33%) followed by fruits & vegetables (947 ha, 27%), pulses (778 ha, 22%), cash crops (312 ha, 9%), roots & tubers (240 ha, 7%) and oil seeds (85 ha, 2%), (Chart 3.76 ). However, the proportion of planted area applied with fungicides was greater in fruits and vegetables and cash crops than in other crop types being 46.3% for fruits & vegetables and 28.8% for cash crops, only 0.3% of roots & tubers was applied with fungicides ( chart 3.77). Kigoma urban had the highest percent of planted area with fungicides (5.7% of the total planted area with annual crops in the district). This was followed by Kigoma rural (2.7%), Kibondo (2.3%). The smallest percentage use was recorded in Kasulu district (1.2%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals and other crops was reported to be by hand. Very small amounts of crops were harvested by machine. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 99.4 percent of the total area planted with cereals during the long rainy season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested by 0.6 percent of the total planted area respectively. Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 240, 7% Pulses, 778, 22% Oil seeds, 85, 2% Fruits & Vegetables, 947, 27% Cereals, 1,145, 33% Cash crops, 312, 9% 0.0 20.0 40.0 60.0 Percent of Planted A rea Fruits & Vegetables Cash crops Cereals Pulses Oil seeds Roots & Tubers Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Kigoma Urb Kigoma Rur Kibondo Kasulu District Percent RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yield. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Kigoma region, the area of annual crops under irrigation was 7,835 ha representing 3 percent of the total area planted (Chart 3.79). The area under irrigation during the long rainy season was 2,566 ha accounting for 32.8 percent of the total area under irrigation. In the short rainy season, 3.6 percent of the total area planted with crops was irrigated. The district with the largest planted area under irrigation for annual crops was Kasulu (2,186 ha, 52.6% of the total irrigated planted area with annual crops in the region). This was followed by Kigoma rural with (1,520 ha, 36.6%), Kibondo (409 ha, 9.8%) and Kigoma urban (42, 1.0%), When expressed as a percentage of the total area planted in each district, Kigoma rural had the highest with 92.3% of the planted area in the district under irrigation. This was followed by Kigoma urban (80.7%), Kasulu (79.2%), and Kibondo 71.9%) (Chart 3.80). Map 3.30 The Planted area with irrigation in Kigoma region appears to have increased over the 7 year period from 3,470 households in 1995/96 to to 11,410 households in 2002/03. (Chart 3.81) Chart 3.79 Area of Irrigated Land Unirrigated Area, 115,518, 97% Irrigated Area, 4,167, 3% Chart 2.80 Planted Area with Irrigation by District 0 1,000 2,000 3,000 Kasulu Kigoma rural Kibondo Kigoma Urban Region I r r ig a t e d A r e a ( h a ) 0.0 10.0 20.0 30.0 40.0 50.0 60.0 P e r c e n t a g e I r r ig a t io n Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation 3,470 11,610 0 5,000 10,000 15,000 1995/96 2002/03 Agriculture Year Planted Area ubder Irrigation RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from river (13,917 households, 79.9% of households with irrigation). This was followed by well (1,321 households, 7.6%), canal (1,038 households, 6.0%), lake (751, 4.3%), borehole (197 households 1.1%) and dam (193 households, 1.1%). (Chart 3.82) 3.6.3 Methods of Obtaining Water for Irrigation The hand bucket was the most common method of getting water for irrigation with 50.2 percent of households using this method. This was followed by gravity with 49.8 percent of households. The remaining methods (hand pump, motor pump and others) were not used (Chart 3.83). The hand bucket was used most in Kigoma urban (100% of the households practicing irrigation) followed by Kigoma rural (77%), Kasulu (37%) and Kibondo (33%). Gravity was more common in Kibondo with 67 percent of households using the method to get water for irrigation, followed by Kasulu (63%) and Kigoma urban (0.0%). 3.6.4 Methods of Water Application Most households (55.2% of households using irrigation) used used bucket/ watering can as a method of field application. This was closely followed by flood (42.7%). Water hose and splinkler were not widely used being 1.1% for sprinkler and 0.9% for the water hose. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 8736 50.2% Gravity, 8,681, 49.8% Gravity Hand Bucket Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 197, 1.1% Bucket / Watering Can, 9,618, 55.2% Flood, 7,442, 42.7% Water Hose, 160, 0.9% Flood Bucket / Watering Can Sprinkler Water Hose Chart 3.82 Number of Households with Irrigation by Source of Water River, 13,917, 79.9% Well, 1,321, 7.6% Canal, 1,038, 6.0% Borehole,197, 1.2% Dam, 193, 1.2% Lake, 751, 4.3% River Well Canal Borehole Dam Lake RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Kigoma region show that there were 186,533 crop growing households (95.8% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 172,631 households storing 18,093 tonnes as of 1st January 2004. This was followed by beans and other pulses 162,195 households, 7,788 tonnes, groundnuts and bambara nuts 15,702 households, 712 tonnes, sorghum and millet with 12,747 households, 520 tonnes, paddy 1,803 households, 1,389 tonnes. Other crops were stored in very small quantities. 3.7.1.1 Methods of Storage The number of households that stored their produce in sacks and/or open drums was 116,887 (62.7%). This was followed by locally made traditional structures 65,673 households (35.2%), improved local structures 1800 households (1.0%), unprotected pile 922 (0.5%) and other methods of storage 1251 households (0.7%). Sacks/Open drums were the dominant storage facilities in all districts with the highest percent in Kigoma urban district (83%) followed by Kigoma rural (79%), Kibondo (57%) and lastly Kasulu (53%), Chart 3.87) (Chart 3.87) Chart 3.85 Number of Households and Quantity Stored by Crop 0 50,000 100,000 150,000 200,000 Maize Pulse & Beans Gnuts/Bamb Nuts Sorghum & Millet Paddy Tobacco Crop Number of households 0 5,000 10,000 15,000 20,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Kibondo Kasulu Kigoma Rural Kigoma Urban District Percen t of h ou seh old s Locally Made Traditional Crib Improved Locally Made Crib Sacks / Open Drum Unprotected Pile Other Chart 3.86 Number of Households by Storage Method Locally Made traditional Crib, 65,673, 35.2% Sacks / Open Drum, 116,887, 62.7% Other methods of storage, 1,251, 0.7% Improved local structures, 1,800, 1.0% Unprotected Pile, 922, 0.5% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.1.2 Duration of Storage Most households (58.5% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of more than 6 months, (23.9%), and lastly those that stored their crops for a period of less than 3 less (17.5%). Most households that stored pulses, stored them for a period of 3 and 6 months (58%), followed by over 6 months (24%), and a small number of households stored pulses for the period of less than 3 months (17%) (Chart 3.88) The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Kigoma urban district (65.9%) followed by Kasulu (64.9%), Kigoma rural (52.5%) and Kibondo (31.4%). (Map 3.35) District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). 3.7.1.3 Purpose of Storage Subsistence food crops i.e maize, paddy, sorghum and millet, beans and pulses are mainly stored for household consumption. The percent of households that stored maize with household consumption as the main purpose of storage was 89.0% followed by paddy (82.8%), pulses (80.8%) and sorghum & millet 62.0%, Practically all stored annual cash crops were stored for selling at a higher price 3.7.1.4 The Magnitude of Storage Loss About 80.3 percent of households that stored crops had little or no loss, up to ¼ losses (13.6%), between ¼ and ½ loss (5.2%), over 1/2 loss (0.9%). The number of households that reported little or no loss was largest for Kigoma urban district being about 87.8%, up to quarter loss Kibondo district had the highest percentage of 19.8%, between a quarter and half loss also Kigoma rural 0 40,000 80,000 120,000 Number of households Maize Beans & Pulses Paddy Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 25,000 50,000 Kasulu Kibondo Kigoma rural Kigoma urban District Quantity (tonnes) 0 15 30 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Tobacco Gnuts Bamb Nuts Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 and Kibondo districts recorded the highest percentage of 5.8% and 5.7% and for over a half loss the highest percentage was recorded in Kibondo district about 1.8 % (Table 3.10) 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced by 185,249 crop growing households in Kigoma region, (95% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in each district being more than 80% (Chart 3.91b). 3.7.2.1 Processing Methods The households that processed their crops using neighbour’s machines were the largest at 110,871 ( 59.8 % of the households that processed crops). They were followed by those processing by trader (51,088 households, 27.6%), on- farm by machine (12,618 households, 6.8%), on-farm by hand (9,241 households, 5.0%). The remaining methods of processing were used by 0.7% of the households. Table 3.10 ;CROP STORAGE: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Kibondo 36,302 9,883 2,849 917 49,951 Kasulu 64,578 8,567 3,523 592 77,260 Kigoma Rural 47,132 6,665 3,331 137 57,265 Kigoma Urban 1,923 200 67 0 2,190 Total 149,802 25,316 9,770 1,646 186,534 0 25 50 75 100 Percent of Households Processing Kibondo Kigoma rural Kigoma u... Kasulu District Chart 3.91b Percentage of Households Processing Crops by District Chart 3.91a Households Processing Crops Households not Processing, 9,446, 5% Households Processing, 185,249, 95% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 KIbondo district had the a highest percent of processing by neighbouring machine (89.8%), followed by Kasulu district (57.8%), Kigoma urban (26.7%) and Kigoma rural (15.5%). Processing on farm by machine was more prevalent in Kigoma rural (72%) with the remaining districts having very few households (less than 5 percent). Whilst processing on farm by hand was more prevalent in Kigoma urban district (12.4%), followed by Kibondo (5.2%) with the remaining districts having less than 5% (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is the secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 165,201 households processing crops into flour (89.2%) followed by oil with 9,944 households (5.4%) and grain (9,124 households 4.9%) The remaining products were produced by a small number of households (0.5%). (Chart 3.93). The number of households producing by-products accounted for 8.6% of the households processing crops. The most common by-product produced by crop processing households was shell with 3635 households (22.9% of the households producing by -products) followed by bran (2689 households, 16.9%), pulp (1336 households, 8.4%). (Chart 3.94). Chart 3.93 Percent of Households by Type of Main Processed Product Grain, 9,124, (4.9%) Oil, 9944, (5.4%) Juice, 980, (0.5%) Flour / Meal, 165,201 (89.2%) Flour / Meal Grain Oil Juice Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Kibondo Kasulu Kigoma Rural Kigoma Urban District P ercent o f H o useho lds On Farm by Hand On Farm by Machine By Neighbour Machine Other By Co-operative Union By Trader On Large Scale Farm By Factory Chart 3.94 Number of Households by Type of By-product Husk, 937, 6.0% Bran, 2,689, 17.2% Pulp, 1,336, 8.5% Cake, 415, 2.6% Other, 6,274, 40.0% Shell, 3,635, 23.2% Juice, 197, 1.3% Fibre, 192, 1% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, for selling and for fuel cooking. The most important use was for household/human consumption which represented 92.8% of the total households that used primary processed product, followed by sales only (6.5%). The remaining uses of primary processed products accounted to 0.2% of the households (Chart 3.95). . Out of 29,737 households that sold processed products, 16,008 households were from Kigoma rural district (53.8% of the total number of households selling processed products in the region), followed by Kasulu with 8,442 households (28.4%), Kibondo with 4,103 households (13.8%) and Kigoma Urban with 1,184 households (3.9%). (Chart 3.96). . 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold them to local market and trade stores (12,772 households, 43% of households that sold crops). This was followed by selling to neighbours (7,165 households, 24%), trader at farm (4,827 households, 16%), others (2,597 households, 9%), farmers association (2,184 households, 7%) and marketing co-perative (192 households, 1.%) (Chart 3.97). 0.00 20.00 40.00 60.00 Percentage of households Kigoma Rural Kasulu Kibondo Kigoma urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.95 Use of Processed Product Household/ human consumption, 172,786, (92.8%) Sale only, 2,197 ( 6.5%) Fuel cooking, 300 (0.1%) Did not use, 133, (0.1%) Household / Human Consumption Sale Only fuel cooking Did not use Chart 3.97 Location of Sale of Processed Products Neighbours, 7,165, 24% Local Market / Trade Store, 12,772, 43% Marketing Co- operative, 192, 1% Other, 2,597, 9% Trader at Farm, 4,827, 16% Farmers Association, 2,184, 7% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 There were large differences between districts in the proportion of households selling processed products to neighbours with Kibondo district having the largest percent of households in the region selling to local market/ trade store (78.8%), whereas Kasulu district had a higher percent of households selling to neighbours than other outlets. Compared to other districts, Kibondo district had the highest percent of households selling processed products to local market/trade store, In Kigoma rural district the sale of processed produce to traders at farm was most prominent compared to other districts, and district that had the highest proportion of households selling processed products to farmers association was Kigoma rural whereas Kasulu and Kigoma urban had no households selling to farmers association. (Chart 3.98). 3.7.3 Crop Marketing The number of households that reported selling crops was 167,633 which represented 86.1% of the total number of crop growing households. The percent of crop growing households selling crops was highest in Kasulu (94%) followed by Kigoma rural (92%), Kigoma urban (87%), and Kibondo (65%) (Chart 3.99 and Map 3.36). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (81.2%) of crop growing households. Apart from low market prices, other problems were lack to transport (7.5%), high transport (4.2%), Market too far (4.1%), other (1.2%). and lack of market information (1.1% Other marketing problems are minor and represented less than 1 percent of the total reported problem (Chart 3.100). Chart 3.98 Percent of Households Selling Processed Products by Outlet and District 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Kibondo Kasulu Kigoma Rural Kigoma Urban District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Trader at Farm Other Other Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Kasulu Kigoma Rural Kibondo Kigoma Urban District Number Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Farmers Assocoation 0.0% Open Market Price Too Low 81.2% Government regulatory board 0.2% Market too far` 4.1% Lack of Market Information 1.1% No Transport 7.5% Transport Cost Too High 4.2% Other 1.2% Kigoma Urban Kigoma Rural 65.8% 57.6% 52.4% 64.9% Kasulu Kibondo 63.2 > 60.5 to 63.2 57.8 to 60.5 55.1 to 57.8 52.4 to 55.1 Kigoma Rural Kasulu Kigoma Urban 57,196 33,570 74,709 2,158 91.6% 65.3% 94.1% 86.6% Kibondo Tanzania Agriculture Sample Census Percent of Household Storing Crops Map 3.33 KIGOMA Percent of Household Storing Crops For 3 to 6 month by district Map 3.34 KIGOMA Number of Households and Percent of Total Households Selling Crops by District Percent of Household Storing Crops Number of Households Selling Crops Number of Households Selling Crops Percent of Total Households Selling Crops 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 64 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 3.7.3.2 Reason for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 88.1% of the smallholders, price too low (7.0%), market too far (1.8%). The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Kigoma region very few agricultural households 3,403, (1.7%) accessed credit out of which 3,211 (94%) were male-headed households and 192 (6%) were female headed households. In Kibondo,Kigoma rural and Kigoma urban districtss, only male-headed households accessed credit. (Table 3.12) 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Kigoma region was co operative which provided credit to 2,347 agricultural households, (69% of the total number of households that accessed credit), followed by family, friends and relatives (22%), tarder/trade store (6%) and religious organisation (4%) (Chart 3.101). Religious organization/NGO/Project were the sole source of credit only in Kibondo district, co operatives provided credit in Kibondo, Kasulu and Kigoma rural districts, while trade/trade stores provided credit only in Kasulu district (Chart 3.102). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 45158 88.1 Other 903 1.8 Price Too Low 3593 7.0 Trade Union Problems 352 0.7 Co-operative Problems 155 0.3 Market Too Far 937 1.8 Government Regulatory Board Problems 132 0.3 Total 15230 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Kibondo 251 100 0 0 251 Kasulu 1,363 88 192 12 1,555 Kigoma rural 1,597 100 0 0 1,597 Kigoma urban 0 0 0 0 0 Total 3,211 94 192 6 3,403 Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Religious Organisation / NGO / Project 4% Trader / Trade Store 6% Co-operative 69.0% Family, Friend and Relative 22% Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Kibondo Kasulu Kigoma rural District P ercent o f H o useho lds Family, Friend and Relative Co-operative Trader / Trade Store Religious Organisation / NGO / Project RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on fertilizers (62%), followed by agro-Chemicals (21%) and seeds (17%) (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was did not know how to get credit accounting to 40.2% percent of the agricultural households. This was followed by households reporting credit not available 20.7%, did not know about credit 19.1%, did not want to go into debt 9.0%, difficult bureaucracy procedure 5.4 %, the rest of the reasons accounted for (5.5%), (Chart 104). 3.8.2 Crop Extension The number of agricultural households that received crop extension was estimated at 118,417 or 61% of total crop growing households in the region.(Chart 3.105) Some districts had more access to extension services than others. Kigoma urban had a relatively high proportion of households (95%) that received crop extension messages in the district followed by Kigoma rural (88%), Kasulu and Kibondo both had (47% of households that received crop extension services) (Chart 3.106 and Map 3.33). 3.8.2.1 Sources of Crop Extension Messages Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Seeds 31% Agro Chemicals 19% Fertilizers 50% Chart 3.104 Reasons for not Using Credit (% of Households) Credit granted too late, 938, 0.5% Don't know about credit, 36,664, 19.1% Other, 554, 0.3% Difficult bureaucracy procedure, 10,404, 5.4% Did not know how to get credit, 77,425, 40.2% Interest rate/cost too high, 3,307, 1.7% Did not want to go into debt, 17,377, 9.0% Not available, 39,909, 20.7% Not needed, 5,784, 3.0% Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 77,348, 40% Households Receiving Extension , 118,417, 60% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 60,000 Kigoma rural Kasulu Kibondo Kigoma urban District Number of Households 0 20 40 60 80 100 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 Of the households receiving extension advice the government provided the greatest proportion 112,202 households (95.3%), NGOs provided extension advice to 3,504 households (3%), The remaining sources provided less than 1 percent each. 3.8.2.2 Quality of Extension An assessment of quality of extension indicates that 58% of the households receiving extension ranked the service as being good followed by average (29%), very good (12%) and poor (1%). (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs 3.9.1 Use of Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections reference was to annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in previous section on Inputs Use (Section 3.5). Data on source of inputs are only found in this section and apply to both annual and permanent crop A small number of households use inputs and this particularly true of inputs that are not produced on farm, such as pesticides/fungicide, inorganic fertilizers and herbicides. In Kigoma region farm yard manure was used 21.2 percent of the crop growing households, compost (8.2%), inorganic fertilizers (7.5%), improved seeds (7.2%), pesticides/fungicides (6.9%), and herbicides (0.1%). Table 2.13 Access to Inputs Households With Access to Input Households Without Access to Input Type of Input Number % Number % Farm yard manure 41,045 21.1 153,920 78.9 Improved seeds 13,963 7.2 181,002 92.8 Pestcides/Fungicide 13,513 6.9 181,452 93.1 Inorganic fertiliser 14,614 7.5 180,351 92.5 Compost 16,039 8.2 178,926 91.8 Herbicide 149 0.1 194,816 99.9 Chart 3.107 Number of Households Receiving Extension by Quality of Services Good, 68,930, 58% Average, 34,650, 29% Poor, 773, 1% Very Good, 13,933, 12% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 3.9.2 Inorganic Fertilizers Most smallholders using inorganic fertilizers purchased them from the local market/trade store (73.7% of the number of households using fertilizers). The other source were cooperatives (23.0%), local farmers group (2.2%) and neighbours (1.1%). (Chart 3.108). For most households the distance from the household to source of inorganic fertilizers was more than 20 km (27.5% of households used the fertilizers), followed by 3 and 10 km (24.7%) , less than 1 km (21.2%), between 1 and 3 km (15.4%) and between 10 and 20 km (11.2%) (Chart 3.109). Due to the very small number of households using inorganic fertilizers coupled with the small number of households responding to ‘’not available’’ (7.2%), as the reason for not using them it may be assumed that access to inorganic fertilizer was not the main reason for not using the fertilizers. Other reasons such as cost were more important with 70 percent of households responding to cost factors as the main reason for not using the fertilizers. In other words, if the cost was affordable the demand would be higher and inorganic fertilizer would be made more available. There were more smallholders using inorganic fertilizers in Kasulu than in other districts in Kigoma region (43.9% of the households used inorganic fertilizers), followed by Kibondo (25.7%) and Kigoma urban (2.3%). Chart 3.108 Number of Households by Source of Inorganic Fertiliser 73.7 23.0 2.2 1.1 0 5,000 10,000 15,000 Local Market / Trade Store Co-operative Local farmers group Neighbour Source of Inorganic Fertiliser Number of Households Chart 3.109 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percen t of H ou seh old s Chart 3.110 Number of Households by Source of Insecticides/Fungicides 3.7 5.0 5.8 13.0 67.5 0 2,000 4,000 6,000 8,000 10,000 Local Market / Trade Store Locally Produced by Household Neighbour Co-o peratives Famers' groups Source of Insecticide/fungicide Number of Households RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 3.9.3 Improved Seeds The percentage of crop growing households that used improved seeds was 7.2. Most of the improved seeds were obtained from the local market/trade stores (67.5%), followed by co-operative (22.7%). Access to improved seeds was better than access to chemical fertilizers with 32 percent of households obtaining the input within 1 km of the household (Chart 3.111). This is in line with the higher use of improved seed compared to chemical inputs, which further supports the concept that it is not the availability that is the the main issue in the use of inputs but rather other factor such as cost. The districts that used improved seeds most was Kigoma urban (23.6 percent of the total number of households using improved seeds in the district), followed by Kasulu (8.1%), Kigoma rural (7.1%) and Kibondo (3.9%).(Map3.34) 3.9.4 Insecticides and Fungicides Most smallholders’ households using insecticides and fungicides purchased them from local markets/trade stores (65.69%) of the total number of fungicides users) followed by cooperatives (22.5%).Other sources of insecticides/fungicides were of minor importance (Chart 3.112 and Chart 3.36). Chart 3.113 shows that for 19%, of the households using insecticides/ fungicides the source was within a distance of 10 kms The district that used insecticide/fungicides most was Kigoma rural (46.4 percent of the total number of households that use fungicides in the region), followed by Kibondo (29.2%), Kasulu (23.2%) and Kigoma urban (1.2%) Chart 3.111 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) P ercent o f H o useho lds Chart 3.113 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percen t of H ou seh old s Chart 3.112 Number of Households by Source of Insecticides/Fungicides 3.3 4.2 4.6 22.3 65.5 0 2,000 4,000 6,000 8,000 10,000 Local Market / Trade Store Co-o peratives Neighbour Locally Produced by Households Local Farmers Group Source of Insecticide/fungicide Number of Households RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 3.10 Tree Planting. The number of households involved in tree farming was 12,796 representing 12 percent of the total number of agriculture households (Chart 3.114). The number of trees planted by smallholders on their allotted land was 3,903,785 trees. The average number of trees planted per households planting trees was 20 trees The main species planted by smallholders is Eucalyptus Spp (19,233 trees, 78.4%), followed by Gravellis (3,449 trees, 14.1%), Senna Spp (10161 trees, 4.1%). 1.94%). The remaining trees species were planted in comparatively small numbers (Chart 3.115 and Map 3.37). Kibondo had the largest number of smallholders with planted trees than any other district (44.7%) and the trees were dominated by Eucalyptus species and Gravellis. This was followed by Kasulu (37.0%) with Eucalyptus species and to a lesser extent Senna spp, Kigoma rural (17.4% dominated by Eucalyptus spp) then Kigoma urban (0.9% mainly Senna Spp). Chart (3.116) Chart 3.116 Number of Trees Planted by Smallholders by Species and District 0 5,000 10,000 15,000 20,000 Kibondo Kasulu Kigoma Rural Kigoma Urban Region Number of Trees Gravellis Senna Spp Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Casurina Equisetfilia Casurina Equisetfilia Tectona Grandis Maesopsis Berchemoides Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Moringa Spp Chart 3.114 Number of Households with Planted Trees . Households with Planted Trees, 23,768, 12% Households without Planted Trees, 171,997, 88% Chart 3.115 Number of Planted Trees by Specie 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 Eucalyptus Spp Gravellis Senna Spp Cyprus Spp Acacia Spp Maesopsis Berchemoide Moringa Spp Azadritachta Spp Casurina Equisetfilia Jakaranda Spp Syszygium Spp Tectona Grandis Tree Species Number of Trees RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 Smallholders mostly plant trees in the Plantation. The proportion of households that plant in plantation was 57 percent followed by scattered around the fields (22%) and then field boundary (21%) (Chart 3.117). The main purpose of planting trees was to obtain fuel wood (40.0%), this was followed by planks/timber (35.8%), shade (10.9%) poles (8.5%), medicinal (2.7 %), charcoal (1.2%) and other purpose (0.6 %), (Chart 3.118 and Chart 3.37) 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 19,370. This number represented 10% of total number of agricultural households in the region. (Chart 3.119) The proportion of farmers with soil erosion control and water harvesting facilities was highest in Kigoma rural (13%) followed by), Kasulu (9%), Kibondo (8%), and Kigoma urban (3%) Chart 3.120). (Map 3.38) Chart 3.119 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 176,395, 90% Households with facilities, 19,370, 10% Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities 9 8 13 3 0 3,000 6,000 9,000 Kigoma Rural Kasulu Kibondo Kigoma Urban District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.117 Number of Trees Planted by Location Field boundary, 729,986, 19% Scattered in field, 530,344, 13% Plantation, 2,643,455, 68% Chart 3.118 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Wood for Fuel Planks / Timber Shade Poles Medicinal Charcoal Other Use Percent of Households Kigoma Urban Kibondo Kasulu Kigoma Rural 4,329 829 2,001 6,802 4.6% 2.9% 5% 25.5% 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Kigoma Urban Kasulu Kigoma Rural 54,882 37,004 24,172 2,359 87.9% 46.6% 47% 94.7% Kibondo 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Receiving Crop Extension Services Map 3.35 KIGOMA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Map 3.36 KIGOMA Number and Percent crop Growing households using improved Seeds by district Number of Households Receiving Crop Extension Services Number of Households Using Improved Seeds Number of Households Using Improved Seeds Percent of Households Crop Growing Using Improved Seeds Percent of Total Households Receiving Crop Extension Services RESULTS 72 Kigoma Urban Kigoma Rural Kibondo Kasulu 0 0 933 974 0% 0.8% 1.5% 0% Kigoma Rural Kibondo Kasulu Kigoma Urban 11,732 3,893 7,866 436 18.8% 7.6% 9.9% 17.5% Tanzania Agriculture Sample Census Number of smallholder Map 3.37 KIGOMA Number and percent of smallholder Planted Trees by district Map 3.38 KIGOMA RESULTS 73 Number and Percent of Households With water Harvesting Bunds by District Number smallholder Planted Trees Number of Households With Water Harvesting Bunds Number of Households With Water Harvesting Bunds Percent of Households With Water Harvesting Bunds Percent smallholder Planted Trees 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 970 to 980 970 to 970 970 to 970 930 to 970 0 to 930 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 The erosion control bunds for 89.4% of the total number of structures builts; it was followed by terraces (3.2%), drainage ditches (3.0%), tree belts (2.4%), vertiver grass (0.5%), and dam (0.1%). 3.12 Livestock Results 3.12.1 Cattle Production The total number of cattle in the region was 422,361. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.5 percent of the total cattle population on Tanzania, Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Kigoma region was 421,613 (99.8 % of the total number of cattle in the region) and daily cattle were 748 cattle (0.2%), There were no improved beef breeds reported The census results show that 21,711 agricultural households (11.09% of the total agricultural households) kept 422,361 million cattle. This was equivalent to an average of 19 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Kigoma rural which had about 215,824 (51.1% of the total cattle in the region). This was followed by Kasulu (166,991 cattle, 39.5%) and Kibondo (38,908 cattle, 9.2%), and Kigoma urban (638 cattle, 0.2%) (Chart 3.122.and Map 3.39) .However, Kasulu district had the highest density (47 heads per Km2), Although Kigoma rural district had the largest number of cattle in the region, most of them were indigenous. There were no improved beef cattle or dairy cattle in the district. Kibondo district had the largest number of diary cattle in the region. (Chart 3.123) and Map 3.40). 0 50 100 150 200 250 Number of Cattle ('000') Kigoma rural Kasulu Kibondo Kigoma urban Districts Chart 3.122 Total Number of Cattle ('000') by District Chart 3.123 Number of Cattle by Type and District 0 40,000 80,000 120,000 160,000 200,000 240,000 Kigoma rural Kasulu Kibondo Kigoma urban Districts N u m b er of C attle Indigenous Beef Dairy Chart 3.121 Number of Erosion Control/Water Harvesting structures by Type of Facility 89.4 3.2 3.0 2.4 0.5 0.1 0 150,000 300,000 450,000 Erosion Control Bunds Terraces Drainage Ditches Tree Belts Vetiver Grass Dam T y p e o f F a cility Number of Structures Kigoma Rural Kigoma Urban Kibondo Kasulu 26.6 1.9 6.6 47.1 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Kigoma Rural Kigoma Urban Kibondo Kasulu 215,824 637 38,908 166,991 172,000 to 250,000 150,000 to 200,000 100,000 to 150,000 50,000 to 100,000 0 to 50,000 Tanzania Agriculture Sample Census Number of Cattle Map 3.39 KIGOMA Cattle Population by District as of 1st Octobers 2003 Cattle Density by District as of 1st October 2003 Number of Cattle Number of Cattle Per Square Km Number of Cattle Per Square Km Map 3.40 KIGOMA RESULTS 75 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.1.2 Cattle Herd Size About eighty percent of the cattle-rearing households had herds of size 1-5 cattle with an average of 3 cattle per household. Heads of size 6-30 cattle were owned by 6 percent of the cattle rearing households. Only 2 per cent of the cattle rearing households had herd sizes of 31-100 cattle. About 42.6 percent of the total cattle rearing households had herds of size 1-30 cattle and owned 20 percent of the total cattle in the region with an average of 4 cattle per cattle rearing household. There were about 517 households with herd sizes of more than 100 cattle each which together owned 291,661 cattle, resulting in an average of 564 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Kigoma increased during the period of five years from 111,800 in 1995 to 421,613 cattle in 2003. This trend implies an overall annual positive growth rate of 3.3 percent (Chart 3.124) However, the rate of increase was 1.1% over four year period from 1995 to 1999. 3.12.1.4 Dairy Cattle Breeds The total number of improved cattle in Kigoma region was 748 all of them being dairy cattle. The dairy cattle constituted 0.2 percent of the total cattle in the region. There were no improved beef cattle reported in region. The number of improved cattle increased from 182 in 1999 to 748 in 2003. The rate of growth was 4.1 over the period 1999 to 2003, there was no figure reported for 1995. Chart 3.125) 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Kigoma region ranked 13 out of the 21 regions with 3.6 percent of all total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Kigoma region was 75,496, (38.6% of all agricultural households in the region) with a total of 425,604 goats giving an average of 6 head of goats per goat-rearing-household. (Map 3.41) 111,800 128,000 421,613 - 150,000 300,000 450,000 Number of cattle 1995 1999 2003 Year Chart 3.124 Cattle Population Trend 182 748 - 200 400 600 800 1,000 Number of cattle 1999 2003 Year Chart 3.125 Dairy Cattle Population Trend 0 40 80 120 160 Number of Goats ('000'). Kibondo Kasulu Kigoma rural Kigoma urban District Chart 3.126 Total Number of Goats ('000') by District RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 77 Kibondo had the largest number of goats (148,799 goats, 35% of all goats in the region) followed by Kasulu and Kigoma rural each had 32 percent (136,156 for Kasulu and 136,239 goats for kigoma rural), Kigoma urban district had the least number of goats (4,410 goats, 1%) (Chart 3.125), However Kasulu district had the highest density (head 38 per km2) (Map 3.40) 3.12.2.2 Goat Herd Size Fifty four percent of the goat-rearing households had herds of size 1-4 goats with an average of 3 goats per goat rearing households. About 95 percent of total goat-rearing households had herds of size 1-14 goats and owned 78 percent of the total goats in the region resulting in an average of 5 goats per goat- rearing household. The region had 451 households (0.6%) with herd of 40 or more goats each (22,433 goats in total), resulting in an average of 50 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted about 99.6 percent of the total goats in Kigoma region. Improved goats for meat and diary goats constituted in very small percentages of total goats. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 1.2 percent. This positive trend implies eight years of population increased from 378,524 in 1995 to 425,604 in 2003. The number of goats increased from 378,524 in 1995 to 453614 in 1999 at an estimated annual rate of 0.9 percent but decreased from 453,614 in 1999 to 425,604 in 2003 at a negative growth rate of 1.6 % (Chart 3.127). 3.12.3 Sheep Production Sheep rearing was the third most important livestock keeping activity in Kigoma region after cattle and goats. The region ranked 14 out of 21 Mainland regions and had 1.3 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was estimated at 12,311 (6.2% of all agricultural households in Kigoma region) rearing 51,805 sheep, giving an average of 4 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Kigoma rural with 28,882 sheep, 55.8%) followed by Kasulu (16,533 sheep, 31.9%), Kibondo (5,502 sheep, 10.6%), and Kigoma urban District had the least number of sheep (888 sheep, 1.7%) Chart 3.128 and Map 3.43).Kasulu district had the highest density (5 head per km2) (Map 3.44). Sheep rearing was dominated by indigenous breeds that constituted 100 percent of all sheep kept in the region. No improved breeds were reported. 378,524 453,614 425,604 - 100,000 200,000 300,000 400,000 500,000 Number of goats 1995 1999 2003 Year Chart 3.127 Goat Population Trend 0 500 1,000 1,500 2,000 2,500 3,000 3,500 N u m b er o f s h eep Kigoma rural Kasulu Kibondo Kigoma urban District Chart 3.128 Total Number of Sheep by District Kigoma Urban Kigoma Rural Kibondo Kasulu 4,410 136,239 148,799 136,156 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Kigoma Rural Kigoma Urban 16.8 25.4 38.4 Kasulu Kibondo 12.9 33.3 to 38.4 28.2 to 33.3 23.1 to 28.2 18 to 23.1 12.9 to 18 Tanzania Agriculture Sample Census Number of Goat Map 3.41 KIGOMA Goat population by District as of 1st Octobers 2003 Goat Density by District as of 1st October 2003 Number of Goat Number of Goat Per Square Km Number of Goat Per Square Km Map 3.42 KIGOMA RESULTS 78 Kigoma Urban Kigoma Rural 2.6 3.6 4.7 0.9 Kasulu Kibondo 33.3 to 38.4 28.2 to 33.3 23.1 to 28.2 18 to 23.1 12.9 to 18 Kibondo Kasulu Kigoma Urban Kigoma Rural 5,502 16,533 888 28,882 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tanzania Agriculture Sample Census Number of Sheep Map 3.43 KIGOMA Sheep population by District as of 1st Octobers 2003 Sheep Density by District as of 1st October 2003 Number of Sheep Number of Sheep Per Square Km Number of Sheep Per Square Km Map 3.44 KIGOMA RESULTS 79 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 80 3.12.8.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at 1.4percent. The population increased at an annual rate of 1.1 percent from 36423 in 1995 to 42,768 in 1999,then at a rate of 1.2 percent from 42.768 in 1999 to 51,805 in 2003 (Chart 3.129).. 3.12.4. Pig Production 3.12.4.1 Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 10 out of 21 mainland regions, and had 2.4 percent of all pigs of Tanzania mailand. The number of pig- rearing agricultural households in Kigoma region was 5221 (2.6% of the total agricultural households) rearing 23,698 pigs. This gives an average of 5 pigs per pig-rearing household. The district with the largest number of pigs was Kasulu with 11,444 pigs,(48.3 % of the total pig population in the region) followed by Kigoma rural (9,914 pigs, 41.8%), Kibondo (1,689 pigs, 7.1%) and Kigoma urban (652 pigs, 2.7 %) (Chart 3.130). However, Kasulu district had the highest density (3.2 head per km2) (Map 3.45). 3.12.4.2 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 4.5 percent. During this period the population increased from 5,230 in 1995 to 23,698 in 2003. The growth rate was 1.9 percent during the four years from 1999 to 2003 in which pig population increased from 12,434 to 23,698 (Chart 3.131 and Map 3.46) 3.12.5 Chicken Production The poultry sector in Kigoma region was dominated by chicken production. The region contributed 2.4 percent to the total chicken population for Tanzania Mainland. 36,423 42,768 51,805 - 20,000 40,000 60,000 Number of sheep 1995 1999 2003 Year Chart 3.129 Sheep Population Trend 0 3,000 6,000 9,000 12,000 Number of Pigs Kasulu Kigoma rural Kibondo Kigoma urban District Chart 3.130 Total Number of Pigs by District 5,230 12,434 23,698 - 6,000 12,000 18,000 24,000 Number of pigs 1995 1999 2003 Year Chart 3.131 Pig Population Trend 36,423 42,768 51,805 - 20,000 40,000 60,000 Number of sheep 1995 1999 2003 Year Chart 3.129 Sheep Population Trend Kigoma Urban Kigoma Rural 1.9 1.2 0.3 3.2 Kasulu Kibondo 2.7 to 3.2 2.1 to 2.7 1.5 to 2.1 0.9 to 1.5 0.3 to 0.9 Kigoma Urban Kigoma Rural 652 9,914 11,444 1,689 Kasulu Kibondo 8,000 > 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Number of Pig Map 3.45 KIGOMA Pig population by District as of 1st Octobers 2003 Pig Density by District as of 1st October 2003 Number of Pig Number of Pig Per Square Km Number of Pig Per Square Km Map 3.46 KIGOMA RESULTS 81 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.5.1 Chicken Population The number of households keeping chicken was 81,952 raising about 797,537 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Kigoma ranked eighteenth out of the 21 Mainland regions. The District with largest number of chicken was Kigoma rural (371,692 chickens, 46.6% of the total number of chickens in the region) followed by Kasulu (211,326 26.5%), Kibondo (202,592 25.4%), and Kigoma urban (11,926 1.5%). (Chart 3.132 and Map 3.47). However Kasulu district had the highest density (59 head per km2) (Map 3.48) 3.12.5.2 Chicken Population Trend The overall annual growth rate during the eight-year period from 1995 to 2003 was 1.1 percent. The population increased at a rate of 1.05 percent from 1995 to 1999 (Chart 3.133). Ninety eight percent of all chickens in Kigoma region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chickens’ more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 87 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 6 chickens per holder. About 12 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 34 chickens per holder. Only 0.2 percent of holders had the flock sizes of more than 100 chickens with an average of 190 chickens per hold (Table 3:14) Table 3:14 Total Number of Households and Chickens Raised by Flock Size Chicken rearing Households Flock size Number % Number of Chicken Average chicken by households 1 - 4 33,489 41.3 85,545 3 5 - 9 22,305 27.5 148,227 7 10 - 19 15,108 18.6 191,735 13 20 - 29 4,547 5.6 103,594 23 30 - 39 3,407 4.2 111,065 33 40 - 49 712 0.9 28,640 40 50 - 99 1,433 1.8 102,695 72 100+ 137 0.2 26,036 190 Total 81,139 100 797,537 10 0 100,000 200,000 300,000 400,000 N u m b er o f C h ick en s Kigoma rural Kasulu kibondo Kigoma urban District Chart 3.132 Total Number of Chickens by District 723,325 762,577 797,537 - 200,000 400,000 600,000 800,000 1,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.133 Chicken Population Trend Kigoma Urban Kigoma Rural 34.9 45.7 34.6 59.6 Kasulu Kibondo 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 Kigoma Rural Kigoma Urban Kibondo 371,692 11,926 211,326 202,592 Kasulu 320,000 to 400,000 240,000 to 320,000 160,000 to 240,000 80,000 to 160,000 0 to 80,000 Tanzania Agriculture Sample Census Number of Chicken Map 3.47 KIGOMA Chicken population by District as of 1st Octobers 2003 Chicken Density by District as of 1st October 2003 Number of Chicken Number of Chicken Per Square Km Number of Chicken Per Square Km Map 3.48 KIGOMA RESULTS 83 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.12.5.4 Improved chicken breeds (layers and broilers) Layers population in Kigoma region region increased at an annual rate of 76 percent for the period of four years from 1090 in 1999 to 10,349 in 2003 while broilers population decreased at annual rate of 35% from 10159 in 1999 to 1879 in 2003. The number of improved chicken was most significant in Kigoma rural district followed by Kigoma urban district (Chart 3.134) 3.12.6 Other livestock There were 51,782 ducks, 592 turkeys, 9,935 donkeys in rural agricultural households of Kigoma region. Table 3-15: indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Kigoma rural district. (67% of all ducks in the region)., followed by Kibondo (23%), Kasulu (9%), and Kigoma urban (1.5%). Table 3.15:Head Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Donkeys Other Kibondo 11,786 0 7,963 0 Kasulu 4,493 592 1,972 2,171 Kigoma rural 34,730 0 0 2,015 Kigoma urban 773 0 0 0 Total 51,782 592 9,935 4,186 9,542 1,879 807 0 0 0 0 0 0 2,000 4,000 6,000 8,000 10,000 N u m b er o f C h ick en s Kigoma rural Kigoma urban Kibondo Kasulu District Chart 3.134 Number of Improved Chicken by Type and District Layers Broilers 1,090 10,159 10,349 1,879 - 5,000 10,000 15,000 Number of layers 1999 2003 Year Chart 3.135 Layers Population Trend RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.12.7 Pests and Parasites Incidences and Control Ticks problems were reported by 50 percent of livestocks-keeping households while tsetsefly problems were reported by 6 percent of such households. (Chart 3.136) shows that there was predominance of tick related diseases over tsetsefly related diseases. Incidences of both problems were highest in Kasulu district but lowest in Kigoma urban district. (Map 3.49). The most practiced method for controlling ticks was spraying with 40 percent of all livestock-rearing households having the problem using that method. Other methods used were dipping (34%), other traditional methods like hand picking (5%), and smearing (1%) However, 20% of livestock-keeping households did not use any method. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 36,738 (61% of the total livestock rearing households in the region), cattle 20,111 households (93%), goats 22,391 households (30%), sheep 6,791 households (55%), pigs 5024 households (10%) (Chart 3.137). 3.12.8. Access to livestock services 3.12.8.1 Access to livestock extension services The total number of households that received livestock advice was 56,251 representing 93 percent of the total livestock rearing households and 29 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 97.7 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (0.7%); Co-operatives (0.9%) and large farms (0.7). Chart 3.136 Percentage of Livestock Keeping Households that Reported Tsetseflies and Tick Problems by District. 0 20 40 60 80 Kasulu Kibondo Kigoma rural Kigoma urban District Percent Ticks Tsetseflies 0 10 20 30 40 50 60 70 P ercen t Kibondo Kasulu Kigoma rural Kigoma urban District Chart 3.137 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 About 48 percent of livestock rearing households described the general quality of livestock extension services as being good, 23 percent said they were very good, average (24%). However 2 percent of the livestock rearing households said the quality was not good whilst 2 percent described them as poor. (Chart 3.138) 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 55 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 45 percent of the them accessed services within 14 kms from their dwellings (Chart 3.139). The most affected district was Kibondo district with livestock rearing households accessing the services at a distance of more than 14 kms. Kigoma urban district was not affected because about 100 percent of the households could access the service less than a distance of 14 kilometers. 3.12.8.3 Access to Village Watering Points/Dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 7,718 (98% of the reporting livestock rearing households in Kigoma region) whilst 197 households (2%) resided between 5 and 9 kms from the watering point. (Chart 3.141) Chart 3.138 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 2% Very Good 23% Good, 48% Average, 24% Poor, 2% Chart 3.139 Number of Households by Distance to Verinary Clinic Less than 14km, 10,470, 55% More than 14km, 8,691, 45% Chart 3.140 Percentage of Households by Distance to Verterinary Clinic and District 0 50 100 Kigoma urban Kigoma rural Kasulu Kibondo District P ercen ta g e o f H o u s eh o ld s Less than 14 kms More than 14kms Chart 3.141 Number of Households by Distance to Village Watering Points 5-9 kms, 197, 2% Less than 5 kms, 7,718, 98% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 Kasulu district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Kibondo and Kigoma rural districts. Also in Kasulu district about 2 percent of the livestock rearing households had to travel a distance of between 5 and 9 kilometers to the nearest watering point (Chart 3.142). 3.12.9 Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Kigoma region was very limited with only 671 households (0.34% of the total agricultural households in the region) using them (Chart 3.143). Kigoma rural 474 households (70.6% of household using draft animals in the region) and Kasulu (197 households, (29.4%), Use of draft animals was not reported in Kibondo and Kigoma urban district. The region had 5,071 oxen, all in Kigoma rural and were used to cultivate 1,811 hectares of land. This represented only 0.2% of the total oxen found on the Mainland. (Map 3.50). 3.143 Number of Households Using Draft Amimals Using draft animal, 671, 0.3% Not using draft animal, 195,094, 99.7% 0 100 200 300 400 500 Number of Households Kigoma rural Kasulu Kibondo Kigoma urban District Chart 3.144 Number of Households Using Draft Animals by District Chart 3.142 Number of Households by Distance to Village Watering Point and District 0 2,000 4,000 6,000 Kasulu Kibondo Kigoma rura; District Number of Households Less than 5 kms 5-9 kms Kigoma Urban Kigoma Rural Kasulu Kibondo 0 474 197 0 0.8% 0% 0.2% 0 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Kigoma Urban Kigoma Rural Kibondo Kasulu 134 5,017 8,784 14,914 32 51 60 22 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanzania Agriculture Sample Census Number of Household Map 3.49 KIGOMA Number and Percent of Households Infected with Ticks by District Number and Percent of Households Using Draft Animals by District Number Households Infected with Ticks Number of Household Number Households Using Draft Animals Map 3.50 KIGOMA Percent Households Infected with Ticks Percent Households Using Draft Animals RESULTS 88 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 89 3.12.9.12 Use of Organic Fertilizers The number of households using farm yard manure in Kigoma region was 41,110 (21% of the total crop growing households in the region) (Chart 3.145). The total area applied with organic fertilizer was 22,360 hectares of which 8051 hectares (36 percent of the total area applied with organic fertilizer of the area planted with annual crops and vegetables in Kigoma region during the long rainy season was applied with farm yard manure. 3.13 Fish Farming The number of households involved in fish farming in Kigoma region was 193, representing 0.1 percent of the total agricultural households in the region (Chart 3.148) Kasulu was the only district with fish farming households Fish farming was not practiced in the remaining three districts. (Chart 3.147). The only source of fingerings was the government/institutions. All fish farming households in the region used the dug-out pond system and the main fish specie planted was Tilapia. The number of fish harversted in Kigoma region was 4,825 all of them were Tilapia. ( Chart 3.149) .None of the fish farming households sold any fish. (Map 3.51) Chart 3.145 Number of Households Using Organic Fertilisers Not Using Organic Fertilizer, 151,824, 79% Using Organic Fertilizer, 41,110, 21% Chart 3.146 Area of Application of Organic Fertilisers by District - 0 2000 4000 6000 8000 Kasulu Kibondo Kigoma rural Kigoma urban District A rea of Fertiliser A pplication (ha) Farm Yard Manure Compost Chart 3.147 Number of Households Practicing Fish Farming Households Prcticing Fish Farming, 193, 0.1% Households Not Prcticing Fish Farming, 195,572, 99.9% Chart 3.148 Fish Production Number of Tilapia, 4,825, 100.0% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 90 3.14 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was the service that was located very far from most of the household’s dwellings. It was located at an average distance of 129 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (87.0), hospital (50.3), tertiary market (26.1) secondary school (22.3), secondary market (18.4), all weather roads (9.0), primary market (6.1 ), health clinic (5.6), feeder road (2.0) and primary school (1.5) (Table 3.15). 3.15 Poverty Indicators The agricultural census collected data on poverty for the purpose of providing the basis for tracking progress in poverty reduction strategies undertaken by the government 3.15.1 Type of toilets A large number of rural agricultural households use traditional pit latrines (185.014 households, 94.5% of all rural agricultural households). Other types of toilets were used as follows flush toilets (4,119 households 2.1%). improved pit latrines (1,237 households 0.6%), However, 5,396 households (2.8%) had no toilet facilities (Chart 3.149). The distribution of the households without toilets within the region showed that 60.7 percent of them were found in Kibondo district and 19.8 percent were from Kigoma rural. The percentages of households without toilets in other districts were as follows Kasulu (18.2%) and and Kigoma rural (1.2%). (Map 3.52) Table 3.16 Mean Distance from Household Dwelling to Infrastructures and Services by District. District Secondary School Primary School All weath er road Feeder Road Hospital Health Clinic Regional Capital Primary Market Secondary Market Tertiary Market Tarmac Road Kibondo 17.8 1.8 2.0 1.3 37.7 9.1 224.3 4.7 20.8 19.0 105.5 Kasulu 24.7 1.3 15.0 1.1 42.2 4.3 108.6 8.0 22.4 31.3 90.3 Kigoma Rural 23.6 1.7 7.3 3.9 72.5 4.4 81.8 5.1 11.5 26.1 70.9 Kigoma Urban 3.8 1.2 0.8 0.3 7.0 1.7 7.6 3.5 17.8 5.8 5.2 Total 22.3 1.5 9.0 2.0 50.3 5.6 129.1 6.1 18.4 26.1 87.0 Chart 3.149 Percentage Distribution of Agricultural Households by Type of Toilets Traditional Pit Latrine, 185,013, 94.5% Flush Toilet, 4,118, 2.1% No Toilet , 5,396, 2.8% Improved Pit Latrine , 1,237, 0.6% Kigoma Urban Kigoma Rural Kibondo Kasulu 64 1,090 3,277 984 1.7% 2.5% 6.4% 1.2% 2,800 to 3,500 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Kigoma Urban Kigoma Rural Kasulu 193 0 0 0 0.3% 0% 0% 0% Kibondo 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Tanzania Agriculture Sample Census Number of Households Map 3.51 KIGOMA Number and Percent of Households Practicing Fish Farming by District Number and Percent of Households Without Toilets by District Number of Households Practicing Fish Farming Number of Households Number of Households Without Toilets Map 3.52 KIGOMA Percent of Households Practicing Fish Farming Percent of Households Without Toilets RESULTS 91 RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.15.2 Household’s Assets Radio are owned by most rural agricultural households in Kigoma region with 114,459 households,(58.5% of the agricultural households in the region) owning this asset, followed by bicycle (86,895 households, 44.4%), iron (23,536 households, 12.0%), wheelbarrow (5450 households, 2.8%), mobile phone (1,404 households 0.7%), television/video (1,138 households, 0.6%), vehicle (678 households 0.3%) and landline phone (32 households, 0.01%) (Chart 3.152). 3.15.3 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region with 78.5 percent of the total rural households using this source of energy followed by hurricane lamp (12.0%), firewood (5.0%), and pressure lamp (4.2%), mains electricity (0.2%). The rest of energy sources accounted for l 0.2 percent of the households, (Chart 3.151). 3.15.4 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households in Kigoma region. This was followed by charcoal (2.7%). The rest of energy sources accounted for 1 percent. These were bottled gas (0.1%), crop residues (0.5%), mains electricity (0.1%). Chart 3.150 Percentage Distribution of Households Owning the Assets 2.8 0.7 0.6 0.3 0.1 58.5 44.4 12.0 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 9,707, 5.0% Solar, 133, 0.1% Hurricane Lamp, 23,580, 12.0% Pressure Lamp, 8,210, 4.2% Mains Electricity, 358, 0.2% Wick Lamp, 153,640, 78.5% Chart 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking Gas, (bottled) 197, 0.1% Crop Residues, 914, 0.5% Mains Electricity, 204, 0.1% Charcoal, 5,772, 2.72% Firewood, 187,993, 96.4% RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 3.15.5 Roofing Materials The most common material used for roofing the main dwelling was grass and/or leaves and it was used by 61.5 percent of the rural agricultural households. It was followed by iron sheets (27.4%), then grass/mud (8.0%), tiles (2.0%), asbestos and concrete (0.5%) each, and others (0.1%). (Chart 3.153 and Map 3.53). Kigoma rural district had the highest percentage of households with grass/leaves roofs (37%), and was followed by Kasulu (36%), Kibondo (26%), and Kigoma urban (1%). (Chart 3.154) 3.15.6 Access to Drinking Water The main source of drinking water for agricultural households in Kigoma region was the piped water (24.0% of households use piped water during the wet season and 20.9% of the households during the dry seasons. This was followed by surface water 19.0% during the wet season and 21.5% during the dry season, unprotected well (17.3% of households during the wet season and 18.7% the dry season), protected well (15.5% during the wet season and 15.7% during the dry season), protected spring (14.1% in the wet season and 14.3% in the dry season), unprotected well (8.5% in the wet and 7.6% in the dry season), the remaining source had less than 2 percent (Chart 3.155) About 59 pecent of the rural agricultural households in Kigoma region obtain drinking water within a distance of less than one kilometer during wet season compared to 55 percent of the households during the dry season. Chart 3.153 Percentage Distribution of Households by Type of Roofing Material Concrete 0.5% Others 0.1% Tiles 2.0% Grass / Leaves 61.5% Iron Sheets 27.4% Grass & Mud 8.0% Asbestos 0.5% Chart 3.154 Percentage Distribution of Households with Grassy/Leafy Roofs by District 1 26 36 37 0 25 50 Kigoma rural Kasulu Kibondo Kigoma urban District P e r c e n t Chart 3.156 Percentof Households by Distance to Main Source of Drinking Water and Season 0.0 5.0 10.0 15.0 less than 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and abov Distance P e r c e n t wet season Dry season Chart 3.155 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Piped Water Sueface water Unprotected well Protected well Protected spring Unprotected spring Main source Percent of Households Wet Season Dry Season RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 However, 41 percent of agricultural households obtained drinking water from a distance of one or more kilometers during the wet season compared to 44 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.157). 3.15.7 Food Consumption Pattern 3.15.7 .1 Number of Meals per Day The majority of households in Kigoma region normally had two meals per day (80.5 percent of the households in the region), this is followed by 3 meals per day (16 percent) and 1 meal per day (3.3 percent). Only 0.2 percnt of the households have 4 meals per day (Chart 3.158 and Map 3.54). Kibondo district had the largest percentage of households eating one meal per day whilst Kigoma urban had the highest percentage of households eating 3 meals per day (Table 3.17) 3.15.7.2 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 91,137 (46.5% of the agricultural households in Kigoma region) with 58,716 households (64.4% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (22.1%). Very few households had meat meat three or more times during the respective week. About 53.4 percent of agricultural households in Kigoma region did not eat meat during the week preceding the census. (Map 3.55). Chart 3.17: Number of Households by Number of Meals the Household Normally had per Day and District Number of meals per day District One % Two % Three % Four % Total Kibondo 3,623 7.0 43,556 84.7 4,219 8.2 0 0.0 51,407 Kasulu 1,174 1.5 66,132 83.3 11,897 15.0 194 0.2 79,396 Kigoma rural 1,719 2.8 45,956 73.6 14646 23.4 194 0.2 62,470 Kigoma urban 0 0 1,854 74.4 638 25.6 0 0.0 2,492 Total 6,516 3.3 157,507 80.5 31399 16.0 343 0.2 195,765 Chart 3.157 Number of Agriculural Households by Number of Meals per Day One Meals,6,515 3.3%. Three Meals, 31,399, 16.0% Two Meals, 157,507, 80.5% Four Meals, 343, 0.2% Chart 3.158 Number of Households by Frequency of Meat and Fish Cosumption 0 25,000 50,000 75,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency N u m b er o f H o u s eh o ld s Meat Fish RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 3.15.7.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 118,852 (60.7% of the total agricultural households in Kigoma region) with 37,834 households (31.8% of those who consumed fish) consuming fish once during the respective week. The number of households that consumed fish twice or more during the week in Kigoma region was 81,018. (68.1% of the agricultural households, that ate fish in the region during the respective period). About 39.3 percent of the agricultural households in Kigoma region did not eat fish during the week preceding the census (Chart 3.158 and Map 3.56) 3.15.8 Food Security In Kigoma region, 124,132 households (63% of the total agricultural households in the region) said they never experienced problems in satisfying the household food requirement. However 42,476 (22%) said they rarely experience problems, 26% had sometimes experienced problems and 4 percent always had problems with satisfying the household food requirements. About 3.4 percent of the agricultural households said they had often experience food sufficiency problems. (Map 3.57) 3.15.9 Main Sources of Cash Income The main cash income of the households in Kigoma region was from the selling of food crops (69.2 percent of smallholder households), followed by casual labour (9.4%), business income (6.0%), sales of cash crops (5.2%), fishing (3.2%), wages& salaries (3.1%),sales of forest products (2.7%), cash remittances (2.3%), livestock 1.7%, livestock products (0.8%), others (0.6%) and not applicable (0.8%) (Chart 3.159). Chart 3.159: Percentage Distribution of the Number of Households by Main Source of Income Other, 2% Food Crops, 63% Business Income, 6% Other Casual Cash Earnings, 9% Cash crops, 5% Fishing, 3% Wages & Salaries, 3% Livestock, 2% Cash remittance, 2% Livestock products, 1% Not applicable, 1% Forest Products 3% Kigoma Urban Kigoma Rural Kasulu 638 14,646 4,219 11,897 23.4% 8.2% 15% 25.6% Kibondo 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Kigoma Urban Kibondo Kasulu Kigoma Rural 1,459 31,178 43,587 44,097 1.2% 25.9% 36.2% 36.6% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Map 3.53 KIGOMA Number and Percent of Households Using Grass/Leaves for Roofing Material by District Number and Percent of Households Eating 3 Meals Per Day by District Number of Households Using Grass/Leaves For Roofing Material Number of Households Number of Households Eating 3 Meals Per Day Map 3.54 KIGOMA Percent of Households Using Grass/Leaves For Roofing Material Percent of Households Eating 3 Meals Per Day RESULTS 96 Kigoma Urban Kigoma Rural Kasulu 532 8,234 7,878 21,191 21.8% 1.4% 20.8% 56% Kibondo 16,000 > 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Kigoma Urban Kigoma Rural Kasulu Kibondo 968 24,191 21,188 12,369 38.7% 38.8% 26.7% 24.1% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Tanzania Agriculture Sample Census Number of Households Map 3.55 KIGOMA Number and Percent of Households Eating Meat Once Per Week by District Number and Percent of Households Eating Fish Once Per Week by District Number of Households Eating Meat Once Per Week Number of Households Number of Households Eating Fish Once Per Week Map 3.56 KIGOMA Percent of Households Eating Meat Once Per Week Percent of Households Eating Fish Once Per Week RESULTS 97 Kigoma Urban Kigoma Rural Kibondo Kasulu 98 474 5,036 965 7.2% 1.5% 76.6% 14.7% 4,800 to 6,000 3,600 to 4,800 2,400 to 3,600 1,200 to 2,400 0 to 1,200 Tanzania Agriculture Sample Census Number of Households Map 3.57 KIGOMA Number and percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency RESULTS 98 Percent of Households Reporting Food Insufficiency RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 4.0 KIGOMA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Kigoma Region Profile The regional profile describes the status of agriculture sector in the region and compares it with other region in the country. Kigoma region has a land area of 265,000 hectares under crop production and it has an average number of crop growing households compared to other regions with the majority being crop only growing households. The land area under crop production per crop growing households is 1.3 ha and it has a low rate of utilization compared to the total land available to smallholders. The number of crop growing households per square kilometer is low to moderate. The regional has a moderate area planted with permanent crops. It has two rainy seasons with the same planted area in each. Kigoma is one of the least important regions for cereal production even though the yield is higher than many other regions with larger planted areas, very small areas of paddy and sorghum are grown. The most important annualcrop in Kigoma is beans and it has one of the highest productions The region also has the fourth largest planted area of cassava in Tanzania. Small to moderate quantities of groundnuts are also grown. The production of vegetables and cash crops is relatively unimportant compared to other regions. The major permanent crop in Kigoma is oil palm and it has 60 percent of the total planted area of the crop in Tanzania. It also the fourth largest planted areas of bananas and oranges. In relative terms, Kigoma has a moderate planted area with irrigation compared to other regions and it appears that there has been a large increase in the number of households with irrigation over a period of 10 years. Most of the irrigation water is obtained from rivers and the method of obtaining water is equally split between buckets /watering cans and gravity. Field application of irrigation water is mainly by bucket/watering cans and this is closely followed by flood. All land preparation is done by hand and only a small proportion of the planted area has farm yard manure. Very little pesticides are use. Storage is normally in sacks or open drum. The region has one of the highest percent of households selling crops. Most processing was done by neighbours machine, however the region has the highest percent of processing done by traders. A large number of the households in Kigoma sell their processed crop, mostly in the local market or trade store the percentage of smallholder households receiving extension services is one of the highest in the country. Moderate numbers of eucalyptus is planted in the region and most of the erosion facilities are bunds. Kigoma can be characterized as a low livestock producing region with fish from Lake Tanganyika possibly substituting livestock as a source of protein. It has a small livestock population with approximately equal numbers of cattle and goats which are almost entirely indigenous. Very little milk is produced and the farm gate price is average. It has very few sheep and pigs. Kigoma has the 4th smallest chicken population in the country. A small area of organic fertilizer is applied and those that do apply it to a small area, possibly reflecting the low availability. Very little land is cultivated using draft animals. Apart from the high rate of helmininthiosis, Kigoma has one of the lowest disease infection rates. RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 Acces to livestock services is moderate to good. In relation to livestock population it receives disproportionately more extension advice compared to other regions with much higher livestock populations. Little fish farming is carried out in the region. 4.2 District Profiles The following district profiles highlight the characteristics of each district and compare them in relation to population. main crops, livestock, production, productivity, access to services, resources and levels of poverty. 4.2.1 Kibondo Kibondo district had the second lowest number of households in the region and it has also the third largest percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kibondo district was annual crop farming, followed by permanent crop farming. The district had the second highest percent of households with no off farm income activities, as well as the lowest percent of households with more than one member with off farm income. Kibondo had a relatively high percent of female headed households (19%) and it had one of the lowest average age of the household heads in the region, with a household size of five members per households and it is average for region. Kibondo had a moderate literacy rate among smallholder households. The literacy rate for the heads of households was slightly higher than most districts in the region. The district has the second lowest planted area in the region and among the largest planted area per households (0.3ha in the long rainy season and 0.4 ha in the short rainy season), the district was important for maize production in the region with a planted area of over 27195 ha, and the planted area per maize growing household was the highest in the region. The district had the moderate planted area of paddy in the region with 954 hectares. The planted area for sorghum was the largest in the region. Cassava production was moderate, accounting for 7 percent of the quantity harvested in the region. The district had no planted area of Irish potatoes. The production of beans in Kibondo was smaller than in other districts. Kibondo district had the second largest groundnut planted area in Kigoma region with a planted area per groundnut growing household of 0.34 ha. Vegetables production was moderate. Traditional cash crops (e.g. tobacco and cotton) were grown in small quantities. Compared to other districts, Kibondo has the second lowest planted area for permanent crops which were dominated by banana (7,586 ha), coffee (426 ha) mango (326 ha) and avocado (202 ha). Other permanent crops were either not grown or grown in very small quantities. As with other districts in the region, most land clearing was done by bush clearance and tractor slashing; however there was a substantial area with no land clearing indicating bare ground before planting. Practically all land preparation was done by hand, however a very small amount of land preparation was done by tractor. The use of farm inputs in the region is very small, however district differences exist. Kibondo had the lowest planted area with improved seed in the region as well as the highest proportion of households not using improved seeds. Though small, the district had the second highest planted area with fertilizers (farm yard manure, compost and inorganic fertilizer), and most of this was with farm yard manure. Compared to other districts, Kibondo districts had a RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 moderate level of insecticides use, the use of herbicides was not reported. It had lower percent area with irrigation compared to other districts with 409 ha of irrigated land. The most common source of water for irrigation was from rivers using hand gravity, flood and bucket are the most common means of irrigation water application, no amount of sprinkler irrigation is used. The most common method of crop storage in Kibondo district was in locally made traditional cribs; however the proportion of households not storing crops was average for the region. Kibondo had lower number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. Kibondo was among the districts with the highest percentage of the households processing crops in Kigoma region and this was almost all done by neighbourrs machine. The district also had the second lowest percent of households selling crops to local market and trade store compared to other districts and no sales to large scale farms, although very small access to credit in the district was to male-headed households only and main sources were the commercial bank and religious organization/NGO/ Project. Moderate number of households received extension services in Kibondo district and most of this was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not very important in Kibondo (with 10,936 planted trees) and mostly Gravellis and Eucalyptus. The second lowest percentage of households with erosion control and water harvesting structures was found in Kibondo district mostly erosion control bunds and drainage ditches, however it also had some vertiver grass and tree belts. The district had the third largest number of cattle in the region and they were almost all indigenous. Goat production was the highest in the region; however it had the second lowest population of sheep in the region and a moderate number of pigs and chickens. Some ducks and donkeys were also found in the district. A number of households reported tsetse and tick problems and it had the second lowest number of households deworming livestock. No household reported to use draft animals, also no household reported to practice fish farming. It had amongst the best access to primary schools, health clinics and primary markets and feeder roads compared to other districts. However, it had one of the worst accesses to district capital and tarmac roads. The percentage of households without toilet facility in Kibondo district was comparatively high 6.3 percent. Also it was amongst the districts with the lowest percent of households owning wheel barrows, vehicles, bicycles tv/video and mobile phones. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing material for most of the households in the districts was grass/leaves (61%) and iron sheets (28%). The most common source of drinking water was the unprotected well. It is one of the districts with the highest percent of households having two meals per day. The district had third low highest percent of households that did not eat meat and the lowest percent of households that did not eat fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.2 Kasulu Kasulu district had the largest number of households in the region and it had one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only followed by crop and livestock farming. Neither livestock only nor pastoralists were found in the district. RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 The most important livelihood activity for smallholder households in Kasulu district was annual crop farming, followed by permanent crop farming. However, the district had the highest percent of households with no farm incomes activities (43%), and also the second lowest percent of households with two or more members with off-farm income. Compared to other districts in the region Kasulu had relatively low percent of female headed households (11%) Its average households size of 5 members per households was equal to the average household size for the region. Kasulu had a comparatively high literacy among smallholder households’ members (69%), and the literacy rate for the heads of households was also the highest in the region. The land area utilized per household (2.0 ha) was slightly higher than the regional average of (1.9 ha). The district had the largest planted area in the region and among the largest planted area per household (0.4 ha) in the long rainy season but among the lowest planted area per household (0.3 ha) in the short rainy season. The district was very important for maize production in the region with a planted area of over 36,958 ha and the planted area per households was 0.5 ha which was more than average for region of is 0.4 ha. Paddy production was also important with a planted area of 1,959 hectares. Sorghum planted area was the second highest in the region. The district had larger planted area of cassava accounting 44 percent of the cassava planted area of 75,675. Oilseeds and vegetables are important in Kasulu with 31.6 percent of the groundnuts planted area being in the district. Permanent crops are important in Kasulu district 47% of the total permanent crop planted area in Kigoma region. The permanent crops in the district include palm oil (8,747 ha), orange (543 ha) and bananas (2,762 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, and a relatively small area of bare ground before planting. Practically all land preparation was done by hand, however a very small amount of land preparation was done by burning. The use of inputs in the region was very small, however district differences existed, Kasulu had a small area planted with improved seeds. The district also had a small planted area applied with fertilizers (farm yard manure, compost and inorganic fertilizer) but practically all of it was farm yard manure. Compared to other districts in the region, Kasulu district had the larger area of insecticide and fungicide use also the use of herbicides was relatively large. It had the largest area of irrigation in the region with 2,186 ha of irrigated land. The most source of water for irrigation was mostly the river and almost all water application was done by gravity and the hand bucket. The most common method of crop storage in Kasulu was locally made traditional cribs. The proportion of households not storing crops in the district was moderate to low when compared to other districts in the region. The district had the highest percent of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. Kasulu district had a high percent of households processing crops in the region and almost all the processing was done by neighbour machine. No processed crops were sold and very few households had access to credit. A moderate number of households received extension services in Kasulu district and almost all of these were from the government and NGO/Development/ Project. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Kasulu district (with 9,066 planted trees) and most of the trees grown were Eucalyptus spp and Sienna Spp. The second highest proportion of households with water harvesting bunds was found in Kasulu RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 district and it also had the largest number of erosion control bunds. The district had a large number of cattle in the region and they were almost all indigenous. Goats and sheep production was high compared to other districts. The district had the largest number of pigs in the region and second largest number of chickens, all of which were indigenous. Virtually no improved chickens were found in the district. The district had a moderate number of ducks, and a small number of donkeys and turkeys were found in the district. A small number of households reported tsetse and tick problems in Kasulu district. A largest amount of de-worming of livestock was practiced in the district; also it had a very small number of households using draft animals and a few households’ practiced fish farming. The percentage of households without toilet facility in Kasulu district was lowest in the region and it had the highest percent of households owing radios, and bicycles. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a high percent of households with grass roofs 55 percent and 27 percent of households had iron sheet roofing. The most common source of drinking water was from protected wells. Eighty three percent of the households in the district reported having two meals per day. The district had a high percent of households that did not eat meat or fish during the week prior to enumeration and most households never had problems with food satisfaction. 4.2.3 Kigoma Rural Kigoma rural district had second largest number of households in the region and it had the large percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock farming. It had a very small number of livestock only households and few pastoralists were found in the district. The most important livelihood activity for smallholder households in Kigoma rural district was annual crop farming, followed by permanent crop farming. It had the second highest percent of households with no off-farm income activities and the second high percent of households with more than one member involved in off-farm income activities. Compared to other districts in the region, Kigoma rural district had a relatively low percent of female headed households (15%) and it had one of the high average ages of the households’ heads. Its average household size of 6 members per households was more than the average household size for the region. Kigoma rural district had a comparatively moderate literacy rate among smallholders. It had the highest utilized area per household (2.2 ha) which was more than the regional average of 2.0 ha. The district was important for maize production in the region with a planted area of 16,958 ha and the planted area per households was among the highest in the region. Paddy production was moderately important with a planted area of 1,859 hectares and the production of sorghum was very small. Cassava and beans production in Kigoma rural district was a bit higher than in other districts, Irish potatos and wheat were not grown. Oilseeds crops and vegetables were moderately important in the district, however, whilst the district had one of the largest areas planted with groundnuts; other crop seeds were not grown of the traditional crops (e.g. tobacco and cotton), cotton production was not very much important crop, whilst tobacco production was high. Compared to other district in the region, Kigoma rural district had a large area planted with permanent crops (30% of total permanent area planted in the region) mostly palm oil (382 ha) and mango (28 ha). Other permanent crop were either not grown or were grown in very small quantities. As with other districts in the region, land clearing by hand slashing was predominant and practically all land preparation was done by hand even though a very small land preparation was done by bush clearance. RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 The use of inputs in the region was small, however districts differences exist. Kigoma rural district had small area planted with improved seeds; the district also had the average percent of planted area applied with fertilizers (farm yard manure, compost and inorganic fertilizer), but most of this was farm yard manure. Compared to other districts, Kigoma rural district had the second lowest area applied with insecticides in the region. The percent of planted area with fungicides and herbicides were amongst the lowest in the region. It had one of the largest areas under irrigation (1,520 ha.). The most common source of water for irrigation was the rivers using land buckets/bucket. Watering cans were the most common means of irrigation water application. The most common method of crop storage was the locally made traditional crib; however the proportion of households not storing crops in Kigoma rural district was one of the highest in the region. The number of households selling crops in the district was among the largest in the region, however for those who did not sell, the main reason for not selling was insufficient production. The smallest percent of households processing crops in the region was found in Kigoma rural district and processing was mostly done by neighbor’s machine. The district had the largest number of households processing crops on farm by neighbour machine. It also had the largest number of households processing crops on farm by hand. Most households that sell crops to local market/trade store. Access to credit in the district is very small. A very large number of households receive extension services in Kigoma rural district and almost all of these were from the government. The quality of extension services was rated between very good and average by the majority of the households. Tree farming was not important in Kigoma rural district (with only 4,266 planted trees) and most of them were Eucalyptus spp, and Gravellies. The largest proportion of households in Kigoma rural district used erosion control bunds. Kigoma rural district had the largest number of cattle in the region and most of them were indigenous. It was one the districts with the large number of goats in the region. Kigoma rural was also the districts with the largest number of sheep, chickens and improved chickens. Small numbers of ducks and rabbits were found in the district. moderate number of households reported tsetse and tick problems in Kigoma rural districts and it had one of the smallest numbers of households deworming livestock. The use draft animal in the district was very small in the region and no households practiced fish farming. It was amongst the districts with the best access to primary schools, feeder roads, all weather roads, and health clinics, compared to other districts. However, it had the worst access to secondary schools, tarmac road, district capital, secondary markets and tertiary and tertiary market. Kigoma rural district had a small number of households with no toilet (1.7 percent). The district has the higher percent of households owning radio, iron and television/video The common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a high percent of households with grass roofs, and only 27 percent of households having iron sheet. The most common source of drinking water was surface water (Lake/dam/river/stream). It had the third highest percent of households having two meal per day compared to other districts and the highest percent with three meals per day. The district had the lowest percent of households that did not eat meat or fish during the week prior to enumeration. Most households never had problems with food satisfaction. 4.2.4 Kigoma Urban Kigoma Urban district had the smallest number of households in the region and one of the lowest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock farming. It had a very small number of livestock only households and no pastoralists were found in the district RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 The most important livelihood activity for smallholder in Kigoma Urban district was off-farm income followed by annual crop farming, permanent crop farming, livestock keeping/herding and remittances. The district had the lowest percent of households with no off farm income activities and the highest percent of households with more than one member involved off-farm income activities. Compared to other districts in the region, Kigoma Urban had moderate percent of female headed households (27%) and it had the second highest average age of the household heads. Its average household size of 6 members per household was more than the regional average household size.. Kigoma Urban had the second largest literacy rates among smallholders’ members in the region (66%). It had one of the smallest utilized land area per household (0.9 ha) which was much lower than the regional average of 1.9 ha per household. The district had the second largest planted area in the region, per household (0.4 ha) in the long rainy season. The district not important for maize production with a planted area of only 760 ha, however the planted area per household was moderate compared to other districts in the region. Paddy production was also not important with a planted area of 83 hectares and the production of sorghum was not important and irish potatoes were not grown in the district. The district had the lowest percent of cassava planted area in the region. The production of beans in Kigoma Urban district was relatively small in the region with planted area of 628 ha. Oil seed crops were not important and small amounts of groundnuts were grown in the district Vegetable production was also not important in the district, however the district had largest planted area per tomato growing household in the region Traditional crops (e.g. tobacco and cotton), were either not grown or were grown in very small quantities. Kigoma Urban had a small area planted with permanent crops (4,46 ha) dominated by palm oils (382 ha) and mango (28 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing was done by hand slashing, however ‘’no land clearing ‘’ was relatively high indicating bare land before cultivation. Practically all land preparation was done by hand, however very small amount of land preparation was done by bush clearance and burning. The use of inputs in the region was very small, however district differences exist. Kigoma Urban had the highest percent of area planted with improved seeds in Kigoma region and it had the highest planted area applied with fertilizers most of this used farm yard manure. Compared to other districts in the region, Kigoma Urban district had a low percent of its planted area applied with insecticides in the region and the use of fungicides was one of the lowest in the region and virtually no herbicides were used. It had the smallest area planted under irrigation in the region with only 42 ha of irrigated land rivers and wells were used as the sources of irrigation water and buckets/water cans were the most common means of irrigation water application. The most common method of crop storage was in sacks/open drum; however the proportion of households not storing crops in the districts was one of the highest in the region. The district had the second highest number of households selling crops and the main reason for not selling was insufficient production. Kigoma Urban district had the higher percent of households processing crops on the far by hand and a small percent of households processed crops mainly by neighbors’ machine and far on by machine. Access to credit was very small in the district and the main reason for not using credit was did not know how to get credit RESULTS ______________________________________________________________________________________ _ ________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 A comparatively small number of households received extension services in Kigoma Urban district and all of these were from the government. The quality of extension services was rated between good and average by most of the households. Tree farming was not important in Kigoma Urban (with only 209 planted trees) and is normally with senna spp with some jacaranda spp. The smallest number of erosion control and erosion control bunds was found in Kigoma Urban district. The district had the smallest number of cattle in the region and they were mostly indigenous. Goats and sheep production were also the smallest in the region and some pigs were found in the district. It had a comparatively large number of chickens; but a small number of ducks.. A moderate number of households reported tsetse flies and ticks problems and the district had the highest number of households de-worming livestock. The use of draft animals in the district was non existent and no fish farming was practiced in the district. It was amongst the districts with the best access to all weather roads, district capital, secondary schools, primary school, feeder roads, and health clinics and primary markets: however it had one of the worst accesses to secondary markets. Kigoma Urban had high percent of households with no toilets facilities (2.3%). The district had the largest percent of households owning radios iron, and bicycles. A very small number of households reported owning vehicles and television/ videos. It had the largest number of households using electricity in the region the most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a large percent of households with grass roofs (35%) and only (61%) of households had iron sheet roofs. The most common source of drinking water were the pipe and the protected well. It had 74 percent of households having two meals per and 26 percent of households with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration; however it had low percent of households that did not eat fish during the preceding week. Most households in the districts never had problems with food satisfaction. APPENDIX II 107 4. APPENDICES Appendix I Tabulation List ..................................................................................................108 Appendix II Tables................................................................................................................ 125 Appendix III Questionnaires................................................................................................. 270 APPENDIX II 108 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD……………………………………………………125 2.1: Number of Agricultural Households by Type of Household and District, 2002/03 Agriculture Year .................................................................... 126 2.2: Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year ....................................................................................................... 126 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES ....................................................127 3.1f Sixth Most Importance................................................................................................................. 128 3.1g Seventh Most Importance............................................................................................................ 128 HOUSEHOLDS DEMOGRAPHS……………..………………………………………...128 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) .................................................................................................... 131 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %)...................................................................................................... 131 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year ................................................................................................... 132 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year ......................... 132 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ................................................ 132 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ..................................................................................... 132 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year................................................... 134 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year............................................................ 135 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .............................. 137 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year ............................... 137 APPENDIX II 109 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year................................................................. 137 3.13 Mean, Meadian, Mode of Age of Head of Agricultural Household and District.................. 137 3.14 Time Series of Male and Female Headed Households ......................................................... 138 3.15 Literacy Rates of Heads of Households by Sex and District ................................................ 138 LAND ACCESS/OWNERSHIP………………………………………………….139 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year .................................................................................................... 140 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year .................................................................................................... 140 LAND USE 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year......................................................................................... 142 5.2 Area of Land (Ha) by type of Land Use and District during 2002/03 Agricultural Year..... 142 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year....................................................................... 143 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District during 2002/03 Agricultural Year ............ 143 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year ............... 143 ANNUAL CROP & VEGETABLE PRODUCTION - LONG RAIN SEASON........................... 145 7.1&7.2a Number of Crop Growing Households and Area Planted (ha) By District - LONG RAINY SEASON ...................................................................................... 146 7.1&7.2b Number of Crop Growing Households Planting Crops By Season and District-LONG RAINY SEASON ................................................................................. 146 7.1&7.2h Number of Crop Growing and Planted Area By Insecticide Use and District for the 2002/03 Crop Year - LONG RAINY SEASON........................................................ 147 7.1&7.2i Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON ......................................................... 147 7.1&7.2d Number of Agriculture Household by Area Planted (ha) and Crop for the Agriculture Year 2002/03 Agriculture Year, Kigoma Region.............................................. 148 APPENDIX II 110 7.1&7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the Year 2002/03 Agriculture Year, Kigoma Region ........................................................................................ 149 7.1&7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Kigoma Region .................................................................................................................... 150 7.1&7.2f Number of Crop Growing Households and Planted Area By Fertilizer Use and District for the 2002/03 Crop Year-LONG RAINY SEASON ............................................................... 150 7.1&7.2g Number of Agriculture Household Crop Growing and Planted Area By Irrigation Use and District for the 2002/03 Crop Year - LONG RAINY SEASON........................................... 151 7.1&7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON ............................................ 152 7.1&7.2kNumber of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON ................................... 152 7.2.1 Number of Households by Planted Area (ha) and Quantity of Maize Harvested (tons) by District and Crop-Long Rainy Season.................................................. 164 7.2.2 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season ....................................... 164 7.2.3 Number of Households by Planted Area (ha) and Quantity of Paddy Harvested (tons) by District and Crop-Long Rainy Season.................................................. 165 7.2.4 Number of Households by Planted Area (ha) and Quantity of Sorghum Harvested (tons) by District and Crop-Long Rainy Season.................................................. 165 7.2.5 Number of Households by Planted Area (ha) and Quantity of Finger Millet Harvested (tons) by District and Crop-Long Rainy Season.................................................. 166 7.2.6 Number of Households by Planted Area (ha) and Quantity of Beans Harvested (tons) by District and Crop-Long Rainy Season.................................................. 166 7.2.7 Number of Households by Planted Area (ha) and Quantity of Green Gram Harvested (tons) by District and Crop-Long Rainy Season........................................ 167 7.2.8 Number of Households by Planted Area (ha) and Quantity of Mung Beans Harvested (tons) by District and Crop-Long Rainy Season ...................................... 167 7.2.9 Number of Households by Planted Area (ha) and Quantity of Cowpeas Harvested (tons) by District and Crop-Long Rainy Season.................................................. 168 7.2.10 Number of Households by Planted Area (ha) and Quantity of Bambaranuts Harvested (tons) by District and Crop-Long Rainy Season........................... 168 APPENDIX II 111 7.2.12 Number of Households by Planted Area (ha) and Quantity of Cassava Harvested (tons) by District and Crop-Long Rainy Season.................................................. 169 7.2.13 Number of Households by Planted Area (ha) and Quantity of Sweet Potatoes Harvested (tons) by District and Crop-Long Rainy Season ................................... 170 7.2.15 Number of Households by Planted Area (ha) and Quantity of Groundnuts Harvested (tons) by District and Crop-Long Rainy Season.............................. 170 7.2.16 Number of Households by Planted Area (ha) and Quantity of Sunflower Harvested (tons) by District and Crop-Long Rainy Season................................................. 170 7.2.23 Number of Households by Planted Area (ha) and Quantity of Onion Harvested (tons) by District and Crop-Long Rainy Season.................................................. 173 7.2.24 Number of Households by Planted Area (ha) and Quantity of Tomatoes Harvested (tons) by District and Crop-Long Rainy Season.................................................. 173 7.2.28 Number of Households by Planted Area (ha) and Quantity of Amaranths Harvested (tons) by District and Crop-Long Rainy Season.................................................. 175 7.2.27 Number of Households by Planted Area (ha) and Quantity of Chillies Harvested (tons) by District and Crop-Long Rainy Season.................................................. 175 PERMANENT CROPS 7.3.1 Production of Permanent Crops by Crop Type and District - Kigoma Region.......................... 178 7.3.2: Area Planted by Crop Type - Kigoma Region........................................................................... 179 7.3.3 Total Area Planted with Mango by District - Kigoma Region................................................... 179 7.3.4 Total Area Planted with Palm Oil by District - Kigoma Region ............................................... 179 AGROPROCESSING........................................................................................................................ 181 8.1.1a: Number of Crops Growing Households Reported to have Processed Farm Products by District; 2002/03 Agriculture Year.......................................................... 182 8.1.1b Number of Crop Growing Households by Method Processing and District; 2002/03 Agriculture Year of Farm Products Produced During 2002/03 Agriculture Year ............... 182 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agriculture Year by Location and Crop, Kigoma Region .................................................... 183 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop, Kigoma Region .............. 183 8.1.e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop, .................... 183 APPENDIX II 112 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year - Kigoma Region ............................................................ 183 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Tanga Region ............................... 183 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year - Kigoma Region ............................................................ 184 8.1.1i Number of Crop Growing Households By Type of By-Product and District During 2002/03 Agriculture Year, Kigoma Region............................................................. 184 MARKETING .................................................................................................................................... 185 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District During 2003/04 Agriculture Year, Kigoma Region................................................. 186 10.2 Number of Households who Reported Main Reason for Not Selling their Crops by District during 2002/03 Agriculture Year, Kigoma Region............................................................... 186 10.3 Proportion of Households who Reported Main Reason for Not Selling their Crops by District During 2002/03 Agriculture Year ......................................................................................... 186 IRRIGATION / EROSION CONTROL.......................................................................................... 187 11.1 Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year by District................................................................................... 188 11.2 Area (ha) of Irrigatable and NON Irrigated Land by District During 2002/03 Agriculture Year...................................................................................................... 188 11.3 Number of Agriculture Households Using Irrigation By Source of Irrigation Water by District During the 2003/04 Agricultural Year .................................... 188 11.4 Number of Agriculture Households by Method Used to obtain Water and District During 2002/03 Agriculture Year ..................................................................... 188 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agriculture Year ........................................... 189 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District....................................................................................... 189 11.7 Number of Erosion Control Harvesting Structures By Type and District as of 2002/03 Agriculture Year................................................................................ 189 APPENDIX II 113 ACCESS TO FARM INPUTS .......................................................................................................... 191 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................................................................... 192 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year................................................................................................................... 192 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year................................................................................................................... 192 12.1.4 Number of Agricultural Households Using Insecticide/Fungicides by District, 2002/03 Agricultural Year................................................................................................................... 193 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year .................................................................................................... 193 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year .................................................................................................... 193 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year............................................................................... 194 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure by District, 2002/03 Agricultural Year ................................................................................. 194 12.1.9 Number of Agricultural Households by Source of COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................ 195 12.1.10 Number of Agricultural Households by Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ...................................................................................... 195 12.1.11 Number of Agricultural Households by Source of Herbicides by District, 2002/03 Agricultural Year ...................................................................................... 195 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................... 196 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year................................................. 196 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year........................................................... 196 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ................................................ 197 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ....................................................................... 197 APPENDIX II 114 12.1.17 Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year.......................................... 197 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year................................................. 198 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year................................................. 198 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ..................................... 198 12.1.21 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year............................................. 199 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .................................................... 199 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year...................................................... 199 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................. 200 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year.................................................................... 200 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year.................................................................... 200 12.1.27 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year .................................................................................................... 201 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year................................................................................................................... 201 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................... 201 ..................................................................................................................................................... 12.1.30 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................. 202 12.1.31 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year................................................................... 202 12.1.32 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year.................................................................... 202 APPENDIX II 115 12.1.33 Number of Agricultural Households With Plan to use Next Year Insecicides/Fungicides by District, 2002/03 Agricultural Year............................................ 202 12.1.34 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year ................................................................................ 202 12.1.35 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year................................................................................................................... 203 AGRICULTURE CREDIT ............................................................................................................... 205 13.1a Number of Agriculture Households Receiving Credit By Sex of Household Head Receiving Credit and District During the 2002/03 Agriculture Year........................ 206 13.1b Number of Households Receiving Credit By Main Source of Credit By District ............... 206 13.2a Number of Households Reported Main Reasons for Not Using Credit By District During the 2002/03 Agriculture Year ..................................................................... 207 13.2b Number of Credits Received By Main Purpose of Credit and District During the 2002/03 Agriculture Year ................................................................................... 207 TREE FARMING AND AGROFORESTRY.................................................................................. 209 14.1 Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Kigoma Region .......................................................................... 210 14.4 Number of Agriculture Households Classified By Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Kigoma Region.... 211 14.5 Number of Responses by Second Use of Planted Trees and District for the 2002/03 Agriculture Year, Kigoma RegionSecond Use of Trees By District .................................... 211 CROP EXTENSION.......................................................................................................................... 113 15.1 Number of Agriculture Households Receiving Extension Messages By District During the 2002/03 Agriculture Year, Kigoma Region........................................................ 214 15.2 Number of Households By Quality of Extension Services and District District During the 2002/03 Agriculture Year, Kigoma Region ....................................................... 214 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 214 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 215 APPENDIX II 116 15.5 Number of Agriculture Households Receiving Advice on Agrochemical By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 215 15.6 Number of Agriculture Households Receiving Advice on Erosion Control By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 215 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Kigoma Region .................. 217 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Kigoma Region ................. 217 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds By Source and District During the 2002/03 Agriculture Year, Kigoma Region .................. 217 15.10 Number of Agriculture Households Receiving Advice on Mechanization/LST By Source and District During the 2002/03 Agriculture Year, Kigoma Region....................... 218 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology By Source and District During the 2002/03 Agriculture Year, Kigoma Region .................. 218 15.12 Number of Agriculture Households Receiving Advice on Crop Storage By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 218 15.13 Number of Agriculture Households Receiving Advice on Vermin Control By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................ 219 15.14 Number of Agriculture Households Receiving Advice on Agro-processing By Source and District During the 2002/03 Agriculture Year, Kigoma Region....................... 219 15.15 Number of Agriculture Households Receivingf Advice on Agro-forestry By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................ 219 15.16 Number of Agriculture Households Receiving Advice on Beekeeping By Source and District During the 2002/03 Agriculture Year, Kigoma Region .................................... 220 15.17 Number of Agriculture Households Receiving Advice on Fish Farming By Source and District During the 2002/03 Agriculture Year, Kigoma Region........................................... 220 15.18 Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Kigoma Region.. ................................................................................................................................. 220 15.19 Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Kigoma Region ..................................................................................................................... 221 ..................................................................................................................................................... 15.20 Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Kigoma Region .......................................................................... 221 APPENDIX II 117 15.21 Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Kigoma Region .......................................................................... 221 ANIMAL CONTRIBUTION TO CROP PRODUCTION................................................................... 17.1 Number of Agriculture Households Using Draft Animal to Cultivate Land By District During 2002/03 Agriculture Year, Kigoma Region ........................................... 224 17.2 Type of Draft Animal By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year, Kigoma Region ............................. 224 17.3 Number of Crop Growing Households Using Organic Fertilizer By District During 2002/03 Agriculture Year, Kigoma Region.............................................................. 224 17.4: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year, Kigoma Region .......................................................................... 224 CATTLE PRODUCTION ................................................................................................................. 225 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Kigoma Region ..................................................................................................................... 226 18.2 Total Number of Cattle By Type and District as of 1st October, 2003................................. 226 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size; on 1st October 2003............................................................... 226 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003............................. 227 18.5 Number of Indigenous Cattle By Category and District as on 1st October, 2003 ............... 227 18.7 Number of Dairy Cattle By Category and District as on 1st October, 2003........................ 228 18.8 Total Number of Cattle By Category and District as on 1st October, 2003 ....................... 228 GOATS PRODUCTION.................................................................................................................... 229 19.1 Total Number of Goats by Goat Type and District as on 1st October, 2003........................ 230 19.2 Number of Households Rearing Goats and Head of Goats by Herd Size on 1st October 2003 .............................................................................................................. 230 19.3 Total Number of Goats by Category and Type of Goat on 1st October, 2003 .................... 231 194 Number of Indigenous Goat by Category and District on 1st October, 2003....................... 231 19.5 Number of Improved Meat Goat by Category and District on 1st October, 2003................ 231 APPENDIX II 118 19.6 Number of Improved Dairy Goat by Category and District as of 1st October, 2003 ........... 232 19.7 Total Number of Goat by Category and District as of 1st October, 2003............................. 232 SHEEP PRODUCTION .................................................................................................................... 233 20.1 Total Number of Sheep By Breed Type on 1st October 2002/03 ........................................ 234 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 ........ 234 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 ...................... 234 20.4 Number of Sheep per Household by District as of 1st October 2003................................... 234 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2002 ........ 235 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2002.......................... 235 PIGS PRODUCTION ........................................................................................................................ 237 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 ................................... 238 21.2 Number of Households and Pigs by District on 1st October 2003 ....................................... 238 21.3 Number of Pigs by Type of Pigs and District on 1st October, 2003..................................... 238 LIVESTOCK PESTS AND PARASITE CONTROL..................................................................... 239 22.1 Number of Livestock Rearing Households deworming Livestock by District During the 2002/03 Agriculture Year ............................ 240 22.2 Number of Livestock Rearing Households dewormed Livestock by Type of Livestock and District During the 2002/03 Agriculture Year ................................ 240 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year..... 141 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year............. 141 OTHER LIVESTOCK....................................................................................................................... 243 23a Total Number of Other Livestock by Type as of 1st October 2003...................................... 244 23b Number of households with chicken and Category of Chicken by District.......................... 244 23c Total Number of Households and Chickens raised by Flock Size as of 1st October 2003... 244 23d Head Number of Other Livestock by Type of Livestock and District.................................. 244 APPENDIX II 119 23e other Livestock/Poultry Population Trend ............................................................................ 244 FISH FARMING................................................................................................................................ 245 28.1 Number of Agricultural Households involved in Fish Farming and District During 2002/03 Agricultural Year ........................................................................................ 246 28.2 Number of Agricultural Households By System of Farming and District During the 2002/03 Agricultural Year .................................................................................. 246 28.3 Number of Agricultural Households By Source of Fingerings and District During the 2002/03 Agricultural Year .................................................................................................... 246 28.4 Number of Agricultural Households By Location of Selling Fish and District During the 2002/03 Agricultural Year .................................................................................................... 246 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year............. 246 LIVESTOCK EXTENSION.............................................................................................................. 247 29.1a Number of Agricultural Households Receiving Extension Advice By District During 2002/03 Agricultural ……………………..………………..... ……………………248 29.1b Number of Households By Source of Extension and District during the 2002/03 Agriculture Year… ...... …………….………248 29.4 Number of Households Receiving Extension roper Milking By Source and District…………………………………………………………………....... ………………248 29.5 Number of Households Receiving Advice on Milk Hygene By Source and District…………………………………………………………………….…...... …………285 29.1e Number of Households Receiving Advice on Disease Control By Source and District……………………………………………………………………..…....... ………..250 29.1f Number of Households Receiving Advice on Herd/Flock Size & Selection By Source and District……………………………………………………… ...... …………250 29.8 Number of Households Receiving Advice on Pasture Establishment By Sourceand District…………………………………………………………………………....... ………250 29.9 9Number of Households Receiving Advice on Group Formation and strengthening by source and District…………………….……………………........ ………250 . 29.10 Number of Households Receiving Advice on Calf Rearing By Source and District………………………………………………………………….…………........ …..250 29.11 Number of Households Receiving Advice on Use of Improved Bulls By Source and District………………………………………………………………........ ……250 APPENDIX II 120 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year……………………………………….…… ....... ……..250 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES 33 01a Mean Distances from Holders Dwellings to Infrastructures and Services by District.......... 256 33.01b: Mean distances from holders dwellings to Secondary Schools by District for 2002/03 Agriculture Year.................................................................................................................... 257 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 Agriculture Year..................................................................................................... 257 33.01d: Number of Households by Distance to Feeder Road and District for 2002/03 Agriculture Year..................................................................................................... 257 33.01e Number of Households by Distance to Hospital by District for 2002/03 Agriculture Year…………………………………………....................................................258 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 Agriculture Year...................................................................................................... 258 33.01g: Number of Households by Distance to Primary School by District for 2002/03 Agriculture Year...................................................................................................... 258 33.01h Number of Households by Distance to Regional Capital and District for 2002/03 Agriculture Year...................................................................................................... 159 33.01i Number of Households by Distance to Tarmac Road and District for 2002/03 Agriculture Year ....................................................................................................................................... 159 33.01j Number of Households by Distance to Primary Market and District for 2002/03 Agriculture Year ....................................................................................................................................... 159 33.01k Number of Households by Distance to Secondary Marketand District for 2002/03 Agriculture Year.................................................................................................................... 160 33.01l Number of Households by Distance to Tertiary Marketand District for 2002/03 Agriculture Year ....................................................................................................................................... 160 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year................................................... 261 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year................................................... 261 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year....................................................... 262 APPENDIX II 121 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year................................................ 262 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center............................................................................................. 262 HOUSEHOLD FACILITIES 34.1: Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year.................................................................................................................... 264 34.2: Number of hoseholds Reporting AverageNumber of Rooms and Type of Roofing Materials by District, 2002/03 Agricultural Year .................................................. 264 34.3: Number of Agricultural Households by Type of Owned Assets and District During 2002/03 Agricultural Year ........................................................................................ 264 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting and District During 2002/03 Agriculture Year .................................................................................. 34.5: Number of Agricultural Households by Main Source of Energy for Cooking and District During 2002/03 Agriculture Year ......................................................................................... 265 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District During 2002/03 Agriculture Year 265 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year ...................................................... 266 34.8: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agriculture Year....................... 266 34.9: Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year................. 267 34.10: Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year................ 267 34.12: Number of Agricultural Households by Number of Meals the Household .......................... 267 34-13: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District ...................................................................... 268 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceeding Week by District................................................................................................. 268 34.15: Number of Households by Type of Roofing Materials and District During 2002/03 Agriculture Year.................................................................................................................... 269 APPENDIX II 122 34.16: Number of Households by Main Source of Income and District During 2002/03 Agriculture Year ....................................................................................................................................... 269 APPENDIX II 123 APPENDIX II: CROP TABLES Type of Agriculture Household.............................................................................................................................................. 128 Number of Agriculture Households ........................................................................................................................................130 Rank of Importance of Livelihood Activities..........................................................................................................................132 Households Demography.........................................................................................................................................................134 Land Access/Ownership ..........................................................................................................................................................146 Land Use………………..........................................................................................................................................................148 Total Annual Crop and Vegetable Production Long and short Seasons ...............................................................................152 Annual Crop and Vegetable Production Long Rainy Seasons ...............................................................................................168 Permanent Crop Production.....................................................................................................................................................182 Agro-processing ..............................................................................................................................................................184 Marketing ..............................................................................................................................................................190 Irrigation/Erosion Control........................................................................................................................................................192 Access to Farm Inputs .............................................................................................................................................................196 Agriculture Credit ..............................................................................................................................................................208 Tree Farming and Agro-forestry..............................................................................................................................................212 Crop Extension ..............................................................................................................................................................216 Animal Contribution to Crop Production................................................................................................................................226 Cattle Production ..............................................................................................................................................................230 Goat Production ..............................................................................................................................................................234 Sheep Production ..............................................................................................................................................................238 Pig Production ..............................................................................................................................................................242 Livestock Pests and Parasite Control.......................................................................................................................................244 Other Livestock ..............................................................................................................................................................248 Fishing Farming ..............................................................................................................................................................250 Livestock Extension ..............................................................................................................................................................252 Access to Infrastructure and other services.............................................................................................................................260 Household Facilities ..............................................................................................................................................................268 Appendix II 125 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 126 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Kibondo 51,407 26.3 524 9.3 51,931 25.8 6,641 16.1 58,572 Kasulu 79,396 40.6 2,567 45.8 81,963 40.7 3,847 9.3 85,810 Kigoma Rural 62,470 31.9 2,431 43.4 64,901 32.2 7,184 17.5 72,085 Kigoma Urban 2,492 1.3 80 1.4 2,572 1.3 23,494 57.1 26,066 Total 195,765 100.0 5,602 100.0 201,367 100.0 41,166 100.0 242,533 Total Number of households % Number of households % Number of households % Number of households % Number of households % Kibondo 34,041 25 266.1 29.2 17,100 29 0 0 51,407 26 51,407 51,407 17,367 Kasulu 53,306 39 0 0.0 26,091 44 0 0 79,396 41 79,396 79,396 26,091 Kigoma Rural 46,422 34 610 67 15,278 26 160 100 62,470 32 62,470 62,310 16,048 Kigoma Urban 1,887 1 34 3.8 571 1 0 0 2,492 1 2,492 2,492 605 Total 135,655 100 911 100.0 59,040 100 160 100 195,765 100 195,765 195,605 60,110 District Type of Agriculture Household Total Number of Households Growing Crops 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year District Agriculture, Non Agriculture and Urban Households Total Number of Households Rearing Livestock Crops Only Livestock Only Crops & Livestock Pastoralist Total Number of Agriculture Households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 127 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 128 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kibondo 0 0 133 133 0 267 398 Kasulu 0 0 0 197 0 0 0 Kigoma Rur 0 0 929 928 0 0 913 Kigoma Urb 34 0 32 0 32 0 67 Total 34 0 1,095 1258 32 267 1,377 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kibondo 0 0 102 0 0 267 267 Kasulu 0 0 0 0 0 0 0 Kigoma Rur 0 0 0 0 0 0 0 Kigoma Urb 0 0 0 0 0 33 0 Total 0 0 102 0 0 300 267 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 129 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 130 Number % Average Household Size Number % Average Household Size Number % Kibondo 41,564 80.9 5 9,844 19.1 4 51,407 100.0 5 Kasulu 70,754 89.1 6 8,642 10.9 4 79,396 100.0 5 Kigoma Rur 53,177 85.1 6 9,293 14.9 5 62,470 100.0 6 Kigoma Urb 1,829 73.4 6 663 26.6 5 2,492 100.0 6 Total 167,324 85.5 6 28,442 14.5 4 195,765 100.0 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittance s Fishing / Hunting & Gathering Tree / Forest Resources Kibondo 1 2 4 3 6 7 5 Kasulu 1 2 3 4 6 7 5 Kigoma Rur 1 2 5 3 7 6 4 Kigoma Urb 2 3 4 1 5 6 7 Total 1 2 3 4 6 7 5 3.0 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size 3.1 HOUSEHOLDS DEMOGRAPHS: The livelyhood Activities/Source of Income of the Households District livelihood activity District Male Female Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 131 Number % Number % Number % Less than 4 74,563 48 80,107 52 154,670 100 05 - 09 89,769 50 90,221 50 179,991 100 10 - 14 83,827 51 80,023 49 163,850 100 15 - 19 61,776 50 61,091 50 122,868 100 20 - 24 39,020 44 48,674 56 87,694 100 25 - 29 35,203 48 38,617 52 73,820 100 30 - 34 25,337 44 31,946 56 57,283 100 35 - 39 24,189 46 27,846 54 52,035 100 40 - 44 23,402 50 23,718 50 47,120 100 45 - 49 16,273 49 17,089 51 33,361 100 50 - 54 13,479 46 15,676 54 29,155 100 55 - 59 10,027 48 10,866 52 20,892 100 60 - 64 9,935 50 9,788 50 19,723 100 65 - 69 7,750 56 6,115 44 13,864 100 70 - 74 4,830 55 3,947 45 8,776 100 75 - 79 3,991 72 1,529 28 5,520 100 80 - 84 1,856 70 805 30 2,661 100 Above 85 2,777 82 597 18 3,374 100 Total 528,004 49 548,654 51 1,076,658 100 Number % Number % Number % Less than 4 74,563 14 80,107 15 154,670 14 05 - 09 89,769 17 90,221 16 179,991 17 10 - 14 83,827 16 80,023 15 163,850 15 15 - 19 61,776 12 61,091 11 122,868 11 20 - 24 39,020 7 48,674 9 87,694 8 25 - 29 35,203 7 38,617 7 73,820 7 30 - 34 25,337 5 31,946 6 57,283 5 35 - 39 24,189 5 27,846 5 52,035 5 40 - 44 23,402 4 23,718 4 47,120 4 45 - 49 16,273 3 17,089 3 33,361 3 50 - 54 13,479 3 15,676 3 29,155 3 55 - 59 10,027 2 10,866 2 20,892 2 60 - 64 9,935 2 9,788 2 19,723 2 65 - 69 7,750 1 6,115 1 13,864 1 70 - 74 4,830 1 3,947 1 8,776 1 75 - 79 3,991 1 1,529 0 5,520 1 80 - 84 1,856 0 805 0 2,661 0 Above 85 2,777 1 597 0 3,374 0 Total 528,004 100 548,654 100 1,076,658 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 132 Number % Number % Number % Kibondo 130,291 49 135,090 51 265,382 100 Kasulu 211,479 49 217,553 51 429,032 100 Kigoma Rur 179,151 49 188,655 51 367,807 100 Kigoma Urb 7,083 49 7,355 51 14,437 100 Total 528,004 49 548,654 51 1,076,658 100 Number % Number % Number % Number % Number % Kibondo 136,292 62.2 8,911 4.1 0 0.0 74,010 33.8 219,212 100 Kasulu 244,868 65.2 13,695 3.6 789 0.2 116,477 31.0 375,828 100 Kigoma Rur 191,960 61.1 11,869 3.8 0 0.0 110,468 35.1 314,297 100 Kigoma Urb 7,786 61.6 466 3.7 34 0.3 4,364 34.5 12,650 100 Total 580,906 63.0 34,940 3.8 823 0.1 305,318 33.1 921,988 100 Number % Number % Number % Number % Kibondo 69,654 31.8 87,231 39.8 62,326 28.4 219,212 100.0 Kasulu 118,664 31.6 148,395 39.5 108,769 28.9 375,828 100.0 Kigoma Rur 97,793 31.1 113,239 36.0 103,265 32.9 314,297 100.0 Kigoma Urb 3,196 25.3 5,320 42.1 4,135 32.7 12,650 100.0 Total 289,307 31.4 354,185 38.4 278,496 30.2 921,988 100.0 Number % Number % Number % Number % Number % Kibondo 105,980 48.3 1,091 0.5 349 0.2 132 0.1 1,493 0.7 Kasulu 189,692 50.5 2,737 0.7 197 0.1 587 0.2 1,564 0.4 Kigoma Rur 129,169 41.1 3,124 1.0 1,923 0.6 9,147 2.9 2,177 0.7 Kigoma Urb 3,618 28.6 230 1.8 0 0.0 399 3.2 201 1.6 Total 428,460 46.5 7,182 0.8 2,470 0.3 10,265 1.1 5,436 0.6 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 133 Number % Number % Number % Number % Number % Kibondo 4,252 1.9 185 0.1 4,900 2.2 3,298 1.5 1,059 0.5 Kasulu 4,291 1.1 1,751 0.5 6,681 1.8 2,533 0.7 1,546 0.4 Kigoma Rur 3,416 1.1 4,779 1.5 15,071 4.8 1,218 0.4 617 0.2 Kigoma Urb 265 2.1 303 2.4 1,406 11.1 328 2.6 377 3.0 Total 12,223 1.3 7,018 0.8 28,059 3.0 7,378 0.8 3,599 0.4 Number % Number % Number % Number % Number % Number % Kibondo 216 0.1 0 0.0 62,953 28.7 32,771 14.9 533 0 219,212 100 Kasulu 591 0.2 1,160 0.3 113,581 30.2 42,449 11.3 6,467 2 375,828 100 Kigoma Rur 625 0.2 310 0.1 94,350 30.0 47,760 15.2 611 0 314,297 100 Kigoma Urb 67 0.5 303 2.4 3,164 25.0 1,623 12.8 365 3 12,650 100 Total 1,499 0.2 1,774 0.2 274,048 29.7 124,603 13.5 7975 0.9 921,988 100 District Not Working & Available Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Total Main Activity Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Unpaid Family Helper (Non Agriculture) District Other Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 134 Number % Number % Number % Number % Number % Kibondo 80,043 37 21,198 10 57,672 26 60,300 28 219,212 100 Kasulu 167,457 45 22,865 6 59,651 16 125,856 33 375,828 100 Kigoma Rur 108,727 35 36,429 12 42,570 14 126,571 40 314,297 100 Kigoma Urb 3,072 24 1,652 13 2,761 22 5,165 41 12,650 100 Total 359,298 39 82,144 9 162,654 18 317,892 34 921,988 100 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 135 Number % Number % Number % Number % Number % Kibondo 854 1.0 1,655 2 1,084 1 1,714 2 6,741 8 Kasulu 783 0.5 390 0 3,149 2 4,105 3 16,294 11 Kigoma Rural 308 0.3 786 1 1,845 2 2,959 3 11,488 10 Kigoma Urban 0 0.0 0 0 101 2 234 4 364 7 Total 1,945 0.5 2,831 1 6,178 2 9,012 3 34,888 10 Number % Number % Number % Number % Number % Kibondo 67,236 77 1,535 2 264 0 121 0 0 0 Kasulu 108,987 73 980 1 197 0 0 0 0 0 Kigoma Rural 77,442 68 303 0 150 0 156 0 0 0 Kigoma Urban 3,551 67 0 0 0 0 0 0 34 1 Total 257,215 73 2,819 1 611 0 277 0 34 0 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Under Standard One Standard One Standard Two Standard Three District Education Level Education Level Standard Four Form One Standard Seven Standard Eight Training After Primary Education Pre Form One Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 136 Number % Number % Number % Number % Number % Kibondo 266 0 0 0 926 1 0 0 0 0 Kasulu 388 0 0 0 1,566 1 0 0 0 0 Kigoma Rural 464 0 315 0 1,392 1 0 0 1,538 1 Kigoma Urban 67 1 0 0 34 1 0 0 67 1 Total 1,185 0 315 0 3,918 1 0 0 1,604 0 Number % Number % Number % Number % Kibondo 0 0 2,549 3 0 0 87,231 100 Kasulu 0 0 5,084 3 0 0 148,395 100 Kigoma Rural 0 0 6,240 6 0 0 113,239 100 Kigoma Urban 0 0 334 6 0 0 5,320 100 Total 0 0 14,208 4 0 0 354,185 100 District Education Level y Tertiary Education Adult Education Not applicable Total cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Form Six Training After Secondary Education cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Form Two Form Three Form Four Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 137 Number % Average Household Size Number % Average Household Size Number % Kibondo 41,564 81 5 9,844 19 4 51,407 100 5 Kasulu 70,754 89 6 8,642 11 4 79,396 100 5 Kigoma Rur 53,177 85 6 9,293 15 5 62,470 100 6 Kigoma Urb 1,829 73 6 663 27 5 2,492 100 6 Total 167,324 85 6 28,442 15 4 195,765 100 5 Number Percent Number Percent Number Percent Number Percent Kibondo 27,442 77 6,659 19 1,755 5 35,856 100 Kasulu 32,333 71 9,566 21 3,502 8 45,401 100 Kigoma Rural 32,830 70 9,851 21 4,021 9 46,702 100 Kigoma Urban 797 41 599 30 569 29 1,965 100 Total 93,401 71.9 26,675 20.5 9,848 7.6 129,924 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Kibondo 15,494 34,126 0 650 0 0 1,138 51,407 Kasulu 22,958 52,334 194 1,175 0 0 2,735 79,396 Kigoma Rur 20,189 37,151 0 774 770 0 3,587 62,470 Kigoma Urb 667 1,560 0 67 34 0 164 2,492 Total 59,307 125,170 194 2,665 804 0 7,624 195,765 Mean Median Mode Mean Median Mode Mean Median Mode Kibondo 42 39 35 47 48 50 43 41 50 Kasulu 43 40 40 50 52 60 44 40 40 Kigoma Rur 43 41 45 49 50 45 44 42 45 Kigoma Urb 46 43 70 47 45 45 46 45 45 Total 43 40 40 49 50 60 44 41 40 District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Median, Mode of Age of Head of Agricultural Household and District 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Household Size Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 138 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 119 141 143 145 149 167 Female Heads 19 18 22 27 20 28 Total 138 159 165 172 169 195 Male headed (Percentage) 86 89 87 84 88 85 Female headed (Percentage) 14 11 13 16 12 15 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Kibondo 77,337 67,865 145,202 29,987 44,022 74,010 107,324 111,887 219,212 Kasulu 136,609 122,743 259,352 48,074 68,403 116,477 184,683 191,146 375,828 Kigoma Rural 108,789 95,040 203,829 46,425 64,043 110,468 155,214 159,083 314,297 Kigoma Urban 4,302 3,985 8,287 1,917 2,447 4,364 6,219 6,431 12,650 Total 327,037 289,632 616,670 126,403 178,915 305,318 453,441 468,547 921,988 3.14 Time Series of Male and Female Headed Households Literacy District Know Don't know Total 3.15 Literacy Rate of Heads of Households by Sex and District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 139 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 140 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 789 1 49,116 73 11,805 18 1,047 2 3,197 5 216 0 927 1 67,097 Kasulu 1,973 2 73,718 62 28,206 24 982 1 10,404 9 197 0 4,323 4 119,804 Kigoma Rur 1,667 2 49,239 54 23,192 25 2,444 3 12,792 14 294 0 2,294 2 91,921 Kigoma Urb 1,649 37 1,355 30 562 12 32 1 739 16 0 0 163 4 4,501 Total 6,079 2 173,429 61 63,765 23 4,505 2 27,132 10 708 0 7,706 3 283,323 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Kibondo 1,061 63,842 8,433 479 1,079 87 335 75,316 Kasulu 2,596 123,555 22,523 299 3,817 20 3,511 156,322 Kigoma Rur 3,157 84,429 40,351 2,145 7,631 659 1,160 139,533 Kigoma Urb 780 833 432 13 237 . 72 2,367 Total 7,595 272,660 71,739 2,936 12,764 766 5,078 373,538 % 2.0 73.0 19.2 0.8 3.4 0.2 1.4 100.0 Total Number of Households 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Land Access Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 141 LAND USE Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 142 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households with area Unusable Households of Uncultivated Usable Land Area of land Utilized by household Total Number of Households Kibondo 40,569 29,586 21,954 2,652 12,122 395 7,568 266 3,449 919 229 8,909 6,145 75,316 Kasulu 60,806 41,984 52,769 9,428 41,587 392 20,235 591 4,721 781 2,355 24,585 29,083 156,362 Kigoma Rur 27,375 31,309 47,010 7,651 27,818 478 3,576 314 3,450 1,249 474 31,149 44,889 139,533 Kigoma Urb 834 1,847 928 337 1,056 0 429 0 32 0 34 98 27 2,367 Total 129,585 104,727 122,661 20,066 82,585 1,264 31,808 1,171 11,652 2,949 3,092 64,740 80,144 373,578 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Kibondo 30,575 16,714 8,447 1,108 5,535 108 4,690 376 850 589 178 8,909 78,079 Kasulu 35,573 22,636 20,891 3,587 24,848 60 16,751 140 965 790 1,038 24,585 151,863 Kigoma Rur 15,711 18,536 30,171 5,032 19,191 401 3,343 127 926 697 508 31,149 125,793 Kigoma Urb 230 719 527 138 499 0 210 0 3 0 14 98 2,438 Total 82,089 58,605 60,037 9,865 50,073 569 24,995 643 2,744 2,076 1,738 64,740 358,173 % 22.9 16.4 16.8 2.8 14.0 0.2 7.0 0.2 0.8 0.6 0.5 18.1 100.0 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts Type of Land Use 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 143 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Kibondo 30,912 60 20,229 40 51,141 100 Kibondo 23,185 45 27,956 55 51,141 100 Kasulu 36,695 46 42,701 54 79,396 100 Kasulu 33,108 42 46,288 58 79,396 100 Kigoma Rur 28,110 46 33,590 54 61,700 100 Kigoma Rur 39,514 64 22,186 36 61,700 100 Kigoma Urb 1,963 80 495 20 2,458 100 Kigoma Urb 954 39 1,504 61 2,458 100 Total 97,680 50 97,015 50 194,695 100 Total 96,761 50 97,934 50 194,695 100 Number Percent Number Percent Number Percent Kibondo 7,319 14 43,822 86 51,141 100 Kasulu 17,353 22 62,043 78 79,396 100 Kigoma Rur 19,341 31 42,359 69 61,700 100 Kigoma Urb 626 25 1,832 75 2,458 100 Total 44,639 23 150,056 77 194,695 100 5.5 LAND USE: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.4 LAND USE: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.3 LAND USE: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census -2003 Kigoma 144 Appendix II 145 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION LONG & SHORT SEASONS Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 146 Number of household Planted area (hectare) Number of household Planted Area (hectare) Kibondo 122070 46202 42429 13542 59744 77.3 Kasulu 187674 65520 127745 53565 119085 55.0 Kigoma Rur 94596 32417 114478 50890 83307 38.9 Kigoma Urb 3,928 1,004 4,130 1,688 2,692 37.3 Total 408,268 145,143 288,782 119,685 264,828 54.8 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Kibondo 51141 266 17622 33,785 68,763 Kasulu 78610 786 58697 20,699 137,308 Kigoma Rur 52080 10,390 41314 21,156 93,394 Kigoma Urb 1931 560 1320 1,172 3,251 Total 183763 12,002 118953 76,812 302,716 District Short Season Long Season Total Number of Crop Growing Households 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area planted in Short Season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Short Season Long Season Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 147 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 6,239 4,618 74,996 55,127 81,235 59,744 92.3 Kasulu 3,118 2,885 148,268 116,200 151,386 119,085 97.6 Kigoma Rur 7,519 5,415 101,709 77,892 109,227 83,307 93.5 Kigoma Urb 232 174 3,653 2,518 3,885 2,692 93.5 Total 17,108 13,092 328,626 251,736 345,733 264,828 95.1 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 1,383 1,786 79,852 57,958 81,235 59,744 3.0 Kasulu 1,952 1,241 149,434 117,844 151,386 119,085 1.0 Kigoma Rur 466 362 108,761 82,946 109,227 83,307 0.4 Kigoma Urb 135 103 3,750 2,589 3,885 2,692 3.8 Total 3,936 3,492 341,797 261,336 345,733 264,828 1.3 % 1.5 1.3 129.1 98.7 130.6 100.0 % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long & Short Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long & Short Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 148 Number of Households Planted area (ha) Number of Households Planted area (ha) CEREALS 196,893 86,420 26,260 7,862 94,282 92 Maize 168,082 77,797 19,560 6,099 83,896 93 Paddy 11,298 4,235 2,510 620 4,855 87 Sorghum 11,935 3,260 4,190 1,144 4,404 74 Bulrush Millet 132 53 0 0 53 100 Finger Millet 5,446 1,074 0 0 1,074 100 ROOTS & TUBERS 0 0 0 0 0 0 Cassava 1,043 178 136,900 75,497 75,675 0 Sweet Potatoes 8,100 1,193 4,928 1,046 2,238 53 Irish Potatoes 573 49 193 39 88 56 PULSES 157,554 46,953 100,366 30,783 77,736 60 Mung Beans 0 0 0 0 0 0 Beans 156,692 46,723 100,196 30,764 77,486 60 Cowpeas 669 214 103 10 224 96 Green Gram 0 0 0 0 0 0 Chich Peas 0 0 0 0 0 0 Bambaranuts 193 16 67 10 26 62 OIL SEEDS & OIL NUTS 31,406 7,944 14,271 3,259 11,202 71 Sunflower 330 37 0 0 37 100 Simsim 197 140 263 53 193 72 Groundnuts 30,879 7,767 14,008 3,205 10,972 71 Soya Beans 0 0 0 0 0 0 FRUITS & VEGETABLES 6,588 811 4,944 1,073 1,884 43 Okra 0 0 123 25 25 0 Radish 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 Onions 1,384 179 657 58 238 75 Cabbage 1,010 122 750 115 237 52 Tomatoes 2,956 384 2,836 396 780 49 Spinnach 34 3 132 5 9 39 Carrot 133 8 0 0 8 100 Chillies 34 4 34 3 7 54 Amaranths 1,037 109 412 470 579 19 Total 811 0 811 100 Total Area Planted Short & Long rainy Season % Area Planted in Short rain 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Long and Short rains, Kigoma Region Long rainy Season Short rainy Season. Crop Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 149 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 77,797 98,592 1,267 6,099 7,583 1,243 83,896 106,175 2,511 Paddy 4,235 6,820 1,610 620 1,040 1,679 4,855 7,860 3,289 Sorghum 3,260 2,890 886 1,144 1,640 1,434 4,404 4,530 2,320 Bulrush Millet 53 71 1,334 0 0 0 53 71 1,334 Finger Millet 1,074 762 709 0 0 0 1,074 762 709 CEREALS 86,420 109,134 5,807 7,862 10,263 4,356 94,282 119,397 10,163 Cassava 178 165 930 75,497 129,549 1,716 75,675 129,715 2,646 Sweet Potatoes 1,193 3,103 2,602 1,046 2,209 2,113 2,238 5,312 4,715 Irish Potatoes 49 90 1,843 39 270 6,916 88 360 8,759 ROOTS & TUBERS 1,419 3,358 5,375 76,582 132,029 10,745 78,001 135,387 16,120 Mung Beans 0 0 0 0 0 0 0 0 0 Beans 46,723 24,588 526 30,764 15,716 511 77,486 40,304 1,037 Cowpeas 214 121 564 10 7 731 224 128 1,295 Green Gram 0 0 0 0 0 0 0 0 0 Chich Peas 0 0 0 0 0 0 0 0 0 Bambaranuts 16 13 810 10 6 625 26 19 1,435 PULSES 46,953 24,722 1,900 30,783 15,730 1,866 77,736 40,451 3,767 Sunflower 37 19 497 0 0 0 37 19 497 Simsim 140 163 1,164 53 41 766 193 203 1,930 Groundnuts 7,767 5,615 723 3,205 2,739 854 10,972 8,353 1,577 Soya Beans 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 7,944 5,796 2,384 3,259 2,779 1,620 11,202 8,575 4,004 Okra 0 0 0 25 13 534 25 13 534 Radish 0 0 0 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Onions 179 372 2,076 58 136 2,333 238 509 4,409 Cabbage 122 449 3,666 115 807 7,028 237 1,256 10,694 Tomatoes 384 1,285 3,343 396 1,923 4,861 780 3,209 8,204 Spinnach 3 15 4,446 5 7 1,235 9 22 5,681 Carrot 8 16 1,976 0 0 0 8 16 1,976 Chillies 4 29 7,240 3 16 4,742 7 46 11,982 Amaranths 109 372 3,410 470 16 34 579 388 3,444 FRUITS & VEGETABLES 811 2,539 26,156 1,073 2,919 20,767 1,884 5,458 46,924 Total 143,547 1,725 1,761 119,559 258,478 393 263,106 260,203 395 *The total area planted include the sum of the planted area for both Wet and Short Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Long Season to esti 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Kigoma Region Crop Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 150 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 397 80 923 499 67,443 50,757 68,763 51,335 Kasulu 783 415 4,112 3,060 132,412 82,402 137,308 85,876 Kigoma Rur 463 146 634 805 92,298 49,223 93,394 50,174 Kigoma Urb 103 473 815 605 2,334 1,174 3,251 2,251 Total 1,746 1,113 6,484 4,969 294,486 183,555 302,716 189,637 % 0.6 2.6 96.8 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kibondo 11,358 11,038 1,453 891 1,508 1,210 66,916 46,604 81,235 59,744 Kasulu 15,501 13,533 5,500 5,498 1,365 1,348 129,020 98,705 151,386 119,085 Kigoma Rur 6,340 6,430 1,885 1,144 4,363 3,193 96,640 72,540 109,227 83,307 Kigoma Urb 735 802 100 23 197 161 2,852 1,706 3,885 2,692 Total 33,934 31,803 8,938 7,557 7,433 5,913 295,428 219,555 345,733 264,828 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Long & Short Season, Kigoma District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Long & Short Season, Mwanza District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 151 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Kibondo 21,330 10,937 8,764 2,605 30,094 13,542 80.8 Kasulu 59,056 46,982 13,720 6,583 72,776 53,565 87.7 Kigoma Rur 45,475 42,766 11,672 8,124 57,147 50,890 84.0 Kigoma Urb 1,257 1,381 696 307 1,953 1,688 81.8 Total 127,118 102,067 34,852 17,618 161,970 119,685 85.3 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Long Season, 2002/03 Agriculture Year % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation Households not Using Irrigation Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 2,288 1,402 78,947 58,342 81,235 59,744 2.3 Kasulu 1,550 1,415 149,836 117,670 151,386 119,085 1.2 Kigoma Rur 3,611 2,263 105,616 81,044 109,227 83,307 2.7 Kigoma Urb 198 154 3,687 2,538 3,885 2,692 5.7 Total 7,647 5,234 338,086 259,594 345,733 264,828 2.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 2,001 1,164 66,762 50,172 68,763 51,335 2.3 Kasulu 6,802 6,612 130,506 79,264 137,308 85,876 7.7 Kigoma Rur 4,329 2,739 89,065 47,435 93,394 50,174 5.5 Kigoma Urb 829 1,017 2,422 1,235 3,251 2,251 45.2 Total 13,960 11,531 288,756 178,106 302,716 189,637 6.1 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Long & Short Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Long & Short Season. % of Planted Area Using Improved Seeds District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 153 ANNUAL CROP & VEGETABLES PRODUCTION Short SEASON Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 0 0 791 485 50,350 45,717 51,141 46,202 Kasulu 194 236 1,568 1,756 76,848 63,528 78,610 65,520 Kigoma Rur 0 0 313 675 51,767 31,741 52,080 32,417 Kigoma Urb 34 7 372 263 1,525 734 1,931 1,004 Total 229 243 3,045 3,180 180,490 141,721 183,763 145,143 % 0.1 0.2 1.7 2.2 98.2 97.6 100.0 100.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 9,176 9,933 1,058 779 888 1,085 40,019 34,404 51,141 46,202 Kasulu 14,122 12,506 4,515 4,866 975 755 58,998 47,393 78,610 65,520 Kigoma Rur 5,099 5,335 1,258 615 1,876 1,045 43,848 25,422 52,080 32,417 Kigoma Urb 431 208 69 10 67 84 1,365 702 1,931 1,004 Total 28,829 27,982 6,899 6,271 3,806 2,969 144,229 107,921 183,763 145,143 % 15.7 19.3 3.8 4.3 2.1 2.0 78.5 74.4 100.0 100.0 Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - Short SEASON, Kigoma Region. District Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Tractor Ploughing Soil Preparation 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Short SEASON, Kigoma Region District Fertilizer Use Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 155 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 934 755 50,207 45,448 51,141 46,202 1.6 Kasulu 2,715 3,590 75,896 61,930 78,610 65,520 5.5 Kigoma Rur 2,195 1,044 49,886 31,373 52,080 32,417 3.2 Kigoma Urb 238 143 1,693 861 1,931 1,004 14.3 Total 6081.299849 5531.75 177681.7799 139611.5 183763.0797 145143.2413 3.811235855 % 3.30931537 3.8112 96.690685 96.1888 100 100 District % of planted area under irrigation in Short season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Short Season, 2002/03 Agriculture Year, Kigoma Region Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 3,672 3,447 47,469 42,756 51,141 46,202 7.5 Kasulu 1,364 1,575 77,247 63,945 78,610 65,520 2.4 Kigoma Rur 2,687 1,195 49,394 31,222 52,080 32,417 3.7 Kigoma Urb 133 110 1,798 894 1,931 1,004 11.0 Total 7,856 6,326 175,907 138,817 183,763 145,143 4.4 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 817 1,601 50,324 44,601 51,141 46,202 3.5 Kasulu 587 274 78,024 65,245 78,610 65,520 0.4 Kigoma Rur 160 65 51,921 32,352 52,080 32,417 0.2 Kigoma Urb 101 65 1,831 940 1,931 1,004 6.5 Total 1,665 2,005 182,098 143,138 183,763 145,143 1.4 % of Planted Area Using Insecticides Household Using Insecticides 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short Season. Households Not Using Insecticides Total Insecticide Use Households Not Using Herbicidess Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Short Season. Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 715 636 50,426 45,567 51,141 46,202 1.4 Kasulu 580 586 78,031 64,933 78,610 65,520 0.9 Kigoma Rur 1,263 502 50,818 31,915 52,080 32,417 1.5 Kigoma Urb 99 90 1,833 914 1,931 1,004 9.0 Total 2,656 1,814 181,107 143,329 183,763 145,143 1.2 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kibondo 1,116 1,000 50,026 45,202 51,141 46,202 2.4 Kasulu 5,441 6,082 73,169 59,438 78,610 65,520 8.3 Kigoma Rur 2,630 1,793 49,450 30,624 52,080 32,417 8.1 Kigoma Urb 402 249 1,529 756 1,931 1,004 40.0 Total 9,589 9,123 174,174 136,020 183,763 145,143 6.6 % 5.2 6.3 94.8 93.7 100.0 100.0 Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted Area Using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Short SEASON 7.1f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Short Season. Fungicide Use % of Planted Area Using Fungicides Household Using Fungicides Households Not Using Fungicides Total District Tanzania Agriculture Sample Census -2003 Kigoma 158 Appendix II 159 ANNUAL CROP & VEGETABLES PRODUCTION LONG SEASON Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 160 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 2,566 1,171 27,528 12,371 30,094 13,542 8.6 Kasulu 1,755 1,310 71,021 52,255 72,776 53,565 2.4 Kigoma Rur 4,832 4,220 52,315 46,670 57,147 50,890 8.3 Kigoma Urb 99 64 1,855 1,623 1,953 1,688 3.8 Total 9,252 6,765 152,719 112,919 161,970 119,685 5.7 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 566 185 29,528 13,357 30,094 13,542 1.4 Kasulu 1,365 967 71,411 52,598 72,776 53,565 1.8 Kigoma Rur 307 297 56,840 50,594 57,147 50,890 0.6 Kigoma Urb 34 38 1,919 1,649 1,953 1,688 2.3 Total 2,272 1,487 159,698 118,198 161,970 119,685 1.2 % 1.4 1.2 98.6 98.8 100.0 100.0 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 397 80 132 13 17,093 5,040 17,622 5,133 Kasulu 589 179 2,544 1,304 55,564 18,874 58,697 20,357 Kigoma Rur 463 146 320 130 40,531 17,482 41,314 17,758 Kigoma Urb 69 466 442 342 809 439 1,320 1,247 Total 1,517 870 3,439 1,789 113,997 41,835 118,953 44,494 % 1.3 2.0 2.9 4.0 95.8 94.0 100.0 100.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 2,182 1,105 395 112 620 125 26,897 12,200 30,094 13,542 Kasulu 1,378 1,027 985 633 390 593 70,023 51,312 72,776 53,565 Kigoma Rur 1,241 1,096 627 529 2,487 2,148 52,792 47,118 57,147 50,890 Kigoma Urb 304 594 32 13 131 77 1,487 1,004 1,953 1,688 Total 5,105 3,821 2,039 1,286 3,628 2,944 151,198 111,634 161,970 119,685 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 21,330 10,937 8,764 2,605 30,094 13,542 80.8 Kasulu 59,056 46,982 13,720 6,583 72,776 53,565 87.7 Kigoma Rur 45,475 42,766 11,672 8,124 57,147 50,890 84.0 Kigoma Urb 1,257 1,381 696 307 1,953 1,688 81.8 Total 127,118 102067 34852 17618 161,970 119685 85.3 % 78.5 85.3 21.5 14.7 100.0 100.0 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Long SEASON, Mwanza Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - Long SEASON, Mwanza Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of planted area under irrigation in short season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Long Season, 2002/03 Agriculture Year, Mwanza Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kibondo 1,573 767 28,520 12,775 30,094 13,542 5.7 Kasulu 970 828 71,806 52,737 72,776 53,565 1.5 Kigoma Rur 2,349 1,761 54,798 49,129 57,147 50,890 3.5 Kigoma Urb 99 64 1,855 1,623 1,953 1,688 3.8 Total 4,991 3,420 156,979 116,265 161,970 119,685 2.9 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kibondo 885 163 16,737 4,969 17,622 5,133 3.2 Kasulu 1,361 530 57,337 19,826 58,697 20,357 2.6 Kigoma Rur 1,698 946 39,616 16,811 41,314 17,758 5.3 Kigoma Urb 427 768 893 479 1,320 1,247 61.6 Total 4,371 2,408 114,582 42,086 118,953 44,494 5.4 % 4 5 96 95 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Long SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under Improved Seed use in Long season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Long SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 163 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 44,152 547 47,862 65 828 4,976 54,278 Maize 162 66 17,009 11,937 196 57 0 0 3,379 827 20,746 12,886 Paddy 616 282 44,140 31,164 83 8 905 828 1,539 897 47,283 33,180 Sorghum 104 42 4,065 2,237 0 0 0 0 6,594 3,021 10,764 5,300 Bulrush Millet 235 157 1,692 1,616 0 0 0 0 334 122 2,261 1,895 Finger Millet 0 0 1,416 908 0 0 0 0 90 109 1,506 1,017 ROOTS & TUBERS 263 10,764 0 43 0 452 11,522 Cassava 0 0 636 201 0 0 0 0 85 11 721 212 Sweet Potatoes 651 196 40,255 10,547 0 0 214 43 1,816 440 42,936 11,227 Irish Potatoes 166 67 167 15 0 0 0 0 0 0 333 83 PULSES 297 25,125 0 2,359 4,576 32,357 Mung Beans 0 0 0 0 0 0 0 0 0 0 0 0 Beans 137 55 6,099 1,433 0 0 0 0 699 190 6,935 1,679 Cowpeas 0 0 2,526 435 0 0 0 0 368 31 2,894 467 Green Gram 0 0 1,146 285 0 0 0 0 0 1,146 285 Chich Peas 0 0 14,338 22,812 0 0 201 2,359 2,802 4,325 17,341 29,496 Bambaranuts 194 242 879 160 0 0 0 0 308 30 1,381 431 OIL SEEDS & OIL NUTS 0 0 580 0 28 17 625 Sunflower 0 0 0 0 0 0 0 0 0 0 0 0 Simsim 0 0 289 58 0 0 0 0 0 0 289 58 Groundnuts 0 0 1,220 521 0 0 88 28 139 17 1,446 566 Soya Beans 0 0 0 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 36 1,087 0 0 186 1,309 Okra 0 0 0 0 0 0 0 0 0 0 0 0 Radish 0 0 169 10 0 0 0 0 0 0 169 10 Turmeric 0 0 0 0 0 0 0 0 0 0 0 0 Onions 90 18 567 92 0 0 0 0 0 0 656 110 Cabbage 0 0 965 108 0 0 0 0 160 20 1,125 127 Tomatoes 90 18 4,598 711 0 0 0 0 637 125 5,325 855 Spinnach 0 0 471 33 0 0 0 0 51 10 522 44 Carrot 0 0 302 55 0 0 0 0 0 0 302 55 Chillies 0 0 476 28 0 0 0 0 54 8 531 35 Amaranths 0 0 406 50 0 0 0 0 153 23 559 73 Total 1,144 85,417 65 3,259 10,206 100,091 % 1.1 85.3 0.1 3.3 10.2 100 Crop 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households During Long Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 164 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 50,747 27,048 32,160 1.189 571 147 76 0.5206 27,195 32,237 1.1854 Kasulu 77,827 35,988 46,936 1.304 2,958 971 649 0.6686 36,958 47,585 1.2875 Kigoma Rural 37,815 14,290 19,049 1.333 15,175 4,693 6,651 1.4172 18,983 25,700 1.3539 Kigoma Urban 1,693 471 447 0.948 857 288 206 0.7157 760 653 0.8596 Total 168,082 77,797 98,592 1.267 19,560 6,099 7,583 1.2433 83,896 106,175 1.2656 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 132 53 71 1.3 0 0 0 53 71 1.3 Kasulu 0 0 0 0.0 0 0 0 0 0 0.0 Kigoma Rural 0 0 0 0.0 0 0 0 0 0 0.0 Kigoma Urban 0 0 0 0.0 0 0 0 0 0 0.0 Total 132 53 71 1.3 0 0 0 53 71 1.3 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year Burlush millet District Short Season Long Season Total Long Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year Maize District Short Season Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 165 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 1,989 618 423 0.685 1,328 336 689 2.050 954 1,112 1.166 Kasulu 8,067 1,931 4,301 2.228 197 28 35 1.270 1,959 4,337 2.214 Kigoma Rural 1,242 1,687 2,095 1.242 759 173 249 1.441 1,859 2,344 1.261 Kigoma Urban 0 0 0 0.000 226 83 68 0.812 83 68 0.812 Total 11,298 4,235 6,820 1.610 2,510 620 1,040 1.679 4,855 7,860 1.619 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 6,863 2,069 1,696 0.820 2,617 806 1,171 1.453 2,875 2,866 0.997 Kasulu 4,923 1,161 1,164 1.003 1,573 338 469 1.389 1,499 1,634 1.090 Kigoma Rural 149 30 30 0.988 0 0 0 0.000 30 30 0.988 Kigoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 11,935 3,260 2,890 0.886 4,190 1,144 1,640 1.434 4,404 4,530 1.029 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Paddy District Short Season Long Season Total 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Sorghum District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 3,473 715 426 0.596 0 0 0 715 426 0.596 Kasulu 1,973 360 335 0.933 0 0 0 360 335 0.933 Kigoma Rural 0 0 0 0.000 0 0 0 0 0 0.000 Kigoma Urban 0 0 0 0.000 0 0 0 0 0 0.000 Total 5,446 1,074 762 0.709 0 0 0 1,074 762 0.709 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 42,787 12,073 6,355 0.526 9,395 2,221 1,024 0.461 14,293 7,379 0.516 Kasulu 70,214 21,852 11,214 0.513 53,184 17,499 8,418 0.481 39,351 19,632 0.499 Kigoma Rural 42,100 12,399 6,865 0.554 36,863 10,814 6,183 0.572 23,214 13,048 0.562 Kigoma Urban 1,591 399 154 0.387 754 230 90 0.393 628 245 0.389 Total 156,692 46,723 24,588 0.526 100,196 30,764 15,716 0.511 77,486 40,304 0.520 Long Season Total 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Short Season 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 167 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 0 0 Kasulu 0 0 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 0 0 Kigoma Urban 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 0 0 0 Kasulu 0 0 0 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 0 0 0 Kigoma Urban 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung beans District Short Season Long Season Total 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 168 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kasulu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kigoma Rural 635 206 119 0.576 0 0 0 0.000 206 119 0.576 Kigoma Urban 34 8 2 0.265 103 10 7 0.000 18 9 0.525 Total 669 214 121 0.564 103 10 7 0.731 224 128 0.572 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 0.000 Kasulu 0 0 0 0 0 0 0 0 0.000 Kigoma Rural 160 13 11 0 0 0 13 11 0.865 Kigoma Urban 32 3 2 67 10 6 13 8 0.617 Total 193 16 13 67 10 6 26 19 0.739 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Short Season Long Season Total Long Season Total 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Cowpeas District Short Season Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 169 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0.000 0 0 0 0 0 0 Kasulu 0 0 0 0.000 0 0 0 0 0 0 Kigoma Rural 0 0 0 0.000 0 0 0 0 0 0 Kigoma Urban 0 0 0 0.000 0 0 0 0 0 0 Total 0 0 0 0.000 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 133 27 9 0.336 21,468 8,476 8,977 1.06 8,503 8,986 1.057 Kasulu 589 105 111 1.058 62,581 33,447 57,355 1.71 33,553 57,467 1.713 Kigoma Rural 320 45 45 0.988 51,560 33,133 61,810 1.87 33,178 61,855 1.864 Kigoma Urban 0 0 0 0.000 1,291 441 1,407 3.19 441 1,407 3.194 Total 1,043 178 165 0.930 136,900 75,497 129,549 1.72 75,675 129,715 1.714 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick peas District Short Season Long Season Total 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 170 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 531 105 54 0.513 133 27 19 0.692 132 72 0.550 Kasulu 5,872 637 1,581 2.483 589 60 160 2.678 696 1,741 2.500 Kigoma Rural 1,561 412 1,417 3.440 3,677 798 1,937 2.427 1,210 3,353 2.772 Kigoma Urban 135 39 51 1.309 529 161 95 0.587 200 146 0.728 Total 8,100 1,193 3,103 2.602 4,928 1,046 2,209 2.113 2,238 5,312 2.374 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kasulu 573 49 90 1.843 193 39 270 6.916 88 360 4.100 Kigoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kigoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 573 49 90 1.843 193 39 270 6.916 88 360 4.100 Long Season Total 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Short Season 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 10,934 2,523 1,797 0.712 4,244 1,215 846 0.696 3,738 2,643 0.707 Kasulu 11,384 2,446 1,743 0.713 5,096 1,024 1,031 1.006 3,470 2,774 0.799 Kigoma Rural 8,460 2,789 2,068 0.741 4,600 954 850 0.890 3,743 2,917 0.779 Kigoma Urban 101 9 7 0.790 69 12 13 1.063 21 20 0.946 Total 30,879 7,767 5,615 0.723 14,008 3,205 2,739 0.854 10,972 8,353 0.761 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 133 13 5 0 0 0 0 0.000 13 5 0.356 Kasulu 197 24 14 1 0 0 0 0.000 24 14 0.576 Kigoma Rural 0 0 0 0 0 0 0 0.000 0 0 0.000 Kigoma Urban 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 330 37 19 0 0 0 0 0.000 37 19 0.497 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Short Season Long Season Total 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 0.000 Kasulu 0 0 0 0 0 0 0 0 0.000 Kigoma Rural 0 0 0 0 0 0 0 0 0.000 Kigoma Urban 0 0 0 0 0 0 0 0 0.000 Total 0 0 0 0 0 0 0 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 0 Kasulu 0 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 0 Kigoma Urban 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 Long Season Total 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Short Season 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year Tumeric District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 173 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 664 77 98 664 77 98 154 195 Kasulu 583 75 272 583 75 272 150 544 Kigoma Rural 137 28 3 137 28 3 55 5 Kigoma Urban 0 0 0 0 0 0 0 0 Total 1,384 179 372 1,384 179 372 359 745 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 457 58 186 1,281 135 663 193 848 Kasulu 1,365 140 471 390 59 683 200 1,154 Kigoma Rural 1,068 170 555 1,066 185 516 354 1,071 Kigoma Urban 67 17 74 99 17 62 33 136 Total 2,956 384 1,285 2,836 396 1,923 780 3,209 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Short Season Long Season Total 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 174 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 132 5 7 5 7 Kasulu 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 Kigoma Urban 34 3 15 0 0 0 3 15 Total 34 3 15 132 5 7 9 22 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 133 8 16 0 0 0 8 16 Kasulu 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 Kigoma Urban 0 0 0 0 0 0 0 0 Total 133 8 16 0 0 0 8 16 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year Carrot District Short Season Long Season Total Long Season Total 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Short Season Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 175 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 0 0 0 0 0 0 0 0 Kasulu 0 0 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 0 0 0 0 Kigoma Urban 34 4 29 34 3 16 7 46 Total 34 4 29 34 3 16 7 46 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kibondo 361 39 42 1.090 0 0 0 0.000 39 42 1.090 Kasulu 388 28 16 0.561 197 20 8 0.395 48 23 0.491 Kigoma Rural 150 15 285 18.772 146 30 4 0.148 45 289 6.456 Kigoma Urban 137 27 29 1.066 69 421 4 0.009 448 33 0.074 Total 1,037 109 372 3.410 412 470 16 0.034 579 388 0.670 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year Chillies District Short Season Long Season Total 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Kigoma 176 Appendix II 177 PERMANENT CROPS Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 178 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Pigeon Pea 103 1,416 39 27 Palm Oil 53 0 1 0 Cashewnut 27 0 0 0 Coffee 426 22 19 898 Sugarcane 23 62 1,953 31,571 Banana 7,586 2,119 20,726 9,780 Avocado 202 55 65 1,170 Mango 326 165 3,825 23,152 Pawpaw 180 101 266 2,651 Pineapple 27 27 0 0 Orange 72 66 0 0 Mandarine/Tangerine 26 0 1,014 0 Guava 20 12 303 25,562 Lime/Lemon 3 0 0 0 Total 9,073 4,044 28,210 6,976 Kasulu Sour Soup 27 0 0 0 Pigeon Pea 604 638 374 587 Palm Oil 1,105 1,953 2,003 1,026 Coffee 401 5,112 869 170 Sugarcane 784 361 2,171 6,012 Banana 10,136 5,102 47,312 9,273 Avocado 0 0 47 0 Mango 6,936 114 6,540 57,166 Pawpaw 0 . 3 0 Pineapple 66 20 88 4,455 Orange 294 44 762 17,500 Mandarine/Tangerine 0 0 72 0 Guava 16 0 122 0 Lime/Lemon 20 8 43 5,457 Total 20,389 13,352 60,409 4,524 Pigeon Pea 243 197 183 930 Palm Oil 8,747 7,438 38,066 5,118 Coffee 265 84 424 5,022 Sugarcane 135 63 8,597 136,698 Mpesheni 6 0 3 0 Banana 2,762 1,657 27,697 16,711 Avocado 1 0 . 0 Mango 86 45 734 16,356 Pawpaw 19 6 11 1,689 Pineapple 130 65 1,634 25,281 Orange 543 480 4,723 9,835 Mandarine/Tangerine 2 0 8 0 Guava 5 0 16 0 Total 12,945 10,036 82,097 8,180 Kigoma Urban Pigeon Pea 5 2 9 3,923 Palm Oil 382 182 437 2,402 Coconut 7 7 3 494 Banana 18 12 93 7,845 Mango 28 22 235 10,666 Pawpaw 1 0 38 0 Orange 0 0 73 0 Mandarine/Tangerine 4 0 3 0 Lime/Lemon 0 . 8 0 Total 446 225 900 3,995 Kigoma Rural District/Crop Kibondo 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Kigoma. Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 179 Crop Area Planted % Mango 7,376 25.59 Orange 909 3.15 Banana 20,502.7 71.12 Guava 40 0.14 Total 28,828 100.00 District Area Planted with Orange Total Area Planted (Ha) % of Total Area Planted Households with Orange Average Planted Area per Household Kibondo 72 9,073 0.8 392 0.2 Kasulu 294 20,389 1.4 976 0.3 Kigoma Rural 543 12,945 4.2 764 0.7 Kigoma Urban 0 446 0.0 0 0.0 Total 909 42,853 2.1 15,446 0.1 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Households with Banana Average Planted Area per Household Kibondo 7,586 9,073 83.6 14,334.0 0.5 Kasulu 10,136 20,389 49.7 22,132 0.5 Kigoma Rural 2,762 12,945 21.3 7,811.0 0.4 Kigoma Urban 18 446 4.0 167.0 0.1 Total 20,502 42,853 47.8 44,444 1.0 Banana 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Kigoma Region Orange 7.3.3 PERMANENT CROPS: Area Planted with Oranges by District 7.3.4 PERMANENT CROPS: Area planted with Banana by District Tanzania Agriculture Sample Census -2003 Kigoma 180 Appendix II 181 AGROPROCESSING Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 182 Number % Number % Number % Kibondo 50,158 98 1,249 2 51,407 100 Kasulu 71,512 90 7,884 10 79,396 100 Kigoma Rural 61,219 98 1,251 2 62,470 100 Kigoma Urban 2,359 95 133 5 2,492 100 Total 185,249 95 10,517 5 195,765 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader Other Total Kibondo 2,623 2,409 45,043 0 0 50,075 Kasulu 2,727 3,315 50,027 15,049 395 71,512 Kigoma Rural 3,471 6,894 14,894 35,007 0 60,266 Kigoma Urban 420 0 907 1,032 0 2,359 Total 9,241 12,618 110,871 51,088 395 184,212 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm Other Total Maize 11,089 9,337 247,899 12,761 152 151 281,388 Paddy 20,484 2,627 82,965 7,163 104 493 113,836 Sorghum 1,107 602 20,068 791 0 0 22,567 Bulrush Millet 1,355 0 1,362 0 0 0 2,717 Cassava 60,362 1,092 47,926 1,831 0 0 111,211 Beans 505 0 306 0 0 0 812 Cowpeas 223 0 75 0 0 0 298 Bambaranut 0 0 0 0 0 0 0 Total 95,124 13,658 400,602 22,546 256 644 532,830 8.1.1b AGRO PROCESSING: Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing Method of Processing Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Kigoma Region 8.1.1a AGRO PROCESSING: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Processed Products Households That did not Process Products Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 183 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 167,941 133 165 196 133 0 168,568 Paddy 10,271 0 324 0 0 0 10,595 Sorghum 6,699 0 131 0 0 0 6,830 Finger Millet 2,494 0 0 0 133 0 2,628 Cassava 97,443 0 1,065 196 0 0 98,703 Beans 15,177 0 83 0 0 0 15,260 Pigeon Peas 132 0 0 0 0 0 132 Groundnut 4,493 197 158 0 0 0 4,848 Oil Palm 4,301 1,184 10,672 0 0 0 16,158 Tobacco 0 0 133 0 0 0 133 Coffee 0 0 2,557 0 0 0 2,557 Banana 2,023 0 3,856 0 0 0 5,879 Mango 133 0 0 0 0 0 133 Orange 0 0 160 0 0 0 160 Total 311,107 1,514 19,305 391 267 0 332,584 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 4,889 6,428 0 33 266 0 274 2,368 154,309 168,568 Paddy 342 490 0 0 0 0 32 0 9,731 10,595 Sorghum 131 195 0 0 0 0 0 0 6,504 6,830 Finger Millet 0 0 0 0 0 0 0 0 2,628 2,628 Cassava 5,894 9,903 0 0 0 197 1,195 1,776 79,739 98,703 Beans 0 127 0 0 0 0 0 0 15,133 15,260 Pigeon Peas 0 0 0 0 0 0 0 0 132 132 Groundnut 133 277 0 0 0 0 158 0 4,280 4,848 Oil Palm 2,529 4,449 0 0 0 0 6,258 32 2,891 16,158 Tobacco 0 133 0 0 0 0 0 0 0 133 Coffee 481 0 0 159 1,918 0 0 0 0 2,557 Banana 3,114 197 0 0 0 0 919 197 1,451 5,879 Mango 0 0 0 0 0 0 0 0 133 133 Orange 0 0 0 0 0 0 160 0 0 160 Total 17,513 22,199 0 192 2,184 197 8,995 4,373 276,931 332,584 Flour / Meal Grain Oil Juice Fiber Other Total Kibondo 49,810 265 83 0 0 0 50,158 Kasulu 63,300 5,498 1,735 980 0 0 71,512 Kigoma Rural 50,521 3,328 7,371 0 0 0 61,219 Kigoma Urban 1,570 33 756 0 0 0 2,359 Total 165,201 9,124 9,944 980 0 0 185,249 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Kibondo 49,892 133 0 0 133 50,158 Kasulu 70,138 0 1,374 0 0 71,512 Kigoma Rural 51,115 0 10,103 0 0 61,219 Kigoma Urban 1,640 0 719 0 0 2,359 Total 172,786 133 12,197 0 133 185,249 District Product Use 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Kigoma Region District Main Product 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Kigoma Region Product Use Crop 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Kigoma Region Where Sold 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Kigoma Region Crop Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 184 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Kibondo 483 3,233 0 0 266 0 121 0 46,056 50,158 Kasulu 3,116 2,367 0 0 0 0 394 2,565 63,070 71,512 Kigoma Rural 3,269 6,709 0 159 1,918 0 3,953 0 45,211 61,219 Kigoma Urban 297 463 0 33 0 0 359 32 1,175 2,359 Total 7,165 12,772 0 192 2,184 0 4,827 2,597 155,512 185,249 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Kibondo 466 133 2,255 0 0 0 0 1,147 46,157 0 50,158 Kasulu 1,774 191 3,550 591 1,574 3,103 394 786 59,549 0 71,512 Kigoma Rural 1,565 320 1,044 0 159 470 319 2,697 52,588 2,057 61,219 Kigoma Urban 507 64 32 0 134 69 32 455 1,068 0 2,359 Total 4,311 708 6,881 591 1,866 3,642 745 5,085 159,362 2,057 185,249 District By Product 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Kigoma Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Kigoma Region Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 185 MARKETING Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 186 Number % Number % Kibondo 33,570 65.3 17,837 34.7 51,407 Kasulu 74,709 94.1 4,687 5.9 79,396 Kigoma Rural 57,196 91.6 5,274 8.4 62,470 Kigoma Urban 2,158 86.6 334 13.4 2,492 Total 167,633 85.6 28,133 14.4 195,765 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Total Kibondo 526 21128 0 0 0 132 0 26769 48556 Kasulu 2758 16075 783 0 197 0 589 57027 77429 Kigoma Rural 310 7619 153 155 154 0 314 53616 62321 Kigoma Urban 0 336 0 0 0 0 0 2122 2458 Total 3593 45158 937 155 352 132 903 139534 190764 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Total Kibondo 1 44 0 0 0 0 0 55 100 Kasulu 4 21 1 0 0 0 1 74 100 Kigoma Rural 0 12 0 0 0 0 1 86 100 Kigoma Urban 0 14 0 0 0 0 0 86 100 Total 2 24 0 0 0 0 0 73 100 10.2 MARKETING: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Kigoma Region District Main Reasons for Not Selling Crops Main Reasons for Not Selling Crops District 10.3 MARKETING: Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Kigoma Region 10.1 MARKETING: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Kigoma Region Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 187 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 188 Number of Household % Number of Household % Number of Household % Kibondo 2,307 4 49,100 96 51,407 100 Kasulu 9,379 12 70,017 88 79,396 100 Kigoma Rural 5,462 9 57,008 91 62,470 100 Kigoma Urban 268 11 2,224 89 2,492 100 Total 17,417 9 178,348 91 195,765 100 District Irrigatable Area (ha) Irrigated Land (ha) % Kibondo 571 409 72 Kasulu 2,760 2,186 79 Kigoma Rural 1,646 1,520 92 Kigoma Urban 52 42 81 Total 5,019 4,167 83 River Lake Dam Well Borehole Canal Pipe water Total Kibondo 2,042 0 0 265 0 0 0 2,307 Kasulu 7,626 0 193 778 197 585 0 9,379 Kigoma Rural 4,112 751 0 146 0 453 0 5,462 Kigoma Urban 137 0 0 131 0 0 0 268 Total 13,917 751 193 1,321 197 1,038 0 17,417 Gravity Hand Bucket Hand Pump Motor Pump Total Kibondo 1,552 755 0 0 2,307 Kasulu 5,883 3,496 0 0 9,379 Kigoma Rural 1,246 4,216 0 0 5,462 Kigoma Urban 0 268 0 0 268 Total 8,681 8,736 0 0 17,417 District Method of Obtaining Water 11.4 IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 189 Flood Sprinkler Water Hose Bucket / Watering Can Total Kibondo 890 0 0 1,417 2,307 Kasulu 5,306 197 0 3,876 9,379 Kigoma Rural 1,246 0 160 4,057 5,462 Kigoma Urban 0 0 0 268 268 Total 7,442 197 160 9,618 17,417 Number % Number % Kibondo 4,072 8 47,336 92 51,407 Kasulu 7,214 9 72,183 91 79,396 Kigoma Rural 8,017 13 54,453 87 62,470 Kigoma Urban 68 3 2,424 97 2,492 Total 19,370 10 176,395 90 195,765 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Kibondo 0 107,746 0 1,333 929 933 1,714 0 112,654 Kasulu 0 44,683 0 573 9,138 974 7,939 197 63,505 Kigoma Rural 14,158 237,631 0 479 618 0 3,678 154 256,718 Kigoma Urban 0 3,388 0 0 0 0 0 0 3,388 Total 14,158 393,448 0 2,385 10,684 1,907 13,331 351 436,265 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6 IRRIGATION: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census -2003 Kigoma 190 Appendix II 191 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 192 No of households % No of households % Kibondo 2,171 4.2 49,236 95.8 51,407 Kasulu 5,292 6.7 74,104 93.3 79,396 Kigoma Rural 6,885 11.0 55,585 89.0 62,470 Kigoma Urban 266 10.7 2,226 89.3 2,492 Total 14,614 7.5 181,151 92.5 195,765 No of households % No of households % Kibondo 12,388 24 39,403 76 51,791 Kasulu 17,840 22 61,556 78 79,396 Kigoma Rural 9,958 16 52,512 84 62,470 Kigoma Urban 860 34 1,632 66 2,492 Total 41,045 21 155,104 79 196,150 No of households % No of households % Kibondo 2,114 4.1 49,172 95.9 51,286 Kasulu 7,472 9.4 71,925 90.6 79,396 Kigoma Rural 6,045 9.7 56,425 90.3 62,470 Kigoma Urban 409 16.4 2,083 83.6 2,492 Total 16,039 8.2 179,605 91.8 195,644 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 193 No of households % No of households % Kibondo 3,949 8 47,459 92 51,407 Kasulu 3,133 4 76,263 96 79,396 Kigoma Rural 6,266 10 56,204 90 62,470 Kigoma Urban 165 7 2,326 93 2,492 Total 13,513 7 182,252 93 195,765 No of households % No of households % Kibondo 0 0 51,407 100 51,407 Kasulu 0 0 79,396 100 79,396 Kigoma Rural 149 0 62,321 100 62,470 Kigoma Urban 0 0 2,492 100 2,492 Total 149 0 195,616 100 195,765 No of households % No of households % Kibondo 2,010 4 49,397 96 51,407 Kasulu 6,447 8 72,949 92 79,396 Kigoma Rural 4,917 8 57,553 92 62,470 Kigoma Urban 589 24 1,903 76 2,492 Ilemela 13,963 7 181,802 93 195,765 Total 27,926 51 363,604 449 391,531 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 194 Number % Number % Number % Number % Kibondo 1,905 3.7 0 0.0 0 0.0 49,236 95.8 51,141.4 Kasulu 4,108 5.2 0 0.0 0 0.0 74,104 93.3 78,212.3 Kigoma Rural 4,490 7.2 319 0.5 160 0.3 55,585 89.0 60,554.2 Kigoma Urban 266 10.7 0 0.0 0 0.0 2,226 89.3 2,491.9 Total 10,770 5.5 319 0.16 160 0.08 181,151 92.5 192,399.8 Number % Number % Number % Number % Number % Number % Kibondo 0 0.0 0 0.0 133 0.3 9,363 18.1 2,760 5.3 39,403 76.1 Kasulu 197 0.2 0 0.0 193 0.2 15,294 19.3 1,960 2.5 61,556 77.5 Kigoma Rural 0 0.0 0 0.0 0 0.0 7,799 12.5 1,998 3.2 52,512 84.1 Kigoma Urban 0 0.0 32 1.3 0 0.0 627 25.1 201 8.1 1,632 65.5 Total 197 0.1 32 0.0 326 0.2 33,083 16.9 6,920 3.5 155,104 79.1 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Local Market / Trade Store Local Farmers Grou Neighbour Not applicable Total Locally Produced by Neighbour Not applicable 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Large Scale Farm Local Farmers Group Local Market / Trade Store Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 195 Number % Number % Number % Number % Number % Kibondo 0 0.0 0 0.0 2,114 4.1 0 0.0 49,172 95.9 51,286 Kasulu 0 0.0 0 0.0 7,080 8.9 194 0.2 71,925 90.6 79,199 Kigoma Rural 156 0.2 0 0.0 5,578 8.9 156 0.2 56,425 90.3 62,314 Kigoma Urban 0 0.0 0 0.0 409 16.4 0 0.0 2,083 83.6 2,492 Total 156 0.1 0 0.0 15,181 7.8 350 0.2 179,605 91.8 195,292 Number % Number % Number % Number % Number % Kibondo 2,600 5.1 262 0.5 500 1.0 455 0.9 47,459 92.3 51,276 Kasulu 2,541 3.2 0 0.0 592 0.7 0 0.0 76,263 96.1 79,396 Kigoma Rural 3,563 5.7 309 0.5 1,916 3.1 160 0.3 56,204 90.0 62,151 Kigoma Urban 165 6.6 0 0.0 0 0.0 0 0.0 2,326 93.4 2,492 Total 8,869 4.5 571 0.3 3,008 1.5 615 0.3 182,252 93.1 195,315 Number % Number % Kibondo 0 0.0 51,407 100.0 Kasulu 0 0.0 79,396 100.0 Kigoma Rural 149 0.2 62,321 99.8 Kigoma Urban 0 0.0 2,492 100.0 Total 149 0.1 195,616 99.9 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Co-operative Crop Buyers Locally Produced by Household Neighbour Not applicable District Not applicable Total Total 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Neighbour Co-operative District Local Market / Trade Store Not applicable Locally Produced by Household District Local Market / Trade Store 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 196 Number % Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 0 0.0 1,116 2.2 0 0.0 133 0.3 262 0.5 500 1.0 0 0.0 0 0.0 49,265 96 51,143 Kasulu 192 0.2 3,722 4.7 0 0.0 0 0.0 0 0.0 0 0.0 1,754 2.2 779 1.0 72,949 92 77,642 Kigoma Rural 319 0.5 4,131 6.6 153 0.2 0 0.0 153 0.2 160 0.3 0 0.0 0 0.0 57,553 92 62,470 Kigoma Urban 0 0.0 459 18.4 0 0.0 0 0.0 0 0.0 32 1.3 66 2.7 32 1.3 1,903 76 2,426 Total 511 0.3 9,428 4.8 153 0.1 133 0.1 415 0.2 692 0.4 1,820 0.9 811 0.4 181,670 93 193,681 Number % Number % Number % Number % Number % Kibondo 132 6 398 18 525 24 396 18 720 33 2,171 Kasulu 1,369 26 580 11 1,574 30 587 11 1,183 22 5,292 Kigoma Rural 1,594 23 1,277 19 1,281 19 618 9 2,115 31 6,885 Kigoma Urban 0 0 0 0 232 87 34 13 0 0 266 Total 3,094 21 2,255 15 3,612 25 1,636 11 4,017 27 14,614 Number % Number % Number % Number % Number % Kibondo 10,751 87 796 6 442 4 266 2 133 1 12,388 Kasulu 16,459 92 1,381 8 0 0 0 0 0 0 17,840 Kigoma Rural 9,649 97 160 2 149 1 0 0 0 0 9,958 Kigoma Urban 725 84 100 12 34 4 0 0 0 0 860 Total 37,584 92 2,437 6 625 2 266 1 133 0 41,045 Between 10 and 20 km 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Locally Produced by Household Neighbour 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Total Not applicable District Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Co-operative Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 197 Number % Number % Kibondo 2,114 100 0 0 2,114 Kasulu 7,274 97 197 2.6 7,471.8 Kigoma Rural 6,045 100 0 0.0 6,044.7 Kigoma Urban 409 100 0 0.0 409.0 Total 15,842 99 197 1.2 16,039.3 Number % Number % Number % Number % Number % Kibondo 121 6 765 38 532 26 133 7 460 23 2,010 Kasulu 3,520 55 1,179 18 0 0 193 3 1,555 24 6,447 Kigoma Rural 779 16 315 6 479 10 295 6 3,048 62 4,917 Kigoma Urban 100 17 32 5 356 61 100 17 0 0 589 Total 4,521 32 2,291 16 1,367 10 721 5 5,063 36 13,963 Less than 1 km Number % Number % Number % Number % Number % Kibondo 457 12 885 22 1,588 40 661 17 358 9 3,949 Kasulu 592 19 191 6 789 25 197 6 1,363 44 3,133 Kigoma Rural 1,582 25 1,277 20 1,121 18 305 5 1,981 32 6,266 Kigoma Urban 0 0 0 0 131 79 34 21 0 0 165 Total 2,631 19 2,353 17 3,629 27 1,198 9 3,702 27 13,513 District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total Number 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Total Number Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 198 Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 3,377 7 44,818 91 264 1 0 0 0 0 777 2 0 0 0 0 49,236 Kasulu 5,863 8 64,722 87 785 1 589 1 392 1 782 1 0 0 972 1 74,104 Kigoma Rural 4,946 9 49,094 88 0 0 0 0 313 1 1,233 2 0 0 0 0 55,585 Kigoma Urban 65 3 2,029 91 0 0 0 0 32 1 66 3 0 0 34 2 2,226 Total 14,251 8 160,662 89 1,049 1 589 0 737 0 2,857 2 0 0 1,006 1 181,151 Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 17,247 44 11,075 28 7,675 19 1,061 3 782 2 1,562 4 0 0 0 0 39,403 Kasulu 35,285 57 18,051 29 5,304 9 1,170 2 387 1 971 2 0 0 389 1 61,556 Kigoma Rural 26,640 51 11,094 21 7,313 14 3,479 7 772 1 1,234 2 146 0 1,832 3 52,512 Kigoma Urban 362 22 970 59 69 4 163 10 0 0 33 2 0 0 34 2 1,632 Total 79,535 51 41,190 27 20,361 13 5,874 4 1,941 1 3,801 2 146 0 2,256 1 155,104 Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 1,388 3 5,087 10 34,746 71 4,656 9 1,473 3 0 4 0 0 0 0 47,350 Kasulu 10,974 15 17,473 24 31,752 44 1,557 2 5,076 7 1,550 2 0 0 3,542 5 68,382 Kigoma Rural 3,673 7 2,000 4 43,479 77 2,459 4 2,666 5 2,148 4 0 0 0 0 56,425 Kigoma Urban 99 5 403 19 1,379 65 33 2 100 5 68 3 0 0 34 2 2,083 Total 16,134 9 24,964 14 111,356 62 8,706 5 9,316 5 5,587 3 0 0 3,576 2 176,063 Too Much Labour Required Too Much Labour Required Do not Know How to Use Total Locally Produced by Household Other Total Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Total Input is of No Use Locally Produced by Household Do not Know How to Use Input is of No Use 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Other Input is of No Use Locally Produced by Household 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 199 Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 3,087 7 40,380 85 697 1 254 1 1,474 3 1,433 3 133 0 0 0 47,459 Kasulu 13,116 17 57,672 76 1,174 2 785 1 1,572 2 582 1 0 0 1,364 2 76,263 Kigoma Rural 3,212 6 49,119 87 456 1 0 0 2,490 4 927 2 0 0 0 0 56,204 Kigoma Urban 65 3 2,162 93 0 0 0 0 32 1 33 1 0 0 34 1 2,326 Total 19,480 11 149,334 82 2,326 1 1,039 1 5,567 3 2,975 2 133 0 1,398 1 182,252 Number % Number % Number % Number % Number % Number % Number % Kibondo 10,260 20.0 35,499 69.1 878 1.7 0 0.0 1,272 2 3,395 7 0 0 51,305 Kasulu 20,321 25.6 52,412 66.0 1,568 2.0 390 0.5 2,754 3 390 0 1,561 2 79,396 Kigoma Rural 3,819 6.1 50,630 81.2 296 0.5 0 0.0 4,044 6 3,532 6 0 0 62,321 Kigoma Urban 928 37.3 1,071 43.0 65 2.6 0 0.0 32 1 361 15 34 1 2,492 Total 35,328 18.1 139,612 71.4 2,808 1.4 390 0 8,101 4 7,679 4 1,595 1 195,514 Number % Number % Number % Number % Number % Number % Number % Number % Kibondo 7,609 15 40,960 83 263 1 0 0 96 0 468 1 0 0 0 0 49,397 Kasulu 10,778 15 58,257 80 1,180 2 585 1 394 1 390 1 197 0 1,169 2 72,949 Kigoma Rural 8,304 14 46,763 81 588 1 0 0 158 0 1,586 3 154 0 0 0 57,553 Kigoma Urban 135 7 1,633 86 67 4 0 0 0 0 33 2 0 0 34 2 1,903 Total 26,827 15 147,613 81 2,098 1 585 0 648 0 2,477 1 351 0 1,203 1 181,802 Other Input is of No Use Total Total 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Other Other Locally Produced by Household Input is of No Use Input is of No Use Locally Produced by Household 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Total Too Much Labour Required Do not Know How to Use 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 200 Number % Number % Number % Kibondo 919 42 1,119 52 133 6 2,171 Kasulu 573 11 3,151 60 1,568 30 5,292 Kigoma Rural 3,166 46 3,719 54 0 0 6,885 Kigoma Urban 167 63 67 25 32 12 266 Total 4,825 33 8,055 55 1,733 12 14,614 Number % Number % Number % Kibondo 2,987 24 7,043 57 2,359 19 12,388 Kasulu 4,297 24 9,602 54 3,940 22 17,840 Kigoma Rural 3,497 35 5,555 56 906 9 9,958 Kigoma Urban 464 54 364 42 32 4 860 Total 11,244 27 22,565 55 7,237 18 41,045 Number % Number % Number % Number % Kibondo 0 0 1,719 81 262 12 133 6 2,114 Kasulu 1,571 21 3,930 53 1,971 26 0 0 7,472 Kigoma Rural 960 16 4,929 82 156 3 0 0 6,045 Kigoma Urban 137 34 240 59 0 0 32 8 409 Total 2,669 17 10,817 67 2,389 15 164 1 16,039 Total Poor Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 District Excellent Good Average Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average District Excellent Good Total Average Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 201 Number % Number % Number % Number % Kibondo 642 16 3,047 77 0 0 260 7 3,949 Kasulu 191 6 2,152 69 789 25 0 0 3,133 Kigoma Rural 2,068 33 3,586 57 612 10 0 0 6,266 Kigoma Urban 34 21 99 60 32 20 0 0 165 Total 2,935 22 8,884 66 1,434 11 260 2 13,513 Number % Number % Kibondo 0 0 0 0 0 Kasulu 0 0 0 0 0 Kigoma Rural 149 100 0 0 149 Kigoma Urban 0 0 0 0 0 Total 149 100 0 0 149 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Kibondo 839 42 1,050 52 0 0 121 6 2,010 Kibondo 12,290 24 39,117 76 51,407 Kasulu 775 12 5,480 85 192 3 0 0 6,447 Kasulu 20,384 26 59,012 74 79,396 Kigoma Rural 1,847 38 2,917 59 153 3 0 0 4,917 Kigoma Rural 27,787 44 34,683 56 62,470 Kigoma Urban 391 66 101 17 96 16 0 0 589 Kigoma Urban 636 26 1,856 74 2,492 Total 3,853 28 9,548 68 442 3 121 1 13,963 Total 61,097 31 134,668 69 195,765 District Excellent Good Average 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Total Poor Total Good Average 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year Total District Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Total District Excellent Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 202 Number % Number % Number % Number % Kibondo 24,468 47 27,323 53 51,791 Kibondo 12,626 25 38,660 75 51,286 Kasulu 35,052 44 44,344 56 79,396 Kasulu 23,138 29 56,259 71 79,396 Kigoma Rural 30,814 49 31,656 51 62,470 Kigoma Rural 21,922 35 40,548 65 62,470 Kigoma Urban 1,462 59 1,030 41 2,492 Kigoma Urban 607 24 1,884 76 2,492 Total 91,795 47 104,354 53 196,150 Total 58,293 30 137,352 70 195,644 Number % Number % Number % Number % Kibondo 11,630 23 39,777 77 51,407 Kibondo 2,688 5 48,719 95 51,407 Kasulu 9,803 12 69,593 88 79,396 Kasulu 3,725 5 75,671 95 79,396 Kigoma Rural 18,735 30 43,735 70 62,470 Kigoma Rural 10,798 17 51,672 83 62,470 Kigoma Urban 299 12 2,193 88 2,492 Kigoma Urban 68 3 2,424 97 2,492 Total 40,468 21 155,298 79 195,765 Total 17,279 9 178,486 91 195,765 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use COMPOST ManureNext Year Agricultural Households With NO Plan to use COMPOST Manure Next Year Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Herbicides Next Year Agricultural Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 203 Number % Number % Kibondo 11,900 23 39,507 77 51,407 Kasulu 19,184 24 60,213 76 79,396 Kigoma Rural 24,996 40 37,474 60 62,470 Kigoma Urban 1,195 48 1,296 52 2,492 Total 57,275 29 138,490 71 195,765 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Improved Seeds Next Year Agricultural Households With NO Plan to use Improved Seeds Next Year Total Tanzania Agriculture Sample Census -2003 Kigoma 204 Appendix II 205 AGRICULTURE CREDIT Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 206 Number % Number % Kibondo 251 100 0 0 251 Kasulu 1,363 88 192 12 1,555 Kigoma Rural 1,597 100 0 0 1,597 Kigoma Urban 3,211 94 192 6 3,403 Total 6,422 94 384 6 6,807 Family, Friend and Relative Commercial Bank Saving & Credit Society Religious Organisation / NGO / Project Kibondo 0 121 0 130 251 Kasulu 575 789 191 0 1,555 Kigoma Rural 160 1,437 0 0 1,597 Kigoma Urban 735 2,347 191 130 3,403 Total 1,470 4,695 382 260 6,807 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year Source of Credit Total Total District Male Female Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 207 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Kibondo 1,809 6,362 2,492 395 18,968 1,584 267 0 19,279 51,156 Kasulu 2,346 29,579 5,860 783 22,189 980 193 394 15,518 77,841 Kigoma Rural 1,425 3,935 8,198 1,866 35,671 7,608 478 160 1,532 60,873 Kigoma Urban 204 33 827 263 597 233 0 0 335 2,492 Total 5,784 39,909 17,377 3,307 77,425 10,404 938 554 36,664 192,362 District Labour Seeds Agro-chemicals Tools / Equipment Livestock Other Total Credits Kibondo 0 251 0 0 0 0 251 Kasulu 0 383 1,172 0 0 0 1,555 Kigoma Rural 0 160 1,437 958 0 0 2,555 Kigoma Urban 0 795 2,609 958 0 0 4,361 Total 0 1,590 5,217 1,916 0 0 8,722 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census -2003 Kigoma 208 Appendix II 209 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 210 District Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Tectona Grandis Total Kibondo 105 3,223 0 0 7,318 182 4 10,832 Kasulu 72 7 0 0 8,939 31 0 9,049 Kigoma Rural 682 219 170 80 2,976 5 1 4,133 Kigoma Urban 202 0 0 0 0 0 0 202 Total 1,061 3,449 170 80 19,233 218 5 24,216 % 4.4 14.2 0.7 0.3 79.4 0.9 0.0 100.0 District Jakaranda Spp Moringa Spp Maesopsis Berchemoides Leucena Spp Syszygium Spp Azadritacht a Spp Trichilia Spp Total Kibondo 2 64 38 0 0 0 0 104 Kasulu 11 0 0 0 6 0 0 17 Kigoma Rural 0 10 88 0 2 33 0 133 Kigoma Urban 7 0 0 0 0 0 0 7 Total 20 74 126 0 8 33 0 261 % 7.7 28.4 48.3 0.0 3.1 12.6 0.0 100.0 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Kigoma Region cont… Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Kigoma Regiont Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 211 1-9 1-19 20-29 30-39 60+ Total Kibondo 4,750 1,846 655 525 129 7,906 Kasulu 8,862 3,550 987 394 0 13,792 Kigoma Rural 0 153 2,240 0 0 2,393 Kigoma Urban 13,612 5,549 3,882 919 129 24,091 Total 27,225 11,097 7,764 1838 259 48182 % 57 23 16 4 1 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Kibondo 6040.0486 1732.4988 0 133 0 0 0 7906 Kasulu 783.15181 3157.1808 592 3749 0 0 4733.2911 13989 Kigoma Rural 0 0 0 153 0 0 0 2393 Kigoma Urban 6823.2004 4889.6796 592 4036 0 0 4733.2911 24289 Total 13646 9779 1184 8072 0 0 9467 48577 14.4 ON FARM TREE PLANTING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Kigoma Region District Second Use District 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Kigoma Region Distance to community planted forest (Km). Tanzania Agriculture Sample Census -2003 Kigoma 212 Appendix II 213 CROP EXTENSION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 214 Number % Number % Kibondo 24,172 47 27,235 53 51,407 Kasulu 37,004 47 42,393 53 79,396 Kigoma Rural 54,882 88 7,588 12 62,470 Kigoma Urban 2,359 95 133 5 2,492 Total 118,417 60 77,348 40 195,765 Number % Number % Number % Number % Number % Kibondo 1,832 7.6 16,102 67.0 5,973 24.8 133 0.6 24,040 100 Kasulu 2,134 5.8 26,038 70.4 8,640 23.3 192 0.5 37,004 100 Kigoma Rural 9,563 17.4 25,637 46.7 19,235 35.0 447 0.8 54,882 100 Kigoma Urban 404 17.1 1,153 48.9 802 34.0 1.4 0.1 2,359 100 Total 13,933 11.8 68,930 58.3 34,650 29.3 773 0.7 118,285 100 Number % Number % Number % Number % Number % Number % Kibondo 23,470 97 572 2 0 0 130 1 0 0 24,172 100 Kasulu 33,878 92 2,150 6 779 2 0 0 0 0 37,004 100 Kigoma Rural 52,529 97 782 1 153 0 476 1 308 1 54,249 100 Kigoma Urban 2,325 99 0 0 34 1 0 0 0 0 2,359 100 Ilemela 112,202 95 3,504 3 966 1 606 1 308 0 117,784 100 Total 224,405 95 7,008 3 1,933 1 1,212 1 617 0 235,568 100 Good Average 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Government NGO / Development Project Large Scale Farm Other Not applicable Total Poor Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Mwanza Region 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Mwanza Region Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households Very Good Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 215 Government NGO / Developme nt Project Large Scale Farm Other Not applicable Total % of total number of households Ukerewe 6,324 0 0 0 0 6,324 11 Magu 14,258 2,741 138 0 0 17,137 28 Kwimba 7,940 0 0 0 0 7,940 13 Sengerema 8,571 0 584 135 0 9,289 15 Geita 5,494 169 507 0 0 6,171 10 Missungwi 6,871 176 0 0 0 7,047 12 Ilemela 5,517 604 58 0 48 6,228 10 Total 54,975 3,690 1,287 135 48 60,136 100 Government NGO / Developme nt Project Cooperative Large Scale Farm Not applicable Ukerewe 3,482 0 0 0 0 3,482 10 Magu 10,274 1,080 0 138 0 11,492 32 Kwimba 4,205 185 102 0 0 4,493 12 Sengerema 4,477 0 0 0 0 4,477 12 Geita 3,889 169 0 0 0 4,058 11 Missungwi 3,281 935 0 0 0 4,217 12 Ilemela 2,886 667 0 216 140 3,910 11 Total 32494.43897 3037.2235 101.8443534 354.2820282 140.09703 36,128 100 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Ukerewe 4,799 0 0 83 0 4,882 12 Magu 6,383 8,200 254 134 0 14,972 38 Kwimba 5,746 0 0 0 0 5,746 15 Sengerema 5,416 0 0 433 0 5,849 15 Geita 1,806 0 0 0 0 1,806 5 Missungwi 2,303 330 0 0 0 2,634 7 Ilemela 2,765 606 0 58 257 3,686 9 Total 29,219 9,137 254 708 257 39,575 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Use of Agrochemicals Total Number of Households District District Spacing % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Erosion Control Total Number of Households District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 216 Government NGO / Developme nt Project Large Scale Farm Other Not applicable Total % of total number of households Kibondo 22,398 572 0 130 0 23,100 20.3 Kasulu 31,712 2,150 779 0 0 34,641 30.5 Kigoma Rural 52,369 315 153 476 308 53,622 47.2 Kigoma Urban 2,161 0 34 0 0 2,195 1.9 Total 108,641 3,037 966 606 308 113,558 100.0 Government NGO / Developme nt Project Cooperative Large Scale Farm Not applicable Kibondo 13,642 1,632 0 0 228 15,502 23.7 Kasulu 10,980 1,758 195 389 192 13,514 20.7 Kigoma Rural 34,047 479 0 153 458 35,298 54.1 Kigoma Urban 931 0 0 34 0 965 1.5 Total 59600.18321 3868.777 194.8525714 576.6221865 878.15035 65,278 100.0 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Kibondo 5,748 3,738 0 0 83 9,569 15.6 Kasulu 9,239 1,963 394 586 0 12,183 19.9 Kigoma Rural 37,367 1,053 0 0 156 38,576 62.9 Kigoma Urban 998 0 0 0 0 998 1.6 Total 53,352 6,754 394 586 239 61,326 100.0 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Use of Agrochemicals Total Number of Households District District Spacing % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Erosion Control Total Number of Households District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 217 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Kibondo 16,198 2,142 0 102 166 133 18,741 51,931 36.1 Kasulu 21,773 1,761 197 389 0 387 24,506 81,963 29.9 Kigoma Rural 43,514 908 0 313 160 0 44,895 64,901 69.2 Kigoma Urban 1,831 32 0 0 0 32 1,895 2,572 73.7 Total 83,315 4,842 197 805 327 552 90,037 201,367 44.7 Government NGO / Development Cooperative Large Scale Other Not applicable Total Kibondo 9,847 2,277 0 0 0 265 12,389 51,931 23.9 Kasulu 14,316 1,178 0 388 0 196 16,078 81,963 19.6 Kigoma Rural 40,431 901 160 160 137 0 41,789 64,901 64.4 Kigoma Urban 1,258 0 0 0 0 0 1,258 2,572 48.9 Total 65,853 4,355 160 548 137 461 71,514 201,367 35.5 Government NGO / Development Project Large Scale Farm Other Not applicable Total Kibondo 14,504 1,821 0 0 361 16,686 51,931 32 Kasulu 10,560 1,178 1,358 192 392 13,680 81,963 16.7 Kigoma Rural 40,115 2,434 0 0 160 42,709 64,901 65.8 Kigoma Urban 1,890 32 0 0 0 1,922 2,572 74.7 Total 67,070 5,464 1,358 192 913 74,998 201,367 37.2 District Total Number of Households % of total number of households % of total number of households % of total number of households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Total Number of Households Total Number of Households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 218 Government NGO / Development Project Large Scale Farm Not applicable Total % of total number of households Kibondo 1,782 0 83 0 1,865 9.7 Kasulu 2,951 394 0 0 3,345 17.4 Kigoma Rural 13,747 0 0 149 13,896 72.5 Kigoma Urban 69 0 0 0 69 0.4 Total 18,548 394 83 149 19,174 100.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total % of total number of households Kibondo 6,125 357 0 0 96 6,578 16.8 Kasulu 2,741 985 197 197 197 4,317 11.0 Kigoma Rural 27,067 156 0 153 309 27,684 70.7 Kigoma Urban 496 0 0 34 32 562 1.4 Total 36,429 1,497 197 384 634 39,142 100.0 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Kibondo 16,710 1,603 83 102 0 889 19,388 21.2 Kasulu 20,841 2,361 197 1,556 0 0 24,955 27.3 Kigoma Rural 44,852 292 0 0 311 0 45,455 49.8 Kigoma Urban 1,422 32 0 34 0 0 1,488 1.6 Total 83,825 4,288 280 1,692 311 889 91,286 100.0 Irrigation Technology Mechanisation / LST % of total number of households Crop Storage 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, District Total 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region District District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 219 Government NGO / Development Project Large Scale Farm Other Not applicable Total Kibondo 4,366 214 133 0 227 4,939 51,931 9.5 Kasulu 6,494 986 2,130 195 592 10,397 81,963 12.7 Kigoma Rural 31,732 685 778 0 160 33,356 64,901 51.4 Kigoma Urban 964 0 0 0 0 964 2,572 37.5 Total 43,556 1,885 3,042 195 979 49,656 201,367 24.7 Government NGO / Development Project Large Scale Farm Other Not applicable Total Kibondo 9,431 367 102 0 1,547 11,447 51,931 22.0 Kasulu 2,356 395 390 0 197 3,338 81,963 4.1 Kigoma Rural 40,722 285 160 156 320 41,642 64,901 64.2 Kigoma Urban 1,251 32 103 0 0 1,385 2,572 53.9 Total 53,760 1,078 755 156 2,064 57,812 201,367 28.7 Government NGO / Development Project Large Scale Farm Cooperativ Not applicable Total Total Number of Households Kibondo 7,279 4,201 0 83 363 11,926 51,931 23.0 Kasulu 3,536 2,546 0 0 0 6,082 81,963 7.4 Kigoma Rural 25,059 2,335 0 0 304 27,697 64,901 42.7 Kigoma Urban 891 34 34 0 0 960 2,572 37.3 Total 36,766 9,116 34 83 666 46,665 201,367 23.2 % of total number of households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Total Number of Households % of total number of households Total Number of Households % of total number of households Vermin Control District Agro-progressing Agro-forestry District District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 220 Government NGO / Development Project Not applicable Total % of total number of households Kibondo 780 398 361 1,539 23.8 Kasulu 1,170 194 0 1,364 21.1 Kigoma Rural 3,095 0 447 3,542 54.7 Kigoma Urban 33 0 0 33 0.5 Total 5,078 592 808 6,479 100.0 Government NGO / Development Project Not applicable Total % of total number of households Kibondo 214 2,499 229 2,943 40.9 Kasulu 583 194 197 974 13.5 Kigoma Rural 2,619 0 596 3,215 44.7 Kigoma Urban 66 0 0 66 0.9 Total 3,482 2,694 1,023 7,198 100.0 Received Adopted % Received Adopted % Received Adopted % Kibondo 23,017 22,704 98.6 15,536 3,228 14.0 10,010 2,408 10.5 Kasulu 34,838 29,133 83.6 13,921 7,242 20.8 12,188 8,456 24.3 Kigoma Rural 53,777 49,440 91.9 34,876 7,807 14.5 38,751 19,429 36.1 Kigoma Urban 2,195 1,937 88.3 965 235 10.7 964 494 22.5 Total 113,828 103,213 90.7 65,299 18,513 16.3 61,913 30,788 27.0 District Use of Agrochemicals Erosion Control Spacing 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Kigoma Region District District Bee keeping Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Kigoma Region Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 221 Received Adopted % Received Adopted % Received Adopted % Kibondo 19,106 6,518 34.1 12,519 1,409 11.3 16,590.4 2,318.1 14.0 Kasulu 24,112 17,457 72.4 14,902 7,252 48.7 14,464.0 3,493.6 24.2 Kigoma Rural 45,046 13,805 30.6 42,095 6,890 16.4 43,020.1 7,712.9 17.9 Kigoma Urban 1,929 967 50.2 1,293 231 17.8 1,922.1 956.3 49.8 Total 90,193 38,748 43.0 70,808 15,781 22.3 75,996.5 14,480.9 19.1 Received Adopted % Received Adopted % Received Adopted % Kibondo 1,832 0 0 6,136 3,384 55 18,631 18,536 99 Kasulu 3,943 0 0 4,317 1,166 27 24,963 23,202 93 Kigoma Rural 13,938 309 2 27,413 5,138 19 45,775 40,249 88 Kigoma Urban 0 0 0 530 236 45 1,488 987 66 Total 19,713 309 2 38,397 9,924 26 90,857 82,974 91 Received Adopted % Received Adopted % Received Adopted % Kibondo 4,600 3,904 85 9,291 10,870 117 12,195 6,128 50.2 Kasulu 10,403 8,040 77 2,946 976 33 6,279 4,512 71.9 Kigoma Rural 33,385 28,021 84 41,497 36,035 87 27,242 11,229 41.2 Kigoma Urban 964 567 59 1,417 1,319 93 960 430 44.8 Total 49,352 40,532 82 55,150 49,199 89 46,676 22,299 47.8 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Kigoma Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Kigoma Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Kigoma Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology District District District Organic Fertilizer Use Vermin Control Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 222 Received Adopted % Received Adopted % Kibondo 662 133 20.1 2,764 132 4.8 Kasulu 1,754 1,169 66.7 387 0 0.0 Kigoma Rural 2,782 0 0.0 2,169 0 0.0 Kigoma Urban 33 0 0.0 0 0 0.0 Total 5,232 1,303 25 5,320 132 2.5 Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Kigoma Region District Beekeeping Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 223 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 224 Number % Number % Kibondo 0 0 51,407 100 51,407 Kasulu 197 0 79,199 100 79,396 Kigoma Rural 474 1 61,996 99 62,470 Kigoma Urban 0 0 2,492 100 2,492 Total 671 0.3 195,094 99.7 195,765 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Kibondo 0 0 0 0 0 0 Kasulu 0 0 0 0 0 0 Kigoma Rural 5,071 5,071 1,811 0 0 0 Kigoma Urban 0 0 0 0 0 0 Total 5,071 5,071 1,811 0 0 0 Number % Number % Number % Kibondo 10,554 25.7 40,770 26.9 51,324 26.6 Kasulu 18,049 43.9 58,599 38.6 76,648 39.7 Kigoma Rural 11,543 28.1 50,927 33.5 62,470 32.4 Kigoma Urban 965 2.3 1,527 1.0 2,492 1.3 Total 41,110 100.0 151,824 100.0 192,934 100.0 Area (Ha) % Area (Ha) % Area (Ha) % Kibondo 4,655 29.0 927 14.7 5,582 25.0 Kasulu 6,665 41.5 3,960 63.0 10,625 47.5 Kigoma Rural 4,496 28.0 1,297 20.6 5,793 25.9 Kigoma Urban 260 1.6 101 1.6 361 1.6 Total 16,075 100.0 6,285 100.0 22,360 100.0 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Kigoma District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Kigoma Region Households Using Draft Animals Household Not Using Draft Animals Total household s 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Kigoma Region District Oxen Bulls Type of Craft 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Kigoma Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 225 CATTLE PRODUCTION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 226 Number % of Total cattle Number % of Total cattle Kibondo 5,181 10.1 46,226 89.9 51,931 5,181 Kasulu 14,722 18.5 64,674 81.5 81,963 14,722 Kigoma Rural 1,740 2.8 60,730 97.2 64,901 1,740 Kigoma Urban 68 2.7 2,424 97.3 2,572 68 Total 21,711 11.1 174,055 88.9 201,367 21,711 Number of Households Number of Cattle % of Total cattle Number of Households Number of Cattle % of Total cattle Number of Households Number of Cattle % of Total cattle Number of Households Number of Cattle % of Total cattle Kibondo 5,098 38,392 99 0 0 0 216 516 1 5,181 38,908 100 Kasulu 14,722 166,793 100 0 0 0 197 197 0 14,722 166,991 100 Kigoma Rural 1,740 215,824 100 0 0 0 0 0 0 1,740 215,824 100 Kigoma Urban 68 603 95 0 0 0 34 34 5 68 637 100 Total 21,627 421,613 100 0 0 0 448 748 0 21,711 422,361 100 Number % Number % 1-5 17,336 81.8 51,465 39.5 3 6-10 2,540 12.0 17,751 13.6 7 11-15 0 0.0 0 0.0 0 16-20 129 0.6 1,728 1.3 13 21-30 421 2.0 11,441 8.8 27 31-40 0 0.0 0 0.0 0 41-50 320 1.5 13,781 10.6 43 51-60 0 0.0 0 0.0 0 61-100 446 2.1 33,965 26.1 76 101-150 0 0.0 0 0.0 0 151+ 0 0.0 0 0.0 0 Total 21,193 100.0 130,132 100.0 6 Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Kigoma Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture households Total livestock keeping households Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 227 Number % Number % Number % Number % Bulls 31,756 99 0 0 216 0.7 31,973 100 Cows 121,564 100 0 0 315 0.3 121,878 100 Steers 13,006 100 0 0 0 0.0 13,006 100 Heifers 200,716 100 0 0 133 0.1 200,850 100 Male Calves 22,708 100 0 0 0 0.0 22,708 100 Female Calves 31862.817 99.739574 0 0 83 0.3 31946.0124 100 Total 421613.02 99.822959 0 0 748 0.2 422360.771 100 Bulls Cows Steers Heifers Male Calves Female Calves Total Kibondo 15,586 12,018 266 3,907 2,702 3,914 38,392 Kasulu 6,082 22,960 786 124,826 6,268 5,871 166,793 Kigoma Rural 9,888 86,317 11,954 71,983 13,705 21,977 215,824 Kigoma Urban 201 269 0 0 33 100 603 Total 31,756 121,564 13,006 200,716 22,708 31,863 421,613 Total 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Category of Cattle Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 228 Bulls Cows Steers Heifers Male Calves Female Calves Total Kibondo 216 83 0 133 0 83 516 Kasulu 0 197 0 0 0 0 197 Kigoma Rural 0 0 0 0 0 0 0 Kigoma Urban 0 34 0 0 0 0 34 Total 216 315 0 133 0 83 748 Bulls Cows Steers Heifers Male Calves Female Calves Total Kibondo 15,802 12,101 266 4,040 2,702 3,997 38,908 Kasulu 6,082 23,157 786 124,826 6,268 5,871 166,991 Kigoma Rural 9,888 86,317 11,954 71,983 13,705 21,977 215,824 Kigoma Urban 201 303 . . 33 100 637 Total 31,973 121,878 13,006 200,850 22,708 31,946 422,361 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 200 Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 229 GOATS PRODUCTION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 230 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Kibondo 27,226 147,950 99.4 83 166 0.1 216 683 0.5 27,226 148,799 100.0 Kasulu 26,852 136,156 100.0 0 0 0.0 0 0 0.0 26,852 136,156 100.0 Kigoma Rural 19,166 135,612 99.5 153 153 0.1 158 473 0.3 19,166 136,239 100.0 Kigoma Urban 895 4,410 100.0 0 0 0.0 0 0 0.0 895 4,410 100.0 Total 74,139 424,129 99.7 236 320 0.1 374 1,156 0.3 74,139 425,604 100.0 Number % Number % 1-4 40,005 54 101,321 24 3 5-9 23,691 32 154,793 36 7 10-14 6,694 9 76,017 18 11 15-19 1,809 2 30,557 7 17 20-24 709 1 15,813 4 22 25-29 157 0 3,964 1 25 30-39 623 1 20,706 5 33 40+ 451 1 22,433 5 50 Total 74,139 100 425,604 100 6 Herd Size Goat Rearing Households Head of Goats Average Number Per Household Total Goat District 19.1 GOAT PRODUCTION: Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 231 19.3 GOAT PRODUCTION:Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 53,160 99.7 0 0.0 133 0.3 53,293 100.0 Castrated Goat 17,080 97.6 0 0.0 416 2.4 17,496 100.0 She Goat 245,701 99.7 166 0.1 606 0.2 246,473 100.0 Male Kid 45,511 100.0 0 0.0 0 0.0 45,511 100.0 She Kid 62,677 99.8 153 0.2 0 0.0 62,831 100.0 Total 424,129 99.7 320 0.1 1,156 0.3 425,604 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kibondo 18,585 8,816 87,982 14,823 17,745 147,950 Kasulu 14,112 5,486 81,330 12,940 22,288 136,156 Kigoma Rural 20,098 2,646 74,053 17,049 21,765 135,612 Kigoma Urban 365 131 2,335 699 880 4,410 Total 53,160 17,080 245,701 45,511 62,677 424,129 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kibondo 0 0 166 0 0 166 Kasulu 0 0 0 0 0 0 Kigoma Rural 0 0 0 0 153 153 Kigoma Urban 0 0 0 0 0 0 Total 0 0 166 0 153 320 Total Category of Goats 19.4 GOAT PRODUCTION:Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Improved Dairy Goats 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 232 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kibondo 133 416 133 0 0 683 Kasulu 0 0 0 0 0 0 Kigoma Rural 0 0 473 0 0 473 Kigoma Urban 0 0 0 0 0 0 Total 133 416 606 0 0 1,156 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kibondo 18,718 9,232 88,282 14,823 17,745 148,799 Kasulu 14,112 5,486 81,330 12,940 22,288 136,156 Kigoma Rural 20,098 2,646 74,527 17,049 21,918 136,239 Kigoma Urban 365 131 2,335 699 880 4,410 Total 53,293 17,496 246,473 45,511 62,831 425,604 District Total Goat 19.6 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 GOAT PRODUCTION: Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 233 SHEEP PRODUCTION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 234 Number % Number % Number % Ram 5,502 5.3 0 0.0 5,502 5.3 Castrated Sheep 16,533 16.0 0 0.0 16,533 16.0 She Sheep 28,882 27.9 0 0.0 28,882 27.9 Male Lamb 888 0.9 0 0.0 888 0.9 She Lamb 51,805 50.0 0 0.0 51,805 50.0 Total 103,611 100.0 0 0.0 103,611 100.0 Number % Number % Kibondo 1,976 4 49,431 96 5,181 51,407 Kasulu 4,130 5 75,266 95 14,722 79,396 Kigoma Rural 5,876 9 56,594 91 1,740 62,470 Kigoma Urban 328 13 2,163 87 68 2,492 Total 12,311 6 183,455 94 21,711 195,765 Number % Number % Number % Kibondo 5,502 10.6 0 0 5,502 10.6 Kasulu 16,533 31.9 0 0 16,533 31.9 Kigoma Rural 28,882 55.8 0 0 28,882 55.8 Kigoma Urban 888 1.7 0 0 888 1.7 Total 51,805 100.0 0 0 51,805 100.0 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 8,738 72 19,636 38 2.2 5-9 2,216 18 14,474 28 6.5 10-14 893 7 10,221 20 11.4 15-19 148 1 2,667 5 18.0 20-24 0 0 0 0 0.0 25-29 0 0 0 0 0.0 30-39 160 1 4,807 9 30.0 40+ 0 0 0 0 0.0 Total 12,155 100 51,805 100 68 District 20.3 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep 20.1 SHEEP PRODUCTION: Total Number of Sheep By Breed and on 1st October 2003 20.4 SHEEP PRODUCTION: Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 SHEEP PRODUCTION: Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Sheep keeping Households Breed Number of Indigenous Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 235 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Kibondo 1,596 133 397 133 396 2,654 Kasulu 197 0 393 0 0 590 Kigoma Rural 1,211 0 1,241 631 149 3,232 Kigoma Urban 32 0 319 64 0 415 Total 3,037 133 2,350 827 545 6,891 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Kibondo 396 0 3,724 490 892 5,502 Kasulu 2,558 1,576 9,245 1,575 1,579 16,533 Kigoma Rural 5,868 153 17,876 1,739 3,245 28,882 Kigoma Urban 200 0 523 67 98 888 Total 9,023 1,729 31,367 3,871 5,815 51,805 District Total Sheep 20.6 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 SHEEP PRODUCTION: Total Number of Sheep by Sheep Type and District on 1st October 2003 Tanzania Agriculture Sample Census -2003 Kigoma 236 Appendix II 237 PIGS PRODUCTION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 238 Number % Number % 1-4 3,005 60 5,717 24 2 5-9 1,435 29 9,362 40 7 10-14 429 9 4,590 19 11 Total 4,869 97 19,668 83 4 District Number of Household Number of Pig Average Number Per Household Kibondo 763 1,689 2.214 Kasulu 1,973 11,444 5.800 Kigoma Rural 2,219 9,914 4.467 Kigoma Urban 69 652 9.500 Total 5,024 23,698 4.717 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Kibondo 131 . 630 398 530 1,689 Kasulu 1,184 592 3,946 3,749 1,973 11,444 Kigoma Rural 790 . 3,157 2,534 3,433 9,914 Kigoma Urban . . 137 69 446 652 Total 2,104 592 7,870 6,750 6,382 23,698 21.2 PIG PRODUCTION: Number of Households and Pigs by District on 1st October 2003 21.3 PIG PRODUCTION: Number of Pigs by Type and District on 1st October, 2003 21.1 PIG PRODUCTION: Number of Households and Pigs by Herd Size on 1st October Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 239 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 240 Number of Households % Number of Households % Kibondo 11,345 65 6,022 35 17,367 Kasulu 17,468 67 8,623 33 26,091 Kigoma Rural 7,754 48 8,294 52 16,048 Kigoma Urban 171 28 434 72 605 Total 36,738 61 23,373 39 60,110 Number of Households % Number of Households % Number of Households % Number of Households % Kibondo 7,685 34 4,760 24 1,530 23 1,951 35 Kasulu 8,440 38 13,146 65 3,351 49 2,562 46 Kigoma Rural 6,163 28 2,172 11 1,841 27 955 17 Kigoma Urban 103 0 33 0 69 1 69 1 Total 22,391 100 20,111 100 6,791 100 5,536 100 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 241 Number of Households % Number of Households % Kibondo 8,784 51 8,366 49 17,150 Kasulu 14,914 60 9,994 40 24,907 Kigoma Rural 5,017 32 10,560 68 15,576 Kigoma Urban 134 22 471 78 605 Total 28,848 50 29,390 50 58,239 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Kibondo 3,245 37 4,719 54 83 1 0 0 736 8 8,784 Kasulu 1,568 11 4,689 31 8,656 58 0 0 0 0 14,914 Kigoma Rural 780 16 2,202 44 1,119 22 153 3 762 15 5,017 Kigoma Urban 101 75 0 0 0 0 33 25 0 0 134 Total 5,695 20 11,610 40 9,858 34 187 1 1,498 5 28,848 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. District Ticks Problems No Ticks Problems Total Dipping Smearing Other 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year Method of Tick Control Total District None Spraying Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 242 Number of Households % Number of Households % Kibondo 397 2 16,703 98 17,100 Kasulu 1,940 8 23,362 92 25,302 Kigoma Rural 1,257 8 14,634 92 15,890 Kigoma Urban 102 17 503 83 605 Total 3,696 6 55,201 94 58,898 Number of Households % Number of Households % Number of Households % Number of Households % Kibondo 397 100 0 0 0 0 397 100 397 Kasulu 587 30 1,354 70 0 0 1,940 100 1,940 Kigoma Rural 476 38 467 37 313 25 1,257 100 1,257 Kigoma Urban 102 100 0 0 0 0 102 100 102 Total 1,562 42 1,821 49 313 8 3,696 100 3,696 District Tsetse Flies Problems No Tsetse Flies Problems 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District Total Trapping Method of Tsetse Flies Control 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year Total District None Spray Dipping Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 243 OTHER LIVESTOCK Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 244 Number % Type Number Indigenous 785,308 98.5 Ducks 51,782 Layer 10,349 1.3 Turkeys 592 Broiler 1,879 0.2 Rabbits 92,174 Total 797,537 100.0 144,548 Indigenous Chicken Layer Broiler Ducks Turkeys Donkeys Other Kibondo 202,592 0 0 202,592 Kibondo 11,786 0 7,963 0 Kasulu 211,326 0 0 211,326 Kasulu 4,493 592 1,972 2,171 Kigoma Rural 360,271 9,542 1,879 371,692 Kigoma Rural 34,730 0 0 2,015 Kigoma Urban 11,119 807 0 11,926 Kigoma Urban 773 0 0 0 Total 785,308 10,349 1,879 797,537 Total 51,782 592 9,935 4,186 Type of Livestock/Poultry 1995 1999 2003 Number % Cattle 62,609 128,360 422,361 1 - 4 33,489 41.3 85,545 3 Improved Cattle 182 748 5 - 9 22,305 27.5 148,227 7 Goats 284,053 453,614 425,604 10 - 19 15,108 18.6 191,735 13 Sheep 25,717 42,768 51,805 20 - 29 4,547 5.6 103,594 23 Pigs 2,041 12,433 23,698 30 - 39 3,407 4.2 111,065 33 Indigenous Chicken 469,080 751,328 785,305 40 - 49 712 0.9 28,640 40 Layers 882 1,090 10,349 50 - 99 1,433 1.8 102,695 72 Broilers 10159 1,879 100+ 137 0.2 26,036 190 Total Chickens 469,962 1,399,934 797,537 Total 81,139 100.0 797,537 10 Chicken Type Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 District Type of Livestock 23c OTHER LIVESTOCK:Head Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e LIVESTOCK/POULTRY POPULATION TREND Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 245 FISH FARMING Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 246 Number % Number % Kibondo 0 0.0 51,407 100.0 51,407 Kasulu 193 0.2 79,203 99.8 79,396 Kigoma Rural 0 0.0 62,470 100.0 62,470 Kigoma Urban 0 0.0 2,492 100.0 2,492 Total 193 0.1 195,572 99.9 195,765 Dug out Pond Total Kasulu 193 193 Total 193 193 NGOs / Project Number Kasulu 99 99 Total 99 99 Did not Sell Number Kasulu 193 193 Total 193 193 District Number of Tilapia Number of Carp Number of Others Kasulu 4,825 0 0 Total 4,825 0 0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year District Fish Farming System 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year Total Total District Source of Fingerling 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 247 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 248 Number % Number % Kibondo 14,181 27.6 37,226 72.4 51,407 5,181.1 Kasulu 13,712 17.3 65,685 82.7 79,396 14,722.0 Kigoma Rural 27,235 43.6 35,235 56.4 62,470 1,739.7 Kigoma Urban 1,123 45.1 1,369 54.9 2,492 67.8 Total 56,251 28.7 139,514 71.3 195,765 21,710.5 Number % Number % Number % Number % Number % Number % Kibondo 3,238 100 0 0 0 0 0 0 0 0 3,238 100 Kasulu 5,675 94 195 3 0 0 197 3 0 0 6,066 100 Kigoma Rural 17,002 100 0 0 0 0 0 0 0 0 17,002 100 Kigoma Urban 858 100 0 0 0 0 0 0 0 0 858 100 Total 26,772 99 195 1 0 0 197 1 0 0 27,164 100 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Large Scale Farmer District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year Total Total Total Number of households raising livestock Source of extension advice Other Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 249 Government NGO / Development Project Total Government NGO / Development Project Large Scale Farmer Total Kibondo 3,238 0 3,238 5,181 62 Kibondo 4,300 204 133 4,638 5,181 89.5 Kasulu 5,675 195 5,869 14,722 40 Kasulu 7,047 0 389 7,436 14,722 50.5 Kigoma Rural 1,230 0 1,230 1,740 71 Kigoma Rural 1,268 0 0 1,268 1,740 72.9 Kigoma Urban 858 0 858 68 1,267 Kigoma Urban 48 0 0 48 68 70.8 Total 26,772 195 26,967 21,711 124 Total 38,651 204 522 13,390 21,711 61.7 % 99.3 0.7 100.0 % 288.7 1.5 3.9 100.0 Government NGO / Development Project Other Total Government NGO / Development Project Total Kibondo 1,276 204 0 1,480 5,181 28.6 Kibondo 1,045 102 1,148 5,181 22.2 Kasulu 1,178 0 0 1,178 14,722 8.0 Kasulu 1,965 0 1,965 14,722 13.3 Kigoma Rural 1,340 0 0 1,340 1,740 77.0 Kigoma Rural 1,100 0 1,100 1,740 63.2 Kigoma Urban 33 0 0 33 68 49.4 Kigoma Urban 33 0 33 68 49.4 Total 8,309 204 0 8,513 21,711 39 Total 8,880 102 8,983 21,711 41.4 % 97.6 2.4 0.0 100.0 % 98.9 1.1 100.0 Total Number of households raising livestock % receiving advice out of total Source of Advice on Housing Total Number of households raising livestock % receiving advice out of total 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year Source of Advice on Feeds and Proper Feeding District Total Number of households raising livestock % receiving advice out of total 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District Source of Advice on Proper Milking District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 250 Government NGO / Development Project Co- operative Total Kibondo 523 204 102 830 5,181 16.0 Kasulu 11,355 0 0 11,355 14,722 77.1 Kigoma Rural 987 293 0 1,280 1,740 73.6 Kigoma Urban 43 0 0 43 68 63.5 Total 12,908 497 102 13,508 21,711 62.2 % 95.6 3.7 0.8 100.0 Government Co-operative Large Scale Farmer Total Kibondo 1,173 0 0 1,173 5,181 22.6 Kasulu 1,964 0 0 1,964 14,722 13.3 Kigoma Rural 1,250 137 0 1,387 1,740 79.7 Kigoma Urban 39 0 0 39 68 57.6 Total 15,318 137 0 15,456 21,711 71.2 % 99.1 0.9 0.0 100.0 Total Number of households raising livestock % receiving advice out of total % receiving advice out of total 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control District Source of Advice on Herd/Flock Size Total Number of households raising livestock Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 251 Government NGO / Development Project Large Scale Farmer not applicable Kibondo 923 0 0 0 923 5,181 17.8 Kasulu 3,735 0 0 0 3,735 14,722 25.4 Kigoma Rural 1,300 0 137 0 1,437 1,740 82.6 Kigoma Urban 12 0 0 0 12 68 17.7 Total 11,280 0 137 0 6,107 21,711 28.1 % 184.7 0.0 2.2 0.0 100.0 Government NGO / Development Project not applicable Total Kibondo 540 133 0 673 5,181 13.0 Kasulu 4,321 0 196 4,516 14,722 30.7 Kigoma Rural 1,460 137 0 1,597 1,740 91.8 Kigoma Urban 31 0 0 31 68 45.8 Total 6,352 270 196 6,818 21,711 31.4 % 93.2 4.0 2.9 100.0 Source of Advice on Group Formation and Strenghthening Total Number of households raising livestock Total Number of households raising livestock District 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Source of Advice on Pasture Establishment and Selection Total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 252 Government NGO / Development Project Other Total Kibondo 1,388 267 0 1,654 5,181 32 Kasulu 4,118 0 0 4,118 14,722 28 Kigoma Rural 1,503 137 0 1,640 1,740 94 Kigoma Urban 0 0 0 0 68 0 Total 12,963 404 0 13,367 21,711 62 % 97.0 3.0 0.0 100.0 Government NGO / Development Project Co- operative Total Kibondo 216 133 0 350 5,181 7 Kasulu 4,315 0 0 4,315 14,722 29 Kigoma Rural 1,500 0 137 1,637 1,740 94 Kigoma Urban 37 0 0 37 68 55 Total 17,679 133 137 17,949 21,711 83 % 98.5 0.7 0.8 100.0 % receiving advice out of total % receiving advice out of total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice on Improved Bulls Total Number of households raising livestock Total Number of households raising livestock District Source of Advice on Calf Rearing Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 253 Number % Number % Number % Number % Number % Kibondo 1,691 9 10,187 54 5,027 27 876 5 928 5 18,709 Kasulu 2,725 20 6,457 46 3,726 27 590 4 395 3 13,892 Kigoma Rural 9,181 34 12,099 45 5,495 21 0 0 0 0 26,775 Kigoma Urban 237 20 458 38 498 42 0 0 0 0 1,192 Total 13,834 23 29,200 48 14,746 24 1,466 2 1,323 2 60,568 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census -2003 Kigoma 254 Appendix II 255 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 256 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Kibondo 17.8 1.8 2.0 1.3 37.7 9.1 224.3 4.7 20.8 19.0 105.5 Kasulu 24.7 1.3 15.0 1.1 42.2 4.3 108.6 8.0 22.4 31.3 90.3 Kigoma Rural 23.6 1.7 7.3 3.9 72.5 4.4 81.8 5.1 11.5 26.1 70.9 Kigoma Urban 3.8 1.2 0.8 0.3 7.0 1.7 7.6 3.5 17.8 5.8 5.2 Total 22.3 1.5 9.0 2.0 50.3 5.6 129.1 6.1 18.4 26.1 87.0 District Capital 129.1 Tarmac Roads 87.0 Tertiary Market 26.1 Hospitals 50.3 Secondary Schools 22.3 Secondary Market 18.4 Primary Markets 6.1 Health Clinics 5.6 All weather roads 9.0 Primary Schools 1.5 Feeder Roads 2.0 33.01a ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 257 No of households % No of households % No of households % No of households % No of households % Kibondo 1,078 4,193 16,963 8,579 20,594 51,407 18 Kasulu 970 3,521 16,810 19,781 38,314 79,396 25 Kigoma Rural 8,450 5,889 11,753 8,489 27,890 62,470 24 Kigoma Urban 171 1,032 1,256 32 0 2,492 4 Total 10,669 14,635 46,782 36,881 86,798 195,765 22 No of households % No of households % No of households % No of households % No of households % Kibondo 21,057 41.0 19,816 38.5 8,833 17.2 1,599 3.1 102 0.2 51,407 2.0 Kasulu 16,456 20.7 16,151 20.3 16,862 21.2 3,150 4.0 26,777 33.7 79,396 15.0 Kigoma Rural 29,597 47.4 10,297 16.5 15,771 25.2 1,953 3.1 4,852 7.8 62,470 7.3 Kigoma Urban 1,919 77.0 340 13.7 233 9.3 0 0.0 0 0.0 2,492 0.8 Total 69,029 35.3 46,604 23.8 41,699 21.3 6,702 3.4 31,732 16.2 195,765 9.0 No of households % No of households % No of households % No of households % No of households % Kibondo 31,046 60.4 17,651 34.3 2,241 4.4 0 0.0 470 0.9 51,407 1.3 Kasulu 46,270 58.3 28,823 36.3 1,367 1.7 2,936 3.7 0 0.0 79,396 1.1 Kigoma Rural 40,997 65.6 14,070 22.5 3,992 6.4 2,492 4.0 918 1.5 62,470 3.9 Kigoma Urban 2,252 90.4 240 9.6 0 0.0 0 0.0 0 0.0 2,492 0.3 Total 120,565 61.6 60,784 31.0 7,600 3.9 5,429 2.8 1,388 0.7 195,765 2.0 33.01d ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of households Mean Distance Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km 33.01c ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01b ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year District Distance to Secondary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 258 No of households % No of households % No of households % No of households % No of households % Kibondo 605 1.2 1,845 3.6 6,962 13.5 7,288 14.2 34,707 67.5 51,407 37.7 Kasulu 585 0.7 987 1.2 9,019 11.4 7,625 9.6 61,180 77.1 79,396 42.2 Kigoma Rural 1,118 1.8 1,910 3.1 3,015 4.8 4,210 6.7 52,218 83.6 62,470 72.5 Kigoma Urban 69 2.8 0 0.0 2,254 90.5 169 6.8 0 0.0 2,492 7.0 Total 2,376 1.2 4,741 2.4 21,250 10.9 19,292 9.9 148,106 76 195,765 50.3 No of households % No of households % No of households % No of households % No of households % Kibondo 7,703 15.0 24,587 47.8 14,941 29.1 3,113 6.1 1,063 2.1 51,407 9.1 Kasulu 12,538 15.8 35,541 44.8 21,716 27.4 5,064 6.4 4,538 5.7 79,396 4.3 Kigoma Rural 19,232 30.8 24,686 39.5 9,155 14.7 5,417 8.7 3,979 6.4 62,470 4.4 Kigoma Urban 830 33.3 1,327 53.2 335 13.5 0 0.0 0 0.0 2,492 1.7 Total 40,302 20.6 86,142 44.0 46,147 23.6 13,594 6.9 9,581 4.9 195,765 5.6 No of households % No of households % No of households % No of households % No of households % Kibondo 12,687 24.7 30,228 58.8 7,995 15.6 263 0.5 235 0.5 51,407 1.8 Kasulu 24,153 30.4 46,470 58.5 8,773 11.0 0 0.0 0 0.0 79,396 1.3 Kigoma Rural 25,253 40.4 28,598 45.8 6,940 11.1 1,374 2.2 306 0.5 62,470 1.7 Kigoma Urban 998 40.0 1,298 52.1 196 7.9 0 0.0 0 0.0 2,492 1.2 Total 63,091 32.2 106,593 54.4 23,904 12.2 1,636 0.8 541 0.3 195,765 1.5 Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total number of households 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School 10.0-19.9 33.01g ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES:Number of Households by distance to Primary School for 2002/03 agriculture year 33.01f ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Above 20 km Above 20 km 33.01e ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES:Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 259 No of households % No of households % No of households % No of households % No of households % Kibondo 255 0.5 0 0.0 265 0.5 132 0.3 50,756 98.7 51,407 224.3 Kasulu 194 0.2 0 0.0 592 0.7 197 0.2 78,413 98.8 79,396 108.6 Kigoma Rural 0 0.0 0 0.0 308 0.5 4,365 7.0 57,797 92.5 62,470 81.8 Kigoma Urban 69 2.8 0 0.0 2,090 83.9 333 13.4 0 0.0 2,492 7.6 Total 518 0.3 0 0.0 3,256 1.7 5,027 2.6 186,965 95.5 195,765 129.1 No of households % No of households % No of households % No of households % No of households % Kibondo 775 1.5 1,443 2.8 6,276 12.2 5,048 9.8 37,865 73.7 51,407 38.3 Kasulu 197 0.2 197 0.2 2,762 3.5 8,415 10.6 67,825 85.4 79,396 46.1 Kigoma Rural 154 0.2 0 0.0 155 0.2 4,365 7.0 57,796 92.5 62,470 79.7 Kigoma Urban 34 1.4 32 1.3 1,435 57.6 990 39.7 0 0.0 2,492 9.7 Total 1,161 0.6 1,672 0.9 10,628 5.4 18,818 9.6 163,486 83.5 195,765 54.3 No of households % No of households % No of households % No of households % No of households % Kibondo 12,471 24.3 129 0.3 0 0.0 0 0.0 38,807 75.5 51,407 105.5 Kasulu 15,257 19.2 0 0.0 0 0.0 0 0.0 64,140 80.8 79,396 90.3 Kigoma Rural 6,807 10.9 1,851 3.0 2,381 3.8 442 0.7 50,988 81.6 62,470 70.9 Kigoma Urban 69 2.8 359 14.4 1,861 74.7 203 8.2 0 0.0 2,492 5.2 Total 34,603 17.7 2,340 1.2 4,242 2.2 646 0.3 153,934 78.6 195,765 87.0 33.01j ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Tarmac Road by District for 2002/03 District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01h ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 260 No of households % No of households % No of households % No of households % No of households % Kibondo 9,798 19.1 19,193 37.3 19,981 38.9 2,303 4.5 131 0.3 51,407 4.7 Kasulu 15,722 19.8 31,794 40.0 13,111 16.5 5,700 7.2 13,069 16.5 79,396 8.0 Kigoma Rural 26,407 42.3 11,341 18.2 15,459 24.7 5,004 8.0 4,260 6.8 62,470 5.1 Kigoma Urban 611 24.5 306 12.3 1,543 61.9 32 1.3 0 0.0 2,492 3.5 Total 52,539 26.8 62,635 32.0 50,094 25.6 13,038 6.7 17,460 8.9 195,765 6.1 No of households % No of households % No of households % No of households % No of households % Kibondo 5,689 11.1 3,709 7.2 11,483 22.3 8,496 16.5 22,030 42.9 51,407 19.0 Kasulu 1,579 2.0 197 0.2 7,691 9.7 12,925 16.3 57,004 71.8 79,396 31.3 Kigoma Rural 6,069 9.7 4,654 7.4 13,236 21.2 7,415 11.9 31,096 49.8 62,470 26.1 Kigoma Urban 0 0.0 100 4.0 2,258 90.6 100 4.0 33 1.3 2,492 5.8 Total 13,337 6.8 8,661 4.4 34,668 17.7 28,937 14.8 110,164 56.3 195,765 26.1 No of households % No of households % No of households % No of households % No of households % Kibondo 16,133 31.4 0 0.0 131 0.3 28,050 54.6 7,092 13.8 51,407 20.8 Kasulu 16,898 21.3 2,171 2.7 2,333 2.9 27,051 34.1 30,943 39.0 79,396 22.4 Kigoma Rural 17,077 27.3 5,535 8.9 2,328 3.7 33,432 53.5 4,099 6.6 62,470 11.5 Kigoma Urban 32 1.3 0 0.0 0 0.0 2,396 96.2 64 2.6 2,492 17.8 Total 50,140 25.6 7,706 3.9 4,792 2.4 90,929 46.4 42,197 21.6 195,765 18.4 33.01m ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01k ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 261 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 139 1 12,959 58 8,463 38 827 4 250 1 22,388 Magu 3,612 6 13,447 22 19,052 31 24,642 41 8,880 15 60,753 Kwimba 600 3 4,290 22 5,008 26 9,418 49 4,680 24 19,316 Sengerema 743 4 6,065 36 4,783 28 5,397 32 432 3 16,989 Geita 5,428 14 1,476 4 3,254 8 29,081 74 33,566 86 39,239 Missungwi 2,672 18 4,312 29 6,866 47 857 6 10,344 70 14,708 Ilemela 224 6 1,310 35 700 19 1,461 40 333 9 3,695 Total 13,417 8 43,860 25 48,127 27 71,684 40 58,486 33 177,089 No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 264 6.3 3,099 73.8 530 12.6 307 7.3 0 0.0 4,200 Kasulu 194 1.0 6,466 34.3 8,851 46.9 3,154 16.7 197 1.0 18,863 Kigoma Rural 2,008 16.8 2,941 24.6 7,015 58.6 0 0.0 0 0.0 11,964 Kigoma Urban 69 18.6 301 81.4 0 0.0 0 0.0 0 0.0 370 Total 2,535 7.2 12,807 36.2 16,396 46.3 3,460 9.8 197 0.6 35,396 No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 0 0.0 0 0.0 0 0.0 409 100.0 0 0.0 409 Kasulu 192 3.2 0 0.0 782 12.8 4,926 80.8 195 3.2 6,095 Kigoma Rural 0 0.0 0 0.0 1,267 90.2 0 0.0 137 9.8 1,404 Kigoma Urban 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 Total 192 2.4 0 0.0 2,049 25.9 5,335 67.5 332 0.0 7,907 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 262 No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 443 46 102 11 0 0 409 43 0 0 955 Kasulu 1,577 22 0 0 977 13 4,534 62 195 3 7,283 Kigoma Rural 0 0 0 0 411 100 0 0 0 0 411 Kigoma Urban 2,021 23 102 1 1,388 16 4,943 57 195 2 8,648 Total 4,042 91 204 12 2,776 129 9,885 162 390 5 17,297 No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 133 6.4 877 42.1 531 25.5 542 26.0 0 0.0 2,082 Kasulu 395 5.2 395 5.2 2,144 28.0 4,341 56.7 385 5.0 7,660 Kigoma Rural 602 14.3 154 3.7 3,002 71.1 463 11.0 0 0.0 4,220 Kigoma Urban 0 0.0 69 22.6 201 66.1 0 0.0 34 11.3 304 Total 1,129 7.9 1,495 10.5 5,877 41.2 5,345 37.5 420 2.9 14,266 No of Households % No of Households % No of Households % No of Households % No of Households % Kibondo 0 0.0 0 0.0 0 0.0 409 100.0 0 0.0 409 Kasulu 0 0.0 0 0.0 977 18.4 4,341 81.6 0 0.0 5,318 Kigoma Rural 0 0.0 0 0.0 429 47.9 307 34.2 160 17.9 896 Kigoma Urban 32 19.1 69 41.2 66 39.7 0 0.0 0 0.0 166 Total 32 0.5 69 1.0 1,472 21.7 5,057 74.5 160 2.4 6,789 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 263 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 264 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Total number of households Kibondo 3,277 765 47,114 251 51,407 Kasulu 984 3,354 74,669 389 79,396 Kigoma Rur 1,070 0 60,934 466 62,470 Kigoma Urb 64 0 2,297 131 2,492 Total 5,396 4,119 185,014 1,237 195,765 % 2.8 2.1 94.5 0.6 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total number of households Kibondo 3 14,553 661 0 0 31,178 4,749 267 51,407 Kasulu 3 21,150 2,552 789 985 43,597 10,323 0 79,396 Kigoma Rur 3 17,101 634 158 0 44,097 480 0 62,470 Kigoma Urb 3 873 0 0 0 1,459 161 0 2,492 Total 3 53,676 3,847 947 985 120,330 15,713 267 195,765 % 27.4 2.0 0.5 0.5 61.5 8.0 0.1 100.0 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 25,293 45,474 42,190 1,502 114,459 Landline phone 0 0 0 32 32 Mobile phone 133 395 776 101 1,404 Iron 4,354 7,805 10,743 635 23,536 Wheelbarrow 639 3,547 1,231 33 5,450 Bicycle 19,752 41,309 25,410 423 86,895 Vehicle 217 394 0 67 678 Television / Video 248 395 464 32 1,138 Total Number of Households 50,636 99,319 80,814 2,825 233,592 34.3 HOUSEHOLD FACILITIES: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Kasulu Kigoma Rural Kigoma Urban 34.1 HOUSEHOLD FACILITIES: Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year 34.2 HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District District Type of Owned Asset Type of toilet Kibondo Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 133 37.2 192 53.6 0 0.0 32 8.9 358 100.0 Solar 133 100.0 0 0.0 0 0.0 0 0.0 133 100.0 Gas (Biogas) 0 0.0 0 0.0 137 100.0 0 0.0 137 100.0 Hurricane Lamp 3,243 13.8 5,686 24.1 13,804 58.5 846 3.6 23,580 100.0 Pressure Lamp 988 12.0 5,087 62.0 2,036 24.8 100 1.2 8,210 100.0 Wick Lamp 41,676 27.1 64,105 41.7 46,344 30.2 1,514 1.0 153,640 100.0 Candles 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Firewood 5,233 53.9 4,326 44.6 148 1.5 0 0.0 9,707 100.0 Total 51,406 26.3 79,396 40.6 62,469 31.9 2,492 1.3 195,765 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 204 100.0 0 0.0 0 0.0 0 0.0 204 100.0 Solar 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Gas (Biogas) 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Bottled Gas 0 0.0 197 100.0 0 0.0 0 0.0 197 100.0 Parraffin / Kerocine 132 27.0 196 40.2 160 32.8 0 0.0 488 100.0 Charcoal 1,334 23.1 1,755 30.4 2,009 34.8 673 11.7 5,772 100.0 Firewood 49,604 26.4 76,270 40.6 60,301 32.1 1,819 1.0 187,993 100.0 Crop Residues 133 14.6 780 85.3 0 0.0 0 0.0 914 100.0 Livestock Dung 0 0.0 197 100.0 0 0.0 0 0.0 197 100.0 Total 51,203 26.2 79,395 41 62,470 32 2,492 1.3 195,561 100.0 34.5 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year 34.6 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Kibondo Main Source of Energy for Lighting District Total Kibondo Kasulu Total Main Source of Energy for Cooking District Kasulu Kigoma Rural Kigoma Urban Kigoma Urban Kigoma Rural Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 266 Kibondo Kasulu Kigoma rural Kigoma Urban Total wet season 4,462 27,748 14,032 686 46,928 dry season 3,584 23,421 13,259 652 40,916 wet season 9,447 17,445 3,261 135 30,287 Dry season 9,692 17,445 3,421 135 30,693 wet season 9,248 11,226 6,620 485 27,580 Dry season 9,747 11,226 6,620 485 28,078 wet season 1,419 6,478 8,363 470 16,731 Dry season 1,419 7,660 5,288 504 14,872 wet season 17,033 10,223 6,279 391 33,926 Dry season 17,165 11,999 7,041 391 36,596 wet season 9,799 4,106 22,995 294 37,194 Dry season 9,799 5,476 26,529 294 42,098 wet season 0 0 0 32 32 Dry season 0 0 0 32 32 wet season 0 393 608 0 1,001 Dry season 0 393 0 0 393 wet season 0 0 0 0 0 Dry season 0 0 0 0 0 wet season 0 0 0 0 0 Dry season 0 0 0 0 0 wet season 0 0 0 0 0 Dry season 0 0 0 0 0 wet season 0 1,776 311 0 2,087 dry season 0 1,776 311 0 2,087 102,814 158,793 124,940 4,984 391,531 Kibondo Kasulu Kigoma rural Kigoma Urban Total wet season 0.0 0.3 0.1 0.0 0.5 dry season 0.0 0.2 0.1 0.0 0.4 wet season 0.1 0.2 0.0 0.0 0.3 Dry season 0.1 0.2 0.0 0.0 0.3 wet season 0.1 0.1 0.1 0.0 0.3 Dry season 0.1 0.1 0.1 0.0 0.3 wet season 0.0 0.1 0.1 0.0 0.2 Dry season 0.0 0.1 0.1 0.0 0.1 wet season 0.2 0.1 0.1 0.0 0.3 Dry season 0.2 0.1 0.1 0.0 0.4 wet season 0.1 0.0 0.2 0.0 0.4 Dry season 0.1 0.1 0.3 0.0 0.4 wet season 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 dry season 0.0 0.0 0.0 0.0 0.0 Bottled Water Other Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Tanker Truck Bottled Water Piped Water 34.7 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Drinking Water by Season (LONG and Short) and District during 2002/03 Agricultural Year Protected Well Protected / Covered Spring Other District Source Season Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Total Agricultural Households per District 34.8 HOUSEHOLD FACILITIES: Proportion of Agricultural Households by Main Source of Drinking Water by Season (LONG and Short) and District during 2002/03 Agricultural Year Source Season District Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 267 Kibondo Kasulu Kigoma rural KigomaUrban wet season 561 589 3,193 0 Dry season 571 980 3,038 0 wet season 10,847 17,993 13,066 543 Dry season 10,355 15,436 11,450 543 wet season 5,767 10,761 13,316 260 Dry season 5,462 11,548 10,503 226 wet season 16,940 18,436 11,184 398 Dry season 16,389 19,223 11,532 398 wet season 3,511 5,113 5,132 198 Dry season 3,636 5,507 5,443 164 wet season 2,919 7,465 4,039 169 Dry season 3,015 6,679 3,735 169 wet season 10,863 19,039 12,539 923 Dry season 11,980 20,024 16,769 992 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 3,623 7.0 1,174 1.5 1,719 2.2 0 0.0 6,516 3.3 Two 43,566 84.7 66,132 83.3 45,956 57.9 1,854 2.3 157,507 80.5 Three 4,219 8.2 11,897 15.0 14,646 18.4 638 0.8 31,399 16.0 Four 0 0.0 194 0.2 149 0.2 0 0.0 343 0.2 Total 51,407 100.0 79,396 100.0 62,470 78.7 2,492 3.1 195,765 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 32,352 63 48,385 61 22,564 36 1,326 53 104,627 53 One 12,369 24 21,188 27 24,191 39 968 39 58,716 30 Two 5,185 10 6,288 8 8,578 14 131 5 20,183 10 Three 1,115 2 2,548 3 5,886 9 67 3 9,616 5 Four 254 0 197 0 626 1 0 0 1,077 1 Five 132 0 0 0 315 1 0 0 447 0 Six 0 0 592 1 160 0 0 0 752 0 Seven 0 0 197 0 149 0 0 0 346 0 Total 51,407 100 79,396 100 62,470 100 2,492 100 195,765 100 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.9 HOUSEHOLD FACILITIES: Number of Households Reporting Time Spent to and from Time Spent to and from Main Source of Drinking Water Season District Total Number of Days Kibondo Kigoma urban District Kigoma rural Kasulu 34.11 HOUSEHOLD FACILITIES: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District 34.12 HOUSEHOLD FACILITIES: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Meals per Day District Total Kibondo Kasulu Kigoma rural Kigoma urban Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 268 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 38,205 50 34,245 45 4,293 6 170 0 76,913 100 One 7,878 21 21,191 56 8,234 22 532 1 37,834 100 Two 4,147 17 12,961 52 7,367 29 527 2 25,002 100 Three 650 5 4,508 33 7,855 58 559 4 13,572 100 Four 264 1 4,717 24 14,526 73 466 2 19,973 100 Five 133 1 984 10 8,860 87 203 2 10,180 100 Six 0 0 394 6 6,057 94 0 0 6,452 100 Seven 131 2 395 7 5,279 90 34 1 5,839 100 Total 51,408 26 79,395 41 62,471 32 2,491 1 195,765 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 20,135 16 54,164 44 48,571 39 1,262 1 124,132 100 Seldom 14,780 35 18,821 44 7,942 19 933 2 42,476 100 Sometimes 6,366 43 3,898 26 4,397 30 199 1 14,859 100 Often 5,036 77 965 15 474 7 98 1 6,573 100 Always 5,089 66 1,550 20 1,086 14 0 0 7,725 100 Total 51,406 26 79,398 41 62,470 32 2,492 1 195,765 100 Number of Days District Total Kibondo Kasulu Kigoma rural 34.13 HOUSEHOLD FACILITIES: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Kigoma urban Status of Food Satisfaction Kibondo 34.14 HOUSEHOLD FACILITIES: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Kasulu Total District Kigoma urban Kigoma rural Tanzania Agriculture Sample Census -2003 Kigoma Appendix II 269 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 14,553 27 21,150 39 17,101 32 873 2 53,676 100 Tiles 661 17 2,552 66 634 16 0 0 3,847 100 Concrete 0 0 789 83 158 17 0 0 947 100 Asbestos 0 0 985 100 0 0 0 0 985 100 Grass / Leaves 31,178 26 43,597 36 44,097 37 1,459 1 120,330 100 Grass & Mud 4,749 30 10,323 66 480 3 161 1 15,712 100 Other 267 100 0 0 0 0 0 0 267 100 Total 51,408 26 79,396 41 62,470 32 2,493 1 195,764 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 27,253 22 59,394 47 38,147 30 818 1 125,612 100 Sale of Livestock 1,842 54 778 23 789 23 0 0 3,409 100 Sale of Livestock Products 623 39 197 12 788 49 0 0 1,608 100 Sales of Cash Crops 132 1 3,935 38 6,088 60 69 1 10,224 100 Sale of Forest Products 2,967 56 1,376 26 933 18 32 1 5,309 100 Business Income 3,816 33 2,342 20 4,933 42 596 5 11,688 100 Wages & Salaries in Cash 1,928 32 1,561 26 2,327 39 204 3 6,020 100 Other Casual Cash Earnings 10,056 55 6,087 33 1,968 11 339 2 18,450 100 Cash Remittance 1,777 40 587 13 2,023 46 34 1 4,421 100 Fishing 0 0 1,574 25 4,322 69 331 5 6,227 100 Other 257 21 777 62 150 12 68 5 1,252 100 Total 50,650 26 78,608 40 62,468 32 2,491 1 194,220 100 Roofing Materials District Total Kibondo Kasulu Kigoma urban 34.15 HOUSEHOLD FACILITIES: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year Kasulu Kigoma rural Main Source of Energy for Cooking District Kibondo Kigoma rural Kigoma urban Total 34.16 HOUSEHOLD FACILITIES: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Tanzania Agriculture Sample Census -2003 Kigoma 270 APPENDIX III QUESTIONNAIRES Appendix III 271 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 272 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 273 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 274 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 275 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 276 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 277 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 278 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 279 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 279 280 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 281 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 282 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 283 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 284 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 285 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 286 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 287 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 288 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 289 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 290 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 291 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 292 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 293 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 294 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 295 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 296 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 297 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 298 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 299 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 300 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 301 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 302 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 303 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 304 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 305 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 306 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 307 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 308 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 309 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 310 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 311 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 312 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 313 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 314 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 315 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 316 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vc: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vc: REGIONAL REPORT: KILIMANJARO REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC i TABLE OF CONTENTS Table of contents........................................................................................................................................... i Acronyms.................................................................................................................................................... vi Preface.........................................................................................................................................................vii Executive summary..................................................................................................................................... vi Illustrations................................................................................................................................................. xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION ...................................................................................... 1 1.1 Introduction................................................................................................................................... 1 1.2 Geographical Location and Boundaries.......................................................................................... 1 1.3 Land Area ...................................................................................................................................... 1 1.4 Climate........................................................................................................................................... 1 1.4.1 Temperature ....................................................................................................................... 1 1.4.2 Rainfall............................................................................................................................... 1 1.5 Population...................................................................................................................................... 1 1.6 Socio-economic Indicators............................................................................................................ 2 PART II: INTRODUCTION ................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................ 3 2.2 Census Objectives ......................................................................................................................... 3 2.3 Census Coverage and Scope......................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture............................................... 5 2.5 Reference Period ........................................................................................................................... 5 2.6 Census Methodology..................................................................................................................... 5 2.6.1 Census Organization .......................................................................................................... 5 2.6.2 Tabulation Plan .................................................................................................................. 6 2.6.3 Sample Design ................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments........................................................ 7 2.6.5 Field Pre-Testing of the Census Instruments ..................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators .......................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign.......................................... 7 2.6.8 Household Listing.............................................................................................................. 8 2.6.9 Data Collection .................................................................................................................. 8 2.6.10 Field Supervision and Consistency Checks ....................................................................... 8 2.6.11 Data Processing.................................................................................................................. 8 - Manual Editing ............................................................................................................. 9 - Data Entry..................................................................................................................... 9 - Data Structure Formatting ............................................................................................ 9 - Batch Validation ........................................................................................................... 9 - Tabulations.................................................................................................................... 9 - Analysis and Report Preparations................................................................................. 9 - Data Quality................................................................................................................ 10 2.7 Funding Arrangements ......................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................ 11 3.1 Holding Characteristics.............................................................................................................. 11 3.1.1 Type of Holdings ............................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income .......................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................. 11 3.1.4 Number of Household Members...................................................................................... 15 3.1.5 Level of Education........................................................................................................... 15 - Literacy....................................................................................................................... 15 - Literacy Level for Household Members..................................................................... 15 TOC ii - Litaracy Rates for Heads of Households .................................................................... 15 - Educational Status....................................................................................................... 16 3.1.6 Off-farm Income .............................................................................................................. 16 3.2 Land Use .................................................................................................................................... 17 3.2.1 Area of Land Utilised....................................................................................................... 17 3.2.2 Types of Land use............................................................................................................ 18 3.3 Annual Crops and Vegetable Production ................................................................................. 18 3.3.1 Area Planted..................................................................................................................... 18 3.3.2 Crop Importance .............................................................................................................. 20 3.3.3 Crop Types....................................................................................................................... 20 3.3.4 Cereal Crop Production.................................................................................................... 22 3.3.4.1 Maize ............................................................................................................... 23 3.3.4.2 Paddy ............................................................................................................... 23 3.3.4.3 Other Cereals ................................................................................................... 26 3.3.5 Roots and Tuber Crops Production.................................................................................. 26 3.3.5.1 Cassava ............................................................................................................ 27 3.3.5.2 Irish Potatoes ................................................................................................... 28 3.3.6 Pulse Crops Production.................................................................................................... 28 3.3.6.1 Beans................................................................................................................ 30 3.3.7 Oil Seed Production ......................................................................................................... 32 3.3.7.1 Groundnuts ...................................................................................................... 32 3.3.8 Fruits and Vegetables........................................................................................................33 3.3.8.1 Tomatoes.......................................................................................................... 35 3.3.8.2 Cabbage ........................................................................................................... 37 3.3.8.3 Chillies............................................................................................................. 37 3.3.9 Other Annual Crops Production....................................................................................... 40 3.3.9.1 Cotton ...............................................................................................................40 3.3.9.2 Tobacco............................................................................................................ 40 3.4 Permanent Crops ........................................................................................................................ 40 3.4.1 Coconuts ......................................................................................................................... 43 3.4.2 Oranges ......................................................................................................................... 45 3.4.3 Banana ......................................................................................................................... 45 3.4.4 Cashew Nuts .................................................................................................................... 45 3.5 Inputs/Implements Use............................................................................................................... 48 3.5.1 Methods of land clearing...................................................................................................48 3.5.2 Methods of soil preparation ............................................................................................. 48 3.5.3 Improved seeds use .......................................................................................................... 50 3.5.4 Fertilizers use................................................................................................................... 51 3.5.4.1 Farm Yard Manure Use ................................................................................... 51 3.5.4.2 Inorganic Fertilizer Use ................................................................................... 52 3.5.4.3 Compost Use.................................................................................................... 53 3.5.5 Pesticide Use.................................................................................................................... 54 3.5.5.1 Insecticide Use................................................................................................. 54 3.5.5.2 Herbicide Use .................................................................................................. 55 3.5.5.3 Fungicide Use.................................................................................................. 55 3.5.6 Harvesting Methods ......................................................................................................... 56 TOC iii 3.5.7 Threshing Methods .........................................................................................................56 3.6 Irrigation ....................................................................................................................................56 3.6.1 Area planted with annual crops and under irrigation ....................................................... 56 3.6.2 Sources of water used for irrigation................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................ 59 3.6.4 Methods of water application .......................................................................................... 59 3.7 Crop Storage, Processing and Marketing................................................................................. 59 3.7.1 Crop Storage .................................................................................................................... 59 3.7.1.1 Method of Storage ........................................................................................... 60 3.7.1.2 Duration of Storage.......................................................................................... 60 3.7.1.3 Purpose of Storage........................................................................................... 61 3.7.1.4 The Magnitude of Storage Loss....................................................................... 61 3.7.2 Agro processing and by-products......................................................................................62 3.7.2.1 Processing Methods......................................................................................... 62 3.7.2.2 Main Agro-processing Products ...................................................................... 62 3.7.2.3 Main use of primary processed Products......................................................... 63 3.7.2.4 Outlet for Sale of Processed Products.............................................................. 63 3.7.3 Crop Marketing................................................................................................................ 64 3.7.3.1 Main Marketing Problems ............................................................................... 64 3.7.3.2 Reasons for Not Selling................................................................................... 64 3.8 Access to Crop Production Services .......................................................................................... 65 3.8.1 Access to Agricultural Credits ......................................................................................... 65 3.8.1.1 Source of Agricultural Credits......................................................................... 65 3.8.1.2 Use of Agricultural Credits.............................................................................. 65 3.8.1.3 Reasons for not using agricultural credits........................................................ 66 3.8.2 Crop Extension................................................................................................................. 66 3.8.2.1 Sources of crop extension messages................................................................ 66 3.8.2.2 Quality of extension......................................................................................... 68 3.9 Access to Inputs ...........................................................................................................................68 3.9.2 Inorganic Fertilisers .........................................................................................................68 3.9.3 Improved Seeds.................................................................................................................69 3.9.4 Insecticides and Fungicide................................................................................................69 3.10 Tree Planting ................................................................................................................................70 3.11 Irrigation and Erosion Control Facilities ................................................................................. 71 3.12 Livestock Results......................................................................................................................... 73 3.12.1 Cattle Production ..............................................................................................................73 3.12.1.1 Cattle Population ............................................................................................. 73 3.12.1.2 Herd size .......................................................................................................... 73 3.12.1.3 Cattle Population Trend................................................................................... 75 3.12.1.4 Improved Cattle Breeds ................................................................................... 75 3.12.2 Goat Production ............................................................................................................... 75 TOC iv 3.12.2.1 Goat Population ............................................................................................... 75 3.12.2.2 Goat Herd Size................................................................................................. 77 3.12.2.3 Goat Breeds ..................................................................................................... 77 3.12.2.4 Goat Population Trend..................................................................................... 77 3.12.3 Sheep Production ............................................................................................................. 77 3.12.3.1 Sheep Population ............................................................................................. 77 3.12.3.2 Sheep Population Trend................................................................................... 79 3.12.4 Pig Production.................................................................................................................. 79 3.12.4.1 Pig Population Trend ....................................................................................... 79 3.12.5 Chicken Production.......................................................................................................... 81 3.12.5.1 Chicken Population.......................................................................................... 81 3.12.5.2 Chicken Population Trend ............................................................................... 81 3.12.5.3 Chicken Flock Size.......................................................................................... 81 3.12.5.4 Improved Chicken Breeds (layers and broilers) .............................................. 82 3.12.6 Other Livestock................................................................................................................ 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................... 82 3.12.7.1 Deworming ...................................................................................................... 82 3.12.8 Access to Livestock Services........................................................................................... 84 3.12.8.1 Access to livestock extension Services............................................................ 84 3.12.8.2 Access to Veterinary Clinic............................................................................. 84 3.12.8.3 Access to village watering points/dam ............................................................ 85 3.12.9 Animal Contribution to Crop Production......................................................................... 85 3.12.9.1 Use of Draft Power .......................................................................................... 85 3.12.9.2 Use of Farm Yard Manure............................................................................... 86 3.12.9.4 Use of Compost ............................................................................................ 86 3.12.10 Fish Farming .................................................................................................................... 86 3.6.0 Access to Infrastructure and Other Services .................................................................... 89 3.13 Poverty Indicators....................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services .................................................................... 89 3.13.2 Type of Toilets................................................................................................................. 90 3.13.3 Household’s assets ........................................................................................................... 90 3.13.4 Sources of Light Energy .................................................................................................. 90 3.13.5 Sources of Energy for Cooking........................................................................................ 90 3.13.6 Roofing Materials ............................................................................................................ 91 3.13.7 Access to Drink Water ..................................................................................................... 91 3.13.8 Food Consumption Pattern............................................................................................... 92 3.13.8.1 Number of Meals per Day ............................................................................... 92 3.13.8.2 Meat Consumption Frequencies ...................................................................... 92 3.13.8.3 Fish Consumption Frequencies........................................................................ 92 3.13.9 Food Security ................................................................................................................... 92 3.13.10 Main Source of Cash Income........................................................................................... 93 TOC v PART IV: KILIMANJARO PROFILES............................................................................................. 109 4.1 Region Profile .............................................................................................................................109 4.2 District Profiles...........................................................................................................................109 4.2.1 Rombo.............................................................................................................................110 4.2.2. Mwanga...........................................................................................................................112 4.2.3 Same................................................................................................................................114 4.2.4 Moshi Rural.....................................................................................................................116 4.2.5 Hai .................................................................................................................................119 ACRONYMS vi ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department for International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ vii PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Kigoma region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ viii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Kigoma region who were selected using statistical sampling techniques. The results presented in this report do not cover urban areas and large-scale farmers. Highlighted are important findings regarding agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural and related activities and poverty in Kigoma region, the aim being to present an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural activities. i) Household Characteristics The number of agricultural households in Kilimanjaro region was 216,173 out of which 57,719 (26.7%) were involved in growing crops only, 1,951 (0.9%) rearing livestock only, 35 (0.1%) were pastoralist and 156,467 (72.4%) were involved in crop production as well as livestock keeping. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, livestock keeping/herding, off farm income, tree/forest resources, remittances, fishing hunting & gathering. Kilimanjaro region had a total literacy rate of 86.7 percent, the highest literacy rate was found in Mwanga district (87.7%) followed by Moshi rural district (89.3%), Rombo (85.3%), Same and Hai districts both had (84.8%), thus Same and Hai district had the lowest literacy rates. The number of heads of agricultural households with formal education in Kilimanjaro region was 185,978 (86.0%), those without formal education were 28,714 (13.3%) and those with only adult education were 1,451 (0.7% percent). The majority of heads of agricultural households (73.4) percent had primary level education whereas only 3.9 percent had post primary education. In Kilimanjaro region 76,886 households (65.3% of households with off-farm income) had each one household member engaged in off-farm income generating activities. Another 38,977 households (27.6%) had two household members engaged in off farm income generating activities and 22,999 households (15.7%) had each more than two members engaged in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 276,325 ha. The regional average land area utilised for crop production per crop growing household was only 1.3 ha. This figure was below the national average of 2.0 hectares ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ ix Planted Area The area planted with annual crops and vegetables was 174,253 hectares out of which 104,994 hectares (60%) were planted during long rainy season and 69,259 hectares (40%) during short rainy season. An estimated area of 63,594 ha (60.6% of the total planted area with annual and vegetable crops) was planted with cereals, followed by 28,590 hectares (27.2%) of pulses, 5,545 ha (5.3%) of root & tubers, 5,358 ha (5.1 percent) of oil seeds and oil nuts, 11,887 ha (1.7%) of fruits & vegetables and 22 ha (0.02%) of cash crops. Maize Maize was the dominant annual crop grown in Kilimanjaro region and it had a planted area 2.2 times greater than beens, which had the second largest planted area. The areas planted with maize constitute 55 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were beans, sunflower, cassava, finger millet, groundnuts, paddy, tomatoes cocoyams and sweet potatoes. Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Kilimanjaro region in the long and short rainy seasons was 103,410 and 73,082 respectively. The total production of beans in the region was 17,662 tonnes from a planted area of 77,486 hectares resulting in a yield of 0.4t/ha. Cassava The area planted with cassava was larger than any other root and tuber crops, followed by Irish potatoes, cocoyams, sweet potatoes and yams. The number of households growing cassava in the region was 12,534. This represented about 2 percent of the total crop growing households in the region. Fruit and Vegetables The total production of fruits and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 11,221 tonnes (57.4% of the total fruits and vegetables produced) followed by onion (2,751t, 14.1%), amaranth (1581t, 8.1%), cabbage (1,425t, 7.2%) production of the other fruits and vegetables crops was relatively small. Permanent Crops The area of smallholders planted with permanent crops was 113,618 hectares (14% of the area planted with annual crops in the region). The most important permanent crop in Kilimanjaro region was banana which had a planted area of 56,038 ha, (54.7% of the planted area of all permanent crops) followed by coffee (35,633 ha, 34.8%), mango (8,045 ha, 7.8%). The remaining permanent crops collectively had a planted area of 2,801 ha (11.0%) ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ x Improved Seeds The planted area using improved seeds was estimated at 73,097 ha which represented 43 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the long rainy season was 59.3 percent, and higher than the corresponding percentage uses for the short rainy season at 54.4 percent Use of Fertilizers The use of fertilisers on annual crops is moderate with a planted area of 114,912 ha (65.9 of the total planted area in the region). Of the area planted with fertiliser application, farm yard manure was applied to 59,341 ha which represents 34 percent of the total planted area (65.9% of the area planted with fertiliser application in the region). This was followed by mostly Inorganic fertiliser (34,082 ha, 20%) and mostly compost 7,579 ha representing only 4 percent of the total planted area. The highest percentage of the area planted with fertilizer (all types) was in Hai district (83.3%) followed by Moshi Rural (70.9%), Mwanga (67.3%), Same (64.7%) and Rombo (48.5%). Irrigation The area of annual crops under irrigation was 25,947 ha representing 15 percent of the total ar ea planted (Chart 3.79). The area under irrigation during the long rainy season was 15,190 ha accounting for 59 percent of the total area under irrigation. In the short rainy season, 10,758 ha or 3.6 percent of the total area planted with crops was irrigated. Crop Storage There were 142,851 crop growing households (90% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 131,869 households storing 39,418 tonnes as of 1st January 2004. This was followed by beans and pulses (84,190 households, 5,366t), paddy (15,765 households, 1,222t), sorghum and millets (7,920 households, 403t), groundnuts and bambaranuts (3,981 household, 123t) and coffee (1,487 household, 63t). Other crops were stored in very small amounts. Crop Marketing The number of households that reported selling crops was 167,709 which represent 77.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Rombo (89%) followed by Moshi Rural (84%), Hai (70%), same (64%) and Mwanga (62%). Crop Extension Services The number of Agricultural households that received crop extension was 135,826 (63% of total crop growing households in the region). Some districts have more access to extension services than others, with Moshi Rural district having a relatively high proportion of households (73%) that received crop extension messages followed by Rombo (59%), Hai (58%), Same (53%) and Mwanga (54%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xi Soil Erosion and Water Harvesting Facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 48,710 which represent 23 percent of the total number of agricultural households in the region. The proportion of households with soil erosion control and water harvesting facilities was highest in Moshi Rural district (36%) followed by Hai (31%), Same (25%), Mwanga (8%) and Rombo had none iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 494,555. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 3 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Kilimanjaro region was 351,191 (71 % of the total number of cattle in the 5,454 cattle (1%) were beef breeds . Goats The number of goat-rearing-households in Kilimanjaro region was 103,017 (65% of all agricultural households in the region) with a total of 572,577 goats giving an average of 6 head of goats per goat-rearing-household. Rombo had the largest number of goats (198,082 goats, 35% of all goats in the region), followed by Moshi Rural (168,107 goats, 29%), Hai (103,077 goats, 18%), same (55,561 goats, 10%) and Mwanga (47,751 goats, 8%). Sheep Sheep rearing was the third important livestock keeping activity in Kilimanjaro region after cattle and goats. The region ranked 5 out of 21 Mainland regions and had 7 percent of all sheep on Tanzania Mainland. Pigs Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 3rd out of 21 Mainland regions and is 14 percent of the Mainland total pigs. Chicken The poultry sector in Kilimanjaro region was dominated by chicken production. The region contributed 5.0 percent to the total chicken population on Tanzania Mainland. • Use of Draft Power Use of draft animals to cultivate land in Kilimanjaro region is encouraging with 10,551 households (4.9% of the total households in the region). The number of households that used draft animals in Hai district was 7,710 (73% of the households using draft animals in the region). In Moshi Rural district the number of households using draft animals was 1,357 (13%), Mwanga (1,238 households, 12%), Same (142 households 1%) and Rombo (103 households, 1%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xii iv) Poverty Indicators Availability of Toilets A large number of rural agricultural households use traditional pit latrines (194,950 households, 90% of all rural agricultural households). This is followed by flush toilets (5,538 houeholds 3%), improved pit latrines (11,310 households, 5%) and other types of toilets (231 household, 0.1%). However, 4,143 households (2%) in the region had no toilet facilities Household Assets Out of all assets, the radio was the most common household assets and was owned by 78% of the households, followed by iron (48%), bicycle (28%), wheelbarrow (21%), mobile phone (10%), television/video (4%), and vehicle (3%) and landline phone (2%). Source of Lighting Energy Hurricane lamp was the most common source of lighting energy in the region. About 42.4 percent of the total rural households used this source of energy followed by wick lamp (38.6%), main electricity (12.4), and pressure lamp (6.0%), the remaining constitute less than (5%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.7 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (1.6 percent). The rest of energy sources accounted for 0.7 percent, the remaining constitute for 1.8 percent, these were crop residues (0.9 percent) and mains electricity (0.7), solar energy (0.5%), paraffin/kerosene oil (0.3%), bottle gas and biogas (0.1%) Roofing Materials The most used roofing material (for the main dwelling) was iron sheet and was used by 89.7% of the rural agricultural households. It was followed by grass/leaves (7.6%). Other roofing materials were grass/mud (1.2 percent), asbestos and tiles both had (0.5 percent). Number of Meals per Day About 61.7% of the households in the region took three meals per day, 33.8% took two meals, 4.1 percent took one meal and 0.5 percent took four meals • Food Security Households which never had problems in satisfying their food needs represented 55% of the total number of agricultural households in the region. Households which rarely experienced problems represented 30% whereas those with often problems represented 6 percent. About 5 percent of the agricultural households always faced food shortages whilst 4% seldom experienced food shortage problems. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xiii Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 43.9% of all rural agricultural households. The second main cash income earning activity was selling of cash crops (15.9 percent), cash and remittance (11.3), wages and salaries (10.9%), businesses income (9.9 percent), sales of livestock (2.7%), sale of livestock product (1.4 percent), sale of forest products (1.4 percent) and fishing (0.2%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xiv ILLUSTRATIONS List of Tables 2.1 Census Sample Size................................................................................................................................6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District ..................................................................................................................................................15 3.2 Area, Production and Yield of Cereal Crops by Season.......................................................................25 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop ..........................31 3.4 Area, Quantity Harvested and Yield of Pulses by Season....................................................................34 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season......................................................36 3.6 Area, Production and Yield of Fruits and Vegetables by Season.........................................................39 3.8 Land Clearing Methods ........................................................................................................................48 3.9 Number of Crop Growing Households and Planted Area (ha) by Type of Fertilizer Used and District during the Long Rainy Season ………………………………………………………….........54 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ..................................66 3.12 Reasons for Not Selling Crop Produce.................................................................................................72 3.13 Access to Inputs....................................................................................................................................74 3.15 Total Number of Households and Chickens Raised by Flock Size ......................................................90 3.16 Head Number of Other Livestock by Type of Livestock and District..................................................94 3.17 Mean Distances from Holders Dwellings to Infrastructures and Services by Districts........................99 3.18 Number of Households by Number of Meals the Household Normally Has per Day and District……………………………………………………………………………………………107 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings..........................................11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head................................15 3.3 Percentage Distribution of Population by Age and Sex in 2003 ..........................................................16 3.4 Percentage Literates Level by District..................................................................................................16 3.5 Literacy Rates of Heads of Household by Sex and District..................................................................17 3.6 Percentage of Person Aged 5 years and Above by District and Educational Status.............................17 3.7 Percentage Distribution of Persons Aged 5 Years and Above in Education Status and District...............................................................................................................17 3.8 Percentage Distribution of Heads of Household by Educational Attainment.......................................18 3.9 Number of Households by Number of Members with Off-farm Activities..........................................18 3.10 Percentage Distribution of Agricultural Households by Number of Members with Off-farm Activities and District....................................................................................18 3.11 Utilized and Usable Land per Household by District...........................................................................20 3.12 Percentage Distribution of Land Area by Type of Land Use ...............................................................20 3.13 Area Planted with Annual Crops (ha) by Season and District..............................................................23 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xv 3.14 Area Planted with Annual Crops per household by Season and District..............................................23 3.15 Area Planted with Annual Crops per household and Vegetables by Season.......................................23 3.16 Planted Area for the Main Annual Crops (ha)......................................................................................24 3.17 Planted Area (ha) per Household for Selected Crops...........................................................................24 3.18 Percentage Distribution of Area Planted with Annual Crops by Crop Type........................................25 3.19 Area Planted with Annual Crops by Type of Crops and Season ..........................................................25 3.20 Area Planted and Yield of Major Cereal Crops....................................................................................27 3.21 Maize: Total Area Planted and Planted Area per Household by District .............................................27 3.22 Maize Production Trend as per Agriculture Censuses and Surveys.....................................................27 3.23 Time Series of Maize Planted Area and yield ......................................................................................28 3.24 Total Area Planted and planted Areas Per Households By District......................................................28 3.25 Time Series Data on Paddy Production ................................................................................................28 3.26 Time Series of Paddy Planted Area and Yield......................................................................................29 3.27 Area planted with Sorghum, Finger Millet and Wheat by District.......................................................29 3.28 Area Planted and Yield of Major Root and Tuber Crops .....................................................................29 3.29a Area Planted with Cassava during the Census/Survey Years...............................................................31 3.29b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District........................31 3.30 Cassava Planted Area per Cassava Growing Households by District ..................................................32 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District...............................32 3.32 Area Planted and Yield of Major Pulse Crops......................................................................................34 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District................................35 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only)...........................35 3.35 Time Series Data on Bean Production..................................................................................................35 3.36 Time Series of Bean Planted Area and Yield .......................................................................................35 3.37 Area Planted and Yield of Major Oil Seed Crops.................................................................................36 3.38 Time Series Data on Groundnuts Production .......................................................................................36 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........... 38 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only)................. 38 3.42 Area Planted and Yield of Fruits and Vegetables................................................................................ 38 3.43 Area Planted per Tomato Growing Household by District (Short Rainy Season Only)...................... 43 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District..................... 43 3.45 Percent of Chilies Planted Area and Percent of Total Land with Chillies by District......................... 43 3.46 Area planted with Annual Cash Crops ................................................................................................ 44 3.47 Percent of Sunflower Planted Area and Percent of Total Land with Sunflower by District ............... 44 3.48 Area Planted for Annual and Permanent Crops....................................................................................45 3.49 Area Planted with the Main Permanent Crops..................................................................................... 45 3.51 Percent of Area Planted with Permanent crops and Average Planted Area per Household by District.......................................................................................................................... 45 3.52 Percent of Area Planted with Coffee and Average Planted Area per Household by District.............. 46 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xvi 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District............ 46 3.54 Percent of Area Planted with Bananas and Average Planted Area per Household by District ........... 47 3.55 Percent of Area Planted with Guava and Average Planted Area per Household by District................47 3.56 Number of Households by Method of Land Clearing During the Long Rainy Season........................48 3.57 Area Cultivated by Cultivation Method............................................................................................... 48 3.58 Area Cultivated by Method of Cultivation and District....................................................................... 52 3.60 Area Planted with Improved Seed by Crop Type................................................................................ 52 3.59 Area Planted with Improved Seeds.......................................................................................................52 3.61 Percentage of Crop Type Area Planted with Improved Seed – Annuals............................................. 53 3.62 Area of Fertilizer Application by Type of Fertilizer............................................................................ 53 3.63 Area of Fertilizer Application by Type of Fertilizer and District........................................................ 53 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season....................................... 54 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals ...................................... 55 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District............................................55 3.66 Planted Area with Inorganic fertilizers by Crop Type ........................................................................ 55 3.67a Percentage of Planted Area with Inorganic Fertilizers by Crop Type– Annuals..................................55 3.67b Proportion of Planted Area Applied with Inorganic Fertilizers by District..........................................57 3.68a Planted Area with Compost by Crop Type - Long Rainy Season ....................................................... 57 3.68b Percentage of Planted Area with Compost by Crop Type ....................................................................58 3.68c Proportion of Planted Area Applied with Compost by District............................................................58 3.69 Planted Area (ha) by Pesticide Use...................................................................................................... 58 3.70 Planted Area Applied with Insecticides by Crop Type........................................................................ 59 3.71 Percentage of Crop Type Planted Area Applied with Insecticides.......................................................59 3.72 Percentage of Planted Area Applied with Insecticides by District ..................................................... 59 3.73 Planted Area Applied with Herbicides by Crop Type ......................................................................... 60 3.74 Percentage of Crop Type Planted Area Applied with Herbicides ........................................................60 3.75 Proportion of Planted Area Applied with Herbicides by District ........................................................60 3.76 Planted Area Applied with Fungicides by Crop Type......................................................................... 61 3.77 Percentage of Crop Type Planted Area applied with Fungicides ........................................................ 61 3.78 Proportion of Planted Area Applied with Fungicides by District ....................................................... 61 3.79 Area of Irrigated Land ......................................................................................................................... 62 3.80 Planted Area with Irrigation by District............................................................................................. 62 3.81 Time Series OF Households with Irrigation.........................................................................................63 3.82 Number of Households with Irrigation by Source of Water.................................................................63 3.83 Number of Households by Method of Obtaining Irrigation Water.......................................................63 3.84 Number of Households and Quantity Stored by Crop .........................................................................64 3.86 Number of Households by Storage Method ........................................................................................ 65 3.87 Number of Households by method of Storage and District (based on the most important household crop) ....................................................................................................................................65 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xvii 3.88 Normal Length of Storage for Selected Crops..................................................................................... 65 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .....................................66 3.90 Number of Households by Purpose of Storage and Crop ....................................................................66 3.91 Households Processing Crops by District.............................................................................................67 3.92 Percent of Crop Processing Households by Method of Processing..................................................... 67 3.93 Number of Households by Type of Main Processed Product.............................................................. 69 3.94 Number of Households by Type of By-product .................................................................................. 69 3.95 Use of Processed Product .....................................................................................................................69 3.96 Percentage of Households Selling Processed Crops by District.......................................................... 70 3.97 Location of Sale of Processed Products............................................................................................... 70 3.98 Percent of Households Selling Processed Products by Outlet and District ......................................... 70 3.99 Number of Crop Growing Households that Sold Crops by District .................................................... 70 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ...... 71 3.101 Percentage Distribution of Households that Received Credit by Main Source ................................... 71 3.102 Proportion of Households who Received Credits by Main Source of the Credit ................................ 72 3.103 Proportion of Households Receiving credit by Main Purpose of the Credit ........................................72 3.104 Reason for nit Using Credit (%of Households)....................................................................................72 3.105 Number of Households Receiving Extension Advice ......................................................................... 73 3.106 Number of Households Receiving Extension by District.................................................................... 73 3.107 Number of Households Receiving Extension masagese by Quality of Service .................................. 73 3.108 Number of Households Receiving Extension by Quality of Service....................................................73 3.109 Number of Households Reporting Distance to Source of Inorganic Fertilizers ...................................74 3.110 Number of Households by Source of Improved Seeds.........................................................................76 3.111 Number of Households Reporting Distance to Source of Improved Seeds..........................................77 3.112 Number of Households by Source of Insecticides/Fungicides .............................................................77 3.114 Number of Households reporting Distance to Source of Insecticides/Fungicides................................78 3.115 Number of Households with Planted Trees ..........................................................................................78 3.115 Number of Planted Trees by Species....................................................................................................78 3.116 Number of Trees Planted by Smallholders by Species and District .....................................................79 3.117 Number of Trees Planted by Location..................................................................................................79 3.118 Number of Households by Purpose of Planted Trees...........................................................................79 3.119 Number of Households with Erosion Control/Water Harvesting Facilities ........................................ 81 3.120 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............................................................................................................................. 81 3.121 Number of Erosion Control/Water Harvesting Structures by Type of Facility ................................... 81 3.122 Total Number of Cattle ('000') by District........................................................................................... 82 3.124 Numbers of Cattle by Type and District.............................................................................................. 82 3.126 Dairy Cattle Population Trend............................................................................................................. 83 3.126 Total Number of Goats ('000') by District ........................................................................................... 84 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xviii 3.128 Goat Population Trend......................................................................................................................... 85 3.129 Total Number of Sheep by District...................................................................................................... 85 3.130 Sheep Population Trend....................................................................................................................... 85 3.131 Total Number of Pigs by District......................................................................................................... 88 3.132 Pig Population Trend ........................................................................................................................... 88 3.133 Total Number of Chicken by District .................................................................................................. 89 3.134 Chicken Population Trend ................................................................................................................... 89 3.135 Layers Population Trend...................................................................................................................... 90 3.136 Broilers Population Trend.................................................................................................................... 90 3.137 Number of Improved Chicken by Breed Type and District................................................................. 94 3.138 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District ................................................................................................................................................. 94 3.139 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........................................................................................................................................... 95 3.140 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services............................................................................................................................... 95 3.141 Number of Households by distance to Verterinary clinic and district..................................................97 3.142 Number of households by Distance to Village watering Points ...........................................................97 3.143 Number of households by Distance to Village watering Points and District........................................97 3.144 Number of Household using Draft Ani,mal..........................................................................................98 3.145 Number of Household using Draft Ani,mal by District........................................................................98 3.146 Number of Household using Organic Fertilizer ...................................................................................98 3.147 Number of Household using Organic Fertilizer by District..................................................................99 3.148 Number of Household Practicing Fish Farming..................................................................................99 3.151 Percentage Distribution of Households Owning the Assets ...............................................................101 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking...............................101 1.153 Percentage Distribution of Households by Main Source of Energy for cooking................................102 1.154 Percentage Distribution of Households by Type of Roofing Material ...............................................102 1.155 Percentage Distribution of Households With iron sheet Roofs ..........................................................102 3.160 Percentage Distribution of the Number of Households by Main Source of Income ..........................108 List of Maps 3.1 Total Number of Agricultural Households by District .........................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District...........................................12 3.3 Number of Crop Growing Households by District..............................................................................13 3.4 Percent of Crop Growing Households by District...............................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District .............................14 3.6 Percent of Crop and Livestock Households by District.......................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land...........................................................21 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xix 3.8 Total Planted Area (annual crops) by District .....................................................................................21 3.9 Area planted and Percentage during the Short Rainy Season by District............................................22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.....................22 3.11 Planted Area and Yield of Maize by District.......................................................................................26 3.12 Area Planted per Maize Growing Household......................................................................................26 3.15 Planted Area and Yield of Cassava by District....................................................................................30 3.16 Area Planted per Cassava Growing Household...................................................................................30 3.17 Planted Area and Yield of Beans by District.......................................................................................33 3.18 Area Planted per Beans Growing Household ......................................................................................33 3.19 Planted Area and Yield of Sunflower by District................................................................................40 3.20 Area Planted per Sunflower Growing Household ...............................................................................40 3.21 Area Planted per Tomatoes Growing Household ................................................................................41 3.22 Planted Area and Yield of Tomatoes by District.................................................................................41 3.23 Area Planted per Banana Growing Household....................................................................................42 3.24 Planted Area and Yield of Banana by District.....................................................................................42 3.26 Area Planted per Coffeee Growing Household ...................................................................................49 3.27 Planted Area and Yield of Coffee by District......................................................................................49 3.29 Area Planted per Mangoes Growing Household .................................................................................50 3.30 Planted Area and Yield of Mangoes by District..................................................................................50 3.31 Area Planted per Avocado Growing Household..................................................................................51 3.32 Planted Area and Yield of Avocado by District ..................................................................................51 3.33 Planted Area and Percent of Planted Area with No Application of Fertilizer by District ...................56 3.34 Area Planted and Percent of Total Planted Area with Irrigation by District .......................................56 3.35 Percent of Households Storing Crops for 3 to 6 Months by District...................................................68 3.36 Number of Households and Percent of Total Households Selling Crops by District..........................68 3.37 Number of Households and Percent of Total Households Receiving Crop Extension Services by District..............................................................................................................................75 3.38 Number and Percent of Crop growing Household Using improved seed by District..........................75 3.39 Number and Percent of Smallholder Pranted Tree by District ............................................................80 3.40 Number and percent of Households with water Harvesting Bunds.....................................................80 3.41 Cattle population by District as of 1st Octobers 2003.........................................................................86 3.42 Cattle Density by District as of 1st October 2003 ...............................................................................86 3.43 Goat population by District as of 1st Octobers 2003...........................................................................87 3.44 Goat Density by District as of 1st October 2003.................................................................................87 3.45 Sheep population by District as of 1st Octobers 2003.........................................................................91 3.46 Sheep Density by District as of 1st October 2003...............................................................................91 3.47 Pig population by District as of 1st Octobers 2003 .............................................................................92 3.48 Pig Density by District as of 1st October 2003 ...................................................................................92 3.49 Number of Chicken by District as of 1st October 2003.......................................................................93 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ xx 3.50 Density of Chicken by District as of 1st October 2003 .......................................................................93 3.51 Number and percent of households Infected by Ticks.........................................................................96 3.52 Number and percent of households Using Draft Animals byDistrict..................................................96 3.53 Planted Area and Percent of Planted Area with FarmYard manure Application...............................100 3.54 Planted Area and Percent of Planted Area With Composit Application by District .........................100 3.55 Number and Percent of Households Practicing Fish Farming...........................................................103 3.56 Number and Percent of Households Without Toilets ........................................................................103 3.57 Number and Percent of Households Using Grass/Leaves as Roofing Material ................................104 3.58 Number and Percent of Households Eating 3 Meals per Day ...........................................................104 3.59 Number and Percent of Households Eating Once Meat per week.....................................................105 3.60 Number and Percent of Households Eating Fish once per week.......................................................105 INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on its geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information is intended to provide the user of this report a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries The region is located in the north eastern part of Tanzania Mainland. It lies, south of the equator between latitude 20 25’ and 40 25’ 3’’ and 380 18’’’ 00’’ east of Greenwich. It has a common boarder with Kenya in the north. To the southeast it shares its boarder with Tanga region. To the south and west the region boarders Arusha region. 1.3 Land Area The region has an area of 13,209 sq. kilometers, or 1.4% of the area of the entire Tanzania Mainland. 1.4 Climate In the mountainous areas, temperature ranges from about 150c-300c. The soils of the region vary but are dominated by alluvial soils in the lowland areas which through irrigation have high agricultural potential. This is a blessing since the lowlands have unreliable rainfall. In the highlands the soils being of volcanic origin are very fertile. Mount Kilimanjaro’s rain shadow dramatically reduces rainfall. 1.4.1 Rainfall Kilimanjaro region has two types of rain seasons namely: Long rainfall season (Masika) which starts from April to Mid June and Short rainfall season, (Vuli) which starts from September to November, mean annual rainfall 500 mm in lowlands and 2000 mm in the highland zone. 1.5 Population Kilimanjaro had a population of 1,376; 702 sq. kilometers according to the 2002 population census represent 4.1% of total population of Tanzania Mainland 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 427,374 million with a per capita income of shillings 306,299 . The region held 9th th position among regions on GDP and contributed about 4.4 percent to the national GDP. Kilimanjaro region is one of the regions that is endowed with richness in terms of wildlife. The region has got several tourist attractions including the Kilimanjaro National Park, which is the home for the high altitude wildlife and a variety of insects and game reserves such as the Mkomazi Game reserve. Another INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 2 important tourist and game reserve such as the Mkomazi Game reserve. Another important tourist attraction is the highest mountain in Africa, which is second to Mount Everest. 2 INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 3 The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Kigoma region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 4 Identification (i.e. region, district, ward and village) Household and holding characteristics Household information Land ownership/tenure Land use Access and use of resources Crop and vegetable production Agro processing and by-Products Crop storage and marketing On-farm investment Access to farm inputs and implements Use of credit for agricultural purposes Tree farming/agro-forestry Crop extension services Livelihood constraints Animal contribution to crop production Livestock Livestock products Fish farming Livestock extension Labour use Access to infrastructure and other services Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 5 items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation Sample design Design of census questionnaires and other instruments. Field pretesting of the census instruments Training of trainers, supervisors and enumerators Information Education and Communication (IEC) campaign Data Collection Field supervision and consistency checks Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 6 Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 7 Where feasible all variables were extensively coded to reduce post enumeration coding error. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. Skip patterns were used to avoid asking unnecessary questions Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during than training Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Kigoma, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 8 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 9 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: Manual editing Data entry Data structure formatting Batch validation Tabulation Illustration production Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR Extraction Technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number INTRODUCTION ______________________________________________________________________________________ ____ ________________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census 10 of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch Validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and Report Preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the census results for Kilimanjaro region, based on the statistical data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Kilimanjaro region was 216,173.The largest number of agricultural households was higher higher in Moshi rural (76,826) followed by Rombo (47,014), Hai (46,481) Same (29,103) and Mwanga (16,749 the highest density of households was found in Moshi rural (221km2) (Map 3.2). Most households (156,467) were involved in crops & Livestock, (1,951, 0.9%) were rearing livestock only, and (59,040, 30.2%) were involved in crop production as well as livestock keeping. There were only (35, 0.1% pastoralist in Kilimanjaro Region. (Chart 3.1 and Map 3.2, 3.3, 3.4, 3.6 and 3.6) Chart 3.1 Agriculture Households by Type Pastoralists 0.02% Crops Only 26.7% Livestock Only 0.9% Crops and Livestock 72.4% Moshi Rural Mwanga Moshi Urban Hai Rombo 30 47 0 43 176 18 Same 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Mwanga Hai Moshi Urban Moshi Rural Rombo 29,103 47,014 0 76,826 46,481 16,749 Same 60,000 to 77,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Number of Agricultural Households Per Square Km of Land by District MAP 3.01 KILIMANJARO MAP 3.02 KILIMANJARO Total Number of Agricultural Households by District Tanzania Agriculture Sample Census Number of Agricultural Households Per Square Km Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km RESULTS 12 Same Mwanga Moshi Urban Moshi Rural 98 98 0 98 100 100 Hai Rombo 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Moshi Urban Mwanga Moshi Rural Hai Rombo 0 45,501 28,623 16,482 47,014 76,566 Same 60,000 > 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Percent of Crop Growing Households by District MAP 3.03 KILIMANJARO MAP 3.04 KILIMANJARO Number of Crop Growing Households by District Tanzania Agriculture Sample Census Percent of Crop Growing Households Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households RESULTS 13 Moshi Rural Moshi Urban Same Mwanga Rombo Hai 0% 12% 8% 24% 20% 36% 24 > 18 to 24 12 to 18 6 to 12 0 to 6 Moshi Rural Same Mwanga Moshi Urban 30 0 18 46 175 43 Hai Rombo 160 > 120 to 160 80 to 120 40 to 80 0 to 40 Percent of Crop and Livestock Households by District MAP 3.05 KILIMANJARO MAP 3.06 KILIMANJARO Number of Crop Growing Households per Square Kilometer of Land by District Tanzania Agriculture Sample Census Percent of Crop and Livestock Households Number of Crop Growing Households per Sq Km Number of Crop Growing Households per Sq Km Percent of Crop and Livestock Households RESULTS 14 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 15 Table 3.1: The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 2 1 3 4 6 7 5 Mwanga 1 3 4 2 6 7 5 Same 1 2 3 5 6 7 4 Moshi Rural 1 2 3 4 6 7 5 Hai 1 2 3 5 6 7 4 Total 1 2 3 4 6 7 5 3.1.2 Livelihood Activities/Source of Income The census results for Kilimanjaro region indicates that most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, livestock keeping/herding, off farm income, tree/forest resources, remittances, fishing hunting & gathering (Table 3.1) Kilimanjaro Urban district was the district where annual crop farming was not the most important livelihood activity and was replaced by permanent crop farming. 3.1.3 Sex and Age of Heads of Households The number of male-headed agriculture households in Kilimanjaro region was 545,216 (48.9% of the total regional agricultural households) whilst the female- headed households it were 569,990 (51.1% of the total regional agricultural households). The mean age of household heads was 51 years (50 years for male heads and 55 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of H ouseholds Male headed households Female headed households RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 16 3.1.4 Number and Age of Household Members Kilimanjaro region had a total rural agricultural Population of 1, 15,206 of which 545,216 (48.9%) were males and (569,990 51.1%) were females. Whereas age group 0-14 constituted 38.5 percent of the total rural agricultural population, age group 15-64 (active population) was 54.5 percent. Kilimanjaro region had an average household size of 5 with Rombo district having the highest households’ size of 6 (Chart 3.3) 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Kilimanjaro region had a total literacy rate of 86.7 percent. The highest literacy rate was found in Mwanga district (87.7%) followed by Moshi rural district (89.3%), Rombo (85.3%), Same and Hai both had (84.8%), thus Same and Hai had the lowest literacy rates. Chart 3.3 Percent Distribution of Population by Age and Sex 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group P ercen t Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 50 100 Mwanga Moshi rural Rombo Same Hai District Percent RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 17 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 87.1 percent. The literacy rate for the male heads was 82% and that of female heads of households was 70%. Literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Mwanga (94.9%) followed by Moshi rural (94.2%), Same (93.9%), Hai (86.5%) and Rombo (86.5%). (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 52 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 37 percent were still attending school. Those who have never attended school were 11 percent (Chart 3.6). Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 52% Never Attended 11% Attending School 37% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Rombo Mwanga Same Moshi rural Hai District Percen t Attending School Completed Never Attended Chart 3.5 Literacy Rates of Head of Household by Sex and District 0.0 25.0 50.0 75.0 100.0 Rombo Mwanga Same Moshi Rur Hai District Percen t Male Female Total RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 18 Agricultural households in Moshi rural had the highest percentage (53.0%) of population aged 5 years and above who had completed different levels of education. This was followed by Rombo and Hai district (52%), Mwanga and Same both had 51 percentage. The number of heads of agricultural households with formal education in Kilimanjaro region was 185,978 (86.0%), those without formal education were 28,714 (13.3%) and those with only adult education were 1,451 (0.7%). The majority of heads of agricultural households (73.4%) had primary level education whereas only 3.9% had post secondary education (Chart 3.8). With regard to the heads of agricultural households with primary or secondary education in Kilimanjaro region, Same district had the highest percentages (83.3% for primary and 4.8% for secondary). It was followed by Mwanga (78.2% primary and 6.9% secondary), Hai (72.5% primary and 5.5% for secondary), Rombo (71.1% primary and 8.6% secondary) and Moshi rural (70.5% for primary and 11.9% for secondary) 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Kilimanjaro with 65.3% of households with at least one household member engaged in off-farm income generating activities, 79,886 households (56.6%) had only one member aged 5 years and above involved in off-farm income generating activities Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment University 0.8% Adult Education School 0.7% Post Secondary Education 3.9% Post Primary Education 0.8% No Education 13.3% Primary Education 73.4% Chart 3.10: Number of Household Members with off-farm Activities 0% 20% 40% 60% 80% 100% Rombo Mwanga Same Moshi rural Hai Districts Percent One Off Farm Income Two Off Farm Income More than Two Off Farm Income RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 19 38,977 households (27.6%) had two members involved in off-farm income generating activities and 22,299 households (15.7%) had more than two members involved in off-farm income generating activities. The districts with highest percentage of households with off-farm income was Moshi rural followed by Rombo, Hai, Same and Mwanga. The district with the highest percent of agriculture households with more than two members with off-farm income was Moshi rural (19.1%), Rombo (17.6%), Hai (13.1%), Mwanga (12.8%) and Same (9.1%). 3.2 Land Use Land area and planted area are different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total of all areas planted with crops in a year and the areas are summed if there were more than one crop on the same year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that had been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agricultural land in the country; Instead it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused through designated of agricultural land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. Chart 3.9 Percentage Distribution of Household Members of Five Years and Above by Number of Off-farm Activities Two Off Farm Income 28% One Off Farm Income 56% More than Two Off Farm Income 16% RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 20 3.2.1 Area of Land Utilised The total area of land available to smallholders was 276,325 ha, including 2,885 of unusable land. At Regional level the average land area utilised for agriculture per household was only 1.3 ha. This figure is below to the national average which was estimated at 2.0 hectares. The percent utilized of the land available to smallholders was 99%. There were small differences in land utilization per household between districts with Hai district utilizing 2.0 ha per household. The smallest land area utilised per household was found in Rombo (0.9 ha). The percentage utilized of the usable land per household is highest in Rombo (99.6%) and lowest in Mwanga where 97.9% of the total land available to smallholders was utilised and only 1.0 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary mixed crops was 119,239 hectares (25.0% of the total land available to smallholders in Kilimanjaro), followed by area of permanent mixed crops (103,463 ha, 21%), area of temporary mono crops (67,419 ha, 14%), planted tree (67,419 ha, 14%), permanent annual mix (50,164 ha, 10%), permanent mono crops 19,457 ha, 4%), area under pasture (14,662 ha, 3%), area under fallow 11,946 ha, 2%), area uncultivated usable land 11,214 2%), area unusable 11,214 ha, 2%) and area rented to others 6,021 ha, 1%). 3.3 Annual Crops and Vegetable Production Kilimanjaro region has two rainy seasons, which are the short rainy season (October to December) and the long rainy season (March to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. Chart 3.12 Land Area by Type of Use 1.0 2.0 2.0 2.0 3.0 4.0 10.0 14.0 14.0 14.9 25.0 21.0 0 50,000 100,000 150,000 Area rented to Others Area Unusable Area Uncultivated Usable Land Area Under Fallow Area Under Pasture Permanent Mono Crops Permanent Annual Mix Planted Trees Temporary Mono Crops Temporary Mixed Crops Permanent mixed crops Area under Temporary Mixed Crops Land Use Area (hectares) Chart 3.11 Utilized and Usable Land per household by district 0.0 1.0 2.0 3.0 Rombo Mwanga Same Moshi rural Hai Districts Area/household 96.5 97.0 97.5 98.0 98.5 99.0 99.5 100.0 Percentage utilized Area utilised (Ha) Total Usable Area available (ha) Percent Utilisation Hai Same Moshi Urban Moshi Rural Mwanga Rombo 69% 62% 0% 73% 75% 81% 80 > 60 to 80 40 to 60 20 to 40 0 to 20 Moshi Rural Same Hai Rombo Moshi Urban Mwanga 38,564ha 37,192ha 36,093ha 45,444ha 0ha 16,960ha 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Total Planted Area (Annual Crops) by District MAP 3.07 KILIMANJARO MAP 3.08 KILIMANJARO Utilized Land Area Expressed as a Percent of Available Land by District Tanzania Agriculture Sample Census Planted Area (Annual Crops) Percent of Utilized Land Area Percent of Utilized Land Area Planted Area (Annual Crops) RESULTS 21 Moshi Urban Moshi Rural Mwanga Same Rombo Hai 2,241ha 0ha 14,336ha 3,759ha 5,335ha 14,303ha 0.8% 0% 0.9% 1.4% 0.8% 0.9% Moshi Urban Moshi Rural Mwanga Rombo Same Hai 0ha 6,662ha 8,139ha 26,804ha 21,782ha 5,873ha 0% 17.3% 59% 48% 58.6% 16.3% Area Planted with Cereals and Percent of Total Land Planted with Cereals by District MAP 3.09 KILIMANJARO MAP 3.10 KILIMANJARO Area Planted and Percentage During the Short Rainy Season by District Tanzania Agriculture Sample Census Planted Area with Cereals Crops Planted Area During the Short Rainy Season Percent of Planted Area with Cereals Crops 20,000 > 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Planted Area During the Short Rainy Season Planted Area with Cereals Crops Percent of Planted Area During the Short Rainy Season RESULTS 22 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 23 3.3.1 Area Planted The area planted with annual crops and vegetables was 174,253 hectares out of which 104,994 hectares (60%) were planted during long rainy season and 69,254 hectares (40%) during long rainy season. The average areas planted per household during the long and short rainy seasons were 1.5 ha and 2.5 ha respectively (Chart 3.13). The district with the large area planted for both two seasons was Rombo while the district with the smallest area planted was Mwanga and the percentage planted during short rainy season was highest in Rombo district (38%), followed by Same (31.4%), Mwanga (12%), Moshi rural (9.6%), and Hai (8.4%). (Chart 3.14 and Map 3.8 ). The planted area occupied by cereals was 63,594 ha, (60.6% of the total area planted with annuals). This was followed by pulses 28,590 hectares, (27.2%), roots & tubers 5,545 hectares (5.3%), oil seeds& oil nuts 5,358 hectares, (5.1%), fruits and vegetables 1,887 hectares, (1.7%) and cash crops 22 hectares (0.02%) The average area planted per household during the long rainy season in Kilimanjaro region was 1.03 hectares, however, there were Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 104,994, 60% Short Rainy Season, 69,259, 40% Long Rainy Season Short Rainy Season Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 Rombo Mwanga Same Moshi Rural Hai Region A rea P la n ted (h a ) 0.00 20.00 40.00 60.00 80.00 P ercen ta g e P la n ted Short Rainy Season Long Rainy Season % Area planted in short rainy season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.0 0.5 1.0 Rombo Mwanga Same Moshi Rural Hai District Area Planted (ha) per Household Long Rainy Season Short Rainy Season RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 24 small district differences. Same had the largest planted area per household (0.5 ha) followed by Hai (0.4 ha), Moshi rural & Mwanga both had 0.3% and Rombo (0.2 ha). In Rombo the area planted per household in the short rainy season represents 38.7 percent of the total planted area per household, whereas in Hai the corresponding figure is 8.4 per cent. (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of all crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize was the dominant annual crop grown in Kilimanjaro region and it had a planted area 96,593 ha, followed by beans which had the second largest planted area of 44,284 ha. Of the area planted with annuals, maize constitutes 55 percent. Other crops in order of their importance (based on area planted) were maize, beans, sunflower, cassava, finger millet, groundnuts, paddy, tomatoes,cocoyams, amaranths, cocoyams and sweet potatoes (Chart 3.16). Households that grow maize, paddy, irish potatoes have larger planted areas per household than other crops (Chart 3.16). 3.3. 3 Crop Types Chart 3.17 shows the area planted per household growing selected crops. Crops that are mainly grown for cereals have a larger planted area per household than other crops e.g paddy and maize. An Irish potato has the third highest planted area per household growing that crop than staple crops whereas vegetables have the lowest planted area per households. Cereals and root and tubers are the dominant crops and other crop types are of minor Chart 3.16 Planted Area (ha) for the Main Annual Crops 0 50,000 100,000 Maize Beans Sunflower Cassava Finger Millet Groundnuts Paddy Tomatoes Cocoyam Sweet potatoes Crop Planted A rea (ha) Chart 3.17 Planted Area (ha) per Household by Selected Crop 0.00 0.30 0.60 paddy Maize Irish potatoes Cassava fingermillet Beans Groundnuts Sunflower Tomatoes Sweet potatoes Cocoyams Crop Planted Area (ha) per household RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 25 Cereals are the main crops grown in Tanzania. The area planted with cereals was 103,563 ha (59.4% of the total planted area), followed by pulse with 46,950 ha (26.9%), oil seeds & oil nuts 9800 ha (5.6%), roots & tubers 9,800 (5.4%), cash crops are normally permanent crops and are not totally reflected in chart 3.18 vegetables are underestimated because of difficulties in establishing the area and production on small household plots (Chart 3.18). There is little difference in proportions of the crop types grown between seasons. Short rainy season production was very small compared to that of the long rainy season and it is therefore inappropriate to make detailed comparison between two seasons. Cereals, pulses and roots and tubers are the dominant crops grown in both seasons. Other crop types are of minor importance in comparison (chart 3.18) 3.3.4 Cereal Crop Production The total production of cereals was 117,190 tonnes. Maize was the dominant cereal crop at 105,222 tonnes which was (89.8%) of total cereal crops produced, followed by paddy 10,724 tonnes (9.1 %) sorghum 146 tonnes (0.1%) , and finger millet 1098 tonnes (0.9 %), (Map 3.10). Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 38,275 33,360 872 58,318 71,861 1,232 96,593 105,222 2104 Paddy 1,443 4,586 3,177 1,585 6,138 3,871 3,029 10,724 7049 Sorghum 116 78 667 137 69 502 253 146 1170 Finger Millet 139 38 273 3,553 1,060 298 3,692 1,098 571 Total 39,973 38,062 63,594 79,128 103,567 117,190 The total area planted with cereals was 103,567 ha out of which 39,973 ha (38.5%) were planted in short rainy season and 63,594 ha (61.4%) were planted during the long rainy season. The long rainy season accounted for 61.4 percent of the total cereals produced in both seasons. The area planted with maize during the long rainy season was 56.3% of the total area planted with cereals in that season followed by finger millet (3.4%), paddy (1.5%), and sorghum (0.1%). Table 3.2 Chart 3.18: Percentage Distribution of Area Planted with Annual Crops by Crop Type Roots & Tubers, 5.4% Pulses, 26.9% Fruits & Vegetables, 2.5% Cash crops, 0.0% Oil Seeds & Oil 5.6 % Cereals, 59.4% Cereals Pulses Oil seeds & Oil nuts Roots & Tubers Fruits & Vegetables Cash crops 63,594 39,973 28,590 18,361 5,545 3,940 1,887 2,543 5,358 4,442 22 0 0 50,000 100,000 A rea (h ectares) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.19 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season Moshi Urban Same Mwanga Moshi Rural Rombo 0ha 1ha 0.4ha 0.2ha 0.4ha 0.3ha Hai Moshi Urban Moshi Rural Same Mwanga Rombo Hai 0ha 20,451ha 10,702ha 26,275ha 17,806ha 21,360ha 0t/ha 0.8t/ha 0.8t/ha 1.5t/ha 0.9t/ha 1.2t/ha Area Planted per Maize Growing Household by District MAP 3.11 KILIMANJARO MAP 3.12 KILIMANJARO Planted Area and Yield of Maize by District Tanzania Agriculture Sample Census 20,000 > 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 26 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 27 The area planted with maize was dominant and it represented 93.3% of the total area planted with cereal crops, was followed by finger millet (3.4%), paddy (2.2%), finger millet (1.1%) and sorghum with (0.2%).. The yield of paddy was 7049 kg/ha, followed by maize (2104 kg/ha), sorghum (1170 kg/ha), finger millet (571 kg/ha) 3.3.4.1 Maize Maize dominated the production of cereal crops in the region. Moshi rural had the largest area of Maize (26,275 ha, 27.2%), followed by Hai (21,360 ha, 22.1%), Same (20,451 ha, 21.2%), Rombo (17,806 ha, 18.4%) and Mwanga ( 10,702 ha, 11.1%). The average area planted with maize per household was 0.4 hectares, however there were small district differences, Same had the largest area planted per household (0.6 ha), Hai (0.5 ha), Mwanga (0.4 ha) Moshi rural (0.4 ha) and Rombo (0.3 ha) Chart 3.21. Chart 3.22 gives maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. There was a continuous increase in maize production over the three year period from 1998 to 2000 followed by a drop in production from 110 tonnes to 105 tones in 2002/03. Chart 3.20 Area Planted and Yield of Major Cereal Crops 100 50,100 Maize Paddy Sorghum Finger Millet Crop Area Planted (ha) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 10,702 17,806 20,451 21,360 26,275 0 10,000 20,000 30,000 40,000 50,000 60,000 Moshi rural Hai Same Rombo Mwanga District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.22: Time Series Data on Maize Production 110 103 126 105 103 91 96 0 100 200 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 28 Chart 3.23 shows that, the yield of maize declined steadily over the period 1996 to 2002/03 the yield for the year 1995 to 1996 was relatively high. On the other hand the area planted with maize increased over the entire eight – year period from 1995 to 2003. (Chart 3.23 and 3.14) 3.3.4.2 Paddy Moshi rural had the largest area of Paddy (1,486 ha, 49.1%), followed by Same (1,169 ha, 38.6%), Hai (303 ha, 10.0%), Rombo (17,806 ha, 18.4%) and Mwanga ( 71 ha, 2.3%) and paddy were not reported in Rombo district The average area planted with paddy per household was 0.4 hectares, however there were small district differences, Moshi rural had the largest area planted per househ0ld (0.5 ha), Same (0.4 ha), Hai (0.3 ha) and Mwanga (0.3 ha) Chart 3.23. There was a fluctuation in the production of paddy in 1995/96, 1997/98, 1998/1999 and 1999/00, but by the 2002/03 production had dropped significantly. Chart 3.24 Chart 3.25 shows that, the yield of paddy declined steadily over the period 1996 to 1998, then the yield for the year 1999 to 2000 was relatively high and the production started declined significantly in 2002/03 On the other hand the area planted with paddy increased over the entire eight –year period from 1995 to 2003. (Chart 3.23 and 3.14) Chart 3.25 Time Series Data on Paddy Production 16 18 24 9 10 23 26 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.24 Paddy: Total Area Planted and Planted Area per Household by District 0 71 303 1,169 1,496 0 1,000 2,000 Moshi rural Same Hai Mwanga Rombo District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.23 Time Series of Maize Planted Area & Yield 0 50000 100000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area Yield RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 29 3.3.4.3 Other Cereals In terms of area planted with other cereals, bulrush millet and finger millet were less important crops compared to sorghum. The district with the largest area planted with sorghum was Rombo (2,875ha) and Hai (1,499 ha) and Moshi rural (30 ha) There was no bulrush and finger millet production reported in Mwanga, Same, and Moshi rural districts. (Chart 3.26 Map 3.16 ). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 21,040 tonnes. Irish potatoes production was higher than any other root and tuber crop in the region with a total production of 15,592 tonnes representing 74.1 percent of the total root and tuber crops production. This was followed by cassava with 2,628 tonnes (12.5%), sweet potatoes (1,283 tonnes 6.1%) the remaining other crops contribute less than 5% of the total production. The estimated yield was highest for sweet potatoes (1,448 kg/ha) followed by yams (1,274 kg/ha) cocoyams (978kg/ha), cassava (639 kg/ha) and irish potatoes (517kg/ha) . The area planted with cassava was larger than any other root and tuber crops, followed by Irish potatoes, cocoyams, sweet potatoes and yams. Chart 3.26 10 2,010 4,010 Area (Ha) Rombo Mwanga Same Moshi rural Hai District Chart 3.27 Area Planted with Sorghum, Fingermillet by District Sorghum Fingermillet Chart 3.26 Time Series of Paddy Planted Area & Yield 0 1000 2000 3000 4000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 2 4 6 8 Yield (t/ha) Area Yield Chart 3.28 Area Planted and Yield of Major Root and Tuber Crops 0 2,000 4,000 6,000 Cassava Irish Potatoes Cocoyam Sweet potatoes Yams Crop Area Planted (ha) 0 1,000 2,000 Yield (kg/ha) Yield (kg/ha) Mwanga Same Rombo Hai Moshi Rural Moshi Urban 0.6ha 0.5ha 0.6ha 0.1ha 0.2ha 0ha Moshi Urban Same Mwanga Moshi Rural Rombo Hai 0ha 2,343ha 389ha 28ha 1,269ha 81ha 0t/ha 0.9t/ha 0t/ha 0t/ha 0.2t/ha 2.1t/ha Area Planted per Cassava Growing Household by District MAP 3.15 KILIMANJARO MAP 3.16 KILIMANJARO Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 0.48 to 0.6 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 30 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 31 Table 3.3: Area planted and quantity harvested by season and type of root and tuber crop Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 820 652 795 3,290 1,977 601 4,110 2,629 1,396 Sweet Potatoes 605 960 1,587 280 322 1,150 885 1,282 934 Irish Potatoes 1,618 8,334 5,151 1,398 7,257 5,191 3,016 15,591 1,346 Yams 237 172 726 1,317 90 68 1,554 262 417 Cocoyam 959 536 559 486 584 1,202 1,445 1,120 2,455 TOTAL 4,239 10,654 6,771 52,752 47,614 67,966 Note: Cassava is produced in both the long and short rainy seasons. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported mainly under the long rainy season. It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava has been reported under the long rainy season. 3.3.5.1 Cassava he number of households growing cassava in the region was 12,534. This represented about 2 percent of the total crop growing households in the region. The total production of cassava during the census year was 2,628 tonnes from a planted area of 4,111 hectares resulting in a yield of 0.6 t/ha. Previous censuses and surveys indicate that the area planted with cassava increased over the period 1995 to 2002/03. (Chart 3.28) The area planted with cassava accounted for 2.4 percent of the total area planted with annual crops and vegetables in the census year. Chart 3.29a Area Planted with Cassava during the Census/Survey Years 0 2,000 4,000 6,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava Chart 3.29b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 0.7 2.0 9.5 30.9 57.0 0.0 20.0 40.0 60.0 Same Rombo Mwanga Hai Moshi rural District Percent of Total Area Planted 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 32 Same district had the largest planted area of cassava (2,343 ha) of cassava planted area in the region), followed by Rombo (1,269 ha), Mwanga (389 ha) Hai (81 ha) and Moshi rural (28 ha) (Chart 3.28 and Map 3.18) However, the district with the highest proportion of its land planted with cassava was in Same (57.0%). This was followed by Rombo (30.9%), Hai (2.0%), and Moshi rural (0.7%) (Chart 3.28). The average cassava planted area per cassava growing household was 0.3 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Same (0.37 ha), Rombo (0.31 ha), Mwanga (0.29 ha), Moshi rural (0.20 ha), and Hai (0.13 ha). (Chart 3.29). 3.3.5.2 Irish Potatoes The number of households growing irish potatoes in Kilimanjaro region was 4,484 and 2,823 during short and long rainy seasons. This was 32% of the total root and tuber crop growing households during both seasons. The total production of irish potatoes during the census year was 15,592 tonnes from a planted area of 3,016 hectares resulting in a yield of 5.1t/ha. Hai district has the largest planted area for irish potatoes (2,391 ha, 79.5%), followed by Same (336 ha, 11.1%), Rombo (265 ha 8.8%) and Moshi rural (17 ha, 0.5%) (Chart 3.31 and Map 3.19). 3.3.6 Pulse Crops Production: The total area planted with pulses was 46,949 hectares out of which 44,283 ha were planted with beans (94 percent of the total area planted with pulses), other pulse crops were of minor importance in terms of area planted, Chart 3.31 Irish Potatoes: Total Area Planted and Planted Area per Household by District 6 17 265 336 2,391 0 2,000 4,000 Hai Same Rombo Moshi rural Mwanga District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Area Planted per Household Area planted (ha) Area planted/hh 0.00 0.20 0.40 0.60 Area per Household Same Rombo Mwanga Moshi rural Hai District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Moshi Urban Moshi Rural Mwanga Same Rombo 0ha 0.2ha 0.5ha 0.8ha 0.6ha 0.3ha Hai Moshi Urban Same Mwanga Moshi Rural Rombo Hai 0ha 10,829ha 4,452ha 6,524ha 13,664ha 8,815ha 0t/ha 0.8t/ha 0.8t/ha 1.5t/ha 0.9t/ha 1.2t/ha Area Planted per Beans Growing Household by District MAP 3.17 KILIMANJARO MAP 3.18 KILIMANJARO Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 33 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 34 The area planted with pulses in the long rainy season was 28,590 ha which represented 61 percent of total area planted with pulses during the year. Beans was the most dominant pulse crop during long rainy season with 27,262 ha (94.6 % of the total area planted with pulses in that particular season), followed by cowpeas 1,004 ha, (3.5%) green gram 260 ha, (0.9%), mung beans 233 ha, (0.8%), and field peas 30 ha (0.1%). The total production of pulses was 18,599 tonnes. Beans production constituted 94.8 percent of the total pulse production. It was followed by cowpeas (561t, 3.0%), green grams (261t, 1.4%), and mung beans (101t, 0.5%) (Chart 3.32). Table 3.4: Area, Quantity Harvested and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 17,221 6,918 402 27,062 10,704 396 44,283 17,622 398 Cowpeas 814 325 399 1,004 237 236 1,818 562 309 Green Gram 308 169 549 260 92 354 568 261 460 Field Peas 4 2 500 30 51 1,700 34 53 1,559 Mung Beans 13 2 154 233 99 425 246 101 411 TOTAL 18,360 7,416 28,589 11,183 46,949 18,599 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 25,000 50,000 Beans Cowpeas Green Gram Mung Beans Field Peas Bambaranuts Chich Peas Crop Area Planted (ha) 0 1,000 2,000 Yield (kg/ha) Yield (kg/ha) RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 35 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Kilimanjaro region in the long and short rainy seasons was 103,410 and 73,082 respectively. The total production of beans in the region was 17,662 tonnes from a planted area of 77,486 hectares resulting in a yield of 0.4t/ha. Rombo with 13,664 ha of beans had the second largest planted area in the region, followed by Same with 10,820 ha. (Chart 3.33). Same district had the largest area planted with beans per household (0.4 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.3 ha. The variations in area planted with beans per household among the districts were small ranging from 0.40 to 0.20 ha, (Chart 3.34 and Map 3.20) In Kilimanjaro region, beans production has increased steadily over the period 1996/97 to 1999/00 from 6 tonnes in 1996 to 33 tonnes in 2000 but thereafter it started dropping and by year 2003 dropped to 18 tonnes (Chart 3.35). Chart 3.36 shows the combined of planted area and production of beans from the year 1997 to the year 2003. From 1997 to 2003 the area planted increased dramatically, the survey a result shows that the production of beans has been fluctuating over the years 1997 to 2002/03. Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 Rombo Same Hai Moshi rural Mwanga District Percent of Land 0 20 40 Percent A rea Planted of Total Land A rea Percent of Land Proportion of Land 0.40 0.27 0.26 0.25 0.20 0.00 0.25 0.50 Area per Household Same Rombo Mwanga Hai Moshi rural District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.35: Time Series Data on Beans Production 33 6 6 18 30 26 6 0 10 20 30 40 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Chart 3.36 Time Series of Beans Planted Area & Yield 0 20000 40000 60000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 0.8 Yield (t/ha) Area Yield RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 36 3.3.7 Oil Seed Production The total production of oilseed crops was 5,279 tonnes planted on an area of 9,800 hectares. The total planted area of oilseeds during the long rainy season was 5,357 ha representing 54.7 percent of the total area planted with oil seeds. The sunflower was the most important oilseed crop with 6,293 ha (54.6 % of the total area planted with oil seeds), followed by groundnuts (3,413 ha, 34.8%) and simsim (94 ha, 0.9 %). (Table 3.5) The yield for simsim was 1057 kg/ha. The yield for ground nuts was 761 kg/ha and the yield for sunflower was 519 kg/ha (Chart 3.37). Chart 3.38 gives Groundnuts production trend (in thousand metric tonnes for the combined long and short rainy seasons. There was a continuous increase in groundnuts production over the four year period from 1995 to 1998/99 followed by a drop in production from 1600 tonnes to 1534 tones Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 2,955 1,445 489 3,338 2,279 0 6,293 3,724 2,964 Simsim 14 0 0 80 19 625 94 19 625 Groundnuts 1,474 528 358 1,939 1,008 422 3,413 1,536 404 TOTAL 4,443 1,973 5,357 3,306 9,800 5,279 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 2,000 4,000 6,000 8,000 Sunflower Groundnuts Simsim Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) Chart 3.38 Time Series Data on Groundnut Production 1250 1100 1536 1600 0 500 1,000 1,500 2,000 1994/95 1995/96 1998/99 2002/03 Year Production ( tonnes) Moshi Urban Moshi Rural Mwanga Same Rombo 0ha 0.2ha 0.5ha 0.8ha 0.6ha 0.3ha Hai Moshi Urban Same Mwanga Moshi Rural Rombo Hai 0ha 10,829ha 4,452ha 6,524ha 13,664ha 8,815ha 0t/ha 0.8t/ha 0.8t/ha 1.5t/ha 0.9t/ha 1.2t/ha Area Planted per Beans Growing Household by District MAP 3.17 KILIMANJARO MAP 3.18 KILIMANJARO Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 37 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 38 3.3.7.1 Groundnuts The district with the largest groundnuts planted area was Rombo with 2,260 hectares (66.2 percent of the total area planted with groundnuts in the region) followed by Hai (551 ha, 16.1%), Moshi rural (529 ha, 15.5%) and Same district have not reported grown of groundnuts (Chart 3.39 and Map 3.21). The largest area planted per groundnut growing household was found in Hai (0.42 ha), followed by Moshi rural (0.37 ha), Mwanga (0.30 ha and Same district were not reported. The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruits and Vegetables The collection of fruits and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. Reliable historical data for time series analysis of fruits and vegetables are not available the short rainy season is relatively important for fruits and vegetables production since 56 percent of the total area planted with fruits and vegetables was during the short rainy season. For tomatoes, onion, cabbage, water mellon, ginger, and pumkins over 50 percent of the planted area was during the short rainy season. Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 60.0 80.0 Rombo Hai Moshi rural Mwanga Same District Percent of Land 0.0 2.0 4.0 6.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 A rea per Household (ha) Hai Moshi rural Mwanga Mwanga Same District Chart 3.40 Area Planted per Groundnut Growing Households by District (Long Rainy Season Only) Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 1,000 2,000 3,000 Tomatoes Cabbage Chillies Water Mellon Amarath Carrot Others Crop A rea Plan ted (h a) 0 2,000 4,000 6,000 8,000 10,000 Y ield (k g/h a) RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 39 The total production of fruits and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoe with a production of 11,221 tonnes (57.4% of the total fruits and vegetables produced) followed by onion (2,751t, 14.1%), amaranth (1581t, 8.1%), cabbage (1,425t, 7.2%) production of the other fruits and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 8,233 kg/ha, onion (7,997 kg/ha), carrot (5,940 kg/ha) and cucumber (5,500 kg/ha). (Chart 3.42 and Map 3.22). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 14 57 4,071 0 0 0 14 57 4,071 Radish 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 4 2 500 4 2 500 Onions 206 1,255 6,092 138 1,496 10,841 344 2,751 7,997 Ginger 464 1,453 3,131 4 0 0 468 1,453 3,105 Cabbage 91 445 4,890 326 980 3,006 417 1,425 3,417 Tomatoes 882 5,971 6,770 481 5,250 10,915 1,363 11,221 8,233 Spinach 127 154 1,213 156 327 2,096 283 481 1,700 Carrot 220 1,148 5,218 163 1,127 6,914 383 2,275 5,940 Chillies 144 431 2,993 208 750 3,606 352 1,181 3,355 Amaranths 265 1,131 4,268 215 450 2,093 480 1,581 3,294 Pumpkins 23 10 435 5 0 0 28 10 357 Cucumber 39 228 5,846 41 212 5,171 80 440 5,500 Egg Plant 18 83 4,611 0 0 0 18 83 4,611 Water Mellon 50 100 2,000 96 129 1,344 146 229 1,568 Total 2,821 10,723 2,525 8,827 5,346 19,550 3.3.8.1Tomatoes The number of households growing tomatoes in the region during the long rainy season was 2,989 and in the short rainy season the number was 5012. This represented 2.8 percent of the total crop growing households in the region during the long rainy season and 7.2 percent during the short rainy season. Hai district had the largest planted area of tomatoes (1680 ha,45.4% of the total area planted with tomatoes in the region), followed by Moshi rural (456 ha, 25.6%), Same (120 ha, 5.1%), Mwanga (108 ha,4.1%) and Rombo district have very small planted The highest proportion of land with tomatoes was found in Hai followed by Moshi rural, Mwanga district, the remaining of the district had relatively low percentage of land used for tomato production (Chart 3.42). Chart 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 80.0 Hai Moshi rural Same Mwanga Rombo District Percent of Land 0.00 0.50 1.00 1.50 2.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Moshi Urban Moshi Rural Mwanga Same Rombo 0ha 1,937ha 0ha 0ha 3,612ha 743ha 0t/ha 0.8t/ha 0t/ha 0t/ha 0.5t/ha 0.6t/ha Hai 2,800 > 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Rombo Hai Moshi Urban Same Mwanga Moshi Rural 0.4ha 0.2ha 0ha 0ha 0ha 0.3ha Area Planted per Sunflower Growing Household by District MAP 3.19 KILIMANJARO MAP 3.20 KILIMANJARO Planted Area and Yield of Sunflower by District Tanzania Agriculture Sample Census 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 40 Moshi Urban Moshi Rural Rombo Mwanga Same 504ha 0ha 0ha 402ha 308ha 149ha 11.6t/ha 0t/ha 0t/ha 7t/ha 6.8t/ha 3.2t/ha Hai 400 > 300 to 400 200 to 300 100 to 200 0 to 100 Moshi Urban Moshi Rural Mwanga Same Hai 0ha 0ha 0.5ha 0.6ha 0.6ha 0.3ha Rombo Area Planted per Tomato Growing Household by District MAP 3.21 KILIMANJARO MAP 3.22 KILIMANJARO Planted Area and Yield of Tomatoes by District Tanzania Agriculture Sample Census 0.48 > 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 41 Hai Same Mwanga Moshi Urban Rombo Moshi Rural 0.3ha 0.5ha 0.4ha 0ha 0.5ha 0.5ha Moshi Urban Moshi Rural Mwanga Same Rombo Hai 0ha 25,512.8ha 3,588ha 3,935.5ha 15,527.9ha 7,898.5ha 0t/ha 9.3t/ha 5.9t/ha 3.4t/ha 1.7t/ha 0t/ha Area Planted per Banana Growing Household by District MAP 3.25 KILIMANJARO MAP 3.26 KILIMANJARO Planted Area and Yield of Banana by District Tanzania Agriculture Sample Census 20,000 to 26,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 42 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 43 The largest area planted per tomato growing household during short rainy season was found in Hai and Moshi districts (0.17) ha) followed by Mwanga (0.15 ha) and Same (0.13 ha) Chart 3.43) and Map 3.23). The total area planted with tomatoes accounted for 0.8 percent of the total area planted with annual crops and vegetables during the census year. 3.3.8.2 Cabbage The number of households growing cabbages in the region during the long rainy season was 2,645 and 808 in the short rainy season. This represented 2.5 percent of the total crop growing households in the region in the long rainy season and 1.2 percent in the short rainy season. Moshi rural district had the largest planted area of cabbage (250 ha, 59.8% of the total area planted with cabbage in the region), followed by Hai (63 ha, 15.1%), Mwanga (55 ha, 13.2%), Same (48 ha, 11.5%) and Rombo (2 ha, 0.5%). (Chart 3.44 and Map 3.24). The total area planted with cabbages accounted for 0.2 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Chillies The number of households growing chillies in the region during both the long and short rainy season was 867. This represented 0.8 percent of the total crop growing households in the region. Moshi rural district had the largest planted area of chilly (154 ha, 43.6% of the total area planted with cabbage in the region), followed by Hai (107 ha, 30.3%), Same (84 ha, 23.8%) and Mwanga (6 ha, 1.7%) and chillies were not reported in Rombo district. (Chart 3.45 and Map 3.24).Moshi rural and Same had largest proportion of the area planted with chillies (0.2) and Hai (0.1). (Chart 3.45), the total area planted with chillies 0.00 0.10 0.20 Area per Household (ha).. Hai Moshi rural Mwanga Same Rombo District Chart 3.43 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) Chart 3.45 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 Moshi rural Hai Same Mwanga Rombo District Percent of Land 0.0 0.1 0.2 0.3 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 75.0 Moshi rural Hai Mwanga Same Rombo District Percent of Land 0.00 0.20 0.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 44 accounted for 0.2 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 9,800 ha was planted with other annual crops and sunflower was the most prominent followed by groundnuts and simsim. The area planted with sunflower was 6293 ha which represented 62.3 percent of the total area planted with annual cash crops in short and long rainy season. 3.3.9.1 Sunflower Only 3,724 tonnes of sunflower were produced in Kilimanjaro Region on a planted area of 6,293 ha. Most of it was produced during the long rainy season. The crop only grown in Rombo and Moshi rural districts and Hai, Sunflower had a planted area of 843 ha, most of which was planted in the long rainy season. Sunflower production was concentrated in 3 districts with Rombo having the largest planted area (3,612 ha, 57.4% of total area planted with sunflower in the region), followed by Moshi rural (1,937 ha, 30.8%) and Hai (743. 11.8%). Same and Mwanga districts had no production of sunflower. (Chart 3.47 and Map 3.25). 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature they can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are Chart 3.46 Area planted with Annual Cash Crops Sunflower, 6,293, 64% Groundnuts, 3,413, 35% Simsim, 94, 1% Chart 3.47 Percent of Sunflower Planted Area and Percent of Total Land with Sunflower by District 0.0 40.0 80.0 Rombo Moshi rural Hai District Percent of Land 0.0 4.0 8.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 45 presented for the most important permanent crops in terms of planted area, production and yield. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 113,618 hectares (14% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it doubles counts the area planted more than once during the year, whilst the planted area for permanent crops is the same as physical land area. So the percentage of physical area planted with permanent crops may be higher than indicated in Chart 3.49. The most important permanent crop in Kilimanjaro region was banana which had a planted area of 56,038 ha, (54.7% of the planted area of all permanent crops) followed by coffee (35,633 ha, 34.8%), mango (8,045 ha, 7.8%). The remaining permanent crops collectively had a planted area of 2,801 ha (11.0%) (Chart 3.50 and Map 3.26 and 3.27).(Chart 3.49). Moshi rural district had the largest area under smallholder permanent crops (46,429 ha, 40.9%), this was followed by Rombo (31031 ha, 27.3%), Hai (18,428 ha, 16.2%), Same (13,184 ha, 11.6%) and Mwanga (4,547 ha, 4.0%), Same had the largest area per permanent crop growing household (0.5 ha) followed by Moshi rural and Rombo both had (0.4ha), Mwanga and Hai both had (0.3ha). (Chart 3.50). Chart 3.48 Area Planted for Annual and Permanent Crops Annual , 174,253, 60.4% Permanent , 113,618 39.6% Chart 3.49 Area Planted with the Main Perennial Crops mango, 8,045, 8% Sour soup, 30, 0% Pigeon Pea, 549, 1% Mango, 4,268, 7% Coffee, 35,633, 35% Sugarcane, 938, 1% Orange, 1,279, 1% Banana, 56,038, 54% Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 25.8 15.3 11.0 3.8 38.6 0.0 20.0 40.0 Moshi rural Rombo Hai Same Mwanga District % of Total A rea Planted 0.0 0.2 0.4 0.6 A verage Planted A rea per Household % of Total Area Planted Average Planted Area per Household RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 46 3.4.1 Coffee The total production of coffee by smallholders was 394,758 tonnes. In terms of area planted, coffee was the second important permanent crop grown by smallholders in the region. They were grown by 91,290 households (26.3% of the total crop growing households). The average area planted with coffee per household was relatively small at around 0.4 ha per coffee growing households Moshi rural had highest percentage in region region with (12,016 ha, 86%), followed by Rombo (10,165 ha, 69%), Hai (8,587 ha, 58%), There was small amount of coffee production in the remaining districts (Chart 3.52 and Map 3.28). 3.4.2 Oranges The total production of oranges by smallholders was 789 tonnes. In terms of area planted, orange was the seventh most important permanent crop grown by smallholders in the region. It was grown by 5,904 households (1.7% of the total crop growing households). The average area planted with oranges per household was relatively small at around 0.2 ha per orange growing household and the average yield obtained by smallholders was 1,284 kg/ha from a harvest area of 789 hectares. Moshi rural had the largest area of oranges in the region (804 ha, 56.3%) followed by Hai (170 ha, 11.9%), Rombo (158 ha, 11.1%), Same (150 ha, 10.5%) and Mwanga had no production. The average area planted with oranges per orange planting household was highest in Same (0.5 ha) (Chart 3.53 and Map 3.29). Chart 3.52 Percent of Area Planted with Coffee and Average Planted Area per Household by District 4.6 58.2 68.8 23.7 86.0 0.0 20.0 40.0 60.0 80.0 100.0 Moshi rural Rombo Hai Same Mwanga District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 11.9 10.5 56.3 11.1 0.0 20.0 40.0 60.0 Moshi rural Hai Rombo Same District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 47 3.4.3 Banana he total production of banana by smallholders was 327,080 tonnes. In terms of area planted, banana was the first most important permanent crop grown by smallholders in the region. It was grown by 145,279 households (41.9% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.4 per banana growing household and the average yield obtained by smallholders was 579 kg/ha from a harvested area of 56,463 hectares. Moshi rural had the largest planted area of bananas in the region (25,513 ha, 45.2%) followed by Rombo (15,528 ha, 27.5%), Hai (7,898 ha, 13.9%), Same (3,936 ha, 6.9%) and Mwanga (3,588 ha, 6.4%). However, the area planted with banana per banana growing household was highest in Rombo (0.6 ha), followed by Same and Moshi rural (0.5 ha), Mwanga (0.4 ha) and Hai (0.3 ha) (Chart 3.54 and Map 3.30). 3.4.4 Guava In terms of area planted, guava was the sixth most important permanent crop grown by smallholders in the region. It was grown by 3,812 households (1.1% of the total crop growing households). The average area planted with pigeon pea per household was relatively small at around 0.01 ha per pigeon pea growing household. Moshi rural had the largest planted area of guava in the region (545 ha, 66.9%) followed by Same (173 ha, 21.3%), Hai (91 ha, 11.2%), Mwanga (3.0 ha, 0.4%), and Rombo (1.0 ha, 0.1%). (Chart 3.55 and Map 3.31) Chart 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District 14.0 6.4 45.2 7.0 27.5 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Moshi rural Rombo Hai Same Mwanga District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.55 Percent of Area Planted with Guava and Average Planted Area per Household by District 11.22 0.12 66.95 0.37 21.33 0.00 20.00 40.00 60.00 80.00 Moshi rural Same Hai Mwanga Rombo District % of Total Area Planted 0.00 0.25 0.50 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 48 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing and clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method used for land clear Table 3.8: Land Clearing Methods 3.5.2 Methods of Soil Preparation Hand cultivation is the most used method for soil preparation and was used on an area of 115,798 ha which represented 67 percent of the total planted area, followed by tractor ploughing (38,937 ha, 23%) and toxen ploughing (16,565 ha, 10%). More hand cultivation was used during short rainy season at 90.02% against 32.7% for the long rainy season; oxen ploughing were more common in the long rainy season with 7.8% against 5.4% Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Area Planted % Mostly Hand Slashing 137,556 46,192 56 111,020 36,447 44 82,639 100.0 No Land clearing 118,720 32,371 52 122,997 29,933 48 62304 100.0 Mostly Bush clearance 12,422 5,200 89 20,027 649 11 5,849 100.0 Mostly tractor slashing 7,914 3,448 96 1,173 152 4 3,600 100.0 Mostly Burning 568 412 70 109 179 30 591 100.0 Total 277,180 87,623 57 255,326 67,360 43 154,983 100.0 Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 22,853 4,026 4,025 430 49,346 0 20,000 40,000 60,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Tractor Slashing Mostly Burning Method of Land Clearing Number of Households Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 16,565, 10% Mostly Hand Hoe Ploughing, 115,798, 67% Mostly Tractor Ploughing,38,937 23% Rombo Same Moshi Rural Moshi Urban 0.4ha 0.8ha 0.3ha 0ha 0.2ha 0.4ha Mwanga Hai Moshi Urban Rombo Same Hai Moshi Rural Mwanga 0ha 8,740.7ha 3,499.9ha 10,171.1ha 683.1ha 12,713.5ha 0t/ha 0.2t/ha 0.1t/ha 0.4t/ha 1t/ha 1.6t/ha Area Planted per Coffee Growing Household by District MAP 3.27 KILIMANJARO MAP 3.28 KILIMANJARO Planted Area and Yield of Coffee by District Tanzania Agriculture Sample Census 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 49 Moshi Urban Same Moshi Rural Mwanga Hai Rombo 0ha 0.5ha 0ha 0.5ha 0.1ha 0.3ha Same Moshi Rural Hai Moshi Urban Mwanga Rombo 1,389ha 15ha 4,319ha 352ha 0ha 1,969ha 4.9t/ha 12.8t/ha 4.7t/ha 6.9t/ha 0t/ha 3.1t/ha Area Planted per Mangoes Growing Household by District MAP 3.29 KILIMANJARO MAP 3.30 KILIMANJARO Planted Area and Yield of Mangoes by District Tanzania Agriculture Sample Census 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 50 Moshi Rural Hai Mwanga Moshi Urban Same Rombo 0.1ha 0.2ha 0.1ha 0ha 0.5ha 0.2ha 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Hai Rombo Moshi Urban Moshi Rural Mwanga Same 144ha 748ha 1,944ha 1,930ha 0ha 1,648ha 6t/ha 1.7t/ha 0.9t/ha 3.4v 0t/ha 3t/ha 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Area Planted per Avocado Growing Household by District MAP 3.31 KILIMANJARO MAP 3.32 KILIMANJARO Planted Area and Yield of Avocado by District Tanzania Agriculture Sample Census Area Planted(ha) per Household Planted Area (ha) Planted Area (ha) Area Planted(ha) per Household Yield (t/ha) RESULTS 51 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 52 in the long rainy season. Similarly tractor ploughing was used more during the long rainy season of 21.9% against 4.5% during the short rainy season. In Kilimanjaro region, Rombo district had the largest planted area cultivated by hand hoe ploughing (41,050 ha, 35.5%) followed by Same (32,618 ha, 28.2%), Moshi rural (15,608, 13.5%), Mwanga (11,872 ha, 10.3%) and Hai (11,872 ha, 10.3%), ( Chart 3.58) 3.3.3 Improved Seeds Use The planted area using improved seeds was estimated at 73,097 ha which represented 43 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the long rainy season was 59.3 percent, and higher than the corresponding percentage uses for the short rainy season at 54.4 percent Cereals had the largest area planted with improved seeds (62254 ha, 74% of the area planted with improved seeds) followed by pulses (15163 ha, 18%), fruits and vegetables (3223 ha, 4%), oil seeds & nuts (2,669 ha, 3%), roots & tubers (1164 ha, 1%) (Chart 3.60). 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 Area Cultivated Moshi rural Hai Rombo Same Mwanga District Chart 3.58 Area Cultivated by Method of Cultivation and District Tractor Ploughing Oxen ploughing Hand Ploughing Chart 3.59 Planted Area of Improved Seeds With Improved Seeds, 98,198, 57% Without Improved Seeds, 73,097, 43% Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 1164, 1% Pulses, 15163, 18% Oilseeds , 2669, 3% Fruits & Vegetables, 3223, 4% Cereals, 62254, 74% RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 53 However, the use of improved seed in fruits and vegetables is much greater than in other crop types (77.5%), followed by cereals (60.1%), pulses (32.3%), oil seeds & nuts (27.4%) and root & tubers (26.4%). (Chart 3.61). 3.5.4 Fertilizer Use The use of fertilisers on annual crops is moderate with a planted area of 114,912 ha (65.9 of the total planted area in the region). The planted area without fertilisers for annual crops was 59,341 hectares representing 34.1 percent of the total planted area with annual crops. Of the area planted with fertiliser application, farm yard manure was applied to 59,341 ha which represents 34 percent of the total planted area (65.9% of the area planted with fertiliser application in the region). This was followed by mostly Inorganic fertiliser (34,082 ha, 20%) and mostly compost 7,579 ha representing only 4 percent of the total planted area The highest percentage of the area planted with fertilizer (all types) was in Hai district (83.3%) followed by Moshi Rural (70.9%), Mwanga (67.3%), Same (64.7%) and Rombo (48.5%) (Table 3.9) Chart 3.62 Area of Fertiliser Application by Type of Fertiliser 4% 20% 42% 34% Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 0 50,000 A rea (h a) Hai Same Rombo Moshi Rural Mwanga District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Farm Yard Manure Mostly Inorganic Fertilizer Mostly Compost 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Fruits & Vegetables Cereals Pulses Oilseeds Roots & Tubers Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 54 Table 3.9 Number of Crop Growing Households and Planted Area by Fertilizer use and District during Long and Short Rainy Season Most annual crop growing households do not use any fertiliser (approximately 199,425 households, 71.4%). The percentage of the planted area with applied fertiliser was highest for cereals (64% of the area planted with no application of fertilizers during short rainy season). This was followed by pulses (24%), Roots & Tubers (5%), fruits and vegetables (4%), oil seeds (3%) and cash crops (0%). (Table 3.10). Table 3.10 Number of Crop Growing Households and Planted Area by Fertilizer use and District- LONG RAINY SEASON Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area Rombo 11,961 6,679 1,096 593 1,514 1,150 19,584 10,218 34,155 18,640 Mwanga 4,599 2,439 163 89 685 550 8,358 5,744 13,806 8,822 Same 3,901 3,194 4,199 3,565 1,404 802 12,265 7,849 21,769 15,410 Moshi R 12,666 8,163 855 288 20,485 10568 19,756 12,883 53,763 31,902 Hai 6,004 4,152 364 168 16,275 10,951 18,582 14,949 41,225 30,220 Total 39,131 24,626 6,679 4,703 40,363 24,021 78,545 51,644 164,718 104,994 Farm Yard Manure Use The total planted area applied with farm yard manure in Kilimanjaro region was 22,083 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 39,131 and it was applied to 22,083 ha representing 21.03 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (64%), followed by Pulses (24%), Roots & Tubers Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area No.of Households Planted Area Rombo 28,672 15,865 545 4,891 4,317 1,294 9,732 23,394 43,266 45,444 Mwanga 5,743 10,297 283 895 399 226 7,068 5,542 13,492 16,960 Same 10,459 16,057 2,195 2,621 2,180 5,378 10,943 13,136 25,777 37,192 Moshi R 10,099 14,073 477 12,812 5,795 453 4,173 11,226 20,544 38,564 Hai 4,614 16,960 73 12,864 3,840 227 4,399 6,043 12,926 36,093 Total 59,587 73,251 3,573 34,082 16,530 7,579 36,315 59,341 116,006 174,253 Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - KILIMANJARO Cash, 0, 0% Fruit& Vegetables, 989, 4% Oil Seeds, 574, 3% Root&Tubers, 1052, 5% Cereals, 14193, 64% Pulses, 5275, 24% RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 55 (5%), Fruits & Vegetables (4%), Oil seeds (3%), No Farm Yard Manure which was applied on Cash crops. (Chart 3.65a). Farm yard manure is mostly used in Moshi ru ral (19% of the total planted area in the district), followed by Mwanga (14%), Hai and Rombo had (12%) each and Same had (7%) (Chart 3.65b). Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Kilimanjaro region was 27,948 ha which represents 16.03 percent of the total planted area with annuals in the region and 50.5 percent of the total planted area with fertiliser. C ha rt 3 .6 5 b P ro po rtio n o f P la nte d A re a A pplie d with F a rm Ya rd M a nure by D is tric t - KIILIM A N J A R O 0.0 5.0 10.0 15.0 20.0 Moshi Rural Mwanga Hai Rombo Same District Percent 0 25 50 75 P ercen t o f Pla n ted A rea Cereals Pulses Root&Tubers Fruit& Vegetables Oil Seeds Cash Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - KILIMANJARO Pulses, 3,295, 12% Root&Tubers, 809, 3% Oil Seeds, 617, 2% Fruit& Vegetables, 616, 2% Cash crops, 0, 0% Cereals, 22,611, 81% 40 50 60 70 80 90 P e r c e n t o f P la n t e d A r e a Cereals Root&Tubers Pulses Oil Seeds Fruit& Vegetables Cash crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - KILIMANJARO Same Mwanga Hai Moshi Urban Moshi Rural Rombo 6,843ha 2,169ha 6,352ha 3,215ha 0ha 952ha 44% 25% 20% 11% 0% 5% Same Moshi Urban Moshi Rural Mwanga Rombo 14,336ha 2,241ha 0ha 3,759ha 5,335ha 14,303ha 51% 49% 0% 65% 40% 55% Hai Area Planted and Percent of Total Planted Area with Irrigation by District MAP 3.33 KILIMANJARO MAP 3.34 KILIMANJARO Planted Area and Percent of Planted Area with No Application of Fertilizer by District Tanzania Agriculture Sample Census Planted Area(ha) with Irrigation Applied Planted Area(ha) With no Fertilizer Applied Percent of Planted Area With no Fertilizer Applied Percent of Total Planted Area with Irrigation Applied 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Planted Area(ha) With no Fertilizer Applied Planted Area(ha) with Irrigation Applied RESULTS 56 RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 57 The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 77,437 and it was applied to 27,948 ha representing 26.6 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (81% of the total area applied with inorganic fertilizers), followed by pulses (12%), roots and tubers (3%), oil seeds and fruits & vegetables had (2%) each. No Inorganic fertilizers which was applied to Cash crops. (Chart 3.66) and (Chart 3.67a). Inorganic fertiliser is mostly used in Hai district (36.9% of the total planted area in the district), followed by Moshi rural (30.7%), Rombo (3%), Same (2.8%) and Mwanga (2.8%) (Chart 3.67b). Compost Use The total planted area applied with compost was 5,290 ha which represents only 3 percent of the total planted area with annual crops in the region and 9.6 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season were 11,181(Table 3.10 and Chart 3.68a). The proportion of area applied with compost was low for each type of crop; however the distribution of the total area using compost manure shows that 20 percent of this area was cultivated with cereals followed by pulses (26%), roots & tubers (4%), oil seeds (2%), and fruits & vegetables (1%). No compost manure which were applied to cash crops, (Chart 3.68b). C ha rt 3 .6 7 b P ro po rtio n o f P la nte d A re a A pplie d with Ino rg a nic F e rtilis e r by D is tric t - KILIM A N J A R O 15.0 19.0 23.0 27.0 31.0 35.0 Hai Moshi Rural Rombo Mwanga Same District Percent Chart 3.68a P lanted A rea with C ompo st by Cro p T ype - KILIM A NJAR O Cereals, 3488, 67% Fruit& Vegetables, 65, 1% Cash crops, 0, 0% Oil Seeds, 105, 2% Root&Tubers, 231, 4% Pulses, 1401, 26% RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 58 Compost is mostly used in Same district (9.7% of the total planted area in the district), followed by Moshi rural (1.9%), Rombo (1.5%), Mwanga (0.6%) and Hai (0.4%) (Chart 3.68c). 3.5.5 Pesticide Use Pesticid es are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 24,539 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (63% of the total area applied with pesticides). This was followed by herbicides (20%) and fungicides (17%) and (Chart 3.69). Insecticide Use The planted area applied with insecticides was estimated at 15,381 ha which represented 8.8 percent of the total planted area for annual crops and vegetables. 20 30 40 50 60 70 P e r c e n t o f P la n t e d A r e a Cereals Pulses Root&Tubers Oil Seeds Fruit& Vegetables Cash crops Crop Type Chart 3.68b P e rc e ntage o f P lante d Are a with Co mpo s t by Cro p Type - KILIMANJARO Chart 3.68c Proportion of Planted Area Applied with Compost by District - KILIMANJARO 0.0 2.0 4.0 6.0 8.0 10.0 Same Moshi Rur Rombo Mwanga Hai District Percent Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 4213, 17% Herbicides, 4945, 20% Insecticides, 15381, 63% RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 59 Cereal crops had the largest planted area applied with insecticides (9,022 ha, 59%) of the total planted area with insecticides) followed by pulses (3,600 ha, 23%), fruits & vegetables (1,326 ha, 9%), roots & tubers (1,132 ha, 7%) and oil seeds & oil (301 ha, 2%). No insecticides which were applied to cash crops. (Chart 3.70). However, the proportion of planted area applied with insecticides was largest for cereals( 59%), pulses (23%), fruits/vegetables (9%), roots & tubers (7%), Only 2 percent the area planted with oil seeds & tubers was applied with insecticides (Chart 3.71). Hai district had the highest percent of planted area with insecticides (12.9% of the total planted area with annual crops in the district). This was followed by Rombo (9.5%), Moshi rural (8.4%) and Same (6.0%). The smallest percentage use was recorded in Mwanga district (5.8%) (Chart 3.72) Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash Crops, 0, 0% Fruits&Veg, 1,326, 9% Cereasls, 9,022, 59% Oilseeds, 301, 2% Pulses, 3,600, 23% Root & Tubers, 1,132, 7% 2 22 42 62 P e r c e n t o f P la n te d A r e a Cereasls Pulses Fruits&Veg Root & Tubers Oilseeds Cash Crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - KILIMANJARO 0.0 4.0 8.0 12.0 16.0 Hai Rombo Moshi Rural Same Mwanga District Percent RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 60 Herbicide Use The planted area applied with herbicides was 3,623 ha which represented 2.8 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (3,623 ha, 73%) followed by roots & tubers (514 ha, 10%), pulses (400 ha, (8%), fruits & vegetables (333 ha, 7%) oil seeds (75 ha, 2%). No herbicides applied on cash crops (Chart 3.73). Hai district had the highest percent of planted area with herbicides (7.8% of the total planted area with annual crops in the dis0.31%). (Chart 3.75). Chart 3.73 Planted Area Applied with Herbicides by Crop Type roots&Tubers, 514, 10% Fruits&Veg, 333, 7% Cash crops, 0, 0% Cereals, 3,623, 73% Pulses, 400, 8% Oilseeds, 75, 2% 0 20 40 60 80 P e r c e n t o f P la n t e d A r e a Cerealsroots&Tubers Pulses Fruits&Veg. Oilseeds Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - KILIMANJARO 0.0 2.0 4.0 6.0 8.0 Hai Moshi Rural Mwanga Same Rombo District P e r c e n t RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 61 Fungicides Use The planted area applied with fungicides was 4,213 ha which represented 2.4 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with fungicides (1,248 ha, 30%) followed by roots & tubers (1,105 ha, 26%), fruits & vegetables (919 ha, 22%), pulses (821 ha, 19%), and oil seeds (120 ha, 3%), (Chart 3.76 ). However, the proportion of planted area applied with fungicides was greater in cereals, roots ant tubers and fruits & vegetables than in other crop types being (78%) for pulses (19%) and oilseeds (3%) chart 3.77). Hai district had the highest percent of planted area with fungicides (6.7% of the total planted area with annual crops in the district). This was followed by Moshi rural (2.5%), Mwanga (1.5%). The smallest percentages use were recorded in Same and Rombo districts with (0.7%) each (Chart 3.78). Chart 3.76 Planted Area Applied with Fungicides by Crop Type Oil seeds, 120, 3% Fruits & Veg., 919, 22% Cereals, 1,248, 30% Root & Tubers, 1,105, 26% Pulses, 821, 19% 0.0 10.0 20.0 30.0 Percent of Planted Area Cereals Root & Tubers Fruits & Veg. Pulses Oil seeds Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - KILIMANJARO 0.0 2.0 4.0 6.0 8.0 Hai Moshi Rural Mwanga Same Rombo District Percent RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 62 3.5.6 Harvesting Methods The main harvesting method for cereals and other crops was reported to be by hand. Very small amounts of crops were harvested by machine. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 53 percent of the total area planted with cereals during the long rainy season being threshed by hand. Bush clearing had (5%), tractor slashing (3%) and burning (1%). 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yield. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Kilimanjaro region, the area of annual crops under irrigation was 25,947 ha representing 15 percent of the total ar ea planted (Chart 3.79). The area under irrigation during the long rainy season was 15,190 ha accounting for 59 percent of the total area under irrigation. In the short rainy season, 10,758 ha or 3.6 percent of the total area planted with crops was irrigated. The district with the largest planted area under irrigation for annual crops was Same (11,255 ha, 43% of the total irrigated planted area with annual crops in the region). This was followed by Moshi rural with (7,029 ha, 27%), Hai (3,570 ha, 14%), Mwanga (3,014 ha, 12%) and Rombo (1,079 ha, 4%), When expressed as a percentage of the total area planted in each district, Same had the highest with 30% of the planted area in the district under irrigation. This was followed by Moshi rural and Mwanga districts with (18%) each and Rombo (2%) (Chart 3.80). Chart 3.79 Area of Irrigated Land Non-Irrigated Land, 148,306, 85% Irrigated Land, 25,947, 15% Chart 3.80: Planted Area with Irrigation by District 0 3,000 6,000 9,000 12,000 Same Moshi ® Hai Mwanga Rombo District Ir r ig a t e d A r e a ( h a ) 0 5 10 15 20 25 30 35 P e r c e n t a g e w it h Ir r ig a t io n Irrigated Land (ha) Percentage of Irrigated Land RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 63 The agricultural households practicing irrigation in Kilimanjaro region appears to have decreased by 38 percent over the 7 year period from 56,836 households in 1995/96 to to 35,410 households in 2002/03. (Chart 3.81) 3.6 .2 Sources of Water Used for Irrigation The main source of water used for irrigation was from canals (27,208 households, 56% of households with irrigation). This was followed by rivers (18,029 households, 37%), dams (1,323 households, 3%), pipe water (1,024 households, 2%), well (959 households 2%), lake (125 households, 0.3%) and borehole (43 households, 0.1% ). (Chart 3.82) 3.6.3 Methods of Obtaining Water for Irrigation The hand gravity was the most common method of getting water for irrigation with 93.5 percent of households using this method. This was followed by hand bucket with 6.1 percent of households. The remaining methods (hand pump, motor pump and others) had 0.1%) each (Chart 3.83). Hand bucket was used most in Moshi rural district by (96.8% of the households practicing irrigation) followed by Mwanga (96.5%), Moshi rural (93.6%) and Hai (88.6%). Hand bucket was more common in Moshi rural district with 11 percent of households using the method to get water for irrigation, followed by Mwanga (5%), Hai and Same districts both had (3%) each. Chart 3.81 Time Series of Households with Irrigation - KILIMANJARO 35,410 56,836 0 10,000 20,000 30,000 40,000 50,000 60,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Chart 3.82 Number of Households with Irrigation by Source of Water Canal, 27208, 56% River, 18029, 37% Dam, 1323, 3% Borehole, 43, 0% Pipe w ater, 1024, 2% Lake, 125, 0% Well, 959, 2% Canal River Dam Pipe w ater Well Lake Borehole Chart 3.84 Number of Households with Irrigation by Method of Field Application Flood, 45,160, 92% Sprinkler, 249, 1% Water Hose, 492, 1% Bucket / Watering Can, 2,809, 6% Flood Bucket / Watering Can Water Hose Sprinkler RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 64 3.6.4 Method s of Water Application Most of agricultural households (55.2% of households using irrigation) used flood as a method of field application. This was far followed by watering cans (6%), both water horse and sprinklers had (1%) each. Chart 3.84 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seeds for planting in the following season. The results for Kilimanjaro region show that there were 142,851 crop growing households (90% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 131,869 households storing 39,418 tonnes as of 1st January 2004. This was followed by beans and pulses (84,190 households, 5,366t), paddy (15,765 households, 1,222t), sorghum and millets (7,920 households, 403t), groundnuts and bambaranuts (3,981 household, 123t) and coffee (1,487 household, 63t). Other crops were stored in very small amounts. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Motor Pump, 67, 0% Hand Pump, 71, 0% Gravity, 45,546, 94% Other, 38, 0% Hand Bucket, 2,988, 6% Gravity Hand Bucket Hand Pump Motor Pump Other Chart 3.84 Number of Households and Quantity Stored by Crop Type - Kilimanjaro 0 35,000 70,000 105,000 140,000 Maize Beans & Pulses Paddy Sorghum & Millet G'nuts/Bambara Nuts Coffee Crop N u m b er o f h o u s eh o ld s 0 8,000 16,000 24,000 32,000 40,000 Q u a n tity (t) Number of households Quantity stored (Tons) RESULTS – Crop Storage, Processing and Marketing ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 65 3.7.1.1 Methods of Storage The region had 68,908 crop growing households storing their produce in airtight drum (48.2% of households that stored crops in the region). The number of households that stored their produce in locally made traditional crib was 12,408 (8.7%). This was followed by improved locally made structures (6,806 households, 4.8%), other types of storage (713 households, 0.5%) and unprotected pile 291 households, 0.2%). Airtight drums were the dominant storage methods in the region, with the highest percent of households in Moshi Rural using this method (54% of the total number of households storing crop products). This is followed by Hai (35%), Rombo (5%) and Mwanga (3%) and Same (3%) (Chart 3.86) The highest percent of households using sacks and open drum was in Rombo and Hai districts (41.5% and 16.6% of the total number of households storing crops respectively), followed by Moshi Rural (16.2%), Same (15.9%) and Mwanga (9.8%). 3.7.1.2 Duration of Storage Most households (47% of the households storing crops) stored their produce for a period of over 6 months followed by those that stored for a period of between 3 and 6 months (42%). The minority of households stored their crop for a period of less than 3 months (11%). Most households that stored pulses stored for a period of between 3 to 6 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.87). The proportion of households that stored their produce for the duration over 6 months was highest in Hai (94.6%) followed by Moshi Rural (75.1%), Same (74.9%), Rombo (56.3%) and Mwanga (22.8%) (Map3.) Chart 3.85 Number of households by Storage Methods - Kilimanjaro In Locally Made Traditional Structure, 12,408, 8.7% In Sacks / Open Drum, 53,088, 37.2% In Improved Locally Made Structure, 6,806, 4.8% In Airtight Drum, 68,908, 48.2% Unprotected Pile, 291, 0.2% Other, 713, 0.5% Chart 3.86 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Rombo Mwanga Same Moshi Rural Hai District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 18,000 36,000 54,000 72,000 Number of households Maize Sorghum & Millet Beans & Pulses Crop Chart 3.87 Normal Length of Storage for Selected Crops Less than 3 Months Between 3 and 6 Months Over 6 Months RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 66 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.88). However, households in Rombo district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, beans and pulses, sorghum and millet, paddy and groundnuts and sorghum) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 97.7 percent followed by to sell for higher price (Chart 3.89). 3.7.1.4 The Magnitude of Storage Loss About 92.2 percent of households that stored crops had little or no loss, followed by household with up to a quarter loss (1.3%), between a quarter and a half (1.3%) and over a half loss (0.2%) (Table 3.11) The proportion of households that reported a loss of more than a quarter was greatest for maize (2.1% of the total number of households that stored crops) and beans and pulses (0.9%). Most households storing coffee had no storage loss (100%) Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Rombo 64,057 3,237 923 231 68,449 Mwang a 12,711 1,626 130 43 14,510 Same 23,301 4,249 429 73 28,053 Moshi Rural 67,887 2,407 389 0 70,684 Hai 49,028 3,392 1,073 231 53,724 Total 216,98 5 14,911 2,945 579 235,41 9 Chart 3.88 Quantity of Maize Produced (tonnes), Stored (tonnes)and Percent Stored by District 0 8,000 16,000 24,000 32,000 40,000 Rombo Mwanga Same Moshi Rural Hai District Quantity (tonnes) 0 20 40 60 % Stored Quantity harvested Quantity stored % stored 0% 25% 50% 75% 100% Percent of Ho useho ld s Maize Beans & Pulses Sorghum & Millets Paddy Groundnuts & Sorghum Crop Type Chart 3.89 Percent of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 67 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Kilimanjaro region (171,910 households, 80% of the total crop growing households) (Chart 3.90). The percentage of households processing crops was highest in Moshi Rural district (35%) followed by Rombo (26%), Hai (16%), Same (15%) and Mwanga (8%). (Chart 3.91) 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 79 percent (136,503 households). This was followed by those processing on-farm by hand (17,198 households, 10%), trader (11,307 households, 7%), on-farm by machine (5,236 households, 3%) and by cooperative union (445 households, 1%). The remaining methods of processing were used by very few households. Although processing by neighbours machine was the most common processing method in all districts in Kilimanjaro region, however district differences existed. Moshi Rural has a higher percent of hand processing than other districts (32%), followed by Rombo (24%), Hai (18%), Same (16%) and Mwanga (10%). Processing by trader was more common in Rombo and Moshi rural (57% and 38% respectively), whilst processing on farm by machine was more prevalent in Moshi Rural, Rombo and Same (Chart 3.92). Chart 3.90 Households Processing Crops Households not Processing, 44,263, 20% Households Processing, 171,910, 80% 0 10 20 30 40 Percent of Households Processing Moshi Rural Rombo Hai Same Mwanga District Chart 3.91 Percentage of Households Processing Crops by District Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Rombo Mwanga Same Moshi Rural Hai District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Co-operative Union By Trader Other By Factory Other Hai Moshi Urban Moshi Rural Mwanga Same Rombo 32,344 41,831 0 64,370 10,443 18,721 70% 89% 0% 84% 62% 64% Rombo Moshi Urban Moshi Rural Same Mwanga 9,789 17,617 0 7,367 6,718 14,893 Hai Number of Households and Percent of Total Households Selling Crops by District MAP 3.35 KILIMANJARO MAP 3.36 KILIMANJARO Percent of Households Storing Crops for 3 to 6 Months by district Tanzania Agriculture Sample Census Number Households Selling Crops Percent of Households Storing Crops Percent of Households Storing Crops Percent of Total Households Selling Crops 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 52,000 to 65,000 39,000 to 52,000 26,000 to 39,000 13,000 to 26,000 0 to 13,000 Number Households Selling Crops RESULTS 68 RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 69 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 150,479 households processing crops into flour (87.5%) followed by grain with 18,016 households (10.5%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 40.4 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 38,244 households (56%) followed by cake (18,186 households, 26%), pulp (7,435 households, 11%) and shell (2,203 households, 3%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for selling, for cooking and for animal consumption. The most important use was for household/human consumption which represented 92.3 percent of the total households that used primary processed product (Chart 3.95). Moshi Rural, Rombo and Mwanga districts were the districts using primary products as fuel for cooking. Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal, 87.5, 88% Oil, 1.8, 2% Juice, 0.2, 0% Grain, 10.5, 10% Chart 3.95 Use of Processed Product Other, 309, 0.2% Household / Human Consumption, 158,700, 92.3% Fuel for Cooking, 294, 0.2% Sale Only, 11,332, 6.6% Animal Consumption, 783, 0.5% Did Not Use, 492, 0.3% Chart 3.94 Number of Households by Type of Bi-product Husk, 2,670, 4% Juice, 317, 0% Pulp, 7,435, 11% Oil, 236, 0% Cake, 18,186, 26% Shell, 2,203, 3% Other, 138, 0% Bran, 38,244, 56% RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 70 Out of 50,115 households that sold processed products, 20,655 were from Rombo district (41% of the total number of households selling processed products in the region), followed by Moshi Rural district with 18,486 households (37%), Same district with 4,933 households (10%), Hai district with 4,087 households (8%) and Mwanga district with 1,954 households (4%). In Kilimanjaro region, all districts sold processed products (Chart 3.96) 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to marketing cooperatives (6,025 households, 39% of households that sold crops). This was followed by selling to farmers associations (4,762 households, 30.9%), neighbours (2,077 households, 13.5%), local market (1,507 households, 9.8%), large scale (412 households, 2.7%), trader at farm (317 households, 2.4%) and other unspecified places (277 households, 1.8%) (Chart 3.97). There are large differences between districts in the proportion of households selling processed products to marketing cooperative with Moshi Rural district having the largest percent of households in the district selling to marketing cooperatives (48%), whereas Rombo had only 35 percent. Hai district had a higher percent of households relying on farmers association than other outlets. Compared to other districts, Same had the highest percent of households selling processed products to local market/trade store. 3.7.3 Crop Marketing The number of households that reported selling crops was 167,709 which represent 77.6 percent of the Chart 3.97 Location of Sale of Processed Products Neighbours, 2,077, 13.5% Local Market / Trade Store, 1,507, 9.8% Marketing Co- operative, 6,025, 39.0% Other, 277, 1.8% Trader at Farm, 371, 2.4% Large Scale Farm, 412, 2.7% Farmers Association, 4,762, 30.9% Chart 3.98 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Rombo Mw anga Same Moshi Rural Hai District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 15,000 30,000 45,000 60,000 75,000 Moshi Rural Rombo Hai Same Mwanga District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops 0.00 25.00 50.00 Percentage of households Rombo Moshi Rural Same Hai Mwanga District Chart 3.96 Percentage of Households Selling Processed Crops by District RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 71 total number of crop growing households. The percent of crop growing households selling crops was highest in Rombo (89%) followed by Moshi Rural (84%), Hai (70%), same (64%) and Mwanga (62%) (Chart 3.99 and Map 3.32). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (27% of crop growing households). Apart from low market prices, other problems were transport cost too high (6%), longer distances to the markets (3%) and lack of transport (2%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 85.5 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Kilimanjaro region very few agricultural households (3,643, 2.3%) accessed credit out of the total number of agricultural households, out of those that received credit 2,967 (81%) were male-headed households and 677 (19%) were female headed households. In Mwanga district only female headed households got agricultural credit whereas in Hai district a large number of male households accessed credit. In Rombo districts both male and female headed households had equal access to agricultural credit (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Kilimanjaro region were family, friends and relatives (46%), Religious Organizations/Non Governmental Organizations/ projects (38%), saving and credit society (8%), trader/trade store (3%), commercial bank (3%) and cooperatives (2% of the total number of households that accessed credit) (Chart 3.101). Commercial banks and trader/trade store were the sole source of credit in Hai district and cooperatives were found in Same district only. (Chart 3.102). Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Price Too Low 5.8% Other 7.0% Farmers Association Problems 0.1% Trade Union Problems 0.6% Production Insufficient to Sell 85.5% Market Too Far 0.7% Co-operative Problems 0.3% Government Regulatory Board Problems 0.0% Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Religio us Organis atio n / NGO / P ro ject 38.0% Co mmercial Bank 3.0% Trader/Trade s to re 3.0% Family, Friend and Relative 46.0% Saving & Credit So ciety 8.0% Co -o perative 2.0% RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 72 3.8.1.2 Use of Agricultural Credit The agricultural credit provided to agricultural households in the region was used as follows seeds (31%), fertilizers (26%), agrochemicals (15%), labour (12%), other unspecified activities (8%), livestock (6%) and tools and equipment (2%) (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 55 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by “not wanting to go into debt” (17%), households reporting the credit not needed (11%), households reporting un-availability of credit (7%) and households reporting interest rate too high (6%). The rest of the reasons were collectively 4% percent of the households. Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Rombo 115 50 114 50 228 Mwanga 0 0 76 100 76 Same 572 89 68 11 641 Moshi Rural 135 43 180 57 315 Hai 2,145 90 238 10 2,383 Total 2,967 81 677 19 3,643 Table 3.12 Reasons for Not Selling Crop Produce Main Reason Househo ld Number % Production Insufficient to Sell 73,877 85.5 Other 6,025 7.0 Price Too Low 5,028 5.8 Trade Union Problems 484 0.6 Co-operative Problems 293 0.3 Market Too Far 629 0.7 Total 86,336 100.0 Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Rombo Mw anga Same Moshi Rural Hai District Percent of Households Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Chart 3.104 Reasons for not Using Credit (% of Households) Not needed 11% Not available 7% Did not want to go into debt 17% Interest rate/cost too high 6% Did not know how to get credit 36% Difficult bureaucracy procedure 3% Other 0% Don't know about credit 19% Credit granted too late 1% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Agro- chemicals 15% Tools / Equipment 2% Livestock 6% Fertilizers 26% Seeds 31% Labour 12% Other 8% RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 73 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 135,826 (63% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Moshi Rural district having a relatively high proportion of households (73%) that received crop extension messages followed by Rombo (59%), Hai (58%), Same (53%) and Mwanga (54%). (Chart 3.106 and Map 4.33) 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (97.3%). NGO/Development project 1.9 percent, large scale farm provided 0.4 percent, cooperatives 0.4% and other providers 0.1 percent (Chart 3.107). 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 56 percent of the households receiving extension ranked the service as being good followed by average (21 %), very good (19%), poor (4%) and none of the households ranked the quality of extension services as no good. (Chart 3.108) However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 80,346, 37% Households Receiving Extension , 135,826, 63% Chart 3.106 Number of Households Receiving Extension by District 0 15,000 30,000 45,000 60,000 Moshi Rural Rombo Hai Same Mwanga District Number of Households 0 15 30 45 60 75 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 0.4% Cooperative 0.4% NGO / Developmen t Project 1.9% Other 0.1% Government 97.3% Chart 3.108 Number of Households Receiving Extension by Quality of Services Average 21% Poor 4% No Good 0% Very Good 19% Good 56% RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 74 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs particularly the inputs that are not produced on the farm such as improved seeds, fungicides, inorganic fertiliser and herbicides. In Kilimanjaro region farm yard manure was used by 159,780 households which represent 74 percent of the total number of crop growing households. This is followed by households using improved seeds (50%), inorganic fertiliser (34%), fungicide (31%), compost (7%) and herbicide (3%) (Table 2.14). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Kilimanjaro mostly purchase from local market/trade store (91.6% of the total number of inorganic fertiliser users) followed by cooperative (4.8%), local farmers group (0.9 %) and the rest sum up to (2.9%) (Chart 3.109). Table 3.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 159,780 74 56,393 26 Improved Seeds 108,843 50 107,456 50 Pestcides/Fungicide 65,983 31 150,189 69 Compost 15,912 7 200,399 93 Inorganic Fertiliser 74,551 34 141,622 66 Herbicide 7,516 3 208,657 97 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 2.7 0.9 4.8 91.6 0 20000 40000 60000 80000 Local Market / Trade Store Co-operative Local Farmers Group The Rest Source of Inorganic Fertiliser Number of Households Moshi Urban Same Mwanga Moshi Rural Rombo Hai 0 21,769 13,806 53,763 34,155 41,225 0% 61% 62% 87% 76% 55% Moshi Urban Same Mwanga Moshi Rural Rombo Hai 0 15,555 9,094 56,317 27,900 26,960 0% 53% 54% 73% 59% 58% Number and Percent of Crop Growing Households using Improved Seed by District MAP 3.37 KILIMANJARO MAP 3.38 KILIMANJARO Number of Households and Percent of Total Households Receiving Crop Extension Services by District Tanzania Agriculture Sample Census Number of Households Growing Crop Using Improved Seed 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Number of Households Growing Crop Using Improved Seed Percent of Total Households Receiving Crop Extension Services Percent of Households Growing Crop Using Improved Seed RESULTS 75 RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 76 Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing between 1 and 3 km (30 %) followed by less than 1 km from the source (27%) and between 1 and 3 km (24%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available”(3%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 76 percent of households responding to cost factors as the main reason for not using inorganic fertilizers. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. More smallholders use inorganic fertilisers in Moshi Rural than in other districts in Kilimanjaro region (46% of households using inorganic fertilisers), followed by Hai (37%), Rombo (9%), Same (7%) and Mwanga (2%). 3.9.3 Improved Seeds The proportion of households that used improved seeds was 50 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (85.6%). Other less important sources of improved seed are from cooperative (6.5%), local farmers group (2.0%), neighbour (1.4%), locally produced by household (1.2%), development project (1.0%) and the remaining sum up to (2.3%). (Chart 3.111). Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111 Number of Households by Source of Improved Seed 0.6 0.4 0.7 0.6 1.0 1.2 1.4 2.0 6.5 85.6 0 25000 50000 75000 100000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Locally Produced by Household Development Project Large Scale Farm Crop Buyers Secondary Market Other Source of Improved Seed Number of Households RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 77 Access to improved seed is better than access to chemical inputs with 27 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The district that used improved seeds are Moshi Rural (32 percent of the total number of households used improved seeds), followed by Rombo (26%), Hai (26%), Same (10%) and Mwanga (6). (Map 3.34). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (75.7% of the total number of fungicide users). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of H ouseholds Chart 3.113 Number of Households by Source of Insecticide/fungicide 75.7 18.5 2.9 1.4 0.8 0.4 0.2 0.2 0 15000 30000 45000 60000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Secondary Market Crop Buyers Development Project Other Source of Insecticide/fungicide Number of Households RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 78 Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 4 percent of households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 73 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Rombo district (61 percent of the total number of households used fungicides), followed by Hai (35%), Same (26%), Mwanga (19%) and Moshi Rural (14%). 3.10 Tree Planting The number of households involved in tree farming was 132,827 representing 61 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 45,827 trees. The average number of trees planted per household planting trees was 35 trees. The main species planted by smallholders is Gravellis (18,252 trees, 40%), followed by Eucalyptus spp (15,505 trees, 34%), senna spp (4,080 trees, 4%), Albizia species (1,837 trees, 4%) and Cyprus (1,632 trees, 2%). The remaining trees species are planted Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.115 Number of Households with Planted Trees Not growing trees, 83,345, 39% hh growing trees, 132,827, 61% Chart 2.116 Number of Planted Trees by Species - KIlimanjaro 0 5,000 10,000 15,000 20,000 Gravellis Eucalyptus Spp Senna Spp Albizia Spp Cyprus Spp Casurina Equisetfilia Acacia Spp Tectona Grandis Azadritachta Spp Afzelia Quanzensis Maesopsis Berchemoides Pinus Spp Tree Species Number of Trees RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 79 in comparatively small numbers (Chart116.). Mwanga district has the largest number of smallholders with planted trees than any other district (53%) which is dominated by Gravellis species. This is followed by Moshi Rural (15%) dominated by Gravellis species and to a lesser extent Senna, then Rombo (14%), Hai (9%) and Same (8%) which are mainly planted with Gravellis and Senna species respectively (Chart 3.117 and Map 3.35.). Smallholders mostly plant trees on the boundary of fields. The proportion of trees planted on field boundaries is 38 percent, followed by plantation or coppice (35%) and scattered around fields (27%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (45.5%). This is followed by shade (28.7%), wood for fuel (17.8%), poles (5.6%), medicinal (1.4%), charcoal (0.1%) and other uses (0.8%) (Chart 3.119). Chart 3.117 Number of Trees Planted by Smallholders by Species and District 1,000 6,000 11,000 16,000 21,000 Rombo Mw anga Same Moshi Rural Hai Region Number of Trees Gravellis Eucalyptus Spp Senna Spp Albizia Spp Cyprus Spp Chart 3.118 Number of Trees Planted by Location Field boundary, 17,497, 38% Scattered in field, 12,164, 27% Plantation, 16,155, 35% Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Shade Fuel for Wood Poles Medicinal Other Charcoal Percent of Households Moshi Urban Moshi Rural Mwanga Same Rombo 0 11,977 6,589 29,591 18,974 461 0 14.2% 7.4% 9.2% 17.3% 1% Hai 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Moshi Urban Moshi Rural Mwanga Same Rombo Hai 0 334 217 182 310 262 0% 0.4% 0.6% 1.3% 0.7% 0.6% 280 to 350 210 to 280 140 to 210 70 to 140 0 to 70 Number and Percent of Households with Water Harvesting Bunds by District MAP 3.39 KILIMANJARO MAP 3.40 KILIMANJARO Number and Percent of Smallholder Panted Trees by District Tanzania Agriculture Sample Census Number of Households with Water Harvesting Bunds Number of Smallholder Planted Tree Number of Smallholder Planted Tree Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Percent of Households with Water Harvesting Bunds RESULTS 80 RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 81 3.10 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 48,710 which represent 23 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Moshi Rural district (36%) followed by Hai (31%), Same (25%), Mwanga (8%) and Rombo had none. (Chart 3.121). Erosion control bunds accounted for 39 percent of the total number of structures, followed by terraces (35%), water harvesting bunds, vetiver grass (6%) (10%), tree belts (5%) and drainage ditches (4%) (Chart 3.122 and Map 3.36). Erosion control bunds, terraces and water harvesting bunds together had 550,578 structures. This represented 85 percent of the total structures in the region. The remaining 15 percentages were shared among the rest of the erosion control methods mentioned above. Same and Rombo districts had 430,472 erosion control structures (66 percent of the total erosion structures in the region). Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households w ith facilities, 48,710, 23% Households Without Facilities, 167,462, 77% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 36 25 8 0 31 0 3,000 6,000 9,000 12,000 15,000 18,000 Moshi Rural Hai Same Mwanga Rombo District Number of Households 0 8 16 24 32 40 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0 0 4 5 6 10 35 39 0 50000 100000 150000 200000 250000 300000 Erosion Control Bunds Terraces Water Harvesting Bunds Vetiver Grass Tree Belts Drainage Ditches Gabions / Sandbag Dam T y p e o f F a c ility Number of Structures RESULTS – Tree Planting and Erosion Control ____________________________________________________________________________________ ______ ____________________________________________________________________________________________________________________ ________ Tanzania Agriculture Sample Census 82 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 494,555. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 3 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Kilimanjaro region was 351,191 (71 % of the total number of cattle in the 5,454 cattle (1%) were beef breeds. The census results show that 128,484 agricultural households in the region (81% of total agricultural households) kept 0.49 million cattle. This was equivalent to an average of 4 heads of cattle per cattle- keeping-household. The district with the largest number of cattle was Hai which had about 187,930 cattle (38% of the total cattle in the region). This was followed by Moshi Rural (131,013 cattle, 26%), Same (79,761 cattle, 16%), Mwanga (51,971 cattle, 11%) and Rombo (43,880 cattle, 6%) (Chart 3.123 and Map 3.37) However, Moshi Rural district had the highest density (234 head per km2) (Map 3.38). Although Hai district had the largest number of cattle in the region, most of then were indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant (Chart 3.124). 0 50000 100000 150000 200000 Number of Cattle ('000') Hai Moshi Rural Same Mwanga Rombo Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 84674 143670 235 428 147 3784 860 29651 15602 6703 42556 43399 13995 35941 72911 0 50000 100000 150000 200000 Rombo Mwanga Same Moshi Rural Hai Districts Number of Cattle Indigenous Improved Beef Improved Dairy EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 83 3.12.1.2 Herd Size Ninty one percent of the cattle-rearing households had herds of size 1-5 cattle with an average of two cattle per household. Herd sizes of 6-30 accounted for about 8 percent of all cattle in the region. Only 0.5 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 91 percent of total cattle rearing households had herds of size 1-30 cattle and owned 74 percent of total cattle in the region, resulting in an average of 3 cattle per cattle rearing household. There were about 101 households with a herd size of more than 151 cattle each (81,616 cattle in total) resulting in an average of 807 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Kilimanjaro region increased during the period of eight years from 464,126 in 1995 to 494,555 cattle in 2003. This trend depicts an overall annual negative growth rate of 0.80 percent (Chart 3.125). There was an increase in number of cattle for the period of four years from 1995 to 1999 at the rate of 5.21 percent whereby the number increased from 464,126 to 568,689. The number of cattle then decreased from 568,689 in 1999 to 494,555 in 2003 at the rate of -3.43 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Kilimanjaro region was 143,364 (137,910 dairy and 5,454 improved beef). The diary cattle constituted 28 percent of the total cattle and 96 percent of improved cattle in the region. The number of beef cattle in the region constituted 1 percent of the improved cattle in the region. The number of improved cattle decreased from 154,403 in 1995 to 143,364 in 2003 at an annual growth rate of -0.92 percent. The growth rate was higher for the period from 1995 to 1999 (9.56%) then there was a sharp decrease from 1999 to 2003 (-10.41%) (Chart 126) 464,126 568,689 494,555 - 150,000 300,000 450,000 600,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 154,403 222,497 143,364 - 50,000 100,000 150,000 200,000 250,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 84 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Kilimanjaro region ranked 10th out of the 21 regions with 5 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Kilimanjaro region was 103,017 (65% of all agricultural households in the region) with a total of 572,577 goats giving an average of 6 head of goats per goat-rearing-household. Rombo had the largest number of goats (198,082 goats, 35% of all goats in the region), followed by Moshi Rural (168,107 goats, 29%), Hai (103,077 goats, 18%) , same (55,561 goats, 10%) and Mwanga (47,751 goats, 8%). (Chart 3.127 and Map 3.39). However Rombo district had the highest density (453 head per km2) (Map 3.40). 3.12.2.2 Goat Herd Size Sixty percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Ninety six percent of total goat-rearing households had herd size of 1-14 goats and owned 73 percent of the total goats in the region resulting in an average of 4 goats per goat-rearing households. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 92 percent of the total goats in Kilimanjaro region. Improved goats for beef and diary constituted of 3 and 5 percent of total goats respectively. 0 50000 100000 150000 200000 Number of Goats ('000'). Rombo Moshi Rural Hai Same Mwanga District Chart 3.127 Total Number of Goats ('000') by District EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 85 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was -4.99 percent. This negative trend implies eight years of population decrease from 862,627 in 1995 to 572,577 in 2003. The number of goats decreased from 862,627 in 1995 at an estimated annual rate of -9.49 percent to 578,891 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -0.27 percent (Chart 128). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Kilimanjaro region after cattle and goats. The region ranked 5 out of 21 Mainland regions and had 7 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 63,696 (40% of all agricultural households in Kilimanjaro region) rearing 257,260 sheep, giving an average of 4 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Rombo with 70,905 sheep (28% of total sheep in Kilimanjaro region) followed by Hai (67,494 sheep, 26%), Moshi Rural (57,156 sheep, 22%), Same (42,457 sheep, 17%) and Mwanga (19,248 sheep, 7%) and Map 3.41). Rombo district also had the highest density (162 head per km2 ) (Map 3.42). Sheep rearing was dominated by indigenous breeds that constituted 96 percent of all sheep kept in the region. Only 4 percent of the total sheep in the region was made up of improved mutton. 862,627 578,891 572,577 - 250,000 500,000 750,000 1,000,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 20000 40000 60000 80000 Number of sheep Rombo Hai Moshi Rural Same Mwanga District Chart 3.129 Total Number of Sheep by District Rombo Moshi Rural Moshi Urban Same Mwanga 100 174 235 0 32 83 Hai Mwanga Moshi Rural Hai Rombo Moshi Urban Same 51,971 131,013 187,930 43,880 0 79,761 Cattle Density by District as of 1st October 2003 by District MAP 3.41 KILIMANJARO MAP 3.42 KILIMANJARO Cattle population by District as of 1st Octobers 2003 by District Tanzania Agriculture Sample Census Number of cattle 160,000 > 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Number of cattle Per Square Km 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 Number of Cattle Cattle Density RESULTS 86 Moshi Rural Hai Mwanga Moshi Urban Same 301 95 76 0 453 22 Rombo Moshi Rural Mwanga Same Moshi Urban Hai 168,107 47,751 55,561 0 103,077 198,082 Rombo Goat Density by District as of 1st October 2003 by District MAP 3.43 KILIMANJARO MAP 3.44 KILIMANJARO Goat population by District as of 1st Octobers 2003 by District Tanzania Agriculture Sample Census Number of Goats Number of Goats Per Square Km 160,000 to 200,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Number of Goats Goats Density RESULTS 87 EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 88 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at -2.96 percent. The population decreased at an annual rate of -5.11 percent from 327,788 in 1995 to 265,746 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -2.96 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 3rd out of 21 Mainland regions and is 14 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Kilimanjaro region was 32,844 (21% of the total agricultural households in the region) rearing 116,877 pigs. This gives an average of 4 pigs per pig-rearing household. The district with the largest number of pigs was Moshi Rural with 65,761 pigs (56% of the total pig population in the region) followed by Rombo (23,872 pigs, 20%), Hai (21,796 pigs, 19%), Same (5,317 pigs, 5%) and Mwanga (131 pig, 0.1%) (Chart 3.131 and Map 3.44). However Moshi Rural district had the highest density (118 head per km2 ) (Map 3.43). 3.12.4.1 Pig Population Trend There was no pig population recorded in 1995. The record available was from 1999. The pig population increased from 51,372 in 1999 to 155,070 in 2003 at a high rate of 31.8 percent. (Chart 3.132). 327,788 265,746 257,260 - 100,000 200,000 300,000 400,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 0 15,000 30,000 45,000 60,000 75,000 Number of Pigs Moshi Rural Rombo Hai Same Mwanga District Chart 3.131 Total Number of Pigs by District - 51,372 155,260 - 40,000 80,000 120,000 160,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 89 3.12.5 Chicken Production The poultry sector in Kilimanjaro region was dominated by chicken production. The region contributed 5.0 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 155,587 raising about 1,561,340 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Kilimanjaro region was ranked tenth out of the 21 Mainland regions. The District with largest number of improved chickens was moshi Rural (160,481 chickens, 78% of the total number of improved chickens in the region) followed by Hai (31,078, 15.2%), Same (8,731, 4.3%), Mwanga (3,800, 1.9%) and Rombo (469, 0.2%) (Chart 3.133 and Map 3.45) However Hai district had the highest density (136 improved chickens per km2) (Map 3.46) 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 3.04 percent. The population increased at a rate of 1.49 percent from 1995 to 1999 after which the population further increased at a rate of 4.62 percent for the four year period from 1999 to 2003 (Chart 3.134). Eighty seven percent of all chicken in Kilimanjaro region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 1,228,606 1,381,225 1,561,340 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend 0 100,000 200,000 Number of Chickens Moshi Rur Hai Same Mwanga Rombo District Chart 3.133 Total Number of Improved Chickens by District EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 90 3.12.5.3 Chicken Flock Size The results indicate that about 81 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 9 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 29 chickens per holder. Only 0.3 percent of holders kept the flock sizes of more than 100 chickens at an average of 439 chickens per holder (Table 3.14). 3.12.5.4 Improved Chickens (layers and broilers) The overall annual broilers chicken population growth rate during the eight-year period from 1995 to 2003 was -9.70 percent. The population decreased at a rate of -13.18 percent from 1995 to 1999 after which the population further decreased at a rate of -6.0 percent for the four year period from 1999 to 2003 (Chart 3.135). The overall annual layers chicken population growth rate during the eight-year period from 1995 to 2003 was 11.14 percent. The population decreased at a rate of 18.94 percent from 1995 to 1999 after which the population increased at a rate of 52.38 percent for the four year period from 1999 to 2003 (Chart 3.136). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 54,867 35 151,020 3 5 - 9 48,974 31 316,884 6 10 - 19 37,959 24 482,724 13 20 - 29 8,939 6 203,688 23 30 - 39 2,059 1 66,695 32 40 - 49 1,174 1 48,928 42 50 - 99 1,108 1 69,000 62 100+ 507 0 222,401 439 Total 155,587 100 1,561,340 10 72,264 82,214 31,194 46,703 168,203 36,355 - 60,000 120,000 180,000 Number of layers 1995 1999 2003 Year Chart 3.135: Number of Improved Chicken by Type and District Layers Broilers 72,264 31,194 168,203 - 60,000 120,000 180,000 Number of Chicken 1995 1999 2003 Year Chart 3.136 Layers Population Trend Moshi Rural Mwanga Same Moshi Urban Rombo 11 31 6 4 0 48 Hai Moshi Urban Moshi Rural Rombo Hai Mwanga Same 0 21,119 12,198 3,957 17,044 9,378 Sheep Density by District as of 1st October 2003 by District MAP 3.45 KILIMANJARO MAP 3.46 KILIMANJARO Sheep Population by District as of 1st Octobers 2003 by District Tanzania Agriculture Sample Census Number of Sheeps Number of Sheeps Per Square Km 16,000 > 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Number of Sheep Sheep Density RESULTS 91 Same Mwanga Moshi Rural Moshi Urban Hai Rombo 2.1 0.2 117.7 0 20.1 54.7 Moshi Urban Same Mwanga Moshi Rural 0 5,317 131 65,761 23,872 21,796 Hai Rombo Pig Density by District as of 1st October 2003 MAP 3.47 KILIMANJARO MAP 3.48 KILIMANJARO Pig Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Pigs Number of Pig Per Square Km 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 80 > 60 to 80 40 to 60 20 to 40 0 to 20 Number of Pigs Pigs Density RESULTS 92 Moshi Urban Moshi Rural Mwanga Same Rombo 0 1,085.1 73.6 235.9 512.8 367.8 Hai Moshi Urban Mwanga Rombo Hai Moshi Rural Same 0 147,260 223,992 398,176 606,027 185,885 Chicken Density by District as of 1st October 2003 MAP 3.49 KILIMANJARO MAP 3.50 KILIMANJARO Chicken Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken Per Square Km 480,000 to 610,000 360,000 to 480,000 240,000 to 360,000 120,000 to 240,000 0 to 120,000 800 > 600 to 800 400 to 600 200 to 400 0 to 200 Number of Chicken Chicken Density RESULTS 93 EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 94 3.12.6. Other Livestock There were 42,319 ducks, donkeys, 36,929, turkeys, 3,194 and rabbits 310 raised by rural agricultural households in Kilimanjaro region. Table 3- 16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Moshi Rural district (56% of all ducks in the region), followed by Rombo (25%), Mwanga (10%), Hai (6%) and Same (3%). Turkeys were reported in Moshi Rural and Mwanga districts only (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 27 percent and 11 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Mwanga district but lowest in Rombo district (Map 3.47). The most practiced method of controlling ticks spraying with 70 percent of all livestock-rearing households in the region using the method. Other methods used were smearing (8%), dipping (3%) and other traditional methods like hand picking (5%). However, 14 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 56 percent of livestock-rearing households and dipping (3%), trapping (4%) and other traditional methods (1%). However, 36 percent of the livestock rearing households did not use any of the four aforementioned methods. Table 3.16 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Rombo 10,664 0 0 1,715 924 Mwanga 4,326 1,079 43 23,405 169 Same 1,383 0 0 148 74 Moshi R 23,551 2,115 266 7,154 1,340 Hai 2,396 0 0 4,505 1,251 Total 42,319 3,194 310 36,929 3,758 Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 Rombo Mwanga Same Moshi Rur Hai District Percent Ticks Tsetseflies 0 10 20 30 40 50 Percent Rombo Mwanga Same Moshi Rur Hai District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 95 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 111,253 (71 % of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 58 percent, goats (36%), sheep (23%) and pigs (15%) (Chart 3.138) 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 114,624, representing 100 percent of the total livestock-rearing households and 46 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 87 percent of all households receiving livestock extension services. The rest of the households got services from other service providers (13%). About 54 percent of livestock rearing households described the general quality of livestock extension services as being good, 25 percent said they were very good and 13 percent said they were average. However, 5 percent of the livestock rearing households said the quality was not good whilst 3 percent described them as poor (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 71 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 29 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The results show that only 9% of the livestock rearing households accessed the services at a distance less than 5 kilometers. (Chart 3.141). Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Average 13% No good 5% Poor 3% Very Good 25% Good 54% Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 137,446, 71% Less than 14km, 57,193, 29% Same Moshi Urban Moshi Rural Mwanga Rombo Hai 142 0 1,357 1,238 103 7,710 0.5 0 1.8 7.4 0.2 16.6 Rombo Mwanga Moshi Urban Moshi Rural Same Hai 13,355 2,211 5,942 8,597 0 10,875 42.7 6 50.7 46.6 0 19.5 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number and Percent of Households Using Draft Animals by District MAP 3.51 KILIMANJARO MAP 3.52 KILIMANJARO Number and Percent of Households Infected with Ticks by District Tanzania Agriculture Sample Census Number of Households Infected with Ticks Percent of Households Infected with Ticks Number of Households Infected with Ticks Number of Households Using Traft Animal Percent of Households Using Traft Animal Number of Households Using Traft Animal 6,400 to 8,000 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 RESULTS 96 EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 97 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 32,943 (97% of livestock rearing households in Kilimanjaro region) whilst 559 households (2%) resided between 5 and 14 kms. However, 432 households (1%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Rombo district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Moshi Rural, Same, Hai and Mwanga districts. Only 3% of the livestock rearing households in the region had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 40,000 50,000 Rombo Mwanga Same Moshi Rur Hai District Number of H ouseholds Less than 14km More than 14km Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 32,943, 97% 5-14 kms, 559, 2% 15 or more kms, 432, 1% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 25 50 75 100 Rombo Mwanga Same Moshi Rur District Number of Households Less than 5 kms 5-14 kms 15 or more kms EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 98 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Kilimanjaro region is encouraging with 10,551 households (4.9% of the total households in the region) using them (Chart 3.144). The number of households that used draft animals in Hai district was 7,710 (73% of the households using draft animals in the region). In Moshi Rural district the number of households using draft animals was 1,357 (13%), Mwanga (1,238 households, 12%), Same (142 households 1%) and Rombo (103 households, 1%) (Chart 3.145 and Map 3.48) The region had 11,759 oxen that were used to cultivate 9,987 hectares of land. This represents only 05 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Hai district (7,825 ha, 78% of the total area cultivated using oxen). 3.12.9.2.1 Use of Farm Yard Manure The number of Households using organic fertilizer in Kilimanjaro region was 150,510 (61% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 78,267 ha or 76% of the area planted with annual crops and vegetables in Kilimanjaro region during the long rainy season) was applied with farm yard manure (Map 3.49). 3.144 Number of Households Using Draft Amimals Using draft animal, 10,551, 4.9% Not using draft animal, 205,622, 95.1% 0 300 600 900 1,200 1,500 Number of Households Hai Moshi Rural Mwanga Same Rombo District Chart 3.145 Number of Households Using Draft Animals by District - Kilimanjaro Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 150,510, 61% Not Using Organic Fertilizer, 97,717, 39% EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 99 3.12.9.4 Use of Compost Only 5,772 ha (7% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost was found in Same district with 4,354 hectares (75.4% of the total area applied with compost) followed by Moshi Rural (535 ha, 9.3%), Rombo (375 ha, 6.5%), Mwanga (338 ha, 5.9%) and Hai (170 ha, 2.9%) (Chart 3.147 and Map 3.50) 3.12.10 Fish Farming The number of households involved in fish farming in Kilimanjaro region was 1132, representing 1 percent of the total agricultural households in the region. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 52.7 kilometers from the agricultural household’s dwelling. Other services and their respective average distances in kilometers from the dwellings were feeder road (1.4), primary school (1.5), all weather road (2.1), health clinics (3.8), primary market (6.0), secondary market (22.0), secondary school (4.3), hospital (16.8) and tertiary market (28.6) (Table 3.17). Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Rombo 4.1 1.2 1.3 0.3 15.8 4.7 69.9 4.9 29.1 54.9 40.1 Mwanga 4.9 1.4 3.6 4.5 18.5 3.6 74.1 7.9 31.1 22.6 25.3 Same 6.9 1.5 6.2 1.3 38.5 4.4 127.8 12.7 31.9 20.5 29.0 Moshi R 3.4 1.7 1.0 1.7 9.9 3.5 23.4 3.9 16.5 19.1 7.3 Hai 4.2 1.7 1.4 1.2 14.8 3.3 29.1 5.5 14.4 25.1 7.2 Total 4.3 1.5 2.1 1.4 16.8 3.8 52.7 6.0 22.0 28.6 18.7 Chart 3.147 Area of Application of Organic Fertiliser by District Kilimanjaro 0 7,000 14,000 21,000 28,000 35,000 Rombo Mwanga Same Moshi Rural Hai District Area of Fertiliser Application (ha) Farm Yard Manure Compost Chart 3.148 Number of Households Practicing Fish Farming - Kilimanjaro , 215,041, 99% Number of Agricultural Households Doing Fish Farming, 1,132, 1% Moshi Urban Moshi Rural Mwanga Same Rombo 0 338 4,354 535 375 170 0 5.9 75.4 9.3 6.5 2.9 Hai 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Moshi Urban Moshi Rural Rombo Mwanga Same Hai 0 17,923 6,294 5,440 30,347 12,491 0 24.7 8.7 7.5 41.9 17.2 24,000 > 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Planted Area and Percent of Planted Area with Compost Application by District MAP 3.53 KILIMANJARO MAP 3.54 KILIMANJARO Planted Area and Percent of Planted Area with Farm Yard Manure Application by District Tanzania Agriculture Sample Census Planted Area a with Farm Yard Manure Applied Percent of Planted Area a with Farm Yard Manure Applied Planted Area a with Farm Yard Manure Applied Planted Area with Compost Applied Percent of Planted Area with Compost Applied Planted Area with Compost Applied RESULTS 100 EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 101 Only 8 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 7 percent reported them to be ‘no good’. Twenty nine percent of the agricultural households said the infrastructure and services were good. Those who said the infrastructures and services were poor were 20 percent while 36 percent said they were average. 3.13.2 Type of Toilet A large number of rural agricultural households use traditional pit latrines (194,950 households, 90% of all rural agricultural households). This is followed by flush toilets (5,538 houeholds 3%), improved pit latrines (11,310 households, 5%) and other types of toilets (231 household, 0.1%). However, 4,143 households (2%) in the region had no toilet facilities (Chart 3.150). 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Kilimanjaro region with 168,412 households (78% of the agriculture households in the region) owning the asset followed by iron (104,453 households, 48%), bicycle (61206 households, 28%), wheelbarrows (44,412 households, 21%), mobile phones (21,676 households, 10%), television/videos (9,366 households, 4%), vehicles (7,046 households, 3%), and landline phone (3,697 households, 2%) (Chart 3.151) 3.13.4 Sources of Lighting Energy Hurricane lamp is the most common source of lighting energy in the region with 42.4 percent of the total rural households using this source of energy followed by wick lamp (38.6%), mains electricity (12.4%) and pressure lamp (6.0%). The remaining sources of lighting were minor. (Chart 3.152) Chart 3.150 Agricultural Households by Type of Toilet Facility No Toilet , 4143, 2% Flush Toilet, 5538, 3% Improved Pit Latrine , 11310, 5% Other Type, 231, 0% Traditional Pit Latrine, 194950, 90% Chart 3.151 Percentage Distribution of Households Owning the Assets 21 10 4 3 2 78 48 28 0 20 40 60 80 Radio Iron Bicycle Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.152 Percentage Distribution of Households by Main Source of Energy for Lighting Firew ood, 605, 0.3% Solar, 441, 0.2% Candles, 118, 0.1% Gas (Biogas), 358, 0.2% Mains Electricity, 26823, 12.4% Pressure Lamp, 12864, 6.0% Hurricane Lamp, 91583, 42.4% Wick Lamp, 83380, 38.6% EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 102 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.7 percent of all rural agricultural households in Kilimanjaro region. This is followed by charcoal (1.6%) and crop residue (0.9%). The rest of energy sources accounted for 1.8 percent. These were mains electricity (0.7%), solar energy (0.5%), paraffin/kerosene (0.3%), bottled gas (0.1%) biogas (0.1%) (Chart 3.153). 3.13.6 Roofing Materials The most common material used for roofing the main dwelling was Iron sheet and it was used by 89.7 percent of the rural agricultural households. This was followed by grass/leaves (7.6%), grass / mud (1.2%), asbestos (0.5%) and tiles (0.5%) (Chart 3.154) Moshi Rural district had the highest percentage of households with Iron sheet roofing (37%) followed by Rombo district (23%), Hai (21%), Same (11%) and Mwanga (8%) (Chart 3.155 and Map 3.52) Chart 3.154 Percentage Distribution of Households by Type of Roofing Material Asbestos, 1083, 0.5% Concrete, 337, 0.2% Tiles, 1171, 0.5% Iron sheet, 193843, 89.7% Grass/leaves, 16504, 7.6% Grass/mud, 2516, 1.2% Other, 720, 0.3% Chart 3.155 Percentage Distribution of Households with Iron sheet Roofs by District 8 11 21 23 37 0 10 20 30 40 Moshi Rur Rombo Hai Same Mwanga District Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Cooking Mains Electricity, 1613, 0.7% Solar, 1131, 0.5% Gas (Biogas), 139, 0.1% Parraffin / Kerocine, 716, 0.3% Charcoal, 3449, 1.6% Firewood, 206963, 95.7% Crop Residues, 1845, 0.9% Bottled Gas, 244, 0.1% Same Moshi Urban Moshi Rural Mwanga Rombo Hai 734 235 0 801 786 1,588 2.5 1.4 0 1 1.7 3.4 1,200 > 900 to 1,200 600 to 900 300 to 600 0 to 300 Moshi Urban Moshi Rural Hai Rombo Mwanga Same 0 371 0 135 336 291 0 0.8 0 0.2 2 1 320 to 400 240 to 320 160 to 240 80 to 160 0 to 80 Number and Percent of Households Without Toilets by District MAP 3.55 KILIMANJARO MAP 3.56 KILIMANJARO Number and Percent of Households Practicing Fish Farming by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming Number of Households Practicing Fish Farming Number of Households Without Toilets Percent of Households Without Toilets Number of Households Without Toilets RESULTS 103 Moshi Urban Moshi Rural Rombo Mwanga Same Hai 0 24,699 51,057 12,167 1,649 25,742 0 18.5 38.3 9.1 6.1 19.3 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Moshi Urban Moshi Rural Same Mwanga Rombo Hai 1,516 3,401 6,589 0 1,024 3,974 9.1 4.4 22.6 0 2.2 8.5 5,200 > 3,900 to 5,200 2,600 to 3,900 1,300 to 2,600 0 to 1,300 Number and Percent of Households Eating 3 Meals per Day by District MAP 3.57 KILIMANJARO MAP 3.58 KILIMANJARO Number and Percent of Households Using Grass/Leaves for Roofing Material by District Tanzania Agriculture Sample Census Number of Households Using Grass/ Leaves for Roofing Material Percent of Households Using Grass/ Leaves for Roofing Material Number of Households Using Grass/ Leaves for Roofing Material Number of Households Eating 3 Meals per Day Percent of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day RESULTS 104 Moshi Rural Rombo Hai Mwanga Moshi Urban Same 4,168 1,749 21,335 21,211 15,759 0 6.5 2.7 33.2 33 24.5 0 16,000 > 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Hai Moshi Urban Moshi Rural Mwanga Same Rombo 12,163 0 26,524 7,514 11,897 26,491 14.4 0 31.4 14.1 8.9 31.3 20,000 > 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Number and Percent of Households Eating Fish Once per Week by District MAP 3.59 KILIMANJARO MAP 3.60 KILIMANJARO Number and Percent of Households Eating Meat Once per Week by District Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Number of Households Eating Fish Once per Week Percent of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week RESULTS 105 EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 106 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Kilimanjaro region was piped water (57.7% of households in the wet season and 56.4 percent during dry season). This is followed by unprotected spring (22.4% of households in the wet season and 25.2 percent during dry season), protected spring (4.2% of households during the wet season and 4.9% in the dry season), protected well (2.6% of households in the wet season and 2.5% during dry season), unprotected well (1.1% of households in both wet season and during dry season), lake /river (none of households fetches water in lake or rivers during wet season while during dry season 9.3% households) and other sources (12.1% of households in the wet season and 0.7% during dry season) (Chart 3.156) About 74 percent of the rural agricultural households in Kilimanjaro region obtained drinking water within a distance of less than one kilometer during wet season compared to 65 percent of the households during the dry season. However, 26 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 35 percent of households in the dry season. The most common distance from the source of drinking water was less 100 meters (Chart 3.157). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Kilimanjaro region normally have 3 meals per day (61.7 percent of the households in the region). This is followed by 2 meals per day (33.8 percent) and 1 meal per day (4.1 percent). Chart 3.156 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Unprotected Spring Piped Water Uprotected Well Lake Protected Well Protected Spring Other Main source Percent of Households Wet Season Dry Season Chart 3.157 Percent of Households by Distance to Main Source of Water and Season 0 10 20 30 40 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season Chart 3.158 Number of Agriculural Households by Number of Meals per Day Three Meals, 133,314, 61.7% Two Meals, 72,977, 33.8% One Meal, 8,860, 4.1% Four Meals, 1,021, 0.5% EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 107 Only 0.5 percent of the households have 4 meals per day (Chart 3.158). Rombo district had the largest percent of households eating one meal per day whilst Moshi Rural had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.53). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 185,915 (86% of the agricultural households in Kilimanjaro region) with 84,588 households (45 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (34%) and those who had meat thrice during the week (15%). Very few households had meat four or more times during the respective week. About 14 percent of the agricultural households in Kilimanjaro region did not eat meat during the week preceding the census (Chart 3.159 and Map 3.54). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 185,590 (85.6% of the total agricultural households in Kilimanjaro region) with 30,583 households (35 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (33%), three times (15%). In general, the percentage of households that consumed fish four or more during the week in Kilimanjaro region was 33,306 (18% of the agricultural households that ate fish in the region during the respective period). About 14 percent of the agricultural households in Kilimanjaro region did not eat fish during the week preceding the census (Chart 3.159 and Map 3.55). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Rombo 4556 9.7 17527 37.3 24699 52.5 233 0.5 47014 Mwanga 175 1.0 4363 26.1 12167 72.6 44 0.3 16749 Same 292 1.0 9162 31.5 19649 67.5 0 0.0 29103 Moshi R 1820 2.4 23442 30.5 51057 66.5 507 0.7 76826 Hai 2018 4.3 18483 39.8 25742 55.4 239 0.5 46481 Total 8,860 4.1 72,977 33.8 133,314 61.7 1,021 0.5 216173 Chart 3.159 Number of Households by Frequency of Meat and Fish Cosumption 0 15000 30000 45000 60000 75000 90000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 108 3.13.9 Food Security In Kilimanjaro region, 64,472 households (30% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 9,438 (4%) said they sometimes experienced problems, 6 percent often experienced problems and 5 percent always had problems in satisfying the household food requirements. About 55 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.56). 3.13.10 Main Sources of Cash Income The main cash income of the households in Kilimanjaro region was from sales of food crops (43.9 percent of smallholder households), followed by sales of cash crops (15.9%), other casual cash earnings (11.3%), wages and salaries in cash (10.0%), business income (9.9%), cash remittance (3.6%), sales of livestock (2.7%), sales of livestock products (1.4%), sales of forestry products (0.4%), fishing (0.2%) and other sources (0.6%) (Chart 3.160). Chart 3.160: Percentage Distribution of the Number of Households by Main Source of Income Sales of Cash Crops 15.9% Sale of Forest Products 0.4% Business Income 9.9% Wages & Salaries in Cash 10.0% Sale of Livestock Products 1.4% Sale of Livestock 2.7% Sales of Food Crops 43.9% Other Casual Cash Earnings 11.3% not applicable 0.1% Other 0.6% Cash Remittance 3.6% Fishing 0.2% EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 109 3.3.5 Kilimanjaro Profile Kilimanjaro has a land area of 230,000 hectares under crop production and has a relatively high number of crop growing households compared to other regions. Most of the crop growing households have livestock. The number of crop growing household per square kilometer is the second highest in the country. The region has a land area per crop growing household of 1.0 ha and almost all available land is utilized. The region has short and long rainy seasons with the long rainy season being slightly more important. Kilimanjaro has a relatively high percent of permanent crops, some of which are in mono-crop stands and the remainder in mixed annual/permanent crop. Cereal production in Kilimanjaro is not important and it has one of the smallest planted areas of maize. Paddy, sorghum, cassava and groundnuts are almost absent in the region. There is moderate to low cultivation of beans and vegetables. The region has the second largest planted area of bananas, third for coffee and mangoes. Small amounts of oranges and sugar canes are also grown in the region. Kilimanjaro has the fourth largest planted area with irrigation in Tanzania and it has the second highest percent of total planted area under irrigation. The region has faced the greatest decline in the number of households with irrigation in 10 years (around 30%). Canals are the most common source of irrigation water and the region has the highest percent of households using canals. Rivers are also used. Practically all irrigation water is obtained by gravity and very few households use buckets/watering cans. Similarly, flood irrigation in the region is the highest in the country and almost all field application of irrigation water is by flood, with very few households applying irrigation water by buckets/watering cans.Most cultivation is done by hand with very few households using oxen. However, it is one of the six regions in the country that has some cultivation by tractor. Kilimanjaro has one of the highest percent of the total planted area with fertilizer application and slightly more farm yard manure than inorganic fertilizer is applied. It has the second highest percentage of total planted area with insecticide application and the fourth highest for fungicides. The region has the highest percent of households using air tight drums for storage and it is the most common method in the region, however this is closely followed by sacks/open drums. Very little storage is done in locally made traditional structures. Although Kilimanjaro has only a moderate number of households selling crops, it has the highest percent of households processing crops. Though small, the region has the second largest number households processing crops on farm by machine, however most processing in the region is done by neighbours machine. It has the second highest number of households selling processed crop and this is mostly to farmers associations (higher than any other region) and the marketing cooperatives (also the highest in the country). Kilimanjaro has one of the highest number and percent of smallholder households receiving extension advice in the country. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 110 Kilimanjaro region has a moderate number of planted trees by smallholders in the country with gravellis being the dominant species. Some eucalyptus and casurina are also grown. It has the largest number of households with erosion control/water harvesting bunds in Tanzania with terraces and erosion control bunds being the most common. 4.1. Rombo Rombo district has the second largest number of households in the region as well as third highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It has no livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Rombo district is Permanent Crop Farming, followed by Annual Crop Farming, Livestock keeping/rearing, Off farm Income, Tree or Forest Resources, Remittances, and Fishing/hunting & gathering. However, the district has one of the highest percent of households with off-farm activities and second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Rombo has the lowest percent of female headed households (9%) but also it has one of the lowest average ages of the household head. With an average household size of 5 members per household it is relative lower than the average for the region which is 6 member households. Rombo has a comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively low level of school attendance in the region. The literacy rates for the heads of household is also slightly higher than most of districts in the region. It has one of the largest utilized land area per household (0.5 ha) and the allocated area was almost utilized indicating a high level of land pressure. The total planted area is one of the greatest than in other districts in the region due to the presence of good wet season, however it has the lowest planted area per household (0.5 ha) attributed to the high number of smallholders in the district. The district is not important for maize production in the region with a planted area of over 17,000ha; however the planted area per household is the lowest in the region. Paddy production was not reported in the district. Rombo district did not show the production of bulrush millet. Cassava production is moderate accounting for 0.5 percent of the area planted in the region. The district did report the production of Irish potatoes. The production of beans in Rombo was higher in the region with a planted area of (13,664 ha). Oilseed crops are very important in Rombo as it ranks first in the region. Vegetable production is not important in the district. Cabbage was reported with lowest production, while, tomatoes, chillies were not recorded in the district. No annual traditional cash crop which was grown in the district. Compared to other districts in the region, Rombo has the second largest planted area with permanent crops, which is dominated by banana (15,128 ha).Other permanent crops includes coffee (10,165 ha) and oranges (158 ha). Guava was grown in very small area (1.0 ha). EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 111 As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is moderate, however district differences exist. Rombo ranked fourthn planted area with improved seed in Kilimanjaro region. The district has moderately low planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Rombo district has a highest level of insecticide use but low use of fungicides. Also, Rombo district had one of the lowest percentages of households that used herbicide in the region. It has the fifth lowest area with irrigation compared to other districts with 81 ha of irrigated land. The most common source of water for irrigation is from canals using gravity. Canal, well and dam are the most common means of irrigation water application and a very small amount of borehole irrigation is used. The most common method of crop storage is in sacks and open drum, however the proportion of households storing crops in the district is moderately low than other districts in the region. The district has the relatively high number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Rombo is among the highest percent of households processing crops in Kilimanjaro region and is almost all done by hand. Rombo is among the two districts with a higher percent of households selling processed crops to neighborours than other districts and also some sales were made to secondary markets and on traders at farm. Although very small, access to credit in the district is to men only and the main sources are from friends and Friends and Relative. A comparatively larger number of households receive extension services in Rombo and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important although small in Rombo as only 6,590 planted trees) and is mostly Gravellis spp, cyprus spp with some and Azadritachta spp. The third lowest proportion of households with erosion control and water harvesting structures is found in Rombo district and is mostly erosion control bunds; however it also has the highest number of terraces, gabions/sandbags and drainage ditches than other districts. The district has the lowest number of cattle in the region and they are almost all improved. Goat production is moderate compared to other districts; however it has the third largest population of sheep in the region. It has the second big number of pigs in the region and a moderate number of chickens. The district is one of the three that did not show the rearing of layers in the region. It has the highest numbers of ducks and donkeys the region is ranked third in the region. Rabbits are also found in the district but there was no turkeys keeping in the district. The smallest number of households reporting Tsetse and tick EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 112 problems was in Rombo district and it had the second smallest number of households de-worming livestock. The use of draft animals in the district is lowest; there were few households who practiced fish farming in the district. It has the moderate access to secondary schools, health clinics, primary and secondary markets but amongst the worst to primary schools compared to other districts. Also, it has the moderate accesses to all weather roads and moderate to regional capital. Rombo district has the relative low percent of households with no toilet facilities and it has one of the lowest percent of households owning vehicles, bicycles and tv/video, but comparative high percent owing mobile phones. It has one of the lowest numbers of households using mains electricity in the region. The most common source of energy for lighting is the hurricane lamp and practically all households use firewood for cooking. The district has the fourth lowest percent of households with grass roofs with 37 percent of households having iron sheets. The most common source of drinking water is from piped water. It has the comparative high percent of households having two meals and highest percent per households having one meal per day when compared to other districts and relative low percent with 3 meals per day. The district had the third highest percent of households that did not eat meat; however, it has one of the lowest percent of households that did not eat fish during the week prior to enumeration; however most households had problems with food satisfaction. 4.2.2 Mwanga Mwanga district has the fifth smallest number of households in the region and it has the lowest percentage of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed crop and livestock. It is the fourth with highest number of livestock only households and also pastoralists were found in the district. The most important livelihood activity for smallholder households Mwanga district is Annual Crop Farming, followed by off farm Income. The district has the lowest percent of households with no off-farm activities and also it has the fourth percent of households with more than one member with off-farm income. Compared to other districts in the region, Mwanga has a highest percent of female headed households (31%) and it has one of the moderately low average ages of the household head in the region. With an average household size of 4.2 members per household it is relatively high for the region. It has a moderate utilized land area per household (0.6 ha) and 99 percent of the allocated area is currently being utilized. The district has the smallest planted area in the region, and the fourth largest planted area per household (0.6 ha). The district is moderately important for maize production in the region with a planted area of 10,702 ha, and the planted area per household is also moderate for the region. The district has the one of the lowest planted area of paddy in the region with 71 hectares. Sorghum is grown in the district. Cassava EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 113 production is moderate to low, accounting for 3 percent of the quantity harvested in the region. The district did not report the planted area of Irish potatoes. The production of beans in Mwanga was the smallest than in other districts in the region with a planted area of (4,452 ha). Mwanga district has the fourth smallest groundnuts planted area in Kilimanjaro region with area planted per groundnut growing household of 0.30 ha. Vegetable production is moderately important in the district. It has the fifth smallest planted area with cabbage (2 ha) but, production of tomatoes was not recorded in the district. A traditional cash crop (e.g. pyrethrum) is not grown in the district. Compared to other districts in the region, Mwanga has the fifth largest planted area with permanent crops which is dominated by coffee (4,547 ha), Banana (3,588 ha), and guava (3 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however a very small amount of land preparation is done by tractor The use of inputs in the region is moderately low, and district differences exist. Mwanga has the fifth smallest planted area with improved seed in the region as well as the moderate high (third) proportion of households using improved seeds. The district has the fourth highest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is farm yard manure. Compared to other districts in the region, Mwanga district has one of the lowest levels of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. Application of herbicides was among the lowest. It has the fourth largest area with irrigation compared to other districts with 3,014 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage in Mwanga district is in Sacks/Open Drums, however the proportion of households storing crops in the district is relatively high. Mwanga district is one of the districts with a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Mwanga is among the districts with the lowest percent of households processing crops in Kilimanjaro region and is almost all done by neighbours machine. The district also has the fifth highest percent of households selling processed crops to marketing cooperatives than other districts and no sales are to farmers associations or large scale farms. Although very small, access to credit in the district is to female headed households only and the main source is “saving and credit societies”. A comparatively small number of households receive extension services in Mwanga district and all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 114 Tree farming is important in Mwanga district with (24,430 planted trees) and is mostly Gravellis and Senna. The moderate proportion of households with erosion control and water harvesting structures is found in Mwanga district and is mostly erosion control bunds and water harvesting bunds; however it also has vetiver grass, number of tree belts and drainage ditches. The district has the fourth largest number of cattle in the region and they are almost all indigenous. Goat production is comparative lower compared to other districts; and also it has the fifth largest population of sheep in the region. It has the fourth largest number of both pigs and chicken in the region. Some ducks, rabbits and turkey are also found in the district. A number of households reported tsetse and tick problems in Mwanga district and it had the fifth largest number of households de-worming livestock. The district has the fifth largest number of households using draft animals in the region. A comparative number of households practice fish farming; however the district has the second largest number in the region. It has amongst the best access to secondary schools, primary schools, health clinics but worst regional capital. However, it has the moderate access to primary and secondary markets compared to other districts. The percentages of households without toilet facility in Mbeya Rural district is 1 percent and it is among the districts with the lowest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the moderate number of households using mains electricity in the region. The most common source of energy for lighting is the hurricane lamp and practically the majority of the households use firewood for cooking. The roofing materials for most of the households in the district is iron sheets (8%) and grass/leaves (9%) and the most common source of drinking water is from piped water. It is one of the districts with the highest percent of households having three meals per day. The district had the second lowest percent of households that did not eat both meat and fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.3 Same Same district has the fourth largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It has a one of the biggest number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Same district is Annual Crop Farming, followed by Permanent Crop Farming. However, the district has the highest percent of households with no off-farm income activities and the fifth lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Same has a relatively high percent of female headed households (17%) and it has the relatively high average age of the household head in the region. With an average household size of 3.9 members per household it is relatively below average for the region. Same has a fourth highest literacy rate among smallholder households regardless the moderate level of school attendance in the region. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 115 The land area utilized per household (0.9) is slightly above the average for the region and 93 percent of the allocated area is currently being utilized which is moderate to high for the region. The district has the moderate to high planted area in the region, and the largest planted area per household (1.1 ha in the wet season and 0.7 ha in short rainy season. The district is comparative important for maize production in the region with a planted area of 20,451 ha and the planted area per household is (0.4 ha) which is equal to the average for the region (0.4 ha). Paddy production is very important with a planted area of 1,169 hectares; however it is the second highest in the region. The district is comparative low for the production of sorghum whereas; As Irish potatoes was produced in the district but, wheat was not grown in the district. The district has the highest planted area of cassava accounting for 57 percent of the cassava planted area in the region. The production of beans in Same is relatively high than in other districts in the region with a planted area of (10,829 ha). Oilseed crops are less important in Same as no production which was reported. Although very small the district is third largest in vegetable production in the region. Tobacco was not are grown in the district. Permanent crops though small but it is important in Same district with only (11% of the total permanent crop planted area in Kilimanjaro region). The most prominent permanent crops in the district include coffee (3,500 ha), banana (3,339 ha) and guavas (173ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has the comparative largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is comparative low, however district differences exist. Same has the comparative small planted area with improved seed in Kilimanjaro region and this is due to high prices and sometimes there are not readily available in time. The district also has one of the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and practically all is with Inorganic fertilizer. Compared to other districts in the region, Same district has the smallest area of insecticide where’s it has the biggest area of fungicide use and the use of herbicides is high. It has the highest area with irrigation in the region with (11,255ha) of irrigated land. The most common source of water for irrigation is from rivers and canals and almost all water application is by using floods and hand bucket/watering canes. The most common method of crop storage in Same is Sacks/Open drums, and the proportion of households not storing crops in the district is moderate to high for the region. The district has the third lowest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Same district has a comparative low percent of households processing crops in the EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 116 region and is almost all done by neighbour machine; however, the district does not process crops by trader. Small quantities of processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Same district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming though small but is important in Same district (with 3,857 planted trees) and is mostly Greville Spp and Senna Spp.. The third highest proportion of households with water harvesting bunds is found in Same district and it is among the five districts which controls erosion by using drainage ditches The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is lowest compared to other districts. It has the fourth largest number of pigs in the region and the comparative low number of chickens, all of which are indigenous. Virtually there was no improved chicken which was found in the district. The district has the fifth lowest number of ducks, but no turkeys and a small number of rabbits but biggest number of donkeys found in the district. Although a small number of households reported tsetse problem but, relative high number of households reported tick problems in Same district. A comparative low amount of de-worming of livestock is practiced in the district draft animals are also used. Fish farming was practiced by households in the district, so it is one of the four districts where fish farming was carried out in the region. It has amongst the best access to secondary schools and feeder roads but also relative access to primary schools, health clinics, and primary markets compared to other districts. However, it has one of the best accesses to tertiary markets and the regional capital. The percentage of households without toilet facility in Same district is above the average of the region; however it has the fourth highest percent of households with toilet facilities. It has the relative low percent of households owning land line phones and vehicles but the lowest percent owing Tv/video. It has also the lowest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. Although, the district has a highest percent of households with grass roofs (40%) but it has 11 percent of households having iron sheet roofing. The most common source of drinking water is from unprotected wells. Thirty three percent of the households in the district reported having one or two meals per day and virtually there were some households that reported having more than three meals per day. The district had a lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Moshi rural Moshi rural district has an average number of households slightly above that of the region and it has the highest percent of households involved in smallholder agriculture in the region. Most smallholders are EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 117 involved in crop farming only, followed by crop and livestock. It has a relative big number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Moshi rural district is annual crop farming followed by Permanent Crop Farming. It has the lowest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Moshi rural district has the highest percent of female headed households (59%) and it has one of the highest average age of the household head. With an average household size of 3.9 members per household it is slightly below average for the region. Moshi rural district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. It has the second smallest utilized land area per household (0.8 ha) and 97 percent of the allocated land area was utilized. The total planted area was moderate to high in the region however it has one of the third largest planted area per household (0.5 ha in the wet season and one of the largest 1.1 ha in the dry season. Moshi rural like any other district is important for maize production in the region with a planted area of (26,275 ha,) and the planted area per household is among the lowest in the region. Paddy production is also important with a planted area of 1,486 hectares and the production of sorghum was very small in the district. Cassava, bean and Irish potato production is relative big in the district, and also wheat was not grown. Irish potatoes were grown in the district and were the fourth highest in the region with 17 hectares. Beans was important in the district and was third in the region with the planted area of (6,524 ha). Oilseed crops and vegetables though small but still there are important in the district however, whist the district has one of the smallest planted area with tomatoes it is the second in terms of tomato planted area per household. As traditional cash crop (e.g. tobacco) is not grown in the district, also, cotton was not planted in the district. Compared to other districts in the region, Moshi rural district has the largest planted area with permanent crops (40.9% of total permanent crop planted area) which is dominated by banana (25,513 ha), coffee (12,016 ha), oranges (804 ha), and guavas (545 ha). A small area of avocado, plums and are grown. Apart from a minor amount of sugarcane no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however the second smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 118 The use of inputs in the region is relative small, however district differences exist. Moshi rural district has the second largest planted area with improved seed; however it has also the fourth highest planted area per household in the region. The district also has the second largest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with inorganic fertilizer. Compared to other districts in the region, Moshi rural district has relative low area planted with insecticide but has the third highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and also is one the highest for herbicides. It has the second highest areas of irrigation with (7,029 ha.) The most common source of water for irrigation is from canals using gravity and hand buckets/Bucket. Floods and Watering cans are the most common means of irrigation water application. The most common method of crop storage is in sacks and /or open drums; however the proportion of households not storing crops in Moshi rural district is amongst the lowest in the region. The number of households selling crops in the district is one of the biggest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The relative big percent of households processing crops in the region is found in Moshi rural district and processing is mostly done by neighbours machine. The district has the largest number of households processing crops on farm by machine. It also has the largest number of households processing crops on farm by hand. Most households that sell crops sell to local markets or trade stores, traders on farm and neighbours no sales are to large scale farms. Access to credit in the district is very small. A relative small number of households receive extension services in Moshi rural district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is equally important in Same district (with 6,989 planted trees) and most of them are Greville spp, Senna spp, Albizia spp and some Eucalyptus Spp spp, The largest proportion of households in Moshi rural district use erosion control bunds for erosion control. Moshi rural district has the second largest number of cattle in the region and most of them are indigenous. It is among the districts with the large number of goats in the region, however the district has the relative high density (97 head per km2) Moshi rural is also the districts with the biggest number of pigs and chicken, relative low number of sheep, however it has the second largest number of improved chickens (both layers and broilers) in the region. Small numbers of rabbits, but comparative high number of ducks and turkeys in the region. A moderate to high number of households reported Tsetse and tick problems in Moshi rural district and it had one of the biggest numbers of households de-worming livestock. The use of draft animals in the district is moderate and fewer number of households practice fish farming in the region. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 119 It is amongst the districts with the moderate access to feeder roads, primary markets and secondary markets compared to other districts. Moshi rural district has one of the lowest numbers of households with no toilet facilities. The district has one of the highest percent of households owning television/video, vehicles, radio, mobile phones, land line, irons, bicycles wheel barrows, it has the second highest percent of households with bicycles and relatively low number of irons. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the second smallest percent of households with grass roofs with 94.6 percent of households having iron sheets. The most common source of drinking water is piped water, and it has the lowest percent of households having two or one meal per day compared to other districts and the highest percent with 3 meals per day. The district had one of the lowest percent of households that did not eat meat during the week prior to enumeration but has the relative low percent of households that did not eat fish. Most households seldom had problems with food satisfaction. 4.2.5 Hai Hai district has the third highest number of households in the region and it has the third highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a relative large number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Hai district is Annual Crop Farming followed by Permanent Crop Farming, Livestock Keeping/Herding, Tree/Forest Resources, Off-Farm Income, Remittances, and Fishing/Hunting and Gathering. The district has the third highest percent of households with no off-farm activities and also the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Hai has a moderate percent of female headed households (54%) and it has one of the moderate average age of the household head. With an average household size of 3.6 members per household it is slightly lower than the regional average. Hai has the fourth highest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the highest in the region. It has one of the moderate utilized land area per household (1.1 ha) which is slightly above to the regional average of 0.6 ha per household. The district has the second smallest planted area in the region, however it has the third largest planted area per household (0.5 ha) in the wet season. The district is equally important for maize production with a planted area of (21,360 ha), however the planted area per household is moderate compared to other districts in the region. Paddy production is EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 120 relatively important with a planted area of only 303 hectares and the production of sorghum is moderate high in the region. Wheat and finger millet are also grown in the district. Both Irish and Sweet potatoes are being grown; cassava was also planted in the district with 81 hectares and is fourth in the region. The district has the highest percent of area planted with irish potatoes with 2,391 hectares. The production of beans in Hai district is the third largest in the region with a planted area of 8,815 hectares, oil crops such as groundnuts and simsim are important in the district. Vegetable production is also very important in the district; however the district has the largest planted area per tomato growing household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Hai has one of the three districts with third largest planted area with permanent crops which are both planted in mixed area of (18,428 ha) and are dominated by banana, coffee, orange and guavas. However, other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by hand hoe plough, oxen plough; however a very small amount of land preparation is done by tractor. The use of inputs in the region is comparative big, however district differences exist. Though small Hai has the second largest planted areas with improved seed in Kilimanjaro region. The district is among those with largest planted area with fertilizers and most of this is with farm yard manure, inorganic fertilizer and compost. Compared to other districts in the region, Hai district has the largest percent of its planted area with insecticides in the region. The use of fungicides was also the highest in the region. Also it has the third largest planted area with irrigation in the region with 3,570 hectares of irrigated land. Canals, dams wells, and pipe water is used as the source of irrigation water and hand bucket was mainly used. Buckets/Water cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in air tight drums; sacks or open drums, in unprotected piles; however the proportion of households not storing crops in the district is among the lowest in the region. The district has one of the smallest numbers of households selling crops and the main reason for not selling is insufficient production. Hai district has the highest percent of households processing crops on farm by hand and a small percent of households selling processed crops mainly to neighbours and trader at farm. No sales were made to neither local market trade stores nor large scale farms. Access to credit is in existent in the district, it has one of the lowest proportions of households that accessed to credit in the region and for those who did not use credit it was because of unavailability of the agricultural credits. EVALUATION AND CONCLUTION _____________________________________________________________________________________ _____ ______________________________________________________________________________________________________________________ ______ Tanzania Agriculture Sample Census 121 A relatively low number of households receive extension services in Hai district and all of this is from the government. The quality of extension services was rated between good and very good by most of the households. Tree farming is equally important in Hai (with 3,950 planted trees) and is mostly with Gravellis spp, Senna spp, Albizia Spp and Azadritachta Spp. The fifthy smallest number of erosion control and water harvesting structures is found in Hai district and they are mainly Erosion Control Bunds and Water Harvesting Bunds. Other minor erosion control includes vetiver grass, terraces drainage ditches and tree belts. The district has one of the highest number of cattle in the region and they are mostly all indigenous. Also it is among the districts with largest number of sheep and relatively low production of both goat and pigs in the region. It has a relative high number of chickens. Small numbers of donkeys and rabbits. Ducks are moderately kept in the district. As the districts with bid number of households reported tick problems, there was small number of households reported Tsetse problems in Hai district and has the moderate number of households de-worming livestock. The use of draft animals in the district is in existent and fish farming is practiced in the district. It is amongst the districts with the best access to regional capital, tertiary market, feeder roads, tarmac roads, secondary schools, primary schools, primary and secondary markets and all weather roads; however it has one of the worst accesses to health clinics. Hai district has the largest percent of households with no toilet facilities. The district has one of the smallest percent of households owning landline phones. Very moderately high number of households reported ownership of vehicles, mobile phones, wheel barrows, bicycles, iron and televisions/videos. It has the second largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the lowest percent of households with grass roofs (9 percent, and 87 percent of households having iron sheets. The most common source of drinking water is from piped water, Surface Water (Lake/Dam/River/Stream, unprotected spring wells and Protected / Covered Spring) and It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a relative high percent of households with 3 meals per day. The district had the fourth highest percent of households that did not eat meat during the week prior to enumeration; however it is among the districts with high percent of households that did not eat fish during the week. Most households in the district seldom had problems with food satisfaction. APPENDIX II 123 4. APPENDICES Appendix I Tabulation List..............................................................................................................123 Appendix II Tables .............................................................................................................................239 Appendix III Questionnaires.............................................................................................................. 380 APPENDIX II 124 APPENDIX I: CROP TABULATION NUMBER OF AGRICULTURAL HOUSEHOLDS............................................................................239 2.1 Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year.......................................................................................................240 2.2 Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year ...........................................................................................................240 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES..........................................................241 3.1: The Livelihood Activities/ Source of Income of the Household in Order of Importance by District..................................................................................................................242 3.1a: First Most Importance..................................................................................................................242 3.1b: Second Most Importance..............................................................................................................242 3.1c: Third Most Importance ................................................................................................................242 3.1d: Fourth Most Importance...............................................................................................................242 3.1e: Fifth Most Importance..................................................................................................................243 3.1f: Sixth Most Importance.................................................................................................................243 3.1g: Seventh Most Importance ............................................................................................................243 HOUSEHOLDS DEMOGRAPHS: .......................................................................................................245 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year................................................................246 3.2: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year .........................................................................................................................247 3.3: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year .........................................................................................................................247 3.4: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year 248 3.5: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year.................................248 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year ..................................................................248 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ...........................................................................................................248 APPENDIX II 125 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year .............................................................................................250 LAND ACCESS/OWNERSHIP.............................................................................................................251 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year ...........................................................................................................252 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year 252 LAND USE...............................................................................................................................................253 5.2 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year .........................................................................................................................254 5.1 : Area of Land by type of Land Use and District during 2002/03 Agricultural Year ..................254 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year ..................................................255 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year...............................................255 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year.......................255 TOTAL ANNUAL CROP AND VEGE PRODUCTION – LONG AND SHORT RAINY SEASON...............................................................................................257 7.1 & 7.2a: Number of Crop Growing Households and Planted Area (ha) by season and District 258 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District.....................258 7.1 & 7.2c: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year .........................................................................................................................259 7.1 & 7.2d: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year...................................................................................................................260 7.1 & 7.2h Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Long & Short Rainy Seasons - Kilimanjaro region....... 261 7.1 & 7.2iNumber of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Long & Short Rainy Seasons- Kilimanjaro region. .............261 7.1 & 7.2e Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Longt & Short Rainy Seasons - Kilimanjaro Region..........................262 7.1 & 7.2f Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Long & Short Rainy Season - Kilimanjaro Region.........262 7.1 & 7.2g Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Long & Short Rainy season - Kilimanjaro Region. .......262 7.1 $ 7.2j: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG SEASON ..........................................................................................263 APPENDIX II 126 7.1&7.2k: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT Rainy Seasons .................................263 ANNUAL CROP AND VEGE PRODUCTION - SHORT RAINY SEASON........................................................................................……………….265 7.1a Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-Short Rainy Season, Kilimanjaro Region...........................266 7.1b Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - SHORT SEASON, Kilimanjaro Region.......................................................................266 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, SHORT SEASON, Kilimanjaro Region. .....................................................................................266 7.1d Number of Crop Growing Households and Planted Area By Pesticide Use and District, SHORT RAINY SEASON, Kilimanjaro Region.........................................................................267 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District, SHORT SEASON, Kilimanjaro Region ......................................................................................267 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District SHORT RAINY SEASON, Kilimanjaro Region.........................................................................268 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, SHORT RAINY SEASON, Kilimanjaro Region.........................................................................268 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, LONG RAINY SEASON, Kilimanjaro Region...................................269 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District LONG RAINY SEASON, Kilimanjaro Region.............................................................269 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During LONG RAINY SEASON ...................................................................................269 7.2d Number of Crop Growing Households and Planted Area By Insecticide Use and District LONG RAINY SEASON, Kilimanjaro Region..............................................................270 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District LONG RAINY SEASON, Kilimanjaro Region..............................................................270 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03...........................................................................................................................270 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 LONG RAINY SEASON, Kilimanjaro Region................................................271 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, LONG RAINY SEASON, Kilimanjaro Region............................................................271 7.2h Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop ............................273 APPENDIX II 127 ANNUAL CROP AND VEGETABLE PRODUCTION: ....................................................................275 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................276 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................276 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................276 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................276 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................277 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................277 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................278 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year............................................................................278 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................278 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year...........................................................................278. 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................279 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................279 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................279 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................280 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................280 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................280 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................280 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year.......................................................................281 APPENDIX II 128 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................281 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................281 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................281 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................282 PERMANENT CROPS ..........................................................................................................................283 7.3 Production of Permanent Crops by Crop Type and District, Kilimanjaro Region.......................284 cont Production of Permanent Crops by Crop Type and District, Kilimanjaro Region...............285 7.4: Total Area Planted with Banana by District - Kilimanjaro Region .............................................287 7.5: Total Area Planted with Coffee by District - Kilimanjaro Region...............................................287 7.6: Total Area Planted with Mangoes by District - Kilimanjaro Region..........................................287 7.7: Total Area Planted with Avocado by District - Kilimanjaro Region 287 Cont Planted Area with Fertiliser by Fertiliser Type and crop ....................................................288 AGROPROCESSING 293 8.1.1a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year. ..........................................................................294 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District...................294 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop.................................295 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop.............295 8.1.1e Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District ..........................................................................................................................296 8.1.1.f Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District ............................................................................296 8.1.1.g Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District.......................................................................................................296 8.1.1.h Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District ..........................................................................................................................296 APPENDIX II 129 MARKETING .........................................................................................................................................297 10 Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District..........................................................................................................298 10 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District ...............................................................298 10.3 Proportion of Households who Repoprted Main Reason for Not Selling their Crops by District During 2002/03 Agricultural Year...................................................................298 IRRIGATION..........................................................................................................................................299 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District..............................................................300 11.2: Area of Irrigated and Non Irrigatable (ha) Land By District .......................................................300 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District.........................................................................................300 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District .........................................................................................................................300 11.5: Number of Households Using Irrigation By Method of Irrigation Application By District........301 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District...........................................................................................................................301 11.7 Number of Erosion Control Harvesting Structures By Type and District ...................................301 ACCESS TO FARM INPUTS/IMPLEMENTS ...................................................................................303 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year .........................................................................................................................304 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year .........................................................................................................................304 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year .........................................................................................................................304 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year .........................................................................................................................305 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year..305 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................................305 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .........................................................................................................................306 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year .........................................................................................................................306 APPENDIX II 130 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .........................................................................................................................306 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ...........................................................................................................307 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year .........................................................................................................................307 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................................307 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................308 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................308 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................309 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................309 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................................309 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................310 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................310 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................310 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................311 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ...........................................................................................................311 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................................311 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ...........................................................................................................312 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ...........................................................................................................312 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ...........................................................................................................312 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year ...........................................................................................................313 APPENDIX II 131 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year .........................................................................................................................313 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................................313 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................313 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................314 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................314 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................315 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year .............................................................................................315 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................................315 AGRICULTURE CREDITS..................................................................................................................317 13.2a: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District........................................................................................................................318 13.2b: Number of Households Receiving Credit By Source of Credit By District..................................318 13.2c: Number of Households Receiving Credit By Reason for Not Using Credit By District ..............319 13.2d: Number of Credits Received By Main Purpose of Credit and District..........................................319 TREE FARMING AND AGROFORESTRY.......................................................................................321 14.1: Number of Planted Trees By Species and District, Kilimanjaro Region ........................................322 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District ................................................................................................323 14:3 Main Use of Trees By District .....................................................................................................323 14.4: Number of Households By Distance to Community Planted Forest (Km) By District................324 14: 5 Number of Responses by second use of Trees and District for 2002/03......................................324 CROP EXTENSION...............................................................................................................................325 15.1 Number of Households Receiving Extension Messages By District ...........................................326 15.2: Number of Households By Quality of Extension Messages by District during the 2002/03 Agricultural year, Kilimanjaro Region.........................................................................................326 15.3: Number of Households By Source of Extension Messages By District during the 2002/03 Agricultural Year, Kilimanjaro Region........................................................................................326 APPENDIX II 132 15.4: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region..............................................327 15.5: Number of Households By Receivingf Advice on the Use of Agro-chemicals By Source of Messages By District Kilimanjaro Region...................................................................................327 15.6: Number of Households By Receivingf Advice on the Erosion Control By Source of Messages By District Kilimanjaro Region ..............................................................................327 15.7: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............................328 15.8: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.......328 15.9: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............328 15.10: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............329 15.11: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.......329 15.12: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.......329 15.13: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............................330 15.14: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.........................330 15.15: Number of Households By Receivingf Advice on Agro-Forestry By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............................330 15.16: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............................331 15.17: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region.............................331 15.18: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Kilimanjaro Region...................................331 15.19: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Kilimanjaro Region...................................332 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Kilimanjaro Region...................................332 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Kilimanjaro Region...................................332 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Kilimanjaro Region....................................333 APPENDIX II 133 ANIMAL CONTRIBUTION TO CROP PRODUCTION ..................................................................335 17 Number of Households Using Draft Animal to Cultivate Land By District................................336 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year ................................................................................................336 17.3 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year ..........................................................................................................................336 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year ..........................................................................................................................336 CATTLE PRODUCTION......................................................................................................................337 18.1a Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year......338 18.3b: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03........................................................................................338 18.4c Number of Cattle by Category and Type of Cattle as of 1st October 2003 .................................339 18.2: Number of Cattle By Type and District as of 1st October, 2003 .................................................340 18.3: Number of Indigenous Cattle By Category and as of 1st October, 2003....................................340 18.4: Number of Indigenous Cattle By Category and as of 1st October, 2003....................................340 GOAT PRODUCTION...........................................................................................................................341 19.1: Total Number of Goats by Type and District as of 2st October, 2003 342 19.2: Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003 ........................................................................342 19.:3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District .....343 19.4 Number of Indigenous Goat by Category and District as of 1st October, 2003 ..........................343 19.5: Number of Improved Meat Goat by Category and District as of 1st October, 2003 ...................343 19.6 Number of Improved Dairy Goat by Category and District as of 1st October, 2003...................344 19.7 Number of Total Goat by Category and District as of 1st October, 2003....................................344 SHEEP PRODUCTION .........................................................................................................................345 20.1: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year ..........................346 20.2: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year346 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 .............................346 20.4: Number of Sheep per Household by Category and district as of 1st October 2003.....................346 APPENDIX II 134 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003. .......................347 20.6 Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year ..........................................................................................................................347 20.7 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year ............................................................................................................347 PIGS PRODUCTION .............................................................................................................................349 21.3.1 Number of Households Rearing Pigs, Herd of Pigs aand Average Head of per Household by Herd Size as of 1st October, 2003 ........................................................................350 21.2 Number of Households Raising Pig by District during 2002/03 Agriculture Year .....................350 21.3 Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 ........................350 LIVESTOCK PESTS AND PARASITE CONTROL..........................................................................351 22.1 Number and Percent of agricultural households reporting to have dewormed livestock during 2002/03 Agriculture Year by District................................................................252 22.2 Number and Percent of agricultural households reporting to have dewormed livestock during 2002/03 Agriculture Year by District and type of dewormed Livestock .........252 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District. ......................................................252 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District. ............................................................................252 OTHER LIVESTOCK............................................................................................................................253 23a: Total number of Other Livestock by Type as of 1st October 2003..............................................254 23b: Number of Households Rearing and number of Other Livestock by Type and District..............254 23c: Number of households with chicken and Category of Chicken by Flock Size............................254 FISH FARMING.....................................................................................................................................255 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year ...........................................................................................................256 28.2 Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year ...........................................................................................................256 28.3 Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year ...........................................................................................................256 28.4 Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year ...........................................................................................................256 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....................256 APPENDIX II 135 LIVESTOCK EXTENSION ..................................................................................................................257 29.1a: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year........................................................................258 29.1b: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year .......................................................258 29.1c: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year.......................................................258 29.1d: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year........................................................259 29.1e: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year........................................................259 29.1f: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year ......................................259 29.1g: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year.......................260 29.1.h: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year ............................................260 29.1i: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.....................................................................261 29.1j: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year...........................................262 29.1h: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .............................................................................................262 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES........................................................263 33.01a: Mean distances from horders dwellings to Infrastructures and services by District ...................264 33.01b: Mean distance from holders dwellings to infrastrures and services by District..........................265 33.01c: Mean distance from holders dwellings to all Weather roads by District.....................................265 33.01d: Mean distance from holders dwellings to Feeder Roads by District...........................................265 33.01e: Mean distance from holders dwellings to Hospital by District ...................................................266 33.01f: Mean distance from holders dwellings to Health Clinic by District............................................266 33.01g: Mean distance from holders dwellings to Primary School by District........................................266 33.1h: Number of Households to Regional Capital ................................................................................267 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year .........................................................................................................................267 APPENDIX II 136 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year .......267 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year .....267 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year .267 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................................268 33.19b Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year .........................................................................................................................268 33. 19c Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year .........................................................................................................................268 33.19d Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year .........................................................................................................................269 33.19e Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year ...........................................................................................................269 33.19f Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year ................................................269 33.19g Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year ...........................................................................................................270 HOUSEHOLDS FACILITIES...............................................................................................................271 34-1: Number of Agricultural Households by Type of TOILET by Districtduring the 2002/03 Agricultural Year .........................................................................................................................372 34-2: Number of Agricultural Households Reported Average Number of Rooms and Type of Roofing Materials by District for the 2002/03 Agricultural Year ..........................................372 34.3: Number of Agricultural Households by Type of Owned Assets and District, 2002/03 Agricultural Year .........................................................................................................................372 34.4 Number of Agricultural Households by Main Source of Energe Used for Lighting and District, 2002/03 Agricultural Year.......................................................................................373 34.5: Number of Agricultural Households by Main Source of Energe Used for Cooking and District, 2002/03 Agricultural Year.......................................................................................373 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year .............................................................374 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year .............................................................374 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year ..................................375 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year ..................................375 APPENDIX II 137 34.10: Number of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year ..................................376 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year ..................................376 34.12: Number of Households by Number of Meals the Household Normally Took per Day by District.....................................................................................................................................377 34.13: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ........................................................................................377 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ........................................................................................378 34-15: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceeding Year by District............................................................378 34-16: Number of Households by Main Source of Income and District, 2002/03 Agricultural Year.....379 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year .........................................................................................................................379 APPENDIX II 138 APPENDIX II: CROPS Type of Agriculture Household....................................................................................................................... Number of Agriculture Households..........................................................................................................239 Rank of Importance of Livelihood activities.............................................................................................241 Households Demographs ..........................................................................................................................245 Land access/ownership..............................................................................................................................251 Land Use ..................................................................................................................................................253 Total annual crop & vege production - long and short rainy season.........................................................257 Annual crop and vege production - short rainy season .............................................................................265 Annual crop and vege production-long rainy season................................................................................275 Permanent Crops .......................................................................................................................................283 Agroprocessing .........................................................................................................................................293 Marketing..................................................................................................................................................297 Irrigation....................................................................................................................................................299 Access to Farm Inputs/ Implements..........................................................................................................303 Agriculture Credit .....................................................................................................................................317 Tree Farming.............................................................................................................................................321 Crop Extension..........................................................................................................................................325 Animal Contribution to crop production...................................................................................................335 Cattle Production.......................................................................................................................................337 Goats Production.......................................................................................................................................341 Sheep Production ......................................................................................................................................345 Pig Production...........................................................................................................................................349 Livestock Pests and Parasite Control ........................................................................................................351 Other livestock ..........................................................................................................................................353 Fish Farming .............................................................................................................................................355 Livestock Extension..................................................................................................................................357 Access to Infrastructure and Other services..............................................................................................363 Household Facilities..................................................................................................................................371 Appendix II 239 NUMBER OF AGRICULTURAL HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 240 Rombo 47,014 94 742 1 47,756 95 2,367 5 50,123 Mwanga 16,749 69 993 4 17,742 73 6,584 27 24,326 Same 29,103 65 890 2 29,993 67 14,481 33 44,474 Moshi Rural 76,826 91 6,480 8 83,306 98 1,556 2 84,862 Hai 46,481 80 4,388 8 50,869 88 7,187 12 58,056 Total 216,173 83 13,493 5 229,666 88 32,175 12 261,841 Livestock Only Crops & Livestock Number % Number % Number % Number % Number % Rombo 9,066 16 0 0 0 0 37,949 24 47,014 22 47,014 9,066 37,949 Mwanga 3,957 7 232 12 35 100 12,525 8 16,749 8 16,749 3,957 12,792 Same 10,597 18 480 25 0 0 18,026 12 29,103 13 29,103 10,597 18,506 Moshi Rural 20,458 35 260 13 0 0 56,108 36 76,826 36 76,826 20,458 56,368 Hai 13,642 24 980 50 0 0 31,859 20 46,481 22 46,481 13,642 32,839 Total 57,719 100 1,951 100 35 100 156,467 100 216,173 100 216,173 57,719 158,453 2.1 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households District Rural Households Involved in Agriculture % of Total Rural Househ olds Rural Households NOT Involved in Agriculture % of Total Rural Househ olds Total Number of Agricultural Households Total Rural Household s Crops Only Pastoralist Total Number of Household s Growing Crops % of Total Rural Househ olds Total Number of Households (From 2002 Pop Census) 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Total Number of Households Rearing Livestock District Type of Agriculture Household % of Total Rural Househo lds Total Urban Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 241 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 242 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 2 1 3 4 6 7 5 Mwanga 1 3 4 2 6 7 5 Same 1 2 3 5 6 7 4 Moshi Rural 1 2 3 4 6 7 5 Hai 1 2 3 4 6 7 5 Total 4 1 2 3 6 7 5 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 9,283 21,822 1,160 14,075 469 0 118 Mwanga 5,657 2,464 721 5,488 1,963 35 114 Same 21,594 1,979 1,473 3,257 1,171 74 148 Moshi Rural 21,148 25,807 1,812 25,086 3,090 0 503 Hai 20,115 10,150 4,611 10,061 891 111 576 Total 77,797 62,222 9,778 57,967 7,584 220 1,458 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 21,088 12,592 8,634 4,116 588 0 932 Mwanga 5,452 4,844 3,207 1,931 359 108 753 Same 5,570 10,454 4,930 5,133 1,822 270 1,802 Moshi Rural 27,805 19,980 17,344 6,611 3,020 136 2,667 Hai 15,900 11,931 8,937 5,143 1,332 101 2,916 Total 75,815 59,800 43,054 22,935 7,121 615 9,069 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 10,804 5,760 19,180 3,993 940 118 5,391 Mwanga 3,663 2,562 3,653 1,867 674 125 2,941 Same 1,238 4,303 7,982 4,340 1,541 287 6,934 Moshi Rural 11,215 8,344 23,406 10,474 3,022 138 9,609 Hai 6,240 8,436 13,991 4,909 570 0 9,774 Total 33,160 29,405 68,212 25,583 6,745 667 34,648 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 3,277 2,527 11,268 8,417 1,396 353 17,455 Mwanga 1,184 1,462 3,958 1,264 1,556 44 2,674 Same 290 2,182 4,126 3,451 3,066 367 8,636 Moshi Rural 6,729 2,259 12,988 5,439 4,780 275 17,484 Hai 1,965 3,629 5,328 5,874 1,292 181 15,894 Total 13,445 12,058 37,668 24,446 12,090 1,219 62,144 3.1d: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance 3.1:The Livelihood Activities/ Source of Income of the Household in Order of Importance by District 3.1a: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 243 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 585 1,399 4,559 2,337 1,508 0 16,039 Mwanga 211 494 844 717 713 0 3,435 Same 0 734 1,326 1,084 1,916 0 4,738 Moshi Rural 1,993 476 6,425 1,827 3,614 259 14,779 Hai 627 1,072 2,538 1,212 1,550 125 9,825 Total 3,417 4,176 15,693 7,178 9,301 384 48,816 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 118 0 350 354 692 0 1,402 Mwanga 0 0 126 88 211 0 651 Same 0 365 292 292 74 74 808 Moshi Rural 138 125 381 271 661 0 4,061 Hai 0 0 107 245 614 0 356 Total 256 490 1,257 1,250 2,252 74 7,278 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Tree / Forest Resources Rombo 118 221 118 0 Mwanga 43 0 44 44 Same 74 74 0 74 Moshi Rural 0 139 0 0 Total 235 434 161 118 3.1f: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance 3.1e: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 244 Appendix II 245 HOUSEHOLDS DEMOGRAPHS: Tanzania Agriculture Sampled Census - 2003 Kilimanjaro Appendix II 246 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Rombo 262,603 42,890 6 21,086 4,124 5 283,689 47,014 6 Mwanga 68,026 11,637 6 21,536 5,111 4 89,563 16,749 5 Same 124,521 24,155 5 19,503 4,948 4 144,024 29,103 5 Moshi Rural 320,784 62,408 5 56,305 14,418 4 377,089 76,826 5 Hai 196,343 39,697 5 24,498 6,785 4 220,842 46,481 5 Total 972,277 180,786 5 142,929 35,386 4 1,115,206 216,173 5 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Rombo 2 1 3 4 6 7 5 Mwanga 1 3 4 2 6 7 5 Same 1 2 3 5 6 7 4 Moshi Rural 1 2 3 4 6 7 5 Hai 1 2 3 5 6 7 4 Total 1 5 4 2 6 7 3 Total 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 247 Male Female Total Number % Number % Number % Less than 4 47,819 52 44,669 48 92,488 100 05 - 09 74,298 47 84,389 53 158,687 100 10 - 14 89,194 50 88,989 50 178,182 100 15 - 19 57,553 47 64,089 53 121,642 100 20 - 24 42,869 49 44,148 51 87,016 100 25 - 29 33,977 48 36,167 52 70,144 100 30 - 34 30,228 47 34,291 53 64,519 100 35 - 39 26,198 49 27,264 51 53,462 100 40 - 44 24,985 47 28,734 53 53,720 100 45 - 49 20,703 44 26,280 56 46,983 100 50 - 54 23,971 49 24,534 51 48,505 100 55 - 59 18,433 57 14,104 43 32,537 100 60 - 64 14,908 51 14,369 49 29,277 100 65 - 69 11,574 51 11,318 49 22,891 100 70 - 74 11,907 52 11,076 48 22,983 100 75 - 79 8,250 60 5,559 40 13,809 100 80 - 84 4,209 49 4,390 51 8,599 100 Above 85 4,141 42 5,621 58 9,762 100 Total 545,216 49 569,990 51 1,115,206 100 Number % Number % Number % Less than 4 47,819 9 44,669 8 92,488 8 05 - 09 74,298 14 84,389 15 158,687 14 10 - 14 89,194 16 88,989 16 178,182 16 15 - 19 57,553 11 64,089 11 121,642 11 20 - 24 42,869 8 44,148 8 87,016 8 25 - 29 33,977 6 36,167 6 70,144 6 30 - 34 30,228 6 34,291 6 64,519 6 35 - 39 26,198 5 27,264 5 53,462 5 40 - 44 24,985 5 28,734 5 53,720 5 45 - 49 20,703 4 26,280 5 46,983 4 50 - 54 23,971 4 24,534 4 48,505 4 55 - 59 18,433 3 14,104 2 32,537 3 60 - 64 14,908 3 14,369 3 29,277 3 65 - 69 11,574 2 11,318 2 22,891 2 70 - 74 11,907 2 11,076 2 22,983 2 75 - 79 8,250 2 5,559 1 13,809 1 80 - 84 4,209 1 4,390 1 8,599 1 Above 85 4,141 1 5,621 1 9,762 1 Total 545,216 100 569,990 100 1,115,206 100 Age Group Sex Male Female Total 3.2: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex 3.3: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 248 Number % Number % Number % Rombo 139,304 49 144,385 51 283,689 100 Mwanga 41,728 47 47,834 53 89,563 100 Same 72,859 51 71,164 49 144,024 100 Moshi Rur 179,916 48 197,173 52 377,089 100 Hai 111,408 50 109,434 50 220,842 100 Total 545,216 49 569,990 51 1,115,206 100 Swahili & English Any Other Language Number % Number % Number % Number % Number % Rombo 187,372 73 32,643 13 230 0 37,925 15 258,169 100 Mwanga 62,085 78 9,110 11 216 0 8,145 10 79,556 100 Same 98,657 76 11,406 9 0 0 19,676 15 129,738 100 Moshi Rural 258,990 74 55,110 16 0 0 37,416 11 351,516 100 Hai 132,991 65 39,688 19 119 0 30,942 15 203,740 100 Total 740,094 72 147,957 14 564 0 134,103 13 1,022,719 100 Attending School Number % Number % Number % Number % Rombo 92,449 36 135,054 52 30,666 12 258,169 100 Mwanga 31,343 39 40,961 51 7,252 9 79,556 100 Same 48,399 37 66,715 51 14,625 11 129,738 100 Moshi Rural 133,184 38 187,488 53 30,843 9 351,516 100 Hai 69,973 34 105,853 52 27,913 14 203,740 100 Total 375,349 37 536,070 52 111,299 11 1,022,719 100 Number % Number % Number % Number % Rombo 99,057 38 1,278 0.5 354 0.1 118 0.0 Mwanga 29,060 37 684 0.9 115 0.1 117 0.1 Same 58,823 45 3,467 2.7 148 0.1 0 0.0 Moshi Rural 119,230 34 4,653 1.3 261 0.1 0 0.0 Hai 87,085 43 6,616 3.2 227 0.1 111 0.1 Total 393,255 38 16,698 1.6 1,105 0.1 346 0.0 District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing District School Attendancy Completed Never Attended to School Total 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity 3.5: HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year 3.4: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 249 Number % Number % Number % Number % Number % Rombo 6,790 3 21,304 8 9,701 4 7,893 3 2,456 1 Mwanga 1,584 2 3,926 5 3,127 4 1,740 2 802 1 Same 1,980 2 2,434 2 1,881 1 1,012 1 370 0 Moshi Rur 9,624 3 24,206 7 17,187 5 9,526 3 3,048 1 Hai 3,562 2 8,000 4 6,201 3 3,992 2 1,766 1 Total 23,540 2 59,869 6 38,097 4 24,164 2 8,443 1 District Rombo 695 0 117 0 1,994 1 87,402 34 15,962 6 Mwanga 290 0 38 0 521 1 30,110 38 4,999 6 Same 1,019 1 142 0 557 0 45,533 35 9,167 7 Moshi Rur 3,446 1 589 0 10,445 3 122,672 35 21,957 6 Hai 1,499 1 338 0 5,798 3 63,490 31 11,548 6 Total 6,950 1 1,224 0 19,316 2 349,207 34 63,633 6 Number % Number % Number % Number % Number % Rombo 98,570 38 13,678 5 69,403 27 76,519 30 258,169 100 Mwanga 28,421 36 6,546 8 24,600 31 19,989 25 79,556 100 Same 57,569 44 6,654 5 35,614 27 29,901 23 129,738 100 Moshi Rural 119,067 34 27,770 8 81,260 23 123,419 35 351,516 100 Hai 85,888 42 13,897 7 47,246 23 56,709 28 203,740 100 Total 389,514 38 68,545 7 258,124 25 306,537 30 1,022,719 100 Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Not Working & Available cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full- time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Government / Parastatal Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 250 Standard One Standard Two Number % Number % Number % Number % Rombo 2,117 2 582 0 2,344 2 2,792 2 Mwanga 209 1 287 1 952 2 869 2 Same 146 0 0 0 786 1 1,210 2 Moshi Rural 1,899 1 1,194 1 2,251 1 3,896 2 Hai 251 0 347 0 1,612 2 2,362 2 Total 4,623 1 2,410 0 7,945 1 11,128 2 Standard Four Standard Five Standard Six Standard Seven Number % Number % Number % Number % Rombo 12,685 9 1,845 1 3,236 2 91,601 68 Mwanga 5,021 12 538 1 996 2 25,993 63 Same 7,723 12 1,572 2 2,962 4 45,831 69 Moshi Rural 18,038 10 2,788 1 6,809 4 111,773 60 Hai 14,251 13 2,387 2 2,252 2 67,658 64 Total 57,717 11 9,130 2 16,254 3 342,855 64 Standard Eight Training After Primary Pre Form One Number % Number % Number % Number % Rombo 1,514 1 4,090 3 0 0 116 0 Mwanga 1,046 3 479 1 88 0 78 0 Same 1,727 3 363 1 132 0 0 0 Moshi Rural 5,254 3 3,309 2 413 0 553 0 Hai 3,185 3 2,002 2 221 0 196 0 Total 12,725 2 10,244 2 854 0 943 0 Number % Number % Number % Number % Rombo 1,025 1 116 0 7,587 6 0 0 Mwanga 722 2 111 0 2,296 6 0 0 Same 586 1 74 0 3,025 5 0 0 Moshi Rural 2,701 1 978 1 17,027 9 182 0 Hai 856 1 376 0 5,707 5 0 0 Total 5,891 1 1,656 0 35,642 7 182 0 Number % Number % Number % Number % Number % Rombo 1,177 1 935 1 350 0 942 1 135,054 100 Mwanga 214 1 347 1 199 0 516 1 40,961 100 Same 74 0 362 1 0 0 143 0 66,715 100 Moshi Rural 2,927 2 2,962 2 1,618 1 916 0 187,488 100 Hai 123 0 1,218 1 348 0 500 0 105,853 100 Total 4,515 1 5,824 1 2,515 0 3,017 1 536,070 100 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Form Five cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District District District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Under Standard On Standard Three University & Other Tertiary Education Form Two Form Three Form Four Adult Education Total Education Level District Form One cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Form Six Training After Secondary Education Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 251 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 252 Total Number of Households No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % % Rombo 455 1 45,064 96 6,068 13 7,935 17 8,802 19 812 2 1,879 4 47,014 Mwanga 834 5 14,807 88 1,591 9 1,189 7 3,767 22 307 2 476 3 16,749 Same 5,343 18 23,619 81 7,611 26 2,798 10 6,643 23 587 2 1,756 6 29,103 Moshi Rural 4,348 6 65,742 86 9,679 13 14,425 19 6,855 9 3,834 5 4,533 6 76,826 Hai 1,300 3 38,618 83 11,136 24 12,980 28 3,694 8 3,179 7 6,077 13 46,481 Total 12,280 6 187,850 87 36,085 17 39,327 18 29,761 14 8,718 4 14,722 7 216,173 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Rombo 138 31,119 4,179 3,777 3,223 339 495 43,271 Mwanga 857 17,309 1,112 561 1,827 93 489 22,248 Same 6,386 26,730 6,041 1,251 3,618 171 897 45,093 Moshi Rural 2,976 49,759 8,786 5,533 2,663 1,692 2,303 73,711 Hai 2,969 64,352 11,182 7,122 1,315 2,582 2,431 91,953 Total 13,326 189,269 31,300 18,244 12,646 4,876 6,615 276,276 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Land Access Households with Area Leased/Certificate of Ownership Households with Area Owned Under Customary Law Households with Area Bought From Others Households with Area Rented From Others Households with Area Borrowed From Others Households with Area Shared Croped From Others Households with Area under Other Forms of Tenure District Land Access/ Ownership (Hectare) 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 253 LAND USE Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 254 Households with Area under Temporary Mono Crops Households with Area under Temporary Mixed Crops Households with Area under Permanent Mono Crops Households with Area under Permanent Mixed Crops Households with Area under Permanent / Annual Mix Households with Area under Pasture Households with Area under Fallow Households with Area under Natural Bush Households with Area under Planted Trees Households with Area Rented to Others Households with Area Unusable Households with Area of Uncultivated Usable Land Total Number of Household s Rombo 4,160 27,385 586 19,286 23,640 8,139 825 115 18,455 1,060 354 471 47,014 Mwanga 8,879 9,279 3,470 6,558 1,788 1,640 1,647 261 6,178 329 426 2,908 16,749 Same 16,547 18,584 6,283 8,728 10,117 1,843 5,941 518 6,290 1,470 1,372 4,522 29,103 Moshi Rural 23,783 33,240 6,014 43,596 8,787 1,721 1,713 0 22,231 1,633 687 2,339 76,826 Hai 14,050 30,751 3,104 25,295 5,832 1,320 1,820 250 13,851 1,529 8,376 1,740 46,481 Total 67,419 119,239 19,457 103,463 50,164 14,662 11,946 1,144 67,004 6,021 11,214 11,980 216,173 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Rombo 2,588 14,256 105 8,801 12,589 2,394 356 2 1,043 758 179 205 43,275 Mwanga 6,349 5,001 1,148 3,128 963 466 876 92 975 308 477 2,510 22,293 Same 12,431 12,246 1,967 3,839 5,482 519 3,292 225 1,031 831 593 2,638 45,093 Moshi Rural 18,088 15,907 2,995 23,484 3,784 435 1,894 . 3,571 1,644 334 1,576 73,711 Hai 9,843 21,229 894 12,997 3,850 14,265 21,456 38 3,240 1,266 1,305 1,570 91,953 Total 49,298 68,639 7,108 52,249 26,668 18,080 27,873 357 9,859 4,807 2,888 8,499 276,325 % 18 25 3 19 10 7 10 0 4 2 1 3 100 Land Use Area District 5.1 LAND USE: Area of Land by type of Land Use and District during 2002/03 Agricultural Year 5.2 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Type of Land Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 255 Was all Land Available to the Hh Used During 2002/03? Do you Consider that you have sufficient land for the Hh? Total Total Number Percent Number Percent Number Number Percent Number Percent Number Rombo 42,672 91 4,342 9 47,014 Rombo 13,130 28 33,884 72 47,014 Mwanga 11,000 67 5,482 33 16,482 Mwanga 8,700 53 7,782 47 16,482 Same 17,702 62 10,921 38 28,623 Same 13,571 47 15,052 53 28,623 Moshi Rural 71,162 93 5,404 7 76,566 Moshi Rural 23,377 31 53,189 69 76,566 Hai 41,354 91 4,147 9 45,501 Hai 7,153 16 38,348 84 45,501 Total 183,891 86 30,296 14 214,187 Total 65,932 31 148,255 69 214,187 Number Percent Number Percent Number Percent Rombo 5,332 11 41,682 89 47,014 100 Mwanga 2,011 12 14,472 88 16,482 100 Same 4,221 15 24,402 85 28,623 100 Moshi Rural 10,619 14 65,947 86 76,566 100 Hai 8,292 18 37,210 82 45,501 100 Total 30,474 14 183,713 86 214,187 100 District Yes No 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Yes No Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 256 Appendix II 257 TOTAL ANNUAL CROP AND VEGE PRODUCTION – LONG AND SHORT RAINY SEASON anzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 258 Number of Households Planted Area Number of Households Planted Area Rombo 110,954 26,804 75,882 18,640 45,444 59 Mwanga 26,169 8,139 26,762 8,822 16,960 48 Same 54,231 21,782 33,624 15,410 37,192 59 Moshi Rural 32,733 6,662 98,542 31,902 38,564 17 Hai 19,606 5,873 80,968 30,220 36,093 16 Total 243,693 69,259 315,777 104,994 174,253 40 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Rombo 43,266 3,748 34,155 12,859 77,422 Mwanga 13,492 3,257 13,806 2,943 27,298 Same 25,777 3,326 20,161 8,941 45,938 Moshi Rural 20,544 56,281 53,763 23,063 74,307 Hai 12,926 33,555 41,225 5,256 54,151 Total 116,006 100,167 163,110 53,063 279,115 7.1 & 7.2a: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) by season and District District Total Area Planted (hectare) % Area planted in Short Rainy season Long Rainy Season 7.1 & 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District Total Number of Crop Growing Households Long Rainy Season Short Rainy Season District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 259 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 39,973 38,062 952 63,594 79,128 1,244 103,567 117,190 1,132 Maize 38,275 33,360 872 58,318 71,861 1,232 96,593 105,222 1,089 Paddy 1,443 4,586 3,177 1,585 6,138 3,871 3,029 10,724 3,541 Sorghum 116 78 667 137 69 502 253 146 578 Finger Millet 139 38 273 3,553 1,060 298 3,692 1,098 297 ROOTS & TUBERS 3,940 10,654 2,704 5,545 10,385 1,873 9,485 21,040 2,218 Cassava 820 652 794 3,290 1,977 601 4,111 2,628 639 Sweet Potatoes 605 960 1,586 280 322 1,150 886 1,283 1,448 Irish Potatoes 1,618 8,334 5,151 1,398 7,257 5,193 3,016 15,592 5,170 Yams 237 172 728 90 244 2,704 327 417 1,274 Cocoyam 659 536 813 486 584 1,202 1,145 1,120 978 PULSES 18,361 7,415 404 28,590 11,183 391 46,950 18,598 396 Mung Beans 13 2 148 233 99 426 247 101 410 Beans 17,221 6,918 402 27,062 10,704 396 44,284 17,622 398 Cowpeas 814 325 398 1,004 237 236 1,819 561 309 Green Gram 308 169 549 260 92 352 568 261 459 Field Peas 4 2 494 30 51 1,729 33 53 1,598 OIL SEEDS & OIL NUTS 4,442 1,973 444 5,358 3,306 617 9,800 5,279 539 Sunflower 2,955 1,445 489 3,338 2,279 683 6,293 3,724 592 Simsim 14 0 0 80 19 239 94 19 204 Groundnuts 1,474 528 358 1,939 1,008 520 3,413 1,536 450 FRUITS & VEGETABLES 2,543 12,466 4,902 1,887 10,743 5,695 4,430 23,209 5,239 Okra 14 57 4,150 . . Bitter Aubergine . . 4 2 570 4 2 570 Onions 206 1,255 6,078 138 1,496 10,879 344 2,751 7,997 Ginger 464 1,453 3,134 4 0 99 468 1,453 3,105 Cabbage 91 445 4,861 326 980 3,011 417 1,425 3,417 Tomatoes 882 5,971 6,771 481 5,250 10,926 1,362 11,220 8,237 Spinnach 127 154 1,216 156 327 2,100 283 481 1,703 Carrot 220 1,148 5,226 163 1,127 6,896 383 2,275 5,938 Chillies 144 431 3,000 208 750 3,609 351 1,181 3,360 Amaranths 265 1,131 4,265 215 450 2,089 480 1,581 3,290 Pumpkins 23 10 450 5 0 69 28 11 384 Cucumber 39 228 5,872 41 212 5,211 79 440 5,534 Egg Plant 18 83 4,509 . . Water Mellon 50 100 1,997 96 129 1,342 146 229 1,566 Cauliflower . . 51 19 371 51 19 371 CASH CROPS 22 13 599 22 13 599 Tobacco . . 22 13 599 22 13 599 Total 69,259 70,570 104,994 114,759 174,253 185,328 Table 7.1 & 7.2c: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 260 Crop Number of Households Area Planted (ha) Number of Households Area Planted (ha) CEREALS 105,257 39,973 144,341 63,594 103,567 38.6 Maize 99,941 38,275 128,816 58,318 96,593 39.6 Paddy 3,698 1,443 3,164 1,585 3,029 47.7 Sorghum 689 116 714 137 253 45.9 Finger Millet 929 139 11,647 3,553 3,692 3.8 ROOTS & TUBERS 19,180 3,940 18,514 5,545 9,485 41.5 Cassava 4,506 820 8,028 3,290 4,111 20.0 Sweet Potatoes 3,772 605 2,042 280 886 68.3 Irish Potatoes 4,484 1,618 2,823 1,398 3,016 53.7 Yams 1,568 237 1,317 90 327 72.4 Cocoyam 4,850 659 4,304 486 1,145 57.6 PULSES 81,251 18,361 18,361 100.0 Mung Beans 67 13 603 233 247 5.5 Beans 73,082 17,221 103,410 27,062 44,284 38.9 Cowpeas 5,884 814 6,068 1,004 1,819 44.8 Green Gram 2,175 308 1,777 260 568 54.2 Field Peas 43 4 73 30 33 10.6 OIL SEEDS & OIL NUTS 22,765 4,442 27,726 5,358 9,800 45.3 Sunflower 15,250 2,955 20,235 3,338 6,293 47.0 Simsim 136 14 396 80 94 14.7 Groundnuts 7,379 1,474 7,096 1,939 3,413 43.2 FRUITS & VEGETABLES 15,241 2,543 13,029 1,887 4,430 57.4 Okra 136 14 0 . Bitter Aubergine 0 . 73 4 4 0.0 Onions 1,415 206 383 138 344 60.0 Ginger 1,286 464 43 4 468 99.1 Cabbage 808 91 2,645 326 417 21.9 Tomatoes 5,012 882 2,989 481 1,362 64.7 Spinnach 1,118 127 1,872 156 283 44.9 Carrot 688 220 441 163 383 57.3 Chillies 982 144 867 208 351 40.9 Amaranths 2,849 265 2,806 215 480 55.2 Pumpkins 145 23 67 5 28 82.7 Cucumber 485 39 447 41 79 48.8 Egg Plant 182 18 0 . Water Mellon 135 50 271 96 146 34.2 Cauliflower 0 . 125 51 CASH CROPS 0 0 236 22 22 0.0 Tobacco 0 . 236 22 22 Total 69,259 104,994 174,253 40 Table 7.1 & 7.2d: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Area Planted Short & Long seasons % Area Planted in Short Rainy Season Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 261 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 12,731 8,254 20,931 14,020 12,731 22,274 49 Mwanga 2,263 1,530 2,035 1,147 2,263 2,677 16 Same 3,679 3,233 5,431 5,294 3,679 8,527 23 Moshi Rural 6,608 5,500 2,102 741 6,608 6,242 16 Hai 7,762 7,372 3,892 1,959 7,762 9,331 26 Total 33,043 25,889 34,391 23,162 33,043 49,051 28 District Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 118 119 1,423 1,487 118 1,606 4 Mwanga 127 51 174 128 127 179 1 Same 209 188 507 469 209 657 2 Moshi Rural 2,901 2,347 389 113 2,901 2,460 6 Hai 1,702 2,169 1,771 974 1,702 3,143 9 Total 5,057 4,874 4,264 3,171 5,057 8,045 5 7.1 & 7.2iTOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Long & Short Rainy Seasons- Kilimanjaro region. % of Planted Area using Insecticide Total Herbicide Use Insecticide Use Insecticide Use 7.1 & 7.2h TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Long & Short Rainy Seasons - Kilimanjaro region. Insecticide Use % of Planted Area using Insecticide Insecticide Use Insecticide Use Total District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 262 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Rombo 706 971 1,038 425 32,411 16,264 32,411 45,444 Mwanga 1,114 858 1,056 614 11,636 7,168 11,636 16,960 Same 1,037 742 1,213 845 17,912 12,027 17,912 37,192 Moshi Rural 23,632 19,497 3,765 2,066 26,366 10,339 26,366 38,564 Hai 20,823 13,756 7,717 8,818 12,686 7,645 12,686 36,093 Total 47,312 35,824 14,788 12,769 101,010 53,443 101,010 174,253 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Total Planted Area Rombo 11,961 23,394 1,096 1,294 1,514 4,891 19,584 10,218 18,640 Mwanga 4,599 5,542 163 226 685 895 8,358 5,744 8,822 Same 3,901 13,136 4,199 5,378 1,404 2,621 12,265 7,849 15,410 Moshi Rural 12,666 11,226 855 453 20,485 12,812 19,756 12,883 31,902 Hai 6,004 6,043 364 227 16,275 12,864 18,582 14,949 30,220 Total 39,131 59,341 6,679 7,579 40,363 34,082 78,545 51,644 104,994 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 940 1,033 940 44,411 940 18,640 5 Mwanga 2,974 3,280 2,974 13,680 2,974 8,822 34 Same 9,190 13,626 9,190 23,566 9,190 15,410 60 Moshi Rural 8,393 7,838 8,393 30,726 8,393 31,902 26 Hai 3,368 4,856 3,368 31,237 3,368 30,220 11 Total 24,864 30,633 24,864 143,620 24,864 104,994 24 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Long & Short Rainy Season - Kilimanjaro Region. 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Longt & Short Rainy Seasons - Kilimanjaro Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Long & Short Rainy season - Kilimanjaro Region. % of Planted Area using Irrigation Household Using Irrigation District Irrigation Use District Fertilisers Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Household NOT Using Irrigation Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 263 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 543 213 33,612 18,427 34,155 18,640 1 Mwanga 684 479 13,121 8,342 13,806 8,822 5 Same 721 451 21,048 14,959 21,769 15,410 3 Moshi Rural 2,148 1,880 51,615 30,023 53,763 31,902 6 Hai 4,454 3,962 36,771 26,258 41,225 30,220 13 Total 8,551 6,985 156,167 98,010 164,718 104,994 7 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 12,071 25,173 22,084 25,173 34,155 45,444 55 Mwanga 5,329 7,333 8,477 7,333 13,806 16,960 43 Same 7,719 15,440 12,442 15,440 21,769 37,192 42 Moshi Rural 37,207 27,475 16,555 27,475 53,763 38,564 71 Hai 27,301 22,778 13,924 22,778 41,225 36,093 63 Total 89,627 98,198 73,483 98,198 164,718 174,253 56 7.1 $ 7.2j: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG SEASON District Fungicide Use % of area planted using Fungicides Households Using Fungicide Households Not Using Fungicide Total 7.1&7.2k: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG & SHORT Rainy Seasons District Improved Seed Use % of area planted using Improved Seeds Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 264 Appendix II 265 ANNUAL CROP AND VEGE PRODUCTION- LONG RAINY SEASON anzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 266 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Rombo 584 977 1,393 860 41,289 24,967 43,266 26,804 Mwanga 232 140 764 545 12,496 7,453 13,492 8,139 Same 566 430 364 389 24,847 20,963 25,777 21,782 Moshi Rural 1,685 639 2,403 684 16,456 5,339 20,544 6,662 Hai 796 471 2,158 1,120 9,973 4,282 12,926 5,873 Total 3,863 2,657 7,082 3,598 105,061 63,004 116,006 69,259 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Rombo 28,672 16,715 545 701 4,317 3,741 9,732 5,646 43,266 26,804 Mwanga 5,743 3,103 283 137 399 345 7,068 4,553 13,492 8,139 Same 10,459 9,943 2,195 1,813 2,180 1,819 10,943 8,208 25,777 21,782 Moshi Rural 10,099 3,063 477 165 5,795 2,244 4,173 1,190 20,544 6,662 Hai 4,614 1,890 73 59 3,840 1,913 4,399 2,011 12,926 5,873 Total 59,587 34,715 3,573 2,875 16,530 10,061 36,315 21,608 116,006 69,259 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 235 81 43,031 26,723 43,266 26,804 0.3 Mwanga 1,925 1,111 11,567 7,027 13,492 8,139 13.7 Same 7,789 6,783 17,988 14,999 25,777 21,782 31.1 Moshi Rural 4,651 1,487 15,893 5,175 20,544 6,662 22.3 Hai 4,001 1,641 8,925 4,232 12,926 5,873 27.9 Total 18,602 11,103 97,404 58,156 116,006 69,259 16.0 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-Short Rainy Season, Kilimanjaro Region District District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Compost 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - SHORT SEASON, Kilimanjaro Region. Household Using Irrigation Mostly Farm Yard Manure Household NOT Using Irrigation Total 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, SHORT SEASON, Kilimanjaro Region. Irrigation Use % of Planted Area using Irrigation District Mostly Inorganic Fertilizer No Fertilizer Applied Total Fertilisers Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 267 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 20,931 14,020 22,335 12,783 43,266 26,804 Mwanga 2,035 1,147 11,457 6,992 13,492 8,139 Same 5,431 5,294 20,346 16,488 25,777 21,782 Moshi Rural 2,102 741 18,442 5,921 20,544 6,662 Hai 3,892 1,959 9,034 3,914 12,926 5,873 Total 34,391 23,162 81,614 46,097 116,006 69,259 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 1,423 1,487 41,843 25,317 43,266 26,804 6 Mwanga 174 128 13,318 8,011 13,492 8,139 2 Same 507 469 25,270 21,313 25,777 21,782 2 Moshi Rural 389 113 20,155 6,549 20,544 6,662 2 Hai 1,771 974 11,155 4,899 12,926 5,873 17 Total 4,264 3,171 111,741 66,088 116,006 69,259 5 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District, SHORT RAINY SEASON, Kilimanjaro Region. District Herbicide Use Household Using Irrigation Household NOT Using Irrigation Total District Insecticide Use Household Using Insecticides % Planted Area using Herbicide Household NOT Using Insecticides Total 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District, SHORT SEASON, Kilimanjaro Region Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 268 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 926 687 42,341 26,117 43,266 26,804 3 Mwanga 206 93 13,286 8,046 13,492 8,139 1 Same 1,319 1,661 24,458 20,120 25,777 21,782 8 Moshi Rural 836 211 19,708 6,451 20,544 6,662 3 Hai 2,848 1,743 10,078 4,130 12,926 5,873 30 Total 6,135 4,394 109,871 64,865 116,006 69,259 6 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 26,787 17,608 16,479 9,196 43,266 26,804 66 Mwanga 5,998 4,015 7,494 4,124 13,492 8,139 49 Same 9,365 8,820 16,412 12,962 25,777 21,782 40 Moshi Rural 12,725 4,793 7,819 1,869 20,544 6,662 72 Hai 6,333 2,450 6,593 3,423 12,926 5,873 42 Total 61,210 37,685 54,796 31,574 116,006 69,259 54 % Planted Area using Fungicides Household Using Fungicides Household NOT Using Fungicides Total 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District SHORT RAINY SEASON, Kilimanjaro Region. District Improved Seed Use % Planted Area using Improved Seeds Household Using Improved Seeds Household NOT Using Improved Seeds Total 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, SHORT RAINY SEASON, Kilimanjaro Region District Fungicide Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 269 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Rombo 706 971 1,038 425 32,411 16,264 34,155 17,659 Mwanga 1,114 858 1,056 614 11,636 7,168 13,806 8,639 Same 1,037 742 1,213 845 17,912 12,027 20,161 13,615 Moshi Rural 23,632 19,497 3,765 2,066 26,366 10,339 53,763 31,902 Hai 20,823 13,756 7,717 8,818 12,686 7,645 41,225 30,220 Total 47,312 35,824 14,788 12,769 101,010 53,443 163,110 102,036 % 29 35 9 13 62 52 163,110 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Total Planted Area Rombo 11,961 6,679 1,096 593 1,514 1,150 19,584 10,218 34,155 18,640 Mwanga 4,599 2,439 163 89 685 550 8,358 5,744 13,806 8,822 Same 3,901 3,194 4,199 3,565 1,404 802 12,265 7,849 21,769 15,410 Moshi Rural 12,666 8,163 855 288 20,485 10,568 19,756 12,883 53,763 31,902 Hai 6,004 4,152 364 168 16,275 10,951 18,582 14,949 41,225 30,220 Total 39,131 24,626 6,679 4,703 40,363 24,021 78,545 51,644 164,718 104,994 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Rombo 940 952 33,215 17,688 34,155 18,640 5 Mwanga 2,974 2,169 10,832 6,653 13,806 8,822 25 Same 9,190 6,843 12,579 8,567 21,769 15,410 44 Moshi Rural 8,393 6,352 45,370 25,551 53,763 31,902 20 Hai 3,368 3,215 37,857 27,005 41,225 30,220 11 Total 24,864 19,530 139,854 85,464 164,718 104,994 19 % 15 19 85 81 100 100 19 Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, LONG RAINY SEASON, Kilimanjaro Region District Soil Preparation Mostly Tractor Ploughing Fertilisers Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During LONG RAINY SEASON District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of Area Planted Under Irrigation in Long Rainy Season District 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District LONG RAINY SEASON, Kilimanjaro Region Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 270 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 12,731 8,254 21,424 10,387 34,155 18,640 Mwanga 2,263 1,530 11,543 7,291 13,806 8,822 Same 3,679 3,233 18,090 12,177 21,769 15,410 Moshi Rural 6,608 5,500 47,155 26,402 53,763 31,902 Hai 7,762 7,372 33,463 22,848 41,225 30,220 Total 33,043 25,889 131,675 79,105 164,718 104,994 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 118 119 34,037 18,521 34,155 18,640 1 Mwanga 127 51 13,679 8,771 13,806 8,822 1 Same 209 188 21,561 15,222 21,769 15,410 1 Moshi Rural 2,901 2,347 50,861 29,555 53,763 31,902 7 Hai 1,702 2,169 39,523 28,051 41,225 30,220 7 Total 5,057 4,874 159,661 100,120 164,718 104,994 5 Total Number of Households Number % Number % Number Rombo 41,831 89 5,183 11 47,014 Mwanga 10,443 62 6,306 38 16,749 Same 18,721 64 10,382 36 29,103 Moshi Rural 64,370 84 12,456 16 76,826 Hai 32,344 70 14,137 30 46,481 Total 167,709 78 48,464 22 216,173 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District LONG RAINY SEASON, Kilimanjaro Region District Insecticide Use Households Using Pesticide Households Not Using Pesticide Total 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District LONG RAINY SEASON, Kilimanjaro Region. 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03 District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total Households that Sold Produce Households that Did not Sold Produce District % of Area Planted Using Herbicide Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 271 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 543 213 33,612 18,427 34,155 18,640 1 Mwanga 684 479 13,121 8,342 13,806 8,822 5 Same 721 451 21,048 14,959 21,769 15,410 3 Moshi Rural 2,148 1,880 51,615 30,023 53,763 31,902 6 Hai 4,454 3,962 36,771 26,258 41,225 30,220 13 Total 8,551 6,985 156,167 98,010 164,718 104,994 7 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Rombo 12,071 7,565 22,084 10,095 34,155 17,659 43 Mwanga 5,329 3,318 8,477 5,321 13,806 8,639 38 Same 7,719 6,621 12,442 6,994 20,161 13,615 49 Moshi Rural 37,207 22,682 16,555 9,220 53,763 31,902 71 Hai 27,301 20,327 13,924 9,893 41,225 30,220 67 Total 89,627 60,513 73,483 41,523 163,110 102,036 59 55 59 45 41 100 100 59 % of Planted Area Using Fungicide 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 LONG RAINY SEASON, Kilimanjaro Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total % of Planted Area Using Improved Seed 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, LONG RAINY SEASON, Kilimanjaro Region District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 272 Mostly Bush Clearancestly Hand SlashingTractor Slashing Mostly BurningNo Land Clearing Total No of Househ olds Planted Area No of Househo lds Planted Area No of House holds Planted Area No of Househ olds Planted Area No of House holds Planted Area No of Househ olds Planted Area Rombo Maize 234 19 3,057 1,076 0 . 0 . 11,274 2,568 14,565 3,664 Sorghum 0 . 0 . 0 . 0 . 236 48 236 48 Finger Millet 0 . 2,233 490 0 . 0 . 8,689 2,893 10,922 3,382 CEREALS 234 19 5,290 1,566 0 . 0 . 20,198 5,508 25,722 7,094 Cassava 0 . 0 . 0 . 0 . 587 136 587 136 Sweet Potatoes 0 . 0 . 0 . 0 . 118 48 118 48 Irish Potatoes 0 . 0 . 0 . 0 . 427 140 427 140 Yams 0 . 590 15 0 . 0 . 472 64 1,061 80 Cocoyam 0 . 1,296 131 0 . 0 . 470 125 1,766 257 ROOTS & TUBERS 0 . 1,886 147 0 . 0 . 2,073 514 3,959 661 Beans 234 143 4,557 1,288 235 89 0 . 19,142 5,093 24,168 6,613 Cowpeas 118 43 1,767 195 0 . 0 . 2,789 462 4,674 699 Green Gram 0 . 1,059 108 0 . 0 . 353 72 1,413 180 PULSES 352 186 7,383 1,590 235 89 0 . 22,284 5,628 30,255 7,493 Sunflower 0 . 1,532 187 236 48 0 . 7,831 1,233 9,599 1,467 Simsim 0 . 0 . 0 . 0 . 118 24 118 24 Groundnuts 0 . 353 42 0 . 0 . 3,875 791 4,228 833 OIL SEEDS & OIL NUTS 0 . 1,886 229 236 48 0 . 11,824 2,048 13,945 2,324 Cabbage 0 . 0 . 0 . 0 . 118 2 118 2 Amaranths 0 . 0 . 0 . 0 . 118 2 118 2 FRUITS & VEGETABLES 0 . 0 . 0 . 0 . 236 5 236 5 Total 586 205 16,445 3,532 471 137 0 . 56,615 13,702 74,117 17,576 Mwanga Maize 559 157 5,698 2,718 0 . 0 . 5,735 2,536 11,993 5,410 Paddy 0 . 38 11 43 17 0 . 38 8 118 36 Sorghum 0 . 0 . 0 . 0 . 43 9 43 9 CEREALS 559 157 5,736 2,729 43 17 0 . 5,816 2,552 12,154 5,455 Cassava 43 4 44 21 0 . 0 . 87 18 174 43 Sweet Potatoes 0 . 466 65 0 . 0 . 687 86 1,153 152 Irish Potatoes 0 . 0 . 0 . 0 . 86 6 86 6 Cocoyam 0 . 88 9 0 . 0 . 470 49 557 58 ROOTS & TUBERS 43 4 597 95 0 . 0 . 1,330 159 1,970 259 Mung Beans 0 . 43 12 0 . 0 . 0 . 43 12 Beans 477 88 4,169 1,194 43 13 0 . 4,776 1,135 9,465 2,430 Cowpeas 0 . 498 99 0 . 0 . 643 107 1,141 206 Green Gram 0 . 120 32 0 . 0 . 244 49 364 80 PULSES 477 88 4,830 1,337 43 13 0 . 5,663 1,291 11,012 2,728 Groundnuts 0 . 40 32 0 . 0 . 174 33 214 65 OIL SEEDS & OIL NUTS 0 . 40 32 0 . 0 . 174 33 214 65 Ginger 0 . 0 . 0 . 0 . 43 4 43 4 Cabbage 73 10 131 27 0 . 0 . 0 . 205 37 Tomatoes 30 6 190 31 0 . 0 . 38 3 259 40 Spinnach 0 . 130 11 0 . 0 . 42 14 173 25 Chillies 0 . 0 . 0 . 0 . 43 4 43 4 Amaranths 0 . 43 2 0 . 0 . 171 15 214 16 FRUITS & VEGETABLES 103 17 495 71 0 . 0 . 338 40 936 128 Total 1,183 266 11,698 4,264 86 30 0 . 13,320 4,074 26,287 8,635 Same Maize 207 92 5,859 2,501 0 . 0 . 4,776 4,232 10,842 6,825 Paddy 0 . 0 . 0 . 0 . 68 28 68 28 CEREALS 207 92 5,859 2,501 0 . 0 . 4,844 4,260 10,910 6,853 Cassava 0 . 73 30 0 . 0 . 68 14 142 43 Sweet Potatoes 0 . 439 61 0 . 0 . 0 . 439 61 Irish Potatoes 0 . 293 22 0 . 0 . 0 . 293 22 Cocoyam 0 . 0 . 0 . 0 . 67 16 67 16 ROOTS & TUBERS 0 . 806 113 0 . 0 . 135 30 940 143 Mung Beans 0 . 353 165 0 . 0 . 208 56 561 221 Beans 369 157 10,367 4,153 0 . 0 . 2,154 656 12,889 4,966 PULSES 369 157 10,719 4,318 0 . 0 . 2,362 712 13,450 5,187 Bitter Aubergine 0 . 73 4 0 . 0 . 0 . 73 4 Onions 0 . 74 7 0 . 0 . 68 28 142 35 Cabbage 0 . 222 19 0 . 0 . 0 . 222 19 Tomatoes 0 . 221 30 0 . 0 . 215 29 436 59 Carrot 0 . 74 7 0 . 0 . 0 . 74 7 Chillies 0 . 74 15 0 . 0 . 67 32 141 47 Water Mellon 0 . 0 . 0 . 0 . 136 69 136 69 FRUITS & VEGETABLES 0 . 739 83 0 . 0 . 486 158 1,225 241 Total 575 249 18,123 7,015 0 . 0 . 7,827 5,159 26,525 12,423 Moshi Rural Maize 3,778 1,770 32,794 16,757 2,208 803 0 . 12,457 3,139 51,236 22,469 Paddy 938 570 1,343 676 0 . 0 . 0 . 2,281 1,246 Sorghum 0 . 190 26 0 . 0 . 0 . 190 26 Land Clearing District 7.2h ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 273 Mostly Bush Clearancestly Hand SlashingTractor Slashing Mostly BurningNo Land Clearing Total No of Househ olds Planted Area No of Househo lds Planted Area No of House holds Planted Area No of Househ olds Planted Area No of House holds Planted Area No of Househ olds Planted Area Land Clearing District 7.2h ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop Finger Millet 0 . 123 12 0 . 0 . 136 28 259 40 CEREALS 4,716 2,340 34,449 17,472 2,208 803 0 . 12,593 3,167 53,966 23,781 Cassava 0 . 139 28 0 . 0 . 0 . 139 28 Sweet Potatoes 0 . 0 . 0 . 0 . 133 2 133 2 Irish Potatoes 0 . 0 . 0 . 0 . 398 12 398 12 Yams 0 . 131 1 0 . 0 . 0 . 131 1 Cocoyam 0 . 804 56 0 . 0 . 1,066 94 1,870 151 ROOTS & TUBERS 0 . 1,074 85 0 . 0 . 1,596 108 2,670 193 Beans 1,308 348 16,545 3,684 764 74 0 . 6,863 907 25,480 5,014 Cowpeas 0 . 0 . 134 27 0 . 0 . 134 27 PULSES 1,308 348 16,545 3,684 898 101 0 . 6,863 907 25,614 5,041 Sunflower 0 . 3,464 623 227 15 138 28 2,210 352 6,039 1,018 Simsim 0 . 278 56 0 . 0 . 0 . 278 56 Groundnuts 329 67 975 407 0 . 0 . 115 47 1,419 520 OIL SEEDS & OIL NUTS 329 67 4,716 1,087 227 15 138 28 2,326 398 7,736 1,595 Cabbage 0 . 689 117 0 . 0 . 1,081 95 1,769 212 Tomatoes 0 . 631 130 0 . 0 . 133 1 764 130 Spinnach 137 28 752 52 0 . 0 . 404 9 1,294 89 Chillies 0 . 0 . 0 . 0 . 267 82 267 82 Amaranths 136 33 1,078 90 0 . 0 . 399 8 1,613 131 Pumpkins 0 . 67 5 0 . 0 . 0 . 67 5 Cucumber 0 . 67 8 0 . 0 . 135 14 201 22 Water Mellon 0 . 0 . 0 . 0 . 135 27 135 27 FRUITS & VEGETABLES 273 61 3,283 402 0 . 0 . 2,553 235 6,109 698 Total 6,627 2,815 60,067 22,730 3,333 920 138 28 25,931 4,816 96,096 31,309 Hai Maize 2,005 1,306 22,408 9,374 1,955 1,631 335 374 11,413 6,433 38,115 19,118 Paddy 0 . 576 212 0 . 0 . 120 63 697 275 Sorghum 0 . 125 30 0 . 0 . 120 24 245 55 Finger Millet 0 . 0 . 0 . 0 . 348 78 348 78 CEREALS 2,005 1,306 23,109 9,616 1,955 1,631 335 374 12,002 6,599 39,405 19,527 Cassava 0 . 368 51 0 . 0 . 243 30 611 81 Sweet Potatoes 0 . 0 . 0 . 0 . 125 10 125 10 Irish Potatoes 76 31 1,411 1,181 0 . 0 . 0 . 1,487 1,212 Yams 0 . 125 10 0 . 0 . 0 . 125 10 ROOTS & TUBERS 76 31 1,904 1,242 0 . 0 . 368 40 2,348 1,313 Beans 1,720 543 18,387 3,668 1,838 636 96 10 7,127 2,314 29,167 7,170 Cowpeas 0 . 0 . 0 . 0 . 119 72 119 72 Field Peas 0 . 73 30 0 . 0 . 0 . 73 30 PULSES 1,720 543 18,460 3,697 1,838 636 96 10 7,246 2,386 29,359 7,272 Sunflower 107 11 3,025 476 232 94 0 . 863 150 4,227 731 Groundnuts 118 24 438 83 0 . 0 . 583 376 1,139 483 OIL SEEDS & OIL NUTS 225 35 3,463 559 232 94 0 . 1,447 525 5,367 1,213 Onions 0 . 120 29 0 . 0 . 120 73 241 102 Cabbage 0 . 126 25 0 . 0 . 0 . 126 25 Tomatoes 0 . 615 140 0 . 0 . 844 103 1,458 243 Spinnach 0 . 96 19 0 . 0 . 238 20 333 39 Carrot 0 . 367 156 0 . 0 . 0 . 367 156 Chillies 0 . 344 59 0 . 0 . 0 . 344 59 Amaranths 0 . 375 48 0 . 0 . 351 13 725 61 Cucumber 0 . 125 13 0 . 0 . 120 6 245 19 Cauliflower 0 . 125 51 0 . 0 . 0 . 125 51 FRUITS & VEGETABLES 0 . 2,292 541 0 . 0 . 1,673 216 3,965 756 Tobacco 0 . 118 10 0 . 0 . 119 12 236 22 CASH CROPS 0 . 118 10 0 . 0 . 119 12 236 22 Total 4,026 1,914 49,346 15,666 4,025 2,361 430 384 22,853 9,778 80,680 30,103 Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 274 Appendix II 275 ANNUAL CROP AND VEGETABLE PRODUCTION anzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 276 District No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 42,682 14,125 13,407 0.9 14,683 3,681 2,409 0.7 17,806 15,817 0.9 Mwanga 12,311 5,292 4,199 0.8 11,993 5,410 3,959 0.7 10,702 8,158 0.8 Same 24,426 13,137 9,829 0.7 11,796 7,314 6,312 0.9 20,451 16,141 0.8 Moshi Rural 14,701 3,519 4,310 1.2 52,133 22,756 35,190 1.5 26,275 39,499 1.5 Hai 5,820 2,202 1,615 0.7 38,211 19,157 23,992 1.3 21,360 25,606 1.2 Total 99,941 38,275 33,360 0.9 128,816 58,318 71,861 1.2 96,593 105,222 1.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 151 35 97 2.8 118 36 14 0.4 71 111 1.6 Same 2,828 1,141 3,601 3.2 68 28 196 7.1 1,169 3,797 3.2 Moshi Rural 527 240 807 3.4 2,281 1,246 5,535 4.4 1,486 6,341 4.3 Hai 192 27 81 3.0 697 275 393 1.4 303 474 1.6 Total 3,698 1,443 4,586 3.2 3,164 1,585 6,138 3.9 3,029 10,724 3.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 438 50 31 0.6 236 48 7 0 98 39 0.4 Mwanga 43 9 0 0.0 43 9 9 1 17 9 0.5 Same 208 58 46 0.8 0 . . 58 46 0.8 Moshi Rural 0 . . 190 26 29 1 26 29 1.1 Hai 0 . . 245 55 25 0 55 25 0.5 Total 689 116 78 0.7 714 137 69 1 253 146 0.6 District No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 818 128 38 0 11,040 3,435 980 0.3 3,563 1,018 0 Mwanga 0 0 0 0 0 0 0 0.0 0 0 0 Same 0 0 0 0 0 0 0 0.0 0 0 0 Moshi Rural 259 0 0 0 259 40 19 0.5 40 19 0 Hai 111 11 0 0 348 78 62 0.8 90 62 1 Total 929 139 38 0 11,647 3,553 1,060 0 3,692 1,098 0 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Maize Short Rainy Season Long Rainy Season Total District Paddy Short Rainy Season Long Rainy Season Total 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sorghum Short Rainy Season Long Rainy Season Total 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year. Finger millet Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 277 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 2,088 152 37 0.2 1,998 1,117 164 0.1 1,269 201 0.2 Mwanga 733 164 67 0.4 605 225 85 0.4 389 152 0.4 Same 1,685 505 547 1.1 4,675 1,839 1,558 0.8 2,343 2,106 0.9 Moshi Rural 0 . . 0.0 139 28 1 0.0 28 1 0.0 Hai 0 . . 0.0 611 81 168 2.1 81 168 2.1 Total 4,506 820 652 0.8 8,028 3,290 1,977 0.6 81 168 2.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 116 10 17 2 118 48 4 0 58 21 0 Mwanga 1,829 240 206 1 1,153 152 121 1 391 328 1 Same 1,827 355 736 2 513 69 161 2 424 897 2 Moshi Rural 0 . . 133 2 7 3 2 7 3 Hai 0 . . 125 10 30 3 10 30 3 Total 3,772 605 960 2 2,042 280 322 1 886 1,283 1 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sweet Poatatoes Short Rainy Season Long Rainy Season Total 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cassava Total Short Rainy Season Long Rainy Season Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 278 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 530 124 288 2.3 427 140 115 0.8 265 403 1.5 Mwanga 0 . . 86 6 6 1.0 6 6 1.0 Same 2,268 314 329 1.0 293 22 25 1.1 336 354 1.1 Moshi Rural 0 . . 531 17 65 3.8 17 65 3.8 Hai 1,686 1,180 7,717 6.5 1,487 1,212 7,046 5.8 2,391 14,763 6.2 Total 4,484 1,618 8,334 5.2 2,823 1,398 7,257 5.2 3,016 15,592 5.2 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 1,291 225 137 0.6 1,061 80 177 2.2 305 314 1.0 Mwanga 0 . . 0 . . Same 146 11 28 2.5 0 . . 11 28 2.5 Moshi Rural 131 1 8 14.8 131 1 8 14.8 1 16 14.8 Hai 0 . . 125 10 60 5.9 10 60 6.0 Total 1,568 237 172 0.7 1,317 90 244 2.7 327 417 1.3 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 3,752 517 377 1 1,766 257 297 1 774 674 1 Mwanga 559 55 84 2 601 62 84 1 118 167 1 Same 144 16 61 4 67 16 20 1 32 81 3 Moshi Rural 395 71 14 0 1,870 151 184 1 222 198 1 Hai 0 . . 0 . . Total 4,850 659 536 1 4,304 486 584 1 1,145 1,120 1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 34,023 7,050 2,457 0.3 24,168 6,613 2,226 0.3 13,664 4,683 0.3 Mwanga 8,384 2,022 871 0.4 9,465 2,430 1,160 0.5 4,452 2,031 0.5 Same 16,014 5,196 1,742 0.3 14,136 5,633 2,034 0.4 10,829 3,776 0.3 Moshi Rural 8,722 1,347 1,118 0.8 26,377 5,177 2,473 0.5 6,524 3,590 0.6 Hai 5,939 1,605 730 0.5 29,263 7,209 2,811 0.4 8,815 3,541 0.4 Total 73,082 17,221 6,918 0.4 103,410 27,062 10,704 0.4 44,284 17,622 0.4 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Irish Poatatoes Short Rainy Season Long Rainy Season Total 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District Yams Short Rainy Season Long Rainy Season Total Coco Yams Short Rainy Season Long Rainy Season Total 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. Beans Short Rainy Season Long Rainy Season Total District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 279 District No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 11,468 2,131 982 0 9,717 1,482 815 1 3,612 1,798 0 Mwanga 0 . . 0 . . Same 0 . . 0 . . Moshi Rural 3,657 812 447 1 6,290 1,126 1,023 1 1,937 1,470 1 Hai 126 13 15 1 4,227 731 441 1 743 456 1 Total 15,250 2,955 1,445 0 20,235 3,338 2,279 1 6,293 3,724 1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 118 24 9 0 24 9 0 Mwanga 0 . . 0 . . Same 0 . . 0 . . Moshi Rural 136 14 0 278 56 10 0 70 10 0 Hai 0 . . 0 . . Total 136 14 0 396 80 19 0 94 19 0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 7,056 1,427 511 0.4 4,228 833 301 0.4 2,260 812 0.4 Mwanga 43 9 1 0.1 214 65 58 0.9 74 59 0.8 Same 0 . . 0 . . Moshi Rural 87 9 8 0.9 1,419 520 577 1.1 529 585 1.1 Hai 192 29 8 0.3 1,235 522 72 0.1 551 79 0.1 Total 7,379 1,474 528 0.4 7,096 1,939 1,008 0.5 3,413 1,536 0.5 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Groundnuts Short Rainy Season Long Rainy Season Total 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Simsim Short Rainy Season Long Rainy Season Total 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year. Sunflower Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 280 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 44 9 13 1.5 0 . . 9 13 1.5 Same 952 134 648 4.8 142 35 417 11.9 170 1,064 6.3 Moshi Rural 67 16 7 0.4 0 . . 16 648 39.9 Hai 352 47 587 12.5 241 102 1,079 10.5 149 1,667 11.2 Total 1,415 206 1,255 6.1 383 138 1,496 10.9 344 2,751 8.0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 118 2 5 2 2 5 2 Mwanga 130 18 127 7 205 37 134 4 55 261 5 Same 217 26 105 4 295 22 140 6 48 246 5 Moshi Rural 132 11 20 2 1,902 239 513 2 250 533 2 Hai 328 37 193 5 126 25 188 7 63 381 6 Total 808 91 445 5 2,645 326 980 3 417 1,425 3 District No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 808 109 300 3 259 40 172 4 149 472 3 Same 1,378 241 1,678 7 509 66 416 6 308 2,094 7 Moshi Rural 1,026 271 1,181 4 764 130 1,633 13 402 2,814 7 Hai 1,799 260 2,811 11 1,458 243 3,029 12 504 5,840 12 Total 5,012 882 5,971 7 2,989 481 5,250 11 1,362 11,220 8 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 171 24 9 0 173 25 11 0 49 20 0 Same 0 . . 72 3 14 5 3 14 5 Moshi Rural 382 36 82 2 1,294 89 268 3 125 350 3 Hai 565 66 64 1 333 39 34 1 106 97 1 Total 1,118 127 154 1 1,872 156 327 2 283 481 2 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year. District Spinach Short Rainy Season Long Rainy Season Total 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. Tomatoes Short Rainy Season Long Rainy Season Total 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cabbage Short Rainy Season Long Rainy Season Total 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year. District Onions Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 281 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 42 1 5 4.9 0 . . 1 5 4.9 Same 0 . . 74 7 7 1.0 7 7 1.0 Moshi Rural 132 11 9 0.9 0 . . 11 9 0.9 Hai 514 208 1,134 5.5 367 156 1,120 7.2 364 2,254 6.2 Total 688 220 1,148 5.2 441 163 1,127 6.9 383 2,275 5.9 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 118 2 2 1.0 2 2 1.0 Mwanga 302 34 45 1.3 214 16 33 2.0 50 78 1.6 Same 72 14 11 0.7 0 . . 14 11 0.8 Moshi Rural 1,178 91 276 3.0 1,749 136 303 2.2 226 579 2.6 Hai 1,297 126 800 6.3 725 61 111 1.8 187 911 4.9 Total 2,849 265 1,131 4.3 2,806 215 450 2.1 480 1,581 3.3 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 0 . . 0 . . Same 145 23 10 0.4 0 . . 23 10 0.4 Moshi Rural 0 . . 67 5 0 5 0 0.1 Hai 0 . . 0 . . Total 145 23 10 0.4 67 5 0 28 11 0.4 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0.0 . . 0.0 . . Mwanga 43.8 2.1 11.0 5.1 43.2 4.4 0.9 0.2 6.5 11.8 1.8 Same 140.6 22.3 71.8 3.2 213.0 61.7 168.1 2.7 84.0 239.9 2.9 Moshi Rural 337.1 71.4 52.9 0.7 267.2 82.2 123.7 1.5 153.7 176.6 1.1 Hai 460.2 47.8 295.5 6.2 343.6 59.4 456.9 7.7 107.2 752.4 7.0 Total 981.7 143.7 431.1 3.0 866.9 207.7 749.6 3.6 351.4 1,180.8 3.4 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year. District Chillies Short Rainy Season Long Rainy Season Total 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year. District Pumpkins Short Rainy Season Long Rainy Season Total 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year. Amaranthas Short Rainy Season Long Rainy Season Total District 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year. District Carrot Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 282 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Rombo 0 . . 0 . . Mwanga 0 . . 0 . . Same 0 . . 0 . . Moshi Rural 0 . . 0 . . Hai 0 . . 236 22 13 0.6 22 13 0.6 Total 0 . . 236 22 13 0.6 22 13 0.6 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tobacco Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 283 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 284 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Pigeon Pea 435 56 95 1,704 Coffee 10,171 4,617 2,074 449 Tea 5 5 5 1,112 Cocoa 162 43 12 274 Wattle 172 33 141 4,234 Jack Fruit 10 . . Banana 15,528 5,556 101,082 18,195 Avocado 1,930 534 6,541 12,239 Mango 1,969 2,436 7,587 3,115 Pawpaw 453 173 701 4,042 Pineapple 14 24 92 3,853 Orange 158 19 280 14,664 Grape Fruit 29 29 9 309 Guava 1 0 76 Lime/Lemon 46 0 19 Total 31,083 13,525 118,715 8,778 Star Fruit 2 0 502 Coconut 0 0 128 Coffee 683 410 396 967 Sugarcane 47 34 199 5,910 Cardamon 60 52 16 300 Cinamon . 0 . Jack Fruit 31 16 410 25,941 Mpesheni 0 2 35 16,439 Banana 3,588 2,456 8,462 3,446 Avocado 144 211 869 4,119 Mango 15 19 244 12,765 Pawpaw 4 2 25 13,185 Pineapple 3 10 7 710 Orange 0 . 11 Guava 3 0 18 Pitches 0 . 0 Lime/Lemon 2 0 0 Total 4,582 3,212 11,323 3,526 Rombo 7.3 Production of Permanent Crops by Crop Type and District, Kilimanjaro Region Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 285 cont……… Production of Permanent Crops by Crop Type and District, Kilimanjaro Region Sour Soup 30 . . Pigeon Pea 29 29 . Coconut 30 25 118 4,792 Coffee 3,500 5,038 338 67 Wattle 30 30 . Sugarcane 822 437 8,440 19,304 Cardamon 167 21 3 166 Cinamon . 0 7 Jack Fruit 284 450 498 1,106 Mpesheni 37 57 376 6,633 Banana 3,936 1,859 10,899 5,864 Avocado 1,944 370 1,707 4,614 Mango 1,389 663 3,255 4,913 Pawpaw 587 205 298 1,453 Orange 150 134 108 806 Grape 30 . 10 Mandarine/Tangerine . . . Guava 173 155 104 670 Plums . . 14 Pears 30 30 155 5,181 Pitches 105 37 314 8,538 Lime/Lemon . . 18 Total 13,274 9,538 26,664 2,795 Pigeon Pea 43 43 191 4,450 Malay Apple 95 25 44 1,764 Coffee 12,713 9,735 15,166 1,558 Sugarcane 73 3 11 3,895 Nutmeg . . 7 Jack Fruit 71 11 67 6,238 Banana 25,513 17,762 165,222 9,302 Avocado 1,648 783 4,882 6,234 Mango 4,319 868 4,108 4,734 Pawpaw 709 266 647 2,435 Pineapple 16 0 . Orange 804 203 285 1,403 Grape 27 27 0 10 Mandarine/Tangerine 6 6 8 1,482 Guava 543 48 39 823 Plums 55 55 13 232 Lime/Lemon . . 88 Rambutan 33 33 143 4,323 Total 46,669 29,866 190,921 6,393 Same Moshi Rural Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 286 Pigeon Pea 41 41 16 390 Star Fruit 48 48 26 543 Palm Oil 3 3 60 23,712 Coconut 75 74 37 493 Coffee 8,741 7,834 1,548 198 Cocoa 25 13 5 395 Rubber 17 17 10 581 Sugarcane 0 0 7 14,820 Cardamon 1 1 11 22,230 Jack Fruit 10 10 88 9,263 Mpesheni 4 4 . Banana 7,898 10,777 41,415 3,843 Avocado 748 469 1,262 2,692 Mango 352 317 2,176 6,872 Pawpaw 397 335 328 979 Orange 172 91 106 1,165 Grape 0 0 10 22,230 Guava 91 61 26 434 Lime/Lemon 23 23 4 187 Total 18,645 20,115 47,135 2,343 Total Pigeon Pea 549 170 303 1,787 Malay Apple 95 25 45 1,816 Star Fruit 49 48 528 11,084 Palm Oil 3 3 60 23,712 Coconut 105 99 283 2,847 Coffee 35,808 27,634 19,523 706 Tea 5 5 5 1,112 Cocoa 188 56 17 302 Rubber 17 17 10 581 Wattle 202 63 141 2,232 Sugarcane 942 474 8,656 18,262 Cardamon 227 73 30 413 Jack Fruit 406 486 1,062 2,185 Mpesheni 42 63 411 6,554 Banana 56,463 38,408 327,080 8,516 Avocado 6,414 2,367 15,261 6,447 Mango 8,045 4,301 17,370 4,038 Pawpaw 2,151 982 2,000 2,037 Pineapple 33 34 99 2,902 Orange 1,284 447 789 1,767 Grape Fruit 29 29 9 309 Grape 58 28 21 743 Mandarine/Tangerine 6 6 9 1,521 Guava 811 264 264 1,000 Plums 55 55 27 498 Pears 30 30 155 5,181 Pitches 105 37 315 8,547 Lime/Lemon 70 23 129 5,686 Rambutan 33 33 143 4,323 Total 114,253 76,257 394,758 5,177 cont……… Production of Permanent Crops by Crop Type and District, Kilimanjaro Region Hai Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 287 District Area Planted with banana Total area planted (ha) % of total area planted (ha) hh with banana Average planted area per household District Area Planted with banana Total area planted (ha) % of total area planted (ha) hh with Coffee Average planted area per household Rombo 15,528 18,640 83 29,985 1 Rombo 10,171 18,640 55 27,302 0 Mwanga 3,588 8,822 41 8,483 0 Mwanga 683 8,822 8 3,185 0 Same 3,936 15,410 26 8,480 0 Same 3,500 15,410 23 4,180 1 Moshi Rural 25,513 31,902 80 54,497 0 Moshi Rural 12,713 31,902 40 40,069 0 Hai 7,898 30,220 26 30,625 0 Hai 8,741 30,220 29 23,715 0 Total 56,463 104,994 54 132,070 0 Total 35,808 104,994 34 98,451 0 District Area Planted with banana Total area planted (ha) % of total area planted (ha) hh with Mangoes Average planted area per household District Area Planted with banana Total area planted (ha) % of total area planted (ha) hh with Avocado Average planted area per household Rombo 1,969 18,640 11 7,296 0 Rombo 1,930 18,640 10 9,636 0 Mwanga 15 8,822 0 426 0 Mwanga 144 8,822 2 1,306 0 Same 1,389 15,410 9 2,631 1 Same 1,944 15,410 13 3,948 0 Moshi Rural 4,319 31,902 14 8,217 1 Moshi Rural 1,648 31,902 5 11,696 0 Hai 352 30,220 1 3,694 0 Hai 748 30,220 2 4,747 0 Total 8,044 104,994 8 22,264 0 Total 6,414 104,994 6 31,333 0 7.4: Total Area Planted with Banana by District - Kilimanjaro Region Mangoes 7.5: Total Area Planted with Coffee by District - Kilimanjaro Region 7.6: Total Area Planted with Mangoes by District - Kilimanjaro Region 7.7: Total Area Planted with Avocado by District - Kilimanjaro Region Banana Coffee Avocado Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 288 Crop Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Planted Area (ha) Planted Area (ha) Planted Area (ha) Planted Area (ha) Planted Area (ha) Sour Soup . 30 . . 30 Pigeon Pea 160 18 . 371 549 Malay Apple 95 . . . 95 Star Fruit 48 . . 2 49 Palm Oil 3 . . . 3 Coconut 68 . . 37 105 Coffee 28,602 632 1,257 4,870 35,361 Tea 5 . . . 5 Cocoa 25 . . 162 188 Rubber 17 . . . 17 Wattle . . . 202 202 Sugarcane 242 145 . 551 938 Cardamon 38 11 13 165 227 Jack Fruit 180 . . 223 403 Mpesheni 30 . . 12 42 Banana 48,089 1,456 1,166 5,562 56,273 Avocado 2,118 748 1 3,536 6,402 Mango 3,026 949 8 4,063 8,045 Pawpaw 849 544 . 758 2,151 Pineapple 17 . . 16 33 Orange 767 144 169 203 1,284 Grape Fruit 29 . . 0 29 Grape 0 . . 57 58 Mandarine/Tangerine 6 . . . 6 Guava 502 155 . 155 811 Plums 55 . . . 55 Pears . 30 . . 30 Pitches 38 7 . 60 105 Lime/Lemon 20 . 5 46 70 Rambutan . . . 33 33 Total 85,027 4,868 2,619 21,082 113,596 cont…Planted Area with Fertiliser by Fertiliser Type and crop Fertilizer Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 289 Crop Mostly Farm Yard Manure Total Planted Area (ha) % Sour Soup 0 30 0 Pigeon Pea 160 549 29 Malay Apple 95 95 100 Star Fruit 48 49 97 Palm Oil 3 3 100 Coconut 68 105 65 Coffee 28,602 35,361 81 Tea 5 5 100 Cocoa 25 188 13 Rubber 17 17 100 Wattle 0 202 0 Sugarcane 242 938 26 Cardamon 38 227 17 Jack Fruit 180 403 45 Mpesheni 30 42 72 Banana 48,089 56,273 85 Avocado 2,118 6,402 33 Mango 3,026 8,045 38 Pawpaw 849 2,151 39 Pineapple 17 33 52 Orange 767 1,284 60 Grape Fruit 29 29 100 Grape 0 58 1 Mandarine/Tangerine 6 6 100 Guava 502 811 62 Plums 55 55 100 Pears 0 30 0 Pitches 38 105 36 Lime/Lemon 20 70 28 Rambutan 0 33 0 Total 85,027 113,596 75 cont…Planted Area with Fertiliser by Fertiliser Type and crop Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 290 Mostly Compost Total Planted Area (ha) % Sour Soup 30 30 100 Pigeon Pea 18 549 3 Malay Apple 0 95 0 Star Fruit 0 49 0 Palm Oil 0 3 0 Coconut 0 105 0 Coffee 632 35,361 2 Tea 0 5 0 Cocoa 0 188 0 Rubber 0 17 0 Wattle 0 202 0 Sugarcane 145 938 15 Cardamon 11 227 5 Jack Fruit 0 403 0 Mpesheni 0 42 0 Banana 1,456 56,273 3 Avocado 748 6,402 12 Mango 949 8,045 12 Pawpaw 544 2,151 25 Pineapple 0 33 0 Orange 144 1,284 11 Grape Fruit 0 29 0 Grape 0 58 0 Mandarine/Tangerine 0 6 0 Guava 155 811 19 Plums 0 55 0 Pears 30 30 100 Pitches 7 105 7 Lime/Lemon 0 70 0 Rambutan 0 33 0 Total 4,868 113,596 4 cont…Planted Area with Fertiliser by Fertiliser Type and crop Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 291 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 30 0 Pigeon Pea 0 549 0 Malay Apple 0 95 0 Star Fruit 0 49 0 Palm Oil 0 3 0 Coconut 0 105 0 Coffee 1,257 35,361 4 Tea 0 5 0 Cocoa 0 188 0 Rubber 0 17 0 Wattle 0 202 0 Sugarcane 0 938 0 Cardamon 13 227 6 Jack Fruit 0 403 0 Mpesheni 0 42 0 Banana 1,166 56,273 2 Avocado 1 6,402 0 Mango 8 8,045 0 Pawpaw 0 2,151 0 Pineapple 0 33 0 Orange 169 1,284 13 Grape Fruit 0 29 0 Grape 0 58 0 Mandarine/Tangerine 0 6 0 Guava 0 811 0 Plums 0 55 0 Pears 0 30 0 Pitches 0 105 0 Lime/Lemon 5 70 7 Rambutan 0 33 0 Total 2,619 113,596 2 cont…Planted Area with Fertiliser by Fertiliser Type and crop Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 292 Appendix II 293 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 294 Number % Number % Number % Rombo 44,239 94 2,775 6 47,014 100 Mwanga 14,045 84 2,704 16 16,749 100 Same 25,050 86 4,052 14 29,103 100 Moshi Rural 60,236 78 16,590 22 76,826 100 Hai 28,339 61 18,142 39 46,481 100 Total 171,910 80 44,263 20 216,173 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Other By Factory Total Rombo 703 3,707 33,411 0 6,419 0 0 44,239 Mwanga 459 164 13,213 88 78 44 0 14,045 Same 1,306 1,891 21,635 0 145 0 74 25,050 Moshi Rural 1,536 10,838 43,000 139 4,328 136 260 60,236 Hai 1,228 599 25,245 819 338 0 111 28,339 Total 5,231 17,198 136,503 1,045 11,307 180 445 171,910 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District District Method of Processing 8.1.1a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year. Households That Processed Product Households That Did Not Process Product Total District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 295 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 157,616 38 581 783 492 0 159,509 Paddy 4,495 0 850 0 0 0 5,346 Sorghum 224 0 0 0 0 0 224 Finger Millet 2,926 0 236 0 0 0 3,162 Cassava 1,808 0 0 0 0 0 1,808 Beans 2,336 0 381 0 191 0 2,908 Sunflower 21,795 116 0 0 0 0 21,911 Simsim 278 0 0 0 0 0 278 Groundnut 2,081 0 2,330 0 0 0 4,411 Coconut 127 0 0 0 0 0 127 Coffee 0 688 39,699 160 0 265 40,812 Sugarcane 73 0 542 0 0 44 659 Banana 1,854 0 199 0 0 0 2,053 Avocado 138 0 0 0 0 0 138 Cauliflower 125 0 0 0 0 0 125 Total 195,875 841 44,817 943 683 309 243,469 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 1,921 1,042 451 126 412 258 134 155,166 159,509 Paddy 67 784 74 71 0 74 0 4,276 5,346 Sorghum 0 0 0 0 0 0 0 224 224 Finger Millet 235 236 0 0 0 0 0 2,691 3,162 Cassava 74 0 0 0 0 0 0 1,734 1,808 Beans 236 669 74 0 0 0 0 1,929 2,908 Sunflower 393 738 235 0 0 118 247 20,180 21,911 Simsim 0 0 0 0 0 0 0 278 278 Groundnut 888 1,609 118 236 0 214 118 1,229 4,411 Coconut 0 0 0 0 0 0 0 127 127 Coffee 0 624 12,696 23,642 0 302 143 3,406 40,812 Sugarcane 301 0 0 0 0 215 144 0 659 Banana 0 0 0 199 0 0 0 1,854 2,053 Avocado 0 0 0 0 0 0 0 138 138 Cauliflower 0 0 0 0 0 0 0 125 125 Total 4,114 5,703 13,648 24,274 412 1,180 785 193,354 243,469 8.1.1d AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Where Sold Crop 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop Crop Product Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 296 Flour / Meal Grain Oil Juice Total Rombo 39,668 2,688 1,883 0 44,239 Mwanga 13,503 376 44 122 14,045 Same 23,085 1,823 0 142 25,050 Moshi Rural 47,794 12,179 263 0 60,236 Hai 26,429 950 960 0 28,339 Total 150,479 18,016 3,150 265 171,910 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Rombo 42,010 118 1,993 0 118 0 44,239 Mwanga 13,662 38 128 130 44 44 14,045 Same 23,891 0 867 221 72 0 25,050 Moshi Rural 51,972 139 7,724 0 136 265 60,236 Hai 27,165 0 619 432 123 0 28,339 Total 158,700 294 11,332 783 492 309 171,910 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Rombo 352 235 942 1,055 0 114 0 41,541 44,239 Mwanga 289 84 219 41 73 123 0 13,218 14,045 Same 507 663 363 71 71 0 143 23,233 25,050 Moshi Rural 679 412 4,501 3,218 268 135 134 50,889 60,236 Hai 251 113 0 377 0 0 0 27,598 28,339 Total 2,077 1,507 6,025 4,762 412 371 277 156,479 171,910 Bran Cake Husk Juice Pulp Oil Shell No by- product Other Total Rombo 7,297 10,468 118 0 3,989 236 118 22,014 0 44,239 Mwanga 7,064 0 0 0 0 0 218 6,764 0 14,045 Same 6,469 0 676 71 356 0 1,377 16,102 0 25,050 Moshi Rural 7,047 4,876 1,204 245 2,842 0 246 43,637 138 60,236 Hai 10,367 2,842 672 0 248 0 245 13,964 0 28,339 Total 38,244 18,186 2,670 317 7,435 236 2,203 102,480 138 171,910 District Where Sold 8.1.1.h AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District By Product District District Product Use 8.1.1.g AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District District Main Product 8.1.1.f AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 297 MARKETING Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 298 Did the Hh Sell any Crops from the 2002/03 season? Number % Number % Rombo 41,831 89 5,183 11 47,014 Mwanga 10,443 62 6,306 38 16,749 Same 18,721 64 10,382 36 29,103 Moshi Rural 64,370 84 12,456 16 76,826 Hai 32,344 70 14,137 30 46,481 Total 167,709 78 48,464 22 216,173 Price Too Low Production Insufficient to Sell Market Too Far Farmers Associatio n Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Rombo 1,145 19,210 118 0 0 0 0 231 23,051 43,754 Mwanga 115 7,012 0 44 43 131 43 116 7,516 15,020 Same 444 8,255 0 0 0 218 0 2,337 17,411 28,665 Moshi Rural 2,670 20,421 263 0 0 136 0 2,093 37,978 63,561 Hai 654 18,979 248 0 250 0 0 1,248 17,992 39,372 Total 5,028 73,877 629 44 293 484 43 6,025 103,947 190,372 Price Too Low Production Insufficient to Sell Market Too Far Farmers Associatio n Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Rombo 2.62 43.90 0.27 0.00 0.00 0.00 0.00 0.53 52.68 100.00 Mwanga 0.77 46.69 0.00 0.29 0.29 0.87 0.28 0.77 50.04 100.00 Same 1.55 28.80 0.00 0.00 0.00 0.76 0.00 8.15 60.74 100.00 Moshi Rural 4.20 32.13 0.41 0.00 0.00 0.21 0.00 3.29 59.75 100.00 Hai 1.66 48.21 0.63 0.00 0.64 0.00 0.00 3.17 45.70 100.00 Total 2.64 38.81 0.33 0.02 0.15 0.25 0.02 3.17 54.60 100.00 10.3 Proportion of Households who Repoprted Main Reason for Not Selling their Crops by District During 2002/03 Agricultural Year Main Reasons for Not Selling Crops 10 MARETING: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District Main Reasons for Not Selling Crops District District 10 MARETING: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District Total Number of Households Number of Households that Sold Number of Households that Did not Sell District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 299 IRRIGATION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 300 Total Number of Household % Number of Household % Number of Household Rombo 0 0 47,014 100 47,014 Mwanga 3,906 23 12,843 77 16,749 Same 12,350 42 16,752 58 29,103 Moshi Rural 17,408 23 59,418 77 76,826 Hai 15,047 32 31,435 68 46,481 Total 48,710 23 167,462 77 216,173 District Irrigatable Area (Ha) Area Irrigated Land (Ha) % Rombo . . . Mwanga 2,546 2,063 81 Same 8,089 6,242 77 Moshi Rural 10,949 8,605 79 Hai 7,392 6,215 84 Total 28,976 23,126 80 River Lake Dam Well Borehole Canal Pipe water Total Mwanga 1,520 0 173 44 43 2,084 42 3,906 Same 7,442 0 942 657 0 3,309 0 12,350 Moshi Rural 5,799 0 0 133 0 10,620 857 17,408 Hai 3,268 125 209 125 0 11,195 126 15,047 Total 18,029 125 1,323 959 43 27,208 1,024 48,710 Gravity Hand Bucket Hand Pump Motor Pump Other Total Mwanga 3,655 212 0 0 38 3,906 Same 11,914 365 71 0 0 12,350 Moshi Rural 15,418 1,922 0 67 0 17,408 Hai 14,559 488 0 0 0 15,047 Total 45,546 2,988 71 67 38 48,710 Households not Practicing Irrigation Table 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water Does the Household Practice Irrigation? 11.2: IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water District Households Practicing Irrigation Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 301 Flood Sprinkler Water Hose Bucket / Watering Can Total Mwanga 3,563 44 129 170 3,906 Same 11,690 73 0 587 12,350 Moshi Rural 15,557 132 267 1,451 17,408 Hai 14,350 0 96 601 15,047 Total 45,160 249 492 2,809 48,710 Have facility Does Not Have Facility Total Number % Number % Number Rombo 23,763 51 23,251 49 47,014 Mwanga 5,668 34 11,081 66 16,749 Same 13,486 46 15,617 54 29,103 Moshi Rural 17,588 23 59,238 77 76,826 Hai 7,243 16 39,238 84 46,481 Total 67,748 31 148,425 69 216,173 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Rombo 3,055 60,647 688 1,985 9,151 18,974 15,100 . 109,599 Mwanga 59,476 11,225 129 8,500 1,833 6,589 738 0 88,489 Same 162,760 99,890 285 11,402 12,227 29,591 4,646 72 320,873 Moshi Rural 3,770 55,424 . 2,470 5,546 11,977 5,163 139 84,488 Hai 1,501 25,239 377 11,430 3,611 461 3,224 873 46,716 Total 230,562 252,425 1,478 35,786 32,368 67,592 28,871 1,084 650,165 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District Type of Erosion Control Presence of Erosuion Control/water Harvesting Facilities District District 11.5: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District District Method of Application 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 302 Appendix II 303 ACCESS TO FARM INPUTS/IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 304 No.of Households % No.of Households % Rombo 6,436 14 40,578 86 47,014 Mwanga 1,238 7 15,511 93 16,749 Same 5,413 19 23,690 81 29,103 Moshi Rural 34,189 45 42,637 55 76,826 Hai 27,275 59 19,206 41 46,481 Total 74,551 34 141,622 66 216,173 No.of Households % No.of Households % Rombo 45,269 96 1,746 4 47,014 Mwanga 11,658 70 5,091 30 16,749 Same 17,319 60 11,784 40 29,103 Moshi Rural 56,228 73 20,597 27 76,826 Hai 29,307 63 17,175 37 46,481 Total 159,780 74 56,393 26 216,173 No.of Households % No.of Households % Rombo 2,453 5 44,561 95 47,014 Mwanga 658 4 16,091 96 16,749 Same 9,030 31 20,073 69 29,103 Moshi Rural 3,056 4 73,908 96 76,963 Hai 715 2 45,766 98 46,481 Total 15,912 7 200,399 93 216,310 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizers NOT Using Chemical Fertilizers Total Crop Growing Households District Using Farm Yard NOT Using Farm Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year Total Crop Growing Households District Using COMPOST NOT Using Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Total Crop Growing Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 305 No.of Households % No.of Households % Rombo 28,552 61 18,462 39 47,014 Mwanga 3,228 19 13,520 81 16,749 Same 7,443 26 21,660 74 29,103 Moshi Rural 10,561 14 66,265 86 76,826 Hai 16,199 35 30,283 65 46,481 Total 65,983 31 150,189 69 216,173 No.of Households % No.of Households % Rombo 1,320 3 45,695 97 47,014 Mwanga 135 1 16,614 99 16,749 Same 72 0 29,031 100 29,103 Moshi Rural 2,510 3 74,316 97 76,826 Hai 3,480 7 43,001 93 46,481 Total 7,516 3 208,657 97 216,173 No.of Households % No.of Households % Rombo 28,450 61 18,564 39 47,014 Mwanga 6,250 37 10,499 63 16,749 Same 11,236 39 17,867 61 29,103 Moshi Rural 34,865 45 41,960 55 76,826 Hai 28,041 60 18,565 40 46,607 Total 108,843 50 107,456 50 216,298 Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Using Herbicides NOT Using Herbicides District Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Total Crop Growing Households Total Crop Growing Households Using Pesticides/Fungicides NOT Using Pesticides/Fungicides District Using Improved Seeds NOT Using Improved Seeds Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Total Crop Growing Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 306 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 823 2 0 0 5,496 12 0 0 0 0 0 0 0 0 117 0 40,578 86 47,014 Mwanga 0 0 0 0 1,238 7 0 0 0 0 0 0 0 0 0 0 15,511 93 16,749 Same 73 0 0 0 5,271 18 0 0 0 0 0 0 68 0 0 0 23,690 81 29,103 Moshi Rural 2,293 3 1,472 2 29,784 39 134 0 0 0 261 0 245 0 0 0 42,637 55 76,826 Hai 353 1 236 1 26,494 57 96 0 96 0 0 0 0 0 0 0 19,082 41 46,356 Total 3,542 2 1,708 1 68,283 32 230 0 96 0 261 0 314 0 117 0 141,497 65 216,048 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 588 1 117 0 588 1 0 0 118 0 41,515 88 2,108 4 235 0 1,746 4 47,014 Mwanga 84 1 126 1 43 0 0 0 0 0 10,318 62 927 6 161 1 5,091 30 16,749 Same 74 0 73 0 220 1 0 0 0 0 12,963 45 3,988 14 0 0 11,784 40 29,103 Moshi Rural 135 0 512 1 3,366 4 133 0 270 0 48,454 63 3,359 4 0 0 20,597 27 76,826 Hai 126 0 0 0 1,045 2 118 0 249 1 21,811 47 4,052 9 1,906 4 17,050 37 46,356 Total 1,006 0 828 0 5,261 2 250 0 637 0 135,061 63 14,434 7 2,301 1 56,268 26 216,048 District Total Number % Number % Number % Number % Number % Number % Number % Number Rombo 0 0 0 0 0 0 2,335 5 118 0 0 0 44,561 95 47,014 Mwanga 43 0 0 0 0 0 615 4 0 0 0 0 16,091 96 16,749 Same 0 0 73 0 74 0 7,646 26 1,022 4 215 1 20,073 69 29,103 Moshi Rural 0 0 0 0 139 0 1,398 2 1,519 2 0 0 73,908 96 76,963 Hai 0 0 0 0 0 0 715 2 0 0 0 0 45,641 98 46,356 Total 43 0 73 0 213 0 12,708 6 2,659 1 215 0 200,274 93 216,186 Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Developmen t Project Crop Buyers Neighbour Other Other Not applicable Not applicable Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Co-operative Local Farmers Group Local Market / Trade Store Development Project Large Scale Farm Locally Produced by Household Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Locally Produced by Household Neighbour Other Not applicable Neighbour Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 307 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 10,103 21 1,288 3 16,343 35 233 0 0 0 118 0 352 1 115 0 0 0 18,462 39 47,014 Mwanga 219 1 44 0 2,922 17 0 0 0 0 0 0 44 0 0 0 0 0 13,520 81 16,749 Same 294 1 294 1 5,340 18 0 0 0 0 0 0 885 3 629 2 0 0 21,660 74 29,103 Moshi Rural 679 1 136 0 9,222 12 134 0 133 0 125 0 0 0 132 0 0 0 66,265 86 76,826 Hai 696 2 118 0 15,135 33 126 0 0 0 0 0 0 0 0 0 125 0 30,158 65 46,356 Total 11,991 6 1,880 1 48,962 23 493 0 133 0 242 0 1,282 1 875 0 125 0 150,065 69 216,048 District Total Number % Number % Number % Number % Number % Number Rombo 118 0 1,202 3 0 0 0 0 45,695 97 47,014 Mwanga 0 0 135 1 0 0 0 0 16,614 99 16,749 Same 0 0 0 0 0 0 72 0 29,031 100 29,103 Moshi Rural 134 0 2,242 3 134 0 0 0 74,316 97 76,826 Hai 0 0 3,480 8 0 0 0 0 42,876 92 46,356 Total 252 0 7,058 3 134 0 72 0 208,532 97 216,048 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 3,998 9 1,059 2 22,456 48 235 0 117 0 0 0 117 0 116 0 233 0 117 0 18,564 39 47,014 Mwanga 86 1 172 1 5,657 34 0 0 0 0 0 0 0 0 43 0 292 2 0 0 10,499 63 16,749 Same 73 0 134 0 9,627 33 0 0 514 2 0 0 304 1 363 1 146 1 74 0 17,867 61 29,103 Moshi Rural 2,364 3 538 1 29,685 39 272 0 133 0 619 1 67 0 654 1 520 1 138 0 41,835 54 76,826 Hai 605 1 324 1 25,819 56 96 0 310 1 0 0 303 1 123 0 355 1 107 0 18,441 40 46,482 Total 7,127 3 2,228 1 93,244 43 603 0 1,074 0 619 0 791 0 1,299 1 1,546 1 437 0 107,206 50 216,174 Not applicable Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year District Co- operative Local Market / Trade Store Secondary Market Development Project Neighbour Other Not applicable Locally Produced by Household Crop Buyers Large Scale Farm Neighbour Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Co- operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Other Locally Produced by Household Not applicable Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Co- operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 308 Total Rombo 1,525 24 3,384 53 1,409 22 118 2 0 0 6,436 Mwanga 128 10 301 24 432 35 260 21 117 9 1,238 Same 1,035 19 2,429 45 590 11 647 12 712 13 5,413 Moshi Rural 9,735 28 7,327 21 12,527 37 3,589 10 1,010 3 34,189 Hai 7,395 27 4,551 17 7,531 28 7,192 26 605 2 27,275 Total 19,818 27 17,993 24 22,489 30 11,806 16 2,444 3 74,551 Total Number % Number % Number % Number % Number % Number Rombo 43,290 96 939 2 583 1 221 0 235 1 45,269 Mwanga 11,427 98 117 1 114 1 0 0 0 0 11,658 Same 15,427 89 1,404 8 487 3 0 0 0 0 17,319 Moshi Rural 51,899 92 1,544 3 2,255 4 261 0 270 0 56,228 Hai 27,882 95 823 3 227 1 375 1 0 0 29,307 Total 149,924 94 4,827 3 3,667 2 857 1 505 0 159,780 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above District Less than 1 km Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 309 Total Number % Number % Number % Number % Number % Number Rombo 2,453 100 0 0 0 0 0 0 0 0 2,453 Mwanga 623 95 0 0 0 0 0 0 35 5 658 Same 8,223 91 363 4 296 3 147 2 0 0 9,030 Moshi Rural 2,714 89 202 7 139 5 0 0 0 0 3,056 Hai 590 82 0 0 0 0 126 18 0 0 715 Total 14,603 92 566 4 434 3 273 2 35 0 15,912 Total Number % Number % Number % Number % Number % Number Rombo 5,647 20 15,314 54 6,648 23 825 3 118 0 28,552 Mwanga 523 16 558 17 1,117 35 629 19 402 12 3,228 Same 1,953 26 1,676 23 1,227 16 951 13 1,637 22 7,443 Moshi Rural 3,062 29 2,188 21 3,896 37 873 8 542 5 10,561 Hai 5,019 31 1,181 7 6,781 42 2,694 17 522 3 16,199 Total 16,204 25 20,917 32 19,669 30 5,973 9 3,221 5 65,983 Total Number % Number % Number % Number % Number % Number Rombo 7,279 26 14,727 52 5,619 20 707 2 118 0 28,450 Mwanga 1,395 22 1,399 22 1,726 28 931 15 798 13 6,250 Same 1,859 17 2,066 18 2,880 26 1,898 17 2,533 23 11,236 Moshi Rural 8,565 24 6,223 18 14,312 41 4,604 13 1,286 4 34,990 Hai 7,732 28 4,499 16 9,821 35 5,608 20 382 1 28,041 Total 26,830 25 28,914 27 34,357 32 13,749 13 5,117 5 108,968 District Less than 1 km Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and Between 3 and Between 10 20 km and Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 310 Input is of No Use Total Number % Number % Number % Number % Number % Number Number % Number % Number Rombo 468 1 32,774 81 2,690 7 0 0 350 1 3,246 8 116 0 933 2 40,578 Mwanga 322 2 12,946 83 87 1 43 0 559 4 1,480 10 0 0 74 0 15,511 Same 2,295 10 17,324 73 634 3 219 1 296 1 2,352 10 0 0 568 2 23,690 Moshi Rural 1,023 2 29,264 69 892 2 0 0 135 0 6,546 15 132 0 4,643 11 42,637 Hai 333 2 15,584 81 201 1 125 1 0 0 1,643 9 0 0 1,322 7 19,206 Total 4,442 3 107,893 76 4,505 3 387 0 1,340 1 15,267 11 248 0 7,541 5 141,622 Input is of No Use Total Number % Number % Number % Number % Number % Number Number % Number % Number Rombo 586 34 350 20 234 13 115 7 344 20 0 0 0 0 117 7 1,746 Mwanga 258 5 300 6 3,387 67 74 1 222 4 615 12 0 0 235 5 5,091 Same 3,195 27 2,615 22 3,969 34 1,168 10 0 0 202 2 0 0 635 5 11,784 Moshi Rural 7,794 38 2,203 11 6,243 30 1,027 5 67 0 1,615 8 115 1 1,532 7 20,597 Hai 6,817 40 3,409 20 3,709 22 588 3 527 3 814 5 0 0 1,312 8 17,175 Total 18,650 33 8,878 16 17,542 31 2,971 5 1,160 2 3,245 6 115 0 3,831 7 56,393 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 2,486 6 3,290 7 20,892 47 580 1 11,420 26 4,140 9 0 0 1,753 4 44,561 Mwanga 392 2 843 5 8,315 52 776 5 3,705 23 1,863 12 87 1 111 1 16,091 Same 3,423 17 4,414 22 9,157 46 1,259 6 268 1 922 5 0 0 630 3 20,073 Moshi Rural 6,430 9 9,308 13 38,760 52 2,760 4 7,816 11 7,686 10 358 0 789 1 73,908 Hai 9,093 20 7,673 17 6,810 15 1,659 4 13,304 29 6,003 13 125 0 1,100 2 45,766 Total 21,823 11 25,528 13 83,934 42 7,035 4 36,513 18 20,613 10 570 0 4,383 2 200,399 District Other Locally Produced by Household Too Much Labour Required Do not Know How to Use Locally Produced by Household Do not Know How to Use District Not Available Price Too High No Money to Buy Do not Know How to Use Not Available Price Too High No Money to Buy Too Much Labour Required Not Available Too Much Labour Price Too High No Money to Buy Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Locally Produced by Other Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year Other Input is of No Use District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 311 Total Number % Number % Number % Number % Number % Number % Number % Number Rombo 232 1 13,098 71 696 4 115 1 2,464 13 1,171 6 685 4 18,462 Mwanga 260 2 9,496 70 358 3 43 0 347 3 2,943 22 73 1 13,520 Same 2,182 10 17,042 79 638 3 145 1 148 1 1,016 5 488 2 21,660 Moshi Rural 1,429 2 48,006 72 1,286 2 833 1 1,581 2 12,074 18 1,056 2 66,265 Hai 1,846 6 21,683 72 479 2 243 1 101 0 5,089 17 842 3 30,283 Total 5,949 4 109,326 73 3,457 2 1,379 1 4,642 3 22,293 15 3,144 2 150,189 Total Number % Number % Number % Number % Number % Number % Number % Number Rombo 937 2 17,109 37 3,047 7 0 0 5,492 12 17,372 38 1,738 4 45,695 Mwanga 727 4 8,223 49 371 2 44 0 1,356 8 5,863 35 30 0 16,614 Same 2,993 10 14,081 49 843 3 0 0 4,199 14 6,199 21 717 2 29,031 Moshi Rural 1,925 3 36,645 49 2,269 3 0 0 3,460 5 29,496 40 521 1 74,316 Hai 1,971 5 29,108 68 251 1 118 0 557 1 10,154 24 842 2 43,001 Total 8,552 4 105,166 50 6,781 3 162 0 15,064 7 69,085 33 3,848 2 208,657 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Total Number % Number % Number % Number % Number % Number % Number % Number % Number Rombo 350 2 13,328 72 1,169 6 0 0 1,646 9 1,615 9 0 0 456 2 18,564 Mwanga 159 2 9,696 92 122 1 0 0 0 0 448 4 44 0 30 0 10,499 Same 1,814 10 14,991 84 499 3 0 0 0 0 216 1 0 0 347 2 17,867 Moshi Rural 1,564 4 33,371 80 670 2 139 0 408 1 4,760 11 0 0 923 2 41,835 Hai 501 3 15,352 83 125 1 125 1 0 0 1,837 10 0 0 625 3 18,565 Total 4,388 4 86,740 81 2,584 2 264 0 2,054 2 8,875 8 44 0 2,382 2 107,331 Too Much Labour Do not Know How to Use Input is of No Use Other District Not Available Price Too High No Money to Buy Other District Not Available Price Too High No Money to Too Much Do not Know How Input is of No Use Other Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 312 Average Total Number % Number % Number % Number % Number Rombo 2,929 46 3,390 53 117 2 0 0 6,436 Mwanga 405 33 750 61 82 7 0 0 1,238 Same 1,139 21 3,129 58 931 17 142 3 5,413 Moshi Rural 11,332 33 19,755 58 3,102 9 0 0 34,189 Hai 11,091 41 14,387 53 1,559 6 113 0 27,275 Total 26,897 36 41,411 56 5,791 8 255 0 74,551 Average Total Number % Number % Number % Number % Number Rombo 25,923 57 18,181 40 1,047 2 118 0 45,269 Mwanga 6,891 59 4,341 37 382 3 44 0 11,658 Same 5,222 30 10,723 62 1,302 8 72 0 17,319 Moshi Rural 24,719 44 28,169 50 3,341 6 0 0 56,228 Hai 10,120 35 17,555 60 1,632 6 0 0 29,307 Total 72,873 46 78,968 49 7,705 5 233 0 159,780 Average Total Number % Number % Number % Number Rombo 941 38 1,394 57 118 5 2,453 Mwanga 298 45 282 43 78 12 658 Same 1,969 22 6,116 68 946 10 9,030 Moshi Rural 1,232 40 1,823 60 0 0 3,056 Hai 126 18 590 82 0 0 715 Total 4,566 29 10,204 64 1,142 7 15,912 Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Poor District Excellent Good Poor District Excellent Good Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 313 Excellent Good Average Poor Total Number % Number % Number % Number % Number % Number Rombo 5,136 18 20,712 73 2,587 9 118 0 0 0 28,552 Mwanga 378 12 2,358 73 462 14 30 1 0 0 3,228 Same 1,627 22 4,588 62 1,228 17 0 0 0 0 7,443 Moshi Rural 4,138 39 5,887 56 536 5 0 0 0 0 10,561 Hai 4,819 30 8,965 55 2,038 13 251 2 126 1 16,199 Total 16,098 24 42,509 64 6,851 10 399 1 126 0 65,983 Total Number % Number % Number % Number Rombo 646 49 673 51 0 0 1,320 Mwanga 0 0 135 100 0 0 135 Same 0 0 72 100 0 0 72 Moshi Rural 1,560 62 812 32 138 5 2,510 Hai 929 27 2,300 66 251 7 3,480 Total 3,136 42 3,991 53 389 5 7,516 District Does not Work Total Number % Number % Number % Number % Number Rombo 8,622 30 17,824 63 2,005 7 0 0 28,450 Mwanga 2,586 41 3,296 53 325 5 43 1 6,250 Same 2,306 21 8,354 74 576 5 0 0 11,236 Moshi Rural 10,155 29 22,578 65 2,257 6 0 0 34,990 Hai 10,527 38 15,575 56 1,814 6 126 0 28,041 Total 34,195 31 67,627 62 6,977 6 169 0 108,968 Total Number % Number % Number Rombo 14,296 30 32,718 70 47,014 Mwanga 4,119 25 12,630 75 16,749 Same 12,728 44 16,375 56 29,103 Moshi Rural 46,543 61 30,283 39 76,826 Hai 34,234 74 12,247 26 46,481 Total 111,920 52 104,253 48 216,173 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Does not Work Excellent Good Average Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District With Plan to use Next Year Chemical Fertilizers NO Plan to use Next Year Chemical Fertilizers Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 314 Total Total Number % Number % Number Number % Number % Number Rombo 45,037 96 1,977 4 47,014 Rombo 5,659 12 41,355 88 47,014 Mwanga 13,216 79 3,533 21 16,749 Mwanga 2,143 13 14,605 87 16,749 Same 23,498 81 5,605 19 29,103 Same 15,537 53 13,566 47 29,103 Moshi Rural 57,201 74 19,625 26 76,826 Moshi Rural 6,197 8 70,767 92 76,963 Hai 31,869 69 14,612 31 46,481 Hai 5,549 12 40,932 88 46,481 Total 170,820 79 45,353 21 216,173 Total 35,085 16 181,226 84 216,310 District With Plan to use Next Year Farm Yard Manure NO Plan to use Next Year Farm Yard Manure Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District With Plan to use Next Year COMPOST Manure NO Plan to use Next Year COMPOST Manure Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 315 Total Number % Number % Number Rombo 35,674 76 11,341 24 47,014 Mwanga 6,071 36 10,678 64 16,749 Same 17,720 61 11,383 39 29,103 Moshi Rural 26,488 34 50,338 66 76,826 Hai 24,995 54 21,486 46 46,481 Total 110,947 51 105,226 49 216,173 Total Number % Number % Number Rombo 4,008 9 43,006 91 47,014 Mwanga 600 4 16,149 96 16,749 Same 3,501 12 25,602 88 29,103 Moshi Rural 9,545 12 67,281 88 76,826 Hai 10,065 22 36,416 78 46,481 Total 27,719 13 188,454 87 216,173 Total Number % Number % Number Rombo 35,347 75 11,667 25 47,014 Mwanga 11,953 71 4,796 29 16,749 Same 21,938 75 7,165 25 29,103 Moshi Rural 48,204 63 28,622 37 76,826 Hai 33,443 72 13,164 28 46,607 Total 150,884 70 65,414 30 216,298 District With Plan to use Next Year Pesticides/Fu ngicides NO Plan to use Next Year Pesticides/Fu ngicides Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 District With Plan to use Next Year Herbicides NO Plan to use Next Year Herbicides Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural District With Plan to use Next Year Improved Seeds NO Plan to use Next Year Improved Seeds Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 316 Appendix II 317 AGRICULTURE CREDITS Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 318 Total Number % Number % Number Rombo 115 50 114 50 228 Mwanga 0 0 76 100 76 Same 572 89 68 11 641 Moshi Rural 135 43 180 57 315 Hai 2,145 90 238 10 2,383 Total 2,967 81 677 19 3,643 % 81 19 District Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Total Rombo 228 0 0 0 0 0 228 Mwanga 0 0 0 76 0 0 76 Same 142 0 73 205 0 220 641 Moshi Rural 248 0 0 0 0 67 315 Hai 1,041 107 0 0 126 1,109 2,383 Total 1,660 107 73 281 126 1,396 3,643 13.2b: AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District Source of Credit 13.2a: AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District District Male Female Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 319 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Rombo 6,229 2,315 10,290 2,441 13,013 680 0 0 11,818 46,786 Mwanga 2,068 728 4,675 1,026 4,227 1,045 166 88 2,648 16,672 Same 1,806 1,357 4,758 648 10,849 293 360 0 8,391 28,462 Moshi Rural 11,157 9,483 8,146 5,986 29,361 337 525 137 11,378 76,511 Hai 2,386 1,681 7,585 2,877 17,516 4,522 224 302 7,006 44,098 Total 23,646 15,564 35,453 12,977 74,966 6,879 1,276 528 41,241 212,529 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Livestock Other Rombo 0 115 0 0 0 0 114 Mwanga 38 38 0 38 38 0 0 Same 208 283 420 205 0 73 68 Moshi Rural 0 0 114 0 114 67 201 Hai 500 1,449 1,105 711 0 249 113 Total Credits 746 1,885 1,639 954 152 390 496 District 13.2d: AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District Credit Use 13.2c: AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District District Reason for Not Using Credit Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 320 Appendix II 321 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 322 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptu s Spp Cyprus Spp Calophylu m Inophyllu m Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Terminalia Ivorensis Maesopsis Berchemoides Leucena Spp Rombo 113 4,480 192 5 79 19 1,268 4 2 . . 29 7 21 . Mwanga 1,228 5,910 91 839 37 15,045 27 . . 1,000 155 4 . . . Same 444 2,283 61 16 6 312 153 . . . 295 11 . . . Moshi Rural 1,453 3,270 58 122 112 107 93 10 94 46 . 4 . 373 50 Hai 842 2,309 3 6 . 22 91 . 15 10 16 11 1 . . Total 4,080 18,252 405 988 234 15,505 1,632 14 111 1,056 466 59 8 394 50 Cont……… Syszygium Spp Azadrita chta Spp Jakarand a Spp Albizia Spp Kyaya Spp Sesbania Spp Calliandra Spp Moringa Spp Saraca Spp Trichilia Spp Total 4 23 . 321 . . 10 13 . . 6,590 2 68 10 81 . . 39 4 . . 24,540 28 69 45 47 . 19 60 . . 50 3,899 16 129 39 973 . . 38 . 2 . 6,989 28 121 36 415 4 . 10 . . 10 3,950 78 410 130 1,837 4 19 157 17 2 60 45,968 14.1: ON FARM TREE PLANTING: Number of Planted Trees By Species and District, Kilimanjaro Region Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 323 District Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Rombo 238 4,390 72 2,200 0 . 310 6,590 Mwanga 112 4,288 70 4,108 35 16,034 217 24,430 Same 130 2,338 49 1,454 3 65 182 3,857 Moshi Rural 186 4,015 146 2,918 2 56 334 6,989 Hai 136 2,466 126 1,484 0 . 262 3,950 Total 802 17,497 463 12,164 40 16,155 1,305 45,816 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Rombo 343 34 0 21 28 5 11 442 Mwanga 168 15 2 95 25 1 0 306 Same 137 11 0 86 30 4 3 271 Moshi Rural 131 33 0 103 346 11 2 626 Hai 174 25 1 68 173 8 1 450 Total 953 118 3 373 602 29 17 2,095 Main Use District 14:3 TREE FARMING: Main Use of Trees By District 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 324 1-9 1-19 20-29 30-39 40-49 60+ Total Mwanga 44 43 248 0 405 84 825 Same 220 368 945 370 516 370 2,789 Moshi Rural 1,034 587 644 265 929 133 3,592 Hai 1,117 1,754 1,480 587 118 0 5,056 Total 2,416 2,753 3,317 1,221 1,968 586 12,261 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Rombo 15 53 2 334 28 7 3 442 Mwanga 32 80 1 147 42 3 0 305 Same 40 44 1 124 42 9 2 262 Moshi Rural 77 79 2 357 89 19 3 626 Hai 32 86 2 235 82 6 7 450 Total 196 342 8 1,197 283 44 15 2,085 14: 5 TREE FARMING: Number of Responses by second use of Trees and District for 2002/03 District Second Use 14.4: TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 325 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 326 District Total Number % Number % Number Rombo 27,900 59 19,114 41 47,014 Mwanga 9,094 54 7,654 46 16,749 Same 15,555 53 13,548 47 29,103 Moshi Rural 56,317 73 20,509 27 76,826 Hai 26,960 58 19,521 42 46,481 Total 135,826 63 80,346 37 216,173 Total Number % Number % Number % Number % Number % Number Rombo 2,328 8 18,181 65 6,806 24 471 2 115 0 27,900 Mwanga 2,619 29 4,742 52 1,442 16 161 2 86 1 9,051 Same 2,166 14 11,442 76 1,143 8 221 1 141 1 15,113 Moshi Rural 10,588 19 28,479 51 13,044 23 3,552 6 0 0 55,663 Hai 7,642 28 12,380 46 6,121 23 567 2 126 0 26,835 Total 25,343 19 75,225 56 28,556 21 4,972 4 467 0 134,562 Total Number % Number % Number % Number % Number % Number % Number Rombo 26,848 97 0 0 0 0 231 1 0 0 707 3 27,786 Mwanga 8,820 97 188 2 0 0 43 0 0 0 44 0 9,094 Same 12,928 84 1,785 12 0 0 74 0 74 0 549 4 15,410 Moshi Rural 54,585 98 138 0 271 0 0 0 0 0 922 2 55,916 Hai 25,794 97 462 2 245 1 125 0 0 0 0 0 26,626 Total 128,975 96 2,573 2 516 0 472 0 74 0 2,222 2 134,832 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District 15.2: CROP EXTENSION: Number of Households By Quality of Extension Messages by District during the 2002/03 Agricultural year, Kilimanjaro Region Households Receiving Extension Advice Households Not Receiving Extension Advice District Quality of service Very Good Good Average Poor No Good 15.3: EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District during the 2002/03 Agricultural Year, Kilimanjaro Region Source of Crop Extension District Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 327 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Rombo 26,613 0 0 231 0 707 27,552 Mwanga 8,533 188 0 0 0 44 8,765 Same 12,072 1,785 0 74 74 489 14,494 Moshi Rural 46,313 138 271 0 0 407 47,129 Hai 24,768 462 245 125 0 0 25,600 Total 118,299 2,573 516 430 74 1,648 123,539 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Rombo 19,554 236 117 116 118 2,937 23,078 Mwanga 6,003 474 44 0 43 637 7,201 Same 7,668 2,333 0 68 0 1,251 11,320 Moshi Rural 30,633 136 263 125 0 1,747 32,903 Hai 15,611 855 0 0 0 352 16,818 Total 79,469 4,033 423 309 161 6,924 91,319 Government NGO / Development Project Large Scale Farm Not applicable Total Rombo 22,856 116 352 2,580 25,904 Mwanga 4,963 1,735 0 917 7,614 Same 8,680 3,222 68 740 12,709 Moshi Rural 30,136 638 0 1,081 31,856 Hai 11,930 688 0 1,280 13,897 Total 78,565 6,398 420 6,597 91,981 15.4: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. District Use of Agrochemicals 15.6: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the Erosion Control By Source of Messages By District Kilimanjaro Region District Spacing Erosion Control District 15.5: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the Use of Agro-chemicals By Source of Messages By District Kilimanjaro Region Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 328 Government NGO / Development Project Cooperative Not applicable Total Total Number of Households % of total number of households Rombo 23,564 235 236 1,530 25,565 34,155 75 Mwanga 6,717 632 0 670 8,018 13,806 58 Same 10,688 1,964 0 813 13,465 21,769 62 Moshi Rural 40,900 277 357 538 42,071 53,763 78 Hai 15,951 847 0 440 17,237 41,225 42 Total 97,819 3,955 593 3,991 106,358 164,718 65 District Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Rombo 15,331 234 236 0 3,982 19,783 34,155 58 Mwanga 4,867 614 0 0 6,787 13,806 49 Same 6,174 1,818 0 0 1,607 9,599 21,769 44 Moshi Rural 34,319 0 125 0 2,361 36,805 53,763 68 Hai 18,781 487 343 125 241 19,976 41,225 48 Total 79,473 3,152 704 125 9,497 92,951 164,718 56 District Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Rombo 24,267 0 116 0 1,526 25,908 34,155 76 Mwanga 8,049 302 0 0 243 8,594 13,806 62 Same 9,129 3,295 0 71 833 13,329 21,769 61 Moshi Rural 45,747 269 138 0 814 46,968 53,763 87 Hai 20,118 949 1,007 0 425 22,499 41,225 55 Total 107,310 4,815 1,261 71 3,840 117,298 164,718 71 Use of Improved Seed 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.8: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.7: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. District Organic Fertilizer Use Inorganic Fertilizer Use Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 329 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 3,300 465 1,415 0 0 8,267 13,447 34,155 39 Mwanga 1,760 449 43 40 0 1,913 4,205 13,806 30 Same 2,765 1,243 0 74 0 1,411 5,494 21,769 25 Moshi Rural 15,173 264 510 0 0 1,077 17,025 53,763 32 Hai 10,096 214 1,505 0 119 428 12,361 41,225 30 Total 33,095 2,636 3,473 114 119 13,096 52,532 164,718 32 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 353 117 0 354 0 11,323 12,147 34,155 36 Mwanga 2,753 2,120 0 85 0 759 5,717 13,806 41 Same 6,303 3,042 74 142 67 1,123 10,751 21,769 49 Moshi Rural 20,301 278 174 87 0 1,441 22,282 53,763 41 Hai 13,054 338 118 0 125 429 14,064 41,225 34 Total 42,764 5,896 366 668 191 15,076 64,962 164,718 39 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 21,220 0 116 232 0 2,229 23,797 34,155 70 Mwanga 6,663 346 0 43 0 759 7,810 13,806 57 Same 8,595 1,879 0 0 74 1,332 11,881 21,769 55 Moshi Rural 34,007 138 212 0 0 540 34,897 53,763 65 Hai 18,396 821 225 0 125 496 20,064 41,225 49 Total 88,882 3,184 553 275 199 5,356 98,449 164,718 60 District 15.12: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.11: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.10: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. Mechanisation / LST Irrigation Technology Crop Storage District District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 330 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 8,113 114 0 0 236 9,108 17,571 34,155 51 Mwanga 3,997 113 0 43 0 1,430 5,583 13,806 40 Same 5,017 1,245 0 0 288 1,389 7,940 21,769 36 Moshi Rural 10,816 264 87 136 0 906 12,209 53,763 23 Hai 10,120 0 125 377 126 599 11,347 41,225 28 Total 38,064 1,737 212 555 650 13,432 54,650 164,718 33 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 14,097 471 707 350 354 6,292 22,271 34,155 65 Mwanga 3,883 175 0 83 0 1,748 5,889 13,806 43 Same 6,293 2,256 72 74 148 1,677 10,520 21,769 48 Moshi Rural 15,401 139 125 135 139 1,408 17,346 53,763 32 Hai 13,046 235 235 238 119 440 14,314 41,225 35 Total 52,720 3,277 1,139 880 759 11,565 70,341 164,718 43 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Rombo 12,454 0 354 118 118 8,991 22,035 34,155 65 Mwanga 4,398 1,005 0 40 43 1,552 7,037 13,806 51 Same 7,010 2,715 72 74 73 1,248 11,192 21,769 51 Moshi Rural 22,671 541 131 0 0 395 23,737 53,763 44 Hai 11,816 331 0 235 119 671 13,172 41,225 32 Total 58,349 4,592 557 467 352 12,856 77,174 164,718 47 15.13: EXTENSION MESSAGES: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. Agro-progressing District Agro-forestry Vermin Control District District 15.14: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.15: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-Forestry By Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 331 Government NGO / Development Project Large Scale Farm Not applicable Total Total Number of Households % of total number of households Rombo 118 0 116 11,795 12,029 34,155 35 Mwanga 477 363 40 2,546 3,425 13,806 25 Same 665 2,357 0 1,685 4,706 21,769 22 Moshi Rural 1,312 132 0 770 2,214 53,763 4 Hai 1,468 501 126 191 2,286 41,225 6 Total 4,039 4,040 281 16,987 24,660 164,718 15 % 16 16 1 69 100 Government NGO / Development Project Large Scale Farm Not applicable Total Total Number of Households % of total number of households Rombo 590 0 0 11,911 12,501 34,155 37 Mwanga 306 463 80 2,376 3,225 13,806 23 Same 364 3,463 0 1,391 5,218 21,769 24 Moshi Rural 2,979 258 0 632 3,869 53,763 7 Hai 879 251 0 191 1,320 41,225 3 Total 5,118 4,434 80 16,502 26,133 164,718 16 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Rombo 26,844 23,935 89 20,024 14,178 71 22,500 18,396 82 Mwanga 8,678 8,257 95 6,485 3,945 61 6,619 4,907 74 Same 14,079 13,560 96 10,061 6,380 63 11,970 9,904 83 Moshi Rural 46,726 44,001 94 33,484 21,546 64 30,755 24,981 81 Hai 25,600 24,272 95 17,059 12,130 71 13,110 9,113 70 Total 121,927 114,025 94 87,112 58,180 67 84,954 67,300 79 15.16: EXTENSION MESSAGES: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. 15.18: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Kilimanjaro Region. District Beekeeping District Fish Farming 15.17: EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Kilimanjaro Region. Spacing Use of Agrochemicals Erosion Control District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 332 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Rombo 23,799 22,739 96 15,329 3,506 23 24,383 18,769 77 Mwanga 7,318 6,256 85 5,321 2,380 45 8,308 5,444 66 Same 12,652 11,107 88 7,679 3,586 47 12,485 9,448 76 Moshi Rural 42,072 39,049 93 36,452 27,675 76 46,189 40,541 88 Hai 17,164 14,684 86 19,859 14,683 74 22,625 18,509 82 Total 103,005 93,835 91 84,640 51,831 61 113,989 92,711 81 Mechanisation / LST Organic Fertilizer Use Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Rombo 3,890 354 9 23,799 22,739 96 471 0 0 Mwanga 2,049 904 44 7,318 6,256 85 4,819 3,211 67 Same 3,343 2,030 61 12,652 11,107 88 9,487 7,268 77 Moshi Rural 15,967 13,433 84 42,072 39,049 93 19,122 14,172 74 Hai 12,046 8,320 69 17,164 14,684 86 13,797 8,956 65 Total 37,295 25,041 67 103,005 93,835 91 47,696 33,607 70 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Rombo 21,686 15,937 73 8,584 6,470 75 15,976 15,509 97 Mwanga 7,048 6,343 90 4,152 3,665 88 4,143 4,132 100 Same 10,622 8,782 83 6,113 5,443 89 8,695 7,885 91 Moshi Rural 35,044 32,384 92 11,041 9,029 82 15,592 14,905 96 Hai 19,806 18,188 92 11,190 8,967 80 13,758 12,145 88 Total 94,207 81,634 87 41,080 33,575 82 58,165 54,575 94 District 15.19: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Kil;imanjaro Region. Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Kilimanjaro Region. Irrigation Technology District 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Kilimanjaro Region. Crop Storage Vermin Control Agro-progressing Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 333 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Rombo 13,397 12,336 92 0 0 0 0 0 Mwanga 5,450 4,119 76 794 215 27 635 85 13 Same 10,092 7,749 77 2,725 1,402 51 3,901 1,175 30 Moshi Rural 24,023 17,930 75 936 268 29 2,852 2,862 100 Hai 12,984 9,351 72 2,333 1,467 63 1,255 251 20 Total 65,947 51,485 78 6,789 3,352 49 8,643 4,373 51 District 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Rukwa Region. Agro-forestry Beekeeping Fish Farming Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 334 Appendix II 335 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 336 Total Households Number % Number % Number Rombo 103 0.2 46,911 99.8 47,014 Mwanga 1,238 7.4 15,511 92.6 16,749 Same 142 0.5 28,961 99.5 29,103 Moshi Rural 1,357 1.8 75,468 98.2 76,826 Hai 7,710 16.6 38,771 83.4 46,481 Total 10,551 4.9 205,622 95.1 216,173 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Rombo 0 206 83 . . . . . . . . . 0 206 83 Mwanga 435 2,465 825 0 0 0 87 0 0 0 0 0 522 2,465 825 Same 216 285 175 . . . . . . . . . 216 285 175 Moshi Rural 523 4,207 1,079 0 0 88 . . . . . . 523 4,207 1,167 Hai 10,584 15,393 7,825 472 694 92 0 0 0 125 317 83 11,181 16,403 8,001 Total 11,759 22,555 9,987 472 694 180 87 0 0 125 317 83 12,443 23,565 10,251 Did you apply organic fertilizer during 2002/03? Total Area (ha) % Area (ha) % Area (ha) % Number % Number % Number Rombo 17,923 25 375 6 18,298 23 Rombo 42,348 28 4,548 7 46,896 Mwanga 5,440 8 338 6 5,778 7 Mwanga 11,563 8 5,099 8 16,662 Same 6,294 9 4,354 75 10,647 14 Same 17,564 12 11,245 18 28,809 Moshi Rural 30,347 42 535 9 30,882 39 Moshi Rural 52,208 35 23,956 38 76,165 Hai 12,491 17 170 3 12,661 16 Hai 26,826 18 18,932 30 45,758 Total 72,495 100 5,772 100 78,267 100 Total 150,510 100 63,781 100 214,291 Total 17 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District Farm Yard Manure Area Applied Compost Area Applied 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year Households Using Draft Animals Household Not Using Draft Animals District 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total District Using Organic Fertilizer Not Using Organic Fertilizer 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 337 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 338 Number % Number % Number % Rombo 24,830 53 22,184 47 47,014 100 Mwanga 11,591 69 5,158 31 16,749 100 Same 14,697 50 14,406 50 29,103 100 Moshi Rural 48,912 64 27,913 36 76,826 100 Hai 28,455 61 18,027 39 46,481 100 Total 128,484 59 87,688 41 216,173 100 District Herd Size Number of Househol d % Number of Cattle % Average Number Per Household Rombo 1-5 24,596 99 42,478 97 2 6-10 234 1 1,402 3 6 Total 24,830 100 43,880 100 2 Mwanga 1-5 9,978 86 24,513 47 2 6-10 769 7 5,703 11 7 11-15 233 2 3,291 6 14 16-20 191 2 3,514 7 18 21-30 226 2 5,772 11 26 31-40 81 1 2,672 5 33 41-50 78 1 3,825 7 49 61-100 35 0 2,680 5 77 Total 11,591 100 51,971 100 4 Same 1-5 12,529 85 28,271 35 2 6-10 928 6 7,024 9 8 11-15 357 2 4,705 6 13 16-20 141 1 2,531 3 18 21-30 340 2 7,601 10 22 31-40 68 0 2,729 3 40 51-60 67 0 3,460 4 52 61-100 207 1 14,604 18 70 101-150 60 0 8,837 11 148 Total 14,697 100 79,761 100 5 Moshi Rural 1-5 45,013 92 97,663 75 2 6-10 3,306 7 23,519 18 7 11-15 340 1 4,267 3 13 21-30 253 1 5,564 4 22 Total 48,912 100 131,013 100 3 Hai 1-5 25,005 88 56,639 30 2 6-10 2,164 8 15,999 9 7 11-15 325 1 3,904 2 12 16-20 220 1 3,920 2 18 21-30 430 2 11,195 6 26 31-40 101 0 3,944 2 39 61-100 107 0 10,715 6 100 151+ 101 0 81,616 43 807 Total 28,455 100 187,930 100 7 18.3b: CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 18.1a CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year Households Rearing Cattle Households Not Rearing Cattle Total Agricultural Households District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 339 Improved Dairy Number of Cattle % Number of Cattle % Number of Cattle % Number of Cattle % Rombo 13,995 32 235 1 29,651 68 43,880 9 Mwanga 35,941 69 428 1 15,602 30 51,971 11 Same 72,911 91 147 0 6,703 8 79,761 16 Moshi Rural 84,674 65 3,784 3 42,556 32 131,013 26 Hai 143,670 76 860 0 43,399 23 187,930 38 Total 351,191 71 5,454 1 137,910 28 494,555 100 18.4c CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 Total Cattle Indigenous Improved Beef District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 340 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Rombo 8,848 13,995 31.9 235 235 1 16,335 29,651 68 24,830 43,880 9 Mwanga 5,659 35,941 69.2 214 428 1 6,143 15,602 30 11,591 51,971 11 Same 12,736 72,911 91.4 147 147 0 2,989 6,703 8 14,697 79,761 16 Moshi Rural 31,428 84,674 64.6 2,372 3,784 3 18,521 42,556 32 48,912 131,013 26 Hai 10,884 143,670 76.4 489 860 0 18,263 43,399 23 28,455 187,930 38 Total 69,554 351,191 71.0 3,457 5,454 1 62,252 137,910 28 128,484 494,555 100 Bulls Cows Steers Heifers Male Calves Female Calves Total Rombo 2,312 5,857 234 2,657 1,292 1,644 13,995 Mwanga 3,309 16,083 1,233 5,966 4,598 4,752 35,941 Same 6,979 39,187 2,777 10,004 6,408 7,556 72,911 Moshi Rural 10,406 33,692 964 13,667 13,350 12,594 84,674 Hai 7,117 65,483 10,918 28,324 12,157 19,672 143,670 Total 30,122 160,302 16,126 60,617 37,807 46,217 351,191 Bulls Cows Steers Heifers Male Calves Female Calves Total Rombo 3,008 12,422 455 7,058 4,082 2,625 29,651 Mwanga 1,111 6,908 . 2,984 2,202 2,397 15,602 Same 812 2,848 . 1,742 719 582 6,703 Moshi Rural 6,067 20,023 353 5,361 4,170 6,580 42,556 Hai 5,000 20,063 251 6,813 6,084 5,188 43,399 Total 15,999 62,264 1,059 23,958 17,258 17,373 137,910 18.2: CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Beef Improved Dairy 18.4: CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Total Cattle 18.3: CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Category - Indigenous District District Category - Improved Dairy Cattle Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 341 GOAT PRODUCTION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 342 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Rombo 39,586 176,044 89 1,154 10,515 5 1,519 11,523 6 40,053 198,082 Mwanga 4,102 44,541 93 179 2,157 5 243 1,052 2 4,144 47,751 Same 7,322 52,785 95 71 71 0 434 2,705 5 7,536 55,561 Moshi Rural 36,591 160,072 95 1,469 4,525 3 1,326 3,509 2 37,503 168,107 Hai 12,421 93,776 91 243 957 1 1,698 8,344 8 13,780 103,077 Total 100,022 527,218 92 3,117 18,226 3 5,220 27,133 5 103,017 572,577 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 61,883 60 158,590 28 3 5-9 31,185 30 196,579 34 6 10-14 5,492 5 62,027 11 11 15-19 1,135 1 18,589 3 16 20-24 1,124 1 24,185 4 22 25-29 325 0 8,771 2 27 30-39 817 1 26,213 5 32 40+ 1,057 1 77,623 14 73 Total 103,017 100 572,577 100 6 19.2: GOAT PRODUCTION: Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st Total Goat 19.1: GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Indigenous Improved for Meat Improved Dairy Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 343 Number % Number % Number % Number % Billy Goat 72,524 87 8,075 10 2,896 3 83,495 15 Castrated Goat 18,701 77 1,243 5 4,490 18 24,434 4 She Goat 292,876 96 5,811 2 7,822 3 306,509 54 Male Kid 65,669 95 1,150 2 2,223 3 69,043 12 She Kid 77,448 87 1,947 2 9,703 11 89,097 16 Total 527,218 92 18,226 3 27,133 5 572,577 100 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Rombo 21,311 4,064 96,216 23,145 31,307 176,044 Mwanga 7,926 1,524 23,815 5,168 6,108 44,541 Same 8,936 2,888 30,419 4,587 5,955 52,785 Moshi Rural 23,613 5,118 91,260 19,255 20,826 160,072 Hai 10,738 5,106 51,166 13,513 13,253 93,776 Total 72,524 18,701 292,876 65,669 77,448 527,218 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Rombo 7,082 617 2,121 118 578 10,515 Mwanga 606 35 1,168 209 139 2,157 Same . 71 . . . 71 Moshi Rural 261 394 2,522 824 524 4,525 Hai 126 126 . . 706 957 Total 8,075 1,243 5,811 1,150 1,947 18,226 19.:3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Category of Goats Number of Indigenous Number of Improved for Meat Number of Improved Dairy 19.5: GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat Total Goat 19.4 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Type Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 344 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Rombo 585 707 2,334 470 7,427 11,523 Mwanga 84 216 128 287 337 1,052 Same 511 . 1,172 581 441 2,705 Moshi Rural 121 805 1,698 132 753 3,509 Hai 1,594 2,762 2,489 754 745 8,344 Total 2,896 4,490 7,822 2,223 9,703 27,133 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Rombo 28,978 5,389 100,671 23,733 39,311 198,082 Mwanga 8,616 1,775 25,111 5,664 6,584 47,751 Same 9,447 2,960 31,591 5,168 6,395 55,561 Moshi Rural 23,996 6,317 95,481 20,211 22,103 168,107 Hai 12,458 7,993 53,655 14,267 14,704 103,077 Total 83,495 24,434 306,509 69,043 89,097 572,577 District Total Goat 19.6 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 District Number of Improved Dairy 19.7 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 345 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 346 Breed Number of Indigenous % Number of Improved for Mutton % Total Sheep % Ram 38,598 44 1,709 4 40,307 16 Castrated Sh 17,547 95 970 5 18,517 7 She Sheep 132,358 22 3,279 2 135,637 53 Male Lamb 29,989 91 2,159 7 32,149 12 She Lamb 29,248 95 1,402 5 30,650 12 Total 247,740 96 9,520 4 257,260 100 Total Livestock Keeping Households Number % Number % Rombo 21,119 45 25,895 55 47,014 21,119 Mwanga 3,957 24 12,792 76 16,749 3,957 Same 9,378 32 19,725 68 29,103 9,378 Moshi Rural 17,044 22 59,782 78 76,826 17,044 Hai 12,198 26 34,283 74 46,481 12,198 Total 63,696 29 152,477 71 216,173 63,696 Number % Number % Number % Rombo 68,769 97 2,136 3 70,905 28 Mwanga 18,025 94 1,223 6 19,248 7 Same 40,752 96 1,704 4 42,457 17 Moshi Rural 55,138 96 2,018 4 57,156 22 Hai 65,055 96 2,439 4 67,494 26 Total 247,740 96 9,520 4 257,260 100 Number of Households Average Sheep Number of Households Average Sheep Rombo 38,598 2 1,709 8 21,119 3 Mwanga 17,547 4 970 25 3,957 5 Same 132,358 14 3,279 35 9,378 5 Moshi Rural 29,989 2 2,159 13 17,044 3 Hai 29,248 2 1,402 11 12,198 6 Total 247,740 4 9,520 15 63,696 4 20.1: SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year District Number of Indigenous Number of Improved for Mutton 20.2: SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year Households Raising Sheep Households Not Raising Sheep Total Numbver of Households District Total Households Raising Sheep Average Sheep Total Sheep District 20.3 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.4: Number of Sheep per Household by Category and district as of 1st October 2003. Number of Indigenous Number of Improved for Mutton Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 347 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 49,983 79 115,089 45 2 5-9 9,482 15 58,542 23 6 10-14 1,625 3 19,838 8 12 15-19 785 1 13,398 5 17 20-24 610 1 12,949 5 21 25-29 67 0 1,664 1 25 30-39 103 0 3,227 1 31 40+ 468 1 32,555 13 70 Total 63,122 100 257,260 100 4 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Number of Indigenous Rombo 11,739 4,453 36,249 8,344 7,984 68,769 Mwanga 2,606 932 9,672 2,080 2,734 18,025 Same 7,124 3,007 20,959 4,380 5,282 40,752 Moshi Rural 7,390 2,313 31,715 6,908 6,811 55,138 Hai 9,738 6,841 33,762 8,278 6,436 65,055 Total 38,598 17,547 132,358 29,989 29,248 247,740 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Sheep Rombo 11,857 4,453 37,185 9,426 7,984 70,905 Mwanga 2,869 932 9,672 2,474 3,300 19,248 Same 7,929 3,150 21,435 4,523 5,420 42,457 Moshi Rural 7,390 3,141 32,102 7,448 7,076 57,156 Hai 10,262 6,841 35,243 8,278 6,870 67,494 Total 40,307 18,517 135,637 32,149 30,650 257,260 20.7 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year Total Sheep District 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.6 SHEEP PRODUCTION: Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 347 348 Appendix II 349 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 350 Number % Number % 1-4 25,688 78 49,711 43 2 5-9 4,287 13 28,740 25 7 10-14 1,820 6 20,441 17 11 15-19 197 1 3,226 3 16 20-24 377 1 7,536 6 20 25-29 118 0 3,061 3 26 40+ 358 1 4,161 4 12 Total 32,844 100 116,877 100 4 District Number of Household Number of Pig Average Number Per Household Rombo 11,531 23,872 2 Mwanga 87 131 1 Same 1,919 5,317 3 Moshi Rural 14,775 65,761 4 Hai 4,531 21,796 5 Total 32,844 116,877 4 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Rombo 5,008 4,055 9,608 2,231 2,969 23,872 Mwanga 44 . 87 . . 131 Same 1,180 148 2,508 592 889 5,317 Moshi Rural 8,305 6,345 22,222 13,789 15,100 65,761 Hai 2,825 1,495 6,168 4,709 6,599 21,796 Total 17,362 12,043 40,594 21,322 25,556 116,877 21.3 PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Pigs Type District 21.3.1 PIG PRODUCTION: Number of Households Rearing Pigs, Herd of Pigs aand Average Head of per Household by Herd Size as of 1st October, 2003 Number of Household Number of Pig Herd Size Average Number Per Household 21.2 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 351 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 352 Total Rombo 23,493 63 13,984 37 37,477 Mwanga 8,890 75 3,009 25 11,899 Same 12,011 65 6,421 35 18,433 Moshi Rur 41,931 75 13,833 25 55,764 Hai 24,928 77 7,428 23 32,357 Total 111,253 71 44,676 29 155,929 Number % Number % Number % Number % Rombo 17,442 30 14,179 15 8,605 24 8,075 34 Mwanga 3,259 6 7,843 9 2,191 6 517 2 Same 4,256 7 9,890 11 5,758 16 1,466 6 Moshi Rur 21,599 38 37,223 40 9,680 27 10,540 44 Hai 10,938 19 22,963 25 9,900 27 3,289 14 Total 57,495 100 92,099 100 36,134 100 23,886 100 Total Number % age Number % age No. of Households Rombo 580 2 35,977 98 36,556 Mwanga 1,607 13 10,506 87 12,113 Same 2,895 16 15,466 84 18,361 Moshi Rur 4,701 9 50,475 91 55,176 Hai 6,791 22 24,027 78 30,819 Total 16,575 11 136,451 89 153,026 Total No. of Households % age No. of Households % age No. of Households % age No. of Households % age No. of Households Rombo 347 60 115 20 118 20 0 0 580 Mwanga 1,071 67 455 28 81 5 0 0 1,607 Same 1,254 43 1,201 41 366 13 0 0 2,895 Moshi Rur 1,598 34 2,965 63 0 0 138 3 4,701 Hai 1,653 24 4,545 67 0 0 476 7 6,791 Total 5,923 36 9,281 56 565 3 614 4 16,575 None Spray Dipping Trapping District Method of Tsetse Flies Control District 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District. 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District. Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs District Tsetse Flies Problems NO Tsetse Flies Problems 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed livestock during 2002/03 Agriculture Year by District and type of dewormed Livestock 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed livestock during 2002/03 Agriculture Year by District. District No.of Agricultural Households Demworming livestock No. of Agricultural Households NOT Demworming livestock Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 353 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 354 Number % Type Number Indigenous Chicken 1,356,781 87 Ducks 42,319 Layer 168,203 11 Turkeys 3,194 Broiler 36,355 2 Rabbits 36,929 0 Donkeys 16,190 Total 1,561,340 100 98,632 Ducks Turkeys Rabbits Donkeys Other Rombo 10,664 . 1,715 8,254 . Mwanga 4,326 1,079 23,405 . 173 Same 1,383 . 148 2,910 296 Moshi Rural 23,551 2,115 7,154 . 1,044 Hai 2,396 . 4,505 5,026 2,245 Total 42,319 3,194 36,929 16,190 3,758 Number % 1 - 4 54,867 35 149,240 3 5 - 9 48,974 31 315,494 6 10 - 19 37,959 24 479,707 13 20 - 29 8,939 6 195,077 22 30 - 39 2,059 1 66,695 32 40 - 49 1,174 1 48,928 42 50 - 99 1,108 1 62,696 57 100+ 507 0 38,944 77 Total 155,587 100 1,356,781 9 23b: OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Type of Livestock 23c: OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Flock Size Chicken rearing Households Number of chicken Average chicken per household 23a: OTHER LIVESTOCK: Total number of Other Livestock by Type as of 1st October 2003 Type Chicken Others Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 355 FISH FARMING Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 356 Yes Total Number % Number % Number Rombo 0 0 47,014 100 47,014 Mwanga 336 2 16,413 98 16,749 Same 291 1 28,812 99 29,103 Moshi Rur 135 0 76,691 100 76,826 Hai 371 1 46,110 99 46,481 Total 1,132 1 215,041 99 216,173 District Dug out Pond Natural Lake Total Mwanga 421 40 461 Same 367 0 367 Hai 371 0 371 Total 1,160 40 1,200 NGOs / Project Neighbour Private Trader Other Total Mwanga 213 165 44 40 461 Same 296 71 0 0 367 Hai 246 125 0 0 371 Total 755 361 44 40 1,200 Neighbor Local Market Trader at Farm Did not Sell Other Total Number Number Number Number Number Number Mwanga 210 0 40 211 0 461 Same 219 217 74 0 0 510 Moshi Rur 135 0 0 269 0 404 Hai 0 0 0 0 246 246 Total 564 217 114 480 246 1,621 District Number of Tilapia Number of Carp Number of Others Mwanga 52,821 0 0 Same 99,412 0 0 Moshi Rural 0 0 0 Hai 3,233 1,231 1,231 Total 155,466 1,231 1,231 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year Source of Fingerling District Fish Farming System 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year NO Where sold District Was fish farming carried out by this household during 2002/03? 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 357 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 358 District Total Total Number of households raising livestock % Number % Number % Number Rombo 21,425 46 25,590 54 47,014 37,949 56 Mwanga 7,051 42 9,698 58 16,749 12,792 55 Same 11,419 39 17,684 61 29,103 18,506 62 Moshi Rural 39,381 51 37,445 49 76,826 56,368 70 Hai 21,085 45 25,397 55 46,481 32,839 64 Total 100,360 46 115,813 54 216,173 158,453 63 Government NGO / Development Project Co- operative Large Scale Farmer Other not applicable Total Rombo 7,735 0 0 0 0 236 7,971 Mwanga 4,333 284 0 85 0 0 4,702 Same 5,146 1,324 0 0 71 74 6,615 Moshi Rural 21,199 0 0 0 0 139 21,337 Hai 12,111 119 118 0 126 0 12,473 Total 50,525 1,726 118 85 197 449 53,099 Government NGO / Development Project Large Scale Farmer Total Rombo 6,678 0 0 6,678 Mwanga 3,388 156 43 3,587 Same 4,057 1,251 0 5,307 Moshi Rural 14,587 138 0 14,725 Hai 10,435 598 125 11,157 Total 39,144 2,142 168 41,454 District Source of Advice 29.1c: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Source of Advice on Proper Milking 29.1b: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year 29.1a: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year Number of Agricultural Households Receiving Advice Number of Agricultural Households NOT Receiving Advice Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 359 Government NGO / Development Project Co-operative Large Scale Farmer Other not applicable Rombo 6,095 0 0 0 118 103 6,316 37,949 17 Mwanga 3,436 79 0 43 0 0 3,558 12,792 28 Same 4,412 585 0 0 0 0 4,997 18,506 27 Moshi Rural 14,705 0 0 0 0 0 14,705 56,368 26 Hai 11,116 604 230 125 0 0 12,076 32,839 37 Total 39,765 1,268 230 168 118 103 41,652 158,453 26 % 95.5 3.0 0.6 0.4 0.3 0.2 100 Government NGO / Development Project Co-operative Large Scale Farmer Other not applicable Total Rombo 15,455 0 0 0 114 103 15,672 37,949 41 Mwanga 6,259 149 0 43 43 0 6,494 12,792 51 Same 7,394 1,540 0 0 207 74 9,215 18,506 50 Moshi Rural 28,880 401 139 0 138 139 29,697 56,368 53 Hai 16,114 214 0 0 126 0 16,454 32,839 50 Total 74,102 2,304 139 43 627 316 77,531 158,453 49 % 96 3 0 0 1 0 100 Government NGO / Development Large Scale Farmer Total Rombo 3,299 236 118 3,653 37,949 10 Mwanga 2,792 72 0 2,864 12,792 22 Same 1,536 652 0 2,188 18,506 12 Moshi Rural 7,780 269 0 8,050 56,368 14 Hai 6,283 0 0 6,283 32,839 19 Total 21,691 1,229 118 23,037 158,453 15 % 94 5 1 100 Total Number of households raising livestock % receiving advice out of total 29.1e: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total Total 29.1d: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice on Milk Hygene District Source of Advice on Disease Control % receiving advice out of total 29.1f: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Herd/Flock Size and Selection Total Number of households raising livestock Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 360 Government NGO / Development Project Co- operative Large Scale Farmer Other not applicable Total Rombo 3,737 0 0 0 118 0 3,855 37,949 10 Mwanga 2,755 190 0 43 0 0 2,987 12,792 23 Same 4,337 800 0 0 0 0 5,136 18,506 28 Moshi Rural 11,931 0 139 0 0 139 12,209 56,368 22 Hai 5,904 0 0 0 0 0 5,904 32,839 18 Total 28,664 989 139 43 118 139 30,091 158,453 19 % 95 3 0 0 0 0 100 Government NGO / Development Project Co- operative Otherot applicable Total Rombo 11,823 117 0 118 236 12,294 37,949 32 Mwanga 1,854 532 131 0 43 2,560 12,792 20 Same 2,417 1,097 591 0 0 4,105 18,506 22 Moshi Rural 12,662 138 278 0 0 13,077 56,368 23 Hai 10,213 338 348 0 0 10,899 32,839 33 Total 38,969 2,223 1,348 118 278 42,935 158,453 27 % 91 5 3 0 1 100 Total Number of households raising livestock % receiving advice out of total Source of Advice on Group Formation District Total Number of households raising livestock 29.1g: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Pasture Establishment 29.1.h: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 361 Government NGO / Development Project Co- operative Large Scale Farmer Other not applicable Total Rombo 7,735 0 0 0 0 236 7,971 37,949 21 Mwanga 4,333 284 0 85 0 0 4,702 12,792 37 Same 5,146 1,324 0 0 71 74 6,615 18,506 36 Moshi Rural 21,199 0 0 0 0 139 21,337 56,368 38 Hai 12,111 119 118 0 126 0 12,473 32,839 38 Total 50,525 1,726 118 85 197 449 53,099 158,453 34 % 95 3 0 0 0 1 100 District Total Number of households raising livestock % receiving advice out of total Source of Advice on Calf Rearing 29.1i: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 362 Government NGO / Development Project Co-operative Large Scale Farmer not applicable Total Rombo 10,877 0 0 0 353 11,230 37,949 30 Mwanga 4,444 198 0 43 0 4,685 12,792 37 Same 5,156 1,319 0 0 0 6,476 18,506 35 Moshi Rural 20,846 0 0 0 0 20,846 56,368 37 Hai 10,300 598 235 0 0 11,134 32,839 34 Total 51,623 2,115 235 43 353 54,370 158,453 34 % 95 4 0 0 1 100 Total Number % Number % Number % Number % Number % Number Rombo 5,273 23 13,573 60 3,749 17 0 0 0 0 22,595 Mwanga 2,644 27 5,704 59 1,179 12 215 2 0 0 9,741 Same 3,451 16 11,624 54 3,025 14 875 4 2,551 12 21,525 Moshi Rural 10,386 26 21,629 55 4,840 12 1,091 3 1,516 4 39,462 Hai 6,766 32 10,038 47 2,106 10 1,216 6 1,175 6 21,301 Total 28,519 25 62,568 55 14,899 13 3,396 3 5,242 5 114,624 % receiving advice out of total 29.1j: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice on the Use of Improved Bulls Total Number of households raising livestock Quality of Service District 29.1h: LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Very Good Good Average Poor No Good Tanzania Agriculture Sample Census - 2003 Kilimanjaro Appendix II 363 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 364 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Rombo 4 1 1 0 16 5 70 5 29 55 40 Mwanga 5 1 4 5 19 4 74 8 31 23 25 Same 7 1 6 1 38 4 128 13 32 20 29 Moshi Rur 3 2 1 2 10 3 23 4 16 19 7 Hai 4 2 1 1 15 3 29 6 14 25 7 Total 4 2 2 1 17 4 53 6 22 29 19 Regional Capital 53 All Weather Roads 2 Tarmac Roads 19 Hospitals 17 Tertiary Markets 29 Secondary Market 22 Secondary Schools 4 Primary Markets 6 Health Clinics 4 Primary Schools 2 Feeder Roads 1 Table 33.01a: Mean distances from horders dwellings to Infrastructures and services by District District Mean Distance to Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region Appendix II 365 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % % Rombo 2,112 4 12,648 27 30,775 65 1,479 3 0 0 47,014 28 Mwanga 2,788 17 4,465 27 6,837 41 1,810 11 849 5 16,749 21 Same 2,393 6,747 14,769 2,798 2,396 29,103 Moshi Rur 9,026 12 31,503 41 33,676 44 2,363 3 258 0 76,826 37 Hai 3,088 7 18,670 40 19,713 42 4,819 10 191 0 46,481 8 Total 19,407 9 74,033 34 105,770 49 13,269 6 3,693 2 216,173 25 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of ho% Rombo 27,064 58 12,262 26 7,230 15 458 1 0 0 47,014 1 Mwanga 9,729 58 4,625 28 1,920 11 218 1 300 2 16,792 4 Same 9,365 7,781 6,505 3,328 2,123 29,103 6 Moshi Rural 50,853 66 18,294 24 7,409 10 138 0 132 0 76,826 1 Hai 28,797 62 11,052 24 5,864 13 768 2 0 0 46,481 1 Total 125,808 58 54,014 25 28,928 13 4,911 2 2,555 1 216,216 2 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % f households % Rombo 42,788 91 3,992 8 234 0 0 0 0 0 47,014 0 Mwanga 12,986 78 3,252 19 341 2 0 0 169 1 16,749 5 Same 17,825 9,858 1,282 0 138 29,103 1 Moshi Rural 62,563 81 12,563 16 927 1 516 1 256 0 76,826 2 Hai 37,519 81 7,864 17 474 1 125 0 499 1 46,481 1 Total 173,682 80 37,529 17 3,259 2 641 0 1,062 0 216,173 1 33.01b: Mean distance from holders dwellings to infrastrures and services by District District Distance to Secondary School Total Number of Households Mean Distance Mean Distance 33.01c: Mean distance from holders dwellings to all Weather roads by District District Distance to All Weather Roads Total Number of Households Mean Distance 33.01d: Mean distance from holders dwellings to Feeder Roads by District District Distance to Feeder Road Total Number of Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 366 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of ho% Rombo 117 0 2,684 6 17,881 38 11,037 23 15,295 33 47,014 74 Mwanga 373 2 3,088 18 2,942 18 2,490 15 7,855 47 16,749 90 Same 592 1,323 5 4,021 14 5,846 20 17,321 60 29,103 38 Moshi Rur 2,146 3 9,868 13 35,931 47 20,400 27 8,481 11 76,826 49 Hai 1,177 3 4,859 10 8,083 17 17,971 39 14,390 31 46,481 15 Total 4,405 2 21,822 10 68,858 32 57,744 27 63,343 29 216,173 72 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of ho% Rombo 5,045 11 18,496 39 22,298 47 943 2 232 0 47,014 7 Mwanga 3,700 22 8,004 48 4,709 28 173 1 206 1 16,749 10 Same 2,765 10 12,650 43 11,978 41 489 2 1,220 4 29,103 10 Moshi Rur 13,157 17 35,142 46 26,189 34 1,844 2 493 1 76,826 7 Hai 5,521 12 19,648 42 20,262 44 927 2 123 0 46,481 6 Total 30,189 14 93,941 43 85,437 40 4,377 2 2,273 1 216,173 8 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of ho% Rombo 18,057 38 25,453 54 3,386 7 118 0 0 0 47,014 Mwanga 7,550 45 7,450 44 1,705 10 0 0 43 0 16,749 Same 11,187 14,493 50 3,143 11 207 1 74 0 29,103 Moshi Rur 25,258 33 43,836 57 7,483 10 0 0 249 0 76,826 Hai 13,423 29 28,422 61 4,342 9 96 0 198 0 46,481 Total 75,475 35 119,654 55 20,059 9 420 0 564 0 216,173 33.01e: Mean distance from holders dwellings to Hospital by District District Distance to Hospital Total Number of Households Mean Distance 33.01g: Mean distance from holders dwellings to Primary School by District 33.01f: Mean distance from holders dwellings to Health Clinic by District District Distance to Health Clinic Total Number of Households Mean Distance District Distance to Primary School Total Number of Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 367 District Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Mean Distance Rombo 467 116 938 118 45,375 47,014 70 Mwanga 0 0 78 44 16,585 16,706 74 Same 370 0 0 0 28,733 29,103 128 Moshi Rural 514 261 18,160 20,293 37,598 76,826 23 Hai 241 731 2,828 14,104 28,576 46,481 29 Total 1,591 1,109 22,004 34,558 156,867 216,130 53 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Households Mean Distance Rombo 823 0 1,414 3,299 41,479 47,014 40 Mwanga 1,222 995 1,863 5,403 7,266 16,749 25 Same 1,315 145 2,320 6,378 18,946 29,103 29 Moshi Rural 8,526 16,763 28,417 19,328 3,792 76,826 7 Hai 4,865 6,368 24,371 8,540 2,337 46,481 7 Total 16,750 24,271 58,384 42,947 73,821 216,173 19 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Households Mean Distance Rombo 3,524 13,368 27,303 2,230 589 47,014 5 Mwanga 2,912 2,462 6,607 4,225 543 16,749 8 Same 2,659 8,017 12,569 2,350 3,508 29,103 13 Moshi Rural 8,848 27,004 35,295 4,184 1,495 76,826 4 Hai 4,607 6,295 29,748 5,346 486 46,481 6 Total 22,549 57,146 111,523 18,334 6,620 216,173 6 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Households Mean Distance Rombo 9,017 354 117 0 37,526 47,014 55 Mwanga 263 303 2,013 5,348 8,822 16,749 23 Same 2,249 760 7,282 4,325 14,487 29,103 20 Moshi Rural 1,011 810 23,657 22,120 29,227 76,826 19 Hai 341 357 7,807 12,300 25,676 46,481 25 Total 12,881 2,584 40,876 44,093 115,739 216,173 29 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Households Mean Distance Rombo 9,841 1,525 7,104 3,410 25,134 47,014 29 Mwanga 2,007 184 930 1,921 11,707 16,749 31 Same 1,723 132 4,667 4,801 17,781 29,103 32 Moshi Rural 1,466 1,309 15,909 33,993 24,148 76,826 16 Hai 655 1,248 16,234 17,232 11,112 46,481 14 Total 15,692 4,398 44,845 61,357 89,881 216,173 22 33.1h: Number of Households to Regional Capital 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 368 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 4,561 2 18,100 6 14,838 5 23,339 8 1,160 0 282,085 Mwanga 2,038 2 6,741 7 9,159 9 4,423 4 87 0 100,493 Same 1,607 10,262 16,589 14,786 12,961 174,617 Moshi Rur 10,022 2 38,798 8 41,983 9 3,381 1 4,741 1 460,954 Hai 7,960 3 25,101 9 38,526 14 20,074 7 2,952 1 278,887 Total 26,187 2 99,001 8 121,096 9 66,003 5 21,901 2 1,297,036 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 2,036 9 9,980 46 6,893 32 2,341 11 235 0 21,484 Mwanga 1,314 3,442 2,087 218 0 7,061 Same 942 8 5,785 47 2,936 24 664 5 1,905 16 12,232 Moshi Rur 4,164 10 20,227 48 16,624 40 125 0 681 2 41,821 Hai 3,373 13 12,007 47 8,645 34 1,648 6 0 0 25,673 Total 11,829 11 51,440 48 37,186 34 4,996 5 2,820 3 108,272 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 0 0 0 0 0 0 4,314 95 231 0 4,545 Mwanga 85 214 1,302 1,130 0 2,731 Same 0 0 588 7 2,061 0 2,958 37 2,493 31 8,100 Moshi Rur 817 9 2,291 26 4,415 50 549 6 811 9 8,884 Hai 658 5 1,729 13 6,079 45 4,865 36 295 2 13,626 Total 1,561 4 4,823 13 13,857 37 13,816 36 3,831 10 37,887 33.19b TYPE OF SERVICE: Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total Number of Households 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total Number of Households 33.19c TYPE OF SERVICE: Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year District Research Station Total Number of Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 369 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 0 0 0 0 0 4,313 97 115 3 4,428 Mwanga 42 2 86 3 1,303 52 1,039 41 43 2 2,513 Same 0 0 364 5 1,626 21 3,399 43 2,493 32 7,882 Moshi Rural 540 8 1,488 23 3,164 48 681 10 677 10 6,550 Hai 246 2 1,595 13 5,497 44 4,753 38 347 3 12,438 Total 828 2 3,533 10 11,591 34 14,186 42 3,675 11 33,811 ` Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 118 2 354 5 1,645 24 4,545 66 231 3 6,893 Mwanga 0 0 219 10 1,073 50 869 40 0 0 2,160 Same 74 1 586 7 3,985 46 1,551 18 2,418 28 8,614 Moshi Rural 799 9 2,901 32 4,110 45 549 6 811 9 9,172 Hai 548 5 2,488 21 6,635 55 2,006 17 337 3 12,014 Total 1,540 4 6,548 17 17,448 45 9,520 25 3,798 10 38,853 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Rombo 2,178 0 6,486 36 5,149 29 3,862 22 231 1 17,907 Mwanga 303 981 29 1,789 52 343 10 0 0 3,415 Same 148 0 438 6 2,069 28 3,034 41 1,752 24 7,441 Moshi Rural 531 0 1,546 24 2,712 42 677 11 949 15 6,415 Hai 251 0 1,650 13 5,631 44 3,937 31 1,337 10 12,806 Total 3,411 0 11,101 23 17,350 36 11,852 25 4,269 9 47,983 33.19d TYPE OF SERVICE: Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year District Plant Protection Lab. Total Number of Households 33.19f TYPE OF SERVICE: Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year District Livestock Development Centre Total Number of Households 33.19e TYPE OF SERVICE: Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total Number of Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 370 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Veterinary Clinic 26,187 0 99,001 1 121,096 1 66,003 1 21,901 1 1,297,036 Extension Services 11,829 6 51,440 30 37,186 28 4,996 20 2,820 15 108,272 Research Station 1,561 2 4,823 9 13,857 22 13,816 31 3,831 36 37,887 Plant Protection Lab 828 0 3,533 0 11,591 5 14,186 37 3,675 58 33,811 Land Registration Office 1,540 11 6,548 10 17,448 23 9,520 30 3,798 27 38,853 Livestock Development Centre 3,411 0 11,101 22 17,350 32 11,852 29 4,269 17 47,983 33.19G TYPE OF SERVICE: Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year TYPE OF SERVICE LEVEL OF SATISFACTION OF THE SERVICE Total Number of Households Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 371 HOUSEHOLDS FACILITIES Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 372 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Number of Households Rombo 786 662 43,098 2,469 0 47,014 Mwanga 235 204 15,665 644 0 16,749 Same 734 132 28,021 217 0 29,103 Moshi Rur 801 3,410 66,805 5,674 136 76,826 Hai 1,588 1,129 41,361 2,307 96 46,481 Total 4,143 5,538 194,950 11,310 231 216,173 % 2 3 90 5 0 100 Average Number of rooms per Household Iron sheet Tiles Concreate Asbestos Grass/Leaves Grass & Mud Other Total Number of Households Rombo 3 45,285 350 118 118 1,024 118 0 47,014 Mwanga 4 14,765 212 86 42 1,516 127 0 16,749 Same 3 20,515 148 0 142 6,589 1,635 74 29,103 Moshi Rur 3 72,684 338 133 139 3,401 132 0 76,826 Hai 3 40,594 123 0 641 3,974 504 646 46,481 Total 3 193,843 1,171 337 1,083 16,504 2,516 720 216,173 % 89.7 0.5 0.2 0.5 7.6 1.2 0.0 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 37,125 22 13,482 8 19,602 12 62,079 37 36,124 21 168,412 78 Landline phones 807 22 640 17 0 0 1,529 41 722 20 3,697 2 Mobile Phones 3,508 16 961 4 436 2 11,574 53 5,197 24 21,676 10 Iron 21,631 21 8,200 8 10,026 10 40,602 39 23,994 23 104,453 48 Wheelbarrow 12,889 29 1,269 3 1,512 3 16,620 37 12,122 27 44,412 21 Bicycles 19,634 32 3,681 6 5,447 9 16,250 27 16,194 26 61,206 28 Vehicles 1,523 22 378 5 219 3 3,747 53 1,180 17 7,046 3 Television/Video 700 7 1,058 11 278 3 5,854 63 1,477 16 9,366 4 Total Number of Households 97,817 29,668 37,520 158,253 97,010 216,173 100 District Type of Roofing materials 34-1: Number of Agricultural Households by Type of TOILET by Districtduring the 2002/03 Agricultural Year District Type of Toilet 34-2: Number of Agricultural Households Reported Average Number of Rooms and Type of Roofing Materials by District for the 2002/03 Agricultural Year 34.3: Number of Agricultural Households by Type of Owned Assets and District, 2002/03 Agricultural Year Type of Owned Asset District Rombo Mwanga Same Moshi Rur Hai Total Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 373 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 2,578 10 3,273 12 730 3 14,841 55 5,400 20 26,823 12 Solar 0 10 0 12 72 3 0 55 370 20 441 12 Gas (Biogas) 0 0 87 24 0 0 271 76 0 0 358 0 Hurricane Lamp 20,819 23 8,416 9 11,434 12 30,497 33 20,417 22 91,583 42 Pressure Lamp 2,503 19 420 3 810 6 6,590 51 2,541 20 12,864 6 Wick Lamp 20,878 25 4,474 5 16,057 19 24,217 29 17,754 21 83,380 39 Candles 118 19 0 0 0 0 0 0 118 19 605 0 Firewood 118 10 78 12 0 3 409 55 0 20 605 12 Total Number of Households 47,014 22 16,749 8 29,103 13 76,826 36 46,599 22 216,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 234 15 170 11 0 0 735 46 474 29 1,613 1 Solar 0 0 0 0 0 0 803 71 327 29 1,131 1 Gas (Biogas) 0 0 0 0 0 0 139 100 0 0 139 0 Bottled Gas 118 48 0 0 0 0 0 0 126 52 244 0 Parraffin / Kerocine 118 16 30 4 0 0 371 52 197 28 716 0 Charcoal 117 3 82 2 265 8 2,026 59 959 28 3,449 2 Firewood 45,719 22 16,337 8 28,617 14 72,139 35 44,151 21 206,963 96 Crop Residues 707 38 129 7 147 8 613 33 248 13 1,845 1 Livestock Dung 0 0 0 0 74 100 0 0 0 0 74 0 Total Number of Households 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 Total Rombo Mwanga Same Moshi Rur Hai 34.5: Number of Agricultural Households by Main Source of Energe Used for Cooking and District, 2002/03 Agricultural Year Main Source of Energe for Lighting District 34.4 Number of Agricultural Households by Main Source of Energe Used for Lighting and District, 2002/03 Agricultural Year Main Source of Energe for Lighting District Total Rombo Mwanga Same Moshi Rur Hai Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 374 Source Rombo Mwanga Same Moshi Rur Hai Piped Water Wet 38,601 6,329 7,620 46,766 25,417 Dry 40,625 5,738 8,215 41,986 25,292 Protected Well Wet 324 1,769 590 2,593 346 Dry 221 1,724 663 2,460 229 Protected / Covered Spring Wet 117 682 2,488 2,298 3,481 Dry 353 767 2,416 3,538 3,481 Uprotected Well Wet 0 555 1,153 602 0 Dry 0 642 1,224 602 0 Unprotected Spring Wet 2,511 4,897 13,062 19,300 8,568 Dry 4,215 5,368 13,274 22,856 8,665 Surface Water (Lake / Dam / River / StreamWet 796 2,390 4,190 4,590 8,668 Dry 1,014 2,433 3,310 4,715 8,613 Covered Rainwater Catchment Wet 1,634 83 0 139 0 Dry 118 41 0 132 0 Uncovered Rainwater Catchment Wet 2,916 0 0 121 0 Dry 116 37 0 121 76 Tanker Truck Wet 0 0 0 417 0 Dry 118 0 0 0 0 Other Wet 117 43 0 0 0 Dry 235 0 0 415 126 Total Agricultural Households per District 94,028 33,498 58,206 153,651 92,962 Source Rombo Mwanga Same Moshi Rur Hai Piped Water Wet 41 19 13 30 27 Dry 43 17 14 27 27 Protected Well Wet 0 5 1 2 0 Dry 0 5 1 2 0 Protected / Covered Spring Wet 0 2 4 1 4 Dry 0 2 4 2 4 Uprotected Well Wet 0 2 2 0 0 Dry 0 2 2 0 0 Unprotected Spring Wet 3 15 22 13 9 Dry 4 16 23 15 9 Surface Water (Lake / Dam / River / StreamWet 1 7 7 3 9 Dry 1 7 6 3 9 Covered Rainwater Catchment Wet 2 0 0 0 0 Dry 0 0 0 0 0 Uncovered Rainwater Catchment Wet 3 0 0 0 0 Dry 0 0 0 0 0 Tanker Truck Wet 0 0 0 0 0 Dry 0 0 0 0 0 Other Wet 0 0 0 0 0 Dry 0 0 0 0 0 Season District 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year Season District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 375 Rombo Mwanga Same Moshi Rur Hai Less than 100m Wet 20,684 2,730 6,723 27,131 13,258 Dry 11,672 2,378 6,132 22,461 13,154 100 - 299 m Wet 9,969 4,222 9,399 13,789 8,525 Dry 6,111 4,024 8,737 13,022 8,864 300 - 499 m Wet 943 1,518 1,617 3,211 2,977 Dry 1,532 1,361 1,621 3,357 2,977 500 - 999 m Wet 3,715 4,290 4,800 11,542 8,562 Dry 4,532 4,103 4,802 11,664 8,231 1 - 1.99 Km Wet 5,162 2,962 4,196 11,422 9,442 Dry 4,180 2,696 4,200 13,590 9,410 2 - 2.99 Km Wet 2,541 678 1,135 5,994 1,889 Dry 4,031 773 1,706 7,401 1,937 3 - 4.99 Km Wet 2,608 200 647 1,357 730 Dry 6,587 663 1,320 2,474 820 5 - 9.99 Km Wet 1,392 149 585 2,378 1,098 Dry 8,016 750 585 2,857 1,087 Rombo Mwanga Same Moshi Rur Hai Less than 100m Wet 22 8 12 18 14 Dry 12 7 11 15 14 100 - 299 m Wet 11 13 16 9 9 Dry 7 12 15 8 10 300 - 499 m Wet 1 5 3 2 3 Dry 2 4 3 2 3 500 - 999 m Wet 4 13 8 8 9 Dry 5 12 8 8 9 1 - 1.99 Km Wet 6 9 7 7 10 Dry 4 8 7 9 10 2 - 2.99 Km Wet 3 2 2 4 2 Dry 4 2 3 5 2 3 - 4.99 Km Wet 3 1 1 1 1 Dry 7 2 2 2 1 5 - 9.99 Km Wet 1 0 1 2 1 Dry 9 2 1 2 1 Distance to main Source of Drinking Water Season 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year District Source Season District 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 376 Rombo Mwanga Same Moshi Rural Hai Wet 11,024 1,470 1,161 18,812 10,510 Dry 4,994 1,168 1,096 17,374 10,674 Wet 13,334 4,835 7,950 20,945 9,557 Dry 7,481 4,334 7,474 17,108 9,671 Wet 2,871 2,080 3,507 5,836 3,866 Dry 1,738 1,919 3,178 5,838 4,097 Wet 6,140 4,044 5,804 10,974 7,408 Dry 6,229 3,972 4,932 12,958 7,968 Wet 927 1,013 2,057 2,764 2,399 Dry 706 1,150 1,983 3,174 1,489 Wet 3,288 1,281 2,354 6,651 3,266 Dry 2,703 959 1,624 6,262 2,415 Wet 9,429 2,027 6,271 10,844 9,475 Dry 23,162 3,247 8,817 14,112 10,168 Rombo Mwanga Same Moshi Rural Hai Less than 100m Wet 22 8 12 18 14 Dry 12 7 11 15 14 100 - 299 m Wet 11 13 16 9 9 Dry 7 12 15 8 10 300 - 499 m Wet 1 5 3 2 3 Dry 2 4 3 2 3 500 - 999 m Wet 4 13 8 8 9 Dry 5 12 8 8 9 1 - 1.99 Km Wet 6 9 7 7 10 Dry 4 8 7 9 10 2 - 2.99 Km Wet 3 2 2 4 2 Dry 4 2 3 5 2 3 - 4.99 Km Wet 3 1 1 1 1 Dry 7 2 2 2 1 5 - 9.99 Km Wet 1 0 1 2 1 Dry 9 2 1 2 1 40 - 49 Minutes 50 - 59 Minutes above one Hour 20 - 29 Minutes 30 - 39 Minutes 34.10: Number of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year District Less than 10 10 - 19 Minutes Distance to main Source of Drinking Water Season 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Source Season District Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 377 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % One 4,556 51 175 2 292 3 1,820 21 2,018 23 8,860 4 Two 17,527 24 4,363 6 9,162 13 23,442 32 18,483 25 72,977 34 Three 24,699 19 12,167 9 19,649 15 51,057 38 25,742 19 133,314 62 Four 233 23 44 4 0 0 507 50 239 23 1,021 0 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 7,570 25 3,880 13 6,858 23 5,948 20 6,003 20 30,258 14 One 26,491 31 7,514 9 11,897 14 26,524 31 12,163 14 84,588 39 Two 10,842 17 4,062 6 7,902 12 23,580 37 17,511 27 63,897 30 Three 1,875 7 820 3 1,649 6 14,377 53 8,282 31 27,004 12 Four 118 2 245 4 429 7 3,887 63 1,474 24 6,153 3 Five 0 0 70 4 74 4 887 51 699 40 1,730 1 Six 0 0 38 3 74 6 872 72 224 19 1,209 1 Seven 118 9 120 9 220 17 751 56 125 9 1,335 1 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 34.12: Number of Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day District Total Rombo Mwanga Same Moshi Rur Hai 34.13: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Rombo Mwanga Same Moshi Rur Hai Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 378 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 13,322 44 678 2 4,053 13 4,711 15 7,819 26 30,583 14 One 21,211 33 1,749 3 4,168 6 21,335 33 15,759 25 64,222 30 Two 9,653 16 2,703 4 5,817 10 29,292 48 13,421 22 60,885 28 Three 2,121 8 3,739 14 5,186 19 11,255 41 4,876 18 27,178 13 Four 354 2 3,507 22 4,832 30 4,548 29 2,632 17 15,873 7 Five 0 0 1,895 20 3,083 32 4,030 42 696 7 9,705 4 Six 0 0 922 27 811 23 1,308 38 421 12 3,462 2 Seven 354 8 1,556 36 1,153 27 347 8 857 20 4,266 2 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Never 18,607 16 5,021 4 9,261 8 53,441 45 31,576 27 117,906 55 Seldom 19,588 30 7,220 11 13,266 21 15,666 24 8,732 14 64,472 30 Sometimes 2,678 28 1,393 15 1,556 16 2,799 30 1,011 11 9,438 4 Often 4,041 29 1,924 14 2,390 17 2,732 20 2,665 19 13,752 6 Always 2,100 20 1,192 11 2,630 25 2,186 21 2,497 24 10,605 5 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 Hai Number of Days District Total Rombo Mwanga Same Moshi Rur Hai 34-15: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceeding Year by District 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Status of Food Satisfaction District Total Rombo Mwanga Same Moshi Rur Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. Appendix II 379 Number of Households % Number of Households % Number of Households % Number of Households % Number of Househo lds % Number of Household % Sales of Food Crops 13,120 14 5,120 5 15,766 17 36,928 39 23,982 25 94,916 44 Sale of Livestock 352 6 880 15 1,021 17 1,278 22 2,358 40 5,889 3 Sale of Livestock Products 471 15 126 4 293 10 785 26 1,374 45 3,050 1 Sales of Cash Crops 16,176 47 1,602 5 3,284 10 8,074 24 5,174 15 34,310 16 Sale of Forest Products 118 13 200 23 221 25 0 0 344 39 883 0 Business Income 6,003 28 1,872 9 1,161 5 8,667 40 3,804 18 21,507 10 Wages & Salaries in Cash 4,773 22 1,917 9 1,729 8 10,589 49 2,634 12 21,641 10 Other Casual Cash Earnings 5,532 23 2,817 12 4,030 17 6,788 28 5,248 21 24,415 11 Cash Remittance 469 6 2,092 27 1,243 16 2,961 38 998 13 7,764 4 Fishing 0 0 35 8 0 0 269 65 111 27 416 0 Other 0 0 88 6 355 26 486 35 453 33 1,382 1 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Iron Sheets 45,285 23 14,765 8 20,515 11 72,684 37 40,594 21 193,843 794 Tiles 350 30 212 18 148 13 338 29 123 10 1,171 5 Concreate 118 35 86 26 0 0 133 39 0 0 337 1 Asbestos 118 11 42 4 142 13 139 13 641 59 1,083 4 Grass/leaves 1,024 6 1,516 9 6,589 40 3,401 21 3,974 24 16,504 68 Grass & Mud 118 5 127 5 1,635 65 132 5 504 20 2,516 10 Other 0 0 0 0 74 10 0 0 646 90 720 3 Total 47,014 22 16,749 8 29,103 13 76,826 36 46,481 22 216,173 885 Same Moshi Rur Hai Hai District 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year Roofing Materials District Total Rombo Mwanga 34-16: Number of Households by Main Source of Income and District, 2002/03 Agricultural Year Main Source of Cash Income Total Rombo Mwanga Same Moshi Rur Tanzania Agriculture Sample Census - 2003 Kilimanjaro Region. 381 APPENDIX III QUESTIONNAIRES Appendix III 382 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 383 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 384 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 385 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 386 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 387 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 388 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 389 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 390 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 391 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 392 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 393 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 394 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 395 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 396 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 397 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 398 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 399 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 400 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 401 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 402 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 403 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 404 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 405 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 406 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 407 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 408 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 409 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 410 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 411 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 412 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 413 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 414 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 415 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 416 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 417 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 418 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 419 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 420 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 421 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 422 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 423 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 424 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 425 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 426 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 427 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content 1 Ministry of Agriculture Food Security and Cooperatives Client Service Charter 2 TABLE OF CONTENTS Page 1.0 PREFACE 2 2.0 VISION, MISSION, OUR CORE VALUES 3 3.0 PURPOSE OF THIS CLIENT SERVICE CHARTER 3 4.0 OUR CLIENTS 3 5.0 OUR SERVICES 4 6.0 OUR SERVICE STANDARDS 5 7.0 OUR RESPONSIBILITIES TO CLIENTS 7 8.0 CLIENTS RIGHTS AND RESPONSIBLITIES 8 9.0 FEEDBACK 9 10. OTHER CONTACTS 10 3 1.0 PREFACE The Ministry of Agriculture Food Security and Cooperatives has the responsibility of spearheading Green Revolution whose aim is to enhance productivity, production and to expand market of internal and external crops of the country with the aim of assuring the Nation with food security and enhancing peasants’ income. In the recognition of its mandates and responsibilities, the Ministry has put emphasis on increasing productivity as per the National Agriculture Policy, Cooperatives Development Policy, National Irrigation Policy and the country’s broad emphasis on KILIMO KWANZA. The ultimate goal of the Ministry’s initiatives is to fulfil the goals of MKUKUTA and the National Development Vision (2025) which target to improve Tanzanian’s welfare so as to reach the target of the income of a developing nation and of a middle income nation by 2025. In order to attain these goals, the Ministry has prepared the client service charter whose aim is to improve Government service delivery, with openness and enhance accountability to the public. As part of the implementation of this client service charter, the Ministry of Agriculture Food Security and Co-operatives is launching a statement of accountability to its clients and customers. This client service charter is a social pact for improving accountability between the Ministry of Agriculture Food Security and Co-operatives which deliver services on the one hand, and its clients on the other. This social pact set service delivery standards which are results of consultation between our customers and clients and it vividly set out rights of our clients and mechanisms for dealing with their complaints. This Charter will be reviewed every three (3) years or as need arises Therefore, I request our customers and clients to follow mechanisms ascribed in this client service charter so as to reach goal of improving standards of services. Minister for Agriculture Food Security and Co-operatives Date 4 2.0 VISION, MISSION AND OUR CORE VALUES 2.1 The Vision The vision of the Ministry is to become:“Nucleus for providing policy guidance and services to a modernized, commercialized, competitive and effective agriculture and cooperative system by2025” 2.2 Mission The Ministry’s Mission is: To deliver quality agricultural and co-operative services, provide a conducive environment to stakeholders, provide technical backstopping to Local Government Authorities and facilitate the private sector to contribute effectively to sustainable agricultural production, productivity and cooperative development. 2.3 Our Core Values i. Persuit of excellence in service delivery; ii. Loyalty to the Government; iii. Deligence on duty; iv. Impartiality in service; v. Integrity; and vi. Accountability. 3.0 Purpose of this Client Service Charter The purpose of this Charter is to create awareness of the availability of services offered by the Ministry of Agriculture Food Security and Co-operatives. Either, this Charter will give a chance to our clients to understand our services. Therefore, this charter presents a procedure that client must follow to communicate, to get services, complain, get feedback or comments on quality of services offered by the Ministry. 4.0 OUR CLIENTS 5 4.1 Public Sector i. Staff of the Ministry of Agriculture Food Security and Co-operatives; ii. Institutions that falls under the Ministry of Agriculture Food Security and Co-operatives; iii. Crop Bodies; iv. Local Government Authorities; v. Various public service Agents; vi. Various Ministries; vii. Public service media; viii. Government Institutions; ix. Public Financial Institutions; and x. Institutions of Higher Learning. 4.2 Private Sector i. Farmers/Pastrolists; ii. Groups of Farmers and Patrolists; iii. Buyers of Farmers’ crops; iv. Faith Based Organisations/Civil Society Organisations; v. Crop processors; vi. Business people; vii. Transporters; viii. Private Media Houses; ix. Owners of agriculture industrial products; x. Investors; xi. Researchers outside MoAFC; xii. Private financial institutions; xiii. Private institutions of higher learning institutions; xiv. Various leaders and politicians; and xv. Consumers. 4.3 Non State Actors-NSA i. Development Partners; ii. International Institutions; and iii. Various service providers. 5.0 Our Services 5.1 To Our Customers i. To prepare, issue and supervise policy, law and various circulars on agriculture; ii. To issue reports and statistics; iii. To undertake various researches; ; iv. To co-ordinate quality of extension services; v. To coordinate communications related to Ministry’s activities; vi. To offer training; vii. To give treatment for crops and guarantee of plants and its crops; 6 viii. To supervise and approve the quality of seeds and agricultural inputs; ix. To supervise the quality of irrigation schemes; x. To advise and co-ordinate availability of agricultural seeds and inputs; xi. To anticipate and control pests outbreak; xii. To prepare and distribute agricultural technologies; xiii. To produce seeds and transplants; xiv. To review agriculture plans, programmes and projects; xv. To plan proper use of agricultural land; xvi. To preserve Germplasm; xvii. To approve training curriculum; xviii. To advice on requirements for agriculture professionals; and xix. To issue copyright to the discovers of new agricultural seeds. 5.2 To the Staff of the Ministry i. To build capacity of the staff and their working environment; ii. To provide various remunerations (timely); and iii. To issue copyright to the discovers of new agricultural seeds. 6.0 Service Standards 6.1 Information and Various Statistics i. We will provide right information available-within five (5) working days; ii. We will issue information concerning internal implementation within ninety (90) working days depending on the existing laws and regulations; iii. We will respond to queries by the Controller and Auditor General within twenty one (21) days after receiving the inquiry; iv. We will issue report on the state of food crops production once every half of the year; v. We will issue report on the assessment of agriculture programmes and projects within ninety days (90) depending on the existing laws and regulations; vi. We will issue report on the assessment of the agricultural sector within one hundred and eighty days (180) depending on the existing laws and regulations; vii. We will educate our clients about agriculture plans, programmes and projects within five days (5); and viii. We will issue report on the use of agricultural land within one hundred and eighty (180) days. 6.2 Research and Various Investigations i. We will undertake research and issue report of quality of seed types appropriate for food and trade between 3 - 10 years depending on the type of crop and weather of the concerned place. 7 ii. We will undertake market research, social economy and acceptance of appropriate technology for agriculture within one (1) year. iii. We will undertake research on agronomy of agricultural crops within three (3) years; iv. We will undertake research on the processing and storage of crops within two (2) years; v. We will underatke research on the destructive crop pests within three (3) years; vi. We will undertake research on the agricultural inputs within three (3) years; vii. We will undertake research on the mixed cropping and natural resources within three (3) years; viii. We will make follow up and investigate acceptance of agricultural technology within one (1) year; ix. We will investigate problems that are preventing proper use of technology in agriculture regularly; x. We will investigate irrigation projects within ninety (90) days; xi. We will undertake soil analysis, quantity, quality of water for irrigation within thirty (30) days; xii. We will undertake assessment of environment in the irrigation projects within ninety (90) days; xiii. We will undertake impact assessment and gender in the agricultural activities within ninety (90) days xiv. We will design irrigation infrastructure within six (6) months; and xv. We will undertake survey of land and feasibility assessment in the irrigation projects within six (6) months. 6.3 Professional Advice i. We will offer professional advice to agents of companies responsible for selling of agriculture inputs within five (5) days after receiving the request; i. We will offer professional advice about sustainable use of agricultural inputs especially fertilizers and pesticides within seven (7) days; ii. We will offer advice about development and use of agriculture land (survey, soil sampling, assessment of natural vegetation) within one hundred and eighty (180) days; iii. We will offer advice on the proper use of agricultural inputs within one season (from the time of preparing farm until harvest); iv. We will give advice on the irrigation agriculture within one season (from the time of preparing farm until harvest); v. We will offer advice on the technology for reducing lose of crops, to increase value and correct use of food crops within three (3) months; vi. We will offer professional advice about sustainable farming that takes into consideration environmental conservantion when need arises; vii. We will offer professional advice about farming of various crops when need arises; viii. We will offer advice about preparation of proper irrigation project write ups within seven (7) days; ix. We will offer advice on the proper use of irrigation schemes when need arises. x. We will offer advice to farmers about Intergrated Pest Management within one (1) month; 8 xi. We offer advice about technology for preserving soil, water and mixed agriculture within fourteen (14) days; xii. We will offer advice about gender issues and HIV/AIDS in the agriculture sector regularly; xiii. We offer advice about processing machine, to set standards for packaging regularly; and xiv. We will offer professional advice about laws and regulations for importing and transporting agriculture products, soil and pesticides regularly. 6.4 Normal Advice i. We will educate clients about policies, laws, regulations of the Ministry of Agriculture Food Security and Cooperatives depending on the their needs; 6.5 Communications i. We will acknowledge lettters within two (2) days and reply to the issues raised in letters within five (5) days or as laws and regulations instructs; ii. We will reply to memo or issues raised in the file between two (2) to three (5) days; iii. We will receive phone call before end of three (3) ring tones. 6.6 To build Capacity of the Staff and Improving their Working Environment i. We will enable staff to attend training each year depending on the agreed training plan; ii. We will deal with staff applications for training loans within three (3) days after fulfilling the required conditions; iii. We will offer various remunerations to staff when s/he joins the Ministry, when s/he is in post and when s/he leave post depending on the existing rules and regualtions; iv. We will enable staff to get permission to join various national and international institutions subject to the existing rules and regulations. 6.7 Payment to Staff and Other Stakeholders i. We will deal with requests for pension and inheritance claims with proper documentation within (3) three days; ii. We will deal with payment for Ministry’s staff within five (5) days after receiving proper claims; iii. We will remit funds for running our Centres within fourteen (14) days, Crop Bodies and other institutions within seven (7) days after receiving monthly allocation; iv. We will pay service providers and other customers within twenty (20) days after receiving their claim invoices; v. We will receive requests for procurement and prepare the required documents within fourteen (14) days after receiving the requests; 9 vi. We will process tenders and inform the winning tenderers and enter into contract with as per the estbalished period in the laws, regulations and rules; and vii. We will return bid securities for the winning bidders after entering into contract with the winning bidder within seven (7) days. 6.8 Various Trainings after Receiving Requests i. We will issue training on the use of quality agriculture inputs within fourteen (14) days; ii. We will conduct training on the Proper Feeding within five (5) days; iii. We will conduct training on the Crop Storage after harvesting within fourteen (14) days; iv. We will conduct basic training on quality farming (through brochures, radio programmes, publications, televisión and public awareness events) within seven (7) days; v. We will conduct diploma and advanced diploma courses within two (2) years after admission; vi. We will offer training to our extension officers, drivers of machineries and farmers on the proper use of agriculture inputs within fourteen (14) days; vii. We will conduct training on the developmenr of curriculum within fourteen (14) days; viii. We will undertake review and certify curriculum within fourteen (14) days; ix. We will offer training on the farming of vegetables, fruits and flowers within seven (7) days; x. We will offer training on the conservation of soil and water in farms within (7) days; xi. We will offer training to farmers on the operationalisation of irrigation schemes, proper use of water in farms and initiation of irrigation groups within fourteen (14) days; xii. We will offer training on policy, strategy, laws and circulars on irrigation within fourteen (14) days; xiii. We will offer training on the safe use and preservation of pesticides within fourteen (14) days xiv. We will offer training on how to manage pests outbreak within fourteen (14) days xv. We will offer training on the technology for processing and mixing of food crops within fourteen (14) days; xvi. We will offer training on the Integrated Pests Management for plant pests within fourteen (14) days xvii. We will offer training on how to destroy expired pestsides without affecting environment within fourteen (14) days; 6.9 Various Permissions i. We will issue permission for importing crops and its products within seven (7) days; ii. We will issue permission for importing and exporting food in the country within seven (7) days; iii. We will issue clean certificate of crops against pests within three (3) days; 10 iv. We will issue permission for importing pesticides and plants or crops within one (1) day; v. We will issue permission for importing friendly insects and agents for biological control within three (3) days; vi. We will issue certificate of competence for rehabilitation work of agriculture machinery within three (3) days; and vii. We will issue certificate of inspection of quality of processing machine (Pre-Delivery Inspection-PDI) within three (3) days. 6.10 To Control Disasters i. We will issue warning on the possible outbreak of crop destructive pests/diseases depending on the behavior and the existing data; ii. We will control outbreak of crop destructive pests/diseases with seven (7) days; iii. We will issue report of food trend/situation in the country twice a year; iv. We will issue detailed report on the food situation in the areas with food shortage Twice (2) a year; v. We will put under guarantee places with crop disease outbreak within seven (7) days after report of the outbreak; vi. We will issue warning on the misuse of lands which can lead to soil erosion regularly ; and vii. We will initiate register with a list of events and indicators of dangerous disaster trends. 7.0 Ministry’s Responsibilities to its Clients It is our responsibility at all times to deliver services with the following considerations: i. To continue improving standards of services to our clients; ii. To be transparent and give correct information, in a clear and simple language to our clients; iii. To solve problems quickly when they occur; iv. To acknowledge, respond and take quick action to complaints that might arise during service delivery; v. To have clear standards of our services to meet clients expectations; vi. To communicate and involve our clients and stakeholders to give their opinions and inputs for the purpose of improving our services; and vii. To co-operate with other service providers so as to improve our services. 8.0 Client’s Rights and Responsibilities 8.1 Client’s Rights 11 i. To assess our service standards and to appeal where s/he is not satisfied; ii. To provide privacy and confidentiality of our clients’ issues; iii. To access services, facilities and information in a manner which meets their particular needs’ subject to the prescribed procedures; iv. To be involved in resolving her/his problems and give feedback on standards of services; and v. To be attended with respect. 8.2 Client’s Responsibilities:- i. To have good relations with service providers; ii. To avoid providing any kind of favour, bribe or inducement to Staff and other service providers; iii. To attend scheduled meetings punctually; iv. To provide correct information and in time when required; v. To observe and abide to the laws, regulations and other procedures applicable; and vi. To provide contribution according to the existing policies and regulations on the development of the agricultural and co-operatives sector. 9.0 Feedback Dear client, your advice and opinion is very important in improving Ministry of Agriculture Food Security and Co-operatives’ services. In that respect, we would like to receive your comments, advice or complaints about our services through the following channels; letters, electronic mails, Website, Questionnare, phone, even on one to one with our leadership or the head of responsible Department. All letters must be addressed to: Permanent Secretary, Ministry of Agriculture Food Security and Cooperatives, P.O Box 9192, Dar es Salaam Phone: +255 22 2862480, +255 22 2862064 Fax: +255 22 2862077 E-mail: [email protected] Website: http://www.kilimo.go.tz; http://www.agriculture.go.tz 12 10.0 OTHER CONTACTS The Offices of the Ministry of Agriculture Food Security and Co-operatives are located in Temeke District, Dar es Salaam. Our Offices are opened working days from 7.30 a.m. morning to 3.30 p.m. evening. Either, the Ministry has various Offices that are located outside Dar es Salaam. These include; Zonal Research Centres, Agriculture Institutes, Plant Protectin Centres, Zonal Irrigation Centres, Farmers Training Centres etc. Their Addresses are provided below: HEADQUARTERS: Minister: Hon.Prof. Jumanne Maghembe Mobile Phone: 0786034888 Fax: + 255 -022-2862077 E-mail: [email protected] Deputy Minister: Hon. Eng. Christopher Kajoro Chiza Mobile Phone: 0754 294283 Fax: +255 022 2862077 E-mail: [email protected] Permanent Secretary: Mr. Mohamed Said Muya Mobile Phone: 0732-934035 Fax: + 255 022 2862077 E-mail: [email protected] Deputy Permanent Secretary (Agriculture): Ms. Sophia E. Kaduma Phone: +255 222863503 Mobile Phone: 0754 883459 Fax: + 255 022 2862077 E-mail: [email protected] Deputy Permanent Secretary (Irrigation): Eng. Mbogo Futakamba Phone: +255 222862067 Mobile Phone: 0713361574 Fax: +255 022 2862077 E-mail: [email protected] 13 Director (Policy and Planning: Mr. Emanuel M. Achayo Phone: + 255 222864460 Mobile Phone: 0784 273434 Fax: + 255 022 284460 E-mail: [email protected] Director (Administration and Human Resources): Lilian L. Mapfa. Phone: +255 222862073 Mobile Phone: 0655 285718 Fax: + 255 022 2864324 E-mail: [email protected] Director (Research and Development): Dr. Fidelis Myaka Phone: + 255 222865317 Mobile Phone: 0784 415905 E-mail: [email protected] Director (Crop Development): Mr. Georey Kirenga Phone: + 255 222861392 Mobile phone: 0756 480069 Fax: + 255 022 2861393 E-mail: [email protected] Acting Director (Food Security) Mr. Karimu Bakari Mtambo Phone: + 255 222865968 Mobile Phone: 0754 296527 Fax: +255 022 2865951 E-mail: [email protected] Director (Training): Ms Anne Assenga Phone: + 255 222865317 Mobile Phone: 0784 797734 Mobile Phone: [email protected] Director (Irrigation and Technical Service): Eng. Raphael L. Daluti Mobile Phone: 0784 328319 14 E-mail: [email protected] Director (Cooperatives Development): Ms. Restuta Kahewangwa Phone: + 255 222863533 Mobile Phone: 0655 803744 Fax: + 255 022 2860802 Director ( Land Use Planning): Mr. Paulo Tarimo Phone: + 255 22286450 Mobile Phone: 0754 494910 Fax: + 255 022 2860444 E-mail: [email protected] Director (Agricultural Mechanization): Eng. Richardi Shetto Phone: + 255 222 864544 Mobile Phone: 0713233417 E-mail: [email protected] 15 ZONAL AGRICULTURAL RESEARCH OFFICES Zonal Director, (Dr. January Mafuru) Lake Zone, Ukiriguru Agriculture Research Centre P.O. Box 1433, MWANZA. Tel: +255-732-980-768 Fax: +255-028-2501-079 Zonal Director, (Dr. Eli Kafiriti) Southern Zone, Naliendele Agriculture Research Centre P.O. Box 509, MTWARA. Zonal Director, (Dr. Lucas Mugendi) Northern Zone, Selian Agriculture Research Centre P.O. Box 6024, ARUSHA Zonal Director, Dr Zakaria Malley Southern Highlands Zone Uyole Agriculture Research Centre P.O. Box 400 MBEYA Fax:+255 25 2510065 E-mail:[email protected] Zonal Director, (Mr. Deusdedit Byamungu) Tumbi Agriculture Research Centre Western Zone, P.O. Box 306 TABORA Zonal Director, (Dr Chaboba Mkangwa) Eastern Zone, Ilonga Agriculture Research Centre P.O. Box 33 KILOSA Phone: + 255 232623358/+255 232623201FaX: + 255 232623284 E-mail: [email protected] Zonal Director, (Mr. Leon Mrosso) Central Zone Makutupora Agriculture Research Institute, P.O. Box 1676, DODOMA, Phone: + 255 262 323634 Fax: + 255 262 323 634 E-mail: [email protected] Officer in Charge, (Mr. Julius Mugini) Mikocheni Agriculture Research Centre, P.O. Box 6224, DAR ES SALAAM. Phone: + 255 222775549 E-mail: [email protected] Officer in Charge (Ms. Demitrai Nyambo) Cholima Agriculture Research Institute -Dakawa P.O. Box 1892, MOROGOROPhone: + 255 023 2628687 E-mail: [email protected] 16 Officer in Charge (Mr. Nkoria Kibanda) KATRIN Agriculture Research Centre, P.O. Box Ifakara, MOROGORO, Phone: + 255 023 262 5361 E-mail:[email protected] Officer in Charge (Dr. Adolph Nyaki ) Mlingano Agriculture Research Centre, P.O. Box 5088, TANGA. Phone: + 255 272 647 647 Fax: + 255 272 641 272 E-mail: mlingano@ iwayafrica.com Officer in Charge (Dr. Jackson Nkuba) Maruku Agriculture Research Centre, P.O. Box 127, BUKOBA. Simu: +255 732 983508 Fax: + 255 732 983283 E-mail: [email protected] Officer in Charge (Mr. Silivesta Samali) Horticulture Research and Training Institute (HORTI) Tengeru P.O. Box 1253 ARUSHA. Simu/Fax: + 255 27 255394 Officer in Charge (Mr. Michael Mhosole) Kifyulilo Agriculture Research Centre, P.O. Box 93, MUFINDI. Phone: + 255 0767 373270 +255 0767373270; +255 0767373270 E-mail: [email protected] Officer in Charge (Dr. Dennis Issa), Sugar Research Centre, P.O.Box 30031, KIBAHA. Phone: + 255 23 2402039 Fax: +255 23 2402039 E-Mail: [email protected] Officer in Charge (Mr. Elias Letayo), Hombolo Agriculture Research Centre, P.O. Box 299, DODOMA, Phone: +255 574 816 021 Fax: + 255 26 232 3634 E-Mail: [email protected] Director, (Mr. J. Deteba) Sugar Institute, P.O. Box 97, KIDATU. Telephone:/fax (0) 23 2626050 17 ZONAL IRRIGATION CENTRES Zonal Irrigation Engineer, (Eng.Juma M. Omari) Kilimanjaro Centre, P.O. Box 1843, Moshi, TANZANIA. Phone/Fax: + 255-27-2750494 Zonal Irrigation Engineer, (Eng.Vicent Chikoleka) Mtwara Zone, P.O. Box 671, Mtwara. TANZANIA. Phone/: + 255-23-23334109, Fax: + 255-23-23334109, Zonal Irrigation Engineer (Eng. Archard G. Ruhangisa) Morogoro Zone, P.O. Box 515, MOROGORO, Phone; + 255-23-2604571 Fax: + 255-2604571 Zonal Irrigation Engineer, (Eng. Peter F. Kweka) Mbeya Zone, P.O. Box 3575, MBEYA. Phone: + 255-25-2503485, Fax: +255-25-2502242 Zonal Irrigation Engineer, (Eng. Wilson B. Kalumuna), Mwanza Zone, P.O. Box 11454, MWANZA. Phone: + 255-28-2570964, Fax: +255-28-2570964. Zonal Irrigation Engineer (Eng.Jeremiah L. Bayaga) Tabora Zone, P.O. Box 1053, TABORA. Phone: + 255-26-2604599, Fax: +255-26-604274/2604599 Zonal Irrigation Engineer (Eng. Seth B. Luswema Central Zone, P.O. Box 2182, DODOMA. Phone: + 255-26-2392466, Fax: + 255-26-394980 18 FARMERS TRAINING CENTRES Officer In Charge Mr Amir M. Waziri Bihawana Farmers Training Centre P.O. Box 877, DODOMA. Mobile Phone: 0784 335625 Officer In Charge Ms Regina E. Kihwele Ichenga Farmers Training Centre, P.O. Box 58, NJOMBE. Mobile Phone: 0784 367604 Officer In Charge, Mr. Peter Sanga Inyala Farmers Training Centre, P.O. Box 57, MBEYA. Mobile Phone: 0715508933 Officer In Charge, Mosses A. Temi Mkindo Farmers Training Centre, P.O. Box 40 Turiani, MOROGORO. Mobile Phone: 0718232378 AGRICULTURE TRAINING INSTITUTES Principal, Mr. Dionis R. Lyimo MATI Uyole P.O Box 2292, MBEYA Phone:+255 25 2510015 Mobile Phone: 0754 936184 Fax: +255 25 2510015 E-mail: [email protected] Principal, Mr. Samson Mbizo Madaha Cheyo) MATI Mlingano P.O. Box: 5051, TANGA Phone: No. 027 274884 Mobile Phone: 0757412386 Fax: (0)27 2642884 E-mail: [email protected] Principal, Mr. Waziri Ali Mwinyi MATI Mtwara, P.O. Box 121, MTWARA Phone: (0) 23 2333837 Mobile Phone: 0786458918 Principal, Mr. Sydney S. Kasele MATI Tumbi, P.O. Box 306, TABORA Phone; +255 783 372900 E-mail: [email protected] Principal, Mr. Eng. George Shundi MATI Igurusi P.O. Box 336 MBEYA Mobile Phone: 0754 529367 Principal, Ms. Patricia M. Makwaia MATI Ukiriguru P.O. Box 1434 MWANZA Phone: 028 2550215; Mobile Phone: 0754 027344 Fax: (0)28 2550169 E-mail: [email protected] 19 Principal, Mr. Adam G. Pyuza KATC Moshi P.O. Box 1241 MOSHI Phone/ Fax: 027 2752293 Mobile Phone: 0754390069 E-mail: [email protected] Principal, Mr. Laurent M. Luhembe MATI Ilonga P.O. Box 66. Ilonga KILOSA Phone:. 023 262064 Mobile Phone: 0787 327435 Fax: (0)23 2623284 e-mail: [email protected] Principal Mr. Waziri Ali Mwinyi MATI Mtwara P.O. Box: 121, MTWARA Phone: 023 2333837 Mobile Phone: 0786 458918 Principal Mr. Juma S. Shekidele HORTI Tengeru, P.O. Box 1253, ARUSHA Phone: + 255 27 255394-5 Mobile Phone: 0754 822506 E-mail: [email protected] CENTRES FOR ZONAL PLANT HEALTH SERVICES Zonal Coordinator, Ms. Edna Kimambo Centre for Plant Health Services, Central Zone, P.O. Box 1101 DODOMA Zonal Coordinator, Mr. Edmund Kasalile Centre for Plant Health Services, Southern Highlands Zone, P.O. Box 6328 MBEYA Phone/Fax: 025 2502411 Mobile Phone: 0784277590 Officer in Charge Ms Victoria Ngowo Rodent Control Centre, P.O. Box 3047, MOROGORO. Phone: 0732 930225 FaX: 023 2613351 Mobile Phone: 0759 249697 Zonal Coordinator, Mr. Didas Moshi Centre for Plants Health Services, Northern Zone, P.O. Box 1004, ARUSHA. Phone/Fax: 027 2553387 Mobile Phone: 0784 451648 Zonal Coordinator Mr. Joshua Muro, Centre for Plant Health Services P.O. Box 476 SHINYANGA. Phone/Fax: 027 2762731 Mobile Phone: 0717033803 Officer in Charge, Mr. Elibariki Msami Biological Control Centre, P.O. Box 30031, KIBAHA Mobile Phone: 0754 746458 20 Zonal Coordinator, Dr F. Katagira Coast Zone Centre for Plant Health Services P.O. Box 9192, DAR ES SALAAM. Mobile Phone: 0713 429252 Acting Officer in charge Mr. Paschal L. Luwanda Land Use Planning Centre-Morogoro Eastern Zone P.O. Box 1885/3047 MOROGORO Phone: 2603044/07322930225 Fax: 2613351/2603044 Acting Officer in Charge Mr. Juma O. Mdeke Land Use Planning Centre -Kilimanjaro P.O. Box 1843, MOSHI Simu: 027 270494 Fax: 027 2750494 Acting Officer in Charge Mr. Godwin M. Makori, Land Use Planning Centre -Dodoma (Central Zone), DODOMA, Phone: 026 23 94980, Fax: 026 2392466 Acting Officer Incharge, (Mr. Maisarah A. Abed) Land Use Planning Centre, Mwanza (Lake Zone), P.O. Box 1484, MWANZA Phone: 028 2540683 Fax: 028 2540683 Acting Officer Incharge, (Ms Helen M. Mkoba), Land Use Planning Centre, Mbeya (Highlands Zone), P.O. Box 400, MBEYA, Phone: 255 2510062/255 2510363, Fax: 255 2510065/025 2504169 | false |
# Extracted Content KISHAPU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT (DASIP) ANNUAL IMPLEMENTATION REPORT 2009/10 DISTRICT EXECUTIVE DIRECTOR P.O.BOX 1288 KISHAPU Telephone N0. 0713 189 009 0787 177 817 Fax Na. 0787 660 817 JUNE, 2010 TABLE OF CONTENTS pg 1.0 EXECUTIVE SUMMARY ................................................................................................ 2 2.0 INTRODUCTION AND BACKGROUND INFORMATION .......................................... 3 2.1 Location and coverage.................................................................................................... 3 2.2 Project objectives............................................................................................................ 3 2.3 Project components......................................................................................................... 3 3.0 Approaches used to collect Data......................................................................................... 3 4.0 PLAN AND IMPLEMENTATION STATUS: .................................................................. 3 4.1 The plan: ......................................................................................................................... 3 4.2 Implementation status..................................................................................................... 4 4.2.1 Physical performance.................................................................................................. 4 4.2.1.1 Community planning and Investment in Agriculture component: ............................. 4 4.2.1.2 Farmer’s capacity building component:.......................................................................... 8 4.2.2 Financial status................................................................................................................ 9 4.2.2.1 Budget and disbursements .............................................................................................. 9 5.0 PROBLEMS AND CHALLENGES................................................................................. 11 6.0 RECOMMENDATION.................................................................................................... 11 7.0 WAY FORWARD............................................................................................................ 11 List of tables Table 1: Summary of Cumulative Revenues Vs Expenditures up to June 2010 ............................. 2 Table 2 Summary of Community Investment Projects............................................................................ 6 Table 3.0 FFs Training Statistics ............................................................................................... 8 Table 4 WTF Training statistics ..................................................................................................... 8 Table 5 Financial status of activities in 2009/10 FY ............................................................. 10 List of abbreviations ASDP Agriculture sector development programe ASDS. Agriculture sector development strategy. CMC. Community members committee. CPC. Community project committee. CSC. Community supervision committees. DADP District agricultural development plans DALDO. District agricultural and livestock development Officer DASIP. District agricultural sector investment project. DCDO. District community development officer DE District engineer DED District executive director DFT. District facilitation team. DMEO District monitoring and evaluation officer DPLO District planning officer DPO. District project officer DTC. District training coordinator DWE District water engineer F Y. Financial year FFS. Farmer field schools. KDC. Kishapu district council MAFC Ministry of agriculture food & cooperative MLD&F Ministry of livestock development & fisheries O&M Operation and maintenance O&OD. Opportunities and obstacles for development. PCU. Project coordination unit. PFGs. Participatory farmer groups. PIDP. Participatory integrated development project. RPO. Regional project officer SGPSC Small group project supervision committees TNA. Training needs assessment. VADP. Village agricultural development plans WFT. Ward facilitation team. WTF. Ward training facilitators. WUA. Water users association. 1 1.0 EXECUTIVE SUMMARY This report gives the status of activities planned for 2009/10 financial year, cumulative performance of activities since Jan 2007, Planned activities for the coming 2010/11 Financial year. It covers the work plan and gives details of the implementation progress, physical and financial status of DASIP activities in the District and highlights the challenges and problems encountered during the implementation period. In 2010 financial year a list of activities were planned to be implemented in all 30 villages under DASIP coverage. These include Activities under Community Planning and Investment in Agriculture and Farmer Capacity Building. Targeted activities were to complete 4 crop storage structures at Kalitu, Kabila, Mwamalasa, and Mwigumbi villages. To construct 10 charco dams at Miyuguyu, Mwanulu, Mwalata, Itongoitale, Kijongo Lagana Bulimba, Mwaweja, Bugoro, and Mwamishoni villages.To construct 3 new crop storage structures at Ngeme, Mwajiginya B and Dulisi villages. To facilitate 180 PFGs in long seasonal training and min projects. To provide 2 grain processing machine for 2 groups at Kabila and Bulimba as well as to supervise and senstize beneficiaries in planning and utilizing completed projects. Implementation situation is that, three crop structures and five charco dams were completed. Procurement and installation of one grain milling machine was also completed at Kabila village. However communities were involved and facilitated in preparation of 2010/11 village agriculture development plans (VADPs) using O&OD approach and the result were incorporated in 2010/11 DADP document. In 2009/10 financial year a total of Tshs 233,344,600 was received from PCU to support activities in this particular year, and at the end of June 2010, Tshs 137,679,000 was spent. Cumulative since January 2007 Tshs 1,051,496,600 have been received from PCU, of which Tshs 730,563,000 have been spent. Revenues Vs Expenditures are summarized in table No 1. Table 1: Summary of Cumulative Revenues Vs Expenditures up to June 2010 FINANCIAL YEAR REVENUES EXPENDITURES BALANCE 2006/07 (QUICK WIN) 27,968,000.00 27,968,000.00 ‐ 2007/08 357,320,000.00 302,418,000.00 54,902,000.00 2008/09 432,864,000.00 262,498,000.00 170,366,000.00 2009/10 233,344,600.00 137,679,000.00 95,665,600.00 TOTAL 1,051,496,600.00 730,563,000.00 320,933,600.00 2 2.0 INTRODUCTION AND BACKGROUND INFORMATION 2.1 Location and coverage Kishapu District council is one of 28 Councils implementing the District Agriculture Sector Investment Project (DASIP) and is one of 7 Councils which constitute Shinyanga Region. In the District, DASIP covers 30 Villages out of 103 2.2 Project objectives The objective of project is to increase agricultural productivity and incomes of rural households in the project area. 2.3 Project components Three Project components which operate in the field are:- • Farmers Capacity Building • Community Planning and Investment in Agriculture • Support to Rural Micro finance and Marketing 3.0 Approaches used to collect Data In a process of collecting data from the field the following approaches were used:- • Direct visit project sites and conducting interviews to various stake holders • Direct observations • Community Project committees reports • District Monitoring team reports • Routine reporting from ward/village level staff • Community participatory Monitoring and Evaluation 4.0 PLAN AND IMPLEMENTATION STATUS: 4.1 The plan: Planned activities include:- Component 1: Planning and Investment in Agriculture 9 To complete construction of 4 crop storage structures at Kabila, Mwamalasa, Kalitu and Mwigumbi 9 To facilitate communities in villages where projects have been completed to enable fully utilization. Villages include mwamanota, Bulekela, Mwanulu, Mwalata and Lagana 9 To construct 10 charco dams at Miyuguyu, Itongoitale, Kijongo, Bulimba, Mwaweja, Bugoro, and Mwamishoni villages 9 To construct 3 new storage structures at Ngeme, Mwajiginya B and Dulisi villages 9 To construct 10.5 km medium size rural feeder road at Shagihilu - Ngeme 9 To supervise beneficiaries in utilization of completed projects at Bulekela, Mwamanota, Mpumbula, Lubaga and Mwanghili 3 9 To provide 2 grain processing machine to 2 groups at Kabila and Bulimba villages Component 2: Farmers capacity Building 9 To facilitate farmers to operate 180 Min projects for PFGs graduated in 2008/09 financial year 9 To collect data for Cost benefit analysis on Farmers Field Schools 9 To carry out training of 30 Farmers facilitators on Business planning 9 To carry out training for 26 WTF on Business planning 9 To form 180 new participatory farmers groups 9 To facilitate 180 (one hundred eighty) 2009/10 PFGs on seasonal long training using Farmers Field Schools approach. 4.2 Implementation status 4.2.1 Physical performance 4.2.1.1 Community planning and Investment in Agriculture component: • Construction of crop storage structure at kabila village:- Construction is on progress and additional funds were provided by District council for completion. Implementation status is 95% • Communities in Mwamanota and Bulekela villages were sensitized and facilitated to form associations for operating cattle dips which are in utilization, Charco dam which completed in Mwanulu, Mwalata and Lagana are to be utilized immediate during the rain season • Construction of crop storage structure at Kalitu village:- Construction was completed with additional fund from the District council. Implementation status is 100% • Construction of crop storage structure at Mwigumbi village:- Construction was completed with additional fund from the District council. Implementation status is 100% • Communities in Dulisi, Ngeme and Mwajiginya B were mobilized and sensitized to open bank accounts to enable funds to be trasfered to their accounts. So far no funds transferred to beneficiaries accounts as a result implementation is stagnant. • Construction of 10 charco dams at Miyuguyu, Mwanulu, Mwalata, Itongoitale, Kijongo, Mwamishoni, Bulimba, Bugoro, Mwaweja villages:- Excavation was completed in Mwanulu, Mwalata, Lagana and Kijongo. Implementation for Miyuguyu charco dam is ongoing. • Facilitation of beneficiaries to open bank accounts was done for Charco dams planned for 2009/10 in first quarter. i.e in Mwaweja, Bulimba, Bugoro and Mwamishoni. Funds for these projects were not transferred to respective beneficiaries as a result implementation is dormant. 4 5 • Procurement of one milling machine was completed for one group at Kabila while re advertisement of tender for supply of Sunflower oil mil was also done for shirikisho group at Bulimba village. Implementation of all investment projects are summarized in table no 2 6 Name of Reporting Officer: Kuhabwa,P.B Financial year: 2009/10 SUMMARY OF COMMUNITY INVESTMENT PROJECTS Reporting Date: June, 2010 Annual Report Table 2 Summary of Community Investment Projects DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) Name of District: Kishapu Project Cost Tshs ‘000’ Contributions by Source DASIP Village Number of Households Invest ment Type Total Community Total Received from PCU Balance Unallocated Remarks Mwamalasa 492 Storage structure 35,000 7,000 28,000 28,000 0 0 Completed Kinampanda 555 Crop storage structure 35,000 7,000 28,000 28,000 28,000 Not funded Bulekela 724 Cattle dip & cattle trough 35,000 7,000 28,000 13,968 14,032 14,032 Dip completed, cattle trough not funded Kisesa 537 Crop storage structure 35,000 7,000 28,000 28,000 28,000 Not funded Mwalata 245 Charco dam 35,000 7,000 28,000 28,000 0 0 completed Shagihilu 403 Crop storage structure 35,000 7,000 28,000 28,000 28,000 Not funded Ngeme 347 Crop storage structure 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Mwanulu 164 Charco dam 35,000 7,000 28,000 28,000 0 0 completed Lubaga 406 Rural feeder road &road drift 35,000 7,000 28,000 12,000 16,000 16,000 Road reh.completed Drift not funded Kakola 176 Shallow wells 35,000 7,000 28,000 28,000 28,000 Not funded Bulimba 392 Charco dam 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Mwaweja 313 Charco dam 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Kijongo 613 Charco dam 35,000 7,000 28,000 28,000 0 0 Completed Mwajiginya B 156 Crop storage structure 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Ikoma 526 Irrigation structure 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Isagala 361 Crop storage structure 35,000 7,000 28,000 28,000 28,000 Not funded Miyuguyu 224 Charco dam 35,000 7,000 28,000 28,000 0 0 On gong Mihama 541 Charco dam 35,000 7,000 28,000 28,000 28,000 Not funded Lagana 502 Charco dam 35,000 7,000 28,000 28,000 0 0 Completed Mwamanota 484 Cattle dip & cattle 35,000 7,000 28,000 13,968 14,032 14,032 Dip completed, 7 Project Cost Tshs ‘000’ Contributions by Source DASIP Village Number of Households Invest ment Type Total Community Total Received from PCU Balance Unallocated Remarks trough cattle trough not funded Kalitu 158 Storage structure 35,000 7,000 28,000 28,000 0 0 completed Bugoro 413 Charco dam 35,000 7,000 28,000 28,000 0 0 Received but not transferred to ben Dulisi 612 Crop Storage structure 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Nyenze 747 Crop Storage structure 35,000 7,000 28,000 28,000 28,000 Not funded Mpumbula 338 Cattle dip & shallow wells 35,000 7,000 28,000 20366 7,634 7,634 Dip completed shallo well not funded Mwigumbi 768 Storage structure 35,000 7,000 28,000 28,000 0 0 completed Kabila 567 Storage structure 35,000 7,000 28,000 28,000 0 0 On going Itongoitale 280 Cattle dip/charco dam 35,000 7,000 28,000 28,000 0 0 ongoing Mwanghili 229 Rural feeder road 35,000 7,000 28,000 28,000 0 0 completed Mwamishoni 490 Charco dam 35,000 7,000 28,000 28,000 0 0 Funds Received but not transferred to beneficiaries Total 1,050,000 210,000 840,000 592,302 247,698 247,698 Source: KISHAPU DC Department of Agriculture 4.2.1.2 Farmer’s capacity building component: To carry out min projects for 180 PFGs 180 Farmers participatory groups, which graduated in 2008/09 farming season, were facilitated to prepare profitable income generating projects. In this exercise 154 out of 180 PFGs managed to prepare business plans. Moreover 99 PFGs have received funds and engaged in preparation of min projects, while the rest 55 PFGs are in a process to open bank accounts. Data collection for cost benefit analysis Collection of data on production was conducted for 2008/09 PFGs and analyzed to check whether the FFS exercise brings a change in production. The results show that there is a great increase in production after the application of FFS. Examples of cost benefit analysis are summarized in the attached annex 1 Training of Farmers Facilitators and WTF business plan Six days training was conducted and completed for both WTFs and FFs on business planning. Participants of this training are applying the knowledge to facilitate PFGs in preparation of Business plans. Table 3.0 FFs Training Statistics Name of District No of Villages Number of FFs trained Total Male Female KISHAPU 30 30 25 5 Table 4 WTF Training statistics Name of District Number of WTFs trained Total Male Female KISHAPU 26 23 3 Formation of Farmers Participatory Groups in 2009/10 farming season In 2009/10 farming season the plan was to form 180 Participatory Farmers Groups, at the end of first quarter, 180 groups were formed as planned. 8 Farmers Field Schools After the formation of participatory farmers groups, members were facilitated to prepare and participating in a long seasonal training through Farmers field school approach. This activity was not performed as planned, due to delayed transfer of funds to targeted beneficiaries as a result only 99 PFGs were funded for this activity. 4.2.2 Financial status 4.2.2.1 Budget and disbursements In 2009/10 financial year, a total of Tshs 621,372,000/= was budgeted to support DASIP activities and at the end of June 2010 Tshs 233,344,600/= was disbursed by PCU, which makes cumulative disbursement of Tshs 1,051,496,600/= from 2006/07 to date. Total expenditure from 2006/07 FY to date is Tshs 730,563,000/=. Financial status for the activities funded during the 2009/10 financial year is summarized in table 5. 9 Table 5 Financial status of activities in 2009/10 FY Activity Approved budget Tshs '000' Amount received Tshs '000' Amount spent Tshs '000' Balance Tshs '000' Training of WTF 6,299.00 6,299.00 6,299.00 ‐ Training of FFs 4,175.00 4,175.00 4,175.00 ‐ Nanenane 2,310.00 2,310.00 2,310.00 ‐ Micro projects Bulimba, Dulisi, Mwajiginya B, Ikoma, Bugoro, Ngeme, Mwaweja, mwamishoni 224,000.00 58,365.60 58,365.60 Long season training for 180 PFGs 90,000.00 90,000.00 49,500.00 40,500.00 Office operation and staff allow 4,147.50 4,147.50 4,147.50 ‐ PFG formation 2,300.00 2,300.00 2,300.00 ‐ Office operation and staff allow 4,147.50 4,147.50 4,147.50 ‐ Support of 2008/09 PFG min projects 61,600.00 61,600.00 36,800.00 24,800.00 Construction of charco dam at Kijongo village (carried over 08/09) 28,000.00 Total 398,979.00 233,344.60 137,679.00 95,665.60 10 5.0 PROBLEMS AND CHALLENGES. The following are the Challenges/problems met 1. It is a challenge that some of funds received from PCU to support activities were not transferred to beneficiaries yet. 2. Inadequate contribution of some of communities as a results projects not completed in time 3. Rapid change of prices especially for fuel and construction materials affects direct the implementation of projects 4. It is a challenge that some of completed projects are not fully utilized for example dip tanks 6.0 RECOMMENDATION 1. Close supervision to communities is needed at least a regular visit three times a week for every project to improve the capacity of community project management 2. Close supervision and follow up should be made by beneficiaries and District technical staff to monitor the performance of service providers especially contractors, thus we request the funds for office maintenance and staff allowance to be increased to meet the cost. 3. Funds which have been received from PCU to be transferred to respective beneficiaries immediately to support the planned activities 7.0 WAY FORWARD The following are the activities planned in quarter II 1. To facilitate communities in utilizing completed projects so as to achieve the planned objectives 2. Participatory Monitoring and evaluation of activities in 30 villages as well as training of weak community supervision committees 3. To sensitize community to contribute and participate in implementation of projects in order to speed up implementation 4. To implement all projects, which have been funded but are dormant due to late transfer of funds to beneficiary’s accounts. 11 List of annexes Annex 1 Cost benefit analysis for cotton KISHAPU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT (DASIP) INCOME ANALYSIS FOR COTTON PRODUCTION IN MWAJIGINYA B VILLAGE KISHAPU Unit Before FFS After FFS Revenue Yield Kg/acre 400 695 Post-harvest loss (8%) Kg/acre 0 0 Net yield Kg/acre 400 695 Selling price Ths/kg 500 500 Total Revenue Tsh/acre 200,000 347,500 Production cost Land preparation Tsh/acre 16,500.00 16,500.00 Seeds Tsh/acre 6,000.00 3,000.00 Planting costs Tsh/acre 3,000.00 15,000.00 Weeding Tsh/acre 30,000.00 45,000.00 Fertilizers: Farm yard manure Tshs/ekari - 40,000.00 Urea - - Pesticides 9,000.00 7,000 …………… Harvesting Tshs/ekari 23,000.00 60,000.00 Storage Tshs/ekari - Total cost Tshs/ekari 87,500.00 186,500.00 Net revenue Tshs/ekari 132,500 161,000.00 Net cash revenue Tshs/ekari Cost:Benefit Ratio 0.66:1 1:1.1 Increase in yield % 74% Break even price Tsh/kg 12 | false |
# Extracted Content KISHAPU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT (DASIP) SEMI ANNUAL (JULY-DEC) PROGRESS REPORT 2008/09 DISTRICT EXECUTIVE DIRECTOR P.O.BOX 1288 KISHAPU Telephone N0. 0713 189 009 0787 177 817 Fax Na. 0787 660 817 DECEMBER, 2008 TABLE OF CONTENTS pg 1.0 INTRODUCTION AND BACKGROUND INFORMATION: ......................................... 1 1.1 Location and coverage.................................................................................................... 1 1.2 Project objectives............................................................................................................ 1 1.3 Project components......................................................................................................... 1 1.4 Scope of the report.......................................................................................................... 1 2.0 PLAN AND IMPLEMENTATION STATUS: .................................................................. 1 2.1 The plan: ......................................................................................................................... 1 2.2 Implementation status..................................................................................................... 2 2.2.1 Physical performance.................................................................................................. 2 2.2.1.1 Community planning and Investment in Agriculture component: ............................. 2 2.2.1.2 Farmer’s capacity building component:.......................................................................... 6 2.2.2 Financial status.............................................................................................................. 10 2.2.2.1 Budget and disbursements ............................................................................................ 10 2.2.2.2 Expenditures ................................................................................................................. 11 3.0 PROBLEMS AND CHALLENGES................................................................................. 11 4.0 RECOMMENDATION.................................................................................................... 11 5.0 WAY FORWARD............................................................................................................ 12 List of tables Table 1 Proposed Sites for Medium size rural infrastructure............................................... 3 Table 2 Summary of Community Investment Projects................................................................... 4 Table 3.0 FFs Training Statistics ............................................................................................... 6 Table 4 Summary for participatory farmer groups .................................................................. 9 Table 5.0 Budget against disbursement................................................................................. 10 Table 6.0 Expenditures for the semi annual .......................................................................... 11 List of figures Figure 1 Rural feeder road under construction at Mwanghili village............................................. 5 Figure 2 picture of FFs class phase 1 training ................................................................................ 7 List of annexes Annex 1 Cost benefit analysis for cotton...................................................................................... 13 1.0 INTRODUCTION AND BACKGROUND INFORMATION: 1.1 Location and coverage Kishapu District council is one of 28 Councils implementing the District Agriculture Sector Investment Project (DASIP) and is one of 7 Councils in Shinyanga Region. In the District DASIP covers 30 Villages out of 103 1.2 Project objectives The objective of the project is to increase agricultural productivity and incomes of rural households in the project area. 1.3 Project components Three Project components which operate in the field are:- • Farmers Capacity Building • Community Planning and Investment in Agriculture • Support to Rural Micro finance and Marketing 1.4 Scope of the report This report gives the status of activities planned during the semi annual 2008/09, cumulative performance of activities since Jan 2007, Planned activities for the coming 2008/09 third quarter. It covers the work plan and gives details of the implementation progress, physical and financial status of DASIP activities in the District and highlights the challenges and problems encountered during the implementation period. 2.0 PLAN AND IMPLEMENTATION STATUS: 2.1 The plan: Planned Activities in the quarter include:- Component 1: Planning and Investment in Agriculture 9 To construct 5 km rural feeder road at Mwanghili village 9 To construct 6 km rural feeder road at lubaga village. 9 To construct 4 crop storage structures at Kabila, Mwamalasa, Kalitu and Mwigumbi 9 To construct 6 charco dams at Miyuguyu, Mwanulu, Mwalata, Itongoitale, Kijongo and Lagana villages 9 To construct two catle dips at Mwamanota and Mpumbula villages 9 To identify areas for Medium size rural infrastructures Component 2: Farmers capacity Building 9 To carry out 60 Min projects for PFGs graduated in 2007/08 financial year 9 To collect data for Cost benefit analysis on Farmers Field Schools 9 To train 30 Farmers facilitators 1 9 To form 180 participatory farmers groups 9 To carry out Farmers Field Schools for 180 formed groups 2.2 Implementation status 2.2.1 Physical performance 2.2.1.1 Community planning and Investment in Agriculture component: • Construction of rural feeder road at Mwanghili village:- 5 km was formed side slopes with drainage structures and 900 m3 morrum applied on 3.5 km length. Implementation is about 90% • Construction of rural feeder roads at Lubaga village:- 6 Km was formed and spot application of morrum. Implementation is about 95% • Construction of storage structure at Kabila village:- Foundation was completed and construction of walls is on going, Implementation is about 30% • Construction of crop storage structure at Mwamalasa village:- Collection of materials and foundation trench excavation stages.This is estimated to be 10% implementation • Construction of crop storage structure at Kabila village:- Collection of materials and excavation of foundation trench. This is estimated to be 10% implementation • Construction of crop storage structure at Mwigumbi village:- Implementation is at Tender advertisement stage • Construction of 6 charco dams at Miyuguyu, Mwanulu, Mwalata, Itongoitale and Kijongo villages:- All projects are under tender advertisement stage • Construction of cattle dip at Mwamanota village:- Roofing and construction of entrance and exit sheds. This is estimated to be 60% implementation stage • Construction of cattle dip at Mpumbula village:- Implementation stage is at tender advertisement • Identification of areas for medium size rural infrastructure:- Through a demand driven process three sites was identified for construction of rural feeder roads and water structure as indicated in table no 1. 2 3 Table 1 Proposed Sites for Medium size rural infrastructure Ward Village Proposed site Size/length Description Mwakipoya Ngeme Rural feeder road Ngeme - Shagihilu 10 km Will facilitate easy access and transportation of agriculture produce cotton and paddy as well as in puts and equipments Uchunga Kakola Kakola – Ngundangali rural feeder road 5 km Proposed Infrastructure will facilitate access to market for agriculture produce including the supply of in puts in the village The village is potential for production of cotton, Horticultural crops and Bulrush millet Talaga Kijong o Kijongo – Nhobola rural feeder road 5 km Proposed project will facilitate access to market for paddy and cotton as the major crops in the village Itilima Ikoma Irrigation Water control structure Potential area 1950ha. Will facilitate production of paddy in 1950 potential areas Implementation of all investment is summarized in table no 2.0 Table 2 Summary of Community Investment Projects DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) SUMMARY OF COMMUNITY INVESTMENT PROJECTS Name of District: Kishapu Reporting Date: December 2008 Quarter: Semi Annual Name of Reporting Officer: Kuhabwa,P.B Financial year: 2008/09 Project Cost Tshs ‘000’ Contributions by Source DASIP Village Number of Households Invest ment Type Total Community Total Disbursed Balance Unallocated Remarks Mwamalasa 492 Storage structure 35,000 7,000 28,000 28,000 Nil Kinampanda 555 28,000 Bulekela 724 Cattle dip 17,460 3,492 13,968 13,968 14032 14,032 Kisesa 537 28,000 Mwalata 245 Charco dam 35,000 7,000 28,000 28,000 Nil Shagihilu 403 28,000 Ngeme 347 28,000 Mwanulu 164 Charco dam 35,000 7,000 28,000 28,000 Nil Lubaga 406 Rural feeder road 15,000 3,000 Kakola 176 Shallow wells 35,000 7,000 28,000 28,000 Bulimba 392 28,000 Mwaweja 313 Kijongo 613 Charco dam 35,000 7,000 28,000 28,000 Nil Mwajiginya B 156 28,000 Ikoma 526 Irrigation structure 35,000 7,000 28,000 28,000 Isagala 361 Miyuguyu 224 Charco dam 35,000 7,000 28,000 28,000 Nil Mihama 541 Lagana 502 Charco dam 35,000 7,000 28,000 28,000 Nil Mwamanota 484 Cattle dip Kalitu 158 Storage structure 35,000 7,000 28,000 28,000 Nil Bugoro 413 28,000 Dulisi 612 28,000 Nyenze 747 28,000 Mpumbula 338 Cattle dip 25,457 5091 20366 20366 7,634 7,634 Mwigumbi 768 Storage structure 35,000 7,000 35,000 28,000 Nil Kabila 567 Storage structure Itongoitale 280 Cattle dip/charco dam 35,000 7,000 35,000 28,000 Nil Mwanghili 229 Rural feeder road 35,000 7,000 35,000 28,000 Nil Mwamishoni 490 28,000 Total 10618 Source: KISHAPU DC Department of Agriculture ** In column 3 (type of investment) blank means Project not yet identified 4 5 Figure 1 Rural feeder road under construction at Mwanghili village 6 2.2.1.2 Farmer’s capacity building component: To carry out min projects for 60 PFGs 60 Farmers participatory groups which graduated in 2007/08 farming season were facilitated to open bank accounts for the purpose of operating income generating projects. 30 PFGs have completed the process and funds transferred to the respective accounts as grants to support activities of these min projects. Data collection for cost benefit analysis Collection of data on production was conducted for 2007/08 PFGs and analyzed to check weather the FFS exercise brings a change in production. The results show that there is a great increase in production after the application of FFS. Examples of cost benefit analysis are summarized in the attached annex …. Training of Farmers Facilitators Training was conducted from 10/12/2008 to 13/12/2008. All 30 trainees from 30 DASIP villages attended the training. Table no 3 summarises training statistics Table 3.0 FFs Training Statistics Name of District No of Villages Number of FFs trained Total Male Female KISHAPU 30 30 25 5 7 Figure 2 picture of FFs class phase 1 training 8 Formation of Farmers Participatory Groups in 2008/09 farming season In 2008/09 farming season the plan was to form 180 Participatory Farmers Groups, at the end of December 2008, 134 groups have been formed. The process is on going. Farmers Field Schools 2008/09 farming season PFGs were engaged in land preparation for crop enterprises and procurement procedures for livestock enterprises. Procurement of materials and in puts to be distributed to all PFGs is at final stage. 9 Table 4 Summary for participatory farmer groups DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) DISTRICT SUMMARY FOR PARTICIPATORY FARMER GROUPS (PFG) NAME OF DISTRICT: Kishapu QUARTER: Semi Annual REPORTING DATE: 18, December 2008 YEAR: 2008/09 NAME OF REPORTING OFFICER: Kuhabwa,P.B 2008/09 NUMBER OF MEMBERS WARD VILLAGE FORMED GRADUATED Male Female Total ENTERPRISE REMARKS Mwamalasa Mwamalasa 2 27 16 43 Cotton/sorghum Mwamalasa Kinampanda Masanga Bulekela 6 77 74 151 Cotton/poultry Somagedi Kisesa 6 82 69 151 Cotton/poultry Shagihilu Mwalata 6 75 61 136 Cotton/poultry Shagihilu Shagihilu 6 62 72 134 Cotton/Sorghum Mwakipoya Ngeme 6 114 37 151 Sunflower/paddy/cotton Kishapu Mwanulu 5 68 24 92 Cotton/sorghum/poultry Kishapu Lubaga 3 45 25 70 Cotton/poutry Uchunga Kakola 4 60 42 142 Poultry/hort./sunflower Ukenyenge Bulimba 6 75 52 127 cotton Ukenyenge Mwaweja Talaga Kijongo 6 86 64 150 Pady/cotton/sorghum Itilima Mwajiginya B 4 31 46 77 Paddy/cotton/sorghum Itilima Ikoma 6 80 69 149 Paddy/cotton/poultry Mwamashele Isagala 6 102 48 150 Cotton/sorghum/poultry Kiloleli Miyuguyu 4 52 23 75 Cotton/sunflower/sorghum Lagana Mihama 6 99 53 152 cotton Lagana Lagana 6 101 49 150 Cotton/sorghum Mwamanota Mwamanota 6 81 69 150 Cotton/sorghum Kalitu Kalitu 6 151 51 202 Cotton sorghum Seke Bugoro Bugoro 6 Seke Bugoro Dulisi 5 43 61 104 cotton Mwadui Lohumboi Nyenze 3 64 5 69 Cotton Songwa Mpumbula 6 89 47 136 Cattle/cotton/sunflower/poultry Mondo Mwigumbi 2 17 33 40 Cotton Mondo Kabila 5 56 69 125 Cotton Bunambiyu Itongoitale 3 41 26 67 Cotton Bunambiyu Mwanghili 5 93 32 125 Cotton Bubiki Mwamishoni Total 131 1871 1217 3118 Source: KISHAPU DC, Department of Agriculture 2.2.2 Financial status 2.2.2.1 Budget and disbursements Planning and investment in Agriculture component: A total 531,214,000/= was budgeted to support projects for the 2008/09 financial year under the component of planning and Agriculture investment. Cumulatively from 2006/07 up to the end of this quarter the District has received a total Tshs 463,436,000 for community projects and Tshs 26,700,000 for office operation and maintenance costs, staff allowance and motorcycle allowances. Farmer capacity building A total 54,727,000/= was budgeted to support farmer capacity building activities this financial year. Cumulatively Under this component the District has received Tshs 192,392,000/= Budget and disbursements are summarized in table no 5.0 Table 5.0 Budget against disbursement Source component Annual budget Actual amount Cummulative received this amount received semi annual from 06/07-08/09 DASIP (PCU) 1.Planning and Investment community projects 519,164,000.00 142,366,000.00 463,436,000.00 - - Operation&maintenance and staff allowances 12,050,000.00 6,025,000.00 26,700,000.00 Sub total 531,214,000.00 148,391,000.00 490,136,000.00 2.Farmer capacity building Operation&maintenance and staff allowances 4,300,000.00 2,150,000.00 2,150,000.00 Support to FFS 50,427,000.00 126,342,000.00 190,242,000.00 Sub total 54,727,000.00 128,492,000.00 192,392,000.00 3.Support to rural financial - - services and marketing Nil Nil Nil Grand Total 585,941,000.00 276,883,000.00 682,528,000.00 10 2.2.2.2 Expenditures A total Tz Shs 61,227,500 expended during this period. Table 6.0 Expenditures for the semi annual Month Expenditure July - Augost 1,290,000.00 September 5,140,000.00 October 30,386,000.00 November 20,181,500.00 December 4,230,000.00 Total for the semi annual 61,227,500.00 3.0 PROBLEMS AND CHALLENGES. The following are the Challenges/problems met 1. It is a challenge that we did not implement and complete 6 charco dams wich has been approved and funded by PCU, We are intending to complete this task next quarter 2. Delays in release of funds planned for implementation of projects in the first quarter of financial year 2008/09 lead to delayed start up of activities as results some of the projects could not be implemented well during the rain season. Project of that nature include irrigation schemes and charco dams 3. Rapid change of prices especially for fuel and construction materials affects direct the implementation of projects 4. Poor participation and contribution of some of communities as a results projects not completed in time 5. Poor performance of some of building contractors 6. Lack of competent contractors on construction of charco dams 4.0 RECOMMENDATION 1. It is recommended that DASIP (PCU) should send the funds timely to the District so that implementation of community investment projects is done in the planned period. 2. Close supervision to communities is needed at least a regular visit three times a week for every project to improve the capacity of community project management 3. Close supervision and follow up should be made by beneficiaries and District technical staff to monitor the performance of service providers especially contractors, thus we request the funds for office maintenance and staff allowance to be increased to meet the cost. 11 5.0 WAY FORWARD The following are the activities planned in quarter III 1. To construct charco dams at Miyuguyu, Itongoitale, Mwanulu, Kijongo and Mwalata. 2. Monitoring and evaluation of activities in 30 villages 3. Formation of 69 PFGs 4. Implementing 60 Min projects for 60 PFGs graduated in 2007/08 financial year 12 List of annexes Annex 1 Cost benefit analysis for cotton KISHAPU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT (DASIP) INCOME ANALYSIS FOR COTTON PRODUCTION IN MWAMISHONI VILLAGE KISHAPU Unit Before FFS After FFS Revenue Yield Kg/acre 320 670 Post-harvest loss (8%) Kg/acre 0 0 Net yield Kg/acre 320 670 Selling price Ths/kg 500 500 Total Revenue Tsh/acre 160,000.00 335,000.00 Production cost Land preparation Tsh/acre 16,000.00 16,000.00 Seeds Tsh/acre 6,000.00 3,000.00 Planting costs Tsh/acre 3,000.00 10,000.00 Weeding Tsh/acre 30,000.00 45,000.00 Fertilizers: Farm yard manure Tshs/ekari - 32,000.00 Urea - - Pesticides 9,000.00 7,000 Karate …………… Harvesting Tshs/ekari 23,000.00 50,000.00 Storage Tshs/ekari - Total cost Tshs/ekari 87,000 153,000 Net revenue Tshs/ekari 51,000.00 182,000 Net cash revenue Tshs/ekari Cost:Benefit Ratio 0.54:1 0.46:1 Increase in yield % 109% Break even price Tsh/kg 13 | false |
# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA PROGRAMU YA KUENDELEZA S EKT A YA KILIMO AWAMU YA PILI (AS DP II) Novemba, 2017 “SEKTA YA KILIMO KWA MAENDELEO YA VIWANDA” JAMHURI YA MUUNGANO WA TANZANIA PROGRAMU YA KUENDELEZA SEKTA YA KILIMO AWAMU YA PILI (ASDP II) “Sekta ya Kilimo kwa Maendeleo ya Viwanda” Novemba, 2017 i ASDP II YALIYOMO 1 Utangulizi ..........................................................................................1 2 Mafanikio ya ASDP I ..........................................................................2 3 Changamoto za ASDP I .......................................................................3 4 Tulichojifunza kutoka ASDP I .............................................................. 4 5 Ajenda ya Mageuzi ya Sekta ya Kilimo katika ASDP II .......................... 4 6 Misingi Mikuu ya Utekelezaji wa ASDP II ............................................ 7 7 Malengo, Mkakati na Matokeo ya ASDP II ........................................... 9 8 Maeneo Makuu ya Utekelezaji na Vipaumbele vya Uwekezaji katika ASDP II ................................................................... 9 9 Utekelezaji wa ASDP II kwa kufuata mpangilio wa maeneo makuu 4 ya programu ........................................................................12 10 Taasisi na Muundo wa Uratibu wa ASDP II ........................................ 13 11 Ufuatiliaji naTathimini ya ASDP II ..................................................... 21 12 Gharama na Ugharamiaji wa Programu ............................................... 22 1 ASDP II 1 Utangulizi Sekta ya kilimo ina mchango mkubwa katika ukuaji wa uchumi wa Tanzania. Asilimia 90 ya ardhi ya Tanzania hulimwa na wakulima wadogo. Sekta inatoa ajira kwa asilimia 65.5 na huchangia asilimia 29.1 ya pato la Taifa, asilimia 30 ya soko la nje na asilimia 65 ya malighafi za viwanda. Ili kuendeleza sekta ya Kilimo, Serikali kupitia Wizara za Sekta ya Kilimo (ASLMs)1 na kwa kushirikiana wa wadau wa sekta imeandaa Programu ya Kuendeleza Sekta ya Kilimo Awamu ya pili (ASDP II). ASDP II ni muendelezo wa awamu ya kwanza ya Programu ya Kuendeleza Sekta ya Kilimo (ASDP I) iliyotekelezwa kuanzia 2006/2007 hadi 2013/2014. ASDP II ni mpango wa miaka kumi utakaotekelezwa kuanzia 2017/2018 hadi 2017/2028 kwa vipindi viwili vya miaka mitano mitano. Utekelezaji wa awamu ya kwanza utaanza 2017/2018 hadi 2022/2023. ASDP II inalenga katika kuleta mageuzi ya Sekta ya kilimo (kilimo, mifugo na uvuvi) ili kuongeza uzalishaji na tija, kufanya kilimo kiwe cha kibiashara zaidi na kuongeza pato la wakulima wadogo kwa ajili ya kuboresha maisha yao, uhakika wa usalama wa chakula na lishe, na kuchangia katika pato la Taifa. ASDP II imeandaliwa kwa kuzingatia mikakati yote ya Taifa: Dira ya Maendeleo ya Taifa ya 2025; Mpango wa Maendeleo wa Muda Mrefu (2012-2021); Mpango wa Maendeleo wa Miaka Mitano (2016- 2021); Mkakati wa Kuendeleza Sekta ya Kilimo (2015) na Mpango wa Uwekezaji katika Sekta ya Kilimo (Tanzania Agriculture and Food Security Investment Plan – TAFSIP 2011). Pia programu hii imezingatia mambo makuu tuliyojifunza katika utekelezaji wa ASDP I ili kukabiliana na mapungufu na changamoto za sekta ya kilimo na kuongeza kasi ya ukuaji wa pato la Taifa, kuboresha ukuaji wa pato la wakulima wadogo na kuwa na uhakika wa usalama wa chakula ifikapo 2025. 1 ASLMs inajumuisha wizara za Kilimo, Mifugo na Uvuvi, Viwanda Biashara na Uwekezaji, Maji na Umwagiliaji, Ardhi Nyumba na Maendeleo ya Makazi na Ofisi ya Rais-TAMISEMI 2 ASDP II 2 Mafanikio ya ASDP I ASDP I ilizinduliwa mwaka 2006 ili kuwa chombo cha kutekeleza Programu ya uwekezaji mpana katika sekta na kuchangia katika kupunguza umasikini vijijini kutoka asilimia 27 hadi 14 ifikapo 2010, na kuongeza ukuaji wa sekta ya kilimo hadi asilimia 10 kwa mwaka ifikapo mwaka 2010. i. Katika kipindi cha miaka saba ya utekelezaji wa ASDP I kuanzia 2006/2007 hadi 2013/14, kati ya mafanikio makuu ni kuboreka kwa uandaaji wa Mipango ya Maendeleo ya Kilimo ya Wilaya (DADPs) kwa kushirikisha jamii na kuongezeka kwa fedha za kutekeleza miradi ya sekta ya Kilimo ambapo asilimia 75 ilitumika ngazi ya wilaya, asilimia 20 ngazi ya Taifa na asilimia 5 katika ngazi ya mikoa. ii. Kuboreka kwa uwezo wa watendaji kwa kupatiwa mafunzo, usafiri na vitendea kazi katika ngazi ya wilaya, mikoa na Taifa, uwezo ambao umeweka mazingira yatakayosaidia katika utekelezaji wa shughuli za ASDP II na miradi mingine hasa katika Mamlaka za Serikali za Mitaa (LGAs), na kufikia malengo makuu ya sekta. Aidha wakulima na wafugaji walijengewa uwezo kwa kupatiwa mafunzo mbalimbali na teknolojia za uzalishaji, usindikaji, hifadhi ya mazao na masoko ili kuongeza tija na kipato. iii. Kuboreka kwa huduma za utafiti pamoja na kuongezeka kwa tafiti za mazao na mbegu bora za mifugo. iv. Kuongezeka kwa matumizi ya pembejeo. Pamoja na kwamba bado kuna changamoto baadhi ya mbegu bora zilizalishwa na kutumika. Programu pia iliongeza mbegu bora na mbolea, upatikanaji na matumizi ya zana bora za kilimo kama matrekta makubwa na madogo na zana za kukokotwa na wanyama kazi, na kuongeza eneo linalolimwa kwa asilimia 148. v. Kukarabati na kujenga skimu za umwagiliaji na kuongeza eneo 3 ASDP II la umwagiliaji kutoka hektari 264,338 (2005/2006 ) hadi hektari 461,326 (2014). vi. Kuendelezwa kwa miundombinu ya masoko na mfumo wa masoko wa kuongeza thamani ya mazao ambapo maghala yalikarabatiwa, masoko ya mazao ya kilimo na mifugo yalijengwa na kuendeleza mfumo wa masoko wa stakabadhi mazao ghalani. vii. Kuongezeka kwa uwezo wa kujitosheleza kwa chakula kutoka asilimia 103 (2009/2010) hadi asilimia 123 (2015/2016). viii. Mabadiliko ya bei ya vyakula: bei ya chakula haikubadilika na kusababisha kupungua kwa mfumuko wa bei kutoka asilimia 7.0 (2006) hadi asilimia 5.56 (2010), na asilimia 5.6 (2015); na mwezi Oktoba 2016 mfumuko wa bei ulishuka hadi asilimia 4.5. Aidha mauzo ya mazao ya biashara nje ya nchi (kahawa, pamba, katani, chai, tumbaku na korosho) yaliongezeka. 3 Changamoto za ASDP I Baadhi ya changamoto zilizojitokeza wakati wa utekelezaji wa ASDP I ni: i. Utawala/uongozi, usimamiaji na uratibu hafifu (ndani na kati) ya wizara, mikoa na wilaya, uliosababisha majukumu kutokuwa wazi/bayana; mfumo hafifu wa uwajibikaji na kushindwa kuratibu wadau wa sekta. Hivyo kusababisha kuwepo kwa miradi midogomidogo sehemu mbalimbali, fedha kusambazwa kidogokidogo na miradi kuwa ya aina moja kulikofanya matokeo kuwa madogo na kushindwa kupima mchango wa Programu. ii. Kukosekana kwa mazingira wezeshi; Programu ilitekelezwa kupitia sera na sheria zenye mapungufu na zinazoingiliana. 4 ASDP II iii. Kukosekana kwa mfumo imara wa ufuatiliaji na tathimini ya sekta na programu kulikosababisha kukosekana kwa takwimu sahihi na kwa wakati iv. Uwezo mdogo wa kitaalamu na kifedha ; hasa katika skimu za umwagiliaji na v. Uwezo mdogo wa kupanga, kusimamia na kutekeleza miradi ya uwekezaji na kusababisha kuchelewa kwa fedha za utekelezaji na kuwepo kwa bakaa kila mwaka. 4 Tulichojifunza kutoka ASDP I Mambo ya kujifunza kutokana na utekelezaji wa ASDP I na ambayo yamekuwa kama mwongozo wa kuandaa ASDP II ni: (i) inawezekana kutekeleza Programu kwa kuzingatia Mtazamo Mpana wa Kisekta (SWAPs) kukiwa na uongozi bora, uwajibikaji na ugatuaji wa madaraka ya upangaji na utekelezaji wa mipango ya maendeleo ya sekta ya kilimo; (ii) kujenga uwezo wa wakulima na kuimarisha vikundi pamoja na vyama vyao; (iii) kuwa na Programu inayolenga na kuweka vipaumbele kwenye maeneo yenye matokeo makubwa ambayo zaidi ya kuwa na tija pia itaimarisha mnyororo wa thamani wa zao la kipaumbele; (iv) kuwa na utawala bora, usimamiaji, uratibu, mfumo mmoja wa ufuatiliaji na tathimini ya programu; (v) kuimarisha mazingira wezeshi katika sekta; (vi) kuwekeza zaidi katika sekta ya kilimo (Serikali, Sekta Binafsi na Wabia wa Maendeleo). Hivyo ni muhimu kuandaa uratibu wa jinsi Serikali itakavyowezesha na kuimarisha ushiriki wa Sekta Binafsi, Wabia wa Maendeleo na Wadau wengine katika sekta ya kilimo. 5 Ajenda ya Mageuzi ya Sekta ya Kilimo katika ASDP II 5.1 ASDP II inalenga katika Mnyororo wa thamani wa zao la kipaumbele na ikolojia ya kanda ya kilimo. Tofauti na utekelezaji wa ASDP I ambao ulifanyika nchi nzima na kuwa na miradi karibu sekta ndogo zote za sekta kuu ya kilimo kutegemeana na vipaumbele na maamuzi ya uwekezaji wa Mamlaka za Serikali za 5 ASDP II Mitaa, ASDP II itatekelezwa katika wilaya zote katika kutoa huduma za umma tu (kama kujenga uwezo, huduma za ushauri, n.k) lakini katika uwekezaji, Programu italenga mazao ya kipaumbele (ya kilimo, mifugo, uvuvi) yenye uwezo mkubwa yaliyochaguliwa kwa kuzingatia mnyororo wa thamani na ikolojia ya kanda ya kilimo. 5.2 Uchaguzi wa mnyororo wa thamani wa zao la kipaumbele utazingatia vigezo vifuatavyo: · Mchango wa zao katika usalama wa chakula; · Zao linalolimwa na wakulima/wafugaji wadogo walio wengi; · Zao muhimu katika soko la ndani na nje ya nchi; · Mchango wa zao katika kuchangia malighafi na ajira katika kiwanda/viwanda nchini; · Mchango wake katika ajenda ya maendeleo ya Taifa ya viwanda na Mpango wa Maendeleo wa miaka mitano · Upatikanaji wa teknolojia za kuongeza tija na faida · Miradi inayoendelea kukamilishwa kwanza. 5.3 Mazao ya Kipaumbele: Katika awamu ya kwanza ya ASDP II, mazao ya kipaumbele yaliyochaguliwa kwa Kilimo ni Mchele, Mahindi, Mtama/Uwele, Muhogo, Mboga/Matunda, Mazao ya Mbegu za Mafuta (Alizeti, Ufuta, Nazi, Michikichi, n.k.), Pamba, Kahawa, Sukari, Korosho, Chai, Viazi mviringo na vitamu, Mikunde, Ndizi; na kwa Mifugo na Uvuvi ni Maziwa, Nyama (ng’ombe), Mbuzi na Kondoo, Kuku, Ngozi, Samaki na Mwani. Jedwali namba 1, linaonyesha mazao ya kipaumbele katika kanda. 5.4 Utekelezaji wa vipaumbele vya uwekezaji na mazao katika Kanda Utaratibu wa utekelezaji utakuwa “zao/bidhaa moja ya kipaumbele kwa kanda” (one - priority crop/product – one AEZ”). Mikoa itawekwa katika makundi (clusters) ili huduma na teknolojia zilizopendekezwa zielekezwe katika mfumo unaofanana wa uzalishaji na aina za vijijini. ASDP II itagharamia huduma za umma kwa wilaya zote na pia itagharamiwa na programu na miradi mingine inayotekelezwa na 6 ASDP II Mawakala, Wafadhili na Taasisi zisizo za kiserikali (NGOs). Mfumo wa ufuatiliaji wa wilaya ulioanzishwa na ASDP II wa kutumia DADPs utaboresha uratibu katika ngazi ya wilaya kwa shughuli/miradi yote ikiwa ni pamoja na ya Sekta Binafsi. 5.5 Vigezo vya Uchaguzi wa Kanda/Kundi Uchaguzi wa kanda na makundi (mikoa/wilaya) utazingatia vigezo 5 kwa kuanzia na kiwango cha uzalishaji cha kanda na umuhimu wake. Vingine ni: · Uzalishaji mkubwa wa mnyororo wa thamani uliochaguliwa kwa asilimia ya uzalishaji wa Taifa · Umuhimu katika uhitaji wa soko kama malighafi na kama zao linalosindikwa ndani ya mkoa na kanda · Kiwango cha usindikaji na uwezo wa usindikaji uliomo katika kanda · Mifumo endelevu au mchango wake katika mifumo endelevu ya uzalishaji, usalama wa chakula na uongezaji wa kipato katika kaya na · Uwezo wa kukua kwa kuongezeka kwa tija na thamani ya zao, pamoja na kuendeleza biashara ya kilimo vijijini na kuongezeka kwa mauzo ya bidhaa za kilimo nje ya nchi. 5.6 Uimarishaji wa uwezo wa taasisi: ASDP II inalenga katika: (a) kujenga uwezo na kuimarisha vyama vya wakulima wadogo ili kuwawezesha kulima kibiashara; (b) kusaidia kuwaunganisha wafanya biashara wa sekta ya kilimo na mfumo wa uzalishaji wa wakulima /wafugaji na wavuvi kwa ajili ya soko na kuendeleza mnyororo wa thamani; (c) kuimarisha huduma zinazotolewa na serikali na sekta binafsi ili kuendeleza matumizi ya teknolojia bora na kilimo cha kibiashara; (d) kuendeleza masoko (sera na miundombinu ya masoko na ya uzalishaji; na (e) kuzijengea uwezo taasisi katika ngazi zote, za Serikali na Sekta Binafsi. 7 ASDP II 6 Misingi Mikuu ya Utekelezaji wa ASDP II Misingi mikuu ya utekelezaji wa ASDP II ni kama ilivyoainishwa hapa chini: a. Viongozi wanaowajibika na kubadili mtazamo katika ngazi zote wataendeleza malengo ya Programu. b. Uratibu mpana wa Sekta (kupanga, kutekeleza, ufuatiliaji na tathimini kwa mtazamo mpana wa kisekta) ikiwa ni pamoja na programu na miradi ya umma katika sekta ya kilimo: (i) Katika ngazi ya taifa, uratibu kati ya wizara za sekta na kati ya mfumo wa serikali na programu na miradi mingine; na (ii) Katika ngazi ya wilaya katika mfumo wa ushirikishaji wa wadau katika kupanga na kutekeleza, kujengea uwezo na uwekezaji. c. Uwekezaji katika ngazi ya wilaya kwa kuzingatia mnyororo wa thamani wa zao la kipaumbele kwa uwiano kati ya kilimo, mifugo na uvuvi unaoendana na zao kuwa na faida zaidi ya lingine katika kila ikolojia ya kanda ya kilimo na kwa kulenga makundi ya wilaya zilizochaguliwa, na wilaya zingine kutoka na kuingia kwa utaratibu wa kuzingatia vigezo vilivyowekwa. d. Maeneo makuu ya uwekezaji ambayo ni kipaumbele katika kuendeleza sekta na kunufaika kwa kuongezeka bajeti ni : (i) umwagiliaji; (ii) utafiti na huduma za ugani (iii) upatikanaji wa teknolojia bora kwa wakulima, pembejeo (mbegu/ wanyama bora/ vifaranga vya samaki, mbolea, vyakula vya mifugo, madawa ya mifugo na chanjo, n.k.); (iv) upatikanaji wa huduma za machine/ vifaa vya kuzalishia, kusindika kuongeza thamani; (v) kupunguza upotevu baada ya kuvuna mazao na mifugo (vifo vya ndama); (vi) kutoa huduma maalum kwa sekta binafsi kuendeleza kilimo cha kibiashara katika ngazi ya mikoa/kanda na (vii) uwezo wa kutambua wadudu waharibifu na vimelea vya magonjwa na kupata chanjo bora. e. Kutumia teknolojia za kisasa za habari na mawasiliano kwa ufanisi wa uratibu, ukusanyaji wa takwimu, kuzichambua na kuzisambaza lakini pia upatikanaji wa taarifa (za kitaalamu, masoko, ufuatiliaji na tathimini) kwa matumizi ya wadau. f. Kujenga uwezo wa wakulima na kuimarisha vikundi/vyama vyao, kuwashirikisha na wamiliki maendeleo ya vijijini mwao, kuelekea 8 ASDP II katika kuboresha maisha yao ikiwa ni pamoja na uchumi wa vyama (mfano katika maeneo yanayozunguka maghala vijijini), ushirika, kuimarika kwa taarifa za ndani na huduma za kitaalamu kwa wanachama; g. Kuendeleza mfumo endelevu wa uzalishaji na matumizi ya maliasili kwa kuhamasisha kilimo cha kuhifadhi mazingira, utunzaji wa udongo, maji na rutuba kwa pamoja (mfumo wa afya ya udongo), kuzuia wadudu kwa kutumia njia mbalimbali, utunzaji bora wa mifugo, idadi ya mifugo inayoendana na uwezo wa eneo, n.k. h. Kutumia tathimni ya pamoja ya matokeo katika ngazi ya sekta kwa kutumia huduma za Taifa za takwimu za kilimo kutoka katika Taasisi ya Takwimu ya Taifa kufanikisha utekelezaji wa ukusanyaji wa takwimu za kilimo na mifugo kitaifa (National Agriculture and Livestock Sample Census –NASC) unaofanyika kila baada ya miaka kumi) na Ukusanyaji wa takwimu za kilimo kwa kila mwaka (Annual Agricultural Sample Survey -AASS) na kuhakikisha kunakuwepo na uchambuzi thabiti wa taarifa na kwa wakati. i. Uiimarishaji wa uwezeshaji wa kuboresha sera na kanuni ili kuwezesha kuzihuisha na kuongeza ushirikishaji wa wadau ikiwa ni pamoja na sekta binafsi na kuendelea kusaidia kuimarisha ugatuaji wa madaraka mikoani na kujengea uwezo ngazi ya wilaya, waweze kumiliki utangazaji wa sera hizo ili zieleweke na kukubalika na wadau. j. Utaratibu wa ugharamiaji na usimamiaji wa fedha unaoweza kubadilika na kuhuishwa ili kuunganisha fedha zilizo ndani ya bajeti (on budget) na fedha zilizo nje ya bajeti (off-budget). Fedha zilizo ndani ya bajeti ni bajeti ya serikali kuu, Mfuko maalum wa fedha (Basket Fund) ambao serikali inausisitizia zaidi, programu na miradi inayotekelezwa kipekee (earmarked and ring-fenced) lakini fedha zake zimeingizwa katika bajeti kuu.Fedha zilizo nje ya bajeti ni za programu na miradi ambayo inatekelezwa katika sekta ya kilimo lakini fedha zake hazijumuishwi kwenye bajeti ya Serikali. Mambo makuu ya programu kama uratibu (uandaaji wa mipango, utekelezaji, ufuatiliaji na tathimini), uimarishaji wa uwezo katika ngazi ya taifa na wilaya utahitaji kugharamiwa na mfuko maalum wa fedha utakaochangiwa na Serikali na Wabia wa Maendeleo wenye 9 ASDP II programu/ miradi isiyo ndani ya bajeti) na /au michango ya hiari (mfano, 5%) kutoka kwa kila programu na miradi ya sekta (ndani na nje ya bajeti). k. Utawala, uwajibikaji, na muundo wa utawala, mifumo, michakato na taratibu zinazofanya kazi. Ni muhimu kuweka wazi wajibu na majukumu, na mamlaka katika ngazi zote kwa mifumo ya uwajibikaji unaolenga kutoa huduma bora. 7 Malengo, Mkakati na Matokeo ya ASDP II LENGO: Kuleta mageuzi ya Sekta ya kilimo (kilimo, mifugo na uvuvi) ili kuongeza uzalishaji na tija , kufanya kilimo kiwe cha kibiashara zaidi na kuongeza pato la wakulima wadogo kwa ajili kuboresha maisha yao, usalama wa chakula na lishe. MKAKATI: Kufanya mageuzi kwa wakulima wadogo kutoka katika kilimo cha kujikimu kwenda kilimo cha kibiashara kwa kuendeleza na kuamsha vichocheo vya ukuaji wa sekta na kuwezesha wakulima wadogo kuongeza tija ya mazao ya kipaumbele (kilimo, mifugo, uvuvi) katika mfumo wa uzalishaji endelevu na kuunganishwa na masoko endelevu kwa ushindani wa kibiashara na uendelezaji wa mnyororo wa thamani wa zao. MATOKEO: Kuongezeka kwa uzalishaji na tija, kuwepo kwa masoko,kuongezeka kwa thamani ya mazao, uhakika wa usalama wa chakula na lishe na kuongezeka kwa kipato cha Mkulima na pato la Taifa 8 Maeneo Makuu ya Utekelezaji na Vipaumbele vya Uwekezaji katika ASDP II 8.1 Programu ina maeneo makuu manne ambayo chini yake yameandaliwa maeneo ya kipaumbele ya uwekezaji 23. Mchoro namba 1 unaonyesha maeneo makuu ya programu pamoja na vipaumbele vya uwekezaji kwa kila eneo kuu. 10 ASDP II Mchoro 1: Malengo, Maeneo Makuu 4 na Maeneo ya Uwekezaji ya ASDP II ! " LENGO LA ASDP II Kuleta mageuzi ya Sekta ya kilimo (kilimo,mifugo na uvuvi) ili kuongeza uzalishaji na tija , kufanya kilimo kiwe cha kibiashara zaidi na kuongeza pato la wakulima wadogo kwa ajili ya kuboresha maisha yao, uhakika wa usalama wa chakula na lishe. 1. Mpango maalum wa matumizi ya ardhi na usimamizi wa mwachano wa maji 2. Kuendeleza miundombinu ya umwagiliaji 3. Kuendesha na Kusimamia skimu za umwagiliaji 4. Kuwezesha uendelezaji wa vyanzo vya maji kwa ajili ya mifugo na samaki 5. Kuendeleza teknolojia za kilimo zenye kuhifadhi mazingira na mabadiliko ya tabianchi ! Lengo: Kuongezeka wa uzalishaji na tija katika sekta ya kilimo kwa kulenga biashara na masoko kwa mazao ya kipaumbele ! 1. Kuendeleza upatikanaji wa masoko na mifumo ya masoko kwa ajili ya mazao yote ya kipaumbele. 2. Kuendeleza upatikanaji wa masoko na mifumo ya masoko kwa ajili ya mifugo, uvuvi na bidhaa zake 3. Kuendeleza usindikaji na kuongeza thamani ya mazao ya kilimo, mifugo na uvuvi 1. Kupitia na kuboresha sera, miongozo na pia kuboresha mazingira ya biashara za kilimo, mifugo na uvuvi. 2. Kuimarisha miundo na uwezo wa kitaalam wa vikundi vya wakulima na /au vyama vya wazalishaji, wafanyabiashara, na wasindikaji wadogo 3. Kuanzisha na kuendeleza ushiriki wa makundi/jinsia tofauti kwenye sekta ya kilimo 4. Kuimarisha uratibu wa sekta katika ngazi zote za utekelezaji 5. Kuwezesha upatikanaji na kuimarisha mifumo ya ukusanyaji wa takwimu katika sekta ya kilimo Eneo la Nne: Kuiwezesha sekta katika Uratibu, Ufuatiliaji na Tathimini Eneo la Kwanza: Usimamizi endelevu wa matumizi ya maji na ardhi Eneo la Pili: Kuongeza tija na faida katika kilimo, mifugo na uvuvi Eneo la Tatu: Biashara na kuongeza thamani ya mazao. Lengo : Usimamizi endelevu wa matumizi ya maji na ardhi kwa kilimo, mifugo na uvuvi 1. Kuimarisha huduma za ugani na mafunzo na kuendeleza upatikanaji wa taarifa za kilimo, mifugo na uvuvi 2. Kuwezesha upatikanaji na usambazaji wa mbegu bora na pembejeo za kilimo, mifugo, uvuvi na huduma za afya. 3. Kuendeleza na kuimarisha shughuli za utafiti 4. Kuimarisha na kuendeleza matumizi ya zana bora (mashine na mitambo) 5. Kuimarisha usalama wa chakula na lishe Lengo: Kuboreka na kuongezeka kwa masoko, na kuongeza thamani ya mazao kwa kuhamasisha ushindani wa Sekta Binafsi na vyama/vikundi vya wakulima vyenye ufanisi LENGO: Kuimarika kwa taasisi na muundo wa kuratibu Maeneo ya Kipaumbele ya Uwekezaji 6. Kuimarisha uwezo na mifumo ya uongozi katika sekta ya kilimo 7. Kuandaa na kuimarisha mifumo ya ufuatiliaji na tathmini 8. Kuwezesha na kuimarisha uwezo wa utendaji wa shughuli za kilimo kwa watendaji wa sekta ya kilimo katika ngazi zote 9. Kuimarisha mifumo ya kiteknolojia ya habari na mawasiliano katika sekta ya kilimo (TEHAMA) 10. Kutoa na kuwezesha huduma za kifedha (kuendeleza shughuli za kilimo Maeneo ya Kipaumbele ya Uwekezaji 8.2 Utekelezaji wa miradi ya programu umejikita katika kuendeleza mnyororo wa thamani wa mazao ya kipaumbele yaliyochaguliwa kwa kuzingatia ikolojia ya kilimo ya kanda (makundi). Kwa utaratibu huu Wilaya zitatekeleza mnyororo wa thamani wa zao kuu la kipaumbele katika kanda kama inavyoonekana katika Jedwali 1 hapo chini. 11 ASDP II Jedwali 1:Mazao ya Kipaumbele katika ikolojia ya kanda ya kilimo/makundi Kanda Mikoa Walengwa- kaya Mazao ya Kipaumbele Mazao Mifugo na Samaki Zao la Biashara Kati 715,000 (8%) Mahindi Tumbaku Nyama: N’gombe Nyama: Mbuzi Mazao ya mafuta Mtama na Ulezi Kuku Mboga na matunda Pwani 2,300,000 (25%) Mchele Maziwa Korosho Mahindi Nyama: Mbuzi Sukari Muhogo Samaki mazao ya mafuta Maharage Mwani Mboga na Matunda Ziwa 2,100,000 Mchele Nyama: Ng’ombe Nyama: Mbuzi Pamba Kahawa ( 23%) Mahindi Samaki Sukari Muhogo Mboga/Matunda na Ndizi 12 ASDP II Kanda Mikoa Walengwa - kaya Mazao ya Kipaumbele Mazao Mifugo na Samaki Zao la Biashara Nyanda za Juu Kaskazini 1,035,000 (11%) Mahindi Maziwa Kahawa Mikunde: maharage Nyama: Ng’ombe Mboga na Matunda Ndizi Kusini 570,000 (6%) Mihogo Nyama: Mbuzi Korosho Mazao ya mafuta Kuku Mahindi Samaki Nyanda za Juu Kusini 2,395,000 (26%) Mahindi Nyama: Ng’ombe Chai/Kahawa Viazi mviringo na vitamu Mboga na Matunda Mchele Sukari Kuku Maziwa Samaki 9 Utekelezaji wa ASDP II kwa Kufuata Mpangilio wa Maeneo Makuu 4 ya Programu 9.1 Programu ina maeneo makuu manne na miradi mingi itakayotekelezwa kwa miaka mitano. Njia pekee ya kufikia malengo au kufanikiwa ni kuweka vipaumbele, makundi, mpangilio na utaratibu unaofaa kutekeleza miradi na shughuli za Programu. Aidha maeneo makuu na miradi ya ASDP II itatekelezwa kwa mfuatano na mpangilio utakaoleta mabadiliko na matokeo makubwa. Mchakato wa mpango wa utekelezaji, mfuatano na mpangilio umelenga umuhimu wa maeneo makuu na miradi ambayo itatatua changamoto za sekta kwa haraka kwa kutumia fursa zilizopo na kuleta mabadiliko chanya. 13 ASDP II 9.2 Pia kuna haja ya kutekeleza miradi ambayo inaweka mazingira wezeshi kwa kuondoa vizuizi “kuzibua bomba ili maji yapite” (“Unclog the pipe and let the water flow”). Kwa hiyo utekelezaji utaanza na eneo kuu la 4 ambalo linaweka mazingira yatakayowezesha sekta binafsi na ya umma kufanikisha shughuli za sekta ya kilimo ikiwa ni pamoja na wakulima wadogo. Litafuatia Eneo kuu la Tatu (Biashara na kuongeza thamani ya mazao) litaunda mfumo wa masoko (markets pull effect) ambao utavutia kuongeza uzalishaji, tija na faida ya mazao ya sekta ya kilimo katika Eneo kuu la Pili. Utekelezaji wa eneo la Pili utasababisha matumizi endelevu ya maji na ardhi katika Eneo kuu la Kwanza. 9.3 Mpangilio wa utekelezaji uliopendekezwa ni kutoa mwongozo wa utekelezaji wa programu kutegemeana na upatikanaji wa rasilimali na malengo makuu ya programu. Kiukweli, miradi yote, inatakiwa ianze wakati mmoja kama fedha inayotakiwa inapatikana. Kama sivyo, eneo la kiwango cha juu cha kipaumbele, maeneo ya uwekezaji na miradi itekelezwe kwanza, halafu miradi yenye vipaumbele vya chini itekelezwe baadae kutegemeana na fedha itakayoongezeka. 10 Taasisi na Muundo wa Uratibu wa ASDP II 10.1 Uratibu wa programu utazingatia mifumo na miundo ya Serikali iliyopo ili kuendeleza juhudi za kuimarisha mifumo ya Serikali katika ngazi ya Taifa, Mkoa na Wilaya. 10.2 Katika ASDP II, utekelezaji utahitaji uwazi katika uongozi/utawala, muundo wa taasisi na mfumo wa kuratibu kuanzia ngazi ya Taifa hadi ya Mamlaka za Serikali za Mitaa. Hii inajumuisha uongozi wa Serikali katika kuratibu, wajibu na majukumu, na mamlaka na uwajibikaji wa watekelezaji unaolenga katika kufikia malengo ya programu/miradi, matokeo, na viashiria vya kupima matokeo ya programu; kuandaa na kusambaza miongozo sahihi ya programu/miradi, utaratibu, na kuweka kumbukumbu kwa ajili ya watekelezaji; kuwezesha usimamiaji sahihi wa fedha na mfumo wa ukaguzi wa programu na miradi; na hatimaye vyote vitawajibika kwa Waziri Mkuu. 10.3 Kitengo cha Taifa cha Kuratibu na Kusimamia Utekelezaji wa ASDP II (NCU) itahakikisha uandaaji wa mpango na utekelezaji wa miradi ya ASDP II unafanyika kwa kushirikiana na wadau mbalimbali 14 ASDP II muhimu. 10.4 Muundo wa uratibu wa ASDP II katika ngazi ya Taifa utakuwa na Mkutano wa Taifa wa Wadau wa Sekta (NASSM), Kamati ya Kusimamia Sekta ya Kilimo (ASC), Washauri katika Sekta ya Kilimo (ASCG), Kamati ya Ufundi ya Wakurugenzi (TCD), Kikundi Kazi (TWGs) na Kitengo cha Taifa cha Kuratibu na kusimamia utekelezaji wa ASDP II (NCU). Jedwali 2 linaonyesha Taasisi na muundo wa uratibu wa sekta katika ASDP II. Jedwali 2: Taasisi na Muundo wa Uratibu, Wajumbe na Majukumu Ngazi ya Taifa katika ASDP II Taasisi/ utaratibu Mwenyekiti Wajumbe Majukumu i) Mkutano wa Taifa wa Wadau wa Sekta ya Kilimo (National Agricultural Sector Stakeholders Meeting (NASSM). Waziri Mkuu Mawaziri wa Wizara za Sekta ya Kilimo (ASLMs), na Wizara zingine, Makatibu Wakuu, Wakurugenzi wa Sera na Mipango kutoka ASLMs, na Maafisa wakuu wa Serikali, Viongozi wa Maeneo makuu ya ASDP II; Sekretariati za Mikoa (RSs); Wakurugezi Watendaji wa Wilaya (DEDs); Wakuu wa Idara ya Kilimo Umwagiliaji na Ushirika wa Wilaya (DAICOs), Wakuu wa Idara ya Mifugo Uvuvi wa Wilaya (DLFOs); Maafisa wa utafiti na Maafisa wa mafunzo; Wawakilishi wa vyuo; Bodi za mazao; Wabia wa Maendeleo, wanafadhili wa kilimo, Sekta Binafsi n.k. 15 ASDP II Taasisi/ utaratibu Mwenyekiti Wajumbe Majukumu Ajenda ya mkutano huu wa mwaka ni miongozo ya sera katika ajenda ya kuleta mageuzi ya sekta ya kilimo, kutoa ushauri na miongozo ya utekelezaji wa ASDP II n.k. ii) Kamati ya Kusimamia sekta ya Kilimo (Agricultural Steering Committee -ASC) Waziri- Wizara ya Kilimo Makatibu Wakuu wa maeneo makuu (Lead Components) ya ASDP II na wizara zingine (ASLMs na zingine); Wawakilishi wa Wabia wa Maendeleo, Sekta Binafsi, Taasisi zisizo za kiserikali (NGOs/NSAs) n.k. Kupitia na kuthibitisha taarifa za mipango, bajeti, ufuatiliaji na tathimini na ripoti za fedha na ukaguzi; Kuidhinisha Hadidu za rejea za mapitio ya pamoja ya sekta ya mwaka, Matumizi ya Umma, ufuatiliaji na tathimini (JSR/ ASR/PER na M&E). 16 ASDP II Taasisi/ utaratibu Mwenyekiti Wajumbe Majukumu iii) Mkutano wa Kikundi cha Ushauri katika Sekta ya Kilimo (Agricultural Sector Consultative Group (ASCG) Meeting) Katibu Mkuu (KM) - Wizara ya Kilimo Makatibu Wakuu wa maeneo makuu ya ASDP II (ASLMs na wizara zingine); Wabia wa Maendeleo wote, Sekta Binafsi, Asasi zisizo za kiserikali (NGOs/NSAs), za Vyuo vya mafunzo na Taasisi za Utafiti n.k. Kutoa ushauri wa sera, mipango, bajeti, mapitio ya matumizi ya umma na sekta ya kilimo; Kuratibu mazungumzo na wadau kuhusu sera mara kwa mara; Kutoa misaada (fedha, vifaa na mingine) kwa sekta; Kushiriki katika mikutano ya mwaka ya pamoja ya kuandaa mipango na bajeti; Mazungumzo na kupata maoni ya Wabia wa Maendeleo, sekta binafsi na asasi zisizo za kiserikali (NGOs/NSAs). 17 ASDP II Taasisi/ utaratibu Mwenyekiti Wajumbe Majukumu iv) Kamati ya Wakurugenzi (Technical Committee of Directors -TCD) KM - Wizara ya Kilimo Wakurugenzi wa Wizara za Sekta, viongozi wa maeneo makuu ya ASDP na Uratibu wa ASDP II- OR-TAMISEMI Kupitia, kuchunguza na kuunganisha taarifa za mipango, bajeti, ufuatiliaji na tathimini za kila msimamizi wa maeneo ya ASDP II; Kupendekeza miongozo na taratibu za kutekeleza ASDP II; Kupendekeza hadidu za rejea za mapitio ya pamoja ya sekta ya mwaka, Matumizi ya Umma, ufuatiliaji na tathimini (JSR/ ASR/PER, n.k v) Mkutano wa kitaalamu wa msimamizi wa maeneo makuu (Lead Agency Component Technical Meeting) Mkurugenzi wa Sera na Mipango (DPP of Lead Component) Wenyeviti wa Vikundi kazi vya Wataalamu (TWGs) na mwakilishi kutoka Kitengo cha Taifa cha kuratibu na Kusimamia ASDP II (NCU) Kupitia mipango na bajeti, zilizowasilishwa kutoka maeneo makuu husika; kupitia na kuchambua taarifa; na kuziwasilisha kwa ASDP II - NCU 18 ASDP II Taasisi/ utaratibu Mwenyekiti Wajumbe Majukumu vi) Vikundi kazi vya Kitaalamu (Thematic Working Groups- TWGs) Kiongozi wa Maeneo makuu (Componen/ sub- component Leaders) Viongozi wa maeneo makuu ya ASDP II, wataalamu waliochaguliwa kutoka Wizara za Sekta ya Kilimo (ASLMs) Kuandaa na kupitia mipango na bajeti za Maeneo makuu ya ASDP II na kuwasilisha kwenye mkutano wa Msimamizi wa kuratibu maeneo ya ASDP II. vii) Kitengo cha Taifa cha Kuratibu ASDP II (NCU) Mratibu wa Programu wa Taifa Wataalamu (experts) katika Uzalishaji na biashara; Masoko na Mnyororo wa thamani (kwa kilimo, mifugo na uvuvi); Ufuatiliaji na Tathimini; Mchambuzi wa sera za sekta ya kilimo Kutoa kichocheo na kuwajibika katika ajenda ya mageuzi ya kilimo. Kuunganisha mipango na bajeti za miradi chini ya ASDP II na kuandaa rasimu ya mpango kazi na bajeti ya m waka; Kuratibu uandaaji wa mipango na bajeti kwa pamoja; Kusimamia, kufuatilia, kutathimini, kuhuisha na kuratibu utekelezaji wa ASDP II na ni Sekretarieti wa ASDP II 19 ASDP II 10.5 Uratibu katika OR-TAMISEMI utaanza na Mkutano wa ushauri wa mwaka wa Mkoa na Serikali za mitaa (Annual Regional and Local Government Consultative Meeting) mwenyekiti akiwa ni Waziri-OR- TAMISEMI. Ukifuatiwa na: (i) Mkutano wa Ushauri wa Sekta ya kilimo (Agricultural Sector Consultative Meeting) (ii) Kamati ya Kitaalamu ya viongozi wa maeneo ya makuu ya ASDP II (Technical Committee of Component Leaders-PO-RALG) na (iii) Kamati ya Ushauri ya Mkoa (Regional Consultative Committee -RCC). Jedwali 3 linaonyesha Taasisi ya Utawala na Muundo wa Uratibu, Wajumbe na Majukumu ya OR-TAMISEMI katika ASDP II. 10.6 Uratibu katika ngazi ya wilaya, ASDP II itaimarisha miundo na shughuli za ngazi ya wilaya kama ilivyokuwa wakati wa utekelezaji wa ASDP I. Mpango wa Maendeleo wa Wilaya (District Agricultural Development Plan -DADP) utaendelea kuwa chombo muhimu kwa maendeleo ya sekta ya kilimo katika ngazi ya wilaya. Mkurugenzi Mtendaji wa Wilaya atawajibika kwa kazi na fedha zitakazotumika katika ngazi ya wilaya. Timu ya Usimamizi ya Baraza (CMT), ambayo Mkurugenzi ni Mwenyekiti inahudhuriwa na Wakuu wa Idara wote wakiwemo Afisa Kilimo Umwagiliaji na Ushirika wa Wilaya (DAICO) na Afisa Mifugo na Uvuvi wa Wilaya (DLFO), na atapewa taarifa za shughuli za maendeleo za sekta ya kilimo na hali ilivyo ndani ya DADP. Jedwali 3 linaonyesha Taasisi ya Utawala na Muundo wa Uratibu, Wajumbe na Majukumu Ngazi ya OR-TAMISEMI katika ASDP II. 20 ASDP II Jedwali 3: Taasisi ya Utawala na Muundo wa Uratibu wa ASDP II, katika Ngazi ya OR-TAMISEMI Taasisi Mwenyekiti Wajumbe Mkutano wa mwaka wa kushauriana wa Mkoa na Serikali za mitaa (Annual Regional and Local Government Consultative Meeting ) Waziri-OR- TAMISEMI Makatibu Wakuu na Wakurugenzi (DPPs) wa Wizara za sekta ya kilimo ( ASLMs), Wabia wa Maendeleo RS & LGAs,Sekta Binafsi, Taasisi zisizo za kiserikali (NGOs/CBOs; FBOs), Wakurugenzi Watendaji wa Wilaya (DED), Wataalamu wa Kata, Wilaya na Mikoa , n.k. Mkutano wa Ushauri wa Sekta ya kilimo (Agricultural Sector Consultative Meeting) Katibu Mkuu-OR- TAMISEMI Wakurugenzi (DPPs) wa ASLMs Kamati ya Kitaalamu ya viongozi wa maeneo ya ASDP II Technical Committee of Component Leaders-PO- RALG) Mkurugenzi wa Uratibu wa Sekta OR- TAMISEMI Viongozi wa maeneo ASDP II wa OR- TAMISEMI na Wakurugenzi wengine Kamati ya Ushauri ya Mkoa (Regional Consultative Committee -RCC) Mkuu wa Mkoa Afisa Msaidizi wa Afisa Tawala wa Mkoa (RAS),Wakuu wa vitengo 21 ASDP II Kamati ya ushauri ya Wilaya (District Consultative Committee) Mkuu wa Wilaya Mkurugenzi wa wilaya , Wakuu wa idara Baraza la Madiwani (Full Council) Mwenyekiti wa Baraza la Madiwani Wajumbe wa baraza, Timu ya Usimamizi ya Baraza (CMT), Mkurugenzi Baraza la Maendeleo la Kata (Ward Development Council) Diwani Wajumbe wa Baraza Mkutano wa Kijiji wa baraza (Village Council Meeting) Mwenyekiti wa Kijiji Wajumbe wa mkutano wa baraza Mkutano mkuu wa Kijiji (Village Assembly) Mwenyekiti wa Kijiji Wanakijiji wote wenye umri kuanzia miaka 18 na mwenye akili timamu 11 Ufuatiliaji naTathimini ya ASDP II 11.1 Ufuatiliaji na Tathimini ya programu na miradi ya ASDP II utafanyika kulingana na mfumo wa Serikali ambapo kutakuwa na ufuatiliaji na tathmini ya NDANI na NJE ya programu/mradi na taasisi husika. Kila ngazi ya utawala itaisimamia na kufuatilia ngazi nyingine ya chini ili kuhakikisha na kujiridhisha na utendaji wa kila ngazi, mfano Afisa Mtendaji wa Kata atasimamia, kufuatilia na kutathmini kazi za Afisa Mtendaji wa Kijiji. Mfumo wa ufuatiliaji na tathmini umeandaliwa katika ngazi zote za uratibu kutoka Taifa, OR-TAMISEMI, Mikoa, Wilaya, Kata na Vijiji. 11.2 Kitengo cha Taifa cha Kuratibu na Kusimamia Utekelezaji wa ASDP II (NCU) kitaratibu mapitio na tathmini ya kila mwaka. Katika ngazi ya Taifa na Wilaya kutakuwa na Kikundi kazi cha Ufuatiliaji na Tathimini (M&E-TWG) kitapata matokoeo yanayohitajika kwa kutumia 22 ASDP II viashiria vya programu na miradi vilivyopo kwenye mfumo wa kupima matokeo (Result Frame work). 12 Gharama na Ugharamiaji wa Programu 12.1 Jumla ya makadirio ya kugharamia ASDP II ni Shilingi za Kitanzania Trilioni 13.819 (sawa na dola za Kimarekani bilioni 5.979) kwa muda wa miaka 5. Asilimia 75 ya fedha hizo zitatekeleza miradi iliyo ngazi ya wilaya na asilimia 25 zitatekeleza miradi na uratibu ngazi ya Mkoa na Taifa. 12.2 Mchanganuo wa makadirio ya bajeti kwa kila eneo kuu la ASDP II umeoneshwa kwenye Jedwali 4 hapo chini. Jedwali 4: Mchanganuo wa Bajeti ya ASDP II kwa Kila Eneo Kuu la Programu kwa Miaka Mitano ya Kwanza Eneo Kuu la Programu Bajeti (TSH) Bajeti (USD) % Eneo Kuu la 1 Usimamizi endelevu wa matumizi ya maji na ardhi 2,024,646,012,085 875,988,893 15 Eneo Kuu la 2 Kuongeza tija na faida katika kilimo, mifugo na uvuvi 8,081,495,303,009 3,496,561,907 58 Eneo Kuu la 3 Biashara na kuongeza thamani ya mazao 3,575,493,642,854 1,546,982,879 26 23 ASDP II Eneo Kuu la Programu Bajeti (TSH) Bajeti (USD) % Eneo Kuu la 4 Kuiwezesha sekta katika uratibu, Ufuatiliaji na Tathimini 137,442,668,522 59,466,322 1 Jumla Kuu 13,819,077,626,470 5,979,000,000 12.3 Programu ya ASDP II itagharamiwa na wadau mbalimbali ambao ni pamoja na Serikali, Wabia wa Maendeleo, Taasisi/Asasi zisizo za kiserikali, Sekta binafsi, Taasisi za Fedha na Wakulima, Wafugaji na Wavuvi. Kitengo cha taifa cha uratibu itakuwa na jukumu la kuratibu wadau wote hawa wakati wote wa utekelezaji wa ASDP II. 12.4 Utaratibu wa uchangiaji wa fedha, ni kwamba kutakuwa na mfuko wa pamoja wa ASDP II ambapo fedha kwa ajili ya utekelezaji wa miradi ya ASDP zitawekwa. Hata hivyo miradi inayogharamiwa nje ya mfuko wa pamoja itafikiriwa, kuratibiwa na kusimamiwa. KITENGO CHA URATIBU WA ASDP II | false |
# Extracted Content The United Republic of Tanzania National Sample Census of Agriculture 2007/08 LARGE SCALE FARMS Volume IV Ministry of Agriculture, Food Security and Cooperatives, Ministry of Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, Prime Minister's Office, Regional Administration and Local Governments, Ministry of Industries, Trade and Marketing, The National Bureau of Statistics and the Office of the Chief Government Statistician, Zanzibar JUNE, 2012 The United Republic of Tanzania National Sample Census of Agriculture 2007/08 LARGE SCALE FARMS Volume IV Ministry of Agriculture, Food Security and Cooperatives, Ministry of Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, Prime Minister's Office, Regional Administration and Local Governments, Ministry of Industries, Trade and Marketing, The National Bureau of Statistics and the Office of the Chief Government Statistician, Zanzibar JUNE, 2012 PREFACE Tanzania Agriculture Sample Census - 2007/08 i PREFACE At the end of the 2007/08 Agricultural Year, the National Bureau of Statistics (NBS) in collaboration with the Ministries of Agriculture Food Security and Cooperatives, Livestock and Fisheries Development; Water; Industry and Trade; the Prime Minister’s Office, Regional Administration and Local Government (PMO-RALG) and the Office of the Chief Government Statistician, (OCGS), Ministries of Agriculture and Natural Resources; Livestock and Fisheries conducted the Agricultural Sample Census. This is the fourth Agricultural Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95), and the third was conducted in 2002/03. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, and poverty indicators. In addition to this, the census was large in its scope and coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 2002/03 National Sample Census of Agriculture. The census covered smallholders in rural areas only and large scale farms. This report presents data disaggregated at regional level and it focuses on livestock kept by small holders and Large Scale Farms. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of the agricultural sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by agricultural households in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the Department for International Development (DFID) and the Japanese Government through the Japan International Cooperation Agency (JICA) and others who contributed through the pooled fund mechanism. My appreciation also goes to all those who in one-way or the other have contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics, Ministry of Agriculture, Food Security and Cooperatives, Ministry of PREFACE Tanzania Agriculture Sample Census - 2007/08 ii Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, the Prime Minister's Office, Regional Administration and Local Government, Ministry of Industries, Trade and Marketing and the Office of the Chief Government Statistician, Zanzibar, the Food and Agriculture Organization of the United Nations and the Censuses and Surveys Technical Working Group (CSTWG). Finally, I would like to extend my sincere gratitude to all the professionals, the consultants, Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been successful. Dr. Albina Chuwa Director General National Bureau of Statistics CONTENTS Tanzania Agriculture Sample Census - 2007/08 iii TABLE OF CONTENTS PREFACE ........................................................................................................................................ i ILLUSTRATIONS .......................................................................................................................... vii LIST OF TABLES ........................................................................................................................... vii LIST OF CHARTS ......................................................................................................................... viii EXECUTIVE SUMMARY ............................................................................................................ xiii 1. INTRODUCTION ....................................................................................................... 1 1.1 Introduction .................................................................................................................... 1 1.2 Background Information ................................................................................................ 1 1.2.1 Census Objectives ....................................................................................................... 2 1.2.2 Census Coverage ........................................................................................................ 3 1.2.3 Census Scope .............................................................................................................. 3 1.3 Census Methodology .................................................................................................... 4 1.3.1 Census Organization ................................................................................................... 5 1.3.2 Tabulation Plan Preparation ....................................................................................... 5 1.3.3 Questionnaire Design and Other Instruments ............................................................. 5 1.3.4 Field Pre-Testing of the Census Instruments .............................................................. 6 1.3.5 Training of Trainers, Supervisors and Enumerators ................................................... 6 1.3.6 Information, Education and Communication (IEC) Campaign ................................. 7 1.3.7 Data Collection ........................................................................................................... 7 1.3.8 Field Supervision and Consistency Checks ................................................................ 8 1.3.9 Data Processing .......................................................................................................... 8 1.4 Funding Arrangements ................................................................................................ 10 2 CROP RESULTS ....................................................................................................... 11 2.1 Number of large scale farms ........................................................................................ 11 2.1.1 Total number of farms and trends ............................................................................. 11 2.1.2 Number by type of farms .......................................................................................... 13 2.2 Land Area under Large Scale Farms ........................................................................... 15 2.2.1 Area under Holdings ................................................................................................. 15 2.3 Land use ....................................................................................................................... 17 CONTENTS Tanzania Agriculture Sample Census - 2007/08 iv 2.3.1 Land Utilization ........................................................................................................ 17 2.3.2 Type of Land Use ..................................................................................................... 18 2.4 Analysis of the Most Important Crops ......................................................................... 20 2.4.1 Cropping Seasons ..................................................................................................... 20 2.4.2 Planted Area .............................................................................................................. 20 2.4.3 Crop Type ................................................................................................................. 21 2.5.1 Cereal production ...................................................................................................... 22 2.5.2 Roots and Tuber Crop Production ........................................................................... 29 2.5.3 Pulse Crop Production .............................................................................................. 31 2.5.4 Oil Seeds Production ................................................................................................ 33 2.6 Perennial Crops ............................................................................................................ 36 2.7 Cash Crop Production .................................................................................................. 37 2.7.1 Tobacco ................................................................................................................... 37 2.7.2 Sisal ......................................................................................................................... 38 2.7.3 Coffee ...................................................................................................................... 38 2.7.4 Tea ........................................................................................................................... 39 2.7.5 Sugarcane ................................................................................................................ 39 2.7.6 Cashewnuts ............................................................................................................... 39 2.7.7 Coconuts ................................................................................................................... 40 2.7.8 Bananas ..................................................................................................................... 40 2.8 Irrigation ...................................................................................................................... 41 2.9 Crop Marketing ............................................................................................................ 42 2.9.1 Main Marketing Problems ........................................................................................ 42 2.10 Use of credit for Agriculture Purpose .......................................................................... 43 2.10.1 Access to credit facilities .......................................................................................... 43 2.10.2 Reasons for Not Using Credit Facilities ................................................................... 43 2.10.3 Credit Sources by Type of Farm Activity ................................................................. 44 2.10.4 Farms which Borrowed Money and Type of Credit Facilities ................................. 44 CONTENTS Tanzania Agriculture Sample Census - 2007/08 v 2.11 Sources of Inputs for Agricultural Holdings ............................................................... 46 3 LIVESTOCK AND POULTRY RESULTS ............................................................ 48 3.1 Livestock Production and Growth ............................................................................... 48 3.1.1 Cattle Population ..................................................................................................... 50 3.1.2 Goat Population ........................................................................................................ 52 3.1.3 Sheep population ...................................................................................................... 53 3.1.4 Pig Population ........................................................................................................... 54 3.1.5 Chicken population ................................................................................................... 54 3.1.6 Other livestock .......................................................................................................... 56 3.2 Livestock and Poultry Products .................................................................................. 56 3.2.1 Meat Production ........................................................................................................ 56 3.2.2 Milk production ........................................................................................................ 57 3.2.3 Egg Production ......................................................................................................... 58 3.2.4 Hides and Skins ........................................................................................................ 58 3.3 Livestock Diseases ....................................................................................................... 59 3.3.1 Chicken ..................................................................................................................... 59 3.3.2 Coccidiosis Disease .................................................................................................. 59 3.3.3 Chorysa Disease ........................................................................................................ 60 3.3.4 Typhoid Disease ....................................................................................................... 60 3.3.5 New Castle Disease .................................................................................................. 60 3.3.6 Deaths due to Disease Infections .............................................................................. 61 3.4 Access to Livestock infrastructure and Services ......................................................... 62 3.4.1 Access to Veterinary Clinic ...................................................................................... 63 3.4.2 Access to Market for Livestock ................................................................................ 63 3.4.3 Access to input supply facilities ............................................................................... 64 3.4.4 Access to Primary Market ........................................................................................ 64 3.4.5 Access to hide and skin shades ................................................................................. 65 3.4.6 Access to nearest village watering point /dam ......................................................... 65 CONTENTS Tanzania Agriculture Sample Census - 2007/08 vi 3.5 Farm Employment ....................................................................................................... 65 3.5.1 Temporary Employees .............................................................................................. 66 3.5.2 Permanent Employees .............................................................................................. 67 3.6 Outgrowers Schemes ................................................................................................... 67 4. REGIONAL PROFILES .......................................................................................... 69 4.1 Arusha .......................................................................................................................... 69 4.2 Dar es Salaam .............................................................................................................. 70 4.3 Dodoma ........................................................................................................................ 70 4.4 Iringa ............................................................................................................................ 71 4.5 Kagera .......................................................................................................................... 72 4.6 Kigoma ........................................................................................................................ 73 4.7 Kilimanjaro .................................................................................................................. 74 4.8 Lindi ............................................................................................................................. 74 4.9 Manyara ....................................................................................................................... 75 4.10 Mara ............................................................................................................................. 76 4.11 Mbeya .......................................................................................................................... 76 4.12 Morogoro ..................................................................................................................... 77 4.13 Mtwara ......................................................................................................................... 78 4.14 Mwanza ........................................................................................................................ 79 4.15 Pwani ........................................................................................................................... 80 4.16 Rukwa .......................................................................................................................... 80 4.17 Ruvuma ........................................................................................................................ 81 4.18 Shinyanga .................................................................................................................... 82 4.19 Singida ......................................................................................................................... 83 4.20 Tabora .......................................................................................................................... 84 4.21 Tanga ........................................................................................................................... 84 4.22 Zanzibar ....................................................................................................................... 85 5. APPENDICES ............................................................................................................ 86 ILLUSTRATIONS Tanzania Agriculture Sample Census - 2007/08 vii ILLUSTRATIONS List of Tables Table 2.1: Number of large scale farms between 1994 and 2008 .................................................. 12 Table 2.2: Time Series of the Number of Large Scale Farms by Type ......................................... 14 Table 2.3 Proportion of Area planted by Large Scale Farms and Small Scale Farms, 2002/03 and 2007.08 Agriculture Sample Census ............................................ 15 Table 2.4 Number of Farms, Area and Area per Farm by Type of Farm ..................................... 16 Table 2.5 Distribution of Land by Type of Ownership 2007/08 ................................................. 17 Table 2.6 Land Area by Type of Use ............................................................................................ 18 Table 2.7 Area Planted with Annual Crops by Crop Type and by Season ................................... 20 Table 2.8: Area Planted and Quantity Harvested on Large Scale Farms and Type of Cereal Crop in 2007/08 ................................................................................... 22 Table 2.9 Area Planted and Yield of Cereal Crops ....................................................................... 23 Table 2.10: Roots and Tuber Crops Production, Storage and Marketing, 2007/08 ......................... 30 Table: 2. 11: Planted Area with Major Pulses ................................................................................... 31 Table 2.12: Oil Seed Crops: Planted Area, Harvested and Marketing, 2007/08 ............................. 34 Table 2.13: Number, Acreage and Percentage of Large Scale Farms, Perennial Crops, 2007/08 .............................................................................................. 37 Table 2.14 Percentage of Farms Reporting Marketing Problems by Problem Type ...................... 42 Table 2.15 Percentage Distribution of Farms that Did Not Borrow and Reasons for Not Borrowing ................................................................................... 44 Table 3.1 Heads of Livestock by Type ......................................................................................... 48 Table 3.2: Comparative Livestock Number and Unit .................................................................... 49 Table 3.4: Number of Chickens died from major poultry diseases in 2007/08 census ................. 62 Table 3.5 Number of Employees by Category .............................................................................. 67 ILLUSTRATIONS Tanzania Agriculture Sample Census - 2007/08 viii List of Charts 2.1 Number of Holdings and Area Covered ...................................................................... 12 2.2 Proportion of Change of Large Scale Farms by Region ............................................... 13 2.4 Number of Large Scale Farms Holdings by Type ........................................................ 14 2.5 Trend of Large Scale Farms by Type from 1995 - 2008 ............................................. 14 2.6 Number of Large Scale Farms by Type and Region .................................................... 14 2.7 Number of Holdings and Area Planted by Regions ...................................................... 15 2.8 Distribution of Area Covered by Type of Farm Holdings ........................................... 16 2.9 Area Covered (ha) by Types of Farm and Regions ...................................................... 16 2.10 Distribution of Land by Type of Ownership 2007/08 .................................................. 17 2.11 Allocated Usable Land and Utilized Land by Region ................................................. 18 2.12 Land Area by Type of Use ........................................................................................... 19 2.13 Area of Annual and Permanent Crop ............................................................................ 19 2.14 Area Planted with Annual Crops by Crop Type ........................................................... 20 2.15 Area Planted with Annual Crops by Season ................................................................. 20 2.16 Area Planted with Annual Crops by Season and Region ............................................. 21 2.18 Planted area per Farm (ha) by Season and Region ...................................................... 21 2.20 Area Planted with Annual Crops by Crop Type ........................................................... 22 2.21 Area Planted and Yield of Cereal Crops ..................................................................... 23 2.22 Pea Planted with Cereal and Percent of Land with Cereals by Region ........................ 23 2.23 Percent of Maize Area Planted and Percent of Total Land Area with Maize by Region ........................................................................................................... 24 2.24 Planted Area per Maize Growing Farm by Region – Long Rainy Season .................. 25 2.25 Percent of Paddy Area Planted and Percent of Total Land Area with Paddy ............... 25 2.26 Area Planted per Paddy Growing Farm by Region Long Rains ................................... 26 2.27 Wheat Area (ha) Planted and Number of Farms by Region ........................................ 26 2.29 Percent of Barley Area Planted and Percent of Total Land Planted by Regions .......... 27 2.30 Area Planted per Barley Growing Farm by Region...................................................... 28 2.31 Percent of Sorghum Ara Planted and Percent of Total land Planted by Regions ........ 28 ILLUSTRATIONS Tanzania Agriculture Sample Census - 2007/08 ix 2.32 Area Planted per Sorghum Growing Farm by Region.................................................. 29 2.33 Area Planted and Yield of Major Roots and Tuber Crops ............................................ 30 2.34 Percent of Irish Potatoes Planted Area and Proportion of Land by Region ................. 31 2.35 Area Planted and Yield of Major Pulse Crops .............................................................. 32 2.36 Percent of Beans Planted area and Proportion of Land Planted with Beans ................ 33 2.37 Planted area per Beans Growing Farm ........................................................................ 33 2.38 Area Planted and Yield of Oil Seed Crops ................................................................... 34 2.39 Percent of Groundnuts Planted Area and Proportion of Land with Groundnuts by Region .................................................................................................. 35 2.40 Area Planted per Groundnut Growing Farm by Regiion – Long Season .................... 35 2.41 Area Planted (ha) for Annual and Permanent Crops .................................................... 36 2.42 Area under Perenial Crops in Tanzania ........................................................................ 37 2.43 Number of Farms by Main Cash Crops in 2007/08 .................................................... 37 2.44 Percentage of Tobacco Planted Area and Proportion of Land by Region .................... 38 2.45 Area Planted with Sisal (ha) by Region ........................................................................ 38 2.46 Area Planted with Coffee (ha) by Region .................................................................... 38 2.47 Area Planted with Tea (ha) by Region ......................................................................... 39 2.48 Area Planted with Sugarcane (ha) by Region ............................................................... 39 2.49 Area Planted with Cashewnuts (ha) by Region ........................................................... 40 2.50 Area Planted with Coconuts (ha) by Region ................................................................ 40 2.51 Area Planted with Banana (ha) by Region .................................................................. 41 2.52 Planted area of Irrigated Land for Cash Crops ............................................................ 41 2.53 Area (ha) under Irrigation for Perenial Crops large Scale Farms ................................. 41 2.54 Percent of Farms Reporting Marketing Problems by Problem Type ........................... 42 2.56 Number of Farm that Borrowed Money from Credit Facilities .................................. 43 2.57 Number of Farms that Received Credit by region ....................................................... 43 2.58 Percent Distribution of Farms that did not Borrow and Reasons for not Borrowing .. 44 2.59 Reason for LSF not Accessing Credit by Regions ...................................................... 44 ILLUSTRATIONS Tanzania Agriculture Sample Census - 2007/08 x 2.60 Number of Holdings Receiving Credit by Source of Credit and Type of Activity (Source A) ......................................................................................... 45 2.61 Number of Holdings Receiving Credity by Soruce of Credit and Type of Activity (Source B) .................................................................................................. 46 2.63 Percent of Holdings by Soruce of Selected Inputs 2007/08 ......................................... 46 2.64 Average Cost (Tshs 1000) per ha for Various Farm Operations/Inputs 2007/08 ........ 47 3.1 Head of Livestock by Type ........................................................................................... 48 3.2 Number of Large Scale Farms Keeping Livestock by Type ....................................... 48 3.3 Comparison of Livestock Number and Unit ................................................................. 49 3.4 Comparison of Livestock Number and LSU by Reason .............................................. 50 3.5 Cattle Population by Region ........................................................................................ 51 3.6 Cattle Population by Region ......................................................................................... 51 3.7 Improve Cattle Population Trend ................................................................................. 51 3.8 Improve Cattle Population Growth ............................................................................... 51 3.9 Goat Population by Region ........................................................................................... 52 3.10 Sheep Population by Region ......................................................................................... 53 3.11 Sheep Population Trend ............................................................................................... 53 3.12 Sheep Population by Region ......................................................................................... 53 3.13 Pig Population Trend (Large Scale Farms) .................................................................. 54 3.14 Chicken Population by Region ..................................................................................... 55 3.16 Number of Improved chicken by Region ..................................................................... 55 3.17 Livestock Products Number Slaughtered Quantity Sold .............................................. 56 3.18 Average Number of Livestock Sold by Region 2007/08 .............................................. 57 3.19 Quantity of Livestock Products and Average Price by Sales Destination ................... 57 3.20 Milk Production in Large Scale Farms 2007/08 by Breeds and Region ...................... 57 3.21 Number of Eggs Produced and Consumed per Day by Region.................................... 58 3.22 Number of Hides and Skin by Region .......................................................................... 58 3.23 Number of Hides/Skins sold by Large Scale Farms ..................................................... 58 3.24 Number of Chicken Infected with Contigious Diseases ............................................... 59 ILLUSTRATIONS Tanzania Agriculture Sample Census - 2007/08 xi 3.25 Percentage of Chicken Infected with Coccidiosis by Region ..................................... 59 3.26 Percentage of Chicken Infected with Chorysa by Region ............................................ 60 3.27 Percentage of Chicken Infected with Fowl Typhoid by Region................................... 60 3.28 Percentage of Chicken in the Region Infected with New Castle ................................. 60 3.29 Percentage of Chicken Died due to Contigious Diseases ............................................ 61 3.30 Number of Chicken Dead by Conagious Disease and Proportion of Death ................. 61 3.31 Number of Chicken Dead by Newcastle Disease by Region ....................................... 61 3.32 Number and Percentage of Chicken Dead due to Contigious Diseases by Region ..... 62 3.33 Percentage of Farms 15km and above to the Nearest Livestock Structure .................. 62 3.34 Peercent of Farms >15km from Veterinary Clinic ....................................................... 63 3.35 First most important outlet by Type of Liestock kept by LSF in 2007/08 ................... 63 3.36 Second most important outlet by Tyype of Livestock Kept by LSF in 2007/08 .......... 63 3.37 Percentage of Farms >15km from Input Supply Center ............................................... 64 3.38 Percentage of Farm >15km from Primary Market ...................................................... 64 3.39 Large Scale Farm Located <5km from Hide/Skins shade by Region .......................... 65 3.40 Number of Holdings and Percentage with Access to Water Point Less than Skin by Region ...................................................................................................... 65 3.41 Number of Employees by Gender ................................................................................ 65 3.42 Number of Employees by Type of Employment .......................................................... 66 3.43 Number of Temporary Employed by Gender and REgion ........................................... 66 3.44 Number of Employees by Category ............................................................................. 67 3.45 Number of Permanent Employees by Gender and Region ........................................... 67 3.46 Area (ha) and Number of Farms under outgrowers Schemes ...................................... 68 3.47 Services Offered by LSF Outgrower Capacity ............................................................. 68 ABBREVIATIONS Tanzania Agriculture Sample Census - 2007/08 xii LIST OF ABBREVIATIONS ASDP Agricultural Sector Development Programme CSPro Census and Survey Processing System CSTWG Census and Surveys Technical Working Group DADIPS District Agricultural Development and Investment Projects DfID Department for International Development EU European Union FAO Food and Agriculture Organisation GDP Gross Domestic Product ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japan International Cooperation Agency LSF Large Scale Farms MAFS Ministry of Agriculture, Food Security and Cooperatives NBS National Bureau of Statistics NGO Non Government Organisation NSGRP National Strategy for Growth and Reduction of Poverty OCGS Office of the Chief Government Statistician, Zanzibar PMO_RALG Prime Minister’s Office, Regional Administration and Local Government SPSS Statistical Package for Social Sciences UNDP United Nations Development Programme EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xiii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2007/08. The report provides detailed description of the state of large scale farms in Tanzania for the agricultural year 1st October 2007 to 30th September 2008. Most of the analysis and tabulation permit comparisons between regions. In some cases, the contribution of smallholder agriculture is included to give the overall country estimate. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources and provision of credit for large scale farms. i) Farm Holding Characteristics During the 2007/08 agricultural year, the number of large scale farms in Tanzania were 1,006 covering an area of 1,113,890 hectares. A total of 520 (52%) farms were involved in crops only, 189 (19%) in livestock only, 286 (28%) were involved in crop production as well as livestock keeping and 11 (1%) were involved in cut flowers production. In summary, Tanzania Mainland had 817 large scale farms involved in crop production and 475 involved in livestock production. The area in crops only farms was 459,827 hectares (41%), for the livestock only was 410,181 hectares (37%), for crops and livestock was 243,140 hectares (22%) and 742 hectares (1%) for cut flowers production. ii) Annual Crop Production Planted Area The area planted with annual crops and vegetables was 62,373 hectares out of which 6,838 hectares (11%) were planted during the short rainy season and 55,535 hectares (89%) during the long rainy season. An area of 42,358 hectares ( 68%) was planted with cereals, followed by -6,624 hectares ( 11%) of pulses, 5,832 hectares ( 9.4%) of cash crops, 4,174 hectares (6.7 %) of oil seed crops, 3,171 hectares ( 5.1%) of fruits & vegetable crops and 213 hectares (0.3%) of root and tuber crops. Maize Maize was grown on 453 large scale farms during the long rainy season covering 20,407 hectares and during the short rainy season, 117 large scale farms covering 3,076 hectares were planted with maize. The total area planted with maize was 23,483 hectares or 52.4 percent of the total area grown with cereal crops. During the long rainy season, the highest concentration of maize farms were in Manyara, followed byArusha, Iringa and Ruvuma, while the lowest EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xiv numbers were in Mwanza, Kigoma, Shinyanga, South Unguja andNorth Pemba, each with only one large scale farm. Manyara had the largest area (5,496 hectares) followed by Arusha (3,404 ha), Dodoma (2,830 ha), Kilimanjaro (2,343ha), Iringa (1,319 ha) and Ruvuma (1,231 ha) while the lowest planted area was in Dar es Salaam ( 17 ha) and South Unguja (3 ha). In the short rainy season, the largest areas under large scale farms were in Pwani (725 ha) and Mara ( 717 ha). Highest number of farmers were recorded in Mwanza (29 farms), Tanga (20 farms), Morogoro (21) and Mara (15 farms). Paddy Paddy was grown on 103 large scale farms during the long rainy season covering 4,361 hectares and during the short rainy season, 36 large scale farms covering 1,087 hectares were planted with paddy. The area harvested was 1,014 hectares. The total area for paddy was 5,448 hectares or 12.1 percent of the total area grown with cereals. During the long rainy season, the highest concentration of farms were in Morogoro, Mbeya Ruvuma and Mwanza, while the lowest numbers were in Rukwa, Kilimanjaro and Singida. Paddy was virtually not grown in Arusha, Kigoma, Shinyanga Kagera and Soutn Unguja. Mbeya had the largest planted area (1,883 ha) followed by Morogoro (1,740 ha), and Tanga (653 ha). Mwanza and Urban West had the smallest planted area of 2 hectares each followed by Mtwara and Dar es Salaam (each with 9 ha). In short rainy season, the largest number of large scale farms were in Mwanza (15 farms) and Morogoro (9 farms) while the lowest numbers of large scale farms were in Urban North, North Pemba and South Pemba (each with 1 farm). Tanga had the largest area of 443 hectares followed by Morogoro (401 ha), Mara (121 ha) and Mwanza (107 ha). North Pemba had the smallest area (3 ha) planted with paddy followed by Urban West (5 ha) and South Pemba (8ha). Wheat Wheat was grown in 9 regions on 67 large scale farms during the long rainy season covering 12,585 hectares. The area harvested was 12,345 hectares. During the short rainy season, it was grown in only one region and in one large scale farm covering 8 hectares. The total area cultivated with wheat was therefore 12,593 hectares or 28% of the total area under cereal crops. Total wheat production during the two seasons was 161,855 tonnes. EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xv Sorghum Sorghum was grown on 35 large scale farms during the long rainy season covering 693 hectares and producing 2,013 tonnes. The area harvested was 679 hectares recording a yield of 3.0 tonnes per hectare. During the short rainy season, 14 large scale farms covering 98 hectares were plated with sorghum and produced 88 tonnes. The area harvested was 96 hectares recording a yield of 1.0 tonne per hectare. The total area for sorghum was therefore 791 hectares or 1.7 percent of the total area grown with cereal crops. Total sorghum production during the two seasons was 2,101 tonnes making an average yield of 3.0 tonnes per hectare. Beans Beans were grown on 175 large scale farms during the long rainy season, covering 4,233 hectares and producing 5,278 tonnes. The area harvested was 3,955 recording a yield of 1.3 tonnes per hectare. Arusha had the largest number of farms (51) followed by Iringa (23), Ruvuma (20) and Kilimanjaro (16). The lowest numbers were in Morogoro (1), Mtwara (1), Kigoma 1) and Shinyanga (1). The largest area planted with beans was in Arusha (2,435 ha), Kilimanjaro (800 ha), Mara (798 ha) and Manyara (765 ha) while the lowest was in Shinyanga (1 ha), Morogoro (1ha), Kagera (3ha) and Kigoma (3 ha). During the short rainy season, beans were grown on 27 large scale farms covering an area of 1,216 hectares and producing 3,017 tonnes. The area harvested was 1,158 recording a yield of 2.6 tonnes per hectare. Arusha had the largest number of farms (7) followed by Mwanza (5), Mara (5) and Kilimanjaro (4). The lowest numbers were in Iringa (1), Kagera (1), and Manyara (1). Area wise, Mara had the largest area (785 ha), while Iringa had the lowest area (1 ha) planted with beans. Cotton Cotton is mainly grown in the Lake Zone. In the 2007/08 agricultural year, 197 hectares were planted on 5 large scale farms during the long rainy season and 137 tonnes were harvested giving an average yield of 0.7 tonnes per hectare. In short rainy season, cotton was grown on 17 large scale farms covering an area of 117 hectares which produced 139 tonnes with an average yield of 1.2 tonnes per hectare. However, Mwanza was the only region which produced cotton on large scale farms during the season. In EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xvi 1994/95 agricultural year, 391 tonnes of cotton were harvested. Therefore, for the period from 1994/95 to 2002/03, the harvest increased by 222 percent but it decreased to 139 tonnes in 2007/08 agricultural year. Tobacco Tobacco is mainly grown in Tabora and Iringa regions. During the long rainy season, 13 large scale farms were grown with tobacco covering an area of 751 hectares. The highest numbers of farms were in Iringa (54%) and Tabora (46%). (iii) Permanent Crop Production The permanent crops were grown on 704 large scale farms covering 164,330 hectares or 9.9 percent of the total area (1,113,890 hectares) covered by all the large scale farms. In 1994/95 agricultural year, 796 large scale farms were planted with perennial crops which covered 98,575 hectares. For the period from 1994/95 to 2002/03, the number of large scale farms planted with perennials increased by 47 percent but the area increased by 12 percent (from 98,575 hectares in 1994/95 to 109,940 hectares in 2002/03). Also, there was an increase in production for most of the perennials. In 2007/08, the number of farms decreased by 39% from 1,173 in 2002/03 to 704 but the total area has increased by 49% from 109,940 ha to 164,330 ha. The most important permanent crop was sisal which accounted for 35.6 percent of the total area planted with perennials followed by sugar cane (18.3%), tea (11.5), cashewnuts (9.7%) and coffee (3.9%). Sisal Sisal was planted on 42 (6%) large scale farms with permanent crops, covering an area of 34,696 (36%) hectares with an average of 826 hectares per farm. The harvest was 50,714 tonnes making an average yield of 1.2 tonnes per hectare. The harvest in 2002/03 was 188,870 tonnes, therefore, for the period from 2002/03 to 2007/08, there was a production decrease of 73 percent between the two agricultural years. Sugar cane Sugar cane was planted on 42 (6%) large scale farms covering an area of 17,804 (17%) hectares with an average of 424 hectares per farm. The harvest was 218,589 tonnes making an average yield of 12 tonnes per hectare. The harvest in 1994/95 was 180,058 tonnes and in 2002/03 was EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xvii 236,073 tonnes, therefore, for the period from 2002/03 to 2007/08 there was a decrease in production by 7.4 percent. Coffee Coffee was planted on 95 (13%) large scale farms covering 3,836 hectares (22%) giving an average of 40 hectares per farm. About 33,279 tonnes were harvested recording an average yield of 9 tonnes per hectare. In 1994/95 agricultural year, the harvest was 2,105.5 tonnes and in 2002/03 was 19,084 tonnes therefore, for the period from 2002/03 to 2007/08 there was an increase in production by 74 percent. Banana Banana crop was planted on 91 (13%) large scale farms covering an area of 1,449 (1%) hectares giving an average of 16 hectares per farm. The harvest was 121,639 tones making an average yield of 84 tones per hectare. Tea Tea crop was planted on 35 (5%) large scale farms covering an area of 11,213 (7%) hectares recording an average of 320 hectares per farm. The harvest was 74,613 tonnes making an average yield of 7 tonnes per hectare. The harvest in 1994/95 was 50,242 tonnes and in 2002/03 was 33,978 tonnes therefore after five years, there was an increase in production of about 120 percent. Cashew nuts Cashew nut crop was planted on 76 (11%) large scale farms covering an area of 9,463 (7%) hectares recording an average of about 125 hectares per farm. The harvest was 28,831 tonnes making an average yield of 3 tonnes per hectare. The harvest in 1994/95 was 439 tonnes, and in 2002/03 was 935 tones therefore, for the period from 2002/03 to 2007/08 there was an increase in production of about 2,984 percent. Livestock and Poultry Production As of 1st October 2008, there were 661,958 heads of the major livestock types (i.e. cattle, goats, sheep and pigs) and 7,097 heads of the minor livestock types (except chicken) making a total number of all types of livestock to be 669,095 heads. Among the major livestock types, cattle EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xviii were the predominant species in terms of major livestock numbers followed by goats, sheep and pigs. For the minor livestock types, chicken were the predominant type. Cattle Cattle were reared on 527 large scale farms with a total population of 120,014 giving an average of 228 headsfarm. Iringa had the largest number of farms rearing cattle (396), followed by Manyara (249), Morogoro(247), and Mwanza (225). The smallest numbers were in Unguja (4) and Shinyanga (11). However, Kagera region had the highest population of cattle (27,372) followed by Iringa (10,679), Morogoro (9,967) and Pwani (9,619). Out of the 120,014 cattle, 44 percent were indigenous. The average number was 227 heads of cattle per farm. Goats Goats were reared on 359 large scale farms with a total of 24,193 goats (i.e. 68 heads/farm). Iringa had the largest number of farms rearing goats (42) followed by Manyara (38), Morogoro (37), and mwanza (22) while the smallest numbers were in North Pemba (1), South Unguja (1), Shinyanga and Kigoma (each with 2 farms) .The highest population of goats was in Iringa (3,400) followed by Morogoro (3,292), Pwani (2,095) and Dodoma (2,028) while South Unguja and North Pemba had the lowest population of goats. Sheep Sheep were reared on 200 large scale farms with 14,609 sheep at an average of 73 heads perfarm. Iringa had the largest number of large farms rearing sheep (36) followed by Morogoro and Manyara while Dodoma, North Pemba, South Unguja, Shinyanga, and Kigoma each with a small number of farms. Sheep population is concentrated in Iringa, Morogoro and Kilimanjaro, the lowest population is in Kigoma, Shinyanga, North Unguja and Rukwa. Pigs Pigs were reared on 108 large scale farms with 8,316 heads representing an average of 79 pigs per farm. Iringa had the largest number of farms followed by Ruvuma, Morogoro and Kilimanjaro while the lowest were Kagera, Singida, lindi and Mtwara. Pigs were more concentrated in Ruvuma followed by Mbeya, and Iringa while the lowest numbers were in Tanga, Singida, and Lindi. The total number of pigs has decreased from 10,186 in 2002/03 EXECUTIVE SUMMARY Tanzania Agriculture Sample Census - 2007/08 xix although the average number of pigs per farm has slightly increased to 79 from 73 pigs per farm in 2002/03. Chicken Chicken are important livestock reared on large scale farms. In total, there were 494,866 chicken of which 47.7% were layers; 47.3% broilers and 5% were indigenous. In terms of numbers of chicken, Pwani had the highest population (188,273) followed by Iringa (113,342) and Dar es Salaam (101,921). Kigoma, Rukwa and Lindi had the lowest population. The total number of chicken has increased by 8.4% (from 456,638 in 2002/03 to 494,866 in 2007/08). Farm Employment There were a total of 98,184 large scale farm employees with the majority (66,597, 68%), being temporary employees and the remaining 32% being permanent employees). Of the permanent employees, 68.4 percent were males and 32.4 percent were females while for temporary employees, 50 percent were males and 50 percent were females. INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 1 1. INTRODUCTION 1.1 Introduction The agricultural sector is the main source of employment and livelihood for more than two-thirds of the Tanzanian population. It is an important economic sector in terms of food production, employment generation, production of raw material for industries, and generation of foreign exchange earnings. It accounts for about 26 percent of the GDP (Economic Survey, 2008). Having a diversity of climatic and geographical zones, Tanzania’s farmers grow a wide variety of annual and permanent crops. The country grows a large number of food crops including maize, cassava, beans, banana, paddy, sorghum and millet. In addition, large scale farms produce a variety of fruits and vegetables such mangoes, oranges, water melon, tomatoes, potatoes, egg plants, etc. Permanent crops like coffee, tea, spices, etc. are also grown. Coffee which is grown on estates and by smallholders is one of the major export crops. Cotton, cashew nuts and tobacco are also grown on large scale farms for export. Smallholders in Tanzania mainly carry out rain-fed agriculture for subsistence purposes. The commercial large scale sub sector is very small (1,006 holdings) and produces some of the export crops in the country (coffee, tea, sisal, sugar, etc.). The present report analyses the data related to land ownership, land use, crop production, input use, marketing, investment in agriculture and access to inputs and services for the crops produced in the country. Also, it analyses livestock production, livestock diseases, access to livestock infrastructure services, livestock extension services and farm employment in general. This report (Volume IV) covers the Large Scale Farming at National and Regional Level. Other Census reports include the Technical Report (Volume I), Crop Report (Volume II), Livestock Report (Volume III), 21 Regional Reports for the Mainland (Volume V) and Zanzibar Crop and Livestock reports (Volume VI & VII respectively). In order to address the specific issues of gender, a separate thematic report on gender will be produced. Other thematic reports will be produced depending on the demand and availability of funds. This report is organized in four main sections: Introduction, Results, Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix I). 1.2 Background Information In 2003, the Government of Tanzania launched the 2002/03 Agricultural Sample Census for smallhold farmers and large scale farmers as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 2 poverty reduction, access to services, gender, as well as the standard production data normally collected in an agricultural census. The census was intended to support and fill the information gap necessary for planning and policy formulation by high level decision making bodies. It was also meant to provide critical benchmark data for monitoring ASDP and other agricultural and rural development programmes as well as prioritizing specific intervention of most agricultural and rural development programmes. Following the privatization, decentralization of the Government’s administration and planning functions, there has been a pressing need for agricultural and rural development data disaggregation at regional and district level. The provision of district level estimates will provide essential baseline information on the state of agriculture that supports decision making by the Local Government Authorities. The increase in investment is an essential element in the national strategy for growth and reduction of poverty. 1.2.1 Census Objectives The 2007/08 Agricultural Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers’ organizations, etc. As a result, the dataset for the large scale farms is based on a complete enumeration. To date, this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: Identify structural changes in the size of farm holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural as well as urban infrastructures. Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture Food Security and Cooperatives and other stakeholders. Establish baseline data for the measurement of the impact of high level objectives of the National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programmes and projects. INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 3 Obtain a benchmark data that will be used to address specific issues such as: food security, poverty, agro-processing, marketing, service delivery etc. 1.2.2 Census Coverage The census covered both large scale and small scale farms. This report covers large scale farms in detail with some summary data from small scale farms in order to provide complete national estimates for some variables. Data were collected from 52,635 small scale farmers, out of which 47,880 were from the Mainland and 4,755 from Zanzibar. For large scale farms, data was collected from a total of 1,006 farms (968 for the Mainland and 38 for Zanzibar) on a complete enumeration basis. 1.2.3 Census Scope The census covered the sector of agriculture in detail as well as many other aspects of rural development and was conducted using three different questionnaires: Small scale questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; and issues on poverty, gender and subsistence versus profit making production unit. Some data from small scale farms have been incorporated in this report, however an in depth analysis of small scale farms is presented in a separate report. The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to all large farms either privately or corporately managed. The main topics covered were: Number of Holdings and Holding/Farm Characteristics Land Access / Ownership / Tenure Land Use Annual Crops and Vegetable Production (Vuli and Masika seasons) Perennial Crop and Fruit Tree Production INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 4 Main Use of Secondary Products Use of Credit for Agricultural Purposes Tree Farming / Agro-forestry Marketing Services provided to Out growers Input Use and Costs by Crop Livestock (Population, Intake and Off-take, Diseases – pests and control) Livestock Extension Services Staff and Labor use 1.3 Census Methodology The main focus at all stages of the census execution was on data quality. The main activities undertaken include: Census Organization Tabulation Plan Preparation Design of Census Questionnaires and Other Instruments Field Pre-Testing of the Census Instruments Training of Trainers, Supervisors and Enumerators Information Education and Communication (IEC) Campaign Data Collection Field Supervision and Consistency Checks Data Processing: o Scanning o Structure formatting application o Batch validation application o Manual data entry application o Tabulation preparation using SPSS Table formatting and charts using Excel, map generation using Arc GIS and. Report preparation using Word and Excel INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 5 1.3.1 Census Organization The census was conducted by the National Bureau of Statistics (NBS) in collaboration with the sector Ministries of Agriculture, and the Office of the Chief Government Statistician (OCGS), Zanzibar. At the National level, the census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group had the responsibility to oversee the operational aspects of the census and this group was comprised of staff from the Department of Agricultural Statistics of NBS and three representatives of the Department of Policy and Planning of the Ministry of Agriculture, Food Security and Cooperatives (MAFC). At the regional level, implementation of the census activities was overseen by the Regional Statistical Officers of NBS and the Regional Agricultural Statistics Supervisors from the Ministry of Agriculture and Food Security. At the District level, the census activities were managed by two Supervisors from the Prime Minister’s Office, Regional Administration and Local Government (PMO-RALG).The supervisors managed the enumerators who also came from PMO- RALG. Members of the Planning Group had a minimum qualification of a bachelor’s degree; the Regional Supervisors were Agricultural Economists, Statisticians or Statistical Officers. The District Supervisors and Enumerators had diploma level qualifications in Agriculture. The Censuses and Surveys Technical Working Group (CSTWG) provided support in sourcing finance, approving budget allocations and Technical Assistance inputs as well as monitoring progress of the census. A Technical Committee for the census was established with members from key stakeholder organizations and its main function was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the census data. 1.3.2 Tabulation Plan Preparation The tabulation plan was developed following three user group workshops which discussed the information and data needs of the end users. It also took into consideration the tabulations from previous censuses and surveys to allow trend analysis and comparisons. 1.3.3 Questionnaire Design and Other Instruments The questionnaires were designed following user meetings to ensure that the questions asked were in line with users data needs. Several features were incorporated into the design of the questionnaires to increase the accuracy of the data: INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 6 Where feasible, all variables were extensively coded to reduce post enumeration coding errors. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer/respondent. The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and Intelligent Character Recognition (ICR) technologies for data entry. Skip patterns were used to reduce unnecessary and incorrect coding of sections which do not apply to the respondent. Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Two other instruments were used: A Training Manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. Enumerator’s Instructions Manual which was used as reference material. 1.3.4 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in two locations (Arusha and Dodoma). This was done to test the wording, flow and relevance of the questions and to finalize crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalized, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentage in the questionnaire and finalizing skip patterns and documenting consistency checks. 1.3.5 Training of Trainers, Supervisors and Enumerators During the training, cascade/pyramid training techniques were employed to maintain statistical standards. The top level of training was provided to 66 national and regional supervisors (3 supervisors per region plus Zanzibar). The trainers were members of the Planning Group from the National Bureau of Statistics, Mainland and the Office of the Chief Government INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 7 Statistician,Zanzibar and the sector Ministries of Agriculture. In each region, three training sessions were conducted for the district supervisors and enumerators. In addition to training them in field level census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the supervisors and enumerators (50 percent of the trainees were selected for the enumeration of the smallholder questionnaire and the community level questionnaire). 1.3.6 Information, Education and Communication (IEC) Campaign Radios, televisions, newspapers, leaflets, t-shirts and caps were used to publicize the Census. This helped in sensitizing the public for the field level activities. The t-shirts and caps were given to the field staff and the village chairpersons. The village chairpersons helped to locate the large scale farms.within their area. 1.3.7 Data Collection Data collection activities for the Census took about three months from June to August, 2009. The data collection methods used during the census were by interview only. No physical measurements, e.g., crop cutting and field area measurement, were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team, followed by the Regional Supervisors and District Supervisors. The Mobile Response Team consisted of two Senior Supervisors who provided overall direction to the field operations and responded to queries raised outside the scope of the training exercise. The mobile response team consisted of the Manager of Agricultural Statistics Department and the Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all the enumerators via the Regional and District Supervisors. On the Mainland, district supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PMO- RALG). Regional and national supervision was provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. In Zanzibar, the enumeration was done by staff from the Ministry of Agriculture and Natural Resources. Supervision was provided by senior officers of the same ministry and the Office of the Chief Government Statistician. During the household listing exercise, 3,192 extension staff were used on the Mainland and 317 in Zanzibar. For the enumeration of the small holder questionnaire, 1,596 enumerators on Mainland and 158 in Zanzibar were used. An additional five percent of the total number of enumerators was held in reserve in case of drop outs during the enumeration exercise. For the large scale farms, 5 INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 8 enumerators were used in each district (2 District Supervisors in corroboration with 2 Regional Supervisors and 1 National Supervisor). 1.3.8 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by Regional and National Supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary, a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by supervisors in the district offices. 1.3.9 Data Processing Data processing consisted the following processes: Data entry Data structure formatting Batch validation Tabulation Data Entry Scanning and ICR data capture technology for the small holder questionnaire were used on the Mainland. This not only increased the speed of data entry, it also increased the accuracy due to the reduction of keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended for adoption in future censuses/surveys. In Zanzibar, all data were entered manually using CSPro. Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 9 Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village ID Code and saved the data of one village in a file named after the village code. Batch Validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to the more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaires. After the long process of data cleaning, tabulations were prepared based on a predesigned tabulation plan. Tabulation Statistical Package for Social Sciences (SPSS) was used to produce the census tabulations and Microsoft Excel was used to organize the tables and compute additional indicators. Excel was also used to produce charts while Arc GIS was used for the maps. Analysis and Report Preparation The analysis in this report focuses on regional / operators comparisons, time series and national production estimates. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data Quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this, it is believed that the census is highly accurate and representative of what was experienced at field level during the census year. With very few exceptions, the variables in the questionnaire are within the norms of Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variations for the main variables are presented in the Technical Report (Volume I). INTRODUCTION Tanzania Agriculture Sample Census - 2007/08 10 1.4 Funding Arrangements The Agricultural Census was supported mainly by Department for International Development (DfID) and the Government of Japan through the Japan International Cooperation Agency (JICA). Other funds for operational activities came from the Government of Tanzania.. In addition to this, technical assistance funds were provided by the United Nations Food and Agricultural Organization (FAO). The support is highly apprecaiated. RESULTS Tanzania Agriculture Sample Census - 2007/08 11 2 CROP RESULTS This part of the report presents the results of the census as on the tables presented in Appendix II. The results are presented in different formats including brief summaries, charts, condensed tables and graphs. Comparisons are made between related variables and between regions. Comparisons are also made with past National Sample Census for Agriculture (NSCA) 1994/95, and the one conducted in 2002/03. The presentation of the results is divided into four main sections which are: types of farm holdings, crop results, livestock results and regional profiles Definition of Large Scale Farm: A large scale farm is an economic unit of agriculture production. It consists of all the livestock kept and all the land used for agricultural production without regard to title. For the purpose of the census, large scale agricultural holdings are restricted to those which meet the following conditions. Having operated at least 20 hectares of arable land cultivated for crop/vegetable/fruits/tree crop production during the agricultural year 2007/08 (1st October 2007 to 30 September 2008); and/or Own or keep at least 50 heads of cattle or 100 goats/sheep/pigs or 1000 chickens/ducks/turkey/rabbits/ during the census year as defined above, and/or Operates 0.5 ha of intensive greenhouse horticultural production; and/or Operate 0.5 ha of fish farming production units Also, so as to be classified as large holder, the following criterias must be met: The greatest part of the produce should go to market; The operation of the farm should be continuous; There should be an application of machinery; and There should be at least one permanent employee 2.1 Number of large scale farms 2.1.1 Total number of farms and trends During the 2007/08 agricultural census, the number of large scale farms was 1,006. Over two decades, the number of large scale farms has increased from 480 in 1987/88 to 1,212 in 2002/03 RESULTS Tanzania Agriculture Sample Census - 2007/08 12 and decreased to 1006 in 2007/08 (Table 2.1). The decrease was mainly caused by the decrease in the number of farms cultivating crops only which droped from 756 in 1994/95 to 520 in 2007/08, a decrease of 31 percent. The decrease could not off-set a 22.7% increase in the number of farms keeping livestock only from 154 in 1994/95 to 189 in 2007/08, farms keeping both crops and livestock (121%) . Table 2.1: Number of large scale farms between 1994 and 2008 Farm type 1994/95 2002/03 2007/08 Crop only 756 710 520 Livestock only 154 242 189 Crop & livestock 129 260 286 Production of flowers 0 0 11 Total 1,039 1,212 1,006 Most of the increase was during the period 1994/95 representing an increase of 116 percent. The percentage decrease in the number of large scale farms over the period (from 1,212 to 1,006 large scale farms) was 17% is more pronounced to other operators (27.4), Private non registered 34.5% and Parastatal organizations 43.2%. On the other hand, private registered operators and government farm operators increased by 2.3 and 6.8% respectively. However, whilst the largest area of large scale farms was owned by private registered operators (559,158 ha), the second and third largest areas were owned by Government (282,490 ha) and Parastatals (167,803) (Chart 2.1). 0 50 100 150 200 250 300 350 400 450 0 100,000 200,000 300,000 400,000 500,000 600,000 Government Parastatal Private registered Private Non- registered Other Area Covered Number of Holdings Type of farm Ownership Chart 2.1 Number of Holdings and Area Covered Area covered Number of holdings The results of this survey revealed that parastatals, despite having the smallest number of operators (25), had the largest area of land per operator (6,712 ha per farm). This is followed by Government RESULTS Tanzania Agriculture Sample Census - 2007/08 13 with 1,822 ha per farm and private registered farms (1,309 ha per farm). From 2002/03 to 2007/08, the rate of increase in the number of large scale farms was highest in Kagera region (218%) followed by Dodoma (80%) and Iringa (54%). However, in some regions, the number of large scale farms decreased with the highest rate of decrease found in Shinyanga (- 90%), Kigoma (- 82.5%), Dar es Salaam (- 60%), Kilimanjaro and Morogoro, (each with - 33.6%), (Chart 2.2). However, in terms of total acreage, out of all the regions, the highest (above 100,000 ha) were recorded in Kagera (178,881 ha) followed by Pwani (169,245 ha), Tanga (125,825 ha) and Morogoro (114,875 ha). The lowest acreage was reported in Shinyanga (18 ha), Kigoma (870 ha) and Rukwa (50,500 ha), (Chart 2.2) Chart 2.2: Proportion of Change of Large Scale farms by Region In terms of number of farms, Tanga had the largest number of large scale farms (113, 11.7%), followed by, Iringa (105, (10.8); Arusha (104, 10.7%) and Manyara 90, (9.3%). Kilimanjaro, Ruvuma, Dar es Salaam, Mwanza, and Pwani regions, each had between 50 and 100 large scale farms. The remaining regions had smaller numbers of large scale farms with Mara, Tabora, Shinyanga, Kigoma, Rukwa and Lindi having betweem 3 and 12 farms, (Chart 2.3). 2.1.2 Number by type of farms At national level, crop farming had more farms (520, 52%) than livestock keeping with 189 or 19% of the total large scale holdings. There were 286 (28%) large scale farms keeping both crops and livestock. About 11 (1%) farms produced cut flowers (Chart 2.4). RESULTS Tanzania Agriculture Sample Census - 2007/08 14 Time series data show a decrease of agricultural large scale farms over the period 1994/95 to 2007/08 except for the farms dealing with crops and livestock (Chart 2.5). As shown on table 2.2, the decrease was higher (27 percent) for farms dealing with crops while the decrease for the farms involved in livestock only was 22 percent. However, the number of large scale- farms dealing with crops and livestock increased by about 10 percent from 260 in1994/95 to 286 in 2007/08. Table 2.2: Time Series of the Number of Large Scale Farms by Type Tanga had the highest number of large scale farms growing crops only followed by Arusha, Manyara, Kilimanjaro and Iringa. Kagera, Mara and Kigoma had the lowest number of farms involved in growing crops only while Shinyanga and Rukwa had no large scale farms growing crops only. Pwani followed by Iringa and Kagera had the highest number of large scale farms involved in livestock only whereas Iringa followed by Morogoro, Manyara and Mwanza regions had the largest number of farms with crops and livestock, (Chart 2.6). 0 20 40 60 80 100 120 Number of Holdings Regions Chart 2.6 Number of Large Scale Farms by type and Region Crops Only Livestock Only Crops and Livestock Flowers Type of Farming Activity 1993/ 94 2002/ 03 2007/ 08 % increase/ decrease Crops only 756 710 520 -27 Livestock only 154 242 189 -20 Crops & livestock 129 260 286 10 Production of flowers 0 0 11 0 RESULTS Tanzania Agriculture Sample Census - 2007/08 15 2.2 Land Area under Large Scale Farms In 2002/03 agricultural censuss the total land area allocated to farmers in Tanzania was 12,990,257 hactares (1,105,125 ha under large scale farms and 11,885,132 ha under smallholders). Therefore, large scale farms represented only 8.5 percent of the total farm land in the country. Table 2.3 Proportion of Area planted by Large Scale Farms and Small Scale Farms, 2002/03 and 2007.08 Agriculture Sample Census In 2007/08 census, the total land area covered by large scale farms has slightly increased about 1% from 1,105,125 hectares in 2002/03 to 1,113,148 hectares resulting into an average of 1,106.5 hectares per farm. However, the area under the small-scale farms has decreased by 3.6% and the total planted land area has also decreased by 3.3% during the two agricultural census periods. The increase in area under large scale farms might be caused by the recent Governments’ review of Land Reform Policies which has promoted Land Consolidation (e.g. MKURABITA). Chart 2.3 shows the number of large scale farms and the area planted by region. Tanga had the largest area of large scale farms representing 17 percent of the total area under large scale farming. This was followed by Morogoro (12%) and Kagera (11%). Dar es Salaam, Singida, Shinyanga, Tabora, and Dodoma had the smallest land areas under large scale farming, Chart 2.7). - 50,000 100,000 150,000 200,000 250,000 300,000 0 20 40 60 80 100 120 Area Planted (Ha) Number of Holdings Regions Chart 2.7 Number of Holdings and Area Planted by Regions Total Number Holdings Total Area 2.2.1 Area under Holdings The total area of large scale farms in 2007/08 was 1,113,148 hectares. The largest area was covered by crops only farms (459,827 ha, 41%) followed by livestock only farms (410,181 ha, 37%) and Type of Farm 2002/03 2007/08 Area (ha) % Area (ha) % Small Scale Farms 11,885,132 91.5 11,445,684 91.1 Large Scale Farms 1,105,125 8.5 1,113,148 8.9 Total 12,990,257 100.0 12,558,832 100.0 RESULTS Tanzania Agriculture Sample Census - 2007/08 16 both, crops and livestock farms (243,140 ha, 14%). Area under flowers covered 746 ha (Table 2.4 and Chart 2.8). Table 2.4 Number of Farms, Area and Area per Farm by Type of Farm Type of Farm Number of Holdings Area (ha) Covered % Area Average Area (ha) per Holding Area Under crops Only 520 459,827 41 884 Area Under Livestock Only 189 410,181 37 2170 Area Under crops and Livestock Only 286 243,140 22 850 Area Under Flowers 11 742 0 67 Total 1,006 1,113,148 100 1,107 The overall average area per farm was about 1,107 hectares which is slightly higher compared to 2002/03 agricultural year with an average of 993 hectares per farm. However, farms with livestock only had a larger average area per farm (2,170 hectares per farm) compared to other types of farms; crops only had 884 hectares per farm; crops and livestock had 850 hectares per farm, The largest cultivated area under large scale farms was in Kagera (178,881 ha, 16.1 %), followed by Pwani (169,245 ha 15.2%),Tanga (125,825 ha, 11.3%) and Morogoro ( 114,875 ha, 10.3%), These four regions contributed more than half (53%) of the total area covered by large scale farms in Tanzania. The smallest area of large scale farms was in Shinyanga, (18 ha) Of the main large scale farms, regions with crop farming only were more important in Tanga (105,151 ha), Pwani (99,355 ha), Morogoro (77,404 ha), Iringa (50,586 ha) Manyara (34,343 ha), Arusha (22,627 ha) than other types of farming. Livestock only large scale farms were more important in Kagera (116,285), Pwani (67,267), Dodoma (46,554 ha), Kilimanjaro (29,927 ha) and Rukwa (27, 200 ha) than other regions, (Chart 2.9). RESULTS Tanzania Agriculture Sample Census - 2007/08 17 Land Access and Ownership Like in 2002/03, most of the area under large scale farms was under lease/certified ownership. The proportion of land under leased/certified ownership has declined from 95% in 2002/03 to 94% in 2007/08. Other types of land holdings accounted for 6%. In general, the area under customary law and area borrowed from others has declined by 42% and 32% respectively between the two censuses while the area bought from others and area rented from others has increased by 59.7% and 75.5% respectively. Most of the increase in the ownership was realized in the area under compulsory acquisition where the percentage increase was 263%, (Table 2.5). Table 2.5 Distribution of Land by Type of Ownership 2007/08 2.3 Land use 2.3.1 Land Utilization Of the total land of large scale farms, Kagera had the largest area allocated for large scale farming (178,881 ha) of which 166,962 ha, (93%) was utilized followed by Pwani 99,796 ha (59%), and Tanga 96,438 ha, (77%). On the other extreme, Shinyanga, Dar es Salaam and Tabora had the lowest land allocated for large scale farming (i.e. 18, 827 and 3,535 ha respectively). The proportion of allocated and used land varied grossly across the regions. Kagera region used 92% of the allocated land for large scale farming followed by Singida (91.9%), Shinyanga (88.8%), Mwanza (87%), Dodoma (86.1%) and Dar es Salaam (83.3%). Regions which used less than 50% Type of ownership Area Covered (ha) Area Leased/Certified of ownership 1,042,309 Area owned under Customary Law 15,422 Area Bought from others(not leased/certified) 18,185 Area Rented from others 2,875 Area Borrowed from others 2,713 Area under Compulsory Acquisition 32,386 Total 1,113,890 RESULTS Tanzania Agriculture Sample Census - 2007/08 18 of the allocated land for large scale farming were Ruvuma, Tabora, Zanzibar, Kigoma, and Pwani, (Chart 2.11). 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000 Percent Used Land Area (Ha) Regions Chart 2.11 Allocated Usable Land and Utilized land by Regions Utilized Land (Ha) 2.3.2 Type of Land Use Pasture was the most common land use on large scale farms (116,003 ha, 41%). This is followed by natural bush (18.35%), fallow (33,467 ha, 11.8%) uncultivated useable land excluding fallow (23,768 ha 8.4%) unusable (17,039 ha 6%), and the planted timber trees 18,592 (6.8%). Area for temporary mono-crops (e.g. maize only) account for 9,590 ha (3.4%) followed by permanent mono- crop (e.g. Sisal only) about 8,010 ha (2.8). Mixed cropping such as temporary mixed crops, permanent/pasture, and permanent/annual accounts for less than 1.5% 0f the total land use (Chart 2.12 and Table 2.6). Table 2.6 Land Area by Type of Use Land Use Land Area (ha) Percentage Pasture only 116,003 41.06 Natural Bush 51,834 18.35 Fallow 33,467 11.85 Uncultivated Usable land (excluding fallow) 23,768 8.41 Planted Timber Trees 18,592 6.58 Unusable 17,039 6.03 Temporary Mono-crops (eg maize only) 9,590 3.39 Permanent Mono-crops (eg Sisal only) 8,010 2.84 Temporary Mixed crops (eg maize & beans) 2,585 0.92 Permanent/Pasture mix (eg orange & pasture) 806 0.29 Permanent/Annual mix (eg bananas & maize) 342 0.12 Permanent Mixed crops (eg bananas & coffee) 336 0.12 Rented to others 120 0.04 Total 282,490 100.00 RESULTS Tanzania Agriculture Sample Census - 2007/08 19 0 20,000 40,000 60,000 80,000 100,000 120,000 Rented to others Permanent Mixed crops (eg bananas & coffee) Permanent/Annual mix (eg bananas & maize) Permanent/Pasture mix (eg orange & pasture) Temporary Mixed crops (eg maize & beans) Permanent Mono-crops (eg Sisal only) Temporary Mono-crops (eg maize only) Unusable Planted Timber Trees Uncultivated Usable land (excluding fallow) Fallow Natural Bush Pasture only Land Use Area (ha) Chart 2.12 Land Area by Type of Use 41.06 18.35% 11.85% 8.41% 6.56% 6.03% 3.39% 2.84% 0.92% 0.29% 0.12 0.12% The area under permanent crops was larger (28,088 ha, 36%) than the area under annual crops (12,295.7 ha, 17%). Mixed cropping of annual and permanent crops was not common (1,484 ha, 2%) and has declined compared to 2002/03 agricultural year, (Chart 2.13). Howezer, the area under fallow has increased (33,461 ha, 45%). The results slightly deviate from the 2002/03 agricultural year where permanent mono-crops covered a larger area than temporary mono-crops. Contrary to the 2007/08 agricultural year, permanent mono-crops was 26,602 (three times higher i.e. 8,010 ha in 2002/03) and temporary mono-crop was 12,295 which was an increase of 2,705 ha compared to 9,590 ha in 2002/03. However, one distinctive observation is that, utilization of land in large scale farming did not exhaust all the usable land. About 45 percent (33,467 ha) of the available land was not used despite the fact that it was available for cultivation, (Chart 2.13). RESULTS Tanzania Agriculture Sample Census - 2007/08 20 2.4 Analysis of the Most Important Crops 2.4.1 Cropping Seasons In some areas of Tanzania, there are two types of rainy seasons, the long rainy season (Masika) and the short rainy season (Vuli). The long rainy season normally covers the whole country while the short rainy season is normally found in few regions (Dar es Salaam, Pwani, Morogoro, Tanga, Kilimanjaro, Kagera, Mwanza, Mara, Kigoma, Zanzibar and parts of Mbeya, Arusha and Shinyanga regions) . During the long rainy season, 1,284 large scale farms were planted with annual crops covering an area of 55,535 ha (89.0%) which was slightly higher than 53,009 hectares (80%) cultivated in 2002/03 while during short rainy season, 350 large scale farms (compared to 172 in 20002/03) planted only 6,860 ha of annual crops, (Table 2.7 and Chart 2.14). Table 2.7 Area Planted with Annual Crops by Crop Type and by Season 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Cash crops Fuits & Vegetables 4,270 139 1,320 467 552 111 40,499 173 7,451 3,715 4,363 2,662 Area Planted (Ha) Crops Chart 2.14 Area Planted with Annual Crops by Crop Type Short Rain Season Long Rain Season 2.4.2 Planted Area The total planted area with annual crops on large scale farms was 62,373 hectares (both long and short rainy seasons). The area is an increase of 78 ha compared to 62,295 ha planted in 2002/03 seasons. The area planted with annual crops in the short rainy season was larger than the area planted in the long rainy season in Mwanza, Kagera, Kigoma and Mara.. In other regions, the planted area was greater in the long rainy season compared to the short rainy season. In regions with long rainy season, the largest area planted with annual crops was in Manyara (21,649 ha) followed by Arusha (7,944 ha), Kilimanjaro (6,349 ha), Iringa (4,793 ha) and Types of Crops Short Rain Season Long Rain Season Cereals 4,270 38,088 Roots & Tubers 105 108 Pulses 1,320 5,304 Oil Seeds & Oil Nuts 467 3,707 Cash crops 309 5,523 Fuits & Vegetables 366 2,805 Total 6,838 55,535 Chart 2.15 Area Planted with Annual Crops by Season Long Rainy Season Planted Area (ha), 58,864, 90% Short Rainy Season Planted Area (ha), 6,860, 10% Long Rainy Season Planted Area (ha) Short Rainy Season Planted Area (ha) RESULTS Tanzania Agriculture Sample Census - 2007/08 21 0 20 40 60 80 100 120 140 Planted Area per Farm Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara Zanzibar Regions Chart 2.18 Planted Area per Farm (Ha) by Season and Region Planted per Farm in VULI Planted per Farm in MASIKA Dodoma (4,547 ha). Regions with the least acreage were Kigoma (13 ha) and Dar es Salaam (60 ha) (Chart 2.16). The average area of annual crops planted per farm during the long rainy season was 55 hectares per region which was higher than 32.5 ha planted in 2002/03. However, there were large differences. Manyara had the largest area planted per farm during long rainy season (98 ha) followed by Kilimanjaro (88 ha), Dodoma (80 ha), Mbeya (66 ha), Pwani (64 ha), and Morogoro (35 ha). The smallest area planted per farm during long rainy season was in Kigoma (1 ha), Dar es Salaam (3 ha) and Mwanza (4 ha), (Chart 2.18). The average area planted per farm during short rainy season was 20.3 hectares. The region with the largest area planted per farm was Pwani (120 ha) followed by Mara (52 ha), Dodoma (34 ha) and Arusha (32 ha). The lowest region was Dar es Salaam followed by Mtwara and Kigoma. 2.4.3 Crop Type Cereals were the main annual crops grown in large scale farms in Tanzania, the total area planted with cereals was 42,358 hectares (68% of the total area planted with annuals), followed by pulses with 6,624 hectares ( 11%), cash crops with 5,832 hectares (9.4%) and oil seeds with 4,174 (7%). Fruits andvegetables contributed only 5 percent (3,171 ha), (Chart 2.20). RESULTS Tanzania Agriculture Sample Census - 2007/08 22 In most of the annual crops, there was a difference in the proportion of the crop types grown between seasons. Production during the short rainy season was smaller compared to that of the long rainy season except for roots and tubers which had a larger planted area during the short rainy season, (Chart 2.20). 2.5.1 Cereal production The total production of cereals on large scale farms was 599,988 tonnes. Maize production was higher than any other cereals with a total production of 344,134 tonnes (small holders produced 2,617,115 tonnes) representing 57.4 percent of the total cereal production. This is followed by wheat with 161,855tonnes (23.3%), paddy with 78,367 tonnes (11.3%) and barley with 9,829 tonnes (1. 4%). Large scale production of sorghum, pearl millets and finger millet was almost negligible. Table 2.8: Area Planted and Quantity Harvested on Large Scale Farms and Type of Cereal Crop in 2007/08 From 2002/03 to 2007/08, the increase in production was higher for paddy and maize compared to other cereals. Paddy production increased by 471 percent from 2,028 tonnes harvested in 1994/95 to 11,589 tonnes harvested in 2002/03. This was followed by maize which increased by 14 percent. There was a reduction in production in other cereals, (Chart 2.21). Cereal name Area Planned Actual Area Planted Area Harvest ed (ha) Amount Harvest ed (ton) Amount Stored (ton) Amount Marketed (ton) Maize 32,727 23,483 22,043 344,134 50,884 241,826 Paddy 9,235 5,448 5,302 78,367 9,715 68,082 Sorghum 935 791 775 2,101 98 1,997 Bulrush Millet 82 41 34 2,313 12 2,302 Finger Millet 745 691 691 1,389 808 581 Wheat 13,242 12,597 12,353 161,855 7,658 154,198 Barley 1,733 1,727 1,717 9,829 20 9,827 Cereals 58,686 44,770 42,911 599,979 69,193 478,805 RESULTS Tanzania Agriculture Sample Census - 2007/08 23 0 10 20 30 40 50 60 70 80 0 5,000 10,000 15,000 20,000 25,000 Maize Paddy Sorghum Bulrush Millet Finger Millet Wheat Barley Yield (T/Ha) Area Planted (Ha) Crops Chart 2.21 Area Planted and Yield of Cereal Crops Actual Area Planted Yield (T/Ha) The planted area with maize was much larger than other cereal crops (55.8% of the total planted area of the cereal crops) followed by wheat (22.6% of the area planted with cereals), paddy (15.7%), and barley (3. 0%). Other crops were minor (Sorghum, finger millet and bulrush millet), (Chart 2.22). 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 0 200 400 600 800 1,000 1,200 Iringa Mara Tanga Pwani Morogoro Mwanza Arusha Manyara Ruvuma Kagera Kilimanj … Dodoma Kigoma Zanzibar Mtwara Dar es … Lindi Mbeya Singida Tabora Rukwa Shinya… Percent of Area Planted of Total Land Area Area Planted Regions Chart 2.22 Area Planted with Cereals and Percent of Land with Cereals by Region Total Planted Area with Cereals From 1994/95 to 2002/03, the yield increased for all the cereal crops. The increase was higher for wheat (from 1.0 tonne per hectare in 1994/95 to 2.9 tonnes per hectare in 2002/03) and lower for paddy (from 2.3 tonnes per hectare in 1994/95 to 2.6 tonnes per hectare in 2002/03). Current yields of important cereals are as highlighted in Table 2.9 below. Table 2.9 Area Planted and Yield of Cereal Crops About 54.7 percent of the total area planted with cereals on large scale farms was in three regions, located in the northern part of the country. Manyara had the largest area planted with cereals (16,662 ha, 37.2%), followed by Actual Area Planted (ha) Yield (tons/ha) Maize 20,407 15.7 Paddy 4,361 12.1 Sorghum 693 2.9 Bulrush Millet 41 57.0 Finger Millet 690 2.0 Wheat 12589 12.8 Barley 1,727 5.7 RESULTS Tanzania Agriculture Sample Census - 2007/08 24 Arusha (5,0241 ha, 11.2%) and Kilimanjaro (2,808 ha, 6.3%). About 16.3% was produced in Southern regions of Iringa and Mbeya and central regions Dodoma and Singida accounts for 13.4%. Very small large scale farm production were in remaining regions, (Chart 2.22). Maize The number of large scale farms growing maize during the long rainy season was 451 farms and 117 in the short rainy season. This represented 79 percent of the total crop growing farms during the long rainy season and 21 percent in the short rainy season. The total production of maize during the 2007/08 agricultural year was 344,134 tonnes. The planted area with maize decreased from 36,000 ha in 1994/95 to 30,000 ha in 2002/03 and a further decrease to 23,483 ha in 2007/08. However, production increased by 14.3 percent from 47,666 tonnes to 54,466 over the same period and a further increase to 344,134 tonnes in 2007/08. This has resulted into an increase in the yield of maize from 1.4 tonnes per hectare in 1994/95 to 2.0 tonnes per hectare in 2002/03 and a further increase in yield to 15.0 tonnes per hectare in 2007/08, (Chart 2.23). Manyara had the largest planted area of maize (5,496 ha, 23.4%) followed by Arusha (3,404 ha, 14.5%), Dodoma (2,830 ha, 12.1%) and Kilimanjaro (2,343 ha, 9.9%). The regions with a moderate planted area of maize under large scale farms were Iringa (1,319 ha, 5.6%) Ruvuma (1,231 ha, 5.2%) Pwani (1,365 ha 5.8%), Tanga (1,211 ha, 5.2%), Mara (1,067 ha, 4,5%) and Morogoro (867 ha, 5.1%). However, the highest proportion of land with maize in large scale farms was in Tabora, Shinyanga, Kagera, Kigoma, Pwani and Manyara, (Chart 2.24). RESULTS Tanzania Agriculture Sample Census - 2007/08 25 The planted area per maize growing farm was largest in Dodoma, followed by Pwani, Kilimanjaro, Rukwa, Manyara, Arusha and Dodoma. The smallest area planted with maize per large scale farm was in Kigoma, Mwanza and Dar es Salaam, (Chart 2.24). Paddy The total production of paddy was 78,367 tonnes. Production has increased by 5,845 percent from 11,453 tonnes harvested in 2002/03 to 78,367 tonnes harvested in 2007/08. This was due to an increase in the plated area and husbandry practices. Over this period, the yield of paddy in large scale farms increased from 2.6 tonnes per hectare in 2002/03 to 14.4 tonnes per hectare in 2007/08, (Chart 2.25) Large scale farm production of paddy was mainly concentrated in Mbeya region with 1,883 hectares (34.5% of the total paddy large scale farms) followed by Morogoro (1,740 hectares, 31.9%) and Tanga (653 hectares, 11.9%). The highest proportion of the land with paddy was in Mbeya, Morogoro, Lindi and Tanga, (Chart 2.26). The area planted per paddy growing farm was largest in Mbeya, followed by Kilimanjaro, Morogoro and Lindi. Kagera, Shinyanga, Rukwa and Arusha had the lowest, (Chart 2.26). RESULTS Tanzania Agriculture Sample Census - 2007/08 26 Wheat The number of large scale farms growing wheat during the long rainy season was 67 farms and only one in the short rainy season. This represents 4.6 percent of the total crop growing farms during the long rainy season and 1.2 percent in the short rainy season. The total production of wheat during the 2007/08 agricultural year was 161,855 tonnes, an increase of 420 percent from 30,606 tonnes harvested in 2002/03. Also, the yield has increased from 1.0 tonne per hectare in 1994/95 to 2.9 tonnes per hectare in 2002/03, and further to 13 tonnes per hectare in 2007/08. The crop was mainly produced in the northern part of the country. Manyara had the largest area planted with wheat 10,027 hectares, (79.7%) followed by Arusha with 1,364 hectares (10.8%), Kilimanjaro with 329 hectares (2.6%). However, Manyara had the highest proportion of land with wheat in the country followed by Arusha and Kilimanjaro, (Chart 2.27). RESULTS Tanzania Agriculture Sample Census - 2007/08 27 The area planted per wheat growing farm was largest in Manyara, Rukwa, Mbeya and Arusha. The four regions had an average of more than 150 hectares per farm. The regions with comparatively moderate planted area per farm were Kilimanjaro, Iringa and Singida. The smallest area planted with wheat per farm was in Lindi. The remaining regions did not plant wheat, (Chart 2.7). Barley The number of large scale farms growing barley during the long rainy season was 14 farms and the crop was not grown during the short rainy season. This represents 1.7 percent of the total crop growing farms during both long and short rainy season. The total production of barley during 2007/08 was 9,829 tonnes, an increase of 471 percent from 2,028 tonnes harvested in 1994/95 to 11,589 tonnes harvested in 2002/03 but later on declined to 9,829 tonnes (a decrease of 15%) in 2007/08. The yield has increased from 0.8 tonnes per hectare in 1994/95 to 1.8 tonnes per hectare in 2002/03 and to 5.7 tonnes per hectare in 2007/08, (Chart 2.29). The increase in production might be due to adoption of suitable husbandry practices. Barley was mainly produced in four regions. Iringa had the largest area planted with barley covering 954 hectares (55.2%) followed by Manyara with 372 hectares (21.5%) and Ruvuma 155 hectares (8.9%). Despite that Kilimanjaro region had the smallest area planted with barley (10 hectares, 0.5%), the region had the highest proportion of land planted with barley in the country, (Chart 2.30). RESULTS Tanzania Agriculture Sample Census - 2007/08 28 The areas planted per barley growing farm was greater in Kilimanjaro and Manyara while Arusha and Iringa had smaller planted areas per farm. The remaining seventeen regions had no large scale farms planted with barley, (Chart 2.30). Sorghum The number of large scale farms growing sorghum was 49. The total production of sorghum during 2007/08 was 2,101 tonnes, an increase of 116% over the 2002/03 production (969 tonnes). Production has also increased in the period 2002/03 by 85 percent (from 525 tonnes in 1994/95 to 969 tonnes in 2002/03). The yield has increased from 0.8 tonnes per hectare in 1994/95 to 1.7 tonnes per hectare in 2002/03 and further to 2.7 tonnes per hectare in 2007/08, (Chart 2.31). Although there has been a decline in the planted area, the increase in productivity has resulted into this large increase in the yield. RESULTS Tanzania Agriculture Sample Census - 2007/08 29 In recent years, Manyara has overtaken Morogoro as it had the largest area planted with sorghum covering 487 hectares (61.7%) followed by Mwanza 87 ha (11%), Singida 48 ha (6%), Morogoro 44 ha (5.5%) and Dodoma 42 ha (5.3%). The smallest area planted with sorghum was in Lindi (1.52%), Ruvuma (1%) and Mtwara (0.6%). However, the highest proportions of land areas with sorghum were in Manyara, Mwanza, Singida, Morogoro, Dodoma and Arusha. Regions such as Shinyanga, Tabora and Iringa, which used to plant sorghum, were no longer planting the crop. However, there were no large scale farms planted with sorghum in, Mbeya, Kigoma, Kagera, and Dar es Salaam. The area planted per farm was greater in Manyara (97 hectares per farm). The regions with comparatively moderate planted areas per holding were Arusha, Kilimanjaro, Lindi, Morogoro and Ruvuma. The lowest areas per farm were in Zamzibar, Mtwara and Mara. Other regions planted below 10 hectares per farm while the remaining had no farms planted with sorghum, (Chart 2.32). 2.5.2 Roots and Tuber Crop Production The total production of roots and tubers was 4,287 tonnes (about 14.1 tons/ha). Onion production was the highest than any other roots and tuber crops with a total production of 2,182 tonnes representing 50.8 percent of the total roots and tuber crops production. The second roots crop with highest production was Irish potatoes with 1,110 tonnes (25.8%) followed by sweet potatoes 935 tonnes (21.7%) and cocoyams with 41 tonnes (0.9%). Cassava was never produced in the large scale farms, (Table 2.10 and Chart 2.33). RESULTS Tanzania Agriculture Sample Census - 2007/08 30 Table 2.10: Roots and Tuber Crops Production, Storage and Marketing, 2007/08 Root crop Area Planned Actual Area Planted Area Harvested (ha) Amount Harvested (ton) Amount Stored (ton) Amount Marketed (ton) Sweet potatoes 203 163 155 935 663 204 Irish Potatoes 49 28 28 1,110 48 1,062 Yams 1,225 11 11 19 1 18 Cocoyams 11 11 10 41 10 31 Onions 99 91 91 2,182 60 1,522 Total 1,587 304 295 4,287 782 2,837 The area planted with sweet potatoes was the largest than other roots and tuber crops (163 ha, 52.2% of the roots and tuber planted area) followed by onions with 91 hectares (29%) and Irish potatoes with 28 hectares (8.9%). Sweet potato which was a minor crop in 2002/03, it was one among the major roots and tuber crops produced by large scale farms in the country. The yield was highest in Irish potatoes (39.6 tonnes/ha) followed by onions (24 tonnes/ha) and sweet potato (6 tonnes/ha), (Table 2.10 and Chart 2.33). Irish potatoes Irish potatoes were grown in 13 large scale farms. Between 2002/03 and 2007/08, total production of Irish potatoes has declined by 22.7% from 1,436 tonnes to 1,110 tonnes. However, the yield has increased from 6.2 tonnes per hectare in 1994/95 to 5.7 tonnes per hectare in 2002/03 and to 39.6 tonnes per ha in 2007/08, (Chart 2.34), suggesting that the increase in production was due to the increase in productivity. RESULTS Tanzania Agriculture Sample Census - 2007/08 31 Iringa had the largest area planted with Irish potatoes covering 18 hectares (65.25%) followed by Tanga with 3 hectares (10.64%). Regions with small areas were Kilimanjaro and Manyara, each with 2 hectares (7.09%), Ruvuma, Mbeya and Rukwa, each with 1 hectare (3.55%). The highest proportion of land with Irish potatoes was also in Iringa followed by Kilimanjaro, Ruvuma, Mbeya and Manyara, (Chart 2.34). 2.5.3 Pulse Crop Production The 2007/08, total production of pulses was 16,735 tonnes which was higher by 13% compared to 14,788 tonnes produced in 2002/03. The production of beans was higher than any other pulse crop with a total production of 8,295 tonnes representing 65.2 percent of the total pulse production followed by bambarra nuts with a total production of 1,013 tonnes (7.9%). Other pulses produced in minor quantities include; seed beans 729 tonnes (7.5%), green beans 545 (4.2%), chick peas 461 tonnes (3.6%), green grams 338 tonnes, (1.2%) and cow peas 1,346 tonnes, (10.5%), (Table 2.11 and Chart 2.35). Table: 2. 11: Planted Area with Major Pulses Pulse crop Area Planned (ha) Actual Area Planted (ha) Area Harvested (ha) Amount Harvested (ton) Amount Stored (ton) Amount Marketed (ton) Beans 10,580 5,457 5,111 8,295 3,754 4,694 Cowpeas 564 558 557 1,346 45 1,297 Green grams 3,197 274 274 338 5 334 Pigeon peas 10 9 9 4,008 40,001 7 Chick peas 156 135 134 461 363 98 Bambarra nuts 71 71 17 1,013 1,006 8 Seed Beans 2,250 2,157 2,132 729 1 728 Green Beans 104 118 76 545 148 538 Total 16,,932 8,779 8,310 16,735 45,323 7,704 RESULTS Tanzania Agriculture Sample Census - 2007/08 32 The total area planted with pulses was 8,779 hectares (14% of the total large scale farm area (62,373 ha) planted with annual crops). Of the total area planted with pulses, beans occupied 5,457 hectares (62.2%), seed beans (2,157 ha, 24.6%), chick peas (135 ha, 1.5%), green grams (274 ha, 3.1%), cow peas (558 ha, 6.3%), and bambarra nuts (71 ha, 0.8%), (Figure 2.35). Beans The number of large scale farms growing beans during the long rainy season was 176 and 27 farms during the short rainy season. This represents 13.7percent of the total crop growing farms in the long rainy season and 8 percent in the short rainy season. The total production of beans during the 2003/03 agricultural year was 8,724 tonnes and during the 2007/08 was 8,295 tonnes, a decline of approximately 5 percent. Time series data on beans shows an increase in production by 17.2 percent from 7,443 tonnes in 1994/95 to 8,724 tonnes in 2002/03 and a decline to 8,295 tonnes in 2007/08, (Chart 2.45). However, although the productivity remained almost constant at 1.1 tonnes per hectare in 1994/95 to 1.0 tonnes per hectare in 2002/03, it increased to 1.5 tonnes/ha in 2007/08, (Chart 2.36). Regions in the northern part of the country had a larger areas planted with beans than in other parts of the country. Arusha region had the largest planted area of beans (2,435 ha, 44.6%) followed by and Kilimanjaro (800 ha, 14.6%), Mara (798 ha, 14.6%) and Manyara (765 ha, 14%). Ruvuma, Mtwara, Iringa, Tanga, and Rukwa had comparatively small areas planted with beans. The highest proportion of land with beans was also in Arusha followed by Ruvuma, Kilimanjaro, Manyara, RESULTS Tanzania Agriculture Sample Census - 2007/08 33 Mtwara, Rukwa and Manyara. However, were no large scale farms which grew beans in Pwani, Dar es Salaam, Lindi, Mwanza Mbeya, Kagera and Shinyanga regions, (Chart 2.45). Arusha and Manyara regions had the largest areas of land planted with beans per farm followed by Tabora and Kilimanjaro with moderately large areas per holding while Singida, Ruvuma and Morogoro had the smallest areas planted with beans per farm, (Chart 2.37). 2.5.4 Oil Seeds Production Main oil seed crops cultivated by large scale farms include sunflower, simsim and groundnuts. The total oil seeds production was 26,868 tonnes. The production of groundnuts was higher (14,287 tonnes 53.2%) than any other oil seed crop in the large scale farms, followed by sunflower with a total production of 12,507 tonnes (46.5%), simsim with 71 tonnes (0.3%), (Table 2.12). RESULTS Tanzania Agriculture Sample Census - 2007/08 34 Table 2.12: Oil Seed Crops: Planted Area, Harvested and Marketing, 2007/08 Area Planned (ha) Actual Area Planted (ha) Area Harvested (ha) Amount Harvested (ton) Amount Stored (ton) Amount Marketed (ton) Sunflower 5,331 2,816 2,787 12,507 2,345 10,173 Simsim 1,133 428 410 74 33 41 Groundnuts 965 931 925 14,287 3,274 11,024 Total 7,429 4,175 4,122 26,868 5,652 21,238 The total area planted with oil seed crops was 4,175 hectares (6.7% of the total area planted with annual crops). Of the total area planted with oil seed crops, sunflower occupied the largest area of 2,816 hectares (67.4%) followed by groundnuts (22.3%), and simsim (10.3%), (Chart 2.38). The short rainy season was much less important than the long rainy season for oil seeds production. The total area planted with oil seeds in short rainy season was 467 hectares or 11.2 percent of the total area planted with oil seeds during 2007/08. Groundnuts The total production of groundnuts during the 2007/08 agricultural year was 14,287 tonnes. Time series data show an increased production by 946 percent from 150 tonnes in 1994/95 to 1,569 tonnes in 2002/03 and to 14,287 tonnes in 2007/08, (Chart 2.39). RESULTS Tanzania Agriculture Sample Census - 2007/08 35 The area planted with groundnuts has also increased from 209 hectares in 1994/95 to 445 hectares in 2002/03 and to 931 ha in 2007/08. The yield has increased from 0.8 tonnes per hectare in 1994/95 to 3.6 tonnes per hectare in 2002/03 and to 15.4 tonnes/ha in 2007/08. This implies that the increase in production was caused by the increase in the planted area as well as the increase in productivity. Mtwara had the largest planted area of groundnuts (792 ha, 85.1% of the oil seeds planted area), followed by Dodoma (29 ha, 3.0%), Mbeya (27 ha, 2.9%). The highest proportion of land with groundnuts was in Mtwara followed by Kilimanjaro, Arusha, Manyara, Dodoma, Rukwa, and Ruvuma. The lowest proportion of land planted with groundnuts was in Morogoro, Tabora, Kigoma, Singida and Iringa, (Chart 2.40). RESULTS Tanzania Agriculture Sample Census - 2007/08 36 The area planted per groundnut growing farm was greater in Mtwara followed by Kilimanjaro. The lowest areas planted with groundnuts per holding were in Dodoma, Tanga, Singida, Morogoro, Rukwa and Kigoma, (Chart 2.40). 2.6 Perennial Crops Perennial or permanent crops refer to crops that normally take over a year to mature and once matured can be harvested for a number of years. For most of the crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas, the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was therefore treated as an annual crop. Bananas normally take less than a year to mature and produce a harvest but the resulting suckers survive for more than one year. Bananas are therefore treated as permanent crops in the census. In this report, the results are presented for the most important permanent crops in terms of production, yield and area planted. The number of large scale farms growing permanent crops was 704 or 70% of all the large scale farms in Tanzania. About 8.6% of all the land under large scale farms was under permanent crops while the remaining (91.4 %) was under annual crops, (Chart 2.41). Perennial crops of significant value are presented in Table 2.13 and Chart 2.42. The total area planted with perennial crops was 96,117 ha. Sisal occupied the largest area 34,696 ha (36.1%) followed by sugarcane (17,804 ha; 18.5%), tea (11,213 ha, 11.7%), cashewnut (9,463 ha; 9.8%), coconut (6,111 ha; 6.4%), coffee (3,836 ha; 4.0%) and banana (1,449 ha; 1.5%). These crops occupied about 96% of the total area under permanent crops. Other crops which were cultivated on the remaining 4% include rubber, palm oil, mandarine, wattle, pawpaw, avocado, guava, shelisheli, pigeon peas, cloves, pears, grapes, mangoes, cardamom, and citrus, (Chart 2.42 and Table 2.13). RESULTS Tanzania Agriculture Sample Census - 2007/08 37 Table 2.13: Number, Acreage and Percentage of Large Scale Farms, Perennial Crops, 2007/08 5,795 34,696 17,804 11,213 892 9,463 840 6,111 692 5861,071 3,836 507 244 19 4571,449163 12 25 232 5 1 5 0 5000 10000 15000 20000 25000 30000 35000 40000 Cacao Sisal Sugarcane Tea Rubber Cashewnut Palm oil Coconut Mandarine Wattle Pawpaw Coffee Avocado Guaves Mashelisheli Pigeon pea Banana Clove Peasi Grapes Mangoes Cardamon Mifyoksi Lemon Hectares Crops Chart 2.42: Area under perenial crops in Tanzania 2.7 Cash Crop Production Traditionally, the major cash crops grown in large scale farms in Tanzania are tobacco, pyrethrum, coffee, sisal, tea, cloves, sugarcane and cotton. In recent years, many other crops have surfaced as major sources of income for the large scale farmers hence, emergence of large scale production. Crops such as flowers, fruits, vegetables, and pulses have become important cash crops. During 2007/08 agricultural year, an area of 4,176 hectares was planted with cash crops out of which coffee was the most important followed by tea and tobacco, (Chart 2.43). In terms of area under production; coffee, followed by banana, coconut, oranges and mangoes were produced by more than 80 large scale farms. Other crops such as cassava, cashewnuts, sugarcane and sisal had more than 40 producers in the country, (Chart 2.43). Crops with largest average area per farm (i.e. above 125 ha) were cocoa, sisal, sugarcane, tea, rubber and cashewnut. 2.7.1 Tobacco During the 2007/08 agricultural year, 13 large scale tobacco farms (7 in Iringa and 6 in Tabora) planted tobacco covering an area of 751 hectares. Amount of harvested was 36,353 tonnes with an average yield of 48.4 tonnes per hectare. Crop No of farms Area (ha) Percentage Area Cocoa 4 5,795 6.0 Sisal 42 34,696 36.1 Sugarcane 42 17,804 18.5 Tea 35 11,213 11.7 Cashewnut 76 9,463 9.8 Coconut 87 6,111 6.4 Coffee 95 3,836 4.0 Banana 91 1,449 1.5 Others 232 5,750 6.0 Total 704 96,117 100.0 RESULTS Tanzania Agriculture Sample Census - 2007/08 38 Chart 2.44 Percentage of Tobacco Planted Area and Proportion of Land by Region 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 Iringa Tabora Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Mbeya Singida Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara Zanzibar Region Percentage of Planted area 0.00 2.00 4.00 6.00 8.00 10.00 12.00 Proportion of Land Percent of Total area 2.7.2 Sisal Sisal is a crop which occupied the largest planted area (34,696 ha,) representing 36.1% of the total area of permanent crops. Tanga with a cultivated area of 28,080 ha was the largest area in Tanzania representing 81% of the total area under sisal. The remaining 19% was cultivated in Morogoro (11%), Kilimanjaro (4.9%), Pwani (2.7%) and Manyara (0.3%). 2.7.3 Coffee The total production of coffee by large scale farms in 2002/03 agricultural year was 19,084 tonnes which represented 23.8 percent of the total coffee produced in the country. According to 2007/08 agricultural census, coffee was grown on 95 large scale farms equivalent to 13.5 percent of the total farms growing major permanent crops. It was the third most important permanent crop with 3,836 hectares or 4% of the total planted area with permanent crops. The production of coffee under large scale farming has increased from 2,105 tonnes in 1994/95 to 19,084 tonnes in 2002/03 and to 33,279 tonnes in 2007/08. In the same sequence, the yield has increased from 0.3 tonnes/ha in 1994/95 to 1.5 tonnes/ha in 2002/03 and to 7.16 tonnes per hectare in 2007/08. RESULTS Tanzania Agriculture Sample Census - 2007/08 39 2.7.4 Tea The total production of tea was 74,613 tonnes grown on 35 farms equivalent to 5 percent of the total large scale permanent crop growing farms. The planted area was 11,213 hectares or 11.7 percent of the total area planted with permanent crops. Therefore the average area planted with tea was 320.4 hectares per farm and the average yield was 6.7 tonnes per hectare. Production has dropped by 32 percent from 50,242 in 1994/95 to 33,978 tonnes in 2002/03. They yield has also dropped from 4.2 tonnes per hectare in 1994/95 to 3.3 tonnes per hectare in 2002/03 but has increased to 6.7 tonnes per hectare in 2007/08. 2.7.5 Sugarcane There were 42 large scale farms covering an area of 17,804 hectares with a total production of 218,598 tonnes and an average yield of 12.3 tonnes per hectare. Regional wise, Morogoro had 9,486 hectares and Kagera had 7,672 hectares which together, accounted for 96.4% of the total area cultivated with sugarcane, (Chart 2.48). 2.7.6 Cashewnuts The total production of cashewnuts has increased from 935 tonnes in 2002/03 to 28,831 tonnes in 2007/08 representing an increase of 2,983% over the five year period. The crop was grown on 76 farms covering an area of 9,463 hectares. Hence, the average area planted with cashewnuts per farm was 124.5 hectares, an increase of 23.4 ha from 101.4 hectares per farm in 2002/03. The average yield was 3.05 tonnes per hectare which was a tremendous increase compared to 0.1 tonnes per hectare in 2002/03. RESULTS Tanzania Agriculture Sample Census - 2007/08 40 The production was mostly in dryer areas in five coastal regions (Lindi, Pwani, Tanga, Dar es Salaam and Mtwara) and the southern region of Ruvuma. During the 2007/08 agricultural year, Pwani had the largest planted area (7,839 ha, 82.84%) followed by Lindi (676 ha, 7.14%), Mtwara (596 ha, 6.3%), Ruvuma (190 ha, 2.01%), Tanga (146 ha, 1.54%) and Morogoro (5 ha, 0.05%). The rest of the regions had very small areas (a total of 11 ha, 0.12%) of the planted area with cashewnuts, (Chart 2.49). 2.7.7 Coconuts The total production of coconuts was 15,559 tonnes an increase of 35% as compared to 11,524 tonnes produced in 2002/03. Harvested area has also increased from 5,181 hectares in 2002/03 to 6,111 hectares, an increase of 630 hectares (18%). The yield has also increased from 2.2 tonnes per hectare in 2002/03 to 2.5 tonnes per hectare. Coconuts were grown on 87 large scale farms with an average of 70 hectares per farm. Production was mostly concentrated in thee east coast part of the country with Pwani region having the highest proportion of the area planted with coconuts (4,939 ha, 80.8% of the total area planted with coconut) followed by Tanga (630 ha, 10.3%), Lindi (458 ha, 7.5%), North Pemba (46 ha, 0.8%), Morogoro (19 ha, 0.3%) and Urban west (12 ha, 0.2%). The remaining regions had a total of 7 hectares equivalent to 0.11 percent of the total area planted with coconuts, (Chart 2.50). 2.7.8 Bananas The total production of bananas was 121,639 tonnes which was an increase of 105,833 tonnes comapred to 15,817 tonnes produced in 2002/03. The crop was grown on 91 farms representing 12.8 percent of the total permanent crop growing farms. It was planted on 1,449 hecatres, an RESULTS Tanzania Agriculture Sample Census - 2007/08 41 increase of 448 ha from 1,001 hectares reported in 2002/03. The average area planted with bananas was 16 hectares per farm, an increase of 9 hectares compared to 7 hectares per farm in 2002/03. The main banana producing regions were those with high rainfall such as Ruvuma which had the largest area planted with banana (202 ha, 48.3%) followed by Morogoro (79 ha, 18.9%), Arusha (69 ha; 16.5%) and to some extent, Kilimanjaro (22 ha, 5.3%), Kagera (13 ha, 3.1%), Tanga (8 ha, 1.9%) and Mbeya (7 ha, 1.6%). Other regions having a planted area under 5 hectares were Pwani, Dar es Salaam, Mtwara, Kigoma, Rukwa, Manyara and Mara, (Chart 2.51). 2.8 Irrigation Water is the limiting factor to crop production in the majority of the areas in Tanzania and without water; most other cultural practices applied to a crop will not result into a significant increase in yield. Unlike in the 2002/03 census, the 2007/08 census collected less information on irrigation status in the country was collected for large scale farms. Out of 97,347 hectares under cash crops only, 18,008 hectares or 19 percent was under irrigation and the remaining 81 percent was cultivated under rainfed, (Chart 2.52). Sugarcane had the largest area under irrigation (11,978 ha) followed by coffee (2,487 ha), tea (2,309 ha), mandarin (690 ha) and coconuts (424 ha). The smallest areas under irrigation were in bananas and mangoes. RESULTS Tanzania Agriculture Sample Census - 2007/08 42 For annual crops, irrigation was done during short (vuli) and long (masika) rainy seasons. Total area irrigated both in long and short rainy seasons was 10,320 hectares of which, 86.3% of the irrigated area (8,878 ha) was irrigated during the long rainy season and the remaining 13.7% (1,442 ha) during the dry season. In all the seasons, more than 59% (6,245 ha) of the irrigated land was under paddy cultivation followed by maize 25.1%, beans/jute 2.4%, and flowers 1.1%. All other crops including vegetables accounted for the remaining 6.5% (678 ha) of the total area under irrigation. 2.9 Crop Marketing The number of farms that reported selling crops was 871 or 89.4% of the total number of crop growing farms. Farms reported number of problems associated with crop marketing as discussed in section 2.9.1 below. 2.9.1 Main Marketing Problems About 871 large scale farms indicated that they sold their crops. The majority, 523 (60%) complained that the prices were low. Other reasons include high transport cost (6.4%), no buyers (2.0%), lack of market information (1.4%), Government over regulations (1%), farmers’ association problems (0.23%) and lack of market information. Long distance from farms to market places was another problem. Other marketing problems were minor and represented less than 1.0 percent of the total reported problems, (Table 2.14 and Chart 2.54). Table 2.14 Percentage of Farms Reporting Marketing Problems by Problem Type Inter-regional comparison shows some variations. Problem of low prices was mostly reported by farmers in Tanga (17%) followed by North Unguja (13%), Mtwara (8%), Morogoro (7.1%) Iringa (6.5%) and Pwani (5.7%). Low prices were not cited as a problem in Singida, and Mwanza. Reason Number Percent Prices too low 523 60.05 No transport 4 0.46 Transport cost too high 56 6.43 No buyers 18 2.07 Farmer association 2 0.23 Cooperative problems 3 0.34 Govt regulatory body problems 9 1.03 Lack of marketing information 12 1.38 Not applicable 244 28.01 Total 871 100 RESULTS Tanzania Agriculture Sample Census - 2007/08 43 2.10 Use of credit for Agriculture Purpose 2.10.1 Access to credit facilities Very few large scale farms borrowed money from credit organizations. Out of 1,006 farms, only 64 farms (6%) borrowed for various farm uses whereas 94 percent did not borrow at all, (Chart 2.56). Chart 2.57 shows the percentage distribution of farms that borrowed by region. The census results show that Iringa had the highest proportion of farms which borrowed money from credit organizations (17.1% of the large scale farms in the region) followed by Mtwara (15.8%) and Lindi (14.3% each), Mbeya (13.2%) and Tabora (9.3%). Tanga had the largest number of farms (113) but only 3 farms (2.7%) borrowed money. A total of 83 large scale farms located in Kilimanjaro, Kigoma, Rukwa, and Shinyanga regions did not borrow money for agricultural purposes, (Chart 2.57). 0 20 40 60 80 100 120 Number of Farms Regions Chart 2.57 Number of Farms That Received Credit by Region Not Received Received The results show that, most (95%) of the farms which borrowed money from the private sector. The private sectors include; the private registered companies, private non-registered companies and other individuals. 2.10.2 Reasons for Not Using Credit Facilities Out of the 975 farms that didn’t use credit, 346 (35%) responded that they did not need to borrow money; followed by 206 farms (21%) claiming that the procedures were difficult and bureaucratic and 16% responded that credit was not available. In addition, 108 farms (11%) indicated high RESULTS Tanzania Agriculture Sample Census - 2007/08 44 interest rates, 63 (6%) indicated other reasons while (1%) claimed that it took too long time between application and receiving credit for the intended activities, (Table 2.15 and Chart 2.58). Table 2.15 Percentage Distribution of Farms that Did Not Borrow and Reasons for Not Borrowing Response Number Percent Not needed 346 35 Not available 152 16 Did not want to go into credit 87 9 Interest rate/cost too high 108 11 Credit grated too late 13 1 Difficult procedures 206 21 Others 63 6 Total 975 100 Analysis by regions shows that all the farms (100%) in North Pemba and South Pemba did not need credit. Other regions with large proportion include; Tabora (90%), Kilimanjaro (57%), Arusha (53%). The smallest percentage, below the national average (35%) who indicated to dislike credit were those farming in Lindi (8%), followed by Kagera (14%), Mtwara (16%), Tanga and Mwanza each with (21%), Dodoma (22%). Problem of long procedures was reported by farmers in Lindi (50%), Singida ((48%), Tanga (38%), Mtwara (37%), Kagera (34%). High interest rate was a major problem in Manyara (31%) while limited credit availability was reported in Shinyanga (50%) followed by North Unguja (41%), Mwanza (40%), and Rukwa (38%), (Chart 2.59). 2.10.3 Credit Sources by Type of Farm Activity A total of 64 farms have borrowed money from credit facilities. Farms involved in crops only had the largest number of farms which borrowed money (43 farms, 57%) followed by crops and livestock (23 farms, 31%) and livestock only (9 farms, 12%). 2.10.4 Farms which Borrowed Money and Type of Credit Facilities The Large Scale Farms questionnaire solicited information on the sources of credit targeting at financing farm labour and for purchasing seeds, fertilizers, agro-chemicals, livestock feeds, farms RESULTS Tanzania Agriculture Sample Census - 2007/08 45 fences, farm tools, stores, machinery, setting irrigation structures and other uses. Primary source for the majority of the holdings which received credits were for financing labour (42) followed by purchase of agro-chemicals (37), fertilizers (35) seeds (30) and tools (12). Other uses with less than 10 holdings include livestock feeds, livestock purchases, fences, stores, and irrigation structures, (Chart 2.60). Main source of financing the above mentioned undertakings was companies’ own farms which financed the use of fertilizers by 100% and other activities by 90%. Very few holdings (less than 10%) obtained credit from commercial banks. 0 10 20 30 40 50 Number of Holdings Activities Chart 2.60 Number of Holdings Receiving Credit by Sorce of Credit and Type of Activity (Source A) Company Owning Farm Commercial Bank Chart 2.61 shows number of holdings which obtained credit from second source (B). Although only one holding responded, the results show that commercial banks were the most important source for financing all the farm activities except for purchasing fertilizers and supplementary uses, (Chart 2.61). RESULTS Tanzania Agriculture Sample Census - 2007/08 46 0 0.5 1 1.5 2 Number of Holdings Activities Chart 2.61: Number of Holdings Receiving Credit by Sorce of Credit and Type of Activity (Source B) Company Owning Farm Commercial Bank 2.11 Sources of Inputs for Agricultural Holdings Inputs used by large scale farms are grouped into six main categories namely; seed planting materials, inorganic fertilizers, organic fertilizers, herbicides, fungicides, and pesticide. During the 2007/08, private sellers and NGOs were the main sources of inputs to large scale holdings accounting for 42% followed by local purchases (15%), imported (9%), and Government (2%). Import was the main source for input seed (15%), Pesticide (12%) and fertilizers (11%). Local purchase was important for seed/planting materials, pesticides, and inorganic fertilizers. Very few farmers depended on local purchases to get inorganic fertilizers. Private sellers/NGOs were a major source for seeds (21%) followed by pesticides (17%) and herbicides (12%). About 36% of the organic fertilizers were produced in the farms and only 2% of the holdings obtained their inputs from the government. Main inputs obtained from the government include; seeds (40%), organic fertilizers, herbicides and pesticides (20% each), (Chart 2.63). RESULTS Tanzania Agriculture Sample Census - 2007/08 47 Cost of various farm operations is presented in chart 2.64. The highest cost (above 100,000 Tsh/ha) was for harvesting and threshing followed by labour cost, land preparation, transportation, and herbicides. Organic fertilizers and herbicides recorded the lowest cost, (Chart 2.64) RESULTS Tanzania Agriculture Sample Census - 2007/08 48 3 LIVESTOCK AND POULTRY RESULTS 3.1 Livestock Production and Growth This section analyses livestock in relation to population, growth, husbandry and service provision at national and regional levels. Some references are made to the contribution of small scale farms. The reference date for livestock population is 1st October 2008. All the other variables collected are for a period of a year prior to the reference date. Population and growth rate trends are presented for the Mainland only due to lack of comparative historical data for Zanzibar. However, the contribution of Zanzibar to the total Tanzania livestock population was relatively small and the trend would not vary significantly with the incorporation of Zanzibar if they were available. Hence, it may be assumed that the trends presented for the Mainland are the same as the national trends. Out of 1,006 large scale farms on the Mainland, 475 (47.2%) reared livestock as compared to 1,659,160 smallholders on Tanzania Mainland. Most of the large scale farms (28%) were not fully dependant on livestock production as they also grew crops. Table 3.1 and Chart 3.1 present the importance of the different types of livestock that are kept by large scale farms on the Mainland. In relation to population, chicken are the most important type of livestock, followed by cattle, goats, sheep and pigs. Table 3.1 Heads of Livestock by Type Type Number Percent Cattle 120,014 18 Chicken 494,866 75 Goat 24,193 4 Sheep 14,609 2 Pigs 8,316 1 Total 661,998 100 However, in terms of number of farm holdings keeping livestock, cattle were the most important accounting for 44%, followed by goats (30%), sheep (17%%) and pigs (9%), (Chart 3.2). Table 3.2 gives the livestock population for different types of livestock on large scale farms. Ducks, turkeys, rabbits, donkeys and horses were of relatively minor importance and the remaining analysis in this RESULTS Tanzania Agriculture Sample Census - 2007/08 49 section concentrates more on the major livestock types (cattle, goats, sheep, pigs and chicken). Large scale farms kept a larger number of livestock per holding compared to smallholders. Table 3.2: Comparative Livestock Number and Unit Table 3.2 and Chart 3.3 compare the number of livestock with livestock Unit (LSU). Livestock Unit is used to estimate total quantity of livestock based on a cow having an LSU of 1, a goat or a sheep 1/5 LSU, a pig 1/3 LSU and a chicken 1/20 LSU. In terms of total livestock (i.e. cows; goats; sheep and pigs), there were 661,998 heads equivalent to 155,290 LSU. Based onthe LSU principle, cattle were more important than other livestock with 120,014 LSU and marginally followed by chicken with LSU 24,743. Pigs had the lowest LSU (2,772). 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Cattle Chicken Goat Sheep Pigs Total Number Livestock Chart 3.3: Comparison of Livestock Number and Unit Number of Livestock Livestock Unit Regional wise, most of the livestock were produced by large scale farms in Pwani region followed by Iringa, Dar es Salaam, Kagera, Kilimanjaro and Mwanza regions. However, in terms of LSU, Kagera had more livestock followed by Pwani, Dar es Salaam and Morogoro due to the higher proportion of cattle than small ruminants. Kigoma, Singida, Tabora, Lindi and Mbeya had the smallest numbers of livestock as well as livestock units, (Chart 3.4). Type Number of Livestock Factor Livestock Unit Cattle 120,014 1 120,014 Chicken 494,866 0.05 24,743 Goat 24,193 0.2 4,839 Sheep 14,609 0.2 2,922 Pigs 8,316 0.2 1,663 Total 661,998 1.65 154,181 RESULTS Tanzania Agriculture Sample Census - 2007/08 50 0 50,000 100,000 150,000 200,000 250,000 Number Region Chart 3.4: Comparison of Livestock Number and LSU by Region Total Livestock Livestock Unit 3.1.1 Cattle Population The total number of cattle raised on large scale farms on Tanzania Mainland was 119,649 and Zanzibar was 365. A further 21,125,251 were raised by smallholders giving a total Mainland number of 21,245,265 heads. These cattle were raised by 527 large scale farms and 1,698,580 smallholder farmers resulting into an average of 228 heas per large scale farm and 13 heads per smallholder household. Cattle were the most important type of livestock on large scale farms on the Mainland. If poultry was not considered, approximately 72 percent of the major livestock kept by large scale farms were cattle and they were kept by 52 percent of the total large scale farms. Female reproductive cattle (cows and heifers) represent 77 percent of the total number of adult cattle. The results show that, 39 percent of the cattle rearing farms kept above 100 heads of cattle, an average of 527 heads per farm, 19 percent kept less than 20 heads at an average of 11 heads per farm, 17 percent of the farms kept between 20 and 39 heads at an average of 28 heads per farm, 12 percent kept between 40 and 59 heads an average of 50 heads per farm. About 7 percent of the farms kept between 60 and 79 heads at an average of 69 heads per farm and the remaining 6 percent kept between 80 and 99 heads at an average of 89 heads per farm. Cattle production was mainly concentrated in Kagera region having the highest population (23%) followed by Iringa (9%) and Morogoro (8%). Singida, Tabora, Kigoma and the rest of the regions in Zanzibar had the lowest number of cattle which accounted for less than one percent. On the other hand, the highest population of cattle per farm was in Rukwa (1028 heads per farm) followed by Kagera (883 heads per farm); Dodoma (583 heads per farm), Pwani (267 heads per farm) and Mwanza (225 heads per farm). The lowest number of cattle per farm was in Singida (35 heads per RESULTS Tanzania Agriculture Sample Census - 2007/08 51 farm), North Unguja (27 heads per farm) and the rest of the regions in Zanzibar had less than 20 cattle per farm, (Chart 3.5). The total cattle population on large scale farms has decreased by 5 percent from 116,280 in 1994/95 to 110,594 in 2002/03 and has increased to 120,014 in 2007/08, an increase of 8.5% between 2002/03 and 2007/08, (Chart 3.6). Indigenous cattle population When large scale farms are compared with small scale holders, the indigenous cattle were the minority. The census results show that there were 52,540 heads of indigenous cattle in 2007/08, which represents 43.8 percent of the total cattle population. The average growth rate of indigenous cattle for the period 2002/03 to 2007/08 was 0.054 percent per year. Improved cattle population The number of improved cattle in large scale farms was 67,460 heads representing 56.2 percent of the total cattle population in large scale farms. There were more improved beef cattle (43,047, 64%) than the dairy cattle (24,413, 36%). The largest number of beef cattle were in Kagera (33.5%) followed by Chart 3.5: Cattle Population by Region 0 5,000 10,000 15,000 20,000 25,000 30,000 Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara North Unguja South Unguja Urban West North Pemba South Pemba Region Number 0 200 400 600 800 1000 1200 Head per Farm Cattle Population Head per Farm 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 1994/1995 2002/2003 2007/2008 116,280 110,594 120,014 33,284 49,840 52,540 Cattle Number Agriculture Year Chart 3.6 Cattle Population by Region Total Cattle Indigenous Cattle 0 10,000 20,000 30,000 40,000 50,000 60,000 1994/1995 2002/2003 2007/2008 24,645 25,981 24,413 58,351 34,773 43,047 Cattle Number Year Chart 3.7 Improved Cattle Population Trend Improved Dairy Improved Beef -1.21 4.76 -2.00 -1.00 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Improved Diary Improved Beef Chart 3.8: Improved Cattle Population Growth RESULTS Tanzania Agriculture Sample Census - 2007/08 52 Chart 3.9: Goat Population by Region 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Iringa Morogoro Pwani Dodoma Arusha Tanga Kilimanjaro Kagera Mwanza Manyara Ruvuma Mara Lindi Singida Dar es salaam Mtwara Rukwa Tabora Mbeya Kigoma Shinyanga North Unguja North Pemba South Unguja Urban West South Pemba Region Number 0 20 40 60 80 100 120 140 160 180 Head per Farm Number Head per Farm Dodoma (15%) and Pwani (10.6%). The smallest numbers were in Kigoma, Mbeya, Rukwa and Lindi which together accounted for less than one percent. There were no improved beef cattle farms in Shinyanga and in Zanzibar. The largest number of improved dairy cattle was in Iringa (21.2%) followed by Morogoro and Pwani, each with 13.5%, (Charts 3.7). However, the number of improved cattle has increased between 1994/95 and 2002/03 and has decreased by 6% between 2002/03 and 2007/08. The growth rate for improved beef cattle for the period 2002/03 to 2007/08 was 4.8 percent per year. However, the growth rate for improved dairy cattle declined slightly from 25,981 in 2002/03 to 24,413 in 2007/08 (-1.21% growth rate per year) (Chart 3.8). 3.1.2 Goat Population The total number of goats was 24,193 kept by 359 large scale farms. Regional wise, Iringa, Morogoro, Pwani and Manyara regions, each had about 39 percent of the large scale farms keeping goats, followed by Ruvuma region with 7%, Singida and Mwanza, each with 6%, Kagera with 5% and Lindi with 2%. In 1994/95 agricultural year, the number of goats was 12,343 reared on 296 large scale farms. The average number of goats has therefore increased from 42 goats per farm in 1994/95 to 56 goats per farm in 2002/03. The rate of growth after eight years was an annual rate of about 7.9%. The highest goat producing regions were Iringa (3,400 goats), Morogoro (3,292 goats), Pwani (2,095 goats) and Dodoma (2,028 goats) together accounted for 44.7 percent of the total goat population in large scale farms. The lowest large scale goat farms were in Shinyanga which kept 71 goats and all the regions in Zanzibar of which together, accounted for 103 heads, or 0.43%. The largest number of goats per farm was in Dodoma (169 goats) followed by Kilimanjaro (125 goats), Arusha (120 goats). However, the goat population trend kept on declining from Northern/Eastern towards the Central/Lake Zone of Tanzania Mainland. RESULTS Tanzania Agriculture Sample Census - 2007/08 53 Chart 3.10: Sheep Population by Region 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 Iringa Morogoro Kilimanjaro Pwani Arusha Tanga Manyara Mara Dodoma Rukwa Mwanza Dar es salaam Kagera Ruvuma Lindi Mtwara Singida Zanzibar Mbeya Tabora Shinyanga Kigoma Region Number 0 50 100 150 200 250 Head per Farm Number Head per Farm Chart 3.12: Sheep Population by Region 0 250 500 750 1,000 1,250 1,500 Ruvuma Mbeya Iringa Morogoro Dar es salaam Kilimanjaro Pwani Mwanza Mtwara Mara Rukwa Arusha Dodoma Tabora Lindi Singida Manyara Kagera Tanga Region Number 0 50 100 150 200 Head per Farm Number Head per Farm 3.1.3 Sheep population The number of sheep kept by large scale farms was 14,609 of which 14,550 (99%) were in the Mainland and 59 (1%) were in Zanzibar. They were reared in 200 farms. The majority of the farms (39%) kept less than 20 sheep per farm which accounted for 5 percent of the total sheep population. About 19 percent of the farms kept sheep between 20 and 39 sheep per farm and 20 percent of the total farms rearing sheep kept more than 100 sheep per farm which accounts for 71 percent of the total number of sheep. Sheep production in large scale farms was concentrated in the North Eastern regions and Pwani region and declines steadily towards the south. Iringa was the largest sheep producing region (4,154 heads) followed by Morogoro (1,973 heads). The regions with smallest sheep production were Kigoma with 5 farms, Shinyanga (12), Tabora (34), Mbeya (53) and Zanzibar (59). Kilimanjaro had the highest number of sheep per farm (196) followed by Rukwa (195), Arusha (152), and Iringa (115). The lowest number of sheep per farm was Singida (10), followed by Shinyanga (12) Mtwara (15), and Ruvuma (22) , (Chart 3.10). Unlike the improved dairy cattle, sheep population has been increasing steadily. Inter-censual data show that, sheep population in large scale farming has increased from 8,071 in 1994/95 to 12,236 in 2002/03 and further to 14,609 in 2007/08 (Chart 3.11). 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 1994/95 2002/03 2007/08 8,071 12,236 14,609 Sheep Number Year Chart 3.11: Sheep Population Trend RESULTS Tanzania Agriculture Sample Census - 2007/08 54 3.1.4 Pig Population The number of pigs kept by large scale farms was 8,316. They were reared in 108 farms. The pig population in large scale farms increased dramatically from 4,755 in 1994/95 to 10,186 in 2002/03 (114% increase over the period) with a growth rate of 10 percent per year but decline to 8,316 in 2007/08 (in small holdings the population increased over the same period by 124% at the growth rate of 11% per year). The highest number of pigs was in Ruvuma (14.5%), followed by Mbeya (13.6%), Iringa (12.5%) and Morogoro (10%). The lowest number was in Tanga (0.2%) and Kagera (0.5%). There were no pigs in large scale farms in Kigoma, Shinyanga and Zanzibar. However, the highest number of pigs per farm was in Mbeya (186) and Dar es Salaam (160), (Chart 3.12). Growth trend shows that there was a slight decrease in 2007/08 to 8,316 pigs from 10,054 pigs in 2002/03, (Chart 3.13). 3.1.5 Chicken population The total number of chicken kept by large scale farms were 494,866 of which 24,971 (5%) were indigenous, 235,923 (47.7%) were layers and 233,972 (47.3%) was broilers. Over the period 1994/95 to 2002/03, chicken population on large scale farms has increased from 245,249 in 1994/95 to 456,638 in 2002/03 and increased to 494,866 chickens in 2007/08 agricultural year. The largest number of chicken was concentrated in regions having large towns/cities or high human population. Of the total number of chicken kept on large scale farms, 82% percent were in Pwani, Iringa and Dar es Salaam regions. Pwani had the highest number of chicken (188, 273, 38%) followed by Iringa (113,342, 23%) Dar es Salaam (101,921, 21%), Kilimanjaro 22,075, 4.6% and Zanzibar (17,914, 4%). Kigoma had the lowest number of chicken (58), followed by Rukwa (180) and Kagera (181), (Chart 3.14). 4,755 10,054 8,316 0 2,000 4,000 6,000 8,000 10,000 12,000 1994/95 2002/03 2007/08 Pig Number Year Chart 3.13: Pig Pupolation Trend (Large Scale Farm) RESULTS Tanzania Agriculture Sample Census - 2007/08 55 Chart 3.16: Number of Improved Chicken by Region 0 25,000 50,000 75,000 100,000 125,000 150,000 175,000 200,000 Pwani Iringa Dar es salaam Kilimanjaro Mwanza Zanzibar Shinyanga Morogoro Tanga Mara Mtwara Ruvuma Arusha Mbeya Manyara Tabora Rukwa Dodoma Lindi Singida Kigoma Kagera Region Number 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 200000 Number Region Chart 3.14: Chicken Population by Region Indigenous chicken population Small numbers of indigenous chicken were kept on large scale farms. Only 24,971 chickens were kept, representing 5.0 percent of the total chicken population. In 1994/95, the population of local chicken was relatively high 82,124 (i.e. 26% of the total chicken population). The number declined to 22,423 (4.9% of the total chicken population). In 2002/03 agricultural year, the population increased to 24,971 (5% of the total chicken population) in 2007/08, (Chart 3.15). Improved Chicken Population Some farms kept chicken on a very small scale and did not represent the main enterprise of the farm. Those farms that kept sufficient chicken to be considered as large scale enterprise (over 500 chicken) kept 469,895 chicken (235,923 layers and 233,972 broilers) representing 48% and 47% respectively, of the total chicken population. The farms were mainly located in Pwani (39%), Dar es Salaam (22%), Iringa (24%), Kilimanjaro (5%), Mwanza (4%) and Zanzibar (3%) regions.(Chart 3.16). RESULTS Tanzania Agriculture Sample Census - 2007/08 56 Chart 3.17: Livestock Products Number Slaughtered and Quantity Sold 4,929 639 1,839 49,476 3,633 28,202 - 10,000 20,000 30,000 40,000 50,000 60,000 Beef Mutton/Goats Pig meat Type of Product Number Quantity sold Number Slaughtered The number of layers has increased in the last 14 years. It increased from 87,124 in 1994/95 to 216,474 in 2002/03 and further increased to 235,923 in 2007/08. For the broilers, almost similar trend was observed. The population increased from 158,125 to 217,741 for the period 1994/95 to 2002/03 and grew further to 233,972 in 2007/08. The population growth rate of layers was therefore higher than the growth rate of broilers for that period, (Chart 3.16 and Chart 3.17). The production of layers was concentrated more in Iringa (42%), Pwani (24%) and Dar es Salaam (17%). These three regions kept about 83% of all the chicken produced in large scale farms. However, there was no production of broilers in Dodoma, Lindi, Singida, Kigoma, and Kagera. Likewise, broiler production was concentrated in Pwani region which kept 51.7% followed by Dar es Salaam (25.2%), Kilimanjaro (7.9%), Iringa 5.2% and Mwanza (1.8). These five regions together kept 92% of all the broilers. There was no production of broilers production in Dodoma, Lindi, Singida, Kigoma, Kagera, Rukwa, and Tabora regions. 3.1.6 Other livestock Other livestock (5,293 ducks, 988 rabbits, 612 turkeys, 147 donkeys, 57 horses and 24,613 other minor livestock) had minor contribution to the large scale farms production. Comparison with 2002/03 agricultural year, there was an increase in the number of ducks from 5,000 in 2002/03 to 5,293 and a significant decrease in the number of rabbits from 1,039 to 988, donkeys from 538 to 147 and horses from 169 to 57. 3.2 Livestock and Poultry Products This section presents the results for milk production from cows, egg production and hides and skins. 3.2.1 Meat Production Beef, mutton/goat meat and pork were the types of meat produced in large scale farms. Beef accounted for 60.8% of the total meat produced during the 2007/08 agricultural year. The remaining 39% accounted for pork (34.6%) and mutton/goat meat (4.4%), (Table 3.3 and chart 3.17). Type of meat Number slaughtered Quantity sold (tones) Beef 4,929 49, 476 Mutton/goat 639 3,633 Pig meat 1,839 28,202 RESULTS Tanzania Agriculture Sample Census - 2007/08 57 Chart 3.20 Milk Production in Large Scale farms 2007/08 by Breeds and Regions 0 550,000 1,100,000 1,650,000 2,200,000 2,750,000 3,300,000 3,850,000 Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara North Unguja South Unguja Urban West North Pemba South Pemba Regions Liters Indigenous Improved 3.2.2 Milk production In Tanzania, milk is obtained from cows and goats. However, goat milk production was of minor importance compared to that of cows therefore, it is not included in this analysis. In 2007/08, the number of milked cattle was 15,988 cows of which 8,275 (51.7%) were indigenous breed and 7,713 (48.3%) were improved breed. Holdings kept 15,988 cows which was an increase of 3,528 (28.3%) compared to 12,460 cows in 2002/03. The cows produced 48,079 litres a day or an average of 3.01 litres per cow per day (in 2002/03, smallholders production was 1.6 litres per cow per day). Average milk production by indigenous cattle per day was 0.9 litres and by improved breed was 5.2 litres. The main milk producing regions (large scale farms) in the country were Iringa with 22 percent of the total cow milk followed by Pwani (10%), Morogoro (9%), Kagera, and Ruvuma (each 8%), Arusha and Kilimanjaro (each 7%). The lowest amount of milk was produced in South Pemba, Urban West, South Unguja, Rukwa, and Singida, (Chart 3.20). The main producers of milk from indigenous cattle were Kagera (808,779 litres) followed by Iringa (364,607 litres) and Morogoro (309,001litres) while the main producers of milk from the improved breeds were Iringa (3,557,680 litres) followed by Pwani (1,585,541 litres), Arusha (1,254,234 litres), Morogoro (1,243,750) and Kilimanjaro (1,136,618). Prices differed considerably between regions and seasons. Prices were higher during dry season when feeds are scarce and decreased during the wet season when the supply of milk was higher due RESULTS Tanzania Agriculture Sample Census - 2007/08 58 Chart 3.23 Number of Hides/Skins Sold by Large Scale Farms Consumed, 123, 6% Sold, 1933, 94% to ample supply of natural growing pastures. Mean price of milk per litre of indigenous cattle was Tshs 415 with a range from Tsh 250 in Tabora to Tsh 743 in Lindi region. For the improved breeds, prices ranged from Ths 200 in Kigoma to Tshs 800 in Mtwara region. 3.2.3 Egg Production The number of eggs produced by large scale farms per day was 44,396 of which 25,260 (57%) eggs were sold and 19,136 (43%) eggs were consumed. The total production was much less than 50,947 eggs, as reported in 2002/03 although the proportion of eggs sold and consumed were more or less the same. Most of the eggs produced in large scale farms were from Pwani region (18.6%), followed by Iringa (15.4%), Dar es Salaam (10.4%), Manyara (7.2%), Kilimanjaro (6.8%) and Zanzibar (6.3%), (Chart 3.21). This represents 64.7 percent of the total eggs production per day in large scale farms. 3.2.4 Hides and Skins The number of hides and skins produced by large scale farms was 2,056 which was less by 304 units (15%) when compared to 2,360 recorded in 2002/03 census. Of the total reported units, 1,933 (94 %) were sold whilst only 6 percent were utilized in other uses (Chart 3,23). Most of the hides and skins were concentrated in Pwani (707 units), followed by Iringa (288 units), Kagera (243 units), and Mara (203 units), (Chart 3.22). The smallest number was in Mtwara, Dar es Salaam, Tabora, Morogoro, and Dodoma, while Lindi, Singida, Rukwa, Kigoma, Shinyanga, and Zanzibar had no hides/skins. All regions sold hides and skins by 100 percent except Arusha, Mtwara, Ruvuma, and Tabora which utilized them locally, (Chart 3.22). RESULTS Tanzania Agriculture Sample Census - 2007/08 59 3.3 Livestock Diseases 3.3.1 Chicken Five contagious diseases affected chicken in large scale farms, namely Coccidiosis, Chorysa, Fowl Typhoid II, Fowl Typhoid and New Castle diseases. The magnitude or extent of infection differed from one type of a disease to another. In total, 247,721 chicken were infected by these contagious diseases. Coccidiosis disease was the most predominant disease which infected 105,528 (43%) chicken followed by Chorysa which affected 72,929 (29%) chicken. This was followed by Gomboro which affected 33,767 (14%) chicken, Fowl Typhoid which affected 18,332 (7%) chicken and lastly, the New Castle Disease which affected 17,165 (7%) chicken, (Chart 3.24). 3.3.2 Coccidiosis Disease In large scale farming, Coccidiosis infected the largest number of chicken as compared to other chicken contagious diseases. The rate of infection in the total population was 43 percent. Pwani had the highest rate of infection (72%) of the total chicken reported to be infected with coccidiossis disease, followed by Tanga ( 9.5%), Arusha (6%), Zanzibar (4.2%) and Dar es salam (2%). The regions with the highest rate of infection were not necessarily closely correlated to the number of chicken in the region and infection appeared to be associated with other factors for example intensive farming systems, improved breeds etc. The lowest infection rate was reported in Tabora (0.1%) and Manyara (0.1%). The cases were reported in Dodoma, Lindi, Mtwara, Singida, Rukwa, Kigoma, and Kagera, ( Chart 3.25). Chart 3.25 Percetage of Chicken Infected with Coccidiosis by Region - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Ruvuma Iringa Mbeya Singida Tabora Shinyanga Kagera Mwanza Mara Manyara Zanzibar Region Number Infected 0 10 20 30 40 50 60 70 80 Percentage of Infection Number Infected Percentage of Infection RESULTS Tanzania Agriculture Sample Census - 2007/08 60 Chart 3.27: Percetage of Chicken Infected with Fowl Typhoid by Region 0 15,000 30,000 45,000 60,000 75,000 90,000 Arusha Kilimanjaro Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Tabora Shinyanga Mwanza North Unguja Region Number Infected 0 10 20 30 40 50 60 70 80 Percentage of Infection Number infected Percentage Infected Chart 3.28: Percentage of Chicken in the Region Infected with New Castle 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000 Pwani Iringa Dar es salaam Kilimanjaro Mwanza North Unguja Shinyanga Morogoro Tanga Urban West Ruvuma Mtwara Mara South Unguja Manyara Tabora Mbeya Arusha Singida Dodoma Lindi Kagera Rukwa Region Chicken Population 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Percentage Infected Total chicken Population Percent Infected Chart 3.26: Percetage of Chicken Infected with Chorysa by Region 0 15,000 30,000 45,000 60,000 75,000 90,000 Arusha Kilimanjaro Morogoro Pwani Dar es salaam Mtwara Ruvuma Iringa Mbeya Shinyanga Kagera Mwanza Manyara North Unguja South Unguja Urban West Region Number Infected 0 10 20 30 40 50 60 70 80 Percentage of Infection Number Infected percentage Infected 3.3.3 Chorysa Disease Chorysa disease infected 14.7 percent of the total chicken population which is higher than 8.1% recorded in 2002/03. Pwani had the highest infection rate of 75 percent of the total chicken reported to be infected with chorysa disease in this region followed by Dar es salam (8.3%), Arusha (8.2%), Shinyanga (4%), Zanzibar (4%). Mtwara, Morogoro, Mbeya, Kagera, Kilimanjaro, Ruvuma, Iringa, and Mwanza each accounted for less than one percent of the total chicken reported to be infected with chorysa disease. While in Dodoma, Lindi, Tanga, Rukwa, Singida, Tabora, Mara and Kigoma the rate was almost zero, (Chart 3.26). 3.3.4 Typhoid Disease Fowl Typhoid infected 3.7 percent of the total population of chicken in large scale farms which was lower than 6.6% as reported in 2002/03. The rate of infection was higher in Dar es Salam compared to other regions where infection reached 76.1% followed by Shinyanga (10%). The rate of infection in Morogoro was 2 percent and Iringa was 7 percent of the total infected chicken. The results show that Kilimanjaro, Dar es Salaam, Mbeya, Tabora, Rukwa, Shinyanga, and Mara had infection rate of less than one percent (Chart 2.27). 3.3.5 New Castle Disease Newcastle disease infected 7 percent of the total chicken population which was higher than 1.6 percent as recorded in 2002/03. South Unguja had the highest (67%) of the total chicken population infected with the disease followed by Tabora (51%), Ruvuma RESULTS Tanzania Agriculture Sample Census - 2007/08 61 Chart 3.29: Percentage of Chicken Died due to Contigious Diseases 0 20,000 40,000 60,000 80,000 100,000 120,000 Newcastle Disease Gumboro Coccidiosis Chorysa Fowl Typhoid Unmber of Chicken Infected 0 1 2 3 4 5 6 7 8 9 10 Percentage Died Number Infected Percentage Died Chart 3.30: Number of Chicken Dead byContagious Disease and Proportion of death Fowl typhoid, 473, 3% Newcastle Disease, 1,529, 9% Gumboro, 1,929, 6% Chorysa, 4,038, 6% Coccidiosis, 5,621, 5% Chart 3.31: Number of Chicken Dead by Newcastle Disease by Region 35 0 3013 45 49 269 0 2130 34 5 13 61 0 5 240 0 9 36 20 16 600 0 0 0 0 100 200 300 400 500 600 700 Dodoma Kilimanjaro Morogoro Dar es salaam Mtwara Iringa Singida Rukwa Shinyanga Mwanza Manyara South Unguja North Pemba Region Number (35%), and Manyara and Dodoma (each 33%). With regard to chicken population, Mtwara, Kigoma and Mara had the moderate rate of infection each with an average of 10 percent. While the lowest rate of infection was recorded in Dar es salam, North Unguja, Mwanza and Iringa of which the rate of infection was less than 2 percent. New castle disease was not reported in Arusha, Lindi, Rukwa and Kagera, (Chart 3.28). 3.3.6 Deaths due to Disease Infections The number of reported deaths from contagious diseases is presented in Chart 3.29 Table 3.4. The results show that, coccidiosis was the most infectious disease which affected 105,528 chicken followed by Choryza and Gumboro. Out of the total chicken affected by the contagious diseases, 13,590 (5%) died. The results show that the rate of death was highest with the New Castle Disease. It shows that, out of all the 17,165 infected with the New Castle Disease, 1,529 (9%) died. The rate of death caused by Gumboro and Chorysa were 6 percent each and the smallest rate of death was recorded in Fowl Typhoid with only 3 percent of the total infected chicken, (Table 3.4 and Chart 3.30). Pwani region had the highest total number of deaths with 4,941 (36%) followed by Tanga region 4,491 (36.2%), and South Unguja 1,181 (8.6%). RESULTS Tanzania Agriculture Sample Census - 2007/08 62 Table 3.4: Number of Chickens died from major poultry diseases in 2007/08 census The number of deaths caused by the Newcastle disease was 1,529 of which the highest was in South Unguja (39.2%) followed by Dar es Salaam (17.5%) and Shinyanga (15.7%). For the Fowl typhoid, out of 473 deaths, Dar es Salaam had 48.9 percent of the deaths; Iringa region 23.9 percent, Mwanza region 6.1 percent and Arusha and Ruvuma (each 4.2%) of the total deaths, (Chart 3.31 and 3.32). Out of 5,521 deaths caused by Coccidiosis, 87.2 percent were reported in Tanga, 4.4 percent in Pwani and 2.7 percent in Urban West region. Chorysa disease caused 4038 deaths, out of which, 93 percent were in Pwani, 1.5% in Dar es Salaam and 1.2 percent were in Arusha. 3.4 Access to Livestock infrastructure and Services Access to livestock services is critical taking into consideration the widespread nature of livestock diseases and the high rate of livestock infection. The distance from large scale farms to livestock services (i.e. Veterinary clinic and input suppliers) are higher than the distances to livestock husbandry structures. Facilities such drenching, water poits, hide & skin shades slaughter slabs, cattle crush and hand powered sprayers were found to close to livestockkeepers. Diseases Number Infected Number Died % Died Newcastle Disease 17,165 1,529 9 Gumboro 33,767 1,929 6 Coccidiosis 105,528 5,621 5 Chorysa 72,929 4,038 6 Fowl typhoid 18,332 473 3 Total 247,721 13,590 5 Chart 2.32: Number and percentage of Chicken Dead due to Contigious Diseases by Region 35 0 30 13 45 49 269 21 30 34 5 13 61 5 240 0 9 36 20 16 600 0 0 50 15 0 20 3,757 61 30 8 34 3 0 0 0 20 10 5 0 0 20 5 0 0% 20% 40% 60% 80% 100% Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Mtwara Ruvuma Iringa Mbeya Singida Tabora Kigoma Shinyanga Kagera Mwanza Mara Manyara North Unguja South Unguja Urban West Newcastle Disease Gumboro Coccidiosis Chorysa Fowl typhoid RESULTS Tanzania Agriculture Sample Census - 2007/08 63 Chart 3.34: Percent of Farms >15km from Veterinary Clinic 0 25000 50000 75000 100000 125000 150000 175000 200000 Pwani Singida Mara Tanga Iringa Kagera Morogoro Dodoma Kilimanjaro Arusha Mbeya Lindi Dar es salaam Mwanza Rukwa Ruvuma Tabora Manyara Mtwara Kigoma North Unguja Shinyanga North Pemba South Unguja Urban West South Pemba Region Livestock Population 0 2 4 6 8 10 12 14 Percentage Number of Livestock Percentage Chart 3.35: First Most Important Outlet by Type of Livestock kept by LSF in 2007/08 0% 20% 40% 60% 80% 100% Percent Others 15 14 9 19 16 Another Farmer 46 24 16 14 22 Abattoir 17 13 8 4 3 Secondary Market/Auction. 13 8 7 4 24 Local Market 135 69 36 4 11 Trader at Farm 157 85 51 44 86 Cattle goats sheep Pigs Chicken Chart 3.36: Secound Most Important Outlet by Type of Livestock kept by LSF in 2007/08 0% 20% 40% 60% 80% 100% Percent Others 18 9 4 12 11 Another Farmer 101 49 30 31 46 Abattoir 53 37 16 6 10 Secondary Market/Auction. 16 11 5 6 12 Local Market 73 30 20 7 20 Trader at Farm 85 51 30 11 39 Cattle Goats Sheep Pigs Chicken Majority (more than 30%) of the livestock keepers accessed other services such as abattoir, Veterinaty clinics, Input markets, Primary and secondary markets more than 15 km from their residents. 3.4.1 Access to Veterinary Clinic Chart 3.34 present proportions of farm within or greater than 15 km from the veterinary clinics. The total of 170 large scale farms were reported to have an access to vetenary clinics for more than 15 km and this presents 36 percent of the total livestock holdings. From the total 170 farms Iringa region account 13 percent, followed by Manyara region (12%), Pwani, morogoro, kagera and Ruvuma (9%) each. only one farm in Singida indicated access greater than 15 km. Other regions account less than 5 percents are found in Dar es salam, mtwara, Mbeya, Singida ToboraRukwa, Kigoma, and Mwanza. Few keeper in remaining regions indicated access less that 15 km (Chart 3.34). Iringa, Pwani and Dar es Salaam had high livestock population and relatively good access to veterinary clinics. 3.4.2 Access to Market for Livestock Chart 3.35 and 3.36 present the primary and secondary outlets for the livestock and associated products. Cattle followed by goats, sheep and to a lesser extent chicken depended on the trader at farm which accounted for 43 percent of the total farms that responded to the first most important outlet for selling livestock followed by local market (26%). Main outlet for the chicken was the market at farm which accounted for 53 percent of the total farms selling chicken. The same sinnerio was for pigs rearing farms with 49 percent of the farms that sold RESULTS Tanzania Agriculture Sample Census - 2007/08 64 Chart 3.37: Percentage of Farms >15km from Input Supply Center 0 25000 50000 75000 100000 125000 150000 175000 200000 Pwani Singida Mara Tanga Iringa Kagera Morogoro Dodoma Kilimanjaro Arusha Mbeya Lindi Dar es salaam Mwanza Rukwa Ruvuma Tabora Manyara Mtwara Kigoma North Unguja Shinyanga North Pemba South Unguja Urban West South Pemba Region Livestock Population 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 Percentage of Farms Livestok Population Percentage Chart 3.38: Percentage of Farms >15km from Primary Market 0 25,000 50,000 75,000 100,000 125,000 150,000 175,000 200,000 Pwani Singida Mara Tanga Iringa Kagera Morogoro Dodoma Kilimanjaro Arusha Mbeya Lindi Dar es salaam Mwanza Rukwa Ruvuma Tabora Manyara Mtwara Kigoma North Unguja Shinyanga North Pemba South Unguja Urban West South Pemba Region Livestock Population 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Percentage of Farms Livestock Population Percentage pigs. Abbator was less common to all especially chicken (Chart 3.35). Almost similar pattern of outlets is revealed with respect to secondary markets but many keepers now depends on other farmers. 3.4.3 Access to input supply facilities The results show that number of Large Scale Famrs reporting access to livestock infrastructure and Services 15km and above were 176 and this presents 37 percent of the total livestock holdings (475). Mbeya account 15 percent of the tota farms reported to have access to input supply facilities 15km and above. This followed by Kagera region (14.2%), Morogoro (13.1%), Ruvuma (10%), Manyara (6%). The smallest percent was observed in South Unguja of which account less than one percent (Chart 3.37). 3.4.4 Access to Primary Market The results reveals that the total number of Large Scale Famrs reporting access to livestock infrastructure and services to primary market were 64 farms and this presnts 13 percent of the total livestock holdings. Kagera region have 19 percent of the total farms, followed by Morogoro (18%), Ruvuma (11%), Pwani (13%). The remaining regions have less than 10 percent. All regions in Zanzibar they have access to primary market less than 15km (Chart 3.38). RESULTS Tanzania Agriculture Sample Census - 2007/08 65 Chart 3.39: Large scale Farms Located <5km from Hide/Skin Shade by Regions 0 5 10 15 20 25 30 Manyara Iringa Ruvuma Pwani Tanga Arusha Kilimanjaro Mara Dodoma Kagera Mbeya Tabora Mwanza Lindi Singida Morogoro Dar es salaam Mtwara Rukwa Kigoma North Unguja Shinyanga Region Number Chart 3.40: Number of Holdings and Percentage with Access to Water Point less than 5km by Region 0 25 50 75 100 Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara North Unguja Region Number of Farms 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Percentage Number of Farms Percentage Chart 3.41: Number of Employee by Gender Male, 43395, 44% Female, 54789, 56% 3.4.5 Access to hide and skin shades In large scale farms keeping livestock, 30 percent (143 farms) are located 5 km or less from a hide and skin shed. The regions of Manyara, Pwani, Iringa, Ruvuma, and Mara have more than 10 holdings located less than 5 km from the nearest shed. Other highly advantaged regions are Pwani (11.2%), Arusha (6%), Mbeya (3%) and Tanga (9%) Chart 3.39. 3.4.6 Access to nearest village watering point /dam During 2007/08 census, 244 large scale farms reported to have access to the village water points/dams. All 244 farms (100%) accessed water less than 5 kilometers away (Chart 3.40). No holding reported over 5 km. Shinyanga, South Unguja, Urban West and two regions in Pemba do not have large scale livestock farming. 3.5 Farm Employment The total number of employees on large scale farms was 98,184 (an increase of 27,224 Farms from 2002/03 census) of which 54,789 (56%) were males and the remaining 43,395 (44%) were females. Compared to 2002/03 census the percentage of female employees has increased from 38% to 44% in 2007/08. Conversely although number of male employees has increased from 44,265 in 2002/03 to 454,789 in 2007/08 the percentage has declined from 62% percent in 2002/03 to 54% in 2007/08 (Chart 3.41). RESULTS Tanzania Agriculture Sample Census - 2007/08 66 Chart 3.43 Number of Temporary Employee by Gender and Region 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 Arusha Tanga Iringa Morogoro Manyara Kilimanjaro Mbeya Ruvuma Dodoma Kigoma Pwani Mtwara Kagera Mwanza Lindi Tabora Mara Singida Rukwa Dar es salaam Region Number of Employee (Male) (Female) Out of 54,789 male employees, 21,622 (39.4%) were permanent employees while 33,167 (60.5%) were temporary employee.. There was an increase of 6% percent of permanent employees For female emloyees, out of 43,395 females , 22.9 percent were permanent and 77.1% were temporary. Out of 31,587 permanent, 68.4 percent were males and 31.6 percent were females. Also, out of 66,597 temporary employees, 50 percent were males and 50 percent were females. 3.5.1 Temporary Employees There were 66,597 temporary employyes. The highest number was in Arusha (26.3%), Tanga (16.7), Morogoro (8.6%), Kilimanjaro (6.7%), Iringa (7.8%) and Manyara (6.7%), Dar es salam (3.6%). The lowest number (below 1 percent) was in Singida, Rukwa, Tabora, Kagera and Lindi. Chart 3.43 presents the number of temporary employees by gender in the regions. The highest number were in Arusha followed by Tanga, Iringa, Morogoro, Manyara and Kilimanjaro.. Arusha, Kilimanjaro, Mtwara, Mara, and Dar es Salaam had higher female temporary employees than males.. Highest female to male ratios were recorded in Dar es Salaam, Mara and Mtwara, (Chart 3.43). Most of the farm employees (67.8%) had temporary employment status and the number of laborers was large (82,177 i.e. 83.7%) than the number of employees from other categories (16.3%). Out of 82,177 laborers, 52 percent were male and 48 percent were female. This was followed of other professional staff whereby 45.6 percent were male permanent employees and 35.2 percent were female permanent employees, while 5.9 percent were males professional temporary employees and 2 percent were femaleProfessinal temporary employees (Chart 3.44 and Table 3.4). RESULTS Tanzania Agriculture Sample Census - 2007/08 67 Table 3.5 Number of Employees by Category 3.5.2 Permanent Employees There were 31,589 permanent employees representing an increase of 11,969 (61%) compared to 2002/03 census results. The highest number was in Tanga (24.9%) followed by Iringa (14.8%), Arusha (14.7%), Morogoro (10.8%), and Kagera (10.5%). The lowest number was found in Shinyanga, followed by Kigoma and all the regions in Zanzibar. Each of these eight regions had less than 5 percent of the total permanent employees (Chart 3.45). With the exptions of Morogoro, all other regions had more male permanent employee than female counterparts. Highest male to female ratios was recorded in Unguja North (1:25), Rukwa (1:23), Mtwara (1:21), Tabora (1:15) and Unguja South (1:10). 3.6 Outgrowers Schemes Number of outgrowers scheme coordinated by large scale farm is presented in Chart 3.46. Tanga followed Pwani, Iringa Morogoro and Manyara had largest areas (ectares) under outgrowers’ Category Permanent Employee Temporary Employee Male Female Male Female Labourers 11,753 6,453 31,219 32,752 Supervisor staff 4,280 385 987 476 Other Professionals staff 2,499 1,492 521 79 Mechanical/workshop/ parts stores manage 870 48 162 8 General manager/Financial managers/accountants 826 185 127 42 Crop/livestock husbandry managers/agronomists 618 111 55 18 Clerical/typist/receptio nist staff 517 1,215 75 42 Product Stores managers 132 52 8 3 Agro-processing/Mill managers 79 17 11 10 Irrigation engineers 48 7 2 0 RESULTS Tanzania Agriculture Sample Census - 2007/08 68 schemes. The number of farms involved were highest in Mwanza followed by Ruvuma, Morogoro, Tanga, Shinyanga and Kagera. There were about 9 types services offered by Large Scale Farm to outgrowers. During the 2002/08, main service recorded was storage services benefiting 226 farms (34.4%) out of 774 farms. Other services in the order of importance include extension serices, cattle fattening, crop processing, cattle dipping, and crop marketing.Provision of livestock facilities and livestock services were provided by relatively few Large Scale Farm (Chart 3.47) REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 69 4. REGIONAL PROFILES 4.1 Arusha Arusha region had 104 large scale farms with a land area totaling 52,717 hectares, the eighth in the total number of large scale farms.. It was the second largest with crop only large scale farms, the fifth in number of crop and livestock farms and the first in number of flower producing farms compared to other regions. The region had a relatively small land area under crop growing farms and 61% of the usable land was utilized. The region had the second largest area under flower cultivation. Normally,the region has short and long rainy seasons with the long rainy season being more important. The planted area during the long rainy season was almost nine times that of in the short rainy season. Also, the area planted with permanent crops was nearly half of that planted with annual crops. Cereal production was moderately important especially for wheat and barley. It ranked second in area under maize and sorghum. The region had the largest area of land planted with beans compared to other regions. Paddy, sorghum, cassava and groundnuts were almost insignificant or not planted at all in the region. There was moderately low cultivation of vegetables. The region had a small number of planted trees by large scale farms. It was the eighth with largest number of farms keeping cattle and the eighth with highest livestock population. The number of cattle was relatively low, producing an average of 3,770 liters of cow milk per day after Iringa, Morogoro, Pwani and Dar es Salaam. Most of the cattle were of improved type. Arusha was the sixth with largest number of improved cattle in the country. Arusha had a moderate number of farms keeping goats (64), sheep (33) and the third with largest number of farms rearing pigs. It was the seventh region with lowest number of chicken. The region had the second largest number of farm employees and the first with largest number of temporary employees and the fourth with largest number of permanent farm employees. In all employment categories, the number of male employees was larger than the number of female employees.The region was less infested with chichen diseases also had a relatively better access to veterinary services compared to other regions. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 70 4.2 Dar es Salaam Dar es Salaam had a total of 32 large scale farms with a land area of 870 hectares. It was the second with smallest area comapared to other regions. Had 227 hectares under crops only, 234 hectares under livestock only and 400 hectares under crops and livestock.. About 83% of the land made available to large scale farms was utilized. The region has both short and long rainy seasons; however, the long rainy season had more production.Both annual and permanent crops were important. The region was among the regions with smallest planted areas of cereals (maize and paddy, on78 hectares). Sorghum, beans and groundnuts were virtually not grown in the region. It was not important for vegetables, although some small amounts of tomatoes and onions were grown. With the exception of coconuts, cashew nuts, mangoes and oranges, permanent crops were not important as well. The region had a moderate population of livestock compared to other regions in terms of large scale farms and most of them were of improved cattle followed by pigs, sheep and goats. The region had a low production of cow milk, probably due to the low number of cattle compared to other regions; however the region had the highest farm gate price of cow milk, supposedly due to high demand caused by high population of consumers. It had the largest population of chicken and almost all the chicken were of improved type. Also, it had the highest production of eggs. Though the infection rate in Dar es Salaam was moderately low, it was the third region with highest infection rate for chorysa disease. Access to livestock services and infrastructure was also moderate for veterinary clinic services and input supply services and low for the remaining services. However, the region had the highest number of large scale farms which received livestock extension services. Dar es Salaam had a relatively small number of farm employees. It was the 17th with largest number of temporary farm employees and the 7th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.3 Dodoma Dodoma had 27 large scale farms and it was the sixth with largest land area under cultivation of annual crops (63,779 ha, 92%). Most of the remaining land area was under permanent mixed crops. The percentage of land utilization was relatively high (86%). Cereals were the most important crops in the region and were the eleventh region with largest planted area of maize in the country. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 71 However, the yield during the census year was amongst the lowest in the country. Paddy, wheat, barley and sorghumwere not important in the region’s large scale farms. The production of beans, groundnuts, simsim and sunflower was relatively small. The vegetable and annual cash crops production was not important; however, the region was the second with largest planted area of pigeon peas in the country. It was the fifteenth region with largest number of tractors, first with smallest number of harvesters, fifth with smallest number of ploughs and harrows. It was the second with lowest population of livestock. The region was the fourth with lowest chicken population, all of which were of indigenous type. Egg production as well as milk production was recorded. The infection rate of Fowl Typhoid, Coccidiosis and Chorysa was almost negligible except for Newcastle diseases which had a very small percentage. Access to livestock infrastructure and services was moderately high. However, a relatively high number of farms received livestock extension services. Dodoma is one of the regions which had a low number of farm employees. It was the third with lowest number of permanent employees and the sixth with lowest number of temporary employees. Most of them were males. 4.4 Iringa Iringa region had 105 large scale farms with a land area totaling 92,594 hectares. The largest part of the land was planted with permanent crops and it had a moderate number of crop farms compared to other regions. Also, it had a moderate average area (hectares) of crop growing farms per farm compared to other regions. The available land area utilized per farm was 551 hectares which was less than the national average of 1,107 hectares. Although the region normally has only the long rainy season, it is considered to be one of the most productive regions in Tanzania. In terms of planted area, the region had a moderate planted area of cereals mostly with maize and a small area was planted with wheat, paddy and barley. Almost no sorghum was produced in the region. The region was the sixth largest with planted area of maize, it was characterized by having the highest production in the country due to highest yield than other regions with larger planted areas. It had a moderate planted area of beans, cabbage, tomatoes, chilies and produced the largest quantity of katumu. It was the second with largest area planted with Irish potatoes and tobacco. Very little cassava and groundnuts were grown and no traditional annual cash crops were grown in the region. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 72 The planted area of permanent crops was larger than annual crops and was the second region with largest area planted with coffee and tea. A small area was planted with banana and sugarcane. The region was the fifth with largest number of farms keeping livestock and was the fourth with highest livestock population in large scale farms. It was the fifth with highest number of cattle and the fourth with highest heads of goats. It was the third with highest number of pigs. Most of the cattle were of the improved type. It was the largest milk producing region in the country. Chicken production is important in Iringa and it was the sixth leading region in chicken rearing. Most of the chickens were of the improved type. The region was the fourth with highest number of layers and the sixth with highest number of broilers in the country. It was the second with highest number of eggs produced. The rate of infection was moderately low compared to other regions. Most of the livestock infrastructure and services were at an average distance of under 15 kilometers from the farms. However, the access to veterinary clinics and input supply services was moderate. The region was the seventh with highest percentage of large scale farms which received extension advice. The Government was the major source of extension service. It was the third with highest number of farm employees, the second with highest number of permanent employees and the third with highest number of temporary employees. The number of female temporary employees was almost equal to the number of male temporary employees. 4.5 Kagera Kagera had 35 large scale farms with a land area totaling 178,881 hectares. The region had less than 20 percent of its land area with annual crops, whilst the remaining was either pure or mixed permanent crops or permanent –annual mix. Kagera had an average of 5110 hectares of land per large scale farm and about 92.4 percent of usable land was utilized. Normally, the region has two seasons, with the short rainy season being more important. Cereal production was not important and the region was one of the regions with smallest planted areas of maize. Paddy, sorghum wheat and barley were not planted during 2007/08 agricultural year. It had the lowest planted area of beans. Vegetable production was moderate and small amounts of Irish potatoes were grown. The region was the eleventh with highest percentage of planted area under permanent crops (tea, coffee and banana) in the country. It was the second with largest population of livestock on large scale farms, characterized by having the largest number of cattle. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 73 Most of the cattle were of the improved type. However, the region had the smallest number of goats and sheep. Pig production in Kagera was very low. Milk production was also low and the farm gate price of milk was below the average. Chicken were not reared on large scale farms. Access to infrastructure and services was moderately high. Access to and receipt of extension services was one of the lowest in the country. Kagera was one of the regions having the lowest number of farm employees. It was the 14th with highest number of permanent employees and the 2nd with lowest number of temporary employees. 4.6 Kigoma Kigoma region had 6 large scale farms with a land area totaling 13,204 hectares under large scale farming. It had the smallest number of crop growing large scale farms compared to other regions with the majority being crops only growing farms. The land area utilized per farm was 4,164 hectares (31.5%) which was a relatively low rate compared to the total land available for large scale farms. The region had a moderate area planted with permanent crops. Normally, the region has two rainy seasons with almost the same planted area in each season. Kigoma was one of the least important regions for cereal production eventhough the yield was higher than in many other regions with larger planted areas. Very small areas were planted with maize, paddy, and sorghum. The most important annual crop in Kigoma was beans and it was one of the regions with highest production. Small to moderate quantities of groundnuts and tobacco were also grown. The production of vegetables and cash crops were relatively unimportant compared to other regions. The major permanent crops in Kigoma were oil palm, coffee and banana. The region was the 7th with smallest number of cattle in the country; the number of improved cattle was very small. Very little milk was produced and the farm gate price was within the average. It kept very few sheep and pigs. Kigoma was the 9th with smallest chicken population in the country, almost all of them were indigenous. A small number of eggs were produced. Access to livestock services was moderately good; however, the access to veterinary centres was worse. More extension advice was provided to large scale farms compared to other regions with much higher livestock population. The region had a small number of farm employees. It was the 9th with lowest number of temporary farm employees and the 6th with lowest number of permanent farm employees. The number of male employees was higher than the number of female employees REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 74 4.7 Kilimanjaro Kilimanjaro region had 63 large scale farms with a land area totaling 49,095 hectares under large scale farms and was the second with highest number of crop growing large scale farms in the country. A few of them (11 farms) kept livestock. The region was the third with largest area under annual crops (6582 ha). The region had a moderate land area per crops only growing farm of 12,912 ha and almost 72% of available land was utilized. Normally, the region has both short and long rainy seasons with the long rainy season being more important. Kilimanjaro had almost equal importance of annual and permanent crops, some of which were in mono-crops and in mixed annual/permanent crops. Cereal production in Kilimanjaro is important especially for maize, wheat and barley. The region had the largest area of land planted with Irish potatoes compared to other regions. Paddy, sorghum, cassava and groundnuts were almost not planted on large scale farms in the region. There was a moderately low cultivation of beans and vegetables. The region was the second with largest planted area of sugar cane and was the third with coffee and banana. Small amounts of oranges and mangoes were also grown in the region. The region was the fourth with highest number of farm implements in the country. It was the fourth with largest number of tractors, the fifth with largest number of harvesters and the third with largest number of ploughs and harrows. Kilimanjaro was among the regions having the highest number and percentage of large scale farms which received extension advice in the country, Government being the main extension provider. 4.8 Lindi Lindi region had 14 large scale farms with a land area totaling of 14,012 hectares under large scale farming and was among the regions with the lowest number of annual crop growing large scale farms in Tanzania. Most of the large scale farms grow crops only and very few of them kept livestock. Three large scale farms had livestock only. The land area per farm was 1,000 hectares and 62 percent of allocated land was utilized. The region had a high percentage of permanent crops, some of which were in mono-crops and in mixed annual/permanent crops. Normally, Lindi has only long rainy season. Cereal production was relatively unimportant and it was among the regions with lowest planted areas and yields of maize in the country. It produced small quantities of rice and sorghum. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 75 The region had the largest planted area of cashew nut and second largest planted area of coconut in the country. It had small quantities of oranges and banana and had the lowest number of farms which reared livestock. It was one of the regions having the lowest number of cattle, goats, sheep and pigs. The number of improved cattle was relatively high. The region produced a small amount of milk and the farm gate price was much higher than any other region (except Dar es Salaam), indicating a higher demand over supply. Chicken production was not important in the region Lindi had the lowest number of farm employees. It had also the lowest number of temporary farm employees and was seventh with lowest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.9 Manyara Manyara region had 58,802 hectares under large scale farms and was the 4th with highest number of large scale farms (90 large scale farms) and had the largest area planted with annual crops (21,654 ha). Also, the region was the 4th with largest area of land under crops only (34,343 ha) and the fifth with largest area of land under crop and livestock only (17,459 ha). It was the seventh largest region in terms of total area of land owned by large scale farms in the country with an average land utilization of 653 hectares per farm. The region had the largest planted area of maize and wheat (annual crops), mangoes and oranges (permanent crops). It was the second with largest planted area of barley, beans and sunflower. It was the third with largest planted area with sugar cane, and the 6th with largest planted area of coffee. The region had the highest number of large scale farms rearing livestock and was the eleventh with largest heads of livestock. It was the tenth with largest number of cattle. It had a small number of chicken which were all of indigenous type. It produced a moderate amount of milk per day (1,408 litres per day) and a small number of eggs per day. The number of large scale farms which received livestock extension services was also moderate. The region had moderate access to livestock infrastructure compared to other regions. About half of the farms had better access to veterinary clinics; however, the region had the highest percentage of large scale farms having worse access to secondary markets. Manyara was the sixth with largest number of farm employees. It was the 5th with largest number of temporary farm employees and the 8th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 76 4.10 Mara Mara had 26 large scale farms with a land area totaling 20,672 hectares under large scale farms and the number of crop growing farms was small compared to other regions. The number of farms keeping livestock was also relatively small. The land area available per large scale farm was moderate; however, the utilized land area was 67%. The region was among those with the lowest areas of permanent crops in the country. Normally, it has two rainy seasons (short and long) and the planted area in the short rainy season was around twice that of the long rainy season. The region had a moderate low planted area of cereals. Maize occupied the sixth largest planted area, the area of sorghum was the eighth with largest area in the country. Paddy was not grown in the region; however, beans, groundnuts, sunflower and cotton were produced in small quantities. The region had moderate low importance in tomatoes, cabbage, carrots, chick peas and onions. Minor quantities of coffee, mangoes, banana and coconuts were also produced. Moderate to low planted areas of irrigation existed in the region. Very few large scale farms had practiced irrigation.As usual; storage was in locally made traditional cribs. The percentage of households which sold crops was within the average for the country. The receipt of extension service per farm was relatively low. Mara region has a small population of livestock on large scale farms compared to other regions. Livestock was dominated by cattle; about half of them were of the indigenous type. The number of goats was moderate whilst sheep and pigs were not reared. It had a moderate milk production; however, the farm gate price of milk was amongst the lowest in the country. The region had the second highest rate of Newcastle disease infection and moderate to low infection rate of Coccidiosis and Chorysa. The infection of Fowl Typhoid disease was virtually negligible. Mara had a moderately good livestock infrastructure and services except access to veterinary clinic centres which was relatively bad. A small number of large scale farms received livestock extension services. It was the tenth with largest number of farm employees. It was the 11th with largest number of temporary farm employees and the 10th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.11 Mbeya Mbeya region had 38 large scale farms with a land area totaling 19,628 hectares. It was more or less dominated by permanent crops but it had some mono and mixed annual crops. The land area REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 77 per large scale farm was below the average for the country and the percentage utilisation of the available land was just above the total average (61.3%) suggesting sufficient land for large scale farming expansion. Mbeya is one of the important cereal production regions in the country. It was the second region with largest planted area of paddy and the fifth with largest planted area of wheat. Mbeya was among the regions with highest yields of maize, paddy and wheat on large scale farms in Tanzania. Moderate amounts of sorghum were grown. High yields were also in groundnuts, cabbages and tomatoes. Mbeya was the fourth with largest planted area of coffee and the fourth with largest planted area of tea. Mbeya has a moderate number of farms which received extension services. Mbeya had moderately low population of livestock. It kept more cattle than other livestock and about half of them were of the improved type. On large scale farming, Mbeya was the 12thlargest region in milk production in the country and the farm gate price of milk was relatively within the average. The region was the fourth with highest number of pigs in the country. It had low number of chicken and most of the chickens were of the improved type. The region was the seventh largest in the production of eggs. The rate of disease infection in the region was moderately low; Newcastle and Coccidiosis being more prevalent than others. In general, access to livestock infrastructure and services was moderately low with access to veterinary clinic and input supply being the leading problems. The region had moderately low number of farm employees. It was the 7th with largest number of temporary farm employees and the 6th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.12 Morogoro Morogoro region had 73 large scale farms with a land area totaling 114,875 hectares making the 4th region with the largest area under large scale farms. Although it had a moderate to high number of crop farming large scale farms compared to other regions, it was the fifth with largest land area planted per farm (1573 ha/farm). Compared to the total area under permanent crops in Tanzania, Morogoro was the second largest with planted area on large scale farms. Sugar cane, sisal, coconuts and oranges were the most important permanent crops. Annual crops were less important crops compared to permanent crops. The region had the highest area (389 hectare) under flowers cultivation. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 78 Normally, the region has both long and short rainy seasons. The planted area during the short rainy season was nine times of that planted in the long rainy season. In terms of planted area, Morogoro was the fifth most important region for annuals in Tanzania. In terms of cereals, it had the largest planted area of sorghum and the fifth with largest planted area of maize and paddy. But, barley and wheat were almost not planted. Cash crops were not important in the region. The region had the largest planted area under sugarcane and it was the second in sisal production. It was the third in the production of coconuts and oranges. Palm oil, bananas and mangoes were also grown in small quantities. It had a moderate number of farms with erosion control/water harvesting facilities. Morogoro was the third with highest livestock population on large scale farms most of which were cattle (76%), followed by goats, sheep and pigs. Morogoro was the third with highest number of cattle and the second with highest number of goats in the country. Most of the cattle were indigenous. Milk production was moderate and the farm gate price was within the average. It had a small chicken population, the majority of which were indigenous. A medium to low number of improved layers were kept; however, the number of improved broilers was small. It had a moderate production of eggs compared to other regions. In general, the rate of disease infection was moderate and the rate was higher for the Newcastle disease. Large scale farms which keept livestock had a moderately better access to livestock infrastructures compared to other regions. Only a moderate proportion of farms received livestock extension advice. Morogoro was the second with largest number of farm employees. It was the third with highest number of permanent employees, a larger proportion being male employees. It was the second with highest number of temporary employees, also, the larger proportion being male employees. 4.13 Mtwara Mtwara region had 38 large scale farms with a land area totaling 14,844 hectares. Number of crops only large scale farms was small (1,560 ha) compared to other regions. Land utilization was at an average of 390 hectares per farm. About 70% of the available land was utilized. The region was characterized by having high percentage of its total planted area under permanent crops, most of which were in mono-crop stands. Maize and groundnuts were among the most important annual crops in Mtwara though not very important when compared to other regions. In terms of planted area, the region was not important for cereal production. The yield for maize was one of the lowest REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 79 in the country during the census year. Comparatively, small quantities of sorghum, paddy, groundnuts and maize were grown. Vegetables were not important in the region and the traditional annual cash crops were not grown in the large scale farms. The main crop in Mtwara was and is still palm oil nuts with 79 percent of the total planted area with palm oil in the country, followed by cashew nuts. Some oranges and bananas were also grown. Mtwara had a small livestock population, most of whichwere cattle. The region was the third with smallest number of cattle in the country. Also, the number of improved cattle was very small which resulted into very small amount of milk produced. The region had very few sheep and pigs. Mtwara region was the 11th with smallest chicken population and most of them were indigenous. It was one of the regions which produced the smallest number of eggs. Access to livestock services was good to some services; however, the access to veterinary clinic and input supply were bad. More extension advice was provided compared to other regions with much higher livestock population. The number of farm employees in the region was moderately low. The temporary employees were about six times as much as the permanent employees. 4.14 Mwanza Mwanza had 42 large scale farms with a land area totaling 12,014 hectares most of which was under livestock only (9,109 ha) and crops and livestock (2,241 ha). The region had the smallest area under crops only (664 ha). The percentage of land utilization during the census year was 87.2% which was among the highest compared to other regions. Mwanza had two planting seasons (short and long rainy seasons). The short rainy season had a greater planted area than the long rainy season during the 2007/08 census year. The region had a moderate planted area of annual crops compared to other regions in the country. It was the tenth with largest planted area of maize, the sixth with largest planted area of paddy, the fifth with largest planted area of sorghum, the third with largest planted area of cotton and was the second with largest planted area of groundnuts. Vegetable production in Mwanza was moderate. Permanent crops were not very important. On large scale farms, Mwanza was the fifth with highest population of livestock. It was the third with largest number of farms which reared cattle and the fourth with highest population of cattle in the country. Most of the cattle were indigenous. The region was the second with largest number of REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 80 farms keeping goats and sheep. However, it had a moderate number of goats and it was one of the regions with the lowest population of pigs. The region was the fourth with highest population of chicken most of which were of improved type. The region was also the fourth with highest number of eggs. The rate of disease infection was moderately low and considering the high population of poultry, it had a low incidence of Newcastle disease, Fowl Typhoid and Chorysa. The incidence Fowl Typhoid and Coccidiosis were moderate. Access to livestock infrastructuresand services was moderate to poor. Mwanza has a moderate number of large scale farms which received livestock extension services and Government was the major source of extension services. The region had a relatively low number of farm employees compared to other regions. It was the 10th with largest number of temporary farm employees and the 13th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.15 Pwani Pwani region had 67 large scale farms with a land area totaling 169,245 hectares, the second in the country in terms of area under cultivation. Its land utilization was 864 hectares or 39.1% per farm which was among the lowest in the country. Normally,the region has two rainy seasons (short and long) with the long rainy season having more production. Cereal production was very small and the region was among those with smallest planted areas of maize in the country; however, there was a little paddy production.. Beans and vegetables were also grown in small quantities.. The region was the second with largest planted area of cashewnuts and it had the largest planted areas of coconuts. It was the second with largest area planted with mangoes in the country. Few trees were planted on large scale farms. Pwani region had the highest number of livestock, mostly cattle followed by goats and a small number of sheep and pigs. A small quantity of milk was produced and the farm gate price was somehow moderate. It was the second with highest chicken population, mostly of improved type. Pwani had a moderately good access to livestock services. The rate of infection in poultry was low and the number of farm employees was relatively small with male employees being more than female employees. 4.16 Rukwa Rukwa had 8 large scale farms on 50,500 hectares. It had no large scale farms with crops only. Normally, the region has no short rainy season. About 61% of the total usable land was utilized. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 81 Rukwa had a moderate planted area of cereals, with maize covering the largest area; however, the region was the fourth with lowest planted area of maize in the country, the eighth with largest planted area of wheat and the tenth with largest planted area of paddy. Sorghum, barley and vegetables were virtually not planted whilst beans, sunflower and groundnuts were planted in small areas. Rukwa was one of the regions with the smallest percentage of the area planted with permanent crops. The region had a moderate number of planted trees. The farmsLarge scale farms in had a moderate small population of livestock compared to other regions and most of the livestock were improved cattle and a small number of goats, sheep and pigs. Milk production was also small with a relatively low farm gate price. Rukwa had a small population of chicken which accounted for the smallest production of eggs. The infection rate was relatively low. Access to livestock services and infrastructure was the worst for veterinary clinic, hides and skin sheds and input supply services; however, the the remaining services were good. Rukwa was among the regions with lowest percentage of large scale farms which received livestock extension services. The region was the third with lowest number of farm employees. It was the 18th region with largest number of temporary farm employees and the 17th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.17 Ruvuma Ruvuma had a total of 43 large scale farms with a land area totaling 32,720 hectares. It had a moderate number (10,143 ha) of crops only and 18,375 ha of crops and livestock. It had an average planted land area of 235 hectares per farm which was below the overall average. Land utilization was 27.9%, being one of the lowest in the country. Normally, Ruvuma has no short rainy season. Cereal production in the region was moderate and most of it was on maize and paddy. Area planted with wheat was one among the smallest areas. Tobacco was also planted in a small area. Beans and groundnuts were produced in moderately low quantities; however, the region was important for vegetables production. It had a moderately low production of cashew nuts. Production of coffee, coconuts, oranges and bananas was low. Ruvuma had a moderately small livestock population on large scale farms. It was the 10th with largest livestock population and the 10th with largest number of farms which reared cattle and the REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 82 13th with highest population of cattle in the country. About half of the cattle were of improved type. The region had a moderate number of goats and sheep. However, it was the second wth largest population of pigs. Milk production was moderately low and the farm gate price for milk was relatively high. The region had a low population of chicken and about 70 percent of them were of improved type. The region was the fifth with highest number of eggs. The rate of disease infection was high in some diseases and low in some other diseases. The region had the highest rate of infection of Coccidiosis and was the second with highest rate of infection of Chorysa. Ruvuma was the fourth with highest infection rate of Fowl Typhoid. It was the fifth with highest infection rate of Fowl Typhoid I and Newcastle Disease. Access to livestock infrastructure and services was poor; however, the access to village watering points was good. The access for veterinary clinics and input supply services was poor. Ruvuma has a moderate number of large scale farms receiving livestock extension services and the Government is the major source of extension service. The regionRuvuma had relatively smaller number of farm employees compared to other regions. It was the 8th with largest number of temporary farm employees and the 11th with largest number of permanent farm employees. The number of male employees was higher than the number of female employees. 4.18 Shinyanga Shinyanga had 3 large scale farms and it had the lowest area of land under cultivation (18 hectares) with livestock only (4 hectares) and crop and livestock (14 hectares). It had the lowest land utilization per farm (an average of 6 hectares per farm). Virtually, no permanent crops wer grown in the region. Cereals were the most important crops in the region. It was among the regions with highest (88.9%) utilization ratio. The region was not important for cassava, beans, fruits and vegetable production but, it was the sixth with largest planted area of groundnuts. In terms of cash crops, Shinyanga was among the most important regions for cotton production in large scale farms. It was one among the regions with smallest areas of irrigation and lowest percentages of erosion control facilities. Despite that REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 83 Shinyanga is one of the important crop growing regions, it only had low contact with extension services. However, the region had the highest number planted trees on large scale farms. Shinyanga was one of the regions having the smallest population of livestock on large scale farms. It had a low number of cattle (eighth lowest and mostly indigenous); and had a small number of goats and sheep. The region had no pigs in large scale farms. It had low milk production and was one of the regions with the lowest farm gate prices for milk. It was also one of the regions wth the lowest chicken population of which, about 60 percent was improved chicken, mostly layers. A small number of eggs were produced. The rate of disease infection was moderately low but was relatively high for the fowl typhoid II. In general, the access to livestock infrastructure and services was moderate. The main extension provider was the Government. Shinyanga was one of the regions having the lowest number of farm employees. It had the lowest number of permanent employees and was the 8th with lowest number of temporary employees. 4.19 Singida Singida had 29 large scale farms with a land area totaling 16,062 hectares. The land area utilized per large scale farm was 553 hectares representing a high land utilization of 92 percent . Normally, the region has only the long rainy season. In terms of planted area, the region was moderately important for cereals and whilst maize had a higher planted area than other cereals in the region. It was an important region for the production of sorghum. The production of wheat was also important. Virtually, neither paddy nor cassava was grown; however, beans and groundnuts were produced in small quantities. Singida had the highest planted area of sunflower. With the exception of onions, vegetable production was not important. The number of farms which practiced irrigation was very small (only three farms). The number of farms which received extension services was relatively small. Singida had the smallest livestock population most of which was of cattle followed by goats. The region had the smallest number of cattle, mostly of indigenous type. The region was among the regions having the lowest number of goats, sheep and pigs. It had the lowest milk production and the farm gate price of milk was low. The entire chicken population was of indigenus type and the production of eggs was low. The rate of disease infection was low except for Newcastle disease. The region had a moderate access to livestock infrastructure and services. The percentage of large scale farms which received livestock extension advice was also moderate and was largely provided by the Government. REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 84 Singida was one of the regions having a low number of farm employees. It was the fourth with lowest number of permanent employees and the seventh with lowest number of temporary employees. Most of the farm employees were males. 4.20 Tabora Tabora region had only 12 large scale farms with a land area totaling 3,765 hectares under cultivation. It was characterised by annual cropping with a very small amount of permanent crops. The percentage of land utilization was 40% which was among the lowest in the country. Also, it was one of the regions having the smallest area of crops per farm. Normally, the region has only one planting season (the long rainy season). Tabora had the fourth largest planted area of maize and sorghum. It was a predominant tobacco growing region and had the largest planted area of groundnuts in the country. Cassava, beans, cotton, paddy, sunflowers were of moderate importance in the region. Permanent crops consisted of small areas of sugarcane, palm oil, mangoes, oranges and bananas. There was a moderate number of planted trees. Tabora had a low livestock population in large scale farms. The region had a small number of farms which reared cattle, goats, sheep and pigs. Also, it had a low number of cattle, goats, sheep and pigs. The number of improved livestock was also small, the quantity of milk produced per day was small and the farm gate price within the country’s average. The number of chicken was small; hence, the number of eggs produced per day was also small. The region was the fourth with highest incidence of Coccidiosis infection in the country. However, the infection rate of most other diseases was moderately low. Access to secondary markets was moderate while access to veterinary services, primary market and input supply was worse. Tabora had a small number of farms which received extension services on livestock. Tabora was one of the regions with lowest number of farm employees, both permanent and temporary. 4.21 Tanga Tanga region had 113 large scale farms with a land area totaling 125,825 hectares under crop production, and was the third with largest planted area after Kagera and Pwani. It had the largest average area per crop growing large scale farm (1,113.5 hectares per farm). It had a moderate land utilization of 56 percent. Most of the region was under permanent crops (sisal and tea) which REGIONAL PROFILES Tanzania Agriculture Sample Census - 2007/08 85 occupied the largest land area in the country. Small quantities of bananas, cashewnuts, sugarcane, coconuts, mangoes, coffee and pigeon peas were produced. For annuals, it was the eighth region with largest planted area with maize in the country, and the third highest for paddy and the forth highest for beans, while sorghum and barley were not grown in the region. There was a relatively high number of large scale farms which received extension services provided mostly by the Government. Very few farms borrowed money for agricultural purposes from credit facilities. The number of farms which kept livestock was moderate (sixth region) with 31 large scale farms. It was the sixth with largest number of cattle (most of them indigenous) which produced a moderate quantity of milk per day. It had a moderate number of goats and sheep and the number of pigs was small. Also, Tanga had a moderate number of chicken most of which was of improved type. Tanga region had a few farms which received livestock extension services. Also, it had the highest number of farm employees, both permanent and temporary. The number of male employees was higher than that of female employees. 4.22 Zanzibar There were 38 large scale farms in Zanzibar which represent 3.8% of the total number of large scale farms in Tanzania. North Unguja had the largest number of farms (17) followed by Noth Pemba (8), South Unguja (7) and Urban West (4). South Pemba had the lowest number of large scale farms (2). Crops only farms accounted for more than 68% of the large scale farms in Zanzibar followed by crops and livestock farms (5) and livestock only (2 farms). Zanzibar was the 8th with respect to the smallest area planted with cereal crops and the third with lowest area under maize. Actual area under paddy was the 6th with lowest acreage under paddy planted area, and no large scale farms which produced wheat, sorghum, and beans. On annual crops, Zanzibar ranked the highest with respect to area under cloves and ranked relatively high in acreage under coconuts production. The number of livestock kept was also ranked the lowest. APPENDICES Tanzania Agriculture Sample Census - 2007/08 86 5. APPENDICES Appendix I Tabulation List....................................................................................................... 87 Appendix II Tables ................................................................................................................... 94 Appendix III Questionnaires ................................................................................................. 277 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 87 APPENDIX I: TABULATION LIST Table 1.1 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings (ALL OPERATORS) ....... 94 Table 1.2 TYPE OF FARM OWNERSHIP: Number of Holdings by Type of Farm Ownership and Type of Activity ....................................................... 95 Table 1.3 TYPE OF HOLDING: Number of Holdings by Type of Activity and Region ........ 95 TYPE OF FARM OWNERSHIP Table 1.4 TYPE OF FARM OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Operator /Ownership .. 97 Table 1.5 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings ........................................... 98 Table 1.6 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings ........................................... 99 Table 1.7 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings ......................................... 100 Table 1.8 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings ......................................... 101 Table 1.9 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings ................... 102 LAND ACCESS/OWNERSHIP Table 3.1.1 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region ........................................................................................... 104 Table 3.1.2 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region ........................................................................................... 105 Table 3.1.3 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region ........................................................................................... 106 Table 3.1.4 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region ........................................................................................... 107 Table 3.1.5 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region ........................................................................................... 108 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 88 Table 3.2.1 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region (ALL OPERATORS) .............................. 109 Table 3.2.2 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region (GOVERNMENT OPERATORS) ......................................................................... 111 Table 3.2.2 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region .............................. 112 Table 3.2.3 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region .............................. 113 Table 3.2.4 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region .............................. 115 Table 3.2.5 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region .............................. 116 CROP PRODUCTION Table 4.1.1 ANNUAL CROPS (VULI) SEASON: Number of Holdings Growing Crops During SHORT RAINY SEASON of 2007/08 and Region ......... 120 Table 4.1.2 ANNUAL CROPS: Planned Area, Actual Area Planted, Area Harvested, Amount Stored and Amount Sold b Crop Type and Region ....... 121 Table 4.1.3 ANNUAL CROPS: Planned Area, Actual Area Planted, Area Harvested, Amount Stored and Amount Sold b Crop Type and Region ....... 122 Table 4.1.4 Area Planted, Iriigated Area, Quantity Harvested, Quantity Sold and Quantity Stored in Large Scale Farms by Type of Cash Crops.............. 123 Table 4.1.5 Number of Large scale farms reporting transport to crop markets by region ........ 124 Table 4.1.6 Number of Large scale farms reporting main markets by region ............................ 125 Table 4.1.7 Number of Large scale farms reporting main marketing problem by region .......... 126 Table 4.1.8 Area Planted, Iriigated Area, Quantity Harvested, Quantity Sold and Quantity Stored in Large Scale Farms by Type of Cash Crops.............. 127 Table 4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region ........................................................................ 128 Table 4.1.10 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region ........................................................................ 135 Table 4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region .............. 150 Table 4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region .............. 163 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 89 Table 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region .............. 175 AGRICULTURE CREDIT Table 6.1.1 AGRICULTURE CREDIT: Number and Percent of Agriculture Holdings Receiving Credit by Region During the 2007/08 Agriculture Year ....... 191 Table 6.1.2 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year( Labour) ............ 192 Table 6.1.3 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year ........................... 193 Table 6.1.4 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year ........................... 194 Table 6.1.5 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year ........................... 195 Table 6.1.6 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year ........................... 196 Table 6.1.7 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year ........................... 197 Table 6.1.8 AGRICUTURE CREDIT: Number of Holdings Who Did Not Receive Credit by Reason and Region During 2007/08 Agriculture Year ............. 198 RANK OF LIVESTOCK MARKET OUTLETS Table 7.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year .......................... 200 LIVESTOCK PRODUCTION Table 9.1.1 LIVESTOCK PRODUCTION Total Number of Large scale farms Rearing Cattle by Region during 2007/08 Agriculture Year .................................. 206 Table 9.1.2 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Goats by Region during 2007/08 Agriculture Year .................................. 206 Table 9.1.4 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Pigs by Region during 2007/08 Agriculture Year .................................... 207 Table 9.1.3 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Sheeps by Region during 2007/08 Agriculture Year .......................................................... 207 Table 9.1.5 LIVESTOCK PRODUCTION Number of cattle by Region .................................. 208 Table 9.1.6 Cattle Production: Number of Farms Rearing Cattle by Herd Size........................ 208 Table 9.1.7 Number of Goats by Region ................................................................................... 209 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 90 Table 9.1.9 Number of sheeps by region ................................................................................... 210 Table 9.1.10 Sheep Production: Number of Farms Rearing Sheep by Herd Size ....................... 210 Table 9.1.12 PigsProduction: Number of Farms Rearing Pig by Herd Size ............................... 211 Table 9.1.11 Number of Pigs by Region ..................................................................................... 211 Table 9.1.13 Number of Livestock Sold and Average price by Region ...................................... 212 Table 9.1.14 Quantity of livestock products and Average Price by Region ................................ 213 Table 9,1,15 Number of Livestock Sold and Average price by Sales Market ............................ 214 Table 9.1.16 Quantity of livestock products and Average Price by sales destinations ............... 214 Table 9.1.17 Chicken Popolation in Large Scale Farms as of 31st October 2008 by Region ..... 215 Table 9.1.18 Population of other Livestock as of 31st October 2008 by Region ..................... 216 Table 9.1.19 Chicken Disease by Region ................................................................................... 217 Table 9.1.20 Chicken DIsease: Number infected, Number Trated and Recovered by type of Disease ................................................................................. 219 Table 9.1.21 ANIMAL PRODUCTS: Eggs, Hides and Skins sold, utilized and average price during 2007/08 by Region ......................................................... 220 RANK OF LIVESTOCK MARKET OUTLET Table 9.2.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Livestock by Region, 2007/08 Agricultural Year .... 222 Table 9.2.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year .......... 223 Table 9.2.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year .......... 224 Table 9.2.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year .......... 225 Table 9.2.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year .......... 226 Table 9.3.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year............ 227 Table 9.3.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Goats by Region, 2007/08 Agricultural Year .......... 228 Table 9.3.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year............ 229 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 91 Table 9.3.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year............ 230 Table 9.3.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year............ 231 Table 9.4.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year.......... 232 Table 9.4.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year.......... 233 Table 9.4.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year.......... 234 Table 9.4.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year.......... 235 Table 9.4.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year.......... 236 Table 9.5.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year ...... 237 Table 9.5.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year ...... 238 Table 9.5.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year ...... 239 Table 9.5.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year ...... 240 Table 9.5.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year ...... 241 Table 9.6.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year ............ 242 Table 9.6.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year ............ 243 Table 9.6.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year ............ 244 Table 9.6.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year ............ 245 Table 9.6.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year ............ 246 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 92 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES Table 9.7.1 ACCESS TO SERVICES: Number, percent and average distance to Livestock functional Livestock Infrastructure and Srvices by tpe of Service ........ 248 Table 9.8.1 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: Cattle DIP ................................................. 250 Table 9.8.2 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: SPRAY RACE ......................................... 251 Table 9.8.3 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HAND POWERD SPRAYER ................. 252 Table 9.8,4 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: CATTLE CRASH .................................... 253 Table 9.8.5 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: PRIMARY MARKET ............................. 254 Table 9.8.6 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: ABBOTOUR ............................................ 255 Table 9.8.7 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: SLUGHTER SLAB ................................. 256 Table 9.8.8 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HIDES/SKIN SHED ................................ 257 Table 9.8.9 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: INPUT SUPPLY ...................................... 258 Table 9.8.10 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: VERTERINARY CLINIC ....................... 259 Table 9.8.11 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HOLDING GROUND ............................. 260 Table 9.8.12 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: WATERING POINT ............................... 261 Table 9.8.13 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: DRENCHER ............................................ 262 FARM EMPLOYMENT Table 10.2 Number of permanent employee by category of employment and Region: GOVERNMENT OPERATORS........................................................ 264 Table 10.3 Farm Employment: Number of Employee by type of employment and Region: ALL .................................................................................................... 268 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 93 Table 10.4 Number of permanent employee by category of employment and Region: PARASTATAL OPERATORS.......................................................... 258 Table 10.5 Number of permanent employee by category of employment and Region: PRIVATE REGISTERD OPERATORS ............................................ 260 Table 10.7 Number of Temporary employee by category of employment and Region: GOVERNMENT OPERATORS........................................................ 270 OUTGROWER SCHEME Table 11.1 OUTGROWER SCHEME: Number of of famrs and Area under outgrower scheme (Hectare) by Region ....................................................... 275 Table 11.2 OUTGROWER SCHEME: Number of of famrs and Service provided under outgrower scheme by Region ........................................................ 276 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 94 APPENDIX II: TABLES TABLES1.1 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings (ALL OPERATORS) Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 4,863 15 46,554 5 12,362 7 . 0 63,779 27 Arusha 22,629 69 20,099 8 9,800 20 191 7 52,719 104 Kilimanjaro 12,912 41 29,927 5 6,106 15 150 2 49,095 63 Tanga 105,151 82 11,413 11 9,262 20 . 0 125,825 113 Morogoro 77,404 28 12,115 13 24,967 31 389 1 114,875 73 Pwani 99,355 25 67,267 32 2,623 10 . 0 169,245 67 Dar es salaam 227 5 243 18 400 9 . 0 870 32 Lindi 10,109 9 1,323 3 2,580 2 . 0 14,012 14 Mtwara 1,560 28 11,411 3 1,873 7 . 0 14,844 38 Ruvuma 10,143 22 4,202 7 18,375 14 . 0 32,720 43 Iringa 50,586 39 24,624 27 17,373 38 12 1 92,594 105 Mbeya 9,510 22 3,124 5 6,994 11 . 0 19,628 38 Singida 2,297 23 12,531 3 1,234 3 . 0 16,062 29 Tabora 3,596 10 . 0 169 2 . 0 3,765 12 Rukwa . 0 27,200 2 23,300 6 . 0 50,500 8 Kigoma 3,692 1 . 0 9,512 5 . 0 13,204 6 Shinyanga . 0 4 2 14 1 . 0 18 3 Kagera 1,296 3 116,285 27 61,300 5 . 0 178,881 35 Mwanza 664 6 9,109 10 2,241 26 . 0 12,014 42 Mara 355 3 5,536 5 14,781 18 . 0 20,672 26 Manyara 34,343 63 7,000 1 17,459 26 . 0 58,802 90 North Unguja 2,688 9 215 2 72 6 . 0 2,975 17 South Unguja 4,026 6 . 0 26 1 . 0 4,052 7 Urban West 696 2 . 0 284 2 . 0 980 4 North Pemba 1,353 7 . 0 34 1 . 0 1,387 8 South Pemba 373 2 . 0 . 0 . 0 373 2 Total 459,827 520 410,181 189 243,140 286 742 11 1,113,890 1,006 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 95 1.2 TYPE OF FARM OWNERSHIP: Number of Holdings by Type of Farm Ownership and Type of Activity Type of Farm Ownership 2.2 Type of Agriculture Holding Crops Only Livestock only Crops and Livestock Production of Flowers Total Government 77 23 54 1 155 Parastatal 10 9 6 0 25 Private registered 227 73 117 10 427 Private Non- registered 65 37 35 0 137 Other 141 47 74 0 262 Total 520 189 286 11 1006 1.3 TYPE OF HOLDING: Number of Holdings by Type of Activity and Region Region 2.2 Type of Agriculture Holding Crops Only Livestock only Crops and Livestock Production of Flowers Total Dodoma 15 5 7 0 27 Arusha 69 8 20 7 104 Kilimanjaro 41 5 15 2 63 Tanga 82 11 20 0 113 Morogoro 28 13 31 1 73 Pwani 25 32 10 0 67 Dar es salaam 5 18 9 0 32 Lindi 9 3 2 0 14 Mtwara 28 3 7 0 38 Ruvuma 22 7 14 0 43 Iringa 39 27 38 1 105 Mbeya 22 5 11 0 38 Singida 23 3 3 0 29 Tabora 10 0 2 0 12 Rukwa 0 2 6 0 8 Kigoma 1 0 5 0 6 Shinyanga 0 2 1 0 3 Kagera 3 27 5 0 35 Mwanza 6 10 26 0 42 Mara 3 5 18 0 26 Manyara 63 1 26 0 90 North Unguja 9 2 6 0 17 South Unguja 6 0 1 0 7 Urban West 2 0 2 0 4 North Pemba 7 0 1 0 8 South Pemba 2 0 0 0 2 Total 520 189 286 11 1006 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 96 TYPE OF FARM OWNERSHIP APPENDIX II Tanzania Agriculture Sample Census - 2007/08 97 1.4 TYPE OF FARM OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Operator /Ownership Region Government Parastatal Private registered Private Non- registered Other Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 18,314 7 37,027 2 766 1 2,995 8 4,677 9 63,779 27 Arusha 8,848 18 1,423 2 38,044 67 1,402 12 3,002 5 52,719 104 Kilimanjaro 771 4 21,181 3 23,359 52 3,050 1 734 3 49,095 63 Tanga 14,791 12 1,826 2 100,469 41 1,268 10 7,472 48 125,825 113 Morogoro 42,755 18 2,500 2 60,550 30 4,955 5 4,115 18 114,875 73 Pwani 24,981 8 43,160 2 69,643 32 26,720 9 4,741 16 169,245 67 Dar es salaam 146 1 69 1 14 5 48 7 593 18 870 32 Lindi 4,893 3 . 0 7,221 4 110 2 1,788 5 14,012 14 Mtwara 7,249 2 . 0 977 8 5,387 4 1,231 24 14,844 38 Ruvuma 15,344 7 . 0 11,291 15 4,170 14 1,915 7 32,720 43 Iringa 24,511 12 810 1 61,672 60 1,757 7 3,843 25 92,594 105 Mbeya 3,419 5 . 0 8,765 15 7,262 17 182 1 19,628 38 Singida 13,930 4 . 0 350 1 . 0 1,782 24 16,062 29 Tabora 1,738 3 124 1 1,667 5 134 1 102 2 3,765 12 Rukwa 12,085 2 20,900 2 17,515 4 . 0 . 0 50,500 8 Kigoma 13,157 4 . 0 . 0 . 0 47 2 13,204 6 Shinyanga . 0 . 0 14 1 4 2 . 0 18 3 Kagera 44,406 7 38,394 3 96,081 25 . 0 . 0 178,881 35 Mwanza 9,731 4 242 1 576 3 189 10 1,276 24 12,014 42 Mara 13,033 11 5 1 6,953 6 106 5 575 3 20,672 26 Manyara 830 3 . 0 51,234 40 4,342 20 2,396 27 58,802 90 North Unguja 934 2 . 0 1,999 12 34 2 8 1 2,975 17 South Unguja 4,007 5 19 1 . 0 26 1 . 0 4,052 7 Urban West 857 3 123 1 . 0 . 0 . 0 980 4 North Pemba 1,387 8 . 0 . 0 . 0 . 0 1,387 8 South Pemba 373 2 . 0 . 0 . 0 . 0 373 2 Total 282,490 155 167,803 25 559,158 427 63,959 137 40,479 262 1.E+06 1,006 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 98 1.5 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings Government Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 41 1 9,543 3 8,730 3 . 0 18,314 7 Arusha 4,811 13 126 1 3,911 4 . 0 8,848 18 Kilimanjaro 580 2 . 0 141 1 50 1 771 4 Tanga 7,967 6 6,144 2 680 4 . 0 14,791 12 Morogoro 24,522 8 9,082 2 9,151 8 . 0 42,755 18 Pwani 7,081 5 17,700 2 200 1 . 0 24,981 8 Dar es salaam . 0 . 0 146 1 . 0 146 1 Lindi 4,870 2 23 1 . 0 . 0 4,893 3 Mtwara . 0 6,175 1 1,074 1 . 0 7,249 2 Ruvuma 1,823 4 1,400 1 12,121 2 . 0 15,344 7 Iringa 2,965 4 15,670 3 5,876 5 . 0 24,511 12 Mbeya 534 3 . 0 2,885 2 . 0 3,419 5 Singida 330 2 12,500 1 1,100 1 . 0 13,930 4 Tabora 1,738 3 . 0 . 0 . 0 1,738 3 Rukwa . 0 . 0 12,085 2 . 0 12,085 2 Kigoma 3,692 1 . 0 9,465 3 . 0 13,157 4 Shinyanga . 0 . 0 . 0 . 0 . 0 Kagera 718 1 30,300 4 13,388 2 . 0 44,406 7 Mwanza 324 2 8,997 1 410 1 . 0 9,731 4 Mara . 0 . 0 13,033 11 . 0 13,033 11 Manyara 830 3 . 0 . 0 . 0 830 3 North Unguja 724 1 210 1 . 0 . 0 934 2 South Unguja 4,007 5 . 0 . 0 . 0 4,007 5 Urban West 696 2 . 0 161 1 . 0 857 3 North Pemba 1,353 7 . 0 34 1 . 0 1,387 8 South Pemba 373 2 . 0 . 0 . 0 373 2 Total 69,979 77 117,870 23 94,591 54 50 1 282,490 155 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 99 1.6 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings Parastatal Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 27 1 37,000 1 . 0 . 0 37,027 2 Arusha 1,423 2 . 0 . 0 . 0 1,423 2 Kilimanjaro 181 2 21,000 1 . 0 . 0 21,181 3 Tanga 590 1 . 0 1,236 1 . 0 1,826 2 Morogoro . 0 . 0 2,500 2 . 0 2,500 2 Pwani . 0 43,160 2 . 0 . 0 43,160 2 Dar es salaam . 0 69 1 . 0 . 0 69 1 Lindi . 0 . 0 . 0 . 0 . 0 Mtwara . 0 . 0 . 0 . 0 . 0 Ruvuma . 0 . 0 . 0 . 0 . 0 Iringa 810 1 . 0 . 0 . 0 810 1 Mbeya . 0 . 0 . 0 . 0 . 0 Singida . 0 . 0 . 0 . 0 . 0 Tabora 124 1 . 0 . 0 . 0 124 1 Rukwa . 0 20,000 1 900 1 . 0 20,900 2 Kigoma . 0 . 0 . 0 . 0 . 0 Shinyanga . 0 . 0 . 0 . 0 . 0 Kagera . 0 21,394 2 17,000 1 . 0 38,394 3 Mwanza 242 1 . 0 . 0 . 0 242 1 Mara . 0 5 1 . 0 . 0 5 1 Manyara . 0 . 0 . 0 . 0 . 0 North Unguja . 0 . 0 . 0 . 0 . 0 South Unguja 19 1 . 0 . 0 . 0 19 1 Urban West . 0 . 0 123 1 . 0 123 1 North Pemba . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 Total 3,416 10 142,628 9 21,759 6 . 0 167,803 25 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 100 1.7 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings Private registered Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 766 1 . 0 . 0 . 0 766 1 Arusha 14,942 44 19,964 6 2,947 10 191 7 38,044 67 Kilimanjaro 11,417 34 5,877 3 5,965 14 100 1 23,359 52 Tanga 89,313 32 4,676 2 6,480 7 . 0 100,469 41 Morogoro 47,896 16 2,114 4 10,151 9 389 1 60,550 30 Pwani 65,583 15 1,991 11 2,069 6 . 0 69,643 32 Dar es salaam . 0 14 5 . 0 . 0 14 5 Lindi 4,721 3 . 0 2,500 1 . 0 7,221 4 Mtwara 493 5 . 0 484 3 . 0 977 8 Ruvuma 4,566 8 1,839 1 4,886 6 . 0 11,291 15 Iringa 43,988 24 7,109 13 10,563 22 12 1 61,672 60 Mbeya 5,018 8 96 2 3,651 5 . 0 8,765 15 Singida 350 1 . 0 . 0 . 0 350 1 Tabora 1,667 5 . 0 . 0 . 0 1,667 5 Rukwa . 0 7,200 1 10,315 3 . 0 17,515 4 Kigoma . 0 . 0 . 0 . 0 . 0 Shinyanga . 0 . 0 14 1 . 0 14 1 Kagera 578 2 64,591 21 30,912 2 . 0 96,081 25 Mwanza . 0 6 1 570 2 . 0 576 3 Mara 280 1 5,009 1 1,664 4 . 0 6,953 6 Manyara 28,804 21 7,000 1 15,430 18 . 0 51,234 40 North Unguja 1,940 7 5 1 54 4 . 0 1,999 12 South Unguja . 0 . 0 . 0 . 0 . 0 Urban West . 0 . 0 . 0 . 0 . 0 North Pemba . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 Total 322,321 227 127,490 73 108,655 117 692 10 559,158 427 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 101 1.8 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings Private Non- registered Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 2,872 5 11 1 112 2 . 0 2,995 8 Arusha 1,158 9 9 1 235 2 . 0 1,402 12 Kilimanjaro . 0 3,050 1 . 0 . 0 3,050 1 Tanga 749 4 457 4 62 2 . 0 1,268 10 Morogoro 4,344 2 200 1 411 2 . 0 4,955 5 Pwani 26,344 2 361 6 15 1 . 0 26,720 9 Dar es salaam . 0 12 5 36 2 . 0 48 7 Lindi 110 2 . 0 . 0 . 0 110 2 Mtwara 155 3 5,232 1 . 0 . 0 5,387 4 Ruvuma 2,576 7 463 3 1,131 4 . 0 4,170 14 Iringa 677 3 1,047 2 33 2 . 0 1,757 7 Mbeya 3,958 11 3,028 3 276 3 . 0 7,262 17 Singida . 0 . 0 . 0 . 0 . 0 Tabora . 0 . 0 134 1 . 0 134 1 Rukwa . 0 . 0 . 0 . 0 . 0 Kigoma . 0 . 0 . 0 . 0 . 0 Shinyanga . 0 4 2 . 0 . 0 4 2 Kagera . 0 . 0 . 0 . 0 . 0 Mwanza . 0 23 5 166 5 . 0 189 10 Mara . 0 23 2 84 3 . 0 106 5 Manyara 2,932 16 . 0 1,410 4 . 0 4,342 20 North Unguja 24 1 . 0 10 1 . 0 34 2 South Unguja . 0 . 0 26 1 . 0 26 1 Urban West . 0 . 0 . 0 . 0 . 0 North Pemba . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 Total 45,899 65 13,920 37 4,140 35 . 0 63,959 137 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 102 1.9 TYPE OF HOLDING: Number of Holdings and Area (in Hectares) of Large Scale Farms By Region and type of Holdings Other Region Crops Only Livestock only Crops and Livestock Production of Flowers Total Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Area (Ha) Number of Holdings Dodoma 1,157 7 . 0 3,520 2 . 0 4,677 9 Arusha 295 1 . 0 2,707 4 . 0 3,002 5 Kilimanjaro 734 3 . 0 . 0 . 0 734 3 Tanga 6,532 39 136 3 804 6 . 0 7,472 48 Morogoro 642 2 719 6 2,754 10 . 0 4,115 18 Pwani 347 3 4,055 11 339 2 . 0 4,741 16 Dar es salaam 227 5 148 7 218 6 . 0 593 18 Lindi 408 2 1,300 2 80 1 . 0 1,788 5 Mtwara 912 20 4 1 315 3 . 0 1,231 24 Ruvuma 1,178 3 500 2 237 2 . 0 1,915 7 Iringa 2,146 7 797 9 900 9 . 0 3,843 25 Mbeya . 0 . 0 182 1 . 0 182 1 Singida 1,617 20 31 2 134 2 . 0 1,782 24 Tabora 67 1 . 0 35 1 . 0 102 2 Rukwa . 0 . 0 . 0 . 0 . 0 Kigoma . 0 . 0 47 2 . 0 47 2 Shinyanga . 0 . 0 . 0 . 0 . 0 Kagera . 0 . 0 . 0 . 0 . 0 Mwanza 98 3 83 3 1,095 18 . 0 1,276 24 Mara 75 2 500 1 . 0 . 0 575 3 Manyara 1,777 23 . 0 619 4 . 0 2,396 27 North Unguja . 0 . 0 8 1 . 0 8 1 South Unguja . 0 . 0 . 0 . 0 . 0 Urban West . 0 . 0 . 0 . 0 . 0 North Pemba . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 Total 18,212 141 8,273 47 13,994 74 . 0 40,479 262 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 103 LAND ACCESS/OWNERSHIP APPENDIX II Tanzania Agriculture Sample Census - 2007/08 104 3.1.1 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region Government Region Area Leased/Certified of ownership Area owned under Customary Law Area Bought from others(not leased/certified) Area Rented from others Area Borrowed from others Area under Compulsory Acquisition TOTAL AREA Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 18,056 6 12 1 12 1 . 0 217 1 17 1 18,314 Arusha 8,272 15 . 0 . 0 . 0 . 0 576 3 8,848 Kilimanjaro 771 4 . 0 . 0 . 0 . 0 . 0 771 Tanga 14,691 9 . 0 60 2 . 0 . 0 40 1 14,791 Morogoro 42,156 13 . 0 20 1 . 0 . 0 579 4 42,755 Pwani 24,981 8 . 0 . 0 . 0 . 0 . 0 24,981 Dar es salaam . 0 . 0 . 0 . 0 . 0 146 1 146 Lindi 4,893 3 . 0 . 0 . 0 . 0 . 0 4,893 Mtwara 7,249 2 . 0 . 0 . 0 . 0 . 0 7,249 Ruvuma 15,344 7 . 0 . 0 . 0 . 0 . 0 15,344 Iringa 16,405 10 . 0 . 0 . 0 . 0 8,106 2 24,511 Mbeya 3,419 5 . 0 . 0 . 0 . 0 . 0 3,419 Singida 13,930 4 . 0 . 0 . 0 . 0 . 0 13,930 Tabora 1,134 2 . 0 4 1 . 0 . 0 600 1 1,738 Rukwa 12,085 2 . 0 . 0 . 0 . 0 . 0 12,085 Kigoma 13,157 4 . 0 . 0 . 0 . 0 . 0 13,157 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera 44,406 7 . 0 . 0 . 0 . 0 . 0 44,406 Mwanza 434 2 . 0 . 0 . 0 . 0 9,297 2 9,731 Mara 12,959 10 3 1 21 2 . 0 . 0 50 1 13,033 Manyara 830 3 . 0 . 0 . 0 . 0 . 0 830 North Unguja . 0 . 0 . 0 . 0 . 0 934 2 934 South Unguja 50 1 . 0 . 0 . 0 . 0 3,957 4 4,007 Urban West . 0 . 0 . 0 . 0 . 0 857 3 857 North Pemba 607 2 . 0 . 0 . 0 . 0 780 6 1,387 South Pemba 373 2 . 0 . 0 . 0 . 0 . 0 373 Total 256,203 121 15 2 117 7 . 0 217 1 25,939 31 282,490 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 105 3.1.2 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region Parastatal Region Area Leased/Certified of ownership Area owned under Customary Law Area Bought from others(not leased/certified) Area Rented from others Area Borrowed from others Area under Compulsory Acquisition TOTAL AREA Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 37,027 2 . 0 . 0 . 0 . 0 . 0 37,027 Arusha 1,423 2 . 0 . 0 . 0 . 0 . 0 1,423 Kilimanjaro 21,181 3 . 0 . 0 . 0 . 0 . 0 21,181 Tanga 1,826 2 . 0 . 0 . 0 . 0 . 0 1,826 Morogoro 1,500 1 . 0 . 0 . 0 . 0 1,000 1 2,500 Pwani 43,160 2 . 0 . 0 . 0 . 0 . 0 43,160 Dar es salaam 69 1 . 0 . 0 . 0 . 0 . 0 69 Lindi . 0 . 0 . 0 . 0 . 0 . 0 - Mtwara . 0 . 0 . 0 . 0 . 0 . 0 - Ruvuma . 0 . 0 . 0 . 0 . 0 . 0 - Iringa 810 1 . 0 . 0 . 0 . 0 . 0 810 Mbeya . 0 . 0 . 0 . 0 . 0 . 0 - Singida . 0 . 0 . 0 . 0 . 0 . 0 - Tabora 124 1 . 0 . 0 . 0 . 0 . 0 124 Rukwa 20,900 2 . 0 . 0 . 0 . 0 . 0 20,900 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera 38,394 3 . 0 . 0 . 0 . 0 . 0 38,394 Mwanza 242 1 . 0 . 0 . 0 . 0 . 0 242 Mara 5 1 . 0 . 0 . 0 . 0 . 0 5 Manyara . 0 . 0 . 0 . 0 . 0 . 0 - North Unguja . 0 . 0 . 0 . 0 . 0 . 0 - South Unguja . 0 . 0 . 0 5 1 . 0 14 1 19 Urban West 123 1 . 0 . 0 . 0 . 0 . 0 123 North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 166,784 23 . 0 . 0 5 1 . 0 1,014 2 167,803 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 106 3.1.3 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region Private registered Region Area Leased/Certified of ownership Area owned under Customary Law Area Bought from others(not leased/certified) Area Rented from others Area Borrowed from others Area under Compulsory Acquisition TOTAL AREA Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma . 0 766 1 . 0 . 0 . 0 . 0 766 Arusha 37,944 66 . 0 . 0 44 1 . 0 56 1 38,044 Kilimanjaro 23,351 52 . 0 . 0 . 0 . 0 8 1 23,359 Tanga 100,284 39 145 1 . 0 . 0 . 0 40 1 100,469 Morogoro 60,204 29 . 0 6 1 . 0 . 0 340 1 60,550 Pwani 69,540 31 . 0 103 5 . 0 . 0 . 0 69,643 Dar es salaam 7 2 . 0 2 1 . 0 2 1 3 1 14 Lindi 7,221 4 . 0 . 0 . 0 . 0 . 0 7,221 Mtwara 893 6 70 3 14 2 . 0 . 0 . 0 977 Ruvuma 9,167 13 220 4 1,904 3 . 0 . 0 . 0 11,291 Iringa 50,901 53 60 1 10,006 2 60 3 1 1 644 4 61,672 Mbeya 8,765 15 . 0 . 0 . 0 . 0 . 0 8,765 Singida . 0 350 1 . 0 . 0 . 0 . 0 350 Tabora 1,561 5 70 1 36 1 . 0 . 0 . 0 1,667 Rukwa 17,515 4 . 0 . 0 . 0 . 0 . 0 17,515 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga 14 1 . 0 . 0 . 0 . 0 . 0 14 Kagera 96,081 25 . 0 . 0 . 0 . 0 . 0 96,081 Mwanza 558 3 9 1 . 0 . 0 9 1 . 0 576 Mara 6,793 5 . 0 . 0 . 0 . 0 160 1 6,953 Manyara 50,637 38 . 0 57 2 40 1 500 1 . 0 51,234 North Unguja 1,992 12 2 1 2 1 . 0 . 0 3 1 1,999 South Unguja . 0 . 0 . 0 . 0 . 0 . 0 - Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 543,426 403 1,692 14 12,130 18 144 5 512 4 1,254 11 559,158 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 107 3.1.4 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region Private Non- registered Region Area Leased/Certified of ownership Area owned under Customary Law Area Bought from others(not leased/certified) Area Rented from others Area Borrowed from others Area under Compulsory Acquisition TOTAL AREA Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 90 2 454 6 645 3 1,806 3 . 0 . 0 2,995 Arusha 1,402 12 . 0 . 0 . 0 . 0 . 0 1,402 Kilimanjaro 3,050 1 . 0 . 0 . 0 . 0 . 0 3,050 Tanga 594 2 51 4 69 4 2 1 236 1 316 6 1,268 Morogoro 4,725 3 30 1 . 0 . 0 . 0 200 1 4,955 Pwani 26,539 7 150 1 31 2 . 0 . 0 . 0 26,720 Dar es salaam 20 4 24 1 4 1 . 0 . 0 . 0 48 Lindi . 0 110 2 . 0 . 0 . 0 . 0 110 Mtwara 5,232 1 93 3 62 3 . 0 . 0 . 0 5,387 Ruvuma 3,397 7 360 2 169 7 19 3 25 1 200 2 4,170 Iringa 1,444 5 238 2 54 3 . 0 6 1 15 1 1,757 Mbeya 7,194 14 8 2 0 1 20 1 . 0 40 1 7,262 Singida . 0 . 0 . 0 . 0 . 0 . 0 - Tabora . 0 134 1 . 0 . 0 . 0 . 0 134 Rukwa . 0 . 0 . 0 . 0 . 0 . 0 - Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga 4 2 . 0 . 0 . 0 . 0 . 0 4 Kagera . 0 . 0 . 0 . 0 . 0 . 0 - Mwanza 3 1 119 9 67 3 . 0 . 0 . 0 189 Mara 23 2 . 0 . 0 . 0 . 0 84 3 106 Manyara 3,687 11 384 10 127 5 144 4 . 0 . 0 4,342 North Unguja 28 2 6 1 . 0 . 0 . 0 . 0 34 South Unguja 10 1 14 1 2 1 . 0 . 0 . 0 26 Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 57,442 77 2,175 46 1,230 33 1,991 12 267 3 855 14 63,959 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 108 3.1.5 LAND ACCESS/ OWNERSHIP: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Ownership and Region Other Region Area Leased/Certified of ownership Area owned under Customary Law Area Bought from others(not leased/certified) Area Rented from others Area Borrowed from others Area under Compulsory Acquisition TOTAL AREA Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 57 2 4,482 7 118 3 20 1 . 0 . 0 4,677 Arusha 2,496 3 506 2 . 0 . 0 . 0 . 0 3,002 Kilimanjaro 734 3 . 0 . 0 . 0 . 0 . 0 734 Tanga 3,874 16 1,073 17 323 12 . 0 1,269 10 933 8 7,472 Morogoro 671 7 383 6 3,051 5 . 0 2 1 8 1 4,115 Pwani 4,104 12 108 2 20 1 . 0 400 1 109 2 4,741 Dar es salaam 274 8 100 3 66 3 8 1 . 0 145 5 593 Lindi 408 2 . 0 . 0 . 0 . 0 1,380 3 1,788 Mtwara 280 6 302 11 648 17 . 0 . 0 . 0 1,231 Ruvuma 1,070 3 730 3 50 1 35 1 30 1 . 0 1,915 Iringa 2,921 15 847 11 1 1 . 0 . 0 74 2 3,843 Mbeya . 0 182 1 . 0 . 0 . 0 . 0 182 Singida 759 7 918 20 . 0 105 3 . 0 . 0 1,782 Tabora 67 1 23 1 2 1 10 1 . 0 . 0 102 Rukwa . 0 . 0 . 0 . 0 . 0 . 0 - Kigoma 30 2 . 0 . 0 . 0 1 1 16 1 47 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera . 0 . 0 . 0 . 0 . 0 . 0 - Mwanza 100 1 1,121 22 7 1 25 3 5 1 18 3 1,276 Mara 20 1 544 3 . 0 . 0 . 0 11 2 575 Manyara 581 4 221 7 422 11 532 7 10 1 630 13 2,396 North Unguja 8 1 . 0 . 0 . 0 . 0 . 0 8 South Unguja . 0 . 0 . 0 . 0 . 0 . 0 - Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 18,454 94 11,541 116 4,708 56 735 17 1,717 16 3,324 40 40,479 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 109 3.2.1 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region (ALL OPERATORS) Region Area under Temporary Mono-crops (eg maize only) Area under Temporary Mixed crops (eg maize & beans) Area under Permanent Mono-crops (eg Sisal only) Area under Permanent Mixed crops (eg bananas & coffee) Area under Permanent/Annual mix (eg bananas & maize) Area under Permanent/Pasture mix (eg orange & pasture) Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 3,536 18 2,908 8 36 4 . 0 12 1 . 0 Arusha 5,167 56 3,016 22 2,819 33 774 10 . 0 280 3 Kilimanjaro 3,644 28 1,741 17 6,484 32 237 11 90 7 . 0 Tanga 1,531 36 112 3 49,040 73 843 14 709 10 489 4 Morogoro 3,433 47 900 2 13,928 25 322 10 349 4 215 5 Pwani 1,448 12 360 2 11,999 20 2,203 7 173 5 447 8 Dar es salaam 49 9 21 2 195 7 58 6 49 2 8 3 Lindi 313 6 14 2 1,944 7 120 1 . 0 . 0 Mtwara 342 15 79 10 1,223 29 209 6 144 6 180 1 Ruvuma 2,036 37 37 7 243 16 22 6 4 3 2 1 Iringa 3,633 61 30 11 6,589 37 50 4 3 2 598 4 Mbeya 4,678 26 . 0 2,286 20 12 4 . 0 4 1 Singida 1,486 28 . 0 . 0 . 0 30 1 80 1 Tabora 383 11 23 1 1 1 . 0 . 0 16 1 Rukwa 766 6 13 2 15 3 . 0 . 0 . 0 Kigoma 46 6 4 2 519 5 2 1 6 1 3 1 Shinyanga 5 1 1 1 . 0 . 0 . 0 . 0 Kagera 1,782 3 5 1 16,841 6 215 2 . 0 1,400 1 Mwanza 273 25 494 27 . 0 . 0 19 2 . 0 Mara 1,208 21 810 6 93 6 12 4 2 1 125 2 Manyara 21,055 73 553 19 2,806 26 76 2 1,873 12 112 1 North Unguja 46 10 11 3 1,446 9 87 11 19 3 32 3 South Unguja 1 1 1 1 13 1 17 1 9 1 4 1 Urban West 2 1 40 1 93 2 3 1 45 1 . 0 North Pemba 32 4 . 0 653 7 79 2 . 0 7 2 South Pemba 15 2 . 0 16 2 5 1 . 0 . 0 Total 56,910 543 11,173 150 119,281 371 5,345 104 3,535 62 4,002 43 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 110 Cont 3.2.1 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region (ALL OPERATORS) Region Area under Pasture only Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma 47,346 12 3,157 10 5,140 8 372 7 629 2 109 5 535 6 63,779 Arusha 23,380 32 9,582 35 1,799 25 1,363 27 750 6 1,521 16 2,268 16 52,719 Kilimanjaro 20,601 21 11,904 18 126 5 187 12 . 0 3,625 17 457 11 49,095 Tanga 12,486 27 17,706 32 11,656 15 1,867 27 . 0 6,270 22 23,118 50 125,825 Morogoro 24,277 43 12,604 22 12,959 21 1,428 15 . 0 36,310 18 8,150 17 114,875 Pwani 41,153 37 37,176 16 4,703 10 134 11 . 0 21,266 13 48,183 16 169,245 Dar es salaam 274 14 36 6 46 3 33 3 2 1 43 7 57 8 870 Lindi 2,918 7 1,022 2 1,000 2 2,642 2 . 0 1,219 2 2,820 3 14,012 Mtwara 8,112 5 58 3 4,108 4 8 3 . 0 203 7 178 3 14,844 Ruvuma 5,541 24 2,496 25 18,023 31 227 17 513 3 1,895 9 1,681 15 32,720 Iringa 21,478 58 1,858 36 12,073 44 24,782 61 780 5 7,999 29 12,720 42 92,594 Mbeya 3,291 15 1,492 13 3,047 13 976 12 196 3 959 14 2,686 17 19,628 Singida 12,696 14 269 13 575 9 1 1 97 5 407 2 421 13 16,062 Tabora 623 8 280 11 1,569 11 374 6 . 0 230 5 266 4 3,765 Rukwa 29,842 7 8,235 5 2,867 5 78 5 . 0 270 3 8,414 4 50,500 Kigoma 1,622 2 5,383 6 2,360 3 1,954 4 8 1 . 0 1,297 5 13,204 Shinyanga 10 2 2 1 . 0 . 0 . 0 . 0 . 0 18 Kagera 136,134 29 2,109 4 2,430 9 6,046 7 . 0 3,017 3 8,902 5 178,881 Mwanza 9,395 17 443 14 120 14 71 11 . 0 258 7 941 25 12,014 Mara 9,372 16 1,904 11 1,194 9 845 11 . 0 2,064 3 3,045 14 20,672 Manyara 7,580 31 14,544 40 1,149 11 1,069 7 144 5 4,130 18 3,711 29 58,802 North Unguja 100 1 10 1 . 0 210 2 . 0 95 1 919 3 2,975 South Unguja 3 1 . 0 2,962 5 985 4 . 0 15 4 42 3 4,052 Urban West 5 1 10 1 270 2 294 4 . 0 30 3 188 3 980 North Pemba 240 2 6 1 60 1 8 1 . 0 8 1 294 2 1,387 South Pemba . 0 . 0 15 1 20 1 . 0 . 0 302 1 373 Total 418,480 426 132,284 326 90,250 261 45,973 261 3,119 31 91,943 209 131,594 315 1,113,890 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 111 3.2.2 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region (GOVERNMENT OPERATORS) Region Area under Temporary Mono- crops (eg maize only) Area under Temporary Mixed crops (eg maize & beans) Area under Permanent Mono- crops (eg Sisal only) Area under Permanent Mixed crops (eg bananas & coffee) Area under Permanent/Annual mix (eg bananas & maize) Area under Permanent/Pasture mix (eg orange & pasture) Area under Pasture only Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 1,564 4 41 1 4 1 . 0 . 0 . 0 9,368 6 Arusha 1,028 6 1,483 10 60 1 . 0 . 0 . 0 1,428 7 Kilimanjaro 116 3 3 1 150 1 3 1 . 0 . 0 17 1 Tanga 170 6 . 0 4,668 3 10 1 3 1 300 1 4,137 6 Morogoro 1,804 14 100 1 654 6 213 5 284 3 121 3 14,363 12 Pwani 84 4 60 1 127 4 . 0 . 0 296 2 11,602 5 Dar es salaam . 0 . 0 146 1 . 0 . 0 . 0 . 0 Lindi 28 2 . 0 26 1 . 0 . 0 . 0 903 3 Mtwara 38 1 . 0 . 0 . 0 . 0 . 0 2,842 2 Ruvuma 71 3 3 1 106 3 12 1 . 0 . 0 3,360 4 Iringa 827 7 1 1 41 3 1 1 . 0 . 0 10,212 8 Mbeya 611 4 . 0 79 3 6 1 . 0 4 1 182 3 Singida 127 3 . 0 . 0 . 0 . 0 . 0 12,530 3 Tabora 30 3 . 0 . 0 . 0 . 0 . 0 526 3 Rukwa 172 2 . 0 . 0 . 0 . 0 . 0 8 1 Kigoma 39 4 1 1 511 4 . 0 . 0 3 1 1,622 2 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 . 0 Kagera 1,780 2 . 0 720 2 . 0 . 0 . 0 29,359 4 Mwanza 56 3 . 0 . 0 . 0 . 0 . 0 9,027 2 Mara 808 11 792 4 36 4 4 2 2 1 75 1 4,177 7 Manyara 190 2 60 1 . 0 . 0 . 0 . 0 . 0 North Unguja . 0 . 0 . 0 . 0 . 0 . 0 100 1 South Unguja . 0 1 1 . 0 . 0 9 1 . 0 . 0 Urban West . 0 40 1 13 1 3 1 45 1 . 0 . 0 North Pemba 32 4 . 0 653 7 79 2 . 0 7 2 240 2 South Pemba 15 2 . 0 16 2 5 1 . 0 . 0 . 0 Total 9,590 90 2,585 24 8,010 47 336 16 342 7 806 11 116,003 82 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 112 3.2.2 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Region Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma 2,486 3 4,382 5 363 4 . 0 91 3 15 1 18,314 Arusha 1,831 9 963 4 427 3 . 0 760 5 868 4 8,848 Kilimanjaro 375 3 . 0 70 2 . 0 12 1 25 1 771 Tanga 206 4 3,890 3 22 3 . 0 38 2 1,347 6 14,791 Morogoro 6,750 8 11,003 8 1,272 7 . 0 5,446 7 745 5 42,755 Pwani 9,429 4 1,030 2 47 4 . 0 870 5 1,436 3 24,981 Dar es salaam . 0 . 0 . 0 . 0 . 0 . 0 146 Lindi 122 1 1,000 2 2,642 2 . 0 160 1 12 1 4,893 Mtwara . 0 4,096 2 3 1 . 0 170 1 100 1 7,249 Ruvuma 445 4 11,159 5 49 5 12 1 . 0 127 2 15,344 Iringa 551 5 700 5 3,596 7 100 1 3,192 6 5,290 8 24,511 Mbeya 399 4 909 2 212 3 . 0 291 3 726 2 3,419 Singida 86 2 557 1 . 0 . 0 400 1 230 2 13,930 Tabora 57 3 934 3 25 2 . 0 132 1 34 1 1,738 Rukwa 1,375 2 2,590 1 56 2 . 0 70 2 7,813 2 12,085 Kigoma 5,377 4 2,359 2 1,953 3 8 1 . 0 1,284 3 13,157 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera 1,702 2 1,816 2 5,829 2 . 0 3,000 1 200 1 44,406 Mwanza 244 2 . 0 . 0 . 0 205 2 199 2 9,731 Mara 1,676 6 1,139 6 710 6 . 0 2,064 3 1,553 9 13,033 Manyara 340 2 . 0 . 0 . 0 . 0 240 1 830 North Unguja 10 1 . 0 10 1 . 0 95 1 719 2 934 South Unguja . 0 2,962 5 985 4 . 0 9 2 41 2 4,007 Urban West . 0 270 2 293 3 . 0 25 2 168 2 857 North Pemba 6 1 60 1 8 1 . 0 8 1 294 2 1,387 South Pemba . 0 15 1 20 1 . 0 . 0 302 1 373 Total 33,467 70 51,834 62 18,592 66 120 3 17,039 50 23,768 64 282,490 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 113 3.2.3 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Parastatal Region Area under Temporary Mono-crops (eg maize only) Area under Temporary Mixed crops (eg maize & beans) Area under Permanent Mono-crops (eg Sisal only) Area under Permanent Mixed crops (eg bananas & coffee) Area under Permanent/Annual mix (eg bananas & maize) Area under Permanent/Pasture mix (eg orange & pasture) Area under Pasture only Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma . 0 . 0 27 1 . 0 . 0 . 0 37,000 1 Arusha 480 1 410 1 . 0 . 0 . 0 . 0 . 0 Kilimanjaro 10 1 32 1 80 2 . 0 40 1 . 0 16,000 1 Tanga 120 1 . 0 318 1 . 0 . 0 . 0 1,116 1 Morogoro 23 2 800 1 . 0 3 1 . 0 93 1 614 2 Pwani . 0 . 0 . 0 . 0 . 0 . 0 23,080 2 Dar es salaam . 0 . 0 . 0 . 0 . 0 . 0 69 1 Lindi . 0 . 0 . 0 . 0 . 0 . 0 . 0 Mtwara . 0 . 0 . 0 . 0 . 0 . 0 . 0 Ruvuma . 0 . 0 . 0 . 0 . 0 . 0 . 0 Iringa 18 1 . 0 14 1 . 0 . 0 . 0 51 1 Mbeya . 0 . 0 . 0 . 0 . 0 . 0 . 0 Singida . 0 . 0 . 0 . 0 . 0 . 0 . 0 Tabora 46 1 . 0 . 0 . 0 . 0 16 1 11 1 Rukwa 302 1 . 0 6 1 . 0 . 0 . 0 20,220 2 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 . 0 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 . 0 Kagera . 0 5 1 8,332 1 10 1 . 0 . 0 21,439 3 Mwanza . 0 . 0 . 0 . 0 . 0 . 0 . 0 Mara . 0 . 0 . 0 . 0 . 0 . 0 1 1 Manyara . 0 . 0 . 0 . 0 . 0 . 0 . 0 North Unguja . 0 . 0 . 0 . 0 . 0 . 0 . 0 South Unguja 1 1 . 0 13 1 . 0 . 0 . 0 . 0 Urban West 2 1 . 0 80 1 . 0 . 0 . 0 5 1 North Pemba . 0 . 0 . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 . 0 . 0 Total 1,002 10 1,247 4 8,870 9 13 2 40 1 109 2 119,606 17 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 114 Cont...3.2.3 AND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Parastatal Region Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma . 0 . 0 . 0 . 0 . 0 . 0 37,027 Arusha . 0 20 1 5 1 . 0 . 0 508 1 1,423 Kilimanjaro 5,000 1 10 1 . 0 . 0 1 1 8 1 21,181 Tanga . 0 . 0 4 1 . 0 . 0 268 1 1,826 Morogoro . 0 217 1 100 1 . 0 200 1 450 1 2,500 Pwani 20,032 2 8 1 20 1 . 0 20 1 . 0 43,160 Dar es salaam . 0 . 0 . 0 . 0 . 0 . 0 69 Lindi . 0 . 0 . 0 . 0 . 0 . 0 - Mtwara . 0 . 0 . 0 . 0 . 0 . 0 - Ruvuma . 0 . 0 . 0 . 0 . 0 . 0 - Iringa 48 1 308 1 265 1 . 0 . 0 106 1 810 Mbeya . 0 . 0 . 0 . 0 . 0 . 0 - Singida . 0 . 0 . 0 . 0 . 0 . 0 - Tabora 23 1 3 1 25 1 . 0 . 0 . 0 124 Rukwa 153 1 215 1 4 1 . 0 . 0 . 0 20,900 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera . 0 5 1 5 1 . 0 . 0 8,598 1 38,394 Mwanza . 0 . 0 4 1 . 0 . 0 238 1 242 Mara 4 1 . 0 . 0 . 0 . 0 . 0 5 Manyara . 0 . 0 . 0 . 0 . 0 . 0 - North Unguja . 0 . 0 . 0 . 0 . 0 . 0 - South Unguja . 0 . 0 . 0 . 0 5 1 . 0 19 Urban West 10 1 . 0 1 1 . 0 5 1 20 1 123 North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 25,270 8 786 8 433 10 . 0 231 5 10,196 8 167,803 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 115 3.2.4 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Private registered Region Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma 140 1 20 1 . 0 . 0 . 0 . 0 766 Arusha 7,537 23 607 17 446 17 639 2 754 10 486 7 38,044 Kilimanjaro 6,529 14 32 3 112 9 . 0 562 14 424 9 23,359 Tanga 16,945 16 7,599 10 1,581 17 . 0 5,625 15 20,341 22 100,469 Morogoro 5,800 10 1,730 8 11 2 . 0 30,611 7 3,618 6 60,550 Pwani 7,645 6 3,599 3 16 3 . 0 518 3 46,707 10 69,643 Dar es salaam 6 2 . 0 . 0 . 0 . 0 . 0 14 Lindi 900 1 . 0 . 0 . 0 1,059 1 2,800 1 7,221 Mtwara 15 2 10 1 1 1 . 0 . 0 . 0 977 Ruvuma 725 10 5,738 12 116 7 500 1 683 3 1,349 6 11,291 Iringa 1,004 18 10,965 30 19,801 38 502 3 4,717 18 6,378 17 61,672 Mbeya 77 6 1,793 7 755 7 176 2 430 7 281 8 8,765 Singida . 0 . 0 . 0 . 0 . 0 . 0 350 Tabora 173 4 576 5 322 2 . 0 78 3 203 2 1,667 Rukwa 6,707 2 62 3 18 2 . 0 200 1 601 2 17,515 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 14 Kagera 407 2 609 6 212 4 . 0 17 2 104 3 96,081 Mwanza 142 2 90 2 30 2 . 0 9 2 1 1 576 Mara 212 3 25 2 55 3 . 0 . 0 1,080 2 6,953 Manyara 13,311 22 911 5 1,058 4 . 0 4,058 12 2,191 15 51,234 North Unguja . 0 . 0 200 1 . 0 . 0 200 1 1,999 South Unguja . 0 . 0 . 0 . 0 . 0 . 0 - Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 68,275 144 34,366 115 24,734 119 1,817 8 49,321 98 86,764 112 559,158 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 116 3.2.5 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Private Non- registered Region Area under Temporary Mono-crops (eg maize only) Area under Temporary Mixed crops (eg maize & beans) Area under Permanent Mono-crops (eg Sisal only) Area under Permanent Mixed crops (eg bananas & coffee) Area under Permanent/Annual mix (eg bananas & maize) Area under Permanent/Pasture mix (eg orange & pasture) Area under Pasture only Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Dodoma 269 6 2,557 3 5 2 . 0 . 0 . 0 12 2 Arusha 723 7 147 4 171 1 . 0 . 0 . 0 8 1 Kilimanjaro . 0 . 0 . 0 . 0 . 0 . 0 . 0 Tanga 62 5 10 1 452 6 . 0 22 1 120 1 312 5 Morogoro 22 3 . 0 1,572 2 . 0 . 0 . 0 549 3 Pwani 4 1 . 0 6,595 2 . 0 2 1 18 3 339 6 Dar es salaam 10 2 . 0 10 3 10 2 . 0 8 3 9 4 Lindi . 0 . 0 110 2 . 0 . 0 . 0 . 0 Mtwara . 0 20 3 122 3 . 0 . 0 . 0 5,232 1 Ruvuma 1,008 14 6 3 85 3 . 0 1 1 . 0 213 7 Iringa 67 6 2 1 411 3 45 1 . 0 . 0 1,051 4 Mbeya 851 13 . 0 232 4 1 1 . 0 . 0 3,036 5 Singida . 0 . 0 . 0 . 0 . 0 . 0 . 0 Tabora 22 1 . 0 1 1 . 0 . 0 . 0 32 1 Rukwa . 0 . 0 . 0 . 0 . 0 . 0 . 0 Kigoma . 0 . 0 . 0 . 0 . 0 . 0 . 0 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 2 1 Kagera . 0 . 0 . 0 . 0 . 0 . 0 . 0 Mwanza 67 4 55 4 . 0 . 0 1 1 . 0 43 9 Mara 44 3 . 0 . 0 . 0 . 0 . 0 36 4 Manyara 1,524 19 120 5 391 4 4 1 . 0 . 0 513 5 North Unguja 2 1 5 1 . 0 15 2 5 1 7 1 . 0 South Unguja . 0 . 0 . 0 17 1 . 0 4 1 3 1 Urban West . 0 . 0 . 0 . 0 . 0 . 0 . 0 North Pemba . 0 . 0 . 0 . 0 . 0 . 0 . 0 South Pemba . 0 . 0 . 0 . 0 . 0 . 0 . 0 Total 4,675 85 2,922 25 10,157 36 92 8 31 5 157 9 11,390 59 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 117 Cont…..3.2.5 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Private Non- registered Region Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma 79 5 1 1 4 2 5 1 18 2 46 2 2,995 Arusha 43 1 9 1 107 3 111 4 . 0 83 2 1,402 Kilimanjaro . 0 . 0 . 0 . 0 3,050 1 . 0 3,050 Tanga . 0 98 1 15 1 . 0 . 0 177 3 1,268 Morogoro 19 1 . 0 . 0 . 0 45 1 2,748 1 4,955 Pwani 2 1 . 0 11 2 . 0 19,741 2 8 1 26,720 Dar es salaam . 0 . 0 . 0 . 0 0 1 1 1 48 Lindi . 0 . 0 . 0 . 0 . 0 . 0 110 Mtwara . 0 . 0 . 0 . 0 13 2 . 0 5,387 Ruvuma 678 6 792 8 40 3 1 1 1,177 3 169 5 4,170 Iringa 75 4 5 1 81 3 . 0 13 1 8 3 1,757 Mbeya 1,014 2 342 3 8 1 20 1 78 3 1,679 7 7,262 Singida . 0 . 0 . 0 . 0 . 0 . 0 - Tabora 12 1 36 1 2 1 . 0 . 0 29 1 134 Rukwa . 0 . 0 . 0 . 0 . 0 . 0 - Kigoma . 0 . 0 . 0 . 0 . 0 . 0 - Shinyanga 2 1 . 0 . 0 . 0 . 0 . 0 4 Kagera . 0 . 0 . 0 . 0 . 0 . 0 - Mwanza 11 3 3 1 9 1 . 0 . 0 . 0 189 Mara 12 1 . 0 . 0 . 0 . 0 14 1 106 Manyara 745 12 218 3 10 2 20 1 38 2 759 7 4,342 North Unguja . 0 . 0 . 0 . 0 . 0 . 0 34 South Unguja . 0 . 0 . 0 . 0 1 1 1 1 26 Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 2,692 38 1,503 20 286 19 157 8 24,174 19 5,722 35 63,959 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 118 Cont……..3.2.6 LAND USE: Number of Holdings and Area (in Hectares) of Large Scale Farms by Different type of Land Use and Region Other Region Area under Fallow Area under Natural Bush Area under Planted Timber Trees Area Rented to others Area Unusable Area of Uncultivated Usable land (excluding fallow) Total Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Number of Holdings Area in Ha Dodoma 452 1 737 1 5 1 624 1 . 0 474 3 4,677 Arusha 171 2 200 2 378 3 . 0 7 1 323 2 3,002 Kilimanjaro . 0 84 1 5 1 . 0 . 0 . 0 734 Tanga 555 12 69 1 245 5 . 0 607 5 985 18 7,472 Morogoro 35 3 9 4 45 5 . 0 8 2 589 4 4,115 Pwani 68 3 66 4 40 1 . 0 117 2 32 2 4,741 Dar es salaam 30 4 46 3 33 3 2 1 43 6 56 7 593 Lindi . 0 . 0 . 0 . 0 . 0 8 1 1,788 Mtwara 43 1 2 1 4 1 . 0 20 4 78 2 1,231 Ruvuma 648 5 334 6 22 2 . 0 35 3 36 2 1,915 Iringa 180 8 95 7 1,039 12 178 1 77 4 938 13 3,843 Mbeya 2 1 3 1 1 1 . 0 160 1 . 0 182 Singida 183 11 18 8 1 1 97 5 7 1 191 11 1,782 Tabora 15 2 20 1 . 0 . 0 20 1 . 0 102 Rukwa . 0 . 0 . 0 . 0 . 0 . 0 - Kigoma 6 2 1 1 1 1 . 0 . 0 13 2 47 Shinyanga . 0 . 0 . 0 . 0 . 0 . 0 - Kagera . 0 . 0 . 0 . 0 . 0 . 0 - Mwanza 46 7 27 11 28 7 . 0 44 3 503 21 1,276 Mara . 0 30 1 80 2 . 0 . 0 398 2 575 Manyara 148 4 20 3 1 1 124 4 34 4 521 6 2,396 North Unguja . 0 . 0 . 0 . 0 . 0 . 0 8 South Unguja . 0 . 0 . 0 . 0 . 0 . 0 - Urban West . 0 . 0 . 0 . 0 . 0 . 0 - North Pemba . 0 . 0 . 0 . 0 . 0 . 0 - South Pemba . 0 . 0 . 0 . 0 . 0 . 0 - Total 2,582 66 1,761 56 1,928 47 1,025 12 1,178 37 5,144 96 40,479 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 119 CROP PRODUCTION APPENDIX II Tanzania Agriculture Sample Census - 2007/08 120 4.1.1 ANNUAL CROPS (VULI) SEASON: Number of Holdings Growing Crops During SHORT RAINY SEASON of 2007/08 and Region Region 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr Yes No Total Number of Holding % Number of Holding % Number of Holding % Dodoma 1 4 26 96 27 100 Arusha 13 13 91 88 104 100 Kilimanjaro 13 21 50 79 63 100 Tanga 25 22 88 78 113 100 Morogoro 27 37 46 63 73 100 Pwani 7 10 60 90 67 100 Dar es salaam 8 25 24 75 32 100 Lindi 0 0 14 100 14 100 Mtwara 1 3 37 97 38 100 Ruvuma 0 0 43 100 43 100 Iringa 3 3 102 97 105 100 Mbeya 0 0 38 100 38 100 Singida 0 0 29 100 29 100 Tabora 0 0 12 100 12 100 Rukwa 0 0 8 100 8 100 Kigoma 5 83 1 17 6 100 Shinyanga 0 0 3 100 3 100 Kagera 3 9 32 91 35 100 Mwanza 32 76 10 24 42 100 Mara 17 65 9 35 26 100 Manyara 1 1 89 99 90 100 MAINLAND 156 16 812 84 968 100 North Unguja 10 59 7 41 17 100 South Unguja 2 29 5 71 7 100 Urban West 2 50 2 50 4 100 North Pemba 1 13 7 88 8 100 South Pemba 1 50 1 50 2 100 ZANZIBAR 16 42 22 58 38 100 NATIONAL 172 17 834 83 1,006 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 121 4.1.2 ANNUAL CROPS: Planned Area, Actual Area Planted, Area Harvested, Amount Stored and Amount Sold b Crop Type and Region SHORT RAINY SEASON CROP NAME Area Planned Actual Area Planted Area Harvested (ha) Amount Harvested (ton) Amount Stored (ton) Amount Marketed (ton) Maize 9,887 3,076 2,470 24,414 4,858 19,455 Paddy 1,882 1,087 1,014 25,452 612 24,840 Sorghum 150 98 96 88 22 57 Finger Millet 1 1 1 2 2 0 Wheat 8 8 8 640 440 200 Sweet potatoes 108 83 79 101 32 64 Irish Potatoes 5 5 5 7 5 2 Yams 1,225 11 11 19 1 18 Cocoyams 6 6 5 23 4 19 Onions 34 34 34 1,806 45 1,161 Beans 1,316 1,216 1,158 3,017 1,108 1,909 Cowpeas 51 51 51 16 7 9 Green Grums 19 19 19 14 2 12 Seed Beans 0 2 2 2 1 1 Green Beans 32 32 14 80 0 80 Sunflower 2,256 154 152 365 216 148 Groundnuts 16 14 14 11 6 6 Nyonyo 1,000 300 300 2 2 0 Cotton 155 117 117 139 0 139 Flowers (Seeds) 114 114 114 140 0 140 Flowers(Kukata) 74 78 76 8,354 0 8,354 Nyasi 250 243 243 258 0 258 Mikunde 40 43 43 1 0 1 Apples 1 1 1 1 0 1 Pears 1 1 1 4 0 4 Cabbage 19 16 16 956 5 950 Tomatoes 23 22 22 1,627 8 1,619 Carrots 2 2 2 401 0 400 Chillie 6 6 6 32 0 32 mchicha 2 2 2 5 2 3 Boga 0 0 0 0 0 0 Tango 3 3 3 7 0 7 Mabilinganya 2 2 2 1 0 1 Matikiti maji 9 13 13 2,039 0 2,039 Total 18,697 6,860 6,094 70,023 7,377 61,928 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 122 4.1.3 ANNUAL CROPS: Planned Area, Actual Area Planted, Area Harvested, Amount Stored and Amount Sold b Crop Type and Region LONG RAINY SEASON CROP NAME Area Planned Actual Area Planted Area Harvested (ha) Amount Harvested (ton) Amount Stored (ton) Amount Marketed (ton) Maize 22,828 20,399 19,569 319,711 46,025 222,363 Paddy 7,353 4,361 4,288 52,915 9,103 43,242 Sorghum 785 693 679 2,013 76 1,941 Bulrush Millet 82 41 34 2,313 12 2,302 Finger Millet 744 690 690 1,388 807 581 Wheat 13,234 12,589 12,345 161,215 7,218 153,998 Barley 1,733 1,727 1,717 9,829 20 9,827 Sweet potatoes 95 80 76 834 631 140 Irish Potatoes 44 23 23 1,103 43 1,060 Cocoyams 5 5 5 18 6 12 Onions 65 57 57 376 15 361 Giligilani 8 8 8 2 0 2 Beans 9,264 4,233 3,945 5,276 2,645 2,784 Cowpeas 513 507 506 1,330 38 1,289 Green Grums 3,178 255 255 324 3 322 Mbaazi 10 9 9 4,008 40,001 7 Dengu 156 135 134 461 363 98 Njugu mawe 71 71 17 1,013 1,006 8 Seed Beans 2,250 2,155 2,130 727 0 727 Green Beans 72 86 62 465 148 458 Sunflower 3,075 2,662 2,635 12,143 2,130 10,025 Ufuta 133 128 110 72 31 41 Groundnuts 950 917 911 14,277 3,269 11,018 Cashewnuts 8 4 0 0 0 0 Soya 4 4 4 9 1 8 Cotton 233 197 197 137 15 137 Tobbacco 774 751 751 36,353 0 36,353 Pyrethrum 5 4 0 0 0 0 Coffee 28 1,968 12 4 0 4 Tea 1,139 1,139 1,139 31,388 0 31,388 Flowers (Seeds) 92 92 90 310 0 310 Flowers(Kukata) 221 212 212 2,004 0 2,004 Nanasi 72 72 64 39 0 39 Plums 3 3 3 5 0 5 Apples 3 3 3 5 0 5 Pears 2 2 2 3 0 3 Pithes 2 2 2 3 0 3 Cabbage 53 49 49 4,178 3,613 565 Tomatoes 98 89 89 2,039 99 2,000 Carrots 10 10 10 2 0 2 Chillie 15 13 13 34 0 34 Boga 0 0 0 0 0 0 Tango 1 1 1 1 0 1 Mabilinganya 1 1 1 8 0 8 Matikiti maji 1 1 1 0 0 0 Kartam 2,471 2,416 1,866 1,470 45 1,425 Total 71,884 58,864 54,715 669,803 117,362 536,898 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 123 4.1.4 Area Planted, Iriigated Area, Quantity Harvested, Quantity Sold and Quantity Stored in Large Scale Farms by Type of Cash Crops Crop Area (ha) of mature plants/trees/bushes in MONO CROP. Irrigated area (ha) Amount Harvested Amount Stored Amount Marketed Total Number of hhds Total Number of hhds Total Number of hhds Total Number of hhds Total Number of hhds pilipili manga . 0 . 0 . 0 . 0 . 0 Cassava 469 68 1 68 17,099 68 2,209 68 14,871 68 Pigeon pea 457 27 0 27 730 27 20 27 710 27 Matofaa . 0 . 0 . 0 . 0 . 0 Embe ng'o/sakuwa . 0 . 0 . 0 . 0 . 0 Coconut 6,111 86 424 86 15,559 86 60 86 15,490 86 Cashewnut 9,463 76 15 76 28,831 76 29 76 28,704 76 Palm oil 840 10 0 10 85 10 40 10 45 10 Sisal 34,696 42 0 42 50,714 42 27,567 42 37,429 42 Coffee 3,836 95 2,487 95 33,279 95 49 95 33,261 95 Tea 11,213 35 2,309 35 74,613 35 0 35 74,613 35 Cacao 5,795 4 0 4 20,000 4 0 4 20,000 4 Rubber 892 4 0 4 326 4 0 4 326 4 Wattle 586 9 13 9 14,200 9 0 9 14,200 9 Kapok . 0 . 0 . 0 . 0 . 0 Sugarcane 17,804 42 11,978 42 218,589 42 4,005 42 211,871 42 Cardamon 5 2 0 2 10 2 1 2 9 2 Jute 0 1 0 1 0 1 0 1 0 1 Kenaf . 0 . 0 . 0 . 0 . 0 Mdalasini . 0 . 0 . 0 . 0 . 0 Kungumanga . 0 . 0 . 0 . 0 . 0 Clove 163 17 0 17 10,083 17 0 17 10,083 17 Mashelisheli 19 1 0 1 10 1 0 1 10 1 Mbalungi . 0 . 0 . 0 . 0 . 0 Fenesi . 0 . 0 . 0 . 0 . 0 Banana 1,449 91 53 91 121,639 91 33,533 91 88,043 91 Avocado 507 13 0 13 28 13 0 13 27 13 Mangoes 232 81 13 81 114,867 81 20,266 81 48,594 81 Pawpaw 1,071 23 2 23 447 23 63 23 383 23 Minanasi . 0 . 0 . 0 . 0 . 0 Oranges 761 81 8 81 90,949 81 85 81 18,727 81 Grapefruit . 0 . 0 . 0 . 0 . 0 Grapes 25 7 21 7 53,020 7 7 7 53,018 7 Mandarine 692 10 690 10 2,088 10 76 10 2,013 10 Guaves 244 12 0 12 90 12 9 12 67 12 Matunda Damu . 0 . 0 . 0 . 0 . 0 Apples . 0 . 0 . 0 . 0 . 0 Peasi 12 2 0 2 94 2 34 2 60 2 Mifyoksi 1 1 0 1 30 1 8 1 22 1 Lemon 5 13 4 13 111 13 9 13 109 13 Doriani . 0 . 0 . 0 . 0 . 0 Mbirimbi . 0 . 0 . 0 . 0 . 0 Shokshoki . 0 . 0 . 0 . 0 . 0 95 0 1 0 1 0 1 0 1 0 1 Total 97,347 854 18,017 854 867,489 854 88,072 854 672,683 854 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 124 4.1.5 Number of Large scale farms reporting transport to crop markets by region Region Own Transport Contract transport Other Large scale Farm at farm gate Other (specify) Not applicable Total Dodoma 10 0 1 1 0 12 Arusha 37 3 6 1 3 50 Kilimanjaro 37 3 4 4 8 56 Tanga 62 24 23 6 8 123 Morogoro 37 10 4 5 9 65 Pwani 20 9 12 4 16 61 Dar es salaam 22 0 8 3 0 33 Lindi 9 1 0 1 0 11 Mtwara 42 2 3 1 8 56 Ruvuma 33 0 1 3 11 48 Iringa 22 14 5 3 19 63 Mbeya 9 7 6 17 0 39 Singida 0 0 0 0 0 0 Tabora 5 0 0 1 3 9 Rukwa 4 0 0 1 0 5 Kigoma 13 0 1 3 0 17 Shinyanga 0 0 0 0 0 0 Kagera 10 1 2 0 0 13 Mwanza 1 0 0 5 0 6 Mara 7 1 2 2 1 13 Manyara 27 14 3 7 6 57 North Unguja 73 0 0 0 8 81 South Unguja 10 0 5 3 2 20 Urban West 10 0 5 1 0 16 North Pemba 4 1 2 0 6 13 South Pemba 3 0 0 0 1 4 Total 507 90 93 72 109 871 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 125 4.1.6 Number of Large scale farms reporting main markets by region Region Secondary Market Cooperative Trade at farm Factory Other Large Scale Farm Exported by farm Other Not applicable Total Dodoma 1 0 3 1 0 1 6 0 12 Arusha 21 3 2 3 0 17 1 3 50 Kilimanjaro 19 14 5 0 1 5 3 9 56 Tanga 10 1 39 18 6 17 23 9 123 Morogoro 7 1 23 12 1 1 11 9 65 Pwani 7 5 13 3 8 0 9 16 61 Dar es salaam 5 1 14 0 0 0 10 3 33 Lindi 0 5 1 4 0 0 1 0 11 Mtwara 1 34 12 0 0 0 1 8 56 Ruvuma 2 5 23 0 2 0 3 13 48 Iringa 5 0 9 18 4 4 4 19 63 Mbeya 4 0 7 7 3 2 16 0 39 Singida 0 0 0 0 0 0 0 0 0 Tabora 5 0 0 0 0 0 1 3 9 Rukwa 0 1 1 0 0 0 3 0 5 Kigoma 0 1 9 0 2 0 5 0 17 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 8 3 0 1 1 0 13 Mwanza 0 0 2 0 0 0 4 0 6 Mara 2 0 5 1 1 0 3 1 13 Manyara 8 0 8 19 5 0 11 6 57 North Unguja 72 0 1 0 0 0 0 8 81 South Unguja 7 0 9 0 0 0 2 2 20 Urban West 2 0 14 0 0 0 0 0 16 North Pemba 3 0 2 1 0 1 0 6 13 South Pemba 3 0 0 0 0 0 0 1 4 Total 184 71 210 90 33 49 118 116 871 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 126 4.1.7 Number of Large scale farms reporting main marketing problem by region Region Price too low No transport Transport cost too high No buyer Farmers association problems Cooperative problems Government Regulatory board problems Lack of marketing information Not applicable Total Dodoma 2 0 3 3 0 0 0 1 3 12 Arusha 36 0 5 0 1 0 0 1 7 50 Kilimanjaro 35 0 1 1 0 0 1 1 17 56 Tanga 89 1 7 5 0 1 0 2 18 123 Morogoro 37 0 3 2 0 0 0 4 19 65 Pwani 30 0 8 3 0 0 1 0 19 61 Dar es salaam 17 0 1 0 0 1 0 0 14 33 Lindi 6 0 4 0 0 0 0 0 1 11 Mtwara 42 0 0 1 0 1 0 0 12 56 Ruvuma 19 2 4 0 0 0 2 2 19 48 Iringa 34 0 2 1 1 0 2 0 23 63 Mbeya 11 0 2 0 0 0 2 0 24 39 Singida 0 0 0 0 0 0 0 0 0 0 Tabora 5 0 0 0 0 0 0 0 4 9 Rukwa 1 1 0 0 0 0 0 0 3 5 Kigoma 5 0 0 0 0 0 0 0 12 17 Shinyanga 0 0 0 0 0 0 0 0 0 0 Kagera 7 0 2 0 0 0 0 0 4 13 Mwanza 1 0 0 0 0 0 0 0 5 6 Mara 9 0 0 1 0 0 0 0 3 13 Manyara 36 0 7 1 0 0 0 0 13 57 North Unguja 68 0 2 0 0 0 0 0 11 81 South Unguja 15 0 1 0 0 0 0 1 3 20 Urban West 13 0 0 0 0 0 1 0 2 16 North Pemba 5 0 1 0 0 0 0 0 7 13 South Pemba 0 0 3 0 0 0 0 0 1 4 Total 523 4 56 18 2 3 9 12 244 871 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 127 4.1.8 Area Planted, Iriigated Area, Quantity Harvested, Quantity Sold and Quantity Stored in Large Scale Farms by Type of Cash Crops Crop Area (ha) of mature plants/trees/bush es in MONO CROP. Irrigated area (ha) Amount Harvested Amount Stored Amount Marketed Total Numbe r of hhds Total Numbe r of hhds Total Numbe r of hhds Total Numbe r of hhds Total Numbe r of hhds pilipili manga . 0 . 0 . 0 . 0 . 0 Cassava 469 68 1 68 17,099 68 2,209 68 14,871 68 Pigeon pea 457 27 0 27 730 27 20 27 710 27 Matofaa . 0 . 0 . 0 . 0 . 0 Embe ng'o/sakuwa . 0 . 0 . 0 . 0 . 0 Coconut 6,111 86 424 86 15,559 86 60 86 15,490 86 Cashewnut 9,463 76 15 76 28,831 76 29 76 28,704 76 Palm oil 840 10 0 10 85 10 40 10 45 10 Sisal 34,696 42 0 42 50,714 42 27,567 42 37,429 42 Coffee 3,836 95 2,487 95 33,279 95 49 95 33,261 95 Tea 11,213 35 2,309 35 74,613 35 0 35 74,613 35 Cacao 5,795 4 0 4 20,000 4 0 4 20,000 4 Rubber 892 4 0 4 326 4 0 4 326 4 Wattle 586 9 13 9 14,200 9 0 9 14,200 9 Kapok . 0 . 0 . 0 . 0 . 0 Sugarcane 17,804 42 11,978 42 218,589 42 4,005 42 211,871 42 Cardamon 5 2 0 2 10 2 1 2 9 2 Jute 0 1 0 1 0 1 0 1 0 1 Kenaf . 0 . 0 . 0 . 0 . 0 Mdalasini . 0 . 0 . 0 . 0 . 0 Kungumanga . 0 . 0 . 0 . 0 . 0 Clove 163 17 0 17 10,083 17 0 17 10,083 17 Mashelisheli 19 1 0 1 10 1 0 1 10 1 Mbalungi . 0 . 0 . 0 . 0 . 0 Fenesi . 0 . 0 . 0 . 0 . 0 Banana 1,449 91 53 91 121,639 91 33,533 91 88,043 91 Avocado 507 13 0 13 28 13 0 13 27 13 Mangoes 232 81 13 81 114,867 81 20,266 81 48,594 81 Pawpaw 1,071 23 2 23 447 23 63 23 383 23 Minanasi . 0 . 0 . 0 . 0 . 0 Oranges 761 81 8 81 90,949 81 85 81 18,727 81 Grapefruit . 0 . 0 . 0 . 0 . 0 Grapes 25 7 21 7 53,020 7 7 7 53,018 7 Mandarine 692 10 690 10 2,088 10 76 10 2,013 10 Guaves 244 12 0 12 90 12 9 12 67 12 Matunda Damu . 0 . 0 . 0 . 0 . 0 Apples . 0 . 0 . 0 . 0 . 0 Peasi 12 2 0 2 94 2 34 2 60 2 Mifyoksi 1 1 0 1 30 1 8 1 22 1 Lemon 5 13 4 13 111 13 9 13 109 13 Doriani . 0 . 0 . 0 . 0 . 0 Mbirimbi . 0 . 0 . 0 . 0 . 0 Shokshoki . 0 . 0 . 0 . 0 . 0 95 0 1 0 1 0 1 0 1 0 1 Total 97,347 854 18,017 854 867,489 854 88,072 854 672,683 854 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 128 4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Finger Millet Wheat Barley Sweet potatoes Dodoma 1 1 Arusha 5 1 Kilimanjaro 7 1 Tanga 20 6 1 Morogoro 21 9 Pwani 3 2 Dar es salaam 1 1 Lindi Mtwara 1 1 Ruvuma Iringa 1 Mbeya Singida Tabora Rukwa Kigoma 3 Shinyanga Kagera 3 1 Mwanza 29 15 10 11 Mara 15 3 3 2 Manyara MAINLAND 110 33 14 1 1 19 North Unguja 6 8 South Unguja 1 1 Urban West 1 North Pemba 1 South Pemba 1 1 ZANZIBAR 7 3 10 NATIONAL 117 36 14 1 1 29 CONT….. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 129 CONT ….4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Beans Cowpeas Green Grums Mbaazi Dodoma Arusha 2 7 Kilimanjaro 1 4 Tanga 1 1 3 2 1 Morogoro 1 Pwani 1 Dar es salaam 2 Lindi Mtwara Ruvuma Iringa 1 Mbeya Singida Tabora Rukwa Kigoma 1 Shinyanga Kagera 1 Mwanza 2 1 5 3 Mara 5 1 Manyara 1 MAINLAND 2 2 5 27 5 6 North Unguja 4 3 South Unguja 1 Urban West North Pemba South Pemba ZANZIBAR 5 3 NATIONAL 2 2 5 5 27 8 6 CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 130 CONT 4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Sunflower Ufuta Groundnuts Nyonyo Dodoma 1 Arusha 1 Kilimanjaro 3 2 1 Tanga Morogoro 3 Pwani 1 Dar es salaam 1 Lindi Mtwara 1 1 Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza 4 Mara 1 1 Manyara MAINLAND 1 3 8 8 1 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 1 3 8 8 1 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 131 CONT….4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Flowers(Kukata) Cabbage Tomatoes Carrots Dodoma Arusha 1 5 1 1 1 Kilimanjaro 1 2 2 1 1 Tanga 2 1 Morogoro 1 Pwani 1 Dar es salaam Lindi Mtwara Ruvuma Iringa 1 Mbeya Singida Tabora Rukwa Kigoma 3 1 Shinyanga Kagera 2 1 Mwanza 17 2 2 Mara 1 Manyara MAINLAND 17 2 8 13 9 2 North Unguja 3 South Unguja Urban West North Pemba South Pemba ZANZIBAR 3 NATIONAL 17 2 8 13 12 2 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 132 CONT……4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Chillie mchicha Boga Tango Mabilinganya Matikiti maji Kartam Giligilani Dodoma Arusha 1 Kilimanjaro 1 Tanga Morogoro Pwani 1 Dar es salaam 1 6 Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma 1 Shinyanga Kagera Mwanza Mara Manyara MAINLAND 2 1 1 7 North Unguja 3 South Unguja Urban West 1 1 1 1 North Pemba South Pemba ZANZIBAR 3 1 1 1 1 NATIONAL 5 1 1 2 1 8 CONT….. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 133 CONT……4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Cashewnuts Soya Coffee Tea Nyasi Mikunde Nanasi Plums Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani 1 1 Dar es salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara MAINLAND 1 1 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 1 1 CONT,,,,,, APPENDIX II Tanzania Agriculture Sample Census - 2007/08 134 CONT….4.1.9 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Apples Pears Pithes Total Dodoma 3 Arusha 26 Kilimanjaro 27 Tanga 1 1 40 Morogoro 35 Pwani 11 Dar es salaam 12 Lindi Mtwara 4 Ruvuma Iringa 3 Mbeya Singida Tabora Rukwa Kigoma 9 Shinyanga Kagera 8 Mwanza 101 Mara 32 Manyara 1 MAINLAND 1 1 312 North Unguja 27 South Unguja 3 Urban West 5 North Pemba 1 South Pemba 2 ZANZIBAR 38 NATIONAL 1 1 350 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 135 4.1.10 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Finger Millet Wheat Barley Sweet potatoes Dodoma 18 2 4 4 1 Arusha 62 1 9 5 Kilimanjaro 28 1 1 1 4 1 Tanga 33 5 Morogoro 21 19 4 Pwani 7 3 Dar es salaam 6 5 6 Lindi 5 2 1 1 1 Mtwara 17 3 3 Ruvuma 35 13 1 3 1 6 Iringa 55 2 11 4 Mbeya 14 16 1 Singida 26 1 11 1 9 Tabora 10 10 4 Rukwa 6 1 1 Kigoma 1 1 Shinyanga 1 Kagera 2 Mwanza 1 1 1 Mara 16 3 3 1 Manyara 82 5 5 5 30 3 MAINLAND 446 92 34 4 11 67 14 19 North Unguja 3 6 4 South Unguja 1 1 Urban West 1 2 North Pemba 1 2 1 1 South Pemba 2 ZANZIBAR 5 11 1 8 NATIONAL 451 103 35 4 11 67 14 27 CONT… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 136 CONT…… CONT……..4.1.10 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Beans Cowpeas Green Grums Mbaazi Dodoma 3 1 Arusha 2 51 5 8 Kilimanjaro 1 16 1 Tanga 1 6 3 1 Morogoro 1 2 Pwani Dar es salaam 1 Lindi Mtwara 1 12 2 Ruvuma 1 2 20 1 Iringa 7 3 23 1 Mbeya 1 2 1 Singida 4 9 1 Tabora 2 3 1 Rukwa 1 4 Kigoma 1 1 Shinyanga 1 1 Kagera Mwanza Mara 5 Manyara 1 31 3 MAINLAND 11 18 175 27 14 4 North Unguja 1 2 South Unguja Urban West North Pemba 1 1 South Pemba ZANZIBAR 2 3 NATIONAL 11 2 18 175 30 14 4 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 137 CONT……..4.1.10 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 29 29 Kilimanjaro . . . . . . 5 4 Tanga . . . . . . 1 1 Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma 1 1 . . . . 4 3 Iringa 39 18 . . . . 3 3 Mbeya 1 1 . . . . 7 7 Singida . . . . . . 14 9 Tabora . . . . . . 2 1 Rukwa 1 1 . . . . . . Kigoma . . . . . . 0 0 Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara 2 2 . . . . . . MAINLAND 44 23 . . . . 65 57 North Unguja . . . . 4 4 . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . 1 1 . . South Pemba . . . . . . . . ZANZIBAR . . . . 5 5 . . NATIONAL 44 23 . . 5 5 65 57 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 138 CONT……4.1.10 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Sunflower Ufuta Groundnuts Nyonyo Dodoma 13 2 6 Arusha 1 3 2 7 Kilimanjaro 3 2 Tanga 4 5 Morogoro 8 2 1 Pwani 1 1 Dar es salaam 1 Lindi 1 Mtwara 5 1 16 Ruvuma 1 9 1 5 Iringa 1 1 10 1 Mbeya 1 1 Singida 11 26 3 Tabora 6 6 Rukwa 1 2 Kigoma 1 Shinyanga Kagera Mwanza 2 Mara 1 1 Manyara 4 8 33 MAINLAND 17 6 13 8 120 6 51 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 17 6 13 8 120 6 51 CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 139 CONT…..4.1.10 ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Flowers(Kukata) Cabbage Tomatoes Carrots Dodoma 2 Arusha 2 4 2 3 1 Kilimanjaro 1 1 2 2 2 Tanga 1 1 3 Morogoro Pwani Dar es salaam 1 Lindi Mtwara 1 Ruvuma 3 2 Iringa 7 2 2 3 6 Mbeya 1 Singida 1 1 1 Tabora 1 6 1 2 Rukwa 1 Kigoma 3 1 Shinyanga Kagera 1 Mwanza Mara 1 Manyara 1 2 MAINLAND 5 13 2 3 10 19 24 2 North Unguja South Unguja 1 Urban West North Pemba 1 South Pemba ZANZIBAR 2 NATIONAL 5 13 2 3 10 19 26 2 CONT……. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 140 CONT…..4.1.10…. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Chillie mchicha Boga Tango Mabilinganya Matikiti maji Kartam Giligilani Dodoma Arusha 1 1 1 Kilimanjaro 1 2 Tanga 1 1 Morogoro 1 Pwani Dar es salaam 1 Lindi Mtwara Ruvuma Iringa Mbeya Singida 7 1 Tabora Rukwa Kigoma 1 Shinyanga Kagera Mwanza Mara Manyara 1 6 MAINLAND 4 2 1 1 1 16 1 North Unguja South Unguja 1 Urban West North Pemba South Pemba ZANZIBAR 1 NATIONAL 5 2 1 1 1 16 1 CONT……. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 141 CONT…..4.1.10……ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Cashewnuts Soya Coffee Tea Nyasi Mikunde Nanasi Plums Dodoma 1 Arusha Kilimanjaro 2 Tanga Morogoro Pwani Dar es salaam Lindi Mtwara Ruvuma 1 Iringa 3 2 1 Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara MAINLAND 1 1 2 3 2 1 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 1 1 2 3 2 1 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 142 CONT….4.1.10…. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Apples Pears Pithes Total Dodoma 57 Arusha 171 Kilimanjaro 72 Tanga 65 Morogoro 59 Pwani 12 Dar es salaam 21 Lindi 11 Mtwara 61 Ruvuma 105 Iringa 1 1 1 148 Mbeya 38 Singida 113 Tabora 52 Rukwa 17 Kigoma 10 Shinyanga 3 Kagera 3 Mwanza 5 Mara 31 Manyara 220 MAINLAND 1 1 1 1,274 North Unguja 16 South Unguja 4 Urban West 3 North Pemba 8 South Pemba 2 ZANZIBAR 33 NATIONAL 1 1 1 1,307 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 143 4.1.11….. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Finger Millet Wheat Barley Sweet potatoes Dodoma 19 2 4 4 1 1 Arusha 67 1 9 5 1 Kilimanjaro 35 1 1 2 4 1 Tanga 53 11 1 Morogoro 42 28 4 Pwani 10 3 2 Dar es salaam 7 5 7 Lindi 5 2 1 1 1 Mtwara 18 3 4 Ruvuma 35 13 1 3 1 6 Iringa 56 2 11 4 Mbeya 14 16 1 Singida 26 1 11 1 9 Tabora 10 10 4 Rukwa 6 1 1 Kigoma 4 1 Shinyanga 1 Kagera 5 1 Mwanza 30 16 10 1 11 Mara 31 6 6 3 Manyara 82 5 5 5 30 3 MAINLAND 556 125 48 4 12 68 14 38 North Unguja 9 6 12 South Unguja 2 2 Urban West 2 2 North Pemba 1 3 1 1 South Pemba 3 1 ZANZIBAR 12 14 1 18 NATIONAL 568 139 49 4 12 68 14 56 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 144 CONT…. CONT…4.1.11…… ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Beans Cowpeas Green Grums Mbaazi Dodoma 3 1 Arusha 4 58 5 8 Kilimanjaro 1 1 20 1 Tanga 1 2 9 5 2 Morogoro 1 3 Pwani 1 Dar es salaam 3 Lindi Mtwara 1 12 2 Ruvuma 1 2 20 1 Iringa 7 3 24 1 Mbeya 1 2 1 Singida 4 9 1 Tabora 2 3 1 Rukwa 1 4 Kigoma 2 1 Shinyanga 1 1 Kagera 1 Mwanza 2 1 5 3 Mara 10 1 Manyara 1 32 3 MAINLAND 13 2 23 202 32 20 4 North Unguja 5 5 South Unguja 1 Urban West North Pemba 1 1 South Pemba ZANZIBAR 7 6 NATIONAL 13 2 7 23 202 38 20 4 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 145 CONT….. CONT…..4.1.11…… ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Sunflower Ufuta Groundnuts Nyonyo Dodoma 14 2 6 Arusha 1 3 2 8 Kilimanjaro 6 4 1 Tanga 4 5 Morogoro 11 2 1 Pwani 1 1 1 Dar es salaam 2 Lindi 1 Mtwara 5 1 1 17 Ruvuma 1 9 1 5 Iringa 1 1 10 1 Mbeya 1 1 Singida 11 26 3 Tabora 6 6 Rukwa 1 2 Kigoma 1 Shinyanga Kagera Mwanza 2 4 Mara 1 1 2 Manyara 4 8 33 MAINLAND 17 6 14 11 128 6 59 1 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 17 6 14 11 128 6 59 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 146 CONT...4.1.11…. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Flowers(Kukata) Cabbage Tomatoes Carrots Dodoma 2 Arusha 3 9 3 4 2 Kilimanjaro 1 2 4 4 3 1 Tanga 1 3 4 Morogoro 1 Pwani 1 Dar es salaam 1 Lindi Mtwara 1 Ruvuma 3 2 Iringa 7 2 3 3 6 Mbeya 1 Singida 1 1 1 Tabora 1 6 1 2 Rukwa 1 Kigoma 6 2 Shinyanga Kagera 3 1 Mwanza 17 2 2 Mara 1 1 Manyara 1 2 MAINLAND 22 13 2 5 18 32 33 4 North Unguja 3 South Unguja 1 Urban West North Pemba 1 South Pemba ZANZIBAR 5 NATIONAL 22 13 2 5 18 32 38 4 CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 147 CONT….5.3 1…….ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Chillie mchicha Boga Tango Mabilinganya Matikiti maji Kartam Giligilani Dodoma Arusha 1 1 1 1 Kilimanjaro 2 2 Tanga 1 1 Morogoro 1 Pwani 1 Dar es salaam 1 1 6 Lindi Mtwara Ruvuma Iringa Mbeya Singida 7 1 Tabora Rukwa Kigoma 2 Shinyanga Kagera Mwanza Mara Manyara 1 6 MAINLAND 6 3 2 1 8 16 1 North Unguja 3 South Unguja 1 Urban West 1 1 1 1 North Pemba South Pemba ZANZIBAR 4 1 1 1 1 NATIONAL 10 1 3 3 2 9 16 1 CONT….. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 148 CONT…… CONT...4.1.11…. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Cashewnuts Soya Coffee Tea Nyasi Mikunde Nanasi Plums Dodoma 1 Arusha Kilimanjaro 2 Tanga Morogoro Pwani 1 1 Dar es salaam Lindi Mtwara Ruvuma 1 Iringa 3 2 1 Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara MAINLAND 1 1 2 3 1 1 2 1 North Unguja South Unguja Urban West North Pemba South Pemba ZANZIBAR NATIONAL 1 1 2 3 1 1 2 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 149 CONT…..4.1.11…. ANNUAL CROPS: Total Number of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Apples Pears Pithes Total Dodoma 60 Arusha 197 Kilimanjaro 99 Tanga 1 1 105 Morogoro 94 Pwani 23 Dar es salaam 33 Lindi 11 Mtwara 65 Ruvuma 105 Iringa 1 1 1 151 Mbeya 38 Singida 113 Tabora 52 Rukwa 17 Kigoma 19 Shinyanga 3 Kagera 11 Mwanza 106 Mara 63 Manyara 221 MAINLAND 2 2 1 1,586 North Unguja 43 South Unguja 7 Urban West 8 North Pemba 9 South Pemba 4 ZANZIBAR 71 NATIONAL 2 2 1 1,657 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 150 4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 69 69 . . . . . . Arusha 277 267 . . . . . . Kilimanjaro 70 68 . . . . . . Tanga 382 380 550 443 . . . . Morogoro 526 307 1,036 401 . . . . Pwani 7,026 725 . . . . . . Dar es salaam 2 2 . . . . . . Lindi . . . . . . . . Mtwara 2 2 . . 1 1 . . Ruvuma . . . . . . . . Iringa 5 5 . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma 35 34 . . . . . . Shinyanga . . . . . . . . Kagera 93 93 . . . . . . Mwanza 609 389 132 107 136 87 . . Mara 772 717 141 121 13 10 . . Manyara . . . . . . . . MAINLAND 9,868 3,058 1,859 1,071 150 98 . . North Unguja 17 17 . . . . . . South Unguja 2 1 . . . . . . Urban West . . 12 5 . . . . North Pemba . . 3 3 . . . . South Pemba . . 8 8 . . . . ZANZIBAR 19 18 23 16 . . . . NATIONAL 9,887 3,076 1,882 1,087 150 98 . . CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 151 CONT,,,,,,,,,4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Finger Millet Wheat Barley Sweet potatoes Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . 8 8 . . . . Arusha . . . . . . 40 30 Kilimanjaro 1 1 . . . . . . Tanga . . . . . . 2 2 Morogoro . . . . . . . . Pwani . . . . . . 3 3 Dar es salaam . . . . . . 2 2 Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . 4 3 Mwanza . . . . . . 28 19 Mara . . . . . . 10 6 Manyara . . . . . . . . MAINLAND 1 1 8 8 . . 89 65 North Unguja . . . . . . 16 16 South Unguja . . . . . . 1 0 Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . 2 2 ZANZIBAR . . . . . . 19 18 NATIONAL 1 1 8 8 . . 108 83 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 152 CONT…….4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 32 32 Kilimanjaro 2 2 . . . . . . Tanga 3 3 . . . . 1 1 Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . 0 0 Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . 1,225 11 . . 1 1 Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 5 5 1,225 11 . . 34 34 North Unguja . . . . 5 5 . . South Unguja . . . . 1 1 . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . 6 6 . . NATIONAL 5 5 1,225 11 6 6 34 34 CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 153 CONT…….4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Beans Cowpeas Green Grums Mbaazi Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 468 383 . . . . . . Kilimanjaro 20 20 . . . . . . Tanga 3 3 7 7 5 5 . . Morogoro . . 37 37 . . . . Pwani . . . . 8 8 . . Dar es salaam . . 2 2 . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa 1 1 . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera 3 3 . . . . . . Mwanza 21 16 . . 5 5 . . Mara 792 785 . . 1 1 . . Manyara 8 5 . . . . . . MAINLAND 1,316 1,216 46 46 19 19 . . North Unguja . . 5 5 . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . 5 5 . . . . NATIONAL 1,316 1,216 51 51 19 19 . . CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 154 CONT……..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . 32 32 Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . 0 2 . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND . . . . 0 2 32 32 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL . . . . 0 2 32 32 CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 155 CONT……..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Sunflower Ufuta Groundnuts Nyonyo Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 24 24 . . . . . . Arusha 14 14 . . . . . . Kilimanjaro 3 3 . . 2 2 . . Tanga . . . . . . . . Morogoro 2,215 105 . . . . . . Pwani . . . . . . 1,000 300 Dar es salaam . . . . 1 1 . . Lindi . . . . . . . . Mtwara . . . . 2 2 . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . 9 8 . . Mara 0 8 . . 2 1 . . Manyara . . . . . . . . MAINLAND 2,256 154 . . 16 14 1,000 300 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 2,256 154 . . 16 14 1,000 300 CONT……. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 156 CONT…..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 42 42 Kilimanjaro . . . . . . 72 72 Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza 155 117 . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 155 117 . . . . 114 114 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 155 117 . . . . 114 114 CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 157 CONT……4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Flowers(Kukata) Cabbage Tomatoes Carrots Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 61 61 2 2 2 2 1 1 Kilimanjaro 5 15 3 3 12 12 1 1 Tanga . . 2 2 1 1 . . Morogoro . . 1 1 . . . . Pwani . . . . 1 0 . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa 8 2 . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . 4 4 0 0 . . Shinyanga . . . . . . . . Kagera . . 2 2 1 1 . . Mwanza . . 6 3 3 2 . . Mara . . . . 1 1 . . Manyara . . . . . . . . MAINLAND 74 78 19 16 20 19 2 2 North Unguja . . . . 3 3 . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . 3 3 . . NATIONAL 74 78 19 16 23 22 2 2 CONT… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 158 CONT……..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Chillie mchicha Boga Tango Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 1 1 . . . . . . Kilimanjaro 2 2 . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . 1 1 Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . 0 0 . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 3 3 . . 0 0 1 1 North Unguja 3 3 . . . . . . South Unguja . . . . . . . . Urban West . . 2 2 . . 2 2 North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR 3 3 2 2 . . 2 2 NATIONAL 6 6 2 2 0 0 3 3 CONT……. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 159 CONT…….4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Mabilinganya Matikiti maji Kartam Giligilani Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . 1 1 . . . . Dar es salaam . . 6 10 . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND . . 7 11 . . . . North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West 2 2 2 2 . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR 2 2 2 2 . . . . NATIONAL 2 2 9 13 . . . . CONT…… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 160 CONT……..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Cashewnuts Soya Coffee Tea Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND . . . . . . . . North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL . . . . . . . . CONT…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 161 CONT….4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Nyasi Mikunde Nanasi Plums Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani 250 243 40 43 . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 250 243 40 43 . . . . North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 250 243 40 43 . . . . CONT… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 162 CONT…..4.1.12 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT RAINY SEASON Region Crop Code Apples Pears Pithes Total Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . 101 101 Arusha . . . . . . 940 835 Kilimanjaro . . . . . . 225 233 Tanga 1 1 1 1 . . 957 848 Morogoro . . . . . . 3,815 851 Pwani . . . . . . 8,329 1,323 Dar es salaam . . . . . . 14 18 Lindi . . . . . . . . Mtwara . . . . . . 5 7 Ruvuma . . . . . . . . Iringa . . . . . . 14 8 Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . 40 39 Shinyanga . . . . . . . . Kagera . . . . . . 103 102 Mwanza . . . . . . 2,330 765 Mara . . . . . . 1,731 1,649 Manyara . . . . . . 8 5 MAINLAND 1 1 1 1 . . 18,611 6,783 North Unguja . . . . . . 49 49 South Unguja . . . . . . 4 2 Urban West . . . . . . 20 13 North Pemba . . . . . . 3 3 South Pemba . . . . . . 10 10 ZANZIBAR . . . . . . 86 77 NATIONAL 1 1 1 1 . . 18,697 6,860 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 163 4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 2,968 2,761 105 65 74 42 82 41 Arusha 3,322 3,137 . . 30 20 . . Kilimanjaro 2,324 2,275 106 106 25 18 . . Tanga 848 831 234 210 . . . . Morogoro 582 560 1,347 1,339 59 44 . . Pwani 760 640 175 113 . . . . Dar es salaam 15 15 9 9 . . . . Lindi 96 41 220 100 12 12 . . Mtwara 252 221 9 9 4 4 . . Ruvuma 1,399 1,231 176 170 8 8 . . Iringa 1,370 1,314 29 39 . . . . Mbeya 607 367 4,559 1,883 . . . . Singida 556 421 20 20 54 48 . . Tabora 130 125 78 58 . . . . Rukwa 708 481 8 0 . . . . Kigoma 3 3 . . . . . . Shinyanga 30 30 . . . . . . Kagera 87 82 . . . . . . Mwanza 3 3 3 2 . . . . Mara 503 350 62 52 12 9 . . Manyara 6,248 5,496 145 135 506 487 . . MAINLAND 22,811 20,383 7,284 4,309 784 692 82 41 North Unguja 6 6 24 22 . . . . South Unguja 3 2 . . . . . . Urban West . . 4 2 . . . . North Pemba 8 8 23 15 1 1 . . South Pemba . . 18 13 . . . . ZANZIBAR 17 16 69 52 1 1 . . NATIONAL 22,828 20,399 7,353 4,361 785 693 82 41 CONT…….. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 164 CONT……..4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Finger Millet Wheat Barley Sweet potatoes Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 522 522 . . . . . . Arusha . . 1,408 1,364 236 236 . . Kilimanjaro 1 1 389 329 0 10 . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . 42 31 Lindi . . 7 16 . . 1 1 Mtwara . . . . . . . . Ruvuma 17 15 . . 155 155 22 19 Iringa . . 389 303 954 954 . . Mbeya . . 183 183 . . . . Singida 4 2 224 160 . . . . Tabora . . . . . . 5 5 Rukwa . . 400 200 . . . . Kigoma . . . . . . 1 1 Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . 3 3 . . . . Mara . . . . . . 6 6 Manyara 200 150 10,231 10,027 388 372 . . MAINLAND 744 690 13,234 12,585 1,733 1,727 77 63 North Unguja . . . . . . 9 9 South Unguja . . . . . . 1 1 Urban West . . . . . . 7 6 North Pemba . . . . . . 1 1 South Pemba . . . . . . . . ZANZIBAR . . . . . . 18 17 NATIONAL 744 690 13,234 12,585 1,733 1,727 95 80 CONT……. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 165 CONT…….4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Beans Cowpeas Green Grums Mbaazi Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 68 55 1 1 . . . . Arusha 2,086 2,052 142 142 190 190 . . Kilimanjaro 690 779 . . 2,970 47 . . Tanga 38 38 27 27 5 5 . . Morogoro 1 1 11 11 . . . . Pwani . . . . . . . . Dar es salaam . . 1 1 . . . . Lindi . . . . . . . . Mtwara 120 120 314 312 2 2 . . Ruvuma 229 213 1 1 . . . . Iringa 93 91 0 0 . . . . Mbeya . . . . 10 10 . . Singida 47 37 . . . . 2 1 Tabora 12 3 5 5 . . . . Rukwa 93 67 . . . . . . Kigoma 3 3 . . . . . . Shinyanga 1 1 . . 1 1 . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara 19 13 . . . . . . Manyara 5,764 760 . . . . 8 8 MAINLAND 9,264 4,233 502 500 3,178 255 10 9 North Unguja . . 3 3 . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . 8 4 . . . . South Pemba . . . . . . . . ZANZIBAR . . 11 7 . . . . NATIONAL 9,264 4,233 513 507 3,178 255 10 9 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 166 CONT……4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 5 5 . . 227 227 47 47 Kilimanjaro . . . . . . 14 28 Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . 71 71 . . . . Ruvuma . . 0 0 . . . . Iringa . . . . 18 18 1 1 Mbeya . . . . 40 40 . . Singida 107 89 . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . 10 10 Mara 12 9 . . . . . . Manyara 32 32 . . 1,965 1,870 . . MAINLAND 156 135 71 71 2,250 2,155 72 86 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 156 135 71 71 2,250 2,155 72 86 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 167 CONT……4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Sunflower Ufuta Groundnuts Nyonyo Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 1,107 971 59 54 47 29 . . Arusha 139 139 . . . . . . Kilimanjaro 70 32 . . . . . . Tanga 36 36 . . 6 6 . . Morogoro 85 74 53 53 6 6 . . Pwani 14 14 . . 4 4 . . Dar es salaam . . . . 0 0 . . Lindi . . . . 1 1 . . Mtwara . . 13 13 792 790 . . Ruvuma 152 137 8 8 27 24 . . Iringa 185 164 . . 4 4 . . Mbeya . . . . 27 27 . . Singida 410 329 . . 9 7 . . Tabora 56 42 . . 20 15 . . Rukwa 1 1 . . 3 2 . . Kigoma . . . . 1 1 . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . 3 1 . . Manyara 820 723 . . . . . . MAINLAND 3,075 2,662 133 128 950 917 . . North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 3,075 2,662 133 128 950 917 . . APPENDIX II Tanzania Agriculture Sample Census - 2007/08 168 CONT……4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 42 42 Kilimanjaro 88 88 . . . . 50 50 Tanga 5 5 . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . 629 614 5 4 . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora 4 4 145 137 . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara 116 80 . . . . . . Manyara 20 20 . . . . . . MAINLAND 233 197 774 751 5 4 92 92 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 233 197 774 751 5 4 92 92 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 169 CONT……4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Flowers(Kukata) Cabbage Tomatoes Carrots Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . 3 3 . . Arusha 148 148 29 29 28 28 9 9 Kilimanjaro 37 37 5 5 15 15 . . Tanga . . 1 1 5 4 . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . 4 4 . . Lindi . . . . . . . . Mtwara . . . . 1 1 . . Ruvuma . . 6 4 5 4 . . Iringa 16 12 1 1 31 28 . . Mbeya . . 1 1 . . . . Singida . . 1 1 1 1 1 1 Tabora . . 1 1 1 0 . . Rukwa . . 3 1 . . . . Kigoma . . 4 4 0 0 . . Shinyanga . . . . . . . . Kagera . . 1 1 . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara 20 15 . . . . . . MAINLAND 221 212 53 49 93 87 10 10 North Unguja . . . . . . . . South Unguja . . . . 3 0 . . Urban West . . . . . . . . North Pemba . . . . 2 2 . . South Pemba . . . . . . . . ZANZIBAR . . . . 5 2 . . NATIONAL 221 212 53 49 98 89 10 10 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 170 CONT…….4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Chillie mchicha Boga Tango Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 1 1 Kilimanjaro 2 2 . . . . . . Tanga 1 1 . . . . . . Morogoro 0 0 . . . . . . Pwani . . . . . . . . Dar es salaam . . . . 0 0 . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . 0 0 . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara 10 10 . . . . . . MAINLAND 13 13 . . 0 0 1 1 North Unguja . . . . . . . . South Unguja 2 0 . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR 2 0 . . . . . . NATIONAL 15 13 . . 0 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 171 CONT…….4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Mabilinganya Matikiti maji Kartam Giligilani Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . 1 1 100 100 . . Kilimanjaro . . . . 555 555 . . Tanga 1 1 . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . 274 219 8 8 Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . 1,542 1,542 . . MAINLAND 1 1 1 1 2,471 2,416 8 8 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 1 1 1 1 2,471 2,416 8 8 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 172 CONT…….4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Cashewnuts Soya Coffee Tea Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 8 4 . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . 28 1,968 . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . 4 4 . . . . Iringa . . . . . . 1,139 1,139 Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 8 4 4 4 28 1,968 1,139 1,139 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 8 4 4 4 28 1,968 1,139 1,139 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 173 CONT…….4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Nyasi Mikunde Nanasi Plums Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . 72 72 3 3 Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND . . . . 72 72 3 3 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL . . . . 72 72 3 3 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 174 CONT 4.1.13 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region LONG RAINY SEASON Region Crop Code Apples Pears Pithes Total Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . 5,043 4,547 Arusha . . . . . . 8,219 7,946 Kilimanjaro . . . . . . 7,374 6,349 Tanga . . . . . . 1,208 1,166 Morogoro . . . . . . 2,144 2,088 Pwani . . . . . . 953 771 Dar es salaam . . . . . . 71 60 Lindi . . . . . . 337 171 Mtwara . . . . . . 1,577 1,542 Ruvuma . . . . . . 2,215 1,997 Iringa 3 3 2 2 2 2 4,989 4,789 Mbeya . . . . . . 5,435 2,519 Singida . . . . . . 1,732 1,353 Tabora . . . . . . 459 396 Rukwa . . . . . . 1,217 753 Kigoma . . . . . . 13 13 Shinyanga . . . . . . 32 32 Kagera . . . . . . 88 83 Mwanza . . . . . . 19 18 Mara . . . . . . 732 519 Manyara . . . . . . 27,901 21,649 MAINLAND 3 3 2 2 2 2 71,756 58,760 North Unguja . . . . . . 46 44 South Unguja . . . . . . 9 3 Urban West . . . . . . 11 8 North Pemba . . . . . . 44 32 South Pemba . . . . . . 18 13 ZANZIBAR . . . . . . 128 100 NATIONAL 3 3 2 2 2 2 71,884 58,860 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 175 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Maize Paddy Sorghum Bulrush Millet Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 3,037 2,830 105 65 74 42 82 41 Arusha 3,599 3,404 . . 30 20 . . Kilimanjaro 2,394 2,343 106 106 25 18 . . Tanga 1,230 1,211 784 653 . . . . Morogoro 1,108 867 2,383 1,740 59 44 . . Pwani 7,786 1,365 175 113 . . . . Dar es salaam 17 17 9 9 . . . . Lindi 96 41 220 100 12 12 . . Mtwara 254 223 9 9 5 5 . . Ruvuma 1,399 1,231 176 170 8 8 . . Iringa 1,375 1,319 29 39 . . . . Mbeya 607 367 4,559 1,883 . . . . Singida 556 421 20 20 54 48 . . Tabora 130 125 78 58 . . . . Rukwa 708 481 8 0 . . . . Kigoma 38 37 . . . . . . Shinyanga 30 30 . . . . . . Kagera 180 175 . . . . . . Mwanza 612 392 135 109 136 87 . . Mara 1,275 1,067 202 172 25 19 . . Manyara 6,248 5,496 145 135 506 487 . . MAINLAND 32,679 23,441 9,143 5,380 934 790 82 41 North Unguja 23 23 24 22 . . . . South Unguja 5 3 . . . . . . Urban West . . 16 7 . . . . North Pemba 8 8 26 18 1 1 . . South Pemba . . 26 21 . . . . ZANZIBAR 36 34 92 68 1 1 . . NATIONAL 32,715 23,475 9,235 5,448 935 791 82 41 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 176 CONT…….4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Finger Millet Wheat Barley Sweet potatoes Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 522 522 8 8 . . . . Arusha . . 1,408 1,364 236 236 40 30 Kilimanjaro 2 2 389 329 0 10 . . Tanga . . . . . . 2 2 Morogoro . . . . . . . . Pwani . . . . . . 3 3 Dar es salaam . . . . . . 44 33 Lindi . . 7 16 . . 1 1 Mtwara . . . . . . . . Ruvuma 17 15 . . 155 155 22 19 Iringa . . 389 303 954 954 . . Mbeya . . 183 183 . . . . Singida 4 2 224 160 . . . . Tabora . . . . . . 5 5 Rukwa . . 400 200 . . . . Kigoma . . . . . . 1 1 Shinyanga . . . . . . . . Kagera . . . . . . 4 3 Mwanza . . 3 3 . . 28 19 Mara . . . . . . 16 12 Manyara 200 150 10,231 10,027 388 372 . . MAINLAND 745 691 13,242 12,593 1,733 1,727 166 128 North Unguja . . . . . . 25 25 South Unguja . . . . . . 2 1 Urban West . . . . . . 7 6 North Pemba . . . . . . 1 1 South Pemba . . . . . . 2 2 ZANZIBAR . . . . . . 37 35 NATIONAL 745 691 13,242 12,593 1,733 1,727 203 163 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 177 CONT……4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 61 61 Kilimanjaro 2 2 . . . . 5 4 Tanga 3 3 . . . . 2 2 Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma 1 1 . . . . 4 3 Iringa 39 18 . . . . 3 3 Mbeya 1 1 . . . . 7 7 Singida . . . . . . 14 9 Tabora . . . . . . 2 1 Rukwa 1 1 . . . . . . Kigoma . . . . . . 1 1 Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . 1,225 11 . . 1 1 Mara . . . . . . . . Manyara 2 2 . . . . . . MAINLAND 49 28 1,225 11 . . 99 91 North Unguja . . . . 9 9 . . South Unguja . . . . 1 1 . . Urban West . . . . . . . . North Pemba . . . . 1 1 . . South Pemba . . . . . . . . ZANZIBAR . . . . 11 11 . . NATIONAL 49 28 1,225 11 11 11 99 91 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 178 CONT 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Irish Potatoes Yams Cocoyams Onions Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 61 61 Kilimanjaro 2 2 . . . . 5 4 Tanga 3 3 . . . . 2 2 Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma 1 1 . . . . 4 3 Iringa 39 18 . . . . 3 3 Mbeya 1 1 . . . . 7 7 Singida . . . . . . 14 9 Tabora . . . . . . 2 1 Rukwa 1 1 . . . . . . Kigoma . . . . . . 1 1 Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . 1,225 11 . . 1 1 Mara . . . . . . . . Manyara 2 2 . . . . . . MAINLAND 49 28 1,225 11 . . 99 91 North Unguja . . . . 9 9 . . South Unguja . . . . 1 1 . . Urban West . . . . . . . . North Pemba . . . . 1 1 . . South Pemba . . . . . . . . ZANZIBAR . . . . 11 11 . . NATIONAL 49 28 1,225 11 11 11 99 91 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 179 CONT…….4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Beans Cowpeas Green Grums Mbaazi Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 68 55 1 1 . . . . Arusha 2,554 2,435 142 142 190 190 . . Kilimanjaro 710 800 . . 2,970 47 . . Tanga 41 41 34 34 10 10 . . Morogoro 1 1 48 48 . . . . Pwani . . . . 8 8 . . Dar es salaam . . 3 3 . . . . Lindi . . . . . . . . Mtwara 120 120 314 312 2 2 . . Ruvuma 229 213 1 1 . . . . Iringa 94 92 0 0 . . . . Mbeya . . . . 10 10 . . Singida 47 37 . . . . 2 1 Tabora 12 3 5 5 . . . . Rukwa 93 67 . . . . . . Kigoma 3 3 . . . . . . Shinyanga 1 1 . . 1 1 . . Kagera 3 3 . . . . . . Mwanza 21 16 . . 5 5 . . Mara 811 798 . . 1 1 . . Manyara 5,772 765 . . . . 8 8 MAINLAND 10,580 5,449 548 546 3,197 274 10 9 North Unguja . . 8 8 . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . 8 4 . . . . South Pemba . . . . . . . . ZANZIBAR . . 16 12 . . . . NATIONAL 10,580 5,449 564 558 3,197 274 10 9 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 180 CONT…..4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 5 5 . . 227 227 47 47 Kilimanjaro . . . . . . 46 60 Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . 71 71 0 2 . . Ruvuma . . 0 0 . . . . Iringa . . . . 18 18 1 1 Mbeya . . . . 40 40 . . Singida 107 89 . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . 10 10 Mara 12 9 . . . . . . Manyara 32 32 . . 1,965 1,870 . . MAINLAND 156 135 71 71 2,250 2,157 104 118 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 156 135 71 71 2,250 2,157 104 118 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 181 CONT 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Dengu Njugu mawe Seed Beans Green Beans Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 5 5 . . 227 227 47 47 Kilimanjaro . . . . . . 46 60 Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . 71 71 0 2 . . Ruvuma . . 0 0 . . . . Iringa . . . . 18 18 1 1 Mbeya . . . . 40 40 . . Singida 107 89 . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . 10 10 Mara 12 9 . . . . . . Manyara 32 32 . . 1,965 1,870 . . MAINLAND 156 135 71 71 2,250 2,157 104 118 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 156 135 71 71 2,250 2,157 104 118 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 182 CONT…..4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Sunflower Ufuta Groundnuts Nyonyo Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 1,131 995 59 54 47 29 . . Arusha 153 153 . . . . . . Kilimanjaro 73 35 . . 2 2 . . Tanga 36 36 . . 6 6 . . Morogoro 2,300 179 53 53 6 6 . . Pwani 14 14 . . 4 4 1,000 300 Dar es salaam . . . . 1 1 . . Lindi . . . . 1 1 . . Mtwara . . 13 13 794 792 . . Ruvuma 152 137 8 8 27 24 . . Iringa 185 164 . . 4 4 . . Mbeya . . . . 27 27 . . Singida 410 329 . . 9 7 . . Tabora 56 42 . . 20 15 . . Rukwa 1 1 . . 3 2 . . Kigoma . . . . 1 1 . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . 9 8 . . Mara 0 8 . . 5 2 . . Manyara 820 723 . . . . . . MAINLAND 5,331 2,816 133 128 965 931 1,000 300 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 5,331 2,816 133 128 965 931 1,000 300 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 183 CONT…..4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Cotton Tobbacco Pyrethrum Flowers (Seeds) Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . 84 84 Kilimanjaro 88 88 . . . . 122 122 Tanga 5 5 . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . 629 614 5 4 . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora 4 4 145 137 . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza 155 117 . . . . . . Mara 116 80 . . . . . . Manyara 20 20 . . . . . . MAINLAND 388 314 774 751 5 4 206 206 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 388 314 774 751 5 4 206 206 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 184 CONT……4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Flowers(Kukata) Cabbage Tomatoes Carrots Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . 3 3 . . Arusha 209 209 31 31 30 30 10 10 Kilimanjaro 42 52 8 8 27 27 1 1 Tanga . . 3 3 5 4 . . Morogoro . . 1 1 . . . . Pwani . . . . 1 0 . . Dar es salaam . . . . 4 4 . . Lindi . . . . . . . . Mtwara . . . . 1 1 . . Ruvuma . . 6 4 5 4 . . Iringa 24 14 1 1 31 28 . . Mbeya . . 1 1 . . . . Singida . . 1 1 1 1 1 1 Tabora . . 1 1 1 0 . . Rukwa . . 3 1 . . . . Kigoma . . 8 8 1 1 . . Shinyanga . . . . . . . . Kagera . . 3 3 1 1 . . Mwanza . . 6 3 3 2 . . Mara . . . . 1 1 . . Manyara 20 15 . . . . . . MAINLAND 295 290 72 65 114 106 12 12 North Unguja . . . . 3 3 . . South Unguja . . . . 3 0 . . Urban West . . . . . . . . North Pemba . . . . 2 2 . . South Pemba . . . . . . . . ZANZIBAR . . . . 8 5 . . NATIONAL 295 290 72 65 122 111 12 12 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 185 CONT…..4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Chillie mchicha Boga Tango Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha 1 1 . . . . 1 1 Kilimanjaro 4 4 . . . . . . Tanga 1 1 . . . . . . Morogoro 0 0 . . . . . . Pwani . . . . . . . . Dar es salaam . . . . 0 0 1 1 Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . 0 0 . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara 10 10 . . . . . . MAINLAND 16 16 . . 1 1 2 2 North Unguja 3 3 . . . . . . South Unguja 2 0 . . . . . . Urban West . . 2 2 . . 2 2 North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR 5 3 2 2 . . 2 2 NATIONAL 21 19 2 2 1 1 4 4 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 186 CONT…..4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Mabilinganya Matikiti maji Kartam Giligilani Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . 1 1 100 100 . . Kilimanjaro . . . . 555 555 . . Tanga 1 1 . . . . . . Morogoro . . . . . . . . Pwani . . 1 1 . . . . Dar es salaam . . 6 10 . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . . . . . Mbeya . . . . . . . . Singida . . . . 274 219 8 8 Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . 1,542 1,542 . . MAINLAND 1 1 8 12 2,471 2,416 8 8 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West 2 2 2 2 . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR 2 2 2 2 . . . . NATIONAL 3 3 10 14 2,471 2,416 8 8 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 187 CONT 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Cashewnuts Soya Coffee Tea Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma 8 4 . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . 28 1,968 . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani . . . . . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . 4 4 . . . . Iringa . . . . . . 1,139 1,139 Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 8 4 4 4 28 1,968 1,139 1,139 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 8 4 4 4 28 1,968 1,139 1,139 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 188 CONT 4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Nyasi Mikunde Nanasi Plums Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . . . Arusha . . . . . . . . Kilimanjaro . . . . . . . . Tanga . . . . . . . . Morogoro . . . . . . . . Pwani 250 243 40 43 . . . . Dar es salaam . . . . . . . . Lindi . . . . . . . . Mtwara . . . . . . . . Ruvuma . . . . . . . . Iringa . . . . 72 72 3 3 Mbeya . . . . . . . . Singida . . . . . . . . Tabora . . . . . . . . Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga . . . . . . . . Kagera . . . . . . . . Mwanza . . . . . . . . Mara . . . . . . . . Manyara . . . . . . . . MAINLAND 250 243 40 43 72 72 3 3 North Unguja . . . . . . . . South Unguja . . . . . . . . Urban West . . . . . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . ZANZIBAR . . . . . . . . NATIONAL 250 243 40 43 72 72 3 3 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 189 CONT……4.1.14 ANNUAL CROPS: Total Planned Area and Actual Planted Area (Hectares) of Large Scale Farms by Specified Annual Crop and Region SHORT & LONG SEASON Region Crop Code Apples Pears Pithes Total Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Area Planned Actual Area Planted Dodoma . . . . . . 5,144 4,648 Arusha . . . . . . 9,159 8,781 Kilimanjaro . . . . . . 7,599 6,582 Tanga 1 1 1 1 . . 2,165 2,013 Morogoro . . . . . . 5,959 2,939 Pwani . . . . . . 9,282 2,094 Dar es salaam . . . . . . 84 78 Lindi . . . . . . 337 171 Mtwara . . . . . . 1,582 1,549 Ruvuma . . . . . . 2,215 1,997 Iringa 3 3 2 2 2 2 5,003 4,797 Mbeya . . . . . . 5,435 2,519 Singida . . . . . . 1,732 1,353 Tabora . . . . . . 459 396 Rukwa . . . . . . 1,217 753 Kigoma . . . . . . 53 52 Shinyanga . . . . . . 32 32 Kagera . . . . . . 191 185 Mwanza . . . . . . 2,349 783 Mara . . . . . . 2,463 2,168 Manyara . . . . . . 27,909 21,654 MAINLAND 4 4 3 3 2 2 90,367 65,544 North Unguja . . . . . . 95 93 South Unguja . . . . . . 13 5 Urban West . . . . . . 31 21 North Pemba . . . . . . 47 35 South Pemba . . . . . . 28 23 ZANZIBAR . . . . . . 214 177 NATIONAL 4 4 3 3 2 2 90,581 65,721 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 190 AGRICULTURE CREDIT APPENDIX II Tanzania Agriculture Sample Census - 2007/08 191 6.1.1 AGRICULTURE CREDIT: Number and Percent of Agriculture Holdings Receiving Credit by Region During the 2007/08 Agriculture Year Region 6.1 During the year 2007/08 did the farmer borrow money for Received Credit Did not Receive Credit Total Count % Count % Count % Dodoma 2 7.4 25 92.6 27 100 Arusha 2 1.9 102 98.1 104 100 Kilimanjaro 0 0 63 100 63 100 Tanga 3 2.7 110 97.3 113 100 Morogoro 6 8.2 67 91.8 73 100 Pwani 2 3 65 97 67 100 Dar es salaam 2 6.3 30 93.8 32 100 Lindi 2 14.3 12 85.7 14 100 Mtwara 6 15.8 32 84.2 38 100 Ruvuma 4 9.3 39 90.7 43 100 Iringa 18 17.1 87 82.9 105 100 Mbeya 5 13.2 33 86.8 38 100 Singida 1 3.4 28 96.6 29 100 Tabora 4 33.3 8 66.7 12 100 Rukwa 0 0 8 100 8 100 Kigoma 0 0 6 100 6 100 Shinyanga 0 0 3 100 3 100 Kagera 0 0 35 100 35 100 Mwanza 2 4.8 40 95.2 42 100 Mara 2 7.7 24 92.3 26 100 Manyara 2 2.2 88 97.8 90 100 MAINLAND 63 6.5 905 93.5 968 100 North Unguja 1 5.9 16 94.1 17 100 South Unguja 0 0 7 100 7 100 Urban West 0 0 4 100 4 100 North Pemba 0 0 8 100 8 100 South Pemba 0 0 2 100 2 100 ZANZIBAR 1 2.6 37 97.4 38 100 NATIONAL 64 6.4 942 93.6 1,006 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 192 6.1.2 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year( Labour) Labour Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 1 0 1 0 0 0 0 0 0 Arusha 2 0 2 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 1 0 1 0 0 0 0 0 0 Morogoro 6 0 6 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 1 0 1 0 0 0 0 0 0 Lindi 2 0 2 0 0 0 0 0 0 Mtwara 5 0 5 0 0 0 0 0 0 Ruvuma 2 0 2 0 0 0 0 0 0 Iringa 14 0 14 0 0 0 0 0 0 Mbeya 4 0 4 0 0 0 0 0 0 Singida 0 1 1 0 1 1 0 1 1 Tabora 1 0 1 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 1 0 1 0 0 0 0 0 0 NATIONAL 41 1 42 0 1 1 0 1 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 41 1 42 0 1 1 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 193 6.1.3 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year Seeds Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 1 0 1 0 0 0 0 0 0 Arusha 2 0 2 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 1 0 1 0 0 0 0 0 0 Morogoro 3 0 3 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 0 0 0 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 Mtwara 1 0 1 0 0 0 0 0 0 Ruvuma 3 0 3 0 0 0 0 0 0 Iringa 11 0 11 0 0 0 0 0 0 Mbeya 2 0 2 0 0 0 0 0 0 Singida 0 1 1 0 1 1 0 1 1 Tabora 2 0 2 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 1 0 1 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 2 0 2 0 0 0 0 0 0 NATIONAL 30 1 31 0 1 1 0 1 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 30 1 31 0 1 1 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 194 6.1.4 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year Fertilisers Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 0 0 0 0 0 0 0 0 0 Arusha 2 0 2 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 1 0 1 0 0 0 0 0 0 Morogoro 4 0 4 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 0 0 0 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 Mtwara 0 0 0 0 0 0 0 0 0 Ruvuma 4 0 4 0 0 0 0 0 0 Iringa 13 0 13 0 0 0 0 0 0 Mbeya 5 0 5 0 0 0 0 0 0 Singida 1 0 1 1 0 1 1 0 1 Tabora 4 0 4 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 0 0 0 0 0 0 0 0 0 NATIONAL 35 0 35 1 0 1 1 0 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 35 0 35 1 0 1 1 0 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 195 6.1.5 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year Agrochemicals Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 0 0 0 0 0 0 0 0 0 Arusha 2 0 2 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 1 0 1 0 0 0 0 0 0 Morogoro 4 0 4 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 0 0 0 0 0 0 0 0 0 Lindi 2 0 2 0 0 0 0 0 0 Mtwara 6 0 6 0 0 0 0 0 0 Ruvuma 1 0 1 0 0 0 0 0 0 Iringa 10 0 10 0 0 0 0 0 0 Mbeya 4 0 4 0 0 0 0 0 0 Singida 0 1 1 0 1 1 0 1 1 Tabora 4 0 4 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 1 0 1 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 1 0 1 0 0 0 0 0 0 NATIONAL 37 1 38 0 1 1 0 1 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 37 1 38 0 1 1 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 196 6.1.6 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year Livestock purchase Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 0 0 0 0 0 0 0 0 0 Arusha 0 0 0 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 0 0 0 0 0 0 0 0 0 Morogoro 2 0 2 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 1 0 1 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 Mtwara 0 0 0 0 0 0 0 0 0 Ruvuma 0 0 0 0 0 0 0 0 0 Iringa 2 0 2 0 0 0 0 0 0 Mbeya 1 0 1 0 0 0 0 0 0 Singida 0 1 1 0 1 1 0 1 1 Tabora 1 0 1 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 0 0 0 0 0 0 0 0 0 NATIONAL 8 1 9 0 1 1 0 1 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 8 1 9 0 1 1 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 197 6.1.7 AGRICULTURE CREDIT: Number of Holdings Received Credit by Source and Region During 2007/08 Agriculture Year Livestock Feed Region Source A Source B Source C Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Company owning the farm Commercial Bank Total Dodoma 0 0 0 0 0 0 0 0 0 Arusha 0 0 0 0 0 0 0 0 0 Kilimanjaro 0 0 0 0 0 0 0 0 0 Tanga 0 0 0 0 0 0 0 0 0 Morogoro 1 0 1 0 0 0 0 0 0 Pwani 0 0 0 0 0 0 0 0 0 Dar es salaam 1 0 1 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 Mtwara 0 0 0 0 0 0 0 0 0 Ruvuma 0 0 0 0 0 0 0 0 0 Iringa 5 0 5 0 0 0 0 0 0 Mbeya 1 0 1 0 0 0 0 0 0 Singida 0 1 1 0 1 1 0 1 1 Tabora 0 0 0 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 Mara 1 0 1 0 0 0 0 0 0 Manyara 0 0 0 0 0 0 0 0 0 NATIONAL 9 1 10 0 1 1 0 1 1 North Unguja 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 ZANZIBAR 0 0 0 0 0 0 0 0 0 NATIONAL 9 1 10 0 1 1 0 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 198 6.1.8 AGRICUTURE CREDIT: Number of Holdings Who Did Not Receive Credit by Reason and Region During 2007/08 Agriculture Year Region Not needed Not available Did not want to go into credit Interest rate/cost too high Credit granted too late Difficult bureacratic procedure Other NATIONAL Count % Count % Count % Count % Count % Count % Count % Count % Dodoma 6 2 9 6 3 3 1 1 0 0 8 4 0 0 27 3 Arusha 55 16 17 11 7 8 17 16 1 8 6 3 0 0 103 11 Kilimanjaro 35 10 3 2 6 7 7 6 0 0 4 2 6 10 61 6 Tanga 23 7 23 15 11 13 5 5 1 8 43 21 6 10 112 11 Morogoro 31 9 9 6 6 7 7 6 2 15 15 7 1 2 71 7 Pwani 27 8 7 5 5 6 8 7 1 8 15 7 4 6 67 7 Dar es salaam 10 3 6 4 2 2 6 6 1 8 4 2 1 2 30 3 Lindi 1 0 4 3 0 0 1 1 0 0 6 3 0 0 12 1 Mtwara 6 2 2 1 6 7 3 3 0 0 14 7 7 11 38 4 Ruvuma 16 5 5 3 6 7 4 4 1 8 8 4 3 5 43 4 Iringa 35 10 10 7 18 21 10 9 1 8 13 6 7 11 94 10 Mbeya 13 4 2 1 2 2 4 4 0 0 10 5 2 3 33 3 Singida 10 3 0 0 4 5 1 1 0 0 14 7 0 0 29 3 Tabora 9 3 1 1 0 0 0 0 0 0 0 0 0 0 10 1 Rukwa 3 1 3 2 1 1 0 0 0 0 0 0 1 2 8 1 Kigoma 2 1 1 1 1 1 0 0 0 0 1 0 1 2 6 1 Shinyanga 1 0 2 1 0 0 0 0 0 0 0 0 0 0 3 0 Kagera 5 1 5 3 1 1 2 2 0 0 12 6 10 16 35 4 Mwanza 9 3 17 11 1 1 3 3 2 15 10 5 0 0 42 4 Mara 9 3 5 3 1 1 0 0 1 8 8 4 0 0 24 2 Manyara 19 5 12 8 6 7 28 26 1 8 13 6 10 16 89 9 MAINLAND 325 94 143 94 87 100 107 99 12 92 204 99 59 94 937 96 North Unguja 7 2 7 5 0 0 1 1 0 0 2 1 0 0 17 2 South Unguja 2 1 2 1 0 0 0 0 0 0 0 0 3 5 7 1 Urban West 2 1 0 0 0 0 0 0 1 8 0 0 1 2 4 0 North Pemba 8 2 0 0 0 0 0 0 0 0 0 0 0 0 8 1 South Pemba 2 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 ZANZIBAR 21 6 9 6 0 0 1 1 1 8 2 1 4 6 38 4 NATIONAL 346 100 152 100 87 100 108 100 13 100 206 100 63 100 975 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 199 RANK OF LIVESTOCK MARKET OUTLETS APPENDIX II Tanzania Agriculture Sample Census - 2007/08 200 7.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region AMOUNT OF LAND OWNERSHIP OF LAND COST OF LAND LENGTH OF LAND TENURE SOIL CULTIVATION SOIL FERTILITY ACCESS TO IMPROVED SEED Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 4 14.8 0 .0 0 .0 2 7.4 1 3.7 2 7.4 Arusha 3 3.0 2 2.0 0 .0 0 .0 2 2.0 1 1.0 3 3.0 Kilimanjaro 5 8.2 4 6.6 0 .0 4 6.6 2 3.3 1 1.6 1 1.6 Tanga 4 3.7 15 13.9 1 .9 0 .0 1 .9 4 3.7 2 1.9 Morogoro 1 1.5 5 7.4 1 1.5 0 .0 0 .0 4 5.9 3 4.4 Pwani 7 10.8 1 1.5 0 .0 1 1.5 0 .0 0 .0 2 3.1 Dar es salaam 3 9.7 5 16.1 2 6.5 1 3.2 1 3.2 1 3.2 3 9.7 Lindi 1 8.3 0 .0 0 .0 0 .0 1 8.3 0 .0 0 .0 Mtwara 1 2.6 3 7.9 5 13.2 0 .0 0 .0 3 7.9 0 .0 Ruvuma 1 2.4 1 2.4 0 .0 0 .0 1 2.4 5 11.9 1 2.4 Iringa 6 6.3 4 4.2 2 2.1 0 .0 0 .0 14 14.6 2 2.1 Mbeya 1 2.8 0 .0 1 2.8 0 .0 0 .0 6 16.7 0 .0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 6 20.7 4 13.8 Tabora 0 .0 0 .0 0 .0 0 .0 0 .0 1 9.1 1 9.1 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 16.7 Kigoma 1 16.7 0 .0 0 .0 0 .0 0 .0 0 .0 1 16.7 Shinyanga 1 50.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 2 5.7 0 .0 0 .0 1 2.9 0 .0 0 .0 Mwanza 6 15.0 2 5.0 3 7.5 0 .0 0 .0 1 2.5 1 2.5 Mara 1 4.5 1 4.5 1 4.5 0 .0 0 .0 0 .0 2 9.1 Manyara 5 5.6 6 6.7 6 6.7 0 .0 3 3.3 13 14.4 7 7.8 North Unguja 0 .0 0 .0 0 .0 0 .0 1 5.9 1 5.9 2 11.8 South Unguja 1 14.3 1 14.3 0 .0 0 .0 0 .0 2 28.6 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 1 25.0 2 50.0 North Pemba 0 .0 1 12.5 0 .0 0 .0 0 .0 3 37.5 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 0 .0 Total 48 5.0 57 5.9 22 2.3 6 .6 15 1.6 70 7.3 40 4.1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 201 Cont 7.1….Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region IRRIGATION FACILITIES ACCESS TO CHEMICAL INPUTS COST OF INPUTS EXTENSION SERVICES ACCESS TO FOREST RESOURCES GOVERNMENT REGULATIONS ACCESS TO CREDIT HARVESTING THRESHING Numbe r % Numbe r % Numbe r % Numbe r % Number % Number % Number % Number % Number % Dodoma 0 .0 1 3.7 3 11.1 0 .0 0 .0 2 7.4 1 3.7 0 .0 0 .0 Arusha 4 4.0 4 4.0 20 19.8 1 1.0 0 .0 4 4.0 7 6.9 1 1.0 0 .0 Kilimanjaro 10 16.4 0 .0 6 9.8 0 .0 0 .0 0 .0 0 .0 2 3.3 0 .0 Tanga 2 1.9 1 .9 9 8.3 2 1.9 0 .0 5 4.6 19 17.6 6 5.6 1 .9 Morogoro 8 11.8 1 1.5 12 17.6 1 1.5 0 .0 0 .0 4 5.9 0 .0 0 .0 Pwani 4 6.2 1 1.5 8 12.3 1 1.5 0 .0 4 6.2 6 9.2 2 3.1 0 .0 Dar es salaam 1 3.2 0 .0 1 3.2 0 .0 1 3.2 1 3.2 1 3.2 0 .0 0 .0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 1 8.3 3 25.0 0 .0 0 .0 Mtwara 0 .0 1 2.6 14 36.8 0 .0 0 .0 0 .0 4 10.5 0 .0 1 2.6 Ruvuma 1 2.4 0 .0 20 47.6 1 2.4 0 .0 0 .0 4 9.5 0 .0 0 .0 Iringa 4 4.2 3 3.1 41 42.7 2 2.1 0 .0 1 1.0 4 4.2 1 1.0 0 .0 Mbeya 1 2.8 2 5.6 9 25.0 0 .0 0 .0 0 .0 8 22.2 1 2.8 0 .0 Singida 0 .0 0 .0 3 10.3 0 .0 0 .0 0 .0 7 24.1 0 .0 0 .0 Tabora 0 .0 0 .0 3 27.3 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Rukwa 1 16.7 0 .0 0 .0 0 .0 0 .0 1 16.7 1 16.7 0 .0 0 .0 Kigoma 1 16.7 1 16.7 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 1 2.9 3 8.6 2 5.7 0 .0 0 .0 0 .0 3 8.6 1 2.9 0 .0 Mwanza 1 2.5 0 .0 9 22.5 3 7.5 0 .0 1 2.5 2 5.0 0 .0 0 .0 Mara 0 .0 1 4.5 2 9.1 1 4.5 0 .0 0 .0 4 18.2 0 .0 0 .0 Manyara 4 4.4 0 .0 7 7.8 4 4.4 0 .0 1 1.1 6 6.7 0 .0 0 .0 North Unguja 0 .0 0 .0 1 5.9 1 5.9 0 .0 3 17.6 0 .0 0 .0 0 .0 South Unguja 0 .0 0 .0 2 28.6 0 .0 0 .0 0 .0 1 14.3 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 1 25.0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 1 12.5 0 .0 0 .0 1 12.5 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 43 4.5 19 2.0 173 17.9 17 1.8 1 .1 26 2.7 85 8.8 14 1.5 2 .2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 202 Cont 7.1….Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region STORAGE PROCESSING MARKET INFORMATION TRANSPORT COSTS DISTRUCTION BY ANIMALS STEALING PESTS AND DISEASES LOCAL GOVERNMENT TAXATION ACCESS TO OFF-FARM INCOME Number % Numbe r % Number % Number % Number % Number % Number % Number % Number % Dodoma 1 3.7 1 3.7 1 3.7 0 .0 0 .0 0 .0 0 .0 1 3.7 0 .0 Arusha 3 3.0 1 1.0 7 6.9 4 4.0 1 1.0 1 1.0 5 5.0 2 2.0 0 .0 Kilimanjaro 0 .0 0 .0 3 4.9 3 4.9 3 4.9 1 1.6 2 3.3 0 .0 0 .0 Tanga 1 .9 1 .9 3 2.8 0 .0 3 2.8 6 5.6 2 1.9 0 .0 0 .0 Morogoro 0 .0 0 .0 1 1.5 0 .0 2 2.9 3 4.4 0 .0 0 .0 0 .0 Pwani 0 .0 0 .0 0 .0 5 7.7 2 3.1 1 1.5 0 .0 1 1.5 1 1.5 Dar es salaam 0 .0 0 .0 1 3.2 0 .0 0 .0 1 3.2 0 .0 0 .0 0 .0 Lindi 0 .0 0 .0 0 .0 0 .0 1 8.3 0 .0 1 8.3 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 1 2.6 2 5.3 0 .0 0 .0 Ruvuma 0 .0 0 .0 0 .0 0 .0 1 2.4 1 2.4 1 2.4 0 .0 0 .0 Iringa 1 1.0 0 .0 1 1.0 1 1.0 0 .0 0 .0 1 1.0 0 .0 0 .0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 3 8.3 0 .0 0 .0 Singida 1 3.4 0 .0 1 3.4 2 6.9 0 .0 0 .0 1 3.4 0 .0 1 3.4 Tabora 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 9.1 0 .0 0 .0 Rukwa 0 .0 0 .0 0 .0 0 .0 1 16.7 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 2 33.3 0 .0 0 .0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 0 .0 1 2.9 6 17.1 0 .0 0 .0 0 .0 Mwanza 0 .0 0 .0 0 .0 0 .0 1 2.5 0 .0 2 5.0 0 .0 0 .0 Mara 0 .0 0 .0 0 .0 0 .0 1 4.5 0 .0 1 4.5 0 .0 0 .0 Manyara 2 2.2 1 1.1 2 2.2 0 .0 0 .0 0 .0 3 3.3 1 1.1 0 .0 North Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 1 5.9 4 23.5 0 .0 0 .0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 1 12.5 0 .0 0 .0 1 12.5 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 9 .9 4 .4 21 2.2 15 1.6 17 1.8 23 2.4 31 3.2 5 .5 2 .2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 203 Cont …7.1 .Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region COST OF MACHINERY AVAILABILITY OF LIVESTOCK DRUGS LIVESTOCK DISEASES AVAILABILITY OF PASTURE KIANGAZI CHA MUDA MREFU UGOMVI KATI YA WAKULIMA NA WAFUGAJI Total Number % Number % Number % Number % Number % Number % Number % Dodoma 3 11.1 0 .0 0 .0 0 .0 4 14.8 0 .0 27 100.0 Arusha 1 1.0 0 .0 1 1.0 1 1.0 20 19.8 2 2.0 101 100.0 Kilimanjaro 1 1.6 0 .0 1 1.6 0 .0 7 11.5 5 8.2 61 100.0 Tanga 2 1.9 0 .0 1 .9 1 .9 15 13.9 1 .9 108 100.0 Morogoro 0 .0 0 .0 8 11.8 1 1.5 12 17.6 1 1.5 68 100.0 Pwani 3 4.6 1 1.5 8 12.3 0 .0 4 6.2 2 3.1 65 100.0 Dar es salaam 0 .0 1 3.2 5 16.1 0 .0 2 6.5 0 .0 31 100.0 Lindi 0 .0 1 8.3 0 .0 0 .0 3 25.0 0 .0 12 100.0 Mtwara 1 2.6 1 2.6 0 .0 0 .0 1 2.6 0 .0 38 100.0 Ruvuma 0 .0 0 .0 3 7.1 0 .0 1 2.4 0 .0 42 100.0 Iringa 1 1.0 2 2.1 3 3.1 0 .0 0 .0 2 2.1 96 100.0 Mbeya 1 2.8 0 .0 2 5.6 0 .0 1 2.8 0 .0 36 100.0 Singida 2 6.9 1 3.4 0 .0 0 .0 0 .0 0 .0 29 100.0 Tabora 0 .0 0 .0 0 .0 0 .0 5 45.5 0 .0 11 100.0 Rukwa 1 16.7 0 .0 0 .0 0 .0 0 .0 0 .0 6 100.0 Kigoma 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 6 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Kagera 0 .0 1 2.9 1 2.9 0 .0 0 .0 13 37.1 35 100.0 Mwanza 1 2.5 1 2.5 2 5.0 0 .0 3 7.5 1 2.5 40 100.0 Mara 0 .0 0 .0 0 .0 1 4.5 5 22.7 1 4.5 22 100.0 Manyara 2 2.2 0 .0 0 .0 0 .0 2 2.2 15 16.7 90 100.0 North Unguja 0 .0 0 .0 2 11.8 0 .0 0 .0 1 5.9 17 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 7 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 4 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 8 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 Total 19 2.0 9 .9 37 3.8 4 .4 86 8.9 44 4.6 964 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 204 Input use and Main Source Input Main Source of inputs Imported by farm Purchased from tanzania factory Produced on farm Private seller/NGO Government Institution Other Total No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Seed/planting material 44 10 89 21 17 4 215 50 19 4 48 11 432 100 Inorganic fertiliser 37 11 62 18 3 1 148 43 8 2 86 25 344 100 Organic fertiliser 11 4 13 5 103 36 72 25 0 0 89 31 288 100 Herbicides 26 9 33 12 2 1 127 45 5 2 89 32 282 100 Fungicides 22 8 34 13 4 2 103 39 3 1 96 37 262 100 Pesticides 41 12 60 17 8 2 153 44 4 1 78 23 344 100 Total 181 9 291 15 137 7 818 42 39 2 486 25 1952 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 205 LIVESTOCK PRODUCTION APPENDIX II Tanzania Agriculture Sample Census - 2007/08 206 9.1.1 LIVESTOCK PRODUCTION Total Number of Large scale farms Rearing Cattle by Region during 2007/08 Agriculture Year Region Yes No Total Number Number Number Dodoma 14 13 27 Arusha 31 73 104 Kilimanjaro 18 45 63 Tanga 36 77 113 Morogoro 45 28 73 Pwani 36 31 67 Dar es salaam 16 16 32 Lindi 9 5 14 Mtwara 14 24 38 Ruvuma 27 16 43 Iringa 68 37 105 Mbeya 16 22 38 Singida 22 7 29 Tabora 10 2 12 Rukwa 8 0 8 Kigoma 5 1 6 Shinyanga 2 1 3 Kagera 31 4 35 Mwanza 34 8 42 Mara 18 8 26 Manyara 50 40 90 North Unguja 7 10 17 South Unguja 2 5 7 Urban West 2 2 4 North Pemba 5 3 8 South Pemba 1 1 2 Total 527 479 1006 9.1.2 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Goats by Region during 2007/08 Agriculture Year Region Yes No Total Number Number Number Dodoma 12 15 27 Arusha 15 89 104 Kilimanjaro 12 50 62 Tanga 24 89 113 Morogoro 37 36 73 Pwani 24 43 67 Dar es salaam 10 22 32 Lindi 6 8 14 Mtwara 12 26 38 Ruvuma 26 17 43 Iringa 42 63 105 Mbeya 5 33 38 Singida 22 7 29 Tabora 6 6 12 Rukwa 6 2 8 Kigoma 2 4 6 Shinyanga 2 1 3 Kagera 17 18 35 Mwanza 22 20 42 Mara 12 14 26 Manyara 38 52 90 North Unguja 4 13 17 South Unguja 2 5 7 Urban West 0 4 4 North Pemba 1 7 8 South Pemba 0 2 2 Total 359 646 1005 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 207 9.1.4 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Pigs by Region during 2007/08 Agriculture Year Region Yes No Total Number Number Number Dodoma 5 22 27 Arusha 6 98 104 Kilimanjaro 7 56 63 Tanga 2 111 113 Morogoro 8 65 73 Pwani 5 62 67 Dar es salaam 5 27 32 Lindi 2 12 14 Mtwara 2 36 38 Ruvuma 14 29 43 Iringa 27 78 105 Mbeya 6 32 38 Singida 2 27 29 Tabora 4 8 12 Rukwa 3 5 8 Kigoma 0 6 6 Shinyanga 0 3 3 Kagera 1 34 35 Mwanza 3 39 42 Mara 4 22 26 Manyara 2 88 90 North Unguja 0 17 17 South Unguja 0 7 7 Urban West 0 4 4 North Pemba 0 8 8 South Pemba 0 2 2 Total 108 898 1006 9.1.3 LIVESTOCK PRODUCTION: Total Number of Large scale farms Rearing Sheeps by Region during 2007/08 Agriculture Year Region Yes No Total Number Number Number Dodoma 5 22 27 Arusha 8 96 104 Kilimanjaro 8 55 63 Tanga 12 101 113 Morogoro 27 46 73 Pwani 16 51 67 Dar es salaam 6 26 32 Lindi 2 12 14 Mtwara 5 33 38 Ruvuma 10 33 43 Iringa 36 69 105 Mbeya 2 36 38 Singida 7 22 29 Tabora 2 10 12 Rukwa 2 6 8 Kigoma 1 5 6 Shinyanga 1 2 3 Kagera 9 26 35 Mwanza 10 32 42 Mara 8 18 26 Manyara 21 69 90 North Unguja 1 16 17 South Unguja 1 6 7 Urban West 0 4 4 North Pemba 0 8 8 South Pemba 0 2 2 Total 200 806 1006 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 208 9.1.5 LIVESTOCK PRODUCTION Number of cattle by Region Region Number of Indigenous Number of Improved Beef Number of Improved Dairy Total Total No of Farms Total No of Farms Total No of Farms Total No of Farms Dodoma 1,382 48 6,499 22 275 22 8,156 80 Arusha 1,483 67 2,679 47 1,232 68 5,404 164 Kilimanjaro 269 20 1,348 26 1,184 81 2,809 107 Tanga 1,659 86 4,257 23 2,151 118 8,067 198 Morogoro 5,741 131 850 27 3,376 123 9,967 247 Pwani 1,760 61 4,587 28 3,272 146 9,619 197 Dar es salaam 792 37 14 2 436 47 1,242 84 Lindi 1,719 33 40 13 100 16 1,859 50 Mtwara 1,779 55 104 5 676 29 2,551 74 Ruvuma 3,500 113 1,150 60 676 70 5,326 161 Iringa 2,359 153 3,171 69 5,149 222 10,679 396 Mbeya 503 53 64 2 475 42 1,046 88 Singida 694 113 50 9 24 12 768 119 Tabora 510 34 10 3 46 14 566 50 Rukwa 7,697 32 27 7 503 32 8,227 47 Kigoma 148 14 26 7 106 11 280 30 Shinyanga . 0 . 0 98 11 98 11 Kagera 11,441 137 14,413 74 1,518 61 27,372 195 Mwanza 4,749 207 1,517 14 1,388 14 7,654 225 Mara 2,496 74 218 6 1,141 44 3,855 106 Manyara 1,639 193 2,023 14 442 96 4,104 249 North Unguja 119 26 . 0 70 9 189 35 South Unguja 21 7 . 0 16 5 37 11 Urban West 1 1 . 0 30 10 31 11 North Pemba 68 21 . 0 29 9 97 22 South Pemba 11 4 . 0 . 0 11 4 Total 52,540 1,720 43,047 458 24,413 1,312 120,014 2,961 9.1.6 Cattle Production: Number of Farms Rearing Cattle by Herd Size Herd Size Number of Farms Number of Cattle Total % Total % Mean Less than 20 102 19 1,131 19 11.09 20 - 39 90 17 2,493 17 27.7 40 - 59 63 12 3,144 12 49.9 60 - 79 37 7 2,538 7 68.59 80 - 99 30 6 2,624 6 87.47 Above 100 205 39 108,084 39 527.24 Total 527 100 120,014 100 227.73 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 209 9.1.7 Number of Goats by Region Region Number of Indigenous Number of Improved goat for meat Number of Improved goat Dairy Total Sum Valid N Sum Valid N Sum Valid N Sum Valid N Dodoma 695 34 1333 19 . 0 2028 48 Arusha 976 45 601 9 222 10 1799 64 Kilimanjaro 908 47 526 17 70 14 1504 59 Tanga 1211 80 231 8 199 11 1641 94 Morogoro 2898 149 315 14 79 13 3292 165 Pwani 1747 82 188 8 160 16 2095 98 Dar es salaam 428 31 50 1 . 0 478 31 Lindi 539 23 . 0 5 2 544 23 Mtwara 444 40 . 0 23 5 467 44 Ruvuma 795 98 15 2 14 3 824 102 Iringa 2192 139 205 22 1003 27 3400 184 Mbeya 231 22 . 0 6 3 237 22 Singida 380 89 120 5 . 0 500 94 Tabora 264 26 . 0 . 0 264 26 Rukwa 326 19 . 0 . 0 326 19 Kigoma 86 6 60 1 . 0 146 7 Shinyanga 71 10 . 0 . 0 71 10 Kagera 1204 59 23 3 155 13 1382 65 Mwanza 1048 91 87 4 137 4 1272 95 Mara 458 46 . 0 103 5 561 51 Manyara 1150 144 56 4 53 10 1259 157 North Unguja 55 15 . 0 . 0 55 15 South Unguja 17 6 . 0 . 0 17 6 Urban West . 0 . 0 . 0 . 0 North Pemba 31 4 . 0 . 0 31 4 South Pemba . 0 . 0 . 0 . 0 Total 18154 1305 3810 117 2229 136 24193 1483 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 210 9.1.9 Number of sheeps by region Region Number of sheeps Sum Valid N Dodoma 461 19 Arusha 1215 33 Kilimanjaro 1569 33 Tanga 1029 40 Morogoro 1973 121 Pwani 1217 62 Dar es salaam 331 15 Lindi 80 8 Mtwara 73 17 Ruvuma 219 40 Iringa 4154 146 Mbeya 53 8 Singida 68 26 Tabora 34 6 Rukwa 389 9 Kigoma 5 1 Shinyanga 12 5 Kagera 225 30 Mwanza 359 36 Mara 523 31 Manyara 561 75 North Unguja 14 3 South Unguja 45 4 Urban West . 0 North Pemba . 0 South Pemba . 0 Total 14609 768 9.1.8 Goat Production: Number of Farms Rearing Goat by Herd Size Herd Size Number of Farms Number of Goat Total % Total % Mean Less than 20 89 25 1,015 25 11.40 20 - 39 98 27 2,649 27 27.03 40 - 59 49 14 2,314 14 47.22 60 - 79 41 11 2,803 11 68.37 80 - 99 21 6 1,862 6 88.67 Above 100 60 17 13,550 17 225.83 Total 358 100 24,193 100 67.58 9.1.10 Sheep Production: Number of Farms Rearing Sheep by Herd Size Herd Size Number of Farms Number of sheep Total % Total % Mean Less than 20 78 39 676 39 8.67 20 - 39 38 19 1,032 19 27.16 40 - 59 24 12 1,144 12 47.67 60 - 79 13 7 834 7 64.15 80 - 99 7 4 609 4 87.00 Above 100 40 20 10,314 20 257.85 Total 200 100 14,609 100 73.05 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 211 9.1.12 PigsProduction: Number of Farms Rearing Pig by Herd Size Herd Size Number of Farms Number of Pigs Total % Total % Mean Less than 20 29 27 242 27 8.34 20 - 39 22 20 559 20 25.41 40 - 59 14 13 641 13 45.79 60 - 79 7 6 506 6 72.29 80 - 99 10 9 871 9 87.10 Above 100 26 24 5,497 24 211.42 Total 108 100 8,316 100 77.00 9.1.11 Number of Pigs by Region Region Number of pigs Sum Valid N Dodoma 200 21 Arusha 204 25 Kilimanjaro 725 31 Tanga 17 6 Morogoro 832 31 Pwani 564 22 Dar es salaam 798 21 Lindi 47 9 Mtwara 290 10 Ruvuma 1207 60 Iringa 1041 98 Mbeya 1132 28 Singida 47 7 Tabora 178 16 Rukwa 241 14 Kigoma . 0 Shinyanga . 0 Kagera 40 5 Mwanza 422 14 Mara 289 18 Manyara 42 6 North Unguja . 0 South Unguja . 0 Urban West . 0 North Pemba . 0 South Pemba . 0 Total 8316 442 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 212 9.1.13 Number of Livestock Sold and Average price by Region Region Live cattle Live goats/sheep Live pigs Number Sold During 2007/08 Average sold during 2007/08 Number Sold During 2007/08 Average sold during 2007/08 Number Sold During 2007/08 Average sold during 2007/08 Dodoma 8718 253,623 729 37,441 1220 31,947 Arusha 354 334,455 452 108,333 10 80,000 Kilimanjaro 226 513,636 386 174,167 219 151,000 Tanga 404 296,320 460 37,455 11 85,000 Morogoro 814 310,355 771 66,333 652 70,725 Pwani 1605 327,250 1720 41,167 135 59,667 Dar es salaam 105 422,222 193 130,000 335 73,833 Lindi 751 316,667 93 34,000 20 45,000 Mtwara 379 287,873 33 35,000 32 100,000 Ruvuma 432 310,014 104 34,000 363 111,364 Iringa 1569 338,221 791 46,536 925 72,699 Mbeya 119 382,222 . 10 638 122,500 Singida 50 235,001 17 32,500 . . Tabora . . . . . . Rukwa 373 282,600 60 22,000 133 53,000 Kigoma 11 201,250 3 3,000 . . Shinyanga 4 600,000 10 55,000 . . Kagera 16686 284,144 98 25,000 10 120,000 Mwanza 1184 258,893 20 35,000 150 130,000 Mara 650 253,462 70 26,000 35 15,000 Manyara 590 318,038 154 28,148 29 65,000 North Unguja 26 340,385 13 37,500 . . South Unguja 2 500,000 2 50,000 . . Urban West 2 200,000 . . . . North Pemba . . . . . . South Pemba . . . . . . Total 35054 314,054 6179 51,349 4917 86,061 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 213 9.1.14 Quantity of livestock products and Average Price by Region Region Beef Goat meat/Mutton Pig meat Quantity Sold During (tons) 2007/08 Number of livestock slaughtered Average price per tonne 2007/08 Quantit y Sold During (tons) 2007/08 Number of livestock slaughtere d Averag e price per tonne 2007/08 Quantit y Sold During (tons) 2007/08 Number of livestock slaughtere d Averag e price per tonne 2007/08 Dodoma 4,551 42 2,823 2,190 14 4,654 . . . Arusha 2,587 18 3,000 . . . 8 10 . Kilimanjaro 14,255 58 58,420 153 25 151,700 217 75 367,667 Tanga 512 2,584 41,361 1 90 181,600 . 3 . Morogoro 12 6 3,800 250 10 4,000 . . . Pwani 2,277 884 3,175 . . . 1,170 15 3,500 Dar es salaam 30 4 3,500 15 5 4,000 15 70 3,002 Lindi 1,729 31 3,600 1 20 2,800 . . . Mtwara 695 62 2,764 135 19 3,167 8 104 2,350 Ruvuma 4,361 249 4,948 708 63 2,795 3,377 199 3,250 Iringa 941 273 70,536 12 348 62,700 36 168 164,125 Mbeya 6 37 14,250 5 25 . 47 770 2,500 Singida . . . . . . . 7 . Tabora . . . . . . 104 36 2,333 Rukwa 801 25 2,000 91 4 1,200 1,500 20 1,500 Kigoma 150 1 2,000 . . . . . . Shinyanga . . . . . . . . . Kagera 16,538 395 15,986 . 11 4,000 . . . Mwanza 21 60 2,000 . . . 21,720 362 3,000 Mara . . . . . . . . . Manyara 10 200 3,000 72 5 19,000 . . . North Unguja . . . . . . . . . South Unguja . . . . . . . . . Urban West . . . . . . . . . North Pemba . . . . . . . . . South Pemba . . . . . . . . . Total 49,476 4,929 27,560 3,633 639 46,639 28,202 1,839 85,588 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 214 9,1,15 Number of Livestock Sold and Average price by Sales Market Sales Market Live cattle Live goats/sheep Live pigs Number Sold During 2007/08 Average sold during 2007/08 Number Sold During 2007/08 Average sold during 2007/08 Number Sold During 2007/08 Average sold during 2007/08 Neighbour 2447 348,021 1727 62,774 2455 82,245 Local Market 305 216,600 65 23,500 129 3,750 Secondary Market 3517 280,606 2372 46,569 87 190,000 Processing industry 916 410,000 . . 180 150,000 Largescale farm 9485 445,109 57 60,000 . . Trader at farm 17250 302,779 1437 44,265 1664 86,742 Did not sell 62 300,000 214 30,003 390 100,000 Other 1072 291,542 307 47,333 12 70,000 Total 35054 314,054 6179 51,349 4917 86,061 9.1.16 Quantity of livestock products and Average Price by sales destinations Sales Destination Beef Goat meat/Mutton Pig meat Quantity Sold During (tons) 2007/08 Number of livestock slaughtered Average price per tonne 2007/08 Quantity Sold During (tons) 2007/08 Number of livestock slaughtered Average price per tonne 2007/08 Quantity Sold During (tons) 2007/08 Number of livestock slaughtered Average price per tonne 2007/08 Neighbour 7,770 2,298 2,696 2,396 89 2,935 23,293 1,396 2,150 Local Market 899 162 3,300 4 186 8,000 103 87 2,500 Secondary Market 10 200 3,000 36 3 35,000 . . . Processing industry . . . . . . . . . Largescale farm . . . . . . . . . Trader at farm 33,258 629 23,558 80 42 2,528 51 108 217,667 Did not sell 3,439 175 75,675 859 114 110,567 222 155 276,625 Other 4,100 1,465 95,357 258 205 125,333 4,533 93 4,500 Total 49,476 4,929 27,560 3,633 639 46,639 28,202 1,839 85,588 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 215 9.1.17 Chicken Popolation in Large Scale Farms as of 31st October 2008 by Region Region Indigenous Chicken Layer Broiler Number of Chicken as of Oct 31, 2007/08 Number sold during 2007/08 Avera ge Price/ Head Quntity Slaughter e (Kg) during 2007/08 Average Price/kg Number of Chicken as of Oct 31, 2007/08 Number sold during 2007/08 Avera ge Price/ Head Quntity Slaughter e (Kg) during 2007/08 Average Price/kg Number of Chicken as of Oct 31, 2007/08 Number sold during 2007/08 Avera ge Price/ Head Quntity Slaughter e (Kg) during 2007/08 Average Price/kg Dodoma 423 70 3,141 2 1,002 . . . . . . . . . . Arusha 57 . . 18 3,500 50 . . . . 708 264 4,400 600 4,000 Kilimanjaro 200 . 8,000 31 4,000 2,666 530 6,000 16 3,000 19,210 9,265 6,800 4,673 2,833 Tanga 1,332 580 7,714 23 2,766 2,400 100 3,000 . . 1,600 2,400 5,500 3 3,000 Morogoro 1,017 775 4,000 43 4,000 1,324 1,722 4,500 36,000 4,500 3,200 43,400 3,767 . 4,200 Pwani 5,202 2,728 6,400 36 5,200 56,982 17,800 4,571 867 3,833 126,089 19,550 5,300 35,166 4,333 Dar es salaam 835 387 16,167 15 3,516 39,576 25,650 4,750 2 2,500 61,510 63,740 3,300 2,001 12,667 Lindi 340 70 7,000 30 4,000 . . . . . . . . . . Mtwara 995 146 4,643 17 4,667 620 . . . . 280 200 4,000 . . Ruvuma 1,280 104 4,333 58 3,833 863 156 6,000 111 4,750 . . . . . Iringa 2,521 586 5,192 2,452 7,179 98,131 93,328 4,333 48 4,667 12,690 10,579 2,950 453 5,100 Mbeya 336 150 4,000 30 2,750 100 1,000 3,500 . . 500 . . . . Singida 459 10 3,000 3 4,375 . . . . . . . . . . Tabora 580 36 4,667 15 3,000 380 120 5,000 8 350 . . . . . Rukwa 146 . . . . 34 . . . . . . . . . Kigoma 58 20 5,000 90 5,000 . . . . . . . . . . Shinyanga 4,530 100 4,500 . . 6,000 450 4,250 . . . . . . . Kagera 181 . 6,000 14 6,000 . . . . . . . . . . Mwanza 1,458 251 7,083 15 3,263 12,818 803 5,000 . . 4,400 400 5,000 . . Mara 588 85 4,250 25 2,750 400 . 5,000 . . 600 600 6,000 . . Manyara 843 238 7,340 18 2,884 360 280 100 . 10 80 80 . 280 3,750 North Unguja 1,590 502 5,200 2 4,000 8,760 718 4,000 . . 1,100 9,100 4,250 . . South Unguja . . . . . 1,500 300 4,000 . . . . . . . Urban West . . . . . 2,959 . . . . 2,005 2,005 4,000 . . Total 24,971 6,838 6,386 314 4,073 235,923 142,957 4,551 2,997 3,419 233,972 161,583 4,597 7,985 5,456 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 216 9.1.18 Population of other Livestock as of 31st October 2008 by Region Region Ducks Turkeys Rabbits Donkeys Horses Other(sp ecify) Dodoma 76 35 20 10 . . Kilimanjaro 118 45 200 . 4 10 Tanga 186 1 . 16 . 32 Morogoro 75 11 80 6 . 73 Pwani 3,819 155 7 . 10 2,411 Dar es salaam 245 178 38 8 4 207 Mtwara 123 . . . . 56 Ruvuma 127 4 82 18 . 66 Iringa 130 31 482 10 24 10,094 Mbeya . . 20 . . 32 Singida 9 . . 26 . . Tabora 20 2 . 16 . . Rukwa . . 21 3 . 3 Kigoma . 4 . . . . Shinyanga 16 4 8 . . 2 Kagera . . . 25 15 . Mwanza 13 120 30 . . 75 Mara 32 . . 7 . 21,009 Manyara 25 . . 2 . 1 North Unguja 259 22 . . . . South Unguja 20 . . . . . Total 5,293 612 988 147 57 34,071 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 217 Continued 9.1.19 Chicken Disease by Region Region Newcastle Disease Gumboro Coccidiosis Number infected Number Treated Number Died Number Recovered Number infected Number Treated Number Died Number Recovered Number infected Number Treated Number Died Number Recovered Dodoma 139 . 35 19 . . . . . . . . Arusha . 180 . . . . . . 6,180 6,180 54 31,950 Kilimanjaro 320 320 30 290 320 320 . . 629 812 8 159 Tanga 70 20 13 9 . . . . 10,000 10,000 4,900 100 Morogoro 614 597 45 52 4,000 4,000 200 3,800 1,432 1,432 70 306 Pwani 654 453 49 69 22,600 25,250 883 5,035 76,434 78,514 248 4,086 Dar es salaam 10,510 550 269 4,484 5,902 5,900 366 3,095 2,183 2,880 55 2,186 Lindi . . . . . . . . . . . . Mtwara 186 163 21 20 . . . . . . . . Ruvuma 757 737 30 113 14 14 2 12 148 148 8 42 Iringa 859 1,193 34 69 184 184 26 40 1,138 1,022 36 59 Mbeya 5 5 5 . . . . . 34 34 5 29 Singida 192 133 13 5 . . . . . . . . Tabora 490 275 61 52 20 310 20 12 60 60 20 40 Rukwa . 100 . 100 . . . . . . . . Kigoma 5 20 5 53 . . . . . . . . Shinyanga 500 . 240 260 200 . 120 80 2,000 2,000 . . Kagera . . . . . . . . . . . . Mwanza 246 174 9 12 147 147 7 18 164 164 5 11 Mara 162 77 36 18 . . . . 609 600 9 . Manyara 425 76 20 12 20 . 15 5 58 33 4 6 North Unguja 31 8,105 16 1,617 360 2,800 290 1,430 1,500 5,040 50 998 South Unguja 1,000 . 600 400 . . . . . . . . Urban West . . . . . . . . 2,959 2,959 150 2,805 North Pemba . . . . . . . . . . . . South Pemba . . . . . . . . . . . . 00 . . . . . . . . . . . . Total 17,165 13,178 43 332 33,767 38,925 247 1,694 105,528 111,878 250 1,909 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 218 Cont…9.1.19….Chicken Disease by Region Region Chorysa Fowl typhoid Number infected Number Treated Number Died Number Recovered Number infected Number Treated Number Died Number Recovered Dodoma . . . . . . . . Arusha 6,000 6,000 50 5,950 65 65 20 61,300 Kilimanjaro 20 20 15 5 160 398 . 75 Tanga . . . . . . . . Morogoro 150 150 20 55 360 337 12 34 Pwani 54,589 56,083 3,757 4,078 10 10 3 7 Dar es salaam 6,017 7,150 61 2,681 13,943 67,892 232 2,889 Lindi . . . 1 . . . . Mtwara 65 64 30 6 23 6 9 6 Ruvuma 30 20 8 22 130 130 20 110 Iringa 341 310 34 22 1,306 264 113 57 Mbeya 29 9 3 6 20 20 . 20 Singida . . . . . . . . Tabora . . . . 175 175 10 83 Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga 2,800 2,800 20 300 1,758 1,758 16 248 Kagera 100 100 10 100 . . . . Mwanza 10 10 5 5 122 122 29 47 Mara . . . . . . . . Manyara 18 18 . 9 . . . . North Unguja 1,950 5,190 20 1,034 260 2,110 10 1,050 South Unguja 800 800 5 795 . . . . Urban West 10 2,005 . 2,005 . . . . North Pemba . . . . . . . . South Pemba . . . . . . . . 00 . . . . . . . . Total 72,929 80,729 964 1,800 18,332 73,287 85 2,222 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 219 9.1.20 Chicken DIsease: Number infected, Number Trated and Recovered by type of Disease Type of Disease Number Infected Number Treated Number Died Number Recovered Average Total % Average Total % Average Total % Average Total % Newcastle Disease 148 17,165 7 155 13,178 4 43 4,538 8 332 30,219 8 Gumboro 1,251 33,767 14 1,557 38,925 12 247 5,192 9 1,694 45,745 12 Coccidiosis 1,389 105,528 43 1,554 111,878 35 250 13,266 24 1,909 137,456 35 Chorysa 1,376 72,929 29 1,682 80,729 25 964 30,832 55 1,800 91,813 23 Fowl typhoid 399 18,332 7 1,745 73,287 23 85 2,379 4 2,222 91,106 23 Total 779 247,721 100 1,169 317,997 100 235 56,207 100 1,405 396,339 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 220 9.1.21 ANIMAL PRODUCTS: Eggs, Hides and Skins sold, utilized and average price during 2007/08 by Region Region Eggs Hides Skins Number Sold Average price/unit sold Number Consumed/utilised Average price/unit consumed/utilised Number Sold Average price/unit sold Number Consumed/utilised Average price/unit consumed/utilised Number Sold Average price/unit sold Number Consumed/utilised Average price/unit consumed utilised Dodoma 750 200 750 200 12 1,000 . . . . . . Arusha 72 200 200 100 54 10,000 54 402 52 400 . . Kilimanjaro 2,501 167 504 129 3 1,000 . . . . . . Tanga 475 116 209 105 40 1,333 . . 40 800 . . Morogoro 2,628 139 600 172 4 300 . 7 20 500 20 254 Pwani 4,680 154 3,592 163 707 4,917 . . 5 2,000 5 4,200 Dar es salaam 2,207 185 2,397 305 5 2,500 . . 11 1,250 . . Lindi 1 150 420 100 . . . . . . . . Mtwara 108 107 1,007 153 2 5,500 3 32,500 . . 3 5,000 Ruvuma 2,070 183 1,482 180 34 3,500 10 3,000 39 1,333 6 1,000 Iringa 3,947 164 2,909 157 288 3,900 . . 25 2,500 . . Mbeya 397 200 520 140 20 4,000 . . . . . 1 Singida . . . . . . . . . . . . Tabora 174 138 484 142 22 3,500 22 3,500 5 500 . . Rukwa 962 175 4 8 . . . . 1 . . . Kigoma 80 150 120 150 . . . . . . . . Shinyanga 652 177 651 200 . . . . . . . . Kagera 3 200 2 135 243 2,275 . . . . . . Mwanza 319 192 81 191 63 6,500 . . 1 1,000 . . Mara 128 150 306 84 230 1,750 . . 6 400 . . Manyara 1,249 129 1,937 114 1 9,900 . 200 . . . . North Unguja 1,689 176 960 185 . . . . . . . . South Unguja 144 160 1 100 . . . . . . . . Urban West 24 160 . . . . . . . . . . North Pemba . . . . . . . . . . . . South Pemba . . . . . . . . . . . . APPENDIX II Tanzania Agriculture Sample Census - 2007/08 221 RANK OF LIVESTOCK MARKET OUTLET APPENDIX II Tanzania Agriculture Sample Census - 2007/08 222 9.2.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Livestock by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 2 22.2 3 33.3 2 22.2 0 .0 2 22.2 0 .0 9 100.0 Arusha 5 29.4 11 64.7 0 .0 0 .0 1 5.9 0 .0 17 100.0 Kilimanjaro 5 50.0 1 10.0 1 10.0 1 10.0 2 20.0 0 .0 10 100.0 Tanga 19 76.0 2 8.0 0 .0 1 4.0 2 8.0 1 4.0 25 100.0 Morogoro 9 26.5 16 47.1 0 .0 1 2.9 7 20.6 1 2.9 34 100.0 Pwani 11 45.8 6 25.0 1 4.2 2 8.3 4 16.7 0 .0 24 100.0 Dar es salaam 6 66.7 0 .0 0 .0 1 11.1 2 22.2 0 .0 9 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Mtwara 5 62.5 0 .0 0 .0 2 25.0 1 12.5 0 .0 8 100.0 Ruvuma 16 64.0 1 4.0 0 .0 3 12.0 2 8.0 3 12.0 25 100.0 Iringa 17 39.5 1 2.3 3 7.0 1 2.3 13 30.2 8 18.6 43 100.0 Mbeya 4 36.4 4 36.4 1 9.1 0 .0 2 18.2 0 .0 11 100.0 Singida 2 8.7 20 87.0 0 .0 0 .0 1 4.3 0 .0 23 100.0 Tabora 1 16.7 4 66.7 0 .0 0 .0 0 .0 1 16.7 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 3 100.0 0 .0 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 13 41.9 14 45.2 1 3.2 0 .0 3 9.7 0 .0 31 100.0 Mwanza 6 19.4 22 71.0 1 3.2 1 3.2 1 3.2 0 .0 31 100.0 Mara 5 31.3 9 56.3 1 6.3 1 6.3 0 .0 0 .0 16 100.0 Manyara 21 48.8 20 46.5 0 .0 0 .0 1 2.3 1 2.3 43 100.0 North Unguja 3 60.0 0 .0 2 40.0 0 .0 0 .0 0 .0 5 100.0 South Unguja 1 50.0 0 .0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Urban West 2 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 North Pemba 4 80.0 1 20.0 0 .0 0 .0 0 .0 0 .0 5 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 157 41.0 135 35.2 13 3.4 17 4.4 46 12.0 15 3.9 383 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 223 9.2.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 3 37.5 2 25.0 0 .0 3 37.5 0 .0 0 .0 8 100.0 Arusha 8 42.1 3 15.8 0 .0 0 .0 7 36.8 1 5.3 19 100.0 Kilimanjaro 0 .0 4 40.0 0 .0 2 20.0 3 30.0 1 10.0 10 100.0 Tanga 5 27.8 2 11.1 0 .0 3 16.7 6 33.3 2 11.1 18 100.0 Morogoro 8 26.7 7 23.3 1 3.3 6 20.0 5 16.7 3 10.0 30 100.0 Pwani 1 6.3 0 .0 0 .0 6 37.5 9 56.3 0 .0 16 100.0 Dar es salaam 1 14.3 1 14.3 0 .0 2 28.6 3 42.9 0 .0 7 100.0 Lindi 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Mtwara 2 28.6 2 28.6 0 .0 0 .0 2 28.6 1 14.3 7 100.0 Ruvuma 2 8.7 2 8.7 5 21.7 5 21.7 9 39.1 0 .0 23 100.0 Iringa 12 34.3 2 5.7 5 14.3 1 2.9 11 31.4 4 11.4 35 100.0 Mbeya 2 25.0 0 .0 0 .0 2 25.0 4 50.0 0 .0 8 100.0 Singida 11 55.0 1 5.0 0 .0 0 .0 8 40.0 0 .0 20 100.0 Tabora 3 50.0 1 16.7 0 .0 1 16.7 0 .0 1 16.7 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 2 66.7 0 .0 0 .0 0 .0 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 7 22.6 10 32.3 2 6.5 0 .0 11 35.5 1 3.2 31 100.0 Mwanza 3 10.0 7 23.3 1 3.3 9 30.0 9 30.0 1 3.3 30 100.0 Mara 3 18.8 2 12.5 0 .0 4 25.0 6 37.5 1 6.3 16 100.0 Manyara 12 27.3 19 43.2 2 4.5 7 15.9 2 4.5 2 4.5 44 100.0 North Unguja 0 .0 1 16.7 0 .0 2 33.3 3 50.0 0 .0 6 100.0 South Unguja 1 50.0 0 .0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Urban West 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 North Pemba 0 .0 2 66.7 0 .0 0 .0 1 33.3 0 .0 3 100.0 South Pemba 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Total 85 24.6 73 21.1 16 4.6 53 15.3 101 29.2 18 5.2 346 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 224 9.2.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 1 16.7 1 16.7 1 16.7 3 50.0 0 .0 6 100.0 Arusha 2 12.5 2 12.5 1 6.3 3 18.8 6 37.5 2 12.5 16 100.0 Kilimanjaro 1 14.3 1 14.3 2 28.6 1 14.3 0 .0 2 28.6 7 100.0 Tanga 2 18.2 3 27.3 1 9.1 2 18.2 3 27.3 0 .0 11 100.0 Morogoro 4 23.5 3 17.6 1 5.9 5 29.4 3 17.6 1 5.9 17 100.0 Pwani 3 21.4 1 7.1 3 21.4 2 14.3 3 21.4 2 14.3 14 100.0 Dar es salaam 1 16.7 0 .0 1 16.7 1 16.7 2 33.3 1 16.7 6 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 1 33.3 2 66.7 3 100.0 Ruvuma 3 15.0 3 15.0 4 20.0 4 20.0 6 30.0 0 .0 20 100.0 Iringa 3 9.4 3 9.4 3 9.4 7 21.9 7 21.9 9 28.1 32 100.0 Mbeya 2 25.0 1 12.5 1 12.5 2 25.0 2 25.0 0 .0 8 100.0 Singida 6 66.7 0 .0 0 .0 3 33.3 0 .0 0 .0 9 100.0 Tabora 1 16.7 0 .0 0 .0 2 33.3 2 33.3 1 16.7 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 0 .0 1 33.3 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 6 19.4 4 12.9 8 25.8 2 6.5 9 29.0 2 6.5 31 100.0 Mwanza 2 13.3 0 .0 7 46.7 1 6.7 2 13.3 3 20.0 15 100.0 Mara 2 12.5 0 .0 1 6.3 2 12.5 6 37.5 5 31.3 16 100.0 Manyara 4 11.1 3 8.3 7 19.4 3 8.3 19 52.8 0 .0 36 100.0 North Unguja 0 .0 4 66.7 2 33.3 0 .0 0 .0 0 .0 6 100.0 South Unguja 0 .0 1 50.0 0 .0 1 50.0 0 .0 0 .0 2 100.0 Urban West 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 North Pemba 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 43 16.0 32 11.9 44 16.4 42 15.7 77 28.7 30 11.2 268 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 225 9.2.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 2 28.6 1 14.3 0 .0 1 14.3 1 14.3 2 28.6 7 100.0 Arusha 2 13.3 1 6.7 3 20.0 5 33.3 0 .0 4 26.7 15 100.0 Kilimanjaro 0 .0 1 16.7 0 .0 3 50.0 1 16.7 1 16.7 6 100.0 Tanga 2 20.0 1 10.0 2 20.0 2 20.0 1 10.0 2 20.0 10 100.0 Morogoro 2 13.3 1 6.7 3 20.0 1 6.7 8 53.3 0 .0 15 100.0 Pwani 2 18.2 3 27.3 1 9.1 1 9.1 2 18.2 2 18.2 11 100.0 Dar es salaam 0 .0 2 50.0 1 25.0 0 .0 0 .0 1 25.0 4 100.0 Lindi 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Mtwara 0 .0 0 .0 0 .0 3 100.0 0 .0 0 .0 3 100.0 Ruvuma 1 5.6 2 11.1 4 22.2 5 27.8 2 11.1 4 22.2 18 100.0 Iringa 2 7.1 5 17.9 6 21.4 8 28.6 4 14.3 3 10.7 28 100.0 Mbeya 1 14.3 1 14.3 0 .0 4 57.1 1 14.3 0 .0 7 100.0 Singida 0 .0 0 .0 0 .0 0 .0 2 100.0 0 .0 2 100.0 Tabora 0 .0 0 .0 1 16.7 2 33.3 1 16.7 2 33.3 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 0 .0 1 33.3 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 5 17.9 1 3.6 7 25.0 12 42.9 1 3.6 2 7.1 28 100.0 Mwanza 2 25.0 0 .0 1 12.5 1 12.5 1 12.5 3 37.5 8 100.0 Mara 3 20.0 4 26.7 3 20.0 1 6.7 0 .0 4 26.7 15 100.0 Manyara 5 16.1 3 9.7 8 25.8 7 22.6 7 22.6 1 3.2 31 100.0 North Unguja 2 33.3 1 16.7 2 33.3 0 .0 1 16.7 0 .0 6 100.0 South Unguja 0 .0 0 .0 1 50.0 0 .0 0 .0 1 50.0 2 100.0 Urban West 0 .0 0 .0 1 50.0 1 50.0 0 .0 0 .0 2 100.0 North Pemba 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 33 14.4 27 11.8 46 20.1 57 24.9 34 14.8 32 14.0 229 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 226 9.2.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Cattle by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer 6 Other (Specify) Total Number % Number % Number % Numbe r % Number % Number % Numbe r % Number % Dodoma 0 .0 1 14.3 2 28.6 0 .0 2 28.6 0 .0 2 28.6 7 100.0 Arusha 2 13.3 1 6.7 3 20.0 4 26.7 0 .0 0 .0 5 33.3 15 100.0 Kilimanjaro 1 16.7 1 16.7 2 33.3 0 .0 1 16.7 0 .0 1 16.7 6 100.0 Tanga 1 12.5 1 12.5 1 12.5 1 12.5 3 37.5 0 .0 1 12.5 8 100.0 Morogoro 1 20.0 1 20.0 0 .0 1 20.0 1 20.0 0 .0 1 20.0 5 100.0 Pwani 1 8.3 1 8.3 2 16.7 1 8.3 3 25.0 0 .0 4 33.3 12 100.0 Dar es salaam 0 .0 1 20.0 2 40.0 0 .0 1 20.0 0 .0 1 20.0 5 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 1 33.3 0 .0 0 .0 2 66.7 0 .0 0 .0 3 100.0 Ruvuma 1 6.7 3 20.0 2 13.3 2 13.3 1 6.7 0 .0 6 40.0 15 100.0 Iringa 1 3.8 2 7.7 10 38.5 8 30.8 1 3.8 0 .0 4 15.4 26 100.0 Mbeya 0 .0 0 .0 3 75.0 0 .0 0 .0 0 .0 1 25.0 4 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Tabora 0 .0 0 .0 2 33.3 0 .0 2 33.3 0 .0 2 33.3 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 1 33.3 0 .0 1 33.3 0 .0 1 33.3 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 4 14.3 6 21.4 0 .0 0 .0 18 64.3 28 100.0 Mwanza 0 .0 0 .0 3 37.5 2 25.0 0 .0 0 .0 3 37.5 8 100.0 Mara 2 13.3 1 6.7 1 6.7 5 33.3 3 20.0 0 .0 3 20.0 15 100.0 Manyara 3 12.5 2 8.3 6 25.0 1 4.2 3 12.5 1 4.2 8 33.3 24 100.0 North Unguja 0 .0 0 .0 0 .0 4 66.7 2 33.3 0 .0 0 .0 6 100.0 South Unguja 0 .0 1 50.0 0 .0 1 50.0 0 .0 0 .0 0 .0 2 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 13 6.4 17 8.4 44 21.8 36 17.8 26 12.9 1 .5 65 32.2 202 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 227 9.3.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 1 16.7 3 50.0 0 .0 0 .0 2 33.3 0 .0 6 100.0 Arusha 1 14.3 3 42.9 0 .0 0 .0 3 42.9 0 .0 7 100.0 Kilimanjaro 3 37.5 1 12.5 1 12.5 1 12.5 1 12.5 1 12.5 8 100.0 Tanga 9 64.3 1 7.1 0 .0 1 7.1 3 21.4 0 .0 14 100.0 Morogoro 7 36.8 6 31.6 1 5.3 0 .0 3 15.8 2 10.5 19 100.0 Pwani 7 50.0 5 35.7 1 7.1 1 7.1 0 .0 0 .0 14 100.0 Dar es salaam 4 57.1 0 .0 0 .0 1 14.3 0 .0 2 28.6 7 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 2 50.0 0 .0 0 .0 2 50.0 0 .0 0 .0 4 100.0 Ruvuma 14 73.7 1 5.3 1 5.3 1 5.3 1 5.3 1 5.3 19 100.0 Iringa 9 39.1 0 .0 1 4.3 1 4.3 7 30.4 5 21.7 23 100.0 Mbeya 2 66.7 1 33.3 0 .0 0 .0 0 .0 0 .0 3 100.0 Singida 3 15.0 16 80.0 0 .0 0 .0 1 5.0 0 .0 20 100.0 Tabora 1 25.0 2 50.0 0 .0 0 .0 0 .0 1 25.0 4 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 3 100.0 0 .0 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 1 25.0 1 25.0 0 .0 0 .0 2 50.0 0 .0 4 100.0 Mwanza 1 4.8 18 85.7 1 4.8 1 4.8 0 .0 0 .0 21 100.0 Mara 4 44.4 5 55.6 0 .0 0 .0 0 .0 0 .0 9 100.0 Manyara 11 55.0 6 30.0 0 .0 0 .0 1 5.0 2 10.0 20 100.0 North Unguja 2 40.0 0 .0 2 40.0 1 20.0 0 .0 0 .0 5 100.0 South Unguja 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 2 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 85 39.9 69 32.4 8 3.8 13 6.1 24 11.3 14 6.6 213 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 228 9.3.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Goats by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 3 50.0 1 16.7 0 .0 2 33.3 0 .0 0 .0 6 100.0 Arusha 5 55.6 2 22.2 0 .0 1 11.1 0 .0 1 11.1 9 100.0 Kilimanjaro 1 12.5 3 37.5 1 12.5 1 12.5 1 12.5 1 12.5 8 100.0 Tanga 4 40.0 0 .0 0 .0 2 20.0 4 40.0 0 .0 10 100.0 Morogoro 3 21.4 6 42.9 2 14.3 1 7.1 1 7.1 1 7.1 14 100.0 Pwani 2 18.2 0 .0 0 .0 4 36.4 5 45.5 0 .0 11 100.0 Dar es salaam 1 16.7 1 16.7 0 .0 2 33.3 2 33.3 0 .0 6 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 1 33.3 0 .0 0 .0 0 .0 2 66.7 0 .0 3 100.0 Ruvuma 2 11.1 2 11.1 2 11.1 4 22.2 8 44.4 0 .0 18 100.0 Iringa 6 35.3 0 .0 3 17.6 3 17.6 5 29.4 0 .0 17 100.0 Mbeya 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Singida 9 50.0 2 11.1 0 .0 0 .0 7 38.9 0 .0 18 100.0 Tabora 1 25.0 1 25.0 0 .0 1 25.0 0 .0 1 25.0 4 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 2 66.7 0 .0 0 .0 0 .0 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 1 50.0 1 50.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Mwanza 3 15.0 1 5.0 2 10.0 6 30.0 7 35.0 1 5.0 20 100.0 Mara 3 33.3 1 11.1 0 .0 1 11.1 3 33.3 1 11.1 9 100.0 Manyara 3 14.3 6 28.6 1 4.8 6 28.6 2 9.5 3 14.3 21 100.0 North Unguja 2 40.0 0 .0 0 .0 2 40.0 1 20.0 0 .0 5 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 51 27.3 30 16.0 11 5.9 37 19.8 49 26.2 9 4.8 187 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 229 9.3.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 1 20.0 1 20.0 0 .0 3 60.0 0 .0 5 100.0 Arusha 1 14.3 2 28.6 0 .0 0 .0 4 57.1 0 .0 7 100.0 Kilimanjaro 0 .0 0 .0 0 .0 2 40.0 1 20.0 2 40.0 5 100.0 Tanga 1 14.3 2 28.6 0 .0 2 28.6 2 28.6 0 .0 7 100.0 Morogoro 1 12.5 3 37.5 0 .0 1 12.5 3 37.5 0 .0 8 100.0 Pwani 2 22.2 1 11.1 1 11.1 1 11.1 3 33.3 1 11.1 9 100.0 Dar es salaam 1 25.0 0 .0 1 25.0 0 .0 2 50.0 0 .0 4 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 4 25.0 1 6.3 1 6.3 6 37.5 4 25.0 0 .0 16 100.0 Iringa 3 17.6 3 17.6 0 .0 0 .0 5 29.4 6 35.3 17 100.0 Mbeya 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Singida 6 66.7 0 .0 1 11.1 0 .0 2 22.2 0 .0 9 100.0 Tabora 1 25.0 0 .0 0 .0 1 25.0 1 25.0 1 25.0 4 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 0 .0 1 33.3 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 2 100.0 0 .0 0 .0 0 .0 2 100.0 Mwanza 4 36.4 1 9.1 2 18.2 0 .0 2 18.2 2 18.2 11 100.0 Mara 1 11.1 1 11.1 0 .0 1 11.1 1 11.1 5 55.6 9 100.0 Manyara 2 12.5 2 12.5 1 6.3 0 .0 9 56.3 2 12.5 16 100.0 North Unguja 0 .0 3 60.0 2 40.0 0 .0 0 .0 0 .0 5 100.0 South Unguja 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 29 20.9 20 14.4 13 9.4 15 10.8 43 30.9 19 13.7 139 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 230 9.3.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer 6 Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 1 25.0 1 25.0 0 .0 0 .0 2 50.0 4 100.0 Arusha 0 .0 0 .0 4 57.1 3 42.9 0 .0 0 .0 0 .0 7 100.0 Kilimanjaro 1 25.0 1 25.0 0 .0 1 25.0 0 .0 0 .0 1 25.0 4 100.0 Tanga 1 16.7 1 16.7 2 33.3 0 .0 0 .0 0 .0 2 33.3 6 100.0 Morogoro 1 25.0 1 25.0 1 25.0 1 25.0 0 .0 0 .0 0 .0 4 100.0 Pwani 1 16.7 1 16.7 1 16.7 0 .0 2 33.3 0 .0 1 16.7 6 100.0 Dar es salaam 0 .0 2 66.7 1 33.3 0 .0 0 .0 0 .0 0 .0 3 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 2 14.3 2 14.3 2 14.3 3 21.4 0 .0 5 35.7 14 100.0 Iringa 2 14.3 2 14.3 5 35.7 5 35.7 0 .0 0 .0 0 .0 14 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Singida 0 .0 0 .0 0 .0 2 100.0 0 .0 0 .0 0 .0 2 100.0 Tabora 0 .0 0 .0 0 .0 1 25.0 1 25.0 0 .0 2 50.0 4 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 0 .0 1 33.3 0 .0 1 33.3 0 .0 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 1 50.0 1 50.0 0 .0 0 .0 2 100.0 Mwanza 0 .0 0 .0 1 16.7 2 33.3 0 .0 0 .0 3 50.0 6 100.0 Mara 1 12.5 0 .0 3 37.5 3 37.5 1 12.5 0 .0 0 .0 8 100.0 Manyara 2 13.3 1 6.7 3 20.0 2 13.3 1 6.7 1 6.7 5 33.3 15 100.0 North Unguja 2 40.0 2 40.0 1 20.0 0 .0 0 .0 0 .0 0 .0 5 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 12 11.0 13 11.9 26 23.9 24 22.0 11 10.1 1 .9 22 20.2 109 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 231 9.3.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Goat by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 1 25.0 1 25.0 0 .0 0 .0 1 25.0 1 25.0 4 100.0 Arusha 2 28.6 0 .0 0 .0 1 14.3 0 .0 4 57.1 7 100.0 Kilimanjaro 1 25.0 1 25.0 0 .0 0 .0 1 25.0 1 25.0 4 100.0 Tanga 1 25.0 1 25.0 0 .0 1 25.0 0 .0 1 25.0 4 100.0 Morogoro 0 .0 2 50.0 0 .0 0 .0 0 .0 2 50.0 4 100.0 Pwani 0 .0 1 16.7 1 16.7 1 16.7 1 16.7 2 33.3 6 100.0 Dar es salaam 0 .0 1 20.0 2 40.0 0 .0 1 20.0 1 20.0 5 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Ruvuma 0 .0 1 11.1 1 11.1 1 11.1 2 22.2 4 44.4 9 100.0 Iringa 1 8.3 2 16.7 3 25.0 4 33.3 0 .0 2 16.7 12 100.0 Mbeya 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Tabora 0 .0 0 .0 1 25.0 0 .0 1 25.0 2 50.0 4 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 1 33.3 0 .0 1 33.3 1 33.3 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Mwanza 0 .0 0 .0 3 60.0 0 .0 2 40.0 0 .0 5 100.0 Mara 0 .0 2 25.0 3 37.5 0 .0 1 12.5 2 25.0 8 100.0 Manyara 2 15.4 2 15.4 1 7.7 1 7.7 1 7.7 6 46.2 13 100.0 North Unguja 0 .0 0 .0 0 .0 2 40.0 3 60.0 0 .0 5 100.0 South Unguja 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 8 8.0 15 15.0 17 17.0 11 11.0 16 16.0 33 33.0 100 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 232 9.4.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 1 25.0 3 75.0 0 .0 0 .0 0 .0 0 .0 4 100.0 Arusha 2 66.7 1 33.3 0 .0 0 .0 0 .0 0 .0 3 100.0 Kilimanjaro 2 33.3 1 16.7 1 16.7 1 16.7 0 .0 1 16.7 6 100.0 Tanga 5 62.5 1 12.5 0 .0 1 12.5 1 12.5 0 .0 8 100.0 Morogoro 6 46.2 3 23.1 2 15.4 0 .0 0 .0 2 15.4 13 100.0 Pwani 7 50.0 5 35.7 0 .0 1 7.1 1 7.1 0 .0 14 100.0 Dar es salaam 2 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 1 25.0 0 .0 0 .0 2 50.0 1 25.0 0 .0 4 100.0 Ruvuma 8 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 8 100.0 Iringa 6 31.6 1 5.3 1 5.3 1 5.3 6 31.6 4 21.1 19 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Singida 1 9.1 9 81.8 0 .0 0 .0 1 9.1 0 .0 11 100.0 Tabora 1 50.0 1 50.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 1 50.0 1 50.0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 1 50.0 0 .0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Mwanza 1 14.3 4 57.1 1 14.3 0 .0 0 .0 1 14.3 7 100.0 Mara 4 57.1 3 42.9 0 .0 0 .0 0 .0 0 .0 7 100.0 Manyara 2 18.2 4 36.4 0 .0 1 9.1 3 27.3 1 9.1 11 100.0 North Unguja 0 .0 0 .0 2 66.7 0 .0 1 33.3 0 .0 3 100.0 South Unguja 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 51 40.2 36 28.3 7 5.5 8 6.3 16 12.6 9 7.1 127 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 233 9.4.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 3 75.0 0 .0 0 .0 1 25.0 0 .0 0 .0 4 100.0 Arusha 1 20.0 3 60.0 0 .0 0 .0 1 20.0 0 .0 5 100.0 Kilimanjaro 0 .0 1 20.0 2 40.0 0 .0 1 20.0 1 20.0 5 100.0 Tanga 2 40.0 0 .0 0 .0 2 40.0 1 20.0 0 .0 5 100.0 Morogoro 0 .0 5 62.5 2 25.0 1 12.5 0 .0 0 .0 8 100.0 Pwani 1 12.5 0 .0 0 .0 3 37.5 4 50.0 0 .0 8 100.0 Dar es salaam 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 1 33.3 0 .0 0 .0 0 .0 2 66.7 0 .0 3 100.0 Ruvuma 1 14.3 1 14.3 0 .0 1 14.3 4 57.1 0 .0 7 100.0 Iringa 7 50.0 1 7.1 0 .0 1 7.1 4 28.6 1 7.1 14 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Singida 6 60.0 1 10.0 0 .0 0 .0 3 30.0 0 .0 10 100.0 Tabora 0 .0 1 50.0 0 .0 1 50.0 0 .0 0 .0 2 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 2 100.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Mwanza 1 14.3 1 14.3 1 14.3 0 .0 2 28.6 2 28.6 7 100.0 Mara 1 16.7 1 16.7 0 .0 1 16.7 3 50.0 0 .0 6 100.0 Manyara 6 50.0 1 8.3 0 .0 3 25.0 2 16.7 0 .0 12 100.0 North Unguja 0 .0 0 .0 0 .0 2 66.7 1 33.3 0 .0 3 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 30 28.6 20 19.0 5 4.8 16 15.2 30 28.6 4 3.8 105 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 234 9.4.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 0 .0 3 100.0 0 .0 3 100.0 Arusha 0 .0 2 50.0 0 .0 0 .0 2 50.0 0 .0 4 100.0 Kilimanjaro 0 .0 1 25.0 0 .0 2 50.0 0 .0 1 25.0 4 100.0 Tanga 0 .0 0 .0 0 .0 1 33.3 2 66.7 0 .0 3 100.0 Morogoro 0 .0 3 50.0 0 .0 1 16.7 2 33.3 0 .0 6 100.0 Pwani 2 28.6 1 14.3 1 14.3 0 .0 2 28.6 1 14.3 7 100.0 Dar es salaam 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 1 16.7 0 .0 2 33.3 3 50.0 0 .0 6 100.0 Iringa 1 8.3 1 8.3 1 8.3 2 16.7 3 25.0 4 33.3 12 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Singida 3 75.0 0 .0 0 .0 0 .0 1 25.0 0 .0 4 100.0 Tabora 1 50.0 0 .0 0 .0 1 50.0 0 .0 0 .0 2 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 50.0 0 .0 1 50.0 0 .0 0 .0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Mwanza 0 .0 0 .0 3 75.0 0 .0 0 .0 1 25.0 4 100.0 Mara 0 .0 0 .0 1 16.7 1 16.7 1 16.7 3 50.0 6 100.0 Manyara 1 11.1 3 33.3 2 22.2 0 .0 2 22.2 1 11.1 9 100.0 North Unguja 0 .0 3 100.0 0 .0 0 .0 0 .0 0 .0 3 100.0 South Unguja 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 9 11.5 15 19.2 11 14.1 11 14.1 21 26.9 11 14.1 78 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 235 9.4.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Arusha 0 .0 2 50.0 1 25.0 0 .0 0 .0 1 25.0 4 100.0 Kilimanjaro 1 33.3 0 .0 0 .0 1 33.3 0 .0 1 33.3 3 100.0 Tanga 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Morogoro 0 .0 0 .0 1 50.0 1 50.0 0 .0 0 .0 2 100.0 Pwani 1 25.0 0 .0 1 25.0 0 .0 1 25.0 1 25.0 4 100.0 Dar es salaam 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Ruvuma 0 .0 2 33.3 3 50.0 0 .0 0 .0 1 16.7 6 100.0 Iringa 1 7.7 2 15.4 5 38.5 2 15.4 2 15.4 1 7.7 13 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Singida 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Tabora 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 50.0 0 .0 1 50.0 0 .0 0 .0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Mwanza 0 .0 0 .0 1 25.0 1 25.0 0 .0 2 50.0 4 100.0 Mara 1 16.7 0 .0 2 33.3 2 33.3 0 .0 1 16.7 6 100.0 Manyara 4 50.0 2 25.0 1 12.5 0 .0 0 .0 1 12.5 8 100.0 North Unguja 2 66.7 0 .0 1 33.3 0 .0 0 .0 0 .0 3 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 12 18.5 8 12.3 17 26.2 9 13.8 4 6.2 15 23.1 65 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 236 9.4.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Sheep by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Arusha 0 .0 1 25.0 0 .0 3 75.0 0 .0 0 .0 4 100.0 Kilimanjaro 0 .0 0 .0 0 .0 0 .0 2 66.7 1 33.3 3 100.0 Tanga 1 50.0 1 50.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Morogoro 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Pwani 0 .0 0 .0 1 25.0 1 25.0 1 25.0 1 25.0 4 100.0 Dar es salaam 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 0 .0 1 20.0 1 20.0 1 20.0 2 40.0 5 100.0 Iringa 0 .0 1 7.7 4 30.8 6 46.2 0 .0 2 15.4 13 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Tabora 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 1 50.0 1 50.0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Mwanza 0 .0 0 .0 2 40.0 1 20.0 1 20.0 1 20.0 5 100.0 Mara 1 16.7 1 16.7 2 33.3 0 .0 1 16.7 1 16.7 6 100.0 Manyara 1 11.1 2 22.2 2 22.2 0 .0 0 .0 4 44.4 9 100.0 North Unguja 0 .0 0 .0 0 .0 1 33.3 2 66.7 0 .0 3 100.0 South Unguja 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 3 4.5 7 10.4 12 17.9 14 20.9 12 17.9 19 28.4 67 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 237 9.5.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 0 3 100 0 0 0 0 0 0 0 0 3 100 Arusha 1 50 1 50 0 0 0 0 0 0 0 0 2 100 Kilimanjaro 2 67 0 0 0 0 0 0 0 0 1 33 3 100 Tanga 8 67 0 0 1 8.3 0 0 1 8.3 2 17 12 100 Morogoro 4 57 0 0 3 43 0 0 0 0 0 0 7 100 Pwani 10 53 0 0 5 26 1 5.3 2 11 1 5.3 19 100 Dar es salaam 8 44 0 0 8 44 0 0 1 5.6 1 5.6 18 100 Lindi 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 2 67 0 0 0 0 0 0 1 33 0 0 3 100 Ruvuma 9 75 0 0 1 8.3 1 8.3 0 0 1 8.3 12 100 Iringa 9 50 0 0 1 5.6 0 0 3 17 5 28 18 100 Mbeya 0 0 0 0 0 0 0 0 1 50 1 50 2 100 Singida 9 53 0 0 0 0 0 0 8 47 0 0 17 100 Tabora 4 67 1 17 0 0 0 0 0 0 1 17 6 100 Rukwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 2 67 0 0 0 0 1 33 0 0 0 0 3 100 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 1 100 0 0 0 0 0 0 0 0 0 0 1 100 Mwanza 1 11 0 0 2 22 0 0 5 56 1 11 9 100 Mara 3 75 1 25 0 0 0 0 0 0 0 0 4 100 Manyara 6 46 5 39 0 0 0 0 0 0 2 15 13 100 North Unguja 5 63 0 0 3 38 0 0 0 0 0 0 8 100 South Unguja 1 100 0 0 0 0 0 0 0 0 0 0 1 100 Urban West 1 100 0 0 0 0 0 0 0 0 0 0 1 100 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 86 53 11 6.8 24 15 3 1.9 22 14 16 9.9 162 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 238 9.5.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 2 66.7 1 33.3 0 .0 0 .0 0 .0 0 .0 3 100.0 Arusha 0 .0 0 .0 1 50.0 0 .0 1 50.0 0 .0 2 100.0 Kilimanjaro 0 .0 0 .0 1 33.3 0 .0 1 33.3 1 33.3 3 100.0 Tanga 1 11.1 0 .0 1 11.1 1 11.1 4 44.4 2 22.2 9 100.0 Morogoro 4 66.7 0 .0 0 .0 0 .0 2 33.3 0 .0 6 100.0 Pwani 4 30.8 1 7.7 0 .0 2 15.4 5 38.5 1 7.7 13 100.0 Dar es salaam 7 53.8 1 7.7 1 7.7 0 .0 3 23.1 1 7.7 13 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 1 33.3 0 .0 0 .0 0 .0 2 66.7 0 .0 3 100.0 Ruvuma 1 9.1 1 9.1 2 18.2 1 9.1 6 54.5 0 .0 11 100.0 Iringa 3 25.0 0 .0 2 16.7 1 8.3 5 41.7 1 8.3 12 100.0 Mbeya 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Singida 5 29.4 3 17.6 0 .0 0 .0 9 52.9 0 .0 17 100.0 Tabora 1 16.7 4 66.7 0 .0 0 .0 0 .0 1 16.7 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 33.3 1 33.3 0 .0 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Mwanza 5 55.6 0 .0 2 22.2 0 .0 1 11.1 1 11.1 9 100.0 Mara 0 .0 0 .0 0 .0 1 33.3 2 66.7 0 .0 3 100.0 Manyara 3 21.4 4 28.6 0 .0 2 14.3 2 14.3 3 21.4 14 100.0 North Unguja 1 14.3 2 28.6 0 .0 2 28.6 2 28.6 0 .0 7 100.0 South Unguja 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 39 28.3 20 14.5 12 8.7 10 7.2 46 33.3 11 8.0 138 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 239 9.5.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Arusha 1 50.0 1 50.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Kilimanjaro 0 .0 0 .0 0 .0 1 33.3 1 33.3 1 33.3 3 100.0 Tanga 1 20.0 0 .0 1 20.0 0 .0 3 60.0 0 .0 5 100.0 Morogoro 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Pwani 2 22.2 1 11.1 0 .0 0 .0 3 33.3 3 33.3 9 100.0 Dar es salaam 2 18.2 2 18.2 2 18.2 1 9.1 2 18.2 2 18.2 11 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 1 10.0 1 10.0 1 10.0 2 20.0 4 40.0 1 10.0 10 100.0 Iringa 1 9.1 0 .0 0 .0 1 9.1 6 54.5 3 27.3 11 100.0 Mbeya 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Singida 0 .0 2 100.0 0 .0 0 .0 0 .0 0 .0 2 100.0 Tabora 0 .0 0 .0 0 .0 1 16.7 4 66.7 1 16.7 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 1 33.3 1 33.3 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Mwanza 0 .0 0 .0 1 12.5 1 12.5 1 12.5 5 62.5 8 100.0 Mara 0 .0 1 33.3 0 .0 0 .0 0 .0 2 66.7 3 100.0 Manyara 2 28.6 0 .0 0 .0 0 .0 4 57.1 1 14.3 7 100.0 North Unguja 0 .0 4 57.1 1 14.3 1 14.3 1 14.3 0 .0 7 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 11 11.7 14 14.9 8 8.5 8 8.5 34 36.2 19 20.2 94 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 240 9.5.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 1 50.0 0 .0 0 .0 0 .0 1 50.0 2 100.0 Arusha 0 .0 0 .0 1 50.0 0 .0 1 50.0 0 .0 2 100.0 Kilimanjaro 0 .0 1 33.3 0 .0 0 .0 0 .0 2 66.7 3 100.0 Tanga 0 .0 0 .0 0 .0 1 33.3 1 33.3 1 33.3 3 100.0 Morogoro 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Pwani 0 .0 0 .0 2 50.0 0 .0 1 25.0 1 25.0 4 100.0 Dar es salaam 0 .0 1 16.7 2 33.3 0 .0 1 16.7 2 33.3 6 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 2 22.2 3 33.3 1 11.1 0 .0 3 33.3 9 100.0 Iringa 0 .0 0 .0 2 20.0 5 50.0 1 10.0 2 20.0 10 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Tabora 0 .0 0 .0 1 16.7 1 16.7 1 16.7 3 50.0 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 2 66.7 0 .0 1 33.3 0 .0 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Mwanza 0 .0 4 50.0 2 25.0 0 .0 0 .0 2 25.0 8 100.0 Mara 0 .0 0 .0 2 66.7 0 .0 0 .0 1 33.3 3 100.0 Manyara 2 28.6 0 .0 1 14.3 0 .0 1 14.3 3 42.9 7 100.0 North Unguja 2 28.6 1 14.3 3 42.9 0 .0 1 14.3 0 .0 7 100.0 South Unguja 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 4 5.1 11 14.1 22 28.2 9 11.5 10 12.8 22 28.2 78 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 241 9.5.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Chicken by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Arusha 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 Kilimanjaro 1 33.3 1 33.3 0 .0 0 .0 0 .0 1 33.3 3 100.0 Tanga 0 .0 1 50.0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Morogoro 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Pwani 0 .0 1 25.0 1 25.0 1 25.0 0 .0 1 25.0 4 100.0 Dar es salaam 1 16.7 0 .0 1 16.7 0 .0 3 50.0 1 16.7 6 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 2 33.3 0 .0 0 .0 1 16.7 3 50.0 6 100.0 Iringa 0 .0 1 10.0 6 60.0 3 30.0 0 .0 0 .0 10 100.0 Mbeya 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Tabora 0 .0 0 .0 2 33.3 1 16.7 1 16.7 2 33.3 6 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 1 33.3 0 .0 2 66.7 3 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Mwanza 0 .0 0 .0 3 42.9 2 28.6 1 14.3 1 14.3 7 100.0 Mara 0 .0 1 33.3 0 .0 2 66.7 0 .0 0 .0 3 100.0 Manyara 0 .0 0 .0 4 66.7 0 .0 0 .0 2 33.3 6 100.0 North Unguja 0 .0 0 .0 0 .0 3 42.9 3 42.9 1 14.3 7 100.0 South Unguja 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 3 4.2 8 11.3 17 23.9 13 18.3 11 15.5 19 26.8 71 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 242 9.6.1 Number of Large scale farms Reporting the FIRST most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Arusha 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Kilimanjaro 2 50.0 0 .0 0 .0 0 .0 1 25.0 1 25.0 4 100.0 Tanga 1 25.0 1 25.0 0 .0 0 .0 1 25.0 1 25.0 4 100.0 Morogoro 5 55.6 0 .0 0 .0 0 .0 4 44.4 0 .0 9 100.0 Pwani 2 50.0 0 .0 0 .0 0 .0 0 .0 2 50.0 4 100.0 Dar es salaam 0 .0 0 .0 1 25.0 1 25.0 0 .0 2 50.0 4 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 2 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 Ruvuma 7 58.3 1 8.3 0 .0 1 8.3 1 8.3 2 16.7 12 100.0 Iringa 10 52.6 1 5.3 1 5.3 0 .0 4 21.1 3 15.8 19 100.0 Mbeya 4 80.0 0 .0 0 .0 0 .0 1 20.0 0 .0 5 100.0 Singida 4 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 4 100.0 Tabora 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 0 .0 2 100.0 0 .0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 2 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 Mwanza 2 40.0 0 .0 1 20.0 0 .0 0 .0 2 40.0 5 100.0 Mara 1 25.0 1 25.0 1 25.0 0 .0 0 .0 1 25.0 4 100.0 Manyara 0 .0 0 .0 0 .0 0 .0 1 33.3 2 66.7 3 100.0 North Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 44 49.4 4 4.5 4 4.5 4 4.5 14 15.7 19 21.3 89 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 243 9.6.2 Number of Large scale farms Reporting the SECOND most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 1 50 0 0 0 0 0 0 0 0 1 50 2 100 Arusha 0 0 0 0 0 0 0 0 0 0 1 100 1 100 Kilimanjaro 1 25 1 25 0 0 0 0 1 25 1 25 4 100 Tanga 1 33.3 0 0 0 0 1 33.3 1 33.3 0 0 3 100 Morogoro 1 16.7 0 0 0 0 0 0 5 83.3 0 0 6 100 Pwani 0 0 0 0 1 33.3 0 0 1 33.3 1 33.3 3 100 Dar es salaam 0 0 0 0 0 0 1 50 1 50 0 0 2 100 Lindi 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 0 0 0 0 0 0 0 0 1 100 0 0 1 100 Ruvuma 1 8.3 1 8.3 2 16.7 1 8.3 7 58.3 0 0 12 100 Iringa 4 26.7 0 0 1 6.7 2 13.3 7 46.7 1 6.7 15 100 Mbeya 1 33.3 1 33.3 0 0 0 0 1 33.3 0 0 3 100 Singida 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 0 0 0 0 0 0 0 0 1 100 0 0 1 100 Rukwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 0 0 2 100 0 0 0 0 0 0 0 0 2 100 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 0 0 1 50 0 0 0 0 1 50 0 0 2 100 Mwanza 0 0 0 0 2 33.3 0 0 2 33.3 2 33.3 6 100 Mara 1 25 1 25 0 0 0 0 1 25 1 25 4 100 Manyara 0 0 0 0 0 0 1 25 1 25 2 50 4 100 North Unguja 0 0 0 0 0 0 0 0 0 0 2 100 2 100 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 11 15.1 7 9.6 6 8.2 6 8.2 31 42.5 12 16.4 73 100 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 244 9.6.3 Number of Large scale farms Reporting the THIRD most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 1 50.0 0 .0 0 .0 1 50.0 2 100.0 Arusha 0 .0 0 .0 0 .0 1 100.0 0 .0 0 .0 1 100.0 Kilimanjaro 0 .0 0 .0 1 25.0 2 50.0 0 .0 1 25.0 4 100.0 Tanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Morogoro 0 .0 0 .0 1 33.3 0 .0 1 33.3 1 33.3 3 100.0 Pwani 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Dar es salaam 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 1 11.1 2 22.2 1 11.1 2 22.2 3 33.3 0 .0 9 100.0 Iringa 1 7.1 2 14.3 1 7.1 2 14.3 3 21.4 5 35.7 14 100.0 Mbeya 0 .0 1 25.0 1 25.0 1 25.0 1 25.0 0 .0 4 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Tabora 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 50.0 0 .0 1 50.0 0 .0 0 .0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 2 100.0 0 .0 0 .0 0 .0 2 100.0 Mwanza 0 .0 0 .0 1 20.0 0 .0 0 .0 4 80.0 5 100.0 Mara 0 .0 1 25.0 0 .0 2 50.0 1 25.0 0 .0 4 100.0 Manyara 0 .0 1 33.3 1 33.3 0 .0 0 .0 1 33.3 3 100.0 North Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 3 5.1 7 11.9 12 20.3 10 16.9 11 18.6 16 27.1 59 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 245 9.6.4 Number of Large scale farms Reporting the FOURTH most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 0 .0 0 .0 1 50.0 0 .0 1 50.0 2 100.0 Arusha 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Kilimanjaro 0 .0 1 33.3 0 .0 0 .0 0 .0 2 66.7 3 100.0 Tanga 0 .0 0 .0 1 100.0 0 .0 0 .0 0 .0 1 100.0 Morogoro 0 .0 0 .0 0 .0 0 .0 1 50.0 1 50.0 2 100.0 Pwani 0 .0 1 50.0 0 .0 0 .0 0 .0 1 50.0 2 100.0 Dar es salaam 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 0 .0 2 22.2 3 33.3 2 22.2 0 .0 2 22.2 9 100.0 Iringa 1 7.7 2 15.4 2 15.4 5 38.5 1 7.7 2 15.4 13 100.0 Mbeya 0 .0 0 .0 0 .0 2 100.0 0 .0 0 .0 2 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Tabora 0 .0 1 100.0 0 .0 0 .0 0 .0 0 .0 1 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 1 50.0 0 .0 0 .0 0 .0 1 50.0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 1 50.0 0 .0 1 50.0 2 100.0 Mwanza 0 .0 0 .0 3 60.0 0 .0 0 .0 2 40.0 5 100.0 Mara 2 50.0 0 .0 0 .0 1 25.0 0 .0 1 25.0 4 100.0 Manyara 1 50.0 0 .0 0 .0 0 .0 0 .0 1 50.0 2 100.0 North Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 6 11.1 8 14.8 9 16.7 12 22.2 3 5.6 16 29.6 54 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 246 9.6.5 Number of Large scale farms Reporting the FIFTH most important Outlet for Sales of Pigs by Region, 2007/08 Agricultural Year Region Trader at farm Local Market Secondary market/auction. Abattoir Another farmer Other (Specify) Total Number % Number % Number % Number % Number % Number % Number % Dodoma 0 .0 1 50.0 0 .0 0 .0 0 .0 1 50.0 2 100.0 Arusha 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Kilimanjaro 1 33.3 0 .0 0 .0 1 33.3 0 .0 1 33.3 3 100.0 Tanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Morogoro 0 .0 0 .0 0 .0 0 .0 1 100.0 0 .0 1 100.0 Pwani 0 .0 0 .0 0 .0 1 50.0 0 .0 1 50.0 2 100.0 Dar es salaam 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Lindi 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Mtwara 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Ruvuma 1 16.7 2 33.3 2 33.3 0 .0 0 .0 1 16.7 6 100.0 Iringa 0 .0 1 8.3 6 50.0 2 16.7 1 8.3 2 16.7 12 100.0 Mbeya 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 1 100.0 Singida 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Tabora 1 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 1 100.0 Rukwa 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kigoma 0 .0 0 .0 1 50.0 0 .0 1 50.0 0 .0 2 100.0 Shinyanga 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Kagera 0 .0 0 .0 0 .0 1 50.0 0 .0 1 50.0 2 100.0 Mwanza 0 .0 0 .0 2 33.3 2 33.3 0 .0 2 33.3 6 100.0 Mara 0 .0 1 25.0 0 .0 1 25.0 1 25.0 1 25.0 4 100.0 Manyara 0 .0 0 .0 0 .0 0 .0 0 .0 3 100.0 3 100.0 North Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 2 100.0 2 100.0 South Unguja 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Urban West 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 North Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 South Pemba 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 Total 3 6.3 5 10.4 11 22.9 8 16.7 5 10.4 16 33.3 48 100.0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 247 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES APPENDIX II Tanzania Agriculture Sample Census - 2007/08 248 9.7.1 ACCESS TO SERVICES: Number, percent and average distance to Livestock functional Livestock Infrastructure and Srvices by tpe of Service Type of Service/Structure Distance to nearest functional structure/Service Less than 5 5 - 9 10 - 14 15 - 19 No Structures Average Distance (km) % No Structures Average Distance (km) % No Structures Average Distance (km) % No Structures Average Distance (km) % Cattle Dip 233 1.2 86 13 7.4 5 13 10.5 5 2 15.0 1 Spray Race 89 .3 90 2 8.5 2 1 10.0 1 0 . 0 Hand powered sprayer 370 .2 97 3 6.7 1 3 10.3 1 1 16.0 0 Cattle crush 359 .6 97 3 8.0 1 5 10.0 1 1 15.0 0 Primary Market 95 2.1 48 14 7.6 7 26 11.0 13 17 15.8 9 Secondary Market 35 2.2 32 14 7.8 13 17 11.1 16 3 15.7 3 Abattoir 35 2.0 28 10 6.7 8 11 10.8 9 7 15.4 6 Slaughter Slab 202 .0 100 0 . 0 0 . 0 0 . 0 Hide/skin shed 143 .8 100 0 . 0 0 . 0 0 . 0 Input supply 145 2.1 35 42 7.6 10 50 11.6 12 24 16.2 6 Veterinary Clinic 99 1.6 32 21 7.3 7 24 11.6 8 20 16.8 6 Holding ground 71 .5 74 2 8.5 2 1 10.0 1 3 16.0 3 Watering point/dam 179 .9 100 0 . 0 0 . 0 0 . 0 Drencher 277 .3 100 0 . 0 0 . 0 0 . 0 Total 2332 .8 73 124 7.5 4 151 11.2 5 78 16.1 2 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 249 Cont 9.7.1 …..ACCESS TO SERVICES: Number, percent and average distance to Livestock functional Livestock Infrastructure and Srvices by tpe of Service Type of Service/Structure Distance to nearest functional structure/Service 20 - 29 30 - 49 More than 50 No Structures Average Distance (km) % No Structures Average Distance (km) % No Structures Average Distance (km) % Cattle Dip 4 23.5 1 5 37.6 2 2 55.1 1 Spray Race 0 . 0 0 . 0 7 94.9 7 Hand powered sprayer 0 . 0 5 38.8 1 0 . 0 Cattle crush 1 20.0 0 1 30.0 0 2 51.0 1 Primary Market 18 22.9 9 18 35.1 9 11 62.1 6 Secondary Market 10 22.5 9 10 35.8 9 19 65.7 18 Abattoir 18 23.2 15 21 36.3 17 21 65.5 17 Slaughter Slab 0 . 0 0 . 0 0 . 0 Hide/skin shed 0 . 0 0 . 0 0 . 0 Input supply 36 23.1 9 58 37.8 14 58 68.2 14 Veterinary Clinic 39 23.5 12 47 37.8 15 64 68.8 20 Holding ground 6 22.5 6 8 36.3 8 5 58.8 5 Watering point/dam 0 . 0 0 . 0 0 . 0 Drencher 0 . 0 0 . 0 0 . 0 Total 132 23.1 4 173 37.2 5 189 67.9 6 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 250 9.8.1 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: Cattle DIP Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 7 88 0 0 1 13 0 0 0 0 0 0 0 0 Arusha 12 92 1 8 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 15 75 4 20 1 5 0 0 0 0 0 0 0 0 Morogoro 16 76 0 0 1 5 0 0 1 5 3 14 0 0 Pwani 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 0 1 100 0 0 Mtwara 4 80 1 20 0 0 0 0 0 0 0 0 0 0 Ruvuma 11 69 3 19 1 6 0 0 1 6 0 0 0 0 Iringa 41 93 1 2 1 2 0 0 0 0 0 0 1 2 Mbeya 8 89 0 0 1 11 0 0 0 0 0 0 0 0 Singida 22 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 3 60 1 20 0 0 0 0 1 20 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 24 92 2 8 0 0 0 0 0 0 0 0 0 0 Mwanza 25 96 0 0 1 4 0 0 0 0 0 0 0 0 Mara 9 90 0 0 0 0 0 0 0 0 1 10 0 0 Manyara 11 52 0 0 6 29 2 10 1 5 0 0 1 5 North Unguja 3 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 1 100 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 251 9.8.2 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: SPRAY RACE Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 10 91 1 9 0 0 0 0 0 0 0 0 0 0 Morogoro 8 89 0 0 1 11 0 0 0 0 0 0 0 0 Pwani 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 13 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Singida 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 27 96 1 4 0 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mara 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Manyara 3 30 0 0 0 0 0 0 0 0 0 0 7 70 North Unguja 2 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 252 9.8.3 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HAND POWERD SPRAYER Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 16 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 13 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 25 93 0 0 1 4 1 4 0 0 0 0 0 0 Morogoro 44 98 0 0 1 2 0 0 0 0 0 0 0 0 Pwani 24 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 23 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 38 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 15 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 20 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 8 89 1 11 0 0 0 0 0 0 0 0 0 0 Rukwa 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 2 50 1 25 1 25 0 0 0 0 0 0 0 0 Shinyanga 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 27 96 1 4 0 0 0 0 0 0 0 0 0 0 Mwanza 11 85 0 0 0 0 0 0 0 0 2 15 0 0 Mara 11 92 0 0 0 0 0 0 0 0 1 8 0 0 Manyara 44 96 0 0 0 0 0 0 0 0 2 4 0 0 North Unguja 7 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 2 100 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 3 100 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 253 9.8,4 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: CATTLE CRASH Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 8 89 0 0 1 11 0 0 0 0 0 0 0 0 Arusha 16 89 1 6 1 6 0 0 0 0 0 0 0 0 Kilimanjaro 15 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 26 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 25 96 0 0 1 4 0 0 0 0 0 0 0 0 Pwani 28 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 19 95 1 5 0 0 0 0 0 0 0 0 0 0 Iringa 54 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 12 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 13 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 9 100 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 31 97 1 3 0 0 0 0 0 0 0 0 0 0 Mwanza 21 100 0 0 0 0 0 0 0 0 0 0 0 0 Mara 12 80 0 0 0 0 0 0 1 7 1 7 1 7 Manyara 25 86 0 0 2 7 1 3 0 0 0 0 1 3 North Unguja 4 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 1 100 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 1 100 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 254 9.8.5 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: PRIMARY MARKET Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 3 60 0 0 2 40 0 0 0 0 0 0 0 0 Arusha 7 64 0 0 4 36 0 0 0 0 0 0 0 0 Kilimanjaro 3 50 0 0 1 17 0 0 1 17 0 0 1 17 Tanga 3 43 0 0 1 14 3 43 0 0 0 0 0 0 Morogoro 12 46 1 4 1 4 5 19 1 4 4 15 2 8 Pwani 3 27 0 0 0 0 0 0 2 18 6 55 0 0 Dar es salaam 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 0 0 0 0 0 0 1 14 3 43 2 29 1 14 Iringa 7 70 0 0 1 10 1 10 1 10 0 0 0 0 Mbeya 5 71 0 0 0 0 1 14 1 14 0 0 0 0 Singida 13 93 1 7 0 0 0 0 0 0 0 0 0 0 Tabora 0 0 1 25 0 0 0 0 0 0 3 75 0 0 Rukwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 12 43 0 0 0 0 4 14 7 25 1 4 4 14 Mwanza 7 35 6 30 4 20 1 5 0 0 2 10 0 0 Mara 4 57 1 14 1 14 0 0 0 0 0 0 1 14 Manyara 16 44 4 11 11 31 1 3 2 6 0 0 2 6 North Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 255 9.8.6 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: ABBOTOUR Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 1 33 0 0 0 0 0 0 0 0 0 0 2 67 Arusha 0 0 3 38 3 38 0 0 1 13 0 0 1 13 Kilimanjaro 1 25 1 25 1 25 0 0 1 25 0 0 0 0 Tanga 4 57 0 0 0 0 0 0 0 0 1 14 2 29 Morogoro 1 6 1 6 1 6 5 28 2 11 3 17 5 28 Pwani 4 67 0 0 0 0 0 0 0 0 1 17 1 17 Dar es salaam 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 1 17 0 0 2 33 0 0 0 0 2 33 1 17 Ruvuma 0 0 0 0 0 0 0 0 5 42 3 25 4 33 Iringa 8 73 1 9 0 0 0 0 0 0 1 9 1 9 Mbeya 1 17 1 17 1 17 0 0 1 17 2 33 0 0 Singida 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 1 33 0 0 0 0 0 0 0 0 0 0 2 67 Rukwa 0 0 0 0 0 0 0 0 1 100 0 0 0 0 Kigoma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 2 67 1 33 0 0 0 0 0 0 Mara 4 50 1 13 0 0 1 13 0 0 2 25 0 0 Manyara 5 22 2 9 1 4 0 0 7 30 6 26 2 9 North Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 256 9.8.7 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: SLUGHTER SLAB Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 11 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 11 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Pwani 15 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 19 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 22 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 11 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 13 100 0 0 0 0 0 0 0 0 0 0 0 0 Mara 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Manyara 35 100 0 0 0 0 0 0 0 0 0 0 0 0 North Unguja 4 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 257 9.8.8 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HIDES/SKIN SHED Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 9 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 13 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Pwani 16 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 18 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 19 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Mara 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Manyara 26 100 0 0 0 0 0 0 0 0 0 0 0 0 North Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 258 9.8.9 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: INPUT SUPPLY Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 2 33 0 0 0 0 0 0 1 17 2 33 1 17 Arusha 6 55 0 0 0 0 0 0 1 9 1 9 3 27 Kilimanjaro 5 42 3 25 3 25 0 0 0 0 0 0 1 8 Tanga 12 38 5 16 8 25 2 6 2 6 1 3 2 6 Morogoro 13 31 3 7 3 7 8 19 4 10 5 12 6 14 Pwani 17 49 5 14 3 9 1 3 4 11 2 6 3 9 Dar es salaam 9 43 2 10 3 14 1 5 1 5 2 10 3 14 Lindi 3 38 0 0 0 0 0 0 2 25 2 25 1 13 Mtwara 5 38 1 8 3 23 0 0 0 0 2 15 2 15 Ruvuma 5 20 2 8 1 4 0 0 3 12 5 20 9 36 Iringa 19 33 10 17 3 5 0 0 4 7 11 19 11 19 Mbeya 7 50 2 14 3 21 0 0 0 0 2 14 0 0 Singida 1 7 2 13 10 67 1 7 0 0 0 0 1 7 Tabora 1 20 0 0 0 0 1 20 0 0 0 0 3 60 Rukwa 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 1 33 0 0 0 0 0 0 0 0 1 33 1 33 Shinyanga 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 1 4 0 0 0 0 0 0 2 8 13 50 10 38 Mwanza 9 45 1 5 2 10 4 20 2 10 2 10 0 0 Mara 5 45 1 9 0 0 1 9 1 9 3 27 0 0 Manyara 15 41 4 11 7 19 2 5 4 11 4 11 1 3 North Unguja 3 30 0 0 1 10 2 20 4 40 0 0 0 0 South Unguja 1 50 0 0 0 0 0 0 1 50 0 0 0 0 Urban West 0 0 1 50 0 0 1 50 0 0 0 0 0 0 North Pemba 2 100 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 259 9.8.10 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: VERTERINARY CLINIC Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 2 33 0 0 0 0 0 0 0 0 0 0 4 67 Arusha 4 40 1 10 1 10 0 0 0 0 1 10 3 30 Kilimanjaro 3 30 1 10 0 0 0 0 0 0 3 30 3 30 Tanga 9 33 1 4 4 15 4 15 3 11 4 15 2 7 Morogoro 8 33 0 0 1 4 2 8 3 13 4 17 6 25 Pwani 11 31 5 14 4 11 3 9 8 23 2 6 2 6 Dar es salaam 8 47 1 6 4 24 0 0 0 0 1 6 3 18 Lindi 1 33 0 0 0 0 0 0 1 33 0 0 1 33 Mtwara 2 29 0 0 1 14 0 0 1 14 0 0 3 43 Ruvuma 6 27 1 5 0 0 1 5 3 14 3 14 8 36 Iringa 17 35 8 16 2 4 0 0 3 6 6 12 13 27 Mbeya 2 25 1 13 2 25 0 0 1 13 0 0 2 25 Singida 0 0 0 0 0 0 0 0 0 0 0 0 1 100 Tabora 1 25 0 0 0 0 0 0 0 0 0 0 3 75 Rukwa 3 75 0 0 0 0 0 0 0 0 1 25 0 0 Kigoma 0 0 1 33 0 0 0 0 0 0 1 33 1 33 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 6 29 0 0 0 0 0 0 1 5 8 38 6 29 Mwanza 2 22 0 0 1 11 4 44 1 11 1 11 0 0 Mara 5 38 0 0 0 0 2 15 2 15 4 31 0 0 Manyara 4 16 0 0 0 0 2 8 8 32 8 32 3 12 North Unguja 2 20 0 0 3 30 1 10 4 40 0 0 0 0 South Unguja 0 0 0 0 1 100 0 0 0 0 0 0 0 0 Urban West 0 0 1 50 0 0 1 50 0 0 0 0 0 0 North Pemba 3 100 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 260 9.8.11 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: HOLDING GROUND Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 10 91 0 0 1 9 0 0 0 0 0 0 0 0 Pwani 4 80 0 0 0 0 1 20 0 0 0 0 0 0 Dar es salaam 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 10 91 1 9 0 0 0 0 0 0 0 0 0 0 Mbeya 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Singida 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 1 25 0 0 0 0 0 0 0 0 0 0 3 75 Rukwa 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mara 6 60 1 10 0 0 1 10 1 10 1 10 0 0 Manyara 5 25 0 0 0 0 1 5 5 25 7 35 2 10 North Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 261 9.8.12 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: WATERING POINT Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 11 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 16 100 0 0 0 0 0 0 0 0 0 0 0 0 Pwani 14 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 15 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 11 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 5 100 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 29 100 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 9 100 0 0 0 0 0 0 0 0 0 0 0 0 Mara 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Manyara 23 100 0 0 0 0 0 0 0 0 0 0 0 0 North Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 262 9.8.13 Number of Large Scale Famrs Reporting Access to Livestock Infrastructure and Services by Region: DRENCHER Region Less than 5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 More than 50 No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % No. Farms % Dodoma 8 100 0 0 0 0 0 0 0 0 0 0 0 0 Arusha 15 100 0 0 0 0 0 0 0 0 0 0 0 0 Kilimanjaro 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Tanga 19 100 0 0 0 0 0 0 0 0 0 0 0 0 Morogoro 23 100 0 0 0 0 0 0 0 0 0 0 0 0 Pwani 26 100 0 0 0 0 0 0 0 0 0 0 0 0 Dar es salaam 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Lindi 4 100 0 0 0 0 0 0 0 0 0 0 0 0 Mtwara 3 100 0 0 0 0 0 0 0 0 0 0 0 0 Ruvuma 22 100 0 0 0 0 0 0 0 0 0 0 0 0 Iringa 46 100 0 0 0 0 0 0 0 0 0 0 0 0 Mbeya 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Singida 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Tabora 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Rukwa 6 100 0 0 0 0 0 0 0 0 0 0 0 0 Kigoma 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga 2 100 0 0 0 0 0 0 0 0 0 0 0 0 Kagera 30 100 0 0 0 0 0 0 0 0 0 0 0 0 Mwanza 7 100 0 0 0 0 0 0 0 0 0 0 0 0 Mara 10 100 0 0 0 0 0 0 0 0 0 0 0 0 Manyara 19 100 0 0 0 0 0 0 0 0 0 0 0 0 North Unguja 5 100 0 0 0 0 0 0 0 0 0 0 0 0 South Unguja 1 100 0 0 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 0 0 0 0 North Pemba 3 100 0 0 0 0 0 0 0 0 0 0 0 0 South Pemba 0 0 0 0 0 0 0 0 0 0 0 0 0 0 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 263 FARM EMPLOYMENT APPENDIX II Tanzania Agriculture Sample Census - 2007/08 264 10.2 Number of permanent employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Mechanical/workshop/parts stores manage Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 6 1 1 1 4 4 7 2 4 1 1 1 Arusha 20 1 2 1 3 2 19 3 7 2 . . Kilimanjaro 6 2 1 1 1 1 3 1 4 4 . . Tanga 10 1 5 3 5 3 6 2 8 2 1 1 Morogoro 18 1 1 1 9 1 14 2 10 1 10 10 Pwani 8 1 . . . . 3 1 6 1 . . Dar es salaam 1 1 . . . . . . . . . . Lindi 3 1 . . 5 3 . . . . . . Mtwara 2 2 . . 1 1 . . . . . . Ruvuma 10 2 1 1 5 3 6 2 3 1 . . Iringa 14 2 1 1 1 1 7 1 14 5 . . Mbeya 9 2 3 1 47 12 6 2 10 3 . . Singida 2 1 . . . . . . . . . . Tabora 4 1 . . . . 3 2 1 1 . . Rukwa 1 1 . . . . 1 1 . . . . Kigoma 7 2 . . . . 3 1 1 1 . . Kagera 8 1 . . 2 1 1 1 2 1 . . Mwanza 2 1 . . . . . . . . . . Mara 9 1 3 2 4 1 6 2 12 2 . . Manyara 1 1 . . . . . . 2 1 . . North Unguja 2 1 . . 1 1 . . 2 2 . . South Unguja 5 1 . . 6 2 1 1 2 2 . . Urban West 3 1 . . 6 3 4 1 1 1 . . North Pemba 7 1 . . 6 2 2 1 2 2 . . South Pemba 1 1 . . 3 2 3 2 . . . . Total 159 1 18 1 109 3 95 2 91 2 12 4 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 265 Continued Cont…10.2 …Number of permanent employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Crop/livestock husbandry managers/agronomists Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 16 3 6 3 . . . . 2 1 . . Arusha 19 2 4 2 1 1 . . 4 1 . . Kilimanjaro 3 2 . . 1 1 . . 2 1 1 1 Tanga 14 2 10 3 . . . . 3 2 . . Morogoro 33 3 9 2 1 1 . . 7 1 2 1 Pwani 12 2 1 1 . . . . 1 1 . . Dar es salaam . . . . . . . . . . . . Lindi 7 2 . . . . . . 2 1 . . Mtwara 5 5 . . . . . . . . . . Ruvuma 6 1 1 1 . . . . 1 1 . . Iringa 24 3 2 1 1 1 . . 3 1 . . Mbeya 8 2 2 1 2 2 . . 6 2 1 1 Singida 3 1 . . . . . . . . . . Tabora 5 2 1 1 1 1 . . 2 1 . . Rukwa 3 3 . . . . . . 1 1 . . Kigoma 5 2 . . . . . . 3 1 . . Kagera 9 3 1 1 . . . . . . . . Mwanza 4 1 . . . . . . 2 1 . . Mara 5 3 . . 2 1 . . 1 1 1 1 Manyara 1 1 . . 1 1 . . 1 1 . . North Unguja 3 3 . . . . . . . . . . South Unguja 7 2 . . . . . . . . . . Urban West 1 1 . . . . . . . . . . North Pemba 10 1 1 1 . . . . 3 2 . . South Pemba 3 2 1 1 . . . . 3 3 1 1 Total 206 2 39 2 10 1 . . 47 1 6 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 266 Cont…10.2 .Number of permanent employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Supervisor staff Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Dodoma 1 1 . . 54 14 14 5 12 4 3 3 Arusha 1 1 . . 19 6 . . 15 4 3 2 Kilimanjar o . . . . 34 17 10 10 201 67 4 2 Tanga 1 1 . . 41 8 8 8 12 2 1 1 Morogoro 3 1 . . 80 10 8 4 18 4 . . Pwani . . . . 23 4 6 2 4 1 . . Dar es salaam . . . . . . . . . . . . Lindi . . . . 12 6 . . 9 3 . . Mtwara . . . . 21 21 . . . . . . Ruvuma . . . . 79 26 . . 2 1 . . Iringa . . . . 70 18 9 5 7 1 1 1 Mbeya 2 1 2 2 11 4 . . 8 3 . . Singida . . . . . . . . 14 14 . . Tabora . . . . 4 4 . . 22 22 . . Rukwa . . . . 97 49 2 2 . . . . Kigoma . . . . . . . . 1 1 . . Kagera . . . . 49 25 1 1 31 8 . . Mwanza . . . . . . . . 14 7 . . Mara 1 1 . . 69 17 2 1 4 2 . . Manyara . . . . 3 3 . . 2 1 . . North Unguja . . . . 12 12 . . 2 1 . . South Unguja . . . . 50 17 4 2 13 3 2 2 Urban West . . . . 55 28 15 8 15 5 4 2 North Pemba 2 2 1 1 7 7 3 3 40 5 8 3 South Pemba . . . . . . . . 10 5 7 4 Total 11 1 3 2 790 14 82 4 456 7 33 2 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 267 Cont…10.2 Number of permanent employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Labourers Total Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Dodoma 74 19 13 7 173 6 45 3 Arusha 24 6 . . 113 3 28 2 Kilimanjaro 48 24 15 15 300 18 34 4 Tanga 163 23 39 8 257 6 70 4 Morogoro 41 10 . . 220 3 44 2 Pwani 6 3 . . 60 2 10 1 Dar es salaam . . . . 1 1 . . Lindi . . . . 38 3 . . Mtwara . . . . 29 7 . . Ruvuma 23 8 . . 129 5 8 2 Iringa 9 5 5 5 143 4 25 2 Mbeya . . . . 103 3 14 1 Singida 30 30 10 10 49 7 10 10 Tabora 30 30 . . 69 5 4 1 Rukwa . . . . 102 20 3 2 Kigoma . . . . 17 1 3 1 Kagera 260 260 . . 361 17 3 1 Mwanza 60 30 . . 82 7 . . Mara 2 1 . . 109 4 12 2 Manyara . . . . 11 1 . . North Unguja 5 3 2 1 27 3 2 1 South Unguja 38 13 . . 121 5 7 2 Urban West 32 16 . . 113 8 23 3 North Pemba 55 9 23 8 132 4 38 3 South Pemba 21 11 20 10 41 4 32 4 Total 921 18 127 7 2800 5 415 3 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 268 Continued 10.3 Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 16 1 7 1 4 1 2 2 13 4 10 2 2 1 . . Arusha 124 1 30 1 4 1 . . 54 2 92 2 3 2 . . Kilimanjaro 70 1 9 2 4 1 . . 25 2 57 2 4 2 7 4 Tanga 111 1 18 1 4 1 2 2 71 3 93 2 4 2 2 2 Morogoro 53 1 9 1 6 2 . . 55 3 753 50 3 3 1 1 Pwani 64 1 15 1 13 1 3 2 12 1 15 2 3 1 1 1 Dar es salaam 7 1 11 1 . . . . 32 8 3 2 2 2 . . Lindi 8 1 1 1 2 1 . . 5 3 . . . . . . Mtwara 9 2 4 1 3 2 2 2 1 1 20 20 . . . . Ruvuma 39 1 16 1 31 2 17 1 16 2 15 1 10 2 6 2 Iringa 82 1 23 1 7 1 7 2 55 3 42 2 21 7 5 3 Mbeya 58 2 20 1 . . 1 1 103 8 39 4 11 3 18 3 Singida 5 1 1 1 2 1 . . 1 1 . . . . . . Tabora 8 1 1 1 4 1 1 1 4 2 3 2 . . . . Rukwa 7 1 1 1 . . . . . . 5 1 . . . . Kigoma 7 2 . . . . . . . . 3 1 . . 1 1 Shinyanga 2 1 3 2 3 3 . . 2 2 . . . . . . Kagera 34 1 5 1 2 1 1 1 19 4 36 5 . . . . Mwanza 10 1 . . 1 1 . . 2 2 . . . . . . Mara 23 1 5 1 3 3 1 1 6 2 7 2 6 2 . . Manyara 55 1 5 1 32 1 4 1 19 1 7 1 5 1 1 1 North Unguja 15 1 . . 2 2 1 1 1 1 . . 1 1 . . South Unguja 7 1 1 1 . . . . 6 2 3 2 . . . . Urban West 4 1 . . . . . . 6 3 7 2 . . . . North Pemba 7 1 . . . . . . 6 2 2 1 . . . . South Pemba 1 1 . . . . . . 3 2 3 2 . . . . Total 826 1 185 1 127 1 42 1 517 3 1215 6 75 2 42 2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 269 Cont…10.3…Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type Mechanical/workshop/parts stores manage Crop/livestock husbandry managers/agronomists Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 12 3 3 1 1 1 . . 19 3 7 2 1 1 . . Arusha 98 2 5 3 18 6 2 1 91 2 17 2 5 3 . . Kilimanjaro 65 2 11 2 5 1 . . 75 2 27 2 1 1 1 1 Tanga 195 5 4 1 25 5 4 4 107 2 12 2 6 3 . . Morogoro 101 4 11 6 3 1 . . 47 2 13 2 3 2 . . Pwani 43 2 . . 4 1 . . 35 2 4 1 2 1 . . Dar es salaam 1 1 . . . . . . 5 1 . . 5 3 . . Lindi 1 1 5 5 . . . . 8 2 3 3 . . . . Mtwara 6 6 . . . . . . 7 2 . . . . . . Ruvuma 13 1 . . 8 1 . . 19 1 5 1 12 2 10 3 Iringa 75 3 6 3 6 2 . . 68 2 7 1 8 3 4 1 Mbeya 80 5 1 1 12 2 . . 36 2 6 2 3 1 . . Singida 2 1 . . 1 1 . . 3 1 . . . . . . Tabora 3 1 . . 2 2 . . 6 2 1 1 . . . . Rukwa 9 2 . . 1 1 . . 9 2 . . . . . . Kigoma 1 1 . . . . . . 5 2 . . . . . . Shinyanga . . . . . . . . . . . . . . . . Kagera 25 4 2 2 2 2 . . 23 2 4 1 1 1 1 1 Mwanza 3 2 . . . . . . 4 1 . . . . . . Mara 21 2 . . 2 2 2 2 13 2 2 2 2 1 2 2 Manyara 107 3 . . 51 2 . . 11 1 1 1 3 1 . . North Unguja 2 2 . . 20 20 . . 3 3 . . 3 3 . . South Unguja 2 2 . . . . . . 7 2 . . . . . . Urban West 3 2 . . . . . . 4 2 . . . . . . North Pemba 2 2 . . . . . . 10 1 1 1 . . . . South Pemba . . . . 1 1 . . 3 2 1 1 . . . . Total 870 3 48 2 162 2 8 2 618 2 111 2 55 2 18 2 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 270 Cont…10.3 .Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . 2 1 . . . . . . Arusha 16 1 . . . . . . 25 1 8 1 1 1 . . Kilimanjaro 6 1 . . . . . . 19 1 15 1 2 1 1 1 Tanga 2 1 . . . . . . 12 1 . . 1 1 1 1 Morogoro 3 2 . . 1 1 . . 11 1 4 1 . . . . Pwani . . . . . . . . 5 1 . . 1 1 . . Dar es salaam . . 2 2 . . . . 1 1 . . . . . . Lindi . . . . . . . . 2 1 . . . . . . Mtwara . . . . . . . . . . 1 1 . . . . Ruvuma 2 1 2 2 . . . . 5 1 1 1 . . . . Iringa 5 1 1 1 . . . . 7 1 5 1 . . . . Mbeya 3 2 1 1 1 1 . . 14 2 12 1 . . 1 1 Singida . . . . . . . . . . . . . . . . Tabora 1 1 . . . . . . 4 1 . . 1 1 . . Rukwa . . . . . . . . 1 1 . . . . . . Kigoma . . . . . . . . 3 1 . . . . . . Shinyanga . . . . . . . . . . . . . . . . Kagera 1 1 . . . . . . . . 1 1 . . . . Mwanza . . . . . . . . 2 1 . . . . . . Mara 3 1 . . . . . . 2 1 1 1 . . . . Manyara 6 1 . . . . . . 8 1 1 1 2 1 . . North Unguja . . . . . . . . . . . . . . . . South Unguja . . . . . . . . . . . . . . . . Urban West . . 1 1 . . . . 3 3 2 2 . . . . North Pemba . . . . . . . . 3 2 . . . . . . South Pemba . . . . . . . . 3 3 1 1 . . . . Total 48 1 7 1 2 1 . . 132 1 52 1 8 1 3 1 Continued APPENDIX II Tanzania Agriculture Sample Census - 2007/08 271 Continued Cont…10.3 .Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 1 1 . . . . . . 85 14 17 4 5 3 1 1 Arusha 13 1 4 1 . . . . 479 9 274 9 64 13 5 1 Kilimanjaro 12 1 6 2 1 1 4 4 156 5 50 3 11 2 9 3 Tanga 21 1 . . . . . . 419 9 96 6 89 13 12 3 Morogoro 5 1 . . . . 2 2 180 11 810 162 1 1 . . Pwani 1 1 . . . . . . 98 7 63 8 21 4 8 8 Dar es salaam . . 1 1 . . . . 24 5 . . 7 4 . . Lindi . . . . . . . . 71 14 4 2 . . . . Mtwara . . . . . . . . 22 11 . . 5 3 . . Ruvuma 1 1 1 1 3 2 1 1 91 9 1 1 7 1 5 1 Iringa 6 2 . . . . . . 213 7 77 5 15 3 4 2 Mbeya 6 1 3 2 . . 2 2 160 11 63 13 46 7 4 1 Singida . . . . . . . . 2 2 . . . . . . Tabora 2 2 . . 2 2 . . 7 4 . . 3 3 . . Rukwa . . . . . . . . 118 20 2 2 91 46 1 1 Kigoma . . . . . . . . . . . . . . . . Shinyanga . . . . . . . . . . . . . . . . Kagera 3 2 . . . . . . 97 11 6 2 12 2 9 9 Mwanza . . . . . . . . 15 3 . . 4 4 1 1 Mara 3 1 1 1 . . 1 1 76 11 2 1 8 3 3 3 Manyara 2 1 . . 4 1 . . 61 3 5 2 125 9 15 4 North Unguja 1 1 . . 1 1 . . 13 7 . . 4 4 . . South Unguja . . . . . . . . 50 17 4 2 . . . . Urban West . . . . . . . . 55 28 15 8 . . . . North Pemba 2 2 1 1 . . . . 7 7 3 3 3 3 2 2 South Pemba . . . . . . . . . . . . . . . . Total 79 1 17 1 11 1 10 2 2499 9 1492 12 521 7 79 3 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 272 Continued… Cont…10.3 ….Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type Supervisor staff Labourers Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 29 4 10 3 22 3 1 1 78 16 13 7 872 55 298 21 Arusha 1847 30 82 3 42 7 7 2 595 20 776 32 8529 122 8835 150 Kilimanjaro 297 8 41 2 14 4 22 4 350 27 413 41 1945 41 2277 53 Tanga 265 4 10 1 65 7 4 2 4098 89 2340 78 5809 82 5079 102 Morogoro 786 27 55 11 29 3 . . 456 24 63 16 3000 71 2689 108 Pwani 71 2 10 2 17 2 3 3 208 12 55 14 629 16 283 14 Dar es salaam 18 2 1 1 2 2 . . 54 4 4 1 115 8 2266 283 Lindi 15 3 . . . . . . 9 3 30 30 206 26 57 11 Mtwara 8 1 7 2 6 1 2 2 1093 99 21 11 590 18 2593 89 Ruvuma 59 3 40 4 164 9 147 11 65 7 12 3 948 27 747 21 Iringa 341 6 49 2 18 4 38 10 1965 60 1642 126 3074 42 1988 34 Mbeya 130 5 23 3 327 27 27 4 45 11 22 7 1303 42 900 32 Singida 14 14 . . 1 1 2 2 70 35 28 14 165 8 128 6 Tabora 28 6 2 2 9 2 2 2 112 22 4 4 176 22 115 14 Rukwa 6 3 1 1 4 2 . . 60 60 . . 64 32 99 33 Kigoma 1 1 . . . . . . 5 5 . . 849 170 136 45 Shinyanga 3 3 . . . . . . 1 1 . . . . . . Kagera 174 8 22 11 29 6 19 6 2002 400 847 424 440 18 81 16 Mwanza 27 4 . . 1 1 . . 100 11 . . 227 10 111 6 Mara 23 2 3 2 24 6 1 1 88 15 63 21 135 10 2136 164 Manyara 52 2 7 1 206 8 201 17 119 10 71 9 1946 25 1844 26 North Unguja 4 1 . . 7 1 . . 12 3 2 1 77 5 25 3 South Unguja 15 3 2 2 . . . . 60 15 4 4 24 12 9 5 Urban West 17 4 5 2 . . . . 32 16 . . 45 23 30 15 North Pemba 40 5 8 3 . . . . 55 9 23 8 43 9 23 6 South Pemba 10 5 7 4 . . . . 21 11 20 10 8 8 3 3 Total 4280 9 385 3 987 7 476 8 11753 45 6453 52 31219 46 32752 61 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 273 . Cont…10.3 Farm Employment: Number of Employee by type of employment and Region: ALL Region Staff/employee type Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . 2 1 . . . . . . Arusha 16 1 . . . . . . 25 1 8 1 1 1 . . Kilimanjaro 6 1 . . . . . . 19 1 15 1 2 1 1 1 Tanga 2 1 . . . . . . 12 1 . . 1 1 1 1 Morogoro 3 2 . . 1 1 . . 11 1 4 1 . . . . Pwani . . . . . . . . 5 1 . . 1 1 . . Dar es salaam . . 2 2 . . . . 1 1 . . . . . . Lindi . . . . . . . . 2 1 . . . . . . Mtwara . . . . . . . . . . 1 1 . . . . Ruvuma 2 1 2 2 . . . . 5 1 1 1 . . . . Iringa 5 1 1 1 . . . . 7 1 5 1 . . . . Mbeya 3 2 1 1 1 1 . . 14 2 12 1 . . 1 1 Singida . . . . . . . . . . . . . . . . Tabora 1 1 . . . . . . 4 1 . . 1 1 . . Rukwa . . . . . . . . 1 1 . . . . . . Kigoma . . . . . . . . 3 1 . . . . . . Shinyanga . . . . . . . . . . . . . . . . Kagera 1 1 . . . . . . . . 1 1 . . . . Mwanza . . . . . . . . 2 1 . . . . . . Mara 3 1 . . . . . . 2 1 1 1 . . . . Manyara 6 1 . . . . . . 8 1 1 1 2 1 . . North Unguja . . . . . . . . . . . . . . . . South Unguja . . . . . . . . . . . . . . . . Urban West . . 1 1 . . . . 3 3 2 2 . . . . North Pemba . . . . . . . . 3 2 . . . . . . South Pemba . . . . . . . . 3 3 1 1 . . . . Total 48 1 7 1 2 1 . . 132 1 52 1 8 1 3 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 258 Continued 10.4 Cont….Number of permanent employee by category of employment and Region: PARASTATAL OPERATORS Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Supervisor staff Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Numbe r Averag e Dodoma . . . . 29 29 . . 10 10 . . Arusha . . . . . . . . 2 2 . . Kilimanjar o . . . . 15 8 7 4 5 2 3 2 Tanga 1 1 . . . . . . 6 6 . . Morogoro . . . . 11 6 . . 6 3 . . Pwani . . . . 8 8 22 22 4 4 . . Dar es salaam . . . . . . . . 7 7 . . Iringa . . . . 2 2 . . . . 1 1 Tabora . . . . 3 3 . . 2 2 . . Rukwa . . . . 2 2 . . 4 4 . . Kagera 1 1 . . 27 9 3 2 46 15 20 20 Mwanza . . . . . . . . 1 1 . . Mara . . . . . . . . 2 2 . . South Unguja . . . . . . . . 2 2 . . Urban West . . . . . . . . 2 2 1 1 Total 2 1 . . 97 8 32 6 99 5 25 5 10.4 Number of permanent employee by category of employment and Region: PARASTATAL OPERATORS Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Mechanical/workshop/parts stores manage Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 3 2 3 3 2 2 2 2 8 8 1 1 Arusha 2 1 . . 1 1 2 2 2 2 . . Kilimanjaro 3 1 . . 1 1 2 1 1 1 . . Tanga 3 2 . . . . 3 2 3 3 . . Morogoro 2 1 . . 2 2 1 1 4 2 . . Pwani 6 3 . . 1 1 1 1 4 2 . . Dar es salaam . . 1 1 . . . . . . . . Iringa 1 1 1 1 . . 1 1 2 2 . . Tabora . . . . . . . . . . . . Rukwa 2 1 . . . . 1 1 3 2 . . Kagera 6 2 1 1 15 15 27 9 16 5 2 2 Mwanza 1 1 . . . . . . . . . . Mara . . . . . . . . . . . . South Unguja 1 1 . . . . 2 2 . . . . Urban West 1 1 . . . . 3 3 2 2 . . Total 31 1 6 2 22 4 45 3 45 3 3 2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 259 Cont…10.4 ..Number of permanent employee by category of employment and Region: PARASTATAL OPERATORS Region Staff/employee type Labourers Total Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Dodoma . . . . 55 8 6 2 Arusha . . 15 15 8 1 17 9 Kilimanjaro 6 6 1 1 34 2 13 2 Tanga 60 60 7 7 76 10 10 3 Morogoro . . . . 30 3 1 1 Pwani 6 6 . . 35 3 23 12 Dar es salaam . . . . 8 4 1 1 Iringa . . . . 7 2 3 1 Tabora 1 1 . . 6 2 . . Rukwa 60 60 . . 75 8 1 1 Kagera 1700 1700 800 800 1815 96 854 85 Mwanza . . . . 2 1 . . Mara . . . . 2 2 . . South Unguja 22 22 4 4 25 8 6 3 Urban West . . . . 11 2 7 2 Total 1855 265 827 165 2189 21 942 24 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 260 Continued 10.5 Number of permanent employee by category of employment and Region: PRIVATE REGISTERD OPERATORS Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Mechanical/workshop/parts stores manage Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . . . . . Arusha 86 1 26 1 47 2 70 2 79 2 5 3 Kilimanjaro 53 1 7 2 22 2 50 2 59 2 11 2 Tanga 48 1 9 1 65 3 71 3 177 6 2 1 Morogoro 19 1 8 1 42 5 735 147 82 8 1 1 Pwani 30 1 7 1 8 1 11 2 31 3 . . Dar es salaam 1 1 4 4 18 9 2 2 . . . . Lindi 3 2 1 1 . . . . 1 1 5 5 Mtwara 1 1 2 2 . . 20 20 6 6 . . Ruvuma 14 1 10 1 4 1 4 1 4 1 . . Iringa 48 1 17 1 51 3 30 3 49 4 4 4 Mbeya 25 2 8 1 48 7 26 7 55 8 1 1 Singida 1 1 . . . . . . 1 1 . . Tabora 3 1 1 1 4 2 . . 2 1 . . Rukwa 4 1 1 1 . . 3 1 6 2 . . Shinyanga 1 1 . . . . . . . . . . Kagera 20 1 4 1 2 1 8 3 7 4 . . Mwanza 2 1 . . . . . . 2 2 . . Mara 9 2 2 1 2 2 1 1 6 3 . . Manyara 41 1 3 1 15 1 6 1 87 3 . . North Unguja 10 1 . . . . . . . . . . Total 419 1 110 1 328 3 1037 9 654 4 29 2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 261 Continued Cont…10.5 ..Number of permanent employee by category of employment and Region: PRIVATE REGISTERD OPERATORS Region Staff/employee type Crop/livestock husbandry managers/agronomists Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . . . . . Arusha 69 2 12 2 15 1 . . 20 1 7 1 Kilimanjar o 68 2 27 2 5 1 . . 16 1 14 1 Tanga 65 2 1 1 2 1 . . 9 1 . . Morogoro 8 1 4 2 2 2 . . 3 1 2 1 Pwani 12 1 1 1 . . . . 2 2 . . Dar es salaam 1 1 . . . . . . . . . . Lindi 1 1 3 3 . . . . . . . . Mtwara 1 1 . . . . . . . . 1 1 Ruvuma 6 1 2 2 . . . . 2 1 . . Iringa 37 2 3 1 4 1 1 1 3 1 5 1 Mbeya 14 2 . . 1 1 1 1 6 2 3 2 Singida . . . . . . . . . . . . Tabora 1 1 . . . . . . 1 1 . . Rukwa 2 1 . . . . . . . . . . Shinyanga . . . . . . . . . . . . Kagera 11 1 2 1 . . . . . . 1 1 Mwanza . . . . . . . . . . . . Mara 8 2 2 2 1 1 . . . . . . Manyara 10 1 1 1 5 1 . . 3 1 . . North Unguja . . . . . . . . . . . . Total 314 2 58 2 35 1 2 1 65 1 33 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 262 Cont 105….Number of permanent employee by category of employment and Region: PRIVATE REGISTERD OPERATORS Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Supervisor staff Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . 4 4 . . Arusha 12 1 4 1 435 10 260 9 1726 38 78 4 Kilimanjaro 10 1 6 2 102 5 31 2 78 3 30 2 Tanga 19 1 . . 330 12 79 7 165 6 7 2 Morogoro 2 1 . . 89 13 802 267 738 67 53 18 Pwani . . . . 52 9 34 11 33 2 8 2 Dar es salaam . . . . . . . . 2 2 1 1 Lindi . . . . 56 28 1 1 4 4 . . Mtwara . . . . . . . . 1 1 4 2 Ruvuma . . 1 1 9 2 1 1 38 6 35 7 Iringa 6 2 . . 131 7 57 5 314 8 32 3 Mbeya 4 1 . . 107 15 51 17 96 8 5 2 Singida . . . . . . . . . . . . Tabora 2 2 . . . . . . 3 2 2 2 Rukwa . . . . 19 6 . . 2 2 1 1 Shinyanga . . . . . . . . . . . . Kagera 2 2 . . 21 5 2 2 97 6 2 2 Mwanza . . . . 6 6 . . 10 5 . . Mara 2 1 1 1 7 2 . . 5 1 1 1 Manyara 1 1 . . 16 3 . . 20 2 2 2 North Unguja 1 1 . . . . . . . . . . Total 61 1 12 1 1380 9 1318 17 3336 15 261 4 Continued… APPENDIX II Tanzania Agriculture Sample Census - 2007/08 263 Cont…10.5 …Number of permanent employee by category of employment and Region: PRIVATE REGISTERD OPERATORS Region Staff/employee type Labourers Total Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Dodoma . . . . 4 4 . . Arusha 391 20 500 28 2880 9 962 7 Kilimanjaro 296 30 397 50 709 4 573 6 Tanga 2207 110 1646 118 3087 14 1815 29 Morogoro 271 90 40 40 1256 19 1645 72 Pwani 185 19 55 14 353 4 116 5 Dar es salaam 5 2 1 1 27 3 8 2 Lindi 1 1 . . 66 8 10 3 Mtwara 39 13 20 20 48 7 47 8 Ruvuma 35 7 12 3 112 3 65 3 Iringa 1899 95 1622 203 2542 14 1771 27 Mbeya 42 14 20 20 398 6 115 5 Singida 40 40 18 18 42 14 18 18 Tabora 77 77 . . 93 7 3 2 Rukwa . . . . 33 3 5 1 Shinyanga 1 1 . . 2 1 . . Kagera 42 14 47 47 202 4 66 5 Mwanza 24 12 . . 44 6 . . Mara 31 16 43 22 71 3 50 6 Manyara 90 23 55 18 288 3 67 5 North Unguja 2 2 . . 13 1 . . Total 5678 50 4476 67 12270 9 7336 15 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 264 Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Mechanical/workshop/parts stores manage Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Numbe r Averag e Num ber Average Number Average Number Average Number Average Number Average Dodoma 3 1 2 1 . . 1 1 . . 1 1 Arusha 12 1 . . 3 2 1 1 6 2 . . Kilimanjaro 4 4 . . . . . . . . . . Tanga 10 1 2 1 . . . . 1 1 . . Morogoro 3 2 . . 2 2 3 3 1 1 . . Pwani 7 1 4 1 1 1 . . 2 2 . . Dar es salaam 1 1 4 1 . . . . . . . . Lindi 2 1 . . . . . . . . . . Mtwara 4 4 1 1 . . . . . . . . Ruvuma 13 1 2 1 5 1 3 1 4 1 . . Iringa 5 1 1 1 . . 1 1 3 3 . . Mbeya 24 2 9 2 8 4 7 4 15 3 . . Tabora 1 1 . . . . . . . . . . Shinyanga 1 1 3 2 2 2 . . . . . . Mwanza 5 1 . . 2 2 . . 1 1 . . Mara 5 1 . . . . . . . . . . Manyara 11 1 . . 2 1 1 1 14 2 . . North Unguja 2 1 . . . . . . . . . . South Unguja 1 1 1 1 . . . . . . . . Total 114 1 29 1 25 2 17 2 47 2 1 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 265 CONT 10.6….Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type Crop/livestock husbandry managers/agronomists Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . 1 1 . . . . . . . . Arusha 2 2 1 1 . . . . 1 1 . . Kilimanjaro 1 1 . . . . . . . . . . Tanga . . . . . . . . . . . . Morogoro 1 1 . . . . . . . . . . Pwani 2 1 . . . . . . 1 1 . . Dar es salaam . . . . . . . . . . . . Lindi . . . . . . . . . . . . Mtwara 1 1 . . . . . . . . . . Ruvuma 5 1 . . 1 1 2 2 2 2 . . Iringa 1 1 . . . . . . 1 1 . . Mbeya 14 4 4 4 . . . . 2 1 8 1 Tabora . . . . . . . . 1 1 . . Shinyanga . . . . . . . . . . . . Mwanza . . . . . . . . . . . . Mara . . . . . . . . 1 1 . . Manyara . . . . . . . . 3 1 1 1 North Unguja . . . . . . . . . . . . South Unguja . . . . . . . . . . . . Total 27 2 6 2 1 1 2 2 12 1 9 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 266 CONT 10.6 Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Supervisor staff Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . . . . . . . 3 3 Arusha . . . . 25 4 12 12 101 10 . . Kilimanjaro . . . . 1 1 . . 2 2 . . Tanga . . . . 22 4 9 3 13 3 . . Morogoro . . . . . . . . 8 4 1 1 Pwani . . . . . . 1 1 24 5 1 1 Dar es salaam . . 1 1 . . . . 6 2 . . Lindi . . . . . . . . 2 1 . . Mtwara . . . . . . . . 2 1 3 2 Ruvuma . . . . 1 1 . . 14 2 5 1 Iringa . . . . . . . . 8 2 2 1 Mbeya . . 1 1 42 8 12 6 26 3 18 4 Tabora . . . . . . . . 1 1 . . Shinyanga . . . . . . . . 3 3 . . Mwanza . . . . 9 2 . . 2 1 . . Mara . . . . . . . . 7 2 2 2 Manyara 1 1 . . 27 3 4 2 15 2 5 1 North Unguja . . . . 1 1 . . . . . . South Unguja . . . . . . . . . . . . Total 1 1 2 1 128 4 38 4 234 3 40 2 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 267 CONT ..10.6 Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type Labourers Total Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Dodoma 4 4 . . 7 2 8 1 Arusha 156 78 255 85 306 9 269 45 Kilimanjaro . . . . 8 2 . . Tanga 58 10 6 2 104 4 17 2 Morogoro 92 31 21 21 107 11 25 8 Pwani 2 2 . . 39 2 6 1 Dar es salaam 14 5 1 1 21 3 6 1 Lindi . . 30 30 4 1 30 30 Mtwara 1028 343 1 1 1035 148 5 1 Ruvuma 7 7 . . 52 1 12 1 Iringa 36 9 7 7 54 3 11 2 Mbeya 3 3 2 1 134 3 61 2 Tabora 1 1 . . 4 1 . . Shinyanga . . . . 6 2 3 2 Mwanza 16 3 . . 35 2 . . Mara . . . . 13 2 2 2 Manyara 12 6 11 4 85 2 22 2 North Unguja . . . . 3 1 . . South Unguja . . . . 1 1 1 1 Total 1429 43 334 21 2018 7 478 5 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 268 CONT…10.6 Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type Crop/livestock husbandry managers/agronomists Irrigation engineers Product Stores managers Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . 1 1 . . . . . . . . Arusha 2 2 1 1 . . . . 1 1 . . Kilimanjaro 1 1 . . . . . . . . . . Tanga . . . . . . . . . . . . Morogoro 1 1 . . . . . . . . . . Pwani 2 1 . . . . . . 1 1 . . Dar es salaam . . . . . . . . . . . . Lindi . . . . . . . . . . . . Mtwara 1 1 . . . . . . . . . . Ruvuma 5 1 . . 1 1 2 2 2 2 . . Iringa 1 1 . . . . . . 1 1 . . Mbeya 14 4 4 4 . . . . 2 1 8 1 Tabora . . . . . . . . 1 1 . . Shinyanga . . . . . . . . . . . . Mwanza . . . . . . . . . . . . Mara . . . . . . . . 1 1 . . Manyara . . . . . . . . 3 1 1 1 North Unguja . . . . . . . . . . . . South Unguja . . . . . . . . . . . . Total 27 2 6 2 1 1 2 2 12 1 9 1 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 269 CONT 10.6 Number of permanent employee by category of employment and Region: PRIVATE NON REGISTERED OPERATORS Region Staff/employee type Labourers Total Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Male) Number of permanent employee (Female) Number Average Number Average Number Average Number Average Dodoma 4 4 . . 7 2 8 1 Arusha 156 78 255 85 306 9 269 45 Kilimanjaro . . . . 8 2 . . Tanga 58 10 6 2 104 4 17 2 Morogoro 92 31 21 21 107 11 25 8 Pwani 2 2 . . 39 2 6 1 Dar es salaam 14 5 1 1 21 3 6 1 Lindi . . 30 30 4 1 30 30 Mtwara 1028 343 1 1 1035 148 5 1 Ruvuma 7 7 . . 52 1 12 1 Iringa 36 9 7 7 54 3 11 2 Mbeya 3 3 2 1 134 3 61 2 Tabora 1 1 . . 4 1 . . Shinyanga . . . . 6 2 3 2 Mwanza 16 3 . . 35 2 . . Mara . . . . 13 2 2 2 Manyara 12 6 11 4 85 2 22 2 North Unguja . . . . 3 1 . . South Unguja . . . . 1 1 1 1 Total 1429 43 334 21 2018 7 478 5 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 270 10.7 Number of Temporary employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type General manager/Financial managers/accountants Clerical/typest/receptionist staff Mechanical/workshop/parts stores manage Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 1 1 . . 1 1 . . 1 1 . . Arusha 2 1 . . . . . . . . . . Kilimanjaro . . . . . . . . . . . . Tanga . . . . . . . . . . . . Morogoro . . . . . . . . . . . . Pwani 2 2 . . . . . . . . . . Dar es salaam . . . . . . . . . . . . Lindi . . . . . . . . . . . . Mtwara . . . . . . . . . . . . Ruvuma 3 2 3 2 . . . . 2 2 . . Iringa . . . . . . 1 1 1 1 . . Mbeya . . . . . . . . 3 3 . . Singida 1 1 . . . . . . . . . . Tabora 2 2 1 1 . . . . . . . . Rukwa . . . . . . . . . . . . Kigoma . . . . . . 1 1 . . . . Kagera . . . . . . . . . . . . Mwanza 1 1 . . . . . . . . . . Mara . . . . 3 3 . . . . . . Manyara 3 3 . . . . . . . . . . North Unguja . . . . . . . . . . . . South Unguja . . . . . . . . . . . . Urban West . . . . . . . . . . . . North Pemba . . . . . . . . . . . . South Pemba . . . . . . . . 1 1 . . Total 15 2 4 1 4 2 2 1 8 2 . . Continued…. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 271 Cont…10.7…..Number of Temporary employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Crop/livestock husbandry managers/agronomists Irrigation engineers Product Stores managers Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma 1 1 . . . . . . . . . . Arusha . . . . . . . . . . . . Kilimanjaro . . . . . . . . . . . . Tanga . . . . . . . . . . . . Morogoro . . . . . . . . . . . . Pwani . . . . . . . . 1 1 . . Dar es salaam . . . . . . . . . . . . Lindi . . . . . . . . . . . . Mtwara . . . . . . . . . . . . Ruvuma 2 2 3 3 . . . . . . . . Iringa 6 6 2 2 . . . . . . . . Mbeya 1 1 . . . . . . . . . . Singida . . . . . . . . . . . . Tabora . . . . . . . . . . . . Rukwa . . . . . . . . . . . . Kigoma . . . . . . . . . . . . Kagera . . . . . . . . . . . . Mwanza . . . . . . . . . . . . Mara . . . . . . . . . . . . Manyara . . . . . . . . . . . . North Unguja . . . . . . . . . . . . South Unguja . . . . . . . . . . . . Urban West . . . . . . . . . . . . North Pemba . . . . . . . . . . . . South Pemba . . . . . . . . . . . . Total 10 3 5 3 . . . . 1 1 . . Continued…….. APPENDIX II Tanzania Agriculture Sample Census - 2007/08 272 Cont…10.7….Number of Temporary employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Agroprocessing/Mill managers Other Professoinal staff Supervisor staff Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Number Average Number Average Dodoma . . . . 1 1 . . . . . . Arusha . . . . . . . . . . . . Kilimanjaro . . . . . . . . . . . . Tanga . . . . . . . . . . . . Morogoro . . . . 1 1 . . 12 6 . . Pwani . . . . . . . . . . 3 3 Dar es salaam . . . . . . . . . . . . Lindi . . . . . . . . . . . . Mtwara . . . . . . . . . . . . Ruvuma . . . . . . . . . . . . Iringa . . . . . . . . . . . . Mbeya . . . . . . . . 215 108 10 10 Singida . . . . . . . . . . . . Tabora . . . . . . . . 3 3 2 2 Rukwa . . . . 77 77 . . . . . . Kigoma . . . . . . . . . . . . Kagera . . . . 2 2 . . . . . . Mwanza . . . . 4 4 1 1 . . . . Mara . . . . 2 2 . . 1 1 . . Manyara . . . . . . . . 1 1 . . North Unguja . . . . 4 4 . . . . . . South Unguja . . . . . . . . . . . . Urban West . . . . . . . . . . . . North Pemba . . . . 3 3 2 2 . . . . South Pemba . . . . . . . . . . . . Total . . . . 94 12 3 2 232 33 15 5 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 273 Cont…10.7 ..Number of Temporary employee by category of employment and Region: GOVERNMENT OPERATORS Region Staff/employee type Labourers Total Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Male) Number of part time employees (Female) Number Average Number Average Number Average Number Average Dodoma 11 6 12 12 16 2 12 12 Arusha 160 11 70 7 162 10 70 7 Kilimanjaro 243 122 220 220 243 122 220 220 Tanga 522 174 3 3 522 174 3 3 Morogoro 118 20 11 4 131 15 11 4 Pwani 50 25 12 12 53 13 15 8 Dar es salaam . . . . . . . . Lindi 20 20 10 10 20 20 10 10 Mtwara 2 2 . . 2 2 . . Ruvuma 31 10 37 12 38 5 43 7 Iringa 41 21 . . 48 12 3 2 Mbeya 15 8 28 14 234 39 38 13 Singida 2 2 . . 3 2 . . Tabora 7 7 4 4 12 4 7 2 Rukwa . . . . 77 77 . . Kigoma 825 275 100 100 825 275 101 51 Kagera 207 41 20 20 209 35 20 20 Mwanza . . . . 5 3 1 1 Mara 65 16 72 18 71 10 72 18 Manyara 35 18 60 30 39 10 60 30 North Unguja 18 9 . . 22 7 . . South Unguja 21 21 8 8 21 21 8 8 Urban West 15 15 20 20 15 15 20 20 North Pemba 43 9 23 6 46 8 25 5 South Pemba 8 8 3 3 9 5 3 3 Total 2459 38 713 18 2823 28 742 15 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 274 OUTGROWER SCHEME APPENDIX II Tanzania Agriculture Sample Census - 2007/08 275 11.1 OUTGROWER SCHEME: Number of of famrs and Area under outgrower scheme (Hectare) by Region Region Number of Farms Area under Outgrower Sheme Dodoma 8 963 Arusha 10 474 Kilimanjaro 7 1,276 Tanga 16 7,253 Morogoro 21 3,566 Pwani 6 4,768 Dar es salaam 2 6 Lindi 4 459 Mtwara 5 1,479 Ruvuma 8 237 Iringa 29 3,692 Mbeya 2 65 Singida 10 664 Tabora 4 1,100 Rukwa 1 18 Kigoma 0 . Shinyanga 0 . Kagera 2 308 Mwanza 13 619 Mara 10 1,232 Manyara 44 2,943 North Unguja 5 51 South Unguja 1 10 Urban West 2 36 North Pemba 0 . South Pemba 0 . Total 210 31,218 APPENDIX II Tanzania Agriculture Sample Census - 2007/08 276 11.2 OUTGROWER SCHEME: Number of of famrs and Service provided under outgrower scheme by Region Region Storing Crop processing Cattle fattening Crop marketing Livestock facilities Livestock products Livestock marketing Extension services Dipping services Total Dodoma 10 4 3 2 1 1 2 4 2 29 Arusha 9 4 4 0 0 0 0 0 0 17 Kilimanjaro 8 7 3 3 0 1 1 3 1 27 Tanga 17 12 9 6 2 2 2 14 7 71 Morogoro 22 6 7 2 3 3 1 6 2 52 Pwani 8 2 6 0 2 3 4 7 4 36 Dar es salaam 2 0 2 1 4 2 4 5 1 21 Lindi 4 3 4 0 0 0 0 0 1 12 Mtwara 6 5 2 0 1 2 3 10 5 34 Ruvuma 13 7 7 4 1 1 2 5 4 44 Iringa 28 9 12 1 2 1 6 23 10 92 Mbeya 3 1 0 0 1 0 0 2 0 7 Singida 10 2 7 0 0 1 0 1 0 21 Tabora 7 6 4 3 1 0 0 3 2 26 Rukwa 1 2 1 0 0 0 0 2 0 6 Kagera 2 2 1 1 1 1 2 12 9 31 Mwanza 17 5 4 1 2 1 1 3 1 35 Mara 11 6 5 2 1 0 0 1 0 26 Manyara 39 11 32 8 2 6 3 35 8 144 North Unguja 6 4 2 1 2 2 2 7 3 29 South Unguja 1 0 0 1 1 1 1 1 1 7 Urban West 2 2 0 0 0 0 0 1 0 5 North Pemba 0 0 0 0 0 0 0 1 1 2 Total 226 100 115 36 27 28 34 146 62 774 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 277 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 278 Table of Contents S/N Topic Page 1 Identification 1 2 Farm Characteristics 1 3 Land Access and Use 3 4 Annual and Permanent Crops Production 4 5 Use of Secondary Products and Agroprocessing 10 6 Access to Credit for Agriculture Purpose 11 7 Livelihood Constraints 10 8 Input Use 10 9 Livestock Production and Diseases 12 10 Employement in Agriculture 16 11 Outgrower Scheme 16 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 279 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward/Shehia …………………………………………………………………… 2.0 FARM CHARACTERISTICS 2.1 Using the options below indicate the type of farm ownership 2.2 Type of Agriculture Holding Codes Agriculture holding codes(Q2.2) Crops only.…………...…… ..1 Livestock only …………….2 Crops and Livestock …….3 Production of Flowers ………4 Type of Ownership codes (Q 2.1) Government.………………..1 Private non registered……..4 Parastatal. ………………….2 Other (Specify) ……………5 Private registered ...……....3 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 280 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Type of Agriculture Holdings Codes (Q 2.2): - Crops only: For large scale farming a holding is referred to be a crops only holding if it has cultivated a piece of land equal exceeding 20 hectares or more than 0.5 hectares of intensive greenhouse horticulture production. This also applies to all holdings owning or have kept livestock whose number does not qualify such holding to be a large scale farm (Less than 50 cattle, less than 100 goats/sheep/pigs, less than 1000 chickens/turkeys/ducks/rabbits, less than 0.5ha of fish farming production units). - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the reference agricultural year. For a large scale farm the number of livestock has to be at least 50 head of cattle, 100 goats/sheep/pigs or 1000 chickens/turkeys/ducks/rabbits. This also applies to all holders owning or having cultivated a piece of land less than 20 hectares or owning less than 0.5hectares of intensive greenhouse horticulture production. - Both crops and livestock: A holding is referred to be a both crops and livestock large scale farm if it has cultivated a piece of land equal or exceeding 20 hectares of crops or over 0.5 hectares of intensive greenhouse horticulture production and if such households is owning or have kept over 50 head of cattle 100 goats/pigs/sheep 1000 Large Scale Agricultural Holding: This is an economic unit of agricultural production. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, large scale agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 20 ha of arable land cultivated for crop/vegetable/fruit/tree crop production during the agriculture year 2007/08 and/or - Own or keep at least fifty head of cattle or 100 goats/sheep/pigs or 1000 chicken/ducks/turkeys/rabbits during the agricultural year 2007/08 (October 2007 to September 2008) . and/or Operates 0.5ha of intensive greenhouse horticulture production (eg cut flowers) and/or keeps 0.5ha of fish farming production units To be classified as a large holder farm the following criteria must also be met: Q 2.2 Type of agriculture holding 1. Using the options under the question classify the type of agriculture holding Note: If the farm had 30 hectares of crops and raised 600 chickens during 2007/08 it is classified as 'Crops only' as the number of chickens do not qualify the holder as keeping livestock. Q 2.1 Type of farm ownership If farm is in joint ownership eg government and private entity, select Other and indicate the partners (eg t & i t APPENDIX III Tanzania Agriculture Sample Census - 2007/08 281 3.0 LAND USE AND ACCESS 3.1 LAND ACCESS/OWNERSHIP/TENURE Details of area "owned" by the household in the 2007/08 agricultural year. Give area reported by the respondent in "acres". Calculation area 3.1.1 Area Leased/Certificate of ownership 3.1.2 Area owned under Customary Law 3.1.3 Area Bought from others 3.1.4 Area Rented from others 3.1.5 Area Borrowed from others 3.1.6 Area under Compulsory Acquisition Total area 3.2 LAND USE Area operated by farm under different forms of land use during 2007/08 agriculture year. Give area reported by the respondent in "hectares". Calculation area 3.2.1 Area under Temporary Mono-crops (eg maize only) 3.2.2 Area under Temporary Mixed crops (eg maize & beans) 3.2.3 Area under Permanent Mono-crops (eg Sisal only) 3.2.4 Area under Permanent Mixed crops (eg bananas & coffee) 3.2.5 Area under Permanent/Annual mix (eg bananas & maize) 3.2.6 Area under Permanent/Pasture mix (eg orange & pasture) 3.2.7 Area under Pasture only 3.2.8 Area under Fallow 3.2.9 Area under Natural Bush 3.2.10 Area under Planted Timber Trees 3.2.11 Area Rented to others 3.2.12 Area Unusable 3.2.13 Area of Uncultivated Usable land (excluding fallow) Total area Area in Hectares Area in Hectare APPENDIX III Tanzania Agriculture Sample Census - 2007/08 282 Section 3.2 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g.apples) but also bushes and shrubs (e.g., berries), palms (e.g. dates), vines (e.g.grapes), herbaceous stems (e.g. bananas) and stemless plants (e.g. pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Annual Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 3.2 - Land Use 1. Ask the respondent the area of the different land use categories the farm has sole access to (Q3.2.1 to 3.2.13) and record in the appropriate spaces. 2.Add up the area of different land use categories and compare with the total area obtained in 3.1 3. If the total area is different , findout which one is correct and make ammendment. Section 3.1 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q3.1.1 to 3.1.6) and record in the appropriate spaces. Section 3.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Area under compulsory acquisition: APPENDIX III Tanzania Agriculture Sample Census - 2007/08 283 4.0 ANNUAL AND PERMANENT CROP PRODUCTION 4.1 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAIN SEASON 4.1.1 Did the farm grow Temporary Crops during the 2007/08 Agriculture year (Yes=1, No=2) (if 'NO' go to section 4.2) Irri Crop -gati Transport Main Main marketing Code Crop Name Planned Planted Harvested -ion Harvested Stored Marketed to market Market problem (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 41 Sunflower 43 Groundnuts 48 Castor 31 Beans 33 Green Grams 37 Field peas 23 Irish Potatoes 24 Yams 26 Onions 27 Ginger 89 Carrots 86 Cabbage 87 Tomatoes 90 Chillie 50 Cotton 51 Tobacco 52 Pyrethrum 98 Kartam 97 Flowers Area in hectares Amount (Metric tonne) Planting Harvest/Storing/Marketing Transport to market (col 9) Own Transport ……1 Contract transport…2 Other Large scale Farm at farm gate…3 Main Market (col 10) Secondary Market……...1 Cooperative….. ……...…2 Trade at farm ……….…. 3 Factory ……………...…...4 Other Large Scale Farm..5 Exported market……...…6 Other …………………..…8 Main Marketing Prolems (col 11) Price too low……........ 1 No transport................ 2 Transport cost too high…3 No buyer.................... 4 Farmers association problems.................... 5 Cooperative problems ... 6 Government Regulatory board problems…….…….7 Lack of marketing information ................. 8 Not applicable……..........9 Irrigation Use (Col 5) Used for the whole crop ….1 Used on 3/4 of whole crop …2 Used on 1/2 of whole crop….3 Used on 1/4 of whole crop ...4 Used on less than 1/4 of whole crop ……………………5 Not used ……………………..6 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 284 working page for page 3 r the calculation by annual crop Total Area of permanent crops in mix AINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary crop name 1 Temporary crop name 2 Temporary crop name 3 Temoporary crop total check Total Area of permanent crops in mix AINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary crop name 1 Temporary crop name 2 Temporary crop name 3 Temoporary crop total check Temp crop% of plants area of plants (Hectare) (d) (Hectare) (e) (f) Crop Name (b) (Hectare) (f) (e) (d) area of plants of plants Total area of mix Hectare (c) Temp crop% of mix (c) (b) Crop Name (Hectare) Total area area/plant Total ground Total no. Total ground Ground area/plant (Hectare) Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Planned Area: Area in Hectare the household planned to plant before the season started Actual Planted Area: The area in Hectare the household was able to plant. Area Harvested: The area in Hectare that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed Permanent and annual use the following procedures to calculate the area occupied by permanent trees before proceeding with step 1. (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 4.1 col 4. 4. Obtain an estimate of the planned area for each crop and enter it in column 2 5. If the area harvested is different to the area planted estimate the harvest area col 4 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/Hectare) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 52 Pyrethrum 62 Jute 19 Seaweed APPENDIX III Tanzania Agriculture Sample Census - 2007/08 285 4.2 ANNUAL CROP AND VEGETABLE PRODUCTION -LONG RAIN SEASON Did the farm grow Temporary Crops during the 2007/08 Agriculture year (Yes=1, No=2) (if 'NO' go to section 4.3) 4.2.1 Irri Crop -gati Transport Main Main marketing Code Crop Name Planned Planted Harvested -ion Harvested Stored Marketed to market Market problem (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 41 Sunflower 43 Groundnuts 48 Castor 31 Beans 33 Green Grams 37 Field peas 23 Irish Potatoes 25 Yams 26 Onions 27 Ginger 89 Carrots 86 Cabbage 87 Tomatoes 90 Chillie 50 Cotton 51 Tobacco 52 Pyrethrum 98 Kartam 97 Flowers Planting Harvest/Storing/Marketing Area in hectares Amount (Metric tonne) Main Market (col 10) Secondary Market……....1 Cooperative ………...…...2 Trader at farm ………….. 3 Factory …………...……...4 Other Large Scale Farm ..5 Exported market……….…6 Other 8 Irrigation Use (Col 5) Used for the whole crop ….1 Used on 3/4 of whole crop …2 Used on 1/2 of whole crop….3 Used on 1/4 of whole crop ...4 Used on less than 1/4 of whole crop ……………………5 Not used ……………………..6 Transport to market (col 9) Own Transport ……1 Contract transport…2 Other Large scale Farm at farm gate…3 Other (Specify)….…8 Main Marketing Prolems (col 11) Price too low…….. 1 No transport.......... 2 Transport cost too high………..…......…3 No buyer............. 4 Farmers association problems.............. 5 Cooperative problems ……...................… 6 Government Regulatory board roblems………7 Lack of markrting information............ 8 Not applicable……....9 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 286 ng page for page 4 calculation nnual crop Total Area of permanent crops in mix G AREA UNDER TEMPORARY CROPS Temp crop area emporary crop name 1 emporary crop name 2 emporary crop name 3 Temoporary crop total check Total Area of permanent crops in mix G AREA UNDER TEMPORARY CROPS Temp crop area emporary crop name 1 emporary crop name 2 emporary crop name 3 Temoporary crop total check (e) (f) Temp crop% (b) (c) (d) (Hectare) (Hectare) area of plants area/plant of plants Name (Hectare) Crop of mix Ground Total no. Total ground Temp crop% Total area (Hectare) (b) (c) (d) (e) (f) Name (Hectare) (Hectare) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 52 Pyrethrum 62 Jute 19 Seaweed Planned Area: Area in Hectare the household planned to plant before the season started Actual Planted Area: The area in Hectare the household was able to plant. Area Harvested: The area in Hectare that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and go to step 1 of these instructions. B. If the mixed crop is mixed Permanent and annual use the following procedures to calculate the area occupied by permanent trees before proceeding with step 1. (i) list each of the permanent crops in column b and enter the ground area per Hectare for each permanent crop (from instructions for page 4) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 4.2 col 4 4. Obtain an estimate of the planned area for each crop and enter it in column 2 5. If the area harvested is different to the area planted estimate the harvest area, col 4 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/Hectare) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . . . APPENDIX III Tanzania Agriculture Sample Census - 2007/08 287 o=2) (if 'NO' go to section 5.0) Trans Main Main Harvested Stored Marketed -port to Mark marketing market -et Problem (7) (8) (9) (10) (11) (12) Amount (Tonne) Harvested/Storing/Marketing Main Market (col 11) Secondary Market…..1 Cooperative ……….…2 Trader at farm ……... 3 Factory ……………....4 Other Large Scale Farm ………………….5 Exported by Farm…..6 Other ……………….…8 Transport to market (col 10) Own Transport ……1 Contract transport…2 Other Large scale Farm at farm gate…3 Other (Specify)……..8 Main Marketing Prolems (col 12) Price too low……....... 1 No transport............... 2 Transport cost too high..3 No buyer.................. 4 Farmers association problems................... 5 Cooperative problems ………....................…. 6 Government Regulatory board roblems……..……7 Lack of marketing information................ 8 Not applicable……........9 Irrigation Use (Col 6) Used for the whole crop ….1 Used on 3/4 of whole crop …2 Used on 1/2 of whole crop….3 Used on 1/4 of whole crop ...4 Used on less than 1/4 of whole crop ……………………5 Not used ……………………..6 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 288 Definitions and working page for page 5 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Permanent Crops: Code Crop Ground area/plant 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin/tangerine 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of trees/bushes This includes both mature harvestable plants and immature non harvestable plants. Number of mature plants: This is the number of plants which bared harvest. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent enter the number of mature trees in column 3 and the Area in column 4 B. For fields that are either mixed permanent or mixed permanent/annual enter the number of mature trees ONLY in column 5 Working Area/calculation space APPENDIX III Tanzania Agriculture Sample Census - 2007/08 289 5.0 USE OF SECONDARY PRODUCTS AND AGROPROCESSING 5.1 MAIN USE OF SECONDARY PRODUCTS Did you use Secondary Products from any of your crops during the 2007/08 year. (Yes=1, No=2) If the response is 'NO' go to section 5.2 List the main crops with secondary products and provide the following details: Name of Secon Used -dary Product for Unit (4) (5) 5.1.1 …………… ………………… 5.1.2 …………… ………………… 5.1.3 …………… ………………… 5.1.4 …………… ………………… 5.1.5 …………… ………………… 5.2 AGROPROCESSING AND BY-PRODUCTS Did the farm process any of the products harvested on the farm during 2007/08 (Yes=1, No=2) If the response is 'NO' go to section 6.1 List the main crops processed and provide the following details: Quantity of Quantity of Main S/N Farm Outgrower/ Prod Quantity Where Whe bi- bi- Quan Crop Crop Produce other farmer's -uct Used of main proce -re product Used Quantity product -tity name Code (tonne) produce (t) code for Unit product ssed sold code for Unit Quantity Sold code Used Unit Quantity Sold (6) (7) (9) (10) (12) (13) (17) (18) 5.2.1 ……. 5.2.2 ……. 5.2.3 ……. 5.2.4 ……. 5.2.5 ……. 5.2.6 ……. Total value of Total value per unit (Tsh.) name Code sold units Total no of Units No of units sold (9) (8) (3) (6) (1) (2) (7) S/N Crop Crop (8) (1) (2) (5) (3) (4) (15) (16) (19) First bi-product Second bi-product (11) (20) (14) Used for (Col 6, 12 & 17) Sale………………...………..1 Animal consumption………..2 On farm factory processing..3 Other (specify) ……………..8 Unit (Col 7, 13 & 18) Loose bundle/bunch ….…1 kilogram………....4 Compressed bunch/bail...2 litre ……………....5 Metric tonne ………….…3 Other (Specify) ....8 Where sold (Col 10) Secondary Market …...1 Factory/Mill ……....5 Marketing Coop...……...2 Exported by farm ...6 Other Largescale farm ...3 Other (specify) …...8 Trader at farm ……...….4 Bi-product code (Col 11 & 16) Bran ………1 Pulp ……………….6 Cake ………2 Oil …………………7 Husk ………3 Shell ………………9 Juice ………4 Other(specify) ……8 Fiber ………5 Main product code (Col 5) Flour/meal..1 Juice……………...4 Grain…...…2 Fiber..………….....5 Oil .. ………3 Other(specify) …...8 Mainly used for (Col 4) Feeding to livestock ………..1 fuel …………......………3 Composting ……………5 Building material …..………..2 Used for processing …..4 Other (Specify) …………8 Unit (Col 5) Loose Bundle/bunch ..……..1 Metric tonne ………..3 litre …………………..5 Compressed bunch/Bail…...2 Kilogram …………...……….4 Other (Specify) …….8 Where Processed (Col 9) On-Farm machine ………….1 Cooperative Union factory …2 Other Large scale farm …….3 Private factory/Mill …………..4 Other (specify)……………....8 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 290 Definition and working page for page 6 Temporary/annual crop codes for section 5.1 and 5.2 col 2 General Definition for Section 5.0 Secondary Crop Crop Product Main Products Code Name Question 5.1(col 3) (Section 5.2) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 5.2) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a farmer may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. Bi-products are the result of a processing activity. Q 5.1 Details of Secondary Products: 1.From the list of crops in Q 4.1.1, 4.2.1 & 4.3.1, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 7,8& 9. Q 5.2 Agroprocessing & bi-products: 1.From the list of crops in Q 4.1.1, 4.2.1 & 4.3.1, ask the respondent if the hh processed any of these crops during the 2007/08 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2.For the listed crops give details of the main and bi-product used. 4. If there is no first bi-product or second bi - product was sold enter "0" in columns 15 and 20 Agroprocessing and bi-products (Q 5.2) Main Product code (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 6, 12 &17): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. APPENDIX III Tanzania Agriculture Sample Census - 2007/08 291 6.0 ACCESS OF CREDIT FOR AGRICULTURE PURPOSES 6.1 USE OF CREDIT FOR AGRICULTURE PURPOSES During the year 2007/08 did the farmer borrow money for agriculture (Yes = 1, No = 2) (if the response is ' NO' go to section 6.3) 6.2 Give details of the credit obtained during the agricultural year 2007/08 (if the credit was provided in kind , for example by the provision of inputs machine or equipments, then estimate the value) 6.2.1 Labour 6.2.2 Seeds 6.2.3 Fertilisers 6.2.4 Agrochemicals 6.2.5 Livestock purchase 6.2.6 Livestock Feed 6.2.7 Tools 6.2.8 Fences 6.2.9 Stores 6.2.10 Irrigation structures 6.2.11 Machinery 6.2.12 Other 6.2.13 Value of Credit ('000 Tsh.) 6.2.14 Value of repayment ('000 Tsh.) 6.3 If the answer to question 6.1 above is NO what is the reason for not applying for Credit? 7.0 AGRICULTURAL CONSTRAINTS From the list of constraints on the right select: S/N Order of most importance Constraint (1) (2) 7.1.1 most important 7.1.2 2nd most important 7.1.3 3rd most important 7.1.4 4th most important 7.1.5 5the most important 8.0 INPUT USE AND COSTS BY CROP ………….. ………….. ………….. S/N Used Used Used (1) (2) (3) (4) (5) (6) (7) (8) 8.1 Soil preparation & planting 8.2 Seed/planting material 8.3 Inorganic fertiliser 8.4 Organic fertiliser 8.5 Herbicides 8.6 Fungicides 8.7 Pesticides 8.8 Harvesting/threshing Source "c" tick the boxes below to indicate the use of credit Source "b" Source "a" Cost/hectare ('000Tsh) Cost/hectare ('000Tsh) Main Source of inputs use codes to indicate source tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of the credit Operation/inputs the 5 most important problems 7.1 CROP NAME CROP CODE Cost/hectare ('000Tsh) Source of credit (Q 6.2-a, b and c)) Company owning the farm ....1 Commercial Bank…..2 Savings and Credit Soc....3 Religious Organisation/NGO/Project …4 Other (Specify)……………..8 Reason for not using credit (Q 6.3) Not needed........1 Did not want to go into credit…... .....3 Credit granted too late......................5 Other(specify) ...... 8 Not available ......2 Interest rate/cost too high................. 4 Difficult bureacratic procedure......... 6 List of constraints 1. Amount of Land 16. Threshing 2. Ownership of Land 17. Storage 3. Cost of Land 18. Processing 4. Length of land tenure 19. Market Information 5. Soil Cultivation 20. Transport costs 6. Soil Fertility 21. Distruction by animals 7. Access to improved seed 22. Stealing 8. Irrigation facilities 23. Pests and Diseases 9. Access to chemical Inputs 24. Local government taxation 10. Cost of Inputs 25. Access to off-farm Income 11. Extension Services 26. Cost of machinery 12. Access to forest resources 27. Availability of livestock drugs 13. Government regulations 28. Livestock diseases 14. Access to credit 29. Availability of pasture 15. Harvesting X X Used (Col 2, 4 & 6) Used for the whole crop ………………...…….1 Used on 3/4 of whole crop …………………….2 Used on 1/2 of whole crop…………………….3 Used on 1/4 of whole crop …………………….4 Used on less than 1/4 of whole crop …………5 Not used ………………………………..………..6 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 292 Definition and working page for page 7 General Definitions for section 7.0 Section 6.0 Credit for Agriculture Purposes Livestock rearing Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agricultural produce. Section 6.1 Credit for Agriculture Purposes and Livestock rearing. Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agricultural produce, then the cash value of this must be estimated. Section 6.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". Make sure that the information given by the respondent concerning the use of credit corresponds to the respective section. Agricultural constraints (section 7.0): The List of constraints are areas in which the farmer may consider a limiting factor to increase profit/livelihood conditions. The responses must be realistic, eg if there is no possibility of having irrrigation on the farm because there is no suitable source of water, then irrigation facilities should NOT be selected as a major problem. Section 7.0 Agricultural constraints 7.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 Section 8.0 Input use and costs by crops 1. For the 3 main crops grown on the farm obtain the amount used and cost per hectare for each crop. Working Area/calculation space APPENDIX III Tanzania Agriculture Sample Census - 2007/08 293 9.0 LIVESTOCK PRODUCTION AND LIVESTOCK DISEASES 9.1 (If no go to section 9.2) Cattle Population as of 1st October2008 Number of S/N Cattle type Indigenous 9.1.1 Bulls 9.1.2 Cows 9.1.3 Steers 9.1.4 Heifers 9.1.5 Male Calves 9.1.6 Female Calves Grand Total SN Unit (2) 9.1.7 9.1.8 9.2 Goat Population as of 1st October 2008 Number of S/N Goat type Indigenous 9.2.1 Ram 9.2.2 Castrated Goat 9.2.3 She Goat 9.2.4 Male Kid 9.2.5 She Kid Grand Total SN Unit (2) 9.2.6 9.2.7 9.3 9.4 Sheep Population as of 1st October 2008 PIG Population as of 1st October 2008 S/N Sheep type Number of Sheep S/N Pig type Number of Pigs 9.3.1 Ram 9.4.1 Boar 9.3.2 Castrated Sheep 9.4.2 Castrated male 9.3.3 She Sheep 9.4.3 Sow/Gilt (1) (2) Dry Season Did the farm own, raise or manage any PIGS during the 2007/08 agriculture year? (Yes =1 No =2) (If no go to section 9.5) (1) (3) (4) (5) (6) Wet Season (Litre) (5) Did the farm own, raise or manage any GOATS during the 2007/08 agriculture year? ( Yes=I, No=2) (If no go to section 9.3) Total Season Amount of milk obtained during 2007/08 Number of goats milked 2007/08 (1) (2) (3) (4) Number of Improved goat for meat Dairy (4) Type of livestock/Product Amount of milk obtained during 2007/08 Average price per litre 2007/08 place sold Milk (Indigenous cattle) (3) (5) (6) Number of livestock milked 2007/08 (Litre) Average price per litre 2007/08 place sold Did the farm own, raise or manage any CATTLE during 2007/08 agriculture year? ( Yes=I, No=2) Dairy Total Number of Improved Beef (5) (3) (4) (1) (2) (2) Did the farm own, raise or manage any SHEEP during the 2007/08 agriculture year? (Yes =1 No =2) (If no go to section 9.4) Milk (Improved cattle) (1) (1) X X X X X X X X X X X X X X X X X X place sold (Col & 6) Neighbour…….............1 Local Market..……........2 Secondary Market ........3 Processing industry .......4 Largescale farm ............5 Trader at Farm .............6 Did not sell ....................7 Other ………...............8 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 294 Definitions and working page for page 8 Question Specific Definitions (Section 9.0) Cattle type (Section 9.1.1 to 9.1.6 Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Section 9.1 Cattle Population. NOTE: Section 9.1 is for the current population (as of 1st October 2008). If the household has cows, you would normally expect them to have calves. Goat type (Section 9.2.1 to 9.2.5 Col 1) Ram: Mature Uncastrated male goat used for breeding. Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age. Kid: Young goat under 9 months of age. Section 9.2 Goat Population NOTE: Section 9.2 is for the current population (as of 1st October 2008). If the household has she goats, you would normally expect them to have kids. APPENDIX III Tanzania Agriculture Sample Census - 2007/08 295 9.5 LIVESTOCK PRODUCTION AND PRODUCTS SN Unit (2) 9.5.1 9.5.2 9.5.3 SN Unit (2) 9.5.4 9.5.5 9.5.6 9.6 LIVESTOCK PEST & PARASITE CONTROL 9.6.5 Do you normally encounter a tsetse fly problem? (Y=1,N=2) 9.6.1 Did you deworm your animals during 2007/08? (Put Yes=1 No= 2) (If the response is 'NO' go to section 9.6.7 and 9.6.8 (If the response is 'NO' go to section 9.6.3) 9.6.6 Which methods of control did you use? 9.6.2 Which animals did you deworm? (Put Yes=1 No= 2) appropriate boxes) Cattle Goats Sheep 9.6.3 Do you normally encounter a tick problem? (Yes=1,No=2) (If the response is 'NO' go to section 9.6.5) 9.6.7 Foot and mouth disease 9.6.8 Lumpyskin 9.6.4 Which methods of tick control did you use? (1) (3) Type of livestock/Product Number Sold during 2007/08 Live pigs Live goats/sheep (Number) Live cattle Pig meat Goat meat/Mutton (Tone) Beef (1) Type of livestock/Product Quantity Sold during 2007/08 Number of livestock slaughtered (3) Average price per unit 2007/08 place sold (5) (4) Average price per tonne 2007/08 (5) (4) Did your livestock get vaccination against the following diseases? (Yes = 1, No = 2). Pigs (6) place sold Control method (Q 9.6.4) Spraying ..1 Dipping..2 Smearing ..3 None...4 Other...8 Control method (Q9.6.6) Spraying ..1 Dipping..2 Trapping ..3 None...4 Other...8 place sold (Col 5 & 6) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 APPENDIX III Tanzania Agriculture Sample Census - 2007/08 296 Definitions for page 9 Section 9.3 Sheep Population. NOTE: Section 9.3 is for the current population (as of 1st October 2008). If the household has ewes, you would normally expect them to have kids Section 9.4 Pig Population. NOTE: Section 9.4 is for the current population (as of 1st October 2008); If the household has sows, you would normally expect them to have piglets i Sheep type (Q 9.3.1 to 9.3.5, Col 1) Ram: Mature Uncastrated male sheep used for breeding Castrated sheep: Male sheep that has been castrated. She sheep: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Pigs type (Section 9.4.1 to 9.4.5 Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow/Gilt: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. APPENDIX III Tanzania Agriculture Sample Census - 2007/08 297 9.7 Information on Other Livestock currently available and details of consumption and sales during the 2007/08 Agriculture year. Animal type 9.7.1 Indigenous Chicken 9.7.2 Layer 9.7.3 Broiler 9.7.4 Ducks 9.7.5 Turkeys 9.7.6 Rabbits 9.7.7 Donkeys 9.7.8 Horses 9.7.9 Other(specify) …………… CHICKEN DISEASES 9.7.10 Newcastle Disease 9.7.11 Gumboro 9.7.12 Coccidiosis 9.7.13 Chorysa 9.7.14 Fowl typhoid 9.8 LIVESTOCK PRODUCTS (1) (2) (3) (4) (5) 9.8.1 Eggs 9.8.2 Hides 9.8.3 Skins 9.9 List in order of importance the outlets for 9.10 Access to functional Livestock structures /accessories( to be filled by the livestock owners only) the sale of Livestock Impo Out Outl Outl Type Source Distance -rtan Outlets -lets -ets -ets S/N of of to struct S/N -ce of for for for for structure/accessory Structure -ure (Km) outlet Cattle Goat chickens Pigs (1) (3) (5) 9.10.1 Cattle Dip 9.9.1 1st 9.10.2 Spray Race 9.9.2 2nd 9.10.3 Hand powered sprayer 9.9.3 3rd 9.10.4 Cattle crush 9.9.4 4th 9.10.5 Primary Market 9.9.5 5th 9.10.6 Secondary Market 9.10.7 Abattoir 9.10.8 Slaughter Slab 9.10.9 Hide/skin shed 9.10.1 Input supply 9.10.11 Veterinary Clinic 9.10.12 Holding ground 9.10.13 Watering point/dam 9.10.14 Drencher (1) (6) (2) (4) Outlets for Sheep (2) (3) Number (3) (5) Average price/unit (2) (1) (4) Sold during 2007/08 Current No. as 1St October. 2008 Number Average Price/head Slaughtered during 2007/08 (6) Kilogram Average price/kg Product Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2007/08 Number Average price/unit Sold during 2007/08 Outlet code (Col 2, 3, 4 ,5 & 6 Qn 9.9) Trader at farm….………….….1 Abattoir…..……………4 Local Market ……….. ……..…2 Another farmer ………5 Secondary market/auction.…..3 Other (Specify)……….8 Source of structure (Col 2 Qn 9.10) Owns …………………………..1 NGO ……....…....…6 Cooperative ...................……..2 Large scale farm.…..7 Local farmers association …... 3 Other ..………….....8 Gov extension/veterinary …….4 Not applicable .........9 Development project ……. …..5 X X X X X . . . . . . . . . . . . . . X X X X X APPENDIX III Tanzania Agriculture Sample Census - 2007/08 298 Definitions for page 10 Question Specific Definitions Section 9.6) Procedures for questions Access to functional Livestock Structures/accessories (Section 9.10): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Drencher: Device for orally administering medicine to livestock. Section 9.9- Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 9.6 - Other Livestock: 1.The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. APPENDIX III Tanzania Agriculture Sample Census - 2007/08 299 10.0 EMPLOYMENT IN AGRICULTURE 10.1 STAFF AND LABOUR USE Give details of employment on the farm during the 2007/08 agriculture year S/N Staff/employee type (2) (3) (4) 10.1.1 General manager/Financial managers/accountants 10.1.2 Clerical/typest/receptionist staff 10.1.3 Mechanical/workshop/parts stores managers 10.1.4 Crop/livestock husbandry managers/agronomists 10.1.5 Irrigation engineers 10.1.6 Product Stores managers 10.1.7 Agroprocessing/Mill managers 10.1.8 Other Professoinal staff 10.1.9 Supervisor staff 10.1.10 Labourers 11.0 SERVICES PROVIDED TO OUTGROWER FARMERS 11.1 Does the farm provide services to small holder farmers (YES=1, No=2) Give details of the services provided to other farmers during the 2007/08 agriculture year S/N Provides service to outgrowers Y=1 N=2 (2) 11.1.1 Cultivation /soil preparation 11.1.2 Weeding and Herbicides 11.1.3 Harvesting S/N Provides service to outgrowers Y=1 N=2 (2) 11.1..4 Storing 11.1..5 Crop processing 11.1..6 Cattle fattening 11.1..7 Crop marketing 11.1..8 Livestock facilities 11.1..9 Livestock products 11.1..10 Livestock marketing 11.1..11 Extension services 11.1..12 Dipping services Area which got service (hectare) (1) (3) (1) Type of Service Number of Outgrower farms (4) (5) Number of permanent employee as 1St October 2008 Number of part time employees as 1St October 2008 Male Female Male Female (1) (3) (4) Type of Service Number of Outgrower farms Crop Quantity(tonne) Is this service paid? (Yes= 1, Average cost (Per hectare) (5) (6) Is this service paid? (Yes= 1, Average cost (Shilling per metric tonne) (5) (6) APPENDIX III Tanzania Agriculture Sample Census - 2007/08 300 Definition and working page for page 11 General Definitions for section 10 Procedures for questions Question Specific Definitions Services provided to outgrowers (section 11.0): These services are normally provided at a cost. - Cultivation: Provision of machinery etc for soil preparation - Crop husbandry: provision of machinery/chemicals for weed/pest control and planting. - Harvesting: provision of machinery for harvesting/threshing/ drying. - Storing: provision of storage space - Crop processing: milling/extraction plant for farm and outgrower produce - Livestock facilities: eg dips, spray races. - Livestock products: eg hide and skin sheds/abatoire - Livestock marketing: transportation/purchase of cattel from outgrowers. - Extension services: advice provided to outgrowers. The Unit (col 4) is different according to the service provided: Cultivation: Hectares Crop Husbandry: Hectares Storing: tonne Procesing: tonne Livestock products: tonne Section 11.0 Services provided to other farmers. 1. Ask respondant if he owns/or has the knowledge to provide each of the listed services and place a "1" in the corresponding boxes in column "2" 2. For each of the boxes marked with "1" in col 2 ask the respondant if he provides the service to out growers and mark with "1" for yes and "2" for no. 3. For each of the services marked with "1" in column "2" complete the remaining columns | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vh: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vh: REGIONAL REPORT: LINDI REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census i =14` TABLE OF CONTENTS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction....................................................................................................................................................... 1 1.2 Geographical Location and Boundaries ........................................................................................................... 1 1.3 Land Area.......................................................................................................................................................... 1 1.4 Climate .............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall ............................................................................................................................................... 1 1.5 Population.......................................................................................................................................................... 1 1.6 Socio-economic Indicators................................................................................................................................ 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 Introduction....................................................................................................................................................... 3 2.2 The Rationale for Conducting the National Sample Census of Agriculture ................................................... 3 2.3 Census Objectives............................................................................................................................................. 3 2.4 Census Coverage and Scope............................................................................................................................. 4 2.5 Legal Authority of the National Sample Census of Agriculture...................................................................... 5 2.6 Reference Period............................................................................................................................................... 5 2.7 Census Methodology....................................................................................................................................... 5 2.7.1 Census Organization........................................................................................................................... 5 2.7.2 Tabulation Plan................................................................................................................................... 5 2.7.3 Sample Design.................................................................................................................................... 5 2.7.4 Questionnaire Design and Other Census Instruments....................................................................... 6 2.7.5 Field Pre-Testing of the Census Instruments..................................................................................... 6 2.7.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 6 2.7.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.7.8 Household Listing .............................................................................................................................. 7 2.7.9 Data Collection................................................................................................................................... 7 2.7.10 Field Supervision and Consistency Checks....................................................................................... 8 2.7.11 Data Processing .................................................................................................................................. 8 - Manual Editing ............................................................................................................................. 8 - Data Entry..................................................................................................................................... 8 - Data Structure Formatting............................................................................................................ 8 - Batch Validation........................................................................................................................... 8 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality.................................................................................................................................. 9 2.7.12 Funding Arrangements....................................................................................................................... 9 PART III: CENSUS RESULTS AND ANALYSIS ................................................................................................ 10 3.1 Introduction................................................................................................................................................... 10 3.2 Holding Characteristics................................................................................................................................ 10 3.2.1 Type of Holdings.............................................................................................................................. 10 3.2.2 Livelihood Activities/Source of Income.......................................................................................... 10 3.2.3 Sex and Age of Heads of Households.............................................................................................. 11 3.2.4 Number of Household Members...................................................................................................... 11 3.2.5 Level of Education ........................................................................................................................... 11 - Literacy ....................................................................................................................................... 11 - Literacy Level for Household Members .................................................................................... 11 - Literacy Rates for Heads of Households.................................................................................... 12 - Educational Status ...................................................................................................................... 12 3.2.6 Off-farm Income............................................................................................................................... 13 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.3 Crop Results .................................................................................................................................................. 13 3.3.1 Land Use........................................................................................................................................... 13 3.3.1.1 Area of Land Utilised..................................................................................................... 13 3.3.1.2 Types of Land use.......................................................................................................... 14 3.3.2 Annual Crops and Vegetable Production......................................................................................... 14 3.3.2.1 Area Planted ................................................................................................................... 14 3.3.2.2 Crop Importance............................................................................................................. 15 3.3.2.3 Crop Types ..................................................................................................................... 15 3.3.2.4 Cereal Crop Production.................................................................................................. 16 - Maize....................................................................................................................... 16 - Sorghum.................................................................................................................. 17 - Other Cereals .......................................................................................................... 17 3.3.2.5 Roots and Tuber Crops Production................................................................................ 17 - Cassava.................................................................................................................... 19 - Sweet Potatoes ........................................................................................................ 19 3.3.2.6 Pulse Crops Production.................................................................................................. 20 - Cowpeas.................................................................................................................. 20 - Green Gram............................................................................................................. 20 3.3.2.7 Oil Seed Production ....................................................................................................... 21 - Simsim..................................................................................................................... 22 3.3.2.8 Fruits and Vegetables..................................................................................................... 22 - Tomatoes................................................................................................................. 23 - Pumpkins................................................................................................................. 24 - Onion....................................................................................................................... 24 3.3.2.9 Other Annual Crops Production .................................................................................... 25 - Tobacco................................................................................................................... 25 3.3.3 Permanent Crops .............................................................................................................................. 25 3.3.3.1 Cashewnuts..................................................................................................................... 27 3.3.3.2 Pigeonpeas...................................................................................................................... 27 3.3.3.3 Coconut .......................................................................................................................... 27 3.3.3.4 Oranges........................................................................................................................... 28 3.3.4 Inputs/Implements Use..................................................................................................................... 29 3.3.4.1 Methods of land clearing................................................................................................ 29 3.3.4.2 Methods of soil preparation ........................................................................................... 29 3.3.4.3 Improved seeds use ........................................................................................................ 30 3.3.4.4 Fertilizers use ................................................................................................................. 30 - Farm Yard Manure Use .......................................................................................... 31 - Inorganic Fertilizer Use.......................................................................................... 32 - Compost Use........................................................................................................... 32 3.3.4.5 Pesticide Use .................................................................................................................. 33 - Insecticide Use........................................................................................................ 33 - Herbicide Use.......................................................................................................... 34 - Fungicide Use ......................................................................................................... 34 3.3.4.6 Harvesting Methods ....................................................................................................... 35 3.3.4.7 Threshing Methods......................................................................................................... 35 3.3.5 Irrigation ........................................................................................................................................... 35 3.3.5.1 Area planted with annual crops and under irrigation.................................................... 36 3.3.5.2 Sources of water used for irrigation............................................................................... 36 3.3.5.3 Methods of obtaining water for irrigation ..................................................................... 36 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.3.5.4 Methods of water application ....................................................................................... 36 3.3.6 Crop Storage, Processing and Marketing......................................................................................... 37 3.3.6.1 Crop Storage................................................................................................................... 37 - Method of Storage .................................................................................................. 37 - Duration of Storage................................................................................................. 38 - Purpose of Storage.................................................................................................. 38 - The Magnitude of Storage Loss ............................................................................. 39 3.3.6.2 - Agro processing and by-products........................................................................... 39 - Processing Methods................................................................................................ 39 - Main Agro-processing Products............................................................................. 40 - Main use of primary processed Products ............................................................... 40 - Outlet for Sale of Processed Products.................................................................... 41 3.3.6.3 Marketing ....................................................................................................................... 41 - Crop Marketing....................................................................................................... 41 - Main Marketing Problems...................................................................................... 42 - Reasons for Not Selling.......................................................................................... 42 3.3.7 Access to Crop Production Services................................................................................................ 42 3.3.7.1 Access to Agricultural Credits....................................................................................... 42 - Source of Agricultural Credits................................................................................ 42 - Use of Agricultural Credits..................................................................................... 43 - Reasons for not using agricultural credits.............................................................. 43 3.3.7.2 Crop Extension............................................................................................................... 43 - Sources of crop extension messages ...................................................................... 44 - Quality of extension................................................................................................ 44 3.3.8 Access to Inputs................................................................................................................................ 42 3.3.8.1 Use of Inputs .................................................................................................................. 42 - Inorganic Fertilisers................................................................................................ 42 - Improved Seeds....................................................................................................... 43 - Insecticides and Fungicides.................................................................................... 43 3.3.9 Tree Planting ...................................................................................................................................... 3.3.9.1 Irrigation and Erosion Control Facilities....................................................................... 43 3.4 Livestock Results........................................................................................................................................... 45 3.4.1 Cattle Production.............................................................................................................................. 45 3.4.1.1 Population....................................................................................................................... 45 3.4.1.2 Herd size......................................................................................................................... 45 3.4.1.3 Population Trend............................................................................................................ 45 3.4.1.4 Improved Breeds ............................................................................................................ 46 3.4.2 Goat Production................................................................................................................................ 46 3.4.2.1 Population....................................................................................................................... 46 3.4.2.2 Herd Size........................................................................................................................ 46 3.4.2.3 Breeds............................................................................................................................. 46 3.4.2.4 Population Trend............................................................................................................ 47 3.4.3 Sheep Production.............................................................................................................................. 47 3.4.3.1 Population....................................................................................................................... 47 3.4.3.2 Population Trend............................................................................................................ 47 3.4.4 Pig Production .................................................................................................................................. 47 3.4.4.1 Population Trend............................................................................................................ 48 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.4.5 Chicken Production .......................................................................................................................... 48 3.4.5.1 Population....................................................................................................................... 48 3.4.5.2 Population Trend............................................................................................................ 48 3.4.5.3 Flock Size....................................................................................................................... 49 3.4.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 49 3.4.6 Other Livestock ................................................................................................................................ 49 3.4.7 Pests and Parasites Incidences and Control..................................................................................... 50 3.4.7.1 Deworming..................................................................................................................... 50 3.4.8 Access to Livestock Services........................................................................................................... 50 3.4.8.1 Access to livestock extension Services ......................................................................... 50 3.4.8.2 Access to Veterinary Clinic ........................................................................................... 51 3.4.8.3 Access to village watering points/dam .......................................................................... 51 3.4.9 Animal Contribution to Crop Production ........................................................................................ 51 3.4.9.1 Use of Draft Power......................................................................................................... 51 3.4.9.2 Use of Farm Yard Manure ............................................................................................. 52 3.5 Fish Farming.................................................................................................................................................. 52 3.6 Access to Infrastructure and Other Services............................................................................................. 52 3.7 Poverty Indicators......................................................................................................................................... 53 3.7.1 Type of Toilets ................................................................................................................................. 53 3.7.2 Household’s assets............................................................................................................................ 53 3.7.3 Sources of Light Energy................................................................................................................... 53 3.7.4 Sources of Energy for Cooking........................................................................................................ 53 3.7.5 Roofing Materials............................................................................................................................. 54 3.7.6 Access to Drink Water ..................................................................................................................... 54 3.7.7 Food Consumption Pattern............................................................................................................... 54 3.7.7.1 Number of Meals per Day.............................................................................................. 54 3.7.7.2 Meat Consumption Frequencies .................................................................................... 55 3.7.7.3 Fish Consumption Frequencies...................................................................................... 55 3.7.8 Food Security.................................................................................................................................... 55 3.7.9 Main Source of Cash Income........................................................................................................... 55 PART IV: CENSUS EVALUATION AND CONCLUSION.................................................................................. 57 4.1 Regional Profile .............................................................................................................................................. 57 4.2 District Profile................................................................................................................................................. 57 4.2.1 Kilwa ................................................................................................................................................ 57 4.2.2 Lindi Rural ....................................................................................................................................... 57 4.2.3 Nachingwea...................................................................................................................................... 58 4.2.4 Liwale............................................................................................................................................... 58 4.2.5 Ruangwa........................................................................................................................................... 58 4.2.6 Lindi Urban ...................................................................................................................................... 59 ACRONYMS ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Lindi region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organization of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Lindi region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings on agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Lindi region. It provides an overview of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Lindi region were 153,173 out of which 138,034 (90.1%) were involved in growing crops only, 159 (0.1%) were rearing livestock only, and 14,981 (9.8%) were involved in crop production as well as livestock keeping. In summary, Lindi region had 153,015 households involved in crop production and 15,139 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by tree/forest resources, off farm income, permanent crop farming, livestock keeping/herding, remittances and fishing/hunting. The region has a literacy rate of 59 percent. The district with the highest literacy rate was Nachingwea district (66%) followed by Lindi Urban district (64%), Liwale district (63%) and Ruangwa (59%). Kilwa and Lindi Rural districts had the lowest literacy rates of 57 and 54 percent respectively. The literacy rate for the heads of households in the region was 65 percent. The number of heads of agricultural households with formal education in Lindi region was 95,471 (62.3%), those without formal education were 57,702 (37.6%) and those with only adult education were 4,660 (3%). The majority of heads of agricultural households (60.3%) had primary level education whereas only 2.0 percent had education that was above primary education. In Lindi region 79,211 household members (71.2%) had only one aged 5 years and above engaged in off farm incone generating activities and 22,672 households (20.4%) had two members in off farm income generating activities and 9,345 (8.4%) had more than two members engaged in such activities. ii) Crop Production Land Area The total area of land available to smallholders was 339,483 ha. The regional average land area utilised for crop production per crop growing household was 1.8 ha. This figure was slightly lower than the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 195,785 hectares planted during wet season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii An estimated area of 122,420 ha (62.7% of the total planted area with annual and vegetable crops) was planted with cereals, followed by of roots and tubers 47,189 ha (24.1%), oil seeds and oil nuts 18,782 ha (9.6%), pulses, 6,016 ha (3.1%), fruits and vegetables 946 ha (0.5%). Maize Maize was the dominant annual crop grown in Lindi region and it had a planted area 1.5 times greater than cassava, which had the second largest planted area. The area planted with maize constituted 37 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were cassava, sorghum, paddy, simsim, cowpeas, bambaranuts, tomatoes, pumpkins and sweet potatoes. There was a sharp increase in maize production in 1996. Maize production remained the same over the two year period from 1998 to 1999 after which the production declined until over the remaing period up to 2003. The average area planted with maize per household was 0.56 hectares; however it ranged from 0.42 hectares in Lindi Rural district to 0.77 hectares in Liwale district. Nachingwea district had the largest area of maize (22,714 ha) followed by Lindi Rural (14,876 ha), Ruangwa (14,191 ha), Kilwa (11,056 ha), Liwale (7,658 ha) and Lindi Urban (975 ha) Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Lindi region during the long rainy season was 76,620 which were 51 percent of the total crop growing households in Lindi region in the long rainy season. The total production of sorghum was 9,768 tonnes from a planted area of 34,872 hectares resulting in a yield of 0.28 t/ha Cassava The number of households growing cassava in the region was 88,540. This represented 58 percent of the total crop growing households in the region. The total production of cassava during the census year was 25,814 tonnes from a planted area 46,788 hectares resulting in a yield of 0.6 t/ha. Fruit and Vegetables The total production of fruit and vegetables was 3,160 tonnes. The most cultivated fruit and vegetable crop was the tomatoe. The production for this crop was 2,177 tonnes (69% percent of the total fruit and vegetable production) followed by onions (405 tonnes, 13%), okra (278 tonnes, 9%) and pumpkins (1,262 tonnes, 8%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The most important permanent crop in Lindi region was a cashew tree which had a planted area of 55,683 ha, (67.5% of the planted area of all permanent crops) followed by pigeon peas (14,142 ha, 17.1%), coconut (8,381 ha, 10.2%), orange (1,869 ha, 2.3%), mango (1,830 ha, 2.2%), banana (437 ha, 0.53%), sugarcane (56 ha, 0.07%), guava (19 ha, 0.02%) and avocado (11 ha, 0.01). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Improved Seeds Improved seeds were used by 8 percent of the total number of crop growing households. Most of the improved seeds were obtained from the local market and trade store 43.2 percent. Other sources of improved seed were from neighbours (29.9%), locally produced by household (15.5%), crop buyers (3.3%) and development projects (1.2%). Use of Fertilizers The use of fertilisers on annual crops was very small being on a planted area of only 6,312 ha (3.2% of the total area planted with annuals in the region). The planted area without fertiliser use for annual crops was 189,063 hectares representing 96.8 percent of the total area planted with annual crops. Of the planted area with fertiliser application, compost was applied to 3,325 ha which represents 2 percent of the total planted area. This was followed by farm yard manure, applied to 2,204 ha which represents one percent. Inorganic fertilizers were used on a very small area and represented only 0.5 percent of the area planted with annual crops. Irrigation In Lindi region, the area under irrigation was 959 ha.. The district with the largest planted area under irrigation was Lindi Rural (431 ha, 44.9% of the total irrigated area in the region). This was closely followed by Liwale with (227 ha, 23.7%) and then Kilwa (176 ha, 18.4%), Ruangwa (118 ha, 12.3%), Nachingwea (7ha, 0.7%) and Lindi Urban had no land under irrigation. • Crop Storage There were 97,394 crop growing households (64% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 78,537 households storing 3,720 tonnes as of 1st January 2004. This was followed by sorghum and millet (41,507 households, 1,432 tonnes), pulses (28,321 households, 832 tonnes), paddy (17,411 households, 700 tonnes), groundnuts and bambaranuts (4,978 households, 113 tonnes) and cashew nuts (1,576 households, 10 tonnes). Other crops were stored in very small quantities. Crop Marketing The number of households that reported selling crops was 107,996 which represented 70.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Lindi Rural (92%), followed by Ruangwa (68%), Kilwa (66%), Nachingwea (58%), Lindi Urban (45%) and Liwale (36%). Agricultural Credit In Lindi region very few agricultural households (535, 0.3% of the total agricultural household) accessed credit out of which 405 (76%) were male-headed households and 130 (24%) were female headed households. In Nachingwea and Ruangwa districts only male headed households got agricultural credit whereas in Lindi Rural credit was equally accessed by male and female headed households. In Liwale district, of the households that accessed agricultural credit, 75% were male headed households. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix Crop Extension Services The number of Agricultural households that received crop extension was 25,571 (16.7% of total crop growing households in the region) Some districts had more access to extension services than others, with Nachingwea having a relatively high proportion of households (37%) that received crop extension messages in the district followed by Lindi Urban (28%), Lindi Rural (21%), Ruangwa (15%), Kilwa (14%) and Liwale (9%) • Soil Erosion and Water Harvesting facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 998. This number represented 1 percent of total number of agricultural households in the region. The proportion of households with soil erosion control and water harvesting facilities was highest in Nachingwea District (61%) followed by Lindi Rural (21%), Liwale (11%) and Ruangwa (7%). iii) Livestock and Poultry Production Cattle The number of indigenous cattle in Lindi region was 2,019 (65.5 % of the total number of cattle in the region), 998 cattle (32.4%) were dairy breeds and 64 cattle (2.1%) were beef breeds. The census results show that 838 agricultural households (0.5% of the total agricultural households) kept 308 cattle. This was equivalent to an average of 4 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Lindi Rural which had about 1,300 (42%) cattle. Other districts and their respective estimated number of cattle were Lindi Urban 1,080 (35%) and Nachingwea 700 (23%). Goats The number of goat-rearing-households in the region was 14,084 (9.2% of all agricultural households) with a total of 110,506 goats giving an average of 8 head of goats per goat-rearing-households. Lindi Rural had the largest number of goats estimated at 42,758 (39% of all goats in the region) followed by Kilwa 20,531 (19%), Nachingwea 18,807 (17%), Ruangwa 12,200 (11%), Lindi Urban 9,694 (9%) and Liwale 6,515 (6%). Sheep The number of sheep-rearing households was 1,555 (1% of all agricultural households in Lindi region) rearing 11,905 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Lindi Rural with 4,464 sheep (37%of total sheep in Lindi region) followed by Ruangwa (3,678 sheep, 31%), Nachingwea (2,285 sheep, 19%) and Liwale (926 sheep, 8%). Lindi Urban District had the least number of sheep (552 sheep, 5%) Pigs The number of pig-rearing agricultural households in Lindi region was 1,407 (1% of the total agricultural households in the region) rearing 4,956 pigs. This gives an average of 4 pigs per pig-rearing household. Chicken The number of households keeping chicken was 83,711 raising about 1,261,290 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country, Lindi region was ranked 14th out of the 21 Mainland regions. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x Use of Draft Power In Lindi region the use of draft power was very minimal Fish Farming Fish farming was not practiced in the region. iv) Poverty Indicators Availability of Toilets A large number of rural agricultural households used traditional pit latrines (142,796 households, 93.2% of all rural agricultural households) 2,302 households (1.5%) used flush toilets and 481(0.3%) used improved pit latrines. However, 7,594 households (5% of agricultural households in the region) had no toilet facilities Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.66 percent of all rural agricultural households in Lindi region. This was followed by charcoal (1.77%). The rest of energy sources accounted for 0.57 percent. These were mains electricity (0.24%) crop residues (0.12%), livestock dung (0.01%), solar (0.05%), paraffin/kerosene (0.02%) and bottled gas (0.02%). Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves and it was used by 81.3 percent of the rural agricultural households. This was followed by iron sheets (15.4%), grass/mud (1.7%), tiles (1.2%), asbestos (0.2%), and concrete (0.1%). Grass/leaves were the main roofing material used in Lindi region. Kilwa district had the highest percentage of households with grass/leaves roofing (87%) followed by Lindi Rural and Nachingwea districts (83%), Ruangwa (76%), Lindi Urban and Liwale (73%). Number of Meals per Day The majority of households in Lindi region normally took 2 meals per day (51.3 percent of the households in the region). This was followed by 3 meals per day (41.4 percent) and 1 meal per day (7.1 percent). Only 0.2 percent of the households had 4 meals per day Food Security In Lindi region, 50,993 households (33.3% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements. However 11,975 (7.8%) said they sometimes experience problems, 16.4 often experienced problems and 9.9 percent always had problems in satisfying the household food requirements. About 32.5 percent of the agricultural households said they did not experience any food sufficiency problems EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Main Source of Cash Income The main cash income of the households in Lindi region was from selling cash crops (40.9 percent of smallholder households), followed by selling of food crops (19.7%), casual labour (15.3%), businesses (6.9%), cash remittances (5%), forest products (4.5%), fishing (2.5%) and wages/salaries (2.2%). Only 1.6% of smallholder households reported the selling of livestock as their main source of income, followed by other sources (0.8%) and livestock products (0.5%) INTRODUCTION ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size................................................................................................................ 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District............................................................................ 10 3.2 Area, Production and Yield of cereal crops by Season ........................................................ 16 3.3 Area Planted, Quantity and Yield Harvested of Root Crops................................................ 18 3.4 Area, Quantity Harvested and Yield of Pulses .................................................................... 20 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops ...................................................... 21 3.6 Area, Production and Yield of Fruits and Vegetables by Season ........................................ 22 3.7 Land Clearing Methods........................................................................................................ 29 3.8 Planted Area by Type of Fertiliser Use and district in Wet Season..................................... 33 3.9 Number of Crop Growing Households and Planted Area (ha) by Type of Fertilizer Use and District ..................................................................................... 31 3.10 Number of Households Storing Crops by Estimated Storage Loss and District.................. 39 3.11 Reasons for Not Selling Crop Produce................................................................................. 42 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District ................................................................................................ 43 3.13 Access to Inputs.................................................................................................................... 49 3.14 Number of Households and Chickens Raised by Flock Size ............................................... 49 3.15 Number of Other Livestock by Type of Livestock and District........................................... 50 3.16 Number of Households by Number of meals the Household normally has per Day and District........................................................................................ 55 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings ......................... 10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ............... 11 3.3 Percentage Distribution of Population by Age and Sex in 2003.......................................... 11 3.4 Percentage Literacy level of Household Members by District............................................. 11 3.5 Literacy Rates for Heads of Household by Sex and District................................................ 12 3.6 Percentage of Persons Aged 5 years and above by Educational Status ............................... 12 3.7 Percentage of Population Aged 5 years and above by District and in Education Status ..... 12 3.8 Percentage Distribution of Heads of Household by Educational Attainment...................... 12 3.9 Number of Household by Number of members with Off-farm Income............................... 13 3.10 Percentage Distribution of Households Members by Off-farm Income Generating Activities and District........................................................................................ 13 3.11 Utilized and Usable Land per Household by District........................................................... 13 3.12 Land Area by Type of Use .................................................................................................. 14 3.13 Area Planted with Annual Crops by Seasons (hectares) ...................................................... 14 3.14 Area Planted with Annual Crops in Wet (rainy) season by District .................................... 14 3.15 Area Planted with Annual Crops per Household by District ............................................... 14 3.16 Planted Area for the Main Annual Crops (ha) ..................................................................... 15 3.17 Planted Area (ha) per Household by Selected Crop ............................................................ 15 3.18 Percentage Distribution of Area Planted with Annual Crops by Crop Type ....................... 15 3.19 Area Planted and Yield of Major Cereal Crops ................................................................... 16 3.20 Time Series Data on Maize Production................................................................................ 16 3.21 Maize: Total Area Planted and Planted Area per Household by District............................. 17 INTRODUCTION ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.22 Time Series of Maize Planted Area and Yield..................................................................... 17 3.23 Sorghum: Total Area Planted and Planted Area per Household by District....................... 17 3.24 Time Series Data on Sorghum Production........................................................................... 17 3.25 Time Series of Sorghum Planted Area and Yield ................................................................ 18 3.26 Area planted with Paddy and Finger Millet by District ....................................................... 18 3.27 Area Planted and Yield of Other Root and Tuber Crops ..................................................... 19 3.28 Area Planted with During the census / Survey Years .......................................................... 19 3.29 Percentage of Cassava Planted Area and Percent of Total Land with Cassava by District . 20 3.30 Cassava Planted Area per Cassava Growing Households by District.................................. 20 3.31 Sweet Potatoes: total Area Planted and Planted Area .......................................................... 21 3.32 Area Planted and Yield of Major Pulse Crops ..................................................................... 21 3.33 Percentage of Cowpeas Planted Area and Percent of Total Land with Cowpeas by District ............................................................................................................. 21 3.34 Area Planted per Cowpeas Growing Household by District (Long Rainy Season Only)... 22 3.35 Percent of Green Gram Planted Area and Percent of Total land with Green Gram by District............................................................................................... 22 3.36 Area Planted per Green gram Growing Household by District (Long rainy Season Only) 22 3.37 Area Planted and Yield of Other Major Oil Seed Crop ...................................................... 23 3.38 Percent of Simsim Planted Area and Percent of Total Land with Simsim by District........ 23 3.39 Area Planted per Simsim Growing Household by District (Long Rainy Season Only) ..... 24 3.40 Area Planted and Yield of Fruits and Vegetables ............................................................... 24 3.41 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ....... 24 3.42 Area planted per Tomato growing Household by District .................................................. 25 3.43 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District 25 3.44 Percent of Onions Planted Area and Percent of Total Land with Onions by District......... 26 3.45 Area Planted with Annual cash Crops................................................................................. 26 3.46 Area Planted for Annual and Permanent Crop.................................................................... 26 3.47 Area Planted with the Main Perennial Crop........................................................................ 26 3.48 Percent of Area Planted and Average Planted Area with Permanent Crops by District..... 27 3.49 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District.......................................................................................................... 27 3.50 Percent of Area Planted with Pigeon peas and Average Planted Area per Household by District.......................................................................................................... 28 3.51a Percent of Area Planted with Oranges and Average Planted Area per Household by District.......................................................................................................... 28 3.51b Number of Households by Method of Land Clearing During the Long Rainy Season ...... 29 3.52 Area Cultivated by Cultivation Method.............................................................................. 29 3.53 Area Cultivated by Method of Cultivation and District...................................................... 29 3.54 Planted Area with Improved Seed ...................................................................................... 30 3.55 Planted Area with Improved Seed by Crop Type................................................................ 30 3.56 Percentage of Crop Type Planted Area with Improved Seed – Annuals ............................ 30 3.57 Area of Fertilizer Application by Type of Fertilizer ........................................................... 30 3.58 Area of Fertilizer Application by Type of Fertilizer and District ....................................... 30 3.59 Planted Area with Farm Yard Manure by Crop Type ........................................................ 31 3.60 Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals...................... 31 3.61 Proportion of Planted Area Applied with Farm Yard Manure by District.......................... 31 3.62 Planted Area with Inorganic Fertilizer by Crop Type......................................................... 32 3.63 Percentage of Crop Type Planted Area with Inorganic Fertilizers – Annuals .................... 32 3.64 Proportion of Planted Area Applied with Inorganic Fertilizer by District........................ 31 3.65 Planted Area with Compost by Crop Type ......................................................................... 32 3.66 Percentage of Planted Area with Compost by District........................................................ 32 3.67 Proportion of Planted Area Applied with Compost by District ........................................ 32 INTRODUCTION ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.68 Planted area (ha) by Pesticide use ....................................................................................... 33 3.69 Planted Area applied with Insecticides by Crop Type ........................................................ 33 3.70 Percentage of Crop Type Planted Area applied with insecticides....................................... 33 3.71 Percent of Planted Area Applied with Insecticides by District........................................... 33 3.72 Planted Area applied with herbicides by Crop Type........................................................... 34 3.73 Percentage of Crop Type Planted Area applied with herbicides......................................... 34 3.74 Proportion of Planted Area applied with Herbicides by District ........................................ 34 3.75 Planted Area applied with Fungicides by Crop Type.......................................................... 34 3.76 Percentage of Crop Type Planted Area applied with Fungicides........................................ 34 3.77 Proportion of Planted Area applied with Fungicides by District ........................................ 35 3.78 Area of Irrigated Land......................................................................................................... 35 3.79 Planted Area and Percentage of Planted Area with Irrigation by District........................... 36 3.80 Number of Households with Irrigation by Source of Water ............................................... 36 3.81 Number of Households by Method of Obtaining Irrigation Water..................................... 36 3.82 Number of Households with Irrigation by Method of Field Application............................ 37 3.83 Number of Households and Quantity Stored by Crop Type ............................................... 37 3.84 Number of households by Storage Methods ....................................................................... 37 3.85 Number of households by method of storage and District (based on the most important household crop) ................................................................... 38 3.86 Normal Length of Storage for Selected Crops .................................................................... 38 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District.................... 38 3.88 Number of Households by Purpose of Storage and Crop Type .......................................... 39 3.89a Households Processing........................................................................................................ 39 3.89b Percentage of Households Processing Crops by District .................................................... 39 3.90 Percent of Crop Processing Households by Method of Processing .................................... 40 3.91 Number of Households by Type of Main Processed Product ............................................. 40 3.92 Number of Households by Type of Bi-product................................................................... 40 3.93 Use of Processed Product.................................................................................................... 41 3.94 Percentage of Households Selling Processed Crops by District ......................................... 41 3.95 Location of Sale of Processed Products .............................................................................. 41 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District ........... 41 3.97 Number of Crop Growing Households Selling Crops by District....................................... 42 3.98 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem............................................................................................. 42 3.99 Percentage Distribution of Households Receiving Credit by Main Sources....................... 43 3.100 Number of Households Receiving Credits by Main Source of Credit and district ............. 43 3.101 Proportion of Households Receiving Credits by Main Purpose of the Credit .................... 43 3.102 Reason for Not Receiving (% of Household)...................................................................... 44 3.103 Number of Households Receiving Extension Advice......................................................... 44 3.104 Number of Households Receiving Extension by District ................................................... 44 3.105 Number of Households Receiving Extension Messages by Type of Extension provider... 44 3.106 Number of Households Receiving Extension by Quality of Services................................. 45 3.107 Number of Households by Source of Inorganic Fertilizer .................................................. 45 3.108 Number of Households Reporting Distance to Source of Inorganic Fertilizer ................... 45 3.109 Number of Households by Source of Improved Seed......................................................... 45 3.110 Number of Households Reporting Distance to Source of Improved Seed.......................... 45 3.111 Number of Households by Source of Insecticide/fungicide................................................ 45 3.112 Number of Households Reporting Distance to Source of Insecticide/fungicide................. 45 3.113 Number of Trees Planted by Smallholders by species and District .................................... 45 3.114 Number of Planted Trees by species ................................................................................... 45 3.115 Number of Trees Planted by Location ................................................................................ 45 3.116 Number of households by Purpose of Planted Trees .......................................................... 45 INTRODUCTION ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.117 Number of Households with Erosion Control/Water Harvesting Facilities........................ 45 3.118 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District.......................................................................................... 45 3.119 Total Number of Cattle ('000') by District .......................................................................... 45 3.120 Numbers of Cattle by Type and District ............................................................................. 46 3.121 Cattle Population Trend....................................................................................................... 46 3.122 Dairy Cattle Population Trend ............................................................................................ 46 3.123 Total Number of Goats ('000') by District........................................................................... 47 3.124 Goat Population Trend ........................................................................................................ 46 3.125 Total Number of Sheep by District ..................................................................................... 48 3.126 Sheep Population Trend ...................................................................................................... 48 3.127 Total Number of Pigs by District ........................................................................................ 48 3.128 Pig Population Trend........................................................................................................... 48 3.129 Total Number of Chicken by District.................................................................................. 49 3.130 Chicken Population Trend................................................................................................... 49 3.131 Number of Improved Chicken by Type and district............................................................ 50 3.132 Layers Population Trend ..................................................................................................... 50 3.133 Percentage of Livestock Keeping Households Reporting tsetse flies and tick Problems by District ............................................................................ 50 3.134 Percent of Livestock Rearing Households that Dewormed Livestock Type and District... 50 3.135 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ............................................................................ 51 3.136 Number of households by Distance to veterinary Clinic .................................................... 51 3.137 Number of households by Distance to veterinary Clinic and District................................. 51 3.138 Number of households by Distance to Village Watering Point and district ....................... 51 3.139 Number of households by Distance to Village Watering Points......................................... 51 3.140 Number of households by Organic Fertilizer...................................................................... 51 3.141 Area of Application of Organic Fertilizer by District ......................................................... 51 3.142 Number of households Practicing Fish Farming................................................................. 51 3.143 Number of households by Practicing Fish Farming by District.......................................... 51 3.144 Fish Production.................................................................................................................... 51 3.145 Number of households by Type of Toilet Facility .............................................................. 51 3.146 Percentage Distribution of Households Owning the Assets................................................ 54 3.147 Percentage Distribution of Households by Main Source of Energy for Lighting............... 54 3.148 Percentage Distribution of Households by Main Source of Energy for Cooking............... 54 3.149 Percentage Distribution of Households by Type of Roofing Material................................ 54 3.150 Percentage Distribution of Households with Grass/Leaves Roofs by District.................... 54 3.151 Percentage Distribution of Main Source of Drinking Water and Season............................ 55 3.152 Number of Agricultural Households by number of meals per day ..................................... 51 3.153 Number of households by Frequency of Meat and Fish Consumption............................... 51 3.154 Percentage Distribution of the Number of Households by Main source of Income ........... 51 INTRODUCTION ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi List of Maps 3.1 Total Number of Agricultural Households by District...................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District......................................12 3.3 Number of Crop Growing Households by District.........................................................................13 3.4 Percent of Crop Growing Households by District..........................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................14 3.6 Percent of Crop and Livestock Households by District .................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land......................................................20 3.8 Total Planted Area (annual crops) by District................................................................................20 3.09 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District................21 3.10 Planted Area and Yield of Maize by District .................................................................................22 3.11 Area Planted per Maize Growing Household.................................................................................22 3.12 Planted Area and Yield of Sorghum by District.............................................................................23 3.13 Area Planted per Sorghum Growing Household............................................................................23 3.14 Planted Area and Yield of Cassava by District ..............................................................................31 3.15 Area Planted per Cassava Growing Household..............................................................................31 3.16 Planted Area and Yield of Beans by District..................................................................................32 3.17 Area Planted per Beans Growing Household.................................................................................32 3.18 Planted Area and Yield of Simsim by District ...............................................................................33 3.19 Area Planted per Simsim Growing Household...............................................................................33 3.20 Area Planted per Tomatoes Growing Household...........................................................................34 3.21 Planted Area and Yield of Tomatoes by District............................................................................34 3.22 Planted Area and Yield of Pumpkins by District ...........................................................................35 3.23 Area Planted per Pumpkins Growing Household...........................................................................35 3.24 Planted Area and Yield of Onions by District................................................................................39 3.25 Area Planted per Onions Growing Household ...............................................................................39 3.26 Planted Area and Yield of Cashew nut by District.........................................................................40 3.27 Area Planted per Cashew nut Growing Household........................................................................40 3.28 Planted Area and Yield of Pegion Peas by District........................................................................42 3.29 Area Planted per Pegion Peas Growing Household .......................................................................42 3.30 Planted Area and Yield of Coconuts by District ............................................................................43 3.31 Area Planted per Coconuts Growing Household............................................................................43 3.32 Planted Area and Yield of Oranges by District..............................................................................44 3.33 Area Planted per Orange Growing Household...............................................................................44 3.34 Percent of households Storing Crops for 3 to 6 months By District ..............................................50 Number of households and Percent of Total household Selling Crops By District .......................50 3.36 Number of Households and Percent of Total Households Receiving Crop Extension Services by District...............................................................................................53 3.37 Number of Households and Percent of Crop Growing household 3.38 Using Improved seed by District....................................................................................................53 3.38 Number and Percent of Smallholder Planted Trees by District......................................................54 3.39 Number and Percent of households With water Harvesting Bunds by District.............................54 3.48 Number and Percent of households Practicing Fish farming .........................................................83 3.49 Number and Percent of households Without Toilets By District ...................................................83 3.50 Number and Percent of households Using Grass/Leaves for Roofing as material District............87 3.51 Number and Percent of Households Eating 3 meals Per day by District .......................................87 3.52 Number and Percent of Households Eating Meat once per week by District ................................88 3.53 Number and Percent of Households Eating Fish once per week by District..................................88 3.54 Number and Percent of Households Reporting Food Insufficiency...............................................89 3.42 Cattle population by District as of 1st Octobers 2003........................................................................ INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Lindi Region was established in 1971.The region comprises six districts namely Lindi Rural, Kilwa, Nachingwea, Liwale, Ruangwa and Lindi Urban. The regional headquarters is located in Lindi Urban District. Lindi region is situated in Southern Tanzania between latitudes 70 55’ and 100 50' South of the equator and longitudes 360 51’ to 400 East. Lindi shares borders with Coast region to the North, Indian Ocean to the East, Mtwara region to the South, Morogoro region to the West and Ruvuma region on the South-West. 1.3 Land Area The region has an area 67,000 square kilometers (7.56% of Tanzania Mainland’s area). About a quarter of the region (18,000 square kilometers) is part of the Selous Game Reserve. 1.4 Climate 1.4.1 Temperature The dominant climate is hot and humid. The normal temperature throughout the year is between 24.5 0C and 27 0C. However, air temperatures have a monthly mean ranging from 22.2 0C in Nachingwea in July to 27.70 C in Kilwa in March. Humidity averages 87% in Lindi Town in March and April. 1.4.2 Rainfall The region has one rainy season which is the long rainy (masika) from November/December to April/May. The annual rainfall ranges between 980 mm to 1,200 mm. 1.5 Population According to the 2002 Population and Housing Census, there were 791,306 inhabitants in Lindi region. District population was: Kilwa (171,850), Lindi Urban (41,549), Lindi Rural (215,764), Liwale (75,546), Nachingwea (162,081) and Ruangwa (124,516). In terms of population, Lindi region ranked 10th out of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 229,264 million with a per capita income of shillings 287,688. The region held 19th position among regions on GDP and contributed about 2.3 percent to the national GDP1 The region is famous for producing food crops. The main food crops produced in Lindi region include: maize, cassava, sorghum, paddy, and simsim. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Lindi region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,LINDI, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scott’s Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS 3.1 Introduction This part of the report presents the results of the census for Lindi region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys, results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.2 Household Characteristics 3.2.1 Type of Household The number of agricultural households in Lindi region was 153,173 out of which 138,034 (90.1%) were involved in growing crops only, 159 (0.1%) were rearing livestock only, and 14,981 (9.8%) were involved in crop production as well as livestock keeping. There were no pastoralists in Lindi Region (Chart 3.1). 3.2.2 Livelihood Activities/Source of Income The census results for Lindi region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off farm income, permanent crop farming, livestock keeping and fishing/hunting and gathering (Table 3.1). 3.2.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Lindi region was 112,618 (74% of the total regional agricultural households) whilst the female-headed households were 40,555 (26% of the total regional agricultural households). The mean age of household heads was 46 years (45 years for male heads and 48 years for female heads) (Chart 3.2). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestoc k Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 1 4 7 3 5 6 2 Lindi Rural 1 4 6 2 5 7 3 Nachingwea 1 2 5 4 6 7 3 Liwale 1 3 5 4 6 7 2 Ruangwa 1 3 5 4 6 7 2 Lindi Urban 1 3 5 2 6 7 4 Total 1 4 5 3 6 7 2 Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Chart 3.1 Agriculture Households by Type - LINDI Crops and Livestock 9.8% Livestock Only 0.1% Crops Only 90.1% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.2.4 Number and Age of Household Members Lindi region had a total rural agricultural population of 646,400 of which 308,426 (48%) were males and 337,974 (52%) were females. Whereas age group 0-14 constituted 40 percent of the total rural agricultural population, age group 15–64 (active population) was only 54 percent. Lindi region had an average household size of 4 with Kilwa and Liwale districts having the highest household size of 5 (Chart 3.3). 3.2.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Lindi region had a total literacy rate of 59 percent. The highest literacy rate was found in Nachingwea district (66%) followed by Lindi Urban district (64%), Liwale district and (63%), Ruangwa (59%). Kilwa and Lindi Rural districts had the lowest literacy rates of 57 and 54 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 64.7 percent. The literacy rate for the male heads was 73.2% while that of female head was 41.2%. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Liwale (73.4%) followed by Nachingwea (72.8%), Ruangwa (63.6%), Kilwa (62.8%), Lindi Rural (58.7%) and Lindi Urban (56.8%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - LINDI 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85+ Age Group Percen t Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 Nachingwea Lindi Urb Liwale Ruangwa Kilwa Lindi Rur District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Lindi 0.0 20.0 40.0 60.0 80.0 Kilwa Lindi Rur Nachingwea Liwale Ruangwa Lindi Urb District Percent Male Female Total Lindi Urban Ruangwa Lindi Rural Nachingwea 532 1 25 16 13 7 Liwale Kilwa 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Ruangwa Lindi Rural Lindi Urban 11,365 27,222 35,167 31,377 3,189 44,853 Liwale Kilwa Nachingwea 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.01 LINDI Total Number of Agricultural Households by District Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.02 LINDI Number of Agricultural Households Per Square Kilometer of Land by District 12 Lindi Urban Lindi Rural Ruangwa Nachingwea 98.9 100% 100% 99.8% 100% 99.5% Liwale Kilwa 99.78 to 100 99.56 to 99.78 99.34 to 99.56 99.12 to 99.34 98.9 to 99.12 Lindi Urban Nachingwea Ruangwa Lindi Rural 44,853 3,153 35,167 27,222 31,309 11,310 Liwale Kilwa 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.03 LINDI Number of Crop Growing Households by District Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.04 LINDI Percent of Crop Growing Households by District 13 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 5.4% 23.5% 12.9% 9.4% 8.2% 7.7% Liwale 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Lindi Urban Nachingwea Lindi Rural Ruangwa 526 16 13 1 7 25 Liwale Kilwa 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Map 3.05 LINDI Number of Crop Growing Households per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Crop Growing Households per Square Km Number of Crop Growing Households per Square Km Percent of Crop and Livestock Households Percent of Crop and Livestock Households Map 3.06 LINDI Percent of Crop and Livestock Households by District 14 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 Educational Status Information on educational status was collected from individual agricultural households. The results show that 40 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 24 percent were still attending school. Those who have never attended school were 36 percent (Chart 3.6). Agricultural households in Nachingwea district had the highest percentage (46.9%) of population aged 5 years and above who had completed different levels of education. This was followed by Liwale (41.6%), Ruangwa (41.0%), Lindi Rural (38.6%), Lindi Urban (38.1%) and Kilwa (34.5%). (Chart 3.7) The number of heads of agricultural households with formal education in Lindi region was 95,471 (62.3%), those without formal education were 57,702 (37.6%) and those with only adult education were 4,660 (3.0%). The majority of heads of agricultural households (60.3%) had primary level education whereas only 2.0 percent had post primary education. With regard to the heads of agricultural households with primary education in Lindi region, Nachingwea district had the highest percent (72%). This was followed by Liwale 66%, Ruangwa (61%), Kilwa (57%), and Lindi Urban (43%). The percent of household heads with secondary education was highest in Liwale district (3.2%) and lowest in Kilwa (1.1%). District where some household heads had post secondary education were Kilwa only (0.5%) and Lindi Urban (2.3%). (Chart 3.8) Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 40% Attending School 24% Never Attended 36% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 3.0% Post Primary Education 2.0% No Education 34.6% Primary Education 60.3% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 3.2.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from 73 percent of households having at least one member with off-farm income. Of the households with at least one member engaged in off farm income generating activities in Lindi region 79,211 households (71.2%) had only one member aged 5 years and above engaged in off-farm income generating activities, 22,672 households (20.4%) had two members involved in off-farm income generating activities and 9,345 households (8.4%) had more than two members involved in off-farm income generating activities. Lindi Rural district had the highest percentage of agriculture households with off-farm income (over 86 % of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Kilwa (78%), Nachingwea (76%) and Lindi Urban (67%). Ruangwa and Liwale districts had the lowest percent of agriculture households with off-farm income being 52% and 49% respectively. The district with the highest percent of agriculture households with more than one member with off-farm income was Kilwa (38%). Ruangwa district had very few households with more than one member having off-farm income (12%). (Chart 3.10) 3.3 Crop results 3.3.1 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban Districts Area/household 0 10 20 30 40 50 60 Percentage utilized Area utilised (Ha) Total Usable Area available (ha) Percent Utilisation Chart 3.9 Number of Household by Number of Members with Off-farm Income None, 41,945, 27% More than Two , 9,345, 6% Two , 22,672, 15% One , 79,211, 52% 27 Chart 3.9 Number of Households by Number of members with Off-farm Income Chart 3.10: Percentage Distribution of Households Members by Off - Farm Income Generating Activities and Districts 0% 20% 40% 60% 80% 100% Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban Districts % of Total number of Household Members One Off Farm Inco me Two Off Farm Inco me Mo re than Two Off Farm Inco me Chart 3.10 Percentage Distribution of Households by Members with Off-farm income generating Activities and District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 country; but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.3.1.1 Area of Land Utilised The total area of land available to smallholders was 339,483 ha. The regional average land area utilised for agriculture per household was 1.8 ha. This figure was slightly below the national average which is estimated at 2.0 hectares. Eighty eight percent of the total land available to smallholders was utilised. Only 12 percent of usable land available to smallholders was not used (Chart 3.11). Large differences in land area utilised per household exist between districts with Kilwa, Lindi Rural and Ruangwa utilizing 0.6 ha per household, followed by Nachingwea and Lindi Urban utilizing 0.5 ha per household. The smallest land area utilised per household was found in Liwale (0.3 ha). The percentage utilized of the usable land per household was highest in Kilwa (51%) and lowest in Liwale and Lindi Urban (17%). Twenty nine percent of the total land available to smallholders was utilised. Only 16 percent of usable land available to smallholders was not used (Chart 3.11). 3.3.1.2 Types of Land Use The area of land under temporary mixed crops was 96,883 hectares (28.52% of the total land available to smallholders in Lindi), followed by permanent/annual mix (79,704 ha, 23.48%), permanent mono crops (45,617 ha, 13.44%), temporary monocrops (36,448 ha, 10.74%), uncultivated usable land (35,758 ha, 10.53%), fallow (18,095 ha, 5.33%), permanent mixed crops (14,214 ha, 4.19%), unusable area (7,602 ha, 2.24%), area under natural bush (3,293 ha, 0.97%), area rented to others (1,783 ha, 0.53%), pasture (79, 0.02%) and area planted with trees (57 ha, 0.02%) (Chart 3.12) Chart 3.12 Land Area by Type of Use 0.0 0.0 0.5 1.0 2.2 4.2 5.3 10.5 10.7 13.4 28.5 23.5 0 50,000 100,000 150,000 Planted Trees Pasture Rented to Others Natural Bush Unusable Permanent Mixed Crops Fallow Uncultivated Usable Land Temporary Mono Crops Permanent Mono Crops Permanent / Annual Mix Temporary Mixed Crops Land Use Area (hectares) Chart 3.14 Area Planted with Annual Crops in Wet (rainy) Season by District 26.38 26.31 18.90 15.52 10.69 2.20 0 20,000 40,000 60,000 Lindi Rural Nachingwea Kilwa Ruangwa Liwale Lindi Urban Districts A rea P la n ted (h a ) 0.00 5.00 10.00 15.00 20.00 25.00 30.00 Area Planted % Area Planted in Wet Season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 195,785, 100% Short Rainy Season, 0, 0% Long Rainy Season Short Rainy Season INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 3.3.2 Annual Crops and Vegetable Production Lindi region has one (unimodal) rainy seasons, namely “masika” The rain (wet) season which starts from November/December to April/May. The quantity of crops produced in wet season will be used as a basis for comparison with the past surveys and censuses. 3.3.2.1 Area Planted The area planted with annual crops and vegetables was 195,785 hectares during the long rainy season. The average area planted per household during the long rainy seasons was 0.3 ha (Chart 3.13). There was not much difference between districts in the average area planted per household during the long rainy season. The districts with the largest area planted per household was Liwale (0.6 ha), followed by Kilwa, Nachingwea, Ruangwa and Lindi Urban (0.5 ha) Lindi Rural at 0.4ha had the smallest planted area per household (Chart 3.15). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2.2 Crop Importance Maize was the dominant annual crop grown in Lindi region and it had a planted area 1.5 times greater than cassava, which had the second largest planted area. The area planted with maize constituted 36.6 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) were cassava, sorghum, paddy, simsim, cowpeas, groundnuts and bambaranuts (Chart 3.16). Table 3.2: Area, Production and Yield of Cereal Crops (Long Rainy Season) Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 71,470 24,854 348 Paddy 15,703 5,180 330 Sorghum 34,872 9,768 280 Finger Millet 218 93 427 Bulrush millets 142 22 154 Barley 16 8 500 Total 122,431 39,925 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Liwale Lindi Urban Kilwa Nachingwea Ruangwa Lindi Rural Districts Average Area Planted per Household (ha) Average Area Planted per Household Chart 3.15 Area Planted with Annual Crops per Household by District Chart 3.15 Area Planted with Annual Crops per Household by District Chart 3.16 Planted Area (ha) for the Main Crops Lindi 0 20000 40000 60000 80000 Maize Cassava Sorghum Paddy Simsim Cowpeas Groundnuts Bambaranuts Crop Planted Area (ha) INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 19 Chart 3.17 shows the area planted per household growing selected crops. Planted area per household was larger for yams, maize, sorghum and groundnuts than for other crops (Chart 3.17). 3.3.2.3 Crop Types Cereals were the main crops grown in Lindi region. The area planted with cereals (maize, paddy and sorghum) was 122,420 ha (62.7% of the total planted area), followed roots and tubers 47,189 ha (24.1%), oil seeds and oil nuts, 18,700 (9.6%), pulses, 6.016 ha (3.1%), fruits and vegetables, 946 ha (0.5%). Annual cash crops had the least planted area of about 56 ha (0.0%) (Chart 3.18) 3.3.2.4 Cereal Crop Production The total production of cereals was 39,925 tonnes. Maize was the dominant cereal crop at 24,854 tonnes which was 62.3 percent of total cereal crops produced, followed by sorghum (24.5%), paddy (13%) and finger millet (0.2%). The total area planted with cereals during the long rainy seasons was 122,421 ha. All cereals were planted during the long rainy season (Table 3.2). The area planted with maize was dominant and it represented 58.4 percent of the total area planted with cereal crops, then followed by sorghum (28.5%), paddy (12.8%), finger millet (0.2%), bulrush millets (0.1%) and barley (0.0%). The yield of barley was 500 kg/ha followed by finger millet 426 kg/ha, maize 348 kg/ha, paddy 330 kg/ha, sorghum 280 kg/ha and bulrush millets 154 kg/ha. Wheat was not grown in the region (Chart 3.19). However small quantity of barley was produced in Kilwa District Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 100,000 200,000 300,000 Maize Sorghum Paddy Finger Millet Crop Area Planted (ha) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.18: Percentage Distribution of Area planted with Annual Crops by Crop Type Roots & Tubers 24.1% Pulses 3.1% Oil seeds & Oil nuts 9.6% Fruits & Vegetables 0.5% Cash crops 0.2% Cereals 62.5% Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Chart 3.20: Time Series Data on Maize Production - Lindi 50 61 26 50 24 27 38 0 25 50 75 94/95 95/96 96/97 97/98 98/99 99/00 2002/03 Census/Survey year P r o d u c tio n ('0 0 0 ') to n n e s Chart 3.17 Planted Area (ha) per Household by Selected Crop - LINDI 0.0 0.5 1.0 1.5 2.0 Yams Maize Sorghum Groundnuts Paddy Simsim Cowpeas Sweet Potatoes Tomatoes Bambaranuts Beans Crop Planted Area (ha) - Ruangwa Lindi Rural Lindi Urban 11,365ha 27,222ha 35,167ha 31,377ha 3,189ha 44,853ha Liwale Kilwa Nachingwea 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.09 LINDI Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Tanzania Agriculture Sample Census Area Planted with Cereal Crop Area Planted with Cereal Crop Percent of Total Land with Cereal Crop 62.2% 61.5% 64.7% 65.2% 61.8% 61.6% 21 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.4ha 0.4ha 0.6ha 0.5ha 0.7ha 0.8ha Liwale Kilwa 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Lindi Urban Lindi Rural Ruangwa Nachingwea 975ha 14,876ha 14,191ha 22,714ha 11,056ha 7,658ha 0.39t/ha 0.17t/ha 0.36t/ha 0.33t/ha 0.33t/ha 0.32t/ha Liwale Kilwa 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Map 3.10 LINDI Planted Area and Yield of Maize by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.11 LINDI Area Planted per Maize Growing Household by District Planted Area per Household 22 Lindi Urban Lindi Rural Nachingwea Kilwa Ruangwa 0.4ha 0.4ha 0.4ha 0.5ha 0.5ha 0.6ha Liwale Ruangwa Kilwa Lindi Urban Lindi Rural Nachingwea 5,108ha 6,937ha 4,273ha 10,850ha 1,066ha 6,638ha 0.28t/ha 0.29t/ha 0.24t/ha 0.33t/ha 0.19t/ha 0.23t/ha Liwale Map 3.12 LINDI Planted Area and Yield of Sorghum by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.13 LINDI Area Planted per Sorghum Growing Household by District Planted Area per Household 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 0.56 to 0.6 0.52 to 0.56 0.48 to 0.52 0.44 to 0.48 0.4 to 0.44 23 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 24 • Maize Maize dominated the production of cereal crops in the region. The number of households growing maize in Lindi region during the long rainy season was 128,506, (85% of the total crop growing households in the region during the long rainy season). The total production of maize was 24,854 tonnes from a planted area of 71,470 hectares resulting in a yield of 0.35 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tonnes). There was a sharp increase in maize production in 1996. Maize production remained the same over the period two year from 1998 to 1999 after which the production declined over the remaining period up to until 2003. The average area planted with maize per household was 0.56 hectares; however it ranged from 0.42 hectares in Lindi Rural district to 0.77 hectares in Liwale district. Nachingwea district had the largest area of maize (22,714 ha) followed by Lindi Rural (14,816 ha), Ruangwa (14,191 ha), Kilwa (11,056 ha), Liwale (7,658 ha) and Lindi Urban (975 ha) Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 8 years, the quantity produced increased and this has been due to a large increase in the area under production. The area planted with maize remained increased over the period from 1994/95 to 1998/99 after which it remained constant up to the year 2002/03. Overall the yield of maize declined over the period 1995/96 up to the year 2002/03 from 1.1t/ha in 1995 to 0.3 t/ha in 2003 (Chart 3.22). Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 22,714 14,876 14,191 11,056 7,658 975 0 5,000 10,000 15,000 20,000 25,000 NachingweaLindi Rural Ruangwa Kilwa Liwale Lindi Urban District Area (Ha) 0.00 0.20 0.40 0.60 0.80 Area Planted per Household Planted Area (ha) Planted Area per Hh Chart 3.22 Time Series of Maize Planted Area and Yield - Lindi - 20,000 40,000 60,000 80,000 94/95 95/96 96/97 97/98 98/99 99/00 2002/03 Agriculture Year Area (hectares) 0.0 0.3 0.6 0.9 1.2 Yield (t/ha) Area Yield INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 25 • Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Lindi region during the long rainy season was 76,620 which were 51 percent of the total crop growing households in Lindi region in the long rainy season. The total production of sorghum was 9,768 tonnes from a planted area of 34,872 hectares resulting in a yield of 0.28 t/ha. The district with the largest area planted with sorghum was Lindi Rural (10,850 ha) followed by Kilwa (6,937 ha), Nachingwea (6,638 ha), Ruangwa (5,108 ha), Liwale (4,273 ha) and Lindi Urban (1,066 ha). There were small insignificant variations in the average area planted per crop growing household among the districts ranging from 0.40 ha in Lindi Rural to 0.60 ha in Liwale (Chart 3.23). There was a sharp increase in the production of sorghum in 1996/97 compared to 1995/96. The production increased from 27,326 tons in 1995/96 to 83,703 tonnes in 1996/97 after which it dropped to 23,532 tonnes in 19997/98. Thereafter production increased gradually to 30,840 tonnes in 1999/2000 followed by decline in 2002/03 to 9,768 tonnes. Charts 3.24 and 3.25 show that, whilst the yield of sorghum has dropped dramatically over the previous 8 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with sorghum remained constant over the period from 1999 to 2000 after which the area under production dropped to 34,872 ha in 2002/03. Over the period 1995 to 1998 the yield of sorghum declined 1.3 t/ha to 0.4 t/ha respectively. In the following year the yield increased to 0.6 t/ha and the yield remained constant. In 2002/03 the yield dropped again to 0.3 t/ha (Chart 3.25). Chart 3.23 Sorghum: Total Area Planted and Planted Area per Household by District 10,850 6,937 6,638 5,108 4,273 1,066 0 3,000 6,000 9,000 12,000 Lindi Rural Kilwa Nachingwea Ruangwa Liwale Lindi Urban District Area (Ha) 0.00 0.20 0.40 0.60 0.80 Area Planted per Household Planted Area (ha) Planted per hh Chart 3.24: Time Series Data on Sorghum Production - Lindi 31 27 41 10 31 24 84 0 30 60 90 94/95 95/96 96/97 97/98 98/99 99/00 2002/03 Census/Survey year Production ('000') tonnes Chart 3.25 Time Series of Sorghum Planted Area and Yield - Lindi - 20,000 40,000 60,000 80,000 94/95 95/96 96/97 97/98 98/99 99/00 2002/03 Agriculture Year Area (hectares) 0.0 0.3 0.6 0.9 1.2 1.5 Yield (t/ha) Area Yield INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 26 • Other Cereals Other cereals that were produced in small quantities are paddy, finger millet, bulrush millet and barley. The district with the largest area planted with paddy was Lindi Rural (6,101 ha) followed by Kilwa (5,970 ha) and Nachingwea (2,183 ha). Other districts had smaller planted areas. Kilwa at 112 hectares had the largest area planted for finger millet. Other districts had insignificant planted areas of finger millet (Chart 3.26). 3.3.2.5 Roots and Tuber Crops Production The total production of roots and tubers was 26,040tonnes. Irish potatoes were not produced in the region. Cassava production was higher than any other root and tuber crop in the region with a total production of 25,814 tonnes representing 99.1 percent of the total root and tuber crops production. This was followed by sweet potatoes with 197 tonnes (0.76%), yams (24 tonnes, 0.09%) and cocoyam (5 tonnes, 0.02%) (Table 3.3 & chart 3.27). The area planted with cassava was larger than any other root and tuber crop and constituted 7.2 percent of the total area planted with annual crops and vegetables and accounted for 64.5 percent of the area planted with roots and tubers, followed by Irish potatoes (32.3%), sweet potatoes (2.3%), coco yams (0.6%) and yams (0.3%). There was a significant increase in area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potatoes and yams remained more or less constant. The total production of roots and tubers was estimated at 26,040 tonnes. Cassava with an estimate of 25,814 tonnes was the most important root and tuber crop. It accounted for 99.1 percent of the total roots and tubers production. Other roots and tuber crops were less important. Sweet potatoes were estimated at 197 tonnes (0.76%), yams 24 tonnes (0.09%) and cocoyam with 5 tonnes (0.02%). The estimated yield was highest for sweet potatoes (0.8 t/ha) and cassava (0.6 t/ha), followed by cocoyam (0.4 t/ha and yams (0.2 t/ha). Table 3.3 Area, Quantity Harvested and Yield of Root Crops Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 46,788 25,814 552 Sweet Potatoes 258 197 762 Yams 131 24 183 Cocoyam 13 5 412 TOTAL 47,189 26,040 Chart 3.27 Area Planted and Yield of other Root and Tuber Crops 0 50 100 150 200 250 300 Sweet Potatoes Yams Cocoyam Crop Area Planted (ha) 0 20 40 60 80 100 120 140 160 180 200 Yield (kg/ha) Yield (kg/ha) 0 1,500 3,000 4,500 6,000 7,500 Area (ha) Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Chart 3.26 Area Planted with Paddy and Finger Millet by District Paddy Burllush millet INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 • Cassava The number of households growing cassava in the region was 88,540. This represented 58 percent of the total crop growing households in the region. The total production of cassava during the census year was 25,814 tonnes from a planted area 46,788 hectares resulting in a yield of 0.6 t/ha. Previous censuses and surveys indicate that the area planted with cassava increased over the period 1996 to 1999. The area planted with cassava dropped from 52,162 ha in 1999 to 46,419 ha in 2003 (Chart 3.28). The area planted with cassava accounted for 24 percent of the total area planted with annual crops and vegetables in the census year. Lindi Rural district had the largest planted area for cassava (12,544 ha, 27% of the cassava planted area in the region), followed by Nachingwea (12,292 ha, 26%), Ruangwa (7,693 ha, 1%), Kilwa (7,566 ha, 16%), Liwale (4,563 ha, 10%) and Lindi Urban (1,829 ha, 4%). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Lindi Urban district (43-5%). This was followed by Ruangwa (25.4%), Lindi Rural (24.9%), Nachingwea (23.9%), Liwale (21.9%) and Kilwa (20.5%) (Chart 3.29) The average cassava planted area per cassava growing household was 0.53 hectares. However, there were small district variations. The area planted per cassava growing household was highest in Lindi Urban (0.84 ha). This was followed by Liwale (0.78 ha), Kilwa (0.71 ha), Lindi Rural (0.50 ha), Nachingwea (0.47 ha) and Ruangwa (0.43 ha) (Chart 3.30). • Sweet Potatoes The number of households growing Sweet potatoes in Lindi region was 1,026. This was 0.7 percent of the total crop growing households during the long rainy season. The total production of sweet potatoes during the census year was 197 tonnes from a planted area of 258 hectares resulting in a yield of 0.76t/ha. Chart 3.31 Sweet potatoes: Total Area Planted and Planted Area per Household by District 0 0 28 31 71 128 0 50 100 150 Kilwa Nachingwea Lindi Rur Liwale Ruangwa Lindi Urb District Area (Ha) 0.00 0.20 0.40 0.60 Area Planted per Household Area Planted Planted Area Per Hh Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 20,000 40,000 60,000 95/96 97/98 98/99 2002/03 Year Area (Ha) Cassava Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 26.4 26.3 18.9 15.5 10.7 2.2 0 6 12 18 24 30 Lindi RuralNachingwea Kilwa Ruangwa Liwale Lindi Urban District Percent of Total Area Planted 0.0 0.6 1.2 1.8 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.8 0.8 0.7 0.5 0.5 0.4 0.00 0.25 0.50 0.75 1.00 Area per Household Lindi Urban Liwale Kilwa Lindi Rural Nachingwea Ruangwa District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 Kilwa district had the largest planted area for sweet potatoes (128 ha, 50%), followed by Nachingwea (71 ha, 28%), Lindi Rural (31 ha, 12%) and Liwale (28 ha, 10%). Sweet potatoes were not grown in the other districts of Lindi region (Chart 3.31).Other root and tuber crops were of minor importance in terms of area planted compared to cassava and sweet potatoes. 3.3.2.6 Pulse Crops Production The total area planted with pulses was 6,016 hectares out of which 5,329 ha were planted with cowpeas (88 percent of the total area planted with pulses), followed by bambaranuts (396 ha, 7%), beans (165, 3%), green gram (73, 1%), pigeon peas (33, 1%) and field peas (20 ha, 0%). Mung beans and soya beans were not cultivated in the region. The total production of pulses was 1,057 tonnes. Cowpeas were the most cultivated crop producing 894 tonnes which accounted for 85 percent of the total pulse production. This was followed by bambaranuts (78 tonnes, 7%), beans (67 tonnes, 6, green gram (14 tonnes, 1.3%), pigeon peas and field peas each (8 tonnes, 0.2%). Beans had the highest yields of 406 kgs/ha. The yields of the rest of the pulses in kilograms per hectare were, bambaranuts 196 kg/ha, green gram 191 kgs/ha, cow peas 167 kg/ha, field peas 100 kg/ha and pigeon peas 60 kg/ha (Chart 3.32). • Cowpeas Cow peas dominated the production of pulse crops in the region. However, no time series data for establishing the production trend of cowpeas. In previous censuses, cowpeas were included in the pulse crops. The number of households growing cowpeas in Lindi region was 17,548. The total production of cowpeas in the region was 894 tonnes from a planted area of 5,329 hectares. . The district with the largest planted area for cowpeas was Lindi Rural distct (2,269 ha, 43% of the total area planted with cow peas) (Chart 3.33). However, the largest area planted with cow peas per household was in Lindi Urban district (0.36 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.30 ha. With exception of Lindi Urban, Kilwa and Nachingwea districts, the variations in area planted with cowpeas per household for the rest of the districts were small ranging from 0.30 ha in Lindi Rural to 0.23 ha in Ruangwa. Table 3.4: Area, Quantity Harvested and Yield of Pulses Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 . . Beans 165 67 406 Cowpeas 5,329 894 167 Green Gram 73 14 191 Pigeon Peas 33 2 60 Chich Peas 0 . . Bambaranuts 396 78 196 Field Peas 20 2 100 TOTAL 6016 1057 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 20,000 40,000 60,000 80,000 Beans Cowpeas Green Gram Mung Beans Field Peas Bambaranuts Chich Peas Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) 0.36 0.34 0.31 0.30 0.28 0.23 0.00 0.25 0.50 Area per Household Lindi Urban Kilwa Nachingwea Lindi Rural Liwale Ruangwa District Chart 3.34 Area Planted per Cowpeas Growing Household by District (Long Rainy Season Only) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 Lindi Rural Nachingwea Kilwa Liwale Ruangwa Lindi Urban District Percent of Land 0 10 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.33 Percentage of Cow peas Planted Area and Percent of Total Land with Cow peas by District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 • Green Gram Green grams were among the pulses grown in the region. There was no time series data to establish the green gram production trend. The number of households growing green grams in Lindi region was 271. The total production of green grams in the region was 14 tonnes from a planted area of 73 hectares. . The largest area planted with green gram in the region (38 ha, 51%) was in Ruangwa district (Chart 3.35) Also the largest area planted with green gram per household was in Ruangwa district (0.12 ha) (Chart 3.36). The average area planted per household in the region during the long rainy season was 0.26 ha. In other districts the average area planted per green grams growing household was insignificant. 3.3.2.7 Oil Seed Production The total production of oilseed crops was 6,784 tonnes from a planted area of 18,698 hectares, representing 9.6 percent of the total area planted with annual crops. Simsim was the most important oilseed crop with 13,956 ha (74.6% of the total area planted with oil seeds), followed by groundnuts (24.5%), soya beans (0.5%), castor seed (0.3%) and sunflower, 0.1% (Chart 3.37). Castor seed had the highest yield of 1,164 kg/ha, followed by sunflower (494 kg/ha). The yield of simsim and groundnuts were moderate at (368 kg/ha) and 339 kg/ha respectively. Soya beans had the lowest yield of 177 kg/ ha (Table 3.5) In terms of production, simsim was 5,142 tonnes and accounted for 76 percent of the total production of oil seeds, followed by groundnuts (23%), castor seed (1%), soya beans (0.2%) and sunflower (0.1%). • Simsim The number of households growing simsim in Lindi region was only 33,452. The total production of simsim in the region was 5,142 tonnes from a planted area of 13,956 hectares resulting in a yield of 0.37 t/ha. Thirty five percent (30.5%) of the area planted with simsim was located in Lindi Rural district (4262 ha) followed by Kilwa (3,406 ha, 24.4%), Ruangwa (2,257 ha, 16.2%), Nachingwea (2,097 ha, 15.0%), Liwale (1,836 ha, 13.2% and Lindi Urban (99 ha, 0.7%). Simsim were grown in all districts. The highest proportion of land with simsim was found in Lindi Rural (12%), followed by Nachingwea (10%), Kilwa (7%), Liwale (6%), Ruangwa (4%) and Lindi Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 10 5 494 Simsim 13,956 5,142 368 Groundnuts 4,579 1,551 339 Castor Seed 60 70 1,164 Soya Beans 93 16 177 Total 18,700 6,785 Chart 3.37 Area Planted and Yield of other Major Oil Seed Crops 0 10 20 30 40 50 60 70 80 90 100 Soya beans Castor Seed Groundnuts Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) 0 0.2 0.4 0.6 Area per Household (ha). Ruangwa Nachingwea Liwale Kilwa Lindi Rural Lindi Urban District Chart 3.36 Area Planted per Green GramGrowing Household by District (Long Rainy Season Only) INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 Chart 3.39 Percent of Simsim Planted Area and Percent of Total Land with simsim by District 30.5 24.4 16.2 15.0 13.2 0.7 0.0 7.0 14.0 21.0 28.0 35.0 Lindi Rur Kilwa Ruangwa Nachingwea Liwale Lindi Urb District Percent of Total Area Planted 0 3 6 9 12 15 Percent Area Planted of Total Land Area % 0f Simsim Proportion Chart 3.38 Percent of Simsim Planted Area and Percent of Total Land with Simsim by District Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 100 200 300 400 500 Tomatoes Cabbage Egg Plant Chillies Water Mellon Cucumber Others Crop A rea Plan ted (h a) 0 1000 2000 3000 4000 5000 6000 7000 Y ield (k g/h a) Chart 3.40 Area Planted and Yield of Fruits and Urban district (2%). (Chart 3.38) The largest area planted per simsim growing household was found in Liwale district (0.63 ha) and the lowest was in Lindi Urban (0.28). (Chart 3.39) 3.3.2.8 Fruits and Vegetables The collection of fruits and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short dry season is relatively important for fruits and vegetables production. Reliable historical data for time series analysis of fruits and vegetables were not available. The total production of fruits and vegetables was 3,160 tonnes. The most cultivated fruit and vegetable crop was the tomato with a production of 2,177 tonnes (69% of the total fruits and vegetables produced) followed by onions (405t, 13%), okra (278t, 9%) and pumpkins (262t, 8%). The production of the other fruits and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 6,202 kg/ha, okra (4,088 kg/ha), onions (2,120 kg/ha) and pumpkins (996 kg/ha), water melon (1111kg/ha), egg plant (750kg/ha) amaranths (170kgha) and cucumber (76kg/ha) (Chart 3.40). • Tomatoes The number of households growing tomatoes in the region during the long rainy season was 1,409. This represented 0.9 percent of the total crop growing households in the region during the long rainy season Table 3.6: Area, Quantity Harvested and Yield of Fruits and Vegetables Wet Season Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tomatoes 351 2,177 6,202 Pumpkins 263 262 996 Onions 191 405 2,120 Okra 68 278 4,088 Amaranths 47 8 170 Water Mellon 18 20 1,111 Cucumber 13 1 76 Egg Plant 12 9 750 Total 946 3,160 0.63 0.49 0.45 0.32 0.31 0.28 0.00 0.25 0.50 0.75 Area per Household Liwale Kilwa Lindi Rur Ruangwa Nachingwea Lindi Urb District Chart 3.40 Area Planted per Simsim Growing Household by District (Long Rainy Season Only) Chart 3.39 Area Planted per Simsim Growing Household by District (Long Rainy Season Only) Kilwa Ruangwa Lindi Urban Lindi Rural Nachingwea 7,566ha 12,845ha 1,829ha 7,693ha 12,292ha 4,563ha 1.1t/ha 0.4t/ha 0.3t/ha 0.4t/ha 0.5t/ha 0.5t/ha Liwale 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.8ha 0.5ha 0.7ha 0.4ha 0.5ha 0.8ha Liwale Kilwa 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Map 3.14 LINDI Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.15 LINDI Area Planted per Cassava Growing Household by District Planted Area per Household 31 Lindi Urban Lindi Rural Ruangwa Nachingwea 97ha 2,269ha 224ha 1,483ha 759ha 496ha 0.03t/ha 0.18t/ha 0.12t/ha 0.15t/ha 0.15t/ha 0.24t/ha Liwale Kilwa 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.36ha 0.3ha 0.23ha 0.31ha 0.34ha 0.28ha Liwale Kilwa 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Map 3.16 LINDI Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.17 LINDI Area Planted per Beans Growing Household by District Planted Area per Household 32 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 0.28ha 0.31ha 0.32ha 0.49ha 0.45ha 0.63ha Liwale 0.56 to 0.63 0.49 to 0.56 0.42 to 0.49 0.35 to 0.42 0.28 to 0.35 Lindi Urban Lindi Rural Ruangwa Nachingwea 99ha 2,097ha 2,257ha 4,262ha 3,406ha 1,836ha 0.3t/ha 0.2t/ha 0.4t/ha 0.3t/ha 0.4t/ha 0.6t/ha Liwale Kilwa 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.18 LINDI Planted Area and Yield of Simsim by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.19 LINDI Area Planted per Simsim Growing Household by District Planted Area per Household 33 Lindi Urban Lindi Rural Ruangwa Nachingwea 0ha 0.23ha 0.1ha 0.19ha 0.61 0.5ha Liwale Kilwa 0.48 to 0.61 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Kilwa Lindi Urban Lindi Rural Ruangwa Nachingwea 7ha 0ha 158ha 90ha 53ha 43ha 0.1t/ha 0t/ha 8.3t/ha 6.6t/ha 4.4t/ha 0.8t/ha Liwale 120 to 160 90 to 120 60 to 90 30 to 60 0 to 30 Map 3.20 LINDI Planted Area and Yield of Tomatoes by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.21 LINDI Area Planted per Tomatoes Growing Household by District Planted Area per Household 34 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.27ha 0.11ha 0ha 0ha 0.1ha 0.47ha Liwale Kilwa 0.36 to 0.47 0.27 to 0.36 0.18 to 0.27 0.09 to 0.18 0 to 0.09 Lindi Urban Lindi Rural Ruangwa Nachingwea 40ha 196ha 9ha 0ha 18ha 0ha 0.6t/ha 1t/ha 0t/ha 0t/ha 2.7t/ha 0t/ha Liwale Kilwa 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Map 3.22 LINDI Planted Area and Yield of Pampkins by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.23 LINDI Area Planted per Pampkins Growing Household by District Planted Area per Household 35 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 Area per Household (ha). Nachingwea Liwale Lindi Rural Ruangwa Kilwa District Chart 3.44 Area Planted per Tomato Growing Household by District Chart 3.42 Area Planted per Tomato Growing Household by District Lindi Rural district had the largest planted area of tomatoes (49.1% of the total area planted with tomatoes in the region), followed by Ruangwa (33.5%), Nachingwea (6.2%), Liwale (6.1%) and Kilwa (5.1%). There were no tomatoes grown in Lindi Urban District. The highest percentage of land with tomatoes was found in Lindi Rural, followed by Ruangwa district. With exception of Lindi Rural district (45%) and Ruangwa (26%), the rest of the districts had relatively low percentage of land used for tomato production (Chart 3.43). Kilwa had the lowest percentage of land used for tomatoes production (2%) (Chart 3.41) The largest area planted per tomato growing household was found in Nachingwea (0.61 ha) followed by Liwale (0.5 ha), Lindi Rural (0.23 ha), Ruangwa (0.19 ha) and Kilwa (0.1 ha). (Chart 3.42) The total area planted with tomatoes accounted for 0.18 percent of the total area planted with annual crops and vegetables (Chart 3.42). . • Pumpkins The number of households growing pumpkins in the region during the long rainy season was 2,048. This represented 1.4 percent of the total annual crop growing households in the region in the wet season. Lindi Rural district had the largest planted area of pumpkins (196 ha, 74.5% of the total area planted with pumpkins in the region), followed by Liwale (40 ha, 15.2%), Nachingwea (18 ha, 6.8%) and Lindi Urban (9 ha, 3.4%). There were no pumpkins planted in both Kilwa and Ruangwa Districts (Chart 3.43). The total area planted with pumpkins accounted for 0.13 percent of the total area planted with annual crops and vegetables during the wet season. Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Lindi Rural Ruangwa Nachingwea Liwale Kilwa District Percent of Land 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 Percent Area Planted of Total Land Area Series2 Series1 Chart 3.41 Percent of Tomato Planted Area and Percent Chart 3.45 Percent of Amaranths Planted, Area and Percent of Total Land with Pumpkins by District 0.0 25.0 50.0 75.0 100.0 Lindi Rural Liwale Nachingwea Lindi Urban District Percen t of L an d 0.000 0.020 0.040 0.060 0.080 0.100 0.120 Percen t A rea Plan ted of T otal L an d A rea Percent of Land Proportion of Land Chart 3.43 Percent of Pumpkins Planted, Area and Percent of Total Land with Pumpkins b District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 37 • Onions The number of households growing onions in the region was 1,172 households. This represented 0.29 percent of the total annual crop growing households in the region. Ruangwa district had the largest planted area of onions (107 ha, 56.0% of the total area planted with onions in the region), followed by Liwale (31 ha, 16.3%), Lindi Rural (27 ha, 14.1%), Nachingwea (18ha, 9.4%) and Kilwa (8 ha, 4.2%) districts. Onions were not produced in Lindi Urban district. The largest proportion of the area planted with onions was found in Ruangwa district (0.055%), followed by Liwale (0.016%), Lindi Rural (0.014%). Kilwa had the smallest proportion (0.004%) of area planted with onions. There was no onion planted in Lindi Urban district. (Chart 3.44) The total area planted with onions accounted for 0.1 percent of the total area planted with annual crops and vegetables during the long rainy season. 3.3.2.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 56 ha was planted with cash crops during the wet season. Tobacco was the most prominent (75%) and was grown in Lindi Rural district, followed by jute 23.7% grown in Lindi Rural and Kilwa district. (Chart 3.45) • Tobacco The quantity of tobacco produced was 21 tonnes. Tobacco had a planted area of 42 ha; all of them were planted in Lindi Rural district during wet season. 3.3.3 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than Chart 3.46 Percent of Onions Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 Kilwa Nachingwea Liwale Lindi Rural Ruangwa District Percent of Land 0.000 0.010 0.020 0.030 0.040 0.050 0.060 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.44: Char 3.44 Percent of Onoins Planted Area and Percent of Total Land with Onions by District Chart 3.47 Area planted with Annual Cash Crops Jute, 27.7% Tobacco, 75.3% Chart 3 45 Chart 3.45 Area Planted with Annual Cash Crops Chart 3.50 Area Planted with the Main Perennial Crops Sugarcane, 56, 0% Pigeon Pea, 14,142, 17% Avocado, 11, 0% Guava, 19, 0% Mango, 4,268, 7% Cashewnut, 55,683, 68% Banana, 437, 1% Orange, 1,869, 2% Coconut, 8,381, 10% Chart 3.47: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 82,503 hectares (30% of the area planted with annual in the region). However, the area planted with annual crops was not the actual physical land area as it included the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops is higher than indicated in Chart 3.47. The most important permanent crop in Lindi region was cashew nuts which had a planted area of 55,683 ha, (67.5% of the planted area of all permanent crops) followed by pigeon peas (14,142 ha, 17.1%), coconut (8,381 ha, 10.2%), orange (1,869 ha, 2.3%), mango (1,830 ha, 2.2%), banana (437 ha, 0.53%), sugarcane (56 ha, 0.07%), guava (19 ha, 0.02%) and avocado (11 ha, 0.01). Each of the remaining permanent crops together, had a area of (75 ha, 0.09%) (Chart 3.47) Nachingwea district had the largest area under smallholder permanent crops (23,005 ha, 27.9%). This was followed by Ruangwa (17,053 ha, 20.7%), Lindi Rural (15,550 ha, 18.8%), Kilwa (13,948 ha, 16.9%), Liwale (11.953 ha, 14.5%), and Lindi Urban (993 ha, 1.2%). However, Ruangwa had the largest area per permanent crop growing household (1.7 ha) followed by Lindi Rural (0.7 ha), Liwale (1.0 ha), Nachingwea and Kilwa had (4.5 ha), and Lindi Urban (0.2 ha) (Chart 3.48). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Ruangwa district had the highest percent (35%) followed by Lindi Rural (22%), Kilwa (14%) and Liwale (10%). Lindi Urban and Nachingwea had (7%) each. 3.3.3.1 Cashewnuts Cashewnut was the first most important permanent crop in Lindi region. The total production of cashew nuts by smallholders was 13,521 tonnes. In terms of area planted, cashew nut was the first most important permanent crop grown by smallholders in the region. It was grown by 40,155 households (26% of the total crop growing households). The average area planted with cashew nuts per household was relatively higher at around 1.39 ha per cashew nut growing household and the average yield obtained by smallholders was 346 kg /ha from a harvested area of 39,062 hectares. Nachingwea had the largest planted area for cashewnuts in the region (13,521 ha, 24.3%) followed by Ruangwa (13,403 ha, 24.1%), Lindi Rural (12,404 ha, 22.3%), Liwale (10,807 ha, 19.4%), Kilwa (5,304 ha, 9.5%) and Lindi Urban (243 ha, 0.4%). However, the average planted area per cashewnut growing household was largest in Lindi Urban (17.16 ha), Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 20.7 18.8 16.9 14.5 1.2 27.9 0.0 20.0 40.0 Nachingwea Ruangwa Lindi Rural Kilwa Liwale Lindi Urban District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.48: Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 0ha 0.1ha 0.1ha 0.1ha 0.2ha 0.5hah Liwale 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Lindi Urban Lindi Rural Ruangwa Nachingwea Kilwa 0ha 27ha 107ha 18ha 8ha 31ha 0t/ha 0.1t/ha 2.8t/ha 4t/ha 2.8t/ha 0.4t/ha Liwale 80 > 60 to 80 40 to 60 20 to 40 0 to 20 Map 3.24 LINDI Planted Area and Yield of Onions by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.25 LINDI Area Planted per Onions Growing Household by District Planted Area per Household 39 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.61ha 0.99ha 0.77ha 0.67ha 0.61ha 0.81ha Liwale Kilwa 0.93 > 0.85 to 0.93 0.77 to 0.85 0.69 to 0.77 0.61 to 0.69 Lindi Urban Lindi Rural Ruangwa Nachingwea Kilwa Liwale 243ha 12,404ha 13,403ha 13,521ha 5,304ha 10,807ha 1,435t/ha 206t/ha 263t/ha 416t/ha 927t/ha 273t/ha 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Map 3.26 LINDI Planted Area and Yield of Cashewnuts by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.27 LINDI Area Planted per Cashewnuts Growing Household by District Planted Area per Household 40 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 followed by Kilwa (8.72 ha), Lindi Rural (5.76 ha), Nachingwea (4.07 ha), Ruangwa (3.90 ha) and Liwale (3.30 ha). (Chart 3.49) 3.3.3.2 Pigeon Peas The total production of pigeon peas by smallholders was 2,308 tonnes. In terms of area planted, the pigeon pea was the second most important permanent crop grown by smallholders in the region. It was grown by 25,995 households (17% of the total crop growing households). The average area planted with pigeon peas per pigeon peas growing 0.54 ha. The average yield obtained by smallholders was 394 kg/ha from a harvest area of 5,849 hectares. Nachingwea had the largest planted area for pigeon peas in the region (9,012 ha, 63.7%) followed by Ruangwa (3,095 ha, 21.9%), Lindi Rural (1,217 ha, 8.6%), Kilwa (635 ha, 4.5%), Liwale (143 ha, 1%) and Lindi Urban (39 ha, 0.3%). However, the average area planted with pigeon peas per pigeon peas growing household was highest in Nachingwea (0.8 ha) followed by Kilwa (0.6 ha), Ruangwa (0.4 ha). Lindi Rural, Lindi Urban and Liwale, each had an average planted area of 0.3 ha per pigeon peas growing household (Chart 3.50). 3.3.3.3 Coconut The total production of coconuts by smallholders was 19,498 tonnes. In terms of area planted, coconut was the third most important permanent crop grown by smallholders in the region. They were grown by 10,736 households (7.0% of the total crop growing households). The average area planted with coconuts per coconut growing household was around 0.78 ha. The average yield obtained by smallholders was 2,147 kg/ha from a harvested area of 9,078 hectares. Lindi Rural district had the highest yield of 3,300 kg/ha, followed by Kilwa (2,026 kg/ha), Ruangwa (950 kg/ha), Lindi Urban (877 kg/ha), Liwale (330 kg/ha) and Nachingwea (31 kg/ha). Kilwa had the largest planted area of coconuts in the region (5,541 ha, 66%) followed by Lindi Rural (1,756 ha, 21%), Lindi Urban (680 ha, 8%), Liwale (293 ha, 3.5%), Ruangwa (109 ha, 1.3%) and Nachingwea (72.4 ha, 0.02%). However, the average area planted with coconuts per coconut growing household was largest in Lindi Urban (1.75 ha) followed by Liwale (1.04 ha), Kilwa (0.81 ha), Lindi Rural (0.6 ha), Ruangwa (0.54 ha) and Nachingwea (0.02 ha) Chart 3.52 Percent of Area Planted with Pigeon peas and AveragePlanted Area per Household by District 11.8 0.2 0.1 13.5 2.8 23.6 0.0 5.0 10.0 15.0 20.0 25.0 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 Average planted area per household % of total area planted Average planted Area per household Chart 3.50: Chart 3.55 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.12 6.35 2.71 6.92 5.53 6.86 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 Nachingwea Ruangwa Lindi Rural Liwale Kilwa Lindi Urban District % of Total Area Planted 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.49: Lindi Urban Lindi Rural Ruangwa Nachingwea 1.11ha 0.59ha 1.02ha 0.73ha 0.27ha 0.53ha Liwale Kilwa 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 Lindi Urban Lindi Rural Ruangwa Nachingwea Kilwa 1,217ha 39ha 3,095ha 9,012ha 143ha 625ha 360t/ha 491t/ha 326t/ha 427t/ha 501t/ha 497t/ha Liwale 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Map 3.28 LINDI Planted Area and Yield of Pegion Peas by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.29 LINDI Area Planted per Pegion Peas Growing Household by District Planted Area per Household 42 Lindi Urban Lindi Rural Ruangwa Nachingwea 0.8ha 1ha 1.2ha 0.5ha 17.9ha 0.8ha Liwale Kilwa 14.5 to 18 11 to 14.5 7.5 to 11 4 to 7.5 0.5 to 4 Lindi Urban Lindi Rural Ruangwa Nachingwea 680ha 1,756ha 109ha 2ha 5,541ha 293ha 877t/ha 3,300t/ha 950t/ha 19t/ha 2,026t/ha 330t/ha Liwale Kilwa 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.30 LINDI Planted Area and Yield of Coconuts by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.31 LINDI Area Planted per Coconuts Growing Household by District Planted Area per Household 43 Lindi Urban Lindi Rural Ruangwa Nachingwea 0ha 0.81ha 1.9haha 0.18ha 1.41ha 0.45ha Liwale Kilwa 1.52 to 1.9 1.14 to 1.52 0.76 to 1.14 0.38 to 0.76 0 to 0.38 Lindi Urban Lindi Rural Ruangwa Nachingwea 1,4hhhhhha37 0ha 79ha 306ha 25ha 22ha 0t/ha 3,625t/ha 13,086t/ha 5,150t/ha 3,869t/ha 20,536t/ha Liwale Kilwa 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Map 3.32 LINDI Planted Area and Yield of Oranges by District Tanzania Agriculture Sample Census Planted Area Planted Area (ha) Planted Area per Household Yield (t/ha) Map 3.33 LINDI Area Planted per Oranges Growing Household by District Planted Area per Household 44 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 Chart 3.51 Number of Households by Method of Land Clearing during the Long Rainy Season 31,824 4,539 1,129 0 0 110,817 0 20,000 40,000 60,000 80,000 100,000 120,000 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart. 3.51b 3.3.3.4 Oranges The total production of oranges by smallholders was 11,880 tonnes. In terms of area planted, orange was the fourth most important permanent crop grown by smallholders in the region. It was grown by 4,256 households (3% of the total crop growing households). The average area planted with oranges per orange growing household was 0.41 ha. The average yield obtained by smallholders was 4,113 kg/ha (4 tonnes per hectare) from a harvested area of 2,888 hectares. Kilwa had the largest planted area for oranges in the region (1,437 ha, 76.9%) followed by Ruangwa (306 ha, 16.4%), Lindi Rural (79 ha, 4.2%), Nachingwea (25 ha, 1.3%) and Liwale (22 ha, 1.2%). There was no orange production in Lindi Urban district. However, the average area planted with oranges per orange going household was largest in Ruangwa (1.5 ha) followed by Kilwa (.0.5 ha). Lindi Rural and Liwale district had 0.2 ha each, and Nachingwea (0.1 ha) (Chart 3.51a). 3.3.4 Inputs/Implements Use 3.3.4.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which had been left fallow for a long period while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing was the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 141,080 ha which represented 73.5 percent of the total planted area, followed by bush clearance (44,723 ha, 23.3%), burning (4,828, 2.5%) and no land clearing (1,265 ha, 0.7%)). Tractor slashing was not practiced by small holders in the region (Table3.8) (Chart 3.51b) 3.3.4.3 Methods of Soil Preparation Hand cultivation was the most method for soil preparation and was used in an area of 187,334 ha which represented 96 percent of the total planted area planted with annual crops, followed by ox-ploughing (5,531 ha, 3%) and tractor ploughing (2,142 ha, 1%). Compared to other districts, Ruangwa district the largest area prepared by tractor being 1,234 ha (57% of total land prepared by tractor in the region). (Chart 3.52) Table 3.7: Land Clearing Methods Method of Land Clearing Number of Households Area Planted % Mostly Hand Slashing 110,817 141,080 73.5 No Land Clearing 1,129 1,265 0.7 Mostly Bush Clearance 31,824 44,723 23.3 Mostly Burning 4,539 4,828 2.5 Mostly Tractor Slashing 0 0 0.0 Other 0 0 0.0 Total 148,309 191,897 100.0 Chart 3.52 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 3509.1, 1% Mostly Hand Hoe Ploughing, 562,002, 96% Mostly Oxen Ploughing, 16,592, 3% Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 4.2 1.3 16.4 1.2 3.9 0.0 5.0 10.0 15.0 20.0 Ruangwa Lindi Rural Kilwa Nachingwea Liwale District % of Total Area Planted 0.00 0.40 0.80 1.20 1.60 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51a: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 46 In Lindi region, Lindi Rural district had the largest planted area cultivated with oxen (2,227 hectares, 40.3%) followed by Nachingwea (1,169 ha, 21.1%), Ruangwa (1,086 ha, 19.6%), Kilwa (427 ha, 7.7%), Liwale (419 ha, 7.6%) and Lindi Urban (202 ha, 3.7%). (Chart 3.53) During the wet season, 62.7 percent of the total area cultivated by using oxen was planted with cereals. 3.3.4.3 Improved Seeds Use The planted area using improved seeds was estimated at 15,930 ha which represents 8.2percent of the total area planted with the annual crops and vegetables area. (Chart 3.54) Cereals had the largest area planted with improved seeds (9,590 ha, 60.2% of the planted area with improved seeds) followed by and oil seed and oil nuts (2,673 ha, 16.8%), rots and tubers (2,614 ha, 16.4%), pulses (592, 2.9%) and fruits and vegetables (62 ha, 2.9%). Other crops were planted without improved seeds (Chart 3.55). However, the use of improved seed in fruits and vegetables was much greater than in other crop types (46%), followed by oilseeds (14%), pulses (10%), cereals (8%) and cassava (6%). (Chart 3.56) Chart 3.59 Planted Area of Improved Seeds - LINDI With Improved Seeds, 15,930, 8% Without Improved Seeds, 179,076, 92% Chart 3.54: 0 10,000 20,000 30,000 40,000 50,000 60,000 Area Cultivated Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Chart 3.58 Area Cultivated by Method of Cultivation and District Area Cultivated by Oxen Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.53: 0 20 40 60 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals Chart 3.56: Chart 3.60 Planted Area with Improved Seed by Crop Type - LINDI Cassava, 2,614, 16% Pulses, 592, 4% Oilseeds and Oil nuts, 2,673, 17% Fruits & Vegetables, 462, 3% Cereals, 9,590, 60% Chart 3.55: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 3.3.4.4 Fertilizer Use The use of fertilisers on annual crops was very small only on a planted area of 6,312 ha (3.2% of the total area planted with annual crops in the region). The area planted without fertiliser use for annual crops was 189,063 hectares representing 96.8 percent of the total area planted with annual crops. Of the planted area with fertiliser application, compost was applied to 3,325 ha which represented 2 percent of the total area planted with annual crops. This was followed by farm yard manure, applied to 1,538 ha which represents 0.8 percent. Inorganic fertilizers were used on a very small area and represented only 0.5 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Kilwa district (31%), followed by Lindi Rural (21%), Ruangwa (20%), Liwale (16%), Nachingwea (10%) and Lindi Urban (3%). There were no area planted with organic fertilizers in Nachingwea and Lindi Urban Districts. (Table 3.9, Charts 3.57 and Chart 3.58) Most annual crop growing households did not use any fertiliser (approximately 189,063 households, 96.8%). The percentage of planted area applied fertilizers was highest in Nachingwea and Lindi Rural district. There was no inorganic fertilizer and compost manure application in planted areas in Lindi Urban district. (Table 3.10) Table 3.8 Planted Area by Type of Fertilizer Use and District in Wet (Masika) Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizers Total No Fertilizers Applied Kilwa 667 1,259 39 1,965 34,964 Lindi Rural 226 942 156 1,324 50,220 Nachingwea 195 478 0 673 50,728 Liwale 46 880 99 1,024 19,852 Ruangwa 233 258 766 1,258 29,066 Lindi Urban 173 . 0 173 4,129 Total 1,538 3,819 1,060 6,416 188,959 Table 3.9 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 384 667 1,025 1,259 75 39 28,312 34,964 29,796 36,929 Lindi Rural 199 226 509 942 192 156 43,852 50,220 44,753 51,544 Nachingwea 175 195 519 478 0 . 34,473 50,728 35,167 51,402 Liwale 57 46 396 880 83 99 10,665 19,852 11,201 20,876 Ruangwa 131 233 330 258 405 766 26,288 29,066 27,154 30,324 Lindi Urban 168 173 0 . 0 . 2,985 4,129 3,153 4,301 Total 1,114 1,538 2,779 3,819 756 1,060 146,576 188,959 151,224 195,375 Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 1,538, 1% No Fertilizer Applied, 188,959, 96% Mostly Compost, 3,819, 2% Mostly Inorganic Fertilizer, 1,060, 1% Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Chart 3.57: Area of Fertiliser Application by Type of Fertiliser 0 10,000 20,000 30,000 40,000 50,000 60,000 Area (ha) District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Inorganic Fertilizer Mostly Compost Mostly Farm Yard Manure Chart 3.58: 0 10,000 20,000 30,000 40,000 50,000 60,000 Area (ha) District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Inorganic Fertilizer Mostly Compost Mostly Farm Yard Manure Chart 3.58: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 • Farm Yard Manure Use The total planted area applied with farm yard manure in Lindi region was 2,204 ha, representing 1.13 percent of the total area planted with annual crops during the wet season. The number of households that applied farm yard manure in their annual crops during the wet season was 1,914 (Table 3.10). Pulses had the highest percent of the total area planted with applied farm yard manure (61%), followed by cereals (34%), roots and tubers (4%), oil and oil seeds (1%) and in fruit and vegetables the use of farm yard manure was very small. (Chart 3.59) Farm yard manure was mostly used in Kilwa (43% of the total planted area in the district), followed by Lindi Rural and Ruangwa (15%), Nachingwea (13%), Lindi Urban (11%) and Liwale (3%) (Chart 3.61) Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - LINDI 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Nachingwea Lindi Urban Kilwa Lindi Rural Ruangwa Liwale District Percent Chart 3.61: 0.0 0.5 1.0 1.5 2.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.60: Percentage of Crop Type Planted Area with Farm Yard Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - LINDI Fruits & Vegetables, 288,37% Cereals, 461, 59% Roots & Tubers, 34, 4% Chart 3.62: Planted Area wiyh Inorganic Fertiliser by Crop Type - 0.0 15.0 30.0 45.0 60.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.67a Percentage of Planted Area with Inorganic fertilizers by Crop Type- Lindi Chart 3.63: Percentage of Planted Area with Inorganic Fertilisers by Crop Type - Lindi Chart 3.59 Planted Area Applied with Farm Yard Manure by Crop Type - Lindi Cereals, 1864, 34% Fruits & Vegetables, 25, 0% Roots & Tubers, 220, 4% Pulses, 3407, 61% Oil seeds & Oil nuts, 37, 1% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 • Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Lindi region was 783 ha which represents 0.40 percent of the total area planted with annuals in the region and 12.4 percent of the total area applied with fertilisers. The number of households that applied inorganic fertilizers on their annual crops during the wet season was 6,820 (Table 3.10). The largest area applied with inorganic fertilizers was for cereals (59% of the total area applied with inorganic fertilizers), followed by fruit and vegetables (37%) and roots and tubers (4%). (Chart 3.62) However, the proportion of fruit and vegetables with inorganic fertilizers was 28.9 percent higher than other crop types, followed by cereals (0.4%) and roots and tubers (0.1%). Inorganic fertilizers were not applied in pulses, cash crops, oil seeds and nut (Chart 3.63). Inorganic fertilisers were mostly used in Liwale (1.63% of the total planted area in the district), followed by Ruangwa (0.63%), Lindi Rural district (0.25%), Nachingwea (0.20%) and Kilwa (0.06%). Lindi Urban district not use any inorganic fertilisers (Chart 3.64). In permanent crops inorganic fertilisers were mainly used in pigeon peas (463 ha). • Compost Use The total planted area applied with compost was 3,325 ha which represented only 1.7 percent of the total area planted with annual crops in the region and 52.7 percent of the total planted area applied with fertiliser in the region. The number of households that applied compost manure on their annual crops during the wet season was 3,092 (Table 3.10 and Chart 3.65). The proportion of area applied with compost was very low for each type of crop (0 to 4%); however the distribution of the total area using compost manure shows that 55 percent of this area was cultivated with cereals, followed by roots & tubers (39%), oil seeds and nuts (6%), and pulses (2 (Chart 3.66). Chart 3.68a Planted Area with Compost by Crop Type - LINDI Roots & Tubers, 1,285, 39% Cereals, 1,764, 53% Pulses, 63, 2% Oilseeds and Oil nuts, 213, 6% Chart 3.65: Planted Area with Compost by Crop Type - Lindi 0 5 10 15 20 25 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds and Oil nuts Crop Type Chart 3.69b Percentage of Planted Area with Compost by Crop Type- LINDI Chart 3.66: Proportion of Planted AreaApplied with Compost by Crop Type - Lindi Chart 3.68c Proportion of Planted Area Applied with Compost by District - LINDI -0.5 0.5 1.5 2.5 Nachingwea Lindi Urban Kilwa Lindi Rural Ruangwa Liwale District Percent Chart 3.67: Proportion of Planted Area with Compost by District - Lindi Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertilizers by District - Lindi 0.00 0.50 1.00 1.50 2.00 Liwale Ruangwa Lindi Rural Nachingwea Kilwa Lindi Urban District Percent Chart 3.64: Proportion of Planted Area Applied with Inorganic Fertilisers by District - Lindi Kilwa Lindi Urban Lindi Rural Ruangwa Nachingwea 9,801 23,300 1,429 28,778 18,466 26,221 86% 74% 45% 64% 68% 75% Liwale 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Lindi Urban Lindi Rural Nachingwea Ruangwa 33% 55% 51% 56% 50% 34% Liwale Kilwa 51.4 to 56 46.8 to 51.4 42.2 to 46.8 37.6 to 42.2 33 to 37.6 Map 3.34 LINDI Percent of Households Storing Crops for 3 to 6 Months by District Tanzania Agriculture Sample Census Percent of Households Storing Crops Percent of Households Storing Crops Number of Households Selling Crops Yield (t/ha) Map 3.35 LINDI Number of Households and Percent of Total Households Selling Crops by District Percent of Total Households Selling Crops Number of Households Selling Crops 50 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 Compost was mostly used in Nachingwea (2% of the total planted area in the district), and this was closely followed by Lindi Urban (1.9%) and Kilwa (0.9%). Other districts, Liwale, Lindi Rural and Ruangwa used very little compost (0.1%) each (Chart 3.67). In permanent crops compost was mainly used on pigeon pea (751 ha, 77%) followed by rubber vine fruit (104 ha, 11%), banana and guava (45 ha, 5% each), mango (23 ha, 2%) and durian (12 ha, 1%). 3.3.4.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 7,548 ha of annual crops and vegetables. Insecticides were the most common pesticide used in the region (46% of the total area applied with pesticides). This was followed by fungicides (33%) and herbicides (21%). (Chart 3.68) • Insecticide Use The planted area applied with insecticides was estimated at 3,495 ha which represented 2 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with insecticides (2,084 ha, 59.6% of the total planted area with insecticides) followed by roots and tubers (596 ha, 17%), pulses (351 ha, 10.1%), and oil seed (209 ha, 6%), fruit and vegetables (246 ha, 7%) and cash crops (10 ha, 0.3%). (Chart 3.69) However, the percent of insecticides used in fruits and vegetables and cash crops was much greater than in other crop types (24.7 and 17.2% respectively), while only 1.1 percent of oil seed crops were applied with insecticides (Chart 3.70). Chart 3.70 Planted Area Applied with Insecticides by Crop Type Roots & Tubers, 596, 17.0% Cereals, 2084, 59.6% Cash crops, 10, 0.3% Pulses, 351, 10.1% Fruits & Vegetables, 246, 7.0% Oil seeds & Oil nuts, 209, 6.0% Chart 3.69: Planted Area Applied with Insecticides by 0.0 5.0 10.0 15.0 20.0 25.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.70: Proportion of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - Lindi 0.00 2.00 4.00 6.00 Kilwa Ruangwa Liwale Lindi UrbanNachingweaLindi Rural District Percent Chart 3.71: Pecent of Planted Area applied with Insecticides by Distrit - Lindi Chart 3.69 Planted Area (ha) by Pesticide Use Insecticides, 3,495, 45% Fungicides, 2,566, 34% Herbicides, 1,572, 21% Chart 3 68 Nachingwea Lindi Urban Lindi Rural Kilwa Ruangwa 28ha 0ha 0ha 0ha 207ha 68ha 0.2% 0% 0% 0% 0.5% 0.3% Liwale 160 to 210 120 to 160 80 to 120 40 to 80 0 to 40 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 276ha 908ha 137ha 512ha 593ha 439ha 2% 8.7% 0.5% 1.6% 5.2% 1.2% Liwale 800 to 1,000 600 to 800 400 to 600 200 to 400 0 to 200 Map 3.46 LINDI Planted Area and Percent of Planted Area with Farm Yard Manure Application by District Tanzania Agriculture Sample Census Planted Area awith Farm Yard Manure Applied Planted Area with Farm Yard Manure Applied Planted Area with Compost Manure Applied Percent of Planted Area with Farm Yard Manure Applied Map 3.47 LINDI Planted Area and Percent of Planted Area with Compost Manure Application by District Percent of Planted Area with Compost Manure Applied Planted Area with Compost Manure Applied 52 Lindi Urban Lindi Rural Kilwa Ruangwa Nachingwea 249 2,217 1,809 5,785 1,129 1,402 5% 8% 6% 21% 3% 12% Liwale 4,000 to 6,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 6,551 888 6,280 5,191 4,194 2,468 15% 28% 20% 19% 12% 22% Liwale 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.36 LINDI Number of Households and Percent of Total Households Receiving Crop Extension Services by District Tanzania Agriculture Sample Census Number of Households Receiving Crop Extension Number of Households Receiving Crop Extension Services Number of Households Using Improved Seed Percent of Total Households Receiving Crop Extension Services Map 3.37 LINDI Number of Households and Percent of Crop Growing Households Using Improved Seed by District Percent Households Using Improved Seed Number of Households Using Improved Seed 53 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 0 207 68 0 608 114 0.5% 0% 0.3% 0% 1.7% 1% Liwale 400 to 700 300 to 400 200 to 300 100 to 200 0 to 100 Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 32 303 257 0 0 28 1% 0.7% 0.9% 0% 0% 0.2% Liwale 240 to 310 180 to 240 120 to 180 60 to 120 0 to 60 Map 3.38 LINDI Number and Percent of Smallholder Planted Trees by District Tanzania Agriculture Sample Census Number of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Map 3.39 LINDI Number and Percent of Households with Water Harvesting Bunds by District Percent of Households with Water Harvesting Bunds Number of Households with Water Harvesting Bunds 54 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 Annual crops with more than 50 percent insecticide use were field peas (80%), jute (70%) and tomatoes (61%). Kilwa had the highest percent of planted area with insecticides (5.3% of the total planted area with annual crops in the district). This was closely followed by Ruangwa (5.0%) then Liwale (4.8%), Lindi Urban (4.1%) and Nachingwea (4.1%). The smallest percentage was recorded in Lindi Rural district (3.3%) (Chart 3.71) • Herbicide Use The planted area applied with herbicides was 1,572 ha which represented 0.8 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,073 ha, 68%) followed by roots and tuber (313 ha, 20%), oil seeds (150 ha, 10%) pulses (36 ha, 2%). Herbicides were not used in cash crops or fruits and vegetables (Chart 3.72). However, the percent of herbicide use on cereals and oil seeds was much greater than in other crop types (0.9% and 0.8% respectively) while only 0.6 percent of pulses were applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (1.0%), sorghum (0.9%), cassava (0.7%), simsim (0.8%), groundnuts (1.0%) and cowpeas (0.7%) Kilwa had the highest percent of planted area with herbicides (1.9% of the total planted area with annual crops in the district). This was followed by Lindi Rural (0.9%) then Nachingwea (0.7%), Liwale (0.7%) and Ruangwa (0.6%). The use of herbicides in Lindi Urban district was zero (Chart 3.74). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Roots & Tubers, 313, 20% Pulses, 36, 2% Oil seeds, 150, 10% Fruits & Vegetables, 0, 0% Cash crops, 0, 0% Cereals, 1,073, 68% Chart 3.72: 0.0 0.3 0.6 0.9 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.73: Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - Lindi 0.0 0.5 1.0 1.5 2.0 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Percent Chart 3.74: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 • Fungicides Use The planted area applied with fungicides was 2,566 ha which represented 1.3 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with fungicides (1,748ha, 68%) followed by roots and tubers (535 ha, 21%), oil seeds (200 ha, 8%), pulses (50 ha, 2%). Fungicides were not applied in cash crops (Chart 3.75). However, the percentage use of fungicide in cereals and roots and tubers was much greater than in other crop types (68% and 21% respectively), while only one percent of fruits and vegetables was applied with fungicides (Chart 3.76). The fungicide use in annual crops was less than 10 percent with tomatoes having the highest use (7%) followed by onions (3.5%), maize (1.7%) and simsim (1.3%) Lindi Urban and Liwale had the highest percent of planted area with insecticides (3.3 % of the total planted area with annual crops in the district). This was closely followed by Nachingwea (2.6%), Ruangwa (1.9%) and Lindi Rural (1.1%). The smallest percentage use was recorded in Kilwa (0.7%). (Chart 3.77) 3.3.4.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of paddy and cassava were harvested by machine (5%). All other cereals and annual crops were harvested by hand. 3.3.4.7 Threshing Methods Hand threshing was the most common method used, with 84 percent of the total area planted with cereals during the wet season being threshed by hand. Human powered tools, draft animals and engine driven machines were only used on crops harvested from 0.7%, 0.4 percent and 0.1 percent of the total planted area respectively. Chart 3.76 Planted Area Applied with Fungicides by Crop Type Cereals, 1,748, 68% Roots & Tubers, 535, 21% Pulses, 50, 2% Oil seeds, 200, 8% Fruits & Vegetables, 33, 1% Cash crops, 0, 0% Chart 3.75: Chart 3.78 Proportion of Planted Area with Fungicides by District - LINDI 0.0 1.0 2.0 3.0 4.0 Lindi Urban Liwale Nachingwea Ruangwa Lindi Rural Kilwa District Percent Chart 3.77: 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.76: Chart 3.76: Proportion of crop Type Planted Area Applied with Fungicides INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 3.3.5 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yield. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.3.5.1 Area Planted with Annual Crops and Under Irrigation In Lindi region, the area of annual crops under irrigation was 2,806 ha representing 1.4percent of the total area planted (Chart 3.78). The district with the largest planted area under irrigation for annual crops was Lindi Rural (828 ha, 29.5% of the total irrigated area planted with annual crops in the region). This was closely followed by Ruangwa with (707 ha, 22.7%) and then Nachingwea (660 ha, 21.2%). When expressed as a percentage of the total area planted in each district, Lindi Urban had the highest percent with 5.4% of the planted area in the district under irrigation. This was followed by Ruangwa (2.3%), Lindi Rural (1.6%), Liwale (1.5%), Nachingwea (1.3%) and Kilwa (1%) (Chart 3.79 and map 3.40). Of all the different crops and in terms of proportion of the irrigated planted area, amaranths and egg plant were the most irrigated crops with 100 percent irrigation followed by okra (71%), onions (70%), tomatoes (29%) and pumpkins (20%). In terms of crop type, the area under irrigation for cereals was 1,980 ha (64% of the total area under irrigation), followed by roots and tubers with 618 ha (20%), fruit and vegetables (418 ha, 13%), oil and oil seeds (51 ha, 2%) and pulses (48 ha, 2%). All of the irrigation on cereals was applied to maize, paddy and sorghum. The area of fruit and vegetables under irrigation was 418 ha which represents 42 percent of the total planted area with fruit and vegetables, followed by cereals (1.6%), roots and tubers (1.3%), pulses (0.8%) and oil seeds and oil nuts (0.3%). 3.3.5.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from river (54% of households with irrigation). This was followed by wells (32%), canals (10%), pipe water (3%) and dam (1%). There were no households using water from boreholes. Using various sources of water for irrigation, Lindi rural had 1,235 (43%) households, followed by Ruangwa 680 households (23%), Liwale 426 households (15%), Kilwa 386 households (13%) and Nachingwea 176 households (6%). (Chart 3.80) Chart 3.79 Area of Irrigated Land Unirrigated Area, 192,260, 98% Irrigated Area, 3,115, 2% Chart 3.78: Area of Irrigated Land Chart 2.80: Planted Area and Percentage of Planted Area with Irrigation by District - LINDI Region 0 100 200 300 400 500 600 700 800 900 Lindi Rural Ruangwa Nachingwea Kilwa Liwale Lindi Urban District Irrigated Area (ha) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Percentage with Irrigation Irrigated Land (ha) Percentage of Irrigated Land Chart 3.79: Chart 3.81 Number of Households with Irrigation by Source of Water Canal, 301, 10% River, 1,569, 54% Well, 923, 32% Dam, 774, 3% Pipe water, 81, 3% Canal River Well Dam Pipe water Chart 3.80: Lake Dam, 78, 1% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.3.5.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 52.7 percent of households using this method. This was closely followed by gravity with 40.2 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.81). Hand bucket was used by most households with irrigation in Lindi Rural (33%), followed by Ruangwa (31%), Liwale (15%), Nachingwea (11%) and Kilwa (9%). Motor pump was used only in Ruangwa district. Gravity was the second most important method of obtaining water for irrigation. Gravity was more common in Lindi Rural with 62 percent of households using the method to get water for irrigation, followed by Kilwa (21%) and Liwale (17%). Gravity was not used in Nachingwea and Ruangwa districts. Although the method of obtaining irrigation water by hand bucket was the most common method in all districts, Ruangwa districts used some hand and motor pumps for obtaining water. 3.3.5.4 Methods of Water Application Most households used watering can (58% of households using irrigation) as a method of field application. This was closely followed by flooding (40%). Sprinklers were not widely used (3%). Water hose were not used at all as a method of water application. (Chart 3.82) 3.3.6 Crop Storage, Processing and Marketing 3.3.6.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Lindi region show that there were 97,394 crop growing households (64% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 78,537 households storing 3,720 tonnes as of 1st January 2004. This was followed by sorghum and millet (41,507 households, 1,432 tonnes), pulses (28,321 households, 832 tonnes), paddy (17,411 households, 700 tonnes), groundnuts and bambara nuts (4,978 households, 113 tonnes) and cashew nuts (1,576 households, 10 tonnes). Other crops were stored in very small quantities. (Chart 3.83) Chart 3.84 Number of Households and Quantity Stored by Crop Type - LINDI 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Maize Sorghum & Millet Pulses Paddy Groundnuts/Bambara nuts Cashew nut Crop Number of households 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.83: Chart 3.83 Number of Households with Irrigation by Method of Field Application Sprinkler, 69, 2% Bucket / Watering Can, 1,667, 58% Flood, 1,167, 40% Flood Bucket / Watering Can Sprinkler Chart 3.82: Chart 3.82 Number of Households by Method of Obtaining Irrigation Water Gravity, 1,167, 40.2% Hand Bucket, 10,123, 43.4% Hand Pump, 84, 0.4% Other, 212, 0.9% Gravity Hand Bucket Other Motor Pump Chart 3.81: Chart 3.81: Number of Households with Irrigation by Method of Obtaining Irrigation Water 1530, 52.7% Other 69, 2.4% Hand Pump 137, 4.7% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 • Methods of Storage The region had 75,282 crop growing households storing their produce in locally made traditional structures (77% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 14,280 (15%). This was followed by improved locally made structures (2,560 households, 3%) air tight drums (1,486 households, 1.5%), modern stores (894 households, 0.9%), unprotected piles (805 households, 0.8%) and other methods (2,088 household, 2.1%) (Chart 3.84) Locally made traditional structures was the dominant storage method in all districts, with the highest percent of households in Lindi Rural using this method (83% of the total number of households storing crops). This was followed by Ruangwa (82%), Liwale (79%), Nachingwea (72%), Kilwa (69%) and Lindi Urban (46%) (Chart 3.85) The highest percent of households using sacks and open drum was that of Lindi Urban and Kilwa districts (54% and 29% of the total number of households storing crops), followed by Nachingwea and Liwale (16% each), Ruangwa (15%) and Lindi Rural (7%). • Duration of Storage Most households (51% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (37%). The minority of households stored their crop for a period of over less than 3 months (12%). Most households that stored pulses stored them for a period of between 3 to 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.86). 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.86 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.86: Chart 3.85 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.85 Chart 3.85 Number of households by Storage Methods - LINDI Unprotected Pile, 805, 1% Improved Locally Made Crib, 2,560, 3% Other, 2,000, 2% Airtight Drum, 1,486, 2% Modern Store, 894, 1% Sacks / Open Drum, 14,280, 15% Locally Made traditional Crib, 75,370, 76% Chart 3.84: 75,282, Chart 3.84: Number of households by Method of Storage - Lindi INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Lindi Rural district (72%) followed by Lindi Urban (59%), Liwale (56%), Kilwa and Ruangwa (36%). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.87). However, households in Lindi Urban district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. • Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 69 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at higher price. A high percent of the stored annual cash crops was used for seeds for planting as was the case of groundnuts and bambaranuts (68.5%), followed by cashewnuts (61.2%) (Chart 3.88). • The Magnitude of Storage Loss About 68 percent of households that stored crops had little or no loss, followed by 23 percent loss up to a quarter. However the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambaranuts. The proportion of households that reported a loss of more than a quarter was greatest for maize (7.1% of the total number of households that stored crops). This was followed by beans and pulses (4.7%), groundnuts and bambaranut (3.7%), sorghum and millet (3.4%) and paddy (1%). All households that stored cash crops such as cotton and tobacco had no loss. Most households storing groundnuts and bambaranuts had little or no storage loss (92.3%). (Table 3.10) Table 3:10 : Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Kilwa 7,602 1,394 538 161 9,694 Lindi Rural 23,970 4,933 920 1,425 31,248 Nachingwea 17,372 10,911 1,923 436 30,642 Liwale 5,809 1,460 395 85 7,749 Ruangwa 10,816 3,892 2,263 403 17,374 Lindi Urban 654 35 0 0 688 Total 66,221 22,624 6,039 2,510 97,395 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Cashew nut Groundnuts and Bambara Nuts Crop Type Chart 3.88 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Chart 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 5,000 10,000 15,000 20,000 25,000 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Quantity (tonnes) 0 2 4 6 8 10 12 14 % Stored Quantity harvested Quantity stored % stored INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.3.6.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase its palatability. Agro-processing was practiced in most crop growing households in Lindi region (135,548) households, 89% of the total crop growing households) (Chart 3.89a). The percent of households processing crops was very high in most districts (above 90%). Nachingwea and Lindi Rural had the highest percent of households processing crops (97% and 91% of crop growing households respectively) Processing Methods Most households processed their crops using neighbour’s machines accounting for 46 percent (62,165 households) of the total crop processing households. This was closely followed by those processing on-farm by hand (59,757 households, 44%), on-farm by machine (6,475 households, 4.8%), trader (6,235 households, 4.6%). The remaining methods of processing crops were used by very few households with each accounting for less than 1% of the total crop growing households. Although processing by machine was the most common processing method in all districts in Lindi region, however district differences existed. Lindi Rural had a higher percent of hand processing than other districts. (43%), followed by Kilwa (31%). Nachingwea and Ruangwa had 8% each and Lindi Urban (3%). Processing by trader was more common in Ruangwa (56%), whilst processing on farm by machine was more prevalent in Lindi Rural (81%), (Chart 3.90). • Main Agro-processing Products Two types of products can be produced from agro-processing namely, the main product and the by-product. The main product is the major product after processing and the by- product is the secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 115,383 households processing crops into flour (85%) followed by grain with 18,694 households (14%). The remaining products were produced by small numbers of households (Chart 3.91). Chart 3.90 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.92 Number of Households by Type of By-product Other, 106, 0% Shell, 1,075, 1% Cake, 2,170, 3% Pulp, 1,576, 3% Bran, 63,326, 83% Husk, 3,807, 8% Chart 3.89a Households Processing Crops Households not Processing, 17,625, 12% Households Processing, 135,549, 88% Chart 3.89a Number of Households Processing Crops INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 The number of households producing by-products accounted for 34 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 37,186 households (80%) followed by Husks (5,884 households, 13%), shell (1,810 households, 4%) and cake (1,250 households, 3%). The remaining by- products were produced by a small numbers of households (Chart 3.92). • Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was household/human consumption which represented 99.5 percent of the total households that used primary processed product (Chart 3.93). Lindi Rural was the only district that used primary products as fuel for cooking. Out of 7,182 households that sold processed products, 570 were from Kilwa (46% of the total number of households selling processed products in the region), followed by Liwale with 307 households (25%), Lindi Rural with 214 households (17%) and Ruangwa with 138 households (11%). There were no processed products sold in Nachingwea and Lindi Urban districts (Chart 3.94). Chart 3.91 Percent of Households by Type of Main Processed Product Grain 13.80% Oil 0.71% Juice 0.15% Other 0.10% Pulp 0.06% Flour / Meal 85.18% Chart 3.93 Use of Processed Product Household/ human consumption, 262,629, 99.15% Fuel for Cooking, 96, 0.04% Sale Only, 1,228, 0.46% Did Not Use, 827, 0.31% Animal Consumption, 101, 0.04% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of hous Kilwa Liwale Lindi Rural Ruangwa District Chart 3.94 Percentage of Households Selling Processed Crops by District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 • Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (3,324 households, 46.3%), followed by to others (3,175 households, 44.2%). This was followed by large scale farm (233 households, 3.2%), cooperatives (201 households, 2.8%), store (106 households, 1.5%), trader at farm (88 households, 1.2%) and farmers association (55 households, 0.8%) (Chart 3.97). There were large differences between districts in the proportion of households selling processed products to neighbours with Ruangwa district selling all the processed products to neighbours (100%), whereas Lindi Urban did not sell any processed products to neighbours. Compared to other districts, Lindi Rural was the only district that sold processed products to local markets/traders (7.3%) and marketing cooperatives (14%). In Liwale, selling processed products to farmer associations (17%) was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to other marketing outlets were Nachingwea (65.4%), followed by Lindi Rural 35.7%), Kilwa (27%) and Liwale (8.2%). (Chart 3.96) 3.3.6.3 Marketing • Crop Marketing The number of households that reported selling crops was 107,996 which represented 70.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Lindi Rural (92%), followed by Ruangwa (68%), Kilwa (66%), Nachingwea (58%), Lindi Urban (45%) and Liwale (36%). (Chart 3.97) Chart 3.95 Location of Sale of Processed Products Neighbours, 7,062, 46% Local Market / Trade Store, 594, 4% Marketing Co-operative, 646, 4% Other, 5,843, 38% Trader at Farm, 539, 3% Large Scale Farm, 542, 4% Farmers Association, 186, 1% Chart 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Percent of Households S Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.97 Number of Crop Growing Households Selling Crops by District 0 10,000 20,000 30,000 Lindi Rural Nachingwea Kilwa Ruangwa Liwale Lindi Urban District Number of House 0 10 20 30 40 50 60 70 80 90 100 Percente Number of Households Selling Crops Percent of Households Selling Crops INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 • Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (82% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (8%), lack of transport (4%), high transport costs (4%), lack of buyers (1%) and lack of market information (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. (Chart 3.98) • Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 28 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts except for Lindi Rural, Kilwa and Nachingwea and where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (36%, 28% and 19% respectively). Farmers’ association problems were reported only in Lindi Rural district. 3.3.7 Access to Crop Production Services 3.3.7.1 Access to Agricultural Credit The census result shows that in Lindi region very few agricultural households (535, 0.3% of total agricultural households) accessed credit out of which 405 (76%) were male-headed households and 130 (24%) were female headed households. In Nachingwea and Ruangwa districts only male headed households got agricultural credit whereas in Lindi Rural credit was equally accessed by the male and female headed households. In Liwale district, of the household that accessed agricultural credit 75% were male headed households. (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Not applicable 98,094 65.5 Production Insufficient to Sell 41,830 28.0 Other 7,152 4.8 Trade Union Problems 927 0.6 Price Too Low 651 0.4 Government Regulatory Board Problems 445 0.3 Co-operative Problems 216 0.1 Farmers Association Problems 209 0.1 Market Too Far 127 0.1 Total 149,653 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Lindi Rural 100 50 101 50 201 Nachingwea 85 100 0 0 85 Liwale 84 75 28 25 112 Ruangwa 137 100 0 0 137 Total 405 76 130 24 535 Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Open Market Price Too Low 82% Co-operative Problems 0% Transport Cost Too High 4% Lack of Market Information 1% Market too Far 8% No Transport 4% No Buyer 1% Chart 3.98: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 • Source of Agricultural Credit The agricultural credit providers in Lindi region were family, friends and relatives (31%), cooperatives (29%) and private individuals (19%), religious organizations/ NGOs/projects (16%) and other sources (5%). (Chart 3.99) Commercial banks did not provide any credits in all districts. Private individuals provided credit in Lindi Rural district only. Family, friends and relatives were major credit providers in Lindi Rural district. Religious organization, NGO and projects were more involved in funding a relatively great number of households in Liwale district (Chart 3.100). • Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used to buy agrochemicals (47%), labour (19%), livestock (16%), tools and equipments (13%) and fertilizers (5%) (Chart 3.101). • Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 64.1 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (23.4%), followed by “not wanting to go into debt” (5.9%) The rest of the reasons collectively accounted for 16.6% of the households that did not access credit. (Chart 3.102) Chart 3.99 Percentage Distribution of Households Receiving Credit by Main Source Trader / Trade Store 25% Other 7% Saving & Credit Society 5% Family, Friend and Relative 42% Religious Organisation / NGO / Project 21% Chart 3.100 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Lindi Rural Nachingwea Liwale Ruangwa District Percent of Househ Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Chart 3.101 Proportion of Households Receiving Credit by Main Purpose of the Credit Agro-chemicals 47% Livestock 16% Labour 19% Tools / Equipment 13% Fertilizers 5% Chart 3.102 Reasons for not Using Credit (% of Households) Did not know how to get credit, 62,954, 41% Don't know about credit, 34,896, 23% Not available, 35,759, 23% Did not want to go into debt, 9,052, 6% Difficult bureaucracy procedure, 4,359, 3% Not needed, 3,255, 2% Credit granted too late, 1,006, 1% Other, 166, 0% Interest rate/cost too high, 1,191, 1% 16% 31% Chart 3.99 Percentage Distribution of Households Receiving Credit by Main Source Trader / Trade Store 25% Other 7% Saving & Credit Society 5% Family, Friend and Relative 42% Religious Organisation / NGO / Project 21% 16% 31% Cooperatives 29% Private/Individual 19% INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 3.3.7.2 Crop Extension The number of agricultural households that received crop extension was 25,571 (16.7% of total crop growing households in the region) (Chart 3.103). Some districts had more access to extension services than others, with Nachingwea having a relatively high proportion of households (37%) that received crop extension messages in the district followed by Lindi Urban (28%), Lindi Rural (21%), Ruangwa (15%), Kilwa (14%) and Liwale (9%) (Chart 3.104) and Map 4.43 • Sources of Crop Extension Messages The major source of extension advice was the government which provided advice to 24,848 agricultural household (97.4 of the total number of households that received advice) large scale farms provided 1.6 percent, followed by NGOs/development projects that provided 0.7 percent, and the cooperatives 0.3 percent. (Chart 3.105 and Map 4:43) However district differences existed with the proportion of the households receiving advice from government services with Kilwa, Liwale and Lindi Urban being 100 percent. • Quality of Extension On the quality of extension, 67 percent of the households receiving extension ranked the service as being good, followed by very good (16%), average (15 %), poor (2%) no good (0.3%) (Chart 3.106).However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias can be expected. Chart 3.104 Number of Households Receiving Extension by District 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 Nachingwea Lindi Urban Lindi Rural Ruangwa Kilwa Liwale District Number of House 0 20 40 Percent of House Households Receiving Extension Percentage of Households Receiving Extension Chart 3.105 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 1.6% Cooperative 0.3% NGO / Development Project 0.7% Government 97.4% Chart 3.106 Number of Households Receiving Extension by Quality of Services Good, 17,117, 66.9% Average, 3,698, 14.5% Poor, 474, 1.9% No Good, 88, 0.3% Very Good, 4,195, 16.4% Chart 3.103 Number of Households Receiving Extension Advice Households Not Receiving Extension , 127,602, 83% Households Receiving Extension , 25,571, 17% 127,444 % INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 A small number of households used inputs and this was particularly true of the inputs that are not produced on farm e.g. improved seeds, fungicides, inorganic fertilisers and herbicides. In Lindi region pesticides/fungicides were used by 26,131 households which represented 17.06 percent of the total number of crop growing households. This was followed by households using improved seeds (8.22%), compost (2.28%), farm yard manure (1.87%), inorganic fertilizers (1.04%) and herbicides (0.04%). (Table 2.13) 3.3.8 Access to Inputs 3.3.8.1 Use of Inputs Access to inputs in this section refers to all crop growing households in Lindi region regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops only. Because of this the figures presented in this section may differ from those in the previous sections on inputs especially section 2.6. Data on source of inputs is only found in this section and applies to both annual and permanent crops. • Inorganic Fertilisers Smallholders who used inorganic fertilisers in Lindi mostly purchased them from the local market/trade store (71.0% of the total number of inorganic fertiliser users) followed by from neighbour (12.5 %), crop buyers (8.5%), development project (4.3%), cooperative (1.8%) and from other sources (1.8%) (Chart 3.107) Access to inorganic fertiliser was mainly less than 10 km from the household with most households being between 3 and 10 km from the source (38.8%), followed by above 20 km (29.5%), less than 1 km (22.3%), between 1 and 3 km (5.8%) and between 10 and 20 km (3.5%). (Chart 3.108) Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “non available” (39%) as the reason for not using the fertilizers, it may be assumed that access to inorganic fertiliser was not the main reason for not using them. Other reasons such as cost were more important with 33 percent of households responding to cost factors as the main reason for not using the fertilizers. In other words, if the cost was affordable the demand would be higher and inorganic fertilisers would be made more available. More smallholders in Ruangwa used inorganic fertilisers than in other districts in Lindi Region (55.5% of households using inorganic fertilisers), followed by Liwale (21.0%), Lindi Rural (18.1%) and Nachingwea (5.4%) (Other districts reported not using inorganic fertiliser in Lindi region. Table 2.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 2,865 1.87 150,150 98.13 Improved Seeds 12,591 8.22 140,424 91.78 Insecticides/Fungicide 26,131 17.06 126,883 82.94 Compost 3,492 2.28 149,523 97.72 Inorganic Fertiliser 1,591 1.04 151,424 98.96 Herbicide 57 0.04 152,958 99.96 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 71.0 12.5 8.5 4.3 1.8 1.8 0 400 800 1,200 Local Market / Trade Store Neighbour Crop buyers Development Project Other Co-operative Source of Inorganic Fertiliser Number of Households Chart 3.107: Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.107: Chart 3.108 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 • Improved Seeds The percent of households that used improved seeds were 8 percent of the total number of crop growing households. Most of the improved seeds were from the local market and trade store 43.2 percent. Other sources of improved seeds were from neighbours (29.9%), locally produced by household (15.5%), crop buyers (3.3%) and development projects (1.2%) (Chart 3.109) The access to improved seeds was better than other inputs (inorganic fertilizers and insecticides) with 48 percent of households obtaining them within 1 km of the household (Chart 2.110). This is in line with the higher use of improved seed compared to other inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. Most of smallholders who used improved seeds were Ruangwa (46% of households using improved seeds in the region), followed by Lindi Rural (18%), Kilwa (14%), Liwale (11%), Nachingwea (9%) and Lindi Urban (2%). (Map 2.98). • Insecticides and Fungicide The percent of households that used insecticides/fungicides was 17 percent of the total number of crop growing households. Most of the insecticides/fungicides were from the local market and trade store 69.8 percent. Other sources of insecticides/fungicides were co-operatives (18.7%), neighbours (7.5%), local farmers groups (1.9%), crop buyers (1.2%), locally produced by household (0.3%), secondary market (0.1%) and from other sources (0.4 (Chart 3.111) Access to insecticides/fungicides was mainly less than 10 km from the household with most households being between 3 and 10 km from the source (25%), followed by between 10 to 20 km (23%), above 20 km (21%), less than 1 km (20%) and between 1 and 3 km (12%). (Chart 3.112) Due to the very small number of households using insecticides/fungicides Chart 3.111 Number of Households by Source of Improved Seed 0.5 0.2 1.2 0.9 1.2 3.3 4.1 15.5 29.9 43.2 0.0 1500.0 3000.0 4500.0 6000.0 Local Market / Trade Store Neighbour Locally Produced by Household Other Crop Buyers Development Project Large Scale Farm Local Farmers Group Secondary Market Co-operative Source of Improved Seed Number of Households Chart 3.109: Chart 3.113 Number of Households by Source of Insecticide/fungicide 69.8 18.7 7.5 1.9 1.2 0.4 0.1 0.3 0 5000 10000 15000 20000 Local Market / Trade Store Co-operative Neighbour Local Farmers Group Crop Buyers Other Locally Produced by Household Secondary Market Source of Insecticide/fungicide Number of Households Chart 3.111: Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.112: Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 50 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.110: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 coupled with the small number of households responding to “not available” (24%) as the reason for not using them, it may be assumed that access to insecticides/fungicides was not the main reason for not using them. Other reasons such as cost were more important with 57 percent of households responding to cost factors as the main reason for not using the insecticides/fungicides. In other words, if the cost was affordable the demand would be higher and insecticides/fungicides would be made more available. Most of the smallholders who used insecticides/fungicides were from Nachingwea districts (32% of households using inorganic fertilisers in the region), followed by Lindi Rural (22%), Ruangwa (21%), Liwale (14%), Kilwa (8%) and Lindi Urban (2%) 3.3.9 Tree Planting Tree farming is not common in Lindi District. Natural trees are the major source of trees products used by households in the region. The number of households involved in tree farming was 707 representing 0.5 percent of the total number of agriculture households. The number of trees planted by smallholders on their allotted land was 2,812 trees. The average number of trees planted per household that plants trees was 4. The main species planted by smallholders is Senna spp (1,008 trees, 36%), followed by Trichila (693, 25%), azadirachta indica (668 trees, 24%), Melcia excelsa (301 trees, 11%), Eucalyptus (142 trees, 5%) and. The remaining trees species were planted in very small numbers (Chart 113.). Lindi Rural had the largest number of smallholders with planted trees than any other district (48%) and is dominated by Senna spp species. This is followed by Ruangwa (41%) which is dominated by Trichilia spp and to a lesser extent Melcia excelsa, then Liwale (6%) and Lindi Urban (5%) which is mainly planted with Eucalyptus spp (Chart 3.114 and Map 3.45.). Chart 2.114 Number of Planted Trees by Species - LINDI 0 5 10 15 20 25 Senna Spp Azadritachta Spp Trichilia Spp Eucalyptus Spp Melicia excelsa Tree Speci Number of Trees Chart 3.114: Chart 3.113 Number of Trees Planted by Smallholders by Species and District - Lindi 0 350 700 1050 1400 Lindi Rural Liw ale Ruangw a Lindi Urban District Number of Trees Senna Spp Trichilia Spp Azadritachta Spp Melicia excelsa Eucalyptus Spp INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 Most smallholders plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 95 percent, followed by scattered around fields (5%). There were no trees planted in a plantation or coppice.(Chart 3.115). The main purpose of planting trees was to provide shade (57%). This wa followed by planks/timber and medicinal use (16% each) and other uses (11%) (Chart 3.116). 3.3.9.1 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 998. This number represented 1 percent of total number of agricultural households in the region (Chart 3.117). The proportion of households with soil erosion control and water harvesting facilities was highest in Nachingwea District (61%) followed by Lindi Rural (21%), Liwale (11%) and Ruangwa (7%) (Chart 3.118). Erosion control by control bunds had 33,797 structures. This represented about 98.8 percent of the total structures in the region, and the remaining percentage was shared among the rest of the erosion control methods mentioned above. gabions/sand bags (0.6%) and vetiver grass and drainage ditches (0.3% each), With exception of Lindi Rural District, erosion control bunds structures were widely used in all districts. Nachingwea had 31,630 erosion control bund structures (93.6%), followed Ruangwa (2,053 structures, 6.1%) and Liwale (114 structures, 0.3%). Drainage ditches and gabions/sandbag were used in Lindi Rural district only and vetiver grass in Liwale. Nachingwea districts reported to have 31,630 control erosion structures and this was about 92.5 percent of the total structures in the region. Chart 3.116 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Planks / Timber Shade Other Medicinal Use Percent of House Chart 3.117 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 152,175, 99% Households with facilities, 998, 1% Chart 3.118 Number of Households with Erosion Control/Water Harvesting Facilities 61 0 0 7 11 21 0 100 200 300 400 500 600 700 NachingweaLindi Rural Liwale Ruangwa Kilwa Lindi Urban District Number of House 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Percen Number of Households Percent Chart 3.115 Number of Trees Planted by Location Field boundary, 40, 89% Scattered in field, 5, 11% Chart 3.115: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 3.4 LIVESTOCK RESULTS 3.4.1 Cattle Production The total number of cattle in the region was 3,081. Goats were the dominant livestock type in the region followed by sheep, pigs and cattle. The region had 0.02 percent of the total cattle population on Tanzania Mainland. 3.4.1.1 Cattle Population The number of indigenous cattle in Lindi region was 2,019 (65.5 % of the total number of cattle in the region), 998 cattle (32.4%) were dairy breeds and 64 cattle (2.1%) were beef breeds. The census results show that 838 agricultural households (0.5% of the total agricultural households) kept 3,081 cattle. This was equivalent to an average of 4 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Lindi Rural which had about 1,300 (42%) cattle. Other districts and their respective estimated number of cattle were Lindi Urban 1,080 (35%) and Nachingwea 700 (23%) (Chart. 3.119) and (Map 3.47) Lindi Rural and Lindi Urban districts had the largest number of both indigenous and improved dairy cattle. Improved beef cattle were only availabe in Lindi Urban district. The number of dairy cattle was very small and the number of beef cattle was insignificant. Lindi Rural district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.120) 3.4.1.2 Herd Size Eighty percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household each. The herds of size 6-10 accounted for about 27 percent of all cattle in the region. Only 4 percent of the cattle rearing households had head sizes of 16- 20 cattle. About 96 percent of total cattle rearing households had herds of size 1-10 cattle and owned 82 percent of total cattle with an average of five cattle per household. There were no households with more than 20 cattle per household. 0 20 40 60 80 100 120 Number of Cattle ( Lindi Rural Nachingwea Lindi Urban Districts Chart 3.119 Total Number of Cattle ('000') by District Chart 3.120 Number of Cattle by Type and District 0 100 200 300 400 500 600 700 800 900 1000 Lindi Rural Nachingwea Lindi Urban Districts Number Cattle Indigenous Beef Dairy 2,853 6,194 3,080 - 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1995 1999 2003 Year Chart 3.121 Cattle Population Trend INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.4.1.3 Population Trend Cattle population in Lindi increased during the period of eight years from 2,853 in 1995 to 3,080 in 2003 which implies an overall positive annual growth rate of 0.96.percent (Chart 3.121). However, there was a very sharp increase in number of cattle over the period of four years from 1995 to 1999 at an average growth rate of 21.4 percent, whereby the number of cattle increased from 2,853 to 6,194. However, the number of cattle is estimated to have decreased from 6,194 in 1999 to 3,080 in 2003 at the rate of -16%. 3.4.1.4 Improved Breeds The total number of improved cattle in Lindi region was 1,062 (998 dairy and 64 improved beef). The diary cattle constituted 32.4 percent of the total cattle and 94 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 6 percent of the total number of the improved cattle and 2.1 percent of the total cattle. No data on improved cattle breeds was collected in Lindi collected in the 1995 sample census. However, the number of improved cattle increased from 891 in 1999 to 998 in 2003 at an average annual growth rate of 2.9 percent (Chart 122). 4.4.2 Goat Production Goat rearing was the most important livestock keeping activity in the region followed by sheep and pig and cattle rearing. In terms of total number of goats on the Mainland, Lindi region ranked 19 out of the 21 regions with 0.9 percent of the total goats on the Mainland 4.4.2.1 Goat Population The number of goat-rearing-households in the region was 14,084 (9.2% of all agricultural households) with a total of 110,506 goats giving an average of 8 head of goats per goat-rearing- households. Lindi Rural had the largest number of goats estimated at 42,758 (39% of all goats in the region) followed by Kilwa 20,531 (19%), Nachingwea 18,807 (17%), Ruangwa 12,200 (11%), Lindi Urban 9,694 (19%) and Liwale 6,515 (6%) (Chart 3.123). (Map 3.49). 3.4.2.2 Goat Herd Size Thirty six percent of the goat-rearing households had herd sizes of 1-4 goats with an average of 3 goats per goat rearing household. Ninety percent of total goat-rearing households had herd sizes of 1-14 goats and owned 66 percent of the total goats in the region resulting in an average of 7 goats per goat-rearing households. The region had 164 households (1%) with herd sizes of 40 or more goats each (12,716 goats in total), resulting in an average of 75 goats per household. - 891 998 - 200 400 600 800 1,000 1995 1999 2003 Year Chart 3.122 Dairy Cattle Population Trend 5000 15000 25000 35000 45000 Lindi Rural Kilwa NachingweaRuangwaLindi UrbanLiwale District Chart 3.123 Total Number of Goats by District Ruangwa Nachingwea Kilwa Lindi Urban Lindi Rural 12,200 18,807 6,515 20,531 9,694 42,758 Liwale 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Lindi Rural Lindi Urban Ruangwa Nachingwea 1,300 0 1,080 0 700 0 Liwale Kilwa 1,200 to 1,300 900 to 1,200 600 to 900 300 to 600 0 to 300 Map 3.40 LINDI Cattle population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Cattle Number of Cattle Number of Goat Map 3.41 LINDI Goat Population by District as of 1st Octobers 2003 Number of Goat 73 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 74 3.4.2.3 Goat Breed Goat husbandry in the region was dominated by the indigenous breeds that constituted 93 percent of the total goats in Lindi region. Improved goats for meat and diary goats constituted 3 and 4 percent of total goats respectively. 3.4.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 15.3 percent. This positive trend implies eight years of population increase from 35,185 in 1995 to 110,505 in 2003. The number of goats increased from 35,185 in 1995 at an estimated annual rate of 18.5 percent to 69,370 in 1999. From 1999 to 2003, the goat population increased at an average annual growth rate of 12.3 percent (Chart 124). 3.4.3 Sheep Production Sheep rearing was the second most important livestock keeping activity in Lindi region after cattle and goats. The region ranked 20th out of 21 Mainland regions and had 0.3 percent of all sheep on Tanzania Mainland. 3.4.3.1 Sheep Population The number of sheep-rearing households was 1,555 (1% of all agricultural households in Lindi region) rearing 11,905 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Lindi Rural with 4,464 sheep (37%of total sheep in Lindi region) followed by Ruangwa (3,678 sheep, 31%), Nachingwea (2,285 sheep, 19%) and Liwale (926 sheep, 8%). Lindi Urban District had the least number of sheep (552 sheep, 5%) (Chart 3.125 and Map 3.51). Sheep rearing was dominated by indigenous breeds that constituted 97.5 percent of all sheep kept in the region. Only 2.5 percent of the total sheep in the region were improved breeds adding up to 299 sheep and all reared in Lindi Rural District. 3.4.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at 35,185 69,370 110,505 - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Number of go 1995 1999 2003 Year Chart 3.124 Goat Population Trend 17,376 7,438 11,905 - 5,000 10,000 15,000 20,000 Number of sh 1995 1999 2003 Year Chart 3.126 Sheep Population Trend 0 1000 2000 3000 4000 5000 Number of sh Lindi Rural Ruangwa Nachingwea Liwale Lindi Urban District Chart 3.125 Total Number of Sheep by District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 75 -4.6 percent. The population decreased at an annual rate of -19.1 percent from 17,376 in 1995 to 7,438 in 1999. From 1999 to 2003, sheep population increased at an average annual rate of 12.5 percent (Chart 3.126). 3.4.4 Pig Production Piggery was the third most important livestock keeping activity in the region followed by cattle. The region ranks 17th out of 21 Mainland regions and had 0.51 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Lindi region was 1,407 (1% of the total agricultural households in the region) rearing 4,956 pigs. This gives an average of 4 pigs per pig-rearing household. Pigs were reared in Nachingwea and Ruangwa districts only. There were no pigs in Lindi Rural, Lindi Urban, Kilwa and Liwale districts. The district with the largest number of pigs was Nachingwea with 4,000 pigs (81% of the total pig population in the region) followed by Ruangwa (956 pigs, 19%). (Chart 3.127 and Map 3.53) 3.4.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 3.72 percent. During this period the population grew from 3,701 to 4,956. The pig population decreased from 3,701 in 1995 to 2,148 in 1999 at a rate of -12.72 percent. The growth rate increased to 23.25 percent during the following four years from 1999 to 2003 in which pig population increased from 2,148 to 4,956 (Chart 3.128). 3.4.5 Chicken Production The poultry sector in Lindi region was dominated by chicken production. The region contributed 3.4 percent to the total chicken population on Tanzania Mainland. 3.4.5.1 Chicken Population The number of households keeping chicken was 83,711 raising about 1,261,290 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country, Lindi region was ranked 14th out of the 21 Mainland regions. 0 1,000 2,000 3,000 4,000 Number Nachingwea Ruangwa District Chart 3.127 Total Number of Pigs by District 3,701 2,148 4,956 - 2,000 4,000 6,000 Number of p 1995 1999 2003 Year Chart 3.128 Pig Population Trend Nachingwea Lindi Rural Lindi Urban Ruangwa 0 4,000 0 0 956 0 Liwale Kilwa 4,000 to 4,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Nachingwea Ruangwa Lindi Urban Lindi Rural 2,285 3,678 552 4,464 0 926 Liwale Kilwa 3,600 to 4,500 2,700 to 3,600 1,800 to 2,700 900 to 1,800 0 to 900 Map 3.42LINDI Sheep Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Sheep Number of Sheep Number of Pig Map 3.43 LINDI Pig Population by District as of 1st Octobers 2003 Number of Pig 76 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 77 The district with largest number of chickens was Lindi Rural (387,594 chickens, 31% of the total number of chickens in the region) followed by Kilwa (345,679, 27%), Nachingwea (230,370, 18%), Ruangwa (175,220, 14%), Liwale (106,553, 8%) and Lindi Urban (15,875 chickens, 1%) (Chart 3.129 and Map 3.55). However, Lindi Urban district had the highest density (2,646 chickens per km2) (Map 3.56). 3.4.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 5.2 percent. The population decreased at a rate of -0.1 percent from 1995 to 1999 after which it increased at the rate of 10.9 percent for the four year period from 1999 to 2003 (Chart 3.130). Eighty five percent of all chicken in Lindi region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.4.5.3 Chicken Flock Size The results indicate that about 82 percent of all chicken- rearing households were keeping 1-19 chickens per household with an average of 7 chickens per holder. About 17 percent of holders reported to be keeping the flocks of size 20 to 99 chickens with an average of 32 chickens per household Only one percent of holders kept the flocks of more than 100 chickens at an average of 479 chickens per household (Table 3.15). Table 3.14 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 22677 27 57500 3 5-9 22390 27 147318 7 10-19 23119 28 298654 13 20-29 7398 9 167849 23 30-39 3763 4 120978 32 40-49 1461 2 62380 43 50-99 1505 2 100646 67 100+ 639 1 305967 479 Total 82952 100 1261290 15 0 100,000 200,000 300,000 400,000 N u m ber of C h ick en s Lindi Rural Kilwa Nachingwea Ruangwa Liwale Lindi Urban District Chart 3.129 Total Number of Chickens by District 838,233 834,820 1,261,290 0 500,000 1,000,000 1,500,000 Number of Chicken 1995 1999 2003 Year Chart 3.130 Chicken Population Trend Lindi Urban Lindi Rural Ruangwa Kilwa Nachingwea 222,123 575,225 354,534 409,515 230,370 264,470 Liwale 480,000 to 600,000 360,000 to 480,000 240,000 to 360,000 120,000 to 240,000 0 to 120,000 Map 3.44 LINDI Chicken Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken 78 INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 3.4.5.4 Improved Chickens (layers and broilers) Layers chicken population in Lindi Region was 33,314 in 2003. The number of improved chicken was most significant in Lindi Rural District followed by Kilwa (Chart 3.131). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 60.83 percent during which the population grew from 3,415 to 152,855. The annual growth rate was 1.93% for the period of four years from 1995 to 1999. The broiler population increased at a very high rate of 153.75 percent per annum during the following four year period resulting in an increase from 3,687 in 1999 to 152,855 in 2003 (Chart 3.132). 3.4.6 Other Livestock There were 35,334 ducks, 6,207 turkeys, 2,489 rabbits and 2,159 donkeys raised by rural agricultural households in Lindi region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Nachingwea district (43.4% of all ducks in the region), followed by Ruangwa (31.5%), Lindi Rural (15.1%), Kilwa (5.9%) and Liwale (3.8%). Lindi Urban district had the least number of ducks estimated at 0.3 percent of total ducks in the region. Turkeys were not reported in Kilwa, Nachingwea and Lindi Urban districts. Lindi rural district had 5,155 turkeys (83%), followed by Liwale (914 turkeys, 15%) and Ruangwa (139 turkeys, 2%). Rabbits were reported in Kilwa and Nachingwea districts, while donkeys were reported only in Liwale district (Table 3.16). 3.4.7 Pest and Parasite Incidence and Control The results indicate that 23 percent and 12 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.133 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Lindi Rural district but lowest in Nachingwea, Liwale and Ruangwa Districts (Map 3.57). Table 3.15 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Kilwa 2,090 0 72 0 0 Lindi Rural 5,344 5,155 0 0 1,592 Nachingwea 15,351 0 176 0 607 Liwale 1,328 914 0 2,159 737 Ruangwa 11,116 139 0 0 716 Lindi Urban 104 o 0 0 0 Total 35,334 6,207 247 2,159 3,653 - 3,415 - 3,687 33,314 152,855 - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Number 1995 1999 2003 Year Chart 3.136 Layers Population Trend Chart 3.132: Layers population Trend Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 200 400 600 800 1000 1200 1400 1600 1800 Lindi Rural Kilwa Lindi Urban Nachingwea Liwale Ruangwa District Percen Ticks Tsetseflies Chart 3.133: 55928 212 96487 14578 439 14505 411 3607 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Number of Chick Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers Chart 3.131: Number of Improved Chicken by Type and INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 The most practiced method of tick control was spraying with 39 percent of all livestock-rearing households in the region using the method. Other methods had (31%) and dipping (5%). However, 25 percent of livestock-keeping households having tick problems did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 26 percent of livestock-rearing households. This was followed by trapping (6%) and dipping (2%). However, 66 percent of the livestock rearing households with tsetse flies problems did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 6,967 (46% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 46 percent, goats (23%), pigs (65%) and sheep (25%) (Chart 3.134). 3.4.8 Access to Livestock Services 3.4.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 5,963, representing 39 percent of the total livestock- rearing households and 0.4 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 92.1 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (7.9%) (0.3%). About 64 percent of livestock rearing households described the general quality of livestock extension services as being good, 16 percent said they were average, 15 percent said they were very good and 2 percent described them as poor (Chart 3.135). 3.4.8.2 Access to Veterinary Clinic About 66 percent of the livestock rearing households accessed the services within a distance of 14 kms. Only 34 percent of them accessed the services at a distance of more than 14 kms from their dwellings (Chart 3.140). The most affected district was Liwale district with many livestock rearing households accessing the services at a distance of more than 14 kms. Kilwa District was the least affected because all of the households could access the service within a distance of 14 kilometres. (Chart 3.136). Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Poor, 2.4% Average, 0.4% Good, 76.4% Very Good 18.3% No good, 2.4% Chart 3.135: 0 1000 2000 Percen Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.134: Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 81 3.4.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 5,703 (97% of livestock rearing households in Lindi region) whilst 190 households (3%) resided at a distance of between 5 and 14 kilometers from the nearest watering point. There were no households traveling 15 kms or more to the nearest watering point in the region. (Chart 3.138). Nachingwea district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Lindi Rural. In Liwale district, the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.139). 3.4.9 Animal Contribution to Crop Production Animal contribution in crop production in Lindi district was very limited. 3.4.9.1 Use of Draft Power Use of draft animals in Lindi was very limited. There were no households that reported using draft animals for cultivation. The region had no oxen, so hand cultivation was the major method used. Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000 12,000 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban District Number of House Series1 Series2 Chart 3.137: Chart 3.140 Number of Households by Distance to Village Watering Point and District 0 1,000 2,000 3,000 4,000 NachingweaLindi RuralRuangwa Kilwa Lindi Urban Liwale District Number of Househ Less than 5 kms 5-14 kms Chart 3.138 Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 3,160, 34% Less than 14km, 6,214, 66% Chart 3.136: Chart 3.142 Number of Households by Distance to Village Watering Points 15 or more kms, 258, 4% 5-14 kms, 190, 3% Less than 5 kms, 5,703, 93% Chart 3.139: INTRODUCTION ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 3.4.9.2 Use of Farm Yard Manure The number of Households using organic fertilizers in Lindi region was 4,746 (3.1% of total crop growing households in the region) (Chart 3.140). The total area applied with organic fertiliser was 5,423 ha of which 2,693 hectares (49.7% of the total area applied with organic fertiliser or 1.4% of the area planted with annual crops and vegetables during the wet season) was applied with farm yard manure (Map 3.59). The largest area applied with farm yard manure was found in Lindi Rural district with 549 hectares (50.4% of the total area applied with farm yard manure) followed by Lindi Urban (136 ha, 12.4%), Kilwa (133 ha, 12.2%), Nachingwea (99 ha, 9.1%), Liwale (91, 8.3%) and Ruangwa (83 ha, 7.6%) (Chart 3.141 and Map 3.60). 3.5 Fish Farming The number of households involved in fish farming in Lindi region was 304, representing 0.2 percent of the total agricultural households in the region (Chart 3.142 and Map 3.61). Lindi Rural was the leading district with 207 households (0.5% of agricultural households in the district) involved in fish farming. This was followed by Ruangwa (68 households, 0.3%) and Liwale (28 households, 0.2%). Fish farming was not practiced in Nachingwea and Lindi Urban districts (Chart 3.143). Chart 3.147 Area of Application of Organic Fertiliser by District LINDI 0 100 200 300 400 500 600 Lindi Rural Pangani Lindi Urban Kilwa Nachingwea Liwale District Area of Fertiliser Applica Farm Yard Manure Compost Chart 3.141: Chart 3.148 Number of Households Practicing Fish Farming - LINDI Households Prcticing Fish Farming, 304, 0.53% Households Not Prcticing Fish Farming, 152,869, 99.47% Chart 3.142: Chart 3.146 Number of Households Using Organic Fertiliser Not Using Organic Fertilizer, 147,018, 97% Using Organic Fertilizer, 4,746,3% Chart 3.140: 147,592 96.5% 5,423, 3.5% Nachingwea Lindi Urban Lindi Rural Ruangwa Kilwa 1,396 1,613 2,714 68 1,075 728 4 3.6 8.6 2.1 4 6.4 Liwale 2,400 to 2,800 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Nachingwea Lindi Urban Lindi Rural Kilwa Ruangwa 28 0 0 0 207 68 0.2 0 0 0 0.5 0.3 Liwale 160 to 210 120 to 160 80 to 120 40 to 80 0 to 40 Map 3.48 LINDI Number and Percent of Households Practicing Fish Farming by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Number of Households Without Toilets Percent of Households Practicing Fish Farming Map 3.49 LINDI Number and Percent of Households Without Toilets by District Percent of Households Without Toilets Number of Households Without Toilets 83 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 The main source of fingerings was the neighbour who provided fingering to 51 percent of the fish farming households. About 32 percent of households practicing fish farming got fingerings from governmental institutions and 17 percent got them from own ponds. Fish farming system was practiced in Lindi Rural, Liwale and Ruangwa districts. Dug-out-pond system were used by 337 (83%) of fish farming households in the region. Natural pond was used by 68 households (17%) fish farming households and in Ruangwa district only. Dug-out ponds were not used in Ruangwa district. The main fish specie planted was Tilapia. The numbers of fish harvested in Lindi region was 21,346, of which 19,977 fish (94%) were tilapia and 342 (2%) were carp. Other types of fish harvested were 1,027 (5 %). (Chart 3.144) About 56 percent of the fish farming households sold their fish to neighbours, 26% did not sell, while 18% sold to large scale farms. 3.6 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was the service located very farthest from most of the household’s dwellings. It was located at an average distance of 137.1 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (56.6), tertiary market (39), hospital (35), secondary school (29), secondary market (25), primary market (11), all weather road (6.4),health clinic (6), primary school (2) and feeder road (1.5) (Table 3.16). Table 3.16: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Road Kilwa 48.5 2.6 14.0 2.1 62.5 9.5 207.0 29.9 42.6 76.3 54.9 Lindi Rural 32.0 3.0 4.6 1.8 39.0 5.7 51.5 4.9 23.4 39.0 23.5 Nachingwea 14.8 2.0 3.4 0.5 14.0 4.8 158.2 3.0 17.6 24.6 68.2 Liwale 42.1 2.3 12.6 1.0 41.6 8.2 256.6 7.0 22.9 41.9 174.1 Ruangwa 15.3 1.4 2.7 1.5 23.6 4.3 135.2 13.3 17.6 15.4 54.6 Lindi Urban 9.0 3.0 2.2 1.8 10.8 4.4 9.5 4.2 15.6 9.1 8.0 Total 28.7 2.3 6.4 1.5 34.9 6.2 137.1 11.2 24.8 38.7 56.6 Chart 3.150 Fish Production Number of Others, 1,027, 4.8% Number of Tilapia, 19,977, 93.6% Number of Carp, 342, 1.6% Chart 3.144: 0 50 100 150 200 250 Number of Househ Lindi RuralRuangwa Liwale Kilwa NachingweaLindi Urban District Chart 3.149 Number of Households Practicing Fish Farming by District - LINDI Chart 3.143: RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 3.7 POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing the basis for tracking progress in poverty reduction strategies undertaken by the government 3.7.1 Type of Toilets The largest number of rural agricultural households used traditional pit latrines (142,796 households, 93.2% of all rural agricultural households) 2,302 households (1.5%) used flush toilets and 481(0.3%) used improved pit latrine. However, 7,594 households (5% of agricultural households in the region) had no toilet facilities (Chart 3.145). The distribution of the households without toilets within the region indicates that 36 percent of them were found in Kilwa District. The percentages of households without toilets in other districts were as follows Lindi Rural (21%), Nachingwea (18%), Ruangwa (14%) and Liwale (10%) Map 3.62) 3.7.2 Household’s Assets Most rural agricultural households in Lindi region owned radios. The number owning radios was 70,952 households (46.3% of the agriculture households in the region). They were followed by those owning bicycle (59,535 households, 38.9%), iron (18,981 households, 12.4%), wheelbarrows (1,531 households, 1%), television/video (964 households, 0.6%), vehicle (751 households, 0.5%), mobile phone (693 households, 0.5%), and landline phone (339 households, 0.2%). (Chart 3.146) 3.7.3 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region with 79.7 percent of the total rural agricultural households using this source of energy followed by hurricane lamp (14.6%), %), pressure lamp (2.3%), firewood (2.2%), candles (0.4%), mains electricity (0.37), solar (0.23%), gas or biogas (0.1%) and other sources (0.04%). (Chart 3.147) Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 142,796, 93.2% Flush Toilet, 2,302, 1.5% No Toilet , 7,594, 5.0% Improved Pit Latrine , 481, 0.3% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 28, 0.02% Crop Residues, 190, 0.12% Mains Electricity, 369, 0.24% Solar, 81, 0.05% Livestock Dung, 173, 0.11% Charcoal, 2,712, 1.77% Firewood, 149,592, 97.66% Parraffin / Kerocine, 29, 0.02% Chart 3.148: Chart 3.152 Percentage Distribution of Households Owning the Assets 1.0 2.2 1.0 0.5 0.2 46.3 38.9 12.4 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Radio Bicycle Iron Wheelbarrow Television / Vide Vehicle Mobile phone Landline phone Assets Percen Chart 3.146: Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Others, 63, 0.04% Wick Lamp, 122,138, 79.7% Gas (Biogas), 152, 0.1% Mains Electricity, 560, 0.37% Pressure Lamp, 3,501, 2.3% Hurricane Lamp, 22,413, 14.6% Candles, 616, 0.4% Solar, 358, 0.23% Firewood, 3,372, 2.2% Chart 3.147: Chart 3.145: RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 86 3.7.4 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.66 percent of all rural agricultural households in Lindi region. This was followed by charcoal (1.77%). The rest of energy sources accounted for 0.57 percent. These were mains electricity (0.24%), crop residues (0.12%), livestock dung (0.01%), solar (0.05%), paraffin/kerosene (0.02%) and bottled gas (0.02%). (Chart 3.154) 3.7.5 Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves and it was used by 81.3 percent of the rural agricultural households. This was followed by iron sheets (15.4%), grass/mud (1.7%), tiles (1.2%), asbestos (0.2%), and concrete (0.1%). (Chart 3.148) Kilwa district had the highest percentage of households with grass/leaves roofing (87%) followed by Lindi Rural and Nachingwea districts (83%), Ruangwa (76%), Lindi Urban and Liwale (73%). (Chart 3.149 and Map 3.63) 3.7.6 Access to Drinking Water The main source of drinking water for rural agricultural households in Lindi region was the well (50.5 percent of households used unprotected wells during the wet season and 59.5 percent of the households used them during the dry seasons). This was followed by lake/river (13.3 % of households in the wet season and 14.7 during the dry season), piped water (9.9% of households in the wet season and13.6% during dry season), unprotected spring (7.8% of households during the wet season and 7.9 % in the dry season), uncovered rainwater catchment (15.1% in the wet season and 1.7 during dry season), protected spring (1.5% of households in the wet season and 1.5% during dry the season), covered rainwater catchment with 1.5 percent of households using the source in the wet season and 0.4 households during the dry season while vendors, truck and other source were used 0.3% of the households during the wet season and 0.8% of the households in the dry season. About 61 percent of the rural agricultural households in Lindi region obtained drinking water within a distance of less than one kilometer during wet season compared to 40 percent of the households during the dry season. However, 38.6 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 59.8 percent of households in the dry season. The most common distance from the source of drinking water was between 500 metres and 2 kms (Chart 3.151). Chart 3.157 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Uprotected Well Protected Well Lake /River Piped Water Protected Spring Unprotected Spring Other Main source Percent of Househ Wet Season Dry Season Chart 3.151: Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 73 73 76 83 83 87 50 75 100 Kilwa Lindi Rural Nachingwea Ruangwa Lindi Urban Liwale District Chart 3.150: Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.2% Grass & Mud 1.7% Iron Sheets 15.4% Grass / Leaves 81.3% Tiles 1.2% Concrete 0.1% Chart 3.149: Lindi Urban Lindi Rural Ruangwa Nachingwea 2,195 18,245 8,284 12,013 16,214 6,450 69% 41% 30% 34% 52% 57% Liwale Kilwa 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Ruangwa Lindi Urban Lindi Rural Kilwa Nachingwea 19,985 8,349 2,412 37,244 27,387 29,170 73% 73% 76% 83% 87% 83% Liwale 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.50 LINDI Number and Percent of Households Using Grass/Leaves for Roofing Material by District Tanzania Agriculture Sample Census Number of Households Using Grass/Leaves for Roofing Number of Households Using Grass/Leaves for Roofing Number of Households Eating 3 Meals per Day Percent of Households Using Grass/Leaves for Roofing Map 3.51 LINDI Number and Percent of Households Eating 3 Meals per Day by District Percent of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day 87 Kilwa Lindi Urban Lindi Rural Ruangwa Nachingwea 2,720 137 7,654 4,588 3,391 934 9% 17% 4% 17% 10% 8% Liwale 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Lindi Urban Kilwa Lindi Rural Ruangwa Nachingwea 10,706 6,860 750 7,877 7,050 2,361 24% 22% 24% 29% 20% 21% Liwale 8,000 to 11,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Map 3.52 LINDI Number and Percent of Households Eating Meat Once per Week by District Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Number of Households Eating Fish Once per Week Percent of Households Eating Meat Once per Week Map 3.51 LINDI Number and Percent of Households Eating Fish Once per Week by District Percent of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week 88 Lindi Urban Lindi Rural Ruangwa Nachingwea 7,571 61 4,515 3,308 2,633 861 49 47 43 39 46 27 Liwale Kilwa 6,000 > 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Map 3.54 LINDI Number and percent of Households Reporting Food Insufficiency by District Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 89 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 3.7.7 Food Consumption Pattern 3.7.7.1 Number of Meals per Day The majority of households in Lindi region normally took 2 meals per day (51.3 percent of the households in the region). This was followed by 3 meals per day (41.4 percent) and 1 meal per day (7.1 percent). Only 0.2 percent of the households had 4 meals per day (Chart 3.152). Lindi Rural district had the largest percent of households eating one meal per day and had the highest percent of households eating 3 meals per day. (Table 3.17 and Map 3.64) 3.7.7.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 69,263 (45.2% of the agricultural households in Lindi region) with 35,604 households (51.4 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (30.9%). Very few households had meat three or more times during the respective week. About 54.8 percent of the agricultural households in Lindi region did not eat meat at all during the week preceding the census (Chart 3.153 and Map 3.65). 3.7.7.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 119,551 (78% of the total agricultural households in Lindi region) with 30,896 households (25.8 % of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish three times (20.9%). In general, the percentage of households that consumed fish twice or more during the week in Lindi region was 100,127 (83.8% of the agricultural households that ate fish in the region during the respective period). About 22 percent of the agricultural households in Lindi region did not eat fish at all during the week preceding the census (Chart 3.160 and Map 3.66). Table 3.17: Number of Households by Number of meals the household normally has per day and District Number of meals per day District One Meal % Two Meals % Three Meals % Four Meals % Total Kilwa 2,451 22.6 12,632 16.1 16,214 25.6 81 22.6 31,377 Lindi Rural 4,023 37.1 22,376 28.5 18,245 28.8 209 58.6 44,853 Nachingwea 1,904 17.5 21,249 27.0 12,013 18.9 0 0.0 35,167 Liwale 308 2.8 4,606 5.9 6,450 10.2 0 0.0 11,365 Ruangwa 2,063 19.0 16,808 21.4 8,284 13.1 67 18.8 27,222 Lindi Urban 104 1.0 889 1.1 2,195 3.5 0 0.0 3,189 Total 10,854 100.0 78,561 100.0 63,402 100.0 357 100.0 153,173 Chart 3.159 Number of Agriculural Households by Number of Meals per Day Four Meals, 357, 0.2% Two Meals, 78,561, 51.3% Three Meals, 63,402, 41.4% One Meal, 10,854, 7.1% Chart 3.152: Number of Agricultural Households by Number of Meals per Day Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 25,000 50,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Househ Meat Fish Chart 3.153: RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 3.7.8 Food Security In Lindi region, 50,993 households (33.3% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 11,975 (7.8%) said they sometimes experience problems, 16.4 often experienced problems and 9.9 percent always had problems in satisfying the household food requirement. About 32.5 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.7.9 Main Sources of Cash Income The main cash income of the households in Lindi region was from selling cash crops (40.9 percent of smallholder households), followed by selling of food crops (19.7%), casual labour (15.3%), businesses (6.9%) and cash remittances (5%).forest products (4.5%), fishing (2.5%) and wages/salaries (2.2%). Only 1.6% of smallholder households reported the selling of livestock as their main source of income, followed by other sources (0.8%) and livestock products (0.5%) (Chart 3.154) Chart 158 Distribution of the Number of Households by Main Source of Income Chart 3.54: Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Other, 0.8, 1% Food Crops, 19.7, 20% Cash Crops, 40.9, 41% Other Casual Cash Earnings, 15.3, 15% Business Income, 6.9, 7% Remittance, 5.0, 5% Wages & Salaries, 2.2, 2% Livestock Products, 0.5, 1% Forest Products, 4.5, 4% Fishing, 2.5, 2% Livestock, 1.6, 2% Chart 3.154: Distribution of Households by main Source of Income EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 4 LINDI PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Lindi Region Profile Lindi has a land area of 272,000 hectares under crop production and has one of the lowest numbers of annual crop growing households in Tanzania. Almost all smallholder households grow crops only and very few of them have livestock. The land area per crop growing household is 1.8 ha and it has a high percent of allocated land that is utilized. The region has a relatively high percent of permanent crops, some of which are in monocrop stands and the remainder in mixed annual/permanent crop. Lindi only has a long rainy season. Cereal production is relatively unimportant in Lindi and it has one of the lowest planted areas and yields of maize in the country. Small quantities of rice is produced, however it has the sixth largest planted area of sorghum. Lindi also has a moderate production of cassava and its low planted area per household suggests that most households grow small amounts. Beans are not grown in the region and only small amounts of groundnuts and vegetables are grown. Traditional annual cash crops are also not grown. Lindi has the third largest planted area of cashew nut, coconut and pigeon peas in the country and it has a moderate area under oranges compared to other regions. Lindi has virtually no planted area under irrigation, however there may have been a small increase in the number of households with irrigation over the period of 10 years. A relatively high percent of land clearing is done by burning and all cultivation by smallholders in the region is done by hand. No fertilizer or pesticides are applied. Storage of maize is practically zero. Lindi has the highest percent of storage in locally made traditional cribs. Compared to the other regions of Tanzania, the percent of smallholders selling crops in Lindi is average. Most processing of crops is done by hand and almost all the processed products are for home consumption. Lindi has the lowest contact with extension services in the country. It also has the lowest number of smallholder planted trees and very little erosion control/water harvesting facilities. 4.2 District Profiles The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Kilwa Kilwa district had the third largest number of agricultural households in the region and it had the fourth highest percent of households involved in smallholder agriculture in the region. It had the third largest number of smallholders involved in EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 crop farming only and was the third for smallholders involved in crop and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kilwa district was annual crop farming, followed by tree/forestry resources then off farm income. However, the district had the second least percent of households with no off- farm income generating activities and the highest percent of households with two or more household involved in off farm income generating activities. Compared to other districts in the region, Kilwa had a relatively high percent of female headed households (27%) and it had the least average age of the household head. Its average household size of 5 members per household was higher than the average for the region. Kilwa has the second least literacy rate for agricultural household members (57%) and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was the fourth highest in the region. It had the smallest utilized land area per household and the allocated area was fully utilized indicating a high level of land pressure. The total planted area was the third greatest in the region. Kilwa was the fourth most important district for maize production in the region with a planted area of 11,056 ha; and the planted area per household was also the fourth largest in the region. Paddy production was very important with a planted area of 5,970 hectares and the production of sorghum was the second highest in the region. Cassava production was the highest and accounted for 34 percent of the total quantity harvested in the region. Sweet potatoes production was also the highest and accounted for 39 percent of the quantity harvested in the region. The district had the second largest planted area of yams (31 ha) and it was among the three districts in the region that grew this crop. Beans were not produced in Kilwa district. Oilseed crops were not important in Kilwa but its production of bambaranuts was the third highest in the region. Vegetable production was less important in the district. It had the least area planted with tomatoes (7 ha) and its contribution to total production was negligible. Production of traditional cash crops was non existent in the district. Compared to other districts in the region, Kilwa has a moderate planted area with permanent crops which were dominated by coconut (5,541 ha), cashewnut (5,304 ha) and orange (1, 4371 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by tractor and oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Kilwa had the second least area planted with improved seed in Lindi region and this was due to the small planted area of vegetables. The district had the largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertiliser), however most of this was compost. Compared to other districts in the region, Kilwa district had the second highest level of insecticide use. The use of fungicides was the second least in the region. The district had the third least use of herbicide in the region. It also had the third least irrigated area (565) ha. The most common source of water for irrigation was from rivers using gravity. Flood and bucket were the most common means of water application. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 94 The most common method of crop storage was the locally made traditional crib. The proportion of households storing crops in the district was the fourth highest in the region. The district had the third largest number of households selling crops, however for those who did not sell, the main reason for not selling was the low open market price. The least percent of households processing crops in Lindi region was found in Kilwa district, most of the processing was done by hand on farm. The district had the second highest percent of households selling processed crops to neighbours in the region, which was the only main selling point including other unspecified selling points. Although very small, access to credit in the district was to both male and female headed households and the main sources of credits were unspecified. A comparatively small number of households received extension services in Kilwa and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not important in Kilwa district with zero planted trees. The use of erosion control and water harvesting structures were not found in Kilwa district. The district had no cattle, sheep or pigs. Goat production was the second largest in the region and had the second largest number of chickens. The district had no layers. The district had moderate numbers of ducks and no donkeys or rabbits. It had the fourth largest number of households that reported tsetse flies problems and the third largest number of households that reported tick problems and it had the least number of households de-worming livestock. The use of draft animals in the district was insignificant while fish farming was not practiced. It had amongst the best access to primary schools and feeder roads compared to other districts. However, it had one of the worst access to district capital, hospital and tertiary markets. Kilwa district had the largest percent of households without toilet facilities and it had the third highest percent of households owning bicycles, pressing iron and the second highest percent of household with radio. The district had insignificant percent of household with wheelbarrow, television/video and landline phone. Moreover, there was none in the district with mobile phones and vehicles. It had the second largest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had small percent of households with grass roofs and moderate percent of households had iron sheet roofs. The most common source of drinking water was the unprotected well. It had the highest percent of households having three meals per day and the lowest percent having two meals per day. The district had the third highest percent of households that did not eat meat and had the highest percent of household that did not eat fish during the week prior to enumeration; however few households seldom had problems with food satisfaction. 4.2.2 Lindi Rural Lindi Rural district had the largest number of agricultural households in the region and it had the second least percentage of households involved in smallholder agriculture. Most smallholders were involved in crop and livestock production, followed by crops only. It had no households raising livestock only or pastoralists in the district. The most important livelihood activity for smallholder households in Lindi Rural district was annual crop farming, followed by off farm income. The district had the least percent of households whose members were not involved in off- farm income generating activities and also had the second highest percent of households with two or more members EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 95 involved in off-farm income generating activities. Compared to other districts in the region, Lindi Rural had a relatively high percent of female headed households (27%) and it had one of the third highest average age for the household head in the region. Its household size of 4 members per household was average for the region. Lindi Rural had the least literacy rate for agricultural household members and this was reflected by the district having low level of school attendance in the region. It had a moderate utilized land area per household (1.7ha) and 82 percent of the allocated area was currently being utilised. The district had the largest planted area in the region, and the third least planted area per household (2.1 ha). The district was moderately important for maize production in the region with a planted area of 14,876 ha, and the planted area per maize growing household was the smallest in the region. Paddy production was important in the district and it had the highest planted area in the region. The district had the largest area planted with sorghum in the region with 10,850 hectares. Cassava production was the highest in the region with a planted area of 12,845 hectares. Sweet potatoes and yams were grown in small quantities while Irish potatoes were not grown in the district. The production of beans in Lindi Rural district was the highest in the region with a planted area of 113ha. Lindi Rural district had the largest groundnut planted area in Lindi region with a planted area per groundnut growing household of 0.4 ha. Vegetable production was moderately important in the district. Although small, it had the largest planted area for tomatoes (158 ha). Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Lindi Rural had the third largest planted area for permanent crops which were dominated by cashewnut (12,404 ha), coconut (1,756 ha) and pigeon pea (1,217 ha). Other permanent crops were either not grown or were grown in very small quantities. As with most districts in the region, most land clearing and preparation was done by hand, with the highest amount of land preparation in Lindi Rural district being done by oxen. The use of inputs in the region was very small, however district differences existed. Lindi Rural district had the fourth largest area planted with improved seeds in the region and had the least proportion of households using improved seeds. The district had the second largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertiliser) and most of these were compost manure. Compared to other districts in the region, Lindi Rural district had the third highest level of insecticide use. The use of fungicides, although small, was also the third highest compared to other districts. Application of herbicides was the second highest. It had the second largest irrigated area (961 ha). The most common source of water for irrigation was from river using gravity. Flood was the major means of water application. The most common method of crop storage in Lindi Rural district was the locally made traditional crib. The proportion of households storing crops in the district was relatively high. Lindi Rural district was one of the districts with a moderate number of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. Lindi Rural was among the districts with the highest percent of households processing crops in Lindi region and most of the processing was done by hand on farm. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 A comparatively small number of households received extension services in Lindi Rural district and all the services were from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming was not important in Lindi Rural (with 1,097 planted trees) and most of the trees were Trichilia species, Melicia excelsa and Eucalyptus species. The third highest proportion of households with erosion control and water harvesting structures was found in Lindi Rural district and most of these were erosion control bunds. The district had the largest number of cattle in the region and almost all of them were indigenous. Goat and sheep production were the highest compared to other districts while pig production was not practiced in the district. The district had the largest number of chickens also some ducks and turkeys. Donkeys and rabbits were not found in the district. In Lindi Rural a few households reported tsetse fly problems and many reported tick problems but it had the highest number of households de-worming livestock. The use of draft animals in the district was insignificant. Fish farming was not practiced in the district. It had amongst the poorest access to secondary schools, hospitals, district capital, regional capital and tertiary market compared to other districts. The percentage of households without toilet facility in Lindi Rural district was 21 percent and was among the districts with the highest percent of households owning radio. Also, the district had zero percentage of households with vehicles, bicycles, tv/video, land line and mobile phones. It had a small number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing material for most of the households in the district was grass/leaves (29.9%) followed by iron sheets (29.7%). The most common source of drinking water was the unprotected well water. It was one of the districts with the second highest percent of households having two meals per day. The district had the highest percent of households that did not eat meat and the third highest district that did not eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.3 Nachingwea Nachingwea district had the second highest number of agricultural households in the region and it had the second highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop production, followed by crop and livestock. Households involved in livestock only and pastoralists were not found in the district. The most important livelihood activity for smallholder households in Nachingwea district was annual crop farming, followed by permanent crop farming. However, the district had the fourth highest percent of households with no off-farm income generating activities and also the fourth highest percent of households with two or more members involved in off- farm income generating activities. Compared to other districts in the region, Nachingwea had the fifth highest percent of female headed households (26.5%) and it had one of the highest average ages for the household heads in the region. Its average household size of 4 members per household was average for the region. Nachingwea had the highest literacy rate for agricultural household members and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household was the second highest in the region. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 It had a slightly higher utilized land area per household (2.3ha) than the regional average of 2.2 ha and 89 percent of the allocated area was currently being utilised. The total planted area was greater than in other districts in the region due to the presence of good wet and dry seasons, however it had moderate planted area per household (2.1ha). The district was the most important maize producer in the region with a planted area of about 22,714 ha, however the planted area per household at 0.66 ha was the second highest in the region. Paddy was also important in the district with a total planted area of 2,183 ha. The district had the third highest production of sorghum (6,638 ha). Small quantities of sweet potatoes and yams were produced in the district. The district had the second largest planted area of cassava accounting for 26 percent of the cassava planted area in the region with a planted area of 11 ha, the production of beans in Nachingwea was the least among the four districts that produced beans in the region. Oilseed crops were not important in Nachingwea which mainly produced simsim (4,262ha) and groundnuts (1,142ha). Vegetable production was not important in the district. Traditional cash crops (tobacco and cotton) were not grown in the district. Nachingwea district had the largest percent of the area under permanent crops (28% of the total permanent crop planted area in Lindi region was found in the district). The most prominent permanent crops in the district included cashewnut (13,521 ha) and pigeon pea (9,012 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand. The use of inputs in the region was very small, however district differences existed. Nachingwea had the second largest area planted with improved seeds in Lindi region and this was due to the dominance of cashewnut crop whose most of the new seedlings came from improved seeds. The district had the second least planted area applied with fertilizers (farm yard manure, compost and inorganic fertiliser), and compost manure was the most common fertilizer used. Compared to other districts in the region, Nachingwea district had the highest area applied with fungicides and the third largest area applied with herbicides. The use of pesticides was relatively moderate. It had the third largest irrigated area (753 ha). The most common source of water for irrigation was from well using hand bucket. Bucket/watering cans was the most common means of water application. The most common method of crop storage in Nachingwea was the locally made traditional crib; however the proportion of households storing crops in the district was the highest in the region. The district had the second highest percent of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. Nachingwea district had the second highest percent of households processing crops in the region and most of the processing was done by neighbours machine. However, the district had the third highest percent of households processing crops by trader. The district had the second highest percent of households selling processed crops. Only female households in the district accessed credit. A comparatively smaller number of households received extension services in Nachingwea district and most of the service were from the government. The quality of extension services was rated between very good and good by the majority of the households. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 Tree farming was not important in Nachingwea district with zero planted trees. The highest proportion of households with water harvesting bunds was found in Nachingwea district and it also with the largest number of erosion control bunds. The district had the third largest number of cattle in the region and most of these were indigenous. Goat and sheep production were the third largest compared to other districts. It had the largest number of pigs in the region and third largest number of chickens. The largest number of layers was found in the district. The district had small number of ducks, turkeys and donkeys however it had no rabbits. A small number of households reported tsetse fly and tick problems. The district had the fourth largest number of households de-worming livestock in Lindi. The use of draft animals in the district was insignificant. It had amongst the best access to feeder roads, primary schools, and all weather roads compared to other districts. However, it had one of the worst accesses to regional capital, tarmac roads, district capital and tertiary market. Nachingwea district had the second highest percent of households with no toilet facilities and it had no households owning landline, television/video and vehicle. Small percentage of households had mobile phones and pressing iron. The use of mains electricity in the district was nonexistence. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had high percent of households with grass roofs (83%) with 16 percent of households having iron sheets. The most common source of drinking water was the unprotected well. Twenty seven percent of the households in the district reported having two meals per day and virtually no household reported having more than four meals per day with (19%) of the households having three meals per day. The district had the second highest percent of households that did not eat meat and the third highest percent of household that did not eat fish during the week prior to enumeration; however few households seldom had problems with food satisfaction. 4.2.4 Liwale Liwale district had the second least number of agricultural households in the region and it had amongst the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. It had zero number of livestock only and pastoralists in the district. The most important livelihood activity for smallholder households in Liwale district was annual crop farming, followed by tree/forest resources then permanent crop farming. However, the district had the largest percent of households with no off-farm income generating activities and the fifth largest percent of households with two or more household members involved in off farm income generating activities. Compared to other districts in the region, Liwale had the least percent of female headed households (12.2%) and it had the second lowest average age for the household heads. Its average household size of 5 members per household was higher than the regional average. Liwale had the second highest literacy rate for agricultural household members and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for heads of household was the second highest in the region. It had the highest utilized land area per household (3.1 ha) and the allocated area was fully utilised indicating a high level of land pressure. The total planted area was greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (3.4 ha) attributed to the high number of smallholders in the district. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 The district was moderately important for maize production in the region with a planted area of over 7,658 ha, however the planted area per household was the highest in the region. Paddy production was not important with a planted area of only 984 hectares and the production of sorghum was moderate (4,273 ha). Liwale was among the districts that did not produce wheat or Irish potatoes. The district was a moderate producer of cassava (4,563 ha). The production of beans in Liwale was small. Oilseed crops were not important in Liwale and simsim was the mostly grown (1,836 ha) followed by groundnuts (699 ha). Vegetable production was not important in the district. The crops grown includes tomatoes (43 ha), okra (72 ha) and onions (31 ha). Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Liwale had the second smallest area planted with permanent crops which were dominated by cashewnut (10,807 ha) mango (657 ha), coconut (293 ha) and pigeon peas (143 ha). Other permanent crops were either not grown were produced in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand. The use of inputs in the region was very small, however district differences existed. Liwale had the third largest area planted with improved seeds in Lindi region. The district had the fourth largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertiliser) and most of these were compost manure. Compared to other districts in the region, Liwale district had low level of insecticides use. The use of fungicides was second highest while the use of herbicides was low compared to other districts. It had the third largest irrigated area in the region (278 ha). The most common source of water for irrigation was from rivers using hand bucket. Bucket /watering can was the most common means of water application. The most common method of crop storage was the locally made traditional crib while other methods were used by small number of households. The district had the highest percentage of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. The fourth highest percent of households processing crops in Lindi region was found in Liwale district and most of the processing was done by neighbours machine. The district had a high percent of households selling processed crops to neighbours and no sales were made to traders on farm. Although very small, access to credit in the district was to both male and female headed households and the main sources of credit were religious organisation/NGO/project. A comparatively large number of households received extension services in Liwale and all the services were from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Liwale (with 142 planted trees) and most of these were Eucalyptus species. The lowest proportion of households with erosion control and water harvesting structures was found in Simanjiro district and most of these were erosion control bunds; however it also has high number vetiver grass. The district had no cattle more over it had the least number of goats (6,515) in the region and had the fourth largest number of sheep (926). It had no pigs but had the fifth largest number of chickens. Although small, the district had the second largest number of layers in the region. The district had a moderate number of ducks, turkeys and the largest number of donkeys. The district had the second largest number of households reporting tsetse fly and tick problems was in Liwale and EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 100 it had the second least percentage of households de-worming livestock. The use of draft animals in the district was nonexistence and fish farming was not practiced It was amongst the districts with the best access to feeder roads and primary schools compared to other districts. However, it had one of the worst accesses to regional capital, tarmac roads secondary schools, district capital and tertiary market. Liwale district had the second least percent of households with no toilet facilities and it had the lowest percent of households owning radio, pressing iron and bicycle. It had the third highest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had amongst the smallest percent of households with grass roofs, with 10 percent of households having iron sheets. The most common source of drinking water was from unprotected well. It had the second least percent of households having two meals per day and also the second lowest percent with 3 meals per day. The district had the second lowest percent of households that did not eat meat and fish during the week prior to enumeration, however very few households seldom had problems with food satisfaction. 4.2.5 Ruangwa Ruangwa district had the fourth largest number of agricultural households in the region and it had a high percentage of households involved in smallholder agriculture in the region. Most smallholders were involved in crop production only followed by crop and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Ruangwa district was annual crop farming, followed by tree/forest resources. The district has the second highest percent of households with no off-farm income generating activities and it had the least percent of households with two or more household members involve in off farm income generating activities. Compared to other districts in the region, Ruangwa had the highest percent of female headed households (31%) and it had the second highest average age for the household heads in the region. The average household size of 4 members per household was the same as the average for the region. Ruangwa has a moderate literacy rate among agricultural household members. The literacy rate for the heads of household was the third highest in the region. It had a moderate utilized land area per household (1.7ha) and 87 percent of the allocated area was currently being utilised. The district had the moderate planted area in the region, and the second least planted area per household (1.9ha). The district was important for maize production in the region with a planted area of over 14,191 ha, and the planted area per household was the third highest in the region. The district had a small area planted with paddy (297 ha) but the production of sorghum was high (5,108 ha). Cassava production was moderately high, accounting for 13 percent of the quantity harvested in the region. The district had no planted area for Irish potatoes. The production of beans in Ruangwa was low in the region with a planted area of 22 ha. Ruangwa district had the second least area planted with groundnuts in Lindi region and the area planted per groundnut growing household was 0.27 ha. Vegetable production was not important in the district and the vegetables produced were mainly onion (107 ha) and tomatoes (66 ha). The traditional cash crops (e.g. tobacco and cotton) were not grown EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 101 Compared to other districts in the region, Ruangwa had the second largest area planted with permanent crops which were dominated by cashewnut (13,403 ha), pigeon peas (3,095 ha), orange (306 ha), banana (139 ha), and coconut (109 ha). Other permanent crops were either not grown or were produced in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand. The use of inputs in the region was very small, however district differences existed. Ruangwa had the largest area planted with improved seeds in the region as well as the highest proportion of households using improved seeds. The district had moderate planted area applied fertilizers (farm yard manure, compost and inorganic fertilisers), and most of these were compost manure. Compared to other districts in the region, Ruangwa district had a moderate level of insecticides use. The use of fungicides in the district was low. Though, the use of herbicides was low in the district but it was the highest in the region (569 ha). It had the highest irrigated area (1,272 ha). The most common source of water for irrigation was from well using hand bucket. Bucket/watering can were the most common means of water application. The most common method of crop storage in Ruangwa district was the sacks/open drum, however the proportion of households not storing crops in the district was relatively low compared to other districts in the region. Ruangwa district was one of the districts with a moderate number of households selling crops, however those that did not sell, the main reason for not selling was insufficient production. Ruangwa had the second highest percent of households processing crops in Lindi region and most of the processing was done by neighbours machine. The district had credit facilities accessed by males only. A comparatively moderate number of households received extension services in Ruangwa district and mainly all of it was from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming was important in Ruangwa (with 1,252 planted trees) and most of these were Senna species and Azadritacht species. The erosion control and water harvesting structures were not found in Ruangwa district. The district had no cattle but had the fourth largest number of goats, the second largest number of sheep, the second largest number of pigs and the fourth largest number of chickens. It had the second largest number of ducks and turkeys. Donkeys were not found in the district. A small number of households reported tsetse fly and tick problems and it had the second highest number of households de-worming livestock. A very small number of households practiced fish farming. It had amongst the best access to primary schools, feeder roads, all weather roads and health clinics compared to other districts. However, it had one of the worst accesses to regional capital and tarmac road. The percentages of households without toilet facility in Ruangwa district was 14 percent. It was among the districts with the lowest percent of households owning pressing iron, bicycles and radio. It had the largest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing material for most of the households in the district was grass/leaves and iron sheets. The most common source of drinking water was the unprotected wells. It was one of the districts with EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 moderate percent of households having two and one meals per day. The district had moderate percent of households that did not eat meat and fish during the week prior to enumeration, however small number of households seldom had problems with food satisfaction. 4.2.1 Lindi Urban Lindi Urban district had the least number of agricultural households in the region and it had the second least percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock farming, followed by livestock only and crops only. Pastoralists were not found in the district. The most important livelihood activity for smallholder households in Lindi Urban district was annual crop farming, followed by off farm income and permanent crop farming. The district had the third highest percent of households with no off-farm income generating activities and also the third highest percent of households with two or household members involved in off farm income generating activities. Compared to other districts in the region, Lindi Urban had the second highest percent of female headed households (27.9%) and it had the highest average age for the household heads. Its average household size of 4 members per household was equal to the average for the region. Lindi Urban had a comparatively high literacy rate among smallholder household members and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of households was the least in the region. It had moderate utilized land area per household (1.9 ha) and the allocated area was by 83 percent utilized. It had the second largest planted area per household (2.3 ha) in the region. The district was the least important for maize production in the region with a planted area of about 975 ha; and the planted area per household was the second lowest in the region. Paddy production was not important with a planted area of only 168 hectares and the production of sorghum was the least in the region. Cassava production was small accounting for 2 percent of the quantity harvested in the region. Oilseed crops were not important in Lindi Urban district. Vegetable production was also not important in the district. Traditional cash crops (e.g. tobacco and cotton) were not grown. Compared to other districts in the region, Lindi Urban had the smallest area planted with permanent crops which were dominated by coconut (680 ha), cashewnut (243 ha) and pigeon peas (39 ha). Other permanent crops were either not grown or small quantities were produced. As with other districts in the region, most land clearing and preparation was done by hand. The use of inputs in the region was very small, however district differences existed. Lindi Urban had the least planted area with improved seeds in Lindi region and this was due to the small planted area of vegetables. The district had a small area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), most of which were farm yard manure. Compared to other districts in the region, Lindi urban district had the least level of insecticide use. The use of fungicides was very small as compared to other districts. Virtually no herbicide was used. It had the second least area under irrigation compared to other districts with 383 ha of irrigated land. EVALUATION AND CONCLUTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 The most common method of crop storage was in locally made traditional cribs, however the proportion of households storing crops in the district was lower than in other districts in the region. The district had moderate number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. The second least percent of households processing crops in Lindi region were found in Lindi Urban district and the processing was almost all done by hand. There was no household that accessed credit in the district. A comparatively small number of households receive extension services in Lindi Urban and all the services were from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is important in Lindi Urban (with 321 planted trees) and was mostly Senna species. The practice of erosion control and water harvesting structures is never done in Lindi Urban. The district had the second largest number of cattle in the region and they were almost all indigenous. Goat production was small compared to other districts; It had the least population of sheep in the region. Pigs were not found in the district , it had the smallest number of chickens. Although small, the district had the third largest number of layers in the region. The district had the second largest number of ducks and small number of turkeys. The largest numbers of households reporting tsetse fly and tick problems were in Lindi Urban district but it had the second largest number of households de-worming livestock. It had amongst the best access to feeder roads, all weather roads, primary schools, health clinics and primary market compared to other districts. However, it had the worst access to secondary market. Lindi urban district had the least percent of households with no toilet facilities and it had the lowest percent of households with landlines, mobile phones, wheel barrow and television/video. It had amongst the lowest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the highest percent of households with grass (75.6%) and 23 percent of households having iron sheets. The most common source of drinking water was the unprotected well. It had the highest percent of households having two or one meal per day compared to other districts and the lowest percent with 3 meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. APPENDIX II 104 4. APPENDICES Appendix I Tabulation List .................................................................................................. 105 Appendix II Tables ................................................................................................................ 123 Appendix III Questionnaires.................................................................................................. 267 APPENDIX II 105 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD................................................................................ 123 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year .................................................................................................. 124 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year ............................................................................................................... 124 NUMBER OF AGRICULTURE HOUSEHOLDS ...................................................................... 125 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .......................................................... 126 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance ......................................................................................................................... 126 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES ................................................. 127 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance......... 128 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance .... 128 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance........ 128 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance..... 128 HOUSEHOLDS DEMOGRAPHS................................................................................................. 129 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) ................................................................................................. 130 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) ........................................................................................... 130 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year ............................................................................................................... 131 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year....................... 131 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year .................................................................................. 131 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year ............................................................................................................... 131 APPENDIX II 106 cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ............................................................................................................... 132 cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ............................................................................................................... 132 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year .............................................................. 132 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year......................................................... 133 cont... Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year......................................................... 133 cont... Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year ................................................................................... 133 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .......................................................... 134 3.11 Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year ............................ 134 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year ................................................................................... 134 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District ................ 134 3.14 Time Series of Male and Female Headed Households ...................................................... 135 3.15 Literacy Rate of Heads of Households by Sex and District............................................... 135 LAND ACCESS/OWNERSHIP..................................................................................................... 137 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year ................................................................................................. 138 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year.................................................................................................................................... 138 LAND USE....................................................................................................................................... 139 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ............................................................................................................... 140 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year. 140 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year........................................ 141 APPENDIX II 107 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year .................................... 141 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year ............ 141 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS...... 143 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by District. .................... 144 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District............. 144 7.1 and 7.2c Area planted (ha) and Quantity Harvested byCrop for the 2002/03 agriculture year, Lindi Region........................................................................................................ 145 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Lindi Region ......................................................................... 146 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District, LINDI......................................................................................... 147 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year, LINDI.............................................. 147 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year....................................... 147 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season. .................................... 148 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season. .................................... 148 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet Season. .................................... 149 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet Season............................. 149 ANNUAL CROP & VEGETABLES PRODUCTION DRY SEASON...................................... 151 7.1a Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, LINDI Region ............. 152 7.1b Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during WET Season, 2002/03 Agriculture Year, LINDI Region................... 152 7.1c Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - WET Season........................................... 153 APPENDIX II 108 7.1d Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - WET Season.......................................... .153 7.1e Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET Season.................................................. 154 7.1f Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON.................................................................... 154 ANNUAL CROP & VEGETABLES PRODUCTION WET SEASON..................................... 155 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, LINDI Region......................................................................................... 156 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, LINDI Region.................... 156 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, LINDI Region............................ 156 7.2d: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year ................................. 157 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year..................................................... 158 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 158 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 159 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 159 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 160 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 160 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 160 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of COW PEAS Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 161 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of BAMBARANUTS Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 161 APPENDIX II 109 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of GREEN GRAM Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 162 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 162 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ..................... 163 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of YAMS Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 163 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 163 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 164 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 165 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 165 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 165 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 166 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 166 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 166 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 167 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 167 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 167 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year.................................... 167 APPENDIX II 110 PERMANENT CROPS 7.3.1 Production of Permanent Crops by Crop Type and District - LINDI......................................... 169 7.3.2 Area Planted by Crop Type - LINDI Region............................................................................. 172 7.3.3 Area Planted with Pigeon peas by District.................................................................................. 172 7.3.4 Area planted with Oranges by District........................................................................................ 173 7.3.5 Planted Area with Fertilizer by Fertilizer Type and Crop........................................................... 174 cont… Planted Area with Fertilizer by Fertilizer Type and Crop........................................................ 175 AGROPROCESSING........................................................................................................................ 177 8.1.1a Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Lindi Region................... 178 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Lindi Region178 8.1.1c Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Lindi Region ............................................................................................ 179 8.1.1d Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Lindi Region.................................................................. 179 8.1.1e: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year ..................................................................................................... 180 8.1.1f Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year .................................................................................................................. 180 8.1.1g Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Lindi Region ....................................................... 180 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year,Lindi Region................................................................... 181 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Lindi Region.................................................................. 181 MARKETING .................................................................................................................................... 183 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Lindi Region................................................................................. 184 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Lindi Region.............................................. 184 APPENDIX II 111 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Lindi Region..................................................... 184 IRRIGATION/EROSION CONTROL............................................................................................ 187 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District ................................................................................................. 188 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year188 11.3: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year .................................................................... 188 11.4: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year............................................................................ 188 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year..................................................................... 189 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District.................................................................................................................... 189 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year................................................................................................ 189 ACCESS TO FARM INPUTS/ IMPLEMENTS............................................................................. 190 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................................................ 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................................................ 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................................................ 12.1.4 Number of Agricultural Households Using Pesticides/ Fungicides by District, 2002/03 Agricultural Year ........................................................................................................................ 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year............................................................................................................................................. 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ........................................................................................................................ 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................................................... 191 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year .................................................................................................... 191 APPENDIX II 112 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .................................................................................................... 191 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year .................................................................................................................. 192 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year .................................................................................................................. 192 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year .................................................................................................................. 192 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ...................................................................................... 193 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ...................................................................................... 193 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ...................................................................................... 193 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ...................................................................................... 193 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year .................................................................................................... 193 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................... 194 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................. 194 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year.................................................................... 194 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year.................................................................... 195 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/ Fungicides by District, 2002/03 Agricultural Year............................................................... 195 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year ................................................................................. 195 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year....................................................................... 195 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................. 196 APPENDIX II 113 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year.................................................................... 196 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ...................................................................................... 196 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ...................................................................................... 197 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .................................................................................................... 197 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................... 197 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................................................... 198 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year .................................................................................................... 198 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year .................................................................................................... 198 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year .................................................................................................... 199 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year .................................................................................................................. 199 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year .................................................................................................................. 199 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year ...................................................................................... 199 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ...................................................................................... 200 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ...................................................................................... 200 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year ...................................................................................... 200 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year .................................................................................................... 201 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year....................................................................................................................................... 201 ACCESS TO EQUIPMENT ................................................................................................................... APPENDIX II 114 12.2. 1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03.............. 201 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year ...................................................................................... 201 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District......................................................................................................... 202 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District....................................................................................... 202 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District .................................................................................................................. 202 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District......................................................................................................... 202 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District....................................................................................... 203 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District......................................................................................................... 203 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District......................................................................................................... 203 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District....................................................................................... 203 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District....................................................................................... 204 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District ............................................................................. 204 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District............................................................................................................................ 204 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District.............................................................................................. 204 12.2.15 Number of Agricultural Households Owning OX Plough by Source of Finance and District............................................................................................................................ 205 12.2.16 Number of Agricultural Households Owning TRACTOR by Source of Finance and District............................................................................................................................ 205 APPENDIX II 115 AGRICULTURE CREDIT ............................................................................................................... 207 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year .............................................................. 208 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. .................................................................................................... 208 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year ...................................................................... 209 13. Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year ..................................................................................................... 209 TREE FARMING AND AGROFORESTRY.................................................................................. 211 14.1 Number of Households Having Planted Trees By District.................................................. 212 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District ........................................................................... 212 14.3 Number of Planted Trees By Species and District................................................................ 212 14.4 Main Use of Trees By District .............................................................................................. 212 14.5 Second Use of Trees By District.......................................................................................... 212 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District ............................................................................................................... 213 14.3 Number of Households By Distance to Community Planted Forest (Km) By District ....... 213 14.3 Number of Households Involved in Community Tree Planting Scheme By Main Use and District..................................................................................................................... 213 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Lindi Region .............................................................................................. 214 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Lindi Region..................... 214 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Lindi Region .............................................................................................. 214 CROP EXTENSION.......................................................................................................................... 215 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Lindi Region .............................................................................. 216 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Lindi Region............................................................................. 216 APPENDIX II 116 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region............................................... 216 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region....... 217 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 217 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region....... 217 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region....... 218 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 218 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 218 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi... 219 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region ......................................................................................................................... 219 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region....... 219 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 220 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 220 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region .. 220 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region....... 221 15.17 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Lindi Region221 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Lindi Region........ 221 APPENDIX II 117 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Lindi Region........ 222 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Lindi Region........ 222 ANIMAL CONTRIBUTION TO CROP PRODUCTION............................................................. 223 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Lindi Region........................................................ 224 17.2 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Lindi Region ................................................................................ 224 17.3 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Lindi Region .............................................................................................. 224 CATTLE PRODUCTION................................................................................................................. 225 18.1 Number of Cattle By Type and District as of 1st October, 2003.......................................... 226 18.2 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 ................................................................. 226 18.3 Number of Cattle by Category and Type of Cattle; on 1st October 2003............................. 226 18.4 Number of Indigenous Cattle By Category and District as on 1st October, 2003................ 226 18.5 Number of Improved Beef Cattle By Category and District as on 1st October, 2003.......... 227 18.6 Number of Improved Dairy Cattle By Category and District as on 1st October, 2003........ 227 18.7 Number of Cattle By Category and District as on 1st October, 2003................................... 227 GOATS PRODUCTION ................................................................................................................... 229 19.1 Total Number of Goats by Type and District as on 1st October, 2003................................. 230 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003......................... 230 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District231 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003......... 231 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003...... 231 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003............... 232 19.7 Total Number of Goats by Category and District on 1st October, 2003.............................. 232 APPENDIX II 118 SHEEP PRODUCTION .................................................................................................................... 233 20.1 Total Number of Sheep By Breed and on 1st October 2003................................................. 234 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 ....... 234 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 ......................... 234 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003................. 234 20.5 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003........ 235 20.6 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ........ 235 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003........................... 235 PIGS PRODUCTION........................................................................................................................ 237 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 ................................... 238 21.2 Number of Households and Pigs by District on 1st October 2003 ....................................... 238 21.3 Number of Pigs by Type and District on 1st October, 2003................................................ 238 LIVESTOCK PESTS AND PARASITE CONTROL..................................................................... 239 22.1 Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year......................................................................................... 240 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year .............................................. 240 22.3: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District................................................. 240 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year .............................................................. 241 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District.................................... 241 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year....................................................... 241 OTHER LIVESTOCK ...................................................................................................................... 243 23a Total Number of Other Livestock by Type on 1st October 2003 ......................................... 244 23b Number of Chicken by Category of Chicken and District on 1st October 2003 .................. 244 23c Head Number of Other Livestock by Type of Livestock and District.................................. 244 APPENDIX II 119 23d Number of households with chicken and Category of Chicken by Flock Size..................... 244 23e LIVESTOCK/POULTRY POPULATION TREND ............................................................ 244 FISH FARMING................................................................................................................................ 245 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year .................................................................................................................. 246 28.2 Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year .................................................................................................................. 246 28.3 Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year .................................................................................................... 246 28.4 Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year .................................................................................................... 246 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year ............ 246 LIVESTOCK EXTENSION ............................................................................................................. 247 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year................................................. 248 29.7 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year ............................... 248 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ............... 248 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year.............. 248 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.............................................................. 249 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year.................................... 249 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .................................................................................................... 249 ACCESS TO INFRASRUCTURE AND OTHER SERVICES ..................................................... 251 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts ... 252 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year...................................................................................................................... 252 APPENDIX II 120 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year...................................................................................................................... 253 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year...................................................................................................................... 253 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year...................................................................................................................... 254 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year .................................................................................................................... 254 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year .......... 254 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year...................................................................................................................... 255 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year...................................................................................................................... 255 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year .................................................................................................................... 255 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year .................................................................................................................... 256 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year .................................................................................................................... 256 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year .................................................................................................................... 256 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .................................................................................................... 257 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year .................................................................................................... 257 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year................................................................................ 257 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ...................................................................................... 258 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year .................................................................... 258 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year.................................................................... 258 APPENDIX II 121 HOUSEHOLD FACILITIES............................................................................................................ 259 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year ................................................................................................................... 260 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ................................................................. 260 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year......................................................................................... 260 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year......................................................................................... 261 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year......................................................................................... 261 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year............................................... 262 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year............................................... 262 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year .......................... 263 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year .......................... 263 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District ...................................................................................................... 264 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District .................................................................................................. 264 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District .................................................................................................. 265 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.............................................................................................. 265 34-14: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year................... 265 34.15: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .................................................................................................................. 267 34.16: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year ................................................................................................................... 266 APPENDIX II 122 APPENDIX II: CROP TABLES Type of Agriculture Household ......................................................................................................................... 123 Number of Agriculture Households.................................................................................................................... 125 Rank of Importance of Livelihood Activities..................................................................................................... 127 Households Demography.................................................................................................................................... 129 Land Access/Ownership ..................................................................................................................................... 137 Land Use………………..................................................................................................................................... 139 Total Annual Crop and Vegetable Production Long and short Seasons............................................................ 151 Annual Crop and Vegetable Production Long Rainy Seasons ........................................................................... 155 Permanent Crop Production................................................................................................................................ 177 Agro-processing ............................................................................................................................................ 184 Marketing ............................................................................................................................................ 183 Irrigation/Erosion Control................................................................................................................................... 187 Access to Farm Inputs ........................................................................................................................................ 190 Agriculture Credit ............................................................................................................................................ 207 Tree Farming and Agro-forestry......................................................................................................................... 211 Crop Extension ............................................................................................................................................ 215 Animal Contribution to Crop Production ........................................................................................................... 223 Cattle Production ............................................................................................................................................ 225 Goat Production ............................................................................................................................................ 229 Sheep Production ............................................................................................................................................ 233 Pig Production ............................................................................................................................................ 237 Livestock Pests and Parasite Control.................................................................................................................. 239 Other Livestock ............................................................................................................................................ 243 Fishing Farming ............................................................................................................................................ 245 Livestock Extension............................................................................................................................................ 247 Access to Infrastructure and other services ........................................................................................................ 251 Household Facilities ........................................................................................................................................... 259 Appendix II 123 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census-2003 Lindi Appendix II 124 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Kilwa 31,377 95 1,522 5 32,898 37 56,995 63 89,893 Lindi Rural 44,853 94 2,913 6 47,766 84 8,797 16 56,563 Nachingwea 35,167 99 202 1 35,369 70 15,508 30 50,877 Liwale 11,365 98 199 2 11,564 11 92,719 89 104,283 Ruangwa 27,222 99 337 1 27,560 37 47,354 63 74,914 Lindi Urban 3,189 79 839 21 4,028 1 372,502 99 376,530 Total 153,173 96 6,011 6 159,185 40 593,875 60 753,060 Number of households % Number of households % Number of households % Number of households % Kilwa 28,733 21 68 43 2,576 17 31,377 20 31,309 20 2,644 Lindi Rural 39,049 28 0 0 5,804 39 44,853 29 44,853 29 5,804 Nachingwea 32,468 24 0 0 2,699 18 35,167 23 35,167 23 2,699 Liwale 10,703 8 54 34 608 4 11,365 7 11,310 7 662 Ruangwa 24,669 18 0 0 2,553 17 27,222 18 27,222 18 2,553 Lindi Urban 2,412 2 36 23 741 5 3,189 2 3,153 2 777 Total 138,034 100 159 100 14,981 100 153,173 100 153,015 100 15,139 Total Number of Households Growing Crops 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year District Agriculture, Non Agriculture and Urban Households Total Number of Households Rearing Livestock Crops Only Livestock Only Crops & Livestock Total Total Number of Agriculture Households District Type of Agriculture Household Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 125 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census-2003 Lindi Appendix II 126 Number % Average Household Size Number % Average Household Size Number % Kilwa 72,176 49 5 76,237 51.4 4 148,413 100 5 Lindi Rural 83,927 46 96,729 53.5 180,656 100 Nachingwea 66,706 47 5 74,282 52.7 4 140,989 100 5 Liwale 29,023 50 5 29,597 50.5 5 58,620 100 5 Ruangwa 50,073 48 4 54,170 52.0 4 104,243 100 4 Lindi Urban 6,521 48 5 6,959 51.6 4 13,480 100 4 Total 308,426 48 5 337,974 52 4 646,400 100 5 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittance s Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 1 4 7 3 5 6 2 Lindi Rural 1 4 6 2 5 7 3 Nachingwea 1 2 5 4 6 7 3 Liwale 1 3 5 4 6 7 2 Ruangwa 1 3 5 4 6 7 2 Lindi Urban 1 3 5 2 6 7 4 Total 1 4 5 3 6 7 2 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size District Male Female Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 127 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census-2003 Lindi Appendix II 128 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 8,636 10,673 78 5,846 1,501 2,151 2,221 Lindi Rural 17,923 7,794 1,431 11,386 3,124 1,238 1,523 Nachingwea 9,693 13,301 437 8,511 1,656 85 1,482 Liwale 4,125 4,745 0 1,933 364 0 141 Ruangwa 13,913 6,386 405 4,960 952 66 204 Lindi Urban 257 470 171 1,084 289 510 443 Total 54,548 43,369 2,522 33,721 7,886 4,050 6,014 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 14,373 4,781 1,050 5,248 641 523 4,774 Lindi Rural 20,390 7,844 1,706 9,675 1,941 998 3,049 Nachingwea 19,648 6,376 2,274 4,081 345 88 2,613 Liwale 5,137 1,709 498 983 255 56 2,863 Ruangwa 11,271 5,136 1,327 3,524 859 0 4,840 Lindi Urban 1,570 464 454 173 136 148 242 Total 72,389 26,309 7,308 23,685 4,177 1,813 18,382 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 4,527 1,894 1,424 6,744 1,196 556 13,350 Lindi Rural 4,715 4,483 4,295 7,003 2,549 1,251 13,487 Nachingwea 4,694 3,136 7,422 6,968 1,387 0 11,123 Liwale 1,240 615 1,661 1,346 448 142 4,414 Ruangwa 1,562 2,081 3,830 2,605 1,476 0 9,703 Lindi Urban 1,042 525 207 510 328 35 248 Total 17,780 12,735 18,839 25,177 7,384 1,984 52,324 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilwa 1,247 1,784 1,451 3,321 1,425 546 8,545 Lindi Rural 1,423 1,900 3,172 3,961 2,253 203 11,305 Nachingwea 783 2,088 7,052 4,449 1,477 520 11,307 Liwale 478 633 1,347 646 528 226 2,355 Ruangwa 270 2,011 1,875 805 661 0 4,563 Lindi Urban 143 315 244 145 144 69 346 Total 4,345 8,731 15,139 13,328 6,488 1,564 38,422 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 129 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Lindi Number % Number % Number % Less than 4 43,770 51 41,566 49 85,336 100 05 - 09 43,786 49 45,323 51 89,109 100 10 - 14 41,516 50 40,879 50 82,394 100 15 - 19 30,415 49 31,366 51 61,781 100 20 - 24 18,698 36 32,537 64 51,235 100 25 - 29 23,448 47 26,913 53 50,361 100 30 - 34 19,250 44 24,311 56 43,561 100 35 - 39 13,973 45 16,790 55 30,764 100 40 - 44 14,656 46 16,871 54 31,527 100 45 - 49 10,730 49 10,977 51 21,707 100 50 - 54 11,478 46 13,372 54 24,850 100 55 - 59 8,610 52 8,041 48 16,651 100 60 - 64 8,606 47 9,584 53 18,191 100 65 - 69 7,142 50 7,047 50 14,189 100 70 - 74 5,861 47 6,541 53 12,402 100 75 - 79 2,900 54 2,506 46 5,407 100 80 - 84 2,240 52 2,043 48 4,283 100 Above 85 1,346 51 1,305 49 2,651 100 Total 308,426 48 337,974 52 646,400 100 Number % Number % Number % Less than 4 43,770 14 41,566 12 85,336 13 05 - 09 43,786 14 45,323 13 89,109 14 10 - 14 41,516 13 40,879 12 82,394 13 15 - 19 30,415 10 31,366 9 61,781 10 20 - 24 18,698 6 32,537 10 51,235 8 25 - 29 23,448 8 26,913 8 50,361 8 30 - 34 19,250 6 24,311 7 43,561 7 35 - 39 13,973 5 16,790 5 30,764 5 40 - 44 14,656 5 16,871 5 31,527 5 45 - 49 10,730 3 10,977 3 21,707 3 50 - 54 11,478 4 13,372 4 24,850 4 55 - 59 8,610 3 8,041 2 16,651 3 60 - 64 8,606 3 9,584 3 18,191 3 65 - 69 7,142 2 7,047 2 14,189 2 70 - 74 5,861 2 6,541 2 12,402 2 75 - 79 2,900 1 2,506 1 5,407 1 80 - 84 2,240 1 2,043 1 4,283 1 Above 85 1,346 0 1,305 0 2,651 0 Total 308,426 100 337,974 100 646,400 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 131 Number % Number % Number % Kilwa 72,176 49 76,237 51 148,413 100 Lindi Rural 83,927 46 96,729 54 180,656 100 Nachingwea 66,706 47 74,282 53 140,989 100 Liwale 29,023 50 29,597 50 58,620 100 Ruangwa 50,073 48 54,170 52 104,243 100 Lindi Urban 6,521 48 6,959 52 13,480 100 Total 308,426 48 337,974 52 646,400 100 Number % Number % Number % Number % Number % Kilwa 69,323 55 2,064 2 377 0 54,158 43 125,922 100 Lindi Rural 82,852 53 1,934 1 203 0 71,703 46 156,692 100 Nachingwea 80,021 65 2,276 2 0 0 41,708 34 124,005 100 Liwale 30,130 61 753 2 0 0 18,527 37 49,411 100 Ruangwa 52,703 57 1,861 2 137 0 38,478 41 93,178 100 Lindi Urban 6,659 56 821 7 69 1 4,307 36 11,856 100 Total 321,687 57 9,709 2 786 0 228,881 41 561,064 100 Number % Number % Number % Number % Kilwa 33,457 27 43,394 34 49,071 39 125,922 100 Lindi Rural 31,146 20 60,413 39 65,133 42 156,692 100 Nachingwea 31,485 25 58,210 47 34,311 28 124,005 100 Liwale 13,308 27 20,536 42 15,567 32 49,411 100 Ruangwa 20,167 22 38,164 41 34,846 37 93,178 100 Lindi Urban 3,336 28 4,513 38 4,006 34 11,856 100 Total 132,899 24 225,230 40 202,935 36 561,064 100 Number % Number % Number % Number % Number % Kilwa 61,479 49 68 0 78 0 2,684 2 845 1 Lindi Rural 88,683 57 1,327 1 0 0 1,744 1 807 1 Nachingwea 73,609 59 0 0 0 0 0 0 696 1 Liwale 27,690 56 0 0 0 0 0 0 388 1 Ruangwa 55,400 59 68 0 0 0 0 0 197 0 Lindi Urban 4,221 36 246 2 0 0 820 7 215 2 Total 311,082 55 1,708 0 78 0 5,248 1 3,149 1 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 132 Number % Number % Number % Number % Number % Kilwa 453 0 545 0 6,370 5 2,274 2 297 0 Lindi Rural 920 1 1,422 1 9,935 6 2,543 2 1,139 1 Nachingwea 2,182 2 176 0 2,687 2 523 0 346 0 Liwale 138 0 240 0 976 2 0 0 80 0 Ruangwa 337 0 67 0 4,623 5 1,407 2 472 1 Lindi Urban 318 3 35 0 1,424 12 106 1 103 1 Total 4,348 1 2,484 0 26,014 5 6,852 1 2,437 0 Number % Number % Number % Number % Number % Number % Kilwa 315 0 861 1 31,824 25 12,747 10 5,082 4 125,922 100 Lindi Rural 615 0 717 0 29,113 19 12,050 8 5,676 4 156,692 100 Nachingwea 784 1 434 0 30,715 25 7,675 6 4,179 3 124,005 100 Liwale 83 0 111 0 12,891 26 5,885 12 930 2 49,411 100 Ruangwa 548 1 268 0 18,813 20 9,675 10 1,303 1 93,178 100 Lindi Urban 35 0 72 1 3,198 27 823 7 242 2 11,856 100 Total 2,378 0 2,463 0 126,553 23 48,856 9 17,413 3 561,064 100 Number % Number % Number % Number % Number % Kilwa 60,968 48 6,133 5 26,315 21 32,506 26 125,922 100 Lindi Rural 85,724 55 8,520 5 22,624 14 39,824 25 156,692 100 Nachingwea 71,596 58 4,779 4 17,520 14 30,111 24 124,005 100 Liwale 27,377 55 1,354 3 5,144 10 15,536 31 49,411 100 Ruangwa 54,434 58 2,422 3 9,697 10 26,626 29 93,178 100 Lindi Urban 4,291 36 995 8 2,081 18 4,488 38 11,856 100 Total 304,391 54 24,202 4 83,381 15 149,091 27 561,064 100 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Other District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Unpaid Family Helper (Non Agriculture) Total Main Activity Main Activity Not Working & Unavailable Housemaker / Housewife Student U ab e to Work / Too Old / Retired / Sick / District Not Working & Available Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 133 Number % Number % Number % Number % Number % Kilwa 633 1 311 1 1240 3 1652 4 4319 10 Lindi Rur 691 1 599 1 1419 2 3548 6 8282 14 Nachingwea 88 0 350 1 1481 3 1922 3 10545 18 Liwale 194 1 85 0 420 2 481 2 1925 9 Ruangwa 743 2 134 0 1806 5 1283 3 6702 18 Lindi Urb 38 1 0 0 207 5 388 9 689 15 Total 2388 1 1480 1 6574 3 9274 4 32462 14 Number % Number % Number % Number % Number % Kilwa 958 2 1026 2 237 1 78 0 81 0 Lindi Rural 2142 4 1491 2 205 0 100 0 103 0 Nachingwea 1043 2 2429 4 347 1 87 0 0 0 Liwale 478 2 610 3 57 0 54 0 0 0 Ruangwa 814 2 1010 3 69 0 63 0 269 1 Lindi Urban 36 1 0 0 36 1 75 2 0 0 Total 5471 2 6565 3 951 0 457 0 452 0 Number % Number % Number % Number % Number % Kilwa 71 0 0 0 542 1 0 0 151 0 Lindi Rural 86 0 0 0 1,213 2 0 0 0 0 Nachingwea 436 1 346 1 875 2 0 0 0 0 Liwale 134 1 26 0 336 2 28 0 0 0 Ruangwa 202 1 67 0 330 1 0 0 0 0 Lindi Urban 35 1 0 0 71 2 0 0 108 2 Total 964 0 438 0 3,367 1 28 0 259 0 Number % Number % Number % Kilwa 0 0 1,358 3 43,394 100 Lindi Rural 0 0 3,587 6 60,413 100 Nachingwea 0 0 0 0 58,210 100 Liwale 0 0 960 5 20,536 100 Ruangwa 0 0 200 1 38,164 100 Lindi Urban 37 1 244 5 4,513 100 Total 37 0 6,349 3 225,230 100 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Education Level Form Two Form Three Form Four District Standard Three District Standard Five Standard Six g y Education Pre Form One Education Level Under Standard One Standard One Standard Two Education Level Adult Education Standard Four Form One District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Total Form Six Training After Secondary Education University & Other Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 134 Number % Average Household Size Number % Average Household Size Number % Kilwa 113,025 22,835 5 35,388 8,542 4 148,413 31,377 5 Lindi Rural 138,207 32,758 4 42,448 12,096 4 180,656 44,853 4 Nachingwea 108,868 25,859 4 32,121 9,308 3 140,989 35,167 4 Liwale 52,460 9,974 5 6,160 1,390 4 58,620 11,365 5 Ruangwa 76,847 18,893 4 27,396 8,329 3 104,243 27,222 4 Lindi Urban 10,311 2,298 4 3,169 891 4 13,480 3,189 4 Total 499,718 112,618 4 146,682 40,555 4 646,400 153,173 4 Number Percent Number Percent Number Percent Number Percent Kilwa 15,015 62 6,370 26 2,944 12 24,330 100 Lindi Rural 25,507 66 9,060 24 3,924 10 38,492 100 Nachingwea 20,357 76 4,520 17 1,748 7 26,625 100 Liwale 4,528 81 784 14 251 5 5,564 100 Ruangwa 12,361 88 1,525 11 199 1 14,084 100 Lindi Urban 1,443 68 413 19 279 13 2,134 100 Total 79,211 71 22,672 20 9,345 8 111,228 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Kilwa 11,990 17,886 75 348 151 0 928 31,377 Lindi Rural 17,876 23,507 102 706 0 0 2,662 44,853 Nachingwea 8,783 25,428 347 523 0 0 86 35,167 Liwale 2,805 7,461 28 366 0 0 705 11,365 Ruangwa 10,102 16,651 0 332 0 0 137 27,222 Lindi Urban 1,487 1,375 0 75 73 37 142 3,189 Total 53,043 92,308 553 2,349 224 37 4,660 153,173 Mean Median Mode Mean Median Mode Mean Median Mode Kilwa 43 40 30 44 43 40 43.3 41 30 Lindi Rural 45 42 45 51 51 50 46.7 45 70 Nachingwea 44 42 26 48 46 32 45.2 42 26 Liwale 43 41 30 46 43 30 43.4 41 30 Ruangwa 46 44 40 49 48 65 47.1 45 40 Lindi Urban 49 46 30 52 52 60 49.7 48 60 Total 45 42 45 48 48 50 45.6 43 40 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Household Size 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Median, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 135 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 103,809 107,835 110,612 111,617 121,669 308,426 Female Heads 25,780 35,328 42,122 46,166 32,649 337,974 Total 129,589 143,163 152,734 157,783 154,318 646,400 Male headed (Percentage) 80 75 72 71 79 48 Female headed (Percentage) 20 25 28 29 21 52 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Kilwa 45,889 5,996 51,885 19,635 13,236 32,871 65,524 19,233 84,756 Lindi Rur Nachingwea 31,362 3,876 35,237 10,042 5,775 15,817 41,404 9,651 51,055 Liwale 27,776 3,738 31,515 11,772 3,951 15,724 39,549 7,689 47,238 Ruangwa 48,267 10,969 59,236 29,081 12,164 41,245 77,348 23,134 100,482 Lindi Urb 19,214 4,087 23,300 10,528 6,360 16,889 29,742 10,447 40,189 Total 172,507 28,666 201,173 81,058 41,487 122,546 253,566 70,153 323,719 Literacy District Know Don't know Total 3.15 Literacy Rate of Heads of Households by Sex and District Tanzania Agriculture Sample Census - 2003 Lindi 136 Appendix II 137 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 138 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 1,206 11 26,216 21 5,219 23 778 13.4 1,734 15 2,221 13 Lindi Rural 1,951 19 32,001 26 7,357 32 3,144 54.2 5,576 47 9,995 57 Nachingwea 3,933 37 29,937 24 6,088 27 262 4.5 2,261 19 2,966 17 Liwale 141 1 10,773 9 638 3 192 3.3 392 3 740 4 Ruangwa 3,253 31 22,306 18 2,692 12 1,393 24.0 1,658 14 862 5 Lindi Urban 37 0 1,911 2 903 4 35 0.6 173 1 858 5 Total 10,521 100 123,145 100 22,897 100 5,803 100 11,793 100 17,641 100 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Kilwa 1,802 43,701 7,814 812 1,369 . 2,676 58,174 Lindi Rural 2,141 60,059 10,255 2,721 3,947 943 16,682 96,748 Nachingwea 6,518 61,731 8,190 177 1,524 36 6,225 84,400 Liwale 183 34,851 701 375 370 45 3,142 39,667 Ruangwa 6,158 40,935 3,004 1,107 1,069 95 934 53,303 Lindi Urban 1,514 2,722 1,635 49 191 . 1,081 7,192 Total 18,316 244,000 31,599 5,241 8,470 1,118 30,740 339,484 % 5 72 9 2 2 0 9 100 Land Access 60,022 12,877 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed under Other Forms of Tenure 45,446 Total Number of Households 37,374 District Land Access/ Ownership (Hectare) 32,164 3,917 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year 191,800 Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 139 LAND USE Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 140 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Total Number of Households Kilwa 8,780 15,954 5,839 5,456 8,746 79 1,033 0 0 0 1,169 1,658 48,715 Lindi Rural 16,453 32,869 9,383 4,061 11,964 103 7,823 416 99 828 1,961 12,548 Nachingwea 12,718 23,498 9,058 1,648 17,950 87 4,268 1,142 0 175 1,574 4,973 77,091 Liwale 4,936 5,488 4,884 422 4,980 0 1,458 251 0 111 556 1,759 24,843 Ruangwa 8,028 19,361 6,897 793 8,920 0 1,198 63 69 604 735 5,897 52,565 Lindi Urban 533 2,049 602 147 1,372 0 241 0 67 35 0 252 5,297 Total 51,448 99,220 36,664 12,526 53,932 268 16,021 1,872 234 1,753 5,994 27,086 307,018 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Kilwa 7,435 17,208 7,657 5,898 15,422 19 1,025 . 0 . 1,764 1,746 58,174 Lindi Rural 9,547 28,308 8,308 4,187 18,463 25 8,060 130 10 780 2,367 16,563 96,748 Nachingwea 9,502 23,867 9,471 2,817 23,162 35 4,821 2,855 0 141 1,911 5,817 84,400 Liwale 4,962 6,600 10,345 390 10,215 0 2,503 282 0 114 896 3,361 39,667 Ruangwa 4,720 18,893 9,119 547 10,052 0 1,501 25 28 720 663 7,035 53,303 Lindi Urban 282 1,958 717 374 2,391 0 186 0 19 28 0 1,237 7,192 Total 36,448 96,833 45,617 14,214 79,704 79 18,095 3,293 57 1,783 7,602 35,758 339,484 % 11 29 13 4 23 0 5 1 0 1 2 11 100 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Type of Land Use Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 141 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Kilwa 25,693 82 5,616 18 31,309 100 Kilwa 19,018 61 12,291 39 31,309 100 Lindi Rural 26,038 58 18,815 42 44,853 100 Lindi Rural 33,068 74 11,785 26 44,853 100 Nachingwea 23,302 66 11,865 34 35,167 100 Nachingwea 26,367 75 8,800 25 35,167 100 Liwale 8,090 72 3,220 28 11,310 100 Liwale 8,776 78 2,534 22 11,310 100 Ruangwa 19,181 70 8,042 30 27,222 100 Ruangwa 20,634 76 6,588 24 27,222 100 Lindi Urban 2,387 76 766 24 3,153 100 Lindi Urban 3,012 96 142 4 3,153 100 Total 104,691 68 48,323 32 153,015 100 Total 110,875 72 42,140 28 153,015 100 Number Percent Number Percent Number Percent Kilwa 2,422 8 28,886 92 31,309 100 Lindi Rural 13,384 30 31,469 70 44,853 100 Nachingwea 8,778 25 26,389 75 35,167 100 Liwale 1,637 14 9,673 86 11,310 100 Ruangwa 7,824 29 19,399 71 27,222 100 Lindi Urban 217 7 2,936 93 3,153 100 Total 34,263 22 118,752 78 153,015 100 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total Tanzania Agriculture Sample Census - 2003 Lindi 142 Appendix II 143 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 144 Number of household Planted area (hectare) Kilwa 67,745 36,929 Lindi Rural 127,669 51,544 Nachingwea 102,172 51,402 Liwale 32,337 20,876 Ruangwa 65,838 30,324 Lindi Urban 7,874 4,301 Total 403,635 195,375 Number of households Growing Crops Number of households NOT Growing Crops Total number of Crop growing Households Kilwa 29,796 1,580 31,377 Lindi Rural 44,753 100 44,853 Nachingwea 35,167 0 35,167 Liwale 11,201 163 11,365 Ruangwa 27,154 69 27,222 Lindi Urban 3,083 106 3,189 Total 151,154 2,019 153,173 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by District. District Wet Season District Wet Season 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 145 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 71,470 24,854 348 Paddy 15,703 5,180 330 Sorghum 34,872 9,768 280 Bulrush Millet 142 22 153 Finger Millet 218 93 427 Wheat . . Barley 16 8 494 CEREALS 122,420 39,924 326 Cassava 46,788 25,814 552 Sweet Potatoes 258 197 762 Irish Potatoes . . Yams 131 24 183 Cocoyam 13 5 412 ROOTS & TUBERS 47,189 26,040 552 Mung Beans . . Beans 165 67 408 Cowpeas 5,329 894 168 Green Gram 73 14 188 Pigeon Peas 33 2 62 Chich Peas . . Bambaranuts 396 78 196 Field Peas 20 2 78 PULSES 6,016 1,056 176 Sunflower 13,956 5,142 368 Simsim 4,579 1,551 339 Groundnuts 93 16 177 Soya Beans 93 0 0 Castor Seed 60 70 1,164 OIL SEEDS & OIL 18,782 7,836 417 Okra 101 37 362 Water Mellon 18 0 0 Cucumbber 13 1 88 Onions 191 405 2,119 Cabbage . . Tomatoes 351 2,177 6,208 Egg Plant 12 9 741 Amaranths 47 8 174 Chillies 0 0 Pumpkins 263 0 0 FRUITS & 995 2,637 2,650 Total 195,402 1,725 1,761 *The total area planted include the sum of the planted area for both Wet and Dry Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Wet Season to estimate physical land area under production to different crops 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested byCrop for the 2002/03 agriculture year, Lindi Region Crop Wet season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 146 Number of Households Planted area (ha) CEREALS 243,318 122,420 Maize 128,506 71,470 Paddy 36,827 15,703 Sorghum 76,620 34,872 Bulrush Millet 501 142 Finger Millet 786 218 Wheat 0 . Barley 79 16 Maize 90,021 47,189 Cassava 88,540 46,788 Sweet Potatoes 1,026 258 Irish Potatoes 0 . Yams 352 131 Cocoyam 104 13 PULSES 20,791 6,016 Mung Beans 0 . Beans 828 165 Cowpeas 17,548 5,329 Green Gram 271 73 Pigeon Peas 68 33 Chich Peas 0 . Bambaranuts 1,907 396 Field Peas 169 20 OIL SEEDS & OIL NUTS 43,927 18,700 Sunflower 103 10 Simsim 33,452 13,956 Groundnuts 10,120 4,579 Soya Beans 145 93 Castor Seed 106 60 FRUITS & VEGETABLES 5,293 995 Okra 110 101 Radish 0 . Turmeric 0 . Onions 1,172 191 Cabbage 0 0 Tomatoes 1,409 351 Spinnach 0 0 Water Mellon 88 18 Cucumber 116 13 Amaranths 322 47 Pumpkins 2,048 263 Total 403,350 195,320 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Lindi Region Wet Season Crop Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 147 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 378 497 388 429 29,030 36,003 29,796 36,929 Lindi Rural 106 21 1,813 2,328 42,834 49,194 44,753 51,544 Nachingwea 435 272 870 1,843 33,862 49,284 35,167 51,398 Liwale 107 161 333 520 10,762 20,196 11,201 20,876 Ruangwa 1,370 1,267 804 954 24,980 27,882 27,154 30,103 Lindi Urban 0 . 36 7 3,047 4,150 3,083 4,157 Total 2,395 2,218 4,244 6,080 144,515 186,708 151,154 195,006 % 1 3 96 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilwa 384 667 1,025 1,259 75 39 28,312 34,964 29,796 36,929 Lindi Rural 199 226 509 942 192 156 43,852 50,220 44,753 51,544 Nachingwea 175 195 519 478 0 . 34,473 50,728 35,167 51,402 Liwale 57 46 396 880 83 99 10,665 19,852 11,201 20,876 Ruangwa 131 233 330 258 405 766 26,288 29,066 27,154 30,324 Lindi Urban 168 173 0 . 0 . 2,985 4,129 3,153 4,301 Total 1,114 1,538 2,779 3,819 756 1,060 146,576 188,959 151,224 195,375 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Kilwa 396 565 29,401 36,364 29,796 36,929 0.29 Lindi Rural 827 961 43,926 50,583 44,753 51,544 0.49 Nachingwea 435 753 34,732 50,649 35,167 51,402 0.39 Liwale 85 132 11,116 20,744 11,201 20,876 0.07 Ruangwa 938 1,272 26,215 29,052 27,154 30,324 0.65 Lindi Urban 316 383 2,837 3,919 3,153 4,301 0.20 Total 2,996 4,066 148,228 191,309 151,224 195,375 0.35 Households Using Irrigation Households not Using Irrigation Total 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year District Irrigation Use % of Area Planted Under Irrigation Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year, LINDI District Fertilizer Use 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District, LINDI District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 148 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 1,426 1,957 28,370 34,972 29,796 36,929 5.30 Lindi Rural 1,206 1,709 43,547 49,835 44,753 51,544 3.32 Nachingwea 1,305 2,085 33,862 49,317 35,167 51,402 4.06 Liwale 510 1,010 10,692 19,866 11,201 20,876 4.84 Ruangwa 1,213 1,501 25,941 28,822 27,154 30,324 4.95 Lindi Urban 106 175 3,048 4,127 3,153 4,301 4.06 Total 5,765 8,437 145,459 186,938 151,224 195,375 4.42 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 233 216 29,564 36,713 29,796 36,929 0.58 Lindi Rural 500 457 44,252 51,087 44,753 51,544 0.89 Nachingwea 256 363 34,911 51,039 35,167 51,402 0.71 Liwale 83 138 11,118 20,738 11,201 20,876 0.66 Ruangwa 677 569 26,476 29,754 27,154 30,324 1.88 Lindi Urban 0 . 3,153 4,301 3,153 4,301 0.00 Total 1,750 1,742 149,475 193,633 151,224 195,375 0.89 % 1.2 0.9 98.8 99.1 100 100 0.93 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 149 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 235 251 29,562 36,678 29,796 36,929 0.68 Lindi Rural 798 583 43,955 50,961 44,753 51,544 1.13 Nachingwea 606 1,348 34,561 50,054 35,167 51,402 2.62 Liwale 339 693 10,863 20,183 11,201 20,876 3.32 Ruangwa 535 575 26,618 29,749 27,154 30,324 1.90 Lindi Urban 37 144 3,116 4,158 3,153 4,301 3.34 Total 2,551 3,593 148,673 191,782 151,224 195,375 1.84 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 1,020 1,060 28,776 35,869 29,796 36,929 2.87 Lindi Rural 1,165 1,457 43,588 50,087 44,753 51,544 2.83 Nachingwea 2,952 4,634 32,215 46,764 35,167 51,398 9.02 Liwale 1,012 2,579 10,189 18,297 11,201 20,876 12.35 Ruangwa 5,853 6,578 21,300 23,525 27,154 30,103 21.85 Lindi Urban 253 774 2,830 3,383 3,083 4,157 18.63 Total 12,255 17,082 138,899 177,924 151,154 195,006 8.76 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet Season. District Improved Seed Use % of Planted Area Using Improved Seeds Households Using Improved Households Not Using Total 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet Season. District Fungicide Use % of Planted Area Using Fungicides Households Using Households Not Using Total Tanzania Agriculture Sample Census - 2003 Lindi 150 Appendix II 151 ANNUAL CROP & VEGETABLES PRODUCTION DRY SEASON Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 384 667 1,025 1,259 75 39 28,312 34,964 29,796 36,929 Lindi Rural 199 226 509 942 192 156 43,852 50,220 44,753 51,544 Nachingwea 175 195 519 478 0 . 34,473 50,728 35,167 51,402 Liwale 57 46 396 880 83 99 10,665 19,852 11,201 20,876 Ruangwa 131 233 330 258 405 766 26,288 29,066 27,154 30,324 Lindi Urban 168 173 0 . 0 . 2,985 4,129 3,153 4,301 Total 1,114 1,538 2,779 3,819 756 1,060 146,576 188,959 151,224 195,375 % 0.7 0.8 1.8 2.0 0.5 0.5 96.9 96.7 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 396 565 29,401 36,364 29,796 36,929 2 Lindi Rural 827 961 43,926 50,583 44,753 51,544 2 Nachingwea 435 753 34,732 50,649 35,167 51,402 0 Liwale 85 132 11,116 20,744 11,201 20,876 0 Ruangwa 938 1,272 26,215 29,052 27,154 30,324 0 Lindi Urban 316 383 2,837 3,919 3,153 4,301 0 Total 2,996 4,066 148,228 191,309 151,224 195,375 2 % 2 2 98 98 100 100 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during WET Season, 2002/03 Agriculture Year, LINDI Region District Irrigation Use % of planted area under irrigation in WET season Households Using Irrigation Households Not Using Total 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, LINDI Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic No Fertilizer Applied Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 1,426 1,957 28,370 34,972 29,796 36,929 1.00 Lindi Rural 1,206 1,709 43,547 49,835 44,753 51,544 0.87 Nachingwea 1,305 2,085 33,862 49,317 35,167 51,402 1.07 Liwale 510 1,010 10,692 19,866 11,201 20,876 0.52 Ruangwa 1,213 1,501 25,941 28,822 27,154 30,324 0.77 Lindi Urban 106 175 3,048 4,127 3,153 4,301 0.09 Total 5,765 8,437 145,459 186,938 151,224 195,375 0.72 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 233 216 29,564 36,713 29,796 36,929 0.11 Lindi Rural 500 457 44,252 51,087 44,753 51,544 0.23 Nachingwea 256 363 34,911 51,039 35,167 51,402 0.19 Liwale 83 138 11,118 20,738 11,201 20,876 0.07 Ruangwa 677 569 26,476 29,754 27,154 30,324 0.29 Lindi Urban 0 0 3,153 4,301 3,153 4,301 0.00 Total 1,750 1,742 149,475 193,633 151,224 195,375 0.15 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - WET Season. District Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess Households Not Using Herbicidess Total 7.1c ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - WET Season. District Insecticide Use % of Planted Area Using Insecticides Household Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 235 251 29,562 36,678 29,796 36,929 0.13 Lindi Rural 798 583 43,955 50,961 44,753 51,544 0.30 Nachingwea 606 1,348 34,561 50,054 35,167 51,402 0.69 Liwale 339 693 10,863 20,183 11,201 20,876 0.35 Ruangwa 535 575 26,618 29,749 27,154 30,324 0.29 Lindi Urban 37 144 3,116 4,158 3,153 4,301 0.07 Total 2,551 3,593 148,673 191,782 151,224 195,375 0.31 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilwa 1,020 1,060 28,776 35,869 29,796 36,929 0.5 Lindi Rural 1,165 1,457 43,588 50,087 44,753 51,544 0.7 Nachingwea 2,952 4,634 32,215 46,764 35,167 51,398 2.4 Liwale 1,012 2,579 10,189 18,297 11,201 20,876 1.3 Ruangwa 5,853 6,578 21,300 23,525 27,154 30,103 3.4 Lindi Urban 253 774 2,830 3,383 3,083 4,157 0.4 Total 12,255 17,082 138,899 177,924 151,154 195,006 8.8 % 8 9 92 91 100 100 2.9 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON District Improved Seed Use % of Planted Area Using Improved Seed Households Using Households Not Using Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET Season. Fungicide Use % of Planted Area Using Fungicides Household Using Households Not Using Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 155 ANNUAL CROP & VEGETABLES PRODUCTION WET SEASON Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 378 497 388 429 29,030 36,003 29,796 36,929 Lindi Rural 106 21 1,813 2,328 42,834 49,194 44,753 51,544 Nachingwea 435 272 870 1,843 33,862 49,284 35,167 51,398 Liwale 107 161 333 520 10,762 20,196 11,201 20,876 Ruangwa 1,370 1,267 804 954 24,980 27,882 27,154 30,103 Lindi Urban 0 . 36 7 3,047 4,150 3,083 4,157 Total 2,395 2,218 4,244 6,080 144,515 186,708 151,154 195,006 % 2 1 3 3 96 96 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 384 667 1,025 1,259 75 39 28,312 34,964 29,796 36,929 Lindi Rural 199 226 509 942 192 156 43,852 50,220 44,753 51,544 Nachingwea 175 195 519 478 0 0 34,473 50,728 35,167 51,402 Liwale 57 46 396 880 83 99 10,665 19,852 11,201 20,876 Ruangwa 131 233 330 258 405 766 26,288 29,066 27,154 30,324 Lindi Urban 168 173 0 0 0 0 2,985 4,129 3,153 4,301 Total 1,114 1,538 2,779 3,819 756 1,060 146,576 188,959 151,224 195,375 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilwa 396 565 29,401 36,364 29,796 36,929 2 Lindi Rural 827 961 43,926 50,583 44,753 51,544 2 Nachingwea 435 753 34,732 50,649 35,167 51,402 1 Liwale 85 132 11,116 20,744 11,201 20,876 1 Ruangwa 938 1,272 26,215 29,052 27,154 30,324 4 Lindi Urban 316 383 2,837 3,919 3,153 4,301 9 Total 2,996 4,066 148,228 191,309 151,224 195,375 2 % 2 2 76 98 100 100 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, LINDI Region District Irrigation Use % of planted area under irrigation in dry season Households Using Irrigation Households Not Using Irrigation Total 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, LINDI Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, LINDI Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 157 Number of House- holds Planted Area Number of House-holds Planted Area Number of House-holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 44,152 29,255 320,540 86,818 3,444 2,063 87,597 3,367 15,889 799 471,622 122,308 Maize 28,711 17,144 93,206 51,050 1,557 882 3,865 1,985 954 336 128,294 71,397 Paddy 7,770 3,670 25,341 10,335 1,823 901 751 411 973 369 36,740 15,692 Sorghum 17,531 8,321 55,688 25,176 734 281 2,117 970 481 95 76,551 34,844 Bulrush Millet 197 41 304 101 0 . 0 . 0 . 501 142 Finger Millet 229 77 557 140 0 . 0 . 0 . 786 218 Barley 0 . 79 16 0 . 0 . 0 . 79 16 ROOTS & TUBERS 1,661 8,380 10,730 36,712 0 498 3,244 792 703 314 16,338 46,696 Cassava 15,415 8,288 67,604 36,403 965 498 2,242 792 1,038 314 87,264 46,294 Sweet P t t 365 93 661 165 0 . 0 . 0 . 1,026 258 Yams 0 . 352 131 0 . 0 . 0 . 352 131 Cocoyam 0 . 104 13 0 . 0 . 0 . 104 13 PULSES 2,655 1,004 40,432 4,878 228 33 10,548 86 2,179 15 56,043 6,016 Beans 318 77 509 87 0 . 0 . 0 . 828 165 Cowpeas 2,846 884 14,106 4,311 81 33 412 86 103 15 17,548 5,329 Green Gram 88 7 183 66 0 . 0 . 0 . 271 73 Pigeon Peas 0 . 68 33 0 . 0 . 0 . 68 33 Bambaranut 176 36 1,731 361 0 . 0 . 0 . 1,907 396 Field Peas 0 . 169 20 0 . 0 . 0 . 169 20 OIL SEEDS & OIL NUTS 17,177 4,637 133,980 13,293 1,621 206 40,644 410 8,759 118 202,181 18,664 Sunflower 0 . 103 10 0 . 0 . 0 . 103 10 Simsim 8,526 3,748 23,551 9,772 136 52 865 250 289 99 33,365 13,921 Groundnuts 1,564 758 7,896 3,489 173 153 391 160 96 19 10,120 4,579 Soya Beans 88 71 57 22 0 . 0 . 0 . 145 93 Castor Seed 106 60 0 . 0 . 0 . 0 . 106 60 FRUITS & VEGETABL ES 245 90 6,337 832 0 . 1,619 54 299 19 8,501 995 Okra 81 30 29 72 0 . 0 . 0 . 110 101 Onions 69 7 897 146 0 . 137 24 69 14 1,172 191 Tomatoes 0 . 1,272 322 0 . 137 29 0 . 1,409 351 Amaranths 0 . 234 42 0 . 0 . 88 5 322 47 Pumpkins 57 35 1,991 227 0 . 0 . 0 . 2,048 263 Cucumber 0 . 116 13 0 . 0 . 0 . 116 13 Egg Plant 0 . 29 12 0 . 0 . 0 . 29 12 Water M ll 88 18 0 . 0 . 0 . 0 . 88 18 Total 65,890 43,366 512,020 142,533 5,294 2,767 143,652 4,709 27,829 1,265 754,685 194,679 % 22 73 1 2 1 100 Table 7.2d: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year Crop Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 158 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 20,747 11,056 3,652 0.330 Lindi Rural 35,765 14,876 5,869 0.395 Nachingwea 34,560 22,714 7,551 0.332 Liwale 9,924 7,658 2,468 0.322 Ruangwa 25,331 14,191 5,146 0.363 Lindi Urban 2,178 975 169 0.173 Total 128,506 71,470 24,854 0.348 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 318 112 14 0.121 Lindi Rural 0 . . 0.000 Nachingwea 88 9 6 0.608 Liwale 29 8 1 0.182 Ruangwa 67 13 1 0.082 Lindi Urban 0 . . 0.000 Total 501 142 22 0.153 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year District Burllush millet Wet Season Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year District Maize Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 159 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 11,767 5,970 1,719 0.288 Lindi Rural 15,143 6,101 2,293 0.376 Nachingwea 6,357 2,183 825 0.000 Liwale 2,305 984 313 0.000 Ruangwa 933 297 25 0.085 Lindi Urban 323 168 4 0.026 Total 36,827 15,703 5,180 0.330 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 13,455 6,937 2,011 0.290 Lindi Rural 27,001 10,850 3,595 0.331 Nachingwea 15,610 6,638 1,507 0.227 Liwale 7,086 4,273 1,017 0.238 Ruangwa 11,092 5,108 1,432 0.280 Lindi Urban 2,376 1,066 206 0.194 Total 76,620 34,872 9,768 0.280 Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year District Sorghum Wet Season Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year District Paddy Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 160 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 206 45 14 0.316 Nachingwea 263 92 62 0.676 Liwale 283 70 13 0.187 Ruangwa 0 . . 0.000 Lindi Urban 35 11 3 0.325 Total 786 218 93 0.427 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 531 113 56 0.490 Nachingwea 172 11 2 0.144 Liwale 57 18 5 0.247 Ruangwa 68 22 5 0.247 Lindi Urban 0 . . 0.000 Total 828 165 67 0.408 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . 0.000 Nachingwea 176 30 13 0.453 Liwale 28 6 0 0.050 Ruangwa 67 38 0 0.000 Lindi Urban 0 . . 0.000 Total 271 73 14 0.188 Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Wet Season Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Wet Season Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 161 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 2,253 759 116 0.152 Lindi Rural 7,483 2,269 405 0.178 Nachingwea 4,795 1,483 226 0.152 Liwale 1,753 496 118 0.237 Ruangwa 995 224 27 0.122 Lindi Urban 270 97 3 0.026 Total 17,548 5,329 894 0.168 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 80 33 20.1 0.618 Lindi Rural 931 138 20.5 0.148 Nachingwea 698 197 26.5 0.135 Liwale 0 . . 0.000 Ruangwa 198 28 11 0.374 Lindi Urban 0 . . 0.000 Total 1,907 396 78 0.196 Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of BAMBARANUTS Harvested (tons) by Season and District;2002/03 Agricultural Year Bambara nuts District Wet Season Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of COW PEAS Harvested (tons) by Season and District;2002/03 Agricultural Year Cow peas District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 162 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . 0.000 Nachingwea 176 30 13 0.453 Liwale 28 6 0 0.000 Ruangwa 67 38 0 0.000 Lindi Urban 0 . . 0.000 Total 271 73 14 0.188 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 10,620 7,566 8,655 1.144 Lindi Rural 25,675 12,845 5,229 0.407 Nachingwea 26,265 12,292 5,648 0.459 Liwale 5,843 4,563 2,364 0.518 Ruangwa 17,971 7,693 3,308 0.430 Lindi Urban 2,166 1,829 610 0.333 Total 88,540 46,788 25,814 0.552 Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Wet Season Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of GREEN GRAM Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 163 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 321 128 76 0.593 Lindi Rural 390 31 65 2.096 Nachingwea 175 71 31 0.432 Liwale 140 28 25 0.892 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 1,026 258 197 0.762 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 58 31 1 0.038 Lindi Rural 206 12 10 0.774 Nachingwea 88 88 13 0.150 Liwale 0 . . 0.000 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 352 131 24 0.183 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 783 861 125 0.146 Lindi Rural 4,040 1,611 788 0.489 Nachingwea 2,794 1,142 283 0.248 Liwale 1,566 699 262 0.375 Ruangwa 803 218 87 0.401 Lindi Urban 135 48 5 0.105 Total 10,120 4,579 1,551 0.339 Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District WET Season Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of YAMS Harvested (tons) by Season and District;2002/03 Agricultural Year Yams District WET Season Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District WET Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 164 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . 0.000 Nachingwea 88 71 10 0.143 Liwale 57 22 6 0.286 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 145 93 16 0.177 Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya beans District WET Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 165 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 6,953 3,406 1,367 0.401 Lindi Rural 6,823 2,097 632 0.301 Nachingwea 9,434 4,262 1,198 0.281 Liwale 2,923 1,836 1,038 0.565 Ruangwa 6,959 2,257 886 0.392 Lindi Urban 360 99 22 0.217 Total 33,452 13,956 5,142 0.368 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 72 7 1 0.099 Lindi Rural 692 158 1,309 8.308 Nachingwea 88 53 237 4.446 Liwale 86 43 33 0.776 Ruangwa 472 90 598 6.645 Lindi Urban 0 . . 0.000 Total 1,409 351 2,177 6.208 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 81 30 2 0.082 Lindi Rural 0 . . 0.000 Nachingwea 0 . . 0.000 Liwale 29 72 34 0.477 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 110 101 37 0.362 Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Okra District Wet Season Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Wet Season Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0 Lindi Rural 1,757 196 189 0.965 Nachingwea 174 18 47 2.666 Liwale 85 40 26 0.636 Ruangwa 0 . . 0.000 Lindi Urban 32 9 0 0.000 Total 2,048 263 262 0.996 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . 0.000 Nachingwea 87 7 1 0.161 Liwale 29 6 . 0.000 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 116 13 1 0.088 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 81 8 23 2.766 Lindi Rural 200 27 2 0.071 Nachingwea 86 18 69 3.952 Liwale 57 31 12 0.376 Ruangwa 748 107 300 2.790 Lindi Urban 0 . . 0.000 Total 1,172 191 405 2.119 Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Wet Season Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Cucumber District Wet Season Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Pumpkins District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 167 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . 0.000 Nachingwea 0 . . Liwale 0 . . 0.000 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 0 . . 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . Nachingwea 0 . . 0.000 Liwale 0 . . 0.000 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 0 . . 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0.000 Lindi Rural 0 . . Nachingwea 0 . . 0.000 Liwale 0 . . 0.000 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 0 . . 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Kilwa 0 . . 0 Lindi Rural 205 30 5.14 0.171 Nachingwea 88 5 0.44 0.082 Liwale 29 12 2.57 0.222 Ruangwa 0 . . 0.000 Lindi Urban 0 . . 0.000 Total 322 47 8.14 0.174 Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Wet Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year Chillies District Wet Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year Carrot District Wet Season Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Wet Season Tanzania Agriculture Sample Census - 2003 Lindi 168 Appendix II 169 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 170 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Pigeon Pea 625 635 316 497 Palm Oil . . 16 0 Coconut 5,541 6,430 13,031 2,026 Cashewnut 5,304 3,255 3,018 927 Sugarcane . . . 0 Jack Fruit . . 1 0 Banana 93 84 1,431 17,023 Mango 880 324 4,854 14,988 Pawpaw . . 237 0 Pineapple 57 57 810 14,314 Orange 1,437 2,724 10,537 3,869 Lime/Lemon . 0 396 0 Total 13,948 13,189 34,458 2,613 Pigeon Pea 1,217 717 352 491 Coconut 1,756 1,775 5,859 3,300 Cashewnut 12,404 9,597 1,978 206 Sugarcane 29 29 124 4,245 Banana 9 73 365 5,003 Avocado 11 11 13 1,186 Mango 44 44 130 2,932 Orange 79 64 233 3,625 Total 15,550 12,310 9,053 735 Pigeon Pea 9,012 2,435 1,039 427 Star Fruit 0 . 24 0 Coconut 2 32 1 19 Cashewnut 13,521 8,247 3,432 416 Sugarcane 18 18 192 10,875 Banana 150 114 443 3,887 Mango 248 216 3,601 16,680 Pawpaw 12 . 46 0 Orange 25 35 180 5,150 Guava 18 18 7 396 Total 23,005 11,114 8,965 807 Pigeon Pea 143 75 38 501 Coconut 293 244 81 330 Cashewnut 10,807 8,767 2,390 273 Sugarcane 9 9 833 94,842 Cloves 2 . 1 0 Banana 15 15 130 8,440 Mango 657 23 342 14,991 Pawpaw 4 . 3 0 Orange 22 10 201 20,536 Guava 1 1 49 42,237 Total 11,953 9,145 4,068 445 Nachingwea Liwale 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - LINDI District/Crop Kilwa Lindi Rural Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 171 Cont….: Production of Permanent Crops by Crop Type and District - LINDI Pigeon Pea 3,095 2,263 738 326 Star Fruit . . 4 Coconut 109 54 51 950 Cashewnut 13,403 8,956 2,359 263 Banana 139 0 44 Mango . . 94 Pawpaw . 0 . Orange 306 56 728 13,086 Lime/Lemon . . . Total 17,053 11,328 4,018 355 Pigeon Pea 39 44 16 360 Coconut 680 543 476 877 Cashewnut 243 240 344 1,435 Banana 30 30 10 331 Mango . 0 . Total 993 857 846 988 Pigeon Pea 14,142 5,849 2,308 395 Star Fruit 0 . 28 Palm Oil . . 16 Coconut 8,381 9,078 19,498 2,148 Cashewnut 55,683 39,062 13,521 346 Sugarcane 56 56 1,149 20,658 Cloves 2 . 1 Jack Fruit . . 1 Banana 437 317 2,423 7,652 Avocado 11 11 13 1,186 Mango 1,830 607 9,022 14,863 Pawpaw 16 0 286 Pineapple 57 57 810 14,314 Orange 1,869 2,888 11,880 4,113 Guava 19 19 56 2,954 Lime/Lemon . 0 396 Total 82,503 57,943 61,407 1,060 Total Ruangwa Lindi Urban Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 172 Crop Area Planted % Cashewnut 55,683 67.49 Pigeon Pea 14,142 17.14 Coconut 8,381 10.16 Orange 1,869 2.27 Mango 1,830 2.22 Banana 437 0.53 Pineapple 57 0.07 Sugarcane 56 0.07 Guava 19 0.02 Pawpaw 16 0.02 Avocado 11 0.01 Cloves 2 0.00 Star Fruit 0 0.00 Total 82,503 100 District Area Planted with Pigeon peas Total Area Planted (Ha) % of Total Area Planted Households with Pigeon peas Average Planted Area per Household Kilwa 635 36,929 1.7 1,067 0.6 Lindi Rural 1,217 51,544 2.4 4,510 0.3 Nachingwea 9,012 51,402 17.5 11,388 0.8 Liwale 143 20,876 0.7 503 0.3 Ruangwa 3,095 30,324 10.2 8,393 0.4 Lindi Urban 39 4,301 0.9 133 0.3 Total 14,142 195,375 7.2 25,995 0.5 7.3.2 PERMANENT CROP: Area Planted by Crop Type - LINDI Region 7.3.3 PERMANENT CROPS: Area Planted with Pigeon peas by District Pigeon peas Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 173 District Area Planted with Oranges Total Area Planted (Ha) % of Total Area Planted Households with Oranges Average Planted Area per Household Kilwa 1,437 36,929 3.9 3103 0.5 Lindi Rural 79 51,544 0.2 407 0.2 Nachingwea 25 51,402 0.0 433 0.1 Liwale 22 20,876 0.1 113 0.2 Ruangwa 306 30,324 1.0 200 1.5 Lindi Urban 0 4,301 0.0 0 0.0 Total 1,869 195,375 1.0 4256 0.4 Oranges 7.3.4 PERMANENT CROPS: Area planted with Oranges by District Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 174 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Rubber Vine Fruit 0 104 0 0 104 Pigeon Pea 2,383 751 463 16,081 19,678 Malay Apple 0 0 0 0 0 Sugarcane 145 0 0 453 598 Nutmeg 0 0 0 0 0 Banana 1,119 45 0 623 1,786 Mango 104 23 0 542 669 Pawpaw 172 0 0 140 312 Orange 48 0 0 1 49 Grape 41 0 0 51 92 Mandarine/Tangerine 0 0 0 0 0 Guava 87 45 0 1,093 1,225 Lime/Lemon 0 0 0 24 24 Durian 0 12 0 0 12 Rambutan 0 0 0 0 0 Total 4,099 979 463 19,007 24,547 7.3.5 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Crop Fertilizer Use Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 175 Crop Mostly Farm Yard Manure Total % Orange 48 49 98.6 Banana 1,119 1,786 62.7 Pawpaw 172 312 55.1 Grape 41 92 44.4 Sugarcane 145 598 24.2 Mango 104 669 15.6 Pigeon Pea 2,383 19,678 12.1 Guava 87 1,225 7.1 Rubber Vine Fruit 0 104 0.0 Nutmeg 0 0 0.0 Mandarine/Tangerine 0 0 0.0 Lime/Lemon 0 24 0.0 Durian 0 12 0.0 Rambutan 0 0 0.0 Total 4,099 24,547 16.7 Crop Mostly Inorganic Fertilizer Total % Pigeon Pea 463 19,678 2 Rubber Vine Fruit 0 104 0 Malay Apple 0 0 0 Sugarcane 0 598 0 Nutmeg 0 0 0 Banana 0 1,786 0 Mango 0 669 0 Pawpaw 0 312 0 Orange 0 49 0 Grape 0 92 0 Mandarine/Tangerine 0 0 0 Guava 0 1,225 0 Lime/Lemon 0 24 0 Durian 0 12 0 Rambutan 0 0 0 Total 463 24,547 2 cont… Planted Area with Fertilizer by Fertilizer Type and Crop cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Lindi 176 Appendix II 177 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 178 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 104,473 0 97 0 79 103 104,753 Paddy 20,999 96 83 0 132 0 21,310 Sorghum 55,850 0 0 101 136 209 56,295 Bulrush Millet 275 0 0 0 0 0 275 Finger Millet 464 0 0 0 0 0 464 Cassava 70,575 0 123 0 289 0 70,987 Cowpeas 2,528 0 161 0 0 0 2,689 Green Gram 28 0 0 0 0 0 28 Pigeon Peas 3,143 0 28 0 0 103 3,274 Bambaranut 106 0 0 0 0 0 106 Simsim 168 0 489 0 0 29 685 Groundnut 311 0 166 0 0 0 477 Oil Palm 80 0 0 0 0 0 80 Coconut 3,466 0 81 0 104 0 3,651 Cashewnut 67 0 0 0 87 0 154 Banana 98 0 0 0 0 0 98 Total 262,629 96 1,228 101 827 443 265,325 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 2,299 106 201 159 232 88 2,337 99,331 104,753 Paddy 1,242 0 103 0 0 56 327 19,581 21,310 Sorghum 757 0 255 28 103 29 961 54,162 56,295 Bulrush Millet 0 0 0 0 0 0 0 275 275 Finger Millet 0 0 0 0 0 0 0 464 464 Cassava 2,140 81 87 0 207 94 2,052 66,327 70,987 Cowpeas 323 0 0 0 0 134 0 2,232 2,689 Green Gram 0 0 0 0 0 0 0 28 28 Pigeon Peas 28 0 0 0 0 0 86 3,160 3,274 Bambaranut 0 0 0 0 0 0 0 106 106 Simsim 0 407 0 0 0 81 0 197 685 Groundnut 191 0 0 0 0 57 0 229 477 Oil Palm 0 0 0 0 0 0 0 80 80 Coconut 81 0 0 0 0 0 81 3,488 3,651 Cashewnut 0 0 0 0 0 0 0 154 154 Banana 0 0 0 0 0 0 0 98 98 Total 7,062 594 646 186 542 539 5,843 249,912 265,325 8.1.1b AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Lindi Region Crop Where Sold 8.1.1a AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Lindi Region Crop Product Use Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 179 Flour / Meal Grain Oil Juice Fiber Rubber Other Total Kilwa 15,315 7,072 161 0 0 0 0 22,548 Lindi Rural 31,565 8,260 803 199 0 0 0 40,826 Nachingwea 33,165 609 0 0 85 88 0 33,947 Liwale 9,073 895 0 0 0 0 0 9,968 Ruangwa 24,257 1,367 0 0 0 0 135 25,760 Lindi Urban 2,008 491 0 0 0 0 0 2,499 Total 115,383 18,694 964 199 85 88 135 135,549 Household / Human Consumption Fuel for Cooking Sale Only Did Not Use Other Total Kilwa 22,390 0 0 158 0 22,548 Lindi Rural 40,425 96 0 202 103 40,826 Nachingwea 33,947 0 0 0 0 33,947 Liwale 9,885 0 83 0 0 9,968 Ruangwa 25,691 0 69 0 0 25,760 Lindi Urban 2,499 0 0 0 0 2,499 Total 134,837 96 152 360 103 135,549 8.1.1c AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Lindi Region 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Lindi Region District Product Use District Main Product Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 180 Number % Number % Number % Kilwa 22,548 72 8,829 28 31,377 100 Lindi Rural 40,826 91 4,027 9 44,853 100 Nachingwea 33,947 97 1,220 3 35,167 100 Liwale 9,968 88 1,396 12 11,365 100 Ruangwa 25,760 95 1,463 5 27,222 100 Lindi Urban 2,499 78 690 22 3,189 100 Total 135,549 88 17,625 12 153,173 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm By Factory Total Kilwa 18,519 78 3,870 0 0 0 0 80 22,548 Lindi Rural 25,399 5,240 9,165 0 0 919 103 0 40,826 Nachingwea 4,684 175 27,602 0 88 1,399 0 0 33,947 Liwale 4,482 564 4,638 0 29 256 0 0 9,968 Ruangwa 4,744 268 16,610 412 205 3,521 0 0 25,760 Lindi Urban 1,930 150 280 0 0 140 0 0 2,499 Total 59,757 6,475 62,165 412 321 6,235 103 80 135,549 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm Other Total Maize 2,715 2,703 17,770 0 91 297 23,576 Paddy 0 0 101 0 0 0 101 Sorghum 705 301 3,364 0 0 0 4,371 Bulrush Millet 3,511 2,004 19,486 0 98 697 25,796 Cassava 403 0 300 0 0 0 703 Beans 101 0 0 0 0 0 101 Cowpeas 1,205 0 201 0 0 0 1,406 Bambaranut 2,912 95 0 0 0 780 3,787 Groundnut 10,426 101 698 0 0 1,586 12,810 8.1.1g AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Lindi Region Crop Method of Processing District Method of Processing 8.1.1f Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year 8.1.1e: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Households That did not Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 181 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Kilwa 876 0 0 0 0 0 323 21,349 22,548 Lindi Rural 418 106 201 0 207 0 518 39,377 40,826 Nachingwea 1,136 0 0 0 0 88 2,308 30,416 33,947 Liwale 224 0 0 55 26 0 27 9,637 9,968 Ruangwa 671 0 0 0 0 0 0 25,089 25,760 Lindi Urban 0 0 0 0 0 0 0 2,499 2,499 Total 3,324 106 201 55 233 88 3,175 128,366 135,549 Bran Cake Husk Fiber Pulp Shell No by- product Total Kilwa 11,084 323 2,575 0 0 0 8,566 22,548 Lindi Rural 20,000 1,603 4,358 106 0 288 14,470 40,826 Nachingwea 13,260 175 2,005 0 783 261 17,463 33,947 Liwale 6,810 0 448 0 0 112 2,598 9,968 Ruangwa 10,577 0 205 0 0 413 14,564 25,760 Lindi Urban 1,595 69 36 0 0 0 799 2,499 Total 63,326 2,170 9,628 106 783 1,075 58,461 135,549 District By Product 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year,Lindi Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Lindi Region Tanzania Agriculture Sample Census - 2003 Lindi 182 Appendix II 183 MARKETING Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 184 Number % Number % Kilwa 23,300 74.3 8,076 25.7 31,377 Lindi Rural 28,778 64.2 16,075 35.8 44,853 Nachingwea 26,221 74.6 8,945 25.4 35,167 Liwale 9,801 86.2 1,564 13.8 11,365 Ruangwa 18,466 67.8 8,756 32.2 27,222 Lindi Urban 1,429 44.8 1,761 55.2 3,189 Total 107,996 70.5 45,178 29.5 153,173 Open Market Price Too Low No Transpo rt Transport Cost Too High No Buyer Market too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Lack of Market Informati on Other Not applicable Total Kilwa 1,862 79 81 0 152 79 0 0 0 0 21,048 23,300 Lindi Rural 6,726 311 776 724 103 0 104 0 210 0 19,825 28,778 Nachingwea 4,797 88 175 0 88 0 0 175 175 348 20,376 26,221 Liwale 1,163 28 0 0 114 0 0 27 28 0 8,440 9,801 Ruangwa 3,609 0 0 0 0 65 0 0 0 0 14,792 18,466 Lindi Urban 72 0 0 0 0 0 0 0 0 0 1,357 1,429 Total 18,230 506 1,032 724 456 143 104 202 413 348 85,838 107,996 Open Market Price Too Low No Transpo rt Transport Cost Too High No Buyer Market too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Lack of Market Informati on Other Not applicable Total Kilwa 1.72 0.07 0.07 0.00 0.14 0.07 0.00 0.00 0.00 0.00 19.49 21.58 Lindi Rural 6.23 0.29 0.72 0.67 0.09 0.00 0.10 0.00 0.19 0.00 18.36 26.65 Nachingwea 4.44 0.08 0.16 0.00 0.08 0.00 0.00 0.16 0.16 0.32 18.87 24.28 Liwale 1.08 0.03 0.00 0.00 0.11 0.00 0.00 0.02 0.03 0.00 7.81 9.08 Ruangwa 3.34 0.00 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.00 13.70 17.10 Lindi Urban 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.26 1.32 Total 16.88 0.47 0.96 0.67 0.42 0.13 0.10 0.19 0.38 0.32 79.48 100.00 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Lindi Region District Main Reasons for Not Selling Crops 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Lindi Region District Main Reasons for Not Selling Crops 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Lindi Region District Households that SolDid not Sell Total Number of househol ds Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 185 Price Too Low Producti on Insuffici ent to Sell Market Too Far Farmer s Associa tion Proble ms Co- operative Problem s Trade Union Problems Governme nt Regulator y Board Problems Other Not applicabl e Total Kilwa 79 6,977 0 0 72 375 0 2,011 21,466 30,980 Lindi Rural 318 15,314 99 209 0 0 307 2,606 25,798 44,651 Nachingwea 0 8,069 0 0 88 438 0 1,398 23,612 33,605 Liwale 85 1,577 28 0 57 114 0 243 8,175 10,280 Ruangwa 131 8,635 0 0 0 0 139 536 17,507 26,947 Lindi Urban 37 1,258 0 0 0 0 0 358 1,536 3,189 Total 651 41,830 127 209 216 927 445 7,152 98,094 149,653 District Main Reasons for Not Selling Crops Tanzania Agriculture Sample Census - 2003 Lindi 186 Appendix II 187 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 188 Number of Household % Number of Household % Number of Household % Kilwa 386 1.2 30,991 98.8 31,377 100 Lindi Rural 1,235 2.8 43,618 97.2 44,853 100 Nachingwea 176 0.5 34,991 99.5 35,167 100 Liwale 426 3.7 10,939 96.3 11,365 100 Ruangwa 680 2.5 26,543 97.5 27,222 100 Lindi Urban 0 0.0 3,189 100.0 3,189 100 Total 2,902 1.9 150,271 98.1 153,173 100 District Irrigatable Area (ha) Irrigated Land (ha) % Kilwa 191 176 92.4 Lindi Rural 590 431 73.0 Nachingwea 7 7 100.0 Liwale 278 227 81.7 Ruangwa 16863 118 0.7 Lindi Urban . . 0.0 Total 17929 959 5.4 River Lake Dam Well Canal Total Kilwa 162 81 0 144 0 386 Lindi Rural 1029 0 0 0 207 1235 Nachingwea 0 0 0 176 0 176 Liwale 312 0 28 57 29 426 Ruangwa 67 0 0 547 66 680 Total 1569 81 28 923 301 2902 Total 2,730 98 417 4,533 129 1,162 Gravity Hand Bucket Motor Pump Other Total Kilwa 242 144 0 0 386 Lindi Rural 727 508 0 0 1,235 Nachingwea 0 176 0 0 176 Liwale 197 228 0 0 426 Ruangwa 0 474 137 69 680 Total 1,167 1,530 137 69 2,902 11.4: IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year District Method of Obtaining Water 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District District Households Practicing Irrigation Households not Practicing Irrigation Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 189 District Flood Sprinkler Bucket / Watering Can Total Kilwa 242 0 144 386 Lindi Rural 727 0 508 1,235 Nachingwea 0 0 176 176 Liwale 197 0 228 426 Ruangwa 0 69 611 680 Total 1,167 69 1,667 2,902 Number % Number % Kilwa 0 0 31,377 100 31,377 Lindi Rural 207 0.5 44,646 99.5 44,853 Nachingwea 608 1.7 34,559 98.3 35,167 Liwale 114 1.0 11,251 99.0 11,365 Ruangwa 68 0.3 27,154 99.7 27,222 Lindi Urban 0 0 3,189 100 3,189 Total 998 0.7 152,175 99.3 153,173 Erosion Control Bunds Gabions / Sandbag Vetiver Grass Drainage Ditches Total Lindi Rural 0 207 0 103 310 Nachingwea 31,630 0 0 0 31,630 Liwale 114 0 86 0 200 Ruangwa 2,053 0 0 0 2,053 Total 33,797 207 86 103 34,193 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year District Presence of Erosion Control/Water Harvesting Facilities Have Facility Does Not Have Facility Number of Households 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Method of Application 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Tanzania Agriculture Sample Census - 2003 Lindi 190 Appendix II 191 Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 0 0 0 0 0 0 0 0 0 0 0 0 31377 100 31377 100 Lindi Rur 0 0 288 1 0 0 0 0 0 0 0 0 44565 99 44853 100 Nachingwea 0 0 86 0 0 0 0 0 0 0 0 0 34645 100 34732 100 Liwale 28 0 277 2 0 0 0 0 0 0 29 0 11031 97 11365 100 Ruangwa 0 0 479 2 69 0 136 1 199 1 0 0 26139 97 27022 100 Lindi Urb 0 0 0 0 0 0 0 0 0 0 0 0 3189 100 3189 100 Total 28 0 1131 1 69 0 136 0 199 0 29 0 150946 99 152537 100 Number % Number % Number % Number % Number % Kilwa 224 1 287 1 0 0 30865 98 31377 100 Lindi Rur 0 0 908 2 0 0 43945 98 44853 100 Nachingwea 263 1 176 1 0 0 34293 99 34732 100 Liwale 453 4 112 1 29 0 10798 95 11392 100 Ruangwa 137 1 0 0 0 0 26885 99 27022 100 Lindi Urb 276 9 0 0 0 0 2913 91 3189 100 Total 1353 1 1483 1 29 0 149699 98 152564 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 644 2 322 1 161 1 0 0 0 0 81 0 311 1 0 0 0 0 29856 95 31377 100 Lindi Rur 0 0 0 0 0 0 0 0 103 0 0 0 504 1 0 0 0 0 44246 99 44853 100 Nachingwea 0 0 0 0 0 0 0 0 0 0 0 0 434 1 0 0 0 0 34298 99 34732 100 Liwale 168 1 168 1 84 1 28 0 0 0 0 0 340 3 114 1 29 0 10381 92 11311 100 Ruangwa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27022 100 27022 100 Lindi Urb 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3189 100 3189 100 Total 812 1 490 0 246 0 28 0 103 0 81 0 1589 1 114 0 29 0 148992 98 152484 100 Other Not applicable Locally Produced b Neighbour Total Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Development Proje Crop Buyers Large Scale Farm Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Locally Produced by Household Neighbour Other Not applicable Total Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Development Project Crop Buyers Neighbour Other Not applicable Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 192 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 315 1 0 0 985 3 0 0 0 0 0 0 753 2 0 0 29324 93 31377 100 Lindi Rur 1255 3 0 0 4309 10 0 0 0 0 0 0 304 1 0 0 38985 87 44853 100 Nachingwea 1390 4 437 1 5925 17 0 0 0 0 88 0 608 2 0 0 26284 76 34732 100 Liwale 28 0 57 1 3338 29 28 0 110 1 0 0 28 0 83 1 7666 68 11338 100 Ruangwa 1901 7 0 0 3210 12 0 0 206 1 0 0 272 1 0 0 21433 79 27022 100 Lindi Urb 0 0 0 0 468 15 0 0 0 0 0 0 0 0 35 1 2687 84 3189 100 Total 4888 3 494 0 18235 12 28 0 316 0 88 0 1965 1 117 0 126379 83 152511 100 Number % Number % Number % Kilwa 0 0 31377 100 31377 100 Lindi Rur 0 0 44853 100 44853 100 Nachingwea 0 0 34732 100 34732 100 Liwale 57 1 11254 99 11311 100 Ruangwa 0 0 27022 100 27022 100 Lindi Urb 0 0 3189 100 3189 100 Total 57 0 152427 100 152484 100 Number % Number % Number % Number % Number % Number % Kilwa 0 0 81 0 515 2 0 0 0 0 0 0 Lindi Rur 0 0 0 0 1091 2 0 0 0 0 0 0 Nachingwea 0 0 0 0 871 3 0 0 86 0 0 0 Liwale 28 0 28 0 932 8 0 0 0 0 0 0 Ruangwa 0 0 0 0 1847 7 69 0 69 0 410 2 Lindi Urb 0 0 0 0 180 6 0 0 0 0 0 0 Total 28 0 109 0 5435 4 69 0 154 0 410 0 Number % Number % Number % Number % Number % Number % Kilwa 81 0 0 0 1132 4 0 0 29568 94 31377 100 Lindi Rur 0 0 106 0 712 2 308 1 42636 95 44853 100 Nachingwea 0 0 0 0 173 0 0 0 33602 97 34732 100 Liwale 0 0 130 1 141 1 143 1 9936 88 11338 100 Ruangwa 68 0 1715 6 1606 6 0 0 21237 79 27022 100 Lindi Urb 0 0 0 0 0 0 69 2 2940 92 3189 100 Total 149 0 1952 1 3764 2 520 0 139920 92 152511 100 Table 12.1.12 ACCESS TO INPUTS: (Ctd) Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural District Large Scale Farm Locally Produced by Neighbour Other Not applicable Total Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers District Other Not applicable Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Secondary Market Crop Buyers Locally Produced by Household District Co-operative Local Farmers Group Local Market / Trade Store Other Not applicable Total Neighbour Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 193 Number % Number % Number % Number % Number % Number % Lindi Rur 0 0 0 0 0 0 0 0 288 100 288 100 Nachingwea 0 0 0 0 0 0 0 0 86 100 86 100 Liwale 81 24 26 8 143 43 56 17 28 9 334 100 Ruangwa 275 31 67 8 475 54 0 0 66 7 883 100 Total 355 22 93 6 618 39 56 4 469 29 1591 100 Number % Number % Number % Number % Number % Kilwa 512 100 0 0 0 0 0 0 512 100 Lindi Rur 605 67 0 0 204 22 100 11 908 100 Nachingwea 351 80 88 20 0 0 0 0 439 100 Liwale 565 95 0 0 29 5 0 0 593 100 Ruangwa 137 100 0 0 0 0 0 0 137 100 Lindi Urb 276 100 0 0 0 0 0 0 276 100 Total 2444 85 88 3 233 8 100 3 2865 100 Number % Number % Number % Number % Kilwa 1520 100 0 0 0 0 1520 100 Lindi Rur 607 100 0 0 0 0 607 100 Nachingwea 434 100 0 0 0 0 434 100 Liwale 762 82 141 15 28 3 931 100 Total 3323 95 141 4 28 1 3492 100 Number % Number % Number % Number % Number % Number % Kilwa 782 38 377 18 472 23 0 0 421 21 2052 100 Lindi Rur 1751 30 410 7 917 16 1194 20 1597 27 5868 100 Nachingwea 1137 13 1396 17 1733 21 2343 28 1838 22 8448 100 Liwale 321 9 161 4 567 15 1324 36 1298 35 3672 100 Ruangwa 1158 21 551 10 2655 48 955 17 269 5 5588 100 Lindi Urb 72 14 112 22 180 36 104 21 35 7 502 100 Total 5222 20 3008 12 6525 25 5919 23 5457 21 26131 100 Number % Number % Number % Liwale 29 50 29 50 57 100 Total 29 50 29 50 57 100 Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Less than 1 km Between 3 and 10 km Total Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 3 and 10 km 20 km and Above Total Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 20 km and Above Total Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 194 Number % Number % Number % Number % Number % Number % Kilwa 890 49 162 9 159 9 81 4 518 29 1809 100 Lindi Rur 903 41 0 0 302 14 213 10 798 36 2217 100 Nachingwea 350 31 87 8 86 8 346 31 261 23 1129 100 Liwale 272 19 82 6 257 18 254 18 537 38 1402 100 Ruangwa 3595 62 409 7 1370 24 275 5 136 2 5785 100 Lindi Urb 0 0 0 0 146 58 35 14 69 28 249 100 Total 6010 48 740 6 2319 18 1203 10 2319 18 12591 100 Number % Number % Number % Number % Number % Lindi Rur 192 67 96 33 0 0 0 0 288 100 Nachingwea 86 100 0 0 0 0 0 0 86 100 Liwale 197 59 109 33 0 0 29 9 334 100 Ruangwa 545 62 269 30 69 8 0 0 883 100 Total 1020 64 474 30 69 4 29 2 1591 100 Number % Number % Number % Number % Number % Kilwa 440 86 0 0 72 14 0 0 512 100 Lindi Rur 309 34 101 11 297 33 202 22 908 100 Nachingwea 439 100 0 0 0 0 0 0 439 100 Liwale 340 57 26 4 56 9 171 29 593 100 Ruangwa 137 100 0 0 0 0 0 0 137 100 Lindi Urb 242 88 0 0 0 0 35 12 276 100 Total 1905 67 127 4 425 15 408 14 2865 100 Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Bank Loan Other Total Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 195 Number % Number % Number % Number % Number % Kilwa 1207 79 81 5 0 0 233 15 1520 100 Lindi Rur 407 67 100 17 0 0 100 16 607 100 Nachingwea 347 80 87 20 0 0 0 0 434 100 Liwale 504 54 84 9 57 6 286 31 931 100 Total 2465 71 353 10 57 2 618 18 3492 100 Number % Number % Number % Number % Number % Number % Kilwa 1307 64 746 36 0 0 0 0 0 0 2052 100 Lindi Rur 3231 55 1818 31 410 7 0 0 409 7 5868 100 Nachingwea 5408 64 2346 28 348 4 86 1 260 3 8448 100 Liwale 3111 85 395 11 110 3 29 1 29 1 3672 100 Ruangwa 4503 81 538 10 274 5 69 1 204 4 5588 100 Lindi Urb 465 93 37 7 0 0 0 0 0 0 502 100 Total 18024 69 5881 23 1142 4 183 1 902 3 26131 100 Number % Number % Liwale 57 100 57 100 Total 57 100 57 100 Number % Number % Number % Number % Number % Kilwa 1187 66 460 25 162 9 0 0 1809 100 Lindi Rur 1105 50 702 32 207 9 202 9 2217 100 Nachingwea 608 54 260 23 88 8 173 15 1129 100 Liwale 1233 88 83 6 57 4 29 2 1402 100 Ruangwa 4981 86 737 13 0 0 67 1 5785 100 Lindi Urb 106 43 72 29 71 28 0 0 249 100 Total 9221 73 2315 18 584 5 471 4 12591 100 Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year District Sale of Farm Products Total Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generatRemittances Bank Loan Other Total Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generatRemittances Other Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 196 Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 16531 53 5834 19 960 3 79 0 1149 4 6510 21 313 1 31377 100 Lindi Rur 18188 41 14045 32 723 2 100 0 4453 10 6851 15 205 0 44565 100 Nachingwea 9869 28 15240 43 703 2 88 0 2800 8 5601 16 781 2 35080 100 Liwale 5228 47 5019 45 225 2 0 0 199 2 332 3 54 0 11058 100 Ruangwa 7107 27 8333 32 135 1 0 0 747 3 9886 38 132 1 26340 100 Lindi Urb 1981 62 926 29 36 1 0 0 144 5 67 2 36 1 3189 100 Total 58903 39 49398 33 2782 2 267 0 9491 6 29246 19 1522 1 151609 100 Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 19012 62 1988 6 2175 7 968 3 3612 12 2636 9 473 2 30865 100 Lindi Rur 14952 34 2948 7 7113 16 503 1 10642 24 7787 18 0 0 43945 100 Nachingwea 16442 47 2260 7 6246 18 1216 4 3933 11 4199 12 432 1 34728 100 Liwale 7950 73 1083 10 1015 9 142 1 556 5 54 1 26 0 10825 100 Ruangwa 9629 36 881 3 2822 10 728 3 3465 13 9301 34 261 1 27086 100 Lindi Urb 1766 61 37 1 178 6 208 7 655 22 35 1 35 1 2913 100 Total 69750 46 9198 6 19549 13 3765 3 22862 15 24012 16 1226 1 150362 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 7400 25 1711 6 7646 26 2302 8 8038 27 2209 7 78 0 473 2 29856 100 Lindi Rur 8321 19 2762 6 9102 21 392 1 15537 35 8133 18 0 0 0 0 44246 100 Nachingwea 7067 20 1645 5 8825 25 1302 4 10741 31 4633 13 0 0 520 1 34733 100 Liwale 1875 18 715 7 4760 46 712 7 2264 22 27 0 28 0 26 0 10407 100 Ruangwa 3389 12 2196 8 3430 13 1123 4 7236 27 9512 35 69 0 267 1 27222 100 Lindi Urb 537 17 37 1 72 2 35 1 2440 77 67 2 0 0 0 0 3189 100 Total 28590 19 9066 6 33835 23 5865 4 46256 31 24582 16 175 0 1286 1 149655 100 Total Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 197 Number % Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 8300 28 17667 60 542 2 79 0 960 3 1384 5 0 0 394 1 29324 100 Lindi Rur 13412 34 18298 47 812 2 318 1 2118 5 3828 10 0 0 199 1 38985 100 Nachingwea 3494 13 16849 63 781 3 88 0 2619 10 2626 10 0 0 262 1 26719 100 Liwale 2118 28 4929 64 140 2 0 0 140 2 56 1 0 0 310 4 7692 100 Ruangwa 2506 12 13618 63 466 2 66 0 1612 7 2967 14 137 1 262 1 21634 100 Lindi Urb 531 20 1316 49 36 1 0 0 141 5 662 25 0 0 0 0 2687 100 Total 30360 24 72677 57 2777 2 551 0 7589 6 11524 9 137 0 1426 1 127042 100 Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 13350 43 13996 45 236 1 0 0 2791 9 530 2 475 2 31377 100 Lindi Rur 18180 41 17265 38 595 1 425 1 4674 10 3515 8 199 0 44853 100 Nachingwea 12741 36 12986 37 1308 4 88 0 3669 10 4289 12 87 0 35167 100 Liwale 5124 45 4504 40 84 1 0 0 730 6 784 7 54 0 11281 100 Ruangwa 5467 20 14016 51 540 2 0 0 3280 12 3720 14 199 1 27222 100 Lindi Urb 1270 40 1033 32 72 2 0 0 329 10 485 15 0 0 3189 100 Total 56132 37 63800 42 2835 2 512 0 15472 10 13323 9 1015 1 153089 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Kilwa 12422 42 15675 53 297 1 0 0 240 1 380 1 159 1 394 1 29568 100 Lindi Rur 21401 50 16743 39 518 1 528 1 1217 3 2126 5 0 0 103 0 42636 100 Nachingwea 11146 33 17029 50 525 2 263 1 2273 7 2540 7 173 1 87 0 34037 100 Liwale 4343 44 5142 52 198 2 0 0 141 1 85 1 0 0 54 1 9963 100 Ruangwa 10236 48 8313 39 465 2 67 0 135 1 2092 10 0 0 129 1 21438 100 Lindi Urb 1836 62 890 30 72 2 35 1 70 2 0 0 0 0 37 1 2940 100 Total 61383 44 63793 45 2074 1 893 1 4077 3 7223 5 332 0 805 1 140582 100 Locally Produced b Other Total Other Total Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour RDo not Know How tInput is of No Use Other Total Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour RDo not Know How tInput is of No Use Locally Produced b Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 198 Number % Number % Number % Number % Lindi Rur 192 67 96 33 0 0 288 100 Nachingwea 0 0 86 100 0 0 86 100 Liwale 168 50 111 33 54 16 334 100 Ruangwa 339 38 478 54 66 7 883 100 Total 700 44 771 48 120 8 1591 100 Number % Number % Number % Number % Kilwa 81 16 287 56 144 28 512 100 Lindi Rur 101 11 501 55 306 34 908 100 Nachingwea 0 0 439 100 0 0 439 100 Liwale 143 24 338 57 112 19 593 100 Ruangwa 68 50 68 50 0 0 137 100 Lindi Urb 101 37 175 63 0 0 276 100 Total 494 17 1809 63 562 20 2865 100 Number % Number % Number % Number % Kilwa 1126 74 395 26 0 0 1520 100 Lindi Rur 103 17 203 33 301 50 607 100 Nachingwea 87 20 260 60 87 20 434 100 Liwale 282 30 594 64 54 6 931 100 Total 1598 46 1451 42 443 13 3492 100 Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total Average Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Total District Excellent Good Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 199 Number % Number % Number % Number % Number % Number % Kilwa 323 16 1506 73 224 11 0 0 0 0 2052 100 Lindi Rur 1113 19 3355 57 1090 19 100 2 210 4 5868 100 Nachingwea 953 11 6009 71 1135 13 350 4 0 0 8448 100 Liwale 566 15 1857 51 1026 28 195 5 28 1 3672 100 Ruangwa 1432 26 2502 45 1516 27 0 0 139 2 5588 100 Lindi Urb 216 43 212 42 37 7 37 7 0 0 502 100 Total 4602 18 15442 59 5029 19 682 3 377 1 26131 100 Number % Number % Number % Liwale 28.55308642 50 28.553086 50 57.10617284 100 Total 28.55308642 50 28.553086 50 57.10617284 100 Number % Number % Number % Number % Number % Number % Kilwa 728 40 919 51 162 9 0 0 0 0 1809 100 Lindi Rur 917 41 1299 59 0 0 0 0 0 0 2217 100 Nachingwea 348 31 782 69 0 0 0 0 0 0 1129 100 Liwale 285 20 755 54 363 26 0 0 0 0 1402 100 Ruangwa 2316 40 2364 41 967 17 69 1 69 1 5785 100 Lindi Urb 108 43 141 57 0 0 0 0 0 0 249 100 Total 4702 37 6260 50 1491 12 69 1 69 1 12591 100 Number % Number % Number % Kilwa 1605 5 29772 95 31377 100 Lindi Rur 3567 8 41287 92 44853 100 Nachingwea 3843 11 31324 89 35167 100 Liwale 1996 18 9395 82 11392 100 Ruangwa 1887 7 25335 93 27222 100 Lindi Urb 326 10 2863 90 3189 100 Total 13225 9 139975 91 153200 100 Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Chemical Fertilizers Number of Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Total Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Poor Does not Work Total Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Excellent Average Total Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Does not Work Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 200 Number % Number % Number % Kilwa 2323 7 29054 93 31377 100 Lindi Rur 9319 21 35534 79 44853 100 Nachingwea 2089 6 33078 94 35167 100 Liwale 986 9 10433 91 11418 100 Ruangwa 871 3 26352 97 27222 100 Lindi Urb 831 26 2358 74 3189 100 Total 16418 11 136809 89 153227 100 Number % Number % Number % Kilwa 2053 7 29323 93 31377 100 Lindi Rur 6930 15 37924 85 44853 100 Nachingwea 3924 11 31243 89 35167 100 Liwale 734 6 10604 94 11338 100 Ruangwa 955 4 26267 96 27222 100 Lindi Urb 553 17 2636 83 3189 100 Total 15149 10 137998 90 153147 100 Number % Number % Number % Kilwa 6094 19 25283 81 31377 100 Lindi Rur 10644 24 34209 76 44853 100 Nachingwea 13606 39 21560 61 35167 100 Liwale 5105 45 6260 55 11365 100 Ruangwa 7950 29 19272 71 27222 100 Lindi Urb 577 18 2612 82 3189 100 Total 43977 29 109196 71 153173 100 Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides Number of Agricultural Households With NO Plan to use Next Year Pesticides/Fungicide s Total Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year COMPOST Manure Number of Agricultural Households With NO Plan to use Next Year COMPOST Manure Total Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Farm Yard Manure Number of Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 201 Number % Number % Number % Kilwa 1743 6 29634 94 31377 100 Lindi Rur 1802 4 43051 96 44853 100 Nachingwea 2098 6 33069 94 35167 100 Liwale 310 3 11028 97 11338 100 Ruangwa 545 2 26678 98 27222 100 Lindi Urb 35 1 3155 99 3189 100 Total 6532 4 146615 96 153147 100 Number % Number % Number % Kilwa 9251 29 22125 71 31377 100 Lindi Rur 14370 32 30484 68 44853 100 Nachingwea 10464 30 24702 70 35167 100 Liwale 3451 30 7913 70 11365 100 Ruangwa 10550 39 16673 61 27222 100 Lindi Urb 1748 55 1442 45 3189 100 Total 49834 33 103339 67 153173 100 Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Kilwa 107571 1271 79 1317 0 0 0 0 0 0 0 0 0 242 0 242 0 0 0 0 107650 3073 Lindi Rur 147360 2459 920 2896 0 0 96 0 0 0 0 0 0 0 0 0 0 0 0 0 148376 5354 Nachingwea 122144 1824 258 2080 0 0 0 438 0 0 0 0 0 0 0 0 0 0 0 0 122402 4342 Liwale 41943 253 142 849 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 42085 1102 Ruangwa 83128 944 0 1149 0 0 0 0 0 0 0 0 62 62 0 0 0 0 0 0 83191 2155 Lindi Urb 11102 0 67 224 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11168 224 Total 513247 6750 1467 8514 0 0 96 438 0 0 0 0 62 305 0 242 0 0 0 0 514872 16250 Hand Hoe Hand Powered Sprayer Ox Plough Tractor Tractor Plough Kilwa 30767 1396 0 242 242 Lindi Rur 44659 3304 96 0 0 Nachingwea 35167 1639 88 0 0 Liwale 11336 963 0 0 0 Ruangwa 27222 1083 0 62 0 Lindi Urb 3189 291 0 0 0 Total 152341 8676 184 305 242 Table 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year District Implement / Asset Name Tractor Plough Tractor Harrow Threshers / Shellers Total Table 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 District Implement / Asset Name Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural HouNumber of AgriculturaTotal Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Herbicides Number of Agricultural Households With NO Plan to use Next Year Herbicides Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 202 Number % Number % Number % Kilwa 139 26 391 74 530 100 Lindi Rur 0 0 99 100 99 100 Liwale 0 0 29 100 29 100 Total 139 21 519 79 658 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 13950 46 10204 34 4248 14 79 0 1580 5 0 0 30060 100 Lindi Rur 18626 45 11193 27 8969 22 0 0 2649 6 208 0 41644 100 Nachingwea 14504 43 8686 26 8853 26 0 0 1397 4 88 0 33528 100 Liwale 5612 54 3428 33 1109 11 0 0 222 2 57 1 10428 100 Ruangwa 9173 35 6401 25 6435 25 0 0 3996 15 68 0 26073 100 Lindi Urb 1706 59 421 15 416 14 0 0 356 12 0 0 2898 100 Total 63570 44 40333 28 30029 21 79 0 10200 7 421 0 144632 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 23770 76 5163 16 1888 6 243 1 313 1 0 0 31377 100 Lindi Rur 31841 71 5194 12 6729 15 634 1 455 1 0 0 44853 100 Nachingwea 23792 68 5725 16 4601 13 0 0 875 2 174 0 35167 100 Liwale 7846 69 2056 18 1270 11 29 0 112 1 0 0 11311 100 Ruangwa 16830 62 2533 9 6716 25 203 1 738 3 67 0 27087 100 Lindi Urb 2691 84 69 2 247 8 0 0 181 6 0 0 3189 100 Total 106769 70 20741 14 21451 14 1109 1 2673 2 241 0 152984 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 22355 71 6411 20 2372 8 0 0 239 1 0 0 31377 100 Lindi Rur 30742 69 6013 13 7078 16 531 1 394 1 0 0 44757 100 Nachingwea 24226 69 5202 15 4774 14 175 0 614 2 88 0 35079 100 Liwale 7812 69 2088 18 1383 12 0 0 56 0 0 0 11338 100 Ruangwa 16684 61 2533 9 7128 26 69 0 673 2 67 0 27156 100 Lindi Urb 2691 84 69 2 279 9 0 0 149 5 0 0 3189 100 Total 104510 68 22317 15 23014 15 775 1 2125 1 155 0 152896 100 Table 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Table 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Table 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total District Not Available Price Too High Total Table 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 203 Number % Number % Number % Number % Number % Number % Number % Kilwa 21225 68 6655 21 2773 9 80 0 643 2 0 0 31377 100 Lindi Rur 28396 63 5663 13 7840 17 531 1 2325 5 100 0 44853 100 Nachingwea 23535 67 5022 14 5033 14 264 1 1225 3 88 0 35167 100 Liwale 7791 69 2050 18 1385 12 0 0 111 1 0 0 11338 100 Ruangwa 14770 54 3907 14 7265 27 69 0 1077 4 67 0 27156 100 Lindi Urb 2437 76 75 2 348 11 0 0 330 10 0 0 3189 100 Total 98155 64 23373 15 24644 16 943 1 5710 4 254 0 153080 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 21316 68 6880 22 2859 9 78 0 243 1 0 0 31377 100 Lindi Rur 30008 67 6391 14 7370 16 531 1 553 1 0 0 44853 100 Nachingwea 22750 65 5371 15 5558 16 87 0 1313 4 88 0 35167 100 Liwale 7593 67 2223 20 1353 12 0 0 139 1 57 1 11365 100 Ruangwa 15201 56 3756 14 7121 26 138 1 939 3 67 0 27222 100 Lindi Urb 2449 77 75 2 412 13 0 0 253 8 0 0 3189 100 Total 99319 65 24696 16 24672 16 834 1 3441 2 212 0 153173 100 Number % Number % Number % Number % Number % Number % Kilwa 14669 47 7467 24 8696 28 302 1 0 0 31134 100 Lindi Rur 12456 28 13792 31 18141 40 464 1 0 0 44853 100 Nachingwea 9540 27 9737 28 15188 43 526 1 176 0 35167 100 Liwale 5297 47 4208 37 1750 15 56 0 0 0 11311 100 Ruangwa 3924 14 10834 40 12268 45 67 0 0 0 27093 100 Lindi Urb 1046 33 572 18 1571 49 0 0 0 0 3189 100 Total 46932 31 46610 31 57615 38 1416 1 176 0 152748 100 Number % Number % Number % Number % Number % Number % Kilwa 15273 49 7498 24 8060 26 302 1 0 0 31134 100 Lindi Rur 14455 32 12228 27 18014 40 156 0 0 0 44853 100 Nachingwea 10591 30 9299 26 14750 42 439 1 88 0 35167 100 Liwale 5496 48 4092 36 1721 15 56 0 0 0 11365 100 Ruangwa 4867 18 8877 33 12061 44 1351 5 67 0 27222 100 Lindi Urb 664 21 576 18 1950 61 0 0 0 0 3189 100 Total 51346 34 42570 28 56556 37 2304 2 155 0 152931 100 Table 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Equipment / Asset of No Use Other Total Table 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Equipment / Asset oOther Total Table 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour REquipment / Asset oOther Total Table 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 204 Number % Number % Number % Number % Number % Number % Number % Kilwa 16495 53 7642 24 7019 22 0 0 221 1 0 0 31377 100 Lindi Rur 16538 37 11618 26 16079 36 106 0 512 1 0 0 44853 100 Nachingwea 11466 33 7809 22 11701 33 0 0 4015 11 176 0 35167 100 Liwale 5384 47 4121 36 1804 16 0 0 56 0 0 0 11365 100 Ruangwa 5551 20 8130 30 10564 39 0 0 2911 11 67 0 27222 100 Lindi Urb 846 27 464 15 1557 49 0 0 322 10 0 0 3189 100 Total 56279 37 39783 26 48724 32 106 0 8038 5 243 0 153173 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 17611 56 7276 23 5121 16 81 0 1208 4 79 0 31377 100 Lindi Rur 21884 49 8535 19 9351 21 0 0 5082 11 0 0 44853 100 Nachingwea 17211 49 5282 15 4836 14 0 0 7751 22 88 0 35167 100 Liwale 6092 54 2843 25 1385 12 0 0 1015 9 28 0 11365 100 Ruangwa 9897 36 4819 18 7627 28 0 0 4812 18 67 0 27222 100 Lindi Urb 941 30 300 9 580 18 0 0 1368 43 0 0 3189 100 Total 73637 48 29055 19 28901 19 81 0 21237 14 262 0 153173 100 Number % Number % Number % Number % Number % Number % Number % Kilwa 21114 69 8125 26 679 2 78 0 80 0 610 2 30686 100 Lindi Rur 23971 54 16748 38 1203 3 98 0 0 0 2539 6 44559 100 Nachingwea 26055 74 6596 19 784 2 260 1 0 0 1472 4 35167 100 Liwale 9949 88 1108 10 113 1 0 0 0 0 167 1 11336 100 Ruangwa 21750 80 3805 14 736 3 69 0 0 0 863 3 27222 100 Lindi Urb 1602 50 1227 38 184 6 35 1 0 0 142 4 3189 100 Total 104441 69 37608 25 3699 2 539 0 80 0 5793 4 152160 100 Number % Number % Number % Number % Number % Kilwa 79 100 0 0 0 0 0 0 79 100 Lindi Rur 203 28 315 44 95 13 100 14 713 100 Nachingwea 258 100 0 0 0 0 0 0 258 100 Liwale 114 100 0 0 0 0 0 0 114 100 Lindi Urb 67 100 0 0 0 0 0 0 67 100 Total 721 59 315 26 95 8 100 8 1231 100 Table 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Remittances Other Total Table 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District District Sale of Farm Products Other Income GeneraRemittances Bank Loan Credit Other Total Table 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Table 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour REquipment / Asset oOther Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 205 Number % Number % Lindi Rur 96.19541667 100 96.195417 100 Total 96.19541667 100 96.195417 100 Number % Number % Ruangwa 62.24662309 100 62.246623 100 Total 62.24662309 100 62.246623 100 Table 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District District Sale of Farm Products Total Table 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District District Other Income Generating Activities Total Tanzania Agriculture Sample Census - 2003 Lindi 206 Appendix II 207 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 208 Number % Number % Lindi Rural 100 50 101 50 201 Nachingwea 85 100 0 0 85 Liwale 84 75 28 25 112 Ruangwa 137 100 0 0 137 Total 405 76 130 24 535 Family, Friend and Relative Co- operative Private Individual Religious Organisatio n / NGO / Project Other Lindi Rural 100 0 101 0 0 201 Nachingwea 0 85 0 0 0 85 Liwale 0 0 0 84 28 112 Ruangwa 68 69 0 0 0 137 Total 168 154 101 84 28 535 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year District Male Female Total 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District Source of Credit Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 209 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Kilwa 449 7,705 917 151 14,638 826 81 0 6,609 31,377 Lindi Rural 1,128 6,291 3,203 202 21,657 1,662 102 0 10,409 44,653 Nachingwea 784 12,222 2,078 87 11,039 788 87 0 7,996 35,081 Liwale 171 3,835 390 582 3,658 452 222 29 1,914 11,253 Ruangwa 539 4,290 2,017 134 11,413 600 404 137 7,549 27,086 Lindi Urban 183 1,416 447 35 549 32 108 0 418 3,189 Total 3,255 35,759 9,052 1,191 62,954 4,359 1,006 166 34,896 152,638 District Labour Fertilizers Agro- chemicals Tools / Equipment Livestock Total Credits Lindi Rural 101 0 100 0 0 201 Nachingwea 0 0 85 0 0 85 Liwale 0 28 0 0 84 112 Ruangwa 0 0 69 68 0 137 Total Credits 101 28 254 68 84 535 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Lindi 210 Appendix II 211 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 212 Number % Number % Number % Kilwa 0 0 31377 100 31377 100 Lindi Rural 303 1 44551 99 44853 100 Nachingwea 0 0 35167 100 35167 100 Liwale 28 0 11336 100 11365 100 Ruangwa 257 1 26965 99 27222 100 Lindi Urban 32 1 3157 99 3189 100 Total 620 0 152553 100 153173 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Lindi Rural 302 1097 0 . 303 1097 Liwale 0 . 28 142 28 142 Ruangwa 256 1252 0 . 257 1252 Lindi Urban 32 321 0 . 32 321 Total 592 2670 28 142 620 2812 District Senna Spp Eucalyptus Spp Melicia excelsa Azadritachta Spp Trichilia Spp Total Lindi Rural . . 301 103 693 1097 Liwale . 142 . . . 142 Ruangwa 687 . . 565 . 1252 Lindi Urban 321 . . . . 321 Total 1008 142 301 668 693 2812 Planks / Timber Shade Medicinal Other Total Lindi Rural 100 103 99 0 303 Liwale 0 28 0 0 28 Ruangwa 0 188 0 69 257 Lindi Urban 0 32 0 0 32 Total 100 352 99 69 620 Charcoal Fuel for Wood Shade Medicinal Other Total Lindi Rural 100 0 0 103 99 303 Liwale 0 28 0 0 0 28 Ruangwa 0 0 69 188 0 257 Lindi Urban 0 32 0 0 0 32 Total 100 60 69 292 99 620 14.1 ON FARM TREE FARMING: Number of Households Having Planted Trees By District District Did your Hh have any Planted Trees on your land during 2002/ Households Having Planted Trees Households Not Having Planted Trees Total 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Where Planted y Boundaries Mostly Scattered in Field Total 14.3 ON FARM TREE PLANTING: Number of Planted Trees By Species and District 14.4 TREE FARMING: Main Use of Trees By District District Main Use 14.5 TREE FARMING: Second Use of Trees By District District Second Use Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 213 Number % Number % Number % Kilwa 1128 4 30249 96 31377 100 Lindi Rural 0 0 44757 100 44757 100 Nachingwea 0 0 35167 100 35167 100 Liwale 28 0 11252 100 11281 100 Ruangwa 66 0 27157 100 27222 100 Lindi Urban 64 2 3125 98 3189 100 Total 1286 1 151707 99 152993 100 0-9 1-19 40-49 Total Kilwa 1128 0 0 1128 Liwale 0 28 0 28 Ruangwa 66 0 0 66 Lindi Urban 0 32 32 64 Total 1194 60 32 1286 Poles Timber Logs Not Ready to Use Not Allowed to Use Total Kilwa 81 886 161 0 1128 Liwale 0 0 0 28 28 Ruangwa 0 0 0 66 66 Lindi Urban 0 0 64 0 64 Total 81 886 225 94 1286 14.3 TREE FARMING: Number of Households By Whether Village Have a Community Tree Planting Scheme By District District does your village have a Community Tree Planting Scheme Have a Community Tree Planting Scheme Does not Have a Community Tree Planting Scheme Total District Main use during 2002/03 14.3 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) 14.3 TREE FARMING: Number of Households Involved in Community Tree Planting Scheme By Main Use and District Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 214 Planks / Timber Shade Medicinal Other Total Lindi Rural 1 1 1 0 3 Liwale 0 1 0 0 1 Ruangwa 0 3 0 1 4 Lindi Urban 0 1 0 0 1 Total 1 6 1 1 9 1-9 1-19 40-49 Total Kilwa 161 0 0 161 Liwale 0 28 0 28 Lindi Urban 0 32 32 64 Total 161 60 32 254 % 16,111 6,048 3,207 25,366 Charcoal Fuel for Wood Shade Medicinal Other Total Lindi Rural 1 0 0 1 1 3 Liwale 0 1 0 0 0 1 Ruangwa 0 0 1 3 0 4 Lindi Urban 0 1 0 0 0 1 Total 1 2 1 4 1 9 % 11.1 22.2 11.1 44.4 11.1 100 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Lindi Region District Main Use 14.4TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Lindi Region District Distance to Community Planted Forest (km) 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Lindi Region District Second Use Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 215 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 216 Number % Number % Kilwa 6,280 20.0 25,097 80.0 31,377 Lindi Rural 6,551 14.6 38,302 85.4 44,853 Nachingwea 4,194 11.9 30,972 88.1 35,167 Liwale 2,468 21.7 8,897 78.3 11,365 Ruangwa 5,191 19.1 22,032 80.9 27,222 Lindi Urban 888 27.8 2,301 72.2 3,189 Total 25,571 16.7 127,602 83.3 153,173 Number % Number % Number % Number % Number % Number % Kilwa 319 5.09 3,879 61.77 1,852 29.49 230 3.65 0 0 6,280 100 Lindi Rural 954 14.56 5,045 77.01 552 8.43 0 0.00 0 0 6,551 100 Nachingwea 1,748 41.67 1,659 39.55 525 12.52 175 4.17 88 2.09 4,194 100 Liwale 481 19.49 1,450 58.76 537 21.74 0 0.00 0 0 2,468 100 Ruangwa 399 7.70 4,525 87.17 197 3.80 69 1.33 0 0 5,191 100 Lindi Urban 293 33.03 560 63.04 35 3.93 0 0.00 0 0 888 100 Total 4,195 16.40 17,117 66.94 3,698 14.46 474 1.85 88 0.34 25,571 100 Total Number % Number % Number % Number % Number Kilwa 6,280 100 0 0 0 0 0 0 6,280 Lindi Rural 6,355 97.01 100 1.52 0 0 96 1.47 6,551 Nachingwea 3,932 93.74 87 2.07 0 0 175 4.18 4,194 Liwale 2,468 100 0 0 0 0 0 0 2,468 Ruangwa 4,926 96.09 0 0 69 1.34 132 2.57 5,126 Lindi Urban 888 100 0 0 0 0 0 0 888 Total 24,848 97.42 187 0.73 69 0.27 403 1.58 25,507 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Lindi Region District Households Receiving Households Not Total Number of Households 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Lind Very Good Good Average Poor No Good Total 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region Government NGO / Development Cooperative Large Scale Farm Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 217 Government NGO / Development Project Large Scale Farm Total Kilwa 5,780 0 0 5,780 Lindi Rural 6,096 100 96 6,292 Nachingwea 3,756 87 88 3,931 Liwale 2,468 0 0 2,468 Ruangwa 4,787 0 132 4,919 Lindi Urban 851 0 0 851 Total 23,738 187 315 24,240 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Kilwa 1,718 0 0 0 79 0 1,797 Lindi Rural 2,653 96 0 96 0 96 2,942 Nachingwea 1,396 87 0 0 87 0 1,570 Liwale 1,363 0 0 29 29 29 1,449 Ruangwa 1,205 0 69 0 0 0 1,274 Lindi Urban 493 0 0 0 0 0 493 Total 8,828 183 69 125 195 125 9,524 Government NGO / Development Project Not applicable Total Kilwa 72 0 0 72 Lindi Rural 791 0 482 1,274 Nachingwea 351 87 0 438 Liwale 684 0 29 712 Ruangwa 62 0 0 62 Lindi Urban 107 0 0 107 Total 2,067 87 511 2,664 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Spacing District Erosion Control 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Use of Agrochemicals 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 218 Government Not applicable Total Kilwa 911 0 911 Lindi Rural 2,273 481 2,754 Nachingwea 175 0 175 Liwale 913 29 941 Ruangwa 273 67 340 Lindi Urban 316 0 316 Total 4,861 576 5,437 Government NGO / Development Project Large Scale Farm Not applicable Total Kilwa 823 0 0 0 823 Lindi Rural 1,654 0 192 192 2,039 Nachingwea 436 87 0 86 609 Liwale 1,307 0 0 0 1,307 Ruangwa 341 0 0 0 341 Lindi Urban 75 0 0 35 109 Total 4,635 87 192 312 5,227 Government NGO / Development Project Large Scale Farm Other Not applicable Total Kilwa 3,682 0 0 0 0 3,682 Lindi Rural 4,626 0 96 0 96 4,818 Nachingwea 1,307 87 88 0 0 1,481 Liwale 1,989 29 0 29 0 2,046 Ruangwa 1,462 0 0 67 0 1,529 Lindi Urban 712 0 0 0 37 749 Total 13,777 116 184 96 134 14,306 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Organic Fertilizer Use 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Inorganic Fertilizer Use 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Use of Improved Seed Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 219 Government Not applicable Total Kilwa 594 0 594 31,377 1.9 Lindi Rural 509 678 1,187 44,853 2.6 Nachingwea 173 0 173 35,167 0.5 Liwale 28 0 28 11,365 0.2 Ruangwa 273 0 273 27,222 1.0 Lindi Urban 389 0 389 3,189 12.2 Total 1,967 678 2,645 153,173 1.7 Government Large Scale Farm Not applicable Total Number of Households Kilwa 243 0 0 243 31,377 0.8 Lindi Rural 505 0 487 992 44,853 2.2 Nachingwea 175 0 0 175 35,167 0.5 Liwale 514 29 0 543 11,365 4.8 Ruangwa 198 0 0 198 27,222 0.7 Lindi Urban 0 0 0 0 3,189 0.0 Total 1,635 29 487 2,150 153,173 1.4 Government NGO / Development Project Large Scale Farm Other Not applicable Total Kilwa 3,201 0 0 79 0 3,279 31,377 10 Lindi Rural 2,083 0 0 0 482 2,566 44,853 6 Nachingwea 608 0 0 176 0 783 35,167 2 Liwale 1,646 29 0 0 29 1,704 11,365 15 Ruangwa 1,759 0 67 0 0 1,826 27,222 7 Lindi Urban 315 0 0 0 0 315 3,189 10 Total 9,611 29 67 255 511 10,472 153,173 7 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi District Mechanisation / LST Total Number of Households % of total number of households 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Irrigation Technology Total Number of Households % of total number of households 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Crop Storage Total Number of Households % of total number of household s Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 220 Government NGO / Development Project Large Scale Farm Not applicable Total Kilwa 3,754 58 0 0 3,812 31,377 12 Lindi Rural 2,275 0 192 540 3,007 44,853 7 Nachingwea 262 0 0 0 262 35,167 1 Liwale 1,561 0 0 0 1,561 11,365 14 Ruangwa 3,640 0 0 0 3,640 27,222 13 Lindi Urban 381 0 0 0 381 3,189 12 Total 11,874 58 192 540 12,664 153,173 8 Government Large Scale Farm Other Not applicable Total Kilwa 552 0 0 0 552 31,377 1.8 Lindi Rural 1,318 96 54 487 1,954 44,853 4.4 Nachingwea 87 0 0 0 87 35,167 0.2 Liwale 620 0 0 29 648 11,365 5.7 Ruangwa 137 0 0 0 137 27,222 0.5 Lindi Urban 0 0 0 0 0 3,189 0.0 Total 2,714 96 54 515 3,378 153,173 2.2 Government NGO / Development Project Not applicable Total Kilwa 504 0 0 504 31,377 1.6 Lindi Rural 605 0 482 1,087 44,853 2.4 Nachingwea 0 0 0 0 35,167 0.0 Liwale 370 0 0 370 11,365 3.3 Ruangwa 62 0 0 62 27,222 0.2 Lindi Urban 35 35 0 69 3,189 2.2 Total 1,575 35 482 2,092 153,173 1.4 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Vermin Control Total Number of Households % of total number of households 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Agro-progressing Total Number of Households % of total number of households 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Agro-forestry Total Number of Households % of total number of households Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 221 Government NGO / Development Project Large Scale Farm Not applicable Total Kilwa 81 0 0 0 81 31,377 0.3 Lindi Rural 99 0 0 482 581 44,853 1.3 Nachingwea 0 0 0 0 0 35,167 0.0 Liwale 0 28 29 0 57 11,365 0.5 Ruangwa 0 0 0 0 0 27,222 0.0 Lindi Urban 35 0 0 0 35 3,189 1.1 Total 214 28 29 482 753 153,173 0.5 Received Adopted % Received Adopted % Received Adopted % Kilwa 839 407 48.5 823 235 29 3,740 948 25 Lindi Rural 2,169 797 36.8 1,645 749 46 4,776 2,206 46 Nachingwea 175 174 99.6 609 349 57 1,481 610 41 Liwale 884 257 29.1 1,307 228 17 2,046 1,532 75 Ruangwa 0 0 0.0 273 341 125 1,596 659 41 Lindi Urban 316 141 44.5 75 0 0 749 351 47 Total 4,383 1,776 40.5 4,732 1,901 40 14,388 6,306 44 Received Adopted % Received Adopted % Received Adopted % Kilwa 594 159 27 243 162 67 3,198 3,058 96 Lindi Rural 204 605 297 505 409 81 1,983 1,379 70 Nachingwea 173 88 51 87 87 100 783 608 78 Liwale 28 0 0 543 343 63 1,704 1,392 82 Ruangwa 205 272 133 0 130 0 1,826 1,690 93 Lindi Urban 389 37 10 0 0 0 315 173 55 Total 1,594 1,162 73 1,378 1,131 82 9,808 8,300 85 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Lindi Region District Beekeeping Total Number of Households % of total number of households 15.17 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Lindi Region District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Lindi Region District Mechanisation / LST Irrigation Technology Crop Storage Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 222 Received Adopted % Received Adopted % Received Adopted % Kilwa 3,812 3,659 96 552 552 100 504 144 29 Lindi Rural 2,567 1,347 52 1,368 1,417 104 506 100 20 Nachingwea 175 87 50 87 87 100 0 0 0 Liwale 1,590 1,476 93 648 394 61 370 370 100 Ruangwa 3,640 2,360 65 69 273 398 0 136 0 Lindi Urban 418 383 92 0 0 0 69 35 50 Total 12,202 9,312 76 2,725 2,724 100 1,449 785 54 Received Adopted % Received Adopted % Kilwa 81 81 100 0 79 0 Lindi Rural 99 99 100 103 99 96 Nachingwea 0 0 0 0 0 0 Liwale 57 57 100 371 0 0 Ruangwa 0 0 0 0 0 0 Lindi Urban 35 0 0 35 0 0 Total 271 237 87 509 177 35 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Lindi Region District Vermin Control Agro-progressing Agro-forestry 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Lindi Region District Beekeeping Fish Farming Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 223 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 224 Number % Number % Kilwa 0 0 31,377 100 31,377 Lindi Rural 0 0 44,853 100 44,853 Nachingwea 0 0 35,167 100 35,167 Liwale 0 0 11,365 100 11,365 Ruangwa 0 0 27,222 100 27,222 Lindi Urban 0 0 3,189 100 3,189 Total 0 0 153,173 100 153,173 Number % Number % Number % Kilwa 1,387 29.2 29,426 20.0 30,813 20.3 Lindi Rural 1,105 23.3 43,381 29.5 44,486 29.3 Nachingwea 872 18.4 34,119 23.2 34,991 23.1 Liwale 1,044 22.0 10,292 7.0 11,337 7.5 Ruangwa 137 2.9 26,811 18.2 26,948 17.8 Lindi Urban 201 4.2 2,988 2.0 3,189 2.1 Total 4,746 100.0 147,018 100.0 151,764 100.0 Area (Ha) %Area (Ha) % Area (Ha) % Kilwa 328 12.2 654 23.9 981 18.1 Lindi Rural 1,356 50.4 802 29.4 2,158 39.8 Nachingwea 246 9.1 954 34.9 1,199 22.1 Liwale 224 8.3 321 11.8 545 10.0 Ruangwa 205 7.6 0 0.0 205 3.8 Lindi Urban 335 12.4 0 0.0 335 6.2 Total 2,693 100.0 2,730 100.0 5,423 100.0 17.3 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost District Farm Yard Manure Area Compost Area Applied Total Area aplied with 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Lindi Region Households Using Draft Animals Household Not Using Draft Animals Total households 17.2 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Lindi District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 225 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 226 18.1 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Lindi Rural 199 896 68.9 0 0 0.0 202 405 31.1 401 1,300 42.2 Nachingwea 88 352 50.2 0 0 0.0 174 348 49.8 262 700 22.7 Lindi Urban 104 772 71.4 32 64 5.9 105 245 22.7 175 1,080 35.1 Total 391 2,019 65.5 32 64 2.1 482 998 32.4 838 3,080 100.0 Number % Number % 1-4 648 42 1,695 14 3 5-9 380 24 2,650 22 7 10-14 362 23 4,237 36 12 15-19 68 4 1,161 10 17 20-24 68 4 1,365 11 20 25-29 28 2 797 7 28 Total 1,555 100 11,905 100 8 Number % Number % Number % Number % Bulls 187 55 64 19 87 26 339 11 Cows 693 70 . 0 293 30 987 32 Heifers 645 84 . 0 122 0 767 25 Male Calves 166 55 . 0 137 45 303 10 Female Calve 326 48 . 0 358 52 685 22 Total 2,019 66 64 2 998 32 3,080 100 Bulls Cows Heifers Male Calves Female Calves Total Lindi Rural 100 299 299 100 100 896 Nachingwea 88 88 88 . 88 352 Lindi Urban . 307 259 67 139 772 Total 187 693 645 166 326 2,019 District Category - Indigenous 18.3 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 Category of Cattle Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Total 18.4 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District Total Cattle 18.2 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Herd Size Cattle Rearing Households Heads of Cattle Average Number Per Household District Indigenous Improved Beef Improved Dairy Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 227 Category - Improved Beef Cattle Bulls Cows Heifers Male Calves Female Calves Total Lindi Rural . . . . . . Nachingwea . . . . . . Lindi Urban 64 . . . . 64 Total 64 . . . . 64 Bulls Cows Heifers Male Calves Female Calves Total Lindi Rural . 101 . 101 202 405 Nachingwea 87 87 87 . 87 348 Lindi Urban . 105 35 36 69 245 Total 87 293 122 137 358 998 Bulls Cows Heifers Male Calves Female Calves Total Lindi Rural 100 400 299 201 302 1,300 Nachingwea 175 175 175 . 175 700 Lindi Urban 64 412 294 103 208 1,080 Total 339 987 767 303 685 3,080 District Total Cattle 18.6 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.7 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 District 18.5 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Lindi 228 Appendix II 229 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 230 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Kilwa 2,552 18,149 88.4 147 1,018 5.0 224 1,364 6.6 2,620 20,531 18.6 Lindi Rural 5,055 41,142 96.2 0 . 0.0 406 1,616 3.8 5,155 42,758 38.7 Nachingwea 3,049 16,540 87.9 87 1,741 9.3 88 526 2.8 3,049 18,807 17.0 Liwale 641 6,318 97.0 28 85 1.3 56 112 1.7 669 6,515 5.9 Ruangwa 1,687 11,449 93.8 136 613 5.0 69 139 1.1 1,687 12,200 11.0 Lindi Urban 869 9,554 98.6 0 . 0.0 35 140 1.4 904 9,694 8.8 Total 13,853 103,152 93.3 398 3,457 3.1 878 3,896 3.5 14,084 110,505 100.0 Number % Number % 1-4 4,979 35 12,651 11 3 5-9 5,633 40 36,963 33 7 10-14 2,146 15 24,288 22 11 15-19 397 3 6,457 6 16 20-24 579 4 12,308 11 21 25-29 119 1 3,074 3 26 30-39 68 0 2,048 2 30 40+ 164 1 12,716 12 77 Total 14,084 100 110,505 100 8 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 District Indigenous Improved for Meat Improved Dairy Total Goat 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Herd Size Goat Rearing Households Head of Goats Average Number Per Household Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 231 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 17,457 95.2 0 0.0 874 4.8 18,331 16.6 Castrated Goat 987 46.5 408 0.0 728 0.0 2,124 1.9 She Goat 53,256 97.0 85 0.2 1,553 2.8 54,895 49.7 Male Kid 14,196 83.1 2,422 14.2 470 2.7 17,088 15.5 She Kid 17,256 95.5 541 3.0 270 1.5 18,067 16.3 Total 103,152 93.3 3,457 3.1 3,896 3.5 110,505 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilwa 2,857 80 9,647 2,602 2,963 18,149 Lindi Rural 7,163 416 19,242 6,004 8,317 41,142 Nachingwea 3,561 87 8,975 1,999 1,918 16,540 Liwale 557 244 4,000 828 688 6,318 Ruangwa 1,889 . 6,489 1,297 1,773 11,449 Lindi Urban 1,430 160 4,903 1,466 1,596 9,554 Total 17,457 987 53,256 14,196 17,256 103,152 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilwa . 408 . 68 541 1,018 Lindi Rural . . . . . . Nachingwea . . . 1,741 . 1,741 Liwale . . 85 . . 85 Ruangwa . . . 613 . 613 Lindi Urban . . . . . . Total . 408 85 2,422 541 3,457 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Total 19.4 Total Number of Indigenous Goat by Category and District as on 1st District Number of Indigenous Goats Category of Goats Indigenous Goats Improved Meat Goatsmproved Dairy Goat Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 232 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilwa 569 . 651 144 . 1,364 Lindi Rural 201 202 811 201 201 1,616 Nachingwea . 526 . . . 526 Liwale . . 56 56 . 112 Ruangwa . . . 69 69 139 Lindi Urban 105 . 35 . . 140 Total 874 728 1,553 470 270 3,896 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilwa 3,425 488 10,299 2,814 3,505 20,531 Lindi Rural 7,364 618 20,053 6,205 8,518 42,758 Nachingwea 3,561 613 8,975 3,740 1,918 18,807 Liwale 557 244 4,142 884 688 6,515 Ruangwa 1,889 . 6,489 1,979 1,843 12,200 Lindi Urban 1,535 160 4,937 1,466 1,596 9,694 Total 18,331 2,124 54,895 17,088 18,067 110,505 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 233 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 234 Number % Number % Number % Ram 1,771 100 0 0 1,771 15 Castrated Sheep 106 100 0 0 106 1 She Sheep 5,912 98 100 0 6,012 50 Male Lamb 1,377 93 100 0 1,476 12 She Lamb 2,440 96 100 4 2,540 21 Total 11,607 97 299 3 11,905 100 Number % Number % Kilwa 0 0.0 31,377 100.2 31,309 2,644 Lindi Rural 606 1.4 44,247 98.6 44,853 5,804 Nachingwea 352 1.0 34,815 99.0 35,167 2,699 Liwale 54 0.5 11,310 100.0 11,310 662 Ruangwa 404 1.5 26,818 98.5 27,222 2,553 Lindi Urban 138 4.4 3,051 96.8 3,153 777 Total 1,555 1.0 151,618 99.1 153,015 15,139 Number % Number % Number % Lindi Rural 4,165 93 299 7 4,464 37 Nachingwea 2,285 100 0 0 2,285 19 Liwale 926 100 0 0 926 8 Ruangwa 3,678 100 0 0 3,678 31 Lindi Urban 552 100 0 0 552 5 Total 11,607 97 299 3 11905.33697 100 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 648 42 1,695 14 3 5-9 380 24 2,650 22 7 10-14 362 23 4,237 36 12 15-19 68 4 1,161 10 17 20-24 68 4 1,365 11 20 25-29 28 2 797 7 28 Total 1,555 100 11,905 100 8 20.1 Total Number of Sheep By Breed and on 1st October 2003 Breed Number of Indigenous Number of Improved for Mutton Total Sheep 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 235 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Lindi Rural 595 106 1,611 503 1,349 4,165 Nachingwea 439 . 1,055 352 439 2,285 Liwale 57 . 450 109 310 926 Ruangwa 615 . 2,380 341 341 3,678 Lindi Urban 64 . 416 72 . 552 Total 1,771 106 5,912 1,377 2,440 11,607 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Lindi Rural . . 100 100 100 299 Nachingwea . . . . . . Liwale . . . . . . Ruangwa . . . . . . Lindi Urban . . . . . . Total . . 100 100 100 299 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Lindi Rural 595 106 1,711 603 1,449 4,464 Nachingwea 439 . 1,055 352 439 2,285 Liwale 57 . 450 109 310 926 Ruangwa 615 . 2,380 341 341 3,678 Lindi Urban 64 . 416 72 . 552 Total 1,771 106 6,012 1,476 2,540 11,905 20.5 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.6 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep Tanzania Agriculture Sample Census - 2003 Lindi 236 Appendix II 237 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 238 Number % Number % 1-4 991 70 2,204 44 2 5-9 415 30 2,752 56 7 Total 1,407 100 4,956 100 4 District Number of Household Number of Pig Average Number Per Household Nachingwea 1,133 4,000 4 Ruangwa 274 956 3 Total 1,407 4,956 4 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Nachingwea 1,305 0 1,132 1,041 522 4,000 Ruangwa 342 . 137 204 273 956 Total 1,647 0 1,268 1,245 795 4,956 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Herd Size Pig Rearing Households Heads of Pigs Average Number Per Household Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 239 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 240 Number of Households % Number of Households % Kilwa 593 26 1,647 74 2,241 Lindi Rural 3,551 62 2,155 38 5,706 Nachingwea 1,134 42 1,565 58 2,699 Liwale 196 31 440 69 636 Ruangwa 1,146 45 1,407 55 2,553 Lindi Urban 345 44 432 56 777 Total 6,967 48 7,646 52 14,613 Number of Households % Number of Households % Number of Households % Number of Households % Kilwa 513 16 81 2 0 0 163 18 Lindi Rural 974 31 2,396 62 100 25 597 65 Nachingwea 874 28 175 5 88 22 86 9 Liwale 196 6 0 0 0 0 0 0 Ruangwa 336 11 1,013 26 137 35 67 7 Lindi Urban 275 9 172 4 67 17 0 0 Total 3,169 100 3,838 100 391 100 913 100 Number of Households % Number of Households % Kilwa 793 34.2 1,528 66 2,321 Lindi Rural 1,594 27 4,210 73 5,804 Nachingwea 260 10 2,439 90 2,699 Liwale 224 33.8 438 66 662 Ruangwa 205 8 2,348 92 2,553 Lindi Urban 416 56 325 44 741 Total 3,493 24 11,288 76 14,781 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. District Ticks Problems No Ticks Problems Total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 241 Number of Households % Number of Households % Number of Households % Number of Households % er of House % Kilwa 362 46 292 37 58 7 0 0 80 10 793 Lindi Rural 203 13 664 42 0 0 105 7 622 39 1,594 Nachingwea 88 34 87 33 0 0 0 0 86 33 260 Liwale 85 38 113 51 26 12 0 0 0 0 224 Ruangwa 68 33 0 0 69 33 0 0 68 33 205 Lindi Urban 38 9 171 41 0 0 0 0 208 50 416 Total 843 24 1,327 38 153 4 105 3 1,065 30 3,493 Number of Households % Number of Households % Kilwa 224 10 2,017 90 2,241 Lindi Rural 823 14 4,981 86 5,804 Nachingwea 87 3 2,612 97 2,699 Liwale 138 22 495 78 634 Ruangwa 137 5 2,416 95 2,553 Lindi Urban 380 49 397 51 777 Total 1,789 12 12,919 88 14,708 Number of Households % Number of Households % Number of Households % Number of Households % Kilwa 224 100 0 0 0 0 0 0 224 Lindi Rural 412 50 307 37 0 0 105 13 823 Nachingwea 87 100 0 0 0 0 0 0 87 Liwale 85 62 27 20 26 19 0 0 138 Ruangwa 137 100 0 0 0 0 0 0 137 Lindi Urban 243 64 137 36 0 0 0 0 380 Total 1,187 66 471 26 26 1 105 6 1,789 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year District Method of Tick Control Total None Spraying Dipping Smearing Other 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District District Tsetse Flies Problems No Tsetse Flies Problems Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year District Method of Tsetse Flies Control None Spray Dipping Trapping Total Tanzania Agriculture Sample Census - 2003 Lindi 242 Appendix II 243 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 244 Number % Type Number Indigenous 1,075,122 85 Ducks 35,334 Layer 33,314 3 Turkeys 6,207 Broiler 152,855 12 Donkeys 2,159 Total 1,261,290 100 43,700 Indigenous Chicken Layer Broiler Ducks Turkeys Donkeys Other Kilwa 409,083 . 55,928 409,515 Kilwa 2,090 . . . Lindi Rural 431,047 212 96,487 575,225 Lindi Rural 5,344 5,155 . 1,592 Nachingwea 14,578 439 Nachingwea 15,351 . . 607 Liwale 256,497 14,505 . 264,470 Liwale 1,328 914 2,159 737 Ruangwa 352,935 411 . 354,534 Ruangwa 11,116 139 . 716 Lindi Urban 184,517 3,607 . 222,123 Lindi Urban 104 . . . Total 1,634,079 33,314 152,855 1,825,867 Total 35,334 6,207 2,159 3,653 Type of Livestock/Poultry 1995 1999 2003 Cattle 1,587,093 774,587 1,031,889 Improved Cattle 8,288 777 6,501 1 - 4 57259 241 . 57500 22677 Goats 788,145 621,405 797,481 5 - 9 145512 411 1395 147318 22390 Sheep 242,314 120,524 187,244 10 - 19 298654 . . 298654 23119 Pigs 31,464 12,725 43,835 20 - 29 167849 . . 167849 7398 Indigenous Chicken 1,990,526 757,075 1,634,079 30 - 39 120978 . . 120978 3763 Layers 6,362 4,262 122,136 40 - 49 62380 . . 62380 1461 Broilers 14,556 5,235 69,652 50 - 99 86067 14578 . 100646 1505 Total Chickens 2,011,444 766,572 1,825,867 100+ 136424 18084 151460 305967 639 Total 1075122 33314 152855 1261290 82952 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 Type Chicken Others 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 23c Head Number of Other Livestock by Type of Livestock and District District Number of Chicken Total Number of Chicken District Type of Livestock 23d OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Flock Size Chicken Type 23e LIVESTOCK/POULTRY POPULATION TREND Indigenous Chicken Layer Broiler Total Number of Household Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 245 FISH FARMING Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 246 Number % Number % Kilwa 0 0.0 31,377 100.0 31,377 Lindi Rural 207 0.5 44,646 99.5 44,853 Nachingwea 0 0.0 35,167 100.0 35,167 Liwale 28 0.2 11,337 99.8 11,365 Ruangwa 68 0.3 27,154 99.7 27,222 Lindi Urban 0 0.0 3,189 100.0 3,189 Total 304 0.2 152,869 99.8 153,173 Natural Pond Dug out Pond Total Lindi Rural 0 309 309 Liwale 0 28 28 Ruangwa 68 0 68 Total 68 337 405 Own Pond Government I Neighbour Number Number Number Number Lindi Rural 0 101 207 309 Liwale 0 28 0 28 Ruangwa 68 0 0 68 Total 68 129 207 405 Total 129 129 Neighbor Large Scale FDid not Sell Total Number Number Number Number Lindi Rural 207 0 0 207 Liwale 0 0 28 28 Ruangwa 0 68 68 137 Total 207 68 97 372 District Number of Tilapia Number of Carp Number of Others Lindi Rural 19276 0 0 Liwale 701 0 0 Ruangwa 0 342 1027 Total 19977 342 1027 District Fish Farming System 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year Source of Fingerling Total 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year District District Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 247 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 248 Government NGO / Development Project Other Total Kilwa 489 0 0 489 2,644 19 Lindi Rural 510 0 0 510 5,804 9 Nachingwea 347 173 0 520 2,699 19 Liwale 28 0 0 28 662 4 Ruangwa 479 0 0 479 2,553 19 Lindi Urban 278 32 0 310 777 40 Total 2,131 205 0 2,336 15,139 15 % 91.2 8.8 0 100 Government NGO / Development Project Other Total Lindi Rural 205 0 0 205 5,804 4 Nachingwea 87 0 0 87 2,699 3 Liwale 112 0 112 662 17 Lindi Urban 0 32 0 32 777 4 Total 404 32 0 436 9,942 4 % 92.6 7.4 0 100 Government NGO / Development Project Other not applic able Lindi Rural 101 0 0 0 101 5,804 2 Nachingwea 87 0 0 0 87 2,699 3 Total 188 0 0 0 188 8,503 2 % 100.0 0 0 0 100 Government NGO / Development Project perative Total Kilwa 158 0 0 158 2,644 6 Lindi Rural 202 100 0 302 5,804 5 Nachingwea 87 87 174 2,699 6 Liwale 29 0 0 29 662 4 Ruangwa 69 0 0 69 2,553 3 Lindi Urban 69 0 0 69 777 9 Total 613 187 0 800 15,139 5 % 76.7 23.3 0.0 100 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Source of Advice on Group Formation and Strenghthening Total Number of households raising livestock % receiving advice out of total 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Pasture Establishment and Selection Total Total Number of households raising livestock % receiving advice out of total 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control Total Number of households raising livestock % receiving advice out of total 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Herd/Flock Size Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 249 Government NGO/Develo pment Projects not applicable Total Lindi Rural 202 0 0 202 5,804 3 Nachingwea 87 0 0 87 2,699 3 Liwale 29 0 0 29 662 4 Lindi Urban 35 32 0 67 777 9 Total 352 32 0 385 9,942 4 % 91.7 8.3 0.0 100 Government NGO / Developmen t Project Other Total Kilwa 79 0 0 79 2,644 3 Lindi Rural 252 0 0 252 5,804 4 Nachingwea 262 87 0 349 2,699 13 Liwale 29 0 0 29 662 4 Lindi Urban 35 32 0 67 777 9 Total 656 119 0 775 12,586 6 % 84.6 15.4 0 100 Number % Number % Number % Number % Number % Kilwa 0 0 832 78 237 22 0 0 0 0 1,068 Lindi Rural 413 25 1,170 69 103 6 0 0 0 0 1,686 Nachingwea 173 22 437 56 88 11 0 0 87 11 785 Liwale 114 11 481 46 310 30 114 11 29 3 1,048 Ruangwa 65 9 481 71 135 20 0 0 0 0 680 Lindi Urban 101 29 209 61 35 10 0 0 0 0 344 Total 866 15 3,609 64 907 16 114 2 116 2 5,612 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Quality of Service Total Very Good Good Average Poor No Good 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice on Calf Rearing Total Number of households raising livestock % receiving advice out of total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice on Improved Bulls Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Lindi 250 Appendix II 251 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 252 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads District Capital Kilwa 48.5 2.6 14.0 2.1 62.5 9.5 207.0 29.9 42.6 76.3 54.9 94.4 Lindi Rural 32 3.0 4.6 1.8 39.0 5.7 51.5 4.9 23.4 39.0 23.5 51.2 Nachingwea 14.8 2.0 3.4 0.5 14.0 4.8 158.2 3.0 17.6 24.6 68.2 32.4 Liwale 42.1 2.3 12.6 1.0 41.6 8.2 256.6 7.0 22.9 41.9 174.1 42.8 Ruangwa 15.3 1.4 2.7 1.5 23.6 4.3 135.2 13.3 17.6 15.4 54.6 28.6 Lindi Urban 9 3.0 2.2 1.8 10.8 4.4 9.5 4.2 15.6 9.1 8.0 9.4 Total 28.7 2.3 6.4 1.5 34.9 6.2 137.1 11.2 24.8 38.7 56.6 50.2 No of households % No of households % No of household s % No of househol ds % No of households % Kilwa 322 1.0 964 3.1 4,327 13.8 3,426 10.9 22,338 71.2 31,377 48.5 Lindi Rural 0 0.0 1,706 3.8 3,680 8.2 7,940 17.7 31,528 70.3 44,853 32.0 Nachingwea 1,139 3.2 2,275 6.5 8,179 23.3 14,500 41.2 9,074 25.8 35,167 14.8 Liwale 29 0.3 315 2.8 894 7.9 2,688 23.6 7,439 65.5 11,365 42.1 Ruangwa 661 2.4 1,023 3.8 6,248 23.0 10,553 38.8 8,738 32.1 27,222 15.3 Lindi Urban 0 0.0 282 8.8 2,029 63.6 671 21.1 207 6.5 3,189 9.0 Total 2,151 1.4 6,564 4.3 25,356 16.6 39,778 26.0 79,324 51.8 153,173 28.7 District Distance to Secondary School Total number of household s Mean Distanc e Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 253 No of households % No of households % No of household s % No of househol ds % No of households % Kilwa 6,395 20.4 7,862 25.1 5,454 17.4 5,067 16.1 6,599 21.0 31,377 14.0 Lindi Rural 27,830 62.0 6,819 15.2 5,072 11.3 3,438 7.7 1,695 3.8 44,853 4.6 Nachingwea 19,120 54.4 6,857 19.5 4,976 14.1 2,108 6.0 2,106 6.0 35,167 3.4 Liwale 4,786 42.1 2,122 18.7 1,158 10.2 1,398 12.3 1,901 16.7 11,365 12.6 Ruangwa 14,036 51.6 5,690 20.9 5,927 21.8 459 1.7 1,111 4.1 27,222 2.7 Lindi Urban 1,845 57.9 302 9.5 1,043 32.7 0 0.0 0 0.0 3,189 2.2 Total 74,012 48.3 29,651 19.4 23,629 15.4 12,470 8.1 13,412 8.8 153,173 6.4 No of households % No of households % No of household s % No of househol ds % No of households % Kilwa 17,317 55.2 9,528 30.4 4,208 13.4 81 0.3 243 0.8 31,377 2.1 Lindi Rural 32,921 73.4 8,815 19.7 2,344 5.2 418 0.9 356 0.8 44,853 1.8 Nachingwea 25,476 72.4 8,377 23.8 1,313 3.7 0 0.0 0 0.0 35,167 0.5 Liwale 6,870 60.5 3,307 29.1 1,102 9.7 85 0.8 0 0.0 11,365 1.0 Ruangwa 17,828 65.5 6,584 24.2 2,609 9.6 69 0.3 132 0.5 27,222 1.5 Lindi Urban 2,410 75.6 176 5.5 565 17.7 0 0.0 37 1.2 3,189 1.8 Total 102,822 67.1 36,788 24.0 12,142 7.9 653 0.4 769 0.5 153,173 1.5 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of household s Mean Distanc e Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of household s Mean Distanc e Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 254 No of households % No of households % No of households % No of households % No of households % Kilwa 162 0.5 81 0.3 3,117 9.9 162 0.5 27,856 88.8 31,377 62.5 Lindi Rural 196 0.4 0 0.0 638 1.4 9,500 21.2 34,520 77.0 44,853 39.0 Nachingwea 1,750 5.0 1,832 5.2 7,915 22.5 15,650 44.5 8,019 22.8 35,167 14.0 Liwale 291 2.6 368 3.2 807 7.1 2,971 26.1 6,928 61.0 11,365 41.6 Ruangwa 68 0.2 69 0.3 3,153 11.6 9,988 36.7 13,944 51.2 27,222 23.6 Lindi Urban 0 0.0 0 0.0 2,273 71.3 568 17.8 348 10.9 3,189 10.8 Total 2,466 1.6 2,350 1.5 17,904 11.7 38,839 25.4 91,615 59.8 153,173 34.9 No of households % No of households % No of households % No of households % No of households % Kilwa 3,713 11.8 8,165 26.0 11,260 35.9 4,283 13.7 3,955 12.6 31,377 9.5 Lindi Rural 9,704 21.6 13,155 29.3 15,081 33.6 3,997 8.9 2,916 6.5 44,853 5.7 Nachingwea 6,543 18.6 9,575 27.2 13,932 39.6 4,770 13.6 347 1.0 35,167 4.8 Liwale 1,909 16.8 2,239 19.7 3,989 35.1 3,113 27.4 114 1.0 11,365 8.2 Ruangwa 5,328 19.6 5,675 20.8 13,856 50.9 2,157 7.9 206 0.8 27,222 4.3 Lindi Urban 406 12.7 984 30.9 1,765 55.3 0 0.0 35 1.1 3,189 4.4 Total 27,604 18.0 39,793 26.0 59,883 39.1 18,321 12.0 7,573 4.9 153,173 6.2 No of households % No of households % No of households % No of households % No of households % Kilwa 8,844 28.2 14,773 47.1 7,521 24.0 160 0.5 79 0.3 31,377 2.6 Lindi Rural 15,453 34.5 21,736 48.5 7,048 15.7 514 1.1 101 0.2 44,853 3.0 Nachingwea 16,180 46.0 13,392 38.1 5,250 14.9 85 0.2 260 0.7 35,167 2.0 Liwale 3,780 33.3 4,349 38.3 3,009 26.5 197 1.7 29 0.3 11,365 2.3 Ruangwa 10,384 38.1 12,611 46.3 4,227 15.5 0 0.0 0 0.0 27,222 1.4 Lindi Urban 406 12.7 1,050 32.9 1,733 54.3 0 0.0 0 0.0 3,189 3.0 Total 55,048 35.9 67,912 44.3 28,789 18.8 956 0.6 468 0.3 153,173 2.3 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year District Distance to Primary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 255 No of households % No of households % No of households % No of households % No of households % Kilwa 79 0.3 0 0.0 0 0.0 0 0.0 31,298 99.7 31,377 207.0 Lindi Rural 203 0.5 0 0.0 210 0.5 4,994 11.1 39,447 87.9 44,853 51.5 Nachingwea 173 0 86 87 34,821 35,167 158.2 Liwale 29 0.3 0 0.0 0 0.0 28 0.2 11,308 99.5 11,365 256.6 Ruangwa 69 0.3 0 0.0 0 0.0 204 0.7 26,949 99.0 27,222 135.2 Lindi Urban 0 0.0 35 1.1 2,276 71.4 602 18.9 276 8.7 3,189 9.5 Total 552 0.4 35 0.0 2,572 1.7 5,915 3.9 144,100 94.1 153,173 137.1 No of households % No of households % No of households % No of households % No of households % Kilwa 0 0.0 0 0.0 71 0.2 215 0.7 31,091 99.1 31,377 94.4 Lindi Rural 203 0.5 0 0.0 107 0.2 4,890 10.9 39,653 88.4 44,853 51.2 Nachingwea 87 1,222 3,892 11,448 18,517 35,167 32.4 Liwale 26 0.2 524 4.6 859 7.6 2,971 26.1 6,985 61.5 11,365 42.8 Ruangwa 207 0.8 0 0.0 3,223 11.8 7,519 27.6 16,273 59.8 27,222 28.6 Lindi Urban 0 0.0 0 0.0 2,311 72.5 602 18.9 276 8.7 3,189 9.4 Total 523 0.3 1,746 1.1 10,462 6.8 27,646 18.0 112,795 73.6 153,173 50.2 No of households % No of households % No of households % No of households % No of households % Kilwa 2,135 6.8 1,079 3.4 1,288 4.1 1,754 5.6 25,122 80.1 31,377 54.9 Lindi Rural 7,206 16.1 3,905 8.7 7,602 16.9 5,831 13.0 20,309 45.3 44,853 23.5 Nachingwea 700 87 88 174 34,118 35,167 68.2 Liwale 0 0.0 0 0.0 0 0.0 0 0.0 11,365 100.0 11,365 174.1 Ruangwa 133 0.5 0 0.0 1,808 6.6 2,063 7.6 23,217 85.3 27,222 54.6 Lindi Urban 320 10.0 383 12.0 2,022 63.4 361 11.3 104 3.3 3,189 8.0 Total 10,493 6.9 5,454 3.6 12,809 8.4 10,183 6.6 114,234 74.6 153,173 56.6 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 256 No of households % No of households % No of households % No of households % No of households % Kilwa 7,113 22.7 9,088 29.0 7,165 22.8 2,168 6.9 5,843 18.6 31,377 29.9 Lindi Rural 16,007 35.7 13,707 30.6 8,743 19.5 4,997 11.1 1,400 3.1 44,853 4.9 Nachingwea 14,987 11,200 6,027 1,570 1,382 35,167 3.0 Liwale 3,664 32.2 3,124 27.5 2,363 20.8 1,591 14.0 622 5.5 11,365 7.0 Ruangwa 6,735 24.7 4,947 18.2 864 3.2 11,546 42.4 3,131 11.5 27,222 13.3 Lindi Urban 1,203 37.7 384 12.1 700 21.9 902 28.3 0 0.0 3,189 4.2 Total 49,710 32.5 42,450 27.7 25,863 16.9 22,773 14.9 12,378 8.1 153,173 11.2 No of households % No of households % No of households % No of households % No of households % Kilwa 2,800 8.9 2,649 8.4 2,611 8.3 1,805 5.8 21,512 68.6 31,377 76.3 Lindi Rural 4,145 9.2 1,821 4.1 2,147 4.8 5,291 11.8 31,449 70.1 44,853 39.0 Nachingwea 2,194 2,182 4,770 11,106 14,915 35,167 24.6 Liwale 319 2.8 482 4.2 978 8.6 2,857 25.1 6,728 59.2 11,365 41.9 Ruangwa 4,567 16.8 4,829 17.7 4,993 18.3 4,404 16.2 8,430 31.0 27,222 15.4 Lindi Urban 37 1.2 244 7.7 2,029 63.6 602 18.9 276 8.7 3,189 9.1 Total 14,062 9.2 12,207 8.0 17,528 11.4 26,066 17.0 83,310 54.4 153,173 38.7 No of households % No of households % No of households % No of households % No of households % Kilwa 5,294 16.9 3,253 10.4 2,315 7.4 237 0.8 20,278 64.6 31,377 42.6 Lindi Rural 9,321 20.8 1,092 2.4 1,180 2.6 1,507 3.4 31,755 70.8 44,853 23.4 Nachingwea 3,671 1,831 4,509 10,757 14,399 35,167 17.6 Liwale 3,346 29.4 387 3.4 410 3.6 138 1.2 7,084 62.3 11,365 22.9 Ruangwa 6,653 24.4 1,548 5.7 1,232 4.5 410 1.5 17,378 63.8 27,222 17.6 Lindi Urban 1,097 34.4 0 0.0 73 2.3 69 2.2 1,950 61.1 3,189 15.6 Total 29,382 19.2 8,111 5.3 9,719 6.3 13,118 8.6 92,843 60.6 153,173 24.8 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 257 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 72 0.5 3,823 24 1,583 10 10,420 65 78 0.5 15,975 Lindi Rural 923 19.4 1,918 40 304 6 1,498 32 102 2.2 4,745 Nachingwea 1,651 9.8 2,442 14 3,232 19 7,517 45 2,000 11.9 16,842 Liwale 227 13.1 710 41 544 31 167 10 86 4.9 1,734 Ruangwa 1,080 25.4 988 23 1,389 33 600 14 201 4.7 4,258 Lindi Urban 147 20.1 184 25 0 0 139 19 261 35.7 730 Total 4,100 9.3 10,064 23 7,053 16 20,340 46 2,727 6.2 44,284 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 72 1 3,036 49 1,210 19 1,896 31 0 0 6,214 Lindi Rural 102 5 1,288 68 304 16 202 11 0 0 1,897 Nachingwea 872 17 1,224 24 2,884 56 176 3 0 0 5,156 Liwale 142 30 165 35 166 35 0 0 0 0 472 Ruangwa 270 21 665 52 270 21 0 0 67 5 1,272 Lindi Urban 75 22 184 55 0 0 37 11 38 11 334 Total 1,533 10 6,562 43 4,834 32 2,312 15 105 1 15,345 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 0 0 225 10 294 13 1,736 77 0 0 2,255 Lindi Rural 103 33 0 0 0 0 206 67 0 0 310 Nachingwea 260 7 521 14 87 2 2,271 61 609 16 3,748 Liwale 0 0 27 24 0 0 57 51 29 25 113 Ruangwa 135 20 0 0 264 40 199 30 69 10 667 Lindi Urban 0 0 0 0 0 0 69 65 38 35 107 Total 498 7 773 11 646 9 4,539 63 744 10 7,200 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 258 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 0 0 81 4 78 4 1,894 92 0 0 2,053 Lindi Rural 0 0 0 0 0 0 206 100 0 0 206 Nachingwea 173 40 0 0 0 0 176 40 88 20 436 Liwale 0 0 27 33 0 0 55 67 0 0 82 Ruangwa 136 25 65 12 129 24 205 38 0 0 535 Lindi Urban 0 0 0 0 0 0 0 0 38 100 38 Total 308 9 172 5 207 6 2,536 76 125 4 3,350 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 0 0 160 8 0 0 1,660 87 78 4 1,899 Lindi Rural 402 41 212 22 0 0 369 38 0 0 983 Nachingwea 87 525 174 2,446 609 3,841 Liwale 0 0 411 49 350 42 54 6 29 3 844 Ruangwa 132 20 258 39 271 41 0 0 0 0 661 Lindi Urban 0 0 0 0 0 0 0 0 72 100 72 Total 621 7 1,566 19 795 10 4,529 55 788 9 8,300 No of Households % No of Households % No of Households % No of Households % No of Households % Kilwa 0 0 159 9 0 0 1,657 91 0 0 1,816 Lindi Rural 212 100 0 0 0 0 0 0 0 0 212 Nachingwea 86 86 0 349 86 605 Liwale 29 26 53 48 28 26 0 0 0 0 110 Ruangwa 346 51 0 0 129 19 133 20 65 10 673 Lindi Urban 0 0 0 0 0 0 0 0 38 100 38 Total 672 19 298 9 158 5 2,138 62 188 5 3,453 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 259 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 260 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total number of households Kilwa 2,714 161 28,430 72 285 31,661 Lindi Rural 1,613 828 42,203 209 906 45,759 Nachingwea 1,396 171 33,426 174 0 35,167 Liwale 728 477 10,135 26 0 11,365 Ruangwa 1,075 595 25,552 0 594 27,816 Lindi Urban 68 71 3,051 0 91 3,280 Total 7,594 2,302 142,796 481 1,875 155,048 % 4.9 1.5 92.1 0.3 1.2 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total number of households Kilwa 2 45,012 0 142 429 11,917 27,256 0 84,756 Lindi Rural 3 14,281 0 0 893 5,847 29,647 387 51,055 Nachingwea Liwale 3 31,720 936 0 226 2,693 11,662 0 47,238 Ruangwa 2 19,227 451 230 0 3,699 76,646 229 100,482 Lindi Urban 3 16,095 501 0 0 703 22,890 0 40,189 Total 2 126,335 1,888 373 1,548 24,858 168,102 616 323,719 % 39.0 0.6 0.1 0.5 7.7 51.9 0.2 100 Lindi Urban Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 17,748 25 18,302 26 15,945 22 5,932 8 11,247 7 1,777 2.5 70,952 Landline phone 81 0 0 0 0 0 57 0 131 0 71 0.1 339 Mobile phone 0 0 101 0 436 1 85 0 0 0 71 0.1 693 Iron 3,804 5 4,771 7 5,132 7 2,005 3 2,880 2 390 0.5 18,982 Wheelbarrow 323 0 513 1 350 0 142 0 134 0 69 0.1 1,531 Bicycle 12,226 17 12,921 18 17,767 25 6,232 9 9,334 6 1,056 1.5 59,536 Vehicle 0 0 300 0 175 0 114 0 131 0 32 0.0 752 Television / Video 240 0 295 0 175 0 52 0 132 0 71 0.1 965 Households 34,422 22 37,203 24 39,980 26 14,619 10 23,989 16 3,536 2.3 153,750 Table 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year District Type of toilet 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year Total Number of Households Table 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Type of Owned Asset District Kilwa Lindi Rural Nachingwea Liwale Ruangwa Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 261 Lindi Urban Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Mains Electricity 161 29 0 0 0 0 130 23 199 35 71 12.7 561 Solar 242 68 0 0 88 25 28 8 0 0 0 0.0 358 Gas (Biogas) 0 0 0 0 87 57 0 0 65 43 0 0.0 152 Hurricane Lamp 4,692 21 4,865 22 5,477 24 2,968 13 3,883 17 527 2.4 22,412 Pressure Lamp 759 22 951 27 871 25 168 5 607 17 145 4.1 3,501 Wick Lamp 25,202 21 38,263 31 27,248 22 7,450 6 21,598 18 2,376 1.9 122,137 Candles 0 0 106 17 88 14 86 14 336 55 0 0.0 616 Firewood 320 9 668 20 1,308 39 507 15 535 16 35 1.0 3,373 Other 0 0 0 0 0 0 29 45 0 0 35 54.7 64 Total 31,376 20 44,853 29 35,167 23 11,366 7 27,223 18 3,189 2 153,174 Lindi Urban Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Mains Electricity 227 62 105 29 0 0 0 0 0 0 36 9.8 368 Solar 81 100 0 0 0 0 0 0 0 0 0 0.0 81 Gas (Biogas) 0 0 0 0 0 0 0 0 0 0 0 0.0 0 Bottled Gas 0 0 0 0 0 0 28 100 0 0 0 0.0 28 Parraffin / Kerocine 0 0 0 0 0 0 29 100 0 0 0 0.0 29 Charcoal 416 15 702 26 866 32 274 10 204 8 251 9.3 2,713 Firewood 30,653 20 43,834 29 34,301 23 10,950 7 26,951 18 2,902 1.9 149,591 Crop Residues 0 0 106 56 0 0 84 44 0 0 0 0.0 190 Livestock Dung 0 0 106 61 0 0 0 0 67 39 0 0.0 173 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year Main Source of Energy for Lighting District Kilwa Lindi Rural Nachingwea Liwale Ruangwa 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Cooking District Kilwa Lindi Rural Nachingwea Liwale Ruangwa Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 262 Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban wet season 2,244 6,933 1,221 617 3,526 696 dry season 2,403 6,993 5,401 473 4,835 692 wet season 1,834 8,132 5,574 799 4,741 138 Dry season 1,603 8,187 9,650 882 5,157 138 wet season 194 462 613 478 268 313 Dry season 204 561 436 422 275 347 wet season 15,002 8,836 13,846 3,421 13,866 1,161 Dry season 19,681 12,066 10,920 5,575 15,744 1,558 wet season 1,044 7,816 1,576 584 586 314 Dry season 1,608 8,730 436 611 403 278 wet season 4,928 7,499 2,014 4,845 600 533 Dry season 5,276 7,716 5,976 3,123 333 32 wet season 322 1,745 0 112 139 0 Dry season 0 206 87 166 208 0 wet season 5,808 3,328 10,063 423 3,496 0 Dry season 486 192 1,559 57 269 0 wet season 0 103 0 0 0 0 Dry season 116 203 0 56 0 108 wet season Dry season 0 0 0 0 0 36 wet season Dry season wet season 0 0 260 85 0 35 dry season 0 0 701 0 0 0 62,753 89,708 70,333 22,729 54,446 Kilwa Lindi rural Nachingwea Liwale Ruangwa Lindi Urban wet season 7 15 3 5 13 22 dry season 8 16 15 4 18 22 wet season 6 18 16 49 17 4 Dry season 5 18 27 85 19 4 wet season 1 1 2 5 1 10 Dry season 1 1 1 4 1 11 wet season 48 20 39 122 51 36 Dry season 63 27 31 96 58 49 wet season 3 17 4 14 2 10 Dry season 5 19 1 4 1 9 wet season 16 17 6 18 2 17 Dry season 17 17 17 53 1 1 wet season 1 4 0 0 1 0 Dry season 0 0 0 1 1 0 wet season 19 7 29 89 13 0 Dry season 2 0 4 14 1 0 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 3 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 1 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 1 2 0 1 dry season 0 0 2 6 0 0 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Other Total Agricultural Households per District 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Other Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 263 Kilwa Lindi Rural Nachingwea Liwale Ruangwa wet season 1,101 1,565 2,589 475 679 Dry season 776 843 434 360 202 wet season 12,789 11,043 7,774 2,388 5,600 Dry season 7,501 9,721 2,965 2,048 4,201 wet season 3,911 5,788 2,616 1,123 3,775 Dry season 2,597 5,373 1,394 1,034 3,021 wet season 5,556 10,750 8,804 3,446 9,641 Dry season 6,483 9,252 3,144 3,307 5,510 wet season 1,005 3,850 2,695 836 2,841 Dry season 1,502 3,741 1,123 644 2,088 wet season 1,613 3,284 2,429 525 532 Dry season 1,078 2,690 1,908 251 475 wet season 5,402 8,573 8,260 2,573 4,154 Dry season 11,440 13,234 24,198 3,719 11,726 Kilwa Lindi Rural Nachingwea Liwale Ruangwa wet season 4 3 7 4 2 Dry season 2 2 1 3 1 wet season 41 25 22 21 21 Dry season 24 22 8 18 15 wet season 12 13 7 10 14 Dry season 8 12 4 9 11 wet season 18 24 25 30 35 Dry season 21 21 9 29 20 wet season 18 24 25 30 35 Dry season 21 21 9 29 20 wet season 3 9 8 7 10 Dry season 5 8 3 6 8 wet season 17 19 23 23 15 Dry season 36 30 69 33 43 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year Time Spent to and from Main Source of Drinking Water Season District Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year p from Main Source of Drinking Water Season District Less than 10 50 - 59 Minutes above one Hour 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 264 District Lindi Urban Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households One 2,451 23 4,023 37 1,904 18 308 3 2,063 19 104 1.0 10,854 Two 12,632 16 22,376 28 21,249 27 4,606 6 16,808 21 889 1.1 78,561 Three 16,214 26 18,245 29 12,013 19 6,450 10 8,284 13 2,195 3.5 63,402 Four 81 23 209 59 0 0 0 0 67 19 0 0.0 357 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 Lindi Urban Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Not Eaten 16,689 20 27,169 32 19,344 23 5,597 7 13,630 16 1,481 1.8 83,910 One 6,860 19 10,706 30 7,050 20 2,361 7 7,877 22 750 2.1 35,604 Two 5,053 24 4,684 22 5,387 25 1,911 9 3,553 17 815 3.8 21,402 Three 1,887 24 974 12 2,699 34 1,044 13 1,357 17 36 0.5 7,997 Four 163 10 607 36 428 25 198 12 271 16 35 2.0 1,702 Five 404 21 612 32 258 14 142 8 399 21 73 3.9 1,889 Six 0 0 102 39 0 0 28 11 135 51 0 0.0 265 Seven 319 79 0 0 0 0 84 21 0 0 0 0.0 404 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Kilwa Lindi Rural Nachingwea Liwale Ruangwa 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day Kilwa Lindi Rural Nachingwea Liwale Ruangwa Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 9,607 29 7,501 22 7,756 23 2,361 7 6,295 19 103 0.3 33,622 22 One 2,720 14 7,654 39 3,391 17 934 5 4,588 24 137 0.7 19,425 13 Two 4,268 14 7,976 26 8,683 28 3,031 10 6,662 22 277 0.9 30,896 20 Three 5,547 22 8,170 33 5,042 20 1,930 8 3,720 15 626 2.5 25,034 16 Four 2,647 17 4,939 32 3,320 22 1,293 8 2,284 15 763 5.0 15,245 10 Five 1,633 13 3,834 30 3,661 28 883 7 2,473 19 496 3.8 12,979 8 Six 1,062 21 1,014 21 1,830 37 311 6 661 13 67 1.3 4,945 3 Seven 3,893 35 3,765 34 1,483 13 621 6 541 5 722 6.6 11,026 7 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of households % Never 8,957 18 10,539 21 11,666 23 3,999 8 12,584 25 2,099 4.2 49,845 32.5 Seldom 9,309 18 15,295 30 14,014 27 3,644 7 8,061 16 668 1.3 50,993 33.3 Sometimes 3,367 28 3,269 27 1,749 15 1,331 11 2,154 18 105 0.9 11,975 7.8 Often 5,983 24 9,911 39 5,215 21 1,407 6 2,413 10 245 1.0 25,174 16.4 Always 3,760 25 5,839 38 2,522 17 984 6 2,010 13 72 0.5 15,187 9.9 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 100.0 District Never Seldom Sometimes Often Always Total Kilwa 8,957 9,309 3,367 5,983 3,760 31,377 Lindi Rur 10,539 15,295 3,269 9,911 5,839 44,853 Nachingwea 11,666 14,014 1,749 5,215 2,522 35,167 Liwale 3,999 3,644 1,331 1,407 984 11,365 Ruangwa 12,584 8,061 2,154 2,413 2,010 27,222 Lindi Urb 2,099 668 105 245 72 3,189 Total 49,845 50,993 11,975 25,174 15,187 153,173 Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban 34-14: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year Lindi urban 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Status of Food Satisfaction District Total Kilwa Liwale Ruangwa 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Number of Days District Total Kilwa Lindi Rural Nachingwea Tanzania Agriculture Sample Census - 2003 Lindi Appendix II 266 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 3,273 14 7,006 30 5,473 23 2,225 9 4,871 21 740 3.1 23,587 15 Tiles 477 25 296 16 523 28 279 15 261 14 38 2.0 1,875 1 Concrete 162 74 0 0 0 0 56 26 0 0 0 0.0 217 0 Asbestos 78 23 0 0 0 0 56 17 206 60 0 0.0 340 0 Grass / Leaves 27,387 22 37,244 30 29,170 23 8,349 7 19,985 16 2,412 1.9 124,547 81 Grass & Mud 0 0 307 12 0 0 400 15 1,900 73 0 0.0 2,607 2 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 4,044 13 12,222 41 5,314 18 1,380 5 7,021 23 144 0.5 30,126 20 Sale of Livestock 160 6 1,540 62 176 7 26 1 468 19 104 4.2 2,474 2 Sale of Livestock Products 0 0 104 12 262 31 0 0 402 48 67 8.0 834 1 Sales of Cash Crops 15,123 24 10,328 16 17,160 27 7,406 12 12,043 19 582 0.9 62,643 41 Sale of Forest Products 2,119 31 1,934 28 1,569 23 170 2 674 10 408 5.9 6,873 4 Business Income 2,313 22 3,284 31 3,223 30 391 4 1,063 10 348 3.3 10,623 7 Wages & Salaries in Cash 852 25 1,205 36 609 18 414 12 195 6 107 3.2 3,383 2 Other Casual Cash Earnings 3,263 14 9,982 42 4,767 20 1,270 5 3,668 16 560 2.4 23,511 15 Cash Remittance 1,179 15 3,116 40 1,568 20 307 4 1,212 16 327 4.2 7,709 5 Fishing 2,266 60 939 25 0 0 0 0 69 2 510 13.5 3,785 2 Other 58 5 199 16 518 43 0 0 408 34 32 2.6 1,215 1 Total 31,377 20 44,853 29 35,167 23 11,365 7 27,222 18 3,189 2.1 153,173 100 34.16: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Cash Income District Total Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi Urban 34.15: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year Roofing Materials District Total Kilwa Lindi Rural Nachingwea Liwale Ruangwa Lindi urban Tanzania Agriculture Sample Census - 2003 Lindi 267 APPENDIX III QUESTIONNAIRES Appendix III 268 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 269 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 270 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 271 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 272 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 273 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 274 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 275 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 276 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 277 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 278 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 279 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 280 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 281 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 282 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 283 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 284 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 285 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 286 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 287 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 288 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 289 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 290 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source "a" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 291 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 292 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 293 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 294 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 295 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 296 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 297 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 298 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 299 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 300 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 301 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 302 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 303 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 304 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 305 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 306 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 307 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 308 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 309 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 310 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 311 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 312 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 313 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE AGRICULTURAL TRAINING, EXTENSION SERVICES AND RESEARCH DIVISION LIST OF AGRICULTURAL TRAINING INSTITUTE FOR ADMISSION 2020/2021 S/ N INSTITUTE COURSES FOR 2020/2021 POSTAL ADDRESS , Phone numbers and Email addresses Bank Account 1 MATI Igurusi Ordinary Diploma in Land Use Planning Ordinary Diploma in Irrigation (NTA Level 5- 6) PRINCIPAL, MATI Igurusi, P.O. BOX 336, Mbeya. 0754917653 [email protected] GePG MATI Igurusi SHFA Account No. 016139000050 NBC, Mbeya. 2 MATI Ilonga Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) Ordinary Diploma in Food Production and Nutrition( NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4- 5) PRINCIPAL, MATI Ilonga, P.O. BOX 66, Kilosa. 0785611114/0756653551 [email protected] GePG MATI – Ilonga SHFA Account No.21810018129, NMB Kilosa 3 MATI Mlingano Ordinary Diploma in Agro mechanization (NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4-5 ) Technician Certificate in Agromechanization (NTA level 4 -5) PRINCIPAL, MATI Mlingano, P.O. BOX 5051, Tanga. 0712997049/0769869823 [email protected] GePG MATI – Mlingano SHFA, Account No. 41710043401 NMB Madaraka 4 MATI Uyole Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) Ordinary Diploma in Crop Production (NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4- 5) PRINCIPAL, MATI Uyole P.O. BOX 2292, Mbeya. 0754605832/0784341803 [email protected] GePG MATI - Uyole SHFA Account No. .61010037823, NMB Mbalizi Road. 5 MATI Ukiriguru Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) Technician Certificate in Agriculture Production (NTA Level 4- 5) Ordinary Diploma in Crop Production (NTA Level 5- 6) PRINCIPAL, MATI Ukiriguru, P.O. BOX 1434, Mwanza . 0754430983/0769320836 [email protected] GePG MATI - Ukiriguru SHFA Account No.31110064154 NMB Kenyata Road 6 KATC Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) Technician Certificate in Agriculture Production (NTA Level 4- 5) PRINCIPAL, KATC P.O BOX 1241, Moshi 0620882759 [email protected] GePG KATC SHFA Account No.017139000053 NBC Moshi 7 HORTI TENGERU Ordinary Diploma in Horticulture (NTA Level 5- 6) PRINCIPAL, HORTI TENGERU P.O BOX 1253, Arusha 0715822506/ 0766643645 mati- [email protected] GePG HORTI-TENGERU SHFA Account No. 014139000067 NBC. ARUSHA. 8 MATI MUBONDO Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) Technician Certificate in Agriculture Production (NTA Level 4- 5) PRINCIPAL, MATI Mubondo P.O. BOX 90, Kasulu 0754653352 [email protected] GePG MATI Mubondo SHFA Account No.51410024991, NMB Kasulu 9 MATI MARUKU Technician Certificate in Agriculture Production (NTA Level 4- 5) PRINCIPAL, MATI Maruku P.O BOX 127, Bukoba 0765020583 [email protected] GePG MATI-Maruku SHF Account No.31810029715, NMB Kaitaba, 10 National Sugar Institute(NSI) Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4- 5) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) PRINCIPAL, NSI P.O BOX 97, KIDATU 0766004008/0687993733 [email protected] GePG National Sugar Institute SHFA, Account No. 21710021681, NMB Kilombero . 11 MATI TUMBI Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4- 5) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) PRINCIPAL, MATI TUMBI P.O BOX 306, TABORA 0783372900/ 0743085208 [email protected] GePG MATI-TUMBI SHFA Account No.51010048019, NMB Mihayo. 12 MATI MTWARA Ordinary Diploma in Agriculture Production (NTA Level 5- 6) Technician Certificate in Agriculture Production (NTA Level 4- 5) Ordinary Diploma in General Agriculture (NTA Level 6- upgrading) PRINCIPAL, MATI MTWARA P.O BOX 121, MTWARA 0784990752/0783591179 [email protected] GePG MATI-MTWARA SHFA Account No. 034139000039, NBC Mtwara 13 KATRIN Technician Certificate in Agriculture Production (NTA Level 4- 5) Ordinary Diploma in General Agriculture (NTA level 6- upgrading) PRINCIPAL, KATRIN P.O BOX 405, IFAKARA 0763273817 [email protected] GePG MATI-KATRIN SHFA Account No.21610026436, NMB Ifakara | false |
# Extracted Content EXECUTIVE SUMMARY __________________________________________________________________________________ ________ Tanzania Agriculture Sample Census - 2007/08 United Republic Of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE SMALL HOLDER AGRICULTIRE Volume III: LIVESTOCK SECTOR – NATIONAL REPORT Ministry of Agriculture, Food Security and Cooperatives, Ministry of Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, Prime Minister's Office, Regional Administration and Local Governments, Ministry of Industries, Trade and Marketing, The National Bureau of Statistics and the Office of the Chief Government Statistician, Zanzibar March, 2012 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2007/2008 SMALL HOLDER AGRICULTURE Volume III: LIVESTOCK SECTOR – NATIONAL REPORT FIRST REPRINT MARCH 2012 Ministry of Agriculture, Food Security and Cooperatives, Ministry of Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, Prime Minister's Office, Regional Administration and Local Governments, Ministry of Industries, Trade and Marketing, The National Bureau of Statistics and the Office of the Chief Government Statistician, Zanzibar CONTENTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 i TABLE OF CONTENTS ABBREVIATIONS ............................................................................................................................................ III PREFACE ........................................................................................................................................................... IV LIST OF TABLES ............................................................................................................................................... V EXECUTIVE SUMMARY ............................................................................................................................... VII 1.1 INTRODUCTION ..................................................................................................................................... 1 1.2 Background Information ...................................................................................................................................... 1 1.3 Census Methodology .............................................................................................................................................. 3 1.3.1 Census Organization ....................................................................................................................... 3 1.3.2 Tabulation Plan Preparation ............................................................................................................ 4 1.3.3 Sample Design ............................................................................................................................... 4 1.3.4 Questionnaire Design and other Census Instruments ...................................................................... 5 1.3.5 Field Pilot-Testing of the Census Instruments ................................................................................ 5 1.3.6 Training of Trainers, Supervisors and Enumerators ....................................................................... 5 1.3.7 Information, Education and Communication (IEC) Campaign ....................................................... 6 1.3.8 Data Collection ................................................................................................................................ 6 1.3.9 Field Supervision and Consistency Checks ..................................................................................... 6 1.3.10 Data Processing ............................................................................................................................... 6 2.0 LIVESTOCK AND POULTRY RESULTS .................................................................................................. 8 2.1 Livestock Population and Growth ............................................................................................................................ 8 2.1.1 Cattle Population ........................................................................................................................... 10 2.1.2 Goat Population ............................................................................................................................. 16 2.1.3 Sheep Population ........................................................................................................................... 20 2.1.5 Chicken Population ....................................................................................................................... 25 2.1.5.1 Indigenous chicken population ...................................................................................................... 27 2.1.5.2 Improved Chicken ......................................................................................................................... 29 2.1.6 Other Livestock ............................................................................................................................. 32 2.2 Livestock and Poultry Products .............................................................................................................................. 32 2.2.1 Milk Production ............................................................................................................................ 32 2.2.2 Egg Production .............................................................................................................................. 35 2.3 Animal Contribution to Crop Production ...................................................................................................... 36 2.3 Animal Contribution to Crop Production ...................................................................................................... 37 2.3.1 Use of Organic Fertilizers ............................................................................................................. 37 2.4 Livestock Pest Control ........................................................................................................................................ 38 PREFACE _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 ii 2.4 Livestock Pest Control ........................................................................................................................................ 39 2.4.1 Common Livestock Diseases ................................................................................................................ 39 2.4.1.1 Tick Problem ................................................................................................................................. 39 2.4.1.2 Foot and Mouth disease ................................................................................................................. 40 2.4.1.3 Tsetse Flies Problems .................................................................................................................... 40 2.4.1.4 Newcastle disease .......................................................................................................................... 41 2.4.2 Specific Livestock Pest control methods........................................................................................ 41 2.4.2.1 Tick Control Methods ................................................................................................................... 41 2.4.2.2 Tsetse fly Control Methods ........................................................................................................... 41 2.4.2.3 Newcastle Control Methods ......................................................................................................... 42 2.4.2.3 Newcastle Control Methods ......................................................................................................... 43 2.4.2.3 Newcastle Control Methods ......................................................................................................... 44 2.4.3 Deworming practices ............................................................................................................................... 45 2.5 Livestock Extension Services ................................................................................................................................... 47 2.5.1 Extension Services Outreach ....................................................................................................... 47 2.5.2 Sources of Extension ................................................................................................................... 47 2.5.3 Types of extension messages ...................................................................................................... 49 2.6 Fish Farming ......................................................................................................................................................... 50 2.6.1 Fish Production ........................................................................................................................... 50 2.6.2. Source of fingerlings ................................................................................................................... 50 2.6.3 Frequencies of stocking ............................................................................................................... 51 2.6.4 Outlets for Selling Fish ............................................................................................................... 52 2.7 Bee Keeping .................................................................................................................................................................. 52 2.7.1 Honey Production ........................................................................................................................ 52 2.7.2 Prices of Honey ........................................................................................................................... 53 3. CONCLUSION ................................................................................................................................................ 54 4. APPENDICES ......................................................................................................................................... 57 PREFACE _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 iii ABBREVIATIONS ACLF Agriculture Census Listing Form ASDP Agriculture Sector Development Programme CSPro Census and Survey Processing System CSTWG Census and Surveys Technical Working group DANIDA Danish Development Agency DADIPS District Agricultural Development and Investment Projects DFID Department for International Development EA Enumeration Area EU European Union FAO Food and Agricultural Organisation GDP Gross Domestic Product ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japan International Development Agency MAFSC Ministry of Agriculture, Food Security and Cooperatives MALE Ministry of Agriculture, Livestock and Environment NACTE National Council for Technical Education NBS National Bureau of Statistics NMS OCGS National Master Sample Office of the Chief Government Statistician OCR Optical Character Recognition PPS Probability Proportional to Size PRS Poverty Reduction Strategy PSU Primary Sampling Unit REPOA Research on Poverty Alleviation RSM Regional Statistical Manager SPSS Statistical Package for Social Science TASAF Tanzania Social Action Funds TOT Training of Trainers UNDP United Nations Development Programme UNICEF United Nations Children Education Funds PREFACE _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 iv PREFACE At the end of the 2007/08 Agricultural Year, the National Bureau of Statistics (NBS) in collaboration with the Ministries of Agriculture, Food Security and Cooperatives, Livestock and Fisheries Development; Water; Industry and Trade; the Prime Minister’s Office, Regional Administration and Local Government (PORALG) and the Office of the Chief Government Statistician, (OCGS), Ministries of Agriculture and Natural Resources; Livestock and Fisheries conducted the Agriculture Sample Census. This is the fourth Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95), and the third was conducted in 2002/03. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 2002/03 National Sample Census of Agriculture. The census covered smallholders in rural areas only and large scale farms. This report presents data disaggregated at regional level and it focuses on livestock kept by small holders and Large Scale Farms. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of the agricultural sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by agricultural households in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the Department for International Development (DFID) and the Japanese Government through the Japan International Cooperation Agency (JICA) and others who contributed through the pool fund mechanism. My appreciation also goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics, Ministry of Agriculture, Food Security and Cooperatives, Ministry of Livestock Development and Fisheries, Ministry of Water and Irrigation, Ministry of Agriculture, Livestock and Environment, Zanzibar, the Prime Minister's Office, Regional Administration and Local Government, Ministry of Industries, Trade and Marketing and the Office of the Chief Government Statistician, Zanzibar, the Food and Agriculture Organization of the United Nations and the Censuses and Surveys Technical Working Group (CSTWG). Finally, I would like to extend my sincere gratitude to all professional, the Consultants, Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Dr. Albina Chuwa Director General National Bureau of Statistics LIST OF TABLES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 v LIST OF TABLES Table 1.1 Census Sample ............................................................................................................................... 4 Table 2.1 Number of Livestock by Type of Livestock as at 1st October 2008 - National Estimates Table 2.2 Number of Household Rearing Cattle by herd size ........................................................................ 9 Table 2.3 Number of Households Raising Goats by Herd size .................................................................... 16 Table 2.4 Number of Households Raising Sheep by Herd Size ................................................................... 20 Table 2.5 Number of Households Raising Pigs by Herd Size ...................................................................... 22 Table 2.6 Time Series Data On Number Of Households And Chicken By Type For The Year 1995, 1999, 2003 And 2008- Mainland ................................................................................................. 25 Table 2.7 Household Raising Indigenous Chicken by Flock size ................................................................ 26 Table 2.8 Number Of Household And Number Of Improved Chicken By Flock Size ................................ 30 Table 2.9 Other Livestock Types ................................................................................................................. 32 Table 2.10 Milk Production From Goat By Season and Region, During 2007/08 Agricurtural Year ........... 35 Table 2.11 Area Planted and Percent of Total Area Using Fertilizers ........................................................... 37 Table 2.12 Number and Proportion of Households Dewormed Livestock By Livestock Type ..................... 45 Table 2.13: Number of Households Deworming and Not Deworming by Region Table .............................. 46 Table 2.14 Number of Households Receiving Livestock Advice by Source of Extension and Region During the 2007/08 Agricultural Year ......................................................................................... 48 LIST OF CHARTS Chart 2.1: Percent of Livestock by Type ........................................................................................................... 8 Chart 2.2: Percent of Households Keeping Livestock by Type ......................................................................... 8 Chart 2.3: Livestock Number by Producer ........................................................................................................ 9 Chart 2.4: Comparison of livestock Numbers and Livestock Units ................................................................. 9 Chart 2.5: Comparison of Livestock and LSU by Region-Mainland .............................................................. 10 Chart 2.6: Cattle Population By Region- Mainland ........................................................................................ 12 Chart 2.7: Cattle Population Trend ................................................................................................................. 13 Chart 2.8: Improved Cattle Population Trend ................................................................................................. 13 Chart 2.9: Improved Cattle Growth Rate ........................................................................................................ 15 Chart 2.10: Goat Population by Region -Mainland ......................................................................................... 16 Chart 2.11: Goat Population Trend -Mainland ................................................................................................ 18 Chart 2.12: Goat Annual Growth Rate Trend- Mainland ................................................................................ 18 Chart 2.13: Sheep Population by Region- Mainland ....................................................................................... 20 Chart 2.14: Sheep Population Trend- Mainland .............................................................................................. 20 Chart 2.15: Sheep Growth Rate....................................................................................................................... 22 Chart 2.16: Pig Population Trend- Mainland ................................................................................................. 23 Chart 2.17: Pig Population Growth Rate ......................................................................................................... 23 Chart 2.18: Chicken Population Trend ............................................................................................................ 25 Chart 2.19: Chicken Growth Rate - Mainland ............................................................................................... 26 Chart 2.20: Chicken Population by Region ..................................................................................................... 26 Chart 2.21: Indigenous Chicken Population Trend ..................................................................................... 27 Chart 2.22: Indigenous Chicken Growth Rate .............................................................................................. 27 Chart 2.23: Improved Chicken Population Trend ........................................................................................... 29 Chart 2.24: Improved Chicken Growth Rate .................................................................................................. 29 Chart 2.25: Layers Population by Region ....................................................................................................... 30 Chart 2.26: Milk production in Wet season by type of livestock (litres) ....................................................... 32 Chart 2.27: Cow Average Milk production (litres) Per Cow Per Day by Region ........................................... 32 Chart 2.28: Cow Milk Average Price (Tshs/litre) by Region .......................................................................... 33 Chart 2.29: Egg Production by Region- Mainland .......................................................................................... 35 Chart 2.30: Percentage of Household Using Organic Fertilizer – Short Rain Season- Mainland ................... 37 Chart 2.31: Percentage of Household Using Organic Fertilizer – Long Rain Season- Mainland ................... 37 Chart 2.32: Area of Organic Fertilizer Application by Region ....................................................................... 37 Chart 2.34: Proportion of Households Encountering Tick Problem During 2002/3 And 2007/08 Agricultural Years by Region ................................................................................. 39 Chart 2.35: Number and Percent of Households Vaccinated Livestock Against FMD by Region .................. 40 LIST OF TABLES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 vi Chart 2.36: Proportion of Households Encountering Tsetse Problem During 2002/3 And 2007/08 Agricultural Years by Region ...................................................................................................... 40 Chart 2.37: Number and Percent of Households Encountering Newcastle Disease by Region ...................... 41 Chart 2.38: Percent of Households Reporting Tick Control Methods ............................................................ 41 Chart 2.39: Percent of Households Reporting Tsetse Control Methods ......................................................... 41 Chart 2.40: Percent of Households Reporting Newcastle Disease Control Methods ...................................... 44 Chart 2.41: Proportion of Households Dewormed Livestock ......................................................................... 45 Chart 2.42: Number and Percent of Households Receiving Livestock Extension Advice by Region ............ 47 Chart 2.43: Number of Households Receiving Livestock Extension Advice On Disease Control by Region ........................................................................................................................ 49 Chart 2.44: Number of Households Receiving Extension Service by Type of Service .................................. 49 Chart 2.45: Number of Households Practicing Fish Farming by Region........................................................ 50 Chart 2.46: Percent Sources of Fingerlings ..................................................................................................... 50 Chart 2.47: Frequencies of Stocking ............................................................................................................... 51 Chart 2.48: Outlets for Sell of Fish ................................................................................................................. 52 Chart 2.49: Percent of Households by Type of Bee Kept ............................................................................... 52 Chart 2.50: Quantity Of Honey Harvested And Average Production Per Household .................................... 52 Chart 2.51: Prices of Honey by Type of Bees and Region .............................................................................. 53 LIST OF MAPS Map 2.1 Cattle Population by Region as of 1st October 2008 ……………………….......................... 11 Map 2.2 Cattle Density by Region as of 1st October 2008 (km2)………………………….……….… 11 Map 2.3 Improved Dairy Cattle Population by Region as of 1st Oct 2008 ……………………….... 14 Map 2.4 Map of improved Beef Cattle Population by Region as of 1st Oct 2008…………………… 14 Map 2.5 Goat Populations by Region as of 1st Oct 2008…………………………………………….. 17 Map 2.6 Goat Densities by Region as of 1st Oct 2008……………………………………………….. 17 Map 2.7 Dairy Goat populations by region as of Oct 2003…………………………………………… 19 Map 2.8 Meat goat populations by region as of Oct 2003……………………………………………. 19 Map 2.9 Sheep population by region as of 1st Oct 2008……………………………………………… 21 Map 2.10 Sheep density by region as of 1st Oct 2008…………………………………………………. 21 Map 2.11 Pig populations by Region as of 1st Oct 2008………………………………………………. 24 Map 2.12 Pig populations Density as of 1st Oct 2008............................................................................. 24 Map 2.13 Number of chicken by Region as of 1st Oct 2008…………………………………………... 28 Map 2.14 Density of chicken by Region as of 1st Oct 2008…………………………………………... 28 Map 2.15 Number of Indigenous chicken by Region as of 1st Oct 2008……………………………… 31 Map 2.16 Number of layer by Region as of 1st Oct 2008……………………………………………… 31 Map 2.17 Milk production per day (l) during wet season by region…………………………………… 34 Map 2.18 Milk Production per day (l) during dry season by region…………………………………… 34 Map 2.19 Egg Production by Region as of 1st October 2008………………………………………….. 36 Map 2.20 Egg Prices by Region as of 1st Oct 2008……………………………………………………. 36 Map 2.21 Area Planted with Organic Fertilizer by Region as of 1st Oct 2008………………………… 38 Map 2.22 Number of Household Applying Organic Fertilizer by Region as of 1st Oct 2008………… 38 Map 2.23 Number of Household Reporting Tick Problem by Region as of 1st Oct 2008…………….. 42 Map 2.24 Number of Household Reporting Newcastle Problem by Region as of 1st Oct 2008………. 42 Map 2.25 Number of Household Reporting Fowl Typhoid Problem by Region as of 1st Oct 2008…... 43 Map 2.26 Number of Household Reporting Foot and Mouth by Region as of 1st Oct 2008………….. 43 Map 2.27 Number of Household Reporting Lympy skin Problem by Region as of 1st Oct 2008…….. 44 Map 2.28 Number of Household Receiving Livestock Extension by Region as of 1st Oct 2008……... 48 Map 2.29 Number of Household Practicing Fish Farming by Region as of 1st Oct 2008…………….. 51 EXECUTIVE SUMMARY _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 vii EXECUTIVE SUMMARY At the end of 2007/08 fiscal year, the Government of Tanzania carried out the 2007/08 Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan in generating relevant and reliable agricultural statistics for advocacy of effective public policy formulation, including poverty reduction, access to services, gender and other development variables. Tanzania has a diversity of climatic and geographical zones suitable for various crops, species and breeds of livestock. Therefore, the census is important since agriculture is an important economic sector of the Tanzanian economy in terms of food production, employment generation, production of raw materials for industries and generation of foreign exchange earnings. The census was conducted for both large scale farms and smallholder farms. A total of 2,329,942 households were raising livestock from which 2,284,257 were from the Mainland and 45,684 from Zanzibar. This report provides detailed description of the state of the livestock sub-sector in Tanzania for the agricultural year 2007-2008. The detailed analysis and tabulation were based on smallholder farms and comparisons between Mainland regions and Zanzibar districts are made. In some cases, the contribution of large scale farms is included to give the overall country estimates. The main types and number of livestock and poultry covered in the 2007/08 Agricultural Sample Census are cattle, goats, sheep, pigs, chickens, ducks, turkeys, rabbits, and donkeys. The dominant species were cattle (21,280,875) followed by goats (15,154,121), sheep (5,715,549) and pigs (1,584,411). The total number of livestock units was 25,977,665 representing 43.8 million livestock of different species, equivalent to about 30 percent increase from 20,353,866 livestock units counted in the 2002/2003 census. The number of cattle in the Mainland was 21,125,251 while in Zanzibar was 155,624. Of the 1,698,580 cattle keeping households, 71 percent kept between 1 and 10 heads of cattle. The average number of livestock per household was 13 for cattle, 9 for goats and 9 for sheep, while for chicken the average was 11 chicks. The contribution of Large Scale Farms to the total livestock number was rather small (0.1%). Most of the cattle were in Shinyanga, Arusha, Manyara, Tabora and Mwanza, however, the highest densities were in Arusha, Mara, Manyara, and Singida. Shinyanga. Arusha, Manyara and Tabora had the highest goat population, however, the highest densities were in Arusha, Kilimanjaro, Manyara and Mara. Pigs were more common in the southern regions of Mbeya and Iringa, however, the highest densities were in Kilimanjaro and Dar es Salaam regions. In the Mainland, Shinyanga, Mbeya, Mwanza, Tabora, Morogoro, Iringa and Tanga regions accounted for EXECUTIVE SUMMARY _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 viii 50 percent of the total chicken population. Nevertheless, Zanzibar, Dar es Salaam, Pwani and Lindi and Mbeya had the highest density of chicken. Compared to previous 2002/03 census, there has been an increase in the number of all major livestock species with cattle showing an annual growth rate of 4 percent over the period 2003 to 2008. The annual growth rates of goats, sheep, pigs and chicken over the same period were 5.1%, 7.7%, 10, 2 and 5.1% respectively while annual growh rate for. dairy cattle was 35% and for beef cattle was 6% . However, there were virtually no growth in the number of layers and broilers. Most of the livestock species were of indigenous type and were kept by 99 % of the agricultural households. In Tanzania, milk is obtained mainly from cows. Milk production from cows during the wet season was 1.6 billion litres and 0.9 billion litres during the dry season. Average milk production per cow was 3 litres during the wet season and 2 litters during the dry season, a difference of about 33.3 percent. The leading regions in terms of milk production during the wet season were Shinyanga (13%), followed by Arusha (12%), Tabora (9%) and Mbeya ( 10%). Milk prices varied between regions and for the majority of the regions, the prices of milk fluctuated between Tsh 255 and Tsh.711 for the wet season and between Tsh 291 to Tsh.676 in the dry season for Tanzania Mainland, while in Zanzibar, the average price of milk was slightly higher than that of the Mainland whereby the prices were Tsh 481 in the wet season and increased to Tsh.497 during the dry season. Highest prices were observed in Dar es Salam, Mtwara and Kilimanjaro regions during the t season. The number of eggs produced by smallholders during the 2007/08 period was 1,298,052,584 of which 1,173,652,417 (90.4%) were from indigenous chicken and layers while, 106,969,876 (8.2%) were of ducks and 17,430,292 (1.3%) were of turkeys. Most of the eggs were produced in Mbeya ( 8.9%), Shinyanga ( 8.7%) and Tabora ( 7.1%). On the Mainland, the average price per egg was Tsh.156 while in Zanzibar, it was Tsh. 165. The price varied from minimum of Tsh. 107 per egg in Mtwara region to a maximum of Tsh. 200 in Dodoma, Arusha and Mbeya regions. The contribution of livestock is not only limited to its share in the total GDP but also, plays other important roles such as contribution to the national food supply (meat, milk and eggs). In addition to providing meat, milk and eggs, livestock also contributes to crop production through the provision of farm yard manure and draft power. In the Mainland and Zanzibar, there were 661,543 households using organic fertilizers in 488,696 hectares during the 2007/2008 agricultural year. EXECUTIVE SUMMARY _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 ix The average area per household which used organic fertilizers was 0.74 ha. while Mbeya and Kilimanjaro had proportionally more area applied with organic fertilizers although they had relatively fewer number of livestock compared to regions such as Shinyanga, Mwanza and Tabora. This phenomenon can be explained by the intensive type of agriculture practiced in these regions. Despite the large number of livestock in Tanzania, the prevalence of diseases has remained a challenge in improving livestock productivity. Tick Born Diseases (TBD), Foot and Mouth Disease (FMD), Trypanosomosis and Heliminthosis were the common diseases in large and small ruminants, while Newcastle Disease (NCD) was the most problematic disease in chicken. There were 1,659,292 households infected with TBD, 2,614,607 infected with NCD and 252,772 infected with FMD. Shinyanga, Mwanza, Mbeya and Arusha regions recorded higher incidences of TBD, while Kilimanjaro, Arusha, Kagera and Mwanza regions had more cases of FMD. On the other hand, Shinyanga, Mbeya and Mwanza encountered more cases of tsetsefly. As for chicken, more incidences of NCD were reported in the regions of Mbeya (262,665) households, Shinyanga (257,498), Mwanza (189,651) and Tanga (165,400) households. In the overall, NCD affected 45% of the total agricultural households. Despite the occurrence of such diseases, most of the farm households (61%) did not use any tick control methods. Dipping was practiced by only 6 percent of the households, while spraying and smearing were practiced by 29 percent and 3 percent respectively. Similarly, 83 % of the households did nothing to control Tsetse fly. Spraying was the most common method in Tsetse control but it was practiced by only 10 percent of the households. Only 22 percent of the households used Newcastle vaccine to control outbreaks of the Newcastle disease. Worm control was practiced by 2, 109,724 households, representing 47% of the livestock keeping households. In Tanzania Mainland the number of livestock rearing households that received extension service was, 2,388,056 (55%), while in Zanzibar, the number was 91,380 households, representing 26 percent of all livestock rearing households. However, in the Mainland, there were large regional differences. The regions with higher proportions of households receiving extension advice were Manyara (75%), Kilimanjaro (74%) , Arusha (71%), Iringa (69%) , Mbeya (68%) , Dodoma (68%). On the other hand the regions with the lowest proportion of households receiving extension service were Tabora (45%), Ruvuma (43%), Mwanza (42%), Rukwa (40%), Mtwara (34%), Lindi (22%) (Chart 2.42, Map 2.34). When compared to 2002/03 Agriculture Sample Census results, the proportion of households receiving Livestock extension has increased from 15.7 to 55 percent in Tanzania Mainland while in Zanzibar the proportion has increased from 9 to 26 percent. INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 1 1.1 INTRODUCTION Agriculture is an important economic sector of the Tanzanian economy in terms of food production, employment generation, production of raw materials for industry, and the generation of foreign exchange earnings. The agricultural sector produces about 26 percent of GDP (Economic Survey, 2008). Having a diversity of climatic and geographical zones, Tanzania’s farmers grow a wide variety of food and cash crops as well as fruits, vegetables and spices. Tanzania Mainland has about 50 million hectares of land suitable for grazing and is the third with largest livestock population in Africa after Sudan and Ethiopia. In 2007/08, the contribution of livestock to GDP was 4.7 percent of which beef, dairy and other stocks provided 40%, 30% and 30% respectively. The main types of livestock raised in Tanzania are cattle, goats, sheep, pigs and chicken. Besides meat production, other products from livestock include hides and skin, milk and eggs. Livestock also contributes to crop and vegetable production by providing draft power for cultivation and organic manure.This report (Volume III) covers the Livestock Sector at National and Regional levels and includes Tanzania Zanzibar estimates. Other census reports include the Technical Report (Volume I), Crop Report (Volume II), 21 Regional Reports for Tanzania Mainland (Volume IV), Large Scale Farm Report (Volume V) and a separate report for Tanzania Zanzibar (Volume VI). This report is in four main sections: Introduction, Results, Conclusions and Appendices. The definitions relating to all aspects of this report can be found in the questionnaires (Appendix III). 1.2 Background Information The Government of Tanzania has embarked on various plans geared to eradicate extreme poverty by the year 2025 and Zanzibar by the year 2020. In order to facilitate intervention and monitoring activities of the Poverty Monitoring Master Plan, the government has planned a series of censuses and surveys to assist in policy formulation, planning and to track changes in the wellbeing of the population of Tanzania Mainland and Tanzania Zanzibar. In this Master Plan, a series of Agricultural Censuses have been planned, the previous one was undertaken in 2002/03 agricultural year. There has also been a pressing need for agriculture and rural development data to be disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture that supports decision making by the Local Government Authorities and in the design of District Agricultural Development and Investment Projects (DADIPs). The increase in investment is an essential element in the National Strategy for Growth and Reduction of Poverty (NSGRP). 1.2.1 Census Objectives The 2007/08 Agricultural Sample Census was designed to meet the data needs of a wide range of users down to the district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers organizations, and the like. The dataset is both extensive in its sample and detailed in its scope and coverage to meet the user demand. The census was carried out in order to: Identify structural changes in the size of farm household holdings, crop and livestock production, farm inputs and implement use. It also seeks to determine if there are any improvements in rural infrastructures and the level of agricultural household living conditions; INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 2 Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stakeholders; and Establish baseline data for the measurement of the impact of high level objectives of the Agricultural Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty and other rural development programmes and projects. 1.2.2 Census Scope and Coverage 1.2.3 The 2007/08 Agricultural Sample Census was conducted for both large and small scale farms. This report covers small scale farms in detail with some summary data from large scale farms in order to provide complete national estimates for some variables such as total livestock populations. The data was collected from a sample of 52,635 small scale agricultural households of which 48,880 were from the Mainland and 4,755 from Zanzibar. Data was also collected from 1,006 Large Scale Farms (968 on the Mainland and 38 in Zanzibar) on a complete enumeration basis. Three different questionnaires were used to collect data on agriculture and related aspects. These were: Small scale farms questionnaire Community questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; and issues on poverty, gender. Main subjects covered during the study include: Household demographics and activities of the household members; Land access, ownership, tenure and use; Crop and livestock production and productivity; Access to inputs and farming implements; Access and use of credits; Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals, veterinary clinics); Crop marketing, storage and agro-processing; Tree farming, agro-forestry and fish farming; Access and use of communal resources (grazing, communal forest, water for human and livestock, beekeeping); Investment activities: Irrigation structures, water harvesting, erosion control, fencing; Off farm income and non agricultural related activities; Household living conditions (housing, sanitary facilities, etc); Livelihood constraints; Poverty Indicators; and Gender issues INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 3 The community level questionnaire was designed to collect village data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The Large Scale Farm questionnaire was administered to all large scale farms either privately or corporately managed. Some data from the Large Scale Farm questionnaire was incorporated in this report, however, an in depth analysis of Large Scale Farms is presented in a separate report (Volume V). 1.3 Census Methodology The main focus and emphasis at all stages of the census execution was on data quality. The main activities undertaken include: Census organization; Tabulation plan preparation; Sample design; Design of census questionnaires and other instruments, Pilot test ; Training of trainers, supervisors and enumerators; Information Education and Communication (IEC) campaigns; Data collection; Field supervision and consistency checks; Data processing: o Scanning; o Structure formatting application; o Batch validation application; o Manual data entry application; o Tabulation preparation using SPSS; and Table formatting and charts using Excel, maps generation using Arc GIS (Geographical Information System) and Report preparation using Word and Excel. 1.3.1 Census Organization The census was conducted by the National Bureau of Statistics (NBS) in collaboration with Ministries of Agriculture, Food Security and Cooperatives, Livestock and Fisheries Development; Water; Industry and Trade; and the Prime Minister’s Office, Regional Administration and Local Government in Tanzania Mainland. The Office of the Chief Government Statistician (OCGS) in collaboration with Ministries of Agriculture and Natural Resources Livestock and Fisheries in Tanzania Zanzibar. At the national level, the Census was headed by the Director General of the National Bureau of Statistics, Tanzania Mainland in collaboration with the Office of the Chief Government Statistician, Tanzania Zanzibar. The Planning Group formed by the Director General of NBS and the Chief Government Statistician consisted of staff from the Department of Agriculture Statistics of NBS, Department of Economic Statistics of OCGS, Department of Policy and Planning of the Ministry of Agriculture, Food Security and Cooperatives, Department of Policy and Planning of the Ministry of Livestock and Fisheries Development in Tanzania Mainland. The Ministry of Livestock and Fisheries and the Ministry of Agriculture and Natural Resources in Tanzania Zanzibar. The Planning Group was responsible for all the census operations. INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 4 For Tanzania Mainland, implementation of census activities at the regional level was overseen by the Regional Statistical Managers of NBS and the Regional Agricultural Officers from the Prime Minister’s Office, Regional Administration and Local Government. At the district level, each district was managed by two supervisors from the Prime Minister’s Office, Regional Administration and Local Government (PMO- RALG). All the enumerators were from the PMO-RALG. As for Tanzania Zanzibar, the implementation of the census activities at regional level was overseen by the Regional Statistical Officers and Regional Agricultural Officers. At district level, the implementation of the census activities were managed by District Agricultural Development Officers (DADOs) while at the national level, there was a national mobile team to supervise the census operations. The Censuses and Surveys Technical Working Group (CSTWG) under MKUKUTA provided support in sourcing financing, approving budget, allocation and monitoring progress of the Census. A Technical Committee for the census was established with members from key stakeholder organizations and its function was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the census data. 1.3.2 Tabulation Plan Preparation The tabulation plan was developed considering the tabulations from previous censuses and surveys so as to allow trend analysis and comparison as well as the needs of end users. 1.3.3 Sample Design The Mainland sample consisted of 3,192 villages. The villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as National Framework for the conduct of household based surveys in the country. The National Master Sample was developed from the previous 2002 Population and Housing Census. The total Mainland sample was 47,880 agricultural households while in Zanzibar, a total of 317 Enumeration Areas (EAs) were selected and 4,755 agriculture households were covered. In both Mainland and Zanzibar, a two stage sampling was used. The number of villages/Enumeration Areas (EAs) were selected for the first stage with probability proportional to the number of villages/EAs in each district. In the second stage, 15 households were selected from a list of households in each village/EA using systematic random sampling. Table 1.1 gives the sample size of households, villages and districts for Tanzania Mainland and Tanzania Zanzibar. Table 1.1: Census Sample Description Mainland Zanzibar Total Households Villages/EAs Districts Regions 47,880 3192 133 21 4,755 317 9 5 52,635 3,509 142 26 INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 5 1.3.4 Questionnaire Design and other Census Instruments The questionnaires were designed following users demand to ensure that the questions asked were in line with the user data needs. Several features were incorporated into the design of the questionnaires to increase the accuracy of the data. Where feasible, all variables were extensively coded to reduce post enumeration coding error. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions while interviewing the respondent; The responses to all the questions were placed in boxes printed on the questionnaires, with one box per character. This feature made it possible to use scanning and Intelligent Character Recognition (ICR) technologies for data capture; Skip patterns were used to reduce unnecessary and incorrect coding of sections which do not apply to the respondent; Each section was clearly numbered, which facilitated the use of skip patterns and provide a reference for data type coding for the programming of CSPro and SPSS; Three other instruments were used: Village Listing Forms were used for the listing of households in the villages/EAs and from this list, a systematic sample of 15 agricultural households were selected. A training manual which was used by the trainer for the cascade/pyramid training of supervisors and enumerators Enumerator Instruction Manual was used as reference material 1.3.5 Field Pilot-Testing of the Census Instruments The questionnaires were pilot-tested in four locations (Arusha, Dodoma, Unguja and Pemba). This was done to check the wording, flow and relevance of the questions and to finalize crop lists, questionnaire coding and manuals. In addition, several data collection methodologies had to be finalized, namely, livestock numbers in pastoral communities, mixed cropping, use of percentages in the questionnaires and finalizing skip patterns and documenting consistency checks. 1.3.6 Training of Trainers, Supervisors and Enumerators During the training, a cascade/pyramid training techniques were employed to maintain statistical standards. The top level of training was provided to 78 national and regional supervisors (65 from Mainland and 13 from Zanzibar). The trainers were members of the Planning Group from the National Bureau of Statistics, the sector Ministries of Agriculture and Office of the Chief Government Statistician, Zanzibar. In each region, three training sessions were conducted for the district supervisors and enumerators. The training concentrated more on questionnaires, listing forms, field level census methodology, concepts and definitions. Emphasis was placed on consistency checking in the field. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected for the actual field work. The remaining 50% were assigned the work of listing the households in the villages they belong and they were later INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 6 terminated. The best trained enumerators were assigned to list the remaining villages. Each enumerator was assigned to enumerate two villages. 1.3.7 Information, Education and Communication (IEC) Campaign Radios, televisions, newspapers, leaflets, t-shirts and caps were used to create awareness of the Agricultural Sample Census to the public. This helped in sensitizing the public for the field level activities in order to increase the response rate. The t-shirts and caps were given to the field staff and the village chairpersons. The village chairpersons assisted the enumerators to locate the selected households. 1.3.8 Data Collection Data collection activities for the 2007/08 Agricultural Sample Census lasted for three months from June to August, 2009. The direct interview method was used to collect data during the census. Data collection was monitored by a hierarchical system of supervisors which included the Mobile Response Team, Regional and District Supervisors. The Mobile Response Team headed by the Manager of Agriculture Statistics Department, provided an overall direction to the field operations and responded to queries arising outside the scope of the training exercise. Decisions made on the definitions and procedures were then communicated back to the enumerators via the Regional and District Supervisors. On the Mainland, each region had two Regional Supervisors (total 42) and two district supervisors per district (total 266). District Enumeration and Supervision were performed by staff from the Prime Minister’s Office, Regional Administration and Local Government (PMO-RALG) and the sector Ministries of Agriculture. Regional and National supervision was provided by senior staff from the NBS and sector Ministries of Agriculture. In Zanzibar, the enumeration was conducted by staff from the Ministry of Agriculture and Natural Resources and the Ministry of Livestock and Fisheries. Supervision was provided by senior officers of the same Ministries and the Office of the Chief Government Statistician. During the household listing exercise a total of 3,192 extension staff participated on the Mainland while a total of 177 enumerators participated during the listing exercise and enumeration of the small holder questionnaire in Zanzibar. A total of 1,596 enumerators were involved in data collection of the small holder questionnaire on the Mainland. Additional five percent of the enumerators were held as reserves in case of drop outs during the enumeration exercise. 1.3.9 Field Supervision and Consistency Checks Enumerators were trained on how to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check on the questionnaire was carried out by enumerators in the field during enumeration, followed by District, Regional and National supervisors. Supervisory visits at all levels of supervision focused on the completeness of the questionnaires and consistency. Inconsistencies encountered were corrected, and where necessary, call backs to the respondents were made by the enumerators to obtain the correct information. Further more quality control checks were made by the supervisors in each district. 1.3.10 Data Processing Data processing involved the following process: Data entry, INTRODUCTION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 7 Data structure formatting, Batch validation and Tabulation. Data entry Scanning and ICR data capture technology was used. This did not only increase the speed of data entry but also increased the accuracy due to reduction of keystroke errors. Interactive validation routines were incorporated into the ICR software to trap errors during the verification process. Prior to scanning, all questionnaires underwent a manual cleaning exercise by checking that the questionnaire had a full set of pages, correct identification and good hand writing. A score was given to each questionnaire based on the legibility and the completeness of the enumeration. This score was used to assess the quality of enumeration and supervision. CSPro was used for data entry of questionnaires that were rejected by ICR extraction application. Batch Validation A batch validation program was developed in CSPro in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. After data cleaning, the tables were prepared based on the pre-designed tabulation plan. Tabulation Statistical Package for Social Sciences (SPSS) was used to produce the Census tables and Microsoft Excel was used to organize the tables and compute the additional indicators. Excel was also used to produce charts while Arc GIS was used for producing the maps. Report Writing The report writing was outsourced to Sokoine University of Agriculture. It focused on the regional comparisons, time series and national estimates. Microsoft Excel was used to produce charts; Arc GIS and Excel were used to generate maps, whereas Microsoft Word was used in the compilation and report writing. Data Quality Control A great deal of emphasis was placed on data quality throughout the whole exercise, from planning; questionnaire design, training supervision, data entry, validation and cleaning/editing. As a result of this process, it is believed that the census is highly accurate and representative of what was experienced at the field level during the Census Year. With very few exceptions, the variables in the questionnaires are within the norms for Tanzania and they follow the expected time series trends when compared to historical data. 1.4 Funding Arrangements The Agricultural Sample Census was supported mainly by the Department for International Development (DFID) and the Japan International Cooperation Agency (JICA) who financed most of the operational activities. Other funds for the census were from the Government of Tanzania. In addition, technical assistance was provided by the Food and Agriculture Organisation (FAO). RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 8 2.0 LIVESTOCK AND POULTRY RESULTS 2.1 Livestock Population and Growth Livestock sector including poultry plays a significant role in the economy of agricultural households in Tanzania. Livestock Sector generates considerable amount of cash income and determine the household economic and social status in many communities. An estimated 2,329,942 households (About 40% of the agricultural households) kept livestock. The main types and number of livestock and poultry covered in the 2007/08 Agricultural Sample Census are cattle, goats, sheep, pigs, chicken, ducks, turkeys, rabbits, donkeys, horses and dogs (Table 2.1). The reference date for livestock population estimate was as at 1st October, 2008 while other variables collected refer to period of one year prior to this reference date (1St October 2007 to 30th September 2008. The section analyzes the results in relation to the population, growth rates, husbandry and the provision of services at the regional level. It also includes data for Zanzibar and some references are made to the contribution of Large Scale Farms. Population and growth rate trends on livestock are compared with previous Agricultural Censuses over the period between 1995 and 2008. In the surveyed households, cattle were the most dominant specie followed by goats, sheep and pigs (Chart 2.1). The respective numbers and percentages were 21,280,875 (48%), 15,154,121(35%), 5,715,549(13%), and 1,584,411 (4%) for cattle, goats, sheep and pigs respectively. About 38 percent of the households kept goats, 37% kept cattle and those which reared sheep were 14%. Similarly, 11% were found to rear pigs (Chart 2.2). Table 2.1 summarizes production data for different types of livestock and incorporates data from the Mainland and Zanzibar including Large Scale Farms. Ducks, Turkeys, Rabbits and Donkeys are of relative minor importance and the remaining analysis in this section concentrates on the major livestock types (cattle, coats, sheep, pigs and Chicken). Combining Mainland and Zanzibar, there were more households rearing chicken followed by cattle and goats both in smallholder farms and large scale farms. Chart 2.1: Percent of Livestock by Type Cattle 48% Sheep 13% Pigs 4% Goats 35% Cattle Goats Sheep Pigs Chart 2.2: Percent of Households Keeping livestock by Type Cattle 37% Pigs 11% Sheep 14% Goats 38% Cattle Goats Sheep Pigs RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 9 Table 2.1 Production data for different types of livestock, Mainland and Zanzibar small Scale and Large Scale Farms Number of household s Number of Livestock Numb er per house hold Number of household s Number of Livestock Numb er per house hold Number of household s Number of Livestock Numb er per house hold Cattle 1,659,160 21,125,251 13 39,420 155,624 4 1,698,580 21,280,875 13 120,014 21,400,889 Goats 1,732,863 15,085,150 9 13,107 68,972 5 1,745,970 15,154,121 9 24,193 15,178,314 Sheep 638,469 5,718,975 9 210 574 3 638,679 5,715,549 9 14,609 5,730,158 Pigs 521,797 1,581,396 3 153 3,015 20 522,025 1,584,411 3 8,316 1,592,727 Chicken 3,745,867 42,666,543 11 80,069 1,078,962 13 3,802,125 43,745,505 12 494,866 44,240,371 Ducks - 1,157,520 - - 34,279 - - 1,191,799 - 5,293 1,197,092 Guinea pigs - 571,739 - - 823 - - 572,562 - - 572,562 Turkeys - 83,297 - - 881 - - 84,178 - 612 84,790 Rabbits - 135,737 - - 1,262 - - 136,999 - 988 137,987 Donkeys - 296,660 - - 353 - - 297,013 - 147 297,160 Horses - 71 - - - - 71 - 57 128 Dogs - 1,000,019 - - 4,214 - - 1,004,233 - - 1,004,233 Number from Large Scale Farms Total Livestock Population Livestock Type Mainland Zanzibar Total Majority of the livestock are kept by smallholders. Smallholders accounted for 99.6%, while large scale accounted for 0.4% of the total livestock population excluding poultry (Chart 2.3). The contribution of Large Scale Farms to the total livestock number was rather small. The number of cattle was 21,125,251 in the Mainland and 155,624 in Zanzibar. The Large Scale Farms had 120,014 heads of cattle. On expressing livestock number in terms of livestock units (LSU), the results show that, there was an equivalent of 25,977,665 livestock units in total representing 43.8 million livestock of different species, mainly cattle, goats, sheep and pigs in the smallholder and large scale farms. The goat livestock units were about 3 million, while of sheep were 1.14 million and pigs about 0.52 million units (Chart 2.4). The LSU is used to estimate total quantity of livestock based on cow having a LSU of 1, a goat or sheep 1/5 Chart 2.3: Livestock Numbers by Producer Small holder Mainland 43,510,772, 99.1% Large Scale Farms 228,185, 0.4% Smallholder Zanzibar 167,132, 0.5% Small holder Mainland Smallholder Zanzibar Large Scale Farms 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 Number Cattle Goats Sheep Pigs Chart 2.4 Comparison of Livestock Numbers and Units Livestock Number Livestock Units RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 10 LSU and a pig 1/3 LSU. In terms of livestock numbers, Shinyanga and Arusha regions had more livestock than the rest of the regions with a total of 4.2 million and 2.5 million LSU respectively (Chart 2.5, Map 2.1 and Map 2.2). The two regions were followed by Tabora, Mwanza, Manyara Mara and Singida regions with about 2.0 million LSU and Dodoma with 1.5 million LSU while, Mbeya, and Kagera had approximately 1.0 million LSU each. Other regions had less than 1 million units, the least being Dar es Salaam, Lindi and Mtwara regions each with about 60,000 livestock units. 2.1.1 Cattle Population The total number of cattle raised in Tanzania was 21,400,889 of which 21,125,251 were kept by smallholders in the Mainland, 155,624 by smallholders in Zanzibar and 120,014 were raised by Large Scale Farms in Tanzania Mainland. On average, the herd size per cattle holding in the smallholder sector was 13 heads. When compared to the 2002/03 Agricultural Census, the cattle population among the smallholders has increased from 16,999,793 to 21,280,875 in the 2007/08 Census, representing an increase of about 25% giving an annual growth rate of about four percent per annum over the five year period. Of the 1,698,580 cattle keeping households, 72 percent kept between 1 and 10 heads of cattle. On average, 13 heads of cattle were kept per household. Fewer households (5.3%) raised cattle in the range between 51 and 100 heads and about 2 percent of the households were keeping more than 101 heads of cattle. The average herd size for those keeping above 150 cattle was about 307 heads (Table 2.2). Large scale herders (keeping more than 100 cattle) are important as they rear 20 percent of the total cattle population. Shinyanga followed by Tabora region had the highest number of cattle (Chart 2.6, Map 2.1 and 2.2). Other regions with relatively high number of cattle in the range of 1 million to about 1.9 million heads include Mwanza, Arusha, Mara, Manyara, Singida and Dodoma. Regions with the least number of cattle were Dar es Salaam, Lindi and Mtwara. For the remaining regions, the number of cattle ranged from 100,000 to about 900,000. The leading regions in terms of number of households keeping cattle were Shinyanga, Mbeya, Arusha Kilimanjaro and Mwanza. Shinyanga, Tabora, Mwanza, Arusha, Mara and Manyara regions accounted for about 60% of the total population. Chart 2.5 Comparison of Livestock number and Livestock Units by Region-Mainland - 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 Shinyanga Arusha Tabora Mwanza Manyara Mara Singida Dodoma Mbeya Kagera Rukwa Tanga Morogoro Kilimanjaro Iringa Pwani Kigoma Ruvuma Mtwara Lindi Dar es Salaam Number/Units Livestock Number Livestock Units RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 11 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 12 The number of heads of cattle per household ranged from 3 in Ruvuma and Kilimanjaro to 36 in Morogoro. National-wide the average number of head of cattle per household was 13. Chart 2.6 Cattle Population by Region-Mainland 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 Shinyanga Tabora Mwanza Arusha Mara Manyara Singida Dodoma Mbeya Kagera Rukwa Tanga Morogoro Kilimanjaro Iringa Pwani Kigoma Ruvuma Dar es Salaam Lindi Mtwara Number 0 5 10 15 20 25 30 35 40 Herd per Household Number Head per Household Despite Pwani region having fewer cattle and fewer households keeping cattle, the average herd size per household was comparably high (24 heads) . Table 2.2 Number of Household Rearing Cattle by herd size Cattle population in the Mainland (both indigenous and exotic or their crosses) has increased by approximately 26 percent from about 15 million in 1995 to 21 million in 2008 giving annual growth rate of 2 percent. The percentage increase in the total cattle population from 1995 to 1999, 1999 to 2003 and 2003 to 2008 were 4.5%, 2.6% and 21% respectively. In Zanzibar, cattle population increased by approximately 27 percent from about 111,693 heads in 1993 to 155,624 heads in 2008. However, in the period between 2003 and 2008, the total cattle population decreased by 4.5% from 162,643 to 155, 624 giving an annual negative growth rate of about 0.9 percent per annum over the five year period. Herd size Cattle Rearing Households % Herd of Cattle % Average Per Household 1 - 5 861,325 51 2,323,902 11 2.7 6 – 10 350,820 21 2,710,081 13 7.7 11 – 15 169,279 10 2,183,557 10 12.9 16 – 20 96,990 6 1,748,543 8 18.0 21 – 30 89,107 5 2,243,759 10 25.2 31 – 40 41,117 2 1,453,761 7 35.4 41 – 50 24,707 1 1,137,085 5 46.0 51 – 60 17,199 1 958,748 4 55.7 61 -100 28,536 2 2,337,968 11 81.9 101 -150 9,439 1 1,191,886 6 126.3 151+ 10,060 1 3,091,585 14 307.3 National 1,698,580 100 21,380,875 100 12.6 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 13 Indigenous cattle population The cattle population is mainly dominated by the indigenous type (96.2%), while the improved beef and dairy breeds contributed 0.9 and 2.9 percent respectively in the Mainland. In Zanzibar, 95.2 percent of the total cattle population were indigenous type while, the beef and dairy breeds were 0.7 percent and 4.1 percent respectively. The census results show a steady increase on the number of indigenous cattle from 15.3 million in 1995 to 20.7 million in 2008 representing a 25 percent increase (Chart 2.7). Improved Cattle Population Trend Improved cattle can either be categorized as beef or dairy breed. Chart 2.8 shows that the number of dairy cattle (pure or their crosses) has increased three times from about 200,000 in 1995 to about 600,000 in 2008. An average increase of 8 percent per year was reported in 2002/03 census and the rate had dropped to about 5 percent. A large increase of about 36 percent was experienced in the period between 2003 and 2008. As for beef cattle, the general trend was a decrease in the number of beef cattle during the period preceding 2003 (a decline of 76%). However, there was an upward trend in the period between 2003 and 2008 where the number of beef cattle increased by 88 percent from 20,527 to 82,656 heads of cattle. Arusha region kept most (19.4 %) of the improved beef cattle followed by Dodoma (16.1%), Kilimanjaro (11.6%), Shinyanga (11.1%), Mbeya (10.1%), Tabora (7.4%), and Mara (6%) regions. Other regions had less than two percent of the improved beef (Map 2.4). In Arusha region, there were 18,486 improved beef cattle raised by 4,633 households (about 18% of the total households raising improved beef cattle). While, Kilimanjaro region kept most of the improved dairy cattle followed by Arusha and Mbeya regions (Map 2.3). Chart 2.7 Cattle population trend 15,340,899 15,943,827 16,424,572 20,666,360 21,280,875 16,837,150 16,394,967 15,644,802 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 1995 1999 2003 2008 Cattle Number Total cattle Indigenous 212,332 91,571 349,932 101,208 390,825 20,527 519,463 82,656 - 100,000 200,000 300,000 400,000 500,000 600,000 Cattle Number 1995 1999 2003 2008 Chart 2.8 Improved Cattle Population Trend Improve d Da iry Improve d Be e f RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 14 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 15 The growth rate for improved dairy cattle for the period 1995 to 2008 was 7.12 percent per year. However the high growth rate of 13.3 percent experienced during the 1995 -1999 period has declined to only 2.8 percent over the last four years (Chart 2.9). Improved beef cattle population has declined from 91,571 in 1995 to 82,656 in 2008 (Chart 2.8) (-0.78% growth rate per year, chart 2.9). Over the period 1995 to 1999, the population of improved beef cattle was stable. However, this declined sharply from a growth rate of 2.5 percent per year in the period 1995-1999 to a negative growth rate of -33 percent over the period 1999 to 2003. Over the period 2003 to 2008 the population of improved beef and improved diary has grown at 32.1 and 5.86 percent respectively, chart 2.9. 7.12 -0.78 13.30 2.53 2.80 -32.89 5.86 32.13 -40.00 -30.00 -20.00 -10.00 0.00 10.00 20.00 30.00 40.00 Cattle Growth Rates 1995-2008 1995-1999 1999-2003 2003-2008 Chart 2.9 Improved Cattle Growth Rate Improve d Da iry Improve d Be e f RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 16 2.1.2 Goat Population The total number of goats raised by smallholders in Tanzania in 2008 was 15,085,150 for the Mainland and 68,972 for Zanzibar. Only 24,193 goats were kept in Large Scale Farms. These goats were raised by 1,745,970 households of which 1,732,863 were from the Mainland and 13,107 from Zanzibar (Table 2.3). Most of the households (45 percent) kept between 1 to 4 goats and a small number of households (less than 5%) had more than 24 goats but accounted for about 40% of the goat population. Only two percent of the households had more than 40 goats, and accounted for 20 percent of the goat population. The average number of goats per household was nine goats, a small increase of approximately one goat per household as compared to 2002/03 Agricultural Sample Census (Table 2.3) Regions with high numbers of goats were Shinyanga, Arusha and Manyara each with about 1.5 million goats which accounted for 31% of the entire goat population. These regions were followed by Tabora, Mwanza, Dodoma, Mara, Singida and Kagera regions each with about one million goats. Like in cattle, the coastal regions of Dar es Salaam, Lindi and Mtwara had fewer goats. Arusha followed by Manyara and Dodoma regions had the highest number of goats per household (more than 12) (Chart 2.10). The average number of goats per household in the Mainland and Zanzibar was 9 and 5 goats respectively. (Map 2.6). Number % Number % 1 - 4 779,239 45 2,010,920 13 3 5 - 9 510,234 29 3,272,351 22 6 10 - 14 208,231 12 2,359,734 16 11 15 - 19 84,258 5 1,384,272 9 16 20 - 24 61,989 4 1,306,875 9 21 25 - 29 25,442 1 673,217 4 26 30 - 34 23,354 1 727,038 5 31 35 - 39 9,659 1 354,489 2 37 40+ 43,565 2 3,065,224 20 70 Total 1,745,970 100.0 15,154,121 100.0 8.7 Table 2.3 Number of Households Raising Goats by Herd Size Goat rearing households Herd of Goats Average Goats per household Herd Size Chart 2.10 Goat Population by Region-Mainland 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 Shinyanga Arusha Manyara Tabora Mwanza Dodoma Mara Singida Kagera Tanga Kilimanjaro Mbeya Kigoma Rukwa Morogoro Ruvuma Iringa Mtwara Pwani Lindi Dar es Salaam Number 0 2 4 6 8 10 12 14 16 Herd per Household Number of Goats Herd Per Household RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 17 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 18 The general trend is an increase in goat population over the past 13 years, particularly in Tanzania Mainland. The goat numbers increased from 10,628,401 to 15,085,150 goats, an increase of about 30 percent for the period 1995 to 2008 representing a growth rate of 1.27 percent per annum (Chart 2.12). However, the annual growth rates for the period 1995 to 1999 was 0.96%, between 1999 and 2003 was 1.58%. A much larger increase of 5.11 percent was observed between 2003 and 2008 (Chart 2.12). In general very few improved goats are kept in Tanzania. The results show that, out of 15,085,150 goats kept in the Mainland, 14,646,855 or (97%) were of indigenous type, 18,763 or (0.12%) were improved meat goats and 419,533 or (2.8%) were improved dairy type. Most of the improved meat goats were found in the regions of Dodoma, Pwani, Kilimanjaro, Kagera, Ruvuma, Rukwa and Shinyanga while Kilimanjaro, Morogoro, Arusha, Shinyanga, Manyara, Kagera and Mbeya regions in that order had the highest numbers of dairy goats and highest density per square kilometre. The results show that Tanga, Morogoro, Mara and Kigoma regions had no improved meat goats (Map 2.7 and Map 2.8). Chart 2.11 Goat population trend (Mainland) 11,756,527 10,628,401 11,043,093 15,085,150 0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 14,000,000 16,000,000 1995 1999 2003 2008 Year Goat number Chart 2.12 Goat Annual Growth Rate trend - Mainland 1.27 0.96 1.58 5.11 0.00 1.00 2.00 3.00 4.00 5.00 6.00 1995-2008 1995-1999 1999-2003 2003-2008 Year Goat Growth Rate RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 19 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 20 2.1.3 Sheep Population Sheep keeping was less important in the Mainland as well as in Zanzibar. By 1st October, 2008, only 638,679 households or 10.9 percent of the agricultural households were keeping sheep. In Tanzania Mainland there were 638,469 smallholder households that kept about 5,714,975 sheep. The majority (95%) of the smallholder households kept less than 10 sheep per household. A small number of households (1%) kept more than 40 sheep which accounts for 20 percent of the entire sheep population. The average number of sheep per sheep keeping household was 9 in the 2007/08 agricultural year (Table 2.4). In the Mainland regions, most of the sheep were raised in the Northern regions and the number declined as one moves to the South (Chart 2.13 and Map 2.9). Arusha region was leading followed by Shinyanga Manyara, Singida, Mara, Kilimanjaro and Tabora regions. These regions raised about 77 percent of all the sheep. Sheep were reared by 28 percent of the livestock keeping households and the average number of sheep per household was about 9 heads. Regions with fewer numbers of sheep include Lindi, Mtwara, Ruvuma and Dar es Salaam. In comparison to the leading regions, Kigoma, Morogoro, Dar es Salaam and Pwani had the highest number of sheep per household due to few households keeping sheep. Map 2.10 shows the sheep density by region as of 1st October, 2008. Chart 2.14 Sheep population trend (Mainland) 3,945,266 3,488,534 3,493,031 5,715,549 0 2,000,000 4,000,000 6,000,000 8,000,000 1995 1999 2003 2008 Year Number Region Sheep Rearing Households % Herd of Sheep Average Per Houseold 1 - 4 336,535 53 811,380 2 5 - 9 164,200 26 1,055,920 6 10 - 14 60,480 9 684,497 11 15 - 19 24,753 4 400,013 16 20 - 24 17,746 3 376,225 21 25 - 29 7,692 1 203,667 26 30 - 34 7,058 1 220,195 31 35 - 39 2,120 0 77,365 36 40+ 18,213 3 1,886,285 104 Total 638,798 100 5,715,549 9 Table 2.4 Number of Households Raising Sheep by Herd Size RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 21 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 22 Over the period of 13 years (1995-2008), there has been a steady increase in the number of sheep from about 3.4 million to 5.7 million heads (Chart 2.14). This represents an average annual growth rate of 3.86 percent. In the period 1995-1999, the growth rate was almost zero, however, in the subsequent years, there was an improvement and a growth rate of 7.7% was realized in the period between 2003 and 2008 (Chart 2.15). This could be attributed to an increase in the number of households raising sheep from 496, 094 in 2003 to 638,679 households in 2008. 2.1.4 Pig Population Trend Pigs accounted for 3.62 percent of the total livestock population and were raised by 22.4 percent of the households. Most of the pigs (1,581,396) were reared by smallholders in Tanzania Mainland. The average number of pigs per household ranged from about 2 to 48 heads. Most of the pig keeping households (93.7) kept 1 to 9 pigs which accounted for 69.1% of the total pig population. The average number of pigs per household in Tanzania Mainland was 3 heads. (Table 2.5). Table 2.5 Number of Households Raising Pigs by Herd Size Chart 2.16 shows that there was a steady increase in the pig population in the smallholder sector ranging from 434,638 pigs in 1995 to 1,581,396 pigs in 2008. Herd Size Pig rearing households Heads of pig Average per household Number % Number % 1-4 437,591 84 771,324 48.8 2 5-9 51,708 10 323,173 20.4 6 10-14 20,918 4 240,315 15.2 11 15-19 7,023 1 111,892 7.1 16 20-24 2,115 0 44,821 2.8 21 25-29 730 0 19,562 1.2 27 30-39 971 0 31,146 2.0 32 40+ 817 0 39,164 2.5 48 Total 521,872 100 1,581,396 100.0 3 3.86 -0.03 2.5 7.7 -1 0 1 2 3 4 5 6 7 8 Sheep Growth Rates 1995-2008 1995-1999 1999-2003 2003-2008 Growth Period Chart 2.15 Sheep Growth Rate RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 23 The largest increase of pigs was during the periods between 1995-1999 and 2003- 2008. The lowest growth rate of 3.5% was during the period between 1999 and 2003. On the overall, the average annual growth rate between 1995 and 2008 was 10.2% (Chart 2.17) Most of the pigs were kept in Mbeya region followed by Iringa, Ruvuma and Kilimanjaro regions and the average number per household ranged between 2 and 4 pigs (Map 2.11 and Map 2.12). On the overall, 59 percent of the households in these regions accounted for 56.6 percent of the total pig population in Tanzania Mainland. Tanzania Zanzibar had very few pigs (3,015) and most of them were in South Unguja and Urban West regions. However, the number of pigs per household was higher being 16 and 36 pigs for the two regions respectively. The higher ratio of pigs per household could be as a result of the smaller number of households engaged in the pig production. RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 24 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 25 2.1.5 Chicken Population Many households both in the Mainland and Zanzibar kept chicken especially the indigenous ones or their crosses with either layer or broiler types (hereafter referred to as local). In Tanzania Mainland, a total of 3,703,273 smallholder households out of 3,745,867 households had local chicken. By 1st October, 2008, Tanzania had about 43.7 million chicken of which 41.9 million (96%) were local, 1.3 million (2.7%) were layers and 0.6 million (1.3%) were broilers (Chart 2.18 and Table 2.6). No. Households Number of Chicken Number of Households Number of Chicken Number of Households Number of Chicken Number of Households Number of Chicken Local 2,763,196 26,593,691 3,275,860 26,736,174 2,925,710 31,614,837 3,781,695 41,895,605 Broiler 14,438 184,002 No data 517,147 8,131 565,712 14,150 584,028 Layers 12,012 287,691 No data 724,587 16,427 1,126,697 30,091 1,265,872 Total improved 471,693 1,241,734 23,756 1,692,409 44,241 1,849,900 Total chicken 27,065,384 27,977,907 2,933,842 33,307,246 3,825,936 43,745,505 2008 Table 2.6: Time series data on number of households and chicken by type for the year 1995, 1999, 2003 and 2008- Mainland Type of Chicken 1995 1999 2003 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000 40,000,000 45,000,000 Chicken Number 1995 1999 2003 2008 Year Chart 2.18 Chicken Population Trend RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 26 The annual growth rate of chicken (both indigenous and commercial) increased at a rate of 0.83% between 1995 and 1999, 3.55%, between 1999- 2003 and 5.57% between 2003 and 2008 census periods. This increase is largely due to the increase in the number of the indigenous chicken. The overall annual growth rate between 1995 and 2008 was 3.76% (Chart 2.19). Most of the local chicken keeping households (99%) kept less than 50 chicken per household and the households accounted for 91.5 percent of the total local chicken population. Only about one percent of the households had more than 50 chicken representing 8.5 percent of the total chicken population (Table 2.7). In the Mainland, Shinyanga, Mbeya, Mwanza, Tabora, Morogoro, Iringa and Tanga regions accounted for 51.4 percent of the total chicken population (Map 2.13). However, Dar es Salaam, Pwani and Lindi had the highest number of chicken per household (Chart 2.20 and Map 2.14). 3.76 0.83 4.49 5.57 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Chicken Growth Rates 1995-2008 1995-1999 1999-2003 2003-2008 Year Chart 2.19 Chicken Growth Rate Number of Households % Number of Indigenous Chicken % Number of Chicken Per Household 3,728,714 98.6 38,326,920 91.5 10 47,148 1.2 2,691,593 6.4 57 5,260 0.1 681,761 1.6 130 573 0.0 195,331 0.5 341 0 0.0 . . . 0 0.0 . . . 3,781,695 100.0 41,895,605 100.0 11 Table 2.7 Households Raising Indigenous Chicken by Flock Size 1-49 50-99 100-299 Flock Size 500-699 700+ Total Indigenous chicken 300-499 Chart 2.20 Chicken Population by Region 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 Shinyanga Mbeya Mwanza Tabora Morogoro Iringa Tanga Dodoma Pwani Mara Ruvuma Kilimanjaro Singida Rukwa Lindi Mtwara Kagera Dar es Salaam Manyara Arusha Kigoma Population - 5 10 15 20 25 Number of Chicken Per Household Number of Chicken % RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 27 2.1.5.1 Indigenous chicken population Most of the chicken kept by smallholder farmers were of indigenous type or their crosses with exotic types. On the Mainland, there were 3,703,273 households keeping 40,963,137 (96%) of the local types. In Zanzibar, 78,422 households kept 932,469 local types representing 86 percent of the entire chicken population. The growth rate of the indigenous chicken was about 3.56 % per annum for the period between 1995 to 2008 (Chart 2.22). The numbers of indigenous chicken in different regions is presented in Map 2.15. Shinyanga, Mbeya, Mwanza, Tabora and Morogoro regions had the highest indigenous chicken than any other region while Dar- es- salaam, Kigoma and Arusha regions had the least number of indigenous chicken. 26,593,691 26,736,174 31,661,837 41,895,605 - 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000 40,000,000 45,000,000 Chicken Number 1995 1999 2003 2008 Chart 2.21 Indigeneous Chicken Population Trend 3.56 0.13 4.32 5.76 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Chicken Growth Rates 1995-2008 1995-1999 1999-2003 2003-2008 Chart 2.22 Indigenous Chicken Growth Rate RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 28 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 29 2.1.5.2 Improved Chicken The number of improved chicken in the smallholder sector is relatively very small contributing only 4.2% of the entire chicken population. In Tanzania Mainland improved chicken population (Layers and Broilers) was about 1,703,406 chicken of which 1,135,838 were layers and 567,568 were broilers and were raised by 42,594 households. In Zanzibar about 130,034 layers and 16,459 broilers were raised by 1,647 households. (Chart 2.23, Table 2.6). The results show that 84.8 percent of the households raised between 1 and 49 layers while the majority (86.1%) kept between 1 and 49 broilers. There were fewer (4.5%) households which raised more than 300 layers. Households raising more than 300 Chicken accounted for 4.5%. The small number of improved chicken in the smallholder sector could be attributed to the nature of the business which is generally capital intensive compared to the raising of local chicken. Tanzania Mainland accounted for 95.4 percent of the households which raised layers and 98.1 percent of households which raised broilers while Tanzania Zanzibar accounted for the remaining percentages. Out of the total number of improved chicken (layers and broilers), 24.9 percent raised between 100 and 299 improved chicken, while 19.5 percent had more than 700 chicken, but still the proportion of the number of chicken raised in the range of 1- 49 was equally high and compares with those in the range of 300 to 499. The trend shows that over the period between 2003 and 2008, the number of layers has increased from 1,126,697 to 1,265,872 or 2.36 percent increase, and the number of broilers has also increased from 565,712 to 584,028 or 0.64 percent increase over the same period (Chart 2.24). 287,691 184,002 724,587 517,147 1,126,697 565,712 1,265,872 584,028 - 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 Cattle Number 1995 1999 2003 2008 Chart 2.23 Improved Chicken Population Trend Layers Broilers 12.07 9.29 25.98 29.48 11.67 2.27 2.36 0.64 0.00 5.00 10.00 15.00 20.00 25.00 30.00 Chicken Growth Rates 1995-2008 1995-1999 1999-2003 2003-2008 Chart 2.24 Improved Chicken Growth Rate Layers Broilers RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 30 Table 2.8 Number of Household and Number of Improved Chicken by Flock Size Flock Size Layers Broilers Numbe r of House holds Number of Layers % Number of Chicken Per Househo ld Number of Households Number of Broilers % Number of Chicken Per Household 1-49 25,509 218,687 0.5 9 12,179 120,246 0.3 10 50-99 1,395 80,834 2.8 58 307 19,489 0.7 63 100-299 1,830 295,607 25.0 162 1,036 164,118 13.9 158 300-499 669 209,086 37.1 313 407 138,864 24.6 341 500-699 305 169,203 69.7 555 135 73,527 30.3 546 700+ 384 292,455 81.2 761 85 67,783 18.8 800 Total 30,091 1,265,872 2.7 42 14,150 584,028 1.2 41 In comparison with the local types, there was a general upward trend in the period between 1995 and 1999; broilers grew at a faster rate (29.48%) as compared to layers (25.98%) and local chicken (0.13%). Between 2003 and 2008, the growth of local chicken was higher (5.76%) as compared to layers (2.36%) and broilers (0.64%) possibly as a result of various poverty reduction programmes which targeted mostly on the poor; while for the improved types, it could be associated with problems in the supply of day old chicks. Most of the layers on the Mainland were raised in Dar es Salaam (41.4%). Other regions with slightly high numbers of layers were Pwani region (16.2%) and Kilimanjaro region (8.4%) (Chart 2.25, Map 2.16). The remaining regions had insignificant number of layers. Chart 2.25 Layers Population by Region - 100,000 200,000 300,000 400,000 500,000 600,000 Dar es Salaam Pwani Kilimanjaro Shinyanga Iringa Tabora Mbeya Morogoro Ruvuma Rukwa Dodoma Mtwara Kigoma Lindi Kagera Manyara Singida Mwanza Arusha Tanga Mara Population - 5 10 15 20 25 30 35 40 45 50 Percent Number of Layers % RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 31 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 32 2.1.6 Other Livestock Other livestock include ducks, guinea pigs, turkeys, rabbits and donkeys (Table 2.9). They are less important to the overall contribution to household food security and as such, are kept by a minimal number of households. Proportionally, there were more ducks compared to other types while the number of horses was the least. Donkeys are mainly used as pack animals and are mainly reared in Arusha and Manyara regions. Dogs are mainly important for household security specifically in the livestock keeping community for scaring livestock scavengers. 2.2 Livestock and Poultry Products Livestock and poultry have other benefits besides meat. In this section, the results for milk production from cows and goats, egg production are presented. The results on the use of farm yard manure are dealt with in the next section. 2.2.1 Milk Production In Tanzania, milk is obtained from cows and goats. However, goat milk production is of minor importance compared to that of cows (Chart 2.26). During the wet season, milk production from cows was 1,649 million litres (99%) and only 22 Million litres (1%) were from goats. The average milk production per cow per day was three litres during the wet season and two litres during the dry season. The lactation length was 151 days in the wet season and 129 days in the dry season. Milk from Cows: Tanzania Mainland produced about 2.5 Billion litres of milk and the leading regions were Shinyanga (14%), Arusha (11%), Tabora and Mbeya each with (9 %), Kilimanjaro (7%). The five regions produced (50%) of the total milked cows. On daily basis, Dar es Salaam, Lindi, Ruvuma and Morogoro regions had the highest daily milk yield, the quantities produced being 8, 7 and 5 litres per day respectively, during the wet season. Across the regions, the differences could be explained by the proportion of improved cattle in the Table 2.9 Other Livestock Types Livestock Type Head Number Ducks 1,1575,520 Guinea pigs 571,739 Turkeys 83,297 Rabbits 135,737 Donkeys 296,660 Horses 71 Dogs 1,004,233 Chart 2.26 Milk Production in Wet Season by Type of Livestock (Litres) Goat Milk, 22,024,585, 1% Cow Milk, 1,649,883,160, 99% Chart 2.27 Cow Average Milk Production (litres) per Cow per day by Region and Season 0 1 2 3 4 5 6 7 8 9 Dar es Salaam Lindi Ruvuma Morogoro Mbeya Pwani Kilimanjaro Rukwa Tanga Kagera Arusha Iringa Kigoma Mtwara Dodoma Tabora Mwanza Shinyanga Manyara Mara Singida Region Litres Wet Season Dry Season RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 33 regions, whereby most of the cattle in Dar es Salaam were of improved types compared to other regions with high numbers of cattle such as Shinyanga, Mwanza and Manyara where the dominant cattle type were indigenous with low genetic potential for milk production. The trend is the same during the dry season and as expected, there was a decrease in the amount of milk produced per cow in all the regions. Milk prices varied between regions and for the majority of the regions, the prices of milk fluctuated between Tsh. 255 and Tsh.711 for the wet season and Tsh. 291 to Tsh. 676 in dry season for Tanzania Mainland. While in Zanzibar, the average milk prices were slightly higher than those of the Mainland whereby the minimum prices were Tsh 481 in the wet season and increased to Tsh.497 during the dry season. Highest prices were observed in Dar es Salam where a litre of milk was sold at Tsh.711 during the wet season (Chart 2.28). There was a significant variation in the prices of milk in Lindi, Mtwara, Rukwa and Kigoma between the dry and wet seasons, while in other regions, the prices have remained stable. Chart 2.28 Cow Milk Average Price (TShillings/litres) by Season and Region 0 100 200 300 400 500 600 700 800 Dar es Salaam Mtwara Lindi Kilimanjaro Pwani Manyara Arusha Mbeya Iringa Morogoro Ruvuma Kigoma Tanga Mwanza Shinyanga Singida Kagera Mara Rukwa Dodoma Tabora Region Price per litre (Tshs) Wet Season Dry Season RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 34 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 35 Milk from Goat Nationalwide, 335,428 goats were milked in the wet season, and the number dropped to 174,088 in the dry season, a difference of 48.1 percent. In the Mainland, a similar scenario was obtained where 334,802 and 173,645 goats were milked in the wet and dry seasons respectively. While in Zanzibar, 627 goats were milked in the wet season and 442 during the dry season. The average milk production per goat per day ranged from 0 to 4 litres whereby Mtwara, Lindi and Mbeya regions had higher average milk production of between 3 to 4 litres per day (Table 2.10). 2.2.2 Egg Production The number of eggs produced by smallholders during the 2007/08 Agricultural Year was 1,298,052,584 of which 1,173,652,417 (90.4%) were from the indigenous chicken and layers while, 106,969,876 (8.2%) were of ducks and 17,430,292 (1.3%) were of turkeys. Out of the total number of eggs, 1,256,672,634 (96.8%) eggs were produced in the Mainland and 41,379,951 (3.2%) were produced in Zanzibar. Most of the eggs produced were from the regions of Mbeya (8.9%), Shinyanga (8.7%), Tabora (7.1%) and Iringa (7.0%). This represents 31.7 percent of the total eggs production in Tanzania (Chart 2.29). On the Mainland, the average price per egg was Tsh. 156 while in Zanzibar, the average price was Tsh. 165. The price varied from a minimum of Tsh. 107 per egg in Mtwara to a maximum of Tsh. 200 in Dodoma, Arusha and Mbeya regions. Wet Season Dry Season Wet Season Dry Season Dodoma 3,234 1,679 2 1 Arusha 199,183 93,790 1 1 Kilimanjaro 19,151 15,768 1 1 Tanga 14,306 9,743 1 1 Morogoro 4,587 4,866 2 2 Pwani 2,209 1,556 2 1 Dar es Salaam 387 324 1 1 Lindi 2,306 2,029 4 2 Mtwara 1,164 927 3 2 Ruvuma 59 59 2 1 Iringa 3,402 2,889 1 1 Mbeya 1,432 1,272 3 2 Singida 706 0 1 0 Tabora 819 582 2 1 Rukwa 0 0 0 0 Kigoma 0 0 0 0 Shinyanga 528 398 2 1 Kagera 9,121 6,382 1 1 Mwanza 234 234 1 0 Mara 0 508 0 0 Manyara 71,974 30,638 1 1 Mainland 334,802 173,645 1 1 North Unguja 95 95 0 0 South Unguja 304 182 1 1 Urban West 126 63 2 2 North Pemba 102 102 2 1 South Pemba 0 0 0 0 Zanzibar 627 442 1 1 Total 335,428 174,088 1 1 Table 2.10 Milk Production from Goat By Season and Region, During the 2007/08 Agricultural Year Region Number of Milked goat Average milk production per goat per day (lts) Chart 2.29 Egg Production by Region-Mainland - 20,000,000 40,000,000 60,000,000 80,000,000 100,000,000 120,000,000 140,000,000 Mbeya Shinyanga Tabora Iringa Singida Mwanza Dar es Salaam Kilimanjaro Arusha Tanga Morogoro Kagera Dodoma Manyara Ruvuma Pwani Mara Rukwa Mtwara Lindi Kigoma Region Number - 1 2 3 4 5 6 7 8 9 10 Percent Total eggs Produced Percent RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 36 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 37 Chart 2.32 Area of Organic Fertilizer Application by Region 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es Salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Rukwa Kigoma Shinyanga Kagera Mwanza Mara Manyara Number 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Area Applied per Household Planted Area Applied with Organic Fertlizer Organic Fertlizer Use per household 2.3 Animal Contribution to Crop Production Livestock contributes to crop production through the provision of draft power for ploughing and pack for transportation as well as farm yard manure used as fertilizer for crop production. Livestock are an important part of the farming system considering the low availability of tractors and the virtual absence of artificial fertilizer used by smallholders in Tanzania (see Crop Report Volume II of Census Publications). 2.3.1 Use of Organic Fertilizers The number of households using organic fertilizers in Tanzania during short rain season was 211,385, of which 203,883 were of Tanzania Mainland representing 11 percent on Tanzania Mainland and 7,502 households in Tanzania Zanzibar representing 0.4 percent of the total agriculture households (Chart 2.30 and Chart 2.31). The number of household planting crops in long rain season was 4,550,746 of which 4,462,382 (98%) were in Tanzania Mainland and 88,364 (2%) in Zanzibar. The total area planted in Masika and, Vuli seasons was 8,808,680 ha. Out of this, the area under organic fertilizer application was 488,696 ha which represents 5.5 percent of the total planted area (Table 2.25). On Inorganic Fertilizer Application the total area planted was was 578,446 which represents 6.7 percent of the total area planted for both Masika and Vuli Seasons Table 2.11 Area Planted and Percent of Total Area using Fertilizers Fertilizer type Area under fertilizer application Total Area Planted % of Total Area Organic fertilizer 488,696 8,808,680 5.55 Inorganic fertilizer 578,446 8,808,680 6.57 The average area per household using organic fertilizers was 0.8 hectares. Regions with highest area applied with organic fertilizers were Singida, Shinyanga, Tabora and Dodoma. However, the application of organic fertilizers depended much on the livestock population in a particular region. For example, Lindi region had the lowest Chart 2.30 Households Using Organic Fertilizer - Short Rain Season - Mainland Households NOT using Organic Fertlizer, 1,666,350, 89% Households using Organic Fertlizer , 203,883, 11% Chart 2.31 Households Using Organic Fertilizer - Long Rain Season - Mainland Number of Households NOT using Organic Fertlizer, 4,019,029, 90% Number of Households usin Organic Fertlizer 443,353, 10% RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 38 number of cattle that is 30,784 but, the average area used with organic fertilizer per household was 0.9 hectares, Mtwara had 18,115 cattle and the average area per household was 0.6 hectares compared with the regions with high number of cattle such as Shinyanga, Mwanza which had 3,668,643 and 1,980,996 cattle with 1.2 hectares and 0.5 hectares applied with organic fertilizers respectively (Chart 2.29). This implies that having high number of cattle does not necessarily imply high use of organic fertilizers. Zanzibar had 156,018 cattle and the average organic fertilizers use was 0.43 hectares per household. RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 39 2.4 Livestock Pest Control Livestock pest control is presented in two sections. The first section presents the results on common livestock diseases whilst the second section presents the results on the control methods of specific types of pests and parasites. 2.4.1 Common Livestock Diseases The livestock pest control focused on cattle, goats, sheep, pigs and chicken. Common Livestock pests amongst cattle, goats, sheep and pigs include tick born disease, foot and mouth diseases, tsetse fly, and Newcastle disease. 2.4.1.1 Tick Problem Tick born disease infects cattle, goats, sheep and pigs. The total number of households with tick problem was 1,659,292 (1,655,203 in the Mainland and 30,121in Zanzibar) which represents 37.4 percent of the livestock keeping households. The number of households not affected with tick problem was 921,438 (904,269 in the Mainland and 17,169 in Zanzibar) which represents 20.4 percent of livestock keepers and the number of households with livestock other than cattle, goats, sheep and pigs which were not infected with Tick problem was 1,907,470 (1,862,452 in the Mainland and 45,019 in Zanzibar) which represent 42.2 percent. During the 2007/08 Agricultural year, the regions with the highest proportion of livestock keeping households infected with tick problem in Tanzania were Mara and Manyara both (82%), Arusha (81%), Shinyanga (79%), Tabora (75%), Singida (70%), Mwanza (70%), Dodoma (69%) and Tanga (69%). As would have been expected, these are the regions with favourable conditions for livestock keeping. The regions with the lowest number of livestock keeping infected with tick problem were Kagera (53%), Kigoma (52%), Iringa (51%), Mtwara (42%), Morogoro (40%), Lindi (39%), Kilimanjaro (38%), Ruvuma (35%) (Chart 2.34). These results reflect the reality that these regions also have smallest numbers of livestock keeping households. There were variations in terms of incidences of ticks between 2002/03 and 2007/08 year. Tick incidence seem to have increased significantly in Dodoma, Tanga, Pwani and Dar es Salaam Regions, when compared to what was observed in 2002/03 agriculture sample census (Chart 2.30) Chart 34 Propotion of Households Encountering Tick Problems during 2002/03 and 2007/08 Agricultural years by Region 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 Mara Manyara Arusha Shinyanga Tabora Singida Mwanza Dodoma Tanga Pwani Rukwa Mbeya Dar es Salam Kagera Kigoma Iringa Mtwara Morogoro Lindi Kilimanja Ruvuma Region Proportion 2002/03 2007/08 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 40 2.4.1.2 Foot and Mouth disease Foot and Mouth Disease (FMD) vaccination was also inquired for cattle, goats, sheep, and pigs. Vaccination was effected on 252,772 livestock keeping households of which 248,258 (98.2%) were in the Mainland and 4,513 (1.8%) were in Zanzibar. The number of livestock keeping households not vaccinated livestock against foot and mouth disease was 1,573,328 of which 1,536,060 (97.6 %) was from the Mainland and 37,268 (2.4%) was from Zanzibar. National wise, the regions with the highest number of livestock keeping households Vaccinated livestock against foot and mouth disease were Kilimanjaro (32,540%), Arusha (31,410%), Kagera (23,486%), Mwanza (20,382%), Tanga (18,015%), Mbeya (15,046%), Shinyanga (14,631%) and Manyara (14,506%). At regional level, the highest percent of households vaccinating livestock against FMD was found in Dar es Salaam (49%) , Kagera ( 32%), Pwani ( 24%) , Tanga and Kilimanjaro ( 22%), Arusha (21%), Kigoma (18%) , Iringa and Dodoma (15%), chart 2.35. 2.4.1.3 Tsetse Flies Problems The number of households reporting Tsetse flies problems was 489,601 from the Mainland representing 21 percent of all livestock rearing households. On the whole, all the regions had relatively high numbers of livestock keeping households with Tsetse flies problems. The number of livestock keeping households with tsetse problem was highest in Arusha with 55 percent followed by Dar es Salaam and Pwani (38%), Tanga (35%), Manyara (34%) and Dodoma, Mara and Morogoro with 26 Percent. (Chart 2.36). As compared to what was observed during the 2002/03 agricultural sample Census, Tsetse flies problem seem to be more prominent in Arusha, Dar es Salaam, Pwani, Tanga, Manyara and Dodoma. Chart 2.36 Propotion of Households Encountering Tsetese flie Problems during 2002/03 and 2007/08 Agricultural years by Region 0 10 20 30 40 50 60 Arusha Dar es Salam Pwani Tanga Manyara Dodoma Morogoro Mara Singida Kilimanjaro Mbeya Shinyanga Iringa Ruvuma Rukwa Kigoma Tabora Lindi Mtwara Mwanza Kagera Region Proportion 2002/03 2007/08 Chart 2.35 Number and Percent of households Vaccinated Livestock against FMD by Region 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Kilimanjaro Arusha Kagera Mwanza Tanga Mbeya Shinyanga Manyara Singida Dodoma Tabora Iringa Rukwa Mara Kigoma Dar es Salaam Pwani Morogoro Ruvuma Mtwara Lindi Region Number Vaccinated 0 10 20 30 40 50 60 Percentage Number Vaccinated Percentage RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 41 2.4.1.4 Newcastle disease Newcastle disease was reported in 2,631,645 livestock keeping households of which 2,578,115 were in the Mainland and 53,530 were in Zanzibar. The leading regions with the households encountering Newcastle disease include Mbeya 262,665, Shinyanga 257,498, Mwanza 189,651, Tanga 165,400, Iringa 155,483, Dodoma 150,254, Morogoro 147,741. However the regions with higher infection rates above the National Average (67%), were Lindi (78%), Tanga (76%), Dodoma (76%), Morogoro (75%), Mbeya (74%), Mtwara 73%), Dar es Salaam (72%) and Shinyanga (69%) (Chart 2.37). 2.4.2 Specific Livestock Pest control methods Specific Livestock Pest control methods dealt with in this section were for Tick problem, Tsetse Fly, and Newcastle Disease. 2.4.2.1 Tick Control Methods Tick born diseases were one of the most serious diseases infecting livestock. As noted earlier, high incidences of this disease were encountered in Mara, Manyara, Arusha, Shinyanga, Tabora, Singida, Mwanza, and Dodoma. The control methods for Tick born disease include spraying applied by 1,292,891 (29%) households; dipping, 259,815 (6%) households; smearing, 199,297 (4%) households; others, 26,445 (1%) households and those which did not practice any control method for the Tick born constituted 2,734,882 households representing 60 percent (Chart 2.38), this might be the reason for the wide spread of tick problems across the regions as noted in para 2.4.1.1. 2.4.2.2 Tsetse fly Control Methods The control methods for Tsetse fly practised by livestock raising households include spraying 409,410 (9.4%) followed by trapping 138,355 (4.2%), and Dipping 107,822 (2.4%). Other methods were practised by 44,266 (1%) of the households. Those which did not practice any control methods for the Tsetse problem include 3,705,289 (83%) of the households (Chart 2.39). Chart 2.37 Number and Percent of households Encountering Newcastle Disease by Region 0 50,000 100,000 150,000 200,000 250,000 300,000 Mbeya Shinyanga Mwanza Tanga Iringa Dodoma Morogoro Tabora Mara Kilimanjaro Singida Rukwa Mtwara Ruvuma Manyara Lindi Arusha Pwani Kagera Kigoma Dar es Salaam Region Number 0 10 20 30 40 50 60 70 80 90 Propotion Number Percent Chart 2.38 Percent of Households Reporting Tick Control Methods Dipping, 259,815, 6% Spraying, 1,292,891, 29% Smearing, 199,297, 4% Other, 26,445, 1% None, 2,734,882, 60% Chart 2.39 Percent of Households Reporting Tsetse Control Methods None, 3,705,289, 83% Other, 44,266, 1% Trappig, 138,355, 4.2% Spraying, 409,410, 9.4% Dipping, 107,822, 2.4% RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 42 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 43 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 44 2.4.2.3 Newcastle Control Methods Newcastle was another serious disease encountered by households raising livestock. The mostly affected regions were in Mbeya, Shinyanga, Mwanza, and Tanga regions. The affected households were noted to use mainly two control methods namely, Local Herbs used by 1,175,142 households representing 26 percent, and Vaccination which was used by 992,431 households representing 22 percent. Households found not using any control method for the Newcastle disease were 2,346,582 or 52 percent (Chart 2.40). Chart 2.40 Percent of Households Reporting Newcastle Control Methods Vaccination, 992,431, 22% Local Herbs, 1,175,142, 26% None, 2,346,582, 52% RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 45 2.4.3 Deworming practices It is estimated that 2,109,724 of livestock keeping households deworm their livestock (2,018,610 on the Mainland and 28,113 in Zanzibar during 2007/08 agricultural year). This represents 46.5 percent of the total livestock raising households. The number and proportion of households practicing deworming of livestock varied by species of livestock, (table 2.11 and chart 2.41). Cattle exhibited high proportion (70% in 2002/03 compared to 49% in 2007/08) followed by pigs (63% in 2002/03 compared to 46% in 2007/08), goats/sheep (56% in 2002/03 compared to 42% in 2007/08) and lastly, chicken (19% in 2007/08). In general, there seems to be a decrease in deworming practice between the two censuses. Most of the deworming was practised in Arusha, 174,354 (93 %) households, Tanga 218,528 (89 %) Manyara (67%), Dar es Salaam 16,414 (58%) of the total households. Deworming was least practised in Pwani (16%), Lindi (16%) and Rukwa (31%) while in Zanzibar, it was practised by less than 50% of the households. (Table 2.11). 70 49 56 42 63 46 19 - 10 20 30 40 50 60 70 80 Proportion Cattle Goats/Sheep Pig Chicken Chart 2.41 Proportion of Households Dewormed Livestock Propotion - 2002/03 Propotion - 2007/08 Table 2.12 Number and Proportion of Households Dewormed Livestock by Livestock type 202/03 2007/08 202/03 2007/08 202/03 2007/08 202/03 2007/08 Households Deworming Livestock 620,652 1,194,220 585,216 981,171 161,715 330,750 . 729,353 Livestok Keepes 1,272,584 1,698,580 1,377,839 1,745,970 348,377 522,025 . 3,802,125 Propotion 49 70 42 56 46 63 . 19 Cattle Goat/Sheep Pig Chicken Households/Prpotion RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 46 Table 2.13 Number of Households Deworming and Not Deworming by Region Region Deworming Livestock Not Deworming Livestock Number % Number % Total Livestock Keepers % Dodoma 76,344 33 152,735 67 229,079 100 Arusha 174,354 93 12,507 7 186,861 100 Kilimanjaro 178,331 81 42,164 19 220,495 100 Tanga 218,528 89 28,333 11 246,861 100 Morogoro 54,361 25 159,550 75 213,911 100 Pwani 19,126 16 97,753 84 116,878 100 Dar es Salaam 16,414 58 11,927 42 28,341 100 Lindi 17,680 16 93,520 84 111,199 100 Mtwara 38,070 25 115,202 75 153,272 100 Ruvuma 83,642 50 82,288 50 165,931 100 Iringa 145,622 55 121,051 45 266,673 100 Mbeya 190,313 49 198,926 51 389,239 100 Singida 71,523 39 110,117 61 181,640 100 Tabora 84,174 36 151,540 64 235,713 100 Rukwa 53,001 31 115,957 69 168,958 100 Kigoma 72,826 46 83,823 54 156,649 100 Shinyanga 161,278 39 256,254 61 417,532 100 Kagera 104,416 39 164,675 61 269,091 100 Mwanza 119,893 37 202,967 63 322,859 100 Mara 87,867 46 101,713 54 189,580 100 Manyara 113,846 67 54,879 33 168,725 100 MAINLAND 2,081,610 46 2,357,879 54 4,439,489 100 North Unguja 5,255 29 12,254 71 17,510 100 South Unguja 5,863 44 7,397 56 13,260 100 Urban West 5,778 42 6,971 58 12,748 100 North Pemba 6,035 23 19,556 77 25,591 100 South Pemba 5,182 23 17,089 77 22,272 100 ZANZIBAR 28,113 27 63,267 73 91,380 100 Total 2,109,724 47 2,421,146 53 4,530,870 100 RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 47 2.5 Livestock Extension Services 2.5.1 Extension Services Outreach In Tanzania Mainland the number of livestock rearing households that received extension service was, 2,388,056 (55%), while in Zanzibar, the number was 23,336 households, representing 26 percent of all livestock rearing households. However, in the Mainland, there were large regional differences. The regions with higher proportions of households receiving extension advice were Manyara (75%), Kilimanjaro (74%) , Arusha (71%), Iringa (69%) , Mbeya (68%) , Dodoma (68%). On the other hand the regions with the lowest proportion of households receiving extension service were Tabora (45%), Ruvuma (43%), Mwanza (42%), Rukwa (40%), Mtwara (34%), Lindi (22%) (Chart 2.42, Map 2.34). When compared to 2002/03 Agriculture Sample Census results, the proportion of households receiving Livestock extension has increased from 15.7 to 55 percent in Tanzania Mainland while in Zanzibar the proportion has increased from 9 to 26 percent. 2.5.2 Sources of Extension The main source of livestock extension services is the Government with 90.5 percent of households receiving advice. Other sources of advice came from neighbours (12.5%), Non Governmental Organisation (NGOs) and Radios/TVs/Newspapers (12.1%), Cooperatives (3.7%), while large scale farms contributed (3.3%), Table 2.12 Chart 2.42 Number and Percent of households Receiving Livestock Extension Advice 0 50,000 100,000 150,000 200,000 250,000 300,000 Mbeya Shinyanga Iringa Kilimanjaro Dodoma Mwanza Arusha Tanga Manyara Kagera Mara Tabora Morogoro Kigoma Singida Ruvuma Rukwa Pwani Mtwara Lindi Dar es Salaam Region Number 0 10 20 30 40 50 60 70 80 households with extension Number Propotion RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 48 1The reader should take a note that this was a multiple response question. The responses for the different sources of livestock extension services cannot add up as this provides duplicate responses. Number % Number % Number % Number % Number % Number % Dodoma 141,677 93.3 17,029 11.2 5,018 3.3 5,135 3.4 34,387 22.6 17,190 11.3 151,873 Arusha 124,493 94.5 32,845 24.9 6,238 4.7 5,906 4.5 14,277 10.8 14,792 11.2 131,712 Kilimanjaro 155,916 95.2 24,413 14.9 15,598 9.5 7,576 4.6 34,958 21.3 24,680 15.1 163,746 Tanga 113,735 91.0 9,953 8.0 2,572 2.1 1,522 1.2 6,269 5.0 13,095 10.5 124,950 Morogoro 84,221 84.0 11,931 11.9 1,897 1.9 1,267 1.3 10,860 10.8 13,229 13.2 100,217 Pwani 50,930 90.9 4,806 8.6 1,699 3.0 2,200 3.9 10,366 18.5 4,364 7.8 56,014 Dar es Salaam 15,334 82.8 2,308 12.5 307 1.7 1,385 7.5 2,795 15.1 2,835 15.3 18,515 Lindi 21,227 88.2 1,330 5.5 669 2.8 421 1.7 1,397 5.8 2,364 9.8 24,065 Mtwara 44,837 88.1 3,417 6.7 2,523 5.0 729 1.4 5,879 11.6 7,361 14.5 50,867 Ruvuma 58,994 84.1 6,112 8.7 876 1.2 397 0.6 8,335 11.9 9,029 12.9 70,129 Iringa 166,589 93.6 18,740 10.5 6,231 3.5 2,076 1.2 9,222 5.2 15,712 8.8 177,915 Mbeya 229,357 87.8 22,808 8.7 9,878 3.8 6,589 2.5 26,855 10.3 45,228 17.3 261,267 Singida 81,001 95.3 5,178 6.1 1,109 1.3 1,404 1.7 8,761 10.3 8,545 10.1 84,975 Tabora 93,113 89.4 15,825 15.2 8,617 8.3 13,926 13.4 24,359 23.4 18,581 17.8 104,206 Rukwa 57,873 84.4 6,905 10.1 702 1.0 1,706 2.5 10,496 15.3 12,972 18.9 68,550 Kigoma 76,296 88.1 12,245 14.1 2,769 3.2 1,543 1.8 7,241 8.4 6,850 7.9 86,651 Shinyanga 211,141 93.0 25,542 11.2 6,799 3.0 9,287 4.1 19,819 8.7 15,296 6.7 227,076 Kagera 100,657 83.8 14,718 12.2 3,860 3.2 3,560 3.0 10,941 9.1 23,884 19.9 120,173 Mwanza 123,225 93.1 14,628 11.1 2,929 2.2 3,627 2.7 13,475 10.2 13,416 10.1 132,302 Mara 97,737 90.4 18,550 17.2 3,877 3.6 1,558 1.4 17,044 15.8 8,238 7.6 108,121 Manyara 119,774 96.0 19,576 15.7 4,543 3.6 4,779 3.8 10,474 8.4 19,100 15.3 124,730 Mainland 2,168,128 90.8 288,858 12.1 88,709 3.7 76,593 3.2 288,211 12.1 296,759 12.4 2,388,056 North Unguja 3,398 61.5 474 8.6 413 7.5 773 14.0 1,423 25.7 1,675 30.3 5,526 South Unguja 2,894 57.9 1,024 20.5 339 6.8 1,161 23.3 645 12.9 1,271 25.5 4,994 Urban West 2,041 39.2 1,444 27.7 314 6.0 1,036 19.9 1,413 27.1 1,444 27.7 5,212 North Pemba 2,834 72.4 417 10.7 0 0.0 204 5.2 337 8.6 504 12.9 3,912 South Pemba 2,620 71.0 333 9.0 0 0.0 89 2.4 677 18.3 339 9.2 3,692 Zanzibar 13,786 59.1 3,692 15.8 1,066 4.6 3,264 14.0 4,494 19.3 5,234 22.4 23,336 Total 2,181,914 90.5 292,550 12.1 89,775 3.7 79,857 3.3 292,705 12.1 301,993 12.5 2,411,391 Table 2.14 Number of Households receiving Livestock advice (overall) By Source of Extension and Region during the 2007/08 agriculture year Region Source of Livestock Extension Number of Household receiving Extension Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 49 There was a slight variation across regions except for Arusha (24.9%), Mara (17.2%), Manyara (15.7%) and Tabora (15.2%) where NGOs and Development Project Extension Services were more prevalent apart from government. and in Tabora (23.4%), Dodoma (22.6%) and Kilimanjaro (21.3%) where Radios/TVs/Newspapers Extension Services were more significant than in other regions. Involvement of large scale Farmers in providing extension services is extremely low in other regions. However, Tabora (13.4%) had more Extension Services provided by Large Scale Farms to smallholders than in other regions (Table 2.12). 2.5.3 Types of extension messages Disease control was the most extension advice provided followed by housing and proper feeding (chart 2.44). There was little variation in the provision of other types of extension messages (Chart 2.43). Households in Mbeya Shinyanga, Iringa and Kilimanjaro received more extension advice on disease than in the remaining regions. Pwani, Dar es Salaam, Lindi and Mtwara had very little advice on disease management Chart 2.43 Number of Households Receiving Extension Advice on Disease Control by Region 0 50,000 100,000 150,000 200,000 250,000 Dodoma Arusha Kilimanjaro Tanga Morogoro Pwani Dar es Salaam Lindi Mtwara Ruvuma Iringa Mbeya Singida Tabora Sumbawanga Kigoma Shinyanga Kagera Mwanza Mara Manyara Region Number Chart 2.44 Number of Households Receiving Extension Service by type of Service 1,821,901 1,451,823 1,116,760 1,077,863 964,046 814,322 715,927 652,119 650,959 613,552 558,451 0 200000 400000 600000 800000 1000000 1200000 1400000 1600000 1800000 2000000 Disease control (dipping/spraying) Housing (Goat, Dairy, Poultry, Pigs) Feeds and Proper feeding Group formation and strengthening Herd/Flock size and selection Calf rearing Proper Milking and Milk Hygene Livestock Feeds processing Livestock fattening Pasture Establishment Use of improved Bulls/AI Number of households RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 50 2.6 Fish Farming Very few households practiced Fish farming in the Mainland (0.2 %) and Zanzibar (0.02%). This is almost the same trend as it was observed during the 2002/03 Agricultural Sample Census. The types of fish considered in the survey include; Tilapia, Milk Fish, Prawns, and Oyster. 2.6.1 Fish Production The number of fish stock farmed by type for the Mainland includes Tilapia (99.4%). Other species of fish farmed include Milk Fish, Prawns and Crabs whose total number when combined together amounted to 0.6 percent. Regions with highest number of households practising fish farming include Ruvuma (37%), Iringa (17%), Mbeya (11%), Tanga (8%), Kilimanjaro (7%) and Tabora (6%). Rukwa, Morogoro, Kigoma, Mtwara, Kagera and Arusha were moderate producers with (3.83%), (2.28%), (1.97%), (1.42%), (1.37%) and (1.13%) of the total households practising fish farming respectively. The remaining regions had insignificant level of fish production (Chart 2.45, Map 3.35). The trend is similar to the 2002/2003 Agricultural Census. 2.6.2. Source of fingerlings The main source of fingerlings was from the neighbours (51%) followed by NGOs/Development projects (20%), Government (9%), natural pond (8%), Own pond (5%), other (4%), and Private sector (3%) (Chart 2.46). Eight regions: Dodoma, Arusha, Dar es Salaam, Rukwa, Kigoma, Shinyanga, Mara and Manyara totally dependent on NGOs and Chart 2.45 Number of Household Practicing Fish Farming by Region 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 Ruvuma Iringa Mbeya Tanga Kilimanjaro Tabora Rukwa Morogoro Kigoma Mtwara Kagera Arusha Dodoma Mwanza Dar es Salaam Pwani Lindi Singida Shinyanga Mara Manyara Region Number Chart 2.46: Percent sources of fingerlings Natural pond, 901, 8% Other, 434, 4% Own pond, 576, 5% Private trade, 349, 3% Government institution, 1,072, 9% NGO/Project, 2,455, 20% Neighbour, 6,200, 51% RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 51 Government institutions as a source of fingerlings. The two major fish farming regions, Ruvuma and Mbeya rely mainly on their neighbours for their fingerlings. 2.6.3 Frequencies of stocking Most of the fish farmers (68%) stock their ponds once per year. Those who stock twice per year are 29.8 percent while two percent stock three times per year and 0.1 percent more than three times per year (Chart 2.47). The number of those who stocked fish once per year has increased from 65% in 2002/2003 agricultural year to 68% according to the 2007/08 Agricultural Sample Census, while the number of those who stocked more than three times has decreased from 4.5% in 2003 to 0.1% in 2007/08 agricultural year. Ruvuma had the highest number of households (2,743) stocking once per year and 1,482 stocking twice per year, followed by Iringa, 1,053 households stocking once per year and 689 households stocking twice, while Mbeya had 1,010 households stocking once a year and 159 households stocking twice a year. Chart 2.47 Frequencies of stocking 68.0 29.8 2.0 0.1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 1 2 3 8 Frequency Percent RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 52 2.6.4 Outlets for Selling Fish The quantity of fish produced in Tanzania was 1,154 tonnes out of which 1,122 tonnes (97%) were sold. This indicates that fish farming can be a good source of cash income and livelihood for the rural agricultural households. Most fish farmers (49%) did not sell fish and the fish produced in these households were used for home consumption. For those households that sold fish, most of the fish was sold to the neighbours and this was followed by local markets (8%), Secondary markets (6%) and traders at the farm (5%). The remaining 5 percent was sold to other selling locations (Chart 2.48). 2.7 Bee Keeping Bee keeping is practised both in Tanzania Mainland and in Tanzania Zanzibar. Two types of beehives are used: the improved type and the local type which is mostly used by the bee keepers. About 75% of the bee keeping households were engaged in sting bee and 25% were engaged in stingless bee keeping. (Chart 2.49). 2.7.1 Honey Production The total number of households involved in honey production was 129,314, which represents 2% of the total number of households involved in agricultural production. Out of the total number of households involved in honey production, 99% were in Tanzania Mainland Chart 2.48 Outllets for Sell of Fish 0 10 20 30 40 50 60 Did not sell Neighbour Local market Secondary market trade at farm Other Outlets Numbee of Households Chart 2.49 Percent of Households by Type of Bee Kept Sting Bee, 75% Stingless Bee, 25% Chart 2.50: Quantity of Honey Harvested and Average Production per Housheold - 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 4,500,000 Tabora Mbeya Rukwa Dodoma Shinyanga Singida Kilimanjaro Arusha Manyara Iringa Tanga Kigoma Kagera Morogoro Mwanza Mtwara Pwani Lindi Ruvuma Mara Dar es Salaam Region Production (lt) - 50 100 150 200 250 300 350 400 450 Average Production per Household Honey Harvested (lts) Average Production Per Household RESULTS _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 53 and 1 % was in Tanzania Zanzibar. The leading regions in honey production include Tabora which produced 3,861,806 litres (21.3%), with an average of 340 litres per household, followed by Mbeya which produced 3,395,109 litres (18.7%), with an average of 421 litres per household and Rukwa which produced 2,311,370 litres (12.7%), with an average of 309 litres per household, Dodoma which produced 1,509,673 litres (8.3%), with an average of 72 litres per household, Shinyanga which produced 1,379,826 litres (7.6%), with an average of 416 litres per household. Singida which produced 1,201,659 litres (6.6%) with an average of 85 litres per household, and Kilimanjaro which produced 1,024,937 litres (5.6%), with an average of 124 litres per household (Chart 2.50). The regions with least production in honey include Mara, Ruvuma, Lindi and Pwani which together produced a total of 106,070 litres. 2.7.2 Prices of Honey The prices of honey from sting and stingless bee varied widely within and between regions. In Kilimanjaro, honey from stingless bee was sold at 1.7 times higher than from sting bees. Higher prices of stingless bee honey were also observed in Manyara and Mara region. In Morogoro, Ruvuma, Mtwara, Iringa and Shinyanga the prices of honey from stingless bee were lower than those from sting bees. In the remaining regions, the prices were almost equal. As would have been expected, the regions with lowest honey production had higher prices of honey per litre especially from stingless bee. Pwani sold honey from sting bees at Tsh. 2,215 per litre and Tsh.1, 956 from stingless bee, while Mtwara sold at Tsh. 2,142 per litre from sting bee as opposed to 675 per litre from stingless bee. In Kilimanjaro, honey from stingless bee was sold at Tsh. 3,673 per litre while the price from sting bees was Tsh. 2,185 per litre, and Arusha sold at 1,932 per litre from sting bees as opposed to 1,670 per litre from stingless bee (Chart 2.51) Chart 2.51: Prices of Honey by Type of Bees and Region 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 Pwani Kilimanjaro Mtwara Arusha Morogoro Lindi Tanga Ruvuma Shinyanga Iringa Kagera Mwanza Manyara Singida Mbeya Tabora Dodoma Kigoma Rukwa Mara Region Price per lt(Tshs) Sting Bee (Price per Litre) Stingless Bee (Price per Litre) CONCLUSION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 54 3. CONCLUSION The 2007/08 Agricultural Sample Census collected large amounts of data on crop and livestock production and productivity, input use, agro-processing and storage, farmers’ access to services, access to social infrastructure, rural demographics, poverty and livelihood. The analysis on livestock sector contained in this report focuses on livestock numbers by specie, regional distribution of livestock, productivity, livestock diseases, access to services and contribution to crop production. Data for the 2007/08 Census is compared with the previous National Censuses data so as to identify any structural changes between the census periods. The main livestock species kept by smallholder farmers include cattle, goats, sheep, pigs and chicken. In 2007/08 Agricultural Census, there were about 2.3 million households which kept livestock. In the surveyed households, cattle were the most dominant specie followed by goats, sheep and pigs. The respective numbers and percentages were 21,280,875(48%) for cattle,, 15,154,121(34%) for goats, 5,715,549(14%) for sheep and 1,584,411 (3%) for pigs. Most of the livestock (99%) were kept by the smallholder sector. The contribution of large scale farms being less than 1%. The number of cattle in the Mainland was 21,125,251 while in Zanzibar it was 155,624. Of the 1,698,580 cattle keeping households, 72 percent kept between 1 and 10 heads of cattle. The average number of cattle, goats and sheep per household were 13, 9 and 9 respectively; while for chicken the average was 12 chicken. The contribution of Large Scale Farms to the total livestock number was rather small. Most of the livestock were raised in the Northern regions mainly Shinyanga and Arusha with a total of 4.2 million and 2.5 million livestock units respectively. The two regions were followed by Tabora, Mwanza, Manyara, Mara and Singida with about 2.0 million units each. The cattle population is mainly dominated by the indigenous type (96.2%), while the improved beef and dairy breeds contributed 0.9 percent and 2.9 percent respectively in the Mainland. When compared to the 2002/2003 Agricultural Census, the population of cattle has increased from 16,999,793 to 21,280,875 in 2007/08, representing an increase of about 20% giving an average annual growth rate of about 4 percent over the five year period. On average, 12 heads of cattle were kept per household. The improved cattle trend shows that, between 1995 and 2003, the growth rate for dairy and beef cattle were 5 percent and 4.1 percent respectively. Between 1999 and 2003, there was a general drop in the rate of growth of both dairy and beef cattle. In the period between 2003 and 2008, both types of cattle showed a positive trend with that of beef being more than twice that of the dairy cattle. Milk production from cows has increased from 4.3 million litres in 2007 /2008 to 4.6 million litres in 2002/2008. Moreover, milk production dropped from an average of 6 and 4 litres per household during the wet and dry seasons in 2002 /2003 agricultural year to 3 and 2 litters per household in the 2007/2008 agricultural year in the same seasons. This drop is likely to have resulted from periodic droughts. The general trend is an increase in goat population over the past 13 years, particularly in the Mainland. The number of goats has increased from 10,628,401 to 15,085,150 a 30% increase during the period 1995 to 2008 representing an equivalent of about 2.5 percent growth rate per annum between 1995 to 2008 and a growth rate of 5.11% between 2003 and 2008. The average number of goats per household in the 2007/08 agricultural census was 9 goats, an increase of approximately one goat when compared to 2002/03 agricultural census. CONCLUSION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 55 Over the same period of 13 years (1995-2008), there has been a steady increase in the number of sheep from about 3.4 million to 5.7 million heads. This represents an average annual increase of 3.8 percent. In the period (1995-1999), the growth rate was almost zero, however, in the following years, the growth rate has improved to 7.7% during the period between 2003 and 2008. This could be attributed to an increase in the number of households raising sheep from 496,094 households in 2002 /2003 to 638,679 householdsin 2007 /2008 agricultural year. Chicken were the dominant specie in most of the households. In the Mainland, there were about 42.6 million chicken of which 96% were local, 2.7% were layers and 1.3% were broilers. The number of households keeping layers was 28711 and that of broilers was 13,986. In contrast, 78,428 households in Zanzibar kept 932,332 local chicken, of which, 11.7% being layers and 1.5% broilers. The annual growth rate of the chicken population was 5.1% between the period 2002/2003 to 2007/2008. This increase is largely due to the increase in the number of local chicken. Despite the general trend in the improvement of livestock numbers across the species, diseases especially the Tick Borne Disease (TBD) have remained problematic. The disease was reported by 37.4% of the livestock keeping households. Shinyanga, Mwanza and Mbeya were the leading regions on the reported TBD incidences. Control methods were spraying (29%), dipping (10%) and smearing (9%). However, there were still a significant number of households (61%) that did not use any of the control methods. Foot and Mouth Disease (FMD) was also among the reported diseases and has infected 252,772 livestock keeping households. Kilimanjaro, Arusha, Kagera and Mwanza were the regions which had higher incidence of FMD. Helminths and Trypanosomosis were other common problems. For chicken, Newcastle Disease (NCD) was the most devastating disease and about 2.6 million households reported cases of NCD. Higher incidences were found in Mbeya, Shinyanga, Mwanza and Tanga regions. However, only 22 percent of the households regularly vaccinated their chicks against the disease, while 26 percent used local herbs and 52 percent did not take any curative measures. For Other Livestock, stingless bee accounted for 76 percent of the farmed bee population and honey was produced by 129,314 households representing two percent of the household involved in crop production. The leading regions in honey production include Tabora which produced 3,861,806 litres (21.3%), with an average of 340 litres per household, followed by Mbeya which produced 3,395,109 litres (18.7%), with an average of 421 litres per household and Rukwa which produced 2,311,370 litres (12.7%), with an average of 309 litres per household. The availability of livestock services and infrastructure varied between the type of services and the region. Infrastructures were generally more accessible in urban and peri-urban areas. Regions such as Shinyanga, Mwanza which had large population of livestock, had less access to livestock services than regions such as Dar es Salaam with relatively fewer livestock. Access to livestock services is more readily in regions like Kilimanjaro and Mbeya where farming is more intensive and the infrastructures are more developed. Noteworthy, the main source of extension service is still under the government (67.6%). Other sources include NGOs and Development Projects (9%) and Cooperatives (2.7%). Regional Profiles The following profiles summarize the status of livestock production in major Livestock Rearing Regions. CONCLUSION _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 56 Shinyanga Region Shinyanga region has the largest population of livestock. It has the largest number of cattle and goats and second highest head of sheep with virtually no pigs. However, it ranked fourth from the bottom in terms of amount of cow’s milk production per day probably due to the large number of unimproved indigenous cattle. The region had also the highest number of chicken population most of which were of local or indigenous type but ranked fourth in terms of number of layers kept. In terms of number of eggs produced, the region did not rank high and this indicates that most of the eggs were produced by indigenous chicken. Considering the large number of cattle, it is encouraging to note that the incidences of diseases such as Tick Borne Diseases and Foot and Mouth Disease were lower compared to the situation of Arusha, Dodoma, and Kilimanjaro regions . Incidences of Newcastle disease were high (60%) compared to other regions. Arusha Region Arusha region is the second region with highest livestock units in Tanzania. However, in terms of cattle population, it ranked fourth after Shinyanga, Tabora and Mwanza regions, but was the second in the number of goats and first in terms of number of sheep. Being predominantly inhabited by pastoral communities, the number of local chicken was not much high compared to the regions practicing agro-pastoral systems such as Shinyanga and Mwanza. Likewise, the number of layers was not much and the region occupied third position after Mara and Tanga regions. Consequently, the total number of eggs produced per annum was also low. Arusha was second best on the amount of milk produced per day by cows after Shinyanga. Comparatively, Arusha experienced higher incidences of FMD and TBD and ranked second after Dodoma region. Manyara Region Manyara region was the third on the number of livestock units kept but was sixth in in the number of cattle and was third in the number of goats and sheep after Shinyanga and Arusha regions. Similar to Arusha, Manyara region was predominantly inhabited by pastoralist. Milk production was the lowest due to the keeping of unimproved zebu cattle. Tabora Region Tabora region ranked fourth in the number of livestock units and second in the cattle population after Shinyanga. It was fourth in the number of goats and chicken and ranked fifth in the number of sheep. Incidences if TBD were comparably higher to Shinyanga, Mwanza, and Dodoma . However, there were fewer cases of Tsetse infections and FMD. Only 6% of the households regularly dewormed their animals as compared to 10% in Shinyanga and 8% in Mbeya. Tabora is also the leading region in terms of honey production and it produced about 4,012,730 litres of honey in 2007/08 agricultural year. The average production of honey was 341 litres per household. . Mwanza Region Mwanza region ranked fifth in terms of livestock units but, was the third in the number of cattle and fifth in the number of goats. The region has modest number of sheep and was the nineth in position . Milk production per cow per day was also lowest due to dominancy of unimproved cattle types. It also ranked low in terms of number of layers and there were virtually no pigs. Like Shinyanga, there were low incidences of TBD and FMD and Tsetse related diseases. However, incidence of Newcastle disease was high (about 60%) and comparable to most of the regions. APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 57 4. APPENDICES Appendix I: Livestock and Poultry Tabulation List Appendix II: Livestock and Poultry Appendix III: Questionnaires APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 58 Appendix I: Livestock and Poultry Tabulation List LIVESTOCK AND POULTRY TABULATION LIST (NATIONAL) CATTLE PRODUCTION Table 9.1.1 Cattle Production: Number of Households Rearing Cattle by Region during the 2007/08 Agriculture Year…………………………………………………... 63 Table 9.1.2 Cattle Production Number of Cattle by Type of Cattle and Region as of 1st October 2008……………………………………………………………………. 64 Table 9.1.3 Cattle Production Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size during 2007/08 Agricultural Year – National………………………………………………………………………… 65 Table 9.1.4 Cattle Production Number of Households Rearing Cattle, Head of Cattle and average Head per Household by Herd Size during 2007/08 Agricultural Year – Tanzania Mainland…………………………………………………………….. 65 Table 9.1.5 Cattle Production Number of Households Rearing Cattle, Head of cattle and Average Head per Household by Herd Size during 2007.08 Agricultural Year – Tanzania Zanzibar…………………………………………………………….. 65 Table 9.1.6 Cattle Production Number of Cattle by Type and Category of Cattle during 2007/08 Agricultural Year – National………………………………………… 66 Table 9.1.7 Cattle Production Number of Cattle by Type and Category of during 2007/08 Agricultural Year Tanzania Mainland ………………………………………….. 66 Table 9.1.8 Cattle Production Number of Cattle by type and Category of Cattle during 2007/08 Agricultural Year Tanzania Zanzibar…………………………………. 66 Table 9.1.9 Cattle Production: Number of Indigenous Cattle by Category of Cattle and Region during 2007/08 Agricultural Year………………………………………. 67 Table 9.1.10 Cattle Production Number of Improved Beef Cattle by Category of Cattle and Region during 2007/08 Agricultural Year……………………………………… 68 Table 9.1.11 Cattle Production Number of Improved Dairy Cattle by Category of Cattle and Region during 2007/08 Agricultural Year……………………………………… 69 Tale 9.1.12 Cattle Production Total Number of Household Rearing cattle and method of cattle identification Region during 2007/08 Agricultural Year…………………. 70 MILK PRODUCTION Table 9.2.1 Cattle Production: Number of Milked Cows by category of cattle, season and Region for the agriculture Year 2007/08……………………………………….. 71 Table 9.2.2 Cattle Production: Average Milk Production per cow per day by Category of Cow, Season and Region during 2007/08 Agricultural Year…………………… 72 Table 9.2.3 Cattle Production: Number of day for cows on milked Cows by category of cattle, season and Region for the agriculture Year 2007/08…………………….. 73 Table 9.2.4 Cattle Production: Average Cattle Milk price (Tshs/litre) per season by category and Region during the 2007/08 Agricultural Year……………………. 74 Table 9.2.5 Cattle Production: Average Cattle Milk price (Tshs/litre) per season by category and Region during the 2007/08 Agricultural Year……………………. 75 Table 9.2.6 Cattle Production: Quantity Milk Produced (litres) by category of cattle, season and Region during the 2007/08 Agricultural Year……………………………… 76 APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 59 GOAT PRODUCTION Table 9.3.1 Goat Production: Number of Households Rearing Goats by Region during the 2007/08 Agricultural Year……………………………………………………… 77 Table 9.3.2 Goat Production: Number of Goats by Type and Region as of 1st October 2008……………………………………………………………………………... 78 Table 9.3.3 Goat Production: Number of Households Rearing Goats, Head of Goat and Average Head per Household by Herd Size as of 1st October 2008 – National… 79 Table 9.3.4 Goat Production: Number of Households Rearing Goats, Head of Goat and Average per Household by Herd Size as of 1st October 2008 – Zanzibar………. 79 Table 9.3.5 Goat Production: Number of Households Rearing Goats, Head of Goat and Average Head per Household by Herd Size as of 1st October 2008 – Mainland…………………………………………………………………………..…. 79 Table 9.3.6 Goat Production: Number of Goats by Category and Type of Goat as of 1st October 2008 – Mainland…………………………………………………… 80 Table 9.3.7 Goat Production: Number of Goats by Category and Type as of 1st October 2008 – Zanzibar………………………………………………………………………..……… 80 Table 9.3.8 Goat Production: Number of Goats by Category and Type of Goat as of 1st October 2008 – National………………………………………………………………..……… 80 Table 9.3.9 Goat Production: Total Number of Indigenous Goats by Category and Region as of 1st October 2008………………………………………………………………………….. 81 Table 9.3.10 Goat Production: Number of Improved Goats for Meat by Category and Region as of 1st October 2008………………………………………………………………………… 82 Table 9.3.11 Goat Production: Number of Improved Dairy Goats by Category and Region as of 1st October 2008…………………………………………………………………………… 83 Table 9.3.12 Goat Production: Milk Production from Goat by Season and Region During the 2007/09 Agricultural Year…………………………………………………..…………. 84 SHEEP PRODUCTION Table 9.4.1 Sheep Production: Number of Households rearing Sheep by Region during the 2007/08 Agricultural Year……………………………………………………… 85 Table 9.4.2 Sheep Production: Number of Sheep by Type and Region as of 1st October 2008…………………………………………………………………………………………. 86 Table 9.4.3 Sheep Production: Number of Indigenous Sheep by Category and Region as of 1st October 2008…………………………………………………………………………………………. 87 Table 9.4.4 Sheep Production: Number of Households Rearing Seep, Head of Sheep and Average Head per Household by Herd Size as of 1st October 2008 – Mainland…………………………… 88 Table 9.4.5 Sheep Production: Number of Households Rearing Sheep, Head of Sheep and Average Head per Household by Herd Size as of 1st October 2008 – Zanzibar…………………………………………………………………………. 88 Table 9.4.6 Sheep Production: Number of Households Rearing Sheep, Head of Sheep and Average Head per Household by Herd Size as of 1st October 2008 – National…………………………………………………………………..……. 88 Table 9.4.7 Sheep Production: Number of Sheep by Breed Type during the 2007/08 Agricultural year Mainland…………………………………………………….. 89 Table 9.4.8 Sheep Production: Number of Sheep by Breed Type During the 2007/08 Agricultural Year Zanzibar……………………………………………………… 89 Table 9.4.9 Sheep Production: Number of Sheep by Breed Type during the 2007/08 Agricultural year National………………………………………………………. 89 APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 60 PIG PRODUCTION Table 9.5.1 Pig Production: Number of Households Rearing Pigs by Region during the 2007/08 Agricultural Year………………………………………………………. 90 Table 9.5.2 Pig Production: Number of Households Rearing Pigs, Head of Pigs and Average Head per Household by Herd Size as of 1st October 2008 – Mainland…………………………………………………………………………. 91 Table 9.5.3 Pig Production: Number of Households Rearing Pigs, Head of Pigs and average Head per Household by Herd Size as of 1st October 2008 – Zanzibar………….. 91 Table 9.5.4 Pig Production: Number of Households Rearing Pigs, Head of Pigs and Average Head per Household by Herd Size as of 1st October 2008 – National ... 91 Table 9.5.5 Pig Production: Number of Pigs by Type of Pigs and Region as of 1st October 2008…………………………………………………………………………….. 92 Table 9.5.6 Pig Production: Number of Pigs per Household by Region as of 1st October 2008…………………………………………………………………………..... 93 CHICKEN PRODUCTION AND OTHER LIVESTOCK Table 9.6.1 Chicken Production: Number of Chicken by Type and region as of October 2008…………………………………………………………………………….. 94 Table 9.6.2 Number of Household Keeping Chickens and Average number of Chicken per Household by flock Size as of 1st October 2008 – Mainland…………………… 95 Table 9.6.3 Number of Household keeping Chickens and Average number of Chicken per Household by Flock Size as of 1st October 2008 – Zanzibar………………….. 95 Table 9.6.4 Number of Household Keeping Chickens and Average number of Chicken per Household by Flock Size as of 1st October 2008 – National……………………. 95 Table 9.6.5 Number of Other livestock by Type of Livestock and Region as 1st October 2008 – Mainland……………………………………………………………….. 96 Table 9.6.6 Number of Livestock by Type as of as of 1st October 2008……………………. 96 Table 9.6.7 Total Number of Egg by type of chicken and Region during 2007/08 Agricultural Year……………………………………………………………….. 97 LIVESTOCK PESTS & PARASITE CONTROL Table 9.7.1 Number of Livestock rearing households deworming Livestock by Region during 2007/08 Agriculture Year……………………………………………….. 98 Table 9.7.2 Number of Livestock Rearing households that dewormed Livestock by type of livestock and region during 2007/08 Agriculture Year………………………… 99 Table 9.7.3 Number of Livestock Rearing Households Normally Encountering Tick Problems by Region during 2007/08 agricultural year…………………………. 100 Table 9.7.4 Number of Livestock Rearing Households by method of Tick Control and Region during 2007/08 Agriculture Year………………………………………. 101 Table 9.7.5 Number of Livestock Rearing Households normally Encountering Tsetse Flied Problem by Region during 2007/08 Agricultural Year…………………………. 102 Table 9.7.6 Number of Livestock Rearing Households by Method of Tsetse Flies Control and Region during 2007/08 Agriculture Year…………………………………. 103 Table 9.7.7 Number of Livestock Rearing Households normally Encountering Newcastle Problems by Region during 2007/08 Agriculture Year 104 APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 61 Table 9.7.8 Number of Livestock Rearing Households by method of Newcastle Control and Region during 2007/08 Agriculture Year………………………………….. 105 Table 9.7.9 Number of Livestock rearing Households normally Encountering Fowl Typhoid Disease Problems by Region during 2007/08 Agriculture Year…….. 106 Table 9.7.10 Number of Livestock rearing Households by method of Fowl Typhoid Control and Region during 2007/08 Agriculture Year…………………………………... 107 Table 9.7.11 Number of Livestock Rearing Households normally Encountering Foot and Lympy skin problems by Region during 2007/08 Agriculture Year……………. 108 Table 9.7.12 Pest and parasites: Number of Livestock Rearing Households normally Encountering Disease Problems by Region during 2007/08 109 LIVESTOCK EXTENSION Table 9.8.1 Number of Households receiving extension advice by region during the 2007/08 agriculture year………………………………………………………… 110 Table 9.8.2 Number of Households receiving advice (overall) by Source of Extension and Region………………………………………………………………………….. 111 Table 9.8.3 Number of Agriculture households receiving advice of feeds and proper feeding by source and region during 2007/08 agriculture year………………… 112 Table 9.8.4 Number of agriculture households receiving advice on project livestock using by Source and Region during the 2007/08 agriculture Year……………………. 113 Table 9.8.5 Number of Households receiving advice on disease control (dipping spraying by source and region…………………………………………………………… 114 Table 9.8.6 Number of Households Receiving extension advice on livestock fattening by Region during the 2007/08 agriculture year…………………………………….. 115 Table 9.8.7 Number of Households receiving advice on disease control (dipping spraying by source and region…………………………………………………………… 116 Table 9.8.8 Number of Households Receiving advice on herd/flock size & selection by source and region……………………………………………………………….. 117 Table 9.8.9 Number of Households receiving advice on pasture establishment by source and Region……………………………………………………………………… 118 Table 9.8,10 Number of Households Receiving Advice on Group Formation and strengthening by Source and Region……………………………………………. 119 Table 9.8.11 Number of Agriculture Households Receiving Advice on Calf Rearing by Source and Region during the 2007/08 Agriculture Year……………………. 120 Table 9.8.12 Number of Agriculture Households Receiving Advice on Improved Bulls by Source and Region During the 2002/03 Agriculture Year……………………… 121 Table 9.8.13 Number of Agriculture Households Receiving Advice on Food processing by source and Region during the 2002/03 Agriculture Year………………………. 122 FISH FARMING Table 9.9.1 Number of Agriculture households Practicing fish farming by Region during the 2007/08 Agriculture Year…………………………………………………… 123 Table 9.9.2 Number of Agriculture households by System of Fish Farming by Region during the 22007/08…………………………………………………………… 124 Table 9.9.3 Number of Agriculture households by source of fingerling and Region during the 2007/08 Agricultural Year…………………………………………………. 125 APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 62 Table 9.9.4 Number of Agriculture households by Location of selling Fish and Region during the 2007/08 Agriculture Year……………………………………………. 126 Table 9.9.5 Number of Fish Harvested their weight and Quantity sold by Region during the 2007/08 Agriculture Year……………………………………………………….. 127 Table 9.9.6 Mean size of Fish Pond and Average number of fingering stocked by Type and Region during the 2007/08 Agriculture Year…………………………………… 128 Table 9.9.7 Number of Agriculture Household frequency of stocking of fingerings Ponds and Region 2007/08 Agriculture Year.………………………………………. 129 Table 9.9.8 Number of Agriculture Household by level of care of fish ponds and Region, 2007/08 Agriculture year……………………………………………………… 129 BEE KEEPING Table 9.10.1 Beekeeping: Number of Agricultural Households involved in Honey Production/Collection and Region, 2007/08 Agricultural Year……………….. 130 Table 9.10.2 Beekeeping: Number of Agriculture Households Harvesting Honey by Type of Bee and Region during the 2007/08 Agriculture Year…………………………. 131 Table 9.10.3 Number of Agriculture Household by Type of bee harvested and type of bee and district 2007/08 Agricultural year…………………………………………... 132 Table 9.10.4 BEE KEEPING: Quantity of Honey Harvested and Sold by Size of Bees and Region during the 2007/08 Agriculture Year ………………………………… 133 Table 9.10.5 BEE KEEPING: Average price of Honey (Tshs/litre) by Size of Bees and Region during the 2007/08 Agriculture Year ………………………………… 134 Table 9.10.6 BEE KEEPING: Number of Agriculture Households by Location of Selling Honey and Region during the 2007/08 Agriculture Year………………………. 135 APPENDICES _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 63 APPENDIX II: LIVESTOCK AND POULTRY TABLES Number % Number % Dodoma 76,145 21 282,824 79 358,969 102,865 Arusha 148,049 72 57,617 28 205,547 167,562 Kilimanjaro 145,628 60 97,080 40 242,708 185,997 Tanga 74,670 23 256,109 77 330,779 116,839 Morogoro 17,808 6 280,613 94 298,421 45,235 Pwani 10,777 6 163,746 94 174,523 28,058 Dar es Salaam 6,468 18 28,692 82 35,160 13,374 Lindi 3,015 2 163,883 98 166,898 18,177 Mtwara 3,291 1 246,081 99 249,373 35,138 Ruvuma 23,941 11 186,340 89 210,281 62,685 Iringa 57,600 19 249,029 81 306,629 88,519 Mbeya 168,859 37 285,965 63 454,824 207,028 Singida 98,881 46 118,111 54 216,992 116,524 Tabora 96,708 34 191,739 66 288,447 124,747 Rukwa 68,944 30 157,305 70 226,250 89,140 Kigoma 20,284 9 204,886 91 225,171 67,755 Shinyanga 217,587 45 267,625 55 485,212 261,150 Kagera 57,565 14 348,345 86 405,910 116,672 Mwanza 146,149 37 252,843 63 398,993 177,086 Mara 96,540 43 130,191 57 226,731 121,803 Manyara 120,249 61 78,263 39 198,513 137,902 Mainland 1,659,160 29 4,047,289 71 5,706,329 2,284,257 North Unguja 4,977 16 25,377 84 30,354 6,579 South Unguja 6,129 30 14,130 70 20,259 7,192 Urban West 4,616 25 14,036 75 18,651 6,060 North Pemba 13,242 40 19,653 60 32,895 14,284 South Pemba 10,457 35 19,578 65 30,034 11,570 Zanzibar 39,420 30 92,773 70 132,193 45,684 Total 1,698,580 29 4,140,062 71 5,838,523 2,329,942 9.1.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle by Region during 2007/08 Agriculture Year Regions Households not rearing cattle Households rearing cattle Total Agriculture households Total Number of Households Rearing Livestock Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 64 Regions Number of households Number of Cattle Percentage Number of households Number of Cattle % Number of households Number of Cattle % Number of households rearing Cattle Number of Cattle % Dodoma 75,878 1,166,715 98.4 876 15,313 1.3 1,617 3,473 0.3 76,145 1,185,501 100 Arusha 124,977 1,716,514 94.6 4,633 18,486 1.0 31,841 78,637 4.3 148,049 1,813,637 100 Kilimanjaro 73,788 321,171 65.0 6,598 10,980 2.2 76,306 161,984 32.8 145,628 494,135 100 Tanga 62,306 688,114 94.0 1,222 2,377 0.3 16,728 41,639 5.7 74,670 732,130 100 Morogoro 15,818 628,475 98.2 417 1,874 0.3 2,297 9,414 1.5 17,808 639,764 100 Pwani 7,162 225,610 88.4 396 1,141 0.4 4,711 28,507 11.2 10,777 255,258 100 Dar es Salaam 1,091 6,108 18.9 929 1,919 5.9 5,750 24,372 75.2 6,468 32,398 100 Lindi 1,854 26,450 85.9 45 135 0.4 1,289 4,199 13.6 3,015 30,784 100 Mtwara 3,172 17,415 96.1 153 305 1.7 275 394 2.2 3,291 18,115 100 Ruvuma 20,286 61,768 82.0 672 1,420 1.9 4,798 12,177 16.2 23,941 75,366 100 Iringa 54,325 459,275 96.7 938 1,498 0.3 5,279 14,258 3.0 57,600 475,031 100 Mbeya 135,544 787,912 90.5 3,598 9,582 1.1 37,660 72,724 8.4 168,859 870,218 100 Singida 98,701 1,584,313 99.7 396 1,115 0.1 657 3,409 0.2 98,881 1,588,837 100 Tabora 96,511 2,123,645 99.6 322 7,075 0.3 1,024 2,370 0.1 96,708 2,133,090 100 Rukwa 67,731 799,700 99.4 337 562 0.1 2,027 4,149 0.5 68,944 804,411 100 Kigoma 19,552 154,000 97.7 359 505 0.3 848 3,077 2.0 20,284 157,581 100 Shinyanga 216,875 3,635,260 99.6 1,538 10,573 0.3 2,552 5,419 0.1 217,587 3,651,251 100 Kagera 46,486 813,212 97.1 129 129 0.0 13,275 23,863 2.9 57,565 837,204 100 Mwanza 145,461 1,970,901 99.7 917 2,277 0.1 1,332 3,794 0.2 146,149 1,976,971 100 Mara 96,260 1,682,569 99.5 677 5,671 0.3 1,193 2,877 0.2 96,540 1,691,118 100 Manyara 118,582 1,648,488 99.2 844 2,115 0.1 4,540 11,848 0.7 120,249 1,662,452 100 Mainland 1,482,359 20,517,616 97.1 25,995 95,053 0.4 215,997 512,583 2.4 1,659,160 21,125,251 100 North Unguja 4,945 22,920 96.7 0 . . 196 790 3.3 4,977 23,710 100 South Unguja 5,916 30,418 93.7 0 . . 746 2,053 6.3 6,129 32,471 100 Urban West 4,490 19,342 91.5 0 . . 659 1,790 8.5 4,616 21,132 100 North Pemba 13,011 44,120 97.3 0 . . 545 1,233 2.7 13,242 45,353 100 South Pemba 10,333 31,943 96.9 0 . . 275 1,015 3.1 10,457 32,958 100 Zanzibar 38,696 148,744 95.6 0 0 0.0 2,422 6,880 4.4 39,420 155,624 100 Total 1,521,055 20,666,360 97.1 25,995 95,053 0.4 218,418 519,463 2.4 1,698,580 21,280,875 100 9.1.2 CATTLE PRODUCTION: Number of Cattle by Type and Region as of 1st October 2008 Total Improved Dairy Improved Beef Indigenous Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 65 9.1.3 CATTLE PRODUCTION: Number of Households rearing cattle, Head of Cattle and Average Head per Household by Herd size During the 2007/08 Agricultural Year - National Herd size Cattle Rearing Households % Herd of Cattle Average Per Houseold 1 - 5 861,325 50.7 2,323,902 2.7 6 - 10 350,820 20.7 2,710,081 7.7 11 - 15 169,279 10.0 2,183,557 12.9 16 - 20 96,990 5.7 1,748,543 18.0 21 - 30 89,107 5.2 2,243,759 25.2 31 - 40 41,117 2.4 1,453,761 35.4 41 - 50 24,707 1.5 1,137,085 46.0 51 - 60 17,199 1.0 958,748 55.7 61 -100 28,536 1.7 2,237,968 78.4 101 -150 9,439 0.6 1,191,886 126.3 151+ 10,060 0.6 3,091,585 307.3 Total 1,698,580 100.0 21,280,875 12.5 9.1.4 CATTLE PRODUCTION: Number of Households rearing cattle, Head of Cattle and Average Head per Household by Herd size During the 2007/08 Agricultural Year - TANZANIA MAINLAND Heard Size Cattle Rearing Households % Heard of Cattle Average Per Houseold 1 - 5 829,697 50 2,240,291 3 6 - 10 344,820 21 2,666,365 8 11 - 15 168,047 10 2,167,896 13 16 - 20 96,659 6 1,742,745 18 21 - 30 88,960 5 2,240,055 25 31 - 40 41,066 2 1,452,025 35 41 - 50 24,677 1 1,135,687 46 51 - 60 17,199 1 958,748 56 61 -100 28,536 2 2,237,968 78 101 -150 9,439 1 1,191,886 126 151+ 10,060 1 3,091,585 307 Total 1,659,160 100 21,125,251 13 9.1.5 CATTLE PRODUCTION: Number of Households rearing cattle, Herd of Cattle and Average Head per Household by Herd size During the 2007/08 Agricultural Year - TANZANIA ZANZIBAR Herd Size Cattle Rearing Households % Heard of Cattle Average Per Houseold 1 - 5 31,627 80 83,610 3 6 - 10 6,001 15 43,716 7 11 - 15 1,232 3 15,662 13 16 - 20 331 1 5,797 18 21 - 30 148 0 3,704 25 31 - 40 51 0 1,736 34 41 - 50 30 0 1,398 46 Total 39,420 100 155,624 4 Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 66 Cattle Types Indigeneous Improved Beef Improved Diary Total Cattle % Castrated Bulls (Oxen) 3,788,582 6,762 18,906 3,815,893 16 Uncastrated Bulls 2,359,760 17,107 36,741 2,415,253 16 Cows 6,949,192 16,583 240,528 7,207,948 24 Steers 470,912 6,723 15,977 493,612 3 Heifers 2,944,983 20,426 82,804 3,049,857 13 Male Calves 1,920,005 9,264 58,043 1,991,486 13 Female Calves 2,232,927 5,791 66,464 2,306,826 14 Total 20,666,360 82,656 519,463 21,280,875 100 Cattle Types Indigeneous Improved Beef Improved Diary Total Cattle % Castrated Bulls (Oxen) 3,784,675 6,762 18,754 3,811,836 17 Uncastrated Bulls 2,332,562 17,107 36,111 2,387,425 16 Cows 6,891,131 16,583 237,236 7,146,594 24 Steers 468,550 6,723 15,832 491,105 3 Heifers 2,920,011 20,426 81,904 3,023,984 13 Male Calves 1,905,094 9,264 57,206 1,975,739 13 Female Calves 2,215,592 5,791 65,541 2,288,568 14 Total 20,517,616 82,656 512,583 21,125,251 100 Cattle Types Indigeneous Improved Beef Improved Diary Total Cattle % Castrated Bulls (Oxen) 3,906 . 151 4,057 2 Uncastrated Bulls 27,197 . 630 27,828 20 Cows 58,061 . 3,292 61,354 32 Steers 2,362 . 145 2,507 2 Heifers 24,972 . 900 25,873 17 Male Calves 14,910 . 837 15,747 12 Female Calves 17,334 . 923 18,258 14 Total 148,744 . 6,880 155,624 100 9.1.8 CATTLE PRODUCTION: Total Number of Cattle by Type and Region, 2007/08 Agricultural Year TANZANIA ZANZIBAR 9.1.7 CATTLE PRODUCTION: Total Number of Cattle by Type and Region, 2007/08 Agricultural Year - TANZANIA MAINLAND 9.1.6 CATTLE PRODUCTION: Total Number of Cattle by Cattle Types and Category, 2007/08 Agricultural Year- National Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 67 Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Dodoma 219,068 19 148,583 13 403,894 35 37,570 3 145,191 12 95,099 8 117,310 10 1,166,715 100 Arusha 237,644 14 180,947 11 675,516 39 48,152 3 172,695 10 190,154 11 211,404 12 1,716,514 100 Kilimanjaro 19,718 6 36,509 11 119,573 37 12,836 4 50,349 16 38,631 12 43,555 14 321,171 100 Tanga 36,935 5 66,658 10 267,204 39 16,240 2 127,482 19 86,407 13 87,188 13 688,114 100 Morogoro 140,549 22 81,056 13 166,090 26 21,077 3 113,006 18 47,620 8 59,077 9 628,475 100 Pwani 16,844 7 19,462 9 92,682 41 8,756 4 37,820 17 24,772 11 25,274 11 225,610 100 Dar es Salaam 539 9 680 11 1,762 29 303 5 1,311 21 579 9 934 15 6,108 100 Lindi 1,589 6 1,965 7 9,947 38 811 3 5,242 20 2,780 11 4,116 16 26,450 100 Mtwara 1,019 6 2,702 16 8,983 52 458 3 1,505 9 305 2 2,442 14 17,415 100 Ruvuma 4,518 7 9,930 16 25,963 42 1,958 3 6,784 11 4,956 8 7,660 12 61,768 100 Iringa 113,547 25 53,616 12 154,311 34 7,869 2 41,703 9 37,740 8 50,488 11 459,275 100 Mbeya 167,284 21 97,926 12 269,541 34 10,729 1 95,644 12 60,383 8 86,405 11 787,912 100 Singida 294,662 19 178,205 11 597,208 38 53,194 3 128,893 8 172,413 11 159,740 10 1,584,313 100 Tabora 439,295 21 232,638 11 601,684 28 50,931 2 393,741 19 186,277 9 219,080 10 2,123,645 100 Rukwa 217,334 27 76,154 10 254,775 32 10,260 1 77,290 10 72,193 9 91,694 11 799,700 100 Kigoma 6,921 4 15,617 10 61,942 40 1,319 1 32,664 21 13,684 9 21,852 14 154,000 100 Shinyanga 947,849 26 388,966 11 1,006,672 28 85,576 2 565,170 16 303,826 8 337,201 9 3,635,260 100 Kagera 57,143 7 69,258 9 379,585 47 13,060 2 126,077 16 67,974 8 100,115 12 813,212 100 Mwanza 376,946 19 216,108 11 584,516 30 36,889 2 348,566 18 175,959 9 231,918 12 1,970,901 100 Mara 252,493 15 232,225 14 620,406 37 25,453 2 248,344 15 150,161 9 153,487 9 1,682,569 100 Manyara 232,777 14 223,360 14 588,876 36 25,109 2 200,534 12 173,180 11 204,653 12 1,648,488 100 Mainland 3,784,675 18 2,332,562 11 6,891,131 34 468,550 2 2,920,011 14 1,905,094 9 2,215,592 11 20,517,616 100 North Unguja 960 4 3,412 15 9,253 40 433 2 2,524 11 2,488 11 3,850 17 22,920 100 South Unguja 708 2 5,168 17 12,711 42 479 2 5,145 17 2,974 10 3,235 11 30,418 100 Urban West 502 3 4,333 22 7,096 37 251 1 2,795 14 2,010 10 2,355 12 19,342 100 North Pemba 654 1 8,198 19 16,720 38 431 1 8,307 19 4,733 11 5,077 12 44,120 100 South Pemba 1,083 3 6,086 19 12,281 38 768 2 6,203 19 2,706 8 2,818 9 31,943 100 Zanzibar 3,906 3 27,197 18 58,061 39 2,362 2 24,972 17 14,910 10 17,334 12 148,744 100 Total 3,788,582 18 2,359,760 11 6,949,192 34 470,912 2 2,944,983 14 1,920,005 9 2,232,927 11 20,666,360 100 9.1.9 CATTLE PRODUCTION: Total Number of indigenous Cattle by Category of cattle and region During the 2007/08 Agricultural Year Region Cattle Type Castrated Bulls (Oxen) Uncastrated Bulls Female Calves Total Male Calves Steers Cows Heifers Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 68 Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Dodoma 569 20 702 24 . 1,644 56 . . . 2,916 100 Arusha 1,914 10 2,102 11 3,841 21 3,731 20 3,209 17 2,279 12 1,410 8 18,486 100 Kilimanjaro 644 6 4,471 41 1,184 11 348 3 1,711 16 2,005 18 616 6 10,980 100 Tanga 167 7 553 23 476 20 206 9 616 26 136 6 223 9 2,377 100 Morogoro 625 33 . . . 1,250 67 . . 1,874 100 Pwani 108 10 167 15 140 12 . 181 16 365 32 181 16 1,141 100 Dar es Salaam 174 9 344 18 238 12 37 2 414 22 355 18 358 19 1,919 100 Lindi . 45 33 45 33 . . . 45 33 135 100 Mtwara . . 153 50 153 50 . . . 305 100 Ruvuma 132 9 266 19 30 2 81 6 . 355 25 556 39 1,420 100 Iringa 410 27 138 9 626 42 . 106 7 . 219 15 1,498 100 Mbeya 568 6 1,081 11 5,334 56 521 5 . 1,670 17 408 4 9,582 100 Singida 899 81 . 216 19 . . . . 1,115 100 Tabora . . . . 7,075 100 . . 7,075 100 Rukwa . . 450 80 . . . 112 20 562 100 Kigoma . . 292 58 . . . 212 42 505 100 Shinyanga 477 5 1,333 13 1,809 17 . 5,780 55 904 9 270 3 10,573 100 Kagera . 129 100 . . . . . 129 100 Mwanza . 793 35 1,039 46 . . 317 14 128 6 2,277 100 Mara . 4,760 84 172 3 . 86 2 567 10 86 2 5,671 100 Manyara 75 4 224 11 540 26 . . 310 15 967 46 2,115 100 Mainland 6,762 8 17,107 21 16,583 20 6,723 8 20,426 25 9,264 11 5,791 7 82,656 100 North Unguja . . . . . . . . . . . . . . . . South Unguja . . . . . . . . . . . . . . . . Urban West . . . . . . . . . . . . . . . . North Pemba . . . . . . . . . . . . . . . . South Pemba . . . . . . . . . . . . . . . . Zanzibar 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 6,762 9 17,107 23 16,583 20 6,723 5 20,426 14 9,264 18 5,791 10 82,656 100 Uncastrated Bulls Male Calves Female Calves 9.1.10 CATTLE PRODUCTION: Total Number of iImproved Beef Cattle by Category of cattle and region During the 2007/08 Agricultural Year Region Cattle Type Steers Heifers Total Castrated Bulls (Oxen) Cows Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 69 Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Total Cattle % Dodoma 126 4 598 17 1,697 49 . . . . . . 1,051 30 3,473 100 Arusha 835 1 3,966 5 40,715 52 2,933 4 10,318 13 9,685 12 10,185 13 78,637 100 Kilimanjaro 2,383 1 11,464 7 78,477 48 4,643 3 27,314 17 20,009 12 17,693 11 161,984 100 Tanga 653 2 802 2 19,355 46 1,184 3 6,462 16 7,605 18 5,578 13 41,639 100 Morogoro 879 9 509 5 4,147 44 282 3 1,980 21 603 6 1,013 11 9,414 100 Pwani 174 1 3,014 11 12,160 43 843 3 4,588 16 3,296 12 4,431 16 28,507 100 Dar es Salaam 894 4 1,376 6 13,259 54 185 1 3,607 15 2,059 8 2,991 12 24,372 100 Lindi 248 6 496 12 1,337 32 . . 1,117 27 500 12 500 12 4,199 100 Mtwara . . . . 159 40 . . 116 29 40 10 79 20 394 100 Ruvuma 989 8 1,806 15 4,682 38 119 1 1,074 9 1,622 13 1,886 15 12,177 100 Iringa 682 5 1,847 13 5,956 42 537 4 2,105 15 1,071 8 2,060 14 14,258 100 Mbeya 2,822 4 3,624 5 32,588 45 2,722 4 14,279 20 6,075 8 10,613 15 72,724 100 Singida 2,469 72 180 5 759 22 . . . . . . . . 3,409 100 Tabora 197 8 197 8 1,600 67 126 5 197 8 56 2 . . 2,370 100 Rukwa 347 8 639 15 2,350 57 47 1 224 5 94 2 447 11 4,149 100 Kigoma . . 958 31 635 21 . . 431 14 373 12 678 22 3,077 100 Shinyanga 2,157 40 163 3 2,044 38 . . 879 16 44 1 132 2 5,419 100 Kagera 987 4 2,857 12 9,982 42 947 4 4,263 18 1,969 8 2,859 12 23,863 100 Mwanza 911 24 383 10 1,284 34 330 9 779 21 53 1 53 1 3,794 100 Mara . . 280 10 516 18 . . 479 17 140 5 1,462 51 2,877 100 Manyara 999 8 953 8 3,532 30 934 8 1,690 14 1,912 16 1,828 15 11,848 100 Mainland 18,754 4 36,111 7 237,236 46 15,832 3 81,904 16 57,206 11 65,541 13 512,583 100 North Unguja 95 12 . . 379 48 . . 82 10 145 18 88 11 790 100 South Unguja . . 138 7 1,003 49 . . 274 13 274 13 365 18 2,053 100 Urban West . . 251 14 722 40 94 5 345 19 157 9 220 12 1,790 100 North Pemba 26 2 241 20 545 44 51 4 106 9 106 9 157 13 1,233 100 South Pemba 31 3 . . 643 63 . . 93 9 155 15 93 9 1,015 100 Zanzibar 151 2 630 9 3,292 48 145 2 900 13 837 12 923 13 6,880 100 Total 18,906 4 36,741 7 240,528 46 15,977 3 82,804 16 58,043 11 66,464 13 519,463 100 Cows Steers Heifers Male Calves Total 9.1.11 CATTLE PRODUCTION: Total Number of iImproved Diary Cattle by Category of cattle and region During the 2007/08 Agricultural Year Region Cattle Type Female Calves Castrated Bulls (Oxen) Uncastrated Bulls Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 70 Number % Number % Number % Number % Number % Number % Number % Dodoma 20,452 27 2,746 4 37,378 49 11,494 15 252 0 3,824 5 76,145 100 Arusha 66,348 43 12,766 8 31,493 20 34,442 22 2,485 2 8,326 5 155,859 100 Kilimanjaro 8,427 6 16,664 11 14,238 10 93,406 63 2,377 2 14,078 9 149,189 100 Tanga 4,367 5 13,405 15 12,609 14 44,007 50 3,142 4 9,922 11 87,452 100 Morogoro 7,535 31 4,761 20 3,974 17 4,749 20 18 0 3,017 13 24,054 100 Pwani 1,392 9 2,657 17 2,087 13 5,727 36 289 2 3,589 23 15,740 100 Dar es Salaam 169 2 1,931 21 285 3 3,545 39 497 5 2,622 29 9,050 100 Lindi 452 15 808 26 124 4 1,340 43 74 2 297 10 3,094 100 Mtwara 40 1 294 9 407 12 2,053 62 79 2 417 13 3,291 100 Ruvuma 743 3 1,424 6 1,326 5 18,861 78 304 1 1,576 7 24,235 100 Iringa 2,317 3 18,049 20 3,640 4 44,114 50 1,294 1 19,478 22 88,891 100 Mbeya 20,238 10 23,947 12 6,898 3 119,893 58 3,270 2 33,279 16 207,526 100 Singida 65,321 55 14,649 12 16,424 14 8,184 7 1,470 1 12,157 10 118,205 100 Tabora 74,027 77 5,326 6 2,267 2 12,084 12 405 0 2,599 3 96,708 100 Rukwa 16,336 24 4,690 7 3,787 5 42,795 62 683 1 1,102 2 69,393 100 Kigoma 2,140 10 2,293 11 545 3 14,556 70 146 1 1,002 5 20,683 100 Shinyanga 176,012 81 12,587 6 5,308 2 16,540 8 852 0 6,418 3 217,716 100 Kagera 15,981 28 7,844 14 2,320 4 21,802 38 6,256 11 3,464 6 57,667 100 Mwanza 72,426 40 25,844 14 12,425 7 49,572 27 1,504 1 19,630 11 181,402 100 Mara 55,732 50 13,195 12 9,597 9 23,936 22 979 1 7,273 7 110,712 100 Manyara 90,988 76 4,413 4 6,914 6 13,709 11 1,048 1 3,176 3 120,249 100 Manyara 91,045 76 4,413 4 6,914 6 13,709 11 1,048 1 3,176 3 120,306 100 North Unguja 190 4 818 16 196 4 3,322 66 25 1 488 10 5,040 100 South Unguja 199 3 710 11 126 2 4,485 72 168 3 519 8 6,206 100 Urban West 63 1 345 7 31 1 3,171 68 283 6 754 16 4,647 100 North Pemba 420 3 834 6 187 1 11,027 83 0 0 830 6 13,297 100 South Pemba 27 0 605 6 80 1 8,551 82 0 0 1,194 11 10,457 100 Zanzibar 899 2 3,312 8 620 2 30,556 77 476 1 3,784 10 39,646 500 Total 702,399 37 193,606 10 174,667 9 617,364 33 27,900 1 161,029 9 1,876,966 100 9.1.12 CATTLE PRODUCTION: Total Number Households rearing Cattle and Method of Cattle Identification by Region during, 2007/08 Agricultural Year Region Branding Cattle Clan Ear notching Colour Earings Others Total Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 71 Improved Breed Indigenous Total Improved Breed Indigenous Total Dodoma 2,769 216,661 219,429 2,614 165,559 168,173 Arusha 51,249 450,804 502,053 46,644 283,776 330,420 Kilimanjaro 65,971 144,305 210,276 61,474 84,494 145,968 Tanga 15,704 180,071 195,774 15,464 135,554 151,018 Morogoro 3,421 83,461 86,882 3,166 75,912 79,078 Pwani 10,177 48,337 58,515 8,917 37,366 46,282 Dar es Salaam 11,058 473 11,530 9,348 552 9,900 Lindi 1,011 7,075 8,087 1,011 7,364 8,376 Mtwara 119 26,829 26,948 477 7,000 7,477 Ruvuma 5,113 8,683 13,796 3,603 6,987 10,590 Iringa 5,190 70,430 75,620 4,030 47,441 51,471 Mbeya 78,981 156,854 235,835 30,295 149,579 179,874 Singida 383 360,961 361,344 3,406 329,856 333,262 Tabora 1,431 408,697 410,128 44,897 312,040 356,937 Rukwa 1,627 127,712 129,339 1,130 111,672 112,801 Kigoma 1,129 30,990 32,119 836 23,136 23,973 Shinyanga 3,463 612,520 615,983 113,349 521,578 634,927 Kagera 8,007 188,497 196,503 6,974 130,011 136,985 Mwanza 6,482 347,168 353,651 26,251 262,868 289,119 Mara 1,135 295,817 296,953 1,610 258,214 259,824 Manyara 4,621 382,931 387,552 5,534 244,665 250,199 Mainland 279,042 4,149,276 4,428,318 391,032 3,195,622 3,586,654 North Unguja 279 7,997 8,275 342 7,162 7,503 South Unguja 942 7,707 8,649 930 4,754 5,684 Urban West 816 5,495 6,311 659 4,961 5,621 North Pemba 450 12,243 12,693 574 10,357 10,931 South Pemba 434 8,355 8,789 279 6,622 6,901 Zanzibar 2,921 41,796 44,718 2,785 33,854 36,639 Total 281,963 4,191,072 4,473,036 393,817 3,229,477 3,623,293 Wet Season Dry Season 9.2.1 CATTLE PRODUCTION: Number of Milked Cows by Category of Cattle, Season and Region, During the 2007/08 Agricultural Year Region Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 72 Improved Breed Indigenous Total Improved Breed Indigenous Total Mean (ltr) Mean (lts) Mean (lts) Mean (lts) Mean (lts) Mean (lts) Dodoma 8 2 3 4 1 1 Arusha 6 2 3 5 1 2 Kilimanjaro 5 2 4 4 2 3 Tanga 6 2 3 5 2 2 Morogoro 10 3 5 7 2 3 Pwani 7 2 4 5 1 3 Dar es Salaam 8 6 8 6 4 6 Lindi 9 7 7 7 5 6 Mtwara 9 2 3 6 1 2 Ruvuma 7 3 5 5 2 3 Iringa 7 2 3 6 2 2 Mbeya 8 3 4 6 2 3 Singida 3 2 2 2 1 1 Tabora 8 2 2 5 1 1 Rukwa 6 3 3 5 2 2 Kigoma 6 2 3 6 2 2 Shinyanga 4 2 2 2 1 1 Kagera 6 2 3 5 2 2 Mwanza 10 2 2 8 1 2 Mara 5 2 2 3 1 1 Manyara 9 2 2 7 1 1 Mainland 6 2 3 5 1 2 North Unguja 8 3 3 8 2 3 South Unguja 6 2 3 5 2 2 Urban West 10 3 4 10 3 4 North Pemba 6 2 2 6 2 2 South Pemba 6 2 2 7 2 2 Zanzibar 7 2 2 7 2 2 Total 6 2 3 5 1 2 9.2.2 CATTLE PRODUCTION: Average milk production per cow per day, by Category of Cow, Season and Region, During the 2007/08 Agricultural Year Wet Season Dry Season Region Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 73 Improved Breed Indigenous Total Improved Breed Indigenous Total Mean Mean Mean Mean Mean Mean Dodoma 150 142 142 125 121 122 Arusha 193 152 162 171 129 141 Kilimanjaro 173 168 171 152 139 146 Tanga 192 135 149 171 117 132 Morogoro 133 156 152 136 148 146 Pwani 191 134 161 189 119 153 Dar es Salaam 200 178 199 188 192 188 Lindi 130 67 93 117 58 81 Mtwara 81 104 103 143 126 129 Ruvuma 216 151 175 218 135 163 Iringa 184 133 139 147 111 116 Mbeya 174 125 139 126 104 110 Singida 174 107 108 78 76 76 Tabora 181 150 150 171 128 129 Rukwa 137 104 106 147 93 96 Kigoma 103 114 114 107 95 96 Shinyanga 179 174 174 146 162 162 Kagera 194 160 166 135 134 134 Mwanza 135 158 158 159 125 125 Mara 175 143 144 118 124 124 Manyara 149 146 146 133 118 119 Mainland 180 147 152 153 125 129 North Unguja 129 110 110 129 101 102 South Unguja 154 118 124 117 106 108 Urban West 190 136 145 186 130 137 North Pemba 113 107 107 118 105 105 South Pemba 164 111 114 151 109 111 Zanzibar 155 114 117 137 108 111 Total 179 146 151 153 124 129 Wet Season Dry Season Region 9.2.3 CATTLE PRODUCTION: Average number of days for cows on milked, by category of Cattle, Season and Region, During the 2007/08 Agricultural Year Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 74 Improved Breed Indigenous Total Improved Breed Indigenous Total Mean Mean Mean Mean Mean Mean Dodoma 317 266 269 292 295 295 Arusha 432 411 416 460 530 509 Kilimanjaro 450 501 471 477 523 497 Tanga 350 338 341 385 350 360 Morogoro 426 362 373 444 397 406 Pwani 507 370 433 509 418 458 Dar es Salaam 712 662 711 671 771 676 Lindi 514 446 473 546 530 536 Mtwara 800 473 501 800 585 622 Ruvuma 409 335 365 418 401 408 Iringa 398 384 386 481 406 417 Mbeya 384 417 408 424 427 426 Singida 175 313 311 316 406 403 Tabora 288 255 255 297 299 299 Rukwa 295 287 288 352 287 291 Kigoma 552 336 349 556 418 430 Shinyanga 279 325 324 358 366 365 Kagera 388 293 311 438 342 362 Mwanza 264 329 328 393 370 370 Mara 290 305 305 388 320 321 Manyara 415 418 418 392 442 439 Mainland 421 349 361 451 392 402 North Unguja 653 484 491 552 498 500 South Unguja 435 460 456 461 470 468 Urban West 541 494 502 583 508 518 North Pemba 516 481 483 539 490 492 South Pemba 513 474 476 543 506 508 Zanzibar 507 478 481 522 494 497 Total 422 353 363 451 394 404 Wet Season Dry Season 9.2.4 CATTLE PRODUCTION: Average Cattle Milk price (Tshs/litre) per season by category of cow and Region, During the 2007/08 Agricultural Year Region Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 75 Wet Season Dry Season Wet Season Dry Season Wet Season Dry Season Wet Season Dry Season Dodoma 219,429 168,173 3 1 142 122 269 295 Arusha 502,053 330,420 3 2 162 141 416 509 Kilimanjaro 210,276 145,968 4 3 171 146 471 497 Tanga 195,774 151,018 3 2 149 132 341 360 Morogoro 86,882 79,078 5 3 152 146 373 406 Pwani 58,515 46,282 4 3 161 153 433 458 Dar es Salaam 11,530 9,900 8 6 199 188 711 676 Lindi 8,087 8,376 7 6 93 81 473 536 Mtwara 26,948 7,477 3 2 103 129 501 622 Ruvuma 13,796 10,590 5 3 175 163 365 408 Iringa 75,620 51,471 3 2 139 116 386 417 Mbeya 235,835 179,874 4 3 139 110 408 426 Singida 361,344 333,262 2 1 108 76 311 403 Tabora 410,128 356,937 2 1 150 129 255 299 Rukwa 129,339 112,801 3 2 106 96 288 291 Kigoma 32,119 23,973 3 2 114 96 349 430 Shinyanga 615,983 634,927 2 1 174 162 324 365 Kagera 196,503 136,985 3 2 166 134 311 362 Mwanza 353,651 289,119 2 2 158 125 328 370 Mara 296,953 259,824 2 1 144 124 305 321 Manyara 387,552 250,199 2 1 146 119 418 439 Mainland 4,428,318 3,586,654 3 2 152 129 361 402 North Unguja 8,275 7,503 3 3 110 102 491 500 South Unguja 8,649 5,684 3 2 124 108 456 468 Urban West 6,311 5,621 4 4 145 137 502 518 North Pemba 12,693 10,931 2 2 107 105 483 492 South Pemba 8,789 6,901 2 2 114 111 476 508 Zanzibar 44,718 36,639 2 2 117 111 481 497 Total 4,473,036 3,623,293 3 2 151 129 363 404 9.2.5 CATTLE PRODUCTION: Average Cattle Milk price (Tshs/litre) per season by category of cow and Region, During the 2007/08 Agricultural Year Average price per litre per season (Tshs) Region Number of milked cows Average milk production per cow per day (lts) Average number of days cows milked Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 76 Improved Breed Indigenous Total Improved Breed Indigenous Total Dodoma 3,263,702 70,698,123 73,961,825 1,214,114 26,244,779 27,458,893 101,420,719 4 Arusha 61,137,992 132,416,054 193,554,047 38,272,666 45,281,015 83,553,681 277,107,727 11 Kilimanjaro 58,702,248 56,869,130 115,571,378 34,924,526 20,808,381 55,732,906 171,304,284 7 Tanga 18,339,797 57,769,931 76,109,728 12,017,546 26,082,578 38,100,124 114,209,852 5 Morogoro 4,335,705 45,498,479 49,834,183 3,139,350 26,859,686 29,999,037 79,833,220 3 Pwani 13,104,388 11,601,913 24,706,301 8,523,728 5,551,596 14,075,324 38,781,625 2 Dar es Salaam 18,598,374 495,838 19,094,211 11,215,157 458,877 11,674,034 30,768,246 1 Lindi 1,158,124 3,122,826 4,280,950 886,439 2,280,889 3,167,328 7,448,277 0 Mtwara 83,992 5,989,384 6,073,376 431,061 1,047,660 1,478,721 7,552,097 0 Ruvuma 7,550,503 3,966,295 11,516,798 4,027,866 2,253,124 6,280,989 17,797,787 1 Iringa 6,873,810 21,507,891 28,381,701 3,304,929 9,134,901 12,439,831 40,821,532 2 Mbeya 116,655,645 53,252,162 169,907,807 24,626,540 30,805,713 55,432,253 225,340,060 9 Singida 213,726 68,838,342 69,052,068 483,627 30,879,167 31,362,794 100,414,863 4 Tabora 2,157,795 140,772,042 142,929,837 35,206,648 55,912,138 91,118,786 234,048,623 9 Rukwa 1,303,093 40,818,389 42,121,482 780,770 21,304,883 22,085,653 64,207,135 3 Kigoma 697,513 8,803,421 9,500,934 537,699 4,309,561 4,847,261 14,348,195 1 Shinyanga 2,458,409 212,529,486 214,987,895 36,243,840 103,107,589 139,351,429 354,339,324 14 Kagera 9,921,351 72,830,282 82,751,633 4,375,151 30,922,685 35,297,836 118,049,469 5 Mwanza 8,911,625 120,244,951 129,156,576 34,429,391 48,318,404 82,747,796 211,904,372 8 Mara 1,023,390 82,335,777 83,359,167 591,681 42,102,279 42,693,960 126,053,126 5 Manyara 5,957,159 99,585,296 105,542,455 5,007,099 36,223,491 41,230,590 146,773,046 6 Mainland 321,582,402 1,319,857,542 1,641,439,944 285,456,883 584,002,455 869,459,339 2,510,899,283 100 North Unguja 286,699 2,532,529 2,819,228 351,509 1,701,345 2,052,855 4,872,083 21 South Unguja 865,802 1,833,911 2,699,713 535,808 770,961 1,306,769 4,006,482 18 Urban West 1,496,404 2,255,723 3,752,127 1,221,485 2,053,571 3,275,056 7,027,183 31 North Pemba 293,692 2,158,078 2,451,770 383,105 1,739,051 2,122,157 4,573,926 20 South Pemba 395,357 1,731,138 2,126,495 273,567 1,215,441 1,489,008 3,615,503 16 Zanzibar 3,164,493 10,048,237 13,212,730 2,509,624 7,108,323 9,617,948 22,830,678 100 Total 324,752,290 1,325,130,870 1,649,883,160 288,413,416 592,992,399 881,405,816 2,531,288,975 100 9.2.6 CATTLE PRODUCTION: Quantity of milk Produced (Litres) by Category of Cattle, Season and Region, During the 2007/08 Agricultural Year ALL season % Region Wet Season Dry Season Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 77 No of households % No of households % Dodoma 71,167 20 287,802 80 358,969 102,865 Arusha 122,677 60 82,990 40 205,667 167,562 Kilimanjaro 112,088 46 130,620 54 242,708 185,997 Tanga 84,350 26 246,428 74 330,779 116,839 Morogoro 33,657 11 264,764 89 298,421 45,235 Pwani 12,663 7 161,860 93 174,523 28,058 Dar es Salaam 7,016 20 28,144 80 35,160 13,374 Lindi 15,448 9 151,450 91 166,898 18,177 Mtwara 35,052 14 214,321 86 249,373 35,138 Ruvuma 77,261 37 133,019 63 210,281 62,685 Iringa 48,188 16 258,441 84 306,629 88,519 Mbeya 96,358 21 358,466 79 454,824 207,028 Singida 81,735 38 135,258 62 216,992 116,524 Tabora 84,035 29 204,412 71 288,447 124,747 Rukwa 56,556 25 169,694 75 226,250 89,140 Kigoma 101,578 45 123,593 55 225,171 67,755 Shinyanga 181,605 37 303,607 63 485,212 261,150 Kagera 161,723 40 244,187 60 405,910 116,672 Mwanza 144,479 36 254,514 64 398,993 177,086 Mara 95,821 42 130,910 58 226,731 121,803 Manyara 109,407 55 89,106 45 198,513 137,902 Mainland 1,732,863 30 3,973,586 70 5,706,449 2,284,257 North Unguja 2,506 8 27,848 92 30,354 6,579 South Unguja 3,125 15 17,134 85 20,259 7,192 Urban West 1,664 9 16,987 91 18,651 6,060 North Pemba 2,579 8 30,316 92 32,895 14,284 South Pemba 3,233 11 26,801 89 30,034 11,570 Zanzibar 13,107 10 119,086 90 132,193 45,684 Total 1,745,970 30 4,092,672 70 5,838,642 2,329,942 9.3.1 GOAT PRODUCTION: Number of Agriculture Households Rearing Goats by Region during the 2007/08 Agricultural Year Raising goats Not raising goats Total Total livestock rearing households Region Appendix II _________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 78 Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats % Number of households Rearing Number of Goats Dodoma 70,169 906,466 99.0 796 5,546 0.6 729 3,343 0.4 71,167 915,356 Arusha 120,348 1,764,510 97.0 151 764 0.0 5,289 53,176 2.9 122,677 1,818,450 Kilimanjaro 104,854 581,840 90.3 1,083 1,742 0.3 8,546 60,753 9.4 112,088 644,334 Tanga 83,996 705,706 98.2 0 . . 659 12,919 1.8 84,350 718,625 Morogoro 32,105 322,614 85.4 0 . . 2,567 54,958 14.6 33,657 377,572 Pwani 12,202 161,320 93.4 549 1,872 1.1 1,255 9,577 5.5 12,663 172,769 Dar es 6,541 50,701 94.4 233 1,115 2.1 767 1,873 3.5 7,016 53,688 Lindi 15,106 154,247 96.8 94 94 0.1 808 4,981 3.1 15,448 159,322 Mtwara 35,012 233,965 99.7 112 560 0.2 40 40 0.0 35,052 234,564 Ruvuma 77,025 338,561 98.2 161 1,346 0.4 850 4,832 1.4 77,261 344,738 Iringa 47,454 290,497 97.2 112 868 0.3 1,337 7,522 2.5 48,188 298,887 Mbeya 95,601 520,603 95.6 126 757 0.1 2,104 23,113 4.2 96,358 544,473 Singida 81,632 835,257 99.5 103 206 0.0 693 3,705 0.4 81,735 839,169 Tabora 84,035 942,887 100.0 40 40 0.0 0 . . 84,035 942,926 Rukwa 56,331 410,480 95.9 402 1,077 0.3 1,363 16,690 3.9 56,556 428,247 Kigoma 101,578 488,165 97.6 0 . . 545 11,854 2.4 101,578 500,019 Shinyanga 181,427 1,910,098 97.3 251 1,047 0.1 2,811 51,911 2.6 181,605 1,963,056 Kagera 158,970 785,391 96.2 443 1,350 0.2 4,334 29,520 3.6 161,723 816,260 Mwanza 144,149 904,695 98.4 53 53 0.0 1,105 15,005 1.6 144,479 919,753 Mara 95,821 902,362 98.8 0 . . 450 11,163 1.2 95,821 913,524 Manyara 108,621 1,436,491 97.1 229 327 0.0 2,933 42,599 2.9 109,407 1,479,417 Mainland 1,712,976 14,646,855 97.1 4,937 18,763 0.1 39,185 419,533 2.8 1,732,863 15,085,150 North Unguja 2,506 12,555 86.5 32 63 0.4 32 1,890 13.0 2,506 14,508 South Unguja 3,033 13,194 63.1 0 . . 182 7,721 36.9 3,125 20,915 Urban West 1,633 10,079 83.8 0 . . 63 1,947 16.2 1,664 12,026 North Pemba 2,528 8,748 97.4 0 . . 51 231 2.6 2,579 8,978 South Pemba 3,117 12,428 99.1 0 . . 116 116 0.9 3,233 12,544 Zanzibar 12,817 57,004 82.6 32 63 0.1 444 11,905 17.3 13,107 68,972 Total 1,725,793 14,703,858 97.0 4,968 18,826 0.1 39,629 431,437 2.8 1,745,970 15,154,121 9.3.2 GOAT PRODUCTION: Number of Goats by Type and Region as of 1st October 2008 Total Improved Dairy Improved for Meat Indigenous Region Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 79 Number % Number % 1 - 4 779,239 45 2,010,920 13 3 5 - 9 510,234 29 3,272,351 22 6 10 - 14 208,231 12 2,359,734 16 11 15 - 19 84,258 5 1,384,272 9 16 20 - 24 61,989 4 1,306,875 9 21 25 - 29 25,442 1 673,217 4 26 30 - 34 23,354 1 727,038 5 31 35 - 39 9,659 1 354,489 2 37 40+ 43,565 2 3,065,224 20 70 Total 1,745,970 100.0 15,154,121 100.0 8.7 Herd Size Number of Household % Number of Goats % Average Number Per Household 1 - 4 8,372 64 20,734 30 2 5 - 9 3,486 27 21,131 31 6 10 - 14 826 6 9,369 14 11 15 - 19 163 1 2,536 4 16 20 - 24 58 0 1,289 2 22 40+ 202 2 13,914 20 69 Total 13,107 100 68,972 100 5 Herd Size Number of Household % Number of Goat % Average Number Per Household 1 - 4 770,866 44 1,990,187 13 3 5 - 9 506,748 29 3,251,221 22 6 10 - 14 207,405 12 2,350,365 16 11 15 - 19 84,095 5 1,381,736 9 16 20 - 24 61,931 4 1,305,586 9 21 25 - 29 25,442 1 673,217 4 26 30 - 34 23,354 1 727,038 5 31 35 - 39 9,659 1 354,489 2 37 40+ 43,363 3 3,051,311 20 70 Total 1,732,863 100.0 15,085,150 100.0 8.7 9.3.3 GOAT PRODUCTION: Number of Households Rearing Goats, Head of Goats and Average Head per Household by Herd Size as of 1st October 2008- NATIONAL Goat rearing households Herd of Goats Average Goats per household 9.3.4 GOAT PRODUCTION: Number of Households Rearing Goats, Head of Goats and Average Head per Household by Herd Size as of 1st October 2008 - ZANZIBAR 9.3.5 GOAT PRODUCTION: Number of Households Rearing Goats, Head of Goats and Average Head per Household by Herd Size as of 1st October 2008- MAINALAND Herd Size Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 80 Number % Number % Number % Number % Billy Goats 2,275,670 95.8 6,519 0.3 93,764 4.0 2,375,952 15.7 She Goats 997,186 97.8 1,219 0.1 20,954 2.1 1,019,359 6.7 Castrated Goat 7,520,777 97.6 6,504 0.1 171,770 2.3 7,699,052 51.1 Male Kid 1,859,281 96.7 2,544 0.1 58,947 3.2 1,920,772 12.7 She Kid 1,993,941 96.2 1,977 0.1 74,097 3.7 2,070,015 13.7 Total 14,646,855 97.0 18,763 0.1 419,533 2.8 15,085,150 100 Number % Number % Number % Number % Billy Goat 8,294 89 63 1 938 10 9,295 13 Castrated Goat 1,294 100 . 0 0 0 1,294 2 She Goat 31,698 85 . 0 5,677 15 37,375 54 Male Kid 7,692 80 . 0 1,880 20 9,572 14 She Kid 8,025 70 . 0 3,410 30 11,435 17 Total 57,004 83 63 0 11,905 17 68,972 100 Number % Number % Number % Number % Billy Goats 2,283,964 95.8 6,582 0.3 94,701 4.0 2,385,247 15.7 She Goats 998,480 97.8 1,219 0.1 20,954 2.1 1,020,653 6.7 Castrated Goat 7,552,475 97.6 6,504 0.1 177,448 2.3 7,736,426 51.1 Male Kid 1,866,973 96.7 2,544 0.1 60,827 3.2 1,930,344 12.7 She Kid 2,001,966 96.2 1,977 0.1 77,507 3.7 2,081,451 13.7 Total 14,703,858 97.0 18,826 0.1 431,437 2.8 15,154,121 100 Total Category Indigenous Improved Meat Improved Dairy 9.3.6 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October 2008 - MAINLAND 9.3.7 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October 2008 - ZANZIBAR Total Improved Dairy Category Indigenous Improved Meat 9.3.8 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October 2008 - TANZANIA Category Indigenous Improved Meat Improved Dairy Total Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 81 Total Goat % Total Goat % Total Goat % Total Goat % Total Goat % Total Goat % Dodoma 150,499 17 83,516 9 422,463 47 121,584 13 128,404 14 906,466 100 Arusha 234,956 13 226,318 13 796,910 45 251,477 14 254,849 14 1,764,510 100 Kilimanjaro 88,287 15 29,297 5 324,561 56 62,237 11 77,458 13 581,840 100 Tanga 94,488 13 27,356 4 382,925 54 98,748 14 102,188 14 705,706 100 Morogoro 51,207 16 19,131 6 164,749 51 39,663 12 47,864 15 322,614 100 Pwani 25,956 16 9,126 6 79,991 50 22,452 14 23,796 15 161,320 100 Dar es Salaam 8,409 17 3,036 6 27,184 54 5,868 12 6,204 12 50,701 100 Lindi 25,662 17 3,851 2 77,011 50 23,659 15 24,064 16 154,247 100 Mtwara 36,663 16 3,338 1 123,245 53 31,028 13 39,690 17 233,965 100 Ruvuma 58,572 17 8,450 2 207,812 61 30,828 9 32,899 10 338,561 100 Iringa 48,548 17 13,141 5 162,165 56 28,204 10 38,439 13 290,497 100 Mbeya 74,126 14 22,188 4 306,877 59 53,087 10 64,325 12 520,603 100 Singida 135,744 16 74,667 9 406,561 49 121,979 15 96,308 12 835,257 100 Tabora 167,518 18 43,110 5 462,391 49 127,707 14 142,160 15 942,887 100 Rukwa 69,936 17 24,849 6 218,482 53 42,814 10 54,399 13 410,480 100 Kigoma 69,731 14 13,591 3 290,235 59 48,140 10 66,469 14 488,165 100 Shinyanga 337,463 18 116,231 6 968,134 51 235,000 12 253,270 13 1,910,098 100 Kagera 94,336 12 22,923 3 469,888 60 86,596 11 111,647 14 785,391 100 Mwanza 155,473 17 36,274 4 472,915 52 119,750 13 120,284 13 904,695 100 Mara 151,891 17 54,003 6 452,048 50 117,400 13 127,019 14 902,362 100 Manyara 196,204 14 162,790 11 704,233 49 191,062 13 182,203 13 1,436,491 100 Mainland 2,275,670 16 997,186 7 7,520,777 51 1,859,281 13 1,993,941 14 14,646,855 100 North Unguja 1,799 14 253 2 6,937 55 1,620 13 1,945 15 12,555 100 South Unguja 1,888 14 282 2 7,205 55 1,886 14 1,933 15 13,194 100 Urban West 1,413 14 188 2 5,495 55 1,319 13 1,664 17 10,079 100 North Pemba 1,450 17 259 3 4,872 56 1,263 14 902 10 8,748 100 South Pemba 1,743 14 311 3 7,188 58 1,604 13 1,581 13 12,428 100 Zanzibar 8,294 15 1,294 2 31,698 56 7,692 13 8,025 14 57,004 100 Total 2,283,964 16 998,480 7 7,552,475 51 1,866,973 13 2,001,966 14 14,703,858 100 9.3.9 GOAT PRODUCTION: Total Number of Indigenous Goat by Category and Region as of 1st October 2008 Region Goat Type Billy Goat Castrated Goat She Goat Male Kid She Kid Total Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 82 Number % Number % Number % Number % Number % Number % Dodoma 1,977 36 822 15 1,750 32 285 5 712 13 5,546 100 Arusha 180 24 87 11 . . 266 35 231 30 764 100 Kilimanjaro 635 36 63 4 1,044 60 . . . . 1,742 100 Tanga . . . . . . . . . . . . Morogoro . . . . . . . . . . . . Pwani 1,436 77 . . 325 17 . . 111 6 1,872 100 Dar es Salaam 588 53 . . 459 41 68 6 . . 1,115 100 Lindi . . . . 94 100 . . . . 94 100 Mtwara . . . . . . 560 100 . . 560 100 Ruvuma 161 12 . . 1,053 78 . . 132 10 1,346 100 Iringa 159 18 159 18 231 27 159 18 159 18 868 100 Mbeya 757 100 . . . . . . . . 757 100 Singida . . . . 103 50 . . 103 50 206 100 Tabora 40 100 . . . . . . . . 40 100 Rukwa 402 37 . . . . 675 63 . . 1,077 100 Kigoma . . . . . . . . . . . . Shinyanga . . 88 8 307 29 326 31 326 31 1,047 100 Kagera . . . . 942 70 204 15 204 15 1,350 100 Mwanza 53 100 . . . . . . . . 53 100 Mara . . . . . . . . . . . . Manyara 132 40 . . 195 60 . . . . 327 100 Mainland 6,519 35 1,219 6 6,504 1,991 2,544 14 1,977 11 18,763 100 North Unguja 63 100 . . . . . . . . 63 100 South Unguja . . . . . . . . . . . . Urban West . . . . . . . . . . . . North Pemba . . . . . . . . . . . . South Pemba . . . . . . . . . . . . Zanzibar 63 100 0 0 0 0 0 0 0 0 63 100 Total 6,582 35 1,219 6 6,504 35 2,544 14 1,977 11 18,826 100 9.3.10 GOAT PRODUCTION: Number of Improved Goats for Meat by Category and Region as of 1st october 2008 Region Goat Type Billy Goat Castrated Goat She Goat Male Kid She Kid Total Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 83 Number % Number % Number % Number % Number % Number % Dodoma 444 13 . . 1,885 56 587 18 427 13 3,343 100 Arusha 10,692 20 2,560 5 24,683 46 5,435 10 9,806 18 53,176 100 Kilimanjaro 16,698 27 519 1 30,476 50 8,133 13 4,927 8 60,753 100 Tanga 1,318 10 . . 3,533 27 2,473 19 5,595 43 12,919 100 Morogoro 9,246 17 . . 16,566 30 10,931 20 18,215 33 54,958 100 Pwani 2,873 30 . . 3,685 38 271 3 2,749 29 9,577 100 Dar es Salaam 1,058 57 . . 475 25 85 5 254 14 1,873 100 Lindi 1,809 36 124 2 372 7 2,057 41 620 12 4,981 100 Mtwara . . . . 40 100 . . . . 40 100 Ruvuma . . 814 17 3,773 78 244 5 . . 4,832 100 Iringa 2,288 30 . . 4,439 59 159 2 636 8 7,522 100 Mbeya 159 1 1,273 6 5,991 26 13,945 60 1,745 8 23,113 100 Singida 319 9 . . 2,327 63 412 11 648 17 3,705 100 Tabora . . . . . . . . . . . . Rukwa 3,031 18 . . 9,532 57 . . 4,127 25 16,690 100 Kigoma . . 4,385 37 7,469 63 . . . . 11,854 100 Shinyanga 16,865 32 129 0 17,527 34 1,783 3 15,606 30 51,911 100 Kagera 7,046 24 7,046 24 14,852 50 484 2 92 0 29,520 100 Mwanza 9,259 62 . . 4,160 28 1,586 11 . . 15,005 100 Mara . . . . 2,665 24 968 9 7,530 67 11,163 100 Manyara 10,659 25 4,104 10 17,322 41 9,396 22 1,119 3 42,599 100 Mainland 93,764 22 20,954 5 171,770 403 58,947 14 74,097 18 419,533 100 North Unguja . . . . . . . . 1,890 100 1,890 100 South Unguja 912 12 . . 3,435 44 1,854 24 1,520 20 7,721 100 Urban West . . . . 1,947 100 . . . . 1,947 100 North Pemba 26 11 . . 179 78 26 11 . . 231 100 South Pemba . . . . 116 100 . . . . 116 100 Zanzibar 938 8 0 0 5,677 48 1,880 16 3,410 29 11,905 100 Total 94,701 22 20,954 5 177,448 41 60,827 14 77,507 18 431,437 100 Total 9.3.11 GOAT PRODUCTION: Number of Improved Dairy Goats by Category and Region as of 1st October 2008 Region Goat Type Billy Goat Castrated Goat She Goat Male Kid She Kid Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 84 Wet Season Dry Season Wet Season Dry Season Wet Season Dry Season Wet Season Dry Season Dodoma 3,234 1,679 2 1 62 36 276 332 Arusha 199,183 93,790 1 1 66 56 379 498 Kilimanjaro 19,151 15,768 1 1 76 63 563 579 Tanga 14,306 9,743 1 1 53 53 390 473 Morogoro 4,587 4,866 2 2 70 55 524 523 Pwani 2,209 1,556 2 1 69 76 607 663 Dar es Salaam 387 324 1 1 61 74 621 621 Lindi 2,306 2,029 4 2 21 28 748 656 Mtwara 1,164 927 3 2 60 66 355 713 Ruvuma 59 59 2 1 87 84 500 754 Iringa 3,402 2,889 1 1 74 54 444 416 Mbeya 1,432 1,272 3 2 76 47 605 446 Singida 706 . 1 . 38 . 556 940 Tabora 819 582 2 1 90 90 850 165 Rukwa . . . . . . . . Kigoma . . . . . . . . Shinyanga 528 398 2 1 80 67 387 720 Kagera 9,121 6,382 1 1 62 63 303 389 Mwanza 234 234 1 . 29 97 100 100 Mara . 508 . . . 90 867 1,000 Manyara 71,974 30,638 1 1 71 71 527 540 Mainland 334,802 173,645 2 1 64 65 505 554 North Unguja 95 95 . . . 90 1,000 1,000 South Unguja 304 182 1 1 78 72 960 960 Urban West 126 63 2 2 75 60 1,000 1,000 North Pemba 102 102 2 1 70 70 758 667 South Pemba . . . . . . 1,100 1,000 Zanzibar 627 442 2 1 74 73 964 925 Total 335,428 174,088 1 1 67 59 441 510 Average price per litre per season (Tshs) 9.3.12 GOAT PRODUCTION:Milk Production from Goat By Season and Region, During the 2007/08 Agricultural Year Region Number of Milked goat Average milk production per goat per day (lts) Average number of days for goats on milked Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 85 Regions Number of households raising or managing sheep % Number of households not raising or managing sheep % Number of agriculture households Total livestock keeping households Dodoma 29,506 8.2 329,463 91.8 358,969 102,865 Arusha 98,431 47.9 107,117 52.1 205,547 167,562 Kilimanjaro 63,608 26.2 179,100 73.8 242,708 185,997 Tanga 39,247 11.9 291,532 88.1 330,779 116,839 Morogoro 8,743 2.9 289,679 97.1 298,421 45,235 Pwani 2,728 1.6 171,795 98.4 174,523 28,058 Dar es Salaam 1,005 2.9 34,155 97.1 35,160 13,374 Lindi 1,081 .6 165,817 99.4 166,898 18,177 Mtwara 2,536 1.0 246,837 99.0 249,373 35,138 Ruvuma 5,703 2.7 204,578 97.3 210,281 62,685 Iringa 12,392 4.0 294,237 96.0 306,629 88,519 Mbeya 14,648 3.2 440,176 96.8 454,824 207,028 Singida 50,852 23.4 166,140 76.6 216,992 116,524 Tabora 38,426 13.3 250,021 86.7 288,447 124,747 Rukwa 5,835 2.6 220,415 97.4 226,250 89,140 Kigoma 13,224 5.9 211,946 94.1 225,171 67,755 Shinyanga 87,549 18.0 397,663 82.0 485,212 261,150 Kagera 18,718 4.6 387,192 95.4 405,910 116,672 Mwanza 33,169 8.3 365,824 91.7 398,993 177,086 Mara 38,308 16.9 188,423 83.1 226,731 121,803 Manyara 72,762 36.7 125,751 63.3 198,513 137,902 Mainland 638,469 11.2 5,067,860 88.8 5,706,329 2,284,257 North Unguja 57 .2 30,297 99.8 30,354 6,579 South Unguja 61 .3 20,198 99.7 20,259 7,192 Urban West 63 .3 18,588 99.7 18,651 6,091 North Pemba 29 .1 32,866 99.9 32,895 14,284 South Pemba 0 .0 30,034 100.0 30,034 11,570 Zanzibar 210 0.2 131,983 99.8 132,193 45,716 National 638,679 10.9 5,199,844 89 5,838,523 2,329,973 9.4.1 SHEEP PRODUCTION: Number of Households Rearing Sheep by Region during the 2007/08 Agriculture Year Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 86 Number of Households % Total Sheep % Dodoma 29,506 4.62 270,299 4.73 Arusha 98,550 15.43 1402236 24.53 Kilimanjaro 63,608 9.96 355,961 6.23 Tanga 39,247 6.14 216,983 3.80 Morogoro 8,743 1.37 118,792 2.08 Pwani 2,728 0.43 43,141 0.75 Dar es Salaam 1,005 0.16 20,888 0.37 Lindi 1,081 0.17 4,908 0.09 Mtwara 2,536 0.40 16,794 0.29 Ruvuma 5,703 0.89 20,535 0.36 Iringa 12,392 1.94 56,448 0.99 Mbeya 14,648 2.29 98,222 1.72 Singida 50,852 7.96 477,772 8.36 Tabora 38,426 6.02 352,543 6.17 Rukwa 5,835 0.91 43,577 0.76 Kigoma 13,224 2.07 116,534 2.04 Shinyanga 87,549 13.71 739,829 12.94 Kagera 18,718 2.93 76,713 1.34 Mwanza 33,169 5.19 224,403 3.93 Mara 38,308 6.00 418,077 7.31 Manyara 72,762 11.39 640,319 11.20 Mainland 638,589 99.97 5,714,975 99.99 North Unguja 57 0.01 82 0.00 South Unguja 61 0.01 122 0.00 Urban West 63 0.01 283 0.00 North Pemba 29 0.00 88 0.00 South Pemba 0 0.00 . 0.00 Zanzibar 210 0.03 574 0.01 Total 638,798 100.00 5,715,549 100.00 9.4.2 SHEEP PRODUCTION: Number of houeholds rearing sheep and number of Sheep by Region as of 1st October 2008 Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 87 Ram Castrated Sheep She Sheep Male Lamb She Lamb Dodoma 47,195 23,111 132,125 31,716 36,152 270,299 Arusha 197,093 152,693 660,167 171,075 221,208 1,402,236 Kilimanjaro 107,993 12,706 169,320 24,963 40,979 355,961 Tanga 35,022 8,592 122,498 25,547 25,323 216,983 Morogoro 14,554 4,535 63,898 14,423 21,382 118,792 Pwani 5,607 2,509 21,971 5,765 7,289 43,141 Dar es Salaam 726 466 19,099 280 317 20,888 Lindi 978 237 2,917 79 698 4,908 Mtwara 3,209 112 9,288 1,703 2,483 16,794 Ruvuma 3,694 262 12,230 864 3,485 20,535 Iringa 10,738 1,498 33,166 5,501 5,545 56,448 Mbeya 30,991 5,042 46,728 6,376 9,084 98,222 Singida 53,814 41,734 282,742 38,889 60,593 477,772 Tabora 62,122 13,651 184,425 47,350 44,995 352,543 Rukwa 8,501 847 23,145 4,813 6,272 43,577 Kigoma 8,270 45,295 49,962 5,182 7,825 116,534 Shinyanga 136,994 20,864 383,664 86,404 111,904 739,829 Kagera 15,776 1,532 43,380 6,822 9,203 76,713 Mwanza 43,183 6,072 114,115 26,890 34,143 224,403 Mara 58,219 13,634 207,537 88,098 50,590 418,077 Manyara 93,557 67,380 295,861 103,123 80,398 640,319 Mainland 938,238 422,771 2,878,236 695,862 779,868 5,714,975 North Unguja . 32 51 . . 82 South Unguja 30 61 30 . . 122 Urban West 31 . 157 . 94 283 North Pemba 58 . 29 . . 88 South Pemba . . . . . . Zanzibar 120 92 267 0 94 574 Total 938,358 422,864 2,878,504 695,862 779,962 5,715,549 9.4.3 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and Region as of 1st October 2008 Region Number of Indigenous Total Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 88 Herd size Sheep Rearing Households % Herd of sheep Average Per Houseold 1 - 4 1,366,143 85 2,461,318 2 5 - 9 159,494 10 987,323 6 10 - 14 40,463 3 444,240 11 15 - 19 12,855 1 208,369 16 20 - 24 10,049 1 207,588 21 25 - 29 3,003 0 77,992 26 30 - 39 5,672 0 182,986 32 40+ 11,556 1 1,145,159 99 Total 1,609,236 100 5,714,975 4 Number of Household % Number of Sheep Average Number Per Household 1 - 4 332 100 574 2 Total 332 100 574 2 Herd Size Number of Household % Number of sheep Average per household 1 - 4 1,366,476 85 2,461,892 2 5 - 9 159,494 10 987,323 6 10 - 14 40,463 3 444,240 11 15 - 19 12,855 1 208,369 16 20 - 24 10,049 1 207,588 21 25 - 29 3,003 0 77,992 26 30 - 39 5,672 0 182,986 32 40+ 11,556 1 1,145,159 99 Total 1,609,568 100 5,715,549 4 9.4.6 SHEEP PRODUCTION: Number of Households Rearing Sheep, Head of Sheep and Average Head per Household by Herd Size as of 1st October 2008 NATIONAL 9.4.4 SHEEP PRODUCTION: Number of Households rearing Sheep, Head of Sheep and Average Head per Household by Herd size During the 2007/08 Agricultural Year, Tanzania Mainland 9.4.5 SHEEP PRODUCTION: Number of Households rearing Sheep, Head of Sheep and Average Head per Household by Herd size During the 2007/08 Agricultural Year, Zanzibar Region Zanzibar Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 89 Category Number of Indigenous % Number of Improved % Total % Lamb 938,238 16 . . 938,238 16 Castrated 422,771 7 . . 422,771 7 She Sheep 2,878,236 50 . . 2,878,236 50 Male Lamb 695,862 12 . . 695,862 12 Female Lamb 779,868 14 . . 779,868 14 Total 5,714,975 100 . . 5,714,975 100 Category Number of Indigenous % Number of Improved % Total % Lamb 120 21 . . 120 21 Castrated 92 16 . . 92 16 She Sheep 267 47 . . 267 47 Male Lamb . . . . Female Lamb 94 16 . . 94 16 Total 574 100 . . 574 100 Category Number of Indigenous % Number of Improved % Total % Lamb 938,358 16 . . 938,358 16 Castrated 422,864 7 . . 422,864 7 She Sheep 2,878,504 50 . . 2,878,504 50 Male Lamb 695,862 12 . . 695,862 12 Female Lamb 779,962 14 . . 779,962 14 Total 5,715,549 100 . . 5,715,549 100 9.4.9 SHEEP PRODUCTION: Total Number of Sheep by Breed Type During the 2007/08 Agriculture Year - NATIONAL 9.4.7 SHEEP PRODUCTION: Total Number of Sheep by Breed Type During the 2007/08 Agriculture Year - MAINLAND 9.4.8 SHEEP PRODUCTION: Total Number of Sheep by Breed Type During the 2007/08 Agriculture Year - ZANZIBAR Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 90 No of households % No of households % No of households % Dodoma 31,631 8.8 327,339 91.2 358,969 100.0 Arusha 8,478 4.1 197,189 95.9 205,667 100.0 Kilimanjaro 33,826 13.9 208,882 86.1 242,708 100.0 Tanga 5,469 1.7 325,310 98.3 330,779 100.0 Morogoro 32,937 11.0 265,484 89.0 298,421 100.0 Pwani 1,387 0.8 173,136 99.2 174,523 100.0 Dar es Salaam 1,987 5.7 33,173 94.3 35,160 100.0 Lindi 1,924 1.2 164,974 98.8 166,898 100.0 Mtwara 4,062 1.6 245,311 98.4 249,373 100.0 Ruvuma 64,624 30.7 145,657 69.3 210,281 100.0 Iringa 103,865 33.9 202,764 66.1 306,629 100.0 Mbeya 106,494 23.4 348,330 76.6 454,824 100.0 Singida 11,120 5.1 205,873 94.9 216,992 100.0 Tabora 5,543 1.9 282,903 98.1 288,447 100.0 Rukwa 19,834 8.8 206,416 91.2 226,250 100.0 Kigoma 6,022 2.7 219,148 97.3 225,171 100.0 Shinyanga 3,015 0.6 482,197 99.4 485,212 100.0 Kagera 37,978 9.4 367,932 90.6 405,910 100.0 Mwanza 2,265 0.6 396,728 99.4 398,993 100.0 Mara 419 0.2 226,312 99.8 226,731 100.0 Manyara 38,994 19.6 159,519 80.4 198,513 100.0 Mainland 521,797 10.1 5,184,532 89.9 5,706,329 100 North Unguja 0 0.0 30,354 100.0 30,354 100 South Unguja 122 0.6 20,137 99.4 20,259 100 Urban West 31 0.2 18,620 99.8 18,651 100 North Pemba 0 0.0 32,895 100.0 32,895 100 South Pemba 0 0.0 30,034 100.0 30,034 100 Zanzibar 153 0.1 132,009 99.9 132,193 100.0 Total 522,025 8.9 5,316,617 91.1 5,838,642 100 9.5.1 PIG PRODUCTION: Number of Households Raising Pigs by Region during 2007/08 Agriculture Year rearing Pigs Not rearing pigs Region Total During the 2007/2008 Agriculture Year Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 91 Number % Number % 1 - 4 437,591 84 771,324 48.8 2 5 - 9 51,708 10 323,173 20.4 6 10 - 14 20,918 4 240,315 15.2 11 15 - 19 7,023 1 111,892 7.1 16 20 - 24 2,115 0 44,821 2.8 21 25 - 29 730 0 19,562 1.2 27 30 - 39 971 0 31,146 2.0 32 40+ 817 0 39,164 2.5 48 Total 521,872 100 1,581,396 100.0 3 Herd Size Number of Household % Number of Pigs % Average Number Per Household 5 - 9 61 40 395 13 7 15 - 19 30 20 578 19 19 30 - 39 62 40 2,042 68 33 Total 153 100 3,015 100 20 Herd Size Number of Household % Number of Pig % Average Number Per Household 1 - 4 437,591 84 771,324 48.7 2 5 - 9 51,768 10 323,568 20.4 6 10 - 14 20,918 4 240,315 15.2 11 15 - 19 7,054 1 112,470 7.1 16 20 - 24 2,115 0 44,821 2.8 21 25 - 29 730 0 19,562 1.2 27 30 - 39 1,033 0 33,188 2.1 32 40+ 817 0 39,164 2.5 48 Total 522,025 100 1,584,411 100 3 9.5.3 PIG PRODUCTION: Number of Households Rearing Pigs, Head of Pigs and Average Head per Household by Herd Size as of 1st October 2008-ZANZIBAR 9.5.4 PIG PRODUCTION: Number of Households Rearing Pigs, Head of Pigs and Average Head per Household by Herd Size as of 1st October 2008 - NATIONAL 9.5.2 PIG PRODUCTION: Number of Households Rearing Pigs, Head of Pigs and Average Head per Household by Herd Size as of 1st October 2008 - MAINLAND Herd Size Pig rearing households Herd of pigs Average per household Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 92 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Dodoma 19,259 19,091 42,700 16,664 19,141 116,854 Arusha 4,656 2,671 10,860 3,462 5,826 27,475 Kilimanjaro 18,696 15,063 46,377 18,497 25,063 123,696 Tanga 3,669 316 7,587 1,578 4,004 17,155 Morogoro 21,321 4,352 41,505 9,107 12,177 88,462 Pwani 1,928 1,280 5,034 2,958 3,258 14,458 Dar es Salaam 2,932 3,312 8,015 11,975 9,246 35,479 Lindi 1,193 152 4,228 1,110 380 7,063 Mtwara 2,010 265 5,007 1,945 1,771 10,998 Ruvuma 29,560 14,414 90,380 26,468 22,454 183,276 Iringa 54,803 12,099 114,416 26,509 34,002 241,829 Mbeya 44,944 37,230 151,351 53,119 59,823 346,466 Singida 10,055 5,857 20,939 2,914 9,171 48,935 Tabora 4,880 855 9,422 3,919 6,592 25,668 Rukwa 14,566 2,489 36,952 9,228 17,373 80,608 Kigoma 5,067 727 8,999 1,781 1,713 18,286 Shinyanga 3,861 402 6,169 1,708 2,612 14,753 Kagera 14,267 2,167 40,460 3,765 3,774 64,432 Mwanza 2,073 983 4,357 4,767 5,096 17,277 Mara 430 . 709 602 . 1,741 Manyara 18,849 11,693 46,629 8,930 10,384 96,485 Mainland 279,017 135,418 702,095 211,007 253,859 1,581,396 North Unguja . . . . . . South Unguja 122 182 608 638 334 1,885 Urban West . . 126 . 1,005 1,130 North Pemba . . . . . . South Pemba . . . . . . Zanzibar 122 182 734 638 1,339 3,015 Total 279,139 135,600 702,829 211,646 255,198 1,584,411 9.5.5 PIG PRODUCTION: Total Number of Pigs by Type of Pigs and Region as of 1st October 2008 Region Pig Type Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 93 Region Number of households Number of pigs Average per household Dodoma 31,631 116,854 4 Arusha 8,478 27,475 3 Kilimanjaro 33,826 123,696 4 Tanga 5,469 17,155 3 Morogoro 32,937 88,462 3 Pwani 1,387 14,458 10 Dar es Salaam 1,987 35,479 18 Lindi 1,924 7,063 4 Mtwara 4,062 10,998 3 Ruvuma 64,624 183,276 3 Iringa 103,865 241,829 2 Mbeya 106,494 346,466 3 Singida 11,120 48,935 4 Tabora 5,543 25,668 5 Rukwa 19,834 80,608 4 Kigoma 6,022 18,286 3 Shinyanga 3,015 14,753 5 Kagera 37,978 64,432 2 Mwanza 2,265 17,277 8 Mara 419 1,741 4 Manyara 38,994 96,485 2 Mainland 521,797 1,581,396 3 North Unguja 0 . South Unguja 122 1,885 16 Urban West 31 1,130 36 North Pemba 0 . South Pemba 0 . Zanzibar 153 3,015 20 Total 522,025 1,584,411 3 9.5.6 PIG PRODUCTION : Number of Pigs per Household by Region as of 1st October 2008 Appendix II _____________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 94 Number of Households Number of Indigenous Chicken % Number of Households Number of Layers % Number of Households Number of Broilers % Households rearing Chicken Number of Chicken Dodoma 193,799 1,926,782 99.0 792 16,853 0.9 357 3,389 0.2 193,953 1,947,024 Arusha 101,376 949,616 99.3 556 4,481 0.5 512 1,868 0.2 101,911 955,966 Kilimanjaro 177,654 1,521,980 91.8 4,200 95,128 5.7 1,096 40,371 2.4 179,580 1,657,479 Tanga 211,460 2,092,981 99.7 408 3,223 0.2 430 3,378 0.2 211,636 2,099,582 Morogoro 195,590 2,683,871 97.0 966 21,379 0.8 1,394 61,610 2.2 197,102 2,766,861 Pwani 106,367 1,619,965 86.4 894 183,508 9.8 553 72,258 3.9 107,386 1,875,732 Dar es Salaam 24,035 514,473 42.5 1,742 501,873 41.4 535 194,995 16.1 25,687 1,211,340 Lindi 105,238 1,552,850 98.6 1,081 12,778 0.8 108 8,847 0.6 106,135 1,574,475 Mtwara 137,547 1,470,393 98.2 753 13,553 0.9 164 12,908 0.9 138,147 1,496,854 Ruvuma 146,934 1,675,862 98.5 1,959 21,258 1.2 420 4,122 0.2 148,464 1,701,242 Iringa 236,482 2,243,187 95.7 2,303 52,668 2.2 477 47,723 2.0 237,735 2,343,579 Mbeya 345,738 3,519,574 98.5 3,351 37,762 1.1 2,054 16,836 0.5 347,206 3,574,172 Singida 155,431 1,598,341 98.9 816 9,676 0.6 899 7,762 0.5 155,637 1,615,779 Tabora 212,269 2,897,591 98.6 1,168 41,890 1.4 0 . 0.0 212,604 2,939,481 Rukwa 146,870 1,566,070 98.4 1,332 21,046 1.3 272 3,644 0.2 147,818 1,590,761 Kigoma 97,542 794,116 91.2 732 13,311 1.5 212 63,707 7.3 98,088 871,134 Shinyanga 351,490 4,833,471 98.8 1,467 53,748 1.1 556 3,151 0.1 352,511 4,890,370 Kagera 185,088 1,326,534 98.5 1,527 12,106 0.9 563 8,010 0.6 186,049 1,346,650 Mwanza 278,693 3,317,383 99.6 676 9,115 0.3 1,147 2,866 0.1 279,099 3,329,364 Mara 164,295 1,799,925 99.9 236 795 0.0 343 1,802 0.1 164,618 1,802,523 Manyara 129,376 1,058,172 98.3 1,753 9,686 0.9 1,790 8,321 0.8 131,316 1,076,179 Mainland 3,703,273 40,963,137 96.0 28,711 1,135,838 2.7 13,883 567,568 1.3 3,745,867 42,666,543 North Unguja 15,073 176,931 86.5 318 22,286 10.9 57 5,279 2.6 15,263 204,497 South Unguja 10,906 147,943 95.4 95 6,906 4.5 30 213 0.1 10,969 155,062 Urban West 10,770 139,445 60.8 471 80,508 35.1 63 9,420 4.1 11,178 229,373 North Pemba 22,149 233,352 93.5 296 14,695 5.9 117 1,548 0.6 22,397 249,594 South Pemba 19,524 234,798 97.7 200 5,638 2.3 0 . 0.0 19,640 240,436 Zanzibar 78,422 932,469 86.4 1,380 130,034 12.1 267 16,459 1.5 80,069 1,078,962 Total 3,781,695 41,895,605 95.8 30,091 1,265,872 2.9 14,150 584,028 1.3 3,802,125 43,745,505 9.6.1 CHICKEN PRODUCTION: Number of CHICKEN by Type and Region as of 1st October 2008 Region Indigenous chicken Layers Broilers Total Appendix II _____________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 95 Number of Households Number of Indigenous Chicken % Number of Chicken Per Household Number of Households Number of Layers % Number of Chicken Per Household Number of Households Number of Broilers % Number of Chicken Per Household 3,651,983 37,531,488 99.1 10 24,788 211,342 0.6 9 12,001 118,296 0.3 10 45,842 2,615,273 96.7 57 1,249 70,909 2.6 57 307 19,489 0.7 63 4,901 631,224 62.1 129 1,436 236,007 23.2 164 948 149,608 14.7 158 548 185,151 36.7 338 580 181,041 35.8 312 407 138,864 27.5 341 0 . 0.0 . 305 169,203 69.7 555 135 73,527 30.3 546 0 . 0.0 . 353 267,336 79.8 758 85 67,783 20.2 800 3,703,273 40,963,137 96.0 11 28,711 1,135,838 2.7 40 13,883 567,568 1.3 41 Number of Households Number of Indigenous Chicken % Number of Chicken Per Household Number of Households Number of Layers % Number of Chicken Per Household Number of Households Number of Broilers % Number of Chicken Per Household 76,731 795,432 98.8 10 721 7,345 0.9 10 179 1,949 0.2 11 1,306 76,320 88.5 58 145 9,925 11.5 68 0 . 0.0 . 359 50,537 40.5 141 394 59,600 47.8 151 88 14,510 11.6 164 25 10,180 26.6 400 88 28,045 73.4 318 0 . 0.0 . 0 . 0.0 . 31 25,120 100.0 800 0 . 0.0 . 78,422 932,469 86 12 1,380 130,034 12.1 94 267 16,459 1.5 62 Number of Households Number of Indigenous Chicken % Number of Chicken Per Household Number of Households Number of Layers % Number of Chicken Per Household Number of Households Number of Broilers % Number of Chicken Per Household 3,728,714 38,326,920 91.6 10 25,509 218,687 0.5 9 12,179 120,246 0.3 10 47,148 2,691,593 94.1 57 1,395 80,834 2.8 58 307 19,489 0.7 63 5,260 681,761 57.7 130 1,830 295,607 25.0 162 1,036 164,118 13.9 158 573 195,331 34.6 341 669 209,086 37.1 313 407 138,864 24.6 341 0 . 0.0 . 305 169,203 69.7 555 135 73,527 30.3 546 0 . 0.0 . 384 292,455 81.2 761 85 67,783 18.8 800 3,781,695 41,895,605 89.1 11 30,091 1,265,872 2.7 42 14,150 584,028 1.2 41 Layers Broilers Broilers Indigenous chicken Layers 9.6.3 CHICKEN PRODUCTION : Number of Households Keeping Chickens and Average Number of Chickens per Household by Flock Size as of 1st October 2008 - ZANZIBAR Flock Size 9.6.2 CHICKEN PRODUCTION : Number of Households Keeping Chickens and Average Number of Chickens per Household by Flock Size as of 1st October 2008 - MAINLAND 1-49 700+ Total 50-99 100-299 300-499 500-699 Flock Size Indigenous chicken 1-49 50-99 100-299 Layers Broilers 300-499 700+ Total 9.6.4 CHICKEN PRODUCTION : Number of Households Keeping Chickens and Average Number of Chickens per Household by Flock Size as of 1st October 2008 - NATIONAL Flock Size Indigenous chicken 500-699 700+ Total 1-49 50-99 100-299 300-499 Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 96 Dodoma 25,742 946 1,891 1,275 19,337 . 35,199 Arusha 7,410 3,689 3,053 3,487 105,023 71 81,213 Kilimanjaro 26,537 9,175 3,918 20,724 8,143 . 35,981 Tanga 139,148 3,432 3,166 5,611 3,584 . 25,119 Morogoro 80,587 8,691 21,496 9,163 4,149 . 31,707 Pwani 40,695 2,735 3,342 4,936 749 . 16,913 Dar es Salaam 60,193 532 4,498 1,472 . . 10,098 Lindi 35,587 6,071 4,796 . 744 . 3,854 Mtwara 12,845 . 305 . . . 1,096 Ruvuma 20,156 22,020 . 10,354 2,145 . 14,158 Iringa 32,579 473,339 3,478 30,364 3,851 . 43,156 Mbeya 54,349 7,153 15,058 20,595 5,733 . 64,339 Singida 17,194 1,646 1,835 1,112 31,562 . 55,527 Tabora 51,764 2,210 786 1,572 7,253 . 79,824 Rukwa 56,626 6,501 . 8,002 8,489 . 34,367 Kigoma 59,786 292 . 637 . . 3,573 Shinyanga 112,980 8,985 601 . 19,419 . 126,460 Kagera 41,717 2,631 703 10,433 . . 26,940 Mwanza 177,075 4,898 3,516 3,970 5,061 . 108,822 Mara 83,572 6,658 3,848 1,203 10,191 . 130,004 Manyara 20,980 132 7,007 827 61,226 . 71,667 Mainland 1,157,520 571,739 83,297 135,737 296,660 71 1,000,019 North Unguja 10,887 331 305 . 63 . 774 South Unguja 3,901 294 365 97 30 . 710 Urban West 16,077 . 157 722 . . 1,758 North Pemba 2,144 175 . 256 51 . 585 South Pemba 1,270 23 54 186 209 . 386 Zanzibar 34,279 823 881 1,262 353 0 4,214 TOTAL 1,191,799 572,562 84,178 136,999 297,013 71 1,004,233 Number % Type Number 41,895,605 95.8 Ducks 1,191,799 1,265,872 2.9 Guine pigs 572,562 584,028 1.3 Turkeys 84,178 Rabbits 136,999 Donkeys 297,013 Horses 71 Dogs 1,004,233 43,745,505 100 3,286,855 Broiler Horses TOTAL Donkeys Turkeys Guine pigs Indigenous Chicken Layer Rabbits 9.6.5 CHICKEN PRODUCTION: Number of Other Livestock by Type of livestock and Region as of 1st October 2008 Region Type Chicken Others Dogs 9.6.6 : THER LIVESTOCK : Total Number of Livestock by Type as of 1st October 2008 Ducks Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 97 Region Indigenous Chicken Layer Total (Indigenous+Layers) Ducks Turkeys Dodoma 46,162,632 875,623 47,038,255 708,490 80,851 Arusha 49,071,785 445,825 49,517,610 10,383,853 90,078 Kilimanjaro 54,189,121 7,265,014 61,454,134 8,570,889 757,780 Tanga 54,347,507 35,985 54,383,492 3,819,457 1,493,229 Morogoro 47,399,917 796,995 48,196,912 4,721,353 358,534 Pwani 26,107,921 10,971,992 37,079,913 591,524 189,519 Dar es Salaam 8,690,148 61,384,720 70,074,868 833,487 27,404 Lindi 18,290,274 134,446 18,424,720 620,492 17,869 Mtwara 22,404,251 400,928 22,805,179 11,332,872 17,616 Ruvuma 26,910,387 5,130,009 32,040,396 8,995,195 289,139 Iringa 69,126,933 15,031,015 84,157,948 6,560,762 107,570 Mbeya 89,603,692 16,813,672 106,417,364 8,613,675 340,255 Singida 68,769,070 10,632,076 79,401,145 8,408,040 842,701 Tabora 85,305,849 506,489 85,812,337 6,587,031 23,580 Rukwa 32,427,256 142,500 32,569,756 627,845 2,190,298 Kigoma 14,682,959 909,501 15,592,460 428,235 877 Shinyanga 97,606,144 996,284 98,602,427 13,408,823 789,821 Kagera 41,600,610 511,313 42,111,923 2,541,860 5,352,244 Mwanza 64,400,351 6,679,995 71,080,346 2,443,929 3,133,285 Mara 34,462,480 836,735 35,299,215 1,391,053 131,445 Manyara 39,209,246 3,247,148 42,456,394 4,061,179 271,698 Mainland 990,768,532 143,748,263 1,134,516,795 105,650,044 16,505,794 North Unguja 3,896,388 3,908,857 7,805,245 323,601 43,519 South Unguja 7,362,938 494,696 7,857,634 341,657 866,426 Urban West 2,983,545 10,403,112 13,386,657 311,859 7,724 North Pemba 2,765,262 3,375,323 6,140,585 309,245 - South Pemba 3,467,297 478,204 3,945,501 33,470 6,828 Zanzibar 20,475,430 18,660,191 39,135,622 1,319,832 924,497 Total 1,011,243,962 162,408,455 1,173,652,417 106,969,876 17,430,292 9.6.7 CHICKEN PRODUCTION: Number of Eggs by type of chicken and Region during 2007/08 Agricultufre Year Appendix II _______________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 98 Number % Number % Total Livestock Keepers % Dodoma 76,344 33 152,735 67 229,079 100 Arusha 174,354 93 12,507 7 186,861 100 Kilimanjaro 178,331 81 42,164 19 220,495 100 Tanga 218,528 89 28,333 11 246,861 100 Morogoro 54,361 25 159,550 75 213,911 100 Pwani 19,126 16 97,753 84 116,878 100 Dar es Salaam 16,414 58 11,927 42 28,341 100 Lindi 17,680 16 93,520 84 111,199 100 Mtwara 38,070 25 115,202 75 153,272 100 Ruvuma 83,642 50 82,288 50 165,931 100 Iringa 145,622 55 121,051 45 266,673 100 Mbeya 190,313 49 198,926 51 389,239 100 Singida 71,523 39 110,117 61 181,640 100 Tabora 84,174 36 151,540 64 235,713 100 Rukwa 53,001 31 115,957 69 168,958 100 Kigoma 72,826 46 83,823 54 156,649 100 Shinyanga 161,278 39 256,254 61 417,532 100 Kagera 104,416 39 164,675 61 269,091 100 Mwanza 119,893 37 202,967 63 322,859 100 Mara 87,867 46 101,713 54 189,580 100 Manyara 113,846 67 54,879 33 168,725 100 MAINLAND 2,081,610 46 2,357,879 54 4,439,489 100 North Unguja 5,255 29 12,254 71 17,510 100 South Unguja 5,863 44 7,397 56 13,260 100 Urban West 5,778 42 6,971 58 12,748 100 North Pemba 6,035 23 19,556 77 25,591 100 South Pemba 5,182 23 17,089 77 22,272 100 ZANZIBAR 28,113 27 63,267 73 91,380 100 Total 2,109,724 47 2,421,146 53 4,530,870 100 9.7.1: PEST AND PARASITES: Number of Livestock Rearing households deworming Livestock by region during 2007/08 Agriculture Year Region Deworming Livestock Not Deworm Livestock Total Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 99 Households that dewormed Households that DID NOT deworm Not Applicable Total Households that dewormed Households that DID NOT deworm Not Applicable Total Households that dewormed Households that DID NOT deworm Not Applicable Total Households that dewormed Households that DID NOT deworm Not Applicable Total Dodoma 40,143 8,906 29,385 78,434 31,085 13,183 31,504 75,773 18,307 9,660 47,679 75,647 22,110 29,206 24,458 75,773 Arusha 135,875 11,196 28,023 175,094 127,338 13,507 34,164 175,009 8,469 20,864 145,408 174,741 43,425 64,736 67,565 175,725 Kilimanjaro 129,771 6,377 42,765 178,913 106,851 15,871 56,316 179,039 28,943 9,642 140,072 178,656 59,511 85,154 34,585 179,250 Tanga 69,690 10,106 139,694 219,491 87,515 14,880 117,233 219,627 5,443 9,918 204,029 219,390 112,326 75,356 32,043 219,726 Morogoro 11,126 3,471 39,829 54,425 14,412 7,090 35,367 56,869 15,195 6,517 36,202 57,914 29,536 42,071 6,041 77,648 Pwani 7,285 1,169 11,262 19,717 7,230 2,021 10,606 19,857 1,231 1,276 17,042 19,548 10,376 14,931 3,223 28,530 Dar es Salaam 6,088 1,264 9,168 16,520 4,966 2,073 9,443 16,483 1,881 1,517 13,047 16,445 11,888 3,765 1,493 17,146 Lindi 2,470 199 15,086 17,756 6,549 967 10,131 17,646 1,108 513 16,380 18,002 10,547 7,922 3,104 21,573 Mtwara 2,066 1,556 35,303 38,925 16,146 3,549 20,721 40,415 3,288 1,049 34,345 38,681 24,199 18,179 5,411 47,789 Ruvuma 18,164 3,640 62,551 84,354 30,393 19,045 35,085 84,523 49,967 3,807 30,490 84,265 26,841 50,250 9,791 86,882 Iringa 43,216 11,130 92,531 146,876 26,039 16,895 104,135 147,068 69,628 14,466 62,914 147,007 82,097 52,849 13,755 148,702 Mbeya 117,161 15,738 66,279 199,178 46,955 26,953 123,502 197,411 66,434 19,339 111,574 197,346 63,499 111,726 26,606 201,831 Singida 57,613 5,691 12,298 75,602 43,223 16,096 15,364 74,683 4,163 7,481 61,178 72,822 16,813 51,542 6,736 75,092 Tabora 55,204 4,801 25,018 85,024 32,192 19,493 32,801 84,485 3,594 4,726 75,117 83,438 27,533 48,693 9,623 85,848 Rukwa 37,288 1,432 14,104 52,823 18,117 8,544 26,116 52,776 5,527 5,961 41,289 52,776 14,312 31,688 6,841 52,841 Kigoma 18,139 4,071 51,215 73,425 57,888 5,701 10,235 73,825 6,056 5,931 60,279 72,266 15,111 31,441 27,524 74,076 Shinyanga 128,370 6,100 28,061 162,531 70,145 39,131 51,729 161,005 2,991 15,370 142,220 160,581 42,534 92,354 26,119 161,008 Kagera 46,952 3,670 55,259 105,881 63,915 11,145 29,543 104,603 18,588 7,006 79,194 104,787 15,488 50,083 39,741 105,312 Mwanza 91,945 5,232 23,230 120,407 52,507 28,250 38,922 119,679 836 7,361 111,482 119,679 25,946 79,175 15,456 120,577 Mara 66,962 3,985 17,471 88,418 56,704 10,691 20,922 88,317 868 8,123 79,241 88,232 16,738 58,294 13,520 88,552 Manyara 90,687 7,509 16,098 114,293 79,318 15,395 19,208 113,920 21,891 16,507 75,522 113,920 26,613 61,139 26,243 113,995 MAINLAND 1,177,136 145,758 1,082,704 2,405,598 977,062 328,712 1,096,871 2,402,645 330,282 209,319 1,856,084 2,395,685 716,746 1,263,389 480,337 2,460,473 North Unguja 2,376 531 2,482 5,389 881 511 4,002 5,395 0 315 5,048 5,363 2,702 1,887 1,178 5,767 South Unguja 3,931 464 1,689 6,084 1,253 1,123 3,676 6,052 91 324 5,618 6,033 2,372 2,766 1,354 6,492 Urban West 2,857 471 2,638 5,966 691 502 4,773 5,966 157 157 5,621 5,934 3,360 1,915 1,068 6,343 North Pemba 4,353 1,546 1,173 7,073 639 914 4,880 6,433 77 80 5,878 6,035 2,216 4,901 859 7,976 South Pemba 3,567 489 1,292 5,347 645 588 4,066 5,298 142 116 4,956 5,213 1,957 2,840 791 5,588 ZANZIBAR 17,084 3,501 9,273 29,859 4,109 3,638 21,396 29,143 467 992 27,120 28,580 12,607 14,310 5,249 32,166 Total 1,194,220 149,260 1,091,977 2,435,457 981,171 332,350 1,118,268 2,431,789 330,750 210,312 1,883,204 2,424,265 729,353 1,277,699 485,586 2,492,639 9.7.2: PEST AND PARASITES: Number of Livestock Rearing households that dewormed Livestock by type of livestock and region, 2007/08 Agricultural Year Region Cattle Goats/Sheep Pig Chicken Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 100 Number % Number % Number % Number % Dodoma 82,861 37 37,327 16 106,267 47 226,456 100 Arusha 135,897 73 32,911 18 18,013 10 186,821 100 Kilimanjaro 71,781 33 114,917 52 33,869 15 220,568 100 Tanga 94,566 39 42,988 18 107,460 44 245,014 100 Morogoro 21,846 10 33,175 16 156,374 74 211,395 100 Pwani 11,940 11 6,155 5 95,459 84 113,554 100 Dar es 5,435 20 4,452 16 17,789 64 27,677 100 Lindi 6,679 6 10,599 10 93,473 84 110,751 100 Mtwara 15,387 10 21,678 15 111,749 75 148,815 100 Ruvuma 27,290 17 50,850 31 86,413 53 164,553 100 Iringa 54,760 20 53,216 20 160,282 60 268,258 100 Mbeya 143,679 36 84,005 21 168,465 43 396,149 100 Singida 80,048 43 33,690 18 70,299 38 184,037 100 Tabora 92,322 39 31,541 13 112,899 48 236,762 100 Rukwa 57,678 34 30,712 18 80,793 48 169,183 100 Kigoma 59,634 38 54,587 35 42,932 27 157,154 100 Shinyanga 214,722 51 56,391 13 147,272 35 418,385 100 Kagera 102,699 39 89,892 34 70,582 27 263,173 100 Mwanza 152,273 48 65,860 21 99,208 31 317,341 100 Mara 109,078 58 23,511 12 55,678 30 188,267 100 Manyara 114,626 68 25,810 15 27,177 16 167,612 100 MAINLAND 1,655,203 37 904,269 20 1,862,452 42 4,421,923 2100 North Unguja 4,090 23 2,866 16 10,623 60 17,579 100 South Unguja 5,401 41 2,572 19 5,288 40 13,260 100 Urban West 3,611 27 2,418 18 7,316 55 13,345 100 North Pemba 8,838 34 5,686 22 11,143 43 25,668 100 South Pemba 8,182 36 3,627 16 10,649 47 22,458 100 ZANZIBAR 30,121 33 17,169 19 45,019 49 92,309 500 Total 1,685,324 37 921,438 20 1,907,470 42 4,514,232 2,200 9.7.3 PEST AND PARASITES: Number of Livestock Rearing Households Normally Encountering Tick Problems by Region during 2007/08 Agriculture Year Region Tick Problem No Tick Problem Not Applicable Total Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 101 Number % Number % Number % Number % Number % Number % Dodoma 25,793 11.4 53,499 23.7 12,678 5.6 130,718 57.9 3,015 1.3 225,704 100 Arusha 14,463 7.7 121,483 65.0 7,242 3.9 42,634 22.8 998 0.5 186,821 100 Kilimanjaro 6,642 3.0 59,857 27.1 13,919 6.3 138,754 62.9 1,396 0.6 220,568 100 Tanga 19,128 7.8 47,183 19.2 7,311 3.0 171,111 69.8 513 0.2 245,246 100 Morogoro 3,646 1.7 20,062 9.5 9,587 4.5 177,751 84.1 349 0.2 211,395 100 Pwani 837 0.7 11,898 10.5 2,719 2.4 98,099 86.4 0 0.0 113,554 100 Dar es Salaam 895 3.2 5,366 19.4 2,806 10.1 18,611 67.2 0 0.0 27,677 100 Lindi 1,416 1.3 3,609 3.3 5,729 5.2 99,730 90.1 173 0.2 110,656 100 Mtwara 1,817 1.2 7,837 5.3 1,467 1.0 137,406 92.3 288 0.2 148,815 100 Ruvuma 6,212 3.8 17,452 10.6 5,661 3.4 134,837 82.0 266 0.2 164,428 100 Iringa 30,782 11.5 24,943 9.3 11,348 4.2 200,071 74.6 934 0.3 268,079 100 Mbeya 23,511 5.9 111,028 28.0 13,845 3.5 245,413 61.9 2,556 0.6 396,353 100 Singida 19,744 10.7 53,940 29.3 14,998 8.1 94,745 51.5 610 0.3 184,037 100 Tabora 15,929 6.7 68,218 28.8 10,396 4.4 142,067 60.0 153 0.1 236,762 100 Rukwa 7,438 4.4 42,913 25.4 3,233 1.9 115,553 68.3 47 0.0 169,183 100 Kigoma 14,596 9.3 41,010 26.1 8,816 5.6 91,735 58.4 811 0.5 156,967 100 Shinyanga 14,820 3.5 199,780 47.8 22,105 5.3 179,864 43.0 1,816 0.4 418,385 100 Kagera 7,873 3.0 79,352 30.2 16,212 6.2 156,576 59.5 3,160 1.2 263,173 100 Mwanza 12,602 4.0 123,912 39.0 7,961 2.5 170,296 53.7 2,569 0.8 317,341 100 Mara 10,586 5.6 82,589 43.9 6,389 3.4 84,847 45.1 3,856 2.0 188,267 100 Manyara 17,060 10.2 99,656 59.5 7,268 4.3 42,685 25.5 942 0.6 167,612 100 MAINLAND 255,791 5.8 1,275,587 28.9 191,690 4.3 2,673,502 60.5 24,452 0.6 4,421,022 100 North Unguja 664 3.8 2,270 12.9 995 5.7 13,479 76.7 171 1.0 17,579 100 South Unguja 491 3.7 2,973 22.4 2,007 15.1 7,683 57.9 107 0.8 13,260 100 Urban West 408 3.1 2,512 18.8 1,978 14.8 8,289 62.1 157 1.2 13,345 100 North Pemba 1,579 6.2 4,408 17.2 1,675 6.5 17,191 67.0 815 3.2 25,668 100 South Pemba 882 3.9 5,142 22.9 952 4.2 14,738 65.6 743 3.3 22,458 100 ZANZIBAR 4,024 4.4 17,304 18.7 7,607 8.2 61,380 66.5 1,994 2.2 92,309 100 Total 259,815 5.8 1,292,891 28.6 199,297 4.4 2,734,882 60.6 26,445 0.6 4,513,331 100 Other Total 9.7.4 PEST AND PARASITES: Number of Livestock Rearing Households by Method of Tick Control and Region during 2007/08 Agriculture Year Region Dipping Spraying Smearing None Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 102 Number % Number % Number % Number % Dodoma 29,249 13 81,566 36 115,640 51 226,456 100 Arusha 90,817 49 74,326 40 21,677 12 186,821 100 Kilimanjaro 33,771 15 146,926 67 39,871 18 220,568 100 Tanga 46,432 19 88,100 36 110,714 45 245,246 100 Morogoro 12,460 6 34,888 17 164,047 78 211,395 100 Pwani 6,804 6 11,243 10 95,615 84 113,662 100 Dar es 3,585 13 5,875 21 18,216 66 27,677 100 Lindi 2,061 2 14,198 13 94,397 85 110,656 100 Mtwara 4,587 3 31,989 21 112,240 75 148,815 100 Ruvuma 11,735 7 70,549 43 82,144 50 164,428 100 Iringa 14,139 5 82,262 31 171,969 64 268,370 100 Mbeya 31,059 8 176,719 45 188,574 48 396,353 100 Singida 26,161 14 80,098 44 77,777 42 184,037 100 Tabora 14,745 6 99,225 42 122,792 52 236,762 100 Rukwa 11,366 7 69,140 41 88,676 52 169,183 100 Kigoma 12,135 8 79,701 51 65,317 42 157,154 100 Shinyanga 35,319 8 203,119 49 179,948 43 418,385 100 Kagera 11,736 4 145,310 55 106,127 40 263,173 100 Mwanza 15,311 5 165,828 52 136,202 43 317,341 100 Mara 30,770 16 88,312 47 69,185 37 188,267 100 Manyara 45,359 27 86,749 52 35,504 21 167,612 100 MAINLAND 489,601 11 1,836,124 42 2,096,635 47 4,422,360 100 North Unguja 588 3 5,090 29 11,902 68 17,579 100 South 466 4 6,675 50 6,119 46 13,260 100 Urban West 471 4 5,307 40 7,567 57 13,345 100 North Pemba 914 4 13,366 52 11,388 44 25,668 100 South 1,117 5 10,700 48 10,641 47 22,458 100 ZANZIBAR 3,556 4 41,137 45 47,617 52 92,309 100 Total 493,156 11 1,877,260 42 2,144,252 47 4,514,669 100 9.7.5 PEST AND PARASITES: Number of Livestock Rearing Households normally Encountering Tsetse Flies Problems by Region during 2007/08 Agriculture Year Region Households Encoutering Tsetse problems Households Without Tsetse Problems Not Applicable Total Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 103 Number % Number % Number % Number % Number % Number % Dodoma 9,134 4 22,863 10 10,433 5 173,334 77 9,939 4 225,704 100 Arusha 9,199 5 67,292 36 7,641 4 93,396 50 9,293 5 186,821 100 Kilimanjaro 4,422 2.0 25,812 11.7 13,074 5.9 172,161 78.1 5,099 2.3 220,568 100 Tanga 10,451 4.3 19,827 8.1 6,681 2.7 206,265 84.1 2,078 0.8 245,302 100 Morogoro 2,262 1.1 12,912 6.1 9,291 4.4 185,778 87.9 1,152 0.5 211,395 100 Pwani 772 0.7 8,207 7.2 2,274 2.0 102,103 89.9 198 0.2 113,554 100 Dar es Salaam 802 2.9 4,107 14.8 2,179 7.9 20,478 74.0 111 0.4 27,677 100 Lindi 734 0.7 1,759 1.6 6,011 5.4 102,029 92.2 123 0.1 110,656 100 Mtwara 469 0.3 2,622 1.8 1,819 1.2 143,793 96.6 112 0.1 148,815 100 Ruvuma 2,689 1.6 11,056 6.7 5,484 3.3 144,949 88.2 250 0.2 164,428 100 Iringa 11,740 4.4 13,007 4.9 12,781 4.8 230,147 85.8 476 0.2 268,151 100 Mbeya 7,410 1.9 29,754 7.5 15,023 3.8 342,664 86.5 1,502 0.4 396,353 100 Singida 2,874 1.6 16,519 9.0 15,143 8.2 146,088 79.4 3,413 1.9 184,037 100 Tabora 4,489 1.9 13,981 5.9 9,252 3.9 208,586 88.1 455 0.2 236,762 100 Rukwa 2,454 1.5 13,680 8.1 2,784 1.6 149,912 88.6 353 0.2 169,183 100 Kigoma 5,584 3.6 13,410 8.5 9,142 5.8 128,645 82.0 187 0.1 156,967 100 Shinyanga 10,682 2.6 47,350 11.3 27,608 6.6 329,464 78.7 3,281 0.8 418,385 100 Kagera 3,749 1.4 15,135 5.8 7,513 2.9 236,106 89.7 669 0.3 263,173 100 Mwanza 2,895 0.9 19,932 6.3 8,587 2.7 285,677 90.0 251 0.1 317,341 100 Mara 8,543 4.5 27,934 14.8 5,659 3.0 144,899 77.0 1,232 0.7 188,267 100 Manyara 6,800 4.1 35,063 20.9 5,620 3.4 115,998 69.2 4,132 2.5 167,612 100 MAINLAND 106,883 2.5 405,677 9.4 133,736 3.1 3,622,500 84.0 44,035 1.0 4,312,832 100 North Unguja 259 1.5 538 3.1 683 3.9 16,067 91.4 32 0.2 17,579 100 South Unguja 49 0.4 499 3.8 902 6.8 11,811 89.1 0 0.0 13,260 100 Urban West 63 0.5 659 4.9 1,507 11.3 11,021 82.6 94 0.7 13,345 100 North Pemba 216 0.8 1,163 4.5 863 3.4 23,375 91.1 51 0.2 25,668 100 South Pemba 352 1.6 873 3.9 663 3.0 20,516 91.4 54 0.2 22,458 100 ZANZIBAR 939 1.1 3,732 6.3 4,618 12.5 82,789 90.3 230 0.3 92,309 100 Total 107,822 2.4 409,410 9.4 138,355 4.2 3,705,289 83.0 44,266 1.0 4,405,141 100 Other Total 9.7. 6 PEST AND PARASITES: Number of Livestock Rearing Households by Method of Tsetse Flies Control and Region during 2007/08 Agriculture Year Region Dipping Spraying Trappig None Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 104 Number % Number % Number % Number % Dodoma 150,254 66 47,039 21 29,162 13 226,456 100 Arusha 76,806 41 39,031 21 70,984 38 186,821 100 Kilimanjaro 106,212 48 83,606 38 30,750 14 220,568 100 Tanga 165,400 67 51,195 21 28,567 12 245,162 100 Morogoro 147,741 70 48,552 23 15,103 7 211,395 100 Pwani 71,926 63 35,051 31 6,577 6 113,554 100 Dar es 18,700 68 7,252 26 1,726 6 27,677 100 Lindi 83,366 75 23,300 21 3,990 4 110,656 100 Mtwara 101,905 68 37,645 25 9,265 6 148,815 100 Ruvuma 101,803 62 53,312 32 9,312 6 164,428 100 Iringa 155,483 58 85,235 32 27,513 10 268,231 100 Mbeya 262,665 66 93,935 24 39,753 10 396,353 100 Singida 104,929 57 58,148 32 20,960 11 184,037 100 Tabora 146,326 62 72,176 30 18,260 8 236,762 100 Rukwa 103,503 61 49,259 29 16,421 10 169,183 100 Kigoma 62,637 40 50,228 32 44,289 28 157,154 100 Shinyanga 257,498 62 114,152 27 46,616 11 418,266 100 Kagera 71,451 27 123,643 47 68,226 26 263,320 100 Mwanza 189,651 60 101,158 32 26,532 8 317,341 100 Mara 109,598 58 64,691 34 13,977 7 188,267 100 Manyara 90,261 54 46,036 27 31,315 19 167,612 100 MAINLAND 2,578,115 59 1,284,642 29 559,299 11 4,422,056 100 North Unguja 10,092 57 5,455 31 2,032 12 17,579 100 South 7,239 55 4,040 30 1,981 15 13,260 100 Urban West 8,446 63 3,266 24 1,633 12 13,345 100 North Pemba 14,291 56 8,007 31 3,369 13 25,668 100 South 13,462 60 6,842 30 2,153 10 22,458 100 ZANZIBAR 53,530 58 27,611 30 11,168 12 92,309 100 Total 2,631,645 58 1,312,253 29 570,467 13 4,514,365 100 9.7.7: PEST AND PARASITES: Number of Livestock Rearing Households normally Encountering Newcastle Disease Problems by Region during 2007/08 Agriculture Year Region Households Encoutering Newcastle Disease problems Households NOT Encoutering Newcastle Disease problems Not Applicable Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 105 Number % Number % Number % Number % Dodoma 54,621 24 65,916 29 105,919 47 226,456 100 Arusha 29,122 16 44,831 24 112,868 60 186,821 100 Kilimanjaro 49,662 23 61,017 28 109,888 50 220,568 100 Tanga 52,393 21 66,178 27 126,675 52 245,246 100 Morogoro 66,002 31 48,024 23 97,369 46 211,395 100 Pwani 28,267 25 31,099 27 54,188 48 113,554 100 Dar es Salaam 11,717 42 8,009 29 7,951 29 27,677 100 Lindi 14,589 13 19,551 18 76,516 69 110,656 100 Mtwara 42,644 29 19,390 13 86,781 58 148,815 100 Ruvuma 46,427 28 39,871 24 78,129 48 164,428 100 Iringa 114,052 43 63,343 24 90,836 34 268,231 100 Mbeya 138,641 35 85,518 22 172,194 43 396,353 100 Singida 18,309 10 77,098 42 88,629 48 184,037 100 Tabora 31,245 13 85,486 36 120,031 51 236,762 100 Rukwa 44,689 26 38,006 22 86,488 51 169,183 100 Kigoma 32,404 21 23,059 15 101,504 65 156,967 100 Shinyanga 96,979 23 119,802 29 201,604 48 418,385 100 Kagera 14,838 6 49,041 19 199,215 76 263,094 100 Mwanza 46,150 15 92,713 29 178,478 56 317,341 100 Mara 21,661 12 72,187 38 94,420 50 188,267 100 Manyara 28,424 17 51,543 31 87,645 52 167,612 100 MAINLAND 977,586 23 1,131,475 26 2,203,771 51 4,312,832 100 North Unguja 1,461 8 2,946 17 13,172 75 17,579 100 South Unguja 1,462 11 2,610 20 9,188 69 13,260 100 Urban West 2,386 18 2,512 19 8,446 63 13,345 100 North Pemba 2,321 9 3,195 12 20,152 79 25,668 100 South Pemba 1,964 9 2,197 10 18,296 81 22,458 100 ZANZIBAR 9,594 10 13,459 14 69,255 76 92,309 100 Total 987,180 22 1,144,934 26 2,273,027 52 4,405,141 100 9.7.8: PEST AND PARASITES: Number of Livestock Rearing Households by Method of Newcastle Disease Control and Region during 2007/08 Agriculture Year Region Vaccination Local Herbs None Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 106 Number % Number % Number % Number % Dodoma 56,480 25 134,021 59 35,954 16 226,456 100 Arusha 37,799 20 73,414 39 75,608 40 186,821 100 Kilimanjaro 38,552 17 150,732 68 31,284 14 220,568 100 Tanga 73,651 30 139,845 57 31,751 13 245,246 100 Morogoro 74,086 35 121,930 58 15,379 7 211,395 100 Pwani 30,597 27 77,433 68 5,524 5 113,554 100 Dar es 8,316 30 17,443 63 1,918 7 27,677 100 Lindi 38,439 35 67,517 61 4,699 4 110,656 100 Mtwara 60,013 40 77,797 52 11,005 7 148,815 100 Ruvuma 38,152 23 114,063 69 12,213 7 164,428 100 Iringa 69,409 26 171,130 64 27,831 10 268,370 100 Mbeya 130,499 33 222,408 56 43,446 11 396,353 100 Singida 72,363 39 89,597 49 22,076 12 184,037 100 Tabora 87,285 37 129,273 55 20,204 9 236,762 100 Rukwa 42,315 25 109,676 65 17,193 10 169,183 100 Kigoma 31,969 20 79,116 50 46,068 29 157,154 100 Shinyanga 154,928 37 211,734 51 51,723 12 418,385 100 Kagera 29,659 11 162,163 62 71,453 27 263,275 100 Mwanza 94,504 30 189,424 60 33,412 11 317,341 100 Mara 68,597 36 101,942 54 17,728 9 188,267 100 Manyara 49,385 29 82,944 49 35,283 21 167,612 100 MAINLAND 1,279,808 30 2,490,269 58 542,754 13 4,312,832 100 North Unguja 2,910 17 11,918 68 2,752 16 17,579 100 South 1,811 14 9,436 71 2,014 15 13,260 100 Urban West 4,019 30 7,473 56 1,853 14 13,345 100 North Pemba 6,932 27 14,980 58 3,756 15 25,668 100 South 4,365 19 15,589 69 2,504 11 22,458 100 ZANZIBAR 20,036 22 59,395 65 12,878 13 92,309 100 Total 1,299,844 29 2,549,664 57 555,633 14 4,405,141 100 9.7.9 PEST AND PARASITES: Number of Livestock Rearing Households normally Encountering Fowl Typhoid Disease Problems by Region during 2007/08 Agriculture Year Region Households Encoutering Fowl Typhoid Disease problems Households NOT Encoutering Fowl Typhoid Disease problems Not Applicable Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 107 Number % Number % Number % Number % Dodoma 11,844 5 44,443 20 170,169 75 226,456 100 Arusha 9,223 5 32,283 17 145,314 78 186,821 100 Kilimanjaro 16,669 8 31,454 14 172,445 78 220,568 100 Tanga 11,380 5 35,504 14 198,363 81 245,246 100 Morogoro 14,729 7 38,273 18 158,393 75 211,395 100 Pwani 6,563 6 20,112 18 86,879 77 113,554 100 Dar es Salaam 6,223 22 4,680 17 16,774 61 27,677 100 Lindi 3,967 4 11,623 10 95,269 86 110,859 100 Mtwara 9,451 6 16,445 11 123,044 83 148,939 100 Ruvuma 7,975 5 25,827 16 130,626 79 164,428 100 Iringa 31,907 12 61,376 23 175,087 65 268,370 100 Mbeya 40,054 10 71,426 18 284,873 72 396,353 100 Singida 4,900 3 61,587 33 117,550 64 184,037 100 Tabora 12,924 5 58,456 25 165,383 70 236,762 100 Rukwa 8,541 5 37,621 22 123,021 73 169,183 100 Kigoma 9,688 6 28,024 18 119,255 76 156,967 100 Shinyanga 42,163 10 108,417 26 268,174 64 418,754 100 Kagera 9,057 3 25,315 10 228,722 87 263,094 100 Mwanza 19,279 6 53,023 17 245,040 77 317,341 100 Mara 10,092 5 53,304 28 124,870 66 188,267 100 Manyara 7,999 5 41,178 25 118,594 71 167,770 100 MAINLAND 294,627 7 860,370 19 3,267,843 74 4,422,839 100 North Unguja 499 3 1,429 8 15,651 89 17,579 100 South Unguja 355 3 1,089 8 11,847 89 13,291 100 Urban West 848 6 1,664 12 10,833 81 13,345 100 North Pemba 753 3 2,891 11 22,023 86 25,668 100 South Pemba 516 2 1,487 7 20,455 91 22,458 100 ZANZIBAR 2,971 3 8,560 9 80,809 88 92,339 100 Total 297,597 7 868,930 19 3,348,652 74 4,515,179 100 9.7.10 PEST AND PARASITES: Number of Livestock Rearing Households by Method of Fowl typhoid Desease Control and Region during 2007/08 Agriculture Year Region Vaccination Local Herbs None Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 108 Number % Number % Number % Number % Dodoma 12,100 5 68,732 30 146,388 64 227,221 100 Arusha 31,410 17 118,971 64 36,529 20 186,910 100 Kilimanjaro 32,540 15 118,472 54 69,556 32 220,568 100 Tanga 18,015 7 62,629 25 165,151 67 245,795 100 Morogoro 2,433 1 19,692 9 185,260 89 207,385 100 Pwani 3,023 3 9,840 9 95,605 88 108,468 100 Dar es Salaam 3,259 12 3,426 12 20,991 76 27,677 100 Lindi 282 0 3,976 4 100,521 96 104,779 100 Mtwara 866 1 6,375 5 130,730 95 137,971 100 Ruvuma 1,482 1 26,218 16 135,735 83 163,435 100 Iringa 9,608 4 53,409 20 203,545 76 266,563 100 Mbeya 15,046 4 170,230 43 207,137 53 392,412 100 Singida 13,051 7 88,737 49 81,169 44 182,957 100 Tabora 9,628 4 89,743 38 136,360 58 235,731 100 Rukwa 8,944 5 62,465 37 98,111 58 169,520 100 Kigoma 5,823 4 26,599 17 122,735 79 155,156 100 Shinyanga 14,631 3 218,180 52 185,814 44 418,625 100 Kagera 23,486 9 50,066 19 190,822 72 264,374 100 Mwanza 20,382 6 132,831 42 164,034 52 317,247 100 Mara 7,742 4 94,751 50 85,774 46 188,267 100 Manyara 14,506 9 110,719 66 42,611 25 167,836 100 MAINLAND 248,258 6 1,536,060 35 2,604,578 59 4,388,896 100 North Unguja 780 5 4,335 25 12,149 70 17,264 100 South Unguja 1,443 11 5,261 41 6,162 48 12,867 100 Urban West 1,507 12 3,360 26 8,101 62 12,968 100 North Pemba 413 2 13,842 56 10,371 42 24,626 100 South Pemba 369 2 10,470 47 11,350 51 22,190 100 ZANZIBAR 4,513 5 37,268 41 48,133 54 89,914 100 Total 252,772 6 1,573,328 35 2,652,711 59 4,478,810 100 9.7.11 PEST AND PARASITES: Number of Livestock Rearing Households Vaccinating Livestock against Foot and Mouth Disease by Region during 2007/08 Agriculture Year Region Households Vaccinating Livestock Against Foot and Mouth Households NOT Vaccinating Livestock Against Foot and Mouth Not Applicable Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 109 Number % Number % Number % Number % Dodoma 9,510 4 72,453 32 145,216 64 227,178 100 Arusha 44,562 24 106,796 57 35,552 19 186,910 100 Kilimanjaro 36,967 17 115,018 52 68,583 31 220,568 100 Tanga 17,812 7 63,176 26 164,398 67 245,387 100 Morogoro 2,613 1 19,612 9 184,953 89 207,177 100 Pwani 1,799 2 11,273 10 95,206 88 108,278 100 Dar es Salaam 3,067 11 3,803 14 20,806 75 27,677 100 Lindi 264 0 3,899 4 100,692 96 104,855 100 Mtwara 723 1 6,655 5 130,501 95 137,879 100 Ruvuma 1,806 1 26,818 16 134,679 82 163,303 100 Iringa 5,154 2 56,626 21 204,716 77 266,497 100 Mbeya 11,408 3 170,420 43 210,584 54 392,412 100 Singida 13,143 7 88,123 48 81,635 45 182,901 100 Tabora 8,764 4 90,238 38 136,586 58 235,589 100 Rukwa 4,310 3 67,027 40 98,071 58 169,408 100 Kigoma 2,193 1 26,491 17 126,326 81 155,010 100 Shinyanga 12,014 3 220,460 53 185,882 44 418,356 100 Kagera 6,830 3 66,745 25 190,754 72 264,328 100 Mwanza 13,606 4 139,478 44 164,163 52 317,247 100 Mara 7,395 4 96,455 51 84,653 45 188,503 100 Manyara 22,256 13 104,529 62 40,976 24 167,761 100 MAINLAND 226,196 5 1,556,096 36 2,604,933 59 4,387,226 100 North Unguja 1,123 7 4,168 24 11,972 69 17,264 100 South Unguja 1,991 15 4,868 38 6,069 47 12,927 100 Urban West 1,664 13 3,077 24 8,227 63 12,968 100 North Pemba 1,828 7 12,372 50 10,396 42 24,597 100 South Pemba 1,227 6 9,430 42 11,563 52 22,221 100 ZANZIBAR 7,834 8 33,916 38 48,227 54 89,977 100 Total 234,030 5 1,590,013 36 2,653,160 59 4,477,203 100 9.7.12 PEST AND PARASITES: Number of Livestock Rearing Households normally Encountering Lympyskin Disease Problems by Region during 2007/08 Agriculture Region Households Encoutering Lympyskin Disease Households NOT Encoutering Lympyskin Disease Not Applicable Total Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 110 Number % Number % Dodoma 151,873 68 71,507 32 223,380 Arusha 131,712 71 53,727 29 185,440 Kilimanjaro 163,746 74 57,176 26 220,921 Tanga 124,950 51 121,120 49 246,070 Morogoro 100,217 48 107,454 52 207,671 Pwani 56,014 50 57,058 50 113,072 Dar es Salaam 18,515 67 9,003 33 27,518 Lindi 24,065 22 86,568 78 110,632 Mtwara 50,867 34 98,290 66 149,158 Ruvuma 70,129 43 92,357 57 162,486 Iringa 177,915 69 81,587 31 259,503 Mbeya 261,267 68 122,185 32 383,452 Singida 84,975 49 87,546 51 172,522 Tabora 104,206 45 127,891 55 232,097 Rukwa 68,550 40 101,303 60 169,854 Kigoma 86,651 58 61,883 42 148,534 Shinyanga 227,076 57 171,694 43 398,770 Kagera 120,173 46 141,319 54 261,492 Mwanza 132,302 42 183,040 58 315,342 Mara 108,121 57 80,079 43 188,200 Manyara 124,730 75 40,585 25 165,315 Mainland 2,388,056 55 1,953,372 45 4,341,427 North Unguja 5,526 32 11,984 68 17,510 South Unguja 4,994 38 8,267 62 13,260 Urban West 5,212 41 7,536 59 12,748 North Pemba 3,912 15 21,678 85 25,591 South Pemba 3,692 17 18,580 83 22,272 Zanzibar 23,336 26 68,045 74 91,380 National 2,411,391 54 2,021,416 46 4,432,808 9.8.1 LIVESTOCK EXTENSION: Number of households receiving extension advice by region during the 2007/08 agriculture year Receiving Livestock services Total Livestock Keepers Region Not Receiving Livestock Extension Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 111 Number % Number % Number % Number % Number % Number % Dodoma 141,677 93.3 17,029 11.2 5,018 3.3 5,135 3.4 34,387 22.6 17,190 11.3 151,873 Arusha 124,493 94.5 32,845 24.9 6,238 4.7 5,906 4.5 14,277 10.8 14,792 11.2 131,712 Kilimanjaro 155,916 95.2 24,413 14.9 15,598 9.5 7,576 4.6 34,958 21.3 24,680 15.1 163,746 Tanga 113,735 91.0 9,953 8.0 2,572 2.1 1,522 1.2 6,269 5.0 13,095 10.5 124,950 Morogoro 84,221 84.0 11,931 11.9 1,897 1.9 1,267 1.3 10,860 10.8 13,229 13.2 100,217 Pwani 50,930 90.9 4,806 8.6 1,699 3.0 2,200 3.9 10,366 18.5 4,364 7.8 56,014 Dar es Salaam 15,334 82.8 2,308 12.5 307 1.7 1,385 7.5 2,795 15.1 2,835 15.3 18,515 Lindi 21,227 88.2 1,330 5.5 669 2.8 421 1.7 1,397 5.8 2,364 9.8 24,065 Mtwara 44,837 88.1 3,417 6.7 2,523 5.0 729 1.4 5,879 11.6 7,361 14.5 50,867 Ruvuma 58,994 84.1 6,112 8.7 876 1.2 397 0.6 8,335 11.9 9,029 12.9 70,129 Iringa 166,589 93.6 18,740 10.5 6,231 3.5 2,076 1.2 9,222 5.2 15,712 8.8 177,915 Mbeya 229,357 87.8 22,808 8.7 9,878 3.8 6,589 2.5 26,855 10.3 45,228 17.3 261,267 Singida 81,001 95.3 5,178 6.1 1,109 1.3 1,404 1.7 8,761 10.3 8,545 10.1 84,975 Tabora 93,113 89.4 15,825 15.2 8,617 8.3 13,926 13.4 24,359 23.4 18,581 17.8 104,206 Rukwa 57,873 84.4 6,905 10.1 702 1.0 1,706 2.5 10,496 15.3 12,972 18.9 68,550 Kigoma 76,296 88.1 12,245 14.1 2,769 3.2 1,543 1.8 7,241 8.4 6,850 7.9 86,651 Shinyanga 211,141 93.0 25,542 11.2 6,799 3.0 9,287 4.1 19,819 8.7 15,296 6.7 227,076 Kagera 100,657 83.8 14,718 12.2 3,860 3.2 3,560 3.0 10,941 9.1 23,884 19.9 120,173 Mwanza 123,225 93.1 14,628 11.1 2,929 2.2 3,627 2.7 13,475 10.2 13,416 10.1 132,302 Mara 97,737 90.4 18,550 17.2 3,877 3.6 1,558 1.4 17,044 15.8 8,238 7.6 108,121 Manyara 119,774 96.0 19,576 15.7 4,543 3.6 4,779 3.8 10,474 8.4 19,100 15.3 124,730 Mainland 2,168,128 90.8 288,858 12.1 88,709 3.7 76,593 3.2 288,211 12.1 296,759 12.4 2,388,056 North Unguja 3,398 61.5 474 8.6 413 7.5 773 14.0 1,423 25.7 1,675 30.3 5,526 South Unguja 2,894 57.9 1,024 20.5 339 6.8 1,161 23.3 645 12.9 1,271 25.5 4,994 Urban West 2,041 39.2 1,444 27.7 314 6.0 1,036 19.9 1,413 27.1 1,444 27.7 5,212 North Pemba 2,834 72.4 417 10.7 0 0.0 204 5.2 337 8.6 504 12.9 3,912 South Pemba 2,620 71.0 333 9.0 0 0.0 89 2.4 677 18.3 339 9.2 3,692 Zanzibar 13,786 59.1 3,692 15.8 1,066 4.6 3,264 14.0 4,494 19.3 5,234 22.4 23,336 Total 2,181,914 90.5 292,550 12.1 89,775 3.7 79,857 3.3 292,705 12.1 301,993 12.5 2,411,391 9.8.2 LIVESTOCK EXTENSION: Number of Households receiving Livestock advice (overall) By Source of Extension and Region during the 2007/08 agriculture year Region Source of Livestock Extension Number of Household receiving Extension Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 112 Number % Number % Number % Number % Number % Number % (Specify) % Dodoma 69,738 87.4 2,725 3.4 0 0.0 632 0.8 4,401 5.5 2,301 2.9 0 0.0 79,798 Arusha 58,326 88.4 3,714 5.6 178 0.3 711 1.1 1,333 2.0 1,642 2.5 89 0.1 65,993 Kilimanjaro 97,878 86.4 4,211 3.7 288 0.3 721 0.6 6,912 6.1 3,080 2.7 140 0.1 113,231 Tanga 45,334 91.6 1,210 2.4 45 0.1 195 0.4 510 1.0 2,221 4.5 0 0.0 49,516 Morogoro 35,855 82.8 2,707 6.3 284 0.7 105 0.2 2,144 5.0 2,165 5.0 35 0.1 43,296 Pwani 27,770 90.7 984 3.2 415 1.4 58 0.2 937 3.1 409 1.3 45 0.1 30,617 Dar es Salaam 8,064 77.0 1,084 10.4 42 0.4 149 1.4 489 4.7 555 5.3 85 0.8 10,468 Lindi 4,719 82.9 393 6.9 0 0.0 0 0.0 182 3.2 398 7.0 0 0.0 5,693 Mtwara 15,518 81.9 397 2.1 112 0.6 112 0.6 1,553 8.2 1,255 6.6 0 0.0 18,947 Ruvuma 28,059 81.4 1,737 5.0 0 0.0 87 0.3 3,350 9.7 1,232 3.6 0 0.0 34,465 Iringa 88,894 91.4 3,119 3.2 617 0.6 443 0.5 1,450 1.5 2,769 2.8 0 0.0 97,291 Mbeya 104,893 84.8 4,765 3.9 567 0.5 1,770 1.4 3,792 3.1 7,386 6.0 471 0.4 123,643 Singida 32,432 93.2 477 1.4 0 0.0 360 1.0 438 1.3 914 2.6 180 0.5 34,801 Tabora 39,209 82.4 1,688 3.5 425 0.9 2,086 4.4 2,601 5.5 1,424 3.0 126 0.3 47,558 Sumbawanga 19,833 79.9 924 3.7 0 0.0 335 1.4 2,405 9.7 1,330 5.4 0 0.0 24,827 Kigoma 27,119 87.4 1,819 5.9 0 0.0 0 0.0 731 2.4 1,358 4.4 0 0.0 31,028 Shinyanga 88,569 90.2 2,923 3.0 0 0.0 881 0.9 3,626 3.7 2,224 2.3 0 0.0 98,222 Kagera 40,994 76.8 3,529 6.6 698 1.3 854 1.6 1,883 3.5 5,288 9.9 102 0.2 53,348 Mwanza 40,161 89.4 1,941 4.3 0 0.0 380 0.8 1,374 3.1 1,065 2.4 0 0.0 44,921 Mara 33,023 86.9 2,401 6.3 0 0.0 0 0.0 2,149 5.7 420 1.1 0 0.0 37,992 Manyara 53,981 87.8 3,463 5.6 0 0.0 790 1.3 1,677 2.7 1,579 2.6 0 0.0 61,489 Mainland 960,369 86.7 46,212 4.2 3,671 0.3 10,670 1.0 43,938 4.0 41,013 3.7 1,272 0.1 1,107,145 North Unguja 1,769 62.3 63 2.2 76 2.7 196 6.9 216 7.6 520 18.3 0 0.0 2,840 South Unguja 722 42.9 367 21.8 0 0.0 229 13.6 182 10.8 182 10.8 0 0.0 1,682 Urban West 973 32.0 283 9.3 94 3.1 377 12.4 722 23.7 597 19.6 0 0.0 3,046 North Pemba 611 67.1 132 14.5 0 0.0 88 9.6 51 5.6 29 3.2 0 0.0 911 South Pemba 778 68.5 160 14.1 0 0.0 36 3.1 77 6.8 85 7.5 0 0.0 1,135 Zanzibar 4,853 50.5 1,004 10.4 171 1.8 925 9.6 1,248 13.0 1,413 14.7 0 0.0 9,615 Total 965,222 86.4 47,216 4.2 3,841 0.3 11,595 1.0 45,187 4.0 42,427 3.8 1,272 0.1 1,116,760 Total Number of households 9.8.3 LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Feeds and ProperFeeding by Source and Region During 2007/08griculture Year Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Region Source of Livestock Extension Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 113 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 89,676 85.8 3,342 3.2 0 0.0 1,272 1.2 5,897 5.6 4,227 4.0 125 0.1 104,538 Arusha 67,256 87.6 5,422 7.1 565 0.7 570 0.7 774 1.0 2,230 2.9 0 0.0 76,816 Kilimanjaro 102,982 85.0 6,971 5.8 114 0.1 1,386 1.1 3,536 2.9 5,925 4.9 175 0.1 121,089 Tanga 60,106 85.3 2,081 3.0 45 0.1 809 1.1 1,474 2.1 5,920 8.4 0 0.0 70,436 Morogoro 44,804 81.2 4,479 8.1 419 0.8 264 0.5 2,651 4.8 2,268 4.1 320 0.6 55,204 Pwani 32,794 87.9 1,088 2.9 108 0.3 324 0.9 2,093 5.6 857 2.3 45 0.1 37,310 Dar es Salaam 10,103 80.3 884 7.0 80 0.6 471 3.7 595 4.7 339 2.7 117 0.9 12,588 Lindi 12,674 83.0 436 2.9 124 0.8 173 1.1 510 3.3 1,353 8.9 0 0.0 15,270 Mtwara 29,410 84.5 790 2.3 153 0.4 577 1.7 1,499 4.3 2,389 6.9 0 0.0 34,818 Ruvuma 29,582 76.5 1,826 4.7 0 0.0 87 0.2 3,614 9.3 3,497 9.0 87 0.2 38,694 Iringa 106,878 86.3 8,061 6.5 169 0.1 1,042 0.8 1,592 1.3 5,915 4.8 169 0.1 123,826 Mbeya 136,567 83.8 6,523 4.0 398 0.2 839 0.5 5,232 3.2 12,395 7.6 933 0.6 162,888 Singida 30,523 85.8 657 1.8 103 0.3 235 0.7 1,138 3.2 1,008 2.8 1,908 5.4 35,572 Tabora 51,446 75.6 2,358 3.5 1,255 1.8 2,990 4.4 5,738 8.4 3,944 5.8 350 0.5 68,081 Sumbawanga 25,658 76.3 953 2.8 0 0.0 271 0.8 1,761 5.2 4,966 14.8 0 0.0 33,609 Kigoma 42,622 82.6 5,802 11.2 146 0.3 333 0.6 1,276 2.5 1,398 2.7 0 0.0 51,576 Shinyanga 102,241 85.1 8,798 7.3 498 0.4 2,606 2.2 3,507 2.9 2,303 1.9 134 0.1 120,086 Kagera 62,326 79.0 3,649 4.6 494 0.6 1,404 1.8 1,769 2.2 9,061 11.5 184 0.2 78,887 Mwanza 66,861 93.3 2,109 2.9 159 0.2 128 0.2 1,282 1.8 1,060 1.5 53 0.1 71,651 Mara 45,242 82.6 5,654 10.3 0 0.0 150 0.3 2,177 4.0 1,578 2.9 0 0.0 54,803 Manyara 63,036 84.2 5,767 7.7 57 0.1 474 0.6 2,105 2.8 3,321 4.4 98 0.1 74,858 Mainland 1,212,786 84.1 77,651 5.4 4,888 0.3 16,405 1.1 50,218 3.5 75,956 5.3 4,698 0.3 1,442,602 North Unguja 1,572 52.6 120 4.0 159 5.3 324 10.8 343 11.5 445 14.9 25 0.9 2,987 South Unguja 847 41.6 351 17.2 91 4.5 259 12.7 213 10.5 274 13.4 0 0.0 2,035 Urban West 848 33.3 345 13.6 63 2.5 440 17.3 565 22.2 283 11.1 0 0.0 2,543 North Pemba 520 56.4 231 25.0 0 0.0 58 6.3 26 2.8 88 9.5 0 0.0 922 South Pemba 423 57.7 191 26.0 0 0.0 36 4.9 85 11.5 0 0.0 0 0.0 734 Zanzibar 4,210 45.7 1,237 13.4 313 3.4 1,117 12.1 1,231 13.3 1,089 11.8 25 0.3 9,222 Total 1,216,996 83.8 78,889 5.4 5,201 0.4 17,521 1.2 51,449 3.5 77,044 5.3 4,723 0.3 1,451,823 9.8.4 LIVESTOCK EXTENSION: Number of households receiving extension advice on ProperLivestock Housing by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Other Radio/TV/Newspapers Neighbour Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 114 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 36,741 77 2,837 6 0 0 376 1 5,255 11 2,478 5 0 0 47,689 Arusha 56,947 85 3,093 5 568 1 952 1 1,662 2 3,857 6 89 0 67,169 Kilimanjaro 71,339 82 4,769 5 1,042 1 1,381 2 3,704 4 4,873 6 371 0 87,478 Tanga 25,174 88 858 3 148 1 195 1 865 3 1,458 5 0 0 28,697 Morogoro 7,336 62 2,248 19 284 2 334 3 1,404 12 175 1 140 1 11,921 Pwani 11,156 72 1,197 8 156 1 222 1 2,315 15 419 3 45 0 15,509 Dar es Salaam 4,340 73 721 12 85 1 207 3 346 6 276 5 0 0 5,973 Lindi 1,404 81 0 0 0 0 0 0 146 8 182 10 0 0 1,732 Mtwara 3,869 73 40 1 124 2 0 0 912 17 348 7 0 0 5,293 Ruvuma 11,962 82 1,203 8 0 0 0 0 616 4 812 6 0 0 14,593 Iringa 25,555 86 1,383 5 0 0 255 1 815 3 1,483 5 159 1 29,650 Mbeya 56,594 78 3,274 5 480 1 876 1 2,497 3 7,794 11 603 1 72,119 Singida 23,449 85 921 3 0 0 180 1 1,566 6 1,423 5 180 1 27,719 Tabora 15,817 51 3,262 11 1,559 5 3,132 10 4,954 16 1,818 6 503 2 31,046 Sumbawanga 11,246 70 1,229 8 47 0 47 0 2,662 17 795 5 0 0 16,027 Kigoma 10,269 91 611 5 0 0 0 0 146 1 212 2 0 0 11,239 Shinyanga 61,405 84 3,940 5 249 0 493 1 4,386 6 2,792 4 0 0 73,265 Kagera 29,790 80 2,617 7 756 2 542 1 1,105 3 2,631 7 0 0 37,440 Mwanza 32,749 86 1,600 4 212 1 159 0 1,962 5 1,376 4 0 0 38,056 Mara 22,052 77 4,047 14 0 0 237 1 2,123 7 140 0 0 0 28,600 Manyara 46,942 80 5,053 9 413 1 790 1 2,900 5 2,629 4 0 0 58,728 Mainland 566,136 80 44,902 6 6,123 1 10,378 1 42,342 6 37,972 5 2,090 0 709,943 North Unguja 705 49 0 0 76 5 165 12 280 20 204 14 0 0 1,430 South Unguja 766 47 351 22 61 4 320 20 47 3 79 5 0 0 1,624 Urban West 565 33 94 6 63 4 157 9 471 28 314 19 31 2 1,696 North Pemba 337 61 102 19 0 0 29 5 55 10 29 5 0 0 552 South Pemba 326 48 213 31 0 0 36 5 80 12 27 4 0 0 682 Zanzibar 2,700 45 761 13 200 3 707 12 933 16 653 11 31 1 5,984 Total 568,836 79 45,663 6 6,323 1 11,085 2 43,275 6 38,625 5 2,121 0 715,927 9.8.5 LIVESTOCK EXTENSION: Number of households receiving extension advice on ProperMilking and Milk Hygene by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 115 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 30,373 70.5 2,945 6.8 0 0.0 772 1.8 7,078 16.4 1,892 4.4 0 0.0 43,061 Arusha 51,165 84.4 4,285 7.1 300 0.5 868 1.4 1,206 2.0 2,665 4.4 151 0.2 60,639 Kilimanjaro 48,964 79.2 2,382 3.9 952 1.5 2,015 3.3 3,241 5.2 3,914 6.3 388 0.6 61,856 Tanga 12,341 85.3 477 3.3 103 0.7 186 1.3 621 4.3 746 5.2 0 0.0 14,475 Morogoro 4,882 72.4 561 8.3 0 0.0 35 0.5 726 10.8 404 6.0 140 2.1 6,748 Pwani 7,571 61.7 824 6.7 45 0.4 665 5.4 2,036 16.6 1,127 9.2 0 0.0 12,268 Dar es Salaam 2,672 64.0 682 16.3 85 2.0 249 6.0 207 5.0 239 5.7 42 1.0 4,176 Lindi 944 74.2 29 2.3 0 0.0 0 0.0 175 13.8 124 9.7 0 0.0 1,273 Mtwara 1,284 63.1 40 2.0 0 0.0 0 0.0 489 24.0 224 11.0 0 0.0 2,036 Ruvuma 9,531 79.0 1,134 9.4 30 0.2 30 0.2 712 5.9 635 5.3 0 0.0 12,071 Iringa 27,218 88.6 1,087 3.5 0 0.0 268 0.9 1,137 3.7 1,027 3.3 0 0.0 30,737 Mbeya 47,387 83.8 2,543 4.5 79 0.1 969 1.7 2,418 4.3 3,093 5.5 79 0.1 56,566 Singida 32,275 85.0 602 1.6 216 0.6 0 0.0 2,073 5.5 2,610 6.9 216 0.6 37,993 Tabora 22,598 60.4 2,865 7.7 1,134 3.0 2,236 6.0 4,930 13.2 3,379 9.0 252 0.7 37,393 Sumbawanga 12,697 65.3 524 2.7 176 0.9 653 3.4 3,243 16.7 1,983 10.2 176 0.9 19,453 Kigoma 7,241 89.6 399 4.9 0 0.0 0 0.0 439 5.4 0 0.0 0 0.0 8,078 Shinyanga 78,052 84.6 5,783 6.3 384 0.4 1,829 2.0 3,460 3.7 2,349 2.5 412 0.4 92,269 Kagera 19,625 79.6 1,942 7.9 0 0.0 319 1.3 1,787 7.3 972 3.9 0 0.0 24,646 Mwanza 30,264 84.9 1,350 3.8 277 0.8 0 0.0 1,706 4.8 2,064 5.8 0 0.0 35,661 Mara 17,094 68.6 4,430 17.8 86 0.3 97 0.4 2,746 11.0 449 1.8 0 0.0 24,902 Manyara 46,845 77.9 3,568 5.9 430 0.7 2,002 3.3 2,208 3.7 5,070 8.4 0 0.0 60,122 Mainland 511,025 79.1 38,452 5.9 4,296 0.7 13,192 2.0 42,638 6.6 34,966 5.4 1,855 0.3 646,425 North Unguja 610 49.5 32 2.6 76 6.2 102 8.3 280 22.7 133 10.8 0 0.0 1,232 South Unguja 397 46.4 182 21.3 61 7.1 107 12.6 30 3.6 77 9.0 0 0.0 855 Urban West 628 40.0 126 8.0 63 4.0 157 10.0 345 22.0 251 16.0 0 0.0 1,570 North Pemba 248 46.9 77 14.5 0 0.0 175 33.1 0 0.0 29 5.5 0 0.0 530 South Pemba 138 39.8 98 28.1 0 0.0 0 0.0 80 23.1 0 0.0 31 8.9 347 Zanzibar 2,021 44.6 514 11.3 200 4.4 541 11.9 736 16.2 491 10.8 31 0.7 4,535 Total 513,046 79 38,966 6 4,496 1 13,734 2 43,374 7 35,457 5 1,886 0 650,959 Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other 9.8.6 LIVESTOCK EXTENSION: Number of households receiving extensionadvice on Livestock fattening by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 116 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 108,556 89.6 2,520 2.1 0 0.0 519 0.4 6,759 5.6 2,545 2.1 268 0.2 121,167 Arusha 92,501 90.1 3,403 3.3 446 0.4 857 0.8 2,268 2.2 3,174 3.1 29 0.0 102,677 Kilimanjaro 121,158 92.2 2,216 1.7 757 0.6 497 0.4 3,239 2.5 2,925 2.2 666 0.5 131,457 Tanga 81,079 90.0 1,077 1.2 279 0.3 309 0.3 1,833 2.0 5,519 6.1 0 0.0 90,097 Morogoro 57,426 80.6 2,532 3.6 558 0.8 332 0.5 3,863 5.4 6,137 8.6 429 0.6 71,277 Pwani 31,964 85.6 1,135 3.0 267 0.7 361 1.0 2,720 7.3 823 2.2 74 0.2 37,344 Dar es Salaam 10,386 73.6 1,016 7.2 42 0.3 271 1.9 876 6.2 1,146 8.1 383 2.7 14,120 Lindi 12,472 89.2 464 3.3 94 0.7 0 0.0 625 4.5 322 2.3 0 0.0 13,978 Mtwara 27,379 86.7 344 1.1 164 0.5 265 0.8 1,461 4.6 1,964 6.2 0 0.0 31,576 Ruvuma 38,535 86.4 1,233 2.8 0 0.0 30 0.1 1,624 3.6 3,162 7.1 0 0.0 44,584 Iringa 126,026 92.3 4,136 3.0 0 0.0 420 0.3 1,925 1.4 3,982 2.9 0 0.0 136,488 Mbeya 169,622 84.7 5,253 2.6 236 0.1 2,313 1.2 7,625 3.8 14,291 7.1 1,037 0.5 200,378 Singida 64,216 95.6 848 1.3 216 0.3 283 0.4 462 0.7 1,119 1.7 0 0.0 67,144 Tabora 64,631 83.6 1,032 1.3 425 0.5 2,865 3.7 4,612 6.0 3,228 4.2 558 0.7 77,351 Sumbawanga 39,038 76.6 1,465 2.9 0 0.0 700 1.4 2,676 5.3 7,033 13.8 47 0.1 50,960 Kigoma 52,299 87.1 3,610 6.0 0 0.0 520 0.9 1,236 2.1 2,167 3.6 212 0.4 60,044 Shinyanga 165,545 91.4 5,407 3.0 264 0.1 3,045 1.7 2,750 1.5 3,619 2.0 498 0.3 181,129 Kagera 65,292 82.6 2,887 3.7 115 0.1 367 0.5 3,375 4.3 6,727 8.5 238 0.3 79,000 Mwanza 90,610 89.5 2,182 2.2 251 0.2 837 0.8 2,600 2.6 4,769 4.7 0 0.0 101,249 Mara 77,428 88.2 5,109 5.8 171 0.2 730 0.8 2,489 2.8 1,903 2.2 0 0.0 87,830 Manyara 97,428 92.0 3,258 3.1 370 0.3 942 0.9 1,303 1.2 2,505 2.4 98 0.1 105,903 Mainland 1,593,590 88.3 51,127 2.8 4,653 0.3 16,463 0.9 56,321 3.1 79,062 4.4 4,536 0.3 1,805,751 North Unguja 2,004 57.9 126 3.6 76 2.2 322 9.3 406 11.7 525 15.2 0 0.0 3,460 South Unguja 2,156 54.8 458 11.7 170 4.3 351 8.9 262 6.7 535 13.6 0 0.0 3,931 Urban West 1,413 41.7 314 9.3 94 2.8 314 9.3 691 20.4 502 14.8 63 1.9 3,391 North Pemba 2,183 77.5 154 5.5 0 0.0 0 0.0 205 7.3 219 7.8 55 1.9 2,816 South Pemba 1,993 78.1 186 7.3 0 0.0 0 0.0 289 11.3 85 3.3 0 0.0 2,553 Zanzibar 9,748 60.4 1,238 7.7 341 2.1 987 6.1 1,852 11.5 1,866 11.6 118 0.7 16,150 Total 1,603,338 88 52,365 3 4,994 0 17,450 1 58,173 3 80,928 4 4,654 0 1,821,901 9.8.7 LIVESTOCK EXTENSION: Number of households receiving extension adviceon Disease control (dipping/spraying) by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 117 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 54,849 82.0 2,578 3.9 368 0.5 281 0.4 6,413 9.6 2,155 3.2 285 0.4 66,929 Arusha 68,594 87.3 3,843 4.9 178 0.2 990 1.3 2,017 2.6 2,907 3.7 29 0.0 78,558 Kilimanjaro 69,326 81.3 2,536 3.0 586 0.7 950 1.1 8,233 9.7 3,486 4.1 140 0.2 85,256 Tanga 35,119 89.3 894 2.3 192 0.5 91 0.2 419 1.1 2,615 6.6 0 0.0 39,329 Morogoro 17,611 81.4 1,350 6.2 0 0.0 71 0.3 2,109 9.7 504 2.3 0 0.0 21,644 Pwani 14,419 75.4 671 3.5 145 0.8 665 3.5 2,373 12.4 839 4.4 0 0.0 19,112 Dar es Salaam 4,667 75.3 461 7.4 80 1.3 249 4.0 588 9.5 154 2.5 0 0.0 6,199 Lindi 2,234 85.1 0 0.0 0 0.0 0 0.0 267 10.2 123 4.7 0 0.0 2,625 Mtwara 6,921 74.2 152 1.6 0 0.0 0 0.0 1,649 17.7 605 6.5 0 0.0 9,326 Ruvuma 15,979 77.0 1,233 5.9 0 0.0 87 0.4 2,247 10.8 1,122 5.4 81 0.4 20,750 Iringa 42,644 88.8 1,118 2.3 0 0.0 175 0.4 1,903 4.0 2,177 4.5 0 0.0 48,018 Mbeya 65,162 82.5 3,771 4.8 775 1.0 844 1.1 3,520 4.5 4,515 5.7 442 0.6 79,029 Singida 51,792 91.9 668 1.2 180 0.3 235 0.4 1,472 2.6 1,365 2.4 648 1.1 56,361 Tabora 31,732 73.8 1,594 3.7 992 2.3 2,684 6.2 3,730 8.7 2,030 4.7 252 0.6 43,014 Sumbawanga 16,339 79.9 365 1.8 0 0.0 318 1.6 2,566 12.6 852 4.2 0 0.0 20,439 Kigoma 21,930 87.3 824 3.3 0 0.0 0 0.0 1,754 7.0 611 2.4 0 0.0 25,119 Shinyanga 103,655 89.3 3,603 3.1 0 0.0 1,663 1.4 5,171 4.5 1,914 1.6 129 0.1 116,137 Kagera 37,861 77.8 3,328 6.8 0 0.0 58 0.1 3,022 6.2 4,396 9.0 0 0.0 48,665 Mwanza 43,312 83.1 1,926 3.7 159 0.3 871 1.7 4,281 8.2 1,547 3.0 0 0.0 52,097 Mara 34,478 76.8 4,994 11.1 86 0.2 86 0.2 4,758 10.6 493 1.1 0 0.0 44,895 Manyara 67,608 88.9 3,590 4.7 430 0.6 207 0.3 1,953 2.6 2,014 2.6 261 0.3 76,063 Mainland 806,233 84.0 39,499 4.1 4,170 0.4 10,525 1.1 60,446 6.3 36,427 3.8 2,267 0.2 959,567 North Unguja 622 62.8 63 6.4 76 7.7 102 10.3 102 10.3 25 2.6 0 0.0 990 South Unguja 505 44.0 259 22.6 0 0.0 245 21.4 107 9.4 30 2.6 0 0.0 1,147 Urban West 471 34.1 157 11.4 94 6.8 31 2.3 534 38.6 94 6.8 0 0.0 1,382 North Pemba 238 90.3 0 0.0 0 0.0 0 0.0 26 9.7 0 0.0 0 0.0 263 South Pemba 376 54.0 186 26.8 0 0.0 54 7.7 80 11.5 0 0.0 0 0.0 697 Zanzibar 2,211 49.4 666 14.9 171 3.8 432 9.6 849 19.0 150 3.4 0 0.0 4,479 Total 808,444 84 40,165 4 4,341 0 10,957 1 61,295 6 36,577 4 2,267 0 964,046 9.8.8 LIVESTOCK EXTENSION: Number of households receiving extension advice on Herd/Flock size and selection by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 118 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 34,106 75.8 3,168 7.0 253 0.6 1,146 2.5 5,685 12.6 646 1.4 0 0.0 45,004 Arusha 44,299 82.1 4,766 8.8 71 0.1 601 1.1 1,511 2.8 2,689 5.0 29 0.1 53,965 Kilimanjaro 47,886 80.4 1,670 2.8 733 1.2 885 1.5 5,104 8.6 3,175 5.3 88 0.1 59,540 Tanga 13,333 89.6 717 4.8 140 0.9 36 0.2 230 1.5 427 2.9 0 0.0 14,884 Morogoro 7,213 72.0 1,606 16.0 0 0.0 35 0.4 933 9.3 88 0.9 140 1.4 10,015 Pwani 9,508 67.0 662 4.7 156 1.1 0 0.0 3,341 23.6 488 3.4 29 0.2 14,184 Dar es Salaam 3,000 77.1 419 10.8 42 1.1 80 2.0 195 5.0 117 3.0 37 1.0 3,890 Lindi 986 68.5 0 0.0 0 0.0 124 8.6 146 10.2 182 12.7 0 0.0 1,439 Mtwara 2,738 58.4 79 1.7 0 0.0 0 0.0 1,344 28.6 529 11.3 0 0.0 4,690 Ruvuma 8,032 77.6 1,223 11.8 0 0.0 87 0.8 630 6.1 347 3.4 30 0.3 10,350 Iringa 30,303 89.4 1,274 3.8 0 0.0 66 0.2 871 2.6 1,375 4.1 0 0.0 33,888 Mbeya 30,539 78.5 2,564 6.6 457 1.2 277 0.7 2,698 6.9 2,209 5.7 157 0.4 38,902 Singida 35,692 92.4 488 1.3 56 0.1 235 0.6 818 2.1 1,138 2.9 216 0.6 38,643 Tabora 21,985 70.1 2,161 6.9 1,456 4.6 1,385 4.4 2,514 8.0 1,614 5.1 252 0.8 31,367 Sumbawanga 10,068 74.8 541 4.0 0 0.0 271 2.0 2,087 15.5 496 3.7 0 0.0 13,463 Kigoma 9,948 82.4 333 2.8 187 1.5 0 0.0 1,462 12.1 146 1.2 0 0.0 12,076 Shinyanga 79,997 86.6 3,503 3.8 748 0.8 393 0.4 4,848 5.3 2,701 2.9 134 0.1 92,325 Kagera 23,222 81.0 1,402 4.9 0 0.0 261 0.9 950 3.3 2,829 9.9 0 0.0 28,664 Mwanza 20,491 79.1 1,059 4.1 159 0.6 159 0.6 3,345 12.9 701 2.7 0 0.0 25,913 Mara 19,831 76.4 2,659 10.2 0 0.0 0 0.0 3,190 12.3 290 1.1 0 0.0 25,971 Manyara 42,549 82.5 3,007 5.8 474 0.9 735 1.4 3,156 6.1 1,476 2.9 158 0.3 51,554 Mainland 495,727 81.2 33,302 5.5 4,931 0.8 6,777 1.1 45,059 7.4 23,664 3.9 1,270 0.2 610,729 North Unguja 292 44.6 25 3.9 76 11.7 127 19.4 133 20.4 0 0.0 0 0.0 654 South Unguja 381 57.8 152 23.1 0 0.0 77 11.7 0 0.0 49 7.4 0 0.0 659 Urban West 345 32.4 94 8.8 94 8.8 31 2.9 471 44.1 31 2.9 0 0.0 1,068 South Pemba 268 60.7 67 15.1 0 0.0 0 0.0 80 18.2 27 6.1 0 0.0 442 North Pemba 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 Total 1,287 45.6 338 12.0 171 6.0 236 8.3 685 24.3 107 3.8 0 0.0 2,823 Total 497,014 81 33,640 5 5,102 1 7,012 1 45,743 7 23,771 4 1,270 0 613,552 9.8.9 LIVESTOCK EXTENSION: Number of households receiving extension advice on Pasture Establishment by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 119 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 76,857 82.0 4,877 5.2 4,013 4.3 308 0.3 6,589 7.0 839 0.9 252 0.3 93,735 Arusha 44,425 68.7 12,293 19.0 2,532 3.9 203 0.3 2,936 4.5 2,321 3.6 0 0.0 64,711 Kilimanjaro 58,174 72.0 5,650 7.0 11,486 14.2 819 1.0 1,985 2.5 2,660 3.3 0 0.0 80,775 Tanga 29,404 79.0 4,455 12.0 1,729 4.6 0 0.0 998 2.7 653 1.8 0 0.0 37,240 Morogoro 31,690 80.4 3,504 8.9 961 2.4 35 0.1 1,386 3.5 1,583 4.0 232 0.6 39,391 Pwani 23,601 83.6 1,926 6.8 648 2.3 111 0.4 1,335 4.7 607 2.2 0 0.0 28,227 Dar es Salaam 7,024 80.8 768 8.8 190 2.2 117 1.3 371 4.3 105 1.2 122 1.4 8,698 Lindi 6,469 79.5 510 6.3 458 5.6 0 0.0 257 3.2 368 4.5 76 0.9 8,138 Mtwara 17,821 74.1 1,824 7.6 2,094 8.7 0 0.0 1,264 5.3 1,061 4.4 0 0.0 24,065 Ruvuma 22,196 77.7 3,351 11.7 846 3.0 219 0.8 1,102 3.9 754 2.6 111 0.4 28,580 Iringa 68,480 82.6 6,280 7.6 4,859 5.9 72 0.1 676 0.8 2,515 3.0 0 0.0 82,883 Mbeya 73,146 79.5 8,308 9.0 6,064 6.6 236 0.3 2,149 2.3 2,151 2.3 0 0.0 92,054 Singida 26,136 83.2 1,177 3.7 261 0.8 235 0.7 2,496 7.9 1,094 3.5 0 0.0 31,399 Tabora 36,987 74.0 4,936 9.9 2,221 4.4 1,118 2.2 3,199 6.4 1,404 2.8 126 0.3 49,991 Sumbawanga 19,357 74.3 4,782 18.3 159 0.6 94 0.4 1,220 4.7 450 1.7 0 0.0 26,062 Kigoma 27,755 72.7 5,677 14.9 2,436 6.4 877 2.3 984 2.6 292 0.8 146 0.4 38,167 Shinyanga 103,161 83.7 8,509 6.9 4,038 3.3 887 0.7 4,683 3.8 1,635 1.3 270 0.2 123,184 Kagera 36,392 76.6 5,902 12.4 1,043 2.2 150 0.3 1,507 3.2 2,543 5.3 0 0.0 47,536 Mwanza 45,888 83.4 5,758 10.5 943 1.7 697 1.3 1,060 1.9 647 1.2 0 0.0 54,993 Mara 32,366 68.9 7,562 16.1 3,169 6.7 172 0.4 2,753 5.9 742 1.6 236 0.5 47,000 Manyara 50,181 78.5 5,789 9.1 2,123 3.3 342 0.5 1,496 2.3 3,522 5.5 474 0.7 63,927 Mainland 837,511 78.2 103,837 9.7 52,276 4.9 6,693 0.6 40,446 3.8 27,947 2.6 2,046 0.2 1,070,756 North Unguja 920 46.9 120 6.1 254 13.0 178 9.1 254 13.0 235 12.0 0 0.0 1,962 South Unguja 541 43.3 414 33.1 107 8.6 30 2.4 61 4.9 95 7.6 0 0.0 1,249 Urban West 408 20.0 911 44.6 157 7.7 63 3.1 471 23.1 31 1.5 0 0.0 2,041 North Pemba 344 59.5 183 31.6 0 0.0 0 0.0 51 8.9 0 0.0 0 0.0 578 South Pemba 984 77.0 129 10.1 0 0.0 0 0.0 134 10.5 31 2.4 0 0.0 1,278 Zanzibar 3,198 45.0 1,756 24.7 519 7.3 271 3.8 971 13.7 393 5.5 0.0 0.0 7,108 Total 840,708 78 105,593 10 52,795 5 6,965 1 41,417 4 28,340 3 2,046 0 1,077,863 9.8.10 LIVESTOCK EXTENSION: Number of households receiving extension advice on Group formation and strengthening by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Radio/TV/Newspapers Neighbour Other Cooperative Large scale farmer Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 120 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 33,523 73.0 1,751 3.8 268 0.6 1,322 2.9 5,019 10.9 3,931 8.6 126 0.3 45,940 Arusha 55,264 77.0 9,444 13.2 1,324 1.8 963 1.3 2,009 2.8 2,742 3.8 0 0.0 71,745 Kilimanjaro 81,055 88.0 4,012 4.4 1,416 1.5 833 0.9 2,478 2.7 2,106 2.3 160 0.2 92,060 Tanga 29,861 90.8 766 2.3 619 1.9 45 0.1 346 1.1 1,259 3.8 0 0.0 32,897 Morogoro 9,316 72.1 1,362 10.5 228 1.8 105 0.8 737 5.7 1,037 8.0 140 1.1 12,926 Pwani 11,574 66.5 1,160 6.7 219 1.3 361 2.1 2,389 13.7 1,668 9.6 45 0.3 17,416 Dar es Salaam 4,304 75.0 768 13.4 122 2.1 122 2.1 227 4.0 154 2.7 42 0.7 5,739 Lindi 2,267 81.8 212 7.6 88 3.2 0 0.0 58 2.1 146 5.3 0 0.0 2,771 Mtwara 4,618 82.9 192 3.5 0 0.0 0 0.0 336 6.0 422 7.6 0 0.0 5,568 Ruvuma 15,071 82.7 1,430 7.8 0 0.0 0 0.0 978 5.4 717 3.9 30 0.2 18,225 Iringa 32,684 87.5 1,654 4.4 159 0.4 138 0.4 497 1.3 2,206 5.9 0 0.0 37,338 Mbeya 61,679 79.5 3,431 4.4 1,649 2.1 798 1.0 3,193 4.1 6,295 8.1 524 0.7 77,569 Singida 24,860 89.5 499 1.8 0 0.0 0 0.0 1,376 5.0 1,046 3.8 0 0.0 27,782 Tabora 23,953 65.6 2,528 6.9 850 2.3 2,926 8.0 4,009 11.0 1,495 4.1 771 2.1 36,533 Sumbawanga 11,534 65.7 1,563 8.9 272 1.6 494 2.8 2,327 13.3 1,371 7.8 0 0.0 17,561 Kigoma 12,864 79.3 2,497 15.4 0 0.0 0 0.0 651 4.0 212 1.3 0 0.0 16,225 Shinyanga 86,501 88.1 3,352 3.4 518 0.5 1,524 1.6 3,673 3.7 2,598 2.6 0 0.0 98,166 Kagera 30,338 75.8 2,831 7.1 1,653 4.1 665 1.7 1,121 2.8 3,157 7.9 233 0.6 39,997 Mwanza 46,707 86.4 1,833 3.4 929 1.7 255 0.5 2,696 5.0 1,611 3.0 0 0.0 54,032 Mara 29,186 80.0 4,510 12.4 226 0.6 86 0.2 1,930 5.3 559 1.5 0 0.0 36,497 Manyara 46,861 78.2 4,860 8.1 1,088 1.8 675 1.1 2,728 4.6 3,679 6.1 0 0.0 59,892 Mainland 654,019 81.1 50,655 6.3 11,631 1.4 11,313 1.4 38,779 4.8 38,414 4.8 2,071 0.3 806,881 North Unguja 1,060 55.4 25 1.3 102 5.3 184 9.6 235 12.3 305 16.0 0 0.0 1,912 South Unguja 927 48.6 334 17.5 30 1.6 290 15.2 91 4.8 233 12.2 0 0.0 1,906 Urban West 565 30.0 345 18.3 126 6.7 126 6.7 534 28.3 157 8.3 31 1.7 1,884 North Pemba 347 53.7 77 11.9 0 0.0 58 9.0 26 4.0 139 21.5 0 0.0 647 South Pemba 678 62.1 186 17.1 0 0.0 0 0.0 142 13.0 85 7.7 0 0.0 1,092 Zanzibar 3,578 48.1 969 13.0 258 3.5 658 8.8 1,028 13.8 919 12.4 31.4 0.4 7,441 Total 657,597 81 51,623 6 11,888 1 11,971 1 39,807 5 39,333 5 2,102 0 814,322 9.8.11 LIVESTOCK EXTENSION: Number of households receiving extension advice on Calf Rearing by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Radio/TV/Newspapers Neighbour Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 121 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 32,062 78.8 1,647 4.0 125 0.3 279 0.7 5,946 14.6 626 1.5 0 0.0 40,686 Arusha 46,280 81.9 5,338 9.4 211 0.4 926 1.6 1,772 3.1 1,850 3.3 165 0.3 56,540 Kilimanjaro 53,717 78.5 5,230 7.6 609 0.9 647 0.9 4,124 6.0 3,992 5.8 88 0.1 68,407 Tanga 13,613 80.9 1,144 6.8 45 0.3 176 1.0 1,421 8.4 434 2.6 0 0.0 16,834 Morogoro 4,431 69.8 1,017 16.0 140 2.2 53 0.8 570 9.0 0 0.0 140 2.2 6,350 Pwani 8,484 64.3 414 3.1 267 2.0 377 2.9 3,492 26.5 156 1.2 0 0.0 13,191 Dar es Salaam 2,770 72.5 614 16.1 80 2.1 159 4.2 112 2.9 42 1.1 42 1.1 3,820 Lindi 993 82.4 0 0.0 0 0.0 124 10.3 58 4.9 29 2.4 0 0.0 1,204 Mtwara 1,585 60.2 40 1.5 0 0.0 0 0.0 784 29.8 224 8.5 0 0.0 2,632 Ruvuma 8,691 76.5 945 8.3 0 0.0 59 0.5 951 8.4 687 6.0 30 0.3 11,363 Iringa 18,693 80.9 468 2.0 0 0.0 109 0.5 2,364 10.2 1,462 6.3 0 0.0 23,097 Mbeya 39,779 85.1 2,142 4.6 205 0.4 275 0.6 2,766 5.9 1,481 3.2 75 0.2 46,724 Singida 25,686 92.7 441 1.6 0 0.0 0 0.0 798 2.9 798 2.9 0 0.0 27,723 Tabora 20,358 71.9 1,016 3.6 992 3.5 1,692 6.0 2,153 7.6 1,440 5.1 668 2.4 28,320 Sumbawanga 6,977 66.2 319 3.0 47 0.4 271 2.6 2,426 23.0 497 4.7 0 0.0 10,537 Kigoma 6,993 76.6 1,635 17.9 0 0.0 0 0.0 292 3.2 212 2.3 0 0.0 9,132 Shinyanga 68,551 91.4 2,318 3.1 0 0.0 393 0.5 2,732 3.6 1,037 1.4 0 0.0 75,031 Kagera 20,093 83.4 1,199 5.0 58 0.2 150 0.6 981 4.1 1,619 6.7 0 0.0 24,098 Mwanza 16,701 81.1 1,377 6.7 159 0.8 159 0.8 1,365 6.6 831 4.0 0 0.0 20,591 Mara 14,737 74.5 3,476 17.6 0 0.0 0 0.0 1,494 7.5 86 0.4 0 0.0 19,793 Manyara 37,452 78.6 2,712 5.7 847 1.8 158 0.3 4,468 9.4 1,868 3.9 158 0.3 47,663 Mainland 448,645 81.0 33,493 6.0 3,783 0.7 6,008 1.1 41,068 7.4 19,373 3.5 1,366 0.2 553,737 North Unguja 547 50.6 0 0.0 102 9.4 76 7.1 178 16.5 178 16.5 0 0.0 1,081 South Unguja 582 40.6 334 23.4 0 0.0 213 14.9 61 4.2 242 16.9 0 0.0 1,431 Urban West 534 40.5 251 19.0 94 7.1 0 0.0 314 23.8 126 9.5 0 0.0 1,319 North Pemba 132 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 132 South Pemba 454 60.4 129 17.1 0 0.0 0 0.0 138 18.4 31 4.1 0 0.0 752 Zanzibar 2,248 47.7 714 15.2 196 4.2 289 6.1 691 14.7 576 12.2 0.0 0.0 4,714 Total 450,892 81 34,207 6 3,979 1 6,297 1 41,759 7 19,950 4 1,366 0 558,451 Radio/TV/Newspapers Neighbour 9.8.12 LIVESTOCK EXTENSION: Number of households receiving extension advice on Use of improved Bulls by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Large scale farmer Other Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 122 Number % Number % Number % Number % Number % Number % Other (Specify) % Dodoma 45,201 81.2 2,655 4.8 126 0.2 743 1.3 5,515 9.9 1,457 2.6 0 0.0 55,698 Arusha 33,664 80.0 3,972 9.4 387 0.9 663 1.6 2,343 5.6 1,035 2.5 29 0.1 42,092 Kilimanjaro 50,076 73.6 3,039 4.5 486 0.7 1,778 2.6 7,395 10.9 5,263 7.7 0 0.0 68,036 Tanga 11,126 79.2 1,169 8.3 45 0.3 379 2.7 782 5.6 541 3.9 0 0.0 14,042 Morogoro 14,980 79.6 1,613 8.6 419 2.2 198 1.1 917 4.9 513 2.7 175 0.9 18,815 Pwani 16,494 81.8 600 3.0 111 0.5 111 0.5 2,518 12.5 275 1.4 45 0.2 20,153 Dar es Salaam 4,970 71.3 925 13.3 80 1.1 351 5.0 207 3.0 439 6.3 0 0.0 6,971 Lindi 1,381 81.9 123 7.3 0 0.0 124 7.3 29 1.7 29 1.7 0 0.0 1,687 Mtwara 4,351 61.1 159 2.2 0 0.0 0 0.0 1,283 18.0 1,334 18.7 0 0.0 7,126 Ruvuma 13,886 84.8 1,329 8.1 0 0.0 59 0.4 616 3.8 459 2.8 30 0.2 16,379 Iringa 47,232 90.9 1,558 3.0 0 0.0 253 0.5 985 1.9 1,947 3.7 0 0.0 51,974 Mbeya 58,101 83.6 3,731 5.4 538 0.8 1,039 1.5 2,262 3.3 3,382 4.9 446 0.6 69,498 Singida 21,067 86.9 386 1.6 283 1.2 0 0.0 1,746 7.2 576 2.4 180 0.7 24,237 Tabora 25,651 72.5 962 2.7 567 1.6 2,392 6.8 3,810 10.8 1,746 4.9 252 0.7 35,379 Sumbawanga 14,501 75.2 1,131 5.9 0 0.0 141 0.7 2,424 12.6 1,086 5.6 0 0.0 19,284 Kigoma 8,987 88.1 669 6.6 0 0.0 0 0.0 146 1.4 399 3.9 0 0.0 10,201 Shinyanga 56,641 85.0 3,584 5.4 479 0.7 992 1.5 3,183 4.8 1,639 2.5 119 0.2 66,636 Kagera 18,230 80.3 1,321 5.8 58 0.3 261 1.2 864 3.8 1,465 6.5 490 2.2 22,689 Mwanza 21,718 83.7 1,319 5.1 0 0.0 766 3.0 1,195 4.6 954 3.7 0 0.0 25,952 Mara 18,341 78.6 3,176 13.6 0 0.0 0 0.0 1,803 7.7 0 0.0 0 0.0 23,320 Manyara 34,446 74.1 3,454 7.4 474 1.0 548 1.2 3,733 8.0 3,686 7.9 158 0.3 46,499 Mainland 521,043 80.6 36,875 5.7 4,050 0.6 10,797 1.7 43,755 6.8 28,225 4.4 1,924 0.3 646,668 North Unguja 780 46.0 114 6.7 51 3.0 267 15.7 382 22.5 102 6.0 0 0.0 1,695 South Unguja 446 35.5 381 30.4 30 2.4 138 11.0 138 11.0 122 9.7 0 0.0 1,255 Urban West 471 30.0 220 14.0 94 6.0 63 4.0 565 36.0 157 10.0 0 0.0 1,570 North Pemba 154 59.2 77 29.6 0 0.0 29 11.2 0 0.0 0 0.0 0 0.0 260 South Pemba 435 64.9 98 14.6 0 0.0 0 0.0 138 20.6 0 0.0 0 0.0 671 Zanzibar 2,286 41.9 889 16.3 175 3.2 496 9.1 1,223 22.4 380 7.0 0.0 0.0 5,451 Total 523,329 80 37,764 6 4,226 1 11,293 2 44,977 7 28,605 4 1,924 0 652,119 Large scale farmer Radio/TV/Newspapers Neighbour Other 9.8.13 LIVESTOCK EXTENSION: Number of households receiving extension advice on Livestock Feeds processing by region during the 2007/08 agriculture year Region Source of Livestock Extension Total Number of households Government NGO/Dev project Cooperative Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 123 Yes % No % Total Dodoma 116 0 358,854 100 358,969 Arusha 122 0 205,425 100 205,547 Kilimanjaro 702 0 242,006 100 242,708 Tanga 825 0 329,953 100 330,779 Morogoro 246 0 298,175 100 298,421 Pwani 0 0 174,523 100 174,523 Dar es Salaam 80 0 35,080 100 35,160 Lindi 0 0 166,898 100 166,898 Mtwara 153 0 249,220 100 249,373 Ruvuma 4,018 2 206,263 98 210,281 Iringa 1,821 1 304,808 99 306,629 Mbeya 1,169 0 453,655 100 454,824 Singida 0 0 216,992 100 216,992 Tabora 653 0 287,794 100 288,447 Rukwa 412 0 225,838 100 226,250 Kigoma 212 0 224,958 100 225,171 Shinyanga 0 0 485,212 100 485,212 Kagera 147 0 405,762 100 405,910 Mwanza 92 0 398,901 100 398,993 Mara 0 0 226,731 100 226,731 Manyara 0 0 198,513 100 198,513 Mainland 10,768 0 5,695,561 100 5,706,329 % 0.19 0.19 99.81 99.81 100.00 North Unguja 0 0 30,354 100 30,354 South Unguja 0 0 20,259 100 20,259 Urban West 0 0 18,651 100 18,651 North Pemba 26 0 32,869 100 32,895 South Pemba 0 0 30,034 100 30,034 Zanzibar 26 100 132,168 100 132,193 % 0.02 0.08 99.98 0.08 100.00 National 10,794 0 5,827,729 100 5,838,523 9.9.1 FISH FARMING: Number of Agriculture Households Practising Fish Farming by Region during the 2007/08 Agriculture Year Region Was Fish farming carried out by this household during 2007/08 Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 124 Natural Pond Dug out Pond Water Resevoir Total Dodoma 0 116 0 116 Arusha 0 122 0 122 Kilimanjaro 0 702 0 702 Tanga 0 825 0 825 Morogoro 88 158 0 246 Pwani 0 0 0 0 Dar es Salaam 0 122 0 122 Lindi 0 0 0 0 Mtwara 0 458 0 458 Ruvuma 200 4,054 0 4,254 Iringa 169 1,732 0 1,901 Mbeya 0 1,169 0 1,169 Singida 0 0 0 0 Tabora 56 864 40 959 Rukwa 0 588 47 635 Kigoma 0 212 0 212 Shinyanga 0 0 0 0 Kagera 147 0 0 147 Mwanza 0 92 0 92 Mara 0 0 0 0 Manyara 0 0 0 0 Mainland 660 11,215 87 11,961 North Unguja 0 0 0 0 South Unguja 0 0 0 0 Urban West 0 0 0 0 North Pemba 0 26 0 26 South Pemba 0 0 0 0 Zanzibar 0 26 0 26 National 660 11,240 87 11,987 Region system of fish farming 9.9.2 FISH FARMING: Number of Agriculture Households by System of Fish Farming and Region during the 2007/08 Agriculture Year Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 125 Own pond Government institution NGO/Proj ect Neighbour Private trade Natural pond Other Total Dodoma 0 0 0 0 0 116 0 116 Arusha 0 0 122 0 0 0 0 122 Kilimanjaro 0 0 0 614 0 0 88 702 Tanga 0 0 516 206 0 103 0 825 Morogoro 88 0 0 18 140 0 0 246 Dar es Salaam 0 0 0 122 0 0 0 122 Mtwara 0 458 0 0 0 0 0 458 Ruvuma 207 141 451 3,295 0 132 30 4,254 Iringa 109 225 553 645 209 159 0 1,901 Mbeya 0 0 0 965 0 0 204 1,169 Tabora 126 248 459 0 0 126 0 959 Rukwa 0 141 335 0 0 112 635 Kigoma 0 0 212 0 0 0 0 212 Kagera 0 0 0 0 0 147 0 147 Mwanza 0 0 0 0 0 92 0 92 North Pemba 0 0 0 0 0 26 0 26 Total 576 1,072 2,455 6,200 349 901 434 11,987 9.9.3 FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2007/08 Agricultural Year Region Source of Fingerling Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 126 Region Did not sell Neighbour Local market Secondary market trade at farm Other Total Dodoma 116 0 0 0 0 0 116 Arusha 122 0 0 0 0 0 122 Kilimanjaro 264 438 0 0 0 0 702 Tanga 309 516 0 0 0 0 825 Morogoro 246 0 0 0 0 0 246 Pwani 0 0 0 0 0 0 0 Dar es Salaam 85 37 0 0 0 0 122 Lindi 0 0 0 0 0 0 0 Mtwara 0 458 0 0 0 0 458 Ruvuma 2,573 1,519 0 0 30 132 4,254 Iringa 1,079 653 0 0 0 169 1,901 Mbeya 806 363 0 0 0 0 1,169 Singida 0 0 0 0 0 0 0 Tabora 153 307 459 0 40 0 959 Rukwa 141 159 0 335 0 0 635 Kigoma 0 212 0 0 0 0 212 Shinyanga 0 0 0 0 0 0 0 Kagera 0 0 0 0 147 0 147 Mwanza 0 0 0 0 92 0 92 Mara 0 0 0 0 0 0 0 Manyara 0 0 0 0 0 0 0 Mainland 5,895 4,662 459 335 309 301 11,961 North Unguja 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 North Pemba 26 0 0 0 0 0 26 South Pemba 0 0 0 0 0 0 0 Zanzibar 26 0 0 0 0 0 26 Total 5,921 4,662 459 335 309 301 11,987 9.9.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2007/08 Agricultural Year Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 127 Fish Sold Number of Fish % Quantity(K g) % Quantity (Kg) Dodoma 0 0 0 0 0 Arusha 6,100 0 610 0 0 Kilimanja 177,751 6 6,592 1 3,251 Tanga 186,819 6 32,495 3 25,480 Morogoro 4,387 0 7,019 1 0 Dar es Salaam 33,089 1 9,861 1 1,863 Lindi 0 0 0 0 0 Mtwara 109,969 4 18,328 2 18,328 Ruvuma 911,657 29 283,454 25 344,111 Iringa 210,284 7 34,618 3 41,924 Mbeya 338,877 11 16,028 1 2,293 Tabora 1,014,913 33 301,229 26 281,464 Rukwa 67,127 2 80,071 7 139,437 Kigoma 21,236 1 0 0 6,371 Shinyanga 0 0 0 0 0 Kagera 12,670 0 19,005 2 17,679 Mwanza 23,026 1 345,391 30 239,471 Mara 0 0 0 0 0 Manyara 0 0 0 0 0 Mainland 3,117,905 100 1,154,702 100 1,121,672 North Unguja 0 0 0 0 0 South Unguja 0 0 0 0 0 Urban West 0 0 0 0 0 North Pemba 0 0 0 0 0 South Pemba 0 0 0 0 0 Zanzibar 0 0 0 0 0 National 3,117,905 1,154,702 1,121,672 9.9.5 FISH FARMING: Total Number of Fish Harvested, their weight and Quantity Sold by Region during 2007/08 agriculture year Fish Harvested Region Appendix II _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 128 Number % Number % Number % Number % Dodoma 16 0 0 0 0 0 0 0 0 0 Arusha 27 300 100.0 0 0 0 0 0 0 300 Kilimanja 61 128 100.0 0 0 0 0 0 0 128 Tanga 59 91 87.9 13 12.1 0 0 0 0 103 Morogoro 34 49 100.0 0 0 0 0 0 0 49 Pwani 0 0 0 0 0 0 0 0 0 0 Dar es Sa 99 547 100.0 0 0 0 0 0 0 547 Lindi 0 0 0.0 0 0 0 0 0 0 0 Mtwara 19 500 100.0 0 0 0 0 0 0 500 Ruvuma 133 124 100.0 0 0 0 0 0 0 124 Iringa 49 70 100.0 0 0 0 0 0 0 70 Mbeya 44 1148 100.0 0 0 0 0 0 0 1148 Singida 0 0 0.0 0 0 0 0 0 0 0 Tabora 151 149 100.0 0 0 0 0 0 0 149 Rukwa 101 421 100.0 0 0 0 0 0 0 421 Kigoma 374 240 100.0 0 0 0 0 0 0 240 Shinyanga 0 0 0.0 0 0 0 0 0 0 0 Kagera 182 200 100.0 0 0 0 0 0 0 200 Mwanza 100 6 100.0 0 0 0 0 0 0 6 Mara 0 0 0.0 0 0 0 0 0 0 0 Manyara 0 0 0.0 0 0 0 0 0 0 0 Mainland 3,972 99.7 13 0.3 0 0.0 0 3,985 North Unguja 0 0 0 0 0 0 0 0 0 0 South Unguja 0 0 0 0 0 0 0 0 0 0 Urban West 0 0 0 0 0 0 0 0 0 0 North Pemba 0 0 0 0 0 12 0 0 0 12 South Pemba 0 0 0 0 0 0 0 0 0 0 Zanzibar 0 0 0 0 12 0 0 0 12 National 97 3,972 99.4 12.50 0.3 12 0.3 0 0.00 3,996.82 9.9.6 FISH FARMING: Mean Size of Fish Pond and aveverage Number of fingerings stocked by Type and Region during 2007/08 agriculture year Milkfish Prawns/Crabs Lulu Type of Fish Tilapia Total Mean Size of Pond (Sq.metre) Region Appendix II ____________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 129 1 2 3 8 Dodoma 116 0 0 0 116 Arusha 122 0 0 0 122 Kilimanjaro 351 351 0 0 702 Tanga 722 103 0 0 825 Morogoro 228 0 0 18 246 Pwani 0 0 0 0 0 Dar es Salaam 122 0 0 0 122 Lindi 0 0 0 0 0 Mtwara 458 0 0 0 458 Ruvuma 2,743 1,482 30 0 4,254 Iringa 1,053 689 159 0 1,901 Mbeya 1,010 159 0 0 1,169 Singida 0 0 0 0 0 Tabora 527 432 0 0 959 Rukwa 253 335 47 0 635 Kigoma 212 0 0 0 212 Shinyanga 0 0 0 Kagera 147 0 0 0 147 Mwanza 92 0 0 0 92 Mara 0 0 0 0 0 Manyara 0 0 0 0 0 Mainland 8,157 3,551 236 18 11,961 North Unguja 0 0 0 0 0 South Unguja 0 0 0 0 0 Urban West 0 0 0 0 0 North Pemba 0 26 0 0 26 South Pemba 0 0 0 0 0 Zanzibar 0 26 0 0 26 National 8,157 3,576 236 18 11,987 9.9.7 FISH FARMING: Number of Agricultural Households By frequency of stocking of Fingerings in fish ponds and Region, 2007/08 Agricultural Year Region Frequency of stocking Total High Average Low Others Dodoma 0 0 116 0 116 Arusha 0 0 122 0 122 Kilimanjaro 0 615 87 0 702 Tanga 103 413 206 103 825 Morogoro 0 18 140 88 246 Pwani 0 0 0 0 0 Dar es Salaam 0 122 0 0 122 Lindi 0 0 0 0 0 Mtwara 0 0 458 0 458 Ruvuma 0 1,773 1,442 1,039 4,254 Iringa 159 842 900 0 1,901 Mbeya 0 488 477 204 1,169 Singida 0 0 0 0 0 Tabora 0 554 405 0 959 Rukwa 47 477 112 0 635 Kigoma 0 0 212 0 212 Shinyanga 0 0 0 0 0 Kagera 0 147 0 0 147 Mwanza 0 0 92 0 92 Mara 0 0 0 0 0 Manyara 0 0 0 0 0 Mainland 309 5,448 4,770 1,434 11,961 North Unguja 0 0 0 0 0 South Unguja 0 0 0 0 0 Urban West 0 0 0 0 0 North Pemba 0 0 0 0 0 South Pemba 0 0 0 0 0 North Pemba 0 26 0 0 26 Zanzibar 0 26 0 0 26 National 309 5,473 4,770 1,434 11,987 Region 9.9.8 FISH FARMING: Number of Agricultural Households By level of care of fish ponds and Region, 2007/08 Agricultural Year Level of Care of Fish Pond Total Appendix II ______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 130 Number % Number % Number % Dodoma 21,138 6 337,831 94 358,969 100 Arusha 8,323 4 197,224 96 205,547 100 Kilimanjaro 8,274 3 234,434 97 242,708 100 Tanga 5,077 2 325,702 98 330,779 100 Morogoro 2,762 1 295,659 99 298,421 100 Pwani 1,150 1 173,373 99 174,523 100 Dar es Salaam 0 0 35,160 100 35,160 100 Lindi 565 0 166,333 100 166,898 100 Mtwara 1,066 0 248,307 100 249,373 100 Ruvuma 1,057 1 209,224 99 210,281 100 Iringa 10,577 3 296,052 97 306,629 100 Mbeya 7,740 2 447,084 98 454,824 100 Singida 14,288 7 202,705 93 216,992 100 Tabora 11,761 4 276,685 96 288,447 100 Rukwa 7,306 3 218,944 97 226,250 100 Kigoma 4,247 2 220,924 98 225,171 100 Shinyanga 3,317 1 481,895 99 485,212 100 Kagera 4,798 1 401,112 99 405,910 100 Mwanza 1,811 0 397,181 100 398,993 100 Mara 1,055 0 225,676 100 226,731 100 Manyara 11,721 6 186,791 94 198,513 100 Mainland 128,031 2 5,578,298 98 5,706,329 100 North Unguja 25 0 30,328 100 30,354 100 South Unguja 335 2 19,924 98 20,259 100 Urban West 31 0 18,620 100 18,651 100 North Pemba 530 2 32,365 98 32,895 100 South Pemba 361 1 29,674 99 30,034 100 Zanzibar 1,282 1 130,911 99 132,193 100 Total (Nationaal) 129,314 2 5,709,209 98 5,838,523 100 9.10.1 BEE KEEPING: Number of Agricultural Households involved in Honey Production/Collection and Region, 2007/08 Agricultural Year Region Agricultural Households Involved in Honey Production/Collection Agricultural Households NOT Involved in Honey Production/Collection Total Appendix II ______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 131 Stingless Bee Sting Bee Total Stingl ess Bee Sting Bee Total Stingless Bee Sting Bee Total Dodoma 4,768 16,221 20,990 629 888 1,518 5,398 17,110 22,507 Arusha 1,525 6,125 7,650 624 231 855 2,149 6,356 8,506 Kilimanjaro 3,679 5,181 8,860 188 298 486 3,867 5,479 9,346 Tanga 875 4,500 5,375 391 0 391 1,266 4,500 5,766 Morogoro 458 2,391 2,850 0 0 0 458 2,391 2,850 Pwani 349 865 1,213 111 111 222 460 976 1,435 Dar es Salaam 0 0 0 0 0 0 0 0 0 Lindi 79 457 536 0 29 29 79 486 565 Mtwara 408 542 950 0 116 116 408 658 1,066 Ruvuma 588 469 1,057 0 207 207 588 675 1,263 Iringa 3,104 7,353 10,458 576 106 682 3,681 7,459 11,140 Mbeya 1,372 6,693 8,065 241 284 525 1,613 6,977 8,590 Singida 4,332 9,853 14,185 715 103 818 5,047 9,955 15,002 Tabora 2,079 9,280 11,359 501 181 683 2,580 9,461 12,041 Rukwa 1,119 6,363 7,482 224 0 224 1,343 6,363 7,706 Kigoma 1,410 2,464 3,873 747 373 1,120 2,156 2,837 4,994 Shinyanga 1,472 1,844 3,317 0 0 0 1,472 1,844 3,317 Kagera 955 3,635 4,590 544 207 751 1,499 3,842 5,342 Mwanza 1,007 1,165 2,172 0 0 0 1,007 1,165 2,172 Mara 491 704 1,195 0 0 0 491 704 1,195 Manyara 1,453 9,794 11,247 158 548 706 1,611 10,343 11,954 Mainland 31,524 95,900 127,424 5,648 3,683 9,332 37,172 99,583 136,755 North Unguja 0 25 25 0 0 0 0 25 25 South Unguja 110 242 351 0 0 0 110 242 351 Urban West 0 31 31 0 0 0 0 31 31 North Pemba 146 413 559 26 0 26 172 413 585 South Pemba 192 165 357 31 62 93 223 227 450 Zanzibar 447 876 1,324 57 62 119 504 938 1,442 9.10.2 BEE KEEPING: Number of Agriculture Households Harvesting Honey by Type of Bee and Region during the 2007/08 Agriculture Year Number of Agricultural Households that Poduced/Collected Honey Number of Agricultural Households that did NOT Poduce/Collect Honey Total Appendix II __________________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 132 Number of households Number of Hives Number of households Number of Hives Number of households Number of Hives Number of households Number of Hives Number of households Number of Hives Number of households Number of Hives Dodoma 5,398 1,708 17,110 8,457 22,507 10,166 5,398 57,902 17,110 198,744 22,507 256,647 Arusha 2,149 73,311 6,478 10,853 8,628 84,165 2,149 226,903 6,478 100,573 8,628 327,476 Kilimanjaro 3,867 22,762 5,479 1,712 9,346 24,474 3,867 35,463 5,479 55,896 9,346 91,360 Tanga 1,266 995 4,500 859 5,766 1,854 1,266 7,992 4,500 113,111 5,766 121,103 Morogoro 458 177 2,391 299 2,850 476 458 2,285 2,391 48,900 2,850 51,185 Pwani 460 640 976 527 1,435 1,167 460 832 976 6,926 1,435 7,757 Lindi 79 0 486 946 565 946 79 158 486 7,778 565 7,935 Mtwara 408 1,020 658 816 1,066 1,835 408 3,772 658 9,282 1,066 13,055 Ruvuma 588 913 675 0 1,263 913 588 3,908 675 4,377 1,263 8,286 Iringa 3,681 3,321 7,459 6,241 11,140 9,562 3,681 29,340 7,459 62,740 11,140 92,080 Mbeya 1,613 568 6,977 9,018 8,590 9,585 1,613 17,609 6,977 173,745 8,590 191,354 Singida 5,047 360 9,955 13,343 15,002 13,703 5,047 38,712 9,955 161,657 15,002 200,368 Tabora 2,886 2,296 9,614 129,525 12,500 131,821 2,886 500,418 9,614 915,666 12,500 1,416,084 Rukwa 1,343 1,793 6,363 11,708 7,706 13,502 1,343 12,914 6,363 586,618 7,706 599,532 Kigoma 2,156 0 2,837 1,210 4,994 1,210 2,156 25,383 2,837 62,734 4,994 88,117 Shinyanga 1,472 0 1,844 2,704 3,317 2,704 1,472 128,447 1,844 180,817 3,317 309,263 Kagera 1,499 0 3,842 390,787 5,342 390,787 1,499 8,867 3,842 290,211 5,342 299,078 Mwanza 1,007 0 1,165 384 2,172 384 1,007 15,312 1,165 15,233 2,172 30,545 Mara 491 564 704 1,094 1,195 1,658 491 643 704 2,004 1,195 2,647 Manyara 1,611 154,053 10,343 2,353 11,954 156,405 1,611 7,597 10,343 91,926 11,954 99,523 Mainland 37,478 264,482 99,859 592,835 137,337 857,316 37,478 1,124,458 99,859 3,088,938 137,337 4,213,396 North Unguja 0 . 25 0 25 0 0 . 25 0 25 0 South Unguja 110 152 242 0 351 152 110 12,511 242 3,401 351 15,912 Urban West 0 . 31 0 31 0 0 . 31 628 31 628 North Pemba 172 263 413 0 585 263 172 905 413 3,829 585 4,734 South Pemba 223 62,382 227 0 450 62,382 223 428 227 3,226 450 3,654 Zanzibar 504 62,797 938 0 1,442 62,797 504 13,845 938 11,084 1,442 24,929 Total 37,982 327,278 100,797 592,835 138,779 920,113 37,982 1,138,303 100,797 3,100,022 138,779 4,238,324 9.10.3 BEE KEEPING: Number of Agricultural Households, type of bee Hives and type of bees and District , 2007/08 Agricultural Year Region Number of Improved Bee Hives Number of Local Bee Hives Stingless Bee Sting Bee Total Stingless Bee Sting Bee Total Appendix II ______________________________________________________________________________________ _ Tanzania Agriculture Sample Census - 2007/08 133 Quantity (lts) % Quantity (lts) % Quantity (lts) % Quantity (lts) % Dodoma 498,628 33 447,200 34 1,011,044 67 869,528 66 1,316,728 1,509,673 Arusha 384,462 42 312,730 38 538,583 58 514,506 62 827,236 923,045 Kilimanjaro 922,955 90 670,277 90 101,982 10 77,729 10 748,006 1,024,937 Tanga 188,859 39 17,380 6 296,019 61 264,118 94 281,498 484,878 Morogoro 6,359 4 5,220 4 141,609 96 120,945 96 126,165 147,968 Pwani 7,597 17 6,696 18 37,267 83 30,922 82 37,618 44,864 Dar es Salaam 0 0 0 0 0 0 0 0 0 0 Lindi 1,971 6 1,577 6 28,944 94 24,050 94 25,627 30,915 Mtwara 5,098 9 6,729 12 52,183 91 49,739 88 56,468 57,280 Ruvuma 7,681 39 6,037 42 12,059 61 8,388 58 14,425 19,740 Iringa 124,685 23 93,742 25 422,379 77 279,380 75 373,122 547,063 Mbeya 837,193 25 8,088 2 2,557,916 75 389,457 98 397,545 3,395,109 Singida 142,891 12 124,891 13 1,058,768 88 841,968 87 966,859 1,201,659 Tabora 828,205 21 812,662 21 3,033,601 79 3,080,291 79 3,892,953 3,861,806 Rukwa 35,068 2 25,203 1 2,276,302 98 2,218,890 99 2,244,093 2,311,370 Kigoma 73,700 26 59,773 10 214,599 74 546,951 90 606,724 288,300 Shinyanga 214,621 16 157,350 16 1,165,206 84 818,731 84 976,081 1,379,826 Kagera 17,254 8 29,398 14 199,111 92 182,075 86 211,474 216,365 Mwanza 40,626 58 30,252 69 29,008 42 13,396 31 43,649 69,634 Mara 4,616 44 2,792 55 5,935 56 2,247 45 5,039 10,550 Manyara 34,511 6 16,675 3 568,294 94 598,737 97 615,413 602,805 Mainland 4,376,979 24 2,834,672 21 13750807.25 76 10932049.42 19 13,766,722 18,127,787 North Unguja . 0 . 0 0 254 0 0 0 South Unguja 13,280 54 13,248 55 11,405 46 10,739 55 23,986 24,685 Urban West . 0 . 0 1,884 0 0 0 0 0 North Pemba 3,585 47 1,694 38 4,092 53 2,762 38 4,456 7,676 South Pemba 2,222 31 2,142 35 4,882 69 4,052 35 6,194 7,104 Zanzibar 19,087 46 17,084 49 22,262 54 17,807 34,890 41,349 National 4,396,067 24 2,851,756 21 13,773,069 76 10,949,856 19 13,801,612 18,169,136 9.10.4 BEE KEEPING: Quantity of Honey Harvested and Sold by Size of Bees and Region during the 2007/08 Agriculture Year Honey Harvested (lts) Total Region Stingless Bee Sting Bee Honey Harvested Honey Sold Honey Harvested Honey Sold (lts) Honey Sold Appendix II ______________________________________________________________________________________ _ Tanzania Agriculture Sample Census - 2007/08 134 Region Sting Bee (Price per Litre) Stingless Bee (Price per Litre) Average Price Per Litre Dodoma 1,179 1,048 1,148 Arusha 1,932 1,670 1,865 Kilimanjaro 2,185 3,673 2,821 Tanga 1,566 1,426 1,544 Morogoro 1,812 1,335 1,735 Pwani 2,215 1,956 2,132 Dar es Salaam 0 0.00 0 Lindi 1,693 1,500 1,666 Mtwara 2,142 675 1,580 Ruvuma 1,565 851 1,233 Iringa 1,429 1,029 1,296 Mbeya 1,228 1,544 1,287 Singida 1,306 1,307 1,306 Tabora 1,201 1,018 1,169 Rukwa 1,046 1,109 1,056 Kigoma 1,156 1,333 1,224 Shinyanga 1,549 799 1,217 Kagera 1,420 1,261 1,388 Mwanza 1,388 1,114 1,261 Mara 454 1,315 808 Manyara 1,326 4,352 1,736 Mainland 1,419 1,444 1,404 North Unguja 3,000 - 3,000 South Unguja 5,052 3,680 4,624 Urban West 8,000 - 8,000 North Pemba 4,702 4,594 4,670 South Pemba 4,933 6,287 5,661 Zanzibar 5,137 4,853 5,191 National 1,423 1,423 1,487 9.10.5 BEE KEEPING: Average price of Honey (Tshs/litre) by Size of Bees and Region during the 2007/08 Agriculture Year Appendix II _________________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 135 scale farm Stingless bee Sting Bee Stingless bee Sting Bee Stingless bee Sting Bee Stingle ss bee Sting Bee Sting Bee Stingless bee Sting Bee Stingless bee Sting Bee Stingles s bee Sting Bee Stingless bee Sting Bee Dodoma 3,436 7,839 222 713 444 3,291 0 0 222 126 803 1,169 3,735 0 507 5,398 17,110 Arusha 833 2,692 71 641 89 0 0 0 0 122 162 913 2,861 122 0 2,149 6,356 Kilimanjaro 1,770 2,139 774 575 0 0 250 63 0 125 382 1,010 2,109 0 0 3,929 5,268 Tanga 438 2,686 0 391 0 73 0 0 0 130 558 307 754 0 84 875 4,546 Morogoro 458 1,398 0 504 0 0 0 0 0 0 0 0 489 0 0 458 2,391 Pwani 168 684 0 0 87 87 0 0 0 175 204 29 0 0 0 460 976 Lindi 79 369 0 0 0 0 0 0 0 0 88 0 29 0 0 79 486 Mtwara 408 658 0 0 0 0 0 0 0 0 0 0 0 0 0 408 658 Ruvuma 500 588 0 0 0 0 0 0 0 0 0 87 87 0 0 588 675 Iringa 1,646 4,394 169 448 0 0 0 0 0 338 725 941 1,761 587 66 3,681 7,393 Mbeya 1,047 3,663 157 836 0 284 0 0 125 0 454 409 1,615 0 0 1,613 6,977 Singida 1,767 6,319 751 909 216 921 0 0 0 319 103 1,675 1,432 216 272 4,944 9,955 Tabora 962 5,377 181 165 111 334 153 40 0 0 1,033 142 1,509 696 1,003 2,246 9,461 Rukwa 831 5,003 0 400 0 225 0 0 0 0 176 288 559 0 0 1,119 6,363 Kigoma 1,596 2,065 0 373 0 0 187 0 0 0 0 0 399 0 0 1,783 2,837 Shinyanga 433 1,193 270 652 0 0 270 0 0 0 0 498 0 0 0 1,472 1,844 Kagera 594 2,966 0 78 129 0 0 0 0 0 102 233 696 0 0 955 3,842 Mwanza 479 202 0 202 0 0 0 0 0 0 0 528 761 0 0 1,007 1,165 Mara 140 365 182 0 0 0 0 0 0 0 0 169 339 0 0 491 704 Manyara 522 3,588 0 264 724 898 0 0 0 0 98 365 5,188 0 233 1,611 10,268 Mainland 18,107 54,187 2,778 7,153 1,801 6,111 860 102 347 1,336 4,887 8,763 24,325 1,621 2,164 35,266 99,277 North Unguja 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 South Unguja 16 193 61 0 16 16 0 0 0 16 32 0 0 0 0 110 242 Urban West 0 0 0 0 0 0 0 0 0 0 31 0 0 0 0 0 31 North Pemba 117 248 0 29 0 0 0 0 0 0 29 55 106 0 0 172 413 South Pemba 161 134 31 0 0 31 0 0 0 0 0 0 0 0 0 192 165 Zanzibar 294 601 92 29 16 47 0 0 0 16 93 55 106 0 0 473 876 National 18,401 54,788 2,870 7,182 1,817 6,159 860 102 347 1,352 4,981 8,817 24,431 1,621 2,164 35,739 100,153 9.10.6 BEE KEEPING: Number of Agriculture Households by Location of Selling Honey and Region during the 2007/08 Agriculture Year Region Neighbour Local market Secondary market Total Processing industry Trade at farm Did not sell Other Appendix III 136 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 APPENDIX III: CENSUS DATA COLLECTION INSTRUMENTS Smallholder Questionnaire Community Questionnaire Village Listing Forms Appendix III 137 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Appendix IIIa: Smallholder Questionnaire Appendix III 138 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Appendix III 139 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 1.0 IDENTIFICATION DETAILS 1.1 Na. 1.1.1 Rgion …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 …………………………………………………………………… 1.2 Deatails of the respondent or household head Na. 1.2.1 Name and number of local leader 1.2.2 Name and number of household head ……………………………………….. 1.2.3 Sex of household head 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to household head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Typeof Agriculture Household Codes Location Location Name Codes Village Household agricultural activities codes(Q 2.1) Crops only.………...1 Livestock only ……....2 Pastoralist…….…3 Crops and Livestock ……....4 Relationship to household head codes (Q 1.2.5) Head of Household ………......1 Son /Daughter……..........3 Grandson/Granddaughter……............5 No relationship…….7 Spouse…………...…..2 Father/Mother……...4 Other relatives…...6 Identification Appendix III 140 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Read and Write (Col 8) Any other language: Must be a written language. For someone who can read and write in Kiswahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Kiswahili the the correct code is 2. Code 4 should only be used for any other language which is not English or Kiswahili. Relation to head (Col 2): Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. Education Level Reached (Col 10): Ask the respondent the highest educational level reached. This aims at establishing whether at the time of enumeration the member of the household is studying has completed or has never studied. Make further enquiry for the level of education reached for those who have completed studies. Establish if the member had attained any training after graduation for the purposes for completing column number 9. For those who still continue attending studies during the period of this survey, establish their learning stage. For instance for a household member who studied up to Standard Three but did complete his/her education at this level, then his/her highest education level reached is Standard Two. For those indicated under code 3 (not studied) in column 8 should be marked code 99 (Not applicable) in column 9. Section 3.0 Note Make sure that you define the hh proper to ensure that all the members of the hh are included. Ensure that you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. If you notice that the hh is large or you see many people around the hh and you have been given a smaller number of the hh members, make further enquiries until you are sure that you have captured all the hh members. Section 3.0 Household information. ii) For each household member complete columns 1,2,3 and 3 After completing columns 1, 2, 3 and 3 for each household member, go back to the first household member and complete the remaining columns for that member. iii) Repeat step 2 for the rest of the household members. Definition and working page for page 2 Question Specific Definitions: Appendix III 141 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all hh members beginning with hh head Ex Sex Start Na. with M = 1 hh Head F = 2 Mother Father yes=1 no=2 (2) (3) (5) (6) (7) (8) (9) (11) (13) 01 1 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 Not applicable for children under 5 years Age Marit al Status Parental Survival Reard and Write Education status Levek of On farm engagem ents Main activity Off farm income …………...… Names of hh members ( 98 years or more enter 97, under one year old write 00) education (Start with hh Head) attained (4) (10) (12) …………...… (1) …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… …………...… Identification Appendix III 142 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Off-farm Income (Col 13) These are income made from activities NOT on the HH’s farming activites. This can be from formal employmenbt (e.g. in gpvrenment etc.), temporary jobs, casual labourers and income generation activity and includes working for cash on other people’s farms. Indicate whether each member was involved in an off farm income generating activity during 2007/08 ................ Main activity (Col 12) Crop farming: ………………..01. Livestock farming/herding: ….02. Pastoralist …………………….03 Fishing ………………………..04 Fish farming ………….……….05 Paid employment / Government/parastal……06 Private/NGOs ………….07 Self employee (Off- farm cativities) - With employees ………...08 - Without employees ……...09 Non paid household member (off – farm activities) ……10. Unemployed but available for work ….11 Unemployed but unavailable for work..12 House mother …………………………13 Student ………………………….….14 Unable to work too old, too young, retired, disabled,child 15 Others (specify) …………………......98 Education Level (Col 10) Primary education Secondary Education Below Standard One.......00 Form One...............................11 Standard One ................01 Form Two ...............................12 Standard Two..................02 Fomr Three...........................13 S tandard Three...........03 Form Four ............................... 14 S tandard Four..............04 Form Five ................................15 S tandard Five...............05 Form Six ..................................16 S tandard S ix ...............06 Training after Seo.ondary Ed.....17 S tandard Seven............07 University and other Tertiary Ed...8 DarasS tandard E ight..08 Adult Education..........................19 Training after Primary Ed...09 Not apllicable .......................99 Pre Form One...............10 Relationship to household head (Col 2) Head of household.......1 Female/Male…...…..….2 Son/Daugther….…....3 Father/Mother……....…4 Grandson/daughter.…5 Other Relatives…..........6 Ed.ucation Level(Col 9) Studying ………………….1 Has completed….………...2 Never been to school ...…3 Involvement in farming activitie (Col 11) Works on farm full time.…..1 Works on farm part time.….2 Rarely works on farm....….3 Never works on farm.....…. 4 Reading and writing (Col 8) Kiswahili……………............………….1 English ………………..................……2 Kiswahili and English….......................3 Lugha nyingine…………...............…...4 Canno tread or write..........................….5 Survival of Parents( Col 6 & 7) Yes.....…1 No …..........2 Dont't know ....…….…….3 Marrital Status(Col 4) Married................……….….1 Single..................….……..…2 Co-habiting ..........................3 Divorced Separated...... …….…...…...4 Widow/widower....…………..5 Appendix III 143 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Overview to section 4 S ection 4.0: Preliminary note L and Access/Ownership Land access/ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between household members. It does not include official communal land that the household has sole access to for example a plot for crop farming in the communal area. S ection 4.2: L and Use 1. Ask the respondent the area of the different land use categories the household has sole access to (Q4.2.1 to 4.2.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Section 4.2 Land Use Temporary crops: are sown and harvested during the same agricultural year Permanent crops: are crops once sown or planted last for some years and need not to be replanted after each annual harvest. Permanent crops /mixed crops: This is a mixture of permanent and seasonal crops. The two crops can either be randomly planted together or in a particular pattern e; for example intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed). This is further subdivided into: Mixture of Permanent crops – two or more permanent crops grown tougher Mixture of Permanent and Temporary crops – permanent crop and annual crop together Mixture of Temporary crops– two or more temporary, annual crops grown together Pasture land: this is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or where other means have been applied to improve the pasture. Or it can be natural pasture. Natural Bush: Land which has naturally grown shrubs and trees and is considered productive but is not utilized for farming or livestock production. Section 4.0 – Land Ownership 1. Ask the respondent if he knows the total areas of land the household has sole access to. If he knows make a note in the calculation space 2 Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1, 1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information) 4. If the total area is different find out which one is correct and make Definitions for Key Specific Questions Section 4.1 – Land Access/Ownership These are areas that were used by the households for the 2007/08 farming season Lease/Certificate of Ownership: Area under lease/certificate of ownership refers to the areas which were issued by the government. The household possesses government issued leasehold little or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the household does not have an official government but its right of use is granted by the traditional leaders. Bought: This refers to the areas of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for cash or for a fixed amount in crop produce (e.g. fixed number of bags at harvest). Borrowed: use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share cropping: where the household is permitted to use land which is then paid for from a percentage of the harvested crop Procedures for questions Definitions and working page for page 3 Overview to section 4 Appendix III 144 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 LAND ACCESS/OWNERSHIP/TENURE Give details on Area owned by the household during 2007/08 agricultural season. Give area as reported by the respondent in acres 4.1.8 4.1.1 Area under certificate of ownership 4.1.2 Area owned under customary law 4.1.3 Area bought 4.1.9 4.1.4 Area rented from others 4.1.5 Area borrowed from others 4.1.6 Area share cropped from others 4.1.10 4.1.7 Area under other forms of tenure Total area 4.2 LAND USE Area used by the household for various agricultural activities during 2007/08 agricultural season 4.2.1 Area planted temporary monocrops 4.2.2 4.2.3 Area planted permanent moncrops 4.2.4 4.2.5 4.2.6 Area under pasture 4.2.7 Area under fallow 4.2.8 Area under natural forest 4.2.9 Area planted trees 4.2.10 Area rented to others 4.2.11 Area unsuitable for agricultrure 4.2.12 Uncultivated arable land (minus area under fallow) Area planted temporary mixed crops (e.g. maize and beans) Total area Area planted permanent mixed crops (e.g. banana, coffee, trees) Area planted permanent and temporary mixed crops (e.g. maize and banana) Area in Acre Area in acre Do you consider to have enough land for your household? (Yes=1, No=2) Is there any female who owns land or has customary rights to land ownership in this household? (Yes=1, No=2) Enter area as reported by the respondent in acres Was the whole household area used during the 2007/08 agricultural season? (Yes=1, No=2) Working space for calculations Identification . . . . . . . . . . . . . . . . . . . . . Appendix III 145 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Working table for the calculation area for annual mixed crops Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 The remaining area for temp crops Name of the crop temp/permanent 1 Name of the crop temp/permanent 2 Name of the crop temp/permanent 3 Check total area Check total area for temporary crops plant Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 The remaining area for temp crops Name of the crop temp/permanent 1 Name of the crop temp/permanent 2 Name of the crop temp/permanent 3 Check total area Check total area for temporary crops Total Area for mixed crops Total area for permanent crops Total area for mixed crops Total area for permanent crops Mixed crops plants (a) (b) (c) Crop Name for plants number of plants Total area of mixed (acre) Area Total Total area (acre) (a) (b) (c) (d) Mixed crops 1 (acre) of plants Name of the plant for plants Total area mix (acre) (f)=(d)*(e) % of temporary Area for permanent crop Total area (e) Area for Total (acre) (acre) of (d) (e) (f)=(d)*(e) % of temporary Area for temporary crop 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . . . . . . . . Planted Area: Area in acre the household was able to plant Harvested Area: Area in acre the household was able to harvest a large portion of harvests . this is the same as the area planted minus the area that was destroyed by floods/ pets / Crop Codes(Creal / Tubers/ Roots: Code Crop 11 Maizei 12 Paddy 13 Sorghum 14 Buirush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatoes 23 Irish Potatyoes 24 Yams 25 Cocoyamsi 26 Onions 27 Gingeri Crop Codes Legumes and Oil Code Crop 31 Beans 32 Cowpeas 33 Green Gram 34 Chick Peas 35 Dengu 36 Bambara nuts 37 Njegere 41 Sun flower 42 Simsim 43 Ground uts 47 Soya beans 48 Caster Seed Vegetable Codes: Code Crop 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkin 93 Cucumber 94 Egg plant 95 Water mellon 96 Cauliflower 06 Melllon 05 nyanyachungu 02 Ocra 03 Radish 01 Green Beans 04 Bizari Cash crop codes: Code Crop 50 Cotton 51 Tobacco 53 Payrethrum 62 Jute 19 Seaweed Temporary/Annual Crops Crops planted and harvested within 12 months after which time the plants die . Most annual crops are planted and harvested on a seasonal base. Instructions for calculating the area of mixed crops in a mixture A. If the mixed crop is mixed annual ly only enter the total area of the field in the remaining area under temporary Crop and go to step one of these instructions. B. If the mixed crop is mixed permanent and annual try to work tyhe percent age taken by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annula crops in the mix. C: Number of trees method to calculate annual crop areas in a permanent-annual crop mix.: (i) List each of the permanent crop in collumn b and enter the ground area per acre for each permanent crop ( from instrcutions for page 8) in colum d. (ii) Enter the number of permanent trees in the mix in collumn e as will be provided to you by the respondent (iii) Calculate the area occpied by each crop by multiplying collumn d and collumn e and sum up these to obatin the total area of permanent crops in the mix. iv) To obatin the area for tempofrary crops , substract (-) the area fro permanent crops from thne total area of crop mix and enter the resulst in in the total area under temporary crops. (v) Proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each temporary crop in tyhe crop mix and estimate percentages of each crop. 2. Using the percentage for each crop, calculate the are for each crop from the remaining area under tenmporary crop. 3. After completing the exrcise for all the fields, sum the area of each crop in tyhe mix plus any monocrops and uenter the totals in section 5.1.1 Collumn 3. 4. Once the quantity harvested is obtained , caklculate the yields (metric tonnes/acre) and compare the figures with the norms given in the crops code box. If there is significantly differentce, check the area and the amouint harvested.. Definitions and working page for page 4 . . Appendix III 146 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 5.0 PERMANENT AND TEMPORARY CROP PRODUCTION 5.1 ANNUAL CROPS AND VEGATBLE PRODUCTION-SHORT RAINY SEASON Did your household palnted any crop duding short rainy season for 2007/08 agricultural year? Yes = 1, No = 2,(If the answer is yes proceed to Section 5.3) 5.1.1 Provide the following details for each crop planted during the short rainy season for 2007/08 agricultural year Quant ity Quantity used Meas urem ent Quantity used (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) …………………. …………………. …………………. …………………. …………………. …………………. …………………. …………………. …………………. Total area planted Cost Name of Crop Quant ity Quantity used Quantity Cost (Tshs) Cultiv ated area Tyep of fertili sers used Planting Main crop owner: Enetr the number of the hh member from page 2 on informati on for hh members Pembejeo Crop code Actual area plnated (acre) Use of Seeds Irriga ted area Use of fertilisers (If 6 is the answer in col 11 proceed to col 16) Use of chemicals agaisnt weeds (If 6 is the answer in col 11 proceed to col 20) The type of seed plant ed Cultiv ated areaE neo lililot umik a Qunaity of agrochemicals Use of seeds (1) (2) (3) Quantity of fertilisers Coist (Ths) Main crop owner: (Col 4) Enter number of hh member from page 2 on details on hh members in Q. 3 Use of agricultural seeds ( Col 6,) For the whole crop..............1 3/4 of the whole crop..…......2 1/2 of tyhe whole crop..……..3 1/4 ofd the whole crop..……..4 Under 1/4 of the whole crop...5 Qunatity ( Col 7) Kg …….1 Seedlings....2 Gram…..3 Type of fertilsers ( Col 12) Organic fertiliser………...1 inorganic fertlisers…....2 Quantity ( Col 17) Kig …….1 Litre.........2 Gram…..3 Millilitre…..6 Use of farm inputs ( SCol10,11 & 16) For the whole crop..............1 3/4 of the wholrecrop..…......2 1/2 of tyhe whole crop..……..3 1/4 ofd the whole crop..……..4 Under 1/4 of the whole crop...5 Not used ……….…….6 Type of seeds planted ( Col 5) Local seeds …1 Improved seeds..……....2 Kipimo ( S/wima 13) Kilo …....1 Lita........2 Milli-lita..3 Identificatoion ● ● ● ● ● ● ● ● ● ● Appendix III 147 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 5.2 ANNUAL CROPS AND VEGATBLE PRODUCTION-LONG RAINY SEASON CONTINUED … 5.2.1 Provide the following details for each crop planted during the short rainy season for 2007/08 agricultural year (20) (21) (22) (23) (24) (25) (26) (27) (30) (32) (33) ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. ………………………….…….. Area used Quant ity Use of fungicides (If 6 is the answer in col 20 proceed to col 24) Size Used Cost (1) (2) Name of crop Crop code Area used Use of pesticides (If 6 is the answer in col 24 proceed to col 28) Harvesting and Storage Cost Quantity harvested (kg) Size Used Quant ity (28) (29) (31) Main stora ge meth ods Main problems in crop marketin g Marketing Quantity sold (kg) Quantity stored (kg) Where was the crop mostly sold? Marketing problems (Col 33) Very low prices….............01 No problem ................11 No transport……….......02 Others (Specify ...........98 High transport costs.......03 Not applicable ......99 Lack of crop buyers .......04 Markets located far away ..05 Problems with farmers Associations 06 Probloems with cooperative Unions ....7 Problems with Businessmen Association ...8 Strigent Government Conditions ...9 L k f k ti i f ti 10 Use of farm inputs ( Col 20&24) For the whole crop..............1 3/4 of the wholrecrop..…......2 1/2 of tyhe whole crop..……..3 1/4 ofd the whole crop..……..4 Under 1/4 of the whole crop...5 Not used ……….…….6 Quantity ( Col 21&25) Kig …….1 Litre.........2 Gram…..3 Millilitre…..6 Main Storage mechanisms (Col 30) Locall storage facilities…………….…..1 Improved Local storage facilitiiies ...........2 Modern store…....……………........…..3 Open drums/sacks.. ..........…..4 Cealed drums.……………..5 In heaps.............O.............................6 not Stored...........................................7 Other means ()Specify.........…………….....8 Where the crop was sold(Col 32) Neighbours………..….…..01 Private Businessman......08 Open markets. ………….......02 Contract farming.....09 Auctions………………...03 Not sold…….…….......10 Main Market….……….....04 Others ..........…...…........98 Cooperative Union….05 Farmers Association..06 Large Scale farm…….....07 Identification Appendix III 148 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Working area/calculation space Storage (Col. 30, Q 5.1.1): - Traditionally Made strcutures: The design of storage structures villagers have inherited from forefathers . - Improved Traditionally made structures: The design of tradional storagesrutures improved through modern technology. Marketing Challenges Q 5.1.1 Col. 33: - Farmers' Association: Village farmers who came together and started an association for the puporses of purchasing inputs/selling/storage of crops aiiming at fetching better prices. - Cooperative Union: A large inter-village/community set up in the district/ region or at national level for providing inputs, markets and storage of farmers' crops. - Government Regulatory laws for crops marketing: Government instituted laws for regulating transportation and selling of crops. Q 5.1.1 Col 31 1. For each of crops listed indicate major marketing problems for 2007/2008 agricultural season. Q 5.1.1. Instructions on crops storage: 1. For the listed crops establish whether or not the household stored crops for 2007/2008 agricultural season. 2. For the listed crops give explanations on storage. Inputs (Q 5.1.1) Farm Yard Manure: An organics fertliser made on farm from animal dung. . Compost: An organic fertiliser made on farm from decomposed plant materials. Insectcides: This is the chemical usde in protecting plants or killing pests. Fungicides: Protects plants from fungi attack. Herbicide: Chemicals used to control or kills weeds. Improved seeds: Scientifically attested to be suitable for agricultural use. Crops storage is keeping/reserving crops in a container or a special place for future use. Definitions and working page for page 5 Questions specific definitions Appendix III 149 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Working table for the calculation area for annual mixed crops Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 The remaining area for temp crops Name of the crop temp/permanent 1 Name of the crop temp/permanent 2 Name of the crop temp/permanent 3 Check total area Check total area for temporary crops plant Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 The remaining area for temp crops Name of the crop temp/permanent 1 Name of the crop temp/permanent 2 Name of the crop temp/permanent 3 Check total area Check total area for temporary crops Total area for mixed crops Total area for permanent crops (a) (b) % of temporary Area for temporary crop (d) (e) (f)=(d)*(e) Mazao mchanganyiko 2 (acre) plants (acre) % of temporary Area for permanent crop Total area mix (acre) Area for Total Total area Name of (e) (f)=(d)*(e) Total Area for mixed crops Total area for permanent crops (a) (b) (c) (d) Mixed crops 1 (acre) of plants Crop Name for plants number of plants Total area of mixed (acre) Area Total Total area (acre) (c) the plant of for plants 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . 0.000 . 0.000 0.000 0.000 0 . 0 . 0 . 0 . 0 . . . . . . . . . . . . Planted Area: Area in acre the household was able to plant Harvested Area: Area in acre the household was able to harvest a large portion of harvests . this is the same as the area planted minus the area that was destroyed by floods/ pets / Crop Codes(Creal / Tubers/ Roots: Code Crop 11 Maizei 12 Paddy 13 Sorghum 14 Buirush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatoes 23 Irish Potatyoes 24 Yams 25 Cocoyamsi 26 Onions 27 Gingeri Crop Codes Legumes and Oil Code Crop 31 Beans 32 Cowpeas 33 Green Gram 34 Chick Peas 35 Dengu 36 Bambara nuts 37 Njegere 41 Sun flower 42 Simsim 43 Ground uts 47 Soya beans 48 Caster Seed Vegetable Codes: Code Crop 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkin 93 Cucumber 94 Egg plant 95 Water mellon 96 Cauliflower 06 Melllon 05 nyanyachungu 02 Ocra 03 Radish 01 Green Beans 04 Bizari Cash crop codes: Code Crop 50 Cotton 51 Tobacco 53 Payrethrum 62 Jute 19 Seaweed Temporary/Annual Crops Crops planted and harvested within 12 months after which time the plants die . Most annual crops are planted and harvested on a seasonal base. Instructions for calculating the area of mixed crops in a mixture A. If the mixed crop is mixed annual ly only enter the total area of the field in the remaining area under temporary Crop and go to step one of these instructions B. If the mixed crop is mixed permanent and annual try to work tyhe percent age taken by the different crops and calcualet the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annula crops in the mix. C: Number of trees method to calculate annual crop areas in a permanent-annual crop mix.: (i) List each of tyhe permanent crop in collumn b and enter the ground area per acre for each permanent crop ( from instrcutions for page 8) in colum d. (ii) Enter the number of permanent trees in the mix in collumn e as will be provided to you by the respondent (iii) Calculate the area occpied by each crop by multiplying collumn d and collumn e and sum up these to obatin the total area of permanent crops in the mix. iv) To obatin the area for tempofrary crops , substract (-) the area fro permanent crops from thne total area of crop mix and enter the resulst in in the total area under temporary crops. (v) Proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each temporary crop in tyhe crop mix and estimate percentages of each crop. 2. Using the percentage for each crop, calculate the are for each crop from the remaining area under tenmporary crop. 3. After completing the exrcise for all the fields, sum the area of each crop in tyhe mix plus any monocrops and uenter the totals in section 5.1.1 Collumn 3. 4. Once the quantity harvested is obtained , caklculate the yields (metric tonnes/acre) and compare the figures with the norms given in the crops code box. If there is significantly differentce, check the area and the amouint harvested.. Definitions and working page for page 6 . . Appendix III 150 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 5.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION Does your household have any permanent/perennial crops or fruit trees Yes =1, No = 2, (If answer is NO proceed to Section 6.0) 5.3.1 Give details on permanent/perennial crops or fruit trees Quant ity Used (1) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) …………………..……… …………………..……… …………………..……… …………………..……… …………………..……… …………………..……… …………………..……… …………………..……… …………………..……… Production Section Mixed crops Monocrops Name of permanent/perennial crop crop code of permane nt / perennial crop/frui t trees Area for trees/seedling/bra nch/bushes Number of Tplants/ trees in the crop mixh of permanent and perennial crop Are for mixed crops Farm inputs Main crop owner: Enetr the number of the hh member from page 2 on informati on for hh Irriga tion Size Uses of Fertilisers (If 6 is the answer in col 13 proceed to col. 17) Area used Quantity of fertiliser (kg) The type of fertilis er used Cost (Ths) Uses of seeds Cost (Ths) Cultiv ated area Type of plant ed seeds (2) (3) (4) (Acre) Area culltivated ( col. 8) For the whole crop..............1 3/4 of the whole crop..…......2 1/2 of tyhe whole crop..……..3 1/4 ofd the whole crop..……..4 Under 1/4 of the whole crop... Type of seed planted ( Col 7) Local seeds...............1 Improved seeds........2 Dont't know/ Not applicable...3 Type of fertils ers ( C ol 14) Organic fertiliser… … … ...1 Qunatity ( Col 9) Kg …….1 Seedlings....2 Gram…..3 Use of farm inputs ( Col 12 & 13) For the whole crop..............1 3/4 of the wholrecrop..…......2 1/2 of tyhe whole crop..……..3 1/4 ofd the whole crop..……..4 Under 1/4 of the whole crop...5 Not used 6 Main crop owner (Col 6): nter the number of the hh member from page 2 on information for hh members in Q 3 Identification ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Appendix III 151 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 5.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION CONTINUED ….. I 5.3.1 Give details on permanent/perennial crops or fruit trees during 2007/08 agricultural year (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (33) (35) ……………………. ……………………. ……………………. ……………………. ……………………. ……………………. ……………………. ……………………. ……………………. Uses of weeds control chemical (If 6 is the naswer in col 17 Proceed to col 21) Area used Size Cost Quant ity Used Area used Quantity harvested (kg) Harvested area (acre) Quantity of mature plants Use of pesticides (If 6 is the answer in col 25 proceed to col 29) Crop harvesting and storage Njia Kuu ya kuhif adhi Cost Size Used Quantity stored (kg) Quant ity Quantity sold (kg) Main marketin g problem Area used Quant ity Use of fungicides (If 6 is the answer in col 20 proceed to col 24) Size Used Cost (1) (2) Name of crop Crop code Marketing (29) (30) (31) (32) (34) Marketing problems (Col 35) Very low prices….............01 No problem ................11 No transport……….......02 Others (Specify ...........98 High transport costs.......03 Not applicable ......99 Lack of crop buyers .......04 Markets located far away ..05 Problems with farmers Associations 06 Probloems with cooperative Unions ....7 Problems with Businessmen Association ...8 Strigent Government Conditions ...9 L k f k ti i f ti 10 Main S torage mechanis ms (C ol 33) Locall storage facilities… … … … … .… ..1 Improved Local storage facilitiiies ...........2 Modern store… ....… … … … … ........… ..3 Open drums/sacks............ ..........… ..4 C ealed drums.… ...................… … … … ..5 In heaps.............................................6 not S tored...........................................7 Other means ()S pecify.........… … … … … .....8 Area us ed ( C ol 20&24) For the whole crop..............1 3/4 of the wholrecrop..… ......2 1/2 of tyhe whole crop..… … ..3 1/4 ofd the whole crop..… … ..4 Under 1/4 of the whole crop...5 d Quantity ( C ol 18, 22, & 26) Kig … … .1 Litre.........2 Gram… ..3 Millilitre… ..6 Identification ● ● ● ● ● ● ● ● ● Appendix III 152 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Working area/calculation space Storage (Col. 30, Q 5.2.1): - Traditionally Made strcutures: The design of storage structures villagers have inherited from forefathers . - Improved Traditionally made structures: The design of tradional storagesrutures improved through modern technology. Marketing Challenges Q 5.2.1 Col. 33: - Farmers' Association: Village farmers who came together and started an association for the puporses of purchasing inputs/selling/storage of crops aiiming at fetching better prices. - Cooperative Union: A large inter-village/community set up in the district/ region or at national level for providing inputs, markets and storage of farmers' crops. - Government Regulatory laws for crops marketing: Government instituted laws for regulating transportation and selling of crops. Q 5.2.1 Col 33 1. For each of crops listed indicate major marketing problems for 2007/2008 agricultural season. Q 5.2.1. Instructions on crops storage: 1. For the listed crops establish whether or not the household stored crops for 2007/2008 agricultural season. 2. For the listed crops give explanations on storage. Inputs (Q 5.2.1) Farm Yard Manure: An organics fertliser made on farm from animal dung. . Compost: An organic fertiliser made on farm from decomposed plant materials. Insectcides: This is the chemical usde in protecting plants or killing pests. Fungicides: Protects plants from fungi attack. Herbicide: Chemicals used to control or kills weeds. Improved seeds: Scientifically attested to be suitable for agricultural use. Crops storage is keeping/reserving crops in a container or a special place for future use. Definitions and working page for page 7 Questions specific definitions Appendix III 153 ___________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Permanent Crops: These are crops once planted last longer in the farm and need not be replanted after each annual harvest. Most of the permanent plants include tress such as coconut tress, apple trees, grape trees, banana trees, pineapple trees etc. Number of Trees: These include manure trees and premature trees. Number of mature plants: A total of fruit bearing tress (e.g. mango trees, orange trees, avocado trees e.t.c). Instructions for permanent monocrops and crop mix: A. For a field with permanent monocrop enter farm size in collumn. 3. B. For a field with a permanent crop mix or a temporary crop mix, enter the number of trees only in collumn 4. C. For a field with a permanent crop mix /temporary annual crops , either: -Enter the area in collumn 4, if the total arae for permanent crops was obatined through calcualtion of percentages of each crop OR Enter the number of tree in collumn 5, if the number of plants/ seedlings of permanent crops was excluded Permanent crops:( crop oils) Code Crop Area per crop 44 Palm Trees 0.00049 45 Coconut tree 0.00037 46 Cashew nut tress 0.00062 Permanent crops: Code Crop Area per crop 70 Passion Fruit 0.00074 71 Bananas 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Pawpaw 0.00037 76 Orange 0.00074 77 Grape fruit 0.00074 78 Grape 0.00012 79 Mandarin 0.00074 80 Guava . 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Peaches 0.00074 84 Mifyoksi 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack Fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread Fruit 0.00099 38 Malay apple 0.00074 39 Star Fruit 0.00074 (Sakua) Permanent crops ( Cash crops) Code Crop Area per crop 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar-cane 0.00012 61 Cardamon 0.00049 63 Tamarin 0.00099 64 Cinarmon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black pepper 0.00037 34 Pigeon Peas 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 86 Lemon Grass 21 Cassava: Cassava is a temporary crop, in order to simplify data collection on areas of production, data on cassava will be collected from areas under permanent crops. Definitions and working page for page 8 Appendix III 154 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Working area/calculation space Storage (Col. 33, Q 5.3.1): - Traditionally Made strcutures: The design of storage structures villagers have inherited from forefathers . - Improved Traditionally made structures: The design of tradional storagesrutures improved through modern technology. Marketing Challenges Q 5.3.1 Col. 35: - Farmers' Association: Village farmers who came together and started an association for the puporses of purchasing inputs/selling/storage of crops aiiming at fetching better prices. - Cooperative Union: A large inter-village/community set up in the district/ region or at national level for providing inputs, markets and storage of farmers' crops. - Government Regulatory laws for crops marketing: Government instituted laws for regulating transportation and selling of crops. Q 5.3.1 Col 35 1. For each of crops listed indicate major marketing problems for 2007/2008 agricultural season. Q 5.3.1. Instructions on crops storage: 1. For the listed crops establish whether or not the household stored crops for 2007/2008 agricultural season. 2. For the listed crops give explanations on storage. Inputs (Q 5.3.1) Farm Yard Manure: An organics fertliser made on farm from animal dung. . Compost: An organic fertiliser made on farm from decomposed plant materials. Insectcides: This is the chemical usde in protecting plants or killing pests. Fungicides: Protects plants from fungi attack. Herbicide: Chemicals used to control or kills weeds. Improved seeds: Scientifically attested to be suitable for agricultural use. Definitions and working page for page 9 Questions specific definitions Appendix III 155 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Irrigated farming: Section 6.5: Source of irrigation water (Col 1): The main source of the water used for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source Irrigatable area (Col 3): The area the irrigation system is designed to cover in acrage Area of irrigated land during the 2007/08 (Col 5): Area of land under irrigation during the 2007/08 agricultural year. This is the actual area nd NOT the cumulative areas recultivated in 2 or more cropping seasons. Q 6.5 Irrigation. 1. If a household uses irrigated farming give explanations aon source and method of obatining water. . 2. See Col 10, Q. 5.1.1 and 5.2.1 and Col 12, Q 5.3.1 to see if irrigation was applied to any crop. Investment in agriculture Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be irrigation structures, erosion conrol and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Section 6.2 Use of draft animals Animals used in agricultural activities by the household during 2007/08 agricultural season. Castrated Bulls: Castrated oxen meant for use in agricultural production. Uncastrated Bulls: mature bulls used for garicultrural activities but are not castrated. Cow: Farmers also use mature female cattle in agricultural activities due to shortage of bulls Donkey: Mature Male or female donekys are also used for agricultural production. Farm inputs: Sections 6.3 and 6.4 1. Collumn 2 Indicate whether or not inputs were used. 2. Compelte collumn 3 by indicating where the inouts were obatined and collumn 4 by indicating the distance from where the inputs were obatined Compost: An organic fertiliser made on farm from decomposed plant materials. Insectcides: This is the chemical usde in protecting plants or killing pests. Fungicides: Protects plants from fungi attack. Herbicide: Chemicals used to control or kills weeds. Improved seeds: Scientifically attested to be suitable for agricultural use. Farm implements, Q 6.1: 1. Collumn 2 Indicate whether or not inputs were used 2. Complete collumn 3 by entering the number of inputs used. Farm Implements (Col. 1): Machette : Includea all implements use in tree cutting namely cicle, et.c. Sprimkler: The pump carrued on the back or a hand used water pump Hand used small tractor: A small tractor used in cultivation while the user walks on foot (see photo). Definitions and working page for page 10 Appendix III 156 ___________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 6.2.6 6.3 USE OF ORGANIC FERTILISERS Cows Donkeys Type of fertiliser Used Yes=1, No=2 Quantit y Shredding Machine (1) (2) (3) (4) (5) Power Tiller 6.3.2 Manure 6.3.3 Compost Name of inputs (4) Compost IRRIGATED FARMING Did the household use irrigated farming during 2007/08 agriculture year? Yes=1, No = 2 If the answer is yes proceed to Section 6.6 Na. 6.5.2 Source Inorganic fertilisers Area that can be irrigated (Acre) Quantity used Area used (Acre) Used (Yes=1, No=2) Distance (3) Give details on inputs used during 2007/08 agricultural year (3) (1) (2) Improved seeds (2) (1) Insecticides/Fungicide Pest and weeds control chemicals Uncastrated bulls Tractor tiller Main source of obtaining water Main source of water for irrigation Oxen pulled plough for making terraces Area irrigated during 2007/08 agriculture year (Acre) ACCES TO INPUTS Tractor hallow Farm yard manure Castrated bulls Give details on the use of organic fertlisers during 2007/08 agriculture year Power Tiller 6.3.1 (4) Source (Col.3) Government.….......................01 Cooperative Union…... ...02 Farm inputs store/market.......03 Auction..............................04 Development project…….....05 Corp buyers…........06 Large Scake farms….......07 Made by the household.......08 Form neighbour...........................09 Cooperative Union…….....10 Others .....……….............98 Not applicable.................99 Distance from the source (Cola 4 ) Under 1 kilometre………….…......1 Btween One and three kilometres ......2 Btween three and 10 killometres3 Between 10 and 20 Kilometres .......4 Over 20 Kilometres......………….........5 Not applicable..........................................9 Means of obtaining water(C0l2) Flwoing. (gravity)...….…………...1 Using a bucket….…………………….....2 Water pump (using hand or leg)...………...3 Electric /fuel driven pump/ mafuta……………..4 Other (Specify).….....……………………….8 Source of irrigation water (Col 1) River…………………1 Wells …………………..…..4 Lake ………………2 Deep wells………….…… .5 Dams.…………….3 Cannals ….…………………. .6 Tape water……..…… …7 ● ● ● KQuantity (Col 3) Kg...….……1 Ton………...2 ● ● Appendix III 157 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Q 6.6 The type of erosion contro/Water harvesting (Col 1) Terraces: Structures constructed on mountain slopes to provide flat terrain for crop planting. Erosion control bunds: these are bunks of earth/stones built perpendicular to the slope to slow dowm the speed of water and thus preventing soil erosion. Its differs from terraces in that the soils on these banks are not at ground level . Gabions: A box like structure made of wire and filled with large stones to prevent gully errosion. Sand bags: Are used in controlling and preventing gully errosion Tree belt/wind breaks: Trees planted against the wind direction for breaking wind speed.. Section 7.0 Acces to credit for crop or livestock production Credit refers to something provided in cash or in kind (such as farm inputs, machines, livestock and other things) for crop or livestock production. The value of the credit must be repaid back to the lender. An Interest may or may not be attached to the value of the credit The credit may be repaid either in cash or through farm produce to be harvested . In this question the enumerator is at liberty to inquire up to three sources of credit where the farmer accessed credit from more than one source. Section 7.0 Source of agriculture credit If tghe farmer obtained credit from more than one source the use the code from the list provided. Start with the main source of credit in Section "7.1.1".a Q 6.6 Number of water harvestin structures and year of construction 1. The number water haversting structures refers to the number of wokring / maintained structures and does not include derelict or iireparable structures. 2. Year of construction refers to the year in which the structures were built, and not the year the structures were last repaired.The year should be written in figures e.g. 1998, 2006. Section 8.0 Agricultural extension services 1. Ask if the household did receive agricultural extension services during 2007/08 agricultural season from the respondents listed in collumn 1, then enter column 2. 2. Complete all columns for every extension officer. Section 8.0 Agricultural Extension Services Agricultural Extension Services: Refers to educational services provided to farmers by exetsion officers for the purposes of increasing crop and livestock production. Share-cropping: Refers to farming where smallholder / Smallscale farmer enters into an agreement with large scale farmer where the former sells produce to the latter in exchange of provisions of farm inputs and the like. . Contract farming Farming: Farming agreement entered between smallscale and large scale farmerswith regards to markets of farm produce and provision of farm inputs Definitions and working page for page 11 Appendix III 158 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 6.6 SOIL EROSION 6.6.1 Did the household experience soil erosion during 2007/08 agriculture year? (Yes=1,No=2) 6.6.2 Na. 6.6.3 6.6.7 Tree belt 6.6.4 6.6.8 6.6.5 6.6.9 Trenches 6.6.6 6.6.10 Other 7.0 7.1 SELECT UP TO THREE SOURCES AND PROCEED TO QUESTIONA 8.0 Source of credit 7.1.1a 7.1.2a 7.1.3a Credit provided to 7.1.1b 7.1.2b 7.1.3b (Male=1, Female=2) 7.2 IF THE ANSWER TO QUESTION 7.1 IS NO Give reasons for not accessing credit 8.0 ADVISORY SERVICES IN AGRICULTURE 8.1 8.2 Na. Advise on agriculture (3) 8.3.1 Spacing 8.3.2 Use of agrochemicals 8.3.3 Soil erosion control 8.3.4 Use of organic manure 8.3.5 Matumizi ya mbolea za viwandani 8.3.6 Use of improved seeds 8.3.7 Use of modern farm implements 8.3.8 Irrigation 8.3.9 Crop Storage 8.3.10 Pest control 8.3.11 Other (Specify) (3) Terraces (2) Is there any household member who accessed on farm credit during 2007/08 agriculture year? Yes=1, No=2 (If answer is NO, Proceed to Section 7.2) (3) (1) (1) (2) Source of advise Soil bunks of water harvesting Did the household participate in the contract farming during 2007/08 agriculture year? (Yes=1, No=2) Gabions/sand bags Bunks for erosion control ACCESS TO ON FARM CREDITS Did the household participate in outgrowers scheme during 2007/08 agriculture year? (Yes=1, No=2) Vetiva leaves (2) Did your household receive agricultural advise on the following : (IF THE ANSWER IS NO IN COL 2 PROCEED TO THE FOLLOWING QUESTION (1) Rceived advice (Yes=1, No=2) Did the household applied any methods for erosion contro/water harvesting during 2007/08 agricultural year? Mechanisms of controlling erosion/ Water harvesting Number of water harvesting Year of construction Type of erosion control/water harvesting Year of construction Number of water harvesting (Yes=1, No =2) (If the answer is No, Proceed to Section 7.0) (Source of credit Q 7.1.1, 7.1.2, 7.1.3) Relative...... 1 Saccos....4 NGO/Development projectsi........7 Bank... ……......................2 Busineman/Shop................5 Cooperative Union...........3 Priviate individuaks...............................6 Other...............9 Source of agricultural advice (Cokl. 3) Government……1 NGO/Development project.....2 Cooperative….3 Large Scale farmer….4 Ratdio/Newspapers….5 Neighbour ..........6 Other source………..8 Reasons for not accessing credit (Q 7.2)COL Not required …........1 Did not to be indebted...........3 Did nott know how to access credit......5 Credit delayed......7 Did not credit existed.....9 Not available ..............2 High interest rates......4 Bureaucracy.............................................6 Other (Specify)...........8 Identification 8.3 Appendix III 159 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Section 9.3 Goat Note: Question 9.3 is for the actual number of owned or raised by the household (as of 1st October 2008) This number does not include g oats kept on behalf by relatives or neig hbours, that is the g oat outside the residential area of the household under survey. 1. If the household has she goats, you would normally expect them to have kids Type of cattle (sectioin 9.1.1 to 9.1.7) Bull: Mature uncastrated made cattle used for breeding Cow: Mature female cattle that has given birth at least once Ox: Castrated made cattle used for farm work Steer: Castrated made cattle us ed for meat Heifer: Female cattle of 1 year up to the first calving Q 9.1 and 9.3 : What is required is to establish whether or not the household kept or raised the listed livetsock during 2007/08 agricultural season (i.e. from October 2007 to September 2008). Also to establish the number of livestock as of 1st October 2008 Keeping or raising livestock is to to keep livestock at home while providing the livestock with animal feeds and medication and other services. The livestock could be owned by the farmer or kept on behalf of relatives or neighbours . Sections 9.1.1 to 9.1.7 Cattle Note: Q 9.1 is for the actual number of cattle owned or kept by the household (as of 1st October 2008). This number does not include herds of cattle kept on behalf by relatives or neighbours; that is, the cattle outside the residential area of the household under survey. 1. If the the household keep mature fecund female cattle, it is expected that such a household will have calves which will be entered in question 9.1.6 or 9.1.7 Type of Goat (Qs 9.3.1 to 9.3.5) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated She Goat: Mature female goat over 9 months of age Definitions and working page for page 12 Appendix III 160 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 9.0 LIVESTOCK (LIVESTOCK AND FISH) 9.1 CATTLE Number of cattle as of 1.10.2008 No. 9.1.1 9.1.2 9.1.3 9.1.4 9.1.5 9.1.6 Male calves 9.1.7 Grand total 9.1.8 What main methods do you use to identify your cattle? 9.2 Milk production: CATTLE Na. Season Type of cattle Number of milked cows (1) (2) (3) 9.2.1 Improved 9.2.2 Indigenous 9.2.3 Improved 9.2.4 Indigenous 9.3 GOAT Number of goats as of 1.10.2008 Na. 9.3.1 9.3.2 9.3.3 9.3.4 9.3.5 Grand total Milk Production: GOAT Na. Number of ilked goats (2) 9.3.6 9.3.7 (3) (4) Average of milk per goat per day (litre) Average number of days which your she goats were milked for meat Dairy (2) (3) (4) Castrated bulls (4) Did your household keep or raise cattle during 2007/08 agriculture year? Yes=1, No= 2 (If the answer is No proceed to Section 9.3) Number of indigenous cattle Type of cattle uncastrated bulls Total Number of improved cattle (5) Cows Steers (1) (2) Heifer Female calves Number of indigenous goat Tyep of goat Did your household keep or raise cattle during 2007/08 agriculture year? Yes=1, No= 2 (If the answer is No proceed to Section 9.3) Number of improved Average of milk per cow per day (litre) Average number of days which your cows were milked Dry (1) She goat Male kid She kid Season (5) Rainy Dry Rainy (3) (4) for meat Dairy Male uncastrated goat Male castrated goat Average price per litre per season (6) Average price per litre per season (5) (5) Total Cattle idenfificatio methods Iron stamp (chapa moto)…......1 Throat….2 Ear/tail cutting…..3 Colour……..4 Earings…5 Other ……………....8 Identification ● ● ● ● ● ● Appendix III 161 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Section 9.5 Pigs Note: Question 9.3 is for the actual number of pigs owned or raised by the household (as of 1st October 2008). This number does not include pigs kept on behalf by relatives or neighbours, that is the cattle outside the residential area of the household under survey. . 1. If the household has she goats, you would normally expect them to have kids in column Type of Sheepe (Sectioin 9.4.1 to 9.4.5) R am: Mature Uncastrated male sheept used for breeding C as trated s heep: Male sheep that has been castrated E we: Mature female sheep over 9 months of age L amb: Y oung sheep under 9 months of age. Q 9.1 and 9.3 : What is required is to establish whether or not the household kept or raised the listed livetsock during 2007/08 agricultural season (i.e. from October 2007 to September 2008). Also to establish the number of livestock as of 1st October 2008 Keeping or raising livestock is to to keep livestock at home while providing the livestock with animal feeds and medication and other services. The livestock could be owned by the farmer or kept on behalf of relatives or neighbours . Sections 9.4 Sheep Note: Q 9.4 is for the actual number of sheep owned or kept by the household (as of 1st October 2008). This number does not include sheep kept on behalf by relatives or neighbours; that is, the sheep outside the residential area of the household under survey. 1. If the the household keep ewes, it is expected that such a household will have calves which will be entered in question 9.1.6 or 9.1.7 Type of Pigs (Qs 9.5.1 to 9.5.5) Boar: Mature Uncastrated male pig used for breeing S ow: Mature female pig that has given birth to at least one ltter of pigs. G ilt; F emale pig of over 3 months up to the first farrowing P iglet: Y oung pig less than 3 months of age Definitions and working page for page 13 Appendix III 162 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Appendix III 163 ___________________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 9.4 SHEEP 9.5 PIGS Number of sheep as of 1.10.2008 Number of pigsp as of 1.10.2008 Na. Na. 9.4.1 9.5.1 9.4.2 9.5.2 9.4.3 9.5.3 9.4.4 9.5.4 9.4.5 9.5.5 Grand total Grand total 9.6 OTHER LIVESTOCK 9.6.1 Local chicken 9.6.2 Layers 9.6.3 Broilers 9.6.4 Ducks 9.6.5 Guinea pigs (2) (3) Turkeys Rabbit 9.6.8 Type of animal 9.6.10 Horses Dogs (3) 9.6.9 1 Donkeys 9.6.6 9.6.7 Number of Eggs Number as of 1 October 2008 2007/08 agriculture year Female lamb Female piglet Type Pigs Number of pigs Boar Castrated male Sow/Gilt Male piglet (1) (2) She sheep Male lamb Did your household keep or raise cattle during 2007/08 agriculture year? Yes=1, No= 2 (If the answer is No proceed to Section 9.6) Ram (5) (1) (2) (3) Castrated sheep Type of animal 2007/08 agriculture year (1) Number as of 1 October 2008 (2) Number of eggs Did your household keep or raise cattle during 2007/08 agriculture year? Yes=1, No= 2 (If the answer is No proceed to Section 9.5) Type of sheep Number of indigenous sheep Total Number of improved Identification Appendix III 164 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Definitions and working page for page 14 Control of livestock dieases causing bugs Livestock worm control medicine: Medicine used to kill or control livestock on livestock . It is often used for cattle, goats, sheep and pigs. Tiick: Is a dangerous bug that sucks blood form livestock and transmits animals diseases from one to the other animal. Tse tse fly: A fly like bug that sucks blood from livetsock and transmits diseases sleewping sickness from one to the other animal. Livestock advice (Section 9.8) IA service provided by extension officers to livestock keepers for increasing livestock production. 9.7 9.7.1 Cattle 9.7.2 Goat/Sheep 9.7.4 Poutry 9.7.5 Do you experience tick problem with your livestock? (Yes =1, No = 2, Not applicable 3) 9.7.6 How did you control tick problem? Do you experience Tse tse problem with your livestock? (Yes =1, No = 2, Not applicable 3) 9.7.8 How did you control Tse tse problem with your livestock? 9.7.9 9.7.10 How do you control Newcastle disease problem with your poutry? 9.7.11 9.7.12 How did you cotrol/ cure Fowl Typhoid with your poutry? 9.7.13 A:Foot and Mouth diseases 9.7.13B: Skin disease 9.8 Extenmsion services on livestock Na. Livestock extension advice Soure of Extension (3) 9.8.1 Feed and better feeding methods 9.8.2 Improved livestock shed (Goat, Dairy cattle, Poutry and pigs) 9.8.3 Milking and hygiene 9.8.4 Cattle fattening 9.8.5 Livetsock diseases control 9.8.6 Livestock keeping in line with land availability 9.8.7 Pasture establsihment and maintanence 9.8.8 Forming and strengthening groups/cooperatives 9.8.9 Calf rearing 9.8.10 Basics of production and use of improved bulls (AI) 9.8.11 Animals feed production 9.8.12 Other extension advice (Specify) ……………………………………… 9.7.13 Were your cattle vaccinated agaionst the following diseases? (Yes = 1, No = 2, Not applicable=3). (1) Received Extension advice (Yes=1, No=2) Did you receive the following extension advice on the followingJe? (IF THE ANSWER IS NO IN COL 2 PROCEED TO THE FOLLOWING QUESTION (2) Do you experience Newcastle disease problem with your poutry? (Yes =1, No = 2, Not applicable 3) Did you experience Fowl Typhoid with your poutry?Yes=1, No=2 , Not applicanblei=3 NOTE : If answers to Qs 9.1 to 9.6 is No (THAIS THE HOUSEHOUSE DOES NOT RAISE LIVESTOCK,) Proceed to q 9.9 LIVESTOCK DISEASES AND PEST CONTROL Which animals did your deworm? ( Yes=1,No =2, Not applicable=3 in the relevant box) Did you livestock during 2007/08 agriculture year? (Yes=1, No=2) (If the answer is No proceed to Section 9.7.5 9.7.3 Pigs Control method (Q. 9.7.6): Dipping………1 Spaying………...2 Application of medicine on back bone……..…………..3 None..4 ........... Other....…8 Control/Curative methods (Q. 9.7.10) Vaccination..1 Herbs....2 None..3 Contro/curative methods(Swali 9.7.12 Vaccination..1 Herbs....2 Noe.3 Control method (Q. 9.7.8): Dipping………1 Spaying………...2 Traps……..…………..3 None..4 ........... Other....…8 Identificatio Source of agriculture extesnion(S/wima 3) SGovernment……1 NGO/Development project.....2 Cooperative Union….3 Large Scale farmer….4 Radio/TV/Newspapere.5 Neighbour……6 Other source …..8 9.7.7 9.7.7 9.7.7 Appendix III 165 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 I Question S pecific Definitions (Q 9.9 ) Production unit number (C ol 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, tye of fish etc. eg. a farmer may have 3 fish ponds (each one is a separate production unit). Frequency of stocking (C ol . 5): What is the number of time the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. S ols: (C ol 10 & 11) If no fish were sold enter “0” in column 10 and 11` Fish sold (Col.12) Kama hakuna samaki waliouzwa jaza "0" katika safuwima 12 General definitions Fish farming: Refers to the rearing/production of fish. It is different from fishing in that in fish farming the fish have to be reared. While in fishing, fishing nets or traps are used to catch fish from rivers, lakes and the sea; thus fishing should not be included in this section Working space for page 15 Definitions and working page for page 15 Appendix III 166 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 9.9 FISH FARMING Did your household practice fish farming? Yes=1, No=2 (If the answer is no proceed to section 9.10) Give details on the fish farming during 2007/08 agriculture year (1) (2) (6) 9.9.1 9.9.2 9.9.3 9.10 HONEY PRODUCTION Is there honey production/harvesting in your household? Yes=1, No=2 (If answer is no PROCEED to Section 9.11) Give details on honery harvesting during 2007/08 agriculture year Number 9.10.1 9.10.2 9.11 AGRICULURAL CHALLENGES Code (1) 9.11.1 Priority 1 9.11.4 Priority 4 9.11.2 Priority 2 9.11.5 Prioty 5 9.11.3 Priority 3 No. What is the main fish outlet? (7) (8) (9) (11) (12) (13) Aina ya ufugaji Square area of pond waliouzwa (kg) (m2) (3) Total number of fish harvested waliovuliwa (kg) Lulu (10) Kiwango cha Huduma ya bwawa Total weight of all fish Number of Ponds (14) Total number of stoked fish Source of fingering s What is the frequency of stocking during the period? Tialpia Mwatiko Crabs (4) (5) No With first five priorities Code (2) Number of improved bee hives Large bees Type of honey Harvesting done ? (Yes=1, No=2) Small bees (1) (2) Amount sold per year (Litre) Amount of honey sold (litre) (5) (7) (8) Main market) Price per litre Number of local bee hives (6) From the list of cahhalengs in farming on the right of the page, SELECT FIVE MAIN CHALLENGES WHICH constrain your development in agriculture LIST OF CHALLENGES (2) No Important for (1) (4) (3) mainly sold to? (Col 14) Neighbour…1 Auction……………………...3 Large Scale farmers….…..5 Open market….2 Fish processing industry..4 Private business people ….6 Did not sell…….......................……….......7 Other ….......……......8 Type of farming (SCol 2) Natural pond……….1 Small earth pond…….2 Large pond..……………….3 Other …….….………….....8 Source of fingerings(Col 4) From the pond.............................1 Neighbour……….4 Government………………..2 Business man…..5 NGO/Development Project…3 Natural Pond……..6 Other …….…………………..8 Standard of servives to the pond (Col6) High leve ………….1 Intermediate level………….2 Low leve..………3 Don't know.….……………..8 Honey outlet Co 8 Neighbour…1 Auction……………………...3 Large Scale farmers….…..5 Open market….2 Fish processing industry..4 Private business people ….6 Did not sell…….......................……….......7 01 Land availability 14 Lack of off farm incomes 02 Land owenership 15 Harvesting problems 03 Poor farm implementso 16 Kupukuchua 04 Soil fertility 17 Crop stiorage 05 Availability of imrpoved seeds 18 Crop processing 06 Irrigation services 19 Market information 07 Availability of agrochemicals 20 High transporation costs 08 Cists of farm inputs 21 Destructive animals 09 Extension services 22 Crop thefty 10 Availability of forest resources 23 Pests and diseases 11 Huntinf and collection problems 24 Advice from Local government 12 Water availability 25 Long dry spells 13 Access to credits 26 Conflicts between livetsock keepera and pastoralists Identification 2 3 1 Appendix III 167 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Definitions and working page for page 16 10.0 Household poverty indicators Number of rooms used for sleeping in the household (Q 10.1.4) Include sitting room, during room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building / house that is not divided into rooms is considered to have one room. Household assets (Q 10.2): There assets must be functionin. Do not include if broken. Access to drinking water (Q 10.4): If there is more than one source use the one, which the hh uses most frequently. Main source of hh cash income:(Q 10.7: Activity that provides the hh with the most can during 2007/08 agricultural season. Appendix III 168 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 10.0 POVERTY INDICATORS 10.1 HOUSE CONSTRUCTION 10.2 Household property Specify materials used in the construction of the following sehemu zifuatazo 10.1.1 Roof 10.1.2 10.1.3 Wall (1) Radio (Radio, Radio Casette, music system) Land line Celkl phone Iron Trolley Bycicle Vehicle TV/ Video Refrigerator 10.1.4 Number of bedrooms Motorbike/vespa 10.3 Energy use and availability in the hsousehold 10.4 Availability of drinking water 10.3.1 Lightining 10.3.2 Cooking 10.4.1 Rainy 10.4.2 Dry period Note: Code01, Bomba kwa Zanzibar hujulikana kama Mfereji 10.5 Toilet facilities 10.6 Eating patterns 10.5.1 What type of toilet does your hosuehold use? 10.6.1 How many meals does your hosue usually get per day ? 10.6.2 How days did the household eat meat last week? 10.6.3 How days did the household eat fish last week? 10.6.4 How many times did the household experience food shortages last year? 10.7 Main source of household cash income? 10.7.1What are the sources of household income? TIME OF FINISHING THE INTERVIEW Minutes Does your houshold woen the following?, (Yeso=1 No =2) 10.2.1 10.2.2 10.2.3 Yes=1, No=2 (Hours) Distance from source Main source of water 10.2.9 ( km) Time spent waitingor going to and from the source 10.2.4 (2) Property Number Hour (4) (3) (2) (1) Floor Season Main source of energy 10.2.6 10.2.8 10.2.7 10.2.10 10.2.5 Roofing materials Iron sheets………..1 Tiles……...……....2 Concrete…………3 Asbestos ….4 GrassiMakuti……....5 Grass and mud….6 Other ……..….. .8 Nishati za Kuangazia Umeme…………….01 Sola………...…....…02 Gesi (biogas) ………03 Taa ya kandili………04 Karabai…………..…05 Kibatari……………..06 Mishumaa…….……07 kuni……………….…08 Nyingine …………... 98 Nishati za kupikia Umeme…………….01 Sola…..................…02 Gesi (biogas) ………03 Gesi (Kiwandani)..…04 Mafuta ya taa………05 Mkaa….………….…06 Kuni …………...……07 Mabaki ya Mazao….08 Kinyesi cha Wanyama………..…09 Nyingine ……...……98 Main sourece of drinking water Col. 2 Tape water……...…..........................01 Water venders..............................09 Arificial well……..……............02 Boozer.......…10 Arificial spring... .….......…....03 Bottled water.............................11 Openwell………..….....................04 Other (Specify)............................98 Natural spring.…...................05 Lake water,piond,river,stream n etc........06 Covered Rain water harvesting well..07 O i t h ti ll 08 Food shortage problems (Swali 10.6.4) Never …………………...…1 Few times……….………….2 Sometimes…………….……..3 Many times……………….……4 Often………………..5 Code for source of income Selling food crops...........01 Sales of foerst products..05 Cash assisnatce...09 Sales of livestock....…...............02 Business.............................06 Fishingi.....................10 Sales of livestock products......03 Salaries...........................07 Other.................98 Sales of cash crops...04 Casual labour...............................08 None...................99 Tyep of toilet No toilet/in the buish…...1 Pit latrine.….4 Flash toilet……...2 Other type (Specify)………...………...8 Ordinal pit latrine..….3 Floor matrials Earthen material……………..1 Wood…...……………………….2 Wooden tiles…3 Tiles…………………………....4 Cement…………………………5 Other……………………......8 Main materials Grass and pieces of woods.….....1 Mud……...……..2 Wet bricks……….3 Burnt bricks...4 Wood……...............5 Block bricks.......6 Stonese …...………...7 Bricks /Mawe ya kichanga………….8 Idetification ● ● ● ● Appendix III 169 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Average/maximum yields per area Use this table to compare the yields calculated in Sections 5.1, 5.2 and 5.3. These stats are strictly to be used used as a guide for the purpose of assisting to get the correct area and yields for each crop. Name of Name of Crop Crop 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Funger Millet 90 Pepper 16 Wheat 91 Amaranthus 17 Barley 92 Pumpkin 16 Cassava 93 Cucumber 17 Sweet potatoes 94 Egg plant 18 Irish potatoes 95 Water melon 19 Yams 96 Caouliflower 25 Coco yams 52 Cotton 26 Onions 54 Coffee 27 Ginger 55 Tea 31 MaharaBeans 56 Cocoa 32 Cow peas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon peas 59 Kapok 35 Chick peas 60 Sugar cane 36 Bambara nuts 61 Cardamon 41 Sun flower 71 Banana 42 Simsim 72 Avocado 43 Gound nuts 73 Mango 47 Soyabeans 74 Pawpaw 48 Caster seeds 76 Orrage 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin 53 Pyrethrum 80 Quava 62 Jute 81 Plums 44 Palm oil 82 Tufaha 45 Cononut 83 Pea 46 Cashw nut 84 Pitches 66 1,000 5,000 3,750 1,500 1,772 1,969 2,000 30,000 10,000 17,000 4,500 15,000 14,000 15,000 7,000 20,000 25,000 15,000 25,000 3,500 20,000 35,000 5,000 Kilogram/acre 57,000 35,000 20,000 27,000 40,000 50,000 30,000 40,000 150,000 40,000 100 10,000 60,000 20,000 20,000 25,000 50,000 60,000 17,000 30,000 30,000 5,000 3,000 10,000 10,000 40,000 10,000 50,000 15,000 1,000 1,400 50,000 25,000 70,000 800 500 2,500 150 400 60,000 20,243 12,146 16,194 14,170 0 8,097 10,931 23,077 0 60,729 0 20,243 0 10,121 28,340 16,194 8,097 16,194 16,194 4,049 24,291 8,097 8,097 10,121 5,668 20,243 24,291 6,883 12,146 0 16,194 16,194 4,049 24,291 6,073 12,146 2,024 6,073 2,834 0 0 6,073 324 0 24,291 1,215 4,049 0 4,049 20,243 12,146 4,049 8,097 14,170 2,024 12,146 4,049 6,883 8,097 14,170 2,024 8,097 10,121 6,073 10,121 24,291 607 607 0 1,417 2,024 3,239 24 607 607 1,619 688 405 1,619 1,012 304 709 2,024 3,441 1,822 729 2,834 4 2,530 1,619 1,417 1,215 1,012 1,822 729 2,834 3,239 121 10,121 121 202 0 324 466 607 1,012 243 202 243 243 121 243 526 121 243 304 466 567 60,000 1,500 1,500 3,500 5,000 8,000 60/tree 1,500 1,500 4,000 1,700 1,000 4,000 2,500 750 9 6,250 4,000 3,500 3,000 2,500 4,500 1,800 7,000 8,000 300 25,000 300 500 800 1,150 1,500 1,500 600 500 600 600 300 600 1,300 600 750 4,000 2,500 30,000 20,000 400 300 1,400 3,000 1,150 700 750 350 Kilogram/ha 300 1,150 121 466 466 283 304 142 Average Max Max Kilogram/acre Kilogram/ha Average Max Average Max 1,750 1,800 Average 8,500 10,000 5,000 50,000 567 1,215 30,000 1,300 1,215 243 304 3,239 3,441 1,417 Clove Black pepper Mung'unye Ocra Appendix III 170 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Appendix IIIb: Community Questionnaire Access to and Use of Community Resources Farmg Gate Prices of commodoties produced by the village Region …………………………… Ward District …………………………… Village Signature Date of Enumeration Hour Minutes Start Time End Time Field level checking by: District Supervisor Name Signature Date / / Regional Supervisor Name Signature Date / / National Supervisor Name Signature Date / / Distric checking in Office District Supervisor Name Signature Date / / For Use at Regional Level Only Data entered by: Name Signature Date / / Queried Name Signature Date / / Ministry of Agriculturte and Food Security, Ministry of Livestock and Fisheries Development, Ministry of Agriculture and Environment of Zanzibar, Ministry of Water and Irrigation, Prime Ministers' Office Regional Adminstration and Local Government, Ministry of Industry Trade and Marketing, National Bureau of Statistics, and the Office of the Government Statistician General of Revolution Governemnet of Zanzibar Enumerator Name 2007/2008 United Republic of Tanzania Village/Community Level Formats Agricultural Sample Census CONFIDENTIAL ACQ 3 NUMBER OF FARMERS HH IN THE VIALLAGE To be filled by the enumerator after completeing form ACLF2 NUMBER OF HH MEMBERS To be filled by the enumerator after completeing form ACLF2 I To be filled by the supervisor ONLY after Field/farm level checking of the enumeration process. This should be countersigned by the Supervisor in front of the enumerator All questionnaires must be checked at the district office. See the back page for details of queries y y y y m m m d d / / Appendix III 171 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Non G overnment Org anis ation: Is managed by people from outside the village and it normally covers more than one village/District/R egion. Its function is to provide deveoopment assistance to the farmer and is free from direct government links. Villag e level org anization: is managed by members of the village. Its purpose is normally to access/provide development assistance to the village Access to community resources. Section 1.0 Community Resources: Resources in which the hh members have no individual claim to and which are shared together by all the village Community Land: The area officiall demarcated by the village as shared/public land. Squatting farmers Land: Communal land where individual hhs make sole claim to (for crop farming or fenced livestock) without official rights to ownership. Available remaining Land: Official area of communal land minus areas of squatting farners. Givernment Land Reserve: Area set aside by the government as national reserve Community tree planting scheme(Section 14.3) C ommunity F ores t: A forest planted on the communal land which is planted, replanted or spt planted by the members of the village. P lant P lanting : An area designated by the village for planting a block of trees. S pot P lanted: R eplanting an area where selective logging has been carried out. A tree is planted to replace the one that has been cut. Indig eous Trees : T rees that are native to T anzania E xotic Trees : T rees that are not native to T anzania Definitions of some specific terms Definitions and working page for page 3 Question Specific Definitions: Obtain answers to the following questions from the meeting between the enumerator and influencial farmers in the village Infuencial people can be Village Chairman, Village Governement Executive Officer, Councillor, Ward Chairman, Extension Officer in the village or any other person in the village and who is well informed about village matters. It is important to not that these questions must be asked in groups (of more than one people) to obtain answers discussed and approved by many people. Appendix III 172 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 ACCESS TO COMMUNAL RESOURCES 1 ACCESS TO COMMUNITY RESOURCES 1.1 Does the village set aside an area for communal resources e.g. forest, grazing, etc. (Yes =1 No =2) (If the answer is no proceed to 1.2) Are of Comminity, Village, Wrad resources 1.1.1 Total area of communal land Oficial figures from the leader 1.1.2 Area of squatting famers in communal land Key informant (Leader/Extension officer etc.) 1.1.3 Remaining available communal land Key informant (Leader/Extension officer etc.) 1.1.4 Government reserve land Key informant (Leader/Extension officer etc.) 1.2 UPATIKANAJI NA MATUMIZI YA MALIASILI ZA JUMUIYA/KIJIJI/SHEHIA Community Resources 1.2.1 Water for human consumption 1.2.2 Wtar for livestock 1.2.3 Communal grazing land 1.2.4 Communal firewood 1.2.5 Wood for chracoal burning 1.2.6 Wood for building poles 1.2.7 Forest for bee keeping (honey) 1.2.8 Hunting 1.2.9 Fishing 2.0 COMMUNITY PLANTED TREES 2.1 Didi your village have community planted trees during 2007/08 agriculture year? (Yeso=1, No=2) If the answer is no proceed to Section 3.0 Details of the community tree planting scheme No. 2.2 3.0 Non governmental Organisation (NGOs) Contact 4.0 Community Based Organisation 3.1 4.1 Visited Number of Distnatce to the Na. Type of NGO Y=1,N=2 visits Office (km) Na. Type of CBO Nd=1,Hap=2 3.2 Extension/ Rsearch 4.2 Extension/ Rsearch 3.3 Service /Input provision 4.3 Service /Input provision 3.4 Community Development 4.4 Community Development 3.5 Other 4.5 Other 5.1 5.2 5.3 5.5 5.4 Number of local ironsmiths 5.6 Did any NGO visit the village during 2007/08 agriculture year? (Yes=1,No=2) (If no provceed to Section 4) Didi the village have any CBO during the 2007/08 agricuylture year?(Yes=1, No=2) (1) Number of training centres for draft animals Did the village participate in any research on crops/ improved livestock during in the village during 2007/08 agriculture year? (Yes=1, No=2) Did the village have Field farm schools during 2007/08,agriculture year? (Yes=1,No=2) Did the village have any training centres on draft animals during 2007/08 agriculture year? (Yes=1, No=2 ) If number 2 is the answer conclude the enumeration. Did the village have local ironsmiths during 2007/08 agriculture year? (Yes=1, No=2 ) (If the answer is 2 proceed to q. 5.5 (4) Type of seeds/ Seedlings Number of (8) (7) (6) (2) (5) (4) (3) (1) (2) (3) Source of Dustance from the community forest Forest Area (acre) Type of Pllanting Trees Area in acre Distance from the resource in Km -season Main Dry Rainy Use Years since the start of planting Main uses of communal forest products agriculture year 2007/08 Main uses Msin uses (Col. 4) Home or farm /livetsock consumption...1 Sold to traders in the village...........…...2 Sold to the village market................…....3 Sold to local wholesalers........................4 Sold to Big wholewsalers .....................5 Not available.........................................6 Instructions on distance from the resource (Cols 2 and 3): Distance is estimated from the centre of the village. If under1 km 1, enter 0 If abover 1 km 1 enter whole number , eg. 1.5km= 2km, 1.25km= 1km Type of planting Col. 3) POlantion planting……….1 Spot planting…. ……...…….2 Main use of revenue (Col.8) Village development fund.1 Household use……....2 Household iIcome…. ……..3 Source of seedlings (Col. 5) Seeds collection and planting……….…..……....1 Villlage Nursery....……….…..2 Department of Forestry.………. ...….3 Private Individuals…. ……...……..4 Type of trees (Col. 4) Indigenous tress………………..1 Exotic tree….……...…….2 Both types..…………...3 Main Uses (Col. 7) Poles ……………...1 Wood ……..………..2 Charcoal ….. ……….….3 Firewoodi ………………...4 Other (Specify) 8 ● Appendix III 173 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 Code of Minimum Maximamun Name of crop/livestock Name of main crop Main crop Per year Per year (1) (2) (3) (4) (5) (6) (7) Code of crop/livestock Price of measure Type of measure Obtain answers to the following questions from the meeting of enumerator and key informants in the village.Key infomants can be a village chairman, Village Local Government Executive Officer, Councellor, Wrad Chairman, Village extsion officer, or any knowledgeble member in the community. Where possible ask these questions to a group inorder to reach a consensus . The numebr should be below five people. Procedure: Administer this frpom after completing asll smallholder questionnaires for the village. 1. Copy the name of all crops from Sections 5.1, 5.2 and 5.3 grown in the village from smallholder questionnaires This should also include livetsock raised by the household from questions 9.1, 9.3, 9.4 and 9.5 and enter them in col na 1 of this form. Also see codes for livetsock below. 2. Enter price estimates per kg in col 5 and 6. Main poroduct- CROPS (sCol.4) Cereals…………...............01 Flowers eg. Pyrethrum.....07 Green maize…................02 Vegetables….......,08 Green leaves and stem ........03 Fruit…………….....09 Straw, dry stems etc..04 Other………….....10 Roots and tubers, etc......05 Leaves (Tobacco etc)...... …..06 Main product- LIVESTOCK (Col. 4) Live animals…..01 Meat ...........02 Milk...........03 Eggs.............04 Hid d ki 05 Type of livestock(Col 2) Cattle ......01 Ducks………………..07 Goat...........02 Turkey……….08 Sheep.........03 Rabbit……………09 Pigs......04 Kanga………………10 Poutry………..05 Simbilisi………….….11 Donkeys………06 Q uantity (Col.5) Kg…….1 Number.......2 Litre……..3 A portion/piece ..4 Appendix III 174 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 APPENIDX III c: Village Listing Forms CONFIDENTIAL ACLF 1 Page Number………….. out of……………… Sub-village /ward leader listing from Comments (3) (5) (1) (2) (4) District _____________________Code Village ________________________ Code Sub village leader Number Name of Ward village leader Number of Households Form Office Register After enumeration UNITED REPUBLIC OF TANZANIA Agriculture Sample Census 2007/08 Region ______________________Code Ward _______________________Code Appendix III 175 _______________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 ACLF 2 Page Number………….. out of……………… Household listing from-for listing hh heads and agriculture activities Region Code District Code Name of sub village leader Ward Code Name of sub village___________________________________________ Village Code (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (2) Total Bulls Cows Calves Sheep Pigs Kuku/Bata/ Rabbit UNITED REPUBLIC OF TANZANIA Agriculture Sample Census 2007/08 Household number Household head name Number of If the Respondent Qualifies X Farmer Serial Number Fields a Cattle Goats CONFIDENTIAL Appendix III 176 ______________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census - 2007/08 ACLF 3 Region Code ward : code Namba Sawia District village code Hatua Code (1) (5) (6) (7) (8) (9) (10) (11) Poutry (2) (3) (4) Cattle Goat Sheep Pigs UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2007/08 Household listing for 15 selected farmers S/N Sub-village leader Number Name of sub-village leader Name of selected head of household Name of a Househol d Head Number of Field CONFIDENTIAL | false |
# Extracted Content 1 TAARIFA KUHUSU UTEKELEZAJI WA MRADI WA UWEKEZAJI KATIKA SEKTA YA KILIMO WILAYANI (DASIP) WARSHA YA MAPITIO YA KUBORESHA UTEKELEZAJI WA MIPANGO YA MAENDELEO YA KILIMO YA WILAYA (DADPs) Charles R. Tulahi Mratibu wa Mradi DASIP MWANZA, 05 – 06 SEPTEMBA 2008 2 MADHUMUNI YA MRADI MADHUMUNI YA MADHUMUNI YA MRADI MRADI Kuongeza Kuongeza tija tija na na pato pato la la mkulima mkulima na na mfugaji mfugaji 3 NAFASI YA MRADI NAFASI YA MRADI NAFASI YA MRADI DASIP DASIP ni ni sehemu sehemu ya ya utekelezaji utekelezaji wa wa Programu Programu ya ya Maendeleo Maendeleo ya ya Sekta Sekta ya ya Kilimo (ASDP) Kilimo (ASDP) Katika Katika ngazi ngazi ya ya Wilaya Wilaya DASIP DASIP ni ni sehemu sehemu ya ya DADPs DADPs Katika Katika ngazi ngazi ya ya Kijiji Kijiji DASIP DASIP ni ni sehemu sehemu ya ya VADPs VADPs 4 ENEO LA MRADI • Kigoma: Kasulu, Kibondo and Kigoma (V); • Kagera: Ngara, Karagwe, Muleba, Chato, Biharamulo, Missenyi na Bukoba (V ); • Mara: Bunda, Serengeti, Rorya, Tarime, na Musoma (V ); • Shinyanga: Bariadi, Bukombe, Kahama, Kishapu, Maswa, Meatu na Shinyanga (V); • Mwanza: Geita, Kwimba, Magu, Misungwi, Sengerema na Ukerewe. 5 DADP DASIP ASDP Basket Fund + GBS Vyanzo Vya Halmashauri Vyanzo Vingine Nje ya Halmashauri 6 VADP DADP Vyanzo vya Kijiji Vyanzo Vingine 7 SEHEMU KUU ZA MRADI 1. Kujenga uwezo wa wakulima 2. Kujenga uwezo wa Kuandaa mipango ya Kilimo ya Wilaya na Vijiji na Uwekezaji 3. Kuimarisha huduma za fedha na Masoko 4. Kuratibu Mradi (PCU) 8 TAARIFA YA UTEKELEZAJI WA MRADI 1. Kujenga uwezo wa Wakulima Lengo: • Kuunda vikundi vya wakulima 10,000 (Vikundi zaidi ya 12 kila kijiji cha DASIP) • Kila Kikundi cha watu 25 (50% wanawake) kuanzisha mradi mdogo baada ya kufuzu mafunzo ya Shamba Darasa • Wakulima watakao fuzu kuhamishia mbinu walizojifunza kwenye mashamba yao 9 Kazi zilizofanyika (i) Kujenga uwezo wa Wataalam • Wataalam 56 wa wilaya na 685 katika ngazi za Kata na Kijiji wamepata mafunzo ya kuunda vikundi na kutoa mafunzo kwa kutumia mbinu ya Shamba Darasa • Wataalam 50 ngazi ya wilaya (DTCs) wamepatiwa pikipiki na vitendea kazi vingine 10 (ii) Kujenga Uwezo wa Wakulima • Vikundi 1,484 vimepatiwa mafunzo kwa kutumia mbinu ya Shamba Darasa • Vikundi 1,450 Vimefuzu na kupelekewa fedha kwa ajili ya kuanzisha miradi midogo 11 TATIZO ¾Wakulima hawajawezeshwa kiasi cha kutosha kuelewa uwezo wao na kuutumia/ wamejengewa mazingira ya utegemezi uliojengwa na baadhi ta asasi 12 Changamoto • Kuunda na kufundisha Vikundi angalau 6 katika kila kijiji kwa mwaka kuanzia 2008/09 • Kuhamisha ujuzi kutoka Shamba Darasa kwenda kwenye mashamba ya wakulima 13 • Kuwezesha vikundi vilivyoundwa kuwa endelevu na kupanua shughuli zao • Kuandaa Mashamba Darasa Kwa Utaratibu utakaowezesha Kuzalisha mazao yenye ubora na kiasi kinachokidhi mahitaji ya soko 14 • Kuweka mpango utakaowezesha wakulima kuzalisha mazao kwa kiasi cha kuwaondolea umaskini (Mbinu Bora + Eneo kwa kila mtu kwenye familia)- Economic Unit of Production • Kuwezesha wakulima kutambua fursa na uwezo wao na kuutumia 15 2. Kujenga uwezo wa Kuandaa mipango na Uwekezaji LENGO – Kujenga uwezo wa vijiji 780 wa kuandaa VADPs nzuri – Kujenga uwezo wa Wilaya 28 wa Kuandaa DADPs – Kuwezesha vijiji 780 kutekeleza miradi ya Jamii – kila kijiji mradi wa thamani ya sh. Milioni 35 au zaidi (kila kijiji kimetengewa sh. Milioni 28 za DASIP na kinatakiwa kuchangia sh. Milioni 7.0) 16 • Kuwezesha Wilaya kutekeleza Miradi ya Kati : Km 20 za barabara + miradi ya umwagiliaji (Sh. Milioni 11 kwa kilometa moja na sh. Milioni 225 kwa miradi ya Umwagiliaji kwa Wilaya) • Kupanua Matumizi ya Teknolojia za kilimo (Shilingi milioni 5 na michango ya jamii sh. Milioni 5 au zaidi 17 Kazi zilizofanyika • Timu 28 za wawezeshaji za Wilaya (DFT) zimepatiwa mafunzo ya kuandaa VADPs na DADPs • Timu 497 za wawezeshaji za Kata (WFT) zimepata mafunzo ya kuandaa VADPs • DADPs 56 zimeandaliwa 18 • VADPs 780 zimeandaliwa • Pikipiki 50 zimenunuliwa na kupelekwa Kwenye halmashauri • Compyuta na Phocopiers zimepelekwa kwenye Halmashauri 25 NB:Halmashauri mpya za Rorya, Missenyi na Chato zipo katika hatua za awali za ununuzi wa pikipiki, compyuta, photocopiers na vifaa vingine 19 2. Miradi ya jamii • Miradi 100 ya “Quick Win” imetekelezwa. 61 tayari imekamilika • Miradi 516 tayari imepelekewa fedha, (bilioni 5.478) na ipo katika hatua mbalimbali za utekelezaji 20 Utekelezaji wa Miradi YA JAMII ‘Quick Win’ Projects 2006/2007 Mwanza Shinyanga Kagera Mara Kigoma Jumla % ya Jumla Malambo 4 0 1 1 1 7 11 Vibanio vya Ng’ombe 0 0 6 0 0 6 10 Majosho 6 5 5 7 4 27 44 Mashine ya Kukuoboa Kahawa (Robusta) 0 0 1 0 0 1 2 Machinjio 0 0 2 1 0 3 5 Masoko 1 1 0 0 1 4 7 Barabara za Vijijini 0 0 1 0 1 2 3 Umwagiliaji 2 4 0 2 0 7 11 Mashine ya Kukuoboa Kahawa (Arabica) 0 0 0 1 0 1 2 Maghala 1 1 0 0 0 2 3 Visima Vifupi 1 0 0 0 0 1 2 JUMLA 15 11 16 12 7 61 100 % ya Jumla Kimkoa 25 18 26 20 11 100 21 MIRADI YA JAMII YA MIRADI YA JAMII YA MWAKA 2007/08 MWAKA 2007/08 Gharama (Tsh. ‘000) Na. Mkoa Idadi ya Miradi Mchango wa Jamii Mchango wa Mradi Jumla 1 Mwanza 130 430,890 1,425,023 1,855,913 2 Shinyanga 150 490,186 1,825,900 2,316,086 3 Mara 121 308,154 916,206 1,334,360 4 Kagera 81 197,999 715,121 913,120 5 Kigoma 34 150,635 596,541 747,176 Jumla 516 1,577,864 5,478,791 7,056,655 22 MIRADI YA JAMII YA MWAKA 2008/09 Gharama (Tshs.'000) Na. Mkoa Idadi ya miradi Mchango wa Jamii Mchango wa Mradi Jumla 1 Kagera 149 695,495 2,879,655 3,575,150 2 Kigoma 26 201,131 845,305 1,046,436 3 Mara 138 573,846 2,085,309 2,659,155 4 Mwanza 124 596,583 2,818,531 3,415,114 5 Shinyanga 128 797,261 3,157,645 3,954,906 Jumla 565 2,864,316 11,786,445 14,650,761 23 Matatizo i. Kuchelewa kwa utekelezaji wa Miradi – Miradi mingi ya jamii haijakamilika au haijaanza kutekelezwa ii. Kupanda kwa gharama za kutekeleza miradi kutokana na kuchelewa kuanza utekelezaji, m.f. ununuzi wa baiskeli; iii. Kutozingatiwa kwa sheria na kanuni za ununuzi iv. Ushirikiano mdogo katika kuhudumia miradi ya kilimo kutoka Idara zingine za Halmashauri 24 V. Kutenganisha miradi ya DASIP na DADPs: Fedha za Basket Fund kutogharamia shughuli ambazo DASIP ina ukomo; VI.Ubora hafifu wa baadhi ya miradi inayotekelezwa 25 Changamoto • Kuandaa VADPs na DADPs shirikishi na Jumuishi, • Kujenga miradi midogo ya jamii na ya kati na kuikamilisha Katika miaka miwili ijayo (Micro-projects and Medium scale projects); • Kuimarisha uwajibikaji na usimamizi wa miradi ya Jamii 26 • Kuwezesha jamii kuibua miradi inayotatua matatizo ya msingi ya wakulima na wafugaji; • Kuimarisha taratibu za ununuzi na fedha na kuhakikisha zinafuatwa 27 3. Kuimarisha huduma za Fedha na Masoko • Eneo hili lipo katika hatua za awali za utekelezaji. Wataalamu waelekezi wanatarajiwa kuanza kazi mwezi huu wa Septemba kwa ajili kufanya utafiti wa namna sahii na bora ya kutoa huduma hizo 28 Changamoto 1. Kuimarisha na kuboresha huduma za fedha kwa kiwango kitakachowawezesha wakulima kuzitumia na kunufaika nazo; 2. Kujenga mifumo ya masoko itakayowawezesha wakulima na wafugaji kushiriki na kunufaika na mfumo wa soko huru. 29 Uratibu wa Miradi • Kitengo cha Kuratibu Miradi (PCU) kimekuwa kikiratibu na kufuatilia utekelezaji wa Mradi. Kazi ambazo zimefanyika : • Kutuma fedha kwenye Halmashauri husika na kufuatilia matumizi yake, • Kutoa miongozo ya utekelezaji wa Mradi, matumizi ya fedha na ununuzi wa bidhaa na huduma, 30 • Kufuatilia utekelezaji wa Mradi, • Kuandaa mafunzo na mikutano mabalimbali, • Kutoa ushauri kuhusu ununuzi, matumizi ya fedha na utekelezaji wa miradi, 31 MAFANIKIO 1. Wataalam katika ngazi mablimbali wamepata mafunzo na wanajua majukumu wanayopaswa kufanya 2. Wakulima wameanza kujua Mradi na kudai fedha na huduma wanazopaswa kuzipata; 3. Miradi iliyotekelezwa vizuri imepunguza matatizo yaliyokuwa yanaikabili jamii; m.f, majosho, mashine za kuongeza thamani ya mazao, maghala, magulio, malambo n.k . 32 4. Wakulima na wafugaji wamepata utaalam kupitia Mashamba Darasa. 6. Kuna Wilaya ambazo viongozi wa wilaya wameonyesha kushiriki kikamilifu katika kusimamia na kufuatilia shughuli za Mradi. 33 MWELEKEO 1. Kuongeza kasi ya kutekeleza miradi ya Kati na ya Jamii (mediaum scale Projects + Micro-projects) 2. Kuunda vikundi vya wakulima (PFGs) na kufikia vikundi angalau 12 kila kijiji katika miaka miwili ijayo. 3. Kuboresha uandaaji na usimamizi wa DADPs 4. Kuimarisha mfumo wa usimamizi, ufuatiliaji na tathmini. 34 5. Kuimarisha huduma za Fedha na Masoko – Mchakato wa kuanza kutekeleza eneo hili upo katika hatua za awali. Utekelezaji utazishirikisha Wilaya zote za DASIP. 35 MWISHO | false |
# Extracted Content http://www.fao.org/mafap Monitoring African Food and Agricultural Policies Building a Sustainable System for Monitoring Food and Agricultural Policies in Africa 1 As FAO sets new priorities and promotes new models for its policy assistance work, MAFAP’s experience and achievements will help us build sustainable policy monitoring systems at country, regional and global levels. - Jomo Sundaram, Assistant Director General, FAO MAFAP is one of the most important programs monitoring agriculture policy in Africa today. By comprehensively tracking various aspects of the policy process – from expenditures to development outcomes – it informs agriculture policy in a unique way. - Prabhu Pingali, Deputy Director of the Agriculture Development Division, Bill and Melinda Gates Foundation MAFAP is expected to become an element of the CAADP monitoring and evaluation framework. - Martin Bwalya, Head of the NEPAD Comprehensive Africa Agriculture Development Programme (CAADP) The WAEMU commission considers MAFAP to be an essential part of its efforts to monitor and evaluate food and agriculture policies in the African Union. Indeed, MAFAP’s tools and methodology, and the institutional framework it promotes, allow us to better understand and compare member states’ policies. We especially appreciate the project’s results in Burkina Faso and Mali, and strongly urge FAO to support MAFAP and expand it to all countries in West Africa. - Soumana Diallo, Permanent Secretary of the CRMV, Rural Development Department, West African Economic and Monetary Union (WAEMU) “ ” ” “ ” “ ” “ MAFAP IN A NUTSHELL Monitoring African Food and Agricultural Policies (MAFAP) FAO is working with national partners to set up a sustainable system for monitoring the impact of food and agricultural policies for the first time in Africa. Through MAFAP, FAO has developed common indicators for monitoring key commodities and public expenditure in agriculture. This helps policy makers and donors understand if policies are having a positive impact and compare results across countries and over time. The challenge After several decades of declining investment in agriculture and the recent crisis caused by high food prices, policymakers and investors are paying renewed attention to agriculture and food security. Interest is strong in developing countries, especially in Africa, where production has not kept pace with the rapidly growing demand for agricultural products. Although decision makers recognize that appropriate policies and adequate public spending are critical for closing this gap, evidence to support decision making is often limited in Africa. MAFAP’s contribution Building a unique system for monitoring national food and agriculture policies MAFAP produces a common set of indicators that can be used to measure the impact of policies on different commodities, countries and over time. Meeting the needs of policy makers and donors who seek solid evidence about the impact of policies Using comparable quantitative indicators makes it easier to understand the impact of policies. Focusing on country ownership to make it sustainable MAFAP is unique in its focus on country ownership and partnerships to establish a sustainable policy monitoring system. It collaborates closely with national institutions to develop capacity and make policy monitoring an integral part of their regular work. Assessing the impact of national policies and how they compare with similar policies in other countries Having common quantitative indicators increases transparency and makes it possible to compare policies across countries. Having objective results empowers people affected by policies, and farmers in particular, in their interaction with governments and donors. Strengthening ongoing policy processes and initiatives MAFAP builds on existing efforts at the regional level such as the Comprehensive Africa Agriculture Development Programme (CAADP). For example, it provides feedback on how well countries are fulfilling their “CAADP compacts” and if they are meeting CAADP targets for public expenditure in agriculture. This information feeds into policy dialogue at the regional level. MAFAP is supported by the Bill and Melinda Gates Foundation and USAID. How MAFAP information is used The system provides regularly updated analyses to African governments seeking to : • improve policy frameworks for producers and consumers; • prioritize investments to increase agricultural production and improve farmers’ incomes and food security; • better target the share of the national budget devoted to agriculture and rural development; and • more effectively allocate the agricultural budget’s resources. Development partners can use this information to: • improve policy advice; and • identify investment opportunities that will have a positive impact on agricultural sector performance. Where we work MAFAP partner countries are Burkina Faso, Ethiopia, Ghana, Kenya, Malawi, Mali, Mozambique, Nigeria, Tanzania and Uganda. Mozambique: Farm workers carrying harvested maize back to the village for processing. In-depth commodity reports for maize are available for all MAFAP countries. 2 3 MEASURING POLICY IMPACT Measuring how much of the national budget is spent on agriculture and how it is composed MAFAP measures how much governments spend to support agriculture. This helps countries keep track of progress towards meeting the Maputo declaration objective of investing ten percent of the national budget on agriculture. MAFAP also provides a detailed analysis of how much is spent on agricultural research, infrastructure, subsidies and other components of the agricultural budget. Based on this information, and on policy impact analysis, policy makers will have a better understanding of where additional investment can generate the biggest impact. Figure 1. Composition of public expenditure for food and agriculture in Tanzania by type of support (2006 - 2011) From 2006 to 2011, the Government of Tanzania invested more in rural development than in specific support to producers and traders. Indeed, spending on infrastructure in rural areas (roads, education, energy and health) was high. Combined spending on research, training and extension was greater than spending on input subsidies and other forms of direct support to producers. Support for rural development declined sharply between 2009 and 2011. Direct support to producers and traders Indirect support to producers and traders Support to rural development Figure 2. Price of rice in Mali at the farm level (2005 - 2010) From 2005 to 2011, and especially after the 2007-2008 price spikes, government policies kept prices received by farmers lower than what they could have been. This can be explained by the government’s focus on consumer-oriented policies such as removing import taxes, subsidizing prices and setting price ceilings. Other constraints included producers’ poor access to markets. Despite an increase in input subsidies for rice from 2008 onwards, MAFAP results suggest that the impact of these subsidies have been outweighed by other policies that favor consumers. Potential price with improved access to markets Potential price with improved domestic policies Actual farm gate price 0 200 400 600 800 1000 1200 2005 2006 2007 2008 2009 2010 In USD/ton Measuring the impact of policies on prices Previous studies on the impact of agricultural policies in Africa were carried out on a one-off basis. Recognizing the need for a more sustainable approach, MAFAP works with national institutions to make measuring and monitoring policy performance part of their regular work. In particular, MAFAP measures how different policies and markets affect the prices farmers receive for their products and the prices consumers pay. It compares these prices with what they would be if current policies or constraints in access to markets did not exist. When there are big differences between incentives for farmers and consumers, MAFAP examines the causes of the disparity. Based on a solid understanding of how prices are affected, MAFAP can help policymakers explore options for enhancing incentives aimed at supporting farmers, while keeping prices affordable for consumers. The challenge Every country has policies which directly or indirectly affect agricultural development. The way these policies interact can support or hinder agricultural growth. However, until MAFAP was implemented, policy impact was not measured in a systematic way in most developing countries. Furthermore, different indicators were used. This made it difficult to compare results for diverse commodities, countries and time periods. ASSESSING POLICY COHERENCE The challenge Agricultural development does not happen in a vacuum, but is affected by the overall policy environment. Even well designed policies may fail to work as expected if other policies contradict them. Furthermore, inadequate funding, weak infrastructure, lack of access to markets, and even corruption may reduce their effectiveness. What MAFAP is doing Through MAFAP, FAO tracks public expenditure related to agriculture and measures the impact of policies on the prices of key agricultural commodities. MAFAP country reports provide policy makers with detailed assessments of: • the impact of food and agricultural policies on producers; • public expenditure to support food and agriculture; and • whether these are consistent with other government policies and objectives. Indeed, systematically comparing policy objectives, public expenditure and policy impact helps identify: • opportunities for making policies more coherent; and • priorities for investment. Analyzing Policy Coherence in Tanzania In Tanzania, many farmers have difficulty accessing markets because of a lack of rural roads and storage facilities. MAFAP price analysis shows that: • difficulty in accessing markets and a lack of infrastructure are the main reasons farmers do not produce more; and • if these constraints were adequately addressed, farmers would be able to obtain higher prices for their products. However, MAFAP’s analysis of public expenditure in the agricultural sector shows that only one percent of the agriculture budget is spent on non-farm agricultural infrastructure and two percent on storage. Furthermore, the biggest share of direct support to producers goes to input subsidies. These inconsistencies draw attention to key investment opportunities, and provide an important input into the dialogue between donors and the government. Figure 3. Policy support to rice producers in Mali through price incentives ( 2005 - 2010) Nominal Rate of Protection In Mali, MAFAP analysis reveals that current policies and public expenditure to support rice producers contradict each other. On one hand, the government and donors have allocated a large share of the agricultural development budget to support the production and marketing of rice (24 percent) and grains in general (12 percent). On the other hand, government policies reduced price incentives for rice producers between 2005 and 2010. Producers did not benefit from the international price surges of 2007 and 2008, mainly because the government eliminated import taxes and supported policies which kept rice prices low for rice consumers. Figure 4. Share of agriculture specific public expenditure for rice, grains and other products in Mali (2005 - 2010) Other 64% Rice 24% Grains 12% Affordable food for consumers versus a fair income for producers: a policy maker’s dilemma. 5 4 Developing a system for monitoring food and agricultural policies in Africa The challenge: building a sustainable system In Africa, there is limited systematically produced information to help governments understand the impact of policies and public spending. MAFAP bridges this information gap by working closely with national partners to set up a sustainable system for monitoring the impact of food and agricultural policies. How? MAFAP also develops the capacity of national partners in policy monitoring and publishes in-depth country and commodity reports (see table below). MAFAP Country and Commodity Reports Burkina Faso Ethiopia Ghana Kenya Mali Malawi Mozam- bique Nigeria Tanzania Uganda Country Report x x x x x x x x x x Public Expenditure Analysis x x x x x x Cassava x x x x x Cocoa x x Coffee x x x x Cotton x x x x x x x Cotton oil x Fish x Groundnuts x x x x x x Gum Arabic x Livestock x x x x x Maize x x x x x x x x x x Milk x x x x x Onion x Palm oil x x Pulses Rice x x x x x x x x Sesame x x Sorghum/Millet x x x x x x Sugar x x x x x Tea x x x Teff x Tobacco x x Wheat x x x x Yam x Ghana The Ministry of Food and Agriculture’s Policy Planning, Monitoring and Evaluation Directorate (PPMED) has strengthened its policy monitoring capacity. PPMED is also applying the MAFAP framework for better agricultural policies in Ghana. The Science and Technology Policy Research Institute (STEPRI-CSIR) provides additional support by conducting a MAFAP public expenditure analysis. Highlight: MAFAP in Burkina Faso Uganda The MAFAP monitoring and analysis system is well integrated into the Ministry of Agriculture, Animal Industry and Fisheries (MAAIF). Two other partners - the Economic Policy Research Centre (EPRC) and the National Agricultural Research Organization (NARO) - also strongly contribute to the analysis. Ethiopia Preliminary results for grains such as teff, wheat and maize, have captured policy makers’ attention and contributed to the debate on export bans and other policy measures. The MAFAP Secretariat is working to develop stronger partnerships with national research institutes such as the Ethiopian Development Research Institute (EDRI). Kenya MAFAP’s partners, the Kenya Agricultural Research Institute (KARI) and Kenya Institute for Public Policy Research and Analysis (KIPPRA), are actively engaged in policy related capacity building and analysis. KARI is setting up a new policy unit to perform MAFAP related work. Closer links have been forged with the Ministry of Agriculture’s policy division which will play an important role in disseminating MAFAP results. United Republic of Tanzania (URT) The local MAFAP team is composed of staff from the Ministry of Agriculture, Food Security and Cooperatives and the Economic and Social Research Foundation. MAFAP preliminary results were presented to the Agricultural Sector Working Group. MAFAP indicators are being considered for inclusion in the regular Agricultural Sector Monitoring and Evaluation Framework and the Performance Assessment Framework for the Basket Fund. Mali The Institut d’Economie Rurale (IER) plans to use MAFAP as a key component of its Policy Analysis Task Force. The IER is Mali’s main agricultural research institute and is directly linked to the Ministry of Agriculture’s planning unit. Malawi In the last few years, Malawi has implemented important economic and agricultural policy changes. MAFAP collaborates with the Ministry of Agriculture and Food Security and a team of local experts to strengthen the country’s capacity for monitoring and analyzing the impact of those reforms. Nigeria Nigeria is implementing a new Agricultural Transformation Agenda (2011-2015) to significantly boost its agricultural sector’s growth. To support this initiative, the MAFAP team collaborates with the Federal Ministry of Agriculture and other partners to identify policy and investments gaps in key commodity chains. Mozambique MAFAP works with the Ministry of Agriculture and Ministry of Planning and Development. Preliminary results for maize, cassava and cotton were presented at a workshop and drew attention at the national level. MAFAP also works with the Ministry of Commerce and the Cotton Institute. a practical methodology and common indicators, adapted to the African context, for measuring the impact of policies on agriculture; in-depth analyses of the impact of policies on the prices of key commodities and on farmers, traders, consumers and other people involved in value chains; and detailed analyses of public expenditure in agriculture. In Burkina Faso, MAFAP works with the Rural Economics Division (DGPER) of the Ministry of Agriculture. DGPER, which is the division responsible for policy analysis, has been actively disseminating and raising awareness about MAFAP findings. Thanks to this, MAFAP results were presented by the Ministry of Agriculture at an international conference on agriculture, livestock and water. MAFAP results will provide key evidence to the discussion among policy makers from Burkina Faso and the region on: • national, regional and international market access; • agricultural value chain organization; • policy coherence in Burkina Faso; and • regional integration. 6 7 COMPARING POLICY PERFORMANCE “Only by having a common set of indicators, can we compare agricultural policies in different African countries.” MAFAP’s unique database makes it possible to compare the effects of agricultural policies in ten African countries over time and for more than twenty commodities. • A consistent set of indicators makes it easier to understand how different policies work in various contexts. Policy makers from different countries will thus be able to learn from one another. In particular, MAFAP indicators make it possible to compare: • • the effects of incentives and disincentives for a specific commodity over time and in different countries; • how incentives affect different commodities in the same country; and • public spending in the agricultural sector, and how it is broken down into various components such as agricultural research, subsidies, infrastructure, etc. Comparing agricultural policies in Mali and Burkina Faso In November 2012, researchers from Mali and Burkina Faso met with a team from FAO and a representative from the West African Economic and Monetary Union (WAEMU) to compare results from MAFAP analyses of commodities such as rice, cotton and sorghum. This led to a deeper understanding of the effects of agricultural policies within each country and in the region. Papers comparing indicators for maize, rice and cotton in MAFAP countries have been prepared and will be available on the MAFAP website: www.fao.org/mafap. Figure 6. Share of food and agriculture budget expenditure on input subsidies (2006/07, 2008/10) Figure 7. Policy support to maize producers through price incentives (2005/07, 2008/10) 2008 - 2010 2006 - 2007 While farmers in Kenya and Burkina Faso have seen their prices move towards those that would prevail in the absence of price distorting policies and with well-functioning markets, discrepancies have increased in Tanzania, Mali and Uganda. In most countries, the policy environment and market structure have led to lower prices for producers. This is especially true where policies aim at lowering prices for consumers. However, some governments have tried to encourage maize producers by providing input subsidies. With the exception of ad-hoc export bans, which lower prices that farmers receive, markets for specific commodities appear to function better in countries that are net exporters of those commodities. In some cases, excessive domestic transport costs and lack of storage facilities have led to domestic prices which are higher than export prices. 2008 - 2010 2005- 2007 Figure 5. Share of government public expenditure going to the agricultural sector, actual spending (2005-2010) Between 2005 and 2010, four of the five countries analyzed reached the Maputo target. Indeed, the share of government public expenditure going to the agricultural sector in terms of actual spending substantially exceeded the ten percent target in Burkina Faso and Uganda. *Data on actual spending in Kenya are not yet available and the figure is based on the allocated budget. Nominal Rate of Protection The Institut d’Économie Rurale (IER), Ministry of Agriculture, Mali The IER is the main agricultural research institute in Mali. Prior to MAFAP, the IER ‘s socioeconomic research focused mainly on value chain analysis and limited research on the impact of policies on agriculture existed. To fill this gap, MAFAP helped IER develop its policy analysis and monitoring capacities and set up a policy analysis unit. This unit aims at providing research that will help policy makers understand the impact of their policy choices. It thereby links research and policy making by providing solid analysis. FAO’s global partners involved in MAFAP include donors, international agencies and research institutes such as: • The Bill and Melinda Gates Foundation • The United States Agency for International Development (USAID) • The Organisation for Economic Co-operation and Development (OECD) • The World Bank • The International Food Policy Research Institute (IFPRI) MAFAP helps partners keep track of whether national governments are: • achieving their objectives for public expenditure; and • implementing policies that are congruent with national policy objectives and strategies such as the CAADP compacts. Regional partners include: • The Planning and Coordinating Agency of the New Partnership for Africa’s Development (NEPAD/NPCA) • The West African Economic and Monetary Union (WAEMU) • The Economic Community of West African States (ECOWAS) • The East African Community (ECA) R E G I O N A L P A R T N E R S MAFAP enables national partners to set up and manage their own processes for monitoring food and agricultural policies. It works closely with stakeholders involved in the policy process from: • national governments • research and policy institutes • statistics offices and CountrySTAT teams in MAFAP countries N A T I O N A L P A R T N E R S MAFAP G L O B A L P A R T N E R S The Comprehensive Africa Agriculture Development Programme (CAADP) MAFAP analyzes how participating countries are implementing specific elements of their CAADP compact. The CAADP compact is a contract between donors, national governments and CAADP/NEPAD which identifies strategic opportunities for agricultural investment. In particular, MAFAP looks at the impact of current policies and if they are coherent with the compact’s objectives. By keeping track of public expenditure on agriculture, MAFAP helps national governments understand if they are making progress in reaching the CAADP target of allocating ten percent of the national budget for agricultural development. The Organisation for Economic Co-operation and Development (OECD) The OECD is a leader in the policy monitoring field for developed countries. MAFAP has worked with the OECD to adapt its policy monitoring methodology for use in developing countries. In particular, MAFAP uses an indicator called the Nominal Rate of Assistance (NRA) which tracks the amount and type of support African governments give to agriculture. The NRA is similar to OECD’s Producer Support Estimate (PSE). Both indicators can be used to monitor levels of government support to agriculture and how it is composed. The NRA, as calculated by MAFAP, makes it possible to estimate disincentives due to excessive costs or margins, bribes or rents. Furthermore, all technical documents produced by MAFAP are reviewed by OECD’s PSE advisory group. WORKING WITH PARTNERS 9 8 ENHANCING POLICY DIALOGUE MAFAP provides decision makers with the evidence they need to implement more effective policies. In several countries, MAFAP has helped set up policy analysis units in the Ministry of Agriculture or related ministries. These units help facilitate a more direct dialogue between researchers, policy makers, farmer organizations, development partners and the private sector. OUR VISION FOR THE FUTURE Expand MAFAP beyond Africa Expanding MAFAP beyond Africa will create oppor- tunities for sharing and comparing policy experienc- es from different regions. This will make it possible to learn about effective solutions to similar problems. It will be easier to foresee, based on experiences in other countries, the likely impact of food and agri- culture policies. Increase the number of MAFAP countries in Africa FAO seeks to increase the number of African coun- tries covered by MAFAP from 10 to 23. It seeks to progressively include all countries belonging to three regional economic organizations (ECOWAS, EAC and SADC). This will further support regional policy dialogue. Deepen analysis and include additional topics Since co-existing policies directly affect each other, FAO will release additional MA- FAP indicators which show the combined effects of policies on key inputs and agri- cultural products. MAFAP will also look at how incentives affect producers and con- sumers to make sure food security is not compromised. Moreover, going beyond price analysis, MAFAP will look at how in- centives affect farmers’ decisions about what to produce. Develop the skills of national professionals in partnership with universities FAO will work with partner uni- versities to develop curricula that build policy analysis and mon- itoring skills and increase the number of qualified graduates able to apply the MAFAP meth- odology. Invest in making MAFAP part of the global policy dialogue MAFAP’s methodology and com- mon indicators make it possible to compare policy impact across countries. In the future, FAO will seek opportunities for incorpo- rating MAFAP findings into glob- al fora in a systematic way. “MAFAP provides valuable information on the impact of our agricultural policies and the effectiveness of our agricultural development strategy. MAFAP’s informa- tion will certainly strength- en our ongoing policy di- alogue with farmers and other stakeholders” - Dr. Emmanuel M. Achayo, Director of Policy and Planning, Ministry of Agriculture, Food Security and Cooperatives, United Republic of Tanzania Contributing to high level policy dialogue in Burkina Faso MAFAP has established a partnership with the Rural Economics Division of Burkina Faso’s Ministry of Agriculture (DGPER). By August 2012, initial results on the impact of policies for nine commodities were available. These caught the attention of decision makers, including the Minister of Agriculture. They expressed great interest in using MAFAP recommendations for policy making - especially for the rice sector. The results will be presented to other ministers and the parliament. MAFAP and its partners supply vital evidence to regional and national policy dialogue by regularly publishing: • commodity reports for key agricultural products; • in-depth country reports which analyze prices, public expenditure and policy coherence; and • policy briefs. African farmer networks use MAFAP results to advocate for food security and sustainable food systems Farmers are directly affected by food and agricultural policies. Therefore, their input is essential in making sure policies enhance agriculture production and farm incomes. One way in which farmers are using MAFAP analysis is to advocate for more effective policies. For instance, the Pan African Farmers Organization has used MAFAP results to build the case for more sustainable food systems. Examples of actions called for include: • enabling small scale family farmers to seize opportunities arising from better connections to booming cities; and • developing a market information system geared to rural producers’ needs. A report was presented to the African Union and CAADP, and is expected to have an impact on policies regarding sustainable food systems. We envision a self-sustaining policy monitoring system based on: Country Ownership Highly Skilled National Professionals Targeted Partnerships Systematic and Comparable Monitoring International Peer Reviews of Technical Work 10 CONTACTS Website: www.fao.org/mafap Email: [email protected] Mailing Address: FAO Headquarters Viale delle Terme di Caracalla 00153 Rome, Italy supported by the Bill and Melinda Gates Foundation Photos: ©FAO/Giulio Napolitano ; ©FAO/Si- mon Maina ; ©FAO/Roberto Faidutti, ©FAO/ Paballo Thekiso, ©FAO/ Alessandra Benedet- ti, ©FAO/Walter Astrada | false |
# Extracted Content 1 Making the United Republic of Tanzania’s Coffee Sector More Competitive Main Findings and Recommendations Although coffee is the URT’s second most important agricultural export, coffee growers receive prices which are lower than those they could potentially obtain. Lower farmers’ prices mainly relate to a few companies’ dominance of the main auction market in Moshi. MAFAP analysis suggests that the following measures would improve prices received by farmers: SUMMARY MAFAP analysis shows that from 2005 to 2010, coffee farmers (Figure 1) and traders (Figure 2) in the URT received relatively lower prices than those they would have received without policy interventions and with better functioning value chains. Disincentives mostly occurred between the farm gate and the auction. These were related to buyers’ excessive market power at the auction and the high transport costs at the port of Dar es Salaam. INTRODUCTION Coffee is the second most important agricultural export commodity in the URT after tobacco. It accounted for 14 Monitoring African Food and Agricultural Policies TANZANIA MAFAP POLICY BRIEF #14 July 2013 The United Republic of ► ►strictly enforcing the one license system to prevent agents from acting both as buyers and sellers at the Moshi auction; ► ►revising the pricing system at the auction to allow farmers, traders and exporters to share risks when large differences between prices paid at the farm gate and prices obtained at the time of export occur; and ► ►reducing transport and processing costs from the farm gate to the point of export. percent of agricultural exports between 2004 and 2009. Over 90 percent of the coffee in the URT is produced by smallholder farmers. The coffee industry provides direct income to more than 400,000 households and livelihoods for more than 2.5 million Tanzanians. Coffee is grown in the northern, western and southern areas of the country and marketing is centralized via an auction in Moshi. As part of the country’s Agricultural Sector Development Programme (ASDP), the government has launched the Coffee Industry Development Strategy 2011–2021. This strategy aims at increasing coffee production from 50,000 to 100,000 tonnes. and improving its quality by increasing the share of premium coffee production from 35 to 70 percent of total production by 2016. 500 0 1,000 1,500 2,000 2,500 3,000 3,500 2005 2006 2007 2008 2009 2010 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 2005 2006 2007 2008 2009 2010 Actual farm gate price Potential price without domestic policy distortions Potential price without domestic policy distortions and improved access costs Actual auction price Potential price without domestic policy distortions Potential price without domestic policy distortions and improved access costs Figure 1: Producers’ price of coffee in the United Republic of Tanzania (in 1000s of Tz Shillings/ tonne), 2005-2010 Figure 2: Auction price of coffee in the United Republic of Tanzania (in 1000s of Tz Shillings/tonne), 2005-2010 Thousands of Tz Shillings / tonne of coffee Thousands of Tz Shillings / tonne of coffee 2 Further Reading MAFAP Technical Note on Incentives and Disincentives for Coffee in the United Republic of Tanzania (2013) By Baregu, S., Barreiro-Hurlé, J. and Maro, F Available at: http://www.fao.org/mafap CONTACTS Website: www.fao.org/mafap Email: [email protected] This note was prepared by FAO’s Monitoring African Food and Agricultural Policies (MAFAP) project, the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC). MAFAP is implemented by FAO with technical support from the OECD and funding from the Bill and Melinda Gates Foundation (BMGF) and USAID. MAFAP supports decision-makers at national, regional and pan-African levels by developing a systematic method for monitoring and analyzing food and agricultural policies in African countries. KEY ISSUES The one licence system needs to be more strongly enforced by the government MAFAP results show that, especially since 2008, disincentives in the value chain have increased for farmers while they have remained lower and more stable at the auction (Figure 3). The difference between the export price and the auction price is partly explained by fees paid to the Tanzania Coffee Research Insitute and the Tanzania Coffee Board. The remaining gap relates to the high cost of transporting coffee from producing areas to the port of Dar es Salaam. The difference between the domestic price and the potential price that would prevail without current policies and better functioning value chains was much higher at the farm gate than at the auction market (Figure 3). This would suggest that traders have more market power than farmers. MAFAP generally estimates normal profit margins at the auction to be around ten per cent of the farm gate price. The price difference indicates that profit margins were close to 25 per cent, although margins decreased when production in the URT was low (Figure 4). The URT introduced the one license system which requires each person to act either as a buyer or as a seller at the auction to improve competion among buyers. However, the system needs to be more strictly enforced to prevent companies from circumventing it. Farmers have not fully benefited from increasing coffee prices MAFAP analysis shows that, although export prices of coffee have been steadily increasing since 2005, farm gate prices have increased at a lower rate (Figure 5). This suggests that farmers have not fully benefited from increasing international coffee prices. Although the current system protects farmers when international prices are stable or decreasing (2008- 2009), it also limits their capacity to benefit from higher prices. To some extent, trade liberalization has helped improve the sector, but smallholder farmers could potentially receive even higher prices. Figure 3: Price gaps of coffee at the farm gate and at the auction (in 1000s of Tz Shillings/tonne), 2005-2010 -1,400 -1,200 -1,000 -800 -600 -400 -200 0 200 2005 2006 2007 2008 2009 2010 Thousands of Tz Shillings / tonne of coffee Price gap at the auction Price gap at the farm gate Figure 4: Implicit traders’ margins between the farm gate and the auction market ( %), 2005-2010 Figure 5: Share of farm gate to export (FOB) prices and changes in farm gate and export (FOB) prices (in 1000s of Tz Shillings/tonne), 2005-2010 Change in export (FOB) price Change in farm gate price Farm gate to export (FOB) price ratio -10% 0% 10% 20% 30% 40% 50% -400 -200 0 200 400 600 800 1,000 1,200 1,400 2005 2006 2007 2008 2009 2010 Thousands of Tz Shillings / tonne of coffee -40% -20% 0% 20% 40% 60% 80% 100% 2005 2006 2007 2008 2009 2010 Traders’ implicit margins at the auction MAFAP analysis also suggests that the pricing system at the main auction could be revised to allow farmers and exporters to share risks when large differences between auction and export prices occur. For example, in 2010 prices had increased by nearly 60 per cent by the end of the year. Thus, prices that farmers received were based on the lower quotations at the beginning of the year. These prices were far lower than what farmers could have potentially received if they had sold their coffee at the end of the year. However, traders who sold coffee later in the year, greatly benefited from higher prices. | false |
# Extracted Content 1 Improving ginning technologies and reviewing taxes to benefit cotton farmers in the United Republic of Tanzania Main Findings and Recommendations Although cotton is a major export crop in the URT, domestic cotton farmers received lower prices than what they could have potentially obtained between 2005 and 2010. Price disincentives were mainly due to taxes and levies applied to the cotton sector, and to inefficient ginneries. Farm input subsidies and additional support from the Tanzania Cotton Board (TCB) do not fully compensate for these disincentives. MAFAP analysis suggests that the following measures would increase prices for producers: SUMMARY MAFAP analysis shows that producers of raw cotton received prices that were lower than what they would have received without policy interventions and with better functioning value chains. These low prices were associated with taxes and levies in the cotton market. Moreover, cotton farmers would get better prices if the technical efficiency of ginners was improved. The reasons why only a very small percentage of cotton lint is spun domestically, and levels of additional processing remain persistently low, should be explored further. Monitoring African Food and Agricultural Policies TANZANIA MAFAP POLICY BRIEF #11 June 2013 The United Republic of ► ►reducing government levies and taxes on cotton producers; and ► ►facilitating investments in the cotton sector to modernize ginning technologies. Figure 1. Producer prices of cotton lint in the United Republic of Tanzania 2005 – 2010 (in Tz shillings/tonne), 2005-2010 INTRODUCTION Cotton is the URT’s largest export crop after coffee and accounts for 14 percent of its total agricultural exports. Forty percent of Tanzanian’s livelihoods are linked to the cotton sector, which also provides livelihoods for over 500,000 rural households. Despite policy makers‘ efforts to boost production and productivity, yields and the technical efficiency of ginneries remain low. Nonetheless, there is a huge potential for increasing production and exports – especially since the global demand for cotton has been steadily growing. 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 2005 2006 2007 2008 2009 2010 Thousands Tz Shillings / tonne Actual farm gate price of cotton lint Potential price without domestic policy distortions, more efficient import procedures and better functioning value chains KEY ISSUES High taxes and levies have increased price disincentives for farmers. The Tanzanian cotton market is subject to taxes and levies imposed at the district, regional and central government levels. Moreover, cooperative unions and societies are also taxed. This heavy taxation, which amounts to an average of 12 per cent of the farm gate price, penalizes farmers. It also has a big impact on farmers’ investment capacity. Reducing the current level of taxation, taking into account its impact on producers and ginners, would be beneficial for the entire cotton sector. In addition, the low efficiency of ginneries pushes farm prices downwards. The ginning sector’s low Ginning Out Turn (GOT) ratio (i.e. the quantity of lint produced by ginners per tonne of seed cotton) also creates price disincentives for farmers. If the investment environment for the cotton sector was improved, ginneries could be modernized to allow for a GOT ratio closer to world standards. This would increase the quantity of cotton lint produced per ton of raw cotton and subsequently improve 2 Further Reading MAFAP Technical Note on Incentives and Disincentives for Cotton in the United Republic of Tanzania (2012) by Mwinuka, L. and Maro, F. Available at: http://www.fao.org/mafap/urt CONTACTS Website: www.fao.org/mafap Email: [email protected] This note was prepared by FAO’s Monitoring African Food and Agricultural Policies (MAFAP) project, the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC) withwith technical support from the OECD and funding from the Bill and Melinda Gates Foundation (BMGF) and USAID. MAFAP supports decision- makers at national, regional and pan-African levels by developing a systematic method for monitoring and analyzing food and agricultural policies in African countries. the prices farmers receive for raw cotton. The investment environment could be improved by making the current Cotton Industry Implementation Plan focus more on the ginning industry, and not only on farmers and the textile industry. MAFAP’s analysis show that taxes account for approximately 20 per cent of total disincentives while the impact of inefficient ginning is at least three times as high (Figure 2). The remaining gap cannot be attributed to any specific causes. Government support for farm input subsidies did not fully compensate price disincentives for cotton farmers. Public expenditure to support the cotton sector steadily increased from 2007 to 2010 (Figure 3). Types of support include fertilizer and insecticide subsidies, as well as funding the Tanzanian Cotton Board and the Ukiliguru Cotton Research Centre. However, the level of public expenditure to support the cotton sector is low compared to the level of disincentives caused by high taxes and the inefficient ginning industry. Public spending on farm input subsidies should be complemented by policies aimed at strengthening the investment capacity of farmers and ginners. Moreover, it would probably be more efficient to reduce the tax burden on cotton producers and allow them to use the additional income they gain to purchase inputs. Figure 3. Price gaps due to taxation and inefficiencies versus public expenditure for the cotton sector (2005-2010) Public expenditure to support cotton producers Price gap Share of price gap compensated by public expenditure Note: Public expenditure to support the cotton sector includes both the expenditure directly allocated to the cotton sector and the proportional share of expenditure not allocated to any specific crop. -90% -70% -50% -30% -10% 10% 30% 50% 70% 90% -250 -200 -150 -100 -50 - 50 100 150 200 250 2007 2008 2009 2010 Thousands Tz Shillings / tonne of raw cotton Percent of price gap covered by public expenditure Competition among ginners (buyers) reduced the level of disincentives for farmers. The URT’s cotton sector is a good example of free market competition. When production was low, as it was in 2009, the competitive market environment allowed ginneries to bid up prices and reduced disincentives for farmers significantly (Figure 1). However, markets operated in a less competitive way when production was not a limiting factor. Indeed, in years when production was relatively high, there were more disincentives not readily explained by taxes or inefficiencies (purple bar in Figure 2). CONCLUSION Price disincentives for cotton farmers were mostly related to taxation and inefficient ginning technology. The Cotton Industry Implementation Plan and other policies should include objectives aimed at modernizing the ginning industry. A more efficient cotton sector would also increase the volume of cotton processed in the country. -250 -200 -150 -100 -50 - 50 100 150 200 250 -100% -80% -60% -40% -20% 0% 20% 40% 60% 80% 100% 2005 2006 2007 2008 2009 2010 Figure 2. Causes of price disincentives for producers of cotton in the United Republic of Tanzania (2005-2010) Share of total disincentives Thousands Tz Shillings / tonne Impact of taxes Impact of ginning inefficiency Residual Price gap at farm gate (right scale) | false |
# Extracted Content 1 Improving sugar cane processing in the United Republic of Tanzania to increase prices for farmers while lowering prices for consumers Main Findings and Recommendations eliminating the 100 percent import tariff or reducing ad-hoc import tariff waivers would allow imported sugar to reach domestic markets at lower prices; facilitating investments aimed at making sugar mills more efficient; fostering higher utilization rates of sugar mills; increasing investment in fertilizer production and irrigation; and implementing the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) approach to the sugar industry in the Kilombero region through improved partnerships and infrastructure. Consumers of sugar in the United Republic of Tanzania pay prices that are high when compared to the price of sugar in international markets. However, prices for sugar cane producers remain low due to inefficient sugar mills and high marketing costs. MAFAP analysis suggests that the following measures would improve prices for both producers and consumers: SUMMARY While the price consumers pay for sugar is higher than international market prices, this does not translate into higher prices for domestic sugar cane producers. Although farmers gain some benefit from tariffs on imported sugar, it is not enough to offset the impact of inefficient sugar mills and high marketing costs. Sugar cane farmers (figure 1) are receiving lower prices than they would get with improved policies and markets. Disincentives are mainly due to excessive processing costs. Figure 1. Producer price of sugar cane in the United Republic of Tanzania (in TZ shillings/ton), 2005-2010 Thousands Tz Shillings / ton of sugar cane On the other hand, sugar wholesale prices (figure 2) are higher than those that would exist without current policies and with better functioning import markets. High prices are mainly related to the East African Community’s common external tariff for sugar (100 percent ad valorem or USD 200/per ton, whichever is higher). Although sugar import tariffs have been partially suspended or reduced since 2008, this has had little impact on reducing the domestic price of sugar. Indeed, domestic prices have remained on average 32 percent higher than import prices. Figure 2. Wholesale price of sugar in the United Republic of Tanzania (in TZ shillings/ton), 2005-2010 10,000 20,000 30,000 40,000 50,000 60,000 70,000 2005 2006 2007 2008 2009 2010 Actual farm gate price of sugar cane Potential price without policy distortion and more efficient processing Potential price without policy distortion, more efficient processing and improved market access 0 200 400 600 800 1,000 1,200 2005 2006 2007 2008 2009 2010 Wholesale price of sugar Potential price without policy distortion and more efficient processing Potential price without policy distortion, more efficient processing and improved market access Monitoring African Food and Agricultural Policies TANZANIA MAFAP POLICY BRIEF #2 February 2013 The United Republic of 2 KEY ISSUES Excessive processing costs prevent farmers from benefiting from the protection offered by import tariffs MAFAP analysis shows that excessive processing costs are the main reason sugar cane producers do not receive better prices. Indeed, processing costs in the United Republic of Tanzania are twice as high as the average cost for Africa. Since access costs (which include processing, profit margins and transport) are higher than sugar producers’ gross profit margins, sugar factories cannot cover their overall costs in most years. Figure 3. Comparison of access costs for sugar cane in the United Republic of Tanzania, (2005-2010) 20 40 60 80 100 120 2005 2006 2007 2008 2009 2010 Thousands Tz Shillings / ton of sugar cane Access costs used in the analysis Gross margins between farm gate and wholesale prices Access costs using data from a sugar mill in the URT Figure 3 compares the estimated cost for processing a ton of sugar cane and selling it as sugar in the Dar es Salaam market. Gross profit margins are included. Figures are based on domestic market data and actual costs reported by the sugar mill. Import tariff waivers have had little impact on reducing the price consumers pay for sugar Since 2008, the United Republic of Tanzania has partially or totally suspended the 100 percent common tariff. Nonetheless, the difference between domestic prices and import prices increased. This suggests that waiving tariffs does not lead to lower sugar prices. Part of the problem may be a lack of coordination between the Tanzania Revenue Authority and the Ministry of Agriculture, Food Security and Cooperatives which has led to imported sugar being stranded at the border for long periods. Despite government incentives, sugar production is not increasing enough to meet domestic demand Domestic production appears to be stagnating. Although the production of both sugar cane and sugar more than doubled between 2000 and 2005, it remained constant between 2005 and 2010. Moreover, domestic production falls short of meeting domestic demand. Existing policies no longer appear to have an impact on increasing production. Public expenditure to support sugar and sugar cane processing is very limited. Less than 0.2 percent of agriculture specific budget is targeted exclusively to sugar. Only one percent of the budget goes towards the processing (of any commodity). The SAGCOT initiative’s new approach to agricultural investment may help increase sugar production and lead to higher prices for producers Sugar has been identified as one of the three key commodities for the initial phase of the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) which will be implemented in the Kilombero region. The initiative’s approach is based on clusters of commercial farms and agri-businesses in areas with high agricultural potential and access to backbone infrastructure. SAGCOT’s newer, more efficient processing facilities and stronger partnerships with smallholders may help overcome current price disincentives. CONCLUSION Currently sugar cane producers receive lower prices than they could, despite high domestic demand, due to elevated processing costs. The tariffs on imported sugar keeps prices high for consumers without boosting prices for farmers. A new policy approach based on liberalized trade and increased competitiveness of sugar processing could lead to higher prices for producers and lower prices for consumers. Further Reading MAFAP Technical Note on Incentives and Disincentives for Sugar in the United Republic of Tanzania (2012) by Nkonya, N. and Barreiro-Hurle, J. Available at: http://www.fao.org/mafap CONTACTS Website: www.fao.org/mafap Email: [email protected] This note was prepared by the Monitoring African Food and Agricultural Policies (MAFAP) team at FAO and at the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC) of the United Republic of Tanzania. MAFAP is implemented by FAO in collaboration with the OECD and the financial participation of the Bill and Melinda Gates Foundation (BMGF) and USAID. MAFAP supports decision-makers at national, regional and pan-African levels by systematically monitoring and analyzing food and agricultural policies in African countries. | false |
# Extracted Content 1 Improving wheat trade policy administration to benefit both consumers and producers in the United Republic of Tanzania Main Findings and Recommendations Import tariffs and costly import procedures help explain why consumers in the United Republic of Tanzania pay relatively high prices for wheat. Although wheat farmers benefit from higher prices, domestic production has not increased. MAFAP analysis suggests that: SUMMARY From 2005 to 2010, wheat farmers (Figure 1) and traders (Figure 2) in the URT received higher prices due to the effects of trade policies such as the East African Community Common External Tariff (35 per cent ad valorem) and expensive import procedures at the Dar es Salaam port. Although producers received significant incentives from tariffs and high import Monitoring African Food and Agricultural Policies TANZANIA MAFAP POLICY BRIEF #8 April 2013 The United Republic of ► ►facilitating procedures for importing wheat and reducing overall import costs would make wheat more affordable for consumers. Indeed, excessive import costs have had an impact similar to that of the tariff in raising domestic prices; ► ►monitoring re-exports of wheat flour to neighboring countries would help ensure that lower import tariffs for wheat actually lead to lower domestic prices; and ► ►more support for research and development, and extension services could help increase wheat production. - 50 100 150 200 250 300 350 400 450 500 550 600 650 700 2005 2006 2007 2008 2009 2010 costs, wheat production did not increase, and wheat imports still account for 30 per cent of the total food import bill. In 2007, the URT decreased the import tariff for wheat to ten per cent. Although this had an immediate impact in terms of reducing the gap between international and domestic prices, from 2008 onwards the gap started increasing again. Figure 1. Producer price of wheat in the United Republic of Tanzania (in Tz shillings/tonne), 2005-2010 Thousands Tz Shillings / tonne Actual farm gate price of wheat Potential price without policy distortion and more efficient import procedures Potential price without policy distortions, more efficient import procedures and better functioning value chains - 100 200 300 400 500 600 700 800 900 2005 2006 2007 2008 2009 2010 Figure 2. Wholesale price of wheat in the United Republic of Tanzania (in Tz shillings/tonne), 2005-2010 Thousands Tz Shillings / tonne Actual wholesale price of wheat Potential price without policy distortion and more efficient import procedures Potential price without policy distortions, more efficient import procedures and better functioning value chains 2 KEY ISSUES Expensive import procedures and the import tariff have raised domestic prices for wheat MAFAP analysis shows that the difference between domestic prices and those that would prevail in the absence of trade policies is significantly higher than the value of the import tariff (Figure 3). This means that traders and farmers receive higher prices partly due to expensive import procedures and importers’ margins which are well above ten per cent. However, it is not possible to identify the relative weight of each factor behind the price difference. Reducing red tape and promoting more competition in the wheat import market could help reduce the gap between domestic and international wheat prices. Reducing the import tariff has had little impact on wheat wholesale prices Except for the year in which it was implemented, reducing the tariff from 35 to 10 per cent did not have a significant impact on domestic prices. One reason for this was that the lower import tariff allowed domestic millers to benefit from lower wheat costs and increase wheat flour exports. Figure 3 shows the difference between the value of the tariff and the price gap between domestic prices and those that would prevail in absence of policies. This gap increased sharply after 2008. As the cost of import procedures did not change significantly from 2007 to 2008, this difference can be attributed to increased importers’ margins. Despite sustained incentives for producers, production and yields have not increased Although wheat producers receive relatively high price Difference between domestic wholesale prices and prices without policy distortions and more efficient import procedures Value of the tariff Difference between domestic farm gate prices and prices without policy distortions and more efficient import procedures Figure 3. The value of the import tariff compared to the the difference between domestic prices and those that would prevail in the absence of current policies and with more efficient import procedures (in Tz shillings/tonne), 2005-2010 (50) - 50 100 150 200 250 300 350 400 2005 2006 2007 2008 2009 2010 Thousands Tz Shillings / tonne incentives, they have not increased production in terms of volume or cultivated land. Since 2000, wheat production in the URT has not been able to cover more than 20 per cent of domestic consumption requirements (Figure 4). Moreover, yield levels have remained relatively flat at just under two tonnes per hectare. Although consumers pay wheat prices that are higher than international prices, this has not led to an increase in domestic production and wheat food import bills remain very high. If increasing domestic wheat production remains a policy objective in the URT, additional measures for developing wheat varieties adapted to the local agro-ecological and climatic conditions are needed. Furthermore, the decline in the share of public spending going to agricultural research and extension (as part of the overall budget to support agriculture) from 2005 to 2010 should be reversed. Further Reading MAFAP Technical Note on Incentives and Disincentives for Wheat in the United Republic of Tanzania (2012) by Barreiro-Hurle, J. and Maro, F. Available at: http://www.fao.org/mafap CONTACTS Website: www.fao.org/mafap Email: [email protected] This note was prepared by FAO’s Monitoring African Food and Agricultural Policies (MAFAP) project, the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC) withwith technical support from the OECD and funding from the Bill and Melinda Gates Foundation (BMGF) and USAID. MAFAP supports decision- makers at national, regional and pan-African levels by developing a systematic method for monitoring and analyzing food and agricultural policies in African countries. Figure 4. Wheat area, production and self-sufficiency ratio for the United Republic of Tanzania (2000-2010) - 0.05 0.10 0.15 0.20 0.25 - 20 40 60 80 100 120 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Thousands of hectares / tonne Self-sufficiency ratio (right scale) Area (Ha) Production (tonnes) | false |
# Extracted Content Monitoring African Food and Agricultural Policies TANZANIA MAFAP Country Profile Inconsistent trade policies and a lack of infrastructure lead to lower prices for farmers and higher prices for consumers. Public expenditure should focus more on overcoming these structural barriers, which hamper agricultural growth. MAFAP’s analysis shows that the actual impact of policy measures have not always been aligned with broader policy objectives. For example, inconsistent trade policies generate uncertainty and risk for producers, especially for producers of exported commodities. Weak markets and outdated processing facilities prevent farmers from obtaining higher prices. Consequently, public expenditure should focus more on improving marketing, storage and processing. However, the government has recently been implementing more policy measures aimed at reducing investment and access costs. Other measures that will help farmers receive better prices include: ► ► reducing the use of export bans; ► ► eliminating district taxes on agricultural products; and ► ► expanding the cluster-based approach currently used in the Southern Agricultural Growth Corridor of Tanzania (SAGCOT), in which commercial farms are located near agribusinesses. Despite progress made in adopting a more coordinated sectoral approach under initiatives such as Kilimo Kwanza and the Agricultural Sector Development Strategy, agricultural policies in Tanzania are implemented through a myriad of programs and projects. Markets in the country have been liberalized to a great extent. However, indicative prices persist for several commodities. The government continues to play a strong role in the market through the National Food Reserve Agency. Furthermore, commodity boards play a significant role in the marketing of specific agricultural products, especially exported commodities and sugar. In addition, the agricultural sector is still subject to export taxes and high local taxes, as well as frequent ad hoc interventions such as tariff waivers and export bans. Moreover, there is a lack of transport and storage infrastructure, and many processing facilities are obsolete. Are current policies and public spending well aligned? Public expenditure to support agriculture and rural development Public expenditure on agriculture is declining overall, and its focus is shifting from rural development to agriculture-specific expenditure. The approved budget for the agricultural sector grew by 53 percent, in nominal terms, from 2007 to 2011. However, in relative terms, it declined from almost 13 percent of the total budget in 2007 to about 9 percent in 2011. Although spending was above the Maputo Declaration target from 2007 to 2009, it has since fallen below the target. Expenditure has shifted from support to rural development towards agriculture-specific expenditure. While from 2006 to 2007, rural development accounted for 72 percent of total expenditure, from 2008 to 2011, it decreased to 45 percent. In addition, agriculture-specific expenditure has shifted from general support to the sector (i.e. extension services and agricultural research) towards payments to individual producers, mainly through input subsidies. The United Republic of 4% 5% 4% 6% 6% 9% 12% 8% 3% 4% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 2006/07 2007/08 2008/09 2009/10 2010/11 Figure 1. Public expenditure on agriculture and rural development in the URT (2006 -2010) Percent of national budget Agricultural specific expenditure Rural development expenditure Maputo Declaration target Price incentives Between 2005 and 2010, producers received higher prices compared to international prices, though this positive gap is decreasing. Current policies and weak market performance make food more expensive for consumers, while reducing prices for producers of exported commodities. Domestic prices for imported commodities (milk, rice, sugar and wheat) are higher than international prices. This is mainly due to trade policy in the form of tariffs. On the other hand, domestic prices for exported commodities (cashew nuts, coffee, cotton and pulses) are lower than international prices. This is due to a combination of national policies (i.e. export taxes), inefficient processing facilities and the concentration of market power among traders in export value chains. Furthermore, the lack of storage facilities often forces producers of exported commodities, pulses in particular, to sell their crop immediately after harvest at very low prices. Deficiencies in commodity value chains in Tanzania increased the gap between domestic and international prices by seven percent for exported commodities. However, these constraints reduced the gap by two percent for imported commodities and three percent for commodities essential for food security. Note. The bars measure the percentage of deviation between the price domestic producers receive and what producers would receive in world markets (the latter is the reference price and is equivalent to 0%). Imports include rice, sugar, wheat and cow milk; Exports include cotton, coffee, cashew nuts and pulses; Food security products include maize, sugar, wheat, rice and beans. (Source: MAFAP) Figure 2. Average deviation of producers’ prices from world prices by major commodity groups (2005-2010) -20% 0% 20% 40% 60% 80% 100% 120% MAFAP PARTNERS Policy Analysis Policy Dialogue The Ministry of Agriculture, Food Security and Cooperatives (MAFC) The Economic and Social Research Foundation (ESRF) The Ministry of Agriculture, Food Security and Cooperatives (MAFC) Agricultural Sector Consultative Group MAFAP PRODUCTS for THE UNITED REPUBLIC OF TANZANIA Nine technical notes on market incentives and disincentives in Tanzania for cashew nuts, coffee, cotton, cow milk, maize, rice, sugar cane and wheat Analysis of public expenditure to support agriculture and rural development in Tanzania A comprehensive country report A database with all indicators and supporting information Information about capacity development in using MAFAP’s methodology to analyze market incentives and disincentives, as well as public expenditure All reports and publications are available at: www.fao.org/mafap Our Vision for the Future MAFAP indicators will become part of the regular monitoring and evaluation system that the URT uses to track the implementation of major policy initiatives, such as the Agricultural Sector Development Strategy. It will thus contribute to policy analysis and dialogue in the URT. MAFAP results will also feed into keeping track of the URT’s progress in meeting the Comprehensive Africa Agriculture Development Program (CAADP) and the G8 New Alliance objectives. The URT (together with Uganda and Kenya) are pilot countries for expanding MAFAP analysis to the East African Community and the Common Market for Eastern and Southern Africa. Staff from the MACF and the ESRF will continue to develop capacity in Tanzania and in other countries, and thereby reinforce technical dialogue and exchange at the regional level. CONTACTS Website: www.fao.org/mafap Email: [email protected] Mailing Address: FAO Headquarters Viale delle Terme di Caracalla 00153 Rome, Italy Agricultural sector Imports Exports Food Security Deviation from reference price (%) Commodity groups 2005-2007 2008-2010 2005-2010 17% 47% -1% 20% | false |
# Extracted Content Monitoring African Food and Agricultural Policies TANZANIA 2005-2011 MONITORING AFRICAN FOOD AND AGRICULTURAL POLICIES (MAFAP) REVIEW OF FOOD AND AGRICULTURAL POLICIES IN THE UNITED REPUBLIC OF COUNTRY REPORT JULY 2013 MONITORING AFRICAN FOOD AND AGRICULTURAL POLICIES (MAFAP) REVIEW OF FOOD AND AGRICULTURAL POLICIES IN THE UNITED REPUBLIC OF TANZANIA 2005-2011 COUNTRY REPORT JULY 2013 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Suggested citation: MAFAP (2013). Review of food and agricultural policies in the United Republic of Tanzania. MAFAP Country Report Series, FAO, Rome, Italy. © FAO 2013 FAO encourages the use, reproduction and dissemination of material in this information product. Except where otherwise indicated, material may be copied, downloaded and printed for private study, research and teaching purposes, or for use in non-commercial products or services, provided that appropriate acknowledgement of FAO as the source and copyright holder is given and that FAO’s endorsement of users’ views, products or services is not implied in any way. All requests for translation and adaptation rights, and for resale and other commercial use rights should be made via www.fao.org/contact-us/licence-request or addressed to [email protected]. FAO information products are available on the FAO website (www.fao.org/publications) and can be purchased through [email protected]. 2 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................................................... 3 List of Figures ........................................................................................................................................... 5 List of Tables ............................................................................................................................................ 9 List of Boxes ........................................................................................................................................... 10 Acronyms ............................................................................................................................................... 11 Acknowledgements ............................................................................................................................... 13 ORGANIZATION AND PARTNERS ........................................................................................................... 14 EXECUTIVE SUMMARY........................................................................................................................... 15 Key Findings ....................................................................................................................................... 15 Conclusions ........................................................................................................................................ 21 Introduction ........................................................................................................................................... 23 Part 1. CONTEXT OF FOOD SECURITY AND AGRICULTURAL POLICIES................................................... 25 1. United Republic of Tanzania in brief ............................................................................................. 25 2. Geographical context .................................................................................................................... 31 3. Socio-economic aspects ................................................................................................................ 35 Population ..................................................................................................................................... 35 Poverty, inequality and employment ............................................................................................ 35 Migration and urbanization ........................................................................................................... 37 Education and gender ................................................................................................................... 38 Food security and health ............................................................................................................... 40 4. Macroeconomic performance ....................................................................................................... 43 Performance of agricultural and rural development .................................................................... 44 Input market and major constraints to production ...................................................................... 47 Environment and agriculture ........................................................................................................ 49 5. Agricultural policy framework ....................................................................................................... 51 Selected agriculture-related laws .................................................................................................. 56 Recent policy decisions ................................................................................................................. 59 Agriculture sector budget process ................................................................................................ 65 Part 2: THE EFFECTS OF AGRICULTURAL AND FOOD POLICIES, PUBLIC EXPENDITURE AND AID ......... 69 6. Incentives, disincentives and market development gaps ............................................................. 71 Commodity selection ..................................................................................................................... 72 Highlights of the methodology ...................................................................................................... 74 Indicators for imports .................................................................................................................... 92 Monitoring African Food and Agricultural Policies (MAFAP) 3 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Indicators for exports .................................................................................................................. 109 Indicators for thinly traded products .......................................................................................... 126 Indicators for commodities important for food security ............................................................ 130 Conclusions .................................................................................................................................. 131 7. Public expenditure and aid .......................................................................................................... 135 Introduction ................................................................................................................................. 136 General trends in public expenditure.......................................................................................... 137 General trends in public spending in support of agriculture ...................................................... 139 Composition of public expenditures in support of the food and agriculture sector .................. 143 Role of aid in agriculture-related public expenditures ................................................................ 151 Analysis of public expenditures ................................................................................................... 151 8. Coherence between incentives and government spending ........................................................ 155 Introduction ................................................................................................................................. 155 Government's main objectives .................................................................................................... 155 Factors driving the value chains .................................................................................................. 156 Assessing the effects of major decisions and policy measures based on the results of the MAFAP analysis ........................................................................................................................................ 164 Conclusion on policy coherence .................................................................................................. 172 Part 3. A REVIEW OF THE IMPACT OF THE MAIZE EXPORT BAN IN THE UNITED REPUBLIC OF TANZANIA ............................................................................................................................................ 173 Maize in the United Republic of Tanzania ................................................................................... 173 Maize market integration in the United Republic of Tanzania ................................................... 176 Impacts of the export ban: a review of the literature ................................................................. 183 Additional measures of the impact of the maize export ban...................................................... 186 Conclusions .................................................................................................................................. 191 Part4. CONCLUSIONS AND RECOMMENDATIONS............................................................................... 193 Incentives, disincentives and market development gaps ........................................................... 193 Public expenditure and aid .......................................................................................................... 197 Coherence of agricultural and food policies ............................................................................... 198 REFERENCES ........................................................................................................................................ 201 Annex I. SUMMARY OF MAIN METHODOLOGICAL CONCEPTS USED IN THE PUBLIC EXPENDITURE ANALYSIS. ............................................................................................................................................ 211 Annex II. PROJECTS AND PROGRAMMES INCLUDE IN EACH OF THE CATEGORIES OF PUBLIC EXPENDITURE. ..................................................................................................................................... 215 4 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report List of Figures Figure i. Average deviation of producers’ prices from the prices producers would receive in world markets .................................................................................................................................................. 16 Figure ii. Nominal rate of protection of exported commodities in the United Republic of Tanzania (2005-2010) ........................................................................................................................................... 17 Figure iii. Level and distribution of public expenditure to support the agricultural sector in the United Republic of Tanzania (2006-2011) ......................................................................................................... 18 Figure iv. Ratio of public expenditure to support specific commodities to disincentives resulting from policy and market performance ............................................................................................................ 20 Figure 1: Contribution of different economic sectors to GDP in the United Republic of Tanzania, 2000 to 2025 .................................................................................................................................................. 25 Figure 2: Aggregate economic (GDP) growth by sector in the United Republic of Tanzania, 2000 to 2011 ....................................................................................................................................................... 26 Figure 3: Map of the United Republic of Tanzania ................................................................................ 31 Figure 4: Evolution of total population in the United Republic of Tanzania, 1967 to 2012.................. 35 Figure 5: Net enrolment rates in primary schools in the United Republic of Tanzania, 2003 to 2010 . 39 Figure 6: Main health and nutrition problems in the United Republic of Tanzania, 2010 ................... 40 Figure 7: Annual real GDP growth rates in the United Republic of Tanzania, 1998 to 2010 ................ 43 Figure 8: Growth rates of total GDP and agriculture in the United Republic of Tanzania, 1998 to 2009 ............................................................................................................................................................... 45 Figure 9: Growth rates of cattle (red line) and sheep and goat (blue line) populations in the United Republic of Tanzania, 2002 to 2010 ...................................................................................................... 46 Figure 10: Annual headline, food and non-food inflation in the United Republic of Tanzania, 2009 to 2012 ....................................................................................................................................................... 46 Figure 11: Trends in the food self-sufficiency ratio and poverty indicators in the United Republic of Tanzania, 2000 to 2010 ......................................................................................................................... 47 Figure 12: Fertilizer use in the United Republic of Tanzania, 2001 to 2010 ......................................... 48 Figure 13: Policy framework for agriculture and food security in the United Republic of Tanzania .... 52 Figure 14: Food and Agricultural Policy Decision Analysis classification of food and agricultural policies ................................................................................................................................................... 60 Figure 15: The MAFAP methodology for price incentive and disincentive analysis ............................. 76 Figure 16: Comparison of costs of cross-border trade in the United Republic of Tanzania calculated by the Doing Business and MAFAP projects .............................................................................................. 84 Figure 17: Ratio of commodity-specific public expenditure support to disincentives resulting from policy and market performance in the United Republic of Tanzania, 2007 to 2010 ............................ 90 Figure 18: Average observed and adjusted nominal rates of protection and market development gaps for the agriculture sector in the United Republic of Tanzania, 2005 to 2010 ....................................... 92 Figure 19: Average observed and adjusted nominal rates of protection and market development gaps at the farmgate for imported products in the United Republic of Tanzania, 2005 to 2010 ................. 93 Figure 20: Volume of rice trade and share of trade in domestic consumption in the United Republic of Tanzania, 2000 to 2010 ......................................................................................................................... 95 Figure 21: MAFAP nominal rates of protection for rice in the United Republic of Tanzania, 2005 to 2010 ....................................................................................................................................................... 96 Monitoring African Food and Agricultural Policies (MAFAP) 5 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 22: Trends in wholesale and farmgate price gaps for rice in the United Republic of Tanzania , 2005 to 2009 ......................................................................................................................................... 97 Figure 23: MAFAP nominal rates of protection for sugar (wholesale) and sugar cane (farmgate) in the United Republic of Tanzania 2005-2010 ............................................................................................. 100 Figure 24: Comparison of sugar processing costs used in the analysis and those reported by the Mtibwa Sugar Plant in the United Republic of Tanzania, 2005 to 2007 ............................................. 101 Figure 25: MAFAP nominal rates of protection for wheat in the United Republic of Tanzania, 2005 to 2010 ..................................................................................................................................................... 103 Figure 26: Comparison of tariff values and price gaps for wheat at wholesale and the farmgate in the United Republic of Tanzania, 2005 to 2010 ........................................................................................ 104 Figure 27: MAFAP nominal rates of protection for milk in the United Republic of Tanzania, 2007 to 2010 ..................................................................................................................................................... 107 Figure 28: Farmgate and implicit prices paid by processors to farmers for milk in the United Republic of Tanzania, 2007 to 2010 ................................................................................................................... 108 Figure 29: Average observed and adjusted nominal rates of protection and market development gaps for exported products in the United Republic of Tanzania, 2005 to 2010.......................................... 109 Figure 30: Farmgate nominal rates of protection for export commodities in the United Republic of Tanzania, 2005 to 2010 ....................................................................................................................... 110 Figure 31: MAFAP nominal rates of protection for coffee in the United Republic of Tanzania, 2005 to 2010 ..................................................................................................................................................... 113 Figure 32: Changes in FOB and farm-gate prices for coffee in the United Republic of Tanzania, 2005 to 2010 ..................................................................................................................................................... 114 Figure 33: MAFAP nominal rates of protection for cotton in the United Republic of Tanzania, 2005 to 2010 ..................................................................................................................................................... 117 Figure 34: Comparison of disincentives due to ginning inefficiency and taxation of seed cotton in the United Republic of Tanzania, 2005 to 2010 ........................................................................................ 118 Figure 35: MAFAP nominal rates of protection for cashew nuts in the United Republic of Tanzania, 2005 to 2011 ....................................................................................................................................... 121 Figure 36: Shares of FOB price represented by farm-gate and auction prices for cashew nuts in the United Republic of Tanzania, 2005 to 2011 ........................................................................................ 122 Figure 37: Revenues from the cashew export tax and public expenditure allocated to the cashew nut sector in the United Republic of Tanzania, 2005 to 2011 ................................................................... 123 Figure 38: MAFAP nominal rates of protection for peas in the United Republic of Tanzania, 2007 to 2010 ..................................................................................................................................................... 125 Figure 39: Price comparisons for peas in the United Republic of Tanzania, 2005 to 2010................. 126 Figure 40: MAFAP nominal rates of protection for maize in the United Republic of Tanzania, 2005 to 2010 ..................................................................................................................................................... 129 Figure 41: Average observed and adjusted nominal rates of protection and market development gaps for commodities important for food security in the United Republic of Tanzania, 2005 to 2010 ..... 131 Figure 42: Observed nominal rates of protection for the agriculture sector and by commodity group in the United Republic of Tanzania, 2005 to 2010 .............................................................................. 132 Figure 43: Adjusted nominal rates of protection for the agriculture sector and by commodity group in the United Republic of Tanzania, 2005 to 2010 .................................................................................. 133 Figure 44: Evolution of total budget for the United Republic of Tanzania, 2006/07 to 2010/11 (current TSh) ...................................................................................................................................................... 138 6 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 45: Evolution of total budget for the United Republic of Tanzania, 2006 to 2010 (constant 2007 TSh) ...................................................................................................................................................... 138 Figure 46a: Public expenditures in support to the food, agriculture and rural development sector as shares of total government expenditures in the United Republic of Tanzania: planned versus actual spending, 2006/07 to 2010/11 ............................................................................................................ 141 Figure 46b: Public expenditures in support to the agriculture sector as shares of total government expenditures in the United Republic of Tanzania: planned versus actual spending, 2006/07 to 2010/11 ............................................................................................................................................... 142 Figure 47: Composition of expenditures in support of the food and agriculture sector in the United Republic of Tanzania: actual spending, 2006/07 to 2010/11.............................................................. 144 Figure 48: Composition of agriculture-specific spending in the United Republic of Tanzania, averages for 2006/07 to 2007/08 ....................................................................................................................... 145 Figure 49: Composition of agriculture-specific spending in the United Republic of Tanzania, averages for 2008/09 to 2010/11 ....................................................................................................................... 145 Figure 50: Composition of agriculture-supportive spending in the United Republic of Tanzania, averages for 2006/07 to 2007/08 ....................................................................................................... 147 Figure 51: Composition of agriculture-supportive spending in the United Republic of Tanzania, averages for 2008/09 to 2010/11 ....................................................................................................... 147 Figure 52: Agriculture-specific spending in support of commodities in the United Republic of Tanzania, 2006/07 to 2010/11 ............................................................................................................ 148 Figure 53: Support to individual and groups of commodities in the United Republic of Tanzania, averages for 2006/07 to 2010/11 ....................................................................................................... 149 Figure 54: Average shares of aid in public expenditures in support of the food and agriculture sector in the United Republic of Tanzania, 2006/07 to 2007/08 and 2008/09 to 2010/11 (billion TzSh) ..... 150 Figure 55: Ratios between access costs from the farmgate to the point of competition and price differentials for selected commodities in the United Republic of Tanzania, 2005 to 2009 ................ 166 Figure 56: Public investments in rural roads in the United Republic of Tanzania, 2007 to 2011 ....... 167 Figure 57: NFRA purchase prices and wholesale prices in the main maize surplus areas in the United Republic of Tanzania, 2006 to 2010 .................................................................................................... 168 Figure 58: Trends in public expenditure in support of storage and public stockholding and marketing in the United Republic of Tanzania, 2007 to 2011 .............................................................................. 169 Figure 59: Price comparison for peas in the United Republic of Tanzania, 2005 to 2011 .................. 171 Figure 60: Trends in public expenditure as transfers to processors in the United Republic of Tanzania, 2007 to 2011 ....................................................................................................................................... 172 Figure 61: Maize area, production and yield in the United Republic of Tanzania .............................. 174 Figure 62: Production and market flows of maize in the United Republic of Tanzania. ..................... 177 Figure 63: Location of the wholesale markets for which maize prices have been analysed .............. 178 Figure 64: Maize prices in five selected wholesale markets in the United Republic of Tanzania, 2006- 2012 ..................................................................................................................................................... 179 Figure 65: Maize prices in selected international markets and Dar es Salaam, 2005–2012 .............. 180 Figure 66: Regional markets for maize in East Africa .......................................................................... 180 Figure 67: Maize prices trends in Dar es Salaam and major capitals of neighbouring countries ....... 182 Table 29: Chronology of export restrictions events in the United Republic of Tanzania, 2004–2013 183 Figure 68: Informal maize exports from the United Republic of Tanzania to Kenya .......................... 184 Monitoring African Food and Agricultural Policies (MAFAP) 7 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 30: Comparison of average informal maize exports from the URT to Kenya during export ban and non-export ban periods, July 2010 to December 2011 ................................................................ 185 Figure 69: Maize prices in selected markets in Nairobi and in the United Republic of Tanzania, 2006– 2012 ..................................................................................................................................................... 187 8 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report List of Tables Table 1: Development and performance indicators (DPIs) in the United Republic of Tanzania........... 28 Table 2: Seasons in the United Republic of Tanzania ............................................................................ 32 Table 3: Incidence of poverty in mainland United Republic of Tanzania: headcount poverty index, 2001 and 2007 (percentages) ................................................................................................................ 36 Table 4: Gini coefficient for the United Republic of Tanzania, 2008/2009 (NPS1) and 2010/2011 (NPS2) .................................................................................................................................................... 36 Table 5: Regional distribution of population between rural and urban areas in mainland United Republic of Tanzania, 2002 ................................................................................................................... 38 Table 6: Literacy among population over 15 years in the United Republic of Tanzania, by residence and gender (percentages) ..................................................................................................................... 38 Table 7: Indicators of child malnutrition in the United Republic of Tanzania, 1999, 2005 and 2010 ... 41 Table 8: Health challenges for children and women in the United Republic of Tanzania, 2010 .......... 41 Table 9: Quarterly GDP growth in the United Republic of Tanzania, 2006 to 2011 (percentages) ...... 44 Table 10: Planned sectoral contributions to GDP for the medium and long terms in the United Republic of Tanzania, 2010 to 2025 ...................................................................................................... 44 Table 11: Agriculture sector objectives and targets from national medium-term strategies in the United Republic of Tanzania.................................................................................................................. 53 Table 12: EAC CET rates for imported commodities used in the MAFAP analysis of the United Republic of Tanzania (percentages) ..................................................................................................................... 64 Table 13: Commodities studied and their coverage of agricultural production, agricultural trade and diet in the United Republic of Tanzania, 2005 to 2010 ......................................................................... 73 Table 14: Commodity groupings used in the analysis of price incentives and disincentives in the United Republic of Tanzania.................................................................................................................. 74 Table 15: Marketing channel assumptions used in the analysis of price incentives and disincentives in the United Republic of Tanzania ........................................................................................................... 80 Table 16: Methodological options and data sources for domestic prices used in the United Republic of Tanzania analysis ............................................................................................................................... 81 Table 17: Methodological options and data sources for benchmark prices used in the United Republic of Tanzania analysis ............................................................................................................................... 82 Table 19: Access cost components for the trade paths in the United Republic of Tanzania ................ 85 Table 20: Observed and adjusted price gaps in the United Republic of Tanzania, 2005 to 2010 (TSh/tonne) ........................................................................................................................................... 87 Table 21: Observed and adjusted nominal rates of protection in the United Republic of Tanzania, 2005 to 2010 ......................................................................................................................................... 88 Table 22: Observed and adjusted nominal rates of assistance to producers in the United Republic of Tanzania, 2005 to 2010 ......................................................................................................................... 89 Table 23: Total public expenditures in support of the food and agriculture sector in the United Republic of Tanzania, 2006/07 to 2010/11 ......................................................................................... 139 Table 24: Public expenditures in support of the food and agriculture sector in the United Republic of Tanzania: actual spending, 2006/07 to 2010/11 ................................................................................. 143 Table 25: Budget allocations versus actual spending in the United Republic of Tanzania, 2006/07 to 2010/11 (billion TSh) ........................................................................................................................... 153 Monitoring African Food and Agricultural Policies (MAFAP) 9 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 26: Shares of policy transfers and administration costs in public expenditures of MAFC and MLFD, 2006/07 to 2010/11 (percentages) .......................................................................................... 154 Table 27: MAFAP coherence matrix for the United Republic of Tanzania .......................................... 157 Table 28: Average port costs and charges in Africa, 2011 (US$ per unit) ........................................... 165 Table 31: Volatility of maize prices in different markets of the URT during export ban and non-export ban periods, 2006–2012 ...................................................................................................................... 186 Table 32: Comparison of average margins for maize in periods with and without the export ban for select markets in the United Republic of Tanzania (2006–2012) ....................................................... 188 Table 33: Comparison of average margins for maize in periods with and without the export ban for select markets in the United Republic of Tanzania and neighbouring countries (2006–2012) .......... 189 Table 34: MAFAP nominal rates of protection (NRP) for maize in the United Republic of Tanzania, 2006–2010 ........................................................................................................................................... 190 List of Boxes Box 1: Main agricultural laws in the United Republic of Tanzania ........................................................ 56 Box 2: Summary of results regarding incentives, disincentives and market development gaps in the United Republic of Tanzania.................................................................................................................. 71 Box 3: Summary of results regarding public expenditure and aid in the United Republic of Tanzania ............................................................................................................................................................. 135 Box 4: Definitions of terminology used in the MAFAP analysis .......................................................... 137 10 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Acronyms ACT Agricultural Council of Tanzania ADB African Development Bank AFSP Accelerated Food Security Project AGITF Agricultural Inputs Trust Fund AMSDP Agricultural Marketing Systems Development Programme ASDP Agricultural Sector Development Programme ASDS Agricultural Sector Development Strategy ASLM Agricultural Sector Lead Ministries BOT Bank of Tanzania CAADP Comprehensive Africa Agriculture Development Programme CBO Community-Based Organization CBT Cashewnut Board of Tanzania CET Common External Tariff (EAC) CIF Cost, Insurance, Freight COMESA Common Market for Eastern and Southern Africa CSO Civil Society Organization DASIP District Agriculture Sector Investment Project DFID Department for International Development DPI Development Performance Indicator EAC East African Community EAGC Eastern Africa Grain Council EIU Economist Intelligence Unit ESRF Economic and Social Research Foundation EU European Union FOB Free On Board FRA Global Forest Resources Assessment (FAO) FYDP Five-Year Development Plan GDP Gross Domestic Product GIEWS Global Information and Early Warning System of the Food and Agricultural Organization of the UN IFAD International Fund for Agricultural Development IFPRI International Food Policy Research Institute IMF International Monetary Fund LEAT Lawyers’ Environmental Action Team LGA Local Government Authority MACEMP Marine and Coastal Environment Management Project MAFAP Monitoring African Food and Agricultural Policies MAFC Ministry of Agriculture, Food Security and Cooperatives MDG Market Development Gap MEVT Ministry of Education and Vocational Training MFN Most-Favoured Nation MKUKUTA National Strategy for Growth and Reduction of Poverty Monitoring African Food and Agricultural Policies (MAFAP) 11 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report MLFD Ministry of Livestock and Fisheries Development MoF Ministry of Finance and Economic Affairs MRAF Medium-Term Expenditure Framework MTI Ministry of Trade and Industry NAIVS National Agricultural Input Voucher Scheme NBS National Bureau of Statistics NFRA National Food Reserve Agency NPS National Panel Survey NRA Nominal Rate of Assistance NRP Nominal Rate of P OECD Organisation for Economic Co-operation and Development PADEP Participatory Agricultural Development and Empowerment Project PMO-RALF Prime Minister’s Office – Regional Administration and Local Government PRS Poverty Reduction Strategy RESAKSS Regional Strategic Analysis and Knowledge Support Systems R&D Research and Development RFSP Rural Financial Services Programme RLDC Rural Livelihood Development Company RPFB Rolling Plan and Forward Budget SACCO Savings And Credit Cooperative SADC Southern African Development Community SAGCOT Southern Agricultural Growth Corridor of Tanzania SBT Sugar Board of Tanzania SUMATRA Surface and Maritime Transport Regulatory Authority of Tanzania TAFSIP Tanzania Agriculture and Food Security Investment Plan TCfB Tanzania Coffee Board TCtB Tanzania Cotton Board TDV Tanzania Development Vision TFNC Tanzania Food and Nutrition Centre UDSM University of Dar es Salaam UN United Nations UNDP United Nations Development Programme UNIDO United Nations Industrial Development Organization URT United Republic of Tanzania USAID United States Agency for International Development VAT Value-Added Tax WCGA Western Cotton Growing Area WDI World Development Indicator WHO World Health Organization WRS Warehouse Receipt System WTO World Trade Organization 12 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Acknowledgements This report is a product of a joint and collaborative work involving many people and institutions within FAO, OECD and partners in the United Republic of Tanzania from the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC). This preparation of the report was coordinated by Jesús Barreiro-Hurlé (FAO). Part 1 was drafted by Hoseana Lunogelo (ESRF), Agnese Bazzucchi (FAO) and Sunae Kim (FAO). It was compiled and revised by Jesús Barreiro-Hurle (FAO). Alban Mas Aparisi (FAO) undertook a final revision of the section and provided valuable comments. Part 2 was compiled and revised by Jesús Barreiro-Hurle (FAO). Price incentives and disincentives analysis is based on a series of commodity specific technical notes which were drafted by Solomon Baregu (ESRF), Festo Maro (ESRF), Lutengano Mwinuka (U. of Dodoma), Nganga M. Nkonya (MAFC), and Jesús Barreiro-Hurle (FAO). The analysis of public expenditure was undertaken by Joanna Ilicic- Komorowska (OECD) with the support of Jesús Barreiro-Hurle (FAO), Happy Pascal (MAFC) and Festo Maro (ESRF). The MAFAP secretariat team at FAO and the PSE Advisory Group at OECD provided valuable inputs for the drafting of these notes. The Ministry of Trade and Industry, the Ministry of Finance, the National Bureau of Statistics, the Tanzania Cotton Board, the Cashew Board of Tanzania, the Tanzania Coffee Board and the Sugar Board of Tanzania were instrumental in facilitating the access to the underlying data used in the analysis. In addition, Helen Gourichon (FAO) and Luis Monroy (FAO) contributed to the drafting of the policy coherence section. Preliminary results of this part were presented in Dar es Salaam to a meeting of the Agricultural Sector Working Group in November 2012 and their feedback incorporated into this final version. Jean Balie (FAO) and Federica Angelucci (FAO) revised this section providing additional and relevant inputs. Part 3 was drafted Jesús Barreiro Hurle (FAO), with contributions of Festo Maro (ESRF) and Solomon Baregu (ESRF) under the guidance of Hoseana Lunogelo (ESRF). Mohamed Ahmed (FAO), Seth Meyer (FAO) and Piero Conforti (FAO) revised this section providing additional and relevant inputs. Special thanks goes to the GIEWS team at FAO for providing access to the price data used for the analysis. The OECD PSE Advisory group revised an earlier draft of the report providing very useful insights that have improved overall readability and accuracy of policy evaluation. A final draft of the report was presented to the MAFC Management on June 2013. Following the presentation detailed feedback was provided to the drafting team.The incorporation of these feedback was instrumental on the quality and comprehensiveness of the final version of the report. The full report was revised by Jane Shaw and Maria Giannini for language, layout and proofing. The executive summary was revised by Robert Brinkman. Special thanks are given to Diana Tempelman (FAO Representative to the URT) and Dr. Emmanuel Achayo (Director of Policy and Planning at the MAFC) for their overall support and commitment to facilitate the work. Monitoring African Food and Agricultural Policies (MAFAP) 13 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report ORGANIZATION AND PARTNERS The MAFAP project in the United Republic of Tanzania is implemented in collaboration with the Ministry of Agriculture, Food Security and Cooperatives (MAFC) and the Economic and Social Research Foundation (ESRF). Staff from these two institutions are involved in the calculation of the indicators and are expected to continue updating this analysis in a regular basis with the support of the MAFAP secretariat. MAFC plays an active role in putting forward MAFAP results as inputs to different forums where agricultural policy is discussed. 14 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report EXECUTIVE SUMMARY This report presents findings from the first agricultural policy review conducted by the Monitoring African Food and Agricultural Policies (MAFAP) project in the United Republic of Tanzania. The report reviews key economic issues and the main policy decisions affecting the agricultural sector. In particular, it focuses on price incentives and disincentives faced by farmers and consumers of nine agricultural commodities which make up a significant part of agricultural production, imports, exports and diet. It also presents a detailed analysis of the composition and level of public expenditure to support the agricultural sector. The periods analysed were 2005 to 2010 for commodities and 2006 to 2011 for public expenditure. Finally, it reviews the impact of the maize export ban on farmers and consumers. The report offers results based on using MAFAP’s rigorous methodology for measuring the effects of agricultural and food policies, as well as public spending, on agriculture and rural development. Its findings and recommendations are expected to support the dialogue on agricultural and food policies in the United Republic of Tanzania. The MAFAP project in the United Republic of Tanzania is implemented in collaboration with the Ministry of Agriculture, Food Security and Cooperatives (MAFC) and the Economic and Social Research Foundation (ESRF). Key Findings About 75 percent of the population of the United Republic of Tanzania is employed in agriculture, but productivity is among the lowest in sub-Saharan Africa. Low productivity is mostly due to over-reliance on unpredictable natural precipitation, use of manual labour to work the land, the limited use of improved seed and fertilizer, and low-productivity indigenous animal breeds. Agriculture, which in the past ten years has been growing at the rate of about 4.2 percent annually, makes up a quarter of the URT’s gross national domestic product, and about 34 percent of foreign exchange earnings. Despite progress made in adopting a more coordinated sectoral approach with initiatives such as Kilimo Kwanza and the Agricultural Sector Development Strategy (ASDS), agricultural policies in Tanzania are still implemented through a myriad of programs and projects. Government decisions on trade, especially those relating to tariffs, are numerous and sometimes contradict other policy objectives. While markets have been liberalized to a great extent, indicative prices persist for several commodities. Indeed, the government intervenes directly through the National Food Reserve Authority. Furthermore, commodity boards play a significant role for specific commodities (mainly export products but also sugar). The agricultural sector is still subject to export taxes and high local taxation; and ad- hoc interventions such as tariff waivers and export bans are frequent. Moreover, the lack of transport and storage infrastructure impedes market integration and processing plants are largely obsolete. Monitoring African Food and Agricultural Policies (MAFAP) 15 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Producers in the URT benefited from price incentives, although these decreased from 2005 to 2010. Policies and market performance keep prices high for consumers but low for producers of export commodities. Figure i. Average deviation of producers’ prices from the prices producers would receive in world markets Note. The bars show the percentage of deviation of producers’ prices from the prices producers would receive in world markets (reference price). Imports include rice, sugar, wheat and cow milk; exports include cotton, coffee, cashew nuts and pulses; food security crops include maize, sugar, wheat, rice and beans. Source: MAFAP This trend for decreasing incentives masks a contradictory situation: producers of imported commodities received price incentives while producers of exported commodities received disincentives. Producers of exported commodities received lower prices than they could have obtained because of policies, traders’ high market power and inefficient processing facilities. Moreover, some commodities were protected at the wholesale (processed) level but penalized at farmgate (raw) level. This has had a negative impact on food security by making food less affordable and scarcer. Most of the incentives for imported commodities were due to trade policies, while disincentives for export commodities related to taxes and inefficient processing industries. In addition, some of the protection for imported goods offered by trade policies was eroded by excessive marketing costs along the value chain. Farmers producing commodities which the URT imports to cover domestic consumption received incentives. The common external tariff which the URT applies to imports from outside the East African Community (EAC) helps keep prices higher for producers. The only exception is sugar, whose producers face strong disincentives. For all imported commodities, 17% 47% -1% 20% -20% 0% 20% 40% 60% 80% 100% 120% Agricultural Sector Imports Exports Food Security Deviation from reference price Commodity groups 2005-2007 2008-2010 2005-2010 16 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report protection at the farmgate was eroded by high transport and marketing costs due to a lack of market integration and inefficiencies in the value chain. Sugarcane growers did not benefit from protection offered by tariffs and did not seem to be affected by changes in trade policy. Inefficient sugar mills kept prices lower than they could have been for sugar farmers. The government should consider removing the sugar import tariff, as it keeps sugar prices high without benefiting farmers. Investments in making sugar mills more efficient should be facilitated so that processors will be able to pay sugarcane producers more. The reduction of incentives for imported products reflects the impact of tariff waivers and increased self-sufficiency ratios for rice. In response to the 2008 high food price crisis, the URT partially waived tariffs for wheat and sugar. This measure was not as effective as expected since domestic wheat and sugar prices remained higher than international benchmark prices. Rice farmers received more incentives than rice wholesalers. However, this situation was reversed after the rice sector was liberalized in 2007. Farmers producing export commodities would have obtained higher prices in a policy-free environment and with better market performance. Factors which kept producers’ prices low included taxes on cotton, cashew nuts; poorly functioning value chains for coffee, and cashew nuts; and inefficiencies in the cotton processing sector. From 2005 to 2010, producers of pulses received higher prices but producers of traditional exports were penalized. Average domestic prices for pulses were higher than export prices. This would usually be considered as an incentive for producers, however, in this specific case, a lack of storage facilities forced traders to export pulses when prices were low. Producers thus missed the opportunity to benefit from higher non seasonal prices in domestic markets. Figure ii. Nominal rate of protection of exported commodities in the United Republic of Tanzania (2005-2010) Note: Traditional export crops include coffee, cotton and cashew nuts Source: MAFAP Producers of commodities important for food security received relatively higher prices, but consumers also paid higher prices. Incentives made food less affordable for consumers and -60% -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 2005 2006 2007 2008 2009 2010 Nominal Rate of Protection at Farm Gate COFFEE COTTON BEANS CASHEW NUTS Traditional exports Monitoring African Food and Agricultural Policies (MAFAP) 17 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report overall analysis shows a conflicting impact on food security. On one hand, farmers received support and were thus more likely to increase investments and production. This has been most apparent for rice, where the URT has gone from being an importing country to a net exporter. However, incentives for other commodities have not had a positive impact on domestic food availability. Excessive marketing costs reduced the benefits of protection and kept producers’ prices for all commodities lower than what they could have been. However, in general, policies and the lack of functioning markets create more disincentives than excessive marketing costs. Public expenditure to support agriculture has been declining. While the total approved budget for the agricultural sector grew by 53 percent in nominal terms from 2007 to 2011, in relative terms it declined from almost 13 percent of total government spending in 2007 to about 9 percent in 2011. Actual spending grew at a slower pace and, in relative terms, decreased significantly in this period. Although public spending was above the Maputo Declaration target from 2007 to 2009, it has since remained below the target. The composition of public spending has shifted from rural development to agriculture- specific expenditure. In the first half of the period studied, rural development accounted for 72 percent of total expenditure. During the second half of the period, it declined to 45 percent. Figure iii. Level and distribution of public expenditure to support the agricultural sector in the United Republic of Tanzania (2006-2011) Source: MAFAP 4% 5% 4% 6% 6% 9% 12% 8% 3% 4% Maputo declaration target 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 2006/07 2007/08 2008/09 2009/10 2010/11p percentage of national budget Agricultural specific expenditure Rural development expenditure 18 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Agriculture-specific support has shifted from general sector support to payments to farmers and other agents in the agricultural sector. General sector support (training, extension, and research and development) accounted for over 60 percent of expenditure in the first half of the period analyzed. However, from 2009 onwards, there was an increased focus on payments to producers via input subsidies. General sector support declined to less than 50 percent. This increasing use of direct transfers to producers has led to fewer extension services and less support for storage facilities, marketing and infrastructure. Expenditures on rural development accounted for about 55 percent of overall support to the food and agriculture sector. Most of this was spent on rural infrastructure, including rural roads, water infrastructure, sanitation and energy. Considerably less was spent on rural health and education. Most public spending was on public services, investments in infrastructure, training, extension services and research. However, spending on input subsidies for agricultural producers, in particular on subsidies for variable inputs, has been rapidly increasing. Only four percent of public expenditure in the agricultural sector was targeted towards specific commodities. 50 percent of total expenditure was not targeted to any specific commodity or group of commodities. The remaining 47 percent was split evenly between maize and rice (mainly on fertilizer subsidies) and generic commodity groups. Close to 25 per cent of the budget was allocated to policy administration costs. The increased share of administration costs after 2008/09 may be partially explained by the reallocation of funds, as part of an overall financial crisis management plan. These funds had been previously allocated for supporting the agricultural sector (policy transfers). Moreover, the rates of actual spending to budget allocation in Tanzania suffered a significant fall between 2008 and 2010. Spending rates were lower for policy transfers compared to administrative spending. At least 50 percent of public expenditure on the food and agriculture sector in the URT came from donor contributions. However, there was a diminishing trend in the role of foreign aid during the period analysed. External aid made up 44 percent of the agriculture- specific budget and 64 percent of the rural development budget. Donor and government priorities in allocating public funds are closely aligned. Policies and market performance had a much greater impact on specific commodities than public expenditure. Indeed, even including both commodity specific and non-targeted support, public expenditure compensated for only about 15 percent of disincentives measured via price gaps. Monitoring African Food and Agricultural Policies (MAFAP) 19 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure iv. Ratio of public expenditure to support specific commodities to disincentives resulting from policy and market performance Note: The bars show the ratio of public expenditure on each commodity to the price gap between observed and reference prices Source: MAFAP The maize export ban was introduced to reduce prices and to ensure food security. However, this study shows that these objectives were only partially achieved. Informal exports surged when export bans were in place and reduced the ban’s expected impact - ie. that of reducing the price of food because of increased food availability. However, the export ban did little to improve the poor integration of domestic markets. Thus, even when more produce remained in the country, areas with a food deficit did not have easy access to the surplus food available. The export ban limited the profits of farmers in the Southern Highlands, while it seemed to promote more trade in the western and northern parts of the country. If the URT is to realize its full potential for becoming the bread basket of East Africa, other policy instruments should be considered. In order to mitigate the impact of consumer price surges when unexpected spikes in export demand occur, subsidized food programmes should be better targeted or substituted by cash transfers. 0% 20% 40% 60% 80% 100% 120% 140% 2007 2008 2009 2010 cashew coffee cotton milk sugar cane Weighted average aggregate 20 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Conclusions The URT should consider adopting less volatile trade policies. This could include deciding whether import tariffs are needed or not and moving definitively away from export bans. Public expenditure should focus more on infrastructure aimed at improving markets (roads, storage, market information systems, etc.). Initiatives such as the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) appear to be a step in the right direction. The draft of the Agricultural Sector Development Strategy (ASDP II) is a unique opportunity for aligning public investment with policies aimed at increasing agricultural output and productivity, while reducing hunger and poverty. The impact of policies and poor market performance kept the URT from adequately meeting its food security objectives. Except for rice and wheat, farmers received lower prices than what they would have obtained without domestic policies and with better performing value chains. Producers of all other commodities received disincentives, thus limiting farmers’ potential for increasing investments and production volume. While lower producers’ prices might imply that food is more affordable for consumers, most of the price disincentives are related to classic export crops, which are not part of the normal Tanzanian diet. At the wholesale level (i.e. the level closest to purchase by consumers), most food security commodities, except for maize, had positive price gaps. Thus, the cost of the average Tanzanian diet is higher than it would be in the absence of policies and with better performing markets. Contradictory trade policy actions (such as tariffs versus waivers) generate uncertainty for producers and penalize export-oriented commodities. Poor market performance and inefficient processing plants reduce the farmgate prices of food crops, without reducing consumer prices. Public expenditure should focus on marketing, storage and processing. Disincentives can be minimized or eliminated in all of these crucial areas. Finally, there appears to be significant room for improving policy coherence in the URT. The government of the URT has delineated policy measures aimed at reducing investment and access costs. Measures aimed at reducing the level of disincentives for farmers include the declared commitment to abandon export bans, the move towards eliminating district taxes for agricultural products, and the SAGCOT approach. Monitoring African Food and Agricultural Policies (MAFAP) 21 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Introduction The Monitoring African Food and Agricultural Policies (MAFAP) project aims to help African policy- makers and development partners ensure that policies and investments in agriculture and rural development focus on improving productivity in agriculture, sustainable use of natural resources and strengthening food security. From this perspective, the project has conducted a thorough analysis of agricultural and food policies based on the results of analyses of the structure, level and composition of public spending and of the incentives and disincentives faced by different actors in the United Republic of Tanzania’s (URT’s) main agricultural sectors. This report is the first review of policies under the MAFAP project. It draws on ten technical notes providing detailed and innovative analyses of nine commodities that are important for production, trade and food security in the URT. These commodities also absorb a large share of government expenditure and aid. The technical notes, which constitute the full results of the MAFAP project, are available at www.mafap.org/urt. This review will be updated periodically as part of biennial country reporting, identifying key developments in the sector. The main objective of this review is to support dialogue on food and agricultural policies in the URT among principal decision-makers and development partners. The report outlines concrete results achieved through the implementation of a rigorous methodology for measuring the effects on agriculture and rural development of agricultural and food policies and public spending. While this approach is not new, its systematic application to a specific period and selection of commodities is innovative. The report aims to shed new light on the rural and agriculture sector in the URT to inform and guide decision-makers and prompt them to support the institutionalization of this type of work in the country. MAFAP seeks to clarify and inform debate on policy reform, but not to promote or influence specific reforms or adjustments which have been designed outside the country. Such developments must be endogenous and based on dialogue on government policies among stakeholders in the country. This report does not claim to be an exhaustive presentation of either methods or viewpoints. It is therefore important that the policy dialogue it engenders be supplemented by contributions from the institutional actors who can provide valuable observations on the situation regarding agricultural and food policies in the URT. The report has three main parts: [1] The first part offers a description and analysis of the context of government policy in the URT, notably through selected development performance indicators (DPIs). It also describes the main government policy decisions in the field of food and agriculture in the country. [2] The second part constitutes the core of the report. First it presents the incentives and disincentives to production observed for the nine main commodities studied. Then it provides an Monitoring African Food and Agricultural Policies (MAFAP) 23 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report in-depth study of the level, composition and efficiency of public expenditure and aid, before exploring and discussing the coherence of government policy. [3] The third part deals with a topic of specific national interest to the URT, selected in collaboration by the MAFAP Secretariat, the Economic and Social Research Foundation (ESRF) and the Ministry of Agriculture, Food Security and Cooperatives (MAFC). This year, this part focuses on a detailed analysis of the maize markets in the URT, considering the impact of trade restrictive measures, which have been common in the last decade. It aims to provide additional arguments for supporting the liberalization efforts currently under way in the URT. The general conclusion summarizes the main results and findings from application of the methodology and analysis, and offers recommendations for enhanced policy dialogue. The concluding paragraph highlights lessons learned from implementing the first phase of the MAFAP project in the URT in terms of strengths, weaknesses, opportunities and challenges for the sustainability of periodic monitoring and analysis of agricultural and food policies. 24 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Part 1. CONTEXT OF FOOD SECURITY AND AGRICULTURAL POLICIES This section presents and analyses the DPIs common to all countries covered by the MAFAP project. The decision to use a common group of indicators aimed to facilitate comparisons between countries and to identify developments within individual countries over time (Table 1). 1. United Republic of Tanzania in brief The economy of the United Republic of Tanzania (URT) is predominantly rural-based, with relatively low levels of manufacturing and value addition of the commodities produced. The weight of the agriculture sector in total gross domestic product (GDP) (Figure 1) decreased from 50 percent in 2000 to 28 percent in 2010, and is forecast to decline further to 18 percent by 2025 (Government of the URT, 2010a). However, the sector’s role in providing employment is forecast to remain close to 50 percent until 2025. During the period 2001–2012, growth of the economy averaged 6.6 percent, with peaks of 7.8 percent in 2004/05 and 7.4 percent in 2008/09 (Figure 2). The services and industry sectors exhibited stronger growth rates compared with agriculture, whose growth averaged 4.2 percent per annum, with a high of 5.9 percent in 2003/04 and a low of 3.1 percent in 2002/03. Figure 1: Contribution of different economic sectors to GDP in the United Republic of Tanzania, 2000 to 2025 (p) = projection. Source: Government of the URT, 201 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2000 2010 2015(p) 2020(p) 2025(p) Agriculture Industry Manufacture Services Monitoring African Food and Agricultural Policies (MAFAP) 25 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 2: Aggregate economic (GDP) growth by sector in the United Republic of Tanzania, 2000 to 2011 Source: Government of URT, 2009a. Over the last decade, the URT’s economy has been resilient to shocks such as the financial crisis of 2008, and is expected to remain buoyant, with GDP forecast to grow by 6.8 percent in 2012 and 7.1 percent in 2013 – well above the regional averages (OECD/ADB, 2012). Services, industry and construction continue to be the driving forces. Exports – which received a boost during the crisis, as demand for gold in world markets continued to rise – are expected to perform well, with growth forecast at 10.9 percent in 2012 and 9.7 percent in 2013 (OECD/ADB, 2012). The URT continues to consolidate gains from rigorous trade reforms that began in the 1990s and resulted in a more liberalized trade regime. Restrictions on imports have been removed, except for those that are necessary for health or security reasons; export and import procedures have been simplified; and the State monopoly on the export of traditional cash crops has ended. Internal trade restrictions have also been removed, and price controls have been eliminated on most products apart from oil. Trade with non-Western economic partners, particularly China, continues to grow. The URT is a member country of both the East African Community (EAC) and the Southern African Development Community (SADC). It is implementing the EAC Common Market Protocol, which became operational in July 2010; is involved in negotiations on EAC monetary union; and plays an important role in the establishment of a common market for SADC Member States. The Bank of Tanzania (BOT) continues to implement monetary policy in support of the government’s macroeconomic objective of maintaining single-digit inflation. However, inflation rose from 6.5 percent in 2010 to 12.7 percent in 2011, driven mainly by food and fuel prices; the rate recorded in 2011 was the highest for a decade (OECD/ADB, 2012). In pursuit of monetary policy objectives, BOT has deployed a mix of instruments, including the sale of government securities, foreign exchange operations, repurchase agreements and stand-by facilities. Monetary policy performance appeared to be on track (as of December 2011) (OECD/ADB, 2012). Food inflation in particular increased consistently throughout 2011, surpassing 20 percent by the end of the year as a result of a combination of factors: infrastructure was inadequate to enable regions 0 2 4 6 8 10 12 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Percentage National Agricultural Industry Services 26 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report generating food surpluses to supply those suffering from food shortages; rising fuel prices pushed up transport costs; and food shortages in neighbouring countries increased the demand in domestic food markets, while depreciation of the Tanzanian shilling, coupled with rising global prices for fuel and other inputs, led to imported inflation. To keep inflation in check, the government decided to remove a number of fuel taxes and levies in the 2011/12 budget (approved in June) – this move should ease pressure on domestic fuel prices (OECD/ADB, 2012). During much of 2011, the government was under growing pressure as economic hardship, corruption allegations and calls for constitutional reform continued to dominate national politics, and there have been threats of organized nationwide demonstrations for change (OECD/ADB 2012). Monitoring African Food and Agricultural Policies (MAFAP) 27 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 1: Development and performance indicators (DPIs) in the United Republic of Tanzania Domain No. Indicator Latest available statistics for the United Republic of Tanzania Reference for Africa Reference for the world 1. Macroeconomic performance DPI 1 Share of agricultural value added/GDP (WBI) 28% (2011) 13.29% (2009) (sub- Saharan Africa) (WDI) 2.76% (2009) (WDI) DPI 2 Growth rate of agricultural GDP (WBI) 7% (2010) 4.35% (2010) (sub- Saharan Africa) 2.74% (2010) 2. Performance of the agriculture and rural sector DPI 3 Share of agricultural/total land area (WDI) 40% (2009) DPI 4 Share of agricultural/total exports, in value (FAOSTAT) 9% (2009) 8.78% (2009) 7.56% (2009) DPI 5 Share of agricultural/total imports, in value (FAOSTAT) 34% (2009) 13.08% (2009) 7.75% (2009) DPI 6 Share of small farms, < 5 ha (MAFC) 90% of the country’s food (2010) 3. Input market and constraints for sector development and performance DPI 7 Fertilizer use, kg/ha of arable land (WDI) 8.7 (2009) 10.46 (2009) (sub- Saharan Africa) 122.13 (2009) DPI 8 Share of farms with a tractor; tractors/100 km2 of arable land (World Bank Report) (General Census of Agriculture 2004) 23.3% (2002) DPI 9 Average doing business index score for the extent of credit information, and average legal rights index score (WBI) 0 out of 6 credit index 7 out of 10 legal rights (2012) n.a. n.a. DPI 10 Share of paved roads/total road network (WBI) 8.7% (2009) 18.3% (2004) (sub- Saharan Africa) 45.02% (2004) 4. Environment and agriculture DPI 11 Share of grassland/total area (FAOSTAT) 27% 30.62% (2009) 25.81% (2009) DPI 12 Deforestation rate (FAO FRA) -1.16% (2005–2010) 0.5% (2005–2010) 0.14% (2005–2010) 5. Demography DPI 13 Average population growth rate (WBI) 3.02% (2011) 2.5% (2011) (sub- Saharan Africa) (WDI) 1.15% (2011) (WDI) DPI 14 Birth and mortality rates (WHO) Births: 41.2/1 000; mortalities: 12.09/1 000 (2011) Births: 37.44/1 000; mortalities 12.55/1 000 (2010) Births: 19.59/1 000; mortalities; 8.18/1 000 (2010) DPI 15 Fertility rate (WDI) 5.53 births/woman (2011) 4.94 births/woman (2010) 2.46 births/woman (2010) 6. Poverty, inequality and employment DPI 16 Share of population living below the poverty line, < US$1.25 PPP per day (WBI) 68% (2007) 47.5% (sub-Saharan Africa) n.a. DPI 17 Per capita gross national income (constant $PPP 2005) (UNDP) US$1 237 (2009) US$1 966 (2011) (sub- Saharan Africa) US$10 082 (2011) 28 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report DPI 18 Gini coefficient (UNDP) 37.6 (2007) DPI 19 Unemployment rate (NBS) 10.7% (2012) 7. Migration and urbanization trends DPI 20 Share of rural population to the total population (WDI) 73% (2012) 62.6% (2010) (sub- Saharan Africa) 49.3% (2010) DPI 21 Growth of urban population (WDI) 4.7% (2011) 3.87% (2010) (sub- Saharan Africa) 2.00% (2010) DPI 22 Net migration rate (UNPD) -0.53% (2011) -0.7 (2005–2010) n.a. 8. Food security and socio-sanitary conditions DPI 23 Human Development Index (UNDP) 0.466 (2011) 0.463 (2011) (sub- Saharan Africa) 0.682 (2011) DPI 24 Rates of child mortality (WHO) 107.9/1 000 (2009) 129 (2009) 58 (2009) DPI 25 Rate of assisted births (WHO) 48.9% (2010) 47.7% (2005–2009) (sub-Saharan Africa) 76.4% (2005–2009) DPI 26 Prevalence of undernutrition (FAO) 38.8% (2010-2012) 26.8% (2010-2012) 12.5% (2010-2012) 9. Education and gender DPI 27 Gross enrolment rate in primary school (WBI) 102.2% (2010) 99.86% (2009) (sub- Saharan Africa) 107.11% (2009) DPI 28 Adult literacy rate (WBI) 73.2% (2010) 61.6% (2005–2010) 80.9% (2005–2010) DPI 29 Index of gender inequality (UNDP) 0.590 (2011) 0.610 (2011) 0.492 (2011) DPI 30 Economic activity rate of women (UNDP) 86% (2006) Women: 62.9%; men: 81.2% (2009) Women: 51.5%; men: 78.0% (2009) FAO = Food and Agriculture Organization of the UN FRA = Global Forest Resources Assessment. UNDP = United Nations Development Programme. WBI = World Bank Indicators. WDI = World Development Indicators. WHO = World Health Organization. Monitoring African Food and Agricultural Policies (MAFAP) 29 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 2. Geographical context The United Republic of Tanzania is located in the eastern part of Africa between longitude 290 and 410 east and latitude 10 and 120 south. It borders the Indian Ocean to the east, Uganda and Kenya to the north, Burundi, Rwanda and the Democratic Republic of Congo to the west, and Mozambique, Zambia and Malawi to the south. Its total land area is 945 087 km2. Agricultural land accounts for about 40.1 percent of the total land area (Government of the URT, 2008). Figure 3: Map of the United Republic of Tanzania Source: www.ezilon.com The climate of the URT is defined by its topography of inland lakes, its vegetation types and its proximity to the Indian Ocean (Devisscher, 2010). The diversity of topographical and other factors means that average rainfall varies between 200 to 2 000 mm per annum. Most of the country receives less than 1 000 mm, except the highlands and parts of the extreme south and west, where 1 400 to 2 000 mm can be expected. In the central arid areas, average rainfall is 200 to 600 mm (FAO, Monitoring African Food and Agricultural Policies (MAFAP) 31 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 2006). Wet season rainfall averages 50 to 200 mm per month, but differs among regions and reaches about 300 mm per month in the wettest parts (Vice President’s Office, 2007). Table 2 shows the seasons in the main zones. Table 2: Seasons in the United Republic of Tanzania Months Wind direction Season Zone North Central South December to March Northeast Kasaki Dry Dry Wet March to May Variable Masika Wet Wet Wet June to September Southeast Kusi Dry Dry Dry October to November Northeast Vuli Wet Wet Wet Source: FAO, 2006 The great range of altitudes for agriculture means great diversity of cropping systems, from coconut groves on the coast to cool-area crops such as pyrethrum and wheat elsewhere. The URT can be classified into five zones (FAO, 2006): [1] Afro-alpine, with 1 percent of total area: Afro-alpine moorland and grassland or barren land above the forest line; of limited use and potential except as water catchment and for tourism. [2] Humid to dry sub-humid, with 9 percent of total area: Forest-derived grasslands and bush with potential for forestry or intensive agriculture, including pyrethrum, coffee and tea; natural grassland responds to intensive management and less than 1 ha can support one stock unit. [3] Dry sub-humid to semi-arid, with 30 percent of total area: Variable cover of moist woodland, bush or savannah without potential for forestry – trees are mostly Brachystegia or Combretum; high agricultural potential with large areas under extensive grazing of less than 2 ha per stock unit; regular burning may be necessary. [4] Semi-arid, with 30 percent of total area: Marginal potential for crops, limited to sisal or quick-maturing cereals; natural vegetation of Acacia-Themeda association, but also including dry Brachystegia woodland; potentially productive grazing of less than 4 ha per stock unit, limited by bush encroachment, leached soils, inadequate water and tsetse fly infestation. [5] Arid, with 30 percent of total area: Unsuitable for agriculture, except in parts with fertile soils and run-on rainfall; pastures typically dominated by Commiphora, Acacia and perennial grasses such as Cenchrus ciliaris and Chloris spp.; more than 4 ha per stock unit, and wildlife is important; burning requires care but can be highly effective for bush control. Administratively, the Tanzanian mainland is divided into 26 regions (Figure 3), with more than 130 administrative councils (municipal, town and district). Each district is subdivided into divisions, wards, villages and hamlets (Vitongoji/Mitaa). Each region is headed politically by a Regional Commissioner, while districts each have a District Commissioner. The head of the civil service at the regional level is the Regional Administrative Secretary, while districts have District Administrative Secretaries. The 32 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report regional administration aims to offer a multi-skilled technical resource to support local development initiatives in exploiting locally identified opportunities, and linking central government ministries, departments and agencies and development partners to local government authorities (LGAs). Monitoring African Food and Agricultural Policies (MAFAP) 33 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 3. Socio-economic aspects Population The United Republic of Tanzania has undertaken four population and housing censuses since achieving independence in 1961. The first census, conducted in 1967, reported a total population of 12.3 million; in the 2002 census, this figure had almost tripled to 34.4 million (Figure 4). Figure 4: Evolution of total population in the United Republic of Tanzania, 1967 to 2012 Sources: NBS, various years. The projection for the total population of the URT in 2012 is 45 million. The country is still sparsely populated, with high and increasing density in small areas (urban areas around Lake Victoria and in the Southern Highlands). In 1967, the average population density was 14 people/km2; this figure had increased significantly to 39 people/km2 in 2002 and is projected to reach 47 people/km2 in 2012. This population growth results from high fertility rates and declining mortality levels. The population of the URT remains predominantly rural despite an increase in the proportion of urban residents over time, from 6 percent in 1967 to 23 percent in 2002; the 2012 projection is 26 percent (NBS, 2010). Life expectancy at birth increased from 42 years in 1967 to 51 years in 2002, and is currently projected at 58 years. This increase can be explained by improvements in health and the global standard of living in the country, which have reduced infant and maternal mortality rates. Analysis of the data gathered for the 2012 census will provide updated figures for most of these population data, including current demographic and population dynamics data. Poverty, inequality and employment Between 2001 and 2007, the incidence of income poverty did not change significantly despite the sustained GDP growth rate of more than 6 percent for the whole of the first decade of this century (Government of the URT, 2010b). Table 3 presents the incidence of poverty in mainland United Republic of Tanzania between 2001 and 2007, showing that 36 percent of Tanzanians were poor in 2001 compared with 34 percent in 2007 – a decline of only 2 percent. Income poverty (basic needs 0 5 10 15 20 25 30 35 40 45 50 1967 1978 1988 2002 2012 Million inhabitants Monitoring African Food and Agricultural Policies (MAFAP) 35 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report and food poverty) varied among geographical areas, with rural areas containing 83.4 percent of the poor in 2007 compared with 87 percent in 2000/01; households engaging in farming, livestock keeping, fishing and forestry are the poorest. The change in rural per capita income was small because annual rural growth (using growth of the agriculture sector as a proxy) was about 4.5 percent, while national population growth was 2.9 percent. Table 3: Incidence of poverty in mainland United Republic of Tanzania: headcount poverty index, 2001 and 2007 (percentages) Year Dar es Salaam Other urban areas Rural areas Mainland United Republic of Tanzania Food poverty 2001 7.5 13.2 20.4 18.7 2007 7.4 12.9 18.4 16.6 Basic needs 2001 17.6 25.8 38.7 35.7 2007 16.4 24.1 37.6 33.6 Source: NBS, 2007. Based on National Panel Surveys undertaken in the URT in 2008/2009 and 2010/2011, the Gini coefficient for income distribution inequality evolved from 0.36 to 0.37 (Table 4), which means that the level of income inequality remained constant over the 2008–2011 period. Inequality is higher in urban than rural areas. Dar es Salaam and other urban areas in mainland URT have higher inequality, while rural areas in mainland URT and Zanzibar display lower inequality. Table 4: Gini coefficient for the United Republic of Tanzania, 2008/2009 (NPS1) and 2010/2011 (NPS2) NPS1 NPS2 United Republic of Tanzania 0.36 0.37 Rural 0.31 0.31 Urban 0.37 0.36 Mainland 0.36 0.37 Dar es Salaam 0.34 0.33 Other Urban 0.35 0.35 Rural 0.31 0.31 Zanzibar 0.32 0.31 NPS = National Panel Survey. Source: NBS, 2012. Although the annual jobs created – about 630 000 – match the labour force growth in the country, unemployment remains a priority issue, particularly because most employment creation has been in small informal businesses, which typically have low earnings and productivity (Government of the URT, 2009b; 2010b). Moreover, the high rates of agricultural employment probably masks high levels of underemployment. The quality of jobs created is an important factor in explaining the stagnation of poverty levels. According to the Integrated Labour Force Survey (NBS, 2006a), unemployment among youth aged 18 to 34 years is a particular issue and stood at 13.4 percent in 2006. It was higher 36 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report among female youth, at about 15.4 percent, compared with 14.3 percent for male youth. Generally, the unemployment rate is higher among females than males, except in rural areas. Migration and urbanization Net urban migration accounted for only 0.6 percent of the urban population in mainland United Republic of Tanzania in 2002. However, this low net migration rate conceals a much higher turnover, with almost 389 000 individuals moving to or from urban areas, accounting for about 5.3 percent of the urban population in mainland URT. Another 2.6 percent of the urban population moved among urban centres. Although urban-to-urban migratory flows do not result in an increase or change in the composition of the urban population as a whole, they signal a high level of geographic mobility within the urban space (World Bank, 2008). Urbanization gives a powerful impetus to the break-up of traditional social structures and leads to readjustments in ways of life and forms of social organization to harmonize with modern requirements. Rapid urbanization leads to unplanned and unsurveyed settlement and the deterioration of social and other services. The rapid growth of cities and towns puts ever-increasing pressure on the urban infrastructure of the URT (transport, housing, water and sanitation, and energy). Table 5 presents figures from the 2002 Population and Housing Census showing the percentage distribution of people living in rural and urban areas in 2002. According to the data, 77.4 percent of people lived in rural areas. Except for Dar es Salam and Arusha, all regions reported less than 30 percent of their populations living in urban areas. Monitoring African Food and Agricultural Policies (MAFAP) 37 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 5: Regional distribution of population between rural and urban areas in mainland United Republic of Tanzania, 2002 Region Population Percentage Total Rural Urban Rural Urban United Republic of Tanzania 33 461 849 25 907 011 7 554 838 77.4 22.6 Dodoma 1 692 025 1 478 782 213 243 87.4 12.6 Arusha 1 288 088 884 491 403 597 68.7 31.3 Kilimanjaro 1 376 702 1 088 611 288 091 79.1 20.9 Tanga 1 636 280 1 335 084 301 196 81.6 18.4 Morogoro 1 753 362 1 279 513 473 849 73.0 27.0 Pwani 885 017 698 156 186 861 78.9 21.1 Dar es Salaam 2 487 288 151 233 2 336 055 6.1 93 9 Linidi 787 624 661 228 126 396 84.0 16.0 Mtwara 1 124 481 895 942 228 539 79.7 20.3 Ruvuma 1 113 715 944 045 169 670 84.8 15.2 Iringa 1 490 892 1 234 560 256 332 82.8 17.2 Mbeya 2 063 328 1 642 183 421 145 79.6 20.4 Singida 1 086 748 938 081 148 667 86.3 13.7 Tabora 1 710 465 1 490 581 219 884 87.1 12.9 Rukwa 1 136 354 936 232 200 122 82.4 17.6 Kigoma 1 674 047 1 471 240 202 807 87.9 12.1 Shinyanga 2 796 630 2 540 578 256 052 90.8 9.2 Kagera 2 028 157 1 901 407 126 750 93.8 6.2 Mwanza 2 929 644 2 328 387 601 257 79.5 20.5 Mara 1 373 397 1 109 791 253 606 81.4 18.6 Manyara 1 037 605 896 886 140 719 86.4 13.6 Source: NBS, 2009. Education and gender Cluster II of the National Strategy for Growth and Reduction of Poverty (MKUKUTA), launched in 2005, includes gender-specific education and training goals: equitable access to quality primary and secondary education for boys and girls; universal literacy among men and women; and expansion of higher, technical and vocational education. The United Republic of Tanzania’s literacy rate remains low, at 72.5 percent of the population over 15 years of age in 2007 (Table 6). Table 6: Literacy among population over 15 years in the United Republic of Tanzania, by residence and gender (percentages) 2000/01 2007 Total Dar es Salaam Other urban Rural Total Dar es Salaam Other urban Rural Male 79.6 94.3 91.5 76.1 79.5 94.6 91.5 74.7 Female 64.0 88.3 81.0 58.8 66.1 87.7 80.9 59.5 Total 71.4 91.3 85.8 66.9 72.5 91.0 85.8 66.8 Source: Household Budget Survey 2007 in NBS, 2009. 38 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Literacy rates are much lower among the rural population than among urban residents, and the gender gap is also greater in rural than urban areas. Literacy is especially low among rural women, at 60 percent. Total enrolment across all integrated community-based adult education programmes – providing functional literacy, post-literacy, new curricula and centres for special needs – totals only 1.28 million people. Increases in literacy are likely to be driven by a steady increase in children’s access to schooling. In 2010, well over one-third (37 percent) of children were enrolled in pre-primary education, and the proportion of children starting pre-primary at the requisite age had increased significantly from the early 2000s, owing to intense government promotion programmes. Most children have access to government pre-primary schools, where enrolments rose from 805 000 in 2008 to 851 000 in 2009. Non-governmental provision grew very fast from a low base, but then fell back from more than 68 000 children enrolled in 2008 to 45 000 in 2009 (MEVT, 2009: 2). Introduction of the Primary Education Development Programme in 2001/02 has had a positive impact on primary school enrolment; net primary enrolment increased from 88.5 percent in 2003 to 100 percent in 2006 (Figure 5). Since then, net enrolment has fallen slightly, to 95.4 percent in 2010 (MEVT, 2011). The proportion of girls in total enrolled pupils in government schools decreases throughout the education cycle. In 2009, girls accounted for 44.6 percent of enrolments in Form 1, dropping to 35 percent in Form 6 (MEVT, 2011). These rates were 10 percent higher in private schools for the same year. Figure 5: Net enrolment rates in primary schools in the United Republic of Tanzania, 2003 to 2010 Source: MVET, 2011. Although the trend at the primary school level is towards gender parity in enrolment, with net enrolment rates for boys and girls now being almost equal, gender disparities become visible later on, and a school pre-entry programme for women and girls with lower qualifications has been designed to equilibrate the balance. Affirmative action has led to increased enrolment of female students at the University of Dar es Salaam (UDSM), from 27 percent in 2001/02 to 38 percent in 2005/06. Gender equity among the academic staff remains low however, with women accounting for only 17 percent of UDSM staff and 10 percent of associate professors. 86 88 90 92 94 96 98 100 102 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Percentage Monitoring African Food and Agricultural Policies (MAFAP) 39 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Food security and health The main health and nutrition challenges faced by the United Republic of Tanzania are related to undernourishment rather than overnutrition, with high rates of protein-energy deficiency, iron- deficiency anaemia, iodine deficiency disorders and vitamin A deficiency (Figure 6). These conditions affect in particular children under five years of age, and pregnant women. Nutrient excess disorders affecting the country are fluorosis in northern, northwestern and central parts of mainland URT, and increasing incidences of overweight, obesity and diet-related non- communicable diseases, especially among the urban elite and business sections of the community as they emulate unhealthy food habits and life styles of Western culture (TFNC, 1993). According to the 1999 Tanzania Reproductive and Child Health Survey (NBS, 2000), 5 percent of children under five were wasted, 44 percent were stunted and 29 percent were underweight. A national survey on vitamin A conducted in 1997 showed that 24.2 percent of children under five were vitamin-A deficient (Government of the URT, 2010a). Figure 6: Main health and nutrition problems in the United Republic of Tanzania, 2010 Source: NBS, 2010. Studies indicate that malnutrition results directly from inadequate dietary intake and infectious diseases caused by food insecurity at the household, village, community and national levels. In the URT, food insecurity is mainly caused by problems related to food production, harvesting, preservation, processing, distribution, preparation and use. Other factors may include inadequate maternal and child care, poor access to health services, and an unhealthy environment. Lack of knowledge and poverty are at the root of all these problems because of their direct impact on the capacity of individuals, households and communities to meet their needs for health, nutrition and a prolonged life (Government of the URT, 1992). Nutrition indicators for children under five have shown some signs of improvement in recent years. Stunting, underweight and wasting rates among children aged 0 to 59 months declined from 44, 29.5 and 5.3 percent respectively in 1999, to 42, 16 and 3.8 percent in 2010 (Table 7). Anaemia was also 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Stunting Anaemia (children under 2) Anaemia (children under 5) Anaemia (women of reproductive age) Normal Mild public health problem Moderate public health problem Severe public health problem Prevalence in Tanzania 40 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report highly prevalent among under-fives, with 72 percent of all children aged 6 to 59 months. The main causes of anaemia are nutrition deficiency, intestinal worms and malaria (Government of the URT, 2010b). Table 7: Indicators of child malnutrition in the United Republic of Tanzania, 1999, 2005 and 2010 Year Stunting (height-for-age below 2 SD) Underweight (weight-for- age below 2 SD) Wasting (weight-for- height below 2 SD) 1999 44.0% 29.5% 5.3% 2005 38.0% 21.9% 3.7% 2010 42.0% 16% 3.8% Source: Government of the URT, 2010b. The 2010 Tanzania Demographic and Health Survey also indicated that the nutrition status of adolescent girls and women is still alarming (NBS, 2010). About one-third of women aged 15 to 49 years were iron-, vitamin A- and iodine-deficient, two-thirds were anaemic, and one-tenth were undernourished; data for overnutrition are not available (Table 8). Table 8: Health challenges for children and women in the United Republic of Tanzania, 2010 Children under 5 years % Women % Stunting 42 Low body mass index 11 Underweight 16 Iodine deficiency 36 Anaemia 72 Anaemia 40 Iron deficiency 35 Iron deficiency 30 Vitamin A deficiency 33 Vitamin A deficiency 37 Source: NBS, 2010. The URT is making great strides in reducing maternal and child mortality, but has demonstrated slower progress in reducing neonatal deaths. Each year, 51 000 newborns die, placing the URT among the top five countries in sub-Saharan Africa for newborn deaths. These deaths represent 29 percent of all child deaths in the URT. Maternal health is a key component of the National Package of Essential Reproductive and Child Health Interventions, which focuses on improving the quality of life for women and children (Government of URT, 2008). In spite of the good coverage of health facilities, not all the services are provided to scale, and maternal, newborn and child mortalities remain a major public health challenge in the URT (NBS, 2010). In addition to the immense burden of neonatal death, between 8 000 and 13 000 Tanzanian women die each year because of pregnancy-related causes – an average of 24 women a day. The use of diverse methodologies makes it difficult to determine trends in maternal mortality accurately, but the URT clearly remains among the ten countries with the most maternal deaths in Africa (NBS, 2010). Monitoring African Food and Agricultural Policies (MAFAP) 41 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 42 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 4. Macroeconomic performance Between 1993 and 2009, the United Republic of Tanzania radically changed its growth path and sectoral contributions to GDP. After economic growth rates of less than 4 percent until 1996, real growth rates steadily increased until 2008, reaching more than 7 percent, before slowing down to 6 percent in 2009, mainly owing to the effects of the global financial crisis according to recent reports (Figure 7). However, the upward trend returned in 2010, when growth reached 6.8 percent, before experiencing a downwards move to 6.4 percent in 2011, when shortage of rains led to a power crisis in the country in 2010/11. On average, the Tanzanian economy has grown by about 5.5 percent per year for the last 15 years, and by about 7 percent for the last ten years(Government of the URT, 2011b). Figure 7: Annual real GDP growth rates in the United Republic of Tanzania, 1998 to 2010 Source: Author’s calculations based on data from BOT, 2012b. The relatively high growth rate of recent years is the result of economic and financial reforms and prudent monetary and fiscal policies, all of which promoted domestic and foreign investment. However, this achievement may be eroded by the ongoing power crisis in the URT, the current drought, and the oil crisis caused by political instability in the major oil producing countries. Real GDP growth remained buoyant during 2011, despite energy rationing, which affected manufacturing and trade activities. Real GDP grew by 6.4 percent compared with a projected level of 6.0 percent. Most of this GDP growth came from trade and repairs (18.2 percent), transport and communications (13.8 percent), agriculture (12.6 percent), manufacturing (11.8 percent), construction (9.8 percent) and real estate (10.3 percent). Financial intermediation registered a strong growth of 10.7 percent, but its contribution to total GDP growth was only 3.3 percent because of its small size relative to other activities. Growth in financial intermediation was associated with ongoing financial sector reforms and increased competition in the provision of insurance services (BOT, 2012a). The quarterly growth of sectors indicated in Table 9 demonstrates the effects of power rationing, with 2011 quarterly growth estimates lower than those for 2010. Other factors mentioned by local experts include drought which affected the agriculture sector. 4.1 4.8 4.9 6 7.2 6.9 7.8 7.4 6.7 7.1 7.4 6 7 0 1 2 3 4 5 6 7 8 9 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Percentage growth rate Year Growth Rate Linear (Growth Rate) Monitoring African Food and Agricultural Policies (MAFAP) 43 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 9: Quarterly GDP growth in the United Republic of Tanzania, 2006 to 2011 (percentages) Quarter 2006 2007 2008 2009 2010 2011 First 9.8 4.5 7.1 5.6 7.7 5.8 Second 8.9 5.8 7.1 5.6 7.7 6.7 Third 5.7 7.2 8.9 3.8 7.2 6.4 Four 2.9 11.3 6.3 5.7 6.7 6.5 Source: BOT, 2012b. The contributions of the four main economic sectors to GDP do not match Tanzania Development Vision (TDV) 2025 targets (Government of URT, 1999a). The GDP shares of both the industry and manufacture sectors are considered too low to enable transformation to a modern sector through attraction of the rural labour reserve, which currently stands at 75 percent, and scaling up of sector capacity to accommodate the labour freed from agriculture (Table 10). Table 10: Planned sectoral contributions to GDP for the medium and long terms in the United Republic of Tanzania, 2010 to 2025 Sector Baseline Current status Targets 2000 2010 2015 2020 2025 Agriculture (% of GDP) 50.0 28.0 24.0 21.0 18.0 Industry (% of GDP) 10.0 12.0 16.0 19.0 22.0 Manufacture (% of GDP) 8.0 10.0 14.0 15.0 17.0 Services (% of GDP) 45.0 48.0 46.0 45.0 43.0 Employment in agriculture (% of total) 74.6 74.6 65.0 55.0 41.2 Source: Government of the URT, 20111b. For the service sector, the TDV 2025 review recommends that the GDP share improves for the first five years (2011 to 2015), and thereafter declines slightly (Government of the URT, 2011b). According to the rationale behind TDV 2025, improvements in agricultural productivity will trigger some labour force shedding from the sector, most of which is expected to be absorbed by an expanding industrial sector. Performance of agricultural and rural development About 75 percent of the population of the United Republic of Tanzania is still employed in agriculture, where the level of productivity is among the lowest in sub-Saharan Africa. This low productivity is mostly the result of overreliance on unpredictable natural precipitation, the use of manual labour in land preparation, very low usage of improved seeds and fertilizer, small farm size, and low productivity of indigenous animal breeds. From 1998 to 2009, agriculture grew by about 4.2 percent per year, contributing about a quarter of national GDP and about 34 percent of foreign exchange earnings. 44 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Over the period 1998–2009, the growth rate of the agriculture sector fluctuated from 0.8 percent in 1998 to 5.9 percent in 2004 (Figure 8), while GDP growth fluctuated from 4.1 percent in 1998 to 7.8 percent in 2004. The agriculture sector has persistently registered a lower growth rate than the industry and service sectors. While agriculture grew by an average of 4 percent between 1998 and 2009, the industry and service sectors grew by averages of 8.3 and 7 percent respectively during the same period. Figure 8: Growth rates of total GDP and agriculture in the United Republic of Tanzania, 1998 to 2009 Source: BOT, 2012b. To a large extent, the GDP growth rate has been determined by growth rates in the service and industry sectors. From this pattern of economic growth, it is obvious that one of the main reasons why economic growth in the URT has not been associated with poverty reduction, especially in rural areas, is that the agriculture sector has been growing more slowly than other major sectors. Therefore, growth of the agriculture sector does not substantially influence GDP growth, as it did in the 1970s and 1980s, when it contributed about 50 percent of total GDP. In addition to providing informal employment to most rural dwellers, agriculture has high potential for creating formal jobs – through its forward and backward linkages to agroprocessing, consumption and export and its provision of raw materials to industries – and as a market for manufactured goods. The livestock sector can also be leveraged to contribute to jobs and poverty reduction. However, average annual increases in the populations of cattle and of sheep and goats have been declining (Figure 9), with cattle increasing by an average of 1.4 percent and sheep and goats by 1.2 percent; these growth rates are less than half that of the human population. 0 1 2 3 4 5 6 7 8 9 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Percentage Year Agriculture GDP Monitoring African Food and Agricultural Policies (MAFAP) 45 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 9: Growth rates of cattle (red line) and sheep and goat (blue line) populations in the United Republic of Tanzania, 2002 to 2010 Source: MAFC, 2011a. The inflation rate dropped to less than 5 percent during the early 2000s but started to rise gradually in 2005, worsening in 2009 with the onset of the global financial crisis and reaching a record high of 19 percent in mid-2011 (Figure 10). Inflation is one of the major macroeconomic imbalances in the URT. Figure 10: Annual headline, food and non-food inflation in the United Republic of Tanzania, 2009 to 2012 Source: BOT, 2012a. The rise was exacerbated by drought-instigated food shortages in neighbouring countries; electricity supply shortfalls, which increased production costs as producers shifted to using generators; and increases in petroleum prices, which raised the import bill and production costs. The increasing food and overall inflation have affected agriculture by reducing farmers’ access to inputs, land and other basic needs, thus frustrating efforts to reduce poverty. In addition, while the cost of living has been pushed up, the incomes of most farmers have not been increasing commensurately. The relief on 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 2002 2003 2004 2005 2006 2007 2008 2009 2010 Growth 46 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report food price pressure in mid-2011 appears to have been temporary, as the situation failed to stabilize and return to single-digit inflation in 2012. Post-harvest retail prices in mid-2012 were almost double those that prevailed in the same period of 2011. The agriculture sector has persistently registered lower growth than other sectors, thus affecting its contribution to poverty reduction in the country. However, the sector has managed to produce between 5 and 19 percent more than the normal national food requirements for basic cereals and steadily, albeit slowly, reduced the percentage of food insecure and rural poor (Figure 11). Increased food production is also an important element in providing employment opportunities for urban youths in the food away from home sector. This sector is rapidly developing in the main urban centers and is based mainly in the processing and selling of domestically produced food. Figure 11: Trends in the food self-sufficiency ratio and poverty indicators in the United Republic of Tanzania, 2000 to 2010 FSSR = food self-sufficiency ratio. Source: MAFC, 2011b. Input market and major constraints to production One of the major constraints to rural development and agricultural growth is the low productivity of land and labour (Government of the URT, 2011a). Key factors affecting agricultural productivity are: i) low public expenditure on agricultural research and development (R&D); ii) inadequate agricultural financing; iii) poor production techniques; iv) underdeveloped markets, market infrastructure and farm-level value addition; and v) poor rural infrastructure, including rural roads, telecommunications and electricity. Tanzanian farmers only use 9 kg of fertilizer per hectare, compared with an average of 16 kg/ha for SADC countries; Malawi uses 27 kg/ha and China 279 kg/ha. In spite of these low levels of application, however, the Tanzanian market has failed to absorb all the fertilizer stocks supplied by -40% -20% 0% 20% 40% 60% 80% 0 20 40 60 80 100 120 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Change in agricultural growth rate FSSR / Rural poor / Food poor %Change in Agric Growth Rate p.a. FSSR % Rural Poor % Food Poor Monitoring African Food and Agricultural Policies (MAFAP) 47 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report traders, recording surpluses of between 15 and 30 percent during the 2007/8 to 2009/10 seasons. The annual supply of improved seeds is around 12 000 tonnes, or 10 percent of total estimated requirements of 120 000 tonnes per year (MAFC, 2011b). However, even this small supply is not fully absorbed, and 6 percent remains with stockists. These figures indicate that traders release more fertilizer and seed stocks than farmers buy, perhaps because of delayed deliveries of stock, farmers’ unforeseen inability to purchase the stock they order, or overestimation of farmers’ effective demand. More effort is needed to improve seed and fertilizer distribution and ensure that they are sold at affordable prices. There has been a sharp increase in supplies, combined with a narrowing of the gap between supplies and purchases since 2007/08, when the government increased funding for its input voucher system, suggesting that this system has been useful in enhancing input absorption by farmers. Figure 12: Fertilizer use in the United Republic of Tanzania, 2001 to 2010 Source: MAFC, 2011b. In 2009/10, there were more than 15 000 tractors in the country, but only 63 percent were operational. The number of tractors in use during 2010/11 increased by 7 percent, reaching 8 556 compared with 7 998 in 2009/10. Power tillers in use increased from 42 percent in 2009/10 to 66 percent in 2010/11. The annual demand for new tractors is approximately 1 800 units, but fewer than 400 tractors (22.2 percent of demand) are sold. The impact of the trend for increased tractor use has not been assessed, but it has clearly not resulted in reductions in the price of cereals. It is possible that most of the increased machinery use is for non-food commercial crops. The URT has a total of about 7.1 million ha of high- (2.3 million ha) and medium-potential land (4.8 million ha), supported by rivers, lakes, wetlands and aquifers. Of the 2.3 million ha classified as high- potential, only 345 690 ha had improved irrigation infrastructure in 2011, accounting for only 1.2 percent of the total land with irrigation potential (Government of the URT, 2011b). The pace of irrigation development is slow, and even if it were doubled to 40 000 ha/year, it would take 38 years to provide irrigation infrastructure to the available high-potential land (MAFC, 2012). Regarding the 0 50 100 150 200 250 300 350 2001/2 2002/3 2003/4 2004/5 2005/6 2006/7 2007/8 2008/9 2009/10 Thousand tonnes Fertilizer Supply Supplied surplus Consumption 48 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report productivity of irrigated farms, the average paddy yield in irrigated areas is about 2.3 tonnes/ha, compared with about 1.8 tonnes/ha in adjacent non-irrigated areas (IFAD, no date). Environment and agriculture An estimated 55 percent of the land in the United Republic of Tanzania could be used for agriculture, and more than 51 percent for pasture. However, only about 23 percent of the agricultural land is cultivated, and the practice of shifting cultivation causes deforestation and land degradation on pastoral land. Despite the implementation of new land laws during the last decade, most Tanzanians have yet to realize the full potential benefits of the new land laws in terms of increased access to land or improved management of communal land. In both rural and urban areas, most occupancy rights have not been registered, and small landholdings rarely, if ever, can be used as collateral for borrowing or property for commercial investment. Moreover, access to large tracts of land with clear title is a serious problem for investors in commercial agriculture (USAID, no date). Lake Manyara basin, gold mine areas, the Usangu wetlands and the Ngorongoro Conservation Area have been the most affected by inadequate control and poorland management (Government of URT, 1999b). The main cause of these problems is the lack of proper instruments for enforcing legislation, policies, procedures, guidelines and by-laws by the central government and local authorities. The environmental management mandates of central and local institutions are also reported to be very weak, conflicting and confusing, leading to difficulties in enforcing laws and implementing environmental management plans. The URT is one of the few countries in Africa that still has extensive wildlife resources, and protected areas account for about 25 percent of its total land area (Nshala, 1999). Protected areas comprise national parks, game reserves, game-controlled areas and the Ngorongoro Conservation Area. Unfortunately, the communities living around these protected areas do not benefit from the wildlife industry (Government of URT, 1999b); instead they live in uncertain conditions facing persistent attacks and crop destruction by wild animals. This situation has resulted in an antagonistic relationship between the wildlife authorities and local people – with local communities resorting to activities such as poaching to benefit from the wildlife and other natural resources – and is a direct result of the exclusion of local communities from wildlife management. Human activities on land have impacts that include deforestation, soil erosion, overgrazing, degradation of water resources and loss of biodiversity. All of these weaknesses in natural resource use have resulted in land degradation. Poor agricultural practices such as shifting cultivation and the lack of crop rotation, conservation methods, agricultural technology and land husbandry techniques exacerbate the problem. Liviga (1999) contends that the localized effects of overstocking have caused serious degradation in areas such as Shinyanga and Mbulu where livestock units exceed the carrying capacity of land resources. This situation is seen as an indicator of low capacity to enforce the laws, by-laws, procedures and instruments for ensuring sound environmental management systems among the newly decentralized institutions at the local level. Monitoring African Food and Agricultural Policies (MAFAP) 49 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 5. Agricultural policy framework Following two previous visions for achieving independence and socio-economic liberation, the United Republic of Tanzania developed TDV 2025 to guide long-term development. Zanzibar has also developed its own long-term Vision 2020. TDV 2025 aims to achieve high-quality livelihoods, good governance and economic growth, and acknowledges agriculture as the backbone of the economy. It also highlights the role of the private sector in attaining a modernized, commercial, highly productive and profitable agriculture sector. At the national level, there are two medium-term strategies for implementing TDV 2025: the National Strategy for Growth and Reduction of Poverty 2005/6–2009/10 (MKUKUTA I) and 2010/11- 2014/15 (MKUKUTA II); and the Tanzania Five-Year Development Plan (FYDP) 2011/12–2015/16 (Figure 13). Monitoring African Food and Agricultural Policies (MAFAP) 51 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 13: Policy framework for agriculture and food security in the United Republic of Tanzania Mainland URT Zanzibar Long-term Tanzania Development Vision (TDV) 2025 Vision 2020 Medium- term National Strategy for Growth and Reduction of Poverty (MKUKUTA I) 2005/6–2009/10 MKUKUTA II 2010/11–2014/15 Five-Year Development Plan (FYDP) 2011/12–2015/16 Zanzibar Strategy for Growth and Reduction of Poverty Sector-level Private investment framework Agricultural Sector Development Strategy (ASDS) 2001 Kilimo Kwanza (Agriculture First) 2009 Agricultural Transformation Initiative Agricultural Sector Development Programme (ASDP) 2006–2012/13 Agriculture Strategic Plan 2002–2011 (revised in 2004 and 2008) Participatory Agricultural Development and Empowerment Project (PADEP) Agricultural Service Support Programme District Agriculture Sector Investment Project (DASIP) Agricultural Marketing Systems Development Programme (AMSDP) Rural Financial Services Programme (RFSP) Marine and Coastal Environment Management Project (MACEMP) Comprehensi ve Africa Agriculture Development Programme (CAADP) financing mechanism and framework Tanzania Agriculture and Food Security Investment Plan (TAFSIP) 2011/12–2020/21 Source: Author’s elaboration. The MKUKUTA strategy outlines three clusters of activities for TDV 2025: i) growth and reduction of income poverty; ii) social services and well-being; and iii) good governance. The contribution of the agriculture sector focuses on the first cluster – growth and reduction of income poverty – and defines five priority areas for driving growth in agriculture (Table 11). FYDP 2011/12–2015/16 was developed to reflect the global economic crisis and national capacity for managing such shocks. The implementation review of TDV 2025 states that agriculture’s potential 52 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report contribution to national development has not been sufficiently explored (President’s Office, Planning Commission, 2011). Delineating key functions and strategies to generate the momentum for economic growth, the plan considers agriculture as one of five key priority areas for which strategic interventions are needed (Table 11). Table 11: Agriculture sector objectives and targets from national medium-term strategies in the United Republic of Tanzania MKUKUTA I (2005/6–2009/10) MKUKUTA II (2010/11–2014/15) FYDP (2011/12–2015/16) Objectives/ priorities • Increased productivity and profitability • Increased sustainable off-farm income-generating activities • Secured and facilitated marketing of agricultural products • Supportive physical infrastructure • Water and irrigation infrastructure • Financial and extension services; incentives to promote investments, knowledge and information • Value-addition activities (agroprocessing, livestock and fish processing, and mechanization) • Trade/export development services • Expansion/improvement of irrigation agriculture • Availability of scientific production methodologies (research, training, extension services) • Promotion of agroprocessing and value-addition activities • Availability and utilization of modern agricultural inputs and mechanization • Climate-compatible agriculture Selected key targets • Increased agricultural growth from 5% in 2002/03 to 10% by 2010 • Increased growth of livestock subsector from 2.7% in 2000/01 to 9% by 2010 • Increased food crop production from 9 million tonnes in 2003/04 to 12 million tonnes in 2010 • Strategic grain reserve of at least 4 months of national food requirement • Reduced proportion of rural population (men and women) below basic-needs poverty line from 38.6% in 2000/01 to 24% in 2010 • Reduced proportion of rural food- poor (men and women) from 27% in 2000/01 to 14% by 2010 • Increased agricultural growth in real terms from 2.7% in 2009 to 6.0% by 2015 • Increased growth of livestock subsector from 2.3% in 2009 to 4.5% by 2015 • Increased area under irrigation from 370 000 ha in 2009 to 1 million ha by 2015 (irrigation farming supplying 25% of domestic food demand by 2015) • Average agricultural growth at least 6% • Increased growth of overall livestock sector from 2.7% to 5% by 2016 • Increased food self- sufficiency for cereals and legumes from 104% to 120% by 2015 • Increased irrigated area from 330 000 ha to 1 million ha by 2015/16 • Increased agricultural labour productivity from TSh 212 671 to TSh 345 724 by 2015/16 • Increased value addition for local agricultural producers from 30% to 50% by 2015/16 • Increased annual agricultural foreign exchange earnings from US$700 million to US$1 500 million by 2015/16 Source: Authors’ elaboration. The Agricultural Sector Development Strategy (ASDS) was adopted in 2001 to support the realization of TDV 2025 and achieve the sectoral policy objectives of MKUKUTA. The strategic objectives of ASDS are to: i) create an enabling and favourable environment for improving productivity and profitability in the agriculture sector; and ii) increase farm incomes to reduce rural poverty and ensure household food security. To serve these objectives five strategic areas are identified: i) strengthening the institutional framework for agricultural development; ii) creating a favourable environment for commercial Monitoring African Food and Agricultural Policies (MAFAP) 53 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report activities; iii) enhancing public–private roles in strengthening supporting services; iv) facilitating marketing efficiency for inputs and outputs; and v) mainstreaming planning for agricultural development in other sectors. ASDS is the main policy framework for agriculture and is accompanied by a set of subsectoral policies, including (ESRF, 2010): • the Cooperative Development Policy, established in 1997 and reviewed in 2002, to create an enabling environment for cooperatives to operate efficiently in the liberalized economy; • the National Livestock Policy of 2006; • the Agricultural Marketing Policy of 2008; • the National Irrigation Policy of 2010; • the National Agricultural Policy of 2011; • the Horticultural Development Strategy 2012–2021. ASDS is implemented through the Agricultural Sector Development Programme (ASDP), a sector-wide investment programme launched in 2006. The main objective of ASDP is to increase productivity, profitability and farm incomes by: i) facilitating farmers’ access to and use of agricultural knowledge, technologies, marketing systems and infrastructure; and ii) promoting private sector investment in agriculture, based on an improved regulatory and policy environment. ASDP has five key operational components: i) policy, regulatory and institutional arrangements; ii) agricultural services – research, advisory and technical services, and training; iii) public investment; iv) private sector development, market development and agriculture finance; and v) cross-cutting and cross-sectoral issues, such as gender mainstreaming and implementation of land acts. ASDP is implemented at the national level, accounting for 25 percent of its total funds, and the local level, with 75 percent of its funds distributed by LGAs. The national-level component is supported by the agriculture sector lead ministries (ASLM)1 and focuses on agricultural research and extension services; capacity building for food security and nutrition interventions; irrigation development and national-level infrastructure; policy development and planning; and market development and programme coordination. The local-level component leads activities on agricultural services, primarily public and private agricultural extension and LGA-based research, capacity development and empowerment of farmers’ groups, LGAs and the private sector; and investments in local infrastructure and productive activities. The Ministry of Agriculture, Food Security and Cooperatives (MAFC) has drafted a second ASDP for the period 2013–2020. For agricultural investment, Kilimo Kwanza (Agriculture First) – a public–private plan launched in 2009 by the Tanzania National Business Council – aims to achieve a green revolution and boost private sector participation by increasing concessionary lending to agriculture, empowering agricultural cooperatives, creating commodity exchanges, removing market barriers to agricultural 1 The Ministry of Agriculture, Food Security and Cooperatives (MAFC); the Ministry of Livestock and Fisheries Development; the Ministry of Industry, Trade and Marketing; the Ministry of Water and Irrigation; and the Prime Minister’s Office – Regional Administration and Local Government (PMO- RALG). 54 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report commodities, enhancing trade integration, promoting public–private partnerships for investment in agriculture-related infrastructure and agricultural services delivery, improving access to and use of agricultural knowledge and technologies, and accelerating land reform. Several programmes are in line with the government’s increased emphasis on food markets and mainstreaming of agriculture-related interventions across ministries. For instance, to boost financial institutional development under Kilimo Kwanza, the Tanzania Agricultural Development Bank was established, and the Tanzania Investment Bank has helped to increase the budgetary allocation for agriculture by promoting concessionary lending to agriculture. Other measures include strengthening the role of the National Food Reserve Agency (NFRA); calling for the maintenance of food stocks for 6 to 12 months, to ensure market stability; discouraging exports of raw materials; government procurement of local products; encouraging local processing; and input subsidies. Following the URT’s signing of the compact for implementation of the African Union’s Comprehensive Africa Agriculture Development Programme (CAADP) in July 2010, the Tanzania Agriculture and Food Security Investment Plan (TAFSIP) (Government of the URT, 2011b) was launched in November 2011 to achieve the CAADP target of 6 percent annual growth in agricultural GDP. TAFSIP aims to be the financing mechanism and framework for ASDP. Other projects, developed under the ASDP framework include: • the Accelerated Food Security Project (AFSP), supporting the government’s efforts to achieve greater food security by increasing food production and productivity; • the government’s National Agricultural Input Voucher Scheme (NAIVS), providing input subsidies for seeds and fertilizer; • the Participatory Agricultural Development and Empowerment Project (PADEP), providing grants to communities and farmers’ groups for investment in agricultural development project activities focusing primarily on improving soil fertility and land management, adopting sustainable agricultural technologies and increasing efficiency in inputs and outputs marketing; • the Tanzania Social Action Fund of the President’s Office, supporting the implementation of projects related to food security, education, roads, water, health, training and environment; • the Rural Energy Fund, implemented by the Ministry of Energy and Minerals with investments in rural roads from the Ministry of Works; • other smaller projects addressing a wide range of agriculture-related areas such as livestock and fisheries development, mechanization, development of irrigation infrastructure, development of marketing infrastructure, development of agricultural cooperatives, development of agriculture-related small and medium enterprises, development of rural financial services, facilitation of trade, and improvement of food security and nutrition. The latest commitment for agricultural policy in the URT regards the G8 New Alliance for Food Security and Nutrition, which the URT joined in September 2012 to increase private investment in agriculture, achieve sustainable food security and reduce poverty, particularly by accelerating TAFSIP implementation. Monitoring African Food and Agricultural Policies (MAFAP) 55 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The Southern Agricultural Growth Corridor of Tanzania (SAGCOT), initiated in 2010 as an international public–private partnership, also aims to promote private investment, particularly in increasing agricultural productivity and developing commercial agriculture in the Southern Corridor. SAGCOT is expected to deliver major benefits for food security, poverty reduction and resilience to climate change, and could be characterized as an investment mobilization initiative, rather than an agricultural policy framework. SAGCOT’s corridor approach is based on clusters of commercial farms and agribusinesses in areas with high agricultural potential and access to supporting infrastructure. An average farm size of 2 ha is preferred, fostering close cooperation with small-scale farmers. This initiative has received great attention from the development community, and its success in delivering on expectations will be key to extension of the growth corridor approach to other parts of Africa. SAGCOT is seen as an excellent way of promoting food security in Africa and at the global level. Selected agriculture-related laws Numerous laws affect the agriculture sector (Box 1). Since the mid-2000s, the only major changes to the institutional legislative framework that governs or is related to agriculture and investment are some new acts such as the National Public–Private Partnership Policy, the Plant Breeders Act, the Cereals and Other Produce Act and the Fertilizers Act. Box 1: Main agricultural laws in the United Republic of Tanzania Area relevant to agriculture Law(s) Customs EAC Protocol, 2005 EAC Customs Management Act, 2004 Customs Tariff Act, 1976 Excise Tariff Ordinance, Chapter 332 Finance Act, 1999 Services EAC Common Market Protocol, 2010 Taxation Value-Added Tax Act, 1997 Import/export control Import Control Ordinance Export Control Act, Chapter 293 Foreign Exchange Act, 1992 Anti-dumping and Countervailing Measures Act, 2004 Technical barriers to trade Standards Act, 2009 Sanitary and phytosanitary measures Food, Drugs and Cosmetics Act, 2003 Animal Disease Act, 2003 Veterinary Act, 2003 Plant Protection Act, 1997 Investment Mainland Tanzania Investment Act, 1997 Export Processing Zones Act, 2002 (amended in 2006 and 2011) Zanzibar Investment Promotion and Protection Act, 2004 Zanzibar Free Economic Zones Acts, 1992 (amended in April 1997) Agriculture Food Security Act, 1991 Agricultural Products (Control of Movement) Act, 1996 Cashew Nut Industry Act, 2009 Cereals and Other Produce Act, 2009 Meat Industry Act, 2006 Hides, Skins and Leather Trade Act, 2008 Animal Welfare Act, 2008 Livestock Identification, Registration and Traceability Act, 2010 Fisheries Act, 2003 Deep Sea Fishing Authority (Amendment) Act, 2007 Others Land Act, 2001 Source: WTO, 2012 and own elaboration based on data provided by the MAFC Legal Unit. 56 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The overall objective of agricultural and agricultural related laws is to contribute to the overall development of the sector by: a. ensuring the quality of agricultural products, increased productivity and boost farmer income; b. enabling the provision of services to farmers including improved farming techniques, access to inputs and pest and disease control; and c. coordinating the production, marketing and trade of agricultural products. The following sections describe the main characteristics of the different agricultural and agricultural related acts based on the input provided by the Legal Unit at the MAFC. The current Tanzania Land Act came into force in 2001, and it consists of The Land Act No. 4 of 1999, and The Village Land Act No. 5 of 19992. These acts specify three categories of land in Tanzania; Reserved Land: These are conservation areas, for example game and forest reserves, and national parks. This category occupies about 40 per cent of the total land area. Village Land: The Village Land Act recognizes the rights of villages to land held collectively by village residents under customary law. Village land can include communal land and land that has been individualized. Villages have rights to the land that their residents have traditionally used and that are considered within the ambit of village land under customary principles, including grazing land, fallow land and unoccupied land. Villages can demarcate their land, register their rights and obtain certificates evidencing their rights. As of 2009, 10,397 villages were registered, and 753 had obtained certificates (Deinenger and Byerlee, 2011). General Land: It consists of all land which is not Village or Reserved Land. It is important to note that the 1999 Land Acts place overall ownership of all land with the President of the United Republic of Tanzania – as Trustee of the People. Another new development states that “customary land rights of occupancy are legally equivalent to any deemed or granted right of occupancy”. The government is also implementing the Strategic Plan for Implementing the Land Acts (SPILL) which was finished in which contained a 10 year action plan with an overall budget of 300 billion TSh of which 1 percent would come from public funds (Hundsbaek-Pedersen, 2010). SPILL pilot projects are being implemented in several districts to roll out the administration of the new land acts together with awareness campaigning. The projects were funded by the EU (2005-2008) and the World Bank (2006-2010). In addition the government also put in place the Property and Business Formalisation Programme (better known by its Swahili acronym MKURABITA) with the purpose of improving access to credit by the formalisation of property rights. The process of entitlement of land was designed as to allow farmers to be able to use their titles as collateral when asking for credit to banking institutions. This has not been widely achieved due to the limitations on 2 Besides the land acts, numerous laws and policies also influence how land is governed in Tanzania. According to Hundsbaek-Pedersen (2010) these include the Land Use Planning Act (2007); the Investment Act (1997); the Law of Marriage Act (1971) and the Land Acquisition Act (1967). Monitoring African Food and Agricultural Policies (MAFAP) 57 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report transferability and since the withdrawal of the Norwegian financial support the program has lost part of its initial pace (Hundsbaek-Pedersen, 2010). According to USAID (no date) greater efforts to register individual property rights, to apply laws regarding communal grazing lands, forests and natural resource reserves and parks, and to involve local authorities in land and mineral rights decisions could increase transparency of reforms as well as improve tenure security and reduce unsustainable practices. In Tanzania, where land rights are firmly vested with villages, less than 50,000 ha were transferred to investors between January 2004 and June 2009 (Deinenger and Byerlee, 2011). The Food Security Act (1991) amended by the Cereals and Other Products Act (2009) is enforced by the Directorate of Food Security at the MAFC. It includes a mechanism for coordinating the production, provision of information regarding food security and specific procedures to deal with food shortages. The act also foresees the establishment of a Cereasls and Other Products Regulatory Authority which should be in charge of the regulation of international trade in food products. With the modifications included in the Cereals and Other Produce Act (2009) new Board was created and vested with significant powers to intervene in rice and maize markets. The board falls under the supervision of the Crop Development Department at the MAFSC. The new Board is empowered to: i) facilitate research on cereals, ii) facilitate the offer of extension services to growers and dealers, iii) facilitate the development of agricultural input services, iv) disseminate information, including market information, v) promote production, processing and storage, vi) promote appropriate technologies, vii) assist with the formation of farmers organizations. Importantly, the Board is further empowered to carry out commercial operations, to buy and sell cereals, to import and export cereals, to process them, to provide warehousing services, to clean, dry, weigh, grade and package and to perform other commercial functions which the Minister approves which aid the development of trade in cereals. To achieve its ends, the Board may build or purchase equipment and buildings, establish market centres and/or provide training. The Act further creates a set of zone councils whose responsibly it will be to act as a liaison with local farmer groups, develop local market information services and further act as a consultative forum in which local farmers and traders can discuss and resolve their differences. The Act also creates a new regulatory authority—the Cereal and Other Produce Regulatory Authority. The Act empowers this authority to: i) develop and enforce sustainable agronomical standards for products, processing and marketing, ii) ensure fair and competitive trade and set indicative market prices, iii) collect, refine and disseminate data, iv) license persons engaged in marketing and processing cereals, v) register growers, dealers and processors, vi) inspect premises in which cereals are stored and processed, and vii) regulate and control the collection, movement, marketing, transportation, importation and exportation and supply of cereals. These are sweeping powers, which depending on how they are implemented may be used either to enhance private sector investment and development of the maize or rice subsectors, or alternatively, can discourage further private investment and private sector lead development. So far we have found no evidence of the performance of the board, however how it will use the powers assigned to them seem to be one of the key issues for the development of the maize sub-sector in the future (Match Maker Associates, 2010). 58 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The cereal board is still not functioning (May 2012). According to the Department of Food Security at the MAFC it should be act as a private commercial agent in the cereals market (maize, sorghum and rice mainly) substituting individual traders. However it seems that there will be budget allocations for the board in 2012/2013 to allow them start functioning with a target volume of purchases of 150.000 tons. Moreover, the Board has inherited the milling assets of the former National Milling Corporation in Arusha and Iringa. The Seeds Act (2003) regulates the production and trade of all varieties of agricultural seeds including the necessary provisions for quality assurance. The law is implemented by the Crop Development Department at MAFC and the Tanzania Official Seed Certification Institute (TOSCI). It lays down the procedures for dealing with seeds and includes a register of authorized producers and dealers. The Plant Breeders Act (2012) regulates the protection of new varieties of plants in order to promote plant-breeding activities that will stimulate, facilitate and improve agricultural research in the country through grant and regulation of plant breeders’ rights, establishment of a plant breeders’ rights office and entrusting with the office functions of granting plant breeders’ rights. Witjh this law the URT expects to boost the domestic production of hybrid seed which is currently 90 per cent imported. The Fertilizer Act (2009) provides for the regulation and control of the quality of fertilizer, either domestically produced or imported. It establishes the Tanzania Fertilizer Regulatory Authority (TFRA) which is responsible for the coordination of manufacture, trade, distribution, sale and use of fertilizers. Any agent involved in the fertilizer business must be registered at TFRA and dealers must be obtain a license from TFRA. Additional supportive legislation was developed as the Public–Private Partnership Act of 2010, with further implementing regulations developed in June 2011. Also related to fertilizer the Agricultural Input Trust Fund Act (1994) regulates the provision of inputs to farmers by the government. The Tropical Pesticides Research Institute Act (1979) regulates research on pesticides for the purpose of ensuring their quality. The mission of the Institute is to enhance high quality pests and pesticides research, training and services in human, animal, plant and ecosystem hygiene, health and safety in order to contribute to food security and an increase in market access and share of agricultural and natural resource products as an economic incentive for sustainable development. Eight commodities have acts establishing and regulating the commodity specific board. These include cashew nuts, coffee, cotton, pytherym, sugar, tobacco, tea and sisal. The original acts enacted were amended by the overall Cereals and Other Products Act (2009) mentioned above. Each board is established for the purpose of managing the specific industry including production and marketing of the respective crops. Recent policy decisions In recent years, The United Republic of Tanzania has also implemented several policy measures for agricultural development. The most important of these are outlined in the following paragraphs following the typology developed by FAO’s Food and Agricultural Policy Decision Analysis tool (Figure 14). Monitoring African Food and Agricultural Policies (MAFAP) 59 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 14: Food and Agricultural Policy Decision Analysis classification of food and agricultural policies Source: www.fao.org/economic/fapda/fapda-home/policy-classification/en/ Consumer-oriented policies Stock and price control: The Government of the United Republic of Tanzania stabilizes the food supply by purchasing food staples in surplus areas and selling them at subsidized prices in deficit regions. In 2008, the Strategic Grain Reserve, which was affiliated to the Food Security Department at the Ministry of Agriculture and Food Security, became the independent National Food Reserve Agency (NFRA). NFRA operates 90 to 120 buying centres, where maize is directly purchased from farmers or warehouses. Most of these centres are in the surplus areas of the Southern Highlands, but their location is subject to annual change, depending on the quality and quantity of the maize produced. This purchasing system creates incentives for increased production through guaranteed purchases at fixed floor prices that are about 10 percent higher than market prices. Revising the available evidence of interventions by the NFRA we have not been able to identify a clear trend of price stabilization and safety nets interventions. Rather both seems to have been applied even simultaneously. Between July and September 2009, a total of 64 545 tonnes of maize and 272 tonnes of sorghum were purchased through NFRA to maintain stocks, and a total of 84 057 tonnes of maize, including carry-over stock, were distributed to deficit areas. In 2010, NFRA was expected to purchase 73 672 tonnes of maize while 126 915 tones was transferred from the Southern Highlands to drought-affected areas. In 2011, in response to drought-related food shortages, it was decided to continue purchasing food crops, and TSh 17.6 billion was allocated for the purchase of 200 000 tonnes of maize from farmers, starting on 1 August 2011. The competitive price of TSh 350/kg was set to discourage cross-border smuggling. When domestic production is insufficient to meet demand, private companies import maize via tenders, as NFRA has no mandate for importing from markets in other countries. 60 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report By August 2009, 780 000 people had benefited from government grain distributions. In July 2007, reserve grains were released to the market for sale at TSh 50/kg, which was less than the market price. Subsidized food distribution aimed to reach 400 000 people in 2008. As of 28 April 2008, a total of 1 083 tonnes of maize and 193 tonnes of sorghum had been distributed. Following NFRA’s release of portions of its stock in November 2008 and July 2009, to reduce food prices in areas where prices rose sharply, in August 2009 the government announced a policy of maintaining stock levels sufficient for six months to one year of demand, to ensure market stability. This level is in line with the EAC Food Security Action Plan 2010–2015, which proposes food and financial reserves for the regional level and recommends that each member country hold food and feed reserves for at least six months by 2015. Taxation: High taxation, of almost 20 percent of the sale price, has been identified as an obstacle to crop exports. In addition, there are local taxes, which vary by district. Taxes on crops were reduced to a maximum of 5 percent in July 2008. The value-added tax (VAT) rate on coffee was cut from 20 to 18 percent during the fiscal year 2009/10, while VAT exemption on processed locally grown tea and coffee was removed, in line with the rules applied to other processed agricultural products, which are taxable. Currently only unprocessed agricultural products are exempted from VAT. Producer-oriented policies Support to storage and marketing: In 2007, the warehouse receipt system (WRS) was introduced to enable farmers to store their produce in warehouses and sell it when prices are higher. The scheme is implemented through primary cooperatives, farmers’ organizations or savings and credit cooperatives (SACCOs). Participating farmers are paid a percentage of the produce price (50 or 70 percent), from which the prices of inputs for the following season are deducted. After storage and sale at auction by the warehouse manager, the farmer is paid the remaining percentage plus any extra gains (less interest and administration costs). The system has been applied for cashew nuts and rice (WTO, 2012). Producer subsidies: Although general fertilizer subsidies were removed in the early 1990s, as part of liberalization reforms, the United Republic of Tanzania restored subsidies for the transport of fertilizers in 2003/04, and for maize and sorghum seeds in 2005 (WTO, 2012). Then, in response to the food and fertilizer price increases in 2008, the government launched AFSP, which aims to boost food production and productivity in targeted areas, as the URT’s agricultural input intensity is among the lowest in the region. A pilot input subsidy programme was launched in 2008, and was expanded into the National Agricultural Input Voucher Scheme (NAIVS) in 2009. This input voucher scheme was planned with US$300 million over three years, of which US$160 million was financed by the World Bank. The initial design of NAIVS focused on six crops: maize and paddy, supported by the provision of fertilizer and improved seeds; and tea, coffee, cotton and cashew nuts, supported with agrochemicals and seedlings. This initial targeting has since been expanded to cover sorghum, sunflower, cotton, cashew nuts, coffee and tea. There are seven eligibility criteria for NAIVS: i) being a full-time farmer residing in the village; ii) cultivating less than 1 ha of maize or rice; iii) using the subsidized inputs for maize or rice; iv) agreeing to serve as an example of the use of good agricultural practices; v) being willing and able to take part in co-financing; vi) being a female-headed household (priority); and vii) not having used inputs for the past five years (priority). Monitoring African Food and Agricultural Policies (MAFAP) 61 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The vouchers distributed provide a 50 percent subsidy on a 100-kg package of fertilizer (urea for nitrogen, and diammonium phosphate for the nutrient phosphorus pentoxide) and 10 kg of improved maize or rice seeds. The scheme was first introduced in 11 regions in 2008, and expanded to 20 regions in 2009 (FAO, 2012). A total of 737 000 farmers benefited, compared with a target of 700 000, giving a success rate of 105.3 percent. In addition, fertilizers were exempted from VAT in June 2009, and duty on farm-level inputs such as fertilizers, insecticides, pesticides and herbicides had already been removed in July 2008. Under the voucher scheme, in 2009 a total of 7 180 tonnes of improved seed (6 488 tonnes of hybrid maize and 692 tonnes of open-pollinated maize varieties) were distributed in 11 regions. The seeds supplied increased from 10 500 tonnes in 2005 to 16 150 tonnes in 2010, which was still far behind the estimated demand of 120 000 tonnes. Research institutions produced a total of 172.72 tonnes of breeder seeds, including seeds for 39 newly improved crop varieties, and the Agricultural Seed Agency was established to support private sector seed production. In the budget of 2009/10, the government released a financial rescue package for traditional exports, including cotton, to compensate for the losses incurred by agricultural cooperatives and private companies during 2008/09. By the end of December 2009, a total of TSh 19.9 billion of the Tsh 28.6 billion requested by 35 cotton buyers had been disbursed. The government has also provided support to increase mechanization. Mechanization is one of the main approaches to modernization of the agriculture sector, as indicated in medium-term development plans such as MKUKUTA II and FYDP. Through ASDP, 65 tractors, 1 972 power tillers, 1 321 ploughs and 1 908 processing machines have been procured through cost sharing arrangements that require beneficiary farmers to contribute 20 percent of the total costs of acquiring the equipment. District agricultural development programmes supported by LGAs have also benefited farmers through a cost sharing mechanism for the purchase and distribution of 166 power tillers, 49 tractors and 81 ox ploughs. The Medium-Term Budget Plan for 2010/2011 reports that during 2009 a total of 472 tractors, 495 power tillers and 62 194 animal-drawn implements were distributed throughout the URT. In the last quarter of 2009, 75 tractors and 11 power tillers were procured through the Agricultural Inputs Trust Fund (AGITF) credit arrangement, and a total of 355 tractors and 1 344 power tillers were imported. In July 2008, to encourage use of the machinery distributed through these various arrangements, annual motor vehicle licence fees were reduced, with full exemption for tractors used for agricultural purposes. In November of the same year, the government allocated TSh 17.5 billion to subsidize fuel prices. Access to credit: The government has disbursed TSh 22 billion to the Tanzania Investment Bank, to provide an agriculture financing window. By April 2011, TSh 13.8 billion of this total had been distributed to 381 agricultural projects. This loan facility supports the procurement of tractors, small hand-operated power tillers, irrigation equipment, livestock, commercial vehicles and other farm implements such as tractor-trailers and storage equipment. It is to be developed into an agricultural development bank; during the 2010/11 financial year, US$500 million was allocated to establish the Tanzania Agricultural Development Bank. AGITF provides smallholder farmers and agri-input dealers/stockists with loans at concessional rates of 8 percent, to be repaid in seven years; market rates are usually between 15 and 20 percent on 62 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report loans for the purchase of inputs and equipment (DFID, 2011). The loans are provided in collaboration with LGAs and microfinance institutions. In 2009/10, AGITF provided loans worth TSh 7.42 billion. SACCOs and other credit associations have also increased the availability of small loans for farmers. However, the conditions imposed are sometimes too stringent for small-scale farmers. For instance, access to AGITF requires borrowers to present a registration certificate for collateral of land or a house, but the low percentage of land registered and the lack of established property rights hinders or slows banks’ granting of loans. Investments in land and water: The United Republic of Tanzania has a vast estimated area of 29.4 million ha suitable for irrigation, but only 330 000 ha is currently under irrigation. Irrigation is one of the main objectives of ASDP. Following drafting of the National Irrigation Policy and Strategy in 2007, six irrigation schemes were financed in Mombo (Korogwe), Nduguti (Shinyanga Vijijini), Mwamapuli (Igunga), Mwega (Kilosa), Mbuyuni (Mbarali) and Nakahuga (Songea Vijijini), to increase the productivity of rice farming. After these measures, it was estimated that the area under irrigation had increased from 289 245 ha in 2007 to 310 745 ha in June 2009. The mid-term budget review estimated that this had resulted in production increases for paddy rice, from 2 to 5 tonnes/ha, and tomatoes, from 5 to 18 tonnes/ha, in Igomelo irrigation scheme (Mbarali); for maize, from 1.5 to 4 tonnes/ha, in Mombo irrigation scheme (Korogwe); and for onions, from 13 to 26 tonnes/ha, in Mangola irrigation scheme (Karatu). Between June and December 2009, the area under irrigation increased from 310 745 to 322 945 ha. To increase production, it was decided that government-owned land would be utilized for agricultural production from December 2009. By the end of 2009, 753 villages (less than 10 per cent of total registered villages) had been issued with certificates of village land, and 14 017 certificates of customary rights of occupancy had also been issued. In the same year, Lindi Region completed the identification of land for crop farming, livestock farming and other purposes. Tax exemptions and reductions: To reduce production costs, in the 2009/10 financial year, VAT exemptions on farm services such as land preparation, cultivation, planting and harvesting were proposed, in addition to existing VAT exemptions on agricultural implements and fertilizers. In 2010, registered farmers and cooperatives were exempted from VAT on goods and services needed for developing infrastructure such as irrigation canals, feeder roads and storage facilities. To promote investment in the diary subsector and improve the income of individual farmers, in the 2010/11 financial year, the government introduced VAT exemptions on machines and equipment used for the collection, transportation and processing of milk products. In 2009, it announced VAT exemptions on heat-insulated milk cooling tanks and aluminium jerry cans for milk storage and collection in the dairy industry, to improve the quality of milk. Trade-oriented policies Import measures: The United Republic of Tanzania is a member of the EAC and applies the Common External Tariff (CET) (EAC, 2007) on imports from outside the EAC, and reduced or zero tariffs on imports from the other four member countries (Kenya, Uganda, Rwanda and Burundi). It also applies reduced tariffs on some commodities from members of SADC and/or the Common Market for Eastern and Southern Africa (COMESA). Tariffs on the main imported commodities are quite high as Monitoring African Food and Agricultural Policies (MAFAP) 63 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report these are considered sensitive items and are thus included in Schedule 2 of the CET. Table 12 reflects the prevailing tariffs for the main export commodities studied in Part 2 of this report. Table 12: EAC CET rates for imported commodities used in the MAFAP analysis of the United Republic of Tanzania (percentages) Product Tariff regime 2005 2006 2007 2008 2009 2010 Fresh milk and milk powder MFN duties (applied) 60 EAC Kenya 25 20 15 10 5 0 Uganda 0 Maize MFN duties (applied) 50 EAC 0 Rice MFN duties (applied) EAC 0 Sugar Refined MFN 35 EAC 0 Raw MFN EAC 0 MFN = most-favoured nation. Sources: EAC, 2007; WITS, 2012. However, in the face of food shortages, the government has temporarily waived import duties on maize, in accordance with the provisions of the EAC Customs Union Protocol, repeating the waivers adopted in July 2007 and January 2008. Import duties on other cereals were also removed from the beginning of 2008 until June 2008, and again in November 2008. When wheat production did not meet demand, the import tariff on wheat was applied at the rate of 10 percent from July 2009, while the CET remained at 35 percent. Specific and general tariff waivers for sugar were granted during the 2005–2010 period. More details on each tariff waiver is provided in Part 2 in the discussion of incentives and disincentives for individual commodities. Export measures: In 2011, the Government of the United Republic of Tanzania was the only government in east Africa that still banned exports, albeit temporarily (World Bank, 2009). The ban has been imposed and lifted several times during the study period. Part 3 of this report provides a more detailed discussion of the maize export ban and its implications for the URT. As export bans are difficult to enforce in the URT, because of the high rate of informal cross-border trade to neighbouring countries, the government announced that it would focus on expanding irrigated land to 1 million ha by 2015 and that the export ban would be removed once NFRA had built up sufficient stocks. Although the 2 percent levy on crop exports has been abolished, and exports are zero-rated for VAT, an export tax of either 15 percent or US$160/tonne is still applied to cashew nuts, to discourage the export of raw nuts and promote local value addition. Under the amended Export Levy Act of June 2012, export taxes on raw hides and skins were increased from 20 to 90 percent or TSh 900/kg, whichever is higher. These export taxes are designed to encourage local processing and value-added exports (WTO, 2012). 64 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Agriculture sector budget process In early 1980s the Government of the United Republic of Tanzania started to implement economic structural reforms under the Structural Adjustment Programme. As in most other developing countries, these reforms evolved to include political, sectoral and governance spheres. Aiming to boost economic growth, rule of law and economic liberalization, they had an impact on budgetary planning and implementation, thereby necessitating budgetary reforms. The budgetary process is dynamic for coping with resource mobilization, planning and expenditures, and a previous initiative, the Rolling Plan and Forward Budget (RPFB), introduced in 1992/93, sought to strengthen linkages between development planning and the budget process. Although the Ministry of Finance and Economic Affairs (MoF) credits RPFB with introducing multi-year budgeting linked to a macro-fiscal framework, in practice the plan had several limitations and was not a participatory process. Some of these limitations regarded the resource envelope and resource allocations, which were frequently overridden during subsequent preparation of the budget. The budgeting process itself was hampered by the institutional separation of responsibility for planning the development budget (by the Planning Commission) and the recurrent budget (by MoF). Because the Planning Commission led the RPFB exercise, RPFB was perceived as focusing primarily on the development budget and consequently failing to contribute to better prioritization of recurrent pending. The new budgetary process is highly decentralized and uses the Medium-Term Expenditure Framework (MTEF) as a tool for planning and monitoring budget outcomes. The MTEF entails planning for a three-year period. It links the budget process to the Poverty Reduction Strategy (PRS) and is aligned with performance budgeting, with cash management systems making quarterly allocations to the priorities and sectors identified in the PRS. Sectoral strategies focus on priority areas for the financial year, reflecting funding constraints. Mainstreaming of the PRS into the MTEF has facilitated the practice of directing higher expenditure shares towards priority sectors. The sequence of activities in the MTEF process is: formulation of the Budget Guideline Committee; preparation of revenue and expenditure estimates; final preparation of the budget; budget implementation; monitoring and control. MoF coordinates the budget planning cycle. The Annual Finance Act empowers the Minister of Finance to mobilize funds to finance the budget by imposing taxes, levies, fees and charges. The Annual Appropriation Act allows the Minister to draw money from the Consolidated Fund and to allocate or reallocate it to the activities of ministries, regions, councils and government agencies. In the URT, the government financial year runs from 1 July to 30 June. The budgeting cycle usually starts with a review of macroeconomic targets, setting revenue and expenditure ceilings. This phase is facilitated by the Budget Guideline Committee, which issues an annual budget guideline. The committee is composed of officers from the Ministries of Finance and Economic Affairs, the President’s Office – Planning Commission, the Prime Minister’s Office – Regional Administration and Local Government (PMO-RALG) and the President’s Office – Public Service Management. The approved version of the budget guideline is submitted to the Inter-Ministerial Technical Committee. Monitoring African Food and Agricultural Policies (MAFAP) 65 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Based on macroeconomic reviews and other development indicators indicated in the macroeconomic performance review, an overall framework is formulated to guide budget planning. The government sets objectives and budget priorities to be achieved in each of the three years of the MTEF. At this stage, the ministries – including the Ministry of Agriculture – draft their requests for resources from the budget. This allows the wider participation of other stakeholders in the budgetary planning process. At local government levels, citizens participate through the Opportunity and Obstacles for Development mechanism, while the public expenditure review provides an avenue for the participation of development partners, academic institutions, political parties, civil society organizations (CSOs) and community-based organizations (CBOs). The public expenditure review informs MAFC on important areas for increased budget allocations over the next financial year. ASDP is the main framework for agriculture activities, and the government has agreed to spend 10 percent of the national budget on agriculture sector development under the CAADP framework. The programme financing arrangement has five windows: the District Agricultural Development Grant; the District Irrigation Development Fund; the National Irrigation Development Fund; the Agricultural Extension Block Grant; and the Discretionary Capacity Building Grant. ASDF implementation arrangements include institutional as well as financial management arrangements. A multi-donor basket fund for ASDP was initiated in 2006 to support national activities via an agreed expenditure programme for the agriculture sector lead ministries, with district- and village-level activities supported by performance-based grants channelled through PMO-RALG. The government, together with development partners and the World Bank, implements the Local Government Capital Development Grant system, which provides discretionary development funds to local authorities, and will over time become the mechanism through which all development funds are transferred to LGAs. The system’s broad objectives are to enhance the delivery and management capabilities, productive efficiencies and financial sustainability of LGAs, and to improve the accessibility of communities. District Agricultural Development Grants are meant to support participatory and community projects/interventions focusing on agriculture at the decentralized district level. Projects funded by these grants can be community- and/or group-owned and should be informed by Opportunities and Obstacles to Development exercises, which are consultative and involve a wide range of stakeholders, to ensure institutional and gender representation. The interventions funded are expected to contribute to addressing food insecurity by increasing production and productivity, thereby reducing hunger and poverty. They must consider the availability of and access to productive resources (seeds, extension/advice services, agrochemicals, farming implements), infrastructure (irrigation, rural roads, electricity, market structures), value-addition facilities and marketing systems. These issues are among the main motivators for small- and large-scale producers to continue in farming. Grants from central government are released monthly, bimonthly and quarterly, depending on the plans submitted by the LGA concerned. Seventy-five percent of ASDP allocations are transferred to the local level, and the remaining 25 percent is retained at the national level to cover overhead costs and national-level interventions. However, there is a mismatch in the release of funds, with 66 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report investment funds being released during the first quarter of the year while capacity building and extension grants are released later. Of the 75 percent of ASDP funds received by LGAs, at least 80 to 85 percent is expected to support community projects through District Agriculture Development Grants, Agricultural Capacity Building Grants and Agricultural Extension Block Grants. In practice, District Agricultural Development Grants receive more than 65 percent of the total funds, and the other two types of grant share the remaining 35 percent. Recurrent expenditure flows from the government exchequer system into the accounts of the sector ministries and is then spent on activities (World Bank, 2010). Recurrent expenditure for LGAs bypasses the national ministries and is directed to PMO-RALG for release to the districts. Donor finance is deposited in the ASDP basket fund account and then disbursed into the government exchequer system. Development partners make quarterly deposits into the basket fund account. Funds are then allocated to the respective ministries on the basis of conditions, which include the presentation of cash flow forecasts, approved annual work plans and budgets, and satisfactory quarterly financial statements. The release of funds for the first quarter is triggered by presentation of a satisfactory progress report for the previous year’s third quarter and an interim financial report. Subsequent quarterly disbursements are conditional on submission of the previous quarter’s interim financial report and a cash flow forecast for approved work plans. Funds can be drawn from the account by submitting to the Treasury a written approval from the Basket Fund Steering Committee. Transfers of funds from the ASDP basket to counterpart implementing agencies are also subject to approval of the Basket Fund Steering Committee. ASDP funds for LGAs are transferred from the Treasury (once it has obtained funds from the basket fund account) to PMO-RALG, and then through regional offices to the District General Fund account, before reaching the District Agricultural Development Planning accounts, from where funds for community projects at the village level are transferred to the village accounts. For development projects outside the ASDP basket, such as PADEP, AFSP and DASIP, funds are released to the MAFC special project accounts, subject to the submission of cash flow projections in withdrawal applications based on the annual work plan and budget. Monitoring African Food and Agricultural Policies (MAFAP) 67 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Part 2: THE EFFECTS OF AGRICULTURAL AND FOOD POLICIES, PUBLIC EXPENDITURE AND AID To attain their development objectives, governments use policies to change the rules governing the economy as a whole (macroeconomic policy) or the rules governing a particular economic sector (sector policies), to guide and modify the behaviour and decisions of agents operating in the economy. These changes can be brought about by establishing a legal framework (e.g., food quality or safety norms, property rights) to which economic agents must adhere or run the risk of legal prosecution or fines. Another approach is through institutional reform, or providing incentives or disincentives to certain types of behaviour via price and trade policies, input and output marketing policies, social policies (income transfers, safety nets, social security schemes) and finance policies. However, price incentives and disincentives do not arise from explicit policy actions alone; in many cases, markets do not function as they are supposed to because there is no integration among different sub-markets within a country owing to excessive transport costs, there is asymmetry among agents regarding price, or some agents have excessive market power. Incentives measured in this report therefore include the effects of explicit policies, market development gaps and interactions between the two. Public expenditure can be used to make goods and services available to the food and agriculture sector, to support the implementation of government policies and to facilitate the achievement of development objectives. For example, public expenditure may provide public goods through public investment in infrastructure, or private benefits such as subsidies or income transfers. To monitor government actions and to ensure that they are consistent with and contribute to development objectives, it is therefore essential that the authorities be fully informed regarding the incentives or disincentives that the policies they implement may provide to the economy, and regarding the consistency, efficacy and adequacy of the ways in which they spend their public resources. The following are some of the key questions that governments need to consider: Do the policies in place and overall market functioning provide incentives for production, processing and marketing in key food and agricultural value chains, or do they penalize them? In the most strategic value chains, who benefits from the policies in place – producers, processors, traders or consumers? Which policies should be changed so that the incentive structure in the food and agriculture sector comes closer into line with government objectives? Is public expenditure spent in ways that address the key issues faced by the food and agriculture sector? For example, what is the most efficient way to improve farmer incomes – through an input subsidy or investment in a road? Does public investment focus on key investment needs? Are policy incentives and public expenditure coherent or do they sometimes send out contradictory signals to the economy, resulting in wastage of precious public resources? Are public resources spent efficiently, or is an excessive share of them used for administrative costs? Monitoring African Food and Agricultural Policies (MAFAP) 69 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The analysis presented in the report is related primarily to domestic policies. Producers and consumers are also affected by policies in other countries and regions. For example, producers of exported agricultural commodities from Tanzania are penalized by import tariffs in destination countries and producers of imported commodities are penalized by subsidized exports by third countries. In this sense, the fact that the recommendations provided refer to domestic policies does not imply that there is no impact of international policies on incentives and disincentives to Tanzanian farmers and consumers nor that reform is not needed in the international policy arena. Although this report refers to incentives and disincentives in the United Republic of Tanzania (URT), most of the analysis is based on data and information for mainland URT. In the future, specific analyses of relevant commodities, policies and value chain performance in Zanzibar should be carried out. 70 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 6. Incentives, disincentives and market development gaps Box 2 provides a summary of the main results of the analysis regarding incentives, disincentives and market development gaps. Box 2: Summary of results regarding incentives, disincentives and market development gaps in the United Republic of Tanzania Overall, producers in the United Republic of Tanzania have been incentivized during the study period, although the level of incentives has declined. It can therefore be concluded that the policy environment and market performance lead farmers to obtain higher prices than they would in the absence of policies and with well-functioning markets. However, this trend masks a dual situation. Producers of commodities that are imported into the URT are incentivized, while producers of export-oriented commodities are penalized. The results also show that some commodities are protected at the wholesale (processed) level and penalized at the farmgate (raw) level. This duality is also detected in the relative roles of policy and market performance in the incentives and disincentives identified. While most incentives for imported commodities relate to trade policy, disincentives for export commodities relate to both explicit taxes and inefficiencies in the processing industry. In addition, part of the protection for imported goods granted by trade policy is eroded by excessive marketing costs along the value chain. Farmers producing commodities that the URT needs to import to cover domestic consumption are generally incentivized. These incentives are related to the Common External Tariff (CET) that the URT applies to imports from outside the Eastern African Community (EAC). The only exception is sugar, whose producers face strong disincentives. In addition, for all imported commodities, protection levels are eroded towards the farmgate, because of poor market integration and inefficiencies in the value chain. Farmers producing export commodities in the URT are generally disincentivized, meaning that the policy environment and market performance lead them to obtain lower prices than they could in a policy-free environment with better market performance. These disincentives are related to taxation of commodities (cotton, cashew nuts), bad functioning of the value chain (coffee, cashew nuts) and inefficiencies in the processing sector (cotton). Contrary to the producers of classic export crops, pulse producers have positive indicators, meaning that average domestic prices are higher than export-parity prices. While this situation would generally be considered an incentive for producers, in this case it reflects bad functioning of the value chain, where lack of storage facilities means that exporters miss the opportunity of benefiting from higher prices in domestic markets while consumers pay higher prices. For thinly traded products, the incentives and disincentives to maize producing farmers are very volatile. For this commodity, a mix of variable policy decisions (trade restrictions, subsidized sales), and lack of market integration in the URT due to excessive transport costs generate disincentives to farmers. Overall, farmers obtain lower prices than would be attainable in the absence of policy and with better market performance. The general pattern for incentives and disincentives in the URT applies to the producers of commodities that represent a significant share of the Tanzanian diet. From a consumer perspective, these incentives lead to increased food bills, reducing affordability. Thus the results show a conflicting impact on food security. Incentivized farmers are likely to invest more, hence increasing their production, as has been most visible for rice, for which the URT has gone from being an importing country to a net exporter. For other commodities, however, incentives do not seem to have a positive impact on domestic food availability. Monitoring African Food and Agricultural Policies (MAFAP) 71 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Commodity selection For this report, price incentives and disincentives for nine commodities have been analysed. These commodities were selected from a systematic review of agricultural production, agricultural trade and average diet in the United Republic of Tanzania (Barreiro-Hurle, 2011a). The following criteria were used: (i) contribution to food security; (ii) contribution to the food import bill; (iii) contribution to export revenue; (iv) contribution to the value of agricultural production. The Monitoring African Food and Agricultural Policies (project) aims to analyse commodities that represent at least 70 percent of the total value of agricultural production, of agricultural trade and of the diet in the country. Owing to the URT’s diverse agricultural production structure, 12 commodities are needed to reach this threshold. In addition, with the exception of cotton and rice, major imports and exports are not among the most important commodities as their shares of total production are low. The diet in the URT is also quite varied. To satisfy all the selection criteria, an initial list of 19 commodities was proposed. To ensure a set of indicators that allows comparisons across African countries, in each country, the MAFAP project also analyses six agricultural products that represent significant shares of total agricultural production value within Africa as a whole (Barreiro-Hurle, 2011b). No additional commodity had to be added to the URT list, which already included these six commodities. The list of 19 commodities was shortened based on data availability, commercialization level of the commodity, policy interest shown by the Ministry of Agriculture, Food Security and Cooperatives (MAFC), and size of domestic agricultural production. Nine commodities have already been analysed (Table 13), and analysis of another four (tea, cassava, livestock, sorghum/millet) is under way. Special attention will be paid to analysing livestock, for which a policy brief is to be prepared. The nine analysed commodities represent 36 percent of total agricultural production, 47 percent of total agricultural exports, 44 percent of total agricultural imports, and 55 percent of total calorie intake. Table 13 identifies the major commodities that would need to be studied to reach the 70 percent thresholds set by the MAFAP methodology. Additional efforts will be made to include these commodities in future analyses. 72 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 13: Commodities studied and their coverage of agricultural production, agricultural trade and diet in the United Republic of Tanzania, 2005 to 2010 Commodity Share of production value Share of export value Share of import value Share of Kcal intake* Cashew nuts 1.2 6.7 0.0 a0.2 Coffee 0.8 14.1 0.0 0.0 Cow milk 7.3 b 0.0 b 0.6 2.6 Maize c 6.5 0.8 2.9 24.3 Pulses e 10.6 f 7.5 f 0.7 8.5 Rice 5.2 n.d. n.d. 9.1 Cottong 2.9 14.5 0.1 n.a. Sugar h 1.2 1.6 8.6 4.0 Wheat 0.2 1.4 31.4 5.9 Total 35.9 46.6 44.3 54.8 Under study Cassava 8.2 0.0 0.0 10.5 Livestock 12.0 d 0.1 d 0.6 1.6 Sorghum/millet 2.4 0.1 0.2 3.8 Tea 0.5 6.3 0.0 0.0 Additional commodities needed to reach MAFAP thresholds Bananas 12.7 0.0 0.0 4.0 Palm oil 0.0 1.6 27.3 3.3 Tobacco 1.3 17.6 1.1 n.a. * Diet figures from 2009 Food Balance Sheet. n.d. = no data available; n.a. = not applicable. a tree nuts; b including fresh, condensed and evaporated milk; c including green maize; d including cattle, cattle meat, boneless cattle meat, and dried, smoked and salted beef; e including beans, chick peas, cow peas, peas, pigeon peas and pulses nes; f including beans, chick peas, peas and pulses nes; g including cotton lint and cotton seed; h sugar cane. Source: FAOSTAT, 2013. The selected food and agricultural commodities are classified according to their trade status: import, export or non-/thinly traded. A commodity is considered non-traded when less than the equivalent of 2.5 percent of the total volume of its domestic production is traded (internationally); commodities that reach this 2.5 threshold are considered “exports” or “imports” depending on whether the country is a net exporter or a net importer. This report presents the commodities selected in each category, along with an aggregated list of commodities for analysis of incentives/disincentives. Monitoring African Food and Agricultural Policies (MAFAP) 73 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The nine commodities analysed fall into the four groupings shown in Table 14, which form the basis for the analysis of price incentives in this section. Detailed analyses of seven commodities are available as technical notes from the MAFAP Web site.3 Technical notes for the remaining three commodities and analyses of those listed as under study in Table 13 will be available in the near future. Table 14: Commodity groupings used in the analysis of price incentives and disincentives in the United Republic of Tanzania Imported Exported Thinly traded Food security Dairy Rice Sugar Wheat Cashew nuts Cotton Coffee Pulses Maize Maize Pulses Rice Sugar Wheat Commodities in bold are those for which technical notes are available on the MAFAP Web site. Source: Authors’ elaboration. Highlights of the methodology The MAFAP methodology seeks to measure market price incentives and disincentives to producers and other agents in commodity markets. The analysis is based on comparisons between observed domestic prices and reference prices. Reference prices are calculated using the prices of the product in the international market, which are considered as benchmark prices, free of the influence of domestic policies and markets. The methodology estimates two types of reference price: observed and adjusted. Observed reference prices are those that would prevail in the presence of distortions from national policy measures (except tariffs and other trade measures) and deficiencies in the structure and functioning of domestic value chains; adjusted reference prices are those that would prevail in the absence of these distortions. The analysis is based on the law of one price, which is the economic theory that states there is only one prevailing price for each product in a perfectly competitive market. This law applies only to homogeneous goods, when information is correct – and therefore free – and when transaction costs are zero. Thus, the analysis was conducted for goods that are perfectly homogeneous or perfect substitutes in the local market in terms of quality, or that are simply comparable goods. Indicators calculated from reference and observed domestic prices will therefore reveal whether domestic prices represent support to (incentives) or taxes (disincentives) on various agents in the value chain. Observed domestic prices are compared with reference prices at two specific locations along the commodity value chain – the farmgate and the point of competition, where domestic products compete with identical products at world market prices. The approach for comparing prices at each 3 www.fao.org/mafap 74 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report location is summarized in Figure 15, using an imported commodity as an example. In the situation illustrated in Figure 15, the country is importing a commodity that arrives in the port at benchmark price 𝑃𝑏, which is usually the unit value CIF price at the port of entry. In the domestic market, the price of the same commodity is observed at the point of competition, 𝑃𝑤ℎ (usually the observed price at wholesale), and at the farmgate, 𝑃𝑓𝑔. Analysis also draws on information about observed access costs, which are all the costs associated with bringing the commodity to market, including marketing costs between the border and the point of competition, 𝐴𝐶𝑜𝑤ℎ, and between the farmgate and the point of competition, 𝐴𝐶𝑜𝑓𝑔. As illustrated in Figure 15, the benchmark price can be compared with the observed domestic price at the point of competition by adding the access costs between the border and the point of competition, resulting in the observed reference price at the point of competition, 𝑅𝑃𝑜𝑤ℎ. This takes into account all the costs an importer would need to bear to bring the commodity to market; in effect, these costs raise the price of the commodity. The reference price at the point of competition is made comparable with the observed domestic price at the farmgate by deducting the access costs between the farmgate and the point of competition, resulting in the observed reference price at the farmgate, 𝑅𝑃𝑜𝑓𝑔. This price takes into account all the costs incurred by farmers and other agents in bringing the commodity from the farm to the wholesale market. Mathematically, the equations for calculating the observed reference prices at the point of competition (𝑅𝑃𝑜𝑤ℎ) and the farmgate ൫𝑅𝑃𝑜𝑓𝑔൯ for an imported commodity are as follows: 𝑅𝑃𝑜𝑤ℎ= 𝑃𝑏+ 𝐴𝐶𝑜𝑤ℎ 𝑅𝑃𝑜𝑓𝑔= 𝑅𝑃𝑜𝑤ℎ−𝐴𝐶𝑜𝑓𝑔 where 𝐴𝐶𝑜𝑤ℎ are the observed access costs from the border to the point of competition, including handling costs at the border, transport costs from the border to the wholesale market, profit margins and all observed taxes and levies, except tariffs; and 𝑃𝑏 is the benchmark price. 𝐴𝐶𝑜𝑓𝑔 are the observed access costs from the farmgate to the point of competition, including handling costs at the farm, transport costs from farm to wholesale market, processing costs, profit margins and all observed taxes and levies. Monitoring African Food and Agricultural Policies (MAFAP) 75 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 15: The MAFAP methodology for price incentive and disincentive analysis This graphical representation is for an imported commodity. Source: Authors’ elaboration. The steps illustrated in Figure 15 can be conducted a second time using benchmark prices and access costs that have been adjusted to eliminate market distortions due to exchange rate misalignments, imperfect functioning and non-competitive pricing in international markets and inefficiencies along domestic value chains,4 where possible and relevant. The adjusted benchmark prices and access costs are then used to generate a second set of adjusted reference prices in addition to the first set of observed reference prices calculated. For exported commodities, a slightly different approach is used. In this case, the border is generally considered the point of competition, and the unit value free on board (FOB) price for the commodity is normally taken as the benchmark price. Observed and adjusted reference prices at the point of competition are obtained by subtracting, rather than adding, the access costs between the border and the point of competition. Mathematically, the equations for calculating the observed reference prices at the point of competition (𝑅𝑃𝑜𝑤ℎ) and the farmgate ൫𝑅𝑃𝑜𝑓𝑔൯ for an exported commodity are as follows: 𝑅𝑃𝑜𝑤ℎ= 𝑃𝑏−𝐴𝐶𝑜𝑤ℎ 𝑅𝑃𝑜𝑓𝑔= 𝑅𝑃𝑜𝑤ℎ−𝐴𝐶𝑜𝑓𝑔 After observed and adjusted reference prices are calculated for the commodity, they are subtracted from the domestic price at each point in the value chain to obtain the observed and adjusted price gaps at wholesale and the farmgate. Observed price gaps capture the effect of trade policy measures 4 Inefficiencies along domestic value chains may include government taxes and fees (excluding fees for services), high transportation and processing costs, and high profit margins captured by various marketing agents. Q P(int$) Pb(int$) ACwh RPwh ACfg Q Q S RPfg D S S Pdwh Pdfg Tanzaniawh Tanzaniafg World markets Price gaps 76 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report that directly influence the price of the commodity in domestic markets (e.g., subsidies and tariffs) and actual market performance; adjusted price gaps capture the effects of distortions resulting from market functioning and government policy measures influencing domestic prices. Mathematically, the equations for calculating the observed price gaps at the point of competition (𝑃𝐺𝑜𝑤ℎ) and the farmgate ൫𝑃𝐺𝑜𝑓𝑔൯ are as follows: 𝑃𝐺𝑜𝑤ℎ= 𝑃𝑓𝑔− 𝑅𝑃𝑜𝑓𝑔 𝑃𝐺𝑜𝑓𝑔= 𝑃𝑤ℎ− 𝑅𝑃𝑜𝑤ℎ where 𝑃𝑓𝑔 is the observed domestic price at the farmgate, 𝑅𝑃𝑜𝑓𝑔 is the observed reference price at the farmgate, 𝑃𝑤ℎ is the observed domestic price at wholesale, and RPowh is the observed reference price at wholesale. A positive price gap, resulting when the observed domestic price exceeds the reference price, means that the policy environment and market functioning as a whole generate incentives (support) to producers or wholesalers. For an import, this result could be due to distortions, such as the existence of a tariff or excessive access costs between the border and the point of competition. On the other hand, if the reference price exceeds the observed domestic price, resulting in a negative price gap, it means that the policy environment and market functioning as a whole generate disincentives (taxes) to producers or wholesalers. Again, for an import, this result could be due to distortions, such as subsidized sales by the government to keep domestic prices low. In general, price gaps provide an absolute measure of the market price incentives (or disincentives) that producers and wholesalers face. Therefore, price gaps at wholesale and the farmgate are divided by their corresponding reference price and expressed as a ratio, referred to as the nominal rate of protection (NRP), which can be compared across commodities and countries. The observed NRPs at the farmgate (𝑁𝑅𝑃𝑜𝑓𝑔) and point of competition (𝑁𝑅𝑃𝑜𝑤ℎ) are defined by the following equations: 𝑁𝑅𝑃𝑜𝑓𝑔= 𝑃𝐺𝑜𝑓𝑔 𝑅𝑃𝑜𝑓𝑔 𝑁𝑅𝑃𝑜𝑤ℎ= 𝑃𝐺𝑜𝑤ℎ 𝑅𝑃𝑜𝑤ℎ where 𝑃𝐺𝑜𝑓𝑔 is the observed price gap at the farmgate, 𝑅𝑃𝑜𝑓𝑔 is the observed reference price at the farmgate, 𝑃𝐺𝑜𝑤ℎis the observed price gap at wholesale, and 𝑅𝑃𝑜𝑤ℎ is the observed reference price at wholesale. Similarly, the adjusted NRPs at the farmgate (𝑁𝑅𝑃𝑎𝑓𝑔) and wholesale (𝑁𝑅𝑃𝑎𝑤ℎ) are defined by the following equations: 𝑁𝑅𝑃𝑎𝑓𝑔= 𝑃𝐺𝑎𝑓𝑔 𝑅𝐹𝑎𝑓𝑔 𝑁𝑅𝑃𝑎𝑤ℎ= 𝑃𝐺𝑎𝑤ℎ 𝑅𝐹𝑎𝑤ℎ where 𝑃𝐺𝑎𝑓𝑔 is the adjusted price gap at the farmgate, 𝑅𝑃𝑎𝑓𝑔 is the adjusted reference price at the farmgate, 𝑃𝐺𝑎𝑤ℎis the adjusted price gap at wholesale and 𝑅𝑃𝑎𝑤ℎ is the adjusted reference price at wholesale. Monitoring African Food and Agricultural Policies (MAFAP) 77 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report If public expenditure allocated to any of the commodities analysed is added to the price gaps at the farmgate when calculating the ratios, the nominal rate of assistance (NRA) is generated. This indicator summarizes the incentives (or disincentives) due to policies, market performance and public expenditure and takes the following expression: 𝑁𝑅𝐴= 𝑃𝐺𝑎𝑓𝑔+ 𝑃𝐸𝑐𝑠𝑝 𝑅𝐹𝑎𝑓𝑔 Where PEcsp is commodity-specific public expenditure measured as monetary units per tonne. The MAFAP methodology also estimates the market development gap (MDG), which is the portion of the price gap that can be attributed to excessive or inefficient access costs within a given value chain, exchange rate misalignments, and imperfect functioning of international markets. Excessive access costs may result from such factors as poor infrastructure, high processing costs due to obsolete technology, government taxes and fees (excluding fees for services), high profit margins captured by various marketing agents, illegal bribes and other non-tariff barriers. Therefore, the total MDG at the farmgate has three components: gaps due to excessive access costs, the exchange rate gap, and the international market gap. When added together, these components are equivalent to the difference between the observed and adjusted price gaps at the farmgate. Similar to the other price gaps calculated, the MDG is an absolute measure, which is expressed as a ratio to allow comparisons across commodities and countries. A relative indicator of the total MDG affecting farmers is derived by calculating the ratio between the total MDG at the farmgate and the adjusted reference price at the farmgate, as follows: 𝑀𝐷𝐺𝑓𝑔= (𝐼𝑀𝐺+𝐸𝑅𝑃𝐺+𝐴𝐶𝐺𝑤ℎ+𝐴𝐶𝐺𝑓𝑔) 𝑅𝑃𝑎𝑓𝑔 where IMG is the international market gap, ERPG is the exchange rate gap, ACGwh is the access cost gap at the point of competition (defined as the difference between the observed and adjusted access costs at the point of competition), and ACGfg is the access cost gap at the farmgate (defined as the difference between the observed and adjusted access costs at the farmgate). MAFAP provides indicators (NRPs, NRAs and MDGs) at both the commodity and aggregate levels to create a more general picture. Farm gate-level indicators for commodities are aggregated into relevant product groups to enable the presentation of results for the agriculture sector as a whole or according to the trade status of the products analysed and their importance to food security. Aggregate indicators are calculated as weighted averages based on each commodity’s relative contribution to the total value of agricultural production. Mathematically, the formula for constructing aggregate indicators for product groups is as follows: 𝑁𝑅𝑃𝑔= ∑ 𝑁𝑅𝑃𝑖∗𝑃𝑅𝑂𝐷𝑖 𝑖=𝑛 𝑖=1 ∗𝑅𝑃𝑓𝑔𝑖 ∑ 𝑃𝑅𝑂𝐷𝑖∗𝑅𝑃𝑓𝑔𝑖 𝑖=𝑛 𝑖=1 78 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report where 𝑁𝑅𝑃𝑔 is the aggregated NRP for a subset of n commodities, 𝑁𝑅𝑃𝑖 is the NRP for the commodity, 𝑃𝑅𝑂𝐷𝑖 is the volume of production in tonnes (or any other unit) of the commodity and 𝑅𝑃𝑓𝑔𝑖 is the reference price of the commodity at the farm gate.5 A more detailed description of the methodology applied in this analysis is available on the MAFAP Web site.6 To demonstrate how the methodology has been applied to the analysis of price incentives and disincentives in the United Republic of Tanzania, the following subsections briefly discuss the main options taken for calculating MAFAP indicators for the commodities studied. Marketing channels Because of the lack of reliable representative farmgate prices, the vast size of the United Republic of Tanzania, the lack of homogeneous access costs throughout the country and the evidence of non- integrated markets (Asche, Gjølberg and Guttormsen, 2012), the analysis had to identify a representative marketing route that includes an area (or areas) of production and a point of competition. The area of production selected is the one with the largest share of domestic production for the commodity concerned. The point of competition is the largest market close to the border through which international trade takes place. It is assumed that domestic and imported products are traded at the same price in this market .7 For some commodities (mainly those thinly traded), the selected production area and point of competition change from year to year, depending on the net trade position and the main trade partners. Details of the marketing corridors selected and analysed are available in the technical notes for each of the products studied. The different approaches used are reflected in Table 15. 5 The same formula also applies for aggregated NRAs and MDGs, though 𝑁𝑅𝑃𝑖 would be 𝑁𝑅𝐴𝑖 and 𝑀𝐷𝐺𝑖, respectively. 6 www.fao.org / mafap-documents 7 Taking into account quality and quantity adjustment factors if applicable. Monitoring African Food and Agricultural Policies (MAFAP) 79 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 15: Marketing channel assumptions used in the analysis of price incentives and disincentives in the United Republic of Tanzania Marketing channel Commodities Farmgate: Country average Point of competition: Countrywide auction/wholesale Benchmark: FOB export price at port of departure of goods Cashew nuts Coffee Cotton Farm gate: Area-specific wholesale price Point of competition: Wholesale price at main market close to border Benchmark: CIF import/FOB export price at port of entrance/exit of goods Maize Pulses Rice Wheat Farm gate: Farmgate price of three main processing plants Point of competition: Wholesale price at main market close to border Benchmark: CIF import price at port of entrance of goods Sugar cane Farm gate: No data Point of competition: Wholesale price at main market close to border Benchmark: CIF import price at port of entrance of goods Milk Source: Authors’ elaboration based on commodity-specific technical notes. Observed prices and reference prices Domestic prices: Two domestic prices are needed for the analysis: a farmgate price and a price at the point of competition. As no specific farmgate prices per region are available for most commodities, farmgate prices are approximated using the wholesale prices in the respective areas. This means that the analysis of incentives or disincentives does not take into account the possible impacts of policies and/or performance of markets between regional wholesale markets and the farmgate. These factors normally include transport from the farmgate to the markets and local taxes (cess). The structure of rural transport and the local taxation of agricultural commodity movements in the United Republic of Tanzania decrease the level of incentives (or increase the level of disincentives), so the farmgate estimates should be considered as the upper bounds of incentives and the lower bounds of disincentives. Farmgate prices are provided by the commodity-specific boards for cashew, coffee, cotton and sugar. Wholesale prices are obtained as yearly averages from monthly data monitored by the Ministry of Trade and Industry (MTI). For some commodities (cashew nuts and coffee), data from the auction where the commodity is traded before export (provided by the commodity board) are used. The options considered for domestic prices in the analysis are summarized in Table 16, which shows that for some commodities, different approaches were used for different years, because of 80 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report inconsistent data availability. The impacts of these changes are taken into account when the results are presented. Table 16: Methodological options and data sources for domestic prices used in the United Republic of Tanzania analysis Option Data source Commodity Farmgate price National average farmgate price CBT NBS SBT TCfB Cashew nuts Cotton Coffee Sugar Cane Wholesale price in main producing area MTI Pulses Maize Rice Wheat Not available Maize (2005) Milk Price at point of competition Wholesale in Dar es Salaam MTI TCtB Cotton Maize (2006–2008) Milk Pulses Rice (2005–2009) Wheat Wholesale price in market closest to destination country MTI Rice (2010) Maize (2005; 2009–2010) Retail price minus retail margins SBT Sugar Auction price CBT TCfB Cashew nuts (2008–2011) Coffee Not available Cashew nuts (2005–2007) CBT = Cashewnut Board of Tanzania; NBS = National Bureau of Statistics; SBT = Sugar Board of Tanzania; TCfB = Tanzania Coffee Board; TCtB = Tanzania Cotton Board. Source: Authors’ elaboration based on commodity-specific technical notes. Monitoring African Food and Agricultural Policies (MAFAP) 81 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Benchmark prices: The benchmark prices are the annual unit values of imports or exports of individual commodities reported in United Nations (UN) trade statistics (UNcomtrade).8 In some cases, when trade volumes are low and unit prices abnormally high (low), such as for maize and rice, import or export prices are constructed using the price prevailing in the destination market for exports (capital cities of neighbouring countries) minus the access costs from the border of the United Republic of Tanzania to the destination market. Table 17 shows the commodities and years to which each option has been applied; again these differences are taken into account when discussing the results by comparing across commodities or across years for a single commodity. Table 17: Methodological options and data sources for benchmark prices used in the United Republic of Tanzania analysis Option Data source Commodities Unit export or import value for all destination (origin) countries of exports (imports) UNcomtrade Cashew nuts Coffee Cotton Maize (2006; 2008) Milk Pulses Rice (2005–2009) Sugar Wheat Unit export or import value for a selection of destination (origin) countries of exports (imports) UNcomtrade Maize (2010) Wholesale price in major export market minus access costs to the URT border EAGC Maize (2005; 2009) Rice (2010) EAGC = Eastern Africa Grain Council. Source: Authors’ elaboration based on commodity-specific technical notes. Reference prices: Starting from benchmark prices – which in theory show market equilibrium in the absence of domestic policies, market interventions or impacts of market performance – the challenge is to identify reference prices that reflect the absence of policies, market interventions and market performance impacts at specific points along the value chain. This requires data on access costs, which are defined as all the costs involved in taking the commodity from one point in the value chain to another. These costs should include all aspects related to market access, such as processing, storage, handling, transport and the different margins applied by economic agents. Two main sets of access costs need to be estimated in the MAFAP methodology: those related to taking the 8 http://comtrade.un.org/ 82 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report commodity from the border to the point of competition, and those related to taking the commodity from the point of competition to the farmgate. Access costs between the farmgate and the point of competition: These costs are calculated as the sum of all the components incurred in taking the commodity from the farmgate to the wholesale market. They include trader margins, other agents’ fees, transport, loading and unloading, and processing if relevant. Data are obtained from literature review and key informants on the different value chains, and margins are considered to be 10 percent of the value of the purchased commodity (i.e., of the farmgate price). In the absence of adequate data, access costs can be calculated as the difference between wholesale prices and producer prices. The gap between these two prices is considered to reflect the real functioning of the chain when all explicit taxes are excluded. In other words, this value is the expression of policies, level of infrastructure development, competitiveness of actors, and actors’ conditions of market power in influencing access costs. In addition, when the commodity produced by farmers is different from the commodity traded at the wholesale level (e.g., sugar cane versus sugar, and seed cotton versus cotton lint), both commodities are expressed in farmgate product units to ease comparison. A detailed explanation of the access costs for each commodity can be found in the technical notes; the access cost components considered for each commodity are summarized in Table 18. Table 18: Access cost components from the farmgate to the point of competition in the United Republic of Tanzania Access cost component Commodities Transport, handling and margins Maize Pulses Rice Wheat Transport, handling, processing and margins Cotton Milk Sugar Transport, handling, processing, agents’ fees and margins Cashew nuts Coffee Source: Authors’ elaboration based on commodity-specific technical notes. Access costs between the point of competition and the border: These costs cover all import or export procedures, transport and handling, agents’ fees, trader margins, and additional processing if relevant. Again, trader margins are estimated at 10 percent of the value of the purchased commodity (i.e., of the wholesale price for exports and the CIF price for imports). Data are taken from literature review and cross-checked with estimates of the cost of cross-border trade from the Doing Business Monitoring African Food and Agricultural Policies (MAFAP) 83 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report project.9 For the period 2006–2010, the estimates calculated for this study are only marginally lower than those reported by the Doing Business project, so can be considered as correctly capturing the costs of export and import in the United Republic of Tanzania (Figure 16). Figure 16: Comparison of costs of cross-border trade in the United Republic of Tanzania calculated by the Doing Business and MAFAP projects Averages for exports and imports are calculated from Doing Business, and averages for all commodities traded via Dar es Salaam (seven) are calculated from MAFAP technical notes. Source: Authors’ elaboration based on commodity-specific technical notes and Doing Business database. The components of access costs from the border to the point of competition considered depend on the trade path. In the URT trade can follow two main paths: by ship from or to the port of Dar es Salaam (or Mtwara);10 or by road to or from neighbouring countries. The components of access 9 The Doing Business project, implemented by the International Finance Corporation of the World Bank Group, provides objective measures of business regulations for local firms in 185 economies, including the URT. Among the domains it assesses is cross-border trade, including estimates of import and export costs based on the fees levied on a twenty-foot equivalent unit in United States dollars. All the fees associated with completing the procedures to export or import the goods are taken into account, including costs for documents, administrative fees for customs clearance and inspections, customs broker fees, port-related charges and inland transport costs. These costs do not include customs tariffs and duties or costs related to sea transport. Only official costs are recorded. For more information see www.doingbusiness.org. 10 Cashew nuts are exported from Mtwara port. 0% 20% 40% 60% 80% 100% 120% 0 20 40 60 80 100 120 140 2007 2008 2009 2010 US$/tonne imported or exported Ratio MAFAP / DB Doing Business MAFAP 84 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report costs differ between these two paths, as there are no port and handling costs when imports (exports) come from (are sent to) a neighbouring country. Table 19 shows the components considered in each trade path. Table 19: Access cost components for the trade paths in the United Republic of Tanzania Access cost component Port of Dar es Salaam Neighbouring countries Preinspection fee Phytosanitary charges Port wharf age fees Tally fee SUMATRA fee Documentation fee Clearing agent fee Loading and unloading Health and food standards fee Transport from wholesale market to border Commodities for which this route is considered Cashew nuts Cotton Coffee Maize (2006–2008) Milk Pulses Rice (2005–2009) Sugar Wheat Maize (2005; 2009–2010) Rice (2010) Source: Authors’ elaboration from Temu, Manyama and Temu, 2010 data. Monitoring African Food and Agricultural Policies (MAFAP) 85 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The adjusted domain Of the four concepts that can be revised to obtain adjusted values (benchmark prices, exchange rates, access costs from border to point of competition and from point of competition to the farm gate) this report only considers adjusted values for two of them: access costs from the border to the point of competition and access costs from the point of competition to the farm gate. No explicit exchange rate policy exists in the URT and thus the observed exchange rate reflects the equilibrium in the free foreign exchange market. In addition there is no commodity for which benchmark prices are assumed to be distorted by the inefficiencies in the international markets. Adjusted access costs: For the analysis of some products, adjusted data on access costs to the point of competition and the producer have been used. Adjusted access costs take into account better- functioning markets. To generate access costs that reflect efficient value chains, the following adjustments have been made were applicable: Profit margins have been reduced from 10 to 5 percent of the commodity purchase price. Local taxes (i.e., local or district cess) have been eliminated. Commodity board fees have been eliminated. Transport costs have been reduced to the lowest estimate for each section, from any information source. Tables 20 and 21 summarize the two sets of indicators that the MAFAP project can generate (price gaps and NRPs) for the nine commodities analysed: • The indicators constructed using observed prices and access costs (observed price gaps and observed NRPs) give an absolute representation of the effects of policy initiatives and overall market performance in the country. • The indicators constructed using adjusted costs (adjusted price gaps and adjusted NRPs) take into account other sources of price distortions, in particular access costs. 86 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 20: Observed and adjusted price gaps in the United Republic of Tanzania, 2005 to 2010 (TSh/tonne) Product Indicators 2005 2006 2007 2008 2009 2010 Cashew nuts Observed price gap at wholesale n.a. n.a. n.a. -18 613 -60 502 -162 310 Adjusted price gap at wholesale n.a. n.a. n.a. -38 448 -85 052 -190 139 Observed price gap at the farmgate -78 964 30 993 -55 665 -11 779 134 832 -219 310 Adjusted price gap at the farmgate -124 908 -20 206 -104 385 -92 615 42 782 -317 139 Coffee Observed price gap at wholesale -429 586 -189 538 -414 044 95 576 -51 459 -210 478 Adjusted price gap at wholesale -457 217 -230 350 -456 930 49 049 -96 383 -279 035 Observed price gap at the farmgate -251 716 -319 097 -347 814 -231 991 -193 650 -1 230 298 Adjusted price gap at the farmgate -336 535 -455 762 -505 914 -399 834 -353 992 -1 442 398 Cow milk Observed price gap at wholesale n.d. n.d. 57 854 162 944 46 712 89 022 Adjusted price gap at wholesale n.d. n.d. 82 153 181 097 72 525 112 853 Observed price gap at the farmgate n.d. n.d. n.d. n.d. n.d. n.d. Adjusted price gap at the farmgate n.d. n.d. n.d. n.d. n.d. n.d. Maize Observed price gap at wholesale 19 382 -54 327 52 488 -19 388 1 533 -64 588 Adjusted price gap at wholesale 13 024 -30 420 27 041 7 576 -8 122 -36 381 Observed price gap at the farmgate n.d. -89 613 28 010 -72 663 13 031 -2 620 Adjusted price gap at the farmgate n.d. -65 705 2 563 -45 698 -3 869 -27 272 Pulses Observed price gap at wholesale n.d. n.d. n.d. n.d. n.d. n.d. Adjusted price gap at wholesale n.d. n.d. n.d. n.d. n.d. n.d. Observed price gap at the farmgate n.d. n.d. 53 951 18 015 54 075 164 428 Adjusted price gap at the farmgate n.d. n.d. 10 951 -30 806 -10 678 90 708 Rice Observed price gap at wholesale 266 426 409 667 333 986 315 630 372 218 -10 871 Adjusted price gap at wholesale 282 508 428 793 354 343 337 202 414 990 -29 059 Observed price gap at the farmgate 280 499 465 852 285 202 249 138 310 547 1 142 Adjusted price gap at the farmgate 264 997 451 106 269 307 230 731 308 486 -22 740 Cotton Observed price gap at wholesale -216 230 -383 879 -221 336 27 498 93 103 -45 141 Adjusted price gap at wholesale -216 230 -383 879 -221 336 27 498 93 103 -45 141 Observed price gap at the farmgate -124 430 -199 943 -188 390 -218 532 -17 443 -167 933 Adjusted price gap at the farmgate -124 430 -199 943 -188 390 -218 532 -17 443 -167 933 Sugar/s ugar cane Observed price gap at wholesale 109 841 9 969 233 596 273 387 227 084 139 810 Adjusted price gap at wholesale 148 423 58 119 281 540 325 992 291 237 217 333 Observed price gap at the farmgate -1 735 -11 842 -121 -5 669 -14 058 -14 094 Adjusted price gap at the farmgate 1 051 -8 189 3 152 -2 095 -9 395 -8 803 Wheat Observed price gap at wholesale 121 547 165 268 64 553 16 247 350 853 347 637 Adjusted price gap at wholesale 151 784 200 948 107 868 67 282 400 949 405 250 Observed price gap at the farmgate 89 482 118 672 -17 173 128 637 350 796 238 529 Adjusted price gap at the farmgate 106 579 138 241 9 679 149 979 368 634 265 736 n.a. = not applicable; n.d. = no data available. Sources: Commodity-specific technical notes. Monitoring African Food and Agricultural Policies (MAFAP) 87 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 21: Observed and adjusted nominal rates of protection in the United Republic of Tanzania, 2005 to 2010 Product Indicators 2005 2006 2007 2008 2009 2010 Cashew nuts Observed NRP to wholesaler n.a. n.a. n.a. -2% -7% -13% Adjusted NRP to wholesaler n.a. n.a. n.a. -4% -10% -15% Observed NRP to producer -11% 5% -8% -2% 25% -24% Adjusted NRP to producer -17% -3% -15% -13% 7% -31% Coffee Observed NRP to wholesaler -24% -8% -16% 4% -2% -5% Adjusted NRP to wholesaler -25% -9% -17% 2% -4% -7% Observed NRP to producer -31% -25% -23% -16% -14% -46% Adjusted NRP to producer -37% -32% -31% -25% -23% -50% Cow milk Observed NRP to wholesaler n.d. n.d. 16% 66% 13% 28% Adjusted NRP to wholesaler n.d. n.d. 25% 80% 22% 38% Observed NRP to producer n.d. n.d. n.d. n.d. n.d. n.d. Adjusted NRP to producer n.d. n.d. n.d. n.d. n.d. n.d. Maize Observed NRP to wholesaler 12% -18% 35% -5% 0% -15% Adjusted NRP to wholesaler 8% -11% 16% 2% -2% -9% Observed NRP to producer n.d. -31% 20% -21% 4% -1% Adjusted NRP to producer n.d. -25% 2% -14% -1% -10% Pulses Observed NRP to wholesaler n.d. n.d. n.d. n.d. n.d. n.d. Adjusted NRP to wholesaler n.d. n.d. n.d. n.d. n.d. n.d. Observed NRP to producer n.d. n.d. 18% 4% 9% 30% Adjusted NRP to producer n.d. n.d. 3% -7% -2% 15% Rice Observed NRP to wholesaler 90% 126% 82% 47% 50% -1% Adjusted NRP to wholesaler 101% 140% 91% 52% 59% -3% Observed NRP to producer 174% 269% 113% 51% 57% 0% Adjusted NRP to producer 150% 240% 100% 45% 57% -3% Cotton Observed NRP to wholesaler -20% -32% -15% 2% 6% -3% Adjusted NRP to wholesaler -20% -32% -15% 2% 6% -3% Observed NRP to producer -33% -48% -35% -33% -4% -26% Adjusted NRP to producer -33% -48% -35% -33% -4% -26% Sugar/sugar cane Observed NRP to wholesaler 24% 2% 42% 44% 30% 15% Adjusted NRP to wholesaler 36% 11% 56% 57% 42% 25% Observed NRP to producer -7% -34% 0% -14% -29% -22% Adjusted NRP to producer 5% -26% 12% -6% -21% -15% Wheat Observed NRP to wholesaler 46% 54% 14% 3% 81% 68% Adjusted NRP to wholesaler 66% 75% 27% 12% 105% 90% Observed NRP to producer 52% 58% -5% 28% 119% 65% Adjusted NRP to producer 68% 75% 3% 34% 133% 78% n.a. = not applicable; n.d. = no data available. Sources: Commodity-specific technical notes. 88 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Commodity-specific public expenditure is identified for five of the ten commodities analysed (cashew nuts, coffee, cotton, milk and sugar) for the years 2007 to 2010. NRAs incorporating the public expenditure dimension are also calculated for these five commodities (Table 22), but not for the others as lack of data meant that NRP and NRA for these commodities would coincide. From these calculations it can be concluded that commodity-specific support via public expenditure is generally dwarfed by the incentives or disincentives derived from policies and market performance. On average, public expenditure support for individual commodities represents less than 10 percent of the disincentives that result from policies and market performance (Figure 17). All commodities except milk have disincentives, so commodity-specific public expenditure is not capable of offsetting disincentives from policies and market performance. However, this conclusion should be taken with care, because these commodities may be receiving additional support via public expenditure in the form of non-targeted support, which accounts for most public expenditure in support of agriculture in the URT. Table 22: Observed and adjusted nominal rates of assistance to producers in the United Republic of Tanzania, 2005 to 2010 Product Indicators 2005 2006 2007 2008 2009 2010 Cashew nuts Observed NRA to producer -11% 5% -7% -1% 27% -22% Adjusted NRA to producer -17% -3% -13% -12% 9% -30% Coffee Observed NRA to producer -31% -25% -18% -9% -9% -45% Adjusted NRA to producer -37% -32% -26% -19% -19% -49% Cotton Observed NRA to producer -33% -48% -35% -33% -3% -14% Adjusted NRA to producer -33% -48% -35% -33% -3% -14% Milk Observed NRA to producer n.d. n.d. 16% 66% 13% 28% Adjusted NRA to producer n.d. n.d. 25% 80% 22% 38% Sugar cane Observed NRA to producer -7% -34% 0% -14% -28% -22% Adjusted NRA to producer 5% -26% 12% -6% -21% -14% n.a. = not applicable; n.d. = no data available. Sources: Commodity-specific technical notes. Monitoring African Food and Agricultural Policies (MAFAP) 89 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 17: Ratio of commodity-specific public expenditure support to disincentives resulting from policy and market performance in the United Republic of Tanzania, 2007 to 2010 Sources: Commodity-specific and public expenditure technical notes. Caveats and limitations Uncertainty about data quality is a limit to analytical work. Although efforts have been made to minimize errors by submitting the data collected to local experts, errors cannot be totally avoided. Efforts to improve data quality continue, and new data will be incorporated into the MAFAP technical notes and indicator database. The project is advocating for increased investments in reliable national statistical systems, which would provide great benefits for informed policy decisions. MAFAP project indicators and interpretation It is important to note that a significant part of the period analysed (2005–2010) was particularly turbulent, with challenges to market fundamentals and drastic changes in price trends. These events made it more difficult to carry out the analysis and determine the causes of incentives and disincentives. Leading indicators in the MAFAP project The headline indicators promoted by the project for monitoring price incentives and disincentives are the NRPs for: • the agriculture sector as a whole (NRPagsec); • imported products (NRPimp); • exported products (NRPexp); • non- or thinly traded products (NRPnot). 90 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report It should not be forgotten that the indicators for these categories are based on the analysis of commodities that represent only a percentage of total agricultural production under each category (Table 13). When the additional commodities have been analysed, these results might vary. Agriculture sector indicators: Figure 18 presents the results for the agriculture sector as a whole.11 Results of the analysis show that producers in the United Republic of Tanzania have overall been incentivized during the study period, but the level of incentives has declined. It can therefore be concluded that the policy environment and market performance lead farmers to receive higher prices than they would in the absence of policies and with well-functioning markets. However, this trend masks a dual situation, in line with the findings of Anderson and Masters (2009): producers of commodities that are imported into the URT are incentivized, while producers of export-oriented commodities are penalized. The analysis results add some details to this overall situation, with some commodities being protected at the wholesale (processed) level but penalized at the farmgate (raw) level. The analysis also distinguishes between policy-induced and market performance-related incentives and disincentives. While most incentives for imported commodities relate to trade policy, disincentives for export commodities relate to both explicit taxes and inefficiencies in the processing industry. In addition, part of the protection that imported commodities derive from trade policy is eroded by excessive marketing costs along the value chain. Thus, although the pattern of domestic prices aligning with international markets classifies the URT as a country where distortions to agricultural production are being reduced, commodity-specific results show that there are still significant distortions to agricultural incentives in the country. Moreover, coherence analysis shows that the structure of incentives and disincentives does not fully reflect policy priorities. 11 Based on results from the nine commodities analysed as representing the agriculture sector. Monitoring African Food and Agricultural Policies (MAFAP) 91 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 18: Average observed and adjusted nominal rates of protection and market development gaps for the agriculture sector in the United Republic of Tanzania, 2005 to 2010 Commodities included are cashew nuts, coffee, cotton, rice, sugar and wheat for the whole period; maize since 2006; and milk and pulses since 2007. Source: Authors’ elaboration. The results for each commodity are discussed in the following subsections, presented as aggregates for each of the three trade-related categories used in the project: imported, exports, and thinly traded. A final subsection focuses on food security and discusses the price incentives and disincentives for commodities that represent a significant part of the diet in the URT. Indicators for imports As shown in Figure 19, farmers producing commodities that the United Republic of Tanzania needs to import to cover domestic consumption are generally incentivized. These incentives are related to the CET that the URT applies to imports from outside the EAC. The only exception is sugar, where producers face strong disincentives. These incentives however mean that consumers of these commodities are penalized as they need to pay higher prices for them. -10% 0% 10% 20% 30% 40% 50% 60% 70% 2005 2006 2007 2008 2009 2010 MDG Average observed NRP for the agricultural sector Average adjusted NRP for the agricultural sector 92 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 19: Average observed and adjusted nominal rates of protection and market development gaps at the farmgate for imported products in the United Republic of Tanzania, 2005 to 2010 Commodities included are rice, sugar cane and wheat for the whole period; and milk since 2007. Sources: Commodity-specific technical notes. The decreasing trend in protection during the studied period is due to three main issues: Milk is included in calculation of the aggregate from 2007, and the average level of protection for milk is much lower than that for other products. Tariffs for wheat and sugar were partially waived from 2008, so their impact on domestic prices has decreased. In 2010, the URT became a net exporter of rice, so domestic prices have aligned with international prices. Even when the overall picture for imported commodities suggests reduced distortions and the alignment of domestic prices with those prevailing in international markets, there are differences across commodities. Some farmers (sugar cane) receive significant disincentives, while a poorly developed value chain prevents other farmers (milk) from benefiting from the protection. Most important, for all imported commodities, protection levels are eroded towards the farmgate because of lack of market integration and inefficiencies in the value chain. Rice Rice is the second most important food and cash crop in the United Republic of Tanzania after maize. It is also a major source of employment and income for many farming households (ACT, 2010). Most rice is produced by small-scale farmers, with marketing dominated by intermediaries and traders (Kilima, 2006). Rice productivity in the URT is lower than in most neighbouring countries and is one of the lowest in the world. The Tanzanian rice market is liberalized and consumers have the option of 0% 20% 40% 60% 80% 100% 120% 140% 160% 180% 200% 2005 2006 2007 2008 2009 2010 MDG Average observed NRP for imported products Average adjusted NRP for imported products Monitoring African Food and Agricultural Policies (MAFAP) 93 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report purchasing rice imported from other countries. The National Rice Sector Development Strategy therefore aims to transform the existing subsistence-dominated rice sector into a commercially viable production system (MAFC, 2009). Production: Rice production uses 18 percent of cultivated land and is located mainly in northern parts of the country. Among agricultural households, 17 percent grow rice (Government of URT, 2007). Nearly all rice (99 percent) is grown by smallholder farmers using traditional seed varieties. Paddy rice production has been increasing since 2000, mainly through the expansion of total land planted rather than increased yields, except for in the 2005–2007 period, when upscaling of a fertilizer subsidy programme – the National Agriculture Input Voucher Scheme (NAIVS) – raised yields and production significantly. However, yields decreased in 2008 and 2009, and the total area allocated to rice production increased again, as many cotton producers switched to rice production after experiencing significant losses because of declining world prices (Ngailo, Kaswamila and Senkoro, 2007). The lack of land suitable for rice production and the insufficient knowledge of new producers partly explain the substantial decline in yields and the stagnant growth in rice production that occurred between 2007 and 2009, despite NAIVS. In 2010, total rice production fell as yields recovered only slightly and the land allocated to rice production dropped to average figures for the decade. Consumption/utilization: The Food Balance Sheet for paddy rice indicates that 90 percent of rice produced is used for food, 5 percent is wasted and another 5 percent is used as seed (FAOSTAT, 2012). The amount of paddy rice available for consumption fluctuated between 28 and 29 kg per capita from 2000 to 2007, and rice is the third most important crop in terms of daily calories consumed per capita. As rice is generally more expensive than maize and other staple foods, it is more important in the diets of high- and middle-income consumers in both urban and rural areas. Trade: Rice is an important commercial crop among farming households: 42 percent of rice production is marketed compared with 28 percent of maize and just 18 percent of sorghum (Government of URT, 2007). Most of the rice traded in the United Republic of Tanzania is milled and broken, so has undergone some kind of processing. Far lower quantities of paddy and husked (brown) – unprocessed – rice is traded. The URT has been a net importer of rice since 2000, with the exception of 2010. The total volume of imported rice has steadily decreased, showing how the URT is moving towards self-sufficiency in rice (Figure 20). The share of imports in total consumption has followed the same trend. 94 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 20: Volume of rice trade and share of trade in domestic consumption in the United Republic of Tanzania, 2000 to 2010 Consumption calculated as apparent consumption (Y + M - X). Paddy and husked rice converted to milled equivalents using conversion ratios of 0.65 and 0.80, respectively. Source: UNcomtrade. Most of the URT’s rice imports come from East Asia. Imports from developed countries have played an important role in some years (mainly during the period leading up to the food price crisis), with imports from mainly Japan and the United States of America probably in the form of food aid. For exports, the URT is mainly a regional player, exporting nearly 80 percent of its surplus to EAC countries and most of the rest to other African countries such as Malawi, the Democratic Republic of the Congo and Zambia. Value chain performance: In general, rice marketing in the United Republic Tanzania of has three main supply channels (Minot, 2010a): (1) traditional rice producers; (2) irrigated rice farmers/traders; (3) larger irrigated rice farmers/traders. The first and second supply channels are generally long and involve many actors before the crop reaches its final consumers; the third channel has a shorter value chain with millers and brokers playing a central role in the trading process. Usually, after paddy has been harvested, it is sold to local traders, who either trade it as paddy in regional markets (there are more than 20 wholesale markets across the country) or send it to mills for processing. The milled rice is then sold wholesale 2% 7% 12% 17% 22% 27% 32% - 20 40 60 80 100 120 140 160 180 200 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 % of domestic consumption Thousand tonnes Total trade as % of domestic consumption [right axis] Total exports Total imports Monitoring African Food and Agricultural Policies (MAFAP) 95 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report to traders from local markets/shops, while paddy might be sold to larger millers who export processed rice. Long supply chains combined with deficient transport networks have contributed to high marketing margins (Eskola, 2005), which have a strong influence on consumer prices and the profitability of rice production, processing, marketing/distribution and retail. High transport costs affect both the internal and export trade of agricultural crops. Local prices are higher than international market prices because of these inefficiencies in the supply chain, and the application of tariffs (Minot, 2010b). Imported rice and rice provided under the Food Aid Counterpart fund follow a different path into the market: 50 percent is distributed through wholesalers, 30 percent through the distribution systems of traders or importers, and 20 percent through retail shops (MAFC and FAO, 2008). MAFAP indicators and interpretation: The United Republic of Tanzania follows a policy of protecting rice farmers by applying a relatively high tariff (75 percent or US$200/tonne) on imports from outside the EAC. This translates into positive NRPs during years when the URT is a net importer (Figure 21), and is coherent with concerns that cheap imports generate unfair competition for farmers. However, while until 2006 most protection was passed through to producing areas, in 2007 the level of incentives was drastically reduced, and protection at the wholesale level became higher than that at the farmgate (Figure 22). Figure 21: MAFAP nominal rates of protection for rice in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration. -50% 0% 50% 100% 150% 200% 250% 300% 2005 2006 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate 96 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report This change in the distribution of incentives along the value chain coincided with liberalization of the rice market, which led to increased market power for traders (i.e., from calculations it can be assumed that margins rose to well above 10 percent) or excessive costs in the value chain (increased production versus limited storage capacity and increasing access costs). There is also evidence that bad functioning of the value chain (with too many intermediaries, high transport costs, asymmetric distribution of information, and lack of storage capacity for farmers) limits protection to farmers and translates into disincentives. Together with other measures such as the input subsidy, protection has enabled an increase in overall rice production in the URT, resulting in the country becoming a rice exporter in the region. In 2010, when the URT was a net rice exporter, there was a slight disincentive to farmers, which was most likely linked to the existence of an export ban. Figure 22: Trends in wholesale and farmgate price gaps for rice in the United Republic of Tanzania , 2005 to 2009 Source: Authors’ elaboration. Main message: Incentives for rice in the United Republic of Tanzania decreased between 2005 and 2010. This is a normal trend for a country moving towards self-sufficiency. However a salient finding is that while the level of incentives used to be higher for farmers than for wholesalers in consumption areas, following liberalization of the rice market in 2007, this balance has changed and protection is now higher in consumption areas. Import tariffs in the URT prevent cheap imports and result in effective price premiums for farmers, but the cost to consumers is quite high. Furthermore, in 2010, when the URT became a net exporter, the export ban prevented farmers from receiving higher prices. If the change in trade status from net rice importer to net exporter becomes permanent it would therefore be advisable to start removing tariffs. Yields remain below average for the region, so without protection Tanzanian rice is unlikely to be competitive in international markets if prices return to their historical levels. The rice sector needs a supporting environment that leads to additional investment at the farm level, to increase yields and lower production costs. In addition, protection to farmers could be increased without affecting consumer prices if market access was improved. Farm gate prices could increase by up to ten per cent if the value chain was more efficient without increasing consumer prices. Alternatively, consumer prices could be reduced by up to 6 per cent. Domestic demand could then be covered at lower prices, thus benefiting consumers, or - 50 100 150 200 250 300 350 400 450 500 2005 2006 2007 2008 2009 Thousand TzSh/tonne Price gap at point of competition Price gap at the farm gate Monitoring African Food and Agricultural Policies (MAFAP) 97 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report surpluses exported to neighbouring countries with higher prices for farmers when prices in those markets are more rewarding. Sugar cane Sugar cane is an important commercial crop in the United Republic of Tanzania, and is transformed into sugar at plants throughout the country. Most sugar cane is grown by contract growers and smallholders in estates owned by sugar processing factories. The Tanzanian sugar industry has an important socio-economic impact in generating employment and economic activity. It provides direct employment to about 14 000 people, and is an outlet for the produce of more than 30 000 farming households. Considering an average of two to three economically active adults per farming household, it therefore provides secondary employment to more than 80 000 people. Cane farmers’ total annual earnings are about TSh 4 billion (approximately US$2.7 million). Activities related to the sugar industry provide about TSh 12.3 billion of tax revenue – 1.7 percent of the total. Production: From 2005 to 2010, sugar cane production in the United Republic of Tanzania increased in area and production, but yields fluctuated. Cane production increased by 17 percent, from 2.3 million tonnes in 2005 to 2.7 million tonnes in 2010, while the area under cane production increased by 15 percent, from 20 000 to 23 000 ha. This implies that most production increases are due to area expansion, with yields remaining at about 120 tonnes/ha. Sugar cane production in the URT is concentrated in three regions – Morogoro, Kagera and Kilimanjaro – in the centre and north of the country, which accounted for 71 percent of total production for the period under study. In these regions, farmers have a reliable market and obtain input loans from buyers, most of which are sugar factories close to sugar growers’ farms, thus providing a key production incentive. Consumption/utilization: The sugar industry is one of the largest agroprocessing industries in the United Republic of Tanzania. It contributes approximately 35 percent of gross output from the food manufacturing sector, and 7 to 10 percent of total manufacturing value-added. Four companies are involved in raw sugar production: Kilombero Sugar Company (KSC) and Mtibwa Sugar Estate (MSE) in Morogoro Region; Tanganyika Planting Company (TPC) in Kilimanjaro Region; and Kagera Sugar Limited (KSL) in Kagera Region. KSC processes nearly 50 percent of total sugar cane, with MSE and TPC processing approximately 20 percent each and KSL the remaining 10 percent. The companies are under the control of domestic capital, except for KSC, which is owned by the South African corporation Illovo. The URT’s level of sugar self-sufficiency is about 75 percent. In 2009/10, total sugar consumption was 377 313 tonnes, of which 23 percent was for industrial use (in sectors such as carbonated drinks, pharmaceuticals and bakeries) and the remaining 77 percent was consumed directly. To manage the sugar supply in the URT, the government has increased sugar imports and imposed a ban on sugar exports to neighbouring countries. The country’s porous borders and ports pose a critical challenge to the local sugar industry. Smuggling not only creates shortages in the local market but also imposes huge losses of tax revenue to the government. For example, in 2011, the government had to engage security services to block illegal exports of sugar to neighbouring countries because acute shortages were pushing sugar prices to extraordinarily high levels. Trade and marketing: The United Republic of Tanzania is a net importer of sugar. Over the study period, annual exports ranged from 10 000 to 65 000 tonnes, and imports from 60 000 to 185 000 tonnes. The URT exports sugar to the European Union (EU) as a way of utilizing its preferential quota 98 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report allocated through initiatives such as the African Caribbean Pacific Sugar Protocol and Everything But Arms. The vast majority of sugar imports are declared as sugar for industrial use (or pure sucrose), as most exemptions from sugar import tariffs are given to industries using the sugar as an input for food production. Most of the URT’s sugar exports are raw cane sugar. Throughout the study period, the URT was a net importer of sugar for industrial use and raw cane sugar, and a net exporter (albeit of reduced quantities) of sugar with added flavouring or colouring. Value chain performance: Sugar cane is produced by estates and outgrowers and sold to sugar factories in eastern, northern and northwestern United Republic of Tanzania. These factories then sell the sugar to local sellers or exporters. Local wholesalers market sugar to retailers, while exporters find regional or global markets. All internal and international sugar marketing is regulated by the Sugar Board of Tanzania (SBT). As locally produced sugar is insufficient for direct and industrial local consumption, there are import inlets throughout the country. When sugar cane was first bought from smallholder farmers in 1962, prices fluctuated according to the cane’s sucrose level, which was measured in laboratories. Since then, various remuneration systems have been developed. Following contract renegotiations in 1999 and 2000, in 2001 sugar mills agreed to fix prices at the 9 percent sucrose level, to mitigate the variability of farmers’ incomes; given the fertility of the area, this level was thought to be achievable for all farmers. Price fixing was seen as a good incentive for smallholder farmers to grow more cane and a solution to the measurement problem. However, processing units have significant market power, and the prices that some factories pay to farmers are lower than the production unit costs. This low pay is ascribed to the monopoly situation created by laws that prohibit the construction of additional sugar factories within 80 km of existing ones and the obligation for farmers to sell to the nearest factory at prices dictated by the factory. Farmers also face delays in payments; although contract farming requires payment within 40 days of delivery, payment often takes three to four months. As farmers generally borrow money from credit cooperative societies, these delays lead to losses through increased interest payments. This situation is assumed to have discouraged farmers from growing sugar cane, leading to a decline in sugar production from 246 to 179 tonnes in 2011. Processing costs at sugar mills in the URT are not publicly available, but data from one of the four main mills show that costs are more than twice as high as those in other countries in the region (NAMC, 2004; Mitchell, 2004), showing a clear relative inefficiency of processing units in the URT. MAFAP indicators and interpretation: As shown in Figure 23, policy and value chain inefficiencies have diverse impacts on the Tanzanian sugar market. While at the point of competition the border policy (i.e., the tariff of 100 percent or US$200/tonne) results in domestic prices being higher than reference prices, sugar cane farmers receive prices that are significantly lower than the reference price. The study results confirm the intuition of Morrissey and Leyaro (2007), who suspected that processors retain a larger proportion of the producer subsidy12 than sugar cane farmers do. Since 2008, the level of protection at the wholesale level has been decreasing, because of tariff exemptions for sugar imports, particularly in 2010 when exemptions were granted for all types of sugar. In 2007, the disincentives to farmers were lower because the low domestic production of sugar created 12 The concept of producer subsidy in the work of Morrissey and Leyaro is similar to that of incentives in the MAFAP framework. Monitoring African Food and Agricultural Policies (MAFAP) 99 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report competition for raw sugar among mills and important quantities of raw cane were exported and imported. Figure 23: MAFAP nominal rates of protection for sugar (wholesale) and sugar cane (farmgate) in the United Republic of Tanzania 2005-2010 Source: Authors’ elaboration. Several policy and market functioning aspects explain this divergence between incentives at the wholesale and farmgate levels. First, the taxes on domestic sugar cane marketing (about TSh 120/tonne) explain only part of the situation, as the disincentives to farmers are far greater than local government taxation. Farmers face significant disincentives from either very high profits for the local sugar industry or high processing costs – it is not clear which. The processing cost data from a single sugar mill are far higher than those used to construct the reference price (Figure 24). Calculating the incentive indicators from these processing cost data for the years they are available shows that farmers as well as the industry benefit from the incentives provided by the tariff. It can therefore be suspected that the main source of disincentives for sugar cane growers arises from high sugar processing costs. -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% 60% 70% 2005 2006 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate 100 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 24: Comparison of sugar processing costs used in the analysis and those reported by the Mtibwa Sugar Plant in the United Republic of Tanzania, 2005 to 2007 Source: Authors’ elaboration. Main message: The effects of trade policy (i.e., the sugar import tariff) are reflected in the prices that consumers pay for sugar in the United Republic of Tanzania, which are higher than international prices. However, farmers do not benefit from this border protection and seem to be disconnected from changes in trade policy; they also face disincentives from the low efficiency of sugar mills. As a consequence, the current trade policy does not benefit farmers as much as a more efficient sugar industry would. The government should therefore consider removing the sugar import tariff, which would require the removal of sugar from the sensitive items list for the EAC CET. The government should also revise the investment environment for the sugar sector, to allow companies to increase their efficiency and thus to pay higher prices to sugar cane producers. Wheat Wheat is not a priority crop for agriculture sector development in the United Republic of Tanzania, and there are no production or marketing subsidies for wheat. The wheat sector’s development and operations are dominated by large private sector commercial farms and millers; smallholder engagement in wheat production is very small-scale and scattered. Farms that were owned by the government through the National Food Company were privatized during the liberalization era. Direct incentives for production and market development are almost absent, with the exception of the EAC CET, for which wheat is a sensitive item with a 35 percent ad valorem tariff at the border. The scarcity of wheat research and breeding activities at national agriculture research stations has resulted in low availability of improved seeds for smallholder farmers. However, the URT has the potential to produce more than 164 000 tonnes of wheat a year, if policy efforts are directed towards improving crop husbandry, trade and marketing. Although wheat accounts for six percent of per capita calorie intake, it is economically important for two reasons: i) most wheat consumed in the URT is imported, implying that price shocks in wheat exporting countries may have significant impacts on foreign exchange reserves; and ii) effective wheat demand is concentrated in urban areas with high population growth, and is bound to increase as the population grows. 0 0.5 1 1.5 2 2.5 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 2005 2006 2007 TSh/tonne of sugar cane Processing costs at Mtibwa Sugar Plant Processing costs used in the analysis Ratio Monitoring African Food and Agricultural Policies (MAFAP) 101 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Production: Between 2000 and 2010, the wheat harvested area fluctuated from a maximum of 75 000 ha to a minimum of 30 000 ha, averaging approximately 50 000 ha – less than 1 percent of the United Republic of Tanzania’s total agricultural area. With average yields of about 2 tonnes/ha, total production is approximately 100 000 tonnes, representing a mere 0.2 percent of total agricultural output. More than 90 percent of domestic wheat production comes from Arusha, Kilimanjaro and Manyara regions in the north, and Iringa and Mbeya regions in the Southern Highlands. While wheat production in the Southern Highlands is predominantly small scale, most production in the north is on large-scale farms. Wheat production can be classified into three production modes: large-scale mechanized; small- to medium-scale mechanized; and hand-tool production. Consumption/utilization: According to FAOSTAT Food Balance Sheets, nearly 100 percent of total wheat production is consumed as food in the United Republic of Tanzania. In terms of calorie intake, wheat ranks fourth in the Tanzanian diet, after maize, cassava and rice. Between 2002 and 2007, the average calorie intake from wheat was one-fifth that from maize. Wheat is consumed mainly in the form of wheat flour, which is both an intermediate and a final product. Wheat consumption is higher in urban areas (accounting for 83 percent of the total) than rural areas (17 percent) (Kilima, 2006). The wheat milling industry is dominated by the AZAM and AZANIA companies in Dar es Salaam, which supply wheat products to consumers in both URT and neighbouring countries in East and Central Africa. Trade and marketing: The United Republic of Tanzania is a net importer of wheat, with amounts traded being more than six times domestic production. Most wheat exports from the URT are recorded as re-exports. Wheat imports account for nearly 30 percent of total agricultural imports, generating an import bill of close to US$150 million a year. The 35 percent ad valorem tariff (EAC CET) was reduced to 10 percent in 2007. In contrast, the URT has been a net exporter of wheat flour during most of the period; volumes traded account for 15 percent of the domestic wheat supply and a non-negligible share of total domestic wheat supply plus wheat flour imports (8 percent from 2000 to 2010 and 11 percent during the 2005–2010 study period). Re-exports are negligible, at less than 1 percent of total exports, apart from in 2005, when they accounted for 86 percent. Thus the wheat processing industry in the URT shows a clear export orientation. Australia, the Russian Federation and Argentina are the main sources of imports, with very small amounts sourced from other African countries. The main export destinations for wheat flour are neighbouring countries, with the Democratic Republic of the Congo accounting for more than 75 percent of the total and the rest going to other EAC partners. Value chain performance: Before reaching urban or rural consumers, wheat follows one of two independent marketing channels: from small-scale farming along the Southern Corridor, or from large-scale activities. Each system operates independently from the farm to final consumers. Bakheresa Ltd is the dominant player among large-scale operations, because of its multiple functions along the supply and value-addition chain. It is followed by Azania and Mohamedi Enterprises Limited. Large commercial farmers and companies supply wheat to large milling companies such as Bakheresa. However, owing to the low domestic wheat production, Bakheresa imports wheat from world markets; it exports various wheat products to East and Central Africa, including bakery products, which are also distributed through retail outlets in the United Republic of Tanzania. Bakheresa’s small-scale chain encompasses intermediaries, small-scale millers and home bakeries, which also sell final products via retail trade. 102 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Raw wheat imports enter the country via Mombasa and Dar es Salaam ports. From there they are transported by road to milling companies in Dar es Salaam or Arusha regions for processing Over the study period, prices increased, with similar price patterns in all the markets considered. The highest wheat prices are reported for Tanga and Moshi, close to the Kenyan border. Prices are higher here because of demand from Kenya, where wheat prices are high. All regions with low prices, such as Iringa and Sumbawanga, show relatively high levels of production. Border towns such as Sumbawanga have the potential to trade with Malawi and Zambia, but wheat trade is very low and maize is the dominant traded crop. MAFAP indicators and interpretation: The results obtained for wheat in the United Republic of Tanzania show a high level of protection for wheat producers and traders throughout the study period (Figure 25). Protection is significantly higher than the CET for wheat (35 percent), even though the CET has been reduced to 10 percent since 2007. Figure 25: MAFAP nominal rates of protection for wheat in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration. Regarding the relationship between the incentive rates at the farmgate and the point of competition and the evolution of trade policy, three periods can be distinguished (Figure 26): before the food price hike of 2007; 2007 and 2008; and 2009 and 2010. Before the food price hike of 2007 prices in the URT reflected the CET and some additional incentives to local traders resulting from imperfect price transmission of international prices to the domestic market. These incentives were particularly important as the URT was importing more than six times as much wheat as it produced domestically. However, even with the tariff in place, more competition in the import market could have made domestic prices for wheat nearly 15 percent -20% 0% 20% 40% 60% 80% 100% 120% 140% 160% 2005 2006 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 103 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report lower than they were. Price gaps were higher at the point of competition than the farmgate, showing that consumers were more penalized than farmers were protected, and traders captured most of the price difference. In 2007 and 2008, as international prices for wheat rose sharply, the URT lowered the CET for wheat to 10 percent. This had the immediate effect of sharply decreasing the level of protection for domestic production. While in 2007 farmers saw their prices fall more than consumers did, in 2008 farmers benefited from lower imports, increasing the share of domestic supply in overall consumption. Despite the reduction of protection for domestic production, the protection rate has remained higher than the tariff because of the excessive access costs from the border to the point of competition. In the third period (2009 and 2010), the tariff was maintained at the reduced level of 10 percent, but domestic prices continued to increase despite reduced international prices. This led to a very high level of protection, which in 2009 benefited farmers more than wholesalers. In 2010 the distribution of incentives between farmers and wholesalers returned to the pre-2007 pattern. Some experts point to exports of wheat flour to neighbouring countries as a potential outlet for the imports of wheat at lower tariffs. However, although formal exports of flour have increased, they account for less than 10 percent of total wheat imports. Figure 26: Comparison of tariff values and price gaps for wheat at wholesale and the farmgate in the United Republic of Tanzania, 2005 to 2010 Sources: Authors’ elaboration based on MTI, UNcomtrade and EAC CET statistics. Main message: Although the United Republic of Tanzania has taken measures to reduce domestic prices of wheat, the impact of these measures has been limited. Domestic wheat prices remain higher than their international equivalents and thus there are clear transfers from consumers to traders and, to a lesser extent, producers. The government should ease import procedures for wheat because the high degree of market power in wheat imports allows traders to charge prices that are well above the import parity price. Additional competition in the import market for wheat or bulk -50,000 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 2005 2006 2007 2008 2009 2010 Tsh/tonne Value of tariff Price gap at wholesale level Price gap at farm gate 104 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report procurement of wheat could reduce the cost of imports and therefore price consumers have to pay for wheat. Wheat is one of the commodities for which increased production could be expected, because of both its high price relative to maize and its high incentives. Even when price incentives were significant during the study period, domestic production has not increased. According to the Sealian Agricultural Research Institute (SARI, no date) this could be because medium- and small-scale farmers lack access to new varieties and grow old varieties that often succumb to new diseases, disease outbreaks or drought. Additional investments in wheat research and development (R&D) are needed if wheat production is to be increased in the URT. Milk The United Republic of Tanzania has a wide range of livestock resources, including an estimated 21.3 million cattle, of which 680 000 are dairy cattle with the capacity to produce a total of 1.6 billion litres a year. The livestock industry accounts for 3.8 percent of gross domestic product (GDP), with the dairy subsector contributing 30 percent of livestock output (TAMPA, 2011). Most of the livestock population are of indigenous breeds, and the most abundant livestock type is cattle. Despite their ability to survive in harsh environmental conditions, indigenous cattle have lower productivity than improved cattle. The dairy industry is reported to be an important component of the livestock sector, with great potential for improving people’s living standards through cow milk consumption and sales of cow milk products (Njombe et al., 2011). Although the dairy sector is not fully commercialized, it employs more than 2 million households and more than 100 000 intermediaries involved in milk processing and marketing. Dairy production also provides small-scale farmers with a regular cash income that can be several times greater than the income from many other types of on- and off-farm enterprise. Given the potential of the livestock sector, particularly the dairy subsector, to reduce poverty, the Ministry of Livestock and Fisheries Development (MLFD) formulated a Livestock Development Strategy in 2010, which identifies four key strategic priority areas for intervention (MLFD, 2010), including the improvement of financial services and incentives for the private sector’s participation in production, processing and marketing of livestock and livestock products. The long- term objective of the National Livestock Policy is to encourage the development of a commercially oriented, efficient and internationally competitive dairy industry (TAMPA, 2011; MLFD, 2010). Production: In the United Republic of Tanzania, the dairy industry contributes one-third of total livestock sector value. The country is not self-sufficient in milk and milk products, despite the large cattle population and the presence of processing industries. Only 3.2 percent of the available cattle population produces milk, mainly from crossbreeds of Friesian, Jersey and Ayrshire cattle with the Tanzania shorthorn zebu. From 2005 to 2010, the average growth rate of dairy animals (head) and production (tonnes) remained unchanged, at 3.6 percent, with yields remaining more or less stable after a significant increase from 2000 to 2005. Milk from indigenous and improved cattle types represented 64.5 and 35.4 percent of total milk production respectively for the 2005–2010 period. In the same period, the average increase in milk production from indigenous cattle was smaller than that from improved cattle, at 1.6 percent/year for indigenous compared with 7 percent for improved. According to Njombe et al. (2011), improved cattle can produce more than four times as much milk per lactation than indigenous cattle. Monitoring African Food and Agricultural Policies (MAFAP) 105 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Consumption/utilization: Fresh and fermented liquid milk dominates dairy consumption in the United Republic of Tanzania, which has a narrower range of dairy products than other African countries (Omore et al., 2009). At 41 litres per annum, national per capita milk consumption is lower than the FAO recommended level of 200 litres. From 2000 to 2010, more cow milk products were produced than equivalent products from other dairy animals, which are mainly goats. According to FAOSTAT, whole, fresh cow milk accounts for 92 percent of total milk production in the URT, and whole, fresh goat milk for the remainder. Most of the cow milk produced in the country is consumed in rural areas. The cattle population is concentrated in areas far from potential markets, where animal feed is available and cattle husbandry is favoured. According to RLDC (2009), cow milk consumption in livestock keeping communities can exceed 100 litres per annum. However, the domestic market is relatively narrow compared with the human population, despite initiatives for expanding and developing a sustainable domestic market for cow milk products and encouraging more investment in milk processing. Most cow milk is consumed without any processing, either on- farm (29.5 percent) or via sales by informal hawkers (67.0 percent), with only 3.5 percent being processed (RLDC, 2010). The situation regarding packaged milk is of particular interest: household survey data for 2007 (NBS, 2007) show that national consumption of packaged milk is very low, even in urban areas, at only 0.078 percent of the population. The highest level is in Dar es Salaam Urban, where 1.148 percent of survey respondents reported consuming packaged milk. Trade and marketing: In the United Republic of Tanzania, milk trade represents only a small share of total milk production but significant shares of off-farm consumption and inputs for processing. On average, only 3.5 percent of domestic milk production is marketed, and nearly one-third of processed milk consumption is covered by imports. Even when informal off-farm marketing is considered, nearly 10 percent of total milk consumption outside the farm is imported (RLDC, 2009). Both fresh milk and milk powder are imported, but milk powder represents nearly 80 percent of total milk imports in liquid milk equivalents during the study period. Most milk imports come from outside the EAC, although there are reduced import tariffs for Kenya and Uganda. Value chain performance: Smallholder farmers have a prominent role in milk production in the United Republic of Tanzania, and most smallholder milk producers keep indigenous cattle types. Cow milk producers have links to milk collection centres, which are in turn connected to markets in periurban and urban areas, especially where farmers produce surplus cow milk above local market requirements. MLFD reports that the surplus milk produced by these farmers is marketed in different ways depending on the production system, location and quantity. Dairy value chain studies reveal that 10 percent of the raw milk produced is marketed, although only 2 percent of this milk trade is formal. According to Kurwijila (2010), in the commercial sector, which accounts for 30 percent of milk production, the milk market shares are 86.1 percent to neighbours, 5.3 percent to local markets, 4.6 percent to traders at the farm, and 1.4 percent to processing factories. On-farm milk consumption has followed a decreasing trend since 2005. For instance, Dillmann and Ijumba (2011) report that most fresh cow milk in the URT is marketed through traditional channels (67 percent), while 30 percent is consumed on-farm and 3 percent is marketed through formal channels. The URT has a total of 62 milk processing plants with varying potential and actual processing capacities; less than 25 percent of potential processing capacity is being used. Currently, the major 106 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report processing regions are Mara, Tanga, Arusha and Iringa. Nationwide, an estimated 41 million litres of cow milk a year is processed into pasteurized milk, ultra-high temperature (UHT) milk, cultured milk, ghee, butter, cheese and cream, and sold on the domestic market. However, Tanzanian processing plants face far higher costs than those in other regions of Africa (Fussi, 2010). It is therefore challenging for local dairy enterprises to produce high-quality milk products cost-effectively, to increase the competitiveness of the URT’s dairy industry domestically and in the region (RLDC, 2009). MAFAP indicators and interpretation: Indicators for milk have to be treated with caution for two main reasons: data are available for only the years 2007 to 2010; and, despite their efforts, the authors have been unable to obtain reliable farmgate price data, so the analysis is of only the wholesale level. These gaps are mainly the result of the dual structure of the milk market, with most production not reaching formal markets and being consumed on-farm or sold to local consumers. As shown in Figure 27, there were incentives to milk producers in the United Republic of Tanzania throughout the study period, reflecting import tariffs, which were always more than 50 percent.13 The level of incentives is driven mainly by benchmark prices, which have fluctuated significantly while domestic prices have remained nearly stable.14 Figure 27: MAFAP nominal rates of protection for milk in the United Republic of Tanzania, 2007 to 2010 Source: Authors’ elaboration. To understand whether or not this protection reaches farmers, two analyses can be made. First, the reference price calculated for the wholesale level can be compared with the farmgate price reported by the National Bureau of Statistics (NBS), assuming that this price is a proxy for the price that farmers obtain on the informal market. The MAFAP analysis shows that farmers receive incentives, 13 Although Kenya and Uganda have reduced tariffs on milk imports into the URT, the weight of these imports in total imports is small. 14 For the 2006–2010 period, the coefficient of variation for domestic prices was zero, while that for benchmark prices was 0.31. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Monitoring African Food and Agricultural Policies (MAFAP) 107 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report albeit much lower ones than those reported for the wholesale level, implying that the tariff promotes market segregation and leads to consumers paying higher prices for milk even in the informal market. Milk processing costs in the URT are reported to be 67 percent higher than those in neighbouring countries such as Kenya (RLDC, 2010). Figure 28 shows that to sell at the reported wholesale prices (i.e., wholesale prices minus processing costs), processing plants could pay milk producers only 40 percent of the reported farmgate prices, so the inefficiencies of the dairy industry (high costs and underutilization) provide disincentives to milk producers selling to processing companies. Figure 28: Farmgate and implicit prices paid by processors to farmers for milk in the United Republic of Tanzania, 2007 to 2010 The implicit price paid by processors is calculated as the wholesale price minus processing costs. Sources: Authors’ elaboration using NBS, Links Tanzania and Dillmann and Ijumba, 2011 data. Main message: Milk traders are protected by the external tariff, leading to consumers paying higher prices for milk than those prevailing in international markets. However, this protection affects only a small share of total milk production; most of the market is disconnected from international markets. Farmers in the informal market also obtain higher than international prices, although price differences are far smaller. The protection therefore provides incentives to milk producers at the cost of consumers in local markets. If more milk production were processed and marketed via more formal channels, the processing industry would have to pay lower prices to farmers because of its high processing costs. To avoid the collapse of farmgate prices for milk, the government should therefore promote the establishment of a more commercial dairy sector accompanied by improvements in milk processing efficiency. 108 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Indicators for exports As shown in Figure 29, farmers producing export commodities in the United Republic of Tanzania are generally disincentivized, meaning that the policy environment together with market performance lead them to get lower prices than they could obtain in a policy-free environment with better market performance. These disincentives are related to taxation of commodities (cotton, cashew nuts), bad functioning of the value chain (coffee, cashew nuts) and inefficiencies in the processing sector (cotton). Figure 29: Average observed and adjusted nominal rates of protection and market development gaps for exported products in the United Republic of Tanzania, 2005 to 2010 Commodities included are coffee, cotton and cashew nuts for the whole period; and pulses since 2007. Source: Authors’ elaboration. Although Figure 29 shows a decrease in the level of disincentives during the study period, this does not imply that there has been a shift towards an export-friendly environment. Since 2007, beans represent nearly 50 percent of the aggregate.15 Pulse producers have positive indicators, meaning that average prices are higher than export prices. In general, this situation would be considered as incentivizing producers, but in this case it shows bad functioning of the value chain. Figure 30 shows the evolution of the NRPs for each of the four commodities considered. Although the levels of disincentives for the three traditional export crops (coffee, cotton and cashew nuts) declined in 2009, the trend throughout the study period is for persistent disincentives. In addition, excessive access 15 Aggregates are based on production value weighted by reference prices. Beans represent more than 50 percent of the value of all the exported commodities considered. -35% -30% -25% -20% -15% -10% -5% 0% 5% 10% 15% 2005 2006 2007 2008 2009 2010 MDG Average observedc NRP for exported products Average adjusted NRP for exported products Monitoring African Food and Agricultural Policies (MAFAP) 109 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report costs and local taxation mean that the adjusted domain shows an increasing level of disincentives throughout the period. Figure 30: Farmgate nominal rates of protection for export commodities in the United Republic of Tanzania, 2005 to 2010 The traditional export aggregate covers coffee, cotton and cashew nuts. Source: Authors’ elaboration. Coffee Coffee is the second most important agricultural export commodity in the United Republic of Tanzania, after tobacco. It accounted for 14 percent of agricultural exports in the 2004–2009 period (FAOSTAT) and 4 percent of total exports during 2004–2011 (UNcomtrade). More than 90 percent of coffee is produced by smallholder farmers. The coffee industry provides direct income to more than 80 000 households and livelihoods for more than 2.5 million Tanzanians (MAFC, 2010). However, low world prices during the late 1990s and early 2000s have forced many local producers to substitute coffee with maize or rice as a source of household income, leading to the stagnation of local coffee production. In response to these changes, since the early 2000s, the government has collaborated with the private sector to implement measures for revamping the coffee sector. As part of the Agricultural Sector Development Programme (ASDP), the government has launched the Coffee Industry Development Strategy 2011–2016, which aims to increase coffee production from 50 000 to 80 000 tonnes, and to improve the quality of outputs by increasing the share of premium coffee production from 35 to 70 percent of total production by 2016. Production: The United Republic of Tanzania has abundant arable land suitable for producing high- quality Arabica and Robusta coffee. The country’s three main coffee producing areas are the Northern Highlands, the Southern Highlands and the Western Lake Zone. In recent years, coffee production has increased in the southern part of the country, but production in the north, where higher-quality coffee is typically grown, has been decreasing. Arabica is the main coffee variety. -60% -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 2005 2006 2007 2008 2009 2010 Nominal Rate of Protection at Farm Gate COFFEE COTTON BEANS CASHEW NUTS Traditional exports 110 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Robusta production is much smaller, although it showed a peak in 2008/09 after reforms in the subsector, including the improvement of Robusta varieties. Cooperatives struggle to sell high-end, premium coffee because of the presence of multinational companies at Tanzanian coffee auctions. These companies use the “buy-back” system, whereby they purchase coffee beans directly from local farmers, carry out primary processing and then buy them back at low prices at auction. The coffee industry faces several challenges, including lack of access to irrigation, a large number of older coffee trees, and highly volatile coffee prices, which cause dramatic fluctuations in coffee production, which is extremely price elastic. Production also suffers from the poor agricultural practices adopted by many smallholder producers, limited access to credit, lack of adequate farming inputs, and low use of inputs. However, despite these major constraints, Tanzanian coffee production is expected to increase as a result of recent market conditions and the introduction of pest- and disease-resistant coffee varieties. Consumption/utilization: Annual per capita coffee consumption in the United Republic of Tanzania is 0.06 kg; and only 4.2 percent of the country’s total coffee production is consumed domestically. Since 2003, the total quantity of coffee consumed by the domestic market has gradually declined (FAOSTAT). The Coffee Industry Development Strategy does not explicitly address the expansion of domestic coffee consumption, but instead assumes that increases in coffee consumption will be proportionate to increases in GDP. However, encouraging and promoting domestic coffee consumption could be a strategy for increasing the bargaining power of local producers, with the domestic market providing an alternative to the export market and farmers able to sell coffee at reasonable prices to local consumers. Trade and marketing: Nearly all the coffee produced in the United Republic of Tanzania is exported as green coffee with no roasting process in the country. From 2005 to 2010, Europe accounted for about 70 percent of the country’s total coffee exports, followed by Asia with 18.2 percent. North America, which means the United States of America in this case, accounted for 7.8 percent. Most coffee exports go though the Moshi auction, with a minor share following a direct export path. Value chain performance: The first stage of primary processing is carried out by producers at the farm level. This involves hand-picking red cherries and pulping on the same day, washing, fermenting, drying and packaging. Before selling, farmers grade their coffee according to the grades established by the Tanzania Coffee Board (TCfB). After primary processing, farmers transport their produce through private buyers or primary cooperatives to curing factories for secondary processing. These curing factories are operated and managed by cooperatives and a few private estate mills. At this stage, the coffee is sampled, tested and blended with other coffee, based on instructions from TCfB. After quality assessment, samples are transported to the Moshi coffee auction, located in the Kilimanjaro Region of northern United Republic of Tanzania. Following auction, the coffee is transported from regional warehouses to the port of Dar es Salaam for export. Four main purchasers account for more than 70 percent of total volume traded through the Moshi coffee auction (Promar Consulting, 2011) Producer organizations that offer high-quality or certified organic coffee and meet the requirements of the 2003 coffee regulations are eligible to make direct exports, and their coffee does not have to pass through the Moshi auction. These organizations accounted for an average of 16 percent of Monitoring African Food and Agricultural Policies (MAFAP) 111 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report export volume between 2005 and 2010. If a producer organization’s coffee does not meet the regulations’ requirements, it has to pass through the auction system for grading and sale according to its established grade. According to Ponte (2004), in 1994 there was shift in control of the coffee trade from cooperatives and/or marketing boards. This monopolistic system ensured that the coffee for the domestic market remained in “local” (mostly Tanzanian or African) hands up to auction. At the export level, smaller (mostly Asian-owned) Tanzanian export companies competed with Kenya-based exporters and the subsidiaries of multinational corporations. Adoption of the 1993 Crop Boards Act marked a profound change in the regulatory framework of Tanzanian coffee marketing, and in the 1994/95 season domestic trade was opened to private traders and processors. However, TCfB retains numerous regulatory powers, including issuing licences and running coffee auctions, allowing domestic traders to buy coffee at only authorized buying posts. TCfB does not permit farmgate buying, although this rule is not observed in some parts of the country, nor does it allow the movement of coffee from one area (southern, northern, western) to another. Liberalization of the coffee market in the URT has yielded mixed results. On one hand farmers are paid cash on delivery and receive a higher proportion of the export price than in the pre-liberalization period. On the other hand input credit schemes have collapsed, the volume of coffee exports has not improved, and there are strong indications that coffee quality has deteriorated because farmers are paid a fixed price regardless of quality. The most important effect of liberalization is foreign companies’ dramatic capture of the Tanzanian coffee market at all levels (domestic trade, processing and export) except farming, where 95 percent of coffee is still produced by smallholders. However, the true degree of liberalization is questionable, as all coffee from private buyers and any other entity must be sold through the Moshi auction run by TCfB or through direct export contracts approved by TCfB. In addition, different licensing requirements are imposed at almost every level of the value chain. Private buyers seeking to operate in the URT have to select their locations well in advance and apply to the District Executive Director to have their selection endorsed by the local committee. After completion of this process, TCfB issues the buyer with a buying licence valid for the following year. Coffee buyers have to apply for additional annual licences to engage in other aspects of the coffee trade. MAFAP indicators and interpretation: The United Republic of Tanzania is a net exporter of coffee. The main coffee commodity traded is unroasted, un-decaffeinated coffee, which is the commodity studied for this analysis. The results presented in Figure 31 indicate that farmers and, to a lesser extent, wholesalers face disincentives for production, as NRPs have been generally negative since 2005 (with the exception of the NRP for the point of competition in 2008). NRPs at the farmgate have remained more or less stable, apart from a significant increase in 2010, when international price increases were only partly transferred to domestic prices. As no export taxes are levied on coffee in the URT, the negative price gaps can be explained by general market development gaps (e.g., lack of price transmission) or malfunctioning of the value chain – the excessive access costs between the farmgate and the border. The access cost gaps from the farmgate to the point of competition are much larger than those from the border to the point of competition. Disincentives are higher when international prices rise, highlighting the lost market opportunities for coffee farmers. Regarding the adjusted domain (adjusted NRPs), the TCfB levy and Tanzania Coffee Research Institute fees represent a minor disincentive compared with other issues. 112 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 31: MAFAP nominal rates of protection for coffee in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration. Main message: Although FOB prices have been increasing steadily since 2005, the ratio of the farmgate price to the FOB price has remained stable, at about 40 percent (Figure 32). Based on the available access cost data, this means that farmers are not fully realizing the benefits they could expect from increasing coffee prices. Farmgate prices are increasing more slowly than international prices, while the variation in access costs is not sufficient to explain this lack of price transmission. As no explicit trade policies are in place, the NRPs identified are related to overall MDGs. This situation could be attributed to the pricing system of the value chain and the administration burden imposed by TCfB, which increases transaction costs in the value chain and limits new entrants. The system protects farmers when prices are low, but limits their capacity to benefit from high prices. To some extent, trade liberalization has helped improve the sector, but little is being done to ensure that small-scale farmers receive the prices they could obtain. -60% -50% -40% -30% -20% -10% 0% 10% 2005 2006 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 113 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 32: Changes in FOB and farm-gate prices for coffee in the United Republic of Tanzania, 2005 to 2010 Sources: Authors’ elaboration from UNcomtrade and TCfB data. The Tanzania Coffee Research Institute fee is of minimal importance compared with the disincentives created by the functioning of the auction system. Other inefficiencies in the value chain also play a role, including levies and charges for membership of TCfB. The burden of disincentives in the value chain lies on farmers, probably because of the market power of exporters, which have maintained a dominant position in spite of government efforts to introduce more competition in the auction system with the one-licence initiative. The government should therefore enforce the one licence system more forcefully, as major multinational companies still control coffee auctions, which leads to farmers receiving a low share of the export price. Even in the best years, farmers get only 46 percent of the export price, and still face a disincentive of nearly US$200/tonne when all access costs are considered. Facilitating the entrance of new players into the coffee auction could break the current dominance of Tanzanian coffee exports by four big companies. Cotton Cotton and coffee rank equally as the second largest agricultural exports from the United Republic of Tanzania. Most of the cotton produced by smallholder farmers is exported, contributing about 24 percent of agricultural and 4 percent of total exports. As cotton production is very labour-intensive, it provides a source of direct and/or indirect income to more than 40 percent of total Tanzanian livelihoods. The government’s Cotton Act of 1994 eliminated the monopoly of the Tanzania Cotton Board (TCtB) and the cooperative unions, and allowed competition in cotton marketing and ginning to boost production. However, deteriorating cotton seed and lint quality, low absorption of local cotton lint in the apparel and textile industries, and low investment in the weaving and yarning industries remain significant challenges for the sector. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% -400 -200 0 200 400 600 800 1,000 2005 2006 2007 2008 2009 2010 FG to FOB ratio US$/tonne Change in FOB price Change in FG price FG to FOB ratio 114 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The second Cotton Sector Development Strategy adopted in 2010/11 addresses these challenges by working with other stakeholders. Measures taken include the introduction of contract cotton farming and a specific strategy for developing the textile and garment industries to process cotton fibre and yarn locally. Production: Although subject to significant yearly shifts, the area under seed cotton production in the United Republic of Tanzania has averaged nearly 400 000 ha for the last 20 years. Production has steadily increased as yields improve, from an average of 0.46 tonnes/ha from 1990 to 1994, to 0.69 tonnes/ha in 2005 to 2009. Seed cotton is processed at ginneries to obtain cotton lint and cotton seed. Between 1990 and 2010, lint outputs were more or less stable, accounting for 34 percent of total raw cotton production, with a seed content of 62 percent and an average waste of 4 percent (FAOSTAT). Although 13 of the country’s 23 regions produce seed cotton, the vast majority of production (more than 99 percent) is concentrated in the western cotton growing area (WCGA). Most seed cotton is grown on small-scale farms with huge potential for increasing productivity. Main drawback factors include reliance on rainfed growing conditions, use of low-yielding seeds, and insufficient use of fertilizer and chemicals (Bursi et al., 2008). The hand-hoe is the most commonly used instrument in cotton farming, with some animal traction for soil preparation and during planting and weeding. The Tanzania Cotton Association promotes farmers’ use of tractors, which has contributed to the adoption of modern farming techniques. Improved seeds, developed by Ukiriguru Agriculture Research Centre, have been used in the WCGA since 1991. These seeds are more uniform, have a slightly higher ginning out-turn, and are far more drought-resistant than other varieties. The URT has potential for producing organic cotton because of its largely unspoiled soil and unpolluted environment. The demand for organic cotton is growing fast, but in the 2009/10 season organic cotton represented only 0.97 percent of total production. Nonetheless, the URT ranks fifth among the world’s organic cotton producers. Consumption/utilization: Seed cotton is used as an input exclusively by local ginneries, which separate the fibre from the seed to produce cotton lint and cotton seed. The Tanzanian ginning industry is characterized as competitive; there is competition for the purchase of seed cotton and many firms are available to buy the product (Poulton and Tschirley, 2009). There are more than 30 ginneries, with the top five alone accounting for 40 percent of total seed cotton purchases. This structure is as close as any African cotton sector has got to the competitive ideal, and allows the payment of reasonably attractive prices to producers, despite high local taxes and transport costs. However, the market structure also presents significant challenges regarding seed supply, quality control and seasonal credit (Poulton and Maro, 2009). The lint goes to the local textile industry, mainly via spinners that transform the fibre into yarn; the seed is typically used for planting, as oil for human consumption, or for animal feed. Cotton oil is sold locally, while the meal is transported to other parts of the country. Cotton oil accounts for only 8 percent of total vegetable oil production in the United Republic of Tanzania. Monitoring African Food and Agricultural Policies (MAFAP) 115 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report According to TCtB, the textile industry produces traditional fabrics, which are mainly sold in the URT and also exported to other countries in Central and East Africa; there is potential for expanding processing capacity to tap market opportunities at the regional level. Marketing and trade: The United Republic of Tanzania is a net exporter of cotton lint, cotton seed and cotton seed cake; it imports cotton seed oil. Cotton processing in the URT is not very developed, with 94 percent of exported cotton fibre products being of the least processed items: cotton not carded with 65 percent; and carded cotton with 29 percent. Products that involve further processing (yarns or fabrics) are traded in very small quantities. This suggests that the country does not make full use of its domestic production, mainly because of the low quality of the cotton lint produced, capacity underutilization and low development in the garment manufacturing industry (Baffes, 2010). The main destination for Tanzanian cotton lint is Asia. Part of lint production is consumed as raw materials for local spinning and textile firms located in the WCGA. Value chain performance: TCtB is the regulator for the cotton sector, from production to export. There are two modes of cotton production: contract and non-contract. Contract farming was introduced in 2007 in the WCGA. Farmers enter into contracts with ginneries, which provide farm inputs on credit and recover input expenses after the sale of cotton lint. TCtB oversees contract performance to protect the interests of both parts. TCtB also provides farm input subsidies to seed cotton producers, whether under contract or not. Both contract and non-contract producers set up collection points where harvested seed cotton is inspected and weighed before being packed into bales. The main challenge facing the cotton value chain is post-harvest contamination of seed cotton by farmers seeking to increase the weight of their cotton, which translates into more money per kilogram of cotton produced. The seed cotton sold to ginneries is processed to separate the seeds from the lint. Most local ginneries then process the seed into oil and animal feed cake. The cotton lint is packed and transported to the port of Dar es Salaam for export or sale to local textile mills. Two systems of ginning are practised: modern roller ginning, and the older saw ginning system. In 2008, a total of 60 ginneries were registered with TCtB, of which 14 were saw ginneries and 46 roller ginneries, with a total ginning capacity of 3 958 bales/day or shift. It should be noted that most ginneries in the United Republic of Tanzania started operation in the 1950s, and some have become fragile because of wear and tear. However, more than 17 new ones have been built – 16 in the WCGA and one in the eastern cotton growing area – since the 1990s cotton sector reforms. Of the 60 registered ginneries, only 50 percent operate throughout the production season (Bursi et al., 2008). The cotton sector is heavily taxed in the URT (Baffes, Tschirley and Gergely, 2009). Before the reforms of the 1980s, taxation of the cotton sector was administered centrally by the Prime Minister’s Office in consultation with MAFC and TCtB. Taxation includes taxes, levies and fees administered at both the district and the central government levels. MAFAP indicators and interpretation: The analysis of incentives to seed cotton growers is based on benchmark prices for cotton lint, for which the United Republic of Tanzania is a net exporter, and assumes that cotton seed attracts no incentives or disincentives. Only farmgate prices have been analysed, as there are no reliable price data for intermediate stages (e.g., ex-ginnery). The point of 116 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report competition is the border, where cotton lint from the URT has to compete with other suppliers to world markets. As shown in Figure 33, there is a clear disincentive for farmers to grow seed cotton in the URT; this disincentive was significantly reduced in 2009 before increasing again from 2010. In 2009, production was low and competition among ginners assured better prices for farmers. As soon as production peaked again in 2010, the disincentive structure returned to its average levels for the period, and TCtB promoted direct payments to farmers to compensate for the low prices. Figure 33: MAFAP nominal rates of protection for cotton in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration. Part of this disincentive is related to taxes and levies in the Tanzanian cotton market, which can exceed TSh 40 000/tonne (Poulton and Maro, 2009). Analysis results show that during the study period the disincentives were even higher than the estimated levies, but these results might be due to the analysis’s use of a ginning outturn ratio of 0.42, while the observed ginning outrun ratio is closer to 0.35. However, this low ginning ratio is also a source of disincentive to farmers, who could get better prices if the ginning outturn ratio in the URT was improved. As shown in Figure 34, in most of the years studied, the impact of lower efficiency of the ginning industry was greater than the taxes on cotton. The impact of ginning inefficiency is calculated as the difference in price differentials and access costs between the farmgate and the border,16 using FAOSTAT estimates of the ginning outturn ratio and the world standard of 0.42. 16 The analysis considers the differences between the price gaps at two points of the value chain (the border and the farmgate) and the calculated access costs, including tax. The ginning outturn ratio influences these differences in two main ways: i) the benchmark price for cotton lint is multiplied by the ratio to make it comparable with the farmgate price of seed cotton; and ii) the ratio affects the quantity of seed that needs to be used to calculate access costs. These two results are compared to identify the disincentives due to ginning inefficiency. -55% -45% -35% -25% -15% -5% 5% 15% 2005 2006 2007 2008 2009 2010 Observed Nominal rate of protection at farm gate Adjusted Nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 117 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 34: Comparison of disincentives due to ginning inefficiency and taxation of seed cotton in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration Even when the government, via TCtB, provides direct support to farmers – as either input subsidies (for insecticides in 2009) or price support (of TSh80 000/tonne in 2010) – the support remains lower than the disincentives, and the NRAs computed for these years are negative. Thus, even when the Tanzanian cotton system is presented as an example of competitiveness, TCtB and government intervention, and outdated ginning capacity result in farmers being significantly taxed or discouraged. Main message: Farmers in the cotton sector are taxed at an average of 30 percent, which limits their investment capacity. This taxation is the result of direct imposition by the government via levies from the regional and central administration, together with the costs imposed by the functioning of the different agents in the value chain. Rather than subsidizing farmers, the Government of the United Republic of Tanzania should consider reducing the tax burden on cotton production as a more efficient way of remunerating cotton growers. The low ginning outturn ratio further penalizes farmers, as the quantity of lint produced by ginners per tonne of seed cotton is lower than it could be. Modernization of ginneries should be a policy objective in the URT. The Cotton Industry Implementation Plan should include the ginning industry among its targets, and not only farmers and the textile industry. Cashew nuts Cashew nuts represent a small portion of agricultural production in the United Republic of Tanzania both in terms of cultivated area and production. Production is mainly in southern coastal regions and most is exported, making cashew nuts one of the URT’s main agricultural exports, following tobacco, coffee and cotton, representing an average of 10 percent of total agricultural exports. Cashew nut exports are subject to export tax. In 2008, a warehouse receipt system (WRS) was put in place, meaning that all cashew production has to be sold via cooperatives at auctions managed by the Cashewnut Board of Tanzania (CBT). - 20 40 60 80 100 120 140 2005 2006 2007 2008 2009 2010 Thousands TSh/tonne of seed cotton Impact of inefficiency of ginning industry Taxes levied on cotton 118 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Production: Since the early 1990s, the United Republic of Tanzania has devoted approximately 100 000 ha to cashew nut production, with an average annual production of 100 000 tonnes. The area under cashew nut increased consistently from 1961, to reach a maximum of 240 000 ha in 1973. Cashew nut production tripled during this first decade of independence (from 50 000 to 150 000 tonnes), because the additional cashew area planted took ten years to reach first harvest. The increase in production is also attributed to a stable institutional environment with private trading and strong cooperative unions. Following this peak, the planted area declined to a minimum of 35 000 ha in 1990, because of forced villagization, which moved farmers from their farms, and other factors such as inefficiencies in the marketing system (Mitchell and Baregu, 2012). In addition, all cooperative unions were replaced by centrally controlled crop authorities. Since then, area and production have recovered, but are still fall far from the maximums reached in the 1970s. The last peak in production, mainly related to increased yields, is partly attributed to farmer–buyer contracts and the WRS, which assure farmers of fixed prices at the beginning of the cropping season. Consumption/utilization: Most of the cashew nuts produced in the United Republic of Tanzania are exported; domestic consumption represents only a marginal share and processing is also limited. However, cashew nuts are consumed as a primary food item in the villages where they are produced, when prices are low relative to other food items. According to production and export data, and assuming that all the production not exported is processed for domestic consumption, since 2005, an average of only 12 percent of total production has been processed, with an estimated maximum of 30 000 tonnes in 2012 and a minimum of less than 5 000 tonnes in 2011. Annual processing capacity for cashew nuts in the URT is 136 700 tonnes at 25 plants, ranging in capacity from 300 to 12 000 tonnes each (UNIDO, 2011). However, in the 2009/10 season only nine of these plants were operational, with a total annual capacity of 42 800 tonnes, of which – according to calculations for the analysis – only 20 percent was utilized. Since the collapse of mechanical processing in the 1980s, manual processing developed in India has been adopted, but without government support it is not competitive with processing in India or Viet Nam. The URT exports about 80 percent of its raw cashew nuts. In 2009, about 7 000 workers were engaged in manual shelling and peeling of approximately 20 000 tonnes of raw nuts (Mitchell and Baregu, 2012). Marketing and trade: The main destination for exports is India, where raw cashew nuts are shelled for export or used in other food products. India is the world’s main processor of cashew nuts, with a competitive processing industry and a policy environment that fosters imports of raw cashews while protecting the internal market for processed ones by imposing a significant import tariff and value- added tax (VAT) (Mitchell and Baregu, 2012). Value chain performance: Marketing of raw cashew nuts in the United Republic of Tanzania has changed over the years, and has included direct sales from farmers to traders and delivery of raw nuts to the primary societies for marketing. Primary societies were the sole marketers of farmers’ cashew nuts from independence until 1991, when marketing was liberalized and farmers were allowed to sell to any buyer. Marketing changed again in 2007, when the private sector was no longer allowed to buy directly from farmers or primary societies and all raw cashew nuts had to be marketed through primary societies and cooperative unions at auction. Following introduction of the WRS, producers sell either in domestic markets or for export, the latter being the most important market. Monitoring African Food and Agricultural Policies (MAFAP) 119 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report When selling to primary cooperatives, farmers receive a first payment, which the cooperative normally finances with credit. The cooperatives then sell to buyers via auctions, charging a fee for their services. Cooperatives are supposed to use the income from these fees to build, upgrade and maintain storage facilities and, eventually, to provide additional services – input procurement, investment in irrigation, etc. However, irrigation is not currently used for cashew production (UNIDO, 2011). Buyers process the nuts (i.e., shelling and peeling) or export them directly. The power of exporters is limited by the concentration of purchasers in India, where two main buyers account for most purchases of raw cashew nuts (UNIDO, 2011). Olam Tanzania Limited, located in Mtwara, is currently the largest Tanzanian cashew processor, with several plants which amount to a total capacity of 25 000 tonnes per annum. Other large-scale processors are the Export Trading Company (in Tunduru) and Mohammed Enterprise (in Dar es Salaam). They have capacity for processing a maximum of 5 000 tonnes per annum. Jumbo Nut (in Dar es salaam) and Perfect Cashew Nut (in Masasi) are medium-scale, processing up to 3 000 tonnes per annum. MAFAP indicators and interpretation: Indicators in the cashew sector have been calculated for the farmgate during the whole period, and for the point of competition (auction prices as reported by CBT) since the WRS was established in 2008. The results reported in Figure 35 show that cashew nut producers faced consistent disincentives throughout the study period. Three clear points emerge. First, the export tax of 10 percent until 2010 and 15 percent from 2011 onwards reduces the prices for cooperatives (at auction) and farmers (at the farmgate). Before introduction of the WRS, in years when disincentives were transmitted along the value chain, the full tax was not passed to farmers and wholesalers, but disincentives have been higher than the export tax since introduction of the WRS. 120 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 35: MAFAP nominal rates of protection for cashew nuts in the United Republic of Tanzania, 2005 to 2011 Source: Authors’ elaboration. The second point is that introduction of the WRS has led to increased disincentives for farmers and wholesalers. This is a striking finding as lack of storage has been identified as one of the major drivers of farmer disincentives. The WRS led to increased production and raising prices for farmers. However, the divergence between the farm gate price and the potential price that could be obtained in absence of policies and with a better functioning value chain increased. This can be partly explained by the increase in the export tax, but this only happened in 2011. The main reason for disincentives increasing as of 2008 could be that the indicators were constructed using different access costs. However, Figure 36 shows that the farmgate price’s share in export prices is decreasing, so the system does not seem to benefit farmers as much as it could, even in periods of increased benchmark prices. Prices at auction seem to follow the evolution of export prices more closely, however. The problem that led to introduction of the WRS – the large number of intermediaries leading to low farmgate prices (UNIDO, 2011) – seems to remain even when intermediaries are eliminated from the chain. -50% -40% -30% -20% -10% 0% 10% 20% 30% 2005 2006 2007 2008 2009 2010 2011 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 121 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 36: Shares of FOB price represented by farm-gate and auction prices for cashew nuts in the United Republic of Tanzania, 2005 to 2011 Sources: Authors’ elaboration using NBS and CBT data. Third, the increase in export tax in 2011, which had the objective of promoting processing inside the country, led to increased disincentives for farmers without delivering the expected results. Although a year may be too short a period to evaluate this measure, figures for 2011 and 2012 show that shelled cashew nuts’ share in total cashew exports has decreased. Comparison of the income generated by export tax with the level of public expenditure for the cashew sector (Ilicic-Komorowska, Maro and Pascal 2012), illustrated in Figure 37, shows that only a small part of the total revenue from export tax is channelled back into the sector (an average of less than 10 percent). Although only 35 percent of the total revenue is transferred to the Treasury, the share of this transfer that reverts to the cashew nut sector is still less than 25 percent. In addition, 36 percent of total revenues are used as input subsidies (55 percent of the share not transferred to the Treasury), so in the most optimistic case less than 50 percent of the revenue generated by the export levy goes back to farmers. 30% 40% 50% 60% 70% 80% 90% 100% 110% 2005 2006 2007 2008 2009 2010 2011 Farm gate price as % of FOB price Farm gate price as % of auction price Auction price as % of FOB price Linear (Farm gate price as % of FOB price) 122 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 37: Revenues from the cashew export tax and public expenditure allocated to the cashew nut sector in the United Republic of Tanzania, 2005 to 2011 Sources: Authors’ calculations from Ilicic-Komorowska, Maro and Pascal (2012) and CBT data. Main message: Cashew nut growers in the United Republic of Tanzania are disincentivized, as they are receiving lower prices than they would in the absence of policy measures and with well- functioning value chains. The main driving force of these disincentives is the export tax on raw cashews. The shift towards centralized auctions and a WRS, despite increasing production and farm gate prices for farmers, has increased the level of disincentives. Rather than moving farmgate prices closer to export prices, it seems that the WRS has induced higher transaction costs. The increase in export tax from 10 to 15 percent of the FOB value to promote in-country processing has had limited effectiveness in the first two years of implementation. Moreover, the revenue generated by the export tax on cashew nuts reverts only marginally to the sector. The government could consider reducing the export tax and monitoring the evolution of indicators to see whether farmers obtain higher prices, which could lead to more investment in cashew nut production and facilitate increased processing inside the country. The government should consider alternative policy instruments to promote cashew nut processing in the URT. CBT should provide additional support to the WRS, to ensure that it delivers the expected results. Pulses Production: During the period 2005–2010, pulses were grown on approximately 1.5 million ha, accounting for 15 percent of total arable land in the United Republic of Tanzania. At average yields of less than 1 tonne/ha, approximately 1 million tonnes of pulses are produced, representing approximately 10 percent of total agricultural output in value from 2005 to 2010. Within the pulses sector, most production falls into the category of beans. Pulse production is concentrated in two areas, with approximately 30 percent in the Southern Highlands, and another 30 percent in the 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% - 5 10 15 20 25 30 2005 2006 2007 2008 2009 2010 2011 % of revenue for cashew export tax Billion TzSh Expenditure to revenue ratio Export tax revenue PE for cashews Monitoring African Food and Agricultural Policies (MAFAP) 123 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report northwest of the country. In the Southern Highlands most of the pulses produced are beans, while in the north of the country pigeon peas and chickpeas predominate. Consumption/utilization: Pulses are an important part of the diet of rural and urban dwellers in the United Republic of Tanzania, with an estimated consumption rate of 14 kg/person/year. Pulses are a relatively inexpensive alternative source of protein compared with animal or fish products (Mishili et al., 2009). National pulse consumption was calculated by adding imports to domestic supply and subtracting exports. The pulse consumption pattern is stable, at less than 1 million tonnes per year with a peak in 2006 (933 000 tonnes) and a minimum in 2008 (820 000 tonnes). Bean consumption increased from 572 000 tonnes in 2005 to 705 000 tonnes in 2009. Marketing and trade: The United Republic of Tanzania was a net exporter of pulses throughout the study period, with internationally traded volumes representing more than 10 percent of total domestic consumption. Pulses can therefore be considered an export with significant traded volumes for the URT. Over the 2005–2010 period, pea exports represented up to 90 percent of total pea production in some years, and averaged 50 percent, while bean exports accounted for an average of only 1.5 percent of bean production. More than 80 percent of pulse exports are directed to India – for all products and years. Value chain performance: Domestic trade in the United Republic of Tanzania is based mainly on long-term personal relationships, which are seen as the only functional way of trading given the absence of adequate market information and the weak legal framework for enforcing contracts. The supply chain from the producer to the final consumer is therefore long and follows various routes. Pulses flow from the northern zone to the regional market centres of Arusha and Moshi, from where they move northwards to Nairobi, through Namanga border point. Other stocks flow to Mombasa (via Taveta), Tanga, Dar es Salaam and Zanzibar. Most farmers (92.1 percent) produce dry pulses for local markets, while only 7.9 percent produce for the export market. MAFAP indicators and interpretation: The analysis of incentives and disincentives for pulses in the United Republic of Tanzania is based on the prices available for peas, which are the most traded pulse crop. Because of limited data availability, indicators have been calculated for only the farmgate level. The results presented in Figure 38 show that during the study period pea producers have been incentivized, as the prices paid in the country were higher than those received at export markets. The same results hold when the analysis uses data for beans, which are the most widely produced pulse in the URT. As bean prices at the point of competition are available, it is also possible to see that incentives are also present at the wholesale level, showing that the prevailing prices paid by consumers are also higher than those received by exporters. 124 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 38: MAFAP nominal rates of protection for peas in the United Republic of Tanzania, 2007 to 2010 Source: Authors’ elaboration. This situation implies that exporters face losses. However, as shown in Figure 39, the overall incentives identified by the indicators mask the seasonality of results, with exports in 2007, 2008 and 2009 showing a theoretically sound situation17 for at least part of the year. This is not the case for 2010, for which domestic price data are missing for the harvest months when prices are lowest. 17 A theoretically sound situation is one in which farmgate prices are equal to or lower than the reference price for the farmgate level. In such a situation the market works as expected, with actors along the value chain being able to purchase the commodity and transfer it to the next point in the value chain covering all costs. -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 2007 2008 2009 2010 Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 125 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 39: Price comparisons for peas in the United Republic of Tanzania, 2005 to 2010 Sources: UNcomtrade for FOB price; International Monetary Fund (IMF) for exchange rate; MTI for domestic prices; and MAFAP for reference price. Main message: Based on analysis of the bean and pea markets in the United Republic of Tanzania, it can be concluded that – overall – farmers obtain higher prices than those in international markets. However, this apparent incentive to producers hides a situation in which lack of storage facilities forces farmers to sell at low prices (post-harvest), resulting in prices in later periods of the season that are higher than those obtained from export. Basically, these results show that the URT faces high domestic prices for pulses, putting additional pressure on net food buyers. In this situation two strategies could be followed: i) increasing the linkages among different markets in the country could allow consumers to purchase pulses at lower prices and traders to obtain larger profits from the domestic market than from exports – particularly with beans, where price gaps are higher; and ii) increasing farmers’ storage capacity would allow them to capture higher prices in domestic markets. Indicators for thinly traded products This category includes only one of the commodities analysed – maize. However, some of the commodities currently under analysis (cassava, sorghum and livestock) also fall under this category, and analyses of them, individually and as a group, will be provided in the future. - 100 200 300 400 500 600 700 800 900 Thousand TSH/tonne Country average Benchmark price Reference price at farm gate level 126 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Maize18 Maize was the United Republic of Tanzania’s fifth agricultural commodity by value of production for the period 2005–2010, accounting for 7.5 percent of total production value. It also represented nearly 5 percent of total agricultural imports for the same period, and was the main source of dietary energy, accounting for 25 percent of total caloric intake (FAOSTAT, 2010). Maize is considered the most important food crop in the URT, covering 45 percent of total arable land and generating nearly 50 percent of rural cash income, with an average of US$100 per maize producing household in 2008 (USAID, 2010). In the past two decades, the URT has ranked among the top 25 maize producing countries in the world, dropping out of this list only three times, in 1986, 1997 and 2003. Production: The United Republic of Tanzania produces mainly white maize. Area planted to maize peaked in 2003, at nearly 3.5 million ha, and has since stabilized at about 2.5 million ha. Production is also more or less stable, at about 3.5 million tonnes, while yields fluctuate from 1 to 1.5 tonnes/ha, down from an average of nearly 2.5 tonnes/ha in 2000–2002. In the 2005–2010 period, maize accounted for more than 70 percent of domestic cereal production. According to MAFC, more than 20 regions in the URT produce maize. The southern regions of Iringa, Rukwa, Ruvuma and Mbeya account for more than 35 percent of total production; the Southern Highlands produce a maize surplus, while there are deficits in the Northern Highlands, Dar es Salaam and central regions. Of the approximately 3 million households in the URT, 65 percent grow maize. Most of these producers are poor smallholder farmers, with an average of 1.2 ha each, relying on traditional methods of cultivation under a rainfed regime (USAID, 2010; Nazir et al., 2010). Approximately 30 percent of all households sold surplus maize in 2009 (NBS, 2009). Consumption/utilization: According to FAOSTAT commodity balances, most of the maize produced in the United Republic of Tanzania goes to food consumption, with average waste of 10 percent. Feed represents 17 percent of total production. Maize food availability per capita has been decreasing steadily since 2000, from 70 kg/person/year to 60 kg in 2007, mainly because of the increased use of maize for feed. Maize is the main staple food and is consumed by most households in both rural and urban areas. Maize seed is usually processed into flour and mixed with water to make porridge or ugali (stiff porridge). Maize consumption is also increasing because the school feeding programme uses maize porridge or ugali as the main component of the meals provided to primary school students. The programme offers three meals from morning to evening and reaches more than 1 064 primary schools across the country. Marketing and trade: Although it is commonly believed that the United Republic of Tanzania is a major maize exporter, official data show that maize was a major agricultural import from 2004 to 2008. From 2000 to 2009, trade intensity (defined as total trade over production) averaged 4 percent, although there has been a decreasing trend since 2006, making trade very thin. This need to import maize seems to contradict the widely held view that the URT could be one of the breadbaskets of East Africa, with the production potential to feed deficit neighbouring areas. During the 2005–2010 period, more than 70 percent of maize imports came from the United States of America and Mexico, with only a minority coming from partners in the EAC (12 percent from Uganda and Kenya). Nearly 45 percent of maize exports go to Kenya, and more than 55 percent to other EAC countries, but the URT imposed export bans on maize throughout much of the study period. The government 18 A more detailed presentation of the maize market in the URT can be found in Part 3 of the report. Monitoring African Food and Agricultural Policies (MAFAP) 127 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report normally imposes these bans in response to a bad harvest or price peaks, to avoid the diversion of maize to Kenya, where prices are significantly higher. Export bans generate uncertainty for economic agents (and it is not always clear whether they are in place or not), have impacts on investments and reduce price incentives at the farmgate (World Bank, 2009). Informal trade seems to be significant for maize in the URT. Although no official statistics exist, an idea of the magnitude of informal trade can be obtained from comparison of the maize trade data reported by the URT and Kenya. The discrepancy between the URT’s declared exports and Kenya’s declared imports is neither consistent nor systematic: in some years, the URT reports more exports to Kenya (2008 and 2005), while in others Kenya reports more imports from the URT ( 2010, 2009 and 2007). This situation is not reflected in the net trade position of maize in the URT, as the country was a net importer in 2008 and a net exporter in 2005. The importance of unrecorded trade seems to be increasing, with estimates for 2011 showing that actual trade might be more than 50 times higher than reported trade (Stryker, 2012). Value chain performance: Maize production in the United Republic of Tanzania is mainly in the Southern Highlands, which sends production surpluses to Dar es Salaam and, to a lesser extent, Zambia, Malawi and the Democratic Republic of the Congo. A second major producing area is in the north of the country, from where surpluses go to Kenya, mainly via informal trade. The main markets for Tanzanian maize are Dar es Salaam (and by extension Zanzibar and Comoros), the Mtwara-Linid Region (southeast), northern cities such as Arusha and Moshi and via export to EAC partners. The main trading market is Dar es Salaam, which is the only market where brokerage between millers and traders takes place (SAGCOT, 2010). Approximately 40 percent of total maize production is marketed. Three main types of agent in the value chain purchase maize from farmers: private traders, the Cereals Board and Other Produce Board, and the National Food Reserve Agency (NFRA). Taking into account the marketed and production volumes and the purchase data available from NFRA and the Cereals and Other Produce Board, the role of public interventions in the market remains low, at less than 10 percent of apparent consumption. However, this role can be significant when compared with marketed volumes. The maize marketing system is characterized by a very large number of small traders operating from both the main production centres and major urban areas. Produce from the farm is taken to primary markets (i.e., large markets in producing areas) directly by the farmer or by intermediaries who purchase the maize at the farm. Marketing channels are characterized by slow brokerage services in village, district and national urban markets (Match Maker Associates, 2010). Market margins are generally quite high, implying inefficiencies in supply chains. Prices vary greatly between seasons (during harvest and periods of scarcity), post-harvest losses are quite significant, and productivity levels are low. Several price transmission analyses of maize in the URT suggest that domestic maize markets were not integrated with international markets in the 2003–2007 period (Minot, 2010b), while other sources suggest that internal markets were integrated during the period 2000–2008 (Ihle and von Cramon-Taubadel, 2010). MAFAP indicators and interpretation: Results are reported for the farmgate level for the period 2006–2010 and for the wholesale level for 2005–2010 (Figure 40). Results need to be treated with caution as the lack of market integration for maize in the United Republic of Tanzania (World Bank, 2009) makes aggregate figures, such as those provided here, unrepresentative for all areas. Additional disaggregated analysis of incentives and disincentives by production area is provided in Part 3. With the exception of 2007, farmers faced disincentives for growing maize in the study 128 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report period. This means that the price they obtained for their product was less than they would have received in the absence of policy and with better market performance. This situation is the result of explicit policy decisions and the lack of market integration for maize. In years when the URT was a net importer of maize (2006, 2008 and 2010), in spite of the 50-percent tariff on maize imports from outside the EAC, domestic prices were below reference prices. This situation can be attributed to subsidized maize sales by NFRA. Analysis by Nyange and Wobst (2005) shows that markets respond differently to food reserve interventions, trade and regional production, depending on their nature. While procurement increases maize prices in production areas, this effect is reversed when the stock is released; in other words, NFRA support to producers is only temporary during procurement. Therefore in years when the URT was a net importer, disincentives were mainly related to NFRA releases, suggesting that affordable prices for net buying households are the main policy objective. Alternative ways of supporting vulnerable households that would be less distorting for maize markets – such as cash-based programmes – have been proposed (Christensen and Cochrane, 2012) and should be considered. As the net importing position of the URT could mask illegal exports to overcome export bans, the analysis results support the view of other studies (Diao, Mabiso and Kennedy, 2012) that these trade restrictive measure have a negative impact. In addition, high access costs represent a barrier to free trade as they raise the cost of imported maize. Simplifying import procedures and reducing other marketing costs would increase the competitiveness of imported maize and, given current domestic prices, reduce producers’ disincentives. Both wholesalers and producers currently receive less support (more disincentives) than they would under more efficient import procedures. On the other hand, measures to reduce access costs between production zones and wholesale markets are likely to improve incentives to producers by increasing the competitiveness of domestic maize in the long run, as domestic prices adjust to world prices. Figure 40: MAFAP nominal rates of protection for maize in the United Republic of Tanzania, 2005 to 2010 Source: Authors’ elaboration. In years when the URT was a net exporter of maize (2005, 2007 and 2009), the export ban had a negative impact on the prices received by farmers – in 2009 mostly in the northern highlands. -40% -30% -20% -10% 0% 10% 20% 30% 40% 2005 2006 2007 2008 2009 2010 Observed nominal rate of protection at point of competition Adjusted nominal rate of protection at point of competition Observed nominal rate of protection at farm gate Adjusted nominal rate of protection at farm gate Monitoring African Food and Agricultural Policies (MAFAP) 129 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Analysis results do not reflect this finding as they are based on a benchmark price from outside the region, owing to the low reported trade volumes. Assuming that Kenya is the destination of illegal exports, the export ban would generate significant disincentives to farmers in the region. In 2005, the export ban led to prices in the URT being higher than they would be in the absence of policy measures. This means that the export ban gave a wrong signal to traders who thought prices in Kenya would be higher and increased informal exports. This reduced domestic supply and resulted in maize prices in northern producer areas of the URT higher than those that could be obtained in Kenya. As no farmgate price is available for 2005, it is unclear whether this higher price observed in wholesale markets was also received by farmers. The situation in 2007 seems different, with lack of storage capacity leading to exports when prices are low and resulting in higher domestic prices in the country. More detailed information on export and production data (i.e., monthly data) would enable verification of this hypothesis. Main message: Incentives and disincentives to maize producing farmers are very volatile. The disincentives for this commodity are explained by the mix of variable policy decisions (trade restrictions, subsidized sales) and the lack of market integration in the United Republic of Tanzania due to excessive transport costs. Overall, farmers are getting lower prices than would be attainable in the absence of policy and with better market performance. Trade restrictions should be lifted as they provide wrong signals to traders and depress prices for farmers. Food affordability concerns for specific consumer groups should be addressed by a less distorting measure than subsidized sales. Market integration should be fostered with more investments in storage and transport infrastructure. Indicators for commodities important for food security As shown in Figure 41, overall, producers of commodities representing a significant share of the diet in the United Republic of Tanzania had diminishing incentives throughout the study period. These reductions are the result of trade policy for imported products (rice, wheat), lack of market integration and storage (pulses) and a volatile policy environment (maize). For consumers, declining incentives lead to increased food bills, reducing the affordability of food. Analysis results therefore show how incentives have conflicting impacts on food security. Incentives for farmers can foster increased investment and production, as is particularly visible for rice, in which the URT has gone from being an importing country to a net exporter. For other commodities, however, incentives do not seem to have a positive impact on domestic food availability, and incentives for producers translate into reduced affordability for consumers. Domestic prices are higher than those that would prevail in the absence of policy interventions and with functioning markets. This situation is aggravated in the sugar cane sector, where growers face disincentives and the import tariff makes wholesale prices higher than they would be in the absence of policy . 130 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 41: Average observed and adjusted nominal rates of protection and market development gaps for commodities important for food security in the United Republic of Tanzania, 2005 to 2010 Commodities included are sugar, wheat and rice for the whole period; maize since 2006; and pulses since 2007. Source: Authors’ elaboration. Conclusions There is a clear dichotomy in the MAFAP analysis results between commodities for which the United Republic of Tanzania is a net importer (milk, rice, sugar and wheat) and those for which it is a net exporter (cashew nuts, coffee, cotton and pulses) (Figure 42). While policies provide incentives to producers of import products, export products face disincentives resulting from policies, traders’ market power, and processing inefficiencies. Levels of incentives and disincentives have been declining. For imports, this decline is due mainly to the move to rice exporter status since 2010, which has brought prices in the URT closer into line with international prices. In addition, the URT partially waived tariffs on imported commodities in 2008, although this measure has been less effective than expected as domestic prices have remained higher than benchmark prices. The situation for exports masks a difference between classic exports (cashew nuts, coffee and cotton), which remain penalized, and pulse exports, which are affected by a lack of storage capacities, leading to the collapse of domestic prices at harvest time, when it becomes profitable to export, and price peaks to above export prices later in the season. Results for thinly traded commodities oscillate between incentives and disincentives owing to policy and market volatility. -20% 0% 20% 40% 60% 80% 100% 120% 140% 160% 2005 2006 2007 2008 2009 2010 MDG Average observed NRP for products important for food security Average adjusted NRP for products important for food security Monitoring African Food and Agricultural Policies (MAFAP) 131 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 42: Observed nominal rates of protection for the agriculture sector and by commodity group in the United Republic of Tanzania, 2005 to 2010 Commodities in each group are listed in Table 14. Source: Authors’ elaboration. The limited data available did not allow identification of the MDG for each domain. Differences between observed and adjusted indicators (Figures 42 and 43) are the result of lower margins along the value chain (5 versus 10 percent of the purchase price), lower costs for import and export procedures, lower transport costs, and the removal of local taxes.19 The average MDG represents an additional disincentive of 7 percent for export commodities, an additional incentive of 2 percent for imported commodities,20 and an additional disincentive of 2 percent for thinly traded products. For commodities that represent a significant share of the Tanzanian diet, MDGs imply that farmers face an additional 3 percent disincentive. However, in general, the impacts of MDGs in the URT are smaller than the impacts of policy and market performance incentives or disincentives in the observed domains. As incentives or disincentives for a commodity are reduced, the weight of the 19 Local taxes are levied from the farmgate to the wholesale market. In the analysis, the farmgate prices for rice, maize, wheat and pulses are approximated from wholesale prices in the main producing areas, while for milk only wholesale indicators are calculated, so the impact of local taxes is considered for only the other four commodities. 20 Calculation of the MDG for imports implies identifying additional incentives to imported products. If the access costs from the border to the point of competition are excessive, the reference prices at the point of competition will be higher than the adjusted ones. When adjusted (lower) access costs are considered, the divergence between the domestic price and the reference price increases, thus the incentive measured by NRP also increases. -50% 0% 50% 100% 150% 200% 2005 2006 2007 2008 2009 2010 Average observed NRP for the agricultural sector Average observed NRP for imported products Average observedc NRP for exported products Average observed NRP for thinly-traded products Average observed NRP for products important for food security 132 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report MDG increases. However, as discussed previously, other issues that could be considered part of the MDG drive a significant part of the observed indicators. Figure 43: Adjusted nominal rates of protection for the agriculture sector and by commodity group in the United Republic of Tanzania, 2005 to 2010 Commodities in each group are listed in Table 14. Source: Authors’ elaboration. -50% 0% 50% 100% 150% 200% 2005 2006 2007 2008 2009 2010 Average adjusted NRP for the agricultural sector Average adjusted NRP for imported products Average adjusted NRP for exported products Average adjusted NRP for thinly-traded products Average adjusted NRP for products important for food security Monitoring African Food and Agricultural Policies (MAFAP) 133 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 7. Public expenditure and aid Box 3 provides a summary of the analysis results regarding public expenditure and aid. Box 3: Summary of results regarding public expenditure and aid in the United Republic of Tanzania In the United Republic of Tanzania, between 2007 and 2011, although the approved budget for the agriculture sector grew by 53 percent in nominal terms, in relative terms agricultural budget allocations declined from almost 13 percent of total government spending to about 9 percent. Actual spending grew more slowly, and decreased significantly in relative terms. Thus, although total expenditure surpassed the 2003 Maputo Declaration target during the period 2007–2009 it has remained below that level since then. Agriculture-specific expenditures account for an average of almost 45 percent of total expenditures in support of food and agriculture sector development. Their importance in overall agricultural support grew from about 29 percent in 2007 to 64 percent in 2011. In terms of spending levels, agriculture-specific expenditures more than doubled over the period analysed, while agriculture-supportive expenditures decreased significantly. During the period of analysis agriculture-specific support has shifted from general support to payments to agents. General support expenditure accounted for more than 60 percent of all agriculture-specific expenditure in the first half of the period analysed; however increased focus on payments to producers via input subsidies meant that this share declined to less than 50 percent in the second half of the period. The increase in direct transfers to producers has led to decreases in key areas such as extension services and general infrastructure for the sector, such as storage facilities and marketing infrastructure. Agriculture-supportive expenditures account for an average of about 55 percent of overall support to the food and agriculture sector in the URT. However, their relative importance in total support to agriculture has decreased over time. Among these expenditures, by far the largest are for rural infrastructure, including roads, water and sanitation and energy. Their relative importance in total agriculture-supportive expenditures has not changed over time. Far less expenditure is devoted to rural health or rural education. Overall, most public expenditures are directed to the provision of public services and investments, with a relatively strong focus on infrastructure but also on training, extension services and research. However, spending on input subsidies for agricultural producers is growing rapidly, particularly subsidies for variable inputs. Only 4 percent of public expenditure for the agriculture sector is targeted to commodities: nearly half of this amount targets commodities in general rather than any specific commodity or group of commodities; approximately one- quarter is directed to maize and rice (mainly via the fertilizer subsidy); and the remaining quarter goes to very broad commodity groups. A large share of expenditure is allocated to policy administration costs. The increased share of administration costs after 2008/09 may be partially explained by the reallocation of funds for policy transfers to manage the financial crisis, but administration costs have increased substantially throughout the period analysed. Moreover, the rates of actual spending to budget allocation are low, with policy transfers having even lower rates than administration costs. On average, donor spending accounts for at least 50 percent of overall public expenditure in support of the food and agriculture sector in the URT. However, the role of foreign aid followed a diminishing trend over the period analysed. External aid contributed 44 percent of total agriculture-specific expenditure and 64 percent of agriculture-supportive expenditure. Donor and government priorities for allocating public expenditure are fairly well aligned with each other. Monitoring African Food and Agricultural Policies (MAFAP) 135 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Introduction The government policy levers likely to influence agricultural development are not restricted to policy measures affecting prices (taxes, quotas etc.). The government can also use the budget as a tool for allocating spending to various sectors of agricultural development. This section of the report seeks to improve understanding of public expenditure in the United Republic of Tanzania. The aim is to provide policy-makers and development stakeholders with fuller knowledge of public spending, especially its breakdown, and to respond to often unanswered questions regarding which development and sector activities receive the most support, the share of aid in total expenditure, administration costs, and actual levels of disbursement. The analysis covers the whole of government expenditure and development aid for the agriculture sector in the URT: projects, programmes and administration costs, as documented by the Ministry of Finance and Economic Affairs (MoF). Data was obtained from revising the budget books published each year by the Ministry of Finance and Economic Affairs (MoFEA, several years). For each fiscal year the data for all expenditure related to agriculture and rural development was identified and classified according to the MAFAP methodology. The analysis goes beyond the more common analyses of public expenditure in support of agriculture by also considering expenditure by other ministries – such as the Ministry of Energy and Minerals, the Ministry of Education and Vocational Training, the Ministry of Health and Social Welfare, the Ministry of Infrastructure Development and the Ministry of Natural Resources and Tourism – and other budget items in support of any programme or project related to agriculture and/or rural development. The analysis uses concepts, terminology and definitions described in the MAFAP methodology for measuring public expenditures in support of food and agriculture sector development. Some of the most important of these definitions are provided in Box 4, while Annex I provides a brief summary of the main concepts. Readers seeking more details about the methodology are invited to refer to Komorowska (2010). 136 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Box 4: Definitions of terminology used in the MAFAP analysis Public expenditures in support of food and agriculture sector development: All the public expenditures that are undertaken in support of food and agriculture sector development financed from the national budget, either central or regional government, regardless of the ministry implementing the policy; and from external aid, provided through either local governments or specific projects conducted by international organization or non-governmental organizations. They are composed of agriculture-specific expenditures and agriculture-supportive expenditures. Agriculture-specific expenditures: All the public expenditure measures that generate monetary transfers to agricultural agents (producers, consumers, input suppliers, trades, processors and transporters) or the sector as a whole (e.g., in the form of research, extension services, etc.). Agriculture-supportive expenditures: Public expenditure measures that are not strictly specific to the agriculture sector, but that have a strong influence on agricultural development, such as rural education, rural health and rural infrastructure (energy, water and sanitation, roads, etc.). Support to individual commodities: Public expenditures that directly target specific individual commodities such as rice or cotton. Support to groups of commodities: Public expenditures that directly target specific groups of commodities such as crops or livestock. Support to all commodities: Public expenditures that do not target specific individual or groups of commodities, but that benefit any food and agricultural activity. General trends in public expenditure Analysis of the total budget approved for the United Republic of Tanzania reveals an almost constant upward trend over the period 2006–2011 (Figure 44). During this period, the country’s budget saw an overall increase of 31 percent, rising from TSh 4 788 billion in the 2006/07 financial year to TSh 10 770 billion in 2010/11. Similar trends are observed in levels of actual disbursements, although there was a increasing gap between the approved budget and actual disbursements, from 1 percent in 2006/07 to nearly 12 percent in 2010/11.21 Taking into account inflation in the URT, which has been increasing in recent years, the budget in constant terms saw a decrease in 2010/11 (Figure 45) 21 Data for financial year 2010/11 were provisional at the time of writing, so the disbursement rate could rise. In 2009/10 this rate was 92 percent. Monitoring African Food and Agricultural Policies (MAFAP) 137 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 44: Evolution of total budget for the United Republic of Tanzania, 2006/07 to 2010/11 (current TSh) Source: Authors’ elaboration based on MoF (several years). Figure 45: Evolution of total budget for the United Republic of Tanzania, 2006 to 2010 (constant 2007 TSh) Sources: Authors’ elaboration based on MoF (several years) and IMF (consumer price index) data. 4,789 5,998 7,192 8,881 10,770 4,762 5,209 6,812 8,174 9,439 0 2,000 4,000 6,000 8,000 10,000 12,000 2006/07 2007/08 2008/09 2009/10 2010/11 billion TSh Budgeted Disbursed 4,789 5,439 5,816 6,762 5,813 4,762 4,724 5,508 6,223 5,095 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 2006/07 2007/08 2008/09 2009/10 2010/11 billion TSh Budgeted Disbursed 138 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report General trends in public spending in support of agriculture The total approved budget22 in support of the agricultural and food sector grew by 53 percent in nominal terms from 2006/07 to 2010/11, reaching TSh 944.5 billion (Table 23). The peak of budget allocations occurred in the 2009/10 financial year, with TSh 1 198.9 billion allocated to support agriculture. Total actual spending has grown more slowly, increasing by 30 percent from 2006/07 to 2010/11, to reach TSh 728 billion, although the highest actual spending value falls in the 2007/08 financial year, with TSh 878.4 billion spent. Table 23: Total public expenditures in support of the food and agriculture sector in the United Republic of Tanzania, 2006/07 to 2010/11 2006/07 2007/08 2008/09 2009/10 2010/11p % change 2006/07– 2010/11 billion TSh Budget allocation 616.0 891.7 1 143.3 1 198.9 944.5 53 Actual spending 584.5 878.4 825.1 759.3 728.0 30 Exchange rate1 (TSh per US$) 1 245 1 196 1 320 1 409 1 572 1 Exchange rates are the annual averages for the calendar years 2007 to 2011. Sources: Authors’ calculations based on MAFAP public expenditure database for the URT and WDI, 2012. In the African context public expenditure is support of agriculture has gained significant attention due to the Maputo Declaration. The Maputo Declaration refers to the Declaration on Agriculture and Food Security in Africa adopted during the African Union Summit held in Maputo from the 10th to the 12th of July 2003. , Maputo, Mozambique. In this declaration it is stated that “We, the Heads of State and Government of the African Union (AU), assembled in Maputo at the Second Ordinary Session of the Assembly, 10 to 12 July, 2003 (…) agree to adopt sound policies for agricultural and rural development, and commit ourselves to allocating at least 10% of national budgetary resources for their implementation within five years”. There is no consensus as to what has to be counted when measuring the achievement of this target. From a strict reading of the text of the declaration one can see that rural development is one of the policies to which 10 per cent of the national budget resources should be allocated. This implicitly considers the wide definition of the agriculture and food sector used for classifying public expenditure under MAFAP. 22 Total agricultural expenditures (budget allocations and actual spending) include policy transfers in support of agriculture and policy administration costs, funded from both national resources and foreign aid. Monitoring African Food and Agricultural Policies (MAFAP) 139 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report However, most ot the documents of the Comprehensive Africa Agriculture Development Programme (CAADP) seem to have narrowed the scope of this commitment to a narrow understanding of agriculture. For example when describing the goal of CAADP its webpage states “Overall, CAADP's goal is to eliminate hunger and reduce poverty through agriculture. To do this, African governments have agreed to increase public investment in agriculture by a minimum of 10 per cent of their national budgets and to raise agricultural productivity by at least 6 per cent” Source: http://www.nepad-caadp.net/about-caadp.php The CAADP Implemention Guide also takes this approach towards understanding the Maputo Declaration when it states that: "Within this context, CAADP's specific objective is to support country- driven agricultural development strategies and programmes by: establishing clear commitment to deliver on specific targets, including investing 10% of national budgets in the agricultural sector...” (CAADP, 2010: page 4). Different definitions of this restricted approach are being used by other initiatives such as RESAKSS and the World Bank when measuring public expenditure in Africa. In this sense one of the added values of the analysis undertaken by MAFAP is that it allows to monitor the achievement of the Maputo target under different assumptions. Below we discuss the progress towards this target using the two assumptions; that proposed by the MAFAP project and that assumed by CAADP. MAFAP as a project considers that measuring against the Maputo Target should include ALL categories reflected in Annex I. Following this approach budget allocations in support of the agricultural and food sector declined from almost 13 percent of total government spending in 2006/07 to about 9 percent in 2010/11 (Figure 46a). Actual spending in relative terms also decreased significantly in the period analysed. The highest shares of expenditures in support of the agricultural and food sector with regards to total budget expenditures occur in the 2007/08 financial year both in terms of both budget allocations and actual spending, which reached 15 and 17 percent respectively. Since then, the importance of agriculture in total government expenditures has been constantly decreasing. 140 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 46a: Public expenditures in support to the food, agriculture and rural development sector as shares of total government expenditures in the United Republic of Tanzania: planned versus actual spending, 2006/07 to 2010/11 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. If we want to measure the achievement of the Maputo Target using the approach followed by CAADP then only Category I (agriculture specific policies) of the MAFAP pulbic expenditure classification should be used. Under this approach during the study period expenditure levels in the United Republic of Tanzania fell below the Maputo Declaration targets for both budgeted amounts and actual expenditure, except for budgeted amounts in 2009/10 (figure 46b). The difference between results using the MAFAP definition of support to the agriculture sector and those using the traditional definition shows a declining trend, mainly due to decreased allocations to agriculture- supportive policies (Figure 47). 0 2 4 6 8 10 12 14 16 18 2006/07 2007/08 2008/09 2009/10 2010/11p % support to agriculture - budget allocations (% of total)-MAFAP definition support to agriculture-actual spending (% of total)-MAFAP defintion Maputo declaration target Monitoring African Food and Agricultural Policies (MAFAP) 141 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 46b: Public expenditures in support to the agriculture sector as shares of total government expenditures in the United Republic of Tanzania: planned versus actual spending, 2006/07 to 2010/11 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. 0 2 4 6 8 10 12 14 16 18 2006/07 2007/08 2008/09 2009/10 2010/11p % support to agriculture - budget allocations (% of total) - Narrow defintion support to agriculture - actual spending (% of total) - Narrow defintion Maputo declaration target 142 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 24: Public expenditures in support of the food and agriculture sector in the United Republic of Tanzania: actual spending, 2006/07 to 2010/11 billion TSh 2006/07 2007/08 2008/09 2009/10 2010/1 I. Agriculture-specific policies 161.0 224.1 272.0 425.8 506.1 I.1. Payments to agents in the agrofood 54.5 67.7 126.0 240.9 211.2 I.1.1. Payments to producers 49.6 62.6 122.8 236.8 207.9 A. Payments based on output 0.0 0.0 0.0 0.0 0.0 B. Input subsidies 44.7 62.3 120.3 229.6 207.4 B1. Variable inputs 32.1 41.6 81.9 197.6 181.0 B2. Capital 11.9 15.8 22.6 21.4 18.9 B3. On-farm services 0.6 5.0 15.7 10.7 7.5 C. Income support 0.0 0.0 0.0 0.0 0.0 D. Other 5.0 0.2 2.6 7.2 0.5 I.1.2. Payments to consumers 0.0 0.0 0.0 0.0 0.0 E. Food aid 0.0 0.0 0.0 0.0 0.0 F. Cash transfers 0.0 0.0 0.0 0.0 0.0 G. School feeding programmes 0.0 0.0 0.0 0.0 0.0 H. Other 0.0 0.0 0.0 0.0 0.0 I.1.3. Payments to input suppliers 0.0 0.0 0.0 0.0 0.0 I.1.4. Payments to processors 4.8 5.1 3.2 4.1 3.3 I.1.5. Payments to traders 0.0 0.0 0.0 0.0 0.0 I.1.6. Payments to transporters 0.0 0.0 0.0 0.0 0.0 I.2. General sector support 106.5 156.4 146.0 184.9 294.9 I. Agricultural research 18.7 38.8 48.9 54.2 59.0 J. Technical assistance 0.0 0.0 0.0 0.0 0.0 K. Training 28.8 59.9 44.7 57.4 171.1 L. Extension 15.1 24.4 22.2 21.8 19.8 M. Inspection (veterinary/plant) 0.7 0.4 1.2 2.7 2.3 N. Infrastructure 1.3 3.2 4.8 4.1 3.6 O. Storage/public stockholding 25.1 6.7 0.8 1.0 0.8 P. Marketing 6.2 11.0 13.6 9.0 7.3 R. Other 10.6 12.0 9.7 34.7 31.0 II. Agriculture-supportive policies 392.9 598.9 473.9 204.4 307.2 S. Rural education 115.3 90.0 42.7 29.1 34.2 T. Rural health 50.0 68.1 130.9 67.4 90.5 U. Rural infrastructure 227.3 439.5 299.2 106.6 180.8 U1. Roads 125.7 289.7 245.6 28.3 124.9 U2. Water and sanitation 34.8 104.8 49.1 24.3 24.4 U3 Energy 66.8 45.1 4.5 52.0 31.3 U4 Other 0.0 0.0 0.0 2.0 0.3 V. Other 0.4 1.4 1.1 1.4 1.6 III. Total expenditures in support of the 553.9 823.1 746.0 630.2 813.3 See Annex I for definitions of categories and Annex II for specific programs and projects included in each category. P Composition of public expenditures in support of the food and agriculture sector Data collected at the country level allow good disaggregation of the expenditures funded from national resources and foreign aid and allocated to the agriculture sector. About 170 projects and Monitoring African Food and Agricultural Policies (MAFAP) 143 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report programmes have been identified and classified into the MAFAP categories outlined in the project methodology (Balie et al., 2010). The data collected cover the period 2006/07 to 2010/11, but for many of the expenditure measures there were no data on actual spending for the most recent year. In such cases, estimation methods have been applied provisionally, until the most recent data are obtained.23 The results are shown in Table 24. Annex II provides a detailed description of each of the projects and programmes that have been classified for each category. Agriculture-specific expenditures account for an average of almost 45 percent of expenditures in support of food and agriculture sector development. Their importance in overall agricultural support grew from about 29 percent in 2006/07 to 64 percent in 2010/11. In terms of spending level, agriculture-specific expenditures more than doubled over the period analysed, while agriculture- supportive expenditures decreased significantly (Figure 47). Figure 47: Composition of expenditures in support of the food and agriculture sector in the United Republic of Tanzania: actual spending, 2006/07 to 2010/11 P = provisional. Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Among agriculture-specific expenditure measures, about 60 percent were in the general sector support category. In the first part of the period analysed – 2006/07 to 2007/08 – the largest share of these expenditures fell into the training category (Figure 48). Other important categories included agriculture research, extension and storage. Far less was spent on marketing (including related infrastructure), infrastructure and inspection. There were no expenditures on technical assistance. In the second part of the period analysed – 2008/09 to 2010/11 – the composition of general sector support was slightly different (Figure 49). Expenditures on training, research, inspection, infrastructure and marketing accounted for similar proportions of agriculture-specific spending. 23 The full database is available on request. 0 100 200 300 400 500 600 700 800 900 2006/07 2007/08 2008/09 2009/10 2010/11p Billion TSh I. Agriculture-specific policies II. Agriculture-supportive policies 144 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report However, extension services accounted for a smaller share of agriculture-specific spending, while expenditures on storage became almost insignificant. Figure 48: Composition of agriculture-specific spending in the United Republic of Tanzania, averages for 2006/07 to 2007/08 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Figure 49: Composition of agriculture-specific spending in the United Republic of Tanzania, averages for 2008/09 to 2010/11 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. On average, payments to agents in the agrofood sector accounted for the remaining 40 percent of agriculture-specific expenditures (Figures 48 and 49). Within this category, most expenditures were payments to producers in the form of input subsidies, particularly for variable inputs, and their importance increased over time, mostly because of implementation of NAIVS. Payments to producers - input subsidies 27.8% Payments to producers - other 1.4% Payments to processors 2.6% Agricultural research 14.9% Training 23.0% Extension 10.3% Inspection (veterinary/plant) 0.3% Infrastructure 1.2% Storage 8.3% Marketing 4.5% Other 5.9% Payments to producers - input subsidies 46% Payments to producers - other 1% Payments to processors 1% Agricultural research 13% Training 23% Extension 5% Inspection (veterinary/plant) 1% Infrastructure 1% Storage 0% Marketing 3% Other 6% Monitoring African Food and Agricultural Policies (MAFAP) 145 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Despite the importance given to irrigation in ASDP and in the Tanzania Agriculture and Food Security Investment Plan (TAFSIP), public resources devoted to irrigation are a very minor part of total expenditure. Irrigation expenditures fall into categories B2 (for on-farm investments) and N (for off- farm investments) (Table 24). Even if these two categories covered only irrigation-related investments, the total expenditure for them never exceeded 5 percent of total expenditure over the period analysed, and fell far below the TSh 474 billion envisaged in ASDP as reported in Table 5 of the Government Programme Document.24 This low level of investment in irrigation means that of the 22 million ha identified as suitable for irrigation, only 1 percent has been developed. There were also some expenditures on other support to producers, but these accounted for a very small proportion of agriculture-specific spending, as did other payments to agents in the agrofood sector, which included payments to processors. The importance of these two categories did not change over time. There were no direct payments to consumers, traders, transporters or input suppliers.25 Agriculture-specific expenditures are complemented by agriculture-supportive expenditures, which account for an average of about 55 percent of overall support to the food and agriculture sector in the United Republic of Tanzania, although their relative importance in total support to agriculture has decreased over time. By far the largest of these expenditures during the period analysed were for rural infrastructure, particularly roads, but also water and sanitation, and energy (Figures 50 and 51). Their relative importance in agriculture-supportive expenditures has not changed over time. In total, more than two-thirds of agriculture-supportive expenditures went to rural infrastructure, with the rest being directed to rural health and rural education. The importance of these two categories has changed over time, with rural education accounting for a larger share of agriculture- supportive spending in the first part of the analysed period, and rural health dominating in the second. 24 http://www.agriculture.go.tz/publications/english%20docs/ASDP%20FINAL%2025%2005%2006%20( 2).pdf 25 This conclusion is based on data collected from the budget books. However, additional projects – such as school feeding programmes supported by the World Food Programme – could fall into these categories, particularly payments to consumers. The MAFAP project is attempting to collect data from these missing projects, although their expenditures are expected to be relatively small compared with those already captured from the database, so would not change significantly the relative importance of spending categories, nor the overall conclusions. 146 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 50: Composition of agriculture-supportive spending in the United Republic of Tanzania, averages for 2006/07 to 2007/08 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Figure 51: Composition of agriculture-supportive spending in the United Republic of Tanzania, averages for 2008/09 to 2010/11 Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Agriculture-specific expenditures can also be disaggregated into the commodities they are intended to support.26 Each agriculture-specific expenditure measure is attributed to a category depending on whether it supports an individual commodity (e.g., cashew nuts at the Naliendele Agricultural Research Institute), a group of commodities (e.g., crops under AFSP) or all commodities (e.g., under the Participatory Agricultural Development and Empowerment Project [PADEP]). 26 Agriculture-supportive expenditures, by definition, are not intended to support the production of any particular commodity so are not considered as specific to agricultural commodities. Rural education 21% Rural health 12% Rural infrastructure - roads 42% Rural infrastructure - water and sanitation 14% Rural infrastructure - energy 11% Rural infrastructure - other 0% Other 0% Rural education 10% Rural health 27% Rural infrastructure - roads 39% Rural infrastructure - water and sanitation 13% Rural infrastructure - energy 11% Rural infrastructure - other 0% Other 0% Monitoring African Food and Agricultural Policies (MAFAP) 147 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The large number of commodities supported through these expenditures include fish, coffee, tea, cashew nuts, tobacco, sisal, sugar, pyrethrum, maize, rice, livestock products and apiculture products. Expenditures in support of all commodities (49 percent of total agriculture-specific measures) and in support of groups of commodities (47 percent) were by far the most important categories throughout the period analysed (Figure 52). Support to individual commodities accounted for only a small proportion of agriculture-specific spending (4 percent). Among expenditures in support of individual commodities, the biggest average shares targeted fish, coffee and tea, followed by cashew nuts, tobacco, cotton, sugar, pyrethrum, sisal and dairy (Figure 53a). Among expenditures in support of groups of commodities, the largest shares were absorbed by maize, rice and all crops, followed by livestock products, forestry and apiculture, cereals, forestry, apiculture, cotton and coffee, and horticulture (Figure 53b). Figure 52: Agriculture-specific spending in support of commodities in the United Republic of Tanzania, 2006/07 to 2010/11 P = provisional. Source: Authors’ calculations based on MAFAP public expenditure database for the URT. 0 100 200 300 400 500 600 2006/07 2007/08 2008/09 2009/10 2010/11(p) Billion TSh support to all commodities support to groups of commodities support to individual commodities 148 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 53: Support to individual and groups of commodities in the United Republic of Tanzania, averages for 2006/07 to 2010/11 53a. Individual commodities (4 percent of agriculture- specific spending) 53b. Groups of commodities (47 percent of agriculture-specific spending) Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Overall, most public expenditures are directed to providing public services and investments, with a relatively strong focus on infrastructure, but also on training, extension services and research. However, there is rapidly growing spending on input subsidies to agricultural producers, particularly for variable inputs. fish coffee tea cashew nut tobacco cotton sugar pyrethrum sisal diary maize and rice crops livestock forestry and apiculture cereals forestry apiculture cotton and coffee horticulture Monitoring African Food and Agricultural Policies (MAFAP) 149 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 54: Average shares of aid in public expenditures in support of the food and agriculture sector in the United Republic of Tanzania, 2006/07 to 2007/08 and 2008/09 to 2010/11 (billion TzSh) Upper bars correspond to 2006/07–2007/08 averages; lower bars to 2008/09–20010/11 averages. Source: Authors’ calculations based on MAFAP public expenditure database for the URT. 44% 25% 32% 28% 95% 87% 38% 7% 27% 18% 0% 0% 73% 25% 64% 37% 18% 37% 82% 43% 4% 14% 77% 48% 49% 19% 64% 58% 89% 58% 99% 98% 48% 42% 13% 15% 0 100 200 300 400 500 I. AGRICULTURE SPECIFIC POLICIES Payments to producers - input subsidies Payments to producers - other Payments to processors General sector support - agricultural research General sector support - technical assistance General sector support - training General sector support - extension General sector support - inspection (veterinary/plant) General sector support - infrastructure General sector support - storage General sector support - marketing General sector support - other II. AGRICULTURE SUPPORTIVE POLICIES Rural education Rural health Rural infrastructure Other donor (% next to the axis) national 150 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Role of aid in agriculture-related public expenditures Donor aid to the Government of the United Republic of Tanzania seems to be consistent with the government’s overall areas of spending, although there are some differences in priorities. On average, from 2006/07 to 2007/08, donor spending accounted for about 60 percent of overall public expenditures in support of the food and agriculture sector in the URT. However, it should be noted that this might be an underestimate of actual donor support, as the data sources used did not identify donor support channelled via general budget support.27 External aid contributes 44 percent of agriculture-specific expenditure and 64 percent of agriculture-supportive expenditure (Figure 54). In the 2008/09 to 2010/11 period, the share of donor support decreased, to only about 40 percent of total spending in support of food and agriculture sector development. The contribution to agriculture-specific expenditures dropped to about 25 percent, while donor aid to agriculture- supportive expenditures represented 58 percent of the total. The contribution of aid differs among categories. In agriculture-specific expenditures, donors contributed the largest proportions of total spending for other payments to producers, marketing, infrastructure, training, and extension services throughout the study period. In terms of donor spending levels, training and input subsidies to agricultural producers received the highest proportions, in both the first and second parts of the period. Among agriculture-supportive measures, the highest share of donor support was directed to rural health, which is the most donor- supported category overall and is almost entirely financed from donor funds. Technical assistance is the only category of spending that did not receive any donor support. Analysis of public expenditures Despite the increased emphasis on agriculture sector development, sector growth in the United Republic of Tanzania falls below the target of 6 percent recommended by CAADP. The observed patterns of public expenditures in support of food and agriculture development suggest that these expenditures do not contribute to sector growth in an optimal way, for a number of reasons. First, the trends in overall level of public expenditures in support of food and agriculture sector development in the URT are of concern. Despite the government’s efforts to mainstream development of the agriculture sector, agriculture’s share in the total government budget has been falling since 2007/08 and is currently below the Maputo Declaration target. Second, the composition of public expenditures in support of agriculture could be improved – the composition of expenditures is at least as important as the total level. There may be trade-offs between spending in different categories (e.g., spending on rural infrastructure versus offering subsidies for seed and fertilizer), and complementarities (e.g., between spending on extension services and spending on the development of infrastructure to enable farmers to get their output to market). From the analysis presented, there seem to be imbalances among categories of spending. High investments in rural infrastructure and extension services provision can bring benefits via lower 27 For example, although the input subsidy component is financed mainly by general budget support provided by the World Bank, the budget books consider this support as national. Monitoring African Food and Agricultural Policies (MAFAP) 151 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report transaction costs and improved access to markets for farmers. High support to rural development can provide off-farm employment opportunities in the future, while expenditures on research, training and extension services can help farmers improve their productivity and adopt more environmentally friendly production methods. Spending in these latter three categories has the greatest chances of bringing positive outcomes in terms of agricultural growth and poverty reduction in the long run.28 On the other hand, there are relatively few investments in the construction of markets (based on projects placed in the marketing category), very few in feeder roads (based on projects placed in the agriculture-specific infrastructure category) and no expenditures on storage. There is also very little expenditure on veterinary/inspection services, which are necessary for pest and disease control efforts at the farm level. Budgeted expenditure for the provision of subsidies for variable inputs has expanded rapidly, growing sixfold between 2006/07 and 2009/10. Although it decreased in 2010/11, it remained more than three times higher than it was at the beginning of the period analysed. Input subsidies may be an important policy instrument for stabilizing the incomes of producers in developing countries in the short run, but they should not compromise the allocation of resources to categories of spending that improve incomes over the long run (for a in-depth discussion, see OECD; 2012 and Brooks and Wiggins, 2010). According to the World Bank (2010), while the recent increases in spending on some inputs, such as NAIVS, are justifiable – because NAIVS is a well-designed, smart input subsidy that is market-based, promotes the private sector and induces supply response in the short-run – input provisions should be temporary and phased out as planned, particularly as they may compromise the increased allocations that are clearly needed for the provision of core public goods, including agricultural research, extension services, veterinary and inspection services and agriculture-specific infrastructure such as feeder roads. Third, data collected for the MAFAP project demonstrate that the rates of actual spending to budget allocation in the URT are low, as reported in Table 25. Actual spending may vary significantly from budgeted amounts, particularly in developing countries where budgets depend largely on donor disbursements and cash budget system are operated, as in the URT. This variation may have several causes: Budget allocations may misjudge the true requirements. Budget allocations may be readjusted during the fiscal year. Fund releases may be delayed or not occur at all if there are unforeseen calls on available funds. Budget execution has been far worse for policy transfers than for administration costs. Administration costs are financed mainly from the recurrent budget and are expected to have a better disbursement rate. In the URT, actual spending on policy administration costs has been almost equal to budgeted amounts, except for in the two most recent years. In this period, the disbursement rate was more than 100 percent, suggesting that more money was spent on policy administration costs than initially envisaged in the budget. This may occur if substantial budget 28 Several recent studies conclude that investments in agricultural R&D bring far better outcomes in terms of agricultural growth and poverty reduction. See FAO (2012b) for an overview of studies that compare the impacts of different types of agricultural expenditure and investment. 152 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report revisions are made during the fiscal year and additional money is allocated to administration, for example, for the recruitment of ministry staff. The budget execution of policy transfers is, on average, much lower than that of policy administration costs. Although the disbursement rate was very good in the two first years of the period analysed, it decreased significantly from 2008/09. The main explanation for these results is the unanticipated impact of the global financial crisis, which required budget reallocations – mainly from MAFC – to the Treasury’s emergency support for commercial banks. Other important reasons include delays in meeting the requirements for donor fund releases (particularly to ASDP), problems with project implementation related to technical difficulties in procurement procedures, and untimely fund releases to local government authorities (LGAs) (World Bank, 2010). Budget execution rates seem to have reverted to previous high levels, a pre-requisite to increase the efficiency of expenditures in support of food and agriculture sector development. Table 25: Budget allocations versus actual spending in the United Republic of Tanzania, 2006/07 to 2010/11 (billion TSh) 2006/07 2007/08 2008/09 2009/10 2010/11p Total agricultural budget1 Budgeted amount 616.0 891.7 1143.3 1198.9 980.1 Actual spending 584.5 878.4 825.1 759.3 947.2 Actual as share of budgeted (%) 95 99 72 63 97 Policy transfers Budgeted amount 585.1 832.4 1063.7 1085.3 862.5 Actual spending 553.9 823.1 746.0 630.2 813.3 Actual as a share of budgeted (%) 95 99 70 58 94 Administration costs Budgeted amount 30.9 59.3 79.6 113.6 117.6 Actual spending 30.6 55.4 79.1 129.1 133.9 Actual as share of budgeted (%) 99 93 99 114 114 1 Total agricultural budget includes policy transfers in support of agriculture and policy administration costs; p = provisional estimate. Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Fourth, a large share of the funds is allocated to policy administration costs and, based on MAFC and MLDF calculations, there seems to be an imbalance between the shares of these costs and of policy Monitoring African Food and Agricultural Policies (MAFAP) 153 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report transfers in total expenditures, particularly for the most recent years (Table 26).29 The increased share of administration costs after 2008/09 may be partially explained by the reallocation of funds devoted to policy transfers for managing the financial crisis, as already mentioned. However, the increases in administration have been substantial over the period analysed. Although the World Bank (2010) reports significant improvements to the agricultural wage bill in the most recent year, further efforts are needed to balance the policy administration costs and the policy transfers. Table 26: Shares of policy transfers and administration costs in public expenditures of MAFC and MLFD, 2006/07 to 2010/11 (percentages) 2006/07 2007/08 2008/09 2009/10 2010/11p Administration costs 16 17 26 33 25 Policy transfers 84 83 74 67 75 Total agricultural budget 100 100 100 100 100 p = provisional estimate. Source: Authors’ calculations based on MAFAP public expenditure database for the URT. Actions to address these issues will be crucial for improving the performance of expenditures in support of food and agriculture sector development. However, whether or not such actions are translated into improved agricultural growth will depend on additional growth factors that are not fully derived from public spending. 29 The projects and programmes included in the analysis involve several ministries. It is not possible to identify all the policy administration costs related to projects and programmes managed by ministries that work mainly on non-agricultural matters because these costs cover several sectors, and the “agricultural” share in them cannot be clearly identified (Komorowska, 2010). To ensure comparisons of only like with like in calculating the shares of policy transfers and administration costs in the total budget, the spending of only MAFC and MLFD was considered. 154 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report 8. Coherence between incentives and government spending Introduction The results of the MAFAP analysis of the rural and agriculture sector in the United Republic of Tanzania must be put into perspective in terms of the government objectives expressed in the agricultural policies reviewed in part 1 of this report. These objectives are set within large policy frameworks, and the analysis considers agricultural policies as being the series of decisions and policy measures aimed at being consistent with the overall objectives. The real risk of inconsistency lies in the proliferation of policies, projects and programmes that are subsequently cancelled and are not prioritized (GDPRD, 2011). In the URT, as in other countries, despite progress in developing a coherent and coordinated sectoral approach through Kilimo Kwanza and ASDS, agricultural policy consists of a maze of programmes and projects, including government decisions on trade, especially relating to tariffs. It should also be remembered that agricultural policy is not the exclusive domain of government. Donors and other development partners also have an influence on policy decisions, dictated by their own agendas and interests. In the URT, at least 60 percent of expenditure for agriculture comes from foreign aid. Therefore, the main questions in addressing policy coherence are: i). What are the main strategies determined by the government? ii). What are the major policy decisions and measures (programmes/projects, taxes/exemptions)? Are these decisions consistent with the stated objectives? iii). Have the adopted measures and policy decisions had an impact or achieved the expected effects, and have they met the objectives? Government's main objectives No single reference document presents a clear and simple outline of the Government of the United Republic of Tanzania’s objectives and priorities regarding agricultural and food policies (see chapter 4). It is therefore necessary to generate an analysis from existing documents. The overall objective of the URT’s national strategy for growth and poverty reduction in 2005–2010 has three pillars for agricultural development: 1) increased productivity and profitability; 2) increased sustainable off-farm income-generating activities; 3) secured and facilitated marketing of agricultural products. In turn, ASDP aspires to: i) improve farmers' access to and use of agricultural knowledge, technologies, marketing systems and infrastructure; and ii) promote private sector investment in agriculture, based on an improved regulatory and policy environment. Monitoring African Food and Agricultural Policies (MAFAP) 155 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The overall objectives against which the analysis results have to be assessed can therefore be considered as covering two aspects of food security: increasing food availability (pillars 1 and 3); and increasing food accessibility (pillar 2). Factors driving the value chains A number of driving factors have been identified for the different commodities and commodity groups presented in chapter 5. These are summarized in Table 27, together with the MAFAP results regarding price incentives and disincentives and public expenditure. 156 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 27: MAFAP coherence matrix for the United Republic of Tanzania Commodity or commodity group Incentives/disincentives What are the price incentives/disincentives for producers? What are the costs/gains that market inefficiencies represent for producers? Driving factors What are the key factors or issues that drive incentives/disincentives for production? Policy What policy measures and objectives are related to these driving factors? Public expenditure How does public spending address these driving factors? All products Average observed NRP: 17% Average adjusted NRP: 14% MDG: -2% • NFRA interventions distributing cheap staples to vulnerable households • Tariff structure for key imports partly waived during the period of high food prices • Inefficiencies in main processing industries (sugar, cotton) • Excessive transport costs in the country and lack of market integration between surplus and deficit areas • High import costs at port of Dar es Salaam and import licence rents • Lack of storage capacity for staples • Taxation of specific commodities • Marketing arrangements for some commodities where farmers have less bargaining power than traders • ASDS (2001) main strategic objectives: (1) Creating an enabling and favourable environment for improved productivity and profitability in the agriculture sector (2) Increasing farm incomes to reduce income poverty and improve household food security by improving farmers’ access to and use of knowledge, technologies, marketing systems and infrastructure (3) Promoting private investments based on an improved regulatory and policy environment • Main priority investment areas identified in subsector strategies: i) infrastructure; ii) irrigation; iii) mechanization; iv) R&D; v) farm inputs; and vi) renewable natural resources • Most relevant programmes: (1) ASDP (2006) (2) AFSP and NAIVS (3) PADEP (4) Tanzania Social Action Fund (5) DASIP • Increase in agricultural actual expenditure from 2006 to 2011: 30%, reaching TSh 728 billion • Agricultural actual expenditure in total government expenditure for the period: 11.7% (decreasing trend) • Increase of funding to input subsidies over other services • Expenditure on agriculture-specific policies: 44% of total agricultural expenditure: o 39% input subsidies o 31% training and extension o 14% research o 3% marketing o 2% storage o 1% inspection o 1% infrastructure o 1% payment to processors o 8% others • Expenditure on Monitoring African Food and Agricultural Policies (MAFAP) 157 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report • General measures: (1) 50% subsidies to fertilizers through NAIVS (2) Deferment of VAT payment on capital goods defined in the tariff book (July 2007) (3) Reduced licence fees and exempted annual fees on motor vehicles and tractors used for agriculture (July 2008) (4) Zero rate duty on all farm implements (fertilizers, herbicides, pesticides, etc.) (July 2008) (5) Reduction of crop tax to maximum 5 percent of production value (July 2008) (6) TSh 17.5 billion to support the price of fuel (November 2008) (7) Establishment of a specific social security fund for farmers (2009) (8) Facilitation of farmers’ access to credit and promotion of rural financing institutions through recapitalization of Tanzania Investment Bank; establishment of Tanzania Agriculture Development Bank (with US$500 million); and the Vision Tanzania Fund (2009) (9) Establishment of Zonal Agricultural Research and Development Funds (2008/2009) (10) General VAT reduction from 20 to 18 percent (July 2009) (11) Improved access to quality seed, through technical assistance and extension to produce quality- declared seeds (2007); promulgation of the Seed Act agriculture-supportive policies: 56% of total agricultural expenditure: o 41% rural roads o 19% rural health o 15% rural education o 13% water and sanitation o 11% rural energy • Supportive expenditure composition remained unchanged throughout the period • Expenditure targeting specific commodities or groups of commodities: 52% of agriculture-specific expenditure 158 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report (2009) to avoid the sale of fake seeds; and empowerment of the Tanzania Official Seed Certification Institute as the national regulator (December 2009) (12) Establishment of the National Agriculture and Cooperatives Commission (NACC), the National Irrigation Agency and the Ministerial Planning Coordination Committee (2009) (13) Establishment of market data/information centres (2010); agricultural resource centres for the provision of inputs (2010); and the agricultural price stabilization mechanism (2010) Imports Average observed NRP: 47% Average adjusted NRP: 48% MDG: 1% • Import tariffs for all commodities • Excessive marketing costs within country • Rents associated with import licensing • Loosening of food import tariffs and duties • Increased restrictions on food exports • Zero-rate VAT on locally produced sacks for packing imported bulk agricultural products (July 2008) • Promotion of local products through “Buy Tanzanian” campaign, starting with government procurement (July 2007) Wheat Average observed NRP:51% Average adjusted NRP: 62% MDG: 8% • Incentives related to trade policy with high external tariff • Exports of processed wheat (flour) to neighbouring countries when tariff lowered, keeping prices high in the country • Low productivity of wheat preventing extension of production, with high domestic prices • Zero tariff for EAC countries and 35% tariff for imports from outside EAC • Tariffs waived to 10% since 2007 • Expenditure targeting crops: 17% of total agriculture-specific expenditure in: o Input subsidies (variable inputs, seeds and capital) o Research, training and extension o Storage/public stockholding Monitoring African Food and Agricultural Policies (MAFAP) 159 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report o Marketing • Expenditure targeting cereals: 2% of total agriculture-specific expenditure in: (1) Research training and extension (2) Strategic grain reserve Sugar cane Average observed NRP: -20% Average adjusted NRP: -18% MDG: 11% • Inefficiencies in the sugar milling industry and/or excessive power of sugar mills • Farmers not benefiting from the tariff protection • Consumers heavily taxed, even with the government’s ad hoc changes to the tariff policy for sugar • Variation and unpredictability of the tariffs. • Government elimination of withholding tax on cash crops, based on Income Tax Act of 2004 • Annual sugar export and import quotas set by SBT • Import license fee of US$10/tonne of sugar • Sugar levy to SBT of US$2.75/tonne sold • CET of 100% – 35% for unrefined sugar; government mandate to vary tariffs between 0 and 25% • Expenditure targeting crops: 17% of agriculture- specific expenditure in: o Input subsidies (variable inputs, seeds and capital) o Research, training and extension o Marketing • Sugar targeted by 0.15% of agriculture-specific expenditure in research, extension, training and marketing Rice Average observed NRP: 68% Average adjusted NRP: 62% MDG: -4% • Protection during the period leading to increased production and URT becoming a net exporter of rice • Export competitiveness not assured when international market prices fall to “normal” levels • Part of protection caused by trader inefficiencies in the port of Dar and captured, due to excessive marketing costs • The URT’s status as a net exporter causing farmers to miss some potential gains of export markets because of trade restrictions (export ban) • 2008 National Rice Development Strategy towards commercially viable production. Short-term (1–3 years) strategies: (1) Increasing production and productivity of rice in selected irrigation schemes (2) Reducing production and post- harvest losses (3) Increasing availability of and access to agricultural inputs (improved seeds, fertilizers, pesticides and appropriate farm machinery) (4) Rehabilitation of old and development of new irrigation • Expenditure targeting crops: 17% of agriculture- specific expenditure in: o Input subsidies (variable inputs, seeds and capital) o Research, training and extension o Storage/public stockholding o Marketing • Expenditure targeting maize and rice: 18% of agriculture-specific expenditure in subsidies to variable inputs 160 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report schemes • Import tariffs of: (1) 75% or US$200/tonne to non- EAC (2) 0% to COMESA and EAC (3) 25–10% to SADC (South Africa only 5% in 2005–2007) • Export ban in place • Producers exempted from VAT and other local taxes • Local trade taxes to other agents in the value chain • Financing of 6 irrigation schemes specifically for rice producers (July 2007) • Expenditure targeting cereals: 2% of agriculture- specific expenditure in: o Research training and extension o Strategic grain reserve Milk Average observed NRP: 28% Average adjusted NRP: 38% MDG: -8% • Import tariff of 35% on fresh milk and milk powder • Very low marketing of milk production • Low efficiency of domestic dairies limiting prices that can be paid to farmers • Low quality of domestic compared with imported milk • Exemption of stamp duty for livestock products (July 2008) • Tax exemption for aluminium and heat- insulated implements for milk storage and collection (July 2009) • Registration and Traceability Act (2010); establishment of the National Livestock Identification, Registration and Traceability System • Amendment of the VAT Act (CAP 148) exempting machines and equipment used for collection, transportation and processing of milk products from VAT (2010) • Expenditure targeting livestock: 5.7% of agriculture-specific expenditure in: o Input subsidies (capital and on- farm services) o Research, training and extension o Inspection o Infrastructure o Marketing • Dairy individually targeted by 0.04% of agriculture- specific expenditure in research, extension and marketing Exports Average observed NRP: -1% Average adjusted NRP: -9% MDG: -8% • Removal of requirement to mark “For export only” on exported excisable products (July 2007) • Government elimination of withholding tax on cash crops, based on Income Tax Act of 2004 • Expenditure targeting crops: 17% of agriculture- specific expenditure Monitoring African Food and Agricultural Policies (MAFAP) 161 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Cotton Average observed NRP: -28% Average adjusted NRP: -28% MDG: -0% • Government and TCtB interventions in form of taxes and levies in the cotton market • Subsidies put in place in 2009, but disincentives higher • Low efficiency of ginning mills penalizing farmers with lower prices than if better technologies were available • Years of lower disincentives (2009, 2010) explained by reduced seed cotton production, increasing competition among ginneries • Objectives of industry strategic plans: i) achieve international quality standards; and ii) double productivity and textile production • TCtB established by Cotton Industry Act No. 2 of 2001 (effective on 2004, amended in 2009) • TCtB price and input subsidy programme since 2008/09 • Government compensation to cotton and coffee buyers selling at a loss in 2008/09 • Market information accessible via Internet • Promotion of contract farming • 0% import tariff on cotton lint • 0–10% import tariff on cotton seed • 10–50% import tariff on textile products • Expenditure targeting cotton and coffee: 0.01% of agriculture-specific expenditure in marketing • Cotton individually targeted by 0.26 percent of agriculture-specific expenditure in research, extension, training and subsidies on variable inputs • Transfer of TSh4 390/tonne of seed cotton to farmers for purchase of insecticides in 2009; TCtB paid price support transfer of TSh80 000/tonne of seed cotton in 2010 Coffee Average observed NRP: -27% Average adjusted NRP: -34% MDG: -9% • Farmers more penalized by functioning of the export value chain and export administration costs than by local taxation • District cess on farmers • First specific action promoting the coffee industry, Tanzania Coffee Industry Development Strategy 2011– 2016, aiming to: i) increase production; ii) improve quality; iii) improve the business environment; iv) increase farmer incomes and price premiums; and v) increase value addition throughout the coffee value chain • Abolishment of VAT exemption on locally grown processed tea and coffee (July 2009) • KILICAFE’s financial services linkage • Introduction of WRS (2007) • Subsidies on agricultural inputs since 2004 • Expenditure targeting cotton and coffee: 0.01% of agriculture-specific expenditure in marketing • Coffee individually targeted by 1% of agriculture-specific expenditure in research, extension, training and marketing Pulses Average observed NRP: 17% Average adjusted NRP: 4% MDG: -11% • Lack of storage forcing farmers to sell after harvest; production exported • High transport and marketing costs limiting market integration • No specific policy for pulses in the URT • Low expenditure in storage limiting capacity to benefit from domestic prices vis à vis export markets 162 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Cashew nuts Average observed NRP: -5% Average adjusted NRP: -14% MDG: -9% • Export tax on raw cashew • Introduction of WRS in 2007 • Excessive port costs, district cess and margins along the value chain, reinforcing disincentives • Small return of export tax to the sector • Export tax on raw cashew of 10% of FOB (15% in 2011), of which 35% to the Treasury; rest returns to the sector minus 5% for local authorities • Centralization of marketing in 2007 through primary societies and cooperative unions for export through auction • Local taxes of about 5% of farm-gate price • Cashew individually targeted by 0.31% of agriculture-specific expenditure, mainly to the Naliendele Institute and CBT Thinly traded Maize Average observed NRP: -9% Average adjusted NRP: -10% MDG: -2% • NFRA’s release of subsidized maize • Excessive marketing costs along the value chain • Erratic trade policy • Lack of storage capacity • Government more interested in keeping maize prices low than ensuring more remunerative prices for farmers (1) NFRA releases of food stocks at lower than market prices (July 2007; March 2008; July 2009) (2) More resources allocated to NFRA to regulate food crop prices (2009) (3) Maintenance food stocks for 6 months to 1 year to support market stability (August 2009) • Frequent trade measures to support food security; CET of 50% on imports from non-EAC countries; 0% for EAC countries. (1) Waiver of maize import duties (July 2007); zero import duty on maize until May 2008 (2) Intermittent bans on maize exports (2004, 2006, 2008, 2011); lifted (2006, 2007, 2010) • Local trade taxation • Introduction of Cereals and Other Produce Act, Cereals and Other Produce Board and Cereals and Other Produce Regulatory Authority, facing delays in becoming operative • Expenditure targeting crops: 17% of agriculture- specific expenditure in: o Input subsidies (variable inputs, seeds and capital) o Research, training and extension o Storage/public stockholding o Marketing • Expenditure targeting maize and rice: 18% of agriculture-specific expenditure in subsidies to variable inputs • Expenditure targeting cereals: 2% of agriculture- specific expenditure in: o Research training and extension o Strategic grain reserve Monitoring African Food and Agricultural Policies (MAFAP) 163 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Assessing the effects of major decisions and policy measures based on the results of the MAFAP analysis This section assesses the coherence between public expenditure decisions and the measures implemented under policies, and their effects in terms of the price incentives and disincentives observed by the MAFAP project analysis. The aim is to identify situations where policies complement each other and those where they seem to contradict or compete with each other. Conflicting policies can result in inconsistent messages, which are difficult to understand and implement for operators, especially producers. MAFAP seeks to assess whether or not government declarations translate into real support for all or at least some producers by combining support prices and government spending in favour of producers. However, it is not possible to cover all government objectives and to measure the performance of policies in all areas with the MAFAP methodology. For example, the methodology is not fit to assess policy coherence with objectives such as improved plant protection, animal health or seed quality; support to livestock through improved animal genetics and animal health; mobilization of water resources; or even job creation. This report therefore focuses on objectives for which the MAFAP approach and methodology can be used to assess performance and consistency in selected areas of agricultural and food policies. As already mentioned, two main objectives seem to underlie the overall policy framework for the agriculture sector in the United Republic of Tanzania. In the food availability domain, it can be seen that – apart from in the rice and wheat sectors – the overall policy environment and, to a greater extent, the functioning of the value chains result in lower prices for farmers than could be expected in the absence of domestic policies and with better-performing value chains. Rice can be seen as a success story, with increased protection leading to higher production, making the URT a surplus country for rice production, but this result should be interpreted with care. First, most of the increased production is due to area rather than yield increases. Yields remain below the average for East Africa, and exports from the URT might no longer be competitive when international prices return to their pre-crisis levels. In the case of wheat, incentives have not resulted in increased yields or areas, suggesting that the URT may not be well suited to producing wheat. All the other commodities analysed show disincentives, which prevent farmers from obtaining higher prices for their output and limit their investments. This situation could promote food accessibility, by making domestic food prices lower than those prevailing in international markets, but most of the disincentives relate to classic export crops (coffee, cotton, cashew nuts), which are not part of the normal diet of Tanzanian citizens. At the wholesale level (i.e., the level closest to consumer purchases), most food security commodities apart from maize show positive price gaps, so the cost to consumers of the average diet is higher than it would be in the absence of policies and with better-performing markets. To address these objectives more effectively, specific recommendations have been made for each commodity. In general these recommendations call for a move towards a less volatile trade policy, ideally by deciding whether or not import tariffs are needed and moving definitively away from export bans, while increasing investment in the infrastructure that facilitates market functioning (roads, storage, market information systems, etc.). Initiatives such as SAGCOT seem to point in this direction, and the drafting of ASDP II provides an excellent opportunity to align public investment 164 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report with the policy environment to deliver the expected growth of agricultural output, increased productivity and reduced hunger and poverty. Such policies as export taxes on cashew nuts and tariffs on sugar are not benefiting farmers. Other tariffs are not fully transmitted to producers because of excessive access costs; even when explicit policies play a role in a commodity, access costs remain a major issue driving incentives and disincentives in the URT (Mugenyi, 2012). Regarding international trade, the URT is responsible for 50 of the 80 non-tariff barriers within the EAC (Financial Times, 2012). For example, in maize trade with its EAC partners, URT had custom clearance costs of US$10/tonne until 2012 (The Citizen, 2012). The inefficiency of import procedures at the port of Dar es Salaam is well known, with scandals related to the Tanzania Ports Authority appearing regularly in the press. The result is that of all the ports evaluated by Gwilliam (2011), the costs at Dar es Salaam are significantly higher than the continental averages and close to the highest in the continent (Table 28). Tariff removals therefore lead to lower prices inside the country, but are not as effective as they could be in lowering prices because of the excessive costs of import procedures. Table 28: Average port costs and charges in Africa, 2011 (US$ per unit) Port Container cargo handling charge per TEU General cargo handling charge per tonne Bulk dry handling charge per tonne Bulk liquid handling charge per tonne Dar es Salaam 275.0 13.5 4.5 3.5 Most expensive 340 17 8.0 4.0 Cheapest 67.5 5.5 1.4 0.4 Average Africa 191.7 9.9 4.3 1.9 Low-income fragile 210 10.1 4.9 3.3 Low-income non- f il 172.8 9.8 4.0 1.8 TEU = twenty-foot equivalent unit. Source: Authors’ elaboration using Gwilliam, 2011 data. Regarding internal trade, several studies have noted the lack of market integration for staple crops (World Bank, 2009; Minot, 2010a; Asche, Gjølberg and Guttormsen, 2012). Analysis results (Figure 55) show that for non-processed crops in 11 out of 14 year-crop data pairs, access costs are lower than price differentials between markets,30 leading to higher prices at the wholesale level and lower prices to farmers. There is therefore potential for further arbitrage, which is prevented by excessive costs from two main sources: transport costs, and cost of doing business. In addition, lack of storage capacity may create bias in analysis based on yearly data. The following paragraphs discuss each aspect of excessive access costs individually. 30 Considering the price differentials between the wholesale level and the farmgate for maize, rice and wheat. Monitoring African Food and Agricultural Policies (MAFAP) 165 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 55: Ratios between access costs from the farmgate to the point of competition and price differentials for selected commodities in the United Republic of Tanzania, 2005 to 2009 Source: Authors’ elaboration using MAFAP technical notes for selected commodities in the URT. For domestic transport, at least six different certificates are required of every commercial vehicle carrying goods in the URT, and almost all of these certificates require annual renewal from different offices, thus increasing transport costs and creating opportunities for corruption at roadblocks (Booz Allen Hamilton, 2010). However, although rent-seeking by licensing agents increases costs, the costs of delays are usually far more significant. Although transport costs remain high, logistics in the URT have improved relative to other countries, with the country ranking 88th out of 155 countries on the International Logistics Performance Index in 2012, up from 95th in 2010, making it fifth among the low-income countries, after Benin, Malawi, Madagascar and the Niger (Arvis et al, 2012). However, improvements seem to have slowed down since 2010 after a significant increase of performance from 2007 and 2010. As shown by MAFAP development performance indicator 10 (DPI 10) (Table 1), less than 10 percent of the URT’s total roads are paved, and nearly 80 percent of the rural population has inadequate access to road networks. Among countries in the region, only Rwanda and Uganda have fewer paved roads. In addition to poor road conditions, roadblocks and weighing stations constitute the most common cause of transport delays. As well as legitimate controls, trucks are often stopped by bribe- seeking police officers; transport professionals report that a truck can be stopped 10 to 15 times on the road from Dar es Salaam to Iringa, with the bribe requested at each stop ranging from US$2 to US$4. The Agricultural Council of Tanzania (ACT) argues that farmers are still forced to pay produce levies at roadblocks across the country before they can reach urban markets (Daily News, 2012). While reinforcing rule of law in the transport sector remains a government priority, results of public expenditure analysis show a significant drop in investments in rural roads between 2007 and 2011 (Figure 56). Additional investments are needed in rural roads if market access is to become an effective business avenue for smallholders. The principles behind the SAGCOT initiative are well aligned with achieving this end, but general infrastructure for all areas of the country lags behind. - 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 2005 2006 2007 2008 2009 Maize Rice Wheat 166 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 56: Public investments in rural roads in the United Republic of Tanzania, 2007 to 2011 PE = public expenditure. Source: Authors’ elaboration based on MAFAP public expenditure database for the URT. However, marketing costs are not related to transport and handling alone, but also to the ease of doing business. In this area, the URT ranks 113th out of 185 countries in the Doing Business Index for starting a business in 2013 (World Bank and International Finance Corporation, 2013). To start a business an entrepreneur needs to complete nine procedures, which require 26 days and cost an average of 28 percent of national per capita annual income. Some agricultural businesses also have to obtain additional permits and licences for specific activities. Primary agricultural businesses are exempt from general business licence requirements, but all agricultural businesses engaged in value addition, including trading, packaging and processing, must hold an annually renewable general business licence. Several institutions are involved in issuing these licences, so licensing procedures for agribusinesses are long, particularly because of weak capacities, poor coordination between central and local government authorities, and lack of awareness among applicants. For instance, district authorities may take up to three months to issue general business licences to local businesses; and businesses that require licences from LGAs must also be licensed at the central level, while the information collected from businesses by central authorities is not made available to LGAs. Although MAFC is committed to removing legal obstacles and streamlining administrative registration rules and approval procedures – particularly by developing performance charters for agencies administering business regulations – these intentions have yet to be put into practice (OECD, 2013). The lack of adequate infrastructure, understood in a broad sense such as to include transport, storage, energy, communications and others, hinders private investment in agriculture and reduces the competitiveness of agricultural supply chains. Because of poor infrastructure development, the URT ranks 120th out of 144 countries in the 2012–2013 Global Competitiveness Report, against 104th out of 139 countries in the 2009–2010 report. Poor infrastructure is cited as one of the main factors behind declining performance, and the URT ranks 132nd out of 144 countries for infrastructure (World Economic Forum, 2012). 0% 5% 10% 15% 20% 25% 30% 35% 40% 0 50 100 150 200 250 300 350 2007 2008 2009 2010 2011 % of total Public Expenditure Billion TSh % of total PE in support of the agriculture sector PE for rural roads Billion TzSh Monitoring African Food and Agricultural Policies (MAFAP) 167 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Last, the lack of storage facilities forces farmers and small traders to sell their produce close to harvest periods when prices are lower, preventing them from benefiting from higher prices later in the season. Even NFRA has limited storage capacities.31 NFRA is a semi-autonomous body reporting to the Permanent Secretary of MAFC and linked to the Department of Food Security. According to MAFC, NFRA has a dual mandate: i) ensuring that food is available for distribution to the vulnerable; and ii) intervening in the market (purchasing or selling) to stabilize prices. Regarding the first mandate, NFRA purchases grains, principally maize, in surplus areas for distribution during times of shortage. In response to Disaster Management Department directives, NFRA sells the grain for TSh 380/kg to the Prime Minister’s Office and local authorities, which then release it to the market at subsidized prices. Regarding the stabilization of market prices, there seems to be some confusion about the roles of different agents in setting prices and quantities. The normal procedure envisages MAFC establishing the quantities to be purchased and NFRA fixing the annual floor prices, which are based on production costs (from MAFC statistics) plus a margin of 5 percent. In practice, the Minister announces the purchasing price for maize during his or her annual budget speech in August. This price is normally higher than the price that NFRA would calculate using the cost plus margin formula, and is often above the wholesale price in the areas where NFRA purchases, particularly during the harvest season (Figure 57). Since 2010, NRFA also sells maize to private millers at lower than domestic market prices (TSh 39 000 per 100 kg). These sales are mandated by MAFC and aim to reduce maize flour prices; most are made to small millers in Dar es Salaam. However, anecdotal evidence suggests that the releases have little if any impact on maize flour prices, and the system is to be revised to give regional commissioners the authority to approve the millers to which subsidized maize can be sold. The underlying rationale is that regional commissioners would licence only millers that sell maize flour at low prices. Figure 57: NFRA purchase prices and wholesale prices in the main maize surplus areas in the United Republic of Tanzania, 2006 to 2010 Shaded areas represent harvest season in uni-modal production areas Sources: Budget speeches (several years) and MTI. 31 According to OECD (2013), NFRA has evaluated the costs of building additional storage facilities. Analysis of public expenditure in future years will allow monitoring of whether or not these plans are being implemented. 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 TSh per 100 kg NFRA purchase price Iringa Songea S'wanga 168 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Good logistics and transportation systems are critical to building efficient agricultural value chains, particularly because most products cannot easily be preserved in tropical climates. The URT’s lack of storage facilities and poor road network generate considerable losses for both producers and traders, resulting in low returns and reducing the competitiveness of agricultural supply chains. Most agricultural goods are currently stored at markets in baskets or bags on the ground. They may therefore deteriorate before being sold on to retailers and final customers, thus hindering traders’ time arbitrage. Overall, post-harvest losses are estimated at 35 percent (Booth Allen Hamilton, 2010): 13 percent for rice, 26 percent for cassava, 42 percent for tomatoes, and 50 percent for fruits/vegetables (OECD, 2013). Public expenditure analysis also shows that marketing and storage facilities are not receiving sufficient funds. As shown in Figure 58, support for these two key aspects – which include processing facilities – declined during the study period. However, most of this apparent decline results from the lack of information on distribution of the NFRA budget across different activities, which leads to NFRA expenditure being classified as “others” in the MAFAP database. When the expenditure of NFRA is counted as being related to storage,32 expenditure on marketing and storage remains more or less constant, albeit at very low levels. Figure 58: Trends in public expenditure in support of storage and public stockholding and marketing in the United Republic of Tanzania, 2007 to 2011 Source: Authors’ elaboration based on MAFAP public expenditure database for the URT. The government has pursued several initiatives to improve transportation systems. The integrated road project aims to open up transport networks, particularly rural roads in key agricultural areas. 32 The expenditures of the Strategic Gran Reserve (NFRA’s predecessor) were classified as “storage/public stockholding”. 0% 1% 2% 3% 4% 5% 6% 7% 0 5 10 15 20 25 30 35 2007 2008 2009 2010 2011 % of total public expenditure in support of agriculture Billion TSh O. Storage/public stockholding P. Marketing TOTAL Monitoring African Food and Agricultural Policies (MAFAP) 169 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The Marketing Infrastructure Value Addition and Rural Finance Programme, funded from a US$64 million loan approved by the concessional window of the African Development Bank (ADB), will be coordinated by the Prime Minister’s Office from 2012/13, and targets 500 000 poor households. It aims to improve rural market infrastructure based on a comprehensive needs assessment and the use of public–private partnerships; and to encourage value addition and enhance smallholders’ access to finance by increasing the outreach of formal and informal financial institutions and improving the legal and policy framework for rural microfinance. Analysis results emphasize the importance of storage and marketing in functioning of the value chain, the incentives and disincentives faced by farmers, and the increased prices that consumers have to pay for food. The lack of storage facilities gives seasonality an increased impact on prices, as can clearly be seen when analysing the pulses sector. Figure 59 shows the annual average export price (FOB value) for peas, the reference price for peas at the farmgate level and the farmgate price received by farmers, approximated from wholesale prices. The pattern of price relationships shows that during the harvest period domestic prices fall below the reference price – i.e., farmers face disincentives as they are getting lower prices than they could get with better-performing marketing systems – and outside the harvest period prices are higher. Outside the harvest period, very few farmers can sell peas, as they cannot store them, so the domestic price reflects the cost of purchasing peas for consumers. MAFAP indicators are calculated as yearly averages; as no data on volumes per month are available for calculating weighted averages, the analysis results show incentives for farmers. However, in the pea market in the URT, farmers face disincentives during net selling periods, while during net buying periods, food prices are higher than they would be if marketing and storage were more developed. 170 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 59: Price comparison for peas in the United Republic of Tanzania, 2005 to 2011 Sources: UNcomtrade for FOB prices; IMF for exchange rates; MTI for domestic prices; and MAFAP for reference prices. For the two main processed commodities analysed (cotton and sugar), the processing industry faces very high costs related to old and inefficient capital stock. The same occurs with cashew nuts, where the export tax on raw nut exports does not seem to foster investments in processing plants and the plants in place cannot function at full capacity; and with milk processing, for which costs are much higher than in neighbouring countries. While the SAGCOT initiative is an excellent example of promoting investments in the agriculture sector to increase processing and productivity, the analysis of public expenditure shows that investments in enhancing processing have been very limited (less than 1 percent of total public expenditure) and are decreasing in time, with a 16 percent decrease from 2007/09 to 2010/11 (Figure 60). - 100 200 300 400 500 600 700 800 900 Thousand TSH/tonne Country average Benchmark price Reference price at farm gate level Monitoring African Food and Agricultural Policies (MAFAP) 171 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 60: Trends in public expenditure as transfers to processors in the United Republic of Tanzania, 2007 to 2011 Source: Authors’ elaboration based on MAFAP public expenditure database for the URT. Conclusion on policy coherence As discussed in the previous section, the analysis results show a contradictory situation regarding policy objectives and the actual impacts of policy measures and market performance. With regards to trade policy, contradictory actions (i.e., tariffs versus waivers) generate uncertainty for producers and tax export-oriented commodities. Moreover, market performance and processing of capital stock prevent farmers from benefiting as much as they could from food prices. Public expenditure does not seem to focus on the areas that the analysis identifies as the most crucial in generating disincentives (i.e., marketing, storage, processing), although the Government of the United Republic of Tanzania seems to have taken policy measures to reduce investment and access costs. The abandonment of export bans, the move towards eliminating district taxation for agricultural products, and the concept behind SAGCOT are all measures that will reduce the level of disincentives to farmers. If these measures continue and are implemented as planned, the results in years to come should show lower disincentives for farmers and better policy coherence. The URT has a unique occasion to improve its agricultural policies with support from development partners. In the future, MAFAP should be able to provide evidence of how the URT has taken advantage of this opportunity. 0.0% 0.1% 0.2% 0.3% 0.4% 0.5% 0.6% 0.7% 0.8% 0.9% 1.0% 0 1 2 3 4 5 6 2007 2008 2009 2010 2011 % of total public expenditure Billion TSh % of total public expenditure in support of agriculture Public expenditure: transfers to processors 172 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Part 3. A REVIEW OF THE IMPACT OF THE MAIZE EXPORT BAN IN THE UNITED REPUBLIC OF TANZANIA This review provides an in-depth study of the impact of the maize export ban on farmers’ production incentives and disincentives. Building on the results reported in the maize technical note (Barreiro- Hurle, 2012), this section is structured as follows. First, it provides a summary snapshot of the importance of maize in the agricultural sector of the United Republic of Tanzania (URT). Second, it reviews the different studies that have dealt with market integration in East Africa and in the URT to identify how maize markets function. Third, it provides a structured analysis of the findings of existing analysis focusing on the maize export ban for the URT, and, finally, it provides additional evidence of the impact of the export ban based on price comparisons. The results further support the new move of the Government of the United Republic of Tanzania to abandon export restrictive measures officially (EFEEDLINK, 2012; Daily News, 2012a), and highlight the importance of providing policy stability in this area as contradictory messages still remain (The Citizen, 2011; Daily News, 2012b). Maize in the United Republic of Tanzania Maize was the fifth largest agricultural commodity in the URT by value of production during the period 2005–2011, accounting for 7.5 percent of total production value. Moreover, it represents close to 5 percent of total value of agricultural imports in the URT for the same period and is the main source of dietary energy accounting for 25 percent of total caloric intake (FAOSTAT, 2010). Though not as high in value terms compared with other commodities, maize is considered the most important food crop, generating close to 50 percent of rural income, an average of USD 100 per maize-producing household in 2008 (USAID, 2010), and is grown by more than 50 percent of Tanzanian farmers. In the past two decades, the URT has ranked among the top 25 maize- producing countries in the world, dropping out of the list only three times, in 1986, 1997 and 2003. Production has reportedly increased from 2 million tonnes in 2000 to over 4 million tonnes in 2011, with yields moving towards 1.5 tonnes per hectare (Figure 61). However, these data are currently put into doubt (Stryker, 2012). Using projections based on household consumption figures, the estimated production of maize in the URT could be closer to 6 million tonnes, and consistently above 5 million tonnes since the start of this century. Monitoring African Food and Agricultural Policies (MAFAP) 173 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 61: Maize area, production and yield in the United Republic of Tanzania Source: FAOSTAT. Maize is produced throughout most the country (in all 21 mainland regions), covering 26 percent of arable land in the URT (2005–2010). Maize is grown on about 41 percent of the cultivated land during the masika (main) season and 47 percent of the cultivated land during the vuli (second) season. The vuli season (October–December) contributes approximately 15 percent of the total annual maize production, with Mara, Arusha, Kilimanjaro, Tanga, Morogoro, Mbeya, Coast, Kagera, Kigoma and Mwanza regions having two agricultural seasons per year (vuli and masika seasons). The remaining maize production is from the unimodal and bimodal masika long, rainy seasons. Maize market efficiency increased in the 1990s following the trade liberalization reforms in the country, which began in the 1980s. Thus, maize producers benefited significantly with the sharp increase of the maize produce price. Transportation costs (TCs) 33 in the URT exceed those in other East African Community (EAC) partners. TCs average USD 6.4 per tonne from farmgate to primary markets, USD 27 per tonne from primary markets to secondary markets, and USD 41.51 per tonne from secondary markets to wholesale markets. They accounted for 60 percent, 78.7 percent and 91 percent of the costs of the first, second and third stages of marketing, respectively (World Bank, 2009). TCs for farmers increase owing to the informal fees farmers pay to avoid delays, overload charges and other problems. On average, Tanzanian farmers pay ten informal fees per year in the full maize supply-chain process, more than the Kenyan (eight bribes) and Ugandan (four bribes) farmers. An average of seven bribes from Tanzanian farmers occurs at roadblocks and three at weighbridges (World Bank, 2009). Nationwide, local taxes on maize commercialization account for around 4.3 percent of marketing costs. However, this percentage varies as each locality has its own tax rate. Most of the maize produced by rural households is for subsistence use, although the marketed share seems to be increasing since the liberalization of markets. For instance, in the early 1990s it was estimated that 25 percent of the maize produced was traded. This reflects an increase of 5 percentage points from the 1983/84 estimate of 20 percent. Current estimates put the percentage of 33 Transportation costs (TCs) account for most of the commercialization cost in the supply chain because most maize farmers do not own their transportation vehicles but rent them (70 percent of small-scale farmers, 100 percent of medium-scale farmers and 67 percent of large-scale farmers) (World Bank, 2009). 0 0.5 1 1.5 2 2.5 3 3.5 - 1 2 3 4 5 6 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 T o n n e s p e r h e c t a r e Million tonnes and hectares Yields (left scale) Area Harvested (Ha) Production (tonnes) 174 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report marketed share at 40 percent (MAFC, 2010). Three main agents act in the value chain and purchase maize from farmers: private traders, the Cereals Board (created in 2009) and the National Food Reserve Agency (NFRA), formerly known as the Strategic Grain Reserve (SGN). Taking into account the marketed and production volumes and the data available for purchases from NFRA and the Cereals Board, the role of public interventions in the market has remained below 10 percent of apparent marketed consumption. The maize marketing system is characterized by a very large number of small traders operating both from the main centres of production and from the major urban areas. Produce from the farm is taken to primary markets (i.e. big markets in producing areas) directly by farmers, or by intermediaries who purchase the maize at the farm. Marketing channels are characterized by lengthy brokerage services dominating at village, district and national urban markets (Match Maker Associated, 2010). The market margins are generally quite high, suggesting inefficiencies in supply chains. Prices vary greatly between seasons (during harvesting and periods of scarcity). In addition, post-harvest losses are quite significant and productivity levels are low. In the United Republic of Tanzania, there is an important role to be played by storage facilities to stabilize prices in the harvesting season and to allow farmers to store maize when supply is high, thus preventing sharp falls in prices during the seasons of plenty. According to Nazir et al. (2010), by the end of 2008 only 50 percent of small-scale maize farms used storage facilities, while 100 percent of large-scale farms did so. Storage costs are counted as costs of commercialization and are assumed to be the same for both small- and large-holder farmers. Storage costs account for 7.5 percent of the total marketing costs during the initial farmgate to primary market stage, 3.4 percent during the primary to secondary market stage, and 0.2 percent during the secondary to wholesale market stage. Because of the low investment in storage facilities, post-harvest storage losses account for USD 19.9 and USD 10.8 per tonne for small- and large-holder farmers, respectively. These values constitute 44.2 percent and 24 percent of the costs associated with the farmgate-primary and the primary- secondary marketing costs, respectively. In addition to the export restrictions, which will be discussed at length below, three main policy measures affect maize markets in the URT: import tariffs, food security policy and input subsidies. As far as trade policy is concerned, the URT applies the East African Community Common External Tariff (EACCET) of 50 percent to maize imports and 0 percent for EAC member countries. Maize imports originate mainly from outside the EAC; thus, it is expected that in years when the URT is a net importer, this policy would generate price incentives. In July 2003, the Government passed a bill enabling protective measure to prevent imports of so-called cheap substandard products. This can be considered a de facto import ban, which was removed in 2008. However, trade measures in the country seem to be very unstable as during the high food prices crisis, the URT suspended the import tariff for maize from July 2007 to May 2008 and again in November 2008. Regarding food security, the NFRA is mandated to intervene directly in the maize market. The NFRA is a semi-autonomous body that reports to the Permanent Secretary of the Ministry of Agriculture Food Security and Cooperatives (MAFC) and is linked to the Department of Food Security. According to the MAFC, it has a dual mandate: i) assuring that there is food available to be distributed to the vulnerable; and ii) intervening in the market (purchasing or selling) to stabilize prices. Regarding the first mandate, the NFRA purchases grains, principally maize, in surplus areas for distribution during Monitoring African Food and Agricultural Policies (MAFAP) 175 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report times of shortage. In response to the Disaster Management Department directives, the NFRA sells grain to beneficiaries at subsidized prices. Through these interventions, the Tanzanian Government seeks to stabilize food supply. The recipients are identified by local authorities (village executive officers), who decide if a household can pay for the food or receive it free. The NFRA aims to procure and store emergency food stock of up to 150 000 tonnes, which should suffice in addressing a food disaster for a three-month period, regarded as enough time to order and secure food imports from abroad. A major policy affecting maize production is the fertilizer subsidy (Mbwele and Pius, 2010). The subsidy was introduced in 2003 just for the Southern Highlands region, and then extended to the entire country in 2004. In 2008, the programme was transformed into a smart subsidy using vouchers for targeting eligible beneficiaries under the name of NAIVS (National Agricultural Input Voucher Scheme), which subsidized 50 percent of the fertilizer and seed costs to selected farmers in 11 regions, expanding to 20 regions in 2009. The NAIVS programme represents a quantitative leap in the amount of resources devoted to this policy measure, representing the single most important area of the MAFC budget allocation (MAFC, 2010). According to the Monitoring African Food and Agricultural Policies (MAFAP) analysis on public expenditure, subsidies to variable inputs accounted for 33 percent of total public expenditure directed to the agricultural sector during the 2006–2010 period, reaching a peak of 46 percent in 2009 (Ilicic-Komorwoska, Maro and Pascal, 2012). Finally, as regards market regulations, traders wishing to embark on regulated international trade for maize need to obtain import and export permits from the Department of Food Security at MAFC and the Ministry of Industry and Trade; and phytosanitary certificates and customs documentation involving at least four ministries (MAFC, Ministry of Industry and Trade, Ministry of East African Cooperation and Ministry of Finance). Even though the official position regarding these procedures is that they take no time and are granted in an automatic manner, Christensen and Cochrane (2012) report that they still prevent major traders from engaging in maize-related activities. Maize market integration in the United Republic of Tanzania34 The United Republic of Tanzania is a large country with low levels of infrastructure stock; thus, the law of one price for agricultural markets cannot be taken for granted. The issue of market integration has been extensively studied both within the URT, between the URT and global markets, and between the EAC member countries. Internal market integration in the United Republic of Tanzania. Maize trade within the URT follows three main routes (Figure 62). With regard to the internal movement of maize , surplus from the production area in the Southern Highlands is assembled in 34 In this section, market integration and price transmission are used as equivalents; however, as Barret and Li (2002) point out, market integration refers to tradability of products between spatially distinct markets irrespective of the existence or absence of spatial equilibrium, and price transmission identifies competitive market equilibrium irrespective of whether physical trade flows exist between markets. 176 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Makambako-Iringa and then shipped either to Dar es Salaam or to Kenya. Smaller amounts flow from the western part of the country towards the lake area. The other two main routes relate to international trade. The main destination of maize exports from the URT is Kenya. When price differentials are high, maize from the Southern Highlands flows via Arusha towards Kenya; when these differentials are smaller, production from the Manyara area is exported to Kenya. During peak deficit periods in Kenya, transit of maize through the URT-Kenya border can reach 1 000 tonnes per day (Mashindano, Bamwenda and Hangi, 2012). Smaller amounts flow to the Democratic Republic of the Congo (DRC), Burundi and Rwanda from Kigoma and towards Malawi and Zambia from the Southern Highlands. Figure 62: Production and market flows of maize in the United Republic of Tanzania. Source: www.fews.net Regarding price transmission studies focusing on maize market integration within the URT, Van Campenhout (2007) found that during the 1990s the level of market integration improved significantly. However, there was an increase of spatial price dispersion in the early 2000s (Sarris and Mantzou, 2005). The World Bank (2009) reports that maize markets in the URT are the least integrated in the EAC. The deficit areas of Dar es Salaam and Arusha35 have similar price levels and move together, while the surplus areas have lower prices and have a looser relationship. The integration between production areas is only moderate, or weak, with very slow price transmission, implying that it takes many months for price signals in one market to be incorporated into prices in other markets. The strongest rate of price adjustment within the URT is found to be lower than the 35 Arusha is considered a deficit area because of the impact of demand from Kenya. Monitoring African Food and Agricultural Policies (MAFAP) 177 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report weakest for Kenya. Notwithstanding this increased price dispersion, the five most important maize markets in the URT share a long-run equilibrium; however, short-term disruptions allow for long periods of time where the markets are not in equilibrium (Ilhe and von Cramon-Taubadel, 2010). Ilhe, von Cramon-Taubadel and Zorya (2011) also report that not only price transmission within the URT is much lower than within markets in Uganda or Kenya, but that also domestic market integration in the URT is lower than that between markets in Uganda and Kenya (i.e. with a border crossing). This is mostly because the main producing areas are physically isolated from the main consumption areas owing to poor transport infrastructure. For stocks of maize to move from Mbeya to Arusha, for example, trucks have to pass through Morogoro and Chalinze route, some 400 km more compared with the ideal route between Iringa, Dodoma and Babati. Overall, market integration studies show that the URT still lacks a single maize market, and even in traditional surplus areas such as Iringa there are low levels of market participation and sales are low in frequency and high in volume, thus missing opportunities for better prices (Mkenda and Van Campenhout, 2011). This lack of domestic market integration is reflected in the trends of domestic maize prices in the country between 2006 and 2012. To illustrate this, the evolution of maize prices in five main markets in the URT was plotted. Dar es Salaam is selected as the main consumption area, Arusha as the market where competition with demand for imports from Kenya is most prominent, Mbeya and Sumbawanga as the main producing areas in the Southern Highlands, and Bukoba as the closest market for exports to Burundi and Rwanda (Figure 63). Figure 63: Location of the wholesale markets for which maize prices have been analysed Source: Authors’ elaboration Figure 64 shows the trends of maize prices for the five markets. The prices in the two main producing areas (Mbeya and Sumbawanga) seem to be closely correlated; the same holds for Arusha and Dar es Salaam, with Bukoba following a more independent path. However, this simple inspection of price trends also supports discarding the notion of a single national market for maize in the URT. Arusha Bukoba Dar es Salaam Mbeya S’wanga 178 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 64: Maize prices in five selected wholesale markets in the United Republic of Tanzania, 2006-2012 Source: Authors’ elaboration using MTI data. Market integration between the world and the United Republic of Tanzania. Integration of maize markets in the URT with world markets is limited. Minot (2010a) finds that out of eight markets analysed only Arusha seems to have a long-term relationship with world markets, a relationship that is caused mainly by the integration of Arusha with Kenyan markets, which are in turn integrated with international markets. Sarris and Mantzou (2005) also conclude that there seemed to be no evidence of a co-integration relationship between any domestic price in the URT and any international price. Figure 65 compares the monthly maize prices in Dar es Salaam and the two main international export prices (Argentina and the United States of America) using data reported in FAO's Global Information and Early Warning System on Food and Agriculture (GIEWS). As shown, prices in Dar es Salaam follow trends that are mostly unrelated to the prices in major exporting areas. This is particularly so during the period between 2008 and 2010 and from 2011 onwards. - 50 100 150 200 250 300 350 400 450 US$/tonne Dar-Es-Salaam Arusha Mbeya Bukoba Sumbawanga Monitoring African Food and Agricultural Policies (MAFAP) 179 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 65: Maize prices in selected international markets and Dar es Salaam, 2005–2012 Source: USDA for USA Gulf, IGC for Argentina and RATIN for Dar es Salaam as reported by FAO GIEWS. Regional market integration in the East African Community. Maize is the most widely traded commodity in East Africa. As depicted in Figure 66, Kenya is the main importer of maize in the region, attracting production from Uganda and the URT. In fact, deficit markets in Kenya act as the main driving force for surplus production in neighbouring countries (World Bank, 2009). In addition, Uganda also exports a share of its surplus towards South Sudan. Figure 66: Regional markets for maize in East Africa Source: www.fews.net 0 100 200 300 400 500 600 Dec-05 Feb-06 Apr-06 Jun-06 Aug-06 Oct-06 Dec-06 Feb-07 Apr-07 Jun-07 Aug-07 Oct-07 Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Dec-08 Feb-09 Apr-09 Jun-09 Aug-09 Oct-09 Dec-09 Feb-10 Apr-10 Jun-10 Aug-10 Oct-10 Dec-10 Feb-11 Apr-11 Jun-11 Aug-11 Oct-11 Dec-11 Feb-12 Apr-12 Jun-12 Aug-12 Oct-12 Dec-12 US$/tonne USA GULF Argentina Dar es Salaam 180 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Notwithstanding the importance of the maize trade, market integration remains weak. The World Bank (2009) also highlights the existence of long-run equilibrium relationships for maize markets between Kenya and the URT; however, once that a shock disrupts the long-run equilibrium is broken, the adjustment pace for the URT is much weaker than that of Kenya. The effect of a border between two EAC countries in reducing long-term elasticities of maize more than doubles when the border involves the URT. Basically, the effect of trading across the border of the URT has the same effect as increasing the distance between markets inside the country by 420 km. These same results are corroborated by Ilhe, von Cramon-Taubadel and Zorya (2011). In their model, they consider that market integration is affected by transaction costs (i.e. MAFAP market access costs); the quality of infrastructure, trade-related institutions and policies; and the costs of border crossing. These are approximated by distance, country specific dummies and border-crossing dummies. When regressing market integration against these variables, they conclude that even when distance plays a significant role in price transmission (i.e. the longer the distance between markets, the lower the price transmission), crossing borders also has an impact on market integration. A general border impact is identified; however, not all borders play the same role in restricting price transmission. The border between Kenya and the URT significantly reduces market integration, while the border between Kenya and Uganda has no effect. No test is done for the border between Uganda and the URT; however, the fact that the URT still charges USD 10 per tonne of maize (USD 200 per truck) as a fee when crossing the border between both countries (The Citizen, 2012) would seem to weaken market integration here also. Less attention has been paid to integration with other neighbouring countries, such as Burundi, the Democratic Republic of the Congo, Malawi, Mozambique, Rwanda or Zambia. However, worse infrastructure in route to those countries would suggest that the border effect of the URT also prevents higher degrees of integration. Plotting the monthly prices of maize in Dar es Salaam versus the main markets in the neighbouring countries (Figure 67) shows that market integration, at best, happens during specific periods of time. For example, with Nairobi, correlation seems to break at 2008, resumes in 2010 and breaks again in 2011. The same appears to happen, even when they are not the exact same periods, with Kigali, Lilongwe and Zambia. Prices in Dar es Salaam and Kampala look much more correlated. However, the period of high maize prices seems to last longer in Dar es Salaam than in Kampala. Lastly, Bujumbura and Dar es Salaam seem to be the least correlated markets in this analysis. In conclusion, maize markets in the URT do not seem to be integrated within the country, nor integrated with its neighbours and international markets. The lack of integration has been associated with high transaction costs inside the country (Kweka, 2006), while the lack of integration with neighbouring countries is related with high non-tariff barriers and erratic trade policy (Cadot and Gourdon, 2012). Against this background, how the maize export trade ban has affected maize farmers and consumers in the URT will be assessed. Monitoring African Food and Agricultural Policies (MAFAP) 181 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Figure 67: Maize prices trends in Dar es Salaam and major capitals of neighbouring countries Dar es Salaam versus Nairobi Dar es Salaam versus Kampala Dar es Salaam versus Zambia (national average) Dar es Salaam versus Lilongwe Dar es Salaam versus Kigali Dar es Salaam versus Bujumbura Source: Authors’ elaboration using MTI and FAO GIEWS price data. - 100 200 300 400 500 600 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam Nairobi - 50 100 150 200 250 300 350 400 450 500 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam Kampala - 50 100 150 200 250 300 350 400 450 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam ZAMBIA - 100 200 300 400 500 600 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam LILONGWE - 100 200 300 400 500 600 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam Kigali - 100 200 300 400 500 600 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per ton Dar-Es-Salaam Bujumbura 182 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Impacts of the export ban: a review of the literature The United Republic of Tanzania has resorted to trade restrictive measures with respect to maize; this makes the URT the only country in East Africa that formally restricts trade (World Bank, 2009). Export bans are called when production falls or when prices are high in order to assure food security in the country. Different arguments have been given in favour of the export ban, including food security (to prevent food leaving the country when there are shortages in some areas) and price stabilization. The latter refers to the practice of imposing a ban before harvests to prevent farmers from selling their crops at very low prices due to the lack of information on destination prices. Bans are lifted after harvests when farmers can obtain higher prices knowing the market conditions in Dar es Salaam or in other countries. The bluntest statement supporting the export ban is that maize cannot be flowing towards neighbouring countries while areas in the URT are facing food shortages. The export ban also affects movement of maize within the country, as traders have to demonstrate that maize being transported is not intended for export. Therefore, the export ban is expected to: i) increase food availability in the country, most importantly in food-deficit areas; ii) limit price hikes; and iii) reduce volatility. In turn, lower output prices result in lower incentives to farmers to produce greater output, which in the long run also hurts net maize buyers, as maize output is kept below its potential (World Bank, 2009). The export ban has been part of the history of the URT during the last decade. Table 29 shows that in the past eight years the ban has been enacted and lifted at least ten times. This is an example of policy volatility; it has also generated a situation whereby there is no certainty to agents in the value chain regarding whether the ban is in place or not. As Stryker (2012) notes, the ban sometimes excludes some regions and sometimes does not. Moreover, delays in transmitting the implementing orders to border posts and agencies involved in trade control means that official announcements do not immediately liberalize or restrict trade. Table 29: Chronology of export restrictions events in the United Republic of Tanzania, 2004–2013 Date Event 2004 Withdrawal of all maize export permits given to traders and the suspension of issuing new ones January 2006 Export ban lifted for two months March 2006 Export ban reintroduced January 2007 Export ban lifted January 2008 Export ban reintroduced May 2008 Export ban lifted January 2009 Export ban reintroduced October 2010 (or April 2010) Export ban lifted May 2011 Export ban reintroduced January 2012 Export ban lifted Source: World Bank (2009), FAPDA and Stryker (2012). Monitoring African Food and Agricultural Policies (MAFAP) 183 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Theoretically, an export ban acts as an infinite export tax. Of course, enforcement of the ban is never complete, and significant informal trade occurs and has been recorded with more or less continuity in time by the Famine Early Warning System of USAID and the Eastern African Grain Council (EAGC). A recent review by Stryker (2012) shows that informal trade happens irrespective of the presence of a ban; however, it increases significantly during ban periods. Figure 68 shows the trends of informal maize exports from the URT to Kenya during the period July 2010 to December 2011 using the data by Stryker (2012). Informal trade includes both the difference between exports reported by the URT and imports reported by Kenya and estimates of informal trade via “panya” 36 routes provided by the sources mentioned above. Formal trade (i.e. exports reported by the URT) remains below the 500 tonnes per month figure during the whole period. As shown, a first impact of the export ban is a surge in informal trade with Kenya. The difference in volumes of informal exports is significant at the 5 percent level, while formal trade does not seem to vary (Table 30). Figure 68: Informal maize exports from the United Republic of Tanzania to Kenya Note: shaded areas show periods in which the export ban was in place. Source: Stryker (2012) and Authors’ elaboration 36 “Panya” means mouse in Swahili; and “panya” routes refer to ungazetted border-crossing routes. 0 10,000 20,000 30,000 40,000 50,000 60,000 Tonnes Informal maize exports from URT to Kenya 184 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 30: Comparison of average informal maize exports from the URT to Kenya during export ban and non- export ban periods, July 2010 to December 2011 Type of exports Average exports (tonnes per month) T-value for means p-value Conclusion Ban No ban Formal 48 108 –1.10 0.350 No significant change Informal 10 240 1 433 1.89 0.049 Significant increase Note: See Table 29 to identify periods of export ban considered. Source: Authors’ elaboration using data from Stryker (2012). The theoretical impacts of an export ban on domestic prices are twofold (Minot, 2010b). First, export bans should lower prices in production areas and be more volatile owing to additional supply being available to meet local demand. In addition, prices in deficit areas should also remain lower. Gillson (2011) notes that many countries have tried to insulate their domestic markets from the volatility on international markets by putting exports bans on export products when prices increased in order to maintain internal prices lower than international prices. Evaluating the impact of export bans in Zambia, Dorosh, Dradri and Haggblade (2007) used a simplified partial equilibrium model to show that when harvests are below average export bans make prices grow five times more than when trade is allowed. When harvests are above average, export restrictions make maize prices fall twice as much as if exports were allowed. In the case of the URT, Diao, Mabiso and Kennedy (2012) use a Computable General Equilibrium model to simulate the impact of the export ban, comparing a scenario where the ban remains in place until 2017 with another where the ban is lifted in 2012. Because of the low share of maize in total food expenditure, export bans have a limited impact on the overall food price index. Taking into account the high domestic transport costs and the evidence mentioned above regarding the lack of domestic market integration, maize prices fall significantly in surplus areas. However, that decrease is not totally transmitted to deficit areas; price reductions in those areas range between 46 percent and 29 percent depending on the pair of markets analysed. Economy-wide impacts lead to a situation where wealthier urban households are the ultimate beneficiaries of the measure. Moreover, the lower maize prices, as a result of the ban, generate a drop in production growth of approximately 20 percent over the long run. This result is further supported by the findings of Chapoto and Jayne (2010), who conclude that countries that have pursued food price stabilization and food-security objectives via direct state operations have lagged behind the regional average of production growth. A less sophisticated analysis was used by the World Bank (2009) to assess whether the export ban has an impact on market integration and prices using margins between the major export markets and prices in the URT. Gross margins are estimated as the absolute price differences between markets. Using data from 2000 to 2008, margins are compared during ban and no-ban periods for three pairs of markets: Nairobi and Dar es Salaam; Nairobi and Mbeya; and Nairobi and Arusha. The price differences were significantly higher during ban periods than during non-ban periods for Nairobi and Dar es Salaam and for Nairobi and Mbeya, but insignificant between Nairobi and Arusha. The fact that no impact is detected between Nairobi and Arusha is because the ban is not effective in this area owing to the porous border and the significant profit potential associated with an average price difference of USD 70 between Nairobi and Arusha. This situation also existed in 2009, with a price Monitoring African Food and Agricultural Policies (MAFAP) 185 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report gap of over USD 72 between those two markets (Barreiro-Hurle, 2012), while marketing costs have been estimated at USD 40 (Short, 2012). Thus, the World Bank (2009) concludes that the export ban has a stronger impact on farmers from the Southern Highlands, who bear the additional transaction costs related to the illegal movement of maize within the country (over 1 000 km) in addition to the informal border crossing. Additional measures of the impact of the maize export ban As far as price volatility is concerned, the coefficient of variation of wholesale prices for maize in the main markets for which the MTI reports prices have been compared for the period 2006–2012. Results reported in Table 31 are consistent with the theoretical assumptions put forward by Minot (2010b). As shown, volatility in producing areas (Iringa, Mbeya and Sumbawanga) increases during the ban periods. However, at an aggregate level, volatility is reduced for the whole country. Table 31: Volatility of maize prices in different markets of the URT during export ban and non-export ban periods, 2006–2012 Market Unconditional coefficient of variation Impact of the ban on the coefficient of variation Export ban periods Non-export ban periods Arusha 0.40 0.26 Increase Babati 0.46 0.27 Increase Bukoba 0.40 0.33 Increase Dar es Salaam 0.40 0.25 Increase Dodoma 0.41 0.23 Increase Iringa* 0.35 0.19 Increase Kigoma* 0.18 0.22 Decrease Lindi 0.28 0.33 Decrease Mbeya* 0.38 0.25 Increase Morogoro 0.34 0.25 Increase Moshi 0.42 0.25 Increase Mtwara 0.26 0.29 Decrease Musoma 0.31 0.31 No change Shinyanga 0.33 0.24 Increase Singida 0.36 0.25 Increase Sumbawanga* 0.29 0.24 Increase Tabora 0.29 0.25 Increase Tanga 0.39 0.30 Increase URT 0.31 0.32 Decrease * Refers to major maize surplus areas. Note: See Table 29 for periods of export ban considered. Coefficient of variation calculated as standard deviation of prices divided by average price for each period. Source: Authors’ elaboration using data from MTI. 186 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report As far as price levels are concerned, there is no counterfactual that would allow to see how prices would have evolved in the absence of the export ban. However, how the prices in the URT evolved compared with the regional hub market of Nairobi can be assessed. As shown in Figure 69, prices during the ban in 2006 started falling earlier than those in Nairobi. During the 2008 ban, prices stopped rising and did not resume the upward trend even when the ban was lifted. The long ban period in 2009–2010 kept prices in the URT below those in Nairobi. Finally, the ban in 2011 partly mitigated the price rise that occurred in Nairobi. From this visual inspection, it cannot be concluded whether the ban actually maintained prices in the URT lower than in the absence of the ban; however, it seems that it was partially successful. During the period when the export ban was in place, moreover, there were also substantial releases of maize from the National Food Reserve Agency (NFRA)37; thus, the impact of the export ban from that of the releases of the NFRA cannot be isolated, as both tend to depress domestic prices. Figure 69: Maize prices in selected markets in Nairobi and in the United Republic of Tanzania, 2006–2012 Note: Shaded areas show periods during which the export ban was in place. Source: MTI and GIEWS FAO. A more formal analysis can be made comparing prices in domestic markets with those in areas where exports would normally flow following the approach by the World Bank (2009). This is done in a two- step approach; first examining the impact of the export ban on domestic markets and then for 37 The NFRA released over 150 000 tonnes in 2005–2006 and in 2009–2010, the highest volumes of the entire period for which data are available on NFRA operations (1999–2011). - 100 200 300 400 500 600 2006-01 2006-03 2006-05 2006-07 2006-09 2006-11 2007-01 2007-03 2007-05 2007-07 2007-09 2007-11 2008-01 2008-03 2008-05 2008-07 2008-09 2008-11 2009-01 2009-03 2009-05 2009-07 2009-09 2009-11 2010-01 2010-03 2010-05 2010-07 2010-09 2010-11 2011-01 2011-03 2011-05 2011-07 2011-09 2011-11 2012-01 2012-03 2012-05 2012-07 USD per Ton Dar-Es-Salaam Mbeya Iringa Sumbawanga Nairobi Monitoring African Food and Agricultural Policies (MAFAP) 187 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report regional trade. Domestic margins are analysed comparing margins calculated as price differences between Dar es Salaam and five other markets (see Figures 62 and 63): i) three in the Southern Highlands (Iringa, Mbeya and Sumbawanga); ii) one on the border with Kenya (Arusha); and iii) one on the border with the Democratic Republic of the Congo and Rwanda (Kigoma). The results are presented in Table 32. As it can be seen for prices in main producer areas, the export ban significantly increases the price difference with respect to Dar es Salaam for two out of the three markets, while there is no impact for the third market (Iringa). Makambako in Iringa is an assembly area for maize from Mbeya and Sumbawanga and is closer to Dar es Salaam. Thus, the ban is lowering the maize price in surplus areas with respect to what would be expected in the absence of the ban. The results for the other two markets show that there is no impact of the ban on price relationships between Dar es Salaam and Arusha, while producer prices in Kigoma increased, highlighting the lack of domestic integration within the URT as surplus productions in the Southern Highlands were not mobilized to decrease price spikes in the lake area of the country. Indeed, additional analysis shows that the price differences between Kigoma and the Southern Highlands significantly increased during the export ban periods. Table 32: Comparison of average margins for maize in periods with and without the export ban for select markets in the United Republic of Tanzania (2006–2012) Markets Average price differences T-value for means p-value Conclusion Ban No ban DSM – MBE 55.41 42.08 1.88 0.032 Decreased producer prices DSM – SUM 92.17 69.81 2.07 0.022 Decreased producer prices DSM – IRI 43.91 56.65 1.47 0.073 No change DSM – ARU 10.66 11.69 0.21 0.417 No change DSM – KIG -17.79 -34.74 1.76 0.042 Increased producer prices DSM: Dar es Salaam; MBE: Mbeya; SUM: Sumbawanga; IRI: Iringa; ARU: Arusha; KIG: Kigoma Note: See Table 29 to identify periods of export ban considered. Source: Authors’ elaboration using wholesale prices from MTI. The second step of the analysis is done comparing prices in border areas with those in the closest export markets. For this analysis, the following market pairs were considered: i) Dar es Salaam versus all major markets in neighbouring countries (Kenya–Nairobi; Uganda– Kampala; the Democratic Republic of the Congo–Bunia and Kisangali, Rwanda–Kigali, Burundi–Bujumbura; Zambia–national average; and Malawi–Lilongwe and Mzuzu); ii) Arusha versus Kenya (Nairobi); iii) Bukoba versus Uganda (Kampala); Rwanda (Kigali) and Burdundi (Bujumbura); iv) Kigoma versus Rwanda (Kigali) and Burdundi (Bujumbura); and v) Mbeya versus Zambia (national average) and Malawi (Lilongwe and Mzuzu). 188 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Table 33 reports the results. The most consistent result is that the Southern Highlands region is the most affected by the export ban. First, the price margins between Mbeya and the countries to the south surge when the export ban is in place. Moreover, most of the surplus from those regions goes either legally to Dar es Salaam, which also increases the price difference with Mbeya (see Table 32), or informally to Nairobi (see Figure 66). The price differential with Nairobi increases, but not significantly. Thus, the ban also curtails opportunities for maize producers to receive higher prices to the south. Moreover, prices in Dar es Salaam seem not to be totally isolated from price spikes when the ban is in place as price differences with neighbouring countries are reduced during the ban period. This, however, might be due to the policies those countries have in place to control prices (i.e. market interventions). Table 33: Comparison of average margins for maize in periods with and without the export ban for select markets in the United Republic of Tanzania and neighbouring countries (2006–2012) Markets Average price differences T-value for means p-value Conclusion Ban No ban DSM – NBO 44.65 43.54 0.09 0.465 No change DSM – KAM -32.02 -6.76 1.76 0.041 Increase DSM – BUN 194.22 259.52 1.91 0.031 Decrease DSM – KIS 29.37 110.06 2.50 0.008 Decrease DSM – KIGA 42.20 71.12 2.21 0.015 Decrease DSM – BUJ 107.31 153.84 3.21 0.001 Decrease DSM – ZAM -7.58 3.84 0.67 0.254 No change DSM – LIL 12.43 12.46 0.00 0.500 No change DSM – MZU 28.57 - 51.60 4.43 0.001 Increase ARU – NBO 44.38 71.95 2.32 0.002 Decrease BUK – KAM 29.72 -48.23 3.65 0.001 Decrease BUK – KIGA 103.72 31.49 4.03 0.001 Increase BUK – BUJ 145.27 144.91 0.02 0.500 No change KIG – KIGA 37.55 140.80 2.78 0.004 Decrease KIG – BUJ 79.11 254.23 5.47 0.001 Decrease MBE – ZAM 77.41 12.36 6.13 0.001 Increase MBE – LIL 88.65 32.17 2.86 0.003 Increase MBE – MZU 79.26 0.65 5.09 0.001 Increase MBE – NBO 100.17 86.53 0.99 0.175 No change DSM: Dar es Salaam; MBE: Mbeya; KIG: Kigoma; BUK: Bukoba; ARU: Arusha; NBO: Nairobi; BUN: Bunia; KIS: Kisangali; KIGA: Kigali; BUJ: Bujumbura: ZAM: Zambia; LIL: Linlongwe; MZU: Mzuzu. Note: See Table 29 to identify periods of export ban considered. Source: Authors’ elaboration using wholesale prices from MTI and FAO GIEWS. Margins between Arusha and Nairobi are lower during the ban, highlighting the role of informal exports mentioned above. It seems that during the ban more informal exports take place and arbitrage the price differences between those two markets. The same seems to happen with the western markets of Kigoma and Bukoba where price differences fall during export ban periods. Monitoring African Food and Agricultural Policies (MAFAP) 189 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report The theoretical impacts associated with an export ban should also be captured in the price incentives and disincentives indicators calculated by MAFAP. In this sense, with well-functioning markets and no other additional policies in place, disincentives to farmers would be reflected in negative nominal rates of protection. This would mean that farmers would be getting lower prices than those attainable in the absence of policy interventions. Because of the limited formal trade, the analysis that MAFAP does regarding incentives and disincentives faces additional challenges. Benchmark prices used to calculate incentives are not very informative in this case and the official or reported trade position of the country may not represent the actual trade flows. Moreover, yearly averages, which are constructed without taking into account volumes marketed, partially mask incentives and disincentives. Indeed, during some parts of the year (mainly when farmers are selling their maize) domestic prices are lower 38 and the methodology would identify disincentives as occurring; however, as there is a lack of storage capacity, domestic prices surge the further we move away from harvest, leading to higher domestic average prices that mask the disincentives. The MAFAP indicators for the 2006–2010 period are reflected in Table 34. Several things seem to be inconsistent: i) The net trade position of maize for the URT based on official data from the UN Comtrade or the Tanzania Revenue Authority does not seem to relate to the export ban. In fact, the trade ban was in place during 2006 (March to December), 2008 (January to May), 2009 (whole year) and 2010 (January to October), and the trade statistics show the URT as a net importer in 2006, 2008 and 2010. ii) The general situation of disincentives holds for years when the URT is considered an importer. This means that the export ban depresses domestic prices making imports too expensive for the domestic market. Importers thus face losses or, if imports are made directly by the state, sell at subsidized prices. iii) When the URT is a net exporter and there is an export ban (i.e. 2009), the MAFAP analysis partially captures the negative impact of it. The data for 2007 show how the lack of domestic integration leads to exports receiving prices below those in other areas of the country, further highlighting the problem of seasonality. Table 34: MAFAP nominal rates of protection (NRP) for maize in the United Republic of Tanzania, 2006–2010 2006 2007 2008 2009 2010 Trade status for the year m x m x m Observed NRP at farmgate (%) -14.2 20.5 -20.9 3.7 -0.9 Adjusted NRP at farmgate (%) -6.6 1.6 -14.2 -1.0 -9.9 Source: Barreiro-Hurle (2012). 38 During the period 2006–2011, prices during harvest in wholesale markets in producing areas were significantly lower than those in non-harvest periods, except for 2007. Price differences ranged from 20 percent to 5 percent. 190 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report In addition, the URT has implemented a large-scale input subsidy since 2008, which might compensate for some of these disincentives. Thus, the impact of the export ban is reflected in the data; however, it is not as straightforward as it might seem. Seasonality, lack of market integration and other policies in place confound their effects. Conclusions This section has reviewed the existing literature on market integration for maize in East Africa and the impact of the trade restrictive measures that have been commonplace in the maize policy mix of the United Republic of Tanzania. The findings can be summarized in three main messages: i) Informal exports surge when export bans are in place. Thus, expected impacts in terms of lowering prices because of higher food availability are muted owing to this leakage. ii) The export ban does not enhance the domestic market linkages inside the URT. Thus, even when some additional production could remain in the country compared with the situation in the absence of the ban, the food deficit areas do not access the excess production in the market. iii) For the Southern Highlands, the export ban limits the profits of farmers; in the west and the north part of the country it seems to promote more trade. The export ban is affecting prices for farmers. As Karfakis and Rapsomanikis (2009) show, high margins reduce the area over which food is marketed, often insulating regions and households from price signals, and increase its cost. This reduction in price information may result in inefficient outcomes. Probably, a common manifestation of high margins is that it worsens export opportunities. However, in the URT, markets close to borders do not suffer impacts from the export ban (i.e. Arusha–Nairobi); thus, it seems that marketing costs in the domestic market are more affected than those related to border crossings. The export ban is introduced to lower prices and assure food security. The results show that these are at best partially achieved. Other research reviewed show that long-term impacts are far from beneficial to consumers and farmers alike. Thus, if the United Republic of Tanzania is to realize its potential as a bread basket for East Africa, other policy instruments should be considered, in particular to avoid low prices discouraging farmers from investing on productivity increases (Christensen and Cochrane, 2012). In turn, by suppressing farm output growth, consumers do not benefit from reduced prices. Currently, productivity trends for maize in the URT have been reported to be declining even in spite of the fertilizer subsidy (Druilhe and Barreiro-Hurle, 2012). As stated by Jayne (2012), the most important message to sub-Saharan African governments is, to manage price volatility they should make their role in markets more predictable. Export bans by definition are ad hoc measures; therefore, they should be avoided at all costs. The review of the empirical evidence regarding their impact on maize farmers in the URT show that they also lead to lower prices for farmers and higher prices for consumers, therefore not contributing to any of the dimensions of food security. As long as costs of exporting are lower than those of marketing within the country, export bans will only generate incentives for illegal exports, keeping farmgate prices low. Monitoring African Food and Agricultural Policies (MAFAP) 191 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Finally, although it is technically recommended that opening marketing for maize for the long-term benefits of producers who are likely to gain from the wider market, there are still required some specific policy instruments to mitigate the impact of consumer price surges when there is an unexpected sudden rise in export demands that drain most of the locally produced maize. It is also important to address the question of share of the producer to the final consumer prices in local urban markets and in external markets so that there is no excessive gains to intermediaries. 192 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Part4. CONCLUSIONS AND RECOMMENDATIONS The United Republic of Tanzania in its Development Vision 2025 is committed to achieve high quality livelihood, good governance and economic growth. This document acknowledges agriculture as the backbone of the economy and highlights the role of the private sector in attaining a ‘modernized, commercial, highly productive and profitable’ agricultural sector. Between 1993 and 2009, the United Republic of Tanzania has radically changed its growth path and its sectoral contribution to the national income (GDP). While the economy was growing at rates below 4 percent until 1996, real growth rates steadily increased until 2008, reaching above 7 percent, before slowing down while remaining above 6 percent from 2009 to 2011. On average, the Tanzanian economy has been growing at around 5.5 percent per year over the last 15 years, with an acceleration of the growth rate to 7 percent on average per year during the last 10 years. The agricultural sector has persistently registered a lower growth rate compared to other industry and service sectors. While agriculture has been growing at an average of 4 percent between 1998 and 2009, industry and service sectors have been growing at an average of 8.3 and 7 percent respectively during the same period. Even when the agricultural sector has persistently registered a lower growth rate compared to other sectors it has managed to produce between 5 and 19 percent above the normal national food requirements for basic cereals. In this context, it is essential to ensure that the agricultural and food policies and expenditures provide clear signals to support decisions by producers that are consistent with national policy goals. It is also essential to measure the consistency between the objectives of these policies, the measures being adopted and their resulting effects. For this, this report has analyzed the incentives to producers resulting from policies and market development gaps via price analysis and the level and composition of public expenditure in support to agriculture. In addition, the results of this two analysis is combined to assess policy coherence. Incentives, disincentives and market development gaps Policy incentives, disincentives and market development gap are measured and analyzed for nine agricultural products (cashew nuts, coffee, cow milk, maize, pulses rice, cotton, sugar and wheat), representing 36 percent of the total value of agricultural production, 47 percent of the value of exports, 44 percent of the imports and 55 percent of the caloric intake in the country. These products are grouped into four categories: Exported: cashew nuts, coffee, cotton and pulses; imported: cow milk, rice, sugar and wheat; thinly traded: maize, and; key products for food security: maize, pulses, rice, sugar and wheat. MAFAP indicators are based on the comparison between domestic prices at farmgate and wholesale and the reference prices, which are estimated by using the price of the product in the international markets. Reference prices are those that producers would obtain in the absence of national policies affecting the price levels and deficiencies in the structure and the functioning of the product’s Monitoring African Food and Agricultural Policies (MAFAP) 193 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report domestic value chain. These indicators are estimated at two levels: an observed and adjusted level. In the observed level, the reference prices measures the price that producers or traders of the commodity would receive in the world market of the commodity given the existing marketing costs, margins and any taxes. In the adjusted level of MAFAP indicators, the reference prices are adjusted to eliminate any distortions found in the market supply chain (for example, taxes or levies and excessive profit margins of economic agents). In other words, the observed indicators measure the level of incentives and disincentives given the existing functioning of the value chain and government policy on commodity transactions while the adjusted indicators measure the level of incentives and disincentives in absence of any distortions caused by market agents (such as monopoly power) or government policy (such as taxes). Overall producers in URT have been incentivized during the study period, although the level of incentives has been declining. In the 2005-2007 triennium the nominal rate of protection stood at 32 percent and it was reduced to 11 percent during the next three years (2008-2010). Thus we can conclude that policy environment and market performance lead farmers to receive higher prices than those that would exist in absence of policies and with well functioning markets. This trend masks a dual situation in the URT. Producers of commodities which are imported into URT are incentivized while producer of export oriented commodities are penalized. Moreover, our results show that while some commodities are protected at wholesale (processed) level they are penalized at farm gate (raw) level. This duality is also detected for the relative role of policy induced and market performance in the identified incentives and disincentives. While for imported commodities most of the incentives relate to trade policy, for export commodities disincentives relate both to explicit taxes and inefficiencies of the processing industry. In addition, we see how part of the protection for imported goods granted by trade policy is eroded due to excessive marketing costs along the value chain. Farmers producing commodities which URT imports to cover domestic consumption are in general incentivized. On average the nominal rate of protection for imports stood at 47 percent but there has been a clear downward trend, with incentives in the 2005-2007 period standing at 97 percent while in the 2008-2010 period they had plunged to 29 percent. These incentives are related to the common external tariff which the URT applies to imports coming from outside the Eastern African Community (EAC). However, for all imported commodities, protection levels are eroded as we move towards the farm gate due to lack of market integration and inefficiencies in the value chain. Incentives for rice in the URT have decreased in the last five years. This is a normal trend when the country moves towards self-sufficiency. However a salient finding is that the level of incentives used to be higher for farmers than for wholesalers in consumption areas, and following liberalization of the rice market in 2007, this balance changed and now protection is higher in consumption areas. Import tariffs in place in the United Republic of Tanzania prevent cheap imports and do result in effective price premiums for farmers but the cost for consumers is quite high. Despite the shift towards an export position for rice, yields remain below the region’s average, therefore, it is probable that without protection Tanzanian rice would not be competitive in international markets if prices return to their historical levels. The rice sector needs a supporting environment that leads to additional investment at farm level so as to increase yields and lower production costs. 194 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Trade policy is also reflected in the additional price that consumers need to pay for sugar in URT. Farmers however are not benefiting from this border protection and seem to be disconnected from changes in trade policy. Moreover, farmers are penalized by the low efficiency of the sugar mills. As a consequence, the current trade policy does not benefit farmers as much as a more efficient sugar industry would. Therefore, the government should consider removing the sugar import tariff, something that would require that sugar is taken away of the Sensitive Items list of the EAC Common External Tariff. In addition, the government of the United Republic of Tanzania should revise the investment environment in the sugar sector so as to allow companies to increase their efficiency and thus allow paying higher prices to sugar cane producers. Domestic wheat prices remain higher than their international equivalents and thus there is a clear transfer from consumers to traders and to lesser extent producers even when Tanzania has taken measures to reduce domestic prices of wheat. The Government of Tanzania should ease import procedures for wheat as there is still a high degree of market power in wheat imports that allows traders to charge prices well above the import parity price. While excessive port and import costs can account for most of the price difference identified, even if the highest cost estimate of imports are considered, protection is well above the prevailing tariff. Even when price incentives have been significant during the study period there has been no increase in domestic production. Additional investment on research and development for wheat is needed if the production of the crop is to be increased in the country. Milk traders are protected by the existence of the external tariff, leading to consumers paying higher prices for milk than those prevailing in international markets. However, this protection only affects a small share of total milk production, the rest of the market is mainly disconnected from international markets. Farmers in the informal market also get higher prices, although the price difference is much smaller, therefore some of the protection also leads to incentives to milk producers at the cost of consumers in local markets. If more milk production were to be processed and marketed in a more formal way, the processing industry could only pay lower prices to farmers due to high processing costs. Therefore if the government does not want to see milk farm gate prices collapsing movements towards a more commercial dairy sector should be accompanied by improvements in milk processing efficiency. Farmers producing export commodities in URT are in general disincentivized, meaning that the policy environment together with the market performance leads then to get lower prices than those they could obtain in a policy free environment and with better market performances. These disincentives are related to taxation of the commodities (cotton, cashew nuts), bad functioning of the value chain (coffee, cashew nuts) and inefficiencies in the processing sector (cotton). Contrary to classic export crops, pulses producers have positive indicators meaning that domestic prices are on average higher than export parity prices. While in general this would be considered an incentive for producers, in this specific case it shows a bad functioning of the value chain, where lack of storage facilities means exporters are missing the opportunity to benefit from higher prices in domestic markets and consumers paying higher prices. Coffee farmers have been receiving disincentives ranging from 15 percent to 50 percent during the period of analysis. As there are no explicit trade policies in place, the disincentives identified are related to overall market development gaps. It could be attributed to the pricing system of the value Monitoring African Food and Agricultural Policies (MAFAP) 195 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report chain and the administrative burden imposed by the Tanzania Coffee Board which both increases transaction costs in the value chain and limit new entrants. The system protects farmers when prices are low, but, it actually limits their capacity to benefit from high prices. Trade liberalization has to some extent helped improve the sector, although, not much is being done to ensure that small-scale farmers are receiving the amount they could potentially obtain. Therefore, the government should further enforce the one license system as it is still clear that major multinationals control the auction and this makes farmers receive a low share of the export price. Even in the best years farmers only get 46 percent of the export price and, when all access costs are included, still face a disincentive of nearly 200 USD per ton. Moreover, facilitating the entrance of new players to the coffee auction could break the current dominance by four big companies in exports of Tanzanian coffee. Cotton farmers also have faced disincentives throughout the whole period of analysis. The organization of the cotton sector taxes cotton farmers on average 30 percent thus limiting the investment capacity of farmers. This taxation is directly imposed by the government to the sector via different levies from regional and central administration together with cost imposed by the functioning of the different agents in the value chain. Instead of subsidizing farmers, the Government of the United Republic of Tanzania should consider reducing the tax burden on cotton production as a more efficient way of remunerating cotton growers. The low ginning out turn ratio of the ginning sector further penalizes farmers as the quantity of lint produced by ginners per tonne of seed cotton is lower than it could be. Modernization of the ginneries in URT should be a policy objective. The current Cotton Industry Implementation Plan should also include in its objectives the ginning industry and not only farmers and textile industry. Cashew nut growers in the United Republic of Tanzania are disincentivized, thus they are receiving a lower price than that they would in the absence of policy measures and well functioning value chains. The main driving force of the disincentives is the export tax on raw cashews. The shift towards a centralized auction and warehouse receipt system has increased the disincentives to farmers. Rather than getting farm gate prices closer to the export prices it seems the WRS has induced higher transaction costs. The increase of the export tax from 10% to 15% of FOB value to promote in country processing has had limited effectiveness in the first two years of implementation. The government of URT could consider reducing the export tax and monitor the evolution of the indicators to see whether farmers get higher prices. This could lead to more investment in the production of cashew nuts. At the same time if the objective of increasing processing inside the country is to be achieved. The government should consider alternative policy instruments to promote the processing of cashew nuts in Tanzania. Last, the CBT should provide additional support to the warehouse receipt system functioning to assure it delivers the expected results. Contrary to the traditional export commodities discussed above, we observe that overall farmers producing pulses in Tanzania face higher prices than those in international markets. This apparent incentive to producers hides a situation where lack of storage makes farmers sell at low prices (post harvest) which later result in prices during non-harvest periods that are higher than those they are made when exporting. Basically these results show that Tanzania is facing higher domestic prices thus putting additional pressure on net food buyers. In this situation two strategies could be sought. First, increasing the linkages between the different markets in the country could allow consumers to purchase pulses at lower prices and traders to make more money selling in the domestic markets than with exports. This is particularly acute in the case of beans where price gaps are higher. Second, 196 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report increasing the storage capacity of farmers would allow them to capture higher prices in domestic markets As far as thinly traded products are concerned we see that incentives and disincentives to maize producing farmers are very volatile. For this commodity, a mix of variable policy decisions (trade restrictions, subsidized sales) and lack of market integration in the country due to excessive transport costs generate disincentives to farmers. Overall farmers are getting lower prices than those that would be attainable in the absence of policy and with better market performance. The general pattern for incentives and disincentives detected in URT applies to producers of commodities representing a significant share of the diet in URT. From a consumer perspective, these incentives lead to increased food bills, reducing affordability. Thus our results show a conflicting impact on food security. On one side, farmers are incentivized thus likely to invest more and hence increase their production. This has been most visible for rice, where URT has gone from being an importing country to a net exporter. However for the rest of the commodities these incentives do not seem to have a positive impact on domestic food availability. Moreover, these incentives for producers imply that Domestic prices are higher than those that would prevail without policy interventions and functioning markets. Public expenditure and aid Despite total approved budget in the sector grew by 53 percent, in nominal terms, from 2007 to 2011, in relative terms, the agricultural budget allocations have declined from almost 13 percent of total government spending in 2007 to about 9 percent in 2011. Actual spending has grown at a slower pace and in relative terms has also decreased significantly in the analysed period. Thus while surpassing the 2003 Maputo Declaration target during the period 2007-2009 it has remained below since then. Agriculture-specific expenditures account, on average, for almost 45 percent of expenditures in support of food and agriculture sector development. Their importance in overall agricultural support grew from about 29% in 2007 to 64 percent in 2011. In terms of the level of spending, agriculture- specific expenditures more than doubled over the analysed period, while agriculture-supportive expenditures decreased significantly. Agricultural specific support has shifted from general support to payments to agents. While the latter accounted for over 60 percent of all this category of expenditure in the first half of the analyzed period, increased focus on payments to producers via input subsidies meant that in the second half of the period analyzed its weight was reduced to less than 50 percent. This increase of direct transfers to producers has led to a decrease on extension services and general infrastructure for the sector such as storage facilities, marketing and infrastructure. Surprisingly, this happened while expenditure in training increased more than offsetting the decrease in extension services. Additional efforts to clarify the nature of the programmes identified for these two categories is needed. The agriculture-specific expenditures are complemented by agriculture-supportive expenditures which, on average, accounted for about 55 percent of the overall support to food and agriculture sector in Tanzania. However, their relative importance in the total support to agriculture has Monitoring African Food and Agricultural Policies (MAFAP) 197 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report decreased over time. Among these expenditures, by far the largest were on rural infrastructure, including rural roads, rural water and sanitation and rural energy. Their relative importance in the agriculture supportive expenditures did not change over time. Much less was devoted to rural health or rural education. Overall, most public expenditures are aimed at the provision of public services and investments, with a relatively strong focus on infrastructure, but also on training, extension services and research. However, there is a rapidly growing spending on input subsidies to agricultural producers, particularly subsidies to variable inputs. Only a minority (four percent) of public expenditure for the agricultural sector is commodity specific, nearly half of the public expenditure is not targeted to any specific commodity or group of commodities. Approximately one fourth is focused on maize and rice (mainly the fertilizer subsidy) while the remaining fourth goes to very broad commodity groups. A large part of funds is allocated to policy administration costs. The increased share of administration costs after 2008/09 may be partially explained by the reallocation of funds devoted to policy transfers due to financial crisis management, as mentioned above, however, they have substantially increased over the analysed period. Moreover, the rates of actual spending to budget allocation in Tanzania are low, and even lower for policy transfers than in case of administrative costs. On average, donor spending accounted for at least 50 percent of overall public expenditures in support of the food and agriculture sector in Tanzania. However, the role of foreign aid has seen a diminishing trend during the period. In terms of composition external aid contributed to 44 percent of agriculture-specific measures and to 64 percent of agriculture supportive measures. Donor and government priorities in allocating public expenditure are quite aligned. Coherence of agricultural and food policies Two main objectives seem to be underlying in the overall policy framework for the agricultural sector in the United Republic of Tanzania: increasing food availability and food accessibility. As far as the food availability domain we can see that with the exception of rice and wheat in general the overall policy environment and, to a greater extent, the functioning of the value chains result in lower prices for farmers than those that could be expected in absence of domestic policies and with better performing value chains. Rice can be seen as a success story in Tanzania where increased protection has led to higher production and making the URT a surplus country in terms of rice production, however this should be taken with care. First, most of the increased production is due to area increase and not yields. Yields remain below the average in east Africa and when international prices return to their pre crisis levels exports from Tanzania might no longer be competitive. In the case of wheat, incentives have not resulted in increased yields or areas, thus showing that maybe the URT is not best suited to produce wheat. All other commodities show disincentives in our analysis, thus not allowing farmers to get higher prices for their output and limiting investment. This could mean that food accessibility would be promoted, as domestic food prices would be below those prevailing in international markets. However, most of the disincentives relate to classic export crops (coffee, cotton, cashew nuts) which are not part of the normal diet of Tanzanian citizens. At wholesale level (i.e. the level closest to consumers purchase) most of the food security commodities show positive 198 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report price gaps with the exception of maize, thus the cost to consumers of the average diet is higher than it would be in absence of policies and with better performing markets. To better address these objectives specific recommendations have been mentioned for each commodity but in general this could be resumed in moving towards a less volatile trade policy (ideally deciding whether import tariffs are needed or not and moving definitively away from export bans) and more investment in infrastructure that facilitates market functioning (i.e. roads, storage, market information systems, etc.). Initiatives such as SAGCOT seem to point towards this direction, the draft of the ASDP II is a unique opportunity to align public investment and policy environment to deliver the expected growth of agricultural output, increased productivity and reduced hunger and poverty. As shown in the discussion above, the results of our analysis show a contradictory story regarding policy objectives and actual impacts of policy measures and market performance. With regards to trade policy, contradictory actions (i.e. tariff versus waivers) generate uncertainty for producers and tax export oriented commodities. Moreover, market performance and processing capital stock does lower prices to farmers. Public expenditure fails to address this issues as it does not seem to focus on the areas which we identify as most crucial in generating these disincentives (i.e. marketing, storage, processing). Nevertheless, the government of URT seems to have taken policy measures to reduce investment costs and reduce access costs. The abandonment of export bans, the move towards eliminating district taxation for agricultural products, the concept behind SAGCOT are all measures that will reduce the level of disincentives for farmers. If these measures persist in time and are implemented as planned results in years to come should show lower disincentives for farmers showing better policy coherence. 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Tanzania Milk Processors Association (TAMPA) 2011. Harmonization of regulatory framework in the dairy sector. Policy brief. Dar es Salaam, Tanzania Milk Processors Association (TAMPA). Temu, A.E., Manyama, A. & Temu, A.A. 2010. Maize trade and policy interventions in Tanzania. In A. Sarris and J. Morrison, eds. Food security in Africa. Market and trade policy for staple foods in Eastern and Southern Africa, pp. 317–353. Rome, FAO and Cheltenham, UK, Edward Elgar. The Citizen. 2011. Food export ban “here to stay”. 20 August 2011. Available online at http://www.thecitizen.co.tz/sunday-citizen/40-sunday-citizen-news/13968-food-export-ban-here-to- stay.html. The Citizen. 2012. One more step towards union of African states. 19 March 2012. Available online At http://thecitizen.co.tz/editorial-analysis/-/20779-one-more-step-towards-union-of-african-states. The Citizen. 2012. One more step towards union of African states.19 March 2012. United Nations Industrial Development Organization (UNIDO). 2011. Tanzania’s cashew value chain: a diagnostic. African Agribusiness and Agro-Industries Development Initiative. Vienna, United Nations Industrial and Development Organization (UNIDO) and Dar es Salaam, Ministry of Industry and Trade. USAID. 2010. Staple foods value chain analysis. Country report Tanzania. Washington, DC, United States Agency for International Development (USAID), Competetiveness and Trade Expansion Program (COMPETE). USAID. No date. Tanzania property rights and resource government profile. Van Campenhout, B. 2007. Modeling trends in food market integration: method and an application to Tanzanian maize markets. Food policy, 32: 112–127. Monitoring African Food and Agricultural Policies (MAFAP) 209 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Vice President’s Office (VPO). 2007. United Republic of Tanzania National Adaptation Programme of Action (NAPA). Dar es Salaam, Division of Environment. WDI. 2012. World Bank World Development Indicators database. http://data.worldbank.org/data- catalog/world-development-indicators WITS. 2012. World Integrated Trade Solutions. World Bank. World Bank. 2008. The urban transition in Tanzania. Washington, DC. World Bank. 2009. Eastern Africa: A study of the regional maize market and marketing costs. Report No. 49831-AFR. Washington, DC, Agriculture and Rural Development Unit. World Bank. 2010. Rapid budget analysis for annual review 2010/11 in the United Republic of Tanzania agriculture sector. Dar es Salaam. (unpublished). World Bank (WB). 2012. Africa can help feed Africa: removing barriers to regional trade in food staples. Poverty Reduction and Economic Management Africa Region, Report No. 66500-AFR. Washington DC, USA. World Bank & International Finance Corporation. 2013. Doing Business 2013. Smarter regulations for small and medium-size enterprises. Washington, DC. World Economic Forum. 2012. The Global Competitiveness Report 2012–2013. Davos, Switzerland. World Trade Organization (WTO). 2012. Trade policy review: East African Community (EAC), Annex 4 Tanzania. Geneva, World Trade Organization (WTO), Trade Policy Review Body. 210 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Annex I. SUMMARY OF MAIN METHODOLOGICAL CONCEPTS USED IN THE PUBLIC EXPENDITURE ANALYSIS. Main concepts The methodology proposes to capture all public expenditures that are undertaken in support of food and agriculture sector development. That includes expenditures from the national budget, either central or regional government, regardless of the ministry that implements the policy, and external aid, provided either through local governments or specific projects conducted by international organisation or NGOs. The primary focus is on the food and agriculture sector, however, for some countries forestry and fisheries may be an important part of rural activity and are also included in the scope of the project. We seek to capture all public expenditures in the rural areas, such as rural infrastructure, rural education and rural health, as they may also have an important role in agriculture’s sector development, even if they are not specific to the sector. Expenditure measures generate explicit or implicit monetary transfers to supported individuals or groups. We consider all those expenditure measures that generate explicit or implicit monetary transfers in support of food and agriculture sector development. These measures are divided into two main categories of expenditures: agricultural-specific expenditures and agricultural supportive expenditures. Agricultural-specific expenditures include those measures that generate monetary transfers to agricultural agents or sector as a whole. The agents, or the sector as a whole, must be the only, or the principal recipient of the transfers generated by the expenditure measure. Agriculture supportive measures should include measures that are not strictly specific to agriculture sector, but that have strong influence on agricultural sector development such as investments in rural development. All the measures that comply with these criteria are considered, regardless their nature, objectives or perceived economic impacts. Further, general expenditure measures available throughout the entire economy are not considered, even if they generate monetary transfers to agricultural sector. Finally, the expenditure measures are considered and classified according to the way in which they are implemented and not on the basis of their objectives or economic impacts. Classification and disaggregation Many expenditures of greatest relevance to agricultural development, in terms of their ability to expand the production frontier, may not be specific to agriculture, but could fall into other categories. Moreover, support can be provided in several different ways. Support to agricultural producers may be provided via reduced input prices (e.g. a fertiliser subsidy), cost sharing for fixed capital (e.g. machinery), revenue foregone by the government (tax concession), reimbursement of Monitoring African Food and Agricultural Policies (MAFAP) 211 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report taxes or charges or services in kind (e.g. delivery of extension services). Agriculture-specific support to the sector more generally may be provided via spending on agricultural education, research, marketing of agricultural goods, irrigation etc. Some policies, which benefit agriculture, may be even more general, such as expenditures on rural infrastructure, rural education or rural health. Although the latter are not sector specific, they may be sector supportive. In order to capture all public expenditures in support of the food and agriculture sector, the following breakdown is proposed. 1. A broad distinction between policies that are: agriculture-specific, agriculture supportive and non-agricultural expenditures. 2. Within the agriculture-specific category, a distinction between support to producers and other agents in the value chain, and general sector support. The agents in the value chain include farmers (producers), input suppliers, processors, consumers, traders and transporters. The detailed classification of support follows the OECD’s principle of classifying policies according to their economic characteristics i.e. the way they are implemented, which provides the basis for further policy analysis (OECD, 2008). The particular categories, however, should be designed to reflect the types of policies applied in African countries. Likewise, the categories proposed in the box below have been elaborated based on the experience of various agencies, including FAO (e.g. FAO, 2006), working on public expenditures in developing countries (for a comprehensive overview, see Balie et al., 2010). Further, drawing on the OECD’s experience, the classification proposed aims at distinguishing, to the extent possible, policies providing private goods as opposed to public goods, given their different economic effects. 212 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Proposed classification of public expenditures in support of the food and agriculture sector I. Agriculture-specific policies – monetary transfers that are specific to agriculture sector i.e. agriculture is the only, or major, beneficiary of a given expenditure measure I.1. Payments to the agents in the agro-food sector – monetary transfers to the agents of agro-food sector individually I.1.1. Payments to producers – monetary transfers to individual agricultural producers (farmers) A. Production subsidies based on outputs – monetary transfers to agricultural producers that are based on current output of a specific agricultural commodity B. Input subsidies – monetary transfers to agricultural producers that are based on on-farm use of inputs: variable inputs (seeds, fertiliser, energy, credit, other) – monetary transfers reducing the on-farm cost of a specific variable input or a mix of variable inputs capital (machinery and equipment, on-farm irrigation, other basic on-farm infrastructure) – monetary transfers reducing the on-farm investment cost of farm buildings, equipment, plantations, irrigation, drainage and soil improvements on-farm services (pest and disease control/veterinary services, on-farm training, technical assistance, extension etc., other) – monetary transfers reducing the cost of technical assistance and training provided to individual farmers C. Income support – monetary transfers to agricultural producers based on their level of income D. Other – monetary transfers to agricultural producers individually for which there is insufficient information to allocate them into above listed categories I.1.2. Payments to consumers – monetary transfers to final consumers of agricultural commodities individually in form of: E. food aid – monetary transfers to final consumers reducing the cost of food F. cash transfers – monetary transfers to final consumers to increase their food consumption expenditure G. school feeding programmes – monetary transfers to final consumers providing free or reduced- cost food in schools H. other – monetary transfers to final consumers individually for which there is insufficient information to allocate them into above listed categories I.1.3. Payments to input suppliers – monetary transfers to agricultural inputs suppliers individually I.1.4. Payments to processors – monetary transfers to agricultural commodities processors individually I.1.5. Payments to traders – monetary transfers to agricultural traders individually I.1.6. Payments to transporters – monetary transfers to agricultural commodities transporters individually 1.2. General sector support – public expenditures generating monetary transfers to the agro-food sector agents collectively I. Agricultural research – public expenditures financing research activities improving agricultural production J. Technical assistance – public expenditures financing technical assistance agricultural sector agents collectively K. Training – public expenditures financing agricultural training L. Extension/technology transfer – public expenditures financing provision of extension services M. Inspection (veterinary/plant) – public expenditures payments financing control of quality and safety of food, agricultural inputs and the environment N. Infrastructure (roads, non-farm irrigation infrastructure, other) – public expenditures financing off-farm collective infrastructure O. Storage/public stockholding – public expenditures financing public storage of agro-food products P. Marketing – public expenditures financing assistance in marketing of agro-food products R. Other – other transfers to the agro-food agents collectively for which there is insufficient information to allocate them into above listed categories II. Agriculture supportive policies – public expenditures that are not specific to agriculture, but which have a strong influence on agricultural sector development S. Rural education – public expenditures on education in rural areas T. Rural health – public expenditures on health services in rural areas U. Rural infrastructure (rural roads, rural water, rural energy and other) – public expenditures on rural infrastructure V. Other – other public expenditures on rural areas benefiting agricultural sector development for which there is insufficient information to allocate them into above listed categories Monitoring African Food and Agricultural Policies (MAFAP) 213 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report For more details on MAFAP methodology on measurement of public expenditures in support of food and agriculture sector development, see www.fao.org/mafap. 214 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Annex II. PROJECTS AND PROGRAMMES INCLUDE IN EACH OF THE CATEGORIES OF PUBLIC EXPENDITURE. List of measures and implementing government bodies included in the analysis of public expenditure in support of the agricultural sector and rural development. The final version of the report will provide further information identifying in which category(ies) each measure has been considered. As a first approach, measures in italics and red font refer to those which are included in the rural development expenditure (Category II. Agriculture supportive policies). Table Annex II.1. RECURRENT BUDGET Measure Implementing Government Body Contingencies non-emergency (subvote 2001) Treasury Prison farms (subvote 4003) MHA-prison services Administration and General (subvote 1001) MAFSC Finance and accounts (subvote 1002) MAFSC Policy and planning (subvote 1003) MAFSC Agriculture Training Institute (subvote 1004) MAFSC Internal audit unit (subvote 1005) MAFSC Procurement management unit (subvote 1006) MAFSC Infromation, education and commucation (subvote 1007) MAFSC Legal unit (sub vote 1008) MAFSC Management information unit (sub vote 1009) MAFSC Environment management unit (subvote 1010) MAFSC crop development (subvote 2001) MAFSC Agricultural mechanisation (subvote 2002) MAFSC Agricultural land use planning and management (subvote 2003) MAFSC Plant breeders'unit (subvote 2004) MAFSC Research development (subvote 3001) MAFSC Cooperative development (subvote 4001) MAFSC National food secuirity (subvote 5001) MAFSC Strategic grain reserve (subvote 5002) MAFSC Commodity market development (subvote 4002) MITM Directorate of irrigation and technical (subvote 2004) MWI Rural water supply (subvote 4001) MWI Drilling and dam construction agency (subvote 6001) MWI Science and technology (subvote 3003) MCST Forestry and beekeeping (subvote 3001) MNRT Fisheries (subvote 3002) MNRT Administration and General (subvote 1001) MLDF Finance and accounts(subvote 1002) MLDF Monitoring African Food and Agricultural Policies (MAFAP) 215 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Policy and planning (subvote 1003) MLDF Livestock research and training institute (subvote 1004) MLDF Information, communication and education (subvote 1005) MLDF National livestock institute - MPWAPWA (subvote 1006) MLDF Internal audit unit (subvote 1007) MLDF Procurement management unit (subvote 1008) MLDF Legal services unit (subvote 1009) MLDF Veterinary services (subvite 7001) MLDF Livestock identification, registration a (subvote 7002) MLDF Pastoral system development (subvote 7003) MLDF Central veterinary laboratories (subvote 7004) MLDF Animal production (subvote 8001) MLDF Fisheries development division (subvote 9001) MLDF Acquaculture development division (subvote 9002) MLDF Government subvetions to internal institutions and parastatals Agricultural council of Tanzania MAFSC Tanzania Official Seed Certification Institute MAFSC Tanzania Fetilizer Regulatory Authority MAFSC Tanzania Sisal Board MAFSC Tanzania Sugar Board MAFSC Tanzania Pyrethrum Board MAFSC Tanzania Tea Board MAFSC Tanzania Coffee Board MAFSC Tanzania Tobacco Board MAFSC Tanzania Cachewnut Board MAFSC Tanzania Cotton Board MAFSC Tanzania Cereal Board MAFSC Agricultural seed agency (asa) MAFSC Tanzania smallholder Tea Dev. Agency MAFSC Horticulture development council MAFSC Agriculture input trust fund MAFSC National sugar training institute MAFSC Tobacco research institute - torita MAFSC Tanzania coffee reseach institute MAFSC Tea Research Institute of Tanzania MAFSC Naliendele cashewnut research institute MAFSC Ukiliguru Cotton Research centre MAFSC Kibaha sugar research centre MAFSC Agricultural research institute- mlingano MAFSC Tanzania pesticides research institute MAFSC National food security agency MAFSC Centre for Agri.Mech. And Rural Tech. (CAMARTEC) MITM Small Industries Development organisation (SIDO) MITM Tanzania warehouse licensing Board MITM Sokoine University of Agriculture (SUA) MEVT 216 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report University of Dar es Salaam - agriculture MEVT Moshi University college Co-op and Business - agriculture MEVT Tanzania Food and Drugs Authority (TFDA) MHSW Tanzania Food and Nutrition centre MHSW Rural electrification agency MEM Tanzania forestry research institute MNRT Forest training institute MNRT Beekeeping training Institute MNRT Tanzania tree seed MNRT Tanzania fisheries research institute MLDF Tanzania diary board MLDF Tanzania meat board MLDF Table Annex II.2. DEVELOPMENT BUDGET Measure Implementing Government Body Small enterpreneurs loan facilities (self) Treasury National income generation programme (nigp) Treasury Cooperative reform and modernisation programme CDC Tasaf PO Lake Tanganyika Environment management programme V-PO Agriculutral markets system development programme (ASMDP) PMO Rural financial services programmes PMO Tanzania Multi- Sectoral AIDS project (TMAP) MAFSC Public sector Reform Programme II (PSRP ii) MAFSC Public sector Reform Programme II (PSRP ii) MAFSC Agriculture Sector programme support MAFSC Agriculture sector development programme (asdp) MAFSC, PMO-RALG, MWI, MITM, MLDF District agriculture sector investment programme ( dasip) MAFSC Public sector Reform Programme II (PSRP ii) MAFSC Enviroment Management Act (EMA) - implementation support programme MAFSC, PMO-RALG, MLDF, V-PO Participatory agricultural development empowerment project (padep) MAFSC Special programme for food security MAFSC Cleaner integral utilisation of sisal waste project MAFSC Accelerated food security project MAFSC Comprehensive agriculture development lower Rufiji MAFSC Lake Victoria enviroment management project MAFSC Agriculture land use planning and manage MAFSC Soil and water conservation MAFSC Tanzania tea research MAFSC Agriculture training institute MAFSC Stabex coffee MAFSC Cooperative Reform and Modernisation programme MAFSC Monitoring African Food and Agricultural Policies (MAFAP) 217 Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Tanzania mini Tiger plan 2020 MITM Epz development MITM BEST project MITM Rural micro, small and medium Enterprises MITM Improvement of Cotton/ coffee marketing MITM Legal sector reform programme MITM Rehabilitation of schools and colleges MEVT Unicef support to education MEVT Primary education development programme MEVT Improvement of primary education MEVT Provision of Secondary Education MEVT Secondary Education Development programme (SEDP) MEVT Implementation of BEST programme MLHSSD Village demarcation and ground photo MLHSSD Expansion and rehabilitation of rural water supply MWI Borehole drilling and dams construction MWI Rehabilitation of rural water MWI Rural water supply and sanitation MWI Rehabilitation of rural water MWI Management support to lgas MWI Tunduma-Sumbawanga Road construction MF Namtumbo-Songea Road construction MF Peramiho-Mbinga Road construction MF Tanga-Horohoro Road construction MF Zanzibar rural roads-construction MF Health sector development programme MHSW HIV / AIDS Control programme MHSW Tanzania food and nutrition centre MHSW TB/Leprosy control Programme MHSW Tanzania food and drugs authority MHSW Rural water suppy and sanitation programme PMO-RALG Village travel and Transport programme PMO-RALG Primary Education development programme (PEDP) PMO-RALG Participatory forest management PMO-RALG Land management programme PMO-RALG Primary Health service Development programme PMO-RALG District Health infrastructure PMO-RALG Rural energy services MEM Rural electrification MEM Rural Energy Agency and rural energy fund MEM Rural pv- market (Barrier removal) MEM Rural electrification projects (spanish phase iiic) MEM Wayleave villages electrical scheme MEM ERT (village Electrification ) MEM Forest policy implementation support MNRT 218 Monitoring African Food and Agricultural Policies (MAFAP) Review of Food and Agricultural Policies in the United Republic of Tanzania 2005-2011 - Country Report Marketing of bee products MNRT Participatory forest management MNRT Support to forest national programme MNRT National forest resource monitoring and assessment (NAFORMA) MNRT UNDP support programme MNRT Rural roads (Subvote 7001) MID/MW Transport infrastructure division (subvote 2005) MID/MW Tanzania Meteorological Agency (TMA ) radar MID/MW Roads division MID/MW Public sector reform programme MLDF Tanzania Multi- Sectoral HIV/AIDS project (TMAP) MLDF Livestock disease control MLDF National diary and rangeland development MLDF Marine and coast Enviroment management project (MACEMP) MLDF UNDP support programme MLDF Monitoring African Food and Agricultural Policies (MAFAP) 219 supported by the Bill and Melinda Gates Foundation CONTACTS www.fao.org/mafap [email protected] FAO Headquarters Viale delle Terme di Caracalla 00153 Rome, Italy | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vu: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vu: REGIONAL REPORT:MANYARA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary......................................................................................................................................................... vi Illustrations..................................................................................................................................................................... xii CENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 PART II: INTRODUCTION..................................................................................................................................... 1 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 1 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope............................................................................................................................ 2 2.4 Legal Authority of the National Sample Census of Agriculture................................................................. 3 2.5 Reference Period .............................................................................................................................................. 3 2.6 Census Methodology....................................................................................................................................... 3 2.6.1 Census Organization........................................................................................................................... 4 2.6.2 Tabulation Plan................................................................................................................................... 4 2.6.3 Sample Design.................................................................................................................................... 4 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 5 2.6.5 Field Pre-Testing of the Census Instruments...................................................................................... 5 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 5 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 6 2.6.8 Household Listing............................................................................................................................... 6 2.6.9 Data Collection .................................................................................................................................... 6 2.6.10 Field Supervision and Consistency Checks ........................................................................................ 6 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................... 9 3.1 Holding Characteristics.................................................................................................................................. 9 3.1.1 Type of Holdings................................................................................................................................ 9 3.1.2 Livelihood Activities/Source of Income............................................................................................ 9 3.1.3 Sex and Age of Heads of Households................................................................................................ 9 3.1.4 Number of Household Members...................................................................................................... 13 3.1.5 Level of Education............................................................................................................................ 13 - Literacy ....................................................................................................................................... 13 - Literacy Level for Household Members .................................................................................... 13 - Litaracy Rates for Heads of Households.................................................................................... 13 - Educational Status....................................................................................................................... 13 3.1.6 Off-farm Income............................................................................................................................... 14 3.2 Land Use ..................................................................................................................................................... 15 3.2.1 Area of Land Utilised ....................................................................................................................... 16 3.2.2 Types of Land use............................................................................................................................. 16 3.3 Annual Crops and Vegetable Production................................................................................................... 16 3.3.1 Area Planted...................................................................................................................................... 16 3.3.2 Crop Importance............................................................................................................................... 17 3.3.3 Crop Types........................................................................................................................................ 17 3.3.4 Cereal Crop Production.................................................................................................................... 18 3.3.4.1 Maize ................................................................................................................................. 21 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ii 3.3.4.2 Sorgham ................................................................................................................................. 21 3.3.4.3 Other Cereals ................................................................................................................................. 22 3.3.4.4 Oil Seed Production........................................................................................................................ 22 3.3.7.1 Sunflowers ........................................................................................................................................ 22 3.3.6 Pulse Crops Production .................................................................................................................... 23 3.3.6.1 Beans............................................................................................................................... 26 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava ................................................................................................................................. 27 3.3.8 Fruits and Vegetables ........................................................................................................................ 28 3.3.8.1 Tomatoes ................................................................................................................................. 29 3.3.8.2 Onion .................................................................................................................................. 29 3.3.9 Other Annual Crops Production....................................................................................................... 29 3.4 Permanent Crops........................................................................................................................................... 29 3.4.1 PigeonPea ........................................................................................................................................ 34 3.4.2 Banana ........................................................................................................................................ 34 3.5 Inputs/Implements Use.................................................................................................................................. 35 3.5.1 Methods of land clearing................................................................................................................... 35 3.5.2 Methods of soil preparation.............................................................................................................. 35 3.5.3 Improved seeds use........................................................................................................................... 35 3.5.4 Fertilizers use.................................................................................................................................... 41 3.5.4.1 Farm Yard Manure Use.................................................................................................................... 42 3.5.4.2 Inorganic Fertilizer Use..................................................................................................................... 43 3.5.4.3 Compost Use 45 3.5.51 Insecicide Use.................................................................................................................................... 46 3.5.5.2 Herbicide Use .................................................................................................................................... 46 3.5.5.3 Fungicide Use .................................................................................................................................... 47 3.5.6 Harvesting Methods.......................................................................................................................... 48 3.5.7 Threshing Methods .......................................................................................................................... 48 3.6 Irrigation .................................................................................................................................................... 48 3.6.1 Area planted with annual crops and under irrigation....................................................................... 48 3.6.2 Sources of water used for irrigation................................................................................................. 49 3.6.3 Methods of obtaining water for irrigation........................................................................................ 51 3.6.4 Methods of water application .......................................................................................................... 51 3.7 Crop Storage, Processing and Marketing .................................................................................................. 51 3.7.1 Crop Storage ..................................................................................................................................... 51 3.7.1.1 Method of Storage ............................................................................................................................ 52 3.7.1.2 Duration of Storage .......................................................................................................................... 52 3.7.1.3 Purpose of Storage............................................................................................................................ 53 3.7.1.4 The Magnitude of Storage Loss ....................................................................................................... 53 3.7.2 Agro processing and by-products...................................................................................................... 55 3.7.2.1 Processing Methods.......................................................................................................................... 55 3.7.2.2 Main Agro-processing Products....................................................................................................... 56 3.7.2.3 Main use of primary processed Products ......................................................................................... 56 3.7.2.4 Outlet for Sale of Processed Products.............................................................................................. 57 3.7.3 Crop Marketing................................................................................................................................. 57 3.7.3.1 Main Marketing Problems................................................................................................................ 58 3.7.3.2 Reasons for Not Selling.................................................................................................................... 58 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iii 3.8 Access to Crop Production Services............................................................................................................ 58 3.8.1 Access to Agricultural Credits ......................................................................................................... 58 3.8.1.1 Source of Agricultural Credits ......................................................................................................... 59 3.8.1.2 Use of Agricultural Credits .............................................................................................................. 59 3.8.1.3 Reasons for not using agricultural credits........................................................................................ 59 3.8.2 Crop Extension .................................................................................................................................. 59 3.8.2.1 Sources of crop extension messages ................................................................................................ 60 3.8.2.2 Quality of extension.......................................................................................................................... 60 3.9 Access to Inputs ............................................................................................................................................. 61 3.9.2 Inorganic Fertilisers .......................................................................................................................... 61 3.9.3 Improved Seeds ................................................................................................................................. 62 3.9.4 Insecticides and Fungicide ................................................................................................................ 62 3.10 Tree Planting................................................................................................................................................... 63 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 64 3.12 Livestock Results........................................................................................................................................... 66 3.12.1 Cattle Production .............................................................................................................................. 66 3.12.1.1 Cattle Population .............................................................................................................................. 66 3.12.1.2 Herd size 67 3.12.2 Goat Production................................................................................................................................ 67 3.12.2.1 Goat Population ................................................................................................................................ 67 3.12.2.2 Goat Herd Size.................................................................................................................................. 67 3.12.2.3 Goat Breeds....................................................................................................................................... 68 3.12.3 Sheep Production.............................................................................................................................. 68 3.12.3.1 Sheep Population .............................................................................................................................. 77 3.12.3.2 Sheep Population Trend ................................................................................................................... 77 3.12.4 Pig Production .................................................................................................................................. 68 3.12.4.1 Pig Population Trend........................................................................................................................ 68 3.12.5 Chicken Production .......................................................................................................................... 72 3.12.5.1 Chicken Population........................................................................................................................... 72 3.12.5.2 Chicken Population Trend................................................................................................................. 72 3.12.5.3 Chicken Flock Size........................................................................................................................... 72 3.12.6 Other Livestock ................................................................................................................................. 72 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 73 3.12.7.1 Deworming ........................................................................................................................................ 73 3.12.8 Access to Livestock Services ........................................................................................................... 73 3.12.8.1 Access to livestock extension Services............................................................................................ 73 3.12.8.2 Access to Veterinary Clinic.............................................................................................................. 76 3.12.8.3 Access to village watering points/dam............................................................................................. 76 3.12.9 Animal Contribution to Crop Production......................................................................................... 77 3.12.9.1 Use of Draft Power........................................................................................................................... 77 3.12.9.2 Use of Farm Yard Manure................................................................................................................ 77 3.12.9.4 Use of Compost ........................................................................................................................... 77 3.12.10 Fish Farming..................................................................................................................................... 79 3.13 Poverty Indicators.......................................................................................................................................... 79 3.13.1 Access to Infrastructure and Other Services.................................................................................... 79 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iv 3.13.2 Type of Toilets.................................................................................................................................. 80 3.13.3 Household’s assets............................................................................................................................. 80 3.13.4 Sources of Light Energy................................................................................................................... 82 3.13.5 Sources of Energy for Cooking......................................................................................................... 82 3.13.6 Roofing Materials.............................................................................................................................. 82 3.13.7 Access to Drink Water...................................................................................................................... 84 3.13.8 Food Consumption Pattern............................................................................................................... 84 3.13.8.1 Number of Meals per Day................................................................................................................ 84 3.13.8.2 Meat Consumption Frequencies....................................................................................................... 85 3.13.8.3 Fish Consumption Frequencies ........................................................................................................ 85 3.13.9 Food Security.................................................................................................................................... 85 3.13.10 Main Source of Cash Income........................................................................................................... 88 PART IV: MANYARA PROFILES .......................................................................................................................... 90 4.1 Region Profile ................................................................................................................................................. 90 4.2 District Profiles............................................................................................................................................... 90 4.2.1 Babati ................................................................................................................................................. 90 4.2.2. Hanang............................................................................................................................................... 92 4.2.3 Mbulu................................................................................................................................................. 94 4.2.4 Simanjiro............................................................................................................................................ 96 4.2.5 Kiteto.................................................................................................................................................. 98 ACRONYMS ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level. The census covered smallholders in rural areas only and large scale farms. This report presents Manyara region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis has not been done in the report due to the fact that it is a new region. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Manyara region that were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Manyara region and indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Manyara region was 154,194 out of which 53,923 (35%) were involved in growing crops only, 3,776 (2.4%) rearing livestock only, 141 (0.1%) were pastoralist, and 96,354 (62.5%) were involved in crop production as well as livestock keeping. In summary, Manyara region had 150,278 households involved in crop production and 100,271 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by livestock keeping/herding, off farm income, tree/forest resources, remittances and fishing/hunting and gathering. The region had a literacy rate of 64 percent. The highest literacy rate was in Babati district (73%) followed by Mbulu district (70%) and Hanang district (68%). Kiteto and Simanjiro districts had the lowest literacy rates of 58 and 52 percent respectively. The literacy rate for the heads of households in the region was 61 percent. The number of heads of agricultural households with formal education in Manyara region was 90,244 (58.5%), those without formal education were 63,950 (41.5%) and those with only adult education were (1.2%). The majority of heads of agricultural households (54.7%) had primary level education whereas only 1.3 percent had post primary education. In Manyara region 46,407 (51%) households had one household member each involved in off-farm income generating activity, 32,014 (35%) households had two household members each involved in off-farm income generating activities and 12,581 (14%) households had more than two household members each involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 387,420 ha. The regional average land area utilised for crop production per crop growing household was only 2.1 ha. This figure was higher than the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 265,260 hectares out of which 4,020 hectares (1.5%) were planted during short rainy season and 261,239 hectares (98.5%) during long rainy season. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii An estimated area of 200,201 ha (76.64% of the total planted area with annual and vegetable crops) was planted with cereals, followed by 46,097 hectares (17.65%) of pulses, 13,097 ha (5.01%) of oil seeds, 1,344 ha (0.51%) of roots and tubers, 407 ha (0.18%) of fruits and vegetables and 30 ha (0.01%) of cash crops. Maize Maize dominated the production of cereal crop in the region. The number of households growing maize in Manyara region during the long rainy season was 144,475, (98% of the total crop growing households in the region during the long rainy season). The total production of maize during the long rainy season was 144,945 tonnes from a planted area of 185,559 hectares resulting in a yield of 0.78 t/ha. Other crops in order of their importance (based on area planted) were beans, sunflower, sorghum, finger millets, wheat, paddy, groundnuts and cassava. The average area planted with maize per maize growing household ranged from 0.7 hectares in Mbulu District to 2.8 hectares in Kiteto District. Kiteto district had the largest planted area of maize (69,186 ha) followed by Babati (35,491 ha), Hanang (35,232 ha), Simanjiro (22,831 ha) and Mbulu (22,818 ha). Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Manyara region during the long rainy season was 15,108. This represented 10 percent of the total crop growing households in Manyara region in the long rainy season. Oil Seeds The total production of oil seeds was 7,031 tonnes. The most cultivated oil seed crop was sunflower. The production for this crop was 6,366 tonnes, which constituted 91 percent of the total oil seeds production, followed by groundnuts 562 tonnes (7%) and simsim 103 tonnes (2%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 33,683 hectares which is 11 percent of the area planted with annual crops in the region. The most important permanent crop was pigeon peas which had a planted area of 26,755 (79 percent of the total area planted with permanent crops) followed by bananas 4,949 ha (15%) and coffee 1,185 ha (4%). Improved Seeds The planted area using improved seeds was 41,071 ha which represents 15 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was at 24.3 percent higher than the corresponding percentage use for the long rainy season (15.3%). Use of Fertilizers The use of fertilizers on annual crops was very small with the application of fertilisers to a planted area of only 87,132 ha (33% of the tatal planted area in the region). The planted area without fertilizer for annual crops was 178,129 hectares representing 67 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 82,194 ha which represented 31.0 percent of the total planted area. This was followed by compost ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix (3,939 ha, 1.5%). Inorganic fertilisers were used on a small area which represented only 0.4 percent of the area planted with fertilisers Irrigation In Manyara region, the area of annual crops and vegetables under irrigation was 6,736 ha representing 2.5 percent of the total area planted. The area under irrigation during the short rainy season was 765 ha accounting for 11 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the long rainy season of which 56 percent of the area planted with vegetables was irrigated, whilst 100 percent of the vegetables were irrigated in the short rainy season. Crop Storage There were 123,200 crop growing households (82.0% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 118,797 households storing 57,729 tonnes as of 1st January 2004. This was followed by beans and other pulses (58,728 households and 5,409 tonnes), sorghum (10,909 households and 1,684 tonnes) and paddy (2,543 households and 2,540 tonnes), wheat (2,000 household, 650 tonnes) and groundnuts (1,638 households,145 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 88,121 which represented 58.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Babati (81%) followed by Kiteto (55%), Hanang (52%), Mbulu (48%) and Simanjiro (23%). Agricultural Credit In Manyara region, few agricultural households (264, 0.2%) accessed credit, out of which 114 (43%) were male-headed households and 150 (57%) were female headed households. In Babati district only female headed households got credit for agriculture purposes, whereas in Hanang district only male households accessed credit. In Kiteto and Mbulu districts both male and female headed households had no access agricultural credit. Crop Extension Services The number of agricultural households that received crop extension was 38,712 (26% of total crop growing households in the region). Some districts have more access to extension services than others with Babati district having a relatively high proportion of households that received crop extension messages (30.5%), followed by Simanjiro (31.5%), Hanang (30.4%), Kiteto (19.8%) and Mbulu (13.9%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 23,486. This number represented 15 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Simanjiro district (7.6%) followed by Mbulu (6.4%), Babati (6.3%), Hanang (0.5%) and Kiteto (0.2%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 1,177,951. Cattle were the dominant livestock in the region followed by goats, sheep and pigs. The region had 7.0 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 1,163,051 head (98.7% of the total number of cattle in the region), 13,761 (1.2%) were dairy breeds and only1,139 (0.1%) were beef breeds. Goats The number of goat-rearing-households in the region was 80,558 (52% of all agricultural households) with a total of 991,152 goats giving an average of 12 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 53,914 (35% of all agricultural households) with a total of 439,314 sheep giving an average of 8 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 16,210 (11% of the total agricultural households) rearing about 41,236 pigs. This gave an average of 3 pigs per pig-rearing household. Chicken The number of households keeping chickens was 90,103, raising 699,345 chickens. This gives an average of 8 chickens per chicken-rearing household. In terms of total number of chickens in the country Manyara ranked twentieth out of the 21 Mainland regions. Use of Draft Power The region has 147,712 oxen that were used to cultivate 110,979 hectares of land. This represented only 6.6 percent of the total oxen found on the mainland. The largest area cultivated using oxen was found in Babati district (39,985 ha, 36% of the total area cultivated using oxen). Fish Farming The number of households involved in fish farming was 153 (0.1 percent of the total agricultural households in the region). Mbulu was the leading district with 84 agricultural households involved in fish farming followed by Kiteto 69. Fish farming was not practiced in the remaining districts. iv) Poverty Indicators Availability of Toilets It was estimated that 81.6 percent of all rural agricultural households used the traditional pit latrines, 0.9 percent used improved pit latrine and 0.7 percent had flush toilets. The remaining 0.2 percent of households had other unspecified types of toilets. Households with no toilet facilities represented 16.6 percent of the total agriculture households in the region. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Household Assets The radio was the most owned asset with 48.7% households owning it followed by bicycle (41.8%), iron (15.8%), wheelbarrow (4.7%), mobile phone (1.3%), vehicle (1.0%), television/video (0.7%), and landline phone (0.4%). Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 72.8 percent of the total rural households used this source of energy followed by hurricane lamp (17.5%), firewood (4.9%), pressure lamp (3.9%), mains electricity (0.7%), solar (0.1%) and gas or biogas (0.6%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.7 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.5%). The rest of energy sources accounted for 0.79 percent. These were bottled gas (0.13%), crop residues (0.30%), mains electricity (0.28%), livestock dung (0.07%). Roofing Materials The most used roofing material (for the main dwelling) was grass/leaves and it was used by 45.6 percent of the rural agricultural households. This was closely followed by iron sheets (32%). Other roofing materials were grass/mud (21.7%), tiles (0.7%) and concrete (0.1%). Number of Meals per Day About 59.7 percent of the holders in the region took three meals per day, 38.7 percent took two meals, 1.1 percent took one meal and 0.5 percent took four meals. Food Security In Manyara region, 56,362 households (36.6% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 7,343 (4.8%) said they sometimes experience problems, 14.4 often experienced problems and 7.2 percent always had problems in satisfying the household food requirement. About 37.1 percent of the agricultural households said they did not experience any food sufficiency problems Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 35.2 percent of all rural agricultural households. The second main cash income earning activity was sales of livestock (17.4%) followed by other casual earnings (15.0%) and businesses (9.2%). Other income earning activities were cash crops (8.4%), sale of forest products (6.3%), wages and salaries (2.8%), remittances (1.9%) and livestock products (1.6%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ...............................................................................................................................................4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .... 9 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 18 3.3 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 22 3.5 Production and Yieldd of Root and Tuber Crops by Season ............................................................................. 26 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 28 33.7 Land Clearing Methods....................................................................................................................................... 35 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season...................................... 41 3.10 Number of Households Storing Crops by Estimated Storage Loss and District ................................................53 3.11 Reason For Not Selling Crops Produce...............................................................................................................58 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District .................58 3.13 Access to Inputs................................................................................................................................................... 61 3.14 Number of Household and Chickens Raised by Flock Size................................................................................72 3.15 Number of Other Livestock by Type of Livestock and District ........................................................................ 72 3.16 Mean distances from holders dwellings to infrastructure and services by districts ..........................................80 3.17 Number of Households by Number of meals the Household normally has per Day and District .....................84 List of Charts 3.1 Agricultural Households by Type of Holdings..................................................................................................... 9 3.2 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 13 3.3 Percentage Literacy Level of Household Members by District......................................................................... 13 3.4 Literacy Rates for Heads of Household by Sex and District.............................................................................. 13 3.5 Percentage of Person Aged 5 years and above by Educational Status................................................................14 3.6 Percentage of Population Aged 5 years and above by District and Educational Status.................................... 14 3.7 Percentage Distribution of Persons Aged 5 years and Above in Agricultural Households by Education Status............................................................................................................................................ 14 3.8 Number of members per household with Off Farm Income – Manyara Region............................................... 15 3.9 Percentage Distribution of Agricultural Households by Number of Off-farm Activities................................. 15 3.10 Utilized and Usable Land per Household by District......................................................................................... 16 3.11 Land Area by Type of Land Use........................................................................................................................ 16 3.13 Area Planted with Annual Crops by Season and District................................................................................... 16 3.14 Area Planted with Annual Crops by Season and District....................................................................................17 3.13 Area Planted with Annual Crops (ha) per Household by District...................................................................... 17 3.15 Area Planted per household by Season and District........................................................................................... 20 3.16 Planted Area for the Main Annual Crops (ha).................................................................................................... 17 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type..................................................... 20 3.18 Area planted with Annual Crops by Type of Crops and Season........................................................................ 22 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 22 3.20 Time Series Data on Maize Production – Manyara Region............................................................................... 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Manyara Region.................................................................... 23 3.23 Total Planted Area and Area of Paddy per Household by District .................................................................... 26 3.24 Time Series Data on Paddy Production – Manyara Region............................................................................... 26 3.25 Time Series of Paddy Planted Area and Yield – Manyara Region.................................................................... 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District................................................................... 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................... 26 3.28 Area planted with Cassava during the census/survey years................................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District ............................................................... 28 3.31 Total Area Planted with Irish Potatoes and Planted Area per Household by District....................................... 28 3.32 Area Planted and Yield of Major Pulse Crops ................................................................................................... 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 30 3.37 Area Planted and Yield of Major Oil Seed Crops.............................................................................................. 32 3.38 Time Series Data on Groundnut production – Manyara Region........................................................................ 32 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiii 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District ........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) .............................. 33 3.42 Area Planted and Yield of Fruit and Vegetables................................................................................................ 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 35 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only)................................... 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District .................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District ..................................... 37 3.47 Area planted with Annual Cash Crops ............................................................................................................... 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District................................... 40 3.49 Area Planted for Annual and Permanent Crops.................................................................................................. 40 3.50 Area Planted with the Main Permanent Crops ................................................................................................... 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District......................... 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 45 3.55 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District................... 46 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season ..................................... 48 3.57 Area Cultivated by Cultivation Method...............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District..................................................................................... 50 3.59 Planted Area with Improved Seed by Crop Type............................................................................................... 50 3.60 Percentage of Crop Type Planted Area with Improved Seed – Annuals........................................................... 50 3.61 Area of Fertilizer Application by Type of Fertilizer .......................................................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 51 3.63 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season..................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop type – Annuals........................................................................ 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District ........................................................ 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals........................................................................ 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 53 3.68a Planted Area with Compost by Crop Type......................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type ................................................................................. 53 3.68b Proportion of Planted Area Applied with Compost by District......................................................................... 53 3.69 Planted area (ha) by Pesticide use....................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type ....................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season ................... 54 3.73 Planted Area applied with herbicides by Crop Type.......................................................................................... 55 3.74 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season..................... 55 3.76 Planted Area applied with Fungicides by Crop Type......................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season..................... 56 3.79 Area of Irrigated Land......................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District......................................................... 57 3.81 Time Series of Households with Irrigation – Manyara...................................................................................... 57 8.82 Number of Households with Irrigation by Source of Water.............................................................................. 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................... 57 3.84 Number of Households with Irrigation by Method of Field Application.......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type.............................................................................. 59 3.86 Number of households by Storage Methods....................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 3.88 Normal Length of Storage for Selected Crops ................................................................................................... 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .................................................. 61 3.90 Number of Households by Purpose of Storage and Crop Type......................................................................... 61 3.91a Percentage of Households Processing Crops by District ................................................................................... 62 3.91b Percent of Households Processing Crops by District......................................................................................... 62 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 62 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 62 3.94 Number of Households by Type of Bi-product.................................................................................................. 63 3.95 Use of Processed Product.................................................................................................................................... 63 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiv 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 63 3.97 Location of Sale of Processed Products.............................................................................................................. 63 3.99 Number of Crop Growing Households that Sold Crops by District .................................................................. 64 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 64 3.101 Percentage Distribution of Households that Received Credit by Main Sources ............................................... 65 3.102 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 65 3.103 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 65 3.104 Reasons for Not using Credit.............................................................................................................................. 65 3.105 Number of Households Receiving Extension Advice........................................................................................ 66 3.106 Number of Households that Received Extension by District............................................................................. 66 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 66 3.108 Number of Households that Received Extension by Reported Quality of Services.......................................... 66 3.109 Number of Households by Source of Inorganic Fertiliser ................................................................................. 68 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser.................................................. 68 3.111 Number of Households by Source of Improved Seed........................................................................................ 69 3.112 Number of Households reporting Distance to Improved Seed .......................................................................... 69 3.113 Number of Households by Source of Insecticide/Fungicide.............................................................................. 69 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 69 3.115 Number of Households with Planted Trees by District...................................................................................... 70 3.116 Number of Planted Trees by Species...................................................................................................................70 3.117 Number of Trees Planted by Smallholders by Species and District .................................................................. 70 3.118 Number of Trees Planted by Location................................................................................................................ 70 3.119 Number of Households by purpose of Planted Trees......................................................................................... 71 3.120 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 71 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District........... 71 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 71 3.123 Total Number of Cattle ('000') by District.......................................................................................................... 73 3.124 Numbers of Cattle by Type and District............................................................................................................. 73 3.125 Cattle Population Trend ...................................................................................................................................... 75 3.126 Dairy Cattle Population Trend............................................................................................................................ 75 3.127 Total Number of Goats ('000') by District.......................................................................................................... 75 3.128 Goat Population Trend........................................................................................................................................ 77 3.129 Total Number of Sheep by District..................................................................................................................... 77 3.130 Sheep Population Trend...................................................................................................................................... 79 3.131 Total Number of Pigs by District........................................................................................................................ 79 3.132 Pig Population Trend........................................................................................................................................... 79 3.133 Total Number of Chicken by District ................................................................................................................. 81 3.134 Chicken Population Trend .................................................................................................................................. 81 3.135 Number of Improved Chicken by Type and District...........................................................................................82 3.136 Layer Population Trend....................................................................................................................................... 82 3.137 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District...... 82 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 84 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........ 73 3.121 Number of Households by Distance to Veterinary Clinic.................................................................................. 76 3.122 Number of Households by Distance to Veterinary Clinic and District.............................................................. 76 3.123 Number of Households by Distance to Village Watering Point ........................................................................ 76 3.124 Number of Households by Distance to Watering Point and District..................................................................76 3.125 Number of Households using Draft Animals ..................................................................................................... 77 3.126 Number of Households using Draft Animals by District................................................................................... 77 3.127 Number of Households using Organic Fertiliser................................................................................................ 77 3.128 Area of Application of Organic Fertiliser by District ........................................................................................ 77 3.129 Number of Households Practicing Fish Farming – Manyara............................................................................. 79 3.130a Number of Households Practicing Fish Farming by District – Manyara ...........................................................79 3.130b Fish Production.....................................................................................................................................................79 3.131 Agricultural Households by Type of Toilet Facility ...........................................................................................80 3.132 Percentage Distribution of Households Owning the Assets................................................................................80 3.133 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................82 3.134 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 82 3.135 Percentage Distribution of Households by Type of Roofing Material .............................................................. 82 3.136 Percentage Distribution of Households With Grass/Leaves Roofs by District ................................................. 82 3.137 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season....84 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xv 3.140 Number of Households by Frequency of Meat and Fish Consumption..............................................................85 3.141 Percent Distribution of the Number of Households by Main Source of Income............................................... 88 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 10 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 10 3.3 Number of Crop Growing Households by District............................................................................................. 11 3.4 Percent of Crop Growing Households by District.............................................................................................. 11 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 13 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 13 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................... 19 3.9 Area planted and Percentage During the Short Rainy Season by District......................................................... 20 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District .................................. 20 3.11 Planted Area and Yield of Maize by District ......................................................................................................24 3.12 Area Planted per Maize Growing Household......................................................................................................24 3.12 Planted Area and Yield of Sorghum by District................................................................................................. 25 3.13 Area Planted per Sorghum Growing Household................................................................................................ 25 3.14 Planted Area and Yield of Sunflower by District............................................................................................... 30 3.15 Area Planted per Sunflower Growing Household.............................................................................................. 30 3.16 Planted Area and Yield of Beans by District...................................................................................................... 31 3.17 Area Planted per Beans Growing Household..................................................................................................... 31 3.18 Planted Area and Yield of Cassava by District .................................................................................................. 32 3.19 Area Planted per Cassava Growing Household.................................................................................................. 32 3.20 Planted Area and Yield of Onion by District ..................................................................................................... 36 3.21 Area Planted per Onion Growing Household..................................................................................................... 36 3.22 Planted Area and Yield of Tomato by District................................................................................................... 37 3.23 Area Planted per Tomato Growing Household ...................................................................................................37 3.24 Planted Area and Yield of Pigeon peas by District............................................................................................ 38 3.25 Area Planted per Pigeon peas Growing Household ........................................................................................... 38 3.26 Planted Area and Yield of Banana by District ................................................................................................... 39 3.27 Area Planted per Banana Growing Household................................................................................................... 39 3.28 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 44 3.29 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 44 3.30 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 50 3.32 Number of Households and Percent of Total Households Selling Crops by District........................................ 50 3.33 Nimber of House holds and Parcent of Total Household Receiving Crop Extension Services.........................54 3.34 Number and Percent of Crop Growing Households using Improved Seed by District..................................... 54 3.35 Number and percent of smallholder planted trees by district............................................................................. 65 3.35 Number and Percent of Households with water Harvesting Bunds by District................................................. 65 3.37 Cattle population by District as of 1st Octobers 2003........................................................................................ 69 3.38 Cattle Density by District as of 1st October 2003.............................................................................................. 69 3.39 Goat population by District as of 1st Octobers 2003 ......................................................................................... 70 3.40 Goat Density by District as of 1st October 2003................................................................................................ 70 3.41 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 71 3.42 Sheep Density by District as of 1st October 2003.............................................................................................. 71 3.43 Pig population by District as of 1st Octobers 2003............................................................................................ 74 3.44 Pig Density by District as of 1st October 2003 .................................................................................................. 74 3.45 Number of Chickens by District as of 1st October 2003 ....................................................................................75 3.46 Density of Chickens by District as of 1st October 2003.................................................................................... 75 3.47 Number and Percent of Households Infected with Ticks by District ................................................................ 78 3.48 Number and Percent of Households Using Draft Animals by District...............................................................78 3.48 Number and Percent of Households Using Farm Yard Manure by District.......................................................81 3.49 Number and Percent of Households using Compost by District........................................................................ 81 3.50 Number and Percent of Households Practicing Fish Farming by District......................................................... 83 3.51 Number and Percent of Households Without Toilets by District ...................................................................... 83 3.53 Number and Percent of Households using Grass for roofing material by District............................................ 86 3.54 Number and Percent of Households eating 3 meals per day by District ........................................................... 86 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xvi 3.55 Number and Percent of Households eating Meat Once per Week by District .................................................. 87 3.56 Number and Percent of Households eating Fish Once per Week by District.................................................... 87 3.57 Number and percent of Households Reporting food insufficiency by District……………………………….. 89. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION Information not readily available at the time of printing this report. 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Manyara region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 • Livestock • Livestock products • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 3. CENSUS RESULTS This part of the report presents census results for Manyara region based on the data tables presented in Appendix AII. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys, more effort has been put in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Manyara region was 154,194. The largest number of agriculture households was in Babati (46,635), followed by Kiteto (34,381), Hanang (31,245), Simanjiro (25,569) and Mbulu (16,364) (Map 3.1). At district level, the highest density of households was found in Mbulu (196 per km2), followed by Hanang (135 per km2) (Map 3.2). Most households (96,354 households, 62.5% of the total agricultural households in the region) were involved in crop production as well as livestock keeping, 53,923 households (35%) were involved in crop production only, 3,776 households (2.4%) were involved in rearing livestock only and 141 households (0.1%) were pastoralists (Chart 3.1) (Maps 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Manyara region indicates that most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income, followed by livestock keeping/herding, off - farm income, tree/forest resources, remittances, permanent crop farming and tree and fishing/hunting and gathering (Table 3.1). 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Manyara region was 134,268 (87% of the total regional agricultural households) whilst in female-headed households it was 19,926 (13% of the total regional agricultural households). The mean age of household heads was 45 years (45 years for male heads and 47 years for female heads) (Chart 3.2) . Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Babati 1 6 3 2 5 7 4 Hanang 1 6 2 3 5 7 4 Mbulu 1 5 2 4 6 7 3 Simanjiro 1 6 2 3 5 7 4 Kiteto 1 5 3 2 6 7 4 Total 1 6 2 3 5 7 4 Chart 3.1 Agriculture Households by Type - Manyara Pastoralists, 141, 0.1% Livestock Only, 3,776, 2.4% Crops Only, 53,923, 35.0% Crops and Livestock, 96,354, 62.5% Hanang Kiteto 16 21 14 3 7 Mbulu Simanjiro Babati Kiteto Hanang 34,381 31,245 46,635 25,569 16,364 Mbulu Simanjiro Babati 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census MAP 3.01 MANYARA Total Number of Agricultural Households by District MAP 3.02 MANYARA Number of Agricultural Households per Square Km of Land by District 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Number of Agriculture Households Agriculture Households Number of Agricultural Households per Square Km Agricultural Households per Square Km RESULTS 10 Hanang Babati Kiteto Mbulu 99.3% 99.3% 97.7% 99.5% 84.1% Simanjiro 96.5 to 99.6 93.4 to 96.5 90.3 to 93.4 87.2 to 90.3 84.1 to 87.2 Mbulu Kiteto Hanang Babati 13,759 31,022 46,305 24,976 34,215 Simanjiro 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census MAP 3.03 MANYARA Number of Crop Growing Households by District MAP 3.04 MANYARA Percent of Crop Growing Households by District Number of Crop Growing Households Crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households RESULTS 11 Hanang Kiteto Simanjiro Babati Mbulu 80.2% 26.9% 63.7% 69.9% 63.2% 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Kiteto Simanjiro Hanang Babati 7 3 21 16 11 Mbulu 20.8 to 26 15.6 to 20.8 10.4 to 15.6 5.2 to 10.4 0 to 5.2 Tanzania Agriculture Sample Census MAP 3.05 MANYARA Number of Crop Growing Households Per Square Kilometer of Land by District MAP 3.06 MANYARA Percent of Crop and Livestock Households by District Number of Crop Growing Households Per Sq Km Crop Growing Households Per Sq Km Percent of Crop and Livestock Households Percent of Crop and Livestock Households RESULTS 12 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 13 3.1.4 Number and Age of Household Members Manyara region had a total rural agricultural population of 861,050 of which 450,336 (52%) were males and 410,714 (48%) were females. Whereas age group 0-14 constituted 44 percent of the total rural agricultural population, age group 15–64 (active population) was only 52 percent. Manyara region had an average household size of 6 with Babati, Simanjiro and Kiteto districts having the lowest household size of 5 persons per households (Chart 3.2). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members The results show that Manyara region had a total literacy rate of 64 percent. The highest literacy rate was found in Babati district (72%), followed by Mbulu district (67%), Hanang (66%), Kiteto (53%) and Simanjiro (50%) (Chart 3.3). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 61 percent. The literacy rates among the male and female heads of households were 64 and 37 percent respectively. The literacy rate for male heads of households was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Babati (65%), followed by Hanang (62%), Mbulu (61%), Kiteto (59%) and Simanjiro (47%) (Chart 3.4). Chart 3.2 Percent Distribution of Population by Age and Sex - Manyara 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percen t Male Female Chart 3.3 Percent Literatecy Level of Household Members by District 0.0 25.0 50.0 75.0 Babati Mbulu Hanang Kiteto Simanjiro District Percent Chart 3.4 Literacy Rates of Head of Household by Sex and District - Manyara 0.0 25.0 50.0 75.0 Babati Hanang Mbulu Simanjiro Kiteto District Percent Male Female Total RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 14 Educational Status Information on educational status was collected from individual agricultural households. The results show that in the region, 35 percent of the population aged 5 years and above in agricultural households had completed different levels of education and 31.8 percent were still attending school. Those who have never attended school were 33.2 percent (Chart 3.5). Agricultural households in Babati district had the highest percentage of population aged 5 years and above who had completed different levels of education (40%). This was followed by Mbulu district with 36 percent, Hanang (33%), Kiteto (31%) and Simanjiro (29%). Simanjiro district had the highest percent of households that have never attended school (48%) followed by Kiteto (42%) (Chart 3.6). The number of heads of agricultural households with formal education in Manyara region was 90,244 (58.5%), those without formal education were 63,950 (41.5%). The majority of heads of agricultural households in Manyara region had primary level education (54.7%), whereas 40.3 percent had no education and only 3.8 percent of them had post primary education (Chart 3.7). With regard to the heads of agricultural households with primary or secondary education in Manyara region, Babati district had the highest percentages (32% for primary and 36% for secondary). This was followed by Mbulu (23% for primary and 19% for secondary), Hanang (21% for primary and 15% for secondary), Kiteto (16% for primary and 17% for secondary) and Simanjiro (8% for primary and 14% for secondary). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income was important amongst agriculture households in Manyara with 59 percent of households having at least one member with off-farm income. In the region, 46,407 households (51%) Chart 3.5 Percentage of Persons Aged 5 Years and Above by Education Status Never Attended 33.2% Attending School 31.8% Completed 35.0% Chart 3.6 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Babati Hanang Mbulu Simanjiro Kiteto District Percent Attending School Completed Never Attended Chart 3 .7 Percentage Distribution of Heads of Household by Educational Attainment Post Primary Education, 5,935, 3.8% Adult Education, 1,792, 1.2% No Education, 62,158, 40.3% Primary Education, 84,309, 54.7% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 had only one member aged 5 and above involved in off-farm income generating activity, 32,014 households (35%) had two members involved in off-farm income generating activities and 12,581 households (14%) had more than two members involved in off-farm income generating activities. Households with no off-farm income in Mara region constitute 41percent of the total agricultural households in the region (Chart 3.8). Babati district had the highest percentage of agriculture households with off-farm income (over 85% of total agriculture households in the district). Other districts with a high percent of agriculture household members with off-farm income were Mbulu (55%), Kiteto (53%) and Simanjiro (46%). Hanang district had the smallest percent of household members with off farm income (37%). The district with the highest percent of agriculture households with more than one member with off-farm income was Babati (58%). Hanang district had few households with more than one member having off-farm income (8%) (Chart 3.9). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g., bare rocks, shallow soils, steep slopes, swamp areas, etc. It does however include un-cleared bush. Utilised land refers to the land that was used during the year. Chart 3.8 Number of Household by Number of Members with Off-farm Income None, 63,192 , 41% One , 46,407 , 30% Two , 32,014 , 21% More than Two , 12,581 , 8% Chart 3.9 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 25% 50% 75% 100% Babati Mbulu Simanjiro Kiteto Hanang Districts Percent More than Two Two One None RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 3.2.1 Area of Land Utilised The total area of land available to smallholders was 387,420 ha. The regional average land area utilised for agriculture per household was only 2.0 ha. This figure was slightly above the national average which was estimated at 2.0 hectares. Eighty four percent of the total land available to smallholders was utilised. Only 16 percent of usable land available to smallholders was not used (Chart 3.10). Large differences in land area utilised per household existed between districts with Kiteto and Mbulu utilizing 10 and 8 ha per household, it was followed by Hanang (4 ha), Babati (2 ha) and Simanjiro (1 ha). The percentage utilized of the usable land per household is highest in Hanang (98%) and lowest in Babati (73%). Ninety one percent of the total land available to smallholders was utilised. Only 16 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary mixed crop was 166,314 hectares (42.9% of the total land available to smallholders in Manyara), followed by temporary mono crops (119,503 ha, 30.8 %), pasture (30,547 ha, 7.9%), uncultivatable usable land (28,815 ha, 7.4%), area under planted trees area (2,977 ha, 0.8 %), area under fallow (13,919 ha, 3.6%), area unusable (7,785 ha, 1.9%), area rented to others (7,475 ha, 1.9%), area under permanent/annual mix (4,636 ha, 1.2%), area under natural bush (3,762 ha, 1.0%), area under permanent mixed crops (1,599 ha, 0.4%), and area planted with permanent mono crops (387 3.3 Annual Crop and Vegetable Production Manyara region has two rainy seasons, namely the short rainy season (October to November) and the long rainy season (April to May). 3.3.1 Area Planted The area planted with annual crops and vegetables was 265,260 hectares out of which 4,020 hectares (1.5%) were planted during short rainy season and 261,239 hectares (98.5%) during long rainy season (Chart 3.12). Chart 3.10 Utilized and Usable Land per Household by District 0 4 8 12 Kiteto Mbulu Hanang Babati Simanjiro Districts Area per household 0 25 50 75 100 Percent Utilisation Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.11 Land Area by Type of Use 30.8 42.9 7.9 7.4 3.6 1.9 1.9 1.2 1.0 0.8 0.4 0.1 0 60,000 120,000 180,000 Permanent Mono Crops Permanent Mixed Crops Planted Trees Natural Bush Permanent / Annual Mix Area Rented to Others Area Unusable Area under Fallow Uncultivated Usable Land Pasture Temporary Mono Crops Temporary Mixed Crops Land Use Area (hectares) Chart 3.12 Area planted with Annual crops by Season (ha) Long Rainy Season, 261,239, 98.5% Short Rainy Season, 4,020, 1.5% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 The average areas planted per household during the short and long rainy seasons was 0.4 and 0.9 ha respectively. The district with the largest area planted per household was Mbulu (2.6 ha), followed by Kiteto with 2.2 ha, Hanang (1.9 ha), Simanjiro (1.3 ha) and Babati (1.2 ha). Mbulu district had the highest percent of planted area in the short rainy season (Chart 3.13 and Map 3.8). The average area planted per household during the long rainy season in Manyara region was 0.94 hectares, however, there were large district differences. Kiteto had the largest planted area per household during the long rainy season (2.28 ha), followed by Simanjiro (1.5 ha) and Hanang (0.89 ha). The smallest planted area per household was in Mbulu (0.5 ha). The area planted per household in the short rainy season was less than one hectare in all the districts with exception of Kiteto district which had zero planted area (Chart 3.14 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Manyara region and it had a planted area 4.1 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 70.8 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are sunflower, sorghum, finger millets, wheat and paddy (Chart 3.15). Households that grow chillies, maize and sunflower have larger planted areas per household than for other crops (Chart 3.16). Chart 3.13 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 Mbulu Babati Simanjiro Hanang Kiteto District Area Planted (ha) 0.00 2.00 4.00 6.00 Percentage Planted Short Rainy Season Long Rainy Season % Area Planted in Short rainy Season Chart 3.14 Area Planted with Annual Crop per Household by Season and District 0 1 2 Kiteto Simanjiro Hanang Babati Mbulu District Area Planted per Household by Season 0 1 2 Overall Area Planted per Household Long Short Total Chart 3.15 Planted Area (ha) for the Main Crops - MANYARA 0 50,000 100,000 150,000 200,000 Maize Beans Sunflower Sorghum Finger Millet Wheat Paddy Groundnuts Cassava Sweet Potatoes Chich Peas Crop Planted Area (ha) Chart 3.16 Planted Area (ha) per Household for Selected Crops in the Long Rainy Season - Manyara 0.0 1.0 2.0 3.0 Chillies Maize Sunflower Bulrush Millet Simsim Wheat Paddy Finger Millet Beans Onions Chick Peas Cowpeas Bambaranuts Groundnuts Sorghum Cassava Green Gram Crop Planted Area (ha) RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 3.3.3 Crop Types Cereals were the main crops grown in Manyara region. The area planted with cereals was 202,913 ha (76.5% of the total planted area), followed by pulses with 47,099 ha (17.8%), oil seeds (13,231 ha, 5.0%), roots and tubers (1,417 ha, 0.5%) and fruit and vegetables (569 ha, 0.21%). Tobacco was the only cash crop grown with a least planted area of about 30 ha (0.01%) (Chart 3.17). Cereals and pulses were the dominant crops in both seasons and other crop types were of minor importance in comparison. There was little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.4 Cereal Crop Production The total production of cereals was 164,788 tonnes. Maize was the dominant cereal crop at 147,773 tonnes which was 90 percent of total cereal crops produced, followed by paddy (4%) sorghum (2%), wheat (2%) and finger millet (2%). Kiteto district had the largest planted area of cereals in the region (70,119ha) followed by Babati (42,650 ha), Hanang (39,081 ha), Mbulu (24,656 ha) and Simanjiro 23,171 ha) (Map 3.10). The total area planted with cereals during the year was 202,913 ha out of which 2,712 ha (1.3%) were planted in short rainy season and 200,201 ha (98.7%) were planted during the long rainy season. The long rainy season accounts for 98 percent of the total cereals produced in both seasons. The area planted with maize during the long rainy season was 185,559 ha (92.7% of the total area planted with cereals in that season), whilst for the short rainy season it was only 2,339 ha (86% of the total area planted with cereals in short rainy season) (Table 3.2). The area planted with maize was the largest and it represented 93 percent of the total area planted with cereal crops, followed by sorghum (3%), finger millets (2%), wheat (1%) and paddy (1%). Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 2,339 2,828 1209 185,559 144,945 781 187,898 147,773 786 Paddy 0 0 0 2,031 6,674 3,287 2,031 6,674 3,287 Sorghum 276 330 1197 6,495 3,747 577 6,771 4,078 602 Bulrush Millet 0 0 0 393 99 253 393 99 253 Finger Millet 97 25 260 3,679 2,618 712 3,775 2,643 700 Wheat 0 0 0 2,046 3,521 1,721 2,046 3,521 1,721 Total 2,712 3,184 200,201 161,605 202,913 164,788 Chart 3.17 Percentage Distribution of Area planted with Annual Crops by Crop Type Roots & Tubers, 1,417, 0.5% Pulses, 47,099, 17.8% Oil seeds, 13,231, 5.0% Fruits & Vegetables, 569, 0.2% Cash crops, 30, 0.0% Cereals, 202,913, 76.5% 200,201 2,712 46,097 1,003 13,097 133 1,344 73 470 100 30 - - 50,000 100,000 150,000 200,000 250,000 Area (hectares) Cereal Pulses Oil Seeds and Oil nuts Roots and Tubers Fruit and Vegetables Cash Crops Crop Type Chart 2.18 Area Planted with Annual Crops by Crop Type and Season Long rainy Season Short Rainy Season Kiteto Simanjiro Mbulu Babati Hanang 3.5% 2.5% 1.7% 2.4% 1.7% 2.8 to 3.5 2.1 to 2.8 1.4 to 2.1 0.7 to 1.4 0 to 0.7 Babati Kiteto Simanjiro Hanang 41,798 58,659 74,511 58,096 32,195 Mbulu MAP 3.07 MANYARA Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Percent of Utilized Land 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census MAP 3.08 MANYARA Total Planted Area (Annual Crops) by District Total Planted Area Area Planted Annual Crops RESULTS 19 Simanjiro Kiteto Hanang Mbulu Babati 39,194ha 70,472ha 23,171ha 42,650ha 24,714ha 168.6% 31.1% 66.8% 73.4% 76.8% 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Mbulu Babati Hanang Kiteto 2,242ha 0ha 191ha 1,261ha 327ha 5.4% 0% 0.3% 2.2% 1% Simanjiro 2,000 to 2,300 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Tanzania Agriculture Sample Census MAP 3.09 MANYARA Area planted and Percentage During the Short Rainy Season by District MAP 3.10 MANYARA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Planted Area (ha) Planted Area (ha) Planted Area (ha) Planted Area Cereal Crop Percent of Area Planted Percent of Area Planted Cereal Crop RESULTS 20 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 21 The yield of paddy was 3,287 kg/ha, that of maize was 786 kg/ha, finger millet was 700 kg/ha, sorghum was 602 kg/ha and that of bulrush millet was 253 kg/ha (Chart 3.19) 3.3.4.1 Maize Maize dominated the production of cereal crops in Manyara region. The number of households growing maize in the region during the long rainy season was 144,475, (98% of the total annual crop growing households in the region during the long rainy season). The total production of maize during the long rainy season was 144,945 tonnes from a planted area of 185,559 hectares resulting in a yield of 0.79 t/ha. Chart 3.20 indicates that Kiteto district had the largest area of maize (69,186 ha) during the long rainy season, followed by Babati (35,491 ha), Hanang (35,232 ha), Simanjiro (22,831 ha) and Mbulu (22,818 ha) (Chart 3.20 and Map 3.11). 3.3.4.2 Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Manyara region during the long rainy season was 15,108. This represented 10 percent of the total crop growing households in Manyara region. The total production of sorghum during the long rainy season was 3,747 tonnes from a planted area of 6,495 hectares resulting in a yield of 0.58 t/ha. During the long rainy season the district with the largest area planted with sorghum was Babati (3,821 ha), followed by Mbulu (1,345 ha), Hanang (1,147 ha), Kiteto (108 ha) and Simanjiro (73 ha) (Map 3.12). The average area planted per crop growing households was highest in Simanjiro (1.62 ha), followed by Kiteto (0.88 ha), Babati (0.53 ha), Hanang (0.50 ha) and Mbulu (0.25 ha) (Chart 3.21 and Map 3.13). Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 200,000 Maize Sorghum Finger Millet Wheat Paddy Bulrush Millet Crop Area Planted (ha) 0.00 1.00 2.00 3.00 4.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.20 Total Area Planted with Maize and Planted Area per Maize Growing Household by District 22,818 22,831 35,232 35,491 69,186 0 25,000 50,000 75,000 Kiteto Babati Hanang Simanjiro Mbulu District Area (Ha) 0.0 1.0 2.0 3.0 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.21 Total Area Planted with Sorghum and Planted Area per Sorghum Growing Household by District 3,821 1,345 1,147 108 73 0 1,000 2,000 3,000 4,000 Babati Mbulu Hanang Kiteto Simanjiro District Area (Ha) 0.00 0.50 1.00 1.50 2.00 Area Planted per Household Planted Area (ha) Area planted/hh RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 22 3.3.4.3 Other Cereals Other cereal produced in the region includes paddy, finger millets, bulrush millet and wheat. Paddy was produced in Babati (1,817 ha) and Simanjiro (213 ha). Finger millet is produced in all districts with Hanang having the largest planted area (1,864 ha), followed by Kiteto (933 ha), Babati (531 ha), Mbulu (299 ha) and Simanjiro (53 ha). Wheat is produced in Babati (990 ha), Hanang (805 ha) and Mbulu (251 ha) (Chart 3.22). 3.3.7 Oil Seed Production The total production of oilseed crops was 7,031 tonnes from a planted area of 13,231 hectares. The total planted area of oilseeds in the long rainy season was 13,098 ha representing 99 percent of the total area planted with oil seeds in the region. Sunflower was the most important oilseed crop with 11,283 ha (85% of the total area planted with oil seeds), followed by groundnuts (12%) and simsim (3%). The yield of sunflower was moderate (564 kg/ha). Groundnut had a yield of 354 kg/ha and that of simsim was 286 kg /ha (Chart 3.23). In terms of production, sunflower produced 6,366 tonnes and accounted for 91 percent of the total production of oil seeds. This was followed by groundnut (8%) and simsim (1%). 3.3.7.1 Sunflower The number of households growing sunflower in Manyara region was 12,082. The total production of sunflower in the region was 6,366 tonnes from a planted area of 11,283 hectares resulting in a yield of 0.56 t/ha. About fifty percent of the area planted with sunflower was located in Hanang district (5,612 ha), followed by Babati (3,185 ha, 28%), Mbulu (2,026 ha, 18%) and Kiteto (460 ha, 4%) (Map 3.14). The highest proportion of land with sunflower was found in Hanang, followed by Babati, Mbulu, and Kiteto. No sunflower was found in Simanjiro disstrict (Chart 3.24) Table 3.3: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 32 19 593 11,251 6,347 564 11,283 6,366 564 Simsim 0 0 0 361 103 286 361 103 286 Groundnuts 102 38 371 1,486 524 353 1,588 562 354 Total 134 57 13,098 6,974 13,232 7,031 0 500 1,000 1,500 2,000 Area (Ha) Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.22 Area Planted with Paddy, Finger Millet and Wheat by District Paddy Fingermillet Wheat Chart 3.23 Area Planted and Yield of Major Oil Seed Crops 0 4,000 8,000 12,000 Sunflower Groundnuts Simsim Crop Area Planted (ha) 0 200 400 600 Yield (kg/ha) Yield kg/ha Chart 3.24 Percent of Sunflower Planted Area and Percent of Total Land with Sunflower by District 0.0 20.0 40.0 60.0 Hanang Babati Mbulu Kiteto Simanjiro District Percent of Land 0.0 2.0 4.0 6.0 8.0 Percent A rea Planted of Total Land A rea Percent of Land Proportional RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 The largest area planted per sunflower growing household was found in Hanang district (1.4 ha) and the lowest was in Mbulu (0.6). The range between the district with the largest and the lowest area planted per household depicts small variations in area planted per household among the districts (Chart 3.25) (Map 3.15). 3.3.6 Pulse Crops Production The total area planted with pulses was 47,099 hectares out of which 45,851 ha were planted with beans (97 percent of the total area planted with pulses), followed by chick peas (530 ha, 1%), cowpeas (455 ha, 1%) and bambara nuts (225 ha, 0.5%). Field peas and green gram were cultivated in small quantities (Table 3.4). The area planted with pulses in the short rainy season was 1,003 ha which represented 2 percent of total area planted with pulses during the year. Beans was the most dominant crop during long rainy season with a planted area of 44,854 ha (97.3% of the total area planted with pulses in that particular season), followed by chick peas (530 ha, 1.1%), cow peas (450 ha, 1.0%) and bambaranuts (225 ha, 0.5%). Field peas and green gram are cultivated in small quantities. The total production of pulses was 16,831 tonnes. Beans were the most cultivated crop producing 16,377 tonnes which accounted for 97.3 percent of the total pulse production. This was followed by chick peas (286t, 1.7%), cow peas (82t, 0.5%), bambara nuts (58t, 0.3%), field peas (23t, 0.1%) and green gram (5t, 0.03%). The yields of chick peas and green gram were 540 and 454 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were beans 357 kgs/ha, bambara nuts 256 kgs/ha and cow peas 181 kgs/ha (Chart 3.26). Table 3.4: Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 997 632 634 44,854 15,745 351 45,851 16,377 357 Cowpeas 6 0 0 450 82 183 455 82 181 Green Gram 0 0 0 11 5 494 11 5 494 Chich Peas 0 0 0 530 286 540 530 286 540 Bambara nuts 0 0 0 225 58 258 225 58 258 Field Peas 0 0 0 27 23 852 27 23 852 Total 1,003 632 46,097 16,199 47,099 16,831 0.0 0.5 1.0 1.5 Area per Household (ha) Hanang Babati Kiteto Mbulu Simanjiro District Chart 3.25 Area Planted per Sunflower Growing Households by District (Long Rainy Season Only) Chart 3.26 Area Planted and Yield of Major Pulse Crops 0 16,000 32,000 48,000 Beans Chich Peas Cowpeas Bambaranuts Field Peas Green Gram Crop Area Planted (ha) 0 250 500 750 1,000 Yield (kg/ha) Yield (kg/ha) Simanjiro Kiteto Hanang Babati Mbulu 2.8ha 0.8ha 1.1ha 0.8ha 1.8ha 2 to 2.9 1.5 to 2.0 1.0 to 1.5 0.5 to 1.0 0.0 to 0.5 Kiteto Babati Mbulu Hanang Simanjiro 69,186ha 23,124ha 35,328ha 36,217ha 24,043ha 0.5% 0.5% 0.8% 1.4% 0.9% 60,000 to 75,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Tanzania Agriculture Sample Census MAP 3.11 MANYARA Planted Area and Yield of Maize by District MAP 3.12 MANYARA Area Planted per Maize Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 24 Kiteto Hanang Babati Mbulu 0.9ha 0.5ha 1.6ha 0.6ha 0.3ha Simanjiro 1.4 to 1.7 1.1 to 1.4 0.8 to 1.1 0.5 to 0.8 0.2 to 0.5 Kiteto Simanjiro Hanang Babati Mbulu 108ha 1,179ha 73ha 3,987ha 1,423ha 0.1t/ha 0.3t/ha 0.1t/ha 0.8t/ha 0.4t/ha 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Tanzania Agriculture Sample Census MAP 3.13 MANYARA Planted Area and Yield of Sorghum by District MAP 3.14 MANYARA Area Planted per Sorghum Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 25 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 26 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Manyara region was 84,139. The total production of beans in the region was 16,377 tonnes from a planted area of 45,851 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Hanang (12,945 ha, 28.2%) (Chart 3.27 and Map 3.16). The largest area planted with beans per beans growing household was found in Simanjiro district (1.4 ha), whilst the smallest was found in Mbulu district. The average area planted per household in the region during the long rainy season was 0.5 ha. The variations in area planted with beans for the rest of the districts were ranging from 0.57 ha in Babati district to 0.80 ha in Kiteto district (Chart 3.28 and Map 3.17). 3.3.7 Roots and Tuber Crops Production The total production of roots and tubers was 1,341 tonnes. Cassava and sweet potato productions were higher than any other root and tuber crop in the region with a total production of 609 tonnes each. The two crops represented 90.8 percent of the total root and tuber crops production. These were followed by Irish potatoes with 122 tonnes (9.1%), and yams (1t, 0.1%). The area planted with cassava was larger than any other root and tuber crop in the region with a planted area of 781 ha (0.3% of the total area planted with annual crops and vegetables) and it accounted for 55 percent of the area planted with roots and tubers, followed by sweet potatoes (38%), Irish potatoes (6%) and yams (1%) (Table 3.5). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava has been reported under the long rainy season. However, excluding cassava, almost 91.3 percent of roots and tubers were grown in the long rainy season and only 8.7 percent were grown in the short rainy season. Table 3.5: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 18 16 889 763 593 777 781 609 780 Sweet Potatoes 55 43 782 488 566 1,160 543 609 1,122 Irish Potatoes 0 0 0 78 122 1,568 78 122 1,568 Yams 0 0 0 15 1 67 15 1 67 TOTAL 73 59 1,344 1,282 1,417 1,341 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. 1.37 0.80 0.58 0.57 0.40 0.00 0.35 0.70 1.05 1.40 Area per Household Simanjiro Kiteto Hanang Babati Mbulu District Chart 3.28 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.27 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 10 20 30 Hanang Mbulu Babati Simanjiro Kiteto District Percent of Land 0 7 14 21 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 The total production of roots and tubers was 1,341 tonnes. Cassava and sweet potatoes, each with a production of 609 tonnes, were the most important root and tuber crops in Manyara region. Each crop accounted for 45.4 percent of the total roots and tubers production, followed by Irish potatoes with 122 tonnes (9.1%) and yams (1 tonne, 0.1%). The yield of Irish potatoes was 1.6 t/ha, that of sweet potatoes was 1.1 t/ha, of cassava was 0.8 t/ha and that of yams was 0.07 t/ha (Chart 3.29). 3.3.5.1 Cassava The number of households growing cassava in Manyara region in the long rainy season was 2,234. This represents 1.5 percent of the total crop growing households in the region. The total production of cassava during the census year was 609 tonnes from a planted area of 781 hectares resulting in a yield of 0.8 t/ha. The area planted with cassava accounted for 0.3 percent of the total area planted with annual crops and vegetables in the census year. Hanang district had the largest planted area of cassava (316 ha, 40.4% of the cassava planted area in the region), followed by Kiteto (253 ha, 32.4%), Babati (137 ha, 17.6%) and Mbulu (75 ha, 9.6%) (Map 3.18). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Hanang district (0.4%). This was followed by Kiteto (0.3%), Babati (0.2%) and Mbulu (0.1%). Cassava was not cultivated in Simanjiro district (Chart 3.30). The average cassava planted area per cassava growing household was 0.34 hectares. However, there were small district variations. The area planted per cassava growing household was greatest in Kiteto (0.6 ha). This was followed by Hanang (0.41 ha), Babati (0.38 ha) and Mbulu (0.1 ha) (Chart 3.31 and Map 3.19). Chart 3.29 Area Planted and Yield of Major Root and Tuber Crops 0 200 400 600 800 Cassava Sweet Potatoes Irish Potatoes Yams Crop Area Planted (ha) 0 500 1,000 1,500 2,000 Yield (kg/ha) Yield (kg/ha) Chart 3.30 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 0.0 40.4 17.6 9.6 32.4 0 15 30 45 Hanang Kiteto Babati Mbulu Simanjiro District Percent of Total Area Planted 0.0 0.2 0.4 0.6 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.58 0.41 0.38 0.09 0.00 0.00 0.20 0.40 0.60 Area per Household Kiteto Hanang Babati Mbulu Simanjiro District Chart 3.31 Cassava Planted Area per Cassava Growing Households by District RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Manyara region during the long rainy season was 2,399. This was 1.6 percent of the total crop growing households in the region. The total production of sweet potatoes during the census year was 609 tonnes from a planted area of 543 hectares resulting in a yield of 1.1t/ha. Mbulu district has the largest planted area for sweet potatoes (465 ha, 86%), followed by Babati (50 ha, 9%) and Kiteto (28 ha, 5%). Sweet potatoes were not grown in Hanang and Simanjiro districts (Chart 3.32). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The production of fruit and vegetables were mainly during the long rainy season with 82 percent of the total area planted with fruits and vegetables during the year. Only 17.5 percent of the total planted area with fruits and vegetables was planted during the short rainy season. The total production of fruits and vegetables was 2,027 tonnes. The most cultivated fruit and vegetable crop was onions with a production of 1,052 tonnes (51.9% of the total fruit and vegetable production), followed by tomatoes (890t, 43.9%). The production of the other fruit and vegetable crops was relatively small (Table 3.6). The yield of onions was 2.965 t/ha, tomatoes (6.268 t/ha) and okra (4,857 kg/ha). The yield of the rest of the fruit and vegetables grown in the region were small (Chart 3.41 and Table 3.6). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 0 0 0 7 34 4,857 7 34 4,857 Onions 28 53 1,893 326 999 3,062 355 1,052 2,965 Cabbage 0 0 0 7 0 0 7 0 0 Tomatoes 24 49 2,042 118 841 7,133 142 890 6,268 Spinnach 12 5 395 0 0 0 12 5 395 Chillies 0 0 0 4 0 0 4 0 0 Pumpkins 12 4 333 0 0 0 12 4 333 Cucumber 12 2 167 4 0 0 16 2 125 Water Mellon 12 23 1,917 4 18 450 16 41 2,563 Total 100 136 470 1,892 571 2,028 Chart 3.32 Total Area Planted with Sweet Potatoes and Planted Area per Sweet Potato Growing Household by District 0 170 340 510 Mbulu Babati Kiteto Hanang Simanjiro District Area Planted (ha) 0.00 0.15 0.30 0.45 Yield (kg/ha) Area per Household Chart 3.33 Area Planted and Yield of Fruit and Vegetables 0 100 200 300 400 Onions Tomatoes Others Crop A rea Plan ted (h a) 0.0 2.5 5.0 7.5 Y ield (t/h a) RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 3.3.8.1 Onions The number of households growing onions in the region during the long rainy season was 598 and 35 households in the short rainy season. This represented 0.4 percent of the households growing crops in the region during the long rainy season and 0.6 percent during the short rainy season. Simanjiro district had the largest planted area of onions (50.1% of the total area planted with onions in the region), followed by Hanang (49.9%). Other districts in the region had no onion production. (Map 3.20). The highest percentage of land with onions was found in Simanjiro, followed by Hanang district. (Chart 3.34). The largest area planted per onion growing household in the long rainy season was found in Simanjiro district (1.1 ha), followed by Hanang (0.4 ha) (Map 3.21). The total area planted with onion accounted for 0.1 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.2 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 404 and 235 in the short rainy season. This is extremely small compared to the number of crop growing households in the region and comparison between seasons and districts is inappropriate. However, Babati district had the largest planted area of tomatoes (64 ha, 45% of the total area planted with tomatoes in the region), followed by Simanjiro (62 ha, 44%) and Hanang (15 ha, 11%) (Chart 3.35 and Map 3.22 and 2,23). The total area planted with tomatoes accounted for 0.05 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 30 ha was planted with tobacco. This was the only cash crop grown in the region and all of it in Babati district. The production of tobacco was 25 tonnes with a yield of 0.82 t/ha. 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature, can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Chart 3.34 Percent of Onion Planted Area and Percent of Total Land with Onions by District 0.000 20.000 40.000 60.000 Simanjiro Hanang Babati Mbulu Kiteto District Percent of Land 0.00 0.15 0.30 0.45 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.35 Percent of Tomatoes Planted Area and Percent of Total Land with Cabbage by District 0.0 15.0 30.0 45.0 Babati Simanjiro Hanang Mbulu Kiteto District Percent of Land 0.00 0.04 0.08 0.12 Percent Area Planted of Total Land Area Percent ofPlanted Area Proportion of Land Hanang Mbulu Babati Kiteto 0.7ha 1.4ha 0ha 0.8ha 0.6ha Simanjiro Mbulu Babati Hanang Kiteto Simanjiro 460ha 0ha 3,185ha 2,026ha 5,612ha 0.4t/ha 0t/ha 0.6t/ha 0.4t/ha 0.6t/ha 4,000 to 6,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census MAP 3.15 MANYARA Planted Area and Yield of Sunflower by District MAP 3.16 MANYARA Area Planted per Sunflower Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 RESULTS 30 Kiteto Simanjiro Hanang Babati Mbulu 0.8ha 0.6ha 1.4ha 0.6ha 0.4ha 1.2 to 1.5 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 Simanjiro Mbulu Hanang Babati Kiteto 12,945ha 2,092ha 8,127ha 9,922ha 12,764ha 0.26t/ha 0.29t/ha 0.53t/ha 0.3t/ha 0.34t/ha 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanzania Agriculture Sample Census MAP 3.17 MANYARA Planted Area and Yield of Beans by District MAP 3.18 MANYARA Area Planted per Beans Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 31 Hanang Babati Mbulu 0.1ha 0.4ha 0.4ha 0.6ha 0ha Simanjiro Kiteto 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Hanang Mbulu Babati Kiteto 0ha 316ha 75ha 137ha 253ha 0t/ha 0.7t/ha 0.1t/ha 1.5t/ha 2.6t/ha Simanjiro 240 to 320 180 to 240 120 to 180 60 to 120 0 to 60 Tanzania Agriculture Sample Census MAP 3.19 MANYARA Planted Area and Yield of Cassava by District MAP 3.20 MANYARA Area Planted per Cassava Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 32 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 33 Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 33,683 hectares (11% of the area planted with annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes all the areas of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as the physical planted land area. So the percentage area planted with permanent crops would be higher than indicated in Chart 3.36. The most important permanent crop in Manyara region was pigeon peas which had a planted area of 26,755 ha, (79% of the total planted area of permanent crops in the region), followed by bananas (4,949 ha, 15%) and coffee (1,185 ha, 4%). Each of the remaining permanent crops had an area of less than one percent of the total area planted with permanent crops (Chart 3.37). Babati district had the largest area under smallholder permanent crops (24,965 ha, 74.1%). This was followed by Kiteto (6,285 ha, 18.7%), Hanang (1,802 ha, 5.4%), Mbulu (486 ha, 1.3%) and Simanjiro (194 ha, 0.6%). However, Kiteto had the largest area per permanent crop growing household (1.7 ha), followed by Babati (1.0 ha), Simanjiro (0.6 ha), Hanang (0.5 ha) and Mbulu (0.2 ha) (Chart 3.38). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Babati had the highest (29.5%), followed by Kiteto (6.4%), Hanang (2.3%), Mbulu (0.7%) and Simanjiro (0.3%). Chart 3.38 Percent of Area Planted and Average Planted Area with Permanent Crops by District 18.7 5.4 1.3 0.6 74.1 0.0 20.0 40.0 60.0 80.0 Babati Kiteto Hanang Mbulu Simanjiro District % of Total Area Planted 0.0 0.5 1.0 1.5 2.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.36 Area Planted for Annual and Permanent Crops Permanent Crops, 33,683, 11% Annual Crops, 265,260, 89% Chart 3.37 Area Planted (ha) with Main Permanent Crops Banana, 4,949, 15% Pigeon Pea, 26,755, 79% Other, 794, 2% Coffee, 1,185, 4% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 3.4.1 Pigeon pea The total production of pigeon peas by smallholders was 9,520 tonnes. In terms of area planted, pigeon pea was the most important permanent crop grown by smallholders in the region. They were grown by 28,801 households (19% of the total crop growing households in the region). The average area planted with pigeon peas per household was around 0.92 ha per pigeon peas growing household and the average yield obtained by smallholders was 550 kg/ha from a harvested area of 17,318 hectares. Babati had the largest area of pigeon peas in the region (19,096 ha, 71.4%), followed by Kiteto (6,226 ha, 23.3%), Hanang (1,391 ha, 5.2%), Simanjiro (21 ha, 0.1%) and Mbulu (21 ha, 0.1%) (Map 3.24). However, the average area planted with pigeon peas per pigeon pea growing household was highest in Kiteto (1.8 ha) followed by Babati (0.9 ha), Simanjiro (0.5 ha), Hanang (0.4 ha) and Mbulu (0.2 ha) (Chart 3.39 and Map 3.25). 3.4.2 Banana The total production of bananas by smallholders was 3,161 tonnes. In terms of area planted, banana was the second most important permanent crop grown by smallholders in the region. It was grown by 2,701 households (1.8% of the total crop growing households in the region). The average area planted per bananas growing household was 1.8 ha and the average yield obtained by smallholders was 771 kg/ha from a harvested area of 4,098 hectares. Babati had the largest area of bananas in the region (4,393 ha, 88.8%), followed by Mbulu (239 ha, 4.8%), Hanang (156 ha, 3.2%), Simanjiro (125 ha, 2.5%) and Kiteto (35 ha, 0.7%) (Map 3.26). However, the average area planted with bananas per banana planting household was highest in Babati (4.2 ha), followed by Simanjiro (0.7 ha), Hanang (0.5 ha), Kiteto (1.3%) and Mbulu (0.2 ha) (Chart 3.40 and Map 3.27). Chart 3.39 Percent of Area Planted with Pigeon peas and Average Planted Area per Household by District 0.1 5.2 23.3 0.1 71.4 0.0 20.0 40.0 60.0 80.0 Babati Kiteto Hanang Simanjiro Mbulu District Percent of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.40 Percent of Area Planted with Bananas and Average Planted Area per Household by District 4.8 2.5 88.8 0.7 3.1 0.0 25.0 50.0 75.0 100.0 Babati Mbulu Hanang Simanjiro Kiteto District Percent of Total Area Planted 0.0 1.5 3.0 4.5 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 35 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing was the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 209,127 ha, which represents 80 percent of the total planted area. Other methods were bush clearance (11,101 ha, 4.3%), burning (7,532ha, 2.9%) and tractor slashing which was less important method for land clearing accounting for 2.0 percent (Chart 3.56 and Table 3.7 ). 3.5.2 Methods of Soil Preparation Ox-ploughing was most used method for soil preparation as it was used on an area of 134,293 ha which represents 50.6 percent of the total planted area, followed by hand- ploughing (71,643 ha, 27%) and tractor ploughing (59,324 ha, 22.4%) (Chart 3.42). Agricultural activities in Manyara region was mainly done during long rainy season. Over 98 percent of the land cultivated using tractor, oxen and hand was cultivated during the long rainy season. Of the area cultivated by hand during the year, 97 percent was during the long rainy season against 3 percent for the short rainy season, whereas, for oxen and tractor ploughing, the long rainy season accounted for 99 percent of the areas cultivated using each method. In Manyara region, Hanang district has the largest planted area cultivated by oxen (51,012 hectares, 38%), followed by Babati (44,123 ha, 33%), Mbulu (28,629 ha, 46%), Simanjiro (7,426 ha, 6%) and Kiteto (3,102 ha, 2%). The majority of agricultural households in Kiteto district cultivate using the hand hoe (63% of agricultural households in the district). The largest planted area cultivated using tractor is found in Kiteto district 26,180 ha, 44% of the planted area in the district) followed by Simanjiro (20,696 ha, 35%) (Chart 3.43). Table 3.7: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Area Planted % Mostly Hand Slashing 238,067 209,127 80 10,276 3,488 87 212,615 80 No Land Clearing 15,973 27,625 11 183 184 5 27,809 11 Mostly Bush Clearance 10,463 11,101 4 955 349 9 11,450 4 Mostly Burning 11,013 7,532 3 0 7,532 3 Mostly Tractor Slashing 1,425 5,275 2 0 5,275 2 Total 260,661 100 4,020 100 264,681 100 Chart 3.42 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 134,293, 50.6% Mostly Tractor Ploughing, 59,324, 22.4% Mostly Hand Hoe Ploughing, 71,643, 27.0% 0 20,000 40,000 60,000 80,000 Area Cultivated Hanang Babati Mbulu Simanjiro Kiteto District Chart 3.43 Area Cultivated by Method of Cultivation and District Oxen Ploughing Hand Hoe Ploughing Tractor Ploughing Chart 3.41 Number of Households by Method of Land Clearing during the Long Rainy Season 238,067 15,973 10,463 11,013 1,425 0 100,000 200,000 300,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Method of Land Clearing Number of Households Kiteto Simanjiro Hanang Babati Mbulu 0ha 1.3ha 0ha 0.4ha 0ha 1.2 to 1.3 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Kiteto Hanang Mbulu 177ha 0ha 178ha 0ha 0ha 0t/ha 4.2t/ha 1.8t/ha 0t/ha 0t/ha Simanjiro Babati 160 to 180 120 to 160 80 to 120 40 to 80 0 to 40 Tanzania Agriculture Sample Census MAP 3.21 MANYARA Planted Area and Yield of Onion by District MAP 3.22 MANYARA Area Planted per Onion Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 36 Kiteto Babati Mbulu Hanang 0ha 0.2ha 0.3ha 0.6ha 0ha Simanjiro 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Mbulu Hanang Simanjiro Babati Kiteto 0ha 15ha 62ha 64ha 0ha 0t/ha 0t/ha 5t/ha 2.5t/ha 8.4t/ha 40 to 70 30 to 40 20 to 30 10 to 20 0 to 10 Tanzania Agriculture Sample Census MAP 3.23 MANYARA Planted Area and Yield of Tomatoes by District MAP 3.24 MANYARA Area Planted per Onion Growing Tomatoes by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 37 Babati Simanjiro Kiteto Hanang Mbulu 1.8ha 0.5ha 0.4ha 0.9ha 0.2ha 1.2 > 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Mbulu Babati Simanjiro Kiteto Hanang 6,226ha 1,391ha 21ha 19,096ha 21ha 1.4t/ha 0.2t/ha 0.8t/ha 0.4t/ha 1.3t/ha 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census MAP 3.25 MANYARA Planted Area and Yield of Pigeon Peas by District MAP 3.26 MANYARA Area Planted per Pigeon Peas Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 38 Kiteto Hanang Babati Mbulu 1.8ha 0.5ha 0.7ha 4.2ha 0.2ha Simanjiro 3.2 to 4.2 2.4 to 3.2 1.6 to 2.4 0.8 to 1.6 0 to 0.8 Mbulu Babati Hanang Kiteto Simanjiro 4,949ha 156ha 125ha 4,393ha 239ha 0.6t/ha 0.6t/ha 4.4t/ha 0.3t/ha 4.9t/ha 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census MAP 3.27 MANYARA Planted Area and Yield of Bananas by District MAP 3.28 MANYARA Area Planted per Bananas Growing Households by District Planted Area (ha) Planted Area (ha) Area Planted per Household Area Planted per Household Yield (t/ha) RESULTS 39 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 40 During the long rainy season, 59.1 percent of the total area cultivated by using oxen was planted with cereals, followed by pulses (33.5%), oil seeds (6.1%), roots and tubers (0.9%), fruit and vegetables (0.4%) and cash crops (0.1%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 41,071 ha which represents 15 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was at 24.3 percent, higher than the corresponding percentage for the long rainy season (15.3%). Cereals had the largest planted area with improved seeds (34,687 ha, 84% of the planted area with improved seeds) followed by pulses (4,526 ha, 11%), oil seeds (1,554 ha, 4%), fruits and vegetables (215 ha, 1%), root and tubers (89 ha, 0%), Improved seeds were not used in cash crops (Chart 3.45). However, the use of improved seed in fruit/ vegetables and cereals was much higher than in other crop types being (38% and 17% respectively. Only 6 percent of the planted area for root and tubers used improved seed (Chart 3.46). Chart 3.45 Planted Area with Improved Seed by Crop Type Cereals, 34687, 84% Roots & Tubers, 89, 0% Pulses, 4526, 11% Oilseeds , 1554, 4% Fruits & Vegetables, 215, 1% Cash Crops, 0, 0% 0 15 30 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.46 Percentage of Crop Type Planted Area with Improved Seed - Annuals Chart 3.44 Planted Area of Improved Seeds - Manyara With Improved Seeds, 41,071 , 15% Without Improved Seeds, 224,189 , 85% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 3.5.4 Fertilizer Use The use of fertilisers on annual crops in Manyara region was very small with the application of fertilisers to a planted area of only 79,502 ha (30% of the total area planted with annual crops in the region). The planted area without fertiliser for annual crops was 185,757 hectares representing 70 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 74,548 ha which represented 28.1 percent of the total planted area. This was followed by compost (3,766 ha, 1.4%). Inorganic fertilizers were used on a very small area (1,188 ha) which represented only 0.4 percent of the area planted with fertilizers (Table 3.8 and Chart 3.47). The highest percentage of the area planted with fertilizer (all types) was in Mbulu district (65.7% of the total planted area with fertilizer in the district), followed by Babati (40.9%), Hanang (28.5%), Simanjiro (17.7%) and Kiteto (7.9%) (Table 3.8 and Chart 3.48). Most annual crop growing households do not use any fertiliser (approximately 98,114 households, 65%) (Map 3.28). The percentage of the planted area with applied fertiliser was highest for cereals (74.0% of the area planted with these cereals during the long rainy season had an application of fertilizers). This was followed by pulses (21.9%), oil seeds (3.3%), root and tubers (0.4%) and oil seeds (0.4%). There was very little quantities of fertiliser applied in cash crops (0.04%) (Table 3.9). Table 3.8 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use (ha) District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Babati 23,489 296 0 23,785 34,311 Hanang 13,764 2,327 600 16,691 41,968 Mbulu 27,211 237 0 27,448 14,350 Simanjiro 4,880 356 479 5,714 26,481 Kiteto 5,204 551 110 5,864 68,647 Total 74,548 3,766 1,188 79,502 185,757 Table 3.9: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Planted Area Babati 17,643 23,035 243 296 0 . 28,297 33,504 56,835 Hanang 6,218 13,764 1,079 2,327 384 600 23,262 41,777 58,469 Mbulu 21,642 25,346 174 176 0 . 11,703 14,035 39,557 Simanjiro 1,925 4,880 167 356 501 479 11,148 26,154 31,868 Kiteto 959 5,204 245 551 68 110 23,704 68,647 74,511 Total 48,387 72,229 1,909 3,705 952 1,188 98,114 184,117 261,239 0 15,000 30,000 45,000 60,000 75,000 Area (ha) Kiteto Hanang Babati Simanjiro Mbulu District Chart 3.48 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.47 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 185,757, 71% Mostly Compost, 3,766, 1% Mostly Inorganic Fertilizer, 1,188, 0% Mostly Farm Yard Manure, 74,548, 28% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 42 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Manyara region was 82,194 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 57,054 and it was applied to 79,945 ha representing 30.6 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (73.7%), followed by pulses (22.1%), oil seeds (3.2%) and roots and tubers (0.45%) and fruits and vegetables (0.49%). However, pulses had the highest percent of the planted area with farm yard manure (39% of the total area of pulses in Manyara). This was followed by cereals (30%), roots and tubers (27%), fruits and vegetables (26%) and oil seeds (11%) (Charts 3.49 and 3.50a). Farm yard manure is mostly used in Mbulu (65.1% of the total planted area in the district), followed by Babati (40.4%), Hanang (23.5%), Simanjiro (15.2%) and Kiteto (7.0%) (Chart 3.50b). For permanent crops, most farm yard manure was used in the production of bananas (48.7%), followed by pigeon peas (33.3%) and coffee (11.7%). Chart 3.49 Planted Area with Farm Yard Manure by Crop Type - Manyara Cereals, 61,755, 75.1% Roots & Tubers, 384, 0.5% Pulses, 18,394, 22.4% Oilseeds, 1,480, 1.8% Fruits & Vegetables, 149, 0.2% Cash Crop, 30, 0.0% 0 25 50 75 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.50a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Manyara region was 999 ha which represents 0.37 percent of the total planted area with annuals in the region and 1.1 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 585 and it was applied to 949 ha representing 0.36 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (46% of the total area applied with inorganic fertilizers), followed by pulses (27%), fruit and vegetables (25%) and oil seeds (2%) (Chart 3.51). The use of inorganic fertiliser on of fruit and vegetables was much greater than in other crop types (58.1% of the area planted with fruit and vegetables), followed by pulses (1.4%), cereals (0.7%) and oil seeds (0.6%) (Chart 3.52). Inorganic fertiliser was mostly used in Simanjiro (1.5% of the total planted area in the district), followed by Hanang (1.0%) and Kiteto (0.1%) Other districts used virtually no inorganic fertilisers (Chart 3.53). In permanent crops inorganic fertilisers were used on pigeon peas (2%), followed by coffee (1%) Chart 3.50b Proportion of Planted Area Applied with Farm Yard Manure by District - Manyara 0.0 15.0 30.0 45.0 60.0 Mbulu Babati Hanang Simanjiro Kiteto District Percent Chart 3.51 Planted Area with Inorganic Fertilizer by Crop Type - Manyara Roots & Tubers, 0, 0.0% Pulses, 270, 28.4% Oilseeds, 17, 1.8% Fruits & Vegetables, 222, 23.4% Cash Crop, 0, 0.0% Cereals, 440, 46.4% Chart 3.53 Proportion of Planted Area Applied with Inorganic Fertiliser by District - Manyara 0.0 0.6 1.2 1.8 Simanjiro Hanang Kiteto Babati Mbulu District Percent 0.0 15.0 30.0 45.0 60.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.52 Percentage of Planted Area with Inorganic Fertilizer by Crop Type - Manyara Kiteto Simanjiro Babati Hanang Mbulu 709ha 1,401ha 662ha 3,942ha 1,356ha 3.4% 0.9% 1.2% 6.8% 4.2% 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Kiteto Hanang Simanjiro Babati Mbulu 68,647ha 41,968ha 26,481ha 34,311ha 14,350ha 92% 82% 59% 34% 72 60,000 to 75,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Tanzania Agriculture Sample Census MAP 3.29 MANYARA Planted Area and Percent of Planted Area with No Application of Fertilizer by District MAP 3.30 MANYARA Area Planted and Percent of Total Planted Area with Irrigation by District Area Planted and Percent of Planted Area with no Fertilizer Applied Planted Area (ha) Planted Planted (ha) Planted Planted (ha) Percent of Planted Area With No Fertilizer Applied Planted Area with Irrigation by District RESULTS 44 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 3.5.4.3 Compost Use The total planted area applied with compost was 3,938 ha which represents only 1.5 percent of the total planted area with annual crops in the region and 4.5 percent of the total planted area with fertilisers in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 1,449 ha and it was applied to 3,846 ha representing 1.5 percent of the total area planted. The results show that 51 percent of the area applied with compost was planted with cereals, followed by pulses ( 33%) oilseeds (15%)and fruit and vegetables (1%). No compost was applied to cash crops (Chart 3.54). The proportion of area applied with compost was very low for each type of crop (0 to 9%); however the distribution of the total area using compost manure shows that 46.6 percent of this area was cultivated with oil seeds, followed by fruits and vegetables (7.2%), cereals (3.1%), pulses (3.1%) and fruit and vegetables (21%)(Chart 3.55). Compost was mostly used in Hanang (4% of the total planted area in the district), and this was closely followed by Simanjiro (1.1%). Other districts, like Babati used the least compost (0.5%) (Chart 3.56) In permanent crops, compost was mainly used on bananas (1%). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in Manyara region. Insecticides were applied to a planted area of 35,531 ha of annual crops and vegetables. Insecticides were the most common pesticides used in the region (56.4% of the total area applied with pesticides). This was followed by fungicides (22.0%) and herbicides (21.7%) (Chart 3.57). Chart 3.54 Planted Area with Compost by Crop Type - Manyara Roots & Tubers, 8, 0% Cereals, 1,985, 51% Fruits & Vegetables, 31, 1% Pulses, 606, 15% Oilseeds, 1,308, 33% Cash Crop, 0, 0% 0 5 10 15 20 25 Percent of Pla nted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.55 Percentage of Planted Area with Compost by Crop Type- Manyara Chart 3.56 Proportion of Planted Area Applied with Compost by District - Manyara 0.0 1.5 3.0 4.5 Hanang Simanjiro Kiteto Mbulu Babati District Percent Chart 3.57 Planted Area (ha) by Pesticide Use Fungicides, 7,807, 22.0% Insecticide s, 20,026, 56.4% Herbicides, 7,698, 21.7% RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 46 3.5.5.1 Insecticide Use The planted area applied with insecticides was 20,025 ha which represents 7.5 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (15,032 ha, 75.1% of the total planted area with insecticides), followed by pulses (4,123 ha, 20.6%), fruits and vegetables (446 ha, 2.2%), oil seeds (338 ha, 1.7%), root and tubers (87 ha, 0.4%) and no insecticides were applied on cash crops (Chart 3.59). However, the percent of pesticides used in fruits and vegetables was much greater than in other crop types (78.3%) followed by pulses (8.8%), cereals (7.4%), roots and tubers (6.1%) and oil seeds (2.6%) Chart 3.59). Annual crops with more than 50 percent insecticide use were spinach (100%), cucumber (100%), water melon (100%), tomatoes (100%), onions (100%), cabbage (100%), chillies (100%) and okra (75%). Hanang and Babati had the highest percent of planted area with insecticides (8.6% of the total planted area with annual crops in the district). This was closely followed by Kiteto (8.0%), Simanjiro (6.3) and Mbulu (4.3%) (Chart 3.60). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 7,698 ha which represented 2.9 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (6,160 ha, 80%) followed by pulses (1,372 ha, 17.8%), fruit and vegetables (128 ha, 1.7%) and oil seeds (37 ha, 0.5%) (Chart 3.61). Chart 3.58 Planted Area Applied with Insecticides by Crop Type Fruits & Vegetables, 446, 2.2% Oil seeds & Oil nuts, 338, 1.7% Cash crops, 0, 0.0% Pulses, 4,123, 20.6% Roots & Tubers, 87, 0.4% Cereals, 15,032, 75.1% 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.59 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.60 Percent of Planted Area Applied with Insecticides by District - Manyara 0.0 3.0 6.0 9.0 Hanang Babati Kiteto Simanjiro Mbulu District Percent Chart 3.61 Planted Area Applied with Herbicides by Crop Type Cereals, 6,160, 80.0% Roots & Tubers, 0, 0.0% Pulses, 1,372, 17.8% Oil seeds, 37, 0.5% Fruits & Vegetables, 128, 1.7% Cash crops, 0, 0.0% T RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 However, the percent of herbicide use on fruit and vegetables was much greater than in other crop types (22.5%) while only 0.3 percent of oil seeds was applied with herbicides (Chart 3.62). The top two annual crops with highest percentage use of herbicides in terms of planted area were tomotoes (71.6%) and paddy (49.7%). Hanang had the highest percent of planted area with herbicides (5.8% of the total planted area with annual crops in the district). This was followed by Babati (3.7%, Kiteto (2.3%), Simanjiro (2.0%) and Mbulu (0.6%) (Chart 3.63). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 7,807 ha which represented 2.9 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season (5.7%) was higher than the corresponding percentage in the long rainy season (2.9%). Cereals had the largest planted area applied with fungicides (5,628ha, 72.1%) ,followed by pulses (1,705 ha, 21.8%), fruits and vegetables (271 ha, 3.5%) and oil seeds (203 ha, 2.6%). No fungicides were used on cash crops (Chart 3.64). However, the percentage use of fungicide in fruits and vegetables was much greater than in other crop types (47.6%), while only3.6 percent of pulses, 2.8 percent of cereals and 15 percent of oil seeds were applied with fungicides (Chart 3.65). Hanang had the highest percent of planted area with fungicides (6.7% of the total planted area with annual crops in the district). This was closely followed by Babati (3.5%), Simanjiro (1.9%), Kiteto (1.5%) and Mbulu (1.1%) (Chart 3.66). 0.0 5.0 10.0 15.0 20.0 25.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.62 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.63 Proportion of Planted Area Applied with Herbicides by District - Manyara 0.0 1.5 3.0 4.5 6.0 Hanang Babati Kiteto Simanjiro Mbulu District Percent Chart 3.64 Planted Area Applied with Fungicides by Crop Type Pulses, 1,705, 21.8% Oil seeds, 203, 2.6% Fruits & Vegetables, 271, 3.5% Cash crops, 0, 0.0% Cereals, 5,628, 72.1% Roots & Tubers, 0, 0.0% 0.0 15.0 30.0 45.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.65 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.66 Proportion of Planted Area with Fungicides by District - Manyara 0.0 2.0 4.0 6.0 Hanang Simanjiro Babati Kiteto Mbulu District Percent RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (1.3%). All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 80 percent of the total area planted with cereals during the long rainy season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.7percent, 5.6 percent and 8.1 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in many areas in Tanzania and without water most other agricultural practices applied to crops do not result in a significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Manyara region, the area of annual crops under irrigation was 6,736 ha representing 2.5 percent of the total area planted (Chart 3.67). The area under irrigation during the short rainy season was 765 ha accounting for 11 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the long rainy season with irrigation. In the long rainy season, 56 percent of the area planted with vegetables was irrigated, whilst 100 percent of the area with vegetables was irrigated in the short rainy season. The district with the largest planted area under irrigation with annual crops was Babati (2,977 ha, 44.2% of the total irrigated planted area with annual crops in the region). This is closely followed by Simanjiro with (1,368 ha, 20.3%) and then Mbulu (1,103 ha, 16.4%). When expressed as a percentage of the total area planted in each district, Babati had the highest with 5.1 percent of the planted area in the district under irrigation. This is followed by Simanjiro (4.3%), Mbulu (2.6%), Hanang (1.0%) and Kiteto (0.9%) (Chart 3.68 and Map 3.29). Of all the different crops and in terms of proportion of the irrigated planted area, okra and onion were the most irrigated crops with 100 percent irrigation followed by paddy (95%). Chart 2.67 Planted Area of Irrigated Land (hectares) Area with no irrigation, 258,523, 97.5% Irrigated Area, 6,736, 2.5% Chart 3.68 Planted Area and Percentage of Planted Area with Irrigation by District 0 1,000 2,000 3,000 Babati Simanjiro Mbulu Kiteto Hanang District Area Planted (ha) 0.0 2.0 4.0 6.0 Percentage with Irrigation % with Irrigation RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 In terms of crop type, the area under irrigation with cereals was 5,477 ha (81.3% of the total area under irrigation), followed by pulses with 869 ha (12.9%), fruit and vegetables (364 ha, 5.4%) and roots and tubers (7 ha, 0.1%), oil seeds (19ha, 0.3%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 364 ha which represents 63 percent of the total planted area with fruit and vegetables. Onions, tomatoes and okra were the most irrigated crops. The planted area with irrigation in Manyara region appears to have increased steadly over a period of 10 years from 5,779 to 6,736 hectares. However, this may not be statistically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was the river (69.6% of households with irrigation). This was followed by canals (17%) and wells (5.7%). Only 0.9 percent of the households used piped water and the proportion of households that used borehole and dams as sources of water for irrigation were very few (4.9% and 1.8% respectively). The highest percent of households that obtain their irrigation water from rivers are found in Simanjiro and Babati districts (82% and 76% respectively) (Chart 3.70). Chart 3.69 Time Series of Households with Irrigation - Manyara 5,779 6,736 0 5,000 10,000 Manyara Agriculture Year Planted Area ubder Irrigation Chart 3.70 Number of Households with Irrigation by Source of Water Dam, 118, 1.8% Pipe water, 60, 0.9% Well, 378, 5.7% Borehole, 321, 4.9% Canal, 1,120, 17.0% River, 4,578, 69.6% Simanjiro Kiteto Hanang Mbulu Babati 13,977 3,843 16,241 37,585 16,476 47.9% 23.5% 54.7% 80.6% 52% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Hanang Simanjiro Kiteto Babati 58.4% 46.5% 45.5% 33% 54.4% Mbulu 53.4 to 58.4 48.3 to 53.4 43.2 to 48.3 38.1 to 43.2 33 to 38.1 Tanzania Agriculture Sample Census MAP 3.31 MANYARA Percent of Households Storing Crops for 3 to 6 Months by district MAP 3.32 MANYARA Number of Households and Percent of Total Households Selling Crops by District Percent of Households Storing Crops Percent of Households Storing Crops Number of Households Selling Crops Number of Households Selling Crops Percent of Planted Area with no Fertilizer Applied Planted of Total Households Selling Crops RESULTS 50 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of obtaining water for irrigation with 74.7 percent of households using this method. This was followed by hand bucket with 24.7 percent of households and motor pump (0.6%) (Chart 3.71). Hand bucket for obtaining water was used by 55 percent of the agricultural households with irrigation in Mbulu district, whilst gravity was used by most of the agricultural households in Babati, Simanjiro and Hanang districts. The few households with Irrigation in Kiteto district used hand bucket for obtaining water for irrigation. 3.6.4 Methods of Water Application Most households in Manyara region used flood irrigation (75% of households using irrigation) as a method of field application. This was followed by hand bucket/watering can (25%) (Chart 3.72). All households with irrigation in Simanjiro and Hanang districts and most households in Babati district used the flood method for applying irrigation water from the source. However, most households in Mbulu district and all households in Kiteto district used hand bucket/watering cans for irrigation water application. 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Manyara region show that there were 123,200 crop growing households (82% of the total crop growing households in Manyara region) that stored various agricultural products in the region. The most important stored crop was maize with 118,797 households storing 57,729 tonnes as of 1st January 2004. This was followed by beans and other pulses (58,728 households, Chart 3.72 Number of Households with Irrigation by Method of Field Application Flood, 4,950, 75% Bucket / Watering Can, 1,624, 25% Chart 3.71 Number of Households by Method of Obtaining Irrigation Water Motor Pump, 36, 0.6% Gravity, 4,914, 74.7% Hand Bucket, 1,624, 24.7% Chart 3.73 Number of Households and Quantity Stored by Crop Type - Manyara 0 40,000 80,000 120,000 Maize Pulses Sorghum & Millet Paddy Wheat Groundnuts/Bambara Nuts Crop N u m b er of h ou seh old s 0 20,000 40,000 60,000 Q u an tity (t) Number of households Quantity stored (Tons) DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 52 5,409t), sorghum and millets (10,909 households, 1,684t), paddy (2,543 households, 2,540t), wheat (2,000 household, 650t) and groundnuts (1,638 household, 145t). Other crops were stored in very small amounts. 3.7.1.1 Methods of Storage The region had 63,055 crop growing households storing their produce in sacks/open drum (51.2% of households that stored crops in the region). The number of households that stored their produce in locally made traditional structures was 55,950 (45.4%). This was followed by improved locally made structures (2,669 households, 2.2%), air tight drum (567 household, 0.5%), unprotected piles (277 households, 0.2%), and modern stores (235 households, 0.2%) and other methods (447 households, 0.4%) (Chart 3.74). Sacks/open drums were the dominant storage method with Simanjiro having the highest percent of households using this method (83% of the total number of households storing crop products). This was followed by Kiteto (78%), Babati (48%), Hanang (39%) and Mbulu (36%). The highest percent of households using locally made traditional crib was in Mbulu and Hanang districts (61% and 60% of the total number of households storing crops respectively), followed by Babati (48%), Kiteto (19%) and Simanjiro (6%) (Chart 3.75). 3.7.1.2 Duration of Storage Most households (44% of the households storing crops in Manyara region) stored their produce for a period of 3 to 6 months followed by those who stored for over 6 months (42%). The minority of households stored their crops for a period of less than 3 months (14%). Most households that stored pulses stored them for a period more than 6 months followed by those who stored for a period of 3 to 6 months. A small number of households stored pulses for the period of less than 3 months. However, most households that stored maize stored them for a period of 3 to 6 months followed by those who stored for a period of more than 6 months (Chart 3.76). Chart 3.74 Number of households by Storage Methods - Manyara In Locally Made Traditional Structure, 55,950, 45.4% In Sacks / Open Drum, 63,055, 51.2% Other, 447, 0.4% Unprotected Pile, 277, 0.2% In Airtight Drum, 567, 0.5% In Improved Locally Made Structure, 2,669, 2.2% In Modern Store, 235, 0.2% Chart 3.75 Number of Households by Method of Storage and District (based on the most important household crop) 0 25 50 75 100 Mbulu Hanang Babati Kiteto Simanjiro District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other 0 20,000 40,000 60,000 Number of households Maize Beans & Pulses Sorghum & Millet Crop Chart 3.76 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mbulu district (58.4%), followed by Simanjiro (54.4%), Hanang (46.5%), Kiteto (44.7%) and Babati (33%) (Map 3.30). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Most districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.77). However, households in Mbulu district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirements of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millets, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 97.4 percent, followed by seed for planting. Practically all stored annual crops were stored for the purpose of food for the household (Chart 3.78). 3.7.1.4 The Magnitude of Storage Loss About 82 percent of households that stored crops had little or no loss, followed by households with up to a quarter loss (13%), household with between a quarter and a half loss (3%) and household with more than a half loss (2%) (Table 3.10). The proportion of households that reported a loss of more than a quarter was greatest for maize (5.3% of the total number of households that stored crops). This was followed by sorghum and millets (5.2%) and beans and pulses (2.2%). Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Babati 34,324 6,173 1,431 719 42,646 Hanang 17,621 3,850 929 1,481 23,881 Mbulu 23,547 2,388 833 257 27,025 Simanjiro 6,182 515 125 38 6,860 Kiteto 19,252 3,039 434 116 22,840 Total 100,924 15,964 3,753 2,611 123,252 Chart 3.77 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 20,000 40,000 60,000 Babati Hanang Mbulu Simanjiro Kiteto District Quantity (tonnes) 0 25 50 75 100 Percent Stored Quantity harvested Quantity stored Percent stored 0% 25% 50% 75% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Wheat Groundnuts Crop Type Chart 3.78 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Others Hanang Kiteto Simanjiro Babati Mbulu 3,028ha 3,232ha 4,318ha 7,564ha 7,019ha 18.9% 15.7% 9.8% 30.7% 12.9% 6,600 to 7,600 5,700 to 6,600 4,800 to 5,700 3,900 to 4,800 3,000 to 3,900 Kiteto Simanjiro Mbulu Hanang Babati 13,977 3,843 16,241 37,585 16,476 47.9% 52% 23.5% 80.6% 54.7% 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanzania Agriculture Sample Census MAP 3.33 MANYARA Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.34 MANYARA Number and Percent of Crop Growing Households Using Improved Seed by District Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Number of Crop Growing Households Using Improved Seed Number of Crop Growing Households Using Improved Seed Percent of Total Households Receiving Crop Extension Services Percent of Total Households Using Improved Seed RESULTS 54 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.7.2 Agro - processing and By-products Agro - processing refers to a process that converts a crop product from one form to another in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Manyara region (136,172 households, 91% of the total crop growing households) (Chart 3.79). The percent of households processing crops was very high in most districts (above 80%). Simanjiro had the lowest percent of households processing crops (50% of crop growing households in the region) (Chart 3.80). 3.7.2.1 Processing Methods Most crop processing households in Manyara region processed their crops using neighbour’s machines (119,955 households, 88% of the crop processing households). This was followed by those processing by trader (9,842 households, 7%), on farm by machine (3,013 households, 2%) and on-farm by hand (2,962 households, 2%). Although processing by machine was the most common processing method in all districts in Manyara region, however district differences existed. Simanjiro had a higher percent of households processing on farm by hand (8%), followed by Kiteto (3%) and Babati (2%). Processing by trader was more common in Mbulu and Hanang (18% and 6% respectively), whilst processing on farm by machine was more prevalent in Babati, Kiteto and Hanang (Chart 3.81). Chart 3.81 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Babati Hanang Mbulu Simanjiro Kiteto District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.79 Households Processing Crops Households not Processing, 14,105, 9% Households Processing, 136,172, 91% 0 25 50 75 100 Percent of Households Processing Mbulu Babati Kiteto Hanang Simanjiro District Chart 3.80 Percentage of Households Processing Crops by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the major product after processing and the by-product is secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product in Manyara region was flour/meal with 130,628 households processing crops into flour (95.9%), followed by grain with 4,780 households (3.5%). The remaining products were produced by a small number of households (Chart 3.82). The number of households producing by-products was 16,393 accounting for 12 percent of the crop processing households in Manyara region. The most common by-product produced by crop processing households was bran with 13,619 households (10.0%), followed by cake (1,437 households, 1.1%), oil (500 households, 0.4%) and husk (347 households, 0.3%). The remaining by-products were produced by 254 households constituting 0.2% of the households processing crops and no by-product were (119,779 households, 88%) (Chart 3.83). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, for selling and for animal consumption. The most important use was for household/human consumption which represented 99.5 percent of the total households that used primary processed product (Chart 3.84). Mbulu was the only district that used primary products for animal consumption. Chart 3.83 Number of Households by Type of By-product Other, 254, 0.2% No by-product, 119,779, 88.0% Husk, 347, 0.3% Cake, 1,437, 1.1% Oil, 500, 0.4% Shell, 148, 0.1% Bran, 13,619, 10.0% Chart 3.84 Use of Processed Product Fuel for Cooking, 0, 0.0% Sale Only, 258, 0.2% Animal Consumption, 174, 0.1% Did Not Use, 227, 0.2% Household / Human Consumption, 135,512, 99.5% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of households Babati Hanang Simanjiro Mbulu Kiteto District Chart 3.85 Percentage of Households Selling Processed Crops by District Chart 3.82 Percent of Households by Type of Main Processed Product Grain, 4,780, 3.5% Oil, 623, 0.5% Other, 44, 0.0% Juice, 85, 0.1% Fiber, 12, 0.0% Flour / Meal, 130,628, 95.9% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 Out of 258 households that sold processed products, 118 were from Babati (45.8% of the total number of households selling processed products in the region), followed by Hanang with 80 households (31%) and Simanjiro with 60 households (23.3%) (Chart 3.85). Compared to other districts in Manyara region, Hanang and Babati had the highest percent of households that sold processed products (0.26% each). This is followed by Simanjiro (0.24%). 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (1,531 households, 7.9% of households that sold crops). This was followed by selling to traders at farm (1,268 households, 6.6%), local market/trade store (320 households, 1.7%), marketing co-operatives (227 households, 1.2%), farmers association (121 households, 0.6%), secondary market (117 households, 0.6%) and large scale farm (87 households, 0.4%) (Chart 3.86). There were large differences between districts in the proportion of households selling processed products to neighbours with Mbulu district having the largest percent of households in the district selling to neighbours (66.6%), whereas Babati had only 2.4 percent. Simanjiro had the highest percent of households relying on local market/trade store than other outlets. Compared to other districts, Hanang had the highest percent of households selling processed products to trader at farm, followed by Kiteto. The districts that had the highest proportion of households selling processed products to marketing cooperative was Hanang. Mbulu was the only district that sold processed products to large scale farms. In Kiteto, the sale of processed produce to farmer associations was most prominent compared to other districts. 3.7.3 Crop Marketing The number of households that reported selling crops was 88,121 which represent 58.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Babati (81%) followed by Kiteto (55%), Hanang (52%), Mbulu (48%), and Simanjiro (23%) (Chart 3.88 and Map 3.31). Chart 3.86 Location of Sale of Processed Products Trader at Farm, 1,268, 6.6% Large Scale Farm, 87, 0.4% Neighbours, 1,531, 7.9% Local Market / Trade Store, 320, 1.7% Marketing Co- operative, 227, 1.2% Secondary Market, 117, 0.6% Farmers Association, 121, 0.6% Other, 15,683, 81.0% Chart 3.88 Number of Crop Growing Households Selling Crops by District 0 10,000 20,000 30,000 40,000 Babati Mbulu Hanang Kiteto Simanjiro District Number of Households 0 30 60 90 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.87 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 25% 50% 75% 100% Mbulu Simanjiro Hanang Kiteto Babati District Percent of Households Selling Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (59.3% of crop growing households that reported marketing problems). Apart from low market prices, other problems were longer distances to the markets (15.1%), no transport (11.2%), high transport costs (7.1%), lack of market information (4.8%) and no buyer (1.6%). Other marketing problems were minor and each represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 84.6 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts except for Simanjiro and Hanang where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (19.4% and 7.4% respectively). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Manyara region very few agricultural households (264, 0.2%) accessed credit out of which 114 (43%) were male-headed households and 150 (57%) were female headed households. In Babati district only female headed households got agricultural credit whereas in Hanang district only male households accessed credit. In Kiteto and Mbulu districts both male and female headed households had no access to agricultural credit (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 55,673 84.6 Other 7,286 11.1 Price Too Low 1,586 2.4 Trade Union Problems 684 1.0 Co-operative Problems 379 0.6 Market Too Far 185 0.3 Government Regulatory Board Problems 75 0.1 Total 65,868 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Babati 0 0 94 100 94 Hanang 74 100 0 0 74 Simanjiro 41 42 56 58 97 Kiteto 0 0 0 0 0 Mbulu 0 0 0 0 0 Total 114 43 150 57 264 Chart 3.89 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Trade Union Problems 0.1% Farmers Association Problems 0.2% Open Market Price Too Low 59.3% Government Regulatory Board Problems 0.2% Transport Cost Too High 7.1% No Buyer 1.6% Market too Far 15.1% No Transport 11.2% Lack of Market Information 4.8% Other 0.3% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Manyara region were family, friends and relatives which collectively provided credit to 170 agricultural households (64% of the total number of households that accessed credit). However 94 households (36%) received agriculture credit from other sources (Charts 3.90 and 3.91). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on unspecified activities (26.1%), followed by hiring labour (22.8%), purchase seeds (18.4%), tools and equipments (11.8%) and livestock rearing (11.8%). The proportion of credits intended to be used to purchase fertilizers and agro-chemicals was very low (Chart 3.92). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little awareness accounting to 68.8 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (16.8%) and “not wanting to go into debt” (6.9%). The rest of the reasons collectively accounted for 7.5 percent of the households not using credit. 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 38,712 (26% of total crop growing households in the region) (Chart 3.94). Some districts had more access to extension services than others, with Simanjiro having a Chart 3.91 Number of Households Receiving Credit by Main Source of Credit and District 0% 25% 50% 75% 100% Babati Hanang Simanjiro District Percent of Households Family, Friend and Relative Other Chart 3.90 Percentage Distribution of Households Receiving Credit by Main Source Other 36% Family, Friend and Relative 64% Chart 3.92 Proportion of Credit Receivied by Main Purpose of the Credit Livestock 11.8% Seeds 18.4% Tools / Equipment 11.8% Irrigation Structures 0.0% Agro-chemicals 4.5% Other 26.1% Fertilizers 4.5% Labour 22.9% Chart 3.93 Reasons for not Using Credit (% of Households) Interest rate/cost too high, 2,113, 1.4% Other, 482, 0.3% Credit granted too late, 802, 0.5% Not needed, 6,077, 3.9% Difficult bureaucracy procedure, 2,043, 1.3% Did not want to go into debt, 10,645, 6.9% Not available, 25,919, 16.8% Don't know about credit, 51,153, 33.2% Did not know how to get credit, 54,697, 35.5% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 relatively high proportion of households (31.5%) that received crop extension messages in t he district, followed by Babati (30.5%), Hanang (30.4%), Kiteto (19.8%) and Mbulu (13.9%) (Chart 3.95 and Map 4.32). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice, the Government provided the greatest proportion (94.8%, 35,400 households). NGOs provided 3.1 percent, large scale farms 1.1 percent and the remaining sources provided less than 1 percent (Chart 3.96). However, district differences existed with the proportion of the households receiving advice from government services ranging from 80.5 percent in Kiteto district to 98.24 percent in Mbulu and Hanang. 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 56.7 percent of the households receiving extension ranked the service as being “good”, followed by “average” (24.2 %), “very good” (13.3%), “poor” (4.8%) and “no good” (0.9%) (Chart 3.97). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias can be expected. Chart 3.94 Number of Households Receiving Extension Advice Households Not Receiving Extension , 111,565, 74% Households Receiving Extension , 38,712, 26% Chart 3.95 Number of Households Receiving Extension by District 0 5,000 10,000 15,000 Babati Hanang Simanjiro Kiteto Mbulu District N um ber of Households 0.0 15.0 30.0 45.0 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.97 Number of Households Receiving Extension by Quality of Services Very Good, 5,049, 13.3% No Good, 357, 0.9% Poor, 1,847, 4.8% Average, 9,235, 24.2% Good, 21,608, 56.7% Chart 3.96 Number of Households Receiving Extension Messages by Type of Extension Provider Government, 35,400, 94.8% Other, 210, 0.6% NGO / Development Project, 1,156, 3.1% Cooperative, 178, 0.5% Large Scale Farm, 410, 1.1% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Manyara regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Manyara region farm yard manure was used by 58,519 households which represent 39 percent of the total number of crop growing households. This is followed by households using improved seeds (13.6%), insecticides/fungicide (6.2%), compost (2.3%), herbicide (1.1%) and inorganic fertiliser (0.6%), (Table 2.13). 3.9.2 Inorganic Fertilisers Smallholders that used inorganic fertiliser in Manyara mainly purchased them from the local market/trade store (100% of the total number of inorganic fertiliser users) (Chart 3.98). Access to inorganic fertiliser was mostly over 20 km involving 82.1 percent of households using inorganic fertilizers, followed by less than 1 km (16%) and between 1 km and 3 km (1.9%) (Chart 3.99). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (20%) as the reason for not using, it may be assumed that access to inorganic fertilisers is not the main reason for not using them. Other reasons such as cost are more important with 50 percent of households responding to cost factors as the main reason for not using them. In other words, it may be assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. The only districts that had households using inorganic fertilizers were Simanjiro and Hanang with 4 percent and 1 percent of the households respectively. Table 2.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 58,519 38.9 91,759 61.1 Improved Seeds 20,492 13.6 129,785 86.4 Insecticides/Fungicide 9,252 6.2 141,025 93.8 Compost 3,434 2.3 146,843 97.7 Inorganic Fertiliser 969 0.6 149,309 99.4 Herbicide 1,691 1.1 148,587 98.9 Chart 3.98 Number of Households by Source of Inorganic Fertiliser 0.0 0.0 0.0 0.0 0.0 100.0 0 250 500 750 1000 1250 Local Market / Trade Store Co-operative Large Scale Farm Locally Produced by Household Neighbour Development Project Source of Inorganic Fertiliser Number of Households Chart 3.99 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 30.0 60.0 90.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 3.9.3 Improved Seeds The percent of households that used improved seeds was 13.6 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (79.1%), followed by neighbours (7.4%), locally produced (5.2%). Other less important sources of improved seed were from crop buyers (2.2%), development projects (2.1%), cooperatives (1.2%), local farmers group (1.0%), secondary market (0.9%) and large farms (0.9%) (Chart 3.100). Access to improved seeds was better than access to chemical inputs with 25 percent of households obtaining the input within 1 km of the household (Chart 3.101). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly use improved seeds were Babati (33.5 percent of the total number of households using improved seeds in Manyara region), followed by Mbulu (24%), Simanjiro (18%), Kiteto (13%) and Hanang (9.4%) (Map 3.33). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (88.2% of the total number of insecticide/fungicide users). Other sources of insecticides/fungicides were of minor importance (Chart 3.102). Chart 3.100 Number of Households by Source of Improved Seeds 0.9 1.0 0.9 1.2 2.1 2.2 5.2 7.4 79.1 0 6000 12000 18000 Local Market / Trade Store Neighbour Locally Produced by Household Crop Buyers Development Project Co-operative Local Farmers Group Secondary Market Large Scale Farm Source of Improved Seeds Number of Households Chart 3.101 Number of Households Reporting Distance to Source of Improved Seeds 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.102 Number of Households by Source of Insecticide/Fungicide 88.2 5.4 3.9 1.4 1.1 0 3000 6000 9000 Local Market / Trade Store Locally Produced by Household Secondary Market Co-operative Large Scale Farm Source of Insecticide/Fungicide Number of Households DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 Chart 3.103 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 8 percent of households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 61 percent of households responding to cost factors as the main reason for not using. In other words, it may be assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide were used more in Simanjiro district (23.8 percent of the total number of households that used insecticide/fungicides in the region), followed by Babati (23.12%), Hanang (23.07%), Kiteto (19.6%) and Mbulu (10.4%). 3.10 Tree Planting The number of households involved in tree farming was 13,510 representing 9 percent of the total number of agriculture households (Chart 3.104). The number of trees planted by smallholders on their allotted land was 806,488 trees. The average number of trees planted per planting tree household was 60 trees. The main species planted by smallholders is Gravellia spp (493,306 trees, 61%), followed by Eucalyptus spp (94,871, 12%), then Cyprus (87,820, 11%) and Albizia spp (64,356 trees, 8%). The remaining trees species are planted in comparatively small numbers (Chart105). Chart 3.103 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 7 14 21 28 35 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.104 Number of Households with Planted Trees - Manyara. Households with no planted trees, 140,684, 91% Households with planted trees, 13,510, 9% Chart 3.106 Number of Trees Planted by Smallholders by Species and Region 0 200,000 400,000 600,000 Mbulu Babati Hanang Simanjiro Kiteto District Number of Trees Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Leucena Spp Jakaranda Spp Syszygium Spp Chart 2.105 Number of Planted Trees by Species - Manyara 0 100,000 200,000 300,000 400,000 500,000 Gravellis Eucalyptus Spp Cyprus Spp Albizia Spp Senna Spp Leucena Spp Azadritachta Spp Pinus Spp Acacia Spp Syszygium Spp Jakaranda Spp Terminalia Catapa Moringa Spp Tree Species Number of Trees DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 Mbulu had the largest number of smallholders with planted trees than any other district (65.2%) and the trees were dominated by Gravellia species. This was followed by Babati (25.7%) where the trees were dominated by Gravellia and to a lesser extent Albizia, then Hanang (5.5%), Simanjiro (2.5%) and Kiteto (1.1%) which were mainly planted with Gravellia, Azadritachta species and Senna species respectively (Chart 3.106 and Map 3.34). Smallholders mostly plant trees on plantations. The proportion of households that plant on plantations was 58.5 percent, followed by field boundaries (35%) and then trees planted scattered in the field (6.5%) (Chart 3.107). The main purpose of planting trees was to obtain planks/timber (57.1%). This is followed by wood for fuel (19.6%), poles (9.1%), shade (9.0%) and medicinal (4.9%) and other purposes 90.3%) (Chart 3.108). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 23,486 which represents 15 percent of the total number of agricultural households in the region (Chart 3.109). Chart 3.107 Number of Trees Planted by Location Plantation, 469,940, 58.5% Scattered in field, 52,572, 6.5% Field boundary, 281,472, 35.0% Chart 3.108 Number of Households by Purpose of Planted Trees 0.0 20.0 40.0 60.0 Planks / Timber Wood for Fuel Shade Poles Other Medicinal Use Percent of Households Chart 3.109 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 130,708, 85% Households with facilities, 23,486, 15% Chart 3.110 Number of Households with Erosion Control/Water Harvesting Facilities 19.3 10.9 25.3 3.8 4.0 0 3,000 6,000 9,000 12,000 Babati Mbulu Hanang Kiteto Simanjiro District Number of Households 0.0 10.0 20.0 30.0 Percent With Water Harvesting Percent with Facility Simanjiro Hanang Kiteto Babati Mbulu 655 3,417 983 11,805 6,626 19.3% 10.9% 25.3% 3.8% 4% 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Simanjiro Kiteto Hanang Mbulu Babati 541 570 1,227 3,348 7,824 2.2% 3.3% 3.9% 16.8% 9.7% 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census MAP 3.35 MANYARA Number and Percent of Smallholder Planted Trees by District MAP 3.36 MANYARA Number and Percent of Households with Water Harvesting Bunds by District Number of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households with Water Harvesting Bunds Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Percent of Households with Water Harvesting Bunds RESULTS 65 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 The proportion of households with soil erosion control and water harvesting facilities was highest in Babati district (25.3%) followed by Mbulu (19.3%), hanang (10.9%), Simanjiro (4.0%) and Kiteto (3.8%) (Chart 3.110). Erosion control bunds accounted for 54.6 percent of the total number of structures, followed by water harvesting bunds (25.2%), vertiver grass (10.1%), drainage ditches (5.5%), tree belts (3.0%), gabions/sandbags (1.0%) terraces (0.5%) and dams (0.1%) (Chart 3.111 and Map 3.35). Erosion control bunds, water harvesting bunds and vetiver grass together had 97,481 structures. This represented 90 percent of the total structures in the region. The remaining 10 percentages were shared among the rest of the erosion control methods mentioned above. Babati and Mbulu districts had 84,511 erosion control structures (78 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 1,177,951. Cattle was the dominant livestock type in the region, followed by goats, sheep and pigs. The region had 7.2 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Manyara region was 1,163,051 (98.7 % of the total number of cattle in the region), 13,761 cattle (1.2%) were dairy breeds and 1,139 cattle (0.001%) were beef breeds. The census results show that 89,747 agricultural households in the region (58.2% of total agricultural households) kept 1.2 million cattle. This was equivalent to an average of 13 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Babati which had about 263,625 cattle (22.4% of the total cattle in the region). This was followed by Simanjiro (263,264 cattle, 22.3%), Mbulu (253,735 cattle, 21.5%), Hanang (219,217 cattle, 18.6%) and Kiteto (178,110 cattle, 15.1%) (Chart 3.112 and Map 3.36). However, Mbulu district had the highest density (209 head per km2 ) (Map 3.37). Chart 3.111 Number of Erosion Control/Water Harvesting Structures by Type of Facility 54.6 25.2 10.1 5.5 3.0 1.0 0.5 0.1 0 20,000 40,000 60,000 Erosion Control Bunds Water Harvesting Bunds Vetiver Grass Drainage Ditches Tree Belts Gabions / Sandbag Terraces Dam Type of Facility Number of Structures 0 100 200 300 Number of Cattle ('000') Babati Simanjiro Mbulu Hanang Kiteto District Chart 3.112 Total Number of Cattle ('000') by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 Although Babati district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle in the district was very small, though it was the largest in the region. The number of beef cattle was insignificant (Chart 3.113). 3.12.1.2 Herd Size Thirty percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 64 percent of all cattle in the region. Only 5 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 94 percent of total cattle rearing households had herds of size 1-30 cattle and owns 67.6 percent of total cattle in the region, resulting in an average of 9 cattle per cattle rearing household. There were about 381 households with a herd size of more than 151 cattle each (88,495 cattle in total) resulting in an average of 232 cattle per household. 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region, followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Manyara region ranked 3 out of the 21 regions with 8.4 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Manyara region was 80,558 (52% of all agricultural households in the region) with a total of 991,152 goats giving an average of 12 head of goats per goat-rearing-household. Simanjiro had the largest number of goats (317,648 goats, 32% of all goats in the region), followed by Babati (191,163 goats, 19.3%), Mbulu (184,256 goats, 18.6%), Hanang (160,469 goats, 16.2%) and Kiteto (137,616 goats, 13.9%) (Chart 3.127 and Map 3.38). However Mbulu district had the highest density (152 head per km2 ) (Map 3.39). 3.12.2.2 Goat Herd Size Thirty percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Seventy seven percent of total goat-rearing households had herd size of 1-14 goats and owned 39 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 3,270 households (4%) with herd sizes of 40 or more goats each (270,730 goats in total), resulting in an average of 83 goats per household. Chart 3.113 Number of Cattle by Type and District 5 3 1 0 6 0 8 0 0 7 ,0 0 7 2 ,9 3 7 3 ,3 3 8 9 1 3 8 7 177,723 263,173 216,280 256,086 249,790 0 100,000 200,000 300,000 Babati Hanang Mbulu Simanjiro Kiteto Districts N u m b er o f C a ttle Indigenous Beef Dairy 0 100 200 300 Number of Goats ('000'). Simanjiro Babati Mbulu Hanang Kiteto District Chart 3.114 Total Number of Goats ('000') by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 99.4 percent of the total goats in Manyara region. Improved goats for meat and diary goats constituted 0.01 and 0.56 percent of total goats respectively. 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Manyara region after cattle and goats. The region ranked 3 out of 21 Mainland regions and had 11 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep rearing households was 53,914 (35% of all agricultural households in Manyara region) rearing 439,314 sheep, giving an average of 8 heads of sheep per sheep rearing household. The district with the largest number of sheep was Simanjiro with 143,162 sheep (33%of total sheep in Manyara region), followed by Mbulu (98,269 sheep, 22%), Hanang (84,186 sheep, 19%), Babati (71,450 sheep, 16%) and Kiteto (42,247 sheep, 10%) (Chart 3.115 and Map 3.40). Mbulu district had the highest density (81 head per km2 ) (Map 3.41). Sheep rearing was dominated by indigenous breeds that constituted 99.5 percent of all sheep kept in the region. Only 0.5 percent of the total sheep in the region were improved breeds. 3.12.4. Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 9 out of 21 Mainland regions and had 4 percent of the Mainland total pigs. The number of pig rearing agricultural households in Manyara region was 16,210 (11% of the total agricultural households in the region) rearing 41,236 pigs. This gives an average of 3 pigs per pig-rearing household. The district with the largest number of pigs was Mbulu with 26,415 pigs (64.1% of the total pig population in the region), followed by Babati (12,254 pigs, 29.7%), Hanang (2,235 pigs, 5.4%), Kiteto (306 pigs, 0.7%) and Simanjiro (25 pigs, 0.06%) (Chart 3.116 and Map 3.42. However, Mbulu district had the highest density (21 head per km2 ) (Map 3.43). 0 50,000 100,000 150,000 Number of Sheep Simanjiro Mbulu Hanang Babati Kiteto District Chart 3.115 Total Number of Sheep by District 0 5,000 10,000 15,000 N u m b er o f P ig s Mbulu Babati Hanang Kiteto Simanjiro District Chart 3.116 Total Number of Pigs by District Kiteto Hanang Simanjiro Mbulu Babati 35.5 145.5 33.6 209.5 92.9 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 Simanjiro Kiteto Hanang Babati Mbulu 263,264 178,110 219,217 263,625 253,735 240,000 to 300,000 180,000 to 240,000 120,000 to 180,000 60,000 to 120,000 0 to 60,000 Tanzania Agriculture Sample Census MAP 3.37 MANYARA Cattle population by District as of 1st Octobers 2003 MAP 3.38 MANYARA Cattle Density by District as of 1st October 2003 Number of Cattle Cattle Population Number of Cattle Per Square Km Cattle Density RESULTS 69 Kiteto Hanang Simanjiro Babati Mbulu 27.4 106.5 40.5 67.3 152.2 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Kiteto Simanjiro Hanang Babati Mbulu 137,616 317,648 160,469 191,163 184,256 290,000 to 320,000 250,000 to 290,000 210,000 to 250,000 170,000 to 210,000 130,000 to 170,000 Tanzania Agriculture Sample Census MAP 3.39 MANYARA Goats population by District as of 1st Octobers 2003 MAP 3.40 MANYARA Goats Density by District as of 1st October 2003 Number of Goats Goats Population Number of Cattle Per Square Km Goats Density RESULTS 70 Babati Hanang Kiteto Simanjiro 25.2 55.9 8.4 81.1 18.3 Mbulu 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Kiteto Simanjiro Hanang Mbulu Babati 42,247 143,162 84,186 98,269 71,450 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tanzania Agriculture Sample Census MAP 3.41 MANYARA Sheep population by District as of 1st Octobers 2003 MAP 3.42 MANYARA Sheep Density by District as of 1st October 2003 Number of Sheep Sheep Population Number of Sheep Per Square Km Sheep Density RESULTS 71 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.12.5 Chicken Production The poultry sector in Manyara region was dominated by chicken production. The region contributed 2.1 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken in Manyara region was 89,848 raising about 699,345 chickens. This gives an average of 8 chickens per chicken-rearing household. In terms of total number of chickens in the country, Manyara region was ranked twenty out of the 21 Mainland regions. The District with largest number of chickens was Babati (271,571 chickens, 39% of the total number of chickens in the region), followed by Mbulu (152,860, 22%), Hanang (149,058, 21%), Simanjiro (82,520, 12%) and Kiteto (43,336, 6%) (Chart 3.117 and Map 3.44). However Mbulu district had the highest chicken density (126 head per km2 (Map 3.45). 3.12.5.3 Chicken Flock Size The results indicate that about 93 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 6 chickens per holder. About 6.5 percent of holders were reported to be keeping the flock size of 20 to 99 chickens (Table 3.14). 3.12.6. Other Livestock There were 18,942 ducks, 10,698 turkeys, 8,707 rabbits and 47,009 donkeys raised by rural agricultural households in Manyara region. Table 3-16 indicates the number of other livestock kept in each district. The biggest number of ducks in the region was found in Kiteto District (59% of all ducks in the region), followed by Babati (26%), Simanjiro (9%), Mbulu (3%) and Hanang (2%). Turkeys were reported in Mbulu, Kiteto and Simanjiroa districts only, whilst rabbits were reported in Kiteto, Simanjiro and Babati. Most of the donkeys were found in Simanjiro, followed by Hanang, mbulu and Kiteto (Table 3.15). Table 3.14 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 33,949 37.8 98,124 3 5-9 28,933 32.2 185,796 6 10-19 21,120 23.5 259,732 12 20-29 4,460 5.0 95,842 21 30-39 726 0.8 23,494 32 40-49 306 0.3 12,239 40 50-99 336 0.4 22,258 66 100+ 18 0.0 1,860 106 Total 89,848 100.0 699,345 8 Table 3.15 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Babati 4,946 . 122 2,968 4,669 Hanang 458 . . 9,735 . Mbulu 599 5,131 . 8,268 . Simanjiro 1,695 2,105 822 18,282 794 Kiteto 11,243 3,462 7,763 7756 . Total 18,942 10,698 8,707 47,009 5,463 0 100,000 200,000 300,000 Number of Chickens Babati Mbulu Hanang Kiteto Simanjiro District Chart 3.117 Total Number of Chickens by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 3.12.7 Pest and Parasite Incidence and Control The results indicate that 74 percent and 26 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.118 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Simanjiro district but lowest in Mbulu district (Map 3.46). The most practiced method of tick controlling was spraying with 55 percent of livestock-rearing households that reported the problem using the method. Other methods used were smearing (19%), dipping (8%) and other traditional methods like hand picking (5%). However, 13 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 39.5 percent of livestock- rearing households reporting the problem, followed by dipping (16%) and other traditional methods (4%). However, 41 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 De-worming Livestock rearing households that de-wormed their animals were 63,343 (63% of the total livestock rearing households in the region). The percentage of the households that de-wormed cattle was 55 percent, goats (51%), sheep (54%) and pigs (75%) (Chart 3.119). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 22,043, representing 22.6 percent of the total livestock-rearing households and 14 percent of the agricultural households in Manyara region. The main livestock extension agent was the government which provided service to about 53 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (17%), Cooperatives (12%), large scale farms (12%) and other sources provided (6%). About 58 percent of livestock rearing households described the general quality of livestock extension services as being good, 20 percent said they were average and 12 percent said they were very good. However, 6 percent of the livestock rearing households said the quality was not good whilst 4 percent described them as poor (Chart 3.120). 0 15 30 45 Percent Babati Hanang Mbulu Simanjiro Kiteto District Chart 3.119 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.118 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 25 50 75 100 Simanjiro Hanang Babati Kiteto Mbulu District Percent Ticks Tsetseflies Chart 3.120 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good, 12,937, 58% Very Good, 2,673, 12% Poor, 1,300, 6% No good, 992, 4% Average, 4,358, 20% Hanang Simanjiro Kiteto Mbulu Babati 1.5 0 0.1 21.8 4.3 17.6 to 21.8 13.2 to 17.6 8.8 to 13.2 4.4 to 8.8 0 to 4.4 Kiteto Simanjiro Babati Hanang Mbulu 306 25 12,254 2,235 26,415 20,000 > 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Tanzania Agriculture Sample Census MAP 3.43 MANYARA Pig population by District as of 1st Octobers 2003 MAP 3.44 MANYARA Pig Density by District as of 1st October 2003 Number of Pig Pig Population Number of Pig Per Square Km Pig Density RESULTS 74 Mbulu Kiteto Hanang Babati 126.2 16.4 5.5 98.9 95.7 Simanjiro 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Babati Mbulu Kiteto Hanang 43,336 271,571 152,860 82,520 149,058 Simanjiro 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Tanzania Agriculture Sample Census MAP 3.45 MANYARA Number of Chicken by District as of 1st Octobers 2003 MAP 3.46 MANYARA Chicken Density by District as of 1st October 2003 Number of Chicken Chicken Population Number of Chicken Per Square Km Chicken Density RESULTS 75 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 56 percent of the livestock rearing households that accessed the service accessed it, at a distance of more than 14 kms. Only 44 percent of them accessed the services within 14 kms from their dwellings (Chart 3.121). The most affected district was Simanjiro district with over 50 percent of livestock rearing households accessing the services at a distance of more than 50 kms. Hanang and Mbulu districts were the least affected because about 61 and 62 percent of the households could access the service within a distance of 14 kilometres respectively (Chart 3.122). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest village watering point was 16,930 (68% of livestock rearing households accessing the watering point in Manyara region), whilst 5,628 households (23%) resided between 5 and 14 kms. However, 2,275 households (9%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.123). Mbulu district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Babati, Hanang, Simanjiro and Kiteto districts. In Kiteto district about 59 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.124). Chart 3.121 Number of Households by Distance to Verinary Clinic Less than 14km, 22,515, 44% More than 14km, 28,190, 56% Chart 3.122 Number of Households by Distance to Verterinary Clinic and District 0 3,000 6,000 9,000 12,000 Babati Hanang Mbulu Simanjiro Kiteto District N u m b er of Hou seh old s Less than 14km More than 14km Chart 3.123 Number of Households by Distance to Village Watering Points Less than 5 kms, 16,930, 68.2% 5-14 kms, 5,628, 22.7% 15 or more kms, 2,275, 9.2% Chart 3.124 Number of Households by Distance to Village Watering Point and District 0 2,100 4,200 6,300 Babati Hanang Mbulu Simanjiro Kiteto District Number of Households Less than 5 kms 5-14 kms 15 or more kms DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 77 3.12.9 Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Manyara region was by 85,025 households (55% of the total households in the region) using them (Chart 3.125). The number of households that used draft animals in Babati was 36,800 representing 43 percent of the households using draft animals in the region, followed by Hanang 22,952 households, 27%), Mbulu 21,505 households, 25%), Simanjiro (2,743 household, 3%) and Kiteto (1,024 households, 1%) (Chart 3.126 and Map 3.47) . The region had 147,712 oxen that were used to cultivate 110,979 hectares of land. This represents only 6.6 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Babati district (39,985 ha, 36% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Manyara region was 57,473 (38% of total crop growing households in the region) (Chart 3.127). The total area applied with organic fertilisers was 47,334 ha of which 999 hectares (2.1% of the total area applied with organic fertiliser or 0.37% of the area planted with annual crops and vegetables in Manyara region during the long rainy season) was applied with farm yard manure (Map 3.48). 3.12.9.4 Use of Compost Only 800 ha (2% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost was found in Hanang district with 387 hectares (48% of the total area applied with compost) followed by Babati (202 ha, 25%), Kiteto (120 ha, 15%), Mbulu (77 ha, 10%) and Simanjiro (14 ha, 2%) (Chart 3.128 and Map 3.49). Chart 3.127 Number of Households Using Organic Fertiliser Not Using Organic Fertilizer, 96,138, 63% Using Organic Fertilizer, 57,473, 37% Chart 3.128 Area of Application of Organic Fertiliser by District Manyara 0 5,000 10,000 15,000 20,000 Babati Mbulu Hanang Simanjiro Kiteto District Area of Fertiliser Application (ha) Series1 Series2 3.125 Number of Households Using Draft Amimals Using draft animal, 85,025, 55% Not using draft animal, 69,169, 45% 0 10,000 20,000 30,000 40,000 Number of Households Babati Hanang Mbulu Simanjiro Kiteto District Chart 3.126 Number of Households Using Draft Animals by District - Manyara Kiteto Mbulu Hanang Babati 2,743 1,024 21,505 22,952 36,800 16.8% 4% 73.5% 78.9% 62.5% Simanjiro 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Babati Simanjiro Kiteto Hanang Mbulu 20,397 10,654 4,978 16,844 16,946 69.8% 68.2% 80.6% 89.8% 66.3% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Tanzania Agriculture Sample Census MAP 3.47 MANYARA Number and Percent of Households Infected with Ticks by District MAP 3.48 MANYARA Number of Households Infected with Ticks Number of Households Infected With Ticks Number of Households Using Draft Animals Number of Households Using Draft Animals Percent of Households Infected With Ticks Percent of Households Using Draft Animals Number and Percent of Households Using Draft Animals by District RESULTS 78 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 3.12.10 Fish Farming The number of households involved in fish farming in Manyara region was 153 representing 0.1 percent of the total agricultural households in the region (Chart 3.129 and Map 3.50). The only districts involved in fish farming were Mbulu and Kiteto with Mbulu having 84 households involved in fish farming and Kiteto 69 households (Chart 3.130a). The main source of fingerings was the non governmental organizations and/or projects which provided fingering to 100 percent of the fish farming households. All fish farming households in the region used the dug-out-pond system and the only fish specie planted was Tilapia. The number of fish harvested in Manyara region was 21,094. (Chart 3.130b) and all fish were sold to their neighbours. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, tarmac roads were the services located very far from most of the household’s dwellings than any other service. It was located at an average distance of 101.7 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were district capital (47.4km) tertiary market (36.9km), hospitals (36.1km), secondary schools (21.7km), secondary markets (12.1km) primary market (10.5km), health clinics (8.4km), all weather roads (5.5km) , primary schools (3.1km) and feeder roads (1.5km) (Table 3.16). Chart 3.129 Number of Households Practicing Fish Farming - Manyara Prcticing Fish Farming, 153, 0.1% Not Prcticing Fish Farming, 154,041, 99.9% 0 30 60 90 Number of Households Mbulu Kiteto Babati Hanang Simanjiro District Chart 3.130a Number of Households Practicing Fish Farming by District - Manyara Chart 3.130 b Fish Production Number of Tilapia, 21,094, 100.0% Number of Carp, 0, 0.0% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 Only 6 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 30 percent reported them to be average. Fifteen percent of the agricultural households said the infrastructures and services were poor were, 25 percent said they were ‘no good’ and 24 percent said they were ‘good’. 3.13.2 Type of Toilets A large number of rural agricultural households used traditional pit latrines (125,839 households, 81.6% of all rural agricultural households), 1,402 households (0.9%) used improved pit latrine and 1,044 households (0.7%) used flush toilets. The remaining 358 household (0.2%) used other toilets facilities. However, 25,551 households (16.6%) in the region had no toilet facilities (Chart 3.131). The distribution of the households without toilets within the region indicates that 43.7 percent of them were found in Simanjiro district and 23.2 percent were from Kiteto. The percentages of households without toilets in other districts were as follows; Babati (18.0%), Hanang (14.5%) and Mbulu (0.6%) Map 3.51). 3.13.3 Household’s Assets The radios was an asset owned by most rural agricultural households in Manyara region with 74,560 households (48.4% of the agriculture households in the region) owning the asset, followed by bicycle ( 64,464 households, 41.8%), iron (24,366 households, 15.8%), wheelbarrow (7,312 households, 4.7%), mobile phone (1,930 households, 1.3%), vehicle (1,483 households, 1.0%), television/video (1,028 households, 0.7%) and landline phone (662 households, 0.4%) (Chart 3.132). Table 3.16: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Babati 8.2 2.0 5.0 1.2 21.6 6.0 30.9 10.5 7.6 30.7 100.2 Hanang 17.0 2.8 7.2 1.3 25.8 12.5 35.6 9.2 9.9 31.1 112.5 Mbulu 10.2 4.3 5.0 1.1 28.0 6.7 44.9 5.8 12.9 17.3 92.4 Simanjiro 65.2 5.2 5.8 1.7 81.9 10.6 108.9 23.7 26.2 93.0 84.5 Kiteto 39.8 2.5 4.6 2.6 56.3 8.9 55.7 10.1 12.9 45.7 114.9 Total 21.7 3.1 5.5 1.5 36.1 8.4 47.4 10.5 12.1 36.9 101.7 Chart 3.131 Agricultural Households by Type of Toilet Facility Improved Pit Latrine - hh Owned, 1,402, 0.9% No Toilet / Bush, 25,551, 16.6% Flush Toilet, 1,044, 0.7% Other Type, 358, 0.2% Traditional Pit Latrine, 125,839, 81.6% Chart 3.132 Percentage Distribution of Households Owning the Assets 4.7 1.3 0.7 1.0 0.4 48.4 41.8 15.8 0.0 15.0 30.0 45.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Babati Simanjiro Kiteto Mbulu Hanang 356ha 296ha 2,327ha 551ha 176ha 1.1% 0.7% 4% 0.5% 0.4% 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Babati Hanang Mbulu Kiteto Simanjiro 13,764ha 5,204ha 4,880ha 23,035ha 25,346ha 7% 15.2% 23.5% 40.4% 65.1% 20,000 to 26,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Tanzania Agriculture Sample Census MAP 3.49 MANYARA MAP 3.50 MANYARA Planted Area With Farm Yard Manure Applied Planted Area With Farm Yard Manure Applied Planted Area With Compost Manure Applied Planted Area With Compost Applied Percent of Planted Area With Farm Yard Manure Applied Percent of Planted Area With Compost Manure Applied Planted Area and Percent of Planted Area With Farm Yard Manure Application by District Planted Area and Percent of Planted Area With Compost Manure Application by District RESULTS 81 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region with 72.8 percent of the total rural households using this source of energy, followed by hurricane lamp (17.5%), firewood (4.9%), pressure lamp (3.4%), mains electricity (0.7%), solar (0.1%), candle (0.0%) and other (0.6%) (Chart 3.133). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.7 percent of all rural agricultural households in Manyara region. This was followed by charcoal (2.5%). The rest of energy sources accounted for 0.79 percent. These were bottled gas (0.13%), crop residues (0.30%), mains electricity (0.28%), livestock dung (0.07%), (Chart 3.134). 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling in Manyara region was grass/leaves which was used by 45.6 percent of the rural agricultural households in the region. This was followed by iron sheets (32.0%), grass/mud (21.7%), tiles (0.7%) and concrete (0.1%) (Chart 3.135). Babati district had the highest percentage of households with grass/leaves roofing (41%), followed by Mbulu district (25%), Hanang (15%), Simanjiro (12%) and Kiteto (1%). Babati also had the highest percentage of households with iron sheet roofing (34%), followed by Kiteto district (31%), Hanang (15%), Mbulu (10%) and Simanjiro (9%) (Chart 3.136 and Map 3.52). Chart 3.133 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 112,237 , 72.8% Hurricane Lamp, 26,999, 17.5% Firewood, 7,522, 4.9% Mains Electricity, 1,025 , 0.7% Pressure Lamp, 5,271, 3.4% Other, 925, 0.6% Candles, 69, 0.0% Solar, 146, 0.1% Chart 3.134 Percentage Distribution of Households by Main Source of Energy for Cooking Livestock Dung, 111, 0.1% Mains Electricity, 436, 0.3% Bottled Gas, 195, 0.1% Crop Residues, 469, 0.3% Charcoal, 3,907, 2.5% Firewood, 149,076, 96.7% Chart 3.136 Percentage Distribution of Households with Grass/Leafy and Iron Sheet Roofs by District 41 25 15 12 6 0.0 15.0 30.0 45.0 Babati Mbulu Hanang Simanjiro Kiteto District Percent Chart 3.135 Percentage Distribution of Households by Type of Roofing Material Tiles, 1,076, 0.7% Grass/Leaves, 70,237, 45.6% Iron Sheets, 49,266, 32.0% Grass / Mud, 33,412, 21.7% Concrete, 204, 0.1% Babati Mbulu Hanang Kiteto Simanjiro 4,608 11,156 3,714 156 5,917 0.5% 23.1% 11.9% 9.9% 68.2% 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Hanang Mbulu 0 84 69 0 0 0% 0% 0% 0% 0% Simanjiro Kiteto Babati 80 to 90 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census MAP 3.51 MANYARA MAP 3.52 MANYARA Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Number of Households Without Toilets Number of Households Without Toilets Percent of Households Practicing Fish Farming Percent of Households Without Toilets Number and Percent of Households Practicing Fish Farming by District Number and Percent of Households Without Toilets by District RESULTS 83 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Manyara region was piped water (24 percent of households use piped water during the wet season and 26 percent of the households during the dry seasons). This was followed by unprotected wells (19% of households during wet season and 23% during the dry season), surface water (22% of households during the wet season and 19% in the dry season), protected wells (15% of households in the wet season and 16% during dry season) and unprotected spring with 11 percent of households using the source for each seasons. Uncovered rain water was used as a main source by 6 percent of the agricultural households in the wet season and by 1 percent in the dry season and protected springs were used by 2 percent of the agricultural households during each season. Chart 3.137). About 38 percent of the rural agricultural households in Manyara region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 62 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.138). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Manyara region normally had 3 meals per day (59.7 percent of the households in the region). This was followed by 2 meals per day (38.7 percent) and 1 meal per day (1.1 percent). Only 0.5 percent of the households have 4 meals per day (Chart 3.139). Simanjiro district had the largest percent of households eating one meal per day whilst Mbulu had the highest percent of households eating 3 meals per day (Table 3.17 and Map 3.53). Chart 3.17: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Babati 604 1.3 15,580 33.4 30,356 65.1 94 0.2 46,635 Hanang 523 1.7 13,345 42.7 17,377 55.6 0 0.0 31,245 Mbulu 160 0.5 7826 22.8 26,395 76.8 0 0.0 34,381 Simanjiro 309 1.9 10,240 62.6 5,128 31.3 688 4.2 16,364 Kiteto 66 0.3 12,727 49.8 12,776 50.0 0 0.0 25,569 Total 1,662 1.1 59,718 38.7 92,032 59.7 782 0.5 154,194 Chart 3.137 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 Piped Water Surface Water Uprotected Well Protected Well Unprotected Spring Uncovered Rainwater Catchment Protected Spring Other Main Source P ercen t o f H o u s eh o ld s Wet Season Dry Season Chart 3.138 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99km 2 - 2.99km 3 - 4.99km 5 - 9.99km 10km or More Distance Percent Wet Dry DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 95,752 (62.1% of the agricultural households in Manyara region) with 55,685 households (58.2 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (27.6%). Very few households had meat three or more times during the respective week. About 37.9 percent of the agricultural households in Manyara region did not eat meat during the week preceding the census (Chart 3.140 and Map 3.54). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 72,509 (47% of the total agricultural households in Manyara region) with 33,246 households (45.9 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish twice (26.9%). In general, the percentage of households that consumed fish three times or more during the week in Manyara region was 19,734 (27.2%) of the agricultural households that ate fish in the region during the respective period). About 53 percent of the agricultural households in Manyara region did not eat fish during the week preceding the census (Chart 3.140 and Map 3.55). 3.13.9 Food Security In Manyara region, about 37 percent of the agricultural households (57,229 households) said they did not experience any food sufficiency problems, 56,362 households (36.6% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement, whilst 7,343 households (4.8%) said they sometimes experience problems. However, 14.4 percent of the agricultural households in the region (22,138 households) often experienced problems in satisfying the household food requirement and 7.2 percent (11,123 households) said they always had problems (Chart 3.140a). Chart ..... Number of Households by Level of Food Availability Seldom, 56,362, 37% Sometimes, 7,343, 5% Often, 22,138, 14% Always, 11,123, 7% Never, 57,229, 37% Chart 3.140 Number of Households by Frequency of Meat and Fish Cosumption 0 20000 40000 60000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Kiteto Babati Mbulu Hanang 26,395 12,776 30,356 5,128 17,377 76.8% 50% 65.1% 55.6% 31.3% Simanjiro 24,000 to 31,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Kiteto Simanjiro Babati Mbulu Hanang 12,713 10,978 5,787 576 3,357 31.9% 40.7% 22.6% 1.2% 20.5% 12,000 to 13,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanzania Agriculture Sample Census MAP 3.53 MANYARA MAP 3.54 MANYARA Number of Households Using Grass/Leaves for Roofing Material Number of Households Using Grass/Leaves for Roofing Material Number of Households Eating 3 Meals Per Day Number of Households Eating 3 Meals Per Day Percent of Households Using Grass/Leaves for Roofing Material Percent of Households Eating 3 Meals Per Day Number and Percent of Households Using Grass/Leaves for Roofing Material by District Number and Percent of Households Eating 3 Meals Per Day by District RESULTS 86 Mbulu Simanjiro Kiteto Babati Hanang 6,209 2,358 4,680 14,138 5,861 18.1% 14.4% 18.8% 30.3% 18.3% 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Babati Mbulu Hanang Simanjiro Kiteto 7,018 21,047 5,320 9,504 12,796 37.2% 27.4% 30.4% 45.1% 32.5% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tanzania Agriculture Sample Census MAP 3.55 MANYARA MAP 3.56 MANYARA Number of Households Eating Meat Once Per Week Number of Households Eating Meat Once Per Week Number of Households Eating Fish Once per Week Number of Households Eating Fish Once Per Week Percent of Households Eating Meat Once Per Week Percent of Households Eating Fish Once Per Week Number and Percent of Households Eating Meat Once Per Week by District Number and Percent of Households Eating Fish Once Per Week by District RESULTS 87 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 Simanjiro district has the highest percent of households that have problems in satisfying their household food requirements (36.6 percent of the agricultural households always or often having food problems). The percentage of households with food problems is also higher in Mbulu and Hanang districts (Chart 3.140b and Map 3.56). 3.13.10 Main Sources of Cash Income The main cash income for the households in Manyara region was from selling food crops (35.2 percent of smallholder households), followed by sales of livestock (17.4%), other casual earnings (15.0%), businesses (9.2%), cash crops (8.4%), forest products (6.3%), wages and salaries (2.8%), remittance (1.9%) and livestock products (1.6%). Only 0.2% of smallholder households reported fishing as their main source of income, followed by other activities (2%) (Chart 3.141). Chart 3.141: Percentage Distribution of the Number of Households by Main Source of Income Not applicable, 42, 0.0% Food Crops, 54,336, 35.2% Cash Crops, 12,917, 8.4% Other Casual Cash Earnings, 23,070, 15.0% Business Income, 14,214, 9.2% Remittance, 3,000, 1.9% Wages & Salaries, 4,381, 2.8% Livestock Products, 2,417, 1.6% Forest Products, 9,718, 6.3% Fishing, 239, 0.2% Other, 3,085, 2.0% Livestock, 26,775, 17.4% Chart ... Percent of Households Reporting Food Availability Status by District 0% 25% 50% 75% 100% Babati Kiteto Hanang Mbulu Simanjiro District Percent of Households Never Seldom Sometimes Often Always Simanjiro Mbulu Hanang Babati Kiteto 12,547 11,765 20,349 26,581 25,724 74.8% 49.1% 65.1% 57% 71.9% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tanzania Agriculture Sample Census MAP 3.57 MANYARA Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency Number and percent of Households Reporting Food Insufficiency by District RESULTS 89 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 MANYARA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Manyara Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. 4.2 District Profiles Thee following district profiles highlight the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Babati Babati district had the largest number of agricultural households in the region and it had one of the highest percent of households involved in smallholder agriculture in the region. It was the second highest district with smallholders involved in crop farming only and the third with smallholders involved in crop and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Babati district was annual crop farming, followed by off farm income and livestock keeping/herding. However, the district had the least percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Babati had a relatively high percent of female headed households (38%) and it had the second highest average age of the household head. Its average household size of 5 members per household was lower than the average for the region. Babati has the highest literacy rate for agricultural household members (73%) and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household was also the highest in the region. It has the smallest utilized land area per household (2 ha) and the allocated area is not fully utilised indicating a low level of land pressure. The total planted area is the second greatest in the region due to the presence of good wet and dry seasons, however it has medium planted area per household as compared to other districts. The district was the second important for maize production in the region with a planted area of 35,491 ha; however the planted area per household was the second lowest in the region. Paddy production was very important with a planted area of 1,817 hectares and the production of sorghum was the highest in the region. Babati had the highest wheat production (990 ha) among the three districts that grew the crop. Cassava production was the highest and accounted for 34 percent of the quantity harvested in the region. The district had the least planted area of Irish potatoes (5 ha) and it was among the two districts in the region that grew this crop. The production of beans in Babati was much higher than in other districts in the region with a planted area of 9,726 ha. Oilseed crops are important in Babati and the second highest with groundnuts in the region. Vegetable production was important in the district. It had the largest area planted with tomatoes (489 ha) accounted for 100 percent of the tomato production. Tobacco was the only traditional cash crop grown in the district (30 ha) and in the region. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 Compared to other districts in the region, Babati has a moderate planted area with permanent crops which were dominated by pigeon peas (19,096 ha), banana (4,393 ha) and coffee (1,041 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Babati had the second largest area planted with improved seed in Manyara region and this was due to the high planted area of vegetables. The district had the second largest area planted with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Babati district had the second highest level of insecticide use. The use of fungicides was also the second highest in the region. Also the district had the second highest use of herbicide in the region. It had the largest irrigated area (2,928) ha. The most common source of water for irrigation was from rivers using gravity. Flood and bucket were the most common means of water application. The most common method of crop storage was the locally made traditional crib. The proportion of households storing crops in the district was higher than in other districts in the region. The district had the largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. The second highest percent of households processing crops in Manyara region was found in Babati district, most of the processing was done by neighbours machine. The district had the third highest percent of households selling processed crops to neighbours in the region and no sales were made to traders on farm. Although very small, access to credit in the district was to women headed households and the main sources of credits were unspecified. A comparatively large number of households received extension services in Babati and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Babati (with 206,885 planted trees) and most of the trees were Gravellis with some Albizia and Senna species. The highest proportion of households with erosion control and water harvesting structures was found in Babati district and was most of these were erosion control bunds, however it also had high number of vetiver grass strips, water harvesting bunds and tree belts than other districts. The district had the largest number of cattle in the region and most of them were indigenous. Goat production was the second largest in the region; however it was the second least district with population of sheep in the region. It had the second largest number of pigs in the region and the largest number of chickens. The district had no layers. The district had high numbers of ducks, moderate number of donkeys and small number of rabbits. It had second largest number of households that reported Tsetse and tick problems and it had the third largest number of households de-worming livestock. The use of draft animals in the district was high while fish farming was not practiced. It had amongst the best access to primary schools and feeder roads compared to other districts. However, it had one of the worst access to primary markets and tarmac roads. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 Babati district had the second least percent of households without toilet facilities and it had the second highest percent of households owning bicycles, vehicles, mobile phones and was the third in regard to tv/video. It had the second smallest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the smallest percent of households with grass roofs and 36 percent of households had iron sheet roofs. The most common source of drinking water was from piped water. It had the highest percent of households having three and two meals per day and the lowest percent having 1 meal per day. The district had the lowest percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.2 Hanang Hanang district had the third largest number of agricultural households in the region and it had the highest percentage of households involved in smallholder agriculture. Most smallholders were involved in crop and livestock production, followed by livestock keeping/herding. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Hanang district was annual crop farming, followed by livestock keeping/herding. The district had the highest percent of households with no off-farm activities although it had the least percent of households with more than one member with off-farm income. Compared to other districts in the region, Hanang had a relatively low percent of female headed households (15%) and it had one of the highest average age of the household head in the region. Its household size of 6 members per household was average for the region. Hanang had a comparatively high literacy rate for agricultural household members and this was reflected by the district having the highest level of school attendance in the region. It has a moderate utilized land area per household (4ha) and 98 percent of the allocated area is currently being utilised. The district has the second largest planted area in the region, and the third largest planted area per household (0.9ha in the long rainy season and 0.6ha in the short rainy season). The district was moderately important for maize production in the region with a planted area of 35,232 ha, and the planted area per maize growing household was also moderate for the region. Paddy was not grown in the district. The district had the third largest area planted with sorghum in the region with 1,179 hectares. Though small, cassava production is the highest in the region with a planted area of 316 hectares. Irish potatoes are not grown in the district. The production of beans in Hanang, district was the highest in the region with a planted area of 12,945ha. Hanang district has the third largest groundnut planted area in Manyara region with a planted area per groundnut growing household of 0.3 ha. Vegetable production was moderately important in the district. Although small, it had the third largest planted area with tomatoes (15 ha). Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Hanang had the third largest planted area with permanent crops which were dominated by pigeon peas (31,391 ha), bananas (156 ha), oranges (130 ha) and guava (156 ha). Other permanent crops were either not grown or were grown in very small quantities. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 As with most districts in the region, most land clearing and preparation was done by oxen, with the highest amount of land preparation in Hanang district being done by oxen. The use of inputs in the region was very small, however district differences existed. Hanang had the third largest area planted with improved seeds in the region and had the least proportion of households using improved seeds. The district had the third largest planted area with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of these were farm yard manure. Compared to other districts in the region, Hanang district had the highest level of insecticide use. The use of fungicides, although small, was the highest compared to other districts. Application of herbicides was high. It had the second least irrigated area (709 ha). The most common source of water for irrigation was from canals using gravity. Flood was the major means of water application. The most common method of crop storage in Hanang district was the locally made traditional crib. The proportion of households storing crops in the district was relatively high. Hanang district was one of the districts with a moderate number of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. Hanang was among the districts with the highest percent of households processing crops in Manyara region and most of the processing was done by neighbours machine. The district was the only one with households selling processed crops to marketing cooperatives and no sales were made to farmers associations, secondary markets or large scale farms. Although very small, access to credit in the district was to men headed households and the main sources were “family, friends and relatives”. A comparatively small number of households received extension services in Hanang district and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not important in Hanang (with 1,227 planted trees) and most of the trees were Gravellis and Senna species. The third highest proportion of households with erosion control and water harvesting structures was found in Hanang district and was most of these were erosion control bunds and water harvesting bunds, however it also had a number of drainage ditches and vetiver grass. The district had the second largest number of cattle in the region and almost all of them were indigenous. Goat production was moderate compared to other districts; however it had the third largest population of sheep in the region. It had the third largest number of pigs in the region and a large number of chickens. Some ducks, many donkeys but no rabbits were found in the district. A few households reported tsetse fly problems and many reported tick problems in Hanang district and it had the second least number of households de-worming livestock. The district had the second largest number of households using draft animals in the region. Fish farming was not practiced in the district. It has amongst the poorest access to secondary schools, hospitals, district capital and tertiary market compared to other districts. It also had one of the worst access to tarmac road. The percentage of households without toilet facility in Hanang district was 14.5 percent and was among the districts with the highest percent of households owning wheel barrows. Also, the district had the lowest percentage of households with vehicles, bicycles, tv/video and mobile phones. It had the second largest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 94 firewood for cooking. The roofing material for most of the households in the district was grass/leaves (40.7%) and iron sheets (24%). The most common source of drinking water was from piped water. It was one of the districts with the second highest percent of households having two meals per day. The district had the second highest percent of households that did not eat meat and the second least district that did not eat fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.3 Mbulu Mbulu district had the least number of agricultural households in the region and it had one of the second highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock production, followed by crop only, livestock only production and pastoralists. The most important livelihood activity for smallholder households in Mbulu district was annual crop farming, followed by livestock keeping/herding. However, the district has the second highest percent of households with off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mbulu had the least percent of female headed households (12%) and it had one of the highest average age of the household head in the region. Its average household size of 6 members per household was average for the region. Mbulu has the second highest literacy rate for agricultural household members and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household was also slightly higher than most of districts in the region. It has a slightly higher utilized land area per household (8.4ha) than the regional average of 7.6 ha and 98 percent of the allocated area is currently being utilised. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the least planted area per household (0.5ha) attributed to the high number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 22,818 ha, however the planted area per household was 0.7 ha which was the least in the region. Paddy was not grown in the district. The district had the second highest production of sorghum (1,423 ha). Irish potatoes were produced in small quantities while production of wheat was the least in the region. The district had the least planted area of cassava accounting for 10 percent of the cassava planted area in the region. The production of beans in Mbulu was the second highest in the region with a planted area of 12,764 ha. Oilseed crops were not important in Mbulu with mainly sunflower grown (799 ha) accounting for 12 percent of the total planted area in the region. Vegetable production was not important in the district. Traditional crops (tobacco and cotton) were not grown in the district. Permanent crops were not important in Mbulu district (1.3% of the total permanent crop planted area in Manyara region was found in the district). The most prominent permanent crops in the district included bananas (239 ha) and coffee (144 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand and large land preparation was done by oxen. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 95 The use of inputs in the region was very small, however district differences existed. Mbulu had the smallest area planted with improved seeds in Manyara region and this was due to the dominance of permanent crops which do not need frequent planting. The district had the largest area planted with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of these were farm yard manure. Compared to other districts in the region, Mbulu district had the smallest area applied with herbicides and fungicides. The use of pesticides was relatively moderate. It had the second largest irrigated area (1,401 ha). The most common source of water for irrigation was from rivers using hand bucket. Bucket/watering cans was the most common means of water application and a very small amount of flood irrigation was also used. The most common method of crop storage in Mbulu was the locally made traditional crib, however the proportion of households storing crops in the district was the third highest in the region. The district had the second least percent of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. Mbulu district had the highest percent of households processing crops in the region and most of the processing was done to neighbours machine. However, the district had the highest percent of households processing crops by trader. The district had the lowest percent of households selling processed crops. No agricultural household accessed credit in the district. A comparatively smaller number of households received extension services in Mbulu district and most of the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Mbulu district (with 94,189 planted trees) and most of these were Gravellis with some Eucalyptus species. The second highest proportion of households with water harvesting bunds was found in Mbulu district and it also had the second largest number of erosion control bunds. The district had a moderate number of cattle in the region and most of these were indigenous. Goat and sheep production was moderate compared to other districts. It had the largest number of pigs in the region and the second largest number of chickens, all of which are indigenous. Virtually all layers were found in the district. The district had small number of ducks, however it had no rabbits and a large number of turkeys. A number of households reported tsetse fly and tick problems. The district had the second largest number of household de-worming livestock in Mbulu. The use of draft animals in the district was high with (63%) of household using draft animals. A small number of households’ practiced fish farming, however the district was the only one practicing fish farming in the region. It had amongst the best access to feeder roads, primary schools, and all weather roads compared to other districts. However, it had one of the worst accesses to tarmac roads, district capital and hospitals. Mbulu district had the lowest percent of households with no toilet facilities and it had no households owning landline and small percentage of households had with vehicles, wheel barrows, Tv/video and mobile phones. The use of mains electricity in the district was nonexistence. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a low percent of households with grass roofs (31.9%) with 15 percent of households having iron sheets. The most common source of drinking water was the unprotected well. Twenty two point eight percent of the households in the district reported having two meals per day and DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 virtually no household reported having more than four meals per day with majority of households (76.8%) having three meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration; however few households seldom had problems with food satisfaction. 4.2.4 Simanjiro Simanjiro district had the second least number of households in the region and it had the least percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. It had a very small number of livestock only and pastoralists in the district. The most important livelihood activity for smallholder households in Simanjiro district was annual crop farming, followed by livestock keeping/herding and off farm income. However, the district had the second lowest percent of households with off-farm activities and also, the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Simanjiro had a relatively high percent of female headed households (23%) and it had one of the lowest average age of the household head. Its average household size of 5 members per household was average for the region. Simanjiro has a comparatively low literacy rate for agricultural household members and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was also slightly low than most of districts in the region. It has the smallest utilized land area per household (0.8ha) and the allocated area is fully utilised indicating a high level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (1.2ha) attributed to the high number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 23,831 ha, however the planted area per household was the second highest in the region. Paddy production was not important with a planted area of only 213 hectares and the production of sorghum was very small. Simanjiro was among the districts that did not produce wheat , Irish potatoes or cassava. The production of beans in Simanjiro was moderate compared to other districts in the region with a planted area of 8,127 hectares. Oilseed crops were not important in Simanjiro and very small quantities of simsim and groundnuts were grown in the district. Vegetable production was important in the district. It had the largest area planted with tomatoes (62 ha) and onions (178 ha) in the region and accounted for 35 percent of the tomato production, 70 percent of the onion production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Simanjiro had the area smallest area planted with permanent crops which were dominated by bananas (125 ha), guava (31 ha) and pigeon peas (21 ha). Other permanent crops were either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Simanjiro had the largest area planted with improved seeds in Manyara region. The district had the smallesr area planted with the application of fertilizers (farm DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 yard manure, compost and inorganic fertiliser), however most were farm yard manure. Compared to other districts in the region, Simanjiro district had low level of insecticides use. The use of fungicides and herbicides were low compared to other districts. It had the the third largest irrigated area in the region (1,356 ha). The most common source of water for irrigation was from rivers using gravity. Flood was the most common means of water application. The most common method of crop storage was the locally made traditional crib; however the proportion of households not storing crops was the highest in the region. The district had the lowest number of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. The least percent of households processing crops in Manyara region was found in Simanjiro district and most of the processing was done by neighbours machine. The district had a high percent of households selling processed crops to neighbours and no sales were made to traders on farm. Although very small, access to credit in the district was to both men and women headed households and the main sources of credit were family, friends and relatives. A comparatively large number of households received extension services in Simanjiro and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Simanjiro (with 541 planted trees) and most of these were Azadritachta species with some Senna species and Leucena. The lowest proportion of households with erosion control and water harvesting structures was found in Simanjiro district and most of these were erosion control bunds; however it also has high number of tree belts, water harvesting bunds and drainage ditches. The district has the third largest number of cattle in the region and most of them were indigenous. Goat and sheep production were the largest in the region with a total number of 317,648 goats and 143,162 sheep; It had the smallest number of pigs and chicken in the region. Although small, the district had the second largest number of broilers in the region. The district had a moderate number of ducks, rabbits and the largest number of donkeys. The largest number of households reporting Tsetse fly and tick problems was in Simanjiro and it had the largest number of households de- worming livestock. The use of draft animals in the district was very small and fish farming was practiced It was amongst the districts with the best access to feeder roads, primary schools and all weather roads compared to other districts. However, it had one of the worst accesses to district capital, tertiary market and tarmac roads. Simanjiro district had the highest percent of households with no toilet facilities and it had the lowest percent of households owning pressing iron, vehicles, tv/video, land line and mobile phones. It had the second lowest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the second smallest percent of households with grass roofs, with 27 percent of households having iron sheets. The most common source of drinking water was from surface water. It had the highest percent of households having two meals per day c and the lowest percent with 3 meals per day. The district had the second lowest percent of households that did not eat meat and was the second highest percent of household that did not eat fish during the week prior to enumeration, however very few households seldom had problems with food satisfaction. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 4.2.5 Kiteto Kiteto district had the second largest number of agricultural households in the region and it had a high percentage of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock production, followed by crop only. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kiteto district was annual crop farming, followed by off farm Income. The district has the third highest percent of households with no off-farm activities and it has the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kiteto had a relatively high percent of female headed households (25%) and it had one of the highest average age of the household head in the region. Its an average household size of 5 members per household was below the average for the region. Kiteto has a comparatively low literacy rate among smallholder households. The literacy rate for the heads of household was the second least in the region. It has a moderate utilized land area per household (10ha) and 91 percent of the allocated area is currently being utilised. The district has the largest planted area in the region, and the third largest planted area per household (2.3ha). The district was important for maize production in the region with a planted area of over 69,186 ha, and the planted area per household was the highest in the region. The district had no area planted with paddy. Sorghum was grown in small quantities. Cassava production was moderatily high, accounting for 30 percent of the quantity harvested in the region. The district had no planted area for Irish potatoes. The production of beans in Kiteto was the least in the region with a planted area of 2,092 ha. Kiteto district had the largest area planted with groundnuts in Manyara region with the area planted per groundnut growing household of 0.45 ha. Vegetable production was not important in the district and traditional cash crops (e.g. tobacco and cotton) were not grown Compared to other districts in the region, Kiteto had the second largest planted area of permanent crops which were dominated by pigeon peas (6,226 ha), bananas (35 ha) and Mpesheni (24 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was done by oxen. The use of inputs in the region was very small, however district differences existed. Kiteto had the largest area planted with improved seeds in the region as well as the lowest proportion of households using improved seeds. The district had the smallest area planted with the application of fertilizers (farm yard manure, compost and inorganic fertilisers), however most of these were farm yard manure. Compared to other districts in the region, Kiteto district had a moderate level of insecticides use. The use of fungicides in the district was very low. Application of herbicides was moderate. It had the smallest irrigated area (662 ha). The most common source of water for irrigation was from pipe water using hand bucket. Bucket/watering can were the most common means of water application. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 The most common method of crop storage in Kiteto district was the sacks/open drum, however the proportion of households not storing crops in the district was relatively low compared to other districts in the region. Kiteto district was one of the districts with a moderate number of households selling crops, however those that did not sell, the main reason for not selling was insufficient production. Kiteto was among the districts with high percent of households processing crops in Manyara region and most of the processing was done by neighbours machine. The district had no access to credit facilities. A comparatively moderate number of households received extension services in Kiteto district and all of it was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Kiteto (with 9,089 planted trees) and most of these were Senna species and Leucena species. The least proportion of households with erosion control and water harvesting structures were found in Kiteto district and most of these were erosion control bunds and tree belts, however it also had the a number of drainage ditches. The district had the smallest number of cattle, goats and sheep in the region and most of those were indigenous. It had the second smallest number of pigs in the region and a second smallest number of chickens. It had the largest number of ducks, rabbits and a moderate number of donkeys but a large number of turkeys. A number of households reported tsetse fly and tick problems and it had the least number of households de-worming livestock. The district had the least number of households using draft animals in the region. A very small number of households practiced fish farming. It had amongst the best access to primary schools and feeder roads compared to other districts. However, it had one of the worst accesses to tarmac road. The percentages of households without toilet facility in Kiteto district was 23.1 percent and it was among the districts with the lowest percent of households owning pressing iron, vehicles, bicycles, tv/video and mobile phones. It had the third largest number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing material for most of the households in the district was iron sheets (60%) and asbestos (22.6%). The most common source of drinking water was from unprotected wells. It is one of the districts with moderate percent of households having two and three meals per day. The district had moderate percent of households that did not eat meat and high percent of household that did not eat fish during the week prior to enumeration, however small number of households seldom had problems with food satisfaction. APPENDIX II 100 4. APPENDICES Appendix I Tabulation List.............................................................................................................. 101 Appendix II Tables............................................................................................................................. 119 Appendix III Questionnaires .............................................................................................................. 264 APPENDIX II 101 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD ..................................................................................119 2.1 Number of Agriculture households by type of household and District during 2002/03 Agriculture Year .....................................................................................................................120 2.2 Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year ....................................................................................................................120 NUMBER OF AGRICULTURE HOUSEHOLDS .........................................................................121 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .................................................122 RANK OF IMPORTANCE OFLIVELIHOOD ACTIVITIES .....................................................123 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District ............................................................................................................124 3.1a First Most Importance.............................................................................................................124 3.1b Second Most Importance ........................................................................................................124 3.1c Third Most Importance ...........................................................................................................124 3.1d Fourth Most Importance .........................................................................................................124 3.1e Fifth Most Importance ............................................................................................................125 3.1f Sixth Most Importance............................................................................................................125 3.1g Seventh Most Importance .......................................................................................................125 HOUSEHOLDS DEMOGRAPHS....................................................................................................127 3.2 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year ....................................................................................................................128 3.3 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year ....................................................................................................................128 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year ....................................................................................................................129 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year ...........................129 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year .......................................................................................130 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ....................................................................................................................130 APPENDIX II 102 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year .................................................................131 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year .................................................................................131 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year ...............................................................132 3.11 Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year............132 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year...................................................................133 3.13 Mean, Meadian, Mode of Age of Head of Agricultural Household and District....................133 3.14 Literacy Rate of Heads of Households by Sex and District....................................................133 3.15 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year.........................................................................133 LAND ACCESS/OWNERSHIP........................................................................................................135 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year ......................................................................................................136 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year ....................................................................................................................136 LAND USE .........................................................................................................................................137 5.1 Area of Land by type of Land Use and District during 2002/03 Agricultural Year ...............138 5.2 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year ....................................................................................................................138 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year ................................................................139 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year .........................................................139 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year ..............................................139 COMMUNIAL RESOURCES..........................................................................................................141 6.1 Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year...................142 APPENDIX II 103 6.2 Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year ...............................................................143 6.3 Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year ...............................................................143 6.4 Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year ...............................................................144 6.5 Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year ...............................................................144 6.6 Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year ...............................................................145 6.7 Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year ...............................................................145 6.8 Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year ...............................................................146 6.9 Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year ...............................................................146 6.10 Number of Agricultural Households with Access to Fishing Resouces by type of Utilization and District, 2002/03 Agricultural Year ...............................................................147 TOTAL ANNUAL CROP AND VEGE PRODUCTION – LONG AND SHORT RAINY SEASON ................................................................................................................................149 7.1 & 7.2a Number of Households and Planted Area By District-SHORT RAINY SEASON..........150 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District - SHORT RAINY SEASON................................................................................................150 7.1 & 7.2c TOTAL Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Manyara Region.....................................................................151 7.1 & 7.2d TOTAL Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Manyara Region.....................................................................152 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON..................153 7.1 1& 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Manyara Region .............153 7.1 & 7.2g Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON ............................................153 7.1 & 7.2h Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON.....................................................154 7.1 & 7.2i Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON .........................................................154 APPENDIX II 104 7.1 & 7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON .........................................................154 7.1& 7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON ....................................154 ANNUAL CROP AND VEGE PRODUCTION - SHORT RAINY SEASON ................................................................................................................155 7.1a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON..................156 7.1b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON.........................................................156 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON .........................................................156 7.1d Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON.....................................................157 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON ............................................157 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON ............................................157 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON...........................................157 ANNUAL CROP AND VEGE PRODUCTION- LONG RAINY SEASON.................................159 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON....................160 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON...........................................................160 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON ...........................................................160 7.2d Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON ...................................................................160 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON ...........................................................161 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District.................................................................................................................161 7.2g Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON ...........................................................161 APPENDIX II 105 7.2h Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON.............................................161 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year......................................................162 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................162 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................162 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................162 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................163 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................163 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................163 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................163 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................164 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................164 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................164 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................164 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................165 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................165 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................165 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................165 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................166 APPENDIX II 106 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................166 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................166 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................166 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................167 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................167 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................167 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................167 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................168 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year...................168 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................168 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................168 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................169 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................169 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................169 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................169 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................170 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................170 APPENDIX II 107 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................170 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................170 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................171 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................171 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year.................................... 171 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year.....................................171 PERMANENT CROPS .....................................................................................................................173 7.3 Number of households by Area planted (ha), Area harvested (ha) and Quantity harvested (tons).......................................................................................................................174 AGROPROCESSING........................................................................................................................179 8.0a Did tthe Household Process any Of the Products Harvested ..................................................180 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District..............180 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop ...........................180 8.1.1c Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District..................................................................................................181 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District..................................................................................................181 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District .......................................................................181 8.1.1f Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop .......................182 8.1.1g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District.....................................................................................................................182 STORAGE..........................................................................................................................................183 9.2a Number of Households Storing Crops By Method of Storage and District............................184 9.2b Number of Households Storing Crops By Duration of Storage and District..........................184 APPENDIX II 108 9.2c Number of Households Storing Crops By Main Purpose of Storage and District..................184 9.2d Number of Households Storing Crops By Estimated Storage Loss and District....................184 9.2 Number of Households Storing Crops By Method of Storage and Crop Type ......................185 MARKETING....................................................................................................................................187 10. Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District.................................................................................................................188 10.2 Number of Households Reporting Selling Crop By Main Marketing Problem By District ...188 10.3 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District..............................................188 IRRIGATION/ EROSION CONTROL...........................................................................................189 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District ........................................................190 11.2: Area of Irrigated and Non Irriga (ha) Land By District..........................................................190 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District..................................................................................................190 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District ....................................................................................................................................190 11.5: Number of Households Using Irrigation By Method of Irrigation Application By District...191 11.5: Number of Households Using Irrigation By Method of Irrigation Application By District...191 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District ....................................................................................................................................191 11.7 Number of Erosion Control Harvesting Structures By Type and District ..............................191 ACCESS TO FARM INPUTS/ IMPLEMENTS.............................................................................193 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year ....................................................................................................................194 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year ....................................................................................................................194 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ....................................................................................................................194 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year ....................................................................................................................194 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year ....................................................................................................................195 APPENDIX II 109 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ....................................................................................................................195 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................195 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................195 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................196 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................196 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year ....................................................................................................................196 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year ....................................................................................................................197 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year....................................................................197 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year......................................................................197 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year......................................................................198 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/ Fungicides by District, 2002/03 Agricultural Year.................................................................198 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year ........................................................................................198 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................198 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year ..................................................199 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year......................................................................199 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year..................................................199 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year................................................199 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year.................................................................200 APPENDIX II 110 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year ........................................................201 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................201 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year......................................................................200 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year......................................................................201 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/F ungicides by District, 2002/03 Agricultural Year...................................................................201 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ........................................................................................201 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ...................................................................................201 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ......................................................................................................202 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ......................................................................................................202 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ......................................................................................................202 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year ......................................................................................................202 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year ....................................................................................................................203 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ....................................................................................................................203 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................203 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................203 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................204 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................204 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year ......................................................................................................204 APPENDIX II 111 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ....................................................................................................................204 AGRICULTURE CREDIT...............................................................................................................205 13.2a Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District..................................................................................................206 13.2b Number of Households Receiving Credit By Source of Credit By District ..........................206 13.2c Number of Households Receiving Credit By Reason for Not Using Credit By District.......206 13.2d Number of Credit Facilities Received By Main Purpose of Credit and District.....................206 TREE FARMING AND AGROFORESTRY..................................................................................207 14.1 Number of Households Having Planted Trees By District.....................................................208 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District ................................................................................................208 14.3 Number of Planted Trees By Species and District..................................................................208 14.4 Main Use of Trees By District................................................................................................209 14.5 Second Use of Trees By District.............................................................................................209 14.6 Number of Households By Whether Village Have a Community Tree Planting Scheme By District .................................................................................................................209 14.7 Number of Households By Distance to Community Planted Forest (Km) By District ..........210 14.8 Number of Households Involved in Community Tree Planting Scheme By Main Use and District.............................................................................................................210 CROP EXTENTION .........................................................................................................................211 15.1 Number of Households Receiving Extension Messages By District......................................212 15.2 Number of Households By Quality of Extension Services By District ..................................212 15.3 Number of Households By Source of Extension Messages By District .................................212 15.4 Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District ..............................................................................................................213 15.5 Number of Households By Receiving and Adopting Extension Messages By Type of Message and District .................................................................................................215 ANIMAL CONTRIBUTION TO CROP PRODUCTION.............................................................217 17.1 Number of Households Using Draft Animal to Cultivate Land By District...........................218 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year...........................................................................................218 APPENDIX II 112 17.3 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year...........................................................................................219 17.4 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year...........................................................................................219 17.5 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year .......................................................................................................219 CATTLE PRODUCTION.................................................................................................................221 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year .....................................................................................................................222 18.2 Number of Cattle By Type and District as of 1st October, 2003............................................222 18.3. Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03...................................................................................223 18.4 Number of Cattle by Category and Type of Cattle as of 1st October 2003............................224 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003...............................224 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003...............................224 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003...............................225 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003...............................225 GOATS PRODUCTION ...................................................................................................................227 19.1 Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year .......................................................................................................228 19.2 Total Number of Goats by Type and District as of 2st October, 2003 ...................................228 19.3 Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003 ...................................................................228 19.4 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District 228 19.5 Number of Indigenous Goat by Category and District as of 1st October, 2003 .....................229 19.6 Number of Improved Meat Goat by Category and District as of 1st October, 2003 ..............229 19.7 Number of Improved Dairy Goat by Category and District as of 1st October, 2003 .............229 19.8 Number of Total Goat by Category and District as of 1st October, 2003 ..............................229 SHEEP PRODUCTION ....................................................................................................................231 20.1 Number of Households Rearing Sheep by District as of 1st October, 2002.0/ Agriculture Year .....................................................................................................................232 APPENDIX II 113 20.2 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 .......................232 20.3 Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03 ..............................................................233 20.4 Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year .....................234 20.5 Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year .......................................................................................................234 20.6 Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year .......................................................................................................234 20.7 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year .....................................................................................................................234 PIGS PRODUCTION........................................................................................................................235 21.1 Number of Households Raising Pig by District during 2002/03 Agriculture Year ................236 21.1 Number of Households Raising Pig by District during 2002/03 Agriculture Year ................236 21.2 Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 ...................236 21.3 Pig Offtake By Type of Pig and District.................................................................................236 LIVESTOCK PESTS AND PARASITE CONTROL.....................................................................237 22.1 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year..............................238 22.2 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03Agriculture Year by District and type of dewormed Livestock ....................238 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year..............238 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year .......................................238 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year..............239 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year............................239 OTHER LIVESTOCK...................................................................................................................241 23.1 Total Number of Other Livestock by Breed and Type ...........................................................242 23.2 Number of Households Rearing and number of Other Livestock by Type and District.........242 23.3 Number of Chicken by Type and District...............................................................................242 APPENDIX II 114 23.4 Number of households with chicken and Category of Chicken by District............................242 23.5 Number of households with chicken and Category of Chicken by Flock Size.......................242 23.6 Number of households with chicken and Category of Chicken by District...........................242 FISH FARMING................................................................................................................................243 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year ....................................................................................................................244 28.2 Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year ....................................................................................................................244 28.3 Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year ....................................................................................................................244 28.4 Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year ....................................................................................................................244 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year ..............244 LIVESTOCK EXTENSION .............................................................................................................245 29.1a Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year...................................................................246 29.1b Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year..................................................246 29.2 Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year .....................................................................246 29.3 Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year..................................................247 29.4 Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year................................................................247 29.5 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year...................................................247 29.6 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year .................................248 29.7 Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year..................248 29.8 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year...............248 29.9 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year................................................................248 APPENDIX II 115 29.10 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year......................................249 29.11 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year ......................................................................................................249 29.12 Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year ........................................................................................249 29.13 Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year...................................................................249 LABOUR USE....................................................................................................................................251 33.0: Mean distances from holders dwellings to infrustructures and services by districts ..............252 33.1 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year ......................................................................................................252 33.2 Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year ......................................................................................................252 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year ......................................................................................................252 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year ......................................................................................................252 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year ......................................................................................................253 33.6 Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year ......................................................................................................253 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year ......................................................................................................253 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year ......................................................................................................253 33.9 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year ......................................................................................................254 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year ......................................................................................................254 33.11 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year ......................................................................................................254 33.12 Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year ......................................................................................................254 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year ......................................................................................................255 APPENDIX II 116 33.14 Number of Agricultural Households by Distance to Extension Center .................................255 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year ......................................................................................................255 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year ......................................................................................................255 33.17 Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year ......................................................................................................256 33.18 Number of Agricultural Households by Distance to Livestock Development Center...........256 33.19 Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .................................................................................256 33.20 Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year .................................................................................256 33.21 Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year .................................................................................257 33.22 Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year .................................................................................257 33.23 Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ......................................................................257 33.24 Number of Agricultural Households by Satisfaction of Using Livestock Development Center ...............................................................................................................257 HOUSEHOLD FACILITIES............................................................................................................259 34.1: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ...................................................................260 34.2: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year ....................................................................................................................260 34.3: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year ....................................................................261 34.4: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year ....................................................................261 34.5: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year...................................................261 34.6: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year.........................262 34.7: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year ........262 APPENDIX II 117 34.8: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year ...................................................262 34.9: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .........................262 34-10: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .........................263 34-11: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year .............................................................263 34-12: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year.................................................263 34-13: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year..........263 34-14: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year...........264 34-15: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year.....................264 34-16: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year ......................................................................................................264 APPENDIX II 118 APPENDIX II: CROPS Type of Agriculture Household ...................................................................................................119 Number of Agriculture Households.............................................................................................121 Rank of Importance of Livelihood activities ...............................................................................123 Households Demographs .............................................................................................................127 Land access/ownership ................................................................................................................135 Land Use......................................................................................................................................137 Communial Resources .................................................................................................................141 Total annual crop & vege production - long and short rainy season ...........................................149 Annual crop and vege production - short rainy season................................................................155 Annual crop and vege production-long rainy season...................................................................159 Permanent Crops..........................................................................................................................173 Agroprocessing ............................................................................................................................179 Storage .........................................................................................................................................183 Marketing.....................................................................................................................................187 Irrigation ......................................................................................................................................189 Access to Farm Inputs/ Implements.............................................................................................193 Agriculture Credit........................................................................................................................205 Crop Extension.............................................................................................................................211 Animal Contribution to crop production......................................................................................217 Cattle Production .........................................................................................................................221 Goats Production..........................................................................................................................227 Sheep Production .........................................................................................................................231 Pig Production..............................................................................................................................235 Livestock Pests and Parasite Control...........................................................................................237 Other livestock.............................................................................................................................241 Fish Farming................................................................................................................................243 Livestock Extension.....................................................................................................................245 Labour Use...................................................................................................................................251 Household Facilities.....................................................................................................................259 Appendix II 119 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Manyara Region Appendix ii 120 Rural households involved in Agriculture % of Total rural households Rural households NOT involed in Agriculture % of Total rural households Total rural households % of Total rural households Urban households Total number of Household (from 2002 pop. Census) Number % Number % Number % Number Number Babati 46,635 93 3,778 7 50,413 84 9,557 59,970 Hanang 31,245 96 1,254 4 32,499 89 4,098 36,597 Kiteto 34,381 93 2,594 7 36,975 116 -4,993 31,982 Mbulu 16,364 95 941 5 17,305 45 21,424 38,729 Simanjiro 25,569 85 4,364 15 29,933 92 2,649 32,582 Total 154,194 92 12,931 8 167,125 84 32,735 199,860 Number % Number % Number % Number % Babati 16,609 35.6 0 0.0 330 0.7 29,697 63.7 46,635 46,305 30,026 Hanang 9,190 29.4 0 0.0 223 0.7 21,833 69.9 31,245 31,022 22,055 Kiteto 6,626 19.3 0 0.0 166 0.5 27,589 80.2 34,381 34,215 27,755 Mbulu 3,413 20.9 72 0.4 2,534 15.5 10,345 63.2 16,364 13,759 12,951 Simanjiro 18,086 70.7 69 0.3 524 2.0 6,891 26.9 25,569 24,976 7,484 Total 53,923 35.0 141 0.1 3,776 2.4 96,354 62.5 154,194 150,278 100,271 District Total Number of Households Rearing Livestock Pastoralist Agriculture, Non Agriculture and Urban Households 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agriculture households by type of household and District during 2002/03 Agriculture Year 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year District Crops Only Livestock Only Crops & Livestock Total Number of agriculture Household Total Number of Households Growing Crops Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 121 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census 2003 Mnnyara Region. Appendix ii 122 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Babati 39,159 84 5 7,476 16 4 46,635 100 5 38 Hanang 28,310 91 6 2,935 9 5 31,245 100 6 15 Mbulu 31,922 93 7 2,459 7 6 34,381 100 6 12 Simanjiro 12,679 77 5 3,685 23 5 16,364 100 5 18 Kiteto 22,199 87 5 3,370 13 4 25,569 100 5 17 Total 134,268 87 6 19,926 13 5 154,194 100 6 100 % of female headed household 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Average Household Size Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 123 RANK OF IMPORTANCE OFLIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census 2003 Mnnyara Region. Appendix ii 124 Babati 1 6 3 2 5 7 4 Hanang 1 6 2 3 5 7 4 Mbulu 1 5 2 4 6 7 3 Simanjiro 1 6 2 3 5 7 4 Kiteto 1 5 3 2 6 7 4 Total 1 6 2 3 5 7 4 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 25,675 125 3,917 13,765 1,275 115 1,176 Hanang 29,221 77 379 1,492 75 0 223 Mbulu 31,002 257 1,364 1,585 0 0 261 Simanjiro 7,076 35 7,560 1,222 89 96 117 Kiteto 17,786 0 4,435 3,241 67 0 135 Total 110,759 495 17,654 21,305 1,505 211 1,912 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 12,867 376 13,494 12,839 1,847 125 4,975 Hanang 1,816 467 19,935 4,280 710 0 2,115 Mbulu 2,714 1,128 21,598 5,969 1,023 0 1,532 Simanjiro 5,859 120 4,471 2,919 554 48 519 Kiteto 7,011 996 3,021 8,325 57 69 1,324 Total 30,268 3,086 62,519 34,330 4,192 242 10,465 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 5,512 1,262 9,275 7,075 2,274 0 13,891 Hanang 142 317 2,306 5,215 473 66 4,877 Mbulu 329 1,818 4,179 7,269 475 172 15,908 Simanjiro 758 282 864 3,265 621 142 1,962 Kiteto 246 633 1,353 2,698 385 0 2,188 Total 6,987 4,312 17,977 25,522 4,227 379 38,826 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 1,358 714 3,905 2,116 1,507 365 10,259 Hanang 0 470 235 384 157 0 1,380 Mbulu 0 2,074 1,645 3,931 406 0 7,535 Simanjiro 88 100 49 534 102 53 531 Kiteto 0 265 197 137 69 0 576 Total 1,446 3,624 6,031 7,102 2,240 419 20,280 Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Livelihood Activity Annual Crop Permanent Crop Farming Livestock Keeping / Off Farm Income Remittances Fishing / Hunting & Tree / Forest Resources Tanzania Agriculture Sample Census 2003 Manyara Region. Appendix ii 125 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 206 441 1,048 357 487 125 685 Hanang 0 0 76 78 0 0 0 Mbulu 0 952 86 344 258 84 1,731 Simanjiro 0 0 0 99 46 0 70 Kiteto 0 70 0 66 0 0 0 Total 206 1,462 1,210 944 791 210 2,486 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 0 0 0 0 0 0 0 Hanang 0 0 0 0 0 0 0 Mbulu 0 0 0 84 87 0 0 Simanjiro 94 0 12 0 0 0 0 Kiteto 0 0 0 0 0 0 0 Total 94 0 12 84 87 0 0 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Babati 0 0 0 0 94 0 125 Hanang 0 0 0 0 0 0 0 Mbulu 0 87 87 0 0 0 0 Simanjiro 0 0 45 0 0 0 0 Kiteto 0 0 0 0 0 0 0 Total 0 87 132 0 94 0 125 Tanzania Agriculture Sample Census 2003 Manyara Region. 126 Appendix ii 127 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census 2003 Mnnyara Region. Appendix ii 128 Number % Number % Number % Less than 4 56,229 50 55,239 50 111,467 100 05 - 09 73,390 53 65,361 47 138,752 100 10 - 14 67,177 52 61,629 48 128,806 100 15 - 19 50,574 54 43,302 46 93,876 100 20 - 24 39,070 52 36,776 48 75,846 100 25 - 29 29,115 48 32,100 52 61,215 100 30 - 34 25,800 47 28,986 53 54,785 100 35 - 39 23,994 52 21,904 48 45,899 100 40 - 44 19,707 58 14,533 42 34,240 100 45 - 49 14,529 52 13,571 48 28,101 100 50 - 54 12,203 55 9,793 45 21,997 100 55 - 59 9,041 61 5,682 39 14,723 100 60 - 64 7,142 47 7,983 53 15,125 100 65 - 69 6,303 66 3,252 34 9,555 100 70 - 74 5,740 64 3,223 36 8,963 100 75 - 79 3,404 52 3,120 48 6,525 100 80 - 84 3,803 60 2,496 40 6,299 100 Above 85 3,113 64 1,762 36 4,875 100 Total 450,336 52 410,714 48 861,049 100 Number % Number % Number % Less than 4 56,229 12 55,239 13 111,467 13 05 - 09 73,390 16 65,361 16 138,752 16 10 - 14 67,177 15 61,629 15 128,806 15 15 - 19 50,574 11 43,302 11 93,876 11 20 - 24 39,070 9 36,776 9 75,846 9 25 - 29 29,115 6 32,100 8 61,215 7 30 - 34 25,800 6 28,986 7 54,785 6 35 - 39 23,994 5 21,904 5 45,899 5 40 - 44 19,707 4 14,533 4 34,240 4 45 - 49 14,529 3 13,571 3 28,101 3 50 - 54 12,203 3 9,793 2 21,997 3 55 - 59 9,041 2 5,682 1 14,723 2 60 - 64 7,142 2 7,983 2 15,125 2 65 - 69 6,303 1 3,252 1 9,555 1 70 - 74 5,740 1 3,223 1 8,963 1 75 - 79 3,404 1 3,120 1 6,525 1 80 - 84 3,803 1 2,496 1 6,299 1 Above 85 3,113 1 1,762 0 4,875 1 Total 450,336 100 410,714 100 861,049 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 129 Number % Number % Number % Babati 119,756 52 108,485 48 228,241 100 Hanang 100,285 52 91,632 48 191,917 100 Mbulu 117,996 53 104,600 47 222,596 100 Simanjiro 44,450 52 41,069 48 85,519 100 Kiteto 67,849 51 64,927 49 132,776 100 Total 450,336 52 410,714 48 861,049 100 Number % Number % Number % Babati 133,130 65 15,810 8 0 0 Hanang 103,760 61 8,067 5 468 0 Mbulu 122,052 64 5,219 3 0 0 Simanjiro 34,639 48 1,567 2 12 0 Kiteto 56,637 51 1,972 2 0 0 Total 450,219 60 32,634 4 481 0 Number % Number % Babati 57,402 28 206,342 100 Hanang 58,508 34 170,803 100 Mbulu 62,784 33 190,055 100 Simanjiro 35,597 50 71,815 100 Kiteto 51,957 47 110,567 100 Total 266,249 36 749,582 100 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Total Read & Write 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Swahili Swahili & English Any Other Language cont...HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Don't Read / Write Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 130 Number % Number % Number % Number % Babati 68,948 33 82,198 40 55,195 27 206,342 100 Hanang 59,189 35 56,134 33 55,480 32 170,803 100 Mbulu 63,815 34 68,842 36 57,398 30 190,055 100 Simanjiro 16,562 23 20,486 29 34,767 48 71,815 100 Kiteto 29,789 27 34,406 31 46,372 42 110,567 100 Total 238,303 32 262,067 35 249,212 33 749,582 100 Number % Number % Number % Number % Number % Babati 102,488 50 6,527 3 359 0 0 0 1,533 1 Hanang 83,945 49 4,565 3 155 0 66 0 618 0 Mbulu 87,247 46 6,363 3 349 0 86 0 1,430 1 Simanjiro 21,870 30 24,498 34 864 1 102 0 436 1 Kiteto 58,979 53 9,264 8 1,033 1 0 0 655 1 Total 354,529 47 51,216 7 2,761 0 254 0 4,673 1 Number % Number % Number % Number % Number % Babati 1,711 1 3,161 2 94 0 916 0 115 0 Hanang 694 0 473 0 0 0 841 0 710 0 Mbulu 2,992 2 732 0 1,164 1 160 0 307 0 Simanjiro 610 1 212 0 576 1 645 1 178 0 Kiteto 275 0 137 0 671 1 666 1 386 0 Total 6,281 1 4,715 1 2,505 0 3,228 0 1,696 0 Number % Number % Number % Number % Number % Babati 118 0 1,545 1 66,314 32 14,416 7 7,044 3 Hanang 312 0 2,967 2 54,295 32 20,226 12 936 1 Mbulu 516 0 3,168 2 60,202 32 24,415 13 926 0 Simanjiro 84 0 653 1 14,541 20 5,694 8 851 1 Kiteto 285 0 675 1 27,033 24 8,695 8 1,812 2 Total 1,315 0 9,008 1 222,386 30 73,446 10 11,569 2 Number % Babati 206,342 100 Hanang 170,803 100 Mbulu 190,055 100 Simanjiro 71,815 100 Kiteto 110,567 100 Total 749,582 100 cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, District Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Private - NGO / Mission Self Employed (Non Livestock Keeping / Livestock Pastoralist Fishing Government / Not Working & Main Activity cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Housemaker / Student Unable to Work / Too Other 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity Main Activity cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Self Employed (Non Unpaid Family Helper Not Working & District Crop/Seaweed Farming Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 131 Number % Number % Number % Number % Number % Babati 89,799 44 6,019 3 50,375 24 60,149 29 206,342 100 Hanang 66,253 39 9,337 5 53,201 31 42,011 25 170,803 100 Mbulu 80,717 42 8,212 4 47,736 25 53,390 28 190,055 100 Simanjiro 19,620 27 7,345 10 28,410 40 16,440 23 71,815 100 Kiteto 61,516 56 5,036 5 19,038 17 24,977 23 110,567 100 Total 317,905 42 35,949 5 198,760 27 196,967 26 749,582 100 Number % Number % Number % Number % Number % Babati 447.4 0.5 231.0 0.3 593.7 0.7 1986.7 2.4 5808.8 7.1 Hanang 222.3 0.4 292.5 0.5 1079.6 1.9 1545.1 2.8 4085.9 7.3 Mbulu 0.0 0.0 508.0 0.7 1093.3 1.6 1351.1 2.0 5865.4 8.5 Simanjiro 237.8 1.2 177.7 0.9 370.9 1.8 818.3 4.0 1429.7 7.0 Kiteto 68.3 0.2 52.0 0.2 515.0 1.5 1157.1 3.4 2472.9 7.2 Total 975.9 0.4 1261.3 0.5 3652.4 1.4 6858.4 2.6 19662.7 7.5 Number % Number % Number % Number % Number % Babati 920.1 1.1 1417.6 1.7 60116.3 73.1 688.7 0.8 6277.0 7.6 Hanang 779.2 1.4 850.0 1.5 44172.3 78.7 152.9 0.3 233.4 0.4 Mbulu 516.6 0.8 590.5 0.9 55039.4 80.0 332.5 0.5 343.7 0.5 Simanjiro 539.1 2.6 496.1 2.4 14728.0 71.9 215.0 1.0 129.4 0.6 Kiteto 507.4 1.5 436.0 1.3 26971.8 78.4 67.1 0.2 205.0 0.6 Total 3262.4 1.2 3790.1 1.4 201027.8 76.7 1456.2 0.6 7188.5 2.7 District Involvement in Farming Works Full-time on Works Part-time on Rarely Works on Farm Never Works on Farm 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year Total Standard Three Standard Four Training After Prim District Under Standard One Standard One Standard Two Standard Five Standard Six Standard Seven Standard Eight 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Education Level cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 132 Form One Number % Number % Number % Number % Number % Babati 0.0 0.0 0.0 0.0 115.3 0.1 2088.6 2.5 0.0 0.0 Hanang 314.1 0.6 80.1 0.1 236.9 0.4 1006.4 1.8 0.0 0.0 Mbulu 0.0 0.0 255.1 0.4 0.0 0.0 1569.7 2.3 86.4 0.1 Simanjiro 38.2 0.2 0.0 0.0 321.7 1.6 413.1 2.0 0.0 0.0 Kiteto 0.0 0.0 0.0 0.0 332.4 1.0 822.2 2.4 0.0 0.0 Total 352.3 0.1 335.2 0.1 1006.4 0.4 5900.0 2.3 86.4 0.0 Number % Number % Number % Number % Babati 1197.5 1.5 0.0 0.0 309.7 0.4 82198.3 100.0 Hanang 154.4 0.3 63.5 0.1 865.7 1.5 56134.3 100.0 Mbulu 433.2 0.6 84.4 0.1 772.9 1.1 68842.2 100.0 Simanjiro 188.4 0.9 0.0 0.0 382.4 1.9 20485.9 100.0 Kiteto 257.1 0.7 0.0 0.0 541.9 1.6 34406.3 100.0 Total 2230.7 0.9 147.9 0.1 2872.6 1.1 262067.1 100.0 Number of Househod Members Number of Households Average Househol d Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Househol ds Average Household Size Babati 196,217 39,159 5 32,024 7,476 4 228,241 46,635 5 Hanang 177,769 28,310 6 14,148 2,935 5 191,917 31,245 6 Mbulu 207,958 31,922 7 14,638 2,459 6 222,596 34,381 6 Simanjiro 68,112 12,679 5 17,407 3,685 5 85,519 16,364 5 Kiteto 119,278 22,199 5 13,498 3,370 4 132,776 25,569 5 Total 769,334 134,268 6 91,715 19,926 5 861,049 154,194 6 Number Percent Number Percent Number Percent Number Percent Babati 12,723 32 19,525 49 7,572 19 39,820 100 Hanang 8,926 78 2,073 18 468 4 11,467 100 Mbulu 11,123 59 5,441 29 2,228 12 18,793 100 Simanjiro 5,000 67 1,453 19 1,015 14 7,468 100 Kiteto 8,635 64 3,522 26 1,298 10 13,455 100 Total 46,407 51 32,014 35 12,581 14 91,002 100 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of District Male Female Total 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income District Off farm income One Two More than Two Total Form Six District Training After SecondaryUniversity & Other TeAdult Education Pre Form One Total Form Two Form Four District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Forma Education Completion and District, 2002/03 Agricultural Year Education Level Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 133 No Education Primary Education Post Primary Educatio n Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Babati 16,933 26,687 1,172 933 601 0 310 46,635 Hanang 12,120 17,808 234 392 154 63 473 31,245 Mbulu 13,320 19,628 258 492 174 84 426 34,381 Simanjiro 8,979 6,554 79 360 148 0 243 16,364 Kiteto 10,806 13,633 275 447 69 0 340 25,569 Total 62,158 84,309 2,017 2,624 1,146 148 1,792 154,194 Mean Median Mode Mean Median Mode Mean Median Mode Babati 45 42 35 51 49 40 46 43 40 Hanang 45 41 35 47 47 45 45 42 35 Mbulu 48 44 30 52 50 50 48 45 40 Simanjiro 44 42 45 40 38 38 43 40 30 Kiteto 41 38 30 44 40 30 42 38 30 Total 45 42 30 47 45 40 45 42 40 Male Female Total Male Female Total Male Female Total Babati 27,302 3,066 30,369 11,856 4,410 16,266 39,159 7,476 46,635 Hanang 18,372 1,005 19,378 9,937 1,930 11,867 28,310 2,935 31,245 Mbulu 20,158 905 21,063 11,764 1,554 13,318 31,922 2,459 34,381 Simanjiro 6,582 1,051 7,632 6,097 2,634 8,732 12,679 3,685 16,364 Kiteto 13,855 1,288 15,143 8,344 2,082 10,426 22,199 3,370 25,569 Total 86,270 7,316 93,586 47,999 12,610 60,609 73,219 133,828 207,046 Male Female Total Male Female Total Male Female Total Babati 27,302 3,066 30,369 11,856 4,410 16,266 39,159 7,476 46,635 Hanang 18,372 1,005 19,378 9,937 1,930 11,867 28,310 2,935 31,245 Mbulu 20,158 905 21,063 11,764 1,554 13,318 31,922 2,459 34,381 Simanjiro 6,582 1,051 7,632 6,097 2,634 8,732 12,679 3,685 16,364 Kiteto 13,855 1,288 15,143 8,344 2,082 10,426 22,199 3,370 25,569 Total 86,270 7,316 93,586 47,999 12,610 60,609 134,268 19,926 154,194 3.15 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 District Male Female Total Know Don't Know Total Male Female Total 3.14 Literacy Rate of Heads of Households by Sex and District District District Literacy Know Don't know Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District Tanzania Agriculture Sample Census 2003 Manyara Region 134 Appendix ii 135 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census 2003 Mnnyara Region. Appendix ii 136 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Babati 10,863 23 33,252 71 9,120 20 4,671 10 1,986 4 361 1 3,478 7 46,635 Hanang 8,674 28 17,373 56 5,051 16 4,062 13 1,438 5 391 1 3,601 12 31,245 Mbulu 1,594 5 30,750 89 1,955 6 1,217 4 1,685 5 173 1 1,193 3 34,381 Simanjiro 1,952 12 11,434 70 1,020 6 613 4 529 3 72 0 242 1 16,364 Kiteto 773 3 17,513 68 2,634 10 5,197 20 441 2 67 0 1,488 6 25,569 Total 23,856 15 110,322 72 19,780 13 15,760 10 6,079 4 1,064 1 10,001 6 154,194 Area Leased/Certifi cate of Ownership Area Owned Under Customar y Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Babati 14,781 50,017 11,823 5,039 1,747 550 2,681 86,639 Hanang 17,811 34,770 11,864 3,851 1,497 487 9,784 80,064 Mbulu 2,746 51,436 4,693 903 804 70 1,726 62,379 Simanjiro 4,856 50,612 2,191 543 549 22 268 59,041 Kiteto 4,735 67,427 9,345 11,137 1,204 273 5,343 99,463 Total 44,929 254,262 39,915 21,473 5,801 1,402 19,802 387,585 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Leased/Certificate of Ownership Area Owned Under Customary Law Bought Rented Borrowed Households with Area Shared Croped Households with Area under Other Forms of Tenure Land Access Total number of Households Tanzania Agriculture Sample Census 2003 Mnnyara Region. Appendix ii 137 LAND USE Tanzania Agriculture Sample Census 2003 Manyara Region. Appendix ii 138 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Babati 18,752 52,014 168 361 594 1,913 3,944 1,097 985 1,787 1,769 3,255 86,639 Hanang 19,488 43,730 17 282 574 9,252 2,468 161 212 191 1,101 2,558 80,034 Mbulu 3,651 36,206 156 376 2,151 15,584 638 550 750 483 1,022 812 62,379 Simanjiro 20,950 12,697 7 279 274 3,364 2,032 1,649 606 990 2,291 13,767 58,906 Kiteto 56,662 21,668 39 301 1,043 434 4,837 305 424 4,024 1,302 8,423 99,463 Total 119,503 166,314 387 1,599 4,636 30,547 13,919 3,762 2,977 7,475 7,485 28,815 387,420 Households with Area under Temporary Mono Crops Households with Area under Temporary Mixed Crops Households with Area under Permanent Mono Crops Households with Area under Permanent Mixed Crops Households with Area under Permanent / Annual Mix Households with Area under Pasture Households with Area under Fallow Households with Area under Natural Bush Households with Area under Planted Trees Households with Area Rented to Others Households with Area Unusable Households with Area of Uncultivated Usable Land Total Babati 16,195 34,279 454 540 1,286 2,738 2,826 476 3,966 1,635 2,036 2,665 69,095 Hanang 10,962 24,510 155 311 395 3,307 1,245 159 763 238 778 2,416 45,240 Mbulu 6,432 32,048 957 779 2,854 11,747 1,264 949 2,763 676 1,201 1,617 63,286 Simanjiro 9,986 4,984 35 237 280 1,121 443 224 478 321 748 5,222 24,079 Kiteto 19,048 7,334 171 137 391 134 1,796 160 262 864 329 3,127 33,752 Total 62,624 103,155 1,772 2,004 5,205 19,047 7,574 1,967 8,232 3,733 5,092 15,047 235,452 % 27 44 1 1 2 8 3 1 3 2 2 6 100 5.2 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District 5.1 LAND USE: Area of Land by type of Land Use and District during 2002/03 Agricultural Year District Size of Holding (Ha) Land Use Land Use Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 139 Number Percent Number Percent Number Percent Babati 37,049 80 9,256 20 46,305 100 Hanang 24,494 79 6,529 21 31,022 100 Mbulu 27,773 81 6,443 19 34,215 100 Simanjiro 6,664 48 7,095 52 13,759 100 Kiteto 18,425 74 6,551 26 24,976 100 Total 114,404 76 35,873 24 150,278 100 Number Percent Number Percent Number Percent Babati 20,925 45 25,380 55 46,305 100 Hanang 13,015 42 18,007 58 31,022 100 Mbulu 15,899 46 18,316 54 34,215 100 Simanjiro 4,182 30 9,577 70 13,759 100 Kiteto 8,857 35 16,119 65 24,976 100 Total 62,879 42 87,399 58 150,278 100 Number Percent Number Percent Number Percent Babati 5,188 11 41,117 89 46,305 100 Hanang 3,033 10 27,989 90 31,022 100 Mbulu 2,420 7 31,795 93 34,215 100 Simanjiro 1,852 13 11,907 87 13,759 100 Kiteto 5,948 24 19,028 76 24,976 100 Total 18,442 12 131,836 88 150,278 100 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census 2003 Manyara Region 140 Appendix ii 141 COMMUNIAL RESOURCES Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 142 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Babati 1.1 1.5 1.2 1.7 2.5 3.2 2.0 2.2 Hanang 2.0 4.2 2.3 4.4 2.2 3.4 1.9 2.1 Mbulu 1.2 1.7 1.4 1.9 2.3 3.0 1.8 1.6 Simanjiro 2.5 4.0 2.7 4.6 2.9 5.8 2.0 2.0 Kiteto 1.7 4.9 2.3 5.9 2.9 3.8 3.3 3.3 Total 1.6 2.9 1.8 3.3 2.5 3.6 2.2 2.2 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Babati 2.5 2.5 2.0 2.2 4.1 4.1 7.8 7.8 7.3 8.2 Hanang 2.9 2.9 3.5 3.7 4.3 4.3 8.0 8.0 7.6 8.6 Mbulu 2.7 2.7 2.4 2.5 5.0 5.0 8.0 8.0 8.0 9.0 Simanjiro 2.4 2.4 3.1 3.3 4.3 4.3 7.7 7.6 6.9 7.7 Kiteto 3.8 3.6 3.5 3.7 4.1 4.1 7.2 7.2 8.3 9.3 Total 2.8 2.8 2.8 2.9 4.3 4.3 7.8 7.8 7.6 8.6 6.1 COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name o Communal Resource, Season and District, 2002/03 Agricultural Year District Communal Firewood Communal Resource Wood for Charcoal Building Poles Forest for Bees (Honey) Hunting (Animal Products) District Water for Humans Water for Livestock Communal Grazing Communal Resource cont... COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Fishing (Fish) Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 143 Home of Farm Consumption / Utilization Sold to Village Market Sold to Local Wholesale Market Not Used by Household Not Available Total Babati 46,411 0 0 114 110 46,635 Hanang 31,094 0 0 151 0 31,245 Mbulu 34,294 0 87 0 0 34,381 Simanjiro 16,255 41 41 27 0 16,364 Kiteto 25,444 0 0 125 0 25,569 Total 153,498 41 128 417 110 154,194 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Village Market Not Used by Household Not Available Total Babati 35,338 112 117 9,560 1,508 46,635 Hanang 26,574 0 0 4,671 0 31,245 Mbulu 29,959 0 0 3,908 514 34,381 Simanjiro 13,445 0 38 1,710 1,171 16,364 Kiteto 11,659 206 0 13,287 417 25,569 Total 116,974 318 155 33,137 3,610 154,194 6.2 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District Water for Humans 6.3 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year District Water for Livestock Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 144 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Not Used by Household Not Available Total Babati 16,508 0 0 0 0 7,628 22,499 46,635 Hanang 7,888 237 66 78 0 4,453 18,523 31,245 Mbulu 7,322 174 0 0 0 2,055 24,831 34,381 Simanjiro 9,883 0 0 0 45 2,350 4,087 16,364 Kiteto 6,752 60 0 0 70 13,557 5,131 25,569 Total 48,352 471 66 78 114 30,042 75,071 154,194 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Babati 39,226 341 243 112 1,410 0 1,362 3,941 46,635 Hanang 30,092 315 0 0 0 78 454 305 31,245 Mbulu 30,996 173 0 86 174 86 73 2,792 34,381 Simanjiro 15,242 49 0 0 0 509 276 288 16,364 Kiteto 24,103 0 60 0 0 0 1,406 0 25,569 Total 139,660 878 303 198 1,584 674 3,571 7,326 154,194 6.4 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District Communal Grazing 6.5 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District Communal Firewood Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 145 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Babati 2,980 3,381 792 0 222 0 10,520 28,740 46,635 Hanang 3,114 671 404 66 232 0 8,993 17,766 31,245 Mbulu 948 166 604 87 0 603 8,326 23,647 34,381 Simanjiro 466 85 27 0 38 0 2,749 12,999 16,364 Kiteto 3,796 789 60 60 0 0 16,662 4,202 25,569 Total 11,304 5,092 1,888 212 492 603 47,250 87,353 154,194 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Babati 29,469 237 243 232 1,044 112 6,282 9,015 46,635 Hanang 24,234 156 78 0 0 0 5,303 1,473 31,245 Mbulu 18,770 690 87 0 2,250 174 6,945 5,464 34,381 Simanjiro 13,410 0 48 36 0 0 1,858 1,013 16,364 Kiteto 15,423 60 0 0 0 0 9,662 424 25,569 Total 101,306 1,144 457 268 3,294 286 30,050 17,389 154,194 6.6 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District Wood for Charcoal 6.7 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District Building Poles Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 146 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Local Wholesale Market Not Used by Household Not Available Total Babati 3,439 337 104 0 14,278 28,476 46,635 Hanang 374 77 146 66 7,894 22,689 31,245 Mbulu 345 0 0 0 86 33,950 34,381 Simanjiro 184 0 0 0 1,700 14,481 16,364 Kiteto 1,141 166 0 0 14,000 10,262 25,569 Total 5,482 580 250 66 37,957 109,859 154,194 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Babati 113 0 0 0 913 908 44,701 46,635 Hanang 63 0 310 0 0 889 29,982 31,245 Mbulu 0 174 0 87 0 86 34,034 34,381 Simanjiro 130 0 0 0 0 1,093 15,141 16,364 Kiteto 391 60 0 0 0 7,576 17,542 25,569 Total 697 234 310 87 913 10,553 141,400 154,194 6.8 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District Forest for Bees Products 6.9 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District Hunting Grounds Tanzania Agriculture Sample Census 2003 Manyara Region Appendix II 147 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Babati 349 0 0 0 115 799 5,586 39,786 46,635 Hanang 0 0 0 0 153 0 2,024 29,067 31,245 Mbulu 0 87 0 0 87 0 86 34,121 34,381 Simanjiro 162 66 18 0 0 0 2,436 13,683 16,364 Kiteto 68 813 0 68 0 0 128 24,493 25,569 Total 578 966 18 68 356 799 10,261 141,149 154,194 District Fishing Resources 6.10 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Fishing Resouces by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region 148 Appendix ii 149 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION - LONG AND SHORT RAINY SEASON Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 150 Number of Households Planted Area Number of Households Planted Area Babati 3,021 1,261 79,914 56,835 58,096 2.17 Hanang 314 191 65,711 58,469 58,659 0.33 Mbulu 7,700 2,242 78,905 39,557 41,798 5.36 Simanjiro 379 327 20,661 31,868 32,195 1.02 Kiteto 0 0 32,618 74,511 74,511 0.00 Total 11,414 4,020 277,809 261,239 265,260 1.52 1.5 98.5 average 0.4 0.9 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Babati 1,854 44,781 46,184 451 46,635 Hanang 79 31,166 30,944 301 31,245 Mbulu 3,633 30,748 33,519 862 34,381 Simanjiro 331 16,033 13,741 2,623 16,364 Kiteto 0 25,569 24,976 593 25,569 Total 5,897 148,297 149,363 4,831 154,194 7.1 & 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area By District-SHORT RAINY SEASON Shorty Rainy Season Long Rainy Season Total area planted (hectares) % Area planted in short rainy season District 7.1 and 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District- SHORT RAINY SEASON Short Rainy Season Long Rainy Season Total Number of Crop Growing Households District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 151 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cereal 2,712 3,184 1174 200,201 161,605 807 202,913 164,788 812 Maize 2,339 2,828 1209 185,559 144,945 781 187,898 147,773 786 Paddy 0 0 0 2,031 6,674 3287 2,031 6,674 3287 Sorghum 276 330 1197 6,495 3,747 577 6,771 4,078 602 Bulrush Millet 0 0 0 393 99 253 393 99 253 Finger Millet 97 25 260 3,679 2,618 712 3,775 2,643 700 Wheat 0 0 0 2,046 3,521 1721 2,046 3,521 1721 Roots and Tubers 73 59 812 1,344 1,282 954 1,417 1,341 946 Cassava 18 16 889 763 593 777 781 609 780 Sweet Potatoes 55 43 787 488 566 1160 543 609 1122 Irish Potatoes 0 0 0 78 122 1568 78 122 1568 Yams 0 0 0 15 1 49 15 1 49 Pulses 1,003 632 630 46,097 16,199 351 47,099 16,831 357 Beans 997 632 634 44,854 15,745 351 45,851 16,377 357 Cowpeas 6 0 0 450 82 183 455 82 181 Green Gram 0 0 0 11 5 494 11 5 494 Chich Peas 0 0 0 530 286 540 530 286 540 Bambaranuts 0 0 0 225 58 256 225 58 256 Field Peas 0 0 0 27 23 0 27 23 0 Oil Seeds and Oil nuts 133 56 423 13,097 6,974 532 13,231 7,031 531 Sunflower 32 19 593 11,251 6,347 564 11,283 6,366 564 Simsim 0 0 0 361 103 286 361 103 286 Groundnuts 102 38 371 1,486 524 353 1,588 562 354 Fruit and Vegetables 100 135 1358 470 1,892 4028 569 2,027 3561 Okra 0 0 0 7 34 4693 7 34 4693 Onions 28 53 1853 326 999 3062 355 1,052 2965 Cabbage 0 0 0 7 0 0 7 0 0 Tomatoes 24 49 2075 118 841 7133 142 890 6285 Spinnach 12 5 395 0 0 0 12 5 395 Chillies 0 0 0 118 841 7133 118 841 7133 Pumpkins 12 4 296 0 0 0 12 4 296 Cucumber 12 2 148 4 0 0 16 2 113 Water Mellon 12 23 1976 4 18 0 16 41 0 Cash Crops 0 0 0 30 25 823 30 25 823 Tobacco 0 0 0 30 25 823 30 25 823 Total 4,020 261,239 265,260 * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to being produced on the same land during the 2 seasons. Previous surveys have used the lpno season to estimate physical land area under production to different crops Table 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Manyara Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 152 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Cereals 6,091 2,712 172,447 200,201 202,913 1 Maize 4,883 2,339 144,475 185,559 187,898 1.2 Paddy 0 0 3,289 2,031 2,031 0.0 Sorghum 774 276 15,108 6,495 6,771 4.1 Bulrush Millet 0 0 491 393 393 0.0 Finger Millet 433 97 6,420 3,679 3,775 2.6 Wheat 0 0 2,664 2,046 2,046 0.0 Barley 0 0 0 0 0 0.0 Root and Tubers 434 73 5,423 1,344 1,417 5.1 Cassava 87 18 2,234 763 781 2.3 Sweet Potatoes 347 55 2,399 488 543 10.2 Irish Potatoes 0 0 714 78 78 0.0 Yams 0 0 75 15 15 0.0 Cocoyam 0 0 0 0 0 0.0 Pulses 3,947 1,003 82,843 46,097 47,099 2.1 Mung Beans 0 0 0 0 0 0.0 Beans 3,917 997 80,222 44,854 45,851 2.2 Cowpeas 30 6 941 450 455 1.3 Green Gram 0 0 36 11 11 0.0 Chich Peas 0 0 1,008 530 530 0.0 Bambaranuts 0 0 488 225 225 0.0 Field Peas 0 0 148 27 27 0.0 Oil Seeds and Oil nuts 204 133 15,789 13,097 13,231 1.0 Sunflower 79 32 12,004 11,251 11,283 0.3 Simsim 0 0 463 361 361 0.0 Groundnuts 125 102 3,322 1,486 1,588 6.4 Fruit and Vegetables 739 100 1,182 470 569 17.5 Okra 0 0 36 7 7 0.0 Bitter Aubergine 0 0 0 0 0 0.0 Onions 35 28 598 326 355 8.0 Cabbage 0 0 36 7 7 0.0 Tomatoes 235 24 404 118 142 16.8 Spinnach 117 12 0 0 12 100.0 Carrot 0 0 0 0 0 0.0 Chillies 0 0 36 118 118 0.0 Amaranths 0 0 0 0 0 0.0 Pumpkins 117 12 0 0 12 100.0 Cucumber 117 12 36 4 16 76.6 Egg Plant 0 0 0 0 0 0.0 Water Mellon 117 12 36 4 16 0.0 Cauliflower 0 0 0 0 0 0.0 Cash Crops 0 0 125 30 0.0 Cotton 0 0 0 0 0.0 Tobacco 0 0 125 30 30 0.0 Pyrethrum 0 0 0 0 0.0 Total 430,589 261,334 265,260 Table 7.1 and 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Manyara Region Crop Short Rainy Season Long Rainy Season Total Area Planted Short and Long Rainy Season % Area Planted in Short Rainy Season Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Babati 5,700 9,807 36,615 44,123 5,722 4,166 48,038 58,096 Hanang 454 1,586 25,421 51,012 5,148 6,061 31,022 58,659 Mbulu 766 1,055 22,385 28,629 14,002 12,114 37,153 41,798 Simanjiro 7,319 20,696 3,008 7,426 3,744 4,073 14,072 32,195 Kiteto 5,833 26,180 1,250 3,102 17,893 45,229 24,976 74,511 Total 20,073 59,324 88,679 134,293 46,508 71,643 155,261 265,260 Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Planted Area Babati 18,338 23,489 243 296 0 0 29,456 34,311 58,096 Hanang 6,218 13,764 1,079 2,327 384 600 23,341 41,968 58,659 Mbulu 24,324 27,211 261 237 0 0 12,568 14,350 41,798 Simanjiro 1,925 4,880 167 356 501 479 11,479 26,481 32,195 Kiteto 959 5,204 245 551 68 110 23,704 68,647 74,511 Total 51,765 74,548 1,996 3,766 952 1,188 100,547 185,757 265,260 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 3,061 3,942 44,977 54,154 48,038 58,096 6.8 Hanang 619 709 30,403 57,950 31,022 58,659 1.2 Mbulu 1,674 1,401 35,479 40,397 37,153 41,798 3.4 Simanjiro 1,350 1,356 12,723 30,839 14,072 32,195 4.2 Kiteto 177 662 24,799 73,849 24,976 74,511 0.9 Total 6,880 8,071 148,381 257,189 155,261 265,260 3.0 7.1 & 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 1nd 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Manyara Region District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied % of area planted under irrigation Number of households is an over estimate due to the double counting of households growing crops in both long and short rain seasons. To compare previous surveys use Number of Long Season District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total 7.1 and 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 154 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 5,185 6,921 42,853 51,175 48,038 58,096 11.9 Hanang 2,883 7,042 28,139 51,617 31,022 58,659 12.0 Mbulu 2,301 2,496 34,851 39,302 37,153 41,798 6.0 Simanjiro 1,354 2,144 12,718 30,051 14,072 32,195 6.7 Kiteto 1,111 6,256 23,866 68,255 24,976 74,511 8.4 Total 12,833 24,859 142,427 240,401 155,261 265,260 9.4 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 1,057 2,135 46,981 55,960 48,038 58,096 3.7 Hanang 1,219 3,374 29,803 55,286 31,022 58,659 5.8 Mbulu 347 262 36,805 41,536 37,153 41,798 0.6 Simanjiro 342 628 13,731 31,567 14,072 32,195 2.0 Kiteto 405 1,694 24,571 72,817 24,976 74,511 2.3 Total 3,370 8,093 151,891 257,167 155,261 265,260 3.1 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 1,159 2,022 46,879 56,073 48,038 58,096 3.5 Hanang 1,407 3,938 29,615 54,721 31,022 58,659 6.7 Mbulu 605 479 36,547 41,319 37,153 41,798 1.1 Simanjiro 479 610 13,593 31,585 14,072 32,195 1.9 Kiteto 136 1,147 24,840 73,364 24,976 74,511 1.5 Total 3,786 8,197 151,475 257,063 155,261 265,260 3.1 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 7,564 10,895 40,474 47,201 48,038 58,096 18.8 Hanang 3,028 8,810 27,994 49,850 31,022 58,659 15.0 Mbulu 7,019 7,398 30,134 34,400 37,153 41,798 17.7 Simanjiro 4,318 8,101 9,754 24,094 14,072 32,195 25.2 Kiteto 3,232 12,075 21,745 62,437 24,976 74,511 16.2 Total 25,160 47,278 130,100 217,982 155,261 265,260 17.8 % of area planted under Herbicide 7.1 & 7.2i ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON 7.1 & 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Herbicide Use Households Using Households Not Using Total % of area planted under pesticide Number of households is an over estimate due to the double counting of households growing crops in both long and short rain seasons. To compare previous surveys use Number of Long Season planters only. District Pesticide Use Households Using Households Not Using Total 7.1 & 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON Fungicide Use Households Using Households Not Using Total % of area planted under Imroved Seeds 7.1& 7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of area planted under Fungicide District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 155 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Babati 475 409 1,052 695 327 158 1,854 1,261 Hanang 0 . 79 191 0 . 79 191 Mbulu 433 131 171 69 3,030 2,041 3,633 2,242 Simanjiro 81 124 71 86 179 118 331 327 Total 989 663 1,373 1,040 3,536 2,317 5,897 4,020 % 17 17 23 26 60 58 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Babati 695 454 0 0 0 0 1,158 807 1,854 1,261 Hanang 0 0 0 0 0 0 79 191 79 191 Mbulu 2,682 1,865 87 61 0 0 864 315 3,633 2,242 Simanjiro 0 0 0 0 0 0 331 327 331 327 Total 3,378 2,319 87 61 0 0 2,433 1,640 5,897 4,020 % 57 58 1 2 0 0 41 41 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 704 404 1,150 857 1,854 1,261 32 Hanang 0 0 79 191 79 191 0 Mbulu 433 248 3,201 1,994 3,633 2,242 11 Simanjiro 70 114 261 214 331 327 35 Total 1,206 765 4,691 3,255 5,897 4,020 19 % 20 19 80 81 100 100 % of area planted under irrigation in short rainy season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Irrigation Use Households Using Households Not Using Total 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic No Fertilizer Applied Total 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 157 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 467 293 1,387 968 1,854 1,261 Hanang 0 . 79 191 79 191 Mbulu 259 140 3,375 2,101 3,633 2,242 Simanjiro 80 162 251 166 331 327 Total 806 594 5,091 3,426 5,897 4,020 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 117 119 1,737 1,142 1,854 1,261 9 Hanang 0 0 79 191 79 191 0 Mbulu 174 106 3,459 2,136 3,633 2,242 5 Simanjiro 0 0 331 327 331 327 0 Total 292 225 5,605 3,796 5,897 4,020 6 % 5 6 95 94 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 235 166 1,619 1,095 1,854 1,261 13 Hanang 0 0 79 191 79 191 0 Mbulu 87 35 3,546 2,206 3,633 2,242 2 Simanjiro 0 0 331 327 331 327 0 Total 322 201 5,575 3,819 5,897 4,020 5 % 5 5 95 95 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 467 295 1,387 966 1,854 1,261 23 Hanang 79 191 0 . 79 191 100 Mbulu 862 707 2,771 1,534 3,633 2,242 32 Simanjiro 186 102 145 225 331 327 31 Total 1,594 1,295 4,303 2,725 5,897 4,020 32 % 27 32 73 68 100 100 % of area planted under Herbicide % of area planted under Fungicide % of area planted under Improved Seeds 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON District Improved Seed Use Households Using Households Not Using Total 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use Households Using Households Not Using Total 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Herbicide Use Households Using Households Not Using Total 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON District Pesticide Use Households Using Households Not Using Total Tanzania Agriculture Sample Census 2003 Manyara Region 158 Appendix ii 159 ANNUAL CROP AND VEGETABLE PRODUCTION- LONG RAINY SEASON Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 160 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Babati 5,225 9,398 35,564 43,428 5,395 4,008 46,184 56,835 Hanang 454 1,586 25,342 50,822 5,148 6,061 30,944 58,469 Mbulu 334 924 22,214 28,560 10,972 10,073 33,519 39,557 Simanjiro 7,238 20,572 2,937 7,340 3,566 3,955 13,741 31,868 Kiteto 5,833 26,180 1,250 3,102 17,893 45,229 24,976 74,511 Total 19,084 58,660 87,306 133,253 42,973 69,326 149,363 261,239 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Babati 17,643 23,035 243 296 0 . 28,297 33,504 46,184 56,835 Hanang 6,218 13,764 1,079 2,327 384 600 23,262 41,777 30,944 58,469 Mbulu 21,642 25,346 174 176 0 . 11,703 14,035 33,519 39,557 Simanjiro 1,925 4,880 167 356 501 479 11,148 26,154 13,741 31,868 Kiteto 959 5,204 245 551 68 110 23,704 68,647 24,976 74,511 Total 48,387 72,229 1,909 3,705 952 1,188 98,114 184,117 149,363 261,239 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 2,357 3,538 43,826 53,297 46,184 56,835 6.2 Hanang 619 709 30,325 57,759 30,944 58,469 1.2 Mbulu 1,241 1,154 32,278 38,403 33,519 39,557 2.9 Simanjiro 1,279 1,242 12,462 30,625 13,741 31,868 3.9 Kiteto 177 662 24,799 73,849 24,976 74,511 0.9 Total 5,674 7,306 143,690 253,934 149,363 261,239 2.8 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 4,718 6,629 41,466 50,206 46,184 56,835 Hanang 2,883 7,042 28,061 51,426 30,944 58,469 Mbulu 2,043 2,356 31,477 37,201 33,519 39,557 Simanjiro 1,274 1,982 12,467 29,886 13,741 31,868 Kiteto 1,111 6,256 23,866 68,255 24,976 74,511 Total 12,028 24,265 137,336 236,974 149,363 261,239 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Pesticide Use Households Using Pesticide Households Not Using Pesticide Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON District Irrigation Use % of area planted under Irrigation Households Using Irrigation Households Not Using Irrigation Total 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON District Soil Preparation Mostly Tractor Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 161 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 940 2,017 45,244 54,818 46,184 56,835 Hanang 1,219 3,374 29,724 55,095 30,944 58,469 Mbulu 173 156 33,346 39,401 33,519 39,557 Simanjiro 342 628 13,399 31,240 13,741 31,868 Kiteto 405 1,694 24,571 72,817 24,976 74,511 Total 3,078 7,868 146,285 253,371 149,363 261,239 Total Number of Households Number % Number % Number Babati 37,585 80.6 9,050 19.4 46,635 Hanang 16,241 52.0 15,004 48.0 31,245 Mbulu 16,476 47.9 17,906 52.1 34,381 Simanjiro 3,843 23.5 12,521 76.5 16,364 Kiteto 13,977 54.7 11,593 45.3 25,569 Total 88,121 57.1 66,073 42.9 154,194 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 924 1,856 45,260 54,979 46,184 56,835 3.3 Hanang 1,407 3,938 29,536 54,530 30,944 58,469 6.7 Mbulu 518 444 33,001 39,113 33,519 39,557 1.1 Simanjiro 479 610 13,262 31,258 13,741 31,868 1.9 Kiteto 136 1,147 24,840 73,364 24,976 74,511 1.5 Total 3,464 7,995 145,900 253,244 149,363 261,239 3.1 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Babati 7,097 10,600 39,087 46,235 46,184 56,835 18.6 Hanang 2,949 8,619 27,994 49,850 30,944 58,469 14.7 Mbulu 6,156 6,691 27,363 32,865 33,519 39,557 16.9 Simanjiro 4,132 7,999 9,609 23,869 13,741 31,868 25.1 Kiteto 3,232 12,075 21,745 62,437 24,976 74,511 16.2 Total 23,566 45,983 125,797 215,257 149,363 261,239 17.6 Total 25160 47278 130100 217982 155261 265260 18 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON District Improved Seed Use % of area planted under Improved Seeds Households Using Improved Seed Households Not Using Improved Seed Total District Fungicide Use % of area planted under Fungicide Households Using Fungicide Households Not Using Fungicide Total 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District District Households that Sold Produce Households that Did not Sell Produce 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 162 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 1,284 726 830 1.14 43,775 35,491 51,491 1.45 36,217 52,321 1.44 Hanang 79 95 24 0.25 30,863 35,232 27,543 0.78 35,328 27,567 0.78 Mbulu 3,207 1,225 1,418 1.16 31,788 22,818 19,066 0.84 24,043 20,483 0.85 Simanjiro 314 293 557 1.90 13,170 22,831 10,294 0.45 23,124 10,851 0.47 Kiteto 0 0 0 0.00 24,878 69,186 36,551 0.53 69,186 36,551 0.53 Total 4,883 2,339 2,828 1.21 144,475 185,559 144,945 0.78 187,898 147,773 0.79 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 2,942 1,817 6,148 3.38 1,817 6,148 3.38 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 348 213 527 2.47 213 527 2.47 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 3,289 2,031 6,674 3.29 2,031 6,674 3.29 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 352 166 234 1.41 7,168 3,821 2,857 0.75 3,987 3,091 0.78 Hanang 79 32 8 0.25 2,311 1,147 352 0.31 1,179 360 0.31 Mbulu 343 78 88 1.13 5,461 1,345 523 0.39 1,423 611 0.43 Simanjiro 0 0 0 0.00 45 73 5 0.06 73 5 0.06 Kiteto 0 0 0 0.00 123 108 11 0.10 108 11 0.10 Total 774 276 330 1.20 15,108 6,495 3,747 0.58 6,771 4,078 0.60 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 920 531 667 1.26 531 667 1.26 Hanang 0 0 0 0.00 2,828 1,864 1,133 0.61 1,864 1,133 0.61 Mbulu 433 97 25 0.26 1,807 299 144 0.48 396 169 0.43 Simanjiro 0 0 0 0.00 44 53 94 1.78 53 94 1.78 Kiteto 0 0 0 0.00 822 933 580 0.62 933 580 0.62 Total 433 97 25 0.26 6,420 3,679 2,618 0.71 3,775 2,643 0.70 Long Rainy bSeason Total Table 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year Table 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultural Year District Maize Short Rainy bseason District Paddy Short Rainy bseason Long Rainy bSeason Total Table 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sorghum Short Rainy bseason Long Rainy bSeason Total Table 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District; 2002/03 Agricultural Year District Fingemillet Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 163 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 158 147 11 0.07 147 11 0.07 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 333 246 89 0.36 246 89 0.36 Total 0 0 0 0.00 491 393 99 0.25 393 99 0.25 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 963 990 1,895 1.91 990 1,895 1.91 Hanang 0 0 0 0.00 1,110 805 1,404 1.75 805 1,404 1.75 Mbulu 0 0 0 0.00 592 251 221 0.88 251 221 0.88 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 2,664 2,046 3,521 1.72 2,046 3,521 1.72 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 358 137 203 1.48 137 203 1.48 Hanang 0 0 0 0.00 765 316 34 0.11 316 34 0.11 Mbulu 87 18 16 0.89 675 57 176 3.07 75 192 2.56 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 437 253 180 0.71 253 180 0.71 Total 87 18 16 0.89 2,234 763 593 0.78 781 609 0.78 Table 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bulrushmillets Short Rainy bseason Long Rainy bSeason Total Table 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/03 Agricultural Year District Wheat Short Rainy bseason Long Rainy bSeason Total Table 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year District Barley Short Rainy bseason Long Rainy bSeason Total Table 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cassava Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 164 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 250 50 53 1.05 50 53 1.05 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 347 55 43 0.79 2,080 410 510 1.24 465 553 1.19 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 70 28 3 0.12 28 3 0.12 Total 347 55 43 0.79 2,399 488 566 1.16 543 609 1.12 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 112 5 34 7.41 5 34 7.41 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 602 73 88 1.21 73 88 1.21 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 714 78 122 1.57 78 122 1.57 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 75 15 1 0.05 15 1 0.05 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 75 15 1 0.05 15 1 0.05 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Table 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sweet potatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Irish potatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year District Yams Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cocoyams Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 165 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 555 196 117 0.60 17,328 9,726 5,108 0.53 9,922 5,225 0.53 Hanang 79 32 13 0.40 22,362 12,913 3,842 0.30 12,945 3,855 0.30 Mbulu 3,283 769 502 0.65 31,993 11,995 3,860 0.32 12,764 4,363 0.34 Simanjiro 0 0 0 0.00 5,914 8,127 2,384 0.29 8,127 2,384 0.29 Kiteto 0 0 0 0.00 2,624 2,092 551 0.26 2,092 551 0.26 Total 3,917 997 632 0.63 80,222 44,854 15,745 0.35 45,851 16,377 0.36 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 259 29 16 0.57 29 16 0.57 Simanjiro 30 6 0 0.00 300 167 40 0.24 172 40 0.23 Kiteto 0 0 0 0.00 382 254 26 0.10 254 26 0.10 Total 30 6 0 0.00 941 450 82 0.18 455 82 0.18 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 11 5 0.49 11 5 0.49 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 36 11 5 0.49 11 5 0.49 Table 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Mungbeans Short Rainy bseason Long Rainy bSeason Total Table 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Beans Short Rainy bseason Long Rainy bSeason Total Table 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cowpeas Short Rainy bseason Long Rainy bSeason Total Table 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/03 Agricultural Year District Greengram Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 166 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 225 91 64 0.71 91 64 0.71 Hanang 0 0 0 0.00 381 186 52 0.28 186 52 0.28 Mbulu 0 0 0 0.00 402 253 169 0.67 253 169 0.67 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 1,008 530 286 0.54 530 286 0.54 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 151 122 15 0.12 122 15 0.12 Kiteto 0 0 0 0.00 337 103 43 0.41 103 43 0.41 Total 0 0 0 0.00 488 225 58 0.26 225 58 0.26 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 112 9 4 0.49 9 4 0.49 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 18 18 0.99 18 18 0.99 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 148 27 23 0.82 27 23 0.82 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 4,009 3,185 1,930 0.61 3,185 1,930 0.61 Hanang 79 32 19 0.59 4,088 5,580 3,445 0.62 5,612 3,464 0.62 Mbulu 0 0 0 0.00 3,246 2,026 799 0.39 2,026 799 0.39 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 660 460 173 0.38 460 173 0.38 Total 79 32 19 0.59 12,004 11,251 6,347 0.56 11,283 6,366 0.56 Table 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chick peas Short Rainy bseason Long Rainy bSeason Total Table 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bambanuts Short Rainy bseason Long Rainy bSeason Total Table 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Fieldpeas Short Rainy bseason Long Rainy bSeason Total Table 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sunflower Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 167 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 427 350 98 0.28 350 98 0.28 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 11 5 0.49 11 5 0.49 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 463 361 103 0.29 361 103 0.29 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 125 102 38 0.37 1,097 562 249 0.44 663 286 0.43 Hanang 0 0 0 0.00 236 72 13 0.18 72 13 0.18 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 4 0 0.00 4 0 0.00 Kiteto 0 0 0 0.00 1,952 849 263 0.31 849 263 0.31 Total 125 102 38 0.37 3,322 1,486 524 0.35 1,588 562 0.35 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Table 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultural Year District Simsim Short Rainy bseason Long Rainy bSeason Total Table 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Groundnuts Short Rainy bseason Long Rainy bSeason Total Table 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 Agricultural Year District Castor oil Short Rainy bseason Long Rainy bSeason Total Table 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Soya beans Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 168 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 7 34 4.69 7 34 4.69 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 36 7 34 4.69 7 34 4.69 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 458 177 312 1.76 177 312 1.76 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 35 28 53 1.85 140 149 687 4.61 178 740 4.17 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 35 28 53 1.85 598 326 999 3.06 355 1,052 2.96 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 7 0 0.00 7 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 36 7 0 0.00 7 0 0.00 Table 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year District Okra Short Rainy bseason Long Rainy bSeason Total Table 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bitter Aubergine Short Rainy bseason Long Rainy bSeason Total Table 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year District Onion Short Rainy bseason Long Rainy bSeason Total Table 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cabbage Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 169 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 235 24 49 2.07 104 40 489 12.17 64 538 8.42 Hanang 0 0 0 0.00 75 15 38 2.47 15 38 2.47 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 225 62 314 5.03 62 314 5.03 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 235 24 49 2.07 404 118 841 7.13 142 890 6.28 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 117 12 5 0.40 0 0 0 0.00 12 5 0.40 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 117 12 5 0.40 0 0 0 0.00 12 5 0.40 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 4 0 0.00 4 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 36 4 0 0.00 4 0 0.00 Table 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tomatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/03 Agricultural Year District Spinnach Short Rainy bseason Long Rainy bSeason Total Table 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year District Carrot Short Rainy bseason Long Rainy bSeason Total Table 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chillies Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 170 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 117 12 4 0.30 0 0 0 0.00 12 4 0.30 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 117 12 4 0.30 0 0 0 0.00 12 4 0.30 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 117 12 2 0.15 0 0 0 0.00 12 2 0.15 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 4 0 0.00 4 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 117 12 2 0.15 36 4 0 0.00 16 2 0.11 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 117 12 2 0.15 0 0 0 0.00 12 2 0.15 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 117 12 2 0.15 0 0 0 0.00 12 2 0.15 Table 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year District Amaranths Short Rainy bseason Long Rainy bSeason Total Table 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year District Pumpkins Short Rainy bseason Long Rainy bSeason Total Table 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cucumber Short Rainy bseason Long Rainy bSeason Total Table 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/03 Agricultural Year District Eggplant Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 171 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 117 12 23 1.98 0 0 0 0.00 12 23 1.98 Hanang 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0.00 36 4 18 4.94 4 18 4.94 Kiteto 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 117 12 23 1.98 36 4 18 4.94 16 41 2.67 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0 0 0 0 0.00 0 0 0.00 Hanang 0 0 0 0 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0.00 0 0 0.00 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Babati 0 0 0 0 125 30 25 0.82 30 25 0.82 Hanang 0 0 0 0 0 0 0 0.00 0 0 0.00 Mbulu 0 0 0 0 0 0 0 0.00 0 0 0.00 Simanjiro 0 0 0 0 0 0 0 0.00 0 0 0.00 Kiteto 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 125 30 25 0.82 30 25 0.82 Table 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year District Water Mellon Short Rainy bseason Long Rainy bSeason Total Table 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cauliflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cotton Short Rainy bseason Long Rainy bSeason Total Table 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tobacco Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census 2003 Manyara Region 172 Appendix ii 173 PERMANENT CROPS Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 174 Number of Households Planted Area (ha) Number of Households Area Harvested (ha) Number of Households Quantity Harvested (tons) Pigeon Pea 22,097 19,096 21,976 11,496 21,023 7,421 Coffee 345 1,041 345 520 219 19 Sugarcane 112 14 112 14 112 112 Mpesheni 94 0 94 0 94 4 Banana 1,052 4,393 1,156 3,673 1,025 1,332 Avocado 210 61 210 13 115 2 Mango 115 51 115 5 0 . Pawpaw 314 56 418 9 418 59 Orange 358 150 584 103 341 1,471 Mandarine/Tangerine 0 . 0 . 0 . Guava 210 52 331 5 331 15 Lime/Lemon 115 51 115 5 115 5 Total 25,021 24,965 25,456 15,841 23,795 10,441 Pigeon Pea 3,137 1,391 4,440 2,737 3,912 1,090 Banana 312 156 312 28 312 96 Mango 80 2 80 0 0 . Pawpaw 78 3 78 3 158 59 Orange 156 130 156 19 237 3 Guava 156 121 156 10 237 10 Lime/Lemon 0 . 0 . 80 0 Total 3,920 1,802 5,223 2,797 4,936 1,258 Pigeon Pea 86 21 254 63 169 26 Coffee 521 144 953 144 521 29 Sugarcane 87 9 259 16 259 110 Banana 1,043 239 3,287 332 3,027 1,180 Mango 0 . 169 0 0 . Orange 0 . 339 7 173 1,769 Guava 0 . 174 10 259 112 Apples 0 . 86 10 86 35 Pears 0 . 86 7 173 112 Lime/Lemon 261 23 261 4 346 101 Total 1,998 436 5,869 593 5,012 3,473 Mbulu Table 7.3 PERMANENT CROPS: Number of households by Area planted (ha), Area harvested (ha) and Quantity harvested (tons) District/Crop Babati Hanang Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 175 Number of Households Planted Area (ha) Number of Households Area Harvested (ha) Number of Households Quantity Harvested (tons) Table 7.3 PERMANENT CROPS: Number of households by Area planted (ha), Area harvested (ha) and Quantity harvested (tons) District/Crop Pigeon Pea 44 21 44 21 44 31 Banana 178 125 214 65 214 554 Mango 75 17 75 1 38 2 Guava 38 31 38 0 38 2 Total 334 194 370 87 334 588 Pigeon Pea 3,438 6,226 3,438 3,000 3,094 952 Mpesheni 60 24 60 0 60 1 Banana 117 35 117 0 0 . Mango 0 . 386 224 311 90 Pawpaw 0 . 132 0 192 329 Guava 0 . 68 0 0 . Apples 0 . 0 . 60 1 Total 3,615 6,285 4,200 3,224 3,717 1,373 Pigeon Pea 28,801 26,755 30,152 17,318 28,242 9,520 Coffee 866 1,185 1,298 664 741 48 Sugarcane 199 22 371 29 371 222 Mpesheni 154 24 154 0 154 5 Banana 2,701 4,949 5,086 4,098 4,578 3,161 Avocado 210 61 210 13 115 2 Mango 270 70 825 230 349 93 Pawpaw 392 59 628 12 768 447 Orange 514 280 1,080 129 750 3,243 Mandarine/Tangerine 0 . 0 . 0 . Guava 404 203 767 25 865 138 Apples 0 . 86 10 146 36 Pears 0 . 86 7 173 112 Lime/Lemon 377 74 377 8 542 106 Total 34,887 33,683 41,118 22,543 37,793 17,134 Simanjiro Kiteto Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 176 Cont…. Area Planted by Crop Type - Manyara Region District/Crop Planted Area (ha) % Pigeon Pea 26,755 79.4 Banana 4,949 14.7 Coffee 1,185 3.5 Orange 280 0.8 Guava 203 0.6 Lime/Lemon 74 0.2 Mango 70 0.2 Avocado 61 0.2 Pawpaw 59 0.2 Mpesheni 24 0.1 Sugarcane 22 0.1 Mandarine/Tangerine 0 0.0 Apples 0 0.0 Pears 0 0.0 Total 33,683 100.0 District Planted Area (ha) Total Planted Area (ha) % of Total Araea Planted Households with Pigeon pea Average Planted Area per Household Babati 19,096 56,835 34 22,097 0.86 Hanang 1,391 58,469 2 3,137 0.44 Mbulu 21 39,557 0 86 0.24 Simanjiro 21 31,868 0 44 0.49 Kiteto 6,226 74,511 8 3,438 1.81 Total 26,755 261,239 10 28,801 0.93 District Planted Area (ha) Total Planted Area (ha) % of Total Araea Planted Households with Banana Average Planted Area per Household Babati 3,673 56,835 6 1,052 3.49 Hanang 28 58,469 0 312 0.09 Mbulu 332 39,557 1 1,043 0.32 Simanjiro 65 31,868 0 178 0.36 Kiteto 0 74,511 0 117 0.00 Total 4,098 261,239 2 2,701 1.52 Cont…. Area Planted by Crop Type - Manyara Region Pigeon pea Banana Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 177 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Pigeon Pea 3,198 0 558 22,999 26,755 Coffee 1,123 0 9 53 1,185 Sugarcane 0 0 0 9 9 Mpesheni 24 0 0 0 24 Banana 4,679 25 0 245 4,949 Avocado 61 0 0 0 61 Mango 51 0 0 19 70 Pawpaw 59 0 0 0 59 Orange 280 0 0 0 280 Mandarine/Tangerine 0 0 0 0 0 Guava 86 0 0 118 203 Apples 0 0 0 0 0 Pears 0 0 0 0 0 Lime/Lemon 55 0 0 9 64 Total 9,617 25 567 23,451 33,659 Crop Mostly Farm Yard Manure Total % Mpesheni 24 24 100 Avocado 61 61 100 Pawpaw 59 59 100 Orange 280 280 100 Coffee 1,123 1,185 95 Banana 4,679 4,949 95 Lime/Lemon 55 64 86 Mango 51 70 73 Guava 86 203 42 Pigeon Pea 3,198 26,755 12 Sugarcane 0 9 0 Mandarine/Tangerine 0 0 0 Apples 0 0 0 Pears 0 0 0 Total 9,617 33,659 29 Crop Mostly Compost Total % Banana 25 4,949 1 Pigeon Pea 0 26,755 0 Coffee 0 1,185 0 Sugarcane 0 9 0 Mpesheni 0 24 0 Avocado 0 61 0 Mango 0 70 0 Pawpaw 0 59 0 Orange 0 280 0 Mandarine/Tangerine 0 0 0 Guava 0 203 0 Apples 0 0 0 Pears 0 0 0 Lime/Lemon 0 64 0 Total 25 33,659 0 Crop Cont…. Area Planted by Crop Type - Manyara Region Fertiliser Use Cont…. Area Planted by Crop Type - Manyara Region Cont…. Area Planted by Crop Type - Manyara Region Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 178 Crop Mostly Inorganic Fertilizer Total % Pigeon Pea 558 26,755 2 Coffee 9 1,185 1 Sugarcane 0 9 0 Mpesheni 0 24 0 Banana 0 4,949 0 Avocado 0 61 0 Mango 0 70 0 Pawpaw 0 59 0 Orange 0 280 0 Mandarine/Tangerine 0 0 0 Guava 0 203 0 Apples 0 0 0 Pears 0 0 0 Lime/Lemon 0 64 0 Total 567 33,659 2 Cont…. Area Planted by Crop Type - Manyara Region Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 179 AGROPROCESSING Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 180 Number % Number % Number % Babati 44,721 96 1,914 4 46,635 100 Hanang 26,045 83 5,200 17 31,245 100 Mbulu 33,267 97 1,114 3 34,381 100 Simanjir o 8,163 50 8,201 50 16,364 100 Kiteto 23,975 94 1,594 6 25,569 100 Total 136,172 88 18,023 12 154,194 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other Total Babati 765 2,093 40,152 0 0 1,483 117 110 44,721 Hanang 155 391 23,921 0 0 1,578 0 0 26,045 Mbulu 774 83 26,288 87 86 5,949 0 0 33,267 Simanjir o 651 44 7,455 0 0 12 0 0 8,163 Kiteto 616 402 22,138 0 0 819 0 0 23,975 Total 2,962 3,013 119,955 87 86 9,842 117 110 136,172 Household / Human Consumptio n Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Other Total Maize 132,218 0 48 174 227 0 132,668 Paddy 2,771 0 25 0 0 0 2,796 Sorghum 6,653 0 80 0 0 0 6,733 Bulrush Millet 343 0 0 0 0 0 343 Finger Millet 1,158 0 70 0 0 0 1,227 Wheat 591 0 0 0 0 0 591 Beans 1,509 0 79 0 0 157 1,744 Pigeon Peas 189 0 0 0 0 0 189 Sunflower 993 0 512 0 79 157 1,741 Simsim 36 0 0 0 0 0 36 Groundnut 553 70 70 0 0 0 692 Coffee 0 0 173 0 0 0 173 Total 147,014 70 1,056 174 306 314 148,933 8.0b AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District District Method of Processing 8.0a AGRO PROCESSING: Did tthe Household Process any Of the Products Harvested District Did the Hh Process any of the products harvested during 2002 Households That Processed Product Households That Did Not Process Product Total 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop Crop Product Use Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 181 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Babati 357 0 117 0 0 0 0 14,209 30,038 44,721 Hanang 389 77 0 227 0 0 938 314 24,101 26,045 Mbulu 173 0 0 0 0 87 0 0 33,008 33,267 Simanjir o 209 178 0 0 0 0 0 49 7,727 8,163 Kiteto 403 65 0 0 121 0 330 1,110 21,946 23,975 Total 1,531 320 117 227 121 87 1,268 15,683 116,818 136,172 Flour / Meal Grain Oil Juice Fiber Other Total Babati 43,193 1,292 236 0 0 0 44,721 Hanang 24,966 771 308 0 0 0 26,045 Mbulu 31,192 1,911 79 85 0 0 33,267 Simanjir o 7,618 489 0 0 12 44 8,163 Kiteto 23,659 317 0 0 0 0 23,975 Total 130,628 4,780 623 85 12 44 136,172 Household / Human Consumptio n Sale Only Animal Consumptio n Did Not Use Total Babati 44,481 118 0 121 44,721 Hanang 25,887 80 0 79 26,045 Mbulu 33,093 0 174 0 33,267 Simanjir o 8,076 60 0 27 8,163 Kiteto 23,975 0 0 0 23,975 Total 135,512 258 174 227 136,172 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use 8.1.1c AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold District Main Product 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 182 Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 1,543 295 0 227 121 87 1,268 13,747 115,380 132,668 Paddy 117 25 117 0 0 0 469 592 1,475 2,796 Sorghum 87 0 0 0 0 0 0 3,594 3,052 6,733 Bulrush Millet 0 0 0 0 0 0 0 0 343 343 Finger Millet 139 0 0 0 0 0 0 314 774 1,227 Wheat 0 0 0 0 0 0 0 0 591 591 Beans 0 0 0 87 0 0 0 361 1,297 1,744 Pigeon Peas 0 0 0 0 0 0 0 0 189 189 Sunflower 87 0 0 0 0 0 85 793 776 1,741 Simsim 0 0 0 0 0 0 0 0 36 36 Groundnut 354 0 0 0 0 0 0 0 338 692 Coffee 0 0 86 87 0 0 0 0 0 173 Total 2,327 320 204 401 121 87 1,822 19,401 124,251 148,933 Bran Cake Husk Pulp Oil Shell No by- product Other Total Babati 2,649 118 118 0 0 0 41,710 125 44,721 Hanang 4,156 311 0 0 393 78 21,107 0 26,045 Mbulu 3,685 972 0 87 0 0 28,435 87 33,267 Simanjir o 682 36 230 0 43 0 7,172 0 8,163 Kiteto 2,446 0 0 0 65 70 21,354 41 23,975 Total 13,619 1,437 347 87 500 148 119,779 254 136,172 District By Product 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District 8.1.1f AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Crop Where Sold Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 183 STORAGE Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 184 In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Total Babati 20,493 1,208 114 20,580 251 0 0 42,646 Hanang 14,282 79 75 9,367 78 0 0 23,881 Mbulu 16,455 688 0 9,621 0 0 260 27,025 Simanjiro 405 487 45 5,706 170 0 48 6,860 Kiteto 4,316 206 0 17,781 69 277 191 22,840 Total 55,950 2,669 235 63,055 567 277 499 123,252 Less than 3 Months Between 3 and 6 Months Over 6 Months Total Babati 2,503 14,059 26,084 42,646 Hanang 3,084 11,106 9,691 23,881 Mbulu 5,463 15,782 5,780 27,025 Simanjiro 1,276 3,729 1,856 6,860 Kiteto 3,940 10,402 8,498 22,840 Total 16,266 55,077 51,909 123,252 Food for the Household To Sell for Higher Price Seeds for Planting Other Total Babati 41,128 1,040 478 0 42,646 Hanang 22,878 382 621 0 23,881 Mbulu 26,334 172 519 0 27,025 Simanjiro 6,097 12 751 0 6,860 Kiteto 22,205 510 59 66 22,840 Total 118,642 2,117 2,428 66 123,252 Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Babati 34,324 6,173 1,431 719 42,646 Hanang 17,621 3,850 929 1,481 23,881 Mbulu 23,547 2,388 833 257 27,025 Simanjiro 6,182 515 125 38 6,860 Kiteto 19,252 3,039 434 116 22,840 Total 100,924 15,964 3,753 2,611 123,252 9.2a CROP STORAGE: Number of Households Storing Crops By Method of Storage and District District Method of Storage 9.2b CROP STORAGE: Number of Households Storing Crops By 9.2dCROP STORAGE: Number of Households Storing Crops By Estimated District Estimate Storage Loss District Normal Duration of Storage 9.2c CROP STORAGE: Number of Households Storing Crops By Main Purpose District Main Purpose Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 185 Number % Number % Number % Number % Number % Number % Number % Number % Maize 19,637 48.7 1,083 2.7 114 0.3 19,261 47.7 251 0.6 0 0.0 0 0.0 40,345 100.0 Paddy 235 9.9 243 10.3 0 0.0 1,887 79.8 0 0.0 0 0.0 0 0.0 2,364 100.0 Sorghum & Millet 39,994 93.3 494 1.2 0 0.0 2,401 5.6 0 0.0 0 0.0 0 0.0 42,889 100.0 Beans & Pulses 7,446 40.2 107 0.6 104 0.6 10,737 58.0 125 0.7 0 0.0 0 0.0 18,519 100.0 Wheat 125 14.7 0 0.0 0 0.0 726 85.3 0 0.0 0 0.0 0 0.0 851 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 42,889 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 42,889 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 42,889 100.0 0 0.0 42,889 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 42,889 100.0 0 0.0 42,889 100.0 Groundnuts/ Bambara Nuts 480 56.1 251 29.3 0 0.0 125 14.6 0 0.0 0 0.0 0 0.0 857 100.0 Total 110,806 47.3 2,177 0.9 219 0.1 35,136 15.0 376 0.2 85,778 36.6 0 0.0 234,492 100.0 Maize 14,045 60.8 79 0.3 75 0.3 8,822 38.2 78 0.3 0 0.0 0 0.0 23,100 100.0 Paddy 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Sorghum & Millet 23,115 95.5 79 0.3 0 0.0 1,001 4.1 0 0.0 0 0.0 0 0.0 24,194 100.0 Beans & Pulses 4,565 32.5 79 0.6 75 0.5 9,242 65.8 0 0.0 0 0.0 79 0.6 14,039 100.0 Wheat 0 0.0 0 0.0 0 0.0 631 100.0 0 0.0 0 0.0 0 0.0 631 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 24,194 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 24,194 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 24,194 100.0 0 0.0 24,194 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 24,194 100.0 0 0.0 24,194 100.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 65,919 49.0 236 0.2 151 0.1 19,695 14.6 78 0.1 48,388 36.0 79 0.1 134,546 100.0 Maize 16,369 61.5 688 2.6 0 0.0 9,280 34.9 0 0.0 0 0.0 260 1.0 26,598 100.0 Paddy 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Sorghum & Millet 24,785 91.7 431 1.6 0 0.0 1,637 6.1 86 0.3 0 0.0 87 0.3 27,025 100.0 Beans & Pulses 9,754 45.6 517 2.4 0 0.0 11,019 51.5 0 0.0 0 0.0 87 0.4 21,377 100.0 Wheat 87 16.8 0 0.0 0 0.0 432 83.2 0 0.0 0 0.0 0 0.0 519 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 27,025 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 27,025 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 27,025 100.0 0 0.0 27,025 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 27,025 100.0 0 0.0 27,025 100.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 78,020 49.8 1,636 1.0 0 0.0 22,367 14.3 86 0.1 54,050 34.5 434 0.3 156,594 100.0 Maize 357 5.9 442 7.3 0 0.0 5,124 84.1 170 2.8 0 0.0 0 0.0 6,092 100.0 Paddy 0 0.0 0 0.0 0 0.0 179 100.0 0 0.0 0 0.0 0 0.0 179 100.0 Sorghum & Millet 6,817 99.4 0 0.0 0 0.0 44 0.6 0 0.0 0 0.0 0 0.0 6,860 100.0 Beans & Pulses 179 6.2 45 1.6 86 3.0 2,459 85.0 36 1.3 41 1.4 48 1.6 2,894 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 6,860 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 6,860 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 6,860 100.0 0 0.0 6,860 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 6,860 100.0 0 0.0 6,860 100.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 50 100.0 0 0.0 0 0.0 0 0.0 50 100.0 Total 14,213 38.8 487 1.3 86 0.2 7,855 21.4 206 0.6 13,762 37.5 48 0.1 36,657 100.0 Simanjiro Total Babati Hanang Mbulu 9.2 CROP STORAGE: Number of Households Storing Crops By Method of Storage and Crop Type Crop Method of Storage In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 186 Number % Number % Number % Number % Number % Number % Number % Number % Total 9.2 CROP STORAGE: Number of Households Storing Crops By Method of Storage and Crop Type Crop Method of Storage In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Maize 4,316 19.0 206 0.9 0 0.0 17,684 77.8 69 0.3 277 1.2 191 0.8 22,742 100.0 Paddy 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Sorghum & Millet 22,359 97.6 0 0.0 0 0.0 481 2.1 0 0.0 0 0.0 70 0.3 22,909 100.0 Beans & Pulses 336 15.7 69 3.2 0 0.0 1,737 81.1 0 0.0 0 0.0 0 0.0 2,142 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 22,909 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 22,909 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 22,909 100.0 0 0.0 22,909 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 22,909 100.0 0 0.0 22,909 100.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 731 100.0 0 0.0 0 0.0 0 0.0 731 100.0 Total 49,921 42.6 275 0.2 0 0.0 20,631 17.6 69 0.1 46,095 39.3 261 0.2 117,252 100.0 Maize 54,725 46.0 2,498 2.1 190 0.2 60,169 50.6 567 0.5 277 0.2 452 0.4 118,877 100.0 Paddy 235 9.2 243 9.6 0 0.0 2,066 81.2 0 0.0 0 0.0 0 0.0 2,543 100.0 Sorghum & Millet 117,069 94.5 1,003 0.8 0 0.0 5,563 4.5 86 0.1 0 0.0 156 0.1 123,878 100.0 Beans & Pulses 22,279 37.8 818 1.4 266 0.5 35,193 59.7 162 0.3 41 0.1 213 0.4 58,971 100.0 Wheat 212 10.6 0 0.0 0 0.0 1,788 89.4 0 0.0 0 0.0 0 0.0 2,000 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 123,878 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 123,878 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 123,878 100.0 0 0.0 123,878 100.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 123,878 100.0 0 0.0 123,878 100.0 Groundnuts/ Bambara Nuts 480 29.3 251 15.3 0 0.0 906 55.3 0 0.0 0 0.0 0 0.0 1,638 100.0 Total 318,879 46.9 4,812 0.7 456 0.1 105,685 15.6 815 0.1 248,073 36.5 821 0.1 679,541 100.0 Kiteto Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 187 MARKETING Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 188 Number % Number % Number % Babati 37,585 80.6 9,050 19.4 46,635 100.0 Hanang 16,241 52.0 15,004 48.0 31,245 100.0 Mbulu 16,476 47.9 17,906 52.1 34,381 100.0 Simanjiro 3,843 23.5 12,521 76.5 16,364 100.0 Kiteto 13,977 54.7 11,593 45.3 25,569 100.0 Total 88,121 57.1 66,073 42.9 154,194 100.0 Open Market Price Too Low No Transport Transport Cost Too High No Buyer Market too Far Farmers Association Problems Trade Union Problems Government Regulatory Board Problems Lack of Market Information Other Not applicable Total Babati 13,277 2,214 1,663 125 1,887 110 0 125 1,978 0 16,206 37,585 Hanang 6,204 476 471 160 708 0 0 0 230 0 7,993 16,241 Mbulu 4,062 3,101 609 0 3,631 0 0 0 86 0 4,986 16,476 Simanjiro 1,265 72 378 45 374 0 0 0 82 86 1,541 3,843 Kiteto 8,548 445 877 557 1,913 0 70 0 348 69 1,149 13,977 Total 33,357 6,308 3,998 886 8,513 110 70 125 2,725 155 31,875 88,121 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Other Not applicable Total Babati 723 10,991 117 0 343 125 541 32,217 45,058 Hanang 63 12,593 0 75 0 311 2,239 14,883 30,164 Mbulu 319 17,051 0 0 0 247 156 15,418 33,191 Simanjiro 50 5,666 0 0 35 0 3,148 7,309 16,208 Kiteto 431 9,372 68 0 0 0 1,203 14,427 25,501 Total 1,586 55,673 185 75 379 684 7,286 84,254 150,123 10.3 MARETING: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By District Main Reasons for Not Selling Crops 10.2 MARKETING: Number of Households Reporting Selling Crop By Main Marketing Problem By District District Main Problem 10.1 MARETING: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District District Did the Hh Sell any Crops from the 2002/03 season? Number of Households that Number of Households Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 189 IRRIGATION/ EROSION CONTROL Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 190 Total Number of Household % Number of Household % Number of Household Babati 2,928 6.3 43,707 93.7 46,635 Hanang 150 0.5 31,095 99.5 31,245 Mbulu 2,185 6.4 32,197 93.6 34,381 Simanjiro 1,251 7.6 15,113 92.4 16,364 Kiteto 60 0.2 25,509 99.8 25,569 Total 6,574 4.3 147,620 95.7 154,194 District Irrigatable Area Area Irrigated Land this Year % Babati 1,756 1,659 94 Hanang 128 128 100 Mbulu 878 674 77 Simanjiro 1,779 1,280 72 Kiteto 24 10 40 Total 4,565 3,751 82 River Dam Well Borehole Canal Pipe water Total Babati 2,224 118 117 234 235 0 2,928 Hanang 0 0 0 0 150 0 150 Mbulu 1,324 0 260 87 513 0 2,185 Simanjiro 1,029 0 0 0 221 0 1,251 Kiteto 0 0 0 0 0 60 60 Total 4,578 118 378 321 1,120 60 6,574 Gravity Hand Bucket Motor Pump Total Babati 2,577 352 0 2,928 Hanang 150 0 0 150 Mbulu 972 1,212 0 2,185 Simanjiro 1,215 0 36 1,251 Kiteto 0 60 0 60 Total 4,914 1,624 36 6,574 District Households Practicing Irrigation Households not Practicing Irrigation Table 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By Does the Household Practice Irrigation? 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water 11.2: IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 191 Flood Bucket / Watering Can Total Babati 2,577 352 2,928 Hanang 150 0 150 Mbulu 972 1,212 2,185 Simanjiro 1,251 0 1,251 Kiteto 0 60 60 Total 4,950 1,624 6,574 Does Not Have Facility Total Number % Number % Number Babati 11,805 25 34,829 75 46,635 Hanang 3,417 11 27,828 89 31,245 Mbulu 6,626 19 27,755 81 34,381 Simanjiro 655 4 15,709 96 16,364 Kiteto 983 4 24,586 96 25,569 Total 23,486 15 130,708 85 154,194 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Babati . 24,504 469 4,986 1,457 18,661 861 . 50,938 Hanang 75 7,952 . 779 226 1,887 1,021 . 11,941 Mbulu . 18,858 609 4,896 314 5,686 3,125 84 33,573 Simanjiro 382 4,968 . 191 955 922 650 . 8,068 Kiteto 113 2,933 . 117 350 139 271 65 3,988 Total 571 59,216 1,078 10,969 3,302 27,296 5,927 149 108,509 11.5: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control District Method of Application District Have facility Does the Household Have Any Erosion Control/Water 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census 2003 Manyara Region 192 Appendix ii 193 ACCESS TO FARM INPUTS/ IMPLEMENTS Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 194 Number % Number % Number % Babati 0 0 46,635 100 46,635 100 Hanang 309 1 30,936 99 31,245 100 Mbulu 0 0 34,381 100 34,381 100 Simanjiro 660 4 15,705 96 16,364 100 Kiteto 0 0 25,569 100 25,569 100 Total 969 1 153,226 99 154,194 100 Number % Number % Number % Babati 20,502 44 26,133 56 46,635 100 Hanang 8,242 26 23,002 74 31,245 100 Mbulu 26,666 78 7,715 22 34,381 100 Simanjiro 2,015 12 14,377 88 16,392 100 Kiteto 1,093 4 24,517 96 25,610 100 Total 58,519 38 95,744 62 154,263 100 Number % Number % Number % Babati 445 1 46,189 99 46,635 100 Hanang 1,937 6 29,308 94 31,245 100 Mbulu 696 2 33,686 98 34,381 100 Simanjiro 163 1 16,202 99 16,364 100 Kiteto 194 1 25,375 99 25,569 100 Total 3,434 2 150,760 98 154,194 100 Number % Number % Number % Babati 3,593 8 43,042 92 46,635 100 Hanang 1,879 6 29,366 94 31,245 100 Mbulu 1,624 5 32,757 95 34,381 100 Simanjiro 1,198 7 15,166 93 16,364 100 Kiteto 958 4 24,612 96 25,569 100 Total 9,252 6 144,942 94 154,194 100 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 195 Number % Number % Number % Babati 724 2 45,910 98 46,635 100 Hanang 634 2 30,611 98 31,245 100 Mbulu 0 0 34,381 100 34,381 100 Simanjiro 265 2 16,072 98 16,336 100 Kiteto 67 0 25,502 100 25,569 100 Total 1,691 1 152,476 99 154,166 100 Number % Number % Number % Babati 6,867 15 39,768 85 46,635 100 Hanang 1,935 6 29,310 94 31,245 100 Mbulu 4,965 14 29,417 86 34,381 100 Simanjiro 3,686 23 12,678 77 16,364 100 Kiteto 3,040 12 22,488 88 25,528 100 Total 20,492 13 133,661 87 154,153 100 Number % Number % Number % Babati 0 0 46,635 100 46,635 100 Hanang 309 1 30,936 99 31,245 100 Mbulu 0 0 34,381 100 34,381 100 Simanjiro 660 4 15,668 96 16,328 100 Kiteto 0 0 25,569 100 25,569 100 Total 969 1 153,190 99 154,158 100 Number % Number % Number % Number % Number % Babati 113 0 0 0 117 0 0 0 0 0 Hanang 0 0 0 0 80 0 78 0 78 0 Mbulu 86 0 87 0 174 1 84 0 0 0 Simanjiro 0 0 0 0 75 0 0 0 0 0 Kiteto 70 0 0 0 67 0 0 0 0 0 Total 269 0 87 0 514 0 163 0 78 0 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Local Market / Trade Store Not applicable Total District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 196 Number % Number % Number % Number % Number % Number % Babati 0 0 1,337 3 16,875 36 2,060 4 26,133 56 46,635 100 Hanang 78 0 0 0 6,601 21 1,326 4 23,002 74 31,245 100 Mbulu 0 0 349 1 22,124 64 3,762 11 7,715 22 34,381 100 Simanjiro 0 0 0 0 1,676 10 265 2 14,341 88 16,356 100 Kiteto 0 0 0 0 622 2 335 1 24,517 96 25,610 100 Total 78 0 1,686 1 47,897 31 7,747 5 95,708 62 154,227 100 Number % Number % Number % Number % Number % Number % Babati 0 0 125 0 320 1 0 0 46,189 99 46,635 100 Hanang 78 0 0 0 759 2 1,099 4 29,308 94 31,245 100 Mbulu 0 0 0 0 696 2 0 0 33,686 98 34,381 100 Simanjiro 0 0 0 0 117 1 46 0 16,165 99 16,328 100 Kiteto 0 0 0 0 57 0 137 1 25,375 99 25,569 100 Total 78 0 125 0 1,948 1 1,282 1 150,724 98 154,158 100 Number % Number % Number % Number % Number % Number % Number % Babati 125 0 3,004 6 0 0 104 0 359 1 43,042 92 46,635 100 Hanang 0 0 1,879 6 0 0 0 0 0 0 29,366 94 31,245 100 Mbulu 0 0 1,540 4 84 0 0 0 0 0 32,757 95 34,381 100 Simanjiro 0 0 1,198 7 0 0 0 0 0 0 15,129 93 16,328 100 Kiteto 0 0 540 2 278 1 0 0 139 1 24,612 96 25,569 100 Total 125 0 8,161 5 363 0 104 0 498 0 144,906 94 154,158 100 Number % Number % Number % Babati 724 2 45,910 98 46,635 100 Hanang 634 2 30,611 98 31,245 100 Mbulu 0 0 34,381 100 34,381 100 Simanjiro 265 2 16,035 98 16,300 100 Kiteto 67 0 25,502 100 25,569 100 Total 1,691 1 152,439 99 154,130 100 Crop Buyers Large Scale Locally Neighbour Not applicable cont…. ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Total District 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Neighbour Not applicable Total 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Crop Buyers Large Scale Farm y Produced by Household Total District Co-operative Local Market / Trade Store Secondary Market Large Scale Farm y Produced by Household Not applicable 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year District Local Market / Trade Store Not applicable Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 197 Number % Number % Number % Number % Number % Number % Babati 117 0 0 0 5,878 13 0 0 209 0 117 0 Hanang 0 0 0 0 1,781 6 0 0 0 0 0 0 Mbulu 0 0 0 0 4,532 13 84 0 87 0 0 0 Simanjiro 0 0 77 0 2,635 16 107 1 62 0 143 1 Kiteto 126 0 134 1 1,385 5 0 0 66 0 187 1 Total 244 0 210 0 16,210 11 192 0 424 0 446 0 Number % Number % Number % Number % Number % Babati 104 0 0 0 442 1 39,768 85 46,635 100 Hanang 0 0 77 0 77 0 29,310 94 31,245 100 Mbulu 0 0 87 0 174 1 29,417 86 34,381 100 Simanjiro 12 0 326 2 324 2 12,678 77 16,364 100 Kiteto 70 0 567 2 506 2 22,488 88 25,528 100 Total 186 0 1,057 1 1,522 1 133,661 87 154,153 100 Number % Number % Number % Number % Hanang 155 50 0 0 153 50 309 100 Simanjiro 0 0 18 3 642 97 660 100 Total 155 16 18 2 796 82 969 100 Number % Number % Number % Number % Number % Number % Babati 19,805 97 347 2 125 1 224 1 0 0 20,502 100 Hanang 7,700 93 462 6 0 0 80 1 0 0 8,242 100 Mbulu 24,716 93 1,288 5 578 2 84 0 0 0 26,666 100 Simanjiro 1,861 92 94 5 12 1 48 2 0 0 2,015 100 Kiteto 961 88 65 6 0 0 0 0 67 6 1,093 100 Total 55,043 94 2,257 4 715 1 436 1 67 0 58,519 100 Not applicable Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Between 3 and 10 km Large Scale Locally 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Total Development Project Less than 1 km Between 1 and 3 km 20 km and Above Neighbour Co-operative Local Farmers Group 20 km and Above Between 1 and 3 km Total Crop Buyers Local Market / Trade Store Secondary Market cont…. ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 10 and 20 km Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 198 Number % Number % Number % Babati 445 100 0 0 445 100 Hanang 1,862 96 75 4 1,937 100 Mbulu 696 100 0 0 696 100 Simanjiro 163 100 0 0 163 100 Kiteto 194 100 0 0 194 100 Total 3,360 98 75 2 3,434 100 Number % Number % Number % Number % Number % Number % Babati 589 16 468 13 1,457 41 711 20 368 10 3,593 100 Hanang 80 4 391 21 868 46 310 17 229 12 1,879 100 Mbulu 86 5 419 26 602 37 347 21 169 10 1,624 100 Simanjiro 41 3 18 1 51 4 51 4 1,037 87 1,198 100 Kiteto 267 28 208 22 139 15 137 14 206 22 958 100 Total 1,064 12 1,504 16 3,117 34 1,557 17 2,009 22 9,252 100 Number % Number % Number % Number % Number % Number % Babati 0 0 239 33 0 0 364 50 121 17 724 100 Hanang 80 13 321 51 233 37 0 0 0 0 634 100 Simanjiro 0 0 0 0 0 0 0 0 265 100 265 100 Kiteto 0 0 0 0 0 0 0 0 67 100 67 100 Total 80 5 560 33 233 14 364 22 453 27 1,691 100 Number % Number % Number % Number % Number % Number % Babati 976 14 1,061 15 1,738 25 1,683 25 1,409 21 6,867 100 Hanang 229 12 312 16 153 8 542 28 699 36 1,935 100 Mbulu 1,299 26 860 17 575 12 1,209 24 1,021 21 4,965 100 Simanjiro 1,246 34 62 2 191 5 488 13 1,699 46 3,686 100 Kiteto 1,290 42 457 15 652 21 250 8 390 13 3,040 100 Total 5,040 25 2,752 13 3,309 16 4,174 20 5,218 25 20,492 100 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Total 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 199 Number % Number % Number % Number % Hanang 309 100 0 0 0 0 309 100 Simanjiro 350 53 274 42 36 5 660 100 Total 659 68 274 28 36 4 969 100 Number % Number % Number % Number % Number % Number % Number % Babati 17,612 86 1,704 8 239 1 0 0 339 2 608 3 20,502 100 Hanang 6,844 83 776 9 78 1 0 0 0 0 545 7 8,242 100 Mbulu 20,685 78 1,189 4 169 1 160 1 1,047 4 3,416 13 26,666 100 Simanjiro 796 40 225 11 98 5 0 0 0 0 896 44 2,015 100 Kiteto 726 66 41 4 0 0 0 0 326 30 0 0 1,093 100 Total 46,663 80 3,935 7 585 1 160 0 1,712 3 5,465 9 58,519 100 Number % Number % Number % Number % Babati 445 100 0 0 0 0 445 100 Hanang 1,860 96 0 0 77 4 1,937 100 Mbulu 609 88 87 12 0 0 696 100 Simanjiro 163 100 0 0 0 0 163 100 Kiteto 194 100 0 0 0 0 194 100 Total 3,271 95 87 3 77 2 3,434 100 Number % Number % Number % Number % Number % Babati 2,987 83 480 13 125 3 0 0 3,593 100 Hanang 1,724 92 80 4 0 0 75 4 1,879 100 Mbulu 1,194 74 430 26 0 0 0 0 1,624 100 Simanjiro 801 67 362 30 0 0 36 3 1,198 100 Kiteto 619 65 338 35 0 0 0 0 958 100 Total 7,325 79 1,690 18 125 1 111 1 9,252 100 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year District Sale of Farm Products generating activities Other Total 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm District Sale of Farm Products generating activities Remittances Bank Loan Produced on form Other Total 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households District Sale of Farm Bank Loan Other Total 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year District Sale of Farm Products generating activities Remittances Other Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 200 Number % Number % Number % Babati 724 100 0 0 724 100 Hanang 557 88 78 12 634 100 Simanjiro 252 95 12 5 265 100 Kiteto 67 100 0 0 67 100 Total 1,601 95 90 5 1,691 100 Number % Number % Number % Number % Number % Number % Number % Babati 5,083 74 1,680 24 0 0 104 2 0 0 0 0 6,867 100 Hanang 1,554 80 228 12 0 0 0 0 0 0 152 8 1,935 100 Mbulu 2,998 60 1,546 31 0 0 0 0 0 0 420 8 4,965 100 Simanjiro 2,036 55 1,215 33 89 2 0 0 36 1 310 8 3,686 100 Kiteto 1,756 58 1,227 40 0 0 0 0 57 2 0 0 3,040 100 Total 13,427 66 5,897 29 89 0 104 1 93 0 883 4 20,492 100 Number % Number % Number % Number % Number % Number % Number % Number % Babati 4,052 9 28,070 60 698 1 233 1 1,808 4 9,979 21 1,795 4 46,635 100 Hanang 6,768 22 14,498 47 1,463 5 79 0 2,632 9 4,550 15 947 3 30,936 100 Mbulu 5,244 15 23,903 70 86 0 0 0 1,810 5 2,664 8 674 2 34,381 100 Simanjiro 2,062 13 6,739 43 608 4 324 2 1,405 9 3,815 24 753 5 15,705 100 Kiteto 12,017 47 2,861 11 277 1 0 0 1,306 5 8,569 34 539 2 25,569 100 Total 30,142 20 76,070 50 3,132 2 637 0 8,961 6 29,577 19 4,707 3 153,226 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Babati 13,073 50 3,099 12 3,419 13 1,659 6 846 3 2,150 8 243 1 1,643 6 26,133 100 Hanang 4,723 21 1,318 6 9,504 41 395 2 3,050 13 2,837 12 78 0 1,098 5 23,002 100 Mbulu 1,863 24 2,245 29 2,411 31 0 0 0 0 518 7 0 0 678 9 7,715 100 Simanjiro 662 5 1,522 11 3,604 25 520 4 3,589 25 3,780 26 36 0 663 5 14,377 100 Kiteto 1,644 7 1,486 6 8,528 35 3,120 13 2,333 10 7,234 30 0 0 173 1 24,517 100 Total 21,966 23 9,670 10 27,465 29 5,693 6 9,817 10 16,519 17 358 0 4,256 4 95,744 100 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year District Sale of Farm Products generating activities Total 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year District Sale of Farm Products generating activities Remittances Bank Loan Produced on form Other Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use y Produced by Household Other Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 201 Number % Number % Number % Number % Number % Number % Number % Number % Number % Babati 5,980 13 4,790 10 23,182 50 1,117 2 4,870 11 4,322 9 112 0 1,818 4 46,189 100 Hanang 3,004 10 1,648 6 10,807 37 782 3 10,362 35 2,319 8 0 0 387 1 29,308 100 Mbulu 3,841 11 10,536 31 7,341 22 87 0 7,599 23 1,588 5 84 0 2,609 8 33,686 100 Simanjiro 487 3 1,387 9 3,934 24 679 4 4,905 30 4,056 25 0 0 753 5 16,202 100 Kiteto 1,096 4 1,344 5 7,351 29 2,580 10 4,946 19 7,529 30 0 0 528 2 25,375 100 Total 14,408 10 19,704 13 52,615 35 5,245 3 32,682 22 19,814 13 196 0 6,096 4 150,760 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Babati 1,431 3 30,841 72 772 2 241 1 1,661 4 6,417 15 0 0 1,679 4 43,042 100 Hanang 2,111 7 15,727 54 1,699 6 78 0 2,896 10 6,384 22 0 0 470 2 29,366 100 Mbulu 1,879 6 23,909 73 259 1 0 0 1,557 5 3,633 11 174 1 1,345 4 32,757 100 Simanjiro 854 6 8,151 54 728 5 238 2 1,249 8 3,103 20 0 0 842 6 15,166 100 Kiteto 4,907 20 10,477 43 439 2 342 1 2,159 9 5,909 24 0 0 380 2 24,612 100 Total 11,182 8 89,105 61 3,898 3 898 1 9,523 7 25,446 18 174 0 4,716 3 144,942 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Babati 1,765 4 29,121 63 532 1 110 0 5,046 11 7,755 17 0 0 1,582 3 45,910 100 Hanang 1,798 6 13,569 44 1,461 5 158 1 5,771 19 7,386 24 0 0 468 2 30,611 100 Mbulu 1,633 5 21,173 62 340 1 0 0 4,350 13 5,439 16 87 0 1,359 4 34,381 100 Simanjiro 782 5 7,549 47 729 5 182 1 2,236 14 3,715 23 37 0 842 5 16,072 100 Kiteto 5,312 21 9,671 38 370 1 207 1 2,577 10 6,385 25 0 0 981 4 25,502 100 Total 11,289 7 81,083 53 3,431 2 657 0 19,980 13 30,679 20 124 0 5,232 3 152,476 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Babati 1,685 4 34,201 86 315 1 228 1 462 1 1,059 3 486 1 1,332 3 39,768 100 Hanang 3,012 10 22,697 77 894 3 0 0 1,837 6 711 2 80 0 79 0 29,310 100 Mbulu 941 3 26,138 89 174 1 0 0 515 2 432 1 0 0 1,216 4 29,417 100 Simanjiro 1,485 12 9,331 74 621 5 45 0 355 3 130 1 0 0 711 6 12,678 100 Kiteto 5,289 24 13,356 59 577 3 69 0 417 2 2,545 11 126 1 109 0 22,488 100 Total 12,412 9 105,723 79 2,581 2 342 0 3,587 3 4,877 4 692 1 3,447 3 133,661 100 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use y Produced by Household Other Total 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use y Produced by Household Other Total 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use y Produced by Household Total Other Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Other Do not Know How to Use Input is of No Use y Produced by Household Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 202 Number % Number % Number % Number % Hanang 0 0 309 100 0 0 309 100 Simanjiro 75 11 326 49 259 39 660 100 Total 75 8 635 66 259 27 969 100 Number % Number % Number % Number % Number % Babati 3,931 19 15,475 75 1,096 5 0 0 20,502 100 Hanang 3,355 41 3,960 48 928 11 0 0 8,242 100 Mbulu 8,252 31 12,177 46 6,067 23 170 1 26,666 100 Simanjiro 608 30 614 30 755 37 38 2 2,015 100 Kiteto 527 48 566 52 0 0 0 0 1,093 100 Total 16,673 28 32,793 56 8,845 15 208 0 58,519 100 Number % Number % Number % Number % Babati 219 49 104 23 122 27 445 100 Hanang 302 16 1,480 76 155 8 1,937 100 Mbulu 87 13 87 12 522 75 696 100 Simanjiro 44 27 118 73 0 0 163 100 Kiteto 0 0 194 100 0 0 194 100 Total 653 19 1,983 58 799 23 3,434 100 Number % Number % Number % Number % Number % Babati 1,046 29 2,066 58 355 10 125 3 3,593 100 Hanang 628 33 1,020 54 231 12 0 0 1,879 100 Mbulu 334 21 948 58 342 21 0 0 1,624 100 Simanjiro 168 14 777 65 253 21 0 0 1,198 100 Kiteto 347 36 472 49 139 15 0 0 958 100 Total 2,523 27 5,284 57 1,320 14 125 1 9,252 100 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Total Good Average Excellent Good Average Poor District Excellent 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Does not Work Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 203 Number % Number % Number % Number % Babati 603 83 121 17 0 0 724 100 Hanang 80 13 554 87 0 0 634 100 Simanjiro 109 41 144 54 12 5 265 100 Kiteto 0 0 67 100 0 0 67 100 Total 792 47 887 52 12 1 1,691 100 Number % Number % Number % Number % Number % Babati 2,219 32 3,621 53 815 12 212 3 6,867 100 Hanang 1,473 76 461 24 0 0 0 0 1,935 100 Mbulu 2,320 47 2,123 43 521 10 0 0 4,965 100 Simanjiro 1,011 27 2,039 55 587 16 48 1 3,686 100 Kiteto 459 15 2,110 69 472 16 0 0 3,040 100 Total 7,482 37 10,355 51 2,395 12 261 1 20,492 100 Number % Number % Number % Babati 1,585 3 45,050 97 46,635 100 Hanang 543 2 30,702 98 31,245 100 Mbulu 339 1 34,042 99 34,381 100 Simanjiro 1,596 10 14,768 90 16,364 100 Kiteto 227 1 25,343 99 25,569 100 Total 4,290 3 149,904 97 154,194 100 Number % Number % Number % Babati 28,401 61 18,234 39 46,635 100 Hanang 15,539 50 15,705 50 31,245 100 Mbulu 28,958 84 5,424 16 34,381 100 Simanjiro 7,972 49 8,420 51 16,392 100 Kiteto 3,080 12 22,530 88 25,610 100 Total 83,951 54 70,312 46 154,263 100 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Excellent Good Poor Total 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 204 Number % Number % Number % Babati 3,445 7 43,190 93 46,635 100 Hanang 3,815 12 27,430 88 31,245 100 Mbulu 2,332 7 32,049 93 34,381 100 Simanjiro 920 6 15,444 94 16,364 100 Kiteto 965 4 24,605 96 25,569 100 Total 11,477 7 142,718 93 154,194 100 Number % Number % Number % Babati 5,840 13 40,795 87 46,635 100 Hanang 5,829 19 25,416 81 31,245 100 Mbulu 2,633 8 31,748 92 34,381 100 Simanjiro 6,000 37 10,364 63 16,364 100 Kiteto 4,961 19 20,608 81 25,569 100 Total 25,263 16 128,932 84 154,194 100 Number % Number % Number % Babati 2,626 6 44,009 94 46,635 100 Hanang 1,579 5 29,665 95 31,245 100 Mbulu 173 1 34,208 99 34,381 100 Simanjiro 1,660 10 14,676 90 16,336 100 Kiteto 672 3 24,897 97 25,569 100 Total 6,712 4 147,455 96 154,166 100 Number % Number % Number % Babati 17,452 37 29,183 63 46,635 100 Hanang 11,490 37 19,755 63 31,245 100 Mbulu 7,552 22 26,829 78 34,381 100 Simanjiro 11,371 69 4,993 31 16,364 100 Kiteto 6,511 26 19,017 74 25,528 100 Total 54,376 35 99,777 65 154,153 100 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Agricultural Households Agricultural Households Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 205 AGRICULTURE CREDIT Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 206 Number % Number % Number % Babati 0 0 94 100 94 100 Hanang 74 100 0 0 74 100 Simanjiro 41 42 56 58 97 100 Total 114 43 150 57 264 100 Family, Friend and Relative Other Total Babati 0 94 94 Hanang 74 0 74 Simanjiro 97 0 97 Total 170 94 264 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Babati 3,205 7,335 3,519 698 16,199 581 454 115 14,435 46,541 Hanang 624 5,765 3,017 782 11,577 370 80 151 8,806 31,171 Mbulu 974 7,404 1,387 0 8,530 174 73 86 15,753 34,381 Simanjiro 816 834 1,132 261 9,042 91 129 130 3,833 16,268 Kiteto 458 4,581 1,590 372 9,350 826 66 0 8,326 25,569 Total 6,077 25,919 10,645 2,113 54,697 2,043 802 482 51,153 153,930 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Livestock Other Total Credits Babati 0 0 0 0 0 0 94 94 Hanang 74 74 0 0 74 74 0 295 Simanjiro 69 41 28 28 0 0 69 234 Total Credits 142 114 28 28 74 74 163 623 13.2a AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District District Male Female Total 13.2b AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District District Source of Credit 13.2c AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District District Reason for Not Using Credit 13.2d AGRICULTURE CREDIT: Number of Credit Facilities Received By Main Purpose of Credit and District District Credit Use Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 207 T TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 208 Number % Number % Number % Babati 7,824 17 38,811 83 46,635 100 Hanang 1,227 4 30,018 96 31,245 100 Mbulu 3,348 10 31,033 90 34,381 100 Simanjiro 541 3 15,823 97 16,364 100 Kiteto 570 2 24,999 98 25,569 100 Total 13,510 9 140,684 91 154,194 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Babati 5,893 147,058 1,507 21,040 424 38,787 7,824 206,885 Hanang 931 16,688 232 5,702 63 22,225 1,227 44,614 Mbulu 1,803 94,189 430 28,615 1,115 403,255 3,348 526,058 Simanjiro 541 19,842 0 . 0 . 541 19,842 Kiteto 376 5,709 136 2,914 58 466 570 9,089 Total 9,544 283,485 2,305 58,270 1,661 464,733 13,510 806,488 District Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Terminalia Catapa Leucena Spp Syszygium Spp Azadritacht a Spp Jakaranda Spp Albizia Spp Moringa Spp Babati 16,818 110,504 2,890 . 440 1,100 117 9,417 . 702 188 64,356 352 Hanang 1,913 38,996 . . 1,507 . . . . 1,884 314 . . Mbulu . 341,010 . 6,621 91,708 86,720 . . . . . . . Simanjiro 6,240 73 . 2,112 422 . . 2,522 73 8,400 . . . Kiteto 4,615 113 . . 794 . 337 2,403 527 300 . . . Total 29,586 490,696 2,890 8,732 94,871 87,820 454 14,342 599 11,287 502 64,356 352 14.1 ON FARM TREE FARMING: Number of Households Having Planted Trees By District District Did your Hh have any Planted Trees on your land during 2002/ Households Having Planted Trees Households Not Having Planted Trees Total 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Where Planted Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total 14.3 ON FARM TREE PLANTING: Number of Planted Trees By Species and District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 209 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Babati 6,432 911 1,668 832 333 0 10,175 Hanang 841 0 235 229 314 0 1,620 Mbulu 2,856 687 1,099 0 0 0 4,642 Simanjiro 159 45 156 374 49 0 783 Kiteto 0 0 371 184 192 60 807 Total 10,288 1,644 3,528 1,619 889 60 18,028 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Babati 1,429 2,355 5,449 941 0 0 10,175 Hanang 239 75 1,153 154 0 0 1,620 Mbulu 770 1,360 2,165 260 0 0 4,556 Simanjiro 45 49 244 290 83 73 783 Kiteto 60 186 184 377 0 0 807 Total 2,544 4,025 9,195 2,021 83 73 17,941 Number % Number % Number % Babati 7,739 17 38,895 83 46,635 100 Hanang 1,183 4 29,982 96 31,165 100 Mbulu 5,445 16 28,936 84 34,381 100 Simanjiro 131 1 16,205 99 16,336 100 Kiteto 139 1 25,102 99 25,241 100 Total 14,637 10 139,121 90 153,758 100 14.4 TREE FARMING: Main Use of Trees By District District Main Use 14.5 TREE FARMING: Second Use of Trees By District District Second Use 14.6 TREE FARMING: Number of Households By Whether Village Have a Community Tree Planting Scheme By District District does your village have a Community Tree Planting Scheme Have a Community Tree Planting Scheme Does not Have a Community Tree Planting Scheme Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 210 0-9 1-19 21-29 30-39 40-49 60+ Total Babati 4,703 660 94 336 497 1,449 7,739 Hanang 621 401 160 0 0 0 1,183 Mbulu 1,986 1,459 608 523 521 348 5,445 Simanjiro 62 27 0 0 0 42 131 Kiteto 0 139 0 0 0 0 139 Total 7,372 2,687 862 859 1,018 1,840 14,637 Poles Timber Logs Charcoal Firewood Not Ready to Use Not Allowed to Use Other Total Babati 1,470 112 114 1,830 2,059 2,154 0 7,739 Hanang 401 0 0 401 300 0 80 1,183 Mbulu 1,633 1,905 84 84 871 783 84 5,445 Simanjiro 12 0 0 0 27 91 0 131 Kiteto 0 0 0 0 139 0 0 139 Total 3,516 2,017 198 2,316 3,396 3,029 165 14,637 District Main use during 2002/03 14.7 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) 14.8 TREE FARMING: Number of Households Involved in Community Tree Planting Scheme By Main Use and District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 211 CROP EXTENTION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 212 Number % Number % Number % Babati 14,204 30.5 32,431 70 46,635 100 Hanang 9,505 30.4 21,739 70 31,245 100 Mbulu 4,782 13.9 29,599 86 34,381 100 Simanjiro 5,147 31.5 11,217 69 16,364 100 Kiteto 5,073 19.8 20,496 80 25,569 100 Total 38,712 25.1 115,482 75 154,194 100 Number % Number % Number % Number % Number % Number % Babati 942 6.6 9,758 68.7 1,866 13.1 1,282 9.0 357 2.5 14,204 100.0 Hanang 1,558 17.5 4,250 47.8 2,770 31.2 311 3.5 0 0.0 8,889 100.0 Mbulu 591 12.4 1,141 23.9 2,795 58.5 255 5.3 0 0.0 4,782 100.0 Simanjiro 1,194 23.2 3,138 61.0 816 15.8 0 0.0 0 0.0 5,147 100.0 Kiteto 765 15.1 3,321 65.5 988 19.5 0 0.0 0 0.0 5,073 100.0 Total 5,049 13.3 21,608 56.7 9,235 24.2 1,847 4.8 357 0.9 38,095 100.0 Number % Number % Number % Number % Number % Number % Number % Babati 13,550 96.9 428 3.1 0 0.0 0 0.0 0 0.0 0 0.0 13,979 100.0 Hanang 8,496 98.2 79 0.9 0 0.0 0 0.0 0 0.0 75 0.9 8,650 100.0 Mbulu 4,698 98.2 0 0.0 0 0.0 0 0.0 84 1.8 0 0.0 4,782 100.0 Simanjiro 4,572 90.4 313 6.2 0 0.0 170 3.4 0 0.0 0 0.0 5,055 100.0 Kiteto 4,084 80.5 336 6.6 178 3.5 239 4.7 126 2.5 110 2.2 5,073 100.0 Total 35,400 94.3 1,156 3.1 178 0.5 410 1.1 210 0.6 185 0.5 37,539 100.0 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District District Did your Hh receive extension advice for crop production dur Households Receiving Households Not Receiving Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services By District District Quality of service Very Good Good Average Poor No Good Total 15.3 EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District District Source of Crop Extension Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 213 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Government NGO / Development Project Large Scale Farm Not applicable Total Babati 12,597 222 0 0 0 0 12,819 2,580 0 0 0 2,580 Hanang 7,563 79 0 0 0 75 7,717 3,133 0 0 151 3,285 Mbulu 4,436 0 0 0 84 0 4,521 3,688 0 0 0 3,688 Simanjiro 3,626 224 0 86 0 0 3,936 1,220 12 41 44 1,318 Kiteto 3,491 336 121 0 70 41 4,059 1,333 134 0 109 1,577 Total 31,713 861 121 86 154 116 33,051 11,955 147 41 305 12,448 Government NGO / Development Project Cooperative Other Not applicable Total Governmen t NGO / Development Project Cooperative Other Not applicable Total Babati 10,246 0 0 0 121 10,368 7,369 117 0 0 0 7,486 Hanang 3,553 0 0 0 0 3,553 5,249 0 0 0 155 5,404 Mbulu 4,005 0 0 0 87 4,092 4,181 0 0 84 0 4,265 Simanjiro 734 268 0 0 0 1,001 810 100 12 0 12 935 Kiteto 2,481 133 57 57 41 2,768 1,124 133 57 0 0 1,314 Total 21,019 401 57 57 249 21,782 18,732 351 69 84 168 19,404 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Babati 1,645 104 0 0 0 0 1,750 8,719 220 0 0 0 117 9,056 Hanang 701 0 0 0 0 75 776 4,634 0 0 0 0 160 4,795 Mbulu 3,080 0 0 0 0 0 3,080 4,015 0 0 0 0 87 4,102 Simanjiro 803 85 12 12 70 50 1,033 2,918 443 12 126 83 48 3,629 Kiteto 268 403 0 0 0 68 739 1,977 469 170 239 0 180 3,036 Total 6,497 592 12 12 70 193 7,378 22,263 1,131 183 365 83 593 24,618 cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District District Inorganic Fertilizer Use Use of Improved Seed 15.4 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District Spacing Use of Agrochemicals Erosion Control Organic Fertilizer Use Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 214 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Government NGO / Development Project Other Not applicable Total Babati 2,069 206 0 0 0 0 2,275 2,345 112 0 0 2,457 Hanang 851 0 0 0 0 75 926 1,252 78 0 0 1,329 Mbulu 3,004 0 0 0 73 0 3,077 485 0 0 172 657 Simanjiro 1,850 121 28 259 35 0 2,293 608 137 98 0 843 Kiteto 695 539 113 125 0 0 1,472 334 337 0 137 808 Total 8,469 866 141 384 108 75 10,044 5,023 663 98 309 6,093 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Government NGO / Development Project Large Scale Farm Other Not applicable Total Babati 7,614 345 120 0 0 0 8,080 1,515 237 0 0 0 1,752 Hanang 5,951 77 0 0 0 80 6,109 933 0 0 0 0 933 Mbulu 3,689 0 0 0 0 73 3,762 2,698 0 0 0 87 2,785 Simanjiro 1,421 218 0 41 0 0 1,679 618 12 123 70 0 824 Kiteto 2,773 268 0 0 70 0 3,110 1,006 67 0 339 0 1,413 Total 21,448 908 120 41 70 153 22,740 6,770 316 123 409 87 7,706 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Government NGO / Development Project Cooperative Not applicable Total Babati 1,207 104 0 0 0 0 1,311 2,302 462 0 0 2,763 Hanang 1,397 0 0 0 0 0 1,397 2,731 0 0 0 2,731 Mbulu 2,831 0 0 0 0 87 2,918 3,102 0 0 87 3,189 Simanjiro 499 188 12 0 0 28 728 339 0 0 0 339 Kiteto 879 67 0 68 203 0 1,218 941 133 67 0 1,142 Total 6,813 360 12 68 203 115 7,572 9,416 595 67 87 10,165 District cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By Distric cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District Mechanisation / LST Irrigation Technology Crop Storage Vermin Control Agro-progressing Agro-forestry Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 215 Government NGO / Development Project Not applicable Total Government NGO / Developme nt Project Not applicable Total Government NGO / Developme nt Project Large Scale Farm Total Babati 973 94 120 1,187 246 125 0 371 458 0 0 458 Hanang 462 0 0 462 80 0 0 80 624 0 0 624 Mbulu 73 0 87 160 73 84 87 244 0 86 0 86 Simanjiro 134 0 0 134 48 0 0 48 0 91 0 91 Kiteto 472 336 0 808 407 335 0 742 329 268 57 654 Total 2,114 430 207 2,752 853 545 87 1,485 1,411 445 57 1,912 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Babati 61,883 2,349 120 0 0 359 64,711 Hanang 39,115 233 0 0 0 772 40,120 Mbulu 39,361 170 0 0 241 853 40,625 Simanjiro 15,627 1,900 78 688 356 183 18,831 Kiteto 18,511 3,960 586 490 738 576 24,861 Total 174,497 8,612 784 1,177 1,335 2,743 189,148 Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Babati 12,819 12,236 2,465 1,415 10,480 6,067 7,366 4,057 1,526 458 Hanang 7,642 7,169 3,053 2,744 3,553 2,560 5,409 3,815 621 544 Mbulu 4,521 4,346 3,602 659 4,005 1,761 4,265 3,448 2,993 0 Simanjiro 3,897 2,575 1,391 1,130 891 878 640 462 885 834 Kiteto 3,990 3,150 1,508 399 2,905 1,273 1,314 380 671 0 Total 32,869 29,475 12,019 6,346 21,834 12,538 18,993 12,162 6,696 1,835 District District cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District Beekeeping Fish Farming Other Total cont….EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District 15.5 EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District District Spacing Use of Agrochemicals Erosion Control Organic Fertilizer Use Inorganic Fertilizer Use Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 216 Irrigation Crop Vermin Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Babati 9,050 3,849 2,163 1,492 2,345 1,863 7,975 7,986 1,752 1,632 Hanang 5,023 3,271 851 776 542 1,099 6,027 5,652 465 940 Mbulu 4,015 497 2,990 146 401 73 3,762 3,283 2,698 2,625 Simanjiro 3,537 2,322 2,293 2,094 734 709 1,557 1,552 824 800 Kiteto 2,966 1,659 1,472 877 740 127 2,972 2,640 1,413 1,213 Total 24,592 11,598 9,769 5,385 4,760 3,871 22,293 21,112 7,152 7,210 Agro- progressing Agro-forestry Beekeeping Fish Farming Other Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Babati 1,311 1,186 2,763 2,176 1,187 816 371 246 229 229 Hanang 1,240 1,323 2,573 2,569 0 156 0 0 307 153 Mbulu 2,904 2,685 3,249 2,758 73 0 157 84 0 0 Simanjiro 633 657 339 302 0 0 0 0 44 0 Kiteto 1,079 1,151 1,142 139 739 68 671 0 527 461 Total 7,168 7,001 10,066 7,943 1,999 1,040 1,199 330 1,107 843 cont…. EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District District cont…. EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District District Use of Improved Seed Mechanisation / LST Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 217 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 218 Number % Number % Number % Babati 36,800 79 9,835 21 46,635 100 Hanang 22,952 73 8,292 27 31,245 100 Mbulu 21,505 63 12,876 37 34,381 100 Simanjiro 2,743 17 13,621 83 16,364 100 Kiteto 1,024 4 24,545 96 25,569 100 Total 85,025 55 69,169 45 154,194 100 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Babati 54,151 136,128 39,985 7,960 12,626 1,137 11,970 687 116 1,313 236 286 75,394 149,676 41,524 Hanang 42,529 89,462 38,118 10,499 14,028 3,426 4,852 0 0 5,139 2,519 1,120 63,019 106,009 42,664 Mbulu 40,999 84,669 23,970 14,541 13,587 2,660 7,020 4,515 18 3,354 2,745 453 65,914 105,516 27,101 Simanjiro 7,605 10,411 5,419 364 144 58 817 0 0 2,031 1,799 710 10,817 12,353 6,187 Kiteto 2,429 3,671 3,487 175 66 0 . . . 227 356 167 2,831 4,093 3,654 Total 147,712 324,342 110,979 33,539 40,451 7,281 24,658 5,201 133 12,064 7,654 2,736 217,974 377,648 121,129 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District Did you use Draft animals to cultivate your land during 2002/03 Households Using Household Not Using Total 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 219 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Babati 54,151 136,128 98,762.2 7,960 12,626 2,808.2 11,970 687 286.2 1,313 236 706.8 75,394 149,676 102,563.5 Hanang 42,529 89,462 94,151.6 10,499 14,028 8,461.2 4,852 0 0.0 5,139 2,519 2,766.5 63,019 106,009 105,379.3 Mbulu 40,999 84,669 59,207.0 14,541 13,587 6,571.1 7,020 4,515 43.3 3,354 2,745 1,117.8 65,914 105,516 66,939.3 Simanjiro 7,605 10,411 13,384.1 364 144 143.6 817 0 0.0 2,031 1,799 1,753.5 10,817 12,353 15,281.2 Kiteto 2,429 3,671 8,612.3 175 66 0.0 . . . 227 356 412.7 2,831 4,093 9,025.1 Total 147,712 324,342 274,117.3 33,539 40,451 17,984.1 24,658 5,201 329.5 12,064 7,654 6,757.4 217,974 377,648 299,188.3 Number % Number % Number % Babati 19,979 34.8 26,656 27.7 46,635 30.4 Hanang 8,550 14.9 22,620 23.5 31,170 20.3 Mbulu 26,068 45.4 8,226 8.6 34,294 22.3 Simanjiro 1,793 3.1 14,354 14.9 16,147 10.5 Kiteto 1,082 1.9 24,282 25.3 25,365 16.5 Total 57,473 100.0 96,138 100.0 153,610 100.0 Area (%) % Area (%) % Area (%) % Babati 18,198 39.1 202 25.3 18,400 38.9 Hanang 6,627 14.2 387 48.3 7,013 14.8 Mbulu 17,973 38.6 77 9.7 18,050 38.1 Simanjiro 2,795 6.0 14 1.7 2,809 5.9 Kiteto 941 2.0 120 15.0 1,062 2.2 Total 46,534 100.0 800 100.0 47,334 100.0 17.3 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total 17.4 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year District Did you apply organic fertilizer during 2002/03? Using Organic Not Using Organic Total 17.5 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Compost Area Applied Q17212_ha Tanzania Agriculture Sample Census 2003 Manyara Region 220 Appendix ii 221 CATTLE PRODUCTION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 222 Number % Number % Number % Babati 25,961 55.7 20,674 44.3 46,635 100.0 Hanang 21,003 67.2 10,242 32.8 31,245 100.0 Mbulu 26,213 76.2 8,168 23.8 34,381 100.0 Simanjiro 10,405 63.6 5,959 36.4 16,364 100.0 Kiteto 6,164 24.1 19,405 75.9 25,569 100.0 Total 89,747 58.2 64,448 41.8 154,194 100.0 Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Babati 25,263 256,086 322 531 2,517 7,007 25,961 263,625 Hanang 20,847 216,280 0 . 553 2,937 21,003 219,217 Mbulu 26,126 249,790 174 608 928 3,338 26,213 253,735 Simanjiro 10,405 263,173 0 . 45 91 10,405 263,264 Kiteto 6,164 177,723 0 . 65 387 6,164 178,110 Total 88,807 1,163,051 496 1,139 4,108 13,761 89,747 1,177,951 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year District Households Rearing Cattle Households Not Rearing Total 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Beef Improved Dairy Total Cattle Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 223 Number of Household % Number of Cattle % Average Number Per Household 1-5 8,657 33 30,849 12 4 6-10 8,596 33 65,047 25 8 11-15 5,079 20 63,292 24 12 16-20 1,975 8 35,430 13 18 21-30 1,070 4 25,734 10 24 31-40 247 1 8,378 3 34 41-50 219 1 10,039 4 46 151+ 118 0 24,856 9 211 Total 25,961 100 263,625 100 10 1-5 6,640 32 21,473 10 3 6-10 7,013 33 53,830 25 8 11-15 3,876 18 48,987 22 13 16-20 1,470 7 27,113 12 18 21-30 1,314 6 33,431 15 25 31-40 310 1 11,316 5 37 41-50 157 1 7,443 3 47 51-60 66 0 3,940 2 60 61-100 159 1 11,684 5 74 Total 21,003 100 219,217 100 10 1-5 7,926 30 26,630 10 3 6-10 9,512 36 73,970 29 8 11-15 4,329 17 53,492 21 12 16-20 2,332 9 41,695 16 18 21-30 1,602 6 37,615 15 23 31-40 340 1 11,130 4 33 41-50 86 0 3,852 2 45 61-100 86 0 5,351 2 62 Total 26,213 100 253,735 100 10 1-5 2,897 28 9,784 4 3 6-10 2,187 21 18,743 7 9 11-15 940 9 12,632 5 13 16-20 1,185 11 22,057 8 19 21-30 1,120 11 27,990 11 25 31-40 464 4 16,532 6 36 41-50 332 3 15,065 6 45 51-60 292 3 16,514 6 56 61-100 656 6 51,786 20 79 101-150 151 1 18,018 7 119 151+ 181 2 54,141 21 298 Total 10,405 100 263,264 100 25 1-5 1,104 18 3,766 2 3 6-10 1,233 20 9,944 6 8 11-15 857 14 10,977 6 13 16-20 205 3 3,823 2 19 21-30 1,464 24 38,101 21 26 31-40 159 3 5,876 3 37 41-50 202 3 8,777 5 43 51-60 314 5 16,944 10 54 61-100 293 5 21,188 12 72 101-150 82 1 9,499 5 116 151+ 251 4 49,215 28 196 Total 6,164 100 178,110 100 29 18.3.1 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 Herd Size Babati Hanang Mbulu Simanjiro Kiteto Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 224 Type Number of Indigenous Number of Improved Beef Number of Improved Dairy Total Cattle Bulls 137,961 115 1,284 139,361 Cows 448,093 . 9,148 457,241 Steers 164,616 . 77 164,693 Heifers 140,422 289 683 141,394 Male Calves 127,806 275 771 128,852 Female Calves 144,153 460 1,797 146,411 Total 1,163,051 1,139 13,761 1,177,951 Bulls Cows Steers Heifers Male Calves Female Calves Total Babati 36,548 83,475 47,402 28,164 27,623 32,874 256,086 Hanang 24,572 80,445 40,082 22,077 23,802 25,302 216,280 Mbulu 37,988 92,114 33,407 29,573 26,913 29,795 249,790 Simanjiro 21,824 121,112 24,381 32,866 30,378 32,611 263,173 Kiteto 17,029 70,947 19,343 27,743 19,089 23,572 177,723 Total 137,961 448,093 164,616 140,422 127,806 144,153 1,163,051 Bulls Cows Steers Heifers Male Calves Female Calves Total Babati 115 . . 115 188 113 531 Hanang . . . . . . . Mbulu . . . 174 87 347 608 Simanjiro . . . . . . . Kiteto . . . . . . . Total 115 . . 289 275 460 1,139 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 18.4.1 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Beef Cattle Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 225 Bulls Cows Steers Heifers Male Calves Female Calves Total Babati 1,052 3,705 . 683 352 1,215 7,007 Hanang 232 2,472 77 . 77 80 2,937 Mbulu . 2,494 . . 342 502 3,338 Simanjiro . 91 . . . . 91 Kiteto . 387 . . . . 387 Total 1,284 9,148 77 683 771 1,797 13,761 Bulls Cows Steers Heifers Male Calves Female Calves Total Babati 37,716 87,179 47,402 28,962 28,163 34,202 263,625 Hanang 24,804 82,917 40,159 22,077 23,879 25,382 219,217 Mbulu 37,988 94,608 33,407 29,746 27,342 30,644 253,735 Simanjiro 21,824 121,203 24,381 32,866 30,378 32,611 263,264 Kiteto 17,029 71,334 19,343 27,743 19,089 23,572 178,110 Total 139,361 457,241 164,693 141,394 128,852 146,411 1,177,951 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Total Cattle 18.7 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Dairy Cattle Tanzania Agriculture Sample Census 2003 Manyara Region 226 Appendix ii 227 GOATS PRODUCTION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 228 Number % Number % Number % Babati 23,864 51 22,771 49 46,635 100 Hanang 17,447 56 13,798 44 31,245 100 Mbulu 20,000 58 14,382 42 34,381 100 Simanjiro 12,274 75 4,090 25 16,364 100 Kiteto 6,974 27 18,595 73 25,569 100 Total 80,559 52 73,636 48 154,194 100 Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Babati 23,374 187,498 0 . 569 3,665 23,621 191,163 Hanang 17,370 160,079 0 . 78 390 17,370 160,469 Mbulu 20,000 184,169 87 87 0 . 20,000 184,256 Simanjiro 12,274 316,379 0 . 174 1,270 12,274 317,648 Kiteto 6,974 137,411 0 . 41 205 6,974 137,616 Total 79,992 985,536 87 87 862 5,530 80,238 991,152 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 24,069 30 67,343 7 3 5-9 23,228 29 157,919 16 7 10-14 14,335 18 162,759 16 11 15-19 7,180 9 118,639 12 17 20-24 3,793 5 80,459 8 21 25-29 1,406 2 36,666 4 26 30-39 2,956 4 96,637 10 33 40+ 3,270 4 270,730 27 83 Total 80,238 100 991,152 100 12 District Number of Indigenous Number of Improved for Meat Number of Improved Dairy Total Goat Billy Goat 122,884 . 341 123,225 Castrated Goat 101,888 . 766 102,654 She Goat 497,928 . 2,309 500,237 Male Kid 127,384 . 867 128,251 She Kid 135,452 87 1,248 136,786 Total 985,536 87 5,530 991,152 19.1 GOAT PRODUCTION: Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year District Did the Hh own, raise or manage any Goat? Households Rearing Goats Households Not Rearing Goat Total 19.3 GOAT PRODUCTION: Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003 19.2 GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Indigenous Improved for Meat Improved Dairy Total Goat 19.4 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 229 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Babati 30,507 15,181 97,577 20,744 23,489 187,498 Hanang 20,172 9,356 86,696 22,784 21,072 160,079 Mbulu 28,358 17,293 88,417 24,817 25,283 184,169 Simanjiro 26,458 39,629 159,176 43,075 48,040 316,379 Kiteto 17,389 20,428 66,061 15,964 17,568 137,411 Total 122,884 101,888 497,928 127,384 135,452 985,536 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Babati . . . . . . Hanang . . . . . . Mbulu . . . . 87 87 Simanjiro . . . . . . Kiteto . . . . . . Total . . . . 87 87 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Babati 341 376 1,876 768 304 3,665 Hanang . 390 . . . 390 Mbulu . . . . . . Simanjiro . . 227 98 944 1,270 Kiteto . . 205 . . 205 Total 341 766 2,309 867 1,248 5,530 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Babati 30,848 15,557 99,454 21,512 23,793 191,163 Hanang 20,172 9,747 86,696 22,784 21,072 160,469 Mbulu 28,358 17,293 88,417 24,817 25,370 184,256 Simanjiro 26,458 39,629 159,403 43,174 48,984 317,648 Kiteto 17,389 20,428 66,266 15,964 17,568 137,616 Total 123,225 102,654 500,237 128,251 136,786 991,152 19.5 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Number of Indigenous 19.6 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat 19.7 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of District Number of Improved Dairy 19.8 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st District Total Goat Tanzania Agriculture Sample Census 2003 Manyara Region 230 Appendix ii 231 SHEEP PRODUCTION Tanzania Agriculture Sample Census 2003 Manyara Region appendix ii 232 Number % Number % Number % Babati 12,669 27 33,966 73 46,635 100 Hanang 11,378 36 19,867 64 31,245 100 Mbulu 16,447 48 17,935 52 34,381 100 Simanjiro 9,909 61 6,455 39 16,364 100 Kiteto 3,512 14 22,057 86 25,569 100 Total 53,914 35 100,280 65 154,194 100 District Number of Indigenous Number of Improved for Mutton Total Sheep Babati 71,450 . 71,450 Hanang 83,475 710 84,186 Mbulu 97,067 1,202 98,269 Simanjiro 143,080 82 143,162 Kiteto 42,247 . 42,247 Total 437,320 1,994 439,314 20.2 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.1 SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002.0/ Agriculture Year District Did the household own, raise or manage any Sheep? Households Raising Sheep Households Not Raising Sheep Total Tanzania Agriculture Sample Census 2003 Manyara Region appendix ii 233 Number of Household % Number of Sheep % Average Number Per Household 1-4 6,058 48 15,826 22 3 5-9 4,868 38 31,124 44 6 10-14 1,042 8 11,578 16 11 15-19 475 4 8,302 12 17 20-24 226 2 4,620 6 20 Total 12,669 100 71,450 100 6 1-4 6,273 55 15,522 18 2 5-9 3,577 31 22,866 27 6 10-14 1,011 9 11,590 14 11 15-19 361 3 5,570 7 15 25-29 76 1 2,052 2 27 40+ 80 1 26,586 32 333 Total 11,378 100 84,186 100 7 1-4 7,833 48 22,314 23 3 5-9 6,199 38 41,174 42 7 10-14 1,496 9 16,652 17 11 15-19 425 3 6,801 7 16 20-24 73 0 1,461 1 20 25-29 173 1 4,592 5 27 30-39 159 1 5,274 5 33 Total 16,359 100 98,269 100 6 1-4 2,390 24 6,186 4 3 5-9 2,838 29 17,989 13 6 10-14 1,430 15 15,303 11 11 15-19 1,102 11 18,657 13 17 20-24 670 7 14,019 10 21 25-29 296 3 7,744 5 26 30-39 502 5 15,951 11 32 40+ 632 6 47,312 33 75 Total 9,860 100 143,162 100 15 1-4 1,111 32 2,951 7 3 5-9 1,005 29 6,720 16 7 10-14 595 17 6,744 16 11 15-19 252 7 4,137 10 16 20-24 296 9 6,545 15 22 40+ 212 6 15,150 36 71 Total 3,471 100 42,247 100 12 1-4 23,665 44 62,799 14 3 5-9 18,487 34 119,872 27 6 10-14 5,574 10 61,867 14 11 15-19 2,614 5 43,466 10 17 20-24 1,265 2 26,646 6 21 25-29 545 1 14,389 3 26 30-39 662 1 21,225 5 32 40+ 925 2 89,048 20 96 Total 53,737 100 439,314 100 8 20.3 SHEEP PRODUCTION: Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03 Herd Size Total Sheep Babati Hanang Mbulu Simanjiro Kiteto Total Tanzania Agriculture Sample Census 2003 Manyara Region appendix ii 234 Breed Number of Indigenous Number of Improved for Mutton Total Sheep Ram 85,483 166 85,649 Castrated Sheep 39,031 172 39,203 She Sheep 210,099 1,115 211,215 Male Lamb 49,869 163 50,032 She Lamb 52,838 378 53,215 Total 437,320 1,994 439,314 Ram Castrated Sheep She Sheep Male Lamb She Lamb Babati 13,571 4,840 36,042 9,183 7,814 71,450 Hanang 33,456 4,167 31,566 6,885 7,402 83,475 Mbulu 16,590 8,143 48,788 11,238 12,308 97,067 Simanjiro 16,662 15,569 73,499 17,592 19,758 143,080 Kiteto 5,204 6,312 20,204 4,972 5,556 42,247 Total 85,483 39,031 210,099 49,869 52,838 437,320 Ram Castrated Sheep She Sheep Male Lamb She Lamb Babati . . . . . . Hanang 80 . 473 77 80 710 Mbulu 86 172 601 86 257 1,202 Simanjiro . . 41 . 41 82 Kiteto . . . . . . Total 166 172 1,115 163 378 1,994 Ram Castrated Sheep She Sheep Male Lamb She Lamb Babati 13,571 4,840 36,042 9,183 7,814 71,450 Hanang 33,536 4,167 32,039 6,962 7,482 84,186 Mbulu 16,675 8,315 49,389 11,324 12,565 98,269 Simanjiro 16,662 15,569 73,540 17,592 19,799 143,162 Kiteto 5,204 6,312 20,204 4,972 5,556 42,247 Total 85,649 39,203 211,215 50,032 53,215 439,314 20.4 SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year 20.5 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Number of Indigenous 20.6 SHEEP PRODUCTION: Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep Total Sheep District Number of Improved for Mutton Number of Improved for Mutton 20.7 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 235 PIGS PRODUCTION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 236 Number % Number % Number % Babati 1,971 4.2 44,664 95.8 46,635 100.0 Hanang 1,089 3.5 30,156 96.5 31,245 100.0 Mbulu 13,166 38.3 21,215 61.7 34,381 100.0 Simanjiro 12 0.1 16,352 99.9 16,364 100.0 Kiteto 255 1.0 25,315 99.0 25,569 100.0 Total 16,493 10.7 137,701 89.3 154,194 100.0 District Number of Household Number of Pig Average Number Per Household Babati 1,861 12,254 7 Hanang 1,089 2,235 2 Mbulu 12,993 26,415 2 Simanjiro 12 25 2 Kiteto 255 306 1 Total 16,210 41,236 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Babati 1,530 3,156 3,060 2,817 1,691 12,254 Hanang 526 77 1,160 394 79 2,235 Mbulu 6,077 3,414 9,994 3,062 3,868 26,415 Simanjiro 12 . 12 . . 25 Kiteto 52 . 189 . 66 306 Total 8,198 6,647 14,415 6,273 5,703 41,236 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Babati . . . . . Hanang 205 79 142 . . Mbulu 1,112 55,251 1,113 1,371 54,144 Simanjiro . . . . . Kiteto . . . . . Total 1,317 55,330 1,255 1,371 54,144 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year District Did the household own, raise or manage any Pig? Households Raising Pig Households Not Raising Pig Total District Total Pig Offtake 21.2 PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 21.3 PIG POPULATION: Pig Offtake By Type of Pig and District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 237 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 238 Number % age Number % age Number % age Babati 20,294 68 9,521 32 29,814 100 Hanang 11,623 56 9,202 44 20,825 100 Mbulu 18,497 69 8,485 31 26,982 100 Simanjiro 9,582 76 2,946 24 12,528 100 Kiteto 3,347 46 3,965 54 7,312 100 Total 63,343 65 34,118 35 97,461 100 Number % Number % Number % Number % Babati 12,719 31 17,171 35 8,050 28 3,450 28 Hanang 6,767 16 8,791 18 4,644 16 1,854 15 Mbulu 11,198 27 15,629 32 7,992 27 5,295 43 Simanjiro 8,415 20 5,391 11 7,121 24 1,131 9 Kiteto 2,065 5 2,288 5 1,336 5 708 6 Total 41,164 100 49,269 100 29,143 100 12,438 100 Number % age Number % age Number % age Babati 20,397 70 8,828 30 29,226 100 Hanang 16,844 81 4,060 19 20,904 100 Mbulu 16,946 66 8,604 34 25,550 100 Simanjiro 10,654 90 1,212 10 11,866 100 Kiteto 4,978 68 2,316 32 7,294 100 Total 69,819 74 25,021 26 94,840 100 Number % age Number % age Number % age Number % age Number % age Number % age Babati 1,873 9 10,316 51 3,913 19 3,939 19 357 2 20,397 100 Hanang 2,717 16 10,278 61 155 1 3,306 20 388 2 16,844 100 Mbulu 1,990 12 7,693 45 87 1 5,575 33 1,601 9 16,946 100 Simanjiro 1,645 15 7,215 68 998 9 335 3 461 4 10,654 100 Kiteto 1,129 23 3,071 62 176 4 52 1 550 11 4,978 100 Total 9,355 13 38,572 55 5,329 8 13,206 19 3,357 5 69,819 100 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock District Dewormed Goats Dewormed Dewormed Sheep Dewormed Pigs Yes Yes Yes Yes 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Households Number of Agricultural Households NOT Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tick Control None Spraying Dipping Smearing Other Total Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 239 Number % age Number % age Number % age Babati 6,933 24 22,524 76 29,457 100 Hanang 1,912 9 18,975 91 20,887 100 Mbulu 4,620 18 20,368 82 24,988 100 Simanjiro 9,773 78 2,713 22 12,485 100 Kiteto 1,899 26 5,519 74 7,418 100 Total 25,137 26 70,097 74 95,235 100 Number % age Number % age Number % age Number % age Number % age Number % age Babati 1,778 26 4,201 61 832 12 0 0 122 2 6,933 100 Hanang 869 45 963 50 0 0 0 0 80 4 1,912 100 Mbulu 3,187 69 1,004 22 429 9 0 0 0 0 4,620 100 Simanjiro 3,298 34 3,143 32 2,656 27 37 0 639 7 9,773 100 Kiteto 1,094 58 607 32 198 10 0 0 0 0 1,899 100 Total 10,227 41 9,917 39 4,115 16 37 0 841 3 25,137 100 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Agricultural Households Encountering Tsetse Flies Agricultural Households NOT Encountering Tsetse Flies Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tsetse Flies Control None Spray Dipping Trapping 5 Total Tanzania Agriculture Sample Census 2003 Manyara Region 240 Appendix II 241 OTHER LIVESTOCK Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 242 Current Number % Type Number Indigenous Chicken 694,081 99.2 Ducks 18,942 Layer 737 0.1 Turkeys 10,698 Broiler 4,528 0.6 Rabbits 8,707 Donkeys 47,009 Horse 0 Other 5,463 699,345 100.0 Total 790,163 Number Number of Households Number Number of Households Number Number of Households Number Number of Households Number Number of Households Babati 4,946 621 . 0 122 122 2,968 1,009 4,669 347 Hanang 458 152 . 0 . 0 9,735 3,895 . 0 Mbulu 599 171 5,131 86 . 0 8,268 3,493 . 0 Simanjiro 1,695 252 2,105 35 822 12 18,282 4,204 794 246 Kiteto 11,243 476 3,462 69 7,763 129 7,756 1,870 . 0 Total 18,942 1,672 10,698 190 8,707 264 47,009 14,471 5,463 593 Hanang . 4,492 4,492 75 Mbulu 610 . 610 174 Simanjiro . 36 36 36 Kiteto 127 . 127 127 Total 737 4,528 5,264 412 Hanang . 4,492 4,492 75 Mbulu 610 . 610 174 Simanjiro . 36 36 36 Kiteto 127 . 127 127 Total 737 4,528 5,264 412 1 - 4 97,787 301 36 98,124 33,949 5 - 9 185,361 435 . 185,796 28,933 10 - 19 259,732 . . 259,732 21,120 20 - 29 95,842 . . 95,842 106.7 30 - 39 23,494 . . 23,494 26.1 40 - 49 12,239 . . 12,239 13.6 50 - 99 17,766 . 4,492 22,258 24.8 100+ 1,860 . . 1,860 18 Total 694,081 737 4,528 699,345 89,848 Babati 271,571 . . 271,571 29,167 Hanang 144,566 . 4,492 149,058 19,992 Mbulu 152,251 610 . 152,860 25,776 Simanjiro 43,300 . 36 43,336 5,887 Kiteto 82,393 127 . 82,520 9,026 Total 694,081 737 4,528 699,345 89,848 Others 23.2 OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Ducks Turkeys Rabbits Donkeys Other Breed Type Chicken Indigenous Chicken 23.3 OTHER LIVESTOCK: Number of Chicken by Type and District District Chicken Type 23.4 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District Layer Broiler Total District Chicken Type 23.5 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Flock Size Chicken Type Layer Broiler Layer Total Layer Broiler Total 23.1 OTHER LIVESTOCK: Total Number of Other Livestock by Breed and Type Indigenous Chicken Total Broiler 23.6 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District District Chicken Type Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 243 FISH FARMING Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 244 Number % Number % Number % Babati 0 0.0 46,635 100.0 46,635 100.0 Hanang 0 0.0 31,245 100.0 31,245 100.0 Mbulu 84 0.2 34,297 99.8 34,381 100.0 Simanjiro 0 0.0 16,364 100.0 16,364 100.0 Kiteto 69 0.3 25,501 99.7 25,569 100.0 Total 153 0.1 154,041 99.9 154,194 100.0 Dug out Pond Total Mbulu 84 84 Total 84 84 NGOs / Project Total Number Number Mbulu 84 84 Total 84 84 Neighbor Total Number Number Mbulu 84 84 Total 84 84 District Number of Tilapia Number of Carp Number of Others Mbulu 21,094 0 0 Kiteto . . . Total 21,094 0 0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Number of Agricultural Households Doing Fish Farming Number of Agricultural Households NOT Doing Fish Farming Total 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year District Fish Farming System 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year District Source of Fingerling 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 245 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 246 Number % Number % Number % Babati 7,549 16 39,086 84 46,635 100 Hanang 3,912 13 27,333 87 31,245 100 Mbulu 3,798 11 30,583 89 34,381 100 Simanjiro 5,468 33 10,896 67 16,364 100 Kiteto 1,316 5 24,253 95 25,569 100 Total 22,043 14 132,151 86 154,194 100 Government NGO / Developm ent Project Total Babati 1,472 522 1,995 Hanang 78 0 78 Mbulu 3,102 0 3,102 Simanjiro 410 28 438 Kiteto 268 0 268 Total 5,331 550 5,881 Government NGO / Developm ent Project Other Total Babati 2,751 544 117 3,412 Mbulu 2,683 0 0 2,683 Simanjiro 593 256 0 849 Kiteto 665 0 0 665 Total 6,691 800 117 7,608 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year District Did Household receive livestock advice during 2002/03? Number of Agricultural Households Receiving Advice Number of Agricultural Households NOT Receiving Advice Total 29.1b LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District Source of Advice 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 247 Government NGO / Developm ent Project Total Babati 1,944 439 2,383 Hanang 78 0 78 Mbulu 3,016 0 3,016 Simanjiro 702 73 775 Kiteto 462 0 462 Total 6,202 512 6,714 Government NGO / Developm ent Project not applicable Total Babati 1,830 449 0 2,279 Hanang 78 0 0 78 Mbulu 3,190 0 0 3,190 Simanjiro 976 45 49 1,070 Kiteto 527 0 0 527 Total 6,601 494 49 7,145 Government NGO / Developm ent Project Large Scale Farmer Other Total Babati 5,416 887 0 0 6,302 Hanang 3,294 0 0 80 3,374 Mbulu 3,362 0 0 0 3,362 Simanjiro 4,504 140 48 36 4,727 Kiteto 792 67 57 0 916 Total 17,367 1,094 104 117 18,682 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Source of Advice 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 248 Government NGO / Developm ent Project not applicable Total Babati 2,069 125 122 2,316 Hanang 1,550 0 0 1,550 Mbulu 2,668 0 0 2,668 Simanjiro 436 0 0 436 Kiteto 133 67 0 201 Total 6,856 193 122 7,170 Government NGO / Developm ent Project Total Babati 1,179 522 1,701 Hanang 312 0 312 Mbulu 2,842 0 2,842 Simanjiro 307 0 307 Kiteto 264 269 532 Total 4,903 791 5,694 Government NGO / Developm ent Project not applicable Total Babati 1,433 522 0 1,955 Hanang 941 0 0 941 Mbulu 1,377 0 0 1,377 Simanjiro 1,284 92 36 1,412 Kiteto 332 133 0 465 Total 5,366 748 36 6,150 Government NGO / Developm ent Project Large Scale Farmer Total Babati 2,192 342 0 2,534 Hanang 309 0 0 309 Mbulu 3,103 0 0 3,103 Simanjiro 571 0 0 571 Kiteto 200 66 67 333 Total 6,375 407 67 6,850 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year District Source of Advice 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 249 Government NGO / Developm ent Project Large Scale Farmer Other not applicable Total Babati 1,840 642 0 0 125 2,608 Hanang 855 0 0 0 0 855 Mbulu 3,291 0 0 0 0 3,291 Simanjiro 594 164 0 46 0 804 Kiteto 133 0 67 0 0 201 Total 6,713 806 67 46 125 7,758 Number % Number % Number % Number % Number % Number % Babati 898 12 5,075 70 943 13 330 5 0 0 7,247 100 Hanang 153 4 2,288 66 1,005 29 0 0 0 0 3,446 100 Mbulu 259 7 841 22 1,560 40 349 9 872 22 3,881 100 Simanjiro 1,227 19 3,816 58 782 12 313 5 428 7 6,567 100 Kiteto 135 12 916 82 68 6 0 0 0 0 1,119 100 Total 2,673 12 12,937 58 4,358 20 992 4 1,300 6 22,260 100 Number % Number % Number % Number % Number % Number % Babati 6,139 47 2,357 18 1,912 15 1,912 15 616 5 12,936 100 Hanang 3,450 63 620 11 542 10 464 8 387 7 5,464 100 Mbulu 2,094 56 509 14 509 14 509 14 87 2 3,709 100 Simanjiro 4,874 53 1,816 20 916 10 812 9 735 8 9,152 100 Kiteto 716 56 257 20 57 4 192 15 57 4 1,279 100 Total 17,274 53 5,560 17 3,936 12 3,889 12 1,882 6 32,541 100 Number % Number % Number % Babati 2,429 19 10,507 81 12,936 100 Hanang 543 10 4,921 90 5,464 100 Mbulu 247 7 3,462 93 3,709 100 Simanjiro 1,946 21 7,206 79 9,152 100 Kiteto 0 0 1,279 100 1,279 100 Total 5,165 16 27,376 84 32,541 100 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Quality of Service Very Good Good Average Poor No Good Total 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year District Extension Provider Government NGO / Development Co-operative Large Scale Other Total 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Number of Agricultural Households WITH Contact Farmers / Group Members Number of Agricultural Households WITHOUT Contact Farmers / Group Total Tanzania Agriculture Sample Census 2003 Manyara Region 250 Appendix ii 251 LABOUR USE Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 252 District Secondary School Primary School All Weather Road Feeder Roads Hospital Health Clinics District Capital Primary Market Secondary Market Tertiary Market Tarmac Road Babati 8.2 2.0 5.0 1.2 21.6 6.0 30.9 10.5 7.6 30.7 100.2 Hanang 17.0 2.8 7.2 1.3 25.8 12.5 35.6 9.2 9.9 31.1 112.5 Mbulu 10.2 4.3 5.0 1.1 28.0 6.7 44.9 5.8 12.9 17.3 92.4 Simanjiro 65.2 5.2 5.8 1.7 81.9 10.6 108.9 23.7 26.2 93.0 84.5 Kiteto 39.8 2.5 4.6 2.6 56.3 8.9 55.7 10.1 12.9 45.7 114.9 Total 21.7 3.1 5.5 1.5 36.1 8.4 47.4 10.5 12.1 36.9 101.7 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Mean Distance Babati 12,142 24,216 9,496 661 120 46,635 2.0 Hanang 3,339 15,068 12,470 368 0 31,245 2.8 Mbulu 3,669 17,233 13,306 87 86 34,381 4.3 Simanjiro 1,596 5,575 7,372 1,537 284 16,364 5.2 Kiteto 8,754 9,653 6,062 485 615 25,569 2.5 Total 29,500 71,746 48,705 3,138 1,105 154,194 3.1 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 1,891 8,683 21,305 10,460 4,297 46,635 8.2 Hanang 3,001 2,844 8,648 4,528 12,224 31,245 17.0 Mbulu 1,436 4,680 15,750 7,819 4,696 34,381 10.2 Simanjiro 1,710 321 1,795 801 11,737 16,364 65.2 Kiteto 609 1,611 5,335 5,884 12,130 25,569 39.8 Total 8,647 18,139 52,833 29,492 45,083 154,194 21.7 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 2,251 12,449 23,623 7,417 895 46,635 6.0 Hanang 1,782 4,721 14,916 5,806 4,020 31,245 12.5 Mbulu 2,312 5,394 19,976 6,176 522 34,381 6.7 Simanjiro 1,424 2,379 6,060 4,223 2,279 16,364 10.6 Kiteto 3,910 5,463 5,792 8,396 2,009 25,569 8.9 Total 11,678 30,406 70,369 32,018 9,724 154,194 8.4 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 466 1,834 8,705 10,944 24,685 46,635 21.6 Hanang 786 305 3,561 7,450 19,142 31,245 25.8 Mbulu 233 422 3,374 9,319 21,033 34,381 28.0 Simanjiro 890 44 523 765 14,142 16,364 81.9 Kiteto 247 911 1,456 5,533 17,422 25,569 56.3 Total 2,622 3,517 17,618 34,012 96,425 154,194 36.1 33.0:Mean distances from holders dwellings to infrustructures and services by districts 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary School Mean Distance 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Health Clinic 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year Mean Distance District Distance (Kilometer) to Hospital Mean Distance Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 253 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 0 238 2,489 9,683 34,224 46,635 30.9 Hanang 943 226 3,102 4,937 22,037 31,245 35.6 Mbulu 87 253 1,175 7,206 25,660 34,381 44.9 Simanjiro 50 98 492 114 15,609 16,364 108.9 Kiteto 127 906 1,456 5,598 17,483 25,569 55.7 Total 1,207 1,721 8,714 27,539 115,014 154,194 47.4 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 0 125 2,729 9,335 34,446 46,635 31.7 Hanang 2,762 80 0 317 28,086 31,245 94.1 Mbulu 2,959 0 0 174 31,248 34,381 106.2 Simanjiro 27 0 0 44 16,292 16,364 272.9 Kiteto 59 0 116 0 25,394 25,569 301.4 Total 5,808 205 2,845 9,870 135,466 154,194 131.3 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 34,368 8,914 1,793 1,097 464 46,635 1.2 Hanang 15,461 12,096 3,400 289 0 31,245 1.3 Mbulu 17,689 13,499 2,757 436 0 34,381 1.1 Simanjiro 7,975 5,828 2,330 100 131 16,364 1.7 Kiteto 17,977 5,135 1,598 679 179 25,569 2.6 Total 93,470 45,471 11,878 2,600 775 154,194 1.5 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 14,566 16,298 7,564 4,222 3,985 46,635 5.0 Hanang 6,432 6,281 11,714 4,412 2,406 31,245 7.2 Mbulu 5,605 14,033 11,986 2,498 260 34,381 5.0 Simanjiro 3,618 5,241 4,690 1,384 1,432 16,364 5.8 Kiteto 10,647 5,477 3,857 4,738 850 25,569 4.6 Total 40,867 47,330 39,811 17,254 8,933 154,194 5.5 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to District Capital Mean Distance 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to Districtal Capital 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Mean Distance District Distance (Kilometer) to Feeder Road 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to ALL Wealther Road Mean Distance Mean Distance Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 254 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 2,856 682 820 342 41,936 46,635 100.2 Hanang 8,305 80 0 0 22,860 31,245 112.5 Mbulu 14,221 0 86 0 20,074 34,381 92.4 Simanjiro 438 44 436 1,244 14,202 16,364 84.5 Kiteto 125 126 0 779 24,538 25,569 114.9 Total 25,945 933 1,342 2,364 123,610 154,194 101.7 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 4,080 7,624 17,922 10,873 6,136 46,635 10.5 Hanang 8,865 1,834 3,844 14,596 2,106 31,245 9.2 Mbulu 18,149 1,925 1,483 11,255 1,569 34,381 5.8 Simanjiro 885 1,380 4,513 3,577 6,009 16,364 23.7 Kiteto 4,162 4,939 6,978 7,459 2,031 25,569 10.1 Total 36,141 17,702 34,740 47,761 17,851 154,194 10.5 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 1,120 7,471 24,203 11,392 2,449 46,635 7.6 Hanang 3,728 3,390 10,931 9,629 3,568 31,245 9.9 Mbulu 732 3,116 11,331 12,709 6,492 34,381 12.9 Simanjiro 637 1,006 3,923 3,384 7,414 16,364 26.2 Kiteto 1,533 3,207 5,256 8,567 7,007 25,569 12.9 Total 7,750 18,190 55,643 45,681 26,930 154,194 12.1 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Babati 1,067 125 6,299 9,479 29,665 46,635 30.7 Hanang 6,678 156 2,165 794 21,452 31,245 31.1 Mbulu 8,819 1,009 5,772 8,563 10,218 34,381 17.3 Simanjiro 161 133 68 129 15,872 16,364 93.0 Kiteto 375 1,677 2,297 6,520 14,700 25,569 45.7 Total 17,100 3,100 16,601 25,486 91,907 154,194 36.9 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tarmac Road 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year Mean Distance District Distance (Kilometer) to Primary Market 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary Market Mean Distance Mean Distance 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tertiary Market Mean Distance Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 255 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 2,580 1,588 3,380 1,268 1,413 26,997 8,934 46,158 41.5 Hanang 1,809 1,562 3,972 719 4,077 14,738 3,758 30,634 36.4 Mbulu 4,545 3,573 4,050 1,644 4,455 6,979 7,403 32,649 44.1 Simanjiro 248 461 237 264 216 3,067 11,823 16,317 86.8 Kiteto 0 461 1,660 3,804 1,188 6,674 9,744 23,531 56.2 Total 9,182 7,644 13,298 7,699 11,350 58,454 41,662 149,289 48.3 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 2,476 4,470 4,032 1,430 16,836 1,466 1,699 32,410 18.6 Hanang 1,196 2,947 4,287 1,296 11,273 6,063 1,257 28,319 23.9 Mbulu 7,712 5,015 4,383 1,817 4,845 1,636 3,781 29,190 22.1 Simanjiro 2,626 1,015 186 671 825 576 8,065 13,964 59.2 Kiteto 341 1,705 2,265 2,135 1,490 5,359 7,246 20,541 43.7 Total 14,352 15,152 15,153 7,350 35,269 15,099 22,049 124,424 28.9 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 3,053 0 125 0 626 114 42,596 46,514 174.7 Hanang 5,412 688 0 160 382 470 23,901 31,015 140.7 Mbulu 11,651 0 0 0 0 0 22,646 34,297 171.4 Simanjiro 1,333 0 49 0 84 955 13,943 16,364 96.5 Kiteto 69 0 0 0 615 0 24,747 25,431 204.0 Total 21,518 688 175 160 1,707 1,539 127,833 153,621 163.6 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 2,934 117 0 0 626 228 42,608 46,514 189.6 Hanang 6,144 0 77 0 233 543 24,247 31,245 160.5 Mbulu 11,822 0 0 0 0 87 22,472 34,381 176.4 Simanjiro 1,243 0 95 0 129 1,368 13,481 16,317 92.7 Kiteto 59 0 0 68 615 68 24,758 25,569 412.8 Total 22,203 117 172 68 1,603 2,295 127,567 154,026 207.5 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year District Distance (Kilometer) to Veterinary Clinic 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center District Distance (Kilometer) to Extension Center Mean Distance Mean Distance 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year District Distance (Kilometer) to Research Station 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year Mean Distance District Distance (Kilometer) to Plant Protection Lab Mean Distance Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 256 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 2,102 1,829 2,750 1,275 2,975 28,048 7,417 46,396 39.9 Hanang 470 2,421 4,449 718 4,677 12,672 5,015 30,421 33.9 Mbulu 1,843 1,992 2,684 2,164 4,892 8,234 11,641 33,450 42.7 Simanjiro 354 540 49 48 375 1,591 13,310 16,266 111.3 Kiteto 0 664 1,712 3,889 1,130 6,537 9,862 23,794 55.1 Total 4,769 7,445 11,644 8,094 14,049 57,082 47,245 150,327 49.4 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Babati 4,654 321 1,417 487 2,004 703 36,816 46,402 121.8 Hanang 4,422 1,343 2,641 0 532 3,794 17,687 30,419 78.5 Mbulu 9,988 1,647 1,716 1,972 1,296 1,289 14,512 32,420 111.3 Simanjiro 1,169 0 48 89 132 1,844 13,082 16,364 91.9 Kiteto 120 0 257 119 0 680 23,978 25,154 165.9 Total 20,353 3,311 6,079 2,667 3,964 8,309 106,075 150,759 114.8 Very Good Good Average Poor No good Not applicable Total Babati 5,027 13,198 4,091 1,714 1,267 254,512 279,809 Hanang 1,790 14,185 24,362 10,455 12,740 123,938 187,469 Mbulu 84 2,816 12,053 9,062 20,645 161,628 206,287 Simanjiro 888 2,660 1,599 672 239 92,127 98,185 Kiteto 325 2,797 1,434 137 615 148,107 153,415 Total 8,114 35,656 43,539 22,040 35,506 780,312 925,166 Very Good Good Average Poor No good Total Babati 3,605 7,367 1,664 247 112 12,995 Hanang 785 5,032 6,660 1,137 1,957 15,571 Mbulu 84 1,434 2,429 1,980 4,130 10,056 Simanjiro 324 1,486 446 143 0 2,398 Kiteto 60 942 663 0 0 1,665 Total 4,857 16,260 11,862 3,506 6,199 42,685 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year District Distance (Kilometer) to Land Registration Office Mean Distance 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center District Distance (Kilometer) to Livestock Development Center 33.19 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Mean Distance District Satisfaction of Using Veterinary Clinic 33.20 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Extension Center Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 257 Very Good Good Average Poor No good Total Babati 125 588 112 247 355 1,427 Hanang 78 1,010 1,625 1,548 2,109 6,370 Mbulu 0 0 87 1,384 3,956 5,428 Simanjiro 48 83 89 181 49 449 Kiteto 0 197 0 0 137 333 Total 251 1,877 1,913 3,360 6,606 14,007 Very Good Good Average Poor No good Total Babati 113 710 229 365 112 1,528 Hanang 543 314 1,454 1,396 2,032 5,740 Mbulu 0 0 87 1,559 3,956 5,603 Simanjiro 130 38 44 90 95 398 Kiteto 0 129 0 0 137 266 Total 786 1,191 1,815 3,410 6,332 13,535 Very Good Good Average Poor No good Total Babati 480 1,733 1,389 486 346 4,436 Hanang 75 2,166 5,895 2,914 2,969 14,018 Mbulu 0 173 6,022 855 863 7,913 Simanjiro 152 132 333 92 48 756 Kiteto 68 949 637 69 137 1,859 Total 775 5,153 14,277 4,416 4,363 28,983 Very Good Good Average Poor No good Total Babati 358 1,178 229 122 112 1,998 Hanang 75 1,694 2,320 2,092 2,737 8,917 Mbulu 0 795 2,028 1,726 3,696 8,244 Simanjiro 95 333 140 0 48 615 Kiteto 70 197 0 68 137 470 Total 597 4,196 4,716 4,007 6,729 20,245 33.21 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Satisfaction of Using Research Station 33.22 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year 33.24 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center District Satisfaction of Using Livestock Development Center District Satisfaction of Using Plant Protection Lab 33.23 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Satisfaction of Using Land Registration Office Tanzania Agriculture Sample Census 2003 Manyara Region 258 Appendix II 259 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 260 District Number of rooms Iron Sheets Tiles Concrete Asbestos Grass / Leaves Total Babati 2 16,690 232 117 29,020 576 46,635 Hanang 3 7,454 294 0 10,784 12,713 31,245 Mbulu 2 5,320 428 86 17,569 10,978 34,381 Simanjiro 2 4,367 0 0 8,640 3,357 16,364 Kiteto 2 15,436 121 0 4,225 5,787 25,569 Total 2 49,266 1,076 204 70,237 33,412 154,194 Yes No Total Yes No Total Yes No Total Babati 25,891 20,744 46,635 115 46,520 46,635 554 46,081 46,635 Hanang 12,595 18,650 31,245 218 31,027 31,245 234 31,011 31,245 Mbulu 9,600 24,781 34,381 0 34,381 34,381 0 34,381 34,381 Simanjiro 10,097 6,267 16,364 144 16,220 16,364 947 15,418 16,364 Kiteto 16,376 9,193 25,569 184 25,385 25,569 195 25,374 25,569 Total 74,560 79,634 154,194 662 153,533 154,194 1,930 152,265 154,194 Yes No Total Yes No Total Yes No Total Babati 10,170 36,465 46,635 2,322 44,313 46,635 22,494 24,141 46,635 Hanang 4,298 26,947 31,245 1,620 29,625 31,245 12,109 19,135 31,245 Mbulu 4,263 30,118 34,381 1,405 32,976 34,381 9,962 24,419 34,381 Simanjiro 2,510 13,854 16,364 869 15,495 16,364 7,508 8,856 16,364 Kiteto 3,125 22,444 25,569 1,096 24,473 25,569 12,391 13,178 25,569 Total 24,366 129,828 154,194 7,312 146,882 154,194 64,464 89,730 154,194 34.1: HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District Radio Landline phone Mobile phone 34.2: HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year cont….HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year District Iron Wheelbarrow Bicycle Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 261 Yes No Total Yes No Total Babati 689 45,946 46,635 324 46,311 46,635 Hanang 141 31,104 31,245 153 31,092 31,245 Mbulu 86 34,296 34,381 86 34,296 34,381 Simanjiro 377 15,987 16,364 269 16,095 16,364 Kiteto 191 25,378 25,569 197 25,372 25,569 Total 1,483 152,711 154,194 1,028 153,167 154,194 District Mains Electricity Solar Hurricane Lamp Pressure Lamp Wick Lamp Candles Firewood Other Total Babati 335 0 10,343 1,440 34,158 0 360 0 46,635 Hanang 294 0 4,177 1,834 21,241 0 3,623 77 31,245 Mbulu 0 86 2,827 930 28,670 0 1,697 171 34,381 Simanjiro 147 0 3,179 481 12,385 0 172 0 16,364 Kiteto 249 59 6,474 586 15,784 69 1,671 677 25,569 Total 1,025 146 26,999 5,271 112,237 69 7,522 925 154,194 District Mains Electricity Bottled Gas Charcoal Firewood Crop Residues Livestock Dung Total Babati 122 0 715 45,689 110 0 46,635 Hanang 237 63 1,077 29,632 234 0 31,245 Mbulu 0 87 258 33,949 87 0 34,381 Simanjiro 12 45 265 15,961 38 42 16,364 Kiteto 65 0 1,591 23,844 0 69 25,569 Total 436 195 3,907 149,076 469 111 154,194 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Other Total Babati 12,607 11,565 1,516 7,827 6,609 6,263 0 125 0 122 0 0 46,635 Hanang 11,664 481 241 3,701 2,781 5,990 818 4,927 80 0 0 562 31,245 Mbulu 4,534 6,959 428 10,132 2,067 9,400 259 428 0 0 87 87 34,381 Simanjiro 3,001 3,009 570 651 1,517 7,019 0 351 246 0 0 0 16,364 Kiteto 4,518 321 197 6,527 3,643 5,502 346 3,739 0 0 0 775 25,569 Total 36,323 22,336 2,952 28,837 16,618 34,174 1,423 9,571 326 122 87 1,424 154,194 Television / Video 34.3: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year 34.4: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year 34.5: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year District Vehicle cont...HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 262 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Babati 6,227 1,929 2,391 12,048 16,006 4,803 2,505 604 121 46,635 Hanang 3,046 1,327 955 4,615 7,350 5,937 4,472 3,465 79 31,245 Mbulu 4,682 2,850 1,190 4,874 10,075 4,380 4,420 1,909 0 34,381 Simanjiro 1,181 431 358 950 4,511 2,473 3,861 2,373 226 16,364 Kiteto 2,846 2,189 1,114 3,685 7,367 2,761 4,044 1,510 52 25,569 Total 17,982 8,725 6,009 26,172 45,310 20,355 19,302 9,862 478 154,194 District Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Babati 2,199 3,243 4,466 12,599 3,763 3,321 17,043 46,635 Hanang 2,500 2,349 1,608 7,820 1,388 450 15,130 31,245 Mbulu 2,019 8,344 1,883 8,811 2,143 2,052 9,129 34,381 Simanjiro 230 1,925 371 3,427 550 398 9,463 16,364 Kiteto 1,293 3,382 1,925 6,778 1,298 1,080 9,813 25,569 Total 8,242 19,243 10,254 39,434 9,141 7,302 60,579 154,194 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Other Total HH Babati 12,041 11,648 1,391 8,200 6,260 6,737 118 118 0 122 0 0 46,635 Hanang 11,977 1,522 475 7,842 3,994 4,884 78 396 0 0 0 79 31,245 Mbulu 3,415 7,500 513 10,650 1,718 9,828 335 335 0 0 87 0 34,381 Simanjiro 3,828 3,199 318 1,315 1,880 5,438 0 99 287 0 0 0 16,364 Kiteto 9,567 265 332 7,593 3,631 2,470 0 1,001 579 132 0 0 25,569 Total 40,827 24,134 3,028 35,600 17,483 29,357 531 1,949 866 254 87 79 154,194 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Babati 5,413 2,044 2,391 11,077 15,896 5,392 3,199 1,102 121 46,635 Hanang 1,576 619 715 3,691 5,399 5,225 6,329 5,741 1,950 31,245 Mbulu 3,257 2,861 1,019 4,531 10,121 5,035 4,800 2,758 0 34,381 Simanjiro 969 287 358 516 3,251 2,153 4,346 3,907 577 16,364 Kiteto 2,026 2,078 1,072 2,493 4,889 2,584 5,484 4,636 306 25,569 Total 13,242 7,888 5,556 22,308 39,557 20,389 24,158 18,143 2,954 154,194 34.6: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season 34.7: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.8: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34.9: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 263 District Less than 10 Minutes 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Babati 1,978 3,110 4,343 11,309 3,857 3,456 18,581 46,635 Hanang 1,093 1,575 1,376 4,908 1,306 215 20,771 31,245 Mbulu 847 8,287 1,539 8,765 1,890 1,622 11,431 34,381 Simanjiro 281 1,068 322 2,402 448 398 11,444 16,364 Kiteto 991 1,513 1,459 3,136 466 811 17,192 25,569 Total 5,190 15,554 9,040 30,522 7,966 6,503 79,419 154,194 District No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Babati 4,608 247 41,305 352 122 46,635 Hanang 3,714 228 26,910 158 235 31,245 Mbulu 156 344 33,542 340 0 34,381 Simanjiro 11,156 116 4,599 493 0 16,364 Kiteto 5,917 109 19,484 60 0 25,569 Total 25,551 1,044 125,839 1,402 358 154,194 District One Two Three Four Total Babati 604 15,580 30,356 94 46,635 Hanang 523 13,345 17,377 0 31,245 Mbulu 160 7,826 26,395 0 34,381 Simanjiro 309 10,240 5,128 688 16,364 Kiteto 66 12,727 12,776 0 25,569 Total 1,662 59,718 92,032 782 154,194 District Not Eaten One Two Three Four Five Six Seven Total Babati 12,914 21,047 8,947 2,468 539 365 125 230 46,635 Hanang 15,018 9,504 4,779 1,329 538 0 0 77 31,245 Mbulu 18,087 12,796 2,578 759 160 0 0 0 34,381 Simanjiro 4,791 5,320 4,262 1,284 566 42 50 49 16,364 Kiteto 7,632 7,018 5,897 2,851 1,125 481 185 381 25,569 Total 58,442 55,685 26,464 8,691 2,927 888 360 737 154,194 34-10: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34-11: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year 34-12: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year 34-13: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region Appendix ii 264 District Not Eaten One Two Three Four Five Six Seven Total Babati 14,003 14,138 9,869 3,698 2,243 2,034 440 210 46,635 Hanang 14,395 5,861 4,628 2,651 2,430 910 74 297 31,245 Mbulu 26,957 6,209 717 244 0 253 0 0 34,381 Simanjiro 10,684 2,358 1,376 500 506 255 220 466 16,364 Kiteto 15,647 4,680 2,938 1,187 430 365 125 196 25,569 Total 81,685 33,246 19,529 8,280 5,609 3,817 859 1,169 154,194 District Never Seldom Sometimes Often Always Total Babati 20,054 18,279 2,100 3,713 2,489 46,635 Hanang 10,896 12,228 1,194 5,015 1,911 31,245 Mbulu 8,657 12,573 2,140 6,241 4,770 34,381 Simanjiro 4,599 4,688 1,088 4,791 1,198 16,364 Kiteto 13,022 8,592 820 2,379 756 25,569 Total 57,229 56,362 7,343 22,138 11,123 154,194 District Sales of Food Crops Sale of Livestock Sale of Livestock Products Sales of Cash Crops Sale of Forest Products Business Income Wages & Salaries in Cash Other Casual Cash Earnings Cash Remittance Fishing Other not applicable Total Babati 15,356 2,821 1,409 3,308 3,432 8,647 1,274 8,873 1,399 115 0 0 46,635 Hanang 7,857 5,965 152 6,596 2,652 1,587 546 5,262 630 0 0 0 31,245 Mbulu 12,009 5,109 260 2,331 2,961 1,693 1,427 6,134 764 0 1,693 0 34,381 Simanjiro 4,597 8,341 395 421 131 1,101 470 436 75 124 232 42 16,364 Kiteto 14,518 4,539 201 261 543 1,187 664 2,364 132 0 1,160 0 25,569 Total 54,336 26,775 2,417 12,917 9,718 14,214 4,381 23,070 3,000 239 3,085 42 154,194 34-14: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year 34-15: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year 34-16: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 Manyara Region 265 APPENDIX III QUESTIONNAIRES Appendix III 266 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 267 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 268 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 269 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 270 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 271 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 272 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 273 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 274 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 275 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 276 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 277 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 278 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 279 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 280 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 281 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 282 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 283 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 284 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 285 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 286 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 287 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 288 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 289 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 290 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 291 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 292 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 293 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 294 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 295 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 296 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 297 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 298 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 299 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 300 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 301 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 302 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 303 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 304 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 305 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 306 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 307 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 308 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 309 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 310 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 311 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content SOURCES OF FUNDS DASIP BENEFICIARY BUNDA BUTIMBA RAGATA Procurement of a grain milling machine. 3,000 1,500 1,500 Procurement of Oxen drawn weeder & carts. 3,000 1,500 1,500 BUNDA MIGUNGANI Construction of a cattle dip. 24,000 19,200 4,800 Procurement of a power tiller. 6,000 3,000 3,000 HUNYARI MARIWANDA Construction of a milk collecting & processing cen 23,520 18,816 4,704 Procurement of a chick incubator. 3,400 1,700 1,700 IGUNDU IGUNDU Procurement of a grain milling machine. 3,000 1,500 1,500 Construction of a bore hole. 21,000 16,800 4,200 BULENDABUFWE Procurement of a power tiller. 6,000 3,000 3,000 IRAMBA MWIRURUMA Construction of a crop market structure 20,000 16,000 4,000 KABASA BITARAGURU Construction of a bore hole. 21,000 16,800 4,200 Rehabilitation of a cattle dip. 4,500 3,600 900 Procurement of an irrigation pump. 6,500 3,250 3,250 KISORYA MASAHUNGA Procurement of a chick incubator. 3,400 1,700 1,700 Procurement of a grain milling machine. 3,000 1,500 1,500 KUZUNGU BUKORE Procurement of a power tiller. 6,000 3,000 3,000 Rehabilitation of a charco dam. 14,760 11,808 2,952 MUGETA SANZATE Rehabilitation of a charco dam. 18,000 14,400 3,600 Procurement of a grain milling machine. 3,000 1,500 1,500 KYANDEGE Construction of a milk collecting & processing cen 18,520 14,816 3,704 NANSIMO NANSIMO Completion of an irrigation scheme 12,000 9,600 2,400 Procurement of a grain milling machine. 3,000 1,500 1,500 NERUMA NERUMA Procurement of a power tiller. 6,000 3,000 3,000 Procurement of a grain milling machine. 3,000 1,500 1,500 KASAHUNGA Procurement of a power tiller. 6,000 3,000 3,000 Procurement of a grain milling machine. 3,000 1,500 1,500 NYAMUSWA KILORELI Construction of a bore hole. 24,000 19,200 4,800 SAZIRA MISISI Procurement of a power tiller. 6,000 3,000 3,000 KITARAMAKA Rehabilitation of a charco dam. 16,000 12,800 3,200 Procurement of a grain milling machine. 3,000 1,500 1,500 Mcharo Nyamatoke Construction of a charco dam. 10,000 8,000 2,000 NAME OF PROJECT TOTAL COST (in '000) DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ALLOCATION OF INVESTMENT FUNDS - 1st QRT 2008/09 KAGERA , SHINYANGA, MARA, KIGOMA AND MWANZA REGIONS MARA REGION DISTRICT WARD VILLAGE TOTAL BUNDA DISTRICT 303,600 219,990 83,610 MUSOMA BUSWAHILI BUSWAHILI Purchase of rice de-hullers 5,000 2,500 2,500 KATARYO Purchase of rice de-hullers 5,000 2,500 2,500 BWAIKITURURU Purchase of rice de-hullers 5,000 2,500 2,500 LYASEMBE Purchase of rice de-hullers 5,000 2,500 2,500 Purchase of grain milling machine 5,000 2,500 2,500 KISAMWENE Construction of a charco dam 35,000 28,000 7,000 Purchase of grain milling machine 5,000 2,500 2,500 KIZARU Construction of a charco dam 35,000 28,000 7,000 KAMUGEGI Purchase of cassava processor 10,000 5,000 5,000 BUGOJI Purchase of cassava processor 10,000 5,000 5,000 Purchase of irrigation pump 8,000 6,400 1,600 BISUMWA Rehabilitation of a charco dam 35,000 28,000 7,000 CHUMWI Purchase of grain milling machine 5,000 2,500 2,500 Purchase of irrigation pump 8,000 6,400 1,600 KWIKUBA Purchase of grain milling machine 5,000 2,500 2,500 TEGERUKA Purchase of grain milling machine 5,000 2,500 2,500 WANYERE Purchase of grain milling machine 5,000 2,500 2,500 MWIKORO Purchase of grain milling machine 5,000 2,500 2,500 NYAMIKOMA Construction of a market shed 35,000 28,000 7,000 Purchase of an oil pressing machine 5,000 2,500 2,500 MIRWA Construction of a cattle dip 18,000 14,400 3,600 KIBUBWA Construction of a cattle dip 18,000 14,400 3,600 TOTAL MUSOMA DISTRICT 272,000 193,600 78,400 RORYA GORIBE PANYAKOO Rehabilitation of a charco dam. 35,000 28,000 7,000 KIGUNGA LUANDA Construction of a charco dam. 35,000 28,000 7,000 NYATHOROGO CHERECHE Purchase of rice hulling machine 8,000 4,000 4,000 KIROGO KIROGO Rehabilitation of a cattle dip. 9,610 7,688 1,922 RABUOR RABUOR Rehabilitation of a cattle dip. 9,610 7,688 1,922 NYAMUNGA KINESI Vegetable Irrigation scheme 18,000 14,400 3,600 Rehabilitation of a cattle dip. 14,415 11,532 2,883 KISUMWA MARASIBORA Rehabilitation of a water source for livestock /dip. 20,000 16,000 4,000 NYAMTINGA RWANG'ENYI Rehabilitation of a cattle dip. 14,415 11,532 2,883 164,050 128,840 35,210 TOTAL RORYA DISTRICT SERENGETNYAMATARE MOSONGO Purchase of Oxen drawn implements 6,000 3,000 3,000 NYAMATOKE Construction of a cattle dip 26,000 20,800 5,200 RING'WANI REMUNG'ORORI Purchase of Oxen drawn implements 6,000 3,000 3,000 NYAMITITA Purchase of a power tiller 6,000 3,000 3,000 ISENYI IHARARA Construction of a charco dam 35,000 28,000 7,000 MUGUMU MOROTONGA Construction of a charco dam 35,000 28,000 7,000 KENYAMONTA MESAGA Construction of a charco dam 35,000 28,000 7,000 MANCHIRA MISEKE Construction of a charco dam 35,000 28,000 7,000 KEBOSONGO Purchase of Oxen drawn implements 6,000 3,000 3,000 MACHOCWE MERENGA Expansion of a charco dam 17,000 13,600 3,400 Construction of a cattle dip 18,000 14,400 3,600 KYAMBAHI BURUNGA Construction of a charco dam 35,000 28,000 7,000 NYAMOKO NYAMOKO Construction of a cattle dip 20,670 16,536 4,134 KISANGURA KORERI Rehabilitation of charco dam 35,000 28,000 7,000 NYAMBURETI MONUNA Purchase of Oxen drawn implements 6,000 3,000 3,000 GUSUHI Purchase of Oxen drawn implements 4,000 2,000 2,000 NATTA KONO Purchase of Oxen drawn implements 6,000 3,000 3,000 Rehabilitation of rural feeder roads 17,000 13,600 3,400 BUSAWE GANTAMOME Purchase of Oxen drawn implements 6,000 3,000 3,000 KEBACHE MARASOMOCHE Construction of a cattle dip 20,670 16,536 4,134 Purchase of Oxen drawn implements 6,000 3,000 3,000 MUSATI Purchase of Oxen drawn implements 6,000 3,000 3,000 Purchase of water pump for irrigation 2,000 1,000 1,000 RIGICHA KITEMBERE Construction of a charco dam. 35,000 28,000 7,000 424,340 321,472 102,868 TARIME KIBASUKA WEIGITA Rehabilitation of a charco dam for livestock. 25000 20000 5000 BINAGI MOGABIRI Rehabilitation of rural feeder road . 20800 16640 4160 NYAMWIGURA Rehabilitation of rural feeder road . 35000 28000 7000 MURIBA NYANTIRA Construction of a cattle dip. 25000 20000 5000 Construction of a shallow well. 10000 8000 2000 NYAKONGA KEBWEYE Rehabilitation of rural feeder road . 9135 7308 1827 PEMBA PEMBA Construction of a cattle dip. 25000 20000 5000 SUSUNI KIONGERA Construction of a charco dam for livestock. 35000 28000 7000 184,935 147,948 36,987 1,348,925 1,011,850 337,075 TOTAL SERENGETI DISTRICT TOTAL TARIME DISTRICT TOTAL MARA REGION | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vt: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vt: REGIONAL REPORT:MARA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of Contents.......................................................................................................................................................... i Abbreviations............................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive Summary ................................................................................................................................................... vii Illustrations................................................................................................................................................................. xv ENSUS RESULTS AND ANALYSIS 1 BACKGROUND INFORMATION............................................................................................................ 1 1.1 Introduction.................................................................................................................................................. 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area..................................................................................................................................................... 1 1.4 Climate.......................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Administrative Setup................................................................................................................................... 1 1.6 Population..................................................................................................................................................... 1 1.7 Socio - Economic Indicators........................................................................................................................ 1 2 INTRODUCTION ....................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture........................................... 3 2.2 Census Objectives ........................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................ 4 2.4 Legal Authority of the National Sample Census of Agriculture.............................................................. 5 2.5 Reference Period.......................................................................................................................................... 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 6 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 7 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparation................................................................................................ 9 - Data Quality............................................................................................................................. 10 2.7 Funding Arrangements ............................................................................................................................. 10 3 CENSUS RESULTS AND ANALYSIS.................................................................................................... 11 3.1 Holding Characteristics............................................................................................................................. 11 3.1.1 Type of Holdings........................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income........................................................................................ 11 3.1.3 Sex and Age of Heads of Households ........................................................................................... 15 3.1.4 Number and Age of Household Members ..................................................................................... 15 3.1.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 - Literacy Rates for Heads of Households.................................................................................. 16 - Educational Status.................................................................................................................... 16 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................ 17 3.2 Land Use ................................................................................................................................................. 17 3.2.1 Area of Land Utilised .................................................................................................................... 18 3.2.2 Types of Land Use......................................................................................................................... 18 3.3 Annual Crops and Vegetable Production ................................................................................................ 19 3.3.1 Planted Area .................................................................................................................................. 19 3.3.2 Crop Importance............................................................................................................................ 22 3.3.3 Crop Types .................................................................................................................................... 22 3.3.4 Cereal Crop Production ................................................................................................................. 23 3.3.4.1 Maize ........................................................................................................................... 23 3.3.4.2 Sorghum....................................................................................................................... 24 3.3.4.3 Other Cereals ............................................................................................................... 27 3.3.5 Roots and Tuber Crops Production................................................................................................ 27 3.3.5.1 Cassava........................................................................................................................ 28 3.3.5.2 Sweet potatoes ............................................................................................................. 30 3.3.6 Pulse Crops Production ................................................................................................................. 30 3.3.6.1 Beans ........................................................................................................................... 31 3.3.7 Oil Seed Production....................................................................................................................... 33 3.3.7.1 Groundnuts .................................................................................................................. 34 3.3.8 Fruits and Vegetables .................................................................................................................... 34 3.3.8.1 Tomatoes ..................................................................................................................... 36 3.3.8.2 Cabbages...................................................................................................................... 37 3.3.8.3 Onions.......................................................................................................................... 37 3.3.9 Other Annual Crop Production...................................................................................................... 37 3.3.9.1 Cotton ........................................................................................................................... 41 3.3.9.2 Tobacco ........................................................................................................................ 41 3.4 Permanent Crops....................................................................................................................................... 41 3.4.1 Banana ..................................................................................................................................... 44 3.4.2 Coffee ..................................................................................................................................... 49 3.4.3 Mango ..................................................................................................................................... 49 3.4.4 Oranges ..................................................................................................................................... 49 3.5 Inputs/Implements Use.............................................................................................................................. 50 3.5.1 Methods of Land Clearing............................................................................................................. 50 3.5.2 Methods of Soil Preparation.......................................................................................................... 50 3.5.3 Improved Seeds Use...................................................................................................................... 51 3.5.4 Fertilizers Use................................................................................................................................ 51 - Farm Yard Manure Use.......................................................................................................... 52 - Inorganic Fertilizer Use.......................................................................................................... 53 - Compost Use .......................................................................................................................... 54 3.5.5 Pesticides Use................................................................................................................................ 55 - Insecticides Use...................................................................................................................... 55 - Herbicides Use ....................................................................................................................... 56 - Fungicides Use ............................................................................................................................ 3.5.6 Harvesting Methods....................................................................................................................... 56 3.5.7 Threshing Methods ...................................................................................................................... 57 3.6 Irrigation ................................................................................................................................................ 57 3.6.1 Area Planted with Annual Crops and Under Irrigation.................................................................. 59 3.6.2 Sources of Water Used for Irrigation............................................................................................. 59 3.6.3 Methods of Obtaining Water for Irrigation.................................................................................... 60 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.6.4 Methods of Water Application ..................................................................................................... 60 3.7 Crop Storage, Processing and Marketing................................................................................................ 60 3.7.1 Crop Storage.................................................................................................................................. 60 - Methods of Storage................................................................................................................. 61 - Duration of Storage ................................................................................................................ 61 - Purposes of Storage................................................................................................................ 62 - The Magnitude of Storage Loss.............................................................................................. 62 3.7.2 Agro processing and By-products ................................................................................................. 63 - Processing Methods................................................................................................................ 63 - Main Agro-processing Products............................................................................................. 64 - Main Use of Primary Processed Products .............................................................................. 64 - Outlet for Sale of Processed Products .................................................................................... 65 3.7.3 Crop Marketing ............................................................................................................................. 65 - Main Marketing Problems...................................................................................................... 67 - Reasons for Not Selling Crops ............................................................................................... 67 3.8 Access to Crop Production Services......................................................................................................... 67 3.8.1 Access to Agricultural Credits....................................................................................................... 67 - Source of Agricultural Credits................................................................................................ 67 - Use of Agricultural Credits..................................................................................................... 68 - Reasons for not Using Agricultural Credits............................................................................ 68 3.8.2 Crop Extension .............................................................................................................................. 68 - Sources of Crop Extension Messages..................................................................................... 69 - Quality of Extension............................................................................................................... 69 3.9 Access to Inputs ......................................................................................................................................... 69 3.9.2 Inorganic Fertilisers ...................................................................................................................... 70 3.9.3 Improved Seeds ............................................................................................................................. 70 3.9.4 Insecticides and Fungicides........................................................................................................... 71 3.10 Tree Planting.............................................................................................................................................. 71 3.11 Irrigation and Erosion Control Facilities ............................................................................................... 74 3.12 Livestock Results........................................................................................................................................ 74 3.12.1 Cattle Production .......................................................................................................................... 74 - Cattle Population .................................................................................................................... 74 - Herd Size................................................................................................................................ 76 - Cattle Population Trend.......................................................................................................... 76 - Improved Cattle Breeds.......................................................................................................... 78 3.12.2 Goat Production............................................................................................................................. 78 - Goat Population...................................................................................................................... 78 - Goat Herd Size ....................................................................................................................... 78 - Goat Breeds............................................................................................................................ 80 - Goat Population Trend ........................................................................................................... 80 3.12.3 Sheep Production........................................................................................................................... 80 - Sheep Population.................................................................................................................... 80 - Sheep Population Trend ......................................................................................................... 80 3.12.4 Pig Production ............................................................................................................................... 82 - Pig Population Trend.............................................................................................................. 82 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5 Chicken Production ....................................................................................................................... 82 - Chicken Population ................................................................................................................ 82 - Chicken Population Trend...................................................................................................... 85 - Chicken Flock Size................................................................................................................. 85 - Improved Chicken Breeds (Layers and Broilers) ................................................................... 85 3.12.6 Other Livestock ............................................................................................................................. 86 3.12.7 Pests and Parasites Incidences and Control ................................................................................... 86 - De-worming............................................................................................................................ 88 3.12.8 Access to Livestock Services......................................................................................................... 88 - Access to Livestock Extension Services................................................................................. 88 - Access to Veterinary Clinic.................................................................................................... 88 - Access to Village Watering Points/Dams............................................................................... 89 3.12.9 Animal Contribution to Crop Production ...................................................................................... 89 - Use of Draft Power................................................................................................................. 89 - Use of Farm Yard Manure...................................................................................................... 90 - Use of Compost ..................................................................................................................... 90 3.12.10 Fish Farming.................................................................................................................................. 90 3.12.11 Access to Infrastructure and Other Services.................................................................................. 93 3.13 Poverty Indicators...................................................................................................................................... 93 3.13.1 Type of Toilets .............................................................................................................................. 93 3.13.2 Household’s Assets........................................................................................................................ 94 3.13.3 Sources of Lighting Energy........................................................................................................... 94 3.13.4 Sources of Energy for Cooking ..................................................................................................... 94 3.13.5 Roofing Materials.......................................................................................................................... 95 3.13.6 Access to Drinking Water.............................................................................................................. 95 3.13.7 Food Consumption Pattern ............................................................................................................ 96 - Number of Meals per Day ...................................................................................................... 96 - Meat Consumption Frequencies............................................................................................. 96 - Fish Consumption Frequencies .............................................................................................. 97 3.13.8 Food Security................................................................................................................................. 97 3.13.9 Main Source of Cash Income ........................................................................................................ 97 4 MARA PROFILES................................................................................................................................. 102 4.1 Region Profile........................................................................................................................................... 102 4.2 District Profiles ........................................................................................................................................ 104 4.2.1 Tarime ......................................................................................................................................... 104 4.2.2. Serengeti...................................................................................................................................... 105 4.2.3 Musoma Rural ............................................................................................................................. 107 4.2.4 Bunda........................................................................................................................................... 109 4.2.5 Musoma Urban ............................................................................................................................ 111 ABBREVIATIONS ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census v ABBREVIATIONS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Dodoma region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Cletus P. B. Mkai The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main census results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households which were selected using statistical sampling techniques in rural areas of Mara region. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Mara region. It provides an overview of the rural agricultural households and their levels of involvement in agricultural related activities at regional level. I. Household Characteristics The number of agricultural households in Mara region was 188,203, of which 103,379 (54.9%) were involved in growing crops only, 2,412 (1.3%) were involved in livestock keeping only and 82,412 (43.8%) were involved in both crop production and livestock keeping. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income, followed by tree/forest resources, permanent crop farming, off farm income, livestock keeping/herding, remittances and fishing/hunting & gathering. Mara region had a total literacy rate of 72 percent. The highest literacy rate was found in Musoma Urban (81%), followed by Tarime and Musoma Rural districts (74% each). Serengeti and Bunda districts had the lowest literacy rates of 69 percent each. The literacy rate for the heads of households in the region was 73.5 percent. The number of heads of agricultural households with formal education in Mara region was 135,160 (71.8%), those without any education were 50,764 (27.0%) and those with only adult education were 2,280 (1.2%). The majority of heads of agricultural households had primary level education (66.2%), whereas only 5.6 percent had post primary education. In Mara region 72,002 households (38%) had only one member aged 5 and above involved in off-farm income generating activity, 25,816 households (14%) had two members involved in off-farm income generating activities and 11,969 households (6%) had more than two members involved in off-farm income generating activities. II. Crop Production Land Area The total area of land available to smallholders was 487,543 ha. The regional average land area utilised for agriculture per household was only 1.9 ha. This figure is close to the national average which is 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 333,525 hectares, of which 120,270 hectares (36%) were planted during the short rainy season and 213,255 hectares (64%) during the long rainy season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii The area planted with cereals was 161,701 ha (48.5% of the total planted area with annual and vegetable crops), followed by roots and tubers with 133,117 ha (39.9%), annual cash crops (20,587 ha, 6.2%), pulses (14,438 ha, 4.3%), fruit and vegetables (2,110 ha, 0.6%) and oil seeds (1,572 ha, 0.5%). i) Cereal Crops Maize Maize was the most important cereal crop in Mara region, however it had the second largest planted area after cassava. The number of households growing maize in Mara region during the long rainy season was 77,336 (62% of the total crop growing households in the region during the long rainy season). The total production of maize was 110,662 tonnes from a planted area of 91,804 hectares resulting in a yield of 1.2 t/ha. There was a sharp drop in maize production from 106,000 tonnes in 1995 to 66,000 tonnes in 1996. This was followed by a gradual increase to 107,000 tonnes in 1999 after which the production remained more or less constant up to the year 2003. The average planted area with maize per household was 0.6 hectares, however it ranged from 0.33 hectares in Musoma Urban district to 0.65 hectares in Bunda district. Tarime district had the largest area of maize (39,273 ha), followed by Musoma Rural (19,326 ha), Serengeti (17,490 ha), Bunda (15,668 ha) and Musoma Urban (47 ha). Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that planted sorghum in Mara region during the long rainy season was 54,589. This represents 43.7 percent of the total crop growing households in Mara region in the long rainy season. The total production of sorghum was 54,506 tonnes from a planted area of 55,040 hectares resulting in a yield of 0.99 t/ha. The district with the largest area planted with sorghum was Tarime (22,060 ha), followed by Serengeti (17,040 ha), Bunda (10,188 ha), Musoma Rural (5,751 ha) and Musoma Urban (1 ha). ii) Roots and Tubers The total production of roots and tubers was 161,111 tonnes. Of all roots and tubers, cassava production was the most important with a total production of 115,747 tonnes representing 71.8 percent of the total root and tuber crop production. This was followed by sweet potatoes with 43,234 tonnes (26.8%), Irish potatoes (1,781 tonnes, 1.1%), yams (277 tonnes, 0.2%) and cocoyam (71 tonnes 0.0%). Cassava The number of households growing cassava in Mara region during the long rainy season was 138,982. This represents 75.4 percent of the total crop growing households in the region. The total production of cassava during the census year was 115,747 tonnes from a planted area of 115,743 hectares resulting in a yield of 1.0 t/ha. Sweet Potatoes The number of households growing sweet potatoes in Mara region during the long rainy season was 36,514 (19.3% of the total crop growing households in the region). The total production of sweet potatoes during the census year was 43,234 tonnes from a planted area of 16,621 hectares resulting in a yield of 2.6 t/ha. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix Pulse Crops Production The total area planted with pulses was 14,438 hectares out of which 11,726 ha were planted with beans (81.2 percent of the total area planted with pulses), followed by chick peas (2,070 ha, 14.3%), cowpeas (278 ha, 1.9%), bambara nuts (256 ha, 1.8%) and mung beans (108 ha, 0.7%). iii) Oil Seed Production The total production of oilseed crops was 1,459 tonnes planted on an area of 1,572 hectares. Groundnuts were the most important oilseed crop with 1,338 ha (85.1% of the total area planted with oil seeds), followed by simsim (176 ha, 11.2%), soya beans (38 ha, 2.4%) and sunflower (21 ha, 1.3%). iv) Fruit and Vegetables The most cultivated fruit and vegetable crop was the tomato with a production of 3,801 tonnes (54% of the total fruits and vegetables produced), followed by cabbage (1,683t, 24%) and onions (907t, 10%). The production of the other fruit and vegetable crops was relatively small. v) Annual Cash Crops An area of 20,587 ha was planted with annual crops, mainly cotton and tobacco. The area planted with annual cash crops in short rainy season was 18,628 ha which represents 15.5 percent of the total area planted with annual crops in short rainy season. The area planted with annual cash crops in long rainy season was 1,959 ha representing 0.9 percent of the total area planted with annual crops during the long rainy season. vi) Permanent Crops The area of smallholders planted with permanent crops was 16,835 hectares (5% of the area planted with annual and permanent crops in the region). The most important permanent crop in Mara region was banana with a planted area of 4,376 ha, (27% of the planted area of all permanent crops), followed by coffee (3,771 ha, 22%), mango (1,701 ha, 10%), orange (1,169 ha, 7%), pawpaw (991 ha, 6%) and sugarcane (383 ha, 2%) III Inputs/Implement Use Methods of Soil Preparation Ox-ploughing was the most common method of soil preparation and it was used on an area of 144,491 ha which represented 66 percent of the total area cultivated, followed by hand hoe cultivation (72,166 ha, 33%) and tractor ploughing (1,822 ha, 1%) Improved Seeds The area planted using improved seeds was 50,862 ha which represents 15 percent of the total area planted with the annual crops and vegetables. The use of improved seed in the short rainy season was 27 percent, much higher than the corresponding percentage use for the extended rainy season (9%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x Use of Fertilizers The use of fertilisers on annual crops was very small with a planted area of only 57,423 ha (17.2% of the total planted area in the region). Of the planted area with fertiliser application, farm yard manure was applied on 47,972 ha which represents 14 percent of the total planted area (83.5% of the area planted with fertiliser application in the region). This was followed by compost (6,719 ha, 2%). Inorganic fertilizers were used on a very small area which represented only 4.7 percent of the area planted with fertilizers. Pesticide Use Insecticides were the most common pesticides used in the region (62% of the total area applied with pesticides). This was followed by fungicides (27%) and herbicides (11.3%). The planted area applied with insecticides was estimated at 21,719 ha which represented 6.5 percent of the total planted area for annual crops and vegetables, followed by fungicides (9,482 ha, 23%) and herbicides (5,011 ha, 12%). Irrigation In Mara region, the area of annual crops under irrigation was 4,202 ha representing 1.3 percent of the total area planted. The area under irrigation during the short rainy season was 2,412 ha accounting for 57 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown during the long rainy season with irrigation. In the long rainy season, 71 percent of the area planted with vegetables was irrigated, whilst 59 percent of the vegetables were irrigated in the short rainy season. IV. Crop Storage, Processing and Marketing Crop Storage There were 135,725 crop growing households (73% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 102,693 households storing 11,353 tonnes as of 1st October 2003. This was followed by Sorghum and millet (78,632 households, 9,567t), beans and pulses (29,539 households, 961t), paddy (7,785 households, 697t) and groundnuts/bambara nuts (2,071 households, 87t). Other crops were stored in very small amounts. The most common method of storage in the region was in locally made traditional structures. Agro - processing Agro-processing was practiced by most crop growing households in Mara region (171,860 households, 91.3% of the total crop growing households). With exception of Musoma Urban district, the percent of households processing crops in the rest of the districts was very high (above 80%). Musoma Urban had the lowest percent of households processing crops (62% of crop growing households). Most crop processing households processed their crops using neighbour’s machines (67%, 115,059 households). This was followed by those processing on-farm by hand (42,052 households, 24.5%), on farm by machine (12,461 households, 7%) and by trader (1,918 households, 1%). The remaining methods of processing were used by very few households (less than 1%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Crop Marketing The number of households that reported selling crops in Mara region was 130,438 which represented 70.2 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Serengeti (77.3%), followed by Musoma Rural (69.5%), Tarime (69.1%), Bunda (67.7%) and Musoma Urban (21.9%). V. Access to Crop Production Services Access to Agricultural Credit In Mara region, very few agricultural households (675, 0.4%) accessed credit, out of which 419 (75%) were male-headed households and 256 (38%) were female headed households. In Musoma Rural district, only female headed households got agricultural credit whereas in Serengeti both male and female headed households accessed agricultural credits. Crop Extension Services The number of agricultural households that received crop extension was 62,800 (34% of total crop growing households in the region). Some districts had more access to extension services than others, with Bunda having a relatively high proportion of households (60%) that received crop extension messages, followed by Musoma Rural (47%), Musoma Urban (25%), Serengeti (23%) and Tarime (18%). The main source of crop extension advice was from the Government. Access to Inputs In Mara region farm yard manure was used by 48,514 households which represented 26.1 percent of the total number of crop growing households. This was followed by improved seeds (22.9%), insecticide/fungicide (11.6%), compost (3.6%), inorganic fertiliser (1.6%) and herbicide (0.1%). The percent of households that use improved seeds was 22.9 percent of the total number of crop growing households. The district that used improved seeds most was Bunda with 36.7 percent of the total number of crop growing households using improved seeds in the district, followed by Musoma Urban (26.9%) and Musoma Rural (24.9%). Percentages of the crop growing households in Tarime and Serengeti districts that used improved seeds were 18.4 and 16.5 respectively VI. Tree Planting The number of households involved in tree farming was 53,900 representing 29 percent of the total number of agriculture households. The number of trees planted by smallholders on their allotted land was 4,540,084 trees. The average number of trees planted per household that plants trees on their land was 84 trees. . VII. Irrigation and Erosion Control Facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 18,282 which represented 10 percent of the total number of agricultural households in the region. The proportion of households with soil erosion control and water harvesting facilities was highest in Musoma Rural district (24%), followed by Musoma Urban (21%), Tarime (6%), Serengeti (2%) and Bunda (1%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xii VIII. Livestock Results i) Livestock Population Cattle The total number of cattle in the region was 1,099,068. Cattle are the dominant livestock type in the region, followed by goats, sheep and pigs. The region had 6.5 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Mara region was 1,090,007 (99.2 % of the total number of cattle in the region). The number of dairy breeds was 8,797 cattle (0.8%) and 264 cattle (0.0%) were beef breeds. Goats The number of goat-rearing households in Mara region was 72,575 (39% of all agricultural households in the region) with a total number of 634,044 goats giving an average of 9 heads of goats per goat-rearing household. Tarime district had the largest number of goats (237,710 goats, 37.5% of all goats in the region), followed by Musoma Rural (173,221 goats, 27.3%), Bunda (118,038 goats, 18.6%), Serengeti (103,574 goats, 16.3%) and Musoma Urban (1,501 goats, 0.2%). Sheep The number of sheep-rearing households was 21,780 (12% of all agricultural households in Mara region) rearing 194,073 sheep, giving an average of 9 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Tarime with 75,196 sheep (39% of total sheep in Mara region) followed by Serengeti (48,376 sheep, 25%), Musoma Rural (40,362 sheep, 21%) and Bunda (30,078 sheep, 16%). Pigs The number of pig-rearing agricultural households in Mara region was 328 (0.2% of the total agricultural households in the region) rearing 2,409 pigs. This gives an average of 7 pigs per pig-rearing household. The district with the largest number of pigs was Tarime with 2,129 pigs (88.4% of the total pig population in the region), followed by Serengeti (279 pigs, 11.6%). Chicken The number of households keeping chickens was 141,825 raising about 1,521,166 chickens mostly indigenous chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Mara region was ranked eleventh out of the 21 Mainland regions. ii) Pests and Parasites Incidences and Control About 69 percent and 17 percent of the total livestock-keeping households in Mara region reported to have encountered ticks and tsetse fly problems respectively. There was a predominance of tick related diseases over tsetse related diseases. While incidences of tick problems were highest in Musoma Urban district and lowest in Serengeti district, tsetse flies incidences were highest in Serengeti but lowest in Musoma Rural district and no tsetse flies incidences were reported in Musoma Urban district. Livestock rearing households that de-wormed their animals were 44,155 (52% of the total livestock rearing households in Mara region). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiii iii) Access to Livestock Services The total number of households that received livestock advice was 31,979, representing 38 percent of the total livestock- rearing households and 17 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to 65.2 percent of all households receiving livestock extension services, followed by NGOs/development projects (12.8%), large scale farmers (8.5%) and cooperatives (7.5%). Many veterinary clinics were located very far from livestock rearing households. About 80 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 20 percent of them accessed the services within 14 kms from their dwellings. The number of livestock rearing households residing less than 5 kms from the nearest watering point was 23,302 (73% of the total livestock rearing households in Mara region), whilst 8,439 households (26%) resided between 5 and 14 kms. iv) Animal Contribution to Crop Production Mara region had the fourth largest proportion of households using draft animals on Tanzania Mainland with 89,548 households (48% of the total agricultural households in the region) using them. The number of households that used draft animals in Tarime district was 49,457 representing 55 percent of the households using draught animals in the region, followed by Serengeti (14,764 households, 16%), Musoma Rural (13,344 households, 15%) and Bunda (11,984 households, 13%). There were no households using draft animals in Musoma Urban district. Use of Organic Feriliser The total area applied with organic fertiliser was 33,009 ha of which 29,792 hectares (90.5% of the total area applied with organic fertilizers or 23.8 percent of the area planted with annual crops and vegetables in Mara region during the long rainy season) was applied with farm yard manure. IX. Fish Farming The number of households involved in fish farming in Mara region was 255, representing 0.1 percent of the total agricultural households in the region. Tarime was the only district in the region practicing fish farming. X. Poverty Indicators i) Type of Toilets Most households in Mara region (75.4% of all rural agricultural households) used traditional pit latrines, 1.7 percent used improved pit latrine and 1.7 percent used flush toilets. The remaining 0.2 percent of households had other unspecified types of toilets. However, households with no toilet facilities represented 21.0 percent of the total agriculture households in the region and most of these were found in Tarime district. ii) Household Assets Out of all assets, radios were ownership was most common (57.3% of households), followed by bicycle (50.4%), iron (26.9%), wheelbarrow (5.9%), mobile phones (2.2%), vehicle (0.9%), television/video (0.8%) and landline phones (0.5%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiv iii) Source of Lighting Energy Wick lamp was the most common source of lighting energy in Mara region with 63.1 percent of the total rural households using this source of energy followed by hurricane lamp (32.1%), pressure lamp (3.0%), firewood (0.7%), main electricity (0.5%), solar (0.3%), candle (0.2%) and biogas (0.1%). iv) Energy for Cooking The most common source of energy for cooking was firewood, which was used by 97.3 percent of all rural agricultural households in Mara region. This is followed by charcoal (1.8%) and mains electricity (0.3%). The rest of energy sources (i.e., bottled gas, crop residues, livestock dung, paraffin/kerosene and solar ) accounted for 0.6 percent. v) Roofing Materials The most common roofing material for the main dwelling was grass and leaves and which was used by 60.4 percent of the rural agricultural households. This is followed by iron sheets (28.7%), grass and mud (9.8%), tiles (0.6%), concrete (0.4%) and asbestos (0.1%). vi) Access to Drinking Water The main source of drinking water for rural agricultural households in Mara region was unprotected wells (39% of households use unprotected wells during the wet season and 36 percent of the households during the dry seasons). This is followed by surface water (Lake / Dam / River / Stream) (20% of households during wet season and 29% in the dry season) and unprotected springs (16% of households in the wet season and 16% during dry season. About 50 percent of the rural agricultural households in Mara region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. vi) Number of Meals per Day About 58.4 percent of the holders in the region took two meals per day, 39.2 percent took three meals, 2.0 percent took one meal and 0.3 percent took four meals per day. Serengeti district had the largest percent of households having 3 meals per day About 69 percent of the agricultural households in Mara region consumed meat during the week preceding the census with 63,808 households (33.9 % of those who consumed meat) consuming it only once during the respective week. This was followed by those who had meat twice during the week (22.2%). Very few households had meat four times or more during the respective week. However, 30.8 percent of the agricultural households in Mara region did not eat meat during the week preceding the census. Most of the total agricultural households in Mara region (88%) of the total agricultural households in the region) consumed fish during the week preceding the census, with 33,998 households (20.1% of those who consumed fish) consuming fish once during the respective week EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xv vii) Food Security About 42 percent of the agricultural households in Mara region said they did not experience any food sufficiency problems. The rest 58 percent of the households did experience food sufficiency problems at different levels from severe to mild. XI. Main Source of Cash Income The main cash income of the households in Mara region was from selling food crops (36.1 percent of smallholder households), followed by other casual cash earnings (13.3%), businesses (11.4%), selling of cash crops (9.6%), and fishing (9.5%). Only 5.9% of smallholder households reported the sale of livestock as their main source of income, followed by cash remittance (4.9%), wages and salaries (4.6%), sale of forest products (2.2%) and sale of livestock products (1.0%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xvi ILLUSTRATIONS List of Tables 2.1 Census Sample Size........................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 15 3.2 Area, Quantity and Yield of cereal crops by Season........................................................................................ 23 3.3 Area, Quantity and Yield by Season and Type of Root and Tuber Crop......................................................... 28 3.4 Area, Quantity and Yield of Pulses by Season................................................................................................. 31 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season ................................................................. 33 3.6 Area, Production and Yield of Fruits and Vegetables by Season..................................................................... 36 3.7 Land Clearing Methods.................................................................................................................................... 50 3.8 Planted Area by Type of Fertilizer Use and District – Short and Long Rainy Season..................................... 52 3.9 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Long Rainy Season......................................................................................................................... 52 3.10 Number of Households Storing Crops by Estimated Storage Loss and Crop.................................................. 62 3.11 Reasons for Not Selling Crop Produce ............................................................................................................ 67 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 67 3.13 Access to Inputs............................................................................................................................................... 69 3.14 Total Number of Households and Chickens Raised by Flock Size...................................................................85 3.15 Head Number of Other Livestock by Type of Livestock and District ............................................................. 86 3.16 Mean distances from household dwellings to infrastructure and services by district ...................................... 93 3.17 Number of Households by Number of meals the Household normally Takes per Day and District................ 96 List of Charts 3.1 Agricultural Households by Type of Holdings ................................................................................................ 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ........................................... 15 3.3 Percentage Distribution of Population by Age and Sex in 2003...................................................................... 15 3.4 Percentage Literacy Level of Household Members by District ....................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District............................................................................ 16 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status ................................................................................................. 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment .................................................. 16 3.9 Number of Households by Number of Members with Off-farm Income......................................................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Household members with Off-farm Income Activities.................................................................. 17 3.11 Utilized and Usable Land per Household by District ...................................................................................... 18 3.12 Percentage Distribution of Land Area by Type of Land Use........................................................................... 18 3.13 Area Planted with Annual Crops by Season .................................................................................................... 19 3.14 Area Planted with Annual Crops by Season and District................................................................................. 19 3.15 Area Planted with Annual Crops (ha) per Household by Season and District................................................. 19 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................. 22 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type.................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season...................................................................... 22 3.19 Area Planted and Yield of Major Cereal Crops ............................................................................................... 22 3.20 Time Series Data on Maize Production - MARA ........................................................................................... 23 3.21 Total Area Planted and Planted Area per Maize Growing Household by District........................................... 23 3.22 Time Series of Maize Planted Area and Yield – MARA Region .................................................................... 24 3.23 Total Planted Area and Area of Sorghum per Household by District.............................................................. 24 3.24 Time Series Data on Sorghum Production – Mara Region.............................................................................. 24 3.25 Time Series of Sorghum Planted Area and Yield – Mara Region ................................................................... 24 3.26 Area Planted with Paddy, Finger millet and Bulrush millet by District........................................................... 27 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................. 27 3.28 Area Planted with Cassava during the Censuses/Survey Years....................................................................... 27 3.29 Percent of Cassava Planted Area and percent of Total Planted Area with Cassava by District....................... 28 3.30 Cassava Planted Area per Cassava Growing Households by District.............................................................. 28 3.31 Total Area Planted with Sweet potatoes and Planted Area per Household by District.................................... 30 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xvii 3.32 Area Planted and Yield of Major Pulses.......................................................................................................... 30 3.33 Percent of Bean Planted Area and Percent of the Total Planted Area with Beans by District......................... 31 3.34 Area Planted per Bean Growing Household by District ................................................................................. 31 3.35 Time Series Data on Bean Production – Mara Region .................................................................................... 33 3.36 Time Series of Beans Planted Area and Yield – Mara Region ........................................................................ 33 3.37 Area Planted and Yield of Major Oil Seed Crops............................................................................................ 33 3.38 Time Series Data on Groundnut Planted Area – Mara Region ........................................................................ 34 3.39 Percent of Groundnuts Planted Area and Proportion of Total Planted Area with Groundnuts by District ...... 34 3.40 Area Planted per Groundnut Growing Household by District ........................................................................ 34 3.41 Area Planted and Yield of Fruit and Vegetables.............................................................................................. 36 3.42 Percent of Tomato Planted Area and Percent of Total Planted Area with Tomato by District........................ 36 3.43 Area Planted per Tomato Growing Household by District ............................................................................. 36 3.44 Percent of Cabbage Planted Area and Percent of Total Planted Area with Cabbages by District ................... 37 3.45 Percent of Onions Planted Area and Percent of Total Planted Area with Onions by District.......................... 37 3.46 Area Planted with Annual Cash Crops............................................................................................................. 37 3.47 Percent of Cotton Planted Area and Percent of Total Planted Area with Cotton by District........................... 41 3.48 Area Planted for Annual and Permanent Crops ............................................................................................... 41 3.49 Area Planted with the Main Perennial Crops................................................................................................... 44 3.50 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 44 3.51 Percent of Area Planted with Banana and Average Planted Area per Household by District.......................... 44 3.52 Percent of Area Planted with Coffee and Average Planted Area per Household by District........................... 49 3.53 Percent of Area Planted with Mango and Average Planted Area per Household by District .......................... 49 3.54 Percent of Area Planted with Orange and Average Planted Area per Household by District.......................... 50 3.55 Number of Households by Method of Land Clearing during the Long Rainy Season..................................... 50 3.56 Area Cultivated by Cultivation Method........................................................................................................... 50 3.57 Area Cultivated by Method of Cultivation and District................................................................................... 51 3.58 Planted Area with Improved Seeds.................................................................................................................. 51 3.59 Planted Area with Improved Seed by Crop Type ............................................................................................ 51 3.60 Percentage of Crop Type Planted Area with Improved Seed – Annuals.......................................................... 51 3.61 Area of Fertilizer Application by Type of Fertilizer........................................................................................ 52 3.62 Area of Fertilizer Application by Type of Fertilizer and District .................................................................... 52 3.63 Planted Area with Farm Yard Manure by Crop type – Annuals...................................................................... 52 3.64 Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals................................................... 53 3.65 Proportion of Planted Area Applied with Farm Yard Manure by District....................................................... 53 3.66 Planted Area with Inorganic Fertilizer by Crop type – Annuals...................................................................... 53 3.67 Percentage of Planted Area with Inorganic Fertilizer by Crop Type............................................................... 54 3.68 Proportion of Planted Area Applied with Inorganic Fertilizer by District....................................................... 54 3.69 Planted Area with Compost by Crop Type ...................................................................................................... 54 3.70 Percentage of Crop Type Planted Area with Compost .................................................................................... 54 3.71 Proportion of Planted Area Applied with Compost by District ....................................................................... 54 3.72 Planted area (ha) by Pesticide use.................................................................................................................... 55 3.73 Planted Area applied with Insecticides by Crop Type..................................................................................... 55 3.74 Percentage of Crop Type Planted Area applied with insecticides.................................................................... 55 3.75 Percent of Planted Area Applied with Insecticides by District ....................................................................... 55 3.76 Planted Area applied with herbicides by Crop Type........................................................................................ 56 3.77 Percentage of Crop Type Planted Area applied with herbicides...................................................................... 56 3.78 Proportion of Planted Area applied with Herbicides by District ..................................................................... 56 3.79 Planted Area applied with Fungicides by Crop Type ...................................................................................... 57 3.80 Percentage of Crop Type Planted Area applied with Fungicides..................................................................... 57 3.81 Proportion of Planted Area applied with Fungicides by District .................................................................... 57 3.82 Area of Irrigated Land ..................................................................................................................................... 57 3.83 Planted Area with Irrigation by District........................................................................................................... 59 3.84 Time Series of Household Practicing Irrigation – Mara .................................................................................. 59 3.85 Number of Households with Irrigation by Source of Water ............................................................................ 59 3.86 Number of Households by Method of Obtaining Irrigation Water.................................................................. 60 3.87 Number of Households with Irrigation by Method of Field Application......................................................... 60 3.88 Number of Households and Quantity Stored by Crop Type ............................................................................ 60 3.89 Number of households by Storage Methods.................................................................................................... 61 3.90 Number of households by method of storage and District (based on the most important household crop)..... 61 3.91 Normal Length of Storage for Selected Crops................................................................................................. 61 3.92 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District................................................. 62 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xviii 3.93 Number of Households by Purpose of Storage and Crop Type ....................................................................... 62 3.94a Households Processing Crops.......................................................................................................................... 63 3.94b Percent of Households Processing Crops by District....................................................................................... 63 3.94c Percent of Crop Processing Households by Method of Processing ................................................................. 63 3.95 Percent of Households by Type of Main Processed Product ........................................................................... 64 3.96 Number of Households by Type of Bi-product................................................................................................ 64 3.97 Use of Processed Product................................................................................................................................. 64 3.98 Percentage of Households Selling Processed Crops by District ...................................................................... 64 3.99 Location of Sale of Processed Products........................................................................................................... 65 3.100 Percent of Households Selling Processed Products by Outlet for Sale and District ........................................ 65 3.101 Number of Crop Growing Households Selling Crops by District.................................................................... 65 3.102 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 67 3.103 Percentage Distribution of Households that Received Credit by Main Sources.............................................. 68 3.104 Number of Households Receiving Credit by Main Source of Credit and District........................................... 68 3.105 Proportion of Credits Received by Main Purposes.......................................................................................... 68 3.106 Reasons for Not using Credit........................................................................................................................... 68 3.107 Number of Households Receiving Extension Advices .................................................................................... 68 3.108 Number of Households that Received Extension by District........................................................................... 69 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider................................ 69 3.110 Number of Households that Received Extension by Reported Quality of Services......................................... 69 3.111 Number of Households by Source of Inorganic Fertilizer ............................................................................... 70 3.112 Number of Households Reporting Distance to Source of Inorganic Fertilizer ................................................ 70 3.113 Number of Households by Source of Improved Seed...................................................................................... 70 3.114 Number of Households reporting Distance to Source of Improved Seed ........................................................ 71 3.115 Number of Households by Source of Insecticide/Fungicide............................................................................ 71 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides.......................................... 71 3.117 Number of Households with Planted Trees ..................................................................................................... 71 3.118 Number of Selected Planted Trees by Species................................................................................................. 73 3.119 Number of Trees Planted by Smallholders by Selected Species and District .................................................. 73 3.120 Number of Trees Planted by Location ............................................................................................................. 73 3.121 Number of Households by purpose of Planted Trees....................................................................................... 73 3.122 Number of Households with Erosion Control/Water Harvesting Facilities..................................................... 74 3.123 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District .......... 74 3.124 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................ 74 3.125 Total Number of Cattle ('000') by District ....................................................................................................... 76 3.126 Numbers of Cattle by Type and District .......................................................................................................... 76 3.127 Cattle Population Trend................................................................................................................................... 76 3.128 Improved Cattle Population Trend................................................................................................................... 78 3.129 Total Number of Goats ('000') by District ....................................................................................................... 78 3.130 Goat Population Trend..................................................................................................................................... 80 3.131 Total Number of Sheep by District.................................................................................................................. 80 3.132 Sheep Population Trend................................................................................................................................... 80 3.133 Total Number of Pigs by District..................................................................................................................... 82 3.134 Pig Population Trend ....................................................................................................................................... 82 3.135 Total Number of Chicken by District .............................................................................................................. 82 3.136 Chicken Population Trend ............................................................................................................................... 85 3.137 Number of Improved Chicken by Type and District........................................................................................ 85 3.138 Improved Chicken Population Trend............................................................................................................... 85 3.139 Percentage of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District..... 86 3.140 Percent of Livestock Rearing Households that De-wormed Livestock by Livestock Type and District ......... 88 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 88 3.142 Number of Households by Distance to Veterinary Clinic................................................................................ 88 3.143 Number of Households by Distance to Veterinary Clinic and District............................................................ 88 3.144 Number of Households by Distance to Village Watering Point ...................................................................... 89 3.145 Number of Households by Distance to Watering Point and District................................................................ 89 3.146 Number of Households using Draft Animals................................................................................................... 89 3.147 Number of Households using Draft Animals by District................................................................................. 89 3.148 Number of Households using Organic Fertilizer ............................................................................................. 90 3.149 Area of Application with Organic Fertilizer by District .................................................................................. 90 3.150 Number of Households Practicing Fish Farming – Mara................................................................................. 93 3.151 Number of Households Practicing Fish Farming by District – Mara............................................................... 93 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xix 3.152 Agricultural Households by Type of Toilet Facility ........................................................................................ 93 3.153 Percentage Distribution of Households Owning the Assets............................................................................. 94 3.154 Percentage Distribution of Households by Main Source of Energy for Lighting ............................................ 94 3.155 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................ 94 3.156 Percentage Distribution of Households by Type of Roofing Material............................................................. 95 3.157 Percentage Distribution of Households with Grassy/leafy Roofs by District .................................................. 95 3.158 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season... 95 3.159 Percentage Distribution of the Number of Households by Main Source of Drinking Water and Season........ 96 3.160 Number of Agriculture Households by Number of Meals per day .................................................................. 96 3.161a Number of Households by Frequency of Meat and Fish Consumption........................................................... 96 3.161b Number of Households by Level of food availability...................................................................................... 97 3.161c Percent of Households reporting Food Availability Status by District............................................................ 97 3.162 Percent Distribution of the Number of Households by Main Source of Income ............................................. 97 List of Maps 3.1 Total Number of Agricultural Households by District..................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District........................................................ 12 3.3 Number of Crop Growing Households by District .......................................................................................... 13 3.4 Percent of Crop Growing Households by District ........................................................................................... 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District.......................................... 14 3.6 Percent of Crop and Livestock Households by District ................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ....................................................................... 20 3.8 Total Planted Area (annual crops) by District.................................................................................................. 20 3.9 Area planted and Percentage During the Dry Season by District .................................................................... 21 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.................................. 21 3.11 Planted Area and Yield of Maize by District................................................................................................... 25 3.12 Area Planted per Maize Growing Household .................................................................................................. 25 3.13 Planted Area and Yield of Sorghum by District .............................................................................................. 26 3.14 Area Planted per Sorghum Growing Households ............................................................................................ 26 3.15 Planted Area and Yield of Cassava by District Area ....................................................................................... 29 3.16 Planted Area per Cassava Growing Households.............................................................................................. 29 3.17 Planted Area and Yield of Beans by District ................................................................................................... 32 3.18 Area Planted per Beans Growing Households................................................................................................. 32 3.19 Planted Area and Yield of Groundnuts by District .......................................................................................... 35 3.20 Planted Area per Groundnuts Growing Households........................................................................................ 35 3.21 Planted Area and Yield of Tomato by District................................................................................................. 38 3.22 Area Planted per Tomato Growing Households .............................................................................................. 38 3.23 Planted Area and Yield of Cabbage by District............................................................................................... 39 3.24 Area Planted per Cabbage Growing Households............................................................................................. 39 3.25 Planted Area and Yield of Onions by District.................................................................................................. 40 3.26 Area Planted per Onion Growing Household .................................................................................................. 40 3.27 Planted Area and Yield of Cotton by District .................................................................................................. 42 3.28 Area Planted per Cotton Growing Household ................................................................................................. 42 3.29 Planted Area and Yield of Tobacco by District ............................................................................................... 43 3.30 Area Planted per Tobacco Growing Household............................................................................................... 43 3.31 Planted Area and Yield of Banana by District................................................................................................. 45 3.32 Area Planted per Banana Growing Household ................................................................................................ 45 3.33 Planted Area and Yield of Coffee by District .................................................................................................. 46 3.34 Area Planted per Coffee Growing Household.................................................................................................. 46 3.35 Planted Area and Yield of Mango by District.................................................................................................. 47 3.36 Area Planted per Mango Growing Household................................................................................................. 47 3.37 Planted Area and Yield of Orange by District ................................................................................................. 48 3.38 Area Planted per Orange Growing Household................................................................................................. 48 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................ 58 3.40 Area Planted and Percent of Total Planted Area with Irrigation by District.................................................... 58 3.41 Percent of households storing crops for 3 to 6 months by district ................................................................... 66 3.42 Number of Households and Percent of Total Households Selling Crops by District....................................... 66 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District.... 72 3.44 Number and Percent of Crop Growing Households using Improved Seed by District ................................... 72 3.45 Number and percent of smallholder planted trees by district........................................................................... 75 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xx 3.46 Number and Percent of Households with water Harvesting Bunds by District ............................................... 75 3.47 Cattle population by District as of 1st Octobers 2003 ..................................................................................... 77 3.48 Cattle Density by District as of 1st October 2003............................................................................................ 77 3.49 Goat population by District as of 1st Octobers 2003 ....................................................................................... 79 3.50 Goat Density by District as of 1st October 2003 ............................................................................................. 79 3.51 Sheep population by District as of 1st Octobers 2003 ..................................................................................... 81 3.52 Sheep Density by District as of 1st October 2003 ........................................................................................... 81 3.53 Pig population by District as of 1st Octobers 2003.......................................................................................... 83 3.54 Pig Density by District as of 1st October 2003................................................................................................ 83 3.55 Number of Chickens by District as of 1st October 2003 ................................................................................. 84 3.56 Density of Chickens by District as of 1st October 2003.................................................................................. 84 3.57 Number and Percent of Households Infected with Ticks by District............................................................... 87 3.58 Number and Percent of Households Using Draft Animals by District ............................................................ 87 3.59 Planted Area and Percent of Planted Area with Farm Yard Manure application by District........................... 91 3.60 Planted Area and Percent of Planted Area with Farm Compost application by District.................................. 91 3.61 Number and Percent of Households Practicing Fish Farming by District ....................................................... 92 3.62 Number and Percent of Households Without Toilets by District..................................................................... 92 3.63 Number and Percent of Households using Grass/Mud for roofing material by District ...................................99 3.64 Number and Percent of Households eating 3 meals per day by District.......................................................... 99 3.65 Number and Percent of Households eating Meat Once per Week by District ............................................... 100 3.66 Number and Percent of Households eating Fish Once per Week by District................................................. 100 3.67 Number and percent of Households Reporting food insufficiency by District .............................................. 101 BACKGROUND _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Mara region is located in the northern part of Mainland Tanzania. The region lies between latitudes 10 and 20 South and longitudes 31010’ and 35015’ East. The region is bordered by Kenya to the north, Mwanza and Shinyanga regions to the south, Arusha region to the east and Kagera region to the west. 1.3 Land Area Mara region occupies a total area of 30,150 square kilometers of which 7,750 sq kms is occupied by Serengeti National Park. 1.4 Climate 1.4.1 Temperature The region has a maximum temperature of 29.320c and a minimum temperature of 27.680 while the average temperature for this region is 28.50. 1.4.2 Rainfall The region has bimodal rainfall pattern with short rainfall period between September and January and long rainfall period between February and June. 1.5 Administrative Setup Mara region is divided into five administrative districts namely Musoma Rural, Musoma Urban, Bunda, Serengeti and Tarime. The headquarters of the region is located in Musoma Urban. 1.6 Population According to the 2002 Population and Housing Census, there were 1,368,602 inhabitants in Mara region and an average household size of 5.5 persons. This was about 4 percent of Tanzania Mainland’s population. The annual Average Population growth rate (1988 – 2002) was 2.5 percent. 1.7 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs. 443,187 million. The region held 7th position among regions on GDP and contributed about 4.5 percent to the national GDP1 1 National Bureau of Statistics BACKGROUND _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 • There are a number of tourist attractions in the region. These are Serengeti National Park, Game Reserves, Game Controlled areas and Lake Victoria. Serengeti National Park occupies the area of 14,763 sq km of which 7,750 sq km (52.5%) are situated in Mara region. • A small part of the population is engaged in fishing activities. This group includes people who live close to the shore of Lake Victoria • Also there are some gold mining activities in the region INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the local government authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the Mainland. Other Census reports include the Technical Report (Volume I), Crop Sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Mara profiles (Regional and Districts) and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, non-government organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 151 villages were from Mara region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the Statistics Act 2002, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel and map generation using Mapinfo. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was the trainers’ guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done for the purpose of testing the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection method used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR Extraction Technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch Validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Analysis and Report Preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data Quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 PART III: RESULTS AND ANALYSIS This part of the report presents the results of the census data for Mara region which are based on the data tables presented in Appendix II. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96, the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. 3.1 Household Characteristics 3.1.1 Type of Households The number of agricultural households in Mara region was 188,203. The largest number of agriculture households was in Tarime (79,170) followed by Musoma Rural (49,995), Bunda (30,721), Serengeti (27,864) and Musoma Urban (453). The highest density of household was found in Musoma Rural district (32 households/km2), Tarime (21 households/km2) and Bunda (20 households/km2). Most households (103,379 households, 54.9% of the total agriculture households in the region) were involved in growing crops only, 2,412 households (1.3%) were involved in livestock keeping only and 82,412 households (43.8%) were involved in crop production as well as livestock keeping. There were no pastoralists in the region (Chart 3.1 and Maps 3.1, 3.2, 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Mara region indicate that most of the agricultural households ranked annual crop farming as an activity that provides most of their livelihood/cash income followed by tree/forest resources, permanent crop farming, off - farm income, livestock keeping/herding, remittances and fishing/hunting & gathering. Musoma Urban district is the only district whereby tree/forest resources is not the second most important livelihood activity, being replaced by off-farm income (Table 3.1). Table 3.1 Rank in Order of Importance Livelihood Activities/Source of Income of the Household in Order of Importance By District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 1 3 4 5 6 7 2 Serengeti 1 3 5 4 6 7 2 Musoma Rural 1 4 5 3 7 6 2 Bunda 1 4 5 3 7 6 2 Musoma Urban 1 3 6 2 7 5 4 Total 1 3 5 4 6 7 2 Chart 3.1 Agriculture Households by Type Crops Only, 103,379, 55% Livestock Only, 2,412, 1% Crops and Livestock, 82,412, 44% Bunda Musoma Urban Serengeti Musoma Rural Tarime 20 2 6 32 21 Musoma Urban Musoma Rural Bunda Tarime 453 49,995 27,864 30,721 79,170 Serengeti Number of Agricultural Households 64,000 to 80,000 48,000 to 64,000 32,000 to 48,000 16,000 to 32,000 0 to 16,000 Total Number of Agricultural Households by District MAP 3.1 MARA MAP 3.2 MARA Number of Agricultural Households Per Square Kilometer of Land by District Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tanzania Agriculture Sample Census RESULTS 12 Musoma Rural Musoma Urban Bunda Tarime 49,023 440 30,646 27,588 78,094 Serengeti 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Bunda Musoma Rural Tarime Musoma Urban 99.8% 98.1% 97.1% 99% 98.6% Serengeti 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 MAP 3.4 MARA Percent of Crop Growing Households by District Percent of Households Growing Crops Percent of Household Growing Crops Number of Crop Growing Households by District Number of Households MAP 3.3 MARA Number of Household Growing Crops Tanzania Agriculture Sample Census RESULTS 13 Musoma Rural Musoma Urban Bunda Tarime 37% 37% 39% 45% 50% Serengeti 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tarime Musoma Rural Bunda Musoma Urban 6 21 32 2 20 Serengeti Number of Crop Growing Households Per Square Kilometer of Land by District Number of Crop Growing Households MAP 3.5 MARA Percent of Crop and Livestock Households MAP 3.6 MARA Percent of Crop and Livestock Households by District Number of Crop Growing Households Per Square Kilometer of Land Percent of Crop and Livestock Household 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tanzania Agriculture Sample Census RESULTS 14 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Mara region was 145,187 (77% of the total regional agricultural households) while the female-headed households were 43,016 (23%). The mean age of household heads in Mara region was 46 years (45 years for male heads and 48 years for female heads). The percentage trend based on six census/survey years shows that there has been a very small change in the distribution of agricultural households between male and female headed households (Chart 3.2). 3.1.4 Number and Age of Household Members Mara region had a total rural agricultural population of 1,097,742 of which 548,314 (50%) were males and 549,427 (50%) were females. Whereas age group 0-14 constituted 46 percent of the total rural agricultural population, age group 15–64 (active population) was only 50 percent (Chart 3.3). Mara region had an average household size of 5.8 persons with Musoma Rural and Bunda having the highest household size of 6.7 and Tarime district having the lowest household size of 4.9. 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all selected households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Chart 3.3 Percent Distribution of Population by Age and Sex 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literacy Level of Household Members by District 0 30 60 90 Musoma Urban Tarime Musoma Rural Serengeti Bunda District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 Literacy Level for Household Members Mara region had a total literacy rate of 72 percent. The highest literacy rate was found in Musoma Urban (81%), followed by Tarime district (74%) and Musoma Rural district (74%), Serengeti and Bunda districts had the lowest literacy rates of 69 percent each (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in Mara region was 73.5 percent. The literacy rate for male heads was 82.1 and that of female heads was 44.2 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Musoma Rural (76.8%), followed by Musoma Urban (74.6%), Bunda (73.1%), Tarime (72.2%) and Serengeti (71.6%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 44 percent of the population aged 5 years and above in agricultural households in Mara region had completed different levels of education and 32 percent were still attending school. Those who have never attended school were 24 percent (Chart 3.6). Agricultural households in Musoma Urban district had the highest percentage of population aged 5 years and above who had completed different levels of education (48.2%). This was followed by Musoma Rural (46.9%), Tarime district (44.2%), Serengeti district (41.0%) and Bunda district with 41 percent (Chart 3.7). The number of heads of agricultural households with formal education in Mara region was 135,160 (71.8%), those without any education were 50,764 (27.0%) and Chart 3.5 Literacy Rates of Head of Household by Sex and District 0.0 30.0 60.0 90.0 Tarime Serengeti Musoma Rural Bunda Musoma Urban District Percent Male Female Total Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed, 407,330, 44% Attending School, 301,073, 32% Never Attended, 218,909, 24% Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education, 2,280, 1.2% Post Primary Education, 10,501, 5.6% No Education, 50,764, 27.0% Primary Education, 124,659, 66.2% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 15 30 45 Tarime Serengeti Musoma Rural Bunda Musoma Urban District Percent Attending Completed Never Attended RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 those with only adult education were 2,280 (1.2%). The majority of heads of agricultural households in Mara region had primary level education (66.2%), whereas only 5.6 percent had post primary education (Chart 3.8). With regard to the heads of agricultural households with primary or secondary education in Mara region, Musoma Rural district had the highest percentage of household heads with primary education (70.5%) and the second lowest percent of household heads with secondary education (3.6%). This was followed by Bunda (69.1% for primary and 3.7% for secondary), Serengeti (65.9% for primary and 2.4% for secondary), Tarime (62.6% for primary and 6.7% for secondary) and Musoma Urban (55.7% for primary and 14.5% for secondary). The district with the highest percent of households with no education was Serengeti (30.2%), followed by Tarime (27.7%), Bunda (26%), Musoma Urban (25.4%) and Musoma Rural (24.6%). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Mara with 58.3 percent of households having at least one member with off-farm income. In the region, 72,002 households (38%) had only one member aged 5 and above involved in off-farm income generating activity, 25,816 households (14%) had two members involved in off-farm income generating activities and 11,969 households (6%) had more than two members involved in off-farm income generating activities. Households with no off-farm income in Mara region constitute 42 percent of the total agricultural households in the region (Chart 3.9). Bunda district had the highest percentage of agriculture households with off-farm income (66.3% of total agriculture households in the district), followed by Musoma Urban (62.5%), Musoma Rural (561.1%) and Tarime (56.8%). Serengeti district had the lowest percentage of agriculture households with off-farm income in the region (48.7%). The district with the highest percent of agriculture households with more than one member with off-farm income was Musoma Urban (24.5%), however Serengeti district had the lowest percent of households with more than one member having off-farm income (10.6%) (Chart 3.10). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Chart 3.9 Number of Households by Number of Members with Off-farm Income None, 78,415, 42% More than two, 11,969, 6% Two, 25,816, 14% One, 72,002, 38% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Household Members with Off-farm Income Activities 0% 25% 50% 75% 100% Tarime Musoma Rural Musoma Urban Bunda Serengeti Districts Percent More than two Two One None RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country, however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders in Mara region was 487,543 ha, however the utilisable land was 475,576 ha (95% of the land area available in the region). The regional average land area utilised for agriculture per household was only 1.9 ha. This figure is below the national average of 2.0 hectares. Large differences in land area utilised per household exist between districts with Serengeti and Bunda utilizing 2.5 ha per household in each district. The smallest land area utilised per household was found in Musoma Urban (0.8 ha). The percentage utilized of the usable land per household was highest in Musoma Urban (84.5%) and lowest in Serengeti (74.6%). About seventy six percent of the total land available to smallholders was utilised implying that only 24 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 157,427 hectares (32.3% of the total land available to smallholders in Mara region), followed by uncultivated usable land (109,823 ha, 22.5%), area under permanent mono crops (86,423 ha, 17.7%), area under temporary mixed crops (34,674 ha, 7.1%), area under permanent /annual mix (27,613 ha, 5.7%), area under fallow (20,348 ha, 4.2%), area under pasture (12,382 ha, 2.5%), area unusable (11,967 ha, 2.5%), area under planted tree (7,956 ha, 1.6%), area rented to others (7,836 ha, 1.6%), Area under permanent mixed crops (6,373 ha, 1.3%) and area under natural bush (4,720 ha, 1.0%) (Chart 3.12). Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Serengeti Bunda Musoma Rural Tarime Musoma Urban Districts Area per Household 0.0 20.0 40.0 60.0 80.0 100.0 Percentage Utilized Area Utilised (ha) per hh Total Usable Area Available (ha) Percent Utilisation Chart 3.12 Land Area by Type of Use 1.0 1.3 1.6 1.6 2.5 2.5 4.2 5.7 7.1 17.7 32.3 22.5 0 50,000 100,000 150,000 200,000 Natural Bush Permanent Mixed Crops Rented to Others Planted Trees Unusable Pasture Area under Fallow Permanent / Annual Mix Temporary Mixed Crops Permanent Mono Crops Uncultivated Usable Land Temporary Mono Crops Land Use Area (hectares) RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 19 3.3 Annual Crops and Vegetable Production Mara region has two rainy seasons, namely the short rainy season (October to December) and the long rainy season (March to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Planted Area The area planted with annual crops and vegetables in Mara region was 333,525 hectares out of which 120,270 hectares (36%) were planted during the short rainy season and 213,255 hectares (64%) during long rainy season (Chart 3.13). The average areas planted per household during the short and long rainy seasons was 0.65 and 1.15 ha respectively. The district with the largest area planted per household in Mara region was Serengeti (2.4 ha), followed by Bunda (2.1 ha) and Musoma Rural (1.8 ha). The district with the smallest average area planted per household was Tarime (1.5 ha). While in Bunda average planted area per household during the short rainy season is higher than that of the long rainy season, the reverse is true for the rest of the districts in the region (Chart 3.14 and Map 3.8). The average area planted per household during the long rainy season in Mara region was 1.7 hectares, however, there were large district differences. Although Musoma Urban had the largest planted area per household of 3.10 ha, it is difficulty to make concrete comments because of the small numbers involved. Bunda had the second largest planted area per household (2.10 ha), followed by Musoma Rural (1.85%) and Serengeti (1.73 ha). The smallest planted area per household during the long rainy season was in Tarime (1.51 ha). During the short rainy season, Bunda district had the largest planted area per household, followed by Serengeti, Musoma Rural and Tarime districts. In Mara region, there is a planted area of 0.8 ha more in the long rainy season compared to the short rainy season and most of the difference is in Musoma Rural district (Chart 3.15 and Map 3.9). Chart 3.14 Area Planted with Annual Crops by Season and District 0 30,000 60,000 90,000 Bunda Serengeti Tarime Musoma Rural Musoma Urban District Area Planted (ha) 0 20 40 60 80 100 Percentage Planted during Short Rainy Season Short Rainy Season Long Rainy Season % Area Planted in Short Rainy Season Chart 3.15 Area Planted with Annual Crop per Household by Season and District 0 1 2 3 Musoma Urban Bunda Musoma Rural Serengeti Tarime District A rea Planted per Household by Season 0 1 2 3 Overall A rea Planted per Household Long Rainy Season Short Rainy Season Total Chart 3.13 Area Planted with Annual Crops by Season (hectares) Short Rainy Season, 120,270, 36% Long Rainy Season, 213,255, 64% Long Rainy Season Short Rainy Season Bunda Musoma Urban Musoma Rural Tarime 64,272ha 65,165ha 732ha 88,024ha 115,331ha Serengeti 92,000 to 116,000 69,000 to 92,000 46,000 to 69,000 23,000 to 46,000 0 to 23,000 Bunda Musoma Urban Musoma Rural Tarime 77% 84.5% 74.9% 74.6% 76.7% Serengeti Utilized Land Area Expressed as a Percent of Available Land by District MAP 3.7 MARA Planted Area (ha) MAP 3.8 MARA Total Planted Area (Annual Crops) by District Planted Area (ha) Utilized Land Area Utilized Land Area Expressed as a Percent 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census RESULTS 20 Serengeti Musoma Urban Musoma Rural Bunda Tarime 40,017 55 28,391 28,070 65,168 2% 5% 3% 4% 1% Musoma Urban Musoma Rural Tarime Bunda 75 25,769 35,307 22,706 36,412 10% 29% 31% 35% 57% Serengeti 52,000 to 66,000 39,000 to 52,000 26,000 to 39,000 13,000 to 26,000 0 to 13,000 29,200 to 36,500 21,900 to 29,200 14,600 to 21,900 7,300 to 14,600 0 to 7,300 Area Planted and Percentage During the Short Rainy Season by District MAP 3.9 MARA Area Planted With Cereals Crops MAP 3.10 MARA Area Planted With Cereals and Percent of Total Land Planted With Cereals by District Area Planted With Cereals Area Planted During the Short Rainy Season Area Planted During the Short Rainy Season Percentage of Area Planted During Short Rainy Season Percent of Total Land Planted With Cereals Crops Tanzania Agriculture Sample Census RESULTS 21 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 22 Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Cassava is the dominant annual crop grown in Mara region and it had a planted area 1.3 times greater than Maize, which had the second largest planted area. The area planted with cassava constituted 34.7 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are sorghum, cotton, sweet potatoes, beans and finger millet (Chart 3.16). Chart 3.17a shows the area planted per household for selected crops. Households that grew finger millet, chick peas, cotton, cassava and mung beans had larger planted areas per household than those growing other crops. 3.3.3 Crop Types Cereals are the main crop type grown in Mara region. The area planted with cereals was 161,701 ha (48.5% of the total planted area), followed by roots and tubers with 133,117 ha (39.9%), annual cash crops (20,614 ha, 6.2%), pulses (14,438 ha, 4.3%), fruits and vegetables (2,110 ha, 0.6%) and oil seeds (1,572 ha, 0.5%) (Chart 17b). About 52 percent of cereals, 47 percent of pulses, 56 percent of oil seeds, 43 percent of fruit and vegetables and 90 percent of cash crops were planted during the short rainy season. 84,614 124,679 8,438 7,639 6,799 695 877 1,195 915 1,959 18,628 0 50,000 100,000 150,000 Area (hectares) Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & vegetables Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops Mara 0 30,000 60,000 90,000 120,000 Cassava Maize Sorghum Cotton Sweet Potatoes Beans Finger Millet Paddy Chich Peas Groundnuts Tomatoes Irish Potatoes Cabbage Crop Planted Area (ha) Chart 3.17b Percentage Distribution of Area Planted with Annual Crops by Crop Type Roots & Tubers 39.9% Cereals 48.5% Cash Crops 6.2% Pulses 4.3% Oil seeds & Oil nuts 0.5% Fruits & vegetables 0.6% Cereals Roots & Tubers Cash Crops Pulses Fruits & vegetables Oil seeds & Oil nuts Chart 3.17a Planted Area (ha) per Household for Selected Crop - Mara 0.00 0.40 0.80 1.20 Finger Millet Chich Peas Cotton Cassava Mung Beans Maize Cocoyam Sorghum Tobacco Paddy Ginger Groundnuts Irish Potatoes Beans Yams Sweet Potatoes Simsim Crop Planted Area (ha) RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 3.3.4 Cereal Crop Production The total production of cereals was 180,022 tonnes. Maize was the dominant cereal crop with a production of 110,662 tonnes which was 61.5 percent of total cereal crop production, followed by sorghum (30.3%), finger millet (4.8%) and paddy (3.5%). Tarime district had the largest planted area of cereals in the region (65,168 ha) followed by Serengeti (40,017 ha), Musoma Rural district (28,391 ha), Bunda district (28,070 ha) and Musoma Urban (55 ha) (Map 3.10). The total area planted with cereals during both the short and long rainy seasons was 161,701 ha out of which 84,614 ha (52%) were planted in short rainy season and 77,087 ha (48%) were planted during the long rainy season. The long rainy season accounted for 49.5 percent of the total cereals produced in both seasons. The area planted with maize during the long rainy season was 56.6 percent of the total area planted with cereals in that season followed by sorghum (32.6%) and finger millet (7.4%) (Table 3.2). The area planted with maize was dominant and it represented 57 percent of the total area planted with cereal crops, then followed by sorghum (34%), finger millet (6%), paddy (3%) and bulrush millet (0.02%). The yields of the main cereal crops were as follows; paddy 1,287 kg/ha, maize 1,205 kg/ha, sorghum 990 kg/ha and finger millet 862 kg/ha (Chart 3.19). Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Mara region during the long rainy season was 77,336 (41.1% of the total crop growing households in the region). The total production of maize was 110,662 tonnes from a planted area of 91,804 hectares resulting in a yield of 1.21 t/ha. Chart 3.20 shows the maize production trend (in thousand metric tonnes) for Mara region (combined long and short rainy seasons). There was a sharp drop in maize production from 106,000 tonnes in 1995 to 66,000 tonnes in 1996. This was followed by a gradual increase to 107,000 tonnes in 1999 after which the production remained more or less constant up to year 2003. The average area planted with maize per Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha ) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 48,177 55,996 1,162 43,628 54,666 1,253 91,804 110,662 1,205 Paddy 2,270 2,366 1,043 2,603 3,905 1,500 4,873 6,271 1,287 Sorghum 29,922 28,842 964 25,118 25,664 1,022 55,040 54,506 990 Finger Millet 4,245 3,776 889 5,712 4,807 842 9,957 8,583 862 Bulrush Millet 0 0 0 27 0 0 27 0 0 Total 84,614 90,980 77,087 89,042 161,701 180,022 Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 25,000 50,000 75,000 100,000 Maize Sorghum Finger Millet Paddy Bulrush Millet Crop Area Planted (ha) 0.00 0.50 1.00 1.50 Yield (t/ha) Yield (t/ha) Chart 3.20 Time Series Data on Maize Production - MARA 88 80 107 111 106 66 107 50 70 90 110 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey Year Prod u ction ('000') ton n es RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 24 household in the long rainy season was 0.56 hectares, however it ranged from 0.30 hectares in Musoma Urban district to 0.73 hectares in Bunda district (Map 3.11). Tarime district had the largest area of maize (39,273 ha), followed by Musoma Rural (19,326 ha), Serengeti (17,490 ha), Bunda (15,668 ha) and Musoma Urban (47 ha) (Chart 3.21 & Map 3.11 & 3.12). Charts 3.20 and 3.22 show that, from the year 1997 to 2003 there has been a gradual increase in yield from 0.6 tons/ha to 1.2 tons/ha as well as gradual decrease in area planted from 143,500 to 91,804 hectares. The quantity produced increased gradually over the same period from 88,200 tonnes to 110,665 tonnes. This trend indicates that the increase in maize production in the region was associated with the increase in yield (Chart 3.22). Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Mara region during the long rainy season was 54,589. This represents 43.7 percent of the total crop growing households in Mara region in the long rainy season. The total production of sorghum was 54,506 tonnes from a planted area of 55,040 hectares resulting in a yield of 0.99 t/ha. The district with the largest area planted with sorghum was Tarime (22,060 ha) followed by Serengeti (17,040 ha), Bunda (10,188 ha), Musoma Rural (5,751 ha) and Musoma Urban (1 ha) (Map 3.13). There are significant variations in the average area planted per sorghum growing household among the districts in the long rainy season ranging from 0.10 ha in Musoma Urban to 0.55 ha in Bunda (Chart 3.23 and Map 3.14). Chart 3.21 Total Area Planted and Planted Area per Maize Growing Household by District 47 39,273 19,326 17,490 15,668 0 10,000 20,000 30,000 40,000 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 Area per Household (ha) Planted area (ha) Area planted per Household (Ha) - Long Rainy Season Chart 3.23: Total Area Planted and Planted Area per Sorghum Growing Household by District 5,751 10,188 17,040 22,060 1 0 10,000 20,000 Tarime Serengeti Bunda Musoma Rural Musoma Urban District Area (ha) 0.0 0.2 0.4 0.6 Planted Area per Household (ha) Planted area (ha) Area planted per Household (Ha) - Long Rainy Season Chart 3.24 Time Series Data on Sorghum Production - MARA 29 26 55 44 57 55 43 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.22 Time Series of Maize Planted Area & Yield -MARA 0 50,000 100,000 150,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area (ha) Yield (t/ha) Bunda Musoma Urban Musoma Rural Tarime 0.65 0.33 0.51 0.62 0.6 Serengeti 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Area Planted Per Maize Growing Household by District Area Planted Per Household MAP 3.12 MARA Musoma Urban Musoma Rural Bunda Tarime 19,326ha 15,668ha 39,273ha 17,490ha 1.5t/ha 1.2t/ha 0.7t/ha 1.2t/ha 0.8t/ha Serengeti 47ha Planted Area and Yield of Maize by District MAP 3.11 MARA Planted Area (ha) Planted Area (ha) Yield (t/ha) 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Tanzania Agriculture Sample Census RESULTS 25 Bunda Musoma Urban Musoma Rural Tarime 0.7 0.5 0.1 0.4 0.5 Serengeti 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Musoma Urban Bunda Musoma Rural Tarime 10,188ha 5,751ha 22,060ha 17,040ha 1.1t/ha 0.7t/ha 1.1t/ha 0.7t/ha 1t/ha Serengeti 1ha Planted Area and Yield of Sorghum by District MAP 3.13 MARA Planted Area (ha) 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Area Planted Per Household MAP 3.14 MARA Area Planted Per Sorghum Growing Household by District Area Planted Per Household Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 26 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 There was an increase in sorghum production from 26,000 tonnes in 1995 to 57,000 tonnes in 1998 after which the production dropped to 43,000 tons by 2000. The production rose again to 55,000 tonnes in 2003. The area planted with sorghum has increased over the three year period from 1996 to 1998. During this period the region experienced decreasing yield in maize. Gradual increase in sorghum production during this period was mainly due to increase in area planted with sorghum. On the other hand, whilst the area planted with sorghum during the four year period from 1999 to 2003 was decreasing, the productivity per unit of land planted with sorghum was increasing. Increasing production from 2000 to 2003 is mainly attributed to the increasing yield (Charts 3.24 and 3.25). Other Cereals Other cereals (finger millet, paddy and bulrush millet) were produced in relatively small quantities compared to maize and sorghum. The district with the largest area planted with finger millet was Serengeti (3,820 ha, 38%) followed by Tarime (2,962 ha, 30%), Musoma Rural (1,742 ha, 17%) and Bunda (1,433 ha, 14%). There was no finger millet produced in Musoma Urban. The district with the highest area planted with paddy was Serengeti (1,641 ha, 33.7%) closely followed by Musoma Rural (1,572 ha, 32.3%), Tarime (872 ha, 17.9%), Bunda (781 ha, 16.0%) and Musoma Urban (7 ha, 0.1%). A small planted area (27ha) of bulrush millet was found in Serengeti district (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 161,111 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 115,747 tonnes representing 71.8 percent of the total root and tuber crops production in the region. This was followed by sweet potatoes with 43,234 tonnes (26.8%), Irish potatoes (1,781 tonnes, 1.1%), yams (277 tonnes, 0.2%) and cocoyam (71 tonnes 0.0%) (Chart 3.27 and Table 3.3). The area planted with cassava was larger than any other root and tuber crop and it was the most important crop in Mara in terms of planted area (34.7% of the total area planted with annual crops and vegetables and it accounted for 86.9 percent of 0 1,000 2,000 3,000 4,000 Area (Ha) Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.26 Area Planted with Paddy, Finger Millet and Bulrush Millet by District Paddy Fingermillet Bulrush millet Chart 3.25 Time Series of Sorghum Planted Area and Yield - MARA 0 30,000 60,000 90,000 120,000 150,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.3 0.6 0.9 1.2 1.5 Yield (t/ha) Area (ha) Yield (t/ha) Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 30,000 60,000 90,000 120,000 Cassava Sweet Potatoes Irish Potatoes Cocoyam Yams Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 Yield (kg/ha) Area Planted (ha) Yield (kg/ha) RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 the area planted with roots and tubers), followed by sweet potatoes (12.5%), Irish potatoes (0.4%), cocoyams (0.1%) and yams (0.1%). Cassava is produced in both the long and the short rainy seasons. However, it was not possible to separate cassava production by season as the growth period spans both seasons, even over a year for certain varieties. Because of this, cassava has been combined and reported under the long rainy season only. Because of this it is difficult to determine the total planted area and production for roots and tubers for individual seasons. However, excluding cassava, 53 percent of the area planted with roots and tubers was during the long rainy season. Sweet potatoes had the largest planted area in each season (95% and 96% in short and long rainy seasons respectively). The yield of Irish potatoes was 3.28 t/ha, that of yams was 2.62 t/ha, sweet potatoes 2.60 t/ha, cassava 1.00 t/ha and cocoyams 0.66 t/ha (Table 3.3). Cassava The number of households growing cassava in Mara region during the long rainy season was 138,982. This represented 74 percent of the total crop growing households in the region. The total production of cassava during the census year was 115,747 tonnes from a planted area of 115,739 hectares resulting in a yield of 1.0 t/ha. Previous censuses and surveys indicate that the area planted with cassava increased gradually over the period 1995 to 1998 after which it decreased in the year 1999 after which there was a small increase in year 2003 (Chart 3.28). The area planted with cassava accounted for 34.7 percent of the total area planted with annual crops and vegetables in the census year. Tarime district had the largest planted area of cassava (41,581 ha, 35.9% of the cassava planted area in the region), followed by Musoma Rural (41,207 ha, 35.6 %), Bunda (16,599 ha, 14.3%), Serengeti (15,760 ha, 13.6%) and Musoma Urban (592 ha, 0.5%) (Map 3.15). However, the percent of the total with cassava for Musoma Urban is comparably high and is considered as unrepresentative due to the small number of observations in the district. The second highest proportion of land planted with cassava, was Musoma Rural district (46.8%), followed by Tarime (36.1%), Bunda (25.8%) and Serengeti (24.2%) (Chart 3.29). Table 3.3: Area, Quantity and Yield of Roots and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Cassava 0 0 0 115,739 115,747 1,000 115,739 115,747 1,000 Sweet Potatoes 7,714 20,906 2,710 8,907 22,328 2,507 16,621 43,234 2,601 Irish Potatoes 299 1,372 4,584 244 409 1,679 543 1,781 3,281 Yams 23 14 603 83 263 3,190 106 277 2,623 Cocoyam 94 2 21 14 70 4,883 108 71 661 Total 8,130 22,294 124,987 138,817 133,117 161,111 Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 40,000 80,000 120,000 160,000 1994/95 1995/96 1997/98 1998/99 2002/03 Census/Survey Years Planted Area (ha) Chart 3.29 Percent of Cassava Planted Area and Percent of Total Planted Area with Cassava by District 0.5 13.6 35.6 14.3 35.9 0 10 20 30 40 Tarime Musoma Rural Bunda Serengeti Musoma Urban District Percent of Total Area Planted 0 20 40 60 80 Percent of Total Planted Area With Cassava Percent of Area Planted Proportion of Total Planted Area with Cassava Bunda Musoma Urban Musoma Rural Tarime Serengeti 16,599ha 592ha 41,207ha 41,581ha 0.59t/ha 0.88t/ha 0.98t/ha 0.4t/ha 1.24t/ha 15,760ha 32,000 to 42,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Musoma Rural Musoma Urban Bunda Tarime 0.97 1.64 0.85 0.68 0.93 Serengeti 1.6 to 2 1.2 to 1.6 0.8 to 1.2 0.4 to 0.8 0 to 0.4 Planted Area and Yield of Cassava by District MAP 3.15 MARA Area Planted Per Household MAP 3.16 MARA Area Planted Per Cassava Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 29 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 The average cassava planted area per cassava growing households was 0.83 hectares. However, with exception of Musoma Urban, there were small district variations in average area planted with cassava per household among the rest of the districts. The largest planted area per cassava growing household was found in Musoma Urban (1.64 ha). This is followed by Musoma Rural (0.98 ha), Serengeti (0.94 ha), Bunda (0.85 ha) and Tarime (0.69 ha) (Chart 3.30 and Map 3.16). Sweet Potatoes The number of households growing sweet potatoes in Mara region during the long rainy season was 36,514 (19.3% of the total crop growing households in the region). The total production of sweet potatoes during the census year was 43,234 tonnes from a planted area of 16,621 hectares resulting in a yield of 2.6 t/ha. The district with the largest planted area with sweet potatoes was Musoma Rural (7,458 ha, 44.9%), followed by Tarime (4,347 ha, 26.2%), Bunda (2,633 ha, 15.8%), Serengeti (2,119 ha, 12.7%) and Musoma Urban (63 ha, 0.4). However, the largest planted area per sweet potato growing household during the long rainy season was found in Serengeti (0.27 ha, followed by Musoma Rural (0.26 ha), Tarime (0.22 ha), Bunda (0.200 ha), and Musoma Urban (0.19ha) (Chart 3.31). 3.3.6 Pulse Crops Production The total area planted with pulses was 14,438 hectares out of which 11,726 ha were planted with beans (81.2 percent of the total area planted with pulses), followed by chick peas (2,070 ha, 14.3%), cowpeas (278 ha, 1.9%), bambaranuts (256 ha, 1.8%) and mung beans (108 ha, 0.7%)(Chart 3.32). The area planted with pulses in the short rainy season was 6,799 ha which represented 47.1 percent of total area planted with pulses during the year. Beans were the dominant pulse crop grown during the short rainy Chart 3.32 Area Planted and Yield of Major Pulses 0 3,000 6,000 9,000 12,000 Beans Chich Peas Cowpeas Bambara nuts Mung Beans Crop Area Planted (ha) 0 500 1,000 1,500 2,000 2,500 Yield (kg/ha) Yield (Kg/ha) 1.64 0.98 0.94 0.85 0.69 0.0 0.5 1.0 1.5 2.0 Area per Household(ha) Musoma Urban Musoma Rural Serengeti Bunda Tarime District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District - Long Rainy Season Chart 3.31 Total Area Planted with Sweet Potatoes and Planted Area per Household by District - Long Rainy Season 0 1,500 3,000 4,500 Musoma Rural Tarime Serengeti Bunda Musoma Urban District Area (ha) 0.0 0.1 0.2 0.3 Area Planted per Household (ha) Planted area (ha) Planted Area per Household (ha)- Long Rainy Season RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 31 season with 6,383 ha (93.9 % of the total area planted with pulses in that particular season), followed by chick peas (186 ha, 2.7%), bambaranuts (134 ha, 2.0%) and cowpeas (97 ha, 1.4%). Mung beans were not grown in the short rainy season. Beans were also the dominant pulse crop grown during the long rainy season in Mara region (Table 3.4). The total production of pulses was 9,295 tonnes. Beans were the most cultivated crop producing 7,612 tonnes which accounted for 82 percent of the total pulse production. This was followed by chick peas (1,073t, 12%), cow peas (280t, 3%), mung beans (240t, 2.6%) and bambara nuts (90t, 1.0%). The yield for mung beans is very high and this may be the results of the small number of observations involved, however cow peas had a relatively high yields of 1,008 kgs/ha. The yields of the rest of the pulses in kilograms per hectare were beans 649 kgs/ha, chick peas 518 kgs/ha and bambara nuts 351 kgs/ha. (Table 3.4) 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Mara region during the long rainy season was 20,683. The total production of beans in the region was 7,612 tonnes from a planted area of 11,726 hectares resulting in a yield of 0.65 t/ha. The largest planted area with beans in the region was in Musoma Rural district (4,173 ha, 35.6%), followed by Bunda (2,974 ha, 25.4%), Serengeti (2,538 ha, 21.6%), Tarime (2,035 ha, 17.4%) and Musoma Urban (6 ha, 0.05%) (Chart 3.33 and Map 3.17). The average area planted per household in the region during the long rainy season was 0.26 ha. However, there were great variations in the area planted with beans per household among the districts ranging from 0.47 ha in Serengeti district to 0.15 ha in Musoma Urban district. The district with the largest area planted with beans per household was Serengeti (0.47 ha), followed by Bunda (0.33 ha), Musoma Rural (0.21 ha), Tarime (0.19 ha) and Musoma Urban (0.15 ha) (Chart 3.34 and Map 3.18). Table 3.4: Area, Quantity and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Mung Beans 0 0 0 108 240 2,223 108 240 2,223 Beans 6,383 4,093 641 5,343 3,519 659 11,726 7,612 649 Cowpeas 97 22 228 181 258 1,425 278 280 1,008 Chich Peas 186 123 661 1,884 950 504 2,070 1,073 518 Bambaranuts 134 57 430 122 33 266 256 90 351 Total 6,799 4,295 7,639 4,999 14,438 9,295 0.47 0.33 0.21 0.19 0.15 0.00 0.15 0.30 0.45 Area per Household (ha) Serengeti Bunda Musoma Rural Tarime Musoma Urban District Chart 3.34 Area Planted per Bean Growing Household by District - Long Rainy Season Chart 3.33 Percent of Bean Planted Area and Percent of Total Planted Area with Beans by District 0.0 17.4 21.6 35.6 25.4 0 10 20 30 40 Musoma Rural Bunda Serengeti Tarime Musoma Urban District Percent of Total Area Planted 0 1 2 3 4 5 Percent of Total Planted Area with Beans Percent of Total Area Planted Proportion of Total Planted Area with Beans Musoma Urban Musoma Rural Bunda Tarime 2,974ha 4,173ha 2,035ha 2,538ha 5t/ha 1t/ha 4t/ha 3t/ha 2t/ha Serengeti 6ha Musoma Rural Bunda Musoma Urban 0.1 0.2 0.2 0.3 0.4 Tarime Serengeti 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Planted Area and Yield of Beans by District MAP 3.17 MARA Area Planted Per Household MAP 3.18 MARA Area Planted Per Beans Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 32 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 33 Apart from a large increase in the quantity of beans produced in the region during 1997/98, there has been a gradual increase in production from 2,000 tonnes in 1994 to 8,000 tonnes in 2003. The reason for the peak in 1997/98 may be due to the El - Nino or it may be the result of the sampling technique used that year (Chart 3.35). The area planted with beans increased sharply over the period from 1995 to 1997 and has remained constant up to the year 2000. The planted area has declined slightly over the period 2000 to 2003 (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 1,459 tonnes planted on an area of 1,572 hectares. The total planted area with oilseeds in the long rainy season was 695 ha representing 44.2 percent of the total area planted with oil seeds. Groundnuts were the most important oilseed crop with 1,337 ha (85.0% of the total area planted with oil seeds), followed by simsim (176 ha, 11.2%), soya beans (38 ha, 2.4%) and sunflower (21 ha, 1.3%). The yield of soya beans was high (1,341 kg/ha), that of groundnuts was 1,011 kg/ha, for sunflower it was 346 kg/ha) and for simsim it was 275 kg/ha (Chart 3.37). The production of groundnut was 1,352 tonnes accounting for 92.7 percent of the total production of oil seeds, followed by soya beans (57 ha, 3.5%), simsim (48 ha, 3.3%) and sunflower (7 ha, 0.5%). (Table 3.5) Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Sunflower 21 7 346 0 0 0 21 7 346 Simsim 73 21 293 103 27 262 176 48 275 Groundnuts 761 797 1,047 577 555 964 1,337 1,352 1,011 Soya Beans 22 27 1,235 16 24 1,482 38 51 1,341 Total 877 853 695 607 1,572 1,459 Chart 3.36 Time Series of Beans Planted Area & Yield - MARA 0 5,000 10,000 15,000 20,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 Yield (t/ha) Area (ha) Yield (t/ha) Chart 3.35: Time Series Data on Beans Production - MARA 6 6 23 6 8 2 3 0 5 10 15 20 25 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Year Production ('000') tons Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 500 1,000 1,500 Groundnuts Simsim Soya Beans Sunflower Crop Area Planted (ha) 0 500 1,000 1,500 Yield (kg/ha) Yield (Kg/ha) RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 Groundnuts The number of households growing groundnuts in Mara region during the short rainy season was only 1,978. The total production of groundnuts in the region was 1,352 tonnes from a planted area of 1,337 hectares resulting in a yield of 1.0 t/ha. With exception of the year 1997 and 2003 in which the area planted were 1,571 and 1,337 hectares respectively, the area planted with groundnut from 1995 to 2003 in Mara region has remained almost constant at around 650 hectares (Chart 3.38). Fourty percent of the area planted with groundnuts was located in Musoma Rural district (539 ha) followed by Bunda (361ha, 27.0%), Tarime (332 ha, 24.8%), Serengeti (105 ha, 7.8%) and Musoma Urban (1 ha, 0.05%) (Map 3.19). The district with the highest proportion of land for groundnuts was Tarime, followed by Serengeti, Musoma Rural, Bunda and Musoma Urban (Chart 3.39 and Map 3.19). The area planted per groundnut growing household was largest in Musoma Rural district (0.42 ha) and the lowest in Bunda (0.00). The planted area with groundnuts per housegold in other districts range from 0.34 ha in Tarime to 0.23 ha in Serengeti and 0.10 ha in Musoma Urban (Chart 3.40 and Map 3.20). 3.3.8 Fruits and Vegetables The collection of fruit and vegetable production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of small holders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops. Both short and long rainy seasons are almost equally important in fruit and vegetable production. While 43 percent of the total planted area with fruits and vegetables was found in the short rainy season, 57 percent was in the long rainy season. While 100 percent of the planted area for bitter aubergine, garlic, cucumber and water mellon was produced during the short rainy season, 100 percent of ginger was produced during the long rainy season. The rest of the fruit and vegetables were produced in both seasons. Reliable historical data for time series analysis of fruit and vegetables were not available 0 400 800 1200 1600 Planted Area (ha) 1994/95 1995/96 1996/97 1997/98 1998/99 2002/03 Year Chart 3.38 Time Series Data on Groundnuts Planted Area 0.42 0.34 0.23 0.10 0.00 0.00 0.15 0.30 0.45 Area per Household (ha) Musoma Rural Tarime Serengeti Musoma Urban Bunda District Chart 3.40 Area Planted per Groundnut Growing Households by District Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Planted Area with Groundnuts by District 0 15 30 45 Musoma Rural Bunda Tarime Serengeti Musoma Urban District Percent of Total Area Planted 0.000 0.200 0.400 0.600 0.800 Percent Planted Area with Groundnuts Percent of Total Area Planted Proportion of Planted Area with Groundnuts Bunda Tarime Musoma Urban Musoma Rural 0.5 0.3 0.4 0.3 0.1 Serengeti 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Bunda Musoma Rural Musoma Urban Tarime 361ha 539ha 332ha 105ha 0.7t/ha 1.7t/ha 0.3t/h 0.6t/ha 0t/ha Serengeti 1ha Area Planted Per Household MAP 3.20 MARA Area Planted per Groundnuts Growing Household by District Area Planted Per Household Planted Area and Yield of Groundnuts by District MAP 3.19 MARA Planted Area (ha) Yield (t/ha) 600 to 700 500 to 600 400 to 500 200 to 400 0 to 200 Planted Area (ha) Tanzania Agriculture Sample Census RESULTS 35 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 The total production of fruits and vegetables was 6,981 tonnes. The most cultivated fruit and vegetable crop was the tomato with a production of 3,801 tonnes (54% of the total fruits and vegetables produced), followed by cabbage (1,683t, 24%) and onions (906t, 13%). The production of the other fruit and vegetable crops was relatively small (Table 3.6). Cabbage had a yield of 4,423 kg/ha, onions 3,674 kg/ha, tomatoes 3,514 kg/ha and ginger 2,470 kg/ha. Spinnach and pumpkins had yields of 871 and 109 kg/ha respectively (Chart 3.41 and Table 3.6). Tomatoes The number of households growing tomatoes in the region during the long rainy season was 3,662 which represent 2.9 percent of the total crop growing households in the region during the long rainy season. Tarime district had the largest planted area of tomatoes (49.2% of the total area planted with tomatoes in the region), followed by Musoma Rural (21.4%), Serengeti (21.3%), Bunda (7.1%) and Musoma Urban (1.0%) (Chart 3.42 and Map 3.21) The proportion of total planted area with tomatoes in the region was very high in Musoma Urban district and this is probably the result of the small number of observations involved, however when compared with other districts in the region, Tarime had a relatively high proportion of its total planted area with tomatoes. This is followed by Serengeti, Musoma Rural and Bunda (Chart 3.42). The distrct with the largest planted area per tomato growing household was in Musoma Urban district (0.24 ha), followed by Tarime (0.20 ha), Serengeti (0.19 ha), Musoma Rural (0.12 ha) and Bunda (0.10 ha) (Chart 3.43 and Map 3.22). The total area planted with tomatoes accounted for 0.3 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy season Long Rainy season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Bitter Aubergine 16 16 988 0 0 0 16 16 988 Garlic 27 0 0 0 0 0 27 0 0 Onions 95 362 3,829 152 544 3,578 247 907 3,674 Cabbage 123 333 2,702 257 1,350 5,249 381 1,683 4,423 Tomatoes 479 1,603 3,346 603 2,198 3,647 1,082 3,801 3,514 Spinnach 53 48 889 58 49 853 111 97 871 Amaranths 57 51 896 59 228 3,857 116 279 2,404 Pumpkins 12 1 59 12 2 158 24 3 109 Cucumber 24 24 1,039 0 0 0 24 24 1,039 Water Mellon 29 37 1,263 0 0 0 29 37 1,263 Ginger 0 0 0 54 135 2,470 54 135 2,470 Total 915 2,475 1,195 4,506 2,110 6,981 Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 300 600 900 1,200 Tomatoes Cabbage Onions Amaranths Spinnach Ginger Other Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) 0.24 0.20 0.19 0.12 0.10 0.00 0.10 0.20 0.30 Area per Household (ha) Musoma Urban Tarime Serengeti Musoma Rural Bunda District Chart 3.43 Area Planted per Tomato Growing Household by District Chart 3.42 Percent of Tomato Planted Area and Percent of Total Planted Area with Tomato by District 0.0 15.0 30.0 45.0 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Percent of Total Area Planted 0.00 0.30 0.60 Percent of Total Planted Area With Tomatoes Proportion of Total Planted Area with Tomato RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 37 Cabbage The number of households growing cabbages in the region during the long rainy season was 1,491 and 1,008 in the short rainy season. This represented 1.2 percent of the total crop growing households in the region in the long rainy season and 0.8 percent in the short rainy season. Tarime district had the largest planted area of cabbage (196 ha, 51.4% of the total area planted with cabbage in the region), followed by Musoma Rural (92 ha, 24.3%), Bunda (51 ha, 13.4%), Serengeti (41 ha, 10.7%) and Musoma Urban (1 ha, 0.2%) (Chart 3.44 and Map 3.23 and 3.24). The total area planted with cabbages accounted for 0.1 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Onions The number of households growing onions in the region during the long rainy season was 1,010 households and 538 in the short rainy season. This represented 0.81 percent of the total crop growing households in the region in the long rainy season and 0.42 percent in the short rainy season. Tarime district had the largest planted area of onions (189 ha, 76.5% of the total area planted with onions in the region), followed by Serengeti (31 ha, 12.5%), Bunda (15 ha, 6.3%) and Musoma Rural (12 ha, 4.7%). There was no onion production in Musoma Urban district (Map 3.25 and 3.26). The total area planted with onions accounted for 0.07 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 20,587 ha was planted with other annual crops mainly cotton and tobacco representing 6.2 percent of total planted area in the region. The area planted with annual cash crops in the short rainy season was 18,628 ha which represents 15.5 percent of the total area planted with annual crops in short rainy season. The area planted with annual cash crops in long rainy season was 1,959 ha representing 0.9 percent of the total area planted with annual crops during the long rainy season Chart 3.46 Area planted with Annual Cash Crops Tobacco, 244, 1% Cotton, 20,342, 99% Chart 3.45 Percent of Onions Planted Area and Percent of Total Planted Area with Onions by District 0.0 20.0 40.0 60.0 80.0 Tarime Serengeti Bunda Musoma Rural Musoma Urban District Percent of Total Area Planted 0.00 0.05 0.10 0.15 0.20 Percent of Total Planted Area With Onions Proportion of Total Planted Area with Onions Chart 3.44 Percent of Cabbage Planted Area and Percent of Total Planted Area with Cabbage by District 0.0 20.0 40.0 60.0 Tarime Musoma Rural Bunda Serengeti Musoma Urban District Percent of Total Area Planted 0.00 0.05 0.10 0.15 0.20 Percent of Total Planted Area With Cabbages Proportion of Total Planted Area with Cabbages Tarime Musoma Urban Musoma Rural Bunda 532ha 11ha 232ha 77ha 231ha 2.9t/ha 3.7t/ha 5.1t/ha 4.5t/ha 3.2t/ha Serengeti 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Tarime Bunda Musoma Urban Musoma Rural 0.2 0.2 0.1 0.3 0.2 Serengeti Planted Area and Yield of Tomatoes by District MAP 3.21 MARA Area Planted Per Household (ha) MAP 3.22 MARA Area Planted Per Tomato Growing Household by District Area Planted Per Household (ha) Planted Area (ha) Planted Area(ha) Yield (t/ha) 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Tanzania Agriculture Sample Census RESULTS 38 Musoma Urban Bunda Musoma Rural Tarime 0.2ha 0.1ha 0.1ha 0.2ha Serengeti 0.1ha 0.2 to 0.25 0.15 to 0.2 0.1 to 0.15 0.05 to 0.1 0 to 0.05 Musoma Urban Musoma Rural Bunda Serengeti Tarime 92ha 51ha 41ha 196 2.4t/ha 5.7t/ha 3.5t/ha 6.2t/ha 3.7 1ha Planted Area and Yield of Cabbages by District MAP 3.23 MARA Area Planted per Household (ha) MAP 3.24 MARA Area Planted Per Cabbage Growing Household by District Area Planted per ousehold (ha) Planted Area(ha) Planted Area(ha) Yield (t/ha) 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Tanzania Agriculture Sample Census RESULTS 39 Bunda Musoma Urban Musoma Rural Tarime 0.1 0.1 0 0.1 0.2 Serengeti Musoma Rural Bunda Musoma Urban Tarime 12ha 15ha 189ha 31ha 3.8t/ha 1.7t/ha 3.8t/ha 4.1t/ha Serengeti 0t/ha 152 to 189 114 to 152 76 to 114 38 to 76 0 to 38 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Planted Area and Yield of Onions by District MAP 3.25 MARA Area Planted Per Household MAP 3.26 MARA Area Planted Per Onions Growing Household by District Area Planted per Household Planted Area (ha) Planted Area(ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 40 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 Cotton The quantity of cotton produced was 14,191 tonnes. Cotton had a total planted area of 20,342 ha (18,443 and 1,899 ha planted during short and long rainy seasons respectively). Cotton production is concentrated in 3 districts with Bunda having the largest planted area (55.3% of total area planted with cotton in the region), followed by Musoma Rural (25.2%) and Serengeti (19.5%) (Chart 3.47 Map 3.27 and 3.28). Tobbaco Only 93 tonnes of tobacco were produced in Mara region from a planted area of 244 ha and virtually all of it was produced during the short rainy season. The crop is grown in Tarime, Musoma Rural and Serengeti districts (Map 3.29). The district with the largest planted area per household was Musoma Rural (0.8 ha), followed by Tarime (0.3 ha) and Serengeti (0.1 ha) (Map 3.30). 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crops. In this report the agriculture census results are presented for the most important permanent crops in terms of area planted, production and yield. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The smallholder planted area of permanent crops was 16,835 hectares (5% of the total plated area of annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of annual crops planted more than once on the same land, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage area planted with permanent crops would be higher than indicated in Chart 3.48. 0.0 20.0 40.0 60.0 Bunda Musoma Rural Serengeti Tarime Musoma Urban District Percent of Total A rea Planted 0.0 6.0 12.0 18.0 Percent of Total Planted A rea W ith C otton Proportion of Total Planted Area with Cotton Chart 3.48 Area Planted for Annual and Permanent Crops Permanent Crops, 16,835, 5% Annual Crops, 333,525, 95% Musoma Urban Bunda Musoma Rural 0.8 0.9 0.1 0 Tarime Serengeti 0 Musoma Rural Bunda Musoma Urban Tarime 5,117ha 11,251ha 3,975ha 0.66t/ha 0t/ha 0.7t/ha 0t/ha 0.72t/ha Serengeti 0ha 0ha 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Planted Area and Yield of Cotton by District MAP 3.27 MARA Area Planted Per Household MAP 3.28 MARA Area Planted per Cotton Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 42 Bunda Musoma Urban Musoma Rural 0.1 0 0 0.3 0.8 Tarime Serengeti Musoma Rural Musoma Urban Tarime Bunda Serengeti 7ha 0ha 171ha 66ha 0ha 0t/ha 0t/ha 0.5t/ha 0t/ha 0t/ha Planted Area and Yield of Tobbaco by District MAP 3.29 MARA Area Planted Per Household MAP 3.30 MARA Area Planted Per Tobbaco Growing Households by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Tanzania Agriculture Sample Census RESULTS 43 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 44 The most important permanent crop in Mara region was banana which had a planted area of 4,376 ha (27% of the planted area with permanent crops), followed by coffee (3,771 ha, 22%), pomelo (3,328 ha, 20%)2, mango (1,701 ha, 10%), orange (1,169 ha, 7%), pawpaw (991 ha, 6%) and sugarcane (383 ha, 2%). Each of the remaining permanent crops had an area of less than 2 percent of the total area planted with permanent crops in Mara region (Chart 3.49). Tarime district had the largest area under smallholder permanent crops (12,727 ha, 76%). This was followed by Serengeti (1,399 ha, 8%), Bunda (1,248 ha, 7%), Musoma Rural (1,056 ha, 6%) and Musoma Urban (405 ha, 2%). Musoma Urban had the largest planted area per permanent crop growing household (1.96 ha), however this may have resulted from the small number of observations. This is followed by Bunda (0.68 ha), Tarime (0.46 ha), Serengeti (0.20 ha) and Musoma Rural (0.05 ha) (Chart 3.50). In terms of planted area of permanent crops expressed as a percentage of the total area planted with crops, Musoma Urban had the highest percent (35.6%), followed by Tarime (9.9%), Serengeti (2.1%), Bunda (1.9%) and Musoma Rural (1.2%). 3.4.1 Banana The total production of banana by smallholders was 12,953 tonnes. Banana was the most important permanent crop grown by smallholders in the region. They were grown by 13,118 households (7.1% of the total crop growing households). The average planted area per banana growing household was relatively small (0.33 ha per banana growing household) and the average yield obtained by smallholders was 5.25 t/ha from a harvest area of 2,467 hectares. Tarime had the largest area of bananas in the region (3,923 ha, 89.7%), followed by Serengeti (257 ha, 5.9%), Musoma Rural (188 ha, 4.3%) and Musoma Urban (8 ha, 0.2%). There was no banana production in Bunda district (Map 3.31). Although the average area planted with banana per banana growing household was highest in Musoma Urban (0.6 ha), caution must be taken in using these figures because of the small number of observations involved. This is followed by Tarime (0.4 ha), Serengeti (0.3 ha) and Musoma Rural (0.1 ha) (Chart 3.51 Map 3.32). 2 The data for pomello seems to be very high and unrepresentative of the situation found at field level. It is therefore not considered an important crop in the region and will not be analysed separately in the following sections. Chart 3.50 Percent of Area Planted and Average Planted Area with Permanent Crops by District 8 7 6 2 76 0 20 40 60 80 Tarime Serengeti Bunda Musoma Rural Musoma Urban District Percent of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51 Percent of Area Planted with Banana and Average Planted Area per Household by District 5.9 0.2 89.7 0.0 4.3 0.0 25.0 50.0 75.0 100.0 Tarime Serengeti Musoma Rural Musoma Urban Bunda District Percent of Total Area Planted 0.0 0.2 0.4 0.6 0.8 Average Planted Area per Household Percent of Total Area Planted Average Planted Area per Household Chart 3.49 Area Planted with the Main Permanent Crops Coffee, 3,771, 22% Pomelo, 3,328, 20% Mango, 1,701, 10% Orange, 1,169, 7% Pawpaw, 991, 6% Sugarcane, 383, 2% Banana, 4,376, 27% Lime/Lemon, 210, 1% Other, 381, 2% Mandarine/Tangeri ne, 225, 1% Guava, 299, 2% Musoma Urban Musoma Rural Bunda 0.4 0.6 0.3 0.1 0 Tarime Serengeti 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0.1 to 0.2 0 to 0.1 Bunda Musoma Urban Musoma Rural Tarime 0ha 8ha 188ha 3,923ha 257ha 0t/ha 49.1t/ha 13.1t/ha 5t/ha 3.2t/ha Serengeti 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Planted Area and Yield of Banana by District MAP 3.31 MARA Area Planted Per Household MAP 3.32 MARA Area Planted Per Banana Growing Households by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 45 Musoma Urban Musoma Rural Bunda Tarime 0 0 0.1 0.5 0.3 Serengeti Musoma Urban Bunda Tarime 40ha 0ha 3,687ha 44ha 0t/ha 0t/ha 0.2t/ha 0.8t/ha 0t/ha Serengeti Musoma Rural 0ha 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 2,800 to 3,700 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Planted Area and Yield of Coffee by District MAP 3.33 MARA Area Planted Per Household MAP 3.34 MARA Area Planted Per Coffee Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 46 Bunda Musoma Rural Tarime Musoma Urban 0.6 0.1 0.2 8.8 0.1 Serengeti 7 to 8.8 5.4 to 7 3.6 to 5.4 1.8 to 3.6 0 to 1.8 Musoma Urban Bunda Musoma Rural Tarime 348ha 531ha 428ha 78ha 0t/ha 4.2t/ha 0t/ha 26.8t/ha 0t/ha Serengeti 317ha Planted Area and Yield of Mango by District MAP 3.35 MARA Area Planted Per Household MAP 3.36 MARA Area Planted Per Mango Growing Households by District Area Planted Per Household Planted Area (ha) Planted Area (ha) Yield (t/ha) 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census RESULTS 47 Musoma Urban Musoma Rural Bunda Tarime 0.4 0.1 0.2 0 0.2 Serengeti 0.4 to 0.4 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Musoma Rural Bunda Musoma Urban Tarime 113ha 60ha 318ha 677ha 1.6t/ha 0.9t/ha 59.5t/ha 22.6t/ha 11.5t/ha Serengeti 2ha 160 to 180 120 to 160 80 to 120 40 to 80 0 to 40 Planted Area and Yield of Orange by District MAP 3.37 MARA Area Planted Per Household MAP 3.38 MARA Area Planted Per Orange Growing Household by District Area Planted per Household Planted Area(ha) Planted Area(ha) Yield(t/ha) Tanzania Agriculture Sample Census RESULTS 48 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 3.4.2 Coffee The total production of coffee by smallholders was 2,246 tonnes. In terms of area planted, coffee was the second most important permanent crop, grown by smallholders in the region. It was grown by 7,581 households (4.1% of the total crop growing households). The average area planted with coffee per household was relatively small at around 0.50 ha per coffee growing household and the average yield obtained by smallholders was 820 kg/ha from a harvest area of 2,738 hectares. Tarime had the largest area of coffee in the region (3,687 ha, 97.8%), followed by Serengeti (44 ha, 1.2%) and Musoma Rural (40 ha, 1.1%) (Map 3.33). The average area planted with coffee per coffee planting household was highest in Tarime (0.52 ha), followed by Serengeti (0.31 ha) and Musoma Rural (0.12 ha) (Chart 3.52). There was no coffee production in Bunda and Musoma Urban districts (Chart 3.52 and Map 34). 3.4.3 Mango The total production of mango by smallholders was 5,573 tonnes. In terms of area planted, mango was the third most important permanent crop grown by smallholders in the region. It was grown by 10,065 households (5.4% of the total crop growing households). The average area planted with mango per household was relatively small (0.17 ha per mango growing household) and the average yield obtained by smallholders was 22.4 t/ha from a harvest area of 249 hectares. Musoma Rural district had the largest area of mango in the region (531 ha, 31.2%), followed by Tarime (428 ha, 25.2%), Bunda (348 ha, 20.5%), Musoma Urban (317 ha, 18.6%) and Serengeti (78 ha, 4.6%) (Map 3.35). The average area planted per mango growing household was highest in Musoma Urban (2.6 ha), followed by Bunda (0.64 ha), Tarime (0.21 ha), Musoma Rural (0.09 ha) and Serengeti (0.06 ha) (Chart 3.53 and Map 3.36). 3.4.4 Orange The total production of orange by smallholders was 3,854 tonnes. In terms of area planted, orange was the fourth most important permanent crop grown by smallholders in the region. It was grown by 6,978 households (3.8% of the total crop growing households). The average area planted with orange per household was relatively small at around 0.16 ha per orange growing household and the average yield obtained by smallholders was 6.3 t/ha from a harvested area of 613 hectares. Chart 3.52 Percent of Area Planted with Coffee and Average Planted Area per Household by District 0.0 1.1 1.2 0.0 97.8 0.0 25.0 50.0 75.0 100.0 Tarime Serengeti Musoma Rural Bunda Musoma Urban District Percent of Area Planted 0.00 0.20 0.40 0.60 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Mango and Average Planted Area per Household by District 4.6 20.5 25.2 18.6 31.2 0 10 20 30 40 Musoma Rural Tarime Bunda Musoma Urban Serengeti District Percent of Area Planted 0.00 1.00 2.00 3.00 Average Planted Area per Household Percent of Total Area Planted Average Planted Area per Household RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 Serengeti had the largest planted area of orange in the region (677 ha, 57.9%), followed by Tarime (318 ha, 27.2%), Musoma Rural (113 ha, 9.6%), Bunda (60 ha, 5.1%) and Musoma Urban (2 ha, 0.1%) (Map 3.37). The area planted with orange per orange growing household was highest in Serengeti (0.41 ha), followed by Tarime (0.18 ha) and Bunda (0.16 ha). Musoma Rural had the smallest area planted with orange per orange growing household (Chart 3.54 and Map 3.38). 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in Mara region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in Mara region during the long rainy season was 82,625 ha which represents 84.2 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 3.2, 1.0 and 0.4 percent respectively (Chart 3.55 and Table 3.7 ). 3.5.2 Methods of Soil Preparation Ox-ploughing was the most used method of soil preparation as was used on an area of 144,920 ha which represented 66 percent of the total area cultivated, followed by hand hoe cultivation (71,848 ha, 33%) and tractor ploughing (1,711 ha, 1%) (Chart 3.56). More ox-ploughing was used during long rainy season with 70 percent of the planted area cultivated using that method against 63 percent for the planted area in the short Table 3.7 Number of Households and planted Area during the Long and Short Rainy Seasons by Land Clearing Methods Short Rainy Season Long Rainy Season Total Method of Land Clearing Number of House -holds Area Planted (ha) % Number of House -holds Area Planted (ha) % Number of House -holds Area Planted (ha) % Mostly Hand Slashing 101,696 94,207 78.3 103,754 82,625 84.2 205,450 176,8319 80.9 No Land Clearing 19,893 20,119 16.7 15,892 11,530 11.7 35,785 31,649 14.5 Mostly Bush Clearance 3,819 4,302 3.6 3,327 2737 2.8 7,146 7,039 3.2 Mostly Burning 1,162 1,112 0.9 1,049 1,019 1.0 2,210 2,250 1.0 Mostly Tractor Slashing 518 28 0.4 385 272 0.3 903 800 0.4 Total 127,087 120,270 100.0 124,407 98,183 100.0 251,494 218,452 100.0 Chart 3.55 Number of Households by Method of Land Clearing during the Long Rainy Season 103,754 15,892 3,327 1,049 385 0 30,000 60,000 90,000 120,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Method of Land Clearing Number of Households Chart 3.54 Percent of Area Planted with Orange and Average Planted Area per Household by District 0.1 9.6 27.2 5.1 57.9 0 15 30 45 60 Serengeti Tarime Musoma Rural Bunda Musoma Urban District Percent of Area Planted 0.00 0.20 0.40 0.60 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.56 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 144,919, 66% Mostly Tractor Ploughing, 1,712, 1% Mostly Hand Hoe Ploughing, 71,848, 33% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 rainy season. The use of tractor for cultivation in the region during the short rainy season was the same as that of the long rainy season. In Mara region, Tarime district had the largest planted area cultivated using oxen (60,822 hectares, 42.0%), followed by Serengeti (31,649 ha, 21.8%), Bunda (27.003 ha, 18.6%) and Musoma Rural (25,445 ha, 17.6%). There was no planted area cultivated using oxen in Musoma Urban district (Chart 3.57). During the long rainy season, 85.1 percent of the total area cultivated using oxen was planted with cereals, followed by pulses (6.3%), roots and tubers (5.2%), cash crops (1.6%), fruit & vegetables (1.1%) and oil seeds (0.7%). 3.5.3 Improved Seeds Use The total planted area using improved seeds was 50,862 ha which represents 15 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was 27 percent, much higher than the corresponding percentage use for the long rainy season (8.6%). Cereals had the largest planted area with improved seeds (25,401 ha, 49.9% of the planted area with improved seeds), followed by cash crops (19,088 ha, 37.5%), roots and tubers (2,800 ha, 5.5%), fruit and vegetables (1,767 ha, 3.5%), pulses (1,734 ha, 3.4%) and oil seed (72 ha, 0.1%) (Chart 3.59). However, the use of improved seeds in cash crops and fruit & vegetables is much greater than in other crop types (92.7%). Improved seeds were used on only 2.1 percent of the planted area with roots and tubers and 4.6 percent of planted area of oil seeds (Chart 3.60). 0 20,000 40,000 60,000 80,000 Area Cultivated (ha) Tarime Serengeti Bunda Musoma Rural Musoma Urban District Chart 3.57 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.58 Planted Area of Improved Seeds - MARA With Improved Seeds, 50,862, 15% Without Improved Seeds, 282,663, 85% Chart 3.59 Planted Area with Improved Seed by Crop Type Pulses, 1,734, 3% Oil seeds, 72, 0% Fruits & Vegetables, 1,767, 3% Roots & Tubers, 2,800, 6% Cereals, 25,401, 50% Cash Crops, 19,088, 38% 0.0 25.0 50.0 75.0 100.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.60 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 52 3.5.4 Fertilizer Use The use of fertilisers on annual crops was very small with a planted area of only 57,423 ha (17.2% of the total annual crops planted area in the region). The planted area without fertiliser for annual crops was 276,102 hectares representing 82.8 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied on 47,972 ha representing 14.4 percent of the total planted area (83.5% of the planted area with fertiliser application in the region). This was followed by compost (6,719 ha, 2%). Inorganic fertilizers were used on a very small area which represents only 4.7 percent of the area planted with fertilizers (Chart 3.61). The highest percentage of the area planted with fertilizer (all types) was in Tarime district (47.8%), followed by Musoma Rural (24.3%), Bunda (15.4%), Serengeti (12.4%) and Musoma Urban (0.1%) (Chart 3.62 and Table 3.8). Most annual crop growing households do not use any fertiliser (Approximately 1478,477 households, 79%) (Map 3.39). The percentage of the planted area with applied fertilizer was highest for fruit and vegetables (70.7% of the area planted with these fruit and vegetables during the long rainy season had an application of fertilizers). This was followed by cereals (23.4%), oil seeds (13.9%), pulses (12.9%), roots and tubers (10.4%) and cash crops (7.2%) (Table 3.9). Farm Yard Manure Use The number of households that applied farm yard manure on their annual crops during the long rainy season was 47,523 and it was Table3.8 Planted Area by Type of Fertiliser Use and District - Short and Long Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Tarime 23,258 1,895 2,306 27,459 87,871 Serengeti 6,678 301 149 7,127 58,038 Musoma Rural 12,668 1,092 178 13,938 74,086 Bunda 5,312 3,431 93 8,836 55,436 Musoma Urban 56 0 7 63 670 Total 47,972 6,719 2,732 57,423 276,102 Table 3.9 Number of Crop Growing Households and Planted Area by Type of Fertiliser Use - Long Rainy Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of House -holds Planted Area (ha) Number of House -holds Planted Area (ha) Number of House -holds Planted Area (ha) Planted Area (ha) Planted Area (ha) Cereals 27,743 14,736 3,568 2,271 1,938 1,032 59,049 77,087 Roots & Tubers 12,381 10,626 3,000 1,813 1,012 587 111,653 124,679 Pulses 2,397 755 519 117 547 110 6,657 7,639 Oil Seeds 341 80 0 0 135 16 599 695 Fruit & Vegetables 4,430 729 0 0 573 116 350 1,195 Cash Crops 232 141 0 0 0 . 1,818 1,959 Total 47,523 27,067 7,087 4,201 4,205 1,861 180,126 213,255 Chart 3.61 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 47,972, 14% No Fertilizer Applied, 276,102, 83% Mostly Inorganic Fertilizer, 2,732, 1% Mostly Compost, 6,719, 2% 0 40,000 80,000 120,000 Area (ha) Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.62 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Chart 3.63 Planted Area with Farm Yard Manure by Crop Type - MARA Roots & Tubers, 11,229, 23% Pulses, 1,504, 3% Oil Seeds & Oil Nuts, 202, 0% Fruits & Vegetables, 1,192, 2% Cash Crops, 2,308, 5% Cereals, 31,538, 67% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 applied to 27,067 ha representing 13 percent of the total area planted during that season (Table 3.9). Cereals had the largest planted area with applied farm yard manure (67% of the total planted area with farm yard manure), followed by roots and tubers (23%), cash crops (5%), pulses (3%), fruits & vegetables (2%) and oil seeds (0.4%) (Chart 3.63). However, fruit and vegetables had the highest proportion of the planted area applied with farm yard manure (56.5% of the total area of fruit and vegetables in Mara region). This was followed by cereals (19.5%), oil seeds (12.8%), cash crops (11.2%), pulses (10.4%) and roots & tubers (8.4%) (Chart 3.64). Farm yard manure is mostly used in Tarime (20.2% of the total planted area in the district), followed by Musoma Rural (14.4%), Serengeti (10.2%), Bunda (8.3%) and Musoma Urban (7.6%) (Chart 3.65). For permanent crops, malay apple had the highest proportion of planted area applied with farm yard manure (99.8%), followed by star fruit (85.9%) and guavas (66.7%). Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Mara region was 2,732 ha which represents 0.82 percent of the total planted area with annuals in the region and 4.76 percent of the total planted area with fertiliser in Mara region. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 4,205 and it was applied to 1,861 ha representing 0.87 percent of the total area planted during that season (Table 3.9). The largest area applied with inorganic fertilizers was that of cereals (61% of the total area applied with inorganic fertilizers), followed by roots and tubers (22%), fruit and vegetables (7%), pulses (5%), oil seeds (4%) and cash crops (1%) (Chart 3.66). However, the proportion of fruit and vegetables with inorganic fertilizers was higher than other crop types (8.5% of the planted area in the district), followed by oil seeds (6.5%), cereals (1.0%), pulses (0.9%), roots and tubers (0.5%) and cash crops (0.2%) (Chart 3.67). Inorganic fertiliser was mostly used in Tarime (1.00% of the total planted area in the district), 0 20 40 60 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.64 Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.65 Proportion of Planted Area Applied with Farm Yard Manure by District - MARA 0 5 10 15 20 25 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Percent Planted Area Chart 3.66 Planted Area with Inorganic Fertilizers by Crop Type - MARA Roots & Tubers, 612, 22% Pulses, 127, 5% Oil Seeds , 103, 4% Fruits & Vegetables, 179, 7% Cash Crops, 40, 1% Cereals, 1,672, 61% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 followed by Musoma Urban (0.93%), Serengeti (0.23%), Musoma Rural (0.20%) and Bunda (0.14%) (Chart 3.68). Inorganic fertilisers were not applied on permanent crops. Compost Use The total planted area applied with compost was 6,719 ha which represents only 2.0 percent of the total planted area with annual crops in the region and 11.7 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 7,087 and it was applied to 4,201 ha representing 1.97 percent of the total area planted in the region during the long rainy season. The number of households that applied compost manure on their farm during the short rainy season was 3,935 and it was applied to 2,518 ha representing 2.1 percent of the total area planted in Mara region during the short rainy season (Table 3.9). The proportion of area applied with compost was very low for each type of crop (0 to 2.7%), however the distribution of the total area using compost manure shows that 65.7 percent of this area was cultivated with cereals, followed by roots and tubers (27.0%), pulses (4.8%), cash crops (2.3%) and fruits and vegetables (0.2%). There were no compost application on oil seed crops (Charts 3.69 and 3.70). Compost is mostly used in Bunda (5.3% of the total planted area in the district), followed by Tarime (1.6%), Musoma Rural (1.2%) and Serengeti (0.5%). There was no compost use in Musoma Urban district (Chart 3.71). In permanent crops, the only crops that compost was mostly used were banana (6.1%) and mango (0.5%). Chart 3.68 Proportion of Planted Area Applied with Inorganic Fertiliser by District - MARA 0.0 0.5 1.0 1.5 2.0 2.5 Tarime Musoma Urban Serengeti Musoma Rural Bunda District Percent 0.0 3.0 6.0 9.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.67 Percentage of Planted Area with Inorganic Fertilizers by Crop Type - MARA Chart 3.69 Planted Area with Compost by Crop Type - MARA Pulses, 325, 4.8% Oil Seeds , 0, 0.0% Fruits & Vegetables, 12, 0.2% Roots & Tubers, 1813, 27.0% Cash Crops, 155, 2.3% Cereals, 4414, 65.7% 0.0 1.0 2.0 3.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.70 Percentage of Planted Area with Compost by Crop Type - MARA Chart 3.71 Proportion of Planted Area Applied with Compost by District - MARA 0.0 2.0 4.0 6.0 Bunda Tarime Musoma Rural Serengeti Musoma Urban District Percent of area Planted RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders in both annual and permanent crops in the region. Pesticides were applied to a planted area of 35,157 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (61.8% of the total area applied with pesticides). This was followed by fungicides (27%) and herbicides (11.3%) (Chart 3.72). 3.5.5.1 Insecticide Use The planted area applied with insecticides was 21,719 ha which represented 6.5 percent of the total planted area for annual crops and vegetables. Cash crops had the largest planted area applied with insecticides (15,653 ha, 72.1% of the total planted area with insecticides), followed by roots an tubers (2,116 ha, 9.6%), cereals (2,033 ha, 9.4%), fruits and vegetables (1,605 ha, 7.4%) and pulses (312 ha, 1.4%). There was no application of insecticides on oil seed crops (Chart 3.73). However, the percent of insecticides used on fruit and vegetables and cash crops was much greater than in other crop types (76.1% and 76.0% respectively), whilst only 1.3 percent of the planted area with cereals was applied with insecticides (Chart 3.74). Annual crops with more than 50 percent insecticide use were spinach (100%), water melon (100%), tomatoes (90.1%), cabbages (89.0%), cotton (76.8%) and cucumber (50.1%). Bunda had the highest percent of planted area with insecticides (15.6% of the total planted area with annual crops in the district). This was followed by Serengeti (6.3%), Musoma Rural (6.0%) and Musoma Urban (6.0%). The smallest percentage use was recorded in Tarime district (2.0%) (Chart 3.75). Chart 3.73 Planted Area Applied with Insecticides by Crop Type Cash Crops, 15,653, 72.1% Cereals, 2,033, 9.4% Roots & Tubers, 2,116, 9.7% Oil Seeds , 0, 0.0% Fruits & Vegetables, 1,605, 7.4% Pulses, 312, 1% 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.75 Percent of Planted Area Applied with Insecticides by District - MARA 0.0 4.0 8.0 12.0 16.0 Bunda Serengeti Musoma Rural Musoma Urban Tarime District Percent of Planted Area Chart 3.72 Planted Area (ha) by Pesticide Use Herbicides, 3,956, 11.3% Fungicides, 9,482, 27.0% Insecticides, 21,719, 61.8% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 3.5.5.2 Herbicide Use The planted area applied with herbicides was 3,956 ha which represents 1.2 percent of the total planted area for annual crops and vegetables. Roots and tubers had the largest planted area applied with herbicides (2,213 ha, 56%), followed by cereals (1,062 ha, 27%), cash crops (378 ha, 9.5%), pulses (159 ha, 4%) and fruits and vegetables (143 ha, 3.6%) (Chart 3.76). However, the percent of herbicide use on fruit and vegetables was much greater than in other crop types (6.8% of the total planted area with fruit and vegetables in the region), whilst only 1.1 percent of pulses was applied with herbicides (Chart 3.77). The top five annual crops with highest percentage use of herbicides in terms of planted area were cucumber (50.1%), spinnach (12%), tomatoes (9.8%), bambaranuts (4.6%) and cabbages (3.1%). Musoma Rural had the highest percent of planted area with herbicides (1.6% of the total planted area with annual crops in the district). This was followed by Tarime (1.5%), then Musoma Urban (1.2%) and Bunda (0.6%). The smallest percentage use was recorded in Serengeti district (0.6%) (Chart 3.78). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 5,953ha which represented 1.8 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (1.9%) was slightly higher than the corresponding percentage for the long rainy season (1.7%). Roots and tubers had the largest planted area applied with fungicides (2,391 ha, 40.2%) followed by cereals (1,633 ha, 27.4%), fruit and vegetables (1,083 ha, 18.2%), cash crops (655 ha, 11.0%) and pulses (192 ha, 3.2%) (Chart 3.79). There was no fungicide application in oil seed crops. Chart 3.76 Planted Area Applied with Herbicides by Crop Type Cereals, 1062, 26.9% Cash Crops, 378, 9.5% Roots & Tubers, 2213, 56.0% Fruits & Vegetables, 143, 3.6% Pulses, 159, 4% 0.0 2.0 4.0 6.0 8.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.77 Percentage of Planted Area Applied with Herbicides by Crop Type Chart 3.78 Proportion of Planted Area Applied with Herbicides by District - MARA 0.0 0.5 1.0 1.5 2.0 Musoma Rural Tarime Musoma Urban Bunda Serengeti District Percent of Planted Area RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 However, the percentage use of fungicide in fruit and vegetables was much greater than in other crop types (51.3%), while only 1.0 percent of cereal crops was applied with fungicides (Chart 3.80). Annual crops with more than 20 percent fungicide use were tomatoes (79.5%), tobacco (59.2%), cucumber (50.1%), spinnach (30.7%), Irish potatoes (29.5%), cabbages (27.8%) and onions (20.2%). Musoma Rural had the highest percent of planted area with fungicide (2.4% of the total planted area with annual crops in the district). This was closely followed by Serengeti (1.8%). The smallest percentage use was recorded in Bunda district (1.0%) (Chart 3.81). 3.5.6 Harvesting Methods The main harvesting method for cereals was by hand. Very small amounts of maize were harvested using machines (0.2%). All other cereals and annual crops were mainly harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with crops from 91.0 percent of the total area planted with cereals during the long rainy season threshed using this method. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.4%, 2.2 percent and 0.1 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. Chart 3.79 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 2,391, 41% Pulses, 192, 3% Fruits & Vegetables, 1,083, 18% Cash Crops, 655, 11% Cereals, 1,633, 27% 0.0 15.0 30.0 45.0 60.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.80 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.81 Proportion of Planted Area with Fungicides by District - MARA 0.0 1.0 2.0 3.0 Musoma Rural Serengeti Musoma Urban Tarime Bunda District Percent Chart 3.82 Area of Irrigated Land Unirrigated Area, 329,323, 98.7% Irrigated Area, 4,202, 1.3% Serengeti Musoma Urban Musoma Rural Bunda Tarime 470 19 1,476 1,105 1,131 0.7 2.6 1.7 1.7 1 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Musoma Rural Bunda Musoma Urban Tarime 74,086 55,436 87,871 58,038 84.2% 91.4% 86.3% 76.2% 89.1% Serengeti 670 80,000 to 90,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Planted Area and Percent of Planted Area With No Application of Fertilizer by District MAP 3.39 MARA Planted Area With Irrigation Applied MAP 3.40 MARA Area Planted and Percent of Total Planted Area With Irrigation by District Planted Area With Irrigation Applied Planted Area With No Fertilizer Applied Planted Area With No Fertilizer Applied Percent of Planted Area With No Fertilizer Applied Percent of Planted Area with Irrigation Tanzania Agriculture Sample Census Tanzania Agriculture Sample Census RESULTS 58 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.6.1 Area Planted with Annual Crops and Under Irrigation In Mara region, the area of annual crops under irrigation was 4,202 ha representing 1.3 percent of the total area planted (Chart 3.82). The area under irrigation during the short rainy season was 2,412 ha accounting for 57 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown during the long rainy season with irrigation. In the long rainy season, 71 percent of the area planted with vegetables was irrigated, whilst 59 percent of the vegetables were irrigated in the short rainy season. The district with the largest planted area under irrigation with annual crops was Musoma Rural (1,476 ha, 35.1% of the total annual crops irrigated planted area in the region). This is followed by Tarime with (1,131 ha, 26.9%), Bunda (1,105 ha, 26.3%), Serengeti (470 ha, 11.2%) and Musoma Urban (19 ha, 0.5%). When expressed as a percentage of the total area planted in each district, Musoma Urban had the highest percentage with 2.6% of the planted area in the district under irrigation. This was followed by Bunda (1.7%), Musoma Rural (1.7%), Tarime (1.0%) and Serengeti (0.7%) (Chart 3.83 and Map 3.40). Of all the different crops and in terms of proportion of the planted are that was irrigated, water melon was the most irrigated crop with 100 percent irrigation followed by tomatoes (77.7%), cabbages (74.3%), cucumber (50.1%), onions (47.7%) and amaranths (41.0%). In terms of crop type, the area under irrigation with cereals was 1,912 ha (45.5% of the total area under irrigation), followed by fruits and vegetables with 1,387 ha (33.0%), cash crops (396 ha, 9.4%), pulses (304 ha, 7.2%) and roots and tubers (204 ha, 4.8%). Oil seed crops were not irrigated. The area of fruit and vegetables under irrigation was 1,387 ha which represents 65.7 percent of the total planted area with fruit and vegetables. Water mellon, tomatoes, cabbages and spinnach were the most irrigated crops. The number of households practicing irrigation in Mara region appears to have increased over the last seven years from 4,299 to 9,012 households (Chart 3.84). This may not be statically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from wells (37% of households with irrigation). This was followed by river (34%), lake (21%), dam (5%) and canal (3%) (Chart 3.85). Chart 3.83 Planted Area with Irrigation by District - MARA Region 0 500 1,000 1,500 Musoma Rural Tarime Bunda Serengeti Musoma Urban District Irrigated Area (ha) 0.0 1.0 2.0 3.0 Percentage Irrigation Irrigated Area Percentage of Irrigated Land Chart 3.84 Time Series of Household with irrigation - MARA 9,012 4,299 0 2,000 4,000 6,000 8,000 10,000 1995/96 2002/03 Agriculture Year Planted Area ubder Irrigation (ha) Chart 3.85 Number of Households with Irrigation by Source of Water Well, 2151, 37% River, 2007, 34% Lake, 1250, 21% Dam, 281, 5% Canal, 191, 3% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 While most households using irrigation in Bunda district get irrigation water from the Lake (50%), most household in Musoma Urban get their irrigation water from wells (49 %). However, most of the households in Serengeti district get irrigation water from rivers (43%). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common method of obtaining water for irrigation with 83 percent of households using this method. This is followed by gravity with 6 percent of households, hand pump (2%) and motor pump (2%) (Chart 3.86). All households with irrigation in Serengeti and Musoma Urban districts used hand bucket in obtaining water from the source, followed by Musoma Rural (85%), Tarime (77%) and Bunda (70%). Gravity method was used by few households in Musoma Rural (11%) and Bunda (10%). Hand pump was used in Tarime only (7%) and motor pump was used in Musoma Rural district only (4%). 3.6.4 Methods of Water Application Most households used buckets/watering cans (87% of households using irrigation) as a method of field application. This was followed by flood irrigation (10%). Water hose and sprinklers were not widely used (2% and 1% respectively) (Chart 3.87). All households with irrigation in Musoma Urban districts used hand bucket/watering cans in applying irrigation water from the source, followed by Tarime (93%), Serengeti (86%), Musoma Rural (84%) and Bunda (80%). Flood method was used by a few households in Bunda and Musoma Rural (20% and 16% respectively) whilst sprinkler was used by few households in Serengeti district (14%). Water hose was used in Tarime only (7%). 3.7 Crop Storage, Processing & Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices and as seed for planting in the following season. The results for Mara region show that there were 135,725 crop growing households (73% of the total crop growing households) that stored various agricultural products in Mara region. Chart 3.86 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 4839, 83% Other, 420, 7% Gravity, 382, 6% Motor Pump, 115, 2% Hand Pump, 124, 2% Chart 3.87 Number of Households with Irrigation by Method of Field Application Sprinkler, 68, 1.2% Water Hose, 124, 2.1% Flood, 612, 10% Bucket / Watering Can, 5075, 86.3% Chart 3.88 Number of Households and Quantity Stored by Crop Type - MARA 0 30,000 60,000 90,000 120,000 Maize Sorghum & Millet Beans & Pulses Paddy Groundnuts/Bambara Nuts Crop Number of households 0 2,000 4,000 6,000 8,000 10,000 12,000 Quantity (t) Quantity stored (Tons) RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.7.1.1 Methods of Storage The region had 82,526 crop growing households storing their produce in locally made traditional structure (60.8% of households that stored crops in the region). The number of households that stored their produce in sacks/open drum was 51,453 (37.9%). This was followed by improved locally made structure (1,017 households, 0.7%), unprotected pile (182 households, 0.1%) and modern stores (141 households, 0.1%) (Chart 3.89). Storage in locally made traditional structures was the dominant storage method in the region, with Serengeti district having the highest percentage of households using this method (82% of the total number of households storing crops in the district). This was followed by Tarime (78%), Musoma Rural (39%), Bunda (29%) and Musoma Urban (5%) (Chart 3.90). Although the highest percent of households using sacks/open drums was in Musoma Urban district (89% of the total number of households storing crops in the district), the figure should be used with caution because of the small number of observations involved. This is followed by Bunda (69%), Tarime (21%) and Serengeti (18%). 3.7.1.2 Duration of Storage Most households (52.9% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months. The minority of households stored their crop for a period of less than 3 months (7.6%). However, most households that stored paddy stored for a period of over 6 months, followed by those who stored for a period of 3 to 6 months. A small number of households stored paddy for the period of less than 3 months (Chart 3.91). The proportion of households whose normal duration of storage is duration of 3 to 6 months was highest in Tarime district (74%), followed by Serengeti (65%), Bunda (50%), Musoma Rural (40%) and Musoma Urban (37%) (Map 3.41). Chart 3.90 Number of Households by Method of Storage and District (based on the most important household crop) 0 25 50 75 100 Serengeti Tarime Musoma Rural Bunda Musoma Urban District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Chart 3.89 Number of Households by Storage Methods - MARA In Sacks / Open Drum, 51,453, 37.9% In Locally Made Traditional Structure, 82,526, 60.8% In Modern Store, 141, 0.1% Unprotected Pile, 182, 0.1% Other, 406, 0.3% In Improved Locally Made Structure, 1,017, 0.7% 0 25,000 50,000 75,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.91 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003. However, households in Tarime district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirements of the household and not to sell during the “off-season” when the farm gate price of maize is higher (Chart 3.92). Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millets, beans and pulses) were mainly stored for household consumption. Ninety percent of households stored maize for household consumption as the main purpose of storage, followed by seed for planting (6%) and selling at higher price (4%). The highest percentage of the households that stored groundnuts/bambara nuts did so for the purpose of reserving seeds for planting (63%) (Chart 3.93). The Magnitude of Storage Loss About 79.7 percent of households that stored crops had little or no loss. However the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale and other purposes such as tobacco, cotton and bambara nuts. Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and Crop Estimated Storage Loss Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Crop Number of House -holds % Number of House -holds % Number of House -holds % Number of House -holds % Total Maize 81,503 79.4 14,844 14.5 5,054 4.9 1,293 1.3 102,693 Paddy 7,472 96.0 195 2.5 0 0.0 117 1.5 7,785 Sorghum and Millets 59,687 75.8 13,596 17.3 4,250 5.4 1,231 1.6 78,764 Beans and Pulses 25,150 85.1 3,054 10.3 455 1.5 879 3.0 29,539 Coffee 132 100.0 0 0.0 0 0.0 0 0.0 132 Tobacco 70 100.0 0 0.0 0 0.0 0 0.0 70 Cotton 149 100.0 0 0.0 0 0.0 0 0.0 149 Groundnuts/Bambara Nuts 2,071 100.0 0 0.0 0 0.0 0 0.0 2,071 Chart 3.92 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 15,000 30,000 45,000 60,000 Tarime Serengeti Musoma Rural Bunda Musoma Urban District Quantity (tonnes) 0 5 10 15 20 25 Percent Stored Quantity harvested Quantity stored % stored 0% 25% 50% 75% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Coffee Tobacco Cottton Groundnuts/Bamb... Crop Type Chart 3.93 Proportion of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millets (7.0% of the total number of households that stored crops). This was followed by maize (6.2%), pulses (4.5%) and paddy (1.5%) (Table 3.10). 3.7.2 Agro-processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced by most crop growing households in Mara region (171,860 households, 91.3% of the total crop growing households) (Chart 3.94a). With exception of Musoma Urban district, the percent of households processing crops in the rest of the districts was very high (above 80%). Musoma Urban had the lowest percent of households processing crops (62% of crop growing households in the district) (Chart 3.94b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 67 percent (115,059 households). This was followed by those processing on-farm by hand (42,052 households, 24.5%), on farm by machine (12,461 households, 7%) and by trader (1,918 households, 1%). The remaining methods of processing were used by very few households (less than 1%). Although processing by neighbours machine was the most common processing method in most of districts in Mara region, district differences existed. Serengeti had the highest percent of households processing using neighbour’s machine (93%), followed by Bunda (80%), Musoma Rural (63%), Tarime (55%) and Musoma Urban (25%). Processing by trader was more common in Musoma Urban (12.3%), whilst processing on farm by machine was more prevalent in Tarime (13.8%) (Chart 3.94c). Chart 3.94a Households Processing Crops Households Processing, 171,860, 91.3% Households not Processing, 16,343, 8.7% 0.0 25.0 50.0 75.0 100.0 Percent of Households Processing Serengeti Bunda Tarime Musoma Rural Musoma Urban District Chart 3.94b Percentage of Households Processing Crops by District Chart 3.94c Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Musoma Urban Musoma Rural Tarime Bunda Serengeti District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm Other By Factory RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the major product after processing and the by-product is the secondary after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 164,261 households processing crops into flour (95.6%) followed by grain with 6,649 households (3.9%). The remaining products were produced by a small number of households (Chart 3.95). The number of households producing by-products accounted for 5.4 percent of the households processing crops. The most common by-product produced by crop processing households was husk with 5,583 households (60% of the households producing by-products), followed by bran (1,705 households, 18%), pulp (533 households, 6%) and juice (514 households, 6%). The remaining by-products were produced by a small number of households (Chart 3.96). Main Use of Primary Processed Products Primary processed products were used for households/ human consumption and for selling. The most important use was for household/human consumption which represented 99.4 percent of the total households that used primary processed products (Chart 3.97). Districts that sold primary processed products were Tarime and Musoma Rural. Out of 471 households that sold processed products, 271 were from Tarime (58% of the total number of households selling processed products in the region) and 199 households (42%) were from Musoma Rural District. Other districts did not sell processed products (Chart 3.98). Musoma Rural had the highest proportion of households that sold processed products (0.4%). This was followed by Tarime (0.3%). Chart 3.95 Percent of Households by Type of Main Processed Product Grain, 3.9, 4% Flour / Meal, 95.6, 96% Rubber, 0.1, 0% Oil, 0.1, 0% Juice, 0.1, 0% Fiber, 0.1, 0% Other, 0.2, 0% Chart 3.96 Number of Households by Type of By-product Husk, 5,583, 60% Cake, 132, 1% Shell, 346, 4% Fiber, 492, 5% Juice, 514, 6% Pulp, 533, 6% Bran, 1,705, 18% Chart 3.97 Use of Processed Product Household / Human Consumption, 170,760, 99.4% Other, 135, 0.1% Did Not Use, 495, 0.3% Sale Only, 471, 0.3% 0.00 20.00 40.00 60.00 Percentage of households Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.98 Percentage of Households Selling Processed Crops by District RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 Outlets for Sale of Processed Products Most households that sold processed products sold to local market and trade stores (12,532 households, 72% of households that sold crops). This was followed by selling to neighbours (2,552 households, 14%), large scale farm (721 households, 4%), secondary markets (717 households, 4%) and traders at farm (613 households, 3%). Households that sold to the remaining outlet accounted for less than 1.5 percent for each location (Chart 3.99). There were large differences between districts in the proportion of households selling processed products to neighbours, with Musoma Urban district having the largest proportion (57% of the households selling processed products in the district), whereas Serengeti had only 5 percent. With exception of Musoma Urban which had the highest percentage of households selling processed products to neighbours, the rest of the districts sold mostly to local markets and trade stores. Compared to other districts, Musoma Rural had the highest percent of households selling processed products to traders at farm and farmers associations. The sale of processed products to secondary markets was most prominent in Serengeti compared to other districts, whilst selling to large scale farms was most prominent in Bunda district. The district which had the highest proportion of households selling processed products to marketing cooperative was Serengeti (Chart 3.100). 3.7.3 Crop Marketing The number of households that reported selling crops was 130,438 which represent 70.2 percent of the total number of crop growing households. The proportion of crop growing households selling crops was highest in Serengeti (77.3%) followed by Musoma Rural (69.5%), Tarime (69.1%), Bunda (67.7%) and Musoma Urban (21.9%) (Chart 3.101 and Map 3.42). Chart 3.99 Location of Sale of Processed Products Trader at Farm, 613, 3.5% Other, 231, 1.3% Large Scale Farm, 721, 4.1% Neighbours, 2,552, 14.4% Marketing Co- operative, 184, 1.0% Farmers Association, 114, 0.6% Secondary Market, 717, 4.1% Local Market / Trade Store, 12,532, 70.9% Chart 3.100 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 25% 50% 75% 100% Musoma Urban Bunda Musoma Rural Tarime Serengeti District Percent of Households Selling Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.101 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Number of Households 0.0 20.0 40.0 60.0 80.0 Percent of Households Percent of Households Selling Crops Serengeti Musoma Urban Musoma Rural Bunda Tarime 20,756 21,552 97 34,052 53,981 21.9% 67.7% 69.5% 78.1% 69.1% Bunda Musoma Urban Musoma Rural Tarime 50% 36% 40% 74% 65% Serengeti 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Percent of Households Storing Crops For 3 to 6 Months by District MAP 3.41 MARA Number of Households Selling Crops MAP 3.42 MARA Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops Percent of Households Storimg Crops Percent of Households Storing Crops Percent Households Selling Crops Tanzania Agriculture Sample Census RESULTS 66 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (76% of crop growing households that reported main marketing problems). Apart from low market prices, other problems were longer distances to the markets (11%), lack of transport (6%), high transport costs (3%) and lack of buyers (2%). Other marketing problems were minor and represented less than 2 percent of the total reported problems (Chart 3.102). Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 84.5 percent of the agricultural households that reported reasons for not selling, followed by low price (4.2%), trade union problems (2.1%), markets location being too far (0.4%), cooperative problems (0.3%) and Government regulatory board problems (0.2%) (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Mara region very few agricultural households (675, 0.4% of agricultural households in the region) accessed credit out of which 419 (75%) were male-headed households and 256 (38%) were female headed households. In Musoma Rural district, only female headed households got agricultural credit whereas in Serengeti both male and female headed households accessed agricultural credit (Table 3.12). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Mara region were traders and/or trade stores which collectively provided credit to 489 agricultural households (73% of the total number of households that accessed credit), followed by saving and credit societies (17%) and family and friends and relatives (10%) (Chart 3.103). Family, friends and relatives were the sole source of credit in Serengeti district and Saving and Credit Societies provided credit to households in Musoma Rural district only (Chart 3.104). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 62,229 84.5 Other 6,103 8.3 Price Too Low 3,085 4.2 Trade Union Problems 1,534 2.1 Market Too Far 304 0.4 Co-operative Problems 251 0.3 Government Regulatory Board Problems 136 0.2 Total 73,642 100 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Number Tarime 0 0 0 0 0 Serengeti 419 75 140 25 559 Musoma Rural 0 0 117 100 117 Bunda 0 0 0 0 0 Musoma Urban 0 0 0 0 0 Total 419 75 256 38 675 Chart 3.102 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Government Regulatory Board Problems, 346, 1% Trade Union Problems, 70, 0% Transport Cost Too High, 2001, 3% Lack of Market Information, 497, 1% No Buyer, 1241, 2% No Transport, 3575, 6% Market too Far, 7094, 11% Open Market Price Too Low, 49711, 76% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 Use of Agricultural Credits A large proportion of the agricultural credit provided to agricultural households in Mara region was used for buying agrochemicals (66%), followed by tools and equipment (9%), purchasing of livestock (9%) and other unspecified activities (16%)(Chart 3.105). Reasons for Not Using Agricultural Credits The main reason for not using agricultural credit was little credit awareness accounting for 69.3 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting “un-availability of credit” (10.0%), followed by “not wanting to go into debt” (9.2%). The rest of the reasons accounted for 11.5 percent of the households (Chart 3.106). 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 62,800 (34% of the total crop growing households in the region) (Chart 3.107). Some districts had more access to extension services than others, with Bunda having a relatively high proportion of households (60% of the crop growing households) that received crop extension messages, followed by Musoma Rural (48%), Musoma Urban (26%), Serengeti (23%) and Tarime (19%) (Chart 3.108 and Map 3.43). Chart 3.105 Proportion of Credits Received by Main Purposes Agro-chemicals 66% Tools / Equipment 9% Livestock 9% Other 16% Chart 3.104 Number of Households Receiving Credit by Main Source of Credit and District 0% 25% 50% 75% 100% Tarime Serengeti Musoma Rural Bunda Musoma Urban District Percent of Households Family, Friend and Relative Saving & Credit Society Trader / Trade Store Chart 3.103 Percentage Distribution of Households Receiving Credit by Main Source Saving & Credit Society 17% Family, Friend and Relative 10% Trader / Trade Store 73% Chart 3.106 Reasons for not Using Credit (% of Households) Credit granted too late, 1,090, 0.6% Other, 727, 0.4% Difficult bureaucracy procedure, 5,432, 2.9% Interest rate/cost too high, 5,075, 2.7% Not needed, 9,237, 4.9% Don't know about credit, 47,065, 25.1% Did not know how to get credit, 82,822, 44.2% Not available, 18,781, 10.0% Did not want to go into debt, 17,298, 9.2% Chart 3.107 Number of Households Receiving Extension Advice Households Not Receiving Extension , 122,991, 66% Households Receiving Extension , 62,800, 34% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (95.2%, 58,531 households). NGOs/Development projects provided 3.9 percent, large scale farms 0.4 percent and the remaining providers less than 0.6 percent (Chart 3.109), however district differences exist with the proportion of the households receiving advice from government services ranging from between 81.0 percent in Musoma Urban to 98.8 percent in Serengeti. Quality of Extension An assessment of the quality of extension indicates that 64 percent of the households receiving extension ranked the service as being good, followed by average (24 %) and very good (11%) (Chart 3.110). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Mara regardless of whether the household grew annual or permanent crops. In previous sections, the reference was on annual crops only. Because of this, the figures presented in this section may differ from those in the previous section on inputs (Section 3.5). Data on source of inputs is only found in this section and applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on the farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Mara region farm yard manure was used by 48,514 households which represented 26.1 percent of the total number of crop growing households. This was followed by improved seeds (22.9%), insecticide/fungicide (11.6%), compost (3.6%), inorganic fertiliser (1.6%) and herbicide (0.1%) (Table 3.13). Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Input Type of Input Number % Number % Farm Yard Manure 48,514 26.1 137,277 73.9 Improved Seeds 42,530 22.9 143,261 77.1 Insecticide/Fungicide 21,587 11.6 164,204 88.4 Compost 6,716 3.6 179,075 96.4 Inorganic Fertiliser 2,932 1.6 182,859 98.4 Herbicide 206 0.1 185,584 99.9 Chart 3.108 Number of Households Receiving Extension by District 0 5,000 10,000 15,000 20,000 25,000 Musoma Rural Bunda Tarime Serengeti Musoma Urban District Number of Households 0 20 40 60 80 Percent of Households Percentage of Households Receiving E i Chart 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider Government, 58,531, 95.2% Other, 134, 0.2% NGO / Development Project, 2,395, 3.9% Cooperative, 188, 0.3% Large Scale Farm, 249, 0.4% Chart 3.110 Number of Households Receiving Extension by Quality of Services Good, 40,174, 64.1% Average, 15,296, 24.4% Poor, 547, 0.9% No Good, 0, 0.0% Very Good, 6,635, 10.6% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertilisers in Mara region mostly purchased them from the local market/trade store (93.3% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.111). Most households reside between 10 and 20 km from the source of inorganic fertilizers (39%), followed by 20 km and above (22%) and between 3 and 10 km (15%) (Chart 3.112). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “non availability” as the reason for not using (32%), it may be assumed that access to inorganic fertiliser is not the main reason for not using. Other reasons such as cost are more important with 57 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and inorganic fertiliser would be made more available. More smallholders use inorganic fertilisers in Tarime than in other districts in Mara region (73% of households using inorganic fertilisers), followed by Musoma Rural (20%), Serengeti (5%), Bunda (3%) and Musoma Urban (0.6%). 3.9.3 Improved Seeds The percent of households that use improved seeds was 22.9 percent of the total number of crop growing households. Most of the improved seeds were from the local markets/trade stores (47.2%). Other less important sources of improved seeds were crop buyers (25.7%), co-operatives (12.0%), neighbours (7.4%), local farmers group (2.7%), locally produced by the household (1.7%), development project (1.7%) and secondary market (1.1%). Only 0.3 percent of households using improved seeds obtained them from large scale farms (Chart 3.113). Chart 3.111 Number of Households by Source of Inorganic Fertiliser 2.2% 4.5% 93.3% 0 500 1,000 1,500 2,000 2,500 3,000 Local Market / Trade Store Neighbour Locally Produced by Household Source of Inorganic Fertiliser Number of Households Chart 3.113 Number of Households by Source of Improved Seed 0.3% 1.1% 1.7% 1.7% 2.7% 7.4% 12.0% 47.2% 25.7% 0 7,000 14,000 21,000 Local Market / Trade Store Crop Buyers Co-operative Neighbour Local Farmers Group Locally Produced by Household Development Project Secondary Market Large Scale Farm Source of Improved Seed Number of Households Chart 3.112 Number of Households reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 Access to improved seeds were better than access to chemical inputs with 31 percent of households obtaining the input within 1 km of the household (Chart 3.114) compared to 11 percent for chemical fertilizer input. The higher use of improved seeds compared to other inputs is an indication that the availability is not the main prohibiting factor for the use of inputs but rather other factors such as cost. The district that used improved seeds most was Bunda with 36.7 percent of the total number of crop growing households using improved seeds in the district, followed by Musoma Urban (26.9%) and Musoma Rural (24.9%). Percentages of the crop growing households in Tarime and Serengeti districts that used improved seeds were 18.4 and 16.5 respectively (Map 3.44). 3.9.4 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (56.1% of the total number of fungicide users), followed by crop buyers (33.9%) and from co-operatives (6.4). Other sources of insecticides/ fungicides are of minor importance (Chart 3.115). Chart 3.116 shows that 74 percent of the crop growing households which used insecticides and pesticides obtained them from the distance of less than or equal to ten kilometres. The small number of households using insecticides/fungicides, coupled with the 15 percent of households responding to “not available” as the reason for not using, then it may be assumed that access was not the main reason for not using the input. Other reasons such as costs were more important with 52 percent of households responding to cost factors as the main reason for not using the inputs. In other words, it may be assumed that if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Insecticide/Fungicide were mostly used in Bunda district with 29 percent of the total number of crop growing households using them, followed by Serengeti (14%), Musoma Rural (12%), Musoma Urban (11%) and Tarime (3%). 3.10 Tree Planting The number of households involved in tree farming was 53,900 representing 29 percent of the total number of agriculture households (Chart 3.117). Chart 3.117 Number of Households with Planted Trees - MARA Households with planted trees, 53,900, 29% Households with no planted trees, 134,303, 71% Chart 3.114 Number of Households Reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.115 Number of Households by Source of Insecticides/Fungicides 33.9% 56.1% 6.4% 1.8% 1.2% 0.6% 0 5,000 10,000 15,000 Local Market / Trade Store Crop Buyers Co-operative Local Farmers Group Secondary Market Development Project Source of Improved Seed Number of Households Musoma Urban Bunda Tarime 92 11,998 6,740 13,875 3,008 21% 24% 22% 18% 11% Serengeti Musoma Rural 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Musoma Urban Musoma Rural Bunda Serengeti Tarime 115 18,303 6,308 14,524 23,549 25 60 23 18 47 Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.43MARA Number of Crop Growing Households Using Improved Seed MAP 3.44 MARA Number and Percent of Crop Growing Households using Improved Seed by District Number of Crop Growing Households Using Improved Seed Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Percent of Households Receiving Crop Extension Services Percent of Crop Growing Households Using Improved Seed 20,000 to 24,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Tanzania Agriculture Sample Census Tanzania Agriculture Sample Census RESULTS 72 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 The number of trees planted by smallholders on their allotted land was 4,540,084 trees. The average number of trees planted per household that plants trees on their land was 84 trees The main species planted by smallholders was Eucalyptus spp (1,807,591 trees, 39.8%), followed by Trichilia spp (1,371,363 trees, 30.2%), then Gravellis spp (388,923 trees, 8.6%), Cyprus spp (324,484 trees, 7.1%), Azadrachta spp (107,041, 2.4%), Sesbania spp (105,817 trees, 2.3%) and Senna spp (101,615 trees, 2.2%). The remaining trees species were planted in comparatively small numbers (Chart118.). Tarime has the largest number of trees planted by smallholders than any other district with 79.3 percent of the total number of trees in Mara region and is dominated by Eucalyptus spp. This is followed by Musoma Rural (11.0%) which was dominated by Gravellia spp, then Serengeti (7.6%) dominated by Eucalyptus spp, Bunda (2.1%) dominated by Azadrachta spp and Musoma Urban (0.1%) which was mainly planted with Gravellis spp (Chart 3.119 and Map 3.45). Trees planted in plantations or coppice are more common among smallholder households. The proportion of trees that were planted in plantations/coppice was 46 percent, followed by trees scattered in fields 29 percent and then trees planted in field boundaries 25 percent (Chart 3.120). The main purpose of planting trees was to obtain planks/timber (56.0%). This is followed by obtaining wood for fuel (18.9%), poles (10.7%), shade (9.4%) and charcoal (0.2%) (Chart 3.121). Chart 3.118 Number of Selected Planted Trees by Species - MARA 0 400000 800000 1200000 1600000 2000000 Eucalyptus Spp Trichilia Spp Gravellis Cyprus Spp Azadritachta Spp Sesbania Spp Senna Spp Calophylum Inophyllum Albizia Spp Jakaranda Spp Leucena Spp Acacia Spp Other Tree Species Number of Trees Chart 3.119 Number of Selected Tree Species Planted by Smallholders and District 0 900,000 1,800,000 2,700,000 3,600,000 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Number of Trees Eucalyptus Spp Trichilia Spp Gravellis Cyprus Spp Azadritachta Spp Sesbania Spp Senna Spp Calophylum Inophyllum Albizia Spp Jakaranda Spp Leucena Spp Acacia Spp Other Chart 3.120 Number of Trees Planted by Location Field Boundaries, 1,126,048, 25% Plantation, 2,085,247, 46% Scattered in Field, 1,326,097, 29% Chart 3.121 Number of Households by Purpose of Planted Trees 0.0 20.0 40.0 60.0 Planks / Timber Wood for Fuel Poles Shade Medicinal Other Charcoal Use Percent of Households RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 74 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 18,282 which represented 10 percent of the total number of agricultural households in the region (Chart 3.122). The proportion of households with soil erosion control and water harvesting facilities was highest in Musoma Rural district (24% of the total agricultural households in the district), followed by Musoma Urban (21%), Tarime (6%), Serengeti (2%) and Bunda (1%) (Chart 3.123 and Map 46). Erosion control bunds accounted for 63.2 percent of the total number of structures, followed by water harvesting bunds (29.2%), drainage ditches (3.7%), tree belts (3.3%), terraces (0.4%), dams (0.1%) and vetiver grass (0.1%) (Chart 3.124). Erosion control bunds and tree belts, together had 290,125 structures. This represented 92.4 percent of the total structures in the region. The remaining 7.5 percentages were shared among the rest of the erosion control methods mentioned above. Musoma Rural district had 282,054 erosion control structures representing 90 percent of the total erosion structures in Mara region. 3.12 Livestock Results 3.12.1 Cattle Production The total number of cattle in the region was 1,099,068. Cattle were the dominant livestock type in the region, followed by goats, sheep and pigs. The region had 6.5 percent of the total cattle population on Tanzania Mainland. Cattle Population The number of indigenous cattle in Mara region was 1,090,007 (99.2 % of the total number of cattle in the region). The number of dairy breeds was 8,797 cattle (0.8%) and 264 cattle (0.02%) were beef breeds. Chart 3.122 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 18,282, 10% Households Without Facilities, 169,921, 90% Chart 3.123 Number of Households with Erosion Control/Water Harvesting Facilities 1 24 21 6 2 0 5,000 10,000 15,000 Musoma Rural Musoma Urban Tarime Serengeti Bunda District Number of Households 0 5 10 15 20 25 Percent of Households Percent of Households Chart 3.124 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.1 0.1 0.4 3.3 3.7 29.2 63.2 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches Tree Belts Terraces Dam Vetiver Grass Type of Facility Number of Structures Tarime Musoma Urban Musoma Rural Bunda 26,986 509 4,852 4,601 1,278 70.6% 1.3% 12.7% 12% 3.3% Serengeti 20,000 to 27,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Bunda Musoma Urban Musoma Rural Tarime 378 12,144 4,982 682 1 24 21 6 2 Serengeti 95 9,600 to 12,200 7,200 to 9,600 4,800 to 7,200 2,400 to 4,800 0 to 2,400 Number and Percent of Smallholder Planted Trees by district MAP 3.45 MARA Number of Households With Water Harvesting Bunds MAP 3.46 MARA Number and Percent of Households With Water Harvesting Bunds by District Number of Households With Water Harvesting Bunds Number of Smallholder Planted Trees Number of Smallholder Planted Trees Percent of Smallholder Planted Trees Percent of Households with Water Harvesting Bunds Tanzania Agriculture Sample Census RESULTS 75 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 The census results show that 63,430 agricultural households in the region (33.7% of total agricultural households) kept about 1.1 million cattle. This was equivalent to an average of 17 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Tarime which had about 349,523 cattle (31.8 % of the total cattle in Mara region). This is followed by Bunda (267,198 cattle, 24.3%), Serengeti (251,329 cattle, 22.9%) and Musoma Rural (229,719 cattle, 20.9%). Musoma Urban had the least number of cattle (1,301 cattle, 0.1%) (Chart 3.125 and Map 47). However, Bunda district had the highest density of cattle in the region (175 heads per sq km) (Map 3.48). Although Tarime district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant. Musoma Rural district had the largest numbers of diary and beef cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.126). Herd Size Thirty one percent of the cattle-rearing households had herds of size 1-5 cattle with an average of 3 cattle per household. Herd sizes of 31-40 accounted for about 7 percent of all cattle-rearing households and 14 percent of all cattle in the region. Only 12 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 87 percent of total cattle rearing households had herds of size 1-30 cattle and owned 49 percent of total cattle in the region, resulting in an average of 10 cattle per cattle rearing household. There were about 557 households with a herd size of more than 151 cattle each (163,616 cattle in total) resulting in an average of 294 cattle per household. Cattle Population Trend Cattle population in Mara decreased during the period of eight years from 1,291,576 in 1995 to 1,099,068 cattle in 2003. This implies an overall annual negative growth rate of -2.00 percent (Chart 3.127). However, the rate of decrease was lower for the period of four years from 1995 to 1999 (-0.37) as compared to that of the period from 1999 to 2003 (-3.60). However, the rate of decrease was lower for the period of four years from 1995 to 1999 (-0.37) as compared to that of the period from 1999 to 2003 (-3.60). 0 100 200 300 Number of Cattle ('000') Tarime Bunda Serengeti Musoma Rural Musoma Urban Districts Chart 3.125 Total Number of Cattle ('000') by District Chart 3.126 Number of Cattle by Type and District 225,012 1,143 264 0 0 0 0 3,588 0 346 4,706 158 267,198 345,671 250,983 0 100,000 200,000 300,000 400,000 Tarime Bunda Serengeti Musoma Rural Musoma Urban Districts Number of Cattle Indigenous Beef Dairy 1,291,576 1,272,538 1,099,068 - 500,000 1,000,000 1,500,000 Number of Cattle 1995 1999 2003 Year Chart 3.127 Cattle Population Trend Musoma Urban Musoma Rural Bunda Tarime 6 175 149 92 52 Serengeti 160 to 180 120 to 160 80 to 120 40 to 80 0 to 40 Serengeti Bunda Musoma Urban Musoma Rural Tarime 349,523 251,329 267,198 1,301 229,719 Cattle Population as of 1st Octobers 2003 by District MAP 3.47 MARA Number of Cattle Per Square Km MAP 3.48 MARA Cattle Density as of 1st October 2003 by District Cattle Density Number of Cattle Cattle Population 280,000 to 350,000 210,000 to 280,000 140,000 to 210,000 70,000 to 140,000 0 to 70,000 Tanzania Agriculture Sample Census RESULTS 77 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 78 Improved Cattle Breeds The total number of improved cattle in Mara region was 9,061 (8,797 dairy and 264 improved beef). The diary cattle constituted 0.8 percent of the total cattle and 97.1 percent of improved cattle in the region. The number of beef cattle in the region constituted 2.9 percent of the total number of the improved cattle and 0.02 percent of the total cattle. The number of improved cattle increased from 1,890 in 1995 to 9,061 in 2003 at an annual rate of 21.6 percent. From the year 1995 to 1999 the number of improved cattle decreased from 1,890 to 704 (an annual decrease rate of -21.9). The population shot from 704 in 1999 to 9,061 at an annual rate of 89.4 percent (Chart.128). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region, followed by sheep and pig rearing. In terms of total number of goats, Mara region ranked 9 out of the 21 regions of Tanzania Mainland with 5.4 percent of the total goats. Goat Population The number of goat-rearing households in Mara region was 72,575 (39% of all agricultural households in the region) with a total number of 634,044 goats giving an average of 9 head of goats per goat-rearing household. Tarime district had the largest number of goats (237,710 goats, 37.5% of all goats in the region), followed by Musoma Rural (173,221 goats, 27.3%), Bunda (118,038 goats, 18.6%), Serengeti (103,574 goats, 16.3%) and Musoma Urban (1,501 goats, 0.2%) (Chart 3.129 and Map 3.49). However Musoma Rural district had the highest density of goats in the region (109 head per km2 ) (Map 3.50). Goat Herd Size Thirty seven percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. About 84 percent of total goat-rearing households had herd size of 1-14 goats and owned 56 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 1,405 households (1.9%) with herd sizes of 40 or more goats each (66,416 goats in total), resulting in an average of 47 goats per goat rearing household. 1,890 704 9,061 - 2,500 5,000 7,500 10,000 Number of Cattle 1995 1999 2003 Year Chart 3.128 Improved Cattle Population Trend 0 50 100 150 200 250 Number of Goats ('000') Tarime Musoma Rural Bunda Serengeti Musoma Urban District Chart 3.129 Total Number of Goats ('000') by District Bunda Musoma Rural Musoma Urban Tarime 77.2 6.4 112.3 62.7 21.6 Serengeti 80 to 120 60 to 80 40 to 60 20 to 40 0 to 20 Bunda Musoma Urban Tarime Musoma Rural 118,038 1,501 237,710 173,221 103,574 Serengeti 200,000 to 240,000 150,000 to 200,000 100,000 to 150,000 50,000 to 100,000 0 to 50,000 Goat Population as of 1st Octobers 2003 by District MAP 3.49 MARA Number of Goats Per Square Km MAP 3.50 MARA Goat Density as of 1st October 2003 by District Goat Density Number of Goat Goat Population Tanzania Agriculture Sample Census RESULTS 79 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.8 percent of the total goats in Mara region. Improved goats for meat and diary goats constituted 0.8 and 0.4 percent of total goats respectively. Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 0.3 percent. This positive trend implied eight years of population increase from 620,748 in 1995 to 634,044 in 2003. The number of goats decreased from 620,748 in 1995 at an annual rate of -1.7 percent to 578,900 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 2.3 percent (Chart 130). 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Mara region after cattle and goats. The region ranked 7 out of 21 Mainland regions and had 4.9 percent of all sheep on Tanzania Mainland. Sheep Population The number of sheep-rearing households was 21,780 (12% of all agricultural households in Mara region) rearing 194,073 sheep, giving an average of 9 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Tarime with 75,196 sheep (39% of total sheep in Mara region) followed by Serengeti (48,376 sheep, 25%), Musoma Rural (40,362 sheep, 21%) and Bunda (30,078 sheep, 16%). Musoma Urban district had the least number of sheep (61 sheep) (Chart 3.131 and Map 3.51). However Musoma Rural district had the highest density of sheep in the region (26 head per km2 ) (Map 3.52). Sheep rearing was dominated by indigenous breeds that constituted 99.8 percent of all sheep kept in the region. Only 0.2 percent of the total sheep in the region were improved breeds. Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 was 1 percent. The population increased at an annual rate of 2 percent from 179,019 in 1995 to 194,036 in 1999. The sheep population remained fairly constant at around 194,000 from year 1999 to 2003 (Chart 3.132). 0 20,000 40,000 60,000 80,000 Number of sheep Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.131 Total Number of Sheep by District 620,748 578,900 634,044 - 200,000 400,000 600,000 Number of Goats 1995 1999 2003 Year Chart 3.130 Goat Population Trend 179,019 194,036 194,073 - 50,000 100,000 150,000 200,000 Number of Sheep 1995 1999 2003 Year Chart 3.132 Sheep Population Trend Serengeti Bunda Musoma Urban Musoma Rural Tarime 3 14 103 60 11 Musoma Urban Musoma Rural Bunda Tarime 23,995 91,890 21,090 13,781 43,318 Serengeti Sheep Population as of 1st Octobers 2003 by District MAP 3.51 MARA Number of Sheep Per Square Km MAP 3.52 MARA Sheep Density as of 1st October 2003 by District Sheep Density Number of Sheep Sheep Population 90,000 to 100,000 70,000 to 90,000 50,000 to 70,000 30,000 to 50,000 10,000 to 30,000 80 to 110 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census RESULTS 81 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 3.12.4. Pig Production Pig rearing is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 20th out of 21 Mainland regions and had 0.2 percent of the total pigs on the Mainland. The number of pig-rearing agricultural households in Mara region was 328 (0.2% of the total agricultural households in the region) rearing 2,409 pigs. This gives an average of 7 pigs per pig-rearing household. The district with the largest number of pigs was Tarime with 2,129 pigs (88.4% of the total pig population in the region), followed by Serengeti (279 pigs, 11.6%). There was no pig rearing in the rest of the districts (Chart 3.133 and Map 3.53). However, Tarime district had the highest density (0.6 head per km2 ) (Map 3.54). Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was -9 percent. During this period, the pig population dropped from 5,139 to 2,409. The pig population increased from 5,139 in 1995 to 17,481 in 1999 at a rate of 36 percent, after which it decreased to 2,409 in 2003 (an annual rate of -39) (Chart 3.134). 3.12.5 Chicken Production The poultry sector in Mara region was dominated by chicken production. The region contributed 4.6 percent to the total chicken population on Tanzania Mainland. Chicken Population The number of households keeping chickens was 141,825 raising about 1,521,166 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Mara region was ranked 11th out of the 21 Mainland regions. The district with largest number of chickens was Tarime with 585,983 chickens (38.5% of the total chickens in the region), followed by Musoma Rural (451,007 chickens, 29.6%), Serengeti (252,277 chickens, 16.6%) and Bunda (228,644 chickens, 15.0%). Musoma Urban district had the smallest number of chickens (3,255 chickens, 0.2%) (Chart 3.135 and Map 55). However Musoma Rural district had the highest chicken density in the region (292 chickens per km2 ) (Map 3.56). 0 500 1,000 1,500 2,000 2,500 Number of Pigs Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.133 Total Number of Pigs by District 5,139 17,481 2,409 - 4,000 8,000 12,000 16,000 20,000 Number of Pigs 1995 1999 2003 Year Chart 3.134 Pig Population Trend 0 200,000 400,000 600,000 Number of Chickens Tarime Musoma Rural Serengeti Bunda Musoma Urban District Chart 3.135 Total Number of Chicken by District Serengeti Bunda Musoma Urban Musoma Rural Tarime 279 0 0 0 2,129 Musoma Urban Musoma Rural Bunda Serengeti Tarime 0 0 0 0.1 0.6 0.48 to 0.60 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Pig Population as of 1st Octobers 2003 by District MAP 3.53 MARA Number of Pig Per Square Km MAP 3.54 MARA Pig Density as of 1st October 2003 by District Pig Density Pig population Pig population Tanzania Agriculture Sample Census RESULTS 83 Tarime Musoma Urban Musoma Rural Bunda 14 292 150 155 53 Serengeti Bunda Musoma Urban Musoma Rural Tarime 228,644 3,255 451,007 585,983 252,277 Serengeti 300 to 400 300 to 400 200 to 300 100 to 200 0 to 100 480,000 to 590,000 360,000 to 480,000 240,000 to 360,000 120,000 to 240,000 0 to 120,000 Number of Chicken as of 1st October 2003 by District MAP 3.55 MARA Numbner of Chicken Per Square Km MAP 3.56 MARA Density of Chicken as of 1st October 2003 by District Chicken Density Number of Chicken Number of Chicken Tanzania Agriculture Sample Census RESULTS 84 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 1.1 percent. The chicken population increased at a rate of 0.9 percent from 1995 to 1999, after which it increased at a rate of 1.2 percent for the four year period from 1999 to 2003 (Chart 3.136). Ninety nine percent of all chicken in Mara region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. Chicken Flock Size The results indicate that about 86 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 11 chickens per chicken rearing household. About 14 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 28 chickens per household. Only 0.1 percent of households kept the flock sizes of more than 100 chickens at an average of 120 chickens per household (Table 3.14). Improved Chickens (layers and broilers) The layer population in Mara Region decreased at an overall annual rate of -4.4 percent over the period of eight years from 20,823 in 1995 to 14,561 in 2003. The number of improved chicken was most significant in Musoma Rural district followed by Serengeti district (Chart 3.137). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was -15.2 percent during which the population dropped from 4,426 to 1,183. The annual growth rate for the period of four years from 1995 to 1999 was 42.7 percent which resulted in an increase of broiler chicken from 4,426 to 18,383. The broiler chicken population Table 3.14 Total Number of Households and Chickens Raised by Flock Size Number of Households % Number of Chicken Average Chicken per Households 1 - 4 36,629 26 103,477 3 5 - 9 42,208 30 278,665 7 10 - 19 41,850 30 535,628 13 20 - 29 14,714 10 325,261 22 30 - 39 3,088 2 98,709 32 40 - 49 1,511 1 63,439 42 50 - 99 1,646 1 94,714 58 100+ 178 0 21,273 120 Total 141,825 100 1,521,166 11 1,395,054 1,448,282 1,521,166 - 400,000 800,000 1,200,000 1,600,000 Number of Chicken 1995 1999 2003 Year Chart 3.136 Chicken Population Trend 536 268 4,607 798 7,872 0 1,546 0 0 117 0 2,000 4,000 6,000 8,000 Number of Chickens Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.137 Number of Improved Chicken by Type and District Layers Broilers 20,823 4,426 61,559 18,383 14,561 1,183 - 20,000 40,000 60,000 80,000 Number of Improved Chickens 1995 1999 2003 Year Chart 3.138 Improved Chicken Population Trend Layers Broilers RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 86 exhibited a decreasing trend at the rate of -49.6 percent per annum for the period of four years from 18,383 chickens in 1999 to 1,183 chickens in 2003 (Chart 3.138). 3.12.6. Other Livestock There were 64,254 ducks, 12,737 turkeys, 37,053 rabbits and 3,104 donkeys raised by rural agricultural households in Mara region. Table 3.15 indicates the number of livestock kept in each district. The largest number of ducks in the region was found in Musoma Rural district with 40,623 ducks (63% of all ducks in the region), followed by Tarime (8,963 ducks, 14%), Bunda (8,167 ducks, 13%), Serengeti (4,826 ducks, 14%) and Musoma Urban (1,675 ducks, 3%). Turkeys were reported in Tarime and Serengeti districts only. The biggest number of rabbits was found in Musoma Rural district (94% of the total rabbits in Mara region), however the largest number of donkeys was found in Tarime district (35% of the total number of donkeys in the region) (Table 3.15). 3.12.7 Pests and Parasites Incidences and Control The results indicate that 69 percent and 17 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. The census results show that there was a predominance of tick related diseases over tsetse related diseases. While incidences of tick problems were highest in Musoma Urban district and lowest in Serengeti district, tsetse flies incidences were highest in Serengeti but lowest in Musoma Rural district and no tsetse flies incidences were reported in Musoma Urban district (Chart 3.139 Map 3.57). The most common method of tick control was spraying which was used by 56 percent of all livestock-rearing households having tick problems. Other methods used were dipping (4%), smearing (4%) and other traditional methods like hand picking (19%). However, 18 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 34.6 percent of livestock- rearing households. This was followed by dipping (3.4%) and trapping (3.3%) and other methods (2.8%). However, 55.9 percent of the livestock rearing households did not use any of the three aforementioned methods. Table 3.15 Head Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbit Donkeys Other Tarime 8,963 5,782 1,333 1,071 2,522 Serengeti 4,826 6,955 419 272 4,733 Musoma Rural 40,623 0 34,865 819 9,498 Bunda 8,167 0 437 942 875 Musoma Urban 1,675 0 0 0 0 Total 64,254 12,737 37,053 3,104 17,629 Chart 3.139 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 Tarime Serengeti Musoma Rural Bunda Musoma Urban District Percent of Households Ticks Tsetseflies Musoma Urban Tarime Bunda Musoma Rural Serengeti 62% 39% 53% 27% 0% 49,457 11,984 13,344 14,764 0 Musoma Rural Serengeti Musoma Urban Bunda Tarime 12,796 136 8,129 7,939 24,589 76% 72% 66% 67% 70% Number and Percent of Households Infected with Ticks by District MAP 3.57 MARA Number of Households Using Draft Animals MAP 3.58 MARA Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Number of Households Infected with Ticks Number of Households Infected With Ticks Percent of Households Infected With Ticks Percent of Households Using Draft Animals 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census RESULTS 87 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 De-worming Livestock rearing households that de-wormed their animals were 44,155 (52% of the total livestock rearing households in Mara region). The percentage of cattle keeping households that de- wormed cattle was 48 percent, goats (35.6%) and sheep (41%). The district with the highest number of households that de-wormed cattle was Tarime (48% of total households that de-wormed cattle) followed by Musoma Rural (20.2%), Serengeti (19.2%), Bunda (12.3%) and Musoma Urban (0.2%) (Chart 3.138). 3.12.8. Access to Livestock Services Access to Livestock Extension Services The total number of households that received livestock advice was 31,979, representing 38 percent of the total livestock- rearing households and 17 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 65 percent of all households receiving livestock extension services. This was followed by NGOs/development projects (12.8%), large scale farmers (8.5%) and cooperatives (7.5%). About 58.1 percent of livestock rearing households described the general quality of livestock extension services as being good, 22.7 percent said they were average and 17.5 percent said they were very good. However, 0.3 percent of the livestock rearing households said the quality was not good and 1.4 percent described them as poor (Chart 3.141). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 80 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 20 percent of them accessed the services within 14 kms from their dwellings (Chart 3.142). Chart 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock ExtensionServices Good 58.1% Average 22.7% Poor 1.4% No good 0.3% Very Good 17.5% Chart 3.142 Number of Households by Distance to Verinary Clinic More than 14km, 67,727, 80% Less than 14km, 16,731, 20% Chart 3.143 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 Musoma Rural Tarime Serengeti Bunda Musoma Urban District Number of Households Less than 14km More than 14km 0 15 30 45 Percent of Households Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.140 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 89 The most affected district was Musoma Rural district with 89 percent of livestock rearing households accessing the services at a distance of more than 14 kms. Musoma Urban was the least affected because all households could access the service within a distance of 14 kilometres (Chart 3.143). Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 23,302 (73% of the total livestock rearing households in Mara region), whilst 8,439 households (26%) resided between 5 and 14 kms. However, 251 households (1%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.144). Tarime district had the best livestock water supply with the majority of livestock rearing households residing within 5 kilometres from the nearest watering point. This was followed by Musoma Rural, Bunda, Serengeti and Musoma Urban districts. In Musoma Rural district about 39 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.145). 3.12.9. Animal Contribution to Crop Production Use of Draft Power Mara region had the fourth largest proportion of households using draft animals on Tanzania Mainland after Shinyanga, Manyara and Singida. The region had 89,548 households (48% of the total agricultural households in the region) using this technology (Chart 3.146). The number of households that used draft animals in Tarime district was 49,457 representing 55 percent of the households using draught animals in the region followed by Serengeti (14,764 households, 16%), Musoma Rural (13,344 households, Chart 3.144 Number of Households by Distance to Village Watering Points Less than 5 kms, 23,302, 73% 15 or more kms, 251, 1% 5-14 kms, 8,439, 26% Chart 3.145 Number of Households by Distance to Village Watering Point and District 0 2,500 5,000 7,500 10,000 Tarime Musoma Rural Bunda Serengeti Musoma Urban District Number of Households Less than 5 kms 5-14 kms 15 or more kms 0 10,000 20,000 30,000 Number of Households Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.147 Number of Households Using Draft Animals by District - MARA Chart 3.146 Number of Households Using Draft Amimals Not using draft animal, 98,655, 52% Using draft animal, 89,548, 48% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 15%) and Bunda (11,984 households, 13%). There were no households using draft animals in Musoma Urban district (Chart 3.147 and Map 3.58). The region had 377,058 oxen that were used to cultivate 107,673 hectares of land. This represents only 9 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Tarime district (41,905 ha, 39% of the total area cultivated using oxen in the region). Other types of draft animals used to cultivate in Mara region were bulls (57,522 bulls, 9,659 ha), cows (13,915 cows, 3,453 ha) and donkeys (5,613 donkeys, 679 ha). Use of Farm Yard Manure The number of Households using organic fertilizer in Mara region was 47,632 (26% of total crop growing households in the region) (Chart 3.148). The total area applied with organic fertiliser was 33,009 ha of which 29,792 hectares (90.3% of the total area applied with organic fertilizers or 14% of the area planted with annual crops and vegetables in Mara region during the long rainy season) was applied with farm yard manure. The largest area applied with farm yard manure was found in Tarime district with 14,657 hectares (49.2% of the total area applied with farm yard manure in the region), followed by Musoma Rural (6,531 ha, 21.9%), Serengeti (4,758 ha, 16.0%), Bunda (3,765 ha, 12.6%) and Musoma Urban (83 ha, 0.3%) (Chart 3.149 and Map 59). 3.12.9.4 Use of Compost Only 3,217 ha (9.7% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost was found in Bunda district with 2,470 hectares (77% of the total area applied with compost in Mara region), followed by Tarime (538 ha, 17%) and Serengeti (27 ha, 1%). No compost application was found in Musoma Urban district (Chart 3.149 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Mara region was 255, representing 0.1 percent of the total agricultural households in the region (Chart 3.150). Tarime was the only district in the region practicing fish farming. (Chart 3.151 and Map 3.61). Non governmental organizations and/or projects were the only suppliers of fingerings. All fish farming households in the region used the dug-out-pond system and the only fish specie planted was tilapia. The number of fish harvested in Mara region was 44,845, all of which were tilapia. None of the fish farming households sold any fish. Chart 3.148 Number of Crop Growing Households Using Organic Fertiliser Not Using Organic Fertilizer, 138,159, 74% Using Organic Fertilizer, 47,632, 26% Chart 3.149 Area of Application with Organic Fertiliser by District - MARA 0 5,000 10,000 15,000 Tarime Musoma Rural Serengeti Bunda Musoma Urban District Area of Fertiliser Application (ha) Farm Yard Manure Compost Serengeti Tarime Musoma Urban Bunda 27 538 0 182 2,470 3.8% 0.1% 0.2% 0.5% 0% Musoma Rural 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Tarime Musoma Rural Bunda Serengeti Musoma Urban 14,657 6,531 83 3,765 4,758 7.4ha 11.3ha 5.9ha 7.3ha 12.7 Planted Area and Percent of Planted Area With Farm Yard Manure Application by District MAP 3.59 MARA Planted Area With Compost Manure Applied MAP 3.60 MARA Planted Area and Percent of Planted Area With Compost Manure Application by District Planted Area With Compost Applied Planted Area With Farm Yard Manure Applied Planted Area With Farm Yard Manure Applied Percent of Planted Area With Farm Yard Manure Applied Percent of Planted Area With Compost Manure Applied 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanzania Agriculture Sample Census RESULTS 91 Tarime Musoma Urban Musoma Rural Bunda 255 0 0 0 0.3% 0% 0% 0% 0% Serengeti 0 Bunda Musoma Urban Tarime 3,555 9,247 22,708 3,986 12% 18% 11% 29% 14% Serengeti Musoma Rural 48 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Number and Percent of Households Practicing Fish Farming by District MAP 3.61 MARA Number of Households Without Toilets MAP 3.62 MARA Number and Percent of Households Without Toilets by District Number of Households Without Toilets Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming Percent of Households Without Toilets 300 to 400 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census RESULTS 92 RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 3.12.11 Access to Infrastructure and Other Services The results indicate that regional capital was located very far from most of the households’ dwellings. It was located at an average distance of 81 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the households’ dwellings were district capital (42), tarmac road (40), tertiary market (37), hospital (33), secondary market (13), secondary school (11), health clinic (7), primary market (6), all weather road (3), primary school (3) and feeder road (1) (Table 3.16). Only 8 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 14 percent reported them to be average. Twenty five percent of the agricultural households said the infrastructure and services were poor and 24 percent said they were ‘no good’. Eighteen percent of the agricultural households said the infrastructure and services were good. 3.13 POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Type of Toilets A large number of rural agricultural households in Mara region used traditional pit latrines (141,915 households, 75.4% of all rural agricultural households), 3,195 Table 3.16: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary School Primary School All weather road Feeder Road Hospital Health Clinic Regional Capital Primary Market Secondary Market Tertiary Market Tarmac Road District Capital Tarime 11 3 3 1 32 9 91 7 16 40 31 43 Serengeti 10 2 6 3 37 6 109 9 13 34 87 37 Musoma Rural 11 2 2 1 37 6 43 3 11 37 29 42 Bunda 13 2 4 1 27 5 91 4 10 31 37 41 Musoma Urban 4 1 0 1 6 3 6 5 28 5 5 6 Overall Mean 11 3 3 1 33 7 81 6 13 37 40 42 Chart 3.150 Number of Households Practicing Fish Farming - MARA Households Practicing Fish Farming, 255, 0.1% Households Not Practicing Fish Farming, 187,948, 99.9% 0 50 100 150 200 250 Number of Households Tarime Serengeti Musoma Rural Bunda Musoma Urban District Chart 3.151 Number of Households Practicing Fish Farming by District - Mara Chart 3.152 Agricultural Households by Type of Toilet Facility Improved Pit Latrine , 3,195, 1.7% Other Type, 293, 0.2% No Toilet , 39,544, 21.0% Traditional Pit Latrine, 141,915, 75.4% Flush Toilet, 3,255, 1.7% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 94 households (1.7%) used improved pit latrines, 3,255 households (1.7%) used flush toilets and 293 household (0.2%) used other toilets facilities. However, 39,544 households (21.0%) in the region had no toilet facilities (Chart 3.152). The distribution of the households without toilets within the region indicates that 57.4 percent of them were found in Tarime district and 0.1 percent were in Musoma Urban. The percentages of households without toilets in the other districts were as follows: Serengeti (10.1%), Musoma Rural (23.4%) and Bunda (9.0%) (Map 3.62). 3.13.2 Household’s Assets Radios were owned by most rural agricultural households in Mara region with 107,845 households (57.3% of the agriculture households in the region) owning them, followed by bicycles (94,942 households, 50.4%), irons (50,680 households, 26.9%), wheelbarrows (11,057 households, 5.9%), mobile phones (4,098 households, 2.2%), vehicles (1,696 households, 0.9%), television/video (1,550 households, 0.8%) and landline phones (977 households, 0.5%) (Chart 3.153). 3.13.3 Sources of Energy for Lighting Wick lamp was the most common source of energy for lighting in the region, with 63.1 percent of the total rural households using this source of energy, followed by hurricane lamp (32.1%), pressure lamp (3.0%), firewood (0.7%), mains electricity (0.5%), solar (0.3%), candle (0.2%) and gas (biogas) (0.1%) (Chart 3.154). 3.13.4 Sources of Energy for Cooking The most prevalent source of energy for cooking in Mara region was firewood, which was used by 97.3 percent of all agricultural households in the region. This is followed by charcoal (1.8%) and mains electricity (0.3%). The rest of energy sources accounted for 0.6 percent. These were bottled gas (0.22%), crop residues (0.18%), livestock dung (0.08%), paraffin/kerosine (0.07%) and solar (0.04%) (Chart 3.155). Chart 3.153 Percentage Distribution of Households Owning the Assets 5.9 2.2 0.9 0.8 0.5 57.3 50.4 26.9 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Vehicle Television / Video Landline phone Assets Percent of Households Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Lighting Pressure Lamp, 5,705, 3.0% Firewood, 1,307, 0.7% Mains Electricity, 936, 0.5% Solar, 563, 0.3% Candles, 376, 0.2% Gas (Biogas), 252, 0.1% Wick Lamp, 118,703, 63.1% Hurricane Lamp, 60,361, 32.1% Chart 3.155 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 183,115, 97.3% Charcoal, 3,460, 1.8% Mains Electricity, 512, 0.3% Bottled Gas, 419, 0.2% Crop Residues, 333, 0.2% Livestock Dung, 160, 0.1% Parraffin / Kerosine, 136, 0.1% Solar, 68, 0.0% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 95 3.13.5 Roofing Materials The most common material used for roofing the main dwelling was grass and leaves and it was used by 60.4 percent of the rural agricultural households in Mara region. This was followed by iron sheets (28.7%), grass and mud (9.8%), tiles (0.6%), concrete (0.4%), asbestos (0.1%) and other materials (0.1%) (Chart 3.156). Serengeti district had the highest percentage of households with grass/leaves roofing material in Mara region (73%), followed by Bunda (65%), Musoma Rural (62%), Tarime (54%) and Musoma Urban (27%) On the other hand, Iringa Urban district had the highest percentage of households whose roofing material for the main building was iron sheets, (73%), followed by Musoma Rural (34%), Bunda (33%), Tarime (30%) and Serengeti (10%) (Chart 3.157 and Map 3.63). 3.13.6 Access to Drinking Water The main source of drinking water for rural agricultural households in Mara region was unprotected wells (39% of households use unprotected wells during the wet season and 36 percent of the households during the dry seasons). This is followed by surface water (Lake / Dam / River / Stream) (20% of households during wet season and 29% in the dry season), unprotected springs (16% of households in the wet season and 16% during dry season), protected wells (11% of households in the wet season and 10% during dry season) and protected /covered springs with 4 percent of households using the source in each season. Other sources of drinking water and their respective percentages of households using the source for drinking water during wet and dry season were piped water (3.8% during wet season, 4.0 during dry season), uncovered rainwater catchments (2.8% during wet season, 0.3% during dry season), covered rainwater catchments (0.8% during wet season, 0.2% during dry season), water vendors (0.04% during dry season) and other unmentioned sources (2.4% during wet season) (Chart 3.158). Chart 3.156 Percentage Distribution of Households by Type of Roofing Material Grass / Leaves, 113,685, 60.4% Other, 116, 0.1% Asbestos, 132, 0.1% Iron Sheets, 54,052, 28.7% Grass & Mud, 18,388, 9.8% Concrete, 663, 0.4% Tiles, 1,166, 0.6% Chart 3.158 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 40 Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotected Spring Surface Water (Lake / Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Other Main Source Percent of Households Wet Season Dry Season Chart 3.157 Percentage Distribution of Households by Type of Roof and y District 11 33 34 30 73 27 54 62 65 73 0 25 50 75 Serengeti Bunda Musoma Rural Tarime Musoma Urban District Percent of Households RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 About 50 percent of the rural agricultural households in Mara region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 50 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during the wet season compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.159). 3.13.7 Food Consumption Pattern Number of Meals per Day The majority of households in Mara region normally had 2 meals per day (58.4 percent of the agricultural households in the region). This was followed by 3 meals per day (39.2 percent) and 1 meal per day (2.0 percent). Only 0.3 percent of the agricultural households had 4 meals per day (Chart 3.160). Serengeti district had the largest percent of households having one meal per day as well as the highest percent of households having 3 meals per day (Table 3.17 and Map 3.64). Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 130,134 (69% of the agricultural households in Mara region) with 63,808 households (49% of the households that consumed meat), consumed meat only once during the respective week. This was followed by those who had meat twice during the week (41,712 households, 32.1%). Very few households had meat four times or more during the respective week. About 58,069 agricultural households (30.8% of the agricultural households in Mara region) did not eat meat during the week preceding the census (Chart 3.161a and Map 3.65). Chart 3.17: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of Meals per Day District One % Two % Three % Four % Total Tarime 2149 2.7 37,161 46.9 39,727 50.2 132 0.2 79,170 Serengeti 1251 4.5 8,781 31.5 17,487 62.8 346 1.2 27,864 Musoma Rural 317 0.6 39,515 79.0 10,164 20.3 0 0.0 49,995 Bunda 78 0.3 24,235 78.9 6,253 20.4 155 0.5 30,721 Musoma Urban 0 0.0 247 54.4 207 45.6 0 0.0 453 Total 3,794 2.0 109,939 58.4 73,838 39.2 633 0.3 188,203 Chart 3.159 Percent of Households by Distance to Main Source of Drinking Water and Season 0 10 20 30 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance Percent of Households Wet Season Dry Season Chart 3.160 Number of Agricultural Households by Number of Meals per Day Three, 73,838, 39.2% One, 3,794, 2.0% Four, 633, 0.3% Two, 109,939, 58.4% Chart 3.161a Number of Households by Frequency of Meat and Fish Cosumption 0 25000 50000 One Two Three Four Five Six Seven Frequency Number of Households Meat Fish RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 164,796 (88% of the total agricultural households in Mara region) with 33,998 households (20.1% of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish twice (17.5%) and seven times (16.3%). In general, the number of households that consumed fish twice or more during the week in Mara region was 130,798 (79.4% of the agricultural households that ate fish in the region during the respective period). About 12.4 percent of the agricultural households in Mara region did not eat fish during the week preceding the census (Chart 3.161a and Map 66). 3.13.8 Food Security In Mara region, 63,989 households (34% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement, whilst 11,292households (6%) said they sometimes experience problems. The number of households that often experienced problems was 18,820 households (10%), however 15,056 households (8%) said they always had problems in satisfying the household food requirement. About 79,045 agricultural households (42%) said they did not experience any food sufficiency problems (Chart 3.161b, Map 67). Bunda district has the highest percent of households that have problems in satisfying their household food requirements (29% of the agricultural households always or often having food problems). The percentage of households with food problems is also higher in Tarime and Musoma Urban districts (21% and 20% respectively). Serengeti district had the lowest percent of households that always or often face food problems (9% of the agricultural households) followed by Musoma Rural (13%) (Chart 3.161c). 3.13.9 Main Sources of Cash Income The main cash income of the households in Mara region was from selling food crops (36.1 percent of smallholder households), followed by other casual cash earnings (13.3%), businesses (11.4%), selling of cash crops (9.6%), and fishing (9.5%). Only 5.9% of Chart 3.162 Percentage Distribution of the Number of Households by Main Source of Income Other 1.5% Livestock Products 1.0% Wages & Salaries 4.6% Forest Products 2.2% Livestock 5.9% Remittance 4.9% Fishing 9.5% Business Income 11.4% Cash Crops 9.6% Other Casual Cash Earnings 13.3% Food Crops 36.1% Chart 3.161c Percent of Households Reporting Food Availability Status by District - Moro 0% 25% 50% 75% 100% Musoma Rural Musoma Urban Serengeti Tarime Bunda District Percent of Households Never Seldom Sometimes Often Always Chart 3.161b Number of Households by Level of Food Availability - Moro Always, 15,493, 8% Often, 19,252, 10% Sometimes, 10,545, 6% Seldom, 64,799, 34% Never, 78,113, 42% RESULTS AND ANALYSIS _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 smallholder households reported the sale of livestock as their main source of income, followed by cash remittance (4.9%), wages and salaries (4.6%), sale of forest products (2.2%) and sale of livestock products (1.0%) (Chart 3.162). Bunda Musoma Rural Musoma Urban Tarime 6,253 10,164 207 17,487 39,727 20% 20% 46% 63% 50% Serengeti 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Serengeti Musoma Urban Musoma Rural Bunda Tarime 20,358 121 30,887 19,854 42,464 73% 27% 62% 65% 54% Number and Percent of Households Using Grass/Leaves for Roofing Material by District MAP 3.63 MARA Number of Households Eating 3 Meals Per Day MAP 3.64 MARA Number and Percent of Households Eating 3 Meals Per Day by District Number of Households eating 3 meals Number of Households Using Grass/Leaves for Roofing Material Number of Households Using Grass/Leaves Percent of Households Using Grass/Leaves Percent of Households eating 3 meals 36,000 to 43,000 27,000 to 36,000 18,000 to 27,000 9,000 to 18,000 0 to 9,000 Tanzania Agriculture Sample Census RESULTS 99 Tarime Musoma Rural Bunda Serengeti Musoma Urban 18,020 2,586 9,250 4,117 22.8 5.2 33.2 5.4 13.4 25 16,000 to 20000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 40,000 to 40,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Bunda Musoma Urban Musoma Rural Tarime 6,916 43 15,645 30,576 10,628 22.5% 31.3% 9.4% 38.%6 38.1% Serengeti Number and Percent of Households Eating Meat Once Per Week by District MAP 3.65 MARA Number of Households Eating Fish Once per Week MAP 3.66 MARA Number and Percent of Households Eating Fish Once Per Week by District Number of Households Eating Fish Once Per Week Number of Households Eating Meat Once Per Week Number of Households Eating Meat Once Per Week Percent of Households Eating Meat Once Per Week Percent of Households eating Fish Once Per Week Tanzania Agriculture Sample Census RESULTS 100 Musoma Urban Musoma Rural Tarime Serengeti Bunda 109 9,386 20,526 4,830 10,440 24% 26% 17% 19% 34% 30,000 to 40,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number and percent of Households Reporting Food Insufficiency by District MAP 3.67 MARA Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency Tanzania Agriculture Sample Census RESULTS 101 MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 PART IV: MARA PROFILES 4.1 Region Profile Mara has a land area of 330,000 hectares under crop production and the number of crop growing households was small compared to most regions, however it had a relatively high number of livestock and crops growing households. The region had a moderate to high number of smallholder households per square kilometer. The land area available per household was moderate to high, however the utilized land area was below the average for the country resulting in one of the lowest land utilization rates in the country. The region had one of the highest areas of permanent mono-crops in the country. It had two seasons and the planted area in the short rainy season is about half that of the long rainy season. The average area planted per crop growing household in the long rainy season was 1.7ha and 0.9 ha in the short rainy season. The region had a moderate to low planted area of cereals. Although maize had the largest planted area, the area of sorghum was fourth largest in the country and its production was the highest. The region had the second largest planted area of cassava, however beans and groundnuts were produced in very small quantities. The region had a moderate to low production of tomato and cabbage and produced minor quantities of onions. A small amount of cotton was grown in the region. Minor quantities of coffee, mangoes, sugar cane and oranges were also produced. Moderate to low planted areas of irrigation exist in the region. Very few households practice irrigation and the number of households with irrigation had not changed significantly for 10 years. Most cultivation was done by using oxen. A small amount of farm yard manure was applied and virtually no pesticides are used. Normally, storage was in locally made traditional cribs. The percentage of households selling crops was average for the country. Most processing was done using neighbours machines and only small amounts of the processed crops were sold and mostly to local markets/trade store (the highest percent using this marketing outlet in the country). The receipt of extension per household was moderate. Mara had the fifth largest number of trees in the country and the dominant species were trichillia and eucalyptus. A moderate number of households have erosion control/water harvesting facilities and erosion control bunds was the most common followed by water harvesting bunds. Mara region has a moderate livestock population compared to other regions. Although it is one of the smallest regions in terms of available land it has a high density of livestock. Livestock is dominated by indigenous cattle; very low numbers of improved breeds are present. Compared to other regions the density of goats is moderate. However, it has a relatively high density of goats. Sheep and pig production is insignificant in the region. The region has a moderate population of chickens and very small numbers of improved layers and broilers. Egg production is low indicating that most chickens are kept for meat. It has a moderate milk production; however the farm gate price of milk is amongst the lowest in the country. The area of organic fertilizer application is moderate to low compared to other regions. The use of draft animals is high however the area cultivated is comparatively low, which indicates that draft animals are probably used less for cultivation purposes. MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 Mara has the highest rate of foot and mouth infection and there is a high incidence of foot rot possibly a result of the wetter conditions in the region. Mara has the worst access to veterinary clinics compared to other regions. In general, access to other infrastructure and services is moderate to good. However a small number of households received extension advice. Mara Region has the eleventh highest rural agriculture population in Tanzania (1,097,741 persons of which 548,314 are males and 549,427 females). It has a moderate number of rural households involved in agriculture (188,203) compared to other regions. It has 96 percent of rural households and 76 percent of total households in the region (including urban) that are involved in agriculture. The region has the fourth highest average household size in the country (5.8 persons per household) and it has a high percent of female headed households (20%) compared to other regions. Crop only and both crop and livestock production are the important types of farming in the region. The number of livestock only households in the region is very small and it also has no pastoralist households. Land under customary law is the predominant type of land ownership, accounting for almost 80 percent of the total rural smallholder owned land and represents the second highest in the country.. There is a small amount of land under official titles. The region has a moderate access to fields with about 45 percent of the rural agriculture households having their nearest field less than 100m from the homestead. Access from the field to the nearest road is moderate to poor compared to other regions. Mara has a high percent of literate rural agriculture population (68%) compared to other regions, however the difference between the literacy rate of males and females is high with 13 percent more literate males than females. It has a comparatively high percent of the rural agriculture population that have completed school and a low percent of household heads with no education. The most important livelihood activity is crop farming followed by livestock keeping and tree/forest resources. Off farm Income is the least important. The percent of the rural agriculture population working full time in farming is high (74%). The main source of cash income for Mara is from the sale of food crops and It has the highest percent of rural agriculture households depending on fishing as a source of cash income. Mara receives virtually no credit. A low percent of households use modern roofing material in the region (around 30%) and the rest is mainly with grass/leaves/mud. The region has the third lowest number of households with no toilet facilities (21%). Energy for lighting is mainly from wick lamps (50%) and about 30 percent of households use hurricane lamps. Mara has the second lowest percent of households using piped drinking water. Most water is from unprotected wells and open water (lake/river etc) About 25 percent of households in Mara region obtain drinking water from piped supplies, with the remaining households mainly using protected and unprotected wells and open water (lake, river etc). Most rural agriculture smallholders are living a subsistence existence. However, it has the fourth highest number of households (15%) that use over 50% of their livelihood activities for non-subsistence purposes. It has the lowest number of households that do not eat animal protein in one week and the highest percent of households that eat animal protein every day. Most households in the region either never or seldom face problems with food shortage. The region has poor access to services and infrastructure in the country. About 60% of the households reported insufficiency of land which is the third highest in the country. MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 104 4.2 DISTRICT PROFILES The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Tarime Tarime district had the largest number of households in the region and it had the third highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock production, followed by crop production only. It had a very small number of households involved in livestock keeping only and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Tarime district was annual crop farming, followed by forestry products and permanent crop farming. However, the district had the second lowest percent of households with off- farm activities and the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tarime had the second highest percent of female headed households (24.8%) and it had the second lowest average age of the household head. The district had the lowest average household size in Mara region (4.9 members per household). Tarime had the second highest literacy rate among smallholder household members and second lowest literacy rate for the heads of household in the region. It had the second lowest utilized land area per household (1.5 ha) and the allocated area was almost fully utilized (77% land utilization) indicating an impending high level of land pressure. The district had the largest total planted area and the second smallest area per household (1.5 ha). The district was the largest maize and sorghum production in the region with a planted area of 39,273 and 22,060 hectares respectively, however the planted area of maize per maize growing household was the second lowest in the region. Paddy production with a planted area of 872 ha (18% of the total planted area in the region). The district was the second largest producer of finger millet in the region and had the largest area planted with cassava. The district was the second largest producer of sweet potatoes with a planted area of 4,347 ha accounting for 26.2 percent of the total area planted with sweet potatoes in the region. Although the district had the second lowest area planted with beans in the region, the area planted with beans is relatively large (2,035 ha). Oilseed crops were not important in Tarime, it had a moderate area planted with groundnuts compared to other districts in the region. Vegetable production was important in the district. It had the largest planted area with spinach (78% of the total area planted with spinach in the region), onions (76%), cabbages (51%) and tomatoes (49%). It was the only district in which garlic and ginger are produced. Tarime had the largest planted area with permanent crops which was dominated by banana (3,923 ha), followed by coffee (3,687 ha). Other permanent crops were grown in small quantities. As with other districts in the region, most land clearing and preparation was done by hand. It had also the largest area of bush clearance in the region, however it had the largest area of land prepared using oxen. Tarime had the largest area planted with improved seed and the largest area planted with fertilizers (farm yard manure, compost and inorganic fertiliser) in Mara. However, most of the applied fertilizer was farm yard manure. Compared to MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 105 other districts in the region, Tarime district had the lowest level of insecticide/fungicide use. It had the second largest area with irrigation compared to other districts having 634 ha of irrigated land. The most common sources of water for irrigation were rivers and wells using hand buckets. Hand buckets/watering cans were the most common means of irrigation water application and very little hand pump was used. The most common method of crop storage was locally made traditional structures followed by sacks/open drums and the proportion of households storing crops in the district was moderate. The district had the largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. The proportion of households processing crops was moderate and more than 50 percent were processed using neighbor machines. The district had the second highest percent of households selling processed crops to large scale farms compared to other districts and no sales were made to marketing cooperatives and farmers associations. No households reported to have accessed agricultural credit. The district had the smallest proportion of households receiving extension services in the region and almost all of this was from the government. The quality of extension services was rated between good and average by the majority of the households (80%). Tree farming was very important in Tarime district (with 3,598,493 planted trees) and the trees were mostly eucalyptus and trichillia spp. The number of households with erosion control and water harvesting structures in Tarime district was moderate and most of them were erosion control bunds, however it also had the largest number of terraces in the region. The district had the largest number of cattle, goats and sheep in the region and they were almost all indigenous. Tarime also had the highest number of pigs and chickens. The latter was dominated by indigenous chickens. Small numbers of ducks, turkeys, rabbits and donkeys were also found in the district. It had the largest number of households reporting tsetse and tick problems in the region and it had the largest number of households de-worming livestock. The use of draft animals in the district was most prominent and it was the only district in the region in which fish farming was practiced. It is amongst the districts with the best access to feeder roads in Mara region. However, it had one of the worst access to health clinics, primary markets, tertiary markets and district capital. Tarime district had the highest percent of households with no toilet facilities and it had one of the highest percent of households owning radios, bicycles and irons. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had relatively high percent of households with grass roofs (53.6%) and 29.9 percent of households having iron sheet roofs. The most common source of drinking water was unprotected wells. It had the second highest percent of households having three meal per day compared to other districts. The district had the second lowest percent of households that did not eat meat during the week prior to enumeration, however it had the highest percent of households that did not eat fish during that period. Most households seldom had problems with food satisfaction. 4.2.2 Serengeti Serengeti was the second district with the least number of households in the region and it was the district with the second highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 106 production only, followed by crop and livestock production and livestock keeping only. No pastoralists were found in the district. The most important livelihood activity for smallholder households in Serengeti district was annual crop farming, followed by tree/forestry resources and permanent crop farming. However, the district had the lowest percentage of households with off-farm activities and the lowest percentage of households with more than one member with off-farm income. Compared to other districts in the region, Serengeti had moderate percentage of female headed households (24.1%) and it had the lowest average age of the household head in the region (6.1 members per household). The district had the second lowest average household size in the region. Serengeti had a comparatively low literacy rate among smallholder household members, however it had the lowest literacy rate for the head of households. It had the largest utilized land area per household (2.5 ha) and the lowest proportion of the allocated area was utilized (75% land utilization). The district had moderate planted area as well as planted area per crop growing household (2.4 ha). Maize production in the district was moderate compared to other districts in the region with a planted area of 17,490 ha and the planted area per household was also moderate. Bulrush millet production was less important with a planted area of only 27 hectares. The district was the second sorghum producer in the region. While paddy production was not important, it had the largest planted area for finger millet. Serengeti had the second smallest area planted with cassava as well as sweet potatoes and the second largest area planted with Irish potatoes. While bean production in the district was moderate, it had the largest area planted with cowpeas. Serengeti district had the second smallest groundnuts planted area in Mara region with area planted per groundnut growing household of 0.25 ha. Vegetable production was not important in the district. Though small the district had the second largest planted area with onions and spinach. Compared to other districts in the region, Serengeti had a moderate area with permanent crops which were dominated by oranges (677 ha), banana (257 ha) and mandarine/tangerine (199 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing was done by hand, however the second largest land area prepared by oxen in the region. Serengeti had the second smallest planted area with improved seed in Mara region, however it had the lowest proportion of households using improved seeds. The district had the second lowest planted area with fertilizers (farm yard manure, compost and inorganic fertiliser), and most of this was farm yard manure. Compared to other districts in the region, Serengeti district had a moderate level of insecticide use. The use of fungicides was the second highest in the region. It had the smallest proportion of planted area applied with herbicides in the region. It had the second smallest area with irrigation compared to other districts, with 109 ha of irrigated land. The most common sources of water for irrigation were from rivers and wells using hand buckets. Buckets/watering cans were the most common means of irrigation water application. The most common methods of crop storage in Serengeti district were locally made traditional structures and sacks and/or open drum; however the proportion of households storing crops in the district was the highest in the region. Serengeti MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 107 district had the highest proportion of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. Serengeti had the highest percent of households processing crops in Mara region and 93 percent of those households used neighbours machine. The district also had the highest percent of households selling processed crops to secondary markets and marketing cooperatives than other districts in the region. No sales were made to farmers associations and traders at farm. Serengeti was the only district in the region in which both male and female headed households accessed agricultural credits. The main source of credit was traders/trade stores, followed by family, friends and relatives. A comparatively low number of households received extension services in Serengeti district and 98.8 percent of this was from the government. The quality of extension services was rated between good and average by the majority of the households (83.3%). The district had moderate number of trees in the region (with 344,415 planted trees) and most of these were eucalyptus spp. Serengeti district had a relatively small number of households with erosion control and water harvesting structures and most of them were erosion control bunds, however it also had the a number of tree belts and water harvesting bunds. The district had the third lowest number of cattle in the region and they were almost all indigenous. While the district had the second smallest number of goats in the region, it also had the second largest number of sheep. The district was among two districts in the region in which pig rearing was practiced and had the second largest number of pigs in the region after Tarime district. Some ducks, turkeys, rabbits and donkeys were also found in the district. The number of households reporting tick problems in Serengeti district was relatively small, however the district had the largest proportion of households reporting tsetse problems in the region. It also had a moderate proportion of households de-worming livestock. The district had the second number of households using draft animals in the region. There was no fish farming in Serengeti district. It is amongst the districts with the best access to primary schools, however it had one of the worst access to all weather roads, feeder roads, primary markets, tarmac roads and regional capital. The percentage of households without toilet facility in Serengeti district was 14 and it was among the districts with the lowest percent of households owning mobile phones, bicycles and televisions/videos in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing materials for most of the households in the district were grass and leaves (73.1%), however the district had the lowest percent of households with iron sheet roofing (11.4% of households in the district). The most common source of drinking water was unprotected wells. It had the highest percent of households having three meals per day. The district had the lowest percent of households that did not eat meat and the highest percentage of households that did not eat fish during the week prior to enumeration, however it had the lowest proportion of households who were always facing food shortage. 4.2.3 Musoma Rural Musoma Rural district had the second largest number of households in the region and the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop production only, followed by those involved in both crop and livestock production and livestock keeping only. No pastoralists were found in the district. MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 108 The most important livelihood activity for smallholder households in Musoma Rural district was annual crop farming, followed by tree/forestry resources and off farm input. However, the district had moderate percent of households with no off-farm activities as well as moderate percentage of households with more than one member with off-farm income. Compared to other districts in the region, Musoma Rural had the lowest percent of female headed households (20.3%) and it had the third highest average age of the household head in the region. The district had one of the highest average household size (6.7 members per household) in the region. Musoma Rural had a comparatively moderate literacy rate among smallholder households and this was reflected by the concomitant relatively moderate level of school attendance in the region. However, it had the highest literacy rate for the heads of household in the region. It had a slightly lower utilized land area per household (1.84 ha) than the regional average of 1.9 ha and 75 percent of the allocated area is currently being utilized. The district had the second largest planted area and the third lowest area planted per crop growing household in the region (2.6 ha). The district was the second maize producer in the region with a planted area of about 19,326 ha. Sorghum and finger millet production were not important with a planted areas of only 5,751 and 1,742 hectares respectively. The district had the second largest area of cassava accounting for 36 percent of the cassava planted area in the region, however Irish potato production was not important. Sweet potato production in the district was relatively important accounting for 45 percent of the total area planted with sweet potatoes in the region. Beans production is important with a planted area of 4,173 ha which was the largest in the region accounting for 36 percent of the total area planted with beans in the region. Oilseed crops were important in Musoma Rural with 40 percent of the total groundnuts grown in the region. Vegetable production was moderate. Though small, the district had the largest planted area of tomatoes and cabbage in the region. Annual cash crop production was important in the district. It had the largest area planted with tobacco and the second largest area planted with cotton. Permanent crops were of little importance in Musoma Rural district (6.3% of the total permanent crop planted area in Mara region was found in the district). The most prominent permanent crop in the district pigeon was mango (531 ha) accounting for 50 percent of the total area planted with permanent crops in the district (1,056 ha), followed by banana (188 ha), oranges (113 ha), pawpaw (78 ha) and sugarcane (65 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing was done by hand, however it had the second largest area planted with “no land clearing” indicating the presence of a large area of bare land before cultivation. The district had the smallest area cultivated using oxen in the region. Musoma Rural district had a moderate area planted with improved seed in Mara region. The district also had the second largest proportion of planted area with fertilisers (farm yard manure, compost and inorganic fertiliser), most of this being farm yard manure. Compared to other districts in the region, Musoma Rural district had the highest proportion of planted area applied with fungicides. However, it has a small proportion of planted area with insecticides and largest proportion of planted area applied with herbicides. It had the second largest area with irrigation compared to other districts with 554 ha of irrigated land. The main sources of water for irrigation in the district were from wells and rivers using hand buckets. Buckets/watering cans were the main means of irrigation water application. MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 109 The most common method of crop storage in Musoma Rural was in sacks/open drums and in locally made traditional structures, however the percent of households storing crops in the district was the second lowest in the region. The district had moderate percent of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. Musoma Rural had the second lowest percentage of households processing crops, with 63 percent of the households processing by neighbours machines and 34 percent processing on farm by hand. The district was one of the districts with the lowest percent of households selling processed crops. The district had the second highest percentage of households receiving credit in the region, all of which were for the female headed households. All credits were provided by saving and credit societies. A moderate number of households received extension services in Musoma Rural district and almost all of this was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was moderately important in Musoma Rural district (with 497,262 planted trees) and most trees were gravellis with some calophlum inophylum spp. The highest proportion of households with erosion control and water harvesting facilities was found in Musoma Rural district and most of them are erosion control bunds and water harvesting bunds. The district had the second smallest number of cattle in the region, however it had the largest number of dairy cattle in the region. Although the district had the second largest number of goats in the region it had the third largest number of sheep. It had the largest number of chicken in the region but there were no pig rearing. The district had the largest number of improved chickens dominated by layers. It also had the largest number of ducks and rabbits in the region and a moderate number of donkeys. No turkeys were found in the district. The second largest number of households reporting tick problems was found in Musoma Rural district, however the district had the smallest number of households reporting tsetse problems in the region. The district had the second highest proportion of household de-worming livestock. The use of draft animals in the district was the largest in the region. There was no fish farming in the district. It is amongst the districts with the best access to feeder roads, primary schools primary markets and all weather roads, however it had one of the worst access to hospitals, tertiary markets and district capital. Musoma Rural district had the second highest percent of households with no toilet facilities. The most common source of energy for lighting was the wick lamp and a large proportion of households (98%) used firewood for cooking. The district had the third largest percent of households with grass/leaves roofing, however it had second highest percent of households with iron sheets roofing (33.5%). The main source of drinking water was the unprotected wells. Musoma Rural had the largest proportion of households having two meals per day and smallest proportion of households having three meals per day. The district had the lowest percent of households that ate meat three times during the week prior to enumeration, however it had the highest percent of the households that consumed fish six times during that particular week. The district had the highest percent of households that never experience food shortage problems. 4.2.4 Bunda Bunda district had the third largest number of households in the region, however it had the second smallest percentage of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 110 followed by crop and livestock production. Very few households were involved in livestock keeping only. No pastoralists were found in the district. The most important livelihood activity for smallholder households in Bunda district was annual crop farming, followed by tree/forest resources, off farm income, permanent crop farming, livestock keeping/herding, remittances and fishing/hunting and gathering. The district had the highest percent of households with off-farm activities however it had the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Bunda had the second lowest percent of female headed households (21%) and it had the second highest average age of the household head. The average household size of 6.7 members per household was one of the highest in the region. The literacy rate among smallholder households in Bunda was the lowest compared to other districts in the region and this is associated with this was the relatively higher proportion of household members who have never attended school. The district had a moderate literacy rate for the heads of households It had the second largest utilized land area per household (2.5 ha) and 77 percent of the allocated area was being utilized. The district had the second smallest total planted area in the region and the largest average area planted per household (3.4 ha) in the region. However, the district had the second smallest planted area per household in the long rainy season (2.1 ha) and largest area planted per household during short season (1.3 ha). Maize production with a planted area of 15,668 ha was moderate, however the planted area per household was the largest in the region. Finger millet production with a planted area of 1,433 hectares was not important in the region, however, the district had the third largest planted area of sorghum (10,188 ha). The district had the second smallest area planted with paddy in the region, however it had largest area planted with cocoyams (101 ha), a moderate planted area of cassava (16,599 ha) and the third largest planted area for sweet potatoes (2,633 ha). It also had the largest area planted with chickpeas and second largest planted area with beans (2,974 ha). Oilseed crops were of moderate importance in Bunda with the second largest planted area of groundnuts (361 ha) as well as second largest planted area for simsim in the region. Vegetable production was not important in the district, however tomatoes, onions, cabbages and amaranths were produced in very small quantities. Bunda district was important for cotton production accounting for 55 percent of the total area planted with cotton in the region. Compared to other districts in the region, Bunda had the third largest area planted with permanent crops which were dominated by pawpaw (747 ha), mango (348 ha), malay apple (92 ha) and oranges (60 ha). Other permanent crops were either not grown or were grown in small quantities. Most land clearing was done by hand slashing, however it had the largest area planted with “no land clearing” indicating the presence of a large area of bare land before cultivation. Most land preparation was done by oxen, followed by hand cultivation. Compared to other districts, Bunda district had the smallest land prepared by tractor. Bunda had the highest proportion of area planted with improved seed in Mara region. The use of fertilizer was moderate compared to other districts and most of it was farm yard manure and compost. It had a relatively small area applied with inorganic fertilizers. Compared to other districts in the region, Bunda district had the smallest percentage of the planted area in the district with fungicides application and the second smallest area of herbicide use. The district had the largest MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 111 percent of area planted with insecticide use. It had the third largest area with irrigation with a planted area of 181 ha under irrigation. The sources of water for irrigation were the lake, rivers and wells using hand buckets. Buckets/watering cans were the main means of irrigation water application in the district, followed by flood. The most common method of crop storage in Bunda district was in sacks/open drums, however the proportion of households storing crops in the district was the second highest when compared to other districts in Mara region. The district had the second lowest proportion of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. Bunda had the second highest percent of households processing crops and was mostly done by neighbours machines. The district had the highest percent of households selling processed crops to large scale farms. There was no access to agricultural credit in the district. The district had the highest proportion of households receiving extension services in the region and mostly was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not important in Bunda (with 95,956 trees) and most trees were azadrachta spp with some acacia spp. A small number of households had erosion control and water harvesting structures in Bunda district, most of which were erosion control bunds and water harvesting bunds. The district had the second largest number of cattle in the region comprised of indigenous breeds only. While goat population was moderate, sheep population was the second smallest in the region. There was no pig rearing in the district, however it had the second smallest number of chicken in the region, dominated by indigenous breeds. It had a considerable number of ducks, a small numbers of rabbits and the second largest number of donkeys. It had the second lowest proportion of households reporting ticks problems and third largest proportion of households reporting tsetse fly problems in the region. It had the second largest number of households de-worming livestock compared to other districts. Use of draft animals in the district was moderate and fish farming was not practiced. It was amongst the districts with the best access to feeder roads and secondary markets, however it had one of the worst access to secondary schools. Bunda district had the second lowest percentage of households with no toilet facilities. It had the lowest proportion of households with landline phones and vehicles; however it had the largest proportion of households with bicycles. It had the largest proportion of households using hurricane lamps and pressure lamps; however it was the only district in the region with households using cow dung as source of energy for cooking. The main source of energy for lighting was the wick lamp and the largest percent of households used firewood for cooking. The district had the second highest percent of households with grass/leaves roofs and 33 percent of households in the district had iron sheet roofing. The main sources of drinking water were the unprotected wells and surface water (lake/river/dam/stream). It had the second smallest percentage of households having three meals per day. The district had the highest percentage of households that did not eat meat and moderate to low percentage of households that did not eat fish during the week prior to enumeration. The district had the highest proportion of households that always face food problems. 4.2.5 Musoma Urban Musoma Urban district had the smallest number of households as well as the smallest proportion of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by those involved in MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 112 both crop and livestock production. Very few households were involved in livestock keeping only. No pastoralists were found in the district. The most important livelihood activity for smallholder households in Musoma Urban district was annual crop farming, followed by off farm income, permanent crop farming and tree/forest resources. However, the district had the second lowest proportion of households with no off-farm activities and the highest percent of households with more than one member with off-farm income compared to other districts in the region. Musoma Urban had the highest percentage of female headed households in the region (28%) and it had the highest average age for the household head. Its average household size of 6.4 members per household was the third largest in the region. Musoma Urban had the highest literacy for smallholder households members and this was reflected in the relatively high level of those attending school in the region. The literacy rate for the heads of household was the second highest in the region. It had the lowest utilized land area per household (0.8 ha) in the region and 84 percent of the available land is currently being utilised. Compared to other districts in the region, the total planted area was the smallest, however it had the second largest planted area per household during long rainy season (3.1 ha) and the smallest planted area per household during the short rainy season (0.3 ha). The district had the smallest area planted with maize and smallest area planted per maize growing household in the region. The district had the lowest planted area of paddy (7 ha) and sorghum (1 ha). Finger millet was not grown in the district. Cassava and sweet potato production were small accounting for only 0.5 and 0.4 percent of the cassava and sweet potato planted area in the region respectively. The production of beans in Musoma Urban was comparatively small (6 ha) and the area planted with bambara nuts was also very small (4 ha). Oilseed crops were not important in Musoma Urban, with the smallest area planted with groundnuts in the region. The district had the smallest area planted with fruits and vegetables in the region which were dominated by tomatoes (11 ha). Compared to other districts in the region, Musoma Urban had a small planted area with permanent crops which were dominated by mango (317 ha). Small quantities of pawpaw, banana and avocado were also grown. Other permanent crops were either not grown or were grown in very small quantities. The only practiced land clearing method in the district was by hand slashing and land preparation method was also done by hand. Musoma Urban had the smallest proportion of its planted area applied with fertilizers (compost, farm yard manure and inorganic manure), however most of this was farm yard manure. It had the second smallest proportion of area planted with improved seeds, however the district had the second lowest level of insecticide use and moderate level herbicide use. However, the use of fungicides was the second highest in the region. It had the smallest irrigated area (12 ha). The main source of water for irrigation was from wells using hand buckets. Buckets/watering cans were the only available means of irrigation water application. The most common method of crop storage was in sacks/open drums. The proportion of households storing crops in the district was the lowest in the region. The district had the smallest proportion of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. The smallest percent of households MARA PROFILES _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 113 processing crops in Mara region was found in Musoma Urban district and most of the the processing was done on farm by hand, followed by neighbours’ machines. Virtually no processing was done on farm by machine, however the district had the highest proportion of households processing by trader. The district had a small number of households selling processed crops mostly to neighbours and local markets/trade stores. There was no access to agricultural credit in the district. A comparatively low number of households received extension services in Musoma Urban district and a large percentage of this was from the government. The quality of extension services was rated between “very good” and “good” by the majority of the households. Tree farming was relatively unimportant in Musoma Urban (with 3,958 planted trees) and most of the trees were gravellis spp. The district had a relatively small number of households with erosion control and water harvesting structures mostly erosion control bunds and water harvesting bunds. The district had the second smallest number of cattle in the region and these were dominated by indigenous breeds. There was no pig husbandry in Musoma Urban district. It had the smallest number of goat, sheep and chicken populations compared to other districts in the region with a small broilers population. Small numbers of ducks were also found in the district. Whilst a small number of households reported tick related problems in the district, there were no households reporting tsetse related problems, however the district had the smallest proportion of households de-worming livestock. Use of draft animals in the district was not reported and no fish farming was practiced. It was among the districts with the best access to primary schools, all weather roads, secondary schools, hospitals, regional capital, tertiary markets, district capital, feeder roads, health clinics and tarmac roads; however it had one of the worst accesses to secondary markets. Musoma Urban district had the lowest percent of households with no toilet facilities and it had the highest proportion of households owning radios, irons, landline phones, mobile phones, vehicles and televisions/videos. The main source of energy for lighting was the wick lamp. Most households used firewood for cooking, however the district had the highest percent of households in the region that used electricity for cooking. It was the district with the lowest percent of households with grassy/leaves roofing, and 73 percent of households having iron sheet roofing. The most common sources of drinking water were surface water (lake/river/dam/stream) and piped water. It had the least percentage of households having one meal per day compared to other districts, however most households normally had 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration, however it had the lowest percent of households that did not eat fish during the respective period. Most households never had problems with food satisfaction. APPENDIX II 114 4. APPENDICES Appendix I Tabulation List.............................................................................................................. 115 Appendix II Tables........................................................................................................................... 128 Appendix III Questionnaires .............................................................................................................. 268 APPENDIX II 115 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD………………………………………………………………………………… 128 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year ...................129 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year.....................129 NUMBER OF AGRICULTURE HOUSEHOLDS ......................................................................................................................130 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year........................................................................................................131 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District........................................................................................................................................131 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.................................................................................................132 3.1a First Most Importance .......................................................................................................................................................133 3.1b Second Most Importance...................................................................................................................................................133 3.1c Third Most Importance......................................................................................................................................................133 3.1d Fourth Most Importance....................................................................................................................................................133 3.1e Fifth Most Importance.......................................................................................................................................................133 3.1f Sixth Most Importance ......................................................................................................................................................134 3.1g Seventh Most Importance..................................................................................................................................................134 HOUSEHOLDS DEMOGRAPHS.................................................................................................................................................136 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) .............................................................................................................................................................................137 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (Column %) ......................................................................................................................................................................137 3.4 Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year..........................138 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year .....................................................................138 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year................................................................................................................................................138 3.7 Number of Agricultural Household Members by Main Activity and District .................................................................138 cont… Number of Agricultural Household Members by Main Activity and District .....................................................139 cont… Number of Agricultural Household Members by Main Activity and District .....................................................139 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year.................................................................................................................................................139 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................140 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................140 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................140 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................140 APPENDIX II 116 3.14 Time Series of Male and Female Headed Households.....................................................................................................141 3.15 Literacy Rate of Heads of Households by Sex and District .............................................................................................141 3.16 Number of Agricultural Households by Number of Household Members Involved in Off Farm Income Generating Activities and District, 2002/03 Agricultural Year........................................................................................141 LAND ACCESS/OWNERSHIP.....................................................................................................................................................142 4.1 Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year...........................................................................................................................................143 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year..............................143 LAND USE .......................................................................................................................................................................................144 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year...............................................................................................................................................................145 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year................................................145 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year............................................................................................................................146 5.4 Number of Agricultural Households by whether they consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year....................................................................................146 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year........................................................................146 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION SHORT & LONG RAINY SEASONS...............................148 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District...........................................149 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District. .....................................................149 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Mara Region ..............................................................................................................................................................150 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Short and Long Rainy Seasons, Mara Region................................................................................151 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Mara ......................................................................................................................152 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Short and Long Rainy , Mara.................................................................................152 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Short and Long Rainy Season, 2002/03 Agriculture Year ..............................................................152 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season.. ................................................................................153 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season...................................................................................153 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season.......................................................................................153 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season.......................................................................................153 ANNUAL CROP & VEGETABLES PRODUCTION SHORT RAINY SEASON..................................................................154 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Mara Region.........................................................................................................155 7.1b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and APPENDIX II 117 District during 2002/03 Agriculture Year - SHORT RAINY SEASON, Mara Region ..................................................155 7.1c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Short Rainy Season, 2002/03 Agriculture Year, Mara Region................................................................155 7.1d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short Rainy Season. ....................................................................................156 7.1e Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Short Rainy Season.. ...................................................................................156 7.1f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Short Rainy Season.. ...................................................................................156 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Short Rainy Season ...............................................................................................156 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON....................................................................158 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District - LONG RAINY SEASON, Mara Region. ..........................................................................................................159 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Mara Region..................................................................159 7.2c Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year...............................................................................159 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long Rainy Season.........................................................................................................160 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long Rainy Season.........................................................................................................160 7.2.f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON ..............................................................................................161 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON...................................................................................................161 7.2h Planted Area and Number of Crop Growing Households During Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year ..................................................................................................162 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year...............................................................................................................163 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year ............................................................................................................................163 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................…163 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush Millet Harvested (tons) by Season and District;2002/03 Agricultural Year..........................................................................................................163 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year..........................................................................................................164 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................164 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year..........................................................................................................164 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ...................................................................................................................................164 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................165 APPENDIX II 118 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................165 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung Beans Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................165 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year ...................................................................................................................................165 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................166 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick Peas Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................166 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................166 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................166 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................167 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................167 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya Beans Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................167 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year...................................................................................................................167 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Garlic Harvested (tons) by Season and District;2002/03 Agricultural Year ...................................................................................................................................168 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................168 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................168 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year ...................................................................................................................................168 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................169 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................169 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................169 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ...................................................................................................................................160 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................170 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Water mellon Harvested (tons) by Season and District;2002/03 Agricultural Year ...........................................................................................................................................170 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................170 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobbaco Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................170 APPENDIX II 119 PERMANENT CROPS...........................................................................................................................................................................172 7.3.1 Production of Permanent Crops by Crop Type and District - Mara.........................................................................................173 7.3.2 Area Planted by Crop Type - Mara Region ..............................................................................................................................175 7.3.3 Area Planted with Banana by District.......................................................................................................................................175 7.3.4 Area planted with Coffee by District ........................................................................................................................................175 7.3.5 Area planted with Orange by District .......................................................................................................................................176 7.3.6 Area Planted with Mango by District........................................................................................................................................176 7.3.7 Planted Area with Fertilizer by Fertilizer Type and Crop ........................................................................................................176 cont… Planted Area with Fertilizer by Fertilizer Type and Crop ............................................................................................177 AGROPROCESSING .............................................................................................................................................................................178 8.1.1a Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year..........179 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year ..........................179 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Mara Region..............................................................................................................................................179 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Mara Region ...................................................................................180 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Mara Region...............................................................180 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Mara Region ..................................................................................................................................180 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Mara Region ..................................................................................................................................180 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Mara Region ..................................................................................................................................181 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Mara Region ..................................................................................................................................181 MARKETING..........................................................................................................................................................................................182 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Mara Region...............................................................................................................................................................183 10.2 Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Mara Region.................................................................................................................................183 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Mara Region .................................................................................................................................183 IRRIGATION/EROSION CONTROL.................................................................................................................................................184 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District.....................185 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year................................................185 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year....................................................................................................................................................185 11.4 Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year.........................................................................................................................................................185 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year...................................................................................................................................................186 APPENDIX II 120 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District...................................186 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year................186 ACCESS TO FARM INPUTS................................................................................................................................................................188 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year..........................189 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year ................189 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year...............189 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year ...........190 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year..............................190 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year ......................190 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year.................191 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year..................191 cont….. Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year.........................................................................................................................................................191 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ................192 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year...........192 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year................................193 12.1.12 Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year.......................194 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ..........................................................................................................................................194 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ..........................................................................................................................................195 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ..........................................................................................................................................196 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................................................196 12.1.17 Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year ..........................................................................................................................................197 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ..........................................................................................................................................197 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ..........................................................................................................................................198 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year…………………………………………………………………..………………………198 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year ..........................................................................................................................................199 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ..........................................................................................................................................199 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ..........................................................................................................................................199 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year...............200 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year................200 APPENDIX II 121 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ..............200 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year.........201 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year..............................201 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year.....................201 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................201 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................202 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................202 12.2.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................202 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................202 12.1.35 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year.........................................................................................................................................................203 AGRICULTURE CREDIT.....................................................................................................................................................................204 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year....................................................................................................................................................205 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year......................205 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year....................................................................................................................................................205 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year .......................205 TREE FARMING AND AGROFORESTRY.......................................................................................................................................206 14.1 Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mara Region...............................207 cont… ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mara Region ............................................................................................................................207 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Mara Region……………………………………………………………207 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Mara Region...................207 CROP EXTENSION ...............................................................................................................................................................................208 15.1 Number of Agriculture Households Receiving Extension Messages by District During he 2002/03 Agriculture Year, Mara Region..............................................................................................................................209 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Mara Region ...........................................................................................................................209 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ............................................................................................................................209 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ...........................................................................210 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region .........................................210 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ...........................................................................210 APPENDIX II 122 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ...........................................................................211 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ...........................................................................211 15.9 EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ....................................211 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ....................................212 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region ....................................212 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region .........................................212 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region..........................................................213 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region..........................................................213 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region..........................................................213 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region..........................................................214 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region..........................................................214 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Mara Region ...............................................................214 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Mara Region ...............................................................215 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Mara Region ...............................................................215 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Mara Region ...............................................................215 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Mara Region ...............................................................216 ANIMAL CONTRIBUTION TO CROP PRODUCTION..................................................................................................................218 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Mara Region ....................................................................................................................................219 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mara Region ....................................................................................................................................219 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Mara...............219 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Mara Region.................220 CATTLE PRODUCTION ......................................................................................................................................................................222 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year,Mara Region ....................................223 18.2 Number of Cattle By Type and District as of 1st October, 2003 .............................................................................................223 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003.............................................................................................................................................223 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003................................................................................224 APPENDIX II 123 18.5 Number of Indigenous Cattle By Category and District as on 1st October, 2003 ...................................................................224 18.6 Number of Improved Beef Cattle By Category and District as on 1st October, 2003.............................................................224 18.7 Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 ...........................................................225 18.8 Number of Cattle By Category and District as on 1st October, 2003 ......................................................................................225 GOATS PRODUCTION.........................................................................................................................................................................226 19.1 Total Number of Goats by Type and District as on 1st October, 2003....................................................................................227 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ............................................................................227 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District.................................................228 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003............................................................228 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003.........................................................228 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003..................................................................229 19.7 Total Number of Goats by Category and District on 1st October, 2003.................................................................................229 SHEEP PRODUCTION..........................................................................................................................................................................230 20.1 Total Number of Sheep By Breed and on 1st October 2003 ....................................................................................................231 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 ..........................................................231 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03..............................................................................231 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 ....................................................................231 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Mara Region .............................................232 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 ...........................................................232 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ...........................................................232 20.8 Total Number of Sheep by sheepType and District on 1st October 2003................................................................................232 PIGS PRODUCTION..............................................................................................................................................................................234 21.1 Number of Households and Pigs by Herd Size on 1st October 2003.......................................................................................235 21.2 Number of Households and Pigs by District on 1st October 2003...........................................................................................235 21.3 Number of Pigs by Type and District on 1st October, 2003 ....................................................................................................235 LIVESTOCK PESTS AND PARASITE CONTROL .........................................................................................................................236 22.1 Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year..................237 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year...................................................................................................................................................237 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. ......................................................................................................................................237 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year...................................................................................................................................................237 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District............................................................................................................................238 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year......................................................................................................................................238 APPENDIX II 124 OTHER LIVESTOCK............................................................................................................................................................................240 23a Total Number of Other Livestock by Type on 1st October 2003.............................................................................................241 23b Number of Chicken by Category of Chicken and District on 1st October 2003......................................................................241 23c Head Number of Other Livestock by Type of Livestock and District .....................................................................................241 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003......................................................241 23e Livestock/Poultry Population Trend .........................................................................................................................................241 FISH FARMING......................................................................................................................................................................................242 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year..............................243 28.2 Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year..................243 28.3 Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year….................................................................................................................................…………....243 28.4 Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year…………………………………………………………………………………..………………..243 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year ...............................................................243 LIVESTOCK EXTENSION...................................................................................................................................................................244 29.1a Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year......................245 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year...................................................................................................................................................245 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year .................................................................................................................246 29.3 Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year.........................................................................................................................................................246 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year.........................................................................................................................................................246 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year.........................................................................................................................................................246 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year.........................................................................................................................................................247 29.7 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year..................................................................................................................247 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year..................................................................................................................248 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year..................................................................................................................248 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.........................................................................................................................................................249 29.1l Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year .......................................................................................................................249 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year.................250 ACCESS TO INFRASRUCTURE AND OTHER SERVICES..........................................................................................................252 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts.......................................................253 33.01b Number of Households By Distance to Secondary School by District for 2002/03 agriculture year .....................................254 APPENDIX II 125 33.01c Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year .....................................254 33.01d Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year...............................................254 33.01e Number of Households By Distance to Hospital by District for 2002/03 agriculture year.....................................................255 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year.............................................255 33.01g Number of Households by distance to Primary School for 2002/03 agriculture year .............................................................255 33.01h Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year ........................................256 33.01i Number of Households by Distance to District Capital by District for 2002/03 agriculture year..........................................256 33.01j Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year ............................................256 33.01k Number of Households by Distance to Primary Market by District for 2002/03 agricultural year.........................................257 33.01l Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year.........................................257 33.01m Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year.....................................257 TYPE OF SERVICE ...............................................................................................................................................................................258 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year.........................................................................................................................................................258 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year .............258 33.19c Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year.........................................................................................................................................................258 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year.........................................................................................................................................................259 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year.........................................................................................................................................................259 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year.........................................................................................................................................................259 HOUSEHOLD FACILITIES .................................................................................................................................................................260 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year ...........................261 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year.........................................................................................................................................................261 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ..................261 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year.........................................................................................................................................................262 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year.........................................................................................................................................................262 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.........................................................................................................................263 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.........................................................................................................................263 34.8 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year..........................................................................................................264 34.9 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year..........................................................................................................264 34.10 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District ...................265 APPENDIX II 126 34.11 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District.........265 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ..........266 34.13 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District ........................................................................................................................................................266 34.14 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year...........................267 34.15 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year.............................267 APPENDIX II 127 APPENDIX II: CROP TABLES Type of Agriculture Household.................................................................................................................................................................... 128 Number of Agriculture Households .............................................................................................................................................................. 130 Rank of Importance of Livelihood Activities ............................................................................................................................................... 132 Households Demography .............................................................................................................................................................................. 136 Land Access/Ownership ............................................................................................................................................................................... 142 Land Use ............................................................................................................................................................................... 144 Total Annual Crop and Vegetable Production – LONG and SHORT Rainy Seasons................................................................................. 148 Annual Crop and Vegetable Production – SHORT Rainy Season ............................................................................................................... 154 Annual Crop and Vegetable Production LONG Rainy Seasons................................................................................................................... 158 Permanent Crop Production........................................................................................................................................................................... 172 Agro-processing ............................................................................................................................................................................... 178 Marketing ............................................................................................................................................................................... 182 Irrigation/Erosion Control ............................................................................................................................................................................. 184 Access to Farm Inputs ............................................................................................................................................................................... 188 Agriculture Credit ............................................................................................................................................................................... 204 Tree Farming and Agro-forestry ................................................................................................................................................................... 206 Crop Extension ............................................................................................................................................................................... 208 Animal Contribution to Crop Production...................................................................................................................................................... 218 Cattle Production ............................................................................................................................................................................... 222 Goat Production ............................................................................................................................................................................... 226 Sheep Production ............................................................................................................................................................................... 230 Pig Production ............................................................................................................................................................................... 234 Livestock Pests and Parasite Control ............................................................................................................................................................ 236 Other Livestock ............................................................................................................................................................................... 240 Fishing Farming ............................................................................................................................................................................... 242 Livestock Extension ............................................................................................................................................................................... 244 Access to Infrastructure and other services................................................................................................................................................... 252 Household Facilities ............................................................................................................................................................................... 280 Appendix II 128 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census-2003 Appendix II 129 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Tarime 79,170 82 1628.40773 2.0 80,798 84 15,810 16 96,608 Serengeti 27,864 89 2769.75176 9.0 30,634 98 579 2 31,213 Musoma Rural 49,995 92 122.526415 0.2 50,118 92 4,095 8 54,213 Bunda 30,721 72 412.872001 1.3 31,133 73 11,472 27 42,605 Musoma Urban 453 2 2531.44728 84.8 2,985 14 18,976 86 21,961 Total 188,203 76 7465.00519 3.8 195,668 79 50,932 21 246,600 Number Percent Number Percent Number Percent Number Percent Tarime 38,817 38 1,076 45 39,277 48 79,170 42 79,170 78,094 40,352 Serengeti 15,064 15 276 11 12,524 15 27,864 15 27,864 27,588 12,800 Musoma Rural 30,527 30 973 40 18,496 22 49,995 27 49,995 49,023 19,468 Bunda 18,695 18 75 3 11,951 15 30,721 16 30,721 30,646 12,025 Musoma Urban 275 0 13 1 166 0 453 0 453 440 179 Total 103,379 100 2,412 100 82,412 100 188,203 100 188,203 185,791 84,824 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Crops & Livestock Total District Type of Agriculture Household Total Number of Agricultural Households 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year District Agriculture, Non Agriculture and Urban Households Crops Only Livestock Only Total Number of Households Growing Crops Total Number of Agricultural Households Rearing Livestock Tanzania Agriculture Sample Census-2003 Appendix II 130 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census-2003 Appendix II 131 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Tarime 313,791 59,514 5.3 72,878 19,655 3.7 386,670 79,170 4.9 Serengeti 133,881 21,137 6.3 36,647 6,727 5.4 170,529 27,864 6.1 Musoma Rural 279,742 39,870 7.0 53,475 10,126 5.3 333,217 49,995 6.7 Bunda 168,997 24,339 6.9 35,414 6,382 5.5 204,411 30,721 6.7 Musoma Urban 2,193 327 6.7 723 126 5.7 2,916 453 6.4 Total 898,604 145,187 6.2 199,138 43,016 4.6 1,097,742 188,203 5.8 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 1 3 4 5 6 7 2 Serengeti 1 3 5 4 6 7 2 Musoma Rural 1 4 5 3 7 6 2 Bunda 1 4 5 3 7 6 2 Musoma Urban 1 3 6 2 7 5 4 Total 1 3 5 4 6 7 2 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District District livelihood activity District Male Female Total Tanzania Agriculture Sample Census - 2003 Dodoma Appendix II 132 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census-2003 Appendix II 133 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 37,795 7,099 4,460 16,967 3,978 6,333 1,334 Serengeti 16,874 3,102 1,859 4,431 345 0 903 Musoma Rural 13,240 14,503 1,173 13,224 2,148 5,154 350 Bunda 13,973 2,284 2,848 6,571 1,046 2,966 436 Musoma Urban 63 59 47 175 12 92 7 Total 81,945 27,047 10,387 41,367 7,528 14,546 3,031 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 23,028 28,417 12,982 7,690 1,337 935 5,580 Serengeti 7,460 10,162 3,971 2,679 959 0 2,571 Musoma Rural 15,215 17,979 5,530 5,484 1,486 2,137 1,886 Bunda 10,812 11,541 3,410 2,692 434 232 2,119 Musoma Urban 156 192 26 13 12 48 0 Total 56,671 68,290 25,919 18,558 4,227 3,353 12,157 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 8,162 16,679 16,596 8,388 3,187 650 22,797 Serengeti 2,703 5,768 5,098 3,631 1,091 0 7,983 Musoma Rural 12,686 6,369 5,810 6,311 1,943 1,508 13,201 Bunda 4,600 4,530 3,678 5,464 712 398 10,263 Musoma Urban 169 43 50 59 7 12 89 Total 28,320 33,390 31,231 23,854 6,940 2,569 54,333 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 2,850 8,593 8,552 5,136 3,199 536 27,325 Serengeti 209 1,247 2,277 2,407 681 70 10,630 Musoma Rural 2,867 4,114 6,921 3,505 2,343 460 19,884 Bunda 570 1,223 2,621 2,411 1,088 234 12,813 Musoma Urban 23 48 61 49 12 24 140 Total 6,520 15,225 20,431 13,508 7,322 1,323 70,792 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 649 4,050 2,929 2,780 1,582 135 11,907 Serengeti 206 140 551 901 276 70 3,084 Musoma Rural 1,270 1,246 4,766 1,717 1,824 347 8,068 Bunda 79 613 1,222 1,899 677 76 4,493 Musoma Urban 12 13 12 61 7 0 109 Total 2,216 6,062 9,479 7,357 4,365 627 27,660 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census-2003 Appendix II 134 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 0 1,676 1,202 542 133 0 1,560 Serengeti 0 0 0 67 70 0 209 Musoma Rural 69 0 1,057 902 581 0 806 Bunda 0 80 459 307 0 76 307 Musoma Urban 0 0 24 12 0 0 12 Total 69 1,756 2,742 1,829 783 76 2,895 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tarime 0 381 0 267 129 135 0 Serengeti 0 136 0 0 0 0 0 Musoma Rural 0 0 117 0 0 0 117 Bunda 80 158 0 0 0 0 0 Musoma Urban 0 0 0 0 0 0 0 Total 80 676 117 267 129 135 117 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census-2003 135 Appendix II 136 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census-2003 Appendix II 137 Number % Number % Number % Less than 4 87,572 51 82,857 49 170,429 100 05 - 09 87,006 51 82,180 49 169,187 100 10 - 14 80,907 51 79,168 49 160,075 100 15 - 19 67,562 55 56,254 45 123,817 100 20 - 24 44,635 48 49,168 52 93,803 100 25 - 29 33,988 42 46,097 58 80,085 100 30 - 34 28,467 48 30,935 52 59,403 100 35 - 39 22,217 46 26,056 54 48,273 100 40 - 44 21,808 49 22,947 51 44,755 100 45 - 49 18,154 53 16,278 47 34,432 100 50 - 54 13,305 48 14,630 52 27,935 100 55 - 59 9,337 44 11,696 56 21,034 100 60 - 64 9,204 52 8,627 48 17,830 100 65 - 69 10,151 56 7,817 44 17,968 100 70 - 74 6,065 48 6,546 52 12,611 100 75 - 79 3,870 51 3,710 49 7,581 100 80 - 84 1,740 39 2,724 61 4,464 100 Above 85 2,325 57 1,736 43 4,060 100 Total 548,314 50 549,427 50 1,097,742 100 Number % Number % Number % Less than 4 87,572 16 82,857 15 170,429 16 05 - 09 87,006 16 82,180 15 169,187 15 10 - 14 80,907 15 79,168 14 160,075 15 15 - 19 67,562 12 56,254 10 123,817 11 20 - 24 44,635 8 49,168 9 93,803 9 25 - 29 33,988 6 46,097 8 80,085 7 30 - 34 28,467 5 30,935 6 59,403 5 35 - 39 22,217 4 26,056 5 48,273 4 40 - 44 21,808 4 22,947 4 44,755 4 45 - 49 18,154 3 16,278 3 34,432 3 50 - 54 13,305 2 14,630 3 27,935 3 55 - 59 9,337 2 11,696 2 21,034 2 60 - 64 9,204 2 8,627 2 17,830 2 65 - 69 10,151 2 7,817 1 17,968 2 70 - 74 6,065 1 6,546 1 12,611 1 75 - 79 3,870 1 3,710 1 7,581 1 80 - 84 1,740 0 2,724 0 4,464 0 Above 85 2,325 0 1,736 0 4,060 0 Total 548,314 100 549,427 100 1,097,742 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Age Group Sex Male Female Total Tanzania Agriculture Sample Census-2003 Appendix II 138 Number % Number % Number % Tarime 195,948 51 190,721 49 386,670 100 Serengeti 85,070 50 85,459 50 170,529 100 Musoma Rural 163,225 49 169,992 51 333,217 100 Bunda 102,638 50 101,772 50 204,411 100 Musoma Urban 1,433 49 1,483 51 2,916 100 Total 548,314 50 549,427 50 1,097,742 100 Number % Number % Number % Number % Number % Tarime 48,077 60.7 8,639 10.9 407 0.5 22,046 27.8 79,170 100 Serengeti 18,014 64.7 1,862 6.7 67 0.2 7,922 28.4 27,864 100 Musoma Rural 33,064 66.1 5,335 10.7 0 0.0 11,596 23.2 49,995 100 Bunda 19,459 63.3 2,997 9.8 0 0.0 8,265 26.9 30,721 100 Musoma Urban 223 49.2 115 25.3 0 0.0 115 25.4 453 100 Total 118,838 63.1 18,947 10.1 474 0.3 49,944 26.5 188,203 100 Number % Number % Number % Number % Tarime 113,608 33 150,752 44 76,943 23 341,303 100 Serengeti 42,617 31 57,111 41 39,616 28 139,344 100 Musoma Rural 86,233 31 129,030 47 59,671 22 274,934 100 Bunda 57,839 34 69,237 41 42,165 25 169,240 100 Musoma Urban 777 31 1,201 48 514 21 2,492 100 Total 301,073 32 407,330 44 218,909 24 927,312 100 Number % Number % Number % Number % Number % Tarime 158,115 46 5,295 2 0 0 9,900 3 4,752 1 Serengeti 69,192 50 1,522 1 140 0 70 0 960 1 Musoma Rural 130,354 47 3,499 1 233 0 8,955 3 1,794 1 Bunda 80,267 47 2,260 1 80 0 3,453 2 825 0 Musoma Urban 760 30 72 3 0 0 182 7 53 2 Total 438,687 47 12,649 1 452 0 22,560 2 8,385 1 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Swahili & English Any Other Language Don't Read / Write 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Total Swahili 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year District Main Activity Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal Tanzania Agriculture Sample Census-2003 Appendix II 139 Number % Number % Number % Number % Number % Tarime 4,548 1 5,326 2 6,862 2 1,865 1 2,341 1 Serengeti 1,244 1 1,666 1 1,109 1 3,260 2 278 0 Musoma Rural 2,908 1 2,693 1 4,653 2 2,728 1 904 0 Bunda 912 1 230 0 613 0 1,829 1 1,041 1 Musoma Urban 92 4 45 2 89 4 0 0 12 0 Total 9,704 1 9,960 1 13,325 1 9,683 1 4,576 0 Number % Number % Number % Number % Number % Number % Tarime 398 0 3,433 1 108,738 32 24,848 7 4,882 1 341,303 100 Serengeti 278 0 679 0 41,033 29 13,020 9 4,893 4 139,344 100 Musoma Rural 609 0 1,311 0 82,361 30 27,708 10 4,223 2 274,934 100 Bunda 311 0 761 0 54,458 32 18,867 11 3,333 2 169,240 100 Musoma Urban 13 1 18 1 765 31 355 14 37 1 2,492 100 Total 1,609 0 6,201 1 287,356 31 84,798 9 17,367 2 927,312 100 Number % Number % Number % Number % Number % Tarime 142,942 42 22,359 7 98,655 29 77,347 23 341,303 100 Serengeti 68,432 49 4,839 3 38,779 28 27,294 20 139,344 100 Musoma Rural 119,103 43 26,954 10 65,224 24 63,652 23 274,934 100 Bunda 74,624 44 2,516 1 53,297 31 38,803 23 169,240 100 Musoma Urban 606 24 68 3 779 31 1,038 42 2,492 100 Total 405,707 44 56,737 6 256,734 28 208,134 22 927,312 100 cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Not Working & Available 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Other Total Tanzania Agriculture Sample Census-2003 Appendix II 140 Number % Number % Number % Number % Number % Tarime 399 0 810 1 1,207 1 2,531 2 10,186 7 Serengeti 551 1 136 0 818 1 818 1 4,267 7 Musoma Rural 817 1 1,466 1 3,755 3 2,363 2 12,491 10 Bunda 470 1 473 1 2,304 3 1,592 2 5,063 7 Musoma Urban 12 1 7 1 13 1 37 3 115 10 Total 2,250 1 2,891 1 8,097 2 7,340 2 32,122 8 Number % Number % Number % Number % Number % Tarime 110,250 73 2,466 2 664 0 260 0 666 0 Serengeti 45,116 79 344 1 481 1 0 0 272 0 Musoma Rural 93,948 73 1,812 1 221 0 116 0 341 0 Bunda 52,956 76 781 1 139 0 134 0 306 0 Musoma Urban 785 65 30 2 0 0 0 0 7 1 Total 303,055 74 5,431 1 1,505 0 510 0 1,592 0 Number % Number % Number % Number % Number % Tarime 2,541 2 535 0 6,910 5 670 0 271 0 Serengeti 481 1 70 0 1,291 2 0 0 0 0 Musoma Rural 974 1 312 0 2,893 2 198 0 231 0 Bunda 232 0 134 0 1,379 2 159 0 0 0 Musoma Urban 0 0 12 1 96 8 31 3 0 0 Total 4,228 1 1,063 0 12,569 3 1,058 0 502 0 Number % Number % Number % Tarime 0 0 2,690 2 150,752 100 Serengeti 0 0 482 1 57,111 100 Musoma Rural 0 0 321 0 129,030 100 Bunda 0 0 311 0 69,237 100 Musoma Urban 7 1 13 1 1,201 100 Total 7 0 3,817 1 407,330 100 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Under Standard One Standard One Standard Two Standard Three Standard Four cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Standard Seven Standard Eight Training After Primary Education Pre Form One Form One cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Form Two Form Three Form Four Form Six Training After Secondary Education District University & Other Tertiary Education Adult Education Total Tanzania Agriculture Sample Census-2003 Appendix II 141 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 210,881 135,180 138,250 148,765 148,981 145,187 Female Heads 43,259 34,646 45,301 48,677 42,537 43,016 Total 254,140 169,826 183,551 197,442 191,518 188,203 Male headed (percentage) 83 80 75 75 78 77 Female headed (percentage) 17 20 25 25 22 23 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Tarime 49,527 7,597 57,124 9,987 12,059 22,046 59,514 19,655 79,170 Serengeti 16,238 3,704 19,943 4,898 3,023 7,922 21,137 6,727 27,864 Musoma Rural 33,080 5,319 38,399 6,790 4,806 11,596 39,870 10,126 49,995 Bunda 20,111 2,345 22,456 4,227 4,037 8,265 24,339 6,382 30,721 Musoma Urban 279 59 338 49 67 115 327 126 453 Total 119,235 19,024 138,259 25,951 23,993 49,944 145,187 43,016 188,203 Number Percent Number Percent Number Percent Number Percent Tarime 27,130 60 11,650 26 6,227 14 45,007 100 Serengeti 10,601 78 1,995 15 971 7 13,567 100 Musoma Rural 20,062 66 7,064 23 3,444 11 30,571 100 Bunda 14,036 69 5,021 25 1,302 6 20,359 100 Musoma Urban 172 61 86 30 25 9 284 100 Total 72,002 66 25,816 24 11,969 11 109,788 100 3.14 Time Series of Male and Female Headed Households 3.15 Literacy Rate of Heads of Households by Sex and District Literacy District Know Don't know Total 3.16 Number of Agricultural Households by Number of Household Members Involved in Off Farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of Household Members Involved in Off-farm Income Generating Activities One Person Two Persons More than Two Persons Total Tanzania Agriculture Sample Census-2003 Appendix II 142 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census-2003 Appendix II 143 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 7,354 9 71,739 91 10,694 14 7,750 10 8,708 11 2,118 3 3,830 5 79,170 Serengeti 3,751 13 23,299 84 1,856 7 688 2 2,683 10 612 2 1,039 4 27,864 Musoma Rural 1,722 3 40,501 81 6,382 13 8,907 18 7,730 15 2,023 4 7,395 15 49,995 Bunda 3,038 10 27,170 88 2,643 9 2,976 10 4,954 16 80 0 216 1 30,721 Musoma Urban 97 21 193 43 70 15 187 41 49 11 0 0 25 5 453 Total 15,961 8 162,902 87 21,645 12 20,508 11 24,123 13 4,833 3 12,506 7 188,203 Area Leased/Certif icate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Tarime 8,312 129,541 8,759 5,964 4,482 1,476 2,699 161,234 Serengeti 7,981 85,015 2,696 774 1,895 916 358 99,634 Musoma Rural 6,902 88,328 9,669 7,169 4,918 1,130 8,163 126,279 Bunda 9,863 78,519 3,817 3,105 4,505 32 132 99,973 Musoma Urban 62 177 53 98 14 . 19 423 Total 33,120 381,581 24,993 17,110 15,814 3,554 11,370 487,543 % 7 78 5 4 3 1 2 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Land Access Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Total Number of Households 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census-2003 Appendix II 144 LAND USE Tanzania Agriculture Sample Census-2003 Appendix II 145 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Area of land Utilized by household Total Number of Households Tarime 60,430 12,904 57,173 4,517 6,157 4,984 5,570 2,403 10,738 2,749 3,151 29,385 200,162 79,170 Serengeti 26,762 4,952 16,280 755 1,738 961 2,399 1,503 4,836 480 5,465 13,528 79,660 27,864 Musoma Rural 33,031 14,898 31,394 1,740 13,932 1,349 4,658 626 12,983 1,827 2,417 25,931 144,785 49,995 Bunda 23,711 9,719 10,798 1,607 7,083 591 5,739 608 3,699 942 548 13,008 78,053 30,721 Musoma Urban 156 43 117 53 204 0 7 0 55 24 12 104 774 453 Total 144,089 42,515 115,763 8,672 29,114 7,885 18,372 5,139 32,312 6,022 11,594 81,956 503,434 188,203 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Tarime 50,950 10,297 35,774 3,271 3,390 6,311 4,654 2,281 3,458 4,320 2,169 34,358 161,234 Serengeti 40,721 5,177 14,431 532 1,326 3,276 3,245 1,953 1,091 821 4,993 22,069 99,634 Musoma Rural 27,177 10,915 27,523 924 15,422 2,498 3,644 301 2,915 1,090 3,279 30,591 126,279 Bunda 38,519 8,266 8,647 1,612 7,324 298 8,796 185 473 1,590 1,523 22,740 99,973 Musoma Urban 60 20 48 33 151 . 9 . 20 14 2 65 423 Total 157,427 34,674 86,423 6,373 27,613 12,382 20,348 4,720 7,956 7,836 11,967 109,823 487,543 District Land use area 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Districts Type of Land Use 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Appendix II 146 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Tarime 41,265 53 36,829 47 78,094 100 Tarime 27,992 36 50,102 64 78,094 100 Serengeti 11,320 41 16,268 59 27,588 100 Serengeti 14,392 52 13,196 48 27,588 100 Musoma Rural 19,359 39 29,664 61 49,023 100 Musoma Rural 17,850 36 31,173 64 49,023 100 Bunda 12,004 39 18,642 61 30,646 100 Bunda 12,200 40 18,446 60 30,646 100 Musoma Urban 325 74 116 26 440 100 Musoma Urban 139 32 301 68 440 100 Total 84,273 45 101,519 55 185,791 100 Total 72,573 39 113,218 61 185,791 100 Number Percent Number Percent Number Percent Tarime 15,953 20 62,141 80 78,094 100 Serengeti 6,977 25 20,612 75 27,588 100 Musoma Rural 12,224 25 36,799 75 49,023 100 Bunda 5,701 19 24,944 81 30,646 100 Musoma Urban 25 6 416 94 440 100 Total 40,879 22 144,912 78 185,791 100 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total Tanzania Agriculture Sample Census-2003 147 Appendix II 148 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION SHORT & LONG RAINY SEASONS Tanzania Agriculture Sample Census-2003 Appendix II 149 Number of household Planted area (hectare) Number of household Planted Area (hectare) Tarime 47725 35,307 53,074 80,024 115,331 31 Serengeti 20,452 22,706 24,548 42,459 65,165 35 Musoma Rural 31,894 25,769 33,698 62,255 88,024 29 Bunda 27,140 36,412 13,266 27,860 64,272 57 Musoma Urban 296 75 212 657 732 10 Total 127,507 120,270 124,798 213,255 333,525 36 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Tarime 47725 30,369 53,074 25,020 78,094 Serengeti 20452 7,136 24,548 3,040 27,588 Musoma Rural 31894 17,128 33,698 15,324 49,023 Bunda 27140 3,506 13,266 17,380 30,646 Musoma Urban 296 144 212 229 440 Total 127507 58,284 124,798 60,993 185,791 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area planted in Short Rainy Season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Short Rainy Season Long Rainy Season District Short Rainy Season Long Rainy Season Total Number of Crop Growing Households Tanzania Agriculture Sample Census-2003 Appendix II 150 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 48,177 55,996 1,162 43,628 54,666 1,253 91,804 110,662 1,205 Paddy 2,270 2,366 1,043 2,603 3,905 1,500 4,873 6,271 1,287 Sorghum 29,922 28,842 964 25,118 25,664 1,022 55,040 54,506 990 Finger Millet 4,245 3,776 889 5,712 4,807 842 9,957 8,583 862 Bulrush Millet 0 0 0 27 0 0 27 0 0 CEREALS 84,614 90,980 77,087 89,042 161,701 180,021 Cassava 307 552 1,796 115,432 115,195 998 115,739 115,747 1,000 Sweet Potatoes 7,714 20,906 2,710 8,907 22,328 2,507 16,621 43,234 2,601 Irish Potatoes 299 1,372 4,584 244 409 1,679 543 1,781 3,281 Yams 23 14 603 83 263 3,190 106 277 2,623 Cocoyam 94 2 21 14 70 4,883 108 71 661 ROOTS & TUBERS 8,438 22,846 124,679 138,265 133,117 161,111 Mung Beans 0 0 0 108 240 2,223 108 240 2,223 Beans 6,383 4,093 641 5,343 3,519 659 11,726 7,612 649 Cowpeas 97 22 228 181 258 1,425 278 280 1,008 Chich Peas 186 123 661 1,884 950 504 2,070 1,073 518 Bambaranuts 134 57 430 122 33 266 256 90 351 PULSES 6,799 4,295 7,639 4,999 14,438 9,295 Sunflower 21 7 346 0 0 0 21 7 346 Simsim 73 21 293 103 27 262 176 48 275 Groundnuts 761 797 1,047 577 555 964 1,337 1,352 1,011 Soya Beans 22 27 1,235 16 24 1,482 38 51 1,341 OIL SEEDS & OIL NUTS 877 853 695 607 1,572 1,459 Bitter Aubergine 16 16 988 0 0 0 16 16 988 Garlic 27 0 0 0 0 0 27 0 0 Onions 95 362 3,829 152 544 3,578 247 907 3,674 Cabbage 123 333 2,702 257 1,350 5,249 381 1,683 4,423 Tomatoes 479 1,603 3,346 603 2,198 3,647 1,082 3,801 3,514 Spinnach 53 48 889 58 49 853 111 97 871 Amaranths 57 51 896 59 228 3,857 116 279 2,404 Pumpkins 12 1 59 12 2 158 24 3 109 Cucumber 24 24 1,039 0 0 0 24 24 1,039 Water Mellon 29 37 1,263 0 0 0 29 37 1,263 Ginger 0 0 0 54 135 2,470 54 135 2,470 FRUITS & VEGETABLES 915 2,475 1,195 4,506 2,110 6,981 Cotton 18,443 12,680 687 1,899 1,418 747 20,342 14,097 693 Tobacco 185 93 506 60 0 0 244 93 382 CASH CROPS 18,628 12,773 1,959 1,418 20,587 14,191 Total 120,270 1,725 1,761 213,255 258,478 393 333,525 260,203 395 *The total area planted include the sum of the planted area for both Short and Long Rainy Seasons and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long Rainy Season to estimate physical land area under production to different crops 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Mara Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 Appendix II 151 Number of Households Planted area (ha) Number of Households Planted area (ha) CEREALS 161,538 84,614 153,732 77,087 161,701 52.3 Maize 84,630 48,177 77,336 43,628 91,804 52.5 Paddy 4,697 2,270 6,982 2,603 4,873 46.6 Sorghum 63,432 29,922 54,589 25,118 55,040 54.4 Finger Millet 8,779 4,245 66 5,712 9,957 42.6 Bulrush Millet 0 0 14,759 27 27 0.0 ROOTS & TUBERS 36,271 8,438 176,754 124,679 133,117 6.3 Cassava 1,057 307 138,982 115,432 115,739 0.3 Sweet Potatoes 34,153 7,714 36,514 8,907 16,621 46.4 Irish Potatoes 869 299 798 244 543 55.1 Yams 115 23 318 83 106 21.9 Cocoyam 77 94 141 14 108 86.8 PULSES 24,094 6,799 24,009 7,639 14,438 47.1 Mung Beans 0 0 133 108 108 0.0 Beans 21,927 6,383 20,683 5,343 11,726 54.4 Cowpeas 688 97 917 181 278 34.9 Chich Peas 266 186 1,625 1,884 2,070 9.0 Bambaranuts 1,213 134 650 122 256 52.2 OIL SEEDS & OIL NUTS 2,538 877 2,183 695 1,572 55.8 Sunflower 103 21 0 0 21 100.0 Simsim 322 73 453 103 176 41.7 Groundnuts 1,978 761 1,596 577 1,337 56.9 Soya Beans 135 22 135 16 38 57.1 FRUITS & VEGETABLES 5,859 915 7,257 1,195 2,110 43.4 Bitter Aubergine 80 16 0 0 16 100.0 Garlic 132 27 0 0 27 100.0 Onions 538 95 1,010 152 247 38.4 Cabbage 1,008 123 1,491 257 381 32.4 Tomatoes 2,770 479 3,662 603 1,082 44.3 Spinnach 264 53 332 58 111 48.1 Amaranths 564 57 510 59 116 49.1 Pumpkins 116 12 116 12 24 50.0 Cucumber 233 24 0 0 24 100.0 Water Mellon 154 29 0 0 29 100.0 Ginger 0 135 54 54 0.0 CASH CROPS 20,232 18,628 2,945 1,959 20,587 90.5 Cotton 19,853 18,443 2,771 1,899 20,342 90.7 Tobacco 379 185 174 60 244 75.5 Total 120,270 213,255 333,525 36.1 Total Area Planted Short & Long Rainy Season % Area Planted in Short Rainy Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Short and Long Rainy Seasons, Mara Region Long Rainy Season Short Rainy Season Crop Tanzania Agriculture Sample Census-2003 Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 1,597 879 76,425 60,734 22,777 12,450 100,799 74,063 Serengeti 538 588 24,561 31,724 19,901 17,254 45,000 49,566 Musoma Rural 576 271 21,801 25,145 43,216 21,561 65,593 46,977 Bunda 235 84 16,279 26,888 23,892 20,761 40,406 47,733 Musoma Urban 0 0 0 0 508 140 508 140 Total 2,946 1,822 139,066 144,491 110,294 72,166 252,305 218,479 % 1 66 33 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tarime 20,170 23,258 2,554 1,895 1,719 2,306 95,498 87,871 119,941 115,331 Serengeti 4,092 6,678 334 301 134 149 42,367 58,038 46,927 65,165 Musoma Rural 11,773 12,668 917 1,092 795 178 65,244 74,086 78,730 88,024 Bunda 5,740 5,312 2,113 3,431 78 93 42,978 55,436 50,910 64,272 Musoma Urban 97 56 0 0 25 7 572 670 694 732 Total 41,873 47,972 5,919 6,719 2,751 2,732 246,660 276,102 297,203 333,525 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Tarime 56,628 41,456 15,589 14,448 72,217 115,331 35.95 Serengeti 15,361 15,673 11,114 12,054 26,475 65,165 24.05 Musoma Rural 38,183 40,769 8,652 10,812 46,835 88,024 46.32 Bunda 18,646 17,523 5,123 7,087 23,770 64,272 27.26 Musoma Urban 362 612 36 9 398 732 83.50 Total 129,180 116,033 40,515 44,410 169,695 333,525 34.79 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Short and Long Rainy Season, 2002/03 Agriculture Year % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation Households not Using Irrigation Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Short and Long Rainy Season, Mara District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Short and Long Rainy , Mara District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Tanzania Agriculture Sample Census-2003 Appendix II 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 4,376 2,316 115,565 113,014 119,941 115,331 2.0 Serengeti 3,637 4,076 43,290 61,090 46,927 65,165 6.3 Musoma Rural 8,234 5,275 70,496 82,750 78,730 88,024 6.0 Bunda 4,950 10,028 45,960 54,245 50,910 64,272 15.6 Musoma Urban 68 24 627 708 694 732 3.3 Total 21,265 21,719 275,938 311,806 297,203 333,525 6.5 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 2,132 1,718 117,809 113,613 119,941 115,331 1.5 Serengeti 412 404 46,515 64,761 46,927 65,165 0.6 Musoma Rural 2,416 1,422 76,314 86,602 78,730 88,024 1.6 Bunda 396 402 50,514 63,870 50,910 64,272 0.6 Musoma Urban 12 9 683 723 694 732 1.2 Total 5,368 3,956 291,835 329,570 297,203 333,525 1.2 % 1.8 1.2 98.2 98.8 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 2,915 3,660 117,026 111,671 119,941 115,331 3.2 Serengeti 1,651 2,117 45,276 63,048 46,927 65,165 3.2 Musoma Rural 3,271 2,403 75,459 85,621 78,730 88,024 2.7 Bunda 1,094 1,283 49,815 62,990 50,910 64,272 2.0 Musoma Urban 48 20 646 713 694 732 2.7 Total 8,980 9,482 288,223 324,043 297,203 333,525 2.8 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 13,875 13,653 106,066 101,677 119,941 115,331 11.8 Serengeti 3,008 3,703 43,919 61,462 46,927 65,165 5.7 Musoma Rural 11,998 9,474 66,732 78,550 78,730 88,024 10.8 Bunda 6,740 8,656 44,170 55,616 50,910 64,272 13.5 Musoma Urban 92 46 602 687 694 732 6.2 Total 35,714 35,532 261,489 297,993 297,203 333,525 10.7 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season. District Improved Seed Use % of Planted Area Using Improved Seeds Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season. District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Short & Long Rainy Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census-2003 Appendix II 154 ANNUAL CROP & VEGETABLES PRODUCTION SHORT RAINY SEASON Tanzania Agriculture Sample Census-2003 Appendix II 155 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 539 229 36,348 28,226 10,837 6,879 47,725 35,334 Serengeti 209 254 11,109 13,858 9,134 8,594 20,452 22,706 Musoma Rural 351 237 11,107 14,024 20,436 11,507 31,894 25,769 Bunda 235 84 10,963 19,652 15,943 16,676 27,140 36,412 Musoma Urban 0 . 0 . 296 75 296 75 Total 1,335 805 69,527 75,761 56,646 43,731 127,507 120,297 % 1 1 55 63 44 36 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 12,833 9,645 938 604 941 713 33,013 24,345 47,725 35,307 Serengeti 2,808 2,948 133 61 0 0 17,511 19,698 20,452 22,706 Musoma Rural 6,152 4,657 199 400 570 90 24,973 20,622 31,894 25,769 Bunda 3,516 3,628 1,174 1,454 0 65 22,450 31,266 27,140 36,412 Musoma Urban 50 27 0 . 12 4 235 45 296 75 Total 25,359 20,905 2,444 2,518 1,522 871 98,183 95,976 127,507 120,270 % 20 17 2 2 1 1 77 80 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 800 405 46,925 34,902 47,725 35,307 1 Serengeti 271 159 20,181 22,548 20,452 22,706 1 Musoma Rural 1,647 858 30,248 24,911 31,894 25,769 3 Bunda 540 983 26600 35,430 27140 36412 3 Musoma Urban 30 9 266 67 296 75 11 Total 3,287 2,412 124,220 117,858 127,507 120,270 2 % 3 2 97 98 100 100 Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Mara Region. District Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Tractor Ploughing Soil Preparation 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - SHORT RAINY SEASON, Mara Region District % of planted area under irrigation in short rainy season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Short Rainy Season, 2002/03 Agriculture Year, Mara Region Irrigation Use Households Using Irrigation Households Not Using Irrigation Total District Fertilizer Use Tanzania Agriculture Sample Census-2003 Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 933 703 46,792 34,604 47,725 35,307 2.0 Serengeti 1,711 2,636 18,741 20,070 20,452 22,706 11.6 Musoma Rural 4,556 3,686 27,338 22,083 31,894 25,769 14.3 Bunda 4,102 9,703 23,038 26,709 27,140 36,412 26.6 Musoma Urban 37 17 260 59 296 75 21.9 Total 11,338 16,745 116,169 103,525 127,507 120,270 13.9 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 923 306 46,802 35,001 47,725 35,307 0.9 Serengeti 206 178 20,246 22,528 20,452 22,706 0.8 Musoma Rural 1,048 397 30,846 25,371 31,894 25,769 1.5 Bunda 239 321 26,901 36,091 27,140 36,412 0.9 Musoma Urban 0 0 296 75 296 75 0.0 Total 2,416 1,203 125,091 119,067 127,507 120,270 1.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 791 588 46,933 34,746 47,725 35,334 1.66 Serengeti 616 597 19,836 22,109 20,452 22,706 2.63 Musoma Rural 1,676 833 30,218 24,936 31,894 25,769 3.23 Bunda 547 731 26,593 35,681 27,140 36,412 2.01 Musoma Urban 24 6 273 70 296 75 7.91 Total 3,655 2,755 123,853 117,541 127,507 120,297 2.29 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tarime 11,751 10,581 35,973 24,752 47,725 35,334 29.95 Serengeti 1,973 2,183 18,479 20,523 20,452 22,706 9.62 Musoma Rural 10,404 7,904 21,491 17,865 31,894 25,769 30.67 Bunda 6,193 8,104 20,947 28,308 27,140 36,412 22.26 Musoma Urban 68 32 229 43 296 75 42.50 Total 30,389 28,805 97,119 91,492 127,507 120,297 23.94 % 24 24 76 76 100 100 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Short Rainy Season District Improved Seed Use % of Planted Area Using Improved Seed Households Using Improved Seed Households Not Using Improved Seed Total 7.1f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Short Rainy Season. Fungicide Use % of Planted Area Using Fungicides Household Using Fungicides Households Not Using Fungicides Total % of Planted Area Using Insecticides Household Using Insecticides 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short Rainy Season. Households Not Using Insecticides Total Insecticide Use Households Not Using Herbicidess Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Short Rainy Season. Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess Tanzania Agriculture Sample Census-2003 157 Appendix II 158 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON Tanzania Agriculture Sample Census-2003 Appendix II 159 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 1,058 649 40,077 32,509 11,940 5,572 53,074 38,730 Serengeti 329 334 13,452 17,866 10,767 8,660 24,548 26,859 Musoma Rural 225 34 10,693 11,120 22,780 10,054 33,698 21,209 Bunda 0 . 5,316 7,236 7,950 4,085 13,266 11,321 Musoma Urban 0 . 0 . 212 64 212 64 Total 1,611 1,017 69,539 68,730 53,648 28,435 124,798 98,183 % 1 1 56 70 43 29 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 7,338 13,613 1,616 1,291 778 1,594 62,485 63,527 72,217 80,024 Serengeti 1,284 3,730 201 240 134 149 24,856 38,340 26,475 42,459 Musoma Rural 5,621 8,011 718 692 225 88 40,271 53,464 46,835 62,255 Bunda 2,224 1,684 940 1,978 78 28 20,528 24,170 23,770 27,860 Musoma Urban 48 29 0 0 13 3 337 624 398 657 Total 16,515 27,067 3,475 4,201 1,229 1,861 148,477 180,126 169,695 213,255 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 56,628 41,052 15,589 38,972 72,217 80,024 51 Serengeti 15,361 15,515 11,114 26,944 26,475 42,459 37 Musoma Rural 38,183 39,911 8,652 22,345 46,835 62,255 64 Bunda 18,646 16,540 5,123 11,320 23,770 27,860 59 Musoma Urban 362 603 36 54 398 657 92 Total 129,180 113,620 40,515 99,635 169,695 213,255 53 % 76 53 24 47 100 100 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Mara Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - LONG RAINY SEASON, Mara Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of planted area under irrigation in long rainy season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Long Rainy Season, 2002/03 Agriculture Year, Mara Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census-2003 Appendix II 160 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 3,443 1,613 68,773 78,411 72,217 80,024 2.02 Serengeti 1,927 1,439 24,549 41,020 26,475 42,459 3.39 Musoma Rural 3,677 1,589 43,158 60,666 46,835 62,255 2.55 Bunda 848 324 22,921 27,536 23,770 27,860 1.16 Musoma Urban 31 8 367 649 398 657 1.18 Total 9,927 4,974 159,768 208,282 169,695 213,255 2.33 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 1,210 1,412 71,007 78,612 72,217 80,024 1.76 Serengeti 206 226 26,269 42,233 26,475 42,459 0.53 Musoma Rural 1,368 1,025 45,468 61,230 46,835 62,255 1.65 Bunda 156 81 23,613 27,779 23,770 27,860 0.29 Musoma Urban 12 9 387 648 398 657 1.38 Total 2,952 2,753 166,744 210,502 169,695 213,255 1.29 % 1.7 1.3 98.3 98.7 100 100 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long Rainy Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long Rainy Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census-2003 Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tarime 2,124 3,072 70,093 76,952 72,217 80,024 3.84 Serengeti 1,035 1,520 25,440 40,939 26,475 42,459 3.58 Musoma Rural 1,594 1,570 45,241 60,686 46,835 62,255 2.52 Bunda 547 552 23,223 27,308 23,770 27,860 1.98 Musoma Urban 25 14 373 643 398 657 2.08 Total 5,325 6,727 164,370 206,528 169,695 213,255 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tarime 12,425 10,345 40,650 28,385 53,074 38,730 26.71 Serengeti 2,285 2,752 22,263 24,107 24,548 26,859 10.25 Musoma Rural 10,061 4,611 23,637 16,597 33,698 21,209 21.74 Bunda 683 397 12,583 10,923 13,266 11,321 3.51 Musoma Urban 43 14 169 50 212 64 21.78 Total 25,496 18,120 99,302 80,063 124,798 98,183 18.46 % 20 18 80 82 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under irrigation in dry season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census-2003 Appendix II 162 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 2,239 65,968 246 936 7,450 76,838 Maize 2,418 1,129 64,201 36,162 320 177 650 597 9,508 5,402 77,098 43,467 Paddy 379 213 5,630 2,128 0 . 0 . 973 262 6,982 2,603 Sorghum 1,686 660 48,786 22,538 200 68 533 325 3,321 1,501 54,526 25,093 Bulrush Millet 0 . 66 27 0 . 0 . 0 . 66 27 Finger Millet 403 236 13,543 5,113 0 . 70 14 664 284 14,681 5,648 ROOTS & TUBERS 205 7,343 0 27 2,031 9,605 Cassava 0 . 1,136 344 0 . 0 . 75 15 1,211 359 Sweet Potatoes 701 165 28,803 6,735 0 . 135 27 6,863 1,979 36,502 8,906 Irish Potatoes 132 40 666 203 0 . 0 . 0 . 798 244 Yams 0 . 229 46 0 . 0 . 90 36 318 83 Cocoyam 0 . 141 14 0 . 0 . 0 . 141 14 PULSES 231 5,923 26 56 1,308 7,543 Mung Beans 0 . 133 108 0 . 0 . 0 . 133 108 Beans 450 231 16,119 3,905 0 . 224 56 3,651 1,055 20,445 5,247 Cowpeas 0 . 662 140 65 26 0 . 191 15 917 181 Chich Peas 0 . 1,398 1,670 0 . 0 . 228 214 1,625 1,884 Bambaranuts 0 . 533 99 0 . 0 . 116 24 650 122 OIL SEEDS & OIL NUTS 0 410 0 0 285 695 Simsim 0 . 453 103 0 . 0 . 0 . 453 103 Groundnuts 0 . 1,003 291 0 . 0 . 593 285 1,596 577 Soya Beans 0 . 135 16 0 . 0 . 0 . 135 16 FRUITS & VEGETABLES 6 1,126 0 0 63 1,195 Onions 0 . 1,010 152 0 . 0 . 0 . 1,010 152 Ginger 0 . 135 54 0 . 0 . 0 . 135 54 Cabbage 0 . 1,491 257 0 . 0 . 0 . 1,491 257 Tomatoes 108 6 3,131 534 0 . 0 . 423 63 3,662 603 Spinnach 0 . 332 58 0 . 0 . 0 . 332 58 Amaranths 0 . 510 59 0 . 0 . 0 . 510 59 Pumpkins 0 . 116 12 0 . 0 . 0 . 116 12 CASH CROPS 57 1,856 0 0 47 1,959 Cotton 70 57 2,586 1,796 0 . 0 . 116 47 2,771 1,899 Tobacco 0 . 174 60 0 . 0 . 0 . 174 60 Total 65,890 2,737 82,625 272 1,019 11,184 97,836 % 3 84 0 1 11 100 Crop Table 7.2h: Planted Area and Number of Crop Growing Households During Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census-2003 Appendix II 163 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 37,237 18,911 27,290 1.443 39,725 20,362 29,562 1.452 39,273 56,852 1.448 Serengeti 13,657 8,039 8,589 1.068 15,672 9,450 11,677 1.236 17,490 20,266 1.159 Musoma Rural 15,970 10,376 12,547 1.209 15,281 8,950 10,765 1.203 19,326 23,312 1.206 Bunda 17,691 10,824 7,551 0.698 6,590 4,844 2,643 0.546 15,668 10,195 0.651 Musoma Urban 75 27 18 0.681 68 21 19 0.927 47 37 0.788 Total 84,630 48,177 55,996 1.162 77,336 43,628 54,666 1.253 91,804 110,662 1.205 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 1,297 427 358 0.838 1,294 445 379 0.852 872 737 0.845 Serengeti 1,221 744 980 1.317 1,512 897 1,404 1.566 1,641 2,385 1.453 Musoma Rural 1,246 460 635 1.381 3,923 1,112 1,997 1.796 1,572 2,632 1.675 Bunda 927 637 393 0.617 235 144 113 0.788 781 506 0.649 Musoma Urban 7 1 0 0.000 18 6 11 1.871 7 11 1.516 Total 4,697 2,270 2,366 1.043 6,982 2,603 3,905 1.500 4,873 6,271 1.287 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 31,564 10,803 10,547 0.976 29,306 11,257 11,127 0.988 22,060 21,674 0.982 Serengeti 14,319 7,374 7,769 1.054 17,299 9,666 11,235 1.162 17,040 19,004 1.115 Musoma Rural 6,648 3,586 4,249 1.185 4,064 2,165 2,250 1.039 5,751 6,500 1.130 Bunda 10,901 8,159 6,277 0.769 3,913 2,029 1,052 0.518 10,188 7,328 0.719 Musoma Urban 0 0 0 0.000 7 1 0 0.741 1 0 0.741 Total 63,432 29,922 28,842 0.964 54,589 25,118 25,664 1.022 55,040 54,506 0.990 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 66 27 0 0.000 27 0 0.000 Musoma Rural 0 0 0 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 66 27 0 0.000 27 0 0.000 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Paddy District Short Rainy Season Long Rainy Season Total Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Sorghum District Short Rainy Season Long Rainy Season Total Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush Millet Harvested (tons) by Season and District;2002/03 Agricultural Year Burlush Millet District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year Maize District Short Rainy Season Tanzania Agriculture Sample Census-2003 Appendix II 164 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 3,250 1,041 813 0.780 7,194 1,921 1,652 0.860 2,962 2,464 0.832 Serengeti 2,610 1,111 924 0.831 5,637 2,709 2,541 0.938 3,820 3,466 0.907 Musoma Rural 1,463 1,042 1,368 1.313 1,015 700 448 0.640 1,742 1,816 1.042 Bunda 1,456 1,050 671 0.639 914 382 166 0.433 1,433 837 0.584 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 8,779 4,245 3,776 0.889 14,759 5,712 4,807 0.842 9,957 8,583 0.862 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 543 164 293 1.785 60,373 41,417 51,097 1.234 41,581 51,390 1.236 Serengeti 209 85 137 1.614 16,739 15,675 9,227 0.589 15,760 9,364 0.594 Musoma Rural 227 30 92 3.016 42,101 41,177 40,096 0.974 41,207 40,187 0.975 Bunda 78 28 31 1.098 19,408 16,571 14,537 0.877 16,599 14,568 0.878 Musoma Urban 0 0 0 0.000 362 592 239 0.403 592 239 0.403 Total 1,057 307 552 1.796 138,982 115,432 115,195 0.998 115,739 115,747 1.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 9,462 1,956 4,553 2.328 10,953 2,392 4,478 1.872 4,347 9,031 2.077 Serengeti 3,580 951 1,617 1.701 4,279 1,168 2,240 1.918 2,119 3,857 1.821 Musoma Rural 12,832 2,999 12,020 4.008 16,853 4,459 14,012 3.142 7,458 26,032 3.490 Bunda 8,038 1,774 2,615 1.474 4,280 860 1,546 1.798 2,633 4,161 1.580 Musoma Urban 242 34 101 2.935 150 28 52 1.850 63 153 2.445 Total 34,153 7,714 20,906 2.710 36,514 8,907 22,328 2.507 16,621 43,234 2.601 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 539 177 1,086 6.130 663 174 294 1.686 351 1,380 3.927 Serengeti 135 83 102 1.235 135 69 115 1.660 152 217 1.429 Musoma Rural 115 23 183 7.904 0 0 0 0.000 23 183 7.904 Bunda 80 16 0 0.025 0 0 0 0.000 16 0 0.025 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 869 299 1,372 4.584 798 244 409 1.679 543 1,781 3.281 Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Short Rainy Season Long Rainy Season Total Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet Potatoes District Short Rainy Season Long Rainy Season Total Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish Potatoes District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Short Rainy Season Tanzania Agriculture Sample Census-2003 Appendix II 165 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 115 23 14 0.603 318 83 263 3.190 106 277 2.623 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 115 23 14 0.603 318 83 263 3.190 106 277 2.623 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 67 7 67 9.880 7 67 9.880 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 77 94 2 0.021 74 8 3 0.395 101 5 0.048 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 77 94 2 0.000 141 14 70 4.883 108 71 0.661 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 133 108 240 2.223 108 240 2.223 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 133 108 240 2.223 108 240 2.223 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 4,932 1,128 910 0.807 4,662 907 759 0.837 2,035 1,670 0.821 Serengeti 3,304 1,174 718 0.611 2,931 1,364 989 0.725 2,538 1,707 0.672 Musoma Rural 7,433 1,967 1,638 0.833 10,422 2,206 1,301 0.590 4,173 2,940 0.704 Bunda 6,222 2,110 824 0.391 2,656 865 469 0.542 2,974 1,293 0.435 Musoma Urban 36 4 3 0.694 13 2 1 0.280 6 3 0.548 Total 21,927 6,383 4,093 0.641 20,683 5,343 3,519 0.659 11,726 7,612 0.649 Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Cocoyams District Short Rainy Season Long Rainy Season Total Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung Beans District Short Rainy Season Long Rainy Season Total Table 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Yams District Short Rainy Season Tanzania Agriculture Sample Census-2003 Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 387 60 43 0.720 60 43 0.720 Serengeti 0 0 0 0.000 260 98 210 2.139 98 210 2.139 Musoma Rural 532 75 18 0.239 116 12 2 0.198 87 20 0.234 Bunda 155 22 4 0.192 154 11 2 0.205 33 7 0.196 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 688 97 22 0.228 917 181 258 1.425 278 280 1.008 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 70 28 28 0.988 28 28 0.988 Musoma Rural 113 91 68 0.741 0 0 0 0.000 91 68 0.741 Bunda 154 94 55 0.584 1,556 1,856 922 0.497 1,951 977 0.501 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 266 186 123 0.661 1,625 1,884 950 0.504 2,070 1,073 0.518 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 132 16 8 0.494 16 8 0.494 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 1,039 95 38 0.400 517 106 25 0.231 201 63 0.311 Bunda 151 35 18 0.520 0 0 0 0.000 35 18 0.520 Musoma Urban 23 4 1 0.329 0 0 0 0.000 4 1 0.329 Total 1,213 134 57 0.430 650 122 33 0.266 256 90 0.351 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 103 21 7 0.346 0 0 0 0.000 21 7 0.346 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 103 21 7 0.346 0 0 0 0.000 21 7 0.346 Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick Peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick Peas District Short Rainy Season Long Rainy Season Total Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Short Rainy Season Long Rainy Season Total Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Cowpeas District Short Rainy Season Tanzania Agriculture Sample Census-2003 Appendix II 167 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 103 10 2 0.198 270 66 6 0.084 76 8 0.100 Serengeti 66 13 13 0.988 69 14 19 1.359 27 32 1.178 Musoma Rural 0 0 0 0.000 113 23 2 0.099 23 2 0.099 Bunda 152 50 6 0.125 0 0 0 0.000 50 6 0.125 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 322 73 21 0.293 453 103 27 0.262 176 48 0.275 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 738 162 172 1.061 496 169 70 0.414 332 242 0.731 Serengeti 139 42 32 0.758 272 63 34 0.546 105 66 0.632 Musoma Rural 235 195 474 2.437 820 344 451 1.312 539 926 1.719 Bunda 865 361 118 0.327 0 0 0 0.000 361 118 0.327 Musoma Urban 0 0 0 0.000 7 1 0 0.000 1 0 0.000 Total 1,978 761 797 1.047 1,596 577 555 0.964 1,337 1,352 1.011 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 135 22 27 1.235 135 16 24 1.482 38 51 1.341 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 135 22 27 1.235 135 16 24 1.482 38 51 1.341 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0 0 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0 0 0 0.000 Bunda 80 16 16 0.988 0 0 0 0 16 16 0.988 Musoma Urban 0 0 0 0.000 0 0 0 0 0 0 0.000 Total 80 16 16 0.988 0 0 0 0 16 16 0.988 Long Rainy Season Total Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Short Rainy Season Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Bitter Aubergine District Short Rainy Season Long Rainy Season Total Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya Beans District Short Rainy Season Long Rainy Season Total Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 Appendix II 168 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 132 27 0 0.000 0 0 0 0.000 27 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 132 27 0 0.000 0 0 0 0.000 27 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 403 81 302 3.732 536 108 410 3.797 189 712 3.769 Serengeti 135 14 60 4.402 205 17 65 3.793 31 125 4.064 Musoma Rural 0 0 0 0.000 115 12 44 3.754 12 44 3.754 Bunda 0 0 0 0.000 153 15 26 1.671 15 26 1.671 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 538 95 362 3.829 1,010 152 544 3.578 247 907 3.674 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 135 54 135 2.470 54 135 2.470 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 135 54 135 2.470 54 135 2.470 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 398 42 78 1.850 652 154 646 4.200 196 723 3.696 Serengeti 66 7 0 0.000 269 34 253 7.437 41 253 6.209 Musoma Rural 234 24 76 3.211 564 69 450 6.540 92 526 5.688 Bunda 311 51 180 3.520 0 0 0 0.000 51 180 3.520 Musoma Urban 0 0 0 0.000 7 1 2 2.371 1 2 2.371 Total 1,008 123 333 2.702 1,491 257 1,350 5.249 381 1,683 4.423 Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Short Rainy Season Long Rainy Season Total Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District;2002/03 Agricultural Year Ginger District Short Rainy Season Long Rainy Season Total Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Cabbage District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Garlic Harvested (tons) by Season and District;2002/03 Agricultural Year Garlic District Short Rainy Season Tanzania Agriculture Sample Census-2003 Appendix II 169 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 1,194 215 539 2.508 1,556 317 977 3.084 532 1,516 2.851 Serengeti 468 81 267 3.284 809 149 464 3.107 231 731 3.170 Musoma Rural 853 147 724 4.927 888 85 446 5.271 232 1,170 5.053 Bunda 231 30 57 1.898 389 47 288 6.089 77 345 4.464 Musoma Urban 24 6 16 2.724 20 5 23 4.954 11 39 3.695 Total 2,770 479 1,603 3.346 3,662 603 2,198 3.647 1,082 3,801 3.514 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 264 53 48 0.889 256 33 42 1.242 87 89 1.025 Serengeti 0 0 0 0.000 70 23 6 0.268 23 6 0.268 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 7 1 1 1.976 1 1 1.976 Total 264 53 48 0.889 332 58 49 0.853 111 97 0.871 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 386 47 50 1.067 47 50 1.067 Serengeti 66 7 2 0.296 0 0 0 0.000 7 2 0.296 Musoma Rural 417 42 37 0.879 117 12 176 14.820 54 213 3.937 Bunda 80 8 12 1.482 0 0 0 0.000 8 12 1.482 Musoma Urban 0 0 0 0.000 7 1 3 3.952 1 3 3.952 Total 564 57 51 0.896 510 59 228 3.857 116 279 2.404 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 116 12 1 0.059 116 12 2 0.158 24 3 0.109 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 116 12 1 0.059 116 12 2 0.158 24 3 0.109 Long Rainy Season Total Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Short Rainy Season Table 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Pumpkins District Short Rainy Season Long Rainy Season Total Table 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Short Rainy Season Long Rainy Season Total Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 Appendix II 170 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 233 24 24 1.039 0 0 0 0.000 24 24 1.039 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 233 24 24 1.039 0 0 0 0.000 24 24 1.039 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Bunda 154 29 37 1.263 0 0 0 0.000 29 37 1.263 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 154 29 37 1.263 0 0 0 0.000 29 37 1.263 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Serengeti 2,617 2,981 2,097 0.704 1,393 994 783 0.788 3,975 2,880 0.725 Musoma Rural 5,770 4,439 2,916 0.657 928 677 477 0.704 5,117 3,393 0.663 Bunda 11,467 11,023 7,666 0.695 451 228 158 0.693 11,251 7,824 0.695 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 19,853 18,443 12,680 0.687 2,771 1,899 1,418 0.747 20,342 14,097 0.693 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tarime 262 66 0 0.000 0 0 0 0.000 66 0 0.000 Serengeti 0 0 0 0.000 70 7 0 0.000 7 0 0.000 Musoma Rural 117 118 93 0.790 104 53 0 0.000 171 93 0.546 Bunda 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Musoma Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 379 185 93 0.506 174 60 0 0.000 244 93 0.382 Long Rainy Season Total Table 7.2.29: Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Cucumber District Short Rainy Season Table 7.2.32: Number of Agricultural Households, Area Planted (ha) and Quantity of Tobbaco Harvested (tons) by Season and District;2002/03 Agricultural Year Tobacco District Short Rainy Season Long Rainy Season Total Table 7.2.31: Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Cotton District Short Rainy Season Long Rainy Season Total Table 7.2.30: Number of Agricultural Households, Area Planted (ha) and Quantity of Water mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Water mellon District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 171 Appendix II 172 PERMANENT CROPS Tanzania Agriculture Sample Census-2003 Appendix II 173 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Star Fruit 94 13 5 40 Sisal 14 5 20 371 Coffee 3,687 2,727 2,244 82 Sugarcane 253 120 3,372 2,811 Pomelo 3,328 49 41 82 Banana 3,923 2,286 11,395 498 Avocado 28 40 184 454 Mango 428 151 636 422 Pawpaw 104 21 133 621 Pineapple 54 0 5 Orange 318 76 1,713 2,261 Mandarine/Tangerine 26 0 694 Guava 266 24 34 139 Lime/Lemon 202 48 1,170 2,412 Total 12,727 5,562 21,646 Coffee 44 0 0 0 Sugarcane 64 35 684 1,939 Jack Fruit 9 0 3 Banana 257 159 508 320 Mango 78 0 507 Pawpaw 28 0 347 Pineapple 40 27 13 49 Orange 677 51 584 1,154 Mandarine/Tangerine 199 198 25 13 Guava 2 0 154 Lime/Lemon 2 0 142 Total 1,399 469 2,966 Coffee 40 12 2 20 Sugarcane 65 23 446 1,911 Banana 188 21 1,029 4,914 Mango 531 98 2,633 2,682 Pawpaw 78 31 779 2,494 Orange 113 473 778 164 Mandarine/Tangerine 1 0 71 Guava 30 0 170 Lime/Lemon 3 0 172 Bilimbi 9 0 32 Total 1,056 2,343 6,167 263 Malay Apple 92 0 51 Mango 348 0 1,746 Pawpaw 747 0 165 Orange 60 13 779 59 Total 1,248 13 3,063 No area harvested or area harvested too small to get accurate yield figures 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Mara Serengeti Musoma Rural Bunda District/Crop Tarime Tanzania Agriculture Sample Census-2003 Appendix II 174 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Sugarcane 2 2 10 463 Banana 8 2 21 1,309 Avocado 5 0 . Mango 317 0 51 Pawpaw 34 1 8 1,571 Orange 2 1 1 86 Lime/Lemon 3 0 . Bilimbi 35 0 . Total 405 5 91 Malay Apple 92 0 51 Star Fruit 94 13 5 40 Sisal 14 5 20 371 Coffee 3,771 2,738 2,246 82 Sugarcane 383 181 4,512 2,497 Pomelo 3,328 49 41 82 Jack Fruit 9 0 34 Banana 4,376 2,467 12,980 526 Avocado 33 40 184 454 Mango 1,701 249 5,573 2,239 Pawpaw 991 53 1,432 2,691 Pineapple 94 27 19 69 Orange 1,169 613 3,854 628 Mandarine/Tangerine 225 198 806 407 Guava 299 24 487 1,991 Lime/Lemon 210 48 1,601 3,301 Bilimbi 43 0 36 Total 16,834 6,708 33,881 No area harvested or area harvested too small to get accurate yield figures cont… PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Mara District/Crop Musoma Urban Total Tanzania Agriculture Sample Census-2003 Appendix II 175 Crop Area Planted % Banana 4,376.12 26.00 Coffee 3,770.67 22.40 Pomelo 3,328.40 19.77 Mango 1,700.53 10.10 Orange 1,169.44 6.95 Pawpaw 990.68 5.88 Sugarcane 383.32 2.28 Guava 299.20 1.78 Mandarine/Tangerine 225.37 1.34 Lime/Lemon 209.80 1.25 Pineapple 94.25 0.56 Star Fruit 94.04 0.56 Malay Apple 92.34 0.55 Bilimbi 43.28 0.26 Avocado 33.12 0.20 Sisal 13.64 0.08 Jack Fruit 9.00 0.05 Apples 0.47 0.00 Mpesheni 0.26 0.00 Sour Soup 0.19 0.00 Nutmeg 0.07 0.00 Plums 0.07 0.00 Tamarin 0.04 0.00 Total 16,834 100.00 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Households with Banana Average Planted Area per Household Tarime 3,923 80,024 4.9 10,413 0.4 Serengeti 257 42,459 0.6 894 0.3 Musoma Rural 188 62,255 0.3 1,798 0.1 Bunda 0 27,860 0.0 0 0.0 Musoma Urban 8 657 1.2 13 0.6 Total 4,376 213,255 2.1 13,118 0.3 District Area Planted with Coffee Total Area Planted (Ha) % of Total Area Planted Households with Coffee Average Planted Area per Household Tarime 3,687 80,024 4.6 7,095 0.5 Serengeti 44 42,459 0.1 140 0.3 Musoma Rural 40 62,255 0.1 346 0.1 Bunda 0 27,860 0.0 0 0.0 Musoma Urban 0 657 0.0 0 0.0 Total 3,771 213,255 1.8 7,581 0.5 Coffee 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Mara Region Banana 7.3.3 PERMANENT CROPS: Area Planted with Banana by District 7.3.4 PERMANENT CROPS: Area planted with Coffee by District Tanzania Agriculture Sample Census-2003 Appendix II 176 District Area Planted with Oranges Total Area Planted (Ha) % of Total Area Planted Households with Oranges Average Planted Area per Household Tarime 318 80,024 0.4 1734 0.2 Serengeti 677 42,459 1.6 1658 0.4 Musoma Rural 113 62,255 0.2 3198 0.0 Bunda 60 27,860 0.2 370 0.2 Musoma Urban 2 657 0.3 18 0.1 Total 1169 213,255 0.5 6978 0.2 District Area Planted with Mango Total Area Planted (Ha) % of Total Area Planted Households with Mango Average Planted Area per Household Tarime 428 80,024 0.5 2,003 0.2 Serengeti 78 42,459 0.2 1,249 0.1 Musoma Rural 531 62,255 0.9 6,145 0.1 Bunda 348 27,860 1.2 548 0.6 Musoma Urban 317 657 48.2 120 2.6 Total 1,701 213,255 0.8 9,981 0.2 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0.00 0.00 0.00 0.19 0.19 Malay Apple 92.18 0.00 0.00 0.16 92.34 Star Fruit 80.76 0.00 0.00 13.28 94.04 Sisal 0.00 0.00 0.00 13.64 13.64 Coffee 1,171.19 0.00 0.00 2,599.48 3,770.67 Sugarcane 170.71 0.00 0.00 212.61 383.32 Tamarin 0.00 0.00 0.00 0.04 0.04 Nutmeg 0.00 0.00 0.00 0.07 0.07 Pomelo 3,328.40 0.00 0.00 0.00 3,328.40 Jack Fruit 0.00 0.00 0.00 9.44 9.44 Mpesheni 0.07 0.00 0.00 0.19 0.26 Banana 2,148.49 266.18 0.00 1,948.08 4,362.75 Avocado 0.13 0.00 0.00 32.98 33.12 Mango 376.01 9.18 0.00 1,289.53 1,674.72 Pawpaw 372.41 0.31 0.00 617.96 990.68 Pineapple 40.41 0.00 0.00 53.84 94.25 Orange 233.24 0.14 0.00 936.06 1,169.44 Mandarine/Tangerine 26.09 0.00 0.00 199.29 225.37 Guava 199.50 0.00 0.00 99.70 299.20 Plums 0.00 0.00 0.00 0.07 0.07 Apples 0.00 0.00 0.00 0.47 0.47 Lime/Lemon 95.22 0.00 0.00 114.58 209.80 Bilimbi 0.23 5.60 0.00 37.45 43.28 Total 8,335.05 281.40 0.00 8,179.11 16,795.56 7.3.7 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Fertilizer Use Crop 7.3.5 PERMANENT CROPS: Area planted with Orange by District Orange 7.3.6 PERMANENT CROPS: Area Planted with Mango by District Mango Tanzania Agriculture Sample Census-2003 Appendix II 177 Crop Mostly Farm Yard Manure Total % Sour Soup 0 0 0.0 Malay Apple 92 92 99.8 Star Fruit 81 94 85.9 Sisal 0 14 0.0 Coffee 1,171 3,771 31.1 Sugarcane 171 383 44.5 Tamarin 0 0 0.0 Nutmeg 0 0 0.0 Pomelo 3,328 3,328 100.0 Jack Fruit 0 9 0.0 Mpesheni 0 0 27.2 Banana 2,148 4,363 49.2 Avocado 0 33 0.4 Mango 376 1,675 22.5 Pawpaw 372 991 37.6 Pineapple 40 94 42.9 Orange 233 1,169 19.9 Mandarine/Tangerine 26 225 11.6 Guava 200 299 66.7 Plums 0 0 0.0 Apples 0 0 0.0 Lime/Lemon 95 210 45.4 Bilimbi 0 43 0.5 Total 8,335 16,796 49.6 Crop Mostly Compost Total % Sour Soup 0.0 0.19 0.00 Malay Apple 0.0 92.34 0.00 Star Fruit 0.0 94.04 0.00 Sisal 0.0 13.64 0.00 Coffee 0.0 3,770.67 0.00 Sugarcane 0.0 383.32 0.00 Tamarin 0.0 0.04 0.00 Nutmeg 0.0 0.07 0.00 Pomelo 0.0 3,328.40 0.00 Jack Fruit 0.0 9.44 0.00 Mpesheni 0.0 0.26 0.00 Banana 266.2 4,362.75 6.10 Avocado 0.0 33.12 0.00 Mango 9.2 1,674.72 0.55 Pawpaw 0.3 990.68 0.03 Pineapple 0.0 94.25 0.00 Orange 0.1 1,169.44 0.01 Mandarine/Tangerine 0.0 225.37 0.00 Guava 0.0 299.20 0.00 Plums 0.0 0.07 0.00 Apples 0.0 0.47 0.00 Lime/Lemon 0.0 209.80 0.00 Bilimbi 5.6 43.28 12.93 Total 281.4 16,795.56 1.68 cont… Planted Area with Fertilizer by Fertilizer Type and Crop cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census-2003 Appendix II 178 AGROPROCESSING Tanzania Agriculture Sample Census-2003 Appendix II 179 Number % Number % Number % Tarime 73,341 92.6 5,828 7 79,170 100 Serengeti 26,969 96.8 895 3 27,864 100 Musoma Rural 42,709 85.4 7,286 15 49,995 100 Bunda 28,558 93.0 2,162 7 30,721 100 Musoma Urban 282 62.3 171 38 453 100 Total 171,860 91.3 16,343 9 188,203 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm By Factory Other Total Tarime 22,502 10,085 40,088 530 0 0 135 73,341 Serengeti 1,387 135 25,040 408 0 0 0 26,969 Musoma Rural 14,602 684 26,958 232 117 116 0 42,709 Bunda 3,384 1,557 22,903 714 0 0 0 28,558 Musoma Urban 178 0 70 35 0 0 0 282 Total 42,052 12,461 115,059 1,918 117 116 135 171,860 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm Other By Factory Total Tarime 22,502 10,085 40,088 530 0 0 135 73,341 Serengeti 1,387 135 25,040 408 0 0 0 26,969 Musoma Rural 14,602 684 26,958 232 117 116 0 42,709 Bunda 3,384 1,557 22,903 714 0 0 0 28,558 Musoma Urban 178 0 70 35 0 0 0 282 Total 42,052 12,461 115,059 1,918 117 116 135 171,860 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Mara Region Method of Processing 8.1.1a: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Processed Crops Households That did not Process Crops Total Method of Processing 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Crop Tanzania Agriculture Sample Census-2003 Appendix II 180 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 107,200 129 665 129 247 135 108,504 Paddy 8,001 0 450 0 0 66 8,518 Sorghum 83,619 0 129 0 199 0 83,947 Finger Millet 17,627 0 617 0 177 0 18,422 Cassava 94,590 0 456 0 232 0 95,279 Sweet Potatoes 1,907 0 116 0 0 0 2,023 Beans 1,586 0 135 0 0 0 1,721 Cowpeas 69 0 0 0 0 0 69 Chick Peas 234 0 0 0 0 0 234 Simsim 201 0 135 0 0 0 336 Groundnut 135 0 0 0 0 0 135 Cotton 75 0 0 0 70 0 144 Coffee 0 0 268 0 0 0 268 Sugarcane 0 0 0 0 0 115 115 Banana 402 0 0 0 0 0 402 Orange 79 0 0 0 0 0 79 Total 315,726 129 2,972 129 924 316 320,196 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 698 7,686 716 114 114 631 225 144 98,176 108,504 Paddy 632 756 400 0 0 0 0 0 6,730 8,518 Sorghum 841 3,531 206 204 0 135 134 155 78,742 83,947 Finger Millet 232 723 0 0 0 245 0 137 17,085 18,422 Cassava 2,129 7,141 195 132 0 438 253 7 84,984 95,279 Sweet Potatoes 205 233 0 0 0 80 0 0 1,506 2,023 Beans 0 133 0 0 0 0 0 0 1,588 1,721 Cowpeas 0 0 0 0 0 0 0 0 69 69 Chick Peas 0 0 0 74 0 0 0 0 160 234 Simsim 0 0 0 0 0 0 0 0 336 336 Groundnut 0 0 0 0 0 0 0 0 135 135 Cotton 0 0 0 70 0 0 0 0 75 144 Coffee 0 0 0 268 0 0 0 0 0 268 Sugarcane 0 0 0 0 0 0 0 0 115 115 Banana 0 0 0 0 0 0 0 0 402 402 Orange 0 0 0 0 0 0 0 0 79 79 Total 4,738 20,201 1,516 862 114 1,529 613 442 290,181 320,196 Flour / Meal Grain Oil Juice Fiber Rubber Other Total Tarime 70,547 2,253 134 134 136 0 136 73,341 Serengeti 26,557 209 68 0 67 0 69 26,969 Musoma Rural 38,406 4,097 0 0 0 90 116 42,709 Bunda 28,480 78 0 0 0 0 0 28,558 Musoma Urban 271 12 0 0 0 0 0 282 Total 164,261 6,649 202 134 203 90 321 171,860 Household / Human Consumption Sale Only Did Not Use Other Total Tarime 72,935 271 0 135 73,341 Serengeti 26,701 0 268 0 26,969 Musoma Rural 42,283 199 227 0 42,709 Bunda 28,558 0 0 0 28,558 Musoma Urban 282 0 0 0 282 Total 170,760 471 495 135 171,860 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Mara Region Where Sold 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Mara Region Crop 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Mara Region District Product Use Crop Product Use Main Product 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Mara Region District Tanzania Agriculture Sample Census-2003 Appendix II 181 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Tarime 530 4,402 135 0 0 402 134 0 67,738 73,341 Serengeti 70 831 272 70 0 70 0 70 25,588 26,969 Musoma Rural 1,619 6,745 232 114 114 111 479 0 33,295 42,709 Bunda 310 542 78 0 0 139 0 155 27,334 28,558 Musoma Urban 24 12 0 0 0 0 0 7 241 282 Total 2,552 12,532 717 184 114 721 613 231 154,196 171,860 Bran Cake Husk Juice Fiber Pulp Shell No by- product Total Tarime 654 0 507 397 377 533 266 70,608 73,341 Serengeti 554 132 1,225 0 0 0 0 25,058 26,969 Musoma Rural 314 0 3,533 117 115 0 0 38,630 42,709 Bunda 160 0 311 0 0 0 80 28,007 28,558 Musoma Urban 23 0 7 0 0 0 0 253 282 Total 1,705 132 5,583 514 492 533 346 162,555 171,860 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Mara Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Mara Region District By Product Tanzania Agriculture Sample Census-2003 Appendix II 182 MARKETING Tanzania Agriculture Sample Census-2003 Appendix II 183 Number % Number % Kondoa 53,981 68.2 25,188 31.8 79,170 Mpwapwa 21,552 77.3 6,312 22.7 27,864 Kongwa 34,052 68.1 15,944 31.9 49,995 Dodoma Rural 20,756 67.6 9,965 32.4 30,721 Dodoma Urban 97 21.3 357 78.7 453 Total 130,438 69.3 57,765 30.7 188,203 Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Tarime 1211 25673 130 135 668 136 3105 47075 78133 Serengeti 548 7345 69 0 70 0 344 19217 27594 Musoma Rural 1158 15974 104 116 796 0 2083 29420 49652 Bunda 156 12943 0 0 0 0 546 16530 30174 Musoma Urban 12 294 0 0 0 0 25 111 441 Total 3085 62229 304 251 1534 136 6103 112353 185994 Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Tarime 1.55 32.86 0.17 0.17 0.86 0.17 3.97 60.25 100.00 Serengeti 1.99 26.62 0.25 0.00 0.25 0.00 1.25 69.64 100.00 Musoma Rural 2.33 32.17 0.21 0.23 1.60 0.00 4.20 59.25 100.00 Bunda 0.52 42.89 0.00 0.00 0.00 0.00 1.81 54.78 100.00 Musoma Urban 2.62 66.65 0.00 0.00 0.00 0.00 5.57 25.16 100.00 Total 1.66 33.46 0.16 0.14 0.82 0.07 3.28 60.41 100.00 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Mara Region 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Mara Region District Main Reasons for Not Selling Crops Main Reasons for Not Selling Crops District 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Mara Region Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census-2003 Appendix II 184 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census-2003 Appendix II 185 Number of Household % Number of Household % Number of Household % Tarime 1,688 2 77,481 98 79,170 100 Serengeti 471 2 27,393 98 27,864 100 Musoma Rural 2,890 6 47,105 94 49,995 100 Bunda 780 3 29,941 97 30,721 100 Musoma Urban 50 11 404 89 453 100 Total 5,879 3 182,324 97 188,203 100 District Irrigatable Area (ha) Irrigated Land (ha) % Tarime 989 634 64.1 Serengeti 128 109 85.1 Musoma Rural 675 554 82.0 Bunda 208 181 87.0 Musoma Urban 13 12 89.6 Total 2,014 1,490 74.0 River Lake Dam Well Canal Total Tarime 666 401 103 518 0 1,688 Serengeti 202 0 70 199 0 471 Musoma Rural 896 439 108 1,256 191 2,890 Bunda 236 391 0 152 0 780 Musoma Urban 7 19 0 25 0 50 Total 2,007 1,250 281 2,151 191 5,879 Gravity Hand Bucket Hand Pump Motor Pump Other Total Tarime 0 1,301 124 0 264 1,688 Serengeti 0 471 0 0 0 471 Musoma Rural 308 2,467 0 115 0 2,890 Bunda 74 549 0 0 156 780 Musoma Urban 0 50 0 0 0 50 Total 382 4,839 124 115 420 5,879 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year District 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total Method of Obtaining Water Source of Irrigation Water 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District 11.4: IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Appendix II 186 Flood Sprinkler Water Hose Bucket / Watering Can Total Tarime 0 0 124 1,564 1,688 Serengeti 0 68 0 403 471 Musoma Rural 455 0 0 2,435 2,890 Bunda 156 0 0 623 780 Musoma Urban 0 0 0 50 50 Total 612 68 124 5,075 5,879 Number % Number % Tarime 4,982 6 74,187 94 79,170 Serengeti 682 2 27,182 98 27,864 Musoma Rural 12,144 24 37,851 76 49,995 Bunda 378 1 30,342 99 30,721 Musoma Urban 95 21 359 79 453 Total 18,282 10 169,921 90 188,203 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Tarime 1,177 15,043 0 0 0 4,870 2,654 0 23,744 Serengeti 0 2,441 0 0 209 279 0 0 2,929 Musoma Rural 0 177,250 0 216 10,222 85,448 8,689 229 282,054 Bunda 0 303 0 0 0 316 148 0 767 Musoma Urban 0 3,343 0 0 0 832 0 12 4,188 Total 1,177 198,380 0 216 10,431 91,745 11,491 241 313,682 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census-2003 187 Appendix II 188 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census-2003 Appendix II 189 No of households % No of households % Tarime 2,127 2.7 75,967 97.3 78,094 Serengeti 134 0.5 27,454 99.5 27,588 Musoma Rural 575 1.2 48,448 98.8 49,023 Bunda 78 0.3 30,568 99.7 30,646 Musoma Urban 18 4.1 422 95.9 440 Total 2,932 1.6 182,859 98.4 185,791 No of households % No of households % Tarime 25,814 33 52,280 67 78,094 Serengeti 5,807 21 21,781 79 27,588 Musoma Rural 11,276 23 37,747 77 49,023 Bunda 5,502 18 25,144 82 30,646 Musoma Urban 116 26 324 74 440 Total 48,514 26 137,277 74 185,791 No of households % No of households % Tarime 3,495 4.5 74,599 95.5 78,094 Serengeti 267 1.0 27,321 99.0 27,588 Musoma Rural 1,627 3.3 47,395 96.7 49,023 Bunda 1,326 4.3 29,320 95.7 30,646 Musoma Urban 0 0.0 440 100.0 440 Total 6,716 3.6 179,075 96.4 185,791 Table 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census-2003 Appendix II 190 No of households % No of households % Tarime 2,651 3.4 75,443 96.6 78,094 Serengeti 3,987 14.5 23,601 85.5 27,588 Musoma Rural 6,030 12.3 42,993 87.7 49,023 Bunda 8,869 28.9 21,777 71.1 30,646 Musoma Urban 50 11.3 391 88.7 440 Total 21,587 11.6 164,204 88.4 185,791 No of households % No of households % Tarime 0 0.0 78,094 100.0 78,094 Serengeti 0 0.0 27,588 100.0 27,588 Musoma Rural 207 0.4 48,816 99.6 49,023 Bunda 0 0.0 30,646 100.0 30,646 Musoma Urban 0 0.0 440 100.0 440 Total 207 0.1 185,584 99.9 185,791 No of households % No of households % Tarime 14,395 18.4 63,698 81.6 78,094 Serengeti 4,554 16.5 23,035 83.5 27,588 Musoma Rural 12,206 24.9 36,817 75.1 49,023 Bunda 11,257 36.7 19,389 63.3 30,646 Musoma Urban 118 26.9 322 73.1 440 Total 42,530 22.9 143,261 77.1 185,791 Table 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Tanzania Agriculture Sample Census-2003 Appendix II 191 Number % Number % Number % Number % Tarime 1,995 2.5 0 0.0 132 0.2 77,043 97.3 79,170 Serengeti 70 0.2 65 0.2 0 0.0 27,730 99.5 27,864 Musoma Rural 575 1.1 0 0.0 0 0.0 49,421 98.9 49,995 Bunda 78 0.3 0 0.0 0 0.0 30,642 99.7 30,721 Musoma Urban 18 4.0 0 0.0 0 0.0 435 96.0 453 Total 2,735 1.5 65 0.0 132 0.1 185,271 98.4 188,203 Number % Number % Number % Number % Number % Tarime 132 0 0 0 124 0 132 0 0 0 Serengeti 0 0 209 1 66 0 0 0 0 0 Musoma Rural 0 0 117 0 0 0 0 0 116 0 Bunda 0 0 0 0 0 0 0 0 0 0 Musoma Urban 0 0 0 0 12 3 0 0 0 0 Total 132 0 327 0 203 0 132 0 116 0 Number % Number % Number % Number % Tarime 15,040 19 10,251 13 135 0 53,356 67 79,170 Serengeti 3,471 12 2,060 7 0 0 22,127 79 27,934 Musoma Rural 3,900 8 7,142 14 0 0 38,719 77 49,995 Bunda 2,444 8 3,058 10 0 0 25,219 82 30,721 Musoma Urban 79 18 25 5 0 0 337 74 453 Total 24,935 13 22,535 12 135 0 139,759 74 188,273 District Other Not applicable District Co-operative Local Farmers Group Local Market / Trade Store Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Local Market / Trade Store Locally Produced by Household Neighbour Not applicable Total Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year cont…..Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year Neighbour Locally Produced by Household Total Secondary Market Development Project Tanzania Agriculture Sample Census-2003 Appendix II 192 Number % Number % Number % Number % Number % Tarime 1,081 1.4 135 0.2 270 0.3 135 0.2 135 0.2 Serengeti 70 0.3 0 0.0 0 0.0 0 0.0 0 0.0 Musoma Rural 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Bunda 78 0.3 0 0.0 0 0.0 0 0.0 0 0.0 Musoma Urban 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 1,229 0.7 135 0.1 270 0.1 135 0.1 135 0.1 Number % Number % Number % Tarime 1,332 1.7 406 0.5 75,675 95.6 79,170 Serengeti 198 0.7 0 0.0 27,527 99.0 27,794 Musoma Rural 1,354 2.7 273 0.5 48,368 96.7 49,995 Bunda 1,248 4.1 0 0.0 29,395 95.7 30,721 Musoma Urban 0 0.0 0 0.0 453 100.0 453 Total 4,132 2.2 678 0.4 181,417 96.4 188,133 Number % Number % Number % Number % Number % Number % Tarime 0 0.0 130 0.2 2,262 2.9 134 0.2 124 0.2 0 0.0 Serengeti 0 0.0 0 0.0 944 3.4 0 0.0 0 0.0 3,043 10.9 Musoma Rural 117 0.2 111 0.2 3,801 7.6 117 0.2 0 0.0 1,767 3.5 Bunda 1,248 4.1 148 0.5 4,955 16.1 0 0.0 0 0.0 2,444 8.0 Musoma Urban 0 0.0 0 0.0 50 11.0 0 0.0 0 0.0 0 0.0 Total 1,365 0.7 389 0.2 12,012 6.4 251 0.1 124 0.1 7,254 3.9 Development Project Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Secondary Market District Co-operative Local Market / Trade Store Crop Buyers Secondary Market Local Market / Trade Store Not applicable District District Local Farmers Group Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Total cont... Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Locally Produced by Household Neighbour Co-operative Local Farmers Group Development Project Tanzania Agriculture Sample Census-2003 Appendix II 193 Number % Number % Number % Tarime 0 0.0 0 0.0 76,518 96.7 79,170 Serengeti 0 0.0 0 0.0 23,877 85.7 27,864 Musoma Rural 117 0.2 0 0.0 43,965 87.9 49,995 Bunda 0 0.0 74 0.2 21,852 71.1 30,721 Musoma Urban 0 0.0 0 0.0 404 89.0 453 Total 117 0.1 74 0.0 166,616 88.5 188,203 Number % Number % Number % Tarime 0 0.0 0 0.0 79,170 100.0 79,170 Serengeti 0 0.0 0 0.0 27,933 100.0 27,933 Musoma Rural 117 0.2 90 0.2 49,788 99.6 49,995 Bunda 0 0.0 0 0.0 30,721 100.0 30,721 Musoma Urban 0 0.0 0 0.0 453 100.0 453 Total 117 0.1 90 0.0 188,065 99.9 188,272 cont...Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Total Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year Locally Produced by Household District Co-operative Local Market / Trade Store Not applicable Neighbour Not applicable District Tanzania Agriculture Sample Census-2003 Appendix II 194 Number % Number % Number % Number % Number % Number % Number % Number % Number % Tarime 135 0.2 234 0.3 12,428 15.7 407 0.5 124 0.2 0 0.0 0 0.0 131 0.2 805 1.0 Serengeti 69 0.2 70 0.3 954 3.4 69 0.2 70 0.3 3,042 10.9 70 0.2 140 0.5 70 0.3 Musoma Rural 933 1.9 466 0.9 4,275 8.6 0 0.0 456 0.9 3,516 7.0 0 0.0 464 0.9 2,096 4.2 Bunda 3,958 12.9 381 1.2 2,262 7.4 0 0.0 74 0.2 4,346 14.1 79 0.3 0 0.0 157 0.5 Musoma Urban 0 0.0 0 0.0 86 18.9 0 0.0 7 1.4 0 0.0 0 0.0 0 0.0 26 5.7 Total 5,094 2.7 1,151 0.6 20,006 10.6 476 0.3 731 0.4 10,905 5.8 148 0.1 735 0.4 3,154 1.7 Number % Number % Tarime 131 0.2 64,774 81.8 79,170 Serengeti 0 0.0 23,311 83.7 27,864 Musoma Rural 0 0.0 37,789 75.6 49,995 Bunda 0 0.0 19,463 63.4 30,721 Musoma Urban 0 0.0 335 73.9 453 Total 131 0.1 145,673 77.4 188,203 Number % Number % Number % Number % Number % Tarime 132 6 400 19 131 6 948 45 515 24 2,127 Serengeti 65 48 0 0 70 52 0 0 0 0 134 Musoma Rural 117 20 0 0 225 39 115 20 117 20 575 Bunda 0 0 0 0 0 0 78 100 0 0 78 Musoma Urban 0 0 0 0 18 100 0 0 0 0 18 Total 313 11 400 14 444 15 1,142 39 632 22 2,932 Large Scale Farm Locally Produced by Household 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year Neighbour District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers District Between 10 and 20 km 20 km and Above Other cont...12.1.12 ACCESS TO INPUTS: Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Total Not applicable Tanzania Agriculture Sample Census-2003 Appendix II 195 Number % Number % Number % Number % Number % Tarime 25,553 91 1,703 6 572 2 0 0 141 1 27,968 Serengeti 11,276 95 387 3 201 2 0 0 0 0 11,865 Musoma Rural 6,512 80 815 10 813 10 0 0 0 0 8,140 Bunda 31,310 95 1,141 3 370 1 0 0 229 1 33,050 Musoma Urban 12,337 78 2,594 16 689 4 194 1 0 0 15,814 Total 86,988 90 6,640 7 2,645 3 194 0 370 0 96,837 Between 10 and 20 km 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Tanzania Agriculture Sample Census-2003 Appendix II 196 Number % Number % Number % Number % Tarime 21,953 85 2,923 11 538 2 400 2 25,814 Serengeti 4,988 86 480 8 209 4 129 2 5,807 Musoma Rural 9,748 86 1,411 13 117 1 0 0 11,276 Bunda 4,799 87 566 10 138 3 0 0 5,502 Musoma Urban 110 94 0 0 7 6 0 0 116 Total 41,597 86 5,380 11 1,009 2 529 1 48,514 Number % Number % Number % Number % Tarime 3,360 96 0 0 135 4 0 0 3,495 Serengeti 133 50 70 26 0 0 65 24 267 Musoma Rural 1,512 93 0 0 115 7 0 0 1,627 Bunda 1,326 100 0 0 0 0 0 0 1,326 Musoma Urban 0 0 0 0 0 0 0 0 0 Total 6,331 94 70 1 251 4 65 1 6,716 Number % Number % Number % Number % Number % Tarime 3,747 26 3,222 22 3,084 21 2,412 17 1,930 13 14,395 Serengeti 954 21 1,319 29 1,591 35 136 3 553 12 4,554 Musoma Rural 5,078 42 2,864 23 2,353 19 1,040 9 870 7 12,206 Bunda 3,471 31 4,496 40 2,137 19 691 6 462 4 11,257 Musoma Urban 13 11 25 21 68 57 0 0 13 11 118 Total 13,263 31 11,926 28 9,234 22 4,280 10 3,828 9 42,530 Total Number District Less than 1 km Between 1 and 3 km Total Number 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Between 10 and 20 km Between 3 and 10 km 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Total Between 10 and 20 km Tanzania Agriculture Sample Census-2003 Appendix II 197 Number % Number % Number % Number % Number % Tarime 396 15 652 25 531 20 936 35 135 5 2,651 Serengeti 884 22 1,307 33 1,592 40 136 3 68 2 3,987 Musoma Rural 1,352 22 1,384 23 1,026 17 797 13 1,470 24 6,030 Bunda 1,685 19 2,708 31 2,307 26 1,557 18 612 7 8,869 Musoma Urban 0 0 7 13 43 87 0 0 0 0 50 Total 4,317 20 6,058 28 5,499 25 3,427 16 2,285 11 21,587 Number % Number % Number % Number % Number % Number % Number % Tarime 14,049 18 54,921 71 1,576 2 269 0 1,823 2 2,577 3 1,828 2 77,043 Serengeti 12,463 45 11,643 42 416 1 0 0 1,303 5 1,085 4 821 3 27,730 Musoma Rural 16,027 32 27,498 56 460 1 114 0 688 1 3,939 8 694 1 49,421 Bunda 16,529 54 11,238 37 472 2 80 0 706 2 1,086 4 532 2 30,642 Musoma Urban 0 0 316 73 12 3 0 0 72 17 35 8 0 0 435 Total 59,068 32 105,616 57 2,936 2 463 0 4,592 2 8,721 5 3,875 2 185,271 Too Much Labour Required Do not Know How to Use Total 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Input is of No Use Other District Not Available Price Too High No Money to Buy 20 km and Above 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total Number Less than 1 km District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Tanzania Agriculture Sample Census-2003 Appendix II 198 Number % Number % Number % Number % Number % Number % Number % Number % Tarime 8,141 15 4,621 9 28,503 53 4,933 9 1,994 4 2,424 5 134 0 2,607 5 53,356 Serengeti 1,422 6 1,093 5 12,783 58 1,111 5 971 4 2,764 12 0 0 1,985 9 22,127 Musoma Rural 9,599 25 7,271 19 14,782 38 3,516 9 113 0 2,630 7 116 0 692 2 38,719 Bunda 6,308 25 1,726 7 13,791 55 1,154 5 550 2 1,078 4 0 0 612 2 25,219 Musoma Urban 23 7 178 53 46 13 0 0 67 20 12 4 0 0 12 3 337 Total 25,493 18 14,889 11 69,904 50 10,714 8 3,694 3 8,908 6 250 0 5,907 4 139,759 Number % Number % Number % Number % Number % Number % Number % Number % Tarime 8,601 11 7,968 11 34,310 45 3,163 4 16,710 22 2,062 3 130 0 2,729 4 75,675 Serengeti 2,698 10 1,577 6 12,489 45 409 1 5,603 20 3,108 11 269 1 1,375 5 27,527 Musoma Rural 2,681 6 8,797 18 22,194 46 1,061 2 9,155 19 3,553 7 0 0 926 2 48,368 Bunda 5,734 20 1,544 5 9,824 33 1,558 5 8,661 29 1,000 3 148 1 926 3 29,395 Musoma Urban 47 10 46 10 235 52 0 0 113 25 12 3 0 0 0 0 453 Total 19,760 11 19,932 11 79,054 44 6,190 3 40,242 22 9,735 5 548 0 5,957 3 181,417 Too Much Labour Required Too Much Labour Required Do not Know How to Use Locally Produced by Household Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Total Price Too High No Money to Buy Do not Know How to Use Input is of No Use Not Available Price Too High 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Total Locally Produced by Household Other No Money to Buy Input is of No Use Tanzania Agriculture Sample Census-2003 Appendix II 199 Number % Number % Number % Number % Number % Number % Number % Tarime 6,207 8 48,165 63 1,604 2 532 1 3,770 5 11,627 15 4,612 6 76,518 Serengeti 5,726 24 13,487 56 347 1 0 0 2,187 9 1,649 7 482 2 23,877 Musoma Rural 7,302 17 26,075 59 1,149 3 0 0 2,008 5 6,848 16 582 1 43,965 Bunda 6,168 28 11,198 51 549 3 0 0 769 4 2,403 11 766 4 21,852 Musoma Urban 12 3 271 67 12 3 0 0 67 17 42 10 0 0 404 Total 25,415 15 99,196 60 3,662 2 532 0 8,801 5 22,569 14 6,442 4 166,616 Number % Number % Number % Number % Number % Number % Number % Number % Tarime 8,323 11 51,343 65 1,201 2 398 1 4,350 5 10,815 14 270 0 2,470 3 79,170 Serengeti 7,739 28 14,381 51 481 2 0 0 3,218 12 1,425 5 0 0 689 2 27,933 Musoma Rural 11,025 22 24,408 49 1,153 2 0 0 3,617 7 9,006 18 0 0 580 1 49,788 Bunda 16,306 53 7,806 25 709 2 0 0 3,043 10 2,085 7 0 0 772 3 30,721 Musoma Urban 31 7 295 65 30 7 0 0 72 16 25 6 0 0 0 0 453 Total 43,424 23 98,233 52 3,575 2 398 0 14,299 8 23,355 12 270 0 4,510 2 188,065 Number % Number % Number % Number % Number % Number % Number % Tarime 12,264 19 45,010 69 1,081 2 116 0 942 1 1,117 2 4,245 7 64,774 Serengeti 6,133 26 14,972 64 485 2 0 0 760 3 409 2 551 2 23,311 Musoma Rural 12,083 32 22,012 58 804 2 226 1 446 1 1,529 4 690 2 37,789 Bunda 10,579 54 7,583 39 313 2 160 1 0 0 376 2 453 2 19,463 Musoma Urban 72 22 190 57 0 0 0 0 61 18 12 4 0 0 335 Total 41,132 28 89,767 62 2,682 2 502 0 2,209 2 3,443 2 5,938 4 145,673 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Total Price Too High No Money to Buy Other Input is of No Use Input is of No Use Other 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Input is of No Use Too Much Labour Required Do not Know How to Use District Not Available Price Too High No Money to Buy Too Much Labour Required Total Other Do not Know How to Use Locally Produced by Household Total Tanzania Agriculture Sample Census-2003 Appendix II 200 Number % Number % Tarime 1,205 57 922 43 2,127 Serengeti 65 48 70 52 134 Musoma Rural 225 39 349 61 575 Bunda 0 0 78 100 78 Musoma Urban 12 64 7 36 18 Total 1,506 51 1,426 49 2,932 Number % Number % Number % Tarime 11,647 45 12,684 49 1,482 6 25,814 Serengeti 2,015 35 3,658 63 133 2 5,807 Musoma Rural 3,962 35 6,075 54 1,238 11 11,276 Bunda 1,186 22 4,241 77 75 1 5,502 Musoma Urban 77 66 33 28 7 6 116 Total 18,888 39 26,692 55 2,935 6 48,514 Number % Number % Number % Tarime 1,619 46 1,741 50 135 4 3,495 Serengeti 65 24 203 76 0 0 267 Musoma Rural 276 17 815 50 536 33 1,627 Bunda 778 59 468 35 80 6 1,326 Musoma Urban 0 0 0 0 0 0 0 Total 2,737 41 3,227 48 751 11 6,716 Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total District Excellent Good Average District Excellent Good Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Appendix II 201 Number % Number % Number % Number % Number % Tarime 1,327 50 1,192 45 132 5 0 0 0 0 2,651 Serengeti 410 10 3,101 78 133 3 66 2 278 7 3,987 Musoma Rural 802 13 4,304 71 573 9 351 6 0 0 6,030 Bunda 1,889 21 5,608 63 1,297 15 75 1 0 0 8,869 Musoma Urban 12 23 38 77 0 0 0 0 0 0 50 Total 4,440 21 14,242 66 2,134 10 493 2 278 1 21,587 Number % Number % Tarime 117 57 90 43 207 Serengeti 0 0 0 0 0 Musoma Rural 0 0 0 0 0 Bunda 0 0 0 0 0 Musoma Urban Total 117 57 90 43 207 Number % Number % Number % Number % Number % Number % Tarime 3,999 28 9,856 68 541 4 0 0 14,395 Tarime 7,830 10 71,340 90 79,170 Serengeti 956 21 3,252 71 346 8 0 0 4,554 Serengeti 1,837 7 26,027 93 27,864 Musoma Rural 2,129 17 7,612 62 2,465 20 0 0 12,206 Musoma Rural 6,214 12 43,782 88 49,995 Bunda 1,119 10 7,677 68 2,387 21 75 1 11,257 Bunda 4,704 15 26,016 85 30,721 Musoma Urban 48 40 71 60 0 0 0 0 118 Musoma Urban 25 5 429 95 453 Total 8,251 19 28,467 67 5,738 13 75 0 42,530 Total 20,610 11 167,593 89 188,203 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year Total District Excellent Good Average District Excellent Good 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year Total District District Excellent Good Average Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Total Tanzania Agriculture Sample Census-2003 Appendix II 202 Number % Number % Number % Number % Tarime 51,924 66 27,246 34 79,170 Tarime 6,913 9 72,257 91 79,170 Serengeti 16,552 59 11,382 41 27,934 Serengeti 6,216 22 21,579 78 27,794 Musoma Rural 25,927 52 24,068 48 49,995 Musoma Rural 9,223 18 40,772 82 49,995 Bunda 15,669 51 15,051 49 30,721 Bunda 3,604 12 27,116 88 30,721 Musoma Urban 141 31 313 69 453 Musoma Urban 26 6 427 94 453 Total 110,213 59 78,059 41 188,273 Total 25,982 14 162,151 86 188,133 Number % Number % Number % Number % Tarime 7,641 10 71,528 90 79,170 Tarime 1,713 2 77,457 98 79,170 Serengeti 6,403 23 21,461 77 27,864 Serengeti 2,118 8 25,815 92 27,933 Musoma Rural 13,112 26 36,883 74 49,995 Musoma Rural 3,654 7 46,341 93 49,995 Bunda 18,884 61 11,837 39 30,721 Bunda 3,556 12 27,165 88 30,721 Musoma Urban 50 11 404 89 453 Musoma Urban 0 0 453 100 453 Total 46,090 24 142,113 76 188,203 Total 11,041 6 177,231 94 188,272 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use COMPOST ManureNext Year Agricultural Households With NO Plan to use COMPOST Manure Next Year Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Herbicides Next Year Agricultural Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census-2003 Appendix II 203 Number % Number % Tarime 34,973 44 44,196 56 79,170 Serengeti 11,920 43 15,944 57 27,864 Musoma Rural 28,167 56 21,828 44 49,995 Bunda 19,372 63 11,348 37 30,721 Musoma Urban 142 31 312 69 453 Total 94,574 50 93,629 50 188,203 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Improved Seeds Next Year Agricultural Households With NO Plan to use Improved Seeds Next Year Total Tanzania Agriculture Sample Census-2003 Appendix II 204 AGRICULTURE CREDIT Tanzania Agriculture Sample Census-2003 Appendix II 205 Number % Number % Tarime 0 0 0 0 0 Serengeti 419 75 140 25 559 Musoma Rural 0 0 117 100 117 Bunda 0 0 0 0 0 Musoma Urban 0 0 0 0 0 Total 419 62 256 38 675 Family, Friend and Relative Saving & Credit Society Trader / Trade Store Tarime 0 0 0 0 Serengeti 70 0 489 559 Musoma Rural 0 117 0 117 Bunda 0 0 0 0 Musoma Urban 0 0 0 0 Total 70 117 489 675 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucrac y procedure Credit granted too late Other Don't know about credit Total Tarime 3,427 6,117 3,692 4,115 35,153 3,790 405 542 21,929 79,170 Serengeti 1,658 3,130 2,664 267 12,755 271 339 70 6,151 27,306 Musoma Rural 3,048 5,383 9,038 232 20,235 896 346 115 10,586 49,878 Bunda 849 4,144 1,866 461 14,588 463 0 0 8,350 30,721 Musoma Urban 257 7 38 0 91 12 0 0 50 453 Total 9,237 18,781 17,298 5,075 82,822 5,432 1,090 727 47,065 187,528 District Agro-chemicals Tools / Equipment Livestock Other Total Credits Tarime 489 70 70 0 628 Serengeti 0 0 0 0 0 Musoma Rural 0 0 0 117 117 Bunda 0 0 0 0 0 Musoma Urban 0 0 0 0 0 Total Credits 489 70 70 117 745 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District Total Source of Credit 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year Total District Male Female Tanzania Agriculture Sample Census-2003 Appendix II 206 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census-2003 Appendix II 207 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Tarime 25,843 101,077 . 1,813 17,119 1,637,546 265,077 13,646 . 811 14,879 . Serengeti 38,255 32,392 2,786 5,736 . 150,968 4,017 13,666 766 . . . Musoma Rural 22,394 246,296 2,755 2,557 4,279 16,267 52,788 52,750 4,318 19,104 . 359 Bunda 14,798 7,333 60 22,243 1,589 2,798 2,532 464 . 465 . . Musoma Urban 325 1,825 . 195 45 12 69 451 127 . . . Total 101,615 388,923 5,601 32,544 23,032 1,807,591 324,484 80,978 5,211 20,380 14,879 359 % 2 9 0 1 1 40 7 2 0 0 0 0 District Terminalia Ivorensis Maesopsis Berchemoide s Leucena Spp Syszygium Spp Azadrachta Spp Jakaranda Spp Albizia Spp Kyaya Spp Sesbania Spp Calliandra Spp Moringa Spp Trichilia Spp Total Tarime . 1,330 16,351 2,706 22,394 1,481 16,597 . 88,946 4,735 1,731 1,364,411 3,598,493 Serengeti . 1,257 1,676 209 16,819 33,142 759 69 . . 4,189 4,957 311,664 Musoma Rural 2,196 576 3,870 2,782 44,475 5,419 25,163 4,301 16,008 . 1,357 . 530,013 Bunda 78 . 11,165 154 23,270 157 4,763 942 863 148 137 1,996 95,956 Musoma Urban . . . 778 83 . . . . . 46 . 3,958 Total 2,274 3,162 33,062 6,629 107,041 40,199 47,282 5,312 105,817 4,883 7,462 1,371,363 4,540,084 % 0 0 1 0 2 1 1 0 2 0 0 30 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Household s Number of Trees Tarime 6,373 842,908 2,928 811,226 3,852 1,944,359 13,153 3,598,493 Serengeti 1,164 32,870 4,205 265,897 346 12,897 5,715 311,664 Musoma Rural 13,603 209,822 7,904 190,766 1,267 126,734 22,773 527,321 Bunda 5,443 37,899 6,244 56,800 158 1,257 11,845 95,956 Musoma Urban 74 2,549 116 1,409 0 . 190 3,958 Total 26,656 1,126,048 21,397 1,326,097 5,623 2,085,247 53,675 4,537,392 63132578 74348506 116910709 254391794 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Tarime 10,215 4,494 0 3,596 930 1,195 135 20,566 Serengeti 2,294 2,800 0 2,553 757 417 70 8,890 Musoma Rural 25,625 1,369 116 3,380 1,887 935 662 33,974 Bunda 7,949 134 74 4,453 2,550 351 232 15,742 Musoma Urban 196 0 0 31 108 12 0 347 Total 46,280 8,797 190 14,012 6,232 2,910 1,099 79,520 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Mara Region District Main Use 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mara Region cont… ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mara Region 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Mara Region Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census-2003 Appendix II 208 CROP EXTENSION Tanzania Agriculture Sample Census-2003 Appendix II 209 Number % Number % Tarime 14,524 18 64,645 82 79,170 Serengeti 6,308 23 21,556 77 27,864 Musoma Rural 23,549 47 26,446 53 49,995 Bunda 18,303 60 12,418 40 30,721 Musoma Urban 115 25 338 75 453 Total 62,800 33 125,403 67 188,203 Number % Number % Number % Number % Number % Tarime 2,785 19 8,928 61 2,812 19 0 0 14,524 100 Serengeti 764 12 3,952 63 1,247 20 276 4 6,239 100 Musoma Rural 2,244 10 13,301 56 7,889 34 116 0 23,549 100 Bunda 818 4 13,916 76 3,335 18 155 1 18,224 100 Musoma Urban 24 21 78 68 13 11 0 0 115 100 Total 6,635 11 40,174 64 15,296 24 547 1 62,652 100 Number % Number % Number % Number % Number % Number % Number % Tarime 12,382 88 1,468 10 0 0 134 1 134 1 0 0 14,119 100 Serengeti 5,960 99 70 1 0 0 0 0 0 0 0 0 6,030 100 Musoma Rural 22,196 95 681 3 108 0 115 0 0 0 331 1 23,432 100 Bunda 17,909 99 157 1 80 0 0 0 0 0 0 0 18,146 100 Musoma Urban 83 81 20 19 0 0 0 0 0 0 0 0 103 100 Total 58,531 95 2,395 4 188 0 249 0 134 0 331 1 61,830 100 Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Mara Region Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households Poor Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Mara Region 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Very Good Good Average Large Scale Farm Other Not applicable Government NGO / Development Project Cooperative Tanzania Agriculture Sample Census-2003 Appendix II 210 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Tarime 11,712 1,202 0 134 134 0 13,182 79,170 17 Serengeti 5,129 0 0 0 0 0 5,129 27,864 18 Musoma Rural 20,224 221 108 0 0 331 20,885 49,995 42 Bunda 16,751 0 80 0 0 0 16,831 30,721 55 Musoma Urban 83 7 0 0 0 0 90 453 20 Total 53,899 1,430 188 134 134 331 56,117 188,203 30 Government NGO / Developme nt Project Large Scale Farm Not applicable Total Tarime 4,938 405 0 406 5,748 79,170 7 Serengeti 2,016 0 0 0 2,016 27,864 7 Musoma Rural 9,309 768 117 339 10,533 49,995 21 Bunda 10,038 0 0 80 10,118 30,721 33 Musoma Urban 24 0 0 0 24 453 5 Total 26,324 1,173 117 825 28,439 188,203 15 Government NGO / Developme nt Project Large Scale Farm Not applicable Total Tarime 3,451 1,875 133 270 5,730 79,170 7 Serengeti 1,253 0 0 0 1,253 27,864 4 Musoma Rural 10,606 1,287 0 116 12,010 49,995 24 Bunda 4,518 385 0 80 4,982 30,721 16 Musoma Urban 60 18 0 0 78 453 17 Total 19,887 3,565 133 466 24,052 188,203 13 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region % of total number of households Total Number of Agriculture Households Total Number of Agriculture Households Use of Agrochemicals District Total Number of Agriculture Households 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region District Erosion Control 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region District Spacing % of total number of households % of total number of households Tanzania Agriculture Sample Census-2003 Appendix II 211 Government NGO / Development Project Large Scale Farm Not applicable Total Tarime 8,233 1,607 264 136 10,240 79,170 13 Serengeti 3,473 0 0 70 3,543 27,864 13 Musoma Rural 16,175 698 117 116 17,106 49,995 34 Bunda 10,520 304 0 66 10,891 30,721 35 Musoma Urban 59 13 0 0 72 453 16 Total 38,460 2,623 381 388 41,853 188,203 22 Government NGO / Development Project Not applicable Total Tarime 3,972 266 135 4,374 79,170 6 Serengeti 419 66 0 485 27,864 2 Musoma Rural 2,233 233 116 2,583 49,995 5 Bunda 2,264 0 309 2,573 30,721 8 Musoma Urban 12 0 0 12 453 3 Total 8,901 566 560 10,026 188,203 5 Government NGO / Development Project Cooperative Not applicable Total Tarime 8,387 1,069 0 0 9,456 79,170 12 Serengeti 3,961 140 0 70 4,170 27,864 15 Musoma Rural 17,324 388 108 301 18,121 49,995 36 Bunda 12,550 0 0 0 12,550 30,721 41 Musoma Urban 60 7 0 0 67 453 15 Total 42,282 1,603 108 371 44,364 188,203 24 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Organic Fertilizer Use Inorganic Fertilizer Use 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture District Total Number of Agriculture Households Total Number of Agriculture Households % of total number of households % of total number of households District Total Number of Agriculture Households Use of Improved Seed 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region District % of total number of households Tanzania Agriculture Sample Census-2003 Appendix II 212 Government NGO / Development Project Not applicable Total Tarime 405 134 0 539 79,170 1 Serengeti 489 0 0 489 27,864 2 Musoma Rural 718 0 116 835 49,995 2 Bunda 752 0 80 831 30,721 3 Musoma Urban 0 0 0 0 453 0 Total 2,363 134 196 2,694 188,203 1 Government NGO / Development Project Not applicable Total Tarime 1,596 400 0 1,996 79,170 3 Serengeti 622 0 0 622 27,864 2 Musoma Rural 2,867 575 116 3,558 49,995 7 Bunda 1,004 77 158 1,240 30,721 4 Musoma Urban 0 7 0 7 453 1 Total 6,089 1,059 275 7,423 188,203 4 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tarime 6,314 535 0 0 132 6,981 79,170 9 Serengeti 3,828 0 0 0 0 3,828 27,864 14 Musoma Rural 12,598 0 349 302 0 13,249 49,995 26 Bunda 7,763 0 0 0 80 7,843 30,721 26 Musoma Urban 12 0 0 0 0 12 453 3 Total 30,515 535 349 302 211 31,912 188,203 17 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Crop Storage District District District Total Number of Agriculture Households % of total number of households % of total number of households % of total number of households Total Number of Agriculture Households Mechanisation / LST 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Irrigation Technology Total Number of Agriculture Households Tanzania Agriculture Sample Census-2003 Appendix II 213 Government NGO / Development Project Large Scale Farm Not applicable Total Tarime 2,279 129 0 0 2,408 79,170 3 Serengeti 973 0 0 0 973 27,864 3 Musoma Rural 6,840 0 349 0 7,189 49,995 14 Bunda 2,466 77 0 155 2,698 30,721 9 Musoma Urban 24 0 0 0 24 453 5 Total 12,582 206 349 155 13,291 188,203 7 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tarime 2,408 399 0 0 0 2,807 79,170 4 Serengeti 2,718 0 0 0 0 2,718 27,864 10 Musoma Rural 6,901 465 467 694 115 8,643 49,995 17 Bunda 4,242 0 0 0 160 4,402 30,721 14 Musoma Urban 12 0 0 0 0 12 453 3 Total 16,281 864 467 694 275 18,581 188,203 10 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tarime 2,263 1,735 0 0 0 3,998 79,170 5 Serengeti 900 0 0 0 0 900 27,864 3 Musoma Rural 3,978 7,554 117 116 0 11,766 49,995 24 Bunda 1,594 1,487 0 0 80 3,161 30,721 10 Musoma Urban 60 20 0 0 0 79 453 17 Total 8,794 10,795 117 116 80 19,903 188,203 11 % of total number of households Total Number of Agriculture Households % of total number of households Total Number of Agriculture Households % of total number of households 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Total Number of Agriculture Households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Vermin Control District Agro-progressing Agro-forestry District District Tanzania Agriculture Sample Census-2003 Appendix II 214 Government NGO / Developme nt Project Large Scale Farm Not applicable Total Tarime 259 532 0 0 791 79,170 1 Serengeti 209 0 0 0 209 27,864 1 Musoma Rural 813 234 117 116 1,279 49,995 3 Bunda 152 0 0 80 232 30,721 1 Musoma Urban 0 0 0 0 0 453 0 Total 1,433 765 117 196 2,512 188,203 1 Government NGO / Development Project Not applicable Total Tarime 395 397 0 792 79,170 1 Serengeti 70 0 0 70 27,864 0 Musoma Rural 1,266 818 0 2,084 49,995 4 Bunda 154 0 80 234 30,721 1 Musoma Urban 0 0 0 0 453 0 Total 1,885 1,214 80 3,179 188,203 2 Received Adopted % Received Adopted % Received Adopted % Tarime 13,046 11,827 91 5,342 1,994 37 5,587 3,067 55 Serengeti 5,129 3,523 69 2,078 1,248 60 1,252 694 55 Musoma Rural 20,911 17,661 84 10,419 6,714 64 12,000 11,701 98 Bunda 16,911 15,754 93 10,043 7,949 79 4,985 2,682 54 Musoma Urban 90 90 100 36 36 100 78 78 100 Total 56,086 48,855 87 27,918 17,941 64 23,901 18,222 76 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region District Use of Agrochemicals Erosion Control Spacing 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Mara Region % of total number of households Total Number of Households % of total number of households Total Number of Agriculture Households Beekeeping 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mara Region Fish Farming District District Tanzania Agriculture Sample Census-2003 Appendix II 215 Received Adopted % Received Adopted % Received Adopted % Tarime 10,373 7,013 68 3,831 1,725 45 9,866 5,435 55 Serengeti 3,612 1,520 42 554 279 50 4,309 1,728 40 Musoma Rural 16,767 10,278 61 2,266 1,144 50 18,119 12,133 67 Bunda 10,880 5,262 48 2,248 314 14 13,229 10,082 76 Musoma Urban 72 42 59 12 12 100 67 43 64 Total 41,703 24,115 58 8,912 3,474 39 45,589 29,421 65 Received Adopted % Received Adopted % Received Adopted % Tarime 539 134 25 1,725 1,193 69 6,713 5,115 76 Serengeti 349 70 20 552 134 24 3,828 3,549 93 Musoma Rural 535 0 0 2,854 3,035 106 13,132 12,271 93 Bunda 673 295 44 930 629 68 7,763 5,224 67 Musoma Urban 0 0 0 7 19 287 12 24 200 Total 2,096 499 24 6,067 5,010 83 31,448 26,183 83 Received Adopted % Received Adopted % Received Adopted % Tarime 2,148 1,470 68 2,547 2,014 79 3,862 2,922 76 Serengeti 973 764 79 2,649 2,509 95 900 345 38 Musoma Rural 6,256 6,956 111 8,530 9,107 107 11,739 9,499 81 Bunda 2,316 2,306 100 4,163 3,849 92 3,085 1,997 65 Musoma Urban 12 24 205 12 12 100 67 44 65 Total 11,705 11,520 98 17,901 17,491 98 19,653 14,806 75 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Mara Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Mara Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Mara Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology District District District Organic Fertilizer Use Vermin Control Tanzania Agriculture Sample Census-2003 Appendix II 216 Received Adopted % Received Adopted % Tarime 3,862 2,922 76 791 391 49 Serengeti 900 345 38 70 0 0 Musoma Rural 11,739 9,499 81 1,169 117 10 Bunda 3,085 1,997 65 74 156 211 Musoma Urban 67 44 65 0 0 0 Total 19,653 14,806 75 2,103 664 32 Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Mara Region District Beekeeping Tanzania Agriculture Sample Census-2003 217 Appendix II 218 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census-2003 Appendix II 219 Number % Number % Tarime 49,457 62 29,713 38 79,170 Serengeti 14,764 53 13,100 47 27,864 Musoma Rural 13,344 27 36,651 73 49,995 Bunda 11,984 39 18,737 61 30,721 Musoma Urban 0 0 453 100 453 Total 89,548 48 98,655 52 188,203 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Tarime 70,313 167,821 41,905 19,627 27,703 2,612 5,013 4,620 465 Serengeti 38,574 68,653 24,600 6,606 8,132 1,976 6,981 5,776 2,152 Musoma Rural 32,619 74,863 20,106 5,710 13,232 1,902 3,104 2,036 474 Bunda 41,644 65,722 21,062 10,177 8,456 3,169 15,600 1,483 363 Musoma Urban 0 0 0 0 0 0 0 0 0 Total 183,149 377,058 107,673 42,120 57,522 9,659 30,698 13,915 3,453 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Tarime 12,133 907 472 107,086 201,051 45,454 Serengeti 690 133 183 52,851 82,694 28,911 Musoma Rural 116 585 24 41,549 90,716 22,506 Bunda 319 3,988 0 67,740 79,648 24,594 Musoma Urban 0 0 0 0 0 0 Total 13,259 5,613 679 269,226 454,109 121,465 Number % Number % Number % Kondoa 26,400 55 51,694 37 78,094 42 Mpwapwa 4,774 10 22,814 17 27,588 15 Kongwa 10,304 22 38,718 28 49,023 26 Dodoma Rural 6,073 13 24,573 18 30,646 16 Dodoma Urban 81 0 360 0 440 0 Total 47,632 100 138,159 100 185,791 100 Cows Type of Craft cont...17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mara Region Donkeys Total Type of Craft 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mara Region District 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Mara Region Households Using Draft Animals Household Not Using Draft Animals Total households District Oxen Bulls 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Mara District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census-2003 Appendix II 220 Area (Ha) % Area (Ha) % Area (Ha) % Tarime 14,657 49 538 17 15,195 46 Serengeti 4,758 16 27 1 4,784 14 Musoma Rural 6,531 22 182 6 6,713 20 Bunda 3,765 13 2,470 77 6,234 19 Musoma Urban 83 0 0 0 83 0 Total 29,792 100 3,217 100 33,009 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Mara Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census-2003 221 Appendix II 222 CATTLE PRODUCTION Tanzania Agriculture Sample Census-2003 Appendix II 223 Number % Number % Tarime 31,860 40 47,309 60 79,170 40,352 Serengeti 10,935 39 16,929 61 27,864 12,800 Musoma Rural 11,429 23 38,566 77 49,995 19,468 Bunda 9,094 30 21,627 70 30,721 12,025 Musoma Urban 112 25 342 75 453 179 Total 63,430 34 124,773 66 188,203 84,824 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Tarime 31,593 345,671 98.9 132 264 0.1 1,465 3,588 1.0 31,860 349,523 31.8 Serengeti 10,869 250,983 99.9 0 0 0.0 136 346 0.1 10,935 251,329 22.9 Musoma Rural 11,088 225,012 98.0 0 0 0.0 918 4,706 2.0 11,429 229,719 20.9 Bunda 9,094 267,198 100.0 0 0 0.0 0 0 0.0 9,094 267,198 24.3 Musoma Urban 87 1,143 87.9 0 0 0.0 36 158 12.1 112 1,301 0.1 Total 62,730 1,090,007 99.2 132 264 0.0 2,555 8,797 0.8 63,430 1,099,068 100.0 Number % Number % 1-5 19,804 31 61,461 6 3 6-10 15,791 25 125,968 11 8 11-15 8,182 13 105,066 10 13 16-20 5,673 9 101,155 9 18 21-30 5,559 9 138,698 13 25 31-40 4,253 7 151,590 14 36 41-50 849 1 38,112 3 45 51-60 1,066 2 58,293 5 55 61-100 1,208 2 91,283 8 76 101-150 487 1 63,828 6 131 151+ 557 1 163,616 15 294 Total 63,430 100 1,099,068 100 17 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year,Mara Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture households Total livestock keeping households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size Tanzania Agriculture Sample Census-2003 Appendix II 224 Number % Number % Number % Number % Bulls 171,585 99.6 0 0.0 756 0.4 172,341 15.7 Cows 347,530 99.4 0 0.0 2,137 0.6 349,667 31.8 Steers 165,865 99.7 0 0.0 494 0.3 166,359 15.1 Heifers 190,634 98.4 0 0.0 3,110 1.6 193,744 17.6 Male Calves 107,079 98.7 264 0.2 1,200 1.1 108,543 9.9 Female Calves 107,315 99.0 0 0.0 1,099 1.0 108,414 9.9 Total 1,090,007 99.2 264 0.0 8,797 0.8 1,099,068 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Tarime 67,493 99,146 51,772 52,182 37,419 37,659 345,671 Serengeti 42,503 76,620 39,571 47,968 21,901 22,420 250,983 Musoma Rural 31,218 68,458 30,626 51,209 22,135 21,366 225,012 Bunda 30,262 102,951 43,882 39,013 25,402 25,688 267,198 Musoma Urban 110 354 13 261 222 183 1,143 Total 171,585 347,530 165,865 190,634 107,079 107,315 1,090,007 Bulls Cows Steers Heifers Male Calves Female Calves Total Tarime 0 0 0 0 264 0 264 Serengeti 0 0 0 0 0 0 0 Musoma Rural 0 0 0 0 0 0 0 Bunda 0 0 0 0 0 0 0 Musoma Urban 0 0 0 0 0 0 0 Total 0 0 0 0 264 0 264 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Category of Cattle 18.6 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle Total Tanzania Agriculture Sample Census-2003 Appendix II 225 Bulls Cows Steers Heifers Male Calves Female Calves Total Tarime 396 265 260 399 1,194 1,074 3,588 Serengeti 0 279 0 66 0 0 346 Musoma Rural 347 1,521 235 2,604 0 0 4,706 Bunda 0 0 0 0 0 0 0 Musoma Urban 13 72 0 41 7 25 158 Total 756 2,137 494 3,110 1,200 1,099 8,797 Bulls Cows Steers Heifers Male Calves Female Calves Total Tarime 67,889 99,411 52,032 52,581 38,877 38,733 349,523 Serengeti 42,503 76,899 39,571 48,035 21,901 22,420 251,329 Musoma Rural 31,565 69,979 30,861 53,813 22,135 21,366 229,719 Bunda 30,262 102,951 43,882 39,013 25,402 25,688 267,198 Musoma Urban 123 426 13 302 228 208 1,301 Total 172,341 349,667 166,359 193,744 108,543 108,414 1,099,068 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census-2003 Appendix II 226 GOATS PRODUCTION Tanzania Agriculture Sample Census-2003 Appendix II 227 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Tarime 31,871 235,607 99.1 0 0 0.0 528 2,103 0.9 31,871 237,710 37.5 Serengeti 9,164 103,574 100.0 0 0 0.0 0 0 0.0 9,164 103,574 16.3 Musoma Rural 20,192 167,535 96.7 455 5,118 3.0 227 569 0.3 20,192 173,221 27.3 Bunda 11,207 118,038 100.0 0 0 0.0 0 0 0.0 11,207 118,038 18.6 Musoma Urban 141 1,501 100.0 0 0 0.0 0 0 0.0 141 1,501 0.2 Total 72,575 626,254 98.8 455 5,118 0.8 756 2,672 0.4 72,575 634,044 100.0 Number % Number % 1-4 27,123 37 73,914 12 3 5-9 22,856 31 146,327 23 6 10-14 11,559 16 134,751 21 12 15-19 3,993 6 65,732 10 16 20-24 2,796 4 59,217 9 21 25-29 1,024 1 26,855 4 26 30-39 1,819 3 60,832 10 33 40+ 1,405 2 66,416 10 47 Total 72,575 100 634,044 100 9 Total Goat District 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Herd Size Goat Rearing Households Head of Goats Average Number Per Household Tanzania Agriculture Sample Census-2003 Appendix II 228 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 235,607 99.1 0 0.0 2,103 0.9 237,710 37.5 Castrated Goat 103,574 100.0 0 0.0 0 0.0 103,574 16.3 She Goat 167,535 96.7 5,118 3.0 569 0.3 173,221 27.3 Male Kid 118,038 100.0 0 0.0 0 0.0 118,038 18.6 She Kid 1,501 100.0 0 0.0 0 0.0 1,501 0.2 Total 626,254 98.8 5,118 0.8 2,672 0.4 634,044 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tarime 45,533 8,927 114,577 31,426 35,144 235,607 Serengeti 18,488 7,118 51,078 13,520 13,370 103,574 Musoma Rural 27,272 7,748 86,372 23,801 22,342 167,535 Bunda 21,600 2,334 63,149 14,176 16,778 118,038 Musoma Urban 376 122 680 123 200 1,501 Total 113,269 26,250 315,856 83,045 87,834 626,254 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tarime . . . . . . Serengeti . . . . . . Musoma Rural 691 111 1,929 1,375 1,012 5,118 Bunda . . . . . . Musoma Urban . . . . . . Total 691 111 1,929 1,375 1,012 5,118 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Total Category of Goats 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Improved Dairy Goats Tanzania Agriculture Sample Census-2003 Appendix II 229 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tarime 396 . 1,707 . . 2,103 Serengeti . . . . . . Musoma Rural . . . 229 340 569 Bunda . . . . . . Musoma Urban . . . . . . Total 396 . 1,707 229 340 2,672 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tarime 45,929 8,927 116,284 31,426 35,144 237,710 Serengeti 18,488 7,118 51,078 13,520 13,370 103,574 Musoma Rural 27,964 7,858 88,301 25,405 23,694 173,221 Bunda 21,600 2,334 63,149 14,176 16,778 118,038 Musoma Urban 376 122 680 123 200 1,501 Total 114,356 26,361 319,491 84,649 89,186 634,044 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census-2003 Appendix II 230 SHEEP PRODUCTION Tanzania Agriculture Sample Census-2003 Appendix II 231 Number % Number % Number % Ram 43,318 22 0 0 43,318 22 Castrated Sheep 13,781 7 0 0 13,781 7 She Sheep 91,890 47 0 0 91,890 47 Male Lamb 21,020 11 70 19 21,090 11 She Lamb 23,695 12 300 81 23,995 12 Total 193,704 100 370 100 194,073 100 Number % Number % Tarime 10,514 13 68,656 87 79,170 40,352 Serengeti 4,690 17 23,174 83 27,864 12,800 Musoma Rural 3,137 6 46,858 94 49,995 19,468 Bunda 3,427 11 27,294 89 30,721 12,025 Musoma Urban 12 3 441 97 453 179 Total 21,780 12 166,423 88 188,203 84,824 Number % Number % Number % Tarime 75,196 100 0 0 75,196 39 Serengeti 48,237 100 139 0 48,376 25 Musoma Rural 40,132 99 230 1 40,362 21 Bunda 30,078 100 0 0 30,078 15 Musoma Urban 61 100 0 0 61 0 Total 193,704 100 370 0 194,073 100 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 8,873 41 21,828 11 2 5-9 6,909 32 45,606 23 7 10-14 3,513 16 39,444 20 11 15-19 616 3 9,770 5 16 20-24 632 3 13,311 7 21 25-29 489 2 12,868 7 26 30-39 178 1 6,091 3 34 40+ 570 3 45,156 23 79 Total 21,780 100 194,073 100 9 20.1 Total Number of Sheep By Breed and on 1st October 2003 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households Breed Number of Indigenous District 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census-2003 Appendix II 232 Number of Households Average Number of Households Average Number of Households Average Tarime 10,514 7 0 . 10,514 7 Serengeti 4,690 10 70 2 4,690 10 Musoma Rural 3,137 13 115 2 3,137 13 Bunda 3,427 9 0 . 3,427 9 Musoma Urban 12 5 0 . 12 5 Total 21,780 9 185 2 21,780 9 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tarime 19,724 5,165 33,610 6,964 9,732 75,196 Serengeti 10,124 7,172 21,122 4,433 5,387 48,237 Musoma Rural 7,764 819 20,469 6,110 4,971 40,132 Bunda 5,694 625 16,641 3,514 3,605 30,078 Musoma Urban 12 . 49 . . 61 Total 43,318 13,781 91,890 21,020 23,695 193,704 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tarime . . . . . . Serengeti . . . 70 70 139 Musoma Rural . . . . 230 230 Bunda . . . . . . Musoma Urban . . . . . . Total . . . 70 300 370 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tarime 19,724 5,165 33,610 6,964 9,732 75,196 Serengeti 10,124 7,172 21,122 4,503 5,456 48,376 Musoma Rural 7,764 819 20,469 6,110 5,201 40,362 Bunda 5,694 625 16,641 3,514 3,605 30,078 Musoma Urban 12 . 49 . . 61 Total 43,318 13,781 91,890 21,090 23,995 194,073 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Mara Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census-2003 233 Appendix II 234 PIGS PRODUCTION Tanzania Agriculture Sample Census-2003 Appendix II 235 Number % Number % 1-4 204 62 548 23 3 15-19 124 38 1,861 77 15 Total 328 100 2,409 100 7 District Number of Household Number of Pig Average Number Per Household Tarime 258 2,129 8 Serengeti 70 279 4 Musoma Rural 0 0 0 Bunda 0 0 0 Musoma Urban 0 0 0 Total 328 2,409 7 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Tarime 631 0 258 496 744 2,129 Serengeti 140 0 140 0 0 279 Musoma Rural 0 0 0 0 0 0 Bunda 0 0 0 0 0 0 Musoma Urban 0 0 0 0 0 0 Total 770 0 398 496 744 2,409 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census-2003 Appendix II 236 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census-2003 Appendix II 237 Number of Households % Number of Households % Tarime 19,808 49 20,544 51 40,352 Serengeti 7,524 59 5,275 41 12,800 Musoma Rural 10,435 54 9,034 46 19,468 Bunda 6,283 52 5,742 48 12,025 Musoma Urban 105 59 74 41 179 Total 44,155 52 40,669 48 84,824 Number of Households % Number of Households % Number of Households % Number of Households % Tarime 10,722 42 14,647 48 3,311 37 1,730 31 Serengeti 4,423 17 5,865 19 2,277 25 554 10 Musoma Rural 6,795 26 6,162 20 2,471 27 2,289 41 Bunda 3,800 15 3,748 12 944 10 979 18 Musoma Urban 87 0 62 0 0 0 0 0 Total 25,827 100 30,484 100 9,003 100 5,552 100 Number of Households % Number of Households % Tarime 24,589 70 10,675 30 35,265 Serengeti 8,129 66 4,116 34 12,245 Musoma Rural 12,796 72 4,926 28 17,722 Bunda 7,939 67 3,853 33 11,792 Musoma Urban 136 76 42 24 179 Total 53,589 69 23,613 31 77,202 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Tarime 5,562 23 12,920 53 134 1 1,078 4 4,895 20 24,589 Serengeti 1,382 17 4,061 50 209 3 140 2 2,336 29 8,129 Musoma Rural 1,702 13 8,446 66 221 2 116 1 2,311 18 12,796 Bunda 929 12 4,395 55 1,679 21 238 3 699 9 7,939 Musoma Urban 31 23 66 49 0 0 0 0 39 29 136 Total 9,606 18 29,889 56 2,243 4 1,572 3 10,280 19 53,589 Dipping Smearing Other 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year Method of Tick Control Total District None Spraying District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census-2003 Appendix II 238 Number of Households % Number of Households % Tarime 6,248 17 30,872 83 37,120 Serengeti 4,535 36 7,989 64 12,524 Musoma Rural 1,254 7 17,893 93 19,147 Bunda 1,831 16 9,894 84 11,725 Musoma Urban 0 0 172 100 172 Total 13,868 17 66,820 83 80,688 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Tarime 3,866 62 1,980 32 268 4 0 0 135 2 6,248 Serengeti 2,607 57 1,318 29 129 3 344 8 137 3 4,535 Musoma Rural 803 64 223 18 0 0 113 9 116 9 1,254 Bunda 469 26 1,284 70 78 4 0 0 0 0 1,831 Musoma Urban 0 0 0 0 0 0 0 0 0 0 0 Total 7,745 56 4,804 35 475 3 456 3 387 3 13,868 District Tsetse Flies Problems Total Method of Tsetse Flies Control No Tsetse Flies Problems 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District Total Trapping 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year District None Spray Dipping Other Tanzania Agriculture Sample Census-2003 239 Appendix II 240 OTHER LIVESTOCK Tanzania Agriculture Sample Census-2003 Appendix II 241 Number % Type Number Indigenous 1,505,422 99 Ducks 64,254 Layer 14,561 1 Turkeys 12,737 Broiler 1,183 0 Donkeys 3,104 Rabbits 37,053 Total 1,521,166 100 117,148 Indigenous Chicken Layer Broiler Tarime 585,180 536 268 585,983 Serengeti 246,871 4,607 798 252,277 Musoma Rural 443,135 7,872 0 451,007 Bunda 227,098 1,546 0 228,644 Musoma Urban 3,138 0 117 3,255 Total 1,505,422 14,561 1,183 1,521,166 Ducks Turkeys Rabbit Donkeys Other Tarime 8,963 5,782 1,333 1,071 2,522 Serengeti 4,826 6,955 419 272 4,733 Musoma Rural 40,623 0 34,865 819 9,498 Bunda 8,167 0 437 942 875 Musoma Urban 1,675 0 0 0 0 Total 64,254 12,737 37,053 3,104 17,629 Type of Livestock/Poultry 1995 1999 2003 Number % Cattle 1,291,576 1,272,538 1,099,068 1 - 4 36,629 26 103,477 3 Improved Cattle 1,890 704 9,061 5 - 9 42,208 30 278,665 7 Goats 620,748 578,900 634,044 10 - 19 41,850 30 535,628 13 Sheep 179,019 194,036 194,073 20 - 29 14,714 10 325,261 22 Pigs 5,139 17,481 2,409 30 - 39 3,088 2 98,709 32 Indigenous Chicken 1,369,805 1,368,340 1,505,422 40 - 49 1,511 1 63,439 42 Layers 20,823 61,559 14,561 50 - 99 1,646 1 94,714 58 Broilers 4,426 18,383 1,183 100+ 178 0 21,273 120 Total Chickens 1,395,054 1,448,282 1,521,166 Total 141,825 100 1,521,166 11 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e LIVESTOCK/POULTRY POPULATION TREND Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household 23c Head Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 Type of Livestock Chicken Type Others District Tanzania Agriculture Sample Census-2003 Appendix II 242 FISH FARMING Tanzania Agriculture Sample Census-2003 Appendix II 243 Number % Number % Tarime 255 0.3 78,914 99.7 79,170 Serengeti 0 0.0 27,864 100.0 27,864 Musoma Rural 0 0.0 49,995 100.0 49,995 Bunda 0 0.0 30,721 100.0 30,721 Musoma Urban 0 0.0 453 100.0 453 Total 255 0.1 187,948 99.9 188,203 Dug out Pond Total Tarime 255 255 Total 255 255 NGOs / Project Number Tarime 255 255 Total 255 255 Did not Sell Number Tarime 255 255 Total 255 255 District Number of Tilapia Number of Carp Number of Others Tarime 44,845 0 0 Total 44,845 0 0 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year Total Total District Source of Fingerling 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year District 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year District Fish Farming System 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census-2003 Appendix II 244 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census-2003 Appendix II 245 Number % Number % Tarime 9,373 11.8 69,797 88.2 79,170 40,352 23 Serengeti 2,475 8.9 25,389 91.1 27,864 12,800 19 Musoma Rural 12,675 25.4 37,320 74.6 49,995 19,468 65 Bunda 7,383 24.0 23,338 76.0 30,721 12,025 61 Musoma Urban 73 16.1 381 83.9 453 179 41 Total 31,979 17.0 156,224 83.0 188,203 84,824 38 Number % Number % Number % Number % Number % Tarime 8,762 74.8 1,336 11.4 538 4.6 538 4.6 538 4.6 Serengeti 2,200 66.6 346 10.5 346 10.5 346 10.5 66 2.0 Musoma Rural 11,987 50.1 4,229 17.7 2,596 10.8 3,037 12.7 2,084 8.7 Bunda 7,167 99.0 0 0.0 0 0.0 0 0.0 74 1.0 Musoma Urban 54 100.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 30,171 65.2 5,911 12.8 3,480 7.5 3,921 8.5 2,763 6.0 Other Source of extension advice Total Total Number of households raising livestock % receiving advice out of total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Large Scale Farmer District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Appendix II 246 Government NGO / Development Project Large Scale Farmer Other Total Government NGO / Development Project Other Total Tarime 1,706 131 131 0 1,969 40,352 4.9 Tarime 2,377 131 0 2,509 40,352 6.2 Serengeti 690 66 0 70 826 12,800 6.5 Serengeti 616 136 70 822 12,800 6.4 Musoma Rural 2,417 341 0 0 2,758 19,468 14.2 Musoma Rural 5,390 574 69 6,033 19,468 31.0 Bunda 512 0 0 0 512 12,025 4.3 Bunda 3,525 0 0 3,525 12,025 29.3 Musoma Urban 12 0 0 0 12 179 6.5 Musoma Urban 54 0 0 54 179 30.3 Total 5,336 538 131 70 6,076 84,824 7.2 Total 11,963 842 139 12,943 84,824 15.3 % 87.8 8.9 2.2 1.1 100.0 % 92 7 1 100 Government NGO / Development Project Total Government NGO / Development Project Large Scale Farmer not applicable Total Tarime 2,106 131 2,237 40,352 5.5 Tarime 2,782 131 131 0 3,044 40,352 7.5 Serengeti 346 206 552 12,800 4.3 Serengeti 555 136 0 0 691 12,800 5.4 Musoma Rural 1,084 0 1,084 19,468 5.6 Musoma Rural 1,313 0 0 0 1,313 19,468 6.7 Bunda 2,389 0 2,389 12,025 19.9 Bunda 2,438 0 0 78 2,515 12,025 20.9 Musoma Urban 13 0 13 179 7.3 Musoma Urban 37 0 0 0 37 179 20.6 Total 5,938 337 6,275 84,824 7.4 Total 7,125 267 131 78 7,601 84,824 9.0 % 94.6 5.4 100.0 % 94 4 2 1 100 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year Source of Advice on Milk Hygene 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock Source of Advice on Feeds and Proper Feeding Total Number of households raising livestock Source of Advice on Proper Milking 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year District District % receiving advice out of total District District % receiving advice out of total Total Number of households raising livestock % receiving advice out of total Source of Advice on Housing Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Appendix II 247 Government NGO / Development Project Other Total Tarime 7,539 533 131 8,202 40,352 20 Serengeti 1,860 66 0 1,927 12,800 15 Musoma Rural 9,719 224 0 9,944 19,468 51 Bunda 5,912 0 0 5,912 12,025 49 Musoma Urban 73 0 0 73 179 41 Total 25,103 824 131 26,057 84,824 31 % 96.3 3.2 0.5 100.0 Government NGO / Development Project Large Scale Farmer Other Total Tarime 1,982 131 131 131 2,375 40,352 6 Serengeti 551 66 0 0 617 12,800 5 Musoma Rural 2,389 117 0 0 2,506 19,468 13 Bunda 1,038 0 0 0 1,038 12,025 9 Musoma Urban 0 0 0 0 0 179 0 Total 5,959 315 131 131 6,536 84,824 8 % 91.2 4.8 2.0 2.0 100.0 % receiving advice out of total % receiving advice out of total Total Number of households raising livestock District Source of Advice on Herd/Flock Size 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control Total Number of households raising livestock Tanzania Agriculture Sample Census-2003 Appendix II 248 Government NGO / Development Project Total Tarime 1,333 131 1,464 40,352 4 Serengeti 410 66 476 12,800 4 Musoma Rural 1,019 224 1,244 19,468 6 Bunda 74 0 74 12,025 1 Musoma Urban 7 0 7 179 4 Total 2,842 422 3,264 84,824 4 % 87.1 12.9 100.0 Government NGO / Development Project Co-operative Large Scale Farmer Other not applicable Total Tarime 1,469 266 0 0 0 0 1,736 40,352 4 Serengeti 136 66 140 0 0 0 342 12,800 3 Musoma Rural 4,927 702 0 233 114 0 5,975 19,468 31 Bunda 2,545 74 0 0 0 79 2,698 12,025 22 Musoma Urban 7 0 0 0 0 0 7 179 4 Total 9,084 1,108 140 233 114 79 10,757 84,824 13 % 84.4 10.3 1.3 2.2 1.1 0.7 100.0 Source of Advice on Group Formation and Strenghthening District % receiving advice out of total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Total Number of households raising livestock Total Number of households raising livestock % receiving advice out of total 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year Source of Advice on Pasture Establishment and Selection Tanzania Agriculture Sample Census-2003 Appendix II 249 Government NGO / Development Project Large Scale Farmer Other Total Tarime 2,113 266 0 0 2,379 40,352 6 Serengeti 830 66 0 66 962 12,800 8 Musoma Rural 1,981 0 116 0 2,097 19,468 11 Bunda 2,870 0 0 0 2,870 12,025 24 Musoma Urban 50 0 0 0 50 179 28 Total 7,843 333 116 66 8,359 84,824 10 % 93.8 4.0 1.4 0.8 100.0 Government NGO / Development Project Large Scale Farmer Total Tarime 2,256 131 0 2,387 40,352 6 Serengeti 624 136 0 760 12,800 6 Musoma Rural 1,383 116 117 1,617 19,468 8 Bunda 1,190 0 0 1,190 12,025 10 Musoma Urban 49 0 0 49 179 28 Total 5,503 384 117 6,003 84,824 7 % 91.7 6.4 2.0 100.0 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice on Improved Bulls Total Number of households raising livestock District Source of Advice on Calf Rearing % receiving advice out of total % receiving advice out of total Total Number of households raising livestock 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Appendix II 250 Number % Number % Number % Number % Number % Tarime 3,454 31 6,003 54 1,467 13 132 1 0 0 11,056 Serengeti 278 10 1,785 66 485 18 140 5 0 0 2,688 Musoma Rural 1,882 12 7,412 49 5,513 36 233 2 117 1 15,157 Bunda 729 10 5,825 80 766 10 0 0 0 0 7,320 Musoma Urban 0 0 30 100 0 0 0 0 0 0 30 Total 6,343 17 21,055 58 8,231 23 504 1 117 0 36,251 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census-2003 251 Appendix II 252 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census-2003 Appendix II 253 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads District Capital Tarime 10.7 3.3 2.9 1.3 32.0 9.5 90.7 7.4 16.3 40.2 31.3 43.3 Serengeti 9.5 2.4 5.7 2.9 37.4 5.7 108.7 8.7 12.9 34.5 86.7 36.8 Musoma Rural 10.5 1.9 2.1 0.6 36.9 5.7 43.5 3.4 11.3 36.9 28.5 42.3 Bunda 12.6 1.6 3.6 0.9 27.2 4.8 91.2 4.4 9.6 30.5 36.8 40.9 Musoma Urban 3.7 1.4 0.5 0.7 5.8 3.1 5.8 5.3 27.6 5.3 4.8 5.8 Total 10.8 2.5 3.2 1.3 33.2 7.1 80.7 6.0 13.4 36.8 39.6 41.6 Regional Capital 80.7 District Capital 41.6 Tarmac Roads 39.6 Tertiary Market 36.8 Hospitals 33.2 Secondary Market 13.4 Secondary Schools 10.8 Health Clinics 7.1 Primary Markets 6.0 All weather roads 3.2 Primary Schools 2.5 Feeder Roads 1.3 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census-2003 Appendix II 254 No of households % No of households % No of households % No of households % No of households % Tarime 1,051 1.3 13,746 17.4 46,790 59.1 14,683 18.5 2,900 3.7 79,170 10.7 Serengeti 343 1.2 2,610 9.4 15,650 56.2 7,312 26.2 1,949 7.0 27,864 9.5 Musoma Rural 3,960 7.9 3,899 7.8 18,845 37.7 19,019 38.0 4,273 8.5 49,995 10.5 Bunda 812 2.6 2,616 8.5 11,288 36.7 8,077 26.3 7,928 25.8 30,721 12.6 Musoma Urban 7 1.4 74 16.3 373 82.3 0 0.0 0 0.0 453 3.7 Total 6,172 3.3 22,944 12.2 92,946 49.4 49,090 26.1 17,050 9.1 188,203 10.8 No of households % No of households % No of households % No of households % No of households % Tarime 30,658 38.7 23,047 29.1 22,122 27.9 924 1.2 2,417 3.1 79,170 2.9 Serengeti 3,390 12.2 10,876 39.0 8,911 32.0 2,993 10.7 1,694 6.1 27,864 5.7 Musoma Rural 26,732 53.5 12,816 25.6 9,635 19.3 347 0.7 464 0.9 49,995 2.1 Bunda 9,052 29.5 8,553 27.8 10,347 33.7 2,541 8.3 227 0.7 30,721 3.6 Musoma Urban 380 83.7 41 9.1 33 7.2 0 0.0 0 0.0 453 0.5 Total 70,213 37.3 55,334 29.4 51,048 27.1 6,806 3.6 4,802 2.6 188,203 3.2 No of households % No of households % No of households % No of households % No of households % Tarime 39,268 49.6 27,370 34.6 12,531 15.8 0 0.0 0 0.0 79,170 1.3 Serengeti 7,720 27.7 12,295 44.1 7,376 26.5 279 1.0 194 0.7 27,864 2.9 Musoma Rural 38,894 77.8 8,166 16.3 2,935 5.9 0 0.0 0 0.0 49,995 0.6 Bunda 18,456 60.1 9,358 30.5 2,906 9.5 0 0.0 0 0.0 30,721 0.9 Musoma Urban 260 57.3 187 41.3 7 1.4 0 0.0 0 0.0 453 0.7 Total 104,598 55.6 57,377 30.5 25,755 13.7 279 0.1 194 0.1 188,203 1.3 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year District Distance to Secondary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of households Mean Distance Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km Tanzania Agriculture Sample Census-2003 Appendix II 255 No of households % No of households % No of households % No of households % No of households % Tarime 378 0.5 136 0.2 8,513 10.8 21,950 27.7 48,192 60.9 79,170 32.0 Serengeti 0 0.0 133 0.5 3,847 13.8 5,468 19.6 18,416 66.1 27,864 37.4 Musoma Rural 108 0.2 1,082 2.2 3,324 6.6 12,914 25.8 32,567 65.1 49,995 36.9 Bunda 0 0.0 146 0.5 4,608 15.0 5,181 16.9 20,786 67.7 30,721 27.2 Musoma Urban 0 0.0 0 0.0 453 100.0 0 0.0 0 0.0 453 5.8 Total 486 0.3 1,497 0.8 20,746 11.0 45,513 24.2 119,961 63.7 188,203 33.2 No of households % No of households % No of households % No of households % No of households % Tarime 3,881 4.9 16,306 20.6 48,566 61.3 7,533 9.5 2,883 3.6 79,170 9.5 Serengeti 623 2.2 5,984 21.5 16,619 59.6 4,430 15.9 209 0.7 27,864 5.7 Musoma Rural 5,269 10.5 19,004 38.0 19,718 39.4 4,963 9.9 1,041 2.1 49,995 5.7 Bunda 2,602 8.5 9,776 31.8 16,116 52.5 1,930 6.3 296 1.0 30,721 4.8 Musoma Urban 13 2.9 89 19.7 351 77.4 0 0.0 0 0.0 453 3.1 Total 12,389 6.6 51,160 27.2 101,369 53.9 18,857 10.0 4,429 2.4 188,203 7.1 No of households % No of households % No of households % No of households % No of households % Tarime 14,235 18.0 44,090 55.7 19,645 24.8 524 0.7 676 0.9 79,170 3.3 Serengeti 2,741 9.8 15,671 56.2 9,244 33.2 139 0.5 70 0.2 27,864 2.4 Musoma Rural 13,439 26.9 28,589 57.2 7,397 14.8 230 0.5 340 0.7 49,995 1.9 Bunda 7,707 25.1 17,697 57.6 5,317 17.3 0 0.0 0 0.0 30,721 1.6 Musoma Urban 170 37.5 213 47.0 71 15.6 0 0.0 0 0.0 453 1.4 Total 38,291 20.3 106,260 56.5 41,673 22.1 893 0.5 1,086 0.6 188,203 2.5 Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total number of households 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School 10.0-19.9 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Above 20 km Above 20 km 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Tanzania Agriculture Sample Census-2003 Appendix II 256 No of households % No of households % No of households % No of households % No of households % Tarime 246 0.3 0 0.0 131 0.2 4,205 5.3 74,587 94.2 79,170 90.7 Serengeti 70 0.2 0 0.0 129 0.5 134 0.5 27,531 98.8 27,864 108.7 Musoma Rural 348 0.7 221 0.4 467 0.9 8,200 16.4 40,758 81.5 49,995 43.5 Bunda 60 0.2 0 0.0 158 0.5 80 0.3 30,423 99.0 30,721 91.2 Musoma Urban 0 0.0 0 0.0 453 100.0 0 0.0 0 0.0 453 5.8 Total 724 0.4 221 0.1 1,340 0.7 12,620 6.7 173,298 92.1 188,203 80.7 No of households % No of households % No of households % No of households % No of households % Tarime 129 0.2 136 0.2 5,443 6.9 9,203 11.6 64,258 81.2 79,170 43.3 Serengeti 0 0.0 201 0.7 3,709 13.3 5,333 19.1 18,620 66.8 27,864 36.8 Musoma Rural 233 0.5 0 0.0 698 1.4 8,188 16.4 40,876 81.8 49,995 42.3 Bunda 0 0.0 0 0.0 1,925 6.3 4,009 13.0 24,787 80.7 30,721 40.9 Musoma Urban 0 0.0 0 0.0 453 100.0 0 0.0 0 0.0 453 5.8 Total 362 0.2 337 0.2 12,229 6.5 26,734 14.2 148,541 78.9 188,203 41.6 No of households % No of households % No of households % No of households % No of households % Tarime 1,777 2.2 3,254 4.1 13,659 17.3 19,463 24.6 41,016 51.8 79,170 31.3 Serengeti 0 0.0 129 0.5 274 1.0 198 0.7 27,263 97.8 27,864 86.7 Musoma Rural 4,195 8.4 3,195 6.4 5,245 10.5 11,611 23.2 25,749 51.5 49,995 28.5 Bunda 1,422 4.6 540 1.8 4,117 13.4 3,121 10.2 21,521 70.1 30,721 36.8 Musoma Urban 7 1.4 33 7.2 414 91.4 0 0.0 0 0.0 453 4.8 Total 7,400 3.9 7,151 3.8 23,710 12.6 34,394 18.3 115,548 61.4 188,203 39.6 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census-2003 Appendix II 257 No of households % No of households % No of households % No of households % No of households % Tarime 5,577 7.0 14,593 18.4 38,916 49.2 18,207 23.0 1,877 2.4 79,170 7.4 Serengeti 809 2.9 7,028 25.2 13,753 49.4 3,778 13.6 2,496 9.0 27,864 8.7 Musoma Rural 10,548 21.1 18,580 37.2 19,369 38.7 1,150 2.3 348 0.7 49,995 3.4 Bunda 5,134 16.7 10,685 34.8 12,468 40.6 1,614 5.3 819 2.7 30,721 4.4 Musoma Urban 12 2.7 18 4.0 358 79.0 65 14.3 0 0.0 453 5.3 Total 22,080 11.7 50,904 27.0 84,864 45.1 24,814 13.2 5,541 2.9 188,203 6.0 No of households % No of households % No of households % No of households % No of households % Tarime 774 1.0 263 0.3 9,406 11.9 11,238 14.2 57,489 72.6 79,170 40.2 Serengeti 66 0.2 614 2.2 4,182 15.0 7,302 26.2 15,700 56.3 27,864 34.5 Musoma Rural 913 1.8 1,374 2.7 2,547 5.1 10,067 20.1 35,095 70.2 49,995 36.9 Bunda 322 1.0 1,727 5.6 6,135 20.0 5,494 17.9 17,043 55.5 30,721 30.5 Musoma Urban 23 5.1 12 2.7 418 92.2 0 0.0 0 0.0 453 5.3 Total 2,098 1.1 3,990 2.1 22,688 12.1 34,100 18.1 125,328 66.6 188,203 36.8 No of households % No of households % No of households % No of households % No of households % Tarime 1,475 1.9 3,789 4.8 27,314 34.5 28,503 36.0 18,089 22.8 79,170 16.3 Serengeti 400 1.4 1,081 3.9 14,373 51.6 9,224 33.1 2,786 10.0 27,864 12.9 Musoma Rural 1,963 3.9 2,377 4.8 21,546 43.1 17,306 34.6 6,804 13.6 49,995 11.3 Bunda 916 3.0 2,919 9.5 15,467 50.3 6,546 21.3 4,872 15.9 30,721 9.6 Musoma Urban 0 0.0 0 0.0 12 2.5 23 5.1 419 92.4 453 27.6 Total 4,754 2.5 10,166 5.4 78,711 41.8 61,602 32.7 32,970 17.5 188,203 13.4 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census-2003 Appendix II 258 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 7,321 2 13,139 3 6,441 1 9,759 2 3,659 1 434,698 92 475,017 Serengeti 830 0 5,712 3 4,515 3 5,695 3 15,781 9 134,652 81 167,185 Musoma Rural 2,477 1 536 0 3,521 1 3,680 1 2,042 1 287,716 96 299,971 Bunda 536 0 4,487 2 2,590 1 8,071 4 160 0 168,480 91 184,324 Musoma Urban 24 1 48 2 13 0 12 0 0 0 2,624 96 2,721 Total 11,188 1 23,922 2 17,080 2 27,217 2 21,643 2 1,028,169 91 1,129,218 No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 2,906 28 5,402 51 1,613 15 258 2 366 3 10,546 Serengeti 345 4 3,382 37 1,770 20 1,169 13 2,380 26 9,046 Musoma Rural 408 10 536 13 1,952 46 887 21 418 10 4,202 Bunda 75 1 3,174 54 1,338 23 1,239 21 0 0 5,826 Musoma Urban 0 0 0 0 0 0 0 0 0 0 0 Total 3,735 13 12,494 42 6,673 23 3,554 12 3,164 11 29,619 No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 0 0 940 30 132 4 1,878 59 231 7 3,180 Serengeti 70 1 341 7 455 10 812 17 3,020 64 4,696 Musoma Rural 206 17 0 0 199 17 467 39 324 27 1,196 Bunda 80 4 0 0 158 8 1,709 88 0 0 1,947 Musoma Urban 0 0 0 0 0 0 12 100 0 0 12 Total 356 3 1,280 12 943 9 4,877 44 3,575 32 11,031 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good Total number of households Not applicable Satisfaction of Using Veterinary Clinic 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Appendix II 259 No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 131 5 402 15 132 5 1,607 61 367 14 2,639 Serengeti 0 0 341 8 325 7 807 18 3,018 67 4,491 Musoma Rural 583 43 0 0 116 8 232 17 440 32 1,371 Bunda 0 0 74 4 80 4 1,615 87 80 4 1,848 Musoma Urban 12 100 0 0 0 0 0 0 0 0 12 Total 727 7 817 8 652 6 4,262 41 3,904 38 10,362 No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 266 3 1,608 19 1,350 16 3,743 45 1,434 17 8,401 Serengeti 139 2 691 12 612 10 1,010 17 3,411 58 5,863 Musoma Rural 469 32 0 0 254 18 465 32 255 18 1,442 Bunda 75 3 150 6 625 27 1,408 60 80 3 2,339 Musoma Urban 12 47 0 0 13 53 0 0 0 0 25 Total 960 5 2,449 14 2,854 16 6,625 37 5,180 29 18,069 No of Households % No of Households % No of Households % No of Households % No of Households % Tarime 2,275 30 2,916 38 1,605 21 538 7 363 5 7,697 Serengeti 136 3 340 7 605 13 674 14 2,938 63 4,694 Musoma Rural 117 10 0 0 498 41 230 19 372 31 1,217 Bunda 77 14 158 29 80 14 237 43 0 0 552 Musoma Urban 0 0 0 0 0 0 0 0 0 0 0 Total 2,605 18 3,414 24 2,788 20 1,679 12 3,674 26 14,160 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Appendix II 260 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census-2003 Appendix II 261 Table 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total number of households Tarime 22,708 1,747 53,245 1,335 135 79,170 Serengeti 3,986 903 22,633 342 0 27,864 Musoma Rural 9,247 466 39,752 530 0 49,995 Bunda 3,555 133 25,939 935 158 30,721 Musoma Urban 48 7 346 53 0 453 Total 39,544 3,255 141,915 3,195 293 188,203 % 21.0 1.7 75.4 1.7 0.2 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total number of households Tarime 3 23,633 398 132 132 42,464 12,409 0 79,170 Serengeti 3 3,165 416 70 0 20,358 3,854 0 27,864 Musoma Rural 3 16,759 117 225 0 30,887 1,891 116 49,995 Bunda 3 10,162 235 236 0 19,854 234 0 30,721 Musoma Urban 3 332 0 0 0 121 0 0 453 Total 3 54,052 1,166 663 132 113,685 18,388 116 188,203 % 28.7 0.6 0.4 0.1 60.4 9.8 0.1 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 48,037 61 17,086 61 31,333 63 11,098 36 291 64 107,845 57.3 Landline phone 534 1 204 1 233 0 0 0 7 1 977 0.5 Mobile phone 2,227 3 278 1 611 1 909 3 72 16 4,098 2.2 Iron 24,315 31 7,153 26 12,221 24 6,803 22 188 41 50,680 26.9 Wheelbarrow 7,460 9 1,523 5 924 2 1,114 4 36 8 11,057 5.9 Bicycle 39,703 50 12,886 46 24,762 50 17,342 56 249 55 94,942 50.4 Vehicle 1,061 1 277 1 321 1 0 0 36 8 1,696 0.9 Television / Video 664 1 204 1 401 1 226 1 54 12 1,550 0.8 Total Number of Households 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District Type of toilet District Type of Owned Asset Tarime Serengeti Musoma Rural Table 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Bunda Musoma Urban Total Tanzania Agriculture Sample Census-2003 Appendix II 262 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 404 1 0 0 352 1 133 0 48 11 936 0.5 Solar 133 0 273 1 0 0 157 1 0 0 563 0.3 Gas (Biogas) 136 0 0 0 116 0 0 0 0 0 252 0.1 Hurricane Lamp 25,386 32 6,062 22 16,212 32 12,524 41 178 39 60,361 32.1 Pressure Lamp 2,121 3 474 2 1,720 3 1,377 4 12 3 5,705 3.0 Wick Lamp 50,180 63 20,377 73 31,402 63 16,528 54 216 48 118,703 63.1 Candles 272 0 0 0 104 0 0 0 0 0 376 0.2 Firewood 538 1 679 2 90 0 0 0 0 0 1,307 0.7 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 134 0 67 0 234 0 78 0 0 0 512 0.3 Solar 0 0 68 0 0 0 0 0 0 0 68 0.0 Gas (Biogas) 0 0 0 0 0 0 0 0 0 0 0 0.0 Bottled Gas 269 0 70 0 0 0 80 0 0 0 419 0.2 Parraffin / Kerocine 136 0 0 0 0 0 0 0 0 0 136 0.1 Charcoal 1,968 2 209 1 660 1 545 2 79 17 3,460 1.8 Firewood 76,532 97 27,318 98 49,033 98 29,859 97 375 83 183,115 97.3 Crop Residues 130 0 134 0 69 0 0 0 0 0 333 0.2 Livestock Dung 0 0 0 0 0 0 160 1 0 0 160 0.1 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 Main Source of Energy for Cooking District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Lighting District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban Tanzania Agriculture Sample Census-2003 Appendix II 263 Tarime Serengeti Musoma Rural Bunda Musoma Urban Total wet season 3,254 1,304 1,443 945 156 7,102 dry season 2,159 2,006 2,278 945 156 7,544 wet season 5,353 6,503 3,550 5,091 12 20,509 Dry season 4,956 5,677 3,684 5,185 12 19,514 wet season 3,489 1,938 1,041 1,236 7 7,711 Dry season 3,758 1,583 1,398 1,474 7 8,220 wet season 30,060 12,830 18,717 12,447 84 74,138 Dry season 26,617 10,539 20,307 10,097 90 67,650 wet season 17,802 3,221 7,606 1,520 19 30,168 Dry season 17,552 3,272 8,203 1,441 19 30,487 wet season 16,552 1,587 10,874 8,270 146 37,429 Dry season 23,727 4,444 14,125 11,354 170 53,821 wet season 937 69 341 80 0 1,427 Dry season 135 70 0 146 0 351 wet season 1,185 411 2,557 1,054 0 5,208 Dry season 265 207 0 78 0 550 wet season 0 0 0 0 0 0 Dry season 0 66 0 0 0 66 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 538 0 3,866 78 31 4,512 dry season 0 0 0 0 0 0 79,170 27,864 49,995 30,721 453 188,203 Tarime Serengeti Musoma Rural Bunda Musoma Urban Total wet season 4 5 3 3 34 4 dry season 3 7 5 3 34 4 wet season 7 23 7 17 3 11 Dry season 6 20 7 17 3 10 wet season 4 7 2 4 1 4 Dry season 5 6 3 5 1 4 wet season 38 46 37 41 18 39 Dry season 34 38 41 33 20 36 wet season 22 12 15 5 4 16 Dry season 22 12 16 5 4 16 wet season 21 6 22 27 32 20 Dry season 30 16 28 37 38 29 wet season 1 0 1 0 0 1 Dry season 0 0 0 0 0 0 wet season 1 1 5 3 0 3 Dry season 0 1 0 0 0 0 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 1 0 8 0 7 2 dry season 0 0 0 0 0 0 Total Agricultural Households per District 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season District Other District Source Season Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Tanker Truck Bottled Water Piped Water 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Protected Well Protected / Covered Spring Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Bottled Water Other Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Tanzania Agriculture Sample Census-2003 Appendix II 264 Tarime Serengeti Musoma Rural Bunda Musoma Urban wet season 3,177 684 3,761 1,191 30 Dry season 1,465 408 346 316 12 wet season 15,861 3,916 8,080 4,528 71 Dry season 12,270 2,394 4,967 2,959 82 wet season 7,215 3,518 5,852 2,726 55 Dry season 4,771 1,992 4,314 1,864 67 wet season 24,775 8,961 13,125 7,400 164 Dry season 19,912 6,323 11,138 6,087 153 wet season 5,461 1,773 7,458 2,916 7 Dry season 5,963 1,578 7,236 2,687 7 wet season 5,516 483 2,389 609 37 Dry season 4,069 342 1,883 369 37 wet season 17,164 8,530 9,330 11,350 91 Dry season 30,719 14,827 20,111 16,438 97 Tarime Serengeti Musoma Rural Bunda Musoma Urban wet season 4 2 8 4 7 Dry season 2 1 1 1 3 wet season 20 14 16 15 16 Dry season 15 9 10 10 18 wet season 9 13 12 9 12 Dry season 6 7 9 6 15 wet season 31 32 26 24 36 Dry season 25 23 22 20 34 wet season 7 6 15 9 1 Dry season 8 6 14 9 1 wet season 7 2 5 2 8 Dry season 5 1 4 1 8 wet season 22 31 19 37 20 Dry season 39 53 40 54 21 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes District 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season District above one Hour 40 - 49 Minutes 50 - 59 Minutes above one Hour 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes Tanzania Agriculture Sample Census-2003 Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 2,149 3 1,251 4 317 1 78 0 0 0 3,794 2.0 Two 37,161 47 8,781 32 39,515 79 24,235 79 247 54 109,939 58.4 Three 39,727 50 17,487 63 10,164 20 6,253 20 207 46 73,838 39.2 Four 132 0 346 1 0 0 155 1 0 0 633 0.3 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 18,402 23 6,141 22 19,795 40 13,544 44 187 41 58,069 31 One 30,576 39 10,628 38 15,645 31 6,916 23 43 9 63,808 34 Two 19,211 24 6,971 25 10,065 20 5,337 17 127 28 41,712 22 Three 8,518 11 2,403 9 2,698 5 2,995 10 60 13 16,673 9 Four 1,563 2 963 3 888 2 620 2 30 7 4,065 2 Five 528 1 414 1 456 1 626 2 7 1 2,030 1 Six 132 0 70 0 225 0 398 1 0 0 825 0 Seven 239 0 274 1 223 0 285 1 0 0 1,022 1 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100 Number of Meals per Day District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban Tanzania Agriculture Sample Census-2003 Appendix II 266 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 13,481 17 4,919 18 2,625 5 2,382 8 0 0 23,407 12 One 18,020 23 9,250 33 2,586 5 4,117 13 25 5 33,998 18 Two 14,025 18 4,069 15 6,991 14 3,664 12 31 7 28,780 15 Three 7,866 10 3,470 12 5,684 11 3,741 12 79 17 20,841 11 Four 6,965 9 2,011 7 7,375 15 3,606 12 79 18 20,036 11 Five 8,307 10 2,965 11 7,196 14 3,463 11 107 24 22,038 12 Six 3,372 4 623 2 5,950 12 2,267 7 12 3 12,223 6 Seven 7,132 9 558 2 11,588 23 7,480 24 120 27 26,879 14 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 29,209 37 13,862 50 26,367 53 8,446 27 228 50 78,113 41.5 Seldom 29,434 37 9,172 33 14,242 28 11,835 39 116 26 64,799 34.4 Sometimes 3,949 5 2,427 9 2,740 5 1,412 5 18 4 10,545 5.6 Often 9,698 12 1,088 4 2,770 6 5,637 18 60 13 19,252 10.2 Always 6,880 9 1,315 5 3,877 8 3,391 11 31 7 15,493 8.2 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 Number of Days District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Status of Food Satisfaction District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Tanzania Agriculture Sample Census-2003 Appendix II 267 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 23,633 30 3,165 11 16,759 34 10,162 33 332 73 54,052 28.7 Tiles 398 1 416 1 117 0 235 1 0 0 1,166 0.6 Concrete 132 0 70 0 225 0 236 1 0 0 663 0.4 Asbestos 132 0 0 0 0 0 0 0 0 0 132 0.1 Grass / Leaves 42,464 54 20,358 73 30,887 62 19,854 65 121 27 113,685 60.4 Grass & Mud 12,409 16 3,854 14 1,891 4 234 1 0 0 18,388 9.8 Other 0 0 0 0 116 0 0 0 0 0 116 0.1 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 36,758 46 9,870 35 15,625 31 5,520 18 12 3 67,784 36.0 Sale of Livestock 3,698 5 2,893 10 1,651 3 2,841 9 12 3 11,095 5.9 Sale of Livestock Products 1,051 1 339 1 230 0 159 1 23 5 1,802 1.0 Sales of Cash Crops 2,395 3 2,902 10 3,439 7 9,376 31 18 4 18,131 9.6 Sale of Forest Products 1,203 2 2,076 7 350 1 588 2 0 0 4,217 2.2 Business Income 9,898 13 3,805 14 5,845 12 1,820 6 80 18 21,448 11.4 Wages & Salaries in Cash 4,216 5 1,237 4 2,252 5 880 3 61 13 8,646 4.6 Other Casual Cash Earnings 7,777 10 3,706 13 9,431 19 4,025 13 55 12 24,994 13.3 Cash Remittance 4,109 5 971 3 3,041 6 1,046 3 12 3 9,178 4.9 Fishing 7,404 9 0 0 7,255 15 3,045 10 128 28 17,832 9.5 Other 661 1 66 0 877 2 1,186 4 53 12 2,844 1.5 Not applicable 0 0 0 0 0 0 234 1 0 0 234 0.1 Total 79,170 100 27,864 100 49,995 100 30,721 100 453 100 188,203 100.0 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Roofing Materials District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban Main Source of Energy for Cooking District Total Tarime Serengeti Musoma Rural Bunda Musoma Urban Tanzania Agriculture Sample Census-2003 268 APPENDIX III QUESTIONNAIRES Appendix III 269 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 270 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 271 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 272 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 273 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 274 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 275 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vemen Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farmin No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 276 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 277 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 277 278 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 279 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 280 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 281 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 282 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 283 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert HerbFun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 284 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 285 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 286 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 287 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 288 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 289 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method ofMethod of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 290 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 291 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source "a" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 292 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 293 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 294 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 295 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importanceConstraint Order of least importanc Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 296 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 297 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 298 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 299 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 300 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 301 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 302 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 303 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 304 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 305 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 306 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 307 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Sourcefrequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 308 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 309 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick i Main Tick if Activity carrie respo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used forused for noCheck hh -ility in activitysubsistancesubsistenceTotal (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 310 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 311 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 312 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 313 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 314 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content 1 TABLE OF CONTENTS page 1.0 Introduction and background information…………………………... 4 2.0 Project Implementation status…………………………………………... 5 2.1 Physical Status…………………………………………………………….... 5 2.1.1 Farmers Capacity Building Component…………………………….. 5 2.1.2 Community planning and Investment in Agriculture……………... 5 3.0 Implementation Status…………………………………………………..... 6 3.1 Farmer Capacity Building Component………………………………... 6 3.2 Community Planning and Investment in Agriculture……………….. 7 3.2.1 Carried Over Activities FY 20007/08………………………………….. 7 3.2.2 Implementation Status for planned second quarter activities FY2008/09………………………………………………………………………… 7 3.3 Support to Rural Financial Services and Marketing…………………. 8 4.0 Financial Status……………………………………………………………... 9 4.1 Funds received……………………………………………………………... 9 4.2 Funds spent………………………………………………………………….. 10 5.0 Problems and Challenges………………………………………………… 11 6.0 Outputs, achievements and results……………………………………. 13 7.0 Plans of implementation in the third quarter (January-march 2009).................13. 2 8.0. List of Annexes …………………………………………………………………….14 Annex I PFGs 2007/2008, Farm budgets for FFS (With and Without FFS), and Financial Status of PFGs...... Annex II Success story........................................................................... Annex III Table matrix shown participatory farmer groups formed FY 2008/09 …………………………………………………………………… Annex IV Funds transferred to PFGs formed FY 2007/08 & PFGs FY 2008/09………………………………………………. Annex V Pictures of completed structures (cattle dip tanks, slaughter slab, market shed and household cereal storage facility)............................................................... 3 Abbreviations and Acronyms BOQ - Bill of Quantities DASIP - District Agriculture Sector Investment Project DE - District Engineer DED - District Executive Director DTCs - District Training Coordinators FFS - Farmer Field Schools FFs - Farmer facilitators FY - Financial Year MDC - Maswa District Council PCU - Project Co-ordination Unit PFGs - Participatory Farmer Groups VEO - Village Executive Officers WEO - Ward Executive Officer 4 1.0 INTRODUCTION AND BACK GROUND INFORMATION Maswa District Council (MDC) is among 28 district councils funded by the District Agriculture Sector Investment Project (DASIP). The objective of the project is mainly crop productivity and income enhancement to rural farming community. The Project covers 30 villages in 18 wards in the district. At the district level the project has three main components namely:- (i) Farmer’s capacity building component (ii) Community planning and investment in Agriculture component. (iii) Support to Rural Financial Services and Agriculture Marketing component. This report briefly explains progress of implementing DASIP activities component-wise from July to December 2008 of FY 2008/2009. The report starts by outlining the plan of implementation and proceeds to explain physical and financial performance, along with problems and challenges met during the course of implementation. The report winds up by outlining some of the measures/suggestions taken to intervene problems and pointing out plans of implementation in the third quarter (January-March 2009). It should be noted that activities done so far were implementation of the carried over activities from the FY 2007/08. This includes construction of two cattle dip tanks at Mwabomba and Mwabagalu villages, Rehabilitation of cattle dip tanks at Isanga, Mwakidiga, Kinamwigulu and Mwamihanza villages, construction of market shed and slaughter slab at Jija village and construction of house hold burnt brick storage facilities, construction of charco dams at Mwabaraturu and Bushitala villages, Rehabilitation of charco dams at Nyabubinza, Kidema and Mwamihanza villages. Also during the period under report farmer capacity building activities like formation of PFGs, training of farmer facilitators and facilitation of PFGs to open bank accounts were executed. 5 2.0 PROJECT IMPLEMENTATION STATUS 2.1 Physical status 2.1.1 Farmers Capacity building component. Under this component, major activities planned were:- • Data collection and analysis of established FFS • Formation of 180 PFGs. • Facilitation of 240 PFGs in opening bank accounts for implementation of FFS and economic mini-projects. • Training of farmer facilitators (FFs) • Establishment of FFS • To conduct season long training of 180 PFGs • Procurement of 80 pieces of bicycles • Monitoring and supervision of FFS. 2.1.2 Community planning and Investment in Agriculture The plan during the period under review was to finalize implementation of carried over activities FY2007/08 and planned activities FY 2008/09. Carried over activities include:- Construction/Rehabilitation of cattle dip tanks (5) Support 25 farmer groups with house hold burnt brick cereals storage facilities (75) Construction/rehabilitation of charco dams (5) Construction of market shed and slaughter slab Planned activities for the second quarter FY 2008/09 were:- • To conduct topographic survey and designing of Kinamwigulu irrigation schemes. • To construct 20 burnt bricks house hold storage facilities at four (4) villages. • To construct one (1) cattle dip tank at Mwandete village and rehabilitation of one (1) cattle dip tank at Nyashimba village. • To construct one (1) charco dam at Iyogelo village. • To construct one (1) cotton storage structure at Buhungukila village. • To procure 20 pcs of oxen- weeders for Mwabagalu village. • Procurement of 7 pieces of grain/ground nut/sweet potato milling/hulling machines for Mandela, Igunya, Isanga, Mwabayanda (M) and Senani villages. • Construction of 6 shallow wells for Mandela, Mwabagalu, Mwabayanda(S), Mwabayanda (M), and Senani villages. • Monitoring and supervision of village/group micro projects. 6 3.0 IMPLEMENTATION STATUS FOR ACTIVITIES UNDER FARMER CAPACITY BUILDING AND COMMUNITY PLANNING AND INVESTMENT IN AGRICULTURE COMPONENTS:- 3.1 Farmer capacity building component implementation status. Data collection of all established FFS were collected. Analysis of Some selected FFS in terms of cost benefit was also done. The result of analysis indicates that cost benefit ratio is high in FFS than in farmer practice. The selected FFS with respect to PFGs names is presented as annex I a –I f. Either success story of Improving cotton storage and Increasing Crop quality at Mandela village is presented as annex II. • 163 out of 180 target Participatory Farmer Groups have been formed where by 1499 are male members and 1240 are female members. Formation of the remaining 17 farmer groups are in progress. A table matrix showing formed group FY2008/09 is attached as annex III • 152 formed Participatory Farmer Groups have been facilitated to open bank accounts ready for implementation of FFS. Facilitation of the remaining 48 PFGs are also in progress. • 51 graduated Participatory Farmer Groups in last year (FY 2007/08) have been facilitated to open bank accounts for implementing economic mini-projects. names of PFGs with their respective account numbers & PFGs for FY 2008/09 in which funds have been transferred is presented as an annex IV • 30 farmer’s facilitators have been trained on improved technologies on crop and livestock production and management of farmer field school plots. • The process of establishing FFS and seasonal long training are at initial stage. • 80 pieces of bicycles have been procured. 7 3.2 . Community planning and Investment in Agriculture implementation status 3.2.1 Carried over activities FY 2007/08 • Improvement of Livestock infrastructures. Under the improvement of livestock infrastructures achievements made so far includes:- Construction of two cattle dips at Mwabagalu and Mwabomba villages have been completed and in use. Two cattle dip tanks at Isanga and Mwamihanza have been rehabilitated. Kinamwigulu and Mwakidiga cattle dip tanks are under rehabilitation following tender award in this month (December). Rehabilitation of charco dams at Nyabubinza and Kidema villages are in progress. Also one slaughter slab at Jija village has been completed. Either construction of charco dam at Mwabaraturu village is in progress (50% completion). Photos of the completed structures are attached as Annex V a -c. • Improvement of market infrastructures Under this activity, one market shed at Jija has been completed and its photo is presented as annex V. • Improvement of post harvest storage facilities in 27 villages Under improvement of post harvest storage facilities the target was to construct 75 burnt brick house hold storage facilities each with capacity of storing 3 tons of cereals in 25 villages. Eighteen (18) storage facilities at Mwandete, Mwabayanda, Kidema, Mwabagalu, Mwabaraturu and Hinduki village have been constructed. The rest 11 villages are still finalizing mobilization of local building materials. Provided in this report as annex V is a photo of completed house hold storage facility at Mwandete village. 3.2.2 Implementation Status for planned second quarter activities FY 2008/09 • Topographic survey and designing of Kinamwigulu irrigation scheme not yet done as this activity is going to be executed by contractor who will be appointed by DASIP- PCU. • Construction 20 burnt bricks house hold storage facilities in four (4) villages not yet done as the targeted community 8 are still mobilizing local building materials together with opening project bank account. • Construction of one (1) cattle dip tank at Mwandete village and rehabilitation of one (1) cattle dip tank at Nyashimba village not yet done as the targeted community are still mobilizing local building materials together with opening project bank account. • Construction one (1) charco dam at Iyogelo village not yet done since the approved budget not yet released. • Construction one (1) cotton storage structure at Buhungukila village not yet done as the targeted community is still mobilizing local building materials together with the process of opening project bank account. • Procurement 20 pieces of ox-weeders for Mwabagalu village are in the final stage. • Procurement of 7 pieces of grain/ground nut/sweet potato milling/hulling machines for Mandela, Igunya, Isanga, Mwabayanda (M) and Senani villages not yet implemented as targeted community is still mobilizing local building materials together with the process of opening project account. . • Construction of 6 shallow wells for Mandela, Mwabagalu, Mwabayanda(S), Mwabayanda (M), and Senani villages not yet started as the targeted community is still in the process of opening project bank account. • Monitoring and supervision of village/group micro projects for both community and group micro projects have been monitored and supervised so as to ensure good quality work and in the required standards. 3.3 . Support to Rural Financial Services and Marketing Until to date no any activity done as the DASIP-PCU Mwanza she is still consulting the best way of performing this component 9 4.0. FINANCIAL STATUS 4.1. Funds Received For the period of July to December 2008 for FY 2008/09 Maswa District Council has received Tshs 253,117,000/= plus Tshs 108,673,380.50 as carried over for FY 2007/08 funds from DASIP- PCU Mwanza as a total budget for the summarized activities in table no. 1 below. Table No 1: Funds received as at 31st December, 2008 Date of letter for funds transfer Amount (Tshs) Targeted activities 08th/08/2008 8,175,000/= • District office operation and maintenance • Motorcycle allowances • Field staff allowances 22nd /08/2008 24,000,000 • To support 60 graduated PFGs min-projects 04/09/2008 2,300,000/= • Formation of Participatory Farmer groups (PFGs) 09th/09/2008 90,000,000/= • Seasonal long training of PFGs 11th/10/2008 118,600,000/= • Support 19 village micro projects 6th/11/2008 10,042,000/= • Training of 30 Farmer Facilitators. 1st /07/2008 108,673,380.50 • Carried over funds for FY 2007/08 Total amount of funds as at 31st December 2008 361,790,380.50 4.2. Funds Spent As At 31st December, 2008 A total of 151,056,210/= was spent both for community planning and farmers capacity building components. The analysis of expenditure component wise is summarized in the table No. 2 below. 10 Table No. 2 Expenditure funding statement component-wise as at 31/12/2008: COMPONENT ACTIVITY AMOUNT SPENT (July- Sept.2008) CUMMULATIVE (July-Dec. 2008) REMARKS Motorcycle operating costs 300,000 600,000 Allowances for 4 months Staff field allowances 4,678,000 8,888,000 Bank charges 15,000 90,000 village micro projects 56,849,144 56,849,144 Transfer of funds (48,640,000/=) to 16 village/group micro projects are in progress Community planning and investment in agriculture component Office operation and maintenance 763,200 1,187,200 Motorcycle operating costs 300,000 600,000 Allowances for 4 months Office operation and maintenance 400,000 600,000 Staff field allowances 350,000 600,000 Purchasing of 80 bicycles 0 7,466,666 Carried over activity To support 60 PFGs min-projects 0 17,400,000 Formation of PFGs 0 2,919,400 Seasonal long training of PFGs 0 45,000,000 Printing of graduation certificates for PFGs members FY 2007/08 4,491,000 4,491,000 Carried over activity Purchasing of equipments for FFS FY2007/08 0 982,800 Carried over activity Bicycle allowances 0 240,000 Carried over activity Farmer capacity building component Training of 30 FFS in three phases 0 3,142,000 One phase training TOTAL 68,146,344 151,056,210 11 4.0 PROBLEMS AND CHALLENGES (ISSUES AND CONSTRAINTS) • Untimely release of funds delayed implementation to some of activities, for instance in this FY 2008/09 the planned first quarter activities which include construction works their funds released at the second week of October, 2008. • Slow pace of community in mobilizing local building materials for construction activities for both community and group investment projects. • Slow pace of project supervision communities and groups in opening bank project accounts for quick implementation of micro projects funded by DASIP, for instance out of 19 funded village/group micro projects only 11 to date have opened their micro project bank accounts. • Low accountability and irresponsible of village local leaders • Inadequate local artisans at village level to carry out construction of cereal burnt brick storage facilities. • Untimely availability of technical staff such as District Engineer and Supplies officer causes slow pace in implementation of some micro project activities. • Lack of clear guidelines on recurrent expenditures for village/group micro project supervision committees. • The dominant culture of depending on the Government to do every thing for community/group micro projects impairs speed of implementation. 12 Table Na 3. List of challenges and actions taken / to be taken to address them. S / N Issues Action taken / to be taken Responsible person 1 Slow response in opening micro project bank account. To continue with sensitization of project supervision communities and groups to opening Bank project account for quick implementation of projects DALDO DPO DMEO 2 Slow pace of community in mobilization of local building materials. To continue educating community on the importance of implementing their projects within the planed time frame. To continue sensitize community on the importance of adhering to work plans and enforcement of village by Laws to laxity community members. DPO DMEO VEO WEO 3 Low accountability and irresponsible village local leaders. Enforcement of Local government ACT No. 7 of 1982 to non accountable and irresponsible local leaders. To continue with educating Local leaders on their responsibilities in implementing development projects. DC DED 4 Untimely release of funds delayed implementation to some of activities PCU-Mwanza to adhere to Annual Work Plan and Budget PCU-Mwanza 5 Lack of clear guidelines on recurrent expenditures for village/group micro project supervision committees. To prepare and submit to the respective districts guidelines on how recurrent expenditure can be accommodated in supervising village micro projects at committees’ level. PCU-Mwanza 6 The dominant culture of depending on the Government to do every thing for community/group micro projects impairs speed of implementation. Political and local leaders should continue educating the community that development is their own role and the government will support them only when they show their efforts. DC Councilors Member of parliament 13 5.0 OUTPUTS,ACHIEVEMENTS AND RESULTS The followings are the outputs/achievements/results obtained so far:- (i) Capacity of ward and village staff as well as that of facilitation committees at ward level has been built. (ii) As pre-requisite for successful micro project implementation, team work has been established and is continued to be strengthened at district, ward and village levels. (iii) Awareness to micro project has been created and rise to the stakeholders, and enthusiasm to implement the micro projects has been raised. (iv) A total of 22 village/group micro projects have so far been completed 7.0 PLANS OF IMPLEMENTATION IN THE THIRD QUARTER (JANUARY- MARCH 2009). • To continue with implementation of Carried over activities (Charcodam and Cattle dips) and planned FY 2008/09 activities. • Intensify monitoring and supervision so as to ensure good quality and timely completion of village/group micro projects. 14 8.0 LIST OF ANNEXES Annex I a. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR TOMATO PRODUCTION FY 2007/08 NAME OF PFGs: NGUVU KAZI – MWABOMBA VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (10%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/kg. Tshs/ Ha 4070 407 3663 300/= 1,098,900/= 1977.5 197.5 1780 300/= 534,000/= Total cost Tshs/Ha 510,625/= 368,125/= Net Revenue Tshs / Ha 588.275/= 174,000/= Cost: Benefit Ratio 1: 1. 1 1: 0. 5 Increase in Yield % 105.8 - Break – Even price 2.15 4.0 Source: M &E surveys, June 2008: Maswa District Council 15 I b. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR MAIZE PRODUCTION NAME OF PFGs: WAKULIMA BORA B – TAMANU VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (5%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/Kg. Tshs/ Ha 2840 355 2485 300/= 745,500/= 1950 243.75 1706.25 300/= 511,875/= Total cost Tshs/Ha 425,000/= 102,500/= Net Revenue Tshs / Ha 320,500/= 409,375/= Cost: Benefit Ratio 1: 0. 8 1: 4 Increase in Yield % 45.6 - Break – Even price 1.8 5.0 Source: M &E surveys, June 2008: Maswa District Council 16 I c. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR GROUNDNUTS PRODUCTION NAME OF PFGs: MSHIKAMANO – HINDUKI VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (12.5%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/Kg. Tshs/ Ha 1000 125 875 1500/= 1,312,500/= 500 62.5 437.5 1500/= 656,250/= Total cost Tshs/Ha 345,000/= 127,500/= Net Revenue Tshs / Ha 967,500/= 528,750/= Cost: Benefit Ratio 1: 2. 8 1: 4 Increase in Yield % 100 - Break – Even price 3.8 5.1 Source: M &E surveys, June 2008: Maswa District Council 17 I d. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR SUNFLOWER PRODUCTION NAME OF PFGs: WALALASAGALA – SENANI VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (12.5%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/kg. Tshs/ Ha 667.5 83.4 584.1 3000/= 584,100/= 125.5 19 133.5 3000/= 133,500/= Total cost Tshs/Ha 338,750/= 100,000/= Net Revenue Tshs / Ha 245,350/= 33,500/= Cost: Benefit Ratio 1: 0. 7 1: 0. 3 Increase in Yield % 337.5 - Break – Even price 5.2 4.0 Source: M &E surveys, June 2008: Maswa District Council 18 I e. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR COTTON PRODUCTION NAME OF PFGs: MAPINDUZI – BUSHITALA VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (5%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/Ha Tshs/ Ha 2405 120.25 2284.75 450/= 1,028,137.50/= 460 23 437 450/= 196,650/= Total cost Tshs/Ha 400,000/= 135,000/= Net cost Revenue Tshs / Ha 628,137.50/= 61,650/= Cost: Benefit Ratio 1:1.6 1: 0.5 Increase in Yield % 422.8 - Break – Even price 2.6 1.1.5 Source: M &E surveys, June 2008: Maswa District Council 19 I f. FARM BUDGET FOR FARMER FIELD SCHOOLS (WITH AND WITHOUT FFS) FOR SORGHUM PRODUCTION NAME OF PFGs: UKOMBOZI – SOMANDA VILLAGE -MASWA DISTRICT COUNCIL REVENUE UNIT WITH FFS WITHOUT FFS Yield Post Harvest loss (12.5%) Net Yield Selling price Total Revenue Kg./ Ha Kg./ Ha Kg./Ha Tshs/Ha Tshs/ Ha 1500 187.5 1312.5 225/= 295,312.50/= 825 103 722 225/= 162,450/= Total cost Tshs/Ha 362,500/= 92,500/= Net cost Revenue Tshs / Ha -67,187.50/= 69,950/= Cost: Benefit Ratio 1:-0.2 1: 0.8 Increase in Yield % 81.8 - Break – Even price 0.8 1:1.8 Source: M &E surveys, June 2008: Maswa District Council 20 Annex II Success Story: Improving cotton storage and Increasing Crop quality. Mandela village is situated about 38 km. North of Maswa headquarter. The village is among of 30 villages where DASIP is collaborating with community to increase agricultural productivity and income of the rural poor farmers in the village. The village is prominent for cattle keeping like cows, goats and cultivation of food and cash crops like maize, groundnuts, sweet potatoes, sorghum, sunflower and cotton. In the past cotton growers did not have any cotton storage facility so they used their available village buildings like village office, resident houses to store cotton before transported to ginneries at Shinyanga. They later realized the importance of having cotton storage facility for storing cotton after harvest. This was revealed in the O&OD exercise that was conducted in year 2005/06 which ranked construction of cotton storage facility as their first priority. This activity was incorporated in their VADPs and was financed by DASIP under ‘quick win’ arrangement in year 2006/07. Tendering works started in year 2007 but due to difficulties in acquiring bidders the construction works started end of June in year 2008 and completed in early of July the same year and is now in use not only by the community at Mandela village, but at neighboring villages of Buhungukila and Seng’wa. The community has formed a strong supervision committee which overseas O&M of the structure. For the case of sustainability the supervision committee at the village has opened account at NMB Maswa branch. To raise their funds the structure used to store cotton by contract manner. Mr. Dastan who is a chairperson at Mandela village and at the same time a Cotton grower on behalf of his community witnessed that the structure is now among the source of funds at the village. The promising and significant point explained by chairperson is the commitment made that every member of the village will be much aware to the use of the structure. Mr. Jilungu who is a hamlet chairperson added that DASIP has done well to finance the construction of the structure because the life standard of Mandela people will change if these funds will be used wisely. The community showed their satisfactions to the services they are getting are more optimistic that the problem of storing cotton now is greatly solved. This success story prepared By DMEO – MASWA. 21 Annex III A TABLE MATRIX SHOWN PARTICIPATORY FARMER GROUPS FORMED FY. 2008/09 SEX S/N WARD S/N VILLAGE S/N GROUP NAME Male Female TATOL 1 Ngwinula 14 7 21 2 Mwakaleka 6 7 13 3 Mwanyomba 8 3 11 4 Gugalama A 12 8 20 5 Ujamaa 14 1 15 1 NYALIKUNGU 1 Iyogelo 6 Balimi ‘A’ 7 Nguvu Kazi 8 Jikomboe na Maji 9 Kisauma Group 10 Umoja ni nguvu 9 9 18 11 Umoja 9 12 21 2 Mwabayanda (M) 12 Catholic Group 12 13 25 13 Uvumilivu 20 12 32 14 Tumaini 15 9 24 15 Wajelajela 6 9 15 16 Ujamaa 11 8 19 17 Igembesabo 9 16 25 2 SUKUMA 3 Hinduki 18 Umoja ni Nguvu 14 11 25 19 Wachapakazi 9 12 21 20 Muungano 6 10 16 21 Twende Mbele 8 6 14 22 Ilonganzala 14 13 27 23 Igembesabo 16 9 25 3 NGULIGULI 4 Mwashegeshi 24 Mkombozi 6 13 19 25 Maendeleo 12 3 15 26 Upendo 27 Juhudi 11 4 15 28 Bagogo 6 5 11 29 Mwamko 4 IPILILO 5 Mwakabeya 30 Majaliwa 31 Smart 32 Mapambano 33 Uamusho 34 Tuinue Maisha 7 17 24 35 Maboresho 10 10 20 6 Ikungulyanko ma 36 Mshikamano 17 9 26 37 Upendo 5 7 12 38 Amani ‘B’ 10 11 21 39 Mwaelia 12 13 25 40 Amani ‘A’ 41 Vumilia 7 Senani 42 Imalamakoye 5 9 14 43 Igembesabo 7 10 17 44 Balimi 20 6 26 5 MPINDO 8 Somanda 45 Muungano 12 13 25 22 SEX S/N WARD S/N VILLAGE S/N GROUP NAME Male Female TATOL 46 Ushirikiano 47 48 49 Maendeleo 16 1 17 50 Mkombozi Group 11 4 15 51 Mshikamano 4 11 15 52 Umoja Group 9 6 15 53 Ushirikiano 11 4 15 9 Tamanu 54 Azimio Group 55 Azimio 3 21 24 56 Upendo 7 18 25 57 Neema Group 10 9 19 58 Tuleane 59 Ujamaa 6 DAKAMA 10 Mwandete 60 61 Azimio 62 Mwabuta 63 Tuwezeshane 64 Ukombozi 8 10 18 65 Kilimifu 11 15 26 7 LALAGO 11 Mwakidiga 66 Buhemba 11 8 19 67 Tupendane 21 4 25 68 Tubadilike 10 9 19 69 Hekima 70 Neema 71 12 Bushitala 72 73 Merelani 8 5 13 74 Mamba Wimate 8 7 15 75 Senegal 10 3 13 76 Walengwa 10 7 17 77 Mkombozi 8 BUSILILI 13 Buhungukila 78 Mtakuja B 79 Nyalusanga 80 Nyota ya Wakulima 8 6 14 81 Nuru Group 9 6 15 82 Ushirika Group 13 5 18 83 Boroboro 20 5 25 9 BUDEKWA 14 Mwabaraturu 84 Vumilia 14 12 26 85 African Inland Church(AIC) 10 5 15 86 Tumaini 87 Amani 88 Maendeleo 89 Moto jembe 10 5 15 15 Mwabomba 90 Igembesabo 10 MASELA 16 Mandela 91 Zinduka Group 23 SEX S/N WARD S/N VILLAGE S/N GROUP NAME Male Female TATOL 92 Bukande A 93 Jidulu 9 6 15 94 Mafanikio 15 10 25 95 Upendo 10 5 15 96 Balimi B 97 Upendo 5 5 10 98 MT. Benedicto 12 18 30 99 Jitegemee 9 9 18 100 Viwawa 101 Fatima 4 17 21 17 Isanga 102 Nanonano 103 Mkombozi 8 12 20 104 Upendo 12 6 18 105 Tubadilike 4 6 10 106 Igembesabo 107 Upendo2 11 ISANGA 18 Kidema 108 Ujamaa 109 Igembesabo 110 Azimio 111 Mapambano 13 5 18 112 Chapa Kazi 7 11 18 113 Maendeleo Supamagembe 9 10 19 19 Mwamihanza 114 Maendeleo 8 8 16 115 Kandokando 21 4 25 116 Igembesabo 17 8 25 117 Ukombozi 14 11 25 118 Upendo Group 19 6 25 119 Kujitolea 12 KULIMI 20 Mwabayanda (S) 120 Mabatini 121 Italemoto 13 12 25 122 Ujamaa 14 4 18 123 Mwamko 124 Mwanzo mgumu 3 22 25 125 Hurumia 21 Nyashimba (S) 126 Tupendane 127 Mshikamano 128 Akina Mama 129 Tuvumilie 130 Mapambano 131 13 BADI 22 Ikungu 132 133 Changanyikeni 134 Ikonga Balimi 135 136 137 14 MALAMPAKA 23 Nyabubinza 138 24 SEX S/N WARD S/N VILLAGE S/N GROUP NAME Male Female TATOL 139 Igalukilo 8 7 15 140 Mpakani Group 7 6 13 141 Umoja 7 10 17 142 Ikolaboro 143 Amani Group 8 14 22 24 Mwabagalu 144 Ukombozi 13 7 20 145 Mkombozi 9 13 22 146 Basukamagembe 8 7 15 147 Luchibila makoye 8 7 15 148 Maisha Bora 11 14 25 149 Mwabageni 6 8 14 15 NYABUBINZA 25 Zawa 150 Upendo 5 14 19 151 Uhuru Jamii 8 9 17 152 Tupendane 14 9 23 153 Washirika 4 7 11 154 Upendo 13 4 17 155 RC Group 8 13 21 26 Jija 156 Chapakazi Jamii 13 8 21 157 Yataka Moyo 21 3 24 158 Tupendane 19 5 25 159 Twende Pamoja 14 6 20 160 Umoja ni Nguvu 5 10 15 161 Amani 16 SHISHIYU 27 Igunya 162 163 Uzalishaji 10 7 17 164 Sauti ya Mnyonge 7 7 14 165 Tumaini 16 6 22 166 Muamini 16 9 25 167 Upendo 17 KADOTO 28 Malekano 168 Tupendane 169 Songambele 12 8 20 170 Ngoshagugema 13 7 20 171 Yanga Vijana B 19 6 25 172 Chapakazi 7 6 13 173 Vijana Songambele 13 6 19 29 Kinamwigulu 174 13 6 19 175 Kujitegemea 176 Tumaini 17 13 30 177 178 179 18 BUCHAMBI 30 Mwabujiku 180 TOTAL 25 ANNEX IV (a) FUNDS TRANSFERRED TO PFGs FORMED FY 2007/08 NO NAME OF PARTICIPATORY FARMER GROUP NAME OF VILLAGE A/C NO. AMOUNT TO BE TRANSFERED 1 Senani Group Senani 3081600238 400,000 2 Walalasagala Senani 3082300556 400,000 3 Maendeleo Tumbili Mwandete 3081600437 400,000 4 Nuru Group Mwabayanda (M) 3082302590 400,000 5 Kiwaki Mwabayanda (M) 3082300264 400,000 6 Faraja Buhungukila 3081600388 400,000 7 Kasi Mpya Mwashegeshi 3081100084 400,000 8 Mwalundi Malekano 3082300617 400,000 9 Jerusalem Mwakidiga 3081100086 400,000 10 Tuamke Mwakidiga 3081100087 400,000 11 Amani Mwandete 3081100093 400,000 12 Ufugaji Nyuki Isanga 3081100085 400,000 13 Mazingira Isanga 3082300521 400,000 14 Mshikamano Hinduki 3082300532 400,000 15 Upendo Hinduki 3082300426 400,000 16 Mshikamano Nyashimba (S) 3081600227 400,000 17 Tumaini Group Mwabaraturu 3081300012 400,000 18 Chapakazi Mwabagalu 3082300637 400,000 19 Matengenezo Mwakabeya 3082300639 400,000 20 Tumaini Nyabubinza 3082300640 400,000 21 Isabilo Mwabayanda (S) 3082300647 400,000 22 Mshitue Ikungulyankom a 3082300648 400,000 23 Mshikamano Iyogelo 3082300668 400,000 24 Igembesabo Igunya 3082300672 400,000 25 Iloganzala Mwabagalu 3082300680 400,000 26 Jikwamue Mwabayanda(S) 3082300655 400,000 27 Tupendane Mwakabeya 3082300669 400,000 28 Ipejanzala Zawa 3082300659 400,000 29 MT. Maria Kidema 3082300696 400,000 30 Wakuji Jija 3082300695 400,000 31 Wasimbangobi Jija 3082300697 400,000 26 NO NAME OF PARTICIPATORY FARMER GROUP NAME OF VILLAGE A/C NO. AMOUNT TO BE TRANSFERED 32 Kazi ni Moyo Igunya 3082300664 400,000 33 Igembesabo Mwamihanza 3081300022 400,000 34 Nguvu Mpya Mwashegeshi 3082300684 400,000 35 Umoja Kinamwigulu 3082300657 400,000 36 Nguvu Kazi Mwabomba 3082300548 400,000 37 Mapinduzi Kinamwigulu 3082300710 400,000 38 MT. Joseph Kidema 3082300709 400,000 39 Mapinduzi Bushitala 3082300712 400,000 40 Mshikamano Group Mwabujiku 3082300724 400,000 41 Chapakazi Mwabujiku 3082300737 400,000 42 Mtapenda Group Zawa 3082300745 400,000 43 Muungano Mwamihanza 3082300753 400,000 44 Akina mama mkombozi Mandela 3082300453 400,000 TOTAL 17,600,000 27 ANNEX IV (b) FUNDS TRANSFERRED TO NEWLY FORMED PFGs FY 2008/09 NO NAME OF PARTICIPATORY FARMER GROUP NAME OF VILLAGE A/C NO. AMOUNT TO BE TRANSFERRED 1 Upendo Senani 3082300301 500,000 2 Amani ‘ B’ Senani 3082300634 500,000 3 Mwaelia Senani 3082300636 500,000 4 Amani ‘ A ‘ Senani 3082300635 500,000 5 Uvumilivu Hinduki 3082300638 500,000 6 Tumaini Hinduki 3081600641 500,000 7 Wachapakazi Mwashegeshi 3082300642 500,000 8 Muungano Mwashegeshi 3082300643 500,000 9 Smart Ikungulyankoma 3082300644 500,000 10 Mapambano Ikungulyankoma 3082300646 500,000 11 Azimio Mwandete 3082300365 500,000 12 Vumilia Senani 3082300561 500,000 13 Imalamakoye Senani 3082300313 500,000 14 Kandokando Mwabayanda(S) 3082300650 500,000 15 Igembesabo Mwabayanda(S) 3082300652 500,000 16 Maendeleo Tamanu 3082300656 500,000 17 Twende mbele Mwashegeshi 3082300653 500,000 18 Uhuru Jamii Jija 3082300654 500,000 19 Igalukilo Mwabagalu 3082300658 500,000 20 Tupendane Jija 3082300689 500,000 21 Nguvukazi Mwabayanda(M) 3082300660 500,000 22 Upendo Isanga 3082300665 500,000 23 MT. Benedicto Isanga 3082300666 500,000 24 Kujitegemea Mwabujiku 3082300663 500,000 25 Azimio Mwamihanza 3082300661 500,000 26 Mkombozi Zawa 3082300662 500,000 27 Mkombozi Group Tamanu 3082300670 500,000 28 Mpakani Group Mwabagalu 3082300675 500,000 29 Italemoto Nyashimba (S) 3082300674 500,000 30 Umoja Mwabagalu 3082300673 500,000 28 NO NAME OF PARTICIPATORY FARMER GROUP NAME OF VILLAGE A/C NO. AMOUNT TO BE TRANSFERRED 31 Mshikamano Group Tamanu 3082300677 500,000 32 Umoja Group Tamanu 3082300678 500,000 33 Zinduka Group Mandela 3082300676 500,000 34 Ngoshagugema Kinamwigulu 3082300679 500,000 35 Ikolaboro Mwabagalu 3082300681 500,000 36 Jikomboe na Maji Mwabayanda (M) 3082300683 500,000 37 Mapambano Mwamihanza 3082300685 500,000 38 Mshikamano Ikungu 3082300682 500,000 39 Igembesabo Mwashegeshi 3082300686 500,000 40 Uamusho Ikungulyankoma 3082300687 500,000 41 Azimio Group Tamanu 3082300690 500,000 42 Tuinue Maisha Ikungulyankoma 3082300691 500,000 43 Ukombozi Mwabayanda (S) 3082300692 500,000 44 Jitegemee Isanga 3082300698 500,000 45 Washirika Jija 3082300699 500,000 46 Ushirikiano Tamanu 3082300694 500,000 47 Igembesabo Somanda 3082300693 500,000 48 Ukombozi Mwabagalu 3082300700 500,000 49 Amani Group Mwabagalu 3082300701 500,000 50 Upendo Group Mwandete 3082300702 500,000 51 Basukamagembe Zawa 3082300703 500,000 52 Upendo Group Mwabayanda (S) 3082300705 500,000 53 Twende Pamoja Igunya 3082300707 500,000 54 Neema Goup Mwandete 3082300649 500,000 55 Fatima Isanga 3082300713 500,000 56 Luchibula Makoye Zawa 3082300711 500,000 57 Chapakazi Kinamwigulu 3082300715 500,000 58 Upendo Kidema 3082300714 500,000 59 Maendeleo Mwakabeya 3082300718 500,000 60 Upendo Mwakabeya 3082300719 500,000 61 Juhudi Mwakabeya 3082300716 500,000 62 RC Group Jija 3082300717 500,000 29 NO NAME OF PARTICIPATORY FARMER GROUP NAME OF VILLAGE A/C NO. AMOUNT TO BE TRANSFERRED 63 Chapakazijamii Group Jija 3082300720 500,000 64 Umoja ni nguvu Mwabayanda (M) 3082300723 500,000 65 Tumaini Mwabujiku 3082300722 500,000 66 Mwamko Nyashimba(S) 3082300726 500,000 67 Mwanzo mgumu Nyashimba(S) 3082300725 500,000 68 Tumaini Mwabomba 3082300727 500,000 69 Motojembe Mwabomba 3082300728 500,000 70 Muungano Nyashimba(S) 3082300730 500,000 71 Amani Mwabomba 3082300729 500,000 72 Maboresho Ikungulyankoma 3082300733 500,000 73 Mafanikio Mandela 3082300735 500,000 74 Jidulu Mandela 3082300734 500,000 75 Vijanasngambele Kinamwigulu 3082300736 500,000 76 Maendeleo Mwabomba 3082300738 500,000 77 Mkombozi Mwashegeshi 3082300739 500,000 78 Mkombozi Buhungukila 3082300741 500,000 79 Iloganzala Mwashegeshi 3082300740 500,000 80 Yanga vijana “B” Kinamwigulu 3082300744 500,000 81 Umoja Mwabayanda (M) 3082300746 500,000 82 Mtakuja “B” Buhungukila 3082300750 500,000 83 Walengwa Buhungukila 3082300751 500,000 84 Maendeleo Mwamihanza 3082300752 500,000 85 Catholic Group Mwabayanda (M) 3082300749 500,000 86 Mapambano Ikungu 3082300825 500,000 87 Mkombozi Kidema 3082300757 500,000 88 Igembesabo Mwabomba 3082300754 500,000 89 Upendo Zawa 3082300755 500,000 90 African Inland Church Mwabomba 3082300756 500,000 TOTAL 45,000,000 | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vl: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vi: REGIONAL REPORT: MBEYA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census i TABLE OF CONTENT Table of contents................................................................................................................................................................i Acronyms......................................................................................................................................................................... v Preface..............................................................................................................................................................................vi Executive summary........................................................................................................................................................ vii Illustrations..................................................................................................................................................................... xii ENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing ................................................................................................................................... 9 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Holding Characteristics................................................................................................................................ 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Literacy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................... 16 TOC ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census ii 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 21 3.3.3 Crop Types........................................................................................................................................ 21 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 24 3.3.4.3 Other Cereals.................................................................................................................. 24 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava........................................................................................................................... 26 3.3.5.2 Irish Potatoes .................................................................................................................. 27 3.3.6 Pulse Crops Production .................................................................................................................... 27 3.3.6.1 Beans............................................................................................................................... 29 3.3.7 Oil Seed Production.......................................................................................................................... 31 3.3.7.1 Groundnuts ..................................................................................................................... 31 3.3.8 Fruits and Vegetables ........................................................................................................................ 32 3.3.8.1 Tomatoes ........................................................................................................................ 35 3.3.8.2 Radish ............................................................................................................................. 35 3.3.8.3 Onion .............................................................................................................................. 35 3.3.9 Other Annual Crops Production....................................................................................................... 36 3.3.9.1 Tobacco ........................................................................................................................... 36 3.3.9.2 Pyrethrum ........................................................................................................................ 36 3.4 Permanent Crops........................................................................................................................................... 36 3.4.1 Coffee ........................................................................................................................................ 39 3.4.2 Banana ........................................................................................................................................ 42 3.4.3 Cocoa ......................................................................................................................................... 42 3.4.4 Mangoes ........................................................................................................................................ 46 3.5 Inputs/Implements Use.................................................................................................................................. 46 3.5.1 Methods of land clearing................................................................................................................... 46 3.5.2 Methods of soil preparation.............................................................................................................. 48 3.5.3 Improved seeds use........................................................................................................................... 48 3.5.4 Fertilizers use.................................................................................................................................... 49 3.5.4.1 Farm Yard Manure Use.................................................................................................. 51 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 51 3.5.4.3 Compost Use .................................................................................................................. 52 3.5.5 Pesticide Use.................................................................................................................................... 53 3.5.5.1 Insecticide Use................................................................................................................ 53 3.5.5.2 Herbicide Use................................................................................................................. 54 3.5.5.3 Fungicide Use................................................................................................................. 54 3.5.6 Harvesting Methods.......................................................................................................................... 55 3.5.7 Threshing Methods .......................................................................................................................... 55 TOC ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census iii 3.6 Irrigation .................................................................................................................................................... 55 3.6.1 Area planted with annual crops and under irrigation....................................................................... 56 3.6.2 Sources of water used for irrigation................................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................................ 57 3.6.4 Methods of water application .......................................................................................................... 57 3.7 Crop Storage, Processing and Marketing .................................................................................................. 58 3.7.1 Crop Storage ..................................................................................................................................... 58 3.7.1.1 Method of Storage.......................................................................................................... 58 3.7.1.2 Duration of Storage ......................................................................................................... 59 3.7.1.3 Purpose of Storage.......................................................................................................... 59 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 60 3.7.2 Agro processing and by-products...................................................................................................... 60 3.7.2.1 Processing Methods......................................................................................................... 60 3.7.2.2 Main Agro-processing Products..................................................................................... 60 3.7.2.3 Main use of primary processed Products....................................................................... 62 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 63 3.7.3 Crop Marketing................................................................................................................................. 63 3.7.3.1 Main Marketing Problems.............................................................................................. 64 3.7.3.2 Reasons for Not Selling.................................................................................................. 64 3.8 Access to Crop Production Services............................................................................................................ 64 3.8.1 Access to Agricultural Credits ......................................................................................................... 64 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits............................................................................................ 65 3.8.1.3 Reasons for not using agricultural credits...................................................................... 65 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of crop extension messages.............................................................................. 66 3.8.2.2 Quality of extension ....................................................................................................... 66 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.2 Inorganic Fertilisers .......................................................................................................................... 68 3.9.3 Improved Seeds ................................................................................................................................. 69 3.9.4 Insecticides and Fungicide ................................................................................................................ 69 3.10 Tree Planting................................................................................................................................................... 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 72 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population............................................................................................................ 73 3.12.1.2 Herd size......................................................................................................................... 73 3.12.1.3 Cattle Population Trend ................................................................................................. 74 3.12.1.4 Improved Cattle Breeds.................................................................................................. 74 3.12.2 Goat Production................................................................................................................................ 74 3.12.2.1 Goat Population.............................................................................................................. 74 3.12.2.2 Goat Herd Size ............................................................................................................... 77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 TOC ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census iv 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 78 3.12.4 Pig Production .................................................................................................................................. 78 3.12.4.1 Pig Population Trend...................................................................................................... 78 3.12.5 Chicken Production........................................................................................................................ 81 3.12.5.1 Chicken Population ........................................................................................................ 81 3.12.5.2 Chicken Population Trend.............................................................................................. 81 3.12.5.3 Chicken Flock Size......................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 82 3.12.6 Other Livestock............................................................................................................................... 82 3.12.7 Pests and Parasites Incidences and Control................................................................................ 84 3.12.7.1 Deworming..................................................................................................................... 84 3.12.8 Access to Livestock Services.......................................................................................................... 84 3.12.8.1 Access to livestock extension Services.......................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to village watering points/dam .......................................................................... 84 3.12.9 Animal Contribution to Crop Production ................................................................................... 87 3.12.9.1 Use of Draft Power......................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 88 3.12.9.3 Use of Compost ............................................................................................................ 88 3.12.10 Fish Farming ................................................................................................................................... 88 3.13 Poverty Indicators......................................................................................................................................... 91 3.13.1 Access to Infrastructure and Other Services.................................................................................... 91 3.13.2 Type of Toilets.................................................................................................................................. 91 3.13.3 Household’s assets............................................................................................................................ 92 3.13.4 Sources of Light Energy................................................................................................................... 92 3.13.5 Sources of Energy for Cooking........................................................................................................ 92 3.13.6 Roofing Materials............................................................................................................................. 92 3.13.7 Access to Drink Water...................................................................................................................... 94 3.13.8 Food Consumption Pattern............................................................................................................... 95 3.13.8.1 Number of Meals per Day.............................................................................................. 95 3.13.8.2 Meat Consumption Frequencies..................................................................................... 95 3.13.8.3 Fish Consumption Frequencies...................................................................................... 98 3.13.9 Food Security.................................................................................................................................... 98 3.13.10 Main Source of Cash Income........................................................................................................... 98 PART IV: MBEYA PROFILES................................................................................................................................. 99 4.1.0 Region Profile.................................................................................................................................... 99 4.1.1 Mbeya RegionProfile............................................................................................................................. 4.1.2 District Profiles................................................................................................................................104 4.2.1. Chunya.............................................................................................................................................105 4.2.2 Mbeya Rural ....................................................................................................................................107 4.2.3 Kyela................................................................................................................................................109 4.2.4 Rungwe ............................................................................................................................................110 4.2.5 Ileje ..................................................................................................................................................110 4.2.6 Mbozi ...............................................................................................................................................114 4.2.7 Mbalari.............................................................................................................................................116 4.2.8 Mbeya Urbani ..................................................................................................................................117 ACRONYMS _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics, Tanzania Mainland and the Office of the Chief Government Statistician, Tanzania Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the President’s Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (data on household characteristics and livestock count were collected in 1993/1994 while data on crop area and production were collected in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Shinyanga region data disaggregated to district level. Due to numerous variables collected, the analysis is based on the most important smallholder variables. More variables can be found in the table of results annex. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Special thanks should go to all those who in one-way or the other contributed to the success of the survey. In particular, I would like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician, Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Finally, let me extend my sincere gratitude to all professional staff of the National Bureau of Statistics and Office of the Chief Government Statistician, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. I am also indepted to the respondents, particularly the heads of households, for spending much of their valuable time in providing data and all necessary information during enumeration. Certainly without their dedication, the census would not have been successful. Albina A. Chuwa Director General, National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Mbeya region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Mbeya region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Mbeya region was 372,844 out of which 232,209 (62.3%) were involved in growing crops only, 1,195 (0.3%) rearing livestock only, 85,121 (32%), 139,441 (37.4%) were involved in crop production as well as livestock keeping. No pastoralist were found in the district. Most of the agricultural households ranked annual crop farming as an activity that provides most of their livelihood/ income followed by off farm income, fishing/hunting, tree/forest resources, permanent crop farming, livestock keeping/herding and remittances. The district with the highest literacy rate for heads of households was Chunya (76%) followed by Rungwe (73%), Mbeya Rural (72%), Mbozi (70%), Ijeje (69%), Ileje (69%), Mbeya Urban (69%), Mbarali (65%) and Kyela (62%). The literacy rate for the heads of households in the region was 69.4 percent. The number of heads of agricultural households with formal education in Mbeya region was 251,109 (68%), those without formal education were 116,395 (31%) and those with only adult education were 5,340 (1%). The majority of heads of agricultural households (64%) had primary level education whereas only 4 percent had post primary education. In Mbeya region there was 158,917 households (42%) with one household member engaged in off-farm income generating activity, 102,665 households (28%) had two members involved in off-farm income generating activities and 22,487 households (6%) had more than two members involved in off-farm income generating activities. Only 24 percent of household members were not involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 672,227 ha. The regional average land area utilised for agriculture per household was only 1.5 ha. This figure is below the national average which is estimated at 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 428,533 hectares out of which 160,820 hectares (37.5%) were planted during short rainy season and 267,713 hectares (62.5%) during long rainy season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census viii The area planted with cereals was 328,941 ha 71.6% of the total planted area for annual crops), followed by pulses with 65,043 ha (14.2%), oil seeds & oil nuts 30,141 ha (6.6%). root and tubers 27,141 ha (5.9%), fruits and vegetables 3,982 ha (0.9%) and Annual cash crops that are mainly constituted of pyrethrum and tobacco had got the least planted area of about 3,979 ha (0.9%) Maize Maize is the dominant annual crop grown in Mbeya region and it had a planted area 3 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 47 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are beans, paddy, sorghum, groundnuts, cassava, finger millet, irish potatoes, wheat, sunflower, tobacco, bulrush millet, field peas and tomatoes There has been little change in production over the years 1995 to 2003. However the area planted increased sharply over the period 1997 to 1998 and remained constant ever since. The increase implanted are has not resulted in an increase in production as the productivity decreased over the same period. The average area planted with maize per maize growing household was 0.7 hectares; however it ranged from 0.4 hectares in both Rungwe and Kyela districts to 1 hectare in Chunya district. Mbozi district had the largest area of maize (67,736 ha) followed by Chunya (40,508 ha), Mbeya Rural (37,429 ha), Mbarali (32,101 ha), Rungwe 28,982 ha), Ileje (14,551 ha), Kyela (7,036 ha) and Mbeya Urban (3,400 ha) Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Mbeya region during the long rainy season was 80,091. This represented 23.3 percent of the total households growing annual crops in Mbeya region in the wet season. The total production of paddy was 62,780 tonnes from a planted area of 54,743 hectares resulting in a yield of 1.15 t/ha Cassava The number of households growing cassava in the region was 41,254. This represents 11.1 percent of the total crop growing households in the region Fruit and Vegetables The total planted area of fruits and vegetables was 3,982 hectares. The most cultivated fruit and vegetable crop was the tomatoes with a production of 1,218 hectares. Permanent Crops The area of smallholders planted with permanent crops was 153,578 hectares (25% of the total area planted with crops in the region). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census ix The most important permanent crop in Mbeya region was coffee which had for a planted area of 59,460 ha, (39% of the planted area of all permanent crops) followed by banana (52,715 ha, 35%), cocoa (15,462 ha, 10%), mango (8,359 ha, 5%), tea (4,608 ha, 3%), avocado (3,662 ha, 2%) and palm oil (3,414 ha, 2%). Improved Seeds The planted area with improved seeds was estimated at 60,124 ha which represented 13 percent of the total area planted with annual crops and vegetables. The percentage use of improved seed in the wet season was 12.4 percent, which was lower than the corresponding percentage use for the dry season (19.9%). Use of Fertilizers The use of fertilisers on annual crops was relative small with an application on a planted area of only 162,977 ha (35.5% of the total area planted with annual crops in the region. Inorganic fertiliser was applied to 83,890 hectares which represented 18.3 percent of the total planted area (51.5 % of the area planted with fertiliser application in the region). This was followed by farm yard manure (55,610 ha, 34.1%) and compost was used on a small area of 23,477 hectares which represented 14.4 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Mbozi district (36.3%) followed by Mbeya Rural (19.5%), Rungwe (13.8%), Ileje (10.0%), Chunya (9.8%), Mbarali (5.1%), Kyela (3.2%) and Mbeya Urban (2.4%) Irrigation In Mbeya region, the area of annual crops under irrigation was 46,241 ha representing 10 percent of the total area planted. The area under irrigation during the short rainy season was 3,229 ha accounting for 7 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the dry season, 59.3 percent of the area planted with cereals was irrigated, whilst 72.1 percent of the cereals were irrigated in the wet season. Crop Storage The results for Mbeya region show that there were 336,776 crop growing households (90.6% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 296,438 households storing 60,824 tonnes as of 1st October 2003. This was followed by beans and other pulses (161,882 households, 4,923t), paddy (63,146 households, 12,747t), sorghum and millets (41,935 households, 8,250t), groundnuts and bambaranuts (22,915 households, 909t), wheat (9,060 households, 1,147t) and coffee (4,693 households, 287t). Crop Marketing The number of households that reported selling crops was 292,480 which represented 80.3 percent of the total number of crop growing households. The percentage of crop growing households selling crops was highest in Mbozi (90%) followed EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census x by Rungwe (88%), Mbeya Rural and Kyela districts had (85%) each, Ileje (84%), Mbeya Urban (77%) Mbarali (53%) and Chunya (43%) Agricultural Credit The census result shows that in Mbeya region very few agricultural households (21,141 households, 6% of agricultural households) accessed credit. Out of which (16,887 households, 80%) were male-headed households and (4,254 households, 20%) were female. In Mbozi district only male headed households got agricultural credit whereas Ileje district had the highest percentage of female headed households (75%) that got agricultural credits. Crop Extension Services The number of Agricultural households that received crop extension was 153,818 (41% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Chunya having a relatively high proportion of households (92%) that received crop extension messages in the district followed by Mbeya Urban (75%), Mbeya Rural (68%), Mbozi (39%), Ileje (35%), Rungwe (29%), Mbarali (12%) and Kyela (8%) Soil Erosion and Water Harvesting Facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 61,540 representing 17 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Ileje district (31% of the agricultural households in the district), followed by Rungwe (25%), Mbeya Rural (23%), Mbozi and Mbeya Urban districts had (21%) each, Mbarali (13%), Chunya (2%) and Kyela (0.2%) (Chart 3.121). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 941,077. Cattle rearing are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 5.6 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 898,050 (95.4 % of the total number of cattle in the region), 40,982 (4.4%) were dairy breeds and only 2,045 (0.2%) were beef breeds. Goats The number of goat-rearing-households in the region was 59,999 (16% of all agricultural households) with a total of 358,789 goats giving an average of 6 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 11,605 (3% of all agricultural households in Mbeya region) rearing 66,031 sheep, giving an average of 6 heads of sheep per sheep-rearing household. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census xi Pigs The number of pig-rearing agricultural households in Mbeya region was 78,724 (21% of the total agricultural households in the region) rearing 227,036 pigs. This gives an average of 3 pigs per pig-rearing household. Chicken The number of households keeping chicken was 256,387 raising about 2,559,913 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Mbeya region ranked third out of the 21 Mainland regions Use of Draft Power The region has 114,206 oxen and they were mainly found in 4 districts. The district with the largest number of oxen was Mbozi (43,361). This was followed by Mbarali (26,073 oxen), Chunya (18,123 oxen) and Kyela (17,496 oxen). The number of oxen in the region accounted for 5 percent of the total oxen found on the Mainland. Fish Farming The number of households involved in fish farming in Mbeya region was 1,713, representing 0.5 percent of the total agricultural households in the region. Rungwe was the leading district with 578 households (34% of agricultural households involved in fish farming). This was followed by Mbozi (534 households, 31%), Ileje (256 households, 15%), Mbeya Rural (243 households, 14%), Chunya (84 households, 5%) and Mbeya Urban (17 households, 1%). Fish farming was not practiced in Kyela and Mbarali districts. iv) Poverty Indicators Availability of Toilets It was estimated that 92 percent of all rural agricultural households used the traditional pit latrines, pit latrine and 4 percent had flush toilets and 2 percent used improved pit latrines. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 2 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (53.4% of households) followed by bicycle (35.1%)), iron (23.8%)), wheelbarrow (5.5%), mobile phone (1.8%), vehicle (1.4%), television/video (1.3%), and landline phone (0.4%). Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region with 68 percent of the total rural households using this source, followed by hurricane lamp (26%), pressure lamp (3%), mains electricity (2%) and firewood (1%). The remaining sources of energy for lighting were insignificant. Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96 percent of all rural agricultural households in Mbeya region. This was followed by charcoal (3%) and crop residues (1%). The rest of energy sources EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ _______________________________________________________________________________________________________________________ ____ Tanzania Agriculture Sample Census xii accounted for 0.7 percent. These were mains electricity and solar had (0.2%) each, paraffin/kerosene, bottled gas and livestock dung each (0.1%) and other sources of energy for cooking (0.02%). Roofing Materials The most common roofing material for roofing of the main dwelling was grass and/or leaves and which was used by 52 percent of the rural agricultural households. This was followed by iron sheets (42%), grass/mud (5%) and tiles (1%). The remaining roofing materials were below one percent Number of Meals per Day About 69 percent of the holders in the region took two meals per day, 28 percent took three meals, 3 percent took one meal and 0.4 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 28 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 6 percent whereas those with little problems represent 5 percent. About 3 percent of agriculture households always faced food shortages whilst 58 percent did not experience any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 50 percent of all rural agricultural households. The second main cash income earning activity was selling cash crops (17%), businesses (11%), other casual cash (9%), wages & salaries (3%), livestock (2%), forest products (2%), other (2%), livestock products (1%) and fishing (1%). ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .............................................................................................................................................. 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 22 3.3 Area, Production and Yield of Root and Tuber Crops by Season ..................................................................... 27 3.4 Area, Production and Yield of Pulse by Season................................................................................................. 28 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 37 3.8 Land Clearing Methods....................................................................................................................................... 48 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season...................................... 51 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Long Rainy Season............................................................................................................................ 51 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ............................................... 62 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 65 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 66 3.14 Access to Inputs................................................................................................................................................... 69 3.15 Number of Households and Chickens Raised by Flock Size..............................................................................82 3.16 Number of Other Livestock by Type of Livestock and District ........................................................................ 84 3.17 Mean distances from dwellings to infrastructure and services by districts ....................................................... 91 3.18 Number of Households by Number of meals the Household normally takes per Day and District ................. 95 List of Charts 3.1 Agricultural Households by Type of Holdings................................................................................................... 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 11 3.3 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District.............................................................................. 15 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status.................................................................................................... 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status.................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Number of Households by number of members with Off Farm Income – Mbeya Region............................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities................................. 17 3.11 Utilized and Usable Land per Household by District......................................................................................... 17 3.12 Land Area by Type of Land Use......................................................................................................................... 18 3.13 Area Planted with Annual Crops (ha) by Season ............................................................................................... 18 3.14 Area Planted with Annual Crops by Season and Region................................................................................... 18 3.15 Area Planted with Annual Crops per Household by Season and District.......................................................... 20 3.16 Planted Area for the Main Annual Crops (ha).................................................................................................... 20 3.17a Planted Area per Household by Selected Crops..................................................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type..................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season........................................................................ 22 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 22 3.20 Time Series Data on Maize Production – Mbeya Region.................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Mbeya Region....................................................................... 23 3.23 Total Planted Area and Area of Paddy per Household by District .................................................................... 26 3.24 Time Series Data on Paddy Production – Mbeya Region.................................................................................. 26 3.25 Time Series of Paddy Planted Area and Yield – Mbeya Region....................................................................... 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District................................................................... 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................... 26 3.28 Area planted with Cassava during the census/survey years................................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District ............................................................... 28 3.31 Total Area Planted and Planted Area per Household by District....................................................................... 28 3.32 Area Planted and Yield of Major Pulse Crops ................................................................................................... 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 30 ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only)........................................ 30 3.35 Time Series Data on Bean Production – Mbeya Region.................................................................................... 30 3.36 Time Series of Beans Planted Area and Yield - Mbeya..................................................................................... 32 3.37 Area Planted and Yield of Major Oil Seed Crops.............................................................................................. 32 3.38 Time Series Data on Groundnut planted area – Mbeya Region......................................................................... 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District ........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) .............................. 33 3.42 Area Planted and Yield of Fruit and Vegetables................................................................................................ 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 35 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only)................................... 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District .................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District ..................................... 37 3.47 Area planted with Annual Cash Crops ............................................................................................................... 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District................................... 40 3.49 Area Planted for Annual and Permanent Crops.................................................................................................. 40 3.50 Area Planted with the Main Permanent Crops ................................................................................................... 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District ................................... 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District......................... 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 45 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District.................. 48 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season ..................................... 48 3.57 Area Cultivated by Cultivation Method...............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District..................................................................................... 50 3.59 Planted Area of Improved Seeds – Mbeya ..........................................................................................................50 3.60 Planted Area with Improved Seed by Crop Type............................................................................................... 50 3.61 Percentage of Crop Type Planted Area with Improved Seed – Annuals........................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer .......................................................................................... 51 3.63 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season..................................................... 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District ........................................................ 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals........................................................................ 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 53 3.68a Planted Area with Compost by Crop Type......................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type ................................................................................. 53 3.68c Proportion of Planted Area Applied with Compost by District......................................................................... 53 3.69 Planted area (ha) by Pesticide use....................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type ....................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season ................... 54 3.73 Planted Area applied with herbicides by Crop Type.......................................................................................... 55 3.74 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season..................... 55 3.76 Planted Area applied with Fungicides by Crop Type......................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season..................... 56 3.79 Area of Irrigated Land......................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District......................................................... 57 3.81 Time Series of Households with Irrigation – Mbeya ......................................................................................... 57 8.82 Number of Households with Irrigation by Source of Water.............................................................................. 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................... 57 3.84 Number of Households with Irrigation by Method of Field Application.......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type.............................................................................. 59 3.86 Number of households by Storage Methods....................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 3.88 Normal Length of Storage for Selected Crops ................................................................................................... 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .................................................. 62 3.90 Number of Households by Purpose of Storage and Crop Type......................................................................... 62 3.91a Percentage of Households Processing Crops by District ................................................................................... 63 3.91b Percent of Households Processing Crops by District......................................................................................... 63 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 63 ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 63 3.94 Number of Households by Type of By-product................................................................................................. 64 3.95 Use of Processed Product.................................................................................................................................... 64 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 64 3.97 Location of Sale of Processed Products.............................................................................................................. 64 3.98 Percent of Household selling Processed Products by Outlets for Sale and Distance.........................................65 3.99 Number of Crop Growing Households Selling Crops by District ..................................................................... 65 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 65 3.101 Percentage Distribution of Households Receiving Credit by Main Sources..................................................... 66 3.102 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 66 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit .................................................... 66 3.104 Reasons for Not using Credit (% of Household)................................................................................................ 66 3.105 Number of Households Receiving Extension Advice........................................................................................ 67 3.106 Number of Households Receiving Extension by District .................................................................................. 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 67 3.108 Number of Households Receiving Extension by Quality of Services ............................................................... 67 3.109 Number of Households by Source of Inorganic Fertiliser ................................................................................. 69 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser.................................................. 69 3.111 Number of Households by Source of Improved Seed........................................................................................ 70 3.112 Number of Households reporting Distance to Source of Improved Seed.......................................................... 70 3.113 Number of Households by Source of Insecticide/Fungicide.............................................................................. 70 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 70 3.115 Number of Households with Planted Trees by District...................................................................................... 71 3.116 Number of Planted Trees by Species...................................................................................................................71 3.117 Number of Trees Planted by Smallholders by Species and District .................................................................. 71 3.118 Number of Trees Planted by Location................................................................................................................ 71 3.119 Number of Households by purpose of Planted Trees......................................................................................... 72 3.120 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 72 3.121 Number of Households with Erosion Control/Water Harvesting Facilities by District.................................... 72 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 72 3.123 Total Number of Cattle ('000') by District.......................................................................................................... 74 3.124 Numbers of Cattle by Type and District............................................................................................................. 74 3.125 Cattle Population Trend ...................................................................................................................................... 76 3.126 Improved Cattle Population Trend...................................................................................................................... 76 3.127 Total Number of Goats ('000') by District.......................................................................................................... 76 3.128 Goat Population Trend........................................................................................................................................ 78 3.129 Total Number of Sheep by District..................................................................................................................... 78 3.130 Sheep Population Trend...................................................................................................................................... 80 3.131 Total Number of Pigs by District........................................................................................................................ 80 3.132 Pig Population Trend........................................................................................................................................... 80 3.133 Total Number of Chicken by District ................................................................................................................. 82 3.134 Chicken Population Trend .................................................................................................................................. 82 3.135 Number of Improved Chicken by Type and District...........................................................................................84 3.136 Improved Chicken Population Trend.................................................................................................................. 84 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 84 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 86 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........ 86 3.140 Number of Households by Distance to Veterinary Clinic.................................................................................. 87 3.141 Number of Households by Distance to Veterinary Clinic and District.............................................................. 87 3.142 Number of Households by Distance to Village Watering Point ........................................................................ 87 3.143 Number of Households by Distance to Watering Point and District................................................................. 87 3.144 Number of Households using Draft Animals ..................................................................................................... 87 3.145 Number of Households using Draft Animals by District................................................................................... 87 3.146 Number of Households using Organic Fertiliser................................................................................................ 88 3.147 Area of Application of Organic Fertiliser by District ........................................................................................ 88 3.148 Number of Households Practicing Fish Farming – Mbeya................................................................................ 88 3.149 Number of Households Practicing Fish Farming by District – Mbeya ............................................................. 91 3.150 Fish Production.................................................................................................................................................... 91 3.151 Agricultural Households by Type of Toilet Facility .......................................................................................... 92 3.152 Percentage Distribution of Households Owning the Assets............................................................................... 92 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................92 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 92 3.155 Percentage Distribution of Households by Type of Roofing Material .............................................................. 94 ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District.................................................. 94 3.157 Percentage of Households by Main Source of Drinking Water and Season...................................................... 94 3.158 Percentage of Households by Distance to Main Source of Water and Season.................................................. 94 3.159 Number of Agriculture Households by Number of Meals per day.................................................................... 95 3.160 Number of Households by Frequency of Meat and Fish Consumption..............................................................95 3.161 Percentage Distribution of the Number of Households by Main Source of Income......................................... 97 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................... 19 3.9 Area planted and Percentage During the Short Rainy Season by District......................................................... 21 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District .................................. 21 3.11 Planted Area and Yield of Maize by District ..................................................................................................... 24 3.12 Area Planted per Maize Growing Household..................................................................................................... 24 3.13 Planted Area and Yield of Paddy by District ..................................................................................................... 25 3.14 Area Planted per Paddy Growing Household..................................................................................................... 25 3.15 Planted Area and Yield of Cassava by District .................................................................................................. 29 3.16 Area Planted per Cassava Growing Household.................................................................................................. 29 3.17 Planted Area and Yield of Beans by District...................................................................................................... 31 3.18 Area Planted per Beans Growing Household..................................................................................................... 31 3.19 Planted Area and Yield of Groundnuts by District ............................................................................................ 34 3.20 Area Planted per Groundnuts Growing Household............................................................................................ 34 3.21 Planted Area and Yield of Tomato by District................................................................................................... 36 3.22 Area Planted per Tomato Growing Household .................................................................................................. 36 3.23 Planted Area and Yield of Cabbage by District ..................................................................................................38 3.24 Area Planted per Cabbage Growing Household................................................................................................. 38 3.25 Planted Area and Yield of Chillies by District................................................................................................... 39 3.26 Area Planted per Chillies Growing Household .................................................................................................. 39 3.27 Planted Area and Yield of Cotton by District..................................................................................................... 41 3.28 Area Planted per Cotton Growing Household.................................................................................................... 41 3.29 Planted Area and Yield of Tobbaco by District ................................................................................................. 42 3.30 Area Planted per Tobacco Growing Household................................................................................................. 42 3.31 Planted Area and Yield of Coconuts by District ................................................................................................ 44 3.32 Area Planted per Coconuts Growing Household................................................................................................ 44 3.33 Planted Area and Yield of Oranges by District.................................................................................................. 46 3.34 Area Planted per Orange Growing Household................................................................................................... 46 3.35 Planted Area and Yield of Banana by District ................................................................................................... 47 3.36 Area Planted per Banana Growing Household................................................................................................... 47 3.37 Planted Area and Yield of Cashew nut by District............................................................................................. 49 3.38 Area Planted per Cashew nut Growing Household............................................................................................ 49 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 58 3.40 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 58 3.41 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 61 3.42 Number of Households and Percent of Total Households Selling Crops by District........................................ 61 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 68 3.44 Number and Percent of Crop Growing Households using Improved Seed by District .....................................68 3.45 Number and percent of smallholder planted trees by district............................................................................. 73 3.46 Number and Percent of Households with water Harvesting Bunds by District................................................. 73 3.47 Cattle population by District as of 1st Octobers 2003.........................................................................................75 3.48 Cattle Density by District as of 1st October 2003...............................................................................................75 3.49 Goat population by District as of 1st Octobers 2003 ......................................................................................... 77 3.50 Goat Density by District as of 1st October 2003................................................................................................ 77 3.51 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 79 3.52 Sheep Density by District as of 1st October 2003.............................................................................................. 79 3.53 Pig population by District as of 1st Octobers 2003............................................................................................ 81 3.54 Pig Density by District as of 1st October 2003 .................................................................................................. 81 ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvii 3.55 Number of Chickens by District as of 1st October 2003 ................................................................................... 83 3.56 Density of Chickens by District as of 1st October 2003.................................................................................... 83 3.57 Number and Percent of Households Infected with Ticks by District ................................................................ 85 3.58 Number and Percent of Households Using Draft Animals by District.............................................................. 85 3.59 Number and Percent of Households Using Farm Yard Manure by District...................................................... 89 3.60 Number and Percent of Households using Compost by District........................................................................ 89 3.61 Number and Percent of Households Practicing Fish Farming by District......................................................... 90 3.62 Number and Percent of Households without Toilets by District ....................................................................... 89 3.63 Number and Percent of Households using Grass/Leaves for roofing material by District ............................... 92 3.64 Number and Percent of Households eating 3 meals per day by District ........................................................... 92 3.65 Number and Percent of Households eating Meat Once per Week by District .................................................. 95 3.66 Number and Percent of Households eating Fish Once per Week by District.................................................... 95 3.67 Number and percent of Households Reporting food insufficiency by District ................................................. 97 ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Mbeya region is located in South West Corner of the Southern Highlands of Tanzania. The region lies between Latitude 7” and 90 - 310 South of Equator, and between Longitudes 320 and 350 East of the Greenwich Meridian. Mbeya region lies at an altitude of 500 meters above sea level with high peaks of 2,981 meters above sea level at rungwe higher altitudes. Mbeya region shares borders with Zambia and Malawi to the South, Rukwa Region to the West; Taborab and Singida Regions to the North; and Iringa Region to the East. Tunduma and Kasumulu in Mbozi and Kyela districts respectively are the main entries into the neighbouring countries of Zambia and Malawi 1.3 Land Area The region has an area of 63,420 square kilometers, which is 6.4% of the total area of Tanzania Mainland. About forty seven percent of the land area is arable 1.4 Climate 1.4.1 Temperature Mbeya region lies at an altitude ranging from 500 meters to 2,400 meters above sea level. The temperatures range between 160C in the highlands and 250C in the lowland areas. 1.4.2 Rainfall Mbeya Region receives abundant and reliable rainfall. Most districts have a mono-modal rainfall pattern. The dry season normally begins in June and ends in December whilst the Wet season runs from January to May. Annual rainfall varies from 650 mm to more than 2,600 mm. 1.5.1 Administrative Setup The region comprises eight districts namely Chunya, Mbeya Rural, Kyela, Rungwe, Ileje, Mbozi, Mbarali and Mbeya Urban. The region headquarters is located in Mbeya Municipality. 1.6 Population Based on the 2002 Population and Housing Census, the population of Mbeya region was 2,070,046. It is among the most populous regions with 6.6% of the Tanzania Mainland Population. In terms of population density Mbeya region is ranked fourth. ILLUSTRATIONS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 1.7 Socio - Economic Indicators The economy of Mbeya region mainly depends on subsistence agriculture. About 80% of the population depends on agriculture. On the average, agriculture accounts for over 40% of the region’s Gross Domestic Product (GDP) and about 80% of the population are engaged in agriculture. The region is famous for producing both food and cash crops. The main food crops produced in Mbeya region include: maize, paddy, beans and sorghum, irish potatoes, and sweet potatoes. The main cash crops include coffee, Pyrethrum and tea. Livestock keeping is also an important economic activity in the region. • Food Crops Mbeya region has suitable land for agricultural production main crops include maize, paddy, sorghum, millet banana and beans. • Cash Crops The main cash crops include: coffee, banana, pyrethrum, banana, paddy and maize • Livestock Livestock kept are: cattle; goats; sheep; pigs, chickens and ducks • Industrial Activities Small scale industrial activities, small-scale mining and other petty businesses. Most rural farmers participate in activities that are related to small- scale industries such as carpentry, weaving; pottery; brick making; skin/hides etc. Mbeya boasts of accommodating the Kiwira Coal Mine and Mbeya Cement Factory 1.7.1: Transport There is a total of 4,831 km of road network in the region. Trunk roads, Regional roads, district roads and feeder roads. Of these, the feeder roads, which cover the distance of 1,463 km, are almost impassable during the wet seasons. From Dar es Salaam, Mbeya region can be reached by road, air and railway (TAZARA). It is also well connected by road to the neighbouring regions. Also, Mbeya region has reliable marine transportation in Lake Nyasa. There are also other communication networks in the region such as postal, telephone telex and fax services. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2. 0 INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Mbeya region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff was used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census for Mbeya region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and districts. Comparisons are also made with past censuses and surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Survey, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The results are divided into four main sections which are household characteristics, crop results, livestock results and Poverty indicators. Compared to previous more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Mbeya region was 372,844. The largest number of agriculture households was in Mbozi (103,486) followed by Rungwe (67,323), Mbeya Rural (53,865), Mbarali (42,718), Chunya (38,262) Kyela (34,192), Ileje (25,819) and Mbeya Urban (7,180) (Map 3.1). The highest density of households was found in Mbeya Urban (838km2, 10%) and Rungwe 60km2, 14%) (Map 3.2). Most households (232,209, 62.3%) were involved in growing crops only, 1,195 (0.3%) rearing livestock only and 139,441 (37.4%) were involved in crop production as well as livestock keeping. No pastoralists were found in the region (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). Livelihood Activities/Source of Income The census results for Mbeya region indicates that all of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm Income, permanent crop farming, livestock keeping/herding tree/forest resources, fishing/hunting and remittances (Table 3.1). Sex and Age of Head of Households The number of male-headed agricultural households in Mbeya region was 278,613 (75% of the total regional agricultural households) whilst the female-headed households were 94,232 (25% of the total regional agricultural households). The mean age of household heads was 44 years (43 years for male heads and 48 years for female heads) (Chart 3.2) The percentage District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt- ances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 1 6 3 2 5 7 4 Mbeya Rural 1 6 5 2 7 4 3 Kyela 1 2 3 4 6 7 5 Rungwe 1 2 3 5 7 4 6 Ileje 1 2 3 4 6 7 5 Mbozi 1 4 5 3 6 7 2 Mbarali 1 7 5 2 6 4 3 Mbeya Urban 1 5 4 2 6 7 3 Total 1 3 4 2 7 6 5 Chart 3.1 Agriculture Households by Type - Mbeya Crops Only, 232,209, 62.3% Pastoralists, 0, 0% Livestock Only, 1,195, 0.3% Crops & Livestock, 139,441, 37.4% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 19 9 4 /9 5 EAS 19 9 5/9 6 EAS 19 9 6 /9 7 IAS 19 9 7/9 8 DIAS 19 9 8 /9 9 NSCA 2 0 0 2 /0 3 Year Percent of Households Male headed households Female headed households Mbeya Urban Mbeya Rural Mbozi Ileje Chunya 157 45 9 48 85 42 4 10 Kyela Rungwe Mbarali Mbeya Urban Mbeya Rural Chunya Ileje Mbozi 67,323 7,180 25,819 103,486 38,262 42,718 34,192 53,865 Kyela Rungwe Mbarali Number of Agricultural Households Total Number of Agricultural Households by District MAP 3.01 MBEYA MAP 3.02 MBEYA Number of Agricultural Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 140 to 175 105 to 140 70 to 105 35 to 70 0 to 35 RESULTS 12 Mbeya Rural Mbeya Urban Mbozi Rungwe Kyela Ileje Chunya 99.2% 79.8% 301.7% 157.3% 67.3% 62.9% 165.1% 36.9% Mbarali 300 to 375 225 to 300 150 to 225 75 to 150 0 to 75 Mbeya Rural Mbeya Urban Mbarali Kyela Ileje Mbozi 7,124 53,743 42,619 67,183 33,889 25,754 103,170 38,168 Chunya Rungwe 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 Number of Crop Growing Households Number of Crop Growing Households by District MAP 3.03 MBEYA MAP 3.04 MBEYA Percent of Crop Growing Households by District Tanzania Agriculture Sample Census Percent of Crop Growing Households Number of Crop Growing Households Number of Agricultural Households Per Square Kilometer RESULTS 13 Kyela Ileje Mbarali Chunya Mbozi Mbeya Rural Mbeya Urban 54 75 28 7 4 27 36 156 Rungwe 140 to 175 105 to 140 70 to 105 35 to 70 0 to 35 Mbeya Urban Mbeya Rural Kyela Ileje Chunya 36% 29% 79% 27% 30% 113% 42% 8% Mbozi Rungwe Mbarali 100 to 125 75 to 100 50 to 75 25 to 50 0 to 25 Number of Crop Growing Households Per Square Km Number of Crop Growing Households Per Square Kilometer of Land by District MAP 3.05 MBEYA MAP 3.06 MBEYA Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census Percent of Crop and Livestock Households Number of Crop Growing Households Per Square Km Percent of Crop and Livestock Households RESULTS 14 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Mbeya region had a total rural agricultural population of 1,608,781 of which 780,102 (48%) were males and 828,679 (52%) were females. Whereas age group 0-14 constituted 43 percent of the total rural agricultural population, age group 15–64 (active population) accounted for 52 percent of the rural agricultural population. Mbeya region had an average household size of 4.3 persons per households with Rungwe district having the lowest household size of 4 people per households (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Mbeya region had a total literacy rate of 68 percent. The highest literacy rate was found in Kyela district (70%) followed by Mbeya Urban district (69%), Ileje (68%), Rungwe (66%), Mbozi (64%) and Mbeya Rural (63%). Mbarali and Chunya districts had the lowest literacy rates of 56 and 61 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 69.4 percent. The literacy rate for the male head was 79 and 21 percent for the female head. The literacy rate of male heads was higher than that of females heads in all districts. The district with the highest literacy rate for heads of households was Mbozi (74.4%) followed by Mbeya Urban (73%), Chunya (71%), Mbeya Rural (70%), Kyela (69%), Ileje (69%), Mbarali (67%) and Rungwe (62%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - MBEYA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.5 Literacy Rates of Head of Household by Sex and District - MBEYA 0 25 50 75 100 Chunya Mbeya Urban Mbozi Kyela Ileje Mbeya Rural Mbarali Rungwe District Percent Male Female Total Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 Kyela Mbeya Urb Ileje Rungwe Mbozi Mbeya Rur Chunya Mbarali District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 42.4 percent of members of agricultural households aged 5 years and above in the region had completed different levels of education and 30.6 percent were still attending school. Those who have never attended school were 27.1 percent (Chart 3.6). Agricultural households in Ileje district had the highest percentage (44.9%) of population aged 5 years and above who had completed different levels of education. This was followed by Kyela (44.5%), Mbeya Urban (44.2%), Mbozi (43.6%), Rungwe and Chunya districts had (42.3%) each. Mbeya Rural and Mbarali districts had the lowest percentages of 38.8 and 40.3 respectively. The number of heads of agricultural households with formal education in Mbeya region was 251,109 (68%), those without formal education were 116,395 (31%) and those with only adult education were 5,340 (1%). The majority of heads of agricultural households (64%) had primary level education whereas only 4 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Mbeya region, Mbozi district had the highest percentage (69% for primary and 3% for secondary). This was followed by Chunya (66% primary and 3% secondary), Kyela (63% primary and 4% secondary) and Ileje and Mbeya Urban had (62% primary) each and (2% and 7% secondary respectively). Rungwea had the lowest percentage of heads of agricultural households with primary education (59%) and secondary education (2%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Mbeya with 76.2 percent of households having at least one member with off-farm income. In Mbeya region there was 158,917 Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Never Attended 27% Completed 42% Attending School 31% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 Ileje Kyela Mbeya Urb Mbozi Rungwe Chunya Mbarali Mbeya Rur District Percent Attending School Completed Never Attended C hart 3 .8 Pe rce ntage Distribution of He ads of House hold by Educational Attainme nt Primary Education 64% No Education 31% Post Primary Education 4% Adult Education 1% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 households (56%) with only one household member engaged in off-farm income generating activity, 102,665 households (36%) had two members involved in off-farm income generating activities and 22,487 households (8%) had more than two members involved in off-farm income generating activities. Mbeya Rural district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Mbozi (92%), Mbeya Urban 91%), Chunya (86%) and Mbarali (71%). Ileje and Kyela districts had (64%) of households each with off-farm income. Rungwe district had the lowest percentage (42%) of households with off-farm icome. 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 672,227 ha. The regional average land area utilised for agriculture per household was only 1.5 ha. This figure is below the national average which is estimated at 2.0 hectares. Of the total land available to smallholders 85 percent was utilised. Only 15 percent of land available to smallholders was not utilized. (Chart 3.11). Chart 3.9 Number of Household by Number of Members Engaged in Off-farm Income Generating Activities None, 88,776, 24% Two, 102,664, 28% More than Two, 22,487, 6% One, 158,917, 42% Chart 3.10 Percentage Distribution of Agricultural Households Members Engaged in off-farm Income Generating Activities 0% 20% 40% 60% 80% 100% Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Districts Percent Mo re o r Two Two One No ne C hart 3.11 Utilized and Usable Land pe r Household by District 0.0 1.0 2.0 3.0 4.0 Chunya Mbarali Mbozi Ileje Mbeya Rur Kyela Rungwe Mbeya Urb Districts Area/household 75 80 85 90 95 100 Percentage utilized T otal Usable Area available (ha) Area utilised (Ha) Percent Utilisation RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 Differences in land area utilised per household exist between districts with Chunya, utilizing between 2.3 hectares and (Mbarali and Mbozi) utilising 1.8 hectares per household each. The smallest land area utilised per household was found in Mbeya Urban district with (0.9 ha) per household. The percentage utilized of the usable land per household was highest in Rungwe (98%) and lowest in Mbarali (85%) (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 382,607 hectares (56.9% of the total land available to smallholders in Mbeya), followed by temporary mixed crops (71,336 ha, 10.6%), permanent mono crop (40,612 ha, 6.1%), permanent mixed crop (40,475 ha, 6.0%), uncultivated land (36,515 ha, 5.4%), fallow (32,723 ha, 4.9%), permanent/annual mix (18,111 ha, 2.7%). Area planted with trees (13,078 ha, 1.9%), area under natural bush (11,629 ha, 1.7%), unusable land (9,854 ha, 1.5%), area rented to others (8,915 ha, 1.3%), and area under pasture (6,372 ha, 0.9%). 3.3 Annual Crop and Vegetable Production Mbeya region has two rainy seasons The short rainy season (October to November) which is not very much important for crop production and the long rainy season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 459,226 hectares out of which 41,640 hectares (9.1%) were planted during dry season and 417,586 hectares (90.9%) during wet season (Chart 3.13). The average area planted per household during the short and long rainy seasons was 0.69 and 1.22 ha respectively. The district with the largest area planted per household (area planted divided by the number of households in the main growing season based on the assumption that households that grow in the off season will also grow in the main season) was Chunya (1.88 ha) followed by Mbarali (1.47 ha), Mbeya Rural, (1.36 ha), Mbozi (1.35 ha), Ileje (1.20ha), Rungwe (1.05ha), Kyela (0.92ha) and Mbeya Rural (0.73ha). rage area planted Chart 3.12 Land Area by Type of Use 56.9 10.6 6.0 6.0 5.4 4.9 2.7 1.9 1.7 1.5 1.3 0.9 0 150,000 300,000 450,000 P as ture Rented to Others Area Unus able Natural Bus h P lanted Trees P ermanent / Annual M ix Fallo w Uncultivated Us able Land P ermanent M ixed Cro ps P ermanent M o no Cro ps Tempo rary M ixed Cro ps Tempo rary M o no Cro ps La nd U se Area (hectares) Chart 3.13 Area Planted (Ha) with Annual Crops by Season Short Rainy Season, 41640, 9% Long Rainy Season, 417585, 91% C hart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Chunya Mbeya Rural Kyela Rungwe Ileje Mbozi' Mbarali Mbeya Urban District Planted Area (ha) 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percentage Planted in Short Rainy Season Short Rainy Season Long Rainy Season % Planted in Short Rainy Season Mbeya Urban Mbeya Rural Ileje 30,792ha 52,466ha 5,191ha 67,256ha 138,870ha 62,299ha 30,564ha 71,788ha Mbozi Chunya Kyela Rungwe Mbarali 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Mbeya Urban Mbeya Rural Mbozi Ileje 98% 96% 96% 97% 94% 96% 85% 86% Chunya Kyela Rungwe Mbarali 95.4 to 98 92.8 to 95.4 90.2 to 92.8 87.6 to 90.2 85 to 87.6 Percent of Utilized Land Area Utilized Land Area Expressed as a Percent of Available Land by District MAP 3.07 MBEYA MAP 3.08 MBEYA Total Planted Area With Annual Crops by District Tanzania Agriculture Sample Census Annual Crops Planted Area Percent of Utilized Land Area Annual Crops Planted Area RESULTS 19 Mbeya Urban Rungwe Ileje Mbeya Rural 138,872ha 31,613ha 34,989ha 8,024ha 58,617ha 48,728ha 65,197ha 50,124ha 0% 43.7% 7.5% 0% 61.4% 32.3% 0% 56.5% Mbozi Chunya Kyela Mbarali 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Mbeya Urban Ileje Mbeya Rural 39ha 27,034ha 10,454ha 4,113ha 0ha 0ha 0ha 0ha 0.7% 15.5% 13.5% 51.5% 0% 0% 0% 0% Mbozi Chunya Kyela Rungwe Mbarali 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Planted Area (ha) Area Planted and Percentage During the Short Rainy Season by District MAP 3.09 MBEYA MAP 3.10 MBEYA Area Planted with Cereals and Percent of Total Land Planted With Cereals by District Tanzania Agriculture Sample Census Planted Area (ha) Percentage of Planted Area During the Rainy Season Planted Area (ha) Planted Area (ha) Percent of Planted Area With Cereals Crops RESULTS 20 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 was Rungwe (0.62ha). Mbeya Urban and Rungwe districts the average area planted during the dry season is higher than that of the wet season the reverse is not true in the rest of the two districts that had dry season (Chart 3.15 and Map 3.8). The planted area occupied by cereals was 328,941 ha (71.6%of the total area planted with annuals). This was followed by pulses (65,043 hectares, 14.2%), oil seeds & oil nuts (30,141 hectares, 6.6%), roots and tubers (27,141 hectares, 5.9%), fruit and vegetables (3,982 hectares, 0.9%), and cash Crops (3,979 hectares, 0.9%). The average area planted per household during the wet season in Mbeya region was 1.22 hectares, however, there were large district differences. Chunya had the largest planted area per household (1.88 ha) followed by Mbarali (1.47 ha) and Mbozi (1.35 ha). The smallest planted area per household during the wet season was in Rungwe (0.62 ha). In Rungwe district the area planted in the short rainy season represents 51.5 percent of the total planted area. (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Mbeya region and it had a planted area 3.7 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 47 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are beans, paddy, sorghum, groundnuts, cassava, finger millet, Irish potatoes, wheat, sunflower, tobacco, bulrush millet, field peas and tomatoes (Chart 3.16). Households that grew maize, beans, paddy and sorghum have larger planted areas per household than for other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Mbeya region. The area planted with cereals was 328,941 ha 71.6% of the total planted area for annual crops), followed by pulses with 65,043 ha (14.2%), oil seeds & oil nuts 30,141 ha (6.6%). root and Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 0.50 1.00 1.50 2.00 Chunya Mbarali Mbozi' Mbeya Rural Ileje Kyela Mbeya Urban Rungwe District Area Planted (ha) Long Rainy Season Short Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops - MBEYA 0 70,000 140,000 210,000 Maize Beans Paddy Sorghum Groundnuts Cassava Finger Millet Irish Potatoes Simsim Sweet Potatoes Wheat Sunflower Tobacco Bulrush Millet Field Peas Tomatoes Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - MBEYA 0.00 0.20 0.40 0.60 0.80 1.00 1.20 Bulrush Millet Sorghum Tobacco Maize Paddy Simsim Irish Potatoes Pyrethrum Wheat Beans Sunflower Cassava Finger Millet Field Peas Sweet Potatoes Groundnuts Cowpeas Crop Planted Area (ha) RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 tubers 27,141 ha (5.9%), fruit and vegetables 3,982 ha (0.9%) and annual cash crops, mainly consisting of pyrethrum and tobacco have the least planted area of about 3,979 ha (0.9%) (Chart 3.17b). Cereals and pulses were the dominant crops in both seasons and other crop types were less important in comparison. NOTE: There is little difference in the proportions of the different crop types grown between seasons and because the short rainy season production was very small compared to the long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). However, the area planted and production of various crops are the combination of both short and long rainy seasons respectively 3.3.4 Cereal Crop Production The total production of cereals was 382,964 tonnes. Maize was the dominant cereal crop at 286,213 tonnes which was 74.7 percent of total cereal crop production, followed by paddy (16.4%) sorghum (5.5%), finger millet (1.8%), wheat (1.2%), bulrush millet (0.3%) and barley (0.02%). Mbozi district had the largest planted area of Cereals in the region (91,979ha) followed by Mbarali, 55,802 ha), Chunya (54,461 ha), Mbeya Rural 44,724 ha), Rungwe (32,678 ha) Kyela (27,933 ha), Ileje (17,709 ha), and Mbeya Urban (3,637 ha) (Table 3.2b and Map 3.10). The total area planted with cereals in both seasons was 328,941. The long rainy season accounted for 91 percent of the total area planted with cereals. (Table 3.2). Table 3.2 Area, Production and Yield of Cereal Crops by Season Crop Short Rainy Season Long Rainy Season Total Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Maize 29,417 41,305 1.40 202,326 244,907 1.21 231,743 286,213 1.24 Paddy 0 0 0.00 54,743 62,780 1.15 54,743 62,780 1.15 Sorghum 0 0 0.00 25,953 21,214 0.82 25,953 21,214 0.82 Bulrush Millet 0 0 0.00 2,162 1,183 0.55 2,162 1,183 0.55 Finger Millet 200 107 0.54 9,828 6,940 0.71 10,028 7,047 0.70 Wheat 0 0 0 4,289 4,436 1.03 4,289 4,436 1.03 Barley 23 91 3.952 0 0 0 23 91 3.95 Total 29,640 41,504 299,301 341,460 328,941 382,964 Table 3.2b Area, Production and Yield of Cereal Crops Long Rainy Season Short Rainy Season Total Planted Area (ha) Quantity (t) Yield (t/ha) Planted Area (ha) Quantity (t) Yield (t/ha) Planted Area (ha) Quantity (t) Yield (t/ha) Chunya 54,461 45,224 0.83 54,461 45,224 0.83 Mbeya Rural 36,995 43,247 1.17 7,730 7,730 1.00 44,724 50,977 1.14 Kyela 27,933 26,850 0.96 27,933 26,850 0.96 Rungwe 13,298 15,054 1.13 19,380 19,380 1.00 32,678 34,433 1.05 Ileje 15,196 16,745 1.10 2,513 2,513 1.00 17,709 19,258 1.09 Mbozi 91,979 134,965 1.47 91,979 134,965 1.47 Mbarali 55,802 52,371 0.94 55,802 52,371 0.94 Mbeya Urban 3,637 7,003 1.93 18 18 1.00 3,655 7,021 1.92 299,301 341,460 29,640 29,640 328,941 371,100 Chart 3.17b: Percentage Distribution of Area planted w ith Annual Crops by Crop Type Oil seeds & Oil nuts, 0.6% Roots & Tubers, 11.1% Fruits & Vegetables, 1.2% Cash crops, 0.1% Pulses, 18.0, % Cereals, 69.0% 29,640 58,882 6,161 29,127 1,013 22,916 4,225 3,906 73 528 528 0 40,000 80,000 120,000 Area (hectares) Cereals Root s & Tubers Fruit s & Veget ables P ulses Cash Crops Oil seeds & Oil Nut s Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Wet Season Dry Season RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 The area planted with maize was dominant and it represented 70.5 percent of the total area planted with to cereal crops, and was followed by paddy (16.6%), sorghum (7.9%), finger millet (3.0%), wheat (1.3%), bulrush millet (0.66%) and barley (0.01%). The yield of maize was 1,240 kg/ha, paddy (1,150 kg/ha), wheat (1,030 kg/ha) sorghum (820 kg/ha), finger millet (700 kg/ha), bulrush millet (550 kg/ha) and barley (395 kg/ha) (Chart 3.19). 3.4.1 Maize Maize dominated the production of cereals in the region. The number of households growing maize in Mbeya region during the long and short rainy season was 342,205 (91.8% of the total crop growing households in the region). The total production of maize was 286,213 tonnes from a planted area of 231,743 hectares resulting in a yield of (1.24 t/ha). (Chart 3.20) indicates maize production trend (in thousand metric tonnes) for the combined wet and dry seasons. There was a sharp increase in maize production (26.6%) over the period of 1998 to 1999 after which the production remained almost constant up to 2003. The average area planted with maize per maize growing household was 0.7 hectares; however it ranged from 0.4 hectares in both Rungwe and Kyela districts to 1 hectares in Chunya district (Map 3.12) Chart 3.21). Mbozi district had the largest area of maize (67,736 ha) followed by Chunya (40,508 ha), Mbeya Rural (37,429 ha), Mbarali (32,101 ha), Rungwe 28,982 ha), Ileje (14,551 ha), Kyela (7,036 ha) and Mbeya Urban (3,400 ha) (Chart 3.21 and Map 3.11). There has been little change in production over the since 1995 with the quantity of maize ranging from 218,000 to 316,000 tonnes (Charts 3.20). Charts 3.21 and 3.22 show that, whilst the area planted increased from 1998 the yield declined sharply and has remained at this low level. The area planted with maize remained almost constant over the period from 1994 and 1995 after which the area under production expanded gradually until 2000 and the area has remained constant ever since. Chart 3.20: Time Series Data on Maize Production - MBEYA 276 251 316 286 276 218 257 0 100 200 300 400 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 RAAS 1999/2000 NSCA 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 3,400 7,036 14,551 28,982 32,101 37,429 40,508 67,736 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Mbozi Chunya Mbeya Rural Mbarali Rungwe Ileje Kyela Mbeya Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 80,000 160,000 240,000 Maize Paddy Sorghum Finger Millet Wheat Bulrush Millet Barley Crop Area Planted (ha) 0.00 1.00 2.00 3.00 4.00 5.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.22 Time Series of Maize Planted Area & Yield - MBEYA 0 100,000 200,000 300,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Yield (t/ha) Area Yield RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 24 3.4.2 Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Mbeya region during the long rainy season was 80,091. This represented 23.3 percent of the total households growing annual crops in Mbeya region in the long rainy season. The total production of paddy was 62,780 tonnes from a planted area of 54,743 hectares resulting in a yield of 1.15 t/ha. The district with the largest area planted with Paddy was Mbarali (21,546 ha) followed by Kyela (20,811 ha), Mbozi (6,346 ha), Rungwe (3,364 ha), Chunya (1,853 ha), Ileje (731 ha), Mbeya Rural (72 ha) and Mbeya Urban (21 ha) (Map 3.13). There are small variations in the average area planted per crop growing household among the districts ranging from 0.20 ha in Mbeya Rural to 0.88 ha in Mbarali (Chart 3.23 and Map 3.14) The production of paddy in the region has been gradually declining since 1995 from 102,000 tonnes in 1994/95 to 63,000 tonnes in 1999/2000. Charts 3.24 and 3.25 show that whilst the planted area of paddy increased , the productivity has declined resulting in a drop in the production of paddy. 3.4.3 Other Cereals Other cereals produced in the region were sorghum; bulrush millet, finger millet; wheat and barley. Chunya district had the largest area planted with sorghum (11,313 ha), followed by Mbozi (10,943 ha), Mbarali (2042 ha) and Mbeya Rural (1,530 ha). Very small quantitities of sorghum were produced in Kyela , Ileje and Mbeya Urban. Rungwe district did not cultivate any sorghum. Bulrush millet was cultivated in Mbozi and Mbeya Urban districts. While finger millets were cultivated in all eight districts wheat cultivation was done in only three districts of Mbeya Rural, Ileje and Mbeya Urban. Barley was cultivated in Rungwe district only (Chart 3.26). Chart 3.23 Total Planted Area and Area of Paddy per Household by District 21 21,546 20,811 6,346 3,364 1,853 731 72 0 5,000 10,000 15,000 20,000 25,000 Mbarali Kyela Mbozi Rungwe Chunya Ileje Mbeya Rur Mbeya Urb District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - MBEYA 41 85 50 41 63 102 87 0 30 60 90 120 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 RAAS 1999/2000 NSCA 2002/03 Census/Survey year Production ('000') tons Chart 3.25 Time Series of Paddy Planted Area and Yield - MBEYA 0 10,000 20,000 30,000 40,000 50,000 60,000 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 RAAS 1999/2000 NSCA 2002/03 Agriculture Year Area (hectares) -2.0 2.0 6.0 10.0 Yield (t/ha) Area P lanted (Ha) Yiels (To n/Ha) 0 2,000 4,000 6,000 8,000 10,000 12,000 Area (H a) Chunya Mbo zi Mbarali Mbeya Rural Kyela Ileje Mbeya Urban Rungwe District Chart 3.26 Area Planted with Finger Millet,Sorghum, Wheat and Bulrush Millet Wheat by District Sorghum Bulrush Millet Finger Millet Wheat Barley Mbeya Urban Rungwe Mbeya Rural Ileje Kyela 3,400ha 28,982ha 67,736ha 37,429ha 14,551ha 7,036ha 32,101ha 40,508ha 2.1t/ha 1.4t/ha 1.5t/ha 1.4t/ha 3.8t/ha 2t/ha 1.6t/ha 1.1t/ha Mbozi Chunya Mbarali 60,000 to 75,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Mbeya Urban Mbeya Rural Ileje Kyela Mbozi 1.22ha 0.48ha 0.92ha 0.65ha 0.41ha 0.69ha 0.84ha 1.1ha Chunya Rungwe Mbarali 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Planted Area (ha) Planted Area and Yield of Maize by District MAP 3.11 MBEYA MAP 3.12 MBEYA Area Planted Per Maize Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Yield (t/ha) Area Planted Per Household Planted Area (ha) RESULTS 25 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 26 3.3.5 Root and Tuber Crop Production The total production of roots and tubers was 52,590 tonnes. Irish potatoe production was the highest with a total production of 23,454 tonnes representing 44.6 percent of the total root and tuber crop production. This was followed by cassava with 19,504 tonnes . (37.1%), sweet potatoes (6,603t, 12.6%), coco yams (2,509t, 4.5%) and yams (55t, 0.9%) (Table 3.3). Cassava had the largest planted area during 2002/03 agricultural year in Mbeya accounting for 50 percent of the area planted with roots and tubers, followed by Irish potatoes (28%), percent sweet potatoes (18%), cocoyams (3%) and yams (1%). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava was reported under the long rainy season. The yield for Irish potatoes (3.0 t/ha) and cocoyams (2.9 t/ha) yams (2.5 t/ha), cassava and sweet potatoes both at (1.4 t/ha). 3.5.1 Cassava The number of households growing cassava in the region was 41,254. This represents 11.1 percent of the total crop growing households in the region. The total production of cassava during the census year was 19,504 tonnes from a planted area of 13,498 hectares resulting in a yield yield of 1.4/ha. Previous censuses and surveys indicate that the area planted with cassava increased over the period 1994/1995 to 2002/03. The planted area with cassava increased sharply from 1,265 hectares in 1996 to 24,535 hectares in 1999 and after which it decreased to 13,498 ha in 2003 (Chart 3.28). In 2002/03 the area planted with cassava accounted for 3 percent of the total area planted with annual crops and vegetables in the region. Mbozi district had the largest planted area of Cassava (5,630 ha, 41.7% of the cassava planted area in the region), followed by Rungwe (2,804 ha, 20.8%), Ileje (2,218 ha, 16.4%), Kyela (1,416 ha, 10.5%) Chunya (729 ha, 5.4%), Mbeya Rural (359 ha, 2.7%), Mbarali (333 ha, 2.5%) and Mbeya Urban (9 ha, 0.1%) (Map 3.15). However, the district with the highest proportion of land planted with cassava was Ileje district (7.3%). This was followed by Rungwe (5.3%), Kyela (4.6%), Mbozi (4.1%), Chunya (1.0%), Mbarali and Mbeya Rural had (0.5%) each and Mbeya urban had (0.1%) (Chart 3.29). Table 3.3 Area, Production and Yield of Cereal Crops by Dry and Wet Seasons combined. Dry and Wet Seasons Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Cassava 13,498 19,504 1.4 Irish Potatoes 7,715 23,454 3.0 Sweet Potatoes 4,867 6,603 1.4 Cocoyam 852 2,509 2.9 Yams 209 520 2.5 Total 27,141 52,590 Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 4,500 9,000 13,500 Cassava Irish Potatoes Sweet Potatoes Cocoyam Yams Crop Area Planted (ha) -0.5 1.0 2.5 4.0 Yield (kg/ha) Yield (kg/ha) Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 The average cassava planted area per cassava growing household was 0.33 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Mbozi district with (2.36 ha). This was followed by Rungwe (0.57 ha), Ileje (0.36 ha), Mbarali (0.30 ha), Mbeya Urban (0.28 ha), Kyela (0.18 ha), Chunya (0.09 ha) and Mbeya Rural (0.03 ha) (Chart 3.30 and Map 3.16). 3.5.2 Irish Potatoes The number of households growing Irish potatoes in Mbeya region was 21,399. This was 5.7 percent of crop growing households in the region. The total production of Irish potatoes during the census year was 23,454 tonnes from a planted area of 7,715 hectares resulting in a yield of 3.0 t/ha. Mbeya Rural district had the largest planted area of Irish potatoes (4,225 ha, 54.8%), followed by Rungwe (2,014 ha, 26.1%), Mbozi 739 ha, 9.6%), Mbeya Urban (458 ha, 5.9%) and Ileje (279 ha, 3.6%). Irish potatoes were not grown in Chunya, Kyela and Mbarali districts (Chart 3.31).Other root and tuber crops were of minor important in terms of area planted compared to cassava , Irish potatoes and sweet potatoes. 3.3.6 Pulse Crops Production The total area planted with pulses was 65,043 hectares out of which 62,592 (96.2%) of the total area planted with pulses were planted with beans, followed by field peas (1,545 ha, 2.4%), bambaranuts (592 ha, 0.9%), cow peas (308 ha, 0.5%) and chick peas (5 ha, 0.01%). Mung beans and green gram were not cultivated in the region. Table 3.4: Area, Production and Yield of Pulses by (Short & Long Seasons) Combined Dry & Wet Seasons Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 62,592 30,029 473 62,592 30,029 473 Field Peas 1,545 449 329 1,545 449 329 Bambaranuts 593 342 578 593 342 578 Cowpeas 308 91 295 308 91 295 Chich Peas 5 1 200 5 1 200 Mung Beans 0 0 0 0 0 0 Green Gram 0 0 0 0 0 0 TOTAL 65,043 30,912 64,864 30,498 Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 41.7 20.8 16.4 10.5 5.4 2.7 2.5 0.1 0.0 15.0 30.0 45.0 Mbozi Rungwe Ileje Kyela Chunya Mbeya Rur Mbarali Mbeya Urb District Percent of Total Area Planted -1 2 5 8 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 2.36 0.57 0.36 0.30 0.28 0.18 0.09 0.00 1.00 2.00 Area per Household Mbozi Rungwe Ileje Mbarali Mbeya Urb Kyela Chunya Mbeya Rur District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.31 Irish Potatoes: Total Area Planted and Planted Area per Household by District 0 4,225 2,014 740 458 279 0 0 0 1,000 2,000 3,000 4,000 5,000 Mbeya Rural Rungwe Mbozi Mbeya Urban Ileje Chunya Kyela Mbarali District Area (H a) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Area Planted per H ousehold Area Planted (ha) Area per Household Mbeya Urban Mbeya Rural Rungwe Ileje Kyela Mbozi 9ha 2,804ha 359ha 1,416ha 2,218ha 333ha 5,630ha 729ha 0.4t/ha 0.8t/ha 3.2t/ha 1.2t/ha 3.1t/ha 1.2t/ha 0.4t/ha 0.4t/ha Chunya Mbarali 4,800 to 6,000 3,600 to 4,800 2,400 to 3,600 1,200 to 2,400 0 to 1,200 Mbeya Urban Ileje Mbeya Rural Mbozi 0.3ha 0.4ha 0.4ha 0.3ha 0.4ha 0.3ha 0.3ha 0.3 Chunya Kyela Rungwe Mbarali 0.38 to 0.4 0.36 to 0.38 0.34 to 0.36 0.32 to 0.34 0 to 0.32 Planted Area (ha) Planted Area and Yield of Cassava by District MAP 3.13 MBEYA MAP 3.14 MBEYA Area Planted Per Cassava Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Yield (t/ha) Area Planted Per Household Planted Area (ha) ha RESULTS 28 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 29 The total production of pulses was 30,912 tonnes. The production of beans was 30,029 tonnes. Field peas had a production of 449 tonnes and other pulse crops were produced in minor quantities (Chart 3,32). 3.6.1 Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Mbeya region was 198,422. The total production of beans in the region was 29,615 tonnes from a planted area of 63,454 hectares resulting in a yield of 0.5 t/ha. The largest area planted with beans in the region was in Mbozi (27,786 ha, 44.4%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per household was in Chunya district (0.43 ha) (Chart 3.34). The average area planted per bean growing household in the region during the long rainy season was 0.33 ha. The variations in area planted with beans for the rest of the districts were small ranging from 0.19 ha in Mbeya Urban district to 0.39 ha in Mbozi district (Map 3.18 and Chart 3.35). In Mbeya region, bean production has increased sharply from 5,805 tonnes in 1995 to 115,697 tonnes in 1997 after which it decreased sharply to 10,155 tonnes in 1998 from 1999/2000 it started increasing gradually to 29,615 tonnes in 2002/03 (Chart 3.35). Charts 3.35 and 3.36 show that, the increase in production from 1995/96 was due to the a sharp increase in planted area has been due to an increase in the planted area and not due to an increase in productivity. (Chart 3.36). Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 20,000 40,000 60,000 Beans Field Peas Bambaranuts Cowpeas Chich Peas Mung Beans Green Gram Crop Area Planted (ha) 0 200 400 600 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 Mbozi Mbeya Rural Rungwe Ileje Chunya Mbeya Urban Mbarali Kyela District Percent of Land 0 2 4 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.43 0.39 0.35 0.25 0.24 0.24 0.23 0.19 0.00 0.20 0.40 Area per Household Chunya Mbozi Mbeya Rur Mbarali Rungwe Kyela Ileje Mbeya Urb District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.36 Time Series of Beans Planted Area & Yield - MBEYA 0 20000 40000 60000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.2 0.4 0.6 Yield (t/ha) Area Planted Yield Chart 3.35: Time Series Data on Beans Production - MBEYA 24 78 116 10 30 13 6 0 40 80 120 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Ye a r Production ('000') tons Mbeya Rural Rungwe Mbeya Urban Mbozi Ileje Kyela 0.35ha 0.19ha 0.39ha 0.23ha 0.24ha 0.24ha 0.25ha 0.43ha Chunya Mbarali 0.36 to 0.45 0.27 to 0.36 0.18 to 0.27 0.09 to 0.18 0 to 0.09 Mbozi Chunya Mbeya Rural Mbarali Mbeya Urban Rungwe Ileje Kyela 27,786ha 3,791ha 787ha 12,167ha 862ha 11,246ha 5,535ha 418ha 0.48t/ha 0.39t/ha 0.88t/ha 0.48t/ha 0.46t/ha 0.45t/ha 0.39t/ha 0.61t/ha 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Planted Area (ha) Planted Area and Yield of Beans by District MAP 3.15 MBEYA MAP 3.16 MBEYA Area Planted Per Beans Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Yield (t/ha) Area Planted Per Household Planted Area (ha) RESULTS 30 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 3.3.7 Oil Seed Production The total production of oilseed crops was 14,620 tonnes planted on an area of 30,141 hectares. Groundnuts were the most important oilseed crop with a planted area of 21,054 ha (69.9% of the total area planted with oil seeds), followed by simsim (17.2%), sunflower (12.7%) and soya beans (0.3%) (Chart 3.37). The yield of groundnuts was moderate at (509 kg/ha). Sunflower had a yield of 475 kg/ha, soya beans of 443kg /ha and simsim 395 kg/ha. 3.3.7.1 Groundnuts The number of households growing groundnuts in Mbeya region was 82,646. The total production of groundnuts in the region was 10,724 tonnes from a planted area of 21,054 hectares resulting in a yield of 0.5 t/ha. The planted area increased from 1,829 hectares in 1995/96 to 21,054 hectares in 2002/03 (Chart 3.38). Mbozi district had the largest planted area of groundnuts at (8,117 ha, 38.6%) of the area planted with oil seeds), followed by Chunya (4,527 ha, 21.5%), Mbarali (2,742 ha, 13.0%), Mbeya Rural (1,799 ha, 8.5%), Rungwe (1,689 ha, 8.0%), Ileje (1,615 ha, 7.7%) Kyela (562 ha, 2.7%) and Mbeya Urban (2 ha, 0.01%) (Map 3.19). The highest proportion of land with groundnuts was in Chunya, followed by Mbozi, Ileje, Mbarali, Rungwe, Mbeya Rural, Kyela and Mbeya Urban (Chart 3.39 and Map 3.20). Table 3.5: Area, Production and Yield of Oil Seeds & Oil Nuts During 2002/03 Agricultural Year (Dry & Wet Seasons Combined) Crop Short & Long Rainy Seasons Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Groundnuts 21,054 10,724 509 Simsim 5,194 2,051 395 Sunflower 3,814 1,810 475 Soya Beans 79 35 438 Total 30,141 14,620 Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 15.0 30.0 45.0 Mbozi Chunya Mbarali Mbeya Rur Rungwe Ileje Kyela Mbeya Urb District Percent of Land -0.01 0.02 0.05 0.08 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 7,000 14,000 21,000 Groundnuts Simsim Sunflower Soya Beans Crop Area Planted (ha) 0 0 0 1 Yield (kg/ha) Yield (kg/ha) 2,443 1,829 18,565 21,054 0 5,000 10,000 15,000 20,000 25,000 Area lanted (Ha) 1994/95 1995/96 1998/99 2002/03 Years Chart 3.38 Time Series Data of Groundnuts Planted Area (Ha) RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 The largest area planted per groundnut growing household was found in Chunya District (0.40ha) and the lowest was in Rungwe district (0.12 ha). The range between the district with the highest and lowest area planted per household depicts small variations between the districts (Chart 3.40). 3.3.8 Fruits and Vegetables The collection of fruit and vegetable production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. The most cultivated fruit and vegetable crop was tomatoes with a production of 6,312 tonnes (46.4% of the total fruit and vegetables produced). The production of onions was 3,787 tonnes (27.8%) and cabbage 1,731 tonnes (12.7%). The production of other fruit and vegetable crops was relatively small (Table 3.6). The yield of bitter aurbergine was (10,333 kg/ha), chillies (76,250 kg/ha), onions 5,449 kg/ha, cabbage (5,443 kg/ha), tomatoes (5,182 kg/ha), cucumber (5,000 kg/ha), carrot (4,700 kg/ha), pumpkins (1,811 kg/ha), spinach (1,650 kg/ha), and Amaranths (1,043 kg/ha). Radish and eggplant had yields of 400 and 125 kg/ha respectively (Chart 3.42). 3.8.1 Tomatoes The number of households growing tomatoes in the region during the wet season was 5,167 and 985 households in the dry season. This represented 1.5 percent of the total households growing annual crops in the region during the wet season and 1.6 percent of the households growing annual crops during the dry season. Mbeya Rural district had the largest planted area of tomatoes (36.5% of the total area planted with tomatoes in the region), followed by Mbarali (19.5%), Mbozi (18.0%), Rungwe (11.1%), Mbeya Urban (9.0%), Kyela (3.5%) and Ileje (2.4%). Chunya district did not grow any tomatoes (Map 3.21). The highest proportion of land area with tomatoes was found in Mbeya Urban followed by Mbeya Rural district. With exception Mbeya Urban, Mbeya Rural, Mbarali, and Rungwe districts, the rest of the districts had relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Mbeya Rural district (0.34 ha) followed by Mbarali (0.22 ha), Mbeya Urban (0.21 ha), Rungwe (0.15 ha), Mbozi (0.13 ha, Ileje (0.11 ha) and Kyela (0.10 ha) (Chart 3.44 and Map 3.22). Table 3.6: Area, Production and Yield of Fruits and Vegetables During 2002/03 Agricultural Year (Dry & Wet Seasons Combined) Short & Long Rainy Seasons Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tomatoes 1,218 6,312 5182 Radish 795 318 400 Onions 695 3,787 5449 Cabbage 318 1,731 5443 Pumpkins 365 661 1811 Amaranths 420 438 1043 Spinnach 137 226 1650 Egg Plant 16 2 125 Carrot 10 47 4700 Bitter Aubergine 6 62 10,333 Chillies 4 25 6,250 Cucumber 0.2 1 5,000 Total 3,982 13,610 0.00 0.20 0.40 Area per Household (ha) Chunya Mbarali Mbeya Rur Mbozi Kyela Mbeya Urb Ileje Rungwe District Chart 3.40 Area Planted per Groundnut Growing Households by District (Long Rainy Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 500 1,000 Tomatoes Radish Onions Cabbage PumpkinsAmaranths Spinnach Crop Area Planted (ha) 0.0 1,000.0 2,000.0 3,000.0 4,000.0 5,000.0 Yield (kg/ha) Chunya Mbozi Mbeya Urban Mbeya Rural Rungwe Kyela Ileje 0.4 0.24ha 0.18ha 0.24ha 0.36ha 0.18ha 0.22ha 0.37ha Mbarali 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 2ha 1,799ha 1,689ha 1,615ha 562ha 8,117ha 4,527ha 2,742ha 1.1t/ha 0.37t/ha 0.56t/ha 0.48t/ha 0.79t/ha 0.58t/ha 0.51t/ha 0.33t/ha Mbozi Chunya Mbarali 7,400 to 8,600 6,300 to 7,400 4,200 to 6,300 2,100 to 4,200 0 to 2,100 Planted Area (ha) Planted Area and Yield of Groundnuts by District MAP 3.17 MBEYA MAP 3.18 MBEYA Area Planted Per Groundnuts Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t/ha) ha RESULTS 33 Mbozi Mbeya Urban Mbeya Rural Ileje 0.11ha 0ha 0.22ha 0.14ha 0.21ha 0.13ha 0ha 0.34ha Chunya Kyela Rungwe Mbarali 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Mbeya Urban Rungwe Ileje Mbeya Rural Kyela Mbozi Chunya 0ha 109ha 237ha 219ha 44ha 29ha 0ha 445ha 0t/ha 1.7t/ha 7.5t/ha 5.5t/ha 5.1t/ha 1.8t/ha 0t/ha 7t/ha Mbarali Planted Area (ha) Planted Area and Yield of Tomatoes by District MAP 3.19 MBEYA MAP 3.20 MBEYA Area Planted Per Tomatoes Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Yield (t\ha) RESULTS 34 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 3.3.8.2 Radish The number of households growing radish in the region during the wet season was 98 households. This represented 0.0003 percent of the total households growing annual crops in the region in the wet season. Chunya was the only district in the region which grew radish. 3.3.8.3 Onions The number of households growing onions in the region during the long rainy season was 3,288 households and 116 in the short rainy season. This represented 0.96 annual crops in the region in the wet season and 0.19 percent of the corresponding households in the dry season. Mbeya Rural district had the largest planted area of onions (2,536 ha, 75% of the total area planted with onions in the region), followed by Ileje (580 ha, 17%), Mbozi (172 ha, 5%), Mbarali (106 ha, 2.5%) and Mbeya Urban (9 ha, 0.3%). However, Chunya, Rungwe, Kyela and Mbeya Urban districts did not grow any onions. The largest proportion of the area planted with onions was found in Mbeya Rural district (0.038%), followed by Ileje (0.019%), Mbarali and mbeya Urban had (0.002%) each and Mbozi district had (0.001%) (Chart 3.46). The total area planted with onions accounted for 0.74 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Chart 3.45 Percent of Radish Planted Area and Percent of Total Land with Cabbage by District 0.0 30.0 60.0 90.0 Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb District Percent of Land 0.00 0.04 0.08 0.12 0.16 0.20 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Onions Planted Area and Percent of Total Land with Cabbage by District 0 20 40 60 80 Mbeya Rur Ileje Mbozi Mbarali Mbeya Urb Chunya Kyela Rungwe District Percent of Land 0.000 0.020 0.040 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha).. Mbeya Rur Mbarali Mbeya Urb Rungwe Mbozi Ileje Chunya Kyela District Chart 3.44 Area Planted per Tomato Growing Household by District (Wet Season Only) Chart 3.43 Percent of Tomatoes Planted Area and Percent of Total Land with Groundnuts by District 0.0 12.0 24.0 36.0 Mbeya Rur Mbarali Mbozi Mbeya Urb Rungwe Ileje Chunya Kyela District Percent of Land 0.00 1.50 3.00 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 36 3.3.9 Other Annual Crop Production The other annual crops were cash crops. An area of 3,978 ha was planted with other annual crops and tobbaco was the most prominent followed by pyrethrum. The area planted with annual cash crops in the short rainy season was 73 ha which represents 1.8 percent of the total area planted with other annual cash crops in short and long rainy season. 3.9.1 Tobacco The quantity of tobacco produced was 3,606 tonnes. Tobacco had a planted area of 3,733 ha, all of which was planted in the wet season. Tobacco production was concentrated in Chunya having 99.5 percent of the total area planted with tobacco in the region, followed by Ileje (0.4%) and Rungwe (0.2%) (Chart 3.48) (Map 3.29 and 3.30). 3.3.9.2 Pyrethrum Only 245 tonnes of pyrethrum was produced in Mbeya Region on a planted area of 245 ha. Pyrethrum was produced during both the wet and dry seasons. The crop was grown in Mbeya Rural district only (Map 3.27) and 0.25 ha was the average area planted per pyrethrum growing households. (Map 3.28). 3.4 Permanent Crops Permanent crops (perennial crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented Table 3.7: Area, Production and Yield of Annual Cash Crops During 2002/03 Agricultural Year by (Dry & Wet seasons Combined) Dry & Wet Seasons Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tobacco 3,733 3,606 966 3,733 3,606 966 Pyrethrum 245 245 1,000 245 245 1,000 Total 3,978 3,851 3,906 3,762 Chart 3.47 Area planted with Annual Cash Crops Pyrethrum, 172, 4% Tobacco, 3,733, 96% Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Chunya Ileje Rungwe Mbeya Rur Kyela Mbozi Mbarali Mbeya Urb District Percent of Land 0.0000 0.0500 0.1000 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land Chart 3.49 Area Planted for Annual and Permanent Crops Annual Crops, 459,226, 75% P ermanent Cro ps, 153,578, 25% Mbeya Urban Ileje Mbeya Rural Mbozi 0ha 0ha 0ha 0ha 0ha 0ha 8.1ha Chunya Kyela Rungwe Mbarali 0ha 6.4 > 4.8 to 6.4 3.2 to 4.8 1.6 to 3.2 0 to 1.6 Ileje Rungwe Mbeya Urban Mbeya Rural Mbozi Kyela 0ha 0ha 0ha 0ha 0ha 0ha 0ha 795ha 0t/ha 0 0t/ha 0t/ha 0t/ha 0 0t/ha 0.4t/ha Chunya Mbarali Planted Area (ha) Planted Area and Yield of Radish by District MAP 3.21 MBEYA MAP 3.22 MBEYA Area Planted Per Radish Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) 640 to 800 480 to 640 320 to 480 160 to 320 0 to 160 Yield (t\ha) RESULTS 37 Mbeya Urban Mbeya Rural Mbozi Ileje 0.2ha 0.2ha 0.2ha 0ha 0.2ha 0ha 0.1ha 0.1ha Chunya Kyela Rungwe Mbarali 1.2 to 1.25 0.15 to 1.2 0.1 to 0.15 0.05 to 0.1 0 to 0.05 Mbeya Rural Rungwe Kyela Mbeya Urban Ileje Chunya 2,420ha 0ha 9ha 580ha 0ha 172ha 106ha 116ha 6.5t/ha 0t/ha 3.2t/ha 3.6t/ha 1.5t/ha 0t/ha 0.2t/ha 9.4t/ha Mbozi Mbarali 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Planted Area (ha) Planted Area and Yield of Onions by District MAP 3.23 MBEYA MAP 3.24 MBEYA Area Planted Per Onions Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t\ha) RESULTS 38 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 153,578 hectares (25% of the total area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst, the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops would be higher than indicated in (Chart 3.49). The most important permanent crop in Mbeya region was coffee which had for a planted area of 59,460 ha, (39% of the planted area of all permanent crops) followed by banana (52,715 ha, 35%), cocoa (15,462 ha, 10%), mango (8,359 ha, 5%), tea (4,608 ha, 3%), avocado (3,662 ha, 2%) and palm oil (3,414 ha, 2%). The remaining permanent crops accounted for only 4 percent of the total area planted with permanent crops (Chart 3.50). Rungwe district had the largest area under smallholder permanent crops (85,058 ha, 55.4%). This was followed by Mbozi (34,603 ha, 22.5%), Kyela (14,296 ha, 9.3%), Mbarali (6,620 ha, 4.3%), Ileje (6,412 ha, 4.2%), Mbeya Rural (5,681 ha, 3.7%), Mbeya Urban (830 ha, 0.5%) and Chunya (80 ha, 0.1%). However, Mbarali district had the largest area per permanent crop growing household (2.40 ha) followed by Rungwe (0.74 ha), Mbozi (0.52 ha), Chunya (0.41 ha), Mbeya Rural and Mbeya Urban had (0.38 ha) each, Kyela (0.28ha) and Ileje (0.25ha) (Chart 3.51). 3.4.1 Coffee The total production of coffee by smallholders was 98,841 tonnes. In terms of area planted, coffee was the most important permanent crop grown by smallholders in the region. It was grown by 90,477 households (24.3% of the total crop growing households). The average area planted with coffee per coffee growing household was relatively small (0.66ha) and the average yield obtained by smallholders was 2,530 kg/ha from a harvest area of 39,061 ha. Chart 3.51 Percent of Area Planted with Coffee and Average Planted Area per Household by District 0.0 0.0 55.8 0.5 34.8 8.9 0.0 0.0 0.0 15.0 30.0 45.0 60.0 Mbozi Rungwe Mbeya Rural Mbeya Urban Chunya Ileje Mbarali Kyela District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household C hart 3.50 A rea P lanted with the M ain P erennial C ro ps others, 1467, 1% Avocado, 3,662, 2% Orange, 2,101, 1% Cardamon, 914, 1% Sugarcane, 839, 1% Cashewnut, 577, 0% Palm Oil, 3,414, 2% Tea, 4,608, 3% M ango, 8,359, 5% Cocoa, 15,462, 10% Banana, 52,715, 34% Coffee, 59,460, 40% Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 22.5 9.3 4.3 4.2 0.5 0.1 3.7 55.4 0.0 20.0 40.0 60.0 Rungwe Mbozi Kyela Mbarali Ileje Mbeya Rural Mbeya Urban Chunya District % of Total Area Planted 0.00 1.50 3.00 Average Planted Area per Household % of Total Area Planted Average Planted Area Per Household Ileje Mbozi Mbeya Urban Mbarali Chunya Mbeya Rural 0.19ha 0.14ha 8.96ha 0ha 0.82ha 0.11ha 0.58ha 0.19ha Kyela Rungwe 7.2 to 9 5.4 to 7.2 3.6 to 5.4 1.8 to 3.6 0 to 1.8 Mbeya Urban Rungwe Mbeya Rural Ileje Kyela 255ha 43,366ha 2,408ha 493ha 1,259ha 3,007ha 0ha 1,926ha 3t/ha 3.9t/ha 6.6t/ha 4.2t/ha 5.6t/ha 5.7t/ha 0t/ha 0t/ha Mbozi Chunya Mbarali 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area (ha) Planted Area and Yield of Banana by District MAP 3.25 MBEYA MAP 3.26 MBEYA Area Planted Per Banana Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t/ha) RESULTS 40 Mbeya Urban Mbeya Rural Ileje 0 0 0 1 0 0 0 0 Mbozi Chunya Kyela Rungwe Mbarali 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Kyela Mbeya Urban Mbeya Rural Rungwe Ileje 7,685 0 7,643 0 134 0 0 0 0 1 1 0 0 3 0 0 Mbozi Chunya Mbarali 6,160 to 7,690 4,620 to 6,160 3,080 to 4,620 1,540 to 3,080 0 to 1,540 Planted Area (ha) Planted Area and Yield of Cocoa by District MAP 3.27 MBEYA MAP 3.28 MBEYA Area Planted Per Cocoa Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t/ha) RESULTS 41 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 42 Mbozi district had the largest area of coffee in the region (31,692 ha, 53.3%) followed by Rungwe (19,761 ha, 33.2%), Mbeya Rural (5,071 ha, 8.5%) and Mbeya Urban (265 ha, 0.4%). However, there was no coffee production in Chunya, Ileje, Mbarali and Kyela districts. (Map 3.31). Moreover, the average area planted with coffee per coffee growing household was highest in Rungwe (0.80 ha) followed by Mbozi (0.66 ha), Mbeya Urban (0.61 ha) and Mbeya Rural (0.47 ha) (Chart 3.52 and Map 3.32). 3.4.2 Banana The total production of bananas by smallholders was 225,241 tonnes. In terms of area planted, banana was the second most important permanent crop grown by smallholders in the region. It was grown by 94,050 households (25.3% of the total crop growing households). The average area planted with banana per banana growing household was 0.6 ha per banana growing and the average yield obtained by smallholders was 8,766 kg/ha from a harvested area of 25,696 hectares. Rungwe had the largest planted area of bananas in the region (43,366 ha, 82.3%) followed by Kyela (3,007 ha, 5.7%), Ileje (2,408 ha, 4.6%), Mbarali (1,926 ha, 3.7%), Mbozi (1,259 ha, 2.4%), Mbeya Rural (493 ha, 0.9%) and Mbeya Urban (255 ha, 0.5%). Chunya district did not grow banana. The area planted with banana per banana growing household was highest in Mbarali (8.9 ha), followed by Rungwe (0.82 ha), Mbeya Urban (0.30 ha), Mbeya Rural (0.20 ha), Kyela and Ileje districts had (0.19 ha) each and Mbozi (0.14 ha) (Chart 3.49 and Map 3.36). 3.4.3 Cocoa The total production of cocoa by smallholders was 5,418 tonnes. In terms of area planted, cocoa was the third most important permanent crop grown by smallholders in the region. It was grown by 28,615 households (7.7% of the total crop growing households). The average area planted with cocoa per household was relatively small at around 0.54 hectares per cocoa growing household and the average yield obtained by smallholders was 611 kg/ha from a harvest ed area of 8,871 hectares. Kyela had the largest area of cocoa in the region (7,685 ha, 49.7%) followed by Rungwe (7,643 ha, 49.4%) and Ileje (134 ha, 0.9%). Chunya, Mbeya Rural, Mbozi, Mbarali and Mbeya Urban did not grow any cocoa (Map 3.33). However, the average area planted with cocoa per cocoa planting household was highest in Rungwe district with (0.73 ha) followed by Kyela (0.44 ha) and Ileje (0.24 ha) (Chart 3.53 and Map 3.34). Chart 3.52 Percent of Area Planted with Banana and Average Planted Area per Household by District 0.00 0.48 0.94 5.70 3.65 82.27 2.39 4.57 0.00 40.00 80.00 Rungwe Kyela Ileje Mbarali Mbozi Mbeya Rural Mbeya Urban Chunya District % of Total Area Planted -0.20 0.20 0.60 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Cocoa and Average Planted Area per Household by District 0.00 0.00 0.00 49.43 0.00 49.70 0.00 0.86 0.00 20.00 40.00 60.00 Kyela Rungwe Ileje Chunya Mbeya Rural Mbozi Mbarali Mbeya Urban District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per H ousehold % of Total Area Planted Average Planted Area per Household Mbeya Urban Mbeya Rural Rungwe Mbozi Ileje Kyela 0.96ha 0ha 0.06ha 0ha 0.1ha 0ha 0ha 0ha Chunya Mbarali 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 0ha 0ha 13ha 7ha 0ha 0ha 0ha 3,713ha 0t/ha 0t/ha 0.52t/ha 0.66t/ha 0t/ha 0t/ha 0t/ha 0.97t/ha Mbozi Chunya Mbarali 1.2 to 1.25 0.15 to 1.2 0.1 to 0.15 0.05 to 0.1 0 to 0.05 Planted Area (ha) Planted Area and Yield of Tobacco by District MAP 3.29 MBEYA MAP 3.30 MBEYA Area Planted Per Tobacco Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t\ha) RESULTS 43 Mbeya Urban Mbeya Rural Ileje 0ha 0.28ha 0ha 0ha 0ha 0ha 0ha Mbozi Chunya Kyela Rungwe Mbarali 0ha 0.24 to 0.29 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 0ha 172ha 0ha 0ha 0ha 0ha 0ha 0ha 0t/ha 0.91t/ha 0t/ha 0t/ha 0t/ha 0t/ha 0t/ha 0t/ha Mbozi Chunya Mbarali 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Planted Area (ha) Planted Area and Yield of Pyrethrum by District MAP 3.31 MBEYA MAP 3.32 MBEYA Area Planted Per Pyrethrum Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t/ha) RESULTS 44 Mbeya Urban Mbeya Rural Ileje 0.6ha 0.7ha 0.5ha 0.8ha 0ha 0ha 0ha 0ha Mbozi Chunya Kyela Rungwe Mbarali 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Mbeya Urban Mbeya Rural Ileje 265ha 5,071ha 19,761ha 0ha 0ha 31,692ha 0ha 0ha 1t/ha 1t/ha 0t/ha 0t/ha 0t/ha 3t/ha 0t/ha 0t/ha Mbozi Chunya Kyela Rungwe Mbarali 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Planted Area (ha) Planted Area and Yield of Coffee by District MAP 3.33 MBEYA MAP 3.34 MBEYA Area Planted Per Coffee Growing Household by District Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t\ha) RESULTS 45 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 3.4.4 Mangoes The total production of mangoes by smallholders was 12,251 tonnes. In terms of area planted, mangoes were the fourth most important permanent crop grown by smallholders in the region. It was grown by 16,272 households (4.4% of the total crop growing households). The average area planted with mangoes per household was relatively small at around 0.51 ha per mango growing household and the average yield obtained by smallholders was 6,821 kg/ha from a harvest area of 1,796 hectares. Mbarali has the largest area of mangoes in the region (4,522 ha, 54.1%) followed by Rungwe (2,466 ha, 29.5%), Kyela (485 ha, 5.8%), Mbozi (477 ha, 5.7%),Ileje (245 ha, 2.9%), Chunya (80 ha, 0.9%), Mbeya Urban (42 ha, 0.5%) and Mbeya Rural (42 ha, 0.5%) (Map 3.37). However, the average area planted per mango growing household was highest in Mbarali (2.25 ha), followed by Chunya (0.52ha), Kyela (0.41 ha), Mbeya Urban (0.34 ha), Mbeya Rural (0.19 ha), Ileje (0.15 ha), Rungwe (0.12 ha) and Mbozi (0.11ha) (Map 3.38). 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies expansion into virgin areas or into areas, which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing was the most widespread method used for land clearing. The area cleared by hand slashing in the region during the wet season was 349,287 hectares which represented 84.9 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 5.2, 1.0 and 0.3 percent respectively. However, 2.5 percent of agricultural households did not clear their land (Chart 3.54 and Table 3.8 ). Table 3.8: Land Clearing Methods Wet Season Dry Season Total Method of Land Clearing Number of Household s Area Planted % Number of Household s Area Planted % Number of Households Area Planted % Mostly Hand Slashing 679,789 349,287 84.9 37,337 103,458 92.0 717,125 452,744 86.5 No Land Clearing 22,588 10,129 2.5 3,777 7,097 6.3 26,365 17,226 3.3 Mostly Bush Clearance 37,774 21,446 5.2 273 1,166 1.0 38,047 22,612 4.3 Mostly Burning 49,003 28,877 7.0 49 243 0.2 49,052 29,120 5.6 Mostly Tractor Slashing 2,953 1,325 0.3 108 399 0.4 3,060 1,724 0.3 Other 49 121 0.0 49 121 0.1 98 243 0.0 Total 792,156 411,185 100.0 41,592 112,484 100.0 833,749 523,669 100.0 Chart 3.54 Number of Households by Method of Land Clearing during the Wet Season 103,458 243 1,166 7,097 399 121 Mostly Hand Slashing Mostly Burning Mostly Bush Clearance No Land Clearing Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.54 Percent of Area Planted with Mangoes and Average Planted Area per Household by District 1 1 1 30 6 54 3 6 0.00 20.00 40.00 60.00 Mbarali Rungwe Kyela Mbozi Ileje Chunya Mbeya Urban Mbeya Rural District % of Total Area Planted -0.50 0.50 1.50 2.50 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Mbeya Urban Mbeya Rural Mbozi Ileje 0.34ha 0.11ha 0.19ha 0.12ha 0.15ha 0.41ha 2.25ha 0.52 Chunya Kyela Rungwe Mbarali 2 to 2.5 1.5 to 2 1 to 1.5 0.5 to 1 0 to 0.5 Mbeya Rural Rungwe Mbeya Urban Ileje Kyela 42ha 42ha 477ha 2,466ha 485ha 245ha 4,522ha 80ha 26.3t/ha 1.8t/ha 7.1t/ha 0.8t/ha 3.6t/ha 6.4t/ha 0.3t/ha 11.6t/ha Mbozi Chunya Mbarali 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Planted Area (ha) Planted Area and Yield of Mangoes by District MAP 3.35 MBEYA MAP 3.36 MBEYA Area Planted Per Mangoes Growing Household by Districts Tanzania Agriculture Sample Census Area Planted Per Household Area Planted Per Household Planted Area (ha) Yield (t/ha) ha RESULTS 47 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 3.5.2 Methods of Soil Preparation Hand cultivation is mostly used for soil preparation with an area of 245,266 hectares (60 percent of the total planted area) followed by ox-ploughing (157,885 ha, 38%) and tractor ploughing (9,278 ha, 2%) (Chart 3.55 In Mbeya region, Mbarali district has the largest planted area cultivated with oxen (5,131 hectares, 8.2%) followed by Kyela (1,472 ha, 4.8%) Chunya (923 ha, 1.3%) and Mbozi (1,432 ha, 1%). While, Rungwe, Ileje and Mbeya Urban had the same percentage of (0.3 %). Mbeya Rural had a very low percentage (0.02%) of area cultivated by ox-plough. (Chart 3.56). 3.5.3 Improved Seed Use The planted area with improved seeds was estimated at 60,124 ha which represented 13 percent of the total area planted with annual crops and vegetables. The percentage use of improved seed in the wet season was 12.4 percent, which was lower than the corresponding percentage use for the dry season (19.9%). Cereals had the largest area planted with improved seeds (45,591 ha, 75.8% of the planted area with improved seeds). This was followed by pulses (4,403 ha, 7.3%), roots and tubers (4,187 ha, 7.0%), cash crops (2,686 ha, 4.5%), fruit and vegetable was more than in other crop types being 76% and 7% respectively. Only 2.5 percent of the planted area for oil seed crops used improved seeds (Chart 3.59). Chart 3.57 Planted Area of Improved Seeds - MBEYA Without Improved Seeds, 399,102, 87% With Improved Seeds, 60,124, 13% Chart 3.58 Planted Area with Improved Seed by Crop Type Cereals, 45,591, 76% Pulses, 4,403, 7% Roots & Tubers, 4,187, 7% Oil Seeds & Oil Nuts, 1,523, 3% Fruits & Vegetables, 1,735, 3% Cash Crops, 2,686, 4% 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.59 Percentage of Crop Type Planted Area with Improved Seed - Annuals 0 1,000 2,000 3,000 4,000 5,000 6,000 Area Cultivated Mbarali Kyela Mbozi Chunya Rungwe Ileje Mbeya Urban Mbeya Rural District Chart 3.56 Area Cultivated by Method of Cultivation and District Mos tly Oxen P loughing Mo s tly Hand ho e plo ughing Mos tly Tracto r P loughing NO P reparation Chart 3.55 Area Cultivated by Cultivation Method Mostly Hand Hoe Ploughing, 245,266, 54% Mostly Oxen Ploughing, 157,885, 34% Mostly Tractor Ploughing, 9,278, 2% No Preparation, 46,797, 10% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 3.5.4 Fertilizer Use The use of fertilisers on annual crops was relatively small with its application on a planted area of only 162,977 ha (35 % of the total area planted with annual crops in the region). The planted area without fertiliser for annual crops was 296,249 hectares representing 65 percent of the total area planted with annual crops. Inorganic fertiliser was applied to only 83,890 hectares which represented 18.3 percent of the total planted area (51.5% of the area planted with fertiliser application in the region). This was followed by farm yard manure (55,610 ha, 12%) and compost was used on a very small area of 23,477 hectares (5%). The highest percentage of the area planted with fertilizer (all types) was in Mbozi district (36.3%) followed by Mbeya Rural (19.5%), Rungwe (13.8%), Ileje (10.0%), Chunya (9.8%), Mbarali (5.1%), Kyela (3.2%) and Mbeya Urban (2.4%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households did not use any fertiliser (approximately 190,356 households, 51.2%) of total crop growing households (Map 3.39). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (78% of the area planted with fruits and vegetables during the wet season was applied with fertilizers. This was followed by roots and tubers (17%), pulses (13%), cereals (12%) and oil seeds (6%). There was no fertiliser application in cash crops (Chart 3.61). Table3.9 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Seasons (Combined) Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Chunya 4,555 1,744 9,736 16,034 55,754 Mbeya Rur 8,644 4,961 18,365 31,970 35,286 Kyela 1,073 2,559 1,561 5,193 25,599 Rungwe 14,610 2,705 5,211 22,526 29,939 Ileje 7,669 2,958 5,669 16,296 15,371 Mbozi 13,605 8,297 37,408 59,309 79,561 Mbarali 4,784 345 3,248 8,378 53,921 Mbeya Urb 994 185 2,703 3,882 1,310 Total 55,933 23,754 83,900 163,587 296,742 Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District – Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Plante d Area Number of Households Planted Area Number of Households Planted Area Chunya 3,198 4,555 1,139 1,744 6,425 9,736 31,837 55,754 38,262 71,788 Mbeya Rur 13,327 7,475 5,433 4,410 22,493 15,819 31,372 29,098 53,865 56,801 Kyela 1,947 1,073 5,284 2,559 1,278 1,561 32,914 25,599 34,192 30,792 Rungwe 36,185 5,211 16,726 1,740 16,624 1,087 50,700 17,393 67,323 25,431 Ileje 13,811 5,632 8,745 2,612 10,803 5,041 15,016 13,165 25,819 26,451 Mbozi 32,105 13,605 18,434 8,297 54,690 37,408 48,796 79,561 103,486 138,870 Mbarali 4,369 4,784 201 345 3,206 3,248 39,512 53,921 42,718 62,299 Mbeya Urb 2,637 992 361 176 4,834 2,694 2,346 1,291 7,180 5,153 Total 107,580 43,326 56,324 21,882 120,352 76,594 252,492 275,783 372,844 417,585 Chart 3.60 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 296,249, 65% Mostly Farm Yard Manure, 55,610, 12% Mostly Compost, 23,477, 5% Mostly Inorganic Fertilizer, 83,890, 18% 0 50,000 100,000 150,000 Area (ha) Mbozi Chunya Mbarali Mbeya Rur Rungwe Kyela Ileje Mbeya Urb District C hart 3.61 A rea o f F ertiliser A pplicatio n by T ype o f F ertiliser and D istrict No Fertilizer Applied M ostly Compost M ostly Inorganic Fertilizer M ostly Farm Yard M anure Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 295ha 14,092ha 2,193ha 3,377ha 2,254ha 370ha 2,506ha 21,154 1% 7% 5% 5% 1% 30% 5% 46% Mbozi Chunya Mbarali 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Mbeya Urban Rungwe Ileje Mbeya Rural Kyela 1,310ha 29,939ha 35,286ha 79,561ha 25,599ha 15,371ha 55,754ha 53,921ha 25% 78% 52% 87% 57% 83% 57% 49% Mbozi Chunya Mbarali 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Planted Area (ha) Planted Area and Percent of Planted Area with No Application of Fertilizer by District MAP 3.37 MBEYA MAP 3.38 MBEYA Area Planted and Percent of Total Planted Area with Irrigation by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) with Irrigation Planted Area (ha) with No Fertilizer Applied Percent of Planted Area (ha) with No Fertilizer Applied Percent of Planted Area (ha) with Irrigation ha RESULTS 50 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 Most annual crop growing households did not use any fertiliser (approximately 190,356 households, 51.2%) of total crop growing households (Map 3.39 and table 3.9)). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (78% of the area planted with fruits and vegetables during the wet season was applied with fertilizers. This was followed by roots and tubers (17%), pulses (13%), cereals (12%) and oil seeds (6%). There was no fertiliser application in cash crops (Table 3.10). 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Mbeya region was 55,610 hectares. The number of households that applied farm yard manure on their annual crops during the wet season was 42,630 and it was applied to 43,004 hectares representing 10.3 percent of the total area planted during that season (Table 3.10). However, cereals had the highest percent (75%) of the planted area applied with farm yard manure followed by pulses (15%), roots and tubers and oilseeds with (4%) each, fruit and vegetables (2%) and cash crops (0.1). Fruit and vegetables had the highest proportion (34%) of planted area applied with farm yard manure followed by cereals and pulses with (14%) each, roots & tubers (9%), oil seeds (8%) and cash crops (2%).(Charts 3.64 and 3.65a). Farm yard manure was mostly used in Rungwe district (27.8% of the total planted area in the district), followed by Ileje (25.1%), Mbeya Urban (19.1%), Mbeya Rural (12.9%), Mbozi (9.8%), Mbarali (7.7%), Chunya (6.3%) and Kyela (3.5%) (Chart 3.65b). For permanent crops, most farm yard manure was used in the production of passion fruits (40.8% of the area planted with passion fruits, followed by apples (31.8%) and coffee (25.7%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Mbeya region was 83,890 hectares which represented 18.3 percent of the total area planted with annuals in the region and 51.5 percent of the total planted area with fertilisers. The number of households that applied inorganic fertilizers on their annual crops during the wet season was 89,672 and it was applied to 76,583 hectares representing 18.3 percent of the total area planted during that season (Table 3.10). The largest planted area applied with inorganic fertilizers was in regard to cereals (84.6% of the total area applied with inorganic fertilizers), followed by roots and tubers (5.2%), pulses (4.4%), cash crops (4.1%), fruit and vegetables (0.9%) and oil seeds (0.8%) (Chart 3.66). However, cash crops had the highest percentage of planted area applied with inorganic Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - MBEYA Roots & Tubers, 1,979, 4% Pulses, 8,335, 15% Oil Seeds, 2,277, 4% Fruits & Vegetables, 1,177 2% Cash Crops, 78, 0.1% Cereals, 42,088, 75% Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - MBEYA 0.0 10.0 20.0 30.0 Rungwe Ileje Mbeya Urban Mbeya Rural Mbozi' Mbarali Chunya Kyela District Percent 0 25 50 75 Percent of Planted Area Cereals Pulses Oil Seeds Roots & Tubers Fruits & Vegetables Cash Crops Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 fertilizers (89%) followed by cereals (24%), fruits & vegetables (23%), roots & tubers (19%), pulses (6%) and oil seeds (2%) (Chart 3.67a). Inorganic fertiliser was mostly used in Mbeya Urban (51.9% of the total planted area in the district), followed by Mbozi (26.9%), Mbeya Rural (23.5%), Ileje (16.5%), Chunya (13.6%), Mbarali (5.2%), Kyela (5.1%) and Rungwe (2.1%). (Chart 3.67b). In permanent crops inorganic fertiliser were used on tea (5.2%), followed by sugarcane (1.1%), coconut (0.3%), mangoes (0.15%) and oranges (0.14%). 3.5.4.3 Compost Use The total planted area applied with compost was 23,477 ha which represented only 5.1 percent of the total area planted with annual crops in the region and 14.4percent of the total area applied with fertilizers in the region. The number of households that applied compost in their annual crops during the wet season was 15,720 and it was applied to 21,606 hectares representing 5.2 percent of the total area planted Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - MBEYA Cereals, 70,980, 85% Cash Crops, 3,478, 4% Roots & Tubers, 4,322, 5% Fruits & Vegetables, 784, 1% Oil Seeds, 678, 1% Pulses, 3,659, 4% Chart 3.68a Planted Area with Compost by Crop Type - MBEYA Cereals, 13,862, 58% Oil Seeds, 1,342, 6% Fruits & Vegetables, 323, 1% Cash Crops, 0, 0% Pulses, 7,024, 30% Roots & Tubers, 1,202, 5% 0.0 20.0 40.0 60.0 Percent of Planted Area Cereals Pulses Oil Seeds Roots & Tubers Fruits & Vegetables Cash Crops Crop Type Chart 3.69b Percentage of Planted Area with Compost by Crop Type- MBEYA Chart 3.68c Proportion of Planted Area Applied with Compost by District - MBEYA 0.0 5.0 10.0 15.0 20.0 Ileje Mbeya Rural Rungwe Kyela Mbeya Urban Mbozi' Chunya Mbarali District Percent 0 30 60 90 Percent of Planted Area Cash Crops Cereals Fruits & Vegetables Roots & Tubers Pulses Oil Seeds Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - MBEYA Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - MBEYA 0.0 20.0 40.0 60.0 Mbeya Urban Mbozi' Mbeya Rural Ileje Chunya Mbarali Kyela Rungwe District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 (Table 3.10 and Chart 3.68a). The proportion of area applied with compost was highest for pulses (12%), followed by fruits & vegetables (9.4%), roots & tubers (5.2%) and cereals and oil seeds with (4.6%) each. No compost manure was applied to cash crops. (Chart 3.68b). Compost was mostly used in Ileje (18.2% of the total planted area in the district), followed by Mbeya Rural (13.9%), Rungwe (8.5%), Kyela (8.3%), Mbeya Urban (6.9%), Mbozi (6.0%), Chunya (2.4%) and Mbarali (1%). (Chart 3.67b). In permanent crops, compost was mostly used in the growing of durian (100.0%) followed by cloves (8.6%), pears (7.8%), avocado (5.3%) cinnamon (4.7%) and mango (4.0%). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 87,626 ha of annual crops and vegetables. Insecticides were the most common pesticide used in the region (56% of the total area applied with pesticides). This was followed by herbicides (30%) and fungicides (14%) (Chart 3.69). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 49,308 ha which represented 10.7 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with insecticides (31,611 ha, 64.1% of the total planted area with insecticides) followed by pulses (8,898 ha, 18.0%), roots and tubers (3,357 ha, 6.8%), cash crops (3,211 ha, 6.5%) fruit and vegetables (1,672 ha, 3.4%), and oil seed (559 ha, 1.1%) (Chart 3.70 and Chart 3.71). Annual crops with more than 50 percent insecticide application were spinach (100%), cucumber (100%), cotton (100%), water mellon (85.4%), tomatoes (83.3%), onions (75.7%), cabbage (71.3%), field peas (56.6%) and chillies (52.2%). Chart 3.69 Planted Area (ha) by Pesticide Use Herbicides, 26,305, 30% Insecticides, 49,308, 56% Fungicides, 12,013, 14% Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cereals, 31,611, 64% Fruits & Vegetables, 1,672, 3% Oil Seeds, 559, 1% Cash Crops, 3,211, 7% Pulses, 8,898, 18% Roots & Tubers, 3,357, 7% 0.0 25.0 50.0 75.0 Percent of Planted Area Cereals Pulses Roots & Tubers Cash Crops Fruits & Vegetables Oil Seeds Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - TANGA 0.0 20.0 40.0 60.0 Mbeya Urban Mbeya Rural Mbozi' Ileje Chunya Rungwe Mbarali Kyela District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 Mbeya Urban district had the highest percent of planted area applied with insecticides (43.5% of the total planted area with annual crops in the district). This was followed by Mbeya Rural (22.1%), Mbozi (14.1%), Ileje (9.7%), Chunya (7.7%), Rungwe (4.4%) and Mbarali (2.8%). The least use was recorded in Kyela district (0.1%) (Chart 3.72). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 26,305 hectares which represented 5.7 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with herbicides (23,179 ha, 88.1%) followed by pulses (1,030 ha, 3.9%), roots and tuber (749 ha, 2.8%), oil seed (598 ha, 2.3%), cash crops (582 ha, 2.2%) and fruits and vegetables (167 ha, 0.6%) (Chart 3.73). Cereals had the highest percentage of the planted area applied with herbicides and fruits and vegetables had the least percentage (0.6 percent) (Chart 3.74). The top six annual crops with the highest percentage use of herbicides in terms of planted area were maize (44%), paddy (41%), beans (4%), tobacco (4%), sorghum (1.2%) and sweet potatoes and irish potatoes (1.2%) each Kyela district had the highest percent of planted area applied with herbicides (32% of the total planted area for annual crops in the district). This was followed by Mbozi (7.1%) , Mbarali (4.3%), Mbeya Urban (2.5%), Chunya (2.2%),Ileje (1.6%), Mbeya Rural (1.3%)and Rungwe (1.0%). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 12,013 ha which represented 2.6 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the long rainy season was 2.3 % higher than the corresponding percentage in short rainy season at (0.3%). However, cereals had the largest planted area applied with fungicides (4,492 ha, 37.4%) followed by roots and tubers (3,188 ha, 26.5% cash crops(1,604 ha, 13.4%), pulses (1,284 ha, 10.7%), fruits & vegetables (1,088 ha, 9.1%) and oil seeds (356 ha, 3.0%) (Chart 3.76). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cereals, 23,179, 88% Cash Crops, 582, 2% Roots & Tubers, 749, 3% Fruits & Vegetables, 167, 1% Pulses, 1,030, 4% Oil Seeds, 598, 2% 0.0 30.0 60.0 90.0 Percent of Planted Area Cereals Pulses Roots & Tubers Oil Seeds Cash Crops Fruits & Vegetables Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - MBEYA 0.0 10.0 20.0 30.0 40.0 Kyela Mbozi' Mbarali Mbeya Urban Chunya Ileje Mbeya Rural Rungwe District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 However, the percentages use of fungicides was highest in cereals and roots and tubers being 37% and 27% respectively, while the least use was in regard to pulses at 3.0 percent only (Chart 3.77). Annual crops with more than 10 percent fungicide use were maize (26%), irish potatoes (19%), tobacco (15%) and beans (12%). Mbeya Urban district had the highest percent of planted area with fungicides (8.5% of the total planted area with annual crops in the district) followed by Chunya (3.3%), Mbeya Rural (3.1%), Mbozi (2.4%), Mbarali and Ileje had (1.7%) each and Rungwe (1.2%. The smallest percentage use was recorded in Kyela (0.8%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.2%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 89 percent of the total area planted with cereals during the wet season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1%, 0.1% and 0.2 % of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. Chart 3.79 Area of Irrigated Land Irrigated area, 46,241, 10% Unirrigated area, 412,985, 90% Chart 3.76 Planted Area Applied with Fungicides by Crop Type Cereals, 4,492, 37% Oil seeds, 356, 3% Fruits & Vegetables, 1,088, 9% Cash Crops, 1,604, 13% Pulses, 1,284, 11% Roots & Tubers, 3,188, 27% 0.0 15.0 30.0 Percent of Planted Area Cereals Roots & Tubers Cash Crops Pulses Fruits & Vegetables Oil seeds Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - MBEYA 0.0 2.5 5.0 7.5 10.0 Mbeya Urban Chunya Mbeya Rural Mbozi' Mbarali Ileje Rungwe Kyela District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.6.1 Area Planted with Annual Crops and Under Irrigation In Mbeya region, the area of annual crops under irrigation was 46,241 ha representing 10 percent of the total area planted (Chart 3.79). The area under irrigation during the dry season was 3,229 ha accounting for 7 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season, 59.3 percent of the area planted with cereals was irrigated, whilst 72.1 percent of the cereals were irrigated in the wet season. The district with the largest planted area under irrigation for annual crops was Mbarali (21,154 ha, 47.7% of the total irrigated planted area with annual crops in the region). This was followed by Mbozi (14,092 ha, 30.5%), Mbeya Rural (3,377 ha, 7.3%), Chunya (2,506 ha, 5.4%), Ileje (2,254 ha, 4.9%), Rungwe (@,193 ha, 4.7%), Kyela (370 ha, 0.8%) and Mbeya Urban (295 ha, 0.6%). Proportionally, Mbarali district had the highest planted area (34 percent of planted area under irrigation). This is followed by Mbozi (10%), Ileje (7%), Mbeya Urban (6%), Mbeya Rural (5%), Rungwe (4%), Chunya (3%) and Kyela (1%) (Chart 3.80 and Map 3.40). Of the total irrigated planted area of annual crops, maize and paddy were the most irrigated crops (over 90 percent of the irrigated planted area) followed by cabbage (96%), onions (96%), Amaranths (89%) and tomatoes (89%). In terms of crop type, the area under irrigation with cereals was highest with 32,922 ha (71.2% of the total area under irrigation), followed by roots & tubers 6,045 ha (13.1%), pulses (3,739 ha, 8.1%), fruit & vegetables (1,471 ha, 3.2%) and oil seeds (202 ha, 0.4%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 1,471 ha which represented 37 percent of the total planted area with fruit and vegetables. Cabbages tomatoes and amaranths were the most irrigated crops. Irrigation was not used on annual cash crops during short rainy season. The number of agricultural households practicing irrigation in Mbeya region has not changed significantly over the 10 year period (32,012 agricultural households in 1995/96 and 32,133 agricultural households in 2002/03). . Chart 3.80: Planted Area with Irrigation by District 0 6,000 12,000 18,000 24,000 Mbarali Mbozi Mbeya rural Chunya Ileje Rungwe Kyela Mbeya urban District Irriga ted Area (ha ) 0 5 10 15 20 25 30 35 40 Percentag e with Irriga tio n Irrigated Land (ha) Percentage of Irrigated Land Chart 3.81 Time Series of Households with Irrigation - MBEYA 32,133 32,012 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 1995/96 2002/03 Agriculture Year Planted Area ubder Irrigation RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 3.6.2 Sources of Water Used for Irrigation Most households obtained irrigation water from rivers (67.2% of households with irrigation). This was followed by canals (26.3%) and wells (5.2%). The proportions of households that used pipe water and dams as a source of water for irrigation were very small being 0.7% and 0.6% respectively. Rivers were the main source of irrigation water 46% of households practicing irrigation, rivers were the main source of irrigation in Mbarali Mbozi and Mbeya rural (16%) 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common methods of getting water for irrigation with 77 percent of households using this method. This was followed by hand bucket with 21 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.83). Gravity was the only method used for obtaining water for irrigation by the households from Kyela district. Hand bucket was the most common method of obtaining irrigation water by the households from Mbozi (52% of households practicing irrigation) followed by Ileje (29%), Mbarali (7%), Rungwe (4%), Chunya and Mbeya Rural (3%) each and Mbeya Urban (2%). The hand bucket was the most common method of obtaining water in all districts except in Kyela district. Sprinklers were used in Mbeya Urban and Mbozi districts only. 3.6.4 Methods of Water Application About 75 percent of the agricultural households that practiced irrigation used flooding for water application. This was closely followed by hand bucket/watering can (23%). Sprinklers and water hose were not widely used as they were used by 2.2% and 0.9% of the households practicing irrigation respectively) (Chart 3.84) Chart 3.82 Number of Households with Irrigation by Source of Water River, 33,543, 67% Dam, 298, 1% Pipe water, 362, 1% Borehole, 0, 0% Well, 2,595, 5% Canal, 13,112, 26% River Canal Well Pipe water Dam Borehole Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Hand Pump, 358, 1% Other, 202, 0% Motor Pump, 384, 1% Gravity, 38,547, 77% Hand Bucket, 10,420, 21% Gravity Hand Bucket Motor Pump Hand Pump Other Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 359, 1% Bucket / Watering Can, 11,462, 23% Flood, 37,693, 75% Water Hose, 397, 1% Flood Bucket / Watering Can Sprinkler Water Hose RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at a higher price or as seed for planting in the following season. The results for Mbeya region show that there were 336,776 crop growing households (90.6% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 296,438 households storing 60,824 tonnes as of 1st October 2003. This was followed by beans and other pulses (161,882 households, 4,923t), paddy (63,146 households, 12,747t), sorghum and millets (41,935 households, 8,250t), groundnuts and bambaranuts (22,915 households, 909t), wheat (9,060 households, 1,147t) and coffee (4,693 households, 287t). 3.7.2 Methods of Storage The region had 222,689 crop growing households storing their produce in sacks and/ or open drums (66% of households that stored crops in the region), followed by the number of households that stored their produce in locally made traditional structures cribs (03,639, (31%), improved locally made structures (4,054 households, 1%), unprotected piles (1,261 households, 0.4%), air tight drums (865 households, 0.3%), modern stores (253 households, 0.1%) and other methods (4,016 households, 1%). Sacks and/or open drums were the dominant storage method in all districts, with Mbeya Urban district having the highest percent of households using this method (97% of the total number of households storing crops. This was followed by Mbarali (79%), Mbeya Rural (76%), Kyela (75%), Mbozi (74%), Chunya (72%), Ileje (55%) and Rungwe (33%) (Chart 3.80). Chart 3.85 Number of Households and Quantity Stored by Crop Type - MBEYA 0 50,000 100,000 150,000 200,000 250,000 300,000 Maize Beans & Pulses Paddy Sorghum and Millet G'nuts/Bamb Nuts Wheat Coffee Crop Number of households 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Quantity (t) Number of Households Quantity Stored (Tons) Chart 3.86 Number of households by Storage Methods - MBEYA Other, 4,016, 1% Improved Locally Made Structure, 4,054, 1% Unprotected Pile, 1,261, 0% Modern Store, 253, 0% Airtight Drum, 865, 0% Sacks / Open Drum, 222,689, 67% Locally Made Traditional Structure, 103,639, 31% Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Mbeya Urban Mbarali Mbeya Rural Kyela Mbozi' Chunya Ileje Rungwe District Percent of households In Sacks / Open Drum In Locally Made Traditional Structure In Improved Locally Made Structure Other Unprotected Pile In Airtight Drum In Modern Store RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 However, the district with the highest percentage of households using locally made traditional structures in Mbeya region was Rungwe district (61% of the total number of households storing crops), followed by Ileje (44%), Chunya (25%), Mbozi (23%), Kyela (22%),Mbeya Rural (21%), Mbarali (19%) and Mbeya Urban (1%). 3.7.3 Duration of Storage Most of the agricultural households (72% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of above 6 months (69%). The minority of households stored their crop for a period of less than 3 months (15%) (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mbeya Urban district (57%) followed by Rungwe (56%), Mbeya Rural (55%), Mbarali (54%), Kyela (51%), Ileje (50%), chunya (34%) and Mbozi (33%) (Map 3.41). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, the agricultural households in Kyela district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.4 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 93.4 percent followed by selling for high prices. Practically all stored annual cash crops were stored for selling at higher price. (Chart 3.90). 0 40,000 80,000 120,000 160,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 Months Between 3 and 6 Months Over 6 Months Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 30,000 60,000 90,000 120,000 MboziMbeya Rural RungweChunyaMbarali Ileje Kyela Mbeya Urban District Quantity (tonnes) 0 5 10 15 20 25 30 35 % Stored Quantity harves ted (to ns ) Quantity s to red (to ns ) % o f s to rage 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of Households Maize Sorghum & Millet Beans & Pulses Paddy G'nuts/Bambara Nuts Wheat Coffee Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 3.7.5 The Magnitude of Storage Loss About 85.5 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than a quarter was highest for sorghum and millet (9.3% of the total number of households that stored those crops). This was followed by maize (9.1%), groundnuts and bambaranut (5.4%), beans and pulses (2.9%) and paddy (1.1%). Most households storing groundnuts and bambara nuts had little or no storage loss (94%) (Table 3.10). 3.8 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Mbeya region (351,176 households, 99.5% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 80%). Mbarali district had the lowest percent of households processing crops (77% of crop growing households) (Chart 3.91b). 3.8.1 Processing Methods Most crop processing agricultural households processed their crops using neighbour’s machines representing 84 percent (294,395 households). This was followed by those processing on-farm by hand (22,173 households, 6%), traders (17,573 households, 5%) and on-farm by machine (15,428 households, 4%). The remaining methods of processing were used by very few households (less than 1%). 9.2 CROP STORAGE: Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Chunya 22,544 7,374 1,081 496 31,495 Mbeya Rural 37,076 8,006 953 237 46,272 Kyela 23,659 5,759 1,934 266 31,618 Rungwe 46,077 12,877 3,776 391 63,120 Ileje 17,666 6,555 765 65 25,051 Mbozi' 90,612 5,704 3,511 708 100,535 Mbarali 29,201 1,917 327 216 31,662 Mbeya Urban 6,011 730 223 59 7,022 Total 272,846 48,921 12,571 2,438 336,776 0 20 40 60 80 100 Percent of Households Processing Mbozi' Ileje ChunyaRungweMbeya Urban Kyela Mbeya Rural Mbarali District Chart 3.91b Percentage of Households Processing Crops by District Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Ileje Kyela Rungwe Chunya Mbeya Rural Mbozi' Mbeya Urban Mbarali District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other By Factory Chart 3.91a Households Processing Crops Households Not Processing 2.047, 5.5% Households Processing, 351,176, 94.5% Mbeya Urban Rungwe Ileje Mbeya Rural Kyela Mbozi Chunya 5,498 60,729 91,048 45,557 29,091 21,649 22,433 16,475 77% 90% 85% 85% 84% 88% 53% 43% Mbarali Ileje Rungwe Mbozi Mbeya Urban Chunya Mbeya Rural Kyela 50% 33% 34% 57% 55% 56% 51% 54% Mbarali Percent of Households Storing Crops Percent of Households Storing Crops for 3 to 6 Months by District MAP 3.39 MBEYA MAP 3.40 MBEYA Number of Households and Percent of Total Households Selling Crops by District Tanzania Agriculture Sample Census Number of Households Selling Crops Number of Households Selling Crops Percent of Households Storing Crops Percent of Total Households Selling Crops 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 61 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 Although processing by neighbours’ machine was the most common processing method in all districts in Mbeya region, district differences existed. Ileje has a highest percentage of hand processing of households processing crops (15.3%), followed by Kyela (13%), (Rungwe (8%), Chunya and Mbeya districts (5%) each, Mbozi (4%), Mbeya Urban (3%) and Mbarali. However, processing on farm by machine was more prevalent in Rungwe, Mbeya Urban and Ileje (Chart 3.92) 3.8.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, main product and by-product. The main product is the major product after processing and the by- product is the secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally bran. The main processed product was flour/meal produced by 294,138 agricultural households (84% of households processing crops) followed by grain (50,522 households, 14%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 69.1 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 218,445 households (79%) followed by pulp (25,451 households, 9.2%), husks (24,154 households, 8.7%), shell (4,510 households, 2%) and cake (2,543 households, 1%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.8.3 Main Use of Primary Processed Products Primary processed products were used for households/human consumption, as fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which accounted for 97 percent of the total households that used primary processed crops (Chart 3.95). Chunya, Mbeya Rural and Rungwe were the only districts that used primary products as fuel for cooking. Out of 8,696 agricultural households that sold processed products, 7,242 were from Chunya (24% of the total number of households selling processed products in the region) followed by Kyela (7,118 households (23%), Rungwe (6,811 households, 22%), Ileje (3,043 households, 10%), Mbozi (2,728 households, 9%), Mbarali (1,503 households, 5%), Mbeya Rural (1,198 households, 3.9%) and Mbeya Urban had (1,135 households, 3.7%) (Chart 3.96). Chart 3.93 Percent of Households by Type of Main Processed Product Oil 1% Juice 0% Other 0% Rubber 0% Pulp 0% Grain 14% Flour / Meal 85% Chart 3.94 Number of Households by Type of By-product Pulp, 25,451, 9% Husk, 24,154, 9% Fiber, 400, 0% Other, 251, 0% Juice, 240, 0% Oil, 114, 0% Cake, 2,543, 1% Shell, 4,510, 2% Bran, 218,445, 79% Chart 3.95 Use of Processed Product Sale Only, 8,696, 2% Fuel for Cooking, 330, 0% Other, 360, 0% Did Not Use, 1,169, 0% Animal Consumption, 2,428, 1% Household / Human Consumption, 338,193, 97% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.8.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (9,009 households, 29% of households that sold crops). This was followed by selling to local market and/or trade stores (7,153 households, 27%), trader at farm (6,520 households, 24%), farmer’s associations (1,631 households, 6%), secondary market (1,177 households, 4%) and large scale farms (266 households, 1%) (Chart 3.97). There were large differences between districts in the proportion of households selling processed products to neighbours with Mbeya Rural district having the largest percentage (60%), whereas Kyela district had only 14 percent. Rungwe district had a higher percent of households selling to local markets/trade stores. Compared to other districts, Kyela district had the highest percentage of households selling processed products to traders at farm. In Mbarali district, the sale of processed products to farmer associations was the most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Mbozi and Mbeya Rural. 3.9 Crop Marketing The number of households that reported selling crops was 292,480 which represented 80.3 percent of the total number of crop growing households. The percentage of crop growing households selling crops was highest in Mbozi (90%) followed by Rungwe (88%), Mbeya Rural and Kyela districts had (85%) each, Ileje (84%), Mbeya Urban (77%) Mbarali (53%) and Chunya (43%) (Chart 3.99 and Map 3.42). 0.00 6.00 12.00 18.00 24.00 30.00 Percentage of households Chunya Kyela Rungwe Ileje Mbozi' Mbarali Mbeya Rural Mbeya Urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Large Scale Farm, 266, 1% Secondary Market, 1,177, 4% Marketing Co- operative, 876, 3% Neighbours, 9,009, 34% Farmers Association, 1,631, 6% Trader at Farm, 6,520, 24% Local Market / Trade Store, 7,153, 27% Chart 3.98 Percent of Households Selling Processed Products by O utlet for Sale and District 0% 20% 40% 60% 80% 100% Mbeya Rural Mbeya Urban Chunya Mbarali Ileje Mbozi' Rungwe Kyela District Percent of Households Selling Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 25,000 50,000 75,000 100,000 Mbozi' Rungwe Mbeya Rural Kyela Mbarali Ileje Chunya Mbeya Urban District Number of Households 0 20 40 60 80 100 Percent Number o f Ho us eho lds Selling Cro ps Percentage of Households Selling Crops RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 3.12.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (81% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (high transport costs (4%), %), lack of transport (3%), lack of market information (2%), no buyers (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.12.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 85 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts in the region. 3.13 Access to Crop Production Services 3.13.1 Access to Agricultural Credit The census result shows that in Mbeya region very few agricultural households (21,141 households, 6% of agricultural households) accessed credit). Out of which (16,887 households, 80%) were male-headed households and (4,254 households, 20%) were female. In Mbozi district only male headed households got agricultural credit whereas Ileje district had the highest percentage of female headed households (75%) that got agricultural credits. (Table 3.13). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Number of households % Production Insufficient to Sell 95,536 84.8 Price Too Low 9,434 8.4 Other 4,361 3.9 Farmers Association Problems 913 0.8 Market Too Far 789 0.7 Co-operative Problems 745 0.7 Trade Union Problems 601 0.5 Government Regulatory Board Problems 225 0.2 Total 112,603 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female Total District Number % Number % Number Chunya 5,221 92 466 8 5,687 Mbeya Rural 2,152 56 1,666 44 3,818 Kyela 2,709 83 537 17 3,246 Rungwe 3,732 80 924 20 4,657 Ileje 64 25 192 75 256 Mbozi' 1,072 100 0 0 1,072 Mbarali 1,565 79 407 21 1,971 Mbeya Urban 371 86 62 14 433 Total 16,887 80 4,254 20 21,141 C ha rt 3 .10 0 P e rc e nta g e D is tributio n o f Ho us e ho lds tha t R e po rte d M a rke ting P ro ble m s by Type o f P ro ble m No Buyer, 1,467, 1% Other, 857, 1% Co -o perative P ro blems , 541, 0% Farmers As s o ciatio n P ro blems , 500, 0% Trade Unio n P ro blems , 373, 0% Go vernment Regulato ry Bo ard P ro blems , 369, 0% No Trans po rt, 5,242, 3% Lack o f Market Info rmatio n, 2,863, 2% Trans po rt Co s t To o High, 7,074, 4% Market to o Far, 12,327, 8% Open Market P rice To o Lo w, 130,236, 81% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 3 .13.2 Source of Agricultural Credit The major agricultural credit providers in Mbeya region were co-operatives (35%), Trader / Trade Store (24%), saving and credit societies (12%), other sources (11%), private individuals (10%), religious organization/NGO’s/project (7%), Commercial banks (2%) (Chart 3.101). Provided credits in Chunya, Mbeya Rural and Mbeya Urban districts. Traders/trader stores provided credits in all districts except in Ileje district. (Chart 3.102). 3.13.3 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region was for buying fertilisers (30%), followed by agro- chemicals and labour had (18%) each, seeds (15%), tools and equipments (11%), livestock (2%) and other purposes (5%). The proportion of agricultural credits used for irrigation purposes was small (1%) (Chart 3.103). 3.13.4 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was said to be little credit awareness accounting for 53 percent of the agricultural household (“Did not know how to get credit” and “don’t know about credit”). This was followed by households reporting un-availability of credit (23%), followed by “not wanting to go into debt” (13%), interest rate/cost too high (4%) and the percentage of households that did not want borrow were (3%). The rest of the reasons collectively accounted for (4%) of the households not accessing credit. Chart 3.102: Percentage Distribution of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Ileje Mbozi' Kyela Mbeya Rural Mbeya Urban Mbarali Chunya Rungwe District Percent of Households Family, Friend and Relative Co mmercial Bank Co -o perative Saving & Credit Society Trader / Trade Store P rivate Individual Religio us Organis atio n / NGO / P ro ject Other Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Other, 1,533, 11% Saving & Credit Society, 1,656, 12% Trader / Trade Store, 3,303, 24% Co-operative, 4,816, 35% Commercial Bank, 230, 2% Religious Organisation / NGO / Project, 915, 7% Private Individual, 1,345, 10% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Seeds 12% Tools / Equipment 7% Irrigation Structures 7% Agro-chemicals 7% Other 27% Fertilizers 17% Labour 23% Chart 3.104 Reasons for not Using Credit (% of Households) Difficult bureaucracy procedure, 7,312, 2% Other, 1,954, 1% Credit granted too late, 3,183, 1% Not needed, 11,878, 3% Interest rate/cost too high, 14,231, 4% Did not w ant to go into debt, 45,545, 13% Don't know about credit, 77,839, 22% Not available, 82,391, 23% Did not know how to get credit, 107,370, 31% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3 .14 Crop Extension The number of Agricultural households that received crop extension was 153,818 (41% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Chunya having a relatively high proportion of households (92%) that received crop extension messages in the district followed by Mbeya 3.106 and Map Urban (75%), Mbeya Rural (68%), Mbozi (39%), Ileje (35%), Rungwe (29%), Mbarali (12%) and Kyela (8%) (Chart 4.43). 3.14.1 Sources of Crop Extension Messages Most of the households received extension advice from the Government (128,318 households, 86%). Other providers were (8,010 households, 5%), NGOs provided (6,162 households, 4%), large scale farms (5,527 households, 4%), co-operatives (1,577 households, 1%) and others (Chart 3.107). At district level there were differences in the proportion of the households receiving advice from the government ranging from between (73%) in Mbozi and (98%) in Chunya. 3.14.2 Quality of Extension On the quality of extension services, 71 percent of the agricultural households receiving extension ranked it as good, followed by average (15 %), very good (13%), poor (1%) and no good (0%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables on extension as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Receiving Extension , 153,818, 41% Households Not Receiving Extension , 219,026, 59% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 Mbozi' Mbeya Rural Chunya Rungwe Ileje Mbeya Urban Mbarali Kyela District Number of Households 0 20 40 60 80 100 Percent of Households Households Receiving Extension Households Not Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Other, 8,010, 5% NGO / Development Project, 6,162, 4% Large Scale Farm, 5,527, 4% Cooperative, 1,577, 1% Government, 128,318, 86% Chart 3.108 Number of Households Receiving Extension by Quality of Services Average, 23,266, 15% Poor, 1,949, 1% Very Good, 19,852, 13% No Good, 303, 0% Good, 107,638, 71% Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 5,354 40,558 36,515 19,459 8,976 2,699 5,134 35,124 75% 39% 68% 35% 8% 29% 12% 92% Mbozi Chunya Mbarali 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Mbeya Urban Mbeya Rural Rungwe Mbozi Ileje Kyela 2,797 14,569 8,760 9,049 3,309 2,230 4,726 6,815 39% 14% 16% 13% 13% 7% 12% 16% Chunya Mbarali Number of Households Receiving Crop Extension Services Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.41 MBEYA MAP 3.42 MBEYA Number and Percent of Crop Growing Households using Improved Seed by District Tanzania Agriculture Sample Census Number of Households Using Improved Seed Number of Households Using Improved Seed Percent of Households Crop Growing Using Improved Seed Percent of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 RESULTS 67 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 3.15 Access to Inputs Access to inputs in this section refers to all crop growing households in the region regardless of whether the households grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in Section 3.5. Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households used inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, inorganic fertilizers, fungicides and herbicides. In Mbeya region inorganic fertilizers were used by 120,352 households which represented 32 percent of the total number of crop growing households. This was followed by households that used farm yard manure (29%), insecticides/fungicides (17%), compost manure (15%), improved seeds (14%) and herbicides (7%) (Table 2.13). 3.15.1 Inorganic Fertilisers Smallholders who used inorganic fertilisers in Mbeya mostly purchased them from the local market/trade stores (86.3% of the total number of inorganic fertiliser users) followed by agricultural households that purchased fertilizers from co-operatives (3.4%), crop buyers (2.4%) and neighbours (1.7%). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.109). The source of inorganic fertilisers was mainly less or equal to 10 km from the households with most households residing between 3 and 10 km from the source (29%), followed by those households residing 20 (km) and above (23%), households residing between 10 km and 20 km (18%), less than 1 km (16%), and between 1 and 3 km (14%), (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12%) as the reason for not using the fertilizers, it may be assumed that access to inorganic fertiliser is not the main reason for not using them. Other reasons such as cost were Table 2.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 107,580 29 264,070 71 Improved Seeds 52,255 14 319,395 86 Insecticides/Fungicides 63,646 17 308,004 83 Compost 56,324 15 319,308 85 Inorganic Fertilizers 120,352 32 251,298 68 Herbicides 27,006 7 344,644 93 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 86.3 4.4 3.4 2.4 1.7 0.8 0.3 0.6 0.1 0 30,000 60,000 90,000 120,000 Local Market/Trade stores Local Farmers Group Co-operatives Crop Buyers Neighbours Secondary Market Other Locally Produced by Households Large Scale Farms Source of Inorganic Fertiliser Number of Households Chart 3.110 Percentage of Households Reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 Less than 1 km Between 1 and 3 Between 3 and 10 Between 10 and 20 20 km and above Distance (km) Percent of H ouseholds RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 more important with 70 percent of households responding to cost factors as the main reason for not using. In other words, it may be assumed that if the cost was affordable the demand would be higher and inorganic fertilisers would be made more available. The percentage of smallholders using inorganic fertilisers was highest in Mbeya Urban than in other districts in Mbeya region (52% of households using inorganic fertilisers), followed by Mbozi (27%),Meya Rural (24%), Ileje (17%) and Chunya (14%). Other three districts of Mbeya Urban, Kyela and Rungwe used very little inorganic fertilisers. 3.15.2 Improved Seeds The percentage of crop growing households that used improved seeds was 14.1 percent. of the total number of crop growing households. Most households obtained improved seeds from the local market/trade stores (74.8%). Other less important sources were neighbours (8.8%), locally produced by households (5.4%), co- operatives (5.0%), large scale farms (2.3%), crop buyers (1.5%), secondary markets (0.8%), local farmers’ groups (0.6%), development projects (0.4%) and other sources (0.3%) (Chart 3.111). Access to improved seeds was slightly better than access to chemical inputs with 19 percent of households obtaining the input within 1 km of the household (Chart 3.112). The district which used improved seeds most was Mbeya Urban (39% percent of the total number of households using improved seeds in Mbeya region), followed by Mbeya Rural and Mbarali had (16%) each, Mbozi (14%), Rungwe and Ileje had (13%) each, Chunya (12%) and Kyela (7%) (Map 3.44). 3.15.3 Insecticides and Fungicide Most smallholders using insecticides and fungicides purchased them from local markets/trade stores (87% of the total number of fungicide users). Other sources of insecticides/ fungicides were of minor importance (Chart 3.113). Chart 3.111 Number of Households by Source of Improved Seed 74.8 8.8 5.4 5.0 2.3 1.5 0.6 0.8 0.3 0.4 0 15,000 30,000 45,000 Local Market/Trade Store Neighbours Locally Produced by Households Co-operatives Large scale Farmers Crop Buyers Secondary Market Local Farners Group Development projects Other Source of Improved Seed Number of Households Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 Between 3 and 10 Between 10 and 20 20 km and above Distance (km) Percent of Households Chart 3.113: Number of Households by Source of Insecticides/Fungicides 0.2 0.4 0.2 0.5 1.6 2.1 2.9 5.1 87.0 0 20,000 40,000 60,000 Local Market / Trade Store Co-operative Secondary Market Neighbour Locally Produced by Household Crop Buyers Local Farmers Group Other Development Project S o u r c e o f Im p r o v e d S e e d Number of Households RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 Chart 3.114 shows that there was no distinct pattern in access to Insecticides and fungicides. From the small number of households using insecticides/fungicides coupled with only 7 percent of households responding to “not available” as the reason for not using them, it may be assumed that access was not the main reason for not using them. Other reasons such as cost are more important with 74 percent of households responding to cost factors as the main reason for not using. In other words, it may be assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Most insecticides/fungicides users were in Mbeya Urban district (44 percent of the total number of households that use fungicide in the region), followed by Mbeya Rural 30%) and Chunya (11%). Insecticides/fungicides used in other five districts was of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 49,701 representing all households in the region (Chart 3.115). The number of trees planted by smallholders on their allotted land was 20,797,861 trees. The average number of trees planted per household planting trees was 56 trees. The main specie planted by smallholders was Cyprus spp (9,539,359 trees, 46%), followed by eucalyptus spp (6,714,472 33%), pinus spp (4,287,540, 21%) and senna spp (173,547 trees, 1%). Other types of trees were planted in comparatively small numbers (Chart116. and Map 3.45) Ileje district had the largest number of smallholders with planted trees than any other district (31%) and dominated by cyptus species. This was followed by Mbeya Urban (30%) which were dominated by euclyptus spp. Mbeya Rural (25%), Rungwe (16%), and Mbozi (13%) which is mainly planted with cyprus spp (Chart 3.117 and Map 3.45.). Chart 3.114 Percentage of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 2.116 Number of Planted Trees by Species - MBEYA 0 1,500,000 3,000,000 4,500,000 6,000,000 7,500,000 9,000,000 Cyprus Spp Eucalyptus Spp Pinus Spp Senna Spp Casurina Equisetfilia Melicia excelsa Gravellis Leucena Spp other Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and District 0 1,500,000 3,000,000 4,500,000 6,000,000 7,500,000 9,000,000 Ileje Mbozi' Rungwe Mbeya Rural Mbeya Urban Chunya Kyela Mbarali Region N um be r o f Tre e s Cyprus Spp Eucalyptus Spp P inus Spp Senna Spp Cas urina Equis etfilia Melicia excels a Gravellis Leucena Spp Azadritachta Spp Other Chart 3.115 Number of Households with Planted Trees - MBEYA. Households without Planted Trees, 323,143, 87% Households with Planted Trees, 49,701, 13% Ileje Rungwe Mbeya Urban Mbeya Rural Kyela 16,145 38,949 2,031 21,158 14,340 0 0 2,371 18% 23% 28% 42% 0% 15% 0% 32% Mbozi Chunya Mbarali 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 2,126 13,475 10,926 13,037 7,892 257 956 1,031 1% 7% 5% 5% 1% 30% 5% 46% Mbozi Chunya Mbarali 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Smallholder Number and Percent of Smallholder Planted Trees by District MAP 3.43 MBEYA MAP 3.44 MBEYA Number and Percent of Households With Water Harvesting Bunds by district Tanzania Agriculture Sample Census Number of Households With Water Harvesting Bunds Number of Households With Water Harvesting Bunds Percent of Households With Water Harvesting Bunds Percent of Smallholder Planted Trees Number of Smallholder Planted Trees RESULTS 71 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 Mostl plant trees were planted in plantations or copies. The proportion of trees that were planted in plantations or copies was 90 percent, followed by trees in field/plot boundaries (5%) and trees scattered in the fields (5%) (Chart 3.118). The main purpose of planting trees was to obtain planks/timber (43%). This was followed by wood for fuel (40%), poles (11%), shade (3%), medicinal, charcoal had (0.2%) each and other purposes (2%) (Chart 3.119). 3.10.1 Irrigation and Erosion Control Facilities. Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 61,540 representing 17 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Ileje district (31% of the agricultural households in the district), followed by Rungwe (25%), Mbeya Rural (23%), Mbozi and Mbeya Urban districts had (21%) each, Mbarali (13%), Chunya (2%) and Kyela (0.2%) (Chart 3.121). Erosion control bunds accounted for 51 percent of the total number of structures, followed by water harvesting bunds (24%), drainage ditches (11%), tree belts (7%), terraces (3%), vetiver grass (2%), gabions/sandbags (1%) dams (0.03%) (Chart 3.122 and Map 3.46). Erosion control by erosion control bunds, water harvesting bunds and drainage ditches together had 338,528 structures. This represented 86 percent of the Chart 3.118 Number of Trees Planted by Location Plantation / Coppice, 18,821,626, 91% Field / Plot Boundaries, 1,045,461, 5% Scattered in Field, 930,774, 4% Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Wood for Fuel Poles Shade Other Medicinal Charcoal Use Percent of Households Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with Facilities, 61,540, 17% Households without Facilities, 311,304, 83% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 21 25 23 31 21 2 0 1.3 0 5,000 10,000 15,000 20,000 25,000 Mbozi' Rungwe Mbeya Rural Ileje Mbeya Urban Chunya Mbarali Kyela District Number of Households 0 5 10 15 20 25 30 35 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0 1 2 3 7 11 24 51 0 50,000 100,000 150,000 200,000 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches Tree Belts Terraces Vetiver Grass Gabions / Sandbag Dam Type of Facility Number of Structures RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 total structures in the region. The remaining 14 percentages was shared among the rest of the erosion control methods mentioned above. Rungwe, Mbozi and Ileje districts had 322,221 erosion control structures (83 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 941,077. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region had 5.6 percent of the total cattle population on Tanzania Mainland. 3.12.2 Cattle Population The number of indigenous cattle in Mbeya region was 898,050 (95.4 % of the total number of cattle in the region). There were 40,982 (4.4%) dairy breeds and 2,045 (0.2%) beef breeds. The census results show that 119,098 agricultural households in the region (31.9% of total agricultural households) kept 0.9 million cattle. This was equivalent to an average of 8 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Mbarali which had about 287,381cattle (31% of the total cattle in the region). This was followed by Mbozi (256,867 cattle, 27%), Chunya (139,491 cattle, 15%), Rungwe (86,639 cattle, 9%), Mbeya Rural (67,205 cattle, 7%), Kyela (59,095, 6%) and Ileje (35,384 cattle, 4%). Mbeya Urban district had the least number of cattle (9,016 cattle, 1%) (Chart 3.123 and Map 3.47). However, Mbeya Urban district had the highest density (92 head per km2 ) (Map 3.48). Although Mbarali district had the largest number of cattle in the region, most of it was indigenous. This id the same for other districts except for Rungwe district which had the largest number diary cattle in the region (23,024, 26% of the cattle in the district) In general, the number of beef cattle in the region was moderate (Chart 3.124). 3.12.3 Herd Size Seventy two percent of the cattle-rearing households had herds of size 1-5 cattle with an average of 2 cattle per household. Herd sizes of 6-30 accounted for about 26 percent of all cattle in the region. Only 1 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 98 percent of total cattle rearing households had herds of size 1-30 cattle and owned 54 percent of total cattle in the region, resulting in an average of 4 cattle per cattle rearing household. There were about 0 50 100 150 200 250 300 Number of Cattle ('000') Mbarali Mbozi' Chunya Rungwe Mbeya Rural Kyela Ileje Mbeya Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 40,000 80,000 120,000 160,000 200,000 240,000 280,000 320,000 Mbarali Mbozi' Chunya Mbeya Rural Kyela Rungwe Ileje Mbeya Urban Districts Number of Cattle Indigenous Improved Beef Improved Dairy RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 979 households with a herd size of more than 151 cattle each (269,967 cattle in total) resulting in an average of 276 cattle per household. 3.12.4 Cattle Population Trend Little change in the cattle population has occurred in Mbeya region eight years: from 924,725 in 1995 to 941,077 cattle in 2003, representing an overall annual positive growth rate of only 0.22 percent (Chart 3.125). However, there was a very sharp decrease in number of cattle from 924,725 in 1995 to 756,720 in 1999. The cattle population recovered between 1999 and 2003 at a rate of 5.6 percent. 3.12.5 Improved Cattle Breeds The total number of improved cattle in Mbeya region was 43,027 (40,982 improved dairy and 2,045 improved beef). The diary cattle constituted 4.4 percent of the total cattle and 95.2 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 4.8 percent of the total number of the improved cattle and 0.2 percent of the total cattle. The number of improved diary increased from 14,037 in 1995 to 40,982 in 2003 at an annual growth rate of 14.3 percent. The growth rate was higher over the period 1995 to 1999 (15.0%) than from 1999 to 2003 (13.6%) (Chart 126). 3.12.6 Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats, Mbeya region ranked 13 out of the 21 regions in Tanzania Mainland with 3.1 percent of the total goats on the Mainland. 3.12.7 Goat Population The number of goat-rearing-households in Mbeya region on 1st October 2003 was 59,999 (16% of all agricultural households in the region) with a total of 358,789 goats giving an average of 6 head of goats per goat-rearing-household. Mbozi had the largest number of goats 96,202 goats, 27% of all goats in the region), followed by Mbarali (79,762 goats, 22%), MbeyaRural (65,476 goats, 18%), Chunya (60,104 goats, 17%), Ileje (35,450 goats, 10%), Rungwe (11,168 goats, 3%, Mbeya Urban (9,327 goats, 2.6% and Kyela (1,299 goats, 0.4% (Chart 3.127 and Map 3.49). However Mbeya Urban district had the highest density (240 head per km2 ) (Map 3.50). 0 25 50 75 100 N um ber of G oats ('000'). Mbozi' Mbarali Mbeya Rural Chunya Ileje Rungw eMbeya Urban Kyela District Chart 3.127 Total Number of Goats ('000') by District 924,725 756,720 941,077 - 400,000 800,000 1,200,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 14,037 24,583 40,982 - 15,000 30,000 45,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend Mbeya Urban Mbeya Rural Ileje Kyela Mbozi 198 45 97 38 94 68 13 45 Chunya Rungwe Mbarali 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Mbeya Urban Mbeya Rural Ileje 9,016 67,205 256,867 86,639 35,384 59,095 287,381 139,491 Mbozi Chunya Kyela Rungwe Mbarali 240,000 to 300,000 180,000 to 240,000 120,000 to 180,000 60,000 to 120,000 0 to 60,000 Number of Cattle Cattle population by District as of 1st Octobers 2003 MAP 3.45 MBEYA MAP 3.46 MBEYA Cattle Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Number of Cattle Per Square Km Number of Cattle Per Square Km Number of Cattle RESULTS 75 Kyela Mbeya Urban Mbeya Rural Mbozi Ileje 59,095 9,016 67,205 256,867 35,384 86,639 139,491 287,381 Chunya Rungwe Mbarali 240,000 to 300,000 180,000 to 240,000 120,000 to 180,000 60,000 to 120,000 0 to 60,000 Mbeya Urban Mbeya Rural Mbozi Ileje 204 44 12 2 39 25 6 13 Chunya Kyela Rungwe Mbarali 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 Number of Goat Goat population by District as of 1st Octobers 2003 MAP 3.47 MBEYA MAP 3.48 MBEYA Goat Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Number of Goat Per Square Km Number of Goat Per Square Km Number of Goat RESULTS 76 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 77 3.12.8 Goat Herd Size Sixty percent of the goat-rearing households had herd size of 1-4 goats with an average of 2 goats per goat rearing household. Ninty two percent of total goat-rearing households had herd size of 1-14 goats and owned 65 percent of the total goats in the region resulting in an average of 4 goats per goat-rearing households. The region had 692 households (1% of goat rearing households) with herd sizes of 40 or more goats each (35,454 goats in total), resulting in an average of 51 goats per household. 3.12.9 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds which constituted 96 percent of the total goats in Mbeya region. Improved goats for meat and diary goats constituted of 2 percent each breed. 3.12.10 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 3.5 percent. This positive trend involves four years of population increase from 242,411 goats in 1999 to 358,789 goats in 2003 at an annual rate of 10.3 percent. The number of goats decreased from 272,604 goats in 1995, at an estimated annual rate of (- 2.9) percent to 242,411 goats in 1999. (Chart 128). 3.12.11 Sheep Production Sheep rearing was the third most important livestock keeping activity in Mbeya region after cattle and goats. The region ranked 14th out of 21 Mainland regions and had 2 percent of all sheep on Tanzania Mainland. 3.12.12 Sheep Population The number of sheep-rearing households was 11,605 (3% of all agricultural households in Mbeya region) rearing 66,031 sheep, giving an average of 6 heads of sheep per sheep- rearing household. The district with the largest number of sheep was Mbarali with 22,260 sheep (34%of total sheep in Mbeya region) followed by Mbeya Rural (12,519 sheep, 19%), Chunyas (11,538 sheep, 17%), Ileje (8,966 sheep, 14%), Mbozi (7,794 sheep, 12%), Rungwe (1,612 sheep, 2.4%) and Mbeya Urban (1,072 sheep, 1.6%). Kyela district had the least number of sheep (269 sheep, 0.4%) (Chart 3.129 and Map 3.51). Chunya district had the highest density of sheep (18 head per km2 ) (Map 3.52). 0 7000 14000 21000 N u m b er of sh eep Mbarali Mbeya Rural Chunya Ileje Mbozi' Rungwe Mbeya Urban Kyela District Chart 3.129 Total Number of Sheep by District 272,604 242,411 358,789 - 150,000 300,000 450,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 Sheep rearing was dominated by indigenous breeds that constituted 94 percent of all sheep kept in the region. Only 6 percent of the total sheep in the region were improved breeds. 3.12.13 Sheep Population Trend The overall annual growth rate of the sheep population over the eight year period from 1995 to 2003 is estimated at negative (-1.7) percent. The sheep population decreased at an annual rate of negative (-5.3) percent from 75,679 sheep in 1995 to 60,849 sheep in 1999. But, from 1999 to 2003, sheep population increased at an annual rate of 2.1 percent (Chart 3.130). 3.12.14 Pig Production Pig production is the least important livestock keeping activity in the region after cattle, goats and sheep, however the region ranks first out of 21 Mainland regions for keeping pigs and it has 20 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Mbeya region was 78,724 (21% of the total agricultural households in the region) rearing 227,036 pigs. This gives an average of 3 pigs per pig-rearing household. The district with the largest number of pigs was Mbozi with 57,898 pigs (26% of the total pig population in the region) followed by Rungwe (47,019 pigs, 21%), Chunya (33,814 pigs, 15%), Mbeya Rural (33,535 pigs, 15%), Kyela (32,292 pigs, 14%), Mbarali (11,798 pigs, 5%), Ileje (7,516 pigs, 3%) and Mbeya Urban 3,164 pigs, 1%) (Chart 3.131 and Map 3.53). However Mbeya Urban district had the highest density (69 head per km2) (Map 3.54). 3.12.15 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 6.9 percent. During this period the pig population grew from 133,274 pigs to 227,036 pigs. The pig population decreased from 133,274 pigs in 1995 to 132,257 in 1999 at the annual rate of (-0.2) percent. However, the growth rate increased to 14.5 percent during the following four years from 1999 to 2003 in which pig population increased from 132,257 pigs to 227,036 pigs (Chart 3.132). 0 20,000 40,000 60,000 Number of Pigs Mbozi' Rungwe Chunya Mbeya Rural Kyela Mbarali Ileje Mbeya Urban District Chart 3.131 Total Number of Pigs by District t 75,679 60,849 66,031 - 30,000 60,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 133,274 132,257 227,036 - 100,000 200,000 300,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend Mbeya Urban Ileje Mbeya Rural 1,072 12,519 7,794 8,966 1,612 269 22,260 11,538 Mbozi Chunya Kyela Rungwe Mbarali 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Kyela Mbeya Urban Mbeya Rural Ileje Mbozi 0 2 23 8 10 2 1 4 Chunya Rungwe Mbarali 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Number of Sheep Sheep population by District as of 1st Octobers 2003 MAP 3.49 MBEYA MAP 3.50 MBEYA Sheep Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Number of Sheep Per Square Km Number of Sheep Per Square Km Number of Sheep RESULTS 79 Mbeya Urban Mbeya Rural Ileje 3,164 57,898 33,535 7,516 47,019 32,292 33,814 11,798 Mbozi Chunya Kyela Rungwe Mbarali 48,000 to 60,000 36,000 to 48,000 24,000 to 36,000 12,000 to 24,000 0 to 12,000 Mbeya Urban Mbeya Rural Ileje 69.3 22.3 52.4 51.1 8.2 15.3 3.2 1.9 Mbozi Chunya Kyela Rungwe Mbarali 60 to 75 45 to 60 30 to 45 15 to 30 0 to 15 Number of Pig Pig Population by District as of 1st Octobers 2003 MAP 3.51 MBEYA MAP 3.52 MBEYA Pig Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Number of Pig Per Square Km Number of Pig Per Square Km Number of Pig RESULTS 80 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 81 3.12.16 Chicken Production The poultry sector in Mbeya region was dominated by chicken production. The region contributed 7.7 percent to the total chicken population on Tanzania Mainland. 3.12.17 Chicken Population The number of households keeping chicken was 256,387 raising about 2,559,913 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Mbeya region ranked third out of the 21 Mainland regions. The District with largest number of chickens was Mbozi (1,009,714 chickens, 39% of the total number of chickens in the region) followed by Rungwe (373,004 chickens, 15%), Mbeya Rural (313,661 chickens, 12%), Chunya (207,975 chickens, 8%), Kyela (206,162 chickens, 8%), Mbarali (201,898 chickens, 8%) and Ileje (192,135 chickens, 8%). However, Mbeya Urban had the smallest number of chickens (55,364 chickens, 2%). (Chart 3.133 and Map 3.55). However Mbeya Urban district had the highest density of chickens (1,213 head per km2) (Map 3.56). 3.12.18 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 4.1 percent. The population decreased at a rate of (-5.4) percent from 1995 to 1999 after which it increased to 17.2 percent for the four year period from 1999 to 2003 (Chart 3.134). About (97.4 %) of all chicken kept in Mbeya region were indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 0 250,000 500,000 750,000 1,000,000 N u m b e r o f C h ic k e n s Mbozi RungweMbeya Rur Chunya Kyela Mbarali Ileje Mbeya Urb District Chart 3.133 Total Number of Chickens by District 1,791,488 1,357,834 2,559,912 - 1,000,000 2,000,000 3,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.19 Chicken Flock Size The results indicate that about 88.2 percent of all chicken- rearing households were keeping 1-19 chickens at an average of 7 chickens per chicken keeping household. About 11.4 percent of holders were reported to be keeping flocks of size of 20 to 99 chickens with an average of 31 chickens per holder. Only 0.3 percent of holders kept the flocks of 100 or more chickens at an average of 129 chickens per holder (Table 3.14). 3.12.20 Improved Chickens (layers and broilers) The Layer population in Mbeya Region increased at an annual rate of 61 percent for the period of four years from were 9,762 layers in 1999 to 65,714 layers in 2003. Districts with significant number of improved chickens was most significant in Mbozi, Rungwe, Mbarali, and Mbeya Urban districts. (Chart 3.135). The overall annual growth rate of growth for broilers during the four year period from 1999 to 2003 was (-64.5) percent during which the population decreased from 26,165 to 402. The annual growth rate was higher (-64.5%) for the period of four years from 1999 to 2003. In 1995 the broilers population was not recorded (Chart 3.136). 3.12.6. Other Livestock In Mbeya Region there were 91,591 ducks, 7,538 turkeys, 122,079 rabbits and 11,373 donkeys raised by rural agricultural households. Table 3 -16 gives the number of other livestock kept in each district. The biggest number of ducks in the region was found in Mbozi district (33% of all ducks in the region), followed by Chunya (18%), Mbarali (17%), Rungwe (15%), Kyela (6%),Ileje (5%),Mbeya Rural (4%) and Mbeya Urban (2).Turkeys were reported in Mbeya Rural, Ileje, Mbozi and Mbeya Urban districts only (Table 3.14). Table 3.15 Number of Households and Chickens Raised by flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 82,589 32.2 218,676 3 5 - 9 79,651 31.1 508,677 6 10 - 19 63,931 24.9 812,012 13 20 - 29 17,290 6.7 390,034 23 30 - 39 6,083 2.4 196,672 32 40 - 49 3,376 1.3 141,848 42 50 - 99 2,642 1.0 185,128 70 100+ 826 0.3 106,865 129 Total 256,387 100.0 2,559,913 10 Table 3.16 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Chunya 16,685 0 2,502 845 7,828 Mbeya Rural 3,741 2,668 15,031 1,565 1,905 Kyela 5,419 0 169 7,309 0 Rungwe 13,553 0 1,939 0 0 Ileje 4,412 3,883 8,190 0 623 Mbozi 30,585 892 25,747 1,428 3,795 Mbarali 15,316 0 66,871 227 0 Mbeya Urban 1,881 94 1,629 0 227 Total 91,591 7,538 122,079 11,373 14,378 25,187 171 23,171 232 8,953 0 8,285 0 117 0 0 0 0 0 0 0 0 6,000 12,000 18,000 24,000 30,000 Number of Chickens Mbozi Rungwe Mbarali Mbeya Urb Mbeya Rur Chunya Kyela Ileje District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers 0.00 0.00 9,762 28,185 65,714 402 0.00 30000.00 60000.00 Number of layers 1995 1999 2003 Year Chart 3.136 Layers Population Trend Mbeya Urban Rungwe Mbeya Rural Ileje Kyela Mbarali Chunya Mbozi 1,213 209 416 209 326 32 20 267 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Mbeya Urban Mbeya Rural Ileje 55,364 313,661 1,009,714 373,004 192,135 206,162 201,898 207,975 Mbozi Chunya Kyela Rungwe Mbarali 880,000 to 1,090,000 660,000 to 880,000 420,000 to 660,000 210,000 to 420,000 0 to 210,000 Number of Chicken Chicken Population by District as of 1st Octobers 2003 MAP 3.53 MBEYA MAP 3.54 MBEYA Chicken Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Number of Chicken Per Square Km Number of Chicken Per Square Km Number of Chicken RESULTS 83 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.13 Pest and Parasite Incidence and Control The results indicate that 60 percent and 10 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. (Chart 3.137) shows that there was a predominance of tick’s related diseases over tsetse flies related diseases. Incidences of both problems were highest in Mbeya Urban district but lowest in Mbarali district (Map 3.57). The most practiced method of tick control was spraying with 66 percent of all livestock-rearing households in the region using this method. Other methods used were dipping (5%), smearing (1%) and other traditional methods like hand picking (8%). However, 20 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 27 percent of livestock-rearing households. This was followed by dipping (3%). However, 70 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.13.1 De-worming Livestock rearing households that de-wormed their animals were 100,282 (71% of the total livestock rearing households in the region). The percentage of the households that de-wormed cattle was 52 percent, goats (13%), sheep (5%) and pigs (30%) (Chart 3.138). 3.13.2 Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 83,789, representing 64 percent of the total livestock-rearing households and 22 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 47 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (15%), co-operatives and large scale farms (13%) each and other providers (12%). Chart 3.137 Percentage of Livestock Keeping Households Reporting Tick and Tsetseflies Problems by District. 0 20 40 60 80 100 Mbeya Urb Ileje Rungwe Mbozi Mbeya Rur Kyela Chunya Mbarali District Percent Ticks Tsetse 0 10 20 30 40 Percent Rungwe Mbozi Mbeya Rural Ileje Kyela Mbarali Mbeya Urban Chunya District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good 64% Average 11% No good 8% Poor 2% Very Good 15% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 About 64 percent of livestock rearing households described the general quality of livestock extension services as being good, 15 percent said that the services were very good, and 11 percent described them as average. However, 8 percent of the livestock rearing households said the quality was poor, whilst 2 percent described the services being not good (Chart 3.139). 3.13.3 Access to Veterinary Clinic Many veterinary clinics were located nearby livestock rearing households. About 55 percent of the livestock rearing households accessed the veterinary clinic services, at a distance of more than 14 kms. And only 5 percent of the households accessed them at a distance of 14 kms from or less their dwellings (Chart 3.140). The most affected district was Mbozi district with 88 percent of all livestock rearing households accessing the services at a distance of more than 14 kms. Mbeya Urban district was the least affected with about 7 percent of the households accessing the service at a distance of more than 14 kilometers. (Chart 3.141). 3.13.4 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 22,119 (84% of the livestock rearing households accessing the watering points in Mbeya region) whilst 793 households (3%) resided between 5 and 14 kms. However, 3,476 households (13%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Mbozi district had the best livestock water supply with the majority of livestock rearing households residing within 5 Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 758, 12% Less than 14km, 5541, 88% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 40,000 80,000 Chunya Mbeya Rural Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urban District N um ber o f H o useho lds Less than 14km More than 14km Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 22119, 84% 5-14 kms, 793, 3% 15 or more kms, 3476, 13% Chart 3.143 Number of Households by Distance to Village Watering Point and District 10,606 4,181 2,167 1,728 1,409 990 577 460 0 0 119 450 225 0 0 0 0 0 0 3,252 224 0 0 0 0 4,000 8,000 12,000 Mbozi Ileje Mbeya Rur Chunya Mbarali Mbeya Urb Rungwe Kyela District N um ber o f H o useho lds Less than 5 kms 5-14 kms 15 or more kms Kyela Ileje Rungwe Mbeya Urban Mbeya Rural 21,531 3,682 567 822 4,761 42,933 18,433 10,491 63% 5% 2% 11% 9% 43% 41% 27% Mbozi Chunya Mbarali 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Ileje Mbeya Urban Mbeya Rural Rungwe Kyela 7,858 22,369 10,374 23,087 1,720 7,313 3,699 4,898 71% 77% 63% 57% 67% 45% 51% 46 Mbozi Chunya Mbarali 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Number of Households Number and Percent of Households Infected with Ticks by District MAP 3.55 MBEYA MAP 3.56 MBEYA Number and Percent of Households Using Draft Animals by District Tanzania Agriculture Sample Census Number of Households Number of Households Using Draft Animals Number of Households Infected with Ticks Percent of Households Infected with Ticks Percent of Households Using Draft Animals % RESULTS 86 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 kms from the nearest watering point. This was followed by Ileje, Mbeya Rural, Chunya, Mbarali, Mbeya Urban and Rungwe. In Kyela district about 2 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.14 Animal Contribution to Crop Production 3.14.1 Use of Draft Power Use of draft animals to cultivate land in Mbeya region was limited with 103,219 households (28% of the total agricultural households in the region) using them (Chart 3.144). The highest number of households using draft animals was in Mbozi with 42,933 households representing 41 percent of the households using draft animals in the region. This was followed by Kyela (21,531 households, 20.9%), Mbarali (18,433 households, 18%), Chunya (10,491 households, 10.2%), Mbeya Rural (4,761 households, 0.6%), Rungwe (3,682 households, 3.6%), Mbeya Urban (822 households, 0.8%) and Ileje (567 households, 0.5%). (Chart 3.145 and Map 3.58). The region had 114,206 oxen that cultivated 147,545 hectares. The district with the largest number of oxen was Mbozi (43,361). This was followed by Mbarali (26,073 oxen), Chunya (18,123 oxen), Kyela (17,496 oxen), Mbeya Rural (6,714 oxen), Rungwe (1,608 oxen), Mbeya Urban (711 oxen) and Ileje (120 oxen). The number of oxen in the region accounted for 5 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Mbozi district (57,041 ha, 40% of the total area cultivated using oxen). 0 12,000 24,000 36,000 Number of Households Mbozi' Kyela Mbarali Chunya Mbeya Rural Rungwe Mbeya Urban Ileje District Chart 3.145 Number of Households Using Draft Animals by District - MBEYA 3.144 Number of Households Using Draft Amimals Using Draft Animals, 103,219, 28% Not Using Draft Animals, 269,625, 72% Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 121,427, 33% Not Using Organic Fertilizer, 251,417, 67% Chart 3.147 Area of Application of Organic Fertiliser by District - MBEYA 0 10,000 20,000 30,000 Mbozi' Rungwe Ileje Mbeya Rural Mbarali Chunya Kyela Mbeya Urban District Area of Fertiliser Application (ha) Farm Yard Manure Compost RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 88 3.14.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Mbeya region was 121,427 (33% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 23,117 ha of which 174,399 hectares (75% of the total area applied with organic fertiliser or 42% of the area planted with annual crops and vegetables in Mbeya region during the long rainy season) was applied with farm yard manure (Map 3.59). 3.12.9.3 Use of Compost About 57,720 ha (25% of the area applied with organic fertilizers was applied with compost. The largest area applied with farm yard manure was found in Mbozi district with 9,579 hectares (41% of the total area applied with farm yard manure) followed by Rungwe (6,012 ha, 26%), Mbeya Rural (4,156 ha, 18%), Ileje (2,771 ha, 12%), Kyela (473 ha, 2%), Mbarali (173 ha, 1%),Mbeya Urban (113 ha, 0.5% and Chunya (92 ha, 0.4%) (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Mbeya region was 1,713, representing 0.5 percent of the total agricultural households in the region (Chart 3.148 and Map 3.61). Rungwe was the leading district with 578 households (34% of agricultural households involved in fish farming). This was followed by Mbozi (534 households, 31%), Ileje (256 households, 15%), Mbeya Rural (243 households, 14%), Chunya (84 households, 5%) and Mbeya Urban (17 households, 1%). However, fish farming was not practiced in Kyela and Mbarali districts (Chart 3.149). The main source of fingerings was from neighbours which provided fingering to 60 percent of the fish farming households. This was followed by government institutions (28%), NGO’s/Projects (7%) and from owned ponds (5%). All fish farming households in the region used the pond system particularly the dug-out-ponds and the main fish specie planted was Tilapia. The number of fish harvested in Mbeya region was 555,161 of which 529,657 fish (95%) was tilapia and 25,504 (5%) were other types of fish (Chart 3.150). About 53 percent of the fish farming households sold their fish to neighbours and traders at farm. However, about 47 percent of fish farming households did not sell. Chart 3.148 Number of Households Practicing Fish Farming - MBEYA Households Doing Fish Farming, 1,713, 0.5% Households NOT Doing Fish Farming, 371,131, 99.5% 0 100 200 300 400 500 600 Number of Households Rungwe Mbozi Ileje Mbeya RurAL Chunya Mbeya UrbAN Kyela Mbarali District Chart 3.149 Number of Households Practicing Fish Farming by District - MBEYA Chart 3.150 Fish Production Number of Tilapia, 529,657, 95% Number of Others, 25,504, 5% Mbeya Urban Rungwe Mbeya Rural Ileje Kyela 1,012ha 26,476ha 21,758ha 5,449ha 7,572ha 1,377ha 2,518ha 4,444ha 1.4% 7.7% 30.8% 6.3% 10.7% 1.9% 37.5% 3.6% Mbozi Chunya Mbarali 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 113ha 4,156ha 9,579ha 6,012ha 2,771ha 473ha 173ha 92ha 0.5% 17.8% 41% 25.7% 0.7% 11.9% 2% 0.4% Mbozi Chunya Mbarali 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Planted Area (ha) Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District MAP 3.57 MBEYA MAP 3.58 MBEYA Planted Area and Percent of Total Planted Area with Compost Manure application by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) with Compost Manure Applied Planted Area (ha) with Farm Yard Manure applied Percent of Planted Area (ha) with Farm Yard Manure applied Percent of Planted Area (ha) with Compost Manure Applied RESULTS 89 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 172 2,479 347 63 1,065 414 1,521 296 2.4% 0.5% 2% 0.2% 1.2% 2.4% 3.6% 0.8% Mbozi Chunya Mbarali 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 17 534 243 256 0 0 84 0.5% 0.2% 0.9% 0% 1% 0.5% 0% 0.2% Mbozi Chunya Mbarali 578 480 to 600 360 to 480 240 to 360 120 to 240 0 to 120 Number of Households Number and Percent of Households Practicing Fish Farming by District MAP 3.59 MBEYA MAP 3.60 MBEYA Number and Percent of Households Without Toilets by District Tanzania Agriculture Sample Census Number of Households Number of Households Without Toilets Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming Percent of Households Without Toilets RESULTS 90 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing the basis for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was the service located very far from most of the households’ dwellings than any other service. It was located at an average distance of 97.6 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were: tarmac road (37.1 km), hospital (35.9 km), tertiary market (26.9 km), secondary market (18.8 km), secondary school (14.4 km), primary market (8.7 km), health clinics (5.6 km), primary school (3.2 km) all weather road (3.1 km) and feeder road (1.1 km) (Table 3.15). Table 3.16: Mean distances from holders dwellings to infrustructures and services by districts Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Chunya 28.4 1.7 4.8 1.5 54.3 6.1 113.7 16.9 26.1 34.5 105.5 Mbeya Rural 15.0 10.4 2.4 0.4 37.5 5.5 40.3 6.9 23.4 26.5 24.0 Kyela 8.6 1.7 2.5 0.9 16.2 4.5 123.5 5.4 12.4 14.0 11.1 Rungwe 9.7 2.2 1.8 1.1 17.8 4.4 82.9 6.7 18.0 22.4 21.3 Ileje 16.1 2.3 2.9 2.6 43.3 5.4 144.3 8.5 22.0 40.9 64.6 Mbozi 15.4 1.8 3.7 0.8 41.5 7.1 111.5 10.7 19.3 30.8 37.4 Mbarali 11.9 2.5 3.8 2.0 47.9 5.5 110.2 5.3 10.6 23.5 26.0 Mbeya Urban 3.8 1.4 0.4 0.2 10.1 3.2 11.0 4.2 11.2 7.6 3.5 Total 14.4 3.2 3.1 1.1 35.9 5.6 97.6 8.7 18.8 26.9 37.1 3.13.2 Type of Toilets A large number of rural agricultural households used traditional pit latrines (346,449 households, 92% of all rural agricultural households), 13,898 households (4%) used flush toilets, 4,663 households (2%) use improved pit latrine and 96 households used other facilities. However, 6,357 households (2%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 39 percent of them were found in Mbozi District and 1 percent was from Ileje. Moreover, the percentages of households without toilets in other districts were as follows Mbarali (24%), Mbeya Rural (17%), Kyela (7%), Chunya and Rungwe districts had (5%) each and Mbeya Urban (3%). ( Map 3.62). Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 346,449, 92% No Toilet / Bush, 6,357, 2% Flush Toilet, 13,898, 4% Improved Pit Latrine, 6,044, 2% Other Type, 96, 0% RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Mbeya region with 199,134 households (53.4% of the agriculture households in the region) owning the asset. This was followed by bicycle (130,803 households, 35.1%), iron (88,658 households, 23.8%), wheelbarrow (20,595 households, 5.5%), mobile phone (6,803 households, 1.8%), vehicle (5,318 households, 1.4%) television/video (4,730 households, 1.3%), and landline phone (1,533 households, 0.4%) (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region with 68 percent of the total rural households using this source, followed by hurricane lamp (26%), pressure lamp (3%), mains electricity (2%) and firewood (1%). The remaining sources of energy for lighting were insignificant. (Chart 3.153). 3 .13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96 percent of all rural agricultural households in Mbeya region. This was followed by charcoal (3%) and crop residues (1%). The rest of energy sources accounted for 0.7 percent. These were mains electricity and solar had (0.2%) each, paraffin/kerosene, bottled gas and livestock dung each (0.1%) and other sources of energy for cooking (0.02%). (Chart 3.154) 3.13.6 Roofing Materials The most common roofing material for roofing of the main dwelling was grass and/or leaves and which was used by 52 percent of the rural agricultural households. This was followed by iron sheets (42%), grass/mud (5%) and tiles (1%). The remaining roofing materials were below one percent. (Chart 3.155). Chart 3.152 Percentage Distribution of Households Owning the Assets 5.5 1.8 1.4 1.3 0.4 53.4 35.1 23.8 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Vehicle Television / Video Landline phone Assets Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 251142, 68% Firewood, 4555, 1% Candles, 758, 0% Solar, 226, 0% Other, 196, 0% Gas (Biogas), 24, 0% Pressure Lamp, 12174, 3% Mains Electricity, 6126, 2% Hurricane Lamp, 97645, 26% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 357390, 96% Livestock Dung, 454, 0% Other, 93, 0% Bottled Gas, 467, 0% Parraffin / Kerocine, 500, 0% Solar, 608, 0% Mains Electricity, 661, 0% Crop Residues, 3167, 1% Charcoal, 9503, 3% Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Asbestos 0% Concrete 0% Tiles 1% Iron Sheets 42% Grass / Leaves 52% Grass & Mud 5% Other 0% Mbeya Urban Rungwe Ileje Mbeya Rural Kyela 2,403 31,145 7,839 11,864 8,925 12,264 11,589 16,894 33% 17% 46% 30% 36% 11% 30% 40% Mbozi Chunya Mbarali 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 568 18,464 52,741 35,373 15,410 22,888 24,678 19,736 34% 8% 53% 60% 67% 51% 58% 52% Mbozi Chunya Mbarali 48,000 to 60,000 36,000 to 48,000 24,000 to 36,000 12,000 to 24,000 0 to 12,000 Number of Households Number and Percent of Households Using Grass/Leaves for Roofing Material by District MAP 3.61 MBEYA MAP 3.62 MBEYA Number and Percent of Households Eating 3 Meals Per Day by District Tanzania Agriculture Sample Census Number of Households Number of Households Eating 3 Meals Per Day Number of Households Using Grass/Leaves for Roofing Material Percent of Households Using Grass/Leaves for Roofing Material Percent of Households Eating 3 Meals Per Day RESULTS 93 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 Kyela district had the highest percentage of households with grass/leaves roofing (67%) followed by Ileje (60%), Mbarali (58%), Rungwe (53%), Chunya (52%), Mbozi (51%), Mbeya Rural (34%) and Mbeya Urban (8%) (Chart 3.156 and Map 3.63). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Mbeya region was unprotected spring (24 percent of households used unprotected wells during the wet season and 24 percent of the households during the dry seasons. This was followed by piped water (24% of households in the wet season and 23% in the dry season, unprotected wells (19% of households in the wet season and 18% in dry season, (protected wells 8% of households for each season), unprotected spring (5% of households for each season). However, the remaining sources of drinking water were of minor importance. (Chart 3.157) About 68 percent of the rural agricultural households in Mbeya region obtained drinking water within a distance of less than one kilometer during wet season compared to 62 percent of the households during the dry season. However, 32 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 38 percent of households in the dry season. The most common distance from the source of drinking water was between 0.5 and 2 km (Chart 3.158). Chart 3.157 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 Unprotected Spring P iped WaterUprotected Well Surface Water (Lake / Dam / River / Stream) P rotected Well P rotected / Covered Spring Uncovered Rainwater Catchment Tanker Truck Covered Rainwater Catchment Water Vendor Main source Wet Season Dry Season Chart 3.158 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 <100 m 100 m - 299 m 300 m - 499 m 500 m - 999 m 1 km - 1.99 Km 2 km - 2.99 Km 3 km - 4.99 Km 5 km - 9.99 Km 10+ km Distance P ercent Wet Season Dry Season Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 8 34 51 52 53 58 60 67 0 20 40 60 80 100 Kyela Ileje Mbarali Rungwe Chunya Mbozi Mbeya Rural Mbeya Urban District Percent RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 3.14 Food Consumption Pattern 3.14.1 Number of Meals per Day The majority of households in Mbeya region normally had 2 meals per day (69 percent of the households in the region). This was followed by 3 meals per day (28 percent) and 1 meal per day (3 percent). Only 0.4 percent of the households had 4 meals per day (Chart 3.159). Mbeya Rural district had the largest percent of households eating one meal per day whilst Rungwe had the highest percent of households eating three (3) meals per day. (Table 3.16 and Map 3.64). 3.14.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 279,600 (75% of the agricultural households in Mbeya region). Out of the households that consumed meat, 135, 509 households (48.5 % of those who consumed meat) consumed meat only once during the respective week. This was followed by those who had meat twice during the week (34.4%), three times during the week (12.1%), four times during the week (3.1%) and five times during the week (1.4%). Very few households had meat sixth or seven times during the respective week being seven times during the week (0.3%) and six times during the week (0.2%). About 25 percent of the agricultural households in Mbeya region did not eat any meat during the week preceding the census (Chart 3.160 and Map 3.65). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes Per Day and District Number of meals per day District One % Two % Three % Four % Total Chunya 1,414 3.7 24,859 65.0 11,589 30.3 399 1.0 38,262 Mbeya Rural 4,225 7.8 40,360 74.9 8,925 16.6 355 0.7 53,865 Kyela 518 1.5 21,411 62.6 12,264 35.9 0 0.0 34,192 Rungwe 347 0.5 35,831 53.2 31,145 46.3 0 0.0 67,323 Ileje 779 3.0 17,201 66.6 7,839 30.4 0 0.0 25,819 Mbozi 4,228 4.1 87,224 84.3 11,864 11.5 171 0.2 103,486 Mbarali 639 1.5 24,664 57.7 16,894 39.5 520 1.2 42,718 Mbeya Urban 265 3.7 4,376 60.9 2,403 33.5 135 1.9 7,180 Total 12,414 3.3 255,926 68.6 102,924 27.6 1,580 0.4 372,844 Chart 3.159 Number of Agriculural Households by Number of Meals per Day Two, 255,926, 69% Four, 1,580, 0% One, 12,414, 3% Three, 102,924, 28% Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 50,000 100,000 150,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Mbeya Urban Mbeya Rural Ileje Kyela 2,540 16,297 33,509 24,098 7,561 3,739 14,222 7,979 30% 32% 35% 36% 29% 11% 33% 21% Mbozi Chunya Rungwe Mbarali 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Mbeya Urban Rungwe Ileje Mbeya Rural Kyela 2,403 31,145 7,839 11,864 8,925 12,264 11,589 16,894 33% 17% 46% 30% 36% 11% 30% 40% Mbozi Chunya Mbarali 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Number of Households Number and Percent of Households Eating Meat Once per Week by District MAP 3.63 MBEYA MAP 3.64 MBEYA Number and Percent of Households Eating Fish Once per Week by District Tanzania Agriculture Sample Census Number of Households Number of Households Eating Fish Once per Week Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once per Week RESULTS 96 Mbeya Urban Mbeya Rural Rungwe Ileje Kyela 2,532 16,262 33,458 24,045 7,501 3,672 7,927 14,164 49% 44% 27% 39% 46% 47% 43% 45% Mbozi Chunya Mbarali 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Number of Households Number and Percent of Households Reporting Food insufficiency by District MAP 3.65 MBEYA Tanzania Agriculture Sample Census Number of Households Reporting food Insufficiency Percent of Households Reporting Food Insufficiency RESULTS 97 RESULTS AND ANALYSIS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 3.14.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 264,954 (71% of the total agricultural households in Mbeya region) with 109,943 households (41 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (31%), three times during the week (14%). The number of households that consumed fish four or more times during the week in Mbeya region was 35,602 (12% of the agricultural households that ate fish in the region during the respective period). Moreover, about 107, 890 (29%) of the agricultural households in Mbeya region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66) 3.15 Food Security In Mbeya region, 103,757 households (28% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements. However, 23,149 (6%) households said they often experienced problems, where’s 19,378 (5%) households said they sometimes experienced problems and 11,512 (3%) households said that they always had problems in satisfying the household food requirements. On the other hand about 215,048 (58%) agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.15.1 Main Sources of Cash Income The main cash income of the households in Mbeya region was from selling food crops (50 percent of smallholder households), followed by cash crops (17%), businesses (11%), other casual cash (9%), wages & salaries (3%), livestock (2%), forest products (2%), other (2%), livestock products (1%) and fishing (1%). (Chart 3.161). Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Food Crops, 184,754, 50% Cash Crops, 65,222, 17% Business Income, 41,478, 11% Other Casual Cash Earnings, 33,093, 9% Cash Remittance, 7,981, 2% Livestock, 8,337, 2% Wages & Salaries in Cash, 9,661, 3% not applicable, 1,207, 0% Fishing, 3,103, 1% Livestock Products, 3,619, 1% Other, 6,635, 2% Forest Products, 7,753, 2% Chart 3.161 Number of Households by Level of Food Availability Seldom, 103,757, 28% Often, 23,149, 6% Never, 215,048, 58% Sometimes, 19,378, 5% Always, 11,512, 3% 0% 25% 50% 75% 100% Percent of Households Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Crop Type Chart 3.162 Number of Households by Purpose of Storage and Crop Type Never Seldom Sometimes Often Always MBEYA PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 4 MBEYA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 MBEYA Region Profile Mbeya region has the fourth largest rural agriculture population in Tanzania (1,608,718 persons of which 780,102 are males and 828,679 females). It has second largest number of rural households involved in agriculture (372,844) in the country and 95.3 percent of the rural households and 79.5 percent of total households in the region (including urban) are involved in agriculture. The region has an average household size of 4.3 persons per household and it has the second highest percent of female headed households (25%) in the country. Crop only farming dominates and there is virtually no pastoralists in the region. The number of households keeping livestock only is small. Land under customary law is the predominant type of land ownership, accounting for 72 percent of the total rural smallholder owned land. There is a very small amount of land under official titles. The region has an average access to their fields with about 40 percent of the rural agriculture households having their nearest field less than 100 m from the homestead. Access from the field to the nearest road is relatively poor. Mbeya region has a comparatively moderate percent of literate rural agriculture population in the country (68%) compared to other regions and the difference between the literacy rate of males and females is fourth highest with 10.4 percent more literate males than females. It has a small percent of the rural agriculture population that have completed school and a moderate percent of household heads with no education. The most important livelihood activity is crop farming followed by tree/forest resources and livestock keeping/rearing. Permanent crop farming is the least important livelihood activity. The percent of the rural agriculture population working full time in farming is the second highest in the country (87%). The main source of cash income for Mbeya is from the sale of food crops followed by sale of cash crops. Mbeya has the third largest number of households receiving credit mainly from family, friends and relatives (35%) and cooperatives (23%). The region has a moderate percent of households that use modern roofing material (around 44%) and the rest is mainly with grass/leaves/mud. Almost all households in the region have toilet facilities (98.3%). Energy for lighting is mainly from wick lamps 67%) and about 26 percent of households use hurricane lamps. Most water used for drinking in Mbeya is from unprotected springs (24%) and piped water (23%), however, 21 percent of households obtain drinking water from unprotected wells. Most rural agriculture smallholders in Mbeya are living a subsistence existence with more than 50 percent of the agriculture households using between 0 and 25 percent of their livelihood activities for non subsistence purposes. Most households eat two meals per day (69%). Only 28 percent of the households take three meals per day. The region has a low percent of households that do not eat animal protein in one week. Most households eat animal protein twice or three times a week. The region has a low percent of households that face problems in satisfying the household food requirements. It is one of the regions with relatively good access to services and infrastructure in the country. About 46 percent of the households in the region reported insufficiency of land which is high compared to other regions in the country. MBEYA PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. Mbeya has a land area under crop production of 575,000 hectares. It is dominated by annual crops but it has some mono and mixed permanent crops. The land area per household is below average for the country and the percentage utilisation of available land is high suggesting insufficient land. This is confirmed by a 49 percent of smallholders responding to insufficiency of land. Although Mbeya has a short rainy season it is not very important and has only a very small planted area. Mbeya is one of the important cereal production regions in the country and it has the sixth largest planted area of maize, with one of the highest yields of maize in Tanzania which results in the region being the second highest producer. It has the fifth largest planted area of paddy and the second highest production. Moderate amounts of sorghum are grown. Although it has the fourth largest planted areas of beans, it has the highest production in the country. Groundnuts are grown in moderate quantities and are moderately important for the production of vegetables. Tobacco is grown in relatively small quantities but has the fourth largest planted area in the country. Cassava is not important in the region. Mbeya has the largest planted area of coffee, second for oil palm and third for bananas. It has moderate quantities of mango, oranges and some sugar cane is produced. The region has the largest planted area of annual crops under irrigation in Tanzania and the number of households using irrigation has not changed in the last 10 years. It has the highest number of households using rivers as a source of irrigation water and it has one of the highest number of households where gravity is used as a method of obtaining irrigation water. It also has the second highest number of households using flood irrigation. Land clearing and preparation is mostly done by hand, however a third of the land clearing is done by oxen. Although no fertiliser is applied to most of the planted area in Mbeya, it has one of the highest area of inorganic fertiliser application. A small amount of farm yard manure is used. Although small, it has a moderate to high application of pesticides compared to other regions. Mbeya had one of the largest utilisation of maize in the country during the census year and it had the third largest quantity stored. Most storage is in sacks/open drums and locally made traditional structures. It has the second highest number of households selling crops. Most processing in the region is done by neighbours’ machines and it has the highest percent of households selling processed products. The region has one lowest percent of households selling to neighbours. Instead, smallholders sell to traders at farm and farmer associations. Mbeya has the second largest number of households in the country receiving extension services. Mbeya is the second most important region for tree planting in the country, with over 20,000,000 trees planted by smallholders. The main species are Cyprus, eucalyptus and pinus. It has the second largest number of households practicing erosion/water harvesting control, however it does not have the highest number of facilities. Most of them are erosion control and water harvesting bunds. Mbeya has a moderate to low population of livestock, though it is characterized by having the highest pig population in the country. The region has more cattle than other livestock and most of these are indigenous. However it has moderate numbers of improved dairy and beef breeds compared to other regions. Mbeya is the fourth largest milk producing region MBEYA PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 in the country and the farm gate price of milk is average. The region has a small to moderate population of goats and a small number of sheep. The region has the fourth largest chicken population in the country and they are almost entirely indigenous. It also produces more eggs than any other region. Although the region has the highest use of organic fertilizer in terms of the area of application, it has an average area of application per household which indicates a higher demand for organic fertiliser. The rate of disease infection in the region is moderate to low. In general access to livestock infrastructure and services is moderate to high. It has a high number of households receiving extension in relation to its relatively small livestock population compared to other regions. Mbeya is the third largest fish farming region in the country. Mbeya region has one of the largest differences in the numbers of males and females (48% males and 52% females). The region has a normal population pyramid with a slightly higher percent of female between the age 20 to 34. The region has an active agriculture population of 843,629 of which 399,226 are males and 444,403 are females resulting in a moderate difference between the percent of total male and female active population in the region 47% and 53% respectively). The region has the 2nd highest number of households in the country compared to other regions (372,844 out of which 278,613 are male headed and 94,232 are female headed) and it has the 3rd highest percent of female headed households compared to other regions in the country. The average household size is slightly smaller than the National average (4.6 members per household for male headed households and 3.4 for female headed households), resulting in a difference in the household size of 1.2 more members in male headed households compared to female headed households. Mbeya region has the 8th highest percent of households keeping livestock and 23 percentage point more male headed households keep livestock compared to female headed households. There is a relatively moderate difference in the dependency ratio between male and female headed households (97 dependants for every 100 active members in male headed households and 120 dependants for every 100 active members in female headed households). The region has a moderate to high difference in sex ratio of the active agriculture population between male and female headed households in the country (105:100 in male headed households compared to 43:100 in female headed households). Mbeya has the 14th largest difference in illiteracy rate between male and female household heads with an illiteracy rate of 17 percent of male household heads and 53 percent of female household heads. Taking the overall population of male and female members in the region there are 10 percentage points more illiterate females than males and this is 11th largest difference in the country. Mbeya has one of the highest percent of orphans in the country and it has more orphans in female headed households compared to male headed households. No orphan headed households were detected in Mbeya. MBEYA PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 Mbeya has around 8 percent of children with off farm income and more female headed households have children with off farm income compared to male headed households. As with all regions, Mbeya has more land per household in male headed households than in female headed households. It has a moderate area of land per household and the difference between male and female headed households is large (1.0 ha). Mbeya region has a moderate to high percent of households reporting insufficiency of land (44%) and there is no difference between male and female headed households. Female headed households in Mbeya have around 30 percentage points more female land holders compared to male headed households and this difference is moderate compared to other regions. In Mbeya, 43 percent of female headed households have female land holders. Assuming that male household members of female headed households do not have rights to land, this would imply that 57 percent of female headed households have insecure access to land. Mbeya has a higher percent of female headed households using land under customary law compared to male headed households, whilst a higher percent of male headed households have bought land and land under certificate of ownership than female headed households. Mbeya has a moderate to high percent of households keeping cattle with 21 percentage points more male headed households compared to female headed households. The region has a moderate to high percent of households keeping goats and male headed households have 13 percentage points more goat keepers than female headed households. Male headed households also have more goats per household compared to female headed households (6 male headed and 3 female headed). Pigs are important in Mbeya and it has the largest difference between male and female headed households, with 22 percent of male headed households keeping pigs compared to 1 percent of female headed households. Sheep are not important in Mbeya. Compared to other regions, Mbeya has a moderate percent of households using improved seeds and 3 percentage points more male headed households than female headed households use improved seed. Compared to other regions Mbeya, has a moderate percent of households using insecticides (11%), however there is little difference between male and female headed households. The region has the 5th lowest percent of households not using fertilisers (70%). A low to moderate percent of farmers use farm yard manure (10%) and there is no difference between male and female headed households. It has the 4th highest percent of households using inorganic fertiliser, with 4 percentage points more male headed households using it compared to female headed households. The region has the 4th largest area of land under irrigation and male headed households have 4 percentage point more planted area under irrigation compared to female headed households. Mbeya region has a high to moderate percent of households receiving extension advice and 7 percentage points more male headed households receive extension advice compared to female headed households. In Mbeya, 93 percent of male headed households plant crops compared to 90 percent of female headed households in the long rainy season and the reason for not planting is mainly they don’t plant crops (livestock only households). This is followed by illness and social problems which is more prevalent in female headed households than in male headed households. During the short rainy season 15 percent of male headed households and 19 percent of female headed households plant crops and the male reason for not planting during this season are associated with rains. Mbeya has a the 7th highest percent of its planted area with maize and female headed households have 5 percentage points more than female headed households. The yield of maize in the region is one of the highest in the country (1.25t/ha) with MBEYA PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 no difference between male and female headed households. A moderate number of households grow paddy in the region and there is a small difference between male and female headed households. There is no difference in yield between male and female headed households. Mbeya has a moderate percent of households utilising secondary products and they are utilised by 7 percentage point more male headed households than female headed households. Mbeya region has a high percent of active agriculture household members working full time on farm (85% of active members) and there is only a 3 percentage point difference between male and female members. Of the most active agriculture population (18 to 44 years of age) 86 percent of males and 91 percent of females are mainly involved in agriculture. In male headed households, 87 percent of the male members and 92 percent of female members are mainly involved in agriculture, whilst in female headed households 76 percent of males and 88 percent of females are mainly involved in agriculture. Mbeya region has a moderate percent of boys and girls involved in agriculture (12 percent of boys and girls). There are more boys and girls involved in agriculture in female headed households compared to male headed households. There are 20 percent more elderly males compared to elderly females in male headed households that are involved in agriculture in the region. Mbeya region has a high percent of households storing crops (90% of households) compared to other regions and there is little difference between male and female headed households. There is no difference between male and female headed households in the percent of households storing for consumption, selling, storage loss and method of storage. Mbeya has a high percent of households processing crops and there is no difference between male and female headed households. A small percent of households receive credit in Mbeya compared in other regions (6% of male headed households and 4% of female headed households).The main reason for not using credit is that they do not know how to access it, followed by not available, don’t know about credit and there is no difference between male and female headed households. The main use of credit is for labour, seeds and fertiliser and there is no difference between male and female headed households. Most households receive credit from a family, friend or relative, followed by religious organisation. The region has the 7th highest percent of households with modern roofing material in the country (41% of households in the region) and there is no difference between male and female headed households. Mbeya has the 7th highest percent of households using hurricane/pressure lamps for lighting (32% of households) and it has 11 percentage points more male headed than female headed households using this type of lighting. Mbeya has a moderate percent of households using piped drinking water (24%) and there is no difference between male and female headed households. The region has virtually no households without toilets. The difference in the ownership of assets (radio, iron and bicycle) between male and female households is high, in favour of male headed households, for all regions. Mbeya has a moderate percent of households with radios and bicycles and a high percent of irons. Male headed households have 31 percentage points more radios, 11 percentage points more irons and 25 percentage points more bicycles than female headed households. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 There is no difference between male and female headed households in the number of meals household members eat per day in all regions. Mbeya region has a moderate percentage difference in the number of times male and female headed households eat meat compared to other regions. Male headed households eat meat 1.3 times per week whilst female headed households eat meat only 1.0 times per week. A higher percent of female headed households face food shortages compared to male headed households, however this is small compared to most other regions. 4.2 District Profile The following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 3.3.5 Mbeya Mbeya has a land area under crop production of 575,000 hectares. It is dominated by annual crops but it has some mono and mixed permanent crops. The land area per household is below average for the country and the percentage utilisation of available land is high suggesting insufficient land. This is confirmed by a 49 percent of smallholders responding to insufficiency of land. Although Mbeya has a short rainy season it is not very important and has only a very small planted area. Mbeya is one of the important cereal production regions in the country and it has the sixth largest planted area of maize, with one of the highest yields of maize in Tanzania which results in the region being the second highest producer. It has the fifth largest planted area of paddy and the second highest production. Moderate amounts of sorghum are grown. Although it has the fourth largest planted areas of beans, it has the highest production in the country. Groundnuts are grown in moderate quantities and the region is moderately important for the production of vegetables. Tobacco is grown in relatively small quantities but has the fourth largest planted area in the country. Cassava is not important in the region. Mbeya has the largest planted area of coffee, second for oil palm and third for bananas. It has moderate quantities of mango, oranges and some sugar cane is produced. The region has the largest planted area of annual crops under irrigation in Tanzania and the number of households using irrigation has not changed in the last 10 years. It has the highest number of households using rivers as a source of irrigation water and it has one of the highest number of households where gravity is used as a method of obtaining irrigation water. It also has the second highest number of households using flood irrigation. Land clearing and preparation is mostly done by hand, however a third of the land clearing is done by oxen. Although no fertiliser is applied to most of the planted area in Mbeya, it has one of the highest area of inorganic fertiliser application. A small amount of farm yard manure is used. Although small, it has a moderate to high application of pesticides compared to other regions. Mbeya had one of the largest utilisation of maize in the country during the census year and it had the third largest quantity stored. Most storage is in sacks/open drums and locally made traditional structures. It has the second highest number of households selling crops. Most processing in the region is done by neighbours’ machines and it has the highest percent of households selling processed products. The region has one lowest percent of households selling to neighbours. Instead, smallholders sell to traders at farm and farmer associations. Mbeya has the second largest number of households in the country receiving extension services. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 Mbeya is the second most important region for tree planting in the country, with over 20,000,000 trees planted by smallholders. The main species are Cyprus, eucalyptus and pinus. It has the second largest number of households practicing erosion/water harvesting control; however it does not have the highest number of facilities. Most of them are erosion control and water harvesting bunds. 4.1. Chunya Chunya district has the sixth largest number of households in the region as well as fifth highest percent of households in the district that are involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It has a second lowest number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Chunya district is Annual Crop Farming, followed by Off farm Income, Livestock keeping/rearing, Tree or Forest Resources, , Remittances, Permanent crop farming and Fishing/hunting & gathering. However, the district has the fourth highest percent of households with off-farm activities and second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Chunya has the second lowest percent of female headed households (21%) and also it has one of the lowest average ages of the household head. With an average household size of 4.2 members per household it is relative lower than the average for the region. Chunya has a comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively low level of school attendance in the region. The literacy rates for the heads of household is also slightly lower than most of districts in the region. It has the largest utilized land area per household (2.3 ha) and the allocated area was almost fully utilized indicating a high level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet season and it has the highest planted area per household (1.1 ha). The district is important for maize production in the region with a planted area of over 50,000ha, however the planted area per household is the second highest in the region. Paddy production is relative important with a planted area of only 1,853 hectares and the production of sorghum is very big. Chunya district did not have bulrush millet production. Cassava production is moderate accounting for 5 percent of the area planted in the region. The district did no report the production of Irish potatoes. The production of beans in Chunya was moderately in the region with a planted area of (3,791 ha). Oilseed crops are very important in Chunya as it ranks second in the region. Vegetable production is not important in the district. Tomatoes, chillies and cabbage were not recorded in the district, but it was the only district in the region which grew radish. A traditional cash crop (e.g. tobacco,) was grown in moderate to small quantities. Permanent crops are not important in Chunya with a planted area of only 80 hectares (mostly mangoes). As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is moderate, however district differences exist. Chunya ranked fifth in planted area with improved seed in Mbeya region. The district has moderately low planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Chunya district has a moderate level of insecticide use as well as fungicides. Also, Chunya district had the highest percentage of DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 households that used herbicide in the region. It has the fourth largest area with irrigation compared to other districts with 2,506 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood irrigation is the most common means of application. The most common method of crop storage is in sacks and open drums, however the proportion of households storing crops in the district is moderately high than other districts in the region. The district has the relatively low number of households selling crops and for those who did not sell, the main reason for not selling is insufficient production. Chunya is among the highest percent of households processing crops in Mbeya region and is almost all done by hand. Chunya is among the four districts with a higher percent of households selling processed crops to neighborours than other districts and also some sales were made to secondary markets and on traders at farm. Although very small, access to credit in the district is to men only and the main sources are from Co-operative and Family, Friends and Relative. A comparatively larger number of households receive extension services in Chunya and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is small in Chunya as only 5,820 planted trees were planted most of which was senna spp with some Gravellis spp and Azadritachta spp. The third lowest proportion of households with erosion control and water harvesting structures is found in Chunya district and most of these were erosion control bunds; however it has the highest number of terraces, gabions/sandbags and drainage ditches than other districts. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts; however it has the third largest population of sheep in the region. It has comparatively big number of pigs in the region and a moderate number of chickens. The district one of the three that did not show the rearing of layers in the region. It is among the districts with comparatively high numbers of ducks and donkeys the district is ranked fourth in the region. Rabbits are also rarely found in the district and there was no turkeys in the district. Chunya had the second and fourth smallest number of households reporting tsetse and tick problems in the district and it had the second smallest number of households de-worming livestock. The use of draft animals in the district is moderate; there was few households who practiced fish farming in the district. It has the best access to secondary schools, health clinics, primary and secondary markets but amongst the worst access to primary schools compared to other districts. However, it has the best access to all weather roads and moderate access to the regional capital. Chunya district has a relatively low percent of households with no toilet facilities and it has one of the lowest percent of households owning vehicles, bicycles and tv/video, but comparative high percent owing mobile phones. It has the highest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the third lowest percent of households with grass roofs with 31 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. It has a comparative high percent of households having two meals and third highest percent per of households having one meal per day when compared to other districts and relative low percent with 3 meals per day. The district had the fourth highest percent of households that did not eat meat; however, it has one of the lowest percent of DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 households that did not eat fish during the week prior to enumeration. Most households had problems satisfying their food satisfaction. 4.2.2 Mbeya Rural Mbeya Rural district has the fourth largest number of households in the region and the fourth highest percentage of households in the district that are involved in smallholder compared to other districts agriculture in the region. Most smallholders are involved in crop farming only, followed crop and livestock. It has the forth highest number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households Mbeya Rural district is Annual Crop Farming, followed by off farm Income. It has the lowest percent of households with no off-farm activities and also it has the highest percent of households with more than two members with off-farm income. Compared to other districts in the region, Mbeya Rural has a highest percent of female headed households (30%) and it has one of the lowest average ages of the household head in the region. With an average household size of 4.4 members per household it is relatively high for the region. It has a moderate utilized land area per household (1.6 ha) and 97 percent of the allocated area is currently being utilized. The district has the third largest planted area in the region, and the second largest planted area per household (0.7 ha). The district is moderately important for maize production in the region with a planted area of 37,429 ha, and the planted area per household is also moderate for the region. Other cereals are grown in small quantities in the district, however it is the only district with a significant planted area of wheat (about 4,000 ha). The district has the one of the lowest planted area of paddy in the region with only 72 hectares. Sorghum is grown in small quantities in the district. Cassava production is low in the district. The district has a relatively large planted area of Irish potatoes (4,225 ha). The production of beans in Mbeya Rural, though small, was second highest compared to other districts in the region with a planted area of (12,167 ha). Mbeya Rural district has a small planted area of groundnuts and a small area planted per groundnut growing household of 0.35 ha. Vegetable production is moderately important in the district. It has the largest planted area of Onion, and tomatoes, (2,536 ha, 445 ha) than other districts in the region accounting for 41 percent of the tomato planted area, 39 percent of the onion and 11 percent cabbage in the region. This was the only district in the region to grow pyrethrum (245 ha). Compared to other districts in the region, Mbeya Rural has a small area with permanent crops of which 5,071 hectares is under coffee and 493 hectares under bananas. Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, with virtually no tractor or oxen ploughing. The use of inputs in the region is moderately high, and district differences exist. Mbeya Rural has the second largest planted area with improved seed in the region as well as the moderate to high proportion of households using improved seeds. The district has the second highest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is farm yard manure. Compared to other districts in the region, Mbeya Rural district has DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 one of the highest levels of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. Application of herbicides was among the lowest. It has a small area with irrigation compared to other districts with 3,377 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage in Mbeya Rural district is in Sacks/Open Drums, however the proportion of households storing crops in the district is relatively high. Mbeya Rural district is one of the districts with a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Mbeya Rural is among the districts with the highest percent of households processing crops in Mbeya region and is almost all done by neighbours machine. The district also has the third highest percent of households selling processed crops to marketing cooperatives than other districts and no sales are to farmers associations or large scale farms. Although very small, access to credit in the district is to men only and the main source is “saving and credit societies”. A comparatively large number of households receive extension services in Mbeya Rural district and all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is important in Mbeya Rural district with (5,494,741 planted trees) and is mostly Eucalyptus. Pinus and Cyprus. The moderate proportion of households with erosion control and water harvesting structures is found in Mbeya Rural district and is mostly erosion control bunds and water harvesting bunds, however it also has vetiver grass, number of tree belts and drainage ditches. The district has the fifth largest number of cattle in the region and they are almost all indigenous. Goat production is comparative higher compared to other districts; however it has the second largest population of sheep in the region. It has the fourth largest number of both pigs and chicken in the region. Some ducks, rabbits and donkeys are also found in the district. A number of households reported tsetse and tick problems in Mbeya Rural district and it had the third largest number of households de-worming livestock. The district has the fifth largest number of households using draft animals in the region. A small number of households practice fish farming; however the district has the fourth largest number in the region. It has amongst the worst access to secondary schools and primary schools, it has one of the best access to the regional capital. However, it has a moderate access to primary and secondary markets compared to other districts. The percentages of households without toilet facility in Mbeya Rural district is 17 percent and it is among the districts with the highest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the least number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically the majority of households use firewood for cooking. The roofing materials for most of the households in the district is iron sheets (58%) and grass/leaves (34%) and The most common source of drinking water is from surface water (lake/dam/river and stream). It is one of the districts with the highest percent of households having three meals per day. The district had the second highest percent of households that did not eat both meat and fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 4.2.3 Kyela Kyela district has the seventh largest number of households in the region and it has the third lowest percent of households in the district involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by both crop and livestock. It has a small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kyela district is Annual Crop Farming, followed by Permanent Crop Farming. However, the district has the second highest percent of households with no off-farm income activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kyela has a relatively high percent of female headed households (27%) and it has the highest average age of the household head in the region. With an average household size of 4.2 members per household it is below average for the region. Kyela has a highest literacy rate among smallholder households despite a moderate level of school attendance in the region. The land area utilized per household (1.3) is slightly above the average for the region and 90 percent of the allocated area is currently being utilized which is moderate to high for the region. The district has a moderate to low planted area in the region, and the fifth largest planted area per household (0.6 ha in the wet season). The district is comparatively important for maize production in the region with a planted area of 7,036 ha and the planted area per household is (0.4 ha) which is equal to the average for the region (0.4 ha). Paddy production is important with a planted area of 20,811 hectares and it is one of the highest in the region. Other cereals were produced in small quantities. Irish potatoes and wheat were not produced in the district. The district has moderate to low planted area of cassava accounting for 11 percent of the cassava planted area in the region. The production of beans in Kyela is relatively low compared to other districts in the region with a planted area of (418 ha). Oilseed crops are less important in Kyela with 3 percent of the groundnuts grown in the district. Vegetable production is not important in the district. Permanent crop production in the district is of low to moderate importance compared to other districts in the region with only (9.3% of the total permanent crop planted area in region). The most prominent permanent crops in the district include cocoa (5,058 ha harvested area) and bananas (3,007 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the district is amongst the lowest in the region.. Kyela has the comparative small planted area with improved seed in the Mbeya region. The district also has one of the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and practically all is with Inorganic fertilizer. Compared to other districts in the region, although Kyela district has the smallest area of insecticide where’s it has the largest area of fungicide use and the use of herbicides is high. It has the second smallest area with irrigation in the region with (370 ha) of irrigated land. The most common source of water for irrigation is from rivers and canals and almost all water application is by using floods and hand bucket/watering canes. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 The most common method of crop storage in Kyela is in Sacks/Open drums, and the proportion of households not storing crops in the district is moderate to high for the region. The district has the second lowest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Kyela district has a comparative low percent of households processing crops in the region and it is almost all done by neighbours machine; however, the district does not process crops by trader. Small quantities of processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Kyela district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming though small in Kyela district (with 1,478 planted trees) and is mostly Melicia Spp and Eucalyptus Spp.. The second lowest proportion of households with water harvesting bunds is found in Kyela district and it is the only district which controls erosion by using drainage ditches The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is low compared to other districts. It has the fifth largest number of pigs in the region and a comparative low number of chickens, all of which are indigenous. The district has the third lowest number of ducks, but no turkeys and a small number of rabbits but largest number of donkeys were found in the district. Although a small number of households reported tsetse problem but, relative high number of households reported tick problems in Kyela district. A comparative high amount of de-worming of livestock is practiced in the district draft animals are also used. Fish farming was not practiced by households in the district (one of the two districts where fish farming was not carried out in the region). It has amongst the best access to secondary schools and feeder roads but also relative access to primary schools, health clinics, and primary markets compared to other districts. However, it has one of the best accesses to tertiary markets and the regional capital. The percentage of households without toilet facility in Kyela district is below the average of the region; however it has the fourth highest percent of households with toilet facilities. It has the relative low percent of households owning land line phones and vehicles and the lowest percent owing Tv/video. It has also the lowest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. Although, the district has a highest percent of households with grass roofs (67%) 29 percent of households are having iron sheet roofing. The most common source of drinking water is from piped water. Sixteen four percent of the households in the district reported having one or two meals per day and virtually there were some household s that reported having more than three meals per day. The district had the lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Rungwe Rungwe district has the second highest number of households in the region and it has second highest percent of households in the district that are involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It has a relative large number of livestock only households and no pastoralists were found in the district. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 111 The most important livelihood activity for smallholder households in Rungwe district is annual crop farming followed by Permanent Crop Farming. It has the second highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Rungwe district has a relatively high percent of female headed households (28%) and it has one of the highest average age of the household head. With an average household size of 4.0 members per household it is slightly below average for the region. Rungwe district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. It has the second smallest utilized land area per household (1.3 ha) and 100 percent of the allocated land area was utilized. The total planted area was moderate to high in the region however it has the fourth lowest planted area per household (0.6ha in the wet season and 0.4ha in the dry season. Maize production is the most important crop in the district with a planted area of (28,982 ha,), however the planted area per household is among the lowest in the region. Paddy production is also important with a planted area of 3,364 hectares and the production of sorghum was not recorded in the district. Cassava, beans and Irish potato production are moderate in the district. Irish potatoes have the second highest planted area in the region(2,014 ha). Beans are important in the district and was third in the region with the planted area of (11,246 ha). Oilseed crops, vegetables and cash crops are not important in the district. Compared to other districts in the region, Rungwe district has the largest planted area with permanent crops (55.4% of total permanent crop planted area) which is dominated by banana (43,366 ha), coffee (19,761 ha), cocoa (7,643 ha), and mangoes (2,466 ha). A small area of avocado, plums and are grown. Apart from a minor amount of sugarcane no other permanent crops are grown. As with other districts in the region, most land clearing is done by hand, however it has a substantial amount of land preparation done by Tractor and virtually none by oxen plough. The use of inputs in the region is relative small, however district differences exist. Rungwe district has the third smallest planted area with improved seed; however it has also the fourth highest planted area per household in the region. The district also has the third smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with inorganic fertilizer. Compared to other districts in the region, Rungwe district has relative low area planted with insecticide. The percent of planted area with fungicides is amongst the lowest in the region and also is one the lowest for herbicides. It has one of the smallest areas of irrigation with 784 ha. The most common source of water for irrigation is from rivers using gravity and hand buckets/Bucket. Floods and Watering cans are the most common means of irrigation water application. The most common method of crop storage is in sacks and /or open drums; however the proportion of households not storing crops in Rungwe district is amongst the highest in the region. The number of households selling crops in the district is among the largest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The relative big percent of households processing crops in the region is found in Rungwe district and processing is mostly done by neighbours machine. The district has the largest number of households processing crops on farm by machine. It also has the largest number of households processing crops on farm by hand. Most households that sell DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 112 crops sell to local markets or trade stores, traders on farm and neighbours no sales are to large scale farms. Access to credit in the district is very small. A relative large number of households receive extension services in Rungwe district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is equally important in Rungwe district (with 4,807,695 planted trees) and most of them are eucalyptus spp, Cyprus spp, Pinnus spp and some Casurina spp, It has the second largest number of households with erosion control bunds in the reigon. Rungwe district has the fourth smallest number of cattle in the region and most of them are indigenous. It is among the districts with the small number of goats in the region, however the district has the relative high density (97 head per km2) Rungwe has one of the largest number of pigs and chickens, It has relatively low number of sheep, however it has the second largest number of improved chickens (both layers and broilers) in the region. The district has a comparatively high number of ducks and turkeys, together with the highest number of donkeys in the region. A moderate to high number of households reported Tsetse and tick problems in Rungwe district and it had one of the biggest numbers of households de- worming livestock. The use of draft animals in the district is very small and largest number of households practicing fish farming in the region. It has moderate access to feeder roads, primary markets and secondary markets compared to other districts in the region. However, it has the worst access to the regional capital, tarmac roads, and tertiary markets Rungwe district has one of the lowest numbers of households with no toilet facilities. It has one of the lowest percent of households owning television/video, vehicles, radio, mobile phones, land line, irons, bicycles and wheel barrows. It has the third largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the fourth largest percent of households with grass roofs with 43 percent of households having iron sheets. The most common source of drinking water is unprotected spring wells, and it has the lowest percent of households having two or one meal per day compared to other districts and the highest percent with 3 meals per day. The district had one of the lowest percent of households that did not eat meat during the week prior to enumeration but it has a relative low percent of households that did not eat fish. Most households seldom had problems with food satisfaction. 4.2.5 Ileje Ileje district has the lowest number of households in the region and it has the highest percent of households in the district involved in agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a relative small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Ileje district is Annual Crop Farming followed by Permanent Crop Farming, Livestock Keeping/Herding, Off-Farm Income, Tree/Forest Resources, Remittances, and Fishing/Hunting and Gathering. The district has the third highest percent of households with no off-farm activities and the third lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Ileje has a moderate percent of female headed households (28%) and it has one of the moderate average age of the DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 113 household head. With an average household size of 4.2 members per household it is slightly lower than the regional average. Ileje has the third highest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the lowest in the region. It has a moderate utilized land area per household (1.6 ha) which is equal to the regional average. Around 95 percent of the allocated land is utilized. The district has the second smallest planted area in the region, however it has the second largest planted area per household (1.6 ha) in the wet season. Although the planted area of maize is small compared to other districts it is the most important crop in the district (14,551 ha), however the planted area per household is moderate compared to other districts in the region. Paddy production is relatively unimportant with a planted area of only 731 hectares and the production of sorghum is very low. Wheat and finger millet are also grown in the district, but in small quantities. Both Irish potatoes, Sweet potatoes and cassava are grown in the region in moderate to small amounts. The district has among the lowest percent of area planted with Irish potatoes with 279 hectares. The production of beans in Ileje district is the fourth largest in the region with a planted area of 5,535 hectares. Vegetable production is not very important in the district and the district has the second smallest planted area per tomato growing household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Ileje has one of the three districts with smallest planted area with permanent crops which are both planted in mixed area of (30,564 ha) and are dominated by banana, coffee, cocoa and mangoes. However, other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by tractor ploughing. The use of inputs in the region is comparative large, however district differences exist. Ileje has one of the smallest planted areas with improved seed in Mbeya region. The district is among those with largest planted area with fertilizers and most of this is with farm yard manure, inorganic fertilizer and compost. Compared to other districts in the region, Ileje district has the fourth lowest percent of its planted area with insecticides in the region. The use of fungicides was one of the lowest in the region. Also it has the fourth smallest planted area with irrigation in the region with only 1,237hectares of irrigated land. Rivers, canals, wells, and pipe water is used as the source of irrigation water and hand bucket was mainly used. Buckets/Water cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in sacks or in open drums; In Locally Made Traditional Structures (Cribs); however the proportion of households not storing crops in the district is the lowest in the region. The district has one of the smallest numbers of households selling crops and the main reason for not selling is insufficient production. Ileje district has the highest percent of households processing crops on farm by hand and a small percent of households selling processed crops mainly to neighbours and trader at farm. No sales were made to neither local market trade stores nor large scale farms. Access to credit is nonexistent in the district, it has one of the lowest proportions of households that accessed to credit in the region and for those who did not use credit it was because of unavailability of the agricultural credits. A relatively low number of households receive extension services in Ileje district and all of this is from the government. The quality of extension services was rated between good and very good by most of the households. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 114 Tree farming is equally important in Ileje (with 4,664,432 planted trees) and is mostly with Cyprus, Eucalyptus, Senna spp Pinus, Gravellis spp and some Melliola spp, Azadritachta Spp ansd albizia spp. The third largest number of erosion control and water harvesting structures is found in Ileje district and they are mainly Erosion Control Bunds and Water Harvesting Bunds. Other minor erosion control includes tree belts, drainage ditches and terraces. The district has one of the lowest number of cattle in the region and they are mostly all indigenous. Also it is among the districts with smallest number of sheep and lowest production of both goat but a relatively high number of pigs in the region. It has a relative low number of chickens. Small numbers of turkeys, donkeys and rabbits. A moderate number of ducks are kept in the district. A relatively large number of households reported tick problems and very few had Tsetse fly problems in the district. A moderate number of households de-worm livestock. The use of draft animals in the district is non existent and some fish farming is practiced in the district. It is amongst the districts with the best access to regional capital, tertiary market, feeder roads, tarmac roads, secondary schools, primary schools, primary and secondary markets and all weather roads; however it has one of the worst accesses to health clinics. Ileje district has the lowest percent of households with no toilet facilities. The district has one of the smallest percent of households owning landline phones. A very small number of households reported ownership of vehicles, mobile phones, wheel barrows, bicycles, iron and televisions/videos. It has the sixth smallest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the highest percent of households with grass roofs (60 percent), and 36 percent of households having iron sheets. The most common source of drinking water is from unprotected spring wells and surface water (Lake/Dam/River/Stream). It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a relative high percent of households with 3 meals per day. The district had the fourth highest percent of households that did not eat meat during the week prior to enumeration; however it is among the districts with a low percent of households that did not eat fish during the week. Most households in the district seldom or never had problems with food satisfaction. 4.2.6: Mbozi Mbozi district has the highest number of households in the region and it has the highest number of households involved in smallholder agriculture in the region. However in terms of percent of households involved in agriculture in the district, it is third highest. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a relative large number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mbozi district is annual crop farming followed by tree forest resources, then off farm income. It has the second lowest percent of households with no off-farm activities and had fourth lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mbozi district has a relatively low percent of female headed households (22%) and it has the lowest average age of the household head. With an average household size of 4.5 members per household it is slightly high the average for the region. Mbozi district has a comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 115 It has the second largest utilized land area per household (1.8 ha) and 94 percent of the allocated land area is utilized. Mbozi like any other district is important for maize production in the region with a planted area of (67,736 ha,) and the planted area of maize per household is among the highest in the region. Paddy production is also moderately important with a planted area of only 6,346 hectares and the production of sorghum is highest in the region (4,200 ha). Cassava, and beans are comparatively important in the region with both having the largest platted area compared to other districts in the region. Oilseed crops were important in the district with the district having the largest planted area of 8,117 hectares for groundnuts. Vegetables were not very important in the district however some tomatoes and onions are grown. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Mbozi district has one of the largest planted area with permanent crops (23% of total permanent crop planted area) which is dominated by coffee (31,692 ha), banana (1,259ha) and mangoes (477 ha). Apart from a minor amount of sugarcane no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however around 10 percent of land preparation is done using oxen and ploughs. The use of inputs in the region is relative large, however district differences exist. Mbozi district has the fifth smallest planted area with improved seed; however it has also the third highest planted area per household in the region. The district also has the fourth smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with inorganic fertilizer. Compared to other districts in the region, Mbozi district has relative high area planted with insecticide but has the highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is one of the highest for herbicides. It has one of the highest areas of irrigation 14,092 ha. The most common sources of water for irrigation is from rivers, canals, wells and dams using gravity, hand buckets and water pumps. Buckets, watering cans are the most common means of irrigation water application. The most common methods of crop storage is in sacks / open drum and locally made traditional cribs; however the proportion of households not storing crops in Mbozi district is the lowest in the region. The number of households selling crops in the district is the biggest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The biggest percent of households processing crops in the region is found in Mbozi district and processing is mostly done by neighbours machine and on farm by hand. The district has the second largest number of households processing crops on farm by machine. It also has the third largest number of households processing crops on farm by hand. Most households that sell crops sell to neighbours, traders on farm, farmer’s associations and marketing co- operatives. Access to credit in the district is very small. A very large number of households receive extension services in Mbozi district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is equally important in Mbozi district (with 5,253,051 planted trees) and most of them are Cyprus Spp Pinnus Spp, eucalyptus Spp, Senna spp, Melicia spp, Gravellis spp and some Azadritachta spp The largest proportion of households in Mbozi district use erosion control bunds for erosion control.. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 116 Mbozi district has the second largest number of cattle in the region and most of them are indigenous. The district also has the largest number of goats in the region, however the district has the relative high density (68 head per km2). Mbozi district also has the largest number of pigs and chickens in the region. It has the largest number of improved chickens (both layers and broilers) in the region. Comparatively large numbers of ducks, rabbits, turkeys and donkeys are found in the district. A moderate to high number of households reported Tsetse and tick problems in Mbozi district and it had one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is high and it has one of the highest number of households practicing fish farming in the region. It is amongst the districts with the best access to health clinics, secondary schools, primary, secondary and tertiary markets, tarmac roads, all weather roads, and hospitals, regional capital and primary schools, compared to other districts. However, it has the worst access to, feeder roads. Mbozi district has the highest number of households with no toilet facilities. The district has one of the lowest percent of households owning mobile phones, television/video, wheel barrows, vehicles, land line and radio; however, it has the third highest percent of households with both bicycles and irons. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the sixth largest percent of households with grass roofs (51 percent) with 48 percent of the households having iron sheets. The most common sources of drinking water is unprotected wells, unprotected spring, surface water (lake / dam / river / stream) and protected wells. I It has the third highest percent of households having two or one meal per day compared to other districts and the lowest percent with 3 meals per day. The district had the third lowest percent of households that did not eat meat during the week prior to enumeration however it had the highest percent households that did not eat fish. Most households seldom had problems with food satisfaction. 4.2.7: Mbarali Mbarali district has the fifth largest number of households in the region; it however has the second highest percent of households in the district that are involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has one of the smallest numbers of livestock only households and no pastoralists. The most important livelihood activity for smallholder households in Mbarali district is Annual Crop Farming, followed by off farm Income/ tree/Forest Resources / Fishing/hunting and Gathering /Livestock keeping/herding/ Remittances and. Permanent crop farming. However, the district has a moderate to low percent of households with no off-farm income activities and a moderate to high percent of households with more than one member with off-farm income compared to other districts in the region. Mbarali has the fourth lowest percent of female headed households (24%) in the region and it has the third highest average age of the household head. With an average household size of 4.3 members per household it is equal to the average of the region. Mbarali has a moderately high literacy rate among smallholder households in and this is reflected by the relatively high level of never attended school in the region. The literacy rate for the heads of household is among the lowest in the region. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 117 It has the third largest utilized land area per household (1.8 ha) in the region. The total planted area is moderate compared to other districts in the region due to the presence of good wet season, The district is moderately important for maize production in the region with a planted area of over 32,000 hectares and the planted area per maize growing household is the one of the largest in the region. The district is very important for the paddy production with 21,546 hectares and is the highest in the region. Other cereals are not important in the region. Root and tubers, pulses and oilseeds are not important in the district. Vegetable production though small is relatively important in the district compared to other districts in the region. Vegetables grown include tomatoes, spinach and pumpkins, other vegetables are grown in small quantities. No tobacco production was recorded in the district. Compared to other districts in the region, Mbarali has the fourth largest planted area with permanent crops, however it only accounts for 4 percent of the total planted area with permanent crops in the region. The most important permanent crops in the district are mangoes (4,522 ha) and banana (1,926 ha). Other permanent crops are either not grown or are grown in very small quantities. Most land clearing is done by hand slashing, however it has a moderate planted area with “no land clearing” indicating the presence of a large area of bare land before cultivation. Most land preparation is done by oxen (83%) and the remaining is predominantly by hand. The use of inputs in the region is low, however district differences exist with Mbarali district being one of the lowest in the region. However, it has the largest area of irrigation (21,154 ha) and the most common sources of water for irrigation is from rivers and canals using gravity and hand buckets The most common methods of crop storage are in sacks or open drums and local made modern structures (cribs); however the proportion of households’ not storing crops in the district is the highest when compared to other districts in Iringa region. The district has a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Mbarali is among the districts in Mbeya Region with a low percent of households processing crops and is mostly done using neighbours machines. The district also has a small percent of households selling processed crops only to neighbours and farmers associations. Access to credit is in existent in the district. A very low number of households receive extension services in Mbarali and mostly from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming though is not important in Mbarali with only 11,078 planted trees (mostly senna Spp. Eucalyptus Spp, and terminalia spp). A small proportion of households with erosion control and water harvesting structures is found in Mbarali district and is mostly erosion control bunds, however it also has a number of water harvesting bunds, drainage ditches and tree belts. The district has the highest number of cattle in the region and they are all indigenous. Goat production is also high compared to most other districts and it has the largest population of sheep compared to other districts in the region. Pig and chicken production are unimportant in the region and no improved chickens were kept. Mbarali district had the largest numbers of rabbits (66,871). A small number of donkeys and no turkeys were recorded in the district. The moderate to low number of households reporting tick problem was from Mbarali district, however it has the third in the district in the region DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 118 reporting tsetse problem, but, the smallest number of households de-worming livestock. The use of draft animals is third largest district in the region, and no fish farming found in the district. It is amongst the districts with the best access to primary schools, tertiary, primary and secondary markets, secondary, and feeder roads, fair access to all weather roads, health clinics, tarmac roads, however it has one of the worst access to the regional capital. Mbarali district has the highest percent of households with no toilet facilities and it has one of the moderate high percent of households owning vehicles, mobile phones, televisions/video and landline phone. It has also access to mains electricity. The most common sources of energy for lighting is the wick lamp and hurricane lamp and most of the households use firewood for cooking. The district has a third highest percent of households with grass roofs with 58 percent of households having iron sheet roofing (26%). The most common source of drinking water is from piped water, unprotected wells and surface water/lake/dam/river/stream. It has the seventh highest percent of households having two or one meal per day compared to other districts and the second highest percent with 3 meals per day. The district had the moderate percent of households that did not eat meat during the week prior to enumeration; however it has the fifth highest percent of households that did not eat fish during the respective period. Most households seldom had problems with food satisfaction. 4.2.8: Mbeya Urban Mbeya Urban district has the smallest number of households in the region and it has the smallest percent of households that are involved in smallholder agriculture in the district compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mbeya Urban is Annual Crop Farming, followed by off farm Income, Tree/Forest resources, Livestock keeping/herding, Permanent Crop Farming, Remittances and Fishing/Hunting and gathering. The district has third lowest percent of households with no off-farm activities however it has moderate to high percent of households with more than one member with off-farm income. Compared to other districts in the region, Mbeya Urban has the lowest percent of female headed households (19%) and it has one of the lowest average ages of the household head. With an average household size of 4.9 members per household it is relative large for the region. The literacy rate among smallholder households in Mbeya Urban second high compared to other districts in the region and associated with this is a number of household members who have never attended school. It has the smallest utilized land area per household (0.9 ha) in Mbeya region and almost all allocated land is used. The total planted area is the smallest in the region. However the planted area per household in the wet season the district had the second lowest in the region. The planted area per household is fourth highest (1.6ha per household) due to planting crops during both the short and long rainy seasons. Mbeya Urban district is least important for maize production in the region with a planted area of only 3,400 ha, and one of the smallest planted areas per household in the region. The production of paddy, sorghum and finger millet production was not recorded in the district. Small quantities of Cassava was produce in the district accounting for 0.1 percent of the total cassava planted area in the region. Irish potato production was also small in the district with a planted area of 458 hectares. Beans production had a DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 119 planted area of 862 hectares and was third lowest in the region. Oilseed crops are not important in Mbeya Urban. Vegetable production is not important in the district; however small quantities of tomatoes are grown. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Mbeya Urban is not important for permanent crops, with only 265 hectares of coffee and 255 hectares of bananas grown in the district. Most land clearing is done by hand slashing; however land clearing was done by hand on all Planted Area. It has also the smallest area of bush clearance in the region. Most land preparation is done by hand, however it has the lowest planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is comparative low, however district differences exist. Mbeya Urban has a lowest planted area with improved seed in Mbeya region. The use of fertilizer is very small and is mostly inorganic fertilizer and farm yard manure. Compost manure was used in small quantity. The district has the smallest area of land under irrigation however it has the forth highest percent of its planted area under irrigation compared to other districts in the region. The most common source of water for irrigation is from canals and rivers using gravity and hand buckets. Buckets/Watering cans are the only means of irrigation water application in the district. The most common method of crop storage is in sacks/open drums; however the proportion of households not storing crops in the district is moderate to low when compared to other districts in Iringa region. The district has a moderate to low number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Mbeya rural is among the districts in Mbeya region with a low percent of households processing crops and it is mostly done using neighbours machines. The district also has a small percent of households selling processed crops only to neighbours. Access to credit is in existent in the district. A comparatively percent of households receive extension services in Mbeya Urban and mostly from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming though small is important in terms number of smallholders in the district. About 3,630 planted trees were recorded in the district and this is dominated by Eucalyptus. The largest proportion of households in Mbeya Urban district use water harvesting bunds for erosion control. The district has the smallest number of cattle in the region and they are mostly indigenous. Goats sheep and pigs were also kept in small numbers compared to other districts in the region. It has the comparatively smallest number of chickens as well as ducks, donkeys and rabbits. Turkeys were not found in the district. The lowest proportion of households reporting Tsetse and comparative high proportion of households reported tick problems in the region and it had a moderate to low number of households de-wormed livestock compared to other districts. Draft animals are used and fish farming was also practiced in the district. It is amongst the districts with the best access to primary schools and feeder roads health clinic, secondary school, all weather roads and but moderate to tertiary primary, secondary markets, DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 120 Mbeya Urban district had the smallest percentage of households with no toilet facilities. Also has the highest percentage of households with radios, wheel barrows, and irons, it is among the districts with a high percent of households owning vehicles and Tv’s, but low percentages of households owning mobile and land phones. It has a big number of households using mains electricity. The most common source of energy for lighting is the wick lamp and almost all households use firewood for cooking. The district has a moderate to low percent of households with grass roofs (8%), with and 89 percent of households had iron sheet roofing. The most common sources of drinking water are from piped water and unprotected spring. It has the lowest percent of households having three meals per day compared to other districts and moderate percent with one meal, but moderate to high with two meals per day. The district has a moderate to low percent of households that did not eat meat but moderate to high percentage of households who eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. APPENDIX II 121 4. APPENDICES APPENDIX I TABULATION LIST...................................................................................................122 APPENDIX II TABLES .......................................................................................................................137 APPENDIX III QUESTIONNAIRES .................................................................................................286 APPENDIX II 122 TYPES OF AGRICULTURAL HOUSEHOLDS 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year ............................................................................................................138 2.2 Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year .........................................................................................................................138 AGRICULTURE HOUSEHOLDS........................................................................................................139 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.......................................................140 3.1: Livelihood Activities/ Source of Income of the Households Ranked in Order of Importance. ...140 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES..........................................................141 3.1a: First Most Importance..................................................................................................................142 3.1b: Second Most Importance..............................................................................................................142 3.1c Third Most Importance ................................................................................................................142 3.1d Fourth Most Importance..............................................................................................................142 3.1e Fifth Most Importance..................................................................................................................143 3.1f Sixth Most Importance.................................................................................................................143 3.1g Seventh Most Importance ............................................................................................................143 HOUSEHOLDS DEMOGRAPHS........................................................................................................145 3.2 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (Row %)..........................................................................................................146 3.3 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year ( Col.%)...........................................................................................................146 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year.147 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year.................................147 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year ..................................................................147 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year ...........................................................................................................148 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year........................................................149 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year...................................................................149 APPENDIX II 123 3.11 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year........................................................................150 3.12 Mean, Meadian, Mode of Age of Head of Agricultural Household and District.........................150 3.13: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ...150 3.14 Literacy Rate of Heads of Households By District (Mbeya Region)..............................................151 LAND ACCESS/OWNERSHIP.............................................................................................................153 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year .........................................................................................................................154 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year 154 LAND USE...............................................................................................................................................155 5.1 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year .........................................................................................................................156 5.2 Area of Land (Ha) By Type of Land Use and District, 2002/03 Agricultural Year.....................156 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year ..................................................157 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year...............................................157 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year.......................157 TOTAL ANNUAL CROPS & VEGE PRODUCTION - WET & DRY SEASONS..........................159 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District...........160 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District-LONG RAINY SEASON ...............................................................................................160 7.1& 7.2c: Area Planted (Ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year, Mbeya Region..................................................................................161 7.1 & 7.2d. Number of Agricultural Households by Area Planted (Ha) and Crop for the Agricultural Year 2002/03 Dry & Wet Season Mbeya Region....................................................162 7.1 & 7.2e Total Number of Agricultural Households and Planted Area by Means of Soil Preparation and District Dry and Wet Seasons- Mbeya Region ....................................163 ANNUAL CROP & VEGE PRODUCTION- DRY SEASON.............................................................165 7.1 Planted Area (ha) By Means Used for Land Clearing and District During 2002/03 Crop Year-SHORT RAINY SEASON ..........................................................................166 7.2 Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON .................................................................................................166 APPENDIX II 124 7.3 Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON ..........................................................................................................166 7.4 Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON ..........................................................................................................167 7.5 Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON ..........................................................................................................167 7.6 Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON ...............................................................................................167 ANNUAL CROP & VEGE PRODUCTION - WET SEASON...........................................................169 7.2a Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year- LONG RAINY SEASON ............................................................................................................170 7.2b Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON ...................................................................................................170 7.2c Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON....................................................................................................170 7.2 Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON....................................................................................................171 7.2 Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON................................................................................................171 7.1.2j: MARETING: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District, 2002/03 Agricultural Year..........................171 7.2 Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON ............................................................................................................172 7.2g Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop ............................173 7.2.1 Number of Agricultural Households, Area Planted (Ha) and Quantity of Maize Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................174 7.2.2 Number of Agricultural Households, Area Planted (Ha) and Quantity of Paddy Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................174 7.2.3 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sorghum Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................174 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity of Finger Millet Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year .........................175 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity of Wheat Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................175 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity ofCassava Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................175 APPENDIX II 125 7.2.5 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sweet Potatoes Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year .....................176 7.2.6 Number of Agricultural Households, Area Planted (Ha) and Quantity of Irish Potatoes Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................176 7.2.7 Number of Agricultural Households, Area Planted (Ha) and Quantity of IYams Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................176 7.2.8 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cocoyams Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year..................177 7.2.9 Number of Agricultural Households, Area Planted (Ha) and Quantity of Beans Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................177 7.2.10 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cowpeas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year ....................177 7.2.11 Number of Agricultural Households, Area Planted (Ha) and Quantity of Chick Peas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year............................178 7.2.12 Number of Agricultural Households, Area Planted (Ha) and Quantity of Bambaranuts Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year..............178 7.2.13 Number of Agricultural Households, Area Planted (Ha) and Quantity of Field Peas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year............................178 7.2.14 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sunflower Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year ..................179 7.2.15 Number of Agricultural Households, Area Planted (Ha) and Quantity of Simsim Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................179 7.2.16 Number of Agricultural Households, Area Planted (Ha) and Quantity of Groundnuts Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................179 7.2.17 Number of Agricultural Households, Area Planted (Ha) and Quantity of Soya Beans Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................180 7.2.18 Number of Agricultural Households, Area Planted (Ha) and Quantity of Radish Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................180 7.2.19 Number of Agricultural Households, Area Planted (Ha) and Quantity of Bitter Aubergine Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year..................180 7.2.20 Number of Agricultural Households, Area Planted (Ha) and Quantity of Onions Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................181 7.2.21 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cabbage Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................181 7.2.22 Number of Agricultural Households, Area Planted (Ha) and Quantity of Tomatoes Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................181 7.2.23 Number of Agricultural Households, Area Planted (Ha) and Quantity of Spinach Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................182 APPENDIX II 126 7.2.24 Number of Agricultural Households, Area Planted (Ha) and Quantity of Carrot Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................182 7.2.25 Number of Agricultural Households, Area Planted (Ha) and Quantity of Chilles Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year....................................182 7.2.25 Number of Agricultural Households, Area Planted (Ha) and Quantity of Amaranths Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year .................183 7.2.26 Number of Agricultural Households, Area Planted (Ha) and Quantity of Pumpkins Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year...................183 7.2.27 Number of Agricultural Households, Area Planted (Ha) and Quantity of Egg plants Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year..................183 PERMANENT CROPS ..........................................................................................................................185 7.3 Production of Permanent Crops by Crop Type and District - Mbeya Rgion ...............................186 7.4 Total Area Planted (Ha) with Coffee - Mbeya Region ................................................................190 7.5 Total Area Planted (Ha) with Banana - Mbeya Region ...............................................................190 7.6 Total Area Planted (Ha) with Cocoa - Mbeya Region.................................................................190 7.7 Total Area Planted (Ha) with Mangoes - Mbeya Region.............................................................190 7.8 Production of Permanent Planted Crops with Fertilizer Use - Mbeya Region ............................191 7.9 Production of Permanent Planted Crops with Fertilizer by Farm Yard Manure..........................192 7.10 Production of Permanent Planted Crops with Fertilizer by Most Compost Manure - Mbeya Region ..............................................................................................................193 7.11 Production of Permanent Planted Crops with Fertilizer by Most Inorganic Manure - Mbeya Region ..............................................................................................................194 AGROPROCESSING.............................................................................................................................195 8.0a Did tthe Household Process any Of the Products Harvested .......................................................196 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District...................196 8.1.1 Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop .................................................197 8.1.1b Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District...............................................................199 8.1.1c Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District.........................................................................................200 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District.......................................................................................................200 APPENDIX II 127 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District ............................................................................200 8.1.1f Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District.........................................................................................201 8.1.1g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District.......................................................................................................201 MARKETING .........................................................................................................................................203 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District..........................................................................................................204 10.2 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District ...............................................................204 10.3 Proportion of Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District ...............................................................205 IRRIGATION/ EROSION CONTROL ...............................................................................................207 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District..............................................................208 11.2 Area of Irrigated and Non Irriga (ha) Land By District ...............................................................208 11.3 Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District.........................................................................................208 11.4 Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District ........................................................................................................208 11.5 Number of Households Using Irrigation By Method of Irrigation Application By District........209 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District..............................................................................................................209 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District ........................................................................................................................209 ACCESS TO FARM INPUTS AND IMPLEMENTS..........................................................................211 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year..............................................................................................................................................212 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year..............................................................................................................................................212 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ...........................................................................................................212 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year ...........................................................................................................213 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year ........................................................................................213 APPENDIX II 128 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................................214 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................214 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year .............................................................................................214 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .............................................................................................214 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................................215 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year ...........................................................................................................215 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................216 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................216 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year...........................................................................216 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/ Fungicides by District, 2002/03 Agricultural Year......................................................................217 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year .............................................................................................217 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ........................................................................................218 12.1.19 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................218 12.1.20 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year...........................................................................219 12.1.21 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year...........................................................................219 12.1.22 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year.....................................................220 12.1.23 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ........................................................................................220 12.1.24 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ..............................................................................221 12.1.25 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year .............................................................................................221 APPENDIX II 129 12.1.26 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year .............................................................................................221 12.1.27 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year .............................................................................................222 12.1.28 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................................222 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year .............................................................................................222 AGRICULTURAL CREDIT .................................................................................................................223 13.1a Number of Households Receiving Credit By Reason for Not Using Credit By District................224 13.1b Number of Credits Received By Main Purpose of Credit and District ..........................................224 13.2a Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District.......................................................................................................224 13.2 Number of Households Receiving Credit By Source of Credit By District................................224 TREE FARMING AND AGROFORESTRY.......................................................................................225 14 Number of Planted Trees By Species and District, During the agricultural Year 2002/03- Mbeya Region......................................................................................................226 Cont Number of Planted Trees By Species and District, During the agricultural Year 2002/03- Mbeya Region...................................................................................226 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District ..................................................................................226 14.3 Number of Responses by Main Use of Trees By District for the Agricultural Year 2002/03 .....227 14.4 Number of Households By Distance to Community Planted Forest (Km) By District................227 14.5 Second Use of Trees By District..................................................................................................227 CROP EXTENSION...............................................................................................................................229 15.1 Number of Households Receiving Extension Messages By District ...........................................230 15.2 Number of Households By Quality of Extension Services By District .......................................230 15.3 Number of Households By Source of Extension Messages By District ......................................230 15.4 Number of Households By Receiving Advice on Plant Spacing By Source of Messages By District....................................................................................................................231 15.5 Number of Households By Receiving Advice on Agrochemicals By Source of Messages By District....................................................................................................................231 15.6 Number of Households By Receiving Advice on Erosion Control By Source of Messages By District....................................................................................................................231 APPENDIX II 130 15.7 Number of Households By Receiving Advice on Organic Fertilizers Usel By Source of Messages By District ...................................................................................................232 15.8 Number of Households By Receiving Advice on Inorganic Fertilizers Use By Source of Messages By District ...................................................................................................232 15.9 Number of Households By Receiving Advice on Use of Improved Seeds By Source of Messages By District ...................................................................................................232 15.10 Number of Households By Receiving Advice on Mechanization/LSF By Source of Messages By District ...................................................................................................233 15.11 Number of Households By Receiving Advice on Use of Irrigation Technology By Source of Messages By District .............................................................................................233 15.12 Number of Households By Receiving Advice onCrop Storage By Source of Messages By District ...............................................................................................................233 15.13 Number of Households By Receiving Advice on Vermin Control By Source of Messages By District ...............................................................................................................234 15.14 Number of Households By Receiving Advice on agro-Processing By Source of Messages By District....................................................................................................................234 15.15 Number of Households By Receiving Advice on Afro-Forestry By Source of Messages By District....................................................................................................................234 15.16 Number of Households By Receiving Advice on Beekeeping By Source of Messages By District ...............................................................................................................235 15.17 Number of Households By Receiving Advice on Fish Farming By Source of Messages By District ...............................................................................................................235 15.18 Number of Households By Receiving Advice on Other By Source of Messages By District.....235 15.19 Number of Households By Receiving Advice on Other By Source of Messages By District.....236 15.20 Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region...................236 15.21 Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region................................236 15.22 Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region................................236 15.23 Number of Households By Receiving Advice on Other By Source of Messages By District.....237 ANIMAL CONTRIBUTION TO CROP PRODUCTION ..................................................................239 17.1 Number of Households Using Draft Animal to Cultivate Land By District ....................................240 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year ...................................................................................240 APPENDIX II 131 17.3 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year ..........................................................................................................................240 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year ............................................................................................................240 CATTLE PRODUCTION......................................................................................................................241 18.1 Nu,mber of Households Rearing Cattle, Head of Cattle and Average Head Per Households by Head Size on 1st. October 2003 ..........................................................................242 18.2 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................242 18.3 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................242 GOATS PRODUCTION ........................................................................................................................243 19. Total Number of Goats by Type and District as of 1st October, 2003........................................244 19.2 Number of Total Goat by Category and District as of 1st October, 2003....................................244 19.3 Number of Improved Meat Goat by Category and District as of 1st October, 2003 ...................245 19.4 Number of Improved Dairy Goat by Category and District as of 1st October, 2003...................245 19.5 Total Number of Goats by Type and District as of 2st October, 2003.........................................245 SHEEP PRODUCTION .........................................................................................................................147 20.1 Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year ..........................248 20.2 Number of Households Rearing Sheep by District as of 1st October, 2002. Agriculture Year...........................................................................................................................248 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 .............................248 20.5 Number of Households and Heads of Sheep by Herd Size as on 1st October 2003....................249 20.6 Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year..............................................................................................249 20.7 Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year..............................................................................................249 20.8 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year ............................................................................................................249 PIGS HUSBANDRY ...............................................................................................................................251 21.9 Number of Households Rearing Pigs, Herd of Pigs aand Average Head of per Household by Herd Size as of 1st October, 2003 ..................................................................252 21.10 Number of Households Raising Pig by District during 2002/03 Agriculture Year .....................252 21.11 Total Number of Pigs by Type of Pigs and District as of 1st October, 2003...............................252 LIVESTOCK PESTS & PARASITES CONTROL.............................................................................253 APPENDIX II 132 22.1 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year .....................254 22.2 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock ...........254 22.3 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ...........254 22.4 Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year....................254 OTHER LIVESTOCK............................................................................................................................255 23b Number of households with chicken and Category of Chicken by District.................................256 23c Number of Households Rearing and number of Other Livestock by Type and District..............256 23d Number of households with chicken and Category of Chicken by Flock Size............................257 23e Number of households with chicken and Category of Chicken by Flock Size............................257 FISH FARMING.....................................................................................................................................259 24.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year ...........................................................................................................260 24.2a Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year ...........................................................................................................260 24.2b Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year ...........................................................................................................260 24.2c Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year ...........................................................................................................260 24.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....................260 LIVESTOCK EXTENSION ..................................................................................................................261 25.1a Number of Agricultural Households Receiving Advice and District, 2002/03 Agricultural Year ............................................................................................................................262 25.1b Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year ...........................................262 25.1c Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year.......................................................262 25.1d Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year........................................................263 25.1e Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year........................................................263 APPENDIX II 133 25.1.f Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year ......................................263 25.1g Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ..............................................264 25.1h Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year .....................................264 25.1i Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year .......................................................264 25.1j Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year...........................................265 29.1k Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .............................................................................................265 29.12 Number of Agricultural Households Receiving Advice on other Extension Providers By Source and District, 2002/03 Agricultural Year.....................................................................265 ACCESS TO INTRASTRUCTURE & OTHER SERVICES .............................................................267 26.1 Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year.......................................................................................268 26.2. Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year.......................................................................................268 26.3 : Mean distances from holders dwellings to infrustructures and services by districts ....................268 26.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year .........................................................................................................................269 26.6 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year .........................................................................................................................269 26.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year ...........................................................................................................270 26.8 Number of Households to Feeder Roads and District 2002/03 agricultural Year........................270 26.9 Number of Households to Regional Capital and District 2002/03 agricultural Year...................271 26.10 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year ...........................................................................................................271 26.11 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year .............................................................................................271 26.12 Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year .........................................................................................................................271 26.13 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year .............................................................................................272 APPENDIX II 134 26.14 Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year.......................................................................................272 26.15 Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year.......................................................................................272 26.16 Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year.......................................................................................273 26.17 Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year ...........................................................................................................273 26.18 Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ...........................................................................273 26.19 Number of Agricultural Households by Satisfaction of Using Livestock Development Center...274 26.20 Number of Agricultural Households by Satisfaction of the service and district for 2002/03 agricultural Year ............................................................................................................274 HOUSEHOLD FACILITIES.................................................................................................................275 27.1: Number of Agricultural Households by Type of TOILET and District, 2002/03 Agricultural Year ............................................................................................................................276 27.2 : : Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ........................................................................276 27.3 Number of Agricultural Households by Type of Owned Asset and District for 2002/03 agricultural Year ..........................................................................................................................277 27.4 Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year..........................................................................277 27.6 Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year..........................................................................278 27.8: Number of Agricultural Households by Main Source of Drinking Water during ( Wet & Dry) Seasons by District, 2002/03 Agricultural Year........................................279 27.9: Number of Agricultural Households by Main Source of Drinking Water during ( Wet & Dry) Seasons by District, 2002/03 Agricultural Year...................................................280 27.10: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District, 2002/03 Agricultural Year......................281 27.11: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District, 2002/03 Agricultural Year......................282 27.12 Number of Agricultural Households by Number of Meals Normally take Took Per Day by District During 2002/03 Agricultural Year ...............................................................282 34-13: Number of Agricultural Households by Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year.................................283 34-14: Number of Agricultural Households by Number of days the household Consumed Fishduring the Preceeding Week by District, 2002/03 Agricultural Year ...................................283 APPENDIX II 135 27-15: Number of Agricultural Households Reporting the status of food of the households during the Preceeding Year by District, 2002/03 Agricultural Year............................................284 27.16 Number of Hoseholds by Type of Roofing Materials by District, 2002/03 Agricultural Year....284 27.17 Number of hoseholds type of Roofing Materials by District, 2002/03 Agricultural Year...........285 27.18 Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year..........................................................................285 APPENDIX II 136 APPENDIX II: CROPS Type of Agriculture Household................................................................................................................ 137 Number of Agriculture Households..........................................................................................................139 Rank of Importance of Livelihood Activities ...........................................................................................141 Households Demography..........................................................................................................................145 Land Access/Ownership............................................................................................................................153 Land Use……………… ...........................................................................................................................155 Total Annual Crop and Vege Production Long and short Seasons..........................................................159 Annual Crop and Vege Production Long Rainy Seasons..........................................................................165 Permanent Crop Production ......................................................................................................................169 Agro-processing ..................................................................................................................................185 Marketing ..................................................................................................................................203 Irrigation/Erosion Control.........................................................................................................................207 Access to Farm Inputs.............................................................................................................................. 211 Agriculture Credit ..................................................................................................................................223 Tree Farming and Agro-forestry ...............................................................................................................225 Crop Extension ..................................................................................................................................229 Animal Contribution to Crop Production..................................................................................................239 Cattle Production ..................................................................................................................................241 Goat Production ..................................................................................................................................243 Sheep Production ..................................................................................................................................247 Pig Production ..................................................................................................................................251 Livestock Pests and Parasite Control ........................................................................................................253 Other Livestock ..................................................................................................................................255 Fishing Farming ..................................................................................................................................259 Livestock Extension..................................................................................................................................261 Access to Infrastructure and other services...............................................................................................267 Households Facilities ................................................................................................................................275 Appendix II 137 TYPES OF AGRICULTURAL HOUSEHOLDS Tanzania agriculture Sample Census - 2003 Mbeya Region Appendix II 138 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Chunya 38,262 84 2,821 6 41,083 91 4,199 9 45,282 Mbeya Rur 53,865 85 456 1 54,321 86 9,201 14 63,522 Kyela 34,192 80 3,675 9 37,867 88 5,097 12 42,964 Rungwe 67,323 90 3,151 4 70,475 95 3,975 5 74,450 Ileje 25,819 96 787 3 26,606 99 226 1 26,832 Mbozi 103,486 87 1,309 1 104,795 88 14,513 12 119,308 Mbarali 42,718 77 4,040 7 46,757 84 8,617 16 55,374 Mbeya Urb 7,180 11 2,217 3 9,397 15 54,800 85 64,197 Total 372,844 76 18,457 4 391,301 80 100,628 20 491,929 Number % Number % Number % Number % Chunya 29,823 13 94 8 8,345 6 38,262 10 46,606 38,168 8,438 Mbeya Rur 34,368 15 121 10 19,376 14 53,865 14 73,241 53,743 19,497 Kyela 19,540 8 303 25 14,349 10 34,192 9 48,541 33,889 14,652 Rungwe 33,571 14 140 12 33,612 24 67,323 18 100,935 67,183 33,752 Ileje 14,133 6 65 5 11,621 8 25,819 7 37,439 25,754 11,685 Mbozi 64,449 28 317 27 38,720 28 103,486 28 142,207 103,170 39,037 Mbarali 31,750 14 99 8 10,869 8 42,718 11 53,586 42,619 10,967 Mbeya Urb 4,574 2 56 5 2,550 2 7,180 2 9,730 7,124 2,606 Total 232,209 100 1,195 100 139,441 100 372,844 100 512,285 371,650 140,636 Total Total Number of Agricultural Households District Total Number of Agricultural Households Growing Crops Total Number of Agricultural Households Rearing Livestock Crops Only Livestock Only Crops & Livestock Type of Agriculture Household 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households District 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 139 AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 140 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Average Household Size Chunya 30,365 79 5 7,897 21 3 38,262 100 4 Mbeya Rural 37,914 70 5 15,951 30 4 53,865 100 4 Kyela 25,083 73 4 9,109 27 3 34,192 100 4 Rungwe 48,381 72 4 18,942 28 3 67,323 100 4 Ileje 18,505 72 5 7,314 28 3 25,819 100 4 Mbozi 80,232 78 5 23,255 22 4 103,486 100 5 Mbarali 32,295 76 5 10,423 24 3 42,718 100 4 Mbeya Urban 5,839 81 5 1,341 19 4 7,180 100 5 Total 278,613 75 5 94,232 25 3 372,844 100 4 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 1 6 3 2 5 7 4 Mbeya Rural 1 6 5 2 7 4 3 Kyela 1 2 3 4 6 7 5 Rungwe 1 2 3 5 7 4 6 Ileje 1 2 3 4 6 7 5 Mbozi 1 4 5 3 6 7 2 Mbarali 1 7 5 2 6 4 3 Mbeya Urban 1 5 4 2 6 7 3 Total 1 3 4 2 7 6 5 3.1: Livelihood Activities/ Source of Income of the Households Ranked in Order of Importance. 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 141 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture sample census-2003 Mbeya Appendix II 142 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 20,527 0 1,358 13,463 379 590 1,656 Mbeya Rur 32,706 6,682 1,662 9,889 1,429 0 1,497 Kyela 24,722 6,401 486 1,944 300 252 0 Rungwe 33,413 29,883 1,022 2,206 455 0 114 Ileje 17,639 4,870 383 2,283 64 0 322 Mbozi 52,148 23,328 1,798 23,383 708 528 1,242 Mbarali 32,913 0 995 7,966 638 0 0 Mbeya Urb 4,900 52 384 1,639 161 0 43 Total 218,968 71,216 8,087 62,772 4,135 1,371 4,873 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 17,359 482 3,717 13,334 744 365 1,249 Mbeya Rur 17,803 4,574 9,734 14,059 1,077 2,656 4,560 Kyela 7,761 10,927 5,654 6,941 790 680 434 Rungwe 24,946 19,124 9,890 7,057 1,766 3,552 1,114 Ileje 6,197 7,086 5,870 4,513 572 63 1,326 Mbozi 40,455 17,942 12,592 20,038 1,770 1,601 8,876 Mbarali 9,167 1,280 8,058 13,950 672 1,762 5,734 Mbeya Urb 2,001 341 1,349 2,701 244 47 568 Total 125,690 61,755 56,864 82,592 7,635 10,725 23,860 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 176 1,368 5,511 3,827 3,224 449 4,857 Mbeya Rur 2,639 3,335 9,307 7,747 1,801 12,844 14,047 Kyela 785 5,385 9,606 3,912 1,946 545 2,417 Rungwe 4,750 5,802 21,141 7,959 1,144 20,462 4,636 Ileje 1,599 4,200 7,544 3,904 1,592 0 2,793 Mbozi 9,577 8,063 21,281 17,154 3,127 1,427 32,597 Mbarali 418 836 4,005 3,798 1,081 9,719 14,061 Mbeya Urb 220 895 1,136 924 529 504 1,935 Total 20,164 29,885 79,531 49,225 14,444 45,951 77,343 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 98 970 1,876 968 199 95 1,687 Mbeya Rur 362 1,682 4,167 7,541 829 21,535 16,543 Kyela 93 926 3,043 3,023 1,368 356 2,213 Rungwe 1,930 3,349 10,663 4,055 1,493 22,260 7,180 Ileje 192 1,218 2,310 3,316 1,267 64 3,368 Mbozi 847 3,679 9,733 8,019 3,049 536 36,809 Mbarali 113 389 1,869 616 420 11,420 7,386 Mbeya Urb 35 667 519 462 565 781 1,201 Total 3,671 12,878 34,181 28,000 9,189 57,048 76,387 3.1a: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture sample census-2003 Mbeya Appendix II 143 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 0 95 196 98 0 0 0 Mbeya Rur 116 3,265 5,836 4,896 841 13,119 11,126 Kyela 0 203 513 141 88 181 450 Rungwe 539 571 4,140 4,136 803 4,379 1,714 Ileje 0 448 700 1,729 442 64 1,125 Mbozi 0 1,851 3,333 2,056 1,477 713 15,078 Mbarali 0 613 515 319 109 2,078 2,664 Mbeya Urb 0 317 238 98 260 432 425 Total 656 7,363 15,471 13,472 4,020 20,966 32,583 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mbeya Rur 0 3,740 2,136 2,624 364 3,232 2,240 Kyela 0 0 0 0 0 0 181 Rungwe 116 116 345 116 340 114 115 Ileje 0 61 124 252 1,192 0 188 Mbozi 0 178 533 355 769 356 1,515 Mbarali 0 0 0 0 106 103 105 Mbeya Urb 0 178 24 59 92 103 0 Total 116 4,273 3,161 3,405 2,862 3,909 4,345 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Chunya 0 101 0 0 0 0 0 Mbeya Rur 0 0 0 121 121 238 349 Kyela 0 0 87 0 0 89 0 Ileje 63 65 0 0 0 0 0 Mbozi 143 0 143 0 0 179 143 Mbarali 106 0 0 0 0 0 0 Mbeya Urb 0 24 0 0 22 45 0 Total 312 189 230 121 143 550 492 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census - 2003 Mbeya 144 Appendix II 145 HOUSEHOLDS DEMOGRAPHS: Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 146 Number % Number % Number % Less than 4 97,920 49 102,126 51 200,047 100 05 - 09 126,051 50 126,750 50 252,801 100 10 - 14 119,063 49 123,349 51 242,413 100 15 - 19 90,482 51 85,869 49 176,350 100 20 - 24 60,483 45 75,167 55 135,650 100 25 - 29 52,937 43 71,276 57 124,213 100 30 - 34 47,208 46 54,648 54 101,855 100 35 - 39 40,057 47 44,888 53 84,945 100 40 - 44 29,365 48 31,195 52 60,559 100 45 - 49 25,266 49 25,995 51 51,261 100 50 - 54 22,748 48 24,284 52 47,032 100 55 - 59 13,389 44 16,909 56 30,299 100 60 - 64 17,291 55 14,173 45 31,464 100 65 - 69 12,999 49 13,544 51 26,543 100 70 - 74 11,853 57 8,850 43 20,704 100 75 - 79 7,345 56 5,705 44 13,050 100 80 - 84 3,921 69 1,771 31 5,693 100 Above 85 1,724 44 2,179 56 3,903 100 Total 780,102 48 828,679 52 1,608,781 100 Number % Number % Number % Less than 4 97,920 13 102,126 12 200,047 12 05 - 09 126,051 16 126,750 15 252,801 16 10 - 14 119,063 15 123,349 15 242,413 15 15 - 19 90,482 12 85,869 10 176,350 11 20 - 24 60,483 8 75,167 9 135,650 8 25 - 29 52,937 7 71,276 9 124,213 8 30 - 34 47,208 6 54,648 7 101,855 6 35 - 39 40,057 5 44,888 5 84,945 5 40 - 44 29,365 4 31,195 4 60,559 4 45 - 49 25,266 3 25,995 3 51,261 3 50 - 54 22,748 3 24,284 3 47,032 3 55 - 59 13,389 2 16,909 2 30,299 2 60 - 64 17,291 2 14,173 2 31,464 2 65 - 69 12,999 2 13,544 2 26,543 2 70 - 74 11,853 2 8,850 1 20,704 1 75 - 79 7,345 1 5,705 1 13,050 1 80 - 84 3,921 1 1,771 0 5,693 0 Above 85 1,724 0 2,179 0 3,903 0 Total 780,102 100 828,679 100 1,608,781 100 Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year ( Col.%) Age Group Sex 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (Row %) Age Group Sex Male Female Total Male Female Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 147 Number % Number % Number % Chunya 80,893 50 81,531 50 162,424 100 Mbeya Rur 110,717 47 125,209 53 235,926 100 Kyela 69,099 49 73,215 51 142,314 100 Rungwe 126,663 47 145,099 53 271,763 100 Ileje 51,820 48 56,021 52 107,841 100 Mbozi 231,066 49 236,578 51 467,644 100 Mbarali 92,686 50 92,949 50 185,636 100 Mbeya Urb 17,158 49 18,077 51 35,234 100 Total 780,102 48 828,679 52 1,608,781 100 Number % Number % Number % Number % Number % Chunya 91,262 63 7,819 5 394 0 45,945 32 145,420 100 Mbeya Rur 127,482 63 13,100 6 121 0 62,002 31 202,704 100 Kyela 84,508 66 9,158 7 357 0 33,319 26 127,342 100 Rungwe 164,880 68 6,632 3 231 0 69,290 29 241,034 100 Ileje 63,616 67 4,590 5 130 0 26,143 28 94,479 100 Mbozi 247,297 61 22,025 5 178 0 136,830 34 406,330 100 Mbarali 88,647 55 4,905 3 99 0 67,204 42 160,854 100 Mbeya Urb 19,922 65 2,724 9 24 0 7,901 26 30,571 100 Total 887,614 63 70,954 5 1,533 0 448,634 32 1,408,735 100 Number % Number % Number % Number % Chunya 37,230 26 61,473 42 46,718 32 145,420 100 Mbeya Rur 69,903 34 78,631 39 54,170 27 202,704 100 Kyela 42,229 33 56,729 45 28,383 22 127,342 100 Rungwe 76,313 32 102,071 42 62,649 26 241,034 100 Ileje 31,180 33 42,452 45 20,847 22 94,479 100 Mbozi 124,287 31 177,283 44 104,761 26 406,330 100 Mbarali 38,398 24 64,895 40 57,561 36 160,854 100 Mbeya Urb 10,925 36 13,522 44 6,125 20 30,571 100 Total 430,465 31 597,055 42 381,215 27 1,408,735 100 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 148 Number % Number % Number % Number % % % Chunya 85,949 59 1,838 1 191 0 196 0 Mbeya Rur 108,364 53 1,909 1 0 0 242 0 Kyela 69,926 55 763 1 89 0 177 0 Rungwe 135,196 56 2,489 1 307 0 805 0 Ileje 51,830 55 253 0 0 0 0 0 Mbozi 217,974 54 2,595 1 178 0 528 0 Mbarali 96,283 60 1,652 1 0 0 0 0 Mbeya Urb 12,874 42 609 2 23 0 0 0 Total 778,397 55 12,109 1 787 0 1,949 0 Cont………. Number % Number % Number % Number % Number % Number % Chunya 1,198 1 1,411 1 1,817 1 534 0 101 0 1,020 1 Mbeya Rur 1,080 1 844 0 242 0 120 0 121 0 241 0 Kyela 610 0 810 1 1,945 2 414 0 254 0 1,336 1 Rungwe 643 0 487 0 3,212 1 412 0 230 0 1,678 1 Ileje 693 1 641 1 635 1 319 0 126 0 258 0 Mbozi 2,651 1 5,956 1 1,671 0 2,029 0 707 0 1,285 0 Mbarali 555 0 1,600 1 1,823 1 106 0 204 0 324 0 Mbeya Urb 348 1 786 3 385 1 261 1 130 0 157 1 Total 7,778 1 12,535 1 11,731 1 4,195 0 1,873 0 6,299 0 Cont………. Number % Number % Number % Number % Chunya 33,591 23 14,906 10 1,048 1 145,420 100 Mbeya Rur 67,757 33 18,821 9 1,197 1 202,704 100 Kyela 38,681 30 9,510 7 1,579 1 127,342 100 Rungwe 69,780 29 21,322 9 2,078 1 241,034 100 Ileje 27,695 29 9,688 10 947 1 94,479 100 Mbozi 120,665 30 43,451 11 1,241 0 406,330 100 Mbarali 35,971 22 19,679 12 1,402 1 160,854 100 Mbeya Urb 10,609 35 2,465 8 106 0 30,571 100 Total 404,749 29 139,843 10 9,599 1 1,408,735 100 Total HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Main Activity District Student / Too Old / Retired Other Not Working & Available Not Working & Unavailable Housemaker / Housewife Main Activity Main Activity District Self Employed (Non Farmimg) with Self Employed (Non Farmimg) without Unpaid Family Helper (Non Agriculture) 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Crop/Seaweed Livestock Keeping Livestock Fishing Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 149 Number % Number % Number % Number % Number % Chunya 86,844 60 8,505 6 26,010 18 24,062 17 145,420 100 Mbeya Rur 103,959 51 5,317 3 28,109 14 65,320 32 202,704 100 Kyela 68,618 54 4,223 3 28,001 22 26,500 21 127,342 100 Rungwe 121,504 50 9,292 4 47,504 20 62,733 26 241,034 100 Ileje 47,479 50 4,522 5 21,865 23 20,613 22 94,479 100 Mbozi 215,072 53 15,751 4 54,901 14 120,606 30 406,330 100 Mbarali 96,733 60 3,919 2 16,768 10 43,435 27 160,854 100 Mbeya Urb 12,832 42 1,626 5 9,077 30 7,037 23 30,571 100 Total 753,042 53 53,154 4 232,234 16 370,306 26 1,408,735 100 Number % Number % Number % Number % % % Chunya 0 0 621 1 1,344 2 1,896 3 Mbeya Rur 364 0 1,552 2 3,000 4 2,490 3 Kyela 280 0 419 1 1,298 2 2,342 4 Rungwe 695 1 348 0 2,621 3 2,306 2 Ileje 389 1 964 2 892 2 1,455 3 Mbozi 2,560 1 2,910 2 6,653 4 6,898 4 Mbarali 533 1 734 1 3,833 6 2,115 3 Mbeya Urb 13 0 0 0 100 1 290 2 Total 4,835 1 7,547 1 19,741 3 19,792 3 Number % Number % Number % Number % Number % Chunya 44,289 72 1,240 2 0 0 159 0 101 0 Mbeya Rur 57,477 73 363 0 116 0 0 0 241 0 Kyela 40,006 71 968 2 260 0 231 0 93 0 Rungwe 75,649 74 909 1 229 0 116 0 0 0 Ileje 33,141 78 194 0 181 0 65 0 189 0 Mbozi 128,404 72 1,013 1 355 0 529 0 522 0 Mbarali 41,826 64 645 1 410 1 0 0 106 0 Mbeya Urb 9,845 73 94 1 65 0 0 0 55 0 Total 430,637 72 5,426 1 1,617 0 1,099 0 1,307 0 Form Two Form Three Form Four Form Five Form Six Number % Number % Number % Number % Number % Chunya 719 1 192 0 1,134 2 0 0 0 0 Mbeya Rur 956 1 121 0 2,139 3 0 0 116 0 Kyela 661 1 257 0 1,392 2 0 0 37 0 Rungwe 116 0 338 0 1,732 2 113 0 152 0 Ileje 0 0 59 0 946 2 0 0 128 0 Mbozi 1,445 1 353 0 2,897 2 178 0 0 0 Mbarali 426 1 0 0 1,346 2 0 0 113 0 Mbeya Urb 116 1 21 0 966 7 0 0 185 1 Total 4,439 1 1,341 0 12,552 2 291 0 731 0 Cont…………..HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Cont…………..HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Pre Form One Form One District Standard Seven Standard Eight Training After Primary Education Standard Three 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level District Under Standard One Standard One Standard Two 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvemen District Involvement in Farming Works Full-time on FarmWorks Part-time on FarmRarely Works on FaNever Works on FarmTotal Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 150 Number % Number % Number % Number % Chunya 165 0 151 0 393 1 61,473 100 Mbeya Rur 0 0 0 0 1,784 2 78,631 100 Kyela 92 0 70 0 627 1 56,729 100 Rungwe 0 0 0 0 736 1 102,071 100 Ileje 63 0 0 0 387 1 42,452 100 Mbozi 358 0 178 0 1,184 1 177,283 100 Mbarali 212 0 0 0 544 1 64,895 100 Mbeya Urb 84 1 58 0 171 1 13,522 100 Total 973 0 458 0 5,826 1 597,055 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Chunya 11,067 25,363 0 1,097 165 76 494 38,262 Mbeya Rur 16,535 33,046 116 2,502 0 0 1,666 53,865 Kyela 10,567 21,423 168 1,332 92 70 539 34,192 Rungwe 25,560 39,715 0 1,587 0 0 461 67,323 Ileje 8,475 15,945 181 639 63 0 516 25,819 Mbozi 27,701 71,293 0 2,949 178 178 1,186 103,486 Mbarali 14,566 26,147 305 1,162 212 0 325 42,718 Mbeya Urb 1,924 4,433 23 534 44 70 152 7,180 Total 116,395 237,366 793 11,801 754 395 5,340 372,844 Mean Median Mode Mean Median Mode Mean Median Mode Chunya 41 38 30 48 45 45 43 40 30 Mbeya Rur 41 38 28 45 40 28 43 39 28 Kyela 46 41 30 56 60 65 49 45 30 Rungwe 46 42 40 54 56 65 48 46 40 Ileje 43 39 40 48 46 40 44 40 40 Mbozi 41 36 30 42 40 35 41 37 35 Mbarali 44 42 40 47 43 37 45 42 30 Mbeya Urb 42 40 35 47 48 50 43 41 35 Total 43 39 30 48 45 45 44 40 35 Number Percent Number Percent Number Percent Number Percent Chunya 17,730 54 11,918 36 3,193 10 32,841 100 Mbeya Rur 27,558 53 22,594 43 2,024 4 52,175 100 Kyela 13,427 62 6,948 32 1,404 6 21,779 100 Rungwe 16,193 58 9,555 34 2,409 9 28,157 100 Ileje 9,422 57 6,349 38 822 5 16,593 100 Mbozi 56,948 60 31,141 33 7,422 8 95,511 100 Mbarali 13,815 45 12,071 40 4,593 15 30,479 100 Mbeya Urb 3,823 59 2,089 32 621 10 6,533 100 Total 158,917 56 102,664 36 22,487 8 284,069 100 District Male Female Total Cont…………..HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District 2002/03 Agricultural Year 3.13 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm IncomTotal 3.11 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year 3.12 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District Total District District Training After SecondUniversity & Other TertAdult Education Maximum Education Level Attained Tanzania Agriculture Sample Census - 2003 Mbeya Appndix II 151 Male Female Total Male Female Total Male Female Total Chunya 25,037 4,055 29,092 5,328 3,842 9,170 30,365 7,897 38,262 Mbeya Rur 30,261 6,698 36,959 7,652 9,253 16,906 37,914 15,951 53,865 Kyela 20,452 3,463 23,915 4,631 5,646 10,277 25,083 9,109 34,192 Rungwe 36,758 5,175 41,933 11,623 13,767 25,390 48,381 18,942 67,323 Ileje 14,867 2,991 17,858 3,637 4,323 7,961 18,505 7,314 25,819 Mbozi 63,377 11,281 74,658 16,854 11,974 28,829 80,232 23,255 103,486 Mbarali 23,217 4,612 27,829 9,078 5,811 14,889 32,295 10,423 42,718 Mbeya Urb 4,754 478 5,232 1,085 863 1,948 5,839 1,341 7,180 Total 218,724 38,752 257,476 59,889 55,479 115,368 278,613 94,232 372,844 3.14 Literacy Rate of Heads of Households By District (Mbeya Region) District Literacy Know Don;t know Total Tanzania Agriculture Sample Census- 2003 Mbeya 152 Appendix II 153 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 154 Total Number of Households No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Chunya 1,590 4 30,461 80 1,934 5 3,599 9 1,577 4 101 0 2,608 7 38,262 Mbeya Rur 1,559 3 49,101 91 11,265 21 12,350 23 5,996 11 967 2 1,210 2 53,865 Kyela 1,732 5 28,161 82 8,616 25 7,955 23 2,857 8 162 0 751 2 34,192 Rungwe 810 1 61,310 91 12,990 19 5,049 7 4,888 7 232 0 5,367 8 67,323 Ileje 453 2 24,232 94 3,769 15 2,306 9 2,991 12 319 1 1,406 5 25,819 Mbozi 5,830 6 89,938 87 19,442 19 12,217 12 8,344 8 711 1 4,082 4 103,486 Mbarali 6,966 16 27,412 64 6,461 15 12,796 30 4,008 9 532 1 1,429 3 42,718 Mbeya Urb 272 4 6,180 86 1,374 19 1,739 24 499 7 145 2 341 5 7,180 Total 19,212 5 316,795 85 65,852 18 58,012 16 31,159 8 3,169 1 17,194 5 372,844 Total Chunya 105,890 Mbeya Rur 90,893 Kyela 47,090 Rungwe 86,975 Ileje 45,620 Mbozi 199,316 Mbarali 89,545 Mbeya Urb 6,811 Total 672,142 2,448 680 277 3,036 600 7,195 2,292 119 26,330 252 644 390 53 41,861 1,560 2,246 1,226 1,274 1,357 4,901 3,155 151 15,870 4,735 484,963 5,030 6,479 4,504 3,185 1,299 8,879 11,742 744 16,671 189 36,383 74,658 69,186 33,685 67,637 39,800 149,081 46,182 750 Area Shared Croped From Others Area Owned Under Customary Law Area under Other Forms of Tenure 6,370 595 12,129 392 51 70 Households with Area Shared Croped 8,126 District Area Rented From Others Area Borrowed From Others Land Access/ Ownership (Hectare) Area Leased/Certificat e of Ownership 3,018 795 465 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Households with Area under Other Forms of Tenure District 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year Land Access Leased/Certificat e of Ownership Owned Under Customary Law Bought Rented Borrowed Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 155 LAND USE Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 156 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households with Rented to Others Households with Unusable Households with Uncultivated Usable Land Total Number of Households Chunya 31,747 16,053 386 400 589 683 4,717 2,671 203 1,111 4,034 5,967 38261.7061 Mbeya Rur 49,920 12,528 10,663 3,932 3,963 706 9,227 602 13,117 1,563 1,453 3,475 53864.8142 Kyela 33,012 3,950 7,213 15,709 176 88 2,198 85 257 758 462 2,582 34191.7565 \\ Rungwe 48,071 33,439 18,179 33,219 12,410 1,497 5,051 230 11,390 1,142 1,032 3,441 67323.1632 Ileje 22,977 17,672 4,944 7,967 6,495 515 3,720 195 7,002 1,027 1,929 3,010 25818.7746 Mbozi 97,171 8,446 41,247 11,506 5,511 1,592 9,561 2,110 11,299 1,590 2,756 7,952 103486.477 Mbarali 40,240 5,350 1,027 598 1,165 105 3,644 0 595 2,194 522 7,489 42717.5595 Mbeya Urb 5,557 3,100 284 458 1,591 89 258 13 2,081 143 114 347 7180.04434 Total 328,695 100,539 83,942 73,790 31,899 5,276 38,376 5,906 45,944 9,527 12,303 34,263 372844.296 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Chunya 53,198 19,426 59 203 1,007 1,682 8,943 4,667 62 1,844 5,413 9,387 105,890 Mbeya Rur 56,728 8,430 4,610 2,032 3,835 321 7,286 176 3,016 1,364 502 2,592 90,893 Kyela 29,812 1,675 3,042 7,633 174 71 1,697 17 60 606 324 1,979 47,090 Rungwe 29,312 17,259 6,912 17,614 6,246 849 2,368 167 4,013 351 466 1,419 86,975 Ileje 18,693 10,350 1,277 3,991 2,519 371 2,103 39 2,470 506 1,413 1,888 45,620 Mbozi 128,678 7,285 24,296 8,701 2,987 2,836 6,682 6,559 2,795 1,097 1,410 5,990 199,316 Mbarali 62,849 5,437 314 142 694 212 3,514 . 251 2,920 290 13,006 89,630 Mbeya Urb 3,337 1,473 102 159 650 30 130 3 411 226 36 255 6,811 Total 382,607 71,336 40,612 40,475 18,111 6,372 32,723 11,629 13,078 8,915 9,854 36,515 672,227 % 57 11 6 6 3 1 5 2 2 1 1 5 100 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Land Use District Land Use 5.2 LAND USE:Area of Land (Ha) By Type of Land Use and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 157 District District Number % Number % Number % Number % Number % Number % Chunya 26,198 69 11,970 31 38,168 100 Chunya 29,134 76 9,035 24 38,168 100 Mbeya Rur 42,132 78 11,612 22 53,743 100 Mbeya Rur 17,435 32 36,308 68 53,743 100 Kyela 28,696 85 5,192 15 33,889 100 Kyela 14,189 42 19,699 58 33,889 100 Rungwe 59,149 88 8,034 12 67,183 100 Rungwe 42,363 63 24,820 37 67,183 100 Ileje 17,498 68 8,256 32 25,754 100 Ileje 15,752 61 10,002 39 25,754 100 Mbozi 80,977 78 22,193 22 103,170 100 Mbozi 58,206 56 44,963 44 103,170 100 Mbarali 28,691 67 13,928 33 42,619 100 Mbarali 22,609 53 20,010 47 42,619 100 Mbeya Urb 6,286 88 838 12 7,124 100 Mbeya Urb 2,034 29 5,090 71 7,124 100 Total 289,627 78 82,023 22 371,650 100 Total 201,722 54 169,927 46 371,650 100 Number % Number % Number % Chunya 4,528 12 33,640 88 38,168 100 Mbeya Rur 19,231 36 34,513 64 53,743 100 Kyela 5,634 17 28,254 83 33,889 100 Rungwe 14,339 21 52,844 79 67,183 100 Ileje 3,882 15 21,872 85 25,754 100 Mbozi 19,935 19 83,235 81 103,170 100 Mbarali 8,711 20 33,908 80 42,619 100 Mbeya Urb 1,957 27 5,167 73 7,124 100 Total 78,216 21 293,433 79 371,650 100 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year Do you Consider that you have sufficient land for the Hh? Yes No Total 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Mbeya 158 Appendix II 159 WET & DRY SEASONS TOTAL ANNUAL CROPS & VEGETABLE PRODUCTION - Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 160 Number of Household Planted Area (hectare) Number of Household Planted Area (hectare) Total area planted (hectare) Chunya 0 0 38,168 71,788 71,788 0 Mbeya Rural 14,441 10,454 49,572 56,801 67,256 16 Kyela 0 0 33,449 30,792 30,792 0 Rungwe 41,014 27,034 44,374 25,431 52,466 52 Ileje 5,288 4,113 25,499 26,451 30,564 13 Mbozi' 0 0 102,992 138,870 138,870 0 Mbarali 0 0 42,520 62,299 62,299 0 Mbeya Urban 44 39 7,112 5,153 5,191 1 Total 60,786 41,640 343,685 417,585 459,226 9 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Chunya 0 38,262 38,168 94 38,262 Mbeya Rural 14,441 39,424 49,572 4,293 53,865 Kyela 0 34,192 33,449 742 34,192 Rungwe 41,014 26,310 44,374 22,950 67,323 Ileje 5,288 20,531 25,499 320 25,819 Mbozi' 0 103,486 102,992 495 103,486 Mbarali 0 42,718 42,520 197 42,718 Mbeya Urban 44 7,136 7,112 68 7,180 Total 60,786 312,058 343,685 29,159 372,844 District 7.1 & 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District-LONG RAINY SEASON Dry Season Wet Season Total Number of Crop Growing Households 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District Dry Season Wet Season % Area planted in dry rainy season District Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 161 Planted area (ha) Quantity Harvested (tons) Yield (Kg/ha) Planted area (ha) Quantity Harvested (tons) Yield (Kg/ha) Planted area (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 29,417 41,305 1,404 202,326 244,907 1,210 231,743 286,213 1,235 Paddy 0 0 0 54,743 62,780 1,147 54,743 62,780 1,147 Sorghum 0 0 0 25,953 21,214 817 25,953 21,214 817 Bulrush Millet 0 0 0 2,162 1,183 547 2,162 1,183 547 Finger Millet 200 107 535 9,828 6,940 706 10,028 7,047 703 Wheat 0 0 0 4,289 4,436 1,034 4,289 4,436 1,034 Barley 23 91 3,952 0 0 0 23 91 3,952 CEREALS 29,640 41,504 1,400 299,301 341,460 1,141 328,941 382,964 1,164 Cassava 665 1,115 1,675 12,832 18,389 1,433 13,498 19,504 1,445 Sweet Potatoes 686 644 938 4,180 5,959 1,425 4,867 6,603 1,357 Irish Potatoes 2,423 8,284 3,419 5,292 15,170 2,867 7,715 23,454 3,040 Yams 23 97 4,150 186 422 2,270 209 520 2,481 Cocoyam 427 1,248 2,923 425 1,261 2,967 852 2,509 2,945 ROOTS & TUBERS 4,225 11,388 2,695 22,916 41,201 1,798 27,141 52,589 1,938 Mung Beans 0 0 0 . . 0 0 0 0 Beans 5,955 3,137 527 56,637 26,477 467 62,593 29,615 473 Cowpeas 18 6 321 290 85 293 309 91 295 Green Gram 0 0 0 . . 0 0 0 0 Pigeon Peas 0 0 0 . . 0 0 0 0 Chich Peas 0 0 0 5 1 148 5 1 148 Bambaranuts 9 20 2,199 584 322 551 593 342 577 Field Peas 178 312 1,756 1,367 449 329 1,544 761 493 PULSES 6,161 3,476 564 58,882 27,334 464 65,043 30,809 474 Sunflower 33 27 816 3,781 1,783 471 3,814 1,809 474 Simsim 0 0 0 5,194 2,051 395 5,194 2,051 395 Groundnuts 981 381 388 20,073 10,343 515 21,054 10,724 509 Soya Beans 0 0 0 79 35 438 79 35 438 Castor Seed 0 0 0 . . 0 0 0 0 OIL SEEDS & OIL NUT 1,013 407 402 29,127 14,212 488 30,141 14,619 485 Okra 0 0 0 . . 0 0 0 0 Radish 0 0 0 795 318 400 795 318 400 Turmeric 0 0 0 . . 0 0 0 0 Bitter Aubergine 0 0 0 6 62 11,066 6 62 11,066 Garlic 0 0 0 . . 0 0 0 0 Onions 10 93 9,410 686 3,694 5,389 695 3,787 5,446 Ginger . . 0 . . 0 0 0 0 Cabbage 150 402 2,684 169 1,329 7,888 318 1,731 5,439 Tomatoes 134 579 4,316 1,084 5,734 5,289 1,218 6,312 5,182 Spinnach 51 10 186 85 216 2,525 137 225 1,650 Carrot 0 0 0 10 47 4,885 10 47 4,885 Chillies 0 0 0 4 25 7,127 4 25 7,127 Amaranths 131 67 513 289 371 1,284 420 438 1,043 Pumpkins 47 16 352 318 645 2,029 365 661 1,814 Cucumber 0 0 0 0 1 3,952 0 1 3,952 Egg Plant 5 1 247 11 1 79 15 2 131 Water Mellon 0 0 0 . . 0 0 0 0 Cauliflower 0 0 0 . . 0 0 0 0 FRUITS & VEGETABL 528 1,168 2,214 3,454 12,442 3,602 3,982 13,610 3,418 Seaweed 0 0 0 . 0 0 0 0 0 Cotton 0 0 0 . 0 0 0 0 0 Tobacco 0 0 0 3,733 3,606 966 3,733 3,606 966 Pyrethrum 73 89 1,210 172 156 906 245 245 997 Jute . . 0 . 0 0 0 0 0 CASH CROPS 73 89 1,210 3,906 3,762 963 3,979 3,850 968 Total 41,640 417,585 0 459,226 0 0 Total 7.1& 7.2c: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (Ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year, Mbeya Region Crop Wet Season Dry Season Tanzania Agriculture Sample Census- 2003 Mbeya ppendix II 162 Number of Households Planted area (ha) Number of Households Planted area (ha) Maize 58,263 29,417 283,942 202,326 231,743 12.7 Paddy 0 0 80,091 54,743 54,743 0.0 Sorghum 0 0 28,156 25,953 25,953 0.0 Bulrush Millet 0 0 2,142 2,162 2,162 0.0 Finger Millet 1,272 200 30,364 9,828 10,028 2.0 Wheat 0 0 11,471 4,289 4,289 0.0 Barley 114 23 0 0 23 100.0 CEREALS 59,649 29,640 436,166 299,301 328,941 9.0 Cassava 3,187 665 38,067 12,832 13,498 4.9 Sweet Potatoes 3,188 686 17,030 4,180 4,867 14.1 Irish Potatoes 7,619 2,423 13,780 5,292 7,715 31.4 Yams 116 23 1,128 186 209 11.2 Cocoyam 2,647 427 3,447 425 852 50.1 ROOTS & TUBERS 16,756 4,225 73,453 22,916 27,141 15.6 Mung Beans 0 . 0 0 0 0.0 Beans 25,710 5,955 172,711 56,637 62,593 9.5 Cowpeas 245 18 1,147 290 309 6.0 Green Gram 0 0 0 0 0 0.0 Pigeon Peas 0 0 0 0 0 0.0 Chich Peas 0 0 23 5 5 0.0 Bambaranuts 245 9 3,742 584 593 1.5 Field Peas 579 178 5,077 1,367 1,544 11.5 PULSES 26,779 6,161 182,700 58,882 65,043 9.5 Sunflower 296 33 10,545 3,781 3,814 0.9 Simsim 0 0 7,719 5,194 5,194 0.0 Groundnuts 5,497 981 77,149 20,073 21,054 4.7 Soya Beans 0 0 464 79 79 0.0 Castor Seed 0 0 0 . 0 0.0 OIL SEEDS & OIL NUTS 5,793 1,013 95,876 29,127 30,141 3.4 Okra 0 0 0 . 0 0.0 Radish 0 0 98 795 795 0.0 Turmeric 0 0 0 0 0 0.0 Bitter Aubergine 0 0 37 6 6 0.0 Garlic 0 0 0 0 0 0.0 Onions 116 10 3,288 686 695 1.4 Ginger 0 . 0 0 0 0.0 Cabbage 929 150 2,145 169 318 47.1 Tomatoes 985 134 5,167 1,084 1,218 11.0 Spinnach 247 51 662 85 137 37.4 Carrot 0 0 105 10 10 0.0 Chillies 0 0 48 4 4 0.0 Amaranths 725 131 2,021 289 420 31.3 Pumpkins 320 47 1,534 318 365 12.8 Cucumber 0 0 9 0 0 0.0 Egg Plant 116 5 104 11 15 30.8 Water Mellon 0 0 0 0 0 0.0 Cauliflower 0 0 0 0 0 0.0 FRUITS & VEGETABLES 3,437 528 15,218 3,454 3,982 13.3 Seaweed 0 0 0 0 0 0.0 Cotton 0 0 0 0 0 0.0 Tobacco 0 0 4,118 3,733 3,733 0.0 Pyrethrum 362 73 607 172 245 29.9 Jute 0 0 0 0 0 0.0 CASH CROPS 362 73 4,725 3,906 3,979 1.8 Total 41,640 417,585 459,226 9.1 7.1 & 7.2d. TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agricultural Households by Area Planted (Ha) and Crop for the Agricultural Year 2002/03 Dry & Wet Season Mbeya Region Wet Season Crop Total Area Planted Dry & Wet Seasons % of Area Planted in Dry Season Dry Season TanzaaniaAgriculture Sample Census- 2003 Mbeya Apendix II 163 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Chunya 475 923 21,871 28,359 59,336 42,487 81,681 71,768 Mbeya Rural 121 12 12,698 8,542 100,422 48,056 113,241 56,610 Kyela 1,007 1,472 34,386 21,703 23,403 7,567 58,797 30,742 Rungwe 807 177 10,840 2,876 77,592 22,175 89,239 25,227 Ileje 254 95 2,234 604 82,050 25,422 84,538 26,122 Mbozi 3,366 1,432 94,422 59,973 172,315 73,229 270,103 134,633 Mbarali 4,472 5,133 37,307 34,862 40,620 22,177 82,399 62,172 Mbeya Urban 244 34 1,837 966 13,401 4,153 15,481 5,153 Total 10,745 9,278 215,595 157,885 569,139 245,266 795,479 412,429 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agricultural Households and Planted Area by Means of Soil Preparation and District Dry and Wet Seasons- Mbeya Region Soil Preparation District Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Mbeya 164 Appendix II 165 ANNUAL CROP & VEGETABLE PRODUCTION- DRY SEASON Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 166 Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning No Land Clearing Other Total Planted Area Planted Area Planted Area Planted Area Planted Area Planted Area Planted Area Mbeya Rural 24 6,730 74 49 3,528 49 10,454 Rungwe 249 26,488 23 . 249 . 27,009 Ileje . 4,091 . . . . 4,091 Mbeya Urban . 28 11 . . . 39 Total 273 37,337 108 49 3,777 49 41,592 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Planted Area Planted Area Planted Area Planted Area Planted Area Mbeya Rural 1,169 551 2,546 6,188 10,454 Rungwe 9,399 964 4,124 12,547 27,034 Ileje 2,037 346 628 1,103 4,113 Mbeya Urban 2 9 8 19 39 Total 12,607 1,871 7,307 19,856 41,640 Households Using Irrigation Households Not Using Irrigation Total Planted Area Planted Area Planted Area Mbeya Rural 1,599 8,856 10,454 Rungwe 659 26,375 27,034 Ileje 962 3,151 4,113 Mbeya Urban 9 29 39 Total 3,229 38,411 41,640 7.1 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area (ha) By Means Used for Land Clearing and District During 2002/03 Crop Year-SHORT RAINY SEASON District 7.3 ANNUAL CROP AND VEGETABLE PRODUCTION: Plante District Irrigation Use 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON District Fertilizer Use Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 167 Households Using Herbicide Households Not Using Herbicide Total Planted Area Planted Area Planted Area Mbeya Rural 86 10,368 10,454 Rungwe 147 26,888 27,034 Ileje 33 4,080 4,113 Mbeya Urban . 39 39 Total 265 41,375 41,640 Households Using Fungicide Households Not Using Fungicide Total Planted Area Planted Area Planted Area Mbeya Rural 208 10,246 10,454 Rungwe 833 26,201 27,034 Ileje 179 3,934 4,113 Mbeya Urban 19 20 39 Total 1,239 40,401 41,640 Households Using Improved Seed Households Not Using Improved Seed Total Planted Area Planted Area Planted Area Mbeya Rural 1,062 9,392 10,454 Rungwe 6,430 20,604 27,034 Ileje 767 3,346 4,113 Mbeya Urban 8 30 39 Total 8,268 33,372 41,640 7.4 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Herbicide Use 7.5 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use 7.6 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY District Improved Seed Use Tanzania Agriculture Sample Census -2003 Mbeya 168 Appendix II 169 ANNUAL CROP & VEGETABLE PRODUCTION - WET SEASON Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 170 Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Planted Area Planted Area Planted Area Planted Area Chunya 923 28,359 42,487 71,768 Mbeya Rural 12 8,542 48,056 56,610 Kyela 1,472 21,703 7,567 30,742 Rungwe 177 2,876 22,175 25,227 Ileje 95 604 25,422 26,122 Mbozi' 1,432 59,973 73,229 134,633 Mbarali 5,133 34,862 22,177 62,172 Mbeya Urban 34 966 4,153 5,153 Total 9,278 157,885 245,266 412,429 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Planted Area Planted Area Planted Area Planted Area Chunya 4,555 1,744 9,736 55,754 71,788 Mbeya Rur 7,475 4,410 15,819 29,098 56,801 Kyela 1,073 2,559 1,561 25,599 30,792 Rungwe 5,211 1,740 1,087 17,393 25,431 Ileje 5,632 2,612 5,041 13,165 26,451 Mbozi 13,605 8,297 37,408 79,561 138,870 Mbarali 4,784 345 3,248 53,921 62,299 Mbeya Urb 992 176 2,694 1,291 5,153 Total 43,326 21,882 76,594 275,783 417,585 Households Using Irrigation Households Not Using Irrigation Total Planted Area Planted Area Planted Area Chunya 2,506 69,282 71,788 Mbeya Rur 1,778 55,023 56,801 Kyela 370 30,422 30,792 Rungwe 1,534 23,897 25,431 Ileje 1,293 25,158 26,451 Mbozi 14,092 124,778 138,870 Mbarali 21,154 41,145 62,299 Mbeya Urb 285 4,867 5,153 Total 43,012 374,573 417,585 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON District Soil Preparation 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON Total District 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON District Irrigation Use Fertilizer Use Tanzania Agriculture Sample Census - 2003 Mbeya Households Using Herbicide Households Not Using Herbicide Total Planted Area Planted Area Planted Area Chunya 1,601 70,188 71,788 Mbeya Rur 861 55,940 56,801 Kyela 9,849 20,943 30,792 Rungwe 536 24,895 25,431 Ileje 480 25,971 26,451 Mbozi 9,890 128,980 138,870 Mbarali 2,694 59,605 62,299 Mbeya Urb 129 5,024 5,153 Total 26,039 391,546 417,585 Households Using Pesticide Households Not Using Pesticide Total Planted Area Planted Area Planted Area Chunya 5,556 66,232 71,788 Mbeya Rur 13,730 43,072 56,801 Kyela 18 30,774 30,792 Rungwe 713 24,718 25,431 Ileje 2,705 23,746 26,451 Mbozi 19,576 119,294 138,870 Mbarali 1,766 60,532 62,299 Mbeya Urb 2,257 2,896 5,153 Total 46,322 371,263 417,585 Total of Households Number % Number % Number Chunya 16,475 43 21,786 57 38,262 Mbeya Rural 45,557 85 8,308 15 53,865 Kyela 29,091 85 5,101 15 34,192 Rungwe 60,729 90 6,594 10 67,323 Ileje 21,649 84 4,170 16 25,819 Mbozi' 91,048 88 12,439 12 103,486 Mbarali 22,433 53 20,285 47 42,718 Mbeya Urban 5,498 77 1,682 23 7,180 Total 292,480 78 80,364 22 372,844 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Pesticide Use Households that Sold Produce Households that Did not Sell Produce District 7.1.2j: MARETING: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District, 2002/03 Agricultural Year Appendix II 172 Households Using Pesticide Households Not Using Pesticide Total Planted Area Planted Area Planted Area Chunya 5,556 66,232 71,788 Mbeya Rur 13,730 43,072 56,801 Kyela 18 30,774 30,792 Rungwe 713 24,718 25,431 Ileje 2,705 23,746 26,451 Mbozi 19,576 119,294 138,870 Mbarali 1,766 60,532 62,299 Mbeya Urb 2,257 2,896 5,153 Total 46,322 371,263 417,585 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Pesticide Use Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 173 No. of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Maize 13,443 10,848 243,387 173,350 947 571 18,719 13,537 6,570 3,649 24 7 283,089 201,963 Paddy 4,567 3,105 64,646 40,936 291 219 4,886 6,003 4,532 3,802 0 . 78,922 54,064 Sorghum 2,598 1,862 23,099 21,895 0 . 2,099 1,834 358 363 0 . 28,156 25,953 Bulrush Millet 0 . 1,789 1,984 0 . 353 178 0 . 0 . 2,142 2,162 Finger Millet 2,082 617 25,809 8,567 121 37 1,922 538 350 54 0 . 30,283 9,812 Wheat 266 128 10,108 3,910 121 37 304 106 672 108 0 . 11,471 4,289 Barley 0 . 0 . 0 . 0 . 0 . 0 . 0 . CEREALS 16,560 250,641 863 22,196 7,976 7 298,243 Cassava 1,789 492 22,353 6,830 85 34 795 106 385 213 0 . 25,407 7,676 Sweet Potatoes 732 266 14,560 3,310 0 . 1,152 441 587 163 0 . 17,030 4,180 Irish Potatoes 0 . 12,753 4,966 121 12 513 119 393 195 0 . 13,780 5,292 Yams 116 2 885 164 62 13 65 7 0 . 0 . 1,128 186 Cocoyam 65 7 3,267 414 0 . 0 . 116 5 0 . 3,447 425 ROOTS & TUBERS 767 15,684 59 673 576 . 17,759 Mung Beans 0 . 0 . 0 . 0 . 0 . 0 . 0 . Beans 5,213 1,946 149,901 49,236 666 160 10,271 3,886 6,040 1,242 0 . 172,091 56,469 Cowpeas 111 11 1,036 279 0 . 0 . 0 . 0 . 1,147 290 Green Gram 0 . 0 . 0 . 0 . 0 . 0 . 0 . Pigeon Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chich Peas 0 . 23 5 0 . 0 . 0 . 0 . 23 5 Bambaranuts 82 8 3,217 528 0 . 212 24 115 12 0 . 3,626 572 Field Peas 178 18 4,494 1,329 0 . 24 2 381 17 0 . 5,077 1,367 PULSES 5,584 1,984 158,671 51,377 666 160 10,507 3,912 6,536 1,271 0 . 181,964 58,702 Sunflower 111 5 9,308 3,514 233 58 713 187 179 18 0 . 10,545 3,781 Simsim 986 292 6,024 4,651 0 . 708 251 0 . 0 . 7,719 5,194 Groundnuts 4,640 1,334 64,345 16,810 0 . 5,930 1,596 1,910 288 0 . 76,825 20,028 Soya Beans 0 . 334 61 0 . 130 18 0 . 0 . 464 79 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . 0 . OIL SEEDS & OIL NUTS 1,630 25,037 58 2,052 306 . 29,082 Okra 0 . 0 . 0 . 0 . 0 . 0 . 0 . Radish 0 . 98 795 0 . 0 . 0 . 0 . 98 795 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 37 6 0 . 0 . 0 . 0 . 37 6 Garlic 0 . 0 . 0 . 0 . 0 . 0 . 0 . Onions 121 37 3,045 636 121 12 0 . 0 . 0 . 3,288 686 Ginger 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cabbage 0 . 2,145 169 0 . 0 . 0 . 0 . 2,145 169 Tomatoes 127 36 4,912 1,036 0 . 128 11 0 . 0 . 5,167 1,084 Spinnach 0 . 662 85 0 . 0 . 0 . 0 . 662 85 Carrot 0 . 105 10 0 . 0 . 0 . 0 . 105 10 Chillies 0 . 48 4 0 . 0 . 0 . 0 . 48 4 Amaranths 0 . 2,021 289 0 . 0 . 0 . 0 . 2,021 289 Pumpkins 0 . 1,534 318 0 . 0 . 0 . 0 . 1,534 318 Cucumber 0 . 9 0 0 . 0 . 0 . 0 . 9 0 Egg Plant 0 . 0 . 0 . 0 . 0 . 0 . 0 . Water Mellon 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 73 3,347 12 11 . . 3,444 Seaweed 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cotton 0 . 0 . 0 . 0 . 0 . 0 . 0 . Tobacco 546 433 3,228 3,030 183 172 81 33 0 . 0 . 4,037 3,668 Pyrethrum 0 . 607 172 0 . 0 . 0 . 0 . 607 172 Jute 0 . 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 546 433 3,835 3,202 183 172 81 33 0 . 0 . 4,644 3,840 Total 37,774 21,446 679,789 349,287 2,953 1,325 49,003 28,877 22,588 10,129 24 7 792,131 411,071 % 5 85 0 7 3.0 0 100 7.2g ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop Crop Land Clearing Methods Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning No Land Clearing Other Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 174 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 36,660 40,508 34,886 0.861 36,660 40,508 34,886 0.861 Mbeya Rur 12,882 7,588 12,389 1,633 40,612 29,841 37,754 1.265 53,493 37,429 50,143 1.340 Kyela 0 0 0 0 17,042 7,036 6,888 0.979 17,042 7,036 6,888 0.979 Rungwe 40,554 19,351 25,672 1,327 23,853 9,631 11,432 1.187 64,407 28,982 37,103 1.280 Ileje 4,784 2,460 3,235 1,315 22,538 12,091 14,533 1.202 27,322 14,551 17,768 1.221 Mbozi 0 0 0 0 98,069 67,736 114,794 1.695 98,069 67,736 114,794 1.695 Mbarali 0 0 0 0 38,146 32,101 17,928 0.558 38,146 32,101 17,928 0.558 Mbeya Urb 44 18 10 577 7,022 3,382 6,692 1.979 7,066 3,400 6,702 1.971 Total 58,263 29,417 41,305 1,404 283,942 202,326 244,907 1.210 342,205 231,743 286,213 1.235 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 2,386 1,853 1,365 0.737 2,386 1,853 1,365 0.737 Mbeya Rur 0 0 0 0 351 72 64 0.890 351 72 64 0.890 Kyela 0 0 0 0 31,343 20,811 19,814 0.952 31,343 20,811 19,814 0.952 Rungwe 0 0 0 0 9,517 3,364 3,484 1.036 9,517 3,364 3,484 1.036 Ileje 0 0 0 0 2,749 731 539 0.737 2,749 731 539 0.737 Mbozi 0 0 0 0 9,210 6,346 4,069 0.641 9,210 6,346 4,069 0.641 Mbarali 0 0 0 0 24,504 21,546 33,430 1.552 24,504 21,546 33,430 1.552 Mbeya Urb 0 0 0 0 31 21 14 0.680 31 21 14 0.680 Total 0 0 0 0 80,091 54,743 62,780 1.147 80,091 54,743 62,780 1.147 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 8,900 11,313 8,672 0.767 8,900 11,313 8,672 0.767 Mbeya Rur 0 0 0 0 1,659 1,530 616 0.403 1,659 1,530 616 0.403 Kyela 0 0 0 0 257 69 148 2.130 257 69 148 2.130 Rungwe 0 0 0 0 0 0 0 0 0 0 0 0.000 Ileje 0 0 0 0 389 46 32 0.697 389 46 32 0.697 Mbozi 0 0 0 0 14,717 10,943 10,732 0.981 14,717 10,943 10,732 0.981 Mbarali 0 0 0 0 2,214 2,042 1,012 0.496 2,214 2,042 1,012 0.496 Mbeya Urb 0 0 0 0 18 11 2 0.165 18 11 2 0.165 Total 0 0 0 0 28,156 25,953 21,214 0.817 28,156 25,953 21,214 0.817 District Paddy Dry Season Wet Season Total 7.2.2 Number of Agricultural Households, Area Planted (Ha) and Quantity of Paddy Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year Total District 7.2.1 Number of Agricultural Households, Area Planted (Ha) and Quantity of Maize Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year Maize Dry Season Wet Season 7.2.3 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sorghum Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Sorghum Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 175 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 2,178 788 300 0.381 2,178 788 300 0.381 Mbeya Rur 1,091 141 90 1 6,321 1,895 816 0.431 7,412 2,037 906 0.445 Kyela 0 0 0 0 86 17 0 0.000 86 17 0 0.000 Rungwe 116 6 9 2 1,619 303 137 0 1,735 309 147 0.475 Ileje 65 53 8 0 4,966 1,903 1,492 0.784 5,031 1,955 1,500 0.767 Mbozi 0 0 0 0 14,757 4,793 4,187 0.874 14,757 4,793 4,187 0.874 Mbarali 0 0 0 0 333 112 1 0.012 333 112 1 0.012 Mbeya Urb 0 0 0 0 104 17 6 0.334 104 17 6 0.334 Total 0 0 0 0 30,364 9,828 6,940 0.706 30,364 9,828 6,940 0.706 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 0 0 0 0 0 0 0 0.000 Mbeya Rur 0 0 0 0 9,674 3,657 3,997 1.093 9,674 3,657 3,997 1.093 Kyela 0 0 0 0 0 0 0 0.000 0 0 0 0.000 Rungwe 0 0 0 0 0 0 0 0.000 0 0 0 0.000 Ileje 0 0 0 0 971 426 149 0 971 426 149 0.351 Mbozi 0 0 0 0 0 0 0 0.000 0 0 0 0.000 Mbarali 0 0 0 0 0 0 0 0.000 0 0 0 0.000 Mbeya Urb 0 0 0 0 825 205 289 1.410 825 205 289 1.410 Total 0 0 0 0 11,471 4,289 4,436 1.034 11,471 4,289 4,436 1.034 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0 2,390 729 278 0 2,390 729 278 0.381 Mbeya Rur 116 47 150 3 947 312 147 0.473 1,062 359 298 0.831 Kyela 0 0 0 0 4,013 1,416 4,382 3.094 4,013 1,416 4,382 3.094 Rungwe 1,970 284 781 3 8,061 2,520 8,228 3.265 10,031 2,804 9,009 3.213 Ileje 1,101 335 183 1 7,813 1,883 2,453 1 8,914 2,218 2,636 1.188 Mbozi 0 0 0 0 13,697 5,630 2,492 0.443 13,697 5,630 2,492 0.443 Mbarali 0 0 0 0 1,113 333 406 1.219 1,113 333 406 1.219 Mbeya Urb 0 0 0 0 33 9 4 0.389 33 9 4 0.389 Total 3,187 665 1,115 0 38,067 12,832 18,389 1.433 41,254 13,498 19,504 1.445 Dry Season Wet Season Total 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity of Wheat Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Wheat 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity ofCassava Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Cassava Dry Season Wet Season Total 7.2.4 Number of Agricultural Households, Area Planted (Ha) and Quantity of Finger Millet Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Finger Millet Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 176 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 1,143 448 377 0.841 1,143 448 377 0.841 Mbeya Rur 237 61 70 1.148 808 298 293 0.983 1,046 359 362 1.011 Kyela 0 0 0 0.000 1,256 373 519 1.393 1,256 373 519 1.393 Rungwe 2,305 491 446 0.908 1,840 203 273 1.346 4,145 693 718 1.036 Ileje 646 135 128 0.955 7,777 1,358 2,380 1.753 8,423 1,492 2,508 1.681 Mbozi 0 0 0 0.000 2,252 604 859 1.424 2,252 604 859 1.424 Mbarali 0 0 0 0.000 1,944 898 1,258 1.401 1,944 898 1,258 1.401 Mbeya Urb 0 0 0 0.000 9 1 1 1.482 9 1 1 1.482 Total 3,188 686 644 0.000 17,030 4,180 5,959 1.425 20,218 4,867 6,603 1.357 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Rur 2,657 714 2,479 3.474 8,551 3,511 9,329 2.657 11,208 4,225 11,809 2.795 Kyela 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Rungwe 4,939 1,691 5,647 3.340 913 323 1,155 3.575 5,851 2,014 6,801 3.378 Ileje 0 0 0 0.000 646 279 290 1.041 646 279 290 1.041 Mbozi 0 0 0 0.000 2,235 740 2,447 3.308 2,235 740 2,447 3.308 Mbarali 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Urb 23 19 158 8.472 1,436 439 1,948 4.438 1,460 458 2,106 4.602 Total 7,619 2,423 8,284 3.419 13,780 5,292 15,170 2.867 21,399 7,715 23,454 3.040 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Rur 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Kyela 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Rungwe 116 23 97 4.150 231 40 31 0.786 347 63 129 2.035 Ileje 0 0 0 0.000 897 146 391 2.674 897 146 391 2.674 Mbozi 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbarali 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Urb 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Total 116 23 97 0.000 1,128 186 422 2.270 1,244 209 520 2.481 7.2.7 Number of Agricultural Households, Area Planted (Ha) and Quantity of IYams Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Yams Dry Season Wet Season Total 7.2.6 Number of Agricultural Households, Area Planted (Ha) and Quantity of Irish Potatoes Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Irish Potatoes Dry Season Wet Season Total 7.2.5 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sweet Potatoes Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Sweet Potatoes Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 177 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Rur 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Kyela 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Rungwe 1,937 321 950 2.963 1,839 218 506 2.318 3,776 539 1,456 2.701 Ileje 710 106 298 2.801 1,608 207 755 3.652 2,318 313 1,053 3.363 Mbozi 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbarali 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Mbeya Urb 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Total 2,647 427 1,248 2.923 3,447 425 1,261 2.967 6,094 852 2,509 2.945 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 8,882 3,791 1,496 0.395 8,882 3,791 1,496 0.395 Mbeya Rur 6,461 1,631 1,000 0.613 30,125 10,536 4,873 0.463 36,585 12,167 5,873 0.483 Kyela 0 0 0 0.000 1,727 418 253 0.606 1,727 418 253 0.606 Rungwe 16,289 3,718 1,847 0.497 30,806 7,528 3,364 0.447 47,096 11,246 5,211 0.463 Ileje 2,940 604 290 0.480 21,556 4,931 1,946 0.395 24,496 5,535 2,236 0.404 Mbozi 0 0 0 0.000 72,033 27,786 13,439 0.484 72,033 27,786 13,439 0.484 Mbarali 0 0 0 0.000 3,142 787 693 0.881 3,142 787 693 0.881 Mbeya Urb 21 2 1 0.296 4,441 860 413 0.480 4,462 862 414 0.480 Total 25,710 5,955 3,137 0.527 172,711 56,637 26,477 0.467 198,422 62,593 29,615 0.473 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.000 289 37 74 1.998 289 37 74 1.998 Mbeya Rur 116 9 3 0.358 0 0 0 0.000 116 9 3 0.358 Kyela 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Rungwe 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Ileje 129 9 3 0.282 129 9 4 0.445 258 18 7 0.363 Mbozi 0 0 0 0.000 172 17 3 0.198 172 17 3 0.198 Mbarali 0 0 0 0.000 558 226 3 0.014 558 226 3 0.014 Mbeya Urb 0 0 0 0.000 0 0 0 0.000 0 0 0 0.000 Total 245 18 6 0.321 1,147 290 85 0.293 1,392 309 91 0.295 7.2.8 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cocoyams Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Cocoyams Dry Season Wet Season Total 7.2.9 Number of Agricultural Households, Area Planted (Ha) and Quantity of Beans Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Beans Dry Season Wet Season Total 7.2.10 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cowpeas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Cowpeas Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 178 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Ileje 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbarali 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 23 5 1 0.148 23 5 1 0.15 Total 0 0 0 0.00 23 5 1 0.148 23 5 1 0.15 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 101 41 10 0.247 101 41 10 0.25 Mbeya Rur 116 5 17 3.71 119 24 3 0.124 235 29 20 0.70 Kyela 0 0 0 0.00 657 89 75 0.844 657 89 75 0.84 Rungwe 0 0 0 0.00 2,082 234 181 0.774 2,082 234 181 0.77 Ileje 129 4 3 0.61 447 48 19 0.389 576 52 21 0.41 Mbozi 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbarali 0 0 0 0.00 336 147 34 0.228 336 147 34 0.23 Mbeya Urb 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Total 245 9 20 2.20 3,742 584 322 0.551 3,987 593 342 0.58 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.000 0 0 0 0.00 Mbeya Rur 121 74 27 0.37 1,441 282 144 0.509 1,563 356 171 0.48 Kyela 0 0 0 0.00 0 . . 0.000 0 0 0 0.00 Rungwe 458 104 285 2.74 461 93 16 0.173 919 197 301 1.52 Ileje 0 0 0 0.00 1,096 356 106 0.297 1,096 356 106 0.30 Mbozi 0 0 0 0.00 1,423 583 152 0.261 1,423 583 152 0.26 Mbarali 0 0 0 0.00 0 . . 0.000 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 656 52 32 0.609 656 52 32 0.61 Total 579 178 312 1.76 5,077 1,367 449 0.329 5,656 1,544 761 0.49 7.2.11 Number of Agricultural Households, Area Planted (Ha) and Quantity of Chick Peas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Chickpeas Dry Season Wet Season Total 7.2.12 Number of Agricultural Households, Area Planted (Ha) and Quantity of Bambaranuts Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Bambaranuts Dry Season Wet Season Total 7.2.13 Number of Agricultural Households, Area Planted (Ha) and Quantity of Field Peas Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Field Peas Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 179 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 266 141 100 0.71 266 141 100 0.71 Mbeya Rur 232 30 25 0.83 3,304 967 497 0.51 3,535 997 523 0.52 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 65 2 2 0.66 1,335 209 113 0.54 1,400 1,400 114 0.08 Mbozi 0 0 0 0.00 4,229 1,495 827 0.55 4,229 4,229 827 0.20 Mbarali 0 0 0 0.00 1,342 956 234 0.25 1,342 1,342 234 0.17 Mbeya Urb 0 0 0 0.00 68 14 11 0.79 68 68 11 0.16 Total 296 33 27 0.82 10,545 3,781 1,783 0.47 10,841 10,841 1,809 0.17 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 3,124 2,981 1,303 0.44 3,124 2,981 1,303 0.44 Mbeya Rur 0 0 0 0.00 345 930 173 0.19 345 930 173 0.19 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 232 23 9 0.40 232 23 9 0.40 Ileje 0 0 0 0.00 126 19 2 0.13 126 19 2 0.13 Mbozi 0 0 0 0.00 3,892 1,240 564 0.45 3,892 1,240 564 0.45 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 0 0 0 0.00 7,719 5,194 2,051 0.39 7,719 5,194 2,051 0.39 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 11,375 4,527 2,299 0.51 11,375 4,527 2,299 0.51 Mbeya Rur 463 47 30 0.64 4,979 1,752 637 0.36 5,442 1,799 667 0.37 Kyela 0 0 0 0.00 2,579 562 444 0.79 2,579 562 444 0.79 Rungwe 4,004 863 337 0.39 7,134 826 608 0.74 11,139 1,689 945 0.56 Ileje 1,029 71 13 0.19 9,160 1,544 759 0.49 10,189 1,615 772 0.48 Mbozi 0 0 0 0.00 34,532 8,117 4,686 0.58 34,532 8,117 4,686 0.58 Mbarali 0 0 0 0.00 7,378 2,742 909 0.33 7,378 2,742 909 0.33 Mbeya Urb 0 0 0 0.00 12 2 2 1.10 12 2 2 1.10 Total 5,497 981 381 0.39 77,149 20,073 10,343 0.52 82,646 21,054 10,724 0.51 7.2.14 Number of Agricultural Households, Area Planted (Ha) and Quantity of Sunflower Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Sunflower Dry Season Wet Season Total 7.2.15 Number of Agricultural Households, Area Planted (Ha) and Quantity of SimsimHarvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Simsim Dry Season Wet Season Total 7.2.16 Number of Agricultural Households, Area Planted (Ha) and Quantity of Groundnuts Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Groundnuts Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 180 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 0 0 0 0.00 324 51 32 0.63 324 51 32 0.63 Mbozi 0 0 0 0.00 139 28 3 0.10 139 28 3 0.10 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 0 0 0 0.00 464 79 35 0.44 464 79 35 0.44 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 98 795 318 0.40 98 795 318 0.40 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 0 0 0 0.00 98 795 318 0.40 98 795 318 0.40 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 37 6 62 11.07 37 6 62 0.00 Total 0 0 0 0.00 37 6 62 11.07 37 6 62 11.07 7.2.17 Number of Agricultural Households, Area Planted (Ha) and Quantity of Soya Beans Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Soya Beans Dry Season Wet Season Total 7.2.18 Number of Agricultural Households, Area Planted (Ha) and Quantity of Radish Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Radish Dry Season Wet Season Total 7.2.19 Number of Agricultural Households, Area Planted (Ha) and Quantity of Bitter Aubergine Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Bitter Aubergine Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 181 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.000 0 0 0 0.000 Mbeya Rur 116 10 93 9.41 2,420 539 3,508 6.505 2,536 549 3,601 6.557 Kyela 0 0 0 0.00 0 0 0 0.000 0 0 0 0.000 Rungwe 0 0 0 0.00 0 0 0 0.000 0 0 0 0.000 Ileje 0 0 0 0.00 580 92 139 1.512 580 92 139 1.512 Mbozi 0 0 0 0.00 172 42 7 0.165 172 42 7 0.165 Mbarali 0 0 0 0.00 106 11 34 3.162 106 11 34 3.162 Mbeya Urb 0 0 0 0.00 9 2 7 3.557 9 2 7 3.557 Total 116 10 93 9.41 3,288 686 3,694 5.389 3,404 695 3,787 5.446 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 121 12 18 1.48 238 24 59 2.44 360 36 77 2.11 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 308 43 315 7.33 163 16 33 1.98 471 59 347 5.85 Ileje 500 95 69 0.73 0 0 0 0.00 500 95 69 0.73 Mbozi 0 0 0 0.00 1,724 126 1,214 9.64 1,724 126 1,214 9.64 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 20 2 24 11.86 20 2 24 11.86 Total 929 150 402 2.68 2,145 169 1,329 7.89 3,074 318 1,731 5.44 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0.00 Mbeya Rur 0 0 0 0.00 1,324 445 3,106 6.99 1,324 445 3,106 6.99 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 424 43 505 11.77 323 44 242 5.46 747 87 747 8.57 Ileje 561 91 74 0.81 258 29 53 1.83 818 120 127 1.06 Mbozi 0 0 0 0.00 1,639 219 1,115 5.09 1,639 219 1,115 5.09 Mbarali 0 0 0 0.00 1,092 237 398 1.68 1,092 237 398 1.68 Mbeya Urb 0 0 0 0.00 532 109 820 7.49 532 109 820 7.49 Total 985 134 579 4.32 5,167 1,084 5,734 5.29 6,151 1,218 6,312 5.18 7.2.20 Number of Agricultural Households, Area Planted (Ha) and Quantity of Onions Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Onions Dry Season Wet Season Total 7.2.21 Number of Agricultural Households, Area Planted (Ha) and Quantity of Cabbage Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Cabbage Dry Season Wet Season Total 7.2.22 Number of Agricultural Households, Area Planted (Ha) and Quantity of Tomatoes Harvested (Tonnes) by Season and District , District Tomatoes Dry Season Wet Season Total Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 182 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 114 23 123 5.34 114 23 123 5.34 Ileje 247 51 10 0.19 0 0 0 0.00 247 51 10 0.19 Mbozi 0 0 0 0.00 529 61 92 1.52 529 61 92 1.52 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 19 2 0 0.16 19 2 0 0.16 Total 247 51 10 0.19 662 85 216 2.53 909 137 225 1.65 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 105 10 47 4.88 105 10 47 4.88 Total 0 0 0 0.00 105 10 47 105 10 47 4.88 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbarali 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Urb 0 0 0 0.00 48 4 25 7.13 48 4 25 7.13 Total 0 0 0 0.00 48 4 25 7.13 48 4 25 7.13 7.2.23 Number of Agricultural Households, Area Planted (Ha) and Quantity of Spinach Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Spinach Dry Season Wet Season Total 7.2.24 Number of Agricultural Households, Area Planted (Ha) and Quantity of Carrot Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Carrot Dry Season Wet Season Total 7.2.25 Number of Agricultural Households, Area Planted (Ha) and Quantity of Chilles Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Chilles Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 183 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 113 11 34 2.96 121 15 6 0.41 235 18 40 2.29 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 232 70 24 0.35 392 33 60 1.84 624 131 85 0.65 Ileje 379 49 9 0.18 64 3 0 0.00 444 49 9 0.18 Mbozi 0 0 0 0.00 1,345 198 88 0.44 1,345 88 88 1.00 Mbarali 0 0 0 0.00 99 40 217 5.43 99 217 217 1.00 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 725 131 67 0.51 2,021 289 371 1.28 2,745 502 438 0.87 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 193 126 121 0.96 193 126 121 0.96 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Ileje 320 47 16 0.35 899 76 70 0.91 1,219 123 86 0.70 Mbozi 0 0 0 0.00 139 6 14 2.47 139 6 14 2.47 Mbarali 0 0 0 0.00 302 110 440 4.00 302 110 440 4.00 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 320 47 16 0.35 1,534 318 645 2.03 1,854 365 661 1.81 Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Number of Household Area Planted Quantity Harvested Yield Chunya 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbeya Rur 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Kyela 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Rungwe 116 5 1 0.25 0 0 0 0.00 116 5 1 0.25 Ileje 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbozi 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Mbarali 0 0 0 0.00 104 11 1 0.08 104 11 1 0.08 Mbeya Urb 0 0 0 0.00 0 0 0 0.00 0 0 0 0.00 Total 116 5 1 0.25 104 11 1 0.08 104 11 1 0.079 7.2.25 Number of Agricultural Households, Area Planted (Ha) and Quantity of Amaranths Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Pumpkins Dry Season Wet Season Total 7.2.26 Number of Agricultural Households, Area Planted (Ha) and Quantity of Pumpkins Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Pumpkins Dry Season Wet Season Total 7.2.27 Number of Agricultural Households, Area Planted (Ha) and Quantity of Egg plants Harvested (Tonnes) by Season and District , 2002/03 Agricultural Year District Egg plants Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mbeya 184 Appendix II 185 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 186 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Mango 80 59 929 15,874 Total 80 59 929 15,874 Coffee 5,071 3,396 3,266 962 Sugarcane 24 12 1,784 148,200 Mpesheni 0 0 . Banana 493 500 1,916 3,835 Avocado 20 63 344 5,459 Mango 42 49 1,104 22,684 Pawpaw . . . Pineapple . 5 1 296 Guava . . . Apples 5 5 5 988 Pitches 26 12 41 3,449 Total 5,681 4,040 8,461 2,094 Pigeon Pea 8 8 5 642 Star Fruit 17 17 374 21,654 Palm Oil 1,807 1,822 2,591 1,422 Coconut 40 40 30 755 Cashewnut 577 363 97 267 Cocoa 7,685 5,058 4,344 859 Rubber 36 0 . Mpesheni 10 10 228 22,870 Banana 3,007 3,177 17,102 5,383 Avocado 50 34 29 856 Mango 485 410 1,768 4,310 Pawpaw 7 7 2 247 Pineapple 3 3 35 11,115 Orange 548 137 476 3,483 Mandarine/Tangerine 15 15 393 25,935 Total 14,296 11,102 27,474 2,475 Sour Soup 46 23 . Pigeon Pea 67 67 48 709 Star Fruit 0 0 5 Palm Oil 1,607 188 967 5,152 Coffee 19,761 5,391 4,386 814 Tea 4,608 3,166 16,691 5,272 Cocoa 7,643 3,708 1,068 288 Sugarcane 228 199 3,417 17,136 Cardamon 440 63 13 210 Cloves 77 31 7 228 Banana 43,366 18,741 183,775 9,806 Avocado 2,974 382 4,211 11,031 Mango 2,466 366 1,938 5,295 Pawpaw 261 52 246 4,764 Pineapple 20 0 25 Orange 1,419 191 940 4,914 Guava 0 47 12 247 Plums 47 0 3 Pitches 27 25 131 5,214 Total 85,058 32,639 217,883 6,676 7.3 Production of Permanent Crops by Crop Type and District - Mbeya Rgion Kyela Rungwe District/Crop Chunya Mbeya Rural Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 187 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/Ha) Pigeon Pea 33 31 9 283 Coffee 2,672 2,199 4,698 2,137 Cocoa 134 106 6 60 Sugarcane 108 108 2,789 25,872 Cardamon 474 416 71 171 Mpesheni 41 49 289 5,938 Banana 2,408 1,754 13,392 7,634 Avocado 161 117 706 6,044 Mango 245 166 1,578 9,476 Pawpaw 5 5 5 926 Pineapple 3 3 . Orange 103 59 89 1,521 Grape 24 0 . Guava . . 7 Pitches . . . Total 6,412 5,011 23,638 4,717 Sour Soup 18 18 215 11,856 Rubber Vine Fruit 29 0 . Pigeon Pea 36 18 2 99 Star Fruit 90 72 36 494 Coffee 31,692 27,980 86,326 3,085 Sugarcane 330 261 3,801 14,559 Jack Fruit . . . Banana 1,259 1,321 8,269 6,258 Avocado 316 153 1,740 11,373 Mango 477 362 3,383 9,348 Pawpaw 0 0 12 Orange 7 7 137 19,714 Grape Fruit 348 69 478 6,923 Guava . . . Total 34,603 30,262 104,398 3,450 Sugarcane 149 148 3,831 25,876 Banana 1,926 45 22 494 Mango 4,522 360 1,477 4,102 Pawpaw . 0 . Orange 23 23 53 2,371 Guava . 13 27 2,141 Lime/Lemon . 8 15 1,820 Total 6,620 597 5,426 9,092 Mangostine 4 4 1 296 Malay Apple 3 3 7 2,058 Palm Oil . . . Sisal 2 0 . Coffee 265 96 165 1,728 Sugarcane . 1 35 37,050 Jack Fruit 2 2 0 191 Banana 255 158 765 4,847 Avocado 141 51 174 3,412 Mango 42 24 75 3,078 Pawpaw 55 14 91 6,286 Orange 3 3 4 1,546 Grape . . . Guava 23 13 34 2,579 Apples 3 2 . Pitches 23 27 174 6,322 Lime/Lemon 9 9 4 481 Total 830 407 1,529 3,756 Mbeya Urban Cont……...Production of Permanent Crops by Crop Type and District - Mbeya Rgion Ileje Mbozi' Mbarali Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 188 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/Ha) Sour Soup 65 41 215 5,203 Rubber Vine F 29 0 . Mangostine 4 4 1 296 Pigeon Pea 145 124 63 510 Malay Apple 3 3 7 2,058 Star Fruit 108 89 415 4,634 Palm Oil 3,414 2,010 3,558 1,770 Coconut 40 40 30 755 Cashewnut 577 363 97 267 Sisal 2 0 . Coffee 59,460 39,061 98,841 2,530 Tea 4,608 3,166 16,691 5,272 Cocoa 15,462 8,871 5,418 611 Rubber 36 0 . Sugarcane 839 729 15,658 21,468 Cardamon 914 479 84 176 Cloves 77 31 7 228 Jack Fruit 2 2 0 191 Mpesheni 51 59 517 8,819 Banana 52,715 25,696 225,241 8,766 Avocado 3,662 799 7,205 9,013 Mango 8,359 1,796 12,251 6,821 Pawpaw 329 78 354 4,553 Pineapple 25 11 62 5,802 Orange 2,101 419 1,700 4,061 Grape Fruit 348 69 478 6,923 Grape 24 0 . Mandarine/Ta 15 15 393 25,935 Guava 23 72 80 1,098 Plums 47 0 3 Apples 8 7 5 732 Pitches 77 64 345 5,364 Lime/Lemon 9 17 20 1,136 Total 153,578 84,116 389,739 4,633 Grand Total Cont…Production of Permanent Crops by Crop Type and District - Mbeya Rgion Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 189 Crop Area Planted (ha) % Coffee 59,460 39 Banana 52,715 34 Cocoa 15,462 10 Mango 8,359 5 Tea 4,608 3 Avocado 3,662 2 Palm Oil 3,414 2 Orange 2,101 1 Cardamon 914 1 Sugarcane 839 1 Cashewnut 577 0 Grape Fruit 348 0 Pawpaw 329 0 Pigeon Pea 145 0 Star Fruit 108 0 Cloves 77 0 Pitches 77 0 Sour Soup 65 0 Mpesheni 51 0 Plums 47 0 Coconut 40 0 Rubber 36 0 Rubber Vine Fruit 29 0 Pineapple 25 0 Grape 24 0 Guava 23 0 Mandarine/Tangerine 15 0 Lime/Lemon 9 0 Apples 8 0 Mangostine 4 0 Malay Apple 3 0 Jack Fruit 2 0 Sisal 2 0 Total 153,578 100 Cont…Area Planted (Ha) by Crop Type - Mbeya Region Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 190 District Area planted with coffee Total Area Planted (Ha) % of Total Area Planted hh with coffee Average Planted Area per Household District Area planted with Banana Total Area Planted (Ha) % of Total Area Planted hh with Banana Average Planted Area per Household Mbozi 31,692 138,870 56 47,842 0.66 Rungwe 43,366 52,466 82 53,157 0.82 Rungwe 19,761 52,466 35 24,743 0.80 Kyela 3,007 30,792 6 15,646 0.19 Mbeya Rural 5,071 67,256 9 10,899 0.47 Ileje 2,408 30,564 5 12,440 0.19 Mbeya Urban 265 5,191 0 435 0.61 Mbarali 1,926 62,299 4 215 8.96 Chunya 0 71,788 0 0 0.00 Mbozi 1,259 138,870 2 9,327 0.14 Ileje 0 30,564 0 0 0.00 Mbeya Rural 493 67,256 1 2,410 0.20 Mbarali 0 62,299 0 0 0.00 Mbeya Urban 255 5,191 0 855 0.30 Kyela 0 30,792 0 0 0.00 Chunya 0 71,788 0 0 0.00 Total 56,788 459,226 100 83,918 0.68 Total 52,715 459,226 100 40,893 1.29 District Area planted with Cocoa Total Area Planted (Ha) % of Total Area Planted hh with Cocoa Average Planted Area per Household District Area planted with Mangoes Total Area Planted (Ha) % of Total Area Planted hh with Manmgoes Average Planted Area per Household Kyela 7,685 30,792 50 17,622 0.44 Mbarali 4,522 62,299 54 2,013 2.25 Rungwe 7,643 52,466 49 10,427 0.73 Rungwe 2,466 67,256 30 354 0.12 Ileje 134 30,564 1 566 0.24 Kyela 485 71,788 6 193 0.41 Chunya 0 71,788 0 0 0.00 Mbozi 477 138,870 6 4,367 0.11 Mbeya Rural 0 67,256 0 0 0.00 Ileje 245 30,792 3 3,180 0.15 Mbozi 0 138,870 0 0 0.00 Chunya 80 52,466 1 4,717 0.52 Mbarali 0 62,299 0 0 0.00 Mbeya Urban 42 5,191 1 127 0.34 Mbeya Urban 0 5,191 0 0 0.00 Mbeya Rural 42 30,564 1 1,323 0.19 Total 15,462 459,226 100 28,615 0.54 Total 8,360 459,226 100 16,272 0.51 7.4 Total Area Planted (Ha) with Coffee - Mbeya Region 7.5 Total Area Planted (Ha) with Banana - Mbeya Region 7.6 Total Area Planted (Ha) with Cocoa - Mbeya Region 7.7 Total Area Planted (Ha) with Mangoes - Mbeya Region Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 191 Crop Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0 0 0 65 65 Rubber Vine Fruit 0 0 0 29 29 Mangostine 0 0 0 4 4 Pigeon Pea 24 0 0 97 122 Malay Apple 3 0 0 0 3 Star Fruit 0 0 0 108 108 Palm Oil 54 0 0 3,353 3,407 Coconut 0 0 0 23 23 Cashewnut 11 0 0 566 577 Sisal 0 0 0 2 2 Coffee 20,572 7,978 15,972 14,563 59,085 Tea 70 0 4,410 128 4,608 Cocoa 975 437 0 14,040 15,452 Rubber 36 0 0 . 36 Sugarcane 102 0 0 716 818 Cardamon 302 121 3 489 914 Cloves 0 0 0 77 77 Jack Fruit 2 0 0 0 2 Mpesheni 31 0 0 20 51 Banana 14,707 9,191 1,436 27,314 52,648 Avocado 371 52 20 3,008 3,452 Mango 309 392 2 7,654 8,357 Pawpaw 107 0 14 207 329 Pineapple 20 0 0 6 25 Orange 103 205 0 1,669 1,977 Grape Fruit 0 0 348 0 348 Grape 0 0 0 24 24 Mandarine/Tangerine 0 0 0 15 15 Guava 15 0 0 9 23 Plums 0 0 0 47 47 Apples 3 0 0 5 8 Pitches 12 11 1 52 77 Lime/Lemon 6 0 2 1 9 Total 37,836 18,387 22,208 74,289 152,721 7.8 Production of Permanent Planted Crops with Fertilizer Use - Mbeya Region Fertilizer Use Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 192 Crop Mostly Farm Yard Manure Total % Sour Soup 0 65 0 Rubber Vine F 0 29 0 Mangostine 0 4 0 Pigeon Pea 24 122 20 Malay Apple 3 3 100 Star Fruit 0 108 0 Palm Oil 54 3,407 2 Coconut 0 23 0 Cashewnut 11 577 2 Sisal 0 2 0 Coffee 20,572 59,085 35 Tea 70 4,608 2 Cocoa 975 15,452 6 Rubber 36 36 100 Sugarcane 102 818 12 Cardamon 302 914 33 Cloves 0 77 0 Jack Fruit 2 2 100 Mpesheni 31 51 60 Banana 14,707 52,648 28 Avocado 371 3,452 11 Mango 309 8,357 4 Pawpaw 107 329 33 Pineapple 20 25 77 Orange 103 1,977 5 Grape Fruit 0 348 0 Grape 0 24 0 Mandarine/Ta 0 15 0 Guava 15 23 63 Plums 0 47 0 Apples 3 8 41 Pitches 12 77 16 Lime/Lemon 6 9 67 Total 37,836 152,721 25 7.9 Production of Permanent Planted Crops with Fertilizer by Farm Yard Manure - Mbeya Region Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 193 Crop Mostly Compost Manure Total % Sour Soup 0 65 0 Rubber Vine Fruit 0 29 0 Mangostine 0 4 0 Pigeon Pea 0 122 0 Malay Apple 0 3 0 Star Fruit 0 108 0 Palm Oil 0 3,407 0 Coconut 0 23 0 Cashewnut 0 577 0 Sisal 0 2 0 Coffee 7,978 59,085 14 Tea 0 4,608 0 Cocoa 437 15,452 3 Rubber 0 36 0 Sugarcane 0 818 0 Cardamon 121 914 13 Cloves 0 77 0 Jack Fruit 0 2 0 Mpesheni 0 51 0 Banana 9,191 52,648 17 Avocado 52 3,452 2 Mango 392 8,357 5 Pawpaw 0 329 0 Pineapple 0 25 0 Orange 205 1,977 10 Grape Fruit 0 348 0 Grape 0 24 0 Mandarine/Tangerine 0 15 0 Guava 0 23 0 Plums 0 47 0 Apples 0 8 0 Pitches 11 77 15 Lime/Lemon 0 9 0 Total 18,387 152,721 12 7.10 Production of Permanent Planted Crops with Fertilizer by Most Compost Manure - Mbeya Region Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 194 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 65 0 Rubber Vine Fruit 0 29 0 Mangostine 0 4 0 Pigeon Pea 0 122 0 Malay Apple 0 3 0 Star Fruit 0 108 0 Palm Oil 0 3,407 0 Coconut 0 23 0 Cashewnut 0 577 0 Sisal 0 2 0 Coffee 15,972 59,085 27 Tea 4,410 4,608 96 Cocoa 0 15,452 0 Rubber 0 36 0 Sugarcane 0 818 0 Cardamon 3 914 0 Cloves 0 77 0 Jack Fruit 0 2 0 Mpesheni 0 51 0 Banana 1,436 52,648 3 Avocado 20 3,452 1 Mango 2 8,357 0 Pawpaw 14 329 4 Pineapple 0 25 0 Orange 0 1,977 0 Grape Fruit 348 348 100 Grape 0 24 0 Mandarine/Tangerine 0 15 0 Guava 0 23 0 Plums 0 47 0 Apples 0 8 0 Pitches 1 77 1 Lime/Lemon 2 9 22 Total 22,208 152,721 15 7.11 Production of Permanent Planted Crops with Fertilizer by Most Inorganic Manure - Mbeya Region Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 195 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 196 Number % Number % Number % Chunya 37,159 97 1,102 3 38,262 100 Mbeya Rural 49,916 93 3,949 7 53,865 100 Kyela 32,663 96 1,529 4 34,192 100 Rungwe 64,922 96 2,402 4 67,323 100 Ileje 25,246 98 573 2 25,819 100 Mbozi' 101,321 98 2,165 2 103,486 100 Mbarali 33,028 77 9,689 23 42,718 100 Mbeya Urban 6,921 96 259 4 7,180 100 Total 351,176 94 21,668 6 372,844 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Chunya 1,838 290 34,930 0 0 101 0 0 0 37,159 Mbeya Rural 2,255 364 39,224 0 0 8,072 0 0 0 49,916 Kyela 4,210 1,723 22,970 0 0 3,588 0 172 0 32,663 Rungwe 5,244 6,696 50,089 0 232 2,661 0 0 0 64,922 Ileje 3,860 2,055 18,230 0 0 1,102 0 0 0 25,246 Mbozi' 4,019 2,424 91,954 352 0 1,861 179 358 173 101,321 Mbarali 542 1,202 31,180 0 105 0 0 0 0 33,028 Mbeya Urban 205 674 5,819 0 37 187 0 0 0 6,921 Total 22,173 15,428 294,395 352 373 17,573 179 530 173 351,176 % 6 4 84 0 0 5 0 0 0 100 8.0a AGRO PROCESSING: Did tthe Household Process any Of the Products Harvested District Did the Hh Process any of the products harvested during 2002 Total 8.0b AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District District Method of Processing Households That Did Not Process Product Households That Processed Product Tanzania Agriculture Sample Census - 2003 Mbeya appendix II 197 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 1,572 290 33,125 0 0 101 0 0 0 35,089 Paddy 681 79 769 0 0 99 0 0 0 1,628 Sorghum 179 101 8,152 0 0 0 0 0 0 8,433 Finger Millet 96 0 883 0 0 0 0 0 0 980 Cassava 781 0 298 0 0 0 0 0 0 1,079 Sweet Potatoes 95 0 0 0 0 0 0 0 0 95 Beans 828 0 0 0 0 0 0 0 0 828 Simsim 0 0 84 0 0 0 0 0 0 84 Groundnut 7,985 201 466 0 0 0 0 98 0 8,750 Tobacco 0 0 0 0 0 0 0 0 96 96 Maize 2,255 243 38,738 0 0 8,072 0 0 0 49,309 Paddy 113 0 0 0 0 238 0 0 0 351 Sorghum 0 0 347 0 0 0 0 0 0 347 Finger Millet 338 0 1,305 0 0 120 0 0 0 1,763 Wheat 0 0 4,360 0 0 471 0 0 0 4,831 Beans 113 121 235 0 0 0 0 0 0 470 Sunflower 0 0 469 0 0 954 0 0 0 1,423 Groundnut 1,382 0 243 0 0 119 0 0 0 1,744 Coffee 0 972 243 0 0 0 0 0 0 1,214 Maize 516 1,257 10,856 0 0 2,002 0 0 0 14,631 Paddy 4,325 1,026 19,075 0 0 4,591 0 663 0 29,680 Cassava 440 0 0 0 0 0 0 0 0 440 Groundnut 356 0 71 0 0 0 0 0 0 427 Oil Palm 1,037 1,375 7,594 0 0 430 0 0 0 10,437 Coconut 185 0 0 0 0 0 0 0 0 185 Cashewnut 0 0 90 0 0 0 0 0 0 90 Cocoa 2,076 173 82 0 0 0 0 0 0 2,332 Banana 93 0 88 0 0 0 0 0 0 181 Maize 3,572 5,765 50,088 0 232 2,661 0 0 0 62,318 Paddy 3,646 1,372 2,765 0 0 695 0 0 0 8,478 Finger Millet 0 0 0 0 0 232 0 0 0 232 Cassava 1,039 114 114 0 0 116 0 0 0 1,383 Beans 1,156 579 2,429 0 0 0 0 0 0 4,165 Groundnut 304 0 0 0 0 0 0 0 0 304 Oil Palm 0 346 345 0 0 0 0 0 0 691 Coffee 4,401 10,359 1,266 0 0 0 0 0 0 16,027 Banana 2,066 116 421 0 0 0 0 0 0 2,603 Maize 3,480 2,305 18,165 0 0 1,102 0 0 0 25,051 Paddy 944 64 868 0 0 65 0 0 0 1,940 Sorghum 0 0 260 0 0 0 0 0 0 260 Finger Millet 453 127 2,382 0 0 0 0 0 0 2,962 Wheat 0 0 454 0 0 0 0 0 0 454 Cassava 1,141 0 322 0 0 0 0 0 0 1,464 Beans 681 65 0 0 0 0 0 0 0 746 Bambaranut 62 0 0 0 0 0 0 0 0 62 Sunflower 0 0 189 0 0 324 65 0 0 578 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop District Method of Processing Tanzania Agriculure Sample Census - Mbeya Appendix II 198 Groundnut 1,080 0 64 0 0 64 0 59 0 1,267 Soya Beans 0 0 0 0 0 0 65 0 0 65 Coffee 62 2,182 1,933 0 0 0 0 0 0 4,177 Banana 0 0 324 0 0 0 0 0 0 324 Maize 2,963 1,574 84,900 179 0 1,861 179 358 173 92,187 Paddy 528 358 5,004 0 0 0 0 0 0 5,891 Sorghum 704 176 13,135 0 0 0 0 0 0 14,014 Bulrush Millet 354 0 1,058 0 0 0 0 0 0 1,412 Finger Millet 1,590 0 4,450 0 0 0 0 0 0 6,040 Cassava 4,454 0 891 0 0 175 0 0 0 5,520 Beans 0 0 179 0 0 172 0 0 0 351 Sunflower 0 0 884 173 0 717 0 0 358 2,132 Groundnut 2,848 0 873 0 0 495 0 0 523 4,739 Coffee 2,931 32,012 6,928 0 0 0 174 0 2,986 45,032 Banana 1,962 0 0 0 0 0 0 0 0 1,962 Maize 218 976 26,802 0 0 0 0 0 0 27,995 Paddy 640 325 13,485 0 211 0 0 0 0 14,662 Sorghum 111 226 1,316 0 0 0 0 0 0 1,653 Cassava 105 0 0 0 0 0 0 0 0 105 Sweet Potatoes 432 0 0 0 0 0 0 0 0 432 Sunflower 111 0 0 0 0 0 0 0 0 111 Groundnut 1,174 0 0 0 0 0 0 0 0 1,174 Maize 181 656 5,802 0 37 187 0 0 0 6,863 Paddy 0 0 17 0 0 0 0 0 0 17 Wheat 0 0 136 23 0 0 0 0 0 159 Beans 0 0 22 0 0 0 0 0 0 22 Sunflower 0 0 41 0 0 0 0 0 0 41 Groundnut 0 0 12 0 0 0 0 0 0 12 Coffee 189 149 128 0 0 0 0 0 0 465 Cont…………..Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop Tanzania Agriculture Sample Censns - 2003 Mbeya Appendix II 199 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Chunya 36,786 95 101 101 76 0 37,159 Mbeya Rural 49,676 119 121 0 0 0 49,916 Kyela 27,655 0 4,481 351 176 0 32,663 Rungwe 62,498 116 1,272 920 0 116 64,922 Ileje 24,794 0 130 129 129 64 25,246 Mbozi' 97,539 0 2,272 840 491 179 101,321 Mbarali 32,534 0 196 0 298 0 33,028 Mbeya Urban 6,711 0 123 87 0 0 6,921 Total 338,193 330 8,696 2,428 1,169 360 351,176 8.1.1b AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 200 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Chunya 3,620 0 398 0 101 0 385 2,738 29,917 37,159 Mbeya Rural 717 242 0 118 0 0 121 0 48,718 49,916 Kyela 1,021 1,854 0 88 279 0 3,622 254 25,545 32,663 Rungwe 1,027 3,239 232 230 0 0 1,504 579 58,111 64,922 Ileje 943 1,337 506 65 65 0 0 128 22,203 25,246 Mbozi' 465 351 0 358 530 179 526 318 98,593 101,321 Mbarali 603 87 0 0 620 87 0 105 31,526 33,028 Mbeya Urban 612 45 41 17 36 0 361 22 5,787 6,921 Total 9,009 7,153 1,177 876 1,631 266 6,520 4,145 320,399 351,176 Flour / Meal Grain Oil Juice Pulp Rubber Other Total Chunya 33,991 3,168 0 0 0 0 0 37,159 Mbeya Rural 48,718 963 235 0 0 0 0 49,916 Kyela 6,786 21,294 4,245 87 90 161 0 32,663 Rungwe 53,349 11,033 191 0 116 0 232 64,922 Ileje 23,771 1,222 124 65 0 0 64 25,246 Mbozi' 94,726 5,712 350 0 357 176 0 101,321 Mbarali 26,022 7,007 0 0 0 0 0 33,028 Mbeya Urban 6,775 123 0 0 0 23 0 6,921 Total 294,138 50,522 5,145 152 564 360 296 351,176 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Chunya 36,786 95 101 101 76 0 37,159 Mbeya Rural 49,676 119 121 0 0 0 49,916 Kyela 27,655 0 4,481 351 176 0 32,663 Rungwe 62,498 116 1,272 920 0 116 64,922 Ileje 24,794 0 130 129 129 64 25,246 Mbozi' 97,539 0 2,272 840 491 179 101,321 Mbarali 32,534 0 196 0 298 0 33,028 Mbeya Urban 6,711 0 123 87 0 0 6,921 Total 338,193 330 8,696 2,428 1,169 360 351,176 8.1.1c AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 201 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Chunya 3,620 0 398 0 101 0 385 2,738 29,917 37,159 Mbeya Rural 717 242 0 118 0 0 121 0 48,718 49,916 Kyela 1,021 1,854 0 88 279 0 3,622 254 25,545 32,663 Rungwe 1,027 3,239 232 230 0 0 1,504 579 58,111 64,922 Ileje 943 1,337 506 65 65 0 0 128 22,203 25,246 Mbozi' 465 351 0 358 530 179 526 318 98,593 101,321 Mbarali 603 87 0 0 620 87 0 105 31,526 33,028 Mbeya Urban 612 45 41 17 36 0 361 22 5,787 6,921 Total 9,009 7,153 1,177 876 1,631 266 6,520 4,145 320,399 351,176 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Chunya 16,615 0 854 0 0 655 0 592 18,256 187 37,159 Mbeya Rural 39,834 359 0 0 0 0 0 352 9,370 0 49,916 Kyela 15,340 463 16,283 0 0 436 0 70 71 0 32,663 Rungwe 62,097 114 1,023 0 230 579 114 0 764 0 64,922 Ileje 23,575 0 63 61 0 64 0 319 1,099 64 25,246 Mbozi' 31,427 1,584 1,612 179 171 23,716 0 2,681 39,951 0 101,321 Mbarali 23,192 0 4,319 0 0 0 0 448 5,069 0 33,028 Mbeya Urban 6,364 23 0 0 0 0 0 47 487 0 6,921 Total 218,445 2,543 24,154 240 400 25,451 114 4,510 75,068 251 351,176 District By Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District Tanzania Agriculture Sample Census - 2003 202 Appendix II 203 MARKETING Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 204 Total Number % Number % Number Chunya 16,475 43 21,786 57 38,262 Mbeya Rural 45,557 85 8,308 15 53,865 Kyela 29,091 85 5,101 15 34,192 Rungwe 60,729 90 6,594 10 67,323 Ileje 21,649 84 4,170 16 25,819 Mbozi' 91,048 88 12,439 12 103,486 Mbarali 22,433 53 20,285 47 42,718 Mbeya Urban 5,498 77 1,682 23 7,180 Total 292,480 78 80,364 22 372,844 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Chunya 1,645 20,391 292 84 0 0 0 712 14,327 37,450 Mbeya Rural 1,570 11,315 121 829 237 0 0 243 38,842 53,157 Kyela 173 5,561 85 0 0 0 0 280 25,454 31,552 Rungwe 1,042 8,405 230 0 229 0 0 231 50,075 60,213 Ileje 254 4,874 61 0 0 0 0 436 17,152 22,777 Mbozi' 2,768 23,945 0 0 279 496 179 179 73,113 100,958 Mbarali 1,812 19,190 0 0 0 105 0 2,257 18,147 41,511 Mbeya Urban 171 1,854 0 0 0 0 46 23 4,978 7,072 Total 9,434 95,536 789 913 745 601 225 4,361 242,088 354,691 10.2 MARETING: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District District Main Reasons for Not Selling Crops 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District District Number of Households that Sold Number of Households that Did not Sell Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 205 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Chunya 1,645 20,391 292 84 0 0 0 712 14,327 37,450 Mbeya Rural 1,570 11,315 121 829 237 0 0 243 38,842 53,157 Kyela 173 5,561 85 0 0 0 0 280 25,454 31,552 Rungwe 1,042 8,405 230 0 229 0 0 231 50,075 60,213 Ileje 254 4,874 61 0 0 0 0 436 17,152 22,777 Mbozi' 2,768 23,945 0 0 279 496 179 179 73,113 100,958 Mbarali 1,812 19,190 0 0 0 105 0 2,257 18,147 41,511 Mbeya Urban 171 1,854 0 0 0 0 46 23 4,978 7,072 Total 9,434 95,536 789 913 745 601 225 4,361 242,088 354,691 10.3 Proportion of Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District District Main Reasons for Not Selling Crops Tanzania Agriculture Sample Census - 2003 Mbeya 206 Appendix II 207 IRRIGATION/ EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 208 Total Number of Household % Number of Household % Number of Household Chunya 842 2 37,420 98 38,262 Mbeya Rural 5,597 10 48,268 90 53,865 Kyela 176 1 34,016 99 34,192 Rungwe 1,565 2 65,758 98 67,323 Ileje 4,193 16 21,625 84 25,819 Mbozi' 11,757 11 91,730 89 103,486 Mbarali 24,978 58 17,739 42 42,718 Mbeya Urban 802 11 6,378 89 7,180 Total 49,911 13 322,934 87 372,844 District Irrigated Area Area Irrigated Land this Year % Chunya 368 284 77 Mbeya Rural 2,767 1,810 65 Kyela 71 53 75 Rungwe 784 354 45 Ileje 1,354 1,237 91 Mbozi' 8,143 4,680 57 Mbarali 31,671 24,649 78 Mbeya Urban 271 224 83 Total 45,429 33,291 73 River Dam Well Canal Pipe water Total Chunya 355 0 487 0 0 842 Mbeya Rural 5,237 0 0 359 0 5,597 Kyela 88 0 0 89 0 176 Rungwe 1,104 116 345 0 0 1,565 Ileje 2,020 0 451 1,661 61 4,193 Mbozi' 8,997 173 995 1,592 0 11,757 Mbarali 15,394 0 317 9,057 210 24,978 Mbeya Urban 348 9 0 353 92 802 Total 33,543 298 2,595 13,112 362 49,911 % 67 1 5 26 1 100 Gravity Hand Bucket Hand Pump Motor Pump Other Total Chunya 181 336 243 81 0 842 Mbeya Rural 5,238 359 0 0 0 5,597 Kyela 176 0 0 0 0 176 Rungwe 912 424 115 115 0 1,565 Ileje 1,131 3,001 0 0 61 4,193 Mbozi' 6,207 5,371 0 179 0 11,757 Mbarali 24,143 730 0 0 105 24,978 Mbeya Urban 559 198 0 9 36 802 Total 38,547 10,420 358 384 202 49,911 Table 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District Households Practicing Irrigation Households not Practicing Irrigation 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water District 11.2 IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 209 Flood Sprinkler Water Hose Bucket / Watering Can Total Chunya 100 0 162 580 842 Mbeya Rural 5,238 0 0 359 5,597 Kyela 176 0 0 0 176 Rungwe 1,026 0 0 538 1,565 Ileje 1,069 0 61 3,064 4,193 Mbozi' 5,498 350 0 5,909 11,757 Mbarali 24,038 0 105 835 24,978 Mbeya Urban 547 9 69 177 802 Total 37,693 359 397 11,462 49,911 Does Not Have Facility Total Number % Number % Number Chunya 731 2 37,531 98 38,262 Mbeya Rural 12,569 23 41,296 77 53,865 Kyela 82 0 34,110 100 34,192 Rungwe 16,792 25 50,531 75 67,323 Ileje 7,881 31 17,937 69 25,819 Mbozi' 21,471 21 82,016 79 103,486 Mbarali 541 1 42,177 99 42,718 Mbeya Urban 1,473 21 5,707 79 7,180 Total 61,540 17 311,304 83 372,844 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Chunya 0 384 571 289 3,373 2,371 386 0 7,374 Mbeya Rural 1,214 11,500 113 602 6,403 21,158 9,079 0 50,068 Kyela 0 0 0 0 0 0 82 0 82 Rungwe 7,587 86,553 . 113 4,284 38,949 0 0 137,487 Ileje 3,757 42,977 321 5,399 7,180 16,145 15,617 127 91,522 Mbozi' 0 53,584 1,423 1,345 3,544 14,340 18,976 0 93,213 Mbarali 0 1,129 0 0 106 0 197 0 1,432 Mbeya Urban 225 2,864 0 356 3,292 2,031 206 0 8,974 Total 12,784 198,991 2,428 8,103 28,183 94,995 44,542 127 390,151 11.5: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District District Method of Application 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control District Presence of erosion Control/Water Harvesting Facilities Have facility Tanzania Agriculture Sample Census - 2003 Mbeya 210 Appendix II 211 ACCESS TO FARM INPUTS AND IMPLEMENTS Tanznania Agriculture Sample Census - 2003 Mbeya Appendix II 212 Total Number % Number % Number Chunya 6,425 17 31,837 83 38,262 Mbeya Rur 22,493 42 31,372 58 53,865 Kyela 1,278 4 32,914 96 34,192 Rungwe 16,624 25 50,700 75 67,323 Ileje 10,803 42 15,016 58 25,819 Mbozi 54,690 53 48,796 47 103,486 Mbarali 3,206 8 39,512 92 42,718 Mbeya Urb 4,834 67 2,346 33 7,180 Total 120,352 32 252,492 68 372,844 Total Number % Number % Number Chunya 3,198 8 35,064 92 38,262 Mbeya Rur 13,327 25 40,537 75 53,865 Kyela 1,947 6 32,336 94 34,283 Rungwe 36,185 54 31,138 46 67,323 Ileje 13,811 53 12,073 47 25,884 Mbozi 32,105 31 71,381 69 103,486 Mbarali 4,369 10 38,348 90 42,718 Mbeya Urb 2,637 37 4,543 63 7,180 Total 107,580 29 265,421 71 373,000 Total Number % Number % Number Chunya 1,139 3 37,122 97 38,262 Mbeya Rur 5,433 10 48,432 90 53,865 Kyela 5,284 15 28,907 85 34,192 Rungwe 16,726 25 50,597 75 67,323 Ileje 8,745 34 17,074 66 25,819 Mbozi 18,434 18 85,052 82 103,486 Mbarali 201 0 42,517 100 42,718 Mbeya Urb 361 5 6,819 95 7,180 Total 56,324 15 316,521 85 372,844 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Number of Agricultural Households Using Chemical Fertilizers Number of Agricultural Households NOT Using Chemical Fertilizers Number of Agricultural Households Using Farm Yard Manure Number of Agricultural Households NOT Using Farm Yard Manure Number of Agricultural Households Using COMPOST Manure Number of Agricultural Households NOT Using COMPOST Manure District District District Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 213 Total Number % Number % Number Chunya 3,198 8 35,064 92 38,262 Mbeya Rur 13,327 25 40,537 75 53,865 Kyela 1,947 6 32,336 94 34,283 Rungwe 36,185 54 31,138 46 67,323 Ileje 13,811 53 12,073 47 25,884 Mbozi 32,105 31 71,381 69 103,486 Mbarali 4,369 10 38,348 90 42,718 Mbeya Urb 2,637 37 4,543 63 7,180 Total 107,580 29 265,421 71 373,000 Total Number % Number % Number Chunya 101 0 38,160 100 38,262 Mbeya Rur 597 1 53,267 99 53,865 Kyela 10,613 31 23,578 69 34,192 Rungwe 4,795 7 62,528 93 67,323 Ileje 64 0 25,690 100 25,754 Mbozi 9,836 10 93,651 90 103,486 Mbarali 854 2 41,863 98 42,718 Mbeya Urb 144 2 7,036 98 7,180 Total 27,006 7 345,774 93 372,779 Total Number % Number % Number Chunya 4,726 12 33,535 88 38,262 Mbeya Rur 8,760 16 45,104 84 53,865 Kyela 2,230 7 31,962 93 34,192 Rungwe 9,049 13 58,274 87 67,323 Ileje 3,309 13 22,510 87 25,819 Mbozi 14,569 14 88,917 86 103,486 Mbarali 6,815 16 35,903 84 42,718 Mbeya Urb 2,797 39 4,383 61 7,180 Total 52,255 14 320,589 86 372,844 Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural Households Using Farm Yard Manure Number of Agricultural Households NOT Using Farm Yard Manure District Number of Agricultural Households Using Herbicides Number of Agricultural Households NOT Using Herbicides District Number of Agricultural Households Using Improved Seeds Number of Agricultural Households NOT Using Improved Seeds Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 214 Co-operative Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 3,761 10 0 0 2,664 7 0 0 0 0 0 0 0 0 0 0 0 0 31,837 83 38,262 Mbeya Rur 0 0 243 0 21,648 40 0 0 481 1 0 0 121 0 0 0 0 0 31,372 58 53,865 Kyela 0 0 0 0 1,190 3 88 0 0 0 0 0 0 0 0 0 0 0 32,914 96 34,192 Rungwe 116 0 3,681 5 9,635 14 0 0 1,731 3 116 0 230 0 1,114 2 0 0 50,700 75 67,323 Ileje 0 0 61 0 9,474 37 258 1 0 0 0 0 0 0 251 1 758 3 15,016 58 25,819 Mbozi 178 0 1,201 1 51,291 50 677 1 675 1 0 0 0 0 667 1 0 0 48,796 47 103,486 Mbarali 0 0 0 0 3,206 8 0 0 0 0 0 0 0 0 0 0 0 0 39,512 92 42,718 Mbeya Urb 0 0 74 1 4,699 65 0 0 40 1 0 0 0 0 21 0 0 0 2,346 33 7,180 Total 4,055 1 5,259 1 103,807 28 1,023 0 2,927 1 116 0 352 0 2,054 1 758 0 252,492 68 372,844 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 0 0 0 0 0 0 0 0 295 1 0 0 187 0 1,487 4 1,133 3 96 0 35,064 92 38,262 Mbeya Rur 0 0 120 0 0 0 0 0 0 0 121 0 0 0 9,372 17 3,714 7 0 0 40,537 75 53,865 Kyela 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1,253 4 694 2 0 0 32,336 94 34,283 Rungwe 0 0 348 1 464 1 0 0 109 0 0 0 464 1 28,760 43 5,994 9 47 0 31,138 46 67,323 Ileje 0 0 0 0 129 0 65 0 0 0 0 0 124 0 9,925 38 3,503 14 65 0 12,073 47 25,884 Mbozi 358 0 0 0 455 0 0 0 116 0 0 0 0 0 23,308 23 7,689 7 179 0 71,040 69 103,145 Mbarali 112 0 104 0 0 0 0 0 0 0 0 0 0 0 2,394 6 1,760 4 0 0 38,348 90 42,718 Mbeya Urb 0 0 0 0 57 1 21 0 0 0 0 0 0 0 1,906 27 653 9 0 0 4,543 63 7,180 Total 470 0 572 0 1,105 0 86 0 520 0 121 0 775 0 78,404 21 25,139 7 387 0 265,080 71 372,659 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 0 0 84 0 0 0 98 0 266 1 167 0 84 0 175 0 266 1 0 0 37,122 97 38,262 Mbeya Rur 0 0 0 0 121 0 0 0 242 0 363 1 0 0 4,221 8 485 1 0 0 48,432 90 53,865 Kyela 0 0 0 0 0 0 0 0 0 0 0 0 0 0 121 0 5,163 15 0 0 28,907 85 34,192 Rungwe 0 0 0 0 232 0 0 0 0 0 0 0 464 1 13,612 20 2,372 4 47 0 50,597 75 67,323 Ileje 0 0 0 0 194 1 0 0 0 0 0 0 0 0 8,295 32 190 1 65 0 17,074 66 25,819 Mbozi 176 0 0 0 478 0 0 0 0 0 0 0 0 0 14,448 14 3,189 3 143 0 84,711 82 103,145 Mbarali 0 0 0 0 0 0 0 0 0 0 0 0 0 0 113 0 88 0 0 0 42,517 100 42,718 Mbeya Urb 44 1 0 0 0 0 0 0 0 0 0 0 0 0 317 4 0 0 0 0 6,819 95 7,180 Total 221 0 84 0 1,025 0 98 0 508 0 531 0 547 0 41,304 11 11,752 3 255 0 316,179 85 372,503 Other Not applicable Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Large Scale Farm Development Project Crop Buyers Large Scale Farm Neighbour Neighbour Other Not applicable Locally Produced by Household Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Large Scale Farm Locally Produced by Household Locally Produced by Household Neighbour Other Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 215 Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 3,117 8 0 0 836 2 101 0 0 0 0 0 0 0 0 0 0 0 34,207 89 38,262 Mbeya Ru 116 0 0 0 16,006 30 119 0 0 0 121 0 243 0 484 1 0 0 36,775 68 53,865 Kyela 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34,101 100 34,101 Rungwe 0 0 226 0 4,588 7 0 0 115 0 0 0 116 0 0 0 47 0 62,232 92 67,323 Ileje 0 0 0 0 2,361 9 0 0 0 0 0 0 519 2 64 0 0 0 22,875 89 25,819 Mbozi 0 0 0 0 27,484 27 1,433 1 0 0 178 0 0 0 712 1 0 0 73,338 71 103,145 Mbarali 0 0 0 0 974 2 215 1 0 0 0 0 0 0 0 0 112 0 41,417 97 42,718 Mbeya Ur 0 0 24 0 3,113 43 0 0 0 0 23 0 151 2 47 1 0 0 3,822 53 7,180 Total 3,233 1 250 0 55,363 15 1,868 1 115 0 322 0 1,029 0 1,307 0 159 0 308,765 83 372,412 Local Farmers Group Local Market / Trade Store Secondar y Market Crop Buyers Locally Produced by Househol d Neighbou r Other Not applicabl e Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 101 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 38,160 100 38,262 Mbeya Ru 0 0 0 0 597 1 0 0 0 0 0 0 0 0 0 0 53,267 99 53,865 Kyela 1,378 4 91 0 8,138 24 176 1 0 0 77 0 600 2 155 0 23,578 69 34,192 Rungwe 0 0 2,068 3 2,264 3 0 0 463 1 0 0 0 0 0 0 62,528 93 67,323 Ileje 0 0 0 0 64 0 0 0 0 0 0 0 0 0 0 0 25,690 100 25,754 Mbozi 0 0 0 0 9,658 9 0 0 178 0 0 0 0 0 0 0 93,310 90 103,145 Mbarali 0 0 0 0 854 2 0 0 0 0 0 0 0 0 0 0 41,863 98 42,718 Mbeya Ur 0 0 0 0 127 2 0 0 0 0 17 0 0 0 0 0 7,036 98 7,180 Total 1,479 0 2,159 1 21,702 6 176 0 641 0 94 0 600 0 155 0 345,433 93 372,438 Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Co- operative Local Farmers Group Local Market / Trade Store Secondary Market Developmen t Project Crop Buyers Locally Produced by Household Neighbour District Other Not applicable Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Co- operative Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 216 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 1,779 28 1,510 23 1,602 25 190 3 1,343 21 6,425 Mbeya Rural 1,212 5 2,873 13 6,917 31 6,669 30 4,823 21 22,493 Kyela 70 6 393 31 176 14 410 32 229 18 1,278 Rungwe 5,214 31 1,079 6 4,004 24 3,922 24 2,404 14 16,624 Ileje 2,277 21 2,483 23 4,234 39 1,168 11 641 6 10,803 Mbozi 8,247 15 7,073 13 12,991 24 9,273 17 17,106 31 54,690 Mbarali 299 9 547 17 1,485 46 319 10 555 17 3,206 Mbeya Urban 90 2 946 20 3,555 74 243 5 0 0 4,834 Total 19,189 16 16,904 14 34,965 29 22,193 18 27,101 23 120,352 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 2,762 86 263 8 173 5 0 0 0 0 3,198 Mbeya Rur 12,014 91 843 6 355 3 0 0 0 0 13,211 Kyela 1,767 91 88 4 92 5 0 0 0 0 1,947 Rungwe 34,699 96 603 2 766 2 116 0 0 0 36,185 Ileje 12,924 94 515 4 246 2 126 1 0 0 13,811 Mbozi 28,866 90 1,385 4 1,345 4 351 1 158 0 32,105 Mbarali 4,282 98 0 0 88 2 0 0 0 0 4,369 Mbeya Urb 2,185 83 108 4 344 13 0 0 0 0 2,637 Total 99,499 93 3,804 4 3,408 3 593 1 158 0 107,463 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 1,139 100 0 0 0 0 0 0 0 0 1,139 Mbeya Rur 5,433 100 0 0 0 0 0 0 0 0 5,433 Kyela 5,284 100 0 0 0 0 0 0 0 0 5,284 Rungwe 16,335 98 163 1 229 1 0 0 0 0 16,726 Ileje 8,615 99 65 1 0 0 0 0 65 1 8,745 Mbozi 17,051 92 178 1 673 4 176 1 356 2 18,434 Mbarali 113 56 88 44 0 0 0 0 0 0 201 Mbeya Urb 320 89 0 0 41 11 0 0 0 0 361 Total 54,291 96 493 1 943 2 176 0 421 1 56,324 Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km District Less than 1 km Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 217 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 1,312 32 988 24 1,055 26 0 0 699 17 4,054 Mbeya Rur 1,329 8 1,659 10 4,983 29 4,784 28 4,336 25 17,090 Rungwe 871 17 305 6 1,463 29 922 18 1,530 30 5,091 Ileje 1,099 37 760 26 701 24 258 9 126 4 2,944 Mbozi 4,423 15 3,700 12 7,352 25 3,688 12 10,644 36 29,807 Mbarali 97 7 0 0 766 59 110 8 328 25 1,301 Mbeya Urb 289 9 834 25 2,071 62 163 5 0 0 3,358 Total 9,422 15 8,246 13 18,392 29 9,926 16 17,662 28 63,646 Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 0 0 101 100 0 0 0 0 0 0 101 Mbeya Rur 0 0 0 0 241 40 237 40 119 20 597 Kyela 1,787 17 845 8 4,185 39 3,249 31 548 5 10,613 Rungwe 1,027 21 347 7 1,462 30 1,611 34 348 7 4,795 Ileje 0 0 0 0 64 100 0 0 0 0 64 Mbozi 1,427 15 1,308 13 1,205 12 1,346 14 4,550 46 9,836 Mbarali 0 0 0 0 421 49 207 24 227 27 854 Mbeya Urb 22 15 83 57 39 27 0 0 0 0 144 Total 4,263 16 2,684 10 7,618 28 6,650 25 5,791 21 27,006 District Less than 1 km Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 218 Between 1 and 3 kmBetween 3 and 10 kBetween 10 and 20 20 km and Above Total Number % Number % Number % Number % Number % Number Chunya 2,002 42 682 14 659 14 384 8 999 21 4,726 Mbeya Rur 1,088 12 1,076 12 1,434 16 2,037 23 3,126 36 8,760 Kyela 1,732 78 0 0 0 0 498 22 0 0 2,230 Rungwe 1,329 15 1,083 12 3,367 37 1,264 14 2,007 22 9,049 Ileje 442 13 438 13 1,721 52 64 2 643 19 3,309 Mbozi 1,915 13 3,123 21 2,435 17 1,918 13 5,179 36 14,569 Mbarali 1,173 17 923 14 1,984 29 825 12 1,910 28 6,815 Mbeya Urb 228 8 838 30 1,566 56 118 4 47 2 2,797 Total 9,908 19 8,163 16 13,166 25 7,108 14 13,910 27 52,255 Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 8,005 25 18,245 57 903 3 0 0 604 2 2,400 8 0 0 1,681 5 31,837 Mbeya Rur 1,333 4 21,512 69 1,807 6 117 0 1,086 3 5,274 17 121 0 121 0 31,372 Kyela 596 2 22,732 69 73 0 71 0 703 2 8,478 26 0 0 260 1 32,914 Rungwe 2,067 4 40,478 80 462 1 0 0 845 2 1,645 3 0 0 5,202 10 50,700 Ileje 511 3 12,438 83 1,098 7 64 0 194 1 582 4 0 0 129 1 15,016 Mbozi 6,711 14 34,208 70 314 1 0 0 883 2 6,186 13 0 0 494 1 48,796 Mbarali 1,088 3 20,530 52 405 1 0 0 864 2 15,561 39 111 0 953 2 39,512 Mbeya Urb 0 0 2,148 92 41 2 13 1 0 0 96 4 0 0 47 2 2,346 Total 20,312 8 172,291 68 5,103 2 266 0 5,178 2 40,223 16 232 0 8,888 4 252,492 District Not Available Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 mbeya Appendix II 219 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 11,456 33 5,188 15 9,240 26 4,924 14 957 3 1,420 4 0 0 1,880 5 35,064 Mbeya Rur 20,708 51 3,242 8 7,329 18 2,270 6 2,825 7 3,440 8 0 0 724 2 40,537 Kyela 3,052 9 1,592 5 13,145 41 3,050 9 977 3 10,259 32 0 0 260 1 32,336 Rungwe 12,979 42 3,978 13 6,424 21 913 3 1,368 4 1,891 6 0 0 3,585 12 31,138 Ileje 6,031 50 1,605 13 2,947 24 194 2 130 1 1,037 9 0 0 128 1 12,073 Mbozi 33,664 47 7,644 11 13,405 19 5,224 7 3,653 5 4,794 7 0 0 2,998 4 71,381 Mbarali 2,350 6 2,788 7 14,937 39 4,746 12 1,997 5 11,097 29 217 1 217 1 38,348 Mbeya Urb 2,368 52 165 4 1,452 32 275 6 202 4 39 1 0 0 43 1 4,543 Total 92,608 35 26,200 10 68,879 26 21,596 8 12,108 5 33,977 13 217 0 9,835 4 265,421 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 4,978 13 4,742 13 11,780 32 6,472 17 4,779 13 1,581 4 0 0 2,790 8 37,122 Mbeya Rur 4,193 9 2,292 5 17,969 37 1,315 3 18,239 38 2,487 5 121 0 1,817 4 48,432 Kyela 2,247 8 886 3 12,212 42 2,371 8 2,872 10 8,141 28 0 0 178 1 28,907 Rungwe 4,992 10 4,625 9 11,617 23 163 0 21,861 43 1,550 3 0 0 5,789 11 50,597 Ileje 1,147 7 1,082 6 10,648 62 944 6 1,898 11 1,101 6 0 0 254 1 17,074 Mbozi 12,226 14 7,246 9 41,280 49 2,714 3 15,615 18 4,412 5 173 0 1,386 2 85,052 Mbarali 731 2 2,168 5 13,344 31 2,028 5 11,819 28 11,624 27 373 1 430 1 42,517 Mbeya Urb 972 14 150 2 2,552 37 409 6 2,593 38 105 2 0 0 37 1 6,819 Total 31,486 10 23,191 7 121,402 38 16,415 5 79,676 25 31,001 10 667 0 12,682 4 316,521 Other District Not Available Price Too High No Money to Buy Too Much Labour ReDo not Know How to UInput is of No Use Locally Produced by HOther Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour ReDo not Know How to UInput is of No Use Locally Produced by H Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 220 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 10,827 32 19,963 58 579 2 170 0 847 2 1,139 3 202 1 479 1 34,207 Mbeya Rur 1,576 4 26,579 72 2,653 7 242 1 1,784 5 3,578 10 0 0 364 1 36,775 Kyela 3,676 11 23,188 68 676 2 0 0 2,785 8 3,538 10 0 0 238 1 34,101 Rungwe 3,114 5 50,317 81 803 1 0 0 1,302 2 1,139 2 0 0 5,557 9 62,232 Ileje 3,069 13 15,511 68 1,032 5 59 0 838 4 2,109 9 0 0 257 1 22,875 Mbozi 6,531 9 53,556 73 1,138 2 0 0 1,377 2 10,226 14 0 0 851 1 73,679 Mbarali 849 2 16,825 41 1,175 3 110 0 4,299 10 17,086 41 111 0 961 2 41,417 Mbeya Urb 0 0 3,198 84 73 2 22 1 65 2 440 12 0 0 24 1 3,822 Total 29,642 10 209,137 68 8,128 3 604 0 13,297 4 39,254 13 313 0 8,731 3 309,107 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 11,896 31 23,459 61 787 2 76 0 732 2 819 2 101 0 292 1 38,160 Mbeya Rur 1,692 3 36,129 68 3,127 6 0 0 4,174 8 7,422 14 0 0 723 1 53,267 Kyela 93 0 21,532 91 344 1 0 0 870 4 409 2 82 0 249 1 23,578 Rungwe 3,109 5 49,309 79 578 1 0 0 2,490 4 1,139 2 116 0 5,788 9 62,528 Ileje 4,206 16 16,228 63 1,228 5 59 0 1,212 5 2,628 10 0 0 129 1 25,690 Mbozi 8,481 9 69,552 74 1,243 1 0 0 3,107 3 9,917 11 501 1 850 1 93,651 Mbarali 623 1 15,838 38 1,280 3 0 0 7,007 17 15,937 38 111 0 1,066 3 41,863 Mbeya Urb 115 2 6,016 86 78 1 20 0 218 3 542 8 0 0 47 1 7,036 Total 30,216 9 238,064 69 8,663 3 155 0 19,809 6 38,813 11 910 0 9,144 3 345,774 Other Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Re Do not Know How toInput is of No Use Locally Produced by Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Re Do not Know How toInput is of No Use Locally Produced byOther Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 221 Too Much Labour R Total Number % Number % Number % Number % Number % Number % Number % Number % Number Chunya 10,314 31 21,343 64 591 2 76 0 292 1 525 2 99 0 296 1 33,535 Mbeya Rur 5,695 13 35,688 79 2,173 5 356 1 360 1 711 2 0 0 121 0 45,104 Kyela 23,168 72 5,868 18 257 1 0 0 645 2 1,938 6 0 0 85 0 31,962 Rungwe 26,716 46 24,509 42 624 1 0 0 341 1 643 1 0 0 5,440 9 58,274 Ileje 4,350 19 15,874 71 1,163 5 0 0 195 1 672 3 192 1 64 0 22,510 Mbozi 14,468 16 69,690 78 1,601 2 0 0 707 1 1,601 2 0 0 851 1 88,917 Mbarali 9,265 26 18,492 52 968 3 0 0 1,093 3 5,636 16 111 0 337 1 35,903 Mbeya Urb 71 2 3,940 90 0 0 0 0 0 0 302 7 0 0 71 2 4,383 Total 94,046 29 195,404 61 7,378 2 432 0 3,633 1 12,028 4 402 0 7,266 2 320,589 Total Number % Number % Number % Number % Number Chunya 2,062 32 3,369 52 994 15 0 0 6,425 Mbeya Rur 2,517 11 15,908 71 3,605 16 463 2 22,493 Kyela 212 17 818 64 247 19 0 0 1,278 Rungwe 4,503 27 10,730 65 1,278 8 113 1 16,624 Ileje 2,308 21 7,480 69 696 6 318 3 10,803 Mbozi 17,844 33 33,467 61 2,430 4 949 2 54,690 Mbarali 1,063 33 1,418 44 612 19 113 4 3,206 Mbeya Urb 838 17 3,016 62 846 18 134 3 4,834 Total 31,348 26 76,206 63 10,709 9 2,090 2 120,352 Total Number % Number % Number % Number % Number Chunya 1,163 36 1,490 47 544 17 0 0 3,198 Mbeya Rur 2,997 23 8,888 67 1,326 10 0 0 13,211 Kyela 1,236 63 626 32 85 4 0 0 1,947 Rungwe 17,601 49 17,175 47 1,293 4 116 0 36,185 Ileje 4,677 34 7,793 56 1,341 10 0 0 13,811 Mbozi 13,144 41 17,417 54 1,372 4 172 1 32,105 Mbarali 1,614 37 1,612 37 1,031 24 112 3 4,369 Mbeya Urb 766 29 1,505 57 353 13 13 1 2,637 Total 43,198 40 56,507 53 7,345 7 413 0 107,463 Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Do not Know How to Use Locally Produced by Household Other No Money to Buy Input is of No Use Average Poor Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Excellent Price Too High Poor Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Good Average Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 222 Total Number % Number % Number % Number % Number Chunya 0 0 77 7 1,062 93 0 0 1,139 Mbeya Rur 0 0 3,616 67 1,816 33 0 0 5,433 Kyela 0 0 5,248 99 37 1 0 0 5,284 Rungwe 4,969 30 11,416 68 341 2 0 0 16,726 Ileje 1,987 23 5,859 67 898 10 0 0 8,745 Mbozi 7,392 40 9,858 53 1,007 5 177 1 18,434 Mbarali 0 0 201 100 0 0 0 0 201 Mbeya Urb 81 22 154 43 127 35 0 0 361 Total 14,428 26 36,429 65 5,289 9 177 0 56,324 Total Number % Number % Number % Number % Number Chunya 459 11 3,296 81 299 7 0 0 4,054 Mbeya Rur 2,865 17 12,559 73 1,319 8 347 2 17,090 Rungwe 1,699 33 3,393 67 0 0 0 0 5,091 Ileje 316 11 2,371 81 257 9 0 0 2,944 Mbozi 9,563 32 19,212 64 715 2 317 1 29,807 Mbarali 326 25 766 59 209 16 0 0 1,301 Mbeya Urb 289 9 2,660 79 347 10 62 2 3,358 Total 15,517 24 44,257 70 3,146 5 727 1 63,646 Total Number % Number % Number % Number % Number Chunya 1,024 22 3,106 66 596 13 0 0 4,726 Mbeya Rur 1,807 21 6,469 74 485 6 0 0 8,760 Kyela 266 12 1,964 88 0 0 0 0 2,230 Rungwe 4,623 51 4,313 48 113 1 0 0 9,049 Ileje 1,140 34 1,980 60 188 6 0 0 3,309 Mbozi 7,010 48 7,380 51 179 1 0 0 14,569 Mbarali 3,986 58 2,099 31 730 11 0 0 6,815 Mbeya Urb 897 32 1,678 60 204 7 18 1 2,797 Total 20,753 40 28,990 55 2,494 5 18 0 52,255 Good Average Does not Work Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 223 AGRICULTURAL CREDIT Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 224 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Chunya 2,017 11,208 2,616 1,027 7,464 437 182 446 7,177 32,575 Mbeya Rural 1,313 5,980 6,828 2,399 20,447 364 717 364 11,634 50,046 Kyela 958 6,853 4,552 1,413 8,929 1,068 90 122 6,960 30,945 Rungwe 813 13,668 5,743 1,743 20,189 460 0 809 19,242 62,667 Ileje 608 9,396 885 323 7,170 1,088 0 0 6,092 25,563 Mbozi' 3,998 29,423 11,311 3,854 28,221 2,855 1,746 171 20,835 102,414 Mbarali 1,719 5,263 11,690 2,936 12,674 978 429 0 5,058 40,746 Mbeya Urban 452 600 1,918 536 2,276 62 18 43 841 6,747 Total 11,878 82,391 45,545 14,231 107,370 7,312 3,183 1,954 77,839 351,703 Labour Seeds Fertilizers Agro-chemica Tools / EquipmIrrigation StrucLivestock Other Total Credits Chunya 1,571 2,079 3,295 3,097 1,571 487 0 354 12,453 Mbeya Rural 1,530 705 1,679 1,072 474 0 601 242 6,303 Kyela 1,417 1,473 0 185 254 0 0 184 3,514 Rungwe 116 115 4,426 1,456 346 0 0 116 6,575 Ileje 64 192 0 0 64 0 0 64 384 Mbozi' 0 179 357 178 358 0 0 0 1,072 Mbarali 1,445 323 106 97 599 0 0 722 3,292 Mbeya Urban 57 86 386 211 0 0 24 0 764 Total Credits 6,200 5,153 10,249 6,295 3,667 487 625 1,682 34,358 Total Number % Number % Number Chunya 5,221 92 466 8 5,687 Mbeya Rural 2,152 56 1,666 44 3,818 Kyela 2,709 83 537 17 3,246 Rungwe 3,732 80 924 20 4,657 Ileje 64 25 192 75 256 Mbozi' 1,072 100 0 0 1,072 Mbarali 1,565 79 407 21 1,971 Mbeya Urban 371 86 62 14 433 Total 16,887 80 4,254 20 21,141 Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader / Trade Store Private Individual Religious Organisation / NGO / Project Other Total Chunya 1,884 97 3,119 288 298 0 0 0 5,687 Mbeya Rural 1,663 116 243 953 243 237 364 0 3,818 Kyela 1,538 0 93 0 810 717 88 0 3,246 Rungwe 459 0 811 0 1,390 0 464 1,533 4,657 Ileje 192 0 0 64 0 0 0 0 256 Mbozi' 715 0 0 0 178 179 0 0 1,072 Mbarali 724 0 514 310 212 212 0 0 1,971 Mbeya Urban 168 17 36 41 172 0 0 0 433 Total 7,343 230 4,816 1,656 3,303 1,345 915 1,533 21,141 13.2 AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District District Source of Credit District Credit Use District Male Female 13.2a AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District 13.1a AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District District Reason for Not Using Credit 13.1b AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District Tanzania agriculture sample Census - 2003 Mbeya Appendix II 225 TREE FARMING AND AGROFORESTRY Tanzania AgricultureSample Census - 2003 Mbeya Appendix II 226 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Melicia excelsa Chunya 31 5 0 0 0 0 0 0 Mbeya Rural 0 3 0 0 11,629 27,845 6,159 . Kyela 0 0 0 0 0 3 0 14 Rungwe 0 16 0 0 12,840 16,029 14,276 103 Ileje 435 200 0 0 3,785 8,186 59,748 41 Mbozi' 746 7 0 0 6,657 3,725 21,254 60 Mbarali 101 0 0 0 0 4 0 0 Mbeya Urban 0 0 0 0 2 28,812 13 0 Total 1,313 231 0 0 34,913 84,604 101,450 218 Casurina Equisetfilia Terminalia Ivorensis Leucena Spp Azadritachta Spp Jakaranda Spp Albizia Spp Sesbania Spp Moringa Spp 0 0 . 14 0 0 0 10 0 0 . 0 0 0 0 0 0 0 . 0 0 0 0 0 248 0 2 0 11 0 0 0 0 0 . 17 0 7 . 0 0 0 . 31 0 0 7 0 0 5 . 0 0 0 0 0 0 . 700 10 0 0 0 0 248 5 702 72 11 7 7 10 Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / CoppicTotal Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Chunya 9 52 1 8 0 . 10 60 Mbeya Rural 11 1,214 2 33 99 44,389 112 45,636 Kyela 3 17 0 . 0 . 3 17 Rungwe 19 688 5 2,690 72 40,147 96 43,525 Ileje 27 3,149 13 153 83 69,117 123 72,419 Mbozi' 32 3,375 5 3,272 41 25,740 78 32,387 Mbarali 7 54 3 56 0 . 10 110 Mbeya Urban 32 2,359 7 1,304 63 25,864 102 29,527 Total 140 10,908 36 7,516 358 205,257 534 223,681 District Where Planted 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District, During the agricultural Year 2002/03- Mbeya Region 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and Number of Trees by Planting Location and District Cont…FARM TREE PLANTING: Number of Planted Trees By Species and District, During the agricultural Year 2002/03- Mbeya Region Tanzania Agriculture Sample Census - 2003 mbeya Appendix II 227 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Chunya 0 0 0 7 3 0 1 11 Mbeya Rural 50 12 0 78 1 0 2 143 Kyela 3 0 0 0 0 0 0 3 Rungwe 46 4 1 63 2 0 0 116 Ileje 108 8 0 32 2 2 5 157 Mbozi' 47 25 0 15 5 0 2 94 Mbarali 0 3 0 5 2 0 0 10 Mbeya Urban 5 3 0 97 3 0 0 108 Total 259 55 1 297 18 2 10 642 0-9 1-19 20-29 30-39 40-49 60+ Total Chunya 2,544 555 0 0 95 95 3,290 Mbeya Rural 9,043 8,226 5,058 4,196 1,323 1,318 29,164 Rungwe 5,669 3,897 3,449 348 1,274 1,159 15,797 Ileje 4,481 2,570 2,704 2,121 1,166 1,547 14,588 Mbozi' 7,835 3,742 5,775 3,187 949 1,807 23,294 Mbarali 0 0 109 0 0 0 109 Mbeya Urban 582 754 1,269 495 22 380 3,502 Total 30,154 19,744 18,364 10,347 4,830 6,305 89,744 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Chunya 0 4 0 2 2 2 1 11 Mbeya Rural 7 87 3 41 3 0 2 143 Kyela 0 1 0 2 0 0 0 3 Rungwe 22 42 1 49 2 0 0 116 Ileje 12 61 1 72 5 2 4 157 Mbozi' 13 37 0 33 7 4 0 94 Mbarali 0 2 0 2 5 0 0 9 Mbeya Urban 3 81 0 8 1 2 13 108 Total 57 315 5 209 25 10 20 641 District Distance to Community Planted Forest (km) 14.5 TREE FARMING: Second Use of Trees By District District Second Use 14.3 TREE FARMING: Number of Responses by Main Use of Trees By District for the Agricultural Year 2002/03 District Main Use 14.4 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District Tanzania Agriculture Sample Census - 2003 Mbeya 228 Appendix II 229 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 230 Total Number % Number % Number Chunya 35,124 92 3,138 8 38,262 Mbeya Rural 36,515 68 17,350 32 53,865 Kyela 2,699 8 31,493 92 34,192 Rungwe 19,459 29 47,864 71 67,323 Ileje 8,976 35 16,843 65 25,819 Mbozi' 40,558 39 62,928 61 103,486 Mbarali 5,134 12 37,583 88 42,718 Mbeya Urban 5,354 75 1,827 25 7,180 Total 153,818 41 219,026 59 372,844 Total Number % Number % Number % Number % Number % Number Chunya 2,780 8 20,898 60 10,217 29 941 3 95 0 34,931 Mbeya Rural 3,937 11 28,761 79 3,338 9 243 1 0 0 36,278 Kyela 501 20 1,457 57 486 19 90 4 0 0 2,535 Rungwe 3,001 15 14,960 77 1,498 8 0 0 0 0 19,459 Ileje 1,673 19 4,876 56 1,846 21 324 4 65 1 8,783 Mbozi' 6,712 17 29,111 72 4,417 11 175 0 143 0 40,558 Mbarali 859 17 3,248 63 921 18 106 2 0 0 5,134 Mbeya Urban 390 7 4,327 81 543 10 70 1 0 0 5,330 Total 19,852 13 107,638 70 23,266 15 1,949 1 303 0 153,008 Total Number % Number % Number % Number % Number % Number % Number Chunya 34,037 98 0 0 659 2 0 0 176 1 0 0 34,873 Mbeya Rural 27,295 76 2,411 7 590 2 1,309 4 4,061 11 486 1 36,151 Kyela 1,929 76 171 7 0 0 263 10 173 7 0 0 2,535 Rungwe 18,887 97 228 1 0 0 114 1 0 0 229 1 19,459 Ileje 7,497 84 961 11 130 1 129 1 259 3 0 0 8,976 Mbozi' 29,693 73 1,582 4 179 0 3,113 8 3,341 8 2,650 7 40,558 Mbarali 4,620 90 411 8 0 0 103 2 0 0 0 0 5,134 Mbeya Urban 4,360 82 398 8 19 0 496 9 0 0 20 0 5,292 Total 128,318 84 6,162 4 1,577 1 5,527 4 8,010 5 3,385 2 152,979 District Government Average Poor No Good Quality of service Other NGO / Development Project Cooperative Source of Crop Extension Not applicable Households Not Receiving Extension Advice 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District District Large Scale Farm 15.3 EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services By District Households Receiving Extension Advice District Very Good Good Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 231 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 33,679 0 563 0 176 0 34,419 Mbeya Rural 27,058 2,048 472 1,072 2,877 486 34,014 Kyela 950 0 0 93 0 0 1,043 Rungwe 17,079 228 0 114 0 229 17,650 Ileje 6,462 251 65 64 64 0 6,906 Mbozi' 27,567 1,408 179 2,754 2,455 2,650 37,015 Mbarali 3,984 302 0 103 0 0 4,389 Mbeya Urban 3,409 354 19 379 0 20 4,181 Total 120,188 4,592 1,298 4,580 5,573 3,385 139,617 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 16,734 500 1,055 0 183 95 18,566 Mbeya Rural 19,707 2,052 835 1,088 1,906 243 25,830 Kyela 979 0 0 169 173 0 1,321 Rungwe 9,631 573 0 114 113 576 11,007 Ileje 2,885 1,213 65 320 193 63 4,740 Mbozi' 16,203 2,116 528 1,244 1,597 5,796 27,483 Mbarali 981 0 109 103 0 204 1,398 Mbeya Urban 2,775 743 0 186 36 0 3,740 Total 69,895 7,197 2,592 3,224 4,200 6,976 94,085 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 15,346 684 964 76 0 0 17,070 Mbeya Rural 15,276 3,514 0 1,082 1,200 972 22,044 Kyela 85 0 0 0 0 0 85 Rungwe 12,929 116 0 230 0 455 13,730 Ileje 4,620 1,220 65 192 259 64 6,421 Mbozi' 10,120 4,264 179 1,422 834 7,434 24,253 Mbarali 332 111 0 0 0 313 757 Mbeya Urban 1,822 292 21 112 0 66 2,312 Total 60,530 10,201 1,229 3,113 2,294 9,304 86,671 Use of Agrochemicals 15.6 EXTENSION MESSAGES: Number of Households By Receiving Advice on Erosion Control By Source of Messages By District Erosion Control District District 15.4 EXTENSION MESSAGES: Number of Households By Receiving Advice on Plant Spacing By Source of Messages By District District Spacing 15.5 EXTENSION MESSAGES: Number of Households By Receiving Advice on Agrochemicals By Source of Messages By District Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 232 Governmen t NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 19,220 557 583 0 0 188 20,549 Mbeya Rura 17,903 3,025 599 1,211 3,598 486 26,821 Kyela 461 93 0 85 0 0 639 Rungwe 16,825 0 0 114 0 113 17,052 Ileje 5,016 1,528 130 514 129 128 7,445 Mbozi' 17,161 3,199 178 2,775 887 5,736 29,935 Mbarali 946 111 0 109 0 207 1,373 Mbeya Urba 3,312 144 21 287 19 20 3,803 Total 80,842 8,658 1,511 5,094 4,633 6,877 107,616 Governmen t NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 14,408 380 1,410 0 0 94 16,292 Mbeya Rura 20,189 1,929 1,079 1,685 3,218 607 28,707 Kyela 167 0 0 178 0 0 345 Rungwe 13,508 229 0 227 0 344 14,307 Ileje 5,185 503 194 0 129 64 6,075 Mbozi' 20,826 3,178 357 2,618 3,478 3,045 33,502 Mbarali 969 109 109 111 0 425 1,724 Mbeya Urba 2,919 1,101 18 547 0 22 4,607 Total 78,171 7,429 3,168 5,366 6,825 4,600 105,559 Governmen t NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Chunya 19,630 98 1,329 0 0 94 21,151 Mbeya Rura 21,280 2,290 474 1,080 2,267 607 27,998 Kyela 249 90 0 93 0 0 433 Rungwe 12,318 0 0 114 0 343 12,775 Ileje 4,870 380 194 0 194 0 5,638 Mbozi' 16,387 3,356 535 709 358 4,497 25,842 Mbarali 1,789 423 213 209 0 112 2,745 Mbeya Urba 2,628 811 59 513 0 0 4,011 Total 79,151 7,448 2,803 2,719 2,819 5,652 100,592 15.7 EXTENSION MESSAGES: Number of Households By Receiving Advice on Organic Fertilizers Usel By Source of Messages By District 15.8 EXTENSION MESSAGES: Number of Households By Receiving Advice on Inorganic Fertilizers Use By Source of Messages By District 15.9 EXTENSION MESSAGES: Number of Households By Receiving Advice on Use of Improved Seeds By Source of Messages By District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District District District Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 233 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 5,809 95 0 0 0 95 5,998 Mbeya Rura 5,276 121 0 120 0 1,457 6,975 Kyela 91 0 0 0 0 0 91 Rungwe 1,254 0 0 0 0 459 1,713 Ileje 374 123 0 0 0 320 817 Mbozi' 1,180 1,358 0 143 171 12,394 15,246 Mbarali 312 97 109 111 0 106 736 Mbeya Urba 641 45 0 46 0 118 851 Total 14,938 1,840 109 420 171 14,949 32,427 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 8,585 304 289 0 0 76 9,254 Mbeya Rura 9,014 243 121 235 463 1,093 11,170 Kyela 0 0 0 0 0 0 0 Rungwe 2,567 229 0 0 0 887 3,683 Ileje 1,156 764 0 192 64 189 2,365 Mbozi' 3,959 1,055 351 1,732 492 13,154 20,743 Mbarali 2,517 0 111 0 0 98 2,725 Mbeya Urba 1,437 112 29 134 43 83 1,838 Total 29,233 2,707 902 2,294 1,061 15,580 51,778 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 33,273 401 96 95 0 101 33,967 Mbeya Rura 19,330 1,203 715 1,058 4,197 729 27,232 Kyela 428 0 0 0 0 0 428 Rungwe 10,802 458 0 114 0 346 11,721 Ileje 4,734 767 65 258 259 0 6,083 Mbozi' 14,061 2,127 357 4,073 4,128 6,106 30,853 Mbarali 824 111 221 418 0 0 1,574 Mbeya Urba 2,777 93 0 126 0 37 3,034 Total 86,231 5,161 1,454 6,142 8,584 7,319 114,891 15.10 EXTENSION MESSAGES: Number of Households By Receiving Advice on Mechanization/LSF By 15.11 EXTENSION MESSAGES: Number of Households By Receiving Advice on Use of Irrigation Technology By Source of Messages By District 15.12 EXTENSION MESSAGES: Number of Households By Receiving Advice onCrop Storage By Source of Messages By District Mechanisation / LST Irrigation Technology Crop Storage District District District Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 234 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 25,730 203 340 0 0 0 26,273 Mbeya Rural 8,290 121 0 579 0 1,214 10,206 Kyela 91 0 0 0 0 0 91 Rungwe 5,187 345 0 109 229 230 6,100 Ileje 1,660 0 64 449 0 637 2,810 Mbozi' 1,675 290 0 3,921 534 14,042 20,461 Mbarali 422 0 0 0 0 98 519 Mbeya Urban 954 67 0 155 43 99 1,320 Total 44,010 1,026 404 5,214 807 16,320 67,781 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 27,498 279 193 0 0 94 28,063 Mbeya Rural 15,239 1,920 836 1,062 3,358 966 23,381 Kyela 0 0 0 0 0 0 0 Rungwe 5,802 113 0 0 0 462 6,377 Ileje 2,752 1,153 130 252 64 0 4,351 Mbozi' 2,447 1,408 321 4,634 5,278 10,987 25,075 Mbarali 519 0 111 0 0 98 728 Mbeya Urban 1,383 232 0 308 0 37 1,959 Total 55,639 5,104 1,591 6,256 8,700 12,643 89,934 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Chunya 8,685 101 268 0 0 101 9,156 Mbeya Rural 8,148 1,092 0 605 956 1,214 12,016 Kyela 0 89 0 0 0 0 89 Rungwe 7,309 343 0 0 0 346 7,997 Ileje 2,366 893 0 128 257 0 3,644 Mbozi' 4,783 2,223 0 534 0 11,451 18,991 Mbarali 0 0 109 0 0 98 207 Mbeya Urban 2,118 86 12 221 19 20 2,475 Total 33,409 4,825 390 1,488 1,232 13,230 54,574 Agro-Forestry District District 15.14 EXTENSION MESSAGES: Number of Households By Receiving Advice on agro-Processing By Source of Messages By District 15.15 EXTENSION MESSAGES: Number of Households By Receiving Advice on Afro-Forestry By Source of Messages By District District 15.13 EXTENSION MESSAGES: Number of Households By Receiving Advice on Vermin Control By Source of Messages By District Vermin Control Agro-progressing Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 235 Government NGO / Development Project Large Scale Farm Other Not applicable Total Chunya 4,473 0 0 0 101 4,574 Mbeya Rural 2,017 121 113 0 1,335 3,587 Kyela 0 0 0 0 0 0 Rungwe 230 113 0 0 230 573 Ileje 451 323 0 0 125 899 Mbozi' 1,003 638 0 178 13,710 15,528 Mbarali 0 0 0 0 98 98 Mbeya Urban 293 46 0 0 126 465 Total 8,467 1,241 113 178 15,725 25,725 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Chunya 3,884 0 0 0 196 4,080 Mbeya Rural 1,076 121 0 121 1,214 2,533 Kyela 0 0 0 0 0 0 Rungwe 116 113 0 0 230 459 Ileje 641 193 0 0 126 959 Mbozi' 356 642 0 178 14,707 15,883 Mbarali 109 0 0 0 98 207 Mbeya Urban 164 41 21 0 170 396 Total 6,347 1,109 21 300 16,741 24,518 Governmentvelopment Project Cooperative Large Scale Farm Other Not applicable Total Chunya 2,148 0 0 0 0 0 2,148 Mbeya Rural 836 0 0 0 0 0 836 Kyela 181 77 0 0 0 0 258 Rungwe 574 113 0 0 0 114 801 Ileje 323 130 65 0 0 0 517 Mbozi' 703 1,054 0 179 538 10,059 12,533 Mbarali 302 0 0 0 0 0 302 Mbeya Urban 94 0 0 0 24 60 177 Total 5,160 1,373 65 179 561 10,233 17,572 Fish Farming Other District District 15.18 EXTENSION MESSAGES: Number of Households By Receiving Advice on Other By Source of Messages By District 15.16 EXTENSION MESSAGES: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District 15.17 EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District District Beekeeping Tanzania Agriculture Sample Census -2003 Mbeya Appendix II Received Adopted % Received Adopted % Received Adopted % Chunya 34,517 33,268 96 17,022 6,092 36 16,881 10,251 61 Mbeya Rural 33,043 32,565 99 24,993 15,790 63 20,234 10,660 53 Kyela 1,043 953 91 1,321 1,022 77 85 85 100 Rungwe 17,190 16,963 99 10,433 6,410 61 13,161 10,413 79 Ileje 6,910 6,521 94 4,679 2,178 47 6,361 4,951 78 Mbozi' 34,248 33,712 98 21,509 15,505 72 15,948 11,884 75 Mbarali 4,389 3,708 84 1,300 653 50 550 221 40 Mbeya Urban 4,161 3,853 93 3,546 2,697 76 2,217 1,317 59 Total 135,502 131,543 97 84,803 50,346 59 75,436 49,781 66 Received Adopted % Received Adopted % Received Adopted % Chunya 19,974 7,939 40 16,122 7,875 49 21,180 5,709 27 Mbeya Rural 25,624 13,680 53 28,096 20,335 72 27,401 10,202 37 Kyela 639 475 74 345 178 52 433 342 79 Rungwe 16,825 15,373 91 13,849 9,994 72 12,204 7,710 63 Ileje 7,320 5,599 76 6,014 2,875 48 5,512 1,406 26 Mbozi' 23,593 15,978 68 30,459 24,697 81 21,182 9,383 44 Mbarali 1,276 648 51 1,517 546 36 2,635 1,566 59 Mbeya Urban 3,720 2,642 71 4,607 3,766 82 3,996 2,725 68 Total 98,970 62,333 63 101,009 70,266 70 94,544 39,042 41 Received Adopted % Received Adopted % Received Adopted % Chunya 25,225 22,347 89 27,708 25,213 91 7,749 4,153 54 Mbeya Rural 6,228 7,819 126 21,933 22,173 101 8,764 5,990 68 Kyela 0 0 0 0 0 0 89 0 0 Rungwe 5,642 5,414 96 5,571 5,340 96 8,104 7,189 89 Ileje 1,023 1,347 132 3,902 3,775 97 3,454 2,375 69 Mbozi' 5,641 4,592 81 14,264 13,912 98 7,104 3,394 48 Mbarali 99 208 211 411 519 126 109 109 100 Mbeya Urban 878 973 111 1,788 1,688 94 2,421 1,902 79 Total 44,736 42,700 95 75,577 72,619 96 37,795 25,113 66 Received Adopted % Received Adopted % Received Adopted % Chunya 4,378 693 16 3,984 198 5 1,486 1,083 73 Mbeya Rural 1,060 1,792 169 479 1,202 251 1,078 1,317 122 Kyela 0 0 0 0 0 0 77 77 100 Rungwe 115 0 0 116 116 100 227 337 148 Ileje 516 65 13 254 192 76 324 259 80 Mbozi' 1,388 178 13 889 178 20 1,955 1,956 100 Mbarali 0 109 0 0 0 0 105 105 100 Mbeya Urban 160 107 67 176 17 10 37 46 125 Total 7,617 2,944 39 5,899 1,903 32 5,289 5,181 98 15.22 EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region District Beekeeping Fish Farming Other District Vermin Control Agro-progressing Agro-forestry 15.21 EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed 15.19 EXTENSION MESSAGES: Number of Households By Receiving Advice on Other By Source of Messages By District 15.20 EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Messages and District for the 2002/03 Agricultural Year _ Mbeya Region Spacing Use of Agrochemicals Erosion Control District Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 237 Received Adopted % Received Adopted % Received Adopted % Chunya 5,124 939 18 6,580 2,824 43 33,870 32,148 95 Mbeya Rural 4,434 2,650 60 8,508 5,841 69 26,020 25,429 98 Kyela 0 0 0 0 0 0 428 428 100 Rungwe 341 116 34 2,035 1,569 77 11,148 9,887 89 Ileje 304 63 21 1,919 961 50 6,089 5,382 88 Mbozi' 2,734 349 13 6,733 4,831 72 25,084 24,567 98 Mbarali 627 411 66 2,628 2,634 100 1,463 1,129 77 Mbeya Urban 457 458 100 1,376 897 65 2,946 2,736 93 Total 14,021 4,986 36 29,779 19,558 66 107,048 101,706 95 15.23 EXTENSION MESSAGES: Number of Households By Receiving Advice on Other By Source of Messages By District District Mechanisation / LST Irrigation Technology Crop Storage Tanzania Agriculture Sample Census - 2003 Mbeya 238 Appendix II 239 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 240 Using Draft Animals Not Using Draft Animals Total Number % Number % Number Chunya 10,491 27 27,771 73 38,262 Mbeya Rural 4,761 9 49,104 91 53,865 Kyela 21,531 63 12,661 37 34,192 Rungwe 3,682 5 63,641 95 67,323 Ileje 567 2 25,252 98 25,819 Mbozi' 42,933 41 60,554 59 103,486 Mbarali 18,433 43 24,285 57 42,718 Mbeya Urban 822 11 6,358 89 7,180 Total 103,219 28 269,625 72 372,844 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Chunya 18,123 39,500 28,326 18,123 39,500 28,326 Mbeya Rural 6,714 11,837 6,018 6,714 11,837 6,018 Kyela 17,496 49,374 19,437 17,496 49,374 19,437 Rungwe 1,608 6,667 1,961 1,608 6,667 1,961 Ileje 120 1,134 409 120 1,134 409 Mbozi' 43,361 95,398 54,699 43,361 95,398 54,699 Mbarali 26,073 58,610 31,650 26,073 58,610 31,650 Mbeya Urban 711 1,862 795 711 1,862 795 Total 114,206 264,382 143,294 114,206 264,382 143,294 Total Number % Number % Number Chunya 2,822 2 34,818 14 37,640 Mbeya Rural 12,118 10 40,174 16 52,292 Kyela 6,232 5 27,960 11 34,192 Rungwe 38,793 32 28,531 11 67,323 Ileje 15,226 13 10,271 4 25,497 Mbozi' 39,409 32 63,721 26 103,130 Mbarali 4,353 4 38,252 15 42,606 Mbeya Urban 2,473 2 4,577 2 7,050 Total 121,427 100 248,304 100 369,730 Area (ha) % Area (ha) % Area (ha) % Chunya 2,518 4 92 0 2,610 3 Mbeya Rural 5,449 8 4,156 18 9,605 10 Kyela 1,377 2 473 2 1,849 2 Rungwe 21,758 31 6,012 26 27,770 30 Ileje 7,572 11 2,771 12 10,343 11 Mbozi' 26,476 37 9,579 41 36,055 38 Mbarali 4,444 6 173 1 4,617 5 Mbeya Urban 1,012 1 113 0 1,125 1 Total 70,606 100 23,368 100 93,975 100 Did you apply organic fertilizer during 2002/03? 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year District Using Organic Fertilizer Not Using Organic Fertilizer 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area Applied with Organic Fertilizers Type of Craft 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Oxen Total Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 241 CATTLE PRODUCTION Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 242 Herd Size Number of Household % Number of Cattle % Average Number Per Household 1-5 86,185 72 209,187 22 2 6-10 20,964 18 157,846 17 8 11-15 4,478 4 57,046 6 13 16-20 2,286 2 40,365 4 18 21-30 1,889 2 46,454 5 25 31-40 383 0 14,524 2 38 41-50 506 0 23,521 2 47 51-60 111 0 5,659 1 51 61-100 982 1 75,770 8 77 101-150 337 0 40,738 4 121 151+ 979 1 269,967 29 276 Total 119,098 100 941,077 100 8 Bulls Cows Steers Heifers Male Calves Female Calves Total Chunya . . . . . . . Mbeya Rural . . . 121 239 243 603 Kyela . . . . . . . Rungwe 805 116 . . 116 226 1,263 Ileje . . . . . . . Mbozi' . . . . 179 . 179 Mbarali . . . . . . . Mbeya Urban . . . . . . . Total 805 116 . 121 534 469 2,045 Bulls Cows Steers Heifers Male Calves Female Calves Total Chunya 11,108 57,001 16,972 30,247 11,268 12,896 139,491 Mbeya Rural 8,614 23,447 6,243 14,030 7,903 6,969 67,205 Kyela 8,432 16,589 13,312 6,889 6,272 7,601 59,095 Rungwe 9,409 33,440 1,941 20,863 9,919 11,067 86,639 Ileje 3,641 15,139 646 5,948 4,450 5,561 35,384 Mbozi' 26,537 85,560 41,228 39,912 27,474 36,155 256,867 Mbarali 26,077 75,119 39,564 66,627 34,096 45,896 287,381 Mbeya Urban 716 3,076 1,002 2,038 997 1,186 9,016 Total 94,534 309,372 120,909 186,553 102,379 127,330 941,077 18.3 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Total Cattle 18.1 Nu,mber of Households Rearing Cattle, Head of Cattle and Average Head Per Households by Head Size on 1st. October 2003 18.2 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Improved Beef Cattle Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 243 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 244 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Chunya 5,446 57,023 94.9 291 2,124 3.5 172 956 1.6 5,446 60,104 Mbeya Rural 13,782 65,119 99.5 0 0 0.0 237 357 0.5 13,902 65,476 Kyela 338 1,041 80.2 0 0 0.0 170 258 19.8 420 1,299 Rungwe 4,990 10,575 94.7 116 232 2.1 157 361 3.2 5,147 11,168 Ileje 8,903 31,200 88.0 129 3,541 10.0 194 709 2.0 8,903 35,450 Mbozi' 18,412 91,531 95.1 279 697 0.7 687 3,975 4.1 18,412 96,202 Mbarali 5,948 77,343 97.0 225 1,356 1.7 106 1,062 1.3 5,948 79,762 Mbeya Urban 1,821 8,738 93.7 46 342 3.7 41 247 2.7 1,821 9,327 Total 59,639 342,571 95.5 1,085 8,292 2.3 1,763 7,926 2.2 59,999 358,789 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Chunya 8,532 3,314 31,072 8,336 8,850 60,104 Mbeya Rural 8,227 1,411 41,205 6,892 7,741 65,476 Kyela 88 . 1,035 . 176 1,299 Rungwe 1,300 . 6,417 1,034 2,417 11,168 Ileje 2,960 771 17,383 3,983 10,353 35,450 Mbozi' 16,970 2,480 48,766 13,545 14,442 96,202 Mbarali 16,176 6,441 37,653 9,580 9,912 79,762 Mbeya Urban 923 179 5,697 1,084 1,445 9,327 Total 55,176 14,596 189,228 44,454 55,335 358,789 19.2 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 District Type 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as of 1st October, 2003 District Total Goat Indigenous Improved for Meat Improved Dairy Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 245 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Chunya . 568 1,557 . . 2,124 Mbeya Rural . . . . . . Kyela . . . . . . Rungwe . . 232 . . 232 Ileje . . . . 3,541 3,541 Mbozi' . . 139 558 . 697 Mbarali 1,133 . 224 . . 1,356 Mbeya Urban 45 . 156 141 . 342 Total 1,177 568 2,308 699 3,541 8,292 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Chunya . . . 956 . 956 Mbeya Rural . . 237 . 121 357 Kyela . . 258 . . 258 Rungwe 157 . 157 . 47 361 Ileje . 322 65 . 322 709 Mbozi' 2,594 . . 810 571 3,975 Mbarali 1,062 . . . . 1,062 Mbeya Urban . 114 . . 134 247 Total 3,813 435 716 1,767 1,194 7,926 District Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Chunya 5,446 57,023 94.9 291 2,124 3.5 172 956 1.6 5,446 60,104 Mbeya Rural 13,782 65,119 99.5 0 0 0.0 237 357 0.5 13,902 65,476 Kyela 338 1,041 80.2 0 0 0.0 170 258 19.8 420 1,299 Rungwe 4,990 10,575 94.7 116 232 2.1 157 361 3.2 5,147 11,168 Ileje 8,903 31,200 88.0 129 3,541 10.0 194 709 2.0 8,903 35,450 Mbozi' 18,412 91,531 95.1 279 697 0.7 687 3,975 4.1 18,412 96,202 Mbarali 5,948 77,343 97.0 225 1,356 1.7 106 1,062 1.3 5,948 79,762 Mbeya Urban 1,821 8,738 93.7 46 342 3.7 41 247 2.7 1,821 9,327 Total 59,639 342,571 95.5 1,085 8,292 2.3 1,763 7,926 2.2 59,999 358,789 Improved Dairy District Number of Improved Dairy 19.5 GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 Total Goat Indigenous Improved for Meat 19.3 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat 19.4 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Mbeya 246 Appendix II 247 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 248 Number % Number % Number % Ram 10,219 100 0 0 10,219 15 Castrated Shee 2,182 60 1,434 40 3,615 5 She Sheep 34,469 98 614 2 35,083 53 Male Lamb 7,047 100 0 0 7,047 11 She Lamb 8,251 82 1,815 18 10,066 15 Total 62,168 94 3,863 6 66,031 100 Number % Number % Number of Agricultural Households Sheep Keeping Households Chunya 1,415 4 36,847 96 38,262 1,415 Mbeya Rural 2,037 4 51,827 96 53,865 2,037 Kyela 269 1 33,923 99 34,192 269 Rungwe 692 1 66,631 99 67,323 692 Ileje 2,251 9 23,568 91 25,819 2,251 Mbozi' 2,119 2 101,367 98 103,486 2,119 Mbarali 2,513 6 40,204 94 42,718 2,513 Mbeya Urban 308 4 6,872 96 7,180 308 Total 11,605 3 361,240 97 372,844 11,605 Number % Number % Number % Mbarali 22,260 100 0 0 22,260 34 Mbeya Rural 12,519 100 0 0 12,519 19 Chunya 11,062 96 476 4 11,538 17 Ileje 7,153 80 1,814 20 8,966 14 Mbozi' 6,221 80 1,573 20 7,794 12 Rungwe 1,612 100 0 0 1,612 2 Mbeya Urban 1,072 100 0 0 1,072 2 Kyela 269 100 0 0 269 0 Total 62,168 94 3,863 6 66,031 100 Number of Indigenous Number of Improved for Mutton Total Sheep 20.2 SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002.0/ Agriculture Year 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 District Raising Sheep Not Raising Sheep Total District 20.1 SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year Total Sheep Number of Improved for Mutton Number of Indigenous Breed Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 249 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 6,727 59 15,398 23 2 5-9 2,067 18 11,597 18 6 10-14 2,018 18 22,764 34 11 20-24 65 1 1,362 2 21 30-39 338 3 10,142 15 30 40+ 95 1 4,768 7 50 Total 11,310 100 66,031 100 6 Ram Castrated Sheep She Sheep Male Lamb She Lamb Chunya 2,276 194 6,387 1,050 1,156 11,062 Mbeya Rural 2,131 480 7,561 946 1,402 12,519 Kyela 93 . 176 0 0 269 Rungwe 229 . 1,267 0 116 1,612 Ileje 578 452 3,542 778 1,802 7,153 Mbozi' 494 179 3,608 912 1,028 6,221 Mbarali 4,324 838 11,394 3,119 2,585 22,260 Mbeya Urban 93 39 534 242 163 1,072 Total 10,219 2,182 34,469 7,047 8,251 62,168 Ram Castrated Sheep She Sheep Male Lamb She Lamb Chunya . . 98 . 378 476 Mbeya Rural . . . . . . Kyela . . . . . . Rungwe . . . . . . Ileje . . 516 . 1,298 1,814 Mbozi' . 1,434 . . 139 1,573 Mbarali . . . . . . Mbeya Urban . . . . . . Total . 1,434 614 . 1,815 3,863 Ram Castrated Sheep She Sheep Male Lamb She Lamb Chunya 2,276 194 6,485 1,050 1,534 11,538 Mbeya Rural 2,131 480 7,561 946 1,402 12,519 Kyela 93 . 176 . . 269 Rungwe 229 . 1,267 . 116 1,612 Ileje 578 452 4,059 778 3,100 8,966 Mbozi' 494 1,613 3,608 912 1,167 7,794 Mbarali 4,324 838 11,394 3,119 2,585 22,260 Mbeya Urban 93 39 534 242 163 1,072 Total 10,219 3,615 35,083 7,047 10,066 66,031 20.5 Number of Households and Heads of Sheep by Herd Size as on 1st October 2003 20.6 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Number of Indigenous 20.7 SHEEP PRODUCTION: Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Improved for Mutton Number of Improved for Mutton 20.8 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep Total Sheep Tanzania Agriculture Sample Census - 2003 Mbeya 250 Appendix II 251 PIGS HUSBANDRY Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 252 Herd Size Number of Household % Number of Pig % Average Number Per Household 1-4 63,893 81 106,653 47 2 5-9 11,436 15 77,783 34 7 10-14 2,693 3 30,976 14 12 15-19 335 0 5,678 3 17 20-24 350 0 5,467 2 16 25-29 17 0 479 0 28 Total 78,724 100 227,036 100 3 District Number of Household Number of Pig Average Number Per Household Chunya 7,144 33,814 5 Mbeya Rural 10,846 33,535 3 Kyela 11,132 32,292 3 Rungwe 24,018 47,019 2 Ileje 4,460 7,516 2 Mbozi' 17,965 57,898 3 Mbarali 2,594 11,798 5 Mbeya Urban 565 3,164 6 Total 78,724 227,036 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Chunya 4,335 3,088 12,551 6,692 7,147 33,814 Mbeya Rural 3,355 1,758 15,454 6,582 6,386 33,535 Kyela 4,528 2,914 11,601 6,167 7,083 32,292 Rungwe 5,623 4,136 21,875 5,071 10,315 47,019 Ileje 1,089 183 3,700 886 1,658 7,516 Mbozi' 5,480 4,835 19,337 13,689 14,557 57,898 Mbarali 2,079 336 4,366 3,962 1,054 11,798 Mbeya Urban 246 351 735 675 1,156 3,164 Total 26,737 17,601 89,618 43,726 49,355 227,036 21.10 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.11 Total Number of Pigs by Type of Pigs and District as of 1st October, 2003 21.9 Number of Households Rearing Pigs, Herd of Pigs aand Average Head of per Household by Herd Size as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 253 LIVESTOCK PESTS & PARASITES CONTROL Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 254 Total Number % Number % Number Chunya 2,958 36 5,307 64 8,265 Mbeya Rur 12,118 64 6,773 36 18,891 Kyela 4,317 31 9,804 69 14,120 Rungwe 21,778 65 11,628 35 33,406 Ileje 5,949 54 4,971 46 10,919 Mbozi 20,138 57 15,397 43 35,535 Mbarali 3,148 30 7,497 70 10,645 Mbeya Urb 2,096 81 499 19 2,594 Total 72,501 54 61,874 46 134,376 No. of Households % No. of Households % No. of Households % No. of Households % Chunya 1,764 3 291 2 266 5 1,289 4 Mbeya Rur 8,294 16 3,369 26 714 14 5,149 17 Kyela 2,726 5 82 1 175 3 2,200 7 Rungwe 15,994 30 804 6 923 18 10,336 35 Ileje 4,218 8 2,685 21 1,917 37 2,688 9 Mbozi 15,439 29 4,141 32 497 10 6,745 23 Mbarali 2,176 4 769 6 439 9 753 3 Mbeya Urb 1,892 4 813 6 203 4 528 2 Total 52,504 100 12,955 100 5,134 100 29,690 100 Total Number % age Number % age Number Chunya 476 6 7,609 94 8,085 Mbeya Rur 1,667 9 16,983 91 18,650 Kyela 2,473 17 11,735 83 14,208 Rungwe 4,840 15 28,227 85 33,067 Ileje 372 3 10,476 97 10,848 Mbozi 1,882 5 34,016 95 35,898 Mbarali 1,412 13 9,451 87 10,862 Mbeya Urb 47 2 2,405 98 2,452 Total 13,168 10 120,902 90 134,070 Total Number % age Number % age Number % age Number Chunya 273 57 203 43 0 0 476 Mbeya Rur 726 44 942 56 0 0 1,667 Kyela 1,704 69 769 31 0 0 2,473 Rungwe 3,802 79 806 17 232 5 4,840 Ileje 246 66 126 34 0 0 372 Mbozi 1,766 94 116 6 0 0 1,882 Mbarali 749 53 551 39 113 8 1,412 Mbeya Urb 23 49 24 51 0 0 47 Total 9,289 71 3,535 27 344 3 13,168 District Demworming Livestock NOT Demworming Livestock 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock Goats Cattles Sheep Pigs 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District District Tsetse Flies Problems NOT Tsetse Flies Problems 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District None Spray Dipping Method of Tsetse Flies Control Tanzania Agriculture Sample Census 2003 Mbeya Appendix II 255 OTHER LIVESTOCK Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 256 Indigenous Chicken Layer Broiler Total Number of Chicken Chunya 207,975 . . 207,975 Mbeya Rur 313,544 117 . 313,661 Kyela 206,162 . . 206,162 Rungwe 349,600 23,171 232 373,004 Ileje 192,135 . . 192,135 Mbozi 984,356 25,187 171 1,009,714 Mbarali 192,945 8,953 . 201,898 Mbeya Urb 47,079 8,285 . 55,364 Total 2,493,796 65,714 402 2,559,913 Number Number of Households Number Number of Households Number Number of Households Number Number of Households Number Number of Households Chunya 16,685 2,037 0 0 2,502 373 845 176 7,828 269 Mbeya Rur 3,741 823 2,668 243 15,031 2,028 1,565 846 1,905 474 Kyela 5,419 764 0 0 169 85 7,309 178 0 0 Rungwe 13,553 834 0 0 1,939 800 0 0 0 0 Ileje 4,412 128 3,883 65 8,190 1,395 0 0 623 124 Mbozi 30,585 3,897 892 178 25,747 3,632 1,428 715 3,795 1,048 Mbarali 15,316 2,526 0 0 66,871 210 227 113 0 0 Mbeya Urb 1,881 460 94 37 1,629 223 0 0 227 48 Total 91,591 11,470 7,538 523 122,079 8,744 11,373 2,028 14,378 1,963 Number of Chicken District 23b OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District 23c OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District Donkeys Other District Ducks Turkeys Rabbits Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 257 Flock Size Number of Households % Number of Chicken % 1 - 4 82,589 32 218,676 9 5 - 9 79,651 31 508,677 20 10 - 19 63,931 25 812,012 32 20 - 29 17,290 7 390,034 15 30 - 39 6,083 2 196,672 8 40 - 49 3,376 1 141,848 6 50 - 99 2,642 1 185,128 7 100+ 826 0 106,865 4 Total 256,387 100 2,559,913 100 Number of Households % 1 - 4 82,589 32 218,676 3 5 - 9 79,651 31 508,677 6 10 - 19 63,931 25 812,012 13 20 - 29 17,290 7 390,034 23 30 - 39 6,083 2 196,672 32 40 - 49 3,376 1 141,848 42 50 - 99 2,642 1 185,128 70 100+ 826 0 106,865 129 Total 256,387 100 2,559,913 10 23d OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size 23e OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Chicken Rearing Households Flock Size Number of Chicken Average Chicken Per Household Tanzania Agriculture Sample Census - 2003 Mbeya 258 Appendix II 259 FISH FARMING Tanzania agriculture Sample Census -2003 Mbeya Appendix II 260 YES % NO % Number Chunya 84 0 38,178 100 38,262 Mbeya Rur 243 0 53,622 100 53,865 Kyela 0 0 34,192 100 34,192 Rungwe 578 1 66,745 99 67,323 Ileje 256 1 25,562 99 25,819 Mbozi 534 1 102,952 99 103,486 Mbarali 0 0 42,718 100 42,718 Mbeya Urb 17 0 7,163 100 7,180 Total 1,713 0 371,131 100 372,844 Natural Pond Dug out Pond Natural Lake Water Rervoir Total Mbeya Rur 0 364 364 Rungwe 0 924 924 Ileje 65 194 259 Mbozi 0 892 892 Mbeya Urb 0 52 52 Total 65 2,427 2,492 Own Pondment Institution NGOs / Project Neighbour Total Mbeya Rur 0 0 0 364 364 Rungwe 116 345 116 347 924 Ileje 0 0 0 259 259 Mbozi 0 358 0 534 892 Mbeya Urb 0 0 52 0 52 Total 116 704 168 1,504 2,492 Neighbor Local Market Large Scale Farms Trader at Farm Did not Sell Other Mbeya Rur 121 0 0 0 243 0 Rungwe 232 0 0 0 345 347 Ileje 65 0 0 0 194 0 Mbozi 177 0 0 357 358 0 Mbeya Urb 0 0 0 17 35 0 Total 595 0 0 374 1,175 347 District Number of Tilapia Number of Carp Number of Others Chunya 0 0 0 Mbeya Rur 41,050 0 25,504 Rungwe 122,795 0 0 Ileje 61,364 0 0 Mbozi 286,093 0 0 Mbeya Urb 18,355 0 0 Total 529,657 0 25,504 24.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year District Was Fish Farming carried out by this Household DURING 2002/03? District Systems of Fish Farming 24.2a FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year District Where Sold? 24.2c FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year 24.2b FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year 24.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year Source of Fingerling District Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 261 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 262 Total No. of Households % No. of Households % Number Chunya 9,728 25 28,534 75 38,262 5,240 14 Mbeya Rur 15,773 29 38,092 71 53,865 15,582 29 Kyela 1,726 5 32,466 95 34,192 12,968 38 Rungwe 11,560 17 55,763 83 67,323 32,441 48 Ileje 5,800 22 20,019 78 25,819 9,334 36 Mbozi 13,265 13 90,221 87 103,486 33,025 32 Mbarali 2,007 5 40,710 95 42,718 8,304 19 Mbeya Urb 2,172 30 5,008 70 7,180 2,204 31 Total 62,031 17 310,813 83 372,844 119,098 32 Government NGO / Development Project Co- operatives Large Scale Farmer Others (Former coding) Other Total Chunya 6,894 0 0 0 6,894 Mbeya Rur 7,282 239 0 237 7,758 Kyela 312 0 0 0 312 Rungwe 6,854 116 116 0 7,086 Ileje 2,236 65 0 64 2,365 Mbozi 5,995 357 0 0 6,352 Mbarali 533 0 0 0 533 Mbeya Urb 1,121 23 32 9 1,185 Total 31,228 799 148 311 32,485 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Total number of Households raising Livestock % of Receiving advice out of total Chunya 3,158 479 0 0 0 3,637 5,240 69 Mbeya Rur 2,844 239 0 116 0 3,198 15,582 21 Kyela 109 89 0 0 0 197 12,968 2 Rungwe 4,317 116 0 0 0 4,433 32,441 14 Ileje 383 65 0 0 0 448 9,334 5 Mbozi 1,622 350 0 0 178 2,150 33,025 7 Mbarali 332 0 0 0 0 332 8,304 4 Mbeya Urb 702 34 23 23 9 791 2,204 36 Total 13,467 1,371 23 139 188 15,187 119,098 13 % 89 9 0 1 1 100 District Source of Advice Proper Milking 25.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year % 25.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice and District, 2002/03 Agricultural Year District Source of Advice 25.1b LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year Received Livestock Advice Did NOT Received Livestock Advice District Total number of Households raising Livestock Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 263 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Total number of Households raising Livestock % of Receiving advice out of total Chunya 2,751 403 0 0 0 3,154 5,240 60 Mbeya Rur 2,965 121 121 237 0 3,445 15,582 22 Kyela 197 0 0 0 0 197 12,968 2 Rungwe 3,389 0 0 0 0 3,389 32,441 10 Ileje 825 65 0 0 0 890 9,334 10 Mbozi 2,190 171 178 0 0 2,539 33,025 8 Mbarali 439 0 0 0 0 439 8,304 5 Mbeya Urb 739 80 19 23 16 877 2,204 40 Total 13,496 840 319 260 16 14,930 119,098 13 % 90 6 2 2 0 100 Government NGO / Development Project Co- operatives Large Scale Farmer Other Total Chunya 5,240 0 0 0 0 5,240 5,240 100 Mbeya Rur 11,110 360 0 0 589 12,060 15,582 77 Kyela 1,476 0 0 0 0 1,476 12,968 11 Rungwe 8,263 116 0 0 0 8,379 32,441 26 Ileje 3,014 193 0 59 129 3,396 9,334 36 Mbozi 7,764 358 0 179 0 8,302 33,025 25 Mbarali 1,027 0 0 0 0 1,027 8,304 12 Mbeya Urb 1,464 23 0 47 57 1,591 2,204 72 Total 42,805 1,050 0 286 775 44,916 119,098 38 % 95 2 0 1 2 100 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Chunya 5,240 0 0 0 0 5,240 5,240 100 Mbeya Rur 2,975 121 0 0 0 3,096 15,582 20 Kyela 158 0 0 0 0 158 12,968 1 Rungwe 1,119 0 0 0 0 1,119 32,441 3 Ileje 319 65 0 0 0 384 9,334 4 Mbozi 1,311 347 0 179 0 1,837 33,025 6 Mbarali 422 0 0 0 111 533 8,304 6 Mbeya Urb 543 90 23 0 0 656 2,204 30 Total 13,039 623 23 179 111 13,976 119,098 12 % 93 4 0 1 1 100 25.1.f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year 25.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Milk Hygene 25.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Total number of Households raising Livestock % of Receiving advice out of total Source of Advice Disease Control (Dipping/spraying) District Source of Advice on Herd/Flock Size $ Selection Total number of Households raising Livestock % of Receiving advice out of total Tanzania Agriculture Sample Census- 2003 Mbeya Appendix II 264 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Chunya 2,761 0 0 0 2,761 5,240 53 Mbeya Rur 1,769 121 0 0 1,890 15,582 12 Kyela 37 0 0 0 37 12,968 0 Rungwe 1,274 116 0 0 1,390 32,441 4 Ileje 444 65 0 0 508 9,334 5 Mbozi 344 695 178 0 1,217 33,025 4 Mbarali 0 0 0 111 111 8,304 1 Mbeya Urb 308 57 0 0 365 2,204 17 Total 6,937 1,053 178 111 8,280 119,098 7 % 84 13 2 0 1 100 Government NGO / Development Project Co-operative Large Scale Farmer not applicable Total Chunya 3,883 227 81 0 4,191 5,240 80 Mbeya Rur 3,113 364 116 0 3,593 15,582 23 Kyela 125 169 0 0 295 12,968 2 Rungwe 1,566 116 0 0 1,682 32,441 5 Ileje 835 127 64 65 1,091 9,334 12 Mbozi 2,058 1,046 172 0 3,276 33,025 10 Mbarali 508 0 223 0 730 8,304 9 Mbeya Urb 664 147 0 0 811 2,204 37 Total 12,752 2,195 656 65 15,669 119,098 13 % 81 14 4 0 0 100 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Chunya 2,940 328 0 0 0 3,268 5,240 62 Mbeya Rur 4,052 360 0 0 0 4,412 15,582 28 Kyela 271 0 0 0 0 271 12,968 2 Rungwe 4,153 0 0 0 0 4,153 32,441 13 Ileje 768 129 0 0 128 1,025 9,334 11 Mbozi 2,657 179 0 172 535 3,543 33,025 11 Mbarali 111 0 0 0 0 111 8,304 1 Mbeya Urb 751 22 23 33 9 838 2,204 38 Total 15,702 1,018 23 205 673 17,620 119,098 15 % 89 6 0 1 4 100 Total number of Households raising Livestock % of Receiving advice out of total 25.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year 25.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year 25.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year Total number of Households raising Livestock % of Receiving advice out of total Source of Advice Total number of Households raising Livestock % of Receiving advice out of total District District Source of Advice District Source of Advice Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 265 Government NGO / Development Project Co- operative Large Scale Farmer Other Total Chunya 3,493 403 0 0 0 3,896 5,240 74 Mbeya Rur 4,645 360 0 121 0 5,126 15,582 33 Kyela 109 0 0 0 0 109 12,968 1 Rungwe 4,334 0 0 0 0 4,334 32,441 13 Ileje 1,418 322 0 65 0 1,806 9,334 19 Mbozi 1,847 178 178 0 178 2,382 33,025 7 Mbarali 0 0 0 0 0 0 8,304 0 Mbeya Urb 727 12 23 41 9 812 2,204 37 Total 16,573 1,276 201 227 188 18,466 119,098 16 % 90 7 1 1 1 100 Total Number % Number % Number % Number % Number % Number Chunya 902 7 6,471 54 3,497 29 913 8 250 2 12,033 Mbeya Rur 1,915 8 13,995 56 1,905 8 5,760 23 1,204 5 24,779 Kyela 89 4 1,236 62 236 12 93 5 355 18 2,008 Rungwe 2,157 18 9,435 80 162 1 0 0 0 0 11,755 Ileje 1,269 20 4,354 70 637 10 0 0 0 0 6,260 Mbozi 5,988 27 14,608 65 1,921 9 0 0 0 0 22,516 Mbarali 220 13 1,298 75 215 12 0 0 0 0 1,732 Mbeya Urb 348 13 1,941 72 370 14 46 2 0 0 2,706 Total 12,888 15 53,338 64 8,942 11 6,812 8 1,808 2 83,789 Government NGO / Development Project Co- operative Large Scale Farmer Other(form er coding) Other Total Total number of Households raising Livestock % Chunya 9,728 9,728 9,728 9,728 0 9,728 48,638 5,240 11 Mbeya Rur 15,773 15,773 15,652 15,652 0 15,652 78,500 15,582 20 Kyela 1,726 1,726 1,726 1,726 0 1,726 8,629 12,968 67 Rungwe 11,560 11,560 11,560 11,560 0 11,560 57,801 32,441 56 Ileje 5,800 5,800 5,800 5,800 0 5,800 29,001 9,334 32 Mbozi 13,265 13,086 13,086 13,086 0 13,086 65,610 33,025 50 Mbarali 2,007 1,896 2,007 1,896 0 1,896 9,702 8,304 86 Mbeya Urb 2,172 2,149 2,149 2,149 0 2,149 10,766 2,204 20 Total 62,031 61,717 61,707 61,596 0 61,596 308,647 119,098 39 % 20 20 20 20 0 20 100 Extension Provider District 29.12 Number of Agricultural Households Receiving Advice on other Extension Providers By Source and District, 2002/03 Agricultural Year District Very Good Good Average Poor No Good Quality of Service 25.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total number of Households raising Livestock % of Receiving advice out of total Tanzania Agriculture Sample Census - 2003 Mbeya 266 Appendix II 267 ACCESS TO INTRASTRUCTURE & OTHER SERVICES Tanzania Agriculture sample Census - 2003 Mbeya Apendix II 268 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Mean Chunya 1,353 4 2,961 8 7,035 18 9,970 26 16,942 44 38,262 28 Mbeya Rur 360 1 3,934 7 25,562 47 10,876 20 13,132 24 53,865 15 Kyela 246 1 2,832 8 18,240 53 11,257 33 1,616 5 34,192 9 Rungwe 1,669 2 7,347 11 34,707 52 14,499 22 9,101 14 67,323 10 Ileje 687 3 2,103 8 7,177 28 5,475 21 10,376 40 25,819 16 Mbozi 5,268 5 8,472 8 30,854 30 33,044 32 25,849 25 103,486 15 Mbarali 0 0 3,958 9 22,094 52 8,614 20 8,052 19 42,718 12 Mbeya Urb 666 9 2,568 36 3,820 53 112 2 13 0 7,180 4 Total 10,250 3 34,176 9 149,490 40 93,847 25 85,082 23 372,844 14 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Chunya 15,887 5,128 8,025 8,652 569 38,262 5 Mbeya Rur 33,193 7,404 10,112 2,913 242 53,865 2 Kyela 22,424 6,375 5,051 88 254 34,192 3 Rungwe 30,763 23,184 12,222 927 227 67,323 2 Ileje 11,521 7,014 5,243 1,851 190 25,819 3 Mbozi 57,582 16,630 18,297 8,329 2,648 103,486 4 Mbarali 24,069 6,610 9,151 880 2,008 42,718 4 Mbeya Urb 6,020 1,082 78 0 0 7,180 0 Total 201,459 73,428 68,178 23,640 6,139 372,844 3 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Chunya 28 2 5 1 54 6 114 17 26 34 106 Mbeya Rural 15 10 2 0 38 5 40 7 23 26 24 Kyela 9 2 3 1 16 4 124 5 12 14 11 Rungwe 10 2 2 1 18 4 83 7 18 22 21 Ileje 16 2 3 3 43 5 144 8 22 41 65 Mbozi 15 2 4 1 42 7 112 11 19 31 37 Mbarali 12 2 4 2 48 6 110 5 11 24 26 Mbeya Urban 4 1 0 0 10 3 11 4 11 8 4 Total 14 3 3 1 36 6 98 9 19 27 37 26.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary School District Mean Distance to District Distance (Kilometer) to ALL Wealther Road 26.2. ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year Table 26.3 : Mean distances from holders dwellings to infrustructures and services by districts Tanzania Agriculture Saample Census - 2003 Mbeya Appendix II 269 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Mean Chunya 525 1 894 2 1,578 4 1,775 5 33,490 88 38,262 54 Mbeya Rur 121 0 0 0 3,142 6 7,664 14 42,938 80 53,865 38 Kyela 0 0 937 3 6,770 20 15,229 45 11,256 33 34,192 16 Rungwe 230 0 2,421 4 21,023 31 18,783 28 24,866 37 67,323 18 Ileje 376 1 551 2 2,477 10 2,757 11 19,657 76 25,819 43 Mbozi 866 1 4,497 4 7,454 7 21,684 21 68,986 67 103,486 42 Mbarali 406 1 2,865 7 4,423 10 5,498 13 29,526 69 42,718 48 Mbeya Urb 0 0 122 2 2,631 37 4,404 61 23 0 7,180 10 Total 2,524 1 12,287 3 49,498 13 77,793 21 230,742 62 372,844 36 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Mean Chunya 8,977 23 6,231 16 12,595 33 9,794 26 665 2 38,262 6 Mbeya Rur 3,933 7 10,883 20 30,680 57 7,156 13 1,213 2 53,865 5 Kyela 5,212 15 11,275 33 16,149 47 1,289 4 267 1 34,192 4 Rungwe 3,814 6 20,092 30 38,572 57 4,382 7 463 1 67,323 4 Ileje 3,214 12 6,799 26 14,001 54 1,419 5 386 1 25,819 5 Mbozi 9,187 9 15,679 15 57,552 56 13,194 13 7,875 8 103,486 7 Mbarali 6,328 15 12,203 29 18,497 43 1,970 5 3,720 9 42,718 6 Mbeya Urb 960 13 2,436 34 3,748 52 23 0 13 0 7,180 3 Total 41,626 11 85,598 23 191,793 51 39,226 11 14,602 4 372,844 6 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Mean Chunya 14,290 15,005 8,873 0 94 38,262 2 Mbeya Rur 16,721 24,825 10,871 840 607 53,865 10 Kyela 10,397 18,601 5,103 0 90 34,192 2 Rungwe 14,324 40,927 11,493 232 348 67,323 2 Ileje 4,509 12,644 8,605 0 61 25,819 2 Mbozi 30,792 53,616 16,947 1,775 356 103,486 2 Mbarali 14,138 16,791 10,706 754 329 42,718 2 Mbeya Urb 2,790 3,480 910 0 0 7,180 1 Total 107,961 185,888 73,509 3,602 1,885 372,844 3 26.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year 26.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Hospital Distance (Kilometer) to Primary School District 26.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Health Clinic Tanzania Agriculture sample Census - 2003 Mbeya Appendix II 270 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 Total Mean Chunya 25,014 65.4 8,618 22.5 4,058 10.6 101 0.3 471 38,262 1.5 Mbeya Rur 47,784 88.7 3,854 7.2 2,227 4.1 0 0.0 0 53,865 0.4 Kyela 28,616 83.7 4,272 12.5 1,122 3.3 0 0.0 182 34,192 0.9 Rungwe 41,601 61.8 20,431 30.3 5,059 7.5 0 0.0 232 67,323 1.1 Ileje 15,048 58.3 7,536 29.2 3,107 12.0 0 0.0 127 25,819 2.6 Mbozi 77,856 75.2 18,520 17.9 5,334 5.2 1,597 1.5 179 103,486 0.8 Mbarali 34,594 81.0 5,831 13.7 1,652 3.9 222 0.5 418 42,718 2.0 Mbeya Urb 6,628 92.3 530 7.4 23 0.3 0 0.0 0 7,180 0.2 Total 277,141 74.3 69,593 18.7 22,581 6.1 1,920 0.5 1,610 372,844 1.1 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 25,014 8,618 4,058 101 471 38,262 1.5 Mbeya Rur 47,784 3,854 2,227 0 0 53,865 0.4 Kyela 28,616 4,272 1,122 0 182 34,192 0.9 Rungwe 41,601 20,431 5,059 0 232 67,323 1.1 Ileje 15,048 7,536 3,107 0 127 25,819 2.6 Mbozi 77,856 18,520 5,334 1,597 179 103,486 0.8 Mbarali 34,594 5,831 1,652 222 418 42,718 2.0 Mbeya Urb 6,628 530 23 0 0 7,180 0.2 Total 277,141 69,593 22,581 1,920 1,610 372,844 1.1 26.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year 26.8 Number of Households to Feeder Roads and District 2002/03 agricultural Year Total Mean Distances District District Distance (Kilometer) to Feeder Road Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 271 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 100 0 99 487 37,576 38,262 114 Mbeya Rur 0 0 1,447 8,149 44,269 53,865 40 Kyela 87 0 93 627 33,384 34,192 124 Rungwe 575 0 529 346 65,873 67,323 83 Ileje 0 0 64 64 25,690 25,819 144 Mbozi 178 0 0 0 103,308 103,486 112 Mbarali 281 198 106 0 42,132 42,718 110 Mbeya Urb 24 0 2,560 4,550 46 7,180 11 Total 1,246 198 4,899 14,223 352,279 372,844 98 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Chunya 197 0 289 98 37,679 38,262 106 Mbeya Rur 4,010 3,204 11,706 12,109 22,835 53,865 24 Kyela 4,135 1,685 13,927 10,663 3,783 34,192 11 Rungwe 4,928 5,927 13,813 9,662 32,992 67,323 21 Ileje 443 377 374 0 24,624 25,819 65 Mbozi 4,675 5,752 15,701 15,638 61,721 103,486 37 Mbarali 7,304 1,870 9,708 7,021 16,815 42,718 26 Mbeya Urb 915 2,524 3,568 158 16 7,180 4 Total 26,607 21,339 69,086 55,348 200,464 372,844 37 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Chunya 6,993 6,131 11,564 7,925 5,649 38,262 17 Mbeya Rur 4,191 8,867 25,422 13,572 1,813 53,865 7 Kyela 3,235 7,687 17,973 5,209 88 34,192 5 Rungwe 6,358 11,633 34,505 12,187 2,640 67,323 7 Ileje 3,108 4,954 9,991 5,584 2,182 25,819 8 Mbozi 15,952 15,628 42,237 16,000 13,669 103,486 11 Mbarali 10,102 8,868 17,070 4,339 2,338 42,718 5 Mbeya Urb 2,187 864 4,107 22 0 7,180 4 Total 52,126 64,632 162,870 64,838 28,378 372,844 9 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Chunya 5,098 3,484 4,793 5,156 19,731 38,262 34 Mbeya Rur 361 1,057 9,619 14,616 28,212 53,865 26 Kyela 407 1,513 12,454 12,888 6,930 34,192 14 Rungwe 5,651 6,139 11,726 11,312 32,495 67,323 22 Ileje 611 1,049 4,783 2,688 16,687 25,819 41 Mbozi 3,694 6,415 11,346 21,828 60,202 103,486 31 Mbarali 3,858 5,891 11,685 6,754 14,529 42,718 24 Mbeya Urb 110 913 4,256 1,875 27 7,180 8 Total 19,790 26,461 70,664 77,116 178,814 372,844 27 26.9 Number of Households to Regional Capital and District 2002/03 agricultural Year District Total Mean Distances 26.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year District 26.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year District Total Mean Distances Total Mean Distances Distance (Kilometer) to Primary Market Distance (Kilometer) to Tarmac Road 26.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Total Mean Distances Distance (Kilometer) to Tertiary Market Tanzania Agriculture sample Census - 2003 Mbeya Appendix II 272 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Chunya 725 2,541 12,459 10,173 12,364 38,262 26 Mbeya Rur 351 591 8,319 29,935 14,670 53,865 23 Kyela 9,351 5,075 7,988 7,630 4,148 34,192 12 Rungwe 9,027 5,831 8,781 39,301 4,383 67,323 18 Ileje 872 1,447 6,495 8,258 8,747 25,819 22 Mbozi 10,053 13,935 26,008 21,265 32,226 103,486 19 Mbarali 2,645 5,067 18,918 8,457 7,629 42,718 11 Mbeya Urb 2,209 0 664 4,307 0 7,180 11 Total 35,234 34,487 89,632 129,324 84,167 372,844 19 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 3,291 8.6 10,092 26.4 5,334 13.9 19,395 50.7 1,718 4.5 38,262 Mbeya Rur 472 0.9 9,566 17.8 4,557 8.5 54,743 98.4 1,778 3.3 53,865 Kyela 598 1.7 1,233 3.6 1,291 3.8 6,075 17.8 3,517 10.3 34,192 Rungwe 1,836 2.7 13,481 20.0 14,090 20.9 5,445 8.1 811 1.2 67,323 Ileje 1,328 5.1 4,923 19.1 5,583 21.6 8,484 32.9 1,231 4.8 25,819 Mbozi 6,964 6.7 15,001 14.5 10,237 9.9 19,129 18.5 11,398 11.0 103,486 Mbarali 547 1.3 3,064 7.2 1,394 3.3 104 0.2 222 0.5 42,718 Mbeya Urb 951 13.2 5,015 69.8 1,713 23.9 1,308 18.2 127 1.8 7,180 Total 15,987 4.3 62,374 16.7 44,200 11.9 114,683 30.8 20,802 5.6 372,844 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 1,539 4.0 4,624 12.1 947 2.5 3,067 8.0 95 0.2 38,262 Mbeya Rur 116 0.2 7,278 13.5 2,277 4.2 7,433 13.8 121 0.2 53,865 Kyela 82 0.2 521 1.5 344 1.0 879 2.6 773 2.3 34,192 Rungwe 572 0.8 7,741 11.5 3,123 4.6 1,041 1.5 116 0.2 67,323 Ileje 1,071 4.1 3,149 12.2 1,222 4.7 1,329 5.1 258 1.0 25,819 Mbozi 2,052 2.0 8,891 8.6 4,452 4.3 1,941 1.9 176 0.2 103,486 Mbarali 110 0.3 1,752 4.1 628 1.5 0 0.0 0 0.0 42,718 Mbeya Urb 235 3.3 2,866 39.9 506 7.0 157 2.2 34 0.5 7,180 Total 5,777 1.5 36,822 9.9 13,499 3.6 15,847 4.3 1,574 0.4 372,844 26.13 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary Market Total Mean Distances Total Number of Households 26.14 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Satisfaction of Using Extension Center Total Number of Households 26.15 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 273 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 151 0.4 966 2.5 1,216 3.2 3,726 9.7 380 1.0 38,262 Mbeya Rur 118 0.2 1,327 2.5 482 0.9 10,915 20.3 474 0.9 53,865 Kyela 264 0.8 269 0.8 0 0.0 1,145 3.3 773 2.3 34,192 Rungwe 230 0.3 1,275 1.9 2,086 3.1 463 0.7 116 0.2 67,323 Ileje 0 0.0 702 2.7 551 2.1 1,456 5.6 195 0.8 25,819 Mbozi 1,061 1.0 1,032 1.0 896 0.9 3,886 3.8 2,137 2.1 103,486 Mbarali 223 0.5 113 0.3 0 0.0 0 0.0 111 0.3 42,718 Mbeya Urb 348 4.9 493 6.9 462 6.4 259 3.6 0 0.0 7,180 Total 2,395 0.6 6,179 1.7 5,693 1.5 21,851 5.9 4,186 1.1 372,844 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 174 0.5 1,067 2.8 1,097 2.9 3,633 9.5 380 1.0 38,262 Mbeya Rur 0 0.0 364 0.7 481 0.9 11,149 20.7 354 0.7 53,865 Kyela 0 0.0 0 0.0 0 0.0 1,320 3.9 598 1.8 34,192 Rungwe 114 0.2 927 1.4 2,318 3.4 695 1.0 116 0.2 67,323 Ileje 0 0.0 512 2.0 551 2.1 1,388 5.4 195 0.8 25,819 Mbozi 523 0.5 531 0.5 0 0.0 3,036 2.9 3,207 3.1 103,486 Mbarali 0 0.0 0 0.0 113 0.3 0 0.0 111 0.3 42,718 Mbeya Urb 99 1.4 225 3.1 235 3.3 322 4.5 24 0.3 7,180 Total 911 0.2 3,625 1.0 4,794 1.3 21,543 5.8 4,985 1.3 372,844 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 174 0.5 1,255 3.3 1,097 2.9 3,642 9.5 196 0.5 38,262 Mbeya Rur 119 0.2 121 0.2 481 0.9 9,468 17.6 475 0.9 53,865 Kyela 82 0.2 0 0.0 321 0.9 967 2.8 701 2.1 34,192 Rungwe 460 0.7 694 1.0 1,970 2.9 1,391 2.1 116 0.2 67,323 Ileje 0 0.0 183 0.7 1,426 5.5 1,467 5.7 195 0.8 25,819 Mbozi 523 0.5 1,011 1.0 1,356 1.3 3,745 3.6 2,317 2.2 103,486 Mbarali 213 0.5 0 0.0 218 0.5 0 0.0 0 0.0 42,718 Mbeya Urb 45 0.6 159 2.2 371 5.2 392 5.5 69 1.0 7,180 Total 1,616 0.4 3,423 0.9 7,241 1.9 21,072 5.7 4,069 1.1 372,844 26.16 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Satisfaction of Using Research Station Total Number of Households 26.17 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year District Satisfaction of Using Plant Protection Lab Total Number of Households District Satisfaction of Using Land Registration Office Total Number of Households 26.18 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year Tanzania Agriculture sample Census-2003 Mbeya Appendix II 274 Very Good % Good % Average % Poor % No good % No. of Households No. of Households No. of Households No. of Households No. of Households Chunya 286 0.7 907 2.4 177 0.5 1,661 4.3 380 1.0 38,262 Mbeya Rur 119 0.2 121 0.2 361 0.7 7,522 14.0 234 0.4 53,865 Kyela 86 0.3 0 0.0 93 0.3 447 1.3 159 0.5 34,192 Rungwe 230 0.3 348 0.5 1,970 2.9 1,043 1.5 232 0.3 67,323 Ileje 195 0.8 255 1.0 808 3.1 1,449 5.6 195 0.8 25,819 Mbozi 703 0.7 1,164 1.1 896 0.9 3,527 3.4 2,136 2.1 103,486 Mbarali 0 0.0 0 0.0 113 0.3 0 0.0 0 0.0 42,718 Mbeya Urb 101 1.4 512 7.1 0 0.0 46 0.6 0 0.0 7,180 Total 1,718 0.5 3,307 0.9 4,420 1.2 15,695 4.2 3,336 0.9 372,844 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Using Veterinary Clinic 15,986.5 4.3 62,373.8 16.7 44,200.1 11.9 114,682.5 30.8 20,801.8 5.6 Extension Center 5,776.9 1.5 36,821.9 9.9 13,499.3 3.6 15,846.5 4.3 1,573.7 0.4 Research Station 2,395.3 0.6 6,178.6 1.7 5,692.6 1.5 21,850.6 5.9 4,185.7 1.1 Plant Protection Lab 910.8 0.2 3,625.4 1.0 4,794.5 1.3 21,543.1 5.8 4,984.9 1.3 Land Registration Office 1,616.3 0.4 3,423.5 0.9 7,240.9 1.9 21,072.4 5.7 4,069.2 1.1 Livestock Development Center 1,718.0 0.5 3,306.9 0.9 4,420.1 1.2 15,694.8 4.2 3,335.6 0.9 TYPE OF SERVICE 26.20 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of the service and district for 2002/03 agricultural Year Total Number of Households 26.19 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center District Satisfaction of Using Livestock Development Center LEVEL OF SATISFACTION OF THE SERVICE Tanzania Agriculture sample Census - 2003 Mbeya Appendix II 275 HOUSEHOLD FACILITIES Tanzania Agriculture sample Census -2003 Mbeya Appendix II 276 District No Toilet or Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Chunya 296 1,219 36,321 330 96 38,262 Mbeya Rur 1,065 6,783 45,658 358 0 53,865 Kyela 414 0 33,352 425 0 34,192 Rungwe 347 835 64,974 1,167 0 67,323 Ileje 63 647 24,155 953 0 25,819 Mbozi 2,479 3,300 96,021 1,687 0 103,486 Mbarali 1,521 940 39,392 864 0 42,718 Mbeya Urb 172 173 6,577 259 0 7,180 Total 6,357 13,898 346,449 6,044 96 372,844 District Number of rooms Iron Sheets Tiles Concrete Asbestos Grass/Lea ves Grass or Mud Other Total Households Chunya 3 11,756 280 0 0 19,736 6,490 0 38,262 Mbeya Rur 2 31,003 242 0 232 18,464 2,594 1,330 53,865 Kyela 2 10,021 86 0 0 22,888 1,197 0 34,192 Rungwe 2 28,714 225 231 0 35,373 2,317 463 67,323 Ileje 2 9,313 519 0 383 15,410 194 0 25,819 Mbozi 2 49,148 1,241 0 0 52,741 357 0 103,486 Mbarali 2 10,932 204 0 1,117 24,678 5,786 0 42,718 Mbeya Urb 3 6,405 0 0 0 568 185 23 7,180 Total 2 157,291 2,797 231 1,733 189,858 19,119 1,816 372,844 27.1: Number of Agricultural Households by Type of TOILET and District, 2002/03 Agricultural Year 27.2 : HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year Tanzania AgricultureSample Census-2003 Mbeya Appendix II 277 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 21,212 10.7 26,989 13.6 14,627 7.3 30,463 15.3 14,881 7.5 59,623 29.9 26,539 13.3 4,800 2.4 199,134 53.4 Landline phone 429 28.0 121 7.9 82 5.3 220 14.3 0 0.0 356 23.2 207 13.5 118 7.7 1,533 0.4 Mobile phone 999 14.7 1,813 26.6 742 10.9 1,214 17.8 194 2.9 924 13.6 429 6.3 487 7.2 6,803 1.8 Iron 8,158 9.2 13,015 14.7 7,620 8.6 15,422 17.4 5,276 6.0 25,765 29.1 10,643 12.0 2,757 3.1 88,656 23.8 Wheelbarrow 2,800 13.6 5,865 28.5 1,568 7.6 2,658 12.9 709 3.4 4,565 22.2 1,601 7.8 829 4.0 20,595 5.5 Bicycle 13,746 10.5 13,525 10.3 16,671 12.7 14,792 11.3 4,214 3.2 43,703 33.4 21,546 16.5 2,605 2.0 130,803 35.1 Vehicle 557 10.5 1,196 22.5 334 6.3 566 10.6 64 1.2 1,705 32.1 770 14.5 126 2.4 5,318 1.4 Television / Video 632 13.4 1,558 32.9 88 1.9 709 15.0 125 2.6 605 12.8 760 16.1 254 5.4 4,730 1.3 Total Number of Households 38,262 10.3 53,865 14.4 34,192 9.2 67,323 18.1 25,819 6.9 103,486 27.8 42,718 11.5 7,180 1.9 372,844 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Electricity 1,376.5 22.5 473.0 7.7 145.5 2.4 1,301.9 21.3 238.6 3.9 1,561.1 25.5 697.9 11.4 331.6 5.4 6,126.1 1.6 Solar 0.0 0.0 119.5 52.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 106.2 47.1 0.0 0.0 225.7 0.1 Gas (Biogas) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 23.6 100.0 23.6 0.0 Hurricane Lamp 13,593.8 13.9 14,469.2 14.8 8,421.6 8.6 12,320.3 12.6 5,413.1 5.5 24,159.4 24.7 16,427.8 16.8 2,839.7 2.9 97,644.8 26.2 Pressure Lamp 637.3 5.2 3,129.9 25.7 770.7 6.3 2,294.3 18.8 703.5 5.8 3,684.5 30.3 848.8 7.0 104.9 0.9 12,173.8 3.3 Wick Lamp 22,056.6 8.8 34,372.3 13.7 24,137.5 9.6 50,947.9 20.3 19,019.6 7.6 72,761.5 29.0 24,012.4 9.6 3,833.8 1.5 251,141.6 67.4 Candles 95.4 12.6 0.0 0.0 257.8 34.0 114.6 15.1 0.0 0.0 179.2 23.6 111.0 14.6 0.0 0.0 757.9 0.2 Firewood 404.5 8.9 1,301.1 28.6 458.6 10.1 344.1 7.6 444.1 9.7 1,140.8 25.0 414.8 9.1 46.4 1.0 4,554.5 1.2 Other 97.7 49.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 98.6 50.2 0.0 0.0 196.3 0.1 Total 38,261.7 10.3 53,864.8 14.4 34,191.8 9.2 67,323.2 18.1 25,818.8 6.9 103,486.5 27.8 42,717.6 11.5 7,180.0 1.9 372,844.3 100.0 Mbeya Urb Total Chunya 27.3 Number of Agricultural Households by Type of Owned Asset and District for 2002/03 agricultural Year Total Mbeya Urb Mbarali Mbozi Ileje Rungwe Type of Owned Asset Chunya Mbeya Rur Kyela Mbeya Rur Kyela 27.4: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year Mbarali Mbozi Type of Owned Asset Rungwe Ileje Tanzania Agriculture sample Census -2003 Mbeya Appendix II 278 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 296.9 44.9 0.0 0.0 72.0 10.9 115.9 17.5 60.9 9.2 0.0 0.0 105.9 16.0 9.4 1.4 660.9 0.2 Solar 196.6 32.3 121.4 20.0 0.0 0.0 115.9 19.1 0.0 0.0 174.0 28.6 0.0 0.0 0.0 0.0 608.0 0.2 Bottled Gas 180.8 38.7 0.0 0.0 0.0 0.0 0.0 0.0 63.9 13.7 0.0 0.0 222.8 47.7 0.0 0.0 467.5 0.1 Parraffin / Kerocine 0.0 0.0 0.0 0.0 82.0 16.4 0.0 0.0 0.0 0.0 178.1 35.6 219.7 44.0 19.8 4.0 499.6 0.1 Charcoal 1,439.7 15.2 237.6 2.5 1,806.1 19.0 999.3 10.5 625.0 6.6 2,508.8 26.4 1,482.8 15.6 403.7 4.2 9,503.1 2.5 Firewood 36,072.1 10.1 53,263.7 14.9 30,202.4 8.5 65,634.6 18.4 25,004.1 7.0 100,446.7 28.1 40,037.0 11.2 6,729.7 1.9 357,390.3 95.9 Crop Residues 0.0 0.0 120.9 3.8 2,029.1 64.1 341.5 10.8 64.9 2.0 178.9 5.6 432.0 13.6 0.0 0.0 3,167.4 0.8 Livestock Dung 0.0 0.0 121.2 26.7 0.0 0.0 115.9 25.5 0.0 0.0 0.0 0.0 217.4 47.8 0.0 0.0 454.4 0.1 Other 75.6 81.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 17.5 18.8 93.1 0.0 Total 38,261.7 10.3 53,864.8 14.4 34,191.8 9.2 67,323.2 18.1 25,818.8 6.9 103,486.5 27.8 42,717.6 11.5 7,180.0 1.9 372,844.3 100.0 Total 27.6: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year Rungwe Ileje Mbozi Mbarali Type of Owned Asset Chunya Mbeya Rur Kyela Mbeya Urb Tanzania Agriculture Sample Census -2003 Mbeya Appendix II 279 Season Chunya Mbeya Rural Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urban Piped Water Wet 8,449 8,895 22,697 11,383 4,536 5,414 20,905 4,965 Dry 8,449 8,895 22,697 11,383 4,536 5,414 20,905 4,965 Protected Well Wet 1,316 2,417 2,107 1,558 1,009 15,331 6,342 181 Dry 1,316 2,417 2,107 1,558 1,009 15,331 6,342 181 Protected / Covered Spring Wet 295 1,572 360 1,725 875 13,705 0 42 Dry 295 1,572 360 1,725 875 13,705 0 42 Uprotected Well Wet 18,093 5,093 5,920 12,573 1,462 27,286 7,819 126 Dry 18,093 5,093 5,920 12,573 1,462 27,286 7,819 126 Unprotected Spring Wet 2,179 16,375 1,063 28,600 13,082 26,004 729 1,374 Dry 2,179 16,375 1,063 28,600 13,082 26,004 729 1,374 Surface Water (Lake / Dam / River / Stream) Wet 6,377 17,992 1,809 11,322 4,790 15,631 6,727 492 Dry 6,377 17,992 1,809 11,322 4,790 15,631 6,727 492 Covered Rainwater Catchment Wet 370 121 158 0 0 0 97 0 Dry 370 121 158 0 0 0 97 0 Uncovered Rainwater Catchment Wet 95 1,174 77 163 0 116 0 0 Dry 95 1,174 77 163 0 116 0 0 Water Vendor Wet 0 227 0 0 0 0 0 0 Dry 0 227 0 0 0 0 0 0 Tanker Truck Wet 1,088 0 0 0 65 0 97 0 Dry 1,088 0 0 0 65 0 97 0 Total Agricultural Households Per District 38,262 53,865 34,192 67,323 25,819 103,486 42,718 7,180 27.8: Number of Agricultural Households by Main Source of Drinking Water during ( Wet & Dry) Seasons by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 280 Source Season Chunya Mbeya Rural Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urban Piped Water Wet 22.1 16.5 66.4 16.9 17.6 5.2 48.9 69.2 Dry 22.1 16.5 66.4 16.9 17.6 5.2 48.9 69.2 Protected Well Wet 3.4 4.5 6.2 2.3 3.9 14.8 14.8 2.5 Dry 3.4 4.5 6.2 2.3 3.9 14.8 14.8 2.5 Protected / Covered Spring Wet 0.8 2.9 1.1 2.6 3.4 13.2 0.0 0.6 Dry 0.8 2.9 1.1 2.6 3.4 13.2 0.0 0.6 Uprotected Well Wet 47.3 9.5 17.3 18.7 5.7 26.4 18.3 1.7 Dry 47.3 9.5 17.3 18.7 5.7 26.4 18.3 1.7 Unprotected Spring Wet 5.7 30.4 3.1 42.5 50.7 25.1 1.7 19.1 Dry 5.7 30.4 3.1 42.5 50.7 25.1 1.7 19.1 Surface Water (Lake / Dam / River / Stream) Wet 16.7 33.4 5.3 16.8 18.6 15.1 15.7 6.8 Dry 16.7 33.4 5.3 16.8 18.6 15.1 15.7 6.8 Covered Rainwater Catchment Wet 1.0 0.2 0.5 0.0 0.0 0.0 0.2 0.0 Dry 1.0 0.2 0.5 0.0 0.0 0.0 0.2 0.0 Uncovered Rainwater Catchment Wet 0.2 2.2 0.2 0.2 0.0 0.1 0.0 0.0 Dry 0.2 2.2 0.2 0.2 0.0 0.1 0.0 0.0 Water Vendor Wet 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 Dry 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 Tanker Truck Wet 2.8 0.0 0.0 0.0 0.3 0.0 0.2 0.0 Dry 2.8 0.0 0.0 0.0 0.3 0.0 0.2 0.0 Total Agricultural Households Per District (% age) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 27.9: Number of Agricultural Households by Main Source of Drinking Water during ( Wet & Dry) Seasons by District, 2002/03 Agricultural Year District Tanzania Agriculture sample Census -2003 Mbeya Appendix II 281 Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Less than 100m Wet 11,115.7 11,779.9 10,516.2 6,347.6 2,317.6 16,492.1 9,032.5 2,252.0 Dry 9,678.5 8,450.7 10,161.6 6,319.3 2,322.8 10,562.1 7,865.6 2,102.5 100 - 299 m Wet 2,620.1 9,972.1 4,205.9 14,913.8 7,408.4 18,248.8 13,126.9 2,268.9 Dry 2,202.9 9,860.0 4,201.8 14,598.6 6,900.7 16,478.5 11,367.3 2,058.5 300 - 499 m Wet 1,592.2 3,259.4 3,914.8 4,147.5 4,485.3 7,901.2 2,239.1 671.0 Dry 1,613.4 3,254.5 3,478.5 4,151.0 4,036.3 7,216.5 2,442.8 659.5 500 - 999 m Wet 5,954.5 6,848.0 9,797.4 18,503.9 6,846.2 22,994.2 8,869.8 1,145.0 Dry 5,376.2 5,907.2 9,454.6 18,385.1 6,780.6 24,645.7 8,747.6 1,459.8 1 - 1.99 Km Wet 10,201.9 14,711.4 4,274.5 18,357.9 4,069.9 23,662.9 6,354.7 519.1 Dry 10,462.3 14,886.7 5,068.6 18,469.1 4,010.7 25,649.9 5,784.8 538.9 2 - 2.99 Km Wet 3,725.9 4,909.4 936.3 4,477.6 564.3 8,246.5 1,802.0 285.1 Dry 3,995.4 7,266.4 842.1 4,366.2 1,455.9 10,153.2 2,766.4 285.1 3 - 4.99 Km Wet 2,747.3 2,038.1 178.2 347.7 127.0 2,771.4 1,080.0 19.3 Dry 3,773.6 3,193.4 616.2 575.0 187.0 4,196.8 2,306.0 58.6 5 - 9.99 Km Wet 202.6 119.6 368.4 227.1 0.0 3,169.4 212.6 19.6 Dry 1,059.3 1,046.0 368.4 458.9 124.9 4,229.9 1,437.2 17.1 10Km and above Wet 101.4 227.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry 100.1 0.0 0.0 0.0 0.0 353.9 0.0 0.0 27.10: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District, 2002/03 Agricultural Year Distance to Main Source of Drinking Water Season District Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 282 Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Less than 100m Wet 29.1 21.9 30.8 9.4 9.0 15.9 21.1 31.4 Dry 25.3 15.7 29.7 9.4 9.0 10.2 18.4 29.3 100 - 299 m Wet 6.8 18.5 12.3 22.2 28.7 17.6 30.7 31.6 Dry 5.8 18.3 12.3 21.7 26.7 15.9 26.6 28.7 300 - 499 m Wet 4.2 6.1 11.4 6.2 17.4 7.6 5.2 9.3 Dry 4.2 6.0 10.2 6.2 15.6 7.0 5.7 9.2 500 - 999 m Wet 15.6 12.7 28.7 27.5 26.5 22.2 20.8 15.9 Dry 14.1 11.0 27.7 27.3 26.3 23.8 20.5 20.3 1 - 1.99 Km Wet 26.7 27.3 12.5 27.3 15.8 22.9 14.9 7.2 Dry 27.3 27.6 14.8 27.4 15.5 24.8 13.5 7.5 2 - 2.99 Km Wet 9.7 9.1 2.7 6.7 2.2 8.0 4.2 4.0 Dry 10.4 13.5 2.5 6.5 5.6 9.8 6.5 4.0 3 - 4.99 Km Wet 7.2 3.8 0.5 0.5 0.5 2.7 2.5 0.3 Dry 9.9 5.9 1.8 0.9 0.7 4.1 5.4 0.8 5 - 9.99 Km Wet 0.5 0.2 1.1 0.3 0.0 3.1 0.5 0.3 Dry 2.8 1.9 1.1 0.7 0.5 4.1 3.4 0.2 10Km and above Wet 0.3 0.4 0.0 0.0 0.0 0.0 0.0 0.0 Dry 0.3 0.0 0.0 0.0 0.0 0.3 0.0 0.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 1,414 11 4,225 34 518 4 347 3 779 6 4,228 34 639 5 265 2 12,414 3.3 Two 24,859 10 40,360 16 21,411 8 35,831 14 17,201 7 87,224 34 24,664 10 4,376 2 255,926 68.6 Three 11,589 11 8,925 9 12,264 12 31,145 30 7,839 8 11,864 12 16,894 16 2,403 2 102,924 27.6 Four 399 25 355 22 0 0 0 0 0 0 171 11 520 33 135 9 1,580 0.4 Total 38,262 10 53,865 14 34,192 9 67,323 18 25,819 7 103,486 28 42,718 11 7,180 2 372,844 100.0 Mbeya Urban 27.11: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District, 2002/03 Agricultural Year Distance to Main Source of Drinking Water Season District Ileje 27.12 Number of Agricultural Households by Number of Meals Normally take Took Per Day by District During 2002/03 Agricultural Year District Number of Meals Per Day Mbozi Mbarali Chunya Mbeya Rural Kyela Rungwe Tanzania Agriculture Sample Census - 2003 Mbeya Appendix II 283 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 11,885.8 12.7 14,349.2 15.4 6,922.9 7.4 14,314.2 15.4 6,091.6 6.5 27,186.5 29.2 10,885.8 11.7 1,608.1 1.7 93,244.2 25.0 One 10,982.3 8.1 17,737.3 13.1 13,637.4 10.1 28,033.9 20.7 8,706.6 6.4 39,501.5 29.2 14,368.1 10.6 2,541.8 1.9 135,508.9 36.3 Two 9,494.8 9.9 14,476.9 15.0 8,136.1 8.5 17,565.8 18.3 8,012.6 8.3 25,053.4 26.0 11,394.7 11.8 2,097.5 2.2 96,231.6 25.8 Three 3,570.8 10.5 5,147.1 15.2 3,323.1 9.8 5,667.0 16.7 2,368.8 7.0 8,635.7 25.5 4,614.4 13.6 535.7 1.6 33,862.7 9.1 Four 1,680.0 19.3 958.9 11.0 1,792.7 20.6 1,466.2 16.9 323.7 3.7 1,411.6 16.2 867.9 10.0 187.1 2.2 8,688.2 2.3 Five 648.0 16.2 958.7 23.9 214.9 5.4 229.3 5.7 251.4 6.3 1,234.6 30.8 305.0 7.6 166.2 4.1 4,008.1 1.1 Six 0.0 0.0 118.9 27.6 128.0 29.7 0.0 0.0 0.0 0.0 0.0 0.0 184.1 42.7 0.0 0.0 431.0 0.1 Seven 0.0 0.0 117.7 13.5 36.7 4.2 46.7 5.4 64.0 7.4 463.2 53.3 97.5 11.2 43.7 5.0 869.6 0.2 Total 38,261.7 10.3 53,864.8 14.4 34,191.8 9.2 67,323.2 18.1 25,818.8 6.9 103,486.5 27.8 42,717.6 11.5 7,180.0 1.9 372,844.3 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 7972 7 23488 22 1299 1 12090 12 13478 12 35793 33 11134 10 2635 2.4 107890 29 One 7979 7 16297 15 3739 3 24098 7 7561 7 33509 30 14222 13 2540 2.3 109943 29 Two 9865 12 9538 12 9079 11 17188 5 3950 5 20232 25 9807 12 1580 1.9 81240 22 Three 4880 13 2507 7 8415 22 9369 1 509 1 7599 20 4652 12 237 0.6 38168 10 Four 2285 13 1316 8 6124 36 2693 1 191 1 2126 12 2264 13 117 0.7 17116 5 Five 1680 18 719 8 2305 25 1770 1 65 1 1937 21 637 7 70 0.8 9184 2 Six 956 31 0 0 1219 40 115 2 65 2 704 23 0 0 0 0 3059 1 Seven 2645 42 0 0 2012 32 0 0 0 0 1586 25 0 0 0 0 6242 2 Total 38,261.7 10 53,864.8 14 34,191.8 9 67,323.2 7 25,818.8 7 103,486.5 28 42,717.6 11 7,180.0 1.9 372,844.3 100 District Number of Meals Per Day Mbarali Mbeya Urb Total District Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Total 34-13: Number of Agricultural Households by Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year 34-14: Number of Agricultural Households by Number of days the household Consumed Fishduring the Preceeding Week by District, 2002/03 Agricultural Year Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Number of Meals Per Day Tanzania Agriculture Sample Census _2003 Mbeya Appendix II 284 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 21,657 10.1 27,274 12.7 18,348 8.5 49,338 22.94 15,752 7.3 55,238 25.7 23,403 10.9 4,038 1.9 215,048 57.7 Seldom 11,201 10.8 18,354 17.7 10,209 9.8 13,893 13.39 8,015 7.7 29,689 28.6 10,661 10.3 1,734 1.7 103,757 27.8 Sometimes 2,010 10.4 2,512 13.0 2,342 12.1 2,034 10.50 834 4.3 7,290 37.6 1,910 9.9 447 2.3 19,378 5.2 Often 1,646 7.1 3,577 15.5 2,079 9.0 1,260 5.45 963 4.2 8,822 38.1 4,212 18.2 589 2.5 23,149 6.2 Always 1,747 15.2 2,147 18.7 1,214 10.5 797 6.92 255 2.2 2,447 21.3 2,532 22.0 372 3.2 11,512 3.1 Total 38,262 10.3 53,865 14.4 34,192 9.2 67,323 18.06 25,819 6.9 103,486 27.8 42,718 11.5 7,180 1.9 372,844 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 10,843 6 26,182 14 22,392 12 39,065 21 15,094 8 42,189 23 25,783 14 3,207 2 184,754 50 Sale of Livestock 2,213 27 1,898 23 260 3 798 10 824 10 534 6 1,541 18 269 3 8,337 2 Sale of Livestock Products 367 10 121 3 300 8 858 24 194 5 1,128 31 322 9 329 9 3,619 1 Sales of Cash Crops 5,014 8 6,441 10 5,774 9 17,516 27 4,684 7 25,475 39 221 0 99 0 65,222 17 Sale of Forest Products 1,656 21 2,225 29 37 0 1,195 15 580 7 1,599 21 315 4 146 2 7,753 2 Business Income 6,669 16 7,422 18 1,858 4 2,349 6 1,711 4 16,810 41 3,767 9 890 2 41,478 11 Wages & Salaries in Cash 943 10 1,420 15 1,046 11 1,067 11 757 8 3,040 31 310 3 1,078 11 9,661 3 Other Casual Cash Earnings 4,939 15 6,372 19 755 2 1,419 4 1,084 3 8,678 26 9,072 27 774 2 33,093 9 Cash Remittance 101 1 1,662 21 867 11 1,708 21 194 2 2,134 27 955 12 360 5 7,981 2 Fishing 1,044 34 0 0 506 16 0 0 322 10 1,230 40 0 0 0 0 3,103 1 Other 4,474 67 121 2 85 1 884 13 373 6 670 10 0 0 28 0 6,635 2 not applicable 0 0 0 0 312 26 463 38 0 0 0 0 432 36 0 0 1,207 0 Total 38,262 10 53,865 14 34,192 9 67,323 18 25,819 7 103,486 28 42,718 11 7,180 372,844 100 Sources of Income 27.16 Number of Hoseholds by Type of Roofing Materials by District, 2002/03 Agricultural Year Mbozi Mbarali Mbeya Urb Total District Chunya Mbeya Rur 27-15: Number of Agricultural Households Reporting the status of food of the households during the Preceeding Year by District, 2002/03 Agricultural Year District Status of Food Availability Rungwe Ileje Mbozi Mbarali Chunya Mbeya Rur Kyela Total Kyela Rungwe Ileje Mbeya Urb Tanzania Agriculture Sample Census - 2003 mbeya Appendix II 285 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 11,756 7 31,003 20 10,021 6 28,714 18 9,313 6 49,148 31 10,932 7 6,405 4 157,291 42.2 Tiles 280 10 242 9 86 3 225 8 519 19 1,241 44 204 7 0 0 2,797 0.8 Concrete 0 0 0 0 0 0 231 100 0 0 0 0 0 0 0 0 231 0.1 Asbestos 0 0 232 13 0 0 0 0 383 22 0 0 1,117 64 0 0 1,733 0.5 Grass/Leaves 19,736 10 18,464 10 22,888 12 35,373 19 15,410 8 52,741 28 24,678 13 568 0 189,858 50.9 Grass & Mud 6,490 34 2,594 14 1,197 6 2,317 12 194 1 357 2 5,786 30 185 1 19,119 5.1 Other 0 0 1,330 73 0 0 463 25 0 0 0 0 0 0 23 1 1,816 0.5 Total 38,262 10 53,865 14 34,192 9 67,323 18 25,819 7 103,486 28 42,718 11 7,180 2 372,844 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 297 44.9 0 0.0 72 10.9 116 17.5 61 9.2 0 0.0 106 16.0 9 1.4 661 0 Solar 197 32.3 121 20.0 0 0.0 116 19.1 0 0.0 174 28.6 0 0.0 0 0.0 608 0 Bottled Gas 181 38.7 0 0.0 0 0.0 0 0.0 64 13.7 0 0.0 223 47.7 0 0.0 467 0 Parraffin / Kerocine 0 0.0 0 0.0 82 16.4 0 0.0 0 0.0 178 35.6 220 44.0 20 4.0 500 0 Charcoal 1,440 15.2 238 2.5 1,806 19.0 999 10.5 625 6.6 2,509 26.4 1,483 15.6 404 4.2 9,503 3 Firewood 36,072 10.1 53,264 14.9 30,202 8.5 65,635 18.4 25,004 7.0 100,447 28.1 40,037 11.2 6,730 1.9 357,390 96 Crop Residues 0 0.0 121 3.8 2,029 64.1 342 10.8 65 2.0 179 5.6 432 13.6 0 0.0 3,167 1 Livestock Dung 0 0.0 121 26.7 0 0.0 116 25.5 0 0.0 0 0.0 217 47.8 0 0.0 454 0 Other 76 81.2 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 17 18.8 93 0 Number of Households 38,262 10.3 53,865 14.4 34,192 9.2 67,323 18.1 25,819 6.9 103,486 27.8 42,718 11.5 7,180 1.9 372,844 100 Sources of Ernegy for cooking District Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Mbeya Urb Total Mbeya Urb 27.18: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year Total 27.17: HOUSEHOLD FACILITIES: Number of hoseholds type of Roofing Materials by District, 2002/03 Agricultural Year Roofing Materials District Chunya Mbeya Rur Kyela Rungwe Ileje Mbozi Mbarali Tanzania Agriculture sample Census - 2003 Mbeya 286 APPENDIX III QUESTIONNAIRES Appendix III 287 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 288 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 289 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 290 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 291 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 292 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 293 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 294 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 295 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 296 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 297 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 298 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 299 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 300 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 301 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 302 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 303 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 304 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 305 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 306 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 307 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 308 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 309 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 310 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 311 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 312 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 313 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 314 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 315 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 316 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 317 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 318 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 319 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 320 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 321 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 322 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 323 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 324 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 325 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 326 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 327 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 328 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 329 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 330 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 331 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 332 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content MEATU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT-DASIP PROGRESS REPORT 2009/2010 QUARTER IV Tel. No. 028 – 2795008, 2795006 Fax No. 028- 2795261 E-Mail meatucouncil @africaonline.co.tz Julai 14, 2008 Table of Contents 1.0 INTRODUCTION....................................................................................................... 2 2.0 ACHIEVEMENTS...................................................................................................... 2 2.1 Livestock dipping facilities....................................................................................... 2 2.2 Crop storage facilities ............................................................................................... 2 2.3 Small tractors (power tillers) .................................................................................... 2 3.0 OVERALL STATUS OF IMPLEMENTATION .................................................... 2 3.1. Village Micro Projects and Agricultural Technology Sub component.................... 3 3.2 Medium size Rural Infrastructure sub component.................................................... 3 3..3 Farmer Training Sub component ............................................................................. 3 4.0 ISSUES AND CHALLENGES .................................................................................. 3 4.1 Late fund release from PCU ..................................................................................... 3 4.2 Low community contribution spirit .......................................................................... 3 4.3 Late and/or failure to open bank accounts................................................................ 3 4.5 Drought ..................................................................................................................... 4 4.6 Money-based over expectations by PFG members................................................... 4 5.0 MEASURES TAKEN................................................................................................. 4 6.0 STRATEGIES IN THE FY 2010/2011...................................................................... 4 7.0 WAY FORWARD....................................................................................................... 4 7.1 Sustainable services from the projects................................................................... 4 7.2 Community involvement and participation ........................................................... 5 7.3 Peer knowledge and skills transfer ........................................................................ 5 List of Annexes Annex 1: Matrix of Village Micro Projects Annex 2: Matrix of Resources (Financial) Utilization Annex 3: DASIP 2009/2010 funds receipts and expenditures as at March 31, 2010 EXECUTIVE SUMMARY Most funds for implementation of investment micro projects were released towards the end of Quarter IV in the FY under review. As at June 30, 2010 the District Council Authority had received a cumulative total of Tshs. 385,438,500 from PCU. The funds were set for implementation of various activities in both Community Planning and Investment in Agriculture and Farmers Capacity Building Components as shown in the Table below. Component Sub- component Amount budgeted (Tshs) Amount received (Tshs) Amount spent (Tshs) Balance Community investment micro projects 267,414,000 180,204,500 9,127,500 171,077,000 Community planning and investment in agriculture Agriculture Technologies 116,077,000 28,923,000 28,923,000 0 Farmer Capacity Building Farmers training 92,300,000 176,311,000 157,911,000 18,400000 Total 475,791,000 385,438,500 195,961,500 189,477,000 The overall implementation status under Community investment micro projects sub component is far behind the Annual Plan of Work (APW) following non-transfer of funds from PCU. This was caused by misunderstandings between District Council Authority and PCU over expenditure of Tshs. 176,000,000 that had been erroneously transferred by PCU towards construction of Malwilo-Lingeka feeder road under Medium Scale Investments sub component. In view of the above, much time was used to chart out initiatives to break the stalemate than implement the planned projects. Following the scenario, implementation of most investment projects will start in the first Quarter of FY 2010/2011, as a consequence of late fund releases. Projects to be implemented include 3 crop storage facilities, 2 micro irrigation schemes, 1 feeder road and 1 chaco dam. Physical and financial implementation progress reports will be quarterly submitted alongside planned projects for FY 2010/2011. However, 7 small tractors (popularly known as power tillers) have been procured. The 6 tillers were procured with funds released in FY 2009/2010 and 1 with carried over funds from FY 2008/2009. 1 1.0 INTRODUCTION The main objective of the District Council in Agriculture sector is ‘Quantity and Quality of Economic Services and Infrastructures Improved’. Major activities/micro projects towards achieving this objective include construction of crop storage facilities, livestock dipping facilities, chaco dams, rural feeder roads and micro-irrigation schemes. Others include farming implements and farmers and staff capacity building. Following delayed funds releases up to the Quarter under review, the major task was to continue with supervision and monitoring of services provision for completed projects and farmers training through FFSs Methodology in 30 villages. 2.0 ACHIEVEMENTS 2.1 Livestock dipping facilities ¾ After completion of 3 livestock dipping facilities funded in FY 2007/2008 and 5 facilities funded in FY 2008/2009, a total of 28,827 head of cattle, 6,532 goats and 3,008 sheep have access to reliable dipping services at Bukundi, Mwagwila, Isengwa, Minyanda, Mwagayi, Mwakaluba, Usiulize and Lubiga villages. It is expected that livestock mortality rate from tick-borne diseases will be reduced from 75 % to 25 % by 2013. 2.2 Crop storage facilities ¾ There are 5 fully operational crop storage facilities at Mwabusalu, Mwamanongu, Mwambiti, Mwakasumbi and Paji villages. Field survey records have shown that grain post harvest losses have been reduced from an average of 60 % to 10 % where the facilities are properly used like in Mwabusalu village. 2.3 Small tractors (power tillers) ¾ Presence of small tractors is a landmark achievement in the district agro mechanization domain. It is expected that proper use and maintenance of the implements will contribute immensely towards improved agricultural production and productivity. Proper care of the implements will need to be adhered to. 3.0 OVERALL STATUS OF IMPLEMENTATION As narrated earlier, implementation of investment projects was marred by a state of lack of funds for the aforesaid reasons. Annexes 1 and 2 attached herewith show the detailed situation on a case-by-case basis as regards to physical and financial implementations. 2 3.1. Village Micro Projects and Agricultural Technology Sub component With the exception of a crop storage facility at Mwashata village, all other funded projects have not yet started. Construction of crop storage facility at Mwashata village is on the right track. The building has reached the lentel level. Funds for other projects have been transferred to village project bank accounts at Itaba, Mbushi, Mwakisandu, Lata, Bukundi and Tindabuligi villages. Invitation of tenders from eligible and reputable bidders and commencement of works are scheduled for Quarter I, 2010/2011. 3.2 Medium size Rural Infrastructure sub component The District Council Authority has earmarked project site for Irrigation Scheme at Mwagwila village with a total of 100 ha. Consultants engaged by PCU have arrived and were introduced to the Authority as a first step to put the envisaged intervention into effect. Cooperation will be extended to the consultants as required in the subsequent project development stages. 3..3 Farmer Training Sub component In this sub component, farmers’ participatory training through 180 PFGs was undertaken. The training is in the final stages, and 4,111 farmers are expected to graduate in a ceremony scheduled for July 2010. 4.0 ISSUES AND CHALLENGES The following are the recorded major challenges and issues in the FY 2009/2010. 4.1 Late fund release from PCU Late fund releases have resulted into delays and postponement of projects planned for execution as per Annual Plan of Work. 4.2 Low community contribution spirit Community members are not responsive enough towards fulfillment of their mandatory contributions for their own-identified interventions. This leads to delays in implementation and/or reduced sense of ownerships for the completed projects, e.g. there is relatively little progress in mobilization of contributions from beneficiaries for power tillers. 4.3 Late and/or failure to open bank accounts There has generally been delayed opening of bank accounts for channeling funds from PCU as directed. Most affected areas include disbursements of mini-grants and PFGs undergoing training through FFS methodology. 3 4.5 Drought This has negatively impacted on the results of FFS, most of which involved field crop enterprises. 4.6 Money-based over expectations by PFG members Some PFG members look upon FFS as an economic venture rather than a learning ground. In that sense, they would wish to divide among themselves little funds for plots inputs and other training materials than pursue training modules in the provided season- long curricula. This leads to member drop outs and poor cooperation in FFS activities. 5.0 MEASURES TAKEN During the implementation period, some coping up measures and initiatives have been taken to mitigate the effects of the above stated challenges. Some of them include: ¾ To raise Tshs. 176,000,000 from Council’s own-sources and re-channel the same to DASIP-eligible micro projects and Agriculture technologies so as to break the year-long deadlock that led to withholding of funds by PCU. ¾ To continue with sensitization campaigns towards timely contributions from community members and other beneficiaries. ¾ To procure some indispensable inputs for PFGs in order to operate in accordance with season farming calendar. Failure to do so would lead to failure of farmers’ training through FFSs in all 30 villages. ¾ To enhance persuasive strategies to PFG members to view the training as opportunity for skills and knowledge acquisition that would later bring them benefits through increased production for their farm-based enterprises. 6.0 STRATEGIES IN THE FY 2010/2011 In the FY 2010/2011, the following course of action will be adhered to. 1. To hasten implementation paces for project whose funds are available. 2. To continue with community contribution mobilization campaigns 3. To enhance participatory monitoring in project sites and periodic evaluations. 7.0 WAY FORWARD In the implementation District Agricultural Development Plan (DADP) 2010/2011, stress will be put on the following: 7.1 Sustainable services from the projects To enable the community members prepare a well-defined plan for sustainable utilization of completed projects; namely dip tanks, feeder roads and crop storage facilities. Capacity building programs for village Project Committees will be formulated and implemented in each of 30 villages. 4 7.2 Community involvement and participation To enter into memoranda of understanding with beneficiary communities in villages on modalities to ensure their compliance to contribution obligations and acquisition of quarrel-free projects sites. This will be done before funds are transferred to their respective village bank accounts. 7.3 Peer knowledge and skills transfer To ensure that knowledge and skills gained in season-long training through FFSs are transferred to farmers’ individual common fields for improved crop and livestock production. The stress will also be laid to attain a multiplier effect by using graduated farmers to train their fellow farmers. 5 | false |
# Extracted Content MEATU DISTRICT COUNCIL DISTRICT AGRICULTURE SECTOR INVESTMENT PROJECT-DASIP SEMIANNUAL PROGRESS REPORT 2008/2009 Tel. No. 028 – 2795008, 2795006 Fax No. 028- 2795261 E-Mail meatucouncil @africaonline.co.tz December 23, 2009 Table of Contents INTRODUCTION............................................................................................................. 1 2.0 PLANS IN THE 1ST HALF OF FY 2008/2009 ......................................................... 1 3.0 ACTUAL OVERALL STATUS OF IMPLEMENTATION .................................. 1 3.1. Village micro projects and Agricultural Technology Sub component .................... 1 3.2. Medium size Rural Infrastructure Sub component.................................................. 2 3.3. Farmer Training Sub component ............................................................................. 2 4.0 ISSUES AND CHALLENGES .................................................................................. 2 4.1 Poor community contribution ................................................................................... 2 4.2 Low capacity for community members to manage projects..................................... 3 4.3 Late funds transference from PCU for implementation of 2008/2009 plan ............. 3 4.4 High costs associated with preparation of micro irrigation schemes........................ 3 4.5 Incapacity of beneficiaries to contribute in cash....................................................... 3 5.0 LESSONS LEARNED................................................................................................ 3 5.1 Use of chargeable services..................................................................................... 3 5.2 Position of microprojects in agriculture sector...................................................... 4 6.0. ACTIONS TAKEN AGAINST CHALLENGING SITUATIONS........................ 4 6.1 Increased involvement of Leadership....................................................................... 4 6.2 Exploration into possibilities of co-financing........................................................... 4 6.3 Capacity Building and enhancement ....................................................................... 4 6.4 By-Laws................................................................................................................... 4 7.0 PLANS IN THE 3rd AND 4TH QUARTERS 2008/2009........................................... 4 8.0 WAY FORWARD....................................................................................................... 5 8.1 Measures to put in to use completed projects..................................................... 5 8.2 Measure to ensure community involvement, participation and contributions.... 5 List of Annexes Annex 1: General Implementation Statuses of microprojects in the 1st Half of FY 2008/2009 Annex 2: Implementation Status for Activities under Farmer Training Sub- component Quarter II -2008/2009 Annex 3: Proposed Plan and Budget for FY 2008/2009 MEATU DISTRICT COUNCIL SEMI ANNUAL PROGRESS REPORT-DASIP INTRODUCTION In the 1st Half of the year under review, the major task has been to supervise and monitor implementation process for 9 projects, whose funds were carried over from FY 2007/2008 and to inaugurate those that were completed. Parallel to this major overall activity, preparation of season long Farmer Field schools (FFSs) continued in all 30 villages covered by the Project. 2.0 PLANS IN THE 1ST HALF OF FY 2008/2009 The annual plan was to accomplish 9 2007/2008 projects, implement 21 new community investment microprojects and installation of 6 units of Agricultural Value Adding technologies for the FY 2008/2009- at a cost of Tsh.833,945,000 (community contribution inclusive). In the 1st quarter, the District Council planned to clear the backlog and commence implementation of 2008/2009 Plan in the 2nd quarter (Annex No.3). However, no funds have so far been received to date regarding implementations of micro-projects in FY 2008/2009. 3.0 ACTUAL OVERALL STATUS OF IMPLEMENTATION Implementation of projects/activities (by Sub-Components) in the semi annual period under review is as concisely depicted hereunder: 3.1. Village micro projects and agricultural technology Sub component 1. 3 Dip tanks at Mwagwila, Bukundi and Isengwa villages. 2. Construction 3 of grain storage facilities at Mwaokoli,Mwabusalu and Mwambiti villages 3. Construction of 1 micro- irrigation scheme at Mwangudo village 4. Construction of 9 km rural road stretch:Mwandulubiga – Mwagayi With the exception of micro-irrigation scheme at Mwangudo village and crop storage facility at Mwaukoli village, the rest of the projects are completed and ready for use for the intended purposes. 1 3.2. Medium size Rural Infrastructure sub component Construction of 20 km rural feeder road: Malwilo-Lingeka-Mwashata So far, 17.5 km of earthwork is completed at a cost of Tsh.176, 000,000. However; this project has been removed from the list of DASIP funded projects following settlement of misunderstandings that surrounded the transference of funds to district DASIP bank account by PCU and expenditure of the same by District Council Authority for the project in question. In effect therefore, the project is now District Council-funded and that the latter is in the process of raising funds (Tsh.176, 000,000) from other sources for re-allocation to respective villages for implementation of 2008/2009 Village Plans in accordance with PCU funding procedures. 3.3. Farmer Training Sub component In this sub component, a total of 180 Farmer Field Schools (FFSs), 6 in each of 30 DASIP-supported villages have been formed. The FFSs are meant for season-long farmer training in 2008/2009 farming season. A total of 30 Farmer Facilitators are already identified, trained and made aware of their roles and responsibilities in the course of training. Overall physical and financial statuses of implementation for micro- projects/activities are indicated in the Annexes No.1 and 2. 4.0 ISSUES AND CHALLENGES 4.1 Poor community contribution As was reported in the 1st Quarter, this has been a greater setback in timely projects completion. 2 4.2 Low capacity for community members to manage projects. This takes the form of failure and/or lack of commitment by the community members to use and manage projects after completion and inauguration. This is particularly salient in projects with service fees component e.g. dip tanks. 4.3 Late funds transference from PCU for implementation of 2008/2009 plan To date, the district council has receive no funds for implementation of micro projects set out for this FY. Now that this is the 2nd Quarter, the remaining implementation period is only quarters 3rd and 4th. If funds will not be released in early January 2009, general 2008/2009 implementation plan will be adversely disrupted. 4.4 High costs associated with preparation of micro irrigation schemes These projects require collaboration with Zonal Irrigation Technicians in the areas of reconnaissance and detailed surveys and designs. In this case, relatively large amount of funds are spent in preparatory stages at the expense of the size of real physical structures. 4.5 Incapacity of beneficiaries to contribute in cash. Implementation of projects whose nature require community members to contribute in cash is generally difficulty. Such projects take long time to completion, while others are never completed at all without bail-out from some other sources of funds. The case in point is Mwangudo micro irrigation scheme. 5.0 LESSONS LEARNED In the course of implementation, several lessons were learnt. The latter need to be tackled for improved efficiency in project implementation and sustainable management of economic and service providing projects. The following were the observed situations. 5.1 Use of chargeable services Farmers and livestock keepers are not motivated in using services that are associated with payment of service fees. This is observable in utilization of livestock dipping facilities at Isengwa na Mwajolo villages. Strategies to counteract this situation included: 5.1.1 More advocacy and sensitization campaigns to the livestock owning community segment on socio-economics associated with usage of livestock dipping infrastructure. 3 5.1.2 To advise central government on the need to increase the scale of subsidy on acaricide. The current market price for acaricide is at Tsh.19, 000- 22,000 per liter (subsidy inclusive). Alone this is a disincentive to most livestock keepers. 5.1.3 To make dipping services compulsory with punitive measures spelt out to livestock owners. 5.2 Position of microprojects in agriculture sector Microprojects in the much politicized Education and Health sectors take precedence over those in the Agriculture sector. This leads to difficulty mobilization of community human, financial and material resources to meet 20 % of 50 % contribution commitments. 6.0. ACTIONS TAKEN AGAINST CHALLENGING SITUATIONS 6.1 Increased involvement of Leadership To continue with the involvement of civic and government executive leaders at ward and village level in sensitizing community members to meet their contribution commitments 6.2 Exploration into possibilities of co-financing To continue efforts to sensitize and mobilize complementary financial resources from beneficiaries themselves at Mwangudo micro-irrigation scheme and government (Local and Central) and non governmental Institutions. 6.3 Capacity Building and enhancement To train Village Project Committee Members in project management basics on a case by case basis. 6.4 By-Laws To instigate the process of formation of by-laws that enforce compulsory accessing of various services e.g. compulsory livestock dipping. 7.0 PLANS IN THE 3rd AND 4TH QUARTERS 2008/2009 In the 2nd half of FY 2008/2009, the District Council Authority is planning to do the following: 4 7.1 To request PCU to release funds within early January, 2009 7.2 To conduct capacity strengthening course to Village Project Supervision Committees on procurement procedures at the community level 7.3 To transfer funds to the respective village bank accounts and undertake close participatory monitoring and supervision of implementation process at all villages on ‘an eyes on- hands off’ arrangements. 7.4 To implement Medium Size Community Investment projects, namely 20 km rural feeder road and irrigation scheme. 8.0 WAY FORWARD In the 2nd part of the annual implementation Plan, stress will be put on the following: 8.1 Measures to put in to use completed projects To enable the community members prepare a well-defined plan for sustainable utilization of completed projects; namely dip tanks, feeder roads and crop storage facilities. 8.2 Measure to ensure community involvement, participation and contributions To enter into memoranda of understanding with communities in villages implementing 2008/2009 micro projects on modalities to ensure their contribution and acquisition of quarrel-free projects sites. This will be done before funds are transferred to their respective village bank accounts. 5 6 | false |
# Extracted Content NOVEMBER, 2021 ACTION PLAN 2021-2031 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE NATIONAL HORTICULTURE DEVELOPMENT STRATEGY AND NOVEMBER, 2021 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE NATIONAL HORTICULTURE DEVELOPMENT STRATEGY AND ACTION PLAN 2021-2031 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 i TABLE OF CONTENTS LIST OF TABLES................................................................................................................................ iv LIST OF FIGURES.............................................................................................................................. iv PREFACE............................................................................................................................................ v FOREWORD....................................................................................................................................... vi ACRONYMS........................................................................................................................................ vii ACKNOWLEDGMENT........................................................................................................................ x EXECUTIVE SUMMARY..................................................................................................................... x 1.0 INTRODUCTION...................................................................................................................... 1 1.1 Background.............................................................................................................................. 1 1.2 Key policies and strategies supporting horticulture strategy.................................................... 2 1.2.1 Global and continental policy landscape........................................................................ 2 1.2.2 Regional policy landscape.............................................................................................. 3 1.2.3 The policy context in Tanzania........................................................................................ 3 2.0 COUNTRY PROFILE AND SITUATION ANALYSIS................................................................. 5 2.1 The horticulture industry........................................................................................................... 5 Figure 1: Horticultural clusters in Tanzania............................................................................... 5 2.1.1 Current situation of horticulture production..................................................................... 6 Table 1: Production trend of horticultural produce (Tons per year)........................................... 6 2.1.2 Importance of horticulture to the national economy........................................................ 6 Table 2: Trends in export of horticultural produce (Tones)........................................................ 6 2.1.3 Challenges in horticulture industry.................................................................................. 7 2.1.3.1 Inadequate horticultural research and training................................................. 7 2.1.3.2 Low number of professionals in horticulture..................................................... 7 Table 3: List of horticulture diploma graduates from Horti-Tengeru (2016 – 2020)................... 7 Table 4: List of horticulture diploma graduates from Borigaram (2019 – 2020)........................ 8 Table 5: Number of students graduated BSc. Horticulture for the past five years from Sokoine University of Agriculture.............................................................................................. 8 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 ii 2.1.3.3 Inadequate agricultural practices.................................................................. 8 2.1.3.4 Inadequate extension services in horticulture............................................... 8 2.1.3.5 Inadequate customer care and after-sale services....................................... 9 Figure 2: World seeds vegetable share.................................................................................... 1 0 2.1.3.6 Limited skills and interventions on pre and post-harvest management................................................................................................. 10 2.1.3.7 Low adaptation to emerging technologies and innovations.......................... 10 2.1.3.8 Inadequate marketing................................................................................... 11 2.1.3.9 Ineffective business reforms in the horticulture industry............................... 11 2.1.3.10 Low adherence to the required quality and standards.................................. 12 2.1.3.11 Low capacity to cope with the certification requirements, guarantee systems and required standards................................................................... 12 2.1.3.12 Limited control of pesticides quality and chemical residues.......................... 13 2.1.3.13 Inadequate plant health services.................................................................. 14 2.1.3.14 Weak enforcement of weight and measurement regulation.......................... 14 2.1.3.15 Potential contribution from horticulture industry in tackling public malnutrition......................................................................................... 14 2.1.3.16 Existence of few farmer organizations in the horticulture industry................ 15 2.1.3.17 Limited finance and investment in the horticulture industry.......................... 15 2.2 Strength, Weaknesses, Opportunity and Challenges in the horticulture industry..................... 15 Table 6: SWOC analysis of the horticulture industry in Tanzania.............................................. 1 6 2.3 Identification and prioritization of key strategic areas............................................................... 17 Table 7: Constraints and proposed solutions/interventions along the horticulture value chain................................................................................................................................ 18 3.0 TANZANIA HORTICULTURE DEVELOPMENT STRATEGY .................................................. 23 3.1 The strategy vision, mission, objectives and strategic interventions........................................ 23 3.1.1 The vision....................................................................................................................... 2 3 3.1.2 The mission.................................................................................................................... 2 3 3.1.3 The objectives................................................................................................................. 2 4 3.2 Scope of the strategy................................................................................................................ 24 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 iii 3.3 Description of strategic objectives............................................................................................ 25 Table 8: Recommended CSA practices and technologies for horticultural crop....................... 2 8 4.0 ACTION PLAN AND IMPLEMENTATION ARRANGEMENT (MATRIX)................................... 42 Table 9: Action plan................................................................................................................... 4 2 5.0 INSTITUTIONAL ARRANGEMENTS, COORDINATION AND FINANCIAL MANAGEMENT... 60 5.1. National implementing structure............................................................................................... 60 6.0 BUDGET................................................................................................................................... 61 6.1 Proposed sustainable sources of funds and funding mechanisms for implementation of the strategy................................................................................................. 61 Table 10: Proposed sources of funding and their target outcomes for implementation of the strategy.................................................................................................. 61 7.0 MONITORING AND EVALUATION........................................................................................... 64 Table 11: Results monitoring matrix.......................................................................................... 6 6 8.0 RISKS AND MITIGATIONS...................................................................................................... 85 Table 12: Initial risk analysis and possible contingency plans.................................................. 8 6 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 iv LIST OF TABLES Table 1: Production trend of horticultural produce (Tons per year)............................................... 9 Table 2: Trends in export of horticultural produce (Tons).............................................................. 10 Table 3: List of horticulture diploma graduates from Horti-Tengeru (2016 – 2020)....................... 11 Table 4: List of horticulture diploma graduates from Borigaram (2019 – 2020)............................ 12 Table 5: Number of students graduated BSc. Horticulture for the past five years Sokoine University of Agriculture.................................................................................... 12 Table 6: SWOC analysis of the horticulture industry in Tanzania................................................. 27 Table 7: An analysis of constraints and proposed solutions and interventions along the horticulture value chain...................................................................................................................... 28 Table 8: Recommended CSA practices and technologies for the crop subsector practices & technologies................................................................................................. 39 Table 9: Action plan...................................................................................................................... 57 Table 10: Proposed sources of funding and their target outcomes for implementation of the strategy................................................................................................................. 74 Table 11: Results monitoring matrix.................................................................................................. 78 Table 12: Initial risk analysis and possible contingency plans.......................................................... 86 LIST OF FIGURES Figure 1: Horticultural clusters in Tanzania....................................................................................... 8 Figure 2: World seed vegetable share.............................................................................................. 15 Figure 3: The four horticulture marketing model (SHEP approach)................................................. 45 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 v PREFACE The National Horticulture Development Strategy and Action Plan 2021-2031 observes the four components of the Agriculture Sector Development Programme (ASDP II) namely (i). Sustainable water and land use management; (ii). Enahanced agricultural productivity and profitability; (iii). Commercialization and value addition; and (iv). Strengtherning sector enablers. This strategy serves as a master plan to develop the horticulture industry in the country. The strategy will guide a horticultural sub-sector in the next ten years (2021-2031) towards a vibrant and sustainably competitive in the domestic, regional and international markets. The previous National Horticulture Development Strategy 2012-2021 envisaged developing a robust competitive horticultural sub-sector capable of contributing a significant amount of foreign income, reducing poverty while ensuring a sustainable supply of high-quality products for domestic, regional, and international markets. The Ministry of Agriculture has reviewed the strategy to ensure coherence direction for better alignment with the government strategic policy framework and the dynamics of horticulture industry development. The review and preparation of this document was participatory and involved a team of experts from the government and the private sector. The Ministry developed this document to be a ground-breaking step for the horticulture industry in Tanzania, giving it a new look. Therefore, all stakeholders are expected to afford their commitment to the full implementation of the strategy. The strategy’s implementation performance is expected to increase foreign income, reduction of poverty, while articulating nutrition and commercialization of the horticulture industry. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 vi FOREWORD This strategy reiterates Tanzania’s commitment to address poverty and hidden hunger, thus the horticulture industry is one of the Agriculture sub sectors with potential for eradication of poverty through increased employment opportunity. This means therefore to ensure that the horticulture sub sector attracts large investments and technologies with a view to be of commercial added value. On the other hand, horticultural crops are main source of vitamins and mineral thus combat the hidden hunger. It’s my sincere hope that the strategy will be useful in providing more insights to enable Tanzania to effectively promote and develop horticulture industry with a view to achieving sustainable development in line with the national efforts and development goals. The government is committed to effectively meet the objectives of the strategy in collaboration with private sector, development partners and all actors along the value chain. I therefore, call upon each and every one of you to participate in implementing the National Horticulture Development Strategy & Action Plan (NHDS & AP) 2021-2031. Andrew W. Massawe PERMANENT SECRETARY NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 vii ACRONYMS ASDP II Agricultural Sector Development Programme Phase II AMCOs Agricultural Marketing Cooperatives Societies ASA Agricultural Seed Agency CHAWAVIA Chama cha Wakulima wa Viungo Amani CSA Climate Smart Agriculture DCD Directorate of Crop Development DPs Development Partners EU European Unions EAC East African Community ECX Commodity Exchange markets FAOSTAT FAO Statistics GAP Good Agricultural Practices GOT Government of Tanzania GHP Good Handling Practices ICT Information and Communication Technology IPM Integrated Pest Management ISFM Integrated Soil Fertility Management LATRA Land Transport Regulatory Authority MoA Ministry of Agriculture MoE Ministry of Education MoHCDEC Ministry of Health, Community Development, Gender, Elderly & Children MUHAS Muhimbili University of Health and Allied Sciences MRLs Maximum Residue Limits MT Metric Tonnes MVIKHO Mtandao wa Vikundi vya Kilimo cha Horticulture - Arumeru DC MVIWATA Mtandao wa Vikundi vya Wakulima Tanzania NAP National Agricultural Policy NMNAP National Multi-Sector Nutritional Action Plan NIMR National Institute for Medical Research NHIDS National Horticulture Industry Development Strategy NM-AIST Nelson Mandela African Institute of Science and Technology NSGRP National Strategy for Growth and Reduction of Poverty PO-RALG President’s Office – Regional Administration and Local Government SACCOs Saving and Credit Cooperatives Societies SADC Southern African Development Cooperation SAT Sustainable Agriculture Tanzania SDGs Sustainable Development Goals SWOC Strengths Weaknesses Opportunities and Challenges SIA Strategic Intervention Areas SHEP Small-scale Horticultural Empowerment and Promotion NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 viii SUA Sokoine University of Agriculture TAA Tanzania Airport Authority TADB Tanzania Agricultural Development Bank TAFOPA Tanzania Food Processors Association TANESCO Tanzania Electrical Supply Company TANROADS Tanzania National Roads Agency TAVFs Traditional African Vegetables and Fruits TARI Tanzania Agricultural Research Institute TARURA Tanzania Rural & Urban Roads Agency TASPA Tanzania Spice Processors Association TBS Tanzania Bureau of Standards TCDC Tanzania Cooperatives Development Commission TCRA Tanzania Communications Regulatory Authority TFNC Tanzania Food & Nutrition Centre TFRA Tanzania Fertilizer Regulatory Authority TMX Tanzania Mercantile Exchange TOSCI Tanzania Official Seed Certification Insititute TPA Tanzania Port Authority TPSF Tanzania Private Sector Foundation TIC Tanzania Investment Centre TIRA Tanzania Insurance Regulatory Authority TDV Tanzania Development Vision R & D Research and Development TVET Technical Vocational Education Training systems UDSM University of Dar es Salaam ULT Usambara Lishe Trust URT United Republic of Tanzania UWAMARU Umoja wa Wakulima wa Maparachichi Rungwe VETA Vocational Education and Training Authority WHO World Health Organisation WVC World Vegetable Centre NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 ix ACKNOWLEDGMENT The preparation of this National Horticulture Development Strategy and Action Plan 2021-2031 involved many stakeholders. Firstly, our word of gratitude goes to the Agriculture Sector Lead Ministries for technical and administrative support and contribution. Secondly, to all key actors within the horticulture value chain, including the farmers, traders, extension workers, and researchers whose efforts were vital to the success of the undertaking. Thirdly, to the Institutions that actively provided vital information that enriched the content of the strategy. We sincerely register our special thanks to the WORLD VEGETABLE CENTRE, HORTI-Tengeru, European Union funded AGRI-CONNECT programme, TAHA, Sustainable Agriculture Trust, Tanzania Bureau of Standards, HELVETAS, Sokoine University of Agriculture, Tanzania Agricultural Development Bank, and Regional Secretariats of Kilimanjaro and Arusha for their technical and financial support throughout the preparation of this strategy. Finally, we kindly acknowledge all who, at different stages, assisted in making the entire task a success. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 x EXECUTIVE SUMMARY The drive for the preparation of the National Horticulture Development Strategy and Action Plan 2021– 2031 responds to the least increasing rate of horticulture economic development. The strategy addresses the low production and productivity as a significant huddle leading to dismal performance of the industry in the domestic, regional and international markets and addresses the Tanzania industrialisation agenda. Therefore, the horticultural industry has to respond to the impacts of the changing horticulture international markets by increasing quality produce production through small and large-scale farmers. The National Horticulture Development Strategy and Action Plan 2021-2031 (NHDS & AP) is comprised of eight (8) strategic objectives broken down into thirty-three (33) interventions which have hundred and fifteen (115) actions carefully planned to bring an increase in production and productivity to satisfy the domestic consumption and contribute to the export demand. This increase in the production of horticultural commodities will enable Tanzania to benefit from the local and international available market opportunities. The NHDS & AP 2021-2031 is prepared to replace the previous Tanzania Horticulture Development Strategy of 2012-2021 by improving the inadequacies and taking on board the current development agenda as stated in various sector documents enhance the sectoral performance. Currently, the horticulture industry contributes 38% of the total agricultural sector foreign exchange earnings. However, the Tanzanian horticulture industry can contribute far beyond similar to other countries in the region. The development of this strategy responds to the above-stated needs by ensuring that there is more coordination and complementarity between key horticulture economic sectors and stakeholders in implementing strategic activities. Moreover, this strategy makes it easier for the country to benefit from the horticulture market and opportunities while contributing significantly to the community economy and peoples’ livelihood. The methodology employed in developing the NHDS & AP 2021-2031 involved extensive literature review and analysis. The preparation team undertook the reviews to identify internal and external factors augmented by consultative meetings with stakeholders along the value chain. Then, a SWOC analysis was used to formulate the vision, mission, and objective for the revised strategy and help identify and prioritise key strategic intervention areas. Furthermore, the preparation team conducted an in-depth analysis of current challenges and constraints along the horticulture value chain for clarity. The strategy is organised to cover background and situation analysis, which provides essential background information on the horticulture industry and the country’s horticulture development profile. The background includes agro-ecological zone and climatic conditions suitable for horticulture growing area; social-economic status of the country including a summative performance of the industry. The second part covers the National Horticulture Development vision, mission, strategy objective and interventions. The NHDS & AP 2021-2031 objective is to increase horticulture productivity and production through motivated domestic, regional and international markets opportunities. The expected outcome will significantly contribute to more income generation to farmers and other actors along the value chain while contributing to the nation’s economy. The proposed specific objectives are:- NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 xi i. To increase the production capacity for fresh and processed horticultural produces in Tanzania by 2031; ii. To promote production and consumption of nutritional and medicinal indigenous fruits, vegetables, herbs and spices by 2031; iii. To strengthen research, innovation and technologies development by 2031; iv. To promote marketing, market access and trade facilitation for horticultural produce by 2031; v. To improve logistical infrastructure related to packaging, storage and transport facilities by 2031; vi. To strengthen coordination, institutional and policy framework by 2031; vii. To enhance capacities along the horticulture value chain by 2031; viii. To facilitate financing and investment in the horticulture Industry by 2031. The National Horticulture Development Strategy and Action Plan 2021-2031 envisions “A horticulture industry that is vibrant and sustainable competitiveness in the domestic, regional and international markets contributing significantly to an inclusive, sustainable economic growth and foreign exchange earning”; Achieving the vision means an increase in the national horticulture production, and productivity of quality produce, improving the business environment and strengthening coordination, institutional and policy framework. The third part of the NHDS & AP 2021-2031 covers the action plan for implementation of the strategy. This part outlines the implementation arrangements required to implement this strategy effectively. Several key strategic intervention areas have been proposed. The implementation of the strategy will enable the country to put in place measures to increase production and productivity target by 40% from the current production of 7,560,010 tons 2019/2020. The anticipated target will be reached through a harmonised multi-sectoral engagement to support and drive the transformation of Tanzania’s horticulture industry. Institutional arrangements, coordination, and financial management are the document’s fourth part. To achieve this, the establishment of an autonomous horticulture governing organ to oversee the industry is paramount. This organ is proposed under the Ministry responsible for Agriculture and can be named “Horticulture Development Agency” or “Horticulture Development Board” with the regulatory mandate. The organ will be responsible for coordinating and regulating all actors along the value chain of the country’s horticulture industry. The last part covers financing of the strategy, monitoring and evaluation, and risk mitigation. The strategy requires sustainable funding to implement various proposed activities under each intervention. The total cost of implementing the National Horticulture Strategy is expected to be around TZS 4.7 trillion. This investment is needed for successful implementation of the strategy, and given its scale, horticulture industry key stakeholders recognise the need to go beyond traditional sources of finance. The monitoring and evaluation framework of the strategy will enable practitioners to monitor, assess and adjust the strategy to deliver the strategy objectives within the set timeframe. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 xii Risk and mitigation of the strategy have classified the anticipated risks as may arise during implementation of the strategy, being considered mostly as low and middle in their magnitude. Some of the identified risks include: (i) Horticulture industry’s capacity to coordinate the necessary stakeholders; (ii) Limited commitment by stakeholders to work within a framework of collaboration; and (iii) Fluctuation in horticulture prices at national/local & international market. Fortunately, cost-effectiveness and efficient horticulture production, business farms management approach, and farmer organisations are expected to reduce the identified risks and implement a successful strategy. The inclusion of strategic mitigation proposes specific roles for key actors, including producers, processors, market operators / off-takers, regulatory entities, agriculture sector lead ministries, research and training institutions, NGOs, private sectors, Farmers organisations and coordinating bodies. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 1 1.0 INTRODUCTION 1.1 Background The National Horticulture Development Strategy and Action Plan 2021-2031 is a roadmap for developing the horticulture industry in Tanzania. The horticulture industry is the fastest-growing industry within the agricultural sector, with an annual growth rate of about 9 to 12 per cent. It also employs about 4 million people making the industry a major employer within the agriculture sector. Furthermore, the horticulture industry contributes 38% of the total foreign income accrued from the agriculture sector. At the same time, its export value has grown tremendously from USD412 million in 2015 to USD779 million in 2019 (MoA Budget Speech 2019/2020). Apart from the economic contribution, the horticulture industry potentially contributes to the improved food security and nutritional balance in the people’s diet. Currently, the horticulture industry is part of the crop industry dominated by small-scale farmers who cultivate fewer than 2 hectares for their subsistence. Based on the estimate, women and youth comprise about 65 -70% of the small-scale horticultural producers in the country. Such small-scale farmers have limited access to regional and international markets leading to worthless horticulture export business for the majority. However, few farmers have access to markets under contract farming or out-grower arrangements with large-scale exporters through their producer groups. As a result, most horticulture commodities are exported to regional and international markets, mainly in the European Union, the Middle East, EAC and SADC in un-processed form due to the limited agro-processing capabilities (Agricultural Marketing Policy, 2008). Moreover, a significant proportion of horticultural produce goes to waste as post-harvest loss due to a lack of appropriate management. Such challenges contribute to less competitiveness of our horticulture industry than other producer countries like Kenya, Ethiopia, China, Mexico, Peru, South Africa, Brazil. The National Horticulture Development Strategy and Action Plan 2021-2031 envisages facilitating the horticulture industry’s development to increase production and productivity of quality horticultural produce. Such a focus intends to improve nutritional status, increase incomes, and reduce poverty. Moreover, horticulture is vital, if adequately supported, can significantly exploit the country’s potential, particularly the under-utilized 44.0 million hectares of arable land and the available 29.4 million hectares of irrigatable land in the country. Currently, the irrigated area is 694,715 hectares, of which a significant portion is used for non-horticultural crops. The previous Tanzania Horticulture Industry Development Strategy 2012- 2021 supported the expansion and intensification of horticulture production to increase the yields of existing farms and facilitated small-scale and large-scale horticultural production. However, despite the strengths of the horticulture industry in Tanzania, several challenges have hindered the successful implementation of the previous horticulture strategy. The most notable challenges include:- limited use of irrigation systems; low farm production and productivity; few application of Good Agricultural Practices and low use of inputs such as improved vegetable, fruits and spice seeds/seedlings and fertilizers; inadequate extension services to guide farmers on improved practices; limited access to credit; insufficient local skills and knowledge base, weak marketing information system, insufficient coordination, and institutional framework and inadequate and inequitable participation of women and youth in the horticulture value chain. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 2 In addition to this, the turbulent horticulture marketing system poses dramatic fluctuations in productivity as large-scale farmers were reluctant to invest in a horticultural industry that had little chance to offer better returns. This is due to the interaction of several factors, including but not limited to; delays in improving internal marketing system and business environment, insufficient market information, high operational and domestic marketing costs, unfavourable local taxation structures, and inadequate functioning of cooperatives. Following these challenges and the government’s desire to enhance the development of the horticulture industry, this National Horticulture Development Strategy and Action Plan 2021-2031 are prepared to address the identified challenges and the current transformation agenda as envisaged under ASDP II. Moreover, it’s now deemed to accommodate the rapid changes needed to bring about the sector’s desired transformation. The new strategic objectives appearing in this strategy were formulated based on stakeholders’ desire to cope with the changing requirements of beneficiaries, the country needs, the challenges of the horticulture value chain, government policies and global priorities. The National Horticulture Development Strategy (NHDS & AP) 2021-2031 is a demand-driven initiative of the horticulture stakeholders to exploit the fast-growing demand and market opportunities available. The strategy envisages transforming horticulture into a competitive industry capable of contributing significant generation of foreign income and reducing poverty through the sustainable supply of high- quality produces to domestic, regional and international markets. Its priorities are to increase production and productivity of quality produce, promote value addition; reduce pre-and post-harvest losses; improve market access; improve business environment; and strengthen coordination, institutional and policy framework. 1.2 Key policies and strategies supporting horticulture strategy 1.2.1 Global and continental policy landscape The Sustainable Development Goals (SDGs) are an inter-governmental agreed set of targets relating to international development. SDGs One and Two intend to end all forms of poverty and hunger for all people. The goals underscore the importance of horticulture contributions to increased income generation, improved food and nutrition security and creating more decent and equitable employment opportunities along the horticulture value chain. The Africa Agenda 2063 address rigorously the past injuries caused by slavery, all forms of colonialism and segregation of all kinds. Then, judiciously provide own grown African solutions entrenched deeply into self-reliance core principles and cultivating the culture of financing own development initiatives. Among the African seven aspirations, the first is more connected to horticulture development that entails seeing a prosperous Africa based on inclusive growth and sustainable development. This aspiration wishes to see transformed modern agriculture characterized by market-led increased production, productivity and value addition contributing to farmers prosperity and Africa’s collective food and nutrition security, reduced food imports and increased intra-Africa trade by 50% in the next fifty years. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 3 The 2014 Malabo Declaration is on accelerated agricultural growth and transformation. The declaration provides goals to achieve the continental agricultural vision: shared prosperity and improved livelihood. It is a framework for harnessing inclusive growth and sustainable development opportunities. Malabo Declaration is enshrined into declarations and decisions in the 2003 Maputo Declaration on agriculture and food security, the 2004 Sirte Declaration on the Challenges of Implementing Integrated and Sustainable Development in Agriculture and Water, the 2009 Sirte Declaration on Investing in Agriculture for Economic Growth and Food Security, the 2007 Abuja Decisions on Fertilizers and Food Security, and the 2013 Decision on Renewed Partnership for a Unified Approach to End Hunger in Africa by 2025 under the CAADP Framework mentioned few of them. Reflected that hunger and malnutrition are major causes of poverty and underdevelopment in Africa, their impact is heavily on poor health, low energy levels, and mental impairments resulting in a vicious cycle. Furthermore, Africa is concerned that little development is achieved on agro-industries and value addition of agricultural commodities, hence less competitive in the domestic and export markets. Thus, Africa is committed to principles and values that define the CAADP process, including i) pursuing agriculture-led growth as the main strategy to tackle poverty and malnutrition; ii) regional complementarity and cooperation; iii) application of the principles of evidence-based planning, policy efficiency, dialogue, review and accountability; iv) partnerships and alliance with key actors including the farmers, agri-business operators, civil societies and v) support the implementation at country levels regional coordination and harmonization. Thus, Malabo Declaration is Africa’s commitment towards enhancing agriculture investment and financing for shared prosperity. 1.2.2 Regional policy landscape Tanzania ascribes to the two vibrant Regional Economic Communities (RECs); the East African Community (EAC) and the Southern Africa Development Community (SADC). In both RECs, horticulture is one of the industries contributing to the livelihood of a large proportion of people. For example, over 4 million people earn their living from the horticulture industry in Kenya and Tanzania. However, faces several hurdles, including a low productivity base, dynamic and changing marketing demands, limited investment through public-private partnerships, limited access to improved technology, inadequate funding for research and development, and inadequate human capacity, especially in tree crop germplasm improvement. To address these, the RECs are preparing policy instruments that will guide the horticulture industry to thrive and become competitive. 1.2.3 The policy context in Tanzania Horticulture misses legislative backup. The Food Security Act 1991 and its consequential amendment that resulted in the Cereals and Other Produce Act 2009 are grossly silent on horticulture. The law calls for the Minister of Agriculture to gazette the crops falling under the definition of horticulture into the “Other Produce: category. However, the definition of “Other Produce” is not specific, and hence it is at the discretion of the Minister to gazette any crop deemed fit at that particular time. Following the importance of the horticulture industry in terms of its contribution to the general agriculture performance, there is a need to make horticulture stand-alone than fitting into the “Other Produce” category. Existing legal frameworks supporting horticulture in Tanzania include the Tanzania Development Vision (TDV) 2025, designed to understand that the 21st century global economy is intensively competitive, dominated by advanced technology, high productivity, modern transport and communication NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 4 infrastructure, and technology managed by highly skilled human resources. The Vision (TDV 2025) prepares Tanzanians to tackle the envisaged challenges, build a resilient and competitive economy and instil professionalism, discipline and strong leadership. The Ruling Party Manifesto (2020-2025) is rooted in the Tanzania Development Vision 2025. Generally, the CCM Election Manifesto of 2020-2025 addresses government commitment to meet the main development goals of transforming agriculture from subsistence to commercial farming. The intention is to increase production and productivity for national food and nutritional security, strengthen economic growth, and catalyze industrialization to enable the country to retain the status, namely “middle-income country”. Increasing the production and productivity of horticultural crops will enhance national food and nutrition security and complement the implementation of the Ruling Party Manifesto. The National Agricultural Policy of 2013 lays a foundation for national economic changes in the agricultural sector in Tanzania. The policy emphasizes the integrated and sustainable utilization of agricultural lands, input supply, marketing value-added commodities and an increase in agricultural financing. Additionally, the policy talks about increasing the application of Information and Communication Technologies (ICTs) crop insurance while embracing youth participation in the sector. Small and Medium Enterprise Development Policy 2003 aims to promote income-generating activities and support diversification of private sector activities in the agricultural sector. This includes creating commercial opportunities in the marketing and processing of agricultural products. In addition, implementing the National Horticulture Development Strategy and Action Plan will complement SMEs policy since most farmers who engage in the horticulture industry are SMEs. The Agricultural Sector Development Programme (ASDP) underpins improved agricultural growth, increasing farm-level production and productivity, increasing farm investments, expanding access to inputs, and improving the agro-industries business environment. The Government of Tanzania has several initiatives to improve horticulture. These include Agriculture Sector Development Programme (ASDP II), Export Processing Zone Act 2006, the Cooperative Societies Act 2013, and Agricultural Marketing Policy (2008). These legal and programme instruments take cognizance of the major agricultural constraints, including inadequate inter-institutional coordination, communication and linkages. Other cross-linking policies and programmes include the National Land Policy of 1999 that ensures better land utilization for rapid social and economic development. The Environmental Policy of 1997 recognizes the importance of land husbandry to enhance high crop productivity by improving water, soil and soil fertility. Water Policy 2002 recognizes better access to agricultural water to achieve food security, ensures water resources management, promotes efficiency, sustainability, productivity, and equity for increased productivity, and mitigates conflict. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 5 Figure 1: Horticultural clusters in Tanzania Songwe Indian Ocean Lake Victoria Lake Tanganyika Lake Nyasa Lindi Tabora Mbeya Katavi Ruvuma Morogoro Iringa Singida Kigoma Manyara Pwani Arusha Dodoma Tanga Mara Rukwa Geita Kagera Simiyu Njombe Mtwara Shinyanga Mwanza Kilimanjaro Mwanza Dar es salaam Kusini Unguja Mwanza Kusini Pemba Kaskazini Pemba Kaskazini Unguja 4 Legend water_bodies International_Boundary Regions Potential Horticulture Areas 2.0 COUNTRY PROFILE AND SITUATION ANALYSIS 2.1 The horticulture industry The current horticulture industry in Tanzania is dominated by small-scale farmers who cultivate an average of 2 hectares per season planted with several crops, including horticultural crops. Small-scale farming in Tanzania accounts for about 70% of horticulture crop production. There are six main potential zones for horticulture production; the Northern, Coastal, Southern Highlands, Central, Western, and Lake zones in the Tanzania mainland (Figure 1). Each zone has specific ecological conditions suitable for particular horticultural crops. The horticulture development potential of Tanzania is bolstered by notable strength, including suitable soil and diverse climatic conditions for the cultivation of a wide range of horticultural crops. The increasing demand for horticulture produces in the local, regional and global market is an added advantage. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 6 2.1.1 Current situation of horticulture production Tanzania is among the 20 largest producers of fresh horticultural produce globally, while the leading countries are Mexico, Vietnam, the Netherlands, the United States, Spain, Germany, Canada, China, Peru, and Turkey (FAOSTAT 2018). Production of horticultural crops in the country has increased from 5,931,900 tons in 2015/2016 to 7,560,010.70 tons in 2019/2020. Such increase is due to some advancements in Good Agricultural Practices, including applying foliar fertilizers, strengthening fertilizer Bulk Procurement System, and using modern technologies such as greenhouses, drip irrigation and soilless cultivation (hydroponics) in various parts of the country. The production trends of horticultural products are shown in Table 1. Table 1: Production trend of horticultural produce (Tons per yea Crop 2014/2015 2015/2016 2016/2017 2017/2018 2018/2019 2019/2020 Fruits 4,574,240 4,711,000 5,243,343 3,703,124 4,576,948 5,582,117.3 Vegetables 1,041,375 1,189,000 1,298,388 1,595,489 1,926,927 1,852,676 Flowers 11,140 11,500 11,615 12,622 13,240 1,709.5 Spices 8,609 20,400 22,062 22,062 80,748.2 123,507.9 Total 5,635,364 5,931,900 6,563,793 5,333,297 6,597,863.2 7,560,010.70 Source: Ministry of Agriculture, 2020 Despite the statistical data in Table 1, horticultural crop production in Tanzania has not significantly improved in the past decade. This dismal performance is due to various persistent, emerging challenges and impediments which face the industry. For example, climate change has resulted in unpredictable weather, which eventually affected the rainfed horticultural farming system. Other challenges include poor agronomic practices, inadequate research, low usage of improved inputs, high inputs prices and limited application of post-harvest technologies. Moreover, several market opportunities have never significantly contributed to the average annual production of horticultural crops in the country. 2.1.2 Importance of horticulture to the national economy Although Tanzania is among the world’s top 20 countries in fresh horticultural produce, its average export is 0.3%. The domestic market consumes most of the horticultural produce predominantly in fresh form, while only 8% is processed. This scenario calls for further promotion of the horticulture industry to tape external markets and increase the domestic agro-processing of the horticultural crops. Table 2: Trends in export of horticultural produce (Tones) Crops 2014/15 2015/16 2016/17 2017/18 2018/19 Flowers 7,393 8,584 7,885 7,544 8,126 Vegetables 3,717 4,678 3,358 3,133 3,672 Fruits 4,902 4,366 6,353 6,922 7,675 Live plants & planting materials 384 799 873 875 903 Spices 369 432 357 306 478 Total 16,765 18,859 18,824 18,780 20,854 Source: Ministry of Agriculture, 2020 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 7 2.1.3 Challenges in horticulture industry The Tanzanian horticulture industry can continue to experience dismal progress if transformation efforts do not address existing and emerging challenges. Challenges of the horticultural industry in Tanzania are described in subsection 2.1.3.1 to 2.1.3.15. 2.1.3.1 Inadequate horticultural research and training Despite numerous research and training institutions engaged with horticulture in Tanzania, research gaps are still hindering the successful development of the industry. The learning and research institutions include UDSM, SUA, Nelson Mandela (NM-AIST), TEMDO, SIDO, CAMARTECH, COSTECH, TIRDO, TARI, and International Private Research institutions such as World Vegetable Centre, Vegetable seed companies - Rijk-Zwaan, East-west. The research gaps that hinder the successful development of the national horticultural industry include:- Inadequacy of research funding resources; Inadequate skilled and trained research personnel (e.g.; entomology, agronomy, breeding in horticulture and tree crops, pomology, pathology, etc.); Uncoordinated research findings (R&D), dissemination of results, Monitoring and Problem-solving researches; Lack of Research policy on germplasm such that Intellectual Property Right protocol of the results found is impeded; Insufficiency of good research infrastructure and transport facilities to researchers with accredited laboratories; Low capacity of National Plant Genetic Resources Centre (NPGRC) especially for the conservation of vegetative propagated traditional vegetables, fruits, herbs, spices, and ornamental plants; and Lack of post-harvest and value addition techniques. 2.1.3.2 Low number of professionals in horticulture Human resource is a powerhouse towards horticulture development in the country. The workforce in the agriculture sector and horticulture, in particular, should be prepared to meet the industry’s new challenges. For this case, there is a need for a more skilled workforce with horticulture professional competency throughout the entire value chain to meet the ever-changing technical and economic development needs. To date, Sokoine University of Agriculture is the only higher learning institution in the country that offers degrees in horticulture, while two technical tertiary Institutes offer courses at the diploma level. For the past five years, a total of 328 Diploma and 437 Degree students graduated (Table 3, 4, & 5). Table 3: List of horticulture diploma graduates from Horti-Tengeru (2016 – 2020) ACADEMIC YEAR FEMALE MALE TOTAL 2016 21 15 36 2017 17 17 34 2018 09 10 19 2019 25 19 44 2020 09 25 34 Total 81 86 167 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 8 Table 4: List of horticulture diploma graduates from Borigaram (2019 – 2020) ACADEMIC YEAR FEMALE MALE TOTAL 2019 14 43 57 2020 18 14 32 Total 32 57 89 Table 5: Number of students graduated BSc. Horticulture for the past five years from Sokoine University of Agriculture Academic Year Male (M) Female (F) Total 2016 33 16 49 2017 56 37 93 2018 49 30 79 2019 61 39 100 2020 67 49 116 Grand Total 266 171 437 Although the number of students who graduated from university increases, the demand for professionals is also increasing. It had been challenging to meet the professional demand in the country due to some of the training gaps that impede the development of horticultural training institutions. Such training gaps include: Old infrastructures and outdated equipment in the tertiary training institutes; Inadequate practical training due to insufficiency of practical training centres with modern agricultural technologies and infrastructures; Lack of horticultural farm management practical training; Low enrolment of horticultural students at tertiary level institutions; and inappropriate teaching methodologies used by responsible instructors, tutors or lecturers. 2.1.3.3 Inadequate agricultural practices Productivity is essential for the growth of the industry. However, the current production does not meet recommended yield per unit area due to poor agricultural practices. Most of the farmers do not follow Good Agricultural Practices (GAP) due to:- Inadequacy of extension services; Inaccessible of improved horticultural seeds, seedlings and other related agricultural inputs; Inadequacy of appropriate technology and innovation to improve production and productivity; Lack of comprehensive extension guideline in potential horticulture crop production; Inadequacy of refresher training to be offered to extension workers to update their skills; Inadequacy of dissemination of technologies related to horticultural issues and Inadequacy of horticulture promotional activities in production areas. 2.1.3.4 Inadequate extension services in horticulture The Ministry of Agriculture’s organisational structure has been changing with the change in the country policy environment. Before the Local Government Reform Program (LGRP) in 1996 and its official approval in 1998, which led to decentralisation of power to local authorities, all local government affairs were under the control of the Central Government (PHDR, 2003). Following the decentralisation policy, agricultural activities, including extension services, are now under the President’s Office, Regional Administration and Local Government (PO-RALG). This was done to give local government authorities more autonomy and power to decide and plan development activities free from central government NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 9 interference. The main idea behind decentralisation was facilitating access to various services, including bringing extension services closer to people. Under such context, the role of the central government is to formulate policy, give support and monitor the implementation of development projects. Regarding the agriculture sector, extension services involve providing knowledge, information, and farm technologies to farmers to increase farm productivity for their well-being and livelihoods (NRI, 2011). However, delivering quality Horticultural extension services in Tanzania has been a centre of attention for a long time. It is, therefore, important that horticultural extension services in Tanzania are present in the right frequency and time (Rutatora and Matee, 2001). Currently, the existing horticultural extension services in Tanzania have been vested in local government authorities to facilitate the participation of beneficiaries and motivate private sector involvement in service delivery (Kimaro et al., 2010). The standard techniques used to deliver extension services include farmers field schools, training and visit, contract farming, participatory extension, and farmer to farmer extension (Kimaro et al., 2010). Despite the delivery techniques used so far, there are prominent gaps in the provision of horticultural extension services in Tanzania which need to be addressed. The gaps include:- Inadequacy of professionals and skilled horticulture extension workers, especially on plant protection; Least funding for horticultural services; Lack of extension working gears, tools and types of equipment; Inadequate information on production costs of various horticultural crops (cost/benefits of best practices) and marketing; Weak linkages between research and extension services; the prevalence of Ad-hoc extension services (No systematic plan schedule of work); Lack of updated technological learning (on-job training etc.); and Absence of monitoring and systematic assessments on performances of extension officers. 2.1.3.5 Inadequate customer care and after-sale services. Planting materials for horticultural production has been a significant constraint on the country. The fruit seedling nurseries are not registered; hence poses a risk of poor quality planting materials being supplied to farmers. Provision of quality planting materials requires expertise in nursery management and proper selection of planting materials. Adequate supply and access to high-quality planting materials are essential for developing the horticulture industry. The industry largely depends on imported seeds and mostly unaffordable planting materials. The inadequacy of locally produced certified material is due to low investments. However, many small-scale commercial nursery operators spread all over the country do not meet standards that would ensure the supply of quality planting materials. Generally, imported materials constitute a significant percentage of the total planting material for flowers and vegetables. However, the climate conditions in the country are very favourable for horticultural seed production and breeding. The giant leading seed companies are located in the northern part of Tanzania, like Rijk Zwaan, East-West Seed Company, and Enza-zaden Seeds, have set up production facilities in Arusha. Although seeds are produced here, the processing, packaging, pelleting, labelling and trademarking are done outside the country. Changing the ownership of such seeds when imported back to Tanzania is very expensive. On the other hand, government institutions (ASA, SUA, Uyole), government mother orchards, private nurseries, individuals/groups, projects and Non-Government Organisations produce seedlings and planting materials. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 10 Figure 2: World seeds vegetable share 2.1.3.6 Limited skills and interventions on pre and post-harvest management In the horticulture industry, pre and post-harvest losses are estimated to be 30-40 per cent of the total horticultural crop produced. Such losses are due to the perishability nature of the horticultural produce coupled with inadequate post-production infrastructure for handling. In addition, the post-harvest loss brings about inconvenience amongst value chain actors by reducing saleable volumes due to inferior primary handling and transporting systems. The factors attributing to pre-and-post-harvest losses in the horticulture industry in Tanzania include:- Limited awareness on the appropriate techniques to reduce crop losses, inadequacy or limited skills in harvesting techniques; inadequate adherence to market requirements, especially during peak demand/ scarcity season; inadequate horticultural post-harvest handling facilities, inappropriate transportation system and transport techniques or facilities; and the improper packaging and unstandardized packaging materials. 2.1.3.7 Low adaptation to emerging technologies and innovations Among the factors contributing to low horticultural production are the technological limitations faced by small-scale farmers. Some emerging technologies like greenhouses, soilless culture, drip irrigation, hydroponics, gene plasma, processing, packaging and transportation technologies are available in the country but are not user friendly to farmers. Farmers use few production, pre-and post-harvest technologies accessed and adopted from other countries while other technologies are not efficient or suitable to our environment. Therefore, there is a need to promote accessibility and the adoption of appropriate technologies that will increase horticultural production and reduce pre-and post-harvest losses based on the Tanzanian context. 1313 11 98 6655 24 0000000000 0000000000 0000000000 0 5 10 15 20 25 Percentage Share World Vegetable Seed Companies Bayer Vimorin Syngenta Rijk Zwaan BASF Sakata Enza Takii Bejo Overig NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 11 In some cases, technologies that were used to be effective are constrained with high investment cost, availability of few spare parts, and limited technical knowledge in adapting the technology. Furthermore, knowledge on applicability is scattered and/or unknown outside the users’ group/cohort. Therefore, such information needs to be collected and stored in a single database to enable users to access it quickly. Furthermore, there is a need to know the available/existing technologies, including the new ones available in the market, test for their suitability and disseminate the appropriate ones to users (producers, processors, and relevant actors along the respective value chain). There is a need to establish a database for all technologies proven to work better for upscaling and continue researching new and innovative technologies to ensure their suitability and applicability. 2.1.3.8 Inadequate marketing Horticultural crops are perishable by nature. That means the quality deteriorates fast due to a lack of appropriate handling. Inadequate post-farm handling of horticultural produce has caused a severe problem in marketing horticultural crops in the region. There is no direct communication between the producers, traders (wholesalers, retailers), and consumers in most cases. One way out is for the farmers to understand the “real demand” of the produce in a market through a survey and then respond by growing horticulture produces based on the market needs to be referred to as shifting from “grow and sell” to “grow to sell.” The domestic market’s constraints include:- Lack of and enforcement of food safety and standards guidelines; inadequate market infrastructures; limited adherence to appropriate marketing requirements; uncoordinated local markets, unstructured and unstandardized produces; lack of appropriate market storage facilities for horticultural produces; inadequate market information; and unsatisfactory contractual farming guideline. On the other hand, export market constraints include weak linkages between upstream actors (producers) and downstream actors (retailers), lack of adequate market intelligence and weak capacity to comply with international food safety standards. 2.1.3.9 Ineffective business reforms in the horticulture industry The government is committed and dedicated to improving the business and investment climate in the country. This is done by devising strategies to clarify the regulatory regime to ensure that the private sector operates in a friendly and predictable business environment. To achieve that, the government has embarked upon a holistic approach to review the policies and regulatory framework governing institutions and agencies through streamlined and rationalized licenses, taxes, charges, fees and levies to ensure inclusive participation of the private sector. In addition, the government has been implementing different programs and strategies to create a conducive environment for investment and business to realize the goals. Some of the programs include the Business Environment Strengthening Tanzania (BEST) Program, the Roadmap for Improvement of Business Environment and Investment Climate in Tanzania, the Blue Print for Regulatory Reforms to Improve the Business Environment and the Agricultural Sector Development Program (ASDP II). Apart from the reforms undertaken by the government, there are still some issues needed to be addressed to improve the business environment in the industry, including:- Waive of VAT on modern horticultural inputs and equipment’s such as plant protection substances; Review of regulatory fees and levies charged by various regulatory authorities; Agriculture Green belt hub establishment at ports; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 12 Accreditation of agriculture laboratories; and Construction of cold storages at ports, collection centres and packhouses in the potential production area. 2.1.3.10 Low adherence to the required quality and standards The certification of producers is encouraged to benefit from market opportunities. However, the market for certified products is complex, and the opportunities and requirements associated with the certification programmes are too demanding. Besides, producers do not always know if the requirements are compulsory as deemed by law or merely voluntary. They also do not know the advantages and limitations of different types of certification. Furthermore, the large import requirements established by other countries make it even more complicated for producers who want to comply. The major challenge is that the participation of the private sector in Standards Committees is limited. Major safety parameters include:- Maximum Residue Limits (MRLs) and heavy metal contaminants limits need to take into account recent risk assessments for a particular contaminant; and the codex committee on contaminants in food reviews the permissible level of heavy metal contaminants in food products. In the context of Tanzania, the standards for fruits, vegetables, herbs, and spices need to be aligned to the latest risk-based limits established by the Codex Alimentarius Commission. 2.1.3.11 Low capacity to cope with the certification requirements, guarantee systems and required standards The number of management and food safety standards adopted in the fresh horticultural industry is vast, and the country’s capacity to cope with these is currently limiting. HACCP, ISO 9001, and BRC Global Standard are the most widely applied for horticultural packing and processing. As food safety is a top priority in all European food sectors, it is logical to expect most buyers to request extra guarantees in certification. All actors in the supply chain, such as traders, food processors, and retailers, must implement a food safety management system based on hazard analysis and critical control points (HACCP). The certification initiatives and processes in Tanzania face several challenges, including- unstructured producer and marketing systems with the majority being SMEs and are not unified; Inadequate skills for development and implementation of effective quality assurance systems; high costs of certification & compliance controlled by foreign certification bodies; limited funds to facilitate the certification process; unavailability of local/domestic certification bodies; and limited skills and professionals in certification. The importance of fresh fruits and vegetables for human health has contributed to the substantial increase in fresh fruits and vegetable consumption. However, the recent rise in foodborne illnesses associated with fresh fruits and vegetables has raised concerns from public health agencies and consumers about the safety of these products. This condition has forced food safety, and traceability certification to enforce stern measures and demand requirements for market compliance as produce may become contaminated anywhere from farm to fork. Protecting consumers, the environment and workers’ health is a significant concern to all players in the agriculture industry. If the produce becomes contaminated, there are limited means to eliminate the contaminants; hence it is essential to ensure food is safe for consumption. In line with this, NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 13 the European Union has developed the Global GAP (the Global Retailer Protocol for Good Agricultural Practice), formerly known as Eurep GAP, as a global partnership scheme with the backing of major European Union retailers that aims at promoting Good Agricultural Practice (GAP), with rules covering areas including food traceability, workers welfare, environmental issues, and food safety. There are attempts to develop sustainable agriculture, cooperation, and transparency in the supply chain and harmonize agricultural standards. However, food certification and the standard are not well developed in East Africa and Tanzania. The EAC needs to protect its people’s trade within and outside. EAC countries need to protect their people and trade within and outside. In that case, there is a significant need to harmonize the certification system and standards of horticultural produce to remove trade barriers encountered when goods and services are exchanged within the community. 2.1.3.12 Limited control of pesticides quality and chemical residues Worldwide application of synthetic pesticides as the main way of controlling pests and diseases on various crops has resulted in failures in pest control, negative environmental impacts, and a build-up of pesticide resistance by pests. Furthermore, the environmental and health impacts of synthetic pesticides are increasingly raising concerns worldwide. For example, in Tanzania, high pesticide residues and microbial contaminants have recently been reported (Kapeleka et al., 2020; Kiwango et al., 2018; Kariathi et al., 2016). Farmers complain of inefficient pesticides in pest control in most parts of Tanzania. Some pesticide traders sell expired or counterfeit chemicals. Lack of knowledge on the judicial use of pesticides by farmers and buying pesticides from unreliable sources also contribute to this problem. Moreover, some traders re-pack pesticides into smaller quantities that most small-scale farmers can afford since the larger packs seem too expensive. In so doing (multiple handling), the chemicals may lose their quality, or the unfaithful traders have the opportunity to degrade the chemicals by increasing the quantity at the expense of quality with the motive of making a profit illegally. Farmers do not adhere to good pesticide application practices such as pre-harvest intervals (usually indicated on pesticide labels) and application rates and frequencies. Factors leading to farmers’ failure to abide by recommended pesticide application include limited knowledge, panic inflicted by high pests, and market demand. Most (if not all) of these challenges are, however, inadequately managed due to the following reasons:- Lack of surveillance data on pesticide, microbial contaminants and other pollutants to provide an alarm for interventions; Lack of pesticide monitoring and surveillance systems at the farmer level; Inadequate knowledge on the use of integrated pest management (IPM) where synthetic pesticides are regarded as a last resort due to failure of other methods; Lack of alternatives to synthetic pesticides; Lack of good quality irrigation water which is free from microbial contaminants and other pollutants; Lack of knowledge on the importance of cleaning the products before sending them to the market; Inadequate control of the unfaithful traders by enforcing the existing laws; Lack of facilities for control and surveillance of pesticide residues as well as microbial contaminants; and Untimely government authorities response to scientific recommendations. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 14 2.1.3.13 Inadequate plant health services There are many institutions involved in plant health services. However, internally produced and consumed produces are not inspected for chemical residues and microbial contaminations. This led to unsafe horticulture produce in the market. Phytosanitary certificates are issued upon inspection at the exit point without necessarily inspecting the plants’ production points and plant products. In a real sense, the responsibility of issuing phytosanitary certificates should reside with the Plant Protection Organ. Furthermore, there is a problem of limited trained personnel for surveillance purposes due to scarce field transport, specialized surveillance equipment, and tools and a lack of a phytosanitary protocol for various plants. The inspectors are also not well facilitated in transport to and from the field and other testing capacities. As a result, the phytosanitary certifications and high product quality are bottlenecks to reducing producers’ ability to reap the benefits available at the international markets. 2.1.3.14 Weak enforcement of weight and measurement regulation Weighing and measuring fresh horticulture produce is the country’s concern. Even though the Weights and Measures Agency-2002 is responsible for consumer protection by ensuring that measuring systems result in fair trade transactions. Certification is done through inspection, calibration, and verification, with regular inspection of the scales at factories to ensure that farmers and consumers obtain fair pricing on inputs. However, the Agency is weak in enforcing the law governing weight and measures of horticultural produce that is in use. As a result, in most markets, unstandardized packaging materials, measurements, and methods mostly favour the traders for producers’ costs, particularly farmers. 2.1.3.15 Potential contribution from horticulture industry in tackling public malnutrition Fruits and vegetables play an important role in providing essential vitamins, minerals, and dietary fibre, whilst spices have significant medicinal and curative potential. In Tanzania, like many other developing countries, the majority consumes few fruits and vegetables, contrary to the recommended daily intake of 200 grams of vegetables and 400 gms of fruits (WHO Global Action Plan for the prevention and control of non-communicable disease 2013-2020). This occurs for several reasons, including low income, lack of nutritional education, and an insufficient supply of fruits and vegetables during the offseason. The low consumption of fruit and vegetables leads to undernourishment, high rates of protein-energy deficiency, iron deficiency anaemia, iodine deficiency disorders, and vitamin A deficiency. Micronutrient deficiency (MD) is a considerable public health problem in developing countries that affects both children and adults. The immediate causes are inadequate intake of micronutrients (NBS, 2011). The major micronutrient deficiencies in Tanzania are iron, vitamin A and Iodine, especially in children and women. The micronutrient deficiency in Tanzania is high compared to Global micronutrient deficiency, accounting for 7.3% of child morbidity and 12% child mortality (WHO, 2002). In Tanzania, about 58% of children are iron deficient (TNNS, 2018); 33% are vitamin A deficient (NBS, 2011), and 34% have chronic malnutrition (TNNS), while women aged 15 - 49 are anaemic (TDHS 2016). These conditions affect children under five years of age and pregnant women. On the other hand, diet-related non-communicable diseases, especially among the urban elite and business sections of NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 15 the community, emulate Western culture’s unhealthy food habits and lifestyles. Based on these feeding habits, there is a need to increase the consumption of fruits, vegetables and spices. The National Multisector Nutritional Action Plan (NMNAP-2016 -2021) and the third five-year development plan 2021-2025 are developed to guide the nation’s nutritional aspect. Thus, the increased consumption of fruit, vegetables, and spices is the best recommendation to reduce and eliminate micronutrient deficiency among Tanzanians. Despite the numerous public awareness campaigns on control of chronic diseases through the consumption of fruits and vegetables, it is high time to ensure sustainable availability of horticultural produce. 2.1.3.16 Existence of few farmer organizations in the horticulture industry The horticulture industry has few farmers organizations compared to other crops. This is due to several reasons depending on the nature of horticultural crops and the related marketing mechanisms. Most farmers’ organizations are informal, composed of small-scale farmers, be it of association, VICCOBA, district-level registered organization, and few producers’ forums. Some of the organizations include TAHA, which is the most efficient horticulture organization in Tanzania, Horticulture Development Council of Tanzania (HODECT), Tanzania Spice Producers Association (TASPA), MVIKIHO, UWAMARU, Usambara Lishe Trust (ULT), MVIWATA, CHAWAVIA, Jukwaa la wazalishaji wa machingwa, TAFOPA and TPSF. They provide training and market-oriented services at a minimal capacity. The horticulture industry in Tanzania also has several private sector actors and projects along the value chain. However, the organizations face several challenges, including:- Un-coordinated private sector projects and activities leading to duplication of efforts; Lack of coordinating apex body; and Inadequate knowledge and skills in organizational management. 2.1.3.17 Limited finance and investment in the horticulture industry The horticulture industry is capital intensive. In Tanzania, there is a minimum investment of this industry due to lack of coordination, few off-takers, and several challenges on taxes and cess. In addition, the industry requires the investment of cold chain facilities, human resources, industry coordination, storage and transportation facilities, green belt and industrial packs, seed production and research. Therefore, funding mechanisms are highly needed to promote investments in the horticulture industry. 2.2 Strength, Weaknesses, Opportunity and Challenges in the horticulture industry After a thorough situational analysis of the horticulture industry in Tanzania, an attempt has been made to develop a SWOC analysis to provide a quick snapshot of the industry in terms of its Strengths, Weaknesses, Opportunities and Challenges. This stage has arrived by examining how the industry operates and the associated dynamics in the country. The fundamental assumption behind the analysis is that both the internal factors (Strengths and Weaknesses) and external factors (Opportunities and Challenges) in their totality will bear the scope for achieving the intended objective of fostering the competitiveness of the industry in the country. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 16 Table 6: SWOC analysis of the horticulture industry in Tanzania STRENGTHS WEAKNESSES • Abundant availability of suitable land for expansion of horticulture production; • Excellent and diverse agro-ecology for horticulture production; • Short term production cycles (e.g. vegetables); • Suitable climatic conditions for continuous production; • Vast domestic market ( e.g. traditional fruits and vegetables) readily saleable locally; • Good export performance pre-established for selected products; • Presence of supporting institutions for technology development; • Good infrastructure (roads, electricity); • Readiness of active stakeholders to support the horticulture industry; • The horticulture industry has vast potential to engage an abundant number of the skilled and unskilled workforce comprising women and youth. • Inadequate production and supply of planting materials • Inadequate technically well equipped responsible expertise in the horticulture sector • Small and weak production base, fragmented sector, the mismatch between Supply Side and Demand Side for processed products; • High pre-and post-harvest losses across the entire VC spectrum (i.e. harvesting, storage, packaging, transportation and marketing) • Poor extension services (insufficient and low skill) with limited availability of local expertise for commercial production of fruits, vegetables, herbs & spices- insufficient local skills and knowledge base; • Irregular supply of necessary inputs, • lack of access to capital for investment in horticulture ; • Low availability of adequate infrastructural facilities (e.g. cold facilities.) – leading to product deterioration; • Underdeveloped infrastructure to support mass production, processing, transportation and marketing; • Limited processing technologies for value addition; • Poor market linkages (small market share, weak info systems, low level of service provision in the sector, a large number of intermediaries along the chain;) • Lack of farmer’s mindset on producing vegetables based on market needs; • Lack of adequate quality control and testing methods as per international standards; • Poor subsector coordination – e.g. inadequately developed linkages between R&D organizations and industry, Horticulture sub-sector has no place in responsible Ministry organogram • Poor market infrastructure (Collections centres etc.) • Low promotion and branding of Tanzanian horticulture produce 1 In the SHEP Approach, farmers start with Market Survey first and improve input and production stages according to market needs. It was originated from the JICA project in Kenya and now being implemented in more than 20 countries in Africa and other regions. INTERNAL FACTORS NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 17 OPPORTUNITIES CHALLENGES • Growing new global market demand for horticultural produce are emerging; • Political will and stability; • Enough land to expand horticulture production into areas previously untapped; • The willingness of the government and development partners to support the horticulture industry; • The established industrial base for the production of supporting equipment and food parks to incentivize green-field projects; e.g., packaging industry; • Available national and international institutions for technology development; • Diverse uses of horticulture (e.g. medicinal value, cosmetics etc.); • High potential for job creation for youth, women etc.; • Steady improvements in agricultural financing; (e.g. TADB, NMB, CRDB) • Rising income levels and changing consumption patterns increase local demand; • High international market demand for organic horticultural produce. • Effect of climate change. e.g. drought • Incidences of horticulture pests and diseases • Unpredictable policies and directives • Seasonal and annual price fluctuations for fruits, vegetables, herbs and spices on both domestic and international markets; • Labour migration to urban areas seeking better employment opportunities; • Absence of collaborative effort within the value chain; • International competition in quality and prices of horticultural produce ; • Incidences of communicable and non- communicable diseases 2.3 Identification and prioritization of key strategic areas This SWOC analysis was used to formulate a horticulture industry vision, mission and objective for the revised strategy. It also helped to identify and prioritize key strategic intervention areas and a more in- depth analysis of challenges/constraints along the horticulture value chain as described in Table 7. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 18 Table 7: Constraints and proposed solutions/interventions along the horticulture value chain 3.0 Value chain Function 4.0 Major challenges 5.0 Proposed solutions 6.0 Key interventions • Policy related • Reduction of taxes • The government Input suppliers • Policy related drivers for input price build-up; • Existence of counterfeit inputs • Reduction of taxes and other related costs for input manufacturers • Packaging of inputs should contain barcode and expiration date, which are credited by regulatory authorities. • The government should provide/ design inputs subsidy scheme/ bulk procurement. • TOSCI TPHPA to regulate, inspect and control the input supplies. A. Producers Individual farmers/farmer groups • High cost of production & Lack of subsidy in horticulture production (costs for inputs, processing) • Poor extension services • Establishment of price stabilization fund; • Engage financial institutions by raising awareness of the ex isting potential of the horticulture industry for suitable credit products. • Recruitment of newly horticulture extension officers and provision of training of youth and women to engage in the horticulture industry • Use of lead farmers in providing extension services and establishment of commodity centres of excellence; • High horticulture potential clusters should be given high priority when recruiting horticulture extension officers. • Introduce subsidy for major inputs used in horticulture production (selling price of fertilizers,) subsidized by at least 50%) • Strengthening and introduction of SACCOs services at each AMCOS/ Cooperatives to ensure a sustainable source of funding (credit) for farm operations activities • Recruitment and training through tailor-made courses. • Engagement of Private sector extension services to support the industry. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 19 • Low productivity • Inconsistence supply of quality horticultural produce • Promote the use of improved high yield varieties • Use of available good agriculture practices • Use of modern production technologies • Promote consistent production of quality horticultural produce according to the market demand. • Research and Development and multiplication of improved horticulture varieties • Introduction of Taxes exemption, subsidy and insurance programs to the industry • Unreliable markets and unreliable market information’s (Domestic and International) • Market intelligence and social marketing strategy • Farmers’ production based on market information and needs; • To match the market demand with consistency in supply the quality and quantity; • Market information from MoA intelligence unity (AM) should be disseminated to relevant stakeholders through media channels such as bulk texts. • Dissemination marketing information to producers in the value chain; • Promotion of market survey and production based on market needs: introduction of SHEP (Small-scale Horticulture Empowerment and Promotion1) approach • High incidences of pests and diseases • Establish early warning systems for surveillance • Horticulture crops field scouting • Employ IPM techniques/method • Documentation and dissemina tion of information to the value chain actors • Develops IPM Tech. • Climate change effects (drought & flood) • Promotion of climate- smart agriculture (shade management, cover crops, soil management and irrigation) • Capacity building in climate- smart agriculture • Resistant variety development like xerophytes and hydrophytes NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 20 Researchers and Development, extension and training • Inadequate government and stakeholders research funding with too much dependence on donor funding which is not sustainable • Establish a sustainable funding mechanism • Implement problems solving research • Develops research thematic agenda and priorities • In collaboration with stakeholders, the government should support resources for research and extension services. • Inadequate researchers and extension officers • Recruitment of researchers & extension officers • Provision of technical knowhow to extension officers and researchers • Employment • On job training • Training in specialized cadre (e.g. Pomology and • Lack of facilities to fulfil roles for research and extension officers • Provision of extension and research facilities (i.e. Laboratories, training materials etc.) • Establish horticulture demonstration plots and horticulture business school for the dissemination of improved technologies • Low dissemination and adoption of improved technologies among farmers • Increase promotion of the use of improved horticulture varieties and other good agronomic practices among small-scale farmers • Establishment of the tech dissemination organ with linkages with private and public institutions • Promote consumption of improved technologies in the local market. • Sensitization program for the adoption of new technologies • Use of multimedia • Few training institutes offer specialized horticulture training • Low enrolment • Infrastructure and equipment are outdated • Inadequate technical’s skills and technical methodologies • Increase number of institutes • Increase enrolment • Modernized infrastructure and equipment • Long and short training abroad and on the job training (PhD) • Establish tertiary Hort Training institute in Sothern Highland • More financial support provision • Bilateral cooperation should be encouraged NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 21 Processors • Inconsistent supply of raw materials. • Inadequate processing industries and packhouses • Unreliable power supply • Low consumption of the locally processed commodity. • To facilitate contractual farming by applications of modern technology (Irrigation) to allow continuous production. • Facilitate financial support for purchasing processing machines and other facilities; • Promote consumption of the locally processed commodity • Mobilize viable production groups (i.e. Small scale, medium & large scale farmers) • Instalment of Horticultural processing machines at primary societies at the village level. The on-farm value addition will ensure a better quality of horticulture produce. Exporters • Bureaucratic procedures that delay the release of documents for horticulture procurement • Absence of the transition period between the announcement of policy changes and their implementation • Lack of locally made packaging • Limited cargo flight • Delay in road transportation • Under established infrastructure with very few existing pack houses and refrigerated trucks. • To have a one-stop centre for exporters (e.g. Trafic, TRA, TMDA, PHS, Customs, Atomic energy, TBS,..) • There must be a clemency period • Facilitates local production • Facilitate local production of packing materials; • Established infrastructure with packhouses and refrigerated trucks. • All horticulture carriages such as refrigerated trucks should be inspected and sealed by the registered authority. • To establish strategic clearing one-stop centres for export • To the establishment of legal written guidelines • To encourage local production of quality packaging materials • Encourage more cargo flights to operate in Tanzania NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 22 Marketing • Lack of marketing information • Strengthening marketing systems, including direct export and centralized auction • To establish a public- private organ that centralizes marketing issues • Encouraging the farmers to conduct a market survey and produce based on the market information. • Promotion of direct export with branding (through farmers groups and AMCOs) • Establish centralized marketing information • Promotion and upscaling of Small-scale farmers Horticulture Empowerment and Promotion (SHEP) approach and market survey. • Poor horticulture quality that does not meet international standards required, • Extensive promotion of Tanzanian horticulture in the world market • Existence of local quality assessment system • To build and register local farm assurer and local quality management experts. • Increasing production of high-quality horticulture and intensification of certification Cross-cutting • Low gender inclusion (i.e. youth and women in horticulture production) • Empowerment of youth and women in terms of access to resources (Credit, land) • 20% of the income generated from the horticulture cess should effectively be used for horticulture development activities at the district level • All horticulture related levies and taxes should be centralized • Financial support for youth in terms of soft loans that financial institutions can design NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 23 3.0 TANZANIA HORTICULTURE DEVELOPMENT STRATEGY The Tanzania Horticulture Development Strategy and Action Plan 2021-2031 envisions a horticulture industry in Tanzania that demonstrates increased production and productivity, a stable competitive and sustainable horticulture industry capable of contributing a significant amount of foreign income towards poverty reduction through a sustainable supply of high-quality produce for domestic, regional and international markets. Critical lessons learnt from previous experiences Horticultural Development Strategy 2012-2021 supported the expansion and intensification of horticulture production, with the specific aim of increasing the yields of existing farms of small scale and large-scale horticultural production. The strategy mentioned above had four thrusts:- (i) increase horticulture production and productivity; (ii) improve the efficiency of the horticulture value chain; (iii) support overall horticulture quality improvement; and (iv) support the promotion of Tanzanian horticulture abroad and explore new market opportunities, including sustainable- certified horticulture produces. The new strategy builds on what was achieved under the Ten-Year Strategy for 2012 - 2021 and draws on the innovations and best practices developed after addressing some of the challenges such as weak production base, low productivity and quality, invisibility and marginalisation, limited access to long-term financing and investment, bottlenecks inland, policy and infrastructure, inadequate market development support, weak industry linkages, lack of entrepreneurship culture, and inadequate skilled and competent human resource. Most importantly, the new strategy will improve markets that focus mainly on high- quality products. The National Horticulture Development Strategy and Action Plan, 2021-2031, highlights the thrust to transform the Tanzanian horticulture industry by improving production and productivity, increasing raw materials for domestic agro-industries; promoting horticulture produce on export markets, exploiting new market opportunities; building a competitive and sustainable horticulture industry, optimising the internal marketing system and improving the overall business environment. A robust National Horticulture Institutional entity with sustainable financing is inevitable for this transformation to be effective. 3.1 The strategy vision, mission, objectives and strategic interventions 3.1.1 The vision A horticulture industry that is vibrant and sustainable competitive in the domestic, regional and international markets contributing significantly to inclusive, sustainable economic growth, nutritional health and foreign exchange earnings. 3.1.2 The mission To increase national horticulture production and productivity of quality produce, improve the business environment, strengthen coordination, institutional and policy framework and increase the horticulture industry contribution to industrialisation. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 24 3.1.3 The objectives The strategic goal is to transform the Tanzania horticulture industry from the current situation to a vibrant industry capable of producing good horticultural produce for domestic consumption and increased export of fresh and processed commodities. Drawing on horticulture stakeholders’ perspectives, modern industrialisation agenda, the emphasis for implementing a blueprint, and implementing ASDP II. This strategy formulates eight (8) strategic objectives (SO) to achieve the vision. The strategic objectives of this strategy are: SO.1: Increase the production capacity of fresh and processed horticultural produces in Tanzania SO.2: Promote production and consumption of nutritional and medicinal indigenous fruits, vegetables, herbs and spices SO.3: Strengthen research and development SO.4: Promote marketing, market access and trade facilitation for horticultural produce SO.5: Improve logistical infrastructures related to packaging, storage and transportation facilities SO.6: Strengthen coordination, institutional and policy framework SO.7: Enhance capacities of actors along the horticulture value chain SO.8: Facilitate financing and investment of the horticulture industry. 3.2 Scope of the strategy This strategy focuses on transforming horticulture from subsistence to commercialised farming by enabling smallscale farmers, private investors, and all other horticulture stakeholders engaged in fruits, vegetables, ornamental plants, herbs/spices input supply, production, exchange and processing. Specifically, the strategy indicates the possible interventions for each of the strategic issues that can enhance production, profitability and competitiveness of the produce likewise end products in all horticultural industries as a focus. It also focuses on the entire value chain in the horticulture industry. Both supply and demand sides of the value chain are addressed with particular attention to nutrient- dense and high-value horticultural crops grown in different agro-ecological zones. Primary beneficiaries of the strategy are smallscale farmers and entrepreneurs engaged in horticulture production and marketing. Besides agro-dealers, farmers’ organisations, cooperatives, processors, transporters and traders, the consumers are the focal point of this strategy. Moreover, service providers, non-financial, and business enabling environments are also considered. This strategy is expected to unlock the sector’s potential by transforming the industry into commercialised farming through promoting farming as a business, clustering and producing quality products for domestic NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 25 and export markets. Therefore, purposive efforts should be directed towards the realisation of these well-thought vision and mission. 3.3 Description of strategic objectives The horticulture industry in Tanzania faces various existing and emerging challenges despite the available several market opportunities. These challenges include unpredictable weather due to mainly relying on a rainfed horticultural farming system; poor agricultural practices; high cost of production, and poor pre-and-post-harvest handling techniques. Others include an uncoordinated institutional framework, unregulated horticultural business environment; poor linkages among the key value chain actors; and Weak research and development interventions. This strategy covers broad areas of strategic interventions which indicate strategic actions that need to be implemented. The broader strategic areas are related to horticulture production and productivity, processing and marketing. This strategy calls for coordination, resource mobilisation, and implementation planning for implementation purposes. There is also the provision of responsibility arrangement that assigns roles for various actors in implementing this strategy. SO.1: Increase production and productivity capacity of fresh and processed horticultural produces in Tanzania This strategic objective seeks to increase the amount of fruits, vegetables, cut flowers - roses, carnation, ornamental parts & plants, herbs and spices in quantity produced. It aims to ensure a sufficient supply of good quality fresh or processed organic and non-organic horticultural produce for the local, regional and international market. This objective intends to address issues of production and productivity through improving the availability of horticultural inputs, strengthening extension services, promoting efficient horticultural production systems and addressing pre and post-harvest losses. Therefore, it comprises eight (8) strategic intervention areas as outlined below: SI.1.1: Increase access to quality agriculture, tools and types of equipment The strategic intervention seeks to improve farm inputs’ availability, accessibility, and affordability. Horticulture crop production requires continued access to quality inputs (seeds, fertilisers, agrochemicals, botanical chemicals and biological control agents). This will be implemented through the following key actions: i. Establish, strengthen and register public and private mother tree orchards (fruits & spices) and commercial nurseries; ii. Facilitate the establishment of inspection and certification system of nurseries; iii. Strengthen registration system of organic and inorganic pesticides; iv. Increase the production capacity of quality seeds and planting materials; v. Establish linkages with local, regional and international organisations and agencies (tree fruit nurseries and vegetable seed companies to access better varieties); NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 26 vi. Strengthen supply of fertilisers, agrochemicals, botanical and biological control agents; vii. Strengthen the capacity of institutions responsible for inspection and certification of seeds; and viii. Enhance the supply of horticultural equipment; SI.1.2: Strengthen insect pests and diseases control mechanisms This strategic intervention seeks to reduce the incidence and occurrences of new and existing insect pests and diseases through strategies such as: i. Strengthen early warning system and disseminate information for surveillance; ii. Horticultural crop field scouting; iii. Employ IPM techniques and methods. SI.1.3: Strengthen horticultural extension services The strategic intervention seeks to improve the knowledge of actors on good agricultural practices to increase the production of sufficient quality horticultural produce. This will be achieved by promoting private/community extension such as local service providers and farmer to farmer extension together with the public extension services. It will ensure that producers apply good agricultural practices (GAP) for optimum output per unit area. Key areas of focus for this intervention are presented below:- i. Provide tailor-made training (capacity building) to actors and extension workers along the horticulture value chain; ii. Establishment of farmers’ business schools and hubs (centre of excellence– booth camps); iii. Develop extension guide manuals for horticultural crop production; iv. Introduce SHEP approach making farmers undertake the market survey and acquire market-oriented production skills; v. Strengthen extension-research-farmers linkages and establish an early warning system; vi. Promote the establishment of an electronic extension system (e.g., M-Kilimo; etc.); and vii. To enhance women and youth skills, access to financial services and participation in the horticulture industry. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 27 SI.1.4: Promote efficient horticultural production systems The key actions for this intervention are:- i. Integrated horticultural production systems This action seeks to ensure the circulation of raw materials within the value chain in different processes so that output for one process becomes an input for another process or a waste from one process becomes an input for the other. It is an efficient way of using resources and also integrating technology solutions. The intervention can also be looked at from Research and Development’s context of green- farm-gate technologies that seek increased use of alternative renewable energy options. ii. Climate Smart Horticulture (CSH) Agricultural practices, technology transfer, and adoption are fundamental in increasing rural productivity incomes and contributing to poverty reduction and adapting to climate change. However, one of the major factors constraining sustainable agriculture development in Tanzania is the low investment and inadequate efforts to support improved agricultural practices and technologies. The CSH guideline identifies a series of key requirements and challenges for implementing and scaling up CSH practices and formulates recommendations accordingly. The table below shows some of the implementation requirements. Capacity building needs (at all levels – national, local & farm) Key requirements for implementation and up-scaling CSH Facilitate effective awareness-raising Undertake training based on the roles of the stakeholders at different levels Integrate climate change topics in the Syllabus Improve capacity and knowledge on M&E of CSH Enable access to resource provision, improved access (information packages) and dissemination of climate information services. Develop and improve risk management and insurance scheme in agriculture Improved productivity, building resilience and associated mitigation co-benefits Value chain integration Research for development and innovations Improving and sustaining agricultural advisory services Climate and weather forecasting Effective institutional coordination Integration among practices Financing CSH Monitoring and evaluation plan NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 28 The intervention on Climate Smart Horticulture will streghthern the use of shade management, greenhouse, hydroponics, vertical farming, cover crops, soil management and irrigation. Key areas of focus for this intervention are presented below:- i. Production of Climate Smart Horticulture manual; ii. Training of stakeholders along the value chain on CSH; iii. Promotion and strengtherning the uses of CSH technologies as described in table 8; Table 8: Recommended CSA practices and technologies for horticultural crop Subcategory Climate-smart practices and technologies Rainwater harvesting and storage Rainwater harvesting and storage structures; Chololo pits2 Irrigation Drip/trickle irrigation; Irrigation canal lining; Hydroponics, Soil and water conservation Ridging, Tie-ridging; Water Retaining/Harvesting Pits Terraces Fanya juu3 & Fanya chini terraces4, Bench terraces, Stone terraces Agroforestry Tree in cropland; Rotational woodlot; Improved fallow; Fodder bank; Tree planting/afforestation Conservation agriculture Cover cropping; Mulching; Crop rotation; Intercropping; Minimum / zero tillage; Crop residue management; Vertical farming Soil fertility management Manuring (farmyard manure and compost manure); Efficient use of fertilizer (micro-dosing); Integrated soil fertility management; Crop management Adapted crops and crop varieties (improved seeds, high yielding, fast-maturing, drought-tolerant, salinity tolerant, flood-tolerant); Integrated pest and diseases management; Timely/ early planting Crop Insurance Introduction of safety net programmes and greenhouse farming practices 2 1 Chololo pit is in-situ rainwater (runoff) harvesting technology initiated by a farmer in Chololo village, Dodoma. 3 Fanya Juu terraces are made by digging a trench along the contour and throwing the soil uphill to form an embankment. 4 Fanya Chini terraces are made by digging a trench along the contour, and the soil is put on the lower side of the contour trench. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 29 Climate Smart Horticulture and soil fertility management technologies SI.1.5: Address pre and post-harvest losses The intervention seeks to improve the primary stage of handling and processing the horticulture produces to reduce crop losses, increase production volume, and avail industrial raw materials within and beyond the country. The key actions for this intervention involve: i. Promote the adoption of pre-and post-harvest best practices including Good Agricultural Practices (GAP) and Good Handling Practices (GHP) on horticultural crops; ii. Promote best practices on harvesting and post-harvest handling techniques (i.e., use of maturity indices, tools to prevent damage, gentle handling); iii. Provide training on the use of improved package and packaging practices (farm to packhouse and packhouse to market); iv. Promote the use of traditional and modern post-harvest handling techniques (i.e., zero energy cooling chambers-ZECC); v. To develop a strategy to address pre and post-harvest losses for strategic horticultural produce. SI.1.6: Horticultural data capture and management system The existing agricultural data management system (ARDS) does not provide adequate information on the horticulture industry. The following interventions are suggested to address this constraint: i. Strengthen the system of collection and management of horticultural data; ii. Use of ICT in mapping farm by using modern digital technologies such as drones, Satelite images, GIS etc.; iii. Establish a mechanism of horticulture import and export data consolidation from various sources such as TRA, BOT, Airport, Border posts etc.; iv. Building capacity of WAEOs/VAEOs for horticulture data collection; v. Building farmers organisations, groups and cooperative societies capacities in data collection and record keeping. SI.1.7: Promote production and productivity of current and emerging priority strategic horticultural crops This introversion seeks to address the prioritisation of horticulture crops according to their potential in production and market preference. It aims at improving and developing a selected crop value chain to explore its maximum potential. The following are proposed key actions; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 30 i. Build capacity of regions and districts in analysing and identifying their strategic horticultural crops; ii. Establish district horticulture forum and platform involving all value chain actors; iii. Training of extension staff specific technical skills in production and post-harvest management of strategic horticultural crop produce as per quality and standard required by markets; iv. Improve market infrastructure (including packhouse, shade house, dry and cooling chambers) as per horticulture crop requirements. SI.1.8: Promote production and productivity of organic horticultural crops The strategy recognises the importance and potential of organic horticulture as the cultivation of plants for their fruits, flowers or vegetables but naturally, i.e. with minimal chemical fertilisers or any other artificial tools and techniques. It also involves the application of eco-friendly practices of soil building and pest management, such as the application of organic manures, compost, biological pest control agents, and following mixed cropping and crop rotation patterns. The following are proposed key actions to realise the intervention; i. Create awareness on the use of organic horticultural produce; ii. Promote production of organic agro-inputs. SI.1.9: To promote the production of horticultural raw materials for industrial uses i. Continue protection of local industries through tax reforms on horticultural pulps and concentrates importation; ii. Encourage the establishment of local industries for the production of concentrates and pulps; iii. Promotion of processed horticultural commodities. SO.2: Promote production and consumption of bio-fortified, nutritional and medicinal indigenous fruits, vegetables, herbs and spices Indigenous fruits and vegetables play an important role in providing essential vitamins, minerals and dietary fibre. On the other hand, indigenous spices have been significantly used for their medicinal and curative properties. Unfortunate, indigenous horticultural plants are in doubt due to progress made in various development interventions such as farm expansion, the spread of urban areas, etc. However, there are signs of public awareness and positive trends in the consumption and marketing of indigenous fruits, vegetables, herbs and spices as an important solution against some illnesses. Furthermore, such awareness is supported by several government efforts aiming to promote indigenous plant species through policies and plans. Also, many campaigns conducted on control of non-communicable diseases emphasise the consumption of fruits and vegetables, including indigenous ones. This strategic objective brings forward critical issues related to the nutrition and health promotion aspects by producing and consuming nutritional and medicinal indigenous horticultural produce and products. The following interventions are proposed:- NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 31 SI.2.1: Promote consumption of fruits and vegetables to improve micro-nutrient intake at the household level This intervention seeks to improve dietary diversity in Tanzania. Traditional horticultural crops are nutrient-rich hence crucial in a balanced healthy diet. Both exotic and traditional African vegetables and fruits (TAVFs), spices and herbs, which have not been important mainly to the urban population in the past, have been proven to be nutritious. Moreover, such plants are highly adaptive to the African environment thus need to be promoted among the horticultural value chains. Below are the key actions for this intervention. i. Conduct a national campaign on conservation, production and utilisation of both nutritious and medicinal (nutraceutical value) exotic and indigenous fruits, vegetables, herbs and spices; ii. Disseminate innovation and information on conservation, production and processing of exotic and indigenous fruits, vegetables, herbs and spices; iii. Integrate the exotic and indigenous beneficial plants aspect into education curriculum at primary and tertiary education levels; iv. Promote consumption of horticultural produce of all kinds at the household level to reach WHO recommended target of 400gm per person per day of vegetable and 300gm of fruits per person per day. SI.2.2: Promote collection and conservation of germplasm This intervention seeks to address the challenges of genetic erosion to safeguard the biodiversity of indigenous vegetables, fruits, herbs and spices. The key actions are: i. Germplasm collection and conservation of indigenous fruits, vegetables, herbs and spices; ii. Characterisation and documentation of germplasm; iii. Recognition and strengthening of the existing gene banks in the country; iv. To build the capacity of the institution responsible for germplasm collection and conservation. SI.2.3: Attract investment in the manufacture of medicinal and cosmetic products Essentially, this intervention unveils business opportunities within the medicinal fruits, vegetables, herbs and spices. The ultimate objective is to scale up and commercialise medicinal and cosmetic plant products in Tanzania. This involves the identification of critical areas which are attractive to the private sector, particularly the pharmaceutical industry. The following are the actions to realise the intervention. i. Encourage development partners to join and support the agenda and foster information sharing; ii. Establish PPP initiatives on investment, promotion, product development and use of medicinal horticultural crops or cosmetic extracts; and NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 32 iii. Highlight critical food safety issues associated with the production and consumption of medicinal horticultural crops along the value chain. SO.3: Strengthen Research and Development Research and Development (R&D) intervention in the horticulture industry is essential; adaptive research on horticulture will help to strengthen the industry. Further, horticulture research will help foster innovation for addressing technological barriers and up-scaling the existing technologies. This strategic objective seeks to promote Research and Development (R&D) activities in seed technology, plant nutrition, plant health and value addition. It intends to foster innovation availability and farmers’ accessibility to the appropriate technology and Good Agricultural Practices (GAP). Specific actions for addressing technological barriers and up-scaling the existing technologies are presented. The strategy prioritises the multiplication and distribution of local improved horticulture innovation technologies and strengthening extension services. The key interventions are:- SI.3.1: Support and strengthen Research and Development The intervention focuses on building the capacity of research institutions to offer cost-effective and efficient technologies in production, post-harvest handling, processing, pest and disease management and marketing. The key actions for this program activity are itemised below. i. Equip national technology and innovation plant health clinic - laboratories with working facilities, equipment and gears to meet accredited international standards; ii. Enhance public research institutions through increased funding and modern infrastructure. iii. Increase human resource capacity in the horticultural industry, including the number of researchers in strategic horticultural areas such as breeding, germplasm conservation, plant health, and soil health. iv. Strengthen linkages and national staff attachment with the international institution; SI.3.2: Enhance and secure intellectual property registration and enforcement mechanisms The technology and innovation support institutions need to be supported with appropriate mechanisms to protect their innovations. This can be achieved by: i. Customise proper regulations and procedures on intellectual property (IP); ii. Propose incentives for innovative activities by domestic enterprises or individuals; iii. Facilitate the linkage between technology developers and users; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 33 SI.3.3: Strengthen horticultural seed system The strategy tasks to carry out the production of organic and inorganic inputs, inspection and certification of quality horticulture seeds and planting materials. Such inspections will check the multiplication of true to type seedlings and possibilities for a breakdown of disease resistance. The focus will be to improve quality and traceability. The action will include:- i. Strengthen quality-control mechanism for certification and verification of standards of horticulture planting materials (seeds and seedling); ii. Educate producers on standards and certification procedures for the production of quality true to type planting material (seeds and seedlings). SO.4: Promote marketing, market access and trade facilitation This strategic objective seeks to address Small-scale Farmers Horticulture Empowerment and Promotion (SHEP) approach through the “demand-driven initiatives” side of various horticultural products produced in Tanzania. It aims to promote farming as a business on the one hand and empower and motivate farmers, both of which lead to farmers changing altitudes from ‘grow and sell’ to ‘grow to sell’. These may include but are not limited to four (4) marketing business models. The following strategic interventions are proposed. Figure 3: The four horticulture marketing model (SHEP approach) NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 34 SI.4.1: Link farmers to off-takers and commercial marketing entities This initiative will address the current challenge of inadequate linkages between farmers and off-takers or marketing entities. The initiative will allow most small-scale farmers to connect to the regional and international markets and therefore increase their chances to conduct export business themselves. It is an important step towards developing formal markets. Major action under this strategic intervention includes:- i) Building the capacity of farmers to conduct a market survey with which farmers can assess the opportunities potentially available in the dynamic market conditions; ii) Establish a database of potential regional and international markets of strategic horticultural crops in compliance with global certification standards requirements (GAPs); and iii) Facilitate match-making between farmers and large-scale marketing companies/ buyers, which the central and local governments can facilitate. SI.4.2: Establish horticulture terminal wholesale markets The initiative involves establishing an alternative marketing structure through terminal wholesale markets that operate parallel to and in addition to the present system of many wholesale markets common in Tanzania. At present, the horticultural supply chain has multi-layered marketing channels and lack market infrastructure. The intervention will be achieved through the following actions:- i. Establish essential infrastructural services for product distribution; cold storage and packhouses (sorting, grading and packing), proper integration of post-harvest technology into marketing supply- chain to meet adequate quantity and quality produce; ii. Facilitate the establishment of a transparent and efficient platform for the sale and purchase of produce by connecting growers through Growers’ Associations (AMCOs) with farmers and wholesale buyers in various Tanzanian markets; iii. Establishment and improvement of horticultural collection centres; iv. Establishment of one-stop centre to market practitioners of horticultural produces to save time and improve efficiency; v. Facilitate vertical coordination of farmers through cooperatives, contract farming and retail chains for better delivery of produce to reduce market risk. SI.4.3: Promote Commodity Exchange (ECX) and digital marketing Market linkages can be promoted by establishing “digital marketing platforms”. A healthy website with a strong social media presence is a dynamic way of promoting market linkages. A user-friendly and technically sound website helps attract more potential clients. The following are proposed actions; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 35 i. Promote the use of Commodity Exchange (ECX) and digital marketing platforms that target potential online buyers for business transactions; ii. Enhance AMCOs capacity to sell directly to the ECX. SI.4.4: Strengthen marketing information system This intervention ensures that information reaches a critical mass of actors within the horticultural value chain for timely decision making. It is proposed against the background that lack of market research results and information is a major problem facing the augmentation of marketing efficiency in the Tanzanian horticultural industry. The followings are the proposed actions: i. Strengthen and promote the use of ICT in providing market information to horticulture farmers on Automated Horticulture Marketing System; ii. Promote the use of existing ICT applications such as TAHA marketing information system and M-Kilimo; iii. Conduct dialogue through Public-Private Partnership with mobile phone companies operating in the country for undertaking marketing research and information systems sharing; iv. Review and integrate existing horticulture marketing information systems; v. Establishment of off-takers platforms for sharing information on overseas market opportunities. SI.4.5: Improve market intelligence and dissemination across the whole value chain. This intervention seeks to build value chain actors’ capacity To increase its utility, the information has to be made “user friendly” and readily available by more traditional means and electronically. This information sharing will include promotional campaigns both at domestic and international levels. The following are proposed actions:- i. Promote SHEP market survey where the farmers are the key actors to collect information on market needs and seek appropriate business chances. ii. Increase and maintain production and supply of horticultural produces based on market requirements; iii. Promote the Tanzania horticultural commodities through the use of diplomatic missions; iv. Participate in international trade fairs through TanTrade and other avenues; v. Capitalize in business opportunity on the regional block where Tanzania is a member such as taking advantage of preferential trade agreements (PTAs)- EAC, SADC etc.; vi. Establish and strengthen the system of capturing export data on prices, quantities and destination countries; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 36 vii. Establish and strengthen the mechanism of capturing data on prices and quantities in the local markets; SI.4.6: Promote adherence to quality, food safety standards and certification. The certification processes in Tanzania need to be established for Good Agricultural Practices and strengthened in food safety standards for national and international. The following are proposed actions: i. To establish, strengthen and promote quality assurance systems at a national level and ongoing initiatives done by the private sector in the country; ii. Enhancing skills and professionals in certification for development and implementation of effective quality assurance systems; iii. Building capacity of producers in compliance with food safety standards and quality assurance for national and international requirements; iv. Establishment of funding mechanism for certification process; v. Establishment of national certification bodies; vi. Capacity building to institutions/agencies for service provision to agro-processors and exporters. SO.5: Improve logistical infrastructures related to packaging, storage and transportation facilities This strategic objective seeks to improve the logistical infrastructure in Tanzania to lower costs of doing business, promote trade competitiveness, and reduce post-harvest losses. Accelerated access to growth markets for horticultural is a key driver of investment in the horticulture industry. Below are the actions proposed to improve the logistical infrastructures. SI.5.1: Strengthen handling systems and transport infrastructure (railways, ports, airfreight services) to cater for the needs of perishable horticultural produces. This intervention seeks to strengthen and improve the storage, handling and transport infrastructure for Horticultural produces. These infrastructures include cold storage facilities, pack houses, refrigerated trucks and leader containers, all needed for safe products and adequate volumes at destination points. The following are the proposed actions: i. To establish a robust National cold chain management system on transportation of perishable horticulture produce that will enable all the regulators (TANROADS, TRA, Traffic Police, WMA, LGAs etc.) to give fast track services whenever dealing with perishable cargo; ii. To establish a “green” belt to fast track clearance at the ports for quick horticulture cargo transit; iii. To improve rural feeder roads on high horticultural potential areas; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 37 iv. To promote investment in refrigerated tracks and cold rooms for transporting and storage of fresh horticultural produce; v. To establish and maintain a port terminal dedicated to horticultural produce and other perishable goods to facilitate trade efficiency and reduce post-harvest losses. SI.5.2: Establish service-oriented collection centres This intervention seeks to build a supply industry that will guarantee a consistent and continuous supply of fresh horticultural produce. i. To establish satellite collection centres including; cooling, sorting, grading, and packaging as primary services; ii. To establish packhouses to enable farmers to meet customers’ quality requirements and allow appropriate planning for planting. SO.6: Strengthen coordination, institutional and policy framework The horticulture industry in Tanzania involves various players along the value chain that requires strong coordination through planned institutions guided by policy, established laws and regulations. Therefore, the strategy success depends upon a strong institutional framework at the national level to coordinate all actors to ensure strategic activities are well embedded and implemented by actors as stipulated. The following are strategic interventions and proposed actions. SI.6.1: Strengthen the institutional framework In Tanzania, the horticulture industry does not have a well organized institutional framework. The Ministry responsible for Agriculture has neither a horticultural department nor an organization with a regulatory or legal mandate to oversee horticulture issues. This necessitates the need to have an institutional framework that spells out the position, roles and responsibilities of the public and private sectors. There is a strong demand from stakeholders to have a regulatory board for horticulture that will control and oversee the general development of the industry. This will be achieved through the establishment of the horticulture governing organ. After being established and guided by law, the organ will be an overseer of the industry. The organ will be under the Ministry responsible for Agriculture and termed Horticulture Development Agency or Horticulture Development Board with a regulatory mandate. The organ will be responsible for coordinating and regulating all actors along the value chain. The following are proposed actions:- i. Enacting a law for the establishment of national horticulture governing organ; ii. Establish the national horticulture governing organ; iii. Prepare regulations for the operationalization of the national horticulture governing organ; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 38 SI.6.2. Strengthening coordination In Tanzania, the horticulture industry is not well coordinated, such that various actors and member-based organizations are working independently. For the industry to thrive, national coordination is imperative. The country needs a platform that comprises all actors in the horticulture industry. The platform will bring together various value chain actors to dialogue issues of mutual interest. The platform’s composition will include but is not limited to farmers associations representing horticulture producers, consumers, input manufacturers and suppliers, processors, exporters, transporters, government enforcement & support service provider agencies, research and training, government lead Ministries representatives and non- government institutions. The following are key actions to be undertaken:- i. Establish and strengthen specific horticultural crop platforms at local and national levels; ii. Linking the established specific horticultural crop platforms with the national policy and advocacy platforms; SI.6.3: Facilitate the establishment of horticulture agenda There is a need to facilitate review of the Agricultural policy (2013) to have an independent chapter for the horticulture industry which will address nutritional security (Hidden hunger), commercial entity, job creation, youth and women inclusion to recognize the industry uniqueness. SI.6.4: Facilitate the establishment of a horticulture professional registration board. The outcome of this intervention is to have a competent and credible core group of horticulture professionals and practitioners in the industry. The main objective is to safeguard horticulture professionalism guide the proper operation of the industry. This will include, among others, inspection and certification of horticultural produce, setting a code of conduct and ethics to horticultural professionals and horticultural enterprises. Once these are is in place, it will safeguard and enhance the competitiveness and the wellbeing of the industry. In Tanzania, the horticulture industry does not have a horticultural professional registration board entrusted to maintain control or oversee the occupation’s legitimate practices. This has led to irregularities in many aspects of the horticulture industry. Therefore, it is necessary to have such an organ in the country. The following key actions are proposed:- i. Facilitation of the establishment of a regulatory organ (Tanzania Horticultural Professionals Registration Board (TAHOPRO) ii. Develop an inventory of trainers who offer relevant horticultural courses to equip skills to the value chain actors; iii. Establish a code of conduct and ethics amongst horticultural professionals and horticultural enterprises. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 39 SO.7: Enhance capacities of actors along the horticulture value chain Horticulture is a dynamic, sophisticated and labour intensive industry. It is the fastest growing industry in agriculture with numerous evolving technologies. Hence, the actors need to be knowledgeable to cope with technological changes. The following are strategic interventions to address capacity building needs along the Horticulture value chain. SI.7.1: Build local skills and knowledge base The horticulture industry’s uniqueness requires sufficient industry-specific technological skills at the local level. The industry needs high technology, knowledge-intensive and focuses on supplying safe and hygienic nutritional food for local and export markets. Therefore, for that reason, there is a need to develop local capacity skills to serve the horticulture industry. The following actions are proposed:- i. To promote formal and informal innovation activities focused on direct linkages with the private sector through industrial attachments, internships, mentorship and coaching programmes, youth incubation schemes, technology-based incubation centres, and apprenticeships schemes; ii. Document lessons learned, good practices and success stories for improvement and up-scaling. SI.7.2: Human skills development to accelerate the absorption, utilization, and maintenance of technologies Based on current experiences in human resource skills challenges within the horticulture industry, together with the unfolding opportunities in the region and beyond, the following actions are being proposed. i. Conduct regular specialized training intended to capture the ever-changing dynamics of the industry; ii. Enhance the capacity of the Technical Vocational Education and Training (TVET) system; iii. Invest in proven models of technology transfer and skills development in the country to equip horticultural practitioners with practical skills using the proven existing and emerging models; iv. Invest in selected high-level specialized skills for analysts and researchers who can lead scientists to the industry. v. Strengthening linkages between the private sector and public institutions by establishing modality for collaboration and consultative forum between the government and private sector along the value chain. SO.8: Facilitate financing and investment of the horticulture industry The provision of affordable and accessible financial services is essential for the development of the horticultural industry due to its investment being capital intensive. It, therefore, requires collaborative efforts from various actors, including government, financial institutions, bilateral and multilateral lending institutions, NGOs, SACCOS and development partners. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 40 However, such financial services are inaccessible to many medium and small-scale operators due to high-interest rates, low level of awareness and low credit portfolio for agriculture by financial institutions. Programs financing the industry are uncoordinated, resulting in duplication of activities. This can partly be attributed to a lack of prioritizing areas that need financing. However, most large-scale farmers and medium-scale commercial horticulture farms have a more comprehensive range of credit packages and options, contrary to small-scale farmers that lack access to credit. Such credit exists; it is not tailored to meet their production needs. Therefore, this strategic objective seeks to increase financing and investments of the industry by deploying the following interventions:- SI.8.1: Improve government budgetary allocation and proper coordination of development partners (DPs) funds to the horticulture industry Horticulture budgetary allocations are currently meagre despite the potential and revenue in government coffers every year. The following are the actions to address the intervention. i. Increase annual budget allocation to horticulture cluster in the Ministry responsible for Agriculture; ii. At least 20% of horticulture crops cess currently collected by central government and local government authorities (LGAs) should be ploughed back to the industry for extension, coordination, research and development; iii. Establishment of Horticulture Development Fund (HDF); iv. Establish a mechanism to coordinate funding by development agencies to avoid duplication and enhance enterprise diversification; v. Encourage the industry’s financing through programmes and projects by local and international funding institutions and development partners. SI.8.2: Provide an enabling environment for the private sector and other stakeholders to establish affordable credit facilities to support horticultural investments and build management capacity for loanees. i. Establish horticultural credit facilities with conditions that fit farming cycles, including adequate grace periods and affordable interest rates. SI.8.3: Provide an enabling environment to insurance companies to develop appropriate and affordable enterprise insurance products to support horticultural investments. The following actions are to be undertaken:- i. Conduct campaign on the importance of ensuring horticulture industry to all registered insurance companies; ii. Create awareness to horticultural producers and other value chain actors on the importance of industry insurance. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 41 SI.8.4: Engage the private sector in identifying the industry’s investment priorities. The following actions are proposed:- i. Identify and dissemination industry’s investment opportunities; ii. Facilitate private sector to invest in manufacturing of horticulture production inputs and value addition/processing facilities; iii. Facilitate the establishment of national horticulture investment forum. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 42 4.0 ACTION PLAN AND IMPLEMENTATION ARRANGEMENT (MATRIX) The implementation arrangements are required to implement this strategy effectively. Eight (8) key strategic objective areas have been identified below Table 8 shows the intervention and time frame that will be used to gauge the strategy’s performance. Table 9: Action plan STRATEGIC INTERVENTION AND ACTION TIME FRAME (YEAR) 2021/ 22 2022/ 23 2023/ 24 2024/ 25 2025/ 26 2026/ 27 2027/ 28 2028/ 29 2029/ 30 2030/ 31 SO.1: Increase production and productivity capacity of fresh, processed, and organic horticultural produces in Tanzania SI.1.1 Increase access of quality, tools, agriculture inputs and implements i) Establish, strengthen and register public and private mother tree orchards (fruits and spices) and commercial nurseries ii) Facilitate the establishment of inspection systems and certification systems iii) Strengthen of registration system of organic and inorganic pesticides iv) Increase the production capacity of quality seeds and planting materials v) Establish linkages with local, regional and international organisations and agencies (tree fruit nurseries and vegetable seed companies to access better varieties) vi) Strengthens supply of fertilisers, agrochemicals, botanicals and biological control agents NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 43 vii) Strengthen the capacity of institutions responsible for inspection and certification of seeds viii) Enhance the supply of horticultural equipment SI.1.2: Strengthen insect pests and disease control mechanisms i) Strengthen early warning system and disseminate information for surveillance ii) Horticultural crop field scouting iii) Employ IPM techniques and methods SI.1.3: Strengthen horticultural extension services i) Provide tailor-made training (capacity building) to actors and extension workers along the value chain ii) Establishment of farmers’ business schools and hubs (centres’ of excellence – booth camps) iii) Develop extension guide manuals for horticultural crop production iv) Introduce SHEP approach making farmers undertake the market survey and acquire market- oriented production skills v) Promote organic crops practices and extension services vi) Strengthen extension-research- farmers linkages and establish an early warning system vii) Promote establishment and uses of an electronic extension system (e.g., M-Kilimo etc.) NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 44 viii) To enhance women and youth skills, access to financial services and participation in the horticultural industry ix) Promote proper land use and soil fertility management S1 1.4: Promote efficient horticultural production systems i) Promote Integrated horticultural production systems ii) Enhance Climate- Smart Horticulture iii) Production of climate-smart horticulture manual SI 1.5: Address pre and post-harvest losses i) Promote pre- and post-harvest best practices (Good Agricultural Practices (GAP) and Good Handling Practices (GHP) on horticultural crops ii) Promote best harvesting practices on harvesting and post-harvest handling techniques (i.e., use of maturity indices) and tools to prevent damages, gentle handling etc. iii) Promote traditional pest harvest handling (zero- energy cooling chamber systems – ZECC) iv) Promote the use of improved package and packaging practices v) Promote the use of national, regional and international quality standards vi) Strengthen handling of transit and cold chain management services NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 45 vii) Develop a strategy to address pre- and post-harvest losses for strategic horticultural produces SI.1.6: Horticultural data capture and management system i) Strengthen the system of collection and management of horticultural data ii) Use of ICT in mapping farm by using modern digital technologies, e.g., drones, Satelite images, GIS etc. iii) Establish a mechanism of horticulture import and export data consolidation from various sources iv) Build capacity of WAEOs/VAEOs for horticulture data collection v) Building farmers organisations, groups and cooperative societies capacities in data collection and record keeping SI.1.7: Promote production and productivity of current and emerging priority strategic horticultural crops i) Build capacity of regions and districts in analysing and identifying their strategic horticultural crops ii) Establish district horticulture forum and platform involving all value chain actors iii) Training of extension staff specific technical skills in production & productivity, pre- and post-harvest management of strategic horticultural crop produce as per quality and standard required by marketing NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 46 iv) Improvement of market infrastructure (including packhouse, shade house and dry and cooling chambers) as per horticulture crop requirements) SI.1.8: Promote production and productivity of organic horticultural crops i) Create awareness on the use of organic horticultural produces ii) Promote production of organic agro- inputs SI.1.9: Promote production of horticultural raw materials for industrial uses i) Continue protection of local industries through tax reforms on horticultural pulps and concentrates importation; ii) Encourage the establishment of local industries to produce horticultural pulps and concentrates. iii) Production of processed horticultural commodities SO.2: Promote production & consumption of bio-fortified, nutritional and medicinal indigenous fruits, vegetables, herbs and spices S.2.1: Promote consumption of fruits and vegetables to improve micronutrients intakes at households levels i) Conduct a national campaign on production and utilisation of nutritious and medicinal (nutraceutical value), exotic and indigenous fruits, vegetable, herbs and spices NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 47 ii) Dissemination of innovation and information on conservation, production, processing, utilisation of nutritional, medicinal of exotic and indigenous fruits, vegetables, herbs and spices iii) Integrate the exotic and indigenous beneficial plant aspects into the education curriculum of primary and tertiary education on good nutrition practices iv) Promote consumption of horticultural produce at the household level to reach WHO recommended target of 400gm of vegetables per person per day and 300gm of fruits per person per day SI.2.2: Promote collection and conservation of germplasm technologies i) Germplasm collection and conservation of indigenous fruits, vegetables, herbs and spices ii) Characterisation and documentation of germplasm iii) Recognition and Strengthening of the existing gene banks in the country iv) To build the capacity of institutions responsible for Germplasm collection and conservations SI.2.3: Attract investment in the manufacture of medicinal and cosmetic products i) Encourage development partners to join and support the agenda and foster information sharing NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 48 ii) Establish PPP initiatives on investment, promotion, product development and use of medicinal horticultural crops or cosmetic extracts iii) Highlight critical food safety issues associated with the production and consumption of medicinal horticultural crops along the value chain SO.3: Strengthen research development, innovation and technologies SI.3.1: Support and strengthen R&D Institutions i) Equip national technology and innovation plant health clinic - laboratories with working facilities, equipment and gears to meet accredited international standards ii) Enhance public and private research institutions on research- extension farmers linkages through increased funding and modernised infrastructure; iii) Encourage local breeders to undertake breeding through partnerships and collaboration with regional and international research institutions., to strengthen Research-Extension- Farmer linkages to increase and improve horticulture production and quality, NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 49 iv) Increase Human resource capacity in the Horticultural subsector (Researchers and field officers) v) Strengthen linkages and national staff attachment with the international institution. SI.3.2: Enhance and secure intellectual property registration and enforcement mechanisms i) Establish appropriate mechanisms for horticultural technology innovations protection ii) Customise proper regulations and procedures on intellectual property rights (IP) iii) Propose incentives scheme for innovative activities by domestic enterprises or individuals iv) Facilitate the linkage between technology developers and users v) Facilitate awareness creation on intellectual property rights (IPR) SI.3.3: Strengthen horticultural seed system i) Strengthen quality- control mechanism for inspection, certification and verification of standards of horticulture planting materials (seeds & seedling) ii) Educate producers on standards and certification procedures for the production of quality true to type planting materials (seeds and seedlings) NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 50 SO.4: Promote marketing and market access of horticultural produce and trade facilitation by addressing the SHEP approach SI 4.1: Link farmers to off-takers and large commercial marketing entities i) Facilitate standard horticultural contract farming and out- growers schemes ii) Establish a database of potential regional and international markets of strategic horticultural crops in compliance with global certification standards requirements (GAPs) iii) Building the capacity of farmers to conduct a market survey with which farmers can assess the opportunities potentially available in the dynamic market conditions and iv) Facilitate match- making between farmers and large- scale marketing companies/ buyers, which the central and local governments can facilitate SI.4.2: Establish horticulture terminal wholesale markets i) Establish essential infrastructural services for product distribution; cold storage and packhouses; sorting, grading, and packaging, proper integration of post- harvest technology into marketing supply chain to meet adequate quantity and quality produce NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 51 ii) Facilitate the establishment of a transparent and efficient platform for the sale and purchase of produce by connecting growers through Horticultural Growers’ and Marketing Associations (HMOs) with farmers and wholesale buyers in various Tanzanian markets iii) Establishment and improvement of horticultural collection centres iv) Establish a one- stop centre to market practitioners of horticultural produces to save time and improve efficiency v) Facilitate vertical coordination of farmers through cooperatives, contract farming and retail chains for better delivery of produce to reduce market risk SI 4.3: Promote Commodity Exchange (TMX) and digital marketing i) Establish & promote the use of Commodity Exchange (ECX) and digital marketing platforms that target potential online buyers for business transactions ii) Enhance AMCOs capacity to sell directly to the ECX SI 4.4: Strengthen market information system i) Strengthen and promote the use of ICT in providing market information to horticulture farmers on Automated Horticulture Marketing System NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 52 ii) Promote the use of existing ICT applications such as TAHA marketing information system and M-Kilimo iii) Conduct dialogue through Public- Private Partnership with mobile phone companies operating in the country for undertaking marketing research and information system sharing iv) Review and integrate existing horticulture marketing information systems v) Establishment and conduct of off-takers platform for sharing information on overseas marketing opportunities SI.4.5: Improve market intelligence and dissemination of information across the whole value chain i) Promote SHEP Market Survey where the farmers are the key actors to collect information on market needs and seek appropriate business chances ii) Increase and maintain production and supply of horticultural produces based on market requirements iii) Promote the Tanzania horticultural commodities through the use of diplomatic missions iv) Participate in international trade fairs through TanTrade and other avenues NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 53 v) Capitalise in business opportunity on the regional block where Tanzania is a member such as taking advantage of preferential trade agreements (PTAs)- EAC, SADC etc. vi) Establish and strengthen a system of capturing export data on prices, quantities and destination countries vii) Establish and strengthen the mechanism of capturing data on prices and quantities in the local markets SI.4.6: Promote adherence to quality, food safety, standards and certification system i) To establish, strengthen and promote quality assurance systems at the national level and strengthen ongoing initiatives done by the private sector in the country ii) Enhancing skills and professionals in certification for development and implementation of effective quality assurance systems iii) Building capacity of producers in compliance with food safety standards and quality assurance for national and international requirements iv) Establishment of funding mechanism for certification process v) Establishment of national certification bodies vi) Capacity building to institutions/agencies for service provision to agro-processors and exporters NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 54 SO.5: Improve logistical infrastructures related to packaging, storage and transportation facilities SI.5.1: Strengthen post handling systems in the transport infrastructure (railways, posts, airfreight services) to cater for the needs of perishable horticultural produces i) To establish a robust national cold chain management system on transportation of perishable horticulture produce that will enable all the regulators (TANROADS, TRA, Traffic Police, WMA, LGAs etc.) to give fast track services whenever dealing with perishable cargo ii) To establish the “green belt” to fast track clearance at the ports for quick horticulture cargo transit iii) To improve rural feeder roads on high horticultural potential areas iv) To promote investment in refrigerated tracks and cold rooms to transport and store fresh horticultural produce v) Establishing and maintaining port terminals dedicated to horticultural products and other perishable goods facilitates trade efficiency and reduces post- harvest losses SI.5.2: Establish service-oriented satellite collection centres and packhouses i) Establish satellite collection centres and packhouses, including cooling, sorting, grading and packaging as primary services NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 55 ii) To establish packhouses to enable farmers to meet customers’ quality requirements and allow appropriate planning for planting SO.6: Strengthen coordination, institutional and policy framework SI.6.1: Strengthen the institutional framework i) Enacting a law for the establishment of national horticulture governing organ ii) Establish the national horticulture governing organ iii) Prepare regulations for the operationalisation of the national horticulture governing organ SI.6.2. Strengthening coordination i) Establish and strengthen specific ational horticultural crop platforms at local and national levels ii) Linking the established specific horticultural crop platforms with the National policy and advocacy platforms SI.6.3: Facilitate the establishment of horticulture agenda Ensure horticulture appear as an independent chapter in Agriculture policy SI.6.4: Facilitate the establishment of a horticulture professional registration board i) Facilitation of the establishment of a regulatory organ (Tanzania Horticultural Professionals Registration Board (TAHOPRO) ii) Develop an inventory of trainers and professionals who offer relevant horticultural courses to equip skills to the value chain actors NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 56 iii) Establish a code of conduct and ethics amongst horticultural professionals and horticultural enterprises SO.7: To enhance capacity of actors along the horticulture value chain (i.e. improving participation of youth and women in horticulture production) SI 7.1: Build local skills and knowledge base i) To promote formal and informal innovation activities focused on direct linkages with the private sector through industrial attachments, internships, mentorship and coaching programmes, youth incubation schemes technology-based incubation centres, and apprenticeships schemes ii) Promote triple helix principles where there is a collaboration between the government, the TVET and the private sector iii) Establishment of National Qualification Frameworks, which comply with international standards iv) Document lessons learned, good practices and success stories for improvement and up-scaling SI.7.2: Human skills development to accelerate the absorption, utilisation, and maintenance of technologies i) Conduct regular specialised training intended to capture the ever-emerging dynamics of the industry NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 57 ii) Enhance the capacity of the Technical Vocational Education and Training (TVET) system iii) Invest in proven models of technology transfer and skills development in the country to equip horticultural practitioners with practical skills using proven existing and emerging models iv) Invest in selected high-level specialised skills for analysts and researchers who can provide lead scientists to the industry v) Strengthen strategic linkages between the private sector and public institutions by establishing modality for collaboration and consultative forum between the government and private sector along the value chain SO.8: Facilitate financing and investment of the horticulture industry SI.8.1: Improve government budgetary allocation and proper coordination of development partners (DPs) funds to the horticulture industry i) Increase annual budget allocation to horticulture cluster in the Ministry responsible for Agriculture ii) Plough back to the horticulture industry at least 20% of Horticulture Crops cess currently collected by Central Government and Local Government Authorities (LGAs) for coordination, research and development NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 58 iii) Establishment of Horticulture Development Fund (HDF) iv) Establish a mechanism to coordinate funding by development agencies to avoid duplication and enhance enterprise diversification v) Encourage the industry’s financing through programs and projects by local and international funding institutions and development partners vi) Establish financing mechanism for the implementation of the strategy SI.8.2: Provide an enabling environment for the private sector and other stakeholders to establish affordable credit facilities to support horticultural investments and build management capacity for loanees i) Establish horticultural credit facilities with terms and conditions that fit farming cycles, including adequate grace periods and affordable interest rates SI.8.3: Provide an enabling environment for private insurance companies to develop appropriate and affordable enterprise insurance products to support horticultural investments i) Conduct campaign on the importance of ensuring horticulture industry to all registered insurance companies ii) Create awareness to horticultural producers and other value chain actors on the importance of industry insurance SI.8.4: Engage the private sector in identifying the industry’s investment priorities i) Identification and dissemination of industry’s investment opportunities NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 59 ii) Facilitate private sector to invest in manufacturing horticulture production inputs and value addition/ processing facilities NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 60 5.0 INSTITUTIONAL ARRANGEMENTS, COORDINATION AND FINANCIAL MANAGEMENT The implementation of this horticulture development strategy will utilize the existing government systems 5.1. National implementing structure Ministry of Agriculture: The Ministry supervises the sector. It liaises between the sector and the legislature and provides legal and policy guidance. The Ministry will ensure that horticulture industry strategy aims are aligned with national agricultural policy, presented and discussed at the national level and within Agricultural Sector Lead Ministries to enhance linkage with other central government institutions and other crops sectors. The Ministry will also play a key role by supporting a favourable environment for horticulture growth (taxes, regulations, agricultural policy) and possibly supporting the strategy’s implementation through various means (financial support, subsidies for horticulture inputs, advocacy to international donors). The United Republic of Tanzania will establish a nation coordination secretariat under the Directorate of Crops Development in the headquarters of the Ministry of Agriculture, as in the figure below. There will be two levels of implementation structure, one is at national level, and the other one will be at the regional and district level. Private-sector traders/exporters/processors: The government supports private sector companies (producers, buyers, processors, exporters etc.) to become a driving force for implementing the strategy through service provision and linking with farmers in availing necessary inputs and technologies. By implementing shared functions and public-private partnerships, these parties can participate in improving the efficiency of the value chain and act as a valuable relay for the improvement of agricultural/harvest/ post-harvest practices on the field. Horticulture growers and farmer organizations: Horticulture growers and their organizations have been central to the Horticulture Industry Strategy for over ten years. Farmers will mobilize themselves to adopt improved horticulture varieties and good agricultural practices to ensure increased productivity and incomes. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 61 6.0 BUDGET 6.1 Proposed sustainable sources of funds and funding mechanisms for implementation of the strategy Implementation of the strategy requires sustainable funding of various activities proposed for each intervention. The cost of implementing the National Horticulture Strategy is expected to reach around TZS 4.7 trillion. This huge investment is needed for the successful implementation of the strategy. Given its scale, horticulture industry key stakeholders recognise the need to go beyond traditional sources of finance and develop innovative ways to mobilise financial resources. Efforts will be directed towards mobilising more finance from domestic sources alongside strategies to leverage private sector investment. Table 10 shows various funding sources and their target outcomes for implementing the National Horticulture Industry Strategy. Table 10: Proposed sources of funding and their target outcomes for implementation of the strategy STRATEGIC OBJECTIVE INTERMEDIATE RESULT BUDGET (Tshs) Millions SOURCE SO1: Increased production and productivity capacity of fresh, processed, and organic horticultural produces by 2030 SI. 1: Access to quality tools, agriculture inputs and implements Increased 5,480.00 SI 1.2: Insect pest and disease control mechanism strengthened 2,000.00 SI 1.3: Horticulture extension service strengthened 23,500.00 SI 1.4: Efficient horticultural production system promoted 4,000.00 SI 1.5: Pre-and post-harvest best practices adopted 3,500.00 SI 1.6: Horticultural data capturing systems established and strengthened 15,600.00 SI 1.7: Production and productivity of current and emerging priority strategic horticultural crops promoted 18,400.00 SI 1.8: Production and productivity of organic horticultural crops promoted 3,000.00 SI 1.9: Production of horticultural raw materials for industrial uses promoted 800.00 Sub Total (SO.1) 76,280.00 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 62 SO2: Promote production & consumption of bio-fortified, nutritional and medicinal indigenous fruits, vegetables, Herbs and spices improved by 2030 SI 2.1: Consumption of fruits and vegetables to improve micronutrients intakes at households levels promoted 4,000.00 SI 2.2: Collection and conservation of Germplasm technologies promoted 30,600.00 SI 2.3: Attracted investment in the manufacture of medicinal and cosmetic products 1,100.00 Sub Total (SO.2) 35,700.00 SO3: Strengthened Research and Development, innovation and technologies transfer/up- scaling by 2030 SI 3.1 Supported and strengthened R&D institutions 100,000.00 SI 3.2: Enhanced and secured intellectual property registration and enforcement mechanisms 10,000.00 SI 3.3 Strengthened horticultural seed system 10,000.00 Sub Total (SO.3) 120,000.00 SO4: Promoted marketing and market access of horticultural produce and trade facilitation by addressing the SHEP approach by 2030. SI 4.1: Farmers linked to off-takers and large commercial marketing entities 1,400.00 SI 4.2: Established horticulture terminal wholesale markets 800,600.00 SI 4.3: Established & promoted Commodity Exchange (ECX) and digital marketing 200.00 SI 4.4: Strengthened market information system 250.00 SI 4.5: Improved market intelligence and dissemination of information across the whole value chain 1,355.00 SI 4.6: Adherence to quality, food safety, standards and certification system promoted 404.00 Sub Total (SO.4) 804,209.00 SO5: Improved logistical infrastructure related to packaging, storage and transport facilities by 2030 SI 5.1: Strengthened post handling systems in the transport infrastructure (railways, posts, airfreight services) to cater to perishable horticultural needs 2,630,330.00 SI 5.2: Established service-oriented collection centres/satellite collection centres and packhouses 1,000,000.00 Sub Total (SO.5) 3,630,330.00 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 63 SO6: Strengthened coordination, institutional and policy framework by 2030 SI 6.1: The institutional framework strengthened 3,600.00 SI 6.2: Strengthened coordination 1,280.00 SI 6.3: Establishment of horticulture agenda facilitated 10.00 SI 6.4: Establishment of horticulture professional registration board facilitated 510.00 Sub Total (SO.6) 5,400.00 SO7: Enhance Capacity building of actors along with the horticulture value by 2030 SI 7.1: Local skills and knowledge base built in the industry 2,000.00 SI 7.2: Human skills developed to accelerate the absorption, utilization, and maintenance of technologies 2,510.00 Sub Total (SO.7) 4,510.00 SO8: Strengthened Financing and Investment system of the Industry by 2030 SI 8.1: Government budgetary allocation and proper coordination of development partners (DPs) fund to the horticulture industry improved 2,000.00 SI 8.2: Environment for the private sector and other stakeholders to establish affordable credit facilities to support horticultural investments and build management capacity for loanees enabled 2,400.00 SI 8.3: Enabling environment for private insurance companies to develop appropriate and affordable enterprise insurance products to support horticultural investments provided 135.00 SI 8.4: Private sector is engaged in identifying the industry’s investment priorities 245.00 Sub Total (SO.8) 4,780.00 GRAND TOTAL (Tshs) 4,681,209.00 NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 64 7.0 MONITORING AND EVALUATION The monitoring and evaluation system of the Tanzania Horticultural Development Strategy (THDS 2021-2031) tracks the implementation of the planned interventions and subsequently takes corrective measures on the implementation strategy when the need arises. Over the implementation period of the strategy, specific actions, responsibilities and resources that will move the industry to a higher level of performance will be mobilized. The actions will be monitored, assessed, and adjusted to deliver the strategic objectives within the set timeframe. The strategy will be reviewed on a mid-term basis and evaluated at the end by an independent evaluator. Critical Success Factors of the strategy: Critical Success Factors (CSFs) ensure an undertaking’s success. In the operationalization of the strategy, there will be inherent critical factors to bring about successful outcomes: These include: i. Good corporate governance; ii. Effective, efficient, transparency and strong leadership; iii. Effective communication and good PPP relations; iv. Adequate, skilled and professional human capital in the industry; v. Teamwork, cooperation and support from partners, collaborators and stakeholders; vi. The objectively-motivated political will to support the horticulture industry; vii. Increased number of satisfied internal and external customers; and viii. Effective monitoring, control and documentation of learning. The Ministry of Agriculture will undertake both internal and external monitoring and evaluation. There will be both mid-term and end of period monitoring and evaluation participatory. The monitoring activity will involve systematic and regular data collection, processing, analysis, and reporting of the MoA and relevant forums and stakeholders’ findings. The monitoring and evaluation will be primarily used to compare planned targets against achievements. It is an important tool that will enable stakeholders to detect deviations from the target plan in time and make the necessary corrections (Table 11). The evaluation’s overall objective will be to draw lessons from experiences gained during the implementation of the management intervention measures and convey them to MoA and other stakeholders to gauge the pace and impact of reducing the horticultural crop post-harvest losses envisaged in the implementation period. Specifically, the M&E exercise will involve: i. Assessment as to whether the action and targets set in the strategy are realistic; ii. Assessment as to whether the implementation of the NHDS is achieving the intended results; NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 65 iii. Assessment as to whether adequate resources (human resources and finance) are being mobilized to implement the industry; iv. Assessment of the efficiency and effectiveness of utilizing the available resources; v. Assessment of the reasons for failures in implementing some of the agreed activities; vi. Assessment of the performance of the Ministry responsible for agriculture in spearheading the implementation of the NHDS. Also, the Ministry of Agriculture will review the monitoring and evaluation system annually to determine elements for improvement. Furthermore, since the THDS is planned to be a strategy of 10 years, there will be an evaluation of the strategy implementation once every three years using an impartial, external evaluator to diagnose potential changes that might affect the performance of THDS during the remaining period of strategy implementation. NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 66 Table 11: Results monitoring matrix STRATEGIC INTERMEDIATE TARGETS MATCHED WITH KEY ACTORS OBJECTIVE RESULT EACH INTERMEDIATE RESULTS SO1: Increased IR1.1: Access to i) At least twelve (12) mother MoA, PO-RALG, production and quality agriculture fruit orchards established, TFRA, TARI productivity inputs, tools and rehabilitated, registered and capacity of equipment functional fresh, increased processed, and ii) Published Report on established MoA,PO-RALG, organic and functional commercial TFRA, TARI horticultural nurseries that were inspected produce by and certified 2030 iii) Published Report on the MoA, PO-RALG, strengthened registration TFRA, TARI system of organic and inorganic pesticides iv) Published progress reports on MoA, PO-RALG, the production capacity of TFRA, TARI quality seeds and planting materials increased by 40% v) Published progress report on MoA, PO-RALG, Established Linkages with Local, TOSCI, TARI regional and international organizations and agencies dealing with tree fruit nurseries and vegetable seeds to access better varieties vi) Published Report on Supply of MoA, PO-RALG, fertilizers, agrochemicals, TFRA, TARI botanicals and biological control agents strengthened vii) Published report on the MoA, PO-RALG, strengthened capacity of TOSCI, TARI institutions responsible for inspection and certification of seeds viii) Report on supply of MoA, PO-RALG, horticultural equipment TFRA, TARI enhanced IR1.2: Insect i) Early warning system and MoA, PO-RALG, Pests and diseases information dissemination TAPHA, TMA, control report produced and submitted TARI mechanisms to horticulture stakeholders strengthened strengthened NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 67 ii) Published periodical report on MoA, PO-RALG, horticulture crops field scouting PHS, TARI iii) Published periodical report on MoA, PO-RALG, engagement of IPM techniques/ TFRA, TARI methods on horticulture production and productivity and reduced incidence and occurrence of pests and diseases IR1.3: Horticulture i) Published progress reports on MoA, LGAs extension service the existence of Number of strengthened Actors and Extension workers trained along the horticulture value chain through tailor-made training programmes ii) Published progress reports on MoA, LGAs the existence of number of farmers’ business schools and hubs (centre’s of excellence – booth camps) established iii) Published Report on SHEP MoA, LGAs approach and market-oriented production skills adopted by all growers and horticulture extension workers iv) Published progress reports on MoA Extension guide manuals for horticultural crop production developed iv) Published Report on Extension- MoA research-farmers linkages and early warning systems established and strengthened v) Published progress reports on MoA, LGAs the uses of electronic extension systems (e.g., M-Kilimo) established and promoted vi) Published progress reports on MoA, LGAs the existence of number of women and youth skills, access to financial services, and participation in the horticultural Industry enhanced all over the country NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 68 vii) Published progress reports on MoA, LGAs various land use and soil fertility management techniques enhanced and adopted by farmers IR1.4: Efficiency i) Published progress reports on MoA, LGAs horticultural the existence of extension guide production system manuals for Climate Smart promoted Horticultural developed and produced ii) Published progress reports on MoA, LGAs the existence of number of actors and extension workers trained in integrated CSH production systems iii) Published progress reports on MoA, LGAs the number of Climate Smart Horticultural technologies promoted, enhanced and adopted IR1.5: Pre- and i) Published progress reports on MoA, TARI post-harvest best the existence of number of practices adopted Good Agricultural Practices (GAP) and Good Handling Practices (GHP) on horticultural crops promoted & adopted ii) Progress report on the number MoA, TARI of integrated post-harvest pest management (IPM) and best harvesting practices and post- harvesting handling techniques adopted iii) Progress report on the number MoA, LGAs of best handling practices (e.g., uses of maturity indices, gentle handling etc.) and tools to prevent damages promoted and adopted iv) Published progress reports on MoA, TARI the existence of number of traditional post-harvesting handling (e.g. Zero energy cooling chamber systems – ZECC) promoted NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 69 v) Published progress reports on MIT, MoA, TBS the existence of type and number of improved packages and packaging practices adopted vi) Progress report on the MIT, MoA, achievement of on transit and Ministry of cold chain management Transport practices adopted vii) Published progress reports on MoA, PO-RALG the existence of strategy to address pre-and post-harvest losses for strategic horticulture produced developed and published for users along the value chain IR1.6: Horticulture i) Published progress reports MIT, MoA data capture the existence of horticultural system practices data system collection and adopted management strengthened at all levels ii) Published report on Use of ICT MIT, MoA, TBS in mapping farm by using modern digital technologies such as drones, satelite images, GIS etc. established and strengthened iii) Published progress reports on MIT, MoA, TBS the existence of mechanisms of horticulture import and export data consolidation from various sources such as TRA, BOT, airport, border posts etc. established iv) Published progress report on MoA, PO-RALG trained WAEOs/VAEOs in horticulture data collection v) Published progress report on MoA, PO-RALG farmers organizations, groups and cooperative societies trained on data collection and record keeping NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 70 IR1.7: Promote i) Published progress reports on MoA, PO-RALG production and the capacity building actions productivity of the capacity building actions current and taken at the regions and emerging strategic districts in analyzing and horticultural crops identifying their strategic horticultural crops ii) Published progress reports on MoA, PO-RALG the established district horticulture forums and platforms involving all value chain actors iii) Published progress reports on MoA, PO-RALG the number of agricultural extension staff trained on specific technical skills in production and post-harvest management of strategic horticultural crop produce as per quality and standard required by marketing iv) Publish progress reports on the MoA, PO-RALG improved market infrastructure (including packhouse, shade house and dry and cooling chambers) based on the requirement of the strategic horticultural crops IR1.8: Promote i) Publish progress report on the MoA, PO-RALG, production and awareness campaign MoH productivity of conducted on the utilization organic of produces from organic horticultural horticulture farming produces ii) Publish progress report on the MoA, PO-RALG, production of organic agro- inputs for horticultural uses IR1.9: Promote i) Presence of established MoA, PO-RALG, production of reports and regulations through MIF horticultural raw continued protection of local materials for industries through tax reforms Ministry of industrial uses on importation of horticultural Investment (fruits) pulps and concentrates (TIC), ii) Published report on established MoA, PO-RALG, local industries for the MIF, TIC. production of horticulture pulps and concentrated NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 71 iii) Published report on the number MoA, PO-RALG, of processed horticultural MIF commodities SO2: Promote IR2.1: Promote i) Published progress reports on DPs, MoA, production & consumption the number of national TARI, NIMRI, consumption of of fruits and campaigns on production Ministry of bio-fortified vegetables to and utilization of nutritious Health, TFNC nutritional and improve and medicinal (nutraceutical medicinal micronutrients value) exotic and indigenous indigenous intakes at fruits, vegetables, herbs, fruits, households and spices vegetables, levels herbs and ii) Published progress reports on MoA, TARI, spices the existence of the number of NIMRI, improved by innovations and information on Ministry of 2030 conservation, production, Health, TFNC, processing and uses of DPs nutritional, medicinal of exotic and indigenous fruits, vegetables, herbs and spices disseminated iii) Published progress reports on MoA, TARI, the existence of primary and NIMRI, tertiary education curriculum Ministry of integrated the exotic and Health, TFNC indigenous beneficial plant aspects into the good nutrition iv) Published progress reports on MoA, TARI, the number of promote NIMRI, campaigns on the consumption Ministry of of horticultural produce at the Health, TFNC, household level to reach WHO DPs recommended target of 400gm of vegetable per person per day and 300gm of fruits per person per day IR2.2: Collected i) Published progress reports on MoA, TARI, and conserved the existence of number of MUHAS germplasm germplasm collected and technologies conserved of indigenous fruits, vegetables, herbs and spices ii) Published progress reports on MoA, TARI, the number of germplasm MUHAS characterized and documented NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 72 iii) Published progress reports on MoA, TARI, the existing capacity on SUA germplasm collection and conservation in the institutions IR2.3: Attracted i) Published progress reports on MoA, MIT, investment in the the existence of the number Ministry of manufacturing of of development partners Investment medicinal and supporting and fostering (TIC), cosmetic products information sharing agenda ii) Published progress reports on MoA, MIT, the existence of the number of Ministry of registered investors who Investment promote product development (TIC), and use of medicinal horticultural crops or cosmetic extracts SO3: IR3.1: Supported i) Published progress reports MoA, TARI, Strengthened and strengthened on the existence of the number Utumishi, Research and R&D institutions of national technology and Development, innovation plant health clinic - innovation and laboratories with working technologies facilities, equipment and gears transfer/up- equipped to meet accredited scaling by international standards 2030 ii) Published progress reports on MoA, TARI, the existence of the number of Utumishi, public and private research institutions enhanced on research-extension farmers linkages through increased funding and modernized infrastructure iii) Published progress reports on MoA, TARI, the existence of the number of Utumishi, national staff attached with international institutions to develop human resource capacity in Horticultural subsector and strengthen linkages NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 73 iv) Published progress reports on MoA, TARI, the existence of the number of Utumishi, local horticultural breeders encouraged to undertake breeding through partnerships and collaboration with regional and international research institutions and strengthen research-extension -farmer linkages to increase and improve horticulture production and quality IR3.2: Enhanced i) Published progress reports on MoA, and secured existing regulations and COSTECH intellectual procedures on horticultural property intellectual property (IPR) registration and developed enforcement mechanisms ii) Published report on established MoA, appropriate mechanisms for COSTECH horticultural technology innovations protection iii) Published report on customized MoA, proper regulations and COSTECH procedures on intellectual property rights (IP) iv) Published report on proposed MoA, incentives scheme for innovative COSTECH activities by domestic enterprises or individuals provided for motivation purposes v) Published progress report on MoA, COSTECH, the facilitated linkage between TARI technology developers and users vi) Published progress report on MoA, COSTECH, the facilitated awareness TARI creation on intellectual property rights (IPR) IR3.3: i) Published report on increased MoA,TOSCI Strengthened production of quality organic horticultural seed inputs, inspection and system certification of quality and traceability of horticulture seeds and planting materials increased NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 74 ii) Published report on the MoA,TOSCI strengthened quality-control mechanism for inspection, certification and verification of standards of horticulture seeds, seedling and planting materials iii) Published progress reports on MoA,TOSCI the existence of the number of producers educated on standards and certification procedures for the production of quality true to type horticulture seeds, seedlings and planting materials SO4: IR 4.1: Farmers i) Published progress reports on MoA, Promoted linked to offtakers’ the existence of the number of OR-PORALG, marketing and and large formal markets through LGAs & MIT market access commercial standard horticultural contract of horticultural marketing entities farming and out-growers produce and schemes developed trade facilitation ii) Published progress report on MoA, (collection the established database of OR-PORALG, centres, safety potential regional and LGAs & MIT and market) international markets of by 2030 strategic horticultural crops in compliance with global certification standards requirements (GAPs) iii) Published progress reports on MoA, the existence of the number of OR-PORALG, small-scale farmers connected LGAs & MIT to the regional and international markets to increase their chances of doing export business iv) Published progress reports on MoA, existing capacity and skills of OR-PORALG, farmers’ enhanced to conduct a LGAs & MIT market survey with which farmers can assess the opportunities potentially available in the dynamic market conditions v) Published report on facilitated MoA, match-making between farmers OR-PORALG, and large-scale marketing LGAs & MIT companies/ buyers, which the central and local governments can facilitate NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 75 vi) Monthly monitoring reports MoA, OR-PORALG, LGAs & MIT IR 4.2: i) Published progress reports on MoA, MIT, PMO, Established the existence of the number of horticulture essential alternative marketing terminal wholesale infrastructural services markets established, including product distribution; cold storage and packhouses; sorting, grading, and packaging proper integration of post-harvest technology into the marketing supply chain to meet adequate quantity and quality produce; and proper integration of post- harvest technology into marketing supply-chain through terminal wholesale markets ii) Published progress reports on MoA, MIT, PMO, the existing number of established standard horticultural contract farming and retail chains through a single gateway to the market iii) Published report on the MoA, MIT, PMO, transparent and efficient platform for sale and purchase of produce established by connecting growers through Horticultural Growers’ and Marketing Associations (HMOs) with farmers and wholesale buyers in various Tanzanian markets iv) Published progress reports on MoA, MIT, PMO, the number of established and improved horticultural collection centres v) Published progress reports on MoA, MIT, PMO, existing/established One-Stop Centre for horticultural market practitioners to improve efficiency NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 76 vi) Published report on farmers’ MoA, MIT, PMO, vertical coordination facilitated through cooperatives, contract farming and retail chains for better delivery of produce to reduce market risk IR 4.3: i) Published progress reports on MoA, TBS, Established & the established digital marketing TPSF, MIT promoted platforms and to promote the Commodity use of Commodity Exchange Exchange (ECX) (ECX) that target potential and digital online buyers for business marketing transaction ii) Published report on enhanced MoA, TBS, AMCOs capacity to sell directly TPSF, MIT to the ECX IR 4.4: i) Published progress reports on MoA, MIT, Strengthened the existence of number of TCRA, Mobile market information small-scale horticulture Phone system farmers using ICT platforms Companies, and applications in providing Digital, market information on Social Media promoted automated horticulture marketing system ii) Published progress reports on dialogue conducted through Public-Private Partnership with mobile phone companies operating in the country for undertaking marketing research and information system sharing iii) Several private mobile MoA, MIT, companies (e.g. TTCL, TCRA, Mobile VODACOM, AIRTEL and TIGO) Phone offer Apps and marketing Companies, programmes strengthened Digital, under PPP to farmers and Social Media traders iv) Published progress report on MoA, MIT, reviewed and integrated TCRA, Mobile existing horticulture marketing Phone information systems Companies, Digital, Social Media NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 77 v) Published progress report on MoA, MIT, the established off-takers TCRA, Mobile platforms for information Phone sharing on external marketing Companies, opportunities Digital, Social Media vi) Published report on promoted MoA, MIT, use of existing ICT applications TCRA, Mobile such as TAHA marketing Phone information system and Companies, M-Kilimo Digital, Social Media IR 4.5: Improve i) Published report on promoted MoA, MIT, PMO market intelligence SHEP market survey where the and dissemination farmers are the key actors to of information collect information on market across the whole needs and seek appropriate value chain business chances ii) Published progress reports on MoA, MIT, PMO the existence of increased and maintained production and supply of horticultural produce based on market requirements iii) Report on promoted the MoA, MIT, PMO Tanzania horticultural commodities through the use of diplomatic missions iv) Published progress reports on MoA, MIT, PMO the existence of number and frequency of participation on international trade fairs through TanTrade and other avenues v) Published report on the MoA, MIT, PMO capitalized business opportunity on the regional block where Tanzania is a member such as taking advantage of preferential trade agreements (PTAs)- EAC, SADC etc. vi) Published report on established MoA, MIT, PMO and strengthened system of capturing export data on prices, quantities and destination countries NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 78 vii) Published progress report on MoA, MIT, PMO the established and strengthened mechanism of capturing data on prices and quantities in the local markets IR 4.6: Promote i) Published progress reports on MoA, TBS, adherence to the number of private sector TPSF, MIT, quality, food safety, initiatives established, PMO standards and strengthened and promoted on certification quality assurance systems at systems the national level ii) Published progress reports on MoA, TBS, Enhanced skills and TPSF, MIT, professionals in certification for PMO development and implementation of effective quality assurance systems iii) Published progress reports on MoA, TBS, capacity Building of producers TPSF, MIT, in compliance with food safety PMO standards and quality assurance for national and international requirements iv) Published progress reports on MoA, TBS, TPSF, established funding mechanism MIT, PMO for certification process v) Published progress reports on MoA, TBS, TPSF, Established national certification MIT, PMO bodies vi) Published progress reports on MoA, TBS, TPSF, the capacity building to MIT, PMO institutions/agencies for service provision to agro-processors and exporters SO5: Improved IR 5.1: i) Monthly progress monitoring MoA, logistical Strengthened post reports; infrastructure handling systems (packaging, in the transport ii) Published progress reports on Ministry of storage and infrastructure number of registered logistical Infrastructure, transport (railways, posts, infrastructure number of facilities airfreight services) improved horticultural storage, to cater for the handling systems and needs of perishable transport infrastructure horticultural produces NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 79 iii) Published progress reports on Ministry of the number of robust national Infrastructure, cold chain management MoA, TPSF, TPA, systems established on TAA, LATRA, transportation of perishable TANROADS, horticultural produces that will TARURA, enable all the regulators TANESCO (TANROADS, TRA, Traffic Police, WMA, LGAs etc.) to give fast track services whenever dealing with perishable cargo iv) Published progress reports on Ministry of the number of “green belt” Infrastructure, established to fast track MoA, TPSF, TPA, clearance at the ports for quick TAA, LATRA, horticulture cargo transit TANROADS, TARURA, TANESCO v) Published progress reports on Ministry of improved rural feeder roads on Infrastructure, high horticultural potential MoA, areas TANROADS, TARURA vi) Published progress reports on Ministry of the number of investments Infrastructure, promoted in refrigerated tracks MoA, and cold rooms to transport and TANROADS, store fresh horticultural produce TARURA vii)Published progress reports on Ministry of the number of port terminals Infrastructure, with facilities dedicated to MoA, horticultural products and other TANROADS, perishable goods to facilitate TARURA trade efficiency and reduce post-harvest losses IR 5.2: i) Published progress reports on Minstry of Established service the list of horticulture quality Infrastructure, -oriented satellite standards protocols established MoA, TBS,TAA collection centres and packhouses ii) Published progress reports on Minstry of the number of satellite Infrastructure, collection centres and MoA, TBS,TAA packhouses for cooling, sorting, grading, and packaging established NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 80 iii) Published progress reports on Minstry of the number of “capital services” Infrastructure, such as “pick-up and delivery MoA, TBS,TAA services” to facilitate farmers to meet customers’ quality requirements. These services will reinforce strict quality standards on all produce agreed with buyers SO6: IR 6.1: i) Published progress on enacting MoA Strengthened The institutional a law for the establishment of coordination, framework national horticulture governing institutional strengthened organ and policy framework by ii) Published progress reports on MoA 2030 establishing a national horticulture governing organ (i.e. Horticulture Development Agency or Horticulture Development Board) coordinating all actors along the value chain, and a mandated speaker of the horticulture industry in the country iii) Published progress reports on MoA the existence of regulations for the operationalization of the national horticulture governing organ iv) Presence of monthly, quarterly MoA and annual monitoring reports IR 6.2: i) Published progress reports on MoA Strengthened the number of functional coordination national platforms for strategic horticultural crops at local and national levels ii) Presence of monthly, quarterly MoA and annual monitoring reports IR 6.3: i) Presence of monthly, quarterly MoA Established and annual monitoring reports national horticulture ii) Published progress reports on MoA platform the number of strategic horticultural crops platforms established and linked with the national policy and advocacy platforms NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 81 IR 6.4: i) Presence of monthly, quarterly MoA Established and annual monitoring reports horticulture agenda IR 6.5: i) Published progress reports on (TAHOPRO) Established the established horticultural MoA a horticulture regulatory organ (i.e. professional Tanzania Horticultural registration board Professionals Registration Board ii) Published progress reports on MoA an inventory list of registered trainers and professionals developed who offer relevant horticultural courses to equip skills to the value chain actors iii) Published progress reports on MoA a list of registered horticulture professionals and practitioners iv) Published progress reports on MoA the established code of conduct and ethics amongst horticultural professionals and horticultural enterprises v) Presence of monthly, quarterly MoA and annual monitoring reports SO7: Enhance IR 7.1: Local skills i) Published progress reports on MoA, MIT, capacity and knowledge the number of formal and Private Sectors, building along base built in the informal innovations promoted the horticulture industry focusing on direct linkages with value the private sector through implemented industrial attachments, by 2030 internships, mentorship and coaching programmes, youth incubation schemes, technology -based incubation centres, and apprenticeships schemes ii) Published progress reports on MoA, MIT, the number of technology- Private Sectors, based incubation centres and apprenticeships schemes established iii) Published progress reports on MoA, MIT, the number of mentorship Private Sectors, programmes youth incubation schemes established NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 82 iv) Published report on the promote MoA, MIT, triple helix principles where Private Sectors, there is a collaboration between the government, the TVET and the private sector v) Published progress reports on MoA, MIT, the established national Private Sectors, qualification framework, which comply with international standards vi) Monthly monitoring reports MoA vii)Published progress reports on MoA, MIT, the existence of documented Private Sectors, lessons learned, good practices and success stories for improvement and up-scaling IR 7.2: Human i) Published progress reports on MoA, skills developed to the number of regular accelerate the specialized training conducted absorption, utilization, and ii) Annual monitoring conducted to MoA, PMO, maintenance of assess the capacity of the TVET, MoE, technologies Technical Vocational Education VETA, Ministry and Training (TVET) system of Foreign Affairs, iii) Published progress reports on MoA, the number of strategic linkages established and strengthened between the private sector and public institutions iv) Published progress reports on MoA, the number of proven models of technology transfer and skills development Invested in the country v) Published progress reports on MoA, the number of selected high- level specialized skills invested vi) Published monitoring report MoA, produced to track the developed strategic linkages and challenges learned with the private sector NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 83 SO8: IR 8.1: Effective i) Published progress reports on Strengthened monitoring national budgetary allocation financing and framework and coordination of investment produced and development partners (DPs) system of the used by RS and funds improved to support industry by TF members the horticulture industry 2030 ii) At least 1.5% of horticulture crops cess currently collected by central government and local government authorities (LGAs) Ministry of is ploughed back to the industry Finance and for coordination, Research and Planning, MoA, Development PO-RALG, Private Sector, iii) Published progress report on the established and functional Horticulture Development Fund (HDF) iv) Published progress reports on the financing of the industry through programmes and projects by local and international funding institutions and development partners enhanced v) Published progress reports on the established financing mechanism for the implementation of the strategy IR 8.2: Enabling i) Published progress reports on MoA, environment for horticultural credit facilities the private sector established with terms and and other conditions fitting farming cycles, stakeholders to including adequate grace establish affordable periods and affordable interest credit facilities to rates support horticultural ii) Published progress reports on MoA, investments the existence of an effective availed monitoring framework produced and used by partner members iii) Monthly field monitoring reports MoA, NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 84 IR 8.3: Enabling i) Presence of progress reports TIRA environment for private insurance ii) Published progress reports on MoA companies to the existence of national develop campaign conducted on the appropriate and importance of ensuring affordable horticulture industry to all enterprise registered insurance insurance products companies to support horticultural iii) Published progress reports on MoA investments an effective monitoring availed framework produced and used by partner members iv) Published progress reports on MoA awareness creation initiatives to horticultural producers and other value chain actors on the importance of crop insurance IR 8.4: Engage i) Published progress reports on MoA & MIT the private sector the number of private sectors in identifying the identified and engaged in the industries horticultural, industrial investments investment opportunities priorities ii) Published progress reports on MoA & MIT the number of the facilitated private sector businesses to invest in manufacturing horticulture production inputs and value addition/processing facilities NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 85 8.0 RISKS AND MITIGATIONS It is anticipated that some risks may arise during the implementation of the strategy; however, for each risk, a potential mitigation measure of the strategy is suggested (Table 12). Potential risks are highlighted and rated high (H), substantial (S), medium (M) and low (L). During implementation, they will be addressed by undertaking appropriate mitigation measures. Table 12: Initial risk analysis and possible contingency plans Strategy risk Description of risk Rating Mitigation measures factor implemented Limited horticulture Institutional capacity L The strategy design has built- industry coordination for participating in coordination mechanisms, capacity organizations with MoA assuming a role in coordination at the facilitating all stakeholders’ national, regional and coordination in terms of district level may limit convening and regulation effective partnerships and teamwork Limited commitment Participating private L All activities will be implemented by stakeholders to stakeholders may not according to the agreed work work within a fully engage in or programs and budgets and framework of commit sufficient discussed and approved for collaboration resources for funding as part of collaborative activities ASDP II plans The decline in Horticulture prices may H The strategy has emphasized horticulture prices at change due to the mechanisms that ensure that the international oversupply of horticulture production is market horticulture produce by efficient and cost-effective. other countries Therefore, capacity building of AMCOs and other value chain actors in management and business skills and knowledge. Promote domestic consumption pattern NATIONAL HORTICULTURE DEVELOPMENT STRATEGY & ACTION PLAN 2021-2031 86 Ministry of Agriculture, Government City - Mtumba, P.O. Box 2182, Dodoma. Tel: +255 (026) 2321407/ 2320035 Fax: +255 (026) 2320037 Email: [email protected] | false |
# Extracted Content 1 The United Republic of Tanzania Ministry of Agriculture Agricultural Marketing Section MONTHLY MARKET BULLETIN March, 2022 2 1. Staple foods In March, prices for major staple food crops fell at varying rates, but remained significantly higher than a year ago. Seasonal rains and the start of early harvesting in some regions may cause prices to fall even further. Tanzania stands to gain by selling grains in regional markets (EAC AND SADC) Table 1: National average market price of major staple foods (TZS/100kg) Maize In March, the average wholesale price dropped by 3.9 percent, from TZS 63,500/100kg bag in February to TZS 63,500/100kg bag in March (Table 1). Similarly, February prices were 2.3 percent lower than the previous five-year March averages (Figure 1). The price was significantly higher (26%) in March 2022 than in the previous year's comparable month. Prices may have fallen in March as a result of increased supply, particularly from lake zone regions. The on-going seasonal rains and the harvesting of short-term crops are expected to drive maize prices even lower in the coming month. Rice The average wholesale rice prices decreased by 1.2 percent in March 2022, from TZS 186,500/100kg bag in January to TZS 184,300/100kg bag in March (Table 1). On the other hand, prices increased significantly by 32% in March 2022 compared to the same month a year ago, and by 6.4 percent to the five-year March average. Commodity Feb 2022 Mar 2022 Monthly change (%) Annual change (%) 5-year average (%) Maize 63,500 61,000 ▼3.9 ▲26.0 ▼2.3 Rice 186,500 184,300 ▼1.2 ▲31.9 ▲6.4 Dry beans 184,200 186,400 ▲1.2 ▲4.7 ▲5.3 Sorghum 121,100 114,500 ▼5.5 ▲13.8 ▲12.4 Round potatoes 82,200 79,800 ▼2.9 ▲12.2 ▲7.7 - 50,000 100,000 150,000 200,000 250,000 Mar-17 Mar-18 Mar-19 Mar-20 Mar-21 Mar-22 TZS/100kg bag Figure 2: Average market price of rice during month of March 2017-2022 Market price 5 year average - 20,000 40,000 60,000 80,000 100,000 120,000 Mar-17 Mar-18 Mar-19 Mar-20 Mar-21 Mar-22 TZS/100kg bag Figure 1: Average market price of maize during month of March 2017-2022 Market price 5 year average 3 Dry beans Wholesale prices of beans were at high levels, by 5.3 higher than the five- year March average. Prices fell in February before rising slightly (1.2 percent) in March to TZS 186,400/100 bag, up from TZS 184,200/100 bag in February. Similarly, prices in March 2022 were 4.7 percent higher than the same month the previous year (Figure 3). Sorghum The monthly average wholesale price of sorghum fell by 5.5 percent, from TZS 121,100/100kg bag in February to TZS 114,500/100kg bag in March. On the other hand, prices rose by 13.8% when compared to the same month in the previous year, and were 12.4% higher than the five-year March average (Figure 4). - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Mar-17 Mar-18 Mar-19 Mar-20 Mar-21 Mar-22 TZS/100kg bag Figure 4: Average market price of sorghum during month of March 2017-2022 Market price 5 year average 145,000 150,000 155,000 160,000 165,000 170,000 175,000 180,000 185,000 190,000 Mar-17 Mar-18 Mar-19Mar-20 Mar-21 Mar-22 TZS/100kg bag Figure 3: Average market price of dry beans during month of March 2017-2022 Market price 5 year average 4 Round potatoes The average wholesale prices for round potatoes slightly declined by 2.9 percent, from TZS 82,200/100kg bag in February to TZS 79,800/100kg bag in March. Prices, on the other hand, were 12.2 percent higher in the reporting period than in the previous year's same period, and 7.7 percent higher than the five-year March average (Figure 5). NOTES ✓ Market price: Refer to nominal or observable prices ✓ Price level: National average wholesale price in Tanzanian Shilling (TZS) per 100kg bag ✓ The symbols (▲▼►) indicate the direction of price changes. (▲) price increased; (▼) price decreased; (►) no changes in price ✓ Source of data: Ministry of Investment, Industry and Trade 60,000 65,000 70,000 75,000 80,000 85,000 Mar-17 Mar-18 Mar-19 Mar-20 Mar-21 Mar-22 TZS/100kg bag Figure 5: Average market price of round potatoes during month of March 2017-2022 Market price 5 year average 5 2. Traditional Export commodities (Source: World Bank, 2022) With the exception of cotton, global market prices for most traditional export crops declined slightly during in March Coffee Coffee prices, mostly arabica variety, have risen slightly over the last year but declined in March 2022. Prices for Arabica and Robusta declined by 8 percent and 5 percent respectively (Figure 6). Despite the fact that prices appeared to recover over time, the global coffee market is still influenced by Covid-19 supply disruptions. It is expected that the supply and demand trends will be further influenced by increased input costs, which will raise production costs as well as consumption as a result of the conflict in Ukraine (ICO, 2022). Benchmark: Coffee (ICO), International Coffee Organization indicator price Tea Tea prices at the Mombasa auction market have risen steadily over the last year, but declined in March 2022 by 7 percent (Figure 7). Tea auction prices have remained stable on average since the Kenyan government decided to set a minimum price of USD 2.43/kg at the beginning of August 2021, after the cost of tea fell to a decade low. While the Russia-Ukraine crisis is affecting India's tea exports (Russia is India's second largest buyer of tea), the ongoing conflict is likely to affect tea prices at the Mombasa auction. Benchmark: Tea (Mombasa/Nairobi auctions), African origin, all tea, arithmetic average of weekly quotes 0.00 0.50 1.00 1.50 2.00 2.50 3.00Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21Oct-21Nov-21Dec-21Jan-22Feb-22Mar-22 USD/Kg Figure 7: Average price of tea at Mombasa auction, March 2021- March 2022 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 USD/kg Figure 6: Average price of coffee, March 2021- March 2022 Arabica Robusta 6 Tobacco Over the last year, global tobacco prices have been steadily declining (Figure 8). Prices fell further in March 2022 (by 0.3 percent). The drop in prices could be attributed to increased health awareness and stringent government policies prohibiting the use of tobacco. According to a World Health Organization report, the global prevalence of tobacco use has been declining for the past two decades (WHO, 2021). Cotton While prices for other traditional export crops fell in March, cotton prices rose by 2 percent, rising from 3.05 USD/Kg in February 2022 to 3.11 USD/Kg in March 2022 (Figure 9). Cotton prices are expected to rise in 2022 as global output, particularly in India and the United States, is expected to fall while demand remains high. 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21Oct-21Nov-21Dec-21Jan-22Feb-22Mar-22 USD/kg Figure 9: Average price of cotton, March 2021- March 2022 4,050 4,100 4,150 4,200 4,250 4,300 4,350 4,400 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 USD/ton Figure 8: Average price of tobacco, March 2021- March 2022 7 3. Import Substitution Commodities (Source: World Bank, 2022) Tanzania imports a significant amount wheat, sugar, and cooking oil. In March, prices of these products were higher than a year before. The war in Ukraine has caused disruption in the flows of wheat and cooking oil (sunflower oil) globally. Ukraine is one of the world’s biggest exporters of wheat and sunflower oil. The Russia-Ukraine war situation brings uncertainties and could further impact domestic prices Edible Oil- (Palm Oil) Palm oil increased by 17% from USD 1,522/ton in February 2022 to USD 1,777/ton in March 2022 (Figure 11). Malaysian palm oil prices have been rising globally since the outbreak of the Covid-19 pandemic, which resulted into reduced production and disruption of supply chain. Consequently, the war between Russia and Ukraine, the top producers and exporters of sunflower oil will cause supply shortages, driving up palm oil prices even further. Prices in the domestic market have also been rising. The retail price increased by approximately 56% from TZS 4,500/lt in March 2019 to around TZS 7,000/lt in March 2022. Ref: Palm oil (Malaysia), palm oil demand and supply outlook report 2022. Wheat Global wheat prices (US SRW) reached USD 533/ton in March 2022, up from USD 332.06/ton in January 2022, a 61 percent increase (Figure 10). The Ukraine crisis has recently heightened volatility in the wheat markets, causing global prices to rise. Russia and Ukraine control at least 30% of the global wheat market (IFPRI, 2022). Tanzania imports 1-1.2 million tonnes of wheat, with Russia and Ukraine accounting for more than 60% of the total. *Wheat (US), soft red winter (SRW) 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 USD/ton Figure 11: Average price of palm oil, March 2021- March 2022 0 100 200 300 400 500 600 Feb-21 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 USD/ton Figure 10: Average price of wheat, March 2021- March 2022 US SRW 8 Sugar Global sugar prices increased slightly in March to USD 0.42/kg, up from USD 0.39/kg in February 2022. Sugar production in Brazil is expected to decline in 2022 (USAD, Nov 2021). Because Brazil is a major producer and exporter of sugar, the reduction is expected to have a significant impact on global as well as domestic sugar supply and prices. 0.00 0.10 0.20 0.30 0.40 0.50 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 USD/kg Figure : Average price of sugar, March 2021- March 2022 9 4. Farm Inputs (Source: World Bank, 2022) Global fertilizer prices are rising. The ongoing Russia-Ukraine war, as well as the Covid-19 supply chain disruptions, have contributed to rising fertilizer prices. Demand-side pressure could drive up the price of fertilizer in the domestic market even further Fertilizers Fertilizer prices continued to increase in March. DAP prices increased by 6% percent from USD 747/ton in February,2022 to USD 938/ton in March,2022. Similarly, Urea prices have trended higher than DAP prices over the last four months, reaching USD 908/ton in March 2022, up from USD 744/ton in February 2022, a 22% increase. (Figure 12). Oil and natural gas prices have risen in recently as a result of supply uncertainty caused by the Russia-Ukraine crisis. Natural gas is a critical component in the manufacturing of nitrogen-based fertilizers. Russia is one of the world’s top exporters of nitrogen fertilizers and the second-largest supplier of both potassic and phosphorous fertilizers. The situation might disrupt the global markets and drive-up fertilizer prices even further in the near future. About the Bulletin This bulletin provides domestic and international markets outlook for five commodity groups including staples (maize, rice, beans, sorghum, and round potatoes), traditional export crops (coffee, cotton, tea, and tobacco), import substitution commodities (edible oil, and wheat) and farm inputs (fertilizer). This bulletin's information serves as a benchmark for key players along the respective value chains to make informed decisions. Disclaimer: The views expressed in this bulletin are those of the authors and may not reflect those of the Ministry of Agriculture (MoA). This bulletin is strictly for informational purposes only. The authors have made every effort to ensure accuracy of information provided; however, neither the Ministry of Agriculture nor the authors can guarantee such accuracy For further information, contact: Ag: Assistant Director, Agricultural Marketing Section, P.O. Box 2182, DODOMA. Email: [email protected] 0 200 400 600 800 1000Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21Oct-21Nov-21Dec-21Jan-22Feb-22Mar-22 USD/ton Figure 12: Average price of fertilizer, March 2021- March 2022 DAP Urea | false |
# Extracted Content 1 Agricultural Marketing Section The United Republic of Tanzania Ministry of Agriculture Agricultural Marketing Section MONTHLY MARKET BULLETIN September, 2021 Introduction This bulletin provides monthly highlights on market prices of major food crops in domestic markets. The bulletin also provides global market information on traditional export crops (coffee, cotton, tea, and tobacco), import substitution commodities (edible oil and wheat) and farm inputs (fertilizer). Information in this bulletin provides a benchmark to key players along the respective value chains to make informed decisions. Disclaimer: The views expressed in this bulletin are those of the authors and may not reflect those of the Ministry of Agriculture (MoA). This bulletin is strictly for informational purposes only. The authors have made every effort to ensure accuracy of information provided; however, neither the Ministry of Agriculture nor the authors can guarantee such accuracy. Key Messages ✓ Food Crops: Prices of staple foods remained stable and significantly lower on average compared to last year and even over a five-year period. Rice prices increased by 0.9 percent in September. While maize, dry beans, sorghum, and round potatoes prices fell by 2, 2.9, 4.9, and 1.8 percent, respectively. Prices may have fallen as a result of increased supply from harvests. ✓ Traditional Export Crops: During the reporting period, global market prices for traditional export crops followed a variety of trends. While coffee, cotton and tea prices increased (including coffee-Robusta by 9.9 percent, coffee-Arabica by 4.3 percent, cotton by 2.35 percent, and tea by 2.85 percent), tobacco prices continued to fall month after month. ✓ Import Substitution: Price for edible oil in the global market increased by 6.4 percent between August and September 2021, owing to a combination of factors such as adverse weather conditions, supply disruptions caused by Covid 19, and increased demand. Similarly, Wheat export prices increased in September 2021, owing to concerns about dwindling production prospects in some of the major exporters. ✓ Farm Inputs: Between August and September 2021, the price of DAP fertilizer increased by 6.7 percent, while the price of urea fertilizer decreased by 6.3 percent. DAP prices have risen as a result of export restrictions imposed by China, the world's largest exporter. 2 Agricultural Marketing Section 1. National monthly average prices of major food crops Table 1: National average market price of major staple food (TZS/100 kg) Maize National average wholesale maize prices declined (by 2 percent) from TZS 44,800/100 kg bag in August to TZS 43,900 kg bag in September (Table 1).Prices remained significantly lower (by 19.4%) than last year's and the five-year average (by 17.8%). Prices continued to fall seasonally across most markets as supplies increased from mainly from May to August harvest. Commodity Aug 2021 Sep 2021 Monthly change (%) Annual change (%) 5 years average (%) Maize 44,800 43,900 ▼2 ▼19.4 ▼17.8 Rice 138,800 140,000 ▲0.9 ▼1.2 ▼10.2 Dry beans 169,700 164,700 ▼2.9 ▼13.2 ▼1.2 Sorghum 98,300 93,500 ▼4.9 ▼5.7 ▲4.1 Round potatoes 64,100 60,300 ▼1.8 ▼18.6 ▼15.6 - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Sep-17 Sep-18 Sep-19 Sep-20 Sep-21 TZS/100kg bag Figure 1: Average market and real price of maize during month of Sep 2017-2021 Market price 5 yr avrg 3 Agricultural Marketing Section Dry beans Between August and September, wholesale prices for dry beans dropped by 2.9 percent, from an average of TZS 169,700/100kg bag to TZS 164,700/100kg bag. Similarly, prices in September 2021 were 13.2 percent lower than in the same month last year (Figure 3). Bean prices, on the other hand, have fallen slightly, falling 1.2 percent below the five-year September average. Rice In general, domestic rice market prices have been declining over the last five years (Figure 2). Prices in September 2021 declined by 1.2 percent when compared to the same month the previous year and by 10.2 percent when compared to the five-year September average. Prices, on the other hand, increased by 0.9 percent in September compared to the previous month, rising from TZS 138,800/100 kg bag in August to TZS 140,000/kg bag in September (Table 1). Despite the ongoing seasonal harvests, domestic prices of rice may continue to increase following the promising regional market. - 50,000 100,000 150,000 200,000 Sep-17 Sep-18 Sep-19 Sep-20 Sep-21 TZS/100kg bag Figure 2: Average market and real price of rice during month of Sep 2017-2021 Market price 5 yr avrg - 50,000 100,000 150,000 200,000 250,000 Sep-17 Sep-18 Sep-19 Sep-20 Sep-21 TZS/100kg bag Figure 3: Average market and real price of dry beans during month of Sep 2017-2021 Market price 5 yr avrg 4 Agricultural Marketing Section Round potatoes The national average wholesale price for round potatoes dropped by 1.8 percent in September, from TZS 64,100/100kg bag in July to TZS 64,700/100kg bag in August 60,300. Similarly, prices in the reporting period were 18.6% lower than in the same period last year. Furthermore, prices in September 2021 were 15.6% lower than their five-year September averages (Figure 5). Sorghum The monthly average wholesale price of sorghum has decreased by 4.9 percent, from TZS 98,300/100kg bag in August to TZS93,500/100kg bag in September. Similarly, prices declined by 5.7 percent in September 2021 when compared to the same period the previous year. Sorghum prices, on the other hand, were 4.1 percent higher than their five- year September averages (Figure 4). Given the market opportunity in South Sudan, Tanzania plans to export approximately 60,000 tons of white sorghum this season via the Cereals and Other Produce Board (CPB). NOTES ✓ Market price: Refer to nominal or observable prices ✓ Price level: National average wholesale price in Tanzanian Shilling (TZS) per 100kg bag ✓ The symbols (▲▼►) indicate the direction of price changes. (▲) price increased; (▼) price decreased; (►) no changes in price ✓ Source of data: Ministry of Industry and Trade - 20,000 40,000 60,000 80,000 100,000 120,000 Sep-17 Sep-18 Sep-19 Sep-20 Sep-21 TZS/100kg bag Figure 4: Average market and real price of sorghum during month of Sep 2017-2021 Market price 5 yr avrg - 20,000 40,000 60,000 80,000 100,000 Sep-17 Sep-18 Sep-19 Sep-20 Sep-21 TZS/100kg bag Figure 5: Average market and real price of round potatoes during month of Sep 2017-2021 Market price 5 yr avrg 5 Agricultural Marketing Section z2. World market prices of selected commodities (Source: World Bank, 2021) Tea Tea prices at the Mombasa auction market have steadily declined over the last ten months. Prices increased by 2.85 percent from the beginning of August 2021 to the end of September 2021, rising from 2.16 USD/Kg in August to 2.22 USD/Kg in September (Figure 7). Benchmark: Tea (Mombasa/Nairobi auctions), African origin, all tea, arithmetic average of weekly quotes Coffee Coffee prices for Arabica and Robusta varieties increased by 4.3 and 9.9 percent, respectively, in comparison to September 2020 prices (Figure 6). Arabica is known to be more expensive to produce than Robusta. This affects the final price of the two varieties. The coffee market was still being driven by adverse weather in Brazil and increased demand as a result of Covid 19 supply disruptions (ICO,2021). Benchmark: Coffee (ICO), International Coffee Organization indicator price, other mild Arabicas, average New York and Bremen/Hamburg markets, ex-dock 0.00 1.00 2.00 3.00 4.00 5.00 6.00Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/kg Figure 6: Average price of coffee, Sep 2020- Sep 2021 Arabica Robusta 0.00 0.50 1.00 1.50 2.00 2.50Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/Kg Figure 7: Average price of tea at Mombasa auction, Sep 2020- Sep 2021 6 Agricultural Marketing Section Cotton Cotton prices increased (by 2.35 percent) in September 2021, rising from 2.23 USD/Kg in August 2021 to 2.29 USD/Kg in September 2021. (Figure 9). Global cotton prices have risen since the beginning of 2021, owing to projected production shortfalls at a four- year low. Lower inventory and insufficient carryover stocks resulted in increased demand from major consuming countries such as China and India. Cotton (Cotton Outlook "CotlookA index"), middling 1-3/32 inch, traded in Far East, C/F beginning 2006; previously Northern Europe, c.i.f. Tobacco Tobacco prices dropped by 0.23 percent from an average of USD 4,286/ton in August to USD 4,276/ton in September 2021. Overall, global tobacco prices have been steadily declining over the last year (Figure 8). Prices are expected to continue falling as a result of increased health consciousness, strict government policies, and the increased availability of substitutes such as e- cigarettes. 4,150 4,200 4,250 4,300 4,350 4,400 4,450 4,500 4,550 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 Feb-21 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 USD/ton Figure 8: Average price of tobacco, Sep 2020- Sep 2021 0.00 0.50 1.00 1.50 2.00 2.50Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/kg Figure 9: Average price of cotton, Sep 2020- Sep 2021 7 Agricultural Marketing Section Wheat The global wheat trade fluctuated slightly from month to month. Prices (US SRW) rose by 5% from USD 250.88/ton in July to USD 263.60/ton in September 2021. Wheat export prices increased in September 2021, owing to concerns about dwindling production prospects in some of the major exporters, including Russia, Canada, and the European Union. (AMIS-Market Monitor). Wheat (US), soft red winter (SRW), export price delivered at the US Gulf port for prompt or 30 days shipment Edible Oil- (Palm Oil) Global palm oil prices have risen by 6.4 percent since August 2021, rising from USD 1,341/ton to USD 1,427/ton in September 2021 (Figure 11). The price increase over the last year has been attributed to a number of factors, including hot and dry weather conditions in Canada, Brazil, Argentina, and the United States, which impacted the canola crop used to produce canola oil. Canola oil is a palm oil substitute. Second, concern over Covid 19 about palm oil production in Malaysia and Indonesia (major producers of palm oil) has resulted in a labor shortage, and third, increased demand for refined palm oil in India following the removal of import duties (The Economic Times). Ref: Palm oil (Malaysia) 0 50 100 150 200 250 300Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/ton Figure 10: Average price of wheat, Sep 2020- Sep 2021 US SRW 0 200 400 600 800 1000 1200 1400Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/ton Figure 11: Average price of palm oil, Sep 2020- Sep 2021 8 Agricultural Marketing Section Fertilizers Between August and September 2021, DAP fertilizer prices increased by 6.7 percent, while urea fertilizer prices decreased by 6.3 percent (Figure 12). DAP prices have risen as a result of export restrictions imposed by China, the world's largest exporter. Morocco remained a viable export option. It is important to note that Brazil and India are the world's largest fertilizer consumers, and thus have an impact on global market prices. Ref: DAP (Diammonium phosphate), spot, f.o.b. US Gulf; Urea, (Ukraine), f.o.b. Black Sea 0 100 200 300 400 500 600 700Sep-20Oct-20Nov-20Dec-20Jan-21Feb-21Mar-21Apr-21May-21Jun-21Jul-21Aug-21Sep-21 USD/ton Figure 12: Average price of fertilizer, Sep 2020- Sep 2021 DAP Urea 9 Agricultural Marketing Section ANNEX: Food crops- price trend and forecast 0 10000 20000 30000 40000 50000 60000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct TZS/100kg bag Maize Price Forecast Price Predicted Price 125000 130000 135000 140000 145000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Rice Price Forecast Price Predicted Price 84000 86000 88000 90000 92000 94000 96000 98000 100000 102000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Sorghum Price Forecast Price Predicted Price 0 10000 20000 30000 40000 50000 60000 70000 80000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Round Potato Price Forecast Price Predicted Price 10 Agricultural Marketing Section Disclaimer: The views expressed in this bulletin are those of the authors and may not reflect those of the Ministry of Agriculture (MoA). This bulletin is strictly for informational purposes only. The authors have made every effort to ensure accuracy of information provided; however, neither the Ministry of Agriculture nor the authors can guarantee such accuracy. For further information, contact: Ag: Assistant Director, Agricultural Marketing Section, P.O. Box 2182, DODOMA. Email: [email protected] Mobile: +255 686 107 673 / +255 713 309 122 | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Ve: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Ve: REGIONAL REPORT: MOROGORO REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents.......................................................................................................................................................................... i Acronyms..................................................................................................................................................................................... v Preface........................................................................................................................................................................................-vi Executive summary....................................................................................................................................................................xii Illustration ...................................................................................................................................................................................... ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION.................................................................................................................. 1 1.1 Introduction ................................................................................................................................................................ 1 1.2 Geographical Location and Boundaries....................................................................................................................... 1 1.3 Land Area.................................................................................................................................................................... 1 1.4 Climate......................................................................................................................................................................... 1 1.4.1 Temperature................................................................................................................................................... 1 1.4.2 Rainfall........................................................................................................................................................... 1 1.5 Population ................................................................................................................................................................... 1 1.6 Socio-economic Indicators......................................................................................................................................... 2 PART II: INTRODUCTION................................................................................................................................................ 3 2.1 Introduction ................................................................................................................................................................ 3 2.2 The Rationale for Conducting the National Sample Census of Agriculture....................................................... 3 2.3 Census Objectives....................................................................................................................................................... 3 2.4 Census Coverage and Scope...................................................................................................................................... 4 2.5 Legal Authority of the National Sample Census of Agriculture........................................................................... 5 2.6 Reference Period ........................................................................................................................................................ 5 2.7 Census Methodology.................................................................................................................................................. 5 2.7.1 Census Organization...................................................................................................................................... 6 2.7.2 Tabulation Plan.............................................................................................................................................. 6 2.7.3 Sample Design............................................................................................................................................... 6 2.7.4 Questionnaire Design and Other Census Instruments ................................................................................... 7 2.7.5 Field Pre-Testing of the Census Instruments................................................................................................. 7 2.7.6 Training of Trainers, Supervisors and Enumerators...................................................................................... 7 2.7.7 Information, Education and Communication (IEC) Campaign..................................................................... 8 2.7.8 Household Listing........................................................................................................................................... 8 2.7.9 Data Collection ............................................................................................................................................... 8 2.7.10 Field Supervision and Consistency Checks ................................................................................................... 8 2.7.11 Data Processing .............................................................................................................................................. 9 - Manual Editing.......................................................................................................................................... 9 - Data Entry ................................................................................................................................................. 9 - Data Structure Formatting.............................................................................................................................. 9 - Batch Validation ....................................................................................................................................... 9 - Tabulations..............................................................................................................................................10 - Analysis and Report Preparations ..........................................................................................................10 - Data Quality............................................................................................................................................10 2.7.12 Funding Arrangements .................................................................................................................................10 PART III: CENSUS RESULTS AND ANALYSIS............................................................................................................ 11 3 Introduction .............................................................................................................................................................. 11 3.1 Holding Characteristics........................................................................................................................................... 11 3.1.1 Type of Holdings......................................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income..................................................................................................... 11 3.1.3 Sex and Age of Heads of Households......................................................................................................... 12 3.1.4 Number of Household Members................................................................................................................. 12 3.1.5 Level of Education....................................................................................................................................... 12 - Literacy .................................................................................................................................................. 12 - Literacy Level for Household Members ............................................................................................... 13 - Literacy Rates for Heads of Households............................................................................................... 13 - Educational Status.................................................................................................................................. 13 - Off-farm Income.................................................................................................................................... 14 TOC ____________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.2 Crop Results............................................................................................................................................................... 15 3.2.1 Land Use.......................................................................................................................................................15 3.2.1.1 Area of Land Utilised.................................................................................................................15 3.2.1.2 Types of Land use ......................................................................................................................15 3.2.2 Annual Crops and Vegetable Production.....................................................................................................16 3.2.2.1 Area Planted ...............................................................................................................................16 3.2.2.2 Crop Importance.........................................................................................................................17 3.2.2.3 Crop Types .................................................................................................................................17 3.2.2.4 Cereal Crop Production..............................................................................................................18 - Maize...................................................................................................................................19 - Paddy...................................................................................................................................19 - Other Cereals.......................................................................................................................20 3.2.2.5 Pulse Crops Production..............................................................................................................20 - Beans...................................................................................................................................21 - Cowpeas..............................................................................................................................22 3.2.2.6 Roots and Tuber Crops Production............................................................................................22 - Cassava...............................................................................................................................23 3.2.2.7 - Oil Seed Production ............................................................................................................23 - Simsim.................................................................................................................................24 3.2.2.8 - Fruits and Vegetables..........................................................................................................25 - Tomatoes.............................................................................................................................26 - Cabbage...............................................................................................................................26 - Carrots .................................................................................................................................27 3.2.2.9 Other Annual Crops Production.................................................................................................27 - Cotton..................................................................................................................................27 - Tobacco ...............................................................................................................................28 3.3.3 Permanent Crops...........................................................................................................................................28 3.3.3.1 Banana .......................................................................................................................................29 3.3.3.2 Sugarcane................................................................................................................................... 30 3.3.3.3 Coconut.......................................................................................................................................30 3.3.3.4 Mango........................................................................................................................................ 31 3.3.4 Inputs/Implements Use.................................................................................................................................32 3.3.4.1 Methods of land clearing............................................................................................................32 3.3.4.2 Methods of soil preparation .......................................................................................................33 3.3.4.3 Improved seeds use ....................................................................................................................34 3.3.4.4 Fertilizers use..............................................................................................................................34 - Farm Yard Manure Use ......................................................................................................36 - Inorganic Fertilizer Use ......................................................................................................37 - Compost Use.......................................................................................................................37 3.3.4.5 Pesticide Use ..............................................................................................................................38 - Insecticide Use ....................................................................................................................38 - Herbicide Use......................................................................................................................39 - Fungicide Use..................................................................................................................... 39 3.3.4.6 Harvesting Methods ...................................................................................................................40 3.3.4.7 Threshing Methods.....................................................................................................................40 3.3.5 Irrigation .......................................................................................................................................................40 3.3.5.1 Area planted with annual crops and under irrigation ................................................................41 3.3.5.2 Sources of water used for irrigation...........................................................................................42 TOC ____________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.3.5.3 Methods of obtaining water for irrigation..................................................................................42 3.3.5.4 Methods of water application ....................................................................................................42 3.3.6 Crop Storage, Processing and Marketing.....................................................................................................43 3.3.6.1 Crop Storage...............................................................................................................................43 - Method of Storage...............................................................................................................43 - Duration of Storage.............................................................................................................44 - Purpose of Storage ..............................................................................................................44 - The Magnitude of Storage Loss..........................................................................................45 3.3.6.2 - Agro processing and by-products.......................................................................................45 - Processing Methods ............................................................................................................46 - Main Agro-processing Products .........................................................................................46 - Main use of primary processed Products............................................................................47 - Outlet for Sale of Processed Products ................................................................................47 3.3.6.3 Marketing....................................................................................................................................48 - Crop Marketing...................................................................................................................48 - Main Marketing Problems ..................................................................................................48 - Reasons for Not Selling ......................................................................................................48 3.3.7 Access to Crop Production Services ............................................................................................................48 3.3.7.1 Access to Agricultural Credits ...................................................................................................49 - Source of Agricultural Credits............................................................................................49 - Use of Agricultural Credits.................................................................................................49 - Reasons for not using agricultural credits ..........................................................................50 3.3.7.2 Crop Extension...........................................................................................................................50 - Sources of crop extension messages...................................................................................51 - Quality of extension............................................................................................................51 3.9 Access to Inputs .........................................................................................................................................................51 3.9.1 Use of Inputs ..............................................................................................................................................................51 3.9.2 Inorganic Fertilizer ...................................................................................................................................................51 3.9.3 Improved Seeds .........................................................................................................................................................52 3.9.4 Insecticides and Fungicides......................................................................................................................................53 3.10 Tree Planting..............................................................................................................................................................53 3.8 Investment in Irrigation and Erosion Control Facilities...................................................................................... 54 3.12 Livestock Results...................................................................................................................................................... 55 3.12.1 Cattle Production ..........................................................................................................................................55 3.12.1.1 Cattle Population........................................................................................................................56 3.12.1.2 Herd size.....................................................................................................................................56 3.12.1.3 Cattle Population Trend .............................................................................................................56 3.12.1.4 Improved Cattle Breeds..............................................................................................................57 3.12.2 Goat Production............................................................................................................................................57 3.12.2.1 Goat Population..........................................................................................................................57 3.12.2.2 Herd Size ....................................................................................................................................57 3.12.2.3 Goat Breeds ................................................................................................................................58 3.12.2.4 Goat Population Trend ...............................................................................................................58 3.12.3 Sheep Production..........................................................................................................................................58 3.12.3.1 Sheep Population........................................................................................................................58 3.12.3.2 Sheep Population Trend .............................................................................................................58 TOC ____________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.4 Pig Production ..............................................................................................................................................59 3.12.4.1 Population Trend....................................................................................................................... 59 3.12.5 Chicken Production ......................................................................................................................................59 3.12.5.1 Chicken Population ....................................................................................................................59 3.12.5.2 Chicken Population Trend..........................................................................................................60 3.12.5.3 Chicken Flock Size.....................................................................................................................60 3.12.5.4 Improved Chicken Breeds (layers and broilers)........................................................................61 3.12.6 Other Livestock ............................................................................................................................................61 3.12.7 Pests and Parasites Incidences and Control .................................................................................................62 3.12.7.1 Deworming.................................................................................................................................62 3.12.8 Access to Livestock Services .......................................................................................................................62 3.12.8.1 Access to livestock extension Services......................................................................................62 3.12.8.2 Access to Veterinary Clinic .......................................................................................................63 3.12.8.3 Access to village watering points/dam ......................................................................................63 3.12.9 Animal Contribution to Crop Production.....................................................................................................64 3.12.9.1 Use of Draft Power.....................................................................................................................64 3.12.9.2 Use of Farm Yard Manure .........................................................................................................64 3.5.0 Fish Farming..............................................................................................................................................................65 3.6.0 Access to Infrastructure and Other Services ........................................................................................................ 65 3.7 Poverty Indicators.....................................................................................................................................................66 3.7.1 Type of Toilets..............................................................................................................................................66 3.7.2 Household’s assets........................................................................................................................................66 3.7.3 Sources of Light Energy...............................................................................................................................67 3.7.4 Sources of Energy for Cooking....................................................................................................................67 3.7.5 Roofing Materials.........................................................................................................................................67 3.7.6 Access to Drink Water..................................................................................................................................68 3.7.7 Food Consumption Pattern...........................................................................................................................68 3.7.7.1 Number of Meals per Day..........................................................................................................68 3.7.7.2 Meat Consumption Frequencies.................................................................................................69 3.7.7.3 Fish Consumption Frequencies..................................................................................................69 3.7.8 Food Security................................................................................................................................................69 3.7.9 Main Source of Cash Income.......................................................................................................................70 PART IV: MOROGORO PROFILES ..................................................................................................................................71 4.1 Regional Profile .........................................................................................................................................................71 4.2 District Profile........................................................................................................................................................... 71 4.2.1 Kilosa............................................................................................................................................................71 4.2.2 Morogoro Rural..........................................................................................................................................73 4.2.3 Kilombero................................................................................................................................................... 75 4.2.4 Ulanga ......................................................................................................................................................... 77 4.5 Morogoro Urban........................................................................................................................................ 79 4.6 Mvomero..................................................................................................................................................... 81 ACRONYMS __________________________________________________________________________________________________ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scott’s Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Morogoro region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Cletus P. B. Mkai The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Morogoro region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Morogoro region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Morogoro region were 265,198 out of which 178,406 (67.2%) were involved in growing crops only, 1,477 (0.6%) rearing livestock only, 194 (0.1%) were pastoralist, and 85,121 (32%) were involved in crop production as well as livestock keeping. In summary, Morogoro region had 259,246 households involved in crop production and 36,524 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock keeping/herding, permanent crop farming, remittances and fishing/hunting and gathering. The region has a literacy rate of 68 percent. The highest literacy rate is in Mvomero district (77%) followed by Kilombero district (73%), Morogoro Urban district (70%), Morogoro Rural (68%), Kilosa (67%) and Ulanga (66%). The literacy rate for the heads of households in the region was 77.2 percent. The number of heads of agricultural households with formal education in Morogoro region was 196,247 (72%), those without formal education were 59,504 (23%) and those with only adult education were 4,995 (2%). The majority of heads of agricultural households (72%) had primary level education whereas less than 0.2 percent had post primary education. In Morogoro region 139,109 household members (53%) were involved in one off-farm income generating activity, 79,217 (30%) involved in two off-farm income generating activities and 28,027 (11%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 558,133 ha. The regional average land area utilised for crop production per crop growing household was only 1.8 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 414,604 hectares out of which 127,604 hectares (31%) were planted during short rainy season and 286,546 hectares (69%) during long rainy season. An estimated area of 337,461 ha (81.5% of the total planted area with annual and vegetable crops) was with cereals, followed by 28,556 hectares (6.9%) of pulses, 22,301 ha (5.4%) of roots and tubers, 12,735 ha (3.1%) of oil seed, 12,400 hectares (3.0%) 0f fruit and vegetable, and 698 ha (0.2%) of cash crops. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Maize Maize is the dominant annual crop grown in Morogoro region and it had a planted area 1.5 times greater than paddy, which had the second largest planted area. The area planted with maize constitutes 47 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) are beans, cassava, sorghum, simsim, tomatoes, sweetpotatoes, groundnuts, cabbage and cocoyam. The yield of maize has dropped over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize increased from 1994/95 to 20002/03. The peak area recorded under maize production was in 1999/00 (242,544 ha). However, the yield of maize has shown a gradual decline over the years since 1994/95 (from 2.1t/ha in 1994/95 to 0.6 t/ha in 2003) Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Morogoro region during the long rainy season was 109,655. This represented 49 percent of the total crop growing households in Morogoro region in the long rainy season. Cassava The area planted with cassava was larger than any other root and tuber crop in Morogoro in terms of planted area (4% of the total area planted with annual crops and vegetables) and it accounted for 77 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 42,229 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 21,747 tonnes, which amounts to 51 percent of the total fruit and vegetable production, followed by cabbage 10,374 tonnes (25%), onion 4686 tonnes (11%), pumpkins 1,877 tonnes (4%), chillies 973 tonnes (2%), and amaranths 849 tonnes (2%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 50,712 hectares which is 11 percent of the area planted with annual crops in the region. The most important permanent crop is bananas which accounts for 19 percent of the total area planted with permanent crops followed by sugarcane (16%), coconut (15%) and mango (10%). Improved Seeds The planted area using improved seeds was 55,330 ha which represents 14 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the long rainy season was 14.1 percent which is slightly higher than the corresponding percentage use for the short rainy season (13.6%). Use of Fertilizers Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 112,856 hectares representing 89 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertiliser was applied to 13,038 ha which represented 5 percent of the total planted area (44 % of the area planted with fertiliser application). This was followed by farm yard manure (10,901 ha, 40%). Compost fertilizers were used on a very small area and represented only 2 percent of the area planted with fertilizers. Irrigation EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix In Morogoro region, the area of annual crops and vegetables under irrigation was 64,685 ha representing 16 percent of the total area planted. The area under irrigation during the short rainy season was 6,810 ha accounting for 11 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 20 percent compared with 5 percent in the short rainy season. Crop Storage There were 336,432 crop growing households (15.3% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was paddy with 99,430 households storing 19870 tonnes as of 1st January 2004. This was followed by maize (183,248 households and 17,805 tonnes), sorghum and millet (15,471 households and 1,436 tonnes) and beans and pulses (35,134 households and 955 tonnes) and groundnuts (1,524 household and 154 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 182,902 which represent 70.1 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Kilombero (87%) followed by Morogoro Urban (76%), Ulanga (74%), Morogoro Rural (69%), Mvomero (69%) and Kilosa (60%) . Agricultural Credit In Morogoro region, few agricultural households (11,457, 4.4%) accessed credit, out of which 7,799 (68%) were male- headed households and 3,658 (32%) were female headed households. In Kilosa district only male headed households got credit for agriculture purposes, whereas in Mvomero district more female household got agricultural credit than male household.. In the remaining districts both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 67,368 (26% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.96). Ulanga district had a relatively high proportion of households that received crop extension messages (37%), followed by Mvomero (35%), Kilombero (32%), Kilosa (21%), Morogoro Rural (13%) and Morogoro Urban (10%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 8,894. This number represents 3 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Mvomero district (28%) followed by Kilosa (26%), Morogoro Rural (20), Kilombero (11%), Ulanga (9%) and Morogoro Urban (6%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 455,985. Cattle rearing is the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.7 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 455,985 head (98.9% of the total number of cattle in the region), 5,052 (1.1%) were dairy breeds and only 26 (0.005%) were beef breeds. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x Goats The number of goat-rearing-households in the region was 27,920 (4.3% of all agricultural households) with a total of 243,175 goats giving an average of 9 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 7,442 (1.2% of all agricultural households) with a total of 95,680 sheep giving an average of 13 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 18,088 (2.8% of the total agricultural households) rearing about 44,986 pigs. This gives an average of 3 pigs per pig-rearing household. Chicken The number of households keeping chickens was 154,850, raising 2,100,861 chickens. This gives an average of 14 chickens per chicken-rearing household. In terms of total number of chickens in the country Morogoro ranked sixth out of the 21 Mainland regions. Use of Draft Power The region has 20,104 oxen and they were found in Ulanga 10,281, Kilombero 6,466, Kilosa 2,591 and Mvomero 766. Morogoro region has 0.9 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 17,218 hectares of land. Fish Farming The number of households involved in fish farming was 902 (0.3 percent of the total agricultural households in the region). Kilombero was the leading district with 369 agricultural households involved in fish farming (41%) followed by Morogoro Rural 363 (40%), Kilosa 93 (10%) and Ulanga 76 (8%). Fish farming was not practiced in Morogoro Urban and Mvomero districts. iv) Poverty Indicators Availability of Toilets It was estimated that 94.7 percent of all rural agricultural households used the traditional pit latrines, 2.2 percent used improved pit latrine and 1.2 percent had flush toilets. The remaining 0.2 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 2.7 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (58% of households) followed by bicycle (38.7%), iron (13.6%), wheelbarrow (4.1%), mobile phone (1.6%), landline phone (0.3%), vehicle (0.2%) and television/video (0.0%). Source of Lighting Energy EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xi Wick lamp is the most common source of lighting energy in the region. About 70.5 percent of the total rural households used this source of energy followed by hurricane lamp (22.4%), pressure lamp (4.3%), mains electricity (1.1%), firewood (1.2%), candle (0.1%), gas or biogas (0.1%) and solar (0.1%), Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 92.2 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (6.3%). The rest of energy sources accounted for 1.5 percent. These were bottled gas (0.22%), crop residues (0.46%), mains electricity (0.21%), solar (0.20%), livestock dung (0.03%), parrafin/kerosene (0.35%) and none for gas/biogas. Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 54 percent of the rural agricultural households however, this was closely followed by iron sheets (36.2%). Other roofing materials are grass/mud (8.4%), asbestos (0.2%), tiles (0.8%), concrete (0.4%) and others (0.1%). Number of Meals per Day About 53.2 percent of the holders in the region took two meals per day, 42.6 percent took three meals, 3.5 percent took one meal and 0.7 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 34.8 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 11.2 percent whereas those with little problems represent 8.1 percent. About 8.7 percent of agriculture households always faced food shortages whilst 37.2 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 56.8 percent of all rural agricultural households. The second main cash income earning activity was casual labour (11.8%) followed by selling of cash crops (9.6%), businesses (8.8%) and cash remittances (2.3%). Other income earning activities were employment (3.2%), sale of livestock (1.6%), sale of forest products (4.3%), sale of livestock products (0.5%) and fishing (0.4%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ...................................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District ..........10 3.2 Area, Production and Yield of cereal crops by Season..............................................................................................16 3.3 Area planted and quantity harvested by season and type of root and tuber crop ......................................................18 3.4 Area, Quantity Harvested and Yield of Pulses by Season .........................................................................................20 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season...........................................................................21 3.6 Area, Production and Yield of Fruits and Vegetables by Season ..............................................................................22 3.7 Area, Production and Yield of Annual Cash Crops by Season..................................................................................25 3.8 Land Clearing Methods...............................................................................................................................................29 3.9 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Long Rainy Season..................................................................................................................................31 3.10 Number of Households Storing Crops by Estimated Storage Loss and District .......................................................39 3.11 Reasons for Not Selling Crop Produce.......................................................................................................................42 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District ........................43 3.13 Total Number of Households and Chickens Raised by Flock Size ...........................................................................49 3.14 Head Number of Other Livestock by Type of Livestock and District.......................................................................50 3.15 Number of Households by Distance to Nearest Veterinary Clinic and District........................................................51 3.16 Number of Households by Distance to Nearest Village Watering Points/Dams and District...................................52 3.17 Mean distances from holders dwellings to infrustructures and services by districts.................................................53 3.18 Number of Households by Number of meals the Household normally has per Day and District ............................55 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings...............................................................10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head.....................................................11 3.3 Percentage Distribution of Population by Age and Sex in 2003................................................................................11 3.4 Percentage Literacy level by District..........................................................................................................................11 3.5 Literacy Rates for Heads of Household by Gender and District................................................................................12 3.6 Percentage of Population Aged 5 years and above by District and Educational Status............................................12 3.7 Percentage of Population Aged 5 years and Above in Agricultural Households by Education Status............................................................................................................12 3.8 Percentage Distribution of Heads of Household by Educational Attainment ...........................................................12 3.9 Percentage Distribution of Agricultural Households by Number of Off-farm Activities.........................................13 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities.........................................13 3.11 Utilized and Usable Land per Household by District.................................................................................................13 3.12 Percentage Distribution of Land Area by Type of Land Use.....................................................................................14 3.13 Area Planted with Annual Crops by season (ha)........................................................................................................14 3.14 Area Planted with Annual Crops (ha) by Season and District...................................................................................14 3.15 Area Planted with Annual Crops per Household by Season and District..................................................................14 3.16 Planted Area for the Main Annual Crops (ha)............................................................................................................15 3.17a Planted Area per Household by Selected Crop ..........................................................................................................15 3.17b Percentage Distribution of Area Planted with Annual Crops by Crop Type ............................................................15 3.18 Area planted with Annual Crops by Type of Crops and Season................................................................................15 3.19 Area Planted and Yield of Major Cereal Crops..........................................................................................................16 3.20 Time Series Data On Maize Production .....................................................................................................................16 3.21 Maize: Total Area Planted and Planted Area per Household by District ..................................................................17 3.22 Time Series of Maize Planted Area and Yield ..........................................................................................................17 3.23 Total Planted Area and Area of Paddy per Household by District ............................................................................17 3.24 Time Series Data on Paddy Production......................................................................................................................17 3.25 Time Series of Paddy Plated Area and Yield ............................................................................................................18 3.26 Area planted with Paddy, Sorghum and Bulrush millets by District.........................................................................18 3.27 Area Planted and Yield of Major Pulse Crops ...........................................................................................................19 3.28 Area Planted with Root Crops during the Census/Survey year .................................................................................19 3.29 Percent of Beans Planted Area and Percent of Total Land with Beans by District...................................................20 3.30 Beans Planted Area per Beans Growing Household by District................................................................................20 3.31 Time Series of Beans Planted Area and Yield ...........................................................................................................21 3.32 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District............................................21 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.33 Cassava Planted Area per Cassava Growing Household by District.........................................................................21 3.34 Area Planted and Yield of Major Oil Seed Crops..................................................................................................... 22 3.35 Percent of Simsim Planted Area and Percent of Total Land with Simsim by District............................................. 22 3.36 Area Planted per Simsim Growing Household by District (Long Rainy Season Only)........................................... 22 3.37 Area Planted and Yield of Fruit and Vegetables....................................................................................................... 23 3.38 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ............................................ 23 3.39 Area Planted per Tomato Growing Household by District (Short Rainy Season Only).......................................... 24 3.40 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ......................................... 24 3.41 Percent of Carrots Planted Area and Percent of Total Land with Carrots by District.............................................. 24 3.42 Area planted with Annual Cash Crops ...................................................................................................................... 25 3.43 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District.......................................... 25 3.44 Area Planted for Annual and Permanent Crops......................................................................................................... 26 3.45 Area Planted with the Main Permanent Crops .......................................................................................................... 26 3.46 Percent of Area Planted and Average Planted Area with Permanent Crops by District .......................................... 26 3.47 Percent of Area Planted with Banana and Average Planted Area per Household by District ................................. 26 3.48 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District............................. 27 3.49 Percent of Area Planted with Coconut and Average Planted Area per Household by District................................ 27 3.50 Percent of Area Planted with Mango and Average Planted Area per Household by District.................................. 28 3.51 Number of Households by Method of Land Clearing During the Long Rainy Season............................................ 28 3.52 Area Cultivated by Cultivation Method..................................................................................................................... 29 3.53 Area Cultivated by Method of Cultivation and District............................................................................................ 29 3.54 Planted Area with Improved Seed by Crop Type...................................................................................................... 30 3.55a Percentage of Crop Type Planted Area with Improved Seed – Annuals.................................................................. 30 3.55b Percentage Area with Improved Seed by Crop Type................................................................................................ 30 3.56 Area of Fertilizer Application by Type of Fertilizer ................................................................................................. 30 3.57 Area of Fertilizer Application by Type of Fertilizer and District............................................................................. 30 3.58 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season............................................................ 31 3.59 Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals ........................................................... 31 3.60 Planted Area with Inorganic Fertiliser by Crop Type - Long rainy season.............................................................. 32 3.61 Percentage of Crop Type Planted Area with Inorganic Fertilizers – Annuals.......................................................... 32 3.62 Planted Area with Compost by Crop Type - Long rainy season............................................................................... 32 3.63 Planted area (ha) by Pesticide use.............................................................................................................................. 33 3.64 Planted Area applied with Pesticide by Crop Type................................................................................................... 33 3.65 Percentage of Crop Type Planted Area applied with Pesticide................................................................................. 33 3.66 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season .......................... 33 3.67 Planted Area Applied with Herbicides by Crop Type............................................................................................... 34 3.68 Percentage of Crop Type Planted Area applied with Herbicides.............................................................................. 34 3.69 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season............................ 34 3.70 Planted Area applied with Fungicides by Crop Type................................................................................................ 34 3.71 Percentage of Crop Type Planted Area applied with Fungicides ............................................................................. 34 3.72 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season............................ 35 3.73 Area of Irrigated Land................................................................................................................................................ 35 3.74 Planted Area and Percentage of Planted Area with Irrigation by District................................................................ 36 3.75 Number of Households with Irrigation by Source of Water..................................................................................... 36 3.76 Number of Households by Method of Obtaining Irrigation Water........................................................................... 36 3.77 Number of Households with Irrigation by Method of Field Application................................................................. 37 3.78 Number of Households and Quantity Stored by Crop Type..................................................................................... 37 3.79 Number of households by Storage Methods.............................................................................................................. 37 3.80 Number of households by method of storage and District (based on the most important household crop)............ 38 3.81 Normal Length of Storage for Selected Crops .......................................................................................................... 38 3.82 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ......................................................... 38 3.83 Number of Households by Purpose of Storage and Crop Type................................................................................ 39 3.84 Percentage of Households Processing Crops by District .......................................................................................... 39 3.85 Percentage of Households Processing Crops by District .......................................................................................... 40 3.86 Percent of Crop Processing Households by Method of Processing.......................................................................... 40 3.87 Percent of Households by Type of Main Processing Product................................................................................... 40 3.88 Number of Households by Type of By-product........................................................................................................ 41 3.89 Use of Processed Product........................................................................................................................................... 41 3.90 Percentage of Households Selling Processed Crops by District............................................................................... 41 3.91 Location of Sale of Processed Product ...................................................................................................................... 41 3.92 Percent of households Selling Processed products by Outlet for sale and District .................................................. 42 3.93 Number of Crop Growing Households Selling Crops by District ............................................................................ 42 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.94 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem .......................... 43 3.95 Percentage Distribution of households that Received Credit by Main Sources ....................................................... 43 3.96 Proportion of Households Receiving Credit by Main Purpose of the Credit ........................................................... 44 3.97 Number of Households Receiving Extension Advice............................................................................................... 44 3.98a Number of Households Receiving Extension by District ......................................................................................... 44 3.99 Number of Households Receiving Extension by Quality of Services ...................................................................... 45 3.100 Number of Households by Source of Inorganic Fertiliser ........................................................................................ 45 3.101 Number of Households Reporting Distance to Source of Inorganic Fertiliser......................................................... 45 3.102 Number of households by source of Improved Seed................................................................................................. 45 3.103 Number of Households reporting Distance to source of Improved seed ................................................................. 46 3.104 Number of Households by source of Insecticide/Fungicide ..................................................................................... 46 3.105 Number of Household reporting Distance to source of insecticides/Fungicide ....................................................... 46 3.106 Number of Households with Planted Treees ............................................................................................................. 47 3.107 Number of Planted Trees by Species......................................................................................................................... 46 3.108 Number of Trees Planted by Smallholders by Species and Region.......................................................................... 48 3.109 Number of Trees Planted by Location....................................................................................................................... 48 3.110 Number of Households by Purpose of Planted Trees................................................................................................ 48 3.111 Number of Households with Erosion Control/Water Harvesting Facilities ............................................................. 48 3.112 Number of Households with Erosion Control/Water Harvesting Facilities ............................................................. 49 3.113 Number of Erosion control/Water Harvesting Structures by Type of Facility......................................................... 49 3.114 Total Number of cattle ............................................................................................................................................... 50 3.115 Number of cattle by Type and District ...................................................................................................................... 50 3.116 Cattle population trend............................................................................................................................................... 50 3.117 Dairy Cattle Population Trend .................................................................................................................................. 50 3.118 Number of Goats (‘000’) by District ......................................................................................................................... 51 3.119 Goat population Trend ............................................................................................................................................... 51 3.120 Total Number of Sheep by District............................................................................................................................ 52 3.121 Sheep Population Trend............................................................................................................................................. 53 3.122 Total Number of Pigs by District............................................................................................................................... 54 3.123 Pig Population Trend.................................................................................................................................................. 54 3.124 Total Number of chickens by District........................................................................................................................ 54 3.125 Chicken Population Trend ......................................................................................................................................... 54 3.126 Number of Improved Chicken (Layers and Broilers)................................................................................................ 54 3.127 Layers Population Trend............................................................................................................................................ 55 3.128 Percentage of Livestock Keeping Households Reporting Tsetse flies and tick Problems by district...................... 56 3.129 Percent of Livestock Rearing Households that De wormed Livestock by Livestock Type and district.................. 50 3.130 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services .............. 50 3.131 Number of Household by distance to Veterinary Clinic........................................................................................... 51 3.132 Number of household sto distance to Veterinary clinic and district......................................................................... 51 3.133 Number of households by Distance to village watering Points ................................................................................ 52 3.134 Number of Households by Distance to Village watering Point and district............................................................. 53 3.135 Number of households Using Draft Animals ............................................................................................................ 54 3.136 Number of Households Using draft Animals by District.......................................................................................... 54 3.137 Number of Households Using Organic fertiliser....................................................................................................... 54 3.138 Area of Application of Organic Fertiliser by District ............................................................................................... 54 3.139 Number of Households Practicing Fish Farming...................................................................................................... 54 3.140 Number of Households practicing Fish farming by district...................................................................................... 55 3.141 Fish Production........................................................................................................................................................... 56 3.142 Agricultural Households by Type of Toilet Facility ................................................................................................. 56 3.143 Percentage Distribution of Households Owning the Assets...................................................................................... 50 3.144 Percentage Distribution of Households by Main source of Energy for Lighting .................................................... 50 3.145 Percentage Distribution of Households by Main Source of Energy for Cooking .................................................... 51 3.146 Percentage Distribution of Households by Type of Roofing Material ..................................................................... 51 3.147 Percentage distribution of Households with Grass/Leafy Roofs by District............................................................ 52 3.148 Percent of Households by Main Souse of Drinking Water and Season.................................................................... 53 3.149 Percent of Households by Distance to Main Source of drinking Water and Season................................................ 54 3.150 Number of agricultural Households by Number of Meals per Day.......................................................................... 54 3.151 Number of Households by Frequency of Meat and Fish Consumption.................................................................... 54 3.152 Percentage Distribution of the number of Households by Main Source of Income................................................. 54 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................... 19 3.9 Area planted and Percentage During the Dry Season by District...................................................................... 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District .................................. 22 3.11 Planted Area and Yield of Maize by District ..................................................................................................... 25 3.12 Area Planted per Maize Growing Household..................................................................................................... 25 3.13 Planted Area and Yield of Paddy by District ..................................................................................................... 26 3.14 Area Planted per Paddy Growing Households ................................................................................................... 26 3.15 Planted Area and Yield of Beans by District...................................................................................................... 28 3.16 Planted Area per Beans Growing Households ................................................................................................... 28 3.17 Planted Area and Yield of Cowpeas by District................................................................................................. 30 3.18 Area Planted per Cowpeas Growing Households .............................................................................................. 30 3.19 Planted Area and Yield of Cassava by District .................................................................................................. 32 3.20 Planted Area per Cassava Growing Households................................................................................................ 32 3.21 Planted Area and Yield of Simsim by District ................................................................................................... 34 3.22 Area Planted per Simsim Growing Households................................................................................................. 34 3.23 Planted Area and Yield of Tomato by District................................................................................................... 36 3.24 Area Planted per Tomato Growing Households................................................................................................. 36 3.25 Planted Area and Yield of Sugarcane by District............................................................................................... 39 3.26 Area Planted per Sugarcane Growing Households ............................................................................................ 39 3.27 Planted Area and Yield of Mango by District.................................................................................................... 42 3.28 Area Planted per Mango Growing Households.................................................................................................. 42 3.29 Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District.................. 45 3.30 Planted Area and Percent of Total Planted Area with Compost Manure application by District..................... 45 3.31 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 48 3.32 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 48 3.33 Percent of households storing crops for 3 to 6 months by district..................................................................... 58 3.34 Number of Households and Percent of Total Households Selling Crops by District........................................ 58 3.35 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 65 3.36 Number and Percent of Crop Growing Households using Improved Seed by District..................................... 65 3.39 Number and percent of smallholder planted trees by district............................................................................. 70 3.40 Number and Percent of Households with water Harvesting Bunds by District................................................. 70 3.41 Cattle population by District as of 1st Octobers 2003........................................................................................ 74 3.42 Cattle Density by District as of 1st October 2003.............................................................................................. 74 3.43 Goat population by District as of 1st Octobers 2003 ......................................................................................... 75 3.44 Goat Density by District as of 1st October 2003................................................................................................ 75 3.45 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 78 3.46 Sheep Density by District as of 1st October 2003.............................................................................................. 78 3.47 Pig population by District as of 1st Octobers 2003............................................................................................ 79 3.48 Pig Density by District as of 1st October 2003 .................................................................................................. 79 3.49 Number of Chickens by District as of 1st October 2003 ................................................................................... 81 3.50 Density of Chickens by District as of 1st October 2003.................................................................................... 81 3.51 Number and Percent of Households Infected with Ticks by District ................................................................ 83 3.52 Number and Percent of Households Using Draft Animals by District.............................................................. 83 3.53 Number and Percent of Households Practicing Fish Farming by District......................................................... 88 3.54 Number and Percent of Households Without Toilets by District ...................................................................... 88 3.55 Number and Percent of Households using Grass/Mud for roofing material by District................................... 90 3.56 Number and Percent of Households eating 3 meals per day by District ........................................................... 90 3.57 Number and Percent of Households eating Meat Once per Week by District .................................................. 94 3.58 Number and Percent of Households eating Fish Once per Week by District.................................................... 94 3.59 Number and percent of Households Reporting food insufficiency by District ................................................. 95 INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Morogoro region is located in the Mid – Eastern part of Tanzania mainland. The region lies between latitudes 5° 58’ and 10’ south of the equator and between longitude 35° 25’ and 38° 30’ East Greenwich. To the north Morogoro region shares boarders with Arusha and Tanga regions. To the east and southeast, it shares boarders with Ruvuma and Lindi regions respectively. To the west and southwest it shares borders with Dodoma and Iringa regions respectively. 1.3 Land Area 1.4 Climate 1.4.1 Temperatur Morogoro region has an average temperature of 24° C. The minimum is 18° C in mountainous areas and has a maximum of 30° C in lowland areas. The coolest months are May, June and July, while the hottest months are September and October. 1.4.2 Rainfall Altitudes vary considerably from one district to another. The main rain season is from November to May, while the dry season in from June to October. The topographical variations in different parts of the region explain the existing variations in the climatic conditions. The variation in rainfall is between 500 mm in low areas and 2,200 mm in the mountainous areas. 1.5 Population According to the 2002 Population and Housing Census, there were 1,759,809 inhabitants in Morogoro region. The population of Morogoro region ranked 6th of the 21 regions in Tanzania. INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 439,520 million with a per capita income of shillings 249,754. The region held 8th position among regions on GDP and contributed about 4.5 percent to the national GDP1 The region headquarter can easily be reached by road from dare s Salaam, Dodoma and Iringa towns. It is also the centre for travelers going to Dodoma, Tabora, Lake zone and Kigoma by train. The region has a tourist attraction – Mikumi National Park that is about 100 kilometers from Morogoro town and about 300 kilometers from DAR ES salaam and Selous game reserve. The region is famous for producing both food and cash crops. The main food crops produced in Morogoro region include: maize, paddy, sorghum, bulrush millets and beans. The main cash crops include cotton and tobacco. Livestock keeping is als an important economic activity in the region. INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2.1 INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.2 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.3 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.4 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.5 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.6 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.7 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 2.7.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.7.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.7.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.7.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.7.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.7.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2.7.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.7.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.7.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.7.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.7.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. INTRODUCTION _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census data for Morogoro region which are based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and Maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. More effort has been placed in analyzing the results in order to formulate solid conclusions than in previous censuses and surveys. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Morogoro region was 260,746. The largest number of agriculture households was in Kilosa (73,435) followed by Morogoro Rural (53,117), Mvomero (50,069), Kilombero (48,782), Ulanga (30,908) and Morogoro Urban (4,434) (Map 3.1). The highest density of household was found in Mvomero (20 km2) and Kilosa (14km2) (Map 3.2). Most household (224,222, 86%) were involved in growing crops only, 1,500 (0.6%) rearing livestock only and 35,024, (13%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3,3.4,3.5 and 3.6) 3.1.2 Livelihood Activities/Source of Income The census results for Morogoro region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock, keeping/herding, permanent crop farming, remittances and fishing/hunting (Table 3.1). 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Morogoro region was 209,037 (80% of the total regional agricultural households) whilst for female-headed households the number was 51,709 (20% of the total regional agricultural households). The mean age of household heads was 44 years (43 years for male heads and 45 years for female heads) Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farmin g Permane nt Crop Farming Livest ock Keepin g / Herdin g Off Farm Inco me Remi ttanc es Fishing / Hunting & Gatherin g Tree / Forest Resour ces Kilosa 1 5 4 2 6 7 3 Morogoro 1 4 5 2 6 7 3 Kilombero 1 4 5 2 6 7 3 Ulanga 1 5 4 2 6 7 3 Morogoro Urb 1 3 5 4 6 7 2 Mvomero 1 5 4 3 6 7 2 Total 1 5 4 2 6 7 3 Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Chart 3.1 Agriculture Households by Type - Morogoro Crops Only, 224222, 86.0% Livestock Only, 1500, 0.6% Crops and Livestock, 35024, 13.4% Morogoro Rural Morogoro Urban Kilombero Mvomero 12 14 10 3 20 Ulanga Kilosa 7 Morogoro Urban Morogoro Rural Kilombero Mvomero Kilosa 4,434 53,117 48,782 30,908 50,069 73,435 Ulanga Total Number of Agricultural Households by District Number of Agriculture Households MAP 3.1 MOROGORO Agricultural Households Per Square Km MAP 3.2 MOROGORO Number of Agricultural Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census 60,000 to 74,000 46,000 to 60,000 32,000 to 46,000 18,000 to 32,000 4,000 to 18,000 15 to 20 12 to 15 9 to 12 6 to 9 3 to 6 Number of Agriculture Households Agricultural Households Per Square Km RESULTS 12 Morogoro Rural Morogoro Urban Mvomero Kilombero 99.3% 98.5% 99.5% 100% 100% Ulanga Kilosa 99.8% Morogoro Rural Kilombero Mvomero Morogoro Urban Kilosa 52,753 48,782 49,316 4,423 73,064 30,908 Ulanga Number of Crop Growing Households by District Number of Crop Growing Households MAP 3.3 MOROGORO Percent of Crop Growing Households MAP 3.4 MOROGORO Percent of Crop Growing Households by District Tanzania Agriculture Sample Census 60,000 to 74,000 46,000 to 60,000 32,000 to 46,000 18,000 to 32,000 4,000 to 18,000 99.7 to 100 99.4 to 99.7 99.1 to 99.4 98.8 to 99.1 98.5 to 98.8 Number of Crop Growing Households Percent of Crop Growing Households RESULTS 13 Morogoro Urban Morogoro Rural Kilombero Mvomero 2% 22% 26% 11% 17% 22% Ulanga Kilosa Kilombero Morogoro Rural Morogoro Urban Mvomero 10 12 20 14 3 Ulanga Kilosa 7 Number of Crop Growing Households Per Square Kilometer of Land by District Number of Crop Growing Households MAP 3.5 MOROGORO Percent of Crop and Livestock Households MAP 3.6 MOROGORO Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census 15 to 20 12 to 15 9 to 12 6 to 9 3 to 6 21.2 to 26 16.4 to 21.2 11.6 to 16.4 6.8 to 11.6 2 to 6.8 Number of Crop Growing Households Per Square Km Percent of Crop and Livestock Households RESULTS 14 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households (Chart 3.2). 3.1.4 Number and Age of Household Members Morogoro region had a total rural agricultural population of 1,235,577 of which 614,454 (50%) were males and 621,124 (50%) were females. Whereas age group 0-14 constituted 41 percent of the total rural agricultural population, age group 15–64 (active population) was only 55 percent. Morogoro region had an average household size of 5 with Kilosa and Morogoro Urban districts having the lowest household size of 4 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Morogoro region had a total literacy rate of 68 percent. The highest literacy rate was found in Mvomero district (77%) followed by Kilombero district (73%), Morogoro Urban district (70%), Morogoro Rural (68%), Kilosa (67%) and Ulanga (66%) (Chart 3.4) Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 77 percent. The literacy rates among the male and female heads of households were 78 and 73 percent respectively. Male head of household literacy rate was higher than that of female heads in all districts. The districts with the highest literacy rate amongst heads of households were Kilombero and Ulanga districts with each having a literacy rate of (82%) followed by Mvomero (77%), Morogoro Rural (76%), Kilosa (72%) and Morogoro Urban (70%) (Chart 3.5) Chart 3.3 Percent Distribution of Population by Age and Sex - Morogoro 0 6 12 18 00 - 04 10 - 14 20 - 24 30 - 34 40 - 44 50 - 54 60 - 64 70 - 74 80 - 84 Age Group Percent Male Female Chart 3.5 Literacy Rates for Heads of Household by Gender and District-Morogoro 0 25 50 75 100 Kilosa M'goro R Kilombero Ulanga M'goro Urb Mvomero District Percent Male Female Total Chart 3.4 Percent Literacy Level of Household Members by District 60 65 70 75 80 Mvomero K'mbero M'oro U M'goro R Kilosa Ulanga District Percent DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households members. The results show that 45 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 26 percent were still attending school. Those who have never attended school were 28 percent (Chart 3.6). Agricultural households in Mvomero district had the highest percentage (48%) of population aged 5 years and above who had completed different levels of education. This was followed by Morogoro Urban and Kilombero districts each having 47% then Kilosa 46%, Ulanga 43% and Morogoro rural 42%. The number of heads of agricultural households with formal education in Morogoro region was 196247 (75%), those without formal education were 64,498 (25%). The majority of heads of agricultural households (72%) had primary level education whereas less than 0.2 percent had post primary education (chart 3.8). With regard to the heads of agricultural households with primary or secondary education in Morogoro region, Kilosa district had the highest percentage (26%) followed by Kilombero and Mvomero each having 20 percent then Morogoro rural 19 percent, Ulanga 13 percent and last was Morogoro Urban one percent. As for secondary education Kilombero had 30 percent followed by Ulanga 24 percent, Kilosa 19 percent, Morogoro Rural 15 percent, Mvomero 10 percent and Morogoro urban 6 percent. (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Morogoro with 94 percent of households having at least one member with off-farm income. In Morogoro region 139,109 households had each one member age five years and above involved in off-farm income generating activity (53%), 79,217 households had each two members involved in off-farm income generating activities (30%) and 28,027 households had each more than two members involved in off-farm income generating activities (11%) and 14,393 households had each no member involved in off farm income generating activities (6%). Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Secondary and above 3% Primary Education 72% No Education 23% Post Primary Education 0% Adult Education 2% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 Kilosa Morogoro Kilombero Ulanga M'goro Urb Mvomero District Percent Attending School Completed Never Attended to School Chart 3.6 Percentage of Persons Aged 5 Years and Above by Educational Status Attending School 26% Never Attended 28% Completed 45% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 Ulanga district had the highest percentage of agriculture households with off-farm income (over 98.5% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Mvomero (98%), Morogoro Urban (98%), Kilosa (95%), Kilombero (94%) and Morogoro Rural (88%). The district with the highest percent of agriculture households with more than one member with off-farm income was Kilosa (48%). Morogoro district had the least number of households with more than one member having off-farm income (35%). 3.2 Crop Production 3.2.1 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land Available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1.1 Area of Land Utilised The total area of land available to smallholders was 558,133 ha. The Regional average land area utilised for agriculture per household was only 1.8 ha. This figure is below the national average which is estimated at 2.0 hectares. Land area utilised per household in five districts were below the national average with exception of Kilombero district which had the national average of 2.0 ha. It was followed by Mvomero 1.9ha, Ulanga 1.8ha, Kilosa 1.8ha, Morogoro Rural 1.6ha and Morogoro Urban 1.5ha. The percentage utilized of the usable land per household is highest in Morogoro Rural (90%) and lowest in Kilombero (78%). Eighty four percent of the total land Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Kilosa Morogoro Kilombero Ulanga Morogoro Urb Mvomero Districts Percent More than Two Off Farm Income Two One None Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 Kilombero Mvomero Ulanga Kilosa M'goro R M'goro Urb Districts Area/household 0 25 50 75 100 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.9 Percentage Distribution of Household Members of Five Years and Above by Number of Off-farm Activities Tw o Off Farm Income 30% One Off Farm Income 53% None 6% More than Tw o Off Farm Income 11% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 available to smallholders was utilised. Only 12.5 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.1.2 Types of Land Use The area of land under temporary mono crop was 328,994 hectares (57.9% of the total land available to smallholders in Morogoro), followed by area of uncultivated usable land (83,452ha, 14.7%), temporary mixed crops (54,759ha, 9.6%), area under permanent mono crops (27,285ha, 4.8%), area under permanent/ annual mix (18,491ha, 3.3%), area under fallow (12,208ha, 2.2%), area rented to others (11,497 ha, 2.0%), area under permanent mixed crops (11,388ha, 2.0%), area unusable (9,659ha, 1.7%), area under natural bush (4,299ha, 0.8%), area under planted trees (2,891ha, 0.5%) and area under pasture (2,868ha, 0.5%). (Chart 3.12) 3.2.2 Annual Crops and Vegetable Production Morogoro region has two rainy seasons, namely the short rainy season (October to November) and the long rainy season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.2.2.1 Area Planted The area planted with annual crops and vegetables was 428,534 hectares out of which 160,820 hectares (38%) were planted during short rainy season and 267,713 hectares (62%) during long rainy season. The average areas planted per household during the short and long rainy seasons was 0.6 and 0.7 ha respectively (Chart 3.13). The districts with the largest area planted per household (the average of the two seasons) were Kilombero (0.8 ha) followed by Ulanga and Mvomero district each having 0.7 ha. The district with the smallest average area planted was Morogoro Urban (0.4ha). The average planted area in all the district was higher in long rainy season than in short rainy season. (Chart 3.14 and Map 3.8) The planted area occupied by cereals was 337,461 ha (81.5% of the total area planted with annuals). This Chart 3.12 Percentage distribution of Land Area by Type of Land Use 0.5 0.5 0.8 1.7 2.0 2.0 2.2 3.3 4.8 9.6 57.9 14.7 0 100000 200000 300000 400000 Pasture Planted Trees Natural Bush Unusable Permanent Mixed Crops Others Fallow Permanent / Annual Mix Permanent Mono Crops Temporary Mixed Crops Uncultivated Usable Land Temporary Mono Crops Land Use Area (hectares) Chart 3.14 Area Planted with Annual Crops by Season and District 0 40000 80000 120000 Kilosa Morogoro Rural Kilombero Ulanga Morogoro Urban Mvomero Area Planted (ha) 0.00 20.00 40.00 60.00 Percentage Planted Short Rainy Season Long Rainy Season % Area planted in short rainy season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Short Rainy Season, 160820, 38% Long Rainy Season, 267713, 62% Long Rainy Season Short Rainy Season Morogoro Rural Kilombero Morogoro Urban Kilosa Mvomero 4,934ha 72,585ha 80,797ha 54,071ha 113,119ha 88,644ha Ulanga Kilombero Morogoro Rural Morogoro Urban Mvomero 78% 90% 87% 83% 86% 85% Ulanga Kilosa Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Area MAP 3.7 MOROGORO Planted Area (ha) MAP 3.8 MOROGORO Total Planted Area (Annual crops) by District Tanzania Agriculture Sample Census 86 to 90 84 to 86 82 to 84 80 to 82 78 to 80 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Planted Area (ha) Percent of Utilized Land Area RESULTS 19 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 was followed by pulses (28,556 hectares, 6.9%), roots and tubers (22,301 hectares, 5.4%), oil seeds (12,735 hectares, 3.1 %) fruit and vegetables (12,400 hectares, 3.0%) and cash crops (698 hectares, 0.2%). The average area planted per household during the long rainy season in Morogoro region was 0.7 hectares. Almost all districts had an average of less than one hectare per household in that season. The district with the largest planted area per household was Kilombero 0.9ha followed by Kilosa and Mvomero each having 0.7ha, Ulanga 0.6ha, Morogoro Rural 0.5ha and the least was Morogoro Urban 0.4ha. (Chart 3.15 and Map 3.9) Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.2.2.2 Crop Importance Maize is the dominant annual crop grown in Morogoro region and it had a planted area 1.5 times greater than paddy, which had the second largest planted area. The area planted with maize constitutes 47 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are beans, cassava, Irish potatoes, cowpeas, paddy and tomatoes (Chart 3.16) Households that grow paddy, maize, carrot and bulrush millets have larger planted areas per household than for other crops (Chart 3.17a) 3.2.2.3 Crop Types Cereals are the main crops grown in Morogoro region. The area planted with cereals was 337,461 ha (81.5% of the total planted area for annuals), followed by pulses with 28,556 ha (6.9%), roots and tubers 22,301 ha (5.4%), oil seeds and oil nuts 12,735 ha (3.1%) and fruits and vegetables 12,400 ha (3.0%). Annual cash crops which are mainly constituted of cotton and tobacco had the least planted area of about 698 ha (0.2%) (Chart 3.17b) Cereals are the dominant crops grown in both seasons followed by pulses and other crop types are of minor importance in Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.0 0.5 1.0 1.5 2.0 Kilosa Morogoro Kilombero Ulanga Morogoro Urb Mvomero District Area Planted (ha) Long Rainy Season Short Rainy Season Chart 3.17a Planted Area (ha) per Household for Selected Crops - Morogoro 0 0.25 0.5 0.75 1 Paddy Maize Carrot Bulrush Millet Water Mellon Sorghum Cotton Beans Simsim Cocoyam Cassava Groundnuts Barley Field Peas Mung Beans Sweet Potatoes Sunflower Crop Plan ted A rea (h a) Chart 3.16 Planted Area (ha) for the Main Annual Crops in Morogoro 0 100000 200000 300000 Maize Beans Cassava Irish Potatoes Cowpeas Paddy Tomatoes Green Gram Groundnuts Sweet Potatoes Cabbage Simsim Chillies Crop Planted Area (ha) DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 comparison. There is little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.2.2.4 Cereal Crop Production The total production of cereals was 234,558 tonnes. Maize was the dominant cereal crop at 115,570 tonnes which was 49 percent of total cereal crops produced, followed by paddy (48%) sorghum (2.36%), bulrush millets (0.04%), finger millets (0.04), wheat (0.09) and barley (0.02) (Map 3.10). The total area planted with cereals during the short and long rainy seasons was 337,461 ha out of which 106,628 ha (32%) were planted in short rainy season and 230,834 ha (68%) were planted during the long rainy season. The long rainy season accounts for 66 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 71 percent of the total area planted with cereals in that season followed by Paddy (26%) and Sorghum (3%) (Table 3.2) The area planted with maize was dominant and it represented 57.81 percent of the total area planted with cereal crops, then followed by paddy (37.49%), sorghum (4.39%), bulrush millets (0.13%) wheat (0.07), finger millet (0.05%), and barley (0.05). The yield of wheat was 936 kg/ha, followed by paddy (893 kg/ha), maize (592 kg/ha), finger millets (543 kg/ha), sorghum 374 kg/ha, barley (254 kg/ha and bulrush millets (197 kg/ha) (Chart 3.19). Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Maize 75654 55292 0.7 11943 60278 0.5 19509 115570 0.6 Paddy 27279 23114 0.8 99248 89889 0.9 12652 113003 0.9 Sorghum 3603 956 0.3 11227 4587 0.4 14830 5543 0.4 Bulrush Millet 39 19 0.5 416 70 0.2 455 89 0.2 Finger Millet 0 0 0.0 165 90 0.5 165 90 0.5 Wheat 0 0 0.0 238 223 0.9 238 223 0.9 Barley 53 0 0.0 104 40 0.4 157 40 0.3 Total 106628 79381 230834 155177 337462 234558 Chart 3.17b: Percentage Distribution of Area planted with Annual Crops by Crop Type Roots and tubers, 22301, 5% Pulses, 28556, 7% Oil seed and oil nuts, 12735, 3% Fruits and vegetables, 12400, 3% Cash crops, 698, 0% Cereals, 337461, 82% Cereals Roots and tubers Pulses Oil seed and oil nuts Fruits and vegetables Cash crops 106628 20122 2179 17483 11073 10258 2477 7167 5232 682 16 0 100000 200000 300000 Area (hectares) Cereals Roots and tubers Pulses Oil seed and oil nuts Fruits and vegetables Cash crops Crop Type Chart 3.18 Area Planted with Annual Crops by Type of Crops and Season Long Rainy Season Short Rainy Season Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50000 100000 150000 200000 Maize Paddy Sorghum Bulrush Millet Wheat Crop Area Planted (ha) 0.0 1.0 Yield (t/ha) Area in Hectare Yield (t/ha) Morogoro Rural Morogoro Urban Kilosa Mvomero Kilombero 21,104ha 24,946ha 950ha 26,368ha 14,219ha 40,016ha 39% 30.9% 36.3% 19.3% 12.6% 45% Ulanga 32,100 to 40,100 24,300 to 32,100 16,500 to 24,300 8,700 to 16,500 900 to 8,700 Morogoro Rural Mvomero Morogoro Urban Kilombero 72,585ha 88,644ha 113,119ha 80,797ha 54,071ha 17.5% 21.4% 1.2% 27.3% 19.5% 13.1% Ulanga Kilosa 4,934ha Area Planted and Percentage During the Short Rainy Season by District Area planted a(ha) MAP 3.9 MOROGORO Area Planted (ha) MAP 3.10 MOROGORO Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Tanzania Agriculture Sample Census 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Area Planted (ha) Percent of Planted Area Area Planted Cereals Crops Percent of Area Planted Cereal Crops RESULTS 22 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Morogoro region during the long rainy season was 148,561 (66% of the total crop growing households in the region during the long rainy season). The total production of maize was 115,570 tonnes from a planted area of 195,090 hectares resulting in a yield of 0.6 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tons) for the combined long and short rainy seasons. The production was steadily increasing from 70,000 tons in 1994/95 to 116,000 tons in 2002/03. The peak maize production was recorded in 1999/2000 with 152,000 tons. The average area planted with maize per household was 0.8 hectares; however it ranged from 0.5 hectares in Kilombero district to 1.0 hectares in Morogoro rural district. Morogoro rural district had the largest area of maize (137,106 ha) followed by Kilosa (72,420 ha), Kilombero (49,324 ha), Ulanga (29,884 ha), Morogoro urban (24,798 ha), and Mvomero (5,081 ha) (Chart 3.21 and Map 3.11). Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize increased from 1994/95 to 20002/03. The peak area recorded under maize production was in 1999/00 (242,544 ha). However, the yield of maize has shown a gradual decline over the years since 1994/95 (from 2.1t/ha in 1994/95 to 0.6 t/ha in 2003) (Chart 3.22) (Map 3.12). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Morogoro region during the long rainy season was 109,655. This represents 49 percent of the total crop growing households in Morogoro region in the long rainy season. The total production of paddy was 113,003 tonnes from a planted area of 126,527 hectares resulting in a yield of 0.89 t/ha. The district with the largest area planted with Paddy was Kilombero (53,096 ha) followed by Ulanga (30,662ha), Kilosa (15,910 ha), Mvomero (13,360 ha), Morogoro rural (13,001 ha), and Morogoro urban (497ha) (Map 3.13). There were significant variations in the average area planted per crop growing household among the districts ranging from 0.4 ha in Morogoro urban to 1.2 ha in Kilombero and Ulanga districts (Chart 3.23 and Map 3.14). Chart 3.20: Time Series Data on Maize Production - Morogoro 116 126 70 152 109 109 0 100 200 1994/95 1995/96 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 5081 24798 29884 49324 72420 137106 0 40000 80000 120000 160000 Morogoro Kilosa Kilombero Ulanga Morogoro Urb Mvomero District Area (Ha) 0.0 0.4 0.8 1.2 Area Planted per Household Area Planted Area Planted/hh Chart 3.22 Time Series of Maize Planted Area & Yield Morogoro 0 100,000 200,000 300,000 1994/95 1995/96 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 1 2 3 Yield (t/ha) Area Yield DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 24 There was a sharp drop in production of paddy in 1995/96 from 102,000 tons to 41,000 tons in 1997/98. The production rose to 103,000 tons in 1998/99 and production increased again to 120,000 tons in 1999/2000 after which it drooped slightly to 113,000 tons in the following year (chart 3.24) Charts 3.23 and 3.25 show that, whilst the yield of paddy has dropped dramatically over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. 3.3.4.3 Other Cereals The third important cereal crop grown in Morogoro region is sorghum (14,830 ha). It is mainly produced in Morogoro rural (7,028 ha), Kilosa (3,224 ha), Mvomero (2,716 ha), Ulanga (903 ha), Kilombero (815 ha) and Morogoro urban (144 ha). Other cereals produced in the region includes bulrush millets (455ha), wheat (238 ha), finger millets (165 ha) and barley (157 ha) (Chart 3.26). 3.35 Pulse Crops Production The total production of pulse crops was 11,595 tonnes. Beans production was higher than any other pulse crop in the region with a total production of 8,617 tonnes representing 74.3 percent of the total pulse crops production. This was followed by cowpeas with 1,948 tonnes (16.8%), field peas (816t, 7.0%), green peas (174t, 1.5%), and the other types represents 40t (0.4%) (Table 3.4a) Chart 3.25 Time Series of Paddy Planted Area and Yield Morogoro 0 40,000 80,000 120,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 1.0 2.0 3.0 Yield (t/ha) Area Yield Chart 3.24 Time Series Data on Paddy Production - Morogoro 120 91 41 103 113 78 102 0 40 80 120 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.27 Area Planted and Yield of Major Pulse Crops 0 15000 30000 45000 60000 75000 Beans Cowpeas Green Gram Field Peas Chich Peas Bambaranuts Mung Beans Crop Area Planted (ha) 0 250 500 750 1,000 Yield (kg/ha) Yield (kg/ha) 0 10000 20000 30000 40000 50000 Area (H a) Kilosa M'goro R Kilombero Ulanga M'goro Urb Mvomero District Chart 3.26 Area Planted with Paddy, Sorghum and Bulrush millet by District Paddy Sorghum Bulrush Millet Chart 3.23 Total Planted Area and Area of Paddy per Household by District 53096 30662 15910 13360 13001 497 0 15000 30000 45000 60000 Kilombero Ulanga Kilosa Mvomero Morogoro Morogoro Urb District Area (Ha) 0.0 0.3 0.6 0.9 1.2 1.5 Area planted per household Area Planted Area Planted/hh Ulanga Kilombero Morogoro Rural Morogoro Urban Mvomero 0.6 0.5 1 0.6 0.6 1 Kilosa 0.9 to 1 0.8 to 0.9 0.7 to 0.8 0.6 to 0.7 0.5 to 0.6 Morogoro Rural Morogoro Urban Kilombero Ulanga Mvomero 32,425ha 72,420ha 22,810ha 16,388ha 48,158ha 0.5t/ha 0.9t/ha 1t/ha 0.5t/ha 0.4t/ha 1.2t/ha Kilosa 2,889ha Planted Area and Yield of Maize by District Planted Area (ha) MAP 3.11 MOROGORO Area Planted Per Household MAP 3.12 MOROGORO Area Planted Per Maize Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) 58,000 to 73,000 44,000 to 58,000 30,000 to 44,000 16,000 to 30,000 2,000 to 16,000 Area Planted Per Household RESULTS 25 Morogoro Rural Morogoro Urban Mvomero Kilombero 0.9 0.6 0.4 0.4 0 0.1 Ulanga Kilosa Morogoro Urban Mvomero Kilosa Morogoro Rural Kilombero 4,769ha 7,004ha 3,880ha 69,406ha 27,764ha 1t/ha 0.8t/ha 1.6t/ha 3.9t/ha 0t/ha 0.1t Ulanga 180ha 40,000 to 70,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area and Yield of Paddy by District MAP 3.13 MOROGORO Area Planted Per Household MAP 3.14 MOROGORO Area Planted per Paddy Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area (ha) 0.8 to 0.9 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household RESULTS 26 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 The area planted with beans was larger than any other pulse crop and it was the most important crop in Morogoro in terms of planted area (5% of the total area planted with annual crops and vegetables) and it accounted for 71.5 percent of the area planted with pulses. The area planted with pulses during the long rainy season was 61% with beans having 70.2 percent of its production in the long rainy season. Other pulse crops were mainly produced during long rainy season with cowpeas 56.2 %, field peas 39.0% (which is mainly grown in short rainy season), green gram 67.8% and bambara nuts 100%. Mung beans and chick peas were grown during the short rainy season. The estimated yield was high for field peas 0.86t/ha, mung beans 0.5t/ha, beans 0.42t/ha, cowpeas 0.32t/ha, green peas .18t/ha, bambaranuts .15t/ha and chick peas 0.11t/ha. 3.3.5.1 Beans The number of households growing beans in the region was 44,718 which represents 17 percent of the total crop growing households in the region. The total production of beans during the census year was 8,617 tons. The area planted with beans increased sharply from 6,363 ha to 25,500 ha over the period 1994 to 1999. Then the area planted with beans dropped to 20,407 in 2003. Mvomero district had the largest planted area of beans (9,422 ha, 46.2% of total area planted area for annual crops in the district), followed by Kilosa (7,813 ha, 38.3%), Ulanga (1,569 ha, 7.7%), Morogoro rural (1,262 ha, 6.2%), Morogoro urban (267 ha, 1.3%), and Kilombero (74 ha, 0.4%). However, the highest proportion of land planted with beans, expressed as a percent of the total land area was in Mvomero district (10.6%). This was followed by Kilosa (6.9%), Morogoro Urban (5.4%), Ulanga (2.9%), Morogoro Rural (1.7%), and Kilombero (0.1%) (Chart 3.29 and Map 3.15). Chart 3.29 Percent of Beans Planted Area and Percent of Total Land with beans by District 46.2 38.3 7.7 6.2 1.3 0.4 0.0 10.0 20.0 30.0 40.0 50.0 Mvomero Kilosa Ulanga M'goro R M'goro U K'mbero District Percent of Total Area Planted 0.0 4.0 8.0 12.0 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 4.28 1.97 0.54 0.36 0.24 0.00 0.0 1.5 3.0 4.5 Area per Household Ulanga Kilosa MvomeroM'goro R M'goro U K'mbero District Chart 3.30 Beans Planted Area per beans Growing Households by District Chart 3.31 Time Series of Beans Planted Area and Yield Morogoro 0 10000 20000 30000 1994/95 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 Yield (t/ha) Area Yield Chart 3.28 Percent of Beans Planted Area by District 0.0 10.0 20.0 30.0 40.0 50.0 Mvomero Kilosa Ulanga M'goro R M'goro U K'mbero District P ercent o f To ta l A rea P la nted Percent of Area Planted Morogoro Urban Morogoro Rural Mvomero Kilosa Kilombero 267ha 1,262ha 9,422ha 7,813ha 74ha 1,569ha 0.4t/ha 1.1t/ha 0.3t/ha 0.5t/ha 0.5t/ha 0.5t/ha Ulanga Mvomero Morogoro Urban Morogoro Rural Kilombero 0.1 0.1 0.4 0.2 0.1 0.2 Ulanga Kilosa Planted Area and Yield of Beans by District MAP 3.15 MOROGORO Area Planted Per Household MAP 3.16 MOROGORO Area Planted per Beans Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) Yield (t/ha) 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 0.34 to 0.4 0.28 to 0.34 0.22 to 0.28 0.16 to 0.22 0.1 to 0.16 Area Planted Per Household RESULTS 28 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 29 The average planted area of beans was 0.5 hectares per beans growing household. However, there were large district variations. The area planted per beans growing household was greatest in Ulanga (4.3 ha). This was followed by Kilosa (2.0 ha), Mvomero (0.5 ha), Morogoro Rural (0.4 ha), and Morogoro Urban (0.2 ha), (Chart 3.30) (Map 3.16). 3.3.5.2 Cow peas The number of households growing cow peas in Morogoro Region during the long rainy season was 13,446. This was 29 percent of the total pulse crops growing households during the long rainy season. The total production of cow peas during the census year was 1,948 tonnes. Cow peas is grown in all the districts of Morogoro region, the district with the highest planted area was Morogoro Rural with (1,953 ha, 32%), followed by Mvomero (1,464 ha, 24%), Kilosa (1,298 ha, 21%), Ulanga (719 ha, 12%), Kilombero (397 ha, 7%) and Morogoro Urban 253 ha, 4%)(Map 3.17,3.18) 3.3.6 Root and Tuber Crops The total area planted with roots and tuber crop was 22,301 hectares out of which 17,174 ha were planted with cassava, this was 77 percent of the total area planted with cassava, followed by sweet potatoes 2,950 ha (13%), coco yam 1,367 ha (6%), Irish potatoes 733 ha (3%) and yams 77 ha (0.2%). The area planted with root and tuber in the short rainy season was 2,179 ha which represented (10%) of total area planted with roots and tuber during the year. Cassava was the most dominant crop during long rainy season at 16,644 ha which represented 83 percent of the total area planted with roots and tubers in that particular season, followed by sweet potatoes 2,514 ha (12%), Irish potatoes 669 ha (3%) and cocoyam 269 ha (1%). The total production of roots and tubers was 31,152 tonnes. Cassava was the most cultivated crop producing 23,625 tonnes which accounted for 76 percent of the total roots and tubers production. This was followed by sweet potatoes 4,883 tons (16%), yams 1,598 tonnes (5%), Irish potatoes 724 tonnes (2%), and cocoyam 322 tonnes (1%) (Table 3.4b). Yams and sweet potatoes had relatively higher yields of 4,200 and 1,700 kgs/ha respectively. The yields of the rest of the roots and tubers in kilograms per hectare were cassava1400, cocoyams 1200 and Irish potatoes 1000. Table 3.4a : Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Mung Beans 49 24 0.5 0 0 0.0 49 24 0.5 Beans 7047 2568 0.4 13360 6050 0.5 20407 8617 0.4 Cowpeas 2987 853 0.3 3096 1095 0.4 6083 1948 0.3 Green Gram 513 56 0.1 441 118 0.3 954 174 0.2 Chich Peas 65 8 0.1 0 0 0.0 65 8 0.1 Bambaranuts 0 0 0.0 52 8 0.2 52 8 0.2 Field Peas 411 497 1.2 535 318 0.6 947 816 0.9 Total 11073 4006 0.4 17483 7589 0.4 28556 11595 0.4 Table 3.4b: Area, Quantity Harvested and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Cassava 530 667 1.3 16,644 22,958 1.4 17,174 23,625 Sweet Potatoes 436 705 1.6 2,514 4,178 1.7 2,950 4,883 Irish Potatoes 63 263 4.1 669 461 0.7 733 724 Yams 52 261 5.0 24 60 2.5 77 322 Cocoyam 1,098 785 0.7 269 813 3.0 1,367 1,598 Total 2,179 2,681 20,122 28,471 22,301 31,152 Morogoro Rural Morogoro Urban Mvomero Kilombero 0.1 0 0.1 0.1 0.2 Ulanga Kilosa 0.1 Morogoro Urban Mvomero Morogoro Rural Kilosa Kilombero 1,464ha 1,953ha 1,298ha 397ha 719ha 0.2t/ha 0.3t/ha 0.3t/ha 0.2t/ha 0.5t/ha 0.8t/ha Ulanga 253ha 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Planted Area and Yield of Cowpeas by District MAP 3.17 MOROGORO Area Planted Per Household MAP 3.18 MOROGORO Area Planted per Cowpeas Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area (ha) 1,800 to 2,000 1,400 to 1,800 1,000 to 1,400 600 to 1,000 200 to 600 Area Planted Per Household RESULTS 30 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 3.3.6.1 Cassava The largest area planted with cassava in the region (5,564ha, 32%) was located in Morogoro Rural District and the largest area planted with cassava per household was in Mvomero District (0.91 ha). The average area planted per household in the region during the long rainy season was 0.42 ha. With exception of Kilosa and Morogoro Rural, the variations in area planted with cassava for the rest of the districts were small ranging from 0.24 ha in Ulanga, Kilombero 0.28ha and Morogoro Urban 0.31ha. (Chart 3.33 and Map 3.20) 3.3.7 Oil Seed Production In Morogoro Region the area planted with oil seeds and nuts was 2,735 hectares. Simsim was the most common oil seeds and nuts crop grown with 9,521 ha. This area represented 75 percent of the total area planted with oil seeds and nuts, followed by groundnuts (20%), sunflower (4%), castor seed and soyabeans each with (1%). The area planted in short rainy season was 2,477 ha which represented (19%) of the total area planted with oil seeds and nuts. More than fifty percent of the simsim was cultivated during the long rainy season. The area planted with this crop at 7,362 ha represented 72 percent of the total area planted with oil seeds and nuts in the long rainy season, followed by groundnuts (22%) and sunflower (5%), castor seeds and soyabeans each with (1%). (Table 3.5) The yield was relatively high for castor seeds (900 kg/ha) followed by groundnuts (500 kg/ha), simsim (290 kg /ha), sunflower (270 kg/ha) and soyabeans (210 kg/ha) (Chart 3.34) Table 3.5: Area, Quantity Harvested and Yield of Oilseed Crop by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Sunflower 0 0 0.0 495 133 0.3 495 133 0.27 Simsim 2159 582 0.3 7362 2170 0.3 9521 2752 0.29 Groundnuts 307 168 0.5 2219 984 0.4 2527 1152 0.46 Soya Beans 11 2 0.2 54 12 0.2 65 14 0.21 Castor Seed 0 0 0.0 128 116 0.9 128 116 0.91 Total 2477 751 0.3 10258 3415 0.3 12735 4167 0.33 Chart 3.32 Percent of Cassava Planted Area and Percent of Total Land with Cassava byDistrict 31 29 14 11 9 3 0 5 10 15 20 25 30 35 M'goro R Mvomero Kilosa Kilombero Ulanga M'goro U District Percent of Total Area Planted 0.0 2.0 4.0 6.0 8.0 10.0 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.91 0.42 0.38 0.31 0.28 0.24 0.00 0.40 0.80 1.20 Area per Household Mvomero Kilosa Moro R Moro UK'mbero Ulanga District Chart 3.33 Cassava Planted Area per Cassava Growing Households by District Chart 3.34 Area Planted and Yield of Major Oil Seed Crops 0 2,500 5,000 7,500 10,000 Simsim Groundnut Sunflower Castor Seed Soya Beans Crop Area Planted (ha) 0 200 400 600 800 1000 Yield (kg/ha) Yield Morogoro Urban Mvomero Morogoro Rural Kilombero 4,973ha 5,564ha 2,483ha 2,174ha 1,534ha 0.5t/ha 2.3t/ha 1.3t/ha 1t/ha 3.9t/ha 1.3t/ha Ulanga Kilosa 446ha Mvomero Morogoro Urban Morogoro Rural Kilombero 0.5 0.7 0.5 0.4 1.1 0.3 Ulanga Kilosa 1.1 to 1.1 0.9 to 1.1 0.7 to 0.9 0.5 to 0.7 0.3 to 0.5 Planted Area and Yield of Cassava by District MAP 3.19 MOROGORO Area Planted Per Household MAP 3.20 MOROGORO Area Planted per Cassava Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) Yield (t/ha) 4,000 to 6,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted Per Household RESULTS 32 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 33 The total production of oil seeds and nuts was 4,167 tons. Out of which simsim were dominant at 2,752 accounted for 66 percent of the total production of oil seeds and nuts followed by groundnuts (28%), sunflower (3.2%), castor seed (2.8%) and soyabeans (0.3). 3.3.7.1 Simsim The number of household growing simsim in Morogoro region was 16,162 ha. The total production of simsim in the region was 2,170 tonnes from a planted area of 7,362 hectares resulting in a yield of 0.3 t/ha. More than fourty nine percent of the area planted with simsim was located in Morogoro Rural District (4,712 ha) followed by Kilosa (4,223 ha’ 44.45), Ulanga (312 ha, 3.2%), Mvomero (222 ha, 2.3%), Morogoro Urban (37.5 ha, 0.4%) and Kilombero (13 ha, 0.1%) (Chart 3.35 and Map 3.21) The largest area planted per simsim growing household was found in Morogoro Urban district (0.58 ha) and the lowest was Kilombero ( 0.1 ha) The range between the district with the highest and lowest area planted per household depicts small variations in area planted among the districts ( Chart 3.36 and Map 3.22) 3.3. 8 Fruits and Vegetables The collection of fruits and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from perennial crops and only water melon is reported as an annual crop in this section. The long rainy season is relatively important for fruits and vegetables production since 58% of the total area planted with fruits and vegetables was during the long rainy season. For onions, cabbage, amaranths and pumpkins over 60 percent of the planted area for each crop was during the long rainy season. The planted area for carrot in the short rainy season was over 90 percent of the total planted area during the survey year. Reliable historical data for time series analysis of fruits and vegetables were not available. 0.58 0.48 0.47 0.42 0.39 0.10 0.00 0.25 0.50 0.75 Area per Household M'goro U M'goro R Mvomero Kilosa Ulanga K'mbero District Chart 3.36 Area Planted per Simsim Growing Household by District (Long Rainy Season Only) Chart 3.35 Percent of Simsim Planted Area and Percent of Total Land with Simsim by District 0 20 40 60 M'goro R Kilosa Ulanga Mvomero M'goro U Kilombero District Percent of Land 0 10 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.37 Area Planted and Yield of Fruit and Vegetables 0 2000 4000 6000 8000 Tomatoes Cabbage Onions Pumpkins Chillies Amaranths Carrot Others Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 6,000 Yield (kg/ha) Yield (kg/ha) Morogoro Urban Morogoro Rural Mvomero Kilombero 38ha 222ha 4,712ha 4,223ha 13ha 313ha 0.2% 0.3% 0.3% 0.3% 0.3% 0.3% Ulanga Kilosa Planted Area and Yield of Simsim by District MAP 3.21 MOROGORO Mvomero Morogoro Urban Morogoro Rural Kilombero 0.1 0.1 0.1 0.1 0 0.1 Ulanga Kilosa 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted Per Household MAP 3.22 MOROGORO Area Planted per Sim sim Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) Yield (t/ha) 0.08 to 0.1 0.06 to 0.08 0.04 to 0.06 0.02 to 0.04 0 to 0.02 Area Planted Per Household RESULTS 34 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 The total production of fruits and vegetables was 42,229 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production estimate for this crop was 21,747 tons which is equivalent to (51%) of the total fruits and vegetables produced, followed by cabbage 10,374 tons (25%) and onions 4,686 tons (11%), pumpkins 1,877 tons (4%), chillies 973 tons (2%) and amaranths 849 tons (2%). The production of other fruits and vegetables crops was relatively small ( Table 3.6) Cabbage had the highest yield of 5,492 kg/ha followed by onions 4,854 kg/ha, tomatoes (3,531kg/ha), cucumber (1,981 kg/ha) and chillies (1,828 kg/ha). Okra and water melon had the lowest yields of 603 and 612 kg/ha respectively (Chart 3.37) 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 11,777 and 7,972 households in the short rainy season. This represented 2.8 percent of the total crop growing households in the region during the long rainy season and 1.2 percent during the short rainy season. Mvomero district had the largest planted area of tomatoes (51.2% of the total area planted with tomatoes in the region), followed by Kilosa (20.8%), Morogoro Rural (19.7%), Kilombero (4.4%), Ulanga (2.4%) and Morogoro Urban (1.5%). The highest percentage of land with tomatoes was found in Mvomero followed by Morogoro Urban, Morogoro rural and Kilosa. The remaining districts have relatively low percentage of land used for tomato production (Chart 3.38 and Map 3.23). The largest area planted per household was found in Mvomero district (0.4 ha) followed by Kilosa (0.30 ha), MorogoroRural (0.27 ha), Kilombero (0.22 ha), Ulanga (0.19 ha) and Morogoro Urban (0.13 ha) (Chart 3.39 and Map 3.24). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Plante d (ha) Quantity Harvested (tonnes) Yield kg/ha) Area in (ha) Quantity harvested (tonnes) Yield (kg/ha) Area in (ha) Quantity harvested (tonnes) Yield (kg/ha) Okra 68 3 50 96 96 993 164 99 603 Bitter Aubergine 44 97 2,208 49 47 969 93 145 1,557 Onions 305 1057 3,462 660 3630 5,499 965 4687 4,854 Cabbage 667 3965 5,943 1222 6409 5,246 1889 10374 5,492 Tomatoes 2685 9700 3,612 3474 12047 3,468 6159 21747 3,531 Spinnach 96 156 1,628 88 191 2,163 184 347 1,884 Carrot 448 491 1,096 30 34 1,142 478 525 1,099 Chillies 278 443 1,595 255 530 2,081 533 973 1,828 Amaranths 90 273 3,029 367 577 1,571 457 849 1,858 Pumpkins 237 282 1,188 710 1595 2,246 947 1877 1,981 Cucumber 91 279 3,078 61 33 541 152 312 2,058 Egg Plant 75 84 1,123 80 68 861 154 153 988 Water Mellon 99 54 545 51 38 741 151 92 612 Cauliflower 49 24 494 25 24 988 74 48 659 Total 5232 16909 7167 25320 12400 42229 Chart 3.38 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Mvomero Kilosa Morogoro Kilombero Ulanga Morogoro Urb District Percent of Land 0.0 1.0 2.0 3.0 4.0 Percent Area Planted of Total Land Area Percent of Land Proportional of Land 0.00 0.10 0.20 0.30 0.40 0.50 Area per Household (ha) Mvomero Kilosa Morogoro Rural Kilombero Ulanga Morogoro Urban District Chart 3.39 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) Mvomero Morogoro Urban Morogoro Rural Kilombero 3,154ha 95ha 1,214ha 1,278ha 271ha 147ha 3.5t/has 2.9t/ha 3.7t/ha 3.2t/ha 4.3t/ha 5.1t/ha Ulanga Kilosa Morogoro Rural Morogoro Urban Mvomero Kilombero 1.1 0.6 1.4 0.8 1 0.7 Ulanga Kilosa Planted Area and Yield of Tomatoes by District MAP 3.23 MOROGORO Area Planted Per Household MAP 3.24 MOROGORO Area Planted per Tomato Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area (ha) 2,400 to 3,200 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 1.24 to 1.4 1.08 to 1.24 0.92 to 1.08 0.76 to 0.92 0.6 to 0.76 Area Planted Per Household RESULTS 36 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 The total area planted with tomatoes accounted for 1.5 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.2 Cabbage The number of households growing cabbages in the region during the long rainy season was 3,588 and 1,883 in the short rainy season .This represented 0.56 percent of the total crop growing households in the region in the long rainy season and 0.29 percent in the short rainy season. Mvomero district had the largest planted area of cabbage (1,371 ha, 72.6% of the total area planted with cabbage in the region), followed by Kilosa (237 ha, 12.5%), Morogoro Rural (133 ha, 7.1%), Ulanga (91 ha, 4.8%), Morogoro Urban (38 ha, 2.0%) and Kilombero (19 ha, 1.0%) districts (Chart 3.40). The total area planted with cabbages accounted for 0.3 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Carrots The number of households growing carrots in the region during the long rainy season was 160 households and 623 in the short rainy season .This represented 0.02 percent of the total crop growing households in the region in the long rainy season and 010 percent in the short rainy season. Mvomero district had the largest planted area of carrots (398 ha, 83.2% of the total area planted with carrots in the region), followed by Morogoro Rural (74 ha, 15.6%), Morogoro Urban (5 ha, 1.1%). Other districts of Kilosa, Kilombero and Ulanga reported no carrot production (Chart 3.41) The largest proportion of the area planted with carrots was found in Mvomero district (0.45%), followed by Morogoro Urban (0.11%), Morogoro Rural (0.1%), the remaining districts of Kilosa, Kilombero and Ulanga reported no area planted with carrots. The total area planted with carrots accounted for 0.07 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Chart 3.40 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 20.0 40.0 60.0 80.0 Mvomero Kilosa M'goro R Ulanga M'goro U Kilombero District Percent of Land 0.000 0.004 0.008 0.012 0.016 0.020 Percent Area Planted of Total Land Area Percent of Area Planted Propotion of land Chart 3.41 Percent of Carrots Planted Area and Percent of Total Land with Carrots by District 0 25 50 75 100 Mvomero M,goro R M'goro U Kilosa Kilombero Ulanga District Percent of Land 0 0.002 0.004 0.006 Percent Area Planted of Total Land Area Percent of Area Planted Propotion of land DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 38 3.3.9 Other Annual Crops Production Most of the other annual crops can be defined as cash crops, however it is difficult to distinguish between cash crops and other crops given that many of the food crops are also used for generating income. During the 2002/03 agriculture year an area of 698 ha was planted with other crops and of this cotton was the most prominent followed by tobacco. The area planted with annual cash crops in short rainy season was 16 ha which represented 2.3 percent of the total area planted with other annual cash crops in short and long rainy season. 3.3.9.1 Cotton The quantity of cotton produced was 248 tonnes. Cotton had a planted area of 620 ha and it was produced during the long rainy season only (Chart 3.42). The crop is mainly grown in Kilosa, Ulanga and Mvomero districts. 3.3.9.2 Tobacco The quantity of tobacco produced was 38 tonnes. Tobacco had a planted area of 78 ha, most of which was planted in the long rainy season. Tobacco production is concentrated in 2 districts with Morogoro Rural having the largest area planted with this crop (79%) and Ulanga (21%) (Chart 3.43) 3.4 Perennial Crops Perennial crops (sometimes referred as permanent crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops it is easy to determine if they are annual or perennial. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census cassava was treated as an annual crop. Bananas normally take less than a year to mature and produce a harvest and survive for more than one year. In the census bananas are treated as perennial crops. In this report the agriculture census results are presented for the most important perennial crop in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for perennials, therefore no time series data in this section. Chart 3.43 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0 40 80 120 M'goro R Ulanga Kilosa K'mbero M'goro UMvomero District Percent of Land 0.0000 0.0002 0.0004 0.0006 Percent Area Planted of Total Land Area Percent of Area Planted Propotion of land Chart 3.42 Area planted with Annual Cash Crops Tobacco, 78 ha, 11% Cotton, 620 ha, 89% Chart 3.44 Area Planted for Annual and Permanent Crops Permanent Crops, 50712 ha, 11% Annual Crops, 414151 ha, 89% Annual Crops Permanent Crops Morogoro Rural Morogoro Urban Mvomero Kilombero Ulanga 1 1 1 1 Kilosa 0 0 Morogoro Urban Mvomero Morogoro Rural Kilombero 2,375ha 346ha 2,588ha 2,596ha 835ha 30% 11.7% 8.5% 19.1% 29.1% 35.6% Ulanga Kilosa 255ha Tanzania Agriculture Sample Census Planted Area and Yield of Sugarcane by District Planted Area (ha) MAP 3.25 MOROGORO Area Planted Per Household MAP 3.26 MOROGORO Area Planted Per Sugarcane Growing Household by District 2,200 to 2,600 1,700 to 2,200 1,200 to 1,700 700 to 1,200 200 to 700 Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household RESULTS 39 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 The area of smallholders planted with perennial crops was estimated at 50,712 hectares equivalent to 11 percent of the area planted with annual and perennial crops in the region. The most important perennial crop is bananas which accounts for 19% of the total area planted with perennial crops followed by sugar canes (16%), coconuts (15%) and mango (10.5%) (Chart 3.45). However, the area planted with annual crops is not the actual physical land area as it includes the area planted more than once on the same land, whilst for the planted area for perennial crops is the same as physical planted land area. So the percentage physical area planted with perennial crops would be higher than indicated in Chart 3.44 Bananas had the highest smallholder planted area (9,396 ha, 19%) of all permanent crops followed by sugarcane (8,330 ha, 16%), coconut (7,550 ha, 15%), mango (5,302 ha, 10.5%) and orange 4,549 ha, 9%). Each of the remaining permanent crops had an area of less than 5% of the total area planted with permanent crops. Morogoro Rural district had the largest area under smallholder permanent crops (17,368 ha, 34%). This is followed by Mvomero (13,773 ha, 27%), Kilosa (9,604 ha, 19%), Kilombero (6,360 ha, 12), Ulanga (2,125 ha, 4%) and Morogoro Urban (1,749 ha, 3%). In terms of area of permanent crops planted per household Ulanga had the largest area (0.50 ha) followed by Mvomero (0.28 ha), Morogoro Rural (0.25 ha), Morogoro Urban (0.24 ha), Kilombero (0.22 ha) and Kilosa (0.18% ha). However, in terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Morogoro Urban had the highest (26%) followed by Morogoro Rural (19%), Mvomero (13%), Kilosa (8%), Kilombero (7%) and Ulanga (4%) (Chart 3.46) Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Area in Hectare Quantity harvested (tons) Yield (t/ha) Cotton 0 0 0.0 620 248 0.4 620 248 0.4 Tobacco 16 2 0.1 62 35 0.6 78 38 0.5 Total 16 2 0.1 682 283 0.4 698 285 0.4 Chart 3.46 Percent of Area Planted and Average Planted Area with Permanent Crops by District 27 19 12 4 3 34 0 10 20 30 40 50 Morogoro Mvomero Kilosa Kilombero Ulanga Morogoro Urb District % of Total Area Planted 0.0 0.2 0.4 0.6 Average planted area per household Percent of Total Area Planted Average planted area/hh Chart 3.45 Area Planted (ha) with Main Perennial Crops Other, 11528, 24% Coconut, 7550, 15% Orange, 4549, 9% Banana, 9396, 19% Cashewnut, 570, 1% Mango, 5,302, 10.5% Coffee, 373, 1% Cardamon, 243, 0% Pigeon Pea, 2113, 4% Sugarcane, 8330, 16% Palm oil 758, 1.5% Coconut Orange Banana Cashewnut Mango Coffee Cardamon Pigeon Pea Sugarcane Palm oil Other DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 3.4.1 Banana The total production of bananas by smallholders was 47,415 tonnes. In terms of area planted, banana was the most important permanent crop grown by smallholders in the region. It was grown by 30,480 households (22% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.3 ha per banana growing household and the average yield obtained by smallholders was 5310 kg /ha from a harvest area of 8,928 hectares. Morogoro Rural had the largest area of banana in the region (2,722 ha, 29%) followed by Kilosa (1,961 ha, 21%), Kilombero (1,330 ha, 14%), Mvomero (1,256 ha, 13%), Morogoro Urban (1,177 ha, 13 and Ulanga (950 ha, 10%). The average area planted with banana per banana planting household was highest in Morogoro Urban (0.63 ha) followed by Morogoro Rural (0.32 ha), Kilombero (0.31 ha), Mvomero (0.30 ha), Ulanga (0.27 ha) and Kilosa (0.24 ha) (Chart 3.47) 3.4.2 Sugarcane The total production of sugarcane by smallholders was 213,556 tonnes. In terms of area planted, sugarcane was the second most important permanent crop grown by smallholders in the region. It was grown by 9,463 households (6.9% of the total crop growing households). The average area planted with sugarcane per household was 0.9 ha per sugarcane growing household and the average yield obtained by smallholders was 28,798 kg /ha from a harvest area of 7,416 hectares.(Map 3.25) Mvomero had the largest area of sugarcane in the region (2,795 ha, 33.6%) followed by Kilosa (2,588 ha, 31.1%), Kilombero (2,573 ha, 30.9%), Morogoro Rural (199 ha, 2.4%), Ulanga (118 ha, 1.4%) and Morogoro Urban (56 ha, 0.7%). However, the average area planted with sugarcane per sugarcane planting household was highest in Mvomero (1.2 ha) followed by Kilombero (1.0 ha), Kilosa (0.8 ha), Morogoro Rural (0.6 ha), Morogoro Urban (0.2 ha) and Ulanga (0.1 ha) (Chart 3.48 and Map 3.26) 3.4.3 Coconut The total production of coconut by smallholders was 7,550 tonnes. In terms of area planted, coconut was the third most important permanent crop grown by smallholders in the region. It was grown by 23,954 households (17% of the total crop growing households). The average area planted with coconut per household was relatively small at around 0.32 ha per coconut Chart 3.47 Percent of Area Planted with banana and Average Planted Area per Household by District 10.1 20.9 13.4 29.0 12.5 14.2 0.0 10.0 20.0 30.0 40.0 Moro R Kilosa K'mberoMvomeroMoro U Ulanga District % of Total Area Planted 0.00 0.10 0.20 0.30 Average planted area per household % of total area planted Average planted Area per household Chart 3.49 Percent of Area Planted withCoconut and Average Planted Area per Household by District 0.4 6.6 3.3 67.4 3.9 18.5 0.0 20.0 40.0 60.0 80.0 Moro R Kilosa Mvomero K'mbero Ulanga Moro U District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average planted area per household % of total area planted Average planted Area per household Chart 3.48 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District 56 2588 199 2795 118 2573 0 1000 2000 3000 Mvomero Kilosa K'mbero Moro R Ulanga Moro U District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average planted area per household Planted Area (ha) Average planted Area per household Morogoro Rural Morogoro Urban Mvomero Kilombero 0.2 0.1 0 0.2 0.2 0.1 Ulanga Kilosa Morogoro Rural Morogoro Urban Kilombero Mvomero 889ha 64ha 615ha 319ha 1,433ha 1,983ha 6.6% 3.6% 56.5% 8.9% 2.2% 3% Ulanga Kilosa Tanzania Agriculture Sample Census Planted Area and Yield of Mango by District Planted Area (ha) MAP 3.27 MOROGORO Area Planted Per Household MAP 3.28 MOROGORO Area Planted per Mango Growing Household by District 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Planted Area (ha) Yield (t/ha) 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Area Planted Per Household RESULTS 42 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 43 growing household and the average yield obtained by smallholders was 6,534 kg /ha from a harvested area of 2,749 hectares. Morogoro Rural had the largest area of coconut in the region (5,086 ha, 67%) followed by Kilosa (1,397 ha, 19%), Mvomero (498 ha, 7%), Kilombero (296 ha, 4%), Ulanga (246 ha, 3%), Morogoro Urban (27 ha, 0.4%). However, the area planted with coconut per coconut growing household was highest in Morogoro Rural (0.46 ha), followed by Kilosa (0.34 ha), Mvomero (0.15 ha), Morogoro Urban (0.15 ha), Ulanga (0.13 ha) and Kilombero (0.09 ha) (Chart 3.49). 3.4.4 Mango The total production of Cashew nuts by smallholders was 49,490 tonnes. In terms of area planted, mango was the fourth most important permanent crop grown by smallholders in the region. It was grown by 21,979 households (16% of the total crop growing households). The average area planted with mango per household was relatively small at around 0.24 ha per mango growing household and the average yield obtained by smallholders was 19713 kg /ha from a harvest area of 2,511 hectares.(Map 3.27) Mvomero has the largest area of mango in the region (1,983 ha, 37%) followed by Kilosa (1,433 ha, 27%), Morogor Rural (889 ha, 17%), Kilombero (615 ha, 12%), Ulanga (319 ha, 6%) and Morogoro Urban (64 ha, 1%). However, the average area planted per mango planting household was highest in Mvomero (0.40 ha), followed by Kilosa (0.24 ha), Morogor Rural (0.20 ha), Kilombero (0.17 ha), Ulanga (0.13 ha) and Morogoro Urban (0.11 ha) (Chart 3.50 and Map 3.28) Chart 3.50 Percent of Area Planted with Mango and Average Planted Area per Household by District 1 27 12 37 6 17 0 10 20 30 40 Mvomero Kilosa Moro R Kilombero Ulanga Moro U District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average planted area per household % of total area planted Average planted Area per household DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 44 3.5 Inputs/Implements Use 3.5.1 Methods of land clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetati on growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 99,288 ha which represented 74.8 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 5.9, 4.6 and 0.3 percent respectively (Table3.8). 3.5.2 Methods of soil preparation Hand cultivation is mostly used for soil preparation as it has been used in an area of 310,153 ha which represented 78 percent of the total planted area, followed by tractor ploughing (52,551, 13%) and ox-ploughing (35,957, 9%). Hand cultivation is mostly used in short rainy season where (81%) of the area used this method for soil preparation compared to (76%) for the long rainy season. Tractor ploughing is mostly used in long rainy season (Chart 3.52). Hand cultivation was mostly used during short rainy season at 81% against 76% for the long rainy season. Tractor ploughing is mostly used in long rainy season with 15% against 8% oxen ploughing while during short rain season oxen ploughing is the most applied method with 11% against tractor ploughing 8%. Table 3.8: Land Clearing Methods Short Rainy Season Long Rainy Season Total Crop Number of Households Area Planted (ha) % Number of Households Area Planted (ha) % Number of Households Area Planted (ha) % Mostly Hand Slashing 167653 197671 73.1 169 99288 77.9 167822 296959 74.6 No Land Clearing 29703 43184 16.0 18675 13228 10.4 48378 56412 14.2 Mostly Bush Clearing 13584 16154 6.0 12844 8046 6.3 26428 24200 6.1 Mostly Burning 12048 12569 4.6 8553 5655 4.4 20601 18224 4.6 Mostly Tractor Slashing 551 442 0.2 849 727 0.6 1400 1169 0.3 Other 242 342 0.1 576 577 0.5 818 919 0.2 223781 270362 100.0 41666 127521 100.0 265447 397883 100.0 0 30000 60000 90000 120000 Area Cultivated Kilosa Morogoro Urban Mvomero Morogoro Rural Kilombero Ulanga District Chart 3.53 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Hoe Ploughing Mostly Tractor Ploughing Chart 3.51 Number of Households by Method of Land Clearing during the Long Rainy Season 304380 49059 22324 16028 932 487 0 100000 200000 300000 400000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.52 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 52551, 13% Mostly Hand hoe ploughing, 310153, 78% Mostly Oxen Ploughing, 35957, 9% Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand hoe ploughing Mvomero Morogoro Urban Morogoro Rural Kilombero 0 3,463 2,897 471 1,036 0% 43.6% 1% 36.5% 5.9% 13% Ulanga Kilosa 77 Morogoro Urban Mvomero Morogoro Rural Kilosa Kilombero 3,760 1,172 4,971 1,589 230 1.5% 31.6% 9.8% 41.8% 13.4% 1.9% Ulanga 178 Planted Area and Percent of Total Planted Area With Farm Yard Manure Application by District Planted Area With Farm Yard Manure Applied MAP 3.29 MOROGORO MAP 3.30 MOROGORO Planted Area and Percent of Total Planted Area With Compost Manure Application by District 4,000 to 4,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Planted Area With Compost Manure Applied Planted Area With Farm Yard Manure Aplied Percent of Area Planted With Farm Manure Aplied Planted Area With Composite Manure Aplied Percent of Area Planted With Compost Manure Aplied RESULTS 45 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 Though ox-ploughing is the most recommended tillage method for the Tanzanian small holder farmers in Morogoro region tractor ploughing is commonly used than oxen ploughing. Kilombero district is leading in practicing this technology having cultivated 17,246 (33%) hectares followed by Mvomero 13,535 (26%) hectares, Kilosa 11,541 (22%), Ulanga 7,543 (14%) hectares, Morogoro Rural 2,343 (4%) hectares and Morogoro Urban 340 (1%) hectares. During the long rainy season, 82.5 percent of the total area cultivated by using oxen was planted with cereals followed by oil seed 9.5percent, pulses 3.9 percent, fruits and vegetables 1.9 percent, roots and tuber 1.7 percent and cash crops 0.6 percent. 3.5.3 Improved seeds use The planted area using improved seeds was estimated at 55,330 ha which represents 14% of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the long rainy season at (14.1%) was slightly higher than the corresponding percentage use for the short rainy season (13.6%). Cereals had the largest planted area with improved seeds (44,355 ha, 80.2%) followed by fruit and vegetables (7,390 ha, 13.4%), pulses (2,087 ha, 3.8%), oilseed and oil nuts (800 ha, 1.4%), Cash crops (441 ha, 0.8%) and roots and tubers (257 ha, 0.5%) (chart 3.54). However the use of improved seed in cash crops and fruits and vegetables is much greater than in other crop types (63% and 60% respectively), only 4% of the planted area for roots and tubers used improved seed (Chart 3.55b). Chart 3.54 Planted Area with Improved Seed by Crop Type Roots & Tubers, 257, 0% Pulses, 8748, 17% Oilseeds , 800, 1% Fruits & Vegetables, 7390, 13% Cereals, 44355, 81% Cash Crops, 441, 1% Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops 0 15 30 45 60 Percent of Planted Area Cash Crops Fruits & Vegetables Cereals Pulses Oilseeds Roots & Tubers Crop Type Chart 3.55a Percentage of Crop Type Planted Area with Improved Seed - Annuals Chart 3.55b Planted Area of Improved Seeds - Morogoro Without Improved Seeds, 343,331, 86% With Improved Seeds, 55,330, 14% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 47 3.5.4 Fertilizers use Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 112,856 hectares representing 89 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertilizer was applied to 13,038 ha which represented 5 percent of the total planted area or 44 percent of the area planted with fertiliser application. This was followed by farm yard manure (10,901 ha, 4%). Compost fertilizers were used on a very small area and represented only 2 percent of the area planted with fertilizers (Chart 3.56) The highest percentage of the area planted that was applied with fertilizer (all types) was in Mvomero District (69%) followed by Kilombero (17%), Morogoro Rural (11%), Kilosa (4%), Ulanga (3%) and Morogoro Urban (1%) (Chart 3.57). Fertilizer application rate was highest in cereals in which 54 percent of the area planted with these crops during the long rainy season was applied with various types of fertilizers. The second highest rate of fertilizer application was in fruits and vegetables (35%) followed by pulses (7%), cereals (4%) and oil seeds/nuts (0.3%). There was no fertilizer application in cash crop. Table 3.9b Number of Crop Growing Households and Planted Area by Fertilizer Use and District - Long Rain Season The highest rate of using inorganic fertilizers among the various types of crops was in regard to cereals (49%) and lowest was in pulses (2.7%). There was no inorganic fertilizer application in oil seed/nuts, cash crops and roots and tubers. Most annual crop growing household do not use any fertilizer (approximately 209,946 Household, 91% (Map>>). The percentage of the planted area with applied fertilizer was highest for cereals (76% of the planted with these fruit and vegetable during the long rainy Season had an application of fertilizers). This was followed fruit and vegetables (17.6%), pulses (4.9%), roots and tubers (1.2%) and oil seeds (0.2%). There was no ferliser application in cash crops (Table 3.9b) Table 3.9a Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Kilosa 5863 733 2492 9088 102444 Moro Rural 775 1850 161 2786 64534 Kilombero 2976 1096 3618 7691 71222 Ulanga 740 142 680 1562 51051 Moro Urban 254 102 201 558 3941 Mvomero 4439 3317 7955 15711 68073 Total 15048 7240 15108 37396 361265 Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilosa 4384 5068 341 470 2281 5918 61960 87444 68966 98900 Morogoro 122 50 1082 835 103 42 44052 45290 45360 46217 Kilombero 497 1051 459 789 1895 2453 41799 51558 44649 55851 Ulanga 230 222 0 . 227 515 26113 32230 26571 32967 Morogoro Urb 126 166 64 81 209 144 3895 3593 4293 3984 Mvomero 2121 2569 1858 1986 3869 4376 32127 39697 39975 48628 Total 7480 9126 3803 4161 8584 13448 209946 259812 229814 286546 Chart 3.56 Area of Fertilizer Application by Type of Fertilizer No Fertilizer Applied, 225712, 89% Mostly Compost, 5557, 2% Mostly Inorganic Fertilizers, 13038, 5% Mostly Farm Yard Manure, 10901, 4% Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizers No Fertilizer Applied 0 30000 60000 90000 Area (ha) Mvomero Kilombero Ulanga Kilosa Moro U Moro R District Chart 3.57 Area of Fertilizer Application by Type of Fertilizer and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizers Mostly Farm Yard Manure Morogoro Urban Morogoro Rural Kilosa Kilombero Mvomero 67,321 111,532 78,913 52,613 83,784 3.2% 1.8% 5.5% 2% 1.7% 9% Ulanga 4,499 Kilombero Morogoro Rural Morogoro Urban Mvomero 67,321 78,913 111,532 52,613 83,784 96% 90% 88% 92% 97% 81% Ulanga Kilosa 4,499 Tanzania Agriculture Sample Census Planted Area and Percent of Planted Area With No Application of Fertilizer by District Planted Area Area With No Fertilizer Applied MAP 3.31 MOROGORO Planted Area With Irrigation MAP 3.32 MOROGORO Area Planted and Percent of Total Planted Area With Irrigation by District 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 110,000 to 120,000 110,000 to 110,000 80,000 to 110,000 70,000 to 80,000 0 to 70,000 Planted Area With No Application of Fertilizer Percent of Planted Area With No Application of Fertilizer Area Planted With Irrigation Percent of Total Planted Area Wth Irrigation RESULTS 48 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 3.5.4.1 Farm yard manure use The number of households that applied farm yard manure in their annual crops during the long rainy season was 7,480 and it was applied to 9,126 ha representing 3% of the total area planted during that season (Table 3.9). The largest proportion of area applied with farm yard manure was on pulses (78%), followed by cereals (37%), fruits and vegetables (33%), roots and tubers (27%) and oil seeds (21%). In the region farm yard manure was not applied in cash crops. However, the largest area applied with farm yard manure was found in cereals (6,750 ha, 75%) followed by fruits and vegetables (1,205 ha, 13%), pulses (1,000 ha, 11%), the use farm yard manure in oil seeds and cash crops was negligible (Chart 3.58 and 3.59a and Map 3.29) Farm yard manure is mostly used in Kilombero (8.0% of the total planted area in the district), followed by Mvomero (5.2%), Ulanga (5.0%), Morogoro Urban (3.8%), Morogoro Urban (2.5%) and Kilosa (0.6%). The results indicate the absence of clear relationship between the number of cattle in the district and the use of farm yard manure (Chart 3.59b)(Map 3.30) For permanent crops, most farm yard manure is used for the production of bananas (35%), followed by mango (17%), coconut (16%), sugarcane (10%), orange (9%), other crops pawpaw, palm oil, pineapple, mandarin and cashew nut comprise (13%). 3.5.4.2 Inorganic Fertiliser Use The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 8,584 and it was applied to 13,448 ha representing 4.7% of the total area planted during that season (Table 3.9). The largest area applied with inorganic fertilizers was on cereals Chart 3.58 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season Fruits and Vegetables, 1205, 13% Oil seeds and Oil nuts, 15, 0% Pulses, 1000, 11% Roots and Tubers, 85, 1% Cereals, 6750, 75% Cereals Roots and Tubers Pulses Oil seeds and Oil nuts Fruits and Vegetables Cash Crrops Chart 3.60 Planted Area with Inorganic Fertilizer by Crop Type- Long rainy season Fruits and Vegetables, 2566, 27% Pulses, 104, 1% Cereals, 6747, 72% Cereals Roots and Tubers Pulses Oil seeds and Oil nuts Fruits and Vegetables Cash Crrops 0 20 40 60 80 Percent of Planted Area Oil seeds/nuts Roots and Tubers Cereals Fruits and Vegetables Pulses Cash Crrops Crop Type Chart 3.59a Percentage of Crop Type Planted Area with Compost -Annuals Chart 3.59b Proportion of Planted Area Applied with Farm Yard Manure by District - Morogoro 0.0 2.5 5.0 7.5 10.0 Kilombero Mvomero Ulanga Morogoro Urban Morogoro Rural Kilosa District Percent DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 (72% of the total area applied with inorganic fertilizers), followed by fruits and vegetables (27%) and pulses (1%) (Chart 3.60) However, the proportion of fruit and vegetables with inorganic fertilizers was at (36%) higher than other crop types, followed by cereals (2.9%) and Pulses (0.6%). Inorganic fertiliser is mostly used in Mvomero district (9.7% of the total planted area in the district), followed by Morogoro Urban (1.6%). Other districts used small quantities of inorganic fertiliser and Morogoro Rural recorded the lowest proportion use of inorganic fertiliser (0.1%)(Map 3.31). In perennial crops inorganic fertiliser were used on sugar cane (80.6%), followed by mango (11.4%), pineapple (4.2%) and coconut (3.8%). 3.5.4.3 Compost Use The number of households that applied compost manure on their annual crops during the long rainy season were 3,803 and it was applied to 4,161 ha representing 1.6% of the total area planted (Table 3.9). The proportion of area applied with compost was very low for each type of crop (0 to 4%); however the distribution of the total area using compost manure shows that 83% of this area was cultivated with cereals, followed by fruits and vegetables (7%), oil seeds (7%) pulses (2%) and roots and tubers (1%)(Chart 3.62)(Map 3.30). In permanent crop, compost was mostly used in coconut (29.3%) followed by mango (18.3%), banana (17.6%), sugarcane (12.7%), orange (7.8%), palm oil (6.1%), coffee (3.7%), pineapple (3.5%), cashew nut and lemon each having (0.4%). 3.3.4.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and perennial crops in the region. Pesticides were applied to 35,902 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (44% of the total area applied with pesticides). This was followed by herbicides (39%) and fungicides (17%) (Chart 3.64a) Chart 3.62 Planted Area with Compost by Crop Type - Long rainy season Oil seeds , 309.6, 7% Pulses, 111.3, 2% Cereals, 3934.8, 83% Cash Crrops, 0.0, 0% Roots and Tubers, 37.2, 1% Fruits and Vegetables, 332.8, 7% Cereals Fruits and Vegetables Pulses Roots and Tubers Oil seeds Cash Crrops Chart 3.61b Proportion of Planted Area Applied with Inorganic Fertiliser by District - Morogoro 0.0 2.5 5.0 7.5 10.0 Mvomero Morogoro Urban Ulanga Kilombero Kilosa Morogoro Rural District Percent 0 20 40 60 80 Percent of Planted Area Cereals Fruits and Vegetables Pulses Roots and Tubers Oil seeds Cash Crrops Crop Type Chart 3.61a Percentage of Crop Type Planted Area Inorganic fertilizers - Annuals Chart 3.64a Planted Area (ha) by Pesticide Use Fungicides, 14180, 17% Insecticides, 35902, 44% Herbicides, 31795, 39% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 Insecticide use The planted area applied with insecticides was estimated at 35,902 ha which represented 9% of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with pesticide (22,552 ha, 57.2%) followed by fruits and vegetables (21,133 ha, 30.5%), pulses (2.021 ha, 9%), cash crops (501 ha, 2.2%), oil seeds (175 ha, 0.8%) and roots and tubers (65 ha, 0.3%) (Chart 3.65) However the percent of insecticides used in cash crops and fruits and vegetables is much greater than in other crop types being 72% and 56% respectively, while only 0.3% of root and tuber crops were applied with insecticides (Chart 3.65). Annual Crops with more than 50% insecticide use were onions (100%), cabbage (86.2%), cucumber (82.5%), cotton (80.8%), chillies (65.3%), spinach (61.2%) tomatoes (60.1%) and carrots (55.3%). Mvomero had the highest percent of planted area with insecticide (13.4% of the total planted area with annual crops in the district). This was closely followed by Ulanga (11.8%) then Kilombero (7.4%), Kilosa (3.4%) and Morogoro Urban (3.1%). The smallest percentage use was recorded in Morogoro Rural district (1.2%) (Chart 3.66) 3.5.5.2 Herbicide Use The planted area applied with herbicides was estimated at 37,867 ha which represented 7.8% of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with herbicides (36,657 ha, 97%) followed by oil seed (900 ha, 2.4%), pulses (217 ha, 0.6%) and fruits and vegetables (93 ha, 0.2%). Herbicides were not applied in cash crops and in roots and tubers (Chart 3.67). Chart 3.67 Planted Area Applied with Herbicides by Crop Type Cereals, 36657, 97% Pulses, 217, 1% Fruits and Vegetables, 93, 0% Roots and Tubers, 0, 0% Oil seeds , 900, 2% Cash Crops, 0, 0% Cereals Fruits and Vegetables Pulses Roots and Tubers Oil seeds Cash Crops Chart 3.64b Planted Area applied with Insecticide by Crop Type Roots and Tubers, 65, 0% Pulses, 2021, 9% Oil seeds and Oil nuts, 175, 1% Fruits and Vegetables, 6886, 31% Cash Crrops, 501, 2% Cereals, 12902, 57% Cereals Roots and Tubers Pulses Oil seeds and Oil nuts Fruits and Vegetables Cash Crrops Chart 3.66 Percent of Planted Area Applied with Insecticides by District - Morogoro 0.0 3.0 6.0 9.0 12.0 15.0 Mvomero Ulanga Kilombero Kilosa Morogoro Urban Morogoro Rural District Percent 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cash Crrops Fruits and Vegetables Pulses Cereals Oil seeds and Oil nuts Roots and Tubers Crop Type Chart 3.65 Percentage of Crop Type Planted Area applied with Insecticide DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 However the percent of herbicide use in oil seed was much greater than in other crop types being 16.1% followed by cereals (8.1%), pulses (2.1%) and fruits and vegetables (1.1%) (Chart 3.68). The top six annual crops with highest percentage use of herbicides in terms of area were paddy (27%), onion (16%), egg plant (16%), tomatoes (10%), cucumber (8%) and cabbage (6%). The highest proportion of the planted area applied with herbicides was found in Kilombero district (19%) followed by Ulanga (18.9%), Mvomero (3.7%), Kilosa (2.3%), Morogoro Urban (2.1%) and Morogoro Rural (0.3%) (Chart 3.69). 3.5.5.3 Fungicide Use The planted area applied with fungicides was estimated at 14,180 ha which represented 3% of the total planted area for annual crops and vegetables. The percentage use of fungicides in the long rainy season at (4%) was higher than the corresponding percentage for the short rainy season (2%). Fruits and vegetables had the largest planted area applied with fungicides (4,808 ha, 55%) followed by cereals (3,624 ha, 41%), pulses (318 ha, 4%) and roots and tubers (9 ha, 0.1%). Fungicides were not used in cash crops and oil seeds (Chart 3.70). However the percentage use of fungicide in fruits and vegetables was much greater than in other crop types being 38% followed by pulses (1.1%), cereals (1.07%) and roots and tubers (0.4%). (Chart 3.71). Annual crops with more than 40% fungicide use were tomatoes (56%), cucumbers (50%), onions (49%) and spinach (40%). 0.0 4.0 8.0 12.0 16.0 Percent of Planted Area Oil seeds Cereals Pulses Fruits and Vegetables Roots and Tubers Cash Crrops Crop Type Chart 3.68 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.70 Planted Area applied with fungicides by Crop Type Cereals, 3624, 41% Cash Crops, 0, 0% Roots and Tubers, 9, 0% Pulses, 318, 4% Oil seeds, 0, 0% Fruits and Vegetables, 4808, 55% Cereals Roots and Tubers Pulses Oil seeds Fruits and Vegetables Cash Crops ` 0.0 10.0 20.0 30.0 40.0 Percent of Planted Area Fruits and Vegetables Pulses Cereals Roots and Tubers Oil seeds Cash Crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area applied with fungicides Chart 3.69 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season 0.0 5.0 10.0 15.0 20.0 K'mbero Ulanga Mvomero Kilosa Moro U Moro R District Percent DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 Kilosa, Morogoro Urban and Mvomero districts reported higher percentage use of fungicides with application to 5.8, 5.5 a.d 5.3 percent respectively of the total area planted while Morogoro Rural, Ulanga and Kilombero districts recorded the lowest percentage use of 1.9, 1.4 and 0.7 respectively (Chart 3.72). 3.5.6 Harvesting methods The main harvesting method for cereals was reported to be by hand. All cereals planted during the agricultural year 2002/03(except maize and paddy) were harvested by hand. It is estimated that 89.6 percent of the total area planted with maize was harvested by hand whereas 0.1 percent was harvested by draft animals and 0.1 percent was harvested by machines. For paddy, 84.7 percent of the total area planted was harvested by hand, whereas 0.4 percent was harvested by machine. The rest of the annual crops and vegetables were harvested by hand. 3.5.7 Threshing methods Hand threshing was the most common method used, out of the total area planted 86 percent of the total area planted with cereals during the long rain season of the agricultural year 2002/03 was threshed by hand. The crops that were threshed by draft animals, human powered tools and engine driven machines were harvested from 0.1%, 0.2% and 0.6% of the total area respectively. Cereals harvested from 13% of the total planted area were not threshed. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.3.5.1 Area planted with annual crops and under irrigation In Morogoro region the area of annual crops and vegetables under irrigation was 64,685 ha representing 16 percent of the total area planted. The area under irrigation during the short rainy season was 6,810 ha accounting for 11 percent of the total area under irrigation in agricultural year 2002/03. However the percentage of the planted area under irrigation during the long rainy season was 20% compared with 5% in the short rainy season. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season 62% of the area planted with vegetables was irrigated, whilst 56% of the vegetables were irrigated in the long rainy season. Chart 3.73 Area of Irrigated Land Unirrigated Area, 349466, 84% Irrigated Area , 64685, 16% Irrigated Area Unirrigated Area Chart 3.72 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season 0.0 2.0 4.0 6.0 8.0 Kilosa Morogoro U Mvomero Morogoro R Ulanga Kilombero District Percent DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 The district with the largest planted area under irrigation for annual crops were Mvomero (17,481 ha, 27% of the total planted area with irrigation) and Kilosa (17,255 ha, 26.7%). When expressed as a percentage of the total area planted, Morogoro Urban (32%) and Mvomero (20%) had proportionally more planted area with irrigation than other districts, followed by Morogoro Rural (19%), Kilosa (15%), Kilombero (11%) and Ulanga (10.7%) (Chart 3.74)(Map 3.32) Of all the different crops and in terms of proportion of the irrigated planted area, watermelon (99.7%), onions (88%), cabbage (80%), chillies (73.8%) and spinach (73.1%). In terms of crop type, the area under irrigation for roots and tubers was 14,756 ha (46% of the total area under irrigation), followed by cereals with 8,162 ha (26%), fruits and vegetables 7,255 (23%) and pulses 1,552 (5%) . All of the irrigation on cereals was applied to maize and paddy. The area of fruits and vegetables under irrigation was estimated at 7,255 ha which represented 59% of the total planted area with fruits and vegetables. Watermelon, onions and cabbage were the most irrigated crops. Irrigation was not used in annual cash crops. 3.6.2 Sources of water used for irrigation The main sources of water used for irrigation were river (57% of households with irrigation), canal (26%) and wells (15%). Only 0.1 percent of the households used water from boreholes and the proportion of households that used pipe water as a source of water for irrigation was (2%). Dams as source of irrigation water were not used in the region. It was estimated that 53 percent of households using irrigation as well as 28 of households using river as source of irrigation water in the region were from Kilosa and Mvomero districts respectively. 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 61% of households using this method. This was closely followed by hand bucket by 35% of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.76). Chart 3.75 Number of Households with Irrigation by Source of Water Pipe water, 502, 2% Borehole, 12, 0% Dam, 0, 0% Canal, 5624, 26% Well, 3313, 15% River, 12136, 57% Canal River Well Dam Pipe water Borehole Chart 3.76 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 7639, 35% Gravity, 13136, 61% Other, 77, 0% Hand Pump, 131, 1% Motor Pump, 710, 3% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.74 Planted Area and Percentage of Planted Area with Irrigation by District 0 4000 8000 12000 16000 20000 Mvomero Kilosa M'goro R K,mbero Ulanga M'goro U District Irrigated Area (ha) 0.00 10.00 20.00 30.00 40.00 Percentage with Irrigation Irrigated Land (ha) Percentage of Irrigated Land DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 Gravity was used by most households with irrigation in Kilosa (49.7%), followed by Mvomero (32.5%), Kilombero (8%), Morogoro Rural (5.5%), Ulanga (2.9%) and Morogoro Urban (1.4%). Hand bucket was more common in Mvomero where 35.6% of households used this method to get water for irrigation, followed by Kilosa (24.4), Ulanga (18%), Morogoro Rural (10.9%), Kilombero (9.7%) and Morogoro Urban (1.3%). 3.6.4 Methods of Water Application Most households used bucket/watering can (50% of households using irrigation). This was closely followed by hand jiijnbucket/watering can (47%). Water horse and sprinkler were not widely used (2% and 1% respectively) (Chart 3.77) Although the method of obtaining irrigation water by hand bucket was very common in all six districts, motor pump as a method of obtaining water for irrigation was practiced in Kilosa and Mvomero district and hand motor was used in Kilosa District. 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping the crop for a certain period of time for various reasons. These reasons include storing the crops for food for the household, storing the crops in order to sell it later at higher prices and storing the crops as seed for planting in the following season. The results for Morogoro region show that there were 336,432 crop growing households (15.3% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop in terms of quantity was paddy with 99,430 households storing 19,870 tonnes as of 1st Januari 2004. This was followed by maize (183,248 households and 17,805 tonnes), sorghum and millets (15,471 households and 1,436 tonnes) and beans and pulses (35,134 households and 955 tonnes) and groundnuts (1,524 household and 154 tonnes). The rest of the crops were stored in very small amounts (Chart 3.78) Chart 3.78 Number of Households and Quantity Stored by Crop Type - Morogoro 0 50000 100000 150000 200000 Maize Paddy Pulses Sorghum & Millet Gnuts/Bamb Nuts Cashew nut Coconut Cloves Tobacco Crop Number of households 0 10000 20000 30000 40000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.77 Number of Households with Irrigation by Method of Field Application Water Hose, 467, 2% Flood, 10258, 47% Bucket / Watering Can, 10717, 50% Sprinkler, 250, 1% Flood Bucket / Watering Can Sprinkler Water Hose DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.7.1.1 Methods of Storage The region had 145,569 farming households storing their produce in sacks/open drum structures. This number is equivalent to 66.7 percent of households that stored crops. The households that stored their produce in locally made structures were estimated at 61,762 (28.3%). The number of households that used other methods of storage and their relative proportions were as follow: improved locally made structures 4,577 (2.1%), air tight drum structures 2,619 (1.2%), unprotected pile 1,670 (0.8%) and modern store 385 (0.2%). Those who stored in structure other than those mentioned above were estimated at 1,659 (0.8%) (Chart 3.79) Sack/open drum structures were the dominating storage method in all districts. It was mostly used by households in Kilombero (82% of the total number of households storing crop products), followed by Kilosa households (76%), Morogoro Urban households (66%), Ulanga households (65%), Morogoro Rural (52%) and Mvomero (51.8%) (Chart 3.80). Locally made traditional structures were mostly used by households living in Mvomero (43.9%) of the total number of households storing crop products), followed Morogoro Rural (40.5%), Ulanga (26.6%), Morogoro Urban (21.5%), Kilosa (20.5%) and Kilombero (14.7%). 3.7.1.2 Duration of storage Most of the households (54% of the households storing crops) stored their produce for the period of three to six months followed by those who stored for the period of more than six months (30%). The minority (16%) are those who stored their crop produce for the period of less than three months. The storage pattern for beans and pulses indicated that most households were those storing for the period of between three and six months followed by over six months and the least number of household were those storing for the period of over less than three months (Chart 3.81). The proportion of households that store their produce for the duration of Chart 3.79 Number of households by Storage Methods - Morogoro Locally Made traditional Crib, 61762, 28% Sacks / Open Drum, 145569, 67% Modern Store, 385, 0% Airtight Drum, 2619, 1% Other, 1659, 1% Improved Locally Made Crib, 4577, 2% Chart 3.80 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Kilosa Morogoro R Kilombero Ulanga Morogoro U Mvomero District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 30000 60000 90000 120000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.81 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 three to six months was the highest in Morogoro Rural (66%) followed by Mvomero (65%), Ulanga (61%), Morogoro Urban (51%), Kilosa (51%) and Kilombero (32%) (Chart 3.82) (Map 3.33) District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003, however Mvomero district used proportionately more of the maize harvest than in some district with lower production indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Basically, there are three major purposes of crop storage. These include storing crops for household consumption, seeds for planting and selling at higher prices. Subsistence food crops (Maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption, with seed for planting being the second most important purpose. Practically all stored annual cash crops are stored for selling at higher price. Some of the stored perennial cash crops are for household consumption and seeds for planting in the case of cashew nuts. The percent of households that stored maize for household consumption as the main purpose of storage is 84.1 percent. This is followed by seed for planting (14%) and selling at a higher price (2%) (Chart 3.83) Chart 3.82 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 Kilosa Morogoro R Kilombero Ulanga Morogoro U Mvomero District Quantity (tonnes) 0 5 10 15 20 25 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Cashewnut Coconut Gnuts/Bamb Nuts Crop Type Chart 3.83 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Morogoro Urban Morogoro Rural Kilombero Mvomero 2% 22% 26% 11% 17% 22% Ulanga Kilosa Percent of Households Storing Crops for 3 to 6 Months by District MAP 3.33 MOROGORO 21.2 to 26 16.4 to 21.2 11.6 to 16.4 6.8 to 11.6 2 to 6.8 Percent of Households Storing Crops Tanzania Agriculture Sample Census Percent of Households Storing Crops Morogoro Urban Morogoro Rural Mvomero Kilombero 4,499 83,784 67,321 111,532 78,913 52,613 3.2 9% 1.8% 5.5% 2% 1.7% Ulanga Kilosa 40,000 to 70,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops MAP 3.34 MOROGORO Number of Household Selling Crops Percent of Total Household Selling Crops RESULTS 58 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.1.4 The Magnitude of Storage Loss About 76 percent of households that stored crops had little or no loss but the proportion of households that reported experiencing a loss of more than a fourth or more is relatively high for foods crops than the crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than one fourth for maize is the highest (6.2 of the total number of households that stored crops), followed by sorghum and millets (3.7%), paddy, beans and pulses (2.7%), It is estimated that 100 percent of the households that grew cash crops such as cashew nut, tobacco and annual crops such as groundnuts and bambara nuts reported little or no loss (Table 3.10) 3.7.2 Agro processing and by-products Agro processing refers to an activity which converts crop product from one form to another form in order to add value or increase the palatability of the product. Agro processing could aim at producing products for household utilization or for sale. Agro-processing was practiced in most crop growing households in the region (232,139 households, 89% of the total crop growing households). The percent of households processing crops was very high in all districts (above 80%). (Chart 3.85) 3.7.2.1 Processing Methods Most crop processing households processed their crops using a neighbour’s machine representing 65.8 percent (152,655 households). This was followed by those processing on-farm by hand (61,677 households, 26%), on farm by machine (14,316, 6.2%) and trader (2,684, 1.2%). The remaining methods of processing were used by very few households (less than 1%). However there were district differences with Kilosa, Kilombero, Mvomero and Ulanga having the highest percent of households processing by hand (26%, 24%, 20% and 14% respectively). All other districts processed mostly by Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Kilosa 48098 8267 1562 1261 59188 Morogoro Rural 25084 13044 2784 607 41519 Kilombero 36186 7931 1698 0 45815 Ulanga 19676 6352 896 225 27149 M’goro Urban 2772 456 87 38 3353 Mvomero 34371 4179 1654 1014 41218 Total 166187 40229 8681 3145 218242 Chart 3.84 Households Processing Crops Households not Processing, 28607, 11% Households Processing, 232139, 89% 0 20 40 60 80 100 Percent of Households Processing Lushoto Kilindi Handeni Muheza Korogwe Pangani Tanga District Chart 3.85 Percentage of Households Processing Crops by District Chart 3.86 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Kilosa Morogoro Rural Kilombero Ulanga Morogoro Urban Mvomero District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader By Factory Other DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 neighbours machines. Processing by trader was more common in Morogoro Urban and Mvomero districts (4.79 and 4.77) than in other districts. Processing on farm by machine was more prevalent in Morogoro Urban, Morogoro Rural and Ulanga than in other districts(Chart 3.86). Main Agro-processing products Two types of products are sometimes produced from agro-processing namely, main product and by-products. The main product is the major product after processing and the by-product is the secondary after processing. For example the main product after processing maize is normally flour whilst the by- product is normally the bran. The main processed product produced by the largest number of crop growing households was flour/meal with 155,687 households (67%) followed by grain with 72,230 households (31%). The remaining products were produced by a small number of households (Chart 3.87). The number of households producing by-products accounted for 84.8 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 151,260 households (94%) followed by Husks (3,807 households, 2%), pulp (1,576, 1%) and cake (3,501, 2%). The remaining by- products were produced by a small number of households (Chart 3.88). 3.7.2.3 Main use of primary processed products: The primary processed products were used for households or human consumption, fuel for cooking, for selling as well as animal consumption. Of all the uses, household/human consumption was leading as it represented about 97 percent of the total households that used primary processed product. Mvomero, Kilombero and Morogoro Rural were the only districts which reported using the primary products as fuel for cooking. Out of 2504 households that sold processed products, 1,938 were from Morogoro Rural (77.4% of the total number of households selling processed products in the region), followed by Ulanga with 296 households (11.8%), Kilosa with 131 households (5.2%), Mvomero with 127 households (5.1%), Morogoro Urban with 12 household (0.5 %) and none from Kilombero district. (Chart 3.89). However, the proportion of households that Chart 3.87 Percent of Households by Type of Main Processed Product Flour / Meal 67% Oil 2% Juice 0% Fiber 0% Other 0% Grain 31% Flour / Meal Grain Oil Juice Fiber Other 0.00 20.00 40.00 60.00 80.00 Percentage of households M,goro R Ulanga Kilosa MvomeroM'goro U K'mbero District Chart 3.90 Percentage of Households Selling Processed Crops by District Chart 3.88 Number of Households by Type of By-product Bran, 151260, 94% Shell, 1059, 1% Juice, 368, 0% Pulp, 1576, 1% Other, 115, 0% Fiber, 270, 0% Cake, 3501, 2% Husk, 3807, 2% Chart 3.89 Use of Processed Product Animal Consumption, 278, 0% Did Not Use, 984, 0% Sale Only, 4,194, 1% Fuel for Cooking, 218, 0% Household/ human consumption, 277,966, 98% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 sold processed products (based on the number of households that used the processed product) is highest in Ulanga (44.3%), followed by Kilombero (13.1), Morogoro Rural (8.9%), Mvomero (8.3%), Morogoro Urban (7.9%) and Kilosa (4.1%). 3.7.2.4 Outlets for Sale of Processed Products The greatest number of households sold processed products to neighbours (9,722 households, 47% of households that sold crops). This was followed by selling to local market/trade store (4,089, 19%), trader at farm (2,760, 13%), Marketing co- operatives (217, 1%), large scale farm (207, 1%) and Farmers Associations (212, 1%) (Chart 3.91) There are small differences between districts on crop processing households that sold processed produce to neighbours. The district differences were large for the rest of the sale outlets. In Kilombero , the sale of processed produce to farmer associations was prominent. The districts that had the highest proportion of farmers selling processed products to marketing cooperative were Ulanga and Kilosa. The districts which had the highest percent of crop processing households selling to local markets or trade stores were Ulanga and Morogoro Rural. The percentage of households selling processed products to traders on farm was highest in Kilombero (51.4%), followed by Kilosa (23.5%), Ulanga (19.7%), Mvomero (3.1%) and Morogoro Urban (2.4%) (Chart 3.92). Morogoro Rural district reported no households selling processed products to traders at farm. 3.7.3 Crop Marketing The number of households that reported selling crop was estimated at 182,902 which represent 70.1 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Kilombero (87%) followed by Morogoro Urban (76%), Ulanga (74%), Morogoro Rural (69%), Mvomero (69%) and Kilosa (60%) (Chart 3.93 and Map 3.34). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main problem reported by households (73% of households). Apart from low market prices, other problems were longer distances to the markets (15%), transport cost too high (5%), no transport (4%), no buyer (1%) and lack of market information (1%). Other marketing problems are minor and represented less than 1% of the total reported problems. Chart 3.91 Location of Sale of Processed Products Other, 3605, 17% Trader at Farm, 2760, 13% Farmers Association, 212, 1% Marketing Co- operative, 217, 1% Large Scale Farm, 207, 1% Local Market / Trade Store, 4089, 19% Secondary Market, 252, 1% Neighbours, 9722, 47% Chart 3.92 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% 0.0 3.5 1.1 1.1 0.0 0.0 District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Secondary Market Chart 3.93 Number of Crop Growing Households Selling Crops by District 0 10000 20000 30000 40000 50000 Kilo s a Kilo mbero M'go ro R Mvo mero Ulanga M'go ro U District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.94 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem No Buyer 1% No Transport 4% Market too Far 8% Lack of Market Information 1% Transport Cost Too High 4% Co-operative Problems 0% Open Market Price Too Low 82% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 88 percent of the smallholders. This may had been a result of the insufficient rain. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance. This general trend applies to all districts except for Kilosa and Morogoro Rural where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high: 9.5 percent and 9.2 percent respectively. 3.8 Access to Crop Production Services 3.8.1 Access to agricultural credits The census result shows that in Morogoro region agricultural households (11,456, 4.4%) have access to credit out of which 7,798 (68%) were male-headed households and 3,658 (32%) were female headed households. In Kilosa district only male headed households got agricultural credits whereas in Mvomero districts more female households got credit than male households. In the remaining districts both male and female headed household’s accessed agricultural credits (Table 3.12). 3.8.1.1 Source of agricultural credits The major agricultural credit provider in Morogoro Region was family, friend and relative who collectively provided credit to 5,176 agricultural households (46% of the total number of households that accessed credit), followed by trader/trade store (22%), saving and credit society (11%), commercial bank (8%), private individual (7%) and other sources (2%),. The district distribution of household’s main sources of credit shows that commercial banks were credit provider in Kilosa, Kilombero and Mvomero districts and savings and credit societies were found in all districts except in Morogoro Rural district. Trader/trader store was a major credit provider in Morogoro Rural district. Religious organization, NGO and projects were more involved in funding a relatively great number of households in Kilosa, Kilombero and Mvomero districts. Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 86429 88.0 Other 7325 7.5 Price Too Low 1879 1.9 Trade Union Problems 710 0.7 Co-operative Problems 1398 1.4 Market Too Far 260 0.3 Government Regulatory Board Problems 239 0.2 Total 98239 100.0 Table 3.12 AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District Male Female District Number % Number % Total Kilosa 1007 100 0 0 1007 Morogoro Rural 4484 65 2415 35 6899 Kilombero 1596 74 561 26 2157 Ulanga 456 60 305 40 761 Mvomero 255 40 377 60 632 Total 7798 68 3658 32 11456 Chart 3.95 Percentage Distribution of Households that Received Credit by Main Sources Private Individual 7% Trader / Trade Store 22% Other 2% Saving & Credit Society 11% Family, Friend and Relative 46% Religious Organisation / NGO / Project 4% Commercial Bank 8% Chart 3.96b Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Kilosa Morogoro Rural Kilombero Ulanga Mvomero District Percent of Households Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Co-operative Private Individual DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.8.1.2 Uses of agricultural credits A big proportion (39%) of the agricultural credits provided to agricultural households in the region were used on hiring labour, (38%) were used on buying seeds, agro-chemicals (9%), fertilizers (6%). The proportion of credits intended to be used for tools, equipment, livestock and other were very low (Chart 3.96a). 3.8.1.3 Reasons for not using agricultural credits The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 42 percent of the agricultural households this was followed by households reporting the un-aware of the credit (19%). The proportions of households whose reasons for not getting agricultural credits were “unavailability” and “not wanting to go into debt” were 18 and 9 percents respectively. The rest of the reasons were collectively mentioned by less than 5 percent of the households (Chart 3.96c). 3.8.2 Crop Extension The number of Agricultural households that received crop extension was estimated at 67,368 or 26 percent of total crop growing households in the region (Chart 3.97). Some districts have more access to extension services than others. Ulanga had a relatively high proportion of households (37%) that received crop extension messages in the district followed by Mvomero (35%), Kilombero (32%), Kilosa (21%), Morogoro Rural (13%) and Morogoro Urban (10%) (Chart 3.98a and Map 3.36). Chart 3.97 Number of Households Receiving Extension Advice Households Receiving Extension , 67368, 26% Households Not Receiving Extension , 193377, 74% Chart 3.98a Number of Households Receiving Extension by District 0 10000 20000 Mvomero Kilombero Kilosa Ulanga Morogoro Rural Morogoro Urban District Number of Households 0 20 40 Percent of Households Households Receiving Extension Advice Percent of household receiving Extension Advice Chart 3.96a Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 1% Other 4% Agro-chemicals 9% Tools / Equipment 3% Seeds 38% Fertilizers 6% Labour 39% Chart 3.96c Reasons for not Using Credit (% of Households) Did not know how to get credit, 102911, 42% Don't know about credit, 48462, 19% Not available, 45746, 18% Did not want to go into debt, 22278, 9% Difficult bureaucracy procedure, 10196, 4% Not needed, 9883, 4% Credit granted too late, 1397, 1% Other, 574, 0% Interest rate/cost too high, 7844, 3% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 3.8.2.1 Sources of crop extension messages Of the households receiving extension advice the Government provided the greatest proportion (92.9%, 61,803 households), NGOs provide 3.5 percent, large scale farms 2.2 percent and the remaining providers less than 0.8 percent. However, district differences exist with the proportion of the households receiving advice from government services ranging between 86% and 97% in Morogoro Rural and Ulanga respectively. 3.8.2.2 Quality of Extension The result on the assessment of extension quality indicates that 67 percent of the households receiving extension ranked the service as being good followed by average (17 %), very good (14%), poor (2%) and no good (0.2%)(Chart 3.99). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, the figures presented in this section may be different from the previous section on inputs (Section 2.6). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and the most applied input is improved seeds which were used by 38,684 households (15% of the total number of crop growing household). This is followed by household using pestcides/fungicide (8%), herbicides (8%), inorganic fertilizers (7%), farm yard manure (6%) and compost (3%) (Table 2.13). Table 2.13 Use of Inputs Households With Access to Input Without Access to Input Type of Input Number % Number % Farm yard manure 14937 6 246809 94 Improved seeds 38684 15 221916 85 Pestcides/Fungicide 20823 8 239784 92 Inorganic fertiliser 17374 7 243137 93 Compost 7421 3 253448 97 Herbicide 20987 8 239278 92 Chart 3.99 Number of Households Receiving Extension by Quality of Services Very Good, 9,539, 14% No Good, 102, 0% Poor, 1,211, 2% Average, 11,138, 17% Good, 45,171, 67% Chart 3.98b Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 2.2% Cooperative 0.4% NGO / Development Project 3.5% Other 0.3% Government 93.6% Tanzania Agriculture Sample Census Morogoro Urban Mvomero Morogoro Rural Kilombero 22,710 5,661 8,117 6,333 4,440 46% 4.4% 11.5% 16.4% 12.8% 9% Ulanga Kilosa 2,153 Number of Households Growing Crop Using Improved Seeds- MAP 3.36 MOROGORO Number and Percent of Crop Growing Households Using Improved Seeds by District 18,000 to 23,000 14,000 to 18,000 10,000 to 14,000 6,000 to 10,000 2,000 to 6,000 Percent of Crop Growing Households Using Improved Seeds- Number of Households Growing Crop Using Improved Seeds- Morogoro Urban Morogoro Rural Mvomero Kilosa Kilombero 4,434 53,117 50,069 73,435 48,783 30,908 35% 13% 26% 21% 32% 10% Ulanga Number of Households MAP 3.35 MOROGORO Number of Households and Percent of Total Households Receiving Crop Extension Services by District 60,000 to 74,000 46,000 to 60,000 32,000 to 46,000 18,000 to 32,000 4,000 to 18,000 Number of Household Receiving Crop Extension Services Percent of Household Receiving Crop Extension Services RESULTS 65 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Morogoro mostly purchase it from the local market/trade store (86.7% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers are minor (Chart 3.100). Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing between 3 and 10 km from the source (33%), followed byless than 1 km (22%) and between 1 and 3 km (21%) (Chart 3.101). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “non available” (18%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using. Other reasons such as cost are more important with 61 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. More smallholders use inorganic fertilisers in Mvomero than in other districts in Morogoro region (44% of households using inorganic fertilisers), followed by Kilosa (25%) and Kilombero (24%). The other districts use very little inorganic fertiliser. 3.9.3 Improved Seeds The percent of households that use improved seeds was 15 percent of the total number of crop growing households. Most of the improved seeds are from the local market/trade store (58.4%). Other less important sources of improved seed are from neighbours (24.9%), locally produced by household (4.8%) and development projects (4.0%). Only 1.5 percent of households using improved seed obtain them from large scale farms (Chart 3.102). Access to improved seed is better than access to chemical inputs with 36 percent of households obtaining the input within 1 km of the household (Chart 3.103). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept Chart 3.100 Number of Households by Source of Inorganic Fertiliser 1.2 1.4 1.5 2.0 2.6 4.7 86.7 0.0 4000.0 8000.0 12000.0 16000.0 Local Market / Trade Store Large Scale Farm Crop Buyers Locally Produced by Household Secondary Market Neighbour Co-operative Source of Inorganic Fertiliser Number of Households Chart 3.101 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.102 Number of Households by Source of Improved Seed 58.4 24.9 4.8 4.0 2.6 1.5 1.4 1.4 1.0 0 10000 20000 30000 Local Market / Trade Store Neighbour Locally Produced by Household Development Project Crop Buyers Large Scale Farm Local Farmers Group Co-operative Secondary Market Source of Improved Seed Number of Households Chart 3.103 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly use improved seeds are Mvomero with 44 percent of the total number of households using improved seeds, followed by Kilosa with 19 percent and Kilombero with 14 percent, Morogoro Rural 10 percent, Ulanga 9 percent and Morogoro Urban 4 percent. 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (78.7% of the total number of fungicide users), neighbours 7.4 percent, locally produced by household 3.2 percent. Other sources of insecticides/ fungicides are of minor importance (Chart 3.104). Chart 3.105 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 12 percent of households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 62 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicides are mostly used in Mvomero district with 51 percent of the total number of households using fungicide, followed by Kilosa (21%) and Ulanga (14%). Insecticides/fungicides use in the other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 18,184 representing 7 percent of the total number of agriculture households (Chart 3.106). The number of trees planted by smallholders on their allotted land was 21,698 trees. The average number of trees planted per household that plants trees on their land was one tree. The main species planted by smallholders is Gravellia spp (17,924 trees, 83%), followed by Senna spp. (904, 4%), then Cyprus spp. (626, 3%) and Canophylum Inophylum (510 trees, 2%). The remaining trees species are planted in Chart 3.104 Number of Households by Source of Insecticide/fungicide 78.7 7.4 3.2 2.8 2.4 2.4 1.0 1.5 0.6 0 5000 10000 15000 Local Market / Trade Store Neighbour Locally Produced by Household Secondary Market Development Project Co-operative Other Crop Buyers Local Farmers Group Source of Insecticide/fungicide Number of Households Chart 3.105 Number of Households Reporting Distance to Source of insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.106 Number of Households with Planted Trees - Morogoro. Households with no planted trees, 242562, 93% Households with planted trees, 18184, 7% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 comparatively small numbers (Chart107.). Mvomero has the largest number of smallholders with planted trees than any other district (79%) and is dominated by Gravellia species. This is followed by Ulanga (10%) which is dominated by Gravellia, then Morogoro Urban (5%) and Kilosa (3%) which is mainly planted with Senna spp. (Chart 3.108 and Map 3.39). Smallholders mostly plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 74 percent, followed by scattered around fields (19%) and then trees planted in a plantation or coppice (7%) (Chart 3.109) The main purpose of planting trees is to obtain planks/timber (40%). This is followed by shade (30%), wood for fuel (17%) and poles (7%) (Chart 3.110) 3.3.8 Investment in Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. Chart 3.107 Number of Planted Trees by Species - Morogoro 0 3000 6000 9000 12000 15000 18000 21000 Gravellis Senna Spp Cyprus Spp Calophylum Kyaya Spp Tectona Grandis Eucalyptus Spp Moringa Spp Azadritachta Spp Acacia Spp Leucena Spp Melicia excelsa Other Tree Species Number of Trees Chart 3.108 Number of Trees Planted by Smallholders by Species and Region 0 4000 8000 12000 16000 Mvomero Ulanga Kilosa Morogoro Urban Kilombero Morogoro Rural R egio n Number of Trees Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Calophylum Inophyllum Moringa Spp Azadritachta Spp Acacia Spp Kyaya Spp Leucena Spp Chart 3.109 Number of Trees Planted by Location Plantation, 14759, 68% Scattered in field, 1732, 8% Field boundary, 5207, 24% Chart 3.110 Number of Households by Purpose of Planted Trees 0 10 20 30 40 50 Planks / Timber Shade Wood for Fuel Poles Other Medicinal Use Percent of Households DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 8,894. This number represented (3%) of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Mvomero district (28%) followed by Kilosa (26%), Morogoro Rural (20%), Kilombero (11%), Ulanga (9%) and Morogoro Urban (6%) (Chart 3.112) The erosion control bunds for soil erosion control accounted for 58 percent of the total number of structures built, this was followed by water harvesting bunds (17%), terraces (15%), tree belts (6%), vetiver grass (2%), drainage ditches (1%), dam (0.4%) and gabions/sandbags (0.3%) ( Map 3.40) Erosion control by erosion control bunds, water harvesting bunds and terraces together had 108,277 structures. This represented about 90 percent of the total structures in the region, and the remaining 10 percentages were shared among the rest of the erosion control methods mentioned above. District-wise, Mvomero and Kilosa districts together were reported to have 4,833 control erosion structures and this is about 2% of the total structures. 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 461,063. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.7 percent of the total cattle population on Tanzania Mainland. 0 50 100 150 200 Number of Cattle ('000') Ulanga Kilosa Mvomero K'mbero M'goro R M'goro U Districts Chart 3.114 Total Number of Cattle ('000') by District Chart 3.113 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0 10000 20000 30000 40000 50000 60000 70000 80000 Erosion Control Bunds Water Harvesting Bunds Terraces Tree Belts Vetiver Grass Drainage Ditches Dam Gabions / Sandbag Type of Facility Number of Structures Chart 3.111 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 30,288, 11% Households Without Facilities, 251,852, 97% Chart 3.112 Number of Households with Erosion Control/Water Harvesting Facilities 28 26 20 9 6 11 0 1000 2000 3000 Mvomero Kilosa M'goro R K'mbero Ulanga M'goro U District Number of Households 0 4 8 12 16 20 24 28 32 Percent Number of Households Percent Morogoro Rural Kilombero Morogoro Urban Mvomero 1,781 2,308 982 768 2,526 11.9% 3.4% 3.1% 2% 2.5% 5% Ulanga Kilosa 530 2,100 to 2,600 1,700 to 2,100 1,300 to 1,700 900 to 1,300 500 to 900 Morogoro Rural Morogoro Urban Kilombero Mvomero 1,929 5,864 3,557 2,973 3,174 15.5% 3.6% 6.3% 8% 7.3% 9.6% Ulanga Kilosa 687 4,000 to 6,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Number and Percent of Smallholder Panted Trees by District Number of Smallholder Planted Trees MAP 3.39 MOROGORO Number of Households With Water Harvesting Bunds MAP 3.40 MOROGORO Number and Percent of Households With Water Harvesting Bunds by District Percent of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households With Water Harvesting Bunds Percent of Households With Water Harvesting Bunds RESULTS 70 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 3.12.1.1 Cattle Population The number of indigenous cattle in Morogoro region was 455,985 (98.9 % of the total number of cattle in the region), 5052 cattle (1.1%) were dairy breeds and 26 cattle (0.006%) were beef breeds. The census results show that 10,037 agricultural households in the region (88% of total agricultural households) kept 0.46 million cattle. This was equivalent to an average of 46 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Ulanga which had about 213,593 cattle (46.3% of the total cattle in the region). This was followed by Kilosa (77,655 cattle, 16.8%), Mvomero (71,988 cattle, 15.6%), Kilombero (71,511 cattle, 15.5%), Morogoro Rural (21,601 cattle, 4.7%) and Morogoro Urban (4,716 cattle, 1.0%). (Chart 3.114) (Map 3.41). However Mvomero district had the highest density (29 head per km2) (Map 3.42) Although Ulanga district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle was very small and the number of beef cattle was zero. Morogoro Rural district had the largest number of diary cattle in the region. In general, the number of beef cattle in the all the districts was zero except in Morogoro Urban with very few beef cattle (Chart 3.115). 3.12.1.2 Herd Size Thirty five percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 48 percent of all cattle in the region. Only 17 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 83 percent of total cattle rearing households had herds of size 1-30 cattle and owns 14 percent of total cattle in the region, resulting in an average of 9 cattle per cattle rearing household. There were about 609 households with a herd size of more than 151 cattle each (277,069 cattle in total) resulting in an average of 455 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Morogoro decreased during the period of four years from 237,857 in 1995 to 102,165 cattle in 1998/99. This trend depicts an annual negative growth rate of -15.55 percent (Chart 3.116). However, there was a very sharp increase in number of cattle for the period of four years from 1998/99 to 2002/03 at the rate of 45.75 percent whereby the number increased from 102,165 to 461,063. However, the number of cattle is estimated to have increased from 237,857 in 1994/95 to 461,063 in 2002/03 at the rate of 7.63 percent. Chart 3.115 Number of Cattle by Type and District 213515 77131 71294 18115 78 524 616 217 3486 132 4558 71372 0 80000 160000 240000 Ulanga Kilosa Mvomero Kilombero Morogoro Rural Morogoro Urban Districts Number of Cattle Indigenous Beef Dairy 237857 102,165 461,063 0 200000 400000 600000 N um ber o f ca ttle 1994/95 1998/99 2002/03 Year Chart 3.116 Cattle Population Trend DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Morogoro region was 5,078 (5,052 dairy and 26 improved beef). The diary cattle constituted 1.1 percent of the total cattle and 99.5 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 0.5 percent of the total number of the improved cattle and 0.005 percent of the total cattle. The number of improved cattle increased from 231 in 1998/99 to 5,052 in 2002/03 at an annual growth rate of 116 percent. The data for improved cattle for the year 1994/95 was not collected Chart 117). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Morogoro region ranked 17 out of the 21 regions with 2.1 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Morogoro region was 27,920 (4.3% of all agricultural households in the region) with a total of 243,175 goats giving an average of 9 head of goats per goat- rearing-household. Kilosa had the largest number of goats (104,202 goats, 43% of all goats in the region), followed by Mvomero (58,073 goats, 24%), Morogoro Rural (41,665 goats, 17%), Ulanga (21,181 goats, 9%) and Kilombero (12,554 goats, 5%). Morogoro Urban district had the least number of goats (5,501 goats, 2%) (Chart 3.118) (Map 3.43). However Mvomero had the highest density (24 head per km2) 3.12.2.2 Goat Herd Size Thirty five percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Eighty two percent of total goat-rearing households had herd size of 1-14 goats and owned 52 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 101 households (0.4%) with herd sizes of 40 or more goats each (9,183 goats in total), resulting in an average of 91 goats per household. 231 5052 0 20000 Number of cattle 1998/99 2002/03 Year Chart 3.117 Dairy Cattle Population Trend 0 30 60 90 120 Number of goats Kilosa Mvomero Morogoro Rural Ulanga Kilombero Morogoro Urban District Chart 3.118 Number of Goats ('000') by Distict DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 97.5 percent of the total goats in Morogoro region. Improved goats for meat and diary goats constituted 0.4 and 2.1 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1994/95 to 2002/03 was -1.40 percent. This negative trend implies eight years of population decrease from 272,162 in 1994/95 to 243,175 in 2002/03. The number of goats decreased from 272,162 in 1994/95 at an estimated annual rate of -4.25 percent to 228,461 in 1998/99. From 1998/99 to 202/03, the goat population increased at an annual rate of 1.57 percent (Chart 119). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Morogoro region after cattle and goats. The region ranked 11 out of 21 Mainland regions and had 2.4 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 7,442 (1.2% of all agricultural households in Morogoro region) rearing 95,680 sheep, giving an average of 13 heads of sheep per sheep- rearing household. The district with the largest number of sheep was Ulanga with 49,823 sheep (52% of total sheep in Morogoro region) followed by Mvomero (17,059 sheep, 18%), Kilosa (15,607 sheep, 16%), Kilombero (7,956 sheep, 8%) and Morogoro Rural (5,096 sheep, 5%). Morogoro Urban district had the least number of sheep (138 sheep, 0.1%) (Chart 3.120 and Map 3.45). Mvomero had the highest density (7 head per km2). Sheep rearing was dominated by indigenous breeds that constituted 98 percent of all sheep kept in the region. Only 2 percent of the total sheep in the region were improved breeds. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1994/95 to 2002/03 is estimated at - 0.28 percent. The population decreased at an annual rate of -12.54 percent from 97,871 in 1994/95 to 57,259 in 1998/99. From 1998/99 to 2002/03, sheep population increased at an annual rate of 13.70 percent (Chart 3.121). 272162 228,461 243,175 0 100000 200000 300000 Number of goats 1994/95 1998/99 2002/03 Year Chart 3.119 Goat Population Trend 0 10000 20000 30000 40000 50000 Number of sheep Ulanga Mvomero Kilosa K'mbero M'goro Rural M'goro Urban District Chart 3.120 Total Number of Sheep by District 97871 57,259 95,680 0 40000 80000 120000 Number of sheep 1994/95 1998/99 2002/03 Year Chart 3.121 Sheep Population Trend Morogoro Rural Morogoro Urban Mvomero Kilombero 5 7 29 15 15 23 Ulanga Kilosa Morogoro Rural Morogoro Urban Mvomero Kilombero 21,601 71,988 77,655 71,511 213,593 Ulanga Kilosa 4,716 Tanzania Agriculture Sample Census Cattle Population by District as of 1st Octobers 2003 Number of Cattle MAP 3.41 MOROGORO Cattle Density MAP 3.42 MOROGORO Cattle Density by District as of 1st October 2003 160,000 to 220,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 24.2 to 29 19.4 to 24.2 14.6 to 19.4 9.8 to 14.6 5 to 9.8 Cattle Population Cattle Density (Number Per Square Km) RESULTS 74 Morogoro Rural Morogoro Urban Mvomero Kilombero 10 9 24 3 2 20 Ulanga Kilosa Morogoro Rural Morogoro Urban Mvomero Kilombero 41,665 5,501 58,073 21,181 12,554 104,202 Ulanga Kilosa MAP 3.44 MOROGORO Goat Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Goat Population by District as of 1st Octobers 2003 MAP 3.43 MOROGORO 19.6 to 24 15.2 to 19.6 10.8 to 15.2 6.4 to 10.8 2 to 6.4 160,000 to 220,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Number of Goat Goat Density Goat Population Goat Density (Number Per Square Km) RESULTS 75 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 8 out of 21 Mainland regions and is 4 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Morogoro region was 18,088 (2.8% of the total agricultural households in the region) rearing 44,986 pigs. This gives an average of 3 pigs per pig- rearing household. The district with the largest number of pigs was Mvomero with 22,254 pigs (49% of the total pig population in the region) followed by Kilosa (11,432 pigs, 25%), Morogoro Rural (6,496 pigs, 14%), Ulanga (2,870 pigs, 6%), Kilombero (1,330 pigs, 3%) and Morogoro Urban (604 pigs, 1%) (Chart 3.122 and Map 3.47) However, Mvomero district had the highest density (9 head pre km2) (Map 3.48) 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1994/95 to 2002/03 was 14.1 percent. During this period the population grew from 15,682 to 44,986. The pig population increased from 15,688 in 1994/95 to 50,449, in 1998/99 a higher rate of 33.93 percent. The growth rate dropped to -2.82 percent during the following four years from 1998/99 to 2002/03 in which pig population decreased from 50,449 to 44,986(Chart 3.123). 3.12.5 Chicken Production The poultry sector in Morogoro region was dominated by chicken production. The region contributed 6.3 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 154,850 raising about 2,100,861 chickens. This gives an average of 14 chickens per chicken-rearing household. In terms of total number of chickens in the country, Morogoro region was ranked sixth out of the 21 Mainland regions 0 8,000 16,000 24,000 Number of Pigs Mvomero Kilosa Morogoro Rural Ulanga Kilombero Morogoro Urban District Chart 3.122 Total Number of Pigs by District 15,682 50,449 44,986 - 20,000 40,000 60,000 Number of pigs 1994/95 1998/99 2002/03 Year Chart 3.123 Pig Population Trend 0 200,000 400,000 600,000 Number of Chickens Kilosa KilomberoMvomero Morogoro Ulanga Morogoro Urb District Chart 3.124 Total Number of Chickens by District DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 77 The District with largest number of chicken was Kilosa with 639,761 chicken (30% of the total chickens in the region) followed by Kilombero (433,045 chicken, 21%), Mvomero (411,992 chicken, 20%), Morogoro Rural (383,509 chicken, 18%), Ulanga (201,607 chicken, 10%) and Morogoro Urban (30,947 chicken, 1%). (Chart 3.124 and Map 3.49). However, Mvomero district had the highest density (167 head per km2) (Map 3.50) 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 4.13 percent. The population increased at a rate of 0.45 percent from 1995 to 1999 after which it increased to 7.94 percent for the four year period from 1999 to 2003 (Chart 3.125). Ninety eight percent of all chicken in Morogoro region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 79 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 20 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 32 chickens per holder. Only 0.4 percent of holders kept the flock sizes of more than 100 chickens at an average of 272 chickens per holder (Table 3.13). Table 3.13 Number of Household and Chickens Raised by Flock Size Flock Size No. of Hh % Number of Chicken Average chicken per household 1 - 4 38527 25 100926 3 5 - 9 41837 27 271789 6 10 - 19 42306 27 538660 13 20 - 29 16841 11 387719 23 30 - 39 7212 5 228874 32 40 - 49 2717 2 113122 42 50 - 99 4786 3 289911 61 100+ 624 0.4 169859 272 Total 154850 100 2100861 14 1,519,844 1,547,504 2,100,861 - 1,000,000 2,000,000 3,000,000 Number of Chicken 1994/95 1998/99 2002/03 Year Chart 3.125 Chicken Population Trend Morogoro Urban Morogoro Rural Kilombero Mvomero 0 1 3 2 5 7 Ulanga Kilosa 5.6 to 7 4.2 to 5.6 2.8 to 4.2 1.4 to 2.8 0 to 1.4 Morogoro Rural Morogoro Urban Mvomero Kilombero 5,096 138 17,059 7,956 49,823 15,607 Ulanga Kilosa MAP 3.46 MOROGORO Sheep Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Sheep Population by District as of 1st Octobers 2003 MAP 3.45 MOROGORO 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Sheep Sheep Density Sheep Population Sheep Density (Number Per Square Km) RESULTS 78 Morogoro Rural Morogoro Urban Mvomero Kilombero 1.5 1 9 2.1 0.3 0.3 Ulanga Kilosa Morogoro Rural Morogoro Urban Mvomero Kilombero 6,496 604 22,254 11,432 1,330 2,870 Ulanga Kilosa Tanzania Agriculture Sample Census Pig Population by District as of 1st Octobers 2003 MAP 3.47 MOROGORO MAP 3.48 MOROGORO Pig Density by District as of 1st October 2003 20,000 to 23,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 7.1 to 9 5.4 to 7.1 3.7 to 5.4 2 to 3.7 0.3 to 2 Number of Pig Pig Density Pig Population Pig Density (Number Per Square Km) RESULTS 79 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 80 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Morogoro region increased at an annual rate of 83 percent for the period of four years from 7,300 in 1999 to 82,168 in 2003. The number of improved chicken was most significant in Kilosa district followed by Ulanga district (Chart 3.126). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was -41.5 percent during which the population dropped from 34,080 to 466. The annual growth rate was -17.43% for the period of four years from 1995 to 1999. The broiler population exhibited a decreasing trend at the rate of -58.6 percent per annum for the period of four years resulting a decrease from 15,842 in 1999 to 466 in 2003 (Chart 3.127). 3.12.6 Other Livestock There were 76,948 ducks, 89,728 turkeys, 8,828 rabbits and 1,892 donkeys raised by rural agricultural households in Morogoro region. Table 3-14 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Kilosa district (31% of all ducks in the region), followed by Mvomero (21%), Kilombero (20%), Morogoro Rural (15%), Ulanga (13%) and Morogoro Urban (0.3%). Turkeys were reported in Ulanga, Kilosa, Mvomero and Morogoro Urban only (Table 3.14). Table 3.14 Head Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Kilosa 23754 11206 6955 0 0 Morogoro Rural 11558 0 0 0 12230 Kilombero 15311 0 0 0 0 Ulanga 9718 69612 385 0 1899 Morogoro Urb 246 862 97 0 0 Mvomero 16362 8047 1390 1892 126 Total 76948 89728 8828 1892 14255 Chart 3.128 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 Ulanga Kilosa Morogoro Urb Kilombero Morogoro Mvomero District P ercen t Ticks Tsetseflies 80605 0 714 0 466 466 383 0 0 0 0 0 0 30000 60000 90000 Number of Chickens Kilosa Kilombero Ulanga Mvomero Morogoro Morogoro Urb District Chart 3.126 Number of Improved Chicken by Type and District Layer Broiler - 34,080 7,300 15,842 82,168 466 - 30,000 60,000 90,000 Number of layers 1994/95 1998/99 2002/03 Year Chart 3.127 Layers Population Trend Mvomero Morogoro Urban Morogoro Rural Kilombero 167 49 90 120 89 22 Ulanga Kilosa Morogoro Rural Morogoro Urban Mvomero Kilombero 383,509 30,947 411,992 639,761 433,045 201,607 Ulanga Kilosa 400,000 to 700,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Tanzania Agriculture Sample Census Number of Chicken by District as of 1st October 2003 MAP 3.49 MOROGORO MAP 3.50 MOROGORO Density of Chicken by District as of 1st October 2003 140 to 170 110 to 140 80 to 110 50 to 80 20 to 50 Number of Chicken Chicken Density Chicken Population Chicken Density (Number Per Square Km) RESULTS 81 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.7 Pest and Parasite Incidence and Control The results indicate that 28 percent and 21 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Ulanga district but lowest in Mvomero district. (Map 3.51) The most practiced method of tick control was spraying with 61 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (5.6%), smearing (2.5%) and other traditional methods like hand picking (2.5%). However, 28.4 percent of livestock- keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 67.9 percent of livestock-rearing households this was followed by trapping (3.0%) and dipping (2.3%). However, 26.7 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 12,038 (33% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 30 percent, goats (57%), sheep (27%) and pigs (31%) (Chart 3.129) 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 31,171 representing 85 percent of the total livestock-rearing households and 12 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 21 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (3%) and large-scale farmers (2%). 0 20 40 60 Percent Kilosa Morogoro Kilombero Ulanga Morogoro Urb Mvomero District Chart 3.129 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Dewormed Cattles Dewormed Goats Dewormed Sheep Dewormed Pigs Chart 3.130 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Very Good 14% Poor 2% No good 0% Average 17% Good 67% Morogoro Rural Morogoro Urban Mvomero Kilombero 0 128 2,341 1,429 1,912 0 0% 0.3% 3.2% 2.9% 6.2% Ulanga Kilosa 0 Morogoro Urban Morogoro Rural Mvomero Kilosa Kilombero 1,244 1,496 5,108 728 1,449 27.1 21.8% 15.9 41.1% 22.6% 46.5% Ulanga 171 Tanzania Agriculture Sample Census Number and Percent of Households Infected With Ticks by District Number of Households Infected With Ticks MAP 3.51 MOROGORO Number of Households Using Draft Animals MAP 3.52 MOROGORO Number and Percent of Households Using Draft Animals by District 4,000 to 6,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 2,000 to 2,400 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Number of Houshold Infected With Ticks Percent of Household Infected With Ticks Number of Household Using Draft Animal Percent of Household Using Draft Animal RESULTS 83 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 About 67 percent of livestock rearing households described the general quality of livestock extension services as being good, 17 percent said they were average and 14 percent said they were very good. However, zero percent of the livestock rearing households said the quality was not good whilst 2 percent described them as poor (Chart 3.130). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 88 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 12 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected districts was Ulanga and Morogoro Rural districts with almost over 95 % of livestock rearing households accessing the services at a distance of more than 14 kms. Mvomero district was the least affected because about 60 percent of the households could access the service within a distance of 14 kilometers. (Chart 3.132) 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 15,838 (97% of livestock rearing households in Morogoro region) whilst 424 households (3%) resided between 5 and 14 kms. However, 122 households (1%) had to travel a distance of 15 or more kms to the nearest watering point. (Chart 3.133) Kilosa district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Mvomero, Ulanga, Kilombero, Morogoro Rural and Morogoro Urban. In the region only 3% of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.134). Chart 3.131 Number of Households by Distance to Verinary Clinic More than 14km, 222396, 88% Less than 14km, 31228, 12% Chart 3.133 Number of Households by Distance to Village Watering Points 15 or more kms, 122, 1% 5-14 kms, 424, 3% Less than 5 kms, 15838, 97% Chart 3.134 Number of Households by Distance to Village Watering Point and District 0 2500 5000 7500 Kilosa Mvomero Ulanga K'mbero M'goro R M'goro U District Number of Households Less than 5 kms 5-14 kms 15 or more kms Chart 3.132 Number of Households by Distance to Veterinary Clinic and District 0 20000 40000 60000 Kilosa M'goro R K'mbero Mvomero Ulanga M'goro U District Number of Households Less than 14km More than 14km DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.12.9 Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Morogoro region is very limited with only 5,810 households (0.90% of the total households in the region) using them (Chart 3.144). Draft animals were used in Kilosa, Ulanga, Kilombero and Mvomero districts only. The number of households that used draft animals in Kilosa was 2,341 representing 40 percent of the households using draught animals in the region followed by Ulanga 33%, Kilombero 25%, and Mvomero 2%. Use of draft animals was not reported in the other districts (Chart 3.135) (Map 3.52). The region had 20,104 oxen (Ulanga 10,281, Kilombero 6,466, Kilosa 2,591 and Mvomero 766) that were used to cultivate 17,218 hectares of land. This represents only 0.9 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Ulanga district (8,839 ha, 51.3% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Morogoro region was 14,620 (6% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 12,613 ha of which 7,103 hectares (56% of the total area applied with organic fertiliser or 2.5% of the area planted with annual crops and vegetables in Morogoro region during the long rainy season) was applied with farm yard manure. 3.135 Number of Households Using Draft Amimals Household Not Using Draft Animals, 254936, 98% Households Using Draft Animals, 5810, 2.2% 0 800 1600 2400 Number of Households Kilosa Ulanga K'mbero MvomeroM'goro R M'goro U District Chart 3.136 Number of Households Using Draft Animals by District - Morogoro Chart 3.137 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 14620, 6% Not Using Organic Fertilizer, 245767, 94% Chart 3.138 Area of Application of Organic Fertiliser by District - Morogoro 0 1000 2000 3000 4000 5000 Kilosa Mvomero Kilombero Ulanga Morogoro Rural Morogoro Urban District Area of Fertiliser Application (ha) Farm Yard Manure Area Applied Compost Area Applied DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 Only 5,511 ha (44% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Kilosa district with 3,014 hectares (42% of the total area applied with farm yard manure) followed by Mvomero (1,775 ha, 25%), Kilombero (1,448 ha, 20%), Ulanga (440 ha, 6%), Morogoro Rural (286 ha, 4%), and Morogoro Urban (143 ha, 2%) (Chart 3.138) 3.5.0 Fish Farming The number of households involved in fish farming in Morogoro region was 902 representing 0.3 percent of the total agricultural households in the region (Chart 3.139). Kilombero was the leading district with 369 households (41% of agricultural households) involved in fish farming. This was followed by Morogor Rural (363 households, 40%), Kilosa (93 households, 10%) and Ulanga (76 households, 8%). Fish farming was not practiced in Morogoro Urban and Mvomero districts (Chart 3.140 and Map 3.53)). The main source of fingerings was the non governmental organizations and/or projects which provided fingering to 55 percent of the fish farming households. About 28 percent of households practicing fish farming got fingerings from their neighbours, 9 percent got them from private trader and 9 percent from other sources. All fish farming households in the region used the dug-out-pond system and the main fish specie planted is Tilapia. The only type of fish harvested in Morogoro region was Tilapia 191,311 (Chart 3.141). About 72 percent of the fish farming households sold their fish while 28 percent did not sell. All fish were sold to their neighbours. 3.6.0 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 161.1 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (69.8), hospitals (54.2), secondary market (28.8), secondary school (23.7), primary market (19.7), tertiary Chart 3.139 Number of Households Practicing Fish Farming - Morogoro Household Not Practicing Fish Farming, 259843.9, 100% Household Practicing Fish Farming, 902, 0.3% 0.0 100.0 200.0 300.0 400.0 Number of Households K'mbero M'goro R Kilosa Ulanga M'goro UMvomero District Chart 3.140 Number of Households Practicing Fish Farming by District - Morogoro Chart 3.141 Fish Production Number of Tilapia, 191311, 100.0% Number of Carp, 0, 0.0% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 market (19.7), health clinics (7.4), all weather roads (5.5), primary schools (2.5) and feeder roads (1.7) (Table 3.15). Only 4.7 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 14.5 percent reported them to be average. Forty two point six percent of the agricultural households said the infrastructure and services were poor were, and 13.8 percent said they were ‘no good’. 3.7. POVERTY INDICATORS The agricultural census had some questions that aimed at getting an indication of the level of poverty that could be used as a base for tracking progress in poverty reduction strategies undertaken by the government. 3.7.1 Type of Toilets A large number of rural agricultural households use traditional pit latrines (244,301 households, 947% of all rural agricultural households) 5,794 households (2.2%) use improved pit latrine and 3,191 households (1.2%) use flush toilets. The remaining 484 household (0.2%) use other toilets facilities. However, 6,975 households (2.7%) in the region had no toilet facilities (Chart 3.142) (Map 3.54). The distribution of the households without toilets within the region indicates that 45 percent of them were found in Kilosa district and 20 percent were from Kilombero. The percentages of households without toilets in other districts were as follows Ulanga (19%), Mvomero (9%), Morogoro Rural (4%), Morogoro Urban (3%). 3.7.2 Household’s Assets Radios are owned by most rural agricultural households in Morogoro region with 151,106 households (58% of the agriculture households in the region) owning the asset. followed by bicycle ( 101,029 households, 38.7%), iron (35,406 households, 13.6%), wheelbarrow (10,595 households, 4.1%), mobile phone (4,230 households, 1.6%), landline phone (889 households, 0.3%), vehicle (2,686 households, 0.2%) and television/video (1,966 households, 0.0%), (Chart 3.143). Table 3.15: Mean distances from Household Dwelling to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmarc Roads Kilosa 31.1 3.4 3.8 1.6 49.6 8.4 131.9 12.6 20.8 12.6 41.1 Morogoro 19.6 2.1 9.2 2.4 77.5 8.6 82.4 16.0 15.2 16.0 71.2 Kilombero 16.9 2.5 3.0 2.0 70.7 6.8 272.4 49.3 49.0 49.3 78.8 Ulanga 23.3 1.8 3.4 1.1 36.6 6.3 333.1 12.2 39.3 12.2 175.4 Morogoro Urb 9.1 3.9 2.6 1.6 12.0 8.2 14.1 9.0 10.1 9.0 6.8 Mvomero 25.5 1.8 8.2 1.1 34.9 5.7 85.9 11.1 30.6 11.1 42.1 Total 23.7 2.5 5.5 1.7 54.2 7.4 161.1 19.7 28.8 19.7 69.8 Chart 3.142 Agricultural Households by Type of Toilet Facility Flush Toilet, 3191, 1.2% Improved Pit Latrine - hh Owned, 5794, 2.2% Other Type, 484, 0.2% No Toilet / Bush, 6975, 2.7% Traditional Pit Latrine, 244301, 93.7% Chart 3.143 Percentage Distribution of Households Owning the Assets 4.1 1.6 0.3 0.2 0.0 13.6 38.7 58.0 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Land line phone Vehicle Television/video Assets Percent Morogoro Urban Mvomero Morogoro Rural Kilombero 617 246 3,173 1,409 1,305 1.2% 5.1% 0.5% 4.3% 2.9% 4.2% Ulanga Kilosa 225 Morogoro Urban Mvomero Morogoro Rural Kilombero 93 0 363 369 76 0.1% 0% 0% 0.7% 0.8% 0.2% Ulanga Kilosa 0 Number and Percent of Households Practicing Fish Farming by District MAP 3.53 MOROGORO 2,600 to 3,200 2,000 to 2,600 1,400 to 2,000 800 to 1,400 200 to 800 280 to 370 210 to 280 140 to 210 70 to 140 0 to 70 Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Number of Households Without Toilets MAP 3.54 MOROGORO Number and Percent of Households Without Toilets Facilities by District Household Practicing Fish Farming Percent of Household Practicing Fish Farming Number of Household Without Toilets Percent of Household Without Toilets RESULTS 88 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 89 3.7.3 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. It was estimated that about 70.5 percent of the total rural households used this source of energy followed by hurricane lamp (22.4%), pressure lamp (4.3%), mains electricity (1.1%), firewood (1.2%), solar (0.1%), candle (0.2%) and gas or biogas (0.2%) (Chart 3.144). 3.7.4 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 92.2 percent of all rural agricultural households in Morogoro region. This is followed by charcoal (6.3%). The rest of energy sources accounted for 1.5 percent. These were bottled gas (0.22%), crop residues (0.46%), mains electricity (0.21%), solar (0.20%), livestock dung (0.03%), paraffin/kerosene (0.35%) and none for gas/biogas (Chart 3.145). 3.7.5 Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 54 percent of the rural agricultural households. This was closely followed by iron sheets (36.2%), grass/mud (8.4%), asbestos (0.2%), tiles (0.8%), concrete (0.4%) and others (0.1%) (Chart 3.155). Mvomero district had the highest percentage of households whose roofing material for the main building was grass/leaves (68%) and was followed by Morogoro district.(63%), Kilombero (60%), Morogoro Urban (55%), Ulanga (39%) and Kilosa (Chart 3.147) (Map 3.55). Chart 3.144 Percentage Distribution of Households by Main Source of Energy for Lighting Gas (Biogas), 562, 0.2% Candles, 640, 0.2% Solar, 368, 0.1% Firewood, 3018, 1.2% Hurricane Lamp, 58452, 22.4% Pressure Lamp, 11136, 4.3% Mains Electricity, 2979, 1.1% Wick Lamp, 184153, 70.5% Chart 3.145 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 240462, 92.22% Charcoal, 16473, 6.32% Gas (Biogas), - , 0.00% Parraffin / Kerocine, 911, 0.35% Livestock Dung, 77, 0.03% Mains Electricity, 541, 0.21% Solar, 513, 0.20% Crop Residues, 1205, 0.46% Bottled Gas, 562, 0.22% Chart 3.146 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.2% Grass & Mud 8.4% Iron Sheets 36.2% Grass / Leaves 54.0% Tiles 0.8% Other 0.1% Concrete 0.4% Chart 3.147 Percentage Distribution of Households with Grassy/Leafy Roofs by District 33 39 55 60 63 68 0 25 50 75 Mvomero M'goro R Kilombero M'goroU Ulanga Kilosa District Percent Morogoro Urban Mvomero Morogoro Rural Kilosa Kilombero 27,489 33,329 28,529 29,114 20,941 55% 33% 63% 39% 60% 68% Ulanga 1,442 29,000 to 34,000 22,000 to 29,000 15,000 to 22,000 8,000 to 15,000 1,000 to 8,000 Morogoro Urban Morogoro Rural Kilombero Mvomero 15,343 28,515 29,852 11,876 23,167 50% 29% 39% 61% 38% 46% Ulanga Kilosa 2,232 26,000 to 30,000 20,000 to 26,000 14,000 to 20,000 8,000 to 14,000 2,000 to 8,000 Tanzania Agriculture Sample Census Number and Percent of Households Using Grass/Leaves For Roofing Material by District Number of Households Using Grass/Leaves For Roofing Material MAP 3.55 MOROGORO Number of Households Eating 3 Meals Per Day MAP 3.56 MOROGORO Number and Percent of Households Eating 3 meals Per Day by District Number of Household Using Grass/ Leaves For Roofing Material Percent of Household Using Grass/ Leaves For Roofing materials Number of Households Eating 3 Meals Per Day Percent of Household Eating 3 Meal Per Day RESULTS 90 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.7.6 Access to Drinking Water The main source of drinking water for rural agricultural households in Morogoro region was piped water with 24 percent of households using it as the main source during the wet season and 25 percent of the households during the dry seasons. This is followed by surface water (23% of households for each season), protected wells (22% of households for each season), unprotected well (20% of households in the wet season and 19% during dry season) and unprotected spring with 9 percent of households using the source for both seasons. Unprotected rainwater catchments was used as a main source by 0.9 percent of the households in wet season and by 0.3 percent in dry season Chart 3.149) About 73 percent of the rural agricultural households in Morogoro region were getting drinking water within a distance of less than one kilometer during wet season compared to 66 of the households during the dry season. However, 27 percent of the agricultural households were getting drinking water from a distance of one or more kilometers during wet compared to 34 percent of households in the dry season. In general 92 percent and 85 percent of rural agricultural households in Morogoro region were getting their drinking water within a distance of 2 kms during the wet season dry season respectively (Chart 3.150). 3.7.7 Food Consumption Pattern 3.7.7.1 Number of Meals per Day The majority of households in Morogoro region normally took 2 meals per day (53.2 percent of the households in the region), 42.6 percent took three meals, 3.5 percent took one meal and 0.7 percent took four meals per day (Chart 3.150) Chart 3.148 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Piped Water Surface Water (Lake / Dam Protected Well Uprotected Well Unprotected Spring Uncovered Rainwater Catchment Other Main source Percent of Households Wet Season Dry Season Chart 3.149 Percentof Households by Distance to Main Source of Drinking Water and Season 0 10 20 30 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance Percent wet season Dry season Chart 3.150 Number of Agriculural Households by Number of Meals per Day One, 9199, 3.5% Three, 110985, 42.6% Two, 138726, 53.2% Four, 1835, 0.7% DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 Morogoro Rural district had the largest number of households that normally takes one meals per day whilst Kilombero had a relatively higher number of households that normally takes three meals per day. In Morogoro region, there were very few households that reported to have taken four meals per day (0.7% of the rural agricultural households) (Table 3.16) (Map 3.56). 3.7.7.2 Meat Consumption Frequencies The number of agricultural households that had consumed meat during the week preceding the census was 164,669 (63% of the agricultural household in Morogoro region) with 79,176 households (48.1 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice (33.8%), and three times (13.2%). Very few households had meat four or more times during the respective week. About 36.8 percent of the agricultural households in Morogoro region did not eat meat during the week preceding the census (Chart 3.151) (Map 3.57). 3.7.7.3 Fish Consumption Frequencies The number of agricultural households that had consumed fish during the week preceding the census was 180,756 (69% of the total agricultural household in Morogoro region) with 68,222 households (37.7 % of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish twice (30.6%). In general, the percentage of households that consumed fish twice or more during the week preceding the census in Morogoro region was 112,534 (62.3% of the agricultural households that ate fish in the region during the respective period). About 30.7 percent of the agricultural households in Morogoro region did not eat fish during the week preceding the census (Chart 3.160) (Map 3.58). 3.7.8 Food Security In Morogoro region, 90,859 households (34.8% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements, whilst 21,083 (8.1%) said they sometimes experience problems. However, 11.2 percent of agricultural households in Morogoro region often experienced problems in satisfying their food needs and 8.7 percent of them said they always had problems. About 37.2 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.59). Table 3.16: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Kilosa 1640 2.2 41720 56.8 28515 38.8 1560 2.1 73435 Morogoro Rural 4707 8.9 33067 62.3 15343 28.9 0 0.0 53117 Kilombero 1006 2.1 17805 36.5 29852 61.2 119 0.2 48782 Ulanga 461 1.5 18416 59.6 11876 38.4 156 0.5 30908 Morogoro Urb 134 3.0 2068 46.6 2232 50.3 0 0.0 4434 Mvomero 1252 2.5 25650 51.2 23167 46.3 0 0.0 50069 Total 9199 3.5 138726 53.2 110985 42.6 1835 0.7 260746 Chart 3.151 Number of Households by Frequency of Meat and Fish Cosumption 0 25000 50000 75000 100000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 3.7.9 Main Sources of Cash Income The results indicate that selling of food crops was the main cash income earning activity reported by 56.8 percent of all rural agricultural households, followed by casual labour (11.8%), selling of cash crops (9.6%), businesses (8.8%) and sale of forest products (4.3%). Other income earning activities were employment (3.2%), cash remittances (2.3%), sale of livestock (1.6%), sale of livestock products (0.5%) and fishing (0.4%) (Chart 3.152). Chart 3.152: Percentage Distribution of the Number of Households by Main Source of Income 118.0, 58% 9.6, 5% 0.4, 0% 0.5, 0% 0.0, 0% 0.5, 0% 4.3, 2% 1.6, 1% 3.2, 2% 2.3, 1% 8.8, 4% 56.6, 27% Sales of Food Crops Other Casual Cash Earnings Sales of Cash Crops Business Income Cash Remittance Wages & Salaries in Cash Sale of Livestock Sale of Forest Products Sale of Livestock Products Fishing not applicable Other Morogoro Urban Mvomero Morogoro Rural Kilombero 9,674 1,238 15,818 23,692 9,922 7,878 19% 28% 30% 32% 20% 25% Ulanga Kilosa 19,200 to 23,700 14,700 to 19,200 10,200 to 14,700 5,700 to 10,200 1,200 to 5,700 Morogoro Urban Mvomero Morogoro Rural Kilombero 14,311 1,775 18,700 21,862 13,421 9,107 29% 40% 35% 30% 28% 29% Ulanga Kilosa 17,700 to 21,900 13,700 to 17,700 9,700 to 13,700 5,700 to 9,700 1,700 to 5,700 Tanzania Agriculture Sample Census Number and Percent of Households Eating Meat Once Per Week by District Number of Households Eating Meat Once Per Week MAP 3.57 MOROGORO Number of Households Eating Fish Once Per Week MAP 3.58 MOROGORO Number and Percent of Households Eating Fish Once Per Week by District Household Eating Fish Once Per Week Percent of Household Eating Fish Once Per Week Number of Households Eating Meat Once Per Week Percent of Households Eating Meat Once Per Week RESULTS 94 Morogoro Urban Mvomero Morogoro Rural Kilombero 101 5,328 7,711 7,608 1,098 846 2% 11% 15% 10% 2% 3% Ulanga Kilosa 6,100 to 7,800 4,600 to 6,100 3,100 to 4,600 1,600 to 3,100 100 to 1,600 Tanzania Agriculture Sample Census Number and Percent of Households Reporting Food Insufficiency by District MAP 3.59 MOROGORO Numberof Households Reporting Food Insufficiency Numberof Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency RESULTS 95 DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 96 MOROGORO PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. 4.2 District Profiles Thee following district profiles highlight the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Kilosa Kilosa district has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kilosa district is Annual Crop Farming, followed by Off farm Income and tree/forest resources. However, the district ranked third in percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kilosa has a relatively high percent of female headed households (22.9%) and it has one of the second lowest average age of the household head. With an average household size of 4.3 members per household it is average for the region. Kilosa has a comparatively low literacy rate (fifth in the region) among smallholder households and this is reflected by the low level of school attendance in the region. The literacy rate for the heads of household is also moderately good (fifth in region). It has the smallest utilized land area per household (1.8ha) and the allocated area is fully utilised indicating a high level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the fourth lowest planted area per household (1.8ha) attributed to the high number of smallholders in the district. The district is important for maize production in the region with a planted area of over 72,420ha, however the planted area per household is the highest in the region. Paddy production is not important with a planted area of only 13,001 hectares and the production of bulrush millet and finger millets were very small. Kilosa is the only district in the region that produces wheat (238ha). Cassava production is low accounting for 11 percent of the quantity harvested in the region. The district has a large planted area of sweet potatoes (1,666 ha) and it produces irish potatoes and yams in small quantities. The production of beans in Kilosa is much higher than in other districts in the region with a planted area of 7,813ha. Oilseed crops are important in Kilosa accounting to (49 percent) of total production in the region. Vegetable production is important in the district. It has the largest planted area with pumpkins, tomatoes and onions (277 ha, 1,278 ha and 544 ha DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 respectively) than other districts in the region and accounts for 62 percent of the pumpkins production, 18 percent of the tomatoes production and 71 percent of the onions production in the region. Traditional cotton is the only cash crop grown in the district. Compared to other districts in the region, Kilosa has a moderate planted area with permanent crops which is dominated by sugarcane (2,588 ha), banana (1,961 ha) and mango (1,433 ha) and coconut (1,397 ha). Other permanent crops are grown small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is very small, however district differences exist. Kilosa has the largest planted area with improved seed in Morogoro region and this is due to the higher planted area of vegetables. The district has the largest planted area with Farm yard manure compared to other districts in the region; Kilosa district has a moderate level of insecticide use. The use of fungicides was second high compared to other districts. It has the largest area with irrigation compared to other districts with 17,255 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage is in locally made traditional structures; however the proportion of households storing crops in the district is lower than other districts in the region. The district has the largest number of households selling crops, however for those who did not sell, the main reason for not selling is open market price too low. Kilosa district is the fourth district in the region with households processing crops and is almost all done by neighbour machine. The district also has a higher percent of households selling processed crops to marketing cooperatives than other districts and no sales are to secondary market and farmers association. Although very small, access to credit in the district is to male only and the main sources are commercial bank, trader/trade store and religious organisations/NGO/ projects. A comparatively larger number of households receive extension services in Lushoto and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in KIlosa (with 604 planted trees) and is mostly Gravellis with some Senna spp and Leucena spp. Small proportion of households with erosion control and water harvesting structures is found in Kilosa district and is mostly erosion control bunds, however it also has the highest number of vetiver grass strips than other districts. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat production is higher compared to other districts, however it has moderate population of sheep in the region. It has the second largest number of pigs and with the highest number of chickens in the region. The district has the highest number of layers in the region. The district has the highest number of ducks and rabbits in the region. Donkeys were not found in the district. The highest number of households reporting Tsetse and tick problems was in Kilosa district and it had the largest number of households de-worming livestock. The use of draft animals in the district is very small and small number of households practice fish farming, however the district has the third largest number in the region. DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 It has amongst the best access to all weather road and primary schools to other districts. However, it has one of the worst access to secondary school, secondary school, health clinic and regional capital Kilosa district has the highest percent of households with no toilet facilities, bicycles and mobile phones. It has the third highest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has almost equal number of households with grass roofs and iron sheets (39%) each. The most common source of drinking water is from surface water. It has high percent of households having two and three meals per day compared to other districts and the lowest percent with one and four meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom or never had problems with food satisfaction. 4.2.2 Morogoro Rural Morogoro Rural district has the fourth largest number of households in the region and it has a second highest percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Morogoro Rural district is Annual Crop Farming, followed by Off farm Income. The district has the highest percent of households with no off-farm activities although it has the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Morogoro Rural has the second highest percent of female headed households (21.8%) and it has one of the highest average age of the household head in the region. With a household size of 5 members per household it is average for the region. Morogoro Rural has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. The literacy rate for the heads of household is also high like other districts in the region. It has a moderate utilized land area per household (1.6ha) and 90 percent of the allocated area is currently being utilised. The district has the fourth largest planted area in the region and the fifth largest planted area per household (1.4ha) The district is important for maize production in the region with a planted area of over 32,425 ha, and the planted area per maize growing household is the lowest in the region. The district has a moderate planted area of paddy in the region with 15,910 hectares, however the district has the largest area under sorghum in the region (7,028 ha). Cassava production is high, accounting for 29 percent of the quantity harvested in the region. The production of beans in Morogoro Rural district is the third largest district in the region with a planted area of 1,262ha however the production of cowpeas is the highest than in other district in the region, with a planted area of 1,953ha. Morogoro Rural district has the largest simsim planted area in Morogoro Rural region with a planted area per simsim growing household of 0.47 ha. Vegetable production is moderately important in the district. It has the third largest planted area with tomatoes, chillies and cabbage (1,214 ha, 135 ha and 133 ha respectively) Traditional cash crop (e.g. tobacco) is grown in very small quantities. Compared to other districts in the region, Morogoro Rural has the second largest planted area with permanent crops which is dominated by coconut (5,086 ha), orange (2,776 ha), banana (2,722 ha) pineapple (2,371 ha) and jack fruit 2,214 ha. Mango, coffee and sugarcane are also grown in smaller quantities. DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 As with other districts in the region, most land clearing is done by hand slashing; however there is a substantial area with no land clearing indicating bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Morogoro Rural has the fourth largest planted area with improved seed in the region with a least proportion of households using improved seeds. The district has the fourth highest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with compost manure. Compared to other districts in the region, Morogoro Rural district has a moderate level of insecticide use. The use of fungicides and herbicides is relatively low. It has the third largest area with irrigation compared to other districts with 13,529 ha of irrigated land. The most common source of water for irrigation is from canal using hand bucket and gravity methods. The most common method of crop storage in Morogoro Rural district is in sacks/open drum, however the proportion of households storing crops is relatively high. Morogoro Rural has slightly high number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Morogoro Rural is among the districts with the highest percent of households processing crops in Morogoro region and is almost all done by neighbours machine. The district also has the highest percent of households selling processed crops to neighbours than other districts and no sales are to marketing cooperative, large scale farms and trader at farm. Access to credit in the district is mainly to men, however women accounts to 35 percent of household that have access to credits. A comparatively small number of households receive extension services in Morogoro Rural district and all of this is mainly from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is less important in Morogoro Rural (with 499 planted trees) and is mostly Kyaya and Senna spp. The third highest proportion of households with erosion control and the second with water harvesting structures and is mostly terraces and water harvesting bunds, however it also has the a number of tree belts and vetiver grass. The district has the fifth largest number of cattle in the region and they are almost all indigenous. Goat production is high compared to other districts; however it has the second lowest population of sheep in the region. It has a moderate number of pigs in the region and a moderate number of chickens. It has a moderate number ducks with no rabbits and donkeys. A number of households reported tsetse and tick problems and it has the second lowest number of households de-worming livestock. Draft animals are not used in the district. A small number of households practice fish farming, however the district has the second largest number in the region. It has amongst the best worst access to secondary schools, secondary market and among the best access to primary schools compared to other districts. However, it has one of the worst access to regional capital. The percentage of households without toilet facility in Morogoro Rural district is very low. It is amongst the districts with the lowest percent of households owning wheel barrows, vehicles, bicycles, and land line phones. Though small, the district has the largest number of households using mains electricity in the region. The most common source of energy for DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is grass/leaves (63%), however it has a moderate percent of households with iron sheet roofing (31%) compared to most other districts. The most common source of drinking water is from unprotected well. It is one of the districts with the highest percent of households having two meals per day. The district had fairly moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Kilombero Kilombero district has the second largest number of households in the region and it has a third highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. Household with livestock only and pastoralists were not found in the district. The most important livelihood activity for smallholder households in Kilombero district is Annual Crop Farming, followed by off farm income. However, the district has the fourth highest percent of households with no off-farm activities and the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kilombero has the lowest percent of female headed households (13.5%) and it has one of the highest average age of the household head in the region. With an average household size of 5.0 members per household it is slightly higher than average for the region. Kilombero district has the highest literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The land area utilized per household (1.9ha) is the second highest in the region and 78 percent of the allocated area is currently being utilized which is the lowest for the region. The district has the third largest planted area in the region, and the forth largest planted area per household (0.87ha in the long rainy season and 0.72ha in the short rainy season). The planted area in the long rainy season is almost double than that of the short rainy season. The district is most important for paddy production in the region with a planted area of over 53,096 ha and the planted area per household is 1.2 ha which is above average for the region. Maize production is moderate important with a planted area of only 22,810 hectares, however it is the fourth highest in the region. Sorghum production is less important with a planted area of only 815 ha and is the fourth highest in the region. Irish potatoes and wheat are not produced in the district. The district has the fourth largest planted area of cassava accounting for 13 percent of the cassava planted area in the region. The production of beans in Kilombero district is much lower than in other districts in the region with a planted area of 74ha. Oilseed crops are less important in Kilombero with 16 percent of the groundnuts grown in the district. Vegetable production is not important and tobacco is not grown in the district. Permanent crops are moderate important in Kilombero district (14% of the total permanent crop planted area in Morogoro region ) and is the fourth highest important district in the region. The most prominent permanent crops in the district include sugarcane (5,086 ha), banana (2,776 ha), orange (2,722 ha) and mango (2,371 ha). It is the only district that produces malay apple (74 ha) and it has the highest area with sugarcane in the region (5,086 ha). Other permanent crops are grown in small to medium quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however small amount of land preparation is done and tractor and oxen. DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 The use of inputs in the region is very small, however district differences exist. Kilombero has the smallest planted area with improved seed in Morogoro region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and mostly is with inorganic fertiliser. Compared to other districts in the region, Kilombero district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively high. It has the fourth largest area with irrigation in the region with 9,019 ha of irrigated land. The most common source of water for irrigation is from rivers and wells and almost all water application is by gravity and using hand bucket. The most common method of crop storage in Kilombero is sacks/open drum, and the proportion of households not storing crops in the district is the lowest for the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Kilombero district has a second highest percent of households processing crops in the region and is almost done by machine from neighbours. Small quantities of processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Kilombero district and almost all of this is from the government. The quality of extension services was rated good by the majority of the households. Tree farming is less important in Kilombero district (with 240 planted trees) and is mostly Senna Spp with some Tectona Grandis and Gravellis. The least proportion of households with water harvesting bunds is found in Kilombero district and it also has the second least number of erosion control bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is small compared to other districts. It has the second least number of pigs in the region and the second largest number of chickens, all of which are indigenous. Virtually layers are the only improved chicken found in the district. The district has the third largest number of ducks and rabbits and turkeys are not found in the district. A small number of households reported tsetse and tick problems in Kilombero district. A relative big amount of de-worming of livestock is practiced in the district no draft animals are used. Fish farming is practiced by a small number of households, however the district has the third largest number in the region. It has amongst the best access to primary school and all weather road compared to other districts. However, it has one of the worst accesses to secondary school, health clinic, secondary market and the regional capital. The percentage of households without toilet facility in Kilombero district is low for the region, however it has the second highest percent of households with no toilet facilities. It has the lowest percent of households owning land line phones, vehicles and Tv/video and wheel barrow. It has the second highest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (60%) and only 37 percent of households have iron sheet roofing. The most common source of drinking water is from unprotected wells. Thirty eighty percent of the households in the district reported having one or two meals per day and only one percent of the households reported having more than three meals per day. The district had a moderate percent of households that did not eat meat and a small percent DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 of household that did not eat fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Ulanga Ulanga district has the least number of households for the region and it has the second smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. Household with livestock only and pastoralists were not found in the district. The most important livelihood activity for smallholder households in Ulanga district is annual crop farming followed by off farm income. It has the lowest percent of households with no off-farm activities and the fourth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Ulanga district has a relatively high percent of female headed households (20.5%) and it has one of the highest average age of the household head. With an average household size of 5.2 members per household it is higher than the average for the region. Ulanga district has a comparatively lowest literacy rate among smallholder households and this is reflected by low level of school attendance in the region. It has the fourth largest utilized land area per household (1.8 ha) and only 85 percent of the allocated land area is utilised. The total planted area is the second smallest in the region however it has the second highest planted area per household (0.63ha) in the long rainy season and 0.78ha in the short rainy season. Ulanga district is less important for maize production in the region with a planted area of only 16,388 ha, and the planted area per household is among the lowest in the region. Paddy production is the second important in the region with a planted area of 30,662 hectares and the production of sorghum is small. Cassava and bean production in Ulanga district was small and Irish potato and wheat are not grown. Oilseed crops and vegetables are not important in the district however, whist the district has second smallest planted area with tomatoes it is the least in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are grown in small quantities in the district. Compared to other districts in the region, Ulanga district has the second smallest planted area with permanent crops (5% of total permanent crop planted area) which is dominated by banana (2,573 ha), mango (1,330 ha) and coconut ((1,049 ha). Medium areas of pawpaw, sugarcane, palm oil are also grown while other cash crops are grown in small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. The use of inputs in the region is very small, however district differences exist. Ulanga district has among the smallest planted area with improved seed; however it has the second highest planted area per household in the region. The district also has the smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 of this is with inorganic fertiliser. Compared to other districts in the region, Ulanga district has a moderate area planted with insecticide but has the second highest percent of the total planted area in the region. The percent of planted area with herbicides is the second highest in the region and is amongst the lowest for fungicide and pesticide. It has one of the smallest area of irrigation 5,805 ha. The most common source of water for irrigation is from rivers using hand buckets/Bucket. Watering cans are the most common means of irrigation water application. The most common method of crop storage is in sacks/open drum, however the proportion of households not storing crops in Ulanga district is the second lowest in the region. The number of households selling crops in the district is among the highest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The second smallest percent of households processing crops in the region is found in Ulanga district and processing is mostly done by neighbours machine. The district has the fourth largest number of households processing crops on farm by machine. It also has the fourth largest number of households processing crops on farm by hand. Most households that sell crops sell to local market/trade store and no sales are to secondary market nor farmers association. Access to credit in the district is very small. Although small, Ulanga has the highest percent of households receive extension services in the region and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Ulanga district (with 2,168 planted trees) and all of them are Gravellis. The largest proportion of households in Ulanga district use erosion control bunds for erosion control. Ulanga district has the highest number of cattle in the region and most of them are indigenous. It is one of the districts with the fourth highest number of goats in the region. Ulanga district has the highest number of sheep in the region and is also one of the districts with the smallest number of pigs and chicken, however it is the only district with broilers in the region. The district has the highest number of turkeys, moderate number of ducks, small number of rabbits and donkeys are not found in the district. The district has the highest percentage of households reported Tsetse and tick problems and it had one of the highest number of households de-worming livestock. Although small, the use of draft animals in the district is the highest and amongst the four regions that practice fish farming Ulanga district is the least. It is amongst the districts with the best access to secondary schools, primary schools, feeder roads, all weather roads, health clinics, hospitals, regional capital, tarmac roads and tertiary markets compared to other districts. However, it has the worst access to primary and secondary markets. Ulanga district has a small number of households with no toilet facilities. The district has low percent of households owning wheel barrows, vehicles and television/video, land line, bicycles and mobile phones and it has high percent of households with radio and the second highest with irons. It has the lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the largest percent of households with grass roofs with only 23 percent of households having iron sheets. The most common source of drinking water is protected well and it has the second highest percent of households having two or three meal per day compared to other districts and the lowest percent with 3 meals per day. The DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 district had the highest percent of households that did not eat meat during the week prior to enumeration but has the second lowest percent of households that did not eat fish. Most households seldom had problems with food satisfaction. 4.5 Morogoro Urban Morogoro Urban district has the second smallest number of households in the region and it has the lowest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Morogoro Urban district is annual crop farming followed by tree and forest resources, and permanent crop farming. The district has amongst the lowest percent of households with no off-farm activities and the second smallest percent of households with more than one member with off- farm income. Compared to other districts in the region, Morogoro Urban has a second smallest percent of female headed households (17.4%) and it has one of the highest average age of the household head. With an average household size of 5.2 members per household it is slightly lower than the regional average. Morogoro Urban has the second highest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the lowest in the region. It has one of the smallest utilized land area per household (1.5 ha) which is slightly lower than the regional average of 1.8 ha per household. The district has smallest planted area in the region, however it has the fourth highest planted area per household (.63 ha) in the long rainy season. The district is not important for maize production with a planted area of 2,889 ha, however the planted area per household is second lowest in the region. Paddy production is also not important with a planted area of only 497 hectares and the production of sorghum is very small. Wheat and finger millet are not grown in the district. The district has the lowest percent of cassava planted area in the region and it has virtually no Irish with small quantities of sweet potatoes. The production of beans in Morogoro Urban district is the second smallest in the region with a planted area of 1,116 ha and oil crops are not important in the district. Vegetable production is also not important in the district; however the district has second lowest planted area per tomato growing household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Morogoro Urban has a small planted area with permanent crops (571 ha) which is dominated by banana (950 ha) and pigeon pea (319ha), mango (246 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Morogoro Urban has one of the smallest planted area with improved seed in Morogoro region however it has the highest percent of planted area using improved DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 seed. The district has the smallest planted area with fertilizers and most of this is with inorganic fertiliser with small quantities of farm yard manure and compost. Compared to other districts in the region, Morogoro Urban district has the lowest percent of its planted area with insecticides in the region. The use of fungicides, herbicides and pesticide was lowest in the region. It has the smallest planted area with irrigation in the region with only 1,596 ha of irrigated land. Rivers, wells boreholes and canals is used as the source of irrigation water while gravity and hand bucket were the only methods for obtaining water. Buckets/Water cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in locally sacks/open drum; however the proportion of households not storing crops in the district is the highest in the region. The district has the high number of households selling crops and the main reason for not selling is insufficient production. Morogoro Urban district has the highest percent of households processing crops on neighbours machine and a small percent of households selling processed crops mainly to neighbours and local market/trade store. No sales were made to secondary market and farmers association. Access to credit is moderate with women having the second highest percent in the region and the main reason for not using credit is lack of awareness. A comparatively small number of households receive extension services in Morogoro Urban district and all of this is from the government. The quality of extension services was rated between good and very good by most of the households. Tree farming is not important in Morogoro Urban (with only 1.084 planted trees) and is mostly with Senna Spp, Cyprus Spp with some Gravellis, Eucalyptus spp and Melicia excelsa. The smallest number of erosion control and water harvesting structures is found in Morogoro Urban district and they are erosion conrol bunds and terraces. The district has the smallest number of cattle in the region and they are mostly all indigenous. Goat, sheep and pig production is smallest in the region. It has a comparatively smallest number of chickens. Small numbers of ducks, turkeys and rabbits are found while donkeys are not found in the district. A moderate number of households reported Tsetse and tick problems in Morogoro Urban district and has the moderate number of households de-worming livestock. The use of draft animals in the district is non existent and no fish farming is practiced in the district. It is amongst the districts with the best access to primary schools and all weather roads however it has one of the worst access to regional capital, secondary markets, health clinics, primary markets, and tarmac roads. Morogoro Urban district has the lowest percent of households with no toilet facilities. The district has the largest percent of households owning radios and Irons and very small number of households reported ownership of vehicles, mobile phones, wheel barrows and televisions/videos. It has the lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the smallest percent of households with grass roofs and the highest 63 percent of households having iron sheets. The most common source of drinking water is from surface water, unprotected spring and piped water. It has a moderate percent of households having two or three meal per day compared to other districts. The district had the fourth highest percent of households that did not eat meat during the week prior to enumeration, however it is the least districts with percent of households that did not eat fish during the week. Most households in the district seldom had problems with food satisfaction. DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 4.6 Mvomero Mvomero district has a moderate number of households in the region and it has the third highest percents of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mvomero district is Annual Crop Farming, followed by tree/forest resources, off farm income and keeping/herding. The district has the second lowest percent of households with no off-farm activities however it has the third highest percent of households with more than one member with off- farm income. Compared to other districts in the region, Mvomero has the third highest percent of female headed households (20.8%) and it has one of the moderate average age of the household head. With an average household size of 4.7 members per household it is the average for the region. The literacy rate among smallholder households in Mvomero is low compared to other districts in the region and associated with this is a number of household members who have never attended school. It has the largest utilized land area per household (1.9 ha) in Morogoro region. The total planted area is the second largest in the region and has the largest planted area in the long rainy season. However the planted area per household in the long rainy season was 0.68ha compared to 0.63 ha per household in the short rainy season. The district is the second most important for maize production in the region with a planted area of 48,158 ha and the planted area per household is the second largest in the region. Paddy production is third for the region with a planted area of 13,360 hectares and the district has the third planted area per paddy growing household. Production of sorghum is low and there is no production of finger millet in the district. The district also has the largest planted area of beans (9,422 ha), cow peas (1,464 ha) and field peas (872 ha), however very little green gram and chick peas are produced. Cassava production is relatively high accounting for 29 percent of the total cassava planted area in the region. Oilseed crops are important in Mvomero district and has the fourth largest planted in the region. The area under sunflower is the second largest in the region (235 ha) and the third largest planted area of simsim. Vegetable production is not important in the district; however tomatoes, cabbage, onion, chillis, amaranths, carot, cucumber and pumpkins are produced in very small quantities. Mvomero is among the three districts that cultivates cotton although the planted area is small. Compared to other districts in the region, Mvomero has the highest planted area with permanent crops which is dominated by mandarine (3,477 ha), sugarcane (2,795 ha), mango (1,983 ha) banana (1,256 ha) and pigeon peas (1,071 ha). Other permanent crops are either not grown or are grown in small quantities. Most land clearing is done by hand slashing, however it has the highest Planted Area with “no land clearing” indicating the presence of a large area of bare land before cultivation. It has also the second largest area of bush clearance in the region. Most land preparation is done by hand, however it has the highest planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Mvomero has the highest planted area with improved seed in Morogoro region. The use of fertilizer is very small, however inorganic fertilizer is mostly used followed by farm yard manure and compost. Compared to other districts in the region, Mvomero district has the second largest DISTRICT PROFILES. ___________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 percentage of the planted area in the district with fungicides application and the highest amount of pesticide was used. It has the largest area with irrigation with a planted area of 17,481 ha under irrigation. The most common source of water for irrigation is from river and canal using gravity. Buckets/Watering cans is the only means of irrigation water application in the district. The most common method of crop storage is in sacks/open drum; however the proportion of households not storing crops in the district is moderate to low when compared to other districts in Morogoro region. The district has a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Mvomero is among the districts in Morogoro region with a high percent of households processing crops and is mostly done using neighbours machines. The district also has a small percent of households selling processed crops mostly to neighbours and traders on farm. Access to credit by households in the district is small. A comparatively small number of households receive extension services in Mvomero district and mostly from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming is the most important in Mvomero district compared to other district (with 17,103 planted trees) and are mostly Gravellis, Calophylum Inophyllum, Cyprus Spp with some Eucalyptus Spp and Moringa Spp. A small proportion of households with erosion control and water harvesting structures is found in Mvomero district and is mostly erosion control bunds, water harvesting bunds and tree belts, It also has a small number of drainage ditches for erosion control. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat population is also the second largest in the region, however it has one of the second largest population of sheep in the region. The district has the highest number of pigs in the region but it has the third largest chicken population, all of which are indigenous. The second largest numbers of ducks, third with turkeys and is the only district with donkeys and rabbits are also found in the district. It has the third highest proportion of households reporting Tsetse and second highest with tick problems in the region and it had a moderate to low number of households de-worming livestock compared to other districts. Draft animals are used to a very small number of household and fish farming is not practiced. It is amongst the districts with the best access to primary schools and all weather roads, however it has one of the worst access to regional capital, secondary school, tertiary markets, tarmac roads, feeder roads, health clinics and primary markets. Mvomero district has the fourth highest percent of households with no toilet facilities. Though small, it has the second highest percent of households with radio, however it is among the districts with a low percent of households owning vehicles and land line phones. It has a small number of households using mains electricity. The most common source of energy for lighting is the wick lamp and almost all households use firewood for cooking. The district has a moderate to high percent of households with grass roofs with and 29 percent of households have iron sheet roofing. The most common sources of drinking water are from unprotected wells and piped water. It has the highest percent of households having three meals per day compared to other districts and moderate percent with one or two meals per day. The district has a moderate to high percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. APPENDIX II 108 4. APPENDICES Appendix I Tabulation List ..............................................................................................................109 Appendix II Tables ........................................................................................................................... 124 Appendix III Questionnaires............................................................................................................... 293 APPENDIX II 109 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD………………………………………………………………………………… 124 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year....................125 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year.....................125 NUMBER OF AGRICULTURE HOUSEHOLDS.......................................................................................................................126 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year ........................................................................................................126 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District ........................................................................................................................................126 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES .................................................................................................128 3.1a First Most Importance........................................................................................................................................................129 3.1b Second Most Importance...................................................................................................................................................129 3.1c Third Most Importance......................................................................................................................................................129 3.1d Fourth Most Importance ....................................................................................................................................................129 3.1e Fifth Most Importance .......................................................................................................................................................129 3.1f Sixth Most Importance ......................................................................................................................................................129 3.1g Seventh Most Importance..................................................................................................................................................129 HOUSEHOLDS DEMOGRAPHS .................................................................................................................................................132 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) .............................................................................................................................................................................133 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (Column %).......................................................................................................................................................................133 3.4 Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year..........................134 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year .....................................................................134 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year................................................................................................................................................134 3.7 Number of Agricultural Household Members by Main Activity and District .................................................................134 cont… Number of Agricultural Household Members by Main Activity and District .....................................................135 cont… Number of Agricultural Household Members by Main Activity and District .....................................................135 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year.................................................................................................................................................135 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................135 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................136 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................136 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year.................................................................................................................................................136 APPENDIX II 110 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year...........................................................................................................................137 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year........................................................................................137 3.12 Number of Heads of Agricultural Households by Maximum Education Level Attained and District, 2002/03 Agricultural Year` ...............................................................................................................................................137 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District...............................................................137 3.14 Time Series of Male and Female Headed Households .....................................................................................................138 3.15 Literacy Rate of Heads of Households by Sex and District..............................................................................................138 LAND ACCESS/OWNERSHIP .....................................................................................................................................................140 4.1 Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year...........................................................................................................................................141 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year..............................142 LAND USE........................................................................................................................................................................................144 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ...............................................................................................................................................................145 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year............................................................................................................................146 5.4 Number of Agricultural Households by whether they consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ....................................................................................146 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year........................................................................146 ACCESS AND USE OF RESOURCE ...........................................................................................................................................148 6.1 Average (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year ..............................................................................................149 Cont……….Average (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year...............................................................................................149 6.2 Number of Agriculture Household with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year............................................................................................................................150 6.3 Number of Agriculture Household with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year............................................................................................................................150 6.4 Number of Agriculture Household with Access Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year............................................................................................................................151 6.5 Number of Agriculture Household with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year............................................................................................................................151 6.6 Number of Agriculture Household with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year...........................................................................................................................151 6.7 Number of Agriculture Household with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year...........................................................................................................................152 6.8 Number of Agriculture Household with Access to Forest for Bees Products by type of Utilization and District, 2002/03 Agricultural Year.................................................................................................................................................152 6.9 Number of Agriculture Household with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year.................................................................................................................................................152 APPENDIX II 111 6.10 Number of Agriculture Household with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year.................................................................................................................................................152 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS .....................................................154 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District. ................................................155 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District.............................................................155 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Morogoro Region...............................................................................................................................................................156 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Morogoro Region .....................................................................157 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Morogoro.......................................................................................................................158 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Wet & Dry Season, Morogoro..................................................................................158 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year................................................................................................................158 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................................................................................159 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. ...................................................................................................159 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. ...................................................................................................159 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. ...................................................................................................159 ANNUAL CROP & VEGETABLES PRODUCTION DRY SEASON......................................................................................160 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District – DRY SEASON, Morogoro Region. ..................................................................................................................................161 7.1b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - DRY SEASON, Morogoro Region ..........................................................................161 7.1c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Dry Season, 2002/03 Agriculture Year, Morogoro Region .....................................................................161 7.1d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Dry Season...................................................................................................161 7.1e Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Dry Season...................................................................................................162 7.1f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season..................................................................................................162 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year – Dry Season...........................................................................................................162 ANNUAL CROP & VEGETABLES PRODUCTION.................................................................................................................162 7.2g Planted Area and Number of crop Growing Households in Long Rainy Season During 2002/03 Crop Year by Method of Land Clearing By Crop.............................................................................................................162 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year ...............................................................................................................164 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year ...............................................................................164 APPENDIX II 112 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year ................................................................................................................164 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................165 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrush millets Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................165 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................165 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................166 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................166 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................166 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................…167 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................167 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyam Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................167 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................168 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................168 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................168 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................169 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................170 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................169 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................170 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................170 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of SimSim Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................170 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................171 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor Oil Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................171 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya Beans Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................................................171 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................172 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................172 APPENDIX II 113 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onoin Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................172 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................173 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................173 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................173 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................174 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................174 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................174 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................175 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................175 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................175 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................176 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................176 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................176 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year ........................................................................................................................177 PERMANENT CROPS ...........................................................................................................................................................................178 7.3 Production of Permanent Crops by Crop Type and District – Morogoro.................................................................................179 7.3 Production of Permanent Crops by Crop Type and District – Morogoro.................................................................................180 7.3 Production of Permanent Crops by Crop Type and District – Morogoro.................................................................................181 7.3 Production of Permanent Crops by Crop Type and District ....................................................................................................182 AGROPROCESSING..............................................................................................................................................................................184 8.0a Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year............................................................................................................................................185 8.0b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year .......................................................................................................................................................................185 8.1.1a Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Morogoro Region ......................................................................................................................................186 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Morogoro Region...............................................................186 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Morogoro Region.......................................................................................................................................................................188 APPENDIX II 114 8.1.1d Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, and District ................................................................................................................188 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, and District ...................................................................................................188 8.1.1f Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, and District.............................................................................................................................188 8.1.1g Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, and District.............................................................................................................................188 MARKETING ..................................................................................................................................................................................190 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Morogoro Region......................................................................................................................191 10.2 Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Morogoro Region .......................................................................................191 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Morogoro Region......................................................................................................191 IRRIGATION/EROSION CONTROL .........................................................................................................................................192 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District..............................................................................................................................................193 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year........................................193 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year..................................................................................................................193 11.4 Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year .....................................................................................................................................193 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year ......................................................................................................194 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District ...........................194 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year...........................................................................................................................194 ACCESS TO FARM INPUTS ........................................................................................................................................................196 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year ...............................................................................................................................................................197 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year .....................................................................................................................................197 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year........................................................................................................................197 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year........................................................................................................................197 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year ......................198 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year .....................................................................................................................................198 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year............................................................................................................................198 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year.................................................................................................................................................199 APPENDIX II 115 cont….. Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ……………………………………………………………………………………...……199 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year.................................................................................................................................................199 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year.................................................................................................................................................199 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year........................200 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year......................200 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................................................................................201 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year................................................................................................................................................201 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year.................................................................................................................................................201 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides / Fungicides by District, 2002/03 Agricultural Year.................................................................................................................................................202 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year.................................................................................................................................................202 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year..................................................................................................................................202 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year..................................................................................................................................202 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year…………………………………………………………………..……………..203 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year...................................................................................................................................203 12.1.22 Number of Agricultural Households Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year...................................................................................................................................203 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year...................................................................................................................................203 12.1.24 Number of Agricultural Households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................................204 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year..................................................................................................................................204 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year...................................................................................................................................205 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year...................................................................................................................................205 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year...................................................................................................................................206 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year...................................................................................................................................206 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................................207 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................................................................................207 APPENDIX II 116 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year...................................................................................................................................207 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year..................................................................................................................................208 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year...................................................................................................................................208 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year...................................................................................................................................208 12.1.36 Number of Agricultural Households and Quality of Improved Seedsby District, 2002/03 Agricultural Year ...............................................................................................................................................................208 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................................................................................209 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year..................................................................................................................................209 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year...................................................................................................................................209 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year.............................................................................................................................209 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year ...............................................................................................................................................................210 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ...............................................................................................................................................................210 ACCESS TO EQUIPMENT ...........................................................................................................................................................211 12.2.1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03.........................................................211 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year .................................................................................................................................................211 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District ...............................................................................................................................................................212 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District......................................................................................................................................................212 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District .........................212 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District......................................................................................................................................................213 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District ...................................................................................................................................213 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District...................213 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District ...............................................................................................................................................................214 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District...............................................................................................................................................214 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District ...............................................................................................................................................214 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District ...................................................................................................................................215 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District .........................................215 APPENDIX II 117 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District.....................215 12.2.15 Number of Agricultural Households Owning OXEN by Source of Finance and District ................................................216 12.2.16 Number of Agricultural Households Owning OX Plough by Source of Finance and District .........................................216 12.2.18 Number of Agricultural Households Owning OX CART by Source of Finance and District..........................................216 12.2.19 Number of Agricultural Households Owning TRACTOR by Source of Finance and District.........................................217 12.2.20 Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District .......................217 12.2.21 Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District......................217 12.2.22 Number of Agricultural Households Owning THRESHERS/SHELLERS by Source of Finance and District...........................................................................................................................................................217 AGRICULTURE CREDIT.............................................................................................................................................................218 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year................................................................................................................................219 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year.................................................................................................................................................219 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year................................................................................................................................219 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year................................................................................................................................219 TREE FARMING AND AGROFORESTRY ...............................................................................................................................220 14.1 Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Morogoro Region...............................................................................................................................................................221 cont… ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, ..............................................................................................................................221 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Morogoro Region……………………………..221 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District ............................223 CROP EXTENSION........................................................................................................................................................................224 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Morogoro Region ...................................................................................225 15.2 Number of Households by Quality of Extension Services and District During the 2002/03 Agricultural Year, Morogoro Region...........................................................................................................225 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ................................................................................................225 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................226 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region......................................226 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region..........................226 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................227 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................227 APPENDIX II 118 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region .........................................227 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region......................................228 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region..........................228 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................228 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................229 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................229 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................229 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................230 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Morogoro Region ..........................................230 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Morogoro Region................................................230 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Morogoro Region................................................231 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Morogoro Region................................................231 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Morogoro Region..................................231 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Morogoro Region..................................232 ANIMAL CONTRIBUTION TO CROP PRODUCTION..........................................................................................................234 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Morogoro Region............................................................................................235 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Morogoro Region............................................................................................235 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Morogoro......................................................................................................................235 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Morogoro Region...............................................................................................................................................................235 CATTLE PRODUCTION...............................................................................................................................................................236 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Morogoro Region...............................................................................................................................................................237 18.2 Number of Cattle By Type and District as of 1st October, 2003......................................................................................237 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003.....................................................................................................................................237 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003........................................................................237 18.5 Number of Indigenous Cattle by Category and District as on 1st October, 2003............................................................238 18.6 Number of Improved Beef Cattle by Category and District as on 1st October, 2003......................................................238 APPENDIX II 119 18.7 Number of Improved Dairy Cattle by Category and District as on 1st October, 2003....................................................238 18.8 Number of Cattle by Category and District as on 1st October, 2003...............................................................................238 GOATS PRODUCTION .................................................................................................................................................................240 19.1 Total Number of Goats by Type and District as on 1st October, 2003 ............................................................................241 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ....................................................................241 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District.........................................241 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 ....................................................242 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003.................................................242 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ..........................................................242 SHEEP PRODUCTION..................................................................................................................................................................244 20.1 Total Number of Sheep by Breed and on 1st October 2003.............................................................................................245 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003...................................................245 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03......................................................................245 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 ............................................................245 20.5 Total Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October ....................................246 20.6 Total Number of Improved Sheep by Category of Sheep and District as of 1st October ...............................................246 20.7 Total Number of Sheep by Category of Sheep and District as of 1st October.................................................................246 PIGS PRODUCTION......................................................................................................................................................................248 21.1 Number of Households and Pigs by Herd Size on 1st October 2003...............................................................................249 21.2 Number of Households and Pigs by District on 1st October 2003...................................................................................249 21.3 Number of Pigs by Type and District on 1st October, 2003.............................................................................................249 LIVESTOCK PESTS AND PARASITE CONTROL..................................................................................................................250 22.1 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year .......................................................................251 22.2 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock..............................................................251 22.3 Number and Percent of agricultural households reporting to have encountered tick problems ` during 2002/03 Agriculture Year by District. ...................................................................................................................251 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year .....................................................................252 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year.......................................................................252 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control During the 2002/03 Agricultural Year and District, 2002/03 Agricultural Year .............................................................252 OTHER LIVESTOCK ....................................................................................................................................................................254 23a Total Number of Other Livestock by Breed and Type .....................................................................................................255 23b Number of households with chicken and Category of Chicken by Flock Size ................................................................255 23c Number of households with chicken and Category of Chicken by Flock Size ................................................................255 APPENDIX II 120 23d Number of Households Rearing and number of Other Livestock by Type and District..................................................255 23e Number of Chicken by Type and District .........................................................................................................................256 LIVESTOCK PRODUCT...............................................................................................................................................................258 25.1 Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year.................................................................................................................................................259 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES .......................................................................................................260 27.1 Number of households by Distance to Nearest Cattle Dip and District ..........................................................................261 27.2 Number of households by Distance to Nearest Spray Raced and District ......................................................................261 27.3 Number of households by Distance to Nearest Hand Powered Sprayer and District .....................................................261 27.4 Number of households by Distance to Nearest Cattle Crush and District.......................................................................262 27.5 Number of households by Distance to Nearest Primary Market and District .................................................................262 27.6 Number of households by Distance to Nearest Secondary Market and District .............................................................262 27.7 Number of households by Distance to Nearest Abattoir and District..............................................................................263 27.8 Number of households by Distance to Nearest Slaughter Slab and District ...................................................................263 27.9 Number of households by Distance to Nearest Hide/ Skin Shade and District...............................................................263 27.10 Number of households by Distance to Nearest Input Supply and District......................................................................264 27.11 Number of households by Distance to Nearest Veterinary Clinic and District...............................................................264 2712 Number of households by Distance to Nearest Village Holding Gound and District.....................................................264 27.13 Number of households by Distance to Nearest Village Watering Point/ Dam and District ...........................................265 27.14 Number of households by Distance to Nearest Drencher and District............................................................................265 FISH FARMING..............................................................................................................................................................................266 28.1a Number of Agricultural Households by Fish Farming and District, 2002/03 Agricultural Year ....................................267 28.2a Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year ..........................267 28.2b Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year……………....267 28.2c Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year…………..267 28.2d Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year........................................................267 LIVESTOCK EXTENSION...........................................................................................................................................................268 29.1a Number of Agricultural Households Receiving Advice By Type of Service Provider and District 2002/03 Agricultural Year.................................................................................................................................................269 29.1b Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year..........................................................................................................269 29.1c Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year................................................................................................................269 29.1d Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year................................................................................................................269 29.1e Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year ..............................................................................................................270 29.1f Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year................................................................................................................270 APPENDIX II 121 29.1g Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year...................................................................................270 29.1h Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year................................................................................270 29.1i Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year...............................................................................................................271 29.1j Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year................................................................................................................271 29.1k Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year................................................................................................................271 29.1l Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year...................................................................................................................................271 29.1m Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year.................................................................................................................................................272 29.1n Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year.................................................................................................................................................272 GOVERNMENT REGULATORY PROBLEMS ........................................................................................................................274 30.1 Number of Agricultural Households by Whether Face Problems with Government Regulation During 2003/04 by District, 2002/03 Agricultural Year...............................................................................275 LABOUR USE..................................................................................................................................................................................276 31.1 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year ..................277 31.2 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year.................278 ACCESS TO INFRASRUCTURE AND OTHER SERVICES ..................................................................................................280 33.1 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year.............281 33.2 Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year ........281 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 002/03 Agricultural Year......281 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year............281 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year.............281 33.6 Number of Agricultural Households by Distance to Districtal Capital and District,2002/03 Agricultural Year...........282 33.7 Number of Agricultural Households by Distance to Feeder Road and District,2002/03 Agricultural Year..................282 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year ........282 33.9 Number of Agricultural Households by Distance to Tarmac Road and District,2002/03 Agricultural Year................282 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year.............282 33.11 Number of Agricultural Households by Distance to Secondary Market and District,2002/03 Agricultural Year..........283 33.12 Number of Agricultural Households by Distance to Tertiary Market and District,2002/03 agricultural year................283 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 agriculture year..............283 33.14 Number of Agricultural Households by Distance to Extension Center............................................................................283 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 agriculture year ..............283 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 agricultural year .......284 33.17 Number of Agricultural Households by Distance to Land Registration Office and District,2002/03 agricultural year .284 APPENDIX II 122 33.18 Number of Agricultural Households by Distance to Livestock Development Center.....................................................284 33.19 Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 agricultural year..................................................................................................................................................284 33.20 Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year.................................................................................................................................................284 33.21 Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year.................................................................................................................................................285 33.22 Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District 2002/03 Agricultural Year.................................................................................................................................................285 33.23 Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year.................................................................................................................................................285 33.24 Number of Agricultural Households by Satisfaction of Using Livestock Development Center ....................................285 HOUSEHOLD FACILITIES .........................................................................................................................................................286 34.1 Number of households reporting average number of rooms and type of Roofing Materials by District 2002/03 Agriculture Year................................................................................................................................287 34.2 Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year.................................................................................................................................................287 34.3 Number of Agricultural Households Reporting Main Source of Energy for Lighting by District 2002/03 Agricultural Year ...............................................................................................................................................288 34.4 Number of Agricultural Households Reporting Main Source of Energy for Cooking by District 2002/03 Agricultural Year.................................................................................................................................................288 34.5 Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District 2002/03 Agricultural Year..................................................................................................................288 34.6 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year..................................................................................289 34.7 Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year .................................................289 34.8 Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 agriculture year ...................................................................................................................289 34.9 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 agriculture year ......................................................................................290 34.10 Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 agriculture year ......................................................................................290 34.11 Number of Agricultural Households Reporting type of TOILET the household normally use by District 2002/03 agriculture year....................................................................................................................................................290 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District...............................................................................................................................................291 34.13 Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 agriculture year......................................................291 34.14 Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year.......................................................................291 34.15 Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agriculture Year .................................................................................292 34.16 Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year.................................................................................................................................................292 APPENDIX II 123 APPENDIX II: CROP TABLES Type of Agriculture Household.................................................................................................................................................................... 124 Number of Agriculture Households...............................................................................................................................................................125 Rank of Importance of Livelihood Activities................................................................................................................................................125 Households Demography...............................................................................................................................................................................132 Land Access/Ownership ................................................................................................................................................................................140 Land Use ................................................................................................................................................................................144 Access and Use of Resource .........................................................................................................................................................................148 Total Annual Crop and Vegetable Production – LONG and SHORT Rainy Seasons.................................................................................154 Annual Crop and Vegetable Production – SHORT Rainy Season ...............................................................................................................160 Annual Crop and Vegetable Production........................................................................................................................................................162 Permanent Crop Production...........................................................................................................................................................................178 Agro-processing ................................................................................................................................................................................184 Marketing ................................................................................................................................................................................190 Irrigation/Erosion Control..............................................................................................................................................................................192 Access to Farm Inputs ................................................................................................................................................................................196 Access to Farm Implements...........................................................................................................................................................................211 Agriculture Credit ................................................................................................................................................................................218 Tree Farming and Agro-forestry....................................................................................................................................................................220 Crop Extension ................................................................................................................................................................................224 Animal Contribution to Crop Production......................................................................................................................................................234 Cattle Production ................................................................................................................................................................................236 Goat Production ................................................................................................................................................................................240 Sheep Production ................................................................................................................................................................................244 Pig Production ................................................................................................................................................................................248 Livestock Pests and Parasite Control.............................................................................................................................................................250 Other Livestock ................................................................................................................................................................................254 Livestock Product ................................................................................................................................................................................258 Access to Functional Livestock Facilities .....................................................................................................................................................260 Fishing Farming ................................................................................................................................................................................266 Livestock Extension ................................................................................................................................................................................268 Government Regulatory Problems ................................................................................................................................................................274 Labour Use ................................................................................................................................................................................276 Access to Infrastructure and other services...................................................................................................................................................280 Household Facilities ................................................................................................................................................................................286 Appendix II 124 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 125 District Rural hosehold involved in Agriculture % of Total rural househ olds Rural households NOT involed in Agriculture % of Total rural househ olds Total rural households % of Total rural househ olds Urban households Total number of Household (from 2002 pop. Census) Number % Number % Number % Number Number Kilosa 73,435 94 4,869 6 78,304 74 27,331 105,635 Morogoro R 53,117 96 2,295 4 55,412 98 1,311 56,723 Kilombero 48,782 93 3,479 7 52,261 71 21,132 73,393 Ulanga 30,908 98 670 2 31,578 85 5,410 36,988 Morogoro U 4,434 90 494 10 4,928 9 49,279 54,207 Mvomero 50,069 97 1,604 3 51,673 89 6,641 58,314 Total 260,746 95 13,411 5 274,157 71 111,103 385,260 Number % Number % Number % Kilosa 60,162 82 371 1 12,902 18 73,435 73,064 13,273 Morogoro 47,421 89 364 1 5,332 10 53,117 52,753 5,696 Kilombero 45,555 93 0 0 3,227 7 48,782 48,782 3,227 Ulanga 27,639 89 0 0 3,269 11 30,908 30,908 3,269 Morogoro Urb 3,779 85 11 0 645 15 4,434 4,423 655 Mvomero 39,666 79 754 2 9,650 19 50,069 49,316 10,403 Total 224,222 86 1,500 1 35,024 13 260,746 259,246 36,524 Total Number of Households Rearing Livestock 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Agriculture, Non Agriculture and Urban Households 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agriculture households by type of household and District during 2002/03 Agriculture Year Crops Only Livestock Only Crops & Livestock Total Number of agriculture Household Total Number of Households Growing Crops Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 126 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Kilosa 57,345 78 4 16,090 22 4 73,435 100 4 Morogoro R 41,550 78 5 11,567 22 5 53,117 100 5 Kilombero 42,217 87 5 6,565 13 5 48,782 100 5 Ulanga 24,582 80 5 6,326 20 4 30,908 100 5 Morogoro Urb 3,663 83 4 771 17 4 4,434 100 4 Mvomero 39,680 79 5 10,390 21 4 50,069 100 5 Total 209,037 80 5 51,709 20 4 260,746 100 5 Kilosa 1 5 4 2 6 7 3 Morogoro R 1 4 5 2 6 7 3 Kilombero 1 4 5 2 6 7 3 Ulanga 1 5 4 2 6 7 3 Morogoro Urb 1 3 5 4 6 7 2 Mvomero 1 5 4 3 6 7 2 Total 1 5 4 2 6 7 3 Fishing / Hunting & Gathering Tree / Forest Resources Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances District 3.0: Number of Agriculture Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agriculture Year Average Household Size Total Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Male Female Livelihood Activity Annual Crop Farming Tanzania Agriculture Sample Census - 2003 Morogoro 127 Appendix II 128 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 129 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 45,647 2,047 1,036 16,941 2,232 0 5,398 Morogoro 39,376 5,008 1,077 5,964 966 0 239 Kilombero 34,252 2,411 738 9,669 1,100 249 482 Ulanga 25,792 156 766 2,595 304 233 1,140 Morogoro Urban 1,689 1,360 61 902 143 55 187 Mvomero 40,841 3,020 618 4,347 497 0 745 Total 187,597 14,002 4,296 40,418 5,241 537 8,192 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 21,590 5,070 10,072 24,430 3,344 386 7,757 Morogoro 9,433 14,576 3,686 20,588 2,914 122 2,635 Kilombero 11,414 4,981 2,455 23,506 757 879 5,035 Ulanga 4,736 2,128 1,229 16,283 1,607 1,003 4,151 Morogoro Urban 2,201 870 168 677 187 33 372 Mvomero 7,129 5,741 11,184 14,716 2,620 0 9,089 Total 56,502 33,367 28,794 100,200 11,430 2,424 29,039 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 4,714 5,731 14,310 12,557 3,486 0 29,013 Morogoro 1,713 7,392 9,201 10,666 3,124 244 19,332 Kilombero 1,325 7,204 6,346 4,580 1,432 1,116 24,892 Ulanga 303 1,907 2,225 6,827 3,998 77 15,037 Morogoro Urban 457 476 571 633 207 45 1,876 Mvomero 745 7,744 7,438 6,032 2,582 251 21,979 Total 9,256 30,455 40,090 41,296 14,828 1,733 112,130 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 905 5,385 14,381 5,573 2,354 228 18,992 Morogoro 733 3,190 10,864 6,490 3,162 122 18,744 Kilombero 719 10,668 11,519 1,325 758 488 12,334 Ulanga 78 3,578 8,483 1,457 1,981 78 7,582 Morogoro Urban 35 373 967 279 158 36 1,652 Mvomero 378 3,593 5,685 2,116 2,090 249 12,406 Total 2,847 26,787 51,899 17,241 10,502 1,200 71,711 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 130 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 0 3,419 3,111 1,394 373 467 7,157 Morogoro 968 3,923 6,482 3,365 4,176 121 6,365 Kilombero 473 6,084 7,944 882 338 372 2,898 Ulanga 0 2,961 4,846 386 151 380 2,230 Morogoro Urban 0 292 766 214 78 20 210 Mvomero 252 2,305 1,367 870 248 121 3,341 Total 1,692 18,985 24,517 7,110 5,365 1,480 22,201 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 0 499 113 250 126 253 482 Morogoro 0 121 1,447 730 960 359 3,625 Kilombero 483 821 744 235 123 118 592 Ulanga 0 607 919 155 304 75 153 Morogoro Urban 11 11 90 12 24 12 38 Mvomero 0 0 118 124 128 0 0 Total 494 2,059 3,431 1,506 1,664 817 4,890 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Kilosa 0 0 0 130 0 0 512 Morogoro 245 0 0 0 0 365 359 Ulanga 0 77 0 0 231 0 0 Morogoro Urban 17 13 13 0 0 0 0 Mvomero 121 0 123 0 0 0 0 Total 382 90 136 130 231 365 871 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census - 2003 Morogoro 131 Appendix II 132 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 133 Number % Number % Number % Less than 4 70,972 50 70,616 50 141,588 100 05 - 09 95,824 51 90,777 49 186,602 100 10 - 14 90,246 51 85,852 49 176,098 100 15 - 19 71,840 52 66,723 48 138,563 100 20 - 24 46,702 45 56,332 55 103,034 100 25 - 29 39,261 42 54,366 58 93,627 100 30 - 34 39,811 48 42,457 52 82,268 100 35 - 39 32,361 48 34,453 52 66,814 100 40 - 44 30,021 53 26,789 47 56,810 100 45 - 49 20,643 47 23,072 53 43,716 100 50 - 54 18,577 48 20,062 52 38,639 100 55 - 59 14,891 56 11,889 44 26,780 100 60 - 64 14,234 50 14,126 50 28,359 100 65 - 69 9,953 54 8,486 46 18,439 100 70 - 74 10,129 61 6,588 39 16,717 100 75 - 79 3,689 54 3,107 46 6,796 100 80 - 84 3,261 65 1,728 35 4,989 100 Above 85 2,037 36 3,700 64 5,737 100 Total 614,454 50 621,124 50 1,235,577 100 Number % Number % Number % Less than 4 70,972 12 70,616 11 141,588 11 05 - 09 95,824 16 90,777 15 186,602 15 10 - 14 90,246 15 85,852 14 176,098 14 15 - 19 71,840 12 66,723 11 138,563 11 20 - 24 46,702 8 56,332 9 103,034 8 25 - 29 39,261 6 54,366 9 93,627 8 30 - 34 39,811 6 42,457 7 82,268 7 35 - 39 32,361 5 34,453 6 66,814 5 40 - 44 30,021 5 26,789 4 56,810 5 45 - 49 20,643 3 23,072 4 43,716 4 50 - 54 18,577 3 20,062 3 38,639 3 55 - 59 14,891 2 11,889 2 26,780 2 60 - 64 14,234 2 14,126 2 28,359 2 65 - 69 9,953 2 8,486 1 18,439 1 70 - 74 10,129 2 6,588 1 16,717 1 75 - 79 3,689 1 3,107 1 6,796 1 80 - 84 3,261 1 1,728 0 4,989 0 Above 85 2,037 0 3,700 1 5,737 0 Total 614,454 100 621,124 100 1,235,577 100 Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (col %) Age Group Sex Male 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 134 Number % Number % Number % Kilosa 255,669 81 59,003 19 314,672 100 M'goro R 209,641 80 53,357 20 262,999 100 Kilombero 215,905 88 29,830 12 245,735 100 Ulanga 132,065 82 28,280 18 160,345 100 M'goro Urb 15,829 83 3,143 17 18,972 100 Mvomero 190,109 82 42,747 18 232,855 100 Total 1,019,217 82 216,360 18 1,235,577 100 Number % Number % Number % Number % Number % Kilosa 186,228 66 4,640 2 359 0 92,427 33 283,654 100 M'goro R 148,357 63 10,338 4 357 0 74,859 32 233,912 100 Kilombero 148,240 69 7,277 3 129 0 58,475 27 214,121 100 Ulanga 89,013 63 4,711 3 154 0 47,599 34 141,477 100 M'goro Urb 11,047 67 530 3 0 0 5,025 30 16,602 100 Mvomero 126,270 62 10,338 5 101 0 67,514 33 204,223 100 Total 709,155 65 37,834 3 1,102 0 345,898 32 1,093,989 100 Number % Number % Number % Number % Kilosa 67,297 24 130,904 46 85,453 30 283,654 100 M'goro R 64,849 28 99,157 42 69,905 30 233,912 100 Kilombero 64,126 30 100,297 47 49,697 23 214,121 100 Ulanga 36,442 26 61,193 43 43,842 31 141,477 100 Morogoro 3,920 24 7,756 47 4,926 30 16,602 100 Mvomero 50,920 25 97,423 48 55,880 27 204,223 100 Total 287,555 26 496,730 45 309,704 28 1,093,989 100 Number % Number % Number % Number % Number % Kilosa 158,010 56 3,345 1 130 0 230 0 1,839 1 M'goro R 87,012 37 1,398 1 122 0 0 0 2,416 1 Kilombero 122,583 57 1,125 1 94 0 250 0 1,244 1 Ulanga 71,529 51 3,689 3 153 0 619 0 1,297 1 M'goro Urb 9,114 55 154 1 51 0 81 0 162 1 Mvomero 119,887 59 3,625 2 0 0 0 0 1,341 1 Total 568,135 52 13,336 1 549 0 1,180 0 8,299 1 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households Members By Sex and district for the 2002/03 Agricultural Year Male Female Total District Sex 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Completed Never Attended to School Total District School Attendancy Attending School Swahili Swahili & English Any Other Language Don't Read / Write Livestock Keeping / Crop/Seaweed Farming Total Livestock Pastoralist Fishing Government / 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 135 Number % Number % Number % Number % Number % Kilosa 2,805 1 2,389 1 8,655 3 6,201 2 1,703 1 M'goro R 16,011 7 1,848 1 26,628 11 2,315 1 768 0 Kilombero 835 0 1,634 1 2,282 1 778 0 381 0 Ulanga 695 0 231 0 4,944 3 914 1 307 0 M'goro Urb 442 3 177 1 650 4 317 2 100 1 Mvomero 985 0 1,360 1 930 0 2,502 1 487 0 Total 21,773 2 7,638 1 44,089 4 13,027 1 3,746 0 Number % Number % Number % Number % Number % Number % Kilosa 238 0 3,384 1 60,329 21 33,180 12 1,215 0 283,654 100 M'goro R 351 0 979 0 62,847 27 29,774 13 1,443 1 233,912 100 Kilombero 119 0 788 0 59,318 28 21,823 10 866 0 214,121 100 Ulanga 76 0 308 0 34,912 25 21,576 15 228 0 141,477 100 M'goro Urb 0 0 183 1 3,640 22 1,441 9 91 1 16,602 100 Mvomero 761 0 2,221 1 46,236 23 22,758 11 1,132 1 204,223 100 Total 1,545 0 7,864 1 267,282 24 130,552 12 4,975 0 1,093,989 100 Number % Number % Number % Number % Number % Kilosa 73,329 26 24,321 9 105,313 37 80,691 28 283,654 100 M'goro R 68,853 29 5,740 2 105,164 45 54,154 23 233,912 100 Kilombero 65,230 30 12,252 6 89,590 42 47,048 22 214,121 100 Ulanga 37,454 26 10,402 7 56,832 40 36,789 26 141,477 100 M'goro Urb 5,247 32 1,470 9 5,477 33 4,409 27 16,602 100 Mvomero 65,249 32 7,615 4 87,241 43 44,118 22 204,223 100 Total 315,361 29 61,800 6 449,618 41 267,211 24 1,093,989 100 Number % Number % Number % Number % Number % Number % Kilosa 128 0 376 0 1,605 1 3,273 3 13,500 10 3,391 3 M'goro R 103 0 244 0 1,585 2 1,403 1 12,053 12 1,437 1 Kilombero 620 1 615 1 2,501 2 4,240 4 12,506 12 2,895 3 Ulanga 0 0 829 1 1,295 2 2,211 4 8,615 14 1,535 3 M'goro Urb 12 0 91 1 304 4 214 3 979 13 213 3 Mvomero 1,477 2 881 1 1,891 2 1,448 1 15,084 15 1,363 1 Total 2,340 0 3,036 1 9,181 2 12,789 3 62,737 13 10,833 2 Not Working & District cont...HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity Total Housemaker / Student Unable to Work / Too Other District Main Activity cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Self Employed (Non Unpaid Family Helper Not Working & Private - NGO / Mission / Self Employed (Non Never Works on Farm Total 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Rarely Works on Farm 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Standard Five District Education Level Standard Three Standard Four Under Standard One Standard One Standard Two Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 136 Number % Number % Number % Number % Number % Number % Kilosa 1,993 2 98,269 75 1,143 1 962 1 338 0 131 0 M'goro R 1,087 1 75,169 76 1,134 1 230 0 0 0 0 0 Kilombero 2,732 3 67,286 67 2,119 2 354 0 189 0 362 0 Ulanga 1,521 2 41,312 68 841 1 72 0 78 0 301 0 M'goro Urb 234 3 5,116 66 91 1 21 0 13 0 0 0 Mvomero 1,336 1 70,868 73 623 1 128 0 0 0 121 0 Total 8,904 2 358,021 72 5,951 1 1,767 0 618 0 915 0 Number % Number % Number % Number % Number % Number % Kilosa 1,047 1 126 0 1,180 1 249 0 198 0 105 0 M'goro R 572 1 238 0 1,065 1 122 0 0 0 61 0 Kilombero 1,229 1 94 0 1,661 2 94 0 439 0 0 0 Ulanga 458 1 228 0 1,444 2 298 0 78 0 0 0 M'goro Urb 45 1 13 0 154 2 24 0 21 0 0 0 Mvomero 361 0 0 0 599 1 0 0 122 0 0 0 Total 3,713 1 698 0 6,103 1 788 0 858 0 167 0 Number % Number % Kilosa 2,888 2 130,904 100 M'goro R 2,655 3 99,157 100 Kilombero 360 0 100,297 100 Ulanga 78 0 61,193 100 M'goro Urb 210 3 7,756 100 Mvomero 1,122 1 97,423 100 Total 7,313 1 496,730 100 District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Training After University & Other Adult Education Total Education Level cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Standard Six Standard Seven Standard Eight Training After Primary Pre Form One District Form Four Form Six Education Level Education Level Form One Form Two Form Three District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 137 Number % Average Household Size Number % Average Household Size Number % Average Household Size Kilosa 57,345 78 553 16,090 22 455 73,435 100 531 Morogoro 41,550 78 600 11,567 22 551 53,117 100 589 Kilombero 42,217 87 622 6,565 13 559 48,782 100 613 Ulanga 24,582 80 410 6,326 20 341 30,908 100 396 Morogoro Urban 3,663 83 53 771 17 50 4,434 100 52 Mvomero 39,680 79 595 10,390 21 511 50,069 100 577 Total 209,037 80 558 51,709 20 481 260,746 100 543 Number Percent Number Percent Number Percent Number Percent Kilosa 36,022 52 24,657 35 8,924 13 69,604 100 Morogoro 29,027 62 13,188 28 4,665 10 46,880 100 Kilombero 24,618 54 14,639 32 6,731 15 45,988 100 Ulanga 19,111 63 7,845 26 3,495 11 30,451 100 Morogoro Urban 2,836 65 1,081 25 429 10 4,346 100 Mvomero 27,495 56 17,807 36 3,781 8 49,083 100 Total 139,109 56 79,217 32 28,027 11 246,352 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Kilosa 21,075 48,796 261 1,397 93 105 1,707 73,435 Morogoro 13,273 36,483 118 1,137 0 61 2,044 53,117 Kilombero 8,422 37,344 235 2,234 187 0 360 48,782 Ulanga 5,206 23,806 72 1,746 78 0 0 30,908 Morogoro Urban 1,344 2,759 21 162 12 0 136 4,434 Mvomero 10,184 38,174 128 714 122 0 747 50,069 Total 59,504 187,363 835 7,391 492 167 4,995 260,746 Mean Median Mode Mean Median Mode Mean Median Mode Kilosa 43 40 30 46 45 45 44 41 45 Morogoro 44 40 35 45 45 50 44 41 35 Kilombero 43 41 40 45 43 50 44 42 40 Ulanga 42 40 30 43 39 32 42 40 30 Morogoro Urban 44 42 30 49 48 50 45 42 30 Mvomero 44 40 30 45 40 30 44 40 30 Total 43 40 30 45 43 50 44 41 30 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 138 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 169,145 195,367 206,387 216,532 189,972 209,037 Female Headed (Number in Thousands) 32,706 44,257 47,028 45,275 55,821 51,709 Total 201,851 239,624 253,415 261,807 245,793 260,746 Male Headed (Percentage) 84 82 81 83 77 80 Female Headed (Percentage) 16 18 19 17 23 20 Total 100 100 100 100 100 100 3.15 Literacy Rate of Heads of Households by Sex and District District Literacy Know Don't know Total Male Female Total Male Female Total Male Female Total Kilosa 97,708 93,519 191,227 40,682 51,745 92,427 138,391 145,263 283,654 Morogoro 86,653 72,400 159,053 26,353 48,506 74,859 113,006 120,905 233,912 Kilombero 82,094 73,552 155,646 26,475 32,000 58,475 108,569 105,552 214,121 Ulanga 49,347 44,531 93,878 21,084 26,515 47,599 70,432 71,045 141,477 Morogoro Urban 6,258 5,320 11,578 1,966 3,059 5,025 8,224 8,379 16,602 Mvomero 74,749 61,960 136,709 30,112 37,403 67,514 104,861 99,363 204,223 Total 396,809 351,282 748,091 146,672 199,226 345,898 543,481 550,508 1,093,989 3.14 Time Series of male and Female Headed Households Tanzania Agriculture Sample Census - 2003 Morogoro 139 Appendix II 140 LAND ACCESS/OWNERSHIP/TENURE Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 141 Total Number of Households No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Kilosa 1,647 2 58,578 59 9,140 9 16,818 17 6,337 6 1,605 2 4,389 4 98,513 Morogoro R 4,473 6 39,781 55 10,482 15 7,961 11 6,817 9 1,285 2 1,438 2 72,236 Kilombero 11,292 17 24,776 37 11,017 17 7,921 12 4,160 6 2,123 3 5,019 8 66,308 Ulanga 7,172 18 22,690 57 1,524 4 3,983 10 2,889 7 382 1 1,504 4 40,144 Morogoro Urb 308 5 3,180 53 1,142 19 703 12 332 6 69 1 230 4 5,965 Mvomero 6,235 9 37,591 53 9,488 13 10,304 15 2,915 4 853 1 3,512 5 70,898 Total 31,126 9 186,595 53 42,792 12 47,689 13 23,452 7 6,317 2 16,092 5 354,064 Borrowed Households with Area Shared Croped From Others Households with Area under Other Forms of Tenure 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District or the 2002/03 agriculture Year Land Access District Leased/Certificate of Ownership Owned Under Customary Law Bought Rented Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 142 Area Leased/Certifi cate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented Area Borrowed Area Shared Croped Area under Other Forms of Tenure Total Kilosa 3,876 108,735 12,998 14,546 3,535 1,360 7,309 152,360 Morogoro 5,696 61,087 11,249 6,850 6,318 1,743 5,972 98,915 Kilombero 26,256 57,482 19,193 6,469 2,615 1,957 10,944 124,916 Ulanga 12,584 45,290 1,954 2,276 1,555 313 1,845 65,817 Morogoro Urban 725 4,564 1,211 448 255 38 473 7,713 Mvomero 16,740 72,406 17,313 8,169 1,596 346 3,309 119,880 Total 65,877 349,563 63,918 38,759 15,873 5,757 29,853 569,600 % 12 61 11 7 3 1 5 100 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census - 2003 Morogoro 143 Appendix II 144 LAND USE Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 145 Households with Area under Temporary Mono Crops Households with Area under Temporary Mixed Crops Households with Area under Permanent Mono Crops Households with Area under Permanent Mixed Crops Households with Area under Permanent / Annual Mix Households with Area under Pasture Households with Area under Fallow Households with Area under Natural Bush Households with Area under Planted Trees Households with Area Rented to Others Households with Area Unusable Households with Area of Uncultivated Usable Land Total Number of Household Kilosa 66,886 15,760 8,968 5,392 4,432 891 1,987 631 1,280 1,463 3,030 17,467 128,186 Morogoro 44,266 10,267 15,987 8,631 10,908 122 1,325 727 1,434 1,803 2,639 4,544 102,653 Kilombero 46,578 3,057 13,039 3,868 2,873 610 1,952 726 1,073 3,530 1,099 13,984 92,390 Ulanga 28,784 5,087 2,532 1,899 4,354 77 1,147 149 918 1,288 763 6,993 53,991 Morogoro Urban 2,515 2,138 1,570 1,162 834 11 152 0 241 126 52 677 9,478 Mvomero 35,809 16,490 11,354 4,233 3,402 493 3,466 124 2,847 1,321 1,628 11,363 92,528 Total 224,838 52,799 53,451 25,185 26,801 2,205 10,029 2,356 7,793 9,531 9,210 55,028 479,226 Table 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year Land Use District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 146 Number Percent Number Percent Number Percent Kilosa 52,391 72 20,673 28 73,064 100 Morogoro 40,810 77 11,943 23 52,753 100 Kilombero 28,969 59 19,813 41 48,782 100 Ulanga 21,241 69 9,667 31 30,908 100 Morogoro Urban 3,358 76 1,065 24 4,423 100 Mvomero 35,344 72 13,972 28 49,316 100 Total 182,114 70 77,132 30 259,246 100 Number Percent Number Percent Number Percent Kilosa 44,404 61 28,660 39 73,064 100 Morogoro 30,846 58 21,907 42 52,753 100 Kilombero 20,834 43 27,948 57 48,782 100 Ulanga 18,252 59 12,657 41 30,908 100 Morogoro Urban 2,809 64 1,614 36 4,423 100 Mvomero 31,534 64 17,782 36 49,316 100 Total 148,678 57 110,568 43 259,246 100 Number Percent Number Percent Number Percent Kilosa 17,694 24 55,370 76 73,064 100 Morogoro 16,650 32 36,103 68 52,753 100 Kilombero 7,834 16 40,948 84 48,782 100 Ulanga 9,035 29 21,873 71 30,908 100 Morogoro Urban 1,329 30 3,094 70 4,423 100 Mvomero 22,658 46 26,658 54 49,316 100 Total 75,200 29 184,047 71 259,246 100 Table 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Table 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total Table 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total Tanzania Agriculture Sample Census - 2003 Morogoro 147 Appendix II 148 ACCESS AND USE OF RESOURCE Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 149 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Kilosa 0.5 1.1 0.8 1.3 1.8 2.7 2.3 2.3 2.5 2.5 Morogoro 0.4 0.9 0.8 1.5 1.8 2.7 2.5 2.6 2.7 2.8 Kilombero 0.2 0.4 0.7 1.4 2.3 3.3 1.8 1.9 2.7 2.7 Ulanga 0.3 0.6 2.2 3.5 5.5 6.4 3.0 3.0 3.8 3.7 Morogoro Urban 1.1 2.5 1.0 1.7 1.9 2.7 2.5 2.4 4.0 4.0 Mvomero 0.6 0.9 0.7 1.6 2.4 3.2 3.2 3.2 3.0 3.0 Total 0.4 0.9 0.9 1.7 2.4 3.3 2.5 2.5 2.8 2.9 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Kilosa 2.5 2.5 4.0 4.0 7.3 7.4 7.3 8.2 Morogoro 3.3 3.3 4.4 4.4 7.5 7.5 7.1 8.0 Kilombero 2.4 2.6 4.4 4.6 9.2 9.8 9.0 10.6 Ulanga 3.8 4.1 4.6 4.6 11.3 11.4 11.4 13.4 Morogoro Urban 3.7 3.6 5.2 5.0 7.6 7.6 7.5 8.4 Mvomero 3.5 3.4 4.6 4.7 7.5 7.5 7.4 8.2 Total 3.0 3.1 4.4 4.4 8.2 8.4 8.1 9.2 District Water for Humans Water for Livestock Communal Grazing Building Poles Hunting (Animal Products) District Forest for Bees (Honey) Communal Resource Communal Resource 6.1 COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Communal Firewood Wood for Charcoal Fishing (Fish) cont…. COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 150 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Village Market Not Used by Household Total Kilosa 73,310 126 0 0 73,435 Morogoro 52,753 121 0 244 53,117 Kilombero 48,666 0 116 0 48,782 Ulanga 30,908 0 0 0 30,908 Morogoro Urban 4,421 0 0 13 4,434 Mvomero 50,069 0 0 0 50,069 Total 260,127 246 116 256 260,746 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Not Used by Household Not Available Total Kilosa 22,429 223 130 93 131 18,789 31,641 73,435 Morogoro 8,545 122 0 0 0 8,487 35,963 53,117 Kilombero 11,017 119 0 0 0 12,381 25,265 48,782 Ulanga 4,063 75 0 0 0 10,589 16,181 30,908 Morogoro Urban 620 0 0 0 0 1,030 2,784 4,434 Mvomero 10,403 0 0 0 0 12,434 27,232 50,069 Total 57,077 539 130 93 131 63,710 139,066 260,746 6.2 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District Water for Humans 6.3 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year District Water for Livestock Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 151 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Local Wholesale Market Not Used by Household Not Available Total Kilosa 7,899 231 117 131 21,146 43,911 73,435 Morogoro 3,220 61 0 0 3,016 46,819 53,117 Kilombero 1,621 119 119 125 5,694 41,103 48,782 Ulanga 1,839 0 0 0 10,253 18,817 30,908 Morogoro Urban 152 12 0 0 822 3,449 4,434 Mvomero 1,980 237 0 0 11,540 36,312 50,069 Total 16,711 661 236 256 52,471 190,411 260,746 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Kilosa 68,355 741 261 612 93 0 1,463 1,910 73,435 Morogoro 49,794 1,218 0 0 118 0 367 1,620 53,117 Kilombero 46,310 603 0 0 0 0 1,511 358 48,782 Ulanga 30,149 223 0 0 0 0 536 0 30,908 Morogoro Urban 4,309 0 0 12 13 0 62 38 4,434 Mvomero 46,900 1,747 0 0 0 127 1,174 122 50,069 Total 245,817 4,532 261 624 224 127 5,113 4,048 260,746 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Kilosa 16,379 2,432 1,939 327 776 130 23,892 27,561 73,435 Morogoro 5,488 4,071 706 359 2,403 0 30,926 9,164 53,117 Kilombero 5,469 612 1,204 129 0 0 13,562 27,807 48,782 Ulanga 3,630 148 0 0 154 850 22,491 3,637 30,908 Morogoro Urban 511 0 258 24 38 71 1,263 2,270 4,434 Mvomero 1,923 1,433 1,074 0 626 249 24,108 20,657 50,069 Total 33,399 8,695 5,180 839 3,996 1,299 116,241 91,096 260,746 6.5 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District Communal Firewood 6.4: COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District Communal Grazing 6.6 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District Wood for Charcoal Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 152 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Kilosa 54,306 1,901 131 728 117 0 9,519 6,734 73,435 Morogoro 39,386 304 229 0 121 0 8,939 4,139 53,117 Kilombero 26,494 364 0 0 0 0 10,834 11,090 48,782 Ulanga 24,371 224 0 0 0 0 6,158 155 30,908 Morogoro Urban 3,057 0 0 0 0 12 1,327 38 4,434 Mvomero 30,224 886 250 128 0 0 16,346 2,235 50,069 Total 177,837 3,679 610 856 238 12 53,123 24,391 260,746 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Not Used by Household Not Available Total Kilosa 1,698 255 260 131 131 20,442 50,519 73,435 Morogoro 1,582 0 0 0 0 6,482 45,052 53,117 Kilombero 988 238 127 0 119 9,902 37,408 48,782 Ulanga 383 152 0 0 0 13,107 17,266 30,908 Morogoro Urban 0 0 0 0 0 26 4,408 4,434 Mvomero 474 124 0 0 0 8,087 41,384 50,069 Total 5,125 769 388 131 250 58,047 196,038 260,746 6.7 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District Building Poles 6.8 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District Forest for Bees Products Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 153 Home of Farm Consumption / Utilization Sold to Neighbours Not Used by Household Not Available Total Kilosa 366 311 11,451 61,307 73,435 Morogoro 0 0 2,203 50,914 53,117 Kilombero 254 119 8,615 39,794 48,782 Ulanga 77 0 16,561 14,270 30,908 Morogoro Urban 12 5 374 4,043 4,434 Mvomero 497 124 8,728 40,721 50,069 Total 1,206 558 47,933 211,048 260,746 Home of Farm Consumption / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Kilosa 994 485 258 0 0 0 6,796 64,902 73,435 Morogoro 585 240 0 0 0 0 4,353 47,939 53,117 Kilombero 1,563 366 0 379 129 117 14,202 32,027 48,782 Ulanga 382 851 231 153 0 0 14,332 14,958 30,908 Morogoro Urban 37 13 11 11 0 0 296 4,066 4,434 Mvomero 362 253 0 0 125 0 6,945 42,383 50,069 Total 3,923 2,208 500 543 254 117 46,924 206,276 260,746 6.9 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District Fishing Resources District Hunting Grounds 6.10 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 154 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION - LONG AND SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 155 Kilosa 28,856 14,219 133,717 98,900 113,119 13 Morogoro Rural 55,685 26,368 100,018 46,217 72,585 36 Kilombero 34,532 24,946 64,189 55,851 80,797 31 Ulanga 27,037 21,104 51,570 32,967 54,071 39 Morogoro Urban 2,860 950 10,276 3,984 4,934 19 Mvomero 62,803 40,016 70,818 48,628 88,644 45 Total 211,773 127,604 430,589 286,546 414,151 31 Kilosa 28,856 133,717 73,064 314,672 Morogoro Rural 55,685 100,018 52,753 262,999 Kilombero 34,532 64,189 48,782 245,735 Ulanga 27,037 51,570 30,908 160,345 Morogoro Urban 2,860 10,276 4,423 18,972 Mvomero 62,803 70,818 49,316 232,855 Total 211,773 430,589 259,246 1,235,577 Table 7.1 and 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households PlantingCrops by Season and District Table 7.1 and 7.2b TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District District Short Rainy Season Long Rainy Season Total Number of Crop Growing Households Number of Households Growing Crops Total Area Planted (hectares) District Number of Households Not Growing Crops % Area Planted in Short Rainy Season Number of Households Area Planted Short Rainy Season Number of Households % Area Planted in Short Rainy Season Long Rainy Season Number of Household Growing Crops Number of Household Not Growing Area Planted Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 156 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cereal 106,628 79,381 744 230,834 155,177 672 337,461 234,558 695 Maize 75,654 55,292 731 119,436 60,278 505 195,090 115,570 592 Paddy 27,279 23,114 847 99,248 89,889 906 126,527 113,003 893 Sorghum 3,603 956 265 11,227 4,587 409 14,830 5,544 374 Bulrush Millet 39 19 494 416 70 169 455 89 197 Finger Millet 0 0 0 165 90 543 165 90 543 Wheat 0 0 0 238 223 936 238 223 936 Barley 53 0 0 104 40 382 157 40 254 Roots and Tubers 2,179 2,681 1230 20,122 28,471 1415 22,301 31,152 1397 Cassava 530 667 1258 16,644 22,958 1379 17,174 23,625 1376 Sweet Potatoes 436 705 1618 2,514 4,178 1662 2,950 4,883 1655 Irish Potatoes 63 263 4150 669 461 689 733 724 988 Yams 52 261 4999 24 60 2475 77 322 4195 Cocoyam 1,098 785 715 269 813 3021 1,367 1,598 1169 Pulses 28556 11595 406 17,483 7,589 434 46,039 19,184 417 Mung Beans 49 24 504 0 0.00 0 49 24 504 Beans 20407 8617 422 13,360 6,050 453 33,766 14,667 434 Cowpeas 6083 1948 320 3,096 1,095 354 9,179 3,043 332 Green Gram 954 174 182 441 118 267 1,395 292 209 Pigeon Peas 0 0 0 0 0 0 0 0 0 Chich Peas 65 8 119 0 0 0 65 8 119 Bambaranuts 52 8 151 52 8 151 104 16 151 Field Peas 947 816 861 535 318 594 1,482 1,134 765 Oil Seeds and Oil nuts 2,477 751 303 10,258 3,415 333 12,735 4,167 327 Sunflower 0 0 0 495 133 270 495 133 270 Simsim 2,159 582 269 7,362 2,170 295 9,521 2,752 289 Groundnuts 307 168 545 2,219 984 443 2,527 1,152 456 Soya Beans 11 2 198 54 12 215 65 14 212 Castor Seed 0 0 0 128 116 907 128 116 907 Fruit and Vegetables 5,232 16,909 3232 7,167 25,320 3533 12,400 42,229 3406 Okra 68 3 50 96 96 993 164 99 603 Radish 0 0 0 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 44 97 2208 49 47 969 93 145 1557 Garlic 0 0 0 0 0 0 0 0 0 Onions 305 1,057 3462 660 3,630 5499 965 4,687 4854 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 667 3,965 5943 1,222 6,409 5246 1,889 10,374 5492 Tomatoes 2,685 9,700 3612 3,474 12,047 3468 6,159 21,747 3531 Spinnach 96 156 1628 88 191 2163 184 347 1884 Carrot 448 491 1096 30 34 1142 478 525 1099 Chillies 278 443 1595 255 530 2081 533 973 1828 Amaranths 90 273 3029 367 577 1571 457 849 1858 Pumpkins 237 282 1188 710 1,595 2246 947 1,877 1981 Cucumber 91 279 3078 61 33 541 152 312 2058 Egg Plant 75 84 1123 80 68 861 154 153 988 Water Mellon 99 54 545 51 38 741 151 92 612 Cauliflower 49 24 494 25 24 988 74 48 659 Cash Crops 16 2 143 682 283 415 698 285 409 Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 620 248 399 620 248 399 Tobacco 16 2 143 62 35 573 78 38 485 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 Total 145,088 286,546 431,634 Crop Table 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Morogoro Region * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to being produced on the same land during the 2 seasons. Previous surveys have used the lpno season to estimate physical land area under production to different crops Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 157 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Cereal 151,780 106,628 281,251 230,834 337,461 32 Maize 118,288 75,654 148,561 119,436 195,090 39 Paddy 26,536 27,279 109,655 99,248 126,527 22 Sorghum 6,698 3,603 20,878 11,227 14,830 24 Bulrush Millet 128 39 623 416 455 9 Finger Millet 0 0 624 165 165 0 Wheat 0 0 653 238 238 0 Barley 130 53 257 104 157 34 Roots and Tubers 5,595 2,179 49,417 20,122 22,301 10 Cassava 2,318 530 39,432 16,644 17,174 3 Sweet Potatoes 1,237 436 6,511 2,514 2,950 15 Irish Potatoes 250 63 1,955 669 733 9 Yams 129 52 166 24 77 68 Cocoyam 1,660 1,098 1,353 1,098 100 Pulses 30,881 28556 46,090 17,483 46,039 62 Mung Beans 122 49 0 0 49 100 Beans 15,536 20407 29,182 13,360 33,766 60 Cowpeas 12,451 6083 13,446 3,096 9,179 66 Green Gram 1,512 954 1,852 441 1,395 68 Chich Peas 246 65 0 0 65 100 Bambaranuts 0 52 261 52 104 50 Field Peas 1,013 947 1,348 535 1,482 64 Oil Seeds and Oil nuts 6,111 2,477 23,003 10,258 12,735 19 Sunflower 0 0 1,303 495 495 0 Simsim 4,744 2,159 16,162 7,362 9,521 23 Groundnuts 1,261 307 4,885 2,219 2,527 12 Soya Beans 105 11 139 54 65 16 Castor Seed 0 0 515 128 128 0 Fruit and Vegetables 17,332 5,232 29,209 7,167 12,400 42 Okra 236 68 630 96 164 41 Bitter Aubergine 362 44 397 49 93 47 Onions 844 305 2,064 660 965 32 Cabbage 1,883 667 3,588 1,222 1,889 35 Tomatoes 7,972 2,685 11,777 3,474 6,159 44 Spinnach 558 96 455 88 184 52 Carrot 623 448 160 30 478 94 Chillies 984 278 1,257 255 533 52 Amaranths 828 90 3,017 367 457 20 Pumpkins 2,005 237 4,563 710 947 25 Cucumber 399 91 334 61 152 60 Egg Plant 376 75 718 80 154 48 Water Mellon 141 99 127 51 151 66 Cauliflower 121 49 121 25 74 67 Cash Crops 76 16 1,619 682 698 2 Cotton 0 0 1,254 620 620 0 Tobacco 76 16 365 62 78 21 Total 145,088 430,589 286,546 431,634 Total Area Planted Short and Long Rainy Season % Area Planted in Short Rainy Season Table 7.1 and 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Morogoro Region Crop Short Rainy Season Long Rainy Season Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilosa 5,986 11,000 5,576 9,017 71,627 91,515 83,189 111,532 Morogoro R 1,584 2,463 2,247 1,896 74,926 62,961 78,757 67,321 Kilombero 14,671 17,234 3,363 10,000 54,154 51,679 72,188 78,913 Ulanga 4,208 7,793 4,876 12,017 31,231 32,803 40,314 52,613 Morogoro Urb 275 340 606 451 4,997 3,707 5,877 4,499 Mvomero 8,174 13,787 2,501 2,676 64,976 67,320 75,652 83,784 Total 34,898 52,617 19,168 36,058 301,911 309,985 355,976 398,661 % 10 13 5 9 85 78 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilosa 4,971 5,450 471 575 2,664 6,021 75,719 101,074 83,824 113,119 Morogoro R 1,172 670 2,897 1,867 103 42 76,645 70,006 80,817 72,585 Kilombero 1,589 3,146 1,036 1,047 2,051 2,668 68,109 73,937 72,785 80,797 Ulanga 230 222 0 0 459 889 41,082 52,960 41,771 54,071 Morogoro Urb 178 200 77 96 320 192 5,432 4,445 6,006 4,934 Mvomero 3,760 4,889 3,463 3,355 7,258 10,155 61,797 70,246 76,278 88,644 Total 11,899 14,576 7,943 6,940 12,855 19,967 328,784 372,668 361,481 414,151 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 12,806 17,255 71,019 95,865 83,824 113,119 15.3 Morogoro R 14,787 13,529 66,029 59,057 80,817 72,585 18.6 Kilombero 6,813 9,019 65,971 71,778 72,785 80,797 11.2 Ulanga 5,962 5,805 35,810 48,267 41,771 54,071 10.7 Morogoro Urb 1,611 1,596 4,394 3,338 6,006 4,934 32.3 Mvomero 12,422 17,481 63,856 71,163 76,278 88,644 19.7 Total 54,401 64,685 307,080 349,466 361,481 414,151 15.6 % 15 16 85 84 100 100 15.6 Mostly Farm Yard Manure Total No Fertilizer Applied Mostly Inorganic Fertilizer Mostly Compost Table 7.1 and 7.2e Total Crop and Vegetable Production: Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District Long and Short Season, Morogoro Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of area planted under irrigation Number of Households is an estimate due to the double counting of households growing crops in both long and short seasons. To compare previous surveys use Number of Long season planters only 7.1 1nd 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Morogoro Region District Fertilizer Use Table 7.1 and 7.2g Total Annual Crop and Vegetable Production: Total Numberof Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 159 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 5,982 11,353 77,842 101,767 83,824 113,119 10.0 Morogoro R 1,689 1,459 79,128 71,127 80,817 72,585 2.0 Kilombero 1,167 1,068 71,618 79,729 72,785 80,797 1.3 Ulanga 2,976 2,869 38,796 51,203 41,771 54,071 5.3 Morogoro Urb 363 295 5,643 4,638 6,006 4,934 6.0 Mvomero 12,189 18,858 64,089 69,786 76,278 88,644 21.3 Total 24,365 35,902 337,116 378,249 361,481 414,151 8.7 % 7 9 93 91 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 1,931 2,581 81,894 110,538 83,824 113,119 2.3 Morogoro R 122 246 80,694 72,340 80,817 72,585 0.3 Kilombero 10,651 15,340 62,134 65,458 72,785 80,797 19.0 Ulanga 5,451 10,245 36,320 43,826 41,771 54,071 18.9 Morogoro Urb 121 104 5,885 4,830 6,006 4,934 2.1 Mvomero 2,398 3,279 73,880 85,365 76,278 88,644 3.7 Total 20,673 31,795 340,808 382,356 361,481 414,151 7.7 % 6 8 94 92 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 3,486 6,573 80,338 106,546 83,824 113,119 5.8 Morogoro R 973 1,369 79,844 71,217 80,817 72,585 1.9 Kilombero 746 564 72,039 80,233 72,785 80,797 0.7 Ulanga 766 744 41,005 53,327 41,771 54,071 1.4 Morogoro Urb 349 274 5,657 4,660 6,006 4,934 5.5 Mvomero 4,920 4,656 71,358 83,987 76,278 88,644 5.3 Total 11,240 14,180 350,240 399,971 361,481 414,151 3.4 % 3 3 97 97 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 8,117 9,729 75,072 101,803 83,189 111,532 8.7 Morogoro R 5,661 4,650 73,096 62,670 78,757 67,321 6.9 Kilombero 6,333 5,902 65,855 73,011 72,188 78,913 7.5 Ulanga 4,440 4,586 35,874 48,027 40,314 52,613 8.7 Morogoro Urb 2,153 1,756 3,723 2,743 5,877 4,499 39.0 Mvomero 22,710 29,518 52,942 54,266 75,652 83,784 35.2 Total 49,414 56,141 306,562 342,520 355,976 398,661 14.1 % 14 14 86 86 100 100 % of Planted area using Herbicide Households Using Fungicide Number of Households is an over estimate due to the double counting of households growing crops in both long and short seasons. To compare previuus surveys use Number of Long Season planters only. District Improved Seed Use Households Using Households Not Using Total Table 7.1 and 7.2h Totao annual Crop and Vegetable Production: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 aggriculture year - Long and Short Rainy Season % of Planted area using Herbicide Table 7.1 and 7.2j Total annual Crop and Vegetable Production: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 aggriculture year - Long and Short Rainy Season, Morogoro Region Table 7.1 and 7.2k Total annual Crop and Vegetable Production: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 aggriculture year - Long and Short Rainy Season, Morogoro Region Table 7.1 and 7.2i Total annual Crop and Vegetable Production: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 aggriculture year - Long and Short Rainy Season, Morogoro Region District Households Using Herbicide Households Not Using Herbicide Total % of Planted area using Herbicide Herbicide Use District Households Using Pesticide Households Not Using Pesticide Total Pesticide Use % of Planted Area using Pesticide District Fungicide Use Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 160 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilosa 5,369 10,589 5,102 8,535 57,859 78,189 68,331 97,313 M'goro R 1,052 1,439 1,457 1,365 40,791 38,148 43,300 40,953 Kilombero 11,836 14,164 1,991 5,090 30,225 34,713 44,053 53,966 Ulanga 2,367 4,456 2,439 4,283 20,308 22,770 25,114 31,508 M'goro U 254 322 532 416 3,378 2,810 4,164 3,549 Mvomero 5,952 11,783 1,375 1,704 32,022 30,281 39,349 43,768 Total 26,830 42,753 12,896 21,393 184,583 206,911 224,310 271,056 % 12 16 6 8 82 76 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Kilosa 4,384 5,068 341 470 2,281 5,918 61,960 87,444 68,966 98,900 M'goro R 122 50 1,082 835 103 42 44,052 45,290 45,360 46,217 Kilombero 497 1,051 459 789 1,895 2,453 41,799 51,558 44,649 55,851 Ulanga 230 222 0 . 227 515 26,113 32,230 26,571 32,967 M'goro U 126 166 64 81 209 144 3,895 3,593 4,293 3,984 Mvomero 2,121 2,569 1,858 1,986 3,869 4,376 32,127 39,697 39,975 48,628 Total 7,480 9,126 3,803 4,161 8,584 13,448 209,946 259,812 229,814 286,546 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 9,665 15,381 59,301 83,519 68,966 98,900 15.6 M'goro R 13,470 12,886 31,891 33,331 45,360 46,217 27.9 Kilombero 6,216 8,754 38,433 47,097 44,649 55,851 15.7 Ulanga 5,660 5,468 20,911 27,499 26,571 32,967 16.6 M'goro U 1,468 1,548 2,825 2,435 4,293 3,984 38.9 Mvomero 9,664 13,837 30,311 34,791 39,975 48,628 28.5 Total 46,143 57,874 183,672 228,672 229,814 286,546 20.2 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 1,802 2,478 67,164 96,423 68,966 98,900 Morogoro 0 . 45,360 46,217 45,360 46,217 Kilombero 7,447 12,013 37,202 43,838 44,649 55,851 Ulanga 2,146 4,480 24,424 28,487 26,571 32,967 Morogoro Urb 75 70 4,218 3,914 4,293 3,984 Mvomero 1,538 2,806 38,437 45,821 39,975 48,628 Total 13,009 21,847 216,806 264,700 229,814 286,546 % of area planted under irrigation in long rainy season Table 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 162 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 5,288 11,047 63,678 87,853 68,966 98,900 Morogoro 959 700 44,401 45,517 45,360 46,217 Kilombero 692 748 43,957 55,103 44,649 55,851 Ulanga 2,826 2,764 23,744 30,203 26,571 32,967 Morogoro Urb 276 249 4,017 3,735 4,293 3,984 Mvomero 9,692 16,198 30,283 32,430 39,975 48,628 Total 19,733 31,705 210,081 254,841 229,814 286,546 Number % Number % Kilosa 43,822 59.7 29,613 40.3 73,435 Morogoro Rural 36,603 68.9 16,514 31.1 53,117 Kilombero 42,308 86.7 6,474 13.3 48,782 Ulanga 22,824 73.8 8,084 26.2 30,908 Morogoro Urban 3,357 75.7 1,077 24.3 4,434 Mvomero 33,987 67.9 16,082 32.1 50,069 Total 182,902 70.1 77,843 29.9 260,746 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 2,902 5,962 66,064 92,939 68,966 98,900 6.0 Morogoro 489 833 44,872 45,384 45,360 46,217 1.8 Kilombero 368 348 44,281 55,503 44,649 55,851 0.6 Ulanga 611 431 25,959 32,536 26,571 32,967 1.3 Morogoro Urb 247 212 4,046 3,771 4,293 3,984 5.3 Mvomero 3,943 4,009 36,032 44,619 39,975 48,628 8.2 Total 8,560 11,794 221,254 274,752 229,814 286,546 4.1 % 4 4 96 96 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Kilosa 5,280 7,163 63,051 90,150 68,331 97,313 7.4 Morogoro Rural 2,522 1,914 40,778 39,038 43,300 40,953 4.7 Kilombero 4,222 4,517 39,831 49,449 44,053 53,966 8.4 Ulanga 3,374 3,365 21,740 28,144 25,114 31,508 10.7 Morogoro Urban 1,427 1,321 2,737 2,228 4,164 3,549 37.2 Mvomero 13,384 19,975 25,965 23,793 39,349 43,768 45.6 Total 30,208 38,254 194,102 232,802 224,310 271,056 14.1 % 13 14 87 86 100 100 % of Planted Area Using Fungicide % of Planted Area Using Imroved Seed 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Households that Sold Produce Households that Did not Sell Produce Total Number of Households Table 7.2j: Number of Crops Producing Households Reporting Selling Agricultural Produce by District; 2002/03 Agricultutal Year 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Pesticide Use Households Using Pesticide Households Not Using Pesticide Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 163 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area 16,136 12,402 211,282 165,656 563 307 14,097 12,588 37,766 38,786 365 342 280,209 230,081 8,013 6,729 116,556 92,818 314 202 3,108 1,720 19,918 17,402 123 50 148,032 118,920 6,727 4,755 76,790 63,574 238 96 10,515 10,711 14,840 19,715 242 292 109,352 99,143 1,395 918 16,272 8,721 12 10 473 157 2,515 1,289 0 . 20,668 11,094 0 . 261 89 0 . 0 . 362 327 0 . 623 416 0 . 493 112 0 . 0 . 131 53 0 . 624 165 0 . 653 238 0 . 0 . 0 . 0 . 653 238 0 . 257 104 0 . 0 . 0 . 0 . 257 104 278 117 11,208 3,871 0 . 362 68 1,452 575 0 . 13,300 4,632 125 94 3,114 1,041 0 . 0 . 75 20 0 . 3,315 1,154 153 23 5,404 2,205 0 . 240 48 715 237 0 . 6,511 2,514 0 . 1,305 354 0 . 0 . 650 315 0 . 1,955 669 0 . 154 22 0 . 0 . 12 2 0 . 166 24 0 . 1,230 249 0 . 122 20 0 . 0 . 1,353 269 2,573 1,177 37,827 14,432 115 18 753 113 4,823 1,744 0 . 46,090 17,483 1,587 833 24,550 11,219 0 . 125 13 2,920 1,294 0 . 29,182 13,360 485 151 11,117 2,592 115 18 502 75 1,228 258 0 . 13,446 3,096 246 37 1,078 244 0 . 126 25 402 135 0 . 1,852 441 0 . 0 . 0 . 0 . 261 52 0 . 261 52 254 154 1,082 376 0 . 0 . 12 5 0 . 1,348 535 957 631 18,869 8,013 130 105 253 24 2,704 1,447 0 . 22,912 10,221 0 . 902 403 0 . 0 . 400 92 0 . 1,303 495 691 554 14,528 6,475 0 . 122 15 728 281 0 . 16,070 7,325 266 77 2,796 956 130 105 130 10 1,563 1,072 0 . 4,885 2,219 0 . 128 52 0 . 0 . 12 2 0 . 139 54 0 . 515 128 0 . 0 . 0 . 0 . 515 128 2,306 995 23,929 5,750 125 51 564 117 2,036 154 122 49 29,082 7,116 76 18 554 78 0 . 0 . 0 . 0 . 630 96 76 18 321 31 0 . 0 . 0 . 0 . 397 49 0 . 1,943 636 0 . 121 25 0 . 0 . 2,064 660 890 515 2,443 694 0 . 0 . 254 13 0 . 3,588 1,222 579 246 10,065 2,994 125 51 123 25 636 57 122 49 11,650 3,422 127 51 227 33 0 . 0 . 101 3 0 . 455 88 0 . 39 5 0 . 121 25 0 . 0 . 160 30 127 51 1,007 178 0 . 123 25 0 . 0 . 1,257 255 76 6 2,738 353 0 . 0 . 203 8 0 . 3,017 367 0 . 3,768 644 0 . 75 18 720 48 0 . 4,563 710 75 6 136 30 0 . 0 . 123 25 0 . 334 61 153 31 566 49 0 . 0 . 0 . 0 . 718 80 127 51 0 . 0 . 0 . 0 . 0 . 127 51 0 . 121 25 0 . 0 . 0 . 0 . 121 25 75 31 1,265 546 0 . 0 . 279 105 0 . 1,619 682 75 31 900 485 0 . 0 . 279 105 0 . 1,254 620 0 . 365 62 0 . 0 . 0 . 0 . 365 62 22,324 15,352 304,380 198,268 932 481 16,028 12,911 49,059 42,812 487 392 393,211 270,215 6 73 0 5 16 0 100 7.2g ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop Crop Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning No Clearing Other Total Cereals Maize Paddy Sorghum Bulrush Millet Finger Millet Wheat Barley Roots and Tubers Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Pulses Beans Cowpeas Green Gram Bambaranuts Field Peas Oil seeds and Oil nuts Sunflower Simsim Groundnuts Soya Beans Castor Seed Fruits and Vegetables Okra Bitter Aubergine Onions Cabbage Tomatoes Spinnach Carrot Chillies Amaranths Pumpkins Cucumber Egg Plant Water Mellon Total % Cauliflower Cash Crops Cotton Tobacco Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 164 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 11,925 7,735 4,774 0.617 61,466 64,685 29,443 0.455 72,420 34,217 0.472 Morogoro R 31,378 15,526 6,055 0.390 32,953 16,899 7,223 0.427 32,425 13,278 0.409 Kilombero 25,282 15,735 20,911 1.329 11,516 7,074 7,836 1.108 22,810 28,748 1.260 Ulanga 13,521 7,977 7,678 0.962 14,553 8,410 7,351 0.874 16,388 15,029 0.917 Morogoro Urb 1,490 697 458 0.657 3,845 2,192 1,260 0.575 2,889 1,718 0.595 Mvomero 34,692 27,983 15,416 0.551 24,228 20,175 7,165 0.355 48,158 22,581 0.469 Total 118,288 75,654 55,292 0.731 148,561 119,436 60,278 0.505 195,090 115,570 0.592 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 2,997 1,757 998 0.568 15,770 11,244 6,006 0.534 13,001 7,004 0.539 Morogoro R 7,550 4,706 1,064 0.226 20,006 11,204 2,817 0.251 15,910 3,880 0.244 Kilombero 4,878 7,991 9,073 1.135 41,272 45,105 60,333 1.338 53,096 69,406 1.307 Ulanga 8,557 11,689 11,634 0.995 18,089 18,973 16,130 0.850 30,662 27,764 0.905 Morogoro Urb 107 44 23 0.525 1,164 453 157 0.346 497 180 0.362 Mvomero 2,446 1,091 322 0.295 13,354 12,269 4,447 0.362 13,360 4,769 0.357 Total 26,536 27,279 23,114 0.847 109,655 99,248 89,889 0.906 126,527 113,003 0.893 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 258 116 13 0.110 5,239 3,107 1,317 0.424 3,224 1,330 0.413 M'goro R 2,789 1,488 485 0.326 12,212 5,541 1,820 0.328 7,028 2,305 0.328 Kilombero 129 26 91 3.498 505 789 434 0.550 815 525 0.644 Ulanga 305 118 52 0.446 1,076 785 895 1.140 903 948 1.050 Morogoro Urb 0 0 0 0.000 283 144 45 0.316 144 45 0.316 Mvomero 3,218 1,855 315 0.170 1,563 861 75 0.087 2,716 390 0.144 Total 6,698 3,603 956 0.265 20,878 11,227 4,587 0.409 14,830 5,544 0.374 District Table 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year District Maize Short Rainy bseason Long Rainy bSeason Total Table 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultural Year Paddy Short Rainy bseason Table 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sorghum Short Rainy bseason Long Rainy bSeason Total Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 165 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 376 102 43 0.420 102 43 0.420 M'goro R 0 0 0 0 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0 248 63 47 0.741 63 47 0.741 Ulanga 0 0 0 0 0 0 0 0.000 0 0 0.000 Morogoro Urb 0 0 0 0 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 624 165 90 0.543 165 90 0.543 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 522 406 65 0.161 406 65 0.161 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Morogoro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 128 39 19 0.494 101 10 5 0.494 49 24 0.494 Total 128 39 19 0.494 623 416 70 0.169 455 89 0.197 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 653 238 223 0.936 238 223 0.936 M'goro R 0 0 0 0 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0 0 0 0 0.000 0 0 0.000 Morogoro Urb 0 0 0 0 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 653 238 223 0.936 238 223 0.936 Table 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District; 2002/03 Agricultural Year District Fingemillet Short Rainy bseason Long Rainy bSeason Total Table 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bulrushmillets Short Rainy bseason Long Rainy bSeason Total Table 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/03 Agricultural Year District Wheat Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 166 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 130 53 0 0.000 0 0 0 0.000 53 0 0.000 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 156 63 40 0.630 63 40 0.630 Morogoro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0.000 101 41 0 0.000 41 0 0.000 Total 130 53 0 0.000 257 104 40 0.382 157 40 0.254 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 258 38 54 1.420 5,718 2,445 2,435 0.996 2,483 2,488 1.002 M'goro R 487 177 79 0.449 14,087 5,388 6,878 1.277 5,564 6,957 1.250 Kilombero 980 256 431 1.685 6,913 1,918 8,023 4.183 2,174 8,454 3.889 Ulanga 463 45 75 1.656 5,970 1,489 1,890 1.270 1,534 1,965 1.281 Morogoro Urb 9 2 5 3.004 1,417 445 1,037 2.332 446 1,042 2.335 Mvomero 123 12 22 1.778 5,327 4,961 2,696 0.544 4,973 2,718 0.547 Total 2,318 530 667 1.258 39,432 16,644 22,958 1.379 17,174 23,625 1.376 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 125 25 38 1.482 3,455 1,641 2,782 1.696 1,666 2,819 1.692 M'goro R 123 25 25 0.988 359 101 111 1.097 126 135 1.076 Kilombero 368 246 556 2.264 719 149 220 1.471 395 776 1.964 Ulanga 232 45 42 0.943 1,528 521 915 1.758 566 957 1.693 Morogoro Urb 18 4 14 3.978 77 15 27 1.771 19 41 2.191 Mvomero 372 91 30 0.327 372 88 124 1.417 179 154 0.862 Total 1,237 436 705 1.618 6,511 2,514 4,178 1.662 2,950 4,883 1.655 Table 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year District Barley Short Rainy bseason Long Rainy bSeason Total Table 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cassava Short Rainy bseason Long Rainy bSeason Total Table 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sweet potatoes Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 167 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 1,955 669 461 0.689 669 461 0.689 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 0 0 129 0.000 0 0 0 0.000 0 129 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Morogoro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 63 263 0 0.000 0 0 0 0.000 263 0 0.000 Total 63 263 129 0.491 1,955 669 461 0.689 932 590 0.633 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 115 17 46 2.772 17 46 2.772 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 129 52 261 4.999 0 0 0 0.000 52 261 4.999 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Morogoro Urb 0 0 0 0.000 51 8 14 1.826 8 14 1.826 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 129 52 261 4.999 166 24 60 2.475 77 322 4.195 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 768 170 703 4.132 170 703 4.132 M'goro R 834 790 286 0.361 245 40 20 0.494 830 305 0.368 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 154 15 15 1.051 0 0 0 0 15 15 1.051 Morogoro Urb 50 15 30 1.958 218 34 90 2.612 50 120 2.411 Mvomero 622 278 454 1.636 122 25 0 0.000 302 454 1.502 Total 1,660 1,098 785 0.715 1,353 269 813 3.021 1,367 1,598 1.169 Table 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Irish potatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year District Yams Short Rainy bseason Long Rainy bSeason Total District Cocoyams Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District; 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 168 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 0 0 0 0 0 0 0 M'goro R 122 49 24 0.504 0 0 0 0 49 24 0.504 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 0 0 0 0 0 0 0 0 0 0 0 Morogoro Urb 0 0 0 0 0 0 0 0 0 0 0 Mvomero 0 0 0 0 0 0 0 0 0 0 0 Total 122 49 24 0.504 0 0 0 0 49 24 0.504 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 3,853 1,413 943 0.667 13,488 6,400 2,732 0.427 7,813 3,675 0.470 M'goro R 1,460 466 212 0.455 2,506 796 1,215 1.526 1,262 1,427 1.130 Kilombero 129 26 26 0.988 237 48 11 0.222 74 36 0.492 Ulanga 1,065 612 246 0.402 2,488 957 495 0.517 1,569 741 0.472 Morogoro Urb 286 60 32 0.536 829 207 75 0.363 267 107 0.402 Mvomero 8,742 4,470 1,109 0.248 9,633 4,952 1,522 0.307 9,422 2,631 0.279 Total 15,536 7,047 2,568 0.364 29,182 13,360 6,050 0.453 20,407 8,617 0.422 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 1,592 314 122 0.389 4,381 983 154 0.156 1,298 276 0.213 M'goro R 4,531 1,182 412 0.349 3,722 771 186 0.242 1,953 599 0.307 Kilombero 893 252 119 0.473 818 146 64 0.435 397 182 0.459 Ulanga 991 117 55 0.465 1,841 601 514 0.855 719 569 0.791 Morogoro Urb 354 47 26 0.567 990 206 60 0.291 253 86 0.342 Mvomero 4,091 1,076 118 0.110 1,696 388 118 0.303 1,464 236 0.161 Total 12,451 2,987 853 0.285 13,446 3,096 1,095 0.354 6,083 1,948 0.320 Table 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year Table 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Mungbeans Short Rainy bseason Long Rainy bSeason Total District Beans Short Rainy bseason Long Rainy bSeason Total Table 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cowpeas Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 169 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 130 26 12 0.445 577 99 31 0.315 126 43 0.342 M'goro R 722 269 23 0.084 595 154 24 0.155 423 47 0.110 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 152 55 17 0.312 154 23 17 0.725 79 34 0.434 Morogoro Urb 12 1 0 0.198 150 38 8 0.218 39 9 0.217 Mvomero 495 161 4 0.026 378 126 37 0.297 287 42 0.145 Total 1,512 513 56 0.109 1,852 441 118 0.267 954 174 0.182 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 0 0 0 0 0 0 0 M'goro R 0 0 0 0 0 0 0 0 0 0 0 Kilombero 119 24 5 0.217 0 0 0 0 24 5 0.217 Ulanga 0 0 0 0 0 0 0 0 0 0 0 Morogoro Urb 0 0 0 0 0 0 0 0 0 0 0 Mvomero 128 41 3 0.062 0 0 0 0 41 3 0.062 Total 246 65 8 0.119 0 0 0 0 65 8 0.119 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 #DIV/0! 261 52 8 0.151 52 8 0.151 M'goro R 0 0 0 #DIV/0! 0 0 0 #DIV/0! 0 0 #DIV/0! Kilombero 0 0 0 #DIV/0! 0 0 0 #DIV/0! 0 0 #DIV/0! Ulanga 0 0 0 #DIV/0! 0 0 0 #DIV/0! 0 0 #DIV/0! Morogoro Urb 0 0 0 #DIV/0! 0 0 0 #DIV/0! 0 0 #DIV/0! Mvomero 0 0 0 #DIV/0! 0 0 0 #DIV/0! 0 0 #DIV/0! Total 0 0 0 #DIV/0! 261 52 8 0.151 52 8 0.151 Table 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bambanuts Short Rainy bseason Long Rainy bSeason Total Table 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chick peas Short Rainy bseason Long Rainy bSeason Total Table 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/03 Agricultural Year District Greengram Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 170 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 0 0 0 0 0 0 0 M'goro R 0 0 0 0 121 25 24 0.988 25 24 0.988 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 0 0 0 0 74 45 4 0.082 45 4 0.082 M'goro Urb 0 0 0 0 12 5 3 0.642 5 3 0.642 Mvomero 1,013 411 497 1.209 1,141 461 287 0.623 872 785 0.899 Total 1,013 411 497 1.209 1,348 535 318 0.594 947 816 0.861 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 627 236 90 0.381 236 90 0.381 M'goro R 0 0 0 0 0 0 0 0 0 0 0 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 0 0 0 0 0 0 0 0 0 0 0 M'goro Urb 0 0 0 0 61 24 7 0.300 24 7 0.300 Mvomero 0 0 0 0 614 235 37 0.155 235 37 0.155 Total 0 0 0 0 1,303 495 133 0.270 495 133 0.270 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 3,557 1,780 447 0.251 5,752 2,444 721 0.295 4,223 1,168 0.276 M'goro R 640 230 85 0.371 9,308 4,482 1,330 0.297 4,712 1,415 0.300 Kilombero 0 0 0 0 127 13 4 0.296 13 4 0.296 Ulanga 308 101 46 0.453 540 212 46 0.219 313 92 0.294 M'goro Urb 0 0 0 0 65 38 7 0.187 38 7 0.187 Mvomero 239 48 4 0.087 369 174 62 0.359 222 67 0.300 Total 4,744 2,159 582 0.269 16,162 7,362 2,170 0.295 9,521 2,752 0.289 Table 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultural Year District Simsim Short Rainy bseason Long Rainy bSeason Total Table 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sunflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Fieldpeas Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 171 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 715 156 64 0.407 3,556 1,670 607 0.364 1,826 671 0.367 M'goro R 119 12 12 0.988 0 0 0 0 12 12 0.988 Kilombero 0 0 0 0 703 398 330 0.830 398 330 0.830 Ulanga 304 126 55 0.435 601 144 44 0.307 271 99 0.366 M'goro Urb 0 0 0 0 25 7 2 0.267 7 2 0.267 Mvomero 124 13 37 2.964 0 0 0 0 13 37 2.964 Total 1,261 307 168 0.545 4,885 2,219 984 0.443 2,527 1,152 0.456 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0 515 128 116 0.907 128 116 0.907 M'goro R 0 0 0 0 0 0 0 0 0 0 0 Kilombero 0 0 0 0 0 0 0 0 0 0 0 Ulanga 0 0 0 0 0 0 0 0 0 0 0 M'goro Urb 0 0 0 0 0 0 0 0 0 0 0 Mvomero 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 515 128 116 0.907 128 116 0.907 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 105 11 2 0.198 128 52 11 0.222 62 14 0.218 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 0 0 0 0.000 12 2 0 0.049 2 0 0.049 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 105 11 2 0.198 139 54 12 0.215 65 14 0.212 Table 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Soya beans Short Rainy bseason Long Rainy bSeason Total Table 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 Agricultural Year District Castor oil Short Rainy bseason Long Rainy bSeason Total Table 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Groundnuts Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 172 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 102 21 6 0.296 21 6 0.296 M'goro R 122 61 0 0.000 0 0 0 0.000 61 0 0.000 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 78 5 2 0.494 305 51 33 0.635 56 35 0.623 M'goro Urb 36 2 1 0.615 223 24 57 2.343 26 58 2.231 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 236 68 3 0.050 630 96 96 0.993 164 99 0.603 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 240 24 31 1.290 0 0 0 0.000 24 31 1.290 M'goro R 122 20 66 3.335 0 0 0 0.000 20 66 3.335 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 384 48 45 0.935 48 45 0.935 M'goro Urb 0 0 0 0.000 13 1 2 4.199 1 2 4.199 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 362 44 97 2.208 397 49 47 0.969 93 145 1.557 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 254 76 217 2.850 1,253 467 3,139 6.718 544 3,356 6.175 M'goro R 0 0 0 0.000 244 49 51 1.035 49 51 1.035 Kilombero 0 0 0 0.000 116 47 233 4.940 47 233 4.940 Ulanga 74 45 185 4.117 76 8 30 3.952 53 215 4.093 M'goro Urb 11 4 17 3.952 0 0 0 0.000 4 17 3.952 Mvomero 505 180 637 3.546 375 89 177 1.993 268 814 3.033 Total 844 305 1,057 3.462 2,064 660 3,630 5.499 965 4,687 4.854 Table 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year District Onion Short Rainy bseason Long Rainy bSeason Total Table 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bitter Aubergine Short Rainy bseason Long Rainy bSeason Total Table 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year District Okra Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 173 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 131 26 7 0.272 131 26 7 0.272 53 14 0.272 M'goro R 365 112 71 0.634 365 112 71 0.634 223 141 0.634 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 151 76 23 0.301 151 76 23 0.301 151 45 0.301 M'goro Urb 92 16 33 2.075 92 16 33 2.075 32 66 2.075 Mvomero 1,145 438 3,831 8.752 1,145 438 3,831 8.752 875 7,662 8.752 Total 1,883 667 3,965 5.943 1,883 667 3,965 5.943 1,334 7,930 5.943 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 1,685 557 1,082 1.944 3,132 722 2,985 4.137 1,278 4,067 3.182 M'goro R 2,774 852 3,852 4.521 1,310 362 617 1.706 1,214 4,469 3.683 Kilombero 733 211 652 3.093 501 61 528 8.706 271 1,180 4.347 Ulanga 77 16 6 0.395 1,068 131 742 5.642 147 748 5.088 M'goro Urb 222 42 138 3.268 292 53 143 2.691 95 281 2.947 Mvomero 2,482 1,008 3,969 3.938 5,473 2,146 7,033 3.278 3,154 11,002 3.489 Total 7,972 2,685 9,700 3.612 11,777 3,474 12,047 3.468 6,159 21,747 3.531 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 197 40 34 0.863 0 0 0 0.000 40 34 0.863 M'goro R 348 54 119 2.183 103 21 47 2.223 75 165 2.194 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 13 1 3 1.830 0 0 0 0.000 1 3 1.830 Mvomero 0 0 0 0.000 352 67 144 2.144 67 144 2.144 Total 558 96 156 1.628 455 88 191 2.163 184 347 1.884 Table 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/03 Agricultural Year District Spinnach Short Rainy bseason Long Rainy bSeason Total Table 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tomatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cabbage Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 174 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro R 123 50 27 0.543 121 25 24 0.988 74 51 0.690 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 0 0 0 0.000 39 5 10 1.853 5 10 1.853 Mvomero 500 398 464 1.165 0 0 0 0.000 398 464 1.165 Total 623 448 491 1.096 160 30 34 1.142 478 525 1.099 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 242 25 17 0.699 239 48 105 2.160 73 122 1.669 M'goro R 242 74 73 0.988 366 62 27 0.434 135 99 0.735 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 0 0 0 0.000 18 3 4 1.256 3 4 1.256 Mvomero 500 180 353 1.966 634 141 395 2.793 321 748 2.330 Total 984 278 443 1.595 1,257 255 530 2.081 533 973 1.828 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 230 9 2 0.247 592 94 44 0.466 103 46 0.446 M'goro R 346 42 137 3.247 448 45 58 1.282 88 195 2.229 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 227 12 3 0.247 12 3 0.247 M'goro Urb 0 0 0 0.000 39 3 5 1.716 3 5 1.716 Mvomero 253 38 133 3.462 1,710 212 466 2.195 251 600 2.390 Total 828 90 273 3.029 3,017 367 577 1.571 457 849 1.858 Table 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year District Amaranths Short Rainy bseason Long Rainy bSeason Total Table 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chillies Short Rainy bseason Long Rainy bSeason Total Table 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year District Carrot Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 175 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 233 37 8 0.219 1,794 240 1,147 4.771 277 1,155 4.168 M'goro R 122 12 15 1.186 366 109 48 0.443 121 63 0.519 Kilombero 770 103 128 1.247 258 20 35 1.755 123 163 1.330 Ulanga 531 47 114 2.438 1,216 153 97 0.638 199 211 1.060 M'goro Urb 97 8 9 1.096 317 43 45 1.049 51 54 1.056 Mvomero 251 31 8 0.266 612 145 222 1.530 176 231 1.310 Total 2,005 237 282 1.188 4,563 710 1,595 2.246 947 1,877 1.981 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro R 0 0 0 0.000 123 25 16 0.642 25 16 0.642 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 75 6 1 0.124 6 1 0.124 M'goro Urb 32 4 4 0.996 13 5 6 1.247 9 10 1.137 Mvomero 367 87 275 3.176 123 25 10 0.395 112 285 2.557 Total 399 91 279 3.078 334 61 33 0.541 152 312 2.058 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 119 0 1 1.235 0 1 1.235 M'goro R 122 25 13 0.519 122 12 6 0.474 37 19 0.504 Kilombero 123 25 45 1.803 0 0 0 0.000 25 45 1.803 Ulanga 0 0 0 0.000 460 61 49 0.798 61 49 0.798 M'goro Urb 13 1 3 2.075 18 6 13 2.377 7 16 2.319 Mvomero 118 24 24 0.988 0 0 0 0.000 24 24 0.988 Total 376 75 84 1.123 718 80 68 0.861 154 153 0.988 Table 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/03 Agricultural Year District Eggplant Short Rainy bseason Long Rainy bSeason Total Table 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cucumber Short Rainy bseason Long Rainy bSeason Total Table 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year District Pumpkins Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 176 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro R 121 98 48 0.494 0 0 0 0.000 98 48 0.494 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 20 1 6 3.953 0 0 0 0.000 1 6 3.953 Mvomero 0 0 0 0.000 127 51 38 0.741 51 38 0.741 Total 141 99 54 0.545 127 51 38 0.741 151 92 0.612 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro R 121 49 24 0.494 121 25 24 0.988 74 48 0.659 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 121 49 24 0.494 121 25 24 0.988 74 48 0.659 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 513 311 111 0.357 311 111 0.357 M'goro R 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 0 0 0 0.000 613 258 121 0.470 258 121 0.470 M'goro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0.000 128 52 15 0.296 52 15 0.296 Total 0 0 0 0.000 1,254 620 248 0.399 620 248 0.399 Table 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cotton Short Rainy bseason Long Rainy bSeason Total Table 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cauliflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year District Water Mellon Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 177 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Kilosa 0 0 0 0.000 0 0 0 0.000 0 0 0.000 M'goro R 0 0 0 0.000 365 62 35 0.573 62 35 0.573 Kilombero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ulanga 76 16 2 0.143 0 0 0 0.000 16 2 0.143 M'goro Urb 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mvomero 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 76 16 2 0.143 365 62 35 0.573 78 38 0.485 Table 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tobacco Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 178 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 179 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha Pigeon Pea 533 577 222 384 Star Fruit 94 0 10 0 Palm Oil 402 0 46 0 Coconut 1,397 637 4,275 6712 Cashewnut 379 235 11 47 Coffee 5 . . 0 Kapok . . . 0 Sugarcane 2,588 2,374 49,448 20833 Tamarin . . . 0 Jack Fruit 94 0 10 0 Mpesheni . 0 . 0 Banana 1,961 2,708 4,176 1542 Avocado 0 0 1 0 Mango 1,433 718 3,188 4442 Pawpaw 106 94 306 3253 Pineapple 13 47 121 2580 Orange 421 10 462 45220 Mandarine/Tan gerine 95 0 24 0 Guava 83 0 126 0 Lime/Lemon . 0 14 0 District Total 9,604 7,399 62,443 8439 Black Pepper 11 10 31 3196 Pigeon Pea 167 141 65 460 Palm Oil 2 0 . 0 Coconut 5,086 1,413 4,968 3516 Cashewnut 27 74 5 67 Coffee 266 215 91 422 Sugarcane 199 199 1,690 8497 Cardamon 49 25 10 395 Cinamon 49 49 22 442 Cloves 194 175 80 459 Mshelisheli 69 69 487 7035 Jack Fruit 2,214 2,018 618 306 Banana 2,722 2,483 17,000 6847 Mango 889 462 3,220 6962 Pawpaw 58 57 142 2507 Pineapple 2,371 2,370 5,711 2409 Orange 2,776 2,519 8,140 3232 Grape Fruit 6 6 14 2280 Mandarine/Tan gerine 74 62 2,450 39382 Guava 139 23 3 148 Lime/Lemon 0 0 10 0 District Total 17,368 12,370 44,756 3618 Malay Apple 0 0 29 0 Palm Oil 172 0 1,893 0 Coconut 296 12 7,263 605114 Cashewnut 35 0 20 0 Cocoa 11 0 25 0 Sugarcane 2,573 2,570 74,956 29168 Jack Fruit 6 0 13 0 Mpesheni 0 0 1 0 Kilombero Table 7.3 Production of Permanent Crops by crop type and Region - Morogoro District/Crop Kilosa Morogoro Rural Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 180 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha Table 7.3 Production of Permanent Crops by crop type and Region - Morogoro District/Crop Banana 1,330 897 15,415 17177 Avocado 0 0 105 0 Mango 615 118 34,734 294438 Pawpaw 1 0 1,505 0 Pineapple 0 0 346 0 Orange 1,049 374 20,718 55455 Grape Fruit 0 0 58 0 Mandarine/Tan 0 0 273 0 Guava 0 0 441 0 Lime/Lemon 2 0 330 0 District Total 6,093 3,971 158,123 39821 Sour Soup . . 5 0 Pigeon Pea 20 22 20 916 Malay Apple 20 20 3 124 Palm Oil 101 81 68 842 Coconut 246 68 506 7425 Cashewnut 72 71 33 467 Sugarcane 118 114 4,199 36891 Tamarin 19 19 1 76 Jack Fruit 1 0 3 0 Mpesheni . . 1 0 Banana 950 399 2,430 6085 Avocado 0 0 5 0 Mango 319 199 2,853 14359 Pawpaw 122 1,852 263 142 Pineapple 0 0 12 0 Orange 97 68 361 5329 Grape Fruit 0 0 11 0 Mandarine/Tan 1 0 56 0 Guava 22 22 46 2120 Lime/Lemon 16 0 18 0 District Total 2,125 2,935 10,894 3712 Pigeon Pea 323 82 52 632 Star Fruit 0 0 3 0 Coconut 27 81 155 1916 Cashewnut 32 33 3 95 Sugarcane 56 52 658 12719 Mshelisheli 1 0 8 0 Jack Fruit 12 8 127 16337 Mpesheni 1 1 1 1100 Banana 1,177 1,640 5,206 3174 Avocado 8 8 69 9095 Mango 64 167 422 2524 Pawpaw 14 13 5 397 Pineapple 17 14 25 1791 Orange 11 13 510 38218 Grape . 1 0 865 Mandarine/Tan 3 3 113 35280 Guava 2 2 6 2430 Pears . . 0 0 Pitches 0 0 0 0 Lime/Lemon 1 0 20 0 Ulanga Morogoro Urban Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 181 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha Table 7.3 Production of Permanent Crops by crop type and Region - Morogoro District/Crop Rambutan . . . 0 District Total 1,749 2,117 7,383 3487 Sour Soup 0 0 6 0 Pigeon Pea 1,071 650 515 793 Malay Apple 0 0 3 0 Palm Oil 82 0 204 0 Coconut 498 538 796 1480 Cashewnut 25 0 609 0 Coffee 102 132 160 1213 Cocoa 937 357 260 730 Sugarcane 2,795 2,108 82,605 39193 Cardamon 194 88 16 183 Jack Fruit 565 41 12 301 Banana 1,256 800 3,188 3984 Mango 1,983 846 5,074 5994 Pawpaw 2 10 97 9927 Pineapple 525 0 1 0 Orange 195 88 693 7834 Grape Fruit 30 0 . 0 Mandarine/Tan 3,477 313 265 846 Guava 0 0 57 0 Plums . . 589 0 Apples . . 57 0 Pears 36 . 47 0 Pitches . . 134 0 Lime/Lemon 0 0 31 0 District Total 13,773 5,971 95,419 15979 Sour Soup 0 0 11 0 Black Pepper 11 10 31 3196 Pigeon Pea 2,113 1,471 873 593 Malay Apple 21 20 34 1673 Star Fruit 94 0 14 0 Palm Oil 758 81 2,211 27254 Coconut 7,550 2,749 17,963 6535 Cashewnut 570 413 682 1649 Coffee 373 347 251 723 Cocoa 948 357 285 799 Kapok . . . 0 Sugarcane 8,330 7,416 213,556 28798 Cardamon 243 113 26 229 Tamarin 19 19 1 76 Cinamon 49 49 22 442 Cloves 194 175 80 459 Mshelisheli 70 69 495 7148 Jack Fruit 2,892 2,067 783 379 Mpesheni 1 1 3 4034 Banana 9,396 8,928 47,415 5311 Avocado 8 8 180 23789 Mango 5,302 2,511 49,490 19713 Pawpaw 303 2,026 2,319 1145 Pineapple 2,926 2,431 6,216 2557 Orange 4,549 3,072 30,883 10053 Region Total Mvomero Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 182 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha Table 7.3 Production of Permanent Crops by crop type and Region - Morogoro District/Crop Grape Fruit 36 6 84 13354 Grape . 1 0 865 Mandarine/Tan 3,651 379 3,180 8399 Guava 248 47 679 14328 Plums . . 589 0 Apples . . 57 0 Pears 36 . 47 0 Pitches 0 0 134 0 Lime/Lemon 19 0 423 0 Rambutan . . . 0 Region Total 50,712 34,764 379,018 10903 Cont… Area Planted by crop type - Morogoro Crop Area Planted % Banana 9,396 18.5 Sugarcane 8,330 16.4 Coconut 7,550 14.9 Mango 5,302 10.5 Orange 4,549 9.0 Mandarine/Tangerine 3,651 7.2 Pineapple 2,926 5.8 Jack Fruit 2,892 5.7 Pigeon Pea 2,113 4.2 Cocoa 948 1.9 Palm Oil 758 1.5 Cashewnut 570 1.1 Coffee 373 0.7 Pawpaw 303 0.6 Guava 248 0.5 Cardamon 243 0.5 Cloves 194 0.4 Star Fruit 94 0.2 Mshelisheli 70 0.1 Cinamon 49 0.1 Grape Fruit 36 0.1 Pears 36 0.1 Malay Apple 21 0.0 Lime/Lemon 19 0.0 Tamarin 19 0.0 Black Pepper 11 0.0 Avocado 8 0.0 Mpesheni 1 0.0 Pitches 0 0.0 Sour Soup 0 0.0 Kapok 0 0.0 Grape 0 0.0 Plums 0 0.0 Apples 0 0.0 Rambutan 0 0.0 Region Total 50,712 100.0 Tanzania Agriculture Sample Census - 2003 Morogoro 183 Appendix II 184 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 185 Number % Number % Number % Kilosa 62,088 85 11,348 15 73,435 100 Morogoro Rural 46,205 87 6,912 13 53,117 100 Kilombero 48,044 98 739 2 48,782 100 Ulanga 30,370 98 538 2 30,908 100 Morogoro Urban 3,718 84 716 16 4,434 100 Mvomero 41,714 83 8,356 17 50,069 100 Total 232,139 89 28,607 11 260,746 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Other By Factory Total Kilosa 18,752 3,293 39,561 0 390 0 91 62,088 Morogoro Rural 20,526 4,732 20,948 0 0 0 0 46,205 Kilombero 8,383 2,155 37,262 119 125 0 0 48,044 Ulanga 6,866 1,684 21,744 0 0 77 0 30,370 Morogoro Urban 662 461 2,404 0 178 13 0 3,718 Mvomero 6,488 1,991 30,737 0 1,990 508 0 41,714 Total 61,677 14,316 152,655 119 2,684 597 91 232,139 % 26.57 6.17 65.76 0.05 1.16 0.26 0.04 100.00 8.0b: Number of Crop Growing Households by Method of Processing and District; 2002/03 Agriculture Year District Method of Processing 8.0a Number of Crops Growing Houreported to have procesed Farm Products by District; 2002/03 agriculture Year District Did the Hh Process any of the products harvested during 2002 Households That Processed Product Households That Did Not Process Product Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 186 On Farm by Hand On Farm by Machine By Neighbour Machine By Co-operative Union By Trader Other By Factory Total Maize 39,065 13,663 139,657 119 2,440 266 91 195,302 Paddy 32,703 4,529 65,586 318 515 227 0 103,878 Sorghum 7,052 1,328 6,127 0 12 0 0 14,520 Bulrush Millet 261 0 131 0 0 0 0 392 Finger Millet 0 0 129 0 0 0 0 129 Wheat 131 0 131 0 0 0 0 261 Cassava 12,642 0 2,898 0 0 75 0 15,616 Sweet Potatoes 426 0 90 0 0 0 0 516 Beans 76 0 13 0 0 0 0 88 Cowpeas 38 115 128 0 0 0 0 280 Green Gram 11 0 0 0 0 0 0 11 Sunflower 12 0 105 0 11 0 0 128 Simsim 518 0 0 0 0 0 0 518 Groundnut 917 0 0 0 0 0 0 917 Oil Palm 1,493 0 0 0 0 151 0 1,644 Coconut 8,596 0 0 0 0 1,186 0 9,782 Cashewnut 285 0 0 0 0 0 0 285 Banana 155 0 0 0 0 0 0 155 Orange 0 0 129 0 0 0 0 129 Tomatoes 0 0 5 0 0 0 0 5 Total 104,382 19,634 215,128 437 2,978 1,905 91 344,556 Human Cooking Sale Only Consumption Did Not Use Other Total Maize 190,925 486 1,558 593 1,605 135 195,302 Paddy 101,035 564 1,441 75 763 0 103,878 Sorghum 14,147 0 0 131 119 123 14,520 Bulrush Millet 392 0 0 0 0 0 392 Finger Millet 129 0 0 0 0 0 129 Wheat 261 0 0 0 0 0 261 Cassava 14,078 0 1,538 0 0 0 15,616 Sweet Potatoes 516 0 0 0 0 0 516 Beans 88 0 0 0 0 0 88 Cowpeas 166 0 115 0 0 0 280 Green Gram 11 0 0 0 0 0 11 Sunflower 128 0 0 0 0 0 128 Simsim 518 0 0 0 0 0 518 Groundnut 696 0 222 0 0 0 917 Oil Palm 1,440 0 205 0 0 0 1,644 Coconut 9,479 111 0 0 192 0 9,782 Cashewnut 285 0 0 0 0 0 285 Banana 155 0 0 0 0 0 155 Orange 0 0 129 0 0 0 129 Tomatoes 5 0 0 0 0 0 5 Total 334,454 1,162 5,206 798 2,678 258 344,556 Method of Processing Crop Table 8.1.1a AGROPROCESSING: Number of Growing households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Morogoro Product Use Table 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Use of Product and Crop, Morogoro Rgion Crop Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 187 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Did not Sell Total Maize 7,651 2,547 244 557 94 78 1,848 179,223 195,302 Paddy 4,864 2,165 207 243 223 142 1,532 92,421 103,878 Sorghum 480 197 0 0 0 0 131 13,712 14,520 Bulrush Millet 0 0 0 0 0 0 0 392 392 Finger Millet 0 0 0 0 0 0 0 129 129 Wheat 0 0 0 0 0 0 131 131 261 Cassava 1,854 609 0 124 0 0 245 12,783 15,616 Sweet Potatoes 0 0 0 0 0 0 0 516 516 Beans 0 0 0 0 0 0 0 88 88 Cowpeas 0 0 0 0 0 0 0 280 280 Green Gram 0 0 0 0 0 0 0 11 11 Sunflower 0 0 0 12 0 0 0 116 128 Simsim 0 0 0 0 118 0 0 400 518 Groundnut 0 222 0 0 0 0 0 696 917 Oil Palm 529 0 0 0 0 0 0 1,115 1,644 Coconut 396 476 0 0 0 0 9 8,901 9,782 Cashewnut 0 0 0 0 0 0 0 285 285 Banana 0 0 0 0 0 0 0 155 155 Orange 0 0 0 0 0 0 0 129 129 Tomatoes 0 0 0 0 0 0 0 5 5 Total 15,774 6,217 451 936 435 220 3,895 311,488 344,556 Where Sold Crop Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 188 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 7,651 2,547 244 557 94 78 1,848 3,061 179,223 195,302 Paddy 4,864 2,165 207 243 223 142 1,532 2,080 92,421 103,878 Sorghum 480 197 0 0 0 0 131 0 13,712 14,520 Bulrush Millet 0 0 0 0 0 0 0 0 392 392 Finger Millet 0 0 0 0 0 0 0 0 129 129 Wheat 0 0 0 0 0 0 131 0 131 261 Cassava 1,854 609 0 124 0 0 245 0 12,783 15,616 Sweet Potatoes 0 0 0 0 0 0 0 0 516 516 Beans 0 0 0 0 0 0 0 0 88 88 Cowpeas 0 0 0 0 0 0 0 0 280 280 Green Gram 0 0 0 0 0 0 0 0 11 11 Sunflower 0 0 0 12 0 0 0 0 116 128 Simsim 0 0 0 0 118 0 0 0 400 518 Groundnut 0 222 0 0 0 0 0 0 696 917 Oil Palm 529 0 0 0 0 0 0 0 1,115 1,644 Coconut 396 476 0 0 0 0 9 0 8,901 9,782 Cashewnut 0 0 0 0 0 0 0 0 285 285 Banana 0 0 0 0 0 0 0 0 155 155 Orange 0 0 0 0 0 0 0 0 129 129 Tomatoes 0 0 0 0 0 0 0 0 5 5 Total 15,774 6,217 451 936 435 220 3,895 5,140 311,488 344,556 Flour / Meal Grain Oil Juice Fiber Other Total Kilosa 50,547 10,468 949 0 124 0 62,088 Morogoro Rural 30,897 13,638 1,322 0 0 349 46,205 Kilombero 20,356 26,936 751 0 0 0 48,044 Ulanga 15,487 14,811 72 0 0 0 30,370 Morogoro Urban 3,486 208 24 0 0 0 3,718 Mvomero 34,913 6,170 508 123 0 0 41,714 Total 155,687 72,230 3,626 123 124 349 232,139 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Kilosa 60,722 0 131 222 1,013 0 62,088 Morogoro Rural 43,547 121 1,938 0 476 123 46,205 Kilombero 47,419 123 0 0 502 0 48,044 Ulanga 29,999 0 296 75 0 0 30,370 Morogoro Urban 3,634 0 12 48 12 12 3,718 Mvomero 40,962 246 127 378 0 0 41,714 Total 226,283 490 2,504 723 2,003 135 232,139 Where Sold Crop[ Table 8.1.1.c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Morogoro Region 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 189 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Kilosa 1,262 250 0 129 0 129 783 0 59,535 62,088 Morogoro Rural 2,299 1,559 122 0 118 0 0 0 42,107 46,205 Kilombero 2,234 258 129 0 94 0 1,375 2,204 41,750 48,044 Ulanga 1,749 1,987 0 76 0 78 464 0 26,016 30,370 Morogoro Urban 62 35 0 12 0 0 18 167 3,425 3,718 Mvomero 2,115 0 0 0 0 0 121 1,234 38,243 41,714 Total 9,722 4,089 252 217 212 207 2,760 3,605 211,075 232,139 Bran Cake Husk Juice Fiber Pulp Shell No by- product Other Total Kilosa 47,982 0 2,920 0 0 0 0 11,185 0 62,088 Morogoro Rural 31,728 1,457 3,703 0 0 0 360 8,842 115 46,205 Kilombero 30,478 246 16,448 117 258 0 116 381 0 48,044 Ulanga 15,443 1,285 12,114 0 0 0 77 1,451 0 30,370 Morogoro Urban 3,060 21 130 0 12 9 13 473 0 3,718 Mvomero 22,569 492 5,052 251 0 0 493 12,857 0 41,714 Total 151,260 3,501 40,367 368 270 9 1,059 35,190 115 232,139 District By Product Table 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 190 MARKETING Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 191 Number % Number % Kilosa 43,822 59.7 29,613 40.3 73,435 Morogoro Rural 36,603 68.9 16,514 31.1 53,117 Kilombero 42,308 86.7 6,474 13.3 48,782 Ulanga 22,824 73.8 8,084 26.2 30,908 Morogoro Urban 3,357 75.7 1,077 24.3 4,434 Mvomero 33,987 67.9 16,082 32.1 50,069 Total 182,902 70.1 77,843 29.9 260,746 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Kilosa 881 27,441 125 0 769 633 126 3,139 37,246 70,359 Morogoro Rural 122 19,670 61 0 176 0 0 2,039 30,451 52,519 Kilombero 257 9,904 0 129 127 0 0 129 36,551 47,097 Ulanga 222 11,120 74 0 77 77 77 156 18,425 30,228 Morogoro Urban 25 2,030 0 26 0 0 36 38 2,017 4,172 Mvomero 372 16,264 0 0 249 0 0 1,431 28,510 46,826 Total 1,879 86,429 260 155 1,398 710 239 6,932 153,201 251,201 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Kilosa 1.25 39.00 0.18 0.00 1.09 0.90 0.18 4.46 52.94 100.00 Morogoro Rural 0.23 37.45 0.12 0.00 0.33 0.00 0.00 3.88 57.98 100.00 Kilombero 0.55 21.03 0.00 0.27 0.27 0.00 0.00 0.27 77.61 100.00 Ulanga 0.73 36.79 0.24 0.00 0.26 0.25 0.26 0.52 60.95 100.00 Morogoro Urban 0.60 48.66 0.00 0.62 0.00 0.00 0.87 0.91 48.34 100.00 Mvomero 0.79 34.73 0.00 0.00 0.53 0.00 0.00 3.06 60.89 100.00 Total 0.75 34.41 0.10 0.06 0.56 0.28 0.10 2.76 60.99 100.00 10.1: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District Number of Households that Sold Number of Households that Did not Sell Total Number of Household Table 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by district during 2002/03 agriculture Y 10.2 MARETING: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District District Main Reasons for Not Selling Crops Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 192 IRRIGATION /EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 193 Number of Household % Number of Household % Kilosa 8,916 12.1 64,519 87.9 73,435 Morogoro Rural 1,560 2.9 51,557 97.1 53,117 Kilombero 1,796 3.7 46,986 96.3 48,782 Ulanga 1,907 6.2 29,001 93.8 30,908 Morogoro Urban 281 6.3 4,152 93.7 4,434 Mvomero 7,231 14.4 42,838 85.6 50,069 Total 21,693 8.3 239,053 91.7 260,746 District Irrigated Area Area Irrigated Land this Year % Kilosa 4,877 4,406 90 Morogoro Rural 833 483 58 Kilombero 730 569 78 Ulanga 523 414 79 Morogoro Urban 122 87 71 Mvomero 4,368 3,372 77 Total 11,453 9,330 81 River Lake Well Borehole Canal Pipe water Total Kilosa 6,378 105 1,119 0 1,314 0 8,916 Morogoro Rural 472 0 0 0 1,088 0 1,560 Kilombero 915 0 635 0 129 116 1,796 Ulanga 835 0 686 0 0 386 1,907 Morogoro Urban 180 0 37 12 52 0 281 Mvomero 3,356 0 835 0 3,041 0 7,231 Total 12,136 105 3,313 12 5,624 502 21,693 Gravity Hand Bucket Hand Pump Motor Pump Other Total Kilosa 6,528 1,866 131 392 0 8,916 Morogoro Rural 725 835 0 0 0 1,560 Kilombero 1,055 741 0 0 0 1,796 Ulanga 381 1,373 0 76 77 1,907 Morogoro Urban 180 101 0 0 0 281 Mvomero 4,266 2,722 0 243 0 7,231 Total 13,136 7,639 131 710 77 21,693 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water Total Number of household 11.2: IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water Households Practicing Irrigation Households not Practicing Irrigation Table 11.1: Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 194 Flood Sprinkler Water Hose Watering Can Total Kilosa 6,789 0 392 1,736 8,916 Morogoro Rural 122 0 0 1,439 1,560 Kilombero 927 0 0 868 1,796 Ulanga 381 0 76 1,450 1,907 Morogoro Urban 177 0 0 105 281 Mvomero 1,862 250 0 5,119 7,231 Total 10,258 250 467 10,717 21,693 Number % Number % Kilosa 2,308 3 71,127 97 73,435 Morogoro Rural 1,781 3 51,336 97 53,117 Kilombero 982 2 47,800 98 48,782 Ulanga 768 2 30,140 98 30,908 Morogoro Urban 530 12 3,904 88 4,434 Mvomero 2,526 5 47,544 95 50,069 Total 8,894 3 251,852 97 260,746 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total number of Structures Kilosa . 7,961 . 1,697 375 2,249 . . 12,281 Morogoro Rural 17,160 729 0 734 1,223 4,369 0 478 24,693 Kilombero 455 4,302 . 123 . 1,508 . . 6,389 Ulanga . 6,473 . . . 1,622 77 . 8,172 Morogoro Urban 828 2,737 364 232 381 486 147 . 5,175 Mvomero . 47,465 . . 5,220 9,932 759 . 63,376 Total 18,443 69,668 364 2,785 7,199 20,166 983 478 120,086 11.5: IRRIGATION: Number of Households by Method of Field Application of Irrigation Water and District for the 2002/03 agricultural Year District Method of Application 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have facility Does Not Have Facility Tanzania Agriculture Sample Census - 2003 Morogoro 195 Appendix II 196 ACCESS TO FARM INPUTS AND IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 197 Number % Number % Number % Kilosa 4,288 6 69,147 94 73,435 100 Morogoro 328 1 52,554 99 52,882 100 Kilombero 4,103 8 44,679 92 48,782 100 Ulanga 533 2 30,375 98 30,908 100 Morogoro Urban 393 9 4,041 91 4,434 100 Mvomero 7,729 15 42,340 85 50,069 100 Total 17,374 7 243,137 93 260,511 100 Number % Number % Number % Kilosa 6,024 8 67,541 92 73,566 100 Morogoro 1,415 3 52,179 97 53,594 100 Kilombero 1,821 4 47,329 96 49,150 100 Ulanga 839 3 30,069 97 30,908 100 Morogoro Urban 208 5 4,251 95 4,459 100 Mvomero 4,630 9 45,440 91 50,069 100 Total 14,937 6 246,809 94 261,746 100 Number % Number % Number % Kilosa 517 1 72,918 99 73,435 100 Morogoro 3,747 7 49,613 93 53,359 100 Kilombero 706 1 47,957 99 48,663 100 Ulanga 155 1 30,753 99 30,908 100 Morogoro Urban 75 2 4,359 98 4,434 100 Mvomero 2,220 4 47,849 96 50,069 100 Total 7,421 3 253,448 97 260,869 100 Number % Number % Number % Kilosa 4,388 6 68,917 94 73,305 100 Morogoro 1,185 2 51,810 98 52,995 100 Kilombero 1,422 3 47,486 97 48,908 100 Ulanga 2,914 9 27,994 91 30,908 100 Morogoro Urban 318 7 4,104 93 4,421 100 Mvomero 10,597 21 39,473 79 50,069 100 Total 20,823 8 239,784 92 260,607 100 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Number of Number of Total Number of District Number of Number of Total District Number of Number of Total Total District Number of Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 198 Number % Number % Number % Kilosa 1,094 1 72,341 99 73,435 100 Morogoro 115 0 52,766 100 52,881 100 Kilombero 10,707 22 37,830 78 48,537 100 Ulanga 7,598 25 23,311 75 30,908 100 Morogoro Urban 37 1 4,397 99 4,434 100 Mvomero 1,436 3 48,633 97 50,069 100 Total 20,987 8 239,278 92 260,265 100 Number % Number % Number % Kilosa 7,497 10 65,938 90 73,435 100 Morogoro 3,702 7 49,411 93 53,113 100 Kilombero 5,531 11 43,122 89 48,653 100 Ulanga 3,432 11 27,477 89 30,908 100 Morogoro Urban 1,690 38 2,731 62 4,421 100 Mvomero 16,833 34 33,236 66 50,069 100 Total 38,684 15 221,916 85 260,600 100 Number % Number % Number % Number % Kilosa 210 0 0 0 3,711 5 0 0 Morogoro 0 0 0 0 328 1 0 0 Kilombero 0 0 94 0 2,984 6 0 0 Ulanga 0 0 0 0 533 2 0 0 Morogoro Urban 0 0 0 0 393 9 0 0 Mvomero 0 0 246 0 7,112 14 252 1 Total 210 0 340 0 15,061 6 252 0 Number % Number % Number % Number % Number % Kilosa 248 0 0 0 119 0 69,147 94 73,435 100 Morogoro 0 0 0 0 0 0 52,554 99 52,882 100 Kilombero 210 0 815 2 0 0 44,679 92 48,782 100 Ulanga 0 0 0 0 0 0 30,375 98 30,908 100 Morogoro Urban 0 0 0 0 0 0 4,041 91 4,434 100 Mvomero 0 0 0 0 118 0 42,340 85 50,069 100 Total 458 0 815 0 237 0 243,137 93 260,511 100 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District District Number of Number of Total Number of Crop Buyers Large Scale Neighbour Total Not applicable Total Number of cont... ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Local Farmers Local Market / Secondary Market Co-operative District District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 199 Number % Number % Number % Number % Number % Kilosa 261 0 130 0 0 0 0 0 2,386 3 Morogoro 0 0 0 0 103 0 0 0 468 1 Kilombero 0 0 0 0 0 0 223 0 486 1 Ulanga 0 0 0 0 0 0 0 0 304 1 Morogoro Urban 12 0 0 0 0 0 0 0 121 3 Mvomero 0 0 128 0 0 0 0 0 2,648 5 Total 273 0 257 0 103 0 223 0 6,411 2 Number % Number % Number % Number % Kilosa 3,248 4 0 0 67,541 92 73,566 100 Morogoro 844 2 0 0 52,179 97 53,594 100 Kilombero 725 1 387 1 47,329 96 49,150 100 Ulanga 536 2 0 0 30,069 97 30,908 100 Morogoro Urban 75 2 0 0 4,251 95 4,459 100 Mvomero 1,854 4 0 0 45,440 91 50,069 100 Total 7,282 3 387 0 246,809 94 261,746 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 0 0 0 0 0 0 130 0 387 1 72,918 99 73,435 100 Morogoro 0 0 121 0 0 0 3,503 7 122 0 49,613 93 53,359 100 Kilombero 0 0 0 0 119 0 587 1 0 0 47,957 99 48,663 100 Ulanga 0 0 0 0 0 0 155 1 0 0 30,753 99 30,908 100 Morogoro Urban 0 0 0 0 0 0 62 1 13 0 4,359 98 4,434 100 Mvomero 124 0 123 0 122 0 1,727 3 124 0 47,849 96 50,069 100 Total 124 0 244 0 241 0 6,165 2 647 0 253,448 97 260,869 100 Number % Number % Number % Number % Number % Number % Kilosa 255 0 0 0 3,494 5 125 0 131 0 129 0 Morogoro 0 0 0 0 1,185 2 0 0 0 0 0 0 Kilombero 0 0 0 0 1,203 2 0 0 0 0 0 0 Ulanga 0 0 0 0 1,608 5 76 0 0 0 75 0 Morogoro Urban 0 0 0 0 306 7 0 0 0 0 0 0 Mvomero 251 1 125 0 8,583 17 377 1 380 1 0 0 Total 506 0 125 0 16,378 6 578 0 510 0 205 0 Total District Co-operative Local Farmers Local Market / Secondary Market Neighbour 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, Locally Produced by Not applicable Development Crop Buyers District Co-operative 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural District Not applicable Local Market / Large Scale Farm Neighbour Other Locally 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year cont…. ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Local Market / Secondary Crop Buyers Large Scale Farm Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 200 Number % Number % Number % Number % Number % Kilosa 0 0 254 0 0 0 68,917 94 73,305 100 Morogoro 0 0 0 0 0 0 51,810 98 52,995 100 Kilombero 0 0 125 0 94 0 47,486 97 48,908 100 Ulanga 153 0 926 3 75 0 27,994 91 30,908 100 Morogoro Urban 0 0 0 0 12 0 4,104 93 4,421 100 Mvomero 510 1 243 0 128 0 39,473 79 50,069 100 Total 664 0 1,547 1 309 0 239,784 92 260,607 100 Number % Number % Number % Number % Number % Kilosa 0 0 0 0 717 1 128 0 119 0 Morogoro 0 0 0 0 115 0 0 0 0 0 Kilombero 0 0 188 0 10,066 21 114 0 210 0 Ulanga 0 0 0 0 5,983 19 155 1 922 3 Morogoro Urban 0 0 0 0 37 1 0 0 0 0 Mvomero 124 0 123 0 1,189 2 0 0 0 0 Total 124 0 311 0 18,108 7 396 0 1,251 0 Number % Number % Number % Number % Kilosa 131 0 0 0 72,341 99 73,435 100 Morogoro 0 0 0 0 52,766 100 52,881 100 Kilombero 129 0 0 0 37,830 78 48,537 100 Ulanga 463 1 75 0 23,311 75 30,908 100 Morogoro Urban 0 0 0 0 4,397 99 4,434 100 Mvomero 0 0 0 0 48,633 97 50,069 100 Total 722 0 75 0 239,278 92 260,265 100 Number % Number % Number % Number % Number % Kilosa 130 0 0 0 4,589 6 0 0 247 0 Morogoro 0 0 0 0 3,354 6 0 0 103 0 Kilombero 0 0 0 0 2,017 4 128 0 238 0 Ulanga 0 0 151 0 1,135 4 0 0 460 1 Morogoro Urban 12 0 0 0 1,590 36 25 1 0 0 Mvomero 379 1 379 1 9,863 20 250 0 501 1 Total 521 0 530 0 22,548 9 403 0 1,549 1 District cont… ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District cont… ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, Local Market / Secondary Market Crop Buyers Not applicable Total Secondary Market Development 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Local Market / District Co-operative Local Farmers Neighbour Other District Co-operative Local Farmers Total Locally Produced Other Not applicable Neighbour Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 201 Number % Number % Number % Number % Number % Number % Number % Kilosa 0 0 235 0 391 1 1,906 3 0 0 65,938 90 73,435 100 Morogoro 0 0 0 0 122 0 122 0 0 0 49,411 93 53,113 100 Kilombero 188 0 327 1 0 0 2,539 5 94 0 43,122 89 48,653 100 Ulanga 75 0 0 0 78 0 1,532 5 0 0 27,477 89 30,908 100 Morogoro Urban 0 0 0 0 0 0 51 1 12 0 2,731 62 4,421 100 Mvomero 747 1 0 0 1,266 3 3,448 7 0 0 33,236 66 50,069 100 Total 1,010 0 562 0 1,857 1 9,598 4 106 0 221,916 85 260,600 100 Number % Number % Number % Number % Number % Number % Kilosa 970 23 980 23 1,232 29 371 9 735 17 4,288 100 Morogoro 0 0 103 32 103 32 0 0 121 37 328 100 Kilombero 759 18 374 9 2,241 55 429 10 300 7 4,103 100 Ulanga 77 14 229 43 0 0 72 14 155 29 533 100 Morogoro Urban 0 0 26 7 254 64 114 29 0 0 393 100 Mvomero 2,090 27 1,884 24 1,891 24 1,372 18 492 6 7,729 100 Total 3,896 22 3,596 21 5,721 33 2,358 14 1,803 10 17,374 100 Number % Number % Number % Number % Number % Number % Kilosa 4,985 83 388 6 521 9 0 0 131 2 6,024 100 Morogoro 1,354 96 0 0 61 4 0 0 0 0 1,415 100 Kilombero 1,578 87 243 13 0 0 0 0 0 0 1,821 100 Ulanga 379 45 153 18 153 18 154 18 0 0 839 100 Morogoro Urban 159 76 0 0 25 12 24 12 0 0 208 100 Mvomero 3,645 79 730 16 0 0 255 6 0 0 4,630 100 Total 12,099 81 1,515 10 760 5 433 3 131 1 14,937 100 Number % Number % Number % Number % Number % Kilosa 387 75 130 25 0 0 0 0 517 100 Morogoro 3,626 97 0 0 0 0 121 3 3,747 100 Kilombero 468 66 119 17 119 17 0 0 706 100 Ulanga 155 100 0 0 0 0 0 0 155 100 Morogoro Urban 75 100 0 0 0 0 0 0 75 100 Mvomero 2,220 100 0 0 0 0 0 0 2,220 100 Total 6,932 93 249 3 119 2 121 2 7,421 100 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and Between 10 and 20 20 km and Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and Between 10 and 20 20 km and Total Total District 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Neighbour Other Not applicable Locally Produced Crop Buyers Large Scale Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 202 Number % Number % Number % Number % Number % Number % Kilosa 846 19 259 6 902 21 386 9 1,995 45 4,388 100 Morogoro 123 10 103 9 103 9 0 0 855 72 1,185 100 Kilombero 251 18 348 24 363 26 213 15 248 17 1,422 100 Ulanga 844 29 842 29 233 8 78 3 917 31 2,914 100 Morogoro Urban 0 0 13 4 181 57 124 39 0 0 318 100 Mvomero 3,734 35 1,873 18 2,249 21 1,628 15 1,111 10 10,597 100 Total 5,798 28 3,439 17 4,031 19 2,429 12 5,125 25 20,823 100 Number % Number % Number % Number % Number % Number % Kilosa 374 34 115 11 349 32 256 23 0 0 1,094 100 Morogoro 0 0 0 0 0 0 0 0 115 100 115 100 Kilombero 2,267 21 755 7 3,397 32 2,230 21 2,057 19 10,707 100 Ulanga 2,696 35 1,609 21 1,619 21 298 4 1,376 18 7,598 100 Morogoro Urban 0 0 13 35 13 35 11 29 0 0 37 100 Mvomero 243 17 619 43 473 33 0 0 101 7 1,436 100 Total 5,580 27 3,111 15 5,851 28 2,795 13 3,650 17 20,987 100 Number % Number % Number % Number % Number % Number % Kilosa 2,208 29 636 8 1,934 26 777 10 1,942 26 7,497 100 Morogoro 471 13 103 3 103 3 122 3 2,901 78 3,702 100 Kilombero 2,048 37 1,062 19 1,457 26 347 6 617 11 5,531 100 Ulanga 1,452 42 460 13 463 13 229 7 828 24 3,432 100 Morogoro Urban 62 4 26 2 676 40 888 53 39 2 1,690 100 Mvomero 7,576 45 3,234 19 3,071 18 1,717 10 1,235 7 16,833 100 Total 13,817 36 5,521 14 7,704 20 4,081 11 7,562 20 38,684 100 Number % Number % Number % Number % Number % Kilosa 2,145 50 1,586 37 115 3 442 10 4,288 100 Morogoro 328 100 0 0 0 0 0 0 328 100 Kilombero 3,124 76 767 19 118 3 94 2 4,103 100 Ulanga 455 85 78 15 0 0 0 0 533 100 Morogoro Urban 262 67 107 27 25 6 0 0 393 100 Mvomero 6,748 87 734 9 247 3 0 0 7,729 100 Total 13,061 75 3,272 19 505 3 535 3 17,374 100 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year District Sale of Farm Other Income Remittances Bank Loan Total 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and Between 10 and 20 20 km and Total 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and Between 10 and 20 20 km and Total 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 Between 3 and Between 10 and 20 20 km and Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 203 Number % Number % Number % Number % Number % Kilosa 5,270 87 365 6 390 6 0 0 6,024 100 Morogoro 485 34 391 28 478 34 61 4 1,415 100 Kilombero 1,180 65 0 0 125 7 516 28 1,821 100 Ulanga 457 54 78 9 229 27 75 9 839 100 Morogoro Urban 146 70 24 12 12 6 25 12 208 100 Mvomero 3,773 81 476 10 128 3 253 5 4,630 100 Total 11,312 76 1,334 9 1,361 9 931 6 14,937 100 Number % Number % Number % Number % Number % Kilosa 517 100 0 0 0 0 0 0 517 100 Morogoro 1,332 36 358 10 123 3 1,933 52 3,747 100 Kilombero 706 100 0 0 0 0 0 0 706 100 Ulanga 0 0 78 50 0 0 78 50 155 100 Morogoro Urban 75 100 0 0 0 0 0 0 75 100 Mvomero 1,234 56 616 28 0 0 370 17 2,220 100 Total 3,865 52 1,052 14 123 2 2,380 32 7,421 100 Number % Number % Number % Number % Number % Number % Kilosa 4,010 91 377 9 0 0 0 0 0 0 4,388 100 Morogoro 1,062 90 123 10 0 0 0 0 0 0 1,185 100 Kilombero 1,050 74 372 26 0 0 0 0 0 0 1,422 100 Ulanga 1,454 50 1,073 37 387 13 0 0 0 0 2,914 100 Morogoro Urban 223 70 95 30 0 0 0 0 0 0 318 100 Mvomero 8,405 79 1,704 16 246 2 118 1 123 1 10,597 100 Total 16,204 78 3,744 18 633 3 118 1 123 1 20,823 100 Number % Number % Number % Number % Number % Number % Kilosa 617 56 243 22 0 0 234 21 0 0 1,094 100 Morogoro 115 100 0 0 0 0 0 0 0 0 115 100 Kilombero 8,573 80 1,534 14 506 5 94 1 0 0 10,707 100 Ulanga 3,681 48 3,152 41 460 6 75 1 229 3 7,598 100 Morogoro Urban 37 100 0 0 0 0 0 0 0 0 37 100 Mvomero 1,211 84 225 16 0 0 0 0 0 0 1,436 100 Total 14,234 68 5,154 25 966 5 403 2 229 1 20,987 100 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year District Sale of Farm Other Income Remittances Bank Loan Other Total 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year District Sale of Farm Other Income Remittances Produced on form Other Total 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year District Sale of Farm Other Income Produced on Other Total 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year District Sale of Farm Other Income Remittances Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 204 Number % Number % Number % Number % Number % Number % Number % Kilosa 5,020 67 1,958 26 260 3 130 2 0 0 130 2 7,497 100 Morogoro 2,096 57 1,181 32 240 6 0 0 0 0 184 5 3,702 100 Kilombero 4,669 84 768 14 0 0 94 2 0 0 0 0 5,531 100 Ulanga 1,596 47 1,375 40 461 13 0 0 0 0 0 0 3,432 100 Morogoro Urban 1,079 64 527 31 63 4 0 0 9 1 12 1 1,690 100 Mvomero 12,182 72 3,298 20 1,108 7 0 0 0 0 245 1 16,833 100 Total 26,641 69 9,106 24 2,133 6 224 1 9 0 572 1 38,684 100 Number % Number % Number % Number % Number % Number % Kilosa 13,303 19 42,896 62 1,413 2 256 0 6,134 9 4,890 7 Morogoro 15,899 30 27,073 52 366 1 224 0 2,664 5 6,208 12 Kilombero 1,745 4 36,404 81 491 1 0 0 0 0 6,039 14 Ulanga 8,082 27 13,637 45 389 1 74 0 388 1 7,729 25 Morogoro Urban 220 5 3,128 77 12 0 0 0 117 3 502 12 Mvomero 4,531 11 26,250 62 734 2 496 1 5,008 12 4,578 11 Total 43,782 18 149,389 61 3,405 1 1,050 0 14,311 6 29,945 12 Number % Number % Number % Kilosa 0 0 254 0 69,147 100 Morogoro 0 0 119 0 52,554 100 Kilombero 0 0 0 0 44,679 100 Ulanga 0 0 76 0 30,375 100 Morogoro Urban 12 0 50 1 4,041 100 Mvomero 125 0 618 1 42,340 100 Total 137 0 1,118 0 243,137 100 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Do not Know Input is of No cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Locally Produced Other Total District 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year District Sale of Farm Other Income Remittances Bank Loan Produced on Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 205 Number % Number % Number % Number % Number % Number % Kilosa 18,151 27 11,130 16 22,627 34 4,888 7 6,928 10 3,308 5 Morogoro 26,566 51 11,501 22 4,204 8 794 2 6,520 12 1,868 4 Kilombero 29,132 62 7,052 15 5,121 11 129 0 594 1 5,302 11 Ulanga 16,107 54 926 3 3,230 11 0 0 3,907 13 5,820 19 Morogoro Urban 2,126 50 500 12 1,243 29 120 3 63 1 133 3 Mvomero 15,241 34 3,721 8 13,397 29 1,194 3 6,282 14 5,114 11 Total 107,323 43 34,830 14 49,822 20 7,125 3 24,294 10 21,545 9 Number % Number % Number % Kilosa 0 0 509 1 67,541 100 Morogoro 119 0 608 1 52,179 100 Kilombero 0 0 0 0 47,329 100 Ulanga 0 0 78 0 30,069 100 Morogoro Urban 0 0 66 2 4,251 100 Mvomero 0 0 491 1 45,440 100 Total 119 0 1,751 1 246,809 100 Number % Number % Number % Number % Number % Number % Kilosa 6,817 9 14,196 19 27,600 38 2,862 4 15,809 22 5,257 7 Morogoro 9,736 20 12,594 25 8,888 18 668 1 13,907 28 1,990 4 Kilombero 6,261 13 6,918 14 27,241 57 775 2 1,494 3 5,023 10 Ulanga 7,319 24 1,157 4 7,813 25 464 2 9,032 29 4,660 15 Morogoro Urban 512 12 556 13 1,880 43 375 9 830 19 155 4 Mvomero 3,253 7 2,990 6 16,441 34 1,430 3 17,296 36 5,832 12 Total 33,898 13 38,410 15 89,862 35 6,575 3 58,367 23 22,916 9 Number % Number % Number % Kilosa 0 0 378 1 72,918 100 Morogoro 738 1 1,093 2 49,613 100 Kilombero 0 0 245 1 47,957 100 Ulanga 0 0 308 1 30,753 100 Morogoro Urban 13 0 38 1 4,359 100 Mvomero 0 0 608 1 47,849 100 Total 750 0 2,671 1 253,448 100 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District District Not Available Price Too High Other Total Locally Produced Input is of No No Money to Buy Other Total 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District District Not Available Price Too High No Money to Buy Too Much Labour Do not Know Input is of No Too Much Labour Do not Know cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year Locally Produced Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 206 Number % Number % Number % Number % Number % Number % Kilosa 6,280 9 42,693 62 3,816 6 0 0 9,131 13 6,747 10 Morogoro 13,304 26 26,527 51 823 2 0 0 7,644 15 3,272 6 Kilombero 2,479 5 37,623 79 2,236 5 126 0 881 2 4,142 9 Ulanga 3,396 12 16,588 59 388 1 74 0 767 3 6,173 22 Morogoro Urban 26 1 3,271 80 47 1 12 0 101 2 621 15 Mvomero 4,401 11 22,777 58 994 3 452 1 6,510 16 3,603 9 Total 29,885 12 149,480 62 8,304 3 663 0 25,034 10 24,557 10 Number % Number % Number % Kilosa 0 0 249 0 68,917 100 Morogoro 0 0 242 0 51,810 100 Kilombero 0 0 0 0 47,486 100 Ulanga 77 0 530 2 27,994 100 Morogoro Urban 0 0 25 1 4,104 100 Mvomero 124 0 613 2 39,473 100 Total 202 0 1,660 1 239,784 100 Number % Number % Number % Number % Number % Number % Kilosa 8,574 12 40,091 55 2,654 4 0 0 13,016 18 7,628 11 Morogoro 11,587 22 27,088 51 576 1 123 0 6,985 13 6,165 12 Kilombero 2,009 5 33,149 88 371 1 0 0 129 0 2,056 5 Ulanga 2,639 11 17,942 77 233 1 0 0 153 1 1,735 7 Morogoro Urban 62 1 3,413 78 60 1 0 0 126 3 710 16 Mvomero 4,905 10 23,175 48 572 1 123 0 10,599 22 8,520 18 Total 29,776 12 144,858 61 4,467 2 246 0 31,007 13 26,815 11 Number % Number % Number % Kilosa 0 0 377 1 72,341 100 Morogoro 0 0 242 0 52,766 100 Kilombero 0 0 116 0 37,830 100 Ulanga 0 0 610 3 23,311 100 Morogoro Urban 0 0 25 1 4,397 100 Mvomero 124 0 616 1 48,633 100 Total 124 0 1,986 1 239,278 100 Input is of No Locally Produced District Not Available Price Too High Do not Know Other Total Too Much Labour District Locally Produced Other Total Too Much Labour 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Do not Know Input is of No No Money to Buy District cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 207 Number % Number % Number % Number % Number % Number % Kilosa 15,485 23 44,969 68 2,205 3 0 0 2,223 3 676 1 Morogoro 27,139 55 20,126 41 224 0 350 1 840 2 723 1 Kilombero 10,368 24 29,896 69 1,352 3 127 0 374 1 635 1 Ulanga 12,132 44 14,205 52 150 1 0 0 0 0 839 3 Morogoro Urban 36 1 2,478 91 23 1 0 0 13 0 131 5 Mvomero 6,997 21 20,590 62 0 0 0 0 3,910 12 996 3 Total 72,157 32 132,265 60 3,955 2 477 0 7,360 3 3,999 2 Number % Number % Number % Kilosa 0 0 379 1 65,938 100 Morogoro 0 0 119 0 49,522 100 Kilombero 0 0 370 1 43,122 100 Ulanga 0 0 152 1 27,477 100 Morogoro Urban 0 0 50 2 2,731 100 Mvomero 125 0 618 2 33,236 100 Total 125 0 1,689 1 222,027 100 Number % Number % Number % Number % Number % Kilosa 1,196 28 2,660 62 313 7 119 3 4,288 100 Morogoro 224 68 103 32 0 0 0 0 328 100 Kilombero 489 12 3,486 85 129 3 0 0 4,103 100 Ulanga 229 43 154 29 150 28 0 0 533 100 Morogoro Urban 236 60 141 36 16 4 0 0 393 100 Mvomero 3,369 44 4,359 56 0 0 0 0 7,729 100 Total 5,743 33 10,903 63 609 4 119 1 17,374 100 Number % Number % Number % Number % Kilosa 2,834 47 2,800 46 391 6 6,024 100 Morogoro 549 39 748 53 119 8 1,415 100 Kilombero 123 7 1,573 86 125 7 1,821 100 Ulanga 304 36 384 46 151 18 839 100 Morogoro Urban 37 18 160 77 11 5 208 100 Mvomero 2,389 52 2,241 48 0 0 4,630 100 Total 6,235 42 7,905 53 797 5 14,937 100 cont… ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Input is of No Locally Produced Other Total No Money to Buy District District Not Available Price Too High Too Much Labour Do not Know Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 208 Number % Number % Number % Number % Kilosa 130 25 130 25 257 50 517 100 Morogoro 1,086 29 1,936 52 725 19 3,747 100 Kilombero 223 32 483 68 0 0 706 100 Ulanga 0 0 78 50 78 50 155 100 Morogoro Urban 0 0 50 67 25 33 75 100 Mvomero 1,477 67 493 22 250 11 2,220 100 Total 2,916 39 3,170 43 1,335 18 7,421 100 Number % Number % Number % Number % Number % Kilosa 641 15 3,264 74 483 11 0 0 4,388 100 Morogoro 103 9 1,081 91 0 0 0 0 1,185 100 Kilombero 252 18 1,171 82 0 0 0 0 1,422 100 Ulanga 767 26 1,914 66 232 8 0 0 2,914 100 Morogoro Urban 146 46 141 44 31 10 0 0 318 100 Mvomero 2,861 27 7,484 71 128 1 124 1 10,597 100 Total 4,769 23 15,055 72 874 4 124 1 20,823 100 Number % Number % Number % Number % Number % Kilosa 845 77 249 23 0 0 0 0 1,094 100 Morogoro 0 0 115 100 0 0 0 0 115 100 Kilombero 889 8 9,051 85 638 6 129 1 10,707 100 Ulanga 2,161 28 5,053 67 384 5 0 0 7,598 100 Morogoro Urban 37 100 0 0 0 0 0 0 37 100 Mvomero 587 41 602 42 246 17 0 0 1,436 100 Total 4,519 22 15,071 72 1,268 6 129 1 20,987 100 Number % Number % Number % Number % Kilosa 2,322 31 4,784 64 392 5 7,497 100 Morogoro 974 26 2,189 59 540 15 3,702 100 Kilombero 1,310 24 3,969 72 251 5 5,531 100 Ulanga 1,229 36 1,978 58 225 7 3,432 100 Morogoro Urban 585 35 969 57 136 8 1,690 100 Mvomero 8,181 49 8,184 49 468 3 16,833 100 Total 14,600 38 22,073 57 2,011 5 38,684 100 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 209 Number % Number % Number % Kilosa 9,136 12 64,300 88 73,435 100 Morogoro 4,939 9 47,943 91 52,882 100 Kilombero 11,307 23 37,475 77 48,782 100 Ulanga 5,654 18 25,254 82 30,908 100 Morogoro Urban 790 18 3,644 82 4,434 100 Mvomero 15,481 31 34,588 69 50,069 100 Total 47,307 18 213,204 82 260,511 100 Number % Number % Number % Kilosa 14,531 20 59,034 80 73,566 100 Morogoro 8,465 16 45,129 84 53,594 100 Kilombero 1,955 4 47,195 96 49,150 100 Ulanga 1,821 6 29,087 94 30,908 100 Morogoro Urban 304 7 4,155 93 4,459 100 Mvomero 12,492 25 37,577 75 50,069 100 Total 39,568 15 222,178 85 261,746 100 Number % Number % Number % Kilosa 2,030 3 71,405 97 73,435 100 Morogoro 9,816 18 43,543 82 53,359 100 Kilombero 1,562 3 47,101 97 48,663 100 Ulanga 1,523 5 29,385 95 30,908 100 Morogoro Urban 375 8 4,059 92 4,434 100 Mvomero 11,270 23 38,799 77 50,069 100 Total 26,577 10 234,292 90 260,869 100 Number % Number % Number % Kilosa 11,792 16 61,513 84 73,305 100 Morogoro 6,053 11 46,942 89 52,995 100 Kilombero 5,610 11 43,298 89 48,908 100 Ulanga 8,815 29 22,094 71 30,908 100 Morogoro Urban 597 14 3,824 86 4,421 100 Mvomero 20,571 41 29,498 59 50,069 100 Total 53,438 21 207,169 79 260,607 100 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Number of 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Total District Number of Number of Total District Number of Number of Total District Number of Number of Total 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 210 Number % Number % Number % Kilosa 4,367 6 69,068 94 73,435 100 Morogoro 3,754 7 49,127 93 52,881 100 Kilombero 15,026 31 33,512 69 48,537 100 Ulanga 17,186 56 13,722 44 30,908 100 Morogoro Urban 107 2 4,327 98 4,434 100 Mvomero 5,640 11 44,429 89 50,069 100 Total 46,080 18 214,185 82 260,265 100 Number % Number % Number % Kilosa 24,823 34 48,613 66 73,435 100 Morogoro 11,503 22 41,610 78 53,113 100 Kilombero 10,575 22 38,078 78 48,653 100 Ulanga 17,498 57 13,410 43 30,908 100 Morogoro Urban 2,205 50 2,217 50 4,421 100 Mvomero 29,014 58 21,055 42 50,069 100 Total 95,618 37 164,982 63 260,600 100 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Number of Number of Total District Number of Number of Total District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 211 Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Kilosa 253,236 5,389 3,774 3,018 2,591 5,607 1,555 2,348 0 0 Morogoro 160,398 1,215 535 242 0 0 0 0 0 0 Kilombero 172,198 1,781 3,576 9,387 10,400 1,290 2,106 365 0 0 Ulanga 110,211 1,045 3,630 7,819 12,904 4,546 2,906 1,233 0 0 Morogoro Urban 13,942 335 228 65 0 0 0 0 0 0 Mvomero 149,921 6,536 3,582 7,087 766 0 128 0 0 0 Total 859,905 16,301 15,324 27,617 26,660 11,443 6,694 3,947 0 0 Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Kilosa 3,104 5,588 126 4,276 126 3,988 1,391 2,571 131 116 266,034 32,900 Morogoro 0 0 122 1,095 122 1,156 0 123 0 0 161,177 3,831 Kilombero 0 0 450 11,595 332 11,582 94 1,974 0 0 189,156 37,974 Ulanga 620 307 0 4,525 0 4,501 0 230 0 0 130,270 24,207 Morogoro Urban 0 0 0 193 0 123 0 9 0 0 14,170 724 Mvomero 0 255 728 8,242 0 8,612 0 863 0 0 155,124 31,596 Total 3,724 6,150 1,427 29,926 580 29,962 1,485 5,769 131 116 915,931 131,232 Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Kilosa 73,180 6,337 2,213 2,212 5,311 4,402 4,114 2,697 247 Morogoro 52,449 657 0 0 0 1,095 1,156 123 0 Kilombero 48,539 11,769 1,222 1,345 0 11,926 11,795 2,068 0 Ulanga 30,908 9,822 2,218 2,294 772 4,370 4,423 230 0 Morogoro Urban 4,408 280 0 0 0 193 123 9 0 Mvomero 49,820 8,078 128 128 255 8,362 8,490 863 0 Total 259,304 36,943 5,781 5,979 6,338 30,348 30,100 5,989 247 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Implement / Asset Name cont… ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 District Implement / Asset Name District Hand Hoe Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Total 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year District Implement / Asset Name Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 212 Number % Number % Number % Number % Number % Number % Kilosa 131 34 130 34 126 33 0 0 0 0 386 100 Morogoro 123 16 423 53 0 0 122 15 123 16 792 100 Kilombero 116 32 246 68 0 0 0 0 0 0 362 100 Morogoro Urban 13 50 13 50 0 0 0 0 0 0 26 100 Mvomero 0 0 125 50 0 0 124 50 0 0 250 100 Total 383 21 936 52 126 7 247 14 123 7 1,815 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 11,815 18 28,362 42 13,288 20 126 0 13,507 20 0 0 67,098 100 Morogoro 14,900 28 26,510 51 7,850 15 123 0 2,465 5 610 1 52,457 100 Kilombero 1,772 5 22,282 60 11,026 30 0 0 2,055 6 116 0 37,252 100 Ulanga 6,140 29 8,957 42 4,248 20 0 0 1,437 7 380 2 21,163 100 Morogoro Urban 76 2 2,730 66 713 17 26 1 621 15 0 0 4,166 100 Mvomero 5,161 12 19,689 47 10,156 24 0 0 7,103 17 128 0 42,237 100 Total 39,865 18 108,529 48 47,280 21 276 0 27,189 12 1,234 1 224,372 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 29,143 41 18,073 25 21,735 31 620 1 1,651 2 0 0 71,222 100 Morogoro 16,045 30 22,391 42 6,872 13 1,231 2 3,170 6 3,408 6 53,117 100 Kilombero 23,919 50 14,333 30 7,501 16 258 1 1,672 4 0 0 47,683 100 Ulanga 17,724 62 3,314 12 6,721 23 0 0 777 3 153 1 28,690 100 Morogoro Urban 1,322 30 1,075 24 763 17 13 0 1,235 28 13 0 4,421 100 Mvomero 13,948 28 6,265 13 6,001 12 485 1 23,119 46 123 0 49,942 100 Total 102,101 40 65,452 26 49,594 19 2,608 1 31,624 12 3,697 1 255,075 100 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District Equipment / Asset Other Total 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 213 Number % Number % Number % Number % Number % Number % Number % Kilosa 27,642 39 16,635 23 23,913 34 883 1 2,150 3 0 0 71,223 100 Morogoro 12,273 23 24,388 46 9,081 17 488 1 3,479 7 3,288 6 52,997 100 Kilombero 23,051 49 13,744 29 8,862 19 364 1 1,415 3 0 0 47,437 100 Ulanga 17,951 63 2,854 10 6,801 24 77 0 855 3 76 0 28,614 100 Morogoro Urban 1,312 30 864 19 917 21 18 0 1,324 30 0 0 4,434 100 Mvomero 13,828 28 7,391 15 4,492 9 485 1 23,500 47 246 0 49,942 100 Total 96,057 38 65,875 26 54,066 21 2,316 1 32,725 13 3,609 1 254,647 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 32,305 44 16,933 23 21,357 29 781 1 2,060 3 0 0 73,435 100 Morogoro 12,126 23 24,406 46 8,420 16 668 1 4,210 8 3,288 6 53,117 100 Kilombero 25,155 52 14,090 29 7,630 16 116 0 1,664 3 0 0 48,655 100 Ulanga 22,785 74 1,922 6 4,342 14 0 0 1,860 6 0 0 30,908 100 Morogoro Urban 1,233 28 906 20 879 20 0 0 1,403 32 13 0 4,434 100 Mvomero 13,901 28 7,771 16 4,852 10 118 0 23,180 46 246 0 50,069 100 Total 107,505 41 66,028 25 47,479 18 1,683 1 34,377 13 3,547 1 260,618 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 28,040 41 16,952 25 20,219 30 648 1 2,265 3 0 0 68,124 100 Morogoro 12,852 24 23,420 44 8,807 17 1,333 3 3,540 7 3,288 6 53,239 100 Kilombero 22,900 47 15,759 32 8,469 17 116 0 1,674 3 0 0 48,918 100 Ulanga 18,338 61 2,696 9 6,021 20 0 0 2,775 9 307 1 30,137 100 Morogoro Urban 1,197 27 819 18 961 22 0 0 1,457 33 0 0 4,434 100 Mvomero 13,680 28 6,388 13 6,324 13 235 0 22,813 46 246 0 49,686 100 Total 97,007 38 66,033 26 50,801 20 2,333 1 34,524 14 3,840 2 254,538 100 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 214 Number % Number % Number % Number % Number % Number % Number % Kilosa 11,602 17 31,373 45 23,451 34 128 0 2,386 3 92 0 69,033 100 Morogoro 6,670 13 27,368 52 13,607 26 604 1 486 1 3,410 7 52,144 100 Kilombero 5,014 14 18,105 49 12,337 34 0 0 1,156 3 125 0 36,737 100 Ulanga 6,286 24 2,853 11 16,479 62 0 0 767 3 153 1 26,538 100 Morogoro Urban 86 2 1,362 32 1,074 25 0 0 1,718 41 0 0 4,241 100 Mvomero 3,606 9 9,134 22 12,579 30 0 0 16,288 39 101 0 41,708 100 Total 33,263 14 90,195 39 79,528 35 733 0 22,801 10 3,881 2 230,401 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 10,676 15 31,517 45 24,052 35 128 0 2,855 4 92 0 69,321 100 Morogoro 6,756 13 26,663 51 14,230 27 481 1 422 1 3,410 7 51,961 100 Kilombero 3,879 11 18,742 51 12,958 35 0 0 1,156 3 125 0 36,860 100 Ulanga 6,672 25 2,846 11 15,968 60 0 0 768 3 231 1 26,485 100 Morogoro Urban 73 2 1,420 33 1,120 26 5 0 1,693 39 0 0 4,311 100 Mvomero 3,508 8 9,007 22 11,220 27 1,215 3 16,529 40 101 0 41,580 100 Total 31,564 14 90,195 39 79,549 35 1,828 1 23,423 10 3,959 2 230,518 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 11,679 17 29,619 42 22,095 31 258 0 6,995 10 92 0 70,739 100 Morogoro 5,772 11 26,878 51 15,174 29 176 0 1,461 3 3,410 6 52,872 100 Kilombero 4,989 11 24,136 52 15,535 33 0 0 1,804 4 250 1 46,715 100 Ulanga 7,745 25 2,617 9 16,631 54 0 0 3,378 11 231 1 30,602 100 Morogoro Urban 43 1 1,292 29 1,173 27 0 0 1,917 43 0 0 4,425 100 Mvomero 4,253 9 10,098 21 13,729 28 1,092 2 19,791 40 126 0 49,089 100 Total 34,481 14 94,640 37 84,339 33 1,526 1 35,346 14 4,109 2 254,440 100 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 215 Number % Number % Number % Number % Number % Number % Number % Kilosa 18,898 26 27,887 38 18,467 25 258 0 7,549 10 0 0 73,058 100 Morogoro 7,828 15 28,608 54 9,737 18 182 0 4,565 9 2,074 4 52,995 100 Kilombero 18,462 38 18,255 38 9,080 19 0 0 1,979 4 764 2 48,540 100 Ulanga 14,543 47 4,329 14 5,788 19 75 0 6,173 20 0 0 30,908 100 Morogoro Urban 117 3 1,716 39 875 20 0 0 1,726 39 0 0 4,434 100 Mvomero 11,719 23 12,668 25 7,273 15 1,340 3 16,947 34 124 0 50,069 100 Total 71,567 28 93,462 36 51,220 20 1,854 1 38,939 15 2,961 1 260,005 100 Number % Number % Number % Number % Number % Number % Number % Kilosa 44,634 61 24,457 33 1,639 2 548 1 258 0 1,645 2 73,180 100 Morogoro 35,726 68 14,599 28 1,581 3 123 0 0 0 420 1 52,449 100 Kilombero 36,935 76 10,235 21 627 1 369 1 0 0 374 1 48,539 100 Ulanga 19,545 63 9,525 31 1,532 5 76 0 0 0 231 1 30,908 100 Morogoro Urban 3,185 72 993 23 195 4 0 0 0 0 35 1 4,408 100 Mvomero 36,110 73 11,014 22 1,360 3 0 0 0 0 853 2 49,338 100 Total 176,134 68 70,822 27 6,934 3 1,116 0 258 0 3,558 1 258,822 100 Number % Number % Number % Number % Kilosa 2,978 84 575 16 0 0 3,554 100 Morogoro 111 21 423 79 0 0 535 100 Kilombero 1,904 76 598 24 0 0 2,502 100 Ulanga 1,460 61 925 39 0 0 2,385 100 Morogoro Urban 191 84 26 11 11 5 228 100 Mvomero 2,485 74 854 26 0 0 3,339 100 Total 9,131 73 3,401 27 11 0 12,543 100 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Too Much Labour Equipment / Asset of Other Total 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District District Sale of Farm Products Other Income Remittances Bank Loan Credit Other Total 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District District Sale of Farm Products Other Income Bank Loan Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 216 Number % Number % Number % Number % Number % Kilosa 518 100 0 0 0 0 0 0 518 100 Kilombero 986 89 117 11 0 0 0 0 1,103 100 Ulanga 910 57 386 24 231 14 77 5 1,603 100 Mvomero 128 100 0 0 0 0 0 0 128 100 Total 2,541 76 502 15 231 7 77 2 3,352 100 Number % Number % Number % Number % Kilosa 908 100 0 0 0 0 908 100 Kilombero 986 89 117 11 0 0 1,103 100 Ulanga 987 65 463 30 77 5 1,527 100 Mvomero 128 100 0 0 0 0 128 100 Total 3,008 82 580 16 77 2 3,665 100 Warnings Number % Number % Number % Number % Number % Kilosa 1,937 94 0 0 130 6 0 0 2,067 100 Ulanga 153 33 234 50 0 0 77 17 464 100 Total 2,090 83 234 9 130 5 77 3 2,531 100 No cases were input to this procedure. Either there are no cases in the working data file or all of them have been filtered out. This command is not executed. 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OXEN by Source of Finance and District District Sale of Farm Products Other Income Remittances Other Total 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District District Sale of Farm Products Other Income Other Total 12.2.18 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX CART by Source of Finance and District District Sale of Farm Products Other Income Remittances Other Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 217 Number % Number % Number % Number % Kilosa 0 0 126 100 0 0 126 100 Morogoro 122 100 0 0 0 0 122 100 Kilombero 119 27 237 53 94 21 450 100 Mvomero 243 100 0 0 0 0 243 100 Total 485 51 363 39 94 10 942 100 Number % Number % Number % Number % Kilosa 0 0 126 100 0 0 126 100 Morogoro 122 100 0 0 0 0 122 100 Kilombero 119 36 119 36 94 28 332 100 Total 242 42 245 42 94 16 580 100 Number % Number % Number % Number % Kilosa 105 31 231 69 0 0 337 100 Kilombero 0 0 0 0 94 100 94 100 Total 105 24 231 54 94 22 431 100 Number % Number % Kilosa 131 100 131 100 Total 131 100 131 100 12.2.19 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District District Sale of Farm Products Other Income Credit Total 12.2.20 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District District Sale of Farm Products Other Income Credit Total 12.2.21 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District District Sale of Farm Products Other Income Credit Total District Sale of Farm Products Total 12.2.22 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning THRESHERS/SHELLERS by Source of Finance and District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 218 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 219 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Kilosa 2,438 13,294 5,516 2,333 26,713 3,496 128 93 18,416 72,428 Morogoro Rural 2,068 9,151 2,755 586 21,559 1,958 103 244 7,794 46,218 Kilombero 1,012 5,588 3,433 2,581 25,752 3,191 324 116 4,628 46,625 Ulanga 149 2,972 3,118 78 14,833 612 77 0 8,308 30,148 Morogoro Urban 274 699 891 308 1,482 98 13 0 669 4,434 Mvomero 3,941 14,042 6,564 1,958 12,572 841 751 121 8,647 49,437 Total 9,883 45,746 22,278 7,844 102,911 10,196 1,397 574 48,462 249,289 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Livestock Other Total Credits Kilosa 512 457 329 232 186 0 131 1,846 Morogoro Rural 3,262 4,477 0 122 119 0 0 7,979 Kilombero 1,922 633 514 304 188 0 118 3,681 Ulanga 307 77 0 531 0 0 0 914 Mvomero 0 128 0 128 0 128 377 759 Total 6,003 5,771 843 1,317 492 128 626 15,180 Number % Number % Kilosa 1,007 100 0 0 1,007 Morogoro Rural 4,484 65 2,415 35 6,899 Kilombero 1,596 74 561 26 2,157 Ulanga 456 60 305 40 761 Mvomero 255 40 377 60 632 Total 7,799 68 3,658 32 11,457 % 68 32 Family, Friend and Relative Commercia l Bank Co-operative Saving & Credit Society Trader / Trade Store Private Individual Religious Organisation / NGO / Project Other Total Kilosa 93 419 117 117 131 0 131 0 1,007 Morogoro Rural 4,588 0 0 0 1,583 728 0 0 6,899 Kilombero 495 365 0 935 116 118 128 0 2,157 Ulanga 0 0 0 77 607 0 0 77 761 Mvomero 0 125 0 128 128 0 252 0 632 Total 5,176 909 117 1,256 2,565 847 510 77 11,457 % 45 8 1 11 22 7 4 1 100 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Households Receiving Credits By Main Source of Credit By District During the 2002/03 agriculture Year Total 13.2a AGRICULTURE CREDIT: Number of Agriculture Households Receiving Credit By Sex of Household head and district During the 2002/03 Agriculture Year District Male Female Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 220 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 221 Number % Number % Number % Kilosa 5,864 8 67,572 92 73,435 100 Morogoro Rural 1,929 4 51,188 96 53,117 100 Kilombero 3,557 7 45,225 93 48,782 100 Ulanga 2,973 10 27,935 90 30,908 100 Morogoro Urban 687 15 3,747 85 4,434 100 Mvomero 3,174 6 46,895 94 50,069 100 Total 18,184 7 242,562 93 260,746 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Kilosa 4,858 26,908 483 9,950 522 39,413 5,864 76,271 Morogoro Rural 1,570 42,316 240 9,626 119 8,310 1,929 60,252 Kilombero 2,873 19,279 684 8,419 0 . 3,557 27,697 Ulanga 2,207 147,519 689 7,810 76 9,164 2,973 164,494 Morogoro Urban 508 9,998 166 2,885 12 24 687 12,907 Mvomero 1,483 211,692 681 124,735 1,011 1,819,441 3,174 2,155,868 Total 13,500 457,712 2,944 163,425 1,740 1,876,354 18,184 2,497,490 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Melicia excelsa Casurina Equisetfilia Tectona Grandis Kilosa 23,710 25,639 1,407 392 119 3,066 5,088 522 379 116 1,958 Morogoro Rural 9,040 . . 6,041 . 7,290 . . 1,580 . . Kilombero 11,142 2,076 . . . 848 187 751 592 239 5,520 Ulanga 7,301 139,452 690 . . . . . 155 931 13,296 Morogoro Urban 4,047 2,346 . . . 714 3,026 . 178 . 79 Mvomero 10,340 2,001,645 . 893 . 23,859 34,118 50,653 . . 12,318 Total 65,581 2,171,157 2,097 7,326 119 35,777 42,418 51,926 2,883 1,286 33,170 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District District Where Planted Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Households Having Planted Trees Households Not Having Planted Trees Total 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District 14.1TREE FARMING / Agroforestry District Did your Hh have any Planted Trees on your land during 2002/ Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 222 District Terminalia Catapa Terminalia Ivorensis Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Albizia Spp Kyaya Spp Moringa Spp Saraca Spp Trichilia Spp Total Kilosa 223 . 6,134 738 3,123 131 . 2,729 521 279 . 76,271 Morogoro Rural . . . . . . . 36,301 . . . 60,252 Kilombero 239 . 341 . 1,023 . . 476 595 2,561 1,108 27,697 Ulanga 232 . . 777 1,276 . . . 383 . . 164,494 Morogoro Urban 13 18 81 139 296 . 54 1,834 83 . . 12,907 Mvomero . . . 128 . . . 1,250 20,666 . . 2,155,868 Total 707 18 6,556 1,782 5,718 131 54 42,590 22,249 2,839 1,108 2,497,490 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Kilosa 2,397 579 93 420 5,109 315 0 8,913 Morogoro Rural 1,568 483 0 122 0 0 0 2,172 Kilombero 1,852 250 0 936 1,230 249 239 4,756 Ulanga 1,770 230 0 384 1,515 153 76 4,128 Morogoro Urban 451 39 0 202 192 0 45 930 Mvomero 1,117 355 0 1,769 330 0 432 4,003 Total 9,156 1,936 93 3,833 8,376 717 791 24,902 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Kilosa 870 2,306 0 3,701 1,114 620 210 8,821 Morogoro Rural 122 1,328 0 600 122 0 0 2,172 Kilombero 355 805 0 1,914 953 248 481 4,756 Ulanga 154 534 0 2,073 155 373 762 4,051 Morogoro Urban 37 37 0 583 143 0 129 930 Mvomero 764 1,132 128 974 574 203 229 4,003 Total 2,302 6,143 128 9,845 3,061 1,444 1,811 24,733 Cont…….. 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District 14 TREE FARMING: Second Use of Trees By District District Second Use 14 TREE FARMING: Main Use of Trees By District District Main Use Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 223 Number % Number % Number % Kilosa 2,433 3 69,802 97 72,235 100 Morogoro Rural 5,391 10 47,726 90 53,117 100 Kilombero 1,519 3 46,759 97 48,278 100 Ulanga 7,129 23 23,625 77 30,754 100 Morogoro Urban 458 10 3,938 90 4,396 100 Mvomero 1,627 3 48,191 97 49,818 100 Total 18,556 7 240,042 93 258,597 100 0-9 1-19 05-29 30-39 40-49 60+ Total Kilosa 1,821 0 92 261 131 128 2,433 Morogoro Rural 5,391 0 0 0 0 0 5,391 Kilombero 1,519 0 0 0 0 0 1,519 Ulanga 2,858 1,443 918 451 0 1,459 7,129 Morogoro Urban 338 59 23 12 0 25 458 Mvomero 1,250 0 255 121 0 0 1,627 Total 13,177 1,502 1,288 846 131 1,612 18,556 Poles Timber Logs Charcoal Firewood Not Ready to Use Not Allowed to Use Other Total Kilosa 0 1,245 0 0 875 1,044 131 3,295 Morogoro Rural 0 119 0 1,616 2,113 1,543 0 5,391 Kilombero 258 94 188 877 242 119 0 1,777 Ulanga 0 2,479 0 0 4,649 78 0 7,206 Morogoro Urban 24 35 0 59 44 295 0 458 Mvomero 0 1,013 0 490 0 250 0 1,753 Total 282 4,985 188 3,041 7,923 3,330 131 19,879 District Main use during 2002/03 14.3 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) 14.3 TREE FARMING: Number of Households Involved in Community Tree Planting Scheme By Main Use and District 14.3 TREE FARMING: Number of Households By Whether Village Have a Community Tree Planting Scheme By District District does your village have a Community Tree Planting Scheme Have a Community Tree Planting Scheme Does not Have a Community Tree Planting Scheme Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 224 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 225 Number % Number % Kilosa 15,318 21 58,117 79 73,435 Morogoro R 6,915 13 46,202 87 53,117 Kilombero 15,455 32 33,328 68 48,782 Ulanga 11,461 37 19,447 63 30,908 Morogoro Urb 464 10 3,970 90 4,434 Mvomero 17,756 35 32,313 65 50,069 Total 67,368 26 193,377 74 260,746 Number % Number % Number % Number % Number % Number % Kilosa 1,035 6.8 11,453 75.4 2,597 17.1 0 0.0 102 0.7 15,187 100.0 Morogoro R 604 8.7 4,613 66.7 1,457 21.1 242 3.5 0 0.0 6,915 100.0 Kilombero 1,000 6.5 13,272 85.9 1,088 7.0 94 0.6 0 0.0 15,455 100.0 Ulanga 1,240 10.9 8,140 71.5 2,004 17.6 0 0.0 0 0.0 11,384 100.0 Morogoro Urban 103 22.3 257 55.4 104 22.4 0 0.0 0 0.0 464 100.0 Mvomero 5,557 31.3 7,436 41.9 3,887 21.9 876 4.9 0 0.0 17,756 100.0 Total 9,539 14.2 45,171 67.3 11,138 16.6 1,211 1.8 102 0.2 67,161 100.0 Number % Number % Number % Number % Number % Number % Number % Kilosa 14,464 94.4 259 1.7 117 0.8 363 2.4 0 0.0 115 0.8 15,318 100.0 Morogoro R 5,737 85.9 708 10.6 0 0.0 122 1.8 111 1.7 0 0.0 6,678 100.0 Kilombero 14,281 94.7 557 3.7 0 0.0 125 0.8 0 0.0 119 0.8 15,082 100.0 Ulanga 10,929 97.3 0 0.0 0 0.0 77 0.7 77 0.7 149 1.3 11,231 100.0 Morogoro Urban 391 86.7 25 5.5 11 2.4 13 2.9 12 2.6 0 0.0 451 100.0 Mvomero 16,002 90.1 758 4.3 121 0.7 751 4.2 0 0.0 125 0.7 17,756 100.0 Total 61,803 92.9 2,306 3.5 248 0.4 1,451 2.2 200 0.3 508 0.8 66,516 100.0 15.3 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Morogoro Region By Source of Extension Messages By District Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 AGRICULTURE Year, Morogoro Region Very Good Good Average Poor No Good Total 15.3 CROP EXTENSION: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 agriculture Year Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 226 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 14,243 259 117 248 0 115 14,981 95,869 16 Morogoro R 4,646 587 0 122 111 0 5,467 24,319 22 Kilombero 13,452 557 0 125 0 119 14,253 82,872 17 Ulanga 9,475 0 0 0 0 149 9,623 59,430 16 Morogoro Urban 314 0 11 0 12 0 336 1,917 18 Mvomero 15,151 631 121 250 0 125 16,278 100,305 16 Total 57,281 2,033 248 745 123 508 60,938 364,713 17 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 6,808 126 117 0 0 504 7,555 95,869 8 Morogoro R 1,202 121 0 0 0 111 1,434 24,319 6 Kilombero 7,338 210 0 0 0 0 7,548 82,872 9 Ulanga 5,358 0 0 153 72 299 5,882 59,430 10 Morogoro Urban 167 0 11 0 0 0 178 1,917 9 Mvomero 7,689 1,391 121 619 0 128 9,948 100,305 10 Total 28,561 1,848 248 772 72 1,043 32,545 364,713 9 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Kilosa 3,373 900 248 0 616 5,137 95,869 5.4 Morogoro R 1,438 1,032 0 0 0 2,470 24,319 10.2 Kilombero 4,591 0 0 114 0 4,704 82,872 5.7 Ulanga 1,300 0 0 0 305 1,605 59,430 2.7 Morogoro Urban 120 0 11 0 0 131 1,917 6.8 Mvomero 2,478 1,399 0 0 128 4,005 100,305 4.0 Total 13,300 3,331 258 114 1,049 18,052 364,713 4.9 Table 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Morogoro Region District Erosion Control Table 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Morogoro Region Table 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Morogoro Region District Use of Agrochemicals District Spacing Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 227 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Kilosa 6,931 261 124 130 993 8,439 95,869 8.8 Morogoro R 1,680 115 122 0 0 1,916 24,319 7.9 Kilombero 4,653 0 0 0 0 4,653 82,872 5.6 Ulanga 1,535 0 0 75 383 1,993 59,430 3.4 Morogoro Urban 45 12 0 0 11 68 1,917 3.5 Mvomero 5,330 1,271 0 123 253 6,977 100,305 7.0 Total 20,173 1,659 245 328 1,640 24,046 364,713 6.6 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Kilosa 5,148 388 489 0 641 6,666 95,869 7.0 Morogoro R 1,186 0 0 0 0 1,186 24,319 4.9 Kilombero 6,617 329 0 125 0 7,071 82,872 8.5 Ulanga 2,199 0 0 0 539 2,738 59,430 4.6 Morogoro Urban 175 0 11 0 26 212 1,917 11.1 Mvomero 5,595 1,266 121 991 128 8,100 100,305 8.1 Total 20,921 1,984 620 1,116 1,333 25,973 364,713 7.1 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 9,570 387 0 115 0 376 10,448 95,869 11 Morogoro R 3,114 122 0 0 0 121 3,357 24,319 14 Kilombero 8,357 443 0 125 0 125 9,049 82,872 11 Ulanga 4,046 0 0 0 77 460 4,582 59,430 8 Morogoro Urban 293 25 11 13 0 0 341 1,917 18 Mvomero 12,149 889 0 499 0 626 14,163 100,305 14 Total 37,528 1,866 11 752 77 1,707 41,941 364,713 11 District Use of Improved Seed Table 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year, Morogoro Region Inorganic Fertilizer Use District Table 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Morogoro Region Table 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Morogoro Region Organic Fertilizer Use District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 228 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 3,311 0 124 625 0 636 4,696 95,869 5 Morogoro R 1,401 121 0 0 0 0 1,522 24,319 6 Kilombero 6,165 582 0 0 0 0 6,747 82,872 8 Ulanga 2,992 0 0 230 144 604 3,970 59,430 7 Morogoro Urban 43 0 11 0 0 0 54 1,917 3 Mvomero 6,192 127 245 615 0 125 7,305 100,305 7 Total 20,104 830 380 1,470 144 1,365 24,293 364,713 7 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 5,213 0 482 233 0 635 6,563 95,869 7 Morogoro R 1,059 0 0 0 0 0 1,059 24,319 4 Kilombero 4,086 0 0 0 0 0 4,086 82,872 5 Ulanga 2,519 0 0 0 77 76 2,672 59,430 4 Morogoro Urban 97 0 11 0 0 0 108 1,917 6 Mvomero 4,330 1,649 121 744 0 124 6,968 100,305 7 Total 17,305 1,649 613 977 77 834 21,456 364,713 6 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 10,663 259 117 117 0 243 11,399 95,869 12 Morogoro R 1,652 122 0 0 111 0 1,886 24,319 8 Kilombero 7,602 227 0 0 0 0 7,829 82,872 9 Ulanga 9,350 0 0 0 0 147 9,497 59,430 16 Morogoro Urban 185 0 0 0 0 0 185 1,917 10 Mvomero 9,721 1,014 0 128 0 375 11,238 100,305 11 Total 39,173 1,623 117 245 111 765 42,034 364,713 12 Table 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Morogoro Region District Crop Storage Table 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Morogoro Region Irrigation Technology District Mechanisation / LST District Table 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/ LST by Source and District During the 2002/03 Agriculture Year, Morogoro Region Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 229 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 7,243 131 117 117 0 504 8,112 95,869 8 Morogoro R 941 241 0 0 0 0 1,182 24,319 5 Kilombero 4,849 114 0 114 0 0 5,076 82,872 6 Ulanga 3,958 0 78 377 149 461 5,023 59,430 8 Morogoro Urban 125 0 0 0 0 0 125 1,917 7 Mvomero 5,230 1,144 123 250 0 247 6,994 100,305 7 Total 22,346 1,630 317 858 149 1,212 26,512 364,713 7 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 1,986 259 351 116 0 728 3,439 95,869 4 Morogoro R 694 0 0 122 111 0 928 24,319 4 Kilombero 5,505 114 119 0 0 0 5,738 82,872 7 Ulanga 7,676 0 0 0 0 150 7,826 59,430 13 Morogoro Urban 78 39 0 0 0 0 118 1,917 6 Mvomero 2,712 505 123 373 0 625 4,337 100,305 4 Total 18,651 916 593 611 111 1,503 22,385 364,713 6 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Kilosa 1,603 770 0 117 0 765 3,255 95,869 3 Morogoro R 593 119 0 0 0 0 712 24,319 3 Kilombero 4,857 94 0 0 125 0 5,076 82,872 6 Ulanga 1,226 228 0 0 0 148 1,601 59,430 3 Morogoro Urban 24 26 0 0 0 0 50 1,917 3 Mvomero 1,491 377 121 0 0 251 2,240 100,305 2 Total 9,794 1,613 121 117 125 1,164 12,934 364,713 4 Agro-forestry District Table 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-forestry by Source and District During the 2002/03 Agriculture Year, Morogoro Region Agro-progressing District Table 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-processing by Source and District During the 2002/03 Agriculture Year, Morogoro Region District Vermin Control Table 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Morogoro Region Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 230 Government NGO / Development Project Not applicable Total Total Number of Households % of total number of households Kilosa 1,636 247 504 2,387 95,869 2.5 Morogoro R 123 122 0 245 24,319 1.0 Kilombero 119 123 0 242 82,872 0.3 Ulanga 687 75 226 988 59,430 1.7 Morogoro Urban 0 0 0 0 1,917 0.0 Mvomero 497 0 124 621 100,305 0.6 Total 3,063 567 854 4,484 364,713 1.2 Government NGO / Development Project Not applicable Total Total Number of Households % of total number of households Kilosa 1,391 116 504 2,012 95,869 2.1 Morogoro R 246 245 0 491 24,319 2.0 Kilombero 123 246 0 369 82,872 0.4 Ulanga 452 0 226 678 59,430 1.1 Morogoro Urban 0 0 0 0 1,917 0.0 Mvomero 0 0 124 124 100,305 0.1 Total 2,213 607 854 3,673 364,713 1.0 Received Adopted % Received Adopted % Received Adopted % Kilosa 14,736 13,057 89 6,662 3,865 58 4,650 1,993 43 Morogoro R 5,467 5,344 98 1,434 842 59 2,470 1,881 76 Kilombero 14,253 12,624 89 7,677 5,109 67 4,704 1,093 23 Ulanga 9,474 7,343 78 5,349 3,370 63 1,070 613 57 Morogoro Urban 325 276 85 166 115 69 120 107 90 Mvomero 16,153 15,413 95 9,450 5,723 61 3,887 2,250 58 Total 60,408 54,057 89 30,739 19,024 62 16,900 7,939 47 Fish Farming District Table 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Morogoro Region Beekeeping District Table 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Beekeeeping by Source and District During the 2002/03 Agriculture Year, Morogoro Region Use of Agrochemicals Erosion Control Table 15.18: CROP EXTENSION: Number of Agriculture Hoseholds Receiving and Adopting Extension Messages by Type of Messages and District (Part I) During the 2002/03 agriculture Year, Morogoro Region District Spacing Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 231 Received Adopted % Received Adopted % Received Adopted % Kilosa 7,704 3,927 51 5,789 2,644 46 10,332 4,655 45 Morogoro R 1,916 1,457 76 1,186 482 41 3,357 2,048 61 Kilombero 4,530 678 15 7,071 1,736 25 9,049 3,572 39 Ulanga 1,610 307 19 2,351 154 7 4,275 1,600 37 Morogoro Urban 57 34 59 188 141 75 330 255 77 Mvomero 6,849 4,504 66 7,976 5,120 64 14,410 11,190 78 Total 22,668 10,907 48 24,562 10,277 42 41,753 23,321 56 Received Adopted % Received Adopted % Received Adopted % Kilosa 4,058 1,166 29 5,928 3,800 64 11,156 10,898 98 Morogoro R 1,522 469 31 1,059 956 90 1,886 1,548 82 Kilombero 6,747 3,646 54 3,967 825 21 7,829 6,324 81 Ulanga 3,521 2,074 59 2,131 611 29 9,116 9,119 100 Morogoro Urban 54 22 42 96 54 56 185 151 82 Mvomero 6,667 5,076 76 6,474 5,115 79 11,109 9,865 89 Total 22,569 12,452 55 19,655 11,360 58 41,281 37,904 92 Received Adopted % Received Adopted % Received Adopted % Kilosa 7,738 7,499 97 2,594 1,981 76 2,751 1,857 68 Morogoro R 1,182 1,078 91 928 824 89 712 363 51 Kilombero 4,951 4,329 87 5,743 5,256 92 5,076 1,535 30 Ulanga 4,411 3,492 79 7,908 7,907 100 1,375 618 45 Morogoro Urban 125 116 93 118 118 100 50 50 100 Mvomero 6,620 5,981 90 3,831 3,964 103 2,371 1,999 84 Total 25,027 22,497 90 21,123 20,050 95 12,335 6,423 52 Table 15.19 CROP EXTENSION: Number of Agriculture Hoseholds Receiving and Adopting Extension Messages by Type of Messages and District (Part 2) During the 2002/03 agriculture Year, Morogoro Region District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed Table 15.20 CROP EXTENSION: Number of Agriculture Hoseholds Receiving and Adopting Extension Messages by Type of Messages and District (Part 3) During the 2002/03 agriculture Year, Morogoro Region District Mechanisation / LST Irrigation Technology Crop Storage Table 15.21 CROP EXTENSION: Number of Agriculture Hoseholds Receiving and Adopting Extension Messages by Type of Messages and District (Part 4) During the 2002/03 agriculture Year, Morogoro Region District Vermin Control Agro-progressing Agro-forestry Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 232 Received Adopted % Received Adopted % Kilosa 1,883 886 47 1,507 510 34 Morogoro R 245 0 0 491 245 50 Kilombero 242 242 100 369 494 134 Ulanga 692 0 0 310 0 0 Morogoro Urban 0 0 0 0 0 0 Mvomero 245 123 50 0 0 0 Total 3,307 1,251 38 2,677 1,250 47 Table 15.22 CROP EXTENSION: Number of Agriculture Hoseholds Receiving and Adopting Extension Messages by Type of Messages and District (Part 5) During the 2002/03 agriculture Year, Morogoro Region District Beekeeping Fish Farming Tanzania Agriculture Sample Census - 2003 Morogoro 233 Appendix II 234 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 235 Number of household % Number of household % Kilosa 2,341 3 71,094 97 73,435 Morogoro R 0 0 53,117 100 53,117 Kilombero 1,429 3 47,354 97 48,782 Ulanga 1,912 6 28,996 94 30,908 Morogoro Urb 0 0 4,434 100 4,434 Mvomero 128 0 49,942 100 50,069 Total 5,810 2 254,936 98 260,746 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Kilosa 2,591 7,677 2,768 648 777 0 1,036 1,295 105 4,275 9,750 2,873 Kilombero 6,466 7,756 5,353 1,229 0 0 9,347 0 0 17,043 7,756 5,353 Ulanga 10,281 14,373 8,839 1,228 153 310 4,460 0 0 15,969 14,526 9,149 Mvomero 766 766 258 . . . . . . 766 766 258 Total 20,104 30,572 17,218 3,105 930 310 14,843 1,295 105 38,052 32,798 17,633 Total Number % Number % Number Kilosa 5,302 36.3 68,003 27.7 73,305 Morogoro R 1,962 13.4 51,155 20.8 53,117 Kilombero 1,440 9.8 47,342 19.3 48,782 Ulanga 764 5.2 30,067 12.2 30,831 Morogoro Urb 147 1.0 4,261 1.7 4,408 Mvomero 5,004 34.2 44,939 18.3 49,943 Total 14,620 100.0 245,767 100.0 260,386 Area (%) % Area (%) % Area (%) % Kilosa 3,014 42.4 116 2.1 3,129 24.8 Morogoro R 282 4.0 517 9.4 799 6.3 Kilombero 1,448 20.4 123 2.2 1,572 12.5 Ulanga 440 6.2 6 0.1 446 3.5 Morogoro Urb 143 2.0 58 1.0 201 1.6 Mvomero 1,775 25.0 4,691 85.1 6,466 51.3 Total 7,103 100.0 5,511 100.0 12,613 100.0 Table 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilezer By District during 2002/03 Agriculture Year, Morogoro Year Did you apply organic fertilizer during 2002/03? 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area Applied with Organic Fertilizers District g g Fertilizer g g Fertilizer 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year, Morogoro Region District Type of Craft Oxen Bulls Cows Total Table 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Agriculture Households Using Draft Animal to Cultivate Land By District during 2002/03 agriculture year Households Using Draft Animals Household Not Using Draft Animals Total households Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 236 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 237 Number % Number % Kilosa 13,273 18 77,655 73,064 13,273 Morogoro R 5,696 11 21,601 52,753 5,696 Kilombero 3,227 7 71,511 48,782 3,227 Ulanga 3,269 11 213,593 30,908 3,269 Morogoro Urb 655 15 4,716 4,423 655 Mvomero 10,403 21 71,988 49,316 10,403 Total 36,524 14 461,063 259,246 36,524 Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Kilosa 4,869 77,131 0 0 208 524 4,974 77,655 Morogoro Rural 429 18,115 0 0 674 3,486 1,104 21,601 Kilombero 1,103 71,294 0 0 217 217 1,320 71,511 Ulanga 1,608 213,515 0 0 78 78 1,685 213,593 Morogoro Urban 71 4,558 13 26 24 132 84 4,716 Mvomero 747 71,372 0 0 246 616 870 71,988 Total 8,826 455,985 13 26 1,447 5,052 10,037 461,063 Number of Household % Number of Cattle % 1-5 3,471 35 10,370 2 3 6-10 1,694 17 12,490 3 7 11-15 780 8 10,919 2 14 16-20 1,136 11 19,950 4 18 21-30 461 5 11,062 2 24 31-40 406 4 14,113 3 35 41-50 388 4 17,600 4 45 51-60 280 3 15,803 3 56 61-100 607 6 45,382 10 75 101-150 206 2 26,306 6 128 151+ 609 6 277,069 60 455 Total 10,037 100 461,063 100 46 Number of Cattle % Number of Cattle % Number of Cattle % Number of Cattle % Kilosa 77,131 99 0 0 524 0.7 77,655 16.8 Morogoro R 18,115 84 0 0 3,486 16.1 21,601 4.7 Kilombero 71,294 100 0 0 217 0.3 71,511 15.5 Ulanga 213,515 100 0 0 78 0.0 213,593 46.3 Morogoro Urb 4,558 97 26 1 132 2.8 4,716 1.0 Mvomero 71,372 99 0 0 616 0.9 71,988 15.6 Total 455,985 99 26 0 5,052 1.1 461,063 100.0 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Beef Improved Dairy Total Cattle 18.4 CATTLE PRODUCTION: Total Number of Cattle by Category and Type of Cattle; on 1st October 2003 Total Indigenous Improved Beef Improved Dairy Total Cattle 18.3 CATTLE PRODUCTION: Total Number of Households Rearing Cattle by Districts Herd Size Cattle Rearin Household Heads of Cattle Average Number Per Household Livestock Keeping 18.1 CATTLE PRODUCTION: Total Number of Household rearing Cattle by District Household Rearing Cattle Cattle Total Agriculture Household District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 238 Bulls Cows Steers Heifers Male Calves Female Calves Total Kilosa 7,340 30,847 6,324 11,063 9,482 12,075 77,131 Morogoro R 1,228 6,207 1,350 3,068 3,255 3,007 18,115 Kilombero 3,623 24,158 11,303 16,947 7,440 7,822 71,294 Ulanga 11,407 69,049 26,150 53,634 22,301 30,973 213,515 Morogoro Urb 287 2,291 389 546 536 508 4,558 Mvomero 8,700 24,093 5,217 11,237 9,394 12,730 71,372 Total 32,585 156,645 50,734 96,495 52,409 67,116 455,985 Bulls Cows Steers Heifers Male Calves Female Calves Total Kilosa . . . . . . . Morogoro R . . . . . . . Kilombero . . . . . . . Ulanga . . . . . . . Morogoro Urb . 13 . . 13 . 26 Mvomero . . . . . . . Total . 13 . . 13 . 26 Bulls Cows Steers Heifers Male Calves Female Calves Total Kilosa 105 105 . 102 105 105 524 Morogoro R 510 1,358 . 545 606 468 3,486 Kilombero . . . 217 . . 217 Ulanga . . . 78 . . 78 Morogoro Urb . 13 . 43 32 43 132 Mvomero . 246 . 123 123 123 616 Total 615 1,723 . 1,108 867 739 5,052 Bulls Cows Steers Heifers Male Calves Female Calves Total Kilosa 7,445 30,953 6,324 11,165 9,587 12,180 77,655 Morogoro R 1,738 7,565 1,350 3,613 3,861 3,475 21,601 Kilombero 3,623 24,158 11,303 17,164 7,440 7,822 71,511 Ulanga 11,407 69,049 26,150 53,712 22,301 30,973 213,593 Morogoro Urb 287 2,317 389 589 582 552 4,716 Mvomero 8,700 24,339 5,217 11,361 9,517 12,853 71,988 Total 33,200 158,381 50,734 97,604 53,289 67,855 461,063 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Total Cattle District Category - Improved Beef Cattle 18.7 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Dairy Cattle Tanzania Agriculture Sample Census - 2003 Morogoro 239 Appendix II 240 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 241 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Kilosa 9,787 101,115 97 0 0 0 616 3,087 3 9,918 104,202 Morogoro R 7,718 41,665 100 0 0 0 0 0 0 7,718 41,665 Kilombero 1,453 12,431 99 0 0 0 123 123 1 1,453 12,554 Ulanga 1,531 21,181 100 0 0 0 0 0 0 1,531 21,181 Morogoro Urb 560 5,100 93 26 104 2 23 297 5 560 5,501 Mvomero 6,403 55,569 96 123 862 1 378 1,641 3 6,530 58,073 Total 27,452 237,061 97 149 966 0 1,141 5,147 2 27,710 243,175 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 9,739 35 24,498 10 3 5-9 9,931 36 65,462 27 7 10-14 3,166 11 36,516 15 12 15-19 1,330 5 21,223 9 16 20-24 1,519 5 32,085 13 21 25-29 1,327 5 34,657 14 26 30-39 597 2 19,551 8 33 40+ 101 0 9,183 4 91 Total 27,710 100 243,175 100 9 Number % Number % Number % Number % Billy Goat 42,936 382 985 44,304 Castrated Goat 9,485 . 800 10,285 She Goat 124,101 285 2,113 126,500 Male Kid 25,494 259 866 26,619 She Kid 35,044 39 383 35,466 Total 237,061 966 5,147 243,175 Total Goat Improved Dairy Goats 19.2 Number of Households Rearing Goats and Heads of Goats by herd Size on 1st October, 2003 19.3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Category Indigenous Goats Improved Meat Goats 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Total Goat Indigenous Improved for Meat Improved Dairy Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 242 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilosa 15,424 5,123 53,759 12,057 14,753 101,115 Morogoro R 11,146 758 23,005 2,678 4,077 41,665 Kilombero 2,623 842 5,794 1,353 1,819 12,431 Ulanga 3,464 1,550 9,076 2,690 4,401 21,181 Morogoro Urb 767 345 2,650 478 860 5,100 Mvomero 9,513 867 29,817 6,238 9,134 55,569 Total 42,936 9,485 124,101 25,494 35,044 237,061 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilosa . . . . . . Morogoro R . . . . . . Kilombero . . . . . . Ulanga . . . . . . Morogoro Urb 13 . 39 13 39 104 Mvomero 370 . 246 246 . 862 Total 382 . 285 259 39 966 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Kilosa 16,040 5,889 55,204 12,316 14,753 104,202 Morogoro R 11,146 758 23,005 2,678 4,077 41,665 Kilombero 2,746 842 5,794 1,353 1,819 12,554 Ulanga 3,464 1,550 9,076 2,690 4,401 21,181 Morogoro Urb 780 379 2,723 719 900 5,501 Mvomero 10,129 867 30,697 6,863 9,517 58,073 Total 44,304 10,285 126,500 26,619 35,466 243,175 District Total Goat 19.5: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat 19.6 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 19.4: Total Number of Indigenous Goat by Category and District as of 1st October, 2003 District Number of Indigenous Tanzania Agriculture Sample Census - 2003 Morogoro 243 Appendix II 244 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 245 Number of Indigenous % Number of Improved for Mutton % Total Sheep % Ram 14,877 100 0 0 14,877 16 Castrated Sheep 5,681 85 985 15 6,666 7 She Sheep 44,583 100 0 0 44,583 47 Male Lamb 11,865 98 257 2 12,122 13 She Lamb 16,726 96 705 4 17,431 18 Total 93,733 98 1,947 2 95,680 100 Number % Number % Number % Kilosa 2,531 3 70,905 97 73,435 100 Morogoro R 817 2 52,300 98 53,117 100 Kilombero 1,061 2 47,722 98 48,782 100 Ulanga 1,379 4 29,529 96 30,908 100 Morogoro Urb 23 1 4,411 99 4,434 100 Mvomero 1,633 3 48,437 97 50,069 100 Total 7,443 3 253,302 97 260,746 100 Number of Indigenous % Number of Improved for Mutton % Total Sheep % Kilosa 14,973 96 634 4 15,607 16.3 Morogoro R 5,096 100 0 0 5,096 5.3 Kilombero 7,723 97 234 3 7,956 8.3 Ulanga 49,745 100 78 0 49,823 52.1 Morogoro Urb 138 100 0 0 138 0.1 Mvomero 16,058 94 1,001 6 17,059 17.8 Total 93,733 98 1,947 2 95,680 100.0 Number of Household % Number of Sheep % Average Number Per Household 1-4 1,663 22 3,333 3 2 5-9 3,244 44 19,161 20 6 10-14 1,110 15 11,916 12 11 15-19 718 10 11,528 12 16 20-24 122 2 2,449 3 20 25-29 77 1 1,914 2 25 30-39 154 2 4,845 5 32 40+ 355 5 40,534 42 114 Total 7,443 100 95,680 100 13 District 20.4 SHEEP PRODUCTION: Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03 Herd Size Total Sheep Households Not Raising Sheep Total Number of Indigenous Number of Improved for Mutton Total Sheep 20.1:Total Number of Sheep by breed Type on 1st October, 2002/03 20.3 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 Number of Indigeneous Number of Improved for Mutton Total Sheep Breed 20.2 SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year District Did the household own, raise or manage any Sheep? Households Raising Sheep Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 246 Ram Castrated Sheep She Sheep Male Lamb She Lamb Kilosa 2,962 515 8,022 908 2,567 14,973 Morogoro R 1,079 452 2,830 490 245 5,096 Kilombero 931 234 3,651 633 2,274 7,723 Ulanga 7,493 4,111 22,400 6,594 9,148 49,745 Morogoro Urb 23 . 78 12 24 138 Mvomero 2,388 370 7,602 3,229 2,469 16,058 Total 14,877 5,681 44,583 11,865 16,726 93,733 Ram Castrated Sheep She Sheep Male Lamb She Lamb Kilosa . . . 257 377 634 Morogoro R . . . . . . Kilombero . 234 . . . 234 Ulanga . . . . 78 78 Morogoro Urb . . . . . . Mvomero . 751 . . 250 1,001 Total . 985 . 257 705 1,947 Ram Castrated Sheep She Sheep Male Lamb She Lamb Kilosa 2,962 515 8,022 1,165 2,943 15,607 Morogoro R 1,079 452 2,830 490 245 5,096 Kilombero 931 467 3,651 633 2,274 7,956 Ulanga 7,493 4,111 22,400 6,594 9,226 49,823 Morogoro Urb 23 . 78 12 24 138 Mvomero 2,388 1,121 7,602 3,229 2,719 17,059 Total 14,877 6,666 44,583 12,122 17,431 95,680 20.6 SHEEP PRODUCTION: Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep Total Sheep District Number of Improved for Mutton Number of Improved for Mutton 20.7 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year 20.5 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Number of Indigenous Tanzania Agriculture Sample Census - 2003 Morogoro 247 Appendix II 248 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 249 Herd Size Number of Household % Number of Pig % Average Number Per Household 1-4 15,687 88 27,714 62 2 5-9 1,521 9 8,997 20 6 10-14 679 4 8,275 18 12 Total 17,887 100 44,986 100 3 District Number of Household Number of Pig Average Number Per Household Kilosa 3,531 11,432 3 Morogoro R 3,272 6,496 2 Kilombero 613 1,330 2 Ulanga 1,064 2,870 3 Morogoro Urb 177 604 3 Mvomero 9,230 22,254 2 Total 17,887 44,986 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Kilosa 2,546 1,424 4,136 1,410 1,917 11,432 Morogoro R 1,928 225 3,130 241 971 6,496 Kilombero 179 117 1,034 0 0 1,330 Ulanga 299 609 987 233 741 2,870 Morogoro Urb 115 32 277 51 128 604 Mvomero 7,319 0 9,358 2,916 2,662 22,254 Total 12,386 2,408 18,922 4,851 6,418 44,986 21.1 PIG PRODUCTION: Number of Households Rearing Pigs, Herd of Pigs aand Average Head of per Household by Herd Size as of 1st October, 2003 21.2 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.3 PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 250 LIVESTOCK PEST & PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 251 Number of houehold % Number of houehold % Kilosa 4,139 35 7,604 65 11,743 Morogoro R 1,227 22 4,469 78 5,696 Kilombero 1,294 40 1,932 60 3,227 Ulanga 1,603 50 1,589 50 3,192 Morogoro Urban 272 42 370 58 642 Mvomero 3,502 37 6,017 63 9,520 Total 12,038 35 21,983 65 34,021 Number % Number % Number % Number % Kilosa 2,933 43 1,114 31 640 20 1,097 30 Morogoro R 716 10 636 18 347 11 225 6 Kilombero 340 5 369 10 258 8 457 12 Ulanga 693 10 1,069 29 924 29 304 8 Morogoro Urban 171 2 72 2 36 1 125 3 Mvomero 1,997 29 369 10 1,001 31 1,512 41 Total 6,849 100 3,628 100 3,206 100 3,719 100 Number % Number % Kilosa 5,108 41 7,333 59 12,441 Morogoro R 1,244 22 4,452 78 5,696 Kilombero 728 23 2,499 77 3,227 Ulanga 1,449 47 1,666 53 3,115 Morogoro Urban 171 27 460 73 630 Mvomero 1,496 16 7,897 84 9,393 Total 10,196 30 24,307 70 34,503 Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Number of Dewormed Pigs Yes Yes Yes Yes 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Dewormed Goats Dewormed Cattles Dewormed Total 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock District Deworming Livestock Not deworming Livestock Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 252 Number % age Number % age Number % age Number % age Number % age Kilosa 2,185 43 2,404 47 261 5 258 5 0 0 5,108 Morogoro R 306 25 514 41 306 25 0 0 119 10 1,244 Kilombero 0 0 728 100 0 0 0 0 0 0 728 Ulanga 76 5 1,374 95 0 0 0 0 0 0 1,449 Morogoro Urban 75 44 83 48 0 0 0 0 13 8 171 Mvomero 254 17 1,119 75 0 0 0 0 124 8 1,496 Total 2,895 28 6,221 61 567 6 258 3 256 3 10,196 Number % age Number % age Kilosa 2,904 24 9,251 76 12,155 Morogoro R 819 14 4,877 86 5,696 Kilombero 1,156 36 2,071 64 3,227 Ulanga 1,602 50 1,590 50 3,192 Morogoro Urban 84 13 571 87 655 Mvomero 1,246 13 8,400 87 9,646 Total 7,811 23 26,760 77 34,572 Number % age Number % age Number % age Number % age Number % age Kilosa 1,531 53 1,373 47 0 0 0 0 2,904 100 Morogoro R 184 22 452 55 184 22 0 0 819 100 Kilombero 0 0 922 80 0 0 234 20 1,156 100 Ulanga 76 5 1,526 95 0 0 0 0 1,602 100 Morogoro Urban 48 57 36 43 0 0 0 0 84 100 Mvomero 250 20 996 80 0 0 0 0 1,246 100 Total 2,088 27 5,306 68 184 2 234 3 7,811 100 Total Total Method of Tick Control 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Number of Number of District 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year Dipping 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tsetse Flies Control None Spray Dipping Trapping Total Smearing Other None Spraying Tanzania Agriculture Sample Census - 2003 Morogoro 253 Appendix II 254 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 255 Breed Type Current Number Indigenous Chicken 2,018,227 Layer 82,168 Broiler 466 Ducks 76,948 Turkeys 89,728 Rabbits 8,828 Donkeys 1,892 Horse 0 Other 14,255 Total 2,292,512 Indigenous Chicken Layer Broiler Total 1 - 4 100,543 383 . 100,926 38,527 5 - 9 270,143 1,180 466 271,789 41,837 10 - 19 538,660 . . 538,660 42,306 20 - 29 385,418 2,301 . 387,719 16,841 30 - 39 228,874 . . 228,874 7,212 40 - 49 113,122 . . 113,122 2,717 50 - 99 289,911 . . 289,911 4,786 100+ 91,555 78,304 . 169,859 624 Total 2,018,227 82,168 466 2,100,861 154,850 Indigenous Chicken Layer Broiler Total 1 - 4 100,543 383 . 100,926 38,527 5 - 9 270,143 1,180 466 271,789 41,837 10 - 19 538,660 . . 538,660 42,306 20 - 29 385,418 2,301 . 387,719 16,841 30 - 39 228,874 . . 228,874 7,212 40 - 49 113,122 . . 113,122 2,717 50 - 99 289,911 . . 289,911 4,786 100+ 91,555 78,304 . 169,859 624 Total 2,018,227 82,168 466 2,100,861 154,850 Number Number of Households Number Number of Households Number Number of Households Number Number of Households Number Number of Households Kilosa 23,754 4,009 11,206 258 6,955 231 . 0 . 0 Morogoro 11,558 1,341 . 0 . 0 . 0 12,230 122 Kilombero 15,311 1,643 . 0 . 0 . 0 . 0 Ulanga 9,718 1,224 69,612 77 385 154 . 0 1,899 231 Morogoro Urban 246 93 862 26 97 12 . 0 . 0 Mvomero 16,362 2,368 8,047 249 1,390 254 1,892 252 126 126 Total 76,948 10,679 89,728 610 8,828 652 1,892 252 14,255 479 Chicken Type Number of Households with Chicken 23c OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Flock Size Chicken Type Number of Households with Chicken 23a OTHER LIVESTOCK: Total Number of Other Livestock by Breed and Type Other Ducks Turkeys Rabbits Donkeys 23d OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District 23b OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size Flock Size Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 256 Layer Broiler Total Kilosa 80,605 . 80,605 246 Kilombero 714 . 714 119 Ulanga 466 466 932 78 Mvomero 383 . 383 128 Total 82,168 466 82,634 570 1994/95 1998/99 2002/03 237857 102,165 461,063 0 231 5052 Dairy cattle pop[ trend 0 0 5,052 0 0 26 Goat Population Trend 272162 228,461 243,175 Sheep Population Trend 97871 57,259 95,680 Pig Population Trend 15682 50,449 44,986 Chicken Population Trend 1519844 1,547,504 2,100,861 Layers Population Trend 0 7300 82,168 Broiler pop trend 34080 15,842 466 23e OTHER LIVESTOCK: Number of Chicken by Type and District District Chicken Type Table 23f LIVESTOCK/POULTRY POPULATION TREND Livestock cartegory Catle PopulationTrend Improved Catle Beef Tanzania Agriculture Sample Census - 2003 Morogoro 257 Appendix II 258 LIVESTOCK PRODUCT Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 259 Sold Consumed / Utilised Sold Consumed / Utilised Sold Consumed / Utilised Kilosa 2,291,652 1,067,907 5,922 1,028 2,051 1,168 Morogoro 1,329,532 496,951 2,068 0 365 616 Kilombero 2,639,503 1,811,807 2,454 0 1,285 0 Ulanga 1,248,669 854,500 3,559 303 6,224 379 Morogoro Urban 29,003 27,591 314 0 1,543 0 Mvomero 2,854,033 2,055,640 2,410 0 250 0 Total 10,392,391 6,314,396 16,727 1,331 11,717 2,163 25.1 LIVESTOCK PRODUCTS: Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year District Product Name Eggs Hides Skins Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 260 ACCESS TO FUNCTIONAL LIVESTOCK STRUCTURES Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 261 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 5,882 261 0 0 0 0 0 6,143 Morogoro 551 121 0 0 122 122 0 915 Kilombero 129 0 467 0 0 0 129 725 Ulanga 2,295 77 0 0 0 0 0 2,372 Morogoro Urban 324 24 0 39 0 0 0 388 Mvomero 6,128 123 0 0 0 0 0 6,251 Total 15,309 605 467 39 122 122 129 16,794 <5 5 - 9 10 - 14 50+ Total Kilosa 5,621 0 0 0 5,621 Morogoro 0 0 0 122 122 Kilombero 363 0 0 0 363 Ulanga 2,372 0 0 0 2,372 Morogoro Urban 324 0 39 0 364 Mvomero 5,877 123 0 0 5,999 Total 14,556 123 39 122 14,841 <5 5 - 9 10 - 14 30 - 49 Total Kilosa 6,402 246 131 0 6,778 Morogoro 1,021 243 0 0 1,264 Kilombero 1,093 0 258 0 1,351 Ulanga 3,450 0 0 72 3,522 Morogoro Urban 347 0 52 0 399 Mvomero 6,744 0 0 0 6,744 Total 19,057 489 441 72 20,058 27.1 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Dip and District District Distance to Nearest Cattle Dip 27.2 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Spray Raced and District District Distance to Nearest Spray Raced 27.3 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hand Powered Sprayer and District District Distance to Nearest Hand Powered Sprayer Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 262 <5 5 - 9 10 - 14 15 - 19 Total Kilosa 5,622 131 0 0 5,753 Morogoro 984 0 0 0 984 Kilombero 978 0 0 0 978 Ulanga 2,680 0 0 0 2,680 Morogoro Urban 360 0 26 13 400 Mvomero 6,247 0 0 0 6,247 Total 16,871 131 26 13 17,041 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 6,528 1,166 1,558 128 131 130 131 9,771 Morogoro 0 207 371 306 245 119 0 1,248 Kilombero 0 251 379 1,004 0 0 258 1,892 Ulanga 2,825 1,082 303 230 230 0 0 4,670 Morogoro Urban 324 0 0 11 0 0 0 335 Mvomero 3,375 2,004 0 123 0 377 3,132 9,011 Total 13,052 4,710 2,612 1,801 605 627 3,520 26,927 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 5,257 0 651 0 125 768 0 6,801 Morogoro 0 103 0 122 0 243 0 468 Kilombero 0 0 0 0 0 0 129 129 Ulanga 2,448 0 0 0 0 0 0 2,448 Morogoro Urban 288 11 36 64 0 0 0 399 Mvomero 3,139 2,387 0 0 0 125 3,228 8,879 Total 11,132 2,502 686 186 125 1,136 3,357 19,124 27.4 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Crush and District District Distance to Nearest Cattle Crush 27.5 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Primary Market and District District Distance to Nearest Primary Market 27.6 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Secondary Market and District District Distance to Nearest Secondary Market Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 263 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 5,512 0 0 0 259 130 385 6,286 Morogoro 0 103 0 0 0 242 122 468 Kilombero 119 123 0 0 0 0 258 500 Ulanga 2,372 0 0 0 0 75 0 2,447 Morogoro Urban 301 0 74 75 0 13 0 464 Mvomero 5,769 243 0 0 0 2,767 101 8,880 Total 14,073 469 74 75 259 3,227 867 19,044 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 5,620 503 392 0 128 131 0 6,773 Morogoro 1,022 592 0 122 0 0 0 1,737 Kilombero 804 125 387 239 1,124 0 129 2,808 Ulanga 2,295 153 0 0 0 72 0 2,521 Morogoro Urban 336 39 24 0 0 0 0 399 Mvomero 4,579 3,469 1,567 124 0 0 128 9,867 Total 14,657 4,881 2,369 486 1,253 203 257 24,105 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 5,518 247 0 0 0 0 254 6,019 Morogoro 842 227 0 0 61 119 122 1,371 Kilombero 0 123 258 125 750 0 129 1,385 Ulanga 2,520 77 0 0 0 0 0 2,597 Morogoro Urban 303 13 111 75 0 0 0 502 Mvomero 3,386 1,418 241 1,567 0 124 0 6,736 Total 12,568 2,104 610 1,767 811 244 506 18,610 27.7 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Abattoir and District District Distance to Nearest Abattoir 27.8 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Slaughter Slab and District District Distance to Nearest Slaughter Slab 27.9 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hide/ Skin Shade and District District Distance to Nearest Hide/ Skin Shade Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 264 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 6,363 1,461 652 0 1,668 652 383 11,178 Morogoro 639 0 0 0 306 119 367 1,432 Kilombero 628 1,849 1,817 1,689 1,767 119 1,596 9,464 Ulanga 1,844 231 233 225 735 1,589 452 5,309 Morogoro Urban 280 116 222 97 0 0 0 715 Mvomero 3,234 5,572 994 1,567 125 124 243 11,860 Total 12,987 9,229 3,918 3,578 4,601 2,604 3,042 39,958 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Kilosa 6,489 696 392 0 256 0 379 8,212 Morogoro 532 0 0 122 0 0 537 1,191 Kilombero 246 123 258 253 1,124 0 375 2,379 Ulanga 1,919 78 0 0 0 1,826 1,101 4,923 Morogoro Urban 298 115 143 113 11 0 0 680 Mvomero 5,775 101 0 0 0 249 250 6,376 Total 15,259 1,113 793 488 1,391 2,075 2,642 23,761 <5 5 - 9 10 - 14 50+ Total Kilosa 5,387 0 0 0 5,387 Morogoro 61 0 0 122 184 Kilombero 119 0 0 0 119 Ulanga 2,295 0 0 0 2,295 Morogoro Urban 324 24 24 0 372 Mvomero 5,877 128 0 0 6,004 Total 14,063 152 24 122 14,361 27.10 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Input Supply and District District Distance to Nearest Input Supply 27.11 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Veterinary Clinic and District District Distance to Nearest Veterinary Clinic 27.12 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Holding Gound and District District Distance to Nearest Village Holding Gound Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 265 <5 5 - 9 10 - 14 50+ Total Kilosa 6,170 0 126 0 6,296 Morogoro 428 0 0 122 551 Kilombero 480 0 117 0 596 Ulanga 2,445 0 0 0 2,445 Morogoro Urban 313 35 23 0 372 Mvomero 6,001 123 0 0 6,124 Total 15,838 158 266 122 16,384 <5 5 - 9 10 - 14 20 - 29 Total Kilosa 5,988 371 259 0 6,618 Morogoro 3,945 122 0 0 4,066 Kilombero 2,416 0 609 0 3,025 Ulanga 2,675 77 0 76 2,828 Morogoro Urban 438 39 12 0 489 Mvomero 6,615 255 0 0 6,870 Total 22,076 864 880 76 23,896 District Distance to Nearest Drencher 27.13 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Watering Point/ Dam and District District Distance to Nearest Village Watering Point/ Dam 27.14 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Drencher and District Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 266 FISH FARMING Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 267 Number % Number % Number % Kilosa 93 0.1 73,342 99.9 73,435 100.0 Morogoro 363 0.7 52,754 99.3 53,117 100.0 Kilombero 369 0.8 48,413 99.2 48,782 100.0 Ulanga 76 0.2 30,832 99.8 30,908 100.0 Morogoro Urban 0 0.0 4,434 100.0 4,434 100.0 Mvomero 0 0.0 50,069 100.0 50,069 100.0 Total 902 0.3 259,844 99.7 260,746 100.0 Dug out Pond Total Morogoro 363 363 Kilombero 369 369 Ulanga 153 153 Total 885 885 NGOs / Project Neighbour Private Trader Other Total Number Number Number Number Number Morogoro 119 244 0 0 363 Kilombero 369 0 0 0 369 Ulanga 0 0 76 76 153 Total 489 244 76 76 885 Neighbor Did not Sell Total Number Number Number Morogoro 241 122 363 Kilombero 246 123 369 Ulanga 153 0 153 Total 640 245 885 District Number of Tilapia Number of Carp Number of Others Kilosa . . . Morogoro 86,890 0 0 Kilombero 73,872 0 0 Ulanga 30,548 0 0 Total 191,311 0 0 28.2d FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year District Source of Fingerling 28.2c FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year District District Fish Farming System 28.2b FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year 28.2a FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year 28.1a FISH FARMING: Number of Agricultural Households by Fish Farming and District, 2002/03 Agricultural Year District g Households Doing Fish g Households NOT Doing Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 268 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 269 Total Number % Number % Number Kilosa 4,725 6 68,711 94 73,435 Morogoro 1,614 3 51,503 97 53,117 Kilombero 4,501 9 44,281 91 48,782 Ulanga 1,530 5 29,378 95 30,908 Morogoro Urban 177 4 4,257 96 4,434 Mvomero 9,833 20 40,236 80 50,069 Total 22,380 9 238,366 91 260,746 Government NGO / Development Project Other Total Kilosa 1,700 0 0 1,700 Morogoro 1,267 0 0 1,267 Kilombero 2,673 0 0 2,673 Ulanga 920 0 78 997 Morogoro Urban 47 11 0 58 Mvomero 4,724 499 0 5,223 Total 11,332 510 78 11,919 Government NGO / Development Project Total Kilosa 1,001 0 1,001 13,273 8 Morogoro 552 0 552 5,696 10 Kilombero 248 123 371 3,227 12 Ulanga 305 0 305 3,269 9 Morogoro Urban 11 11 23 655 3 Mvomero 0 246 246 10,403 2 Total 2,118 381 2,499 Government NGO / Development Project Total Kilosa 871 0 871 13,273 7 Morogoro 552 0 552 5,696 10 Kilombero 248 0 248 3,227 8 Ulanga 305 0 305 3,269 9 Morogoro Urban 11 11 23 655 3 Mvomero 246 123 369 10,403 4 Total 2,233 135 2,368 Total Number of House hold raising Livestock % receiving advice of total Total Number of House hold raising Livestock % receiving advice of total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year Received livestock advice Did not Receive Livestock advice 291b LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District Source of Advice 29.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Source of Advice District Source of Advice 29.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 270 Government NGO / Development Project Large Scale Farmer not applicable Total Kilosa 2,933 0 0 0 2,933 13,273 22 Morogoro 1,021 0 0 0 1,021 5,696 18 Kilombero 1,267 0 0 0 1,267 3,227 39 Ulanga 845 0 0 0 845 3,269 26 Morogoro Urban 46 11 0 0 57 655 9 Mvomero 2,969 749 253 124 4,095 10,403 39 Total 9,080 761 253 124 10,218 Government NGO / Development Project Total Kilosa 611 0 611 13,273 5 Morogoro 575 0 575 5,696 10 Kilombero 429 0 429 3,227 13 Ulanga 540 0 540 3,269 17 Morogoro Urban 26 0 26 655 4 Mvomero 246 246 493 10,403 5 Total 2,428 246 2,674 Government NGO / Development Project Large Scale Farmer Total Kilosa 481 0 0 481 13,273 4 Morogoro 391 0 0 391 5,696 7 Kilombero 248 0 0 248 3,227 8 Ulanga 77 0 0 77 3,269 2 Morogoro Urban 13 11 0 24 655 4 Mvomero 123 123 123 369 10,403 4 Total 1,333 135 123 1,591 Government NGO / Development Project not applicable Total Kilosa 1,113 0 0 1,113 13,273 8 Morogoro 433 0 0 433 5,696 8 Kilombero 800 0 0 800 3,227 25 Ulanga 463 0 0 463 3,269 14 Morogoro Urban 11 0 0 11 655 2 Mvomero 1,116 251 124 1,490 10,403 14 Total 3,936 251 124 4,310 % receiving advice of total 29.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year Total Number of House hold raising % receiving advice of total 29.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving District Source of Advice Total Number of House hold raising % receiving advice of total Total Number of House hold raising Livestock % receiving advice of total Total Number of House hold raising District Source of Advice 29.1f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 271 Government NGO / Development Project Total Kilosa 1,261 0 1,261 13,273 9 Morogoro 779 0 779 5,696 14 Kilombero 119 246 366 3,227 11 Ulanga 76 0 76 3,269 2 Mvomero 123 123 246 10,403 2 Total 2,357 369 2,727 Government NGO / Development Project Other Total Kilosa 742 0 0 742 13,273 0 Morogoro 717 0 0 717 5,696 0 Kilombero 311 123 0 434 3,227 0 Ulanga 76 0 0 76 3,269 0 Morogoro Urban 26 0 13 39 655 0 Mvomero 491 497 0 987 10,403 0 Total 2,362 620 13 2,995 Government NGO / Development Project Large Scale Farmer not applicable Total Kilosa 2,939 0 0 0 2,939 13,273 22 Morogoro 1,389 0 0 0 1,389 5,696 24 Kilombero 3,288 123 0 0 3,411 3,227 106 Ulanga 1,074 0 0 0 1,074 3,269 33 Morogoro Urban 96 11 0 0 108 655 16 Mvomero 6,835 378 378 122 7,713 10,403 74 Total 15,622 512 378 122 16,634 36,524 46 Number % Number % Number % Number % Number % Kilosa 953 11 2,630 31 931 11 2,687 31 1,345 16 8,547 Morogoro 306 12 1,888 76 305 12 0 0 0 0 2,499 Kilombero 429 12 3,104 85 119 3 0 0 0 0 3,652 Ulanga 0 0 1,381 67 77 4 616 30 0 0 2,075 Morogoro Urban 37 22 92 55 11 7 26 15 0 0 166 Mvomero 5,346 38 6,115 43 1,374 10 890 6 507 4 14,231 Total 7,071 23 15,211 49 2,818 9 4,220 14 1,851 6 31,171 29.1l LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Source of Advice % receiving advice of total Total Total Number of House hold raising Livestock % receiving advice of total District Source of Advice 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year Poor No Good Quality of Service Total 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Very Good Good Average Total Number of House hold raising % receiving advice of total Total Number of House hold raising 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year Source of Advice Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 272 Number % Number % Number % Number % Number % Kilosa 4,725 20 4,725 20 4,725 20 4,725 20 4,725 20 23,624 Morogoro 1,614 32 938 19 835 17 835 17 835 17 5,056 Kilombero 4,501 21 4,133 20 4,133 20 4,133 20 4,133 20 21,034 Ulanga 1,530 20 1,530 20 1,530 20 1,530 20 1,530 20 7,651 Morogoro Urban 177 20 177 20 177 20 177 20 177 20 886 Mvomero 9,710 20 9,586 20 9,586 20 9,586 20 9,586 20 48,054 Total 22,257 21 21,090 20 20,986 20 20,986 20 20,986 20 106,305 Number % Number % Kilosa 750 6 11,634 94 12,385 Morogoro 1,088 34 2,150 66 3,238 Kilombero 2,683 59 1,844 41 4,527 Ulanga 455 11 3,535 89 3,990 Morogoro Urban 23 4 548 96 571 Mvomero 3,898 21 14,557 79 18,455 Total 8,898 21 34,269 79 43,166 Extension Provider 29.1n LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Government Co-operative Large Scale 29.1m LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural NGO / Development Total Other Total Tanzania Agriculture Sample Census - 2003 Morogoro 273 Appendix II 274 GOVERNMENT REGULATORY PROBLEMS Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 275 Number % Number % Number % Kilosa 1,076 1 72,098 99 73,174 100 Morogoro 299 1 52,818 99 53,117 100 Kilombero 125 0 48,657 100 48,782 100 Ulanga 229 1 30,679 99 30,908 100 Morogoro Urb 96 2 4,338 98 4,434 100 Mvomero 229 0 49,718 100 49,947 100 Total 2,053 1 258,309 99 260,362 100 30.1 GOVERNMENT REGULATORY PROBLEMS: Number of Agricultural Households by Whether Face Problems with Governmet Regulation During 2003/04 by District, 2002/03 Agricultural Year District Did you face problems with Govt regulations during 02/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 276 LABOUR USE Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 277 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 112,198 12,775 2,860 55,190 886 117 119 35,145 17,007 236,298 Soil Preparation by Hand 65,049 5,066 4,709 90,753 327 201 124 62,092 19,229 247,549 Soil Preparation bu Oxen / Tractor 18,167 1,234 508 7,818 605 0 259 2,575 7,705 38,872 Planting 30,931 1,696 5,893 93,898 337 255 1,027 105,468 15,088 254,594 Weeding 28,767 1,670 5,546 96,756 245 263 0 103,533 19,128 255,908 Crop Protection 28,522 1,551 19,945 61,339 1,909 616 9,402 67,090 7,766 198,141 Harvesting 29,184 2,147 9,581 90,566 364 168 602 102,335 15,504 250,451 Crop Processing 32,730 3,625 121,092 22,493 2,659 6,697 5,610 24,238 2,335 221,478 Crop Marketing 146,831 4,086 6,351 34,483 518 394 509 16,515 238 209,925 Cattle Rearing 7,307 697 368 835 124 0 201 2,030 261 11,823 Cattle Herding 1,706 1,043 116 562 3,609 12 1,112 843 995 9,999 Cattle Marketing 8,862 374 119 334 321 0 0 122 0 10,132 Goat & Sheep Rearing 10,012 874 776 4,618 1,225 0 251 8,010 498 26,263 Goat & Sheep Herding 4,023 1,273 518 2,897 8,237 154 2,874 5,502 1,687 27,164 Goat & Sheep Marketing 16,619 726 154 2,014 715 0 0 1,898 0 22,124 Milking 1,225 519 3,193 1,518 794 94 630 361 352 8,685 Pig Rearing 6,034 376 1,616 2,149 252 75 476 7,889 0 18,867 Poultry Keeping 35,029 1,825 48,780 21,533 341 714 981 46,739 218 156,161 Collecting Water 30,270 5,607 159,384 11,017 1,148 13,303 8,147 22,160 1,061 252,097 Collecting Firewood 43,027 8,229 136,145 24,918 1,135 5,614 7,384 23,332 2,945 252,728 Pole Cutting 111,369 30,493 4,453 6,039 1,923 129 460 4,079 9,147 168,092 Timber Wood Cutting 9,218 1,152 381 503 0 0 88 121 131 11,593 Building / Maintaining Houses 125,863 30,830 3,644 7,053 2,028 574 144 5,418 18,735 194,287 Making Beer 14,301 1,827 34,021 1,691 511 248 78 1,207 325 54,208 Beekeeping 2,396 321 121 119 0 0 0 129 0 3,085 Fishing 7,846 889 11 416 218 0 0 129 11 9,519 Fish Farming 1,119 122 244 199 122 127 0 248 0 2,181 Off - farm Income Generation 144,797 7,373 18,961 49,257 1,704 355 395 13,349 760 236,951 31.1 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Activity Type of Household Member Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 278 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 47 5 1 23 0 0 0 15 7 100 Soil Preparation by Hand 26 2 2 37 0 0 0 25 8 100 Soil Preparation bu Oxen / Tractor 47 3 1 20 2 0 1 7 20 100 Planting 12 1 2 37 0 0 0 41 6 100 Weeding 11 1 2 38 0 0 0 40 7 100 Crop Protection 14 1 10 31 1 0 5 34 4 100 Harvesting 12 1 4 36 0 0 0 41 6 100 Crop Processing 15 2 55 10 1 3 3 11 1 100 Crop Marketing 70 2 3 16 0 0 0 8 0 100 Cattle Rearing 62 6 3 7 1 0 2 17 2 100 Cattle Herding 17 10 1 6 36 0 11 8 10 100 Cattle Marketing 87 4 1 3 3 0 0 1 0 100 Goat & Sheep Rearing 38 3 3 18 5 0 1 30 2 100 Goat & Sheep Herding 15 5 2 11 30 1 11 20 6 100 Goat & Sheep Marketing 75 3 1 9 3 0 0 9 0 100 Milking 14 6 37 17 9 1 7 4 4 100 Pig Rearing 32 2 9 11 1 0 3 42 0 100 Poultry Keeping 22 1 31 14 0 0 1 30 0 100 Collecting Water 12 2 63 4 0 5 3 9 0 100 Collecting Firewood 17 3 54 10 0 2 3 9 1 100 Pole Cutting 66 18 3 4 1 0 0 2 5 100 Timber Wood Cutting 80 10 3 4 0 0 1 1 1 100 Building / Maintaining Houses 65 16 2 4 1 0 0 3 10 100 Making Beer 26 3 63 3 1 0 0 2 1 100 Beekeeping 78 10 4 4 0 0 0 4 0 100 Fishing 82 9 0 4 2 0 0 1 0 100 Fish Farming 51 6 11 9 6 6 0 11 0 100 Off - farm Income Generation 61 3 8 21 1 0 0 6 0 100 Activity Type of Household Member 31.2 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Morogoro 279 Appendix II 280 ACCESS TO INFRASTRUCTURE & OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 281 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 1,377 1.9 1,109 1.5 13,964 19.0 14,931 20.3 42,053 57.3 73,435 31.1 Morogoro 2,278 4.3 1,665 3.1 10,715 20.2 15,528 29.2 22,932 43.2 53,117 19.6 Kilombero 1,280 2.6 5,005 10.3 11,969 24.5 14,355 29.4 16,174 33.2 48,782 16.9 Ulanga 1,071 3.5 3,772 12.2 6,528 21.1 4,521 14.6 15,015 48.6 30,908 23.3 Morogoro Urban 76 1.7 73 1.6 2,360 53.2 1,877 42.3 48 1.1 4,434 9.1 Mvomero 1,729 3.5 2,093 4.2 17,378 34.7 10,904 21.8 17,965 35.9 50,069 25.5 Total 7,812 3.0 13,716 5.3 62,914 24.1 62,116 23.8 114,187 43.8 260,746 23.7 District Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Mean Distance Kilosa 22,067 30.0 31,331 42.7 18,171 24.7 1,168 1.6 698 1.0 73,435 3.4 Morogoro 16,789 31.6 21,589 40.6 13,536 25.5 1,203 2.3 0 0.0 53,117 2.1 Kilombero 17,787 36.5 16,370 33.6 13,145 26.9 986 2.0 494 1.0 48,782 2.5 Ulanga 12,609 40.8 12,977 42.0 4,714 15.3 455 1.5 152 0.5 30,908 1.8 Morogoro Urban 875 19.7 1,852 41.8 1,369 30.9 326 7.4 12 0.3 4,434 3.9 Mvomero 16,076 32.1 22,323 44.6 10,434 20.8 1,114 2.2 122 0.2 50,069 1.8 Total 86,203 33.1 106,442 40.8 61,368 23.5 5,254 2.0 1,479 0.6 260,746 2.5 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 6,460 8.8 11,548 15.7 38,543 52.5 12,420 16.9 4,464 6.1 73,435 8.4 Morogoro 5,137 9.7 11,175 21.0 24,589 46.3 6,546 12.3 5,671 10.7 53,117 8.6 Kilombero 7,330 15.0 14,201 29.1 14,027 28.8 8,838 18.1 4,387 9.0 48,782 6.8 Ulanga 3,592 11.6 11,227 36.3 13,877 44.9 1,754 5.7 458 1.5 30,908 6.3 Morogoro Urban 148 3.3 1,024 23.1 1,910 43.1 1,262 28.5 90 2.0 4,434 8.2 Mvomero 6,861 13.7 12,077 24.1 24,873 49.7 4,907 9.8 1,351 2.7 50,069 5.7 Total 29,527 11.3 61,252 23.5 117,819 45.2 35,727 13.7 16,421 6.3 260,746 7.4 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 358 0.5 506 0.7 9,686 13.2 11,563 15.7 51,323 69.9 73,435 49.6 Morogoro 2,880 5.4 119 0.2 123 0.2 535 1.0 49,460 93.1 53,117 77.5 Kilombero 242 0.5 2,366 4.9 5,796 11.9 4,474 9.2 35,905 73.6 48,782 70.7 Ulanga 155 0.5 834 2.7 5,064 16.4 994 3.2 23,863 77.2 30,908 36.6 Morogoro Urban 0 0.0 25 0.6 1,402 31.6 2,594 58.5 413 9.3 4,434 12.0 Mvomero 609 1.2 1,975 3.9 9,809 19.6 7,467 14.9 30,208 60.3 50,069 34.9 Total 4,244 1.6 5,825 2.2 31,879 12.2 27,626 10.6 191,172 73.3 260,746 54.2 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 0 0.0 125 0.2 3,567 4.9 4,205 5.7 65,538 89.2 73,435 98.3 Morogoro 486 0.9 0 0.0 242 0.5 61 0.1 52,328 98.5 53,117 82.4 Kilombero 492 1.0 1,981 4.1 5,045 10.3 123 0.3 41,141 84.3 48,782 78.2 Ulanga 0 0.0 444 1.4 2,674 8.7 383 1.2 27,407 88.7 30,908 75.6 Morogoro Urban 0 0.0 13 0.3 1,293 29.2 2,704 61.0 425 9.6 4,434 12.7 Mvomero 126 0.3 0 0.0 121 0.2 366 0.7 49,455 98.8 50,069 69.5 Total 1,104 0.4 2,563 1.0 12,942 5.0 7,842 3.0 236,295 90.6 260,746 81.6 District Distance (Kilometer) to Hospital 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to District Capital 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Health Clinic 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 District Distance (Kilometer) to Secondary School Mean Distance Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 282 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 310 0.4 0 0.0 0 0.0 102 0.1 73,022 99.4 73,435 131.9 Morogoro 845 1.6 0 0.0 0 0.0 0 0.0 52,272 98.4 53,117 82.4 Kilombero 891 1.8 126 0.3 246 0.5 0 0.0 47,519 97.4 48,782 272.4 Ulanga 77 0.2 0 0.0 0 0.0 0 0.0 30,831 99.8 30,908 333.1 Morogoro Urban 20 0.5 23 0.5 1,206 27.2 2,705 61.0 481 10.8 4,434 14.1 Mvomero 126 0.3 0 0.0 121 0.2 245 0.5 49,577 99.0 50,069 85.9 Total 2,270 0.9 149 0.1 1,573 0.6 3,052 1.2 253,702 97.3 260,746 161.1 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 46,774 63.7 17,253 23.5 6,295 8.6 2,729 3.7 384 0.5 73,435 1.6 Morogoro 29,222 55.0 13,481 25.4 9,331 17.6 604 1.1 479 0.9 53,117 2.4 Kilombero 37,948 77.8 6,836 14.0 3,249 6.7 503 1.0 246 0.5 48,782 2.0 Ulanga 25,356 82.0 3,124 10.1 2,121 6.9 77 0.2 230 0.7 30,908 1.1 Morogoro Urban 2,373 53.5 989 22.3 951 21.4 121 2.7 0 0.0 4,434 1.6 Mvomero 33,379 66.7 10,739 21.4 5,572 11.1 252 0.5 126 0.3 50,069 1.1 Total 175,053 67.1 52,422 20.1 27,519 10.6 4,287 1.6 1,465 0.6 260,746 1.7 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 39,164 53.3 13,486 18.4 13,746 18.7 2,614 3.6 4,425 6.0 73,435 3.8 Morogoro 15,681 29.5 7,039 13.3 14,153 26.6 6,648 12.5 9,595 18.1 53,117 9.2 Kilombero 26,779 54.9 10,027 20.6 7,241 14.8 3,601 7.4 1,134 2.3 48,782 3.0 Ulanga 15,280 49.4 7,845 25.4 4,702 15.2 917 3.0 2,164 7.0 30,908 3.4 Morogoro Urban 1,741 39.3 1,206 27.2 1,263 28.5 224 5.0 0 0.0 4,434 2.6 Mvomero 21,658 43.3 8,445 16.9 13,404 26.8 755 1.5 5,808 11.6 50,069 8.2 Total 120,303 46.1 48,048 18.4 54,510 20.9 14,758 5.7 23,126 8.9 260,746 5.5 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 8,516 11.6 3,292 4.5 10,725 14.6 10,251 14.0 40,651 55.4 73,435 41.1 Morogoro 419 0.8 1,315 2.5 3,589 6.8 1,548 2.9 46,245 87.1 53,117 71.2 Kilombero 1,001 2.1 1,786 3.7 2,370 4.9 5,837 12.0 37,788 77.5 48,782 78.8 Ulanga 0 0.0 0 0.0 77 0.2 0 0.0 30,831 99.8 30,908 175.4 Morogoro Urban 622 14.0 509 11.5 2,083 47.0 1,210 27.3 11 0.2 4,434 6.8 Mvomero 3,264 6.5 1,308 2.6 3,912 7.8 4,727 9.4 36,859 73.6 50,069 42.1 Total 13,822 5.3 8,210 3.1 22,755 8.7 23,573 9.0 192,385 73.8 260,746 69.8 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 15,472 21.1 8,893 12.1 25,908 35.3 14,967 20.4 8,195 11.2 73,435 12.6 Morogoro 4,771 9.0 4,205 7.9 23,480 44.2 9,739 18.3 10,921 20.6 53,117 16.0 Kilombero 3,879 8.0 3,023 6.2 9,944 20.4 8,031 16.5 23,905 49.0 48,782 49.3 Ulanga 3,747 12.1 6,723 21.8 9,680 31.3 2,383 7.7 8,375 27.1 30,908 12.2 Morogoro Urban 254 5.7 321 7.2 1,774 40.0 2,035 45.9 50 1.1 4,434 9.0 Mvomero 7,374 14.7 7,881 15.7 18,694 37.3 9,552 19.1 6,568 13.1 50,069 11.1 Total 35,499 13.6 31,046 11.9 89,479 34.3 46,707 17.9 58,015 22.2 260,746 19.7 District Distance (Kilometer) to Primary Market 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tarmac Road 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Feeder Road 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to ALL Wealther Road 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to Districtal Capital 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 283 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 9,335 12.7 6,864 9.3 17,974 24.5 23,523 32.0 15,740 21.4 73,435 20.8 Morogoro 6,461 12.2 3,233 6.1 17,185 32.4 12,040 22.7 14,197 26.7 53,117 15.2 Kilombero 3,393 7.0 3,268 6.7 10,597 21.7 8,813 18.1 22,711 46.6 48,782 49.0 Ulanga 833 2.7 3,466 11.2 8,917 28.9 3,694 12.0 13,998 45.3 30,908 39.3 Morogoro Urban 231 5.2 12 0.3 1,590 35.9 2,569 57.9 32 0.7 4,434 10.1 Mvomero 2,106 4.2 1,713 3.4 12,451 24.9 8,995 18.0 24,805 49.5 50,069 30.6 Total 22,360 8.6 18,556 7.1 68,713 26.4 59,634 22.9 91,482 35.1 260,746 28.8 Less than 1 % 1 - 2.9 % 3 - 9 9 % 10 - 19.9 % Above 20 % Total Kilosa 12,022 16.4 2,594 3.5 11,298 15.4 8,423 11.5 39,098 53.2 73,435 44.0 Morogoro 2,760 5.2 1,839 3.5 7,315 13.8 6,909 13.0 34,293 64.6 53,117 51.6 Kilombero 1,385 2.8 2,887 5.9 11,693 24.0 9,650 19.8 23,167 47.5 48,782 49.1 Ulanga 1,749 5.7 2,439 7.9 6,008 19.4 1,454 4.7 19,259 62.3 30,908 48.5 Morogoro Urban 52 1.2 0 0.0 1,319 29.8 2,617 59.0 446 10.1 4,434 12.3 Mvomero 2,607 5.2 2,585 5.2 6,419 12.8 2,485 5.0 35,974 71.8 50,069 50.3 Total 20,575 7.9 12,343 4.7 44,052 16.9 31,538 12.1 152,238 58.4 260,746 47.7 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 1,235 1.7 6,294 8.8 4,075 5.7 2,455 3.4 6,822 9.5 11,416 16.0 39,242 54.9 71,539 74.1 Morogoro 2,298 4.4 246 0.5 0 0.0 1,714 3.3 3,801 7.3 4,578 8.9 39,082 75.6 51,719 76.3 Kilombero 2,982 6.5 1,261 2.8 242 0.5 1,600 3.5 1,743 3.8 7,298 16.0 30,617 66.9 45,743 88.3 Ulanga 1,226 4.0 0 0.0 154 0.5 2,087 6.8 1,058 3.5 5,132 16.8 20,943 68.4 30,600 206.7 Morogoro Urban 483 11.5 1,034 24.6 1,016 24.1 1,129 26.8 402 9.6 0 0.0 143 3.4 4,208 13.6 Mvomero 8,072 16.2 610 1.2 0 0.0 372 0.7 4,692 9.4 3,866 7.8 32,203 64.6 49,815 69.9 Total 16,297 6.4 9,445 3.7 5,487 2.2 9,358 3.7 18,518 7.3 32,290 12.7 162,230 64.0 253,624 91.1 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 8,714 17.0 19,967 39.0 11,694 22.8 3,360 6.6 4,320 8.4 1,968 3.8 1,184 2.3 51,208 11.0 Morogoro 1,578 3.8 11,028 26.4 4,197 10.0 363 0.9 4,900 11.7 5,578 13.4 14,118 33.8 41,763 37.0 Kilombero 10,882 32.8 4,346 13.1 4,076 12.3 1,765 5.3 3,157 9.5 2,417 7.3 6,513 19.6 33,157 20.9 Ulanga 1,274 7.0 5,680 31.3 1,923 10.6 922 5.1 967 5.3 4,529 25.0 2,856 15.7 18,151 26.0 Morogoro Urban 95 2.6 1,884 50.6 998 26.8 689 18.5 33 0.9 12 0.3 16 0.4 3,727 9.5 Mvomero 12,641 35.9 7,106 20.2 1,643 4.7 1,389 3.9 3,988 11.3 253 0.7 8,210 23.3 35,230 26.8 Total 35,184 19.2 50,011 27.3 24,530 13.4 8,489 4.6 17,365 9.5 14,758 8.1 32,898 18.0 183,236 22.9 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 123 0.2 813 1.1 3,970 5.4 6,430 8.8 3,234 4.4 6,223 8.5 52,221 71.5 73,014 100.5 Morogoro 5,728 10.9 362 0.7 0 0.0 0 0.0 1,039 1.4 236 0.3 45,262 62.0 52,628 90.1 Kilombero 119 0.3 3,229 7.1 385 0.5 0 0.0 125 0.2 8,281 11.3 33,228 45.5 45,367 82.3 Ulanga 74 0.2 151 0.5 0 0.0 226 0.3 1,023 1.4 2,269 3.1 27,165 37.2 30,908 159.5 Morogoro Urban 431 10.3 1,121 26.7 867 1.2 1,106 1.5 38 0.1 0 0.0 627 0.9 4,190 19.8 Mvomero 7,822 15.7 4,103 8.2 128 0.2 1,850 2.5 4,467 6.1 2,783 3.8 28,791 39.4 49,944 51.3 Total 14,298 5.6 9,779 3.8 5,349 7.3 9,612 13.2 9,927 13.6 19,792 27.1 187,294 256.5 256,052 91.2 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year District Distance (Kilometer) to Research Station District Distance (Kilometer) to Veterinary Clinic 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center District Distance (Kilometer) to Extension Center 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tertiary Market 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary Market Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 284 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 383 0.5 918 1.3 3,175 4.3 4,758 6.5 2,213 3.0 6,215 8.5 55,561 75.9 73,224 101.7 Morogoro 6,406 12.1 0 0.0 119 0.2 0 0.0 121 0.2 2,765 3.8 43,706 59.7 53,117 82.8 Kilombero 252 0.6 3,352 7.4 385 0.5 0 0.0 252 0.3 8,162 11.1 33,200 45.3 45,603 81.6 Ulanga 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 3,216 4.4 27,692 37.8 30,908 140.9 Morogoro Urban 472 11.1 997 23.5 932 1.3 1,058 1.4 63 0.1 0 0.0 718 1.0 4,239 21.6 Mvomero 7,826 15.6 2,864 5.7 0 0.0 368 0.5 4,575 6.2 2,357 3.2 32,080 43.8 50,069 65.2 Total 15,338 6.0 8,131 3.2 4,611 6.3 6,184 8.4 7,224 9.9 22,715 31.0 192,958 263.5 257,160 90.4 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 0 0.0 2,134 2.9 3,813 5.2 1,644 2.2 4,706 6.4 11,363 15.5 49,542 67.7 73,203 100.5 Morogoro 1,821 3.4 0 0.0 119 0.2 0 0.0 2,751 3.8 5,534 7.6 42,892 58.6 53,117 85.8 Kilombero 123 0.3 1,643 2.2 128 0.2 1,724 2.4 1,743 2.4 7,408 10.1 32,473 44.4 45,242 79.4 Ulanga 0 0.0 1,151 1.6 153 0.2 153 0.2 962 1.3 9,062 12.4 17,534 24.0 29,015 77.6 Morogoro Urban 118 2.8 1,222 1.7 1,214 1.7 1,208 1.6 390 0.5 0 0.0 45 0.1 4,196 12.4 Mvomero 7,829 15.6 121 0.2 0 0.0 245 0.3 5,064 6.9 4,361 6.0 32,448 44.3 50,069 70.7 Total 9,890 3.9 6,272 8.6 5,428 7.4 4,973 6.8 15,615 21.3 37,729 51.5 174,936 239.0 254,842 83.6 <5 % 5 - 9 % 10 - 14 % 15 - 19 % 20 - 29 % 30 - 49 % 50 + % Total Kilosa 616 0.8 2,145 2.9 516 0.7 1,169 1.6 963 1.3 4,992 6.8 62,805 85.8 73,206 112.3 Morogoro 6,668 12.8 0 0.0 0 0.0 0 0.0 1,833 2.5 3,987 5.4 39,711 54.2 52,199 76.3 Kilombero 3,080 6.8 1,268 1.7 128 0.2 1,724 2.4 126 0.2 5,240 7.2 33,914 46.3 45,480 138.3 Ulanga 385 1.3 914 1.2 153 0.2 153 0.2 77 0.1 4,475 6.1 23,563 32.2 29,719 267.0 Morogoro Urban 525 12.5 899 1.2 986 1.3 1,073 1.5 403 0.6 0 0.0 318 0.4 4,204 18.5 Mvomero 8,324 16.7 243 0.3 0 0.0 369 0.5 5,057 6.9 4,243 5.8 31,706 43.3 49,942 69.6 Total 19,597 7.7 5,470 7.5 1,783 2.4 4,487 6.1 8,459 11.6 22,938 31.3 192,016 262.3 254,750 118.4 Very Good % Good % Average % Poor % No good % Not applicable Total Kilosa 1,038 0.2 10,988 2.5 6,838 1.6 65,255 14.8 12,884 2.9 343,607 440,611 Morogoro 550 0.2 8,263 2.6 5,057 1.6 3,861 1.2 3,624 1.1 297,346 318,702 Kilombero 496 0.2 7,873 2.7 2,372 0.8 2,442 0.8 1,922 0.7 277,588 292,693 Ulanga 986 0.5 11,498 6.2 5,248 2.8 2,848 1.5 154 0.1 164,716 185,449 Morogoro Urban 107 0.4 210 0.8 79 0.3 628 2.4 453 1.7 25,127 26,604 Mvomero 5,094 1.7 5,077 1.7 6,882 2.3 13,559 4.5 9,119 3.0 260,683 300,415 Total 8,272 0.5 43,910 2.8 26,476 1.7 88,592 5.7 28,157 1.8 1,369,068 1,564,475 Very Good % Good % Average % Poor % No good % Total Kilosa 1,038 4.5 7,946 34.7 3,566 15.6 8,957 39.1 1,402 6.1 22,908 Morogoro 367 1.6 3,609 44.2 2,740 33.6 842 10.3 604 7.4 8,163 Kilombero 377 1.6 6,199 78.3 965 12.2 126 1.6 248 3.1 7,915 Ulanga 680 3.0 6,768 66.9 2,518 24.9 151 1.5 0 0.0 10,118 Morogoro Urban 48 0.2 90 29.0 5 1.5 95 30.7 73 23.6 311 Mvomero 4,717 20.6 4,327 27.4 4,989 31.6 753 4.8 1,019 6.4 15,805 Total 7,227 31.5 28,940 44.4 14,783 22.7 10,924 16.7 3,346 5.1 65,220 District Satisfaction of Using Veterinary Clinic 33.20 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Extension Center 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center District Distance (Kilometer) to Livestock Development Center 33.19 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Distance (Kilometer) to Plant Protection Lab 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year District Distance (Kilometer) to Land Registration Office 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 285 Very Good % Good % Average % Poor % No good % Total Kilosa 0 0 1,245 8.4 764 5.1 10,900 73.3 1,968 13.2 14,878 Morogoro 0 0 861 32.2 609 22.8 604 22.5 604 22.6 2,678 Kilombero 0 0 338 23.2 258 17.7 603 41.4 258 17.7 1,456 Ulanga 0 0 2,085 66.0 538 17.0 538 17.0 0 0.0 3,161 Morogoro Urban 26 9 39 13.9 13 4.6 128 45.8 73 26.3 279 Mvomero 0 0 127 2.7 254 5.5 2,634 56.8 1,620 34.9 4,636 Total 26 0 4,695 17.3 2,437 9.0 15,407 56.9 4,523 16.7 27,088 Very Good % Good % Average % Poor % No good % Total Kilosa 0 0.0 564 3.9 637 4.4 11,062 75.7 2,347 16.1 14,609 Morogoro 0 0.0 861 35.4 365 15.0 604 24.8 604 24.8 2,434 Kilombero 0 0.0 244 19.7 258 20.9 478 38.6 258 20.8 1,237 Ulanga 153 12.5 148 12.0 231 18.9 693 56.6 0 0.0 1,225 Morogoro Urban 0 0.0 0 0.0 12 6.6 92 52.0 73 41.4 177 Mvomero 123 2.5 250 5.1 379 7.8 2,509 51.4 1,620 33.2 4,881 Total 276 1.1 2,067 8.4 1,882 7.7 15,438 62.8 4,901 20.0 24,564 Very Good % Good % Average % Poor % No good % Total Kilosa 0 0.0 369 2.5 878 6.0 11,023 75.4 2,347 16.1 14,618 Morogoro 0 0.0 842 30.2 735 26.4 604 21.7 604 21.7 2,785 Kilombero 119 7.4 477 29.5 510 31.5 126 7.8 387 23.9 1,618 Ulanga 76 2.7 981 34.9 829 29.5 846 30.1 78 2.8 2,811 Morogoro Urban 0 0.0 12 5.0 12 4.9 128 53.9 86 36.2 238 Mvomero 0 0.0 246 5.3 377 8.1 2,393 51.6 1,620 34.9 4,636 Total 196 0.7 2,927 11.0 3,341 12.5 15,120 56.6 5,122 19.2 26,705 Very Good % Good % Average % Poor % No good % Total Kilosa 0 0.0 113 0.8 379 2.6 11,388 78.8 2,576 17.8 14,456 Morogoro 61 2.4 1,045 40.9 242 9.5 604 23.6 604 23.6 2,556 Kilombero 0 0.0 371 23.0 258 16.0 468 29.0 515 32.0 1,612 Ulanga 0 0.0 1,363 51.4 905 34.1 310 11.7 77 2.9 2,655 Morogoro Urban 0 0.0 24 10.7 25 10.9 104 45.9 73 32.5 226 Mvomero 127 2.7 0 0.0 377 7.9 2,636 55.4 1,620 34.0 4,760 Total 188 0.7 2,917 11.1 2,186 8.3 15,509 59.0 5,465 20.8 26,266 33.24 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center District Satisfaction of Using Livestock Development Center District Satisfaction of Using Plant Protection Lab 33.23 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Satisfaction of Using Land Registration Office 33.21 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Satisfaction of Using Research Station 33.22 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 286 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 287 District Number of rooms Iron Sheets Tiles Concrete Asbestos Grass/Leaves Grass & Mud Other Total Kilosa 3 28,621 861 386 254 28,529 14,784 0 73,435 Morogoro 3 16,296 364 122 119 33,329 2,763 122 53,117 Kilombero 3 18,291 495 258 118 29,114 382 123 48,782 Ulanga 3 7,224 75 155 0 20,941 2,512 0 30,908 Morogoro Urban 3 2,787 25 0 21 1,442 159 0 4,434 Mvomero 3 21,066 249 0 0 27,489 1,266 0 50,069 Total 3 94,284 2,070 922 512 140,845 21,867 245 260,746 Yes No Total Yes No Total Yes No Total Yes No Total Kilosa 39,605 33,830 73,435 223 73,213 73,435 1,167 72,268 73,435 10,393 63,042 73,435 Morogoro 34,074 19,043 53,117 307 52,810 53,117 961 52,156 53,117 5,583 47,534 53,117 Kilombero 28,414 20,368 48,782 123 48,659 48,782 1,055 47,727 48,782 7,865 40,917 48,782 Ulanga 16,024 14,884 30,908 77 30,832 30,908 461 30,447 30,908 4,720 26,188 30,908 Morogoro Urban 2,901 1,533 4,434 37 4,397 4,434 91 4,343 4,434 476 3,958 4,434 Mvomero 30,087 19,982 50,069 123 49,946 50,069 495 49,575 50,069 6,369 43,700 50,069 Total 151,106 109,640 260,746 889 259,857 260,746 4,230 256,516 260,746 35,406 225,340 260,746 Yes No Total Yes No Total Yes No Total Yes No Total Kilosa 4,201 69,234 73,435 29,628 43,807 73,435 455 72,980 73,435 407 73,028 73,435 Morogoro 1,293 51,824 53,117 14,879 38,238 53,117 655 52,461 53,117 942 52,175 53,117 Kilombero 2,850 45,932 48,782 25,806 22,976 48,782 744 48,039 48,782 116 48,666 48,782 Ulanga 1,382 29,526 30,908 10,696 20,212 30,908 307 30,602 30,908 228 30,680 30,908 Morogoro Urban 250 4,184 4,434 1,524 2,910 4,434 36 4,398 4,434 22 4,412 4,434 Mvomero 618 49,451 50,069 18,495 31,574 50,069 489 49,580 50,069 251 49,818 50,069 Total 10,595 250,151 260,746 101,029 159,717 260,746 2,686 258,060 260,746 1,966 258,779 260,746 Vehicle 34.1: HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District Radio Landline phone Mobile phone 34.2 HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year District cont… HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Television / Video Iron Wheelbarrow Bicycle Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 288 District Mains Electricity Solar Hurricane Lamp Pressure Lamp Wick Lamp Candles Firewood Total Kilosa 685 0 16,058 2,008 53,296 259 1,129 73,435 Morogoro 1,021 120 7,741 2,726 40,290 0 1,219 53,117 Kilombero 913 247 12,202 1,149 34,029 242 0 48,782 Ulanga 72 0 8,403 693 21,355 0 385 30,908 Morogoro Urban 44 0 1,753 99 2,488 13 37 4,434 Mvomero 245 0 12,296 4,460 32,694 126 248 50,069 Total 2,979 368 58,452 11,136 184,153 640 3,018 260,746 District Mains Electricity Solar Bottled Gas Parraffin / Kerocine Charcoal Firewood Crop Residues Livestock Dung Total Kilosa 218 130 220 130 4,596 67,635 507 0 73,435 Morogoro 245 120 122 0 2,519 50,111 0 0 53,117 Kilombero 0 255 119 328 3,304 44,156 621 0 48,782 Ulanga 78 0 78 77 1,531 28,990 77 77 30,908 Morogoro Urban 0 9 24 12 193 4,196 0 0 4,434 Mvomero 0 0 0 365 4,331 45,374 0 0 50,069 Total 541 513 562 911 16,473 240,462 1,205 77 260,746 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Other Total Kilosa 20,888 14,383 131 6,275 8,095 22,294 261 1,109 0 0 73,435 Morogoro 8,095 6,530 121 16,143 5,702 15,860 245 242 61 118 53,117 Kilombero 15,020 14,114 370 16,313 478 2,239 0 246 0 0 48,782 Ulanga 8,247 13,165 1,118 3,747 1,289 3,033 77 232 0 0 30,908 Morogoro Urban 715 184 38 594 728 1,816 36 324 0 0 4,434 Mvomero 9,009 9,074 378 8,089 8,464 14,681 0 124 252 0 50,069 Total 61,975 57,450 2,155 51,160 24,757 59,923 618 2,276 313 118 260,746 34.4 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year 34.5 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.3 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 289 District Less than 100m 100-299 m 300-499 m 500-999 m 1-1.99 Km 2-2.99 Km 3-4.99 Km 5-9.99 Km 10Km and above Total Kilosa 13,490 9,287 4,450 20,674 18,070 4,971 1,538 955 0 73,435 Morogoro 14,382 7,849 2,394 13,450 11,135 1,806 1,077 1,023 0 53,117 Kilombero 11,875 14,150 4,011 10,538 6,329 1,259 621 0 0 48,782 Ulanga 4,129 12,218 3,129 7,773 2,816 458 155 230 0 30,908 Morogoro Urban 602 1,505 276 804 853 252 95 35 12 4,434 Mvomero 12,450 8,723 2,813 10,665 10,113 3,112 1,699 370 124 50,069 Total 56,927 53,733 17,072 63,904 49,317 11,857 5,186 2,614 136 260,746 District Less than 10 10-19 Minutes 20-29 Minutes 30-39 Minutes 40-49 Minutes 50-59 Minutes above one Hour Total Kilosa 471 16,349 10,845 22,113 6,137 5,707 11,813 73,435 Morogoro 11,601 14,090 5,283 11,183 3,080 1,263 6,618 53,117 Kilombero 8,491 16,965 8,416 5,302 1,355 4,405 3,848 48,782 Ulanga 834 11,492 4,597 5,202 1,605 4,125 3,052 30,908 Morogoro Urban 573 1,026 656 907 112 425 735 4,434 Mvomero 1,599 17,421 7,926 10,308 1,367 5,515 5,934 50,069 Total 23,569 77,343 37,724 55,015 13,655 21,441 31,999 260,746 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Total HH Kilosa 22,592 16,731 516 4,983 7,724 20,263 0 500 126 73,435 Morogoro 8,812 6,533 121 14,097 5,575 16,939 123 121 795 53,117 Kilombero 15,271 14,579 370 15,344 360 2,858 0 0 0 48,782 Ulanga 8,325 10,635 1,041 6,275 1,289 3,188 0 155 0 30,908 Morogoro Urban 1,167 235 38 433 751 1,762 12 36 0 4,434 Mvomero 8,277 9,435 500 7,616 8,214 15,780 0 0 247 50,069 Total 64,444 58,148 2,587 48,749 23,913 60,790 135 812 1,168 260,746 34.6 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.7 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.8 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 290 District Less than 100m 100-299 m 300-499 m 500-999 m 1-1.99 Km 2-2.99 Km 3-4.99 Km 5-9.99 Km 10Km and above Total Kilosa 12,822 7,993 3,704 18,897 16,922 6,735 2,933 3,430 0 73,435 Morogoro 11,843 7,129 1,922 11,811 10,951 4,486 2,120 2,381 473 53,117 Kilombero 10,787 12,638 3,847 9,804 6,662 3,525 1,425 94 0 48,782 Ulanga 4,050 11,147 3,053 7,098 3,579 920 310 751 0 30,908 Morogoro Urb 412 1,421 266 787 806 279 220 119 125 4,434 Mvomero 10,014 7,985 2,322 10,924 10,456 4,108 2,669 1,466 124 50,069 Total 49,927 48,313 15,114 59,322 49,376 20,054 9,678 8,240 722 260,746 District Less than 10 Minutes 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Kilosa 728 14,727 8,296 18,596 6,867 5,590 18,631 73,435 Morogoro 10,151 11,472 4,932 8,425 4,032 1,140 12,964 53,117 Kilombero 7,523 14,546 8,670 4,746 2,025 4,530 6,742 48,782 Ulanga 835 10,670 4,589 4,275 1,455 3,902 5,181 30,908 Morogoro Urban 426 883 570 680 225 419 1,230 4,434 Mvomero 2,103 13,720 6,716 11,035 2,351 4,169 9,975 50,069 Total 21,766 66,018 33,773 47,759 16,955 19,749 54,724 260,746 District No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Kilosa 3,173 1,327 68,175 759 0 73,435 Morogoro 246 712 51,362 674 123 53,117 Kilombero 1,409 352 44,053 2,969 0 48,782 Ulanga 1,305 155 29,224 224 0 30,908 Morogoro Urban 225 20 4,139 50 0 4,434 Mvomero 617 625 47,348 1,117 362 50,069 Total 6,975 3,191 244,301 5,794 484 260,746 34.10 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34.11 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year 34.9 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro Appendix II 291 District One Two Three Four Total Kilosa 1,640 41,720 28,515 1,560 73,435 Morogoro 4,707 33,067 15,343 0 53,117 Kilombero 1,006 17,805 29,852 119 48,782 Ulanga 461 18,416 11,876 156 30,908 Morogoro Urban 134 2,068 2,232 0 4,434 Mvomero 1,252 25,650 23,167 0 50,069 Total 9,199 138,726 110,985 1,835 260,746 District Not Eaten One Two Three Four Five Six Seven Total Kilosa 22,524 21,862 22,185 4,160 1,969 259 347 129 73,435 Morogoro 17,855 18,700 10,471 5,399 477 0 111 103 53,117 Kilombero 18,585 13,421 10,400 4,634 883 735 0 125 48,782 Ulanga 15,318 9,107 3,802 2,140 309 78 154 0 30,908 Morogoro Urban 1,605 1,775 758 176 90 21 0 9 4,434 Mvomero 20,189 14,311 8,042 5,155 854 510 765 244 50,069 Total 96,077 79,176 55,659 21,664 4,581 1,603 1,377 609 260,746 District Not Eaten One Two Three Four Five Six Seven Total Kilosa 22,113 23,692 16,684 7,746 1,953 642 218 385 73,435 Morogoro 18,473 15,818 11,155 4,534 1,699 717 353 367 53,117 Kilombero 8,618 9,922 10,639 9,237 5,424 2,437 1,336 1,169 48,782 Ulanga 7,978 7,878 7,320 3,983 2,152 917 452 228 30,908 Morogoro Urban 1,302 1,238 876 525 211 163 13 106 4,434 Mvomero 21,505 9,674 8,583 5,442 3,009 1,107 502 247 50,069 Total 79,990 68,222 55,258 31,467 14,448 5,984 2,875 2,503 260,746 34.12 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year 34.13 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year 34.14 HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Morogoro 293 APPENDIX III QUESTIONNAIRES Appendix III 294 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 295 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 296 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 297 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 298 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 299 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 300 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vemen Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farmin No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 301 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 302 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 302 303 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 304 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 305 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 306 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 307 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 308 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert HerbFun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 309 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 310 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 311 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 312 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 313 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 314 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method ofMethod of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 315 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 316 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 317 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 318 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 319 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 320 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importanceConstraint Order of least importanc Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 321 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 322 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 323 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 324 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 325 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 326 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 327 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 328 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 329 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 330 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 331 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 332 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Sourcefrequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 333 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 334 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick i Main Tick if Activity carrie respo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used forused for noCheck hh -ility in activitysubsistancesubsistenceTotal (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 335 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 336 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 337 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 338 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 339 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vi: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vi: REGIONAL REPORT: MTWARA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents........................................................................................................................................................... i Acronyms..................................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive summary.................................................................................................................................................... vii Illustration.................................................................................................................................................................. xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION .................................................................................................... 1 1.1 Introduction.................................................................................................................................................... 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area ...................................................................................................................................................... 1 1.4 Climate........................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Population...................................................................................................................................................... 1 1.6 Socio-economic Indicators............................................................................................................................. 1 PART II: INTRODUCTION.................................................................................................................................. 3 2.0 Introduction.................................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture .................................................. 3 2.2 Census Objectives.......................................................................................................................................... 4 2.3 Census Coverage and Scope .......................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture.................................................................... 5 2.5 Reference Period............................................................................................................................................ 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 5 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 8 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparations............................................................................................ 10 - Data Quality............................................................................................................................. 10 2.6.12 Funding Arrangements .................................................................................................................. 10 PART III: CENSUS RESULTS AND ANALYSIS .............................................................................................. 11 3.1 Introduction................................................................................................................................................ 11 3.2 Holding Characteristics............................................................................................................................. 11 3.2.1 Type of Holdings........................................................................................................................... 11 3.2.2 Livelihood Activities/Source of Income........................................................................................ 11 3.2.3 Sex and Age of Heads of Households ........................................................................................... 11 3.2.4 Number on a Age of Household Members ................................................................................... 15 3.2.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii - Litaracy Rates for Heads of Households.................................................................................. 15 - Educational Status.................................................................................................................... 16 3.2.6 Off-farm Income............................................................................................................................ 16 3.3.1 Land Use........................................................................................................................................ 17 3.3.1.1 Area of Land Utilised .................................................................................................. 18 3.3.1.2 Types of Land use........................................................................................................ 18 3.3.2 Annual Crops and Vegetable Production....................................................................................... 18 3.3.2.1 Area Planted ................................................................................................................ 18 3.3.2.2 Crop Importance.......................................................................................................... 20 3.3.2.3 Crop Types .................................................................................................................. 20 3.3.2.4 Cereal Crop Production ............................................................................................... 21 - Maize.................................................................................................................... 23 - Sorghum ............................................................................................................... 23 - Other Cereals........................................................................................................ 24 3.3.2.5 Roots and Tuber Crops Production.............................................................................. 24 - Cassava................................................................................................................. 25 - Yams..................................................................................................................... 28 3.3.2.6 Pulse Crops Production................................................................................................ 30 Bambaranuts ................................................................................................................ 30 3.3.2.7 Oil Seed Production..................................................................................................... 31 - Groundnuts ........................................................................................................... 31 3.3.2.8 Fruits and Vegetables .................................................................................................. 32 - Tomatoes .............................................................................................................. 35 - Cabbage................................................................................................................. 35 - Chillies.................................................................................................................. 37 3.3.2.9 Other Annual Crops Production .................................................................................. 37 - Tobacco ................................................................................................................ 37 3.3.3 Permanent Crops............................................................................................................................ 39 3.3.3.1 Cashewnuts.................................................................................................................. 40 3.3.3.2 Pigeon Peas.................................................................................................................. 40 3.3.3.3 Coconuts...................................................................................................................... 43 3.3.3.4 Mango.......................................................................................................................... 43 3.3.4 Inputs/Implements Use.................................................................................................................. 43 3.3.4.1 Methods of land clearing ............................................................................................. 43 3.3.4.2 Methods of soil preparation......................................................................................... 46 3.3.4.3 Improved seeds use...................................................................................................... 46 3.3.4.4 Fertilizers use............................................................................................................... 47 - Farm Yard Manure Use ........................................................................................ 48 - Inorganic Fertilizer Use........................................................................................ 49 - Compost Use ........................................................................................................ 50 3.3.4.5 Pesticide Use................................................................................................................ 50 - Insecticide Use...................................................................................................... 51 - Herbicide Use....................................................................................................... 51 - Fungicide Use....................................................................................................... 52 3.3.4.6 Harvesting Methods..................................................................................................... 53 3.3.4.7 Threshing Methods...................................................................................................... 53 3.3.5 Irrigation........................................................................................................................................ 53 3.3.5.1 Area planted with annual crops and under irrigation................................................... 53 3.3.5.2 Sources of water used for irrigation............................................................................. 54 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.3.5.3 Methods of obtaining water for irrigation.................................................................... 56 3.3.5.4 Methods of water application ..................................................................................... 56 3.3.6 Crop Storage, Processing and Marketing ...................................................................................... 56 3.3.6.1 Crop Storage................................................................................................................ 56 - Method of Storage ................................................................................................ 57 - Duration of Storage .............................................................................................. 57 - Purpose of Storage................................................................................................ 58 - The Magnitude of Storage Loss............................................................................ 58 3.3.6.2 - Agro processing and by-products ......................................................................... 59 - Processing Methods.............................................................................................. 59 - Main Agro-processing Products ........................................................................... 59 - Main use of primary processed Products.............................................................. 60 - Outlet for Sale of Processed Products................................................................... 60 3.3.6.3 Marketing..................................................................................................................... 61 - Crop Marketing .................................................................................................... 61 - Main Marketing Problems.................................................................................... 61 - Reasons for Not Selling........................................................................................ 63 3.3.7 Access to Crop Production Services.............................................................................................. 63 3.3.7.1 Access to Agricultural Credits..................................................................................... 63 - Source of Agricultural Credits.............................................................................. 63 - Use of Agricultural Credits................................................................................... 64 - Reasons for not using agricultural credits............................................................. 64 3.3.7.2 Crop Extension ............................................................................................................ 64 - Sources of crop extension messages..................................................................... 65 - Quality of extension.............................................................................................. 65 3.3.8 Access to Inputs............................................................................................................................. 65 3.3.8.1 Inorganic Fertilizer ...................................................................................................... 66 3.3.8.2 Improved Seeds ........................................................................................................... 66 3.3.8.3 Insecticides and Fungicide........................................................................................... 67 3.3.9 Investment in Irrigation and Erosion Control Facilities................................................................. 70 3.4 Livestock Results........................................................................................................................................ 72 3.4.1 Cattle Production........................................................................................................................... 72 3.4.1.1 Population.................................................................................................................... 72 3.4.1.2 Herd size...................................................................................................................... 72 3.4.1.3 Population Trend ......................................................................................................... 74 3.4.1.4 Improved Breeds.......................................................................................................... 74 3.4.2 Goat Production............................................................................................................................. 74 3.4.2.1 Population.................................................................................................................... 74 3.4.2.2 Herd Size ..................................................................................................................... 76 3.4.2.3 Breeds.......................................................................................................................... 76 3.4.2.4 Population Trend ......................................................................................................... 76 3.4.3 Sheep Production........................................................................................................................... 76 3.4.3.1 Population.................................................................................................................... 76 3.4.3.2 Population Trend ......................................................................................................... 78 3.4.4 Pig Production ............................................................................................................................... 78 3.4.4.1 Population Trend ......................................................................................................... 78 3.4.5 Chicken Production ....................................................................................................................... 80 3.4.5.1 Population.................................................................................................................... 80 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.4.5.2 Population Trend ......................................................................................................... 80 3.4.5.3 Flock Size .................................................................................................................... 80 3.4.5.4 Improved Chicken Breeds (layers and broilers) .......................................................... 82 3.4.6 Other Livestock .............................................................................................................................. 82 3.4.7 Pests and Parasites Incidences and Control ................................................................................... 82 3.4.7.1 Deworming .................................................................................................................. 84 3.4.8 Access to Livestock Services......................................................................................................... 84 3.4.8.1 Access to livestock extension Services........................................................................ 84 3.4.8.2 Access to Veterinary Clinic......................................................................................... 84 3.4.8.3 Access to village watering points/dam ........................................................................ 85 3.4.9 Animal Contribution to Crop Production ...................................................................................... 85 3.4.9.1 Use of Draft Power ...................................................................................................... 85 3.4.9.2 Use of Farm Yard Manure........................................................................................... 86 3.4.9.3 Use of Compost ........................................................................................................... 86 3.5 Fish Farming .............................................................................................................................................. 86 3.6 Poverty Indicators...................................................................................................................................... 88 3.7 Access to Infrastructure and Other Services........................................................................................... 88 3.7.1 Type of Toilets .............................................................................................................................. 89 3.7.2 Household’s assets......................................................................................................................... 89 3.7.3 Sources of Light Energy................................................................................................................ 89 3.7.4 Sources of Energy for Cooking ..................................................................................................... 89 3.7.5 Roofing Materials.......................................................................................................................... 90 3.7.6 Access to Drink Water................................................................................................................... 90 3.7.7 Food Consumption Pattern ............................................................................................................ 92 3.7.7.1 Number of Meals per Day ........................................................................................... 92 3.7.7.2 Meat Consumption Frequencies .................................................................................. 92 3.7.7.3 Fish Consumption Frequencies.................................................................................... 92 3.7.8 Food Security................................................................................................................................. 93 3.7.9 Main Source of Cash Income ........................................................................................................ 93 PART IV: MTWARA PROFILE ........................................................................................................................... 96 4.1 Mtwara Region profile................................................................................................................................. 96 4.2 District profile.............................................................................................................................................. 98 4.2.1 Masasi............................................................................................................................................ 98 4.2.2 Mtwara Rural............................................................................................................................... 100 4.2.3 Newala......................................................................................................................................... 101 4.2.4 Tandahimba................................................................................................................................. 103 4.2.5 Mtwara Urban.............................................................................................................................. 105 ACRONYMS __________________________________________________________________________________________________ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Mtwara region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Mtwara region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings on agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Mtwara region included are activities’ indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural and related activities. i) Household Characteristics The number of agricultural households in Mtwara region was 229,314 out of which 204,241 (89.1%) were involved in growing crops only, 112 (0.0%) rearing livestock only and 24,961 (10.9%) were involved in crop production as well as livestock keeping. In summary, Mtwara region had 229,202 households involved in crop production and 25,073 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by permanent crop farming, tree/forest resources, off farm income, livestock keeping/herding, remittances and fishing/hunting & gathering. The region has a literacy rate of 62 percent. The highest literacy rate is in Masasi (73%) followed by Newala district (67%) and Mtwara Urban district (63%). Mtwara Rural and Tandahimba districts have the lowest literacy rates of 57 and 56 percent respectively. The literacy rate for the heads of households in the region was 65.6 percent. The number of heads of agricultural households with formal education in Mtwara region was 146,360 (64%), those without education were 79,566 (35%) and those with only adult education were 3,389 (1%). The majority of heads of agricultural households (61%) had primary level education whereas only 3 percent had above primary education. In Mtwara region of the households with a household member involved in off-farm income generating activities, 93,214 households (59%) had only one member involved in such activities, 41,978 (27%) had only two members involved and 21,486 (14%) more thamn two household members involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 476,196 ha. The regional average land area utilised for agricultural production per agricultural growing household was only 1.8 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 256,405 hectares out of which 481 hectares (0.2%) were planted during dry season and 255,923 hectares (99.8%) during wet season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii An estimated area of 114,309 ha (44.6% of the total planted area with annual and vegetable crops) was with roots and tubers, followed by 106,835 hectares (41.7%) of cereals, 19,849 ha (7.7%) of oils seeds and nuts, 14,171 ha (5.5%) of pulses, 949 ha (0.4%) of fruit and vegetables and cash crops were not planted in this region.. Cassava Cassava was the dominant annual crop grown in Mtwara region and it had a planted area 1.59 times greater than maize, which had the second largest planted area. The area planted with cassava constitutes 45 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were sorghum, groundnuts, paddy, bambaranuts, cowpeas and simsim. There was a sharp increase in cassava production (122%) over the period of 1997 to 1999, whereas there was a sharp decrease in cassava production (46%) over the period from 2000 to 2003. Maize The total production of maize in 2002/03 was 29,607 tonnes. The average area planted with maize per household ranged from 0.3 hectares in Mtwara Rural and Urban districts to 0.5 hectares in Masasi district. Masasi district had the largest planted area of maize (41,922 ha) followed by Newala (15,543 ha), Tandahimba (8,427 ha), Mtwara Rural (5,617 ha) and Mtwara Urban (505 ha). Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Mtwara region during the wet season was 66,919. This represented 30 percent of the total households growing annual crops in Mtwara Region in the wet season. Fruit and Vegetables The total production of fruit and vegetables was 2,123 tonnes. The most cultivated fruit and vegetable crop was tomatoes. Its production f was 1,326 tonnes, which represented 62.4 percent of the total fruit and vegetable production. It was followed by pumpkins 299 tonnes (14%) and okra 278 tonnes (13%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The smallholders planted area with permanent crops was 247,188 hectares which was equivalent to 96 percent of the area planted with annual crops in the region. The most important permanent crop was cashewnuts which accounted for 92 percent of the total area planted with permanent crops followed by pigeon peas (3%), coconuts (2%) and mangoes (1.5%). Improved Seeds The area planted using improved seeds was 7,691 ha which represented 3 percent of the total area planted area with annual crops and vegetables. The percentage use of improved seed in the wet season was the same 3 percent since improved seeds were not used in the dry season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix Use of Fertilizers Most annual crop growing households did not use any fertilisers. The planted area without fertilisers for annual crops was 236,820 hectares representing 92.4 percent of the total area planted with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 10,110 ha which represented 3.9 percent of the total planted area and (63.7 % of the area planted with fertiliser application). This was followed by inorganic fertilisers (6,792, 34.7%). Compost was used on a very small area which represented only 13.7 percent of the area applied with fertilizers. Irrigation In Mtwara region, the area of annual crops and vegetables under irrigation was 2,337 ha 1.0 percent of the total area planted. There was no area under irrigation during the dry season. Crop Storage There were 161,435 crop growing households (70% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 135,282 households storing 5,745 tonnes as of 1st January 2004. This was followed by sorghum and millet (47,730 households and 852 tonnes), beans and pulses (35,793 households and 526 tonnes), groundnuts and bambara nuts (35,613 households and 1,040 tonnes), paddy (23,989 households and 972 tonnes) and cashwnuts (1,421 households and 37 tonnes). Crop Marketing The number of households that reported selling crop was 149,163 which represents 65.0 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Newala (70%) followed by Tandahimba (69%), Mtwara Rural (66%), Masasi (61%) and Mtwara Urban (46%). Agricultural Credit In Mtwara region, few agricultural households (1,509, 0.7%) accessed credit, out of which 1,410 (93%) were male-headed households and 99 (7%) were female headed households. In Masasi, Tandahimba and Mtwara Urban districts only male- headed households accessed credit but in Newala district both male and female headed households accessed credit. There was no household that accessed credit in Mtwara rural district. Crop Extension Services The number of agricultural households that received crop extension was 40,456 (18% of total crop growing households in the region). Some districts had more access to extension services than others. Tandahimba district had a relatively high proportion of households that received crop extension messages (24%), followed by Mtwara rural (20%), Masasi (18%), Mtwara urban (12%), and Newala (8%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 1,474. This number represented 0.6 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Mtwara urban district (3%) followed by Masasi (1.3%), Newala (0.2%) and both in Tandahimba and Mtwara rural (0%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 17,158. Goats rearing was the dominant livestock type in the region followed by sheep, cattle and pigs. The region had 0.1 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 16,383 head (95.5% of the total number of cattle in the region), 775 (4.5%) were dairy breeds but there were no beef breeds. Goats The number of goat-rearing-households in the region was 32,950 (14.4% of all agricultural households) with a total of 196,675 goats giving an average of 6 heads of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 3,487 (1.5% of all agricultural households) with a total of 25,275 sheep giving an average of 7 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 3,355 (1.5% of the total agricultural households) rearing about 6,293 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 97,384, raising 710,132 chickens. This gives an average of 7 chickens per chicken-rearing household. In terms of total number of chickens in the country Mtwara ranked nineteenth out of the 21 Mainland regions. Use of Draft Power The region had no oxen at all. Fish Farming The number of households involved in fish farming was 477 (0.2 percent of the total agricultural households in the region). Masasi was the only district with 477 agricultural households involved in fish farming (0.5%). Fish farming was not practiced in other districts. iv) Poverty Indicators Availability of Toilets It was estimated that 94.0 percent of all rural agricultural households used the traditional pit latrines, 2.2 percent had flush toilets and 0.8 percent used improved pit latrine. Households with no toilet facilities accounted for 3 percent of the total agriculture households in the region. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xi Household Assets The bicycle was the asset owned by the highest percent of households (44.8% of households) followed by radios (42.6%), iron (14.0%), wheelbarrow (1.1%), vehicle (1.0%), television/video (0.5%), mobile phone (0.3%) and landline phone (0.1%). Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 69.6 percent of the agricultural households used this source of energy followed by hurricane lamp (24.5%), pressure lamp (2.7%), firewood (0.9%), mains electricity (0.8%), candle (0.4%) and biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 98.03 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (1.30%). The rest of energy sources accounted for 0.58 percent. These were crop residues (0.27%), paraffin/kerosene (0.19%), bottled gas (0.08%), mains electricity (0.08%) and solar (0.04%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 72.7 percent of the rural agricultural households however, this was closely followed by iron sheets (21.7%). Other roofing materials were grass/mud (4.2%), tiles (0.7%), asbestos (0.5%) and concrete (0.2%). Number of Meals per Day About 33.8 percent of the holders in the region took three meals per day, 57.3 percent took two meals, 8.7 percent took one meal and 0.2 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represented 33 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represented 11.4 percent whereas those with little problems represented 8.2 percent. About 6 percent of agriculture households always faced food shortages whilst 41 percent had problem in satisfying their food requirements. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 46.2 percent of the rural agricultural households. The second main cash income earning activity was cash crops (37.0%) followed by casual labour (3.8%), businesses (3.3%) and cash remittances (2.2%). Other income earning activities were sale of forest products (2.0%), employment (1.8%), fishing (1.5%), sale of livestock products (0.5%) and sale of livestock products (0.2%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.0 Census Sample Size...................................................................................................................................................6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District ..........11 3.2 Area, Production and Yield of cereal crops by Season............................................................................................21 3.3 Area planted and quantity harvested by season and type of root and tuber crop .....................................................27 3.4 Area, Quantity Harvested and Yield of Pulses by Season .......................................................................................30 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season .........................................................................31 3.6 Area, Production and Yield of Fruits and Vegetables by Season.............................................................................35 3.7 Area, Production and Yield of Annual Cash Crops by Season................................................................................35 3.9 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District – Wet Season........................................................................................................................................48 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District .................................... during the Long Rainy Season...............................................................................................................................48 3.11 Number of Households Storing Crops by Estimated Storage Loss and District.....................................................58 3.12 Reasons for Not Selling Crop Produce ....................................................................................................................63 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District........................63 3.14 Access to Inputs.......................................................................................................................................................63 3.15 Total Number of Households and Chickens Raised by Flock Size..........................................................................80 3.16 Head Number of Other Livestock by Type of Livestock and District .....................................................................82 3.17 Mean distances from holders dwellings to infrustructures and services by districts................................................88 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings .............................................................11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ...................................................11 3.3 Percentage Distribution of Population by Age and Sex in 2003..............................................................................15 3.4 Percentage Literatecy level by District ....................................................................................................................15 3.5 Literacy Rates for Heads of Household by Gender and District..............................................................................15 3.6 Percentage of Population Aged 5 years and above by District and Educational Status...........................................16 3.7 Percentage Distribution of Persons Aged 5 years and Above in Agricultural Households by Education Status.....16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ..........................................................16 3.9 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ........................................17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ........................................17 3.11 Utilized and Usable Land per Household by District ..............................................................................................17 3.12 Percentage Distribution of Land Area by Type of Land Use...................................................................................18 3.13 Total Area Planted with Annual Crops and Vegetables by Crop Types and Districts.............................................18 3.14 Area Planted with Annual Crops (ha) per Household by District............................................................................18 3.15 Area Planted with Annual Crops by Season and District.........................................................................................20 3.16 Planted Area for the Main Annual Crops (ha) .........................................................................................................20 3.17a Planted Area (ha) per Households by Selected Crop Mtwara Region .....................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type............................................................21 3.19 Area Planted and Yield of Major Cereal Crops .......................................................................................................21 3.20 Time series data on maize production......................................................................................................................23 3.21 Maize: Total Area Planted and Planted Area per Household by District.................................................................23 3.22 Time series of maize planted area and yield ............................................................................................................23 3.23 Total Planted Area and Area of Sorghum per Household by District ....................................................................24 3.24 Time Series Data on Sourghum Production MTWARA..........................................................................................24 3.25 Time Series of Sourghum Planted Area and Yield - Mtwara...................................................................................24 3.26 Area Planted with Paddy, Fingermillet and Bulrush Millet by district ..................................................................24 3.27 Area Planted and Yield of MajorRoot and Tuber crops ..........................................................................................24 3.28 Area Planted with Cassava during the Census/Survey Years .................................................................................27 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District .......................................28 3.30 Cassava Planted Area per Cassava Growing Households by District......................................................................28 3.31 Total Area Planted with Yams and Planted Area per Household by District .........................................................28 3.32 Area Planted and Yield of Major Pulse Crops ........................................................................................................30 3.33 Percent of Bean Planted Area and Percent of Total Land with Bambaranuts by District .......................................30 3.34 Area Planted per Bambaranuts Growing Household by District (Wet Season Only) .............................................30 3.37 Area Planted and yield of major oil Seed Crops......................................................................................................31 3.38 Time Seried Data on Groungnuts Planted area - Mtwara .......................................................................................31 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District................................32 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.40 Area Planted per Groundnut Growing Households by District (Wet Season Only) ................................................32 3.42 Area Planted and Yield of Fruit and Vegetables......................................................................................................32 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ............................................35 3.45 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District ....................................37 3.46 Percent of Okra Planted Area and Percent of Total Land with Okra by District .....................................................37 3.47 Area planted with Annual Cash Crops.....................................................................................................................37 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District..........................................37 3.49 Area Planted for Annual and Permanent Crops .......................................................................................................39 3.50 Area Planted with the Main Permanent Crop ..........................................................................................................39 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District ........................................39 3.52 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District .......................40 3.53 Percent of Area Planted with Pigeon Pea and Average Planted Area per Household by District ...........................40 3.54 Percent of Area Planted with Coconuts andAverage Planted Area per Household by District ..............................43 3.56 Number of Households by Method of Land Clearing during the Wet Season ........................................................43 3.57 Area Cultivated by Cultivation Method...................................................................................................................46 3.58 Area Cultivated by Method of Cultivation and District ..........................................................................................46 3.59 Planted Area of Improved Seeds .............................................................................................................................46 3.60 Planted Area with Improved Seed by Crop Type ...................................................................................................47 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals .................................................................47 3.62 Area of Fertiliser Application by Type of Fertiliser ................................................................................................47 3.63 Area of Fertiliser Application by Type of Fertiliser and District ...........................................................................47 3.64 Planted Area with Farm Yard Manure by Crop Type - MTWARA.........................................................................48 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals............................................................48 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - MTWARA .......................................49 3.66 Planted Area with Inorganic Fertilizer by Crop Type - MTWARA ........................................................................49 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - MTWARA ...............................................49 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - MTWARA ........................................49 3.68 Planted Area with Compost by Crop Type - MTWARA ...................................................................................50 3.68c Proportion of Planted Area Applied with Compost by District - MTWARA ........................................................50 3.69 Planted Area (ha) by Pesticide Use..........................................................................................................................50 3.69b Percentage of Planted Area with Compost by Crop Type- ..................................................................................50 3.70 Planted Area applied with Insecticides by Crop Type.............................................................................................51 3.71 Percentage of Crop Type Planted Area applied with Insecticides ...........................................................................51 3.72 Percentage of Planted Area applied with Insecticides by District -MTWARA .......................................................51 3.73 Planted Area applied with Herbicides by Crop Type...............................................................................................51 3.74 Percentage of Crop Type Planted Area Applied with Herdicides............................................................................52 3.75 Proportion Area Applied with Herbicides by District - MTWARA ........................................................................52 3.76 Planted Area Applied with Fingicides by Crop Type .............................................................................................52 3.77 Percentage of Crops Type Planted Area Applioed with Fingicides.........................................................................52 3.78 Proportion of Planted Area with Fingicides by District - MTWARA......................................................................53 3.79 Area of Irrigated Land .............................................................................................................................................53 3.80 Planted Area with Irrigation by District -TANGA Region......................................................................................54 3.81 Time Series of Households with Irrigation - MTWARA.........................................................................................54 3.82 Number of Households with Irrigation gy Source of Water ....................................................................................54 3.83 Number of Households by Method of obtaining Irrigation Water...........................................................................56 3.84 Number of Households by Method of Field Application.........................................................................................56 3.85 Number of Households and Quantity Stored by Crop Type - MTWARA...............................................................56 3.86 Number of Households by Stored Methods - MTWARA........................................................................................57 3.87 Number of Households by Methods of Storage and District (based on the most important household crop) ........57 3.88 Nomal Lengh of Storage for Selected Crops ...........................................................................................................57 3.89 Quantity of Maize Produced (tonnes), Stored and Percent stored by District..........................................................58 3.90 Number of Households by Purpose of Storage and Crop Type ...............................................................................58 3.91a Households Processing Crops..................................................................................................................................59 3.91b Percentage of Households Processing Crops by District .........................................................................................59 3.92 Percentage of Crops Processing Households by Method of Processing ..................................................................59 3.93 Percentage of Householda by Type of Main Processed Product.............................................................................59 3.94 Number of Households by Type of By- Product .....................................................................................................60 3.95 Use of Processed Product.........................................................................................................................................60 3.96 Percentage of Households Selling Processed Crops by District ..............................................................................60 3.97 Location of Sale of Processed Products...................................................................................................................60 3.98 Percent of Household Selling Processed Products by Outlet Sell and District ........................................................61 3.99 Number of Crop Growing Households Selling Crops By District...........................................................................61 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.100 Percentage Distribution of Househoulds that Reported Marketing Problems by Type of Problem.........................61 3.101 Percentage Distribution of Househoulds Receiving Credit by Main Source ...........................................................63 3.102 Number of Households Receiving Credit by Main Source of Credit and District...................................................63 3.103 Proportion of Households Receiving Credit by Purpose of the Credit ....................................................................64 3.104 Reasons for not using (% of households).................................................................................................................64 3.105 Number of Households Receiving Extension Advice.............................................................................................64 3.106 Number of Households Receiving Extension by District .......................................................................................64 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider......................................65 3.108 Number of Households Receiving Extension by Quality of Services.....................................................................66 3.109 Number of Households by Source of Inorganic Fertiliser .....................................................................................65 3.110 Percent of Household Reporting Distance to Source of Inorganic Fertiliser ..........................................................66 3.111 Number of Households by Source of Improved Seed...........................................................................................66 3.112 Percentage of Househoulds Reporting Distance to Source of Improved Seed.......................................................67 3.113 Percentage of Househoulds Reporting Distance to Source of Insecticides/ Fungicide...........................................67 3.114 Number of Improved Chicken by Breed Type and District Insecticides/ Fungicides.............................................67 3.115 Number of Households with Planted Trees .............................................................................................................67 3.116 Number of Planted Trees by Species - MTWARA..................................................................................................69 3.117 Number of Trees Planted smallholders by Species and Districts ..........................................................................69 3.118 Number of Trees Planted By Location.....................................................................................................................69 3.119 Percentage of Households by Purpose of Planted Trees.........................................................................................69 3.120 Number of Households with Erosion Control / Water Harvesting Facilities...........................................................70 3.121 Number of Households with Erosion Control / Water Harvesting Facilities...........................................................70 3.122 Number of Erosion Control / Water Harvesting Structures by Type of Facility....................................................70 3.123 Total Number of Cattle ( 000 ) by District ...........................................................................................................72 3.124 Number of cattle by Type and District.....................................................................................................................72 3.125 Cattle Population Trend...........................................................................................................................................74 3.126 Dairy Cattle Population Trend ...............................................................................................................................74 3.127 Total Number of Goats ( 000 ) by District ............................................................................................................74 3.128 Goats Population Trend ...........................................................................................................................................76 3.129 Total Number of Sheep by District .......................................................................................................................76 3.130 Sheep Population Trend...........................................................................................................................................78 3.131 Total Number of Pigs by District.............................................................................................................................78 3.132 Pig Population Trend ...............................................................................................................................................78 3.133 Totol Number Of Chickens by District....................................................................................................................80 3.134 Chicken Population Trend .......................................................................................................................................80 3.135 Number of improved Chicken by Type and District ..............................................................................................82 3.136 Layers Population Trend..........................................................................................................................................82 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problem by District.......................82 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District...................84 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ...............84 3.140 Number of Households by Distance to Verterinary clinic .......................................................................................85 3.141 Number of Households by Distance to Verterinary clinic and District....................................................................85 3.142 Number of Households by Distance to Village Watering Points............................................................................85 3.143 Number of Households by Distance to Village Watering Point and District..........................................................85 3.144 Number of HouseholdsUsing Draft Animals...........................................................................................................85 3.145 Number of HouseholdsUsing Draft Animals by District - MTWARA....................................................................85 3.146 Number of HouseholdsUsing Organic Fertiliser......................................................................................................86 3.147 Area of Application of Organic Fertiliser by District MTWARA ...........................................................................86 3.148 Number of Households Practicing Fish Farming - MTWARA ..............................................................................86 3.149 Number of Households Practicing Fish Farming - Mtwara ....................................................................................88 3.150 Fish Production .......................................................................................................................................................88 3.151 Agricultural Households by Type of Toilet Facility ................................................................................................89 3.152 Percentage Distribution of Households Owning the Assets.....................................................................................89 3.153 Percentage Distribution of Households Main Source of Energy for Lighting .........................................................89 3.154 Percentage Distribution of Households Main Source of Energy for cooking..........................................................89 3.155 Percentage Distribution of Households by Type of Roofing Material.....................................................................90 3.156 Percentage Distribution of Households by Type of Roofing Material.....................................................................90 3.157 Percentage Distribution of Households with Grassy/ Leafy Roofs by District........................................................90 3.158 Percentage Distribution of Households by Main Source of Drinking Water and season.........................................90 3.159 Number of Agriculture Households By Number of Meals per day..........................................................................92 3.160 Number of Agriculture Households by Frequency of Meal and Fish Cosumption..................................................92 3.161 Percentage Distribution of the Number of Households by Main Source of Income...............................................93 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv List of Maps 3.1 Total Number of Agricultural Households by District.............................................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District................................................................12 3.3 Number of Crop Growing Households by District ..................................................................................................13 3.4 Percent of Crop Growing Households by District ...................................................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District..................................................14 3.6 Percent of Crop and Livestock Households by District ...........................................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land ...............................................................................19 3.8 Total Planted Area (annual crops) by District..........................................................................................................19 3.9 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District..........................................22 3.10 Planted Area and Yield of Maize by District...........................................................................................................25 3.11 Area Planted per Maize Growing Household ..........................................................................................................25 3.12 Planted Area and Yield of Sorghum by District ......................................................................................................26 3.13 Area Planted per Sorghum Growing Household......................................................................................................26 3.14 Planted Area and Yield of Cassava by District........................................................................................................29 3.15 Area Planted per Cassava Growing Household .......................................................................................................29 3.16 Planted Area and Yield of Beans by District ...........................................................................................................33 3.17 Area Planted per Maize Growing Household ..........................................................................................................33 3.18 Planted Area and Yield of Groundnuts by District ..................................................................................................34 3.19 Area Planted per Groundnuts Growing Household..................................................................................................34 3.20 Area Planted per Tomatoes Growing Household.....................................................................................................36 3.21 Planted Area and Yield of Cabbage by District.......................................................................................................36 3.22 Planted Area and Yield of Tobbaco by District.......................................................................................................38 3.23 Area Planted per Tobacco Growing Household.......................................................................................................38 3.24 Planted Area and Yield of Cashewnut by District ...................................................................................................41 3.25 Area Planted per Cashewnut Growing Household...................................................................................................41 3.26 Planted Area and Yield of Pigeon Peas by District..................................................................................................42 3.27 Area Planted per Pigeon Peas Growing Household.................................................................................................42 3.28 Planted Area and Yield of Coconuts by District......................................................................................................44 3.29 Area Planted per Coconuts Growing Household .....................................................................................................44 3.30 Planted Area and Yield of Mango by District..........................................................................................................45 3.31 Area Planted per Mango Growing Household.........................................................................................................45 3.32 Planted Area and Percent of Planted Area with No Application of Fertilizer by District........................................55 3.33 Area Planted and Percent of Total Planted Area with Irrigation by District............................................................55 3.34 Percent of households storing crops for 3 to 6 months by district ...........................................................................62 3.35 Number of Households and Percent of Total Households Selling Crops by District...............................................62 3.36 Number of Households and Percent of Total Households Receiving Crop Extension Services by District............68 3.37 Number and percent of crop growing households using improved seeds by district...............................................68 3.38 Number and percent of smallholder planted trees by district...................................................................................71 3.39 Number and percent of households with water harvesting bunds by district...........................................................71 3.40 Cattle population by District as of 1st Octobers 2003 .............................................................................................73 3.41 Cattle Density by District as of 1st October 2003....................................................................................................73 3.42 Goat population by District as of 1st Octobers 2003 ...............................................................................................75 3.43 Goat Density by District as of 1st October 2003 .....................................................................................................75 3.44 Sheep population by District as of 1st Octobers 2003 .............................................................................................77 3.45 Sheep Density by District as of 1st October 2003 ...................................................................................................77 3.46 Pig population by District as of 1st Octobers 2003..................................................................................................79 3.47 Pig Density by District as of 1st October 2003........................................................................................................79 3.48 Number of Chicken by District as of 1st October 2003...........................................................................................81 3.49 Density of Chicken by District as of 1st October 2003............................................................................................81 3.50 Number and percent of households Infected by with Tsetseby by district...............................................................83 3.51 Planted Area and Percent of Planted Area with Farm Yard Manure Application by District .................................87 3.52 Planted Area and Percent of Planted Area with Compost application by District.................................................. 87 3.53 Number and Percent of Households Without Toilets by District ...........................................................................91 3.54 Number and Percent of Households Using Iron Sheets for Roofing Material by District ......................................91 3.55 Number and Percent of Households Eating 3 Meals per Day by District ...............................................................94 3.56 Number and Percent of Households Eating Meat Once per Week by District .......................................................94 3.57 Number and Percent of Households Eating Fish Once per Week by District .........................................................95 3.58 Number and Percent of Households Reporting Food Insufficiency by District .....................................................95 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on the geographical location, land area, climate, administrative set up, population and the socio-economic situation. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Mtwara region is situated at the Southern-East corner of Tanzania between 100 and 110degrees below the Equartor and 380 – 40030’ degrees East of the Greenwich Meridian. Mtwara shares borders with Lindi region to the North, the Indian Ocean, to the east and the southern boundary is the great Ruvuma River, which separates Tanzania from the Republic of Mozambique and Ruvuma region to the west. . The region comprises five districts namely Mtwara Rural, Newala, Masasi, Tandahimba and Mtwara Urban. The region headquarters is located in the Mtwara Urban District. 1.3 Land Area The region has an area of 16,720 square kilometers, it accounts for 1.9% of the total area of Tanzania Mainland, which is 885,978 square kilometers. 1.4.0 Climate The region receives only the long rains which normally start from November/December to April/may. This is the wet rainy (Masika) season. 1.4.1 Temperature The dominant climate is warm and wet. The mean annual maximum temperature in the region varies between 230C during July and 270C during December. 1.5 Population According to the 2002 Population and Housing Census, there were 1,128,523 inhabitants in Mtwara region. The population of Mtwara region ranked 16th of the 21 regions on Tanzania Mainland.. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 292,085 million with a per capita income of shillings 255,860. The region held 17th position among regions on GDP and contributed about 3.0 percent to the national GDP1 Mtwara region has agriculture as its main economic activity, employing about 90% of the economically active population. It has variety of tourist attractions, which include; virgin beaches on a 125 – kilometer coastline, scenic Msimbati bay, the Mikindani historical old town and Monuments. The Game reserves are Msanjesi and Lukwisa/Lumese, which are rich in a variety of wildlife species. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 The region is famous for producing both food and cash crops. The main food crops produced in Mtwara region include: maize, paddy, cassava and sorghum. The main cash crop is tobacco. Livestock keeping is also an important economic activity in the region. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census for Mtwara region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Mtwara region was 229,314. The largest number of agriculture households was in Masasi (96,421) followed by Mtwara rural (45,154), Newala (43,065), Tandahimba (41,823) and Mtwara urban (2,850) (Map 3.1). The highest density of households was found in Mtwara urban (1,668/km2) followed by Newala (67/km2) (Map 3.2). Most households (204,241, 89.1%) were involved in growing crops only, 112 (0.0%) rearing livestock only and 24,961 (10.9%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Mtwara region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by permanent crop farming, tree/forest resources, off-farm income, livestock keeping/herding, remittances and fishing/hunting & gathering (Table 3.1). 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Mtwara region was 175,579 (76.6% of the total regional agricultural households) whilst the female- headed households it were 53,735 (23.4% of the total regional agricultural households). The mean age of household heads was 45 years (44 years for male heads and 50 years for female heads) (Chart 3.2). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittan ces Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 1 4 5 3 6 7 2 Newala 1 3 4 5 6 7 2 Masasi 1 3 5 4 6 7 2 Tandahimba 1 2 3 4 5 7 6 Mtwara Urban 2 4 5 3 6 7 1 Total 1 2 5 4 6 7 3 Chart 3.1 Agriculture Households by Type - Mtwara Crops Only 89.1% Livestock Only 0.0% Crops and Livestock 10.9% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Tandahimba Newala Mtwara Rural Mtwara Urban 49 69 32 24 49 Masasi 56 to 70 42 to 56 28 to 42 14 to 28 0 to 14 Mtwara Urban Mtwara Rural Tandahimba Newala 96,421 2,850 45,154 41,823 43,065 Masasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Agricultural Households Per Square Km of Land by District MAP 3.01 MTWARA MAP 3.02 MTWARA Total Number of Agricultural Households by District Tanzania Agriculture Sample Census Number of Agricultural Households Per Square Km Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km RESULTS 12 Mtwara Urban Mtwara Rural Tandahimba Newala 85.8% 90.6% 83.4% 82.6% 93.8% Masasi 90 to 94 88 to 90 86 to 88 84 to 86 82 to 84 Mtwara Urban Mtwara Rural Tandahimba Newala 2,446 40,908 34,886 35,560 90,441 Masasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Percent of Crop Growing Households by District MAP 3.03 MTWARA MAP 3.04 MTWARA Number of Crop Growing Households by District Tanzania Agriculture Sample Census Percent of Crop Growing Households Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households RESULTS 13 Newala Mtwara Urban Mtwara Rural Tandahimba 17% 13% 9% 16% 6% Masasi 16 to 20 12 to 16 8 to 12 4 to 8 0 to 4 Mtwara Urban Mtwara Rural Tandahimba Newala 42 29 41 57 23 Masasi 40 > 30 to 40 20 to 30 10 to 20 0 to 10 Percent of Crop and Livestock Households by District MAP 3.05 MTWARA MAP 3.06 MTWARA Number of Crop Growing Households per Square Kilometer of Land by District Tanzania Agriculture Sample Census Percent of Crop and Livestock Households Number of Crop Growing Households per Square Kilometer Number of Crop Growing Households per Square Kilometer Percent of Crop and Livestock Households RESULTS 14 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households by the sex of the household head. 3.1.4 Number and Age of Household Members Mtwara region had a total rural agricultural population 928,521 of which 448,169 (48%) were males and 480,353 (52%) were females. Whereas age group 0-14 was constituted 39 percent of the total rural agricultural population, age group 15–64 (active population) was only 56 percent. Mtwara region had an average household size of 4.0 with Newala district having the lowest household size of 3.7 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Mtwara region had a total literacy rate of 62 percent. The highest literacy rate was found in Newala district (67%) followed by Masasi district (66%). Mtwara rural, Tandahimba and Mtwara urban had the lowest literacy rates of 55, 57 and 58 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 66 percent. The literacy rate for the male heads was 73 percent and that of female heads was 42 percent. and female heads of households were 60 and 85 percent respectively. The literacy rate of male heads was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Mtwara Urban (78.6%) followed by Masasi (77.2%), Newala (Mtwara Rural (76.4%), and Tandahimba (74.8%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex -MTWARA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literatecy Level of Household Members by District - 20 40 60 80 Masasi Newala Mtwara Urb Tandahimba Mtwara Rur District Percent Chart 3.5 Literacy Rates of Heads of Household by Sex and District MTWARA 0.0 25.0 50.0 75.0 100.0 Mtwara Urban Masasi Newala Mtwara Rural Tandahimba District Percent Male Female Total RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 42 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 25 percent were still attending school. Those who had never attended school were 33 percent (Chart 3.6). Agricultural households in Masasi district had the highest percentage (47%) of population aged 5 years and above who had completed various levels of education. This was followed by Newala 46 percent, Tandahimba districts 39 percent, Mtwara urban district 38 percent, the last district is Mtwara rural with 34 percent (Chart 3.7). The number of heads of agricultural households with formal education in Mtwara region was 146,360 (64%), those without education were 79,566 (35%) and those with only adult education were 3,389 (1%). The majority of heads of agricultural households (61%) had primary level education whereas only 3 percent had above primary education. With regard to the heads of agricultural households with primary or secondary education in Mtwara region, Masasi district had the highest percentages (49% for primary and 47% for secondary). This was followed by Newala (20% primary and 13% secondary), Mtwara rural (15% primary and 22% secondary) and Tandahimba (15% primary and 16% secondary). Mtwara urban had the lowest percentage of heads of agricultural households with both primary education (1%) and secondary education (2%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or laborers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Mtwara with 68 percent of households having at least one member with off-farm income. In the agricultural household more than two members involved in off-farm income generating activities 93,214 households (41%) had only one member aged 5 and Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Never Attended 33% Attending School 25% Completed 42% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Masasi Newala Tandahimba Mtwara Urban Mtwara Rural District Percent Attending School Completed % Never Attended % Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education, 1.5% Post Primary Education, 0.4% No Education, 35% Primary Education, 61% RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 above involved in only one off-farm income generating activity and 41,978 households (18%) had two members involved in off-farm income generating activities. Mtwara Urbarn district had the highest percentage of agriculture households with off-farm income (over 80% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Newala (84%) and Mtwara Rural (79%). Masasi and Tandahimba districts had the lowest percent of agriculture households with off-farm income (67%) % and 41% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Masasi (36%). Tandahimba district had very few households with more than one member having off-farm income (8%). 3.3.1 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country, but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. Chart 3.11 Utilized and Usable Land per Household by District 0.0 0.5 1.0 1.5 2.0 2.5 Tandahimba Mtwara Rural Masasi Newala Mtwara Urban District Area/household 0 20 40 60 80 100 120 Percentage Utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Masasi Newala Mtwara Urban Mtwara Rural Tandahimba District P ercen ra g e More than Two Two One None Chart 3.9 Number of Households by Number with Off-farm Income One, 93,214 , 41% None, 72636, 32% Two, 41,978 , 18% More than Two, 21,486 , 9% RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 3.3.1.1 Area of Land Utilised The total area of land available to smallholders was 476,196 ha. The regional average land area utilised for agriculture per household was only 1.8 ha. This figure is below the national average which is estimated at 2.0 hectares. Eighty eight percent of the total land available to smallholders was utilised. Only 12 percent of the land available to smallholders was not used (Chart 3.11 and Map 3.7). Large differences in land area utilised per household exist between districts with Masasi and Tandahimba utilizing between 2.0 and 2.0 ha per household. The smallest land area utilised per household was found in Mtwara Urban (1.6 ha). The percentage utilized of the usable land per household was highest in Masasi (96%) and lowest in Mtwara Rural (84%). 3.3.1.2 Types of Land Use The area of land under temporary mixed crops was 136,667 hectares (28.7% of the total land available to smallholders in Mtwara), followed by permanent mono crops (105,477 ha, 22.1%), permanent/annual mix (98,209 ha, 20.6%), temporary mono crops (63,675 ha, 13.4%), uncultivatable usable land (34,159 ha, 7.2%), permanent mixed crop (11,863 ha, 2.5%), area under fallow (11,536 ha, 2.4%), area under natural bush (6,356 ha, 1.3%), unusable area (4,543 ha, 1.0%), area rented to others (2,280 ha, 0.5%), area under pasture (1,027 ha, 0.2%) and area planted with trees (403 ha, 0.1%). 3.3.2 Annual Crop and Vegetable Production Mtwara region has two seasons, namely the dry season (October to November) and the wet season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.2.1 Area Planted The area planted with annual crops and vegetables was 256,404 hectares out of which 482 hectares (0.2%) were planted during dry season and 255,923 hectares (99.8%) during wet season. The average areas planted per household during the dry and wet seasons were 1.7 and 1.1 ha respectively. The districts with the largest area planted per household (the average of the two seasons) were Masasi (1.21 ha) followed by Newala (1.18 ha). The district with the smallest average area planted was Mtwara Rural (0.89 ha). The average area planted during the wet season is higher than that of the dry season in all districts (Chart 3.14 and Map 3.8). Chart 3.12 Land Area by Type of Use 0.1 0.2 0.5 1.0 1.3 2.4 2.5 7.2 13.4 20.6 28.7 22.1 - 50,000 100,000 150,000 Planted Trees Pasture Rented to Others Unusable Natural Bush Fallow Permanent Mixed Crops Uncultivated Usable Land Temporary Mono Crops Permanent / Annual Mix Permanent Mono Crops Temporary Mixed Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (hectares) Wet Season, 255,923, 100% Dry Season, 482, 0% Wet Season Dry Season 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 Mtwara Rural Newala Masasi Tandahimba Mtwara Urban District A r e a P l a te d (H a ) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 P e r c e n ta g e P la n te d Dry Season Wet Season % Area Planted in Dry Season Mtwara Urban Mtwara Rural Tandahimba Newala 2,878 40,290 45,400 50,805 117,031 Masasi 80,000 > 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Mtwara Urban Mtwara Rural Tandahimba Newala 90.2% 81.7% 88.2% 90.8% 95.9% Masasi 92.9 > 90.1 to 92.9 87.3 to 90.1 84.5 to 87.3 81.7 to 84.5 Total Planted Area Annual Crops by District MAP 3.07 MTWARA MAP 3.08 MTWARA Utilized Land Area Expressed as a Percent of Available Land by District Tanzania Agriculture Sample Census Planted Area Annual Crops Percent of Utilized Land Percent of Utilized Land Planted Area Annual Crops RESULTS 19 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 The planted area occupied by roots and tubers was 114,309 ha (44.6% of the total area planted with annuals). This was followed by cereals (106,835 hectares, 41.7%), oil seeds and oil nuts (19,849 hectares, 7.7%), pulses (14,171 hectares, 5.5%), fruit and vegetables (949 hectares, 0.4%), and cash crops (291 hectares, 0.1%). The average area planted per household during the wet season in Mtwara region was 1.1 hectares, however, there were large district differences. Newala had the largest planted area per household (2.4 ha) followed by Tandahimba (2.1 ha) The smallest planted area per household was for Mtwara rural (1.1 ha), Masasi and Mtwara urban 0.5 each. In Newala the area planted per household in the dry season represented 0.38 percent of the total planted area per household, whereas in Masasi and Mtwara urban the corresponding figure were 0.0 percent per each (Chart 3.15). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2.2 Crop Importance Cassava was the dominant annual crop grown in Mtwara region and it had a planted area 1.59 times greater than maize, which had the second largest planted area. The area planted with cassava constituted 45% percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) were sorghum, groundnuts, paddy, bambaranuts and cowpeas (Chart 3.16). Households that grew pigeon peas, tobacco and cassava had larger planted areas per household than for other crops (Chart 3.17a). 3.3.2.3 Crop Types Roots and tubers were the main crops grown in Mtwara region. The area planted with roots and tubers was 114,309 ha (44.6% of the total planted area), followed by cereals with 106,835 ha (41.7%), oil seeds and oil nuts 19,849 ha (17.7%), Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 1.00 2.00 3.00 Mtwara Rural Newala Masasi Tandahimba Mtwara Urb District Area Planted (ha) Wet Season Dry Season Chart 3.16 Planted Area (ha) for the Main Crops Mtwara -50,000 50,000 150,000 Cassava Maize Sorghum Groundnuts Paddy Bambaranuts Cowpeas Simsim Green Gram Tomatoes Beans Finger Millet Pigeon Peas Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - MTWARA 0.00 0.50 1.00 Pigeon Peas Tobacco Cassava Chillies Maize Paddy Beans Groundnuts Simsim Sorghum Tomatoes Bambaranuts Green Gram Cowpeas Finger Millet Onions Pumpkins Crop Planted Area (ha) RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 pulses 14,171 ha (15.5%), fruits and vegetables 949 ha (0.4%) and cash crops 291 ha (0.1%). Tobacco with an area of about 291 ha (0.1%) was the only annual cash crop grown in the region (Chart 3.17b). Roots/tubers and cereals were the dominant crops in both seasons. Other crop types are of minor importance in comparison. There was little difference in the proportions of the different crop types grown between seasons and the because dry season’s production was very small compared to the wet season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.2.4 Cereal Crop Production The total production of cereals was 39,730 tonnes. Maize was the dominant cereal crop with a proportion of 29,607 tonnes which was 75 percent of total cereal crops produced, followed by sorghum (13%) paddy (12%), finger millet and bulrush millet (0.18% each). Masasi district had the largest planted area of Cereals in the region (54,483 ha) followed by Newala, (21,541ha), Tandahimba (15,371ha), Mtwara rural (14,622ha) and Mtwara urban (818ha) (Map 3.9). The total area planted with cereals during the year was 106,835 ha out of which 272 ha (0.25%) were planted in dry season and 106,563 ha (99.75%) were planted during the wet season. The wet season accounted for 99.8 percent of the total cereals produced in both seasons. The area planted with maize during the dry season was 100 percent of the total area planted with cereals in that season. (Table 3.2). The area planted with maize was dominant and it represented 67.4 percent of the total area planted with cereal crops, then followed by sorghum (19.3%), paddy (13.1), finger millet (0.2) and bulrush millet (0.03). Wheat and barley were not grown in the region. (Chart 3.19). The yield of bulrush was 2,223 kg/ha, followed by maize (411 kg/ha), finger millet (361 kg/ha), paddy (352 kg/ha) and sorghum (245 kg/ha) (Chart 3.19). Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 272 94 345 71,743 29,512 411 72,015 29,607 411 Paddy 0 0 0 14,018 4,932 352 14,018 4,932 352 Sorghum 0 0 0 20,569 5,048 245 20,569 5,048 245 Bulrush Millet 0 0 0 32 71 2,223 32 71 2,223 Finger Millet 0 0 0 201 73 361 201 73 361 Wheat 0 0 0 0 0 0 0 0 0 Barley 0 0 0 0 0 0 0 0 0 Total 272 94 106,563 39,635 106,835 39,730 Chart 3.17b: Percentage Distribution of Area planted with Annual Crops by Crop Type Fruits & Vegetables 0% Pulses 6% Oil seeds & Oil Nuts 8% Cash Crops 0% Roots & Tubers 44% Cereals 42% Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 25,000 50,000 75,000 Maize Sorghum Paddy Finger Millet Bulrush Millet Barley Crop Area Planted (ha) 0.00 1.00 2.00 3.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Newala Mtwara Rural Mtwara Urban Tandahimba 15,371 21,541 54,483 14,622 818 33.9% 42.4% 46.6% 36.3% 28.4% Masasi 44,000 to 55,000 33,000 to 44,000 22,000 to 33,000 11,000 to 22,000 0 to 11,000 MAP 3.09 MTWARA Area Planted with Cereals Crops and Percent of Total Land Planted with Cereals Crops by District Tanzania Agriculture Sample Census Area Planted with Cereals Crops Area Planted with Cereals Crops Percent of Area Planted with Cereals Crops RESULTS 22 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.2.4.1 Maize Maize dominated the production of cereal crops in the region. The number of households growing maize in Mtwara region during the wet season was 163,573, (72% of the total household growing annual crops in the region during the wet season). The total production of maize was 29,607 tonnes from a planted area of 72,015 hectares resulting in a yield of 0.4 t/ha. Chart 3.20 shows the maize production (in thousand metric tones) for the combined wet and dry seasons. There was a47 percent increase in maize production in 1995 to 1996 after which the production dropped sharply in 1997. The average area planted with maize per household was 0.44 hectares, however it ranged from 0.3 hectares in Mtwara rural and Mtwara urban district to 0.5 hectares in Masasi district (Map 3.11). Masasi district had the largest area of maize (41,922 ha) followed by Newala (15,543 ha), Tandahimba (8,427 ha), Mtwara rural (5,617 ha) and Mtwara urban (505 ha) (Chart 3.21 and Map 3.10). Charts 3.20 and 3.22 show that, the yield of maize as well as production dropped sharply from the year 1996 to 1997, inspite of the increase in the area under production. The area planted with maize remained constant over the period from 1998 to 1999 but it had decreased by the year 2002/03. The yield of maize increased (from 0.5t/ha in 1997 to 0.4 t/ha in 2003) (Chart 3.22). 3.3.2.4.2 Sorghum Sorghum was the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Mtwara region during the wet season was 66,919. This represented 30 percent of the total household growing annual crops in Mtwara region in the wet season. The total production of sorghum was 5,048 tonnes from a planted area of 20,569 hectares resulting in a yield of 0.25t/ha. The district with the largest area planted with sourghum was Masasi (6,524 ha) followed by Mtwara rural (4,741 ha), Newala (4,570 ha), Tandahimba (4,457 ha), and Mtwara urban (276 ha) (Map 3.12). There were small insignificant variations in the average area planted per crop growing household among the districts ranging from 0.25 ha in Newala to 0.41 ha in Masasi (Chart 3.23 and Map 3.13). Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 41,922 15,543 8,427 5,617 505 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 Masasi Newala Tandahimba Mtwara Rur Mtwara Urb District Area (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.20: Time Series Data on Maize Production - MTWARA 29 94 64 47 47 39 0 100 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.22 Time Series of Maize Pla ted Area & Yield - MTWARA - 20,000 40,000 60,000 80,000 100,000 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year A r e a (H e c ta r e s ) 0 0.5 1 1.5 2 2.5 3 Y i e l d (t/ h a ) Area Yield RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 24 There was a rise in the production of sorghum in 1996/97 compared to 1995/96. The production rose from 2,000 tons in 1995/96 to 8,000 tones in 1996/97 after which it increased further to 20,000 tones in 1997/98. Thereafter the production increased slightly to 21,000 tones in 1998/1999, followed by a sharp decline to 12 tones in and 5, 000 tones in 2002/03. Charts 3.24 and 3.25 show that, the yield of sorghum has dropped dramatically over the previous 8 years, but the area planted increased. The area planted with sorghum increased over the period 1995 to 1997 after which it declined slightly by the year 2000. There was a sharp decline in the yield for the period from 1994 to 1995 (down to 1.0 t/ha) and it has remained at this low level since then (Chart 3.25). 3.3.2.4. 3 Other Cereals Other cereals were produced in small quantities. A small quantity of paddy was produced in Masasi (5,914 ha), followed by Mtwara rural (4,264 ha), Tandahimba (2,419 ha), Newala (1,385 ha) and Mtwara urban (36 ha). Fingermillet was produced in Masasi district (90 ha), Tandahimba (68 ha) and Newala (43 ha). Bulrush Millet was produced in Masasi district only (32 ha) (Chart 3.26). 3.3.2. 5 Roots and Tuber Crops Production The total production of roots and tubers was 72,274 tonnes. Cassava production the highest for roots and tuber crops in the region with a total production of 72,087 tonnes representing 99.7 percent of the total root and tuber crops production. This was followed by yams with 78 tonnes 0 1,000 2,000 3,000 4,000 5,000 6,000 Area (Ha) Masasi Mtwara Rur Tandahimba Newala Mtwara Urb District Chart 3.26 Area Planted with Paddy, Fingermillet and Bulrush Millet by District Paddy Finger Milet Bulrush Millet Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 50,000 100,000 150,000 Cassava Yams Sweet Potatoes Cocoyam Crop Area Planted (ha) 0 1000 2000 3000 Yield (kg/ha) Yield (kg/ha) Chart 3.23 Total Planted Area and Area of Sorghum per Household by District 6,524 4,741 4,570 4,457 276 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 Masasi Mtwara Rur Newala Tandahimba Mtwara Urb District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24: Time Series Data on Sourghum Production - MTWARA 12 8 20 21 5 5 2 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Chart 3.25 Time Series of Sourghum Planted Area and Yield - MTWARA - 3,000 6,000 9,000 12,000 15,000 18,000 21,000 24,000 27,000 30,000 1994/95 1995/96 1996/97 1997/98 1998/99* 1999/00 2002/03 Agriculture Year A rea (h ecta res) - 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.500 Y ield (t/h a ) Planted Area Yield Tandahimba Mtwara Urban Newala 0.4ha 0.3ha 0.3ha 0.4ha 0.5ha Masasi Mtwara Rural 0.48 to 0.6 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Mtwara Urban Tandahimba Newala 505ha 5,617ha 8,427ha 15,543ha 41,922ha 0.2t/ha 0.4t/ha 0.3t/ha 0.5t/ha 0.4t/ha Masasi Mtwara Rural 36,000 to 45,000 27,000 to 36,000 18,000 to 27,000 9,000 to 18,000 0 to 9,000 Area Planted per Maize Growing Household by District MAP 3.10 MTWARA MAP 3.11 MTWARA Planted Area and Yield of Maize by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 25 Mtwara Urban Tandahimba Newala 0.3ha 0.3ha 0.3ha 0.3ha 0.4ha Masasi Mtwara Rural 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Mtwara Urban Mtwara Rural Tandahimba Newala 4,570ha 276ha 4,741ha 4,457 6,524ha 0.3t/ha 0.2t/ha 0.3t/ha 0.1t/ha 0.3t/ha Masasi 4,800 > 3,600 to 4,800 2,400 to 3,600 1,200 to 2,400 0 to 1,200 Area Planted per Sorghum Growing Household by District MAP 3.12 MTWARA MAP 3.13 MTWARA Planted Area and Yield of Sorghum by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 26 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 (0.1%), sweet potatoes (77t, 0.1%) and cocoyams (29t, 0.0%) (Table 3.3). The area planted with cassava was larger than any other root and tuber crops and it was the most important annual crop in Mtwara in terms of planted area (44.5% of the total area planted with annual crops and vegetables) and it accounted for 99.9 percent of the area planted with roots and tubers, followed by yams (0.1%). It is difficult to determine the total planted area and production for the dry and wet seasons for roots and tubers as the total production of cassava has been reported under the wet season. However, excluding cassava, there was no area planted with roots and tubers during the dry season. While a relatively high percent of sweet potatoes and yams having (0.11%) each, was produced during the wet season. The total production of roots and tubers was estimated at 72,274 tones. Cassava with an estimate of 72,087 tonnes was the most important root and tuber crop. It almost accounted for the entire production of roots and tubers in the region. The estimated yield was highest for sweet potatoes (2.0 t/ha), followed by yams and cocoyams (1.0 t/ha each), cassava (0.6 t/ha) and Irish potatoes (0.2 t/ha). 3.3.2. 5.1 Cassava The number of households growing cassava in the region was 188,744. This represents 33 percent of the total crop growing households in the region. The total production of cassava during the census year was 72,087 tonnes from a planted area of 114,157 hectares resulting in a yield of 0.6t/ha. Previous censuses and surveys indicate that the area planted with cassava increased for the period 1996 to 1999. Since 1999 the area planted with cassava dropped from 43,000 ha in 1999 to 30,732 ha in 2003 (Chart 3.28). Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Cassava 61 50 823 114,097 72,037 631 114,157 72,087 631 Sweet Potatoes 0 0 0 38 77 2,043 38 77 2,026 Irish Potatoes 0 0 0 10 2 198 10 2 198 Yams 0 0 0 75 78 1,046 75 78 1,046 Cocoyam 0 0 0 29 29 1,001 29 29 1,001 Total 61 50 114,248 72,224 114,309 72,274 Note: Cassava is produced in both the wet and dry season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the wet season only. Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 28 The area planted with cassava accounted for 45 percent of the total area planted with annual crops and vegetables in the census year. Masasi district had the largest planted area for cassava (41,873ha, 37% of the cassava planted area in the region), followed by Tandahimba (25,434 ha, 22%), Mtwara rural (23,126 ha, 20%), Newala (21,752 ha, 19%) and Mtwara urban (1,972 ha, 2%) (Map 3.14). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Masasi district (16%). This was followed by Tandahimba (10%), Mtwara rural (9%), Newala (8%), and Mtwara urban (0.8%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.6 hectares. However, there were small district variations. The area planted per cassava growing household was highest in Mtwara urban (0.8 ha). This was followed by Tandahimba (0.7 ha), Mtwara rural and Masasi (0.6 ha) each, and Newala (0.5 ha) (Chart 3.30 and Map 3.15). 3.3. 2. 5.2 Yams The number of households growing yam in Mtwara region was 315. The total production of yams during the census year was 78 tonnes from a planted area of 75 hectares resulting in a yield of 1.0t/ha. Tandahimba District had the largest planted area for yam (71 ha, 95.6%), followed by Mtwara urban (3ha, 4.4%). Yams were not grown in the other districts of Mtwara region(Chart 3.31). Other root and tuber crops were of minor importance in terms of area planted compared to cassava and yams. Chart 3.31 Total Area Planted with Yams and Planted Area per Household by District 71 3 0 0 50 100 150 Tandahimba Mtwara Urb Masasi District Area (Ha) 0.00 0.10 0.20 0.30 Area Planted per Household Planted Area (ha) Planted Area per hh Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 36.7 22.3 20.3 19.1 1.7 0.0 15.0 30.0 45.0 Masasi Tandahimba Mtwara Rur Newala Mtwara Urb District Percent of Total Area Planted 0 10 20 30 40 50 60 70 80 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.76 0.71 0.62 0.58 0.54 0.00 0.20 0.40 0.60 0.80 Area per Household Mtwara Urb Tandahimba Mtwara Rur Masasi Newala District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Mtwara Urban Tandahimba Newala 0.8ha 0.6ha 0.7ha 0.5ha 0.6ha Masasi Mtwara Rural 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Mtwara Urban Mtwara Rural Tandahimba Newala 1,972ha 23,126ha 25,434ha 21,752ha 41,873ha 0.3t/ha 0.7t/ha 0.7t/ha 0.8t/ha 0.5t/ha Masasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Area Planted per Cassava Growing Household by District MAP 3.14 MTWARA MAP 3.15 MTWARA Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 29 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 3.3.2. 6 Pulse Crops Production The total area planted with pulses was 14,171 hectares out of which 7,346 ha were planted with bambaranuts (52 percent of the total area planted with pulses), followed by cow peas (5,333 ha, 37.6%), green gram (1,040 ha, 7.3%), beans (260 ha, 1.8%), pigeon peas (131 ha, 0.9%), chich peas (40 ha, 0.3%) and mung beans (21 ha, 0.2%). Field peas were not cultivated in the region. The bambaranut crop was therefore the dominant crop. The pulses were not grown in the dry season during the year. The total production of pulses was 4,253 tonnes. Bambaranuts were the most cultivated crop producing 2,366 tonnes which accounted for 55.6 percent of the total pulse production. This was followed by cow peas (1,229t, 28.9%), green gram (279t, 6.6%), beans (177t, 4.2%), mung beans (105t, 2.5%) and pigeon peas (97t, 2.3%). Mung beans had the highest yields of 4,940 kgs/ha. The yields of the rest of the pulses in kilograms per hectare were pigeon peas 741kgs/ha, beans 681 kgs/ha, bambaranuts 322 kgs/ha, green gram 269 kgs/ha and cowpeas 230 kgs/ha (Chart 3,32). 3.3.6.1 Bambaranuts Bambaranuts dominated the production of pulse crops in the region. The number of households growing bambaranuts in Mtwara region was 29,205. The total production of bambaranuts in the region was 2,366 tonne from a planted area of 7,346 hectares resulting in a yield of 0.3 t/ha. The largest area planted with bambaranuts in the region was in Newala (2,902 ha, 39.5%) (Chart 3.33 and Map 3.16), however, the largest area planted with bambaranuts per household was in Tandahimba district (0.31 ha) (Chart 3.34). The average area planted per household in the region during the wet season was 0.25 ha. With exception of Tandahimba Table 3.4: Area, Production and Yield of Pulses by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 21 105 4,940 21 105 4,940 Beans 0 0 0 260 177 681 260 177 681 Cowpeas 0 0 0 5,333 1,229 230 5,333 1,229 230 Green Gram 0 0 0 1,040 279 269 1,040 279 269 Pigeon Peas 0 0 0 131 97 741 131 97 741 Chich Peas 0 0 0 40 0 0 40 0 0 Bambaranuts 0 0 0 7,346 2,366 322 7,346 2,366 322 Field Peas 0 0 0 0 0 0 0 0 0 TOTAL 0 0 14,171 4,253 14,171 4,253 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 4,000 8,000 Bambaranuts Cowpeas Green Gram Beans Pigeon Peas Chich Peas Mung Beans Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 6,000 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Bambaranuts by District -10 10 30 50 Newala Masasi Tandahimba Mtwara Rur Mtwara Urb District Percen t of Lan d 0 10 Percen t A rea Plan ted of T otal Lan d A rea Percent of Land Proportion of Land 0.31 0.26 0.23 0.18 0.12 0.00 0.25 0.50 Area per Household Tandahimba Masasi Newala Mtwara Rur Mtwara Urb District Chart 3.34 Area Planted per Bambaranuts Growing Household by District (Wet Season Only) RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 district, the variations in area planted with bambaranuts per household for the rest of the districts were small ranging from 0.1 ha in Mtwara urban to 0.3 ha in Masasi district (Map 3.17). 3.3.2. 7 Oil Seed Production The total production of oilseed crops was 6,124 tonnes planted from an area of 19,849 hectares. The total planted area of oilseeds in the wet season was 19,849 ha representing 100 percent of the total area planted with oil seeds. Groundnut was the most important oilseed crop with 16,330 ha (82% of the total area planted with oil seeds) and followed by simsim (18%) (Chart 3.37). The yield of castor seed was moderate (988 kg/ha). Groundnuts had a yield of 315 kg/ha and simsim 279 kg/ha. The production of groundnuts was 5,137 tonnes and accounted for 84 percent of the total production of oil seeds, followed by simsim (16%). 3.3.2. 7.1 Groundnuts The number of households growing groundnuts in Mtwara region was 45,840. The total production of groundnuts in the region was 5,137 tonnes from a planted area of 16,330 hectares resulting in a yield of 0.3 t/ha. Area planted increased from 4,008 hectares in 1994/95 to 4,268 hectares in 1995/96 after which it decreased to 1,400 hectares in 1998/99 and then increased to 16,330 in 2002/03. (Chart 3.38) Sixty nine percent of the area planted with groundnuts was located in Masasi District (11,180 ha) followed by Newala (2,918ha, 17.9%), Tandahimba (1,333 ha, 8.2%), Mtwara rural (862 ha, 5.3%) and Mtwara urban (36 ha, 0.2%). (Map 3.18). The highest proportion of land with groundnuts was found in Masasi followed by Newala, Tandahimba, Mtwara rural, and Mtwara urban (Chart 3.39 and Map 3.1920). Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 0 0 0 0 0 0 Simsim 0 0 0 3,512 979 279 3,512 979 279 Groundnuts 0 0 0 16,330 5,137 315 16,330 5,137 315 Soya Beans 0 0 0 0 0 0 0 0 0 Castor Seed 0 0 0 8 8 988 8 8 988 Total 0 0 19,849 6,124 19,849 6,124 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 10,000 20,000 Groundnuts Simsim Castor Seed Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) 4,008 4,268 1,400 16,330 0 1000 2000 3000 4000 5000 Planted Area 1994/95 1995/96 1998/99 2002/03 Year Chart 3.38 Time Seried Data on Groungnuts Planted Area - MTWARA RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 The largest area planted per groundnut growing household was found in Masasi District (0.45 ha) and the lowest was in Mtwara urban (0.18). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.2. 8 Fruits and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. Fruit and vegetables were not grown in dry season. Reliable historical data for time series analysis of fruit and vegetables were not available. The total production of fruits and vegetables was 2,123 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 1,326 tonnes (62% of the total fruit and vegetables produced) followed by pumpkins (299t, 14%) and okra (278t, 13%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of okra was 4,117 kg/ha, tomatoes (2,543 kg/ha), water mellon (2,422 kg/h), pumpkins (2,337 kg/ha) and egg plant (1,370 kg/ha), onion (937 kg/h), cucumber and amaranths had yields of 166 and 25 kg/ha respectively (Chart 3.42). Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District -50.0 50.0 150.0 250.0 Masasi Newala Tandahimba Mtwara Rur Mtwara Urb District Percent of Lan d 0.0 5.0 10.0 15.0 Percent A rea Plan ted of Total Land A rea Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 A rea per H o useho ld (ha ) Masasi Mtwara Rur Tandahimba Newala Mtwara Urb District Chart 3.40 Area Planted per Groundnut Growing Households by District (Wet Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 1000 2000 3000 TomatoesPumpkins Onions Okra Egg Plant Ginger Other Crop Area Planted (ha) 0 1000 2000 3000 4000 5000 Yield (kg/ha) Tandahimba Mtwara Urban Mtwara Rural Newala 0ha 0ha 0.6ha 0.1ha 0.4ha Masasi 0.48 > 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Mtwara Urban Mtwara Rural Tandahimba Newala 0ha 65ha 0ha 10ha 186ha 0t/ha 1.4t/ha 0t/ha 0.2t/ha 0.46t/ha Masasi 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Area Planted per Beans Growing Household by District MAP 3.16 MTWARA MAP 3.17 MTWARA Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 33 Tandahimba Mtwara Urban Newala 0.3ha 0.3ha 0.2ha 0.2ha 0.4ha Masasi Mtwara Rural 0.36 to 0.4 0.32 to 0.36 0.28 to 0.32 0.24 to 0.28 0.2 to 0.24 Mtwara Urban Mtwara Rural Tandahimba Newala 36ha 862ha 1,333ha 2,918ha 11,181ha 0.1t/ha 0.2t/ha 0.1t/ha 0.4t/ha 0.3t/ha Masasi 8,000 > 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Area Planted per Groundnuts Growing Household by District MAP 3.18 MTWARA MAP 3.19 MTWARA Planted Area and Yield of Groundnuts by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 34 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 3.3. 2. 8. 1 Tomatoes The number of households growing tomatoes in the region during the wet season was 1,856 and there were no households growing tomatoes in the dry season. This represented 0.8 percent of the total crop growing households in the region during the wet season. Mtwara rural district had the largest planted area of tomatoes (56.6% of the total area planted with tomatoes in the region), followed by Tandahimba (33.6%), Masasi (6.3%), Newala (3.5%) and there was no tomatoes planted area in Mtwara urban district. (Map 3.20). The highest percentage of land with tomatoes was found in Mtwara rural, followed by Tandahimba district. With exception of Mtwara rural district, the rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). (Chart 3.44 and Map 3.21). The total area planted with tomatoes accounted for 0.2 percent of the total area planted with annual crops and vegetables during the dry and wet seasons. 3.3. 2. 8. 2 Pumpkins The number of households growing pumpkins in the region during the wet season was 796 and there were no households growing pumpkins in the dry season. This represented 0.4 percent of the total crop growing households in the region in the wet season. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 0 0 0 68 278 4,117 68 278 4,117 Onions 0 0 0 75 71 937 75 71 937 Ginger 0 0 0 35 0 0 35 0 0 Tomatoes 0 0 0 521 1,326 2,543 521 1,326 2,543 Amaranths 0 0 0 20 0 25 20 0 25 Pumpkins 0 0 0 128 299 2,337 128 299 2,337 Cucumber 0 0 0 12 2 1666 12 2 166 Egg Plant 0 0 0 68 94 1,370 68 94 1,370 Water Mellon 0 0 0 22 53 2,422 22 53 2,422 Total 0 0 949 2,123 949 2,123 Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tobacco 149 61 412 142 32 2,926 291 93 319 Total 149 61 412 142 32 2,926 291 93 319 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Mtwara Rur Tandahimba Masasi Newala Mtwara Urb District Percent of Land 0.00 0.50 1.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Mtwara Urban Mtwara Rural Tandahimba Newala 0ha 0.4ha 0.2ha 0.2ha 0.2ha Masasi 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Newala Mtwara Urban Mtwara Rural Tandahimba Masasi 18ha 0ha 295ha 175ha 33ha 1t/ha 0t/ha 3.6t/ha 1.4t/ha 0.3t/ha 240 to 300 180 to 240 120 to 180 60 to 120 0 to 60 Area Planted per Tomatoes Growing Household by District MAP 3.20 MTWARA MAP 3.21 MTWARA Planted Area and Yield of Tomatoes by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 36 RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 Mtwara rural district had the largest area planted with pumpkins (89 ha, 69% of the total area planted with pumpkins in the region), followed by Tandahimba (23 ha, 18%) and Newala (16 ha, 12%). The remaining districts had no planted area for pumpkins. (Chart 3.45). The total area planted with pumpkins accounted for 0.05 percent of the total area planted with annual crops and vegetables during the dry and wet seasons. 3.3. 2. 8.3 Okra The number of households growing okra in the region during the wet season was 357 households and there was no household growing okra in the dry season. This represented 0.12 percent of the total crop growing households in the region in the wet season. Mtwara rural district had the largest planted area for chillies (44 ha, 64.7% of the total area planted with okra in the region) and followed by Tandahimba district (24 ha, 35.1%). Okra was not produced in Newala, Masasi and Mtwara districts. The largest proportion of the area planted with okra was found in Mtwara rural district (0.11%) and Tandahimba (0.05%) only. (Chart 3.46). The total area planted with okra accounted for 0.03 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3. 2. 9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 291 ha was planted with other annual crops and tobacco was the only prominent cash crop. The area planted with annual cash crops in dry season was 149 ha which represents 51 percent of the total area planted with other annual cash crops in dry and wet season. 3.3. 2. 9. 1 Tobacco The quantity of tobacco produced was 93 tonnes. Tobacco had a planted area of 291 ha, most of which was planted in the wet season. Tobacco production was concentrated in 2 districts with Tandahimba having the largest planted area (63% of total area planted with tobacco in the region) and followed by Masasi. (Map 3.22 and 3.23). Chart 3.45 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District 0.0 25.0 50.0 75.0 Mtwara Rur Tandahimba Newala Masasi Mtwara Urb District Percent of Land 0.00 0.20 0.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Okra Planted Area and Percent of Total Land with Okra by District 0.0 20.0 40.0 60.0 80.0 Mtwara Rur Tandahimba Newala Masasi Mtwara Urb District Percent of Land 0.00 0.10 0.20 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 80.0 100.0 Tandahimba Masasi Newala Mtwara Rur Mtwara Urb District Percent of Land 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.47 Area planted with Annual Cash Crops Tobacco 291, 100% Mtwara Urban Tandahimba Newala 0ha 0ha 0.7ha 0ha 0.1ha Masasi Mtwara Rural 0.56 to 0.7 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 0ha 0ha 129ha 0ha 13ha 0t/ha 0t/ha 0.2t/ha 0t/ha 0.4t/ha 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Area Planted per Tobbaco Growing Household by District MAP 3.22 MTWARA MAP 3.23 MTWARA Planted Area and Yield of Tobbaco by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 38 RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 3. 3.3 Permanent Crops Permanent crops (sometimes referred to perennial crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 247,188 hectares (49% of the area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops would be higher than indicated in Chart 3.49. The most important permanent crop in Mtwara region was Cashewnut which had a planted area of 228,078 ha, (93% of the planted area of all permanent crops) followed by pigeon peas (7,841 ha, 3%), coconut (5,947 ha, 2%), mango (3,804 ha, 2%). Each of the remaining permanent crops had an area of zero percent of the total area planted with permanent crops (Chart 3.50). Masasi district had the largest area under smallholder permanent crops (99,923 ha, 40.4%). This was followed by Tandahimba (60,206 ha, 24.4%), Mtwara rural (51,953 ha, 21%), Newala (34,377 ha, 13.9%) and Mtwara Urban (680 ha, 0.3%). However, Tandahimba had the largest area per permanent crop growing household (1.9 ha) followed by Mtwara rural (1.7 ha), Masasi and Newala (1.3 ha) each and Mtwara Urban (0.6 ha) (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Tandahimba had the highest percent (57%) followed by Mtwara rural (56%), Masasi (46%), Newala (40%) and Mtwara Urban (19%). Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 24.4 21.0 13.9 0.3 40.4 0.0 20.0 40.0 Masasi Tandahimba Mtwara Rural Newala Mtwara Urban District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.49 Area Planted for Annual and Permanent Crops Annual Crops, 256,405, 51% Permanent Crops, 247,188, 49% Chart 3.50 Area Planted with the Main Permanent Crop Orange, 369, 0% Banana, 426, 0% Others, 93, 0% Coconut, 5947, 2% Sugarcane, 45, 0% Pawpaw, 289, 0% Pigeon Pea, 7841, 3% Sour Soup, 86, 0% Mango, 3804, 2% Cloves, 212, 0% Cashewnut, 228078, 93% RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 3.3.3. 1 Cashewnut The total production of cashewnuts by smallholders was 38,295 tonnes. In terms of area planted, cashewnuts was the most important permanent crop grown by smallholders in the region. They were grown by 131,000 households (57.2% of the total crop growing households). The average area planted with Cashewnuts per household was relatively small at around 1.74 ha per cashewnut growing household and the average yield obtained by smallholders was 302 kg/ha from a harvest area of 126,660 hectares. Mtwara rural had the largest area of cashewnuts in the region (91,793.9 ha, 40.2%) followed by Newala (57,200.5 ha, 25.1%), Masasi (45,632.5 ha, 20%), Tandahimba (32,956.5 ha, 14.4%) and Mtwara Urban (494.1 ha, 0.2%). (Map 3.24). Likewise, the average area planted with cashewnuts per cashewnuts growing household was highest in Mtwara rual (1.87 ha) followed by Newala (1.83 ha), Masasi (1.74 ha), Tandahimba (1.39 ha) and Mtwara Urban (0.68 ha) (Chart 3.52 and Map 3.25). 3. 3.3. 2 Pigeon peas The total production of pigeon peas by smallholders was 1,836 tonnes. In terms of area planted, pigeon pea was the second most important permanent crop grown by smallholders in the region. It was grown by 25,949 households (11.3% of the total crop growing households). The average area planted with pigeon pea per household was relatively small at around 0.30 ha per pigeon pea growing household and the average yield obtained by smallholders was 99 kg/ha from a harvest area of 18,518 hectares. Masasi had the largest area of pigeon peas in the region (7,084 ha, 90.3%) followed by Newala (600 ha, 7.7%), Mtwara rural (141 ha, 1.8%), Mtwara urban (16 ha, 0.2%) and there was no area planted with pegion peas in Tandahimba district. (Map 3.2633). However, the average area planted with pigeon pea per pigeon pea planting household was highest in Masasi (0.09 ha) followed by Newala (0.02 ha), Mtwara urban (0.01 ha) and the rest of the districts had zero average area planted with pigeon pea per pigeon pea planting household. (Chart 3.53 and Map 3.27). Chart 3.52 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.2 20.0 25.1 14.4 40.2 0.0 25.0 50.0 Mtwara Rural Newala Masasi Tandahimba Mtwara Urban District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Pigeon Pea and Average Planted Area per Household by District 7.65 0.21 90.34 0.00 1.80 0.00 20.00 40.00 60.00 80.00 100.00 Masasi Newala Mtwara Rural Mtwara Urban Tandahimba Districts % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tandahimba Mtwara Urban Mtwara Rural Newala 57,200ha 494ha 45,633ha 32,957ha 91,794ha 0.4t/ha 0.2t/ha 0.4t/ha 0.6t/ha 0.2t/ha Masasi Mtwara Urban Tandahimba Newala 0.7ha 1.7ha 1.8ha 1.4ha 1.9ha Masasi Mtwara Rural 1.6 to 2 1.2 to 1.6 0.8 to 1.2 0.4 to 0.8 0 to 0.4 Area Planted per Cashewnuts Growing Household by District MAP 3.24 MTWARA MAP 3.25 MTWARA Planted Area and Yield of Cashewnuts by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 41 Mtwara Urban Mtwara Rural Tandahimba Newala 0.3ha 0.8ha 0ha 0.7ha 0.3ha Masasi 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Mtwara Urban Mtwara Rural Newala Tandahimba 16ha 600ha 141ha 0ha 7,084ha 0.3t/ha 0.2t/ha 0.2t/ha 0t/ha 0.1t/ha Masasi 5,600 to 7,200 4,200 to 5,600 2,800 to 4,200 1,400 to 2,800 0 to 1,400 Area Planted per Pegion Peas Growing Household by District MAP 3.26 MTWARA MAP 3.27 MTWARA Planted Area and Yield of Pigeon Peas by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 42 RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 43 3.3. 3. 3 Coconut The total production of coconuts by smallholders was 1,931 tonnes. In terms of area planted, coconut was the third most important permanent crop grown by smallholders in the region. It was grown by 4,255 households (1.9% of the total crop growing households). The average area planted with coconut per household was around 1.4 ha per coconut growing household and the average yield obtained by smallholders was 1,017 kg/ha from a harvested area of 1,898 hectares. Mtwara rural had the largest planted area of coconut in the region (5,339 ha, 89.8%) followed by Masasi (197 ha, 3.3%), Mtwara urban (158 ha, 2.7%), Newala (152 ha, 2.6%) and Tandahimba (100 ha, 1.7%) (Map 3.28). However, the area planted with coconut per coconut growing household was highest in Mtwara rural (1.69 ha), followed by Masasi (1.21 ha), Tandahimba (0.54 ha), Mtwara urban (0.45 ha) and Newala (0.39 ha) (Chart 3.49 and Map 3.29). 3.3. 3. 4 Mango The total production of mangoes by smallholders was 313 tonnes. In terms of area planted, mango was the fourth most important permanent crop grown by smallholders in the region. It was grown by 605 households (0.26% of the total crop growing households). The average area planted with mango per household was around 6.29 ha per mango growing household and the average yield obtained by smallholders was 6,803 kg /ha from a harvest area of 46 hectares. Tandahimba district has the largest area of mangoes in the region (2,906 ha, 76%) followed by Masasi (817 ha, 21%), Mtwara rural (71 ha, 1.9%), Mtwara urban (11 ha, 0.3%) and there was no area planted with mangoes in Newala district. (Map 3.37). Likewise, the average area planted per mango growing household was highest in Tandahimba (15.12 ha), followed by Masasi (4.98 ha), Mtwara rural (0.39 ha), and Mtwara urban (0.15 ha) (Map 3.31). Newala district reported no mango production. 3.3. 4 Input/Implement Use 3.3. 4. 1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into Chart 3.56: Number of Households by Method of Land Clearing during the Wet Season 373,227 48,572 9,117 4,244 1,431 0 100,000 200,000 300,000 400,000 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor Slashing Method of Land Clearing Number of Households Chart 3.54 Percent of Area Planted with Coconuts and Average Planted Area per Household by District 2.66 1.68 89.78 2.56 3.32 0.00 20.00 40.00 60.00 80.00 100.00 Mtwara Rural Masasi Mtwara Urban Newala Tandahimba District % of Total Area Planted 0.00 0.30 0.60 0.90 1.20 1.50 1.80 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Mangoes and Average Planted Area per Household by District 21.5 0.3 76.4 0.0 1.9 0.0 30.0 60.0 90.0 Tandahimba Masasi Mtwara rural Mtwara urban Newala District % of Total Area Planted 0.00 5.00 10.00 15.00 20.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Mtwara Urban Mtwara Rural Tandahimba Newala 0.5ha 1.7ha 0.5ha 0.4ha 1.2ha Masasi 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Mtwara Urban Mtwara Rural Tandahimba Newala 158ha 5,339ha 100ha 152ha 197ha 3.6t/ha 1t/ha 0t/ha 0.7t/ha 0.4t/ha Masasi 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted per Coconuts Growing Household by District MAP 3.28 MTWARA MAP 3.29 MTWARA Planted Area and Yield of Coconuts by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 44 Mtwara Urban Mtwara Rural Tandahimba Newala 0.2ha 0.4ha 15.1ha 0ha 5ha Masasi 12.08 > 9.06 to 12.08 6.04 to 9.06 3.02 to 6.04 0 to 3.02 Mtwara Urban Mtwara Rural Tandahimba Newala 11ha 71ha 2,906ha 0ha 817ha 10.5t/ha 7.8t/ha 0.5t/ha 0t/ha 4.3t/ha Masasi 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Area Planted per Mango Growing Household by District MAP 3.30 MTWARA MAP 3.31 MTWARA Planted Area and Yield of Mango by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Area Planted per Household Yield (t/ha) RESULTS 45 RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. 3.3. 4. 2 Methods of Soil Preparation Hand cultivation is the most used method for soil preparation and was used in an area of 241,423 ha which represented 95 percent of the total planted area, followed by ox-ploughing (9,796 ha, 4%) and tractor ploughing (3,808 ha, 1%). Slightly more hand cultivation was used during dry rainy season at 100 percent against 95 percent for the wet season, whereas, oxen and tractor ploughing was more common in the wet season with 3 percent and 1 percent respectively. The oxen and tractor ploughing were not used in the dry season. In Mtwara region, Newala district has the largest planted area cultivated with oxen (3,734 hectares, 7.4%) followed by Tandahimba (2,580 ha, 5.7%), Mtwara Rural (2,034 ha, 5.1%), Masasi (1,664 ha, 1.4%) and Mtwara Urban (16 ha, 0.6%). During the wet season, 80.8 percent of the total area cultivated by using oxen was planted with roots and tubers followed by cereals (16.4%), pulses (2.4%) and oil seeds (0.4%). 3.3. 4. .3 Improved Seed Use The planted area using improved seeds was estimated at 7,691 ha which represents 3 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the wet season was the same 3 percent, since there was no use of improved seed in the dry season. Chart 3.59 Planted Area of Improved Seeds - TANGA With Improved Seeds, 52,089, 13% Without Improved Seeds, 348,221, 87% Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 9,796 4% Mostly Hand Hoe Ploughing, 241,423 95% Mostly Tractor Ploughing, 3,808 1% - 20,000 40,000 60,000 80,000 100,000 120,000 Area Cultivated Masasi Newala Tandahimba Mtwara Rural Mtwara Urban District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 47 Roots and Tubers had the largest planted area with improved seeds (112,932 ha, 44% of the planted area with improved seeds) followed by cereals (106,644 ha, 42%), and Oil seed (19,849 ha, 8%) and Pulses (14,171 ha, 6%) (Chart 3.60). However, the use of improved seed in cereals and roots and tubers is much greater than in other crop types (48% and 34% respectively) (Chart 3.61). 3. 3. 4. 4 Fertilizer Use The use of fertilisers on annual crops is very small with a planted area of only 57,966 ha (15.6% of the total planted area in the region). The planted area without fertiliser for annual crops was 370,460 hectares representing 86.5 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 40,772 ha which represents 9.5 percent of the total planted area (70.3% of the area planted with fertiliser application in the region). This was followed by compost (12,226 ha, 21.1%). Inorganic fertilizers were used on a very small area and represented only 8.6 percent of the area planted with fertilizers. Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 40,772, 10% Mostly Inorganic Fertilizer, 4,968, 1% Mostly Compost, 12,226, 3% No Fertilizer Applied, 370,460, 86% - 50,000 100,000 150,000 Area (ha) Tandahimba Newala Mtwara Rural Masasi Mtwara Urban District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 112,932 , 44% Cereals, 106,644 , 42% Cash Crops, 291 , 0% Fruits & Vegetables, 949 , 0% Oilseeds , 19,849 , 8% Pulses, 14,171 , 6% 0.0 20.0 40.0 60.0 Percent of Planted A rea Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 The highest percentage of the area planted with fertilizer (all types) was in Tandahimba district (47.8%) followed by Newala (17.7%), Mtwara Rural (16.8%), Masasi (16.6%), and Mtwara urban (1.1%) (Table 3.9 and Charts 3.62 and 3.63 Most annual crop growing households do not use any fertiliser (approximately 543,109 households, 94.2%) (Map 3.32). The percentage of the planted area with applied fertilizer was highest for cereal (65% of the area planted with these cereal during the wet season had an application of fertilizers). This was followed by roots and tubers (32%), oil seeds (2%) and pulses (1%). There was no fertilizer application in cash crops (Table 3.10). 3.3. 4. 4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Mtwara region was 10,110 ha. The number of households that applied farm yard manure in their annual crops during the wet season was 18,463 and it was applied to 10,110 ha representing 52.1 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (55%), followed by roots and tubers (40%), pulses (2%), Oil seeds (2%) and fruit and vegetables (1%). Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District – Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Districts Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mtwara rural 945 486 618 459 100 30 1,473 471 3,136 1,447 Newala 7,259 3,345 2,134 869 7,729 4,778 120,235 41,622 137,357 50,614 Masasi 1,940 1,260 1,429 794 970 1,755 238,133 113,222 242,471 117,031 Tandahimba 8,126 4,929 1,336 520 286 189 88,323 39,613 98,071 45,251 Mtwara urban 193 89 100 41 99 41 5,587 2,707 5,979 2,878 Total 18,463 10,110 5,617 2,683 9,183 6,792 453,751 197,636 487,015 217,221 0 25 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - MTWARA Roots & Tubers, 4,050 , 40% Pulses, 3,407 17% Oilseeds, 232 2% Fruits & Vegetables, 53 1% Cereals, 5,576 55% Cash Crops, 0, 0% Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total applied Tandahimba 4,929 520 189 5,638 113,222 Newala 3,345 869 4,778 8,992 41,813 Mtwara Rural 486 459 30 976 39,762 Masasi 1,260 794 1,755 3,809 39,315 Mtwara Urban 89 41 41 171 2,707 Total 10,110 2,683 6,792 19,585 236,819 Table3.9 Planted Area by Type of Fertiliser Use and District - Wet and Dry Rainy Season District Fertilizer Use No Fertilizer Applied RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 However, fruit and vegetables had the highest percent of the planted area with farm yard manure (5.5% of the total area of fruit and vegetables in Mtwara). This was followed by cereals (5.2%), roots and tubers (3.5%), pulses (1.4%) and oil seeds (1.2%) (Chart 3.64). Farm yard manure is mostly used in Newala (6.6% of the total planted area in the district), followed by Tandahimba (4.1%), Mtwara Urban (3.1%), Masasi (2.9) and Mtwara Rural (1.2%) (Chart 3.65b). For permanent crops, most farm yard manure is used for the production of tomatoes (10%), followed by apples (31.8%) and coffee (25.7%). 3.3. 4. 4. 2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Mtwara region was 6,603 ha which represents 2.58 percent of the total planted area with annuals in the region and 34.0 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the wet season was 9,183 and it was applied to 6,792 ha representing 3.1 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (43% of the total area applied with inorganic fertilizers), followed by Oilseeds (20%), pulses (18%) and roots and tubers (17%) (Chart 3.66). However, the proportion of fruit and vegetables with inorganic fertilizers was 12.7 percent higher than other crop types, followed by roots and tubers (1.1%), Pulses (0.8%) and cereals (0.3%) (Chart 3.67a). Inorganic fertiliser is mostly used in Newala (9.4% of the total planted area in the district), followed by Mtwara Rural (2.1%), Masasi (1.5%), Mtwara Urban (1.4%) and Tandahimba (0.4%). (Chart 3.67b). In permanent crops inorganic fertiliser were used on tea (5.2%), followed by sugarcane (1.1%), coconut (0.3%), mangoes (0.15%) and oranges (0.14%). Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - MTWARA 0.0 5.0 10.0 15.0 20.0 Newala Tandahimba Mtwara Urban Masasi Mtwara Rural Total District Percent Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - MTWARA Pulses, 48 1% Oilseeds, 62 1% Cash Crop, 0% Cereals, 5,436 , 82% Roots & Tubers, 1,058 , 16% Fruit & Vegetables, 671, 16% 0 5 10 15 20 25 30 35 40 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - MTWARA Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - MTWARA 0.0 4.0 8.0 12.0 Newala Tandahimba Mtwara Urban Masasi Mtwara Rural District Percent RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 3.3. 4. 4.3 Compost Use The total planted area applied with compost was 2,683 ha which represents only 1.0 percent of the total planted area with annual crops in the region and 14 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on th eir annual crops during the wet season was 5,617 and it was applied to 2,683 ha representing 1.0 percent of the total area planted (Table 3.10 and Chart 3.68a). The proportion of area applied with compost was not very low for each type of crop (5 to 10%); however the distribution of the total area using compost manure shows that 57.2 percent of this area was cultivated with cereals, followed by roots & tubers (41.2%), pulses (1%), and oilseeds (0.5%)(Chart 3.68b). Compost is mostly used in Masasi (1.8% of the total planted area in the district), and this is closely followed by Newala (1.7%), Mtwara Urban (1.4%), Mtwara rural (1.1%) and Tandahimba (0.4%). (Chart 3.67b). In permanent crops, compost was mostly used to durian (100.0%) followed by cloves (8.6%), pears (7.8%), avocado (5.3%) cinnamon (4.7%) and mango (4.0%). 3.3. 4. 5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 25,121 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (56% of the total area applied with pesticides). This was followed by fungicides (29%) and herbicides (14%) (Chart 3.69). Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 7346, 29% Herbicides, 3600, 14% Insecticides, 14175, 56% Chart 3.68a Planted Area with Compost by Crop Type - MTWARA Cash Crop, 0% Oilseeds, 14 1% Pulses, 27 1% Fruits & Vegetables, 0% Cereals, 1,535 57% Roots & Tubers, 1,107 41% 0 5 10 15 20 25 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.69b Percentage of Planted Area with Compost by Crop Type- MTWARA Chart 3.68c Proportion of Planted Area Applied with Compost by District - MTWARA 0.0 2.0 4.0 6.0 8.0 Masasi Mtwara Rural Mtwara Urban Tandahimba District Percent RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 3.3. 4. 5.1 Insecticide Use The planted area applied with insecticides was estimated at 6,259 ha which represented 2.4 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (3,241 ha, 51.8% of the total planted area with insecticides) followed by pulses (2,778 ha, 44.4%), fruit and vegetables (232 ha, 3.7%), roots and tubers (8 ha, 0.1%), but insecticides were not applied on cash crops and oil seed (Chart 3.70). However, t he percent of insecticides used in cereal, roots and tubers and pulses is much greater than in other crop types (2.6%, 2.6% and 2.4% respectively), while only 1.0 percent of fruits and vegetables crops were applied with insecticides (Chart 3.71). There was no annual Crops used insecticide with more than 50 percent. Mtwara Urban had the highest percent of planted area with insecticides (5.4% of the total planted area with annual crops in the district). This was closely followed by Masasi (2.9%) then Newala (2.3%) and Mtwara rural (2.1%). The smallest percentage use was recorded in Tandahimba (1.5%) (Chart 3.72). 3.3. 4. 5 .2 Herbicide Use The planted area applied with herbicides was 2,645 ha which represented 1.0 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,425 ha, 54%) followed by roots and tuber (1,183 ha, 44.7%), oil seed (29 ha, 1%) and pulses (8 ha, 0.3%). There was no area planted with fruits and vegetables as well as cash crops applied with herbicides. (Chart 3.73). Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 0, 0.0% Cereals, 3,241, 51.8% Fruits & Vegetables, 232, 3.7% Oil seeds & Oil nuts, 18, 0.1% Pulses, 2,778, 44.4% Roots & Tubers, 8, 0.1% 0.0 1.0 2.0 3.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - MTWARA 0.0 2.0 4.0 6.0 Mtwara Urban Masasi Newala Mtwara Rural Tandahimba District Percent Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cash crops, 0, 0% Cereals, 1,425, 54% Fruits & Vegetables, 0, 0% Oil seeds & Oil nuts, 29, 1% Pulses, 8, 0.3% Roots & Tubers, 1,183, 44.7% RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - MTWARA 0.00 1.00 2.00 3.00 4.00 5.00 Newala Masasi Tandahimba Mtwara Rur Mtwara Urb District Percent However, the percent of herbicide use on creal and roots and tubers was much greater than in other crop types (1.3% and 1.0% respectively) while only 0.1 percent of pulses and oil seeds was applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (1.5%), Sorghum (1.2%), Cassava (1.0%), paddy (0.9%), groundnuts (0.2%) and bambaranut (0.1%). Newala had the highest percent of planted area with herbicides (4.1% of the total planted area with annual crops in the district). This was followed by Masasi (0.4%) then Tandahimba (0.2%) and Mtwara rural (0.2%). There was no planted area recorded in Mtwara urban district (Chart 3.75). 3.3. 4. 5.3 Fungicide Use The planted area applied with fungicides was 5,051 ha which represented 1.9 percent of the total area planted with annual crops and vegetables. The use of fungicides was in the wet season and no fungicides were applied in the dry season. Roots and tubers (2,404 ha, 48%) had the largest planted area applied with fungicides, followed by cereals (2,261 ha, 45%), pulses (239 ha, 5.0%) and oil seeds (147 ha, 3%) (Chart 3.76). However, the percentage use of fungicide in oil seeds and roots and tubers was much greater than in other crop types (0.057% and 0.050% respectively), while only 0.008 percent of cereals and 0.003 percent of pulses were applied with fungicides (Chart 3.77). 0.0 1.0 2.0 Percent of Planted A rea Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 2,404, 48% Pulses, 239, 5% Oil seeds, 147, 3% Cereals, 2,261, 45% 0.0 0.2 P e r c e n t o f P la n t e d A r e a Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 Annual crop with more than 40 percent fungicide use was only castor seed (100%). Mtwara urban had the highest percent of planted area with fungicides (6.4% of the total planted area with annual crops in the district). This was closely followed by Newala (3.9%) and Tandahimba (3.3%). The smallest percentage use was recorded in Mtwara rural district (0.9%) and Masasi district (0.6%) (Chart 3.78). 3.3. 4. 6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize (0.8%) and sorghum (0.2%) were harvested by draft animals and sorghum (0.2%) was harvested by machine. All other cereals and annual crops were harvested by hand. 3.3. 4.7 Threshing Methods Hand threshing was the most common method used, with 87 percent of the total area planted with cereals during the wet season being threshed by hand. Draft animals, human powered tools and engine driven machines were used on crops harvested from 0.2 percent, 2.1 percent and 0.1 percent of the total planted area respectively. 3.3.5 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.3.5.1 Area Planted with Annual Crops and Under Irrigation In Mtwara region, the area of annual crops under irrigation was 2,924 ha representing 1.1 percent of the total area planted (Chart 3.79). The area under irrigation during the wet season was 2,924 ha accounting for 1.1 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the wet season with irrigation. In the wet season, 46 percent of the area planted with vegetables was irrigated, whilst there was no crop irrigated in the dry season. Chart 3.78 Proportion of Planted Area with Fungicides by District - MTWARA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Mtwara Urb Newala Tandahimba Mtwara Rur Masasi District P e r c e nt Chart 3.79 Area of Irrigated Land Unirrigated Area, 253,480, 99% Irrigated Area, 2,924, 1% RESULTS – Irrigation _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 The district with the largest planted area under irrigation with annual crops was Masasi (1,257 ha, 34.5% of the total irrigated planted area with annual crops in the region). This was closely followed by Tandahimba with (1,237 ha, 33.9%) and then Mtwara rural (784 ha, 21.5%), Newala (214, 5.9%) and Mtwara Urban (158, 4.3%). When expressed as a percentage of the total area planted in each district, Mtwara urban had the highest with 5.5 percent of the planted area in the district under irrigation. This was followed by Tandahimba (2.7%), Mtwara rural (1.9%), Masasi (1.1%) and Newala (0.4%) (Chart 3.80 and Map 3.33). Of all the different crops and in terms of proportion of the irrigated planted area, Okra was the most irrigated crops with 65 percent irrigation followed by pumpkins (63%), tomatoes (55%) and egg plant (32%). In terms of crop type, the largest area under irrigation was cereals was 1,328 ha (46% of the total area under irrigation), followed by and tubers with 1,014 ha (35%), fruit and vegetables (439 ha, 15%), pulses (77 ha, 3%) and oil seeds ( 67 ha, 2%). All of the irrigation on cereals was applied to paddy, maize and sorghum. The area of fruit and vegetables under irrigation was 439 ha which represents 46 percent of the total planted area with fruit and vegetables. Tomatoes, pumpkins and okra were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Mtwara region appears to have increased over the 10 year intercensal period from 1,901 to 2,304 hectares. This may not be statically significant due to the small number of households sampled with irrigation. 3.3. 5.2 Sources of Water Used for Irrigation The main source of water used for irrigation was the river (60% of households with irrigation). This was followed by wells (20%) and dams (16%). There was no households using water from boreholes and the proportions of households that used pipe water and canals as sources of water for irrigation were very few (2.3% and 2.0% respectively). Most households practicing irrigation in Mtwara rural (100%) and Masasi (100%) get their irrigation water from dams and piped water, respectively. Chart 3.80 Planted Area with Irrigation by District - TANGA Region - 500 1,000 1,500 Masasi Tandahimba Mtwara Rur Newala Mtwara Urb Region Irrigated A rea (ha) 0 3 6 Percentage Irrigation Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation - MTWARA 2,304 1,901 0 5,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrig Chart 3.82 Number of Households with Irrigation by Source of Water Canal, 81, 2% River, 2,424, 60% Well, 791, 20% Dam, 637, 16% Pipe water, 94, 2% Canal River Well Dam Pipe water Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 2,878ha 40,290ha 45,400ha 50,805ha 117,031ha 5.5% 2.3% 3.1% 0.8% 1.1% 80,000 > 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 858ha 149ha 4,686ha 6,200ha 2,027ha 97.9% 94.8% 89.6% 87.7% 98.3% 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted and Percent of Total Planted Area with Irrigation by District MAP 3.32 MTWARA MAP 3.33 MTWARA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Tanzania Agriculture Sample Census Area Planted with Irrigation Applied Planted Area With no Fertilizer Applied Planted Area With no Fertilizer Applied Area Planted with Irrigation Applied Percent of Planted Area With no Fertilizer Applied Percent of Area Planted with Irrigation Applied RESULTS 55 RESULTS RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.3.5.3 Methods of Obtaining Water for Irrigation Gravity was the most common method getting water for irrigation with 52.3 percent of households using this method. This was closely followed by hand bucket with 45.4 percent of households. The remaining methods were of minor importance (Chart 3.83). Gravity was used by all households with irrigation in Tandahimba. Hand bucket was more common in Masasi with 60.7 percent of households using the method to get water for irrigation, followed by Mtwara rural (34.9). Although the method of obtaining irrigation water by hand bucket was the most common method in three districts, Newala districts used other methods apart from gravity and hand bucket for obtaining water. 3.3. 5. 4 Methods of Water Application Most households used flooding (52% of households using irrigation) as a method of field application. This was closely followed by hand bucket/watering can (45%). Water hose were not widely used (2%). 3.3. 6 Crop Storage, Processing and Marketing 3.3. 6.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at a higher prices or as seed for planting in the following season. The results for Mtwara region show that there were 161,435 crop growing households (70% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 135,282 households storing 5,745 tonnes as of 1st January 2004. This was followed by sorghum and millet (47,730 households, 852t), pulses (35,793 households, 526t), groundnuts and bambara nuts (35,613 households, 1,040t), paddy (23,989 households, 972t) and cashew nut (1,421 households, 37t). Chart 3.84 Number of Households with Irrigation by Method of Field Application Water Hose, 94, 2% Bucket / Watering Can, 1,828, 45% Flood, 2,104, 52% Flood Bucket / Watering Can Water Hose Chart 3.85 Number of Households and Quantity Stored by Crop Type - MTWARA 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Maize Sorghum & Millet Pulses Gnuts/Bamb Nuts Paddy Cashewnut Cloves Sea weed Tobacco Coconut Crop Number of househ 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 Quantity ( Number of households Quantity stored (Tons) Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 2,104, 52.3% Hand Bucket, 1,828, 45.4% Other, 94, 2.3% Gravity Hand Bucket Other RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 Methods of Storage The region had 123,258 crop growing households storing their produce in locally made traditional structures (76% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 28,749 (18%). This was followed by improved locally made structures (3,647 households, 2%), air tight drums (1,779 households, 1%) and modern stores (846 households, 1%), unprotected piles (779 households, 1%) and modern store (846 households, 1%) and other methods (2,573, 2%). Locally made traditional structures was the dominant storage method in all districts, with the highest percent of households in Tandahimba using this method (91% of the total number of households storing crop products). This was followed by Mtwara Urban (86%), Newala (83%), Masasi (73%) and Mtwara rural (59%), (Chart 3.80). The highest percent of households using sacks and open drum was in Mtwara rural districts (36% of the total number of households storing crops), followed by Masasi (19%), Newala and Mtwara urban (14%) each and Tandahimba (4%). Duration of Storage Most households (44% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of more than 6 months (38%). The households that stored their crops for a period of less than 3 months constituted eighteen percent of the households storing crops. Most households that stored beans and pulses stored for a period of 3 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months. (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mtwara urban district (54%) followed by Mtwara rural (48%), Newala and Tandahimba (46% each) and Masasi (41%) (Map 3.34). Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Mtwara Rural Newala Masasi Tandahimba Mtwara Urban District Percent of househol Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other 0 30,000 60,000 90,000 Number of househ Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.86 Number of households by Storage Methods - MTWARA Unprotected Pile, 779, 1% Improved Locally Made Crib, 3,647, 2% Other, 2,573, 2% Airtight Drams, 1,779, 1% Modern Store, 846, 1% Sacks / Open Drum, 28,749, 18% Locally Made traditional Crib, 123,258, 76% RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 District comparison of duration of storage cannot be done for all crops combined. The analysis has therefore been done for maize only as it is the most commonly stored crop. In general, the quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, there are districts where households tored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirements of the households and not to sell during the “off-season” when the farm gate price of maize is higher. Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for the purpose of household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 68.5 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at a higher price. A high percent of the stored permanent crops was used for household consumption as was the case for cashewnuts (6.7%). This was followed by selling at a higher price (18.3%). (Chart 3.90). The Magnitude of Storage Loss About 81 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as tobacco, cashewnut, groundnut and bambara- nuts. The proportion of households that reported a loss of more than a quarter was greatest for maize, sorghum and millet (3% of the total number of households that stored crops). This was followed by paddy (1%) and groundnuts and bambaranut (1%). All households that stored cash crops such as cashewnut had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (86%) (Table 3.10). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Mtwara Rural 17,871 1,586 874 80 20,411 Newala 30,275 6,203 1,160 296 37,934 Masasi 62,987 11,720 1,896 1,289 77,892 Tandahimba 19,473 4,388 384 0 24,245 Mtwara Urban 982 168 0 0 1,149 Total 131,588 24,064 4,315 1,665 161,631 Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 Masasi Newala TandahimbaMtwara Rural Mtwara Urban District Quantity (tonn 0 5 10 15 20 25 30 % Store Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Househo Crop MaizeBeans & PulsesPaddy Sorghum & Millet Groundnuts/Bambara Nuts CashewnutWheat Coffee Tobacco Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.3.6.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Mtwara region (210,760 households, 92% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 90%). Mtwara urban and Mtwara rural had the lowest percent of households processing crops (89% and 83% of crop growing households respectively) (Chart 3.91b). Processing Methods Most crop processing households processed their crops on-farm by hand a method used by 113,971 households (54% of households that processed crops).. This was followed by those processing by neighbour’s machines (86,481 households, 41%) and trader (2,294 households, 1%). The remaining methods of processing were used by very few households each method by less than one percent. Although processing by hand and machine were the most common processing method in all districts in Mtwara region, however district differences existed. Tandahimba had a higher percent of hand processing than other districts (81.3%) followed by Mtwara rural (79.0%), Mtwara Urban (74.9%) and Newala (53.5%). Processing by neighbour machine was more common in Masasi and Newala (67.2% and 39.2% respectively), whilst processing by factory was more prevalent in Mtwara Urban (7.2%) (Chart 3.92). Main Agro-processing Products Two types of products can be produced from agro- processing namely the main product and the by-product. The main product is the major product after processing and the by-product is the secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. Chart 3.91a Households Processing Crops Households not Processing, 18,554, 8% Households Processing, 210,760, 92% 60 80 100 Percent of Households Processing Masasi Newala Tandahimba Mtwara Rural Mtwara Urban District Chart 3.91b Percentage of Households Processing Crops by District Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal 92% Other 0.1% Fiber 0.2% Oil 0.4% Grain 7% Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Tandahimba Mtwara Rural Mtwara Urban Newala Masasi District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Co-operative Union By Trader By Factory Other RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 The main processed product was flour/meal with 193,922 households processing crops into flour (92% of the households processing crops) followed by grain with 15,423 households (7%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 35.8 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 44,086 households (21%) followed by shell (16,575 households, 8%), Husks (12,415 households, 6%). The remaining by-products were produced by a small number of households (Chart 3.94). Main Use of Primary Processed Products Primary processed products were used for households/ human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 97 percent of the total households that processed crop (Chart 3.95). Newala was the only district that used primary products for animal consumption. Out of 873 households that sold processed products, 871 were from Masasi (74% of the total number of households selling processed products in the region), followed by Newala with 99 households (11.3%), Tandahimba with 97 households (11.1%) and Mtwara urban with 31 households (3.6%) (Chart 3.96). Compared to other districts in Mtwara region, Mtwara rural had the highest percent of households that sold processed products. This was followed by Tandahimba (0.72), Newala and Mtwara urban districts had (0.25%) each. Outlets for Sale of Processed Products Most households that sold processed products sold them to neighbours (7,933 households, 68% of households that sold crops). This was followed by selling to trader at farm (890 households, 8%), local market and trade stores (557 households, 5%), Farmers Associations (584 households, 5%), marketing co-operatives ( 295 households, 3%), secondary market (97 households, 1%) and large scale farm (94 households, 1%). (Chart 3.97). Chart 3.94 Number of Households by Type of By-product Other, 91, 0.0% Oil, 354 0.2% Husk, 12,415, 6% Bran, 44,086 21% Cake, 286 0.1% Fiber, 513, 0.2% Shell, 16,575 8% Juice, 561, 0.3% Chart 3.95 Use of Processed Product Household/ human consumption, 436,694, 97% Fuel for Cooking, 973 , 0% Sale Only, 9,289 , 2% Did Not Use, 3,226 , 1% Animal Consumption, 813 , 0% 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Percentage of households Masasi Newala Tandahimba Mtwara Urban Mtwara Rural District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Other, 1,125, 9% Neighbours, 7,933, 68% Local Market / Trade Store, 557, 5% Secondary Market, 97, 1% Trader at Farm, 890, 8% Large Scale Farm, 94, 1% Farmers Association, 584, 5% Marketing Co- operative, 295, 3% RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 There were large differences between districts in the proportion of households selling processed products to neighbours with Tandahimba district having the largest percent of households selling to neighbours (77%), whereas Newala had only 51 percent. Newala had the largest percent of households selling to the local markets/trade stores (11%). Compared to other districts, Masasi had the highest percent of households selling processed products to traders at farm. In Masasi, the sale of processed produce to farmer associations was most prominent compared to other districts. The district that had the highest proportion of household selling processed products to marketing cooperative was Tandahimba. 3.3.6.3 Crop Marketing The number of households that reported selling crops was 149,163 which represent 65.0 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Newala (70%) followed by Tandahimba (69%), Mtwara rural (66%), Masasi (61%) and Mtwara urban (46%) (Chart 3.99 and Map 3.35). Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (85% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (5%), lack of market information (3%), lack of buyers (2%), high transport costs (2%) and lack of transport (1%). Other marketing problems are minor and represented by 2 percent of the total reported problems. Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Masasi Newala Mtwara Rural Tandahimba Mtwara Urban District Number of Households 0 20 40 60 80 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Farmers Association Problems 0% Other 2% Open Market Price Too Low 85% Co-operative Problems 0% Transport Cost Too High 2% Lack of Market Information 3% Market too Far 5% No Transport 1% No Buyer 2% Chart 3.98 Percent of Household Selling Processed Products by Outlet for Sell and District 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Tandahimba Masasi Mtwara Urban Mtwara Rural Newala District Percent of Households Selling Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 1,307 29,648 28,990 30,353 58,866 45.8% 65.7% 69.3% 70.5% 61.1% 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Mtwara Urban Mtwara Rural Tandahimba Newala 21.7% 21.7% 26.5% 40.8% 33.3% Masasi 36 to 45 27 to 36 18 to 27 9 to 18 0 to 9 Number of Households and Percent of Total Households Selling Crops by District MAP 3.34 MTWARA MAP 3.35 MTWARA Percent of Households Storing Crops for 3 to 6 Months by District Tanzania Agriculture Sample Census Number of Households Households Selling Crops Percent of Households Storing Crops Percent of Households Storing Crops Number of Households Households Selling Crops Percent of Planted Area With no Fertilizer Applied Percent of Households Households Selling Crops RESULTS 62 RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 86 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts except for Mtwara Urban and Tandahimba where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (39% and 13% respectively). 3.3.7 Access to Crop Production Services 3.3.7.1 Access to Agricultural Credit The census result shows that in Mtwara region very few agricultural households (1,509, 0.7%) accessed credit out of which 1,410 (93%) were male-headed households and 99 (7%) were female headed households. In Masasi, Tandahimba and Mtwara Urban districts only male headed households accessed agricultural credit whereas in Newala district both male and female headed households accessed agricultural credit. There was no household which received credit in Mtwara rural district (Table 3.12). Source of Agricultural Credit The major agricultural credit providers in Mtwara region were cooperative which provided credit to 716 agricultural households (47% of the total number of households that accessed credit), followed by family, friends and relatives (30%), saving and credit society (11%), commercial bank (10%) and religious organizations/Non Governmental Organizations/ projects (2%) (Chart 3.101). Cooperatives were the sole source of credit in Tandahimba district as well as the major credit facility in Newala district. Family, friends and relatives were somehow greater credit providers in Mtwara urban district compared to religious Organization/NGO/Project. (Chart 3.102). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 94,174 86.2 Other 7,717 7.1 Price Too Low 3,515 3.2 Trade Union Problems 1,961 1.8 Co-operative Problems 769 0.7 Market Too Far 158 0.1 Government Regulatory Board Problems 422 0.4 Farmers Association Problems 582 0.5 Total 109,299 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Newala 291 75 99 25 390 Masasi 964 100 0 0 964 Tandahimba 96 100 0 0 96 Mtwara Urban 58 100 0 0 58 Mtwara Rural 0 0 0 0 0 Total 1,410 93 99 7 1,509 Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Saving & Credit Society 11% Commercial Bank 10% Co-operative 47% Family, Friend and Relative 30% Religious Organisation / NGO / Project 2% Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% New ala Masasi Tandahimba Mtw ara Urban District Percent of Households Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Religious Organisation / NGO / Project RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on agro-chemicals (79%), followed by hiring labour (10%), tools/equipment (9). The proportion of credits intended to be used for livestock rearing was very low (2%) (Chart 3.103). Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 68 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (20.2%), followed by “not wanting to go into debt” (5.9%) The rest of the reasons were collectively reported by about 7 percent of the households. 3.3.7.2 Crop Extension The number of agricultural households that received crop extension was 40,456 (18% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Tandahimba having a relatively high proportion of households (24%) that received crop extension messages in the district followed by Mtwara rural (20%), Masasi (18%), Mtwara urban (12%) and Newala (8%) (Chart 3.106 and Map 4.36). Chart 3.104 Reasons for not Using Credit (% of Households) Interest rate/cost too high, 2,039, 1% Other, 393, 0% Credit granted too late, 1,121, 0% Not needed, 5,384, 2% Difficult bureaucracy procedure, 6,300, 3% Did not want to go into debt, 13,458, 6% Not available, 46,096, 20% Don't know about credit, 54,133, 24% Did not know how to get credit, 98,881, 44% Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 188,858, 82% Households Receiving Extension , 40,456, 18% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 Masasi Tandahimba Mtwara Rural Newala Mtwara Urban District Number of Households 0 20 40 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 103 Proportion of Households Receiving Credit by Main Purpose of the Credit Tools / Equipment, 159, 9% Labour, 162, 10% Livestock, 26, 2% Agro-chemicals, 1,324, 79% RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 Sources of Crop Extension Messages Of the households receiving extension advice the government provided the greatest proportion (97.5%, 39,227 households). NGOs provided 0.9 percent, large scale farms 1.2 percent and the cooperative 0.4 percent. (Chart 3.107), however district differences existed with the proportion of the households receiving advice from government services ranging from 90.7 percent in Mtwara Urban to 99.1 percent in Masasi district. Quality of Extension An assessment of the quality of extension indicates that 68.2 percent of the households receiving extension ranked the service as being good followed by very good 20.1%), average (10.1 %), poor (1.2%) and no good (0.4%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.3.8 Access to Inputs Access to inputs in this section refers to all crop growing households in Mtwara region regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm eg. improved seeds, fungicides, inorganic fertiliser and herbicides. In Mtwara region pesticides/fungicides were used by 52,961 households which represent 23.1 percent of the total number of crop growing households. This was followed by households using farm yard manure (4.9%), improved seeds (3.7%), inorganic fertiliser (3.2%), compost (2.2%), and herbicide (0.1%) (Table 2.14). Table 2.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Insecticide/Fungicide 52,961 23.1 176,241 76.9 Farm Yard Manure 11,334 4.9 217,868 95.1 Improved Seeds 8,531 3.7 220,671 96.3 Inorganic Fertiliser 7,333 3.2 221,869 96.8 Compost 5,038 2.2 224,164 97.8 Herbicide 189 0.1 229,013 99.9 Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 1.2% Cooperative 0.4% NGO / Development Project 0.9% Government 97.5% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 27,511, 68.2% Average, 4,069, 10.1% Poor, 488, 1.2% No Good, 178, 0.4% Very Good, 8,115, 20.1% RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.3.8.1 Inorganic Fertilisers Smallholders that used inorganic fertilisers in Mtwara region mostly purchased them from the local market/trade store (89.7% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Access to inorganic fertiliser was mainly more than 20 km from the household with 28 percent of the households residing 20 km and above from the source, followed by between 3 and 10 km (27%) and between 10 and 20 km (24%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households (21%) responding to “not available” as the reason for not using them, it may be assumed that access to inorganic fertilisers was not the main reason for not using them. Other reasons such as cost are more important with 69 percent of households responding to cost factors as the main reason for not using the fertilisers. In other words, if the cost was affordable the demand would be higher and inorganic fertiliser would be made more available. More smallholders used inorganic fertilisers in Newala than in other districts in Mtwara region with 81 percent of households using inorganic fertilisers, followed by Masasi (13%) and Tandahimba (4%). Other districts used very little inorganic fertilisers. 3.3.8.2 Improved Seeds The percent of crop growing households that used improved seeds was 4 percent. Most of the improved seeds were from the local market/trade store (49.3%). Other less important sources of improved seed were neighbours (27.7%), projects (4.0%), farmer groups (3.8%), locally produced by households (3.0) and large scale farms (3.0%). Only 1.5 percent of households using improved seed obtain them from co-operatives (Chart 3.111). Chart 3.110 Percent of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) P ercent o f H o useho lds Chart 3.111 Number of Households by Source of Improved Seed 0.2 3.0 1.5 3.0 3.8 4.0 7.7 27.7 49.3 0 1,000 2,000 3,000 4,000 5,000 Local Market / Trade Store Neighbour Other Development Project Local Farmers Group Locally Produced by Household Large Scale Farm Co-operative Secondary Market Source of Improved Seed Number of Households Chart 3.109 Number of Households by Source of Inorganic Fertiliser 86.1 3.5 2.6 1.3 1.3 1.3 3.9 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 Local Market/Trade Store Co-operative Local Farmer Group Locally Produced Crop Buyer Neighbour Other Source of Inorganic Fertiliser Number of Household RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 Access to improved seed was better than access to chemical inputs with 59 percent of households obtaining the input within 1 km of the household dwelling (Chart 3.112). The districts that mostly use improved seeds most was Mtwara rural with 52.3 percent of the total number of households using improved seeds followed by Masasi (24.4%) and Tandahimba (14.5%). Use of improved seeds in other districts was very little (Map 3.37). 3.3.8.3 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (57.7% of the total number of fungicide users), followed by cooperatives (32.2%). Other sources of insecticides/ fungicides were of minor importance (Chart 3.113). Chart 3.114 shows that there was no distinct pattern for the distance to the source of insecticides/fungicides. The small number of households using insecticides/fungicides coupled with the 12 percent of households responding to “not available” as the reason for not using them it may be assumed that access was not the main reason for not using the insecticides/fungicides. Other reasons such as cost were more important with 75 percent of households responding to cost factors as the main reason for not using them. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicide were used more in Tandahimba district (33.4 percent of the total number of households that used fungicides in the region), followed by Masasi (24.6%), Newala (21.3%), and Mtwara rural (19.8). Insecticides/fungicides use in Mtwara Urban was very minor. 3.3.8.4 Tree Planting The number of households involved in tree farming was 2,088 representing 1 percent of the total number of agriculture households (Chart 3.115). Chart 3.112 Percentage of Households reporting Distance to Source of Improved Seed 0 20 40 60 80 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.113 Number of Households by Source of Insecticide/fungicide 57.7 32.2 4.1 3.4 0.9 0.5 0.3 0.3 0.2 0.3 0 10,000 20,000 30,000 40,000 Local Market / Trade Store Co-operative Neighbour Local Farmers Group Other Development Project Locally Produced by Household Crop Buyers Secondary Market Large Scale Farm Source of Insecticide/fungicide Number of Households Chart 3.114 Percentage of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 40 50 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.115 Number of Households with Planted Trees Growing trees, 2,088, 1% Not growing trees, 227,226, 99% Mtwara Urban Mtwara Rural Tandahimba Newala 1,754 58 3,853 658 955 1.8% 2% 8.5% 1.6% 2.2% Masasi 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 342 9,100 10,236 3,344 17,435 12% 20.2% 24.5% 7.8% 18.1% 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Number and Percent of Crop Growing Households using Improved Seed by District MAP 3.36 MTWARA MAP 3.37 MTWARA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Tanzania Agriculture Sample Census Number of Households Growing Crops Using Improved Seed Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Number of Households Growing Crops Using Improved Seed Percent of Households Receiving Crop Extension Services Percent of Households Growing Crops Using Improved Seed RESULTS 68 RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 The number of trees planted by smallholders on their allotted land was 23,051 trees. The average number of trees planted per household planting trees was 11 trees. The main species planted by smallholders is Senna spp (16,086 trees, 75%), followed by Acacia spp (2,095, 10%), and Moringa spp (1,815, 9%). The remaining trees species were planted in comparatively small numbers (Chart116.). Masasi had the largest number of smallholders with planted trees (49.5%) and the trees were dominated by senna spp. This was followed by Mtwara urban (30.1%) with the trees also dominated by senna spp and to a lesser extent Azadritachta spp, then Newala (20.4%) with most of the trees being mainly senna spp (Chart 3.117 and Map 3.38.). For most mallholders (66%) the trees were scattered around the fields. The proportion of households that planted trees on field boundaries was 37 percent. (Chart 3.118). The main purpose of planting trees is to obtain shade (34.7%). This was followed by poles (19.5%), wood for fuel (18.35%) and planks/timber (9.3%). (Chart 3.119). Chart 3.116 Number of Planted Trees by Species - MTWARA 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Senna Spp Acacia Spp Moringa Spp Gravellis Melicia excelsa Others Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and Districts 0 5,000 10,000 15,000 Masasi New ala Mtw ara Urban District Number of Trees Senna Spp Acacia Spp Moringa Spp Gravellis Melicia excelsa Azadritachta Spp Chart 3.118 Number of Trees Planted by Location Scattered in field, 15,279, 66% Field boundary, 7,772, 34% Chart 3.119 Percentage of Households by Purpose of Planted Trees 34.7 19.5 18.3 18.1 9.3 0.0 10.0 20.0 30.0 40.0 50.0 Shade Poles Fuel for Wood Other Planks / Timber Use Percent of Households RESULTS –Irrigation and Erosion Control Facilities _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 3.3.9 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 1,474 which represents 1 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Mtwara urban district (3%) and followed by Masasi (1%).) (Chart 3.121). Erosion control bunds accounted for 99.4 percent of the total number of structures, followed by water harvesting bunds (0.4%) and drainage ditches (0.2%) (Chart 3.122 and Map 3.39). Erosion control bunds were 40,232 and all of them were in Masasi and Mtwara Urban districts. Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 227,840, 99% Households with facilities, 1,474 , 1% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 1 3 0 0 0 0 200 400 600 800 1,000 1,200 1,400 Masasi Mtwara Urban Newala Mtwara Rural Tandahimba District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 99.4 0.4 0.2 0 15,000 30,000 45,000 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches T y p e o f F a c i l ity Number of Structures Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 841 0 0 95 39,542 29.8% 0% 0% 0.2% 41% 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 225 0 0 574 1,289 7.9% 0% 0% 1.3% 1.3% 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Number and Percent of Households with Water Harvesting Bunds by District MAP 3.38 MTWARA MAP 3.39 MTWARA Number and Percent of Smallholder Planted Trees by District Tanzania Agriculture Sample Census Number of Households with Water Harvesting Bunds Number of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Percent of Households with Water Harvesting Bunds RESULTS 71 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.4 LIVESTOCK RESULTS 3.4.1 Cattle Production The total number of cattle in the region was 17,158. Cattle were the third most dominant livestock type in the region followed by pigs. The region had 0.1 percent of the total number cattle population on Tanzania Mainland. 3.4.1.1 Cattle Population The number of indigenous cattle in Mtwara region was 16,383 (95.5 % of the total number of cattle in the region), 775 cattle (4.5%) were dairy breeds and there were no beef breeds. The census results show that 3,567 livestock keeping households in the region (1.6% of total agricultural households) kept 0.02 million cattle. This was equivalent to an average of 5 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Masasi which had about 9,346 cattle (54.5% of the total number of cattle in the region). This was followed by Mtwara rural (4,775 cattle, 27.8%), Newala (1,891 cattle, 11.0%) and Tandahimba (1,083 cattle, 6.3%). Mtwara Urban district had the least number of cattle (63 cattle, 0.4%). (Chart 3.123 and Map 3.40). However Mtwara Rural and Newala districts had the highest density (3 head per km2 ) (Map 3.41). Although Masasi district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and there were no beef cattle. Mtwara rural district had the largest number of diary cattle in the region (Chart 3.124). 3.4.1.2 Herd Size Seventy nine percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herds size of 6-30 cattle accounted for about 56 percent of all cattle in the region. There was no cattle rearing households had herds of size of 31- 100 cattle. All cattle rearing households had herds of size 1-30 cattle. 0 1 2 3 4 5 6 7 8 9 10 Number of Cattle ('000') Masasi Mtwara Rural Newala Tandahimba Mtwara Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District - 2,000 4,000 6,000 8,000 10,000 Masasi Mtwara Rural Newala Tandahimba Mtwara Urban Districts Number of Cattle Indigenous Beef Dairy Mtwara Urban Mtwara Rural Tandahimba Newala 1.1 3.4 1.3 3 2.4 Masasi 2.4 > 1.8 to 2.4 1.2 to 1.8 0.6 to 1.2 0 to 0.6 Mtwara Urban Mtwara Rural Tandahimba Newala 63 4,775 1,083 1,891 9,346 Masasi 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Cattle Density by District as of 1st October 2003 MAP 3.40 MTWARA MAP 3.41 MTWARA Cattle Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Cattle of per Sq Km Number of Cattle Cattle Population Cattle Density RESULTS 73 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.4.1.3 CattlePopulation Trend During the 8-year period cattle population in Mtwara increased from 15,119 in 1995 to 17,158 cattle in 2003. This implies an overall positive annual growth rate of -1.6 percent (Chart 3.125). There was an increase in number of cattle over the 4-year period from 1995 to 1999 at an annual rate of 7.81 percent whereby the number increased from 15,119 to 20,412. However, the number of cattle decreased from 20,412 in 1999 to 17,158 in 2003 at the negative annual growth rate of -4.25 percent. 3.4.1.4 Improved Cattle Breeds The total number of improved cattle in Mtwara region was 775 (all dairy breeds). The diary cattle constituted 4.5 percent of the total cattle and 100 percent of improved cattle in the region. There were no beef cattle breeds in the region. The number of dairy cattle increased from 445 in 1999 to 775 in 2003 at an annual growth rate of 14.9 percent. The annual rate of growth for the period from 1995 to 1999 was not determined due to lack of information for the year 1995 (Chart 126). 3.4.2. Goat Production Goat rearing was the most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Mtwara region ranked 18 out of the 21 regions with 1.7 percent of the total goats on the Mainland. 3.4.2.1 Goat Population The number of goat-rearing-households in Mtwara region was 32,950 (14.4% of all agricultural households in the region) with a total of 196,675 goats giving an average of 6 head of goats per goat-rearing-household. Newala had the largest number of goats (62,594 goats, 32% of all goats in the region), followed by Tandahimba (60,634 goats, 31%), Mtwara rural (36,126 goats, 18%), and Masasi (35,493 goats, 18%). Mtwara Urban district had the least number of goats (1,828 goats, 1%) (Chart 3.127 and Map 3.42). Newala district had also the highest density (101 heads per km2) (Map 3.43). 0 40 80 N u m b er of G oats ('000'). Newala Tandahimba Mtwara Rural Masasi Mtwara Urban District Chart 3.127 Total Number of Goats ('000') by District 15,119 20,412 17,158 - 10,000 20,000 30,000 Number of cat 1995 1999 2003 Year Chart 3.125 Cattle Population Trend - 445 775 - 500 1,000 Number of cat 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend Mtwara Rural Mtwara Urban Tandahimba Newala 9 25.7 31.6 70.9 100.7 Masasi 80 > 60 to 80 40 to 60 20 to 40 0 to 20 Mtwara Urban Mtwara Rural Tandahimba Newala 1,828 36,126 60,634 62,594 35,493 Masasi 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Goat Density by District as of 1st October 2003 MAP 3.42 MTWARA MAP 3.43 MTWARA Goat Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Goat of per Sq Km Number of Goat Goat Population Goat Density RESULTS 75 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.4.2.2 Goat Herd Size Forty eight percent of the goat-rearing households had herds of size 1-4 goats with an average of 2 goats per goat rearing household. Ninety four percent of total goat-rearing households had herds of size 1-14 goats and owned 78 percent of the total goats in the region resulting of an average of 5 goats per goat-rearing households. The region had 181 households (0.5%) with herd sizes of 40 or more goats each (7,227 goats in total), resulting in an average of 40 goats per household. 3.4.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 96 percent of the total goats in Mtwara region. Improved goats for meat and diary goats constituted 2 percent of total goats each. 3.4.2.4 Goat Population Trend The overall average annual growth rate of goat population from 1995 to 2003 was -4.8 percent. This negative trend implies eight years of population decrease from 290,444 in 1995 to 196,675 in 2003. The number of goats decreased from 290,444 in 1995 at an estimated average annual growth rate of -8.7 percent to 201,586 in 1999. From 1999 to 2003, the goat population decreased at an average annual growth rate of -0.6 percent (Chart 128). 3.4.3. Sheep Production Sheep rearing was the second most important livestock keeping activity in Mtwara region after goats. The region ranked 17 out of 21 Mainland regions and had 0.6 percent of all sheep on Tanzania Mainland. 3.4.3.1 Sheep Population The number of sheep-rearing households was 3,487 (2% of all agricultural households in Mtwara region) rearing 25,275 sheep, giving an average of 7 heads of sheep per sheep- rearing household. The district with the largest number of sheep was Tandahimba with 11,731 sheep (46%of total sheep in Mtwara region) followed by Newala (5,428 sheep, 22%), Mtwara rural (4,567 sheep, 18%) and Masasi (3,361 sheep, 13%). Mtwara urban District had the least number of sheep (188 sheep, 1%) (Chart 3.129 and Map 3.44). Tandahimba district also had the highest density (14 head per km2 ) (Map 3.45). Sheep rearing was dominated by indigenous breeds which accounted for all sheep kept in the region. 0 5,000 10,000 15,000 Number of sheep Tandahimba Newala Mtwara Rural Masasi Mtwara Urban District Chart 3.129 Total Number of Sheep by District 290,444 201,586 196,675 - 200,000 400,000 Number of go 1995 1999 2003 Year Chart 3.128 Goat Population Trend Mtwara Urban Mtwara Rural Tandahimba Newala 3.3 3.2 13.7 8.7 0.9 Masasi 12 to 15 9 to 12 6 to 9 3 to 6 0 to 3 Mtwara Urban Mtwara Rural Tandahimba Newala 188 4,567 11,731 5,428 3,361 Masasi 8,000 > 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Sheep Density by District as of 1st October 2003 MAP 3.44 MTWARA MAP 3.45 MTWARA Sheep Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Sheep of per Sq Km Number of Sheep Sheep Population Sheep Density RESULTS 77 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 3.4.3.2 Sheep Population Trend The overall annual growth rate of the sheep population over the eight-year period from 1995 to 2003 is estimated at 5.5 percent. The population increased at an average annual rate of growth of 0.1 percent from 16,518 in 1995 to 16,566 in 1999. From 1999 to 2003, sheep population increased at an average annual rate of growth of 11.1 percent (Chart 3.130). 3.4.4. Pig Production Piggery was the least important livestock keeping activity in the region after goats, sheep and cattle. The region ranked at 14 out of 21 Mainland regions and had 0.6 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Mtwara region was 3,355 (2% of the total agricultural households in the region) rearing 6,293 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Masasi with 5,826 pigs (93% of the total pig population in the region) followed by Newala (467 pigs, 7%), (Chart 3.131 and Map 3.46). Masasi district also had the highest density (2 head per km2 ) (Map 3.47). No pigs were recorded in Tandahimba, Mtwara rural and Mtwara urban districts. 3.4.4.1 Pig Population Trend The overall average annual growth rate of the pig population over the eight-year period from 1995 to 2003 was 7.5 percent. During this period the population grew from 3,524 in 1995 to 6,293 in 2002. The pig population increased from 3,524 in 1995 to 5,812 in 1999 at a higher average annual growth rate of 13.3 percent. The growth rate dropped to 2.0 percent during the following four years from 1999 to 2003 in which pig population increased from 5,812 to 6,293 (Chart 3.132). 0 2,000 4,000 6,000 8,000 Number of Pigs Masasi Newala District Chart 3.131 Total Number of Pigs by District 16,518 16,566 25,275 - 100,000 Number of she 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 3,524 5,812 6,293 - 4,000 8,000 Number of p 1995 1999 2003 Year Chart 3.132 Pig Population Trend Newala Mtwara Urban Mtwara Rural Tandahimba 1.5 0.8 0 0 0 Masasi 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Mtwara Urban Mtwara Rural Tandahimba Newala 0 0 0 467 5,826 Masasi 4,000 > 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Pig Density by District as of 1st October 2003 MAP 3.46 MTWARA MAP 3.47 MTWARA Pig Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Pig of per Sq Km Number of Pig Pig Population Pig Density RESULTS 79 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 80 3.4.5 Chicken Production The poultry sector in Mtwara region was dominated by chicken production. The region contributed 2.1 percent to the total chicken population on Tanzania Mainland. 3.4.5.1 Chicken Population The number of households keeping chicken was 96,984 raising about 710,132 chickens. This gives an average of 7 chickens per chicken-rearing household. In terms of total number of chickens in the country, Mtwara region was ranked nineteenth out of the 21 Mainland regions. The District with largest number of chickens was Masasi (298,246 chickens, 42% of the total number of chickens in the region) followed by Tandahimba (158,038, 22%), Newala (128,122, 18%), Mtwara rural (115,205, 16%) and Mtwara urban (10,521 chickens, 1%). (chart 133 and Map 3.48) 3.4.5.2 Chicken Population Trend The overall average annual chicken population growth rate during the eight-year period from 1995 to 2003 was - 1.7 percent. The population decreased at a rate of -1.2 percent from 1995 to 1999 after which the rate decreased further to -2.2 percent over the four year period from 1999 to 2003 (Chart 3.134 and Map 3.49). Ninety nine percent of all chicken in Mtwara region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.4.5.3 Chicken Flock Size The results indicate that about 94 percent of all chicken-rearing households were keept 1-19 chickens at an average of 6 chickens per holder. About 6 percent of holders were reported to be keeping the flocks of size 20 to 99 chickens at an average of 31 chickens per holder. Only 0.3 percent of holders had flock sizes of more than 100 chickens at an average of 285 chickens per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken per Households 1-4 53,208 55 125,735 2 5-9 22,734 23 147,040 6 10 -19 15,273 16 193,532 13 20-29 3,681 4 86,977 24 30-39 858 1 27,688 32 40-49 258 0 11,117 43 50-99 720 1 45,999 64 100+ 253 0 72,045 285 Total 96,984 100 710,132 7 0 100,000 N um ber o f C hicke Masasi Newala TandahimbaMtwara RurMtwara Urb District Chart 3.133 Total Number of Chickens by District 815,351 777,543 710,132 - 1,000,000 Number of Chick 1995 1999 2003 Year Chart 3.134 Chicken Population Trend Mtwara Urban Mtwara Rural Tandahimba Newala 182.1 81.9 184.8 206.1 75.5 Masasi 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 Mtwara Urban Mtwara Rural Tandahimba Newala 10,521 115,205 158,038 128,122 298,246 Masasi 240,000 to 300,000 180,000 to 240,000 120,000 to 180,000 60,000 to 120,000 0 to 60,000 Chicken Density by District as of 1st October 2003 MAP 3.48 MTWARA MAP 3.49 MTWARA Chicken Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Chicken of per Sq Km Number of Chicken Chicken Population Chicken Density RESULTS 81 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.4.5.4 Improved Chickens (layers and broilers) The overall averageannual growth rate for layers during the eight-year period from 1995 to 2003 was 3.4 percent during which the population grew from 1,938 to 2,627. During four-year period from 1995 to 1999 layers chicken population decreased at an average annual rate of growth of -27.7 percent from 1,938 layers in 1995 to 529 layers in 1999. The rate increased to 49.3 percent per annum over the following four years in which the number of layers increased from 529 in 1999 to 2,627 in 2003. The number of improved chicken was most significant in Masasi district followed by Mtwara rural district (Chart 3.135). The overall average annual growth rate for broilers during the eight-year period from 1995 to 2003 was 170.7 percent during which the population grew from 0 to 2,886. The annual growth rate was highest (855.9%) during the four-year period with the population increasing from 0 in 1995 to 8,352 in 1999. The broiler population exhibited a decreasing trend at the rate of -23.3 percent per annum over the next four-year period resulting in a decrease from 8,352 in 1999 to 2,886 in 2003 (Chart 3.136). 3.4.6. Other Livestock There were 8,885 ducks, 20,607 turkeys and 589 rabbits raised by rural agricultural households in Mtwara region. Table 3.16 indicates the number of other livestock kept in each district. The biggest number of ducks in the region was found in Masasi District (54% of all ducks in the region), followed by Newala (35%) and Mtwara rural (8%). Tandahimba district had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Masasi district only (Table 3.16). 3.4.7 Pest and Parasite Incidence and Control The results indicate that 16 percent and 8 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there were a predominance of tick related diseases over tsetseflies related diseases. Incidences of both problems were highest in Mtwara rural district but lowest in Newala district (Map 3.50). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Other Mtwara Rural 719 0 0 0 Newala 3,143 0 589 838 Masasi 4,839 20,607 0 0 Tandahimba 184 0 0 0 Total 8,885 20,607 589 838 Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. - 20 40 Mtwara Rur Masasi Tandahimba Mtwara Urb Newala District Percent Ticks Tsetseflies 1,963 820 318 - 184 - 163 - - 2,066 - 500 1,000 1,500 2,000 2,500 Number of Chick Masasi Mtwara Rur Tandahimba Mtwara Urb Newala District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers 1,938 - 529 8,352 2,627 2,886 - 10,000 Number of lay 1995 1999 2003 Year Chart 3.136 Layers Population Trend Mtwara Urban Mtwara Rural Tandahimba Newala 0 495 559 95 802 0% 14.5% 8.1% 1.3% 13.8% Masasi 800 > 600 to 800 400 to 600 200 to 400 0 to 200 MAP 3.50 MTWARA Number and Percent of Households Infected with Tsetse by District Tanzania Agriculture Sample Census Number of Households Infected with Tsetse Number of Households Infected with Tsetse Percent of Households Infected with Tsetse RESULTS 83 RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 The most practiced method of tick controll was spraying with 18 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (4%) and other traditional methods like hand picking (28%). However, 50 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 22 percent of livestock-rearing households. However, 78 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.4.7.1 Deworming Livestock rearing households that dewormed their animals were 4,736 (19% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 77 percent, goats (7%), sheep (3%) and pigs (3%) (Chart 3.138). 3.4.8. Access to Livestock Services 3.4.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 10,211, representing 41 percent of the total livestock- rearing households and 4.5 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 94 percent of all households receiving livestock extension services. The rest were other. About 36 percent of livestock rearing households described the general quality of livestock extension services as being good, 15 percent said they were average and 14 percent said they were very good. However, 2 percent of the livestock rearing households said the quality was not good whilst 32 percent described them as poor (Chart 3.139). 3.4.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 69 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 31 percent of the households accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected district was Tandahimba district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Mtwara Urban District was the least affected because about 63 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.141). - 25 50 75 100 Percent Mtwara Rur Newala Masasi Tandahimba Mtwara Urb District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 2% Very Good 14% Good, 36% Average, 15% Poor, 32% RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.4.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 5,647 (98% of livestock rearing households that accessed the village watering point in Mtwara region) whilst 98 households (2%) resided between 5 and 9 kms. (Chart 3.142). Masasi district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Newala, and Mtwara rural districts. In Newala district about 6 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.4.9. Animal Contribution to Crop Production 3.4.9.1 Use of Draft Power There is no agriculture household in Mtwara region that used draft animals to cultivate land (Chart 3.144). There were no households that used draft animals to cultivate all districts of Mtwara region. (Chart 3.145). Chart 3.140 Number of Households by Distance to Verinary Clinic Less than 14km, 23,658, 10% More than 14km, 203,826, 90% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 30,000 60,000 90,000 Masasi Newala Tandahimba Mtwara Rur Mtwara Urb District N um ber o f H o useho lds Less than 14 kms More than 14kms Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 5,647, 98% 5-9 kms, 98, 2% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 1,000 2,000 Masasi Newala Mtwara Rur Mtwara Urb Tandahimba District Number of Households Less than 5 kms 5-9 kms 3.144 Number of Households Using Draft Amimals Using draft animal, 0, 0.0% Not using draft animal, 229,314, 100% 0 50 100 Number of Households Mtwara Rural Newala Masasi Tandahimba Mtwara Urban District Chart 3.145 Number of Households Using Draft Animals by District - MTWARA RESULTS – Livestock Production _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 3.4.9.2 Use of Farm Yard Manure The number of Households using organic fertilizers in Mtwara region was 12,123 (5% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertilisers was 12,400 hectares of which 3,252 hectares (65% of the total area applied with organic fertilizers or 3.1% of the area planted with annual crops and vegetables in Mtwara region during the long rainy season) was applied with farm yard manure. 3.12.9.3 Use of Compost Only 4.369 ha (35% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Newala district with 1,216 hectares (37% of the total area applied with farm yard manure) followed by Tandahimba (1,088 ha, 33%), Masasi (572 ha, 18%), Mtwara rural (316 ha, 10%) and Mtwara urban (59 ha, 3%) (Chart 3.147 and Map 3.51). 3.5 Fish Farming The number of households involved in fish farming in Mtwara region was 477, representing 0.2 percent of the total agricultural households in the region (Chart 3.148 and Map 3.52). Masasi was the only district in Mtwara region with all 477 households (0.5% of agricultural households) involved in fish farming. (Chart 3.149). Chart 3.146 Number of Households Using Organic Fertiliser Not Using Organic Fertilizer, 215,348, 95% Using Organic Fertilizer, 12,123, 5% Chart 3.147 Area of Application of Organic Fertiliser by District MTWARA 0 500 1,000 1,500 Newala Tandahimba Masasi Mtwara Rural Mtwara Urban District Area of Fertiliser Application (ha) Farm Yard Manure Compost Chart 3.148 Number of Households Practicing Fish Farming - MTWARA Households Prcticing Fish Farming, 477, 0.2% Households Not Prcticing Fish Farming, 228,837, 99.8% Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 3ha 426ha 398ha 560ha 382ha 0.1% 24.1% 22.5% 31.6% 21.6% 400 > 300 to 400 200 to 300 100 to 200 0 to 100 Mtwara Urban Mtwara Rural Tandahimba Newala 59ha 316ha 1,088ha 1,216ha 572ha 1.8% 9.7% 33.5% 37.4% 17.6% Masasi 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 Planted Area and Percent of Planted Area with Compost Application by District MAP 3.51 MTWARA MAP 3.52 MTWARA Planted Area and Percent of Planted Area with FarmYard Manure Application by District Tanzania Agriculture Sample Census Planted Area with Compost Manure Applied Planted Area with Farm Yard Manure Applied Planted Area with Farm Yard Manure Applied Planted Area with Compost Manure Applied Percent of Planted Area with Farm Yard Manure Applied Percent of Planted Area with Compost Manure Applied RESULTS 87 RESULTS – Poverty Indicators _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 88 The main source of fingerings was the non governmental organizations and/or projects which provided fingering to all fish farming households that bought fingerings. All fish farming households in the region used the dug-out-pond system and the main fish specie planted was Tilapia. The number of fish harvested in Mtwara region was 71,391 all of which were tilapia (Chart 3.150). About None of the fish farming households sold their fish. 3.6. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.6.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the tarmac road was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 49 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were district capital (38), hospital (37), tertiary market (35), secondary school (16), secondary market (16), health clinic (5), primary markets (5), all weather roads (3), primary school (1) and feeder road (1), (Table 3.15). Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 52 percent reported them to be poor. Twenty percent of the agricultural households said the infrastructure and services were average, 14 percent said ‘good’ and 11 percent said they were ‘no good’. Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Mtwara Rur 25.9 2.0 4.6 0.6 48.3 4.5 48.1 6.3 16.2 40.7 35.3 Newala 10.7 1.5 4.0 1.1 24.8 4.6 27.5 1.9 2.8 20.9 53.1 Masasi 14.7 1.1 3.5 0.8 36.4 6.1 43.9 2.8 10.7 38.6 36.9 Tandahimba 14.7 0.6 1.7 0.3 42.5 5.5 23.9 10.0 41.6 35.5 90.4 Mtwara Urb 5.6 1.3 0.8 0.3 10.1 1.9 10.3 2.0 6.3 10.8 4.3 Total 16.0 1.2 3.4 0.8 37.4 5.4 37.6 4.6 15.9 34.8 49.0 0 100 200 300 400 500 600 N um ber o f H o useho lds Masasi Mtwara Rur Newala Tandahimba Mtwara Urb District Chart 3.149 Number of Households Practicing Fish Farming by District - Mtwara Chart 3.150 Fish Production Number of Tilapia, 71,391, 100.0% Number of Carp, 0, 0.0% RESULTS – Poverty Indicators _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 89 3.6.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (215,622 households, 94.0% of all rural agricultural households), 4,990 households (2.2%) use flush toilets and 1,752 households (0.8%) use improved pit latrine. However, 6,950 household (3.0%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 68.3 percent of them were found in Mtwara rural District and 15.5 percent were from Newala. The percentages of households without toilets in other districts were as follows Masasi (9.4%), Tandahimba (5.4%), and Mtwara urban (1.4%) Map 3.53). 3.6.3 Household’s Assets Bicycles are owned by most rural agricultural households in Mtwara region with 102,726 households (42.9% of the agriculture households in the region) owning the asset. followed by redio ( 97,775 households, 40.8%), iron (32,058 households, 13.4%), wheelbarrow (2,482 households, 1.0%), vehicle (2,266 households, 0.9%), television/video (1,203 households, 0.5%), mobile phone (633 households, 0.3%), and landline phone (256 households, 0.1%) (Chart 3.152). 3.6.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region. with 69.6 percent of the total rural agricultural households using this source followed by hurricane lamp (24.5%), pressure lamp (2.7%), firewood (2.0%), mains electricity (0.8%), candle (0.4%) and gas or biogas (0.1%) (Chart 3.153). 3.6.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 98.0 percent of all rural agricultural households in Mtwara region. This was followed by charcoal (1.3%). The rest of energy sources accounted for 0.67 percent. These were crop residues (0.27%), parrafin/kerosene (0.19%), mains electricity (0.08%), bottled gas (0.08%) and solar (0.04%) and gas/biogas (0.01%) (Chart 3.154) Chart 3.152 Percentage Distribution of Households Owning the Assets 1.0 0.9 0.5 0.3 0.1 42.9 40.8 13.4 0.0 20.0 40.0 60.0 Bicycle Radio Iron Wheelbarrow Vehicle Television / Video Mobile phone Landline phone Assets P ercent Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 215,622, 94.0% Flush Toilet, 4,990, 2.2% No Toilet , 6,950, 3.0% Improved Pit Latrine , 1,752, 0.8% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 189, 0.08% Crop Residues, 615, 0.27% Mains Electricity, 194, 0.08% Solar, 97, 0.04% Gas(Biogas), 21, 0.01% Charcoal, 2,989, 1.3% Firewood, 224,785, 98.0% Parraffin / Kerocine, 446, 0.19% Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 4,517, 2.0% Gas(Biogas), 260, 0.1% Candles, 886, 0.4% Hurricane Lamp, 56,138, 24.5% Pressure Lamp, 6,228, 2.7% Mains Electricity, 1,782, 0.8% Wick Lamp, 159,502, 69.6% RESULTS – Poverty Indicators _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 90 3.6.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 72.7 percent of the rural agricultural households. This was closely followed by iron sheets (21.7%), grass/mud (4.2%), tiles (0.7%), asbestos (0.5%) and concrete (0.2%) (Chart 3.155). Mtwara Rural district had the highest percentage of households with grass/leaves roofing (81%) followed by Masasi district (76%), Mtwara Urban (75%), Newala (69%) and Tandahimba (59%) (Chart 3.156 and Map 3.54). 3.6.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Mtwara region was the unprotected well (29 percent of households used the unprotected well during both the wet and dry seasons. This was followed by piped water (26% of households during the wet season and 28% in the dry season), uncovered rainwater catchment (11% of households for wet season and 0.6% for dry season), unprotected spring (10% of households during the wet season and 13% in the dry season), surface water (9% of households in the wet season and 18% during the dry season) and protected spring with 2 percent of households using this source in both seasons. Covered rain water catchment was used as a main source by 3 percent of the households in the wet season and by 1 percent in the dry season Chart 3.157) About 48 percent of the rural agricultural households in Mtwara region obtained drinking water within a distance of less than one kilometer during wet season compared to 31 percent of the households during the dry season. However, 52 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 69 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). Chart 3.157 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 40.0 Uprotected Well Piped Water Uncovered Rainwater Catchment Unprotected Spring Lake /River Protected Well Covered Rainwater Catchment Protected Spring Water Vendor Other Main source Percent of Households Wet Season Dry Season Chart 3.158 Percentage of Households by Distance to Main Source of Water and Season - 10 20 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Grass & Mud 4.2% Iron Sheets 21.7% Grass/Leaves 72.7% Concrete 0.2% Tiles 0.7% Asbestos 0.5% Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 81 76 75 59 69 0 25 50 75 100 Mtwara Rural Masasi Mtwara Urban Newala Tandahimba District P ercen t Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 676 7,244 12,645 12,566 16,657 23.7% 16% 30.2 29.2% 17.3% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 4,749 98 376 1,075 651 10.5% 3.4% 0.9% 2.5% 0.7% 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Number and Percent of Households Using Iron Sheets for Roofing Material by District MAP 3.53 MTWARA MAP 3.54 MTWARA Number and Percent of Households Without Toilets by District Tanzania Agriculture Sample Census Number of Households Using Iron Sheets for Roofing Material Number of Households Without Toilets Number of Households Without Toilets Number of Households Using Iron Sheets for Roofing Material Percent of Households Without Toilets Percent of Households Using Iron Sheets for Roofing Material RESULTS 91 RESULTS – Poverty Indicators _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.6.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Mtwara region normally had 2 meals per day (57.3 percent of the households in the region). This was followed by 3 meals per day (33.8 percent) and 1 meal per day (8.7 percent). Only 0.2 percent of the households had 4 meals per day (Chart 3.159). Mtwara rural and Masasi districts had the largest percent of households eating one meal per day whilst Tandahimba had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.55). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 112,209 (48.9% of the agricultural households in Mtwara region) with 52,588 households (46.9 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (30.9%). Very few households had meat three or more times during the respective week. About 51.1 percent of the agricultural households in Mtwara region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.56). 3.6.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 203,012 (88.5% of the total agricultural households in Mtwara region) with 43,818 households (21.6 % of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish once (18.6%). The number of households that consumed fish twice or more during the week in Mtwara region was 165,226 (72.0% of the agricultural households that ate fish in the region during the respective period). About 12 percent of the agricultural households in Mtwara region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.57) Chart 3.17: Number of Households by Number of meals the household normally has per day and District Number of meals per day District One Meal % Two Meals % Three Meals % Four Meals % Total Mtwara Rural 5585 12.4 24228 53.7 15341 34.0 0 0.0 45154 Newala 683 1.6 25399 59.0 16982 39.4 0 0.0 43065 Masasi 11971 12.4 59028 61.2 25098 26.0 324 0.3 96421 Tandahimba 1457 3.5 21255 50.8 19020 45.5 92 0.2 41823 Mtwara Urban 155 5.4 1541 54.0 1155 40.5 0 0.0 2850 Total 19,850 8.7 131,451 57.3 77,597 33.8 416 0.2 229,314 Chart 3.159 Number of Agriculural Households by Number of Meals per Day One meal, 19,850, 8.7%. Three Meals, 77,597, 33.8% Two Meals, 131,451, 57.3% Four Meals, 416, 0.2% Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 20,000 40,000 60,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish RESULTS – Poverty Indicators _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 3.6.9 Food Security In Mtwara region, 75,463 households (33% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements. However 26,093 (11%) said they often experience problems, 8 percent sometimes experienced problems and 6 percent always had problems in satisfying the household food requirements. About 41 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.58). 3.6.10 Main Sources of Cash Income The main cash income of the households in Mtwara region was from selling food crops (46.2 percent of smallholder households), followed by cash crops (37.0%), other casual cash earnings (3.8), businesses (3.3), remittance (2.2%), forest products (2.0), wages and salaries (1.8) and fishing (1.5). Only 0.5% of smallholder households reported the sale of livestock as their main source of cash income, followed by livestock products (0.2). (Chart 3.161). Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Livestock Products, 0.2% Food Crops, 46.2% Other Casual Cash Earnings, 3.8% Cash Crops, 37.0% Business Income, 3.3% Remittance, 2.2% Forest Products, 2.0% Other, 1.4% Fishing, 1.5% Livestock, 0.5% Not applicable, 0.0% Wages & Salaries, 1.8% Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 528 8,640 10,128 13,388 19,904 1 16.4 19.3 25.5 37.8 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Mtwara Urban Mtwara Rural Tandahimba Newala 15,341 25,098 1,155 19,020 16,982 19.8 32.3 1.5 24.5 21.9 Masasi 20,000 > 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Number and Percent of Households Eating Meat Once per Week by District MAP 3.55 MTWARA MAP 3.56 MTWARA Number and Percent of Households Eating 3 Meals per Day by District Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Number of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day Number of Households Eating Meat Once per Week Percent of Households Eating 3 Meals per Day Percent of Households Eating Meat Once per Week RESULTS 94 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 2,078 35,441 39,822 41,621 70,132 72.9% 78.5% 95.2% 96.6% 72.7% 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Mtwara Urban Mtwara Rural Tandahimba Newala Masasi 131 6,639 3,751 10,297 16,966 0.3% 17.6% 9.9% 27.3% 44.9% 12,000 > 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number and percent of Households Reporting Food Insufficiency by District MAP 3.57 MTWARA MAP 3.58 MTWARA Number and Percent of Households Eating Fish Once per Week by District Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week Number of Households Reporting Food Insufficiency Percent of Households Eating Fish Once per Week Percent of Households Reporting Food Insufficiency RESULTS 95 EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 96 4 MTWARA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Mtwara Region Profile The region profile describes the status of the agriculture sector in the region and compares it with other regions in the country. Mtwara has around 460,000 hectares for crop production and the number of crop farming households is moderate compared to other regions, however, due to the small land area, the region has one of the largest number of crop growing households per square kilometer in the country and this is reflected in the high percent of available land that is utilized. The region is characterized by having the highest percent of its total planted area under permanent crops, most of which are monocrop stands. The region gets long rains season only. Cassava is one of the most important crops in Mtwara and it has the third highest planted area in the country. In terms of planted area, the region is not important for cereal production and the yield for maize was one of the lowest in the country during the census year. Comparatively moderate quantities of sorghum and paddy were grown. Moderate quantities of groundnuts are grown and relatively small amounts of beans. Vegetables were not important in the region and traditional annual cash crops were virtually absent. The main crop in Mtwara was cashewnuts for which the region accounted for 55 percent of the total planted area with cashewnuts in the country. Some mangoes and coconuts are also grown. Mtwara has virtually no irrigation. Soil preparation was mainly done by hand and apart from Lindi it had the least pesticide application in the country. It had one of the smallest storage of maize in the country and this was mostly stored in locally made traditional cribs. A moderate number of households sold crops. Most of the crop processing was done on farm by hand and a comparative moderate number of households sold processed crops and most of these is to neighbours. Extension services were provided to a very small number of smallholder households in Mtwara. Tree planting was carried out by a very small number of smallholders in Mtwara and the number of households with erosion control/water harvesting facilities was also very small. This region had extremely low numbers of livestock compared to other regions. Cattle numbers were very small but more goats were kept. The region produced small amounts of milk and the farm gate price was much higher than in other regions indicating a high demand over supply. Sheep and pig production were extremely low but chicken production was more important. Very few households used organic fertilizers and no draft animals were used for cultivation. Very little fish farming took place in this region. Mtwara Region has a moderate to low agriculture population in Tanzania, 928,521 persons, of which 448,168 were males and 480,352 females representing one of the highest gender imbalances in the country. It had a moderate to high number of households involved in agriculture compared to other regions (229,313), with 97 percent of the rural households and 78 EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 percent of the total households (including urban) in the region classified as agriculture households. The region had the lowest average household size of 4.0 persons per household and it had a high percent of female headed households (23%). Crop production was the dominant agriculture activity with virtually no livestock farmers. Ownership of land was mostly by customary law (81% of total land area under agriculture), however although small, it had a comparatively high percent of land under official certificate of ownership compared to most regions. Access to fields was low compared to other regions with only 6 percent of the households having their nearest field less than 100 m from the homestead. Mtwara had a comparatively low literate rural agriculture population compared to most other regions (62%) and the difference between the literacy rate of males and females was also moderate with 9 percent more literate males than females. It had a moderate to high percent of the rural agriculture population that had completed school and a high percent of household heads with no education compared to other regions. The most important livelihood activity was crop farming followed by livestock keeping and tree/forest resources. Off farm income is the least important livelihood activity. The percent of the rural agriculture population working full time in farming was the seventh highest in the country and the region had a moderate number of households using food crops as their main sources of cash income (about 50%of households). It was one of the regions with the highest percent of households that use cash crops as their main source of cash income. And other sources were of minor importance. A very small amount of credit was accessed in the region, mostly from cooperatives and family friends and relatives. A low percent of households (28%) had the roof of the main dwelling made of modern material (mainly iron sheets), the rest were with grass/leaves/mud and only 3 percent of the households had no toilet facility. Energy for lighting was a predominantly from wick lamps and a very small proportion from hurricane lamps. The main sources of drinking water in Mtwara region was from piped water and unprotected wells. It also had the highest percent of households obtaining water from protected springs and lakes, rivers and streams. About 46 percent of the rural agriculture households in Mtwara region used 26 percent or more of their livelihood activities for non – subsistence purposes, however a small proportion of the rural agriculture smallholders in Mtwara lived a subsistence existence (14%). Most of the rural agriculture households in Mtwara region took two or three meals per day and though small, the region had the highest proportion of households taking one meal per day. More than 70 percent of the rural households in the region ate animal protein at least twice a week and it had a relatively low percent of households that did not eat animal protein in a week. The region had a high percent of households that never faced food shortages (75%), however it was also among the regions that had a high percent of households that often or always faced shortages. Access to services and infrastructure was moderate. About 31.6 percent of the households in the region reported insufficiency of land which was the third lowest percent in the country. EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 4.2 District Profile The following district profiles highlight the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Masasi Masasi district had the largest number of households in the region and it had one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock farming. It had no household involved in livestock only and pastoralists households were not found in the district. The most important livelihood activity for smallholder households in Masasi district was annual crop farming, followed by tree/forest resources and permanent crop farming. However, the district had the lowest percent of households with one household member involved inoff-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Masasi had a relatively low percent of female headed households (22.9%) and the lowest average age of the household head. Its average household size of 4.0 members per household it was average for the region. Masasi had a comparatively low literacy rate among smallholder household members and this was reflected in the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was lowers than most of districts in the region. It had the largest utilized land area per household (2.0ha) and the allocated area was almost fully utilised indicating a high level of land pressure. The total planted area was greater than in other districts in the region due to the presence of good wet and dry seasons, however it had the first planted area per household (1.2ha) attributed to the high number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 41,000ha and the planted area per household was the highest in the region. Sorghum production was not important with a planted area of only 7,000 hectares and the production of paddy was 6,000 hectares. Masasi was the only district in the region that produced bulrush millet (32ha). Cassava production was moderate accounting for 27 percent of the quantity harvested in the region. The district had no planted area of Irish potatoes. The production of beans in Masasi was the second highest in the region with a planted area of 186ha. Oilseed crops were important in Masasi but no groundnuts were grown in the district. Vegetable production was important in the district. It had the largest planted area for ginger and tomatoes (35 ha and 33 ha respectively) and in ginger it accounted for 100 percent of the production but 0.4 percent of the tomatoes production in the region. Traditional cash crops (e.g. tobacco and cotton) were grown in very small quantities. Compared to other districts in the region, Masasi had a moderate planted area with permanent crops, which were dominated by cashewnuts (53,000 ha) and pigeon peas (18,000 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation were done by hand, however very slightly more land preparation was done by tractor compared to most other districts. EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 The use of inputs in the region was very small, however district differences existed. Masasi had the second largest area planted with improved seed in Mtwara region and this was due to the higher planted area for vegetables. The district had the largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertiliser), however most of these were inorganic fertilisers. Compared to other districts in the region, Masasi district had a moderate level of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts, except Tandahimba. Virtually no herbicides were used. The area under irrigation was 431 ha. The most common source of water for irrigation was the well. Bucket and watering can were the most common means of irrigation water application and no other method of field application was used. The most common method of crop storage was in locally made traditional cribs; however the proportion of households not storing crops in the district was lower than other districts in the region. The district had the largest number of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. The highest percent of households processing crops in Mtwara region was found in Masasi district and almost all the processing was done by neighbours’ machine. The district also had a higher percent of households selling processed crops to neighbours stores than other districts and no sales were made to secondary markets, cooperatives and large scale farms. The access to credit for women was very small and the main sources were cooperatives, family/friends and relatives, credit and bank.. A comparatively larger number of households received extension services in Masasi and all of these were from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming was important in Masasi (with 16,986 planted trees) and most of the trees were senna spp with some moringa spp and gravellis. The highest proportion of households with erosion control and water harvesting structures were found in Masasi district and these were mostly erosion control bunds, however it also had the highest number of water harvesting bunds. The district had the largest number of cattle in the region and all were indigenous. Goat production was moderate compared to other districts, however it had the second highest number of sheep in the region. It had the largest number of pigs as well as chickens in the region. The district had the highest number of layers, ducks and turkeys in the region. The largest number of households reporting Tsetse and tick problems was in Masasi district and it had the largest number of households de-worming livestock. Draft animals were not used in the district. It is the only district which practiced fish farming in the region. It was amongst the districts with the best access to secondary schools, primary schools, all weather roads, primary and secondary markets. However, the district was the one with the worst access to health clinics and regional capital. Masasi district had the third highest percent of households with no toilet facilities and it had the lowest percent of households owning mobile phone, vehicles, tv/video and wheelbarrow. It had the largest number of households used mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the second largest percent of households roofed their houses using grass/leaves and had the second lowest percent of households having iron sheets. The most common source of drinking water is from unprotected wells. It had the highest percent of households having two or one meal per day compared to other districts and the lowest percent with 3 meals per day. The district had the highest percent of households that did not EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 eat meat and third highest percent of households without eating fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.2 Mtwara rural Mtwara rural district had the second largest number of households in the region and it had a high percentage of households involved in smallholder agriculture. Most smallholders were involved in crop farming only, followed by crop and livestock farming. It had no livestock only households or pastoralists were found in the district. The most important livelihood activity for smallholder households in Mtwara rural district was Annual crop farming, followed by tree/forest resources. The district had the third highest percent of households with no off-farm activities although it had the fourth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mtwara rural had a low percent of female headed households (20%) but it had one of the highest average age for the household heads in the region. Its average household size of 4 members per household was average for the region. Mtwara rural had a comparatively low literacy rate among smallholder households and this was reflected in the district having the lowest level of school attendance in the region. It had a moderate utilized land area per household (1.7ha) and 84 percent of the allocated area was currently being utilised. The district had the fourth largest planted area in the region and the firth largest planted area per household (0.7ha in the dry season and 0.4ha in the wet season). The district was moderately important for maize production in the region with a planted area of over 5,617 ha, and the planted area per maize growing household was also moderate for the region. The district had the second largest planted area of paddy in the region with 4,264 hectares. Sorghum was grown in the district with 4,741 hectares. Cassava production was moderate to low, accounting for 23 percent of the quantity harvested in the region. The district did not plant Irish potatoes. The production of beans in Mtwara rural district was moderate to low with a planted area of 65ha. Mtwara rural district had the fourth largest groundnut planted area in Mtwara region with a planted area per groundnut growing household of 0.31 ha. Vegetable production was very important in the district. It had the largest planted area for tomatoes (295ha), but cabbage and chilies were not grown in the district. Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Mtwara rural district had the third largest planted area with permanent crops which were dominated by cashew nuts (45,633 ha), coconuts (5,339 ha), Orange (264 ha) and Cloves (212 ha). Pawpaw, pigeon pea, sour soup and mango were also grown but in smaller quantities. As with other districts in the region, most land clearing was done by hand slashing, however there was a substantial area where there was no land clearing indicating. Practically all Land preparation was done by hand, however a very small amount of land preparation done using tractors. Mtwara rural district had the largest area planted improved seed in the region as well as the highest proportion of households using improved seeds. The district had the fourth largest area planted with fertilizers (farm yard manure, compost and inorganic fertiliser), and most of these were farm yard manure. Compared to other districts in the region, Mtwara rural district had a moderate level of insecticides use. The use of fungicides and herbicides was low. It had the EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 third largest area under irrigation. The most common source of water for irrigation was the dams using hand bucket methods. Buckets/watering cans were the most common means of irrigation water application in the district. The most common method of crop storage in Mtwara rural district was in locally made traditional cribs, however the proportion of households not stored crops was average for the region. Mtwara rural district had moderate number of households sold crops, the main reason for not selling was insufficient production. Mtwara rural was among the districts with highest percent of households processed crops in Mtwara region and mostly was done by hand on farm. The district also had the second highest percent of households sold processed crops to cooperatives than other districts and no sales were made to traders at farm and large scale farms. The access to credit was not reported in the district. A comparatively larger number of households received extension services in Mtwara rural district and the highest percent of the services was provided by the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming was not important in Mtwara rural district. Erosion control and water harvesting structures were not found in Mtwara rural district. The district had the second largest number of cattle in the region and most of them were indigenous. Goat production was moderate compared to other districts and had the third largest number of sheep in the region. Pigs were not reported whilst there were a moderate number of chickens. Small numbers of ducks were found. A number of households reported tsetseflies and tick problems and it had the largest number of households de-wormed livestock. The use of draft animals was not reported whilst fish farming was not practiced in the district. Mtwara rural district was amongst the best access to health clinics but had fourth percent of households accessed to primary and secondary markets compared to other districts. Also, it was among the district with worst access to secondary schools, primary schools and regional capital. The percentage of households without toilet facility in Mtwara rural district was comparatively high. It was amongst the districts with the lowest percent of households owned wheel barrows, highest percent of households owned tv/video, moderate percent of households owned vehicles, bicycles and mobile phones. It had the second largest number of households used mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The roofing materials for most of the households in the district were grass/leaves (81%). Also, the district had the lowest percent of households with iron sheet roofing (15%). The most common source of drinking water was from unprotected well. It was one of the districts with the lowest percent of households having three meals per day. The district had one of the highest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Newala Newala district had the fourth largest number of households in the region and it had a high percentage of households involved in smallholder agriculture. Most smallholders were involved in crop farming only, followed by crop and livestock farming. It had no agricultural household involved in livestock only and pastoralist were not found in the district. EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 The most important livelihood activity for smallholder households in Newala district was annual crop farming, followed by tree/forest resources. The district had the fourth highest percent of households with no off-farm activities although it had the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Newala had a low percent of female headed households (18%) and it has one of the lowest average age of the household head in the region. With a household size of 4 members per household it is average for the region. Newala has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. It has a moderate utilized land area per household (1.7ha) and 91 percent of the allocated area is currently being utilised. The district has the second largest planted area in the region and the second largest planted area per household (2.0ha in the dry season and 0.4ha in the wet season). The district is moderately important for maize production in the region with a planted area of over 15,000 ha and the planted area per household is 0.4 ha which average for the region is. Paddy production is not important with a planted area of only 1,385 hectares; however it is the second lowest in the region. Sorghum and Irish potatoes are produced, but wheat is not grown in the district. The district has the lowest planted area of cassava accounting for 19 percent of the cassava planted area in the region. The production of beans in Newala is much lower than in other districts in the region with a planted area of 10ha. Oilseed crops are important in Newala with 20 percent of the groundnuts grown in the district. Vegetable production is not important and very small quantities of tobacco are grown in the district. Permanent crops are not very important in Newala district (14% of the total permanent crop planted area in Mtwara region) and are fourth important than any other district in the region. The most prominent permanent crops in the district include cashew nuts (32,957 ha), pigeon pea (600 ha), bananas (419 ha) and coconuts (152 ha). Black pepper is not grown in the district and it has the lowest area with oranges in the region (31 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has no area cleared by other methods before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is very small, however district differences exist. Newala has the smallest planted area with improved seed in Mtwara region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a large planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and practically large area is with inorganic fertilizer. Compared to other districts in the region, Newala district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively small. It has the last largest area with irrigation in the region with 11 ha of irrigated land. The most common source of water for irrigation is from piped water and almost all water application is by using water hose. The most common method of crop storage is in Newala is locally made traditional cribs, and the proportion of households not storing crops in the district is moderate to low for the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Newala district has a high percent of households processing crops in the region and is almost all done by hand; however, the district has the EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 highest percent of households processing crops by neighbour machine. Small quantities of processed crops are sold and many households have access to credit. A few numbers of households receive extension services in Newala district and almost all of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming is important in Newala district (with 38 planted trees) and is mostly Senna Spp with some Melicia excelsa. There is no proportion of households with water harvesting bunds is found in Newala district and it also has the highest number of drainage ditches. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat production is high compared to other districts, but it is a second highest in sheep production. It has the second largest number of pigs in the region as well as the second largest number of chickens, all of which are broiler. Virtually no improved chicken are found in the district. The district has the largest number of ducks and rabbits and no turkeys are found in the district. A small number of households reported tsetse and tick problems in Newala district. A small amount of de-worming of livestock is practiced in the district. No draft animals are used and fish farming is not practiced by households in the district. It has amongst the moderate access to secondary schools, health clinics, primary markets, tertiary markets and regional capital compared to other districts. However, it has one of the worst accesses to feeder roads and primary schools. The percentage of households without toilet facility in Newala district is average for the region; however it has the second highest percent of households with no toilet facilities. It has the lowest percent of households owning land line phones, but highest percent of households owning vehicles and TV/video. It has the third lowest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (69%) and only 29 percent of households have iron sheet roofing. The most common source of drinking water is from piped water. Two percent of the households in the district reported having one meal per day, fifty nine percent reported having two meals per day, thirty nine percent reported having three meals per day and virtually no household reported having more than three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households never had problems with food satisfaction. 4.2.4 Tandahimba Tandahimba district has an average number of households for the region and it has the smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very moderate number of livestock only households and pastoralists were found in the district. The most important livelihood activity for smallholder households in Tandahimba district is Annual crop farming followed by Permanent crop farming. It has the highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tandahimba district has a relatively high percent of female headed households (22%) and it has one of the highest average ages of the household head. With an average household size of 4.3 members per household it is average for the region. Tandahimba EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 district has a comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively low level of school attendance in the region. It has the largest utilized land area per household (2.0 ha) and only 88 percent of the allocated land area is utilised. The total planted area is the third in the region however it has the second largest planted area per household (0.46ha in the long rainy season and 1.62ha in the wet season. Tandahimba district is third important for maize production in the region with a planted area of 8,427 ha, and the planted area per household is among the highest in the region. Paddy production is also important with a planted area of 2,419hectares and the production of sorghum is small. Cassava production in Tandahimba district was high and beans, Irish potato and wheat is not grown. Vegetables is important in the district compared to oilseed crops, whist the district has the second planted areas with tomatoes also it is the second in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are grown in the district. Compared to other districts in the region, Tandahimba district has the smallest planted area with permanent crops (24.4% of total permanent crop planted area) which is dominated by cashew nuts (57,201 ha), mango (2,906 ha), A small area of coconut is grown and no other permanent crop. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. The use of inputs in the region is very small, however district differences exist. Tandahimba district has the smallest planted area with improved seed; however it has the highest planted area per household in the region. The district also has the second percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with farm yard manure. Compared to other districts in the region, Tandahimba district has the lowest area planted with insecticide but has the second highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the highest for herbicides. It has one of the smallest areas of irrigation 1,247 ha. The most common source of water for irrigation is from rivers using gravity. Floods are the most common means of irrigation water application with some few using bucket/watering cans. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in Tanga district is the highest in the region. The number of households selling crops in the district is among the highest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The third percent of households processing crops in the region is found in Tandahimba district and processing is mostly done by on farm by hand. The district has the smallest number of households processing crops on farm by machine. It also has the largest number of households processing crops on farm by hand. Most households that sell crops sell to neighbors and no sales are to traders on neither farm nor large scale farms. Access to credit in the district is very small. EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 A very big number of households receive extension services in Tandahimba district and almost all of this is from the government. The quality of extension services was rated between very good and good by the majority of the households. Tree farming is not important in Tandahimba district (with no household planting trees). The largest proportion of households in Tandahimba district doesn’t use any of the erosion control method. Tandahimba district has the fourth smallest number of cattle in the region and all of them are indigenous. It is one of the districts with the second largest number of goats in the region, however the district has the highest density (87 head per km2). Tandahimba is also one of the districts with the largest number of sheep, no pigs and small number of chicken; also it has the second smallest number of improved chickens (layers) in the region. Small numbers of ducks but no rabbits, turkeys and donkeys are also found in the district. A largest number of households reported tick and Tsetse problems in Tandahimba district and it had one of the largest numbers of households de-worming livestock. There are no household use draft animals in the district as well as fishing farming practice. It is amongst the districts with the best access to feeder roads and primary schools compared to other districts. However, it has the moderate access to all weather roads, secondary schools, health clinics, regional capital and primary schools but worst access to tarmac roads, secondary markets, hospitals and tertiary markets. Tandahimba district has a small number of households with no toilet facilities. The district has the highest percent of households owning bicycles, wheelbarrows and mobile phones but it has the second highest percent of households with television/video. It has no households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the fourth largest percent of households with grass roofs with only 25 percent of households having iron sheets. The most common source of drinking water is surface water and it has the fifth highest percent of households having two or one meal per day compared to other districts and the first highest percent with 3 meals per day. The district had the smallest percent of households that did not eat meat and fish during the week prior to enumeration. Most households never had problems with food satisfaction. 4.2.5 Mtwara Urban Mtwara Urban district has the smallest number of households in the region and it has the last lowest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mtwara Urban district is tree/forest resources followed by Annual Crop Farming, off farm income and permanent crop farming. The district has the last lowest percent of households with no off-farm activities and the third largest percent of households with more than one member with off- farm income. Compared to other districts in the region, Mtwara Urban has a lowest percent of female headed households (21%) and it has one of the highest average ages of the household head. With an average household size of 4.4 members per household it is slightly higher than the regional average. Mtwara Urban has the second lowest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the moderate in the region. EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 It has one of the smallest utilized land area per household (1.6 ha) which is slightly lower than the regional average of 1.9 ha per household. The district has smallest planted area in the region, however it has the second largest planted area per household (1.6 ha) in the long rainy season. The district is not important for maize production with a planted area of 505 ha, however the planted area per household is second smallest compared to other districts in the region. Paddy production is also not important with a planted area of only 36 hectares and the production of sorghum is very small. Wheat and finger millet are not grown in the district. The district has among the lowest percent of cassava planted area in the region and it has virtually no Irish or sweet potatoes. There is no production of beans in Mtwara Urban district and oil crops are not important in the district. Vegetable is not grown at all in the district. Traditional cash crops (e.g. tobacco and cotton) are also not grown in the district. Compared to other districts in the region, Mtwara Urban has a small planted area with permanent crops (680 ha) which is dominated by cashew nuts (494 ha) and coconuts (158 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by hand, however no land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Mtwara Urban has one of the smallest planted areas with improved seed in Mtwara region however it has the second highest percent of planted area using improved seed. The district has the smallest planted area with fertilizers and most of this is with farm yard manure and compost with no inorganic fertiliser. Compared to other districts in the region, Mtwara Urban district has the second highest percent of its planted area with insecticides in the region. The use of fungicides was the one of the lowest in the region and virtually no herbicide was used. There was no planted area with irrigation in Mtwara Urban district. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is the second highest in the region. The district has the smallest number of households selling crops and the main reason for not selling is insufficient production. Mtwara Urban district has the highest percent of households processing crops on farm by hand and a highest percent of households selling processed crops mainly to neighbours. No sales were made to local markets/trade stores, secondary market, market cooperatives, farmers associations, traders at farm or large scale farms. Access to credit is extremely small. A comparatively small number of households receive extension services in Mtwara Urban district and the highest percentage of this is from the government. The quality of extension services was rated good/well by all households in the district. Tree farming is not important in Mtwara Urban district (with only 56 planted trees) and is mostly with Senna Spp with some Azadritachta Spp, Terminalia Catapa and Jakaranda Spp. The smallest number of erosion control and water harvesting structures is found in Mtwara Urban district. The district has the smallest number of cattle in the region and they are mostly all indigenous and diary. Goat and sheep production is smallest in the district and no pigs are found in the district. It has a comparatively smallest number of EVALUATION AND CONCLUTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 chickens. Ducks and donkeys are not found in the district. A moderate number of households reported tick problems in Mtwara Urban district and has the smallest number of households de-worming livestock. No households reported about Tsetse problem in the district. The use of draft animals in the district is non existent and no fish farming is practiced in the district. It is amongst the districts with the best access to Secondary schools, feeder roads, health clinics, all weather roads, hospitals, health clinics, regional capital, tertiary markets and tarmac roads; however it has the moderate accesses to secondary Markets, primary Schools and primary Markets. Mtwara Urban district has a low percent of households with no toilet facilities. The district has the largest percent of households owning bicycles and radios and no ownership of mobile phones, vehicles and television/video were reported. Very small number of households reported ownership of iron, landline phones and wheel barrows,The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the largest percent of households with grass roofs and only 1.4 percent of households having iron sheets. The most common source of drinking water is from piped water, protected wells and protected/covered spring. It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a high percent of households with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration; however it is among the districts with low percent of households that did not eat fish during the week. Most households in the district seldom had problems with food satisfaction. APPENDIX II 108 4. APPENDICES APPENDIX I TABULATION LIST...................................................................................................109 APPENDIX II TABLES .......................................................................................................................124 APPENDIX III QUESTIONNAIRES .................................................................................................258 APPENDIX II 109 TYPE OF AGRICULTURE HOULSEHOLDS...................................................................................124 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year ............................................................................................................125 2. 2 Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year .............................................................................................................125 AGRICULTURE HOUSEHOLDS........................................................................................................126 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.......................................................127 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District during 2002/03 Agriculture Year .............................................127 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES..........................................................128 3.1a First Most Importance..................................................................................................................129 3.1b Second Most Importance..............................................................................................................129 3.1c Third Most Importance ................................................................................................................129 3.1d Fourth Most Importance...............................................................................................................129 3.1e Fifth Most Importance..................................................................................................................130 3.1f Sixth Most Importance.................................................................................................................130 3.1g Seventh Most Importance ............................................................................................................130 HOUSEHOLDS DEMOGRAPHS.........................................................................................................132 3.2 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (row %) .............................................................................................133 3.3 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (col %) ..............................................................................................133 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year.134 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year.......134 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year ..................................................................135 3.7 Number of Agricultural Household Members By Main Activity and District.............................135 Number of Agricultural Household Members By Main Activity and District,............................136 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year..........................................................136 APPENDIX II 110 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year .............................................................................................137 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year.......................................................138 3.11 Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ...138 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year..............................................................138 3.13 Mean, Meadian, Mode of Age of Head of Agricultural Household and District.........................138 3.14 Time Series of Male and Female Headed Households ................................................................139 3.15 Literacy Rate of Heads of Households By District......................................................................139 LAND ACCESS/OWNERSHIP.............................................................................................................140 4.1 Number of Farming Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year .........................................................................................................................141 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year ...........................................................................................................141 4.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.......................................................................................142 4.4: Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District, 2002/03 Agricultural Year........................................................142 4.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year.............................................142 LAND USE: .............................................................................................................................................144 5.1 Area of Land by type of Land Use and District during 2002/03 Agricultural Year ....................145 5.2 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year ...........................................................................................................145 ANNUAL CROP AND VEGETABLE PRODUCTION: ....................................................................146 7.1 & 7.2a: Number of Crop Growing Households and Planted Area (ha) by season and District .........147 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District....................147 7.1 & 7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year, Mtwara Region........................................................................................148 7.1 & 7.2d : Number of Agricultural Households by Area Planted (ha) and Crop for Agricultural Year 2002/03 - Dry anf Wet Seasons, Mtwara region. ...........................................149 7.1 & 7.2j Number of Agriculture Households and Planted Area By Fungicide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Mtwara region........................149 APPENDIX II 111 7.1 & 7.2k Number of Agriculture Households and Planted Area By Improved seed Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Mtwara region........................151 7.1a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Mtwara Region. .............152 7.1b: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-DRY SEASON - Mtwara Region .......................................152 7.1c: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year DRY SEASON - Mtwara Region .......................................152 72a: Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year- WET SEASON - Mtwara Region ..............................153 7.2b: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-WET SEASON - Mtwara Region.......................................153 7.2c: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON - Mtwara Region .......................153 7.1: Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region.................................154 7.2.2: Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region.................................154 7.2.3: Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region ...............154 7.2.4: Number of Crop Growing Households, Planted Area (ha) and Finger Millet Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region ...............154 7.2.5: Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region ...............155 7.2.6: Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region.................................155 7.2.7: Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region ...............155 7.2.8: Number of Crop Growing Households, Planted Area (ha) and Irish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region ...............155 7.2.9: Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year............................................156 7.2.10: Number of Crop Growing Households, Planted Area (ha) and Cocoyams Harevsted (tons) by season and District 2002/03 Agricultural Year............................................156 7.2.11: Number of Crop Growing Households, Planted Area (ha) and Mug beans Harevsted (tons) by season and District 2002/03 Agricultural Year............................................156 7.2.12: Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year............................................156 APPENDIX II 112 7.2.13: Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year............................................157 7.2.14: Number of Crop Growing Households, Planted Area (ha) and Green gram Harevsted (tons) by season and District 2002/03 Agricultural Year. .................................157 7.2.15: Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year............................................157 7.2.17: Number of Crop Growing Households, Planted Area (ha) and Okra Harevsted (tons) by season and District 2002/03 Agricultural Year............................................158 7.2.18: Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year............................................158 7.2.20: Number of Crop Growing Households, Planted Area (ha) and Castor Seed Harevsted (tons) by season and District 2002/03 Agricultural Year............................................158 7.2.21: Number of Crop Growing Households, Planted Area (ha) and Onion Harevsted (tons) by season and District 2002/03 Agricultural Year............................................159 7.2.22: Number of Crop Growing Households, Planted Area (ha) and Ginger Harevsted (tons) by season and District 2002/03 Agricultural Year............................................159 7.2.23: Number of Crop Growing Households, Planted Area (ha) and Cucumber Harevsted (tons) by season and District 2002/03 Agricultural Year............................................159 7.2.24: Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year............................................159 7.2.25: Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year............................................160 7.2.26: Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year............................................160 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Chillies Harevsted (tons) by season and District 2002/03 Agricultural Year............................................160 7.2.28: Number of Crop Growing Households, Planted Area (ha) and Amaraths Harevsted (tons) by season and District 2002/03 Agricultural Year............................................160 7.2.29: Number of Crop Growing Households, Planted Area (ha) and Pumpkin Harevsted (tons) by season and District 2002/03 Agricultural Year............................................161 7.2.30: Number of Crop Growing Households, Planted Area (ha) and Egg plant Harevsted (tons) by season and District 2002/03 Agricultural Year............................................161 7.2.31: Number of Crop Growing Households, Planted Area (ha) and Water Mellon Harevsted (tons) by season and District 2002/03 Agricultural Year............................................161 7.2.32: Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................161 7.2.32: Number of Crop Growing Households, Planted Area (ha) and Pyrthrum Harevsted (tons) by season and District 2002/03 Agricultural Year.............................................................162 APPENDIX II 113 PERMANENT CROPS ..........................................................................................................................164 7.3: Production of Permanent Crops by Crop Type and Region –Mtwara .........................................165 AGROPROCESSING.............................................................................................................................172 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District , 2002/03 Agricultural Year ......................................................................................173 8.0b: Number of Crop Growing Households By Method of Processing and District; Agricultural Year .........................................................................................................................173 8.1.1 Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Mtwara Region. .............................................................................174 8.1.1b: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop, Mtwara Region......................174 8.1.1c: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Mtwara Region..175 8.1.1d: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year, Mtwara Region...................................................................................................................175 8.1.1e: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year, Mtwara Region...................................................................................................................175 8.I.1f: Number of Crop Growing Households By Where Product Sold During 2002/03 Agricultural Year, Mtwara Region ..............................................................................................176 8.1.1g: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District During 2002/03 Agricultural Year, Mtwara Region........................................176 MARKETING .........................................................................................................................................178 10.1: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District, Mtwara Region...............................................................................179 10.2: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2002/03 Agricultural Year, Mtwara Region. ...................................................................179 10.3: Proportion of Households who Reported Not Selling their crops by district during 2002/03 Agricultural Year, Mtwara Region ................................................................................179 IRRIGATION/.........................................................................................................................................180 11.1: Number and Percent of Households Reporting use of Irrigation During 2002/03 Agricultural Year By District....................................................................................................................................181 11.2: Area of Irrigated and Non Irrigatable (ha) Land By District during 2002/03 agricultural year...181 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District...........................................................................................181 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District .........................................................................................................................181 APPENDIX II 114 11.5: Number of Agricultural Households By Method of Field Application of Irrigation Water and District for the 2002/03 agricultural year ...................................................................182 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District...........................................................................................................................182 11.7: Number of Erosion Control Harvesting Structures By Type and District ...................................182 ACCESS TO FARM INPUTS AND IMPLEMENTS..........................................................................184 12.1.1: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year ...........................................................................................................185 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year ...........................................................................................................185 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ...........................................................................................................185 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................................186 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year..186 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................................186 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................187 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year .............................................................................................187 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................................187 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................................188 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year ...........................................................................................................188 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................................188 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................189 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year...........................................................................189 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year...........................................................................190 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ........................................................................................190 APPENDIX II 115 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/ Fungicides by District, 2002/03 Agricultural Year......................................................................190 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................191 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year..................................................................191 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year...........................................................................191 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/ Fungicides by District, 2002/03 Agricultural Year......................................................................192 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .............................................................................................192 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ..............................................................................192 AGRICULTURAL CREDIT .................................................................................................................194 13.2 Number of Households Receiving Credit By Source of Credit By District................................195 13.1a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year .............................................................................196 13.1b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year.......................................................................................................196 TREE FARMING AND AGROFORESTRY.......................................................................................198 14 Number of Planted Trees By Species and District during the Year 2002/03 Agricultural Year, Mtwara region................................................................................................199 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District during the 2002/03 Agricultural year - Mtwara Region..............199 14.3 Number of Agricultural Households Classified by Distance to Community Planted Forest (Km) By District during the 2002/03 Agricultural Year, Mtwara Region........................199 14 Number of Responses by main use of planted tree and District for the 2002/03 agricultural year, Mtwara region ................................................................................................ 200 14 Second Use of Trees By District.................................................................................................200 CROP EXTENSION...............................................................................................................................202 15.1 Number of Households Receiving Extension Messages By District ...........................................203 15.1 Number of Households By Quality of Extension Services By District .......................................203 15.2 Number of Households By Source of Extension Messages By Distric .......................................203 APPENDIX II 116 15.4: Number of Households By Receivingf Advice on Plant Spacing By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................204 15.5: Number of Households By Receivingf Advice on Use of Agrochemical By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................204 15.6: Number of Households By Receivingf Advice on Erosion Control By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...........................................204 15.7: Number of Households By Receivingf Advice on Organic Fertiliser Use By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................205 15.8: Number of Households By Receivingf Advice on Plant Spacing By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................205 15.9: Number of Households By Receivingf Advice on Use of Improved Seed By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................205 15.10: Number of Households Receiving Advice on Mechanisation/LST By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................206 15.11 Number of Households Receiving Advice on Irrigation Technology By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................206 15.12 Number of Households Receiving Advice on Crop storage By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................................................206 15.13 Number of Households By Receivingf Advice on Vermin Control By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................207 15.14 Number of Households By Receivingf Advice on Agro - Processing By Source and District during the 2002/03 Agricultural Year, Mtwara Region ..................................................207 15.15 Number of Households By Receivingf Advice on Agro- Forestry By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................................................207 15.16 Number of Households By Receivingf Advice on Beekeeping By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................................................208 15.17: Number of Households By Receiving Advice on Fish Farming By Source and District during the 2002/03 Agricultural Year, Mtwara Region ...............................................................208 15.18: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region.......................................208 15.19: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region.......................................209 15.20: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region.......................................209 15.21: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region ..................................210 15.22: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region ..................................210 APPENDIX II 117 ANIMAL CONTRIBUTION TO CROP PRODUCTION ..................................................................212 17.1: Number of Households Using Draft Animal to Cultivate Land By District during 2002/03 agricultural year, Mtwara Region.......................................................................213 17.2 Number of Crop Growing Households Using Organic Fertilizer By District During 2002/03 Agriculture Year, Mtwara Region .....................................................................213 17.3 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year ..........................................................................................................................213 CATTLE PRODUCTION......................................................................................................................214 18.2 Number of Cattle By Type and District as of 1st October, 2003 .................................................215 18.3: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size; on 1 st October 2003.............................................................................215 18.4. Number of Cattle by Category and Type of Cattle as of 1st October 2003 .................................215 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................215 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................215 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................216 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003....................................216 18.13 Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year.................................................................................................216 GOATS PRODUCTION ........................................................................................................................218 19.1 Total Number of Goats by Type and District as of 1st October, 2003.........................................219 19.2: Number of Households Rearing Goats and Herds of Goats and Average Head per Household by Herd Size as on 1st October, 2003...............................................................................................219 19.3: Total Number of Goats by Category and Type of Goat as on 1st October, 2003 ........................220 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 ................220 19.5: Total Number of Indigenous Goat by Category and District as on 1st October, 2003 ................220 19.6: Total Number of Improved Dairy Goat by Category and District as on 1st October, 2003.........221 19.7: Total Number of Total Goat by Category and District as on 1st October, 2003..........................221 SHEEP PRODUCTION .........................................................................................................................222 20.1: Total Number of Sheep by Type as on 1st October, 2003 ...........................................................223 20.2: Number of Households Rearing or Managing Sheep by District as on 1st October, 2003..........223 20.3: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 .............................223 APPENDIX II 118 20.5: Number of Households and Herds of Sheep by Herd Size as on 1st October, 2002/03 ..............224 20.6: Total Number of Indigenous Sheep by Type and District as of 1st October, 2002/03 ................224 20.7: Total Number of Improved Sheep by Type and District as of 1st October..................................224 20.8: Total Number of Sheep by Type of Sheep and District as of 1st October, 2002/03....................224 PIGS HUSBANDRY ...............................................................................................................................226 21.1: Number of Households and Pigs, by Herd Size as on 1st October, 2003 ....................................227 21.2: Number of Households and Pigs by District during 2002/03. .....................................................227 21.3: Total Number of Pigs by Type and District as on1st October, 2003 ...........................................227 LIVESTOCK PESTS & PARASITES CONTROL.............................................................................228 22.1: Number of Livestock Rearing households that dewormed Livestock by Type and District during 2002/03 Agriculture Year...................................................................................229 22.2: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agriculture Year ..........................................................................................................................229 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ...........229 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control use during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year...........................229 OTHER LIVESTOCK............................................................................................................................230 23a Total Number of Other Livestock by Type as of 1st October 2003.............................................231 23b Number of households with chicken and Category of Chicken by District.................................231 23c. Number of Households Rearing and number of Other Livestock by Type and District..............231 23d: Total Number of households and chicken raised by flock size as of 1 st October 2003..............231 FISH FARMING.....................................................................................................................................232 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year .........................................................................................................................233 28.2a Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year .........................................................................................................................233 28.2b Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year .........................................................................................................................233 28.2c Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year .........................................................................................................................233 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....................233 APPENDIX II 119 LIVESTOCK EXTENSION ..................................................................................................................234 29.1a Number of Agricultural Households Receiving Extension Advice By District during the 2002/03 Agricultural Year..........................................................................................235 29.1 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year ...........................................235 29.1e Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year.......................................................235 29.1f Number of Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year .............................................................................................236 29.1g Number of Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year.......................................................................................236 29.6 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year ......................................236 29.1i Number of Agricultural Households Receiving Advice Pasture Establishment By Source and District, 2002/03 Agricultural Year.....................................................................237 29.1j Number of Households Receiving Advice Group Formation By Source and District, 2002/03 Agricultural Year .........................................................................................................................237 29.1k Number of Households Receiving Advice on Calf rearing By Source and District, 2002/03 Agricultural Year .........................................................................................................................237 29.1l Number of Households Receiving Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year.......................................................................................238 29.11 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year ...........................................................................................................238 29.1 Number of Households Receiving Advice on Other Extension Messages by Source and District, 2002/03....................................................................................................................239 3.16: Mean distances from holders dwellings to infrustructures and services by districts ...................239 ACCESS TO INTRASTRUCTURE & OTHER SERVICES .............................................................240 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year ............................................................................................................................241 33.01c: Number of Households By Distance to All Weather Road by Distcrict for 2002/03 agriculture year ............................................................................................................................241 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year ...........................................................................................................241 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year.........242 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year ..........................................................................................................................242 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year.................242 APPENDIX II 120 33.01h: Number of Households by Distance to Feeder Road and District, 2002/03 Agricultural Year ..243 33.01i: Number of Households by Distance to Regional Capital and District, 2002/03 Agricultural Year ...........................................................................................................243 33.01: Number of Households By Distance toTarmac Road and Distric for the 2002/03 Agricultural Year .........................................................................................................................244 33.10: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year .........................................................................................................................244 33.01: Number of Households By Distance to Tertiary Market Market and Distric for the 2002/03 Agricultural Year .........................................................................................................................244 33.01: Number of Households By Distance to Secondary Market Market and Distric for the 2002/03 Agricultural Year ...........................................................................................................244 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................................245 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year ...........................................................................................................245 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year .............................................................................................245 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year.......................................................................................246 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ...........................................................................246 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year .....................................................246 33.19g Number of Agricultural Households by Level of Satisfaction of the Service and District for 2002/03 Agricultural year...........................................................246 HOUSEHOLD FACILITIES.................................................................................................................248 34-1: Number of Households by Type of Toilet and District, during the 2002/03 Agricultural Year .249 34.2: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ........................................................................249 34.3: Number of hoseholds type of Owned Asset and District, 2002/03 Agricultural Year................249 34.4: Number of Agricultural Households Source of Energy for Lighting and District, 2002/03 Agricultural Year .........................................................................................................................250 34.5: Number of Agricultural Households Source of Energy for Cooking and District, 2002/03 Agricultural Year .........................................................................................................................250 34.6: Number of Agricultural Households by Main Source of Drinking Water (Wet & Dry) and District during 2002/03 Agricultural ...............................................................251 APPENDIX II 121 34.6: Proportion Number of Agricultural Households by Main Source of Drinking Water (Wet & Dry) and District during 2002/03 Agricultural ...............................................................251 34.8: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year.............................252 34.9: Proportion Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year.........252 34.10: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year.........253 34.11: Proportion Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year253 34.12: Number of Households by Number of Meals the household Normally Took per Day by District254 34.13: Number of Households by Number of Days the household Consumed Meat during the Preceding Week by District ........................................................................................254 34.14: Number of Households by Number of Days the household Consumed Fish during the Preceding Week by District ........................................................................................255 34.15: Number of Households Reportying the status of food satisfaction of the households during the Preceding Year by District..........................................................................................255 34-16: Number of Households Reporting Main Source of Income by District, 2002/03 Agricultural Year .........................................................................................................................256 34.18: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 ......................................................................................................257 APPENDIX II 122 APPENDIX II: CROPS Type of Agriculture Household.................................................................................................................124 Number of Agriculture Households..........................................................................................................126 Rank of Importance of Livelihood Activities ...........................................................................................126 Households Demography..........................................................................................................................132 Land Access/Ownership............................................................................................................................140 Land Use……………… ...........................................................................................................................144 Total Annual Crop and Vege Production Long and short Seasons..........................................................146 Permanent Crop Production ......................................................................................................................164 Agro-processing ..................................................................................................................................172 Marketing ..................................................................................................................................178 Irrigation/Erosion Control.........................................................................................................................180 Access to Farm Inputs...............................................................................................................................184 Agriculture Credit ..................................................................................................................................194 Tree Farming and Agro-forestry ...............................................................................................................198 Crop Extension ..................................................................................................................................202 Animal Contribution to Crop Production..................................................................................................212 Cattle Production ..................................................................................................................................214 Goat Production ..................................................................................................................................218 Sheep Production ..................................................................................................................................222 Pig Production ..................................................................................................................................226 Livestock Pests and Parasite Control ........................................................................................................228 Other Livestock ..................................................................................................................................230 Fishing Farming ..................................................................................................................................232 Livestock Extension..................................................................................................................................234 Access to Infrastructure and other services...............................................................................................240 Household Facilities..................................................................................................................................248 Appendix II 124 TYPE OF AGRICULTURE HOULSEHOLDS Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 125 Rural households involved in Agriculture % of Total rural househ olds Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total household s Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Mtwara Rurural 45,154 94 2,776 6 47,930 23 156,227 77 204,157 Newala 43,065 97 1,336 3 44,402 24 138,942 76 183,344 Masasi 96,421 98 1,974 2 98,395 22 342,592 78 440,987 Tandahimba 41,823 96 1,753 4 43,576 21 160,261 79 203,837 Mtwara Urban 2,850 88 371 12 3,221 3 88,935 97 92,156 Total 229,314 94 15,869 6 245,183 22 879,298 78 1,124,481 Number of households % Number of households % Number of households % Mtwara Rural 40,908 91 0 0 4,246 9 45,154 100 45,154 4,246 Newala 35,560 83 0 0 7,505 17 43,065 100 43,065 7,505 Masasi 90,441 94 0 0 5,980 6 96,421 100 96,421 5,980 Tandahimba 34,886 83 81 0 6,857 16 41,823 100 41,743 6,937 Mtwara Urban 2,446 86 31 1 373 13 2,850 100 2,819 404 Total 204,241 89.1 112 0.05 24,961 10.9 229,314 100 229,202 25,073 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 2. 2 TYPE OF AGRICULTURE HOULSEHOLDS: Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year District District Crops Only Livestock Only Crops & Livestock Total Number of Agriculture Households % Agriculture, Non Agriculture and Urban Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 126 AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 127 Number % Average HH Size Number % Average HH Size Number % Mtwara Rural 34,507 80 4.5 10,647 20 3.50 45,154 100 4.2 Newala 33,153 82 3.9 9,912 18 2.98 43,065 100 3.7 Masasi 74,391 82 4.2 22,029 18 3.17 96,421 100 4.0 Tandahimba 31,288 78 4.5 10,535 22 3.84 41,823 100 4.3 Mtwara Urban 2,240 80 4.5 611 20 4.01 2,850 100 4.4 Total 175,579 81 4.3 53,735 19 3.34 229,314 100 4.0 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 1 4 5 3 6 7 2 Newala 1 3 4 5 6 7 2 Masasi 1 3 5 4 6 7 2 Tandahimba 1 2 3 4 5 7 6 Mtwara Urban 2 4 5 3 6 7 1 Total 1 2 5 4 6 7 3 Average HH Size District 3.0 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Male Female District Livelihod Activity Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District during 2002/03 Agriculture Year Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 128 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 129 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 25,683 9,282 172 5,044 605 2,598 1,118 Newala 32,083 8,325 197 2,079 381 - 99 Masasi 64,245 26,167 303 4,523 1,301 - 325 Tandahimba 16,811 23,421 170 760 381 - 94 Mtwara Urbun 795 842 - 934 148 - 99 Total 139,618 68,038 842 13,339 2,815 2,598 1,734 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 15,173 14,346 792 9,104 2,086 738 3,337 Newala 9,638 14,912 2,498 7,333 2,185 191 6,301 Masasi 29,271 27,032 5,089 15,591 3,024 163 14,475 Tandahimba 22,963 8,998 3,036 2,802 1,025 190 183 Mtwara Urban 1,635 602 58 327 - - 228 Total 78,679 65,890 11,473 35,157 8,321 1,282 24,524 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 3,096 4,820 3,406 13,081 2,272 1,246 14,600 Newala 955 2,967 9,575 8,125 4,288 572 12,943 Masasi 1,771 4,017 18,126 11,407 2,882 1,111 32,733 Tandahimba 1,225 1,780 12,814 7,271 2,391 447 986 Mtwara Urban 270 389 230 584 93 - 1,317 Total 7,317 13,973 44,152 40,468 11,926 3,375 62,579 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural 572 3,376 3,976 5,607 1,458 468 15,704 Newala 94 2,025 8,771 3,518 2,302 474 15,892 Masasi 811 2,587 10,316 5,440 2,089 641 17,482 Tandahimba 186 184 4,952 2,045 1,210 284 541 Mtwara Urban 59 150 426 373 166 - 922 Total 1,723 8,323 28,441 16,983 7,225 1,867 50,541 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 130 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural - 853 4,193 1,355 485 89 4,063 Newala 98 574 4,133 1,637 869 384 6,869 Masasi 159 649 2,577 1,122 159 2,903 6,712 Tandahimba - 189 97 376 287 374 363 Mtwara Urban 33 33 261 58 - - 169 Total 289 2,298 11,261 4,548 1,800 3,750 18,177 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural - - 106 275 - 93 466 Newala 98 98 583 96 288 - 478 Masasi - 159 976 - - - 304 Tandahimba - 92 - - 188 94 - Mtwara Urban - - - - - - - Total 98 349 1,665 372 476 187 1,247 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mtwara Rural - - - 107 - - - Newala - 95 - 98 96 96 - Masasi - - - 318 - - - Mtwara Urban - - - - - - - Tandahimba - 187 - 95 - 95 95 Total - 282 - 618 96 191 95 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance Tanzania Agriculture Sample Census - 2003 Mtwara 131 Appendix II 132 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 133 Number % Number % Number % Less than 4 56,710 50 56,169 50 112,880 100 05 - 09 65,699 51 63,991 49 129,690 100 10 - 14 64,574 55 53,797 45 118,371 100 15 - 19 41,722 51 40,819 49 82,542 100 20 - 24 31,041 40 45,872 60 76,913 100 25 - 29 30,465 40 46,478 60 76,943 100 30 - 34 29,098 44 37,108 56 66,206 100 35 - 39 23,203 44 29,556 56 52,759 100 40 - 44 21,242 45 25,670 55 46,912 100 45 - 49 15,460 50 15,424 50 30,884 100 50 - 54 16,136 48 17,660 52 33,796 100 55 - 59 12,892 57 9,534 43 22,426 100 60 - 64 13,635 49 14,083 51 27,718 100 65 - 69 9,017 49 9,371 51 18,388 100 70 - 74 8,075 57 6,162 43 14,237 100 75 - 79 3,783 47 4,194 53 7,977 100 80 - 84 3,759 65 1,989 35 5,748 100 Above 85 1,655 40 2,476 60 4,131 100 Total 448,169 48 480,353 52 928,521 100 Number % Number % Number % Less than 4 56,710 13 56,169 12 112,880 12 05 - 09 65,699 15 63,991 13 129,690 14 10 - 14 64,574 14 53,797 11 118,371 13 15 - 19 41,722 9 40,819 8 82,542 9 20 - 24 31,041 7 45,872 10 76,913 8 25 - 29 30,465 7 46,478 10 76,943 8 30 - 34 29,098 6 37,108 8 66,206 7 35 - 39 23,203 5 29,556 6 52,759 6 40 - 44 21,242 5 25,670 5 46,912 5 45 - 49 15,460 3 15,424 3 30,884 3 50 - 54 16,136 4 17,660 4 33,796 4 55 - 59 12,892 3 9,534 2 22,426 2 60 - 64 13,635 3 14,083 3 27,718 3 65 - 69 9,017 2 9,371 2 18,388 2 70 - 74 8,075 2 6,162 1 14,237 2 75 - 79 3,783 1 4,194 1 7,977 1 80 - 84 3,759 1 1,989 0 5,748 1 Above 85 1,655 0 2,476 1 4,131 0 Total 448,169 100 480,353 100 928,521 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 134 Number % Number % Number % Mtwara Rural 92,275 48 98,541 52 190,816 100 Newala 75,262 47 84,909 53 160,171 100 Masasi 187,360 49 196,768 51 384,128 100 Tandahimba 86,823 48 94,051 52 180,874 100 Mtwara Urban 6,449 51 6,083 49 12,532 100 Total 448,169 48 480,353 52 928,521 100 Number % Number % Number % Number % Number % Mtwara Rural 85,654 51 3,971 2 1,378 0.8 75,852 45 166,854 100 Newala 91,305 65 3,794 3 0 0.0 46,447 33 141,545 100 Masasi 211,525 63 12,238 4 326 0.1 114,320 34 338,409 100 Tandahimba 87,491 55 2,755 2 186 0.1 67,774 43 158,206 100 Mtwara Urban 6,009 57 206 2 0 0.0 4,413 42 10,628 100 Total 481,984 59 22,962 3 1,890 0.2 308,805 38 815,642 100 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 135 Number % Number % Number % Number % Mtwara Rural 38,537 23 56,358 34 71,960 43 166,854 100 Newala 37,687 27 64,455 46 39,403 28 141,545 100 Masasi 86,791 26 157,705 47 93,913 28 338,409 100 Tandahimba 34,202 22 61,452 39 62,553 40 158,206 100 Mtwara Urban 2,630 25 4,036 38 3,962 37 10,628 100 Total 199,846 25 344,005 42 271,791 33 815,642 100 Number % Number % Number % Number % Number % Number % Mtwara Rural 95,296 57 89 0 - - 5,330 3 902 1 951 1 Newala 88,286 62 290 0 - - 96 0 854 1 283 0 Masasi 212,373 63 639 0 - - - - 1,620 0 642 0 Tandahimba 100,491 64 184 0 161 0 - - 378 0 283 0 Mtwara Urban 5,443 51 - - - - - - 185 2 35 0 Total 501,889 62 1,202 0 161 0 5,426 1 3,939 0 2,195 0 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal Private - NGO / Mission / etc Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 136 cont… Number % Number % Number % Number % Number % Number % Mtwara Rural 1,096 1 1,112 1 1,373 1 513 0 1,700 1 688 0 Newala 1,135 1 369 0 785 1 278 0 - - 1,030 1 Masasi 1,899 1 632 0 765 0 638 0 325 0 793 0 Tandahimba 289 0 1,506 1 1,502 1 727 0 1,573 1 274 0 Mtwara Urban 128 1 458 4 - - 312 3 98 1 58 1 Total 4,546 1 4,078 0 4,425 1 2,467 0 3,696 0 2,844 0 cont… Number % Number % Number % Number % Mtwara Rural 36,332 22 17,802 11 3,670 2 166,854 100 Newala 36,050 25 9,221 7 2,868 2 141,545 100 Masasi 80,979 24 18,400 5 18,704 6 338,409 100 Tandahimba 32,244 20 15,719 10 2,877 2 158,206 100 Mtwara Urban 2,526 24 998 9 385 4 10,628 100 Total 188,130 23 62,140 8 28,503 3 815,642 100 Number % Number % Number % Number % Number % Mtwara Rural 52,233 31 30,570 18 45,612 27 38,440 23 166,854 100 Newala 54,436 38 11,891 8 48,512 34 26,706 19 141,545 100 Masasi 130,525 39 36,812 11 78,720 23 92,353 27 338,409 100 Tandahimba 81,232 51 14,531 9 17,816 11 44,628 28 158,206 100 Mtwara Urban 1,569 15 844 8 4,451 42 3,763 35 10,628 100 Total 319,994 39 94,647 12 195,111 24 205,889 25 815,642 100 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, Student Unable to Work / Too Old / Retired / Sick / Disabled Other Total Unpaid Family Helper (Non Agriculture) District Self Employed (Non Farmimg) with Employees 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total Self Employed (Non Farmimg) without Employees Not Working & Available Not Working & Unavailable Housemaker / Housewife Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 137 Number % Number % Number % Number % Number % Number % Number % Mtwara Rural 1952 3 561 1 2006 4 1913 3 5971 11 2072 4 1755 3 Newala 386 1 0 0 1131 2 1063 2 8131 13 960 1 1149 2 Masasi 805 1 328 0 3865 2 5175 3 23849 15 3411 2 5635 4 Tandahimba 563 1 96 0 1213 2 1036 2 4367 7 1212 2 1208 2 Mtwara Urban 35 1 0 0 155 4 0 0 549 14 147 4 26 1 Total 3741 1 985 0 8370 2 9188 3 42867 12 7,801 2 9,772 3 Number % Number % Number % Number % Number % Mtwara Rural Newala 35,730 63 301 1 603 1 89 0 93 0 Masasi 48,770 76 676 1 375 1 197 0 94 0 Tandahimba 108,980 69 2,105 1 145 0 162 0 0 0 Mtwara Urban 47,213 77 731 1 97 0 88 0 0 0 Total 2,660 66 58 1 64 2 0 0 0 0 Number % Number % Number % Number % Number % Mtwara Rural 515 1 87 0 675 1 0 0 0 0 Newala 278 0 0 0 573 1 0 0 293 0 Masasi 327 0 328 0 2,100 1 162 0 162 0 Tandahimba 177 0 81 0 1,285 2 0 0 189 0 Mtwara Urban 34 1 0 0 121 3 0 0 0 0 Total 1,332 0 496 0 4,755 1 162 0 645 0 Number % Number % Mtwara Rural 2,034 4 56,358 100 Newala 377 1 64,455 100 Masasi 164 0 157,705 100 Tandahimba 1,898 3 61,452 100 Mtwara Urban 187 5 4,036 100 Total 4,660 1 344,005 100 cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Adult Education Total cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Form Two Form Three Form Four District Training After Secondary Education District cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Form Six Pre Form One Form One Standard Seven Standard Eight Training After Primary Education District Education Level Standard Five Standard Six Standard Three Under Standard One Standard One Standard Two Standard Four Tanzania Agriculture Sample census -2003 Mtwara Appendix II 138 Number % Average Household Size Number % Average Household Size Number % Average Household Size Mtwara Rural 34,507 80 4 10,647 20 3 190,816 45,154 4 Newala 33,153 82 4 9,912 18 3 160,171 43,065 4 Masasi 74,391 82 4 22,029 18 3 384,128 96,421 4 Tandahimba 31,288 78 4 10,535 22 4 180,874 41,823 4 Mtwara Urban 2,240 80 5 611 20 4 12,532 2,850 4 Total 175,579 81 4 53,735 19 3 928,521 229,314 4 Number % Number % Number % Number % Mtwara Rural 25,798 71 6,478 18 3,825 11 36,100 100 Newala 21,875 60 9,536 26 4,796 13 36,207 100 Masasi 30,416 47 22,685 35 11,781 18 64,881 100 Tandahimba 13,559 80 2,616 15 832 5 17,007 100 Mtwara Urban 1,567 63 664 27 252 10 2,483 100 Total 93,214 59 41,978 27 21,486 14 156,678 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Mtwara Rural 20,411 21,608 496 990 0 0 1,648 45,154 Newala 14,400 27,531 280 566 97 0 190 43,065 Masasi 24,797 69,186 0 2,112 162 0 163 96,421 Tandahimba 18,929 20,622 97 721 189 0 1,266 41,823 Mtwara Urban 1,029 1,548 64 90 0 0 121 2,850 Total 79,566 140,495 937 4,479 448 0 3,389 229,314 Mean Median Mode Mean Median Mode Mean Median Mode Mtwara Rural 46 44 40 50 50 60 47 45 40 Newala 43 40 40 53 53 65 45 42 50 Masasi 44 40 32 47 43 70 44 41 32 Tandahimba 44 41 40 52 52 60 46 44 40 Mtwara Urban 45 43 30 51 45 45 47 45 45 Total 44 41 40 50 49 60 45 43 40 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Two More than Two Maximum Education Level Attained District Off farm income One Total 3.10 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year Male Head Female Head Total District 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 139 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 148 143 158 169 144 749 FemaleHeaded (Number in Thousands 44 43 41 48 51 179 Total 192 186 199 217 195 928 Male Headed (Percentage) 77 77 79 78 74 81 Female Headed (Percentage) 23 23 21 22 26 19 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Mtwara Rural 11,997 22,510 34,507 7,242 3,405 10,647 19,239 25,915 45,154 Newala 8,009 25,143 33,153 6,400 3,513 9,912 14,409 28,656 43,065 Masasi 16,620 57,771 74,391 9,158 12,871 22,029 25,778 70,643 96,421 Tandahimba 10,526 20,762 31,288 7,945 2,591 10,535 18,471 23,352 41,823 Mtwara Urban 574 1,665 2,240 489 121 611 1,064 1,787 2,850 Total 47,727 127,852 175,579 31,233 22,501 53,735 78,960 150,354 229,314 3.14 Time Series of Male and Female Headed Households 3.15 Literacy Rate of Heads of Households By District District Literacy Know Don;t know Total Tanzania Agriculture sample Census -2003 Mtwara Appendix II 140 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Mtwara Appendix ii 141 No. of Households % No. of Househol ds % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mtwara Rural 2,103 4 38,628 70 8,069 15 100 0 4,571 8 80 0 1,442 3 54,993 Newala 1,738 3 37,345 69 7,023 13 2,183 4 4,021 7 1,039 2 845 2 54,195 Masasi 12,848 11 70,955 61 18,676 16 1,911 2 6,286 5 646 1 5,192 4 116,515 Tandahimba 465 1 37,397 77 6,422 13 381 1 3,153 6 284 1 563 1 48,666 Mtwara Urban 119 4 1,384 42 1,071 33 33 1 439 13 26 1 193 6 3,265 Total 17,273 6 185,710 67 41,262 15 4,607 2 18,472 7 2,075 1 8,236 3 277,634 District Area Leased/Certificat e of Ownership Area Owned Under Customary Law Area Bought Area Rented From Others Area Borrowed Area Shared Croped Area under Other Forms of Tenure Total Mtwara Rural 4,272 73,368 14,020 121 2,436 49 2,291 96,556 Newala 2,085 62,831 8,779 2,484 3,629 1,308 493 81,609 Masasi 22,918 122,627 36,800 1,092 4,811 1,043 7,335 196,626 Tandahimba 734 79,298 12,215 212 1,732 770 1,212 96,173 Mtwara Urban 122 2,193 1,931 66 299 5 314 4,930 Total 30,132 340,316 73,745 3,976 12,908 3,174 11,645 475,895 % 6 72 15 1 3 1 2 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Total Number of Households Land Access 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Households with Area under Other Forms of Tenure Households with Area Shared Croped Borrowed Rented Bought Owned Under Customary Law Leased/Certificate of Ownership Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 142 Total Total Number % Number % Number Number % Number % Number Mtwara Rural 29,979 66 15,175 34 45,154 Mtwara Rural 30,671 68 14,483 32 45,154 Newala 30,586 71 12,479 29 43,065 Newala 28,634 66 14,431 34 43,065 Masasi 78,782 82 17,639 18 96,421 Masasi 70,508 73 25,912 27 96,421 Tandahimba 30,877 74 10,865 26 41,743 Tandahimba 25,652 61 16,091 39 41,743 Mtwara Urban 1,571 56 1,249 44 2,819 Mtwara Urban 1,321 47 1,498 53 2,819 Total 171,795 75 57,407 25 229,202 Total 156,787 68 72,415 32 229,202 Total Number % Number % Number Mtwara Rural 11,369 25 33,785 75 45,154 Newala 20,280 47 22,785 53 43,065 Masasi 25,642 27 70,779 73 96,421 Tandahimba 11,716 28 30,027 72 41,743 Mtwara Urban 695 25 2,124 75 2,819 Total 69,703 30 159,499 70 229,202 No Table 4.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Customary right to land Yes No Was all Land Available to the Hh Used During 2002/03? Table 4.4: Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District, 2002/03 Agricultural Year District Yes No Do you Consider that you have sufficient land for the Hh? Table 4.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Yes Tazania Agriculture Sample Census - 2003 Mtwara 143 Appendix II 144 LAND USE Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 145 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Mtwara Rural 19,755 16,016 24,908 4,809 9,268 537 2,830 3,721 20 711 3,150 10,831 96,556 Newala 10,354 26,781 10,369 1,848 17,327 58 6,649 2,322 205 402 268 4,935 81,517 Masasi 21,527 77,427 39,996 3,507 44,047 394 949 33 179 988 999 6,976 197,020 Tandahimba 11,389 15,688 29,666 1,232 26,229 39 511 273 . 77 59 11,010 96,173 Mtwara Urban 651 755 538 467 1,338 . 597 7 . 102 68 408 4,930 Total 63,675 136,667 105,477 11,863 98,209 1,027 11,536 6,356 403 2,280 4,543 34,159 476,196 Households with Area under Temporary Mono Crops Households with Area under Temporary Mixed Crops Households with Area under Permanent Mono Crops Households with Area under Permanent Mixed Crops Households with Area under Permanent / Annual Mix Households with Area under Pasture Households with Area under Fallow Households with Area under Natural Bush Households with Area under Planted Trees Households with Area Rented to Others Households with Area Unusable Households with Area of Uncultivated Usable Land Mtwara Rural 26,675 19,341 22,709 4,240 8,069 195 1,936 1,348 100 404 1,626 9,442 Newala 12,950 29,635 12,695 2,692 13,486 188 6,593 1,424 194 581 283 4,220 Masasi 32,927 67,331 32,266 2,588 23,032 162 1,610 164 803 804 799 8,318 Tandahimba 15,678 17,377 21,774 1,098 15,665 95 945 386 0 95 97 8,850 Mtwara Urban 1,220 1,203 671 418 934 0 591 33 0 93 66 372 Total 89,449 134,887 90,115 11,036 61,186 641 11,674 3,354 1,097 1,978 2,871 31,202 5.1 LAND USE: Area of Land by type of Land Use and District during 2002/03 Agricultural Year District Land Use 5.2 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Type of Land Use Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 146 ANNUAL CROP AND VEGETABLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 147 Number of Households Planted Area Number of Households Planted Area Mtwara Rural 200 141 92,494 40,149 40,290 0.35 Newala 94 191 137,357 50,614 50,805 0.38 Masasi 0 0 242,471 117,031 117,031 0.00 Tandahimba 92 149 98,071 45,251 45,400 0.33 Mtwara Urb 0 0 5,979 2,878 2,878 0.00 Total 386 481 576,372 255,923 256,405 1.05 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Mtwara Rural 200 92494 86,435 Newala 94 137357 45,700 Masasi 0 242471 48,815 Tandahimba 92 98071 8,555 Mtwara Urb 0 5979 7,076 Total 386 11682 576372 1068 47,631 7.1 & 7.2a: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) by season and District District Total Area Planted (hectare) % Area planted in Dry season Dry Season Wet Season 7.1 & 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District District Dry Season Wet Season Total Number of Crop Growing Households Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 148 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 272 94 106,563 39,635 106,835 39,730 Maize 272 94 347 71,743 29,512 411 72,015 29,607 411 Paddy 0 0 0 14,018 4,932 352 14,018 4,932 352 Sorghum 0 0 0 20,569 5,048 245 20,569 5,048 245 Bulrush Millet 0 0 0 32 71 2,223 32 71 2223 Finger Millet 0 0 0 201 73 361 201 73 361 Wheat 0 0 0 0 0 0 0 0 0 Barley 0 0 0 0 0 0 0 0 0 ROOTS & TUBERS 61 50 114,248 72,224 114,309 72,274 Cassava 61 50 823 114,097 72,037 631 114,157 72,087 631 Sweet Potatoes 0 0 0 38 77 2,043 38 77 2043 Irish Potatoes 0 0 0 10 2 198 10 2 198 Yams 0 0 0 75 78 1,046 75 78 1046 Cocoyam 0 0 0 29 29 1,001 29 29 1001 PULSES 0 0 14,171 4,253 14,171 4,253 Mung Beans 0 0 0 21 105 4,940 21 105 4940 Beans 0 0 0 260 177 681 260 177 681 Cowpeas 0 0 0 5,333 1,229 230 5,333 1,229 230 Green Gram 0 0 0 1,040 279 269 1,040 279 269 Pigeon Peas 0 0 0 131 97 741 131 97 741 Chich Peas 0 0 0 40 0 0 40 0 0 Bambaranuts 0 0 0 7,346 2,366 322 7,346 2,366 322 Field Peas 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 0 0 19,849 6,124 19,849 6,124 Sunflower 0 0 0 0 0 0 0 0 0 Simsim 0 0 0 3,512 979 279 3,512 979 279 Groundnuts 0 0 0 16,330 5,137 315 16,330 5,137 315 Soya Beans 0 0 0 0 0 0 0 0 0 Castor Seed 0 0 0 8 8 988 8 8 988 FRUITS & VEGETABLES 0 0 949 2,123 949 2,123 Okra 0 0 0 68 278 4,117 68 278 4117 Radish 0 0 0 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 0 0 0 Onions 0 0 0 75 71 937 75 71 937 Ginger 0 0 0 35 0 0 35 0 0 Cabbage 0 0 0 0 0 0 0 0 0 Tomatoes 0 0 0 521 1,326 2,543 521 1,326 2543 Spinnach 0 0 0 0 0 0 0 0 0 Carrot 0 0 0 0 0 0 0 0 0 Chillies 0 0 0 0 0 0 0 0 0 Amaranths 0 0 0 20 0 25 20 0 25 Pumpkins 0 0 0 128 299 2,337 128 299 2337 Cucumber 0 0 0 12 2 206 12 2 206 Egg Plant 0 0 0 68 94 1,370 68 94 1370 Water Mellon 0 0 0 22 53 2,422 22 53 2422 Cauliflower 0 0 0 0 0 0 0 0 0 CASH CROPS 149 61 142 32 291 94 0 Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 0 0 0 0 0 0 Tobacco 149 61 412 142 32 226 291 94 639 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 Total 481 255,923 256,405 Table 7.1 & 7.2c: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year, Mtwara Region Crop Dry Season Wet Season Total Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 149 Number of Households Area Planted (ha) Number of Households Area Planted (ha) CEREALS 61 12 331,599 280,644 280,656 0.004 Maize 61 12 271,618 253,874 253,874 0.005 Paddy 0 0 8,760 4,666 4,666 0.000 Sorghum 0 0 5,741 2,555 2,555 0.000 Finger Millet 0 0 9,956 3,326 3,326 0.000 Wheat 0 0 35,524 16,223 16,223 0.000 ROOTS & TUBERS 0 0 61,538 23,839 23,839 0.000 Cassava 0 0 11,204 4,737 4,737 0.000 Sweet Potatoes 0 0 4,534 649 649 0.000 Irish Potatoes 0 0 44,849 18,178 18,178 0.000 Yams 0 0 706 227 227 0.000 Cocoyam 0 0 246 48 48 0.000 PULSES 62 13 199,901 70,483 70,496 0.02 Mung Beans 0 0 12 4 4 0.00 Beans 0 0 165,191 59,661 59,661 0.00 Cowpeas 0 0 13,800 4,112 4,112 0.00 Green Gram 0 0 260 89 89 0.00 Chich Peas 0 0 0 0 0 0.00 Bambaranuts 0 0 1,682 848 848 0.00 Field Peas 62 13 18,955 5,769 5,769 0.23 OIL SEEDS & OIL NUTS 53,071 24,570 24,570 0.0 Sunflower 0 0 37,496 15,674 15,674 0.0 Simsim 0 0 1,575 1,245 1,245 0.0 Groundnuts 0 0 14,001 7,650 7,650 0.0 Castor Seed 0 0 0 0 0 0.0 FRUITS & VEGETABLES 0 0 25,855 5,625 5,625 0.0 Okra 0 0 96 21 21 0.0 Radish 0 0 0 0 0 0.0 Bitter Aubergine 0 0 0 0 0 0.0 Onions 0 0 1,970 386 386 0.0 Ginger 0 0 59 12 12 0.0 Cabbage 0 0 7,478 1,380 1,380 0.0 Tomatoes 0 0 11,796 3,274 3,274 0.0 Spinnach 0 0 2,006 154 154 0.0 Carrot 0 0 60 3 3 0.0 Chillies 0 0 251 196 196 0.0 Amaranths 0 0 974 86 86 0.0 Pumpkins 0 0 1,090 111 111 0.0 Cucumber 0 0 0 0 0 0.0 Egg Plant 0 0 12 1 1 0.0 Water Mellon 0 0 62 2 2 0.0 CASH CROPS 0 0 734 396 396 0.0 Pyrethrum 0 0 618 336 336 0.0 Cotton 0 0 0 0 0 0.0 Tobacco 0 0 116 60 60 0.0 Jute 0 0 0 0 0 0.0 Total 25 405,556 405,581 0.0 Total Area Planted Dry & Wet Seasons % Area Planted in Dry season Table 7.1 & 7.2d : TOTAL CROP AND VEGETABLE PRODUCTION: Number of Agricultural Households by Area Planted (ha) and Crop for Agricultural Year 2002/03 - Dry anf Wet Seasons, Mtwara region. Crop Dry Season Wet Season Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 150 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mtwara Rural 92 9 2,071 2,092 42,373 37,927 44,536 40,029 Newala 293 187 1,899 3,621 40,390 46,836 42,583 50,644 Masasi 3,549 3,410 1,460 1,533 90,761 111,325 95,770 116,268 Tandahimba 180 128 2,858 2,550 38,332 42,722 41,370 45,400 Mtwara Urban 89 74 0 0 2,562 2,613 2,651 2,686 Total 4,204 3,808 8,287 9,796 214,418 241,423 226,910 255,027 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Total Planted Area Mtwara rural 590 482 515 375 0 0 43,640 39,433 40,290 Newala 1,637 3,014 778 919 1,899 2,267 38,268 44,604 50,805 Masasi 486 669 0 0 317 1,358 94,967 115,004 117,031 Tandahimba 2,156 4,617 194 69 0 0 39,021 40,714 45,400 Mtwara urban 93 80 68 69 0 0 2,626 2,729 2,878 Total 4,961 8,862 1,555 1,432 2,216 3,626 218,522 242,485 256,405 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mtwara Rural 637 623 44,517 39,808 45,154 40,432 1.5 Newala 94 11 42,971 50,984 43,065 50,996 0.0 Masasi 1,110 193 95,311 116,838 96,421 117,031 0.2 Tandahimba 2,185 1,247 39,638 44,302 41,823 45,549 2.7 Mtwara Urban - - 2,850 2,878 2,850 2,878 0.0 Total 4,027 2,075 225,287 254,811 229,314 256,886 0.8 % 2 1 98 99 100.0 100.0 1 % of Area planted under irrigation 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agricultural Households and Planted Area By Irrigation Use and District for the 2002/03 Agricultural - Wet and Dry seasons - Mtwara region. Note: Number of households is over estimated due to double counting of households growing crops in both wet and dry seasons. To compare previous surveys use Number of wet season planters only. District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Wet & Dry Seasons- Mtwara Region. Mostly Oxen Ploughing Mostly Hand Cultivation Total District Soil Preparation Mostly Tractor Ploughing 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Wet & Dry season - Mtwara Region. District Fertilisers Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 151 Number of Household Using Planted Area Number of Household Planted Area Number of Household Planted Area Mtwara Rural 206 206 44,639 40,226 44,845 40,432 0.51 Newala 681 2,264 41,996 48,732 42,677 50,996 4.44 Masasi 319 452 95,451 116,579 95,770 117,031 0.39 Tandahimba 188 227 41,274 45,322 41,462 45,549 0.50 Mtwara Urban 0 0 2,786 2,878 2,786 2,878 0.00 Total 1,395 3,149 226,145 253,737 227,540 256,886 1.23 % 6 1 896 99 902 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mtwara Rural 515 348 44,230 39,942 44,745 40,290 0.86 Newala 1,534 1,970 41,048 48,835 42,583 50,805 3.88 Masasi 622 682 95,148 116,350 95,770 117,031 0.58 Tandahimba 1,285 1,623 40,085 43,777 41,370 45,400 3.57 Mtwara Urban 101 184 2,685 2,694 2,786 2,878 6.40 Total 4,057 4,806 223,198 251,598 227,254 256,405 1.87 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mtwara Rural 3,753 3,090 40,783 36,938 44,536 40,029 7.72 Newala 861 872 41,722 49,773 42,583 50,644 1.72 Masasi 1,754 2,698 94,016 113,570 95,770 116,268 2.32 Tandahimba 566 625 40,804 44,775 41,370 45,400 1.38 Mtwara Urban 58 99 2,593 2,587 2,651 2,686 3.70 Total 6,991 7,384 219,919 247,644 226,910 255,027 2.90 % 3 3 97 97 100 100 District 7.1 & 7.2k TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Improved seed Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Mtwara region. Improved Seed Use % of Planted Area using Insecticide Total Households Using Households Not Using 7.1 & 7.2j TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Fungicide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Mtwara region. g Fungicide g Fungicide Total Fungicide Use % of Planted Area using Insecticide District 7.1 & 7.2i TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Herbicide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Mtwara region. District Herbicide Use % of Planted Area using Herbicide Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mtwara Rural - - - - 100 141 100 141 Newala - - - - 94 191 94 191 Masasi - - - - - - - - Tandahimba - - - - 92 149 92 149 Mtwara Urban - - - - - - - - Total - - - - 286 481 286 481 % 0 0 0 0 100 100 100 100 Number of Households Planted Area Number of Households Planted Area Mtwara Rural 100 141 100 141 Newala 94 191 94 191 Tandahimba 92 149 92 149 Total 286 481 286 481 Number of Household Planted Area Number of Household Planted Area Mtwara Rural 100 141 100 141 Newala 94 191 94 191 Tandahimba 92 149 92 149 Total 286 481 286 481 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Mtwara Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1b: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-DRY SEASON - Mtwara Region District Fertilizer Use No Fertilizer Applied Total 7.1c: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year DRY SEASON - Mtwara Region District Irrigation Use Households Not Using Total Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mtwara Rural 92 9 2,071 2,092 42,274 37,786 44,436 39,887 Newala 293 187 1,899 3,621 40,296 46,645 42,488 50,453 Masasi 3,549 3,410 1,460 1,533 90,761 111,325 95,770 116,268 Tandahimba 180 128 2,858 2,550 38,240 42,573 41,278 45,251 Mtwara Urban 89 74 0 . 2,562 2,613 2,651 2,686 Total 4,204 3,808 8,287 9,796 214,132 240,942 226,624 254,546 % 2 1 4 4 94 95 100 100 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Mtwara Rural 590 482 515 375 0 . 43,540 39,291 44,645 40,149 Newala 1,637 3,014 778 919 1,899 2,267 38,174 44,413 42,488 50,614 Masasi 486 669 0 . 317 1,358 94,967 115,004 95,770 117,031 Tandahimba 2,156 4,617 194 69 0 . 38,929 40,566 41,278 45,251 Mtwara Urban 93 80 68 69 0 . 2,626 2,729 2,786 2,878 Total 4,961 8,862 1,555 1,432 2,216 3,626 218,236 242,003 226,968 255,923 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Mtwara Rural 530 784 44,116 39,365 44,645 40,149 Newala 288 214 42,201 50,400 42,488 50,614 Masasi 793 1,257 94,977 115,774 95,770 117,031 Tandahimba 1,458 1,237 39,820 44,015 41,278 45,251 Mtwara Urban 65 158 2,721 2,720 2,786 2,878 Total 3,135 3,650 223,834 252,274 226,968 255,923 72a: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year- WET SEASON - Mtwara Region Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total District 7.2b: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-WET SEASON - Mtwara Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.2c: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON - Mtwara Region District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Cenusus - 2003 Mtwara Appendix II 154 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 100 81 0 0.00 18,609 5,537 2,038 0.37 5,617 2,038 0.36 Newala 94 191 94 0.49 40,113 15,352 7,704 0.50 15,543 7,799 0.50 Masasi 0 0 0 0.00 80,053 41,922 17,352 0.41 41,922 17,352 0.41 Tandahimba 0 0 0 0.00 23,125 8,427 2,321 0.28 8,427 2,321 0.28 Mtwara Urb 0 0 0 0.00 1,674 505 98 0.19 505 98 0.19 Total 194 272 94 163,573 71,743 29,512 72,015 29,607 0.41 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 10,541 4,264 1,469 0.34 4,264 1,469 0.34 Newala 0 0 0 0.00 4,475 1,385 579 0.42 1,385 579 0.42 Masasi 0 0 0 0.00 16,655 5,914 1,722 0.29 5,914 1,722 0.29 Tandahimba 0 0 0 0.00 4,945 2,419 1,157 0.48 2,419 1,157 0.48 Mtwara Urb 0 0 0 0.00 163 36 5 0.13 36 5 0.13 Total 0 0 0 36,779 14,018 4,932 0.35 14,018 4,932 0.35 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 15,878 4,741 1,444 0.30 4,741 1,444 0.30 Newala 0 0 0 0.00 17,955 4570 1300 0 4570 1,300 0.28 Masasi 0 0 0 0.00 15,965 6,524 1,789 0.27 6,524 1,789 0.27 Tandahimba 0 0 0 0.00 16,087 4,457 472 0.11 4,457 472 0.11 Mtwara Urb 0 0 0 0.00 1,033 276 43 0.15 276 43 0.15 Total 0 0 0 66,919 20,569 5,048 20,569 5,048 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 195 43 12 0.3 43 12 0.3 Masasi 0 0 0 0.00 483 90 50 0.6 90 50 0.6 Tandahimba 0 0 0 0.00 384 68 11 0.2 68 11 0.2 Mtwara Urb 0 0 0 0.00 0 0 0 0.0 0 0 0.0 Total 0 0 0 1062 201 73 201 73 7.2.4: Number of Crop Growing Households, Planted Area (ha) and Finger Millet Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Finger Millet Dry Season Wet Season Total 7.1: Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Maize Dry Season Wet Season Total 7.2.2: Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Paddy Dry Season Wet Season Total 7.2.3: Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Sorghum Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 155 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 158 32 71 2.22 32 71 2.22 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 158 32 71 32 71 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 100 61 50 0.82 37,442 23,065 16,505 7.00 23,126 16,555 0.72 Newala 0 0 0 0.00 40,423 21,752 17,169 0.79 21,752 17,169 0.79 Masasi 0 0 0 0.00 72,292 41,873 19,510 0.47 41,873 19,510 0.47 Tandahimba 0 0 0 0.00 35,885 25,434 18,293 0.72 25,434 18,293 0.72 Mtwara Urb 0 0 0 0.00 2,603 1,972 560 0.28 1,972 560 0.28 Total 100 61 50 188,644 114,097 72,037 114,097 72,037 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0 283 38 77 2.04 38 77 2.04 Mtwara Urb 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 283 38 77 38 77 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0 95 10 2 0.20 10 2 0.20 Masasi 0 0 0 0 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 95 10 2 10 2 7.2.8: Number of Crop Growing Households, Planted Area (ha) and Irish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Irish Potatoes Dry Season Wet Season Total 7.2.7: Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Sweet Potatoes Dry Season Wet Season Total 7.2.5: Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Bulrush Millet Dry Season Wet Season Total 7.2.6: Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year - Mtwara Region District Cassava Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 156 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 283 71 68 0.96 71 68 0.96 Mtwara Urb 0 0 0 0.00 33 3 10 2.96 3 10 2.96 Total 0 0 0 315 75 78 75 78 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 94.051 6 15 2.47 6 15 2.47 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 96 23 14 0.62 23 14 0.62 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 190 29 29 29 29 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 105 21 105 4.94 21 105 4.94 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 105 21.2 105 21.2 105 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 107 65 91 1.40 65 91 1.40 Newala 0 0 0 0.00 94 10 2 0.20 10 2 0.20 Masasi 0 0 0 0.00 490 186 85 0.46 186 85 0.46 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 691 260 177 260 177 7.2.10: Number of Crop Growing Households, Planted Area (ha) and Cocoyams Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cocoyams Dry Season Wet Season Total 7.2.9: Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District Yams Dry Season Wet Season Total 7.2.11: Number of Crop Growing Households, Planted Area (ha) and Mug beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Mug beans Dry Season Wet Season Total 7.2.12: Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Beans Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 157 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 1,968 320 68 0.21 320 68 0.21 Newala 0 0 0 0 7,134 1,431 259 0.18 1,431 259 0.18 Masasi 0 0 0 0 9,762 2,953 842 0.28 2,953 842 0.28 Tandahimba 0 0 0 0 3,090 583 57 0.10 583 57 0.10 Mtwara Urb 0 0 0 0 247 45 4 0.08 45 4 0.08 Total 0 0 0 22,200 5,333 1,229 5,333 1,229 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 92.14613 18.65306 5.5287675 0.30 18.653 5.5287675 0.30 Newala 0 0 0 0 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0 4044 1022 274 0.27 1022 274 0.27 Tandahimba 0 0 0 0 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 4136 1040 279 1040 279 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 2,338 412 185 0.45 412 185 0.45 Newala 0 0 0 0 12,759 2,902 1,202 0.41 2,902 1,202 0.41 Masasi 0 0 0 0 7,956 2,102 545 0.26 2,102 545 0.26 Tandahimba 0 0 0 0 6,118 1,926 434 0.23 1,926 434 0.23 Mtwara Urb 0 0 0 0 33 4 0 0.04 4 0 0.04 Total 0 0 0 0 29,205 7,346 2,366 7,346 2,366 Wet Season Total 7.2.14: Number of Crop Growing Households, Planted Area (ha) and Green gram Harevsted (tons) by season and District 2002/03 Agricultural Year. District Green gram Dry Season Wet Season Total 7.2.15: Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year. District 7.2.13: Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cowpeas Dry Season Wet Season Total Bambaranuts Dry Season Tanzania Agriculure Sample Census- 2003 Mtwara Appendix II 158 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 106 44 265 6.05 44 265 6.05 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 251 24 13 0.54 24 13 0.54 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 357 68 278 68 278 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 1127 372 45 0 372 45 0 Newala 0 0 0 0 376 67 8 0 67 8 0 Masasi 0 0 0 0 8991 3021 923 0 3021 923 0 Tandahimba 0 0 0 0 386 52 3 0.06 52 3 0.06 Mtwara Urb 0 0 0 0 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 10,880 3,512 979 3,512 979 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0 0 0 0.00 Newala 0 0 0 0.00 98 8 8 1 8 8 0.99 Masasi 0 0 0 0.00 0 0 0 0 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0 0 0 0.00 Total 0 0 0 98 8 8 8 8 7.2.18: Number of Crop Growing Households, Planted Area (ha) and SimsimHarevsted (tons) by season and District 2002/03 Agricultural Year. District Simsim Dry Season Wet Season Total 7.2.20: Number of Crop Growing Households, Planted Area (ha) and Castor Seed Harevsted (tons) by season and District 2002/03 Agricultural Year. District Castor Seed Dry Season Wet Season Total 7.2.17: Number of Crop Growing Households, Planted Area (ha) and Okra Harevsted (tons) by season and District 2002/03 Agricultural Year. District Okra Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 159 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Plante d Area (ha) Quantity Harveste d (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 279 54 42 0.77 54 42 0.77 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 161 21 29 1.37 21 29 1.37 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 440 75 71 75 71 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Plante d Area (ha) Quantity Harveste d (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0 0 0 0 0 0 0 0 Newala 0 0 0 0 0 0 0 0 0 0 0 Masasi 0 0 0 0 144.9123 35 0 0 35 0 0 Tandahimba 0 0 0 0 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 145 35 0 35 0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Plante d Area (ha) Quantity Harveste d (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 98 12 2 0.21 12 2 0.21 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 98 12 2 12 2 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Plante d Area (ha) Quantity Harveste d (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 743 295 1,058 3.59 295 1,058 3.59 Newala 0 0 0 0.00 89 18 18 0.99 18 18 0.99 Masasi 0 0 0 0.00 163 33 10 0.30 33 10 0.30 Tandahimba 0 0 0 0.00 860 175 240 1.37 175 240 1.37 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 1,856 521 1,326 521 1,326 7.2.24: Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tomatoes Dry Season Wet Season Total 7.2.22: Number of Crop Growing Households, Planted Area (ha) and Ginger Harevsted (tons) by season and District 2002/03 Agricultural Year. District Ginger Dry Season Wet Season Total 7.2.21: Number of Crop Growing Households, Planted Area (ha) and Onion Harevsted (tons) by season and District 2002/03 Agricultural Year. District Onion Dry Season Wet Season Total 7.2.23: Number of Crop Growing Households, Planted Area (ha) and Cucumber Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cucumber Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 160 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 99 20 0 0.00 20 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0 7.2.26: Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year. 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Chillies Harevsted (tons) by season and District 2002/03 Agricultural Year. District Chillies Dry Season Wet Season Total District Carrot Dry Season Wet Season Total 7.2.28: Number of Crop Growing Households, Planted Area (ha) and Amaraths Harevsted (tons) by season and District 2002/03 Agricultural Year. District Amaranths Dry Season Wet Season Total 7.2.25: Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year. District Spinach Dry Season Wet Season Total Tanzania Agreiculture Sample Census - 2993 Mtwara Appendix II 161 No.of H/holds Plante d Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 411.475 88.6695 279.277925 3.15 88.6695 279.277925 3.15 Newala 0 0 0 0.00 98.228 15.9074 3.53620958 0.22 15.9074 3.53620958 0.22 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 287 23 16 0.68 23 16 0.68 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 796 128 299 128 299 No.of H/holds Plante d Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 106 22 64 2.91 22 64 2.91 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 591 46 30 0.64 46 30 0.64 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 697 68 94 68 94 No.of H/holds Plante d Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 106 22 53 2.42 22 53 2.42 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 106 22 53 22 53 No.of H/holds Plante d Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 159 13 5 0.37 13 5 0.37 Tandahimba 92 149 61 0.41 183 129 27 0.21 129 27 0.21 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 92 149 61 342 142 32 142 32 7.2.29: Number of Crop Growing Households, Planted Area (ha) and Pumpkin Harevsted (tons) by season and District 2002/03 Agricultural Year. District Pumpkin Dry Season Wet Season Total 7.2.32: Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tobacco Dry Season Wet Season Total 7.2.31: Number of Crop Growing Households, Planted Area (ha) and Water MellonHarevsted (tons) by season and District 2002/03 Agricultural Year. District Water Mellon Dry Season Wet Season Total 7.2.30: Number of Crop Growing Households, Planted Area (ha) and Egg plant Harevsted (tons) by season and District 2002/03 Agricultural Year. District Egg Plant Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 162 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No. of H/holds Plante d Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mtwara Rur 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Newala 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Masasi 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Tandahimba 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Mtwara Urb 0 0 0 0.00 0 0 0 0.00 0 0 0.00 Total 0 0 0 0 0 0 0 0 7.2.32: Number of Crop Growing Households, Planted Area (ha) and Pyrthrum Harevsted (tons) by season and District 2002/03 Agricultural Year. District Pyrethrum Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Mtwara 163 Appendix II 164 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 165 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Sour Soup 86 86 11 124 Pigeon Pea 141 47 10 209 Star Fruit . - 35 - Coconut 5,339 1,642 1,576 960 Cashewnut 45,633 23,982 5,344 223 Cloves 212 42 16 371 Banana . 21 64 2,988 Mango 71 18 141 7,768 Pawpaw 208 208 9 43 Orange 264 94 486 5,149 Total 51,953 26,142 7,691 294 Pigeon Pea 600 204 50 245 Coconut 152 40 29 737 Cashewnut 32,957 14,870 8,349 561 Sugarcane 45 7 18 2,470 Mpesheni 40 - . - Banana 419 429 100 233 Pawpaw 81 24 13 550 Pineapple 22 4 7 1,828 Orange 30 10 39 3,965 Mandarine/Tanger 12 - . - Guava 20 10 . - Total 34,377 15,597 8,606 552 Pigeon Pea 7,084 18,258 1,774 97 Coconut 197 99 38 384 Cashewnut 91,794 53,351 11,235 211 Banana 7 7 16 2,470 Mango 817 13 57 4,323 Pawpaw . . 1 - Orange 74 66 328 4,963 Guava . . 20 - Total 99,972 71,793 13,471 188 Coconut 100 37 . - Cashewnut 57,200 34,045 13,212 388 Mango 2,906 4 2 494 Total 60,206 34,086 13,214 388 Pigeon Pea 16 10 3 294 Coconut 158 80 287 3,581 Cashewnut 494 412 155 376 Banana . . 31 - Mango 11 11 113 10,519 Pawpaw . . . - Pineapple . . 1 - Orange . . 15 - Guava . . 1 - Total 679 513 606 1,182 7.3: Production of Permanent Crops by Crop Type and Region -Mtwara Mtwara Rural Newala Masasi Tandahimba Mtwara Urban Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 166 Sour Soup 86 86 11 124 Pigeon Pea 7,841 18,518 1,836 99 Star Fruit . . 35 - Coconut 5,947 1,898 1,931 1,017 Cashewnut 228,078 126,660 38,295 302 Sugarcane 45 7 18 2,470 Cloves 212 42 16 371 Mpesheni 40 - . - Banana 426 457 212 464 Mango 3,804 46 313 6,803 Pawpaw 289 232 23 98 Pineapple 22 4 7 2,054 Orange 369 170 868 5,093 Mandarine/Tangerine 12 - . - Guava 20 10 21 2,149 Total 247,188 148,131 43,587 294 Cont…..Production of Permanet by Type and Region. Crop Area planted % Cashewnut 228078 92.3 Pigeon Pea 7841 3.2 Coconut 5947 2.4 Mango 3804 1.5 Banana 426 0.2 Orange 369 0.1 Pawpaw 289 0.1 Cloves 212 0.1 Sour Soup 86 0.0 Sugarcane 45 0.0 Mpesheni 40 0.0 Pineapple 22 0.0 Guava 20 0.0 Mandarine/Tangerine 12 0.0 Total 247188 100.0 cont...Production of Permanent Crops by Crop Type and Region - Mtwara Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 167 District Area Planted with cashewnut Total area planted (ha) % of total area planted (ha) hh with Cashewnut s Average planted area per household District Area planted(Ha) Total area planted (ha) % of total area planted hh with Pegion pea Average planted area per household Mtwara Rural 45,633 92,244 20.01 49,145 1.87 Mtwara Rural 141 92,244 1.8 30,188 0.00 Newala 32,957 85,182 14.45 31,255 1.83 Newala 600 85,182 7.7 26,692 0.02 Masasi 91,794 217,004 40.25 26,153 1.74 Masasi 7,084 217,004 90.3 74,652 0.09 Tandahimba 57,200 105,606 25.08 23,722 1.39 Tandahimba 0 105,606 0.0 31,631 0.00 Mtwara Urban 494 3,558 0.22 726 0.68 Mtwara Urban 16 3,558 0.2 1,209 0.01 Total 228,078 503,593 100.00 131,000 1.74 Total 7,841 503,593 100.0 164,371 0.05 District Area planted with Coconut(Ha) Total Area planted (ha) % of Total Area Planted hh with coconut Average Planted Area per Household District Area planted with mangos(Ha) Total Area planted (ha) % of Total Area Planted hh with mangoes Average Planted Area per Household Mtwara Rural 5,339 92,244 89.78 3,167 1.69 Mtwara rural 71 51,953 1.86 179 0.39 Newala 152 85,182 2.56 393 0.39 Newala 0 34,377 0.00 0 0.00 Masasi 197 217,004 3.32 162 1.21 Masasi 817 99,972 21.47 164 4.98 Tandahimba 100 105,606 1.68 184 0.54 Tandahimba 2,906 60,206 76.39 192 15.12 Mtwara Urban 158 3,558 2.66 348 0.45 Mtwara urban 11 679 0.28 70 0.15 Total 5,947 503,593 100.00 4,255 4.28 Total 3,804 247,188 100.00 605 6.29 Coconut Mango cont……Area Planted and area per household by region -Mtwara Region Cashewnut Pegion pea Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 168 Crop Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total ` 4,607 1,280 5,367 60,489 71,743 Paddy 95 140 50 13,733 14,018 Sorghum 874 114 195 19,385 20,569 Bulrush Millet 0 0 0 32 32 Finger Millet 0 0 12 189 201 Cassava 4,047 1,107 1,058 107,885 114,097 Irish Potatoes 0 0 0 10 10 Sweet Potatoes 0 0 0 38 38 Yams 3 0 0 71 75 Cocoyam 0 0 0 29 29 Mung Beans 0 0 0 21 21 Beans 0 0 0 260 260 Cowpeas 83 7 0 5,243 5,333 Green Gram 0 0 0 1,040 1,040 Chich Peas 0 0 0 40 40 Pigeon Peas 0 0 0 131 131 Bambaranuts 115 21 48 7,163 7,346 Simsim 0 0 0 3,512 3,512 Groundnuts 232 14 62 16,021 16,330 Castor Seed 0 0 0 8 8 Okra 0 0 0 68 68 Tomatoes 53 0 0 469 521 Pumpkins 0 0 0 128 128 Egg Plant 0 0 0 68 68 Water Mellon 0 0 0 22 22 Onions 0 0 0 75 75 Amaranths 0 0 0 20 20 Cucumber 0 0 0 12 12 Ginger 0 0 0 35 35 Tobacco 0 0 0 142 142 Total 10,110 2,683 6,792 236,338 255,923 cont…Planted Area with Fertiliser by Fertiliser Type and region- Mtwara Region Tanzania Agriculture Sanple Census - 2003 Mtwara Appendix II 169 Crop Mostly Farm Yard Manure Total % Maize 4,607 71,743 6.4 Paddy 95 14,018 0.7 Sorghum 874 20,569 4.3 Bulrush Millet 0 32 0.0 Finger Millet 0 201 0.0 Cassava 4,047 114,097 3.5 Irish Potatoes 0 10 0.0 Sweet Potatoes 0 38 0.0 Yams 3 75 4.4 Cocoyam 0 29 0.0 Mung Beans 0 21 0.0 Beans 0 260 0.0 Cowpeas 83 5,333 1.6 Green Gram 0 1,040 0.0 Chich Peas 0 40 0.0 Pigeon Peas 0 131 0.0 Bambaranuts 115 7,346 1.6 Simsim 0 3,512 0.0 Groundnuts 232 16,330 1.4 Castor Seed 0 8 0.0 Okra 0 68 0.0 Tomatoes 53 521 10.1 Pumpkins 0 128 0.0 Egg Plant 0 68 0.0 Water Mellon 0 22 0.0 Onions 0 75 0.0 Amaranths 0 20 0.0 Cucumber 0 12 0.0 Ginger 0 35 0.0 Tobacco 0 142 0.0 Total 10,110 255,923 4.0 cont…Planted Area with Fertiliser by Fertiliser Type and region- Mtwara Region Tanzania Agriculture Sample census - 2003 Mtwara Appendix II 170 Crop Mostly Inorganic Fertiliser Total % Maize 5,367 71,743 7.48 Paddy 50 14,018 0.36 Sorghum 195 20,569 0.95 Bulrush Millet 0 32 0.00 Finger Millet 12 201 5.93 Cassava 1,058 114,097 0.93 Irish Potatoes 0 10 0.00 Sweet Potatoes 0 38 0.00 Yams 0 75 0.00 Cocoyam 0 29 0.00 Mung Beans 0 21 0.00 Beans 0 260 0.00 Cowpeas 0 5,333 0.00 Green Gram 0 1,040 0.00 Chich Peas 0 40 0.00 Pigeon Peas 0 131 0.00 Bambaranuts 48 7,346 0.66 Simsim 0 3,512 0.00 Groundnuts 62 16,330 0.38 Castor Seed 0 8 0.00 Okra 0 68 0.00 Tomatoes 0 521 0.00 Pumpkins 0 128 0.00 Egg Plant 0 68 0.00 Water Mellon 0 22 0.00 Onions 0 75 0.00 Amaranths 0 20 0.00 Cucumber 0 12 0.00 Ginger 0 35 0.00 Tobacco 0 142 0.00 Total 6,792 255,923 2.65 cont…Planted Area with Fertiliser by Fertiliser Type and region- Mtwara Region Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 171 Mostly Compost Total % Maize 1,280 71,743 1.78 Paddy 140 14,018 1.00 Sorghum 114 20,569 0.56 Bulrush Millet 0 32 0.00 Finger Millet 0 201 0.00 Cassava 1,107 114,097 0.97 Irish Potatoes 0 10 0.00 Sweet Potatoes 0 38 0.00 Yams 0 75 0.00 Cocoyam 0 29 0.00 Mung Beans 0 21 0.00 Beans 0 260 0.00 Cowpeas 7 5,333 0.12 Green Gram 0 1,040 0.00 Chich Peas 0 40 0.00 Pigeon Peas 0 131 0.00 Bambaranuts 21 7,346 0.28 Simsim 0 3,512 0.00 Groundnuts 14 16,330 0.09 Castor Seed 0 8 0.00 Okra 0 68 0.00 Tomatoes 0 521 0.00 Pumpkins 0 128 0.00 Egg Plant 0 68 0.00 Water Mellon 0 22 0.00 Onions 0 75 0.00 Amaranths 0 20 0.00 Cucumber 0 12 0.00 Ginger 0 35 0.00 Tobacco 0 142 0.00 Total 2,683 255,923 1.05 cont…Planted Area with Fertiliser by Fertiliser Type and region- Mtwara Region Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 172 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 173 Number % Number % Number % Mtwara Rural 40,190 89 4,964 11 45,154 100 Newala 39,907 93 3,159 7 43,065 100 Masasi 90,189 94 6,232 6 96,421 100 Tandahimba 38,106 91 3,717 9 41,823 100 Mtwara Urban 2,369 83 482 17 2,850 100 Total 210,760 92 18,554 8 229,314 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Other By Factory Total Mtwara Rural 31,732 0 5,572 0 104 2,689 93 40,190 Newala 21,361 383 15,912 95 94 1,670 391 39,907 Masasi 28,137 164 60,601 485 163 639 0 90,189 Tandahimba 30,966 193 3,999 0 1,933 1,015 0 38,106 Mtwara Urban 1,774 26 397 0 0 0 171 2,369 Total 113,971 765 86,481 580 2,294 6,014 655 210,760 % 54.08 0.36 41.03 0.28 1.09 2.85 0.31 100.00 District Method of Processing 8.0b: Number of Crop Growing Households By Method of Processing and District; Agricultural Year 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District , 2002/03 Agricultural Year District Households That Processed Product Households That Did Not Process Product Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 174 Crop On Farm by Hand On Farm by Machine By Neighbou r Machine By Co- operative Union By Trader Other By Factory Total Maize 19,627 1,734 111,137 744 3,162 597 404 137,405 Paddy 17,715 409 3,542 0 0 1,642 66 23,375 Sorghum 31,723 287 10,589 0 290 1,596 66 44,550 Bulrush Millet 0 0 158 0 0 0 0 158 Finger Millet 291 0 0 0 0 0 0 291 Cassava 135,463 438 22,808 481 193 5,250 455 165,088 Beans 107 0 0 0 0 0 0 107 Cowpeas 10,379 316 259 0 0 0 35 10,989 Green Gram 1,605 0 0 0 0 0 0 1,605 Pigeon Peas 23,883 0 325 0 0 0 0 24,208 Bambaranuts 13,689 0 260 0 0 0 0 13,950 Simsim 3,496 0 0 0 0 0 0 3,496 Groundnuts 24,075 164 259 0 0 0 0 24,498 Coconut 929 0 0 0 0 98 0 1,027 Cashewnut 622 0 0 0 0 0 94 716 Crop Household / Human Consumptio n Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Total Maize 136,131 - 259 708 306 137,405 Paddy 22,495 163 89 - 627 23,375 Sorghum 44,338 - - - 212 44,550 Bulrush Millet 158 - - - - 158 Finger Millet 291 - - - - 291 Cassava 163,848 158 130 - 951 165,088 Beans 107 - - - - 107 Cowpeas 10,465 - 420 - 105 10,989 Green Gram 1,448 - 157 - - 1,605 Pigeon Peas 23,070 162 975 - - 24,208 Bambaranut 13,500 - 255 - 194 13,950 Simsim 788 - 2,090 - 151 3,496 Groundnut 18,406 489 4,913 105 585 24,498 Coconut 1,027 - - - - 1,027 Cashewnut 622 - - - 94 716 Total 436,694 973 9,289 813 3,226 451,461 Method of Processing 8.1.1 AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Mtwara Region. 8.1.1b: AGROPROCESSING: Number of Crop Growing Households Reporting Product Use Tanzania agriculture Sample Census - 2003 Mtwara Appendix II 175 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Maize 4,558 189 0 391 484 94 791 829 130,068 137,405 Paddy 859 0 0 0 263 0 106 104 22,042 23,375 Sorghum 1,144 253 103 0 163 0 0 247 42,640 44,550 Bulrush Millet 0 0 0 0 0 0 0 0 158 158 Finger Millet 0 0 0 0 0 0 0 0 291 291 Cassava 6,241 494 97 659 326 0 1,083 917 155,272 165,088 Beans 0 0 0 0 0 0 0 0 107 107 Cowpeas 574 164 0 0 98 0 0 0 10,153 10,989 Green Gram 157 0 0 0 0 0 0 0 1,448 1,605 Pigeon Peas 1,462 0 0 0 0 0 328 0 22,417 24,208 Bambaranut 417 91 159 0 162 0 0 0 13,121 13,950 Simsim 159 2,391 162 0 159 0 0 0 625 3,496 Groundnut 3,609 581 159 0 260 0 2,187 318 17,384 24,498 Coconut 0 0 0 0 0 0 103 0 924 1,027 Cashewnut 0 0 0 0 94 0 140 0 482 716 Total 19,179 4,163 680 1,050 2,010 94 4,738 2,416 417,131 451,461 Flour / Meal Grain Oil Fiber Other Total Mtwara Rural 33,218 6,471 395 106 0 40,190 Newala 38,243 1,565 99 0 0 39,907 Masasi 83,958 5,915 316 0 0 90,189 Tandahimba 36,160 1,473 95 282 96 38,106 Mtwara Urban 2,343 0 26 0 0 2,369 Total 193,922 15,423 931 388 96 210,760 Household / Human Consumption Sale Only Animal Consumpti on Did Not Use Total Mtwara Rural 39,793 0 0 397 40,190 Newala 39,515 99 196 96 39,907 Masasi 88,897 646 0 646 90,189 Tandahimba 38,010 97 0 0 38,106 Mtwara Urban 2,338 31 0 0 2,369 Total 208,552 873 196 1,139 210,760 District Product Use 8.1.1e: AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year, Mtwara Region 8.1.1c: AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Mtwara Region. Total Where Sold District Main Product 8.1.1d: AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year, Mtwara Region Crop Tazania Agriculture Sample Census -2003 Mtwara Appendix II 176 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Mtwara Rural 1,510 211 97 107 100 0 0 525 37,641 40,190 Newala 875 189 0 0 0 94 99 470 38,180 39,907 Masasi 4,524 157 0 0 484 0 791 0 84,232 90,189 Tandahimba 942 0 0 188 0 0 0 95 36,881 38,106 Mtwara Urban 83 0 0 0 0 0 0 35 2,251 2,369 Total 7,933 557 97 295 584 94 890 1,125 199,185 210,760 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Mtwara Rural 13,708 0 2,598 0 290 209 100 4,372 18,913 0 40,190 Newala 8,060 98 764 99 98 0 0 767 30,020 0 39,907 Masasi 12,800 0 7,971 462 0 325 164 10,773 57,694 0 90,189 Tandahimba 9,095 188 1,082 0 92 0 89 284 27,185 91 38,106 Mtwara Urban 423 0 0 0 33 0 0 379 1,534 0 2,369 Total 44,086 286 12,415 561 513 534 354 16,575 135,346 91 210,760 8.I.1f: AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agricultural Year, Mtwara Region 8.1.1g: AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District During 2002/03 Agricultural Year, Mtwara Region. District By Product District Where Sold Tanzania Agriculture Sample Census - 2003 Mtwara 177 Appendix II 178 MARKETING Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 179 District Total Number % Number % Number Mtwara Rural 29,648 65.7 15,506 34.3 45,154 Newala 30,353 70.5 12,713 29.5 43,065 Masasi 58,866 61.1 37,555 38.9 96,421 Tandahimba 28,990 69.3 12,833 30.7 41,823 Mtwara Urban 1,307 45.8 1,544 54.2 2,850 Total 149,163 65.0 80,151 35.0 229,314 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Governmen t Regulatory Board Problems Other Not applicable Total Mtwara Rural 638 13,409 0 0 92 107 0 1,384 29,039 44,669 Newala 1,763 12,448 93 99 94 389 95 1,357 25,848 42,185 Masasi 1,114 54,610 0 483 491 1,465 328 2,400 31,261 92,152 Tandahimba 0 12,712 0 0 92 0 0 1,890 26,762 41,456 Mtwara Urban 0 995 65 0 0 0 0 686 1,006 2,753 Total 3,515 94,174 158 582 769 1,961 422 7,717 113,916 223,215 District Price Too Low Insufficient to Sell Market Too Far Association Problems operative Problems Union Problems t Regulatory Other Not applicable Total Mtwara Rural 1.43 30.02 0.00 0.00 0.21 0.24 0.00 3.10 65.01 100.00 Newala 3.95 27.87 0.21 0.22 0.21 0.87 0.21 3.04 57.87 94.44 Masasi 2.49 122.26 0.00 1.08 1.10 3.28 0.73 5.37 69.98 206.30 Tandahimba 0.00 28.46 0.00 0.00 0.21 0.00 0.00 4.23 59.91 92.81 Mtwara Urban 0.00 2.23 0.15 0.00 0.00 0.00 0.00 1.54 2.25 6.16 Total 7.87 210.83 0.35 1.30 1.72 4.39 0.95 17.27 255.02 499.71 10.1: Number of Crop Producing Households Reporting Selling Agricultural Products During 2003/04 By District, Mtwara Region Number of Households that Sold Number of Households that Did not Sell 10.3: Proportion of Households who Reported Not Selling their crops by district during 2002/03 Agricultural Year, Mtwara Region. 10.2: Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2002/03 Agricultural Year, Mtwara Region. District Main Reasons for Not Selling Crops Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 180 IRRIGATION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 181 District Total Number of Household % Number of Household % Number of Household Mtwara Rural 637 1.4 44,517 98.6 45,154 Newala 94 0.2 42,971 99.8 43,065 Masasi 1,110 1.2 95,311 98.8 96,421 Tandahimba 2,185 5.2 39,638 94.8 41,823 Mtwara Urban 0 0.0 2,850 100.0 2,850 Total 4,027 1.8 225,287 98.2 229,314 District Irrigated Area Area Irrigate d Land this Year % Mtwara Rural 666 623 94 Newala 11 11 100 Masasi 431 193 45 Tandahimba 1,247 1,247 100 Mtwara Urban 0 0 0 Total 2,356 2,075 88 River Dam Well Canal Pipe water Total Mtwara Rural 0 637 0 0 0 637 Newala 0 0 0 0 94 94 Masasi 319 0 791 0 0 1,110 Tandahimba 2,104 0 0 81 0 2,185 Total 2,424 637 791 81 94 4,027 % 60 16 20 2 2 100 Gravity Hand Bucket Other Total Mtwara Rural 0 637 0 637 Newala 0 0 94 94 Masasi 0 1,110 0 1,110 Tandahimba 2,104 81 0 2,185 Total 2,104 1,828 94 4,027 % 52 45 2 100 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District Table 11.1: Number and Percent of Households Reporting use of Irrigation During 2002/03 Agricultural Year By District Households Practicing Irrigation Households not Practicing Irrigation 11.2: IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District during 2002/03 agricultural year District Method of Obtaining Water District Source of Irrigation Water 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 182 Flood Water Hose Bucket / Watering Can Total Mtwara Rural 0 0 637 637 Newala 0 94 0 94 Masasi 0 0 1,110 1,110 Tandahimba 2,104 0 81 2,185 Total 2,104 94 1,828 4026.70707 % 52 2 45 100 Does Not Have Facility Total Number % Number % Number Mtwara Rural 0 0 45,154 100 45,154 Newala 95 0 42,970 100 43,065 Masasi 1,282 1 95,139 99 96,421 Tandahimba 0 0 41,823 100 41,823 Mtwara Urban 98 3 2,753 97 2,850 Total 1,474 1 227,840 99 229,314 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches Total Number of Structures Newala 0 0 95 95 Masasi 39,391 151 0 39,542 Mtwara Urban 841 0 0 841 Total 40,232 151 95 40,478 11.7: EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control Presence of Erosion control/Water Harvesting Facilities 11.5: IRRIGATION: Number of Agricultural Households By Method of Field Application of Irrigation Water and District for the 2002/03 agricultural year 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District District Have facility District Method of Application Tanzania agriculture Sample Census - 2003 Mtwara 183 Appendix II 184 ACCESS TO INPUTS Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 185 No of households % No of households % Mtwara Rur 100 0 45,054 100 45,154 Newala 5,912 14 37,153 86 43,065 Masasi 970 1 95,451 99 96,421 Tandahimba 286 1 41,538 99 41,823 Mtwara Urb 65 2 2,785 98 2,850 Total 7,333 3 221,981 97 229,314 No of households % No of households % Mtwara Rur 587 1 44,567 99 45,154 Newala 4,035 9 39,030 91 43,065 Masasi 1,615 2 94,806 98 96,421 Tandahimba 4,879 12 36,945 88 41,823 Mtwara Urb 218 8 2,633 92 2,850 Total 11,334 5 217,980 95 229,314 No of households % No of households % Mtwara Rur 1,652 4 43,502 96 45,154 Newala 1,453 3 41,612 97 43,065 Masasi 794 1 95,627 99 96,421 Tandahimba 1,040 2 40,783 98 41,823 Mtwara Urb 99 3 2,751 97 2,850 Total 5,038 2 224,276 98 229,314 Table 12.1.1: ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 186 No of households % No of households % Mtwara Rur 10,495 23 34,659 77 45,154 Newala 11,259 26 31,807 74 43,065 Masasi 13,040 14 83,380 86 96,421 Tandahimba 17,706 42 24,117 58 41,823 Mtwara Urb 461 16 2,389 84 2,850 Total 52,961 23 176,353 77 229,314 No of households % No of households % Mtwara Rur 93 0 45,061 100 45,154 Newala 96 0 42,969 100 43,065 Masasi 0 0 96,421 100 96,421 Tandahimba 0 0 41,823 100 41,823 Mtwara Urb 0 0 2,850 100 2,850 Total 189 0 229,125 100 229,314 No of households % No of households % Mtwara Rur 4,459 10 40,695 90 45,154 Newala 489 1 42,576 99 43,065 Masasi 2,081 2 94,340 98 96,421 Tandahimba 1,241 3 40,582 97 41,823 Mtwara Urb 261 9 2,589 91 2,850 Total 8,531 4 220,783 96 229,314 Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Using Pesticides/Fungicid e Not Using Pesticides/Fungi Total Number of Crop growing households Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 187 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 0 0 0 0 100 0 0 0 0 0 0 0 0 0 45,054 100 45,154 Newala 95 0 189 0 5,055 12 94 0 96 0 94 0 288 1 37,153 86 43,065 Masasi 159 0 0 0 811 1 0 0 0 0 0 0 0 0 95,451 99 96,421 Tandahimba 0 0 0 0 286 1 0 0 0 0 0 0 0 0 41,538 99 41,823 Mtwara Urb 0 0 0 0 65 2 0 0 0 0 0 0 0 0 2,785 98 2,850 Total 254 0 189 0 6,317 3 94 0 96 0 94 0 288 0 221,981 97 229,314 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 0 0 0 0 0 0 87 0 106 0 394 1 0 0 44,461 99 45,048 Newala 0 0 98 0 98 0 96 0 1,802 4 1,745 4 195 0 39,126 91 43,161 Masasi 0 0 0 0 0 0 0 0 164 0 1,294 1 157 0 94,806 98 96,421 Tandahimba 96 0 0 0 285 1 0 0 2,148 5 2,349 6 0 0 36,945 88 41,823 Mtwara Urb 0 0 0 0 0 0 0 0 69 2 149 5 0 0 2,633 92 2,850 Total 96 0 98 0 383 0 183 0 4,289 2 5,931 3 353 0 217,970 95 229,304 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 515 1 618 1 309 1 103 0 106 0 0 0 0 0 43,608 96 45,260 Newala 0 0 0 0 0 0 0 0 1,355 3 98 0 0 0 41,612 97 43,065 Masasi 157 0 0 0 0 0 0 0 478 0 158 0 0 0 95,627 99 96,421 Tandahimba 0 0 0 0 0 0 0 0 387 1 556 1 97 0 40,783 98 41,823 Mtwara Urb 0 0 0 0 0 0 0 0 99 3 0 0 0 0 2,751 97 2,850 Neighbour Other Local Farmers Group Local Market / Trade Store Crop Buyers Locally Produced by Household Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Large Scale Farm Locally Produced by Household Not applicable District Co-operative Other Other Not applicable Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Not applicable Neighbour Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Neighbour District Co-operative Local Farmers Group Local Market / Trade Store Large Scale Farm Locally Produced by Household Tanzania Agriculture Sampl3e Census - 2003 Mtwara Appendix II 188 Not applicable Number % Number % Number % Numbe% Number% Numbe % Number % Number % Number % Number % Number Mtwara Rur 2015.28 4.5 657.6161 1.456 7,037 16 0 0 0 0 80 0 0 0 0 0 705 2 0 0 34,659 45154.1 Newala 947 2 183 0 9,154 21 0 0 98 0 0 0 98 0 96 0 293 1 389 1 31,807 43065.2 Masasi 5,622 6 307 0 6,949 7 162 0 0 0 0 0 0 0 0 0 0 0 0 0 83,380 96420.8 Tandahimba 8,490 20 631 2 7,004 17 0 0 181 0 92 0 0 0 89 0 1,128 3 91 0 24,117 41823.3 Mtwara Urb 0 0 0 0 394 14 0 0 0 0 0 0 0 0 0 0 67 2 0 0 2,389 2850.44 Total 17,075 7 1,778 1 30,539 13 162 0 280 0 172 0 98 0 185 0 2,192 1 480 0 176,353 229314 Total Number % Number % Mtwara Rur 93 0 45,061 100 45,154 Newala 96 0 42,873 100 42,969 Masasi 0 0 96,421 100 96,421 Tandahimba 0 0 41,823 100 41,823 Mtwara Urb 0 0 2,850 100 2,850 Total 189 0 229,029 100 229,218 Total Number % Number % Number % Numbe% Number% Numbe % Number % Number % Number % Number Mtwara Rur 0 0 0 0 2,631 6 180 0 0 0 100 0 928 2 621 1 40,695 90 45,154 Newala 0 0 0 0 390 1 0 0 0 0 0 0 99 0 0 0 42,576 99 43,065 Masasi 0 0 321 0 487 1 159 0 159 0 159 0 798 1 0 0 94,340 98 96,421 Tandahimba 95 0 0 0 574 1 0 0 94 0 0 0 478 1 0 0 40,582 97 41,823 Mtwara Urb 33 1 0 0 130 5 0 0 0 0 0 0 63 2 35 1 2,589 91 2,850 Total 128 0 321 0 4,212 2 338 0 253 0 258 0 2,365 1 656 0 220,783 96 229,314 Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Not applicable Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Developm ent Project Large Scale Farm Locally Produced by Household Neighbour Other District Neighbour Not applicable Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Local Farmers Group Local Market / Trade Store Secondary Market Developme nt Project Crop Buyers Large Scale Farm Locally Produced by Household Neighbour District Co-operative Other Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 189 Total Number % Number % Number % Number % Number % Number Mtwara Rur 100 100 0 0 0 0 0 0 0 0 100 Newala 951 16 283 5 1,809 31 1,413 24 1,457 25 5,912 Masasi 159 16 0 0 0 0 321 33 490 51 970 Tandahimba 0 0 95 33 94 33 0 0 96 34 286 Mtwara Urb 0 0 0 0 65 100 0 0 0 0 65 Total 1,209 16 378 5 1,968 27 1,733 24 2,044 28 7,333 Number % Number % Number % Number % Number % Mtwara Rur 587 100 0 0 0 0 0 0 0 0 587 Newala 3,747 93 95 2 0 0 0 0 193 5 4,035 Masasi 1,294 80 0 0 159 10 162 10 0 0 1,615 Tandahimba 4,879 100 0 0 0 0 0 0 0 0 4,879 Mtwara Urb 218 100 0 0 0 0 0 0 0 0 218 Total 10,725 95 95 1 159 1 162 1 193 2 11,334 Total Number Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District 20 km and Above Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 190 Total Number % Number % Number % Number Mtwara Rur 1549 94 103 6 0 0 1652 Newala 1256 86 98 7 98 7 1453 Masasi 630 79 163 21 0 0 794 Tandahimba 1040 100 0 0 0 0 1040 Mtwara Urb 99 100 0 0 0 0 99 Total 4575 91 365 7 98 2 5038 Total Number % Number % Number % Number % Number % Number Mtwara Rur 3,222 72 213 5 107 2 200 4 718 16 4,459 Newala 0 0 0 0 0 0 98 20 391 80 489 Masasi 1,436 69 0 0 323 16 0 0 322 15 2,081 Tandahimba 383 31 95 8 286 23 190 15 287 23 1,241 Mtwara Urb 32 12 0 0 194 74 0 0 35 13 261 Total 5,072 59 308 4 910 11 489 6 1,753 21 8,531 Total Number % Number % Number % Number % Number % Number % Mtwara Rur 3,699 35 194 2 1,755 17 1,151 11 3,697 35 10,495 100 Newala 2,209 20 652 6 1,257 11 2,583 23 4,558 40 11,259 100 Masasi 5,304 41 790 6 2,103 16 2,614 20 2,230 17 13,040 100 Tandahimba 11,868 67 1,488 8 2,614 15 1,365 8 372 2 17,706 100 Mtwara Urb 32 7 0 0 226 49 169 37 35 8 461 100 Total 23,112 44 3,123 6 7,955 15 7,880 15 10,891 21 52,961 100 20 km and Above Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year Between 10 and 20 km 20 km and Above Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 kBetween 3 and 10Between 10 and 2 District Less than 1 km km 10 km Tanzania Agriculture Sample census-2003 Mtwara Appendix II 191 Other Total Number % Number % Number % Number % Number % Number% Number % Number Number Mtwara Rur 10,349 23 29,311 65 831 2 0 0 1,967 4 2,315 5 0 0 281 0.623 45,054 Newala 6,797 18 24,830 67 852 2 96 0 284 1 292 1 0 0 4,002 10.77 37,153 Masasi 15,545 16 72,633 76 803 1 466 0 2,579 3 2,613 3 0 0 812 0.85 95,451 Tandahimba 14,560 35 23,585 57 179 0 0 0 1,465 4 1,567 4 182 0 0 0 41,538 Mtwara Urb 66 2 2,276 82 33 1 0 0 262 9 63 2 0 0 85 3.051 2,785 Total 47,317 21 152,636 69 2,699 1 562 0 6,556 3 6,851 3 182 0 5,179 2.333 221,981 Total Number % Number % Number % Number % Number % Number% Number % Number Mtwara Rur 13,399 30 6,433 14 12,688 29 879 2 9,069 20 1,304 3 689 2 44,461 Newala 13,067 33 4,585 12 15,281 39 1,268 3 1,522 4 292 1 3,111 8 39,126 Masasi 25,920 27 14,590 15 34,626 37 3,056 3 12,547 13 3,420 4 646 1 94,806 Tandahimba 16,693 45 2,871 8 13,206 36 1,467 4 1,684 5 934 3 91 0 36,945 Mtwara Urb 814 31 600 23 299 11 292 11 481 18 95 4 51 2 2,633 Total 69,894 32 29,079 13 76,099 35 6,962 3 25,303 12 6,045 3 4,589 2 217,970 Total Number % Number % Number % Number % Number %Number % Number % Number Mtwara Rur 2,253 5 5,730 13 16,022 37 773 2 17,329 40 892 2 610 1 43,608 Newala 2,565 6 4,380 11 15,850 38 5,985 14 8,842 21 98 0 3,893 9 41,612 Masasi 14,711 15 11,842 12 34,134 36 4,817 5 26,214 27 3,420 4 489 1 95,627 Tandahimba 5,508 14 2,600 6 17,680 43 2,822 7 11,152 27 647 2 376 1 40,783 Mtwara Urb 129 5 533 19 533 19 556 20 827 30 96 3 77 3 2,751 Total 25,165 11 25,084 11 84,218 38 14,953 7 64,364 29 5,153 2 5,445 2 224,382 Too Much Labour Required Do not Know How to Use Input is of No Use Other District Not Available Price Too High No Money to Buy Other Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Tanzania Agriculuture Sample Census - 2003 Mtwara Appendix II 192 Total Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 2,524 7 24,042 69 2,270 7 0 0 1,342 4 4,093 12 390 1 34,659 Newala 5,364 17 20,945 66 762 2 94 0 773 2 941 3 2,928 9 31,807 Masasi 8,703 10 67,563 81 971 1 321 0 1,781 2 2,591 3 1,451 2 83,380 Tandahimba 4,182 17 18,085 75 0 0 0 0 1,007 4 657 3 186 1 24,117 Mtwara Urb 66 3 1,911 80 0 0 0 0 266 11 63 3 83 3 2,389 Total 20,838 12 132,545 75 4,003 2 415 0 5,168 3 8,345 5 5,038 3 176,353 Total Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 9,103 20 22,780 51 2,161 5 212 0 5,759 13 4,858 11 189 0 45,061 Newala 13,327 31 19,660 46 1,302 3 197 0 4,592 11 379 1 3,414 8 42,873 Masasi 15,917 17 67,602 70 811 1 321 0 5,918 6 5,037 5 815 1 96,421 Tandahimba 19,727 47 14,645 35 188 0 0 0 5,517 13 1,655 4 91 0 41,823 Mtwara Urb 31 1 1,974 69 0 0 0 0 730 26 63 2 51 2 2,850 Total 58,105 25 126,661 55 4,463 2 730 0 22,517 10 11,992 5 4,561 2 229,029 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mtwara Rur 19,400 48 18,968 47 1,219 3 0 0 816 2 197 0 0 0 96 0 40,695 Newala 13,732 32 21,624 51 1,030 2 0 0 477 1 1,541 4 99 0 4,074 10 42,576 Masasi 29,354 31 60,916 65 490 1 162 0 1,145 1 972 1 0 0 1,301 1 94,340 Tandahimba 20,077 49 19,860 49 181 0 0 0 190 0 183 0 0 0 91 0 40,582 Mtwara Urb 100 4 2,045 79 0 0 64 2 199 8 98 4 0 0 84 3 2,589 Total 82,662 37 123,412 56 2,920 1 226 0 2,827 1 2,991 1 99 0 5,646 2.557 220,783 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labou Do not Know Ho Input is of No Use Locally ProduceOther Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Tanzania Agriculture Sample Census - 2003 193 Appendix II 194 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 195 Total Number % Number % Number Newala 291 75 99 25 390 Masasi 964 100 0 0 964 Tandahimba 96 100 0 0 96 Mtwara Urba 58 100 0 0 58 Total 1,410 93 99 7 1,509 Family, Friend and Relative Commercia l Bank Co- operative Saving & Credit Society Religious Organisatio n / NGO / Project Total Newala 97 0 293 0 0 390 Masasi 317 159 326 162 0 964 Tandahimba 0 0 96 0 0 96 Mtwara Urba 33 0 0 0 26 58 Total 446 159 716 162 26 1,509 13.2 AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household head and District during the 2002/03 Agricultural Year Source of Credit 13.2 AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District District District Male Female Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 196 District Did not know how to get credit Don't know about credit Not available Did not want to go into debt Difficult bureaucrac y procedure Not needed Interest rate/cost too high Credit granted too late Other Total Mtwara Rural 22,970 9,176 6,869 2,515 1,185 1,229 819 292 100 45,154 Newala 16,723 9,199 11,141 3,098 950 1,076 192 198 99 42,675 Masasi 38,017 26,958 20,493 4,202 2,272 2,234 486 631 163 95,457 Tandahimba 19,475 8,384 7,593 3,324 1,663 813 475 0 0 41,727 Mtwara Urban 1,696 415 0 318 230 34 67 0 33 2,792 Total 98,881 54,133 46,096 13,458 6,300 5,384 2,039 1,121 393 227,805 District Labour Tools / Equipment Agro- chemicals Livestock Total Credits Newala 0 0 390 0 390 Masasi 162 159 805 0 1,126 Tandahimba 0 0 96 0 96 Mtwara Urban 0 0 33 26 58 Total Credits 162 159 1,324 26 1,671 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Mtwara 197 Appendix II 198 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 199 District Senna Spp Gravellis Acacia Spp Melicia excelsa Terminalia Catapa Azadritacht a Spp Jakaranda Spp Moringa Spp Newala 38 . . 5 . . . . Masasi 70 10 13 . . . . 12 Mtwara Urban 29 . . 2 9 12 6 . Total 137 10 13 7 9 12 6 12 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Newala 6 43 0 . 6 43 Masasi 2 14 6 91 8 105 Mtwara Urban 5 41 2 17 7 58 Total 13 98 8 108 21 206 District 1-9 1-19 20-29 30-39 60+ Total Newala 393 0 0 0 98 491 Masasi 163 488 488 163 163 1,463 Tandahimba 1,040 1,248 531 0 0 2,820 Total 1,595 1,736 1,019 163 261 4,773 14.3 TREE FARMING: Number of Agricultural Households Classified by Distance to Community Planted Forest (Km) By District during the 2002/03 Agricultural Year, Mtwara Region Distance to Community Planted Forest (km) 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District during the Year 2002/03 Agricultural Year, Mtwara region. 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District during the 2002/03 Agricultural year - Mtwara Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 200 District Planks / Timber Poles Fuel for Wood Shade Other Total Newala 2 2 1 1 1 7 Masasi 0 0 2 4 2 8 Mtwara Urban 1 8 0 2 0 11 Total 3 10 3 7 3 26 Poles Fuel for Wood Shade Medicinal Other Total Newala 2 0 4 0 1 7 Masasi 1 4 2 1 0 8 Mtwara Urban 0 5 2 0 2 9 Total 3 9 8 1 3 24 District Second Use 14 TREE FARMING: Second Use of Trees By District 14 TREE FARMING: Number of Responses by main use of planted tree and District for the 2002/03 agricultural year, Mtwara region Tanzania Agriculture sample Censns -2003 Mtwara 201 Appendix II 202 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 203 District Total umber of Households Number % Number % Number Mtwara Rural 9,100 20 36,054 80 45,154 Newala 3,344 8 39,722 92 43,065 Masasi 17,435 18 78,986 82 96,421 Tandahimba 10,236 24 31,588 76 41,823 Mtwara Urban 342 12 2,508 88 2,850 Total 40,456 18 188,858 82 229,314 Very Good Good Average Poor No Good Number % Number % Number % Number % Number % Mtwara Rural 503 5.5 8,252 90.7 265 2.9 0 0.0 80 0.9 9,100 Newala 757 22.6 2,106 63.0 383 11.5 0 0.0 98 2.9 3,344 Masasi 4,585 26.3 10,908 62.6 1,454 8.3 488 2.8 0 0.0 17,435 Tandahimba 2,270 22.4 5,904 58.2 1,967 19.4 0 0.0 0 0.0 10,141 Mtwara Urban 0 0.0 342 100.0 0 0.0 0 0.0 0 0.0 342 Total 8,115 20.1 27,511 68.2 4,069 10.1 488 1.2 178 0.4 40,361 District Total Number % Number % Number % Number % Number Mtwara Rural 8,727 95.9 213 2.3 80 0.9 80 0.9 9,100 Newala 3,058 94.2 0 0.0 0 0.0 187 5.8 3,245 Masasi 17,273 99.1 161 0.9 0 0.0 0 0.0 17,435 Tandahimba 9,858 97.2 0 0.0 90 0.9 193 1.9 10,141 Mtwara Urban 311 90.7 0 0.0 0 0.0 32 9.3 342 Total 39,227 97.4 374 0.9 170 0.4 492 1.2 40,263 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District Households Not Receiving Extension Advice Households Receiving Extension Advice 15.2 EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District 15.1 CROP EXTENSION: Number of Households By Quality of Extension Services By District District Total Number of Households Government NGO / Cooperative Large Scale Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 204 Government NGO / Development Project Cooperative Large Scale Farm Total Total number of households % of total number of households Mtwara Rural 8,320 213 80 80 8,693 30,940 28 Newala 3,058 0 0 187 3,245 16,907 19 Masasi 16,327 161 0 0 16,488 82,572 20 Tandahimba 9,858 0 0 0 9,858 70,339 14 Mtwara Urban 279 0 0 32 311 1,343 23 Total 37,842 374 80 299 38,595 202,102 19 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total number of households % of total number of households Mtwara Rural 2,304 94 93 80 199 2,770 30,940 9 Newala 2,015 0 0 98 0 2,113 16,907 12 Masasi 8,514 161 151 0 801 9,628 82,572 12 Tandahimba 8,913 190 90 193 0 9,387 70,339 13 Mtwara Urban 95 0 0 32 0 127 1,343 9 Total 21,842 445 334 403 1,001 24,025 202,102 12 Government NGO / Development Project Not applicable Total Total number of households % of total number of households Mtwara Rural 697 0 107 804 30,940 3 Newala 293 0 0 293 16,907 2 Masasi 1,126 0 803 1,929 82,572 2 Tandahimba 4,296 194 374 4,864 70,339 7 Mtwara Urban 97 0 0 97 1,343 7 Total 6,509 194 1,284 7,987 202,102 4 15.4: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Use of Agrochemicals 15.5: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Use of Agrochemical By Source and District during the 2002/03 Agricultural Year, Mtwara Region District District Erosion Control Spacing 15.6: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Erosion Control By Source and District during the 2002/03 Agricultural Year, Mtwara Region Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 205 Government NGO / Development Project Large Scale Farm Not applicable Total Total number of households % of total number of households Mtwara Rural 1,917 465 93 303 2,778 30,940 9 Newala 2,569 0 0 0 2,569 16,907 15 Masasi 8,597 161 0 325 9,082 82,572 11 Tandahimba 7,900 94 0 194 8,188 70,339 12 Mtwara Urban 154 0 32 0 186 1,343 14 Total 21,137 721 125 821 22,804 202,102 11 Government NGO / Development Project Cooperative Other Not applicabl e Total Total number of households % of total number of households Mtwara Rural 2,296 280 0 0 211 2,786 30,940 9 Newala 2,198 0 0 0 0 2,198 16,907 13 Masasi 6,686 0 0 0 636 7,322 82,572 9 Tandahimba 5,831 378 95 96 287 6,688 70,339 10 Mtwara Urban 115 0 0 0 0 115 1,343 9 Total 17,126 658 95 96 1,134 19,110 202,102 9 Government NGO / Development Project Cooperative Not applicable Total Total number of households % of total number of households Mtwara Rural 4,140 666 80 199 5,085 30,940 16 Newala 2,482 0 0 0 2,482 16,907 15 Masasi 8,607 161 0 477 9,246 82,572 11 Tandahimba 7,346 190 95 188 7,820 70,339 11 Mtwara Urban 243 0 0 0 243 1,343 18 Total 22,818 1,017 175 865 24,875 202,102 12 % 92 4 1 3 100 District Use of Improved Seed 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Use of Improved Seed By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Organic Fertilizer Use 15.7: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Organic Fertiliser Use By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Inorganic Fertilizer Use 15.8: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source and District during the 2002/03 Agricultural Year, Mtwara Region Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 206 Government Other Not applicable Total Total number of households % of total number of households Mtwara Rural 398 0 105 503 30,940 2 Newala 186 99 0 285 16,907 2 Masasi 4,088 0 803 4,891 82,572 6 Tandahimba 2,958 0 97 3,055 70,339 4 Mtwara Urban 0 0 0 0 1,343 0 Total 7,630 99 1,005 8,734 202,102 4 Government Other Not applicable Total Total number of households % of total number of households Mtwara Rural 500 0 0 500 30,940 2 Newala 0 0 0 0 16,907 0 Masasi 1,278 162 641 2,081 82,572 3 Tandahimba 2,086 0 0 2,086 70,339 3 Mtwara Urban 0 0 0 0 1,343 0 Total 3,863 162 641 4,666 202,102 2 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Total number of households % of total number of households Mtwara Rural 2,046 0 0 0 0 0 2,046 30,940 6.6 Newala 1,997 0 0 0 0 97 2,094 16,907 12.4 Masasi 6,867 161 0 151 0 315 7,495 82,572 9.1 Tandahimba 6,870 0 95 96 193 0 7,255 70,339 10.3 Mtwara Urban 59 0 0 0 0 0 59 1,343 4.4 Total 17,840 161 95 248 193 412 18,949 202,102 9 District Crop Storage 15.12 EXTENSION MESSAGES: Number of Households Receiving Advice on Crop storage By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Mechanisation / LST 15.10: EXTENSION MESSAGES: Number of Households Receiving Advice on Mechanisation/LST By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Irrigation Technology 15.11 EXTENSION MESSAGES: Number of Households Receiving Advice on Irrigation Technology By Source and District during the 2002/03 Agricultural Year, Mtwara Region Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 207 Government Large Scale Farm Other Not applicable Total Total number of households % of total number of households Mtwara Rural 2,374 105 105 105 2,688 30,940 9 Newala 197 0 0 0 197 16,907 1 Masasi 1,932 0 0 807 2,739 82,572 3 Tandahimba 6,786 0 0 0 6,786 70,339 10 Mtwara Urban 31 0 0 0 31 1,343 2 Total 11,321 105 105 911 12,441 202,102 6 % 91.0 0.8 0.8 7.3 100.0 Government NGO / Developme nt Project Large Scale Farm Not applicable Total Total number of households % of total number of households Mtwara Rural 792 0 0 0 792 30,940 3 Newala 656 0 0 0 656 16,907 4 Masasi 1,118 162 0 969 2,250 82,572 3 Tandahimba 2,368 0 97 189 2,654 70,339 4 Mtwara Urban 91 0 0 0 91 1,343 7 Total 5,025 162 97 1,159 6,443 202,102 3 Government NGO / Developme nt Project Not applicable Total Total number of households % of total number of households Mtwara Rural 600 0 0 600 30,940 2 Newala 576 0 0 576 16,907 3 Masasi 4,241 324 807 5,372 82,572 7 Tandahimba 652 0 0 652 70,339 1 Mtwara Urban 26 0 32 58 1,343 4 Total 6,095 324 839 7,257 202,102 4 % 84.0 4.5 11.6 100.0 15.13 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Vermin Control By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Agro-forestry 15.15 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro- Forestry By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Vermin Control District Agro-progressing 15.14 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro - Processing By Source and District during the 2002/03 Agricultural Year, Mtwara Region Tanzania Agriculture Sample Census-2003 Mtwara Appendix II 208 Government Other Not applicable Total Total number of households % of total number of households Mtwara Rural 292 0 0 292 30,940 1 Newala 0 99 0 99 16,907 1 Masasi 1,474 0 805 2,279 82,572 3 Tandahimba 288 0 0 288 70,339 0 Mtwara Urban 0 0 0 0 1,343 0 Total 2,054 99 805 2,958 202,102 1 Government NGO / Development Project Other Not applicable Total Total number of households % of total number of households Mtwara Rural 292 0 0 0 292 30,940 1 Newala 0 0 99 0 99 16,907 1 Masasi 164 159 0 969 1,292 82,572 2 Tandahimba 289 0 0 0 289 70,339 0 Mtwara Urban 0 0 0 0 0 1,343 0 Total 745 159 99 969 1,972 202,102 1 % % % Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Mtwara Rural 8,693 7,585 87 2,567 1,501 58 609 206 34 Newala 3,245 3,147 97 2,113 972 46 293 195 66 Masasi 16,644 16,159 97 8,506 5,737 67 803 965 120 Tandahimba 9,858 8,818 89 9,579 6,055 63 4,296 569 13 Mtwara Urban 311 245 79 127 95 75 97 32 33 Total 38,751 35,954 93 22,892 14,360 63 6,098 1,967 32 15.16 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Beekeeping By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Fish Farming 15.17: EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source and District during the 2002/03 Agricultural Year, Mtwara Region District Beekeeping 15.18: EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region District Spacing Use of Agrochemicals Erosion Control Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 209 % % % Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Mtwara Rural 2,677 799 30 2,580 507 20 5,289 2,908 55 Newala 2,471 489 20 2,198 483 22 2,482 390 16 Masasi 7,949 1,602 20 6,204 1,282 21 8,440 2,227 26 Tandahimba 8,188 2,760 34 6,499 572 9 7,820 1,237 16 Mtwara Urban 186 121 65 115 0 0 243 146 60 Total 21,471 5,771 27 17,596 2,845 16 24,274 6,909 28 % % % Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Mtwara Rural 398 0 0 398 101 25 1,840 1,135 62 Newala 186 0 0 0 0 0 2,094 1,511 72 Masasi 3,929 968 25 640 1,117 175 6,690 4,560 68 Tandahimba 2,681 191 7 1,799 91 5 7,160 3,534 49 Mtwara Urban 0 0 0 0 0 0 59 26 43 Total 7,194 1,159 16 2,837 1,310 46 17,843 10,766 60 Inorganic Fertilizer Use Use of Improved Seed 15.19: EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region Mechanisation / LST District Irrigation Technology Crop Storage 15.20: EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region Organic Fertilizer Use District Tanzania Agriculture sample Census - 2003 Mtwara Appendix II 210 % % % Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Mtwara Rural 2,784 1,216 44 691 691 100 498 100 20 Newala 197 197 100 656 656 100 576 291 51 Masasi 1,286 2,095 163 310 1,118 361 4,577 804 18 Tandahimba 6,691 4,032 60 2,471 1,235 50 652 187 29 Mtwara Urban 31 31 100 91 57 63 58 26 45 Total 10,989 7,571 69 4,219 3,757 89 6,360 1,407 22 % % % Received Advice Adopted Message Received Advice Adopted Message Received Advice Adopted Message Mtwara Rural 292 0 0 292 0 0 107 107 100 Newala 0 0 0 0 0 0 0 0 0 Masasi 984 490 50 159 487 307 328 164 50 Tandahimba 193 0 0 289 0 0 280 280 100 Mtwara Urban 0 0 0 0 0 0 26 26 100 Total 1,469 490 33 740 487 66 740 576 78 Agro-progressing Agro-forestry 15.21: EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region Beekeeping District 15.22: EXTENSION MESSAGES: Number of Households By Receiving and Adopting Extension Messages By Type of Message and District for the 2002/03 agricultural year Mtwara region Fish Farming Other Vermin Control District Tanzania Agriculture sample Census -2003 Mtwara 211 Appendix II 212 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 213 Total households No of households % Mtwara Rural 45,154 100 45,154 Newala 43,065 100 43,065 Masasi 96,421 100 96,421 Tandahimba 41,823 100 41,823 Mtwara Urban 2,850 100 2,850 Total 229313.9552 100 229313.9552 Did you apply organic fertilizer during 2002/03? Number % Number % Mtwara Rural 1,517.4 13 42,820.1 20 44,338 Newala 3,945.3 33 39,023.9 18 42,969 Masasi 1,923.9 16 93,690.8 44 95,615 Tandahimba 4,486.7 37 37,244.9 17 41,732 Mtwara Urban 249.7 2 2,568.1 1 2,818 Total 12123.07578 100 215347.7862 100 227470.862 Area (%) % Area (%) % Area (%) % Mtwara Rural 316 10 426 24 742 15 Newala 1,216 37 560 32 1,776 35 Masasi 572 18 382 22 955 19 Tandahimba 1,088 33 398 22 1,486 30 Mtwara Urban 59 2 3 0 62 1 Total 3,252 100 1,769 100 5,020 100 District Not Using Draft Animals 17.1: ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District during 2002/03 agricultural year, Mtwara Region. 17.2 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By District During 2002/03 Agriculture Year, Mtwara Region 17.3 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area applied with Organic fertiliser District Using Organic Fertilizer Not Using Organic Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census- 2003 Mtwara Appendix II 214 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 215 Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Mtwara Rural 384 4,031 0 . 93 743.2589582 477 4,775 Newala 749 1,891 0 . 0 . 749 1,891 Masasi 1,947 9,346 0 . 0 . 1,947 9,346 Tandahimba 364 1,083 0 . 0 . 364 1,083 Mtwara Urban 31 31 0 . 31 31.36338112 31 63 Total 3474.422301 16383.44 0 . 124.2707509 774.6223394 3567.329671 17158.063 Herd Size Number of Household % Number of Cattle % Average Number Per Household 1-5 2,806 79 7,475 44 3 6-10 418 12 3,178 19 8 11-15 96 3 1,057 6 11 16-20 159 4 2,856 17 18 21-30 89 3 2,592 15 29 Total 3,567 100 17,158 100 5 Type Number of Indigenous Number of Improved Beef Number of Improved Dairy Total Cattle Bulls 2,482 0 93 2,575 Cows 6,482 0 496 6,978 Steers 0 0 0 0 Heifers 2,810 0 186 2,996 Male Calves 1,865 0 0 1,865 Female Calves 2,744 0 0 2,744 Total 16383 0 774.6 17158.06253 Bulls Cows Steers Heifers Male Calves Female Calves Total Mtwara Rural 635 1,290 0 454 742 911 4,031 Newala 288 936 0 281 194 193 1,891 Masasi 1,292 3,717 0 2,076 806 1456 9,346 Tandahimba 268 539 0 0 92 184 1,083 Mtwara Urban 0 0 0 0 31 0 31 Total 2482 6482 . 2810 1865 2744 16383 Bulls Cows Steers Heifers Male Calves Female Calves Total Mtwara Rural . . . . . . . Newala . . . . . . . Masasi . . . . . . . Tandahimba . . . . . . . Mtwara Urban . . . . . . . Total . . . . . . . District Category - Improved Beef Cattle 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 18.4. CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 Improved Dairy 18.3: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size; on 1 st October 2003 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 Total Cattle District Indigenous Improved Beef Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 216 Bulls Cows Steers Heifers Male Calves Female Calves Total Mtwara Rural 93 465 . 186 . . 743 Newala . . . . . . . Masasi . . . . . . . Tandahimba . . . . . . . Mtwara Urban . 31 . . . . 31 Total 93 496 . 186 . . 775 Bulls Cows Steers Heifers Male Calves Female Calves Total Mtwara Rural 728 1,755 . 639 742 911 4,775 Newala 288 936 . 281 194 193 1,891 Masasi 1,292 3,717 . 2,076 806 1,456 9,346 Tandahimba 268 539 . . 92 184 1,083 Mtwara Urban . 31 . . 31 . 63 Total 2,575 6,978 . 2,996 1,865 2,744 17,158 Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Mtwara Rural 92 281 92 185 . . . . . . 192 192 658 Newala . . 94 186 . . 5,500 5,500 . . . . 5,685 Masasi 328 1,296 492 1,134 . . . . . 484 162 321 3,234 Tandahimba . 176 . 176 . . . . . . . . 351 Mtwara Urban . . . . . . . . . . . . . Total 420 1,753 678 1,681 . . 5,500 5,500 . 484 354 513 9,929 Male Calves Female Calves Total Cattle Offtake 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Total Cattle 18.13 CATTLE OFFTAKE: Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year 18.7 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Dairy Cattle District Bulls Cows Steers Heifers Tanzania Agriculture Sample Census -2003 Mtwara 217 Appendix II 218 GOAT PRODUCTION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 219 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Mtwara Rural 6,561 34,233 95 177 673 2 290 1,219 3 6,561 36,126 Newala 10,894 58,520 93 389 2,035 3 392 2,039 3 10,894 62,594 Masasi 6,779 32,899 93 162 1,621 5 162 972 3 6,779 35,493 Tandahimba 8,460 60,366 100 0 0 0 89 268 0 8,460 60,634 Mtwara Urban 256 1,828 100 0 0 0 0 0 0 256 1,828 Total 32,950 187,847 96 727 4,329 2 934 4,499 2 32,950 196,675 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 15796 48 39486 20 2 5-9 11906 36 78027 40 7 10-14 3126 9 35196 18 11 15-19 1108 3 18481 9 17 20-24 646 2 13467 7 21 25-29 188 1 4791 2 26 40+ 181 1 7227 4 40 Total 32950 100 196675 100 6 Total Goat 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as of 1st October, 2003 19.2: Number of Households Rearing Goats and Herds of Goats and Average Head per Household by Herd Size as on 1st October, 2003 Indigenous Improved for Meat Improved Dairy District Tanzania Agriculture Sample Cenusus - 2003 Mtwara Appendix II 220 Number Number Number Number Billy Goat 27,288 % 998 % 1,707 % 29,993 % Castrated Goat 760 61 297 24 198 16 1,255 She Goat 106,708 97 1,968 2 1,166 1 109,842 Male Kid 19,981 100 0 0 89 0 20,071 She Kid 33,110 93 1,066 3 1,340 4 35,515 Total 187,847 96 4,329 2 4,499 2 196,675 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mtwara Rural 5,341 . 20,531 2,707 5,654 34,233 Newala 8,337 486 34,134 5,669 9,893 58,520 Masasi 4,705 . 19,393 4,001 4,800 32,899 Tandahimba 8,631 274 31,892 7,272 12,297 60,366 Mtwara Urban 273 . 757 332 467 1,828 Total 27,288 760 106,708 19,981 33,110 187,847 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mtwara Rural 673 . . . . 673 Newala . 297 1,158 . 580 2,035 Masasi 324 . 810 . 486 1,621 Tandahimba . . . . . . Mtwara Urban . . . . . . Total 998 297 1,968 . 1,066 4,329 19.3: Total Number of Goats by Category and Type of Goat as on 1st October, 2003 District Type 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 Indigenous Goats Improved Meat Goat Improved Dairy Goat Total Goat District Number of Improved for Meat 19.5: Total Number of Indigenous Goat by Category and District as on 1st October, 2003 Category of Goats Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 221 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mtwara Rural 635.34 . . . 584 1,219 Newala 98.88 197.76 1,166 . 576.80 2,039 Masasi 972 . . . . 972 Tandahimba . . . 89 179 268 Mtwara Urban . . . . . . Total 1,707 198 1,166 89 1,340 4,499 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mtwara Rural 6,650 . 20,531 2,707 6,238 36,126 Newala 8,436 981 36,458 5,669 11,050 62,594 Masasi 6,002 . 20,203 4,001 5,286 35,493 Tandahimba 8,631 274 31,892 7,361 12,475 60,634 Mtwara Urban 273 . 757 332 467 1,828 Total 29,993 1,255 109,842 20,071 35,515 196,675 Total Goat 19.7: Total Number of Total Goat by Category and District as on 1st October, 2003 19.6: Total Number of Improved Dairy Goat by Category and District as on 1st October, 2003 District Improved Dairy Goats District Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 222 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 223 20.1: Total Number of Sheep by Type as on 1st October, 2003 Number % Number % Number % Ram 3,900 100 0 0 3,900 15 Castrated Sheep 0 0 0 0 0 0 She Sheep 13,090 100 0 0 13,090 52 Male Lamb 3,525 100 0 0 3,525 14 She Lamb 4,762 100 0 0 4,762 19 Total 25,275 100 0 0 25,275 100 Number % Number % Number % Mtwara Rural 482 1 44,672 99 45,154 100 Newala 554 1 42,511 99 43,065 100 Masasi 484 1 95,937 99 96,421 100 Tandahimba 1,935 5 39,888 95 41,823 100 Mtwara Urban 31 1 2,819 99 2,850 100 Total 3,487 2 225,827 98 229,314 100 District Number % Number % Number % Mtwara Rural 4,567 100 0 0 4,567 18 Newala 5,428 100 0 0 5,428 21 Masasi 3,361 100 0 0 3,361 13 Tandahimba 11,731 100 0 0 11,731 46 Mtwara Urban 188 100 0 0 188 1 Total 25,275 100 0 0 25,275 100 20.2: Number of Households Rearing or Managing Sheep by District as on 1st October, 2003. Number of Indigenous Total Sheep Number of Improved for Mutton Breed Number of Indigenous Number of Improved for Mutton Total Sheep 20.3: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 Households Raising Sheep Households Not Raising Sheep Total Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 224 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 1,462 42 3,654 14 3 5-9 827 24 5,324 21 6 10-14 915 26 10,717 42 12 15-19 188 5 3,388 13 18 20-24 95 3 2,192 9 23 Total 3,487 100 25,275 100 7 Ram Castrated Sheep She Sheep Male Lamb She Lamb Mtwara Rural 557 0 1,899 571 1,540 4,567 Newala 750 0 2,984 751 944 5,428 Masasi 973 0 1,443 630 315 3,361 Tandahimba 1,588 0 6,607 1,573 1,963 11,731 Mtwara Urban 31 0 157 0 0 188 Total 3,900 0 13,090 3,525 4,762 25,275 Ram Castrated Sheep She Sheep Male Lamb She Lamb Mtwara Rural . . . . . . Newala . . . . . . Masasi . . . . . . Tandahimba . . . . . . Mtwara Urban . . . . . . Total . . . . . . Ram Castrated Sheep She Sheep Male Lamb She Lamb Mtwara Rural 557 . 1,899 571 1,540 4,567 Newala 750 . 2,984 751 944 5,428 Masasi 973 . 1,443 630 315 3,361 Tandahimba 1,588 . 6,607 1,573 1,963 11,731 Mtwara Urban 31 . 157 . . 188 Total 3,900 . 13,090 3,525 4,762 25,275 20.3.5: Number of Households and Herds of Sheep by Herd Size as on 1st October, 2002/03 District Number of Indigenous 20.6: Total Number of Indigenous Sheep by Type and District as of 1st October, 2002/03 20.7: Total Number of Improved Sheep by Type and District as of 1st October. District Number of Improved for Mutton Total 20.8: Total Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 District Total Sheep Total Sheep Tanzania Agriculture Sample census -2003 Mtwara 225 Appendix II 226 PIGS HUSBANDRY Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 227 Herd Size Number of Household % Number of Pig % Average Number Per Household 1-4 3,031 90 4,675 74 2 5-9 324 10 1,618 26 5 Total 3,355 100 6,293 100 2 District Number of Household Number of Pig Average Number Per Household Newala 280 467 2 Masasi 3,075 5,826 2 Total 3,355 6,293 2 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Newala 186 0 93 94 94 467 Masasi 809 484 2,758 489 1,288 5,826 Total 994 484 2,851 583 1,382 6,293 District Pig Type 21.8: Total Number of Pigs by Type and District as on1st October, 2003 21.1: Number of Households and Pigs, by Herd Size as on 1st October, 2003 21.1: Number of Households and Pigs by District during 2002/03. Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 228 PESTS AND PARASITE Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 229 No of % No of % Mtwara Rur 1,076 30 2,485 70 3,561 Newala 752 10 6,754 90 7,505 Masasi 1,611 27 4,369 73 5,980 Tandahimba 1,213 17 5,725 83 6,937 Mtwara Urb 85 21 319 79 404 Total 4,736 19 19,651 81 24,388 No of % No of % No of % No of % Mtwara Rur 581 21 495 21 0 0 92 100 Newala 191 7 653 27 89 100 0 0 Masasi 1,296 47 640 27 0 0 0 0 Tandahimba 651 24 561 23 0 0 0 0 Mtwara Urb 26 1 59 2 0 0 0 0 Total 2,745 100 2,408 100 89 100 92 100 Total Number % Number % Number Mtwara Rur 495 14 2,922 86 3,417 Newala 95 1 7,410 99 7,505 Masasi 802 14 5,019 86 5,821 Tandahimba 559 8 6,378 92 6,937 Mtwara Urb 0 0 404 100 404 Total 1,951 8 22,134 92 24,085 Total Number % age Number % age Number Mtwara Rur 388 78 107 22 495 Newala 95 100 0 0 95 Masasi 485 60 317 40 802 Tandahimba 559 100 0 0 559 Total 1,528 78 424 22 1,951 Pigs 22.2: PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agriculture Year. District Deworming Livestock Not deworming Livestock Total 22.1: PESTS AND PARASITE: Number of Livestock Rearing households that dewormed Livestock by Type and District during 2002/03 Agriculture Year. District Cattle Goats Sheep 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District None Spray Method of Tsetse Flies Control 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control use during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Tsetse flies No Tsetse flies Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 230 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 231 Number % Type Number Indigenous Chicken 1,751,278 98 Ducks 117,486 Layer 29,630 2 Turkeys 503 Broiler 7,859 0 Rabbits 16,611 0 Donkeys 17,502 Total 1,788,767 100 152,103 Indigenous Chicken Layer Broiler Total Mtwara Rur 114,887 318 . 115,205 Ducks Turkeys Rabbits Other Newala 126,056 . 2,066 128,122 Mtwara Rur 719 0 0 . Masasi 295,463 1,963 820 298,246 Newala 3,143 0 589 838 Tandahimba 157,855 184 . 158,038 Masasi 4,839 20,607 0 . Mtwara Urb 10,358 163 . 10,521 Tandahimba 184 . 0 . Total 704,619 2,627 2,886 710,132 Total 8,885 20,607 589 838 Flock Size Number of Household s % Number of Chicken Average Chicken per Households 1-4 53,208 54.9 125,735 2 5-9 22,734 23.4 147,040 6 19-Oct 15,273 15.7 193,532 13 20-29 3,681 3.8 86,977 24 30-39 858 0.9 27,688 32 40-49 258 0.3 11,117 43 50-99 720 0.7 45,999 64 100+ 253 0.3 72,045 285 Total 96,984 100 710,132 7 23d: OTHER LIVESTOCK: Total Number of households and chicken raised by flock size as of 1 st October 2003. 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 Chicken Others District Chicken Type 23b OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District District Type of Livestock 23c. OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 232 FISH FARMING Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 233 District Was Fish farming carried out by this household during 2002/03 Yes % NO % Number Masasi 477 0.5 95,943 99.5 96,421 Mtwara Rur 0 0.0 45,154 100.0 45,154 Newala 0 0.0 43,065 100.0 43,065 Tandahimba 0 0.0 41,823 100.0 41,823 Mtwara Urb 0 0.0 2,850 100.0 2,850 Total 477 0.2 228,837 99.8 229,314 Natural Pond Dug out Pond Natural Lake Water Resevoir Other Masasi 0 317 0 0 0 Total 0 317 0 0 0 Source of fingerlings NGOs / Project Masasi 317 Total 317.2923749 Neighbour Local Market Large Scale Farm Trader at Farm Did not Sell Other Masasi 0 0 0 0 317 0 Total 0 0 0 0 317 0 District Number of Tilapia Number of Carp Number of Others Masasi 71,391 0 0 Total 71391 0 0 28.2b FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year 28.2a FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year where sold District 28.2c FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year District District system of fish farming Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 234 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 235 No of households % No of households % Mtwara Rur 2,623 6 42,531 94 45,154 4,246 62 Newala 1,694 4 41,371 96 43,065 7,505 23 Masasi 3,517 4 92,904 96 96,421 5,980 59 Tandahimba 2,253 5 39,570 95 41,823 6,937 32 Mtwara Urb 124 4 2,726 96 2,850 404 31 Total 10,211 4 219,103 96 229,314 14,886 69 Government Total Mtwara Rur 1,404 1,404 Newala 855 855 Masasi 971 971 Tandahimba 1,596 1,596 Mtwara Urb 65 65 Total 4,891 4,891 Government Total Total number of households raising livestock % of receiving advice out of total Mtwara Rur 697 697 4,246 37 Tandahimba 189 189 6,937 60 Mtwara Urb 31 31 404 3 Total 917 917 11,588 100 % 100 100 % 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year 29.1 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice By District during the 2002/03 Agricultural Year Received livestock advice Did Not receive livestock advice Total Total Number of households raising livestock District Source of Advice District District Source of Advice Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 236 Government Total Total number of households raising livestock % of receiving advice out of total Mtwara Rur 505 505 4,246 40 Masasi 162 162 5,980 56 Mtwara Urb 31 31 404 4 Total 698 698 10,630 100 % 100 100 Government NGO / Developmen t Project Total Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 1,254 0 1,254 4,246 30 Newala 480 0 480 7,505 6 Masasi 1,428 151 1,579 5,980 26 Tandahimba 1,022 0 1,022 6,937 15 Mtwara Urb 124 0 124 404 31 Total 4,307 151 4,459 14,886 30 % 96.6 3.4 100.0 Government Other Total Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 107 92 199 4,246 5 Newala 99 0 99 7,505 1 Masasi 326 0 326 5,980 5 Tandahimba 287 0 287 6,937 4 Mtwara Urb 31 0 31 404 8 Total 850 92 942 14,886 6 % 90.2 9.8 100.0 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice District Source of Advice District Source of Advice 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 237 Government Total Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 107 107 4,246 3 Newala 186 186 7,505 2 Masasi 164 164 5,980 3 Tandahimba 191 191 6,937 3 Mtwara Urb 31 31 404 8 Total 679 679 14,886 5 % 100 100 Government NGO / Developme nt Project Co- operative Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 318 0 0 318 4246 7 Masasi 320 461 0 781 5980 5 Tandahimba 0 0 281 281 6937 1 Mtwara Urb 31 0 26 57 404 355 Total 669 461 307 1,437 14886 1 % 46.5 32.1 21.4 100.0 Government Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 730 730 4,246 17 Newala 285 285 7,505 4 Masasi 326 326 5,980 5 Mtwara Urb 31 31 404 339 Total 1,372 1,372 14,886 1 % 100 100 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice Pasture Establishment By Source and District, 2002/03 Agricultural Year District Source of Advice District Source of Advice District Source of Advice 29.1k LIVESTOCK EXTENSION: Number of Households Receiving Advice on Calf rearing By Source and District, 2002/03 Agricultural Year 29.1j LIVESTOCK EXTENSION: Number of Households Receiving Advice Group Formation By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 238 Government Total Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 292 292 4246 7 Newala 186 186 7505 2 Masasi 326 326 5980 5 Tandahimba 287 287 6937 4 Mtwara Urb 31 31 404 8 Total 1121 1121 14886 8 % 100 100 Number % Number % Number % Number % Number % Mtwara Rur 482 16 2,337 77 213 7 0 0 0 0 3,032 Newala 193 14 559 40 574 41 89 6 0 0 1,415 Masasi 1,144 12 2,369 24 1,296 13 5,016 51 0 0 9,825 Tandahimba 650 19 1,132 32 654 19 665 19 387 11 3,489 Mtwara Urb 31 12 124 48 26 10 26 10 51 20 258 Total 2,501 14 6521 36 2763 15 5796 32 439 2 18019 No Good Quality of Service District Source of Advice 29.1l LIVESTOCK EXTENSION: Number of Households Receiving Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Very Good Good Average Poor Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 239 Government NGO / Developmen t Project Co-operative Large Scale Farmer Other Total Total Number of households raising livestock % of receiving advice out of total Mtwara Rur 2,623 2,623 2,623 2,623 2,623 13,114 4,246 309 Newala 1,694 1,601 1,601 1,601 1,601 8,097 7,505 108 Masasi 3,517 3,517 3,517 3,517 3,517 17,583 5,980 294 Tandahimba 2,253 2,253 2,253 2,253 2,253 11,266 6,937 162 Mtwara Urb 124 124 124 124 124 621 404 154 Total 10,211 10,118 10,118 10,118 10,118 50,681 14,886 340 % 20 20 20 20 20 100 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Mtwara Rur 25.9 2.0 4.6 0.6 48.3 4.5 48.1 6.3 16.2 40.7 35.3 Newala 10.7 1.5 4.0 1.1 24.8 4.6 27.5 1.9 2.8 20.9 53.1 Masasi 14.7 1.1 3.5 0.8 36.4 6.1 43.9 2.8 10.7 38.6 36.9 Tandahimba 14.7 0.6 1.7 0.3 42.5 5.5 23.9 10.0 41.6 35.5 90.4 Mtwara Urb 5.6 1.3 0.8 0.3 10.1 1.9 10.3 2.0 6.3 10.8 4.3 Total 16.0 1.2 3.4 0.8 37.4 5.4 37.6 4.6 15.9 34.8 49.0 Regiona Capital Tertiary Market Hospitals Tarmac Roads Secondary Market Primary Market Health Clinics All Weather Roads Feeder Roads 131.09 34.76 37.38 48.96 15.86 4.64 5.35 37.56 0.76 29.1 LIVESTOCK EXTENSION: Number of Households Receiving Advice on Other Extension Messages by Source and District, 2002/03 Table 3.16: Mean distances from holders dwellings to infrustructures and services by districts District Mean Distance to District Extension Provider Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 240 ACCESS TO INTRASTRUCTURE & OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 241 No of households % No of households % No of households % No of households % No of households % Mtwara Rur 2,015 4.5 703 1.6 10,980 24.3 7,538 16.7 23,918 53.0 45,154 25.9 Newala 1,119 2.6 1,233 2.9 16,449 38.2 21,139 49.1 3,125 7.3 43,065 10.7 Masasi 2,091 2.2 2,572 2.7 33,602 34.8 34,087 35.4 24,068 25.0 96,421 14.7 Tandahimba 1,700 4.1 376 0.9 16,463 39.4 8,394 20.1 14,891 35.6 41,823 14.7 Mtwara Urb 672 23.6 544 19.1 1,076 37.7 559 19.6 0 0.0 2,850 5.6 Total 7,597 3.3 5,427 2.4 78,571 34.3 71,718 31.3 66,002 28.8 229,314 16.0 No of households % No of households % No of households % No of households % No of households % Mtwara Rur 24,245 53.7 5,348 11.8 10,417 23.1 3,363 7.4 1,780 3.9 45,154 4.55 Newala 24,523 56.9 9,501 22.1 8,168 19.0 94 0.2 780 1.8 43,065 3.99 Masasi 45,336 47.0 18,796 19.5 20,861 21.6 10,937 11.3 491 0.5 96,421 3.52 Tandahimba 31,484 75.3 4,023 9.6 4,678 11.2 1,453 3.5 187 0.4 41,823 1.71 Mtwara Urb 1,926 67.6 718 25.2 206 7.2 0 0.0 0 0.0 2,850 0.76 Total 127,514 55.6 38,385 16.7 44,329 19.3 15,846 6.9 3,239 1.4 229,314 3.45 No of households % No of households % No of households % No of households % Mtwara Rur 38,753 85.8 4,561 10.1 1,628 3.6 212 0.5 45,154 0.6 Newala 31,617 73.4 10,470 24.3 786 1.8 192 0.4 43,065 1.1 Masasi 83,584 86.7 5,823 6.0 6,033 6.3 980 1.0 96,421 0.8 Tandahimba 38,023 90.9 2,343 5.6 1,458 3.5 0 0.0 41,823 0.3 Mtwara Urb 2,480 87.0 336 11.8 35 1.2 0 0.0 2,850 0.3 Total 194,457 84.8 23,532 10.3 9,941 4.3 1,384 0.6 229,314 0.8 Distance to Secondary School Table 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year Table 33.01c: Number of Households By Distance to All Weather Road by Distcrict for 2002/03 agriculture year District Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Total Mean Distance to All Weather Road District Less than 1 km 1-2.9 km 3.0-9.9 Above 20 km Distance to Feeder Road 1-2.9 km 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Total Mean Total Mean 3.0-9.9 10.0-19.9 Above 20 km District Less than 1 km Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 242 No of households % No of households % No of households % No of households % No of households % Mtwara Rur 92 0.2 0 0.0 3,907 8.7 3,266 7.2 37,889 83.9 45,154 48.3 Newala 381 0.9 0 0.0 6,829 15.9 9,908 23.0 25,947 60.3 43,065 24.8 Masasi 653 0.7 161 0.2 11,991 12.4 25,061 26.0 58,555 60.7 96,421 36.4 Tandahimba 97 0.2 0 0.0 187 0.4 3,133 7.5 38,406 91.8 41,823 42.5 Mtwara Urb 0 0.0 0 0.0 1,588 55.7 1,262 44.3 0 0.0 2,850 10.1 Total 1,223 0.5 161 0.1 24,502 10.7 42,631 18.6 160,797 70.1 229,314 37.4 No of households % No of households % No of households % No of households % No of households % Mtwara Rur 12,113 26.8 8,775 19.4 19,637 43.5 4,009 8.9 620 1.4 45,154 4.5 Newala 12,804 29.7 10,233 23.8 13,375 31.1 4,874 11.3 1,779 4.1 43,065 4.6 Masasi 18,634 19.3 10,659 11.1 52,730 54.7 12,636 13.1 1,762 1.8 96,421 6.1 Tandahimba 12,085 28.9 4,489 10.7 22,416 53.6 2,556 6.1 278 0.7 41,823 5.5 Mtwara Urb 682 23.9 1,302 45.7 866 30.4 0 0.0 0 0.0 2,850 1.9 Total 56,318 24.6 35,458 15.5 109,024 47.5 24,075 10.5 4,439 1.9 229,314 5.4 No of households % No of households % No of households % No of households % No of households % Mtwara Rur 21,022 46.6 14,119 31.3 9,800 21.7 0 0.0 213 0.5 45,154 Newala 23,829 55.3 15,858 36.8 2,897 6.7 99 0.2 383 0.9 43,065 Masasi 52,578 54.5 35,181 36.5 7,367 7.6 1,144 1.2 151 0.2 96,421 Tandahimba 32,939 78.8 8,040 19.2 844 2.0 0 0.0 0 0.0 41,823 Mtwara Urb 1,284 45.1 1,122 39.4 444 15.6 0 0.0 0 0.0 2,850 Total 131,652 57.4 74,319 32.4 21,352 9.3 1,242 0.5 748 0.3 229,314 Above 20 km Total Distance to Primary Schools Table 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Distance to Health Clinic Distance to hospital Total Mean Table 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Total Mean Table 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year District Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 District Less than 1 km Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 243 District Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Total Mean Distance Mtwara Rur 38,753 4,561 1,628 212 45,154 90,308 0.6 Newala 31,617 10,470 786 192 43,065 86,130 1.1 Masasi 83,584 5,823 6,033 980 96,421 192,842 0.8 Tandahimba 38,023 2,343 1,458 0 41,823 83,647 0.3 Mtwara Urb 2,480 336 35 0 2,850 5,701 0.3 Total 194,457 23,532 9,941 1,384 229,314 458,628 0.8 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Mean Distance Mtwara Rur 412 0 1,539 2,964 40,239 45,154 48 Newala 0 0 6,727 8,769 27,570 43,065 27 Masasi 0 161 7,378 20,566 68,317 96,421 44 Tandahimba 185 0 2,965 9,268 29,406 41,823 24 Mtwara Urb 32 0 1,555 1,264 0 2,850 10 Total 629 161 20,163 42,830 165,531 229,314 38 33.01i: Number of Households by Distance to Regional Capital and District, 2002/03 Agricultural 33.01h: Number of Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Tanzania Agriculure Sample Census -2003 Mtwara Appendix II 244 District Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Mtwara Rur 1,948 0 6,769 7,119 29,318 45,154 35.3 Newala 4,561 0 295 4,310 33,899 43,065 53.1 Masasi 9,568 5,151 7,872 16,794 57,035 96,421 36.9 Tandahimba 2,266 0 194 1,259 38,105 41,823 90.4 Mtwara Urb 405 713 1,627 105 0 2,850 4.3 Total 18,749 5,864 16,756 29,587 158,357 229,314 49.0 District Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Mtwara Rur 25,505 7,278 5,102 1,527 5,742 45,154 6.3 Newala 24,188 14,604 3,696 0 577 43,065 1.9 Masasi 61,979 7,510 17,487 7,351 2,094 96,421 2.8 Tandahimba 35,217 2,827 939 0 2,841 41,823 10.0 Mtwara Urb 1,458 195 1,197 0 0 2,850 2.0 Total 148,347 32,413 28,421 8,879 11,254 229,314 4.6 Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Mtwara Rur 1,042.8 0.0 6,299.1 1,831.6 35,980.7 45,154.1 40.7 Newala 3,318.9 5,100.6 10,030.1 7,484.6 17,131.1 43,065.2 20.9 Masasi 10,694.2 1,447.4 9,191.7 17,617.3 57,470.4 96,420.8 38.6 Tandahimba 12,985.0 288.9 5,149.8 5,434.7 17,964.9 41,823.3 35.5 Mtwara Urb 57.1 0.0 1,366.2 1,327.3 99.9 2,850.4 10.8 Total 28,097.9 6,836.9 32,036.8 33,695.4 128,647.0 229,314.0 34.8 Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Mtwara Rur 20,808.6 513.1 3,716.5 4,691.7 15,424.3 45,154.1 16.2 Newala 25,606.8 12,896.1 3,887.9 191.2 483.2 43,065.2 2.8 Masasi 46,796.3 1,927.2 3,471.0 37,266.6 6,959.8 96,420.8 10.7 Tandahimba 20,653.6 1,237.9 1,126.4 2,648.8 16,156.6 41,823.3 41.6 Mtwara Urb 1,292.8 0.0 716.2 841.4 0.0 2,850.4 6.3 Total 115,158.1 16,574.3 12,917.9 45,639.7 39,023.9 229,314.0 15.9 Table 33.01: Number of Households By Distance to Secondary Market Market and Distric for the 2002/03 Agricultural Year Table 33.01: Number of Households By Distance toTarmac Road and Distric for the 2002/03 Agricultural Year 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year Table 33.01: Number of Households By Distance to Tertiary Market Market and Distric for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 245 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 1,118 0.4 3,285 1.2 1,409 0.5 12,361 4.6 213 0.1 270,925 Newala 279 0.1 384 0.1 4,876 1.9 5,152 2.0 15,109 5.8 258,391 Masasi 1,622 0.3 10,789 1.9 21,333 3.7 65,731 11.4 2,749 0.5 578,525 Tandahimba 2,583 1.0 7,159 2.9 7,221 2.9 4,972 2.0 95 0.0 250,940 Mtwara Urb 0 0.0 725 4.2 299 1.8 128 0.7 63 0.4 17,103 Total 5,602 0.4 22,341 1.6 35,140 2.6 88,342 6.4 18,229 1.3 1,375,884 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 515 8.9 2,046 35.2 412 7.1 2,730 47.0 107 1.8 5,809 Newala 99 1.9 96 1.8 1,662 31.5 750 14.2 2,672 50.6 5,280 Masasi 323 1.4 8,853 37.7 6,132 26.1 7,538 32.1 644 2.7 23,490 Tandahimba 637 6.9 5,194 56.1 3,042 32.9 378 4.1 0 0.0 9,251 Mtwara Urb 0 0.0 133 58.4 31 13.7 64 27.8 0 0.0 228 Total 1,574 3.6 16,323 37.0 11,279 25.6 11,459 26.0 3,423 7.8 44,058 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 199 4.0 716 4.0 0 4.0 2,833 84.0 107 4.0 3,854 Newala 0 50.0 0 50.0 1,378 0.0 942 0.0 2,669 0.0 4,989 Masasi 161 0.0 164 35.6 2,291 16.7 11,897 14.9 328 32.8 14,841 Tandahimba 1,117 0.0 280 12.0 360 79.4 741 8.6 0 0.0 2,498 Mtwara Urb 0 0.0 172 0.0 69 0.0 0 100.0 0 0.0 240 Total 1,477 4.5 1,332 13.9 4,098 20.7 16,413 50.1 3,103 10.8 26,423 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District District Research Station Total Number of households District Extension Centre Total Number of households 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year Satisfaction of Using Veterinary Clinic Total Number of households 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 246 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 0 0.0 209 7.7 301 11.0 2,215 81.3 0 0.0 2,726 Newala 0 0.0 0 0.0 1,279 26.7 750 15.6 2,771 57.7 4,800 Masasi 162 1.1 0 0.0 2,291 16.0 11,577 80.6 328 2.3 14,358 Tandahimba 90 5.4 285 16.9 462 27.4 845 50.3 0 0.0 1,682 Mtwara Urb 0 0.0 140 58.9 66 27.9 0 0.0 31 13.2 238 Total 252 1.1 634 2.7 4,399 18.5 15,388 64.6 3,130 13.2 23,804 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 313 9.8 0 0.0 199 6.2 2673 83.9 0 0.0 3184 Newala 180 4.9 287 7.8 277 7.5 932 25.2 2028 54.8 3704 Masasi 163 0.9 326 1.9 2290 13.2 14290 82.1 328 1.9 17397 Tandahimba 269 5.9 1125 24.5 2439 53.2 660 14.4 95 2.1 4588 Mtwara Urb 0 0.0 105 39.0 101 37.7 31 11.7 31 11.7 269 Total 925 3.2 1844 6.3 5306 18.2 18586 63.8 2483 8.5 29143 Very Good Good Average Poor No good No of Households % No of Households % No of Households % No of Households % No of Households % Mtwara Rur 0 0.0 105 9.6 301 27.6 684 62.8 0 0.0 1,090 Newala 0 0.0 0 0.0 95 2.7 934 26.6 2,486 70.7 3,515 Masasi 324 1.9 960 5.6 3,438 20.1 11,899 69.5 492 2.9 17,113 Tandahimba 186 9.1 180 8.8 462 22.6 1,218 59.5 0 0.0 2,045 Total 510 2.1 1,244 5.2 4,296 18.1 14,734 62.0 2,978 12.5 23,762 TYPE OF SERVI Very Good No of Households % No of Households % No of Households % No of Households % No of Households % Veterinary Clinic 5,602 0 22,341 2 35,140 3 88,342 6 18,229 1 Centre 1,574 4 16,323 37 11,279 26 11,459 26 3,423 8 Station 1,477 5 1,332 14 4,098 21 16,413 50 3,103 11 Lab 252 1 634 3 4,399 18 15,388 65 3,130 13 Registration 925 3 1,844 6 5,306 18 18,586 64 2,483 9 Livestock Development Centre 510 2 1,244 5 4,296 18 14,734 62 2,978 13 OVERALL % 10339 3 43717 14 64518 20 164923 52 33345 11 LEVEL OF SATISFACTION OF THE SERVICE 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and District for 2002/03 Agricultural year Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District District Livestock Development Centre Total Number of households Land Registration Office Total Number of households 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total Number of households Tanzania Agriculture Sample Census -2003 Mtwara 247 Appendix II 248 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 249 District No Toilet Flush Toilet Traditional Pit Latrine Improve d Pit Latrine Total number of households Mtwara Rur 4,749 3,002 36,450 953 45,154 Newala 1,075 98 41,703 189 43,065 Masasi 651 1,613 93,840 317 96,421 Tandahimba 376 278 40,908 261 41,823 Mtwara Urb 98 0 2,721 32 2,850 Total 6,950 4,990 215,622 1,752 229,314 District Number of rooms and Type of roof construction material Iron Sheets Tiles Concret e Asbestos Grass / Leaves Grass & Mud Total Mtwara Rur 3 7,244 392 0 672 36,447 399 45,154 Newala 3 12,566 468 0 97 29,544 391 43,065 Masasi 2 16,657 443 164 0 73,760 5,397 96,421 Tandahimba 3 12,645 372 276 287 24,736 3,507 41,823 Mtwara Urb 2 676 0 0 0 2,142 32 2,850 Total 2 49,788 1,675 440 1,056 166,629 9,726 229,314 Number of households % Number of households % Number of households % Number of households % Number of households % Number of households % Radio 14,846 15 20,486 21 43,692 45 17,037 17 1,714 2 97,775 41 Landline phone 103 40 89 35 0 0 0 0 64 25 256 0 Mobile phone 103 16 0 0 162 26 367 58 0 0 633 0 Iron 2,710 8 8,148 25 15,130 47 5,372 17 698 2 32,058 13 Wheelbarrow 207 8 379 15 1,123 45 739 30 34 1 2,482 1 Bicycle 17,293 17 20,972 20 39,981 39 22,712 22 1,768 2 102,726 43 Vehicle 508 22 763 34 628 28 367 16 0 0 2,266 1 Television/Video 314 26 289 24 327 27 274 23 0 0 1,203 1 Total Number of Households 36084 15 51126 21 101044 42 46869 20 4277 2 239399 100 Tandahimba Mtwara Urb Total Mtwara Rur Newala Masasi 34.2: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year Type of toilet 34-1:Number of Households by Type of Toilet and District, during the 2002/03 Agricultural Year 34.3: Number of hoseholds type of Owned Asset and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 250 Number of households % Number of households % Number of households % Number of households % Number of households % Number of households % Main Electricity 608 34 463 26 646 36 0 0 64 4 1782 1 Gas(Biogas) 0 0 0 0 164 63 96 37 0 0 260 0 Hurrican Lamp 7390 13 15851 28 18178 32 14075 25 644 1 56138 24 Prussure Lamp 1,501 24 1,816 29 1,777 29 1,134 18 0 0 6,228 3 Wick Lamp 34,598 22 23,976 15 72,741 46 26,046 16 2,142 1 159,502 70 Candles 212 24 189 21 485 55 0 0 0 0 886 0 Firewood 845 19 770 17 2,430 54 473 10 0 0 4,517 2 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Number of households % Number of households % Number of households % Number of households % Number of households % Number of households % Main Electricity 0 0 194 100 0 0 0 0 0 0 194 0 Solar 96.749985 100 0 0 0 0 0 0 0 0 97 0 Gas(Biogas) 103 55 86 45 0 0 0 0 0 0 189 0 Parraffin / Kerocine 0 0 0 0 324 73 96 22 26 6 446 0 Charcoal 614 21 98 3 1,623 54 565 19 89 3 2,989 1 Firewood 44,341 20 42,492 19 94,149 42 41,068 18 2,735 1 224,785 98 Crop Residues 0 0 196 32 325 53 94 15 0 0 615 0 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Total 34.4: Number of Agricultural Households Source of Energy for Lighting and District, 2002/03 Agricultural Year 34.5: Number of Agricultural Households Source of Energy for Cooking and District, 2002/03 Agricultural Year Type of Owned Asset Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Total Masasi Tandahimba Mtwara Urb Type of Owned Asset Mtwara Rur Newala Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 251 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Total Wet 9,270 28,612 15,766 5,355 1,476 60,480 Dry 11,236 30,345 15,305 6,801 1,451 65,138 Wet 4,489 1,259 7,663 1,537 843 15,791 Dry 5,745 1,363 6,850 556 948 15,462 Wet 813 869 2,440 191 197 4,510 Dry 789 1,053 2,440 384 199 4,865 Wet 10,156 2,199 50,660 3,501 99 66,615 Dry 9,037 837 54,213 2,283 125 66,495 Wet 3,776 1,811 9,497 6,197 102 21,384 Dry 8,127 1,908 9,661 21,703 - 41,399 Wet 735 1,268 164 4,634 - 6,801 Dry 735 974 328 1,098 31 3,166 Wet 8,602 1,172 2,641 12,495 70 24,980 Dry 522 - - 931 - 1,453 Wet - - - 1,928 - 1,928 Dry 87 92 - 365 - 543 Wet 7,314 5,776 7,427 1,741 63 22,320 Dry 8,876 6,493 7,623 7,607 96 30,697 Wet - 99 163 4,244 - 4,506 Dry - - - 96 - 96 Total Agricultural Households per District 90,308 86,130 192,842 83,647 5,701 458,628 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Total Wet 10 33 8 6 26 13 Dry 12 35 8 8 25 14 Wet 5 1 4 2 15 3 Dry 6 2 4 1 17 3 Wet 1 1 1 0 3 1 Dry 1 1 1 0 3 1 Wet 11 3 26 4 2 15 Dry 10 1 28 3 2 14 Wet 4 2 5 7 2 5 Dry 9 2 5 26 - 9 Wet 1 1 0 6 - 1 Dry 1 1 0 1 1 1 Wet 10 1 1 15 1 5 Dry 1 - - 1 - 0 Wet - - - 2 - 0 Dry 0 0 - 0 - 0 Wet 8 7 4 2 1 5 Dry 10 8 4 9 2 7 Wet - 0 0 5 - 1 Dry - - - 0 - 0 Total Agricultural Households per District 100 100 100 100 100 100 Other 34.6: Number of Agricultural Households by Main Source of Drinking Water (Wet & Dry) and District during 2002/03 Agricultural 34.6: Proportion Number of Agricultural Households by Main Source of Drinking Water (Wet & Dry) and District during 2002/03 Agricultural Covered Rainy Water Catchment Uncovered Rain Water Catchment Water Vendor Unprotected Spring Protected Well Protected/Covered Spring Unprotected Well Surface Water(Lake/Dam/River/Stream Source Season District Pipe water Water Vendor Unprotected Spring Other Unprotected Well Surface Water(Lake/Dam/River/Stream Covered Rainy Water Catchment Uncovered Rain Water Catchment Protected/Covered Spring District Season Source Pipe water Protected Well Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 252 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Wet 11,702 3,664 10,308 22,193 591 Dry 7,602 3,573 8,392 5,138 522 Wet 6,082 4,856 10,949 5,394 533 Dry 3,263 4,858 9,868 572 502 Wet 1,720 1,062 5,416 1,615 180 Dry 1,423 1,062 4,933 954 154 Wet 6,343 2,683 10,367 4,397 449 Dry 4,469 2,585 8,292 1,629 413 Wet 12,786 4,221 26,042 3,516 689 Dry 7,174 4,123 21,491 1,586 722 Wet 4,919 7,045 11,181 2,451 137 Dry 4,929 7,333 11,936 4,566 67 Wet 1,499 1,881 14,354 1,248 240 Dry 9,562 1,790 18,073 6,248 379 Wet 104 11,060 7,640 1,010 32 Dry 6,306 11,154 13,115 19,872 91 Wet - 6,593 164 - - Dry 426 6,587 320 1,259 - Total 90,308 86,130 192,842 83,647 5,701 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Wet 13 4 5 27 10 Dry 8 4 4 6 9 Wet 7 6 6 6 9 Dry 4 6 5 1 9 Wet 2 1 3 2 3 Dry 2 1 3 1 3 Wet 7 3 5 5 8 Dry 5 3 4 2 7 Wet 14 5 14 4 12 Dry 8 5 11 2 13 Wet 5 8 6 3 2 Dry 5 9 6 5 1 Wet 2 2 7 1 4 Dry 11 2 9 7 7 Wet 0 13 4 1 1 Dry 7 13 7 24 2 Wet - 8 0 - - Dry 0 8 0 2 - 500 - 999 m 10 Km and above 1 - 1.99 m 2 - 2.99 m 3 - 4.99 m 5 - 9.99 m 34.8: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year Less than 100m 100 - 299 m 300 - 499 m District Distance to Main Source of Drinking Water Season District 34.9: Proportion Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year Less than 100m 10 Km and above Season Distance to Main Source of Drinking Water 2 - 2.99 m 3 - 4.99 m 5 - 9.99 m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 m Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 253 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Wet 2,603 2,402 1,123 8,748 459 Dry 1,671 2,332 978 1,279 450 Wet 12,552 3,566 7,912 10,985 822 Dry 8,300 3,649 6,613 3,543 712 Wet 4,399 2,952 6,124 4,949 318 Dry 2,119 2,947 5,191 1,512 388 Wet 9,097 4,281 25,847 5,407 486 Dry 4,327 4,470 18,444 1,610 396 Wet 3,451 1,172 7,428 1,755 125 Dry 1,491 1,170 6,145 739 190 Wet 4,268 1,583 3,540 4,127 348 Dry 1,652 1,390 4,977 665 289 Wet 8,783 27,110 44,447 5,853 294 Dry 25,594 27,107 54,074 32,475 426 Total 90,308 86,130 192,842 83,647 5,701 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Wet 3 3 1 10 8 Dry 2 3 1 2 8 Wet 14 4 4 13 14 Dry 9 4 3 4 12 Wet 5 3 3 6 6 Dry 2 3 3 2 7 Wet 10 5 13 6 9 Dry 5 5 10 2 7 Wet 4 1 4 2 2 Dry 2 1 3 1 3 Wet 5 2 2 5 6 Dry 2 2 3 1 5 Wet 10 31 23 7 5 Dry 28 31 28 39 7 34.10: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year District 20 - 29 Minutes Season Time Spent to and from Main Source of drinking Water Less than 10 minute 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes Less than 10 minute Above one hour 40 - 49 Minutes 50 - 59 Minutes 30 - 39 Minutes 40 - 49 Minutes 10 - 19 Minutes Above one hour Distance to Main Source of Drinking Water 50 - 59 Minutes 34.11: Proportion Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet & Dry) and District during 2002/03 agricultural year District Season Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 254 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 5,585 28 683 3 11,971 60 1,457 7 155 1 19,850.19 8.7 Two 24,228 18 25,399 19 59,028 45 21,255 16 1,541 1 131,450.97 57.3 Three 15,341 20 16,982 22 25,098 32 19,020 25 1,155 1 77,597.12 33.8 Four 0 0 0 0 324 78 92 22 0 0 415.67 0.2 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,313.96 100.0 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 26,435 23 15,290 13 58,973 50 14,686 13 1,720 1 117,105 51 One 8,640 16 13,388 25 19,904 38 10,128 19 528 1 52,588 23 Two 6,307 18 8,206 24 10,324 30 9,392 27 406 1 34,634 15 Three 1,811 14 3,750 30 2,866 23 4,011 32 131 1 12,569 5 Four 925 13 1,260 18 2,259 33 2,403 35 65 1 6,912 3 Five 828 30 585 21 652 24 657 24 - - 2,721 1 Six 103 9 191 17 646 57 192 17 - - 1,132 0 Seven 107 6 396 24 796 48 354 21 - - 1,653 1 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Number of Meals per Day Total District 34.13: Number of Households by Number of Days the household Consumed Meat during the Preceding Week by District Total 34.12: Number of Households by Number of Meals the household Normally Took per Day by District Number of Meals per Day District Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 255 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 4,122 16 2,720 10 16,744 64 2,534 10 183 1 26,303 11 One 6,639 18 10,297 27 16,966 45 3,751 10 131 0 37,785 16 Two 7,064 16 10,737 25 17,406 40 8,329 19 281 1 43,818 19 Three 4,219 11 11,485 31 12,562 33 8,801 23 528 1 37,595 16 Four 7,108 25 4,051 14 10,507 37 6,205 22 394 1 28,265 12 Five 5,216 25 1,628 8 8,029 39 5,312 26 558 3 20,743 9 Six 1,124 13 880 10 3,690 43 2,669 31 295 3 8,657 4 Seven 9,662 37 1,267 5 10,516 40 4,223 16 481 2 26,148 11 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 11,513 12 29,677 31 27,351 29 25,888 27 477 1 94,907 41 Seldom 18,512 25 8,743 12 36,043 48 11,151 15 1,015 1 75,463 33 Sometimes 5,415 29 3,201 17 6,738 36 2,784 15 586 3 18,724 8 Often 6,065 23 1,152 4 16,579 64 1,811 7 486 2 26,093 11 Always 3,648 26 291 2 9,711 69 190 1 287 2 14,127 6 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Number of Meals per Day District Total 34.15: Number of Households Reportying the status of food satisfaction of the households during the Preceding Year by District Number of Meals per Day District Total 34.14: Number of Households by Number of Days the household Consumed Fish during the Preceding Week by District Tanzania Agriculture Sample Census -2003 Mtwara Appendix II 256 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 17,812 17 30,549 29 46,104 43 10,967 10 570 1 106,002 46 Sales of Livestock 379 35 99 9 324 30 273 25 - - 1,075 0 Sales of Livestock Products 105 23 98 21 164 35 96 21 - - 463 0 Sales of Cash Crops 10,881 13 9,189 11 37,042 44 26,793 32 875 1 84,781 37 Sales of Forest Products 2,281 49 - - 1,937 42 278 6 132 3 4,628 2 Business Income 3,832 51 1,041 14 1,458 19 938 12 294 4 7,564 3 Wages & salaries in Cash 1,414 33 853 20 1,619 38 193 5 153 4 4,232 2 Other Casual Cash Earnings 2,573 29 484 6 4,034 46 1,057 12 644 7 8,792 4 Cash Remittances 1,818 37 379 8 1,943 39 657 13 148 3 4,945 2 Fishing 2,913 83 - - 323 9 284 8 - - 3,521 2 Other 1,146 36 372 12 1,471 46 191 6 35 1 3,215 1 Not applicable - - - - - - 96 100 - - 96 0 Total 45,154 20 43,065 19 96,421 42 41,823 18 2,850 1 229,314 100 Number of Meals per Day 34-16: Number of Households Reporting Main Source of Income by District, 2002/03 Agricultural Year District Total District Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Tanzania Agriculture Sample Census - 2003 Mtwara Appendix II 257 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Rooms 3 84 3 88 2 76 3 92 2 79 3 0 Iron Sheets 7,244 15 12,566 25 16,657 33 12,645 25 676 1 49,788 22 Tiles 392 23 468 28 443 26 372 22 - - 1,675 1 Concreate - - - - 164 37 276 63 - - 440 0 Asbestos 672 64 97 9 - - 287 27 - - 1,056 0 Grass & Mud 36,447 22 29,544 18 73,760 44 24,736 15 2,142 1 166,629 73 Grass/Leaves 399 4 391 4 5,397 55 3,507 36 32 0 9,726 4 Total 45,157 20 43,068 19 96,423 42 41,826 18 2,853 1 229,327 100 34.18: HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District Total Mtwara Rur Newala Masasi Tandahimba Mtwara Urb Roofing Materials Tanzania Agriculture Sample Census - 2003 Mtwara 258 APPENDIX III QUESTIONNAIRES Appendix III 259 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 260 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 261 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 262 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 263 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 264 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 265 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 266 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 267 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 268 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 269 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 270 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 271 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 272 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 273 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 274 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 275 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 276 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 277 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 278 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 279 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 280 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 281 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 282 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 283 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 284 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 285 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 286 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 287 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 288 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 289 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 290 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 291 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 292 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 293 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 294 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 295 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 296 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 297 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 298 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 299 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 300 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 301 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 302 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 303 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 304 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Anzia Sokoni, Malizia Shambani, Kwa Kipato Zaidi Desemba, 2023 MWONGOZO WA UTEKELEZAJI WA DHANA YA SHEP - TANZANIA MWONGOZO WA UTEKELEZAJI WA DHANA YA SHEP - TANZANIA Desemba 2023 ii Yaliyomo 1.0 UTANGULIZI 2.0 DHANA YA SHEP NA HATUA ZAKE MUHIMU 3.0 MUUNDO WA UTEKELEZAJI DHANA YA SHEP 4.0 UTEKELEZAJI WA DHANA YA SHEP 1.1 Historia ya Dhana ya SHEP 1.2 Lengo la mwongozo 1.2.1 Malengo mahsusi ya mwongozo 1.3 Walengwa na namna ya kutumia mwongozo 2.1 Dhana ya SHEP 3.1 Ngazi ya Serikali Kuu 4.1 Utekelezaji katika Ngazi ya Serikali Kuu na Sekretarieti za Mikoa 3.2 Ngazi ya Sekretarieti za Mikoa 3.3 Ngazi ya Mamlaka za Serikali za Mitaa 3.4 Majukumu ya Wakulima 3.5 Majukumu ya Sekta Binafsi 4.2 Utekelezaji wa Dhana ya SHEP (Hatua 4) kwa Ngazi ya Halmashauri na mipango inayotumia mbinu ya SHEP 2.2 Nguzo na hatua za SHEP 2.2.1 Hatua ya kwanza: Kushirikisha Wakulima Malengo 3.1.1 Majukumu ya Kikosi Kazi cha Utekelezaji 3.3.1 Majukumu ya Maafisa Ugani wa Kata na Vijiji 4.1.1 Uanzishaji na usimamizi wa Dhana ya SHEP Ngazi ya Mikoa 4.1.2 Kujenga uwezo wa kutumia Dhana ya SHEP 4.2.1 Warsha ya Utambulisho 4.2.2 Utafiti wa Awali 4.2.3 Utafiti wa Soko 2.2.2 Hatua ya Pili: Kuongeza Uelewa wa Wakulima 2.2.3 Hatua ya Tatu: Wakulima Kufanya Maamuzi 2.2.4 Hatua ya Nne: Wakulima kupata Ujuzi na Maarifa 1 1 1 1 1 3 3 3 3 3 3 4 5 5 5 5 5 6 6 6 7 7 7 9 11 12 13 15 iii 4.2.4 Hafla ya Kuunganisha Wadau 4.2.5 Mpango kazi 4.2.6 Mafunzo kwa Vikundi Vya Wakulima 4.2.7 Kufanya tathmini ya Mwisho 4.2.9 Matumizi ya SHEP kwa Mazao Mengine 4.2.8 Mafunzo Yaliyopatikana kutoka Mradi wa TANSHEP 4.2.5.1 Uchaguzi wa mazao 4.2.5.2 Uandaaji wa kalenda ya Uzalishaji 5.4.1 Ufuatiliaji na Tathmini ya Kila Mwezi Unaofanywa na MSM 5.3.1 Ufuatiliaji unaofanywa na Maafisa Ugani wa Kata na Vijiji 5.4.2 Taarifa ya Utekelezaji na Maendeleo za Robo Mwaka unaofanywa na MSM 5.4.3 Taarifa ya Utekelezaji wa SHEP ya Mwaka Unaofanywa na MSM 5.4.4 Ufuatiliaji wa Utoaji na Matumizi wa fedha kwa ajili ya kutekeleza dhana ya SHEP ngazi ya MSM 17 19 22 23 27 24 19 21 37 35 38 38 38 5.0 UFUATILIAJI NA TATHMINI 29 5.1 Ufuatiliaji na tathmini wa serikali kuu 5.2 Ufuatiliaji na tathmini kwa kutumia Bango kitita 5.3 Ufuatiliaji na tathmini ngazi ya tawala za mikoa 5.4 Ufuatiliaji na tathmini ngazi ya halmashauri 29 30 34 36 iv Kiambatisho Na: 03-02; Kiambatisho Na: 03-03; Kiambatisho Na: 03-04; Kiambatisho Na: 04; Kiambatisho Na: 05; 53 54 55 56-57 58-60 Mpango wa Utafiti wa soko Muundo wa Utafiti wa Soko Zoezi la kikundi la utafiti wa Soko Kuunganisha wadau Mpango wa Uzalishaji Kiambatisho Na: 01; Kiambatisho Na: 02-01; Kiambatisho Na: 02-02; Kiambatisho Na: 02-03; Kiambatisho Na: 03-01; VIAMBATISHO 41-43 44-45 46-47 48-49 50-52 Dhana ya SHEP Utafiti wa Awali Muundo wa Kumbukumbu ya mapato (FIR) Kubadilisha vipimo vya Mazao Utafiti wa Soko v Mwongozo huu ni miongoni mwa miongozo iliyoandaliwa na Serikali katika kuhakikisha wakulima wanazalisha kwa tija na kuzifikia fursa za masoko. Dhana ya SHEP inatoa elimu ya masoko na uzalishaji wa mazao kulingana na mahitaji ya soko lengwa. Pia,dhana hii inatoa mafunzo kwa wakulima ili waweze kufanya kilimo endelevu hasa kwa kuzingatia uelewa na taaluma ya masoko na uzalishaji wa kitaalam. Katika hali hii dhana ya SHEP itasaidia wakulima kujiamini na kujitegemea ikiwa ni hatua muhimu ya kufikia fursa za masoko. Vilevile,mwongozo huu umejikita katika nguzo kuu mbili za SHEP ambazo ni: “kilimo kama biashara” na “kuwezesha na kuinua hamasa ya Mkulima” ambazo zote hizi zitamsaidia mkulima kubadilika kutoka “kulima na kuuza” na kwenda “kulima kwa ajili ya kuuza”. Kutokana na changamoto za masoko ya mazao ya kilimo ikiwemo mazao ya bustani, dhana ya SHEP itakuwa suluhisho la changamoto hizo endapo nguzo kuu za SHEP zitatumiwa ipasavyo sambamba na hatua kuu nne ambazo zinamfanya mkulima kuwa na taarifa zitakazomuwezesha kupanga na kufanya maamuzi ya nini cha kulima kwa ajili ya soko. Wizara kwa kushirikiana na OR-TAMISEMI chini ya mradi wa TANSHEP, imeandaa mwongozo huu wa utekelezaji wa dhana ya SHEP Tanzania ambao umejikita katika kuwajengea uwezo maafisa ugani na kutoa elimu kwa wakulima kuhusu kuanza na utafiti wa soko. Mwongozo huu utakuwa nguzo ya kupanga na kuimarisha mazingira ya uzalishaji kulingana na uhitaji wa soko husika. Lengo likiwa kuongeza kipato cha mkulima kwa kuongeza uzalishaji na tija. Wizara inapenda kutoa shukrani za dhati kwa Shirika la Maendeleo la Kimataifa la Japan (JICA), Wataalam kutoka Wizara ya Kilimo na OR-TAMISEMI kwa kuandaa mwongozo huu. Vilevile, tunawashukuru wakulima na wadau wengine kwa ushirikiano wao mzuri hadi kukamilika kwa mwongozo huu. Nitoe wito kwa Wataalam wa kilimo, Wadau wa Maendeleo na Taasisi Zisizo za Kiserikali kutumia maarifa yaliyomo katika mwongozo huu ili kuwawezesha wakulima kutatua changamoto za masoko katika mazao wanayozalisha. DIBAJI Gerald G. Mweli, ndc KATIBU MKUU 1 1.0 UTANGULIZI 1.1 Historia ya Dhana ya SHEP 1.2 Lengo la Mwongozo 1.2.1 Malengo mahsusi ya mwongozo 1.3 Walengwa wa Mwongozo na namna ya kutumia Mwongozo SHEP ni kifupisho cha maneno “Smallholder Horticulture Empowerment and Promotion” ambayo ni dhana yenye lengo la kuwezesha wakulima wadogo wa mazao ya bustani kutekeleza kilimo endelevu cha kibiashara kwa kulenga mahitaji ya soko. Hata hivyo, dhana hii inalenga kutoa elimu ya masoko na uzalishaji kwa kuanza na utafiti wa soko kwa kuzingatia aina ya zao na mahitaji ya soko lengwa. Pia, dhana hii inatoa mafunzo kwa wakulima ili waweze kutekeleza kilimo endelevu hasa kwa kuzingatia uelewa na taaluma ya masoko na uzalishaji wa kitaalam. Katika hali hii, dhana ya SHEP inalenga kuwasaidia wakulima kujiamini na kujitegemea kama hatua muhimu ya kufikia malengo. Dhana hii ilijaribiwa na kutekelezwa nchini Kenya kuanzia mwaka 2006 kwa ushirikiano kati ya Serikali ya Jamhuri ya Kenya na Shirika la Maendeleo la Kimataifa la Japan (JICA) na kusambazwa kwenye nchi zaidi ya 30 duniani. Nchini Tanzania, dhana hii ilianza kutekelezwa kupitia mradi wa TANSHEP mwaka 2019 katika mikoa ya Tanga, Arusha na Kilimanjaro. Dhana hii imezifikia zaidi ya kaya 4,000 ambazo zilitekeleza kwa mafanikio makubwa sana. Takwimu zinaonesha kwamba, katika kipindi cha miaka mitano (5) ya utekelezaji wa Mradi, kipato cha mkulima kimeongezeka kwa wastani wa asilimia 45. Kutokana na mafanikio hayo, Serikali imeona ni vyema dhana hii itumike katika mikoa yote ya Tanzania katika mazao ya bustani na hata mazao mengine. Lengo kuu la mwongozo huu ni kusaidia wakulima, Wataalam katika Sekta ya Kilimo, Wadau wa Maendeleo pamoja na Taasisi Zisizo za Kiserikali kuelewa jinsi ya kutekeleza dhana ya SHEP katika kilimo biashara cha mazao ya bustani. Mwongozo huu unaweza kutumiwa na maafisa ugani na maafisa mipango wanaofanya kazi za maendeleo ya Sekta ya Kilimo katika ngazi mbalimbali kuanzia Serikali Kuu, Sekretarieti za Mikoa, Mamlaka za Serikali za Mitaa na Asasi Zisizo za Kiserikali. Maeneo yaliyoainishwa katika mwongozo huu kulingana na aina ya mtumiaji na umuhimu wake yameainishwa katika Jedwali Na. 01. »» Kuwawezesha watumiaji kuelewa dhana ya SHEP na hatua zake za utekelezaji; »» Kuwawezesha watumiaji kuwa na uelewa wa vitendo na kuwa na vitendea kazi vya kufundishia na kuwezesha wakulima kutekeleza dhana ya SHEP; na »» Kuwawezesha Wataalam katika Sekta ya Kilimo, kuelewa jinsi ya kufanya ufuatiliaji na tathmini ya utekelezaji wa dhana ya SHEP. 2 Jedwali Na. 01: Maeneo muhimu kulingana na aina ya mtumiaji YALIYOMO MLENGWA Maafisa Serikali Kuu Historia ya Dhana ya SHEP Majukumu katika Ngazi zote Utekelezaji wa Dhana ya SHEP Ufuatiliaji na Thathmini Sehemu ya 3.3 ni muhimu Sehemu ya 4.1 ni muhimu Sehemu ya 5.2 ni muhimu Tumia zile ambazo zinafaa Tumia zile ambazo zinafaa Tumia zile ambazo zinafaa Tumia zile ambazo zinafaa Sehemu ya 5.4 ni muhimu Tazama 4.2.7 kwa Ufuatiliaji na Tathmini yao(iliyojumuishwa katika hatua za SHEP) Vitendea kazi vya kufundishia na Shuhuda za mafanikio ya Dhana Sehemu ya 5.4 inaweza kutumika kama marejeleo ya kubuni mfumo wa Ufuatiliaji na Tathmini Sehemu ya 4.2 ni muhimu Sehemu ya 4.2 husaidia kuelewa hatua 4 za SHEP kwa undani Sehemu ya 4.2 husaidia kuelewa hatua 4 za SHEP kwa undani Sehemu ya 3.4 ni muhimu Sehemu ya 3.5 ni muhimu Lazima Lazima Lazima Lazima Maafisa Ugani MSM/Kata/Vijiji Vikundi vya wakulima Watendaji wengine wa mbinu ya SHEP Lazima 3 2.1 Dhana ya SHEP 2.2 Nguzo na hatua za SHEP Dhana ya SHEP ni moja kati ya njia za ugani zinazotumika katika kufikisha taarifa na maarifa ya kilimo kwa wakulima. Moja kati ya sifa kuu ni pamoja na kukifanya kilimo kiwe cha kibiashara kwa kuwezesha upatikanaji wa taarifa za masoko katika mnyororo wa thamani, na hili linasaidia sana kuondoa ukosefu wa taarifa muhimu za masoko kwa kuanzisha utaratibu wa shughuli mbalimbali zinazolenga kuwapa wakulima hamasa. Dhana hii ni shirikishi ambapo, wakulima wanashirikishwa kuzalisha kulingana na mahitaji ya soko. Hivyo, wakulima ni lazima kubadilishwa mtazamo wa fikra kutoka “kuzalisha na kuuza” na kwenda “kuzalisha kwa ajili ya kuuza”. Dhana hii inahusisha hatua mbalimbali za kuwawezesha wakulima kupata taarifa za soko ili aweze kupanga na kufanya maamuzi sahihi ya nini cha kulima kwa ajili ya soko husika kwa bei zilizokubalika na kwa muda muafaka. Kuna nguzo kuu mbili za SHEP nazo ni “kilimo kama biashara” na “kuwezesha na kuinua hamasa ya wakulima” ambazo zote hizi zinawasaidia wakulima kubadilika kutoka “kulima na kuuza” na kwenda “kulima kwa ajili ya kuuza”. Kutokana na changamoto za masoko ya mazao ya kilimo, dhana ya SHEP ni suluhisho la changamoto hizo na hata kwa mazao mengine yasiyo ya bustani endapo nguzo kuu mbili zitatumiwa ipasavyo na kwa kufuata hatua kuu nne za dhana yanSHEP. Dhana ya SHEP inatoa mfululizo wa mafunzo ya kuwajengea uwezo wakulima kwa namna ambavyo itawapatia motisha na kuwasaidia kubadili fikra na mitazamo. Mafunzo hayo hutolewa kwa kufuata utaratibu shirikishi na maalum unaofuata hatua nne (4) za dhana ya SHEP. SHEP inachukulia suala la kushirikisha wakulima malengo na mtazamo kama hatua muhimu kwao kwani ni eneo litakalowasaidia kupiga hatua kiuchumi kwa kufanya kilimo kama biashara katika mtiririko mzima wa masomo. Wakulima ni lazima washawishiwe na wakubali malengo na mtazamo ambao SHEP inajaribu kufikia. Hatua hii inahusu kuongeza kiwango cha uelewa wa wakulima katika maeneo yenye fursa za kilimo cha mazao ya bustani na mazao mengine ambapo, wakulima watapata nafasi ya kufanya maamuzi stahiki ya kubadili kilimo chao kiwe cha tija na cha kibiashara. Hatua hii pia, itasaidia kuonesha hali ya kilimo cha kibiashara na hali halisi ya fursa za masoko Ongezeko la ufahamu na ujuzi uliopatikana katika hatua ya pili litawafanya wakulima kubadili mfumo wa kilimo kutoka “kulima na kuuza” kwenda “kulima kwa ajili ya kuuza”. Hata hivyo, hatua hii inaenda sambamba na wakulima kuchagua mazao ya kulima, maandalizi ya kalenda za uzalishaji na mipango kazi yenye lengo la kimkakati ili kuhakikisha wanazalisha mazao kwa ajili ya kufikia mahitaji ya soko. 2.0 DHANA YA SHEP NA HATUA ZAKE MUHIMU 2.2.1 Hatua ya kwanza: Kushirikisha Wakulima Malengo 2.2.2 Hatua ya Pili: Kuongeza Uelewa wa Wakulima 2.2.3 Hatua ya Tatu: Wakulima Kufanya Maamuzi 4 Katika hatua hii, Wataalam wa kilimo watatoa mafunzo ya kitaalamu kwa wakulima ikiwa ni pamoja na mafunzo mashambani kulingana na zao husika. Hata hivyo, tathmini na ufuatiliaji ni lazima ifanyike ili kuhakikisha kuwa wakulima wanatumia maarifa watakayoyapata. 2.2.4 Hatua ya Nne: Wakulima kupata Ujuzi na Maarifa 5 3.1 Ngazi ya Serikali Kuu 3.1.1 Majukumu ya Kikosi Kazi cha Utekelezaji 3.2 Ngazi ya Sekretarieti za Mikoa 3.3 Ngazi ya Mamlaka za Serikali za Mitaa Dhana ya SHEP katika ngazi ya Serikali Kuu itatekelezwa kupitia Kikosi Kazi cha utekelezaji. Kikosi Kazi hicho kitajumuisha Wataalam kutoka Wizara ya Kilimo (Idara za Maendeleo ya Mazao, Sera, Mipango na Utafiti, Mafunzo ya Kilimo na Utafiti, Masoko ya Mazao na Usalama wa Chakula, Tume ya Maendeleo ya Ushirika, HORTI–Tengeru), Ofisi ya Rais TAMISEMI (Idara ya Tawala za Mikoa) na Sekta Binafsi. Ngazi ya Sekretarieti za Mikoa itajumuisha Wataalam wanaosimamia shughuli za kilimo katika kila mkoa. Majukumu ya Wataalam hawa ni pamoja na; Sekretarieti za Mikoa zitatoa usaidizi wa kitaalam na kiusimamizi kwa MSM katika utekelezaji wa dhana ya SHEP ambao utakuwa ukiratibiwa na OR–TAMISEMI na watakuwa wanafanya kazi kwa karibu zaidi na Kikosi kazi cha Utekelezaji ya Dhana ya SHEP (TF). Ngazi ya MSM itakuwa na jukumu la moja kwa moja la utekelezaji wa dhana ya SHEP. Katika ngazi hii, kutakuwa na timu ya Wataalam ya utekelezaji wa dhana, ambayo itajumuisha Mkuu wa Idara ya Kilimo, Mifugo na Uvuvi; Mkuu wa Sehemu ya Kilimo, Wataalam wa Ugani hususan katika mazao ya bustani, Wataalam wa Ushirika na Wataalam wa Umwagiliaji. Timu hii itakuwa chini ya Mkurugenzi Mtendaji wa MSM na kazi kubwa ya Wataalam hawa ni kuhakikisha malengo ya dhana ya SHEP yanatimia. Kusimamia, kufuatilia na kutathmini utekelezaji wa shughuli za dhana ya SHEP katika ngazi zote; Kutoa mafunzo kwa Timu za Uwezeshaji za mikoa na Wilaya kila inapohitajika; na Kuhamasisha na kujenga uelewa juu ya dhana ya SHEP katika maendeleo ya Sekta ya Kilimo kwa viongozi wa ngazi mbalimbali za Wizara ya Kilimo, na OR-TAMISEMI. Kusimamia timu ya utekelezaji wa dhana ya SHEP ya Wataalam wa MSM (DFTs) katika kuandaa mipango na Bajeti zitakazotekeleza dhana ya SHEP; Kufanya ufuatiliaji wa utekelezaji wa dhana ya SHEP; Kusaidia DFTs katika utayarishaji wa ripoti mbalimbali za utekelezaji wa dhana ya SHEP ikiwemo ripoti za mwezi, robo mwaka na mwaka; na Kusaidia DFTs katika kutoa mafunzo ya kilimo bora cha mazao ya bustani kwa vikundi vya wakulima wanaotekeleza dhana ya SHEP pale inapohitajika. Utekelezaji wa dhana ya SHEP nchini utajumuisha Serikali Kuu, Sekretarieti za Mikoa, Mamlaka za Serikali za Mitaa (MSM), na Sekta Binafsi. 3.0 MUUNDO WA UTEKELEZAJI DHANA YA SHEP 6 Aidha, majukumu mengine watakayokuwa nayo ni pamoja na:- Majukumu ya wakulima katika kutekeleza dhana ya SHEP ni kama yafuatayo: - Majukumu na uwajibikaji ya Sekta Binafsi ni kama ifuatavyo:- i. Kuhakikisha dhana ya SHEP inajumuishwa katika Mipango na Bajeti ya MSM; ii. Kutoa mafunzo ya kilimo bora cha mazao ya bustani kwa Wataalam wa kilimo wa Kata na Vijiji; iii. Kutoa mafunzo ya utunzaji wa kumbukumbu kwa vikundi vya wakulima; iv. Kuandaa na kuratibu hafla ya wadau katika ngazi ya Halmashauri v. Kufanya tathmini na ufuatiliaji mashambani; na vi. Kutayarisha ripoti za utekelezaji wa dhana ya SHEP zikiwemo za wiki, mwezi, robo na mwaka. Kuwawezesha wakulima kuelewa dhana ya SHEP; Kuwawezesha wakulima kufanya Utafiti wa Masoko; Kuwaunganisha wakulima na wadau wote katika mnyororo wa thamani; Kuwawezesha wakulima kufanya tathmini shirikishi; Kuwawezesha wakulima kufanya maamuzi ya kibiashara na ki-ujasiriamali kwa kuwa na mipango kazi; Kuimarisha uwezo na ujuzi wa wakulima kufanya uzalishaji wenye tija kwa kuzingatia mahitaji ya soko; Kuandaa taarifa za utekelezaji za wiki, mwezi, robo na mwaka na kuziwasilisha ngazi ya Halmashauri; Kuratibu ziara za mafunzo baina ya vikundi vya wakulima vilivyofanya vizuri katika kata na vijiji; na Kufanya ufuatiliaji na tathimini wa mfumo na dhana ya SHEP kwa wakulima. Kufanya maamuzi ya kuzalisha mazao ya bustani kibiashara; Kuwa na utayari wa kutoa ardhi na nguvu kazi kwa ajili ya uzalishaji wa majaribio; Kushiriki katika utafiti wa awali kwa kutoa taarifa sahihi; Kushiriki katika kufanya utafiti wa soko; Kushiriki katika hafla ya wadau iwapo atachaguliwa na wakulima wenzake; Kuchagua mazao kulingana na mahitaji ya soko na ushauri wa watalaam; Kuandaa kalenda za uzalishaji wa mazao; Kuzalisha mazao kwa kufuata kalenda za mazao zilizoandaliwa; Kutoa taarifa sahihi wakati wa kufanya tathmini ya utendaji wa kikundi na uchambuzi wa faida; Kueleza mafanikio na changamoto za utekelezaji wa dhana ya SHEP; na Kuwa tayari kushirikiana na kubadilishana uzoefu na wakulima wengine. Kubuni mpango wa mafunzo ya kutambulisha hatua nne za SHEP kwa walengwa wao; Kuratibu na kushauriana na Serikali Kuu na/ au MSM kuhusu jinsi ya kuanzisha dhana ya SHEP kwa walengwa wao; Kuendesha mafunzo juu ya dhana ya SHEP kulingana na miradi au mipango yao wenyewe; na Kufuatilia na kutathmini maendeleo na mafanikio ya walengwa wao na kutoa taarifa za utekelezaji kwa Serikali. 3.3.1 Majukumu ya Maafisa Ugani wa Kata na Vijiji 3.4 Majukumu ya Wakulima 3.5 Majukumu ya Sekta Binafsi 7 4.0 UTEKELEZAJI WA DHANA YA SHEP Utekelezaji wa dhana hii umejikita katika misingi mikuu miwili ambayo ni; kilimo kama biashara na mkulima kufanya maamuzi wenyewe. Katika utekelezaji wa misingi hiyo, dhana hii imejikita katika hatua nne za utekelezaji ambazo zimefafanuliwa kwa kina katika Kiambatisho Na. 1. Ni vema kutambua kuwa, watekelezaji wote wa dhana ya SHEP wanapaswa kuzingatia kufanya utafiti wa soko, kuandaa kalenda ya mazao kulingana na taarifa za soko, kuzalisha mazao kulingana na mahitaji ya soko na kuweka kumbukumbu ili kuongeza tija ya uzalishaji na kipato cha wakulima. Utekelezaji na usimamizi wa dhana ya SHEP katika ngazi ya mikoa hupitia hatua mbalimbali za msingi ambapo, utekelezaji huo huanza na MSM zenye vipaumbele vya uzalishaji wa mazao ya bustani na hatimae huenea hadi MSM nyingine. Uanzishwaji wa dhana hii katika ngazi ya mikoa hufuata hatua tatu (3) za msingi kama ifuatavyo; Kuwaelimisha viongozi na Wataalam katika Sekretarieti za Mikoa na MSM juu ya dhana ya SHEP na namna inavyofanya kazi; Kupata idhini ya kutekeleza dhana ya SHEP katika eneo husika; na Kuhamasiha MSM kuandaa na kuweka mipango kazi na bajeti za utekelezaji wa dhana ya SHEP katika maeneo yao. Warsha ya Utambulisho kwa Wataalam wa Sekretarieti za Mikoa na MSM Lengo la Warsha ya Utambulisho 4.1 Utekelezaji katika Ngazi ya Serikali Kuu na Sekretarieti za Mikoa 4.1.1 Uanzishaji na usimamizi wa Dhana ya SHEP Ngazi ya Mikoa Serikali Kuu pamoja na Sekretarieti za Mikoa wanawajibika kufanya yafuatayo:- Hatua ya Kwanza: Kusimamia utekelezaji wa dhana ya SHEP katika Mikoa kwa kushirikiana na Wizara ya Kilimo na OR-TAMISEMI kwa kuzingatia uwepo wa bajeti au kupitia wadau wa maendeleo katika utekelezaji wa miradi; Kuwezesha ushauri wa kitaalam kwa MSM kutekeleza dhana ya SHEP kama moja ya Mipango ya Maendeleo ya Kilimo ya MSM (DADPs). 8 Mpangilio wa uendeshaji wa Warsha ya Utambulisho Washiriki 1 2 Washiriki wa msingi wa Warsha ya Utambulisho ngazi ya mkoa ni pamoja na Mratibu wa SHEP kitaifa, Mwezeshaji wa SHEP kitaifa, Katibu Tawala Mkoa, Wataalamu wa Sekta ya Kilimo (Uchumi na Uzalishaji Mkoa), Wakurugenzi Watendaji wa MSM na Maafisa ugani wawezeshaji wa MSM (DFTs). Dhana ya SHEP; Kazi na Majukumu ya Wadau ya Timu ya Uwezeshaji ya Wilaya (DFTs) na Kikosi Kazi; Kazi na Majukumu ya Maafisa Ugani; na Kazi na Majukumu ya Vikundi vya Wakulima Mambo ya Kuzingatia Mwezeshaji anatakiwa kufundisha mada zifuatazo 9 Uandaaji na utoaji mafunzo kwa DFTs Uchaguzi wa Vikundi vya wakulima 1. WIZARA YA KILIMO Mafunzo haya hutolewa kwa DFTs kwa ajili ya kuwajengea uwezo wa kutoa mafunzo kwa Maafisa Ugani wa Kata na Vijiji na Vikundi vya Wakulima. Dhana ya SHEP inalenga kuwawezesha wakulima kulima kwa ajili ya kuuza. Ni muhimu kuchagua vikundi vinavyoendana na malengo na mtazamo wa SHEP ili kuwa chachu ya mabadiliko kwa vikundi na wakulima wengine. Vikundi hivi vinachaguliwa kwa kuzingatia vigezo vilivyowekwa na Kikosi Kazi. Lengo ni kuchochea matumizi ya dhana ya SHEP kuwa sehemu ya utekelezaji wa mbinu za ugani katika Sekta ya Kilimo kwa kuwafanya watendaji katika Serikali kufuatilia kwa ukaribu na kuwezesha MSM kutekeleza Mipango ya Maendeleo ya Sekta ya Kilimo kila mwaka. Shughuli zinazoweza kutekelezwa na wadau mbalimbali katika mnyororo wa thamani ili kuhakikisha ufuatiliaji na tathmini wa mipango ya kilimo kupitia dhana ya SHEP ni kama zilivyoainishwa hapo chini: Idara hii ina jukumu la kukuza dhana ya SHEP kupitia Mipango ya Maendeleo ya Sekta ya Kilimo ya MSM. Yafuatayo yanaweza kuleta tija kubwa yakifanyika:- Idara hii ina jukumu la kutoa ushauri wa kitaalam kwa MSM na Wakulima ili kutekeleza dhana hii. Yafuatayo yanaweza kufanyika katika Idara hii kuifanya dhana itekelezwe kwa mafanikio:- Kutoa miongozo ya kibajeti kupitia OR-TAMISEMI, kuhusu vipaumbele na mikakati ya Wizara kwa mwaka husika ili kujumuishwa katika mipango ya Sekta ya Kilimo ya MSM; Kutenga bajeti ya uratibu wa utekelezaji wa dhana ya SHEP; na Kupanga ziara za kutembelea maeneo ambayo dhana ya SHEP inatekelezwa kwa viongozi wa Wizara. Hatua ya Pili: Hatua ya tatu Lengo: Mambo ya kuzingatia katika utoaji wa mafunzo: Kuwawezesha DFTs kujua malengo, dhana na shughuli za SHEP kwa kina; na Kuwawezesha DFTs kuelewa wajibu na majukumu yao na ya Maafisa Ugani. Nguzo na hatua za dhana ya SHEP; na Wajibu na majukumu ya DFTs na maafisa ugani katika kusimamia dhana ya SHEP. 4.1.2 Kujenga uwezo wa kutumia Dhana ya SHEP (A) Idara ya Sera, Mipango na Utafiti (B) Idara ya Maendeleo ya Mazao 10 Kufanya utambuzi wa mbinu na namna mbalimbali zinazoweza kutumika na tasnia nyingine za Sekta ya Kilimo ili kutekeleza dhana ya SHEP; Kukusanya na kuhuisha orodha ya vikundi vya wakulima na vile vya wadau katika mnyororo wa thamani wa mazao ya kilimo na kuziwasilisha kwa wadau mbalimbali wakiwemo wakulima na MSM kupitia Mobile-Kilimo, vijarida na vyombo vya habari; Kuingiza ajenda ya SHEP katika matukio yote muhimu ya Sekta ya Kilimo kitaifa; na Kuhakikisha mfumo wa kuwatambua watekelezaji wa dhana ya SHEP kwa kuwapatia vyeti vya utambulisho unafanya kazi kwa Maafisa Ugani ngazi za Wilaya, Kata na Vijiji, wakulima na wadau. Kukusanya taarifa na ujuzi wa uzalishaji na masoko na kuusambaza kwa wadau mbalimbali wakiwemo Wakulima na MSM kupitia Mobile-Kilimo au njia nyingine rasmi; na Kutumia dhana ya SHEP katika mafunzo ya kilimo biashara yanayotolewa kwa wakulima. Kufanya tafiti ambazo zinamsaidia mkulima kuyafikia mahitaji ya soko kama utambuzi wa aina za mbegu zinazohitajika, Kuhakikisha Taasisi za Mafunzo ya Kilimo (ikiwemo HORTI-Tengeru) inatoa mafunzo kwa wanafunzi na maafisa ugani kwa kuzingatia mitaala mipya inayolenga dhana ya SHEP, na Kutoa mafunzo ya kitaalam kwa wakulima kwa kutembelea mashamba na maeneo yote ya uzalishaji kama itakavyoombwa na MSM. Kutoa maelekezo kuhusu mipango ya bajeti katika Sekta ya Kilimo ikiwemo utekelezaji wa SHEP kama shughuli ya kawaida ya ugani katika Mipango ya Maendeleo ya Wilaya ya Sekta ya Kilimo, Kuratibu mafunzo na matukio ya kupashana habari juu ya utekelezaji wa dhana ya SHEP katika ngazi za kitaifa na mikoa, Kufuatilia maendeleo ya utekelezaji wa dhana ya SHEP katika Mipango ya Maendeleo ya Sekta ya Kilimo katika MSM kwa kutumia mapato ya ndani, na Kukusanya matokeo chanya yatokanayo na mafanikio ya utekelezaji wa dhana ya SHEP na kuwashirikisha wadau. (C) Idara ya Masoko ya Mazao na Usalama wa Chakula (D) Idara ya Mafunzo ya Kilimo na Utafiti Idara hii kupitia Sehemu ya Masoko ya Mazao ya Kilimo inahusika na kuhamasisha matumizi ya dhana ya SHEP kwa wakulima nchini kupitia shughuli mbalimbali ikiwemo mafunzo ya Kilimo Biashara inayotoa kwa wakulima. Vilevile, kwa kutekeleza yafuatayo itasaidia kuendeleza dhana ya SHEP:- Idara ya Mafunzo ya Kilimo na Utafiti inahusika na kusambaza dhana ya SHEP katika maeneo yote ya nchi kupitia shughuli za mafunzo na utafiti. Shughuli zifuatazo zitafanyika na kuleta ufanisi katika utekelezaji wa dhana ya SHEP: Idara ya Tawala za Mikoa, Sehemu ya Uchumi na Uzalishaji inahusika na kutoa maelekezo na miongozo kwa Tawala za Mikoa na MSM katika kutekeleza dhana ya SHEP kwenye Mipango ya Maendeleo ya Sekta ya Kilimo ya Wilaya. Kimahsusi, yafuatayo hufanywa na Idara hii kuhakikisha dhana inafanikiwa kiutekelezaji: 2. OR-TAMISEMI 11 Kutoa takwimu za maendelo ya ushirika hususan katika AMCOs kama walengwa wakuu katika utekelezaji wa dhana, Kutoa miongozo na maelekezo juu ya taratibu za usajili kwa vikundi vya Wakulima kwa ajili ya kuboresha utendaji wao hasa wa kiuongozi, na Kutoa ushauri wa kitaalam kwa Sekretarieti za Mikoa na MSM juu ya mafunzo ya uongozi na namna ya kuiga na kuifuata dhana ya SHEP. Kuitambulisha dhana ya SHEP (hasa namna ya kutafiti masoko) kwa wanachama walio kwenye vikundi na mmoja mmoja, Kutoa taarifa sahihi juu ya mwenendo wa bei na wadau wote katika mnyororo wa thamani kwa Serikali kwa ajili ya maendeleo ya dhana ya SHEP, na Kukutanisha wadau wote katika mnyororo wa thamani wa Sekta ya Kilimo. Tume ya Maendeleo ya Ushirika ina jukumu la kuvijengea uwezo Vikundi vya Wakulima ambavyo vinatekeleza dhana ya SHEP katika uzalishaji wao. Kimahsusi, yafuatayo hufanywa na Tume hii katika utekelezaji wa dhana ya SHEP, Utekelezaji wa dhana ya SHEP katika ngazi ya MSM au mipango yoyote inayotumia dhana ya SHEP inapitia hatua kuu nne. Mchoro Na. 01 unaonesha muhtasari wa hatua hizo ambazo MSM zinatakiwa kuzipitia ili kutekeleza dhana ya SHEP. Msisitizo unawekwa kwenye utafiti wa soko, utayarishaji wa kalenda ya mazao kulingana na utafiti wa soko na utekelezaji wake. Sekta Binafsi inasaidia wakulima kutokana na utaalam na uzoefu wao katika kilimo. Katika utekelezaji wa dhana ya SHEP, Sekta Binafsi ina jukumu la kufanya yafuatayo: 3. TUME YA MAENDELEO YA USHIRIKA 4. SEKTA BINAFSI 4.2 Utekelezaji wa Dhana ya SHEP (Hatua 4) kwa Ngazi ya MSM na mipango inayotumia mbinu ya SHEP Warsha ya Utambulisho Utafiti wa Awali Wawakilishi wa Vikundi/Afisa Ugani kwa pamoja Utafiti wa Soko Kuunganishwa na Wadau Uchaguzi wa mazao/Kalenda ya uzalishaji Mafunzo (mf. shamba la mfano, mafunzo ya lishe na jinsia) Tathmini ya mwisho Hatua 1: Kuwa na malengo ya pamoja Hatua 2: Kuongeza uelewa kwa wakulima (Wakulima kutambua soko) Hatua 3: Wakulima kufanya maamuzi Hatua 4: Wakulima kujiandaa kukabiliana na changamoto Mchoro Na : 01 HATUA ZA UTEKELEZAJI WA DHANA YA SHEP 12 Utaratibu wa kutekeleza shughuli za dhana ya SHEP unafuata hatua zilizoainishwa hapa chini. Ni hatua ya kwanza kwa MSM kutekeleza dhana ya SHEP ili kuwa na malengo ya pamoja kati ya wakulima na malengo ya dhana ya SHEP. 4.2.1 Warsha ya Utambulisho Hatua ya SHEP Hatua 1: Kuwa na malengo ya pamoja Malengo Kuwa na uelewa wa pamoja wa dhana na malengo ya SHEP ambayo husaidia wakulima waweze kujitegemea katika mtazamo wa kilimo biashara. (Anzia sokoni malizia shambani kwa kipato zaidi) Mahitaji ya Warsha Tazama Kiambatisho Na. 01 (Dhana ya SHEP) Utaratibu wa Uendeshaji Warsha Mkutano ufanyike mahali ambapo wakulima wanaweza kufika kwa urahisi kama shuleni, ukumbi wa mikutano wa Kijiji au nyumbani kwa kiongozi Wawezeshaji wakiwemo DFT waelezee dhana ya SHEP ili pande zote mbili waweze kuwa na maono yanayofanana Maelezo zaidi yatolewe kwa kuhusisha muda wa shughuli za utekelezaji wa dhana ya SHEP, kazi na majukumu ya wakulima katika ukamilishaji wa mafunzo ya dhana ya SHEP, Wawezeshaji wasisitize usawa wa jinsia katika kutoa maamuzi ya pamoja katika kipindi chote cha utekelezaji wa dhana ya SHEP. Muwezeshaji asaidie wakulima kufanya majadiliano ya umuhimu wa usawa wa kijinsia na uwezeshaji wanawake. Dondoo za Dhana ya SHEP Wahusika: Wawezeshaji MSM, Viongozi na Wawakilishi wa vikundi vya wakulima. Dondoo: Warsha ni muhimu katika kupanga maono na malengo ya pamoja ya dhana ya SHEP Wakulima waelewe na kukubali kuwa maono yatafanikiwa pale watakapoweka juhudi zao binafsi kuelekea kilimo biashara Wakulima waelewe dhana ya SHEP haitoi msaada wa kifedha wala miundombinu ila inatoa mbinu za kitaalam. Gharama za uendeshaji ni pamoja na usafiri, posho za washiriki, chakula na shajala Mambo ya Kuzingatia Warsha ya Utambulisho inafanyika mara moja mwanzoni mwa utekelezaji wa dhana ya SHEP Ni vema warsha hii ikashirikisha vikundi vilivyochaguliwa kutekeleza dhana ya SHEP Wakulima watakaoshiriki wawe angalau watatu ambapo kati yao kiongozi mmoja na wawakilishi wawili (Me=1: Ke=1). Matokeo Wakulima kuelewa na kukubali utaratibu mzima wa kutekeleza dhana ya SHEP Wakulima wataweza kueleza malengo watakayoyafikia baada ya kukamilisha hatua zote za kutekeleza dhana ya SHEP Wakulima kuelewa na kuelezea kazi, majukumu na haki walizokuwa nazo kama watekelezaji wa dhana ya SHEP Wakulima kubadili mtazamo kutoka “Kulima na Kuuza” na kuwa “Kulima kwa ajili ya Kuuza” Kuwa na uwiano sawa wa ushiriki kati ya wanaume na wanawake 13 4.2.2 Utafiti wa Awali Utafiti wa awali huongeza uelewa zaidi kwenye vikundi vya wakulima, umuhimu na namna ya kutunza kumbukumbu za shughuli za shamba na kuwafanya kutambua hali halisi ya gharama za uzalishaji, faida na hasara. 14 Hatua ya SHEP Hatua 2: Kuongeza uelewa kwa wakulima Malengo Kuwezesha wakulima kutunza taarifa za uzalishaji, masoko na mapato ili aweze kutambua h ali halisi y a kulima k ibiashara ili kupata f aida k wa k utumia kumbukumbu za mapato ya kilimo. Kukusanya taarifa za msingi juu ya maisha ya wakulima, ushiriki wa kijinsia na usimamizi wa vikundi kwa ajili ya tathmini rahisi ya mafanikio ya mradi. Mahitaji (Viambatisho) Kiambatisho 02-01: Utafiti wa awali Kiambatisho 02-02: Muundo wa kumbukumbu ya mapato (FIR) Kiambatisho 02-03: Kubadilisha vipimo vya mazao Utaratibu wa Uendeshaji Wawezeshaji wa Ngazi ya MSM watatumia kabrasha la Utafiti wa awali (Kiambatisho 02-01: Utafiti wa awali) kuwafundisha Maafisa Ugani wa Kata na Vijiji. Maafisa Ugani Kata na Vijiji watatumia kabrasha la kumbukumbu za Kipato cha mkulima (Kiambatisho 02-02: FIR) kufundisha wakulima namna ya kuweka kumbukumbu za mapato yatokanayo na kilimo. Dondoo za Utekelezaji Wahusika: Wawezeshaji ngazi ya MSM, Maafisa Ugani Ngazi ya Kata na Vijiji, Viongozi na Wawakilishi wa vikundi vya wakulima. Dondoo: Utafiti unapaswa kuwa kwa faida ya wakulima zaidi kuliko ya wawezeshaji Utafiti unatakiwa kuwa shirikishi ili wakulima waliolengwa wawe watekelezaji wakuu Maafisa Ugani wawasaidie wakulima kukokotoa kiasi cha mavuno, gharama za uzalishaji na faida ambavyo ni muhimu katika utunzaji wa Shamba. Gharama za uendeshaji ni pamoja na usafiri, posho za washiriki, chakula na shajala Mambo ya Kuzingatia Kumbukumbu za mapato ya shamba (Farm Income Record: FIR) ni muhimu kufanywa k abla y a shughuli za u zalishaji ili kupima m atokeo y a uzalishaji uliopita. Ni muhimu maafisa ugani wakutane na wakulima ili kuwasaidia namna ya kujaza FIR wakulima wote na wakulima waweze kusaidiana kujaza fomu hizo. Ikiwa ni lazima pima shamba kwa kutumia hatua za miguu ili kupata makadirio ya ukubwa wa shamba. Kwa mazao ya bustani vipimo tofauti hutumika kulingana na mazao kwa mfano: magunia, ndoo na kreti. Hivyo, tafuta uzito halisi kwa kilogram kwa kila kipimo. Matokeo Wakulima kutambua umuhimu wa utafiti wa awali ambao utawezesha kujua hali halisi waliyonayo kabla na baada ya kutekeleza dhana ya SHEP Wakulima kushiriki kikamilifu ili waweze kuwa watekelezaji wakuu Wakulima kuwa na uwezo wa kukokotoa kiasi cha mavuno, gharama na faida za uzalishaji. 15 4.2.3 Utafiti wa Soko Utafiti wa Soko ni hatua muhimu katika utekelezaji na ndio inayobeba dhana nzima ya SHEP yenye kauli mbiu ya “anzia sokoni malizia Shambani kwa Kipato zaidi”. Hatua hii inawawezesha wakulima kujua mahitaji ya soko ikiwa ni pamoja na kiasi, wakati, bei na ubora. 16 Hatua ya SHEP Hatua 2: Kuongezeka kwa uelewa wa wakulima (wakulima kutambua soko) Malengo Kuwawezesha wakulima kupata uzoefu wa namna masoko yanavyofanya kazi na kinachohitajika kutoka kwa wazalishaji Kutambua nyakati za msimu zenye bei za juu na zenye bei za chini, misimu yenye kuhitaji mazao mengi kwa wakati mmoja au kidogo kidogo na kuwa msingi wa kuandaa mpango kazi na kalenda ya uzalishaji) Wakulima kujenga mahusiano ya kudumu na wafanyabiasha wakiwemo wauzaji wa jumla na rejareja, madalali na viongozi wa soko. Mahitaji (Viambatishi) Kiambatisho 03-01_Utafiti_wa_Soko Kiambatisho 03-02 Mpango wa utafiti wa soko Kiambatisho 03-03 Muundo wa utafiti wa soko Kiambatisho 03-04 Zoezi la kikundi la utafiti wa soko Utaratibu wa utekelezaji Maafisa Ugani wa Halmashauri watatumia kabrasha la Utafiti wa Masoko Shirikishi (Kiambatisho 03-01) kwa ajili ya mafunzo kwa Maafisa Ugani wa Kata na Vijiji Maafisa Ugani wa Kata na Vijiji watatumia kabrasha la Mpango wa Utafiti wa Soko (Kiambatisho 03-02) kuwezesha wakulima kuandaa mpango wa utafiti wa masoko Wakulima watatumia kabrasha la TANSHEP fomati ya Utafiti wa Soko (Kiambatisho 03-03) kujaza taarifa zitakazokusanywa wakati wa utafiti wa soko. Maafisa Ugani na wakulima pia wanaweza kufanya zoezi la utafiti wa soko kabla ya kwenda sokoni (Kiambatisho 03-04) Dondoo Wahusika: Wawezeshaji ngazi ya Halmashauri, Maafisa Ugani Ngazi ya Kata na Vijiji, Viongozi na Wawakilishi wa vikundi vya wakulima, Wafanyabiashara na viongozi wa masoko. Dondoo: Wakulima watafanya mahojiano na wafanyabiashara wakiwa na fomu ya kujaza mkononi yale yote atakayojibiwa kutokana na maswali yao wakulima watakusanya taarifa zote muhimu wakati wa utafiti zikiwemo nyakati za bei ya juu nay a chini, washindani, namna ya malipo, ubora unaotakiwa, kiasi/ wingi n.k wakulima wahakikishe wanaanzisha mahusiano na wafanyabiashara na/ au madalali na viongozi wa soko kwa kubadilishana mawasiliano yatakayowafanya waendelee kupata taarifa za soko kwa muda mrefu Mambo ya kuzingatia Utafiti wa Soko unatakiwa kufanywa na Wakulima wenyewe na siyo maafisa ugani Utafiti wa Soko unalenga kukusanya taarifa mbalimbali na siyo bei peke yake Wakati wa kufanya utafiti wa soko, Wakulima wanapaswa kutiwa moyo kuanzisha mahusiano ya kibiashara na wadau wanaokutana nao sokoni Wakulima wanapaswa kuelewa kuwa utafiti wa soko si suala la mara moja bali liwe endelevu. Matokeo Wakulima kujua namna ya kudodosa taarifa za soko na dodoso kujazwa taarifa zote muhimu kikamilifu wakulima kuwa namahusiano endelevu na wafanyabiashara 17 4.2.4 Hafla ya Kuunganisha Wadau Utafiti wa soko hufuatiwa na hafla ya kunganisha wadau ambayo ni moja ya shughuli za msingi katika dhana ya SHEP. Lengo la hafla hii ni kuimarisha ushirikiano wa kibiashara kati ya wakulima na wadau mbalimbali katika mnyororo wa thamani wa mazao husika. Hafla hii hufanywa kwa kuwakutanisha wakulima na wadau mbalimbali katika mnyororo wa thamani wa mazao husika wakiwemo wauza pembejeo, taasisi za fedha, wasafirishaji wa mazao, watoa huduma za ugani, taasisi za utafiti, wasindikaji na wengine wote wanaohusika. Kazi hii hufanyika sambamba kama shughuli ya kawaida ya ugani. Timu ya uwezeshaji ya wilaya au maafisa ugani hutambulisha wakulima kwa wadau mbalimbali au kinyume chake kwa ajili ya kuanzisha mahusianio ya kibiashara, mfano ni pamoja na kuanzisha mashamba darasa ya mafunzo kwa kutumia pembejeo, kilimo cha mkataba na wanunuzi, na namna ya kupata mikofo ya kifedha toka taasisi za kibenki / kifedha. 18 Hatua ya SHEP Hatua 2: Kuongeza uelewa kwa wakulima Malengo Kuwaonyesha wakulima fursa za biashara katika uzalishaji wa mazao ya bustani Kupata fursa ya kushirikiana na wadau mbalimbali kwa ajili ya kutatua changamoto za uzalishaji na masoko Inasaidia wakulima kujenga miunganiko ya kibiashara na wadau wote katika mnyororo wa thamani wa mazao ya bustani Wakulima kufahamu bidhaa na huduma zitolewazo na wadau Wakulima kujifunza mambo kadhaa kupitia majadiliano Mahitaji (Viambatishi) Kiambatisho Na. 04 Kuunganisha wadau Orodha ya Vikundi vya Wakulima Orodha ya Wadau Utaratibu wa utekelezaji Wawezeshaji ngazi ya Halmashauri na wale wa Kata na Vijiji watakusanya taarifa za wadau wote (mfano; watoa huduma za fedha, wauzaji pembejeo, wanunuzi wa mazao, wamiliki wa mahoteli na migahawa, Taasisi za Utafiti n.k) na kuandaa orodha yenye taarifa za wadau. Kama yalivyo majukumu ya ugani, Maafisa Ugani watawasaidia wakulima kuwa na mtandao na wadau muhimu kwa kutumia orodha ya wadau. Kama bajeti itaruhusu, Wawezeshaji ngazi ya Wilaya wataandaa fomu. Kabla ya hafla, Wawezeshaji ngazi ya Wilaya watatumia kabrasha la Hafla ya Wadau (Kiambatisho Na. 04) kwa ajili ya mafunzo kwa Maafisa Ugani. Wakati wa hafla, sambaza orodha ya vikundi vya wakulima kwa wadau, na orodha ya wadau kwa wakulima, ili waweze kufahamiana. Baada ya kuendesha hafla ya kuunganisha wadau, timu ya uwezeshaji ya Wilaya na maafisa ugani hufanya ufuatiliaji kuthibitisha kama mashirikiano yanaendelea kadri ya majadiliano na makubaliano yaliyowekwa na wadau hao Dondoo Wahusika: Wawezeshaji ngazi ya Halmashauri, Maafisa Ugani Ngazi ya Kata na Vijiji, Viongozi na Wawakilishi wa vikundi vya wakulima, Wadau wote kwenye mnyororo wa thamani wa mazao husika. Dondoo: Waandaaji wahakikishe wana idadi ndogo ya washiriki, wale tu ambao ni muhimu, kurahisisha mawasiliano Maafisa ugani wawasaidie wakulima kuwa na mahojiano yenye tija Gharama za uendeshaji ni pamoja na usafiri, posho za washiriki, chakula na shajala Mambo ya kuzingatia Wakulima kujitambulisha na kujinadi kupitia shughuli za kilimo ili kuwavutia wadau wanaohusika na mazao wanayoyalima. Wakulima ni muhimu waende na mazao wanayozalisha ili kuonyesha kwa vitendo yale watakayojinadi nayo na kuwapa imani wadau watakaokuwa tayari kufanya nao kazi, Wadau kujitambulisha na kujinadi kupitia shughuli wanazozifanya katika mnyororo wa thamani wa mazao husika ili wakulima waweze kuchagua mdau watakaefanya nae majadiliano na kuanzisha/ kukuza ushirikiano, Wakulima waonane na wadau wale tu wanaowahitaji, si lazima kuonana na kila mdau, na Wakulima wanatakiwa kurekodi mambo yote wanayojadili na wadau ikiwemo mawasiliano ili kuendeleza mahusiano. Matokeo Wakulima kufahamu fursa za kibiashara zilizopo kutoka kwa wadau Wakulima kuwa na miunganiko ya kibiashara na wadau mbalimbali. 19 Tukio la Kikao cha pamoja cha hafla ya kuunganisha wadau 4.2.5 Mpango kazi 4.2.5.1 Uchaguzi wa mazao Baada ya wakulima kutambua fursa za kibiashara katika hatua ya pili, wakulima watafuata hatua ya tatu ambayo watafanya maamuzi muhimu katika biashara ya mazao ya kilimo. Maamuzi hayo ni pamoja na kupanga mazao yatakayozalishwa, wakati, kiasi na ubora wa mazao yanayohitajika. Jukumu la wawezeshaji wa Dhana ya SHEP siyo kufanya maamuzi kwa niaba ya wakulima bali ni kuwasaidia wakulima kufanya maamuzi sahihi kwa kuwapa miongozo na utaalam katika kilimo. Uchaguzi wa mazao ni hatua nyingine muhimu katika dhana ya SHEP. Hatua hii huhusisha uchaguzi wa mazao kwa ajili ya uzalishaji kwa kuzingatia mambo ya msingi yaliyofanyika awali yakiwemo utafiti wa awali, utafiti wa soko na hafla ya wadau. 20 Hatua ya SHEP Hatua 3: Wakulima kufanya maamuzi Malengo Wakulima kufanya uchaguzi wa mazao kufuatia matokeo ya tathmini ya faida, utafiti wa masoko, na hafla ya kuunganisha wadau kwa umoja wao ili waweze kuainisha mazao yanayotakiwa sokoni kuelekea kwenye uzalishaji. Mahitaji Kiambatisho Na. 05: Mpango wa uzalishaji Utaratibu w a utekelezaji Maafisa ugani wataandaa mkutano n a kuwaalika wakulima wote (na ikiwezekana) na wenza wao Maafisa ugani watawaomba wakulima wajadili matokeo ya tafiti za soko na wajaze taarifa za mazao yanayoonekana yatafanya vizuri kwenye mazao lengwa ‘target crop selection sheet’ Maafisa ugani hushirikiana na wakulima kufanya tahmini ya kujua faida baada ya kupata taarifa za utafiti wa masoko. Wakulima waombwe kujadili faida na hasara za mazao walioyachagua kama mazao pendekezwa. Kila mkulima atapiga kura kuchagua mazao anayopendekeza kwa kuandika machaguo yake kwa m fuatano na zao litakalopata alama nyingi ndilo litakalochaguliwa kuzalishwa. Maafisa Ugani wasaidie wakulima kuwasiliana na wadau ikiwa kuna makubaliano yoyote kupitia mkutano wa wadau (Mf. Wasambazaji pembejeo, utoaji mafunzo, upatikanaji wa mikopo n.k) Dondoo Wahusika: Wawezeshaji ngazi ya Halmashauri, Maafisa Ugani Ngazi ya Kata na Vijiji, Viongozi na Wawakilishi wa vikundi vya wakulima. Dondoo: Ni muhimu kushirikisha wenza katika kufanya maamuzi kwani kilimo biashara kinategemea maamuzi ya wote wawili Upigaji wa kura katika ucaguzi wa mazao ni muhimu ukashabihiana na ushauri wa kitaalam Gharama za Uendeshaji ni p amoja na usafiri, posho za w ashiriki, chakula n a shajala. Mambo ya kuzingatia Wakulima wajadili fursa za uzalishaji na watoe maamuzi kuhusu uchaguzi wa mazao kwa kuzingatia shughuli zilizotangulia hasa Utafiti wa Soko Afisa Ugani atoe ushauri wa kitaalamu wenye manufaa hasa katika eneo la mahusianisho ya kiikolojia na m azao p endekezwa ili wakulima waweze kufanya maamuzi sahihi. Wakulima wanapaswa kuleta fomu za utafiti wa soko na hafla ya w adau waliokubaliana nao Matokeo Uchaguzi wa mazao kufanyika kwa kufuata taarifa za awali, masoko na ushauri wa kitaalam na kwa kushirikisha wenza. 21 4.2.5.2 Uandaaji wa kalenda ya Uzalishaji Wakulima hupanga mpango wa uzalishaji pamoja na ule wa masoko wakizingatia mazao waliyoyachagua hapo awali. Mipango hii inajumuisha shughuli za pamoja za uzalishaji na masoko na zile za kikundi ambazo kwa ujumla hupelekea kuwa na kilimo biashara. Hatua ya SHEP Hatua 3: Wakulima kufanya maamuzi Malengo Kalenda ya uzalishaji huwawezesha wakulima kupanga shughuli zao za wakati ujao kama kikundi katika uzalishaji na masoko ya mazao waliyoyachagua. Mahitaji (Viambatisho) Kiambatisho Na. 05: Mpango wa uzalishaji Utaratibu wa utekelezaji Wakulima huanza kwa kuchagua mabadiliko wanayotaka kuyafikia katika uzalishaji na masoko kama vile aina (varieties), ubora, kiasi, muda wa kuvuna, wanunuzi n.k Baada ya k uchagua, wakulima hutengeneza kalenda y a uzalishaji wakiainisha shughuli za kutekeleza katika kipindi cha msimu mzima wa uzalishaji. Wahusika Wawezeshaji ngazi ya Halmashauri, Maafisa Ugani Ngazi ya Kata na Vijiji, Viongozi na Wawakilishi wa vikundi vya wakulima. Gharama za Uendeshaji ni pamoja na usafiri, posho za washiriki, chakula na shajala Mambo ya kuzingatia Afisa Ugani ahakikishe mipango inakuwa na uhalisia na inayotekelezeka Mpango kazi uhusishe pia shughuli zile zote zinazoweza kuongeza kipato katika vikundi vyao. Matokeo Kalenda ya uzalishaji kutengenezwa ikionyesha mtiririko mzima wa matukio ya uzalishaji na masoko. 22 Kalenda ya Mazao / Mpango wa uzalishaji Tathmini ya Faida 4.2.6 Mafunzo kwa Vikundi Vya Wakulima Wakulima kupata ujuzi na maarifa ni hatua ya mwisho katika utekelezaji wa Dhana ya SHEP ambapo wakulima hupata ujuzi na maarifa kulingana na mahitaji ya mazao yanayohitajika sokoni. Katika hatua hii, mkulima huwa na utayari wa kupata ujuzi mpya wa kuzalisha mazao ili kutumia fursa za masoko. Hatua ya SHEP Hatua 4: Wakulima kujiandaa kukabiliana na changamoto Malengo Kutoa ujuzi na maarifa muhimu ya uzalishaji kwa vitendo kwa zao lililochaguliwa na mkulima katika kipindi cha msimu ya mahitaji ya juu kadri ya kalenda ya uzalishaji mazao. Utaratibu wa utekelezaji Afisa Ugani lazima awe na ujuzi na maarifa muhimu ya kufundishia wakulima. Ikihitajika wawezeshaji waandae mafunzo ya maafisa ugani kabla ya kufundisha wakulima. Afisa Ugani aandae mafunzo ambayo yatajumuisha m azaezi kwa vitendo (Demostrations) kwa kila mada kwa kutumia zana bora za kufundishia. Mada zinazofundishwa ziendane na mahitaji ya uzalishaji wa zao lililochaguliwa na kulingana na mahitaji ya mkulima Mada zinazofundishwa ziwe katika makundi matatu (1) Mafunzo ya Jumla ya uzalishaji w a mazao y a bustani n a mbinu bora za u vunaji ( 2) m afunzo y a uzalishaji w a zao m aalum ( 3) m aarifa y a menejimenti kama u tunzaji wa kumbukumbu, mahesabu na gharama za uzalishaji mazao. Mambo ya kuzingatia Mafunzo lazima yazingatie mahitaji ya mkulima. Muda mwingi utumike katika sehemu ambazo mkulima anahitaji uelewa zaidi na utumike muda mfupi katika maeneo ambayo mkulima tayari ana ujuzi Mafunzo yafanyike kwa kutumia mbinu na vifaa rahisi kueleweka kama Bango Mgeuzo (flip chat) na vipeperushi. Iwapo familia inajihusisha n a uzalishaji w a mazao ya b ustani, mke au m ume aalikwe katika mafunzo. 23 Pia ni vizuri kuweka ziara ya kubadilishana uzoefu kati ya wakulima. Kwa vile changamoto nyingi za uzalishaji hutokea shambani, ni vyema kuuliza maswali moja kwa moja na kutafuta suluhu na wakulima wenzao. Ziara hiyo pia itawasaidia wakulima wanaozuru kuongeza hamasa kwa kuangalia mafanikio ya wakulima wenzao. Mafunzo kwa maafisa ugani juu ya magonjwa na wadudu Mafunzo kwa wakulima namna ya kutengeneza matuta 4.2.7 Kufanya tathmini ya mwisho Baada ya kufanya shughuli / hatua mbalimbali za utekelezaji wa dhana ya SHEP, timu ya uwezeshaji ya wilaya na maafisa ugani huwawezesha vikundi vya wakulima kufanya tathmini ya mwisho ili kujua matokeo ya mipango kazi yao pamoja na utekelezaji wa dhana ya SHEP, na tathmini hii kufanyika kwa njia mbili zifuatazo: Wakulima hufanya tathmini halisi ya faida kwa kuzingatia gharama halisi za uzalishaji, wingi wa mavuno, na bei halisi za mauzo sokoni. Kwa kulinganisha matokeo sahihi ya tathmini ya faida iliyopatikana kwenye mpango kazi, wataweza kubainisha mambo yafuatayo; Wakulima watarajiwa kuboresha pia taarifa na kumbukumba zao za mapato ya shamba na uchunguzi wa awali ili kufanya tathimini ya utekelezaji wa shughuli za shamba kwa msimu na mwaka mzima wakijumuisha mipango kazi na uzalishaji wa mazao mengine. Wakulima hupaswa kufanya ulinganifu wa; i). Mazao mbalimbali walizalisha kwa kuona mazao yenye uzalishaji bora na tija ya kutosha kwani kilimo ni biashara; ii). Kwa kuzingatia kumbukumbu za shamba na takwimu za tathimini za awali ili ili kutambua / kubaini ongezeko la mapato / faida au kupunguza kwa mapato / hasara za shamba. Kumbukumbu za mapato ya shamba zinapaswa kuboreshwa kila mwaka. Hii inapaswwa kuwa miendendo ya wakulima ya kuwawezesha wakulima kufanya maamuzi sahihi ya kuchagua aina ya mazao ya kuzalisha na kukifanya kilimo kuwa biashara. Utofauti wa mpango kazi uliotekelezwa na ule uliopangwa Matokeo ya mambo waliyojifunza na changamoto zilizojitokeza kwa ajili ya kupanga shughuli za kilimo zijazo. i. Kufanya mapitio ya tathmini ya faida ii. Kuboresha kumbukumbu za Mapato ya Shamba 24 Inapotokea muda kuwa hautoshi, taarifa za Mapato ya shamba hutumika pia kufanya tathimini ya mwisho ambayo hufanyika kwa njia zifuatazo. Yafuatayo ni mafunzo yaliyopatikana kutoka mradi wa TANSHEP, ikiwa ni pamoja na maarifa ya kuifanya SHEP na shughuli zake kuwa za vitendo na zenye ufanisi: Hatua ya SHEP Hatua 4: Wakulima kujiandaa kukabiliana na changamoto Malengo Hatua hii ni kwa ajili ya kuthibitisha mapato ya mkulima, iwapo mkulima amepata faida kadri ya utafiti wa soko na mpango kazi; au mkulima amepata ujuzi sahihi wa shughuli za shamba na uzalishaji kulingana na kalenda ya mazao. Hii huwa ni fursa ya kufanya maamuzi sahihi kwa ajili ya msimu unaofuata iwapo mkulima anaweza kubadili zao la kulima au kubadili msimu pia. Mahitaji (Viambatishi) Kiambatisho Na. 02-01: Utafiti wa awali Kiambatisho Na. 02-02: Muundo wa kumbukumbu ya mapato (FIR) Utaratibu wa utekelezaji Maafisa ugani wawasaidie wakulima kujaza fomu ya utafiti wa mwisho, ambayo kimsingi inafanana na ile ya utafiti wa awali, isipokuwa hii inajazwa kutokana nautekelezaji, Taarifa zisizo za uzalishaji na masoko pia ziangaliwe ili kujua hatua iliyofikiwa baada ya utekelezaji, mfano, ushiriki wa jinsia, Maafisa ugani wawasaidie wakulima kurejea m atokeo ya utafiti wa awali na kulinganisha na yale ya utafiti wa mwisho, Wakulima watoe ushuhuda kama wamepiga hatua au la, na Maafisa ugani watoe ushauri pale inapohitajika, mfano changamoto au mafanikio yaliyojitokeza. Mambo ya kuzingatia Utafiti wa mwisho uendane na mipango kazi ya u tekelezaji wa shughuli zao wenyewe. Matokeo Wakulima kutambua mafanikio na mapungufu yao, na Wakulima kupanga mipango kazi yao ambayo wataanza kuitekeleza kwa kutumia mbinu zao wenyewe chini ya usimamizi mdogo wa wataalam. 4.2.8 Mafunzo Yaliyopatikana kupitia Mradi wa TANSHEP Kanuni ya SHEP ni kwamba wakulima wazalishe mazao kulingana na mahitaji ya soko. Kanuni hii inaangazia moja kwa moja shughuli za msingi tatu (3) ambazo ni mafunzo ya utangulizi wa SHEP, utafiti wa soko na utekelezaji wa Mpango Kazi. Shughuli hizi zinaweza kutekelezwa kwa gharama ndogo, hasa kwa wakulima wenye uwezo mkubwa, ambao wanaweza i) kufanya utafiti wa soko mara kwa mara na ii) kurekebisha mifumo na mbinu za uzalishaji kwa kutumia rasilimali zao. Kwa hivyo, ikiwa Mamlaka ya Serikali za Mitaa au watendaji wengine wataweka kipaumbele kwa wakulima lengwa kwa matumizi ya dhana ya SHEP, wanaweza kujikita kuwafahamisha wakulima juu ya lengo la SHEP.(anzia sokoni malizia shambani kwa kipato zaidi) na kutoa mwongozo wa jinsi ya kufanya utafiti wa soko. Hii ina maana kwamba wanaweza kutumia mbinu ya SHEP kwa gharama ndogo kama sehemu ya huduma za ugani za kawaida, ambapo maafisa ugani huanzisha/hutambulisha misingi ya SHEP bila kuwa na mafunzo rasmi au warsha. I. SHEP inaweza kutekelezwa kwa gharama ndogo au katika huduma za kawaida za ugani 25 Mamlaka ya Serikali za Mitaa au watendaji wengine wanaweza kufikiria kuunganisha mbinu ya SHEP na huduma nyingine za serikali/Mradi wa Washirika wa Maendeleo ili kufanya utendaji kuwa na ubora na ufanisi zaidi. Mfano mzuri ni mchanganyiko wa SHEP na mikopo isiyo na dhamana wala riba inayotolewa na Halmashauri (mikopo ya wanawake, vijana na walemavu). Mkopo huo unasaidia wakulima kuandaa miundombinu na nyenzo muhimu, kama vile kitalu nyumba, pampu za maji na mbegu, ili kuboresha mifumo ya uzalishaji kulingana na mahitaji ya soko. Matumizi ya dhana ya SHEP, kwa upande mwingine, husaidia wakopaji wa mkopo kurejesha pesa kwa njia inayofaa, kwani inaweza kuongeza uwezo wao wa masoko/uuzaji. Kwa hivyo, kuna Halmashauri nyingi zilizotoa Kuna masomo mahususi waliyojifunza kwa kila shughuli ya SHEP. Jedwali lifuatalo linatoa muhtasari wa masomo ambao unaweza kutumiwa na wasomaji. Mfano mwingine ni mgawanyo wa majukumu kati ya watendaji. Halmashauri iliwawezesha wakulima kufanya utafiti wa soko, wakati Washirika wa Maendeleo/ Asasi Zisizo za Kiserikali zilisaidia uzalishaji kwa kuzingatia utafiti wa soko. Uzoefu wa TANSHEP unaonyesha kuwa uwezeshwaji wa pembejeo unaotolewa na Halmashauri kwa wakulima si wa uhakika kutokana na ufinyu wa bajeti. Hii ina maana kwamba Halmashauri zijikite katika kuwezesha utafiti wa soko na uunganishwaji wa wakulima na wadau wa kilimo ambao hauna msimu na hivyo unaweza kufanywa wakati wowote. II. SHEP inaweza kuunganishwa na huduma zingine za Serikali/ Miradi ya Washirika wa Maendeleo III. Uzoefu uliopatikana katika utekelezaji wa dhana ya SHEP kupitia mradi wa TANSHEP mikopo kwa wanawake, vijana na walemavu kwa vikundi vya wakulima na kutumia mbinu ya SHEP Mafunzo ya utangulizi ya SHEP kwa vikundi vinavyopokea mkopo. 26 Utafiti wa Awali na Kumbukumbu ya Mapato ya Shamba Kunaweza kuwa na changamoto kwa wakulima kuhifadhi taarifa sahihi katika hatua ya awali ya utunzaji wa kumbukumbu. Kwahiyo, kuna haja ya kuangalia ikiwa taarifa zao ni sahihi au la, kwa mfano, juu ya gharama za uzalishaji, ukubwa wa eneo, kiasi cha uzalishaji na mauzo. Maafisa ugani au wataalamu wengine huwasaidia wakulima kuweka taarifa sahihi ili watambue mauzo yao, gharama na faida . Utafiti wa Soko Wakulima wanahitaji tu usaidizi wa awali kama hatua ya mwanzo mfano, kuwatambulisha kwa wasimamizi wa soko au wanunuzi na kuwafundisha namna ya kufanya utafiti. Mara tu wanapofahamu, wanakuwa na furaha ya kuendeleza peke yao. Kwa hivyo, inashauriwa kwa Halmashauri ya Wilaya au watendaji wengine kusaidia mara ya kwanza tu ya Utafiti wa soko kama zoezi la majaribio kwenye soko la karibu, ambapo wakulima wanaweza kwenda wenyewe baadaye. Utafiti wa soko unaweza kusaidia wakulima sio tu kutambua mwelekeo wa bei lakini pia kuunda biashara kwa kuwaunganisha na wanunuzi muhimu. Kwa hivyo, inaweza kuwa na ufanisi kwa wakulima kutembelea soko mbalimbali iwezekanavyo. Utafiti wa soko unapaswa kufanywa hata baada ya kupanda. Mawasiliano ya mara kwa mara na wanunuzi huwasaidia wakulima kujua mabadiliko katika mahitaji ya soko, na Utafiti wa soko wa ziada husaidia kupata mnunuzi mwingine. Kuna baadhi ya taarifa kwamba mnunuzi anaweza asiwe mwaminifu au kushindwa kutambua mwenendo bei za mazao sokoni. Kwa hiyo, wakulima wanahimizwa sana kuwa na wanunuzi zaidi ya mmoja kama mbadala wa kupata taarifa Zaidi za utafiti wa soko Wakulima huwa wanafikiria kuwa masoko makubwa katika miji mikubwa yanaweza kutoa biashara nzuri kwao. Hata hivyo, hii si lazima. Mara nyingi zaidi, kuuza kwa masoko ya ndani ya karibu kunaweza kupunguza muda na gharama za usafiri, hivyo kuwanufaisha wakulima na wanunuzi. Kwa mfano, katika Halmashauri ya Wilaya ya Karatu, utafiti wa soko uliofanywa na wakulima ulibaini kuwa wanunuzi wa ndani walikwenda kwenye masoko makubwa ya (Kilombero au soko kuu la Arusha) kununua mboga kwa ajili ya kuuza kwenye masoko ya ndani. Wanunuzi walisema kuwa walifurahi kununua mboga kutoka kwa wazalishaji wa ndani moja kwa moja. Kwa matokeo haya, wakulima waliamua kuuza mazao yao kwa wanunuzi wa ndani, ambayo ilirudisha faida zaidi kuliko ile ya kuuza kwenye masoko makubwa. Mkutano wa wadau wa Kilimo Jukwaa la wadau ni sehemu ya kuanzia tu ya majadiliano na makubaliano ya ushirikiano wa kibiashara. Ufuatiliaji makini kutoka kwa upande wa wakulima ni muhimu zaidi ili kupata ushirikiano huku wakulima wakisubiri wadau waje. Hivyo, maafisa ugani wanatakiwa kuwezesha mawasiliano baina yao baada ya kongamano. Mkutano wa wadau unaweza kufanywa katika huduma za kawaida za ugani: afisa ugani humtambulisha mdau (mfano. kampuni ya pembejeo) kwa wakulima au kinyume chake. Mkutano wa wadau sio lazima kuwa kongamano kubwa. Jukwaa la wadau kati ya wakulima na wakulima au ugani wa Mkulima-kwa-Mkulima, ikiwa ni pamoja na ziara ya mafunzo baina ya vikundi vya wakulima ni nzuri sana katika kueneza mazoea mazuri na kushiriki taarifa za soko. 27 Mpango Kazi Ni muhimu kufanya uchambuzi wa faida kabla ya kulima. Na baada ya kuvuna na kuuza, mchanganuo huu wa faida upitiwe upya kwa kuzingatia takwimu halisi za uzalishaji na mauzo, ili wakulima waweze kutambua udhaifu na changamoto katika makadirio yao au uzalishaji halisi. Kutokana na ugunduzi wa utafiti wa soko, wakulima wengi wamedhamiria kuboresha uzalishaji wao kwa mfano, wakati wa kupanda, kubadilisha aina au ukubwa. Mara nyingi, wao hufikiria kitu kinachozidi uwezo wao au kisichofaa katika mazingira yao. Kwa hiyo, katika kuandaa mpango kazi, maofisa ugani wanapaswa kuwapa wakulima ushauri wa kitaalamu kwa mtazamo wa kiutendaji, ili kuzuia hatari kubwa katika uzalishaji (mfano, uhaba wa maji kutokana na kukauka kwa chanzo cha maji, mafuriko kutokana na mvua zisizotarajiwa, wadudu waharibifu na magonjwa). Ni jambo la muhimu sana kuwezesha wakulima kuelewa faida mbalimbali za SHEP, si tu kwa uzalishaji hatarishi wa faida kubwa ili kupata bei ya juu zaidi bali pia kwa mikakati mingine kama vile i) kukidhi mahitaji ya ubora wa mnunuzi, ii) kuepuka msimu wa bei ya chini zaidi na kulenga masilahi ya wastani ya faida, iii) kuwa na masoko/wanunuzi tofauti ili kufanya ulinganifu wa faida. Katika Halmashauri ya Wilaya ya Lushoto, kwa mfano, utafiti wa soko alieleza kuwa wanunuzi walihitaji saizi kubwa ya viazi kuliko vile ambavyo wakulima huzalisha kwa kawaida. Ugunduzi huu u lifanya wakulima kujenga matuta katika mashamba y ao n a kufuata nafasi ifaayo y a kupanda, ili kuzalisha viazi v ikubwa zaidi, na hatimaye walifanikiwa kuuza kwa bei nzuri zaidi. Hii ina maana kwamba kuna aina mbalimbali za mipango kazi zinazoweza kutumika ili kuboresha mapato yao ya kilimo. Dhana ya SHEP ilitokana na maendeleo ndani ya sekta ndogo ya mazao ya bustani, hata hivyo uhitaji wa matumizi ya dhana hii katika mazao mengine umeongezeka. Baadhi ya mifano katika matumizi ya dhana ya SHEP kwenye mazao mengine ni kama ifuatavyo: Kikundi cha wakulima cha Paumi kilichopo katika Halmashauri ya Wilaya ya Muheza kilikuwa kinafanya uzalishaji wa mazao ya mbogamboga. Kutokana na changamoto ya uhaba wa maji waliamua kufanya utafiti wa soko la zao la mahindi kwa sababu walidhani ni rahisi kuzalisha mahindi kwa gharama nafuu na mbinu rahisi. Matokeo ya utafiti yalibaini kuwa kuna mahitaji makubwa ya mahindi mabichi ikilinganishwa na upatikanaji wake. Hivyo, walifanya maamuzi ya kuzalisha mahindi mabichi kulingana na matokeo ya utafiti wa soko yaliyopelekea kuongeza faida na kipato cha wakulima. Baada ya mauzo, walifurahia faida, si kutokana na mauzo makubwa, bali kutokana na gharama ndogo za uzalishaji. Vikundi vya Kisha na Changamka vilivyopo Halmashauri ya Wilaya ya Siha vilikuwa vinalima Maharage mabichi na kuyauza katika masoko ya ndani ya Wilaya. Baada ya kupata elimu ya utafiti wa soko, walifanya utafiti kwenye masoko ya Arusha na kugundua kuwa bei ya maharage mabichi iko juu ikilinganishwa na masoko ya ndani ya Wilaya ya Siha. Aidha, utafiti ulionyesha kuwa mahitaji ya maharage mabichi mjini ni makubwa sana ikilinganishwa na yale makavu kwasababu hutumia muda mfupi kupika. Vikundi viliamua kufanya uzalishaji wa maharage kibiashara na kuyauza katika masoko ya Arusha. 4.2.9 Matumizi ya SHEP kwa Mazao Mengine MAHINDI MABICHI MAHARAGE MABICHI 28 Vikundi vya Ichesa, Msia na Hamwelo katika Halmashauri ya Wilaya ya Mbozi walishangazwa na tathmini ya kahawa yao kuwa daraja la chini na kuwa bei ndogo. Katika kutafuta ufumbuzi wa changamoto hiyo, waliamua kufanya utafiti wa soko na ziara ya mafunzo katika mnyororo wa thamani. Walishauriwa na wanunuzi kutochanganya kahawa mbichi na zilizoiva wakati wa kuvuna kwani kufanya hivyo kunaharibu ubora wa kahawa. Hatimae wakagundua tatizo halikuwa ubora wa miche wala kupogolea isipokuwa ni namna ya kuchambua wakati wa kuvuna. Matokeo hayo yalisaidia kuboresha ubora na kupelekea mabadiliko ya daraja kutoka daraja la 9 hadi la 5 na hatimae kupata bei nzuri ukilinganisha na hapo awali. Kikundi cha wakulima cha Mshikamano kilichopo katika Halmashauri ya Wilaya ya Karatu, kilifanya utafiti wa soko la alizeti pamoja na mazao ya nyanya na pilipili hoho. Walifanya utafiti wa soko na kubaini uzalishaji mdogo na upatikanaji wa mafuta ya alizeti. Pia waliamua kuchagua zao la alizeti kutokana na gharama nafuu za uzalishaji na matumizi mbalimbali ya zao hilo ikiwemo mafuta ya kula na vyakula vya mifugo. Utafiti huu uliwafanya kuchagua alizeti kuwa ndiyo yenye faida zaidi. Kupitia utafiti wa soko, walijenga mtandao na wasindikaji wa mafuta. Baada ya matokeo ya utafiti, wakulima walianza kulima alizeti kama zao jipya la biashara. KAHAWA ALIZETI 29 5.0 UFUATILIAJI NA TATHMINI Dhana ya SHEP inatumia mbinu mbalimbali katika kufuatilia utekelezaji wa shughuli za kila siku kwa ajili ya kupima matokeo. Utoaji wa taarifa za utekelezaji wa kila mwezi hufanywa na maafisa ugani na timu ya uwezeshaji ya wilaya ili kupima hatua zilizofikiwa katika kuleta mabadiliko chanya au kujifunza pamoja na utoaji wa taarifa za kifedha. Ufuatiliaji wa mara kwa mara hufanywa kupima uelewa na uwezo wa wakulima dhidi ya mafunzo waliyopewa ukiambatana na ukusanyaji wa takwimu sahihi juu ya mbinu bora za kilimo cha mazao ya bustani na taarifa za masoko. Taarifa jumuishi za kila Halmashauri huandaliwa na timu ya Mkoa na kuwasilishwa kwenye kikosi kazi cha mikoa na kujadiliwa katika kikao kazi cha kila mwezi. Taarifa ya nusu mwaka na mwaka mzima huwasilishwa kwa Katibu Mkuu Wizara ya Kilimo na Makatibu Tawala wa Mikoa kwa ajili ya ufuatiliaji na kufahamu mienendo ya utekelezaji wa mpango wa SHEP, na hatimaye huwasilishwa kwa wadau wa maendeleo pamoja na wadau wa msingi katika mnyororo wa thamani wa mazao ya bustani. Tathmini ya utelezaji hutakiwa kufanyika kwa kila awamu ya mradi wa SHEP na mapitio huwasilishwa katika vikao mbali mbali vya wadau ikiwemo vikao vya Kikosi kazi cha mikoa na Wizara husika na Kikao kazi cha Kamati ya Ushauri ya Kitaifa (National Consultative Commetttee (NCC) kwa lengo la kufanya mapitio na marekebisho ya mpango mzima na kupima mafanikio na matokeo chanya na mambo ya kujifunza ili kuboresha mfumo mzima wa utekelezaji pamoja na kuweka mikakati ya kutatua changamoto zilizojitokeza. Ufuatiliaji na tathmini kwenye vikundi vya wakulima hufanywa kila mwezi ukiwa umelenga kuhakikisha kuwa wakulima wanapata ujuzi, maarifa na kuyatumia katika kukabiliana na changamoto za uzalishaji wa mazao ya bustani na upatikanaji wa masoko. Wataalamu hufuatilia kwa kina mafanikio na changamoto kwa kukusanya takwimu zitakazolinganishwa na taarifa za utafiti wa awali ili kujua hatua iliyofikiwa na wakulima. Mfumo wa ufuatiliaji na tathmini wa Serikali kuu utafuata utaratibu uliopo wa kuanzia ngazi ya wilaya, mkoa hadi wizara kwa kufuatilia taarifa za kila mwezi, robo mwaka, na mwaka mzima zilizoandaliwa na mikoa. Taarifa hizo ni kwa ajili ya matumizi ya ndani na nje ya taasisi hizo kama inavyoonyeshwa kwenye jedwali Na 04. 5.1 Ufuatiliaji na tathmini wa serikali kuu LENGO 30 Jedwali Na 04: Muhtasari wa matumizi ya taarifa 5.2 Ufuatiliaji na tathmini kwa kutumia Bango kitita Mfumo wa Ufuatiliaji na Tathmini wa SHEP utategemea bango kitita (Logical framework na Result based matrix) lenye viashiria hitajika kulingana na malengo na mipango kazi dhidi ya maendeleo yaliyofikiwa pamoja na kutoa fursa ya kurekebisha mapungufu yaliyojitokeza, mfano idadi ya vikundi, walengwa, idadi ya vikao, idadi ya taarifa nk. (Tazama jedwali la Upimaji wa matokeo) TAARIFA NYANJA UWAJIBIKAJI KUFANYA MAAMUZI KUJIFUNZA WAFADHILI WIZARA Ufuatiliaji Utoaji taarifa Hutumika kwa ajili ya uwajibikaji wa wafadhili Uwajibikaji wa Katibu tawala Mkoa (RAS), Katibu Mkuu (PS) Kwa ajili ya Kutoa maamuzi RAS, PS Kiwago kidogo cha kujifunza Upimaji mwingine Haitumiki Wakurugenzi wa MSM (DED, & DAICO) na Baraza la Madiwani; Kwa ajili ya kutoa maamuzi ya Kibajeti na mipango kazi Mwenendo wa utekelezaji Tathmini Tathmini ya nje Hutumika kwa ajili ya wafadhili juu ya Matokeo ya Mradi Katibu tawala Mkoa (RAS), Katibu Mkuu (PS), Kufanya maamuzi juu ya mahusiano bora ya Wizara na wafadhili Kujifunza kwa Katibu Mkuu (PS/DPSO) Tathmini nyinginezo Haitumiki Haitumiki Hutoa taarifa za kubora mipango kazi ya mwaka Kujifunza na mabadiliko ya ngazi za utendaji mradi 31 MALENGO MKAKATI MATOKEO YA KATI VIASHIRIA VYA KILA TOKEO LM 01: Kujenga uwezo wa Halmashauri Uwezo wa Halmashauri umeimarika katika kutekeleza dhana ya SHEP TK 1.1 Utambulisho wa Dhana ya SHEP umefanyika kwa Wakurugenzi watendaji wa Wilaya na Wenyeviti wa Halmashauri 1) Warsha moja (1) elekezi ya inayojumuisha Halmashauri 52- LGAs katika mikoa 26 imefanyika. 2) Uwepo wa taarifa ya Warsha na Makabrasha ya mafunzo. TK 1.2 Uwezo wa Halmashauri katika kutekeleza dhana ya SHEP umeimarika. 1) Idadi / Orodha ya DFTs walifundishwa dhana ya SHEP kila Halmashauri. 2) Uwepo wa taarifa ya mafunzo kwa DFTs na makabrasha ya kufundishia LM 02: Uwezo wa Wakulima kufikia masoko kirahisi Kuongezeka kwa uwezo wa wakulima kufikia masoko na upatikanaji wa taarifa za masoko TK 2.1 Utafiti wa awali umefanywa na wakulima kwa kushirikiana na maafisa ugani na DFTs 1) Utafiti wa awali umefanywa katika Halmashauri zote 52 na mikoa yote 26 Tanzania bara 2) Uwepo wa taarifa za utafiti wa awali ngazi za Halmashauri. TK 2.2 Mfumo wa Kumbukumbu za Mapato ya Shamba (FIR) na Faida (PA) kuimarika [Uelewa wa wakulima wa namna ya kukusanya taarifa kwa kujaza vema Kumbukumbu za Mapato ya Shamba (FIR) na Faida (PA)] 1) Uwepo wa nyaraka zenye Kumbukumbu za Mapato ya Shamba (FIR) na Faida (PA) zilizojazwa na wakulima na kuwasilishwa mkoani 2) Uwepo wa taarifa za kila mwezi TK 2.3 Utafiti wa masoko umefanywa na wakulima kwa kushirikiana na DFTs na Maafisa ugani 1) Uwepo wa taarifa za utafiti wa masoko zenye orodha ya wanuuzi wa kila zao na majina ya masoko (ndani na nje) LM 03: Ujuzi wa Wakulima Kuongezeka kwa fursa za wakulima kufikia huduma za pembejeo na msaada wa kitaalamu TK 3.1 Mafunzo ya kitaalamu kwa maafisa ugani na vikundi vya wakulima juu ya Mbinu bora za Kilimo, Udhibiti wa wadudu, magonjwa na matumizi sahihi ya pembejeo (Mbolea, Madawa nk) yamefanika 1) Idadi ya wakulima na Maafisa ugani waliofundishwa Mbinu bora za Kilimo, ikiwemo udhibiti wa wadudu, magonjwa na matumizi sahihi ya pembejeo (Mbolea, Madawa nk) 2) Uwepo wa taarifa ya utekelezaji wa tokeo hili TK 3.2 Utekelezaji wa Hafla ya kuunganisha wadau imefanywa na Mikoa, wawezeshaji wa Wilaya (DFTs) na wakulima 1) Uwepo wa taarifa wa hafla ya kuunganisha wadau 2) Uwepo wa orodha ya wadau wa Pembejeo, taasisi za fedha nk.na kupewa wakulima TK 3.3 Mipango kazi imeandaliwa na wakulima kwa kusaidiwa na DFTs kwa kutumia taarifa za utafiti wa awali na za masoko. 1) Uwepo wa Mipango kazi na kalenda za mazao/kilimo zilizoandaliwa kwa ajili ya mafunzo 2) Uwepo wa mfumo wa utoaji taarifa wa mipango kazi hiyo LM 04: Kuimarika kwa mfumo na mbinu za ufuatiliaji na tathimini wa dhana ya SHEP TK 4.1 Mfumo wa ufuatiliaji na tathmini umeandaliwa na kutumiwa na Kikosi kazi cha Mikoa, na Halmashauri. 1) Mfumo wa Ufuatiliaji unatumiwa na DFTs na kutoa taarifa na takwimu sahihi. 2) Taarifa za kila mwezi zinatolewa TK 4.2 Kikao cha kila mwezi cha kikosi kazi cha mkoa kinafanyika kwa ajili ya kupima mafanikio ya dhana ya SHEP na kufuatilia changamoto zake. 1) Taarifa za ufuatiliaji za kila mwezi zinawasilishwa na DFTs na TF 2) Uwepo wa Mihutasari ya Vikao na maazimio ya TF ya kila mwezi. Jedwali 05: Bango la Mfumo wa Upimaji Matokeo - Ngazi ya Halmashauri na Mikoa 32 Ufuatiliaji na tathmini ya ndani na nje, Utafanyika kwa kuzingatia umakini wa ukusanyaji takwimu mbalimbali, uchambuzi na utoaji taarifa ngazi ya wizara na katika vikao kazi vya wadau wa maendeleo ya mazao ya Bustani. Lengo likiwa ni kupima mafanikio na kutathmini changamoto. Mbinu mbalimbali zitatumika ikiwa ni pamoja na Bango kitita (Jedwali 06). 33 LENGO MKAKATI TOKEO LA KATI VIASHIRIA WATEKELEZAJI LM1: Kuongezeka kwa tija, uzalishaji na ubora wa mazao ya Bustani TK 1.1: Kupatikana kwa pembejeo bora. i) Kuimarika kwa usambazaji na matumizi sahihi ya Pembejeo bora (Mbegu, madawa, mbolea nk); ii) Upatikanaji wa zana za kilimo cha mazao ya bustani umeimarika. WK, PO-RALG, TFRA, TARI, TOSCI, ASA, TPRI TK 1.2 : Kuimarika kwa huduma za ugani wa mazao ya bustani. i) Idadi ya wakulima wanaotumia mbinu bora za kilimo cha mazao ya bustani imeongezeka; ii) Idadi ya maafisa ugani wenye elimu na ujuzi wa fani ya Kilimo cha mazao ya bustani imeongezeka, iii) Kuongezeka kwa tija, uzalishaji na ubora wa mazao ya bustani katika maeneo yanayotumia dhana ya SHEP iv) Mwongozo wa Kilimo cha mazao ya bustani unaotumia dhana ya SHEP unatumika. WK, OR-TAMISEMI TK 1.3: Mbinu za kupunguza uharibifu na upotevu wa mazao ya bustani zinatumiwa na wakulima. i) Kiwango cha upotevu (Pre-& Post-harvest losses) mazao ya bustani kimepungua; WK, TARI ii) Mbinu za Hifadhi na usafirishaji kwa kutumia magari maalumu zinatumika. WK, TARI, Ministry of Transport LM2: Kuongezeka kwa ushiriki wa taasisi ya utafiti, mafunzo na uthibiti wa mazao ya Bustani TK 2.1: Kuimarika kwa taasisi za utafiti shirikishi. i) Kuongezeka kwa idadi ya taasisi zinazoshirikiana na Halmashauri zinazotekeleza dhana ya SHEP; WK, TARI, ASA, MATIs, TOSCI, WV, TAPHA, TFRA TK 2.2: Kuongezeka kwa ushiriki wa makampuni ya mbegu na pembejeo zingine. i) Idadi ya Makampuni ya Mbegu na pembejeo nyingine yanayoshirika kutoa huduma kwa watekelezaji wa dhana ya SHEP ii) Kuongezeka kwa matumizi ya mbegu na pembejeo bora za mazao ya Bustani iii) WK, TOSCI, TAPHA, TARI, ASA, TFRA, OR-TAMISEMI LK3: Kuimarika kwa mfumo wa masoko ya mazao ya Bustani ndani na nje ya nchi TK 3.1: Wakulima wadogo kuunganishwa na masoko i) Idadi ya masoko rasmi ya mazao ya Bustani; ii) Idadi ya wakulima wanaoyafikia masoko rasmi ya mazao ya Bustani (jumla na Rejereja); WK, OR-TAMISEMI Jedwali 06: Bango la Mfumo wa Upimaji Matokeo - Ngazi ya Taifa 34 5.3 Ufuatiliaji na tathmini ngazi ya tawala za mikoa Mfumo wa ufuatiliaji na tathmini kwa ngazi ya Tawala za Mikoa hufuata utaratibu uliopo wa kuanzia ngazi ya MSM, Kata hadi Kijijii kwa kufuatilia taarifa za kila mwezi, robo mwaka, na mwaka mzima zilizoandaliwa na MSM. Malengo Kufuatilia na kutathmini uandaaji na utekelezaji wa Mipango ya Maendeleo ya Kilimo Wilaya (DADPs) kwa kutumia dhana ya SHEP katika MSM. Kutathmini uwezeshaji wa MSM katika vikundi vya wakulima vinavyotekeleza dhana ya SHEP ( kifedha, mafunzo na huduma za ugani). Kuunganisha taarifa za ufuatiliaji za Mkoa na kuziwasilisha OR-TAMISEMI. 35 5.3.1 Ufuatiliaji unaofanywa na Maafisa Ugani wa Kata na Vijiji Utangulizi (Kwa kuzingatia Hatua za SHEP) Tathimini ya kila wiki kwa vikundi vya wakulima hufanywa na Afisa ugani wa Kata na/au Kijiji aliye karibu na kikundi husika. Malengo Kufuatilia i li kujua mafanikio, changamoto, matumizi sahihi ya pembejeo, uzingatiaji wa mpango kazi wa wakulima. Mambo ya Kuzingatia (Dhana ya SHEP) Walengwa/Wahusika: Wakulima, Afisa Ugani ngazi ya Kata na Kijiji Ratiba ya kazi: Kila wiki, Kalenda ya mazao, Mpango kazi Gharama / Bajeti: Usafiri na Shajala Mahitaji ya vifaa kazi (Zana) Orodha ya Wakulima Shajala, Penseli/Kalamu, na Kikokotozi Takwimu za malipo ya wakulima (Kumbukumbu za wakulima) kadri ya mipango kazi; Kalenda ya U zalishaji, F omu za U chaguzi wa M azao ( Tazama Kiambatisho) Fomu ya Ufuatiliaji na Tathimini ya Afisa Ugani Pamoja na Fomu zingine zote kwenye Viambatisho 02-02 na 02-03 Utekelezaji 1) Fanya ziara za u fuatiliaji k ila mwezi ili kukagua mafanikio na k utoa ushauri wa kitaalam kwa wakulima. 2) Rejea uchunguzi wa awali sehemu ya 2 (Mbinu za kilimo) ili kubaini namna wakulima walivyopokea ushauri na kuutumia, pima na tathmini mapungufu na k ubaini n amna y a kusaidia w akulima ili kupata u juzi mpya. 3) Rejea kalenda ya m azao w aliyoiandaa wakulima k wa a jili y a kupima mafanikio na toa ushauri stahili wa kitaalam. 4) Kusanya takwimu za mgawanyo wa majukumu ya kijinsia na mafanikio yake. Mfano, t aarifa z a mafanikio kwa kuzingatia u sawa w a jinsia n a namna wanawake walivyojengewa uwezo kufikia malengo na lengo kuu la kikundi. 5) Baada ya muda, mfano mwezi mmoja, fanya tathmini ya mafanikio kwa kulinganisha taarifa za uchunguzi wa awali na takwimu zilizopatikana ndani ya kipindi husika kwa kuwashirikisha wakulima kupitia vikundi vyao ili kupima mafaninikio na kubaini changamoto kuu za utekelezaji ili kuzirekebisha. 6) Kusanya / Chukua t aarifa z a mabadiliko c hanya katika m aisha yao yaliyopatikana kutoka na matumizi ya dhana ya SHEP toka kwa wakulima. 36 Mambo ya Kuzingatia Ushiriki sawa wa jinsia (wanawake na wanaume) kwa kuzingatia dhana ya SHEP Ukusanyaji n a uchambuzi w a takwimu za u shiriki w a majukumu k wa kuzingatia jinsia Kubadilika kwa maamuzi yenye usawa kwa kuzingatia jinsia. Mambo ya Kuepuka Mazao kuharibika na kukosekana kwa tija kwa mkulima Mbinu za uzalishaji zilizofundishwa kutozingatiwa Kusambaratika kwa kikundi cha wakulima 5.4 ufuatiliaji na tathmini ngazi ya Halmashauri Ufuatiliaji wa vikundi vya wakulima hufanyika kwa kutembelea vikundi vyote kwa ajili ya kupima uelewa/ kiwango cha ujuzi uliotokana na mafunzo waliyoyapata mashambani juu ya matumizi bora ya Kalenda ya Mazao, Utafiti shirikishi wa soko, ununuzi wa pembejeo za kilimo, na mafunzo ya mbinu bora ya kilimo katika kupambana na magonjwa na wadudu waharibifu katika mazao ya bustani. Jedwali Na 07: Muundo wa taarifa za kila mwezi ngazi ya Halmashauri Wilaya……………. Tarehe: …………… Mtoa taarifa: …………………………. Malengo Kutathmini ubora wa mafunzo mashambani; na Kutathmini utekelezaji wa mipango kazi ya vikundi vya wakulima. JINA LA KIKUN DI ZAO (Ain a) KIMO CHA ZAO (Hatua ya mafanik io) (%) Inaenda na n a mpango kazi AP? Wadudu na Magonjwa Utunzaji wa Kumbukumbu Shughuli za Masoko (Mawasilia no n a wanunuzi, Matokeo ya Soko m f. Bei) Pembejeo zilizopokel ewa na kutumika Hoja zingine (mf. Mafunzo, Changam oto etc) Aina y a wadudu na magonj wa Hatua za udhibit i Matokeo (Imedhibi tiwa, Hakuna madhara? ) Je Wakulima wanatunza kumbuku mbu? Kam a si wote (Kwa nini) USHAURI WA K ITAALAMU NA MAPENDEKEZO 37 5.4.1 Ufuatiliaji na Tathmini ya Kila Mwezi Unaofanywa na MSM Utangulizi (Kwa kuzingatia Hatua za SHEP) Tathimini ya vikundi vya wakulima hufanywa kwa kila kikundi kinachotekeleza dhana ya SHEP. Tathimini hii hufanywa na DFTs na Wajumbe wa Kikosi Kazi Malengo • Kujua Mafanikio, changamoto, matumizi sahihi ya pembejeo, uzingatiaji wa mpango kazi wa wakulima Kupima utendaji wa Maafisa Ugani ngazi za Kata na Vijiji. Mambo ya Kuzingatia Walengwa/Wahusika: DFTs; Wajumbe wa Kikosi kazi Mkoa, Wataalamu wa mazao ya bustani toka Taasisi na vyuo vya Kilimo mfano Chuo cha Kilimo cha Mazao ya Bustani (Hort-Tengeru), Wakulima, Afisa Ugani ngazi ya Kata na Vijiji Dondoo o Ratiba ya kazi za kila mwezi (Ukaguzi) o Kalenda ya mazao ya kama inaendana na uzalishaji o Mpango kazi kama unaendana na utekelezaji Gharama / Bajeti: Usafiri,Mafuta, Posho na Shajala Mahitaji ya vifaa kazi (Zana) Orodha ya Wakulima; Shajala, Penseli/Kalamu na Kikokotozi Taarifa za mauzo na Kumbukumbu za wakulima kadri ya mipango kazi; Kalenda ya Uzalishaji, Mipango kazi ya Vikundi vya Wakulima; Fomu ya Ufuatiliaji na tathimini ya DFTs Pamoja na Fomu zingine zote kuanzia Viambatisho 02-02, 02-03 na 04. Utekelezaji 1) Fanya ziara za ufuatiliaji kila mwezi ili kukagua mafanikio na kutoa ushauri wa kitaalam kwa wakulima. 2) Rejea uchunguzi wa awali sehemu ya 2 (Mbinu za kilimo) ili kubaini namna wakulima walivyopokea ushauri na kuutumia, pima na tathmini mapungufu na kubaini namna ya kusaidia wakulima ili kupata ujuzi mpya. 3) Rejea kalenda ya mazao walioiandaa wakulima kwa ajili ya kupima mafanikio na toa ushauri stahili wa kitaalam. 4) Kusanya takwimu za mgawanyo wa majukumu ya kijinsia na mafanikio yake, mfano, taarifa za mafanikio kwa kuzingatia usawa wa jinsia na namna wanawake walivyojengewa uwezo kufikia malengo na lengo kuu la kikundi. 5) Baada ya muda, mfano mwezi mmoja, fanya tathmini ya mafanikio kwa kulinganisha taarifa za uchunguzi wa awali na takwimu zilizopatikana ndani ya kipindi husika kwa kuwashirikisha w akulima kupitia vikundi vyao i li k upima mafaninikio na k ubaini changamoto kuu za utekelezaji ili kuzirekebisha. 6) Kusanya / Chukua taarifa za mabadiliko chanya katika maisha yao yaliyopatikana kutoka na matumizi ya dhana ya SHEP toka kwa wakulima. Mambo ya Kuzingatia Hakikisha kuna k uwa na u shiriki sawa w a jinsia ( wanawake n a wanaume) k atika kutekeleza dhana ya SHEP. Kusanya na chambua takwimu za ushiriki wa majukumu kwa kuzingatia jinsia. Hakikisha Maamuzi yeyote ndani ya mipango kazi katika kikundi yazingatie usawa wa jinsia. Hakikisha kikundi kinafanya kazi kwa umoja ili kuepuka kusambaratika. Hakikisha wakulima w anazalisha k wa t ija kwa kuzingatia m binu z a kitaalamu walizofundishwa. 38 Matokeo Uwepo wa Taarifa shirikishi ya maendeleo ya mwezi inayotumwa kwenda Sekretariati ya Mkoa. Wakulima walengwa wanatambua uwezo, ujuzi na udhaifu wao ili kupewa ushauri na maelekezo kwa ajili ya kuboresha uzalishaji na masoko. Wakulima walengwa wanakuwa na uelewa wa kuimarika na kufuzu dhana ya SHEP. Wakulima wanakuwa na imani na kukubali kufanya utafiti wa masoko, uchaguzi wa mazao, kutengeneza kalenda ya uzalishaji na kutumia maarifa waliyoyapata ya uzalishaji kila wakati. Kuwepo k wa m aamuzi y enye u sawa k wa k uzingatia jinsia n dani y a vikundi vya wakulima. 5.4.2 Taarifa ya Utekelezaji na Maendeleo za Robo Mwaka unaofanywa na MSM 5.4.4 Ufuatiliaji wa Utoaji na Matumizi wa fedha kwa ajili ya kutekeleza dhana ya SHEP ngazi ya MSM 5.4.3Taarifa ya Utekelezaji wa SHEP ya Mwaka Unaofanywa na MSM MSM ziandae taarifa za maendeleo ya utekelezaji wa dhana ya SHEP kila robo mwaka na kuwasilisha katika kikao cha uratibu wa SHEP mkoa husika, na taarifa hizo ziwasilishwe ngazi za Wizara / Taifa kwa kufuata mfumo na miongozo ya utoaji taarifa. MSM ziandae taarifa ya maendeleo ya utekelezaji wa dhana ya SHEP kila mwaka na kuwasilisha katika kikao cha uratibu wa SHEP mkoa husika, na taarifa hiyo iwasilishwe ngazi ya Wizara / Taifa kwa kufuata mfumo na miongozo ya utoaji taarifa. Ni muhimu kutenga fedha kwa ajili ya kutumika ngazi ya MSM ili kuwezesha uendelevu wa dhana ya SHEP. Kimsingi dhana ya SHEP inahitaji bajeti ya ziada tofauti na ile ya kawaida ya kuendeleza mazao ya bustani ili kuwezesha matokeo chanya. Bajeti hii hutumika kuwawezesha DFTs, Maafisa Ugani ngazi ya Kata na Vijiji ili kuwafikia na kuwahudumia wakulima. Maafisa Ugani wanaofanya kazi moja kwa moja na wakulima wakati wa kufanya utafiti wa awali, utafiti wa soko, hafla ya kuunganisha wadau (match-making), mafunzo kwa wakulima juu ya mbinu bora za kilimo, udhibiti wa wadudu na magonjwa huhitaji kuwezeshwa gharama za usafiri, shajala, na posho zao za kujikimu nk., hivyo MSM zinapaswa kutenga fedha na kuzisimamia kwa ajili ya utekelezaji wa majukumu ya Watalam kupitia dhana ya SHEP. Kwa mantiki hiyo, ili kuwa na matokeo chanya ya dhana SHEP, Serikali kupitia MSM inatakiwa kutenga bajeti toshelezi kwa ajili ya uendelevu na kupanua shughuli za dhana ya SHEP ndani ya wilaya husika, na kutenga bajeti ndogo kwa ajili ya ufuatiliaji na tathmini kwa watendaji wa ngazi ya Wilaya. (Tazama Jedwali la Mfano wa Bajeti) 39 Jedwali Na 08: Mfano wa Bajeti ya Maafisa Ugani MSM zote zinazotekeleza dhana ya SHEP zinawajibika kutenga na kutoa fedha kutoka mapato ya ndani angalau 20% kwa ajili ya utekelezaji w dhana ya SHEP na taarifa hiyo ya kibajeti iwasilishwe OR-TAMISEMI kupitia Mikoa kwa ajili ya ufuatiliaji. Na. SHUGHULI KUU IDADI YA SIKU KIASI CHA MALIPO (Tshs) IDADI YA WATU KIASI CHA FEDHA (Tshs) 1. Posho ya Kutwa, Chakula (Kama ni lazima)-DFTs/EOs 2. Gharama za Usafiri (Mafuta, Vipuri, nk) 3. Gharama za Ukumbi 4. Gharama za vifaa 5. Shajara 6. Pembejeo (Mbegu, Madawa, Mbolea nk,) 7. Chakula cha Wakulima 8. Nauli za wakulima 9. n. k JUMLA 40 Wafuatao wameshiriki moja kwa moja kwenye kuandaa mwongozo huu:- SN Jina Taasisi 1 Tabu Likoko Wizara ya Kilimo 2 Juma Shekidele HORTI-Tengeru 3 Issa Hatibu Sekretarieti ya Mkoa Tanga 4 Daniel Loiruck Sekretarieti ya Mkoa Arusha 5 Bai Omary Wizara ya Kilimo 6 Mhandisi Apolinary K. Medard Sekretarieti ya Mkoa Kilimanjaro 7 Mukara Mugini Wizara ya Kilimo 8 Hoffu Mwakaje OR-TAMISEMI 9 Masumbuko M. Weswa Wizara ya Kilimo 10 Anneth Mwangasa Wizara ya Kilimo 11 Abdallah Mussa HORTI-Tengeru 12 Ippei Itakura TANSHEP-JICA 13 Chiaki Shiga TANSHEP-JICA 14 Fuminori Arai TANSHEP-JICA 15 Kyoko Akasaka TANSHEP-JICA 16 Getrude Sombe Wizara ya Kilimo | false |
# Extracted Content MWANZA REGION SOURCES OF FUNDS DASIP BENEFICIARY GEITA CHIGUNGA SARAGULWA Purchase of hulling machine 5,000 2,500 2,500 NYAKAGOMBA ISIMA Purchase of hulling machine 5,000 2,500 2,500 Construction of a market shed 33,400 26,720 6,680 NZERA IDOSERO Purchase of hulling machine 5,000 2,500 2,500 KASEME MAGENGE Purchase of hulling machine 5,000 2,500 2,500 KAKORA KABIGA Purchase of hulling machine 5,000 2,500 2,500 KHARUMWA BUMANDA Purchase of hulling machine 5,000 2,500 2,500 BULELA NYAMBOGO Purchase of hulling machine 5,000 2,500 2,500 Construction of a crop storage facility 35,000 28,000 7,000 MWINGIRO IDETEMYA Purchase of hulling machine 5,000 2,500 2,500 Construction of a charco dam. 35,000 28,000 7,000 Nyang'hwale NYIJUNDU Purchase of hulling machine 5,000 2,500 2,500 Construction of a market shed 33,400 26,720 6,680 NYAMALIMBE NYAMIGOGO Purchase of hulling machine 5,000 2,500 2,500 Construction of a crop storage facility 35,000 28,000 7,000 KHARUMWA IZUNYA Purchase of hulling machine 5,000 2,500 2,500 Construction of a charco dam. 35,000 28,000 7,000 SENGA SENGA Construction of a market shed 33,400 26,720 6,680 NZERA LWENZERA Construction of a market shed 33,400 26,720 6,680 IHANAMILO NYAKATO Construction of a market shed 33,400 26,720 6,680 KAKORA KAKORA Construction of a crop storage facility 35,000 28,000 7,000 NYAMALIMBE LWAMWIZO Construction of a crop storage facility 35,000 28,000 7,000 BUSOLWA BUSOLWA Construction of a charco dam. 35,000 28,000 7,000 467,000 357,100 109,900 KWIMBA NYASHANA Construction of a cattle crush for vaccination 6,500 5,200 1,300 NYAMBITI SOLWE Construction of a shallow well for irrigation 5,000 4,000 1,000 Purchase of Oxen drawn implements 2,200 1,100 1,100 MALIGISU MWABARATURU Construction of a shallow well for irrigation 5,000 4,000 1,000 Construction of a cattle crush for vaccination 6,500 5,200 1,300 TOTAL GEITA DISTRICT TOTAL COST (in '000) DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ALLOCATION OF INVESTMENT FUNDS - 1st QRT 2008/09 KAGERA , SHINYANGA, MARA, KIGOMA AND MWANZA REGIONS DISTRICT WARD VILLAGE NAME OF PROJECT Purchase of Oxen drawn implements 2,200 1,100 1,100 TALAGA Rehabilitation of a charco dam 35,000 28,000 7,000 Purchase of Oxen drawn implements 2,200 1,100 1,100 IGONGWA MWADUBI Construction of a shallow well for irrigation 5,000 4,000 1,000 Purchase of Oxen drawn implements 2,200 1,100 1,100 NGUDU ILUMBA Construction of a shallow well for irrigation 5,000 4,000 1,000 MWAMAKOYE Rehabilitation of a charco dam 35,000 28,000 7,000 Purchase of Oxen drawn implements 2,200 1,100 1,100 MANTARE MWAMPULU Construction of a cattle crush for vaccination 6,500 5,200 1,300 NGULLA NYAMBUYI Construction of a cattle crush for vaccination 6,500 5,200 1,300 Purchase of Oxen drawn implements 2,200 1,100 1,100 MWAMALA MWALUJO Construction of a cattle crush for vaccination 6,500 5,200 1,300 MHANDE MHANDE Construction of a cattle crush for vaccination 6,500 5,200 1,300 Purchase of Oxen drawn implements 2,200 1,100 1,100 FUKALO CHIBUJI Construction of a cattle crush for vaccination 6,500 5,200 1,300 BUPAMWA CHASALAWI Rehabilitation of a charco dam 35,000 28,000 7,000 Purchase of Oxen drawn implements 2,200 1,100 1,100 MALYA MALYA Purchase of Oxen drawn implements 2,200 1,100 1,100 KISHILI Purchase of Oxen drawn implements 2,200 1,100 1,100 SUMVE MWASHILALAGE Purchase of Oxen drawn implements 2,200 1,100 1,100 MHANDE GULUMWA Purchase of Oxen drawn implements 2,200 1,100 1,100 196,900 149,600 47,300 MISUNGWI USAGARA BUJINGWA Construction of a market shed. 35,000 28,000 7,000 MISUNGWI MABUKI Construction of a charco dam 13,000 10,400 2,600 Construction of a Cattle dip 22,000 17,600 4,400 70,000 56,000 14,000 SENGEREMA NYAKASASA ISENYI Procurement of Ia power tiller 5,000 2,500 2,500 LUGATA KABAGANGA Procurement of Irrigation equipment 5,600 2,800 2,800 LUGATA Procurement of Irrigation equipment 5,600 2,800 2,800 KATWE KASHEKA Procurement of Irrigation equipment 5,600 2,800 2,800 KATUNGURU NYAMTELELA Construction of a crop marketing shed 35,000 28,000 7,000 Purchase of oxen drawn implements 7,600 3,800 3,800 KAFUNZO KAFUNZO Market shed 35,000 17,500 17,500 99,400 60,200 39,200 TOTAL KWIMBA DISTRICT TOTAL MISUNGWI DISTRICT TOTAL SENGEREMA DISTRICT 833,300 622,900 210,400 #REF! #REF! #REF! GRAND TOTAL TOTAL MWANZA REGION | false |
# Extracted Content T.O.C. Tanzania Agriculture Sample Census i United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vs: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government September 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vs: REGIONAL REPORT: MWANZA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of Contents.............................................................................................................................................................. i Acronyms......................................................................................................................................................................... v Preface ...........................................................................................................................................................................vi Executive Summary....................................................................................................................................................... vii Illustration ...................................................................................................................................................................... xii 1. BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ....................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area .......................................................................................................................................................... 1 1.4 Climate............................................................................................................................................................... 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population.......................................................................................................................................................... 1 1.6 Socio-economic Indicators................................................................................................................................ 2 2. INTRODUCTION............................................................................................................................................. 3 2.1 Introduction ....................................................................................................................................................... 3 2.2 The Rationale for Conducting the National Sample Census of Agriculture.................................................... 3 2.3 Census Objectives ............................................................................................................................................. 3 2.4 Census Coverage and Scope ............................................................................................................................. 4 2.5 Legal Authority of the National Sample Census of Agriculture...................................................................... 5 2.6 Reference Period ............................................................................................................................................... 5 2.7 Census Methodology....................................................................................................................................... 5 2.7.1 Census Organization............................................................................................................................ 5 2.7.2 Tabulation Plan................................................................................................................ 6 2.7.3 Sample Design.................................................................................................................................... 6 2.7.4 Questionnaire Design and Other Census Instruments ........................................................................ 7 2.7.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.7.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.7.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.7.8 Household Listing................................................................................................................................ 8 2.7.9 Data Collection ................................................................................................................................... 8 2.7.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.7.11 Data Processing ................................................................................................................................... 9 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations .............................................................................................. 10 - Data Quality................................................................................................................................. 10 2.8 Funding Arrangements................................................................................................................................. 10 3. CENSUS RESULTS ..................................................................................................................................... 11 3.1 Household Characteristics ........................................................................................................................... 11 3.1.1 Type of Household ........................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 15 3.1.4 Number and of Age Household Members ...................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 16 - Literacy Rates for Heads of Households.................................................................................... 16 - Educational Status....................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................... 17 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.2 Land Use .......................................................................................................................................... 18 3.2.1 Area of Land Utilised..................................................................................................... 18 3.2.2 Types of Land use .......................................................................................................... 20 3.3. Annual Crops and Vegetable Production.................................................................................... 20 3.3.1 Area Planted .................................................................................................................... 20 3.3.2 Crop Importance............................................................................................................. 21 3.3.3 Crop Types ..................................................................................................................... 21 3.3.4 Cereal Crop Production.................................................................................................. 22 Maize .............................................................................................................................. 22 Paddy .............................................................................................................................. 24 Other Cereals.................................................................................................................. 27 3.3.5 Roots and Tuber Crops Production................................................................................ 27 Cassava........................................................................................................................... 28 Sweet Potatoes................................................................................................................ 30 3.3.6 Pulse Crops Production.................................................................................................. 30 Beans............................................................................................................................... 32 3.3.7 Oil Seed Production........................................................................................................ 34 Groundnuts ..................................................................................................................... 34 3.3.8 Fruits and Vegetables..................................................................................................... 35 Tomatoes ........................................................................................................................ 37 Cabbage .......................................................................................................................... 39 Chilies............................................................................................................................. 39 3.3.9 Other Annual Crops Production..................................................................................... 42 Cotton ............................................................................................................................. 42 Tobacco .......................................................................................................................... 42 3.4 Permanent Crops..................................................................................................................................... 42 3.4.1 Mango............................................................................................................................. 46 3.4.2 Oranges.......................................................................................................................... 46 3.4.3 Banana ............................................................................................................................ 48 3.4.4 Guava.............................................................................................................................. 48 3.5. Inputs/Implements Use .................................................................................................................. 50 3.5.1 Methods of Land Clearing................................................................................................................ 50 3.5.2 Methods of Soil Preparation........................................................................................... 50 3.5.3 Improved Seeds Use....................................................................................................... 51 3.5.4 Fertilizers Use................................................................................................................. 52 Farm Yard Manure Use.................................................................................................. 53 Inorganic Fertilizer Use.................................................................................................. 53 Compost Use .................................................................................................................. 55 3.5.5 Pesticides Use................................................................................................................. 56 Insecticides Use.............................................................................................................. 56 Herbicides Use................................................................................................................ 58 3.5.5.3 Fungicides Use ............................................................................................................... 59 3.5.6 Harvesting Methods ........................................................................................................ 60 3.5.7 Threshing Methods......................................................................................................... 60 3.6 Irrigation.......................................................................................................................................... 60 3.6.1 Area Planted with Annual Crops and Under irrigation ................................................. 60 3.6.2 Sources of Water Used for Irrigation............................................................................. 61 3.6.3 Methods of Obtaining Water for Irrigation ................................................................... 61 3.6.4 Methods of Water Application ...................................................................................... 63 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing.................................................................................... 63 3.7.1 Crop Storage................................................................................................................... 63 Method of Storage.......................................................................................................... 63 Duration of Storage ........................................................................................................ 64 Purpose of Storage.......................................................................................................... 64 The Magnitude of Storage Loss...................................................................................... 65 3.7.2 Agro Processing and By-Products ................................................................................. 65 - Processing Methods ................................................................................................ 65 - Main Agro-Processing Products............................................................................. 66 - Main Use of Primary Processed Products .............................................................. 66 - Outlet for Sale of Processed Products .................................................................... 67 3.7.3 Crop Marketing .............................................................................................................. 68 Main Marketing Problems ............................................................................................. 68 Reasons for Not Selling.................................................................................................. 68 3.8 Access to Crop Production Services............................................................................................. 68 3.8.1 Access to Agricultural Credits ....................................................................................... 68 Source of Agricultural Credits ....................................................................................... 70 Use of Agricultural Credits............................................................................................ 70 Reasons for not using agricultural credits...................................................................... 70 3.8.2 Crop Extension............................................................................................................... 71 Sources of Crop Extension Messages.......................................................................... 71 Quality of Extension...................................................................................................... 71 3.9 Access to Inputs............................................................................................................................… 71 3.9.1 Use of Inputs................................................................................................................... 71 3.9.2 Inorganic Fertilizers ....................................................................................................... 72 3.9.3 Improved Seeds .............................................................................................................. 72 3.9.4 Insecticides and Fungicides............................................................................................ 73 3.10 Tree Planting................................................................................................................................... 74 3.11 Irrigation and Erosion Control Facilities .................................................................................... 75 3.12 Livestock Results ............................................................................................................................ 77 3.12.1 Cattle Production .............................................................................................................................. 77 Cattle Population .............................................................................................................................. 77 Cattle Herd size................................................................................................................................. 77 Cattle Population Trend.................................................................................................................... 79 Dairy Cattle Breeds .......................................................................................................................... 79 3.12.2 Goat Production................................................................................................................................ 79 Goat Population ................................................................................................................................ 79 Goat Herd Size................................................................................................................................... 81 Goat Breeds....................................................................................................................................... 81 Goat Population Trend ..................................................................................................................... 81 3.12.3 Sheep Production.............................................................................................................................. 81 Sheep Population .............................................................................................................................. 81 Sheep Population Trend ................................................................................................................... 83 3.12.4 Pig Production .................................................................................................................................. 83 Pig Population Trend........................................................................................................................ 83 3.12.5 Chicken Production .......................................................................................................................... 85 Chicken Population........................................................................................................................... 85 Chicken Population Trend................................................................................................................ 85 TOC ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv Chicken Flock Size........................................................................................................................... 87 Improved Chicken Breeds (layers and broilers) .............................................................................. 87 3.12.6 Other Livestock ................................................................................................................................ 87 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 88 Deworming ....................................................................................................................................... 88 3.12.8 Access to Livestock Services ........................................................................................................... 88 Access to livestock extension Services............................................................................................ 88 Access to Veterinary Clinic.............................................................................................................. 89 Access to village watering points/dam............................................................................................. 89 3.12.9 Animal Contribution to Crop Production......................................................................................... 90 Use of Draft Power........................................................................................................................... 90 Use of Farm Yard Manure................................................................................................................ 90 3.13 Fish Farming.................................................................................................................................................. 92 3.14 Access to Infrastructure and Other Services ............................................................................................. 92 3.15 Poverty Indicators......................................................................................................................................... 93 3.15.1 Type of Toilets.................................................................................................................................. 93 3.15.2 Household’s assets............................................................................................................................ 93 3.15.3 Sources of Lighting Energy.............................................................................................................. 93 3.15.4 Sources of Energy for Cooking......................................................................................................... 95 3.15.5 Roofing Materials.............................................................................................................................. 95 3.15.6 Access to Drinking Water ................................................................................................................ 95 3.15.7 Food Consumption Pattern............................................................................................................... 96 Number of Meals per Day................................................................................................................ 96 Meat Consumption Frequencies....................................................................................................... 98 Fish Consumption Frequencies ........................................................................................................ 98 3.15.8 Food Security..................................................................................................................................... 98 3.15.9 Main Source of Cash Income........................................................................................................... 98 4. MWANZA PROFILES................................................................................................................................101 4.1 Mwanza Regional Profile............................................................................................................................. 101 4.2 District Profiles...............................................................................................................................................102 4.2.1 Ukerewe.......................................................................................................................................... 102 4.2.2 Magu ................................................................................................................................................104 4.2.3 Kwimba........................................................................................................................................... 105 4.2.4 Sengerema........................................................................................................................................107 4.2.5 Geita................................................................................................................................................ 108 4.2.6 Missungwi....................................................................................................................................... 110 4.4.7 Ilemela............................................................................................................................................. 111 ACRONYMS __________________________________________________________________________________________________ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department for International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Mwanza region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Mwanza region who were selected using statistical sampling techniques. The results presented in this report do not cover urban areas and large-scale farmers. Highlighted are important findings regarding agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural and related activities and poverty in Mwanza region, the aim being to present an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural activities. i) Household Characteristics The number of agricultural households in Mwanza region was 340,085 out of which 197,780 (58.2%) were involved in growing crops only, 1,156 (0.3%) rearing livestock only, there were no pastoralist in Mwanza region and 141,149 (41.5%) were involved in crop production as well as livestock keeping. In summary, Mwanza region had 338,929 households involved in crop production and 142,305 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, permanent crop farming, tree/forest resources, livestock keeping/herding ,fishing and remittances. The region has a literacy rate of 64 percent. The highest literacy rate is in Ukerewe district (73%), followed by Magu district (71%), Sengerema district (65.2%), Missungwi district (65%) and Ilemela district (64%). Kwimba and Geita districts both have literacy rates of 60.3 and 59.0 percents. The literacy rate for the heads of households in the region was 65 percent. The number of heads of agricultural households with formal education in Mwanza region was 213,880 (62.9) percent, those without formal education were 126,204 (37.1) percent and those with only adult education were 5144 (1.5) percent. The majority of heads of agricultural households (59.1) percent had primary level education whereas only 0.3 percent had post primary education. In Mwanza region 157,655 household members (68% of households with off-farm income) had each household member engaged in off-farm income generating activities. Another 50,366 households (22%) had two household members engaged in off farm income generating activities and 24,841 households (11%) had each more than two members engaged in off- farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 864,585 ha. The regional average land area utilised for crop production per crop growing household was only 2.0 ha. This figure is equivalent to the national average of 2.0 hectares. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Planted Area The area planted with annual crops and vegetables was 679,107 hectares out of which 438,178 hectares (64.5%) were planted during short rainy season and 240,929 hectares (35.5%) during long rainy season. An estimated area of 315,648 ha (46.5% of the total planted area with annual and vegetable crops) was planted with cereals, followed by 176,633 hectares (26.0%) of root and vegetables, 86,938 ha (12.8%) of cash crops, 77,101 ha (11.3%) of pulses, 19,501 ha (2.9%) of oil seeds & oil nuts and 3,286 ha (0.5%) of fruits and vegetables. Maize Maize was the dominant annual crop grown in Mwanza region and it had a planted area 1.5 times greater than cassava, which had the second largest planted area. The areas planted with maize constitute 30.7 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were paddy, cassava, sweet potatoes, beans, groundnuts and sorghum. There was a sharp decrease in maize production from 109,000 tonnes in 1998/89 to 84,000 tonnes in 1999/2000 and then a sharp increase to 150,804 tonnes in 2002/03. 2003. The total production of maize in 2002/03 was 150,804 tonnes. The average area planted with maize per household ranged from 0.1 hectares in Ukerewe District to 1.0 hectares in Kwimba District. Geita district had the largest planted area of maize (64083 ha) followed by Magu (40,412 ha), Kwimba (39,709 ha), Sengerema (32,278 ha), Missungwi (26,675 ha), Ilemela (3,737 ha) and Ukerewe (1,617 ha). Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Mwanza region during the short rainy season was 77,984. This represented 24.2 percent of the total crop growing households in Mwanza Region in the short rainy season. The total production of paddy was 81,805 tonnes from a planted area of hectare 87,231 resulting in a yield of 0.9 t/ha. The district with the largest area planted with paddy was Missungwi (24,726 ha) followed by Kwimba (20,641 ha), Sengerema (15,371 ha), Ilemela (14,865 ha), Magu (8,826 ha), Ukerewe (1534 ha) and Geita (1,268 ha). Cassava The area planted with cassava was larger than any other root and tuber crop in Mwanza region in terms of planted area (23.9% of the total area planted with annual crops and vegetables) and it accounted for 80.0 percent of the area planted with roots and tubers. The total production of cassava during the census year was 204,303 tonnes from a planted area of 141,223 hectares resulting in a yield of 1.4t/ha. Fruit and Vegetables The total production of fruit and vegetables was 16,817 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 10,715 tonnes, which accounted for 63.7.4 percent of the total fruit and vegetable production, followed by onions 1,664 tonnes (10.9%) and cabbage 1,547 tonnes (10.1%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The planted area of smallholders with permanent crops was 17,819 hectares which was 2.6 percent of the area planted with crops in the region. The most important permanent crop was mango which accounted for 35.7 percent of the total area planted with permanent crops followed by oranges (16.0%), bananas (12.7%) EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix Improved Seeds The planted area using improved seeds was 169,898 ha which represented 25.0 percent of the total area planted with annuals. The percentage use of improved seed in the short rainy season was 33.5 percent and higher than the corresponding percentage use for the long rainy season (9.5%). Use of Fertilizers Most annual crop growing households did not use any fertilisers. The area planted without fertilisers for annual crops was 549,417 hectares representing 81 percent of the total area planted with annual crops. Of the area planted with fertiliser application, farm yard manure was applied to 115,464 ha which represented 17 percent of the total planted area (89 % of the area planted with fertiliser application). This was followed by Inorganic fertilizers (7,139 ha, 6%) and compost (7,087 ha) representing 5 percent of the area planted with fertilizers. Irrigation In Mwanza region, the area of annual crops and vegetables under irrigation was 181,460 ha representing 26.7 percent of the total area planted. The area under irrigation during the short rainy season was 10,137 ha accounting for 5.6 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 94.6 percent compared with 5.6 percent in the short rainy season. Crop Storage There were 295,746 crop growing households (87.3% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 273,370 households storing 20,026 tonnes as of 1st January 2004. This was followed by Beans & Pulses (130,653 households and 2,269 tonnes) Paddy (109,350 households and 12,144 tonnes), and sorghum & millet (26,270 households and 1,642 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crops was 243,200 which represent 71.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Sengerema (78.3%) followed by Magu (76.6%), Geita (72.0%), Ukerewe (703%), Missungwi (67.0%), Kwimba (61.9%) and Ilemela (60.7%). Agricultural Credit In Mwanza region, few agricultural households (9,991, 2.9%) accessed credit, out of which 7,358 (74%) were male-headed households and 209 (26%) were female headed households. In Ukerewe district there were no households heads who got credit for agricultural purposes, whereas in Geita only male households accessed credit. In Magu, Kwimba, Sengerema, Missungwi and Ilemela districts both male and female headed households’ accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 71,522 (21% of total crop growing households in the region). Some districts had more access to extension services than others (Chart 3.106). Ilemela district had a relatively high proportion of households that received crop extension messages (65%), followed by Magu (40%), Missungwi (23%), Ukerewe (22%), Kwimba (18%), Sengerema (15%) and Geita (8%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 28,852. This number represents 8 percent of the total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Magu district (24%) followed by Kwimba (12%), Ukerewe (10%), Sengerema (6%), Missungwi (5%), Ilemela (4%) and Geita (1%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 1,718,191. Cattle were the most dominant livestock type in the region followed by goats, sheep and pigs. The region had 10.2 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 1,710,309 head (99.5% of the total number of cattle in the region), and 7,882 (0.5%) were dairy breeds. There were no beef breeds. Goats The number of goat-rearing households was 124,250 (36.5% of all agricultural households) with a total of 829,997 goats giving an average of 7 heads of goats per goats-rearing household. Sheep The number of sheep-rearing-households in the region was 24,433 (7% of all agricultural households) with a total of 121,978 sheep giving an average of 5 head of sheep per sheep-rearing-households. Pigs The number of pig-rearing households in the region was 76 (0.02% of the total agricultural households) rearing about 610 pigs. This gives an average of 8 pigs per pig-rearing household. Chicken The number of households keeping chickens was 240,279, raising 2,620,818 chickens. This gave an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country Mwanza ranked second out of the 21 Mainland regions. Use of Draft Power The region has 335,501 oxen and they were found in all districts, Magu (141,016), Ukerewe (112,801), Geita (89,023), Sengerema (75,944), Kwimba (28,873) and Missungwi with 645. Mwanza region has 20 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 211,975 hectares of land. Fish Farming The number of households involved in fish farming was 326 (0.1 percent of the total agricultural households in the region). Kwimba was the only district with agricultural households involved in fish farming. iv) Poverty Indicators Availability of Toilets The results show that 85.3 percent of all rural agricultural households used traditional pit latrines, 2.1 percent used improved pit latrines and 3.3 percent had flush toilets. Households with no toilet facilities represented 9.2 percent of the total agriculture households in the region. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xi Household Assets Out of all assets, the bicycle was the most common household asset and was owned by 64% of the households, followed by radios (63%), iron (17%), wheelbarrow (6%), mobile phone (2%), television/video (1%), vehicle (1%) and landline phone (0.4%). Source of Lighting Energy The wick lamp was the most common source of lighting energy in the region. About 74 percent of the total rural households used this source of energy followed by hurricane lamp (20.5%), pressure lamp (4.0%), mains electricity (0.8%), firewood (0.6%), solar (0.2%), candle (0.1%) and gas or biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.7%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity(0.14) solar (0.04%), livestock dung (0.04%), paraffin/kerosene (0.03%) and gas/biogas (0.01%). Roofing Materials The most popular roofing material (for the main dwelling) was grass and/or leaves and was used by 49.3 percent of the rural agricultural households. It was closely followed by iron sheets (39.9%). Other roofing materials were grass/mud (9.1%), tiles (0.7%), asbestos (0.5%), concrete (0.4%) and others (0.2%). Number of Meals per Day About 26 percent of the households in the region took three meals per day, 72 percent took two meals, 2 percent took one meal and 0.5 percent took four meals Food Security Households which rarely had problems in satisfying their food needs represented 27.1 percent of the total number of agricultural households in the region. Households which often experienced problems represented 10.0 percent whereas those with little problems represented 3.7 percent. About 6.1 percent of the agricultural households always faced food shortages whilst 53 percent did not experience any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 27.2 percent of all rural agricultural households. The second main cash income earning activity was casual labour (20.9%) followed by selling of cash crops (15.8%), businesses (9.9%) and fishing (8.2%). Other income earning activities were livestock (4.5%), employment (4.1%) sale of forest products (2.3%) and sale of livestock products (1.8%) ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ...............................................................................................................................................6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District ...11 3.2 Area, Production and Yield of Cereal Crops by Season .....................................................................................22 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop........................................27 3.4 Area, Quantity Harvested and Yield of Pulses by Season ..................................................................................30 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season....................................................................34 3.6 Area, Production and Yield of Fruits and Vegetables by Season .......................................................................37 3.8 Land Clearing Methods........................................................................................................................................50 3.9 Number of Crop Growing Households and Planted Area (ha) by Type of Fertilizer Used and District During the Long Rainy Season..........................................................................................................................52 3.10 Number of Households Storing Crops by Estimated Storage Loss and District ................................................52 3.11 Reasons for Not Selling Crop Produce................................................................................................................68 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District ................68 3.13 Access to Inputs....................................................................................................................................................72 3.14 Total Number of Households and Chickens Raised by Flock Size ....................................................................87 3.15 Head Number of Other Livestock by Type of Livestock and District................................................................87 3.16 Mean Distances from Holders Dwellings to Infrastructures and Services by Districts .....................................92 3.17 Number of Households by Number of Meals the Household Normally Has per Day and District...................96 List of Charts 3.1 Percentage Distribution of Agricultural Households by Type of Holdings........................................................11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head..............................................15 3.3 Percentage Distribution of Population by Age and Sex in 2003.........................................................................15 3.4 Percentage Literates Level by District.................................................................................................................16 3.5 Literacy Rates of Heads of Household by Sex and District................................................................................16 3.6 Percentage of Person Aged 5 years and Above by District and Educational Status ..........................................16 3.7 Percentage Distribution of Persons Aged 5 Years and Above in Agricultural Households by Education Status and District.................................................................................16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ....................................................17 3.9 Number of Households by Number of Members with Off-farm Activities .......................................................17 3.10 Percentage Distribution of Agricultural Households by Number of Members with Off-farm Activities and District ...........................................................................................................................................................17 3.11 Utilized and Usable Land per Household by District..........................................................................................18 3.12 Percentage Distribution of Land Area by Type of Land Use..............................................................................18 3.13 Area Planted with Annual Crops per household and Vegetables by Season.....................................................20 3.14 Area Planted with Annual Crops (ha) by Season and District............................................................................20 3.15 Area Planted with Annual Crops per household by Season and District............................................................20 3.16 Planted Area for the Main Annual Crops (ha).....................................................................................................21 3.17 Planted Area (ha) per Household for Selected Crops..........................................................................................21 3.18 Percentage Distribution of Area Planted with Annual Crops by Crop Type......................................................21 3.20 Area Planted and Yield of Major Cereal Crops...................................................................................................22 3.21 Maize: Total Area Planted and Planted Area per Household by District ...........................................................22 3.22 Maize Production Trend as per Agriculture Censuses and Surveys ...................................................................24 3.23 Time Series of Maize Planted Area and yield.....................................................................................................24 3.24 Paddy: Total Area and Area of Paddy per Household by District......................................................................24 3.25 Paddy: Production Trend as per Agriculture Censuses and Surveys.................................................................24 3.26 Time Series of Paddy Planted Area and Yield ....................................................................................................27 3.27 Area planted with Sorghum, Finger Millet and Wheat by District.....................................................................27 3.28 Area Planted and Yield of Major Root and Tuber Crops....................................................................................27 3.29a Area Planted with Cassava during the Census/Survey Years .............................................................................28 3.29b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District.....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District ................................................................28 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District.............................................30 3.32 Area Planted and Yield of Major Pulse Crops ....................................................................................................30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District .............................................32 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only).........................................32 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.35 Time Series Data on Bean Production.................................................................................................................32 3.36 Time Series of Bean Planted Area and Yield......................................................................................................32 3.37 Area Planted and Yield of Major Oil Seed Crops...............................................................................................34 3.38 Time Series Data on Groundnuts Production......................................................................................................34 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District .........................35 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) ...............................35 3.42 Area Planted and Yield of Fruits and Vegetables .............................................................................................. 35 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 37 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only)................................... 37 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District .................................. 39 3.46 Percent of Chilies Planted Area and Percent of Total Land with Chillies by District ...................................... 39 3.47 Area planted with Annual Cash Crops ............................................................................................................... 42 3.49 Area Planted for Annual and Permanent Crops.................................................................................................. 42 3.50 Area Planted with the Main Permanent Crops ....................................................................................................45 3.51 Percent of Area Planted with Permanent crops and Average Planted Area per Household by District ........... 45 3.52 Percent of Area Planted with Mangoes and Average Planted Area per Household by District........................ 46 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District......................... 46 3.54 Percent of Area Planted with Bananas and Average Planted Area per Household by District......................... 48 3.55 Percent of Area Planted with Guava and Average Planted Area per Household by District............................ 48 3.56 Number of Households by Method of Land Clearing During the Long Rainy Season..................................... 50 3.57 Area Cultivated by Cultivation Method.............................................................................................................. 50 3.58 Area Cultivated by Method of Cultivation and District..................................................................................... 51 3.59 Area Planted with Improved Seeds......................................................................................................................51 3.60 Area Planted with Improved Seed by Crop Type................................................................................................51 3.61 Percentage of Crop Type Area Planted with Improved Seed – Annuals............................................................51 3.62 Area of Fertilizer Application by Type of Fertilizer .......................................................................................... 52 3.63 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 52 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season..................................................... 53 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .....................................................53 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District .........................................................53 3.66 Planted Area with Inorganic fertilizers by Crop Type ...................................................................................... 53 3.67a Percentage of Planted Area with Inorganic Fertilizers by Crop Type– Annuals............................................... 55 3.67b Proportion of Planted Area Applied with Inorganic Fertilizers by District........................................................55 3.68a Planted Area with Compost by Crop Type - Long Rainy Season...................................................................... 55 3.68b Percentage of Planted Area with Compost by Crop Type ..................................................................................56 3.68c Proportion of Planted Area Applied with Compost by District..........................................................................56 3.69 Planted Area (ha) by Pesticide Use..................................................................................................................... 56 3.70 Planted Area Applied with Insecticides by Crop Type...................................................................................... 56 3.71 Percentage of Crop Type Planted Area Applied with Insecticides.................................................................... 58 3.72 Percentage of Planted Area Applied with Insecticides by District ................................................................... 58 3.73 Planted Area Applied with Herbicides by Crop Type........................................................................................ 58 3.74 Percentage of Crop Type Planted Area Applied with Herbicides...................................................................... 59 3.75 Proportion of Planted Area Applied with Herbicides by District ..................................................................... 59 3.76 Planted Area Applied with Fungicides by Crop Type ....................................................................................... 59 3.77 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 60 3.78 Proportion of Planted Area Applied with Fungicides by District ..................................................................... 60 3.79 Area of Irrigated Land......................................................................................................................................... 60 3.80 Planted Area with Irrigation by District............................................................................................................. 60 3.81 Time Series OF Households with Irrigation........................................................................................................61 3.82 Number of Households with Irrigation by Source of Water.............................................................................. 61 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................... 61 3.85 Number of Households and Quantity Stored by Crop ...................................................................................... 63 3.86 Number of Households by Storage Method ....................................................................................................... 63 3.87 Number of Households by method of Storage and District (based on the most important household crop) ... 63 3.88 Normal Length of Storage for Selected Crops ................................................................................................... 64 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .................................................. 64 3.90 Number of Households by Purpose of Storage and Crop ..................................................................................64 3.91a Households Processing Crops..............................................................................................................................65 3.91b Households Processing Crops by District........................................................................................................... 65 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 65 3.93 Number of Households by Type of Main Processed Product............................................................................ 66 3.94 Number of Households by Type of By-product................................................................................................. 66 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.95 Use of Processed Product.....................................................................................................................................66 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 67 3.97 Location of Sale of Processed Products...............................................................................................................67 3.98 Percent of Households Selling Processed Products by Outlet and District ....................................................... 67 3.99 Number of Crop Growing Households that Sold Crops by District ...................................................................68 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 68 3.101 Percentage Distribution of Households that Received Credit by Main Source................................................. 70 3.102 Proportion of Households who Received Credits by Main Source of the Credit.............................................. 70 3.103 Proportion of Households Receiving credit by Main Purpose of the Credit ......................................................70 3.104 Reason for nit Using Credit (%of Households)...................................................................................................70 3.105 Number of Households Receiving Extension Advice........................................................................................ 71 3.106 Number of Households Receiving Extension by District .................................................................................. 71 3.107 Number of Households Receiving Extension by Quality of Service................................................................. 71 3.108 Number of Households by Source of Inorganic Fertilizers.................................................................................72 3.109 Number of Households Reporting Distance to Source of Inorganic Fertilizers.................................................72 3.110 Number of Households by Source of Improved Seeds .......................................................................................72 3.111 Number of Households Reporting Distance to Source of Improved Seeds........................................................73 3.112 Number of Households by Source of Insecticides/Fungicides............................................................................73 3.113 Number of Households reporting Distance to Source of Insecticides/Fungicides .............................................73 3.114 Number of Households with Planted Trees.........................................................................................................74 3.115 Number of Planted Trees by Species...................................................................................................................74 3.116 Number of Trees Planted by Smallholders by Species and District ...................................................................74 3.117 Number of Trees Planted by Location.................................................................................................................75 3.118 Number of Households by Purpose of Planted Trees..........................................................................................75 3.119 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 75 3.120 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District........... 75 3.121 Number of Erosion Control/Water Harvesting Structures by Type of Facility................................................. 77 3.122 Total Number of Cattle ('000') by District.......................................................................................................... 77 3.123 Numbers of Cattle by Type and District............................................................................................................. 77 3.124 Cattle Population Trend ...................................................................................................................................... 79 3.125 Dairy Cattle Population Trend............................................................................................................................ 79 3.126 Total Number of Goats ('000') by District.......................................................................................................... 79 3.127 Goat Population Trend........................................................................................................................................ 81 3.128 Total Number of Sheep by District..................................................................................................................... 81 3.129 Sheep Population Trend...................................................................................................................................... 83 3.130 Total Number of Pigs by District........................................................................................................................ 83 3.131 Pig Population Trend........................................................................................................................................... 83 3.132 Total Number of Chicken by District ................................................................................................................. 85 3.133 Chicken Population Trend .................................................................................................................................. 85 3.134 Number of Improved Chicken by Type and district............................................................................................87 3.135 Layers Population Trend..................................................................................................................................... 87 3.136 Percentage of Livestock keeping Households that Reported Tsetse flies and Tick problems by District........ 88 3.137 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District .......... 88 3.138 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........ 88 3.139 Number of Households by Distance to verinary Clinic ..................................................................................... 89 3.140 Percentage of Households by Distance to veterinary Clinic and District.......................................................... 89 3.141 Number of Households by Distance to village watering points......................................................................... 89 3.142 Percentage of Households by distance to village watering point and district ................................................... 89 3.143 Number of Households using draft animals ....................................................................................................... 90 3.144 Number of Households using draft animals by district...................................................................................... 90 3.145 Number of Households using organic fertilisers................................................................................................ 90 3.146 Area of Application of organic fertilisers by district.......................................................................................... 90 3.147 Number of Households practicing fish farming Mwanza .................................................................................. 92 3.148 Number of Households practicing fish farming by district Mwanza................................................................. 92 3.149 Fish Production.................................................................................................................................................... 92 3.150 Percentage distribution of Agricultural Households by type of toilets.............................................................. 93 3.151 Percentage of Households Owning the assets .................................................................................................... 93 3.152 Percentage distribution of Households by main source of energy for lighting ................................................. 93 3.153 Percentage distribution of Households by main source of energy for cooking................................................. 95 3.154 Percentage distribution of Households by type of roofing material .................................................................. 95 3.155 Percent of Households with grass/ leaves roofs by district................................................................................ 95 3.156 Percent of Households by main source of drinking water and season............................................................... 95 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.157 Percent of Households by distance to main source of drinking water and season ............................................ 96 3.158 Number of Agricultural households by number of meals per day..................................................................... 96 3.159 Number of households by frequency of meat and fish consumption................................................................. 98 3.160 Percentage distribution of the number of households by main source of income............................................. 98 List of Maps 3.1 Total Number of Agricultural Households by District........................................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District..........................................................12 3.3 Number of Crop Growing Households by District..............................................................................................13 3.4 Percent of Crop Growing Households by District...............................................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................14 3.6 Percent of Crop and Livestock Households by District ......................................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land ..........................................................................19 3.8 Total Planted Area (annual crops) by District.....................................................................................................19 3.9 Area planted and Percentage During the Short Rainy Season by District......................................................... 23 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................23 3.11 Planted Area and Yield of Maize by District ......................................................................................................25 3.12 Area Planted per Maize Growing Household......................................................................................................25 3.13 Planted Area and Yield of Paddy by District ......................................................................................................26 3.14 Area Planted per Paddy Growing Household......................................................................................................26 3.15 Planted Area and Yield of Cassava by District ...................................................................................................29 3.16 Area Planted per Cassava Growing Household...................................................................................................29 3.17 Planted Area and Yield of Sweet Potatoes by District........................................................................................31 3.18 Area Planted per Sweet Potatoes Growing Household ......................................................................................31 3.19 Planted Area and Yield of Beans by District.......................................................................................................33 3.20 Area Planted per Beans Growing Household......................................................................................................33 3.21 Planted Area and Yield of Groundnuts by District .............................................................................................36 3.22 Area Planted per Groundnuts Growing Household.............................................................................................36 3.23 Planted Area and Yield of Tomatoes by District.................................................................................................38 3.24 Area Planted per Tomatoes Growing Household................................................................................................38 3.25 Planted Area and Yield of Cabbage by District ..................................................................................................40 3.26 Area Planted per Cabbage Growing Household..................................................................................................40 3.27 Planted Area and Yield of Chillies by District....................................................................................................41 3.28 Area Planted per Chillies Growing Household ...................................................................................................41 3.29 Planted Area and Yield of Cotton by District......................................................................................................43 3.30 Area Planted per Cotton Growing Household.....................................................................................................43 3.31 Planted Area and Yield of Tobbaco by District ..................................................................................................44 3.32 Area Planted per Tobacco Growing Household..................................................................................................44 3.33 Planted Area and Yield of Oranges by District...................................................................................................47 3.34 Area Planted per Orange Growing Household....................................................................................................47 3.35 Planted Area and Yield of Banana by District ....................................................................................................49 3.36 Area Planted per Banana Growing Household....................................................................................................49 3.37 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..................................54 3.38 Area Planted and Percent of Total Planted Area with Irrigation by District ......................................................54 3.39 Planted Area and with Farm yard Manure Application by District ....................................................................57 3.40 Planted Area and percent of Total Planted Area with compost Manure Application by District......................57 3.41 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .....62 3.42 Number and Percent of Crop Growing Households using Improved Seeds by District ....................................62 3.43 Percent of Households storing Crops for 3 to 6 months by district ....................................................................69 3.44 Number of Households and Percent of Total Households Selling Crops by District.........................................69 3.45 Number and Percent of Smallholder planted Trees by District ..........................................................................76 3.46 Number and Percent of Households with water harvesting bunds by District...................................................76 3.47 Cattle population by District as of 1st Octobers 2003.........................................................................................78 3.48 Cattle Density by District as of 1st October 2003...............................................................................................78 3.49 Goat population by District as of 1st Octobers 2003 ..........................................................................................80 3.50 Goat Density by District as of 1st October 2003.................................................................................................80 3.51 Sheep population by District as of 1st Octobers 2003 ........................................................................................82 3.52 Sheep Density by District as of 1st October 2003...............................................................................................82 3.53 Pig population by District as of 1st Octobers 2003.............................................................................................84 3.54 Pig Density by District as of 1st October 2003 ...................................................................................................84 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.55 Number of Chicken by District as of 1st October 2003......................................................................................86 3.56 Density of Chicken by District as of 1st October 2003.......................................................................................86 3.57 Number and percent of Households Infected with ticks by District...................................................................91 3.58 Number and percent of Households using draft Animals by District.................................................................91 3.59 Number and percent of Households practicing Fish farm by District ................................................................94 3.60 Number and percent of Households without Toilets by District.........................................................................94 3.61 Number and percent of Households using Grass/leaves for Roofing material by District ................................97 3.62 Number and percent of Households eating 3 meals per pay by District.............................................................97 3.63 Number and percent of Households eating meals once per week by District ....................................................99 3.64 Number and percent of Households eating meals fish once per week by District .............................................99 3.65 Number and percent of Households reporting food insufficiency by District..................................................100 BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Mwanza region lies in the northern part of Tanzania located between latitude 10 30’ and 30 south of the Equator. Longitudinally the region is located between 310 450 and 430 10’ east of Greenwich, the northern part of the region is surrounded by the waters of Lake Victoria, locally known as Lake Nyanza. That water in turn separates the region from the neighbouring countries of Kenya and Uganda. To the west is Kagera region while the South and Southern parts border Shinyanga region, Mara region borders Mwanza in the northeast. The region is divided into eight districts namely Ukerewe, Magu, Kwimba, Sengerema, Geita, Missungwi, Ilemela and Nyamagana. The region headquarters is located in Nyamagana District. 1.3 Land Area The region has an area of 35,187 sq.km: out of this area, 20,095 sq.km is dry land and 15,092 sq.km is covered by Lake Victoria. 1.4 Climate 1.4.1 Temperature The temperature in the region is to some extent influenced by Lake Victoria, about 250 to 280C being generally the average maximum temperature from September to December. The cool dry season from June to August experiences low temperatures which range between 200 - 110 .. 1.4.2 Rainfall The average annual rainfall of Mwanza region is about 930mm varying from 1,800mm in the western parts of Ukerewe Island to 570 mm.Under normal conditions the rainfall is distributed mainly during two periods, namely the short rains in October-December and long-rains from March to May. There is a dry spell from January to March. 1.5 Population Mwanza region has the largest population of any region in Tanzania. It has a population of 2,929,644 according to the 2002 population census BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TSh 835,048 million with a per capita income of shillings 277,556 . The region held 6th position among regions on GDP and contributed about percent to the national GDP The main economic activities carried out by Mwanza region’s population are agricultural production, livestock keeping and to significant extent fishing. There is no commercial farming in the region. Subsistence farming is the main form of farming. Mwanza region posses great development potential and which is relatively well developed, the region is connected to the other part of the country by road, rail, water and air networks. BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2.1 Introduction This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.2 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.3 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.4 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Mwanza region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labor use • Access to infrastructure and other services • Household facilities BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.5 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.6 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.7 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 2.7.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), supervised the overall operational aspects of the Census and guidance was provided by the Agriculture Sample Census Consultant. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.7.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.7.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 2.7.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during than training • Enumerator Instruction Manual which was used as reference material. 2.7.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Mwanza, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.7.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.7.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.7.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.7.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.7.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 2.7.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR Extraction Technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. BACKGROUNG INFORMATION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 Analysis and Report Preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.8 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Services and the Food and Agriculture Organisation (FAO). RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the census results for Mwanza region, based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and Maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Mwanza region was 340,085.The largest number of agriculture households was in Geita (93,286) followed by Sengerema (64,661), Magu (56,360) Kwimba (45,813) Missungwi (34,132) Ukerewe (32,909) and Ilemela (12,922) (Map 1). The highest density of households was found in Missungwi (40km2) and Geita (33/km2) (Map 3.2). Most households (197,780, 58%) were involved in growing crops only, 1,156 (0.3%) rearing livestock only, and 141,149, (41.5%) were involved in crop production as well as livestock keeping. There were no pastoralists in Mwanza Region. (Chart 3.1 and Map 3.1, 3.2, 3.3 and 3.6) Table 3.1: The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District 3.1.2 Livelihood Activities/Source of Income The census results for Mwanza region indicates that most of the agricultural households ranked annual crop farming as an activity that provided most of their livelihood followed by off farm income, permanent crop farming, tree/forest resources, Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt- ances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 2 1 4 3 7 5 6 Magu 1 4 5 3 6 7 2 Kwimba 1 5 4 2 6 7 3 Sengerema 1 2 5 3 7 6 4 Geita 1 4 5 3 6 7 2 Missungwi 1 2 5 4 6 7 3 Ilemela 1 2 5 3 7 6 4 Total 1 3 5 2 7 6 4 Chart 3.1 Agriculture Households by Type -Mwanza Pastoralist 0% Livestock Only 0.3% Crops Only 58.2% Crops and Livestock 41.5% Missungwi Ilemela Sengerema Magu Kwimba Nyamagana Ukerewe 29 40 33 17 26 14 0 29 Geita 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Nyamagana Ilemela Kwimba Missungwi Sengerema Geita Magu Ukerewe 0 12,922 45,813 34,132 64,661.4 93,286 56,360 32,908.7 74,800 to 93,300 56,100 to 74,800 37,400 to 56,100 18,700 to 37,400 0 to 18,700 Total Number of Agricultural Households by District Number of Agriculture Households MAP 3.1 MWANZA Agricultural Households Per Square Km MAP 3.2 MWANZA Number of Agricultural Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Agriculture Households Agricultural Households Per Square Km RESULTS AND ANALYSIS 12 Ukerewe Geita Missungwi Kwimba Nyamagana Ilemela Sengerema Magu 32,909 92,866 34,132 0 45,813 12,827 64,533 55,848 76,000 to 93,000 57,000 to 76,000 38,000 to 57,000 19,000 to 38,000 0 to 19,000 Geita Ilemela Nyamagana Kwimba Missungwi Magu 29.4% 4.2% 13.2% 0% 9.2% 19% 17.7% 7.3% Sengerema Ukerewe Number of Crop Growing Households by District Number of Crop Growing Households MAP 3.3 MWANZA Percent of Crop Growing Households MAP 3.4 MWANZA Percent of Crop Growing Households by District Number of Crop Growing Households Percent of Crop Growing Households 23.6 to 29.4 17.7 to 23.6 11.8 to 17.7 5.9 to 11.8 0 to 5.9 Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 13 Geita Missungwi Kwimba Nyamagana Ilemela 24.5 11.3 0 14 3.2 19.1 14.8 13.1 Sengerema Magu Ukerewe 19.6 to 24.5 14.7 to 19.6 9.8 to 14.7 4.9 to 9.8 0 to 4.9 Ukerewe Kwimba Missungwi Geita Sengerema Ilemela Nyamagana Magu 14 17 26 29 29 40 33 0 Percent of Crop and Livestock Households Percent of Crop and Livestock Households 46.4 to 58 34.8 to 46.4 23.2 to 34.8 11.6 to 23.2 0 to 11.6 Number of Crop Growing Households Per Square Kilometer of Land by District Number of Crop Growing Households Per Square Km MAP 3.5 MWANZA MAP 3.6 MWANZA Percent of Crop and Livestock Households by District Number of Crop Growing Households Per Square Km Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 14 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 livestock keeping/herding, fishing/hunting & Gathering and remittances (Table 3.1). Ukerewe district was the district where annual crop farming was not the most important livelihood activity and was replaced by permanent crop farming. 3.1.3 Sex and Age of Heads of Households The number of male-headed agriculture households in Mwanza region was 286,000 (84% of the total regional agricultural Households) whilst in female- headed households it was 54,000 (16% of the total regional agricultural households). The mean age of household heads was 47 years (46 years for males and 52 years for female heads) (Chart 3.2). The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Mwanza region had a total rural agricultural Population of 2,134,382 of which 1, 082,746, (50.7%) were males and 1,051,636 (49.3%) were females. Whereas age group 0-14 constituted 45.2 percent of the total rural agricultural population, age group 15-64 (active population) was 50.7 percent. Mwanza region had an average household size of 6 with Ilemela district having the lowest households’ size of 4. (Chart 3.3) 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 20 40 60 80 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Ye a r Male headed households Female headed households Chart 3.3 Percent age Distribution of Population by Age and Sex - MWANZA 0 6 12 18 24 Ag e Gro up P e r c e n t Male Female RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Literacy Level for Household Members Mwanza region had a total literacy rate of 64 percent. The highest literacy rate was found in Ukerewe district (73.0%) followed by Magu district (71.4%), Sengerema district (65.2%), Missungwi district (65.0%), Ilemela district (64.0%), Kwimba and Geita had the lowest literacy rates of 60.3 and 59.3 percent respectively. Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 64.7 percent. The literacy rates among the male and female heads of households were 70.6 and 33.8 respectively. Male head of household literacy rate was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Ukerewe (85.2%) followed by Sengerema (74.8%), Magu (73.7%), Ilemela (70.7%), Geita (66.5%), Missungwi and Kwimba had (66.1%) and (61.3%) respectively (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 38.0 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 29.1 percent were still attending school. Those who have never attended school were 32.9 percent (Chart 3.6). Agricultural households in Ukerewe district had the highest percentage (46.7%) of population aged 5 years and above who had completed different levels of education. This was followed by Missungwi district (40.1%), Magu district (39.3%), Ilemela district (38.9%), Sengerema district (37.7%), Kwimba and Geita districts had the lowest percentage of 36.0 and 34.6. Chart 3.5 Literacy Rates of Head of Household by Sex and District - Mwanza. 0.0 25.0 50.0 75.0 100.0 District Percent Male Female Total Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.0% Never Attended 32.9% Attending School 29.1% Chart 3 .7 Pe rc e nt ag e o f Po p ulat io n Ag e d 5 Ye ars and A b o ve b y D is t ric t and Ed uc at io nal S t at us 0.0 10.0 20.0 30.0 40.0 50.0 Dis t ri c t Attending School Completed Never Attended Chart 3.4 Percentage Literatecy Level by District 0.0 20.0 40.0 60.0 80.0 Ukerewe Magu Sengerema Missungwi Ilemela Kwimba Geita Districts P ercen t RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 The number of heads of agricultural households with formal education in Mwanza region was 213,880 (62.9%), those without formal education were 126,204 (37.1%) and those with only adult education were 5,144 (1.5%). The majority of heads of agricultural households (59.1%) had primary level education whereas only 0.1% had University education (Chart 3.8). With regard to the heads of agricultural households with primary or secondary education in Mwanza region, Ukerewe district had the highest percentages (75.7% for primary and 2.4% for secondary). This was followed by Sengerema (61.9% primary and 4.4% secondary), Magu (61.5% primary and 2.9% secondary), Geita (56.7% primary and 2.1% secondary). Ilemela (55.9% primary and 2.7% secondary), Missungwi (53.4%, primary and 3.5% secondary) and Kwimba had the lowest percentage of heads of agricultural households with primary education (50.3%) and secondary education (2.5%) 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Mwanza with 68.5% of households having at least one member with off-farm income. In Mwanza region 157,655 households (67.5%) had only one member aged 5 and above involved in an off-farm income generating activity, 50,366 households (21.6%) had two members involved in off-farm income generating activities and 24,841 households (10.7%) had more than two members involved in off-farm income generating activities. The districts with highest percentage of households with off-farm income were Kwimba and Ilemela followed by Magu, Ukerewe, Missungwi, Missungwi, Sengerema and Geita. The district with the highest percent of agriculture households with more than two members with off-farm income was Kwimba (14.2), Magu (14.1), Sengerema (10.1), other District had very few households with more than two members having off-farm income. Chart 3.9 Percentage Distribution of Household Members of Five Years and Above by Number of Off-farm Activities More than Two Off Farm Income 24,841,11% One Off Farm Income 157,655,68% Two Off Farm Income 50,366,22% Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Secondary Education 3% University Educution 0.1% Post Secondary Education 1% Adult Education 1.5% Post Primary Education 0.2% No Education 35.6% Primary Education 59.1% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Household Members with off-farm Activities 0% 20% 40% 60% 80% 100% Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela Districts Percent Mo re than Two Two One No ne RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 3.2 Land Use Land area and planted area are different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total of all areas planted with crops in a year and the areas are summed if there were more than one crop on the same in ar year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that had been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agricultural land in the country; Instead it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused through designated of agricultural land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 864,585 ha, and 845,350 excluding area unusable. At Regional level the average land area utilised for agriculture per household was only 2.0 ha. This figure is equivalent to the national average which was estimated at 2.0 hectares. 81% of the land available to smallholders was utilised. Only 13.5 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). There were small differences in land utilization per household between districts with Sengerema and Ilemela utilizing 2.3 ha per household. The smallest land area utilised per household was found in Geita (1.8ha). The percentage utilized of the usable land per household is highest in Ilemela (92.9%) and lowest in Magu, where 85.1% of the total land available to smallholders was utilised and only 14.9% of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela Districts Area/household 80 82 84 86 88 90 92 94 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.12 Percentage Distribution of Land Area by Type of Land Use 0.7 0.7 1.4 1.4 2.0 2.1 5.0 10.1 12.0 16.2 19.8 28.7 0 5 10 15 20 25 30 35 Natural Bush Fallow Rented to Others Pasture Permanent Mixed Area Unusable Planted Trees Permanent Mono Crops Uncultivated Usable Land Permanent / Annual Mix Crops Temporary Mono Crops Temporary Mixed Crops Type of Land Use Percent Kwimba Nyamagana Magu Missungwi Geita Ilemela 83.3ha 82.8ha 0ha 83.1ha 82.9ha 90.7ha 86.8ha 88.6ha Sengerema Ukerewe Ilemela Nyamagana Kwimba Missungwi Ukerewe 14,979ha 0ha 84,679ha 116,345ha 186,958ha 120,102ha 34,599ha 121,444ha Sengerema Geita Magu 72.4 to 90.7 54.3 to 72.4 36.2 to 54.3 18.1 to 36.2 0 to 18.1 Utilized Land Area Expressed as a Percent of Available Land by District Utilized Land Area (ha) MAP 3.7 MWANZA Planted Area (ha) MAP 3.8 MWANZA Total Planted Area (Annual Crops) by District 148,000 to 187,000 111,000 to 148,000 74,000 to 111,000 37,000 to 74,000 0 to 37,000 Utilized Land Area Expressed in Percent of Available Land Area Planted Annual Crops Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 19 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 3.2.2 Types of Land Use The area of land under temporary mix was 242,740 hectares (28.7% of the total land available to smallholders in Mwanza), followed by temporary mono crop (167,575 ha, 19.8%), permanent/annual mix (136,569 ha, 16.2%), uncultivatable usable land (101350 ha, 12.0%), permanent mono crop (85,472 ha, 10.1%), planted trees (42,153 ha, 5.0%), unusable area (7446 ha, 2.1%), (permanent mixed 16520 ha, 2.0%), pasture (11,950 ha, 1.4%), rented to others (11584 ha, 1.4%),fallow (6060 ha, 0.7%) and natural bush (5645 ha, 0.7%). 3 Annual Crops and Vegetable Production Mwanza region has two rainy seasons, namely the short rainy season (October to December) and the long rainy season (March to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 679,107 hectares out of which 438,178 hectares (65%) were planted during short rainy season and 240,929 hectares (35%) during long rainy season. The average areas planted per household during the short and long rainy seasons was 0.5 and 0.7 ha respectively (Chart 3.13). The districts with the largest area planted per household (the average of the two seasons) were Kwimba (0.8 ha) followed by Magu and Geita each with (0.7ha), Missungwi (0.6ha), Ukerewe and Ilemela with (0.77 ha). The district with the smallest average area planted was Sengerema (0.5 ha) While in Magu district the average area planted during the short rainy season is higher than that of the long rainy season the reverse is true in the rest of the districts. (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 315,648 ha, (46.5 %of the total area planted with annuals). This was followed by root and tubers 176,633 hectares, (26.0%), cash crops 86,938 hectares, (12.8%), pulses 77,041 hectares, (11.3%), oil seeds 19,501 hectares, (2.9%), and fruits and vegetables (3,286 hectares (0.5%). The average area planted per household during the long rainy season in Mwanza region was 0.7 hectares, however, there were large district differences. Kwimba had the largest planted area per household (1.0 ha) followed by Magu (0.8 ha) and Geita and Missungwi both had (0.7 ha.) The smallest planted area per household is in Ilemela (0.4 ha.) In Kwimba the area planted per household in the short rainy season represents 62 percent of the total planted area per household, whereas in Ilemela the corresponding figure is 20 per cent. (Chart 3.15 and Map 3.9). Chart 3.13 Area Planted with Annual Crops by Season (hectares) Short Rain Season, 438,178, 65% Long Rain Season, 240,929, 35% Short Rain Season Long Rain Season Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Ukerewe Magu Kwimba Sengerema Geita Misungwi Ilemela A rea Plan ted (h a) 0.00 20.00 40.00 60.00 80.00 Percentage Plan ted Short Rainy Season Long Rainy Season % Area planted in short rainy season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 1.00 2.00 Kwimba Magu Geita Missungwi Sengerema Ilemela Ukerewe District Area Planted (ha) Long Rainy Season Short Rainy Season RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of all crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance The area planted with annuals was 679,107 ha. Maize is the dominant annual crop grown in Mwanza region and it had a planted area 208,512 ha (31% of the total area planted with annual crops in the region), followed by cassava with a planted area of 141,223 ha. Other crops in order of their importance (based on area planted) are paddy, cotton, sweet potatoes, beans and groundnuts (Chart 3.16). Households that grow cotton, paddy, maize and sorghum have larger planted areas per household than for other crops (Chart 3.17). 3.3.3 Crop Types Cereals are the main crops grown in Mwanza region. The area planted with cereals was 315,648 ha (46.5% of the total area planted with annual crops), followed by root & tubes with 176,633 ha (26.0%), cash crop 86,938 ha (12.8%), Pulses 77,101 ha (11.3%) and oil seeds 19,501 ha (2.9%). Fruit and Vegetables had got the least planted area of about 3,286 ha (0.5%), (Chart 3.17). Cereals and root and tubers are the dominant crops and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.17 Planted Area (ha) per Household for Selected Crop 0.00 0.50 1.00 1.50 2.00 Cotton Paddy Maize Sorghum Irish Potatoes Cocoyam Groundnuts Green Gram Yams Tomatoes Sunflower Cowpeas Carrot Beans Water Mellon Simsim Chillies Crop Planted Area (ha) Chart 3.16 Planted Area (ha) for the Main Annual Crops 0 100,000 200,000 300,000 Maize Cassava Paddy Cotton Sweet Potatoes Beans Groundnuts Sorghum Green Gram Cowpeas Finger Millet Tomatoes Bambaranuts Crop Planted Area (ha) Chart 3.18: Percentage Distribution of Area Planted with Annual Crops by Crop Type Oil seeds & Oil nuts, 2.9% Roots & Tubers, 26.0% Fruits & Vegetables, 0.5% Cash crops, 12.8% Pulses, 11.4 % Cereals, 46.6% Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 3.3.4 Cereal Crop Production The total production of cereals was 244,466 tonnes. Maize was the dominant cereal crop at 150,804 tonnes which was 61.7 percent of total cereal crops produced, followed by paddy 81,805 tonnes (33.4%), sorghum 8,271 tonnes (3.4%), finger millet 2393 (0.9%) and bulrush millet 1192 tonnes (0.5%), (Map 3.10). The total area planted with cereals was 315,648 ha out of which 262,198 ha (83.1%) were planted in the short rainy season and 51,450 ha (16.9%) were planted during the long rainy season. The long rainy season accounted for 21 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 75% of the total area planted with cereals in that season followed by paddy (20%) and Sorghum (4%) (Table 3.2). The area planted with maize was dominant and it represented 66.1% of the total area planted with cereal crops, then followed by paddy (27.6%), sorghum (4.1%), finger millet and bulrush millet with (1.1%), each. The yield of paddy was 938 kg/ha, followed by maize (723 kg/ha), finger millet (709 kg/ha) and sorghum (638 kg/ha) and bulrush millet (334 kg/ha). Maize The number of households growing maize in Mwanza region during the long rainy season was 18,906 (23.9% of the total annual crops growing households in the region during the long rainy season). The total production of maize was 150,804 tonnes from a planted area of 208,512 hectares resulting in a yield of 0.7 t/ha. Geita had the highest area planted with maize (64,083ha), followed by Magu and Kwimba. Ilamela and Ukerewe only had a small planted area of maize (Chart 3.21). The average area planted with maize per household was 0.7 hectares; however it ranged from 0.2 hectares in Ukerewe district to 0.9 hectares in Kwimba district. Geita district had the largest area of maize (64,083 ha) followed by Magu (40,412 ha), Kwimba (39,709 ha), Sengerema (32,278 ha), Missungwi (26,675 ha), Ilemela (3,737 ha) and Ukerewe(1,617 ha).(Chart 3.21 and Map 3.11 and 3.12) Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 195,556 142,605 729 12,956 8,199 633 208,512 150,804 723 Paddy 51,928 42,906 826 35,303 38,899 1,102 87,231 81,805 938 Sorghum 10,556 6,698 635 2,401 1,573 655 12,957 8,271 638 Finger Millet 2,468 1,202 487 908 1,191 1,312 3,376 2,393 709 Bulrush Millet 1690 509 300 1982 684 363 3572 1193 334 Total 262,198 193,920 53,450 50,546 315’648 244,466 Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 1,617 3,737 26,675 32,278 39,709 40,412 64,083 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Geita Magu Kwimba Sengerema Missungwi Ilemela Ukerewe District Area (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.20 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 200,000 250,000 Maize Paddy Finger Millet Sorghum Crop Area Planted (ha) 0.00 0.20 0.40 0.60 0.80 1.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Nyamagana Magu Missungwi Ilemela Kwimba Ukerewe 0ha 5,427ha 52,358ha 48,042ha 49,575ha 93,500ha 63,734ha 3,013ha 0% 1.7% 16.6% 15.2% 15.7% 29.6% 20.2% 1% Sengerema Geita Nyamagana Ilemela Magu Kwimba Missungwi 6,153ha 89,481ha 56,631ha 78,941ha 135,878ha 64,538ha 6,557ha 1.4% 20.4% 12.9% 18% 31% 14.7% 1.5% Sengerema Geita Ukerewe 0% 76,000 to 94,000 57,000 to 76,000 38,000 to 57,000 19,000 to 38,000 0 to 19,000 108,000 to 136,000 81,000 to 108,000 54,000 to 81,000 27,000 to 54,000 0 to 27,000 Area Planted and Percentage During the Short Rainy Season by District Area Planted (ha) MAP 3.9 MWANZA Area Planted (ha) MAP 3.10 MWANZA Area Planted With Cereals and Percent of Total Land Planted With Cereals by District Area planted (ha) Percentage of Area Planted Area Planted (ha) Percent of Area Planted Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 23 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 24 Chart 3.22 indicates maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. There was a sharp increase in maize production between the period of 1998 to 1999 and 2000 to 2002. Show that, the yield of maize decreased sharply from 1996/97 to 1997/98 and remained constant at this lower level over the period 1997 to 2003 this shows that the increase in production was due to an increase in planted area and not to an increase in yield (Charts 3.22 and Map 3.12). Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Mwanza region during the short and long season were 77,984 and 52,338 respectively. These represent 24.2% and 43.7% of the total annual crop growing households in the respective seasons. The total production of paddy was 81,805 tonnes from a planted area of hectare 87,231 resulting in a yield of 0.9 t/ha. The district with the largest area planted with paddy was Missungwi (24,726 ha) followed by Kwimba (20,641 ha), Sengerema (15,371 ha), Ilemela (14,865 ha), Magu (8,826 ha), Ukerewe (1534 ha) and Geita (1,268 ha) (Chart 3.24 and Map 3.13 and 3.14). The production of paddy since 1995 has fluctuated erratically. The production rose from 34,000 tonnes in 1996/97 to 104,000 tonnes in 1998/99 after which it dropped to 61,000 tonnes in 2000. Charts 3.26 shows that, the yield of paddy dropped between 1995/96 and 1997/98, after which it started Chart 3.22: Time Series Data on Maize Production 84 14 20 109 151 18 133 0 20 40 60 80 100 120 140 160 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year P r o d u c t io n ( '0 0 0 ') t o n n e s Chart 3.23 Time Series of Maize Planted Area & Yield 0 100000 200000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Area Yield Chart 3.25 Time Series Data on Paddy Production 67 104 82 104 91 34 61 0 20 40 60 80 100 120 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.24 Total Planted Area and Area of Paddy per Household by District 24,726 20,641 15,371 14,865 8,826 1,534 1,268 0 5,000 10,000 15,000 20,000 25,000 30,000 Geita Kwimba Sengerema Missungwi Magu Ilemela Ukerewe District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 Area planted per household Planted Area (ha) Area planted/hh Nyamagana Ilemela Kwimba Geita Sengerema Magu Ukerewe 3,737ha 39,709ha 26,675ha 64,083ha 32,278ha 40,412ha 1,617ha 0t/ha 1t/ha 0t/ha 1t/ha 1t/ha 1t/ha 1t/ha 1t/ha Missungwi 0ha 52,000 to 65,000 39,000 to 52,000 26,000 to 39,000 13,000 to 26,000 0 to 13,000 Nyamagana Kwimba Missungwi Ilemela 0 0.8 0.9 0.3 0.7 0.8 0.5 0.2 Sengerema Geita Magu Ukerewe 0.8 to 0.9 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Planted Area and Yield of Maize by District Planted Area (ha) MAP 3.11 MWANZA Area Planted Per Household MAP 3.12 MWANZA Area Planted Per Maize Growing Household by District Area Planted (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 25 Kwimba Missungwi Nyamagana Ilemela 0.7 0.6 0.8 0 0.3 0.8 0.6 0.2 Sengerema Geita Magu Ukerewe Nyamagana Missungwi Kwimba Ilemela Magu 15,371ha 24,726ha 20,641ha 8,826ha 14,865ha 1,534ha 1,268ha 0t/ha 1t/ha 1t/ha 1t/ha 1t/ha 1t/ha 1t/ha 2t/ha Sengerema Geita Ukerewe 0ha Planted Area and Yield of Paddy by District Planted Area (ha) MAP 3.13 MWANZA 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Area Planted (ha) Area Planted Per Household MAP 3.14 MWANZA Area Planted Per Paddy Growing Household by Disrtict Tanzania Agriculture Sample Census Yield (t/ha) 0.8 to 0.8 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household RESULTS AND ANALYSIS 26 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 increasing up to 1999/00 years, then declined a sharply over the period up to 2002/03. The Yield of paddy has increased by around 0.5 t/ha, however it is the change in planted area that determines the fluctuation in production. And increases in production are a result of increases in planted area and not due to a greater productivity. Other Cereals In terms of area planted in other Cereals production, Bulrush millet was the least important crop compared to sorghum and finger millet in the region. There was no bulrush millet production reported in Magu, Kwimba, Geita and Ilemela districts. (Chart 3.27 and Map 3.15). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 252,312 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 204,303 tonnes representing 81.0 percent of the total root and tuber crops production. This was followed by Sweet potatoes with 47,091 tonnes (18.7%), the remaining other crops contribute less than 1% of the total production of roots and tubers. The area planted with cassava was larger than any other root and tuber crops (80.0% of the total area planted with roots and tubers), followed by sweet potatoes (19.7%), and the remaining roots and tubers had less than (1%) Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported mainly under the long rainy season. Table 3.3: Area Planted and Quantity Harvested by Season and Type of Root and tuber Crop Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 1,443 2,238 1,551 139,780 202,065 1,446 141,223 204,303 1,447 Sweet Potatoes 23,491 31,770 1,352 11,227 15,321 1,365 34,718 47,091 1,356 Irish Potatoes 304 319 1,049 83 78 940 387 397 1,026 Yams 241 460 1,909 0 0 0 241 460 1,909 Cocoyam 0 0 0 66 61 924 66 61 924 TOTAL 25,479 34,787 151,156 217,525 176,635 252,312 Chart 3.26 Time Series of Paddy Planted Area and Yield 0 20000 40000 60000 80000 100000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Planted Area Yield 0 500 1,000 1,500 2,000 2,500 3,000 3,500 Area (Ha) Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela District Chart 3.27 Area Planted with Sorghum, Fingermillet and Bulrush millet by District Sorghum Fingermillet Bulrush Millet Chart 3.28 Area Planted and Yield of Major Root and Tuber Crops 0 75,000 150,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 750 1,500 Yield (kg/ha) Yield (kg/ha) RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 28 It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava has been reported under the long rainy season. However, excluding cassava, 3.7 percent of the area planted with roots and tubers was during the short rainy season with sweet potatoes having 3.4 percent of its production in the short rainy season. There was no production of cocoyams during the short rainy season. There was a significant increase in area planted with cassava and sweet potatoes from 1994/95 to 2002/03. The area for cocoyams and yams remained more or less constant. Cassava The number of households growing cassava in the region was 192,722. This represents 57 percent of the total crop growing households in the region. The total production of cassava during the census year was 204,303 tonnes from a planted area of 141,223 hectares resulting in a yield of 1.4t/ha. Previous censuses and surveys indicate that the area planted with cassava increased over the period 1995 to 1999 (Chart 3.29a). The area planted with cassava accounted for 21 percent of the total area planted with annual crops and vegetables in the census year. Sengerema district had the largest planted area of cassava (38,868 ha, 27.5% of cassava planted area in the region). followed by Geita (34,992 ha, 24.8%), Ukerewe (23,933 ha, 16.9%), Magu (19079 ha, 13.5%),Missungwi (10,185 ha,7.2%), Kwimba (8,390 ha,5.9%) and Ilemela (5776 ha, 4.1%) (Chart 3.29 b and Map 3.15 and 3. 16). The average cassava planted area per cassava growing household was 0.7 hectares. However, there were large district variations. The area planted per cassava growing household was greatest in Missungwi (1.00 ha). This was followed by Geita (0.87 ha), Magu (0.85 ha), Sengerema (0.75 ha), Ukerewe (0.73 ha), Kwimba (0.58 ha) and Ilemela (0.56 ha) (Chart 3.30 ). 1.00 0.87 0.85 0.75 0.73 0.58 0.56 0.000 0.200 0.400 0.600 0.800 1.000 Area per Household Missungwi Geita Magu Sengerema Ukerewe Kwimba Ilemela District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.29 b Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 27.7 24.5 17.0 13.5 7.3 6.0 4.1 0 15 30 45 Sengerema Geita Ukerewe Magu Missungwi Kwimba Ilemela District Percent of Total Area Planted 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land Chart 3.29a Area Planted with Cassava During the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava Nyamagana Misungwi Kwimba Ilemela Magu 5,775.7ha 8,391.6ha 10,184.5ha 34,991.6ha 38,867.5ha 19,078.6ha 23,933ha 0t/ha 2t/ha 2t/ha 1t/ha 1t/ha 2t/ha 1t/ha 2t/ha Sengerema Geita Ukerewe 0ha Sengerema Ukerewe Nyamagana Misungwi Kwimba Ilemela Magu 0.7 0.7 0 0.5 0.6 0.9 0.6 0.8 Geita 0.8 to 0.9 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 32,000 to 39,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Planted Area and Yield of Cassava by District Planted Area (ha) MAP 3.15 MWANZA Area Planted Per Household MAP 3.16 MWANZA Area Planted Per Cassava Growing Household by Disrtict Tanzania Agriculture Sample Census Area planted (ha) Yield (t/ha) Area Planted Per Household RESULTS AND ANALYSIS 29 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 Sweet Potatoes The number of households growing sweet potatoes in Mwanza region was 142,010. This was 42%% of the total root and tuber crop growing households during both seasons. The total production of sweet potatoes during the census year was 47,091 tonnes from a planted area of 34,718 hectares resulting in a yield of 1.3t/ha. Sengerema District has the largest planted area of Sweet potatoes (7,094 ha, 20.4%), followed by kerewe (6676 ha, 19.2%), Magu (5,42 ha 15.1%) Kwimba (5025ha 14.5%), Missungwi (4766 ha,13.7%), Geita (4,595 ha, 13.2%) and Ilemela (1,321 ha, 3.8%). (Chart 3.31 and Map 3.17 and Map 3.18). Other root and tuber crops are of minor important in terms of area planted compared to cassava and Sweet potatoes. 3.3.6 Pulse Crops Production: Table 3.4. Area Quantity Harvested and Yields of Pulses by Season The total area planted with pulses was 77,968 hectares out of which 32,544 ha were planted with beans (42.2 percent of the total area planted with pulses), followed by chick peas 29,895 ha, (38.3%), green gram 8,728 ha, (11.3%), cow peas 4,845 ha, (6.3%), bambara nuts 559 ha, (1.2%). and field peas 131 ha (0.2%). Mung beans was not cultivated in the region (Chart 3.32). The area planted with pulses in the short rainy season was 44,743 ha which represents 58.0 percent of total area planted with pulses during the year. Chick peas was the most dominant pulse crop during long rainy season with 29,738 ha (91.9 % of the total area planted with pulses in that particular season), followed by beans 1,679 ha, (5.2%), cow peas 467 ha, (1.4%), green grams 285 ha (0.9%) and bambaranuts 190 ha (0.6%). On the other hand beans were the most important pulse crop grown in the long rainy season with a polanted area of 30,865ha and a production of 12,575 tonnes. Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 30,865 12,575 407 1,679 642 382 32,544 13,217 406 Cowpeas 4,378 1,509 345 467 149 319 4,845 1,658 342 Green Gram 8,443 2,362 280 285 71 249 8,728 2,433 279 Chick Peas 157 142 904 29,738 15,090 507 29,895 15,232 510 Bambaranuts 769 414 538 190 64 337 959 478 498 Field Peas 131 14 107 0 0 0 131 14 107 TOTAL 44,612 17,002 33,356 16,142 77,101 33,144 Chart 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 1,321 4,595 4,766 5,025 5,242 6,676 7,094 0 5,000 10,000 Sengerema Ukerewe Magu Kwimba Missungwi Geita Ilemela District Area (Ha) 0 0.2 0.4 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Beans Chich Peas Green Gram Cowpeas Bambaranuts Field Peas Crop Area Planted (ha) 0 100 200 300 400 500 600 Yield (kg/ha) Yield (kg/ha) Ilemela Magu Missungwi Kwimba Nyamagana 0.2 0.2 0.3 0.3 0.3 0 1.9 0.3 Sengerema Geita Ukerewe Nyamagana Missungwi Kwimba Magu Ilemela 4,766ha 5,025ha 6,676ha 5,242ha 1,321ha 4,595ha 7,094ha 1t/ha 0.7t/ha 1.8t/ha 0t/ha 1.7t/ha 1.2t/ha 1.2t/ha 1.8t/ha Sengerema Geita Ukerewe 0ha Planted Area (ha) MAP 3.17 MWANZA Area Planted Per Household MAP 3.18 MWANZA Area Planted per Sweet Potatoes GrowingHousehold by District Tanzania Agriculture Sample Census Planted Area and Yield of Sweet Potatoes by District 8,000 to 8,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Area Planted (ha) Yield (t/ha) 1.6 to 1.9 1.2 to 1.6 0.8 to 1.2 0.4 to 0.8 0 to 0.4 Area Planted Per Household RESULTS AND ANALYSIS 31 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 The total production of pulses was 33,032 tonnes. Beans Chick peas accounts for most production at 15,232 tonnes (41.1 percent of total pulse production). This was followed by beans (13,217t, 40.0%), green gram (2,433t, 7.3%), cow peas (1,658t, 5.0%), bambaranuts (478t, 1.4%) and field peas (14t, 0%). (Table 3.4). Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Mwanza region was 131,803. The total production of beans in the region was 13,217 tonnes from a planted area of 32,544 hectares resulting in a yield of 0.4 t/ha. While Geita had the largest area under beans with 17,055 hectares (Chart 3.33), the largest area planted with beans per household was in Missungwi district (0.48 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.2 ha. The variations in area planted with beans per household for the rest of the districts were relatively small ranging from 0.17 to 0.27 ha, (Map 3.19 and Map 3.20) In Mwanza region, bean production has increased steadily over the period 1998 to 2003 from 1,000 tonnes in 1998 to 13,000 tonnes in 2003 (Chart 3.35). The area planted with beans increased erratically over the period from 1996 to 2003.except in 2000 when both the area planted and production dropped (Chart 3.36). Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 Geita Sengerema Magu Missungwi Ilemela Ukerewe Kwimba District Percent of Land 0 20 40 60 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.36 Time Series of Beans Planted Area & Yield 0 5000 10000 15000 20000 25000 30000 35000 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Area Yield 0.48 0.27 0.21 0.17 0.12 0.12 0.10 0.00 0.25 0.50 Area per Household Missungwi Magu Sengerema Ilemela Ukerewe Kwimba Geita District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.35: Time Series Data on Beans Production 6 4 13 33 0.8 0 5 10 15 20 25 30 35 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Nyamagana Ilemela Sengerema Magu 203ha 358ha 87ha 7,247ha 3,983ha 1,163ha 177ha 0t/ha 25t/ha 18t/ha 21t/ha 0t/ha 2t/ha 5t/ha 8t/ha Geita Kwimba Missungwi Ukerewe 0ha 6,000 to 7,300 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Ukerewe Missungwi Nyamagana Ilemela Kwimba 0.4 0.3 0.3 0.2 0.3 0.4 0.4 Sengerema Geita Magu 0 Planted Area and Yield of Beans by District Planted Area (ha) MAP 3.19 MWANZA Area Planted Per Household MAP 3. 20 MWANZA Area Planted Per Beans Growing Household by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) 0.4 to 0.4 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household RESULTS AND ANALYSIS 33 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.7 Oil Seed Production The total production of oilseed crops was 10,091 tonnes planted on an area of 19,501 hectares.. The total planted area of oilseeds in the short rainy season was 18,864 ha representing 96.7 percent of the total area planted with oil seeds. Groundnuts were the most important oilseed crop with 18,933 ha (97.1% of the total area planted with oil seeds), followed by simsim (1.6%), soya beans (0.7%), sunflower (0.2%) and castor seed (0.1%) (Table 3.5). The yield of castor seed was relatively high (12,861 kg/ha). simsim had a yield of 639 kg/ha, groundnuts 496 kg /ha and sunflower 424 kg/ha . Groundnuts The number of households growing groundnuts in Mwanza region was 59,101. The total production of groundnuts in the region was 9,388 tonnes from a planted area of 18,933 hectares resulting in a yield of 0.5 t/ha.There has been a large decrease in production of groundnuts over the period 2002 to 2003, from 25,300 tonnes in 2001/02 to 17,200 tonnes in 2002/03. Area planted decreased from 29,300 hectares in 2000/01 to 19,000 hectares in 2002/03. Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 66 28 424 0 0 0 66 28 424 Simsim 266 181 680 58 26 448 324 207 639 Groundnuts 18,367 9,208 501 566 180 318 18,933 9,388 496 Soya Beans 142 5 35 0 0 0 142 5 35 Castor Seed 23 285 12,391 13 178 13,692 36 463 12,861 Total 18,864 9,707 637 384 19,501 10,091 Chart 3.38: Time Series Data on Groundnuts Production 25.3 17.2 24.5 0 15 30 2000/01 2001/02 2002/03 Year Production (000) tons Chart 3.37 Area Planted and Yield of other Major Oil Seed Crops 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 Groundnuts Simsim Sunflower Soya Beans Castro Seeds Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 The district with the largest groundnuts planted area was Geita with 7825 hectares (41.3 percent of the total area planted with groundnuts in the region) followed by Kwimba (5,677 ha, 30.0%), Sengerema (2439 ha, 12.9%), Missungwi (2,325 ha, 12.3%), Magu (601 ha, 3.2%), Ilemela (42 ha, 0.2%) and Ukerewe (24 ha, 0.1%). The highest proportion of land with groundnuts was found in Kwimba followed by Geita, Missungwi, Sengerema,Magu Ilemela and Ukerewe (Chart 3.39 and Map 3.19). The largest area planted per groundnut growing household was found in Kwimba District (0.43 ha) and the lowest planted area was in Ilemela (0.13ha) (Chart 3.40 and Map 3.22). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short rainy season is relatively important for fruits and vegetables production since 56 percent of the total area planted with fruit and vegetables was during this season. For tomatoes, onion, cabbage, water melon, ginger, and pumpkin over 50 percent of the planted area was during the short rainy season. Reliable historical data for time series analysis of fruits and vegetables are not available. The total production of fruit and vegetables was 16,817 tonnes. The most cultivated fruit and vegetable crop was tomato with a production of 10,715 tonnes. followed by onions (1,664t),cabbage (1,547t). The production of the other fruits and vegetables crops was relatively small (Table 3.6). Chart 3.42 Area Planted and Yield of Fruits and Vegetables 0 500 1000 1500 2000 2500 Tomatoes Cabbage Chillies Cucumber Egg Plant Water Mellon Crop A rea Plan ted (h a) 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 Y ield (k g/ha) Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 60.0 Geita Kwimba Sengerema Missungwi Magu Ilemela Ukerewe District P ercen t o f L a n d 0.00 0.01 0.02 0.03 0.04 0.05 0.06 P ercen t A rea P la n ted o f T o ta l L a n d A rea Percent of Land Proportion of Land 0.0 0.2 0.4 A rea per H o useho ld (ha Kwimba Geita Ukerewe Missungwi Sengerema Magu Ilemela District Chart 3.40 Area Planted per Groundnut Growing Household by District (Short Rainy Season Only) Ilemela Nyamagana Kwimba Missungwi Magu 0 0.5 0.3 0.2 0.3 0.2 0.3 Sengerema Geita Ukerewe 0.1 Nyamagana Missungwi Kwimba Ilemela Magu 0ha 42.3ha 2,324.9ha 379ha 7,824.8ha 600.9ha 2,439.3ha 24ha 0% 0.3% 0.1% 0.4% 0.3% 0.5% 0.6% 0.9% Sengerema Geita Ukerewe 6,400 to 7,900 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 Planted Area (ha) MAP 3.21 MWANZA Area Planted Per Household MAP 3.22 MWANZA Area Planted per Groundnuts Growing Household by District Planted Area and Yield of Groundnuts by District 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Planted Area (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 36 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 The yield of tomatoes was 5,589 kg/ha, cabbage (4.7 t/ha), water melon (17t/ha) and pumpkins (1t/ha). Radish and spinach had yields of 6.8 and 3.5t/ha respectively (Chart 3.42). Tomatoes The number of households growing tomatoes in the region during the long rainy season was 5,400 and in the short rainy season the number was 5,016. This represents 4.5 percent of the total crop growing households in the region during the long rainy season and 1.6 percent during the short rainy season. Missungwi district had the largest planted area of tomatoes (23.5% of the total area planted with tomatoes in the region), followed by Sengerema (22.7%), Ilemela (17.5%), Magu (14.3%), Geita (11.3%), Kwimba (6.9%) and Ukerewe (3.9%). (Chart 3.43 and Map 3.22) The highest proportion of land with tomatoes was found in Ilemela followed by Geita and Missungwi district, the rest of the districts had relatively low percentage of land used for tomato production (Chart 3.43 and Map 3.20). The largest area planted per tomato growing household was found in Kwimba district (0.26 ha) followed by Magu (0.24 ha), Sengerema (0.22 ha), Missungwi (0.21 ha), Ilemela (0.14 ha), Geita (0.14 ha) and Ukerewe (0.12 ha) (Chart 3.44 and Map 3.23). The total area planted with tomatoes accounted for 0.3 percent of the total area planted with annual crops and vegetables during the census year. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 6 1 167 0 0 0 6 1 167 Radish 0 0 0 10 68 6,800 10 68 6,800 BitterAubergine 0 0 0 0 0 0 0 0 0 Onions 206 998 4,845 110 666 6055 316 1664 5,266 Ginger 21 10 476 0 0 0 21 10 476 Cabbage 199 890 4,472 127 657 5,173 326 1,547 4745 Tomatoes 1,047 6,058 5,786 870 4,657 5,353 1,917 10,715 5589 Spinnach 20 36 1,800 44 190 4,318 64 226 3531 Carrot 45 66 1,467 55 51 927 100 117 1170 Chillies 68 69 1,015 35 108 3,086 103 177 1718 Amaranths 69 530 7,681 73 173 2,370 142 703 4951 Pumpkins 42 50 1,190 0 0 0 42 50 1,190 Cucumber 54 450 8,333 46 230 5,000 100 680 6800 Egg Plant 16 49 3,063 58 95 1,638 74 144 1946 Water Mellon 49 656 13,388 15 59 3,933 64 715 11172 Total 1,842 9,863 1,443 6,954 16,817 16,817 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 Missungwi Sengerema Ilemela Magu Geita Kwimba Ukerewe District Percent of Land 0.00 0.01 0.02 0.03 Percent Area Planted of Total Land Area Series2 Series1 0.0000 1.0000 2.0000 3.0000 4.0000 5.0000 6.0000 7.0000 8.0000 9.0000 Area per Household (ha). Sengerema Geita Missungwi Ilemela Kwimba Magu Ukerewe District Chart 3.44 Area Planted per Tomato Growing Household by District -Short Rainy Season Kwimba Missungwi Nyamagana Magu Ilemela 0.3 0.2 0.2 0.1 0.1 0.2 0.1 Sengerema Geita Ukerewe 0 Ukerewe Magu Kwimba Missungwi Nyamagana Ilemela Geita 217ha 74ha 132ha 450ha 335ha 436ha 6.7t/ha 2.8t/ha 1.8t/ha 5.5t/ha 0t/ha 5.1t/ha 5t/ha 9t/ha Sengerema 273ha 0ha Planted Area (ha) Planted Area and Yield of Tomatoes by District MAP 3.23 MWANZA Area Planted Per Household Area Planted Per Tomatoes Growing Household by District MAP 3.24 MWANZA 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Area Planted (ha) Yield (t/ha) 0.4 to 0.4 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 38 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 Cabbage The number of households growing cabbages in the region during the long rainy season was 1,125 and 1,339 in the short rainy season. This represents 0.94 percent of the total crop growing households in the region in the long rainy season and 0.42 percent in the short rainy season. Ilemela district had the largest planted area of cabbage (120 ha, 36.9% of the total area planted with cabbage in the region), followed by Geita (72 ha, 22.2%), Sengerema (69 ha, 21.2%), Missungwi (51 ha, 15.7%), Ukerewe (13 ha, 4.2%) Magu and Kwimba reported to have no planted area (Chart 3.45 and Map 3.25 and 3.26). The total area planted with cabbages accounted for 0.05 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Chillies The number of households growing chillies in the region during the long rainy season was 531 and it was 325 during the short rainy season. This represented 0.44 percent of the total crop growing households in the region in the long rainy season and 0.10 percent in the short rainy season. Sengerema district had the largest planted area of chillies (54 ha, 52.1% of the total area planted with chillies in the region), followed by Geita (22 ha,21.6%),Missungwi (18ha, 17.5%) and Ilemela (9ha,8.7%), Chillies are not produced in Ukerewe,Magu, and Kwimba districts. The largest proportion of the area planted with chillies was found in Sengerema and Ilemela districts (0.1%), followed by Missungwi (0.04%), and Geita (0.04%). (Chart 3.46 and Map 3.27 and 3.28). The total area planted with chillies accounted for 0.02 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Chart 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 Ilemela Geita Sengerema Missungwi Ukerewe Magu Kwimba District Percent of Land 0.00 0.20 0.40 0.60 0.80 1.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 Sengerema Geita Missungwi Ilemela Ukerewe Magu Kwimba District Percent of Land 0.00 0.10 0.20 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Kwimba Missungwi Magu Nyamagana Ilemela 0 0.1 0 0 0.1 0.2 0.1 Sengerema Geita Ukerewe 0.2 Missungwi Nyamagana Ilemela Sengerema Ukerewe Magu Kwimba 51ha 0ha 120ha 72ha 69ha 13haha 0hat 0ha 0t/ha 7.5t/ha 5t/ha 5.6t/ha 2t/ha 1.6t/ha 0t/ha 0t/ha Geita Planted Area (ha) MAP 3.25 MWANZA Area Planted Per Household MAP 3.26 MWANZA Area Planted Per Cabbage Growing Household by District Planted Area and Yield of Cabbage by District 80 to 120 60 to 80 40 to 60 20 to 40 0 to 20 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Area Planted (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 40 Missungwi Kwimba Magu Nyamagana Ilemela 0.1 0 0 0 0.1 0.4 0 Sengerema Geita Ukerewe 0.1 Kwimba Missungwi Nyamagana Geita Sengerema Ilemela Magu 0ha 9ha 0ha 18ha 22ha 0ha 0ha 0t/ha 0t/ha 0.4t/ha 2.4t/ha 0.6t/ha 4.8t/ha 0t/ha 0t/ha Ukerewe 54ha Planted Area (ha) MAP 3.27 MWANZA Area Planted Per Household MAP 3.28 MWANZA Area Planted Per Chillies Growing Household by District Planted Area and Yield of Chillies by District 40 to 60 30 to 40 20 to 30 10 to 20 0 to 10 Area Planted (ha) Yield (t/ha) 0.4 to 0.4 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 41 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 42 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 86,935 ha was planted with other annual crops and cotton was the most prominent followed by tobacco, jute and seaweed. The area planted with annual cash crops in short rainy season was 86,938 ha which represents 99.5 percent of the total area planted with other annual cash crops in short and long rainy season. Only 49,837 tonnes of cotton was produced in Mwanza Region on a planted area of 86,533 ha. It was produced during both the long and short rainy seasons. The crop is grown in all districts except Ukerewe. Cotton Only 49,837 tonnes of cotton was produced in Mwanza Region on a planted area of 86,533 ha. It was many produced in the short rainy season. The crop is grown in all districts except Ukerewe (Map3.29 and 3.30) Tobacco The quantity of tobacco produced was 100 tonnes. Tobacco had a planted area of 402 ha, most of which was planted in the short rainy season. Tobacco production is concentrated in 3 districts with Geita having the largest planted area (71.6% of total area planted with tobacco in the region), followed by Magu (22.1%) and Sengerema (6.3%). other districts had no production of Tobacco. (Map 3.31 and 3.32) 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once mature they can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties Table 3.6: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 0 0 0 0 0 0 0 0 0 Cotton 84,683 49,026 579 1,850 811 438 86,533 49,837 576 Tobacco 369 83 225 33 17 515 402 100 249 Jute 0 0 0 0 0 0 0 0 0 TOTAL 85,052 49,109 1,883 828 86,935 49,937 Chart 3.49 Area Planted for Annual and Permanent Crops Annual crops, 679,107 97.4% Permanent , 17,819 2.5% Chart 3.47 Area planted with Annual Cash Crops Cotton 86,533, 99.5% Tobacco, 402, 0.5% Magu Kwimba Missungwi Nyamagana Ilemela Geita 1 0.9 0.8 1 0.8 0 Sengerema Ukerewe 1 0 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Kwimba Missungwi Nyamagana Ilemela Magu Ukerewe 12,440ha 5,300ha 0ha 44ha 33,601ha 25,799ha 0ha 9,348ha 0.5t/ha 0.4t/ha 0t/ha 0.6t/ha 0.6t/ha 0t/ha 0.7t/ha Sengerema Geita 0.2t/ha Planted Area (ha) MAP 3.29 MWANZA Area Planted Per Household MAP 3.30 MWANZA Area Planted per Cotton Growing Household by District Planted Area and Yield of Cotton by District Planted Area (ha) Yield (t/ha) Area Planted Per Household 28,000 to 34,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 43 Nyamagana Kwimba Missungwi Ilemela 0 0 0 0.3 0 0.6 0.2 0 Sengerema Geita Magu Ukerewe 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Kwimba Missungwi Nyamagana Magu Ilemela Sengerema Ukerewe 0ha 0ha 0ha 0ha 288ha 25ha 0ha 0t/ha 0t/ha 0t/ha 0.4t/ha 0t/ha 0.2t/ha 0.6t/ha 0t/ha Geita 89ha Planted Area (ha) MAP 3.31 MWANZA Area Planted Per Household MAP 3.32 MWANZA Area Planted per Tobbaco Growing Household by District Planted Area and Yield of Tobbaco by District Planted Area (ha) Yield (t/ha) 240 to 290 180 to 240 120 to 180 60 to 120 0 to 60 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 44 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 45 That mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of planted area, production and yield. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholder land with permanent crops was 17,819 hectares (2.6% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it double counts the area planted more than during the year, whilst for the planted area for permanent crops is the same as physical land area. So the percentage physical area planted with permanent crops would be higher than indicated in Chart 3.49. The most important permanent crop in Mwanza region is mango which accounts for a planted area of 6,358 ha, (35.5% of the planted area of all permanent crops) followed by oranges (2,855 ha, 16.0%), banana (2,264 ha, 12.7%). Each of the remaining permanent crops had an area of less than 5 percent of the total area planted with permanent crops (Chart 3.50). Geita district had the largest area under smallholder permanent crops (10,383 ha, 58.3%). This is followed by Sengerema (3,197 ha, 17.9%), Ukerewe (2,480 ha, 13.9%), Kwimba (846 ha, 4.7%), Ilemela (451 ha, 2.5%), Missungwi (390 ha, 2.2%) and Magu (73 ha, 0.4%). However, Kwimba had the largest area per permanent crop growing household (0.48 ha) followed by Geita (0.45 ha), Sengerema (0.37 ha), Missungwu (0.13 ha), Ilemela (0.11 ha), Magu and Ukerewe both had 0.1 ha, (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Ukerewe had the highest (7.2%) followed by Geita (5.6%), Ilemela (3.0%), Sengerema (2.7%), Kwimba (0.7%), Missungwi (0.5%) and Magu (0.1%). Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 4.7 0.4 17.9 13.9 2.2 2.5 58.3 0.0 20.0 40.0 60.0 80.0 Geita sengerema Ukerewe Kwimba Ilemela Missungwi Magu District % of Total A rea Planted 0.00 0.20 0.40 0.60 0.80 1.00 A verage Planted A rea per Household % of Total Area Planted Average Planted Area per Household Chart 3.50 Area Planted with the Main Permanent Crops Mango, 6,358, 50% Orange, 2,855, 22% Banana, 2,264, 17% Guava, 746, 6% Sugar cane, 455, 3.5% Lime/lemon, 126, 1.0% Coffee, 97, 0.7% Pegeon Pea, 52, 0.4% Cashewnuts, 48, 0.4% Tea, 1,941, 3% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 3.4.1 Mango The total production of Mango by smallholders was 56,094 tonnes. In terms of area planted, mango was the most important permanent crop grown by smallholders in the region. They were grown by 22,492 households ( 6.6% of the total crop growing households). The average area planted with mango per household was relatively small at around 0.28 ha per mango growing household and the average yield obtained was 24,982 kg/ha from a harvest area of 670 hectares. Geita had the largest area of mango in the region (5,118 ha, 80.5%), followed by Sengerema (695 ha 10.9%), Ukerewe (252 ha, 3.9%), Missungwi (134 ha, 2.1%), Ilemela (97 ha, 1.5%), Kwimba (53 ha 0.8%) and Magu (9 ha, 0.1%) .(Chart 3.52 ). 3.4.2 Oranges The total production of oranges by smallholders was 22,737 tonnes. In terms of area planted, orange was the second most important permanent crop grown by smallholders in the region. Oranges was grown by 13,851 households (4.1% of the total crop growing households). The average area planted with oranges per household was relatively small at around 0.27 ha per orange growing household and the average yield obtained by smallholders was 22.2 t/ha from a harvest area of 1,022 hectares.( Chart 3.53, Map 3.33and 3.34) Sengerema had the largest area of oranges in the region (1,557 ha, 54.5%) followed by Ukerewe (1,010 ha, 35.4%), Ilemela (132 ha, 4.6%), Geita (107 ha, 3.7%), Missungwi (33 ha, 1.2%),Kwimba (16 ha, 0.6%) and Magu district had no production, the average area planted with oranges per orange planting household was highest in Sengerema (0.49 ha) followed by Ilemela (0.25 ha), Missungwi (0.13 ha), Ukerewe () Kwimba (0.08 ha), and Geita (0.06 ha). Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 0.0 0.6 35.4 3.7 54.5 1.2 4.6 0.0 20.0 40.0 60.0 Sengerema Ukerewe Ilemela Geita Missungwi Kwimba Magu District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Mango and Average Planted Area per Household by District 0.14 0.83 10.93 2.11 80.50 1.53 3.96 0.00 20.00 40.00 60.00 80.00 100.00 Geita Sengerema Ukerewe Missungwi Ilemela Kwimba Magu District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Ilemela Nyamagana 0.1 0.3 0 0 0.1 0.1 0.1 1 Sengerema Geita Kwimba Magu Missungwi Ukerewe Missungwi Kwimba Nyamagana Magu Ilemela 33ha 16ha 0ha 1,010ha 1,557ha 107ha 3.5t/ha 0t/ha 1.6t/ha 1.8t/ha 0t/ha 17.3t/ha 2.2t/ha 13.6t/ha Sengerema Geita Ukerewe 132ha 0ha Planted Area MAP 3.33 MWANZA Area Planted Per Household MAP 3.34 MWANZA Area Planted per Oranges Growing Household by District Planted Area and Yield of Oranges by District 1,200 to 1,600 900 to 1,200 600 to 900 300 to 600 0 to 300 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Yield (t/ha) Planted Area Area Planted Per Household Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 47 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 3.4.3 Banana The total production of banana by smallholders was 12,351 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 10,472 households (3.09% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.22 ha per banana growing household and the average yield obtained by smallholders was 8,374 kg/ha from a harvested area of 1,475 hectares. Geita had the largest planted area of bananas in the region (1,189 ha, 52.5%) followed by Sengerema (644 ha, 28.4%), Ukerewe (215 ha, 9.5%), Missungwi (109 ha, 4.9%), Kwimba (59 ha, 2.6%) and Ilemela (48 ha, 2.1%) However, the area planted with banana per banana growing household was highest in Sengerema and Geita both had (0.31 ha), followed by Kwimba (0.30 ha), Missungwi (0.2 ha), Ilemela (0.08 ha) and Ukerewe (0.06 ha) (Chart 3.54 and Map 3.35 and 3.36). 3.4.4 Guava The total production of guava by smallholders was 354 tonnes, in terms of area planted, with a planted area of 746 ha was the fifteenth most important permanent crop grown by smallholders in the region. It was grown by 1538 households (0.4% of the total crop growing households). The average area planted with guava per household was relatively small at around 0.2 ha per guava growing household, and the average yield obtained by smallholders was 120 kg/ha from a harvest area of 354 hectares Ukerewe district has the largest planted area of guava in the region (708 ha, 94.9%) followed by Kwimba district (32 ha, 4.2%), Geita (2 ha 0.2%), Missungwi ( 1 ha 0.1%), there was no guava planted in Magu and Sengerema district (Chart 3.55) Chart 3.54 Percent of Area Planted with Bananas and Average Planted Area per Household by District 9.5 2.6 52.5 4.9 28.4 2.1 0.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Geita Sengerema Ukerewe Missungwi Kwimba Ilemela Magu District % of Total Area Planted -0.05 0.05 0.15 0.25 0.35 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.55 Percent of Area Planted with Guava and Average Planted Area per Household by District 0.0 0.0 0.4 0.1 94.9 0.3 4.3 0.00 20.00 40.00 60.00 80.00 100.00 Ukerewe Kwimba Ilemela Geita Missungwi Magu Sengerema District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Magu Misungwi Kwimba Nyamagana Ilemela 0 0 0.2 0.3 0.1 0.1 0.3 0.3 Sengerema Geita Ukerewe Misungwi Kwimba Nyamagana Magu Ukerewe Ilemela 110ha 59ha 0ha 215ha 1,189ha 644ha 0t/ha 6.3t/ha 1.5t/ha 3.3t/ha 0t/ha 18.1t/ha 6.3t/ha 4.6t/ha Sengerema Geita 48ha 0ha Planted Area (ha) MAP 3.35 MWANZA Area Planted Per Household MAP 3.36 MWANZA Area Planted per Bananas Growing Household by District Tanzania Agriculture Sample Census Planted Area and Yield of Bananas by District 800 to 1,200 600 to 800 400 to 600 200 to 400 0 to 200 Area Planted (ha) Yield (t/ha) 0.4 to 0.4 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household RESULTS AND ANALYSIS 49 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. Other categories includes burning, hand slashing or tractor slashing, are normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 61,754 ha which represented 89.0 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 2.5, 1.3 and 0.1 percent respectively (Table3.8). 3.5.2 Methods of Soil Preparation Hand cultivation is the most common method used for soil preparation as it was used in an area of 299,151 ha which represented 55 percent of the total planted area, followed by ox-ploughing (236,565 ha, 44%) and tractor ploughing (3,825 ha, 1%). Slightly more hand cultivation was used during short rainy season at 81.2 percent against 18.8 percent for the long rainy season, whereas, oxen and tractor ploughing was more common in the short rainy season with 33.5 percent and 0.6 percent respectively. For the long rainy season the corresponding percentages are 10.3 and 0.07 respectively. Table 3.8: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 241,660 61,754 89.0 281,454 388,627 88.7 523,114 450,381 88.8 No Land Clearing 41,526 4,916 7.1 25,492 29,841 6.8 67,018 34,757 6.9 Mostly Bush Clearance 3,664 1,741 2.5 9,191 11,782 2.7 12,855 13,523 2.7 Mostly Burning 1,923 900 1.3 4,653 6,545 1.5 6,576 7,445 1.5 Mostly Tractor Slashing 931 65 0.1 945 1,065 0.2 1,876 1,130 0.2 Other 33 0 0.0 223 101 0.0 256 101 0.0 Total 289,737 69,376 100.0 321,958 437,961 100.0 611,695 507,337 100.0 Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 236,565, 44% Mostly Hand Hoe Ploughing, 299,151, 55% Mostly Tractor Ploughing, 3824, 1% Chart 3.56 Number of Households by Method of Land Clearing During the Long Rainy Season 241,660 41,526 3,664 1,923 931 33 0 100,000 200,000 300,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 In Mwanza region, Kwimba district has the largest planted area cultivated with oxen (85,785 hectares, 36.3%) followed by Magu (67,965 ha, 28.7%), Missungwi (37,126 ha, 15.7%), Geita (32,070 ha, 13.6%), Sengerema (13,149 ha, 5.6%), Ilemela (249 ha, 0.1%) and Ukerewe (221 ha, 0.1%). 3.5.3 Improved Seeds Use The planted area using improved seeds was estimated at 179,608 ha which represents 33 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the short rainy season was percent, and higher than the corresponding percentage uses for the long rainy season 9.5 percent. Cash crops had the largest area planted with improved seeds (79,281 ha, 46.7% of the area planted with improved seeds) followed by cereals (65,871 ha, 38.8%), pulses (16,381 ha, 9.6%), roots and tubers (3,713 ha, 2.2%), fruit & vegetables (2,952 ha, 1.7%) and oil seeds (1,699 ha, 1.0%) (Chart 3.60). However, the use of improved seed in cash crops and fruit and vegetables is much greater than in other crop types (91.2% and 90.3% respectively), only 4.2 percent of the planted area for oil seed crops used improved seed (Chart 3.61). Chart 3.59 Area Planted with Improved Seeds With Improved Seeds, 179,608, 33% Without Improved Seeds, 359,932, 67% 0 20 40 60 80 100 Percent of Planted Area Cash Crops Fruits & Vegetables Cereals Pulses Roots & Tubers Oilseeds Crop Type Chart 3.61 Percentage of Crop Type Area Planted with Improved Seed - Annuals Chart 3.60 Area Planted with Improved Seed by Crop Type Roots & Tubers, 3,713, 2% Pulses, 16,381, 10% Oil Seeds & Oilnuts, 1% Fruits & Vegetables, 2,952, 2% Cereals, 65,871, 39% Cash Crops, 79,281, 46% 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Area Cultivated Geita Kwimba Magu Sengerema Missungwi Ukerewe Ilemela District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 3.5.4 Fertilizer Use The use of fertilisers on annual crops is very small with a planted area of only 185,722 ha (27% of the total planted area in the region). The planted area without fertilisers for annual crops was 549,417 hectares representing 73 percent of the total planted area with annual crops. Of the area planted with fertiliser application, farm yard manure was applied to 169,331 ha which represents 25 percent of the total planted area (91% of the area planted with fertiliser application in the region). This was followed by inorganic fertilizer (8627 ha, 4.6%) and compost (7,764) representing only 4.2 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Geita district (23%) followed by Sengerema (22%), Magu (18%), Kwimba (14%), Missungwi and Ukerewe (9% each) and Ilemela (3%) (Table 3.9). Most annual crop growing households do not use any fertiliser (approximately 194,495 households, 83%). The percentage of the planted area with applied fertiliser was highest for roots and tubers (70% of the area planted with roots and tubers during the long rainy season had an application of fertilizers). This was followed by cereals (19%), pulses (8%), fruit and vegetables (2.1%) cash crops and oil seeds (0.3%). (Table 3.10). and Map 3.37 Table 3.9 Planted Area (ha) by Type of Fertiliser Use and District during- both Rainy Seasons. Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Ukerewe 16,288 1,065 78 17,431 17,168 Magu 30,187 2,450 853 33,490 87,954 Kwimba 24,408 2,129 115 26,652 89,692 Sengerema 37,854 210 3,546 41,610 78,492 Geita 40,664 1,193 1,714 43,572 143,386 Misungwi 14,806 253 1,527 16,585 68,094 Ilemela 5,124 465 794 6,382 8,597 Total 169,331 7,764 8,627 185,722 493,385 TTable 3.10: Number of Crop Growing Households and Planted Area By Fertilizer Use and District -Long Rainy Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 13,856 13,406 1,312 910 167 71 17,048 13,655 32,383 28,042 Magu 4,194 6,142 1,918 1,511 244 101 24,902 24,210 31,257 31,964 Kwimba 1,735 5,047 102 31 103 10 24,439 32,316 26,379 37,404 Sengerema 7,515 12,807 0 0 731 535 49,317 42,224 57,563 55,565 Geita 1,263 2,459 167 27 795 1,026 49,012 47,568 51,237 51,080 Missungwi 1,931 1,766 151 84 658 1,071 22,463 25,129 25,204 28,049 Ilemela 2,563 2,745 321 259 680 475 7,313 5,347 10,878 8,826 Total 33,057 44,372 3,971 2,822 3,378 3,289 194,495 190,447 234,901 240,929 0 50000 100000 150000 200000 Area (ha) Geita Kwimba Magu Sengerema Misungwi Ukerewe Ilemela District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District Mostly Farm Yard Manure Mostly Inorganic Fertilizer Mostly Compost Ukerewe Magu Kwimba Sengerema Geita Misungwi Ilemela Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 169,331, 25% Mostly Inorganic Fertilizer, 8,627, 1% Mostly Compost, 7,764, 1% No Fertilizer Applied, 493,385, 73% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 Farm Yard Manure Use The total planted area applied with farm yard manure in Mwanza region was 169,332 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 33,057 and it was applied to 44,372 ha representing 26 percent of the total area planted during that season (Table 3.10). Roots & tubers had the highest percent of the total area planted with applied farm yard manure (64.4%), followed by cereals (22.2%), Pulses (10.1%), fruits & vegetables (1.8%). Cash crops, (0.7%), oil seeds (0.4%). However, fruit and vegetables had the highest percent of the proportion of planted area with farm yard manure (51.5% of the total area of fruit and vegetables in Mwanza). This was followed by cereals (23%), oil seeds (20.6%), cash crops (19.9%), pulses (18.6%) and root & tubers (18.2%). A higher percent of the planted area in Ukerewe was with Farm Yard Manure (47.1% of the total planted area in the district), followed by Ilemela (34.2%), Sengerema (31.5%), Magu (524.9%), Geita (21.8%), Kwimba (21.0%) and Missungwi (17.5%) (Chart 3.65b and Map 3.38 ). Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Mwanza region was 7,731 ha which represents 4.9 percent of the total planted area with annuals in the region and 5.0 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 3,378 and it was applied to 3,289 ha representing 1.4 percent of the total area planted during that season (Table 3.10). Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District 0.0 10.0 20.0 30.0 40.0 50.0 Ukerewe Sengerema Ilemela Magu Geita Kwimba Misungwi District Percent 0.0 25.0 50.0 75.0 Percent of Planted Area Fruits & Vegetables Cereals Oilseeds Cash Crop Pulses Roots & Tubers Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.66 Area Planted with Inorganic Fertilizers by Crop Type Pulses, 535, 7% Oilseeds & Oil nuts, 212, 3% Cash Crop, 1,222, 16% Cereals, 3,963, 51% Roots & Tubers, 649, 8% Fruit & Vegetables, 1,150, 15% Chart 3.64 Planted Area with Farm Yard Manure by Crop Type Roots & Tubers, 37,739, 69% Pulses, 3,407, 17% Oilseeds & Oil nuts, 164, 0% Fruits & Vegetables, 1,709, (1%) Cereals, 15,824, 28% Cash Crops, 17,275 (12%) 64.4 22.2 10.1 1.8% 0.4% 10.1 Misungwi Kwimba Geita Magu Nyamagana Ilemela Ukerewe 745 240 2,673 305 908 0 173 1,477 0.9% 0% 0.2% 6.1% 0.3% 0.5% 1.4% 1.2% Sengerema Misungwi Kwimba Nyamagana Magu Ilemela 28,049 37,404 0 8,826 31,964 28,042 55,565 51,080 0% 33.1% 32.1% 58.9% 26.3% 81% 46.3% 27.3% Sengerema Geita Ukerewe Planted Area With no Fertilizer Applied MAP 3.37 MWANZA Area Planted With Irrigation MAP 3.38 MWANZA Area Planted and Percent of Total Planted Area With Irrigation by District Tanzania Agriculture Sample Census Planted Area and Percent of Planted Area With No Application of Fertilizer by District 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 2,000 to 2,700 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Area Planted With Irrigation Percent of Area Planted with Irrigation Planted Area With no Fertilizer Applied Percent of Planted Area With no Fertilizer Applied RESULTS AND ANALYSIS 54 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 The largest area applied with inorganic fertilizers was on cereals (51% of the total area applied with inorganic fertilizers), followed by cash crops (16%), fruit and vegetables (15%) and roots and tubers (8%), pulses (7%) and oil seeds (3%). (Chart 3.66). However, the proportion of fruit and vegetables with inorganic fertilizers was 39.1 percent higher than other crop types, followed by cash crops (6.0%), cereals (4.9%), and oil seeds (4.8%), pulses (3.8%) and roots & tubers (1.9%) (Chart 3.67a). The percent of land in Ilemela with inorganic fertilisers is higher than any other district in the region (5.3% of the total planted area in the district), followed by Missungwi (1.8%). Other districts used less than 1 percent (Chart 3.67b). Compost Use The total planted area applied with compost was 8,935 ha which represents only 1.3 percent of the total planted area with annual crops in the region and 5.6 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 3,971 and it was applied to 2,822 ha representing 1.6 percent of the total area planted (Table 3.10 and Chart 3.68a). The proportion of the area applied with compost was low for each type of crop; however the distribution of the total area using compost manure shows that 40 percent of this area was cultivated with cereals, followed by roots & tubers (24%), cash crops (20%), pulse (12%) and fruits & vegetables (0.9%). (Chart 3.68a). Map 3.39 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 Percent of Planted Area Fruits & Vegetables Cash Crop Cereals Oilseeds Pulses Roots & Tubers Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District 0 5 10 15 Ilemela Missungwi Sengerema Geita Magu Kwimba Ukerewe District Percent Chart 3.68a Planted Area with Compost by Crop Type Roots & Tubers, 2,162, 24% Cereals, 3,569, 40% Fruits & Vegetables, 85, 1% Pulses, 1,086, 12% Oilseeds, 229, 3% Cash Crop, 1,804, 20% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 The highest percent of planted area with compost was in Kwimba (8.0% of the total planted area in the district), and this is closely followed by Magu and Ilemela both had (7.3%), Ukerewe (6.1%), Geita (2.7%) Other districts, like Sengerema used little compost (0.5%) (Chart 3.69b). Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 110,665 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (63% of the total area applied with pesticides). This was followed by fungicides (20%) and herbicides (18%) (Chart 3.69). Insecticide Use The planted area applied with insecticides was estimated at 88,612 ha which represented 13.2 percent of the total planted area of annual crops and vegetables. Cash crops had the largest planted area applied with insecticides (51,306 ha, 57.9%) of the total planted area with insecticides) followed by Cereals (20,279 ha, 22.9%), pulses (7070 ha, 8.0%), roots & tubers (1,100 ha, 7.8%) oil seeds & nuts (5,371 ha, 6.1%) and fruits & vegetables (2760 ha, 3.1%). (Chart 3.70). Map 3.40 0.0 25.0 50.0 Percent of Planted Area Cereals Roots &vegetables cash crops Pulses Oil seeds Fruit & vegetables Crop Type Chart 3.69b Percentage of Planted Area with Compost by Crop Type- Chart 3.68c Proportion of Planted Area Applied with Compost by District 0.0 2.0 4.0 6.0 8.0 10.0 Kwimba Magu Ilemela Ukerewe Geita Misungwi Sengerema District Percent Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 21876, 20% Herbicides, 19438, 18% Insecticides, 69351, 63% Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 51306, 57.9% Cereals, 20,279, 22.9% Fruits & Vegetables, 2760, 3.1% Oil seeds & Oil nuts,5371 6.1% Pulses, 7070, 8.0% Roots & Tubers, 1,100, 7.8% Ilemela Magu Ukerewe Nyamagana Misungwi Kwimba Geita Sengerema 159 1,396 315 114 996 484 21.2% 31.8% 0% 3.6% 7.2% 2.6% 22.7% 11% 930 0 Nyamagana Kwimba Misungwi Ilemela Magu Ukerewe Sengerema 0 9,232 3,059 19,977 10,216 9,565 16,487 19,886 0% 10.4% 3.5% 22.6% 11.6% 10.8% 18.6% 22.5% Geita 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area With Farm Yard Manure Applied MAP 3.39 MWANZA Planted Area With Compost Manure Applied MAP 3.40 MWANZA Planted Area and Percent of Total Planted Area With Compost Manure Application by District Tanzania Agriculture Sample Census Planted Area and Percent of Total Planted Area with Farm Yard Manure Application by District Planted Area With Compost Manure Applied Percent of Planted Area With Compost Manure Applied Planted Area With Farm Yard Manure Applied Percent of Planted Area With Farm Yard Manure Applied 1,200 to 1,400 900 to 1,200 600 to 900 300 to 600 0 to 300 RESULTS AND ANALYSIS 57 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 However, the proportion of planted area applied with insecticides was largest for fruits/vegetables and cash crops being 84.0% for fruits/vegetables and 59.0% for cash crops. Only 1.0 percent the area planted with roots and tubers was applied with insecticides (Chart 3.71). Annual crops with more than 50 percent insecticide use were spinach, cucumber , cotton , water mellon, tomatoes, onions, cabbage, field peas, and chillies. Magu had the highest percent of planted area with insecticides (29.2% of the total planted area with annual crops in the district). This was followed by Ilemela (12.5%), Sengerema (12.3%),Missungwi (8.3%), Geita (7.9%) and Kwimba (7.5%) The smallest percentage use was recorded in Ukerewe district (1.3%) (Chart 3.72). Herbicide Use The planted area applied with herbicides was 22,203 ha which represented 3.2 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (11,282 ha, 50.8%) followed by cash crops (8,623 ha, 38.8%), root & tubers (1,526 ha, 6.9%), pulses (383 ha, 1.7%), fruits & vegetables (224 ha 1.0%) and oil seeds (165ha, 0.7%) (Chart 3.73). 0.0 50.0 100.0 Percent of Planted Area Fruits & Vegetables Cash crops Pulses Oil seeds & Oil nuts Cereals Roots & Tubers Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cash crops, 8,623, 38.8% Cereals, 11,282, 50.8% Fruits & Vegetables, 224, 1.0% Oil seeds & Oil nuts, 165, 0.7% Pulses, 383, 1.7% Roots & Tubers, 1,526, 6.9% Chart 3.72 Percentage of Planted Area Applied with Insecticides by District 0.0 5.0 10.0 15.0 Magu Kwimba Ilemela Missungwi Geita Sengerema Ukerewe District Percent RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 However, the proportion of the planted area applied with herbicides was greater for cash crops and fruit and vegetables (9.9% for cash crops and 6.8% for fruits/vegetables). Only 0.5 percent of pulses were applied with herbicides Magu had the highest percent of planted area with herbicides (4.5% of the total planted area with annual crops in the district). This was followed by Geita (4.2%), Kwimba (3.6%), Missungwi (1.2%) and the remaining districts had less than (1%). 3.75). 3.5.5.3 Fungicides Use The planted area applied with fungicides was 18,872 ha which represented 2.8 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (3.4%) was higher than the corresponding percentage for the long rainy season (1.4%). Cereals had the largest planted area applied with fungicides (9,072ha, 48.1%) followed by cash crops (3,554 ha, 18.8%), pulses (2,484 ha, 13.2%), fruits and vegetables (2,402 ha, 12.7%), roots and tubers (921 ha, 4.9%) and oil seeds (438 ha, 2.3%) (Chart 3.76). However, the percentage use of fungicide in cash crops and fruits & vegetables was much greater than in other crop types (1.9% and 1.7% respectively), while only 0.01 percent of roots & tubers was applied with fungicides (Chart 3.77). Magu had the highest percent of planted area with insecticides (6.4% of the total planted area with annual crops in the district). This was followed by Kwimba (3.4%) and Ilemela (3.6%). The smallest percentage use was recorded in Ukerewe district (0.3%) (Chart 3.78). 0.0 3.7 7.4 11.1 Percen t of Plan ted A rea Cash crops Fruits & Vegetables Cereals Roots & Tubers Oil seeds Pulses Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District 0.0 2.5 5.0 Magu Geita Kwimba Missungwi Ilemela Sengerema Ukerewe District Percent Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 921, 4.9% Pulses, 2,484, 13.2% Oil seeds, 438, 2.3% Fruits & Vegetables, 2,402, 12.7% Cereals, 9,072, 48.1% Cash crops, 3,554, 18.8% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 3.5.6 Harvesting Methods The main harvesting method for cereals and other crops was reported to be by hand. Very small amounts of crops were harvested by machine. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 56.7 percent of the total area planted with cereals during the long rainy season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1 percent 0.2 percent and of the total planted area respectively. 3. 6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yield. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Mwanza region, the area of annual crops under irrigation was 182,343 ha representing 27 percent of the total area planted (Chart 3.79). The area under irrigation during the long rainy season was 135,143 ha accounting for 56.1 percent of the total area under irrigation. In the short rainy season, 1.5 percent of the total area planted with crops was irrigated, whilst 25.3 percent of the total area planted were irrigated in the long rainy season. The district with the largest planted area under irrigation for annual crops was Geita (45,960 ha, 25% of the total irrigated planted area with annual crops in the region). This was closely followed by Sengerema with (44,029 ha, 24%) and Ukerewe (27,778, 15%), When expressed as 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Percent of Planted Area Cash crops Fruits & Vegetables Oil seeds Cereals Pulses Roots & Tubers Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Magu Kwimba Ilemela Geita Sengerema Missungwi Ukerewe District Percent Chart 3.79 Area of Irrigated Land Irrigated Area, 182,343, 27% Unirrigated Area, 496,766, 73% Chart 2.80 Planted Area with Irrigation by District 0 25,000 50,000 Geita Sengerema Ukerewe Magu Missungwi Kwimba Ilemela Region Irrigated Area (ha) 0 45 90 Percentage Irrigation Irrigated Area Percentage of Irigated Land RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 a percentage of the total area planted in each district, Ukerewe had the highest with 80% of the planted area in the district under irrigation. This was followed by Ilemela (58%), Sengerema (37%), Geita (25%), Missungwi (22%), Magu (18%) and Kwimba (13%) (Chart 3.80). Time series of households with irrigation in Mwanza region appears to have increased over the 10 year intercensal period from 11,688 to 15,380 households 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from well (33.9% of households with irrigation). This was followed by river (21.1%) and lake (16.7%), canal (15.8%), dam (11.6%), borehole (0.4%), and piped water (0.5%). Most households using irrigation in Geita get their irrigation water from rivers and canal (both were 36 percent) 3.6.3 Methods of Obtaining Water for Irrigation Hand Bucket was the most common method of getting water for irrigation with 67.0 percent of households using this method. This was followed by gravity with 26.1 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.82). Hand Bucket was used most in Missungwi (26.0% of the households practicing irrigation), followed by Ilemela (24.3%), Sengerema (16.2%), Magu (10.2%), Ukerewe (7.5%) and Kwimba (4.1%). Gravity was more common in Geita with 65.8 percent of households using the method to get water for irrigation, followed by Ilemela (18.6), Kwimba (5.5%), Sengerema (4.1%), Ukerewe (3.9%), Missungwi (2.1%) and Magu (0.0%). Mp 3.41 Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 3,817, 26.1% Hand Bucket, 9795, 67.0% Motor Pump, 157, 1.1% Hand Pump, 857, 5.9% Gravity Hand Bucket Hand Pump Motor Pump Chart 3.81 Time Series of Households with Irrigation 15,380 11,688 0 5,000 10,000 15,000 20,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Chart 3.82 Number of Households with Irrigation by Source of Water River, 3,081, 21% Lake, 2,443, 17% Dam, 1,701, 12% Dam, 774, 3% Borehole, 55, 0% Canal, 2,317, 16% River Lake Dam Well Borehole Canal Well 33.9% Kwimba Misungwi Nyamagana Magu Ilemela 8,327 0 7,965 22,455 7,379 8,389 7,110 9,897 0% 64.9% 18.2% 23.3% 39.8% 22.4% 7.6% 15.3% Sengerema Geita Ukerewe Kwimba Misungwi Nyamagana Magu Geita Ukerewe Ilemela Sengerema 34,228 6,542 26,873 32,372 11,577 12,752 0 3,639 28% 61% 0% 34% 11% 51% 35% 42% Number of Households Crop Growing Using Improved Seeds Number and Percent of Crop Growing Households Using Improved Seeds by District Tanzania Agriculture Sample Census MAP 3.42 MWANZA 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Number of Households Receiving Crop Extension Services MAP 3.41 MWANZA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Number of Households Receiving Crop Extension Services Percent of Households Receiving Crop Extension Services 18,000 to 22,500 13,500 to 18,000 9,000 to 13,500 4,500 to 9,000 0 to 4,500 Number of Households Crop Growing Using Improved Seeds- Percent of Households Crop Growing Using Improved Seeds- RESULTS AND ANALYSIS 62 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.6.4 Methods of Water Application Most households used 65% of households using irrigation bucket/watering can irrigation, 65% of households using irrigation as a method of field application. This was closely followed by flood (26%), water hose and sprinkler were not widely used being 5.0% for water hose and 4% for the sprinkler. 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Mwanza region show that there were 338,929 crop growing households 87.3% of the total crop growing households that stored various agricultural products in the region. The most important stored crop was maize with 273,370 households storing 20,026 tonnes as of 1st October 2003. This was followed by beans and other pulses 130,653 households, 2,269 tonnes, paddy 109,350 households, 12,144 tonnes, sorghum and millet with 26,270 households, 1,642 tonnes and groundnuts and bambara nuts 30,368 households, 683 tonnes. Other crops were stored in very small amounts. Methods of Storage The number of households that stored their produce in sacks and/or open drums was 233,530 (78.9%). This was followed by locally made traditional structures 56,898 households (18.9%), improved locally made structure 2,604 (0.9%), unprotected pile 1,553 (0.5%), modern store 1,038 households (0.4%), airtight drum 744 households, (0.3%), and other 258 households (0.1%). Sacks/Open drum were the dominant storage method in all districts with the highest percent in Ilemela and Kwimba districts of 91.4% for Ilemela and 86.5% for kwimba followed by Ukerewe (86.5%),Sengerema (79.9%), Geita (78.0%) Missungwi (76.7%) and lastly Magu (69.9%) (Chart 3.87) Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Ukerewe Magu Kwimba Sengerema Geita Misungwi Ilemela District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.86 Number of Households by Storage Method Unprotected Pile, 1,553, 0.5% Improved Locally Made structures, 2,604, 0.9% Other, 258, 0.1% Airtight Drum, 744, 0.3% Modern Store, 1,038, 0.4% Sacks / Open Drum, 233,530, 78.9% Locally Made traditional structures, 56,148, 19.0% Chart 3.85 Number of Households and Quantity Stored by Crop 0 150,000 300,000 Maize Beans & Pulses Paddy Groundnuts/Bambara Nuts Sorghum & Millet Coconut Tobacco Cashewnut Crop Number of households 0 12,000 24,000 Quantity (t) Number of households Quantity stored (Tons) RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 Duration of Storage Most households (146,134 or 49% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (99,137, 34%) and those that stored their crops for a period of less than 3 months (50,475, 17%) (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Geita district (58.6%) followed by Ukerewe district (56.9%), Magu district (51.3%), Kwimba district (44.2%), Ilemela district (41.2%) and Sengerema district (37.2%). (Map 3.33) District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). Purposes of Storage Subsistence food crops i.e maize, paddy, sorghum and millet, beans and pulses are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 93.6 percent followed by Paddy 84.6 percent. Practically all stored annual cash crops were stored for selling at higher price. A high percent of the stored crop was used for household consumption as was the case of Maize 93.6% (Chart 3.90 and Map 3.34). 0 30,000 60,000 90,000 120,000 150,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Ukerewe Magu KwimbaSengerema Geita Missungwi Ilemela District Quantity (tonnes) 0 5 10 15 20 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Seaweed Cloves Cashewnut Tobacco Groundnuts/Bambara ... Crop Chart 3.90 Number of Households by Purpose of Storage and Crop Food for the household To sell for higher price Seeds for planting Others RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 The Magnitude of Storage Loss About 81.5 percent of households that stored crops had little or no loss, 14 percent had up to ¼ losses,3.2 percent between ¼ and ½ loss and 1.3 percent over 1/2 loss. Storage loss is more important in Geita district than in other districts in the region. The number of households that reported little or no loss was largest in Geita district about 30%. Geita and Sengerema districts had the highest percentage of households reporting up to a ¼ loss (28% and 27% respectively). between a quarter and half loss also Geita and Sengerema districts recorded the highest percentage of 36% and 33% and for over a half loss the highest percentage was recorded in Geita district about 47 % (Table 3.10). 3.7.2 Agro processing and By-products Agro processing refers to the process of converting a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Mwanza region with 325,929 crop growing households (95.6%) reporting processing (Chart 3.91a). The percent of households processing crops was very high in all districts (80% of households processed crops) (Chart 3.91b). Processing Methods Most households processed their crops using neighbour’s machines representing 78.2% (254,456 households). This was followed by those processing on-farm by hand (45,446 households, 14.0%), trader (14,929 households, 4.6 %) and on-farm by machine (9,644 households, 3.0%). The remaining methods of processing were used by very few households (less than 1%). Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Ukerewe 9,724 1,898 169 83 11,874 Magu 39,960 7,006 938 271 48,175 Kwimba 32,587 5,645 624 699 39,555 Sengerema 46,996 11,302 3,215 725 62,238 Geita 73,528 11,497 3,488 1,811 90,324 Misungwi 27,648 3,081 969 179 31,877 Ilemela 10,642 980 158 55 11,835 Total 241,083 41,409 9,560 3,823 228,187 Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Ukerewe Magu Kwimba Sengerema Geita Misungwi Ilemela District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other 0 20 40 60 80 100 Percent of Households Processing Geita SengeremaMisungwi Ilemela Ukerewe Kwimba Magu District Chart 3.91b Percentage of Households Processing Crops by District RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 Although processing by machine was the most common processing method in all districts in Mwanza region, there were differences in districts. Ukerewe district has a higher percent of hand processing than other districts.(79.5%), followed by Ilemela district (21.5%), and Missungwi district (16.7%). Processing by trader was more common in Ilemela and Kwimba districts (12.0% and 11.7% respectively), whilst processing on farm by machine was more prevalent in Ilemela, Magu and Kwimba (Chart 3.92). Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the most important product after processing and the by- product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 290,516 households processing crops into flour (89.3%) followed by bran (34,326 households, 10.5%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by- products accounted for 96% of the households processing crops. The most common by-product produced by crop processing households was husk with 85,950 households (26.5%) followed by Bran (25221 households, 78%), Juice (2,756 households, 0.85%) and pulp (1,751 households, 0.5%). The remaining by-products were produced by a small number of households (Chart 3.94). Main Use of Primary Processed Products The most important use of primary products was for household/human consumption which represented 99.3% of the total households that used primary processed product (Chart 3.95). Missungwi was the only district that used primary products animal consumption. Other uses are of minor importance. Chart 3.93 Percent of Households by Type of Main Processed Product Grain, 10.50, (11.0%) Oil, 0.06, (0.0%) Juice, 0.07, (0.0%) Flour / Meal, 89.32, (89.0%) Flour / Meal Grain Oil Juice Chart 3.94 Number of Households by Type of By-product Husk, 22,420 (57.3%) Bran, 12,898, (33.0%) Pulp, 749, (1.9%) Juice, 2029,(5.2%) Oil ,( 0.7%) Shell, 615, ( 1.6%) Cake, 104, (0.3)% Bran Husk Juice Pulp Shell Cake Oil Chart 3.95 Use of Processed Product Animal Consumption, 69, (0.0%) Did Not Use, 1,037 (0.3%) Sale Only, 1382 (0.4%) Fuel for Cooking, 395 ( 0.1%) Household/ human consumption, 322,381 (99.11%) Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 Out of 1,382 households that sold processed products, 409 were from Kwimba district (29.6% of the total number of households selling processed products in the region), followed by Ukerewe with 311 households (22.5%), Geita with 304 households (22.0%), Sengerema with 300 households (21.7%) and Ilemela with 59 households (4.2%). Two districts Magu and Missungwi had no households that sold processed products in the region (Chart 3.96). . Outlets for Sale of Processed Products Most households that sold processed products sold to local market and trade stores (9,404 households, 37% of households that sold crops). This was followed by selling to neighbours (4,659 households, 19%), trader at farm (2,732 households, 11%), farmers associations (1,012 households, 4%), large scale farm (814 households, 3%) and marketing co- peratives (382 households, 2.%) (Chart 3.97). There were large differences between districts in the proportion of households selling processed products to neighbours with Ukerewe district having the largest percent of households selling to neighbours (56.6%), whereas in Sengerema district there no household sold processed products to neighbours. However, Sengerema district had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Ukerewe district had the highest percent of households selling processed products to traders at farm. In Kwimba district the sale of processed produce to farmer associations was most prominent compared to other districts, and district that had the highest proportion of households selling processed products to marketing cooperative was Missungwi. (Chart 3.98). 0.00 5.00 10.00 15.00 20.00 25.00 30.00 Percentage of households Kwimba Ukerewe Geita Sengerema Ilemela Misungwi Magu District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Farmers Association, 1,012, 4% Large Scale Farm, 814, 3% Trader at Farm, 2,732, 11% Other, 6,130, 24% Marketing Co- operative, 382, 2% Local Market / Trade Store, 9,404, 37% Neighbours, 4,659, 19% Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm O h Chart 3.98 Percent of Households Selling Processed Products by Outlet and District 0% 20% 40% 60% 80% 100% Ukerewe Magu Kwimba Sengerema Geita Misungwi Ilemela District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 3.7.3 Crop Marketing The number of households that reported selling crops was 243,200 which represent 71.8% of the total number of crop growing households. There was little difference between districts in the percent of households selling crops. The percent of crop growing households selling crops was highest in Sengerema (78.3%) followed by Magu (76.6%), Geita (72.0%), Ukerewe (70.3%), Missungwi (67.6%) Kwimba (61.9%) and Ilemela (60.7%) (Chart 3.99). Main Marketing Problems The main marketing problem reported by crop growing households was open market price too low 53,292 households, (75.8%). This was followed by market too far, 6,824 households (9.7%), other problems were transport cost too high, 3,235 households (4.6%), lack of transport, 3,083 households (4.4%), lack of information, 2,336 households (3.3%). Other marketing problems are minor and represent less than 1 percent of the total reported problem Reason for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 92.8% of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Mwanza region very few agricultural households (9,991, 0.4%) accessed credit out of which 7,358 (74%) were male-headed households and 2,633 (26%) were female headed households. In Geita district, only male headed households accessed credit. (Table 3.12) Map 3.43 and 3.44 Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 114,758 92.8 Other 2,282 1.8 Price Too Low 3,539 2.9 Trade Union Problems 1,641 1.3 Co-operative Problems 180 0.1 Market Too Far 1,032 0.8 Government Regulatory Board Problems 260 0.2 Total 123,692 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Magu 3,659 71 1,527 29 5,187 Kwimba 920 69 409 31 1,329 Sengerema 761 71 308 29 1,069 Geita 460 100 0 0 460 Misungwi 1,059 86 179 14 1,238 Ilemela 498 70 209 30 707 Total 7,357 74 2,632 26 9,989 Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 40,000 80,000 Geita Sengerema Magu Kwimba Ukerewe Misungwi Ilemela District Number of Households 0 50 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Government Regulatory Board 0.5% Open Market Price Too Low 75.8% Trade Union Problems 0.1% Transport Cost Too High 4.6% Lack of Market Information 3.3% Market too Far 9.7% No Transport 4.4% No Buyer 1.1% Geita Kwimba Misungwi Ukerewe Magu Nyamagana Ilemela 67,156 28,366 23,124 43,178 22,882 0 7,847 50,648 72% 67% 62% 0% 61% 77% 70% 78% Sengerema 56,000 to 68,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Magu Nyamagana Ilemela Kwimba Missungwi Ukerewe 47% 36% 43% 57% 47% 58% 0% 36% Sengerema Geita Percent of Households Storing Crops MAP 3.43 MWANZA MAP 3.44 MWANZA Percent of Households Storing Crops For 3 to 6 months by district Percent of Households Storing Crops 46.4 to 58 34.8 to 46.4 23.2 to 34.8 11.6 to 23.2 0 to 11.6 Number of Households Selling Crops Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops Percent of Households Selling Crops Tanzania Agriculture Sample Census RESULTS AND ANALYSIS 69 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 Source of Agricultural Credit The major agricultural credit provider in Mwanza region were Saving & Credit Societies which collectively provided credit to 4,352 agricultural households, 43.6% of the total number of households that accessed credit), followed by family, friends and relatives (32.6%), Religious Organization/NGO/Project (14.1%), Co operative (4.5%), commercial bank (3.0%) and trader/trade(1.4%) (Chart 3.101). Trader/Trade Store was the most important source of credit in Magu district; Commercial Banks were found in Magu, Kwimba and Ilemela districts. (Chart 3.102). Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on labour (31.7%), followed by Seeds (17.7%), tools/equipment (16.2%) other (15%) and Agro-Chemicals (7.6%). The proportion of credit intended to be used for fertilizers, and irrigation Structures was very low (Chart 3.103). Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was did not know how to get credit accounting to 34.6 percent of the agricultural households. This was followed by households reporting don’t know about credit 22.2 percent Credit not available 22.1 percent, did not want to go into debt 11.6 percent. The rest of the reasons for not using credit were not important. Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Private Individual 0.9% Trader / Trade Store 1.4% Saving&Credit Society 43.6% Family, Friend and Relative 32.6% Religious Organisation/NG O/Project 14.1% Co-operative 4.5% Commercial Bank 3.0% Chart 3.102 Proportion of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Magu Kw imba Sengerema Geita Misungw i Ilemela District Percent of Households Family, Friend and Relative Commercial Banks Saving & Credit Society Trader/Trade Store Religious Organisation/NGO/Project Private Individual Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Other 15.1% Agro-chemicals 7.6% Tools / Equipment 16.2% Irrigation Structures 1.2% Livestock 6.8% Labour 31.7% Fertilizers 3.7% Seeds 17.7% Chart 3.104 Reasons for not Using Credit (% of Households) Not needed, 11,752, 3.6% Not available, 72,934, 22.1% Did not want to go into debt, 38,419, 11.6% Interest rate/cost too high, 10,983, 3.3% Did not know how to get credit, 114,347, 34.6% Difficult bureaucracy procedure, 5,106, 1.5% Other, 296, 0.1% Don't know about credit, 73,437, 22.2% Credit granted too late, 2,819, 0.9% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 3.8.2 Crop Extension The number of Agricultural households that received crop extension was estimated at 71,522 or 21% of total crop growing households in the region.(Chart 3.105) Some districts have more access to extension services than others. (Chart 3.106).. Ilemela had a relatively high proportion of households (65%) that received crop extension messages in the district followed by Magu (40%), Missungwi (23%), Ukerewe (22%), Kwimba(18%), Sengerema(15%) and Geita (8%) (Chart 3.106 and Map 3.41). Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the most with 61,731 households (87% of the households receiving extension), NGOs provide 6,754 households (10%) and large scale farms 1,691 households (2%) (chart Map 3.41) Quality of Extension An assessment of quality of extension indicated that 63.7% of the households receiving extension ranked the service as being good followed by Very Good (18.8%), Average (16.6%), Poor (0.8%) and No Good (0.1%), (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension section as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs 3.9.1 Use of Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crop. Chart 3.107 Number of Households Receiving Extension by Quality of Services Good, 45,399, 63.7% Average, 11,801, 16.6% Poor, 587, 0.8% No Good, 101, 0.1% Very Good, 13,371, 18.8% Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 268,562, 79% Households Receiving Extension , 71,522, 21% Chart 3.106 Number of Households Receiving Extension by District 0 5,000 10,000 15,000 20,000 25,000 Magu Sengerema Ilemela Kwimba Misungwi Ukerewe Geita District Number of Households 0 20 40 60 80 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 A small number of households use inputs and this particularly true of inputs that are not produced on farm, pesticides/fungicide, compost and herbicides. In Mwanza region Inorganic fertilizers were used by households which represents 2.8 percent of the total number of crop growing households, farm yard manure (30.3%), improved seeds (37.9%), pestcides/fungicides (16.9%), compost (3.8%) and herbicides (0.3%). 3.9.2 Inorganic Fertilizers Practically all farmers using inorganic fertilizer purchase it from the local market/trade store (98.6% of the number of households using fertilizers). The other source, although minor, was local farmers groups (Chart 3.108). The distance from the household to source of inorganic fertilizer was mainly less than than 10 km with most households residing between 3 and 10 km from the source (28%), followed by 1 and 3 km (21%) and less than 1 km (11%) (Chart 3.109). Due to the very small number of households using inorganic fertilizers, it may be assumed that access to inorganic fertilizer was not the main reason for not using it. Other reasons such as cost are more important with 70 percent of households responding to cost factors as the main reason for not using the fertilizers. In other words, it may be assumed that if the cost was affordable the demand would be higher and access to inorganic fertilizer would be made available. There were more smallholders using inorganic fertilizers in Ilemela than in other districts in Mwanza region (15% of the households used inorganic fertilizers), followed by Missungwi (6%), and Sengerema (3%). Other districts used very little inorganic fertilizers. 3.9.3 Improved Seeds The percentage of crop growing households that used improved seeds was 37.6. Most of the improved seeds were obtained from the local market/trade stores (44.2%), crop buyers (22.2%), co-operative (21.5%), other less important sources of improved seeds were neighbours (5.1%), local farmers groups (2.1%), locally produced by households (1.9%). Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Input Type of Input Number % Number % Farm yard manure 103,260 30.3 237,259 69.7 Improved seeds 127,982 27.9 330,624 72.1 Pestcides/Fungicide 57,260 16.8 282,716 83.2 Inorganic fertiliser 9460 2.8 329,468 97.2 Compost 12,896 3.8 327,019 96.2 Herbicide 1,054 0.3 339,031 99.7 Chart 3.108 Number of Households by Source of Inorganic Fertiliser 1.4 98.6 0 5000 10000 Local Market / Trade Store Local Farmers Group Source of Inorganic Fertiliser Number of Households Chart 3.109 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 15.0 30.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.110 Number of Households by Source of Improved Seed 44.3 22.2 21.5 5.1 2.1 2.0 0.4 1.9 0.3 0.3 0 40,000 80,000 Local Market / Trade Store Crop Buyers Co-operative Neighbour Local Farmers Group Development Project Locally Produced by Household Secondary Market Other Large Scale Farm Source of Improved Seed Number of Households RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 Secondary markets (0.4%), large scale farms (0.3%) and other sources (0.3%). Access to improved seeds was better than access to chemical fertilizers with 33 percent of households obtaining this input within 1 km of the household (Chart 3.111). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that used improved seeds most was Magu (26.7 percent of the total number of households using improved seeds in Mwanza region), followed by Geita (25.3%) and Sengerema (21.0%), Use of improved seeds in other districts is of was not significant (Map3.44). 3.9.4 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (55.2% of the total number of fungicides users) followed by cooperatives (24.5%) and crop buyers (17.3%).Other sources of insecticides/fungicides are of minor importance (Chart 3.112) Chart 3.113 shows that there for 78.7%, of the households using insecticides/ fungicides the sources was within a distance of 10 kms. The district that used insecticide/fungicides most was Geita (37.1 percent of the total number of households that use fungicides in the region), followed by Magu (26.2%), Sengerema (20.0%), insecticides/fungicides use in other districts was of no importance Chart 3.113 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111Number of Households Reporting Distance to Source of Improved Seeds 0 20 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.112 Number of Households by Source of Insecticides/Fungicides 55.3 24.6 17.3 0.8 0.8 0.7 0.2 0.5 0 20,000 40,000 Local Market / Trade Store Co-operative Crop buyers Secondary Market Local Farmers Group Neighbour Other Development Project Source of Insecticide/fungicide Number of Households RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.10 Tree Planting. The number of households involved in tree farming was 44,741 representing 13 percent of the total number of agriculture households (Chart 3.114). The number of trees planted by smallholders on their allotted land was 3,170,706 trees. The average number of trees planted per households planting trees was 71 trees The main species planted by smallholders is Eucalyptus Spp (12018 trees, 56.5%), followed by Gravellis (4,764 trees, 22.4%), Cyprus Spp 2921 trees, 13.7%), Senna Spp 920 trees, 4.3% and Laucena Spp 413 trees, 1.94%). The remaining trees species were planted in comparatively small numbers (Chart 3.115). Sengerema had the largest number of smallholders with planted trees than any other district (33.8%) and was dominated by Eucalyptus species. This is followed by Ilemela (30.3%) which was also dominated by Eucalyptus species and to a lesser extent Gravellia, then Magu (50.0% which was mainly planted with Azadritachta Spp. (Chart 3.116 and Map 3.45). Chart 3.114 Number of Households with Planted Trees. Growing trees, 44,742, 13% Not growing Trees, 295,343, 87% Chart 2.115 Number of Planted Trees by Species 0 7500 15000 Eucalyptus Spp Gravellis Cyprus Spp Senna Spp Leucena Spp Tectona Grandis Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp Tree Species Number of Trees Chart 3.116 Number of Trees Planted by Smallholders by Species and District 0 7,500 15,000 Ukerew e Magu Kw imba Sengerema Geita Misungw i Ilemela Districts Number of Trees Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Maesopsis Berchemoides Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Sesbania Spp Moringa Spp RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 75 Smallholders mostly plant trees in a plantation. The proportion of households that plant in plantations were 49.2 percent followed by scattered around the fields (35%) and then field boundary (15.2%) (Chart 3.117). The main purpose of planting trees is to obtain planks/Timber (62.6%), this is followed by Wood for fuel (18.2%), Poles (7.8%) Shade (5.1%), Charcoal (0.7%) and other (0.6 %), (Chart 3.118) 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 28,852. This number represents 8% of total number of agricultural households in the region. (Chart 3.119). The proportion of farmers with soil erosion control and water harvesting facilities was highest in Magu District (24%) followed by Kwimba (12%), Ukerewe (10%), Sengerema (6%), Missungwi (5%), Ilemela(4%) Geita (1%) Chart 3.120). Erosion control bunds accounted for 56.7% of the total number of structures builts; it was followed by water harvesting bunds (35.0%), terraces (5.3%), drainage ditches (1.4%), gabions (0.6%), tree belts (0.6%) vertiver grass (0.2%) and dam (0.1%). (Chart 3.121 and Map 3.46) Chart 3.118 Number of Households by Purpose of Planted Trees 0.0 35.0 70.0 Planks / Timber Wood for Fuel Poles Shade Medicinal Other Use Percent of H ouseholds Chart 3.119 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 311,233, 92% Households with facilities, 28,852 8% Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities 24 12 6 10 5 1 4.1 0 5,000 10,000 15,000 Magu Kwimba Sengerema Ukerewe Misungwi Geita Ilemela District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.117 Number of Trees Planted by Location Field boundary, 482,868, 15.2% Scattered in field, 1,127,899, 35.6% Plantation, 1,559,939, 49.2% Magu Kwimba Nyamagana Misungwi Ilemela Ukerewe Sengerema 230,710ha 16,730ha 5,737ha 0ha 0ha 965 16,849ha 1,825ha 8% 0% 0% 49% 42% 23%ha 19% 6% Geita Nyamagana Ilemela Ukerewe Magu Misungwi Kwimba Sengerema 4,232ha 0ha 6,659ha 8,819ha 3,821ha 3,030ha 4,182ha 11,411ha 33% 20% 16% 0% 8% 9% 4% 18% Geita Number of Smallholder Planted Trees MAP 3.45 MWANZA Number of Households With Water Harvesting Bunds MAP 3.46 MWANZA Number and Percent of Households With Water Harvesting Bunds by District Tanzania Agriculture Sample Census Number and Percent of Smallholder Planted Trees by District Number of Households With Water Harvesting Bunds Percent of Households With Water Harvesting Bunds Number of Smallholder Planted Trees Percent of Smallholder Planted Trees 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 184,800 to 230,800 138,600 to 184,800 92,400 to 138,600 46,200 to 92,400 0 to 46,200 RESULTS AND ANALYSIS 76 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 77 3.12 Livestock Results Cattle Production Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 10.2 percent of the total cattle population on Tanzania, Mainland. 3.12.1 Cattle Population The total number of cattle in the region was 1,718,191 and out of this 1,710,309 were indigenous (99.5% of the total number of cattle in the region), 7,882 were improved dairy (0.5%) and there were no improved beef cattle in the region. The census results show that 118,062 agricultural households (34.7% of the total agricultural households) kept 1,718,191 million cattle. This was equivalent to an average of 15 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Magu which had about 416,484 (24.2% of the total cattle in the region). This was followed by Geita (407,829 cattle, 23.7%), Sengerema (305,936 cattle, 17.8%), Missungwi (254,780 cattle, 14.8%), Kwimba 251,548 cattle 14.6%) Ukerewe (58,301 cattle, 3.4%), and Ilemela (23,313 cattle, 1.4%) (Chart 3.122.and Map 3.47) However, Missungwi district had the highest density (301 head per Km2 ), (Map 3.48). Although Magu district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and there were no improved beef cattle in the district. Magu district had the largest number of diary cattle in the region. (Chart 3.123). Cattle Herd Size Thirty eight percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Fifty percent of the cattle rearing households had herds of size 6-30. Only 4 per cent of the cattle rearing households had herd sizes of between 31 to 100 cattle, 88 percent of the total cattle rearing households had herds of size 1- 30 cattle and owned 53 percent of the total cattle in the region of an average of 2 cattle per cattle rearing household. There were about 451 households with a herd size of more than 100 cattle each which together owned 105,500 cattle, resulting in an average of 229 cattle per household. Chart 3.121 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.1 0.2 0.6 0.6 1.4 5.3 35.0 56.7 0 250,000 500,000 Erosion Control Bunds Water Harvesting Bunds Terraces Drainage Ditches Gabions / Sandbag Tree Belts Vetiver Grass Dam T y p e o f F a cility Number of Structures 0 250 500 N u m b er of C attle ('000') Magu Geita Sengerema Misungwi Kwimba Ukerewe Ilemela Districts Chart 3.122 Total Number of Cattle ('000') by District Chart 3.123 Number of Cattle by Type and District 0 250,000 500,000 Magu Geita Sengerema Misungwi Kwimba Ukerewe Ilemela Districts N um ber o f C a ttle Indigenous Beef Dairy Missungwi Nyamagana Kwimba Ilemela 301.3 0 161.8 48.1 214.4 145.5 82.2 25.7 Sengerema Geita Magu Ukerewe 240 to 310 180 to 240 120 to 180 60 to 120 0 to 60 Magu Missungwi Nyamagana Ilemela 416,484 0 254,780 251,548 23,313 58,301 407,829 305,936 Sengerema Geita Kwimba Ukerewe 320,000 to 420,000 240,000 to 320,000 160,000 to 240,000 80,000 to 160,000 0 to 80,000 Number of Cattle MAP 3.47 MWANZA Number of Cattle Per Sq Km MAP 3.48 MWANZA Cattle Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Cattle Population by District as of 1st Octobers 2003 Cattle Density Cattle Population RESULTS AND ANALYSIS 78 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 79 Cattle Population Trend Cattle population in Mwanza decreased during the period of eight years from 2,450,396 in 1995 to 1,718,190 cattle in 2003. This trend depicts an overall annual negative growth rate of 12.46 percent (Chart 3.124) However, the rate of decline was -5.6% over a four year period from 1995 to 1999 whereby the number dropped from 2,450,396 to 2,163,997, and it was -4-34% over the period 1999 to 2003 resulting in a drop from 2,163,997 cattle in 1999 to 1,718,190 in 2003. Dairy Cattle Breeds The total number of improved cattle in Mwanza region was 7,882 all of them being dairy cattle. The daily cattle constituted 0.5 percent of the total cattle in the region. There were no improved beef cattle reported in region. The number of improved cattle increased from 1,700 in 1999 to 7,882 in 2003. The rate of growth was therefore very high over the period 1999 to 2003, there was no figure reported for 1995. Chart 3.125) 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Mwanza region ranked 4th out of the 21 regions with 7 percent of all total goats on the Mainland. Goat Population The number of goat-rearing-households in Mwanza region was 124,250, (37% of all agricultural households in the region) with a total of 829,997 goats giving an average of 7 head of goats per goat-rearing-household. Geita had the largest number of goats (232,464 goats, 28% of all goats in the region) followed by Sengerema (169,042 goats, 20%), Magu (146,908 goats, 18%), Kwimba (107,509 goats, 13%), Missungwi (95,249 goats, 12%) Ukerewe (59,472 goats, 7%), Ilemela district has the least number of goats (19,354 goats, 2%) (Chart 3.126). However Missungwi district had the highest density (head 113 per km2 ) (Chart 3.126 and Map 3.49, 3.50) 0 40 80 120 160 200 240 Number of goats ('000') Geita Sengerema Magu Kwimba Misungwi Ukerewe Ilemela District Chart 3.126 Total Number of Goats ('000') by District 2,450,396 2,163,997 1,718,190 - 1,250,000 2,500,000 Number of cattle 1995 1999 2003 Year Chart 3.124 Cattle Population Trend 1,700 7,882 - 5,000 10,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Dairy Cattle Population Trend Nyamagana Misungwi Kwimba Ilemela Magu Geita 0 112.6 69.1 39.9 75.6 83 26.2 45.4 Sengerema Ukerewe 80 to 120 60 to 80 40 to 60 20 to 40 0 to 20 Nyamagana Geita Misungwi Kwimba Ukerewe Magu Ilemela 0 169,042 232,464 95,249 107,509 59,472 146,908 19,354 Sengerema 188,000 to 233,000 141,000 to 188,000 94,000 to 141,000 47,000 to 94,000 0 to 47,000 Number of Goat MAP 3.49 MWANZA Number of Goats Per Sq Km MAP 3.50 MWANZA Goat Density by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Goat Population by District as of 1st Octobers 2003 Goat Density Goat Population RESULTS AND ANALYSIS 80 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 81 Goat Herd Size Forty eight percent of the goat-rearing households had herd of size 1-4 goats with an average of 3 goats per goat rearing households. About 91 percent of total goat-rearing households had herd of size 1-14 goats and owned 71 percent of the total goats in the region resulting in an average of 11 goats per goat-rearing households. The region had 755 households (0.6%) with herd sizes of 40 or more goats each (37,965 goats in total), resulting in an average of 50 goats per household. Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted about 99.4 percent of the total goats in Mwanza region. Improved goats for meat and diary goats constituted 0.5 %and 0.1 percent of total goats respectively. Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 1.04 percent. The population of goats increased over the period 1995 to 1999 from 764,260 to 863,640 at an estimated annual rate of 3.1 percent. However from 1999 to 2003, the goat population decreased at annual rate of 0.9 percent (Chart 3.127). 3.12.3 Sheep Production Sheep rearing was the third, most important livestock keeping activity in Mwanza region after cattle and goats. The region ranked 10 out of 21 Mainland regions and had 3 percent of all sheep on Tanzania Mainland. Sheep Population The number of sheep-rearing households was estimated at 24,433 (7% of all agricultural households in Mwanza region) rearing 121,978 sheep, giving an average of 5 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Kwimba with 39,364 sheep, 32%) followed by Missungwi (28,634 sheep, 24%), Magu (27,299 sheep, 22%), Geita (15,090 sheep, 12%), Sengerema (9,801 sheep, 8%) Ilemela (1,624 sheep, 1.3%) and Ukerewe District had the least number of sheep (166 sheep, 0.1%) Chart 3.128 and Map 3.36). However Missungwi district had the highest density (34 head per km2). (Map.3.51 and 3.52) 0 20,000 40,000 Number of sheep Kwimba Misungwi Magu Geita Sengerema Ilemela Ukerewe District Chart 3.128 Total Number of Sheep by District 764,260 863,640 829,997 - 500,000 1,000,000 Number of goats 1995 1999 2003 Year Chart 3.127 Goat Population Trend Ilemela Nyamagana 3.4 0 33.9 25.3 14 0.1 5.4 2.6 Sengerema Geita Kwimba Magu Misungwi Ukerewe 27.2 to 33.9 20.4 to 27.2 13.6 to 20.4 6.8 to 13.6 0 to 6.8 Magu Kwimba Misungwi Nyamagana Ilemela Ukerewe 27,299 39,364 28,634 0 1,624 166 15,090 9,801 Sengerema Geita 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Number of Sheep MAP 3.51 MWANZA Number of Sheep Per Sq Km MAP 3.52 MWANZA Sheep Density by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Sheep Population by District as of 1st Octobers 2003 Sheep Density Sheep Population RESULTS AND ANALYSIS 82 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 83 Sheep rearing was dominated by indigenous breeds that constituted 99.9 percent of all sheep kept in the region. Only 0.05 percent of the total sheep in the region were improved breeds. Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at -5.9 percent. The population decreased at an annual rate of -17.4 percent from 199,317 in 1995 to 116,565 in 1999, and increased at 1.4 percent from 116,565 in 1999 to 121978 in 2003 (Chart 3.129).. 3.12.4 Pig Production Pigs are the least important livestock keeping activity in the region after cattle, goats and sheep and the region had the smallest number of pigs on the compared to other regions with 0.05 percent of the pigs in the country. The number of pig-rearing agricultural households in Mwanza region was 76 (0.02% of the total agricultural households) rearing 610 pigs. This gives an average of 8 pigs per pig-rearing household. The district with the largest number of pigs was Geita with 310 pigs,(51 % of the total pig population in the region) followed by Missungwi (161 pigs, 26%) and Magu (138 pigs, 23 %) (Chart 3.130 and Map 3.43), However, Missungwi district had the highest density (0.2 head per km2) (Map 3.53 and 3.54). Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was -18.3 percent. During this period the population declined from 1020 in 1995 to 610. The growth rate dropped to -6.2 percent during the four years from 1999 to 2003 in which pig population decreased from 1000 to 610 (Chart 3.131) 0 200 400 Number of Pigs Geita Missungwi Magu Ukerewe Sengerema Kwimba Ilemela District Chart 3.130 Total Number of Pigs by District 1,020 1,000 610 - 500 1,000 1,500 Number of pigs 1995 1999 2003 Year Chart 3.131 Pig Population Trend 199,317 116,565 121,978 - 100,000 200,000 Number of sheep 1994/95 1998/99 2002/03 Year Chart 3.129 Sheep Population Trend Misungwi Magu Ilemela Nyamagana Kwimba 0.1 0 0 0.1 0 0.1 0 0 Sengerema Geita Ukerewe 0.08 to 0.1 0.06 to 0.08 0.04 to 0.06 0.02 to 0.04 0 to 0.02 0 139 0 0 161 310 0 0 Sengerema Geita Kwimba Magu Ilemela Misungwi Nyamagana Ukerewe Number of Pig MAP 3.53 MWANZA Number of Pig Per Sq Km MAP 3.54 MWANZA Pig Density by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Pig Population by District as of 1st Octobers 2003 Pig Density Pig Population 400 to 400 300 to 400 200 to 300 100 to 200 0 to 100 RESULTS AND ANALYSIS 84 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.12.5 Chicken Production The poultry sector in Mwanza region was dominated by chicken production. The region contributed 7.9 percent to the total chicken population for Tanzania Mainland. Chicken Population The number of households keeping chicken was 240,279 raising about 2,620,818 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country Mwanza ranked second out of the 21 Mainland regions. The District with largest number of chicken was Geita (468,300 chickens, 31% of the total number of chickens in the region) followed by Sengerema (577,470 22%), Kwimba (399,645 15%), Magu (342,581 13%), Missungwi (249,636 9%) and Ilemela (45,290 2%). (Chart 3.132 and Map 3.38). However Missungwi district had the highest density (295 head per km2) (Map 3.55 and 3.56) Chicken Population Trend The overall annual population growth rate during the eight-year period from 1995 to 2003 was -0.2 percent. The population increased at a rate of 2.5 percent from 1995 to 1999 after which it decreased at a rate of -2.7 percent for the four year period from 1999 to 2003. (Chart 3.133). Ninety eight percent of all chickens in Mwanza region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chickens’ more-or-less the same as that of the total chickens in the region. 0 450,000 900,000 Number of Chickens Geita Sengerema Kwimba Magu MissungwiUkerewe Ilemela District Chart 3.132 Total Number of Chickens by District 2,623,825 2,965,850 2,650,264 - 1,500,000 3,000,000 Number of Chicken 1994/95 1998/99 2002/03 Year Chart 3.133 Chicken Population Trend Magu Misungwi Kwimba Nyamagana Ilemela 176.3 295.2 0 257 93.4 87.7 155.2 288 Sengerema Geita Ukerewe Nyamagana Kwimba Misungwi Geita Ilemela Magu 0 249,636 806,975 45,290 342,581 399,645 199,222 577,470 Sengerema Ukerewe 640,000 to 810,000 480,000 to 640,000 320,000 to 480,000 160,000 to 320,000 0 to 160,000 Number of Chicken MAP 3.55 MWANZA Number of Chicken Per Sq Km Chicken Density by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Chicken Population by District as of 1st Octobers 2003 Chicken Density Chicken Population MAP 3.56 MWANZA 240 to 300 180 to 240 120 to 180 60 to 120 0 to 60 RESULTS AND ANALYSIS 86 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 Chicken Flock Size The results indicate that about 85 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 8 chickens per holder. About 15 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 29 chickens per holder. Only 0.2 percent of holders kept the flock sizes of more than 100 chickens at an average of 154 chickens per hold (Table 3:14) Improved chicken breeds (layers and broilers) The Layer population in Mwanza region increased at an annual rate of 16.4 percent for the period of four years from 45,600 in 1995 to 92,228 in 1999, after which it decreased at rate of -2.6 percent to 29,446 in 2003. The number of improved chicken was most significant in Misungwi district followed by Sengerema district (Chart 3.134) 3.12.6. Other livestock There were 152,904 ducks, 9786 turkeys, 17,570 rabbits and 9038 donkeys in rural agricultural households of Mwanza region. Table 3-15: gives the number of livestock kept in each district. The largest number of ducks in the region was found in Ukerewe district. (35% of all ducks in the region)., followed by Sengerema (33%), Geita (16%), Magu (7%), Ilemela (4%), Missungwi (3%) and Kwimba (2%) (Table 3.13). Table 3:14 Total Number of Households and Chickens Raised by Flock Size Chicken rearing Households Flock size Number % Number of Chicken Average chicken by households 1 - 4 60,907 25 167,268 3 5 - 9 72,432 30 476,437 7 10 - 19 70,807 30 897,803 13 20 - 29 21,625 9 476,439 22 30 - 39 8,389 4 272,062 32 40 - 49 2,667 1 115,708 43 50 - 99 2,185 1 133,911 61 100+ 528 0 81,189 154 Total 239,539 100 2,620,818 11 Table 3.15: Head Number of Other Livestock by Type of Livestock and District Type of livestock District Ducks Turkeys Rabbits Donkeys Other Ukerewe 54,204 232 3,761 0 0 Magu 10,683 4,972 13,809 0 0 Kwimba 2,465 0 0 6,271 0 Sengerema 49,784 4,354 0 0 1,461 Geita 25,237 0 0 2,415 1,299 Missungwi 5,248 229 0 353 0 Ilemela 5,283 0 0 0 0 Total 152,904 9,786 17,570 9,038 2,760 4,010 0 2,912 0 0 0 2,945 9,182 0 1,299 18,885 0 695 0 0 10,000 20,000 Number of Chickens Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela District Chart 3.134 Number of Improved Chicken by Type and District Layers Broilers 45,600 92,228 29,446 - 50,000 100,000 Number of layers 1995 1999 2003 Year Chart 3.135 Layers Population Trend RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 88 3.12.7 Pests and Parasites Incidences and Control Ticks problems were reported by 71 percent of livestocks-keeping households while tsetsefly problems were reported by 3 percent of such households. (Chart 3.136) shows that there was predominance of tick related diseases over tsetsefly related diseases. Incidences of both problems were highest in Missungwi district but lowest in Kwimba district. (Map 3.57). The most popular method of controlling ticks was spraying with 68 perent of all livestock-rearing households in the region using that method. Other methods used were dipping (2.3%), smearing (2.0%) and other traditional methods like hand picking (6.4%). However, 21.3% of livestock-keeping households did not use any method. Deworming Livestock rearing households that dewormed their animals were 65,218 (46.3% of the total livestock rearing households in the region). Deworming was practiced in 52,413 cattle households (8.4%), 25,927 goat households (6.6%), 25,566 sheep households and (2.9%), 7,320 pig households (4.5%) (Chart 3.137). 3.12.8. Access to livestock services Access to Livestock Extension Services The total number of households that received livestock advice was 34,262 representing 24 percent of the total livestock rearing households and 10.1 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 20.2 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (20.0%); Co-operatives (20.0%) and large- scale farmers (19.9%). Chart 3.136 Percentage of Livestock Keeping Households that Reported Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela District Percent Ticks Tsetseflies 0 25 50 Percent Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela District Chart 3.137 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs Chart 3.138 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Poor, 3% Average, 12% Good, 47% Very Good 25% No good, 13% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 89 About 47 percent of livestock rearing households described the general quality of livestock extension services as being good, 12 percent said they were average and 25 percent said they were very good. However 13 percent of the livestock rearing households said the quality was not good whilst 3 percent described them as poor. (Chart 3.138) . Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 59 percent of the livestock rearing households live more than 14 kms from a veterinary clinic. Only 41 percent of the them accessed services within 14 kms from their dwellings (Table 3.14). The district with the worst access to veterinary clinics where 85 percent of the households living more than 14 km from a veterinary clinic. Missungwi district was the least affected with only 7 percent of the households living more than 14 kilometers from the veterinary clinic. 3.12.8.3 Access to Village Watering Points/Dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 67,294 (80% of livestock rearing households in Mwanza region) whilst 14,222 households (17%) resided between 5 and 14 kms. However, 2,144 households (3%) had to travel a distance of 15 km or more to the nearest watering point (Chart 3.142) Ukerewe district had the best access to village watering points with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Missungwi, Kwimba and Ilemela districts. Also in Magu district about 30 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.142). Chart 3.141 Number of Households by Distance to Village Watering Points Less than 5 kms, 67,293, 80% 5-14 kms, 14,219, 17% 15 or more kms, 2,094, 3% Chart 3.139 Number of Households by Distance to Verinary Clinic Less than 14km, 47,572, 41% More than 14km, 68,864, 59% Chart 3.140 Percentage of Households by Distance to Verterinary Clinic and District 0 50 100 Ukerewe M agu Kwim ba Sengerem a Geita M issungwi Ilemela District Percentage of Households Less than 14 kms More than 14kms Chart 3.142 Percentage of Households by Distance to Village Watering Point and District 0 50 100 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela District Percentage of Households Less than 5 kms 5-14 kms 15 or more kms RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 90 3.12.9. Animal Contribution to Crop Production Use of Draft Power Use of draft animals to cultivate land in Mwanza region was very limited with only 93,867 households (27.6% of the total agricultural households in the region) using them (Chart 3.139). The number of households that used draft animals in Kwimba was 31,837 representing (34 percent of the households using draft animals in the region) Magu they were 23,088 households (25%), Missungwi, 16,838 households, (18%), Geita 16,044 households, (17%), Sengerema, 5,899 households, (6%), Ilemela 161 households, (0.2%). Use of draft animals was not reported in Ukerewe district. The region had 335,501 oxen (with 141,016 oxen in Magu and 89,023 in Geita) that were used to cultivate 211,975 hectares of land. This representing only 11.5% of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Magu district 68,708 ha, (32.4% of the total area cultivated using oxen). Use of Farm Yard Manure The number of households using mostly farm yard manure in Mwanza region was 98,394 (0.3% of the total crop growing households in the region) (Chart 3.145). The total area applied with organic fertilizer was 92,815 hectares. Magu and Sengerema had the largest area with organic manure application (Chart 3.146 and Map 3.59). 3.143 Number of Households Using Draft Amimals Using draft animal, 93,867, 27.6% Not using draft animal, 246,218, 72.4% 0 20,000 40,000 N um ber o f H o useho lds Kwimba Magu Missungwi Geita Sengerema Ilemela Ukerewe District Chart 3.144 Number of Households Using Draft Animals by District Chart 3.145 Number of Households Using Organic Fertilisers Not Using Organic Fertilizer, 240,535, 71% Using Organic Fertilizer, 98,394, 29% Chart 3.146 Area of Application of Organic Fertilisers by District - 0 12500 25000 Magu Sengerema Geita Ukerewe Missungwi Kwimba Ilemela District Area of Fertiliser Application (ha) Farm Yard Manure Compost Misungwi Nyamagana Kwimba Ilemela Ukerewe Magu 0 0 83 0 401 0 0 0 0% 0% 0% 0% 1% 0% 0% 0% Sengerema Geita Nyamagana Kwimba Ilemela Magu Missungwi Geita Ukerewe Sengerema 0 2,590 15,670 11,263 12,589 18,718 13,014 19,831 0% 63% 75% 60% 81% 61% 77% 81% Number of Households Infected With Ticks MAP 3.57 MWANZA Number of Households Using Draft Animals MAP 3.58 MWANZA Number and Percent of Households Using Draft Animals by District Tanzania Agriculture Sample Census Number and Percent of Households Infected With Ticks by District Number of Households Using Draft Animals Percent of Households Using Draft Animals Number of Households Infected With Ticks Percent of Households Infected With Ticks 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 320 to 410 240 to 320 160 to 240 80 to 160 0 to 80 RESULTS AND ANALYSIS 91 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13 Fish Farming The number of households involved in fish farming in Mwanza region was 326, representing 0.1 percent of the total agricultural households in the region (Chart 3.148). Magu was the leading district with 138 households (42% of agricultural households involved in fish farming). This was followed by Kwimba (99 households, 30%) and Missungwi (336 households, 27%). Fish farming was not practiced in the remaining five districts. (Chart 3.144 and map 3.59). The main source of fingerings was the NGO’s/Projects which provided fingering to 99 percent of the fish farming households. All fish farming households in the region used the dug-out pond system and the main fish species is Tilapia. The number of fish harvested in Mwanza region was 4,930 of which 1,972 were Tilapia ( Chart 3.149). None of the fish farming households sold fish. 3.14 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was the service that was located furthest from most of the household dwellings. It was located at an average distance of 88.3 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (52.3), tertiary market (41.4), hospital (31), secondary markets (21.1) secondary school (12.6), health clinic (6.0), all weather roads (4.2), primary market (2.5), primary school (2.5) and feeder road (1.3) (Table 3.15). Table 3.16: Mean Distances from Holders Dwellings to Infrastructures and Services by Districts Mean Distance from Household Dwelling to Infrastructures and Services by District. District Secondary School Primary School All weather road Feeder road Hospital Health Clinic Regional Capital Primary Market Secondary Market Tertiary Market Tarmac road Ukerewe 17.9 1.1 0.9 0.8 18 4.1 70.0 1.1 11.8 21.5 22.7 Magu 12.5 3.1 3.0 2.0 25 7.3 79.0 3.1 19.3 30.4 14.5 Kwimba 9.6 2.5 4.7 1.7 26 4.8 85.6 2.5 11.9 28.8 27.4 Sengerema 12.1 1.6 4.3 0.6 30 6.3 64.7 1.6 34.9 33.5 59.8 Geita 13.5 3.4 5.6 1.4 45 7.1 136.4 3.4 23.9 65.1 110.5 Missungwi 11.1 2.0 5.3 1.2 26 4.3 63.8 2.0 15.6 55.0 19.6 Ilemela 10.8 1.8 1.7 1.0 16 5.0 20.9 1.8 11.5 17.4 9.7 Total 12.6 2.5 4.2 1.3 31 6.0 88.3 2.5 21.1 41.4 52.3 Chart 3.147 Number of Households Practicing Fish Farming - Mwanza Households Prcticing Fish Farming, 326, 0.1% Households Not Prcticing Fish Farming, 339,758, 99.9% 0 20 40 60 80 100 120 140 Number of Households Magu Kwimba MissungwiUkereweSengeremaIlemela Geita District Chart 3.148 Number of Households Practicing Fish Farming by District -Mwanza Chart 3.149 Fish Production Number of Tilapia, 1,972, 40.0% Number of Carp, 2,958, 60.0% RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 3.15 Poverty Indicators The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government 3.15.1 Type of toilets A large number of rural agricultural households use traditional pit latrines (290,238 households, 85.3% of all rural agricultural households), 7,164 households (2.1%) use improved pit latrines and 11,317 (3.3%) use flush toilets. However, 31,365 households (9.2%) had no toilet facilities (Chart 3.150). The distribution of the households without toilets within the region indicates that 34.6 percent of them were found in Geita district and 19.2 percent were from Kwimba. The percentages of households without toilets in other districts were as follows Sengerema (18.2%), Magu (11.0%), Ukerewe (8.2%), Missungwi(6.0%) and Ilemela (2.8%). (Map 3.60) 3.15.2 Household’s Assets Bicycles are owned by many rural agricultural households in Mwanza region with 216,332 households (63.6% of the agricultural households in the region) owning this asset, followed by radio (214,481 households, 63.1%), iron (56,452 households, 16.6%), wheelbarrow (19,607 households, 5.8%), mobile phone (6,390 households 1.9%), television/video (3,697 households, 1.1%), vehicle (2891 households 0.8%) and landline phone (177 households, 0.4%) (Chart 3.152). 3.15.3 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region with 73.6 percent of the total rural households using this source of energy followed by hurricane lamp (20.5%), pressure lamp (4.0%), mains electricity (0.8%), firewood (0.6%), solar (0.2%), candle (0.1%) and gas or biogas (0.1%) (Chart 3.148). Chart 3.150 Percentage Distribution of Agricultural Households by Type of Toilets Flush Toilet, 3.3 No Toilet , 9.2 Improved Pit Latrine , 2.1 Other Type, 0.0 Traditional Pit Latrine, 85.3 Chart 3.151 Percentage of Households Owning the Assets 5.8 1.9 1.1 1.0 0.4 16.6 63.1 63.6 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Bicycle Radio Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percen t Chart 3.152 Percentage Distribution of Households by Main Source of Energy for Lighting Mains Electricity, 1% Firewood, 1% Pressure Lamp, 4% Solar, , 0% Candles, , 0% Hurricane Lamp, 21% Gas (Biogas), 0% Wick Lamp, 73% Nyamagana Misungwi Kwimba Magu Ukerewe Ilemela Sengerema 1,883 6,016 3,442 2,585 864 10,861 5,714 13% 6% 12% 0% 6% 7% 8% 9% Geita 0 8,000 to 11,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Nyamagana Kwimba Misungwi Magu Ukerewe Ilemela 138 99 90 0 0 0 0 0% 0% 0% 0% 0% 0% 0% 0% Sengerema Geita 0 120 to 140 90 to 120 60 to 90 30 to 60 0 to 30 Number of Households Practicing Fish Farm MAP 3.59 MWANZA Number of Households Without Toilets MAP 3.60 MWANZA Number and Percent of Households Without Toilets by District Tanzania Agriculture Sample Census Number and Percent of Households Practicing Fish Farm by District Numberof Households Without Toilets Percent of Households Without Toilets Number of Households Practicing Fish Farm Percent of Households Practcing Fish Farm RESULTS AND ANALYSIS 94 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Cooking Charcoal 2.72% Crop Residues 0.28% Livestock Dung 0.04% Bottled Gas 0.28% Mains Electricity 0.14% Solar 0.10% Parraffin / Kerocine 0.03% Gas (Biogas) 0.01% Firewood 96.4% Chart 3.156 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Unprotected Spring Piped Water Uprotected Well Surface Water (Lake / Dam Protected Well Protected / Covered Spring Other Main source Percent of Households Dry Season Wet Season 3.15.4 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households in Mwanza region. This is followed by charcoal (2.7%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.0%), livestock dung (0.04%), parrafin/kerosene (0.03%) and gas/biogas (0.01%). 3.15.5 Roofing Materials The most common material used for roofing the main dwelling was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households. However this was closely followed by iron sheets (39.9%), then grass/mud (9.1%), tiles (0.7%), asbestos (0.5%), concrete (0.4%) and others (0.2%). (Chart 3.154), Map 3.61 Missungwi district had the highest percentage of households with grass/leaves roofs (74%), and was followed by Kwimba (60%),Sengerema (49%), Geita (46%), Magu (41%), Ilemela (40%) and Ukerewe (36%). (Chart 3.155) 3.15.6 Access to Drinking Water The main source of drinking water for agricultural households in Mwanza region was the unprotected spring (36 percent of households use unprotected spring during the wet season and 24 percent of the households during the dry seasons. This was followed by piped water 9 percent during the wet season and 22 percent during the dry season, unprotected well (20 percent of households during the wet season and 21 percent during the dry season), surface water (17 percent during the wet season and 18 percent during the dry season), Chart 3.154 Percentage Distribution of Households by Type of Roofing Material Grass/Mud 9.1% Grass/Leaves 49.3% Tiles 0.7% Iron Sheets 39.9% Asbestos 0.5% Concrete 0.4% Others 0.2% Chart 3.155 Percent of Households with Grass/Leaves Roofs by District 36 40 41 46 49 60 74 0 25 50 75 100 Missungwi Kwimba Sengerema Geita Magu Iemela Ukerewe District Percent RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 96 protected well (9 percent of households for each season) and protected/covered spring (4 percent of households for each season) (Chart 3.152) About 55 percent of the rural agricultural households in Mwanza region obtain drinking water within a distance of less than one kilometer during wet season compared to 44 percent of the households during the dry season. However, 45 percent of agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 56 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.157). 3.15.7 Food Consumption Pattern Number of Meals per Day The majority of households in Mwanza region normally had two meals per day (72.2 percent of the households in the region), this is followed by 3 meals per day (25.8 percent) and 1 meal per day (1.5 percent). Only 0.5 percnt of the households have 4 meals per day (Chart 3.158). Ilemela district had the largest percentage of households eating one meal per day whilst Kwimba had the highest percentage of households eating 3 meals per day (Table 3.17 and Map 3.62) Chart 3.17: Number of Households by Number of Meals the Household Normally has per Day and District Number of meals per day District One % Two % Three % Four % Total Ukerewe 83 0.3 30,548 92.8 2,125 6.5 153 0.5 32,909 Magu 1,488 2.6 41,378 73.4 13,246 23.5 247 0.4 56,359 Kwimba 206 0.4 22,895 50.0 22,612 49.4 100 0.2 45,813 Sengerema 304 0.5 46,480 71.9 17,877 27.6 0 0.0 64,661 Geita 2,123 2.3 76,687 82.2 13,843 14.8 634 0.7 93,287 Missungwi 574 1.7 17,365 50.9 15,787 46.3 406 1.2 34,132 Ilemela 468 3.6 10,323 79.9 2,132 16.5 0 0.0 12,923 Total 5,246 1.5 245,676 72.2 87,622 25.8 1,540 0.5 340,084 Chart 3.157 Percentage of Households by Distance to Main Source of Drinking Water and Season 0 20 40 less than 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season Chart 3.158 Number of Agriculural Households by Number of Meals per Day One Meal 5,245, 1.5%. Three Meals, 87,622, 25.8% Two Meals, 245,676, 72.2% Four Meals, 1,541, 0.5% Kwimba Missungwi Nyamagana Magu Ukerewe Ilemela Geita Sengerema 22,612 15,787 13,246 2,125 2,132 0 13,843 17,877 49% 24% 7% 17% 0% 47% 15% 28% 20,000 to 23,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Nyamagana Kwimba Missungwi Geita Ilemela Magu Ukerewe Sengerema 0 27,271 25,401 42,764 5,210 23,200 11,859 31,889 0% 60% 74% 46% 40% 41% 36% 49% Number of Households Using Grass/Leaves For Roofing MAP 3.61 MWANZA Number of Households Eating 3 Meals Per Day MAP 3.62 MWANZA Number and Percent of Households Eating 3 Meals Per Pay by District Tanzania Agriculture Sample Census Number and Percent of Households Using Grass/Leaves for Roofing Material by District Number of Households Eating 3 Meals Per Day Percent of Households Eating 3 Meals Per Day Number of Households Using Grass/Leaves For Roofing Percent of Households Using Grass/Leaves For Roofing 36,000 to 43,000 27,000 to 36,000 18,000 to 27,000 9,000 to 18,000 0 to 9,000 RESULTS AND ANALYSIS 97 RESULTS – Household Characteristics ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 212,222 (62% of the agricultural households in Mwanza region) with 116,948 households (55.1% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (18.7%). Very few households had meat three or more times during the respective week. About 38 percent of agricultural households in Mwanza region did not eat meat during the week preceding the census. (Map 3.66). Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 303,513 (89.2% of the total agricultural households in Mwanza region) with 59,801 households (19.7% of those who consumed fish) consuming fish twice during the respective week. In general, the percentage of households that consumed fish twice or more during the week in Mwanza region was 244,378. (80.5% of the agricultural households, that ate fish in the region during the respective period). About 10.8 percent of the agricultural households in Mwanza region did not eat fish during the week preceding the census (chart 3.159 and Map 3. 65). 3.15.8 Food Security In Mwanza region, 92,100 households (27.1% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 12,614 (3.7%) said they sometimes experience problems, 10.0 % had often experienced problems and 6.1 percent always had problems with satisfying the household food requirements. About 53 percent of the agricultural households said they did not experience any food sufficiency problems. (Map 3.67) 3.15.9 Main Sources of Cash Income The main cash income of the households in Mwanza region was the selling of food crops (27.2 percent of smallholder households), followed by casual labour (20.9%), selling of cash crops (15.8%), business (9.9%) fishing (8.2%) and cash remittances (4.2%), wages salaries (4.1%), sales of forest product (2.3%), sales of livestock and their products (1.8%) (Chart3.160). Chart 3.159 Number of Households by Frequency of Meat and Fish Consumption 0 75,000 150,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Chart 3.160: Percentage Distribution of the Number of Households by Main Source of Income 4.5, % 2.3, % 1.8, % 4.1% 4.2% 9.9% 28% 16% 21% Sales of Food Crops Other Casual Cash Earnings Sales of Cash Crops Business Income Cash Remittance Wages & Salaries in Cash Sale of Livestock Sale of Forest Products Sale of Livestock Fishing Other Magu Nyamagana Misungwi Kwimba Ukerewe Ilemela 20,003 17,957 12,927 9,668 4,897 17,667 33,828 36% 0% 38% 39% 29% 38% 27% 36% Sengerema Geita 0 Kwimba Misungwi Nyamagana Magu Ilemela 1,947 13,590 6,992 0 9,403 477 22,826 3,899 6% 30% 21% 0% 17% 4% 25% 6% Sengerema Geita Ukerewe 28,000 to 34,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Number of Households Eating Meat Once Per Week MAP 3.66 MWANZA Number of Households Eating Fish Once Per Week MAP 3.64 MWANZA Number and Percent of Households Eating Fish Once Per Week by District Tanzania Agriculture Sample Census Number and Percent of Households Eating Meat Once Per Week by District Number of Households Eating Fish Once Per Week Percent of Households eating Fish Once Per Week Number of Households Eating Meat Once Per Week Percent of Households Eating Meat Once Per Week 20,000 to 23,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 RESULTS AND ANALYSIS 99 Magu Nyamagana Kwimba Misungwi Ukerewe Ilemela 21,084 0 8,330 15,932 8,175 4,723 20,892 2,964 37% 0% 24% 35% 25% 37% 22% 20% Sengerema Geita Number of Households Reporting Food Insufficiency MAP 3.65 MWANZA Tanzania Agriculture Sample Census Number and Percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 16,000 to 22,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 RESULTS AND ANALYSIS 100 REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 4 MWANZA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Mwanza Region Profile The regional profile describes the status of the Agriculture sector in the region and compares it with other region in the country. Mwanza region has the third largest utilised land area (approximately 700,000 ha) most of which is planted with annual crops, however permanent crops are also grown mainly as mixed crops with annuals but also small amounts of permanent mono-crop stands exist. The percent of land available to smallholders that was utilised during the census year was average compared to other regions, however the response to insufficiency of land was high (57%). Mwanza has two planting seasons and the short rainy season had a greater planted area than the long rainy season during the census year, however the area planted per household was greater in the long rainy season than in the short rainy season. The region has the largest planted area of maize and paddy per square kilometre and the largest planted areas under cassava in the country. It also has the second largest planted areas of cotton in the country. Compared to other regions, the area under sorghum and bean production is moderate to low. Vegetable production in Mwanza is moderate. Of the permanent crops mangos and oranges are the most important. The region has the fourth largest planted area under irrigation; however the number of households practicing irrigation has remained unchanged over the last 10 years. As with most regions, most land clearing is done by hand slashing. The region has the third largest planted area cultivated by oxen, however around 60 percent is cultivated by hand. Eighty percent of the planted area had no fertiliser, the remaining area was applied with farm yard manure and virtually no chemical fertiliser was used. Mwanza has the highest percent of unprotected storage in Tanzania with approximately 80 percent of households using sacks or open drums for storage. Most processing was done by neighbours’ machines and of the small amount of processed products sold, most was to the local market/trade store. The region had one of the lowest percent of households receiving extension services in the country. It has low to moderate number of trees planted by smallholders and a moderate number of households with erosion control/water harvesting structures; however in has the largest number of erosion control and water harvesting bunds in the country. Mwanza has a high population of livestock. It has the second highest population of cattle in the country and has the highest density. Improved cattle types are virtually absent in Mwanza. The region has one of the highest densities of goats in the country; however it has low numbers of sheep and one of the lowest populations of pigs. It is the third highest milk producer in the country and the farm gate price for milk is very low. The region has the second highest population of chickens in the country and it has the highest density. The number of improved chickens is very low however egg production is relatively high. The region has one of the highest utilization of organic fertilizer in terms of area although the application rate per household was average. It has a moderate to high use of draft animals for cultivation. REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 The rate of disease infection is moderate to low and considering the high cattle population it has a low incidence of trypanosomiasis. Access to livestock infrastructure and services is moderate to poor. Mwanza has the highest number of smallholders receiving extension services from Large Scale Farmers. However, this is still a very small number compared to extension provision from the government. There are a small number of fish farmers in the region. Mwanza has a high population of livestock. It has the second highest population of cattle in the country and has the highest density. Improved cattle types are virtually absent in Mwanza. The region has one of the highest densities of goats in the country; however it has low numbers of sheep and one of the lowest populations of pigs. It is the third highest milk producer in the country and the farm gate price for milk is very low. The region has the second highest population of chickens in the country and it has the highest density. The number of improved chickens is very low however egg production is relatively high. The region has one of the highest utilization of organic fertilizer in terms of area although the application rate per household was average. It has a moderate to high use of draft animals for cultivation. The rate of disease infection is moderate to low and considering the high cattle population it has a low incidence of trypanosomiasis. Access to livestock infrastructure and services is moderate to poor. Mwanza has the highest number of smallholders receiving extension services from Large Scale Farmers. However, this is still a very small number compared to extension provision from the government. There are a small number of fish farmers in the region. 4.2 District Profiles The following district profiles highlight the characteristics of each district and compare them in relation to population, main crops, livestock, production, productivity, access to services, resources and levels of poverty. 4.2.1 Ukerewe Ukerewe district has the second lowest number of households in the region and it has a low percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Ukerewe district is permanent crop farm, followed by annual crop farming. The district has the highest percent of households with no off farm income activities (95%) also it has the highest percent of households with more than two members with off farm income, compared to other districts in the region. Ukerewe has a relatively low percent of female headed households (13%) and it has one of the highest average age of the household head in the region. With a household size of six members per households it is average for region. Ukerewe has the highest literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. The district has the second lowest planted area in the region and third largest planted area per households (0.5ha in the long rainy season and 0.77 ha in the short rainy season), the district is moderately important for maize production in the region with a planted area of over 1,617 ha, and the planted area per maize growing household is also lowest for the region. The REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 district has the lowest planted area of paddy in the region with 1,268 hectares. Little sorghum is grown in the district. Cassava production is higher, accounting for 19 percent of the quantity harvested in the region. The district has a very small planted area of Irish potatoes (15 ha). The production of beans in Ukerewe district is low with a planted area of 428 ha. Ukerewe district has the second lowest groundnut planted area in Mwanza region with a planted area per groundnut growing household of 0.3 ha. Vegetables production is moderately important in the district. Although small, it has the second largest planted area with tomatoes, cabbage and chillies (74 ha, 13 ha and 37 ha respectively) Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. Compared to other districts, Ukerewe has the second largest planted area with permanent crops which is dominated by oranges (9,641 ha) and Bananas (2,480 ha). A small amount of mango is grown (252 ha). As with other districts in the region, most land clearing is done by hand slashing; however there is a substantial area with no land clearing indicating bare ground before planting. Practically all land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Ukerewe has lowest second planted area with improved seed in the region as well as the lowest proportion of households using improved seeds. Though small, the district has the second lowest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts, Ukerewe districts has the lowest level of insecticide use, the use of fungicides and herbicides is low and it has the largest percent area with irrigation compared to other districts with 17,023 ha of irrigated land. The most common source of water for irrigation is from Lake using hand bucket methods, flood is the most common means of irrigation water application followed by Gravity and no pump water is used. The most common method of crop storage in Ukerewe district is in sacks/open drum, however the proportion of households not storing crops is average for the region. Ukerewe has a lower number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Ukerewe is among the districts with the lowest percentage of the households processing crops in Mwanza region and is almost all done by neighbourrs machine. The district also has the second lowest percent of households selling crops to local market and trade store compared to other districts and no sales to large scale farms, no access to credit in the district were reported. Comparatively larger number of households receives extension services in Ukerewe district and all of this is from the government, the quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Ukerewe (with 2,109 planted trees) and is mostly maesopsis Berchemoides and Gravellis. The third lowest proportion of households with erosion control and water harvesting structures is found in Ukerewe district is mostly erosion control bunds and water harvesting bunds, however it also has the number of vertiver grass and drainage ditches. The district has the second lowest number of cattle in the region and they are almost all indigenous. Goat production is less compared to other districts; also it has the lowest population of sheep in the region. It has reported to have no number of pigs in the districts and a moderate number of chickens. Some ducks and turkeys are also found in the district, a number of households reported tsetse and tick problems and it has the second lowest number of households deworming livestock, no household reported the use draft animals, also no number of households reported to practice fish farming. It has amongst the best access to primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst accesses to regional capital, secondary schools and tarmac roads. The percentage REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 of households without a toilet facility in Ukerewe district is comparatively high (7.8%). Also it is amongst the districts with the lowest percent of households owning wheel barrows, vehicles and bicycles. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the districts is iron sheets (58%), also it has a comparatively low percent of households with grass/leaves (36%) compared to other districts. The most common source of drinking water is from protected wells, it is one of the districts with the highest percent of households having two meals per day. The district had third low highest percent of households that did not eat meat and the lowest percent of households that did not eat fish during the week prior to enumeration and most households never had problems with food satisfaction. 4.2.2 Magu Magu district has the third largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important activity for smallholder households in Magu district is Annual crop farming, followed by Trees/forest resources. However, the district has the highest percent of households with no farm incomes activities (89%), and the highest percent of households with more than two member with off-farm income. Compared to other districts in the region. Magu has relatively low percent of female headed households (18%) and it has one of the higher average size in the region, with an average households size of 5 members per households it is slightly below average for the region. Magu has a comparatively high literacy among smallholder households (67%). The land area utilized per household (1.9 ha) which is slightly lower to regional average of (2.0 ha). The district has the third largest planted area in the region and the forth largest planted area per (0.8 ha) in the long rainy season and (0.6 ha) in the short rainy season. The district is moderately important for maize production in the region with a planted area of over 208,512 ha and the planted area per households is 0.8 ha which more than average for region of is 0.7 ha. Paddy production is another important crop with a planted area of 8,826 hectares; however it is the third lowest in the region. Sorghum is the third highest planted area in the region, while Irish potatoes and wheat are not produced in the district; the district has low planted area of cassava accounting 11 percent of the cassava planted area of 3,328 oilseed and vegetables crops are not important in Magu with only 3 percent of the groundnuts grown in the district but there is large quantities of cotton grown in the Magu district. Permanent crops are not important in Magu district (11% of the total permanent crop planted area in Mwanza region), the permanent crops in the district include mango (9 ha), sugarcane (12 ha), other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, and a relatively small area of bare ground before planting. Practically all land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist, Magu has the small planted area with improved seed in Mwanza region. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer) and practically all is with farm yard manure. Compared to other districts in the region, Magu district has the largest area of insecticide and fungicide use and the use of herbicides is relatively small, it has the fifth REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 largest area of irrigation in the region with 246 ha of irrigated land, the most source of water for irrigation is from wells, Lake and rivers, almost all water application is done by using Bucket/watering can. The most common method of crop storage in Magu is locally made traditional cribs, the district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Magu district has a high percent of households processing crops in the region and is almost all done by neighbour machine. No processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Magu district and almost all of this is from the government and NGO/Development Project, the quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Magu district (with 4,342 planted trees) and is mostly Eucalyptus spp and Azadritachta spp, Gravellis and Sienna Spp. The highest proportion of households with water harvesting bunds is found in Magu dusrict and it also has the highest number of erosion control bunds. The district has a largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is high compared to other districts; it has very small number of pigs in the district and the larger number of chickens, all of which are indigenous. Virtually no improved chickens are found in the district. The district has the largest number of ducks, and a small number of rabbits and turkeys are found in the district. A small number of households reported tsetse and tick problems in Magu district. A small amount of de- worming of livestock is practiced in the district; also it has the second largest number of households using draft animals. There is no fish farming in the district. The percentage of households without toilet facility in Magu district is average for the region; however it has the fourth highest percent of households with no toilet facilities. It has the second highest percent of households owing radio, mobile phone, vehicles and Tv/Video. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs 41 percent and 42 percent of households have iron sheet roofing. The most common source of drinking water is from protected wells. Seventy three percent of the households in the district reported having two meals per day. The district had a highest percent of households that did not eat meat and the fourth lowest percent of households that did not eat fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4. 2.3 Kwimba Kwimba district has fourth highest number of households for the region and it has the largest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming, it has very small number of livestock only households and pastoralists were found in the district. The most important livelihood activity for smallholder households in Kwimba district is Annual crop farming, followed by off farm income. It has the larger percent of households with no off incomes activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kwimba district has a relatively high percent of female headed households (21%) and it has one of the highest average ages of the households head. With average household size of 6 members per households and it is average for the region. Kwimba district has a comparatively moderate literacy rate among smallholders. It has higher utilized area per household (2.0 ha) which is equivalent to regional average of 2.0 ha. The district is important for maize production in the region with a planted area of 39,709 ha and the planted area per households is among the highest in the region. Paddy production is also REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 important with a planted area of 20,641 hectares and the production of sorghum is high. Cassava and beans production in Kwimba district was small, Irish potato and wheat was not grown. Oilseeds crops and vegetables are moderately important in the district, however, whilst the district has one of the largest planted areas with groundnuts; sunflower is not grown in the disrict. Traditional crops (e.g. tobacco and cotton) are grown in the district, cotton production is moderately high, whilst tobacco is not important. Compared to other districts in the region, Kwimba district has the smallest planted area with permanent crops (0.8 percent of total permanent area planted in the region) mostly is dominated by Sour soup (533 ha), Mango (53 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is done by hand. The use of inputs in the region is very small, however districts differences exist. Kwimba district has the highest planted area with improved seed; the district also has the highest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts, Kwimba district has the lower area planted with insecticides but has the fourth highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the highest for herbicides. It has one of the smallest areas of irrigation 8,752 ha. The most common source of water for irrigation is from rivers using land buckets/bucket. Watering cans are the most popular means of irrigation water application. The most common method of crop storage is in locally made traditional cribs. The proportion of households not storing crops in Kwimba district is relatively small. The number of households selling crops in the district is among the smallest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The smallest percent of households processing crops in the region is found in Kwimba district and processing is mostly done by neighbor’s machine. The district has the larger number of households processing crops on farm by machine. It also has the fourth largest number of households processing crops on farm by hand. Most households that sell crops sell to local market/trade store. Access to credit in the district is very small. A very small number of households receive extension services in Kwimba district and almost of all this is from the government. The quality of extension services was rated between very good and average by the majority of the households. Tree farming is not important in Kwimba district (with only 1,962 planted tree ) and most of them are Eucalyptus spp, and Gravellies. Kwimba district has the largest proportion of households in the region using water harvesting bunds. Kwimba district has the fourth highest number of cattle in the region and most of them are indigenous. It has also the fourth highest number of goats in the region, Kwimba has the highest number of sheep in the region, however it no pigs. It has the third highest number of chickens in the region and a relatively high number donkey is found in the district. A small number households reported tsetse and tick problems in kwimba district and it had one of the smallest numbers of households worming livestock. The use of draft animals in the district is highest in the region and very few households practice fish farming. It is amongst the districts with the best access to primary schools, feeder roads, all weather roads, and health clinics, tertiary market, compared to other districts. However, it has the worst access to secondary schools, Regional capital, and tarmac road. Kwimba district has a larger number of households with no toilet (13%). The district has the higher percent of households owning bicycle, radio and iron. The common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the second largest percent of households with grass roofs with only 25 percent of households having iron sheet. The most common source of drinking water is protected wells and it has fifty percent of households having two meals per day and the highest percent with 3 meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration. Most households seldom had problems with food satisfaction. REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 4.2.4 Sengerema Sengerema district has the second highest number of households in the region and it is one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district The most important livelihood activity for smallholder in Sengerema district is Annual crop farming, followed by permanent crop farming, off-farm income, tree/forest resources and livestock keeping/herding. The district has the fourth highest percent of households with no off incomes activities and the second largest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sengerema has a moderate percent of female headed households (15%) and it has a slightly low average age of the household head. With an average household size of 7 members per household it is bit higher than the regional average. Sengerema has the higher literacy rate among smallholders’ households in the region (70%). It has one of the highest utilized land area per household (2.3 ha) which is slightly higher the regional average of 2.0 ha per household. The district has higher planted area in the region, however it has the third lowest planted area per household (0.5 ha) both to short and long rainy season. The district is important for maize production with a planted area of 32,278 ha, however the planted area per household is moderate compared to other districts in the region. Paddy production is also important with a planted area of 15,371 hectares and the production of sorghum is moderately high. Wheat is not grown in the district. The district has the highest percent of cassava planted area in the region and it has virtually no irish potatoes. The production of beans in Sengerema district is relatively high in the region and oil seed crops are important, the district has a large planted area of groundnuts, however it did not have sunflower production. Traditional crops (e.g. tobacco and cotton), cotton production is relatively high, with very small amount of tobacco (3,197 ha). And compared to other districts in the region, Sengerema has more planted area with permanent crops (3,197 ha) dominated by oranges (1,557 ha) and Banana (644 ha), other permanent crops are either not grown or grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however ‘’no land clearing ‘’ is relatively high indicating bare land before cultivation. Practically all land preparation is done by hand, however very small amount of land preparation is done by Bush clearance. The use of inputs in the region is very small, however district differences exist. Sengerema has a moderate planted area with improved seed compared to other districts. The district has the largest planted area with fertilizers and most of this is with farm yard manure. Compared to other districts in the region, Sengerema district has the third highest percent of its planted area with insecticides in the region. The use of fungicides was one of the lowest in the region and virtually none was used. It has the smallest planted area with irrigation in the region with only 683 ha of irrigated land, rivers, wells and dam is used as the source of irrigation water and hand bucket was mainly used Buckets/Water cans are the most common means of irrigation water application. The most common method of crop storage is in locally made cribs; however the proportion of households not storing crops in the districts is one of the highest in the region. The district has the high number of households selling crops and the main reason for not selling is insufficient production. Sengerema district has the highest percent of households processing crops on the farm by hand and a small percent of households processed crops mainly using neighbours machine and on farm by machine. Access to credit is very small in the district and the main reason for not using credit is did not know how to get credit REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 A comparatively small number of households receive extension services in Sengerema district and all of this is from the government. The quality of extension services was rated between good and average by most of the households. Tree farming is important in Sengerema (with 10,304 planted trees) and is normally with Eucalyptus spp, Cyprus spp, and Maesopsis Berchemoides. It has the smallest number of erosion control and erosion control bunds, Gabion/sand bag, tree belts The district has higher number of cattle in the region and they are mostly all indigenous. Goat and Sheep production is higher in the region and no pigs found in the district. It has a comparatively highest number of chickens, small numbers of ducks and turkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Sengerema district and has the highest number of households de-worming livestock. The use of draft animals in the district is small and no fish farming is practiced in the district. It is amongst the districts with the best access to secondary schools, feeder roads, and health clinics and primary markets: however it has one of the worst accesses to the regional capital, secondary markets and tarmac roads. Sengerema has high percent of households with no toilet facilities (9%). The district has the largest percent of households owning radios and bicycles and mobile phones. Very small number of households reported owning vehicles and television/ videos. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the larger percent of households with grass roofs (49%) and only 44 percent of households having iron sheets. The most common source of drinking water is from unprotected well and protected well. It has seventy two percent of households having two meals per day compared to other districts and it has twenty seven percent of households with 3 meals per day. The district had the second highest percent of households that did not eat meat during the prior to enumeration; however it has third lowest percent of households that did not eat fish during the preceding week. Most households in the districts never had problems with food satisfaction. 4.2.5 Geita. Geita disrict has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. A very small number of households keep cattle only and there are no pastoralists in the district. The most important livelihood activity for smallholder households in Geita district is Annual Crop Farming, followed by tree/forest resources and off farm income. However, the district has the higher percent of households with no off farm income activities (90%) and among the lowest percentage of households with more than one member with off-farm income compared to other districts in the region. Geita has a relatively low percent of female headed households (11%) and it has the highest average household size of 7 members per household. Geita has a comparatively moderate literacy rate among smallholder household, about 62% of the smallholder households in the district. The literacy rate for the heads of household is also slightly moderate (57%) compared to other districts in the region. It has the smallest utilized land area per household (1.9 ha) and it has the highest unutilized area in the region suggesting less land pressure than in other districts. The total planted area is greater than in other districts in the region due to the presence of good long and short seasons, however it has the second highest planted area per household (0.7 ha) attributed to the high number of smallholders in the districts. The district is moderately important for maize production in the region with a planted area of over 64,083 ha; however the planted area per household is among the lowest in the region. Paddy production is another important crop with a planted REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 area of 24,726 ha and the production of sorghum is moderately high. Cassava production is moderate accounting for 16 percent of the quantity harvested in the region. The district has a large planted area of Irish potatoes (67 ha) and it is the only district in the region that grows this crop. The production of beans in Geita is much higher than in other districts in the region with planted area of 17,055 ha .Also oilseeds crops are important in Geita and 41 percent of the area planted with groundnuts (7,825 ha) were grown in the Geita districts .Vegetable production is less important in the district, it has a moderate planted area with tomatoes, cabbage and chillies (217 ha, 72ha and 22 ha respectively) compared to other districts in the region and accounts for 13 percent of the tomato production, 22 percent of the cabbage production and 21 percent of the chilly production in the region. Traditional cash crops (e.g. tobacco and cotton) are grown in very high quantities. Geita districts had the largest area under small holders permanent crops (10,383 ha) and second largest area per permanent crop growing household (0.48 ha). As with other districts in the region, most land clearing and preparation is done by hand, however and very slightly more land is done by oxen compared to some other districts. The use of inputs in the region is very small, however districts differences exist. Geita has the largest planted area with fertilizer use in Mwanza region, however most of this is farm yard manure, compared to other districts in the region, Geita district has a low level of insecticide use and the use of herbicides was moderate to high compared to other districts. Also it has the largest area with irrigation compared to other districts with 2,648 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity, flood and bucket are the most common means of irrigation water application and very small amount of sprinkler irrigation is used. The most method of crop storage is in locally made traditional cribs, however the proportion of households not storing crops in the districts is among the lower than other districts in the region. The districts has the largest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The highest percent of households processing crops in Mwanza region is found in Geita districts and is almost all done by neighboring machine. The districts also have a higher percent of households selling processed crops to local markets/trade stores than other districts and no sales at secondary market. Although very small, access to credit in the districts is to men only and the main sources are religious organization/NGO projects and family friends and relatives... Comparatively larger number of households receive extension services in Geita and all of this is from the government, the quality of extension services was rated between very good and average by the majority of the households. Tree farming is less important in Geita (with 1,543 planted trees) and is mostly Gravel’s with some senna spp, acacia spp. The lowest proportion of households with erosion control is found in Geita and no water harvesting structures, the little practiced is erosion control bunds and it also has the moderate number of vertiver grass. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat production is highest compared to other districts and it has moderate population of sheep in the region. There are no pigs in the district duty it has the highest number of chickens in the region. There are on improved layers. Small number of ducks and donkeys are also found in the districts, the highest number of households reporting tsetse and tick problems was in Geita REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 districts and it had the largest number of households de-worming livestock. The use of draft animals in the districts is moderate and no fish farming was practiced. It has amongst the worst access to secondary schools, primary schools, and health clinics and primary and secondary markets compared to other districts in the region. However, it has one of the worst accesses to district capital, regional capital and tarmac road. Geita district has the highest percent of households with no toilet facilities and it has the highest percent of households owning bicycles, wheelbarrow, and radio and landline phone. It has lower number of households using main electricity, the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a moderate percent of households with grass roofs with 39 percent of households having iron sheets. The most common source of drinking water is from unprotected springs. It has eighty two percent of households having two meals per day compared to other districts and fourteen percent with 3 meals per day, the districts had the third highest percent of households that did not eat meat and the second highest percent of households that did not eat fish during the week prior to enumeration, however most households never had problems with food satisfaction. 4.2.6 Missungwi Missungwi district has a moderate number of households in the region and most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Missungwi district is Annual crop farming followed permanent crop farming and tree/forest resources. The district has a high percent of households with no off-farm income activities however it has the fourth highest percent of households with one member with off farm income compared to other districts in the region. Missungwi has the second highest percent of female headed households (22%) and it has one of the moderate average ages of the households head. With an average household’s size of 6 members per households, this is equivalent to average size for the region. The literacy rate among smallholder households in Missungwi is second lowest percent in the region and associated with this is a high number of households members who have never attended school. It has the largest utilized land area per household (2.2 ha). The total planted area is the fifth largest in the region and has the largest planted area in the short rainy season. However the planted area per household in the long rainy season (0.7 ha) is the second highest in the region. The district is important for maize production in the region with a planted area of 26,675 ha and the planted area per household is the second largest in the region. Paddy production is high for the region with a planted area of 81,805 hectares and the district has large planted area per paddy growing household. Production of sorghum is high. The district also has the largest planted area of cow peas (1,320 ha) and green gram (599 ha), however very little beans and field peas are produced. Cassava production is relatively low accounting for 7.2 percent of the total cassava planted area in the region. Oilseed is not important in Missungwi with a moderate planted area of groundnuts (2,325 ha) and virtually no sunflower production. Also vegetable production is not important in the district however tomatoes and onion are produced in high quantities. Missungwi is amongst the district that cultivates cotton and the planted area is moderate. REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 111 Compared to other districts in the region, Missungwi has a small planted area with permanent crops which is dominated by mango (3,704 ha), banana (688 ha) and orange (116 ha). Other permanent crops are either not grown or are grown in small quantities. Most land clearing is done by hand slashing; it has also the moderate area of bush clearance in the region. Most land preparation is done by hand, however it has the highest planted area cultivated by oxen and a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Missungwi has a high planted area with improved seed in Mwanza region. The use of fertilizer is moderate and is mostly farm yard manure with small inorganic fertilizer use. Compared to other districts, Missungwi has a high percentage of the planted area in the district with fungicide application and a moderate amount of herbicide was used. It has the fourth largest area with irrigation with a planted area of 631 ha under irrigation. The most common source of water for irrigation is from wells using hand buckets. Buckets/watering cans are the only means of irrigation water application in the district. A comparatively small number of households receive extension services in Missungwi and mostly from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Missungwi (with only 141 planted trees) and is mostly Azadritachta spp and Leucena spp. A small proportion of households with erosion control and water harvesting structures is found in the district and is mostly erosion control bunds. The district has the large number of cattle in the region and they are almost all indigenous. Goat and Sheep population is also large in the region, the district has a comparatively high number of pigs in the region and it has a moderate number of chickens, all of which are indigenous. A moderate number of ducks, donkeys and rabbits are also found in the district. It has highest proportion of households reporting Tsetse and tick problems in the region and it had high number of households de-worming livestock compared to other districts. Number of household using draft animals is high but fish farming is not practiced. It is amongst the districts with the best access to primary schools, feeder roads, health clinics and primary markets, tarmac roads; however it has one of the worst accesses to regional capital, secondary and tertiary markets. Missungwi district has a low percent of households with no toilet facilities (5.5%) compared to other districts, it has moderate percent of households with bicycle, wheelbarrow and iron, and it among the district with a low percent of households owning mobile phones and land line phones. The most common sources of drinking water are from unprotected and protected wells. It has fifty one percent of households having two meals per day compared to other districts and forty six percent with three meals per day. The district has lowest percent of households that did not eat meat however it has second highest of households that did not eat fish during the week prior to enumeration; however most households never had problems with food satisfaction. 4.2.7 Ilemela. Ilemela district has the smallest number of households in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households. The most important livelihood activity for smallholder households in Ilemela district is annual crop farming, followed by Permanent crop farming, off-farm income and tree/forest resources. However the district has high percent of households with no off farm income activities and a lowest percent of households with more than one member with off farm income compared to other districts in the region. Ilemela has the highest percent of female headed households (22%) in the region and it has the third average age of the household head. With an average household size of 5 members per household, it is the lowest average REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 112 size for the region. Ilemela has a moderate literacy rate among smallholder households in Mwanza region and this is reflected by the relatively high level of never attended school in the region. It has largest utilized land area per household (2.3 ha) in the region. The total area is smaller compared than other districts. However it has the second lowest area per household 0.7 ha during the long rainy season and 0.5 ha in the short rainy season. The district is not important for maize production in the region with a planted area of over 3,737 ha and the planted area per maize growing household is the second lowest in the region. The district has the smallest planted area of paddy (1,534 ha) while sorghum, finger millet are produced in very small quantities. Cassava production is small accounting for only 5 percent of cassava planted area in the region. Other pulses produced in the district are of minor importance. Oilseed crops are not important in Ilemela. Vegetable production is not important in the district; however tomatoes, cabbage, onions and other vegetables are grown in small quantities. Cotton is the only traditional cash crop grown in the district in small quantities. Compared to other districts, Ilemela has a moderate planted area with permanent crops which is dominated by Mango (4,537 ha) and Sugarcane (1,431 ha). Small quantities of banana, guava orange and lime/lemon grown and other permanent crops are either not grown or are grown in the very small quantities. Most land clearing is done by hand slashing; it has a high planted area with ‘’ no land clearing ‘’ indicating the presence of a large area of bare land before cultivation. Most land preparation is done by hand, however it has a very small planted area cultivated by oxen. A large amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Ilemela has a one of the smallest percentage of its planted area with improved seed and fertilizers (compost and farm yard manure, however most of this is farm yard manure). The district has a relatively small level of insecticide and fungicides use, however the use of herbicides, though small, was the second lowest in the region. It has the second biggest area of irrigation with 686 ha of irrigated land. The most common source of water for irrigation is from wells using hand buckets, Buckets/watering cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in sacks/open drums, locally made traditional crib. The proportion of households not storing crops in the districts is the lowest in the region. The district has a small number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. It is the third highest percent of households processing crops in Mwanza region and is mostly done using neighbours machines. The district has a small percent of households selling processed crops mostly to neighbours and local markets/trade stores. There is small access to credit in the district. A comparatively highest percent of households receive extension services in the Ilemela district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Ilemela (with 9,021 planted trees) and is mostly Eucalylyptus spp and Gravellis. A relatively small proportion of households with erosion control and water harvesting structure are found in Ilemela district and is mostly tree belts and erosion control bunds; however it also has a number of water harvesting bunds, drainage ditches and vertiver grass The district has a moderate to low number of cattle in the region and they are all indigenous. Goat production is also moderate to low compared to most other districts. Also it has a relatively small population of sheep compared to other districts in the region. It has no pigs and a moderate to low number of chickens with some improved chickens. Small numbers of ducks are found in the district. The large number of households reporting tsetse and tick problems in Ilemela REGIONAL PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 113 district and it has one of the moderate numbers of households de-worming livestock. The use of draft animals in the district is very small and no fish farming is practiced in the district. It is the only district with the best access to primary schools, feeder roads, health clinics, tarmac roads, all whether roads and primary markets. Ilemela district has the second lowest percent of households with no toilet facilities (6.6%) and it has one of the highest percent of households owning radio, mobile phones and televisions/video. The most common source of energy for lighting is the hurricane lamp and most of the households use charcoal for cooking. The district has a moderate percent of households with grass roofs and with 49 percent of households having iron sheet roofing. The most common source of drinking water is from protected wells and it has the second highest percent of households having two or one meal per day. Also it is the third lowest percent with 3 meals per day. The district had the fourth highest percent of the households that did not eat meat during the week prior to enumeration; however it has the lowest percent of households that did not eat fish during the respective period. Most households never had problems with food satisfaction. APPENDIX II 114 4. APPENDICES Appendix I Tabulation List...............................................................................................................................115 Appendix II Tables ............................................................................................................................................ 130 Appendix III Questionnaires.................................................................................................................................. 281 APPENDIX II 115 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD…………………………………...………………………………...130 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 131 2.2 Number of Agriculture Households by Type of Holding and District during 2002/03 Agricultural Year..131 NUMBER OF AGRICULTURE HOUSEHOLDS .................................................................................................132 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year......................................................................................133 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District....................................................................................................................................133 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES............................................................................134 3.1a First Most Importance....................................................................................................................................135 3.1b Second Most Importance................................................................................................................................135 3.1c Third Most Importance ..................................................................................................................................135 3.1d Fourth Most Importance.................................................................................................................................135 3.1e Fifth Most Importance....................................................................................................................................136 3.1f Sixth Most Importance...................................................................................................................................136 3.1g Seventh Most Importance ..............................................................................................................................136 HOUSEHOLDS DEMOGRAPHS............................................................................................................................138 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) .............................................................................................................................139 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) .......................................................................................................................139 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year.......140 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year ......................................140 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year ............................................................................................................................140 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year.140 cont… Number of Agricultural Household Members By Main Activity and District.................................141 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ........................................................................................................142 APPENDIX II 116 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................ 143 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................143 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year ........................................................................................................................................................................144 3.11 Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year.......................................................144 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District 2002/03 Agricultural Year`...............................................................................................................144 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District...........................................144 3.14 Time Series of Male and Female Headed Households..................................................................................145 3.15 Literacy Rate of Heads of Households by Sex and District..........................................................................145 LAND ACCESS/OWNERSHIP................................................................................................................................146 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year .......................................................................................................................147 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year ..........147 LAND USE...................................................................................................................................................................148 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year149 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year............................149 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.......................................................................................150 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ................................................................150 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year................................................150 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION LONG & SHORT SEASONS........................152 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District...........................153 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District.......................................153 7.1 & 7.2c Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long & Short Season. ..........................................................154 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Long and Short rains, Mwanza Region...........................................................................155 APPENDIX II 117 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Long & Short Season, Mwanza ............................................................................................156 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Long & Short Season, Mwanza............................................................156 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Long Season, 2002/03 Agriculture Year ..............................................................................157 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long & Short Season ..........................................................158 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long & Short Season. .............................................................................158 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Long & Short Season. .........................................................159 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Long & Short Season. ..........................................................159 ANNUAL CROP & VEGETABLES PRODUCTION Short SEASON ...............................................................160 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - Short SEASON, Mwanza Region. .........................................................................................161 7.1b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Short SEASON, Mwanza Region............................................161 7.1c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Short Season, 2002/03 Agriculture Year, Mwanza Region...............................................................162 7.1d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short Season.............................................................................163 7.1e Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Short Season.............................................................................163 7.1f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season. .............................................................................164 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Short SEASON .................................................................................164 ANNUAL CROP & VEGETABLES PRODUCTION LONG SEASON.............................................................166 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District - Long SEASON, Mwanza Region...................................................................................................167 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Long SEASON, Mwanza Region............................................167 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Long Season, 2002/03 Agriculture Year, Mwanza Region..................................................167 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long Season.............................................................................168 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long Season............................................................................168 APPENDIX II 118 7.2f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Long SEASON................................................................................ 169 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Long SEASON ......................................................................................... 169 7.2h Planted Area and Number of Crop Growing Households During Long Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year ........................................................................ 170 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year ............................................................................................. 171 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year .................................................................. 171 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year ............................................................................................. 172 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................... 172 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year........................................................ 173 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................... 173 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................... 174 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 175 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 175 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 176 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 176 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ................................................................ 177 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 177 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................... 178 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................... 178 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 179 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 179 APPENDIX II 119 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 180 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year................................................................................... 180 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by Season and District; 2002/03 Agricultural Year................................................................................................... 181 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by Season and District; 2002/03 Agricultural Year................................................................................................... 181 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Chillies Harevsted (tons)by Season and District; 2002/03 Agricultural Year................................................................................................... 182 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Amaraths Harevsted (tons) by Season and District; 2002/03 Agricultural Year................................................................................................... 182 PERMANENT CROPS..................................................................................................................................................... 184 7.3.1 Production of Permanent Crops by Crop Type and District - Mwanza............................................................... 185 7.3.2 Area Planted by Crop Type - Mwanza Region..................................................................................................... 186 7.3.3 Area Planted with Oranges by District ................................................................................................................. 186 7.3.4 Area planted with Banana by District................................................................................................................... 186 AGROPROCESSING ....................................................................................................................................................... 188 8.1.1a Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year .................................................................................................................................... 189 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year .................................................................................................................................... 189 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Mwanza Region................................................................... 189 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Mwanza Region ........................................... 190 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and ......................................................................... 190 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Mwanza Region......................................................................................................... 190 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Mwanza Region......................................................................................................... 191 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Mwanza Region......................................................................................................... 191 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Mwanza Region................................................................................................... ….191 MARKETING.............................................................................................................................................................192 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce APPENDIX II 120 by District During 2002/03; Mwanza Region ...............................................................................................193 10.2 Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Mwanza Region................................................................193 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Mwanza Region...................................................................193 IRRIGATION/EROSION CONTROL....................................................................................................................194 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District............................................................................................................195 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year....................195 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year.........................................................................................195 11.4 Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year.................................................................................................................195 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year .................................................................................196 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land by District........196 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year ...................................................................................................................197 ACCESS TO FARM INPUTS AND IMPLEMENTS ............................................................................................198 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year.........................................................................................................199 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year..................................................................................................................199 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year..................................................................................................................199 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year..................................................................................................................200 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year ..200 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year..................................................................................................................200 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year ........................................................................................................201 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ...........................................................................................................................201 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................................................202 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year ............................................................................................................................202 APPENDIX II 121 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year....202 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year..203 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year..........................................................................................................203 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year..........................................................................................................203 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.17 Number of Agricultural Households and Distance to Source of Insecticide/ Fungicides by District, 2002/03 Agricultural Year .......................................................................................204 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year..........................................................................................205 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ............................................................................................205 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................205 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/ Fungicides by District, 2002/03 Agricultural Year .......................................................................................206 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year.........................................................................................................206 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ...............................................................................................206 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year .............................................................................................................................207 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year .............................................................................................................................207 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ...............................................................................................................................207 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................................................................208 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year .............................................................................................................................208 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ............................................................................................................................208 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year..........................................................................................................208 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year.........................................................................................................209 APPENDIX II 122 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year..........................................................................................................209 12.1.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year .......................................................................................209 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year......................................................................................................... 209 12.1.35 Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year..........................................................................................................210 AGRICULTURE CREDIT........................................................................................................................................212 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year........................................................................................213 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year............................................................................................................... 213 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year..........................................................................................214 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year............................................................................................................214 TREE FARMING AND AGROFORESTRY..........................................................................................................216 14.1 Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mwanza Region.................................................................................................217 cont… Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mwanza Region.................................................................................................217 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Mwanza Region………...218 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Mwanza Region..............................................................................................218 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Mwanza Region................................................................................................................219 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Mwanza Region...................................................................................................219 CROP EXTENSION...................................................................................................................................................220 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Mwanza Region..............................................................................221 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Mwanza Region..............................................................................221 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region..........................................................221 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region...222 APPENDIX II 123 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region...222 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ........222 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region..223 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................223 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region........................223 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................224 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................224 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................224 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................225 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................225 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................225 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ..........................................226 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region ....................226 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Mwanza Region..........................226 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Mwanza Region..........................227 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Mwanza Region..........................227 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Mwanza Region..........................227 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Mwanza Region..........................228 ANIMAL CONTRIBUTION TO CROP PRODUCTION.....................................................................................230 17.1 Number of agriculture households using draft animal to cultivate land by District during APPENDIX II 124 2002/03 agriculture year, Mwanza Region...................................................................................................231 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mwanza Region...................................................................................................231 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Mwanza ................................................................................................................231 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Mwanza Region....................................................................................................232 CATTLE PRODUCTION..........................................................................................................................................234 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Mwanza Region ..235 18.2 Number of Cattle By Type and District as of 1st October, 2003..................................................................235 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003..........................................................................................235 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003 ....................................................236 18.5 Number of Indigenous Cattle By Category and District as on 1st October, 2003........................................236 18.7 Number of Improved Dairy Cattle By Category and District as on 1st October, 2003................................237 18.8 Number of Cattle By Category and District as on 1st October, 2003...........................................................237 GOATS PRODUCTION............................................................................................................................................238 19.1 Number of Goats by Type and District as on 1st October, 2003..................................................................239 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003.................................................239 19.3 Number of Goats by Category and Type of Goat as of 1st October, 2003 and District...............................240 19.4 Number of Indigenous Goat by Category and District as on 1st October, 2003..........................................240 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003 .............................240 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ......................................241 19.7 Number of Goats by Category and District on 1st October, 2003...............................................................241 SHEEP PRODUCTION.............................................................................................................................................242 20.1 Total Number of Sheep By Breed and on 1st October 2003.........................................................................243 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003...............................243 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 ..................................................243 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003.........................................243 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Mwanza Region............244 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003................................244 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003................................244 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003...................................................244 APPENDIX II 125 PIGS PRODUCTION.................................................................................................................................................246 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 ...........................................................247 21.2 Number of Households and Pigs by District on 1st October 2003 ...............................................................247 21.3 Number of Pigs by Type and District on 1st October, 2003.........................................................................247 LIVESTOCK PESTS AND PARASITE CONTROL ............................................................................................248 22.1 Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year .............................................................................................................................249 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year ..................................................................249 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. ........................................................................249 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year..........................................................................................................249 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District............................................................250 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year......................................................................................250 OTHER LIVESTOCK ...............................................................................................................................................252 23a Total Number of Other Livestock by Type on 1st October 2003 .................................................................253 23b Number of Chicken by Category of Chicken and District on 1st October 2003..........................................253 23c Head Number of Other Livestock by Type of Livestock and District..........................................................253 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003..........................253 23e LIVESTOCK/POULTRY POPULATION TREND.....................................................................................253 FISH FARMING.........................................................................................................................................................254 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year..255 28.2 Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year .............................................................................................................................255 28.3 Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year…………………………………………………………..………....255 28.4 Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year……………………………………………………………………...255 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....................................255 LIVESTOCK EXTENSION......................................................................................................................................256 29.1a Number of Agricultural Households Receiving Extension by District During the APPENDIX II 126 2002/03 Agricultural Year .............................................................................................................................257 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year........................................................................................257 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year ............................................................258 29.3 Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year.....................................................................................258 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year .......................................................................258 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year ........................................................................................................258 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year.........................................................................259 29.7 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year .............................................................. 259 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ..........................260 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year..........................260 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year ........................................................................261 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year ............................................................................261 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .............................................................................................................................262 ACCESS TO INFRASRUCTURE AND OTHER SERVICES.............................................................................264 30.1a Mean Distances from Household Dwellings to Infrastructures and Services by Districts...........................265 30.1b Number of Households By Distance to Secondary School by District for 2002/03 agriculture year..........265 33.1c Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year..........266 33.1d Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year ...................266 33.1e Number of Households By Distance to Hospital by District for 2002/03 agriculture year .........................266 33.1f Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year.................267 33.1g Number of Households by distance to Primary School for 2002/03 agriculture year..................................267 33.1h Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year ...........268 33.1i Number of Households by Distance to District Capital by District for 2002/03 agriculture year..............268 33.1j Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year.................268 33.1k Number of Households by Distance to Primary Market by District for 2002/03 agricultural year............269 APPENDIX II 127 33.1l Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year............269 33.1m Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year........269 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year...............................................................................................................270 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year ...................................................................................................... 270 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year .......................................................................................................270 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ........................................................................................................271 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year.............................................................................................271 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year ............................................................................................271 HOUSEHOLD FACILITIES ....................................................................................................................................272 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year ..............................................................................................................................273 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year..........................................................................................273 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ....................................................................................................274 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year..................................................................................................................274 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year...................................................................................................275 34.6 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year.................................................................................................................. 275 34.7 Number of Agricultural Households by Main Source of Drinking Water by Season (LONG and Short) and District during 2002/03 Agricultural Year.............................................................276 34.9 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year..................................................277 34.10 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year.................................................277 34.11 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District..............................................................................................................278 34.12 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ...........................................................278 34.13 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District..........................................................................................................279 APPENDIX II 128 34.14 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District ...........................................................................................................279 34.15 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .............................................................................................................................280 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year.280 APPENDIX II 129 APPENDIX II: CROP TABLES Type of Agriculture Household.............................................................................................................................................. 130 Number of Agriculture Households ........................................................................................................................................ 132 Rank of Importance of Livelihood Activities ......................................................................................................................... 134 Households Demography......................................................................................................................................................... 138 Land Access/Ownership .......................................................................................................................................................... 146 Land Use ............................................................................................................................................................. 148 Total Annual Crop and Vegetable Production Long and short Seasons ............................................................................... 152 Annual Crop and Vegetable Production and Short Seasons................................................................................................... 160 Annual Crop and Vegetable Production Long Seasons.......................................................................................................... 166 Permanent Crop Production..................................................................................................................................................... 184 Agro-processing ............................................................................................................................................................. 188 Marketing ............................................................................................................................................................. 192 Irrigation/Erosion Control ....................................................................................................................................................... 194 Access to Farm Inputs ............................................................................................................................................................ 198 Agriculture Credit ............................................................................................................................................................. 212 Tree Farming and Agro-forestry.............................................................................................................................................. 216 Crop Extension ............................................................................................................................................................. 220 Animal Contribution to Crop Production................................................................................................................................ 230 Cattle Production ............................................................................................................................................................. 234 Goat Production ............................................................................................................................................................. 238 Sheep Production ............................................................................................................................................................. 242 Pig Production ............................................................................................................................................................. 246 Livestock Pests and Parasite Control ...................................................................................................................................... 248 Other Livestock ............................................................................................................................................................. 252 Fishing Farming ............................................................................................................................................................. 254 Livestock Extension ............................................................................................................................................................. 256 Access to Infrastructure and other services............................................................................................................................. 264 Household Facilities ............................................................................................................................................................. 272 Appendix II 130 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 131 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Ukerewe 32,909 9.7 1,701 0.5 34,610 9.4 6,119 7.8 40,729 Magu 56,360 16.6 6,167 1.8 62,527 17.0 7,538 9.7 70,065 Kwimba 45,813 13.5 1,338 0.4 47,151 12.8 2,740 3.5 49,891 Sengerema 64,661 19.0 5,490 1.6 70,151 19.0 6,481 8.3 76,632 Geita 93,286 27.4 8,893 2.6 102,179 27.7 13,461 17.3 115,640 Missungwi 34,132 10.0 2,152 0.6 36,284 9.9 3,672 4.7 39,956 Ilemela 12,922 3.8 2,462 0.7 15,384 4.2 37,965 48.7 53,349 Total 340,085 100.0 28,202 8.3 368,286 100.0 77,976 100.0 446,262 Number of households % Number of households % Number of households % Number of households % Ukerewe 14,420 44 0.0 0.0 18,489 56 32,909 10 32,909 32,909 18,489 Magu 34,935 62 512 0.9 20,913 37 56,360 17 56,360 55,848 21,426 Kwimba 26,050 57 0 0 19,763 43 45,813 13 45,813 45,813 19,763 Sengerema 37,527 58 128 0.2 27,007 42 64,661 19 64,661 64,533 27,134 Geita 58,220 62 421 0.5 34,646 37 93,286 27 93,286 92,866 35,066 Missungwi 18,252 53 0 0 15,880 47 34,132 10 34,132 34,132 15,880 Ilemela 8,376 65 95 0.2 4,451 34 12,922 4 12,922 12,827 4,547 Total 197,780 58 1,156 0.3 141,149 42 340,085 100 340,085 338,929 142,305 Total Number of Agriculture Households District Type of Agriculture Household Total Number of Households Growing Crops 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year District Agriculture, Non Agriculture and Urban Households Total Number of Households Rearing Livestock Crops Only Livestock Only Crops & Livestock Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 132 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 133 Number % Average Household Size Number % Average Household Size Number % Ukerewe 28,751 87 6 4,157 12.6 5 32,909 100 6 Magu 46,417 82 6 9,944 17.6 5 56,360 100 6 Kwimba 36,394 79 6 9,419 20.6 5 45,813 100 6 Sengerema 54,681 85 7 9,980 15.4 5 64,661 100 7 Geita 82,793 89 7 10,494 11.2 5 93,286 100 6 Missungwi 26,748 78 6 7,384 21.6 5 34,132 100 6 Ilemela 10,116 78 5 2,806 21.7 4 12,922 100 5 Total 285,901 84 7 54,184 16 5 340,085 100 6 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittance s Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 2 1 4 3 7 5 6 Magu 1 4 5 3 6 7 2 Kwimba 1 5 4 2 6 7 3 Sengerema 1 2 5 3 7 6 4 Geita 1 4 5 3 6 7 2 Missungwi 1 2 5 4 6 7 3 Ilemela 1 2 5 3 7 6 4 Total 1 3 5 2 7 6 4 3.0 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size 3.1 HOUSEHOLDS DEMOGRAPHS: The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District District livelihood activity District Male Female Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 134 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 135 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 3,944 10,463 499 7,251 1,364 9,077 308 Magu 28,902 4,549 3,030 13,442 3,344 2,352 492 Kwimba 20,935 1,035 2,440 18,759 2,359 105 201 Sengerema 21,067 5,066 4,020 19,271 3,718 9,523 1,244 Geita 47,780 5,114 3,303 30,690 1,715 1,768 2,885 Missungwi 22,497 3,792 1,640 4,471 334 874 428 Ilemela 3,507 2,445 305 4,621 530 1,063 338 Total 148,634 32,464 15,236 98,505 13,364 24,762 5,895 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 14,101 14,795 2,117 573 420 821 248 Magu 19,354 9,169 9,466 10,521 2,801 1,152 3,880 Kwimba 20,568 5,161 9,021 8,738 694 - 1,224 Sengerema 31,451 25,775 3,198 2,626 277 775 755 Geita 38,452 22,707 12,849 11,382 768 - 6,870 Missungwi 9,288 10,512 6,153 5,572 148 571 2,078 Ilemela 5,274 5,424 742 1,112 59 165 217 Total 138,488 93,542 43,546 40,523 5,168 3,485 15,272 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 10,597 5,512 8,709 3,678 254 1,231 1,524 Magu 5,316 8,715 6,921 5,773 3,626 138 22,567 Kwimba 2,831 6,437 6,365 8,282 1,447 103 17,768 Sengerema 10,224 19,613 15,382 5,759 735 738 9,390 Geita 5,320 22,750 12,630 8,407 932 322 35,499 Missungwi 2,257 6,006 6,062 5,304 944 394 10,075 Ilemela 3,325 2,933 1,816 1,393 198 155 1,993 Total 39,869 71,965 57,887 38,597 8,137 3,080 98,817 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 2,692 1,503 7,546 6,497 80 643 3,880 Magu 1,267 2,969 3,321 4,000 2,495 277 18,204 Kwimba 891 2,757 2,040 2,753 1,445 103 18,387 Sengerema 803 4,839 7,878 6,514 447 1,548 23,708 Geita 384 10,453 8,491 2,721 527 332 31,637 Missungwi 90 1,452 3,057 4,230 920 168 10,353 Ilemela 553 652 2,538 1,142 421 81 2,752 Total 6,681 24,624 34,872 27,856 6,335 3,152 108,920 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 136 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 82 170 2,651 2,990 246 243 6,478 Magu 231 739 1,568 2,229 1,525 248 6,415 Kwimba - 1,727 828 412 1,044 99 4,506 Sengerema - 1,318 3,165 3,326 1,033 152 11,558 Geita - 1,810 4,071 286 327 152 6,506 Missungwi - 170 415 1,077 497 436 5,185 Ilemela 54 228 544 292 123 54 1,592 Total 368 6,162 13,244 10,612 4,794 1,382 42,239 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe - - 567 322 402 83 1,762 Magu - - - 261 509 - 1,175 Kwimba - - 105 - 105 - 403 Sengerema - 153 373 678 689 - 954 Geita - - 167 166 - - - Missungwi - - - - 402 - 592 Ilemela - - 152 188 - - 159 Total - 153 1,363 1,614 2,106 83 5,046 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Ukerewe 85 - - 80 - 83 164 Magu - - - 129 - - - Kwimba 385 - - - - - - Sengerema 109 148 126 281 - - - Geita 102 - 166 221 - - 136 Missungwi - - 148 - 157 - - Ilemela - - - - - 26 - Total 681 148 440 710 157 109 299 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census -2003 Mwanza 137 Appendix II 138 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 139 Number % Number % Number % Less than 4 141,729 50 143,356 50 285,086 100 05 - 09 187,272 52 170,228 48 357,501 100 10 - 14 165,652 51 156,522 49 322,174 100 15 - 19 125,138 52 114,394 48 239,531 100 20 - 24 87,530 48 93,620 52 181,150 100 25 - 29 77,199 48 85,253 52 162,452 100 30 - 34 58,149 49 61,513 51 119,661 100 35 - 39 49,009 51 48,027 49 97,035 100 40 - 44 41,957 48 44,730 52 86,687 100 45 - 49 29,990 48 32,881 52 62,872 100 50 - 54 26,714 47 30,130 53 56,845 100 55 - 59 24,296 59 16,649 41 40,945 100 60 - 64 18,900 52 17,631 48 36,531 100 65 - 69 16,595 56 13,281 44 29,876 100 70 - 74 14,442 57 11,077 43 25,520 100 75 - 79 8,690 61 5,634 39 14,324 100 80 - 84 4,044 53 3,562 47 7,606 100 Above 85 5,440 63 3,147 37 8,586 100 Total 1,082,746 51 1,051,636 49 2,134,382 100 Number % Number % Number % Less than 4 141,729 13 143,356 14 285,086 13 05 - 09 187,272 17 170,228 16 357,501 17 10 - 14 165,652 15 156,522 15 322,174 15 15 - 19 125,138 12 114,394 11 239,531 11 20 - 24 87,530 8 93,620 9 181,150 8 25 - 29 77,199 7 85,253 8 162,452 8 30 - 34 58,149 5 61,513 6 119,661 6 35 - 39 49,009 5 48,027 5 97,035 5 40 - 44 41,957 4 44,730 4 86,687 4 45 - 49 29,990 3 32,881 3 62,872 3 50 - 54 26,714 2 30,130 3 56,845 3 55 - 59 24,296 2 16,649 2 40,945 2 60 - 64 18,900 2 17,631 2 36,531 2 65 - 69 16,595 2 13,281 1 29,876 1 70 - 74 14,442 1 11,077 1 25,520 1 75 - 79 8,690 1 5,634 1 14,324 1 80 - 84 4,044 0 3,562 0 7,606 0 Above 85 5,440 1 3,147 0 8,586 0 Total 1,082,746 100 1,051,636 100 2,134,382 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 140 Number % Number % Number % Ukerewe 102,453 50 103,274 50 205,727 100 Magu 177,451 52 164,953 48 342,404 100 Kwimba 135,814 50 134,930 50 270,744 100 Sengerema 224,434 51 211,979 49 436,413 100 Geita 305,318 51 298,539 49 603,856 100 Missungwi 102,498 49 105,007 51 207,505 100 Ilemela 34,779 51 32,954 49 67,732 100 Total 1,082,746 51 1,051,636 49 2,134,382 100 Number % Number % Number % Number % Number % Ukerewe 123,712 71.6 1,959 1.1 330 0.2 46,684 27.0 172,685 100 Magu 212,326 69.1 6,523 2.1 338 0.1 87,878 28.6 307,066 100 Kwimba 142,813 57.8 6,173 2.5 102 0.0 98,016 39.7 247,104 100 Sengerema 227,858 62.2 10,442 2.9 725 0.2 127,327 34.8 366,353 100 Geita 298,912 58.1 9,010 1.8 0 0.0 206,912 40.2 514,834 100 Missungwi 114,131 62.7 4,216 2.3 89 0.0 63,690 35.0 182,125 100 Ilemela 36,130 61.1 2,035 3.4 229 0.4 20,735 35.1 59,128 100 Total 1,155,882 62.5 40,358 2.2 1,813 0.1 651,243 35.2 1,849,296 100 Number % Number % Number % Number % Ukerewe 52,787 30.6 80,669 46.7 39,229 22.7 172,685 100.0 Magu 99,867 32.5 120,750 39.3 86,449 28.2 307,066 100.0 Kwimba 65,393 26.5 88,863 36.0 92,848 37.6 247,104 100.0 Sengerema 113,098 30.9 138,036 37.7 115,219 31.5 366,353 100.0 Geita 139,042 27.0 178,234 34.6 197,559 38.4 514,834 100.0 Missungwi 51,084 28.0 73,051 40.1 57,990 31.8 182,125 100.0 Ilemela 16,929 28.6 23,008 38.9 19,192 32.5 59,128 100.0 Total 538,199 29.1 702,612 38.0 608,486 32.9 1,849,296 100.0 Number % Number % Number % Number % Number % Ukerewe 78,813 45.6 3,373 2.0 84 0.0 13,703 7.9 1,136 1 Magu 156,097 50.8 4,081 1.3 199 0.1 6,339 2.1 772 0 Kwimba 136,944 55.4 5,311 2.1 0 0.0 0 0.0 988 0 Sengerema 155,555 42.5 1,904 0.5 0 0.0 12,917 3.5 3,066 1 Geita 293,452 57.0 4,854 0.9 331 0.1 467 0.1 2,475 0 Missungwi 98,006 53.8 2,517 1.4 90 0.0 1,458 0.8 1,727 1 Ilemela 29,599 50.1 323 0.5 0 0.0 1,172 2.0 631 1 Total 948,466 51.3 22,363 1.2 704 0.0 36,055 1.9 10,794 1 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 141 Number % Number % Number % Number % Number % Ukerewe 1,465 0.8 1,278 0.7 925 0.5 159 0.1 72 0.0 Magu 2,839 0.9 2,267 0.7 1,714 0.6 1,453 0.5 773 0.3 Kwimba 2,624 1.1 1,131 0.5 992 0.4 718 0.3 1,462 0.6 Sengerema 2,257 0.6 851 0.2 21,443 5.9 1,161 0.3 299 0.1 Geita 2,068 0.4 3,937 0.8 1,931 0.4 2,087 0.4 1,301 0.3 Missungwi 1,017 0.6 1,364 0.7 3,257 1.8 607 0.3 176 0.1 Ilemela 1,179 2.0 489 0.8 3,162 5.3 157 0.3 0 0.0 Total 13,450 0.7 11,317 0.6 33,424 1.8 6,342 0.3 4,084 0.2 Number % Number % Number % Number % Number % Number % Ukerewe 0 0.0 83 0.0 50,724 29.4 18,870 10.9 2,002 1 172,685 100 Magu 263 0.1 1,985 0.6 96,818 31.5 31,207 10.2 258 0 307,066 100 Kwimba 0 0.0 1,503 0.6 62,764 25.4 30,196 12.2 2,471 1 247,104 100 Sengerema 0 0.0 1,057 0.3 108,408 29.6 52,914 14.4 4,520 1 366,353 100 Geita 165 0.0 2,468 0.5 134,520 26.1 58,782 11.4 5,995 1 514,834 100 Missungwi 90 0.0 427 0.2 49,381 27.1 21,008 11.5 1,003 1 182,125 100 Ilemela 114 0.2 101 0.2 16,181 27.4 5,966 10.1 54 0 59,128 100 Total 632 0.0 7,625 0.4 518,794 28.1 218,943 11.8 16304 0.9 1,849,296 100 District Other cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Unpaid Family Helper (Non Agriculture) Total Main Activity Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled District Not Working & Available Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 142 Number % Number % Number % Number % Number % Ukerewe 80,999 47 2,782 2 52,884 31 36,020 21 172,685 100 Magu 136,964 45 9,706 3 103,466 34 56,930 19 307,066 100 Kwimba 104,228 42 15,651 6 84,408 34 42,817 17 247,104 100 Sengerema 145,062 40 9,344 3 146,381 40 65,566 18 366,353 100 Geita 226,401 44 8,288 2 199,231 39 80,914 16 514,834 100 Missungwi 92,568 51 8,813 5 49,300 27 31,444 17 182,125 100 Ilemela 24,944 42 1,784 3 22,548 38 9,852 17 59,128 100 Total 811,167 44 56,369 3 658,218 36 323,543 17 1,849,296 100 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 143 Number % Number % Number % Number % Number % Ukerewe 80 0.1 480 1 1,616 2 3,805 5 7,620 9 Magu 512 0.4 2,759 2 3,207 3 4,714 4 12,861 11 Kwimba 104 0.1 308 0 1,752 2 2,235 3 9,095 10 Sengerema 0 0.0 821 1 4,755 3 4,831 3 14,577 11 Geita 480 0.3 2,671 1 5,615 3 7,357 4 15,092 8 Missungwi 0 0.0 338 0 1,392 2 1,419 2 5,282 7 Ilemela 0 0.0 176 1 919 4 1,216 5 1,848 8 Total 1,176 0.2 7,552 1 19,257 3 25,576 4 66,375 9 Number % Number % Number % Number % Number % Ukerewe 57,859 72 951 1 82 0 0 0 0 0 Magu 84,808 70 1,086 1 0 0 0 0 393 0 Kwimba 66,033 74 1,083 1 308 0 0 0 194 0 Sengerema 92,105 67 1,674 1 454 0 126 0 454 0 Geita 126,334 71 1,802 1 709 0 0 0 331 0 Missungwi 57,260 78 1,082 1 165 0 0 0 76 0 Ilemela 15,947 69 192 1 113 0 0 0 97 0 Total 500,346 71 7,869 1 1,832 0 126 0 1,547 0 Number % Number % Number % Number % Number % Ukerewe 653 1 0 0 885 1 0 0 164 0 Magu 729 1 417 0 1,277 1 218 0 80 0 Kwimba 210 0 101 0 2,334 3 0 0 92 0 Sengerema 438 0 419 0 3,767 3 153 0 893 1 Geita 1,379 1 168 0 2,316 1 0 0 822 0 Missungwi 394 1 0 0 1,904 3 159 0 240 0 Ilemela 78 0 0 0 449 2 87 0 145 1 Total 3,881 1 1,106 0 12,933 2 618 0 2,436 0 Number % Number % Number % Number % Ukerewe 83 0 1,419 2 0 0 80,669 100 Magu 0 0 1,124 1 0 0 120,750 100 Kwimba 0 0 1,235 1 0 0 88,863 100 Sengerema 129 0 2,179 2 0 0 138,036 100 Geita 0 0 1,795 1 0 0 178,234 100 Missungwi 69 0 923 1 0 0 73,051 100 Ilemela 0 0 157 1 0 0 23,008 100 Total 281 0 8,834 1 0 0 702,612 100 cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Form One Form Two Form Three Form Four Standard Seven Standard Eight Training After Primary Education Pre Form One District Education Level Education Level Standard Four 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Under Standard One Standard One Standard Two Standard Three cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Form Six g Secondary Education District Education Level y Tertiary Education Adult Education Not applicable Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 144 Number % Average Household Size Number % Average Household Size Number % Ukerewe 28,751 87 6 4,157 12.6 5 32,909 100 6 Magu 46,417 82 6 9,944 17.6 5 56,360 100 6 Kwimba 36,394 79 6 9,419 20.6 5 45,813 100 6 Sengerema 54,681 85 7 9,980 15.4 5 64,661 100 7 Geita 82,793 89 7 10,494 11.2 5 93,286 100 6 Missungwi 26,748 78 6 7,384 21.6 5 34,132 100 6 Ilemela 10,116 78 5 2,806 21.7 4 12,922 100 5 Total 285,901 84 7 54,184 16 5 340,085 100 6 Number Percent Number Percent Number Percent Number Percent Ukerewe 16,909 75 3,739 17 1,755 8 22,403 100 Magu 25,180 64 8,374 21 5,497 14 39,051 100 Kwimba 20,045 51 13,599 35 5,588 14 39,231 100 Sengerema 32,578 77 5,540 13 4,313 10 42,431 100 Geita 39,365 68 13,014 23 5,394 9 57,773 100 Missungwi 16,457 73 4,134 18 1,827 8 22,418 100 Ilemela 7,121 75 1,967 21 467 5 9,555 100 Total 157,655 68 50,366 22 24,841 11 232,862 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Ukerewe 6,395 24,899 82 788 82 83 580 32,909 Magu 19,218 34,638 0 1,619 160 0 726 56,360 Kwimba 20,828 23,025 103 1,136 0 0 721 45,813 Sengerema 19,335 40,056 303 2,814 740 129 1,285 64,661 Geita 36,504 52,889 85 1,941 822 0 1,045 93,286 Missungwi 13,776 18,216 0 1,201 240 69 631 34,132 Ilemela 5,005 7,218 113 344 86 0 157 12,922 Total 121,060 200,941 686 9,843 2,130 281 5,144 340,085 Mean Median Mode Mean Median Mode Mean Median Mode Ukerewe 45 42 40 52 50 45 46 42 40 Magu 49 45 30 54 54 60 50 48 45 Kwimba 47 46 40 54 53 70 49 47 40 Sengerema 45 42 40 49 48 42 46 43 40 Geita 44 41 30 51 50 50 45 42 30 Missungwi 46 43 30 50 49 50 47 44 30 Ilemela 46 41 40 52 55 56 47 45 35 Total 46 43 30 52 50 50 47 44 30 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Household Size 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Median, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 145 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 175 179 192 204 205 200 Female Heads 203 230 255 268 261 264 Total 378 409 447 472 466 464 Male headed (Percentage) 82 78 75 76 78 76 Female headed (Percentage) 18 22 25 24 22 24 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Ukerewe 24,506 2,156 26,661 4,246 2,002 6,247 28,751 4,157 32,909 Magu 34,219 3,570 37,790 12,197 6,373 18,571 46,417 9,944 56,360 Kwimba 22,305 2,568 24,873 14,089 6,851 20,940 36,394 9,419 45,813 Sengerema 40,914 4,291 45,205 13,767 5,689 19,457 54,681 9,980 64,661 Geita 55,081 2,506 57,587 27,712 7,988 35,700 82,793 10,494 93,286 Missungwi 17,674 2,403 20,077 9,075 4,981 14,055 26,748 7,384 34,132 Ilemela 7,149 820 7,968 2,968 1,986 4,954 10,116 2,806 12,922 Total 201,847 18,315 220,161 84,054 35,869 119,923 285,901 54,184 340,085 3.14 Time Series of Male and Female Headed Households Literacy District Know Don't know Total 3.15 Literacy Rate of Heads of Households by Sex and District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 146 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 147 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 6,404 13 27,684 55 2,745 5 8,623 17 2,867 6 300 1 2,113 4 50,736 Magu 1,105 1 47,174 63 11,813 16 7,416 10 6,118 8 537 1 886 1 75,048 Kwimba 1,756 3 34,987 54 13,307 20 9,145 14 3,737 6 311 0 1,813 3 65,057 Sengerema 2,422 3 39,132 45 23,990 27 14,872 17 4,558 5 1,092 1 1,430 2 87,496 Geita 6,688 6 53,640 44 29,178 24 17,661 15 8,718 7 896 1 4,144 3 120,926 Missungwi 1,789 3 24,603 48 13,312 26 6,468 12 3,576 7 819 2 1,209 2 51,777 Ilemela 714 4 8,820 46 5,372 28 2,867 15 1,189 6 53 0 260 1 19,276 Total 20,878 4 236,041 50 99,716 21 67,053 14 30,762 7 4,009 1 11,857 3 470,316 Area Leased/Certifi cate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Ukerewe 2,544 23,491 1,282 3,662 996 70 641 32,686 Magu 3,579 119,209 19,174 7,021 4,642 202 1,118 154,944 Kwimba 1,975 81,670 46,195 9,013 2,555 168 1,879 143,455 Sengerema 6,684 81,689 44,685 10,440 2,952 1,660 1,187 149,297 Geita 15,604 144,341 73,648 14,971 7,357 330 4,355 260,606 Missungwi 1,503 66,192 27,322 6,186 2,751 1,069 1,248 106,270 Ilemela 771 10,248 4,404 1,418 340 11 70 17,262 Total 32,661 526,839 216,710 52,710 21,592 3,510 10,498 864,520 % 3.8 60.9 25.1 6.1 2.5 0.4 1.2 100.0 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Land Access Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Total Number of Households 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 148 LAND USE Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 149 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households with area Unusable Households of Uncultivated Usable Land Area of land Utilized by household Total Number of Households Ukerewe 11,590 3,549 11,507 4,423 25,379 247 572 831 8,819 2,661 3,256 17,990 90,823 32,909 Magu 49,355 19,226 12,269 1,356 10,867 874 790 928 3,821 2,146 2,908 14,176 118,714 56,360 Kwimba 40,796 22,805 12,833 915 1,848 4,289 415 1,742 11,411 2,142 1,950 18,916 120,061 45,813 Sengerema 42,218 25,928 20,817 3,123 39,316 2,363 1,124 1,151 4,182 2,706 5,380 28,916 177,223 64,661 Geita 60,440 38,352 17,297 4,279 39,782 3,037 2,064 535 3,030 943 2,307 12,175 184,240 93,286 Missungwi 30,212 17,039 7,857 1,635 11,206 1,141 605 225 4,232 499 782 2,015 77,446 34,132 Ilemela 8,129 4,194 2,892 790 8,172 0 490 5,645 42,153 11,584 17,446 101,350 202,847 12,922 Total 242,740 131,092 85,472 16,520 136,569 11,950 6,060 11,057 77,647 22,681 34,029 195,537 971,355 340,085 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Ukerewe 2,880 1,294 5,336 1,880 16,112 135 179 190 499 350 302 3,529 32,686 Magu 71,235 21,938 8,128 999 9,826 2,416 361 1,914 7,702 2,331 3,204 24,889 154,944 Kwimba 64,685 31,790 7,068 660 1,696 7,255 2,094 1,425 1,051 2,620 3,209 19,902 143,455 Sengerema 37,119 25,694 16,231 2,751 34,710 4,587 828 1,191 1,849 2,568 1,091 20,678 149,297 Geita 78,090 39,477 13,049 3,182 51,045 3,417 2,801 487 2,247 5,959 8,661 52,257 260,672 Missungwi 45,024 21,589 5,655 1,120 9,214 1,571 519 452 334 1,453 2,439 16,901 106,270 Ilemela 3,791 1,939 1,504 480 6,658 0 285 61 534 360 329 1,320 17,262 Total 302,825 143,721 56,971 11,071 129,262 19,382 7,068 5,720 14,216 15,640 19,235 139,476 864,585 % 0.4 0.2 0.2 0.1 0.8 0.0 0.0 0.0 0.1 0.0 0.0 0.2 2.0 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts Type of Land Use 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 150 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Ukerewe 24,516 74 8,393 26 32,909 100 Ukerewe 11,901 36 21,008 64 32,909 100 Magu 34,824 62 21,024 38 55,848 100 Magu 24,829 44 31,019 56 55,848 100 Kwimba 28,721 63 17,092 37 45,813 100 Kwimba 21,662 47 24,151 53 45,813 100 Sengerema 41,702 65 22,831 35 64,533 100 Sengerema 27,729 43 36,804 57 64,533 100 Geita 56,088 60 36,778 40 92,866 100 Geita 37,246 40 55,620 60 92,866 100 Missungwi 19,722 58 14,411 42 34,132 100 Missungwi 18,923 55 15,209 45 34,132 100 Ilemela 9,295 72 3,532 28 12,827 100 Ilemela 5,066 39 7,761 61 12,827 100 Total 214,868 63 124,060 37 338,929 100 Total 147,356 43 191,573 57 338,929 100 Number Percent Number Percent Number Percent Ukerewe 4,788 15 28,121 85 32,909 100 Magu 10,233 18 45,615 82 55,848 100 Kwimba 8,208 18 37,605 82 45,813 100 Sengerema 10,133 16 54,401 84 64,533 100 Geita 7,014 8 85,852 92 92,866 100 Missungwi 10,378 30 23,754 70 34,132 100 Ilemela 1,810 14 11,017 86 12,827 100 Total 52,563 16 286,366 84 338,929 100 5.3 LAND USE: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total 5.4 LAND USE: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.5 LAND USE: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total Tanzania Agriculture Sample Census -2003 Mwanza 151 Appendix II 152 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION LONG & SHORT SEASONS Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 153 Number of household Planted area (hectare) Number of household Planted Area (hectare) Ukerewe 38424 6557 55794 28042 34599 19.0 Magu 147701 89481 40099 31964 121444 73.7 Kwimba 127954 78941 38375 37404 116345 67.9 Sengerema 164,220 64,538 89,057 55,565 120,102 53.7 Geita 237,525 135,878 66,607 51,080 186,958 72.7 Missungwi 99,896 56,631 41,771 28,049 84,679 66.9 Ilemela 30,388 6,153 23,189 8,826 14,979 41.1 Total 846,108 438,177 354,891 240,929 679,107 64.5 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Ukerewe 24298 32,909 18,980 13,929 43,278 Magu 54345 56,360 13,409 42,952 67,754 Kwimba 45001 45,813 15,451 30,362 60,452 Sengerema 63078 64,661 27,234 37,428 90,312 Geita 91318 93,286 22,362 70,925 113,680 Missungwi 33872 34,132 14,898 19,234 48,771 Ilemela 10334 12,922 7,192 5,731 17,525 Total 322248 340,085 119,525 220,560 441,773 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area planted in Short Season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Short Season Long Season District Short Season Long Season Total Number of Crop Growing Households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 154 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 195,556 142,605 729 12,956 8,199 633 208,512 150,804 1,362 Paddy 51,928 42,906 826 35,303 38,899 1,102 87,231 81,805 1,928 Sorghum 10,556 6,698 635 1,882 1,573 836 12,438 8,271 1,470 Bulrush Millet 1,690 509 301 1,882 684 363 3,572 1,192 664 Finger Millet 2,468 1,202 487 908 1,191 1,311 3,376 2,394 1,799 CEREALS 262,197 193,921 2,978 52,931 50,546 4,245 315,128 Cassava 1,443 2,238 1,551 139,780 202,065 1,446 141,223 204,303 2,997 Sweet Potatoes 23,491 31,770 1,352 11,227 15,321 1,365 34,717 47,092 2,717 Irish Potatoes 304 319 1,048 83 78 941 387 396 1,989 ROOTS & TUBERS 25,238 34,327 3,952 151,089 217,463 3,751 176,327 Mung Beans 0 0 0 0 0 0 0 0 0 Beans 30,865 12,575 407 1,679 642 382 32,544 13,217 790 Cowpeas 4,378 1,509 345 467 149 320 4,845 1,658 665 Green Gram 8,443 2,362 280 285 71 249 8,728 2,433 529 Chich Peas 157 142 908 29,738 15,090 507 29,894 15,232 1,416 Bambaranuts 769 414 538 190 64 339 959 478 876 PULSES 44,612 17,002 2,478 32,357 16,016 1,798 76,970 Sunflower 66 28 430 0 0 0 65.503 28 430 Simsim 266 181 682 58 26 441 325 207 1,123 Groundnuts 18,367 9,208 501 566 180 317 18,934 9,388 818 Soya Beans 142 5 38 0 0 0 142 5 38 OIL SEEDS & OIL NUTS 18,841 9,423 1,651 625 205 758 19,466 Okra 6 1 247 0 0 0 6 1 247 Radish 0 0 0 10 68 6,587 10 68 6,587 Onions 206 998 4,845 110 666 6,054 316 1,664 10,899 Cabbage 199 890 4,472 127 657 5,167 326 1,547 9,638 Tomatoes 1,047 6,058 5,786 870 4,657 5,354 1,917 10,714 11,140 Spinnach 20 36 1,840 44 190 4,354 63 226 6,194 Carrot 45 66 1,456 55 51 913 101 117 2,369 Chillies 68 69 1,023 35 108 3,066 103 178 4,089 Amaranths 69 530 7,669 73 173 2,379 142 704 10,049 FRUITS & VEGETABLES 1,660 8,649 27,337 1,324 6,569 33,874 2,984 Total 352,548 1,725 1,761 238,327 258,478 393 590,875 260,203 395 *The total area planted include the sum of the planted area for both Wet and Short Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Long Season to estimat 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Mwanza Region Crop Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 155 Number of Households Planted area (ha) Number of Households Planted area (ha) CEREALS 395,037 262,197 79,180 52,931 315,128 83 Maize 288,518 195,556 18,906 12,956 208,512 94 Paddy 77,984 51,928 52,338 35,303 87,231 60 Sorghum 23,161 10,556 4,503 1,882 12,438 85 Bulrush Millet 1,238 1,690 2,017 1,882 3,572 47 Finger Millet 4,137 2,468 1,416 908 3,376 73 ROOTS & TUBERS 103,568 25,238 232,122 151,089 176,327 14 Cassava 3,870 1,443 188,853 139,780 141,223 1 Sweet Potatoes 99,073 23,491 42,936 11,227 34,717 68 Irish Potatoes 625 304 333 83 387 79 PULSES 186,853 44,612 31,445 32,357 76,970 58 Mung Beans 0 0 0 0 0 0 Beans 124,869 30,865 6,935 1,679 32,544 95 Cowpeas 26,972 4,378 2,894 467 4,845 90 Green Gram 29,184 8,443 2,894 285 8,728 97 Chich Peas 498 157 17,535 29,738 29,894 1 Bambaranuts 5,331 769 1,187 190 959 80 OIL SEEDS & OIL NUTS 59,923 18,841 1,735 625 19,466 97 Sunflower 315 66 0 0 66 100 Simsim 1,646 266 289 58 325 82 Groundnuts 57,655 18,367 1,446 566 18,934 97 Soya Beans 307 142 0 0 142 100 FRUITS & VEGETABLES 9,108 1,660 9,264 1,324 2,984 56 Okra 57 6 0 0 6 100 Radish 0 0 169 10 10 0 Onions 1,237 206 656 110 316 65 Cabbage 1,339 199 1,125 127 326 61 Tomatoes 5,016 1,047 5,400 870 1,917 55 Spinnach 153 20 522 44 63 31 Carrot 184 45 302 55 101 45 Chillies 325 68 531 35 103 66 Amaranths 798 69 559 73 142 49 Total 1,660 1,324 2,984 56 Total Area Planted Short & Long rainy Season % Area Planted in Short rain 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Long and Short rains, Mwanza Region Long rainy Season Short rainy Season. Crop Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 83 7 1,117 210 60,887 10,713 62,087 10,931 Magu 1,503 1,137 75,448 67,443 88,717 34,038 165,668 102,618 Kwimba 307 326 91,527 82,037 28,207 25,621 120,042 107,985 Sengerema 1,066 239 15,209 12,822 185,702 68,430 201,977 81,492 Geita 486 573 38,321 37,031 225,826 115,146 264,633 152,750 Missungwi 1,881 1,056 42,845 36,057 78,460 37,422 123,187 74,535 Ilemela 58 23 693 267 42,677 8,939 43,429 9,229 Total 3,362 235,868 300,310 539,539 % 0.6 43.7 55.7 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Ukerewe 24,258 16,288 1,549 1,065 242 78 30,632 17,168 56,681 34,599 Magu 16,822 30,187 3,288 2,450 624 853 64,869 87,954 85,603 121,444 Kwimba 10,559 24,408 1,192 2,129 207 115 59,423 89,692 71,380 116,345 Sengerema 27,399 37,854 148 210 1,738 3,546 91,357 78,492 120,642 120,102 Geita 17,938 40,664 1,420 1,193 1,264 1,714 121,933 143,386 142,555 186,958 Missungwi 9,388 14,806 317 253 1,109 1,527 48,262 68,094 59,076 84,679 Ilemela 6,176 5,124 896 465 1,159 794 12,982 8,597 21,212 14,979 Total 112,540 169,331 8,809 7,764 6,341 8,627 429,458 493,385 557,149 679,107 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Long & Short Season, Mwanza District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Long & Short Season, Mwanza District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 157 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Ukerewe 31,277 27,551 1,106 491 32,383 28,042 98 Magu 21,722 20,701 9,536 11,263 31,257 31,964 65 Kwimba 14,553 13,383 11,826 24,020 26,379 37,404 36 Sengerema 48,580 43,305 8,984 12,260 57,563 55,565 78 Geita 39,860 40,759 11,377 10,321 51,237 51,080 80 Missungwi 18,487 18,284 6,717 9,765 25,204 28,049 65 Ilemela 10,041 8,220 836 606 10,878 8,826 93 Total 184,520 172,204 50,381 68,725 234,901 240,929 71 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Long Season & short, 2002/03 Agriculture Year % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation Households not Using Irrigation Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 733 98 93,642 34,491 94,375 34,590 0.3 Magu 9,319 7,775 178,298 63,910 187,617 71,685 10.8 Kwimba 3,006 5,287 163,623 111,235 166,629 116,522 4.5 Sengerema 4,948 1,548 249,133 118,562 254,081 120,110 1.3 Geita 7,610 2,755 297,373 183,173 304,983 185,928 1.5 Missungwi 3,576 867 139,686 30,726 143,262 31,593 2.7 Ilemela 3,532 426 51,088 14,553 54,620 14,979 2.8 Total 32,725 18,756 1,172,843 556,650 1,205,568 575,406 3.3 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 333 84 93,885 34,516 94,218 34,599 1.0 Magu 9,006 5,457 178,794 115,987 187,800 121,444 7.4 Kwimba 2,142 4,214 164,187 112,131 166,329 116,345 1.8 Sengerema 1,554 676 251,723 119,426 253,276 120,102 1.3 Geita 9,082 7,873 295,049 179,084 304,131 186,958 4.9 Missungwi 1,841 1,026 139,826 83,653 141,667 84,679 2.2 Ilemela 570 141 53,007 14,838 53,577 14,979 3.8 Total 24,528 19,472 1,176,471 659,634 1,200,999 679,107 3.6 % 2.0 2.9 98.0 97.1 100.0 100.0 % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long & Short Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long & Short Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 159 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 409 153 56,272 34,447 56,681 34,599 0.4 Magu 3,975 8,139 81,628 113,305 85,603 121,444 6.7 Kwimba 1,550 5,787 69,829 110,558 71,380 116,345 5.0 Sengerema 1,704 2,108 118,938 117,994 120,642 120,102 1.8 Geita 1,890 2,631 140,665 184,326 142,555 186,958 1.4 Missungwi 1,575 1,695 57,502 82,985 59,076 84,679 2.0 Ilemela 1,435 1,362 19,777 13,617 21,212 14,979 9.1 Total 12,539 21,876 544,610 657,231 557,149 679,107 3.2 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 8,198 2,615 35,080 8,315 16,514 10,930 23.9 Magu 30,450 51,630 37,305 50,987 81,437 102,618 50.3 Kwimba 14,220 35,225 46,233 72,760 86,980 107,985 32.6 Sengerema 25,644 33,089 64,668 48,402 74,046 81,492 40.6 Geita 23,149 34,154 90,531 118,596 141,745 152,750 22.4 Missungwi 13,313 18,805 35,458 55,730 69,043 74,535 25.2 Ilemela 6,661 4,089 10,864 5,141 11,802 9,229 44.3 Total 121,634 179,608 320,139 359,932 481,566 539,539 33.3 Fungicide Use Households Using Fungicide Households Not Using Fungicide Total 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Long & Short Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Long & Short Season. % of Planted Area Using Improved Seeds District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 160 ANNUAL CROP & VEGETABLES PRODUCTION Short SEASON Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 83 7 715 114 23,807 6,421 24,605 6,541 Magu 1,503 1,137 65,088 56,770 31,315 30,854 97,906 88,761 Kwimba 203 242 73,777 56,570 16,173 18,992 90,152 75,804 Sengerema 461 87 10,819 8,476 58,638 55,619 69,918 64,181 Geita 486 573 33,122 31,605 79,434 108,857 113,042 141,036 Missungwi 1,283 901 34,929 27,147 21,056 27,235 57,268 55,284 Ilemela 0 0 315 152 10,174 5,991 10,489 6,143 Total 4,019 2,947 218,765 180,834 240,596 253,970 463,379 437,751 % 0.9 0.7 47.2 41 51.9 58.0 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 10,402 2,881 237 154 75 8 13,584 3,514 24,298 6,557 Magu 12,628 24,045 1,369 940 380 752 39,968 63,744 54,345 89,481 Kwimba 8,824 19,362 1,090 2,098 104 105 34,984 57,376 45,001 78,941 Sengerema 19,884 25,047 148 210 1,007 3,012 42,040 36,269 63,078 64,538 Geita 16,675 38,205 1,253 1,166 469 688 72,921 95,818 91,318 135,878 Missungwi 7,457 13,040 166 169 450 456 25,799 42,966 33,872 56,631 Ilemela 3,613 2,378 575 206 478 318 5,668 3,251 10,334 6,153 Total 79,483 124,960 4,839 4,942 2,963 5,339 234,963 302,938 322,248 438,177 % 24.7 29 1.5 1.1 0.9 1.2 73 69 100 100 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Short SEASON, Mwanza Region District Fertilizer Use 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - Short SEASON, Mwanza Region. District Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Tractor Ploughing Soil Preparation Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 1069 227 37,355 6,331 38424 6,557 3.5 Magu 3036 1,569 144,665 87,912 147701 89,481 1.8 Kwimba 1243 1,178 126,711 77,763 127954 78,941 1.5 Sengerema 3,269 724 160,951 63,814 164,220 64,538 1.1 Geita 9862 5,201 227,663 130,677 237525 135,878 3.8 Missungwi 2527 737 97370 55894 99896 56631 1.3 Ilemela 3494 503 26894 5650 30388 6153 8.2 Total 24,500 10,137 821,609 428,040 846,108 438,177 2.3 % 2.9 2.3 97.1 97.7 100.0 100 District % of planted area under irrigation in Short season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Short Season, 2002/03 Agriculture Year, Mwanza Region Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 163 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 587 171 23,711 6,387 24,298 6,557 3 Magu 11,883 30,578 42,462 58,902 54,345 89,481 34 Kwimba 1,456 5,396 43,545 73,545 45,001 78,941 7 Sengerema 6,513 12,512 56,565 52,026 63,078 64,538 19 Geita 7,226 14,936 84,092 120,941 91,318 135,878 11 Missungwi 2,290 4,934 31,582 51,697 33,872 56,631 9 Ilemela 414 403 9,919 5,749 10,334 6,153 7 Total 30,371 68,931 291,877 369,247 322,248 438,177 16 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 83 12 24,215 6,545 24,298 6,557 0.2 Magu 2,828 4,346 51,517 85,134 54,345 89,481 4.9 Kwimba 606 3,113 44,396 75,828 45,001 78,941 3.9 Sengerema 277 275 62,802 64,263 63,078 64,538 0.4 Geita 2,812 6,381 88,507 129,496 91,318 135,878 4.7 Missungwi 252 781 33,620 55,850 33,872 56,631 1.4 Ilemela 157 71 10,176 6,082 10,334 6,153 1.2 Total 7,015 14,979 315,233 423,199 322,248 438,177 3.4 Households Not Using Herbicidess Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Short Season. District Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess % of Planted Area Using Insecticides Household Using Insecticides 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short Season. Households Not Using Insecticides Total District Insecticide Use Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 164 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 167 25 24,131 6,532 24,298 6,557 0.4 Magu 3,089 7,366 51,256 82,114 54,345 89,481 8.2 Kwimba 727 3,888 44,274 75,053 45,001 78,941 4.9 Sengerema 847 1,405 62,232 63,132 63,078 64,538 2.2 Geita 1,086 1,495 90,232 134,382 91,318 135,878 1.1 Missungwi 395 372 33,477 56,258 33,872 56,631 0.7 Ilemela 408 436 9,926 5,717 10,334 6,153 7.1 Total 6,719 14,989 315,529 423,189 322,248 438,177 3.4 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Ukerewe 6,125 2,021 18,173 4,536 24,298 6,557 30.8 Magu 26,982 49,673 27,363 39,808 54,345 89,481 55.5 Kwimba 10,026 22,428 34,975 56,513 45,001 78,941 28.4 Sengerema 21,885 29,482 41,194 35,056 63,078 64,538 45.7 Geita 21,318 33,093 70,000 102,785 91,318 135,878 24.4 Missungwi 10,685 15,933 23,188 40,698 33,872 56,631 28.1 Ilemela 4,365 3,157 5,969 2,995 10,334 6,153 51.3 Total 101,387 155,787 220,861 282,391 322,248 438,177 % 31 36 69 64 100 100 35.6 7.1f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season. District Fungicide Use % of Planted Area Using Fungicides Household Using Fungicides Households Not Using Fungicides Total % of Planted Area Using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Short SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census -2003 Mwanza 165 Appendix II 166 ANNUAL CROP & VEGETABLES PRODUCTION LONG SEASON Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 167 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 0 0 323 92 18,657 4,281 18,980 4,373 Magu 0 0 7,871 10,673 5,538 2,464 13,409 13,137 Kwimba 105 85 12,251 25,836 3,095 3,124 15,451 29,044 Sengerema 605 183 3,157 4,317 23,471 12,455 27,234 16,954 Geita 0 0 4,875 5,655 17,487 11,218 22,362 16,873 Missungwi 331 126 5,979 9,104 8,589 8,674 14,898 17,904 Ilemela 58 23 188 88 6,946 2,966 7,192 3,077 Total 1,098 417 34,644 55,764 83,783 45,181 119,525 101,362 % 0.9 0.4 29.0 55.0 70.1 45 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 21,405 13,006 2,288 849 333 79 31,768 14,109 55,794 28,042 Magu 5,857 6,027 2,140 1,523 630 361 31,471 24,052 40,099 31,964 Kwimba 4,011 5,346 299 151 196 85 33,869 31,821 38,375 37,404 Sengerema 12,244 12,407 589 207 731 218 75,492 42,732 89,057 55,565 Geita 3,433 2,711 598 499 1,303 280 61,273 47,590 66,607 51,080 Missungwi 4,345 2,225 151 61 1,105 676 36,170 25,086 41,771 28,049 Ilemela 5,810 2,355 957 346 1,216 345 15,206 5,781 23,189 8,826 Total 57,106 44,079 7,024 3,636 5,514 2,044 285,248 191,171 354,891 240,929 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 32,241 23,584 23,554 4,458 55,794 28,042 84 Magu 22,899 19,037 17,199 12,927 40,099 31,964 60 Kwimba 14,750 8,752 23,624 28,652 38,375 37,404 23 Sengerema 50,931 32,437 38,126 23,127 89,057 55,565 58 Geita 43,188 34,940 23,419 16,140 66,607 51,080 68 Missungwi 20,245 10,249 21,526 17,800 41,771 28,049 37 Ilemela 12,678 6,143 10,511 2,683 23,189 8,826 70 Total 196,932 135143 157958 105786 354,891 240929 56 % 55.5 56.1 44.5 43.9 100 100 % of planted area under irrigation in short season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Long Season, 2002/03 Agriculture Year, Mwanza Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - Long SEASON, Mwanza Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - Long SEASON, Mwanza Region Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 168 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 663 130 55,131 27,912 55,794 28,042 0.46 Magu 2,648 3,955 37,451 28,008 40,099 31,964 12.37 Kwimba 1,033 2,934 37,342 34,470 38,375 37,404 7.84 Sengerema 3,607 1,044 85,449 54,521 89,057 55,565 1.88 Geita 3,730 1,918 62,876 49,162 66,607 51,080 3.75 Missungwi 2,364 859 39,407 27,190 41,771 28,049 3.06 Ilemela 1,850 420 21,339 8,407 23,189 8,826 4.75 Total 15,895 11,259 338,995 229,670 354,891 240,929 4.67 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 250 93 32,132 27,950 32,383 28,042 0.3 Magu 792 810 30,465 31,153 31,257 31,964 2.5 Kwimba 524 1,590 25,855 35,814 26,379 37,404 4.3 Sengerema 563 431 57,001 55,133 57,563 55,565 0.8 Geita 1,057 1,203 50,181 49,877 51,237 51,080 2.4 Missungwi 90 73 25,114 27,976 25,204 28,049 0.3 Ilemela 209 259 10,669 8,567 10,878 8,826 2.9 Total 3,484 4,459 231,417 236,470 234,901 240,929 1.9 % 1.5 1.9 98.5 98.1 100 100 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Long Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Long Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 169 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Ukerewe 242 127 32,141 27,915 32,383 28,042 0.5 Magu 886 773 30,371 31,191 31,257 31,964 2.4 Kwimba 824 1,899 25,555 35,505 26,379 37,404 5.1 Sengerema 858 703 56,706 54,861 57,563 55,565 1.3 Geita 804 1,136 50,433 49,944 51,237 51,080 2.2 Missungwi 1,179 1,323 24,025 26,726 25,204 28,049 4.7 Ilemela 1,027 926 9,851 7,900 10,878 8,826 10.5 Total 5,820 6,887 229,082 234,042 234,901 240,929 2.9 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Ukerewe 2,073 594 16,906 3,779 18,980 4,373 13.6 Magu 3,467 1,957 9,942 11,180 13,409 13,137 14.9 Kwimba 4,193 12,797 11,258 16,247 15,451 29,044 44.1 Sengerema 3,759 3,608 23,475 13,347 27,234 16,954 21.3 Geita 1,831 1,062 20,531 15,811 22,362 16,873 6.3 Missungwi 2,628 2,872 12,270 15,032 14,898 17,904 16.0 Ilemela 2,296 931 4,896 2,145 7,192 3,077 30.3 Total 20,248 23,821 99,277 77,541 119,525 101,362 23.5 % 17 24 83 76 100 100 % of planted area under Improved Seed use in Long season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - Long SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Long SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 170 Number of House- holds Plante d Area Number of House- holds Plante d Area Number of House- holds Plante d Area Number of House- holds Plante d Area Number of House- holds Plante d Area Number of House- holds Plante d Area CEREALS 44,152 389 46,246 65 828 4,040 51,569 Maize 162 66 17,009 11,937 196 57 0 0 1,539 897 18,710 12,956 Paddy 616 282 44,140 31,164 83 8 905 828 6,594 3,021 52,255 35,303 Sorghum 104 42 4,065 2,237 0 0 0 0 334 122 4,503 2,401 Bulrush Millet 0 0 1,416 908 0 0 0 0 0 0 1,416 908 Finger Millet 0 0 0 0 0 0 0 0 0 0 0 0 ROOTS & TUBERS 263 10,764 0 43 452 11,522 Cassava 0 0 636 201 0 0 0 0 85 11 721 212 Sweet Potatoes 651 196 40,255 10,547 0 0 214 43 1,816 440 42,936 11,227 Irish Potatoes 166 67 167 15 0 0 0 0 0 0 333 83 PULSES 55 2,153 0 0 221 2,430 Mung Beans 0 0 0 0 0 0 0 0 0 0 0 0 Beans 137 55 6,099 1,433 0 0 0 0 699 190 6,935 1,679 Cowpeas 0 0 2,526 435 0 0 0 0 368 31 2,894 467 Green Gram 0 0 1,146 285 0 0 0 0 0 0 1,146 285 Chich Peas 0 0 0 0 0 0 0 0 0 0 0 0 Bambaranuts 0 0 0 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 0 521 0 28 17 566 Groundnuts 0 0 1,220 521 0 0 88 28 139 17 1,446 566 Soya Beans 0 0 0 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 36 1,514 0 0 176 1,726 Onions 90 18 567 92 0 0 0 0 0 0 656 110 Cabbage 0 0 965 108 0 0 0 0 160 20 1,125 127 Tomatoes 90 18 4,598 711 0 0 0 0 637 125 5,325 855 Spinnach 0 0 0 471 60 0 0 0 0 0 0 471 Carrot 0 0 302 55 0 0 0 0 0 0 302 55 Chillies 0 0 476 28 0 0 0 0 54 8 531 35 Amaranths 0 0 406 50 0 0 0 0 153 23 559 73 Total 744 61,199 65 900 4,905 67,814 % 1.1 90.2 0.1 1.3 7.2 100 Crop 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households During Long Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 8,440 1,375 1,439 1.047 1,436 243 243 1.002 1,617 1,683 1.04 Magu 47,741 36,339 23,358 0.643 4,546 4,073 2,976 0.731 40,412 26,334 0.65 Kwimba 39,698 34,786 12,792 0.368 4,334 4,923 1,832 0.372 39,709 14,625 0.37 Sengerema 61,297 31,158 35,861 1.151 2,721 1,120 1,185 1.058 32,278 37,046 1.15 Geita 89,936 63,683 54,586 0.857 792 399 303 0.758 64,083 54,888 0.86 Missungwi 32,006 25,456 12,706 0.499 2,151 1,219 858 0.704 26,675 13,563 0.51 Ilemela 9,399 2,758 1,863 0.676 2,926 979 802 0.820 3,737 2,666 0.71 Total 288,518 195,556 142,605 0.729 18,906 12,956 8,199 0.633 208,512 150,804 0.72 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 85 9 5 0.534 9 5 0.53 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.00 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.00 Sengerema 0 0 0 0.000 154 125 46 0.371 125 46 0.37 Geita 0 0 0 0.000 0 0 0 0.000 0 0 0.00 Missungwi 1,238 1,690 509 0.301 1,777 1,748 633 0.362 3,438 1,141 0.33 Ilemela 0 0 0 0.000 0 0 0 0.000 0 0 0.00 Total 1,238 1,690 509 0.301 2,017 1,882 684 0.363 3,572 1,192 0.33 Long Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year Maize District Short Season 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year Burlush millet District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 662 190 210 1.104 5,534 1,078 1,757 1.630 1,268 1,966 1.551 Magu 12,986 6,473 5,240 0.809 2,116 2,353 1,990 0.846 8,826 7,230 0.819 Kwimba 22,645 14,517 8,210 0.566 6,675 6,124 3,391 0.554 20,641 11,601 0.562 Sengerema 7,740 5,351 7,184 1.343 17,318 10,021 13,950 1.392 15,371 21,134 1.375 Geita 18,604 13,709 14,885 1.086 12,390 11,017 14,384 1.306 24,726 29,269 1.184 Missungwi 13,667 11,190 6,766 0.605 4,743 3,675 2,097 0.571 14,865 8,862 0.596 Ilemela 1,680 498 412 0.828 3,560 1,036 1,330 1.285 1,534 1,743 1.136 Total 77,984 51,928 42,906 0.826 52,338 35,303 38,899 1.102 87,231 81,805 0.938 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 336 47 50 1.054 248 47 16 0.335 94 66 0.697 Magu 6,455 2,842 1,959 0.689 532 147 149 1.014 2,989 2,108 0.705 Kwimba 6,822 2,709 1,257 0.464 727 675 261 0.386 3,384 1,518 0.449 Sengerema 1,204 1,022 714 0.698 1,241 725 720 0.993 1,747 1,434 0.821 Geita 2,871 1,118 1,424 1.274 999 406 201 0.496 1,524 1,625 1.066 Missungwi 4,898 2,710 1,235 0.456 647 354 200 0.565 3,064 1,435 0.468 Ilemela 574 107 59 0.551 109 49 27 0.556 156 86 0.552 Total 23,161 10,556 6,698 0.635 4,503 2,401 1,573 0.655 12,958 8,271 0.638 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Sorghum District Short Season Long Season Total 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Paddy District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 173 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 85 17 41 2.371 82 8 5 0.644 17 41 2.371 Magu 258 131 27 0.207 0 0 0 0.000 131 27 0.207 Kwimba 0 0 0 0.000 0 0 0 0.000 54 16 0.296 Sengerema 0 0 0 0.000 133 54 16 0.296 847 1,171 1.382 Geita 3,793 2,320 1,134 0.489 1,202 847 1,171 1.382 2,320 1,134 0.489 Missungwi 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ilemela 0 0 0 0.000 0 0 0 0.000 908 1,191 1.311 Total 4,137 2,468 1,202 0.487 1,416 908 1,191 1.311 2,468 1,202 0.487 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 2,850 327 144 0.441 810 101 33 0.325 428 177 0.414 Magu 12,076 2,617 887 0.339 2,678 711 276 0.389 3,328 1,163 0.350 Kwimba 2,208 411 83 0.201 105 13 4 0.329 424 87 0.205 Sengerema 42,814 8,940 3,873 0.433 1,195 245 109 0.445 9,186 3,983 0.434 Geita 56,285 17,038 7,237 0.425 167 17 10 0.593 17,055 7,247 0.425 Missungwi 3,697 921 185 0.201 837 402 173 0.430 1,323 358 0.271 Ilemela 4,938 611 167 0.273 1,143 190 36 0.192 801 203 0.253 Total 124,869 30,865 12,575 0.407 6,935 1,679 642 0.382 32,544 13,217 0.406 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Short Season Long Season Total Long Season Total 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Short Season Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 174 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0 0 0 0 0.000 0 0 0.000 Magu 6,321 866 402 0.464 139 11 5 0.469 877 407 0.933 Kwimba 12,632 4,694 1,325 0.282 830 256 64 1.000 4,950 1,389 1.282 Sengerema 414 84 22 0.261 0 0 0 0.000 84 22 0.261 Geita 160 6 2 0.247 0 0 0 2.000 6 2 2.247 Missungwi 9,198 2,712 597 0.220 177 18 2 0.100 2,730 599 0.321 Ilemela 460 80 14 0.174 0 0 0 3.000 80 14 3.174 Total 29,184 8,443 2,362 0.280 1,146 285 71 0.249 8,728 2,433 0.529 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 175 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 1,145 116 35 0.303 330 35 15 0.420 151 50 0.330 Magu 5,050 659 230 0.349 693 76 22 0.289 734 252 0.343 Kwimba 1,746 326 72 0.221 105 17 1 0.074 343 73 0.214 Sengerema 6,375 1,025 588 0.574 605 205 85 0.414 1,230 673 0.547 Geita 2,183 352 55 0.157 0 0 0 0.000 352 55 0.157 Missungwi 6,243 1,296 279 0.215 267 23 6 0.237 1,320 284 0.215 Ilemela 4,229 604 250 0.414 895 110 21 0.191 715 271 0.379 Total 26,972 4,378 1,509 0.345 2,894 467 149 0.320 4,845 1,658 0.342 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 1,314 165 115 0.699 247 46 17 0.380 211 133 0.630 Magu 120 15 7 0.502 0 0 0 0.000 15 7 0.502 Kwimba 516 147 52 0.357 210 42 9 0.217 189 62 0.326 Sengerema 460 53 36 0.668 109 27 2 0.074 80 37 0.470 Geita 888 132 45 0.340 0 0 0 0.000 132 45 0.340 Missungwi 1,315 176 134 0.765 504 65 35 0.539 241 169 0.703 Ilemela 717 82 24 0.292 117 9 0 0.043 92 24 0.266 Total 5,331 769 414 0.538 1,187 190 64 0.339 959 478 0.498 Long Season Total 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Cowpeas District Short Season 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 176 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 0 0 0 0.0000 0 0 0.0000 Magu 0 0 0 0.000 4,144 5,066 4,373 0.8632 5,066 4,373 0.8632 Kwimba 408 128 141 1.101 6,914 14,373 5,950 0.4140 14,500 6,091 0.4200 Sengerema 0 0 0 0.000 896 915 670 0.7322 915 670 0.7322 Geita 0 0 0 0.000 1,100 1,643 645 0.3924 1,643 645 0.3924 Missungwi 90 29 2 0.062 4,482 7,740 3,452 0.4459 7,769 3,453 0.4445 Ilemela 0 0 0 0.000 0 0 0 0.0000 0 0 0.0000 Total 498 157 142 0.908 17,535 29,738 15,090 0.5074 29,894 15,232 0.5095 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 1,140 221 540 2.438 32,294 23,712 37,408 2 23,933 37,948 2 Magu 210 198 25 0.128 22,267 18,881 21,930 1 19,079 21,956 1 Kwimba 0 0 0 0.000 14,546 8,392 17,837 2 8,392 17,837 2 Sengerema 1,057 185 79 0.425 51,560 38,682 76,993 2 38,868 77,072 2 Geita 1,239 784 1,567 1.998 39,498 34,207 30,970 1 34,992 32,538 1 Missungwi 164 40 3 0.087 18,481 10,144 7,860 1 10,185 7,863 1 Ilemela 59 14 24 1.647 10,207 5,761 9,066 2 5,776 9,089 2 Total 3,870 1,443 2,238 1.551 188,853 139,780 202,065 1 141,223 204,303 1 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Short Season Long Season Total 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick peas District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 177 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 21,705 3,992 7,973 1.997 13,992 2,684 4,218 1.572 6,676 12,191 1.826 Magu 19,187 4,729 5,295 1.120 1,956 513 989 1.927 5,242 6,284 1.199 Kwimba 15,345 4,213 2,950 0.700 2,287 812 524 0.646 5,025 3,474 0.691 Sengerema 17,635 4,379 8,466 1.933 10,085 2,714 4,386 1.616 7,094 12,852 1.812 Geita 9,354 2,512 2,523 1.005 7,103 2,083 2,967 1.424 4,595 5,490 1.195 Missungwi 11,074 2,752 3,056 1.110 5,338 2,014 1,542 0.766 4,766 4,598 0.965 Ilemela 4,773 914 1,507 1.649 2,176 407 696 1.709 1,321 2,203 1.667 Total 99,073 23,491 31,770 1.352 42,936 11,227 15,321 1.365 34,717 47,092 1.356 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 167 15 44 2.901 15 44 2.901 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Sengerema 0 0 134 0.000 0 0 0 0.000 0 0 0.000 Geita 0 0 0 0.000 166 67 33 0.494 67 33 0.494 Missungwi 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ilemela 59 5 9 0.000 0 0 0 0.000 5 9 1.853 Total 59 5 143 0 333 83 78 3 87 220 2.524 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Short Season Long Season Total Long Season Total 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Short Season Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 178 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 85 24 3 0.113 0 0 0 0.000 24 3 0.113 Magu 2,969 584 309 0.530 139 17 22 1.317 601 332 0.552 Kwimba 12,222 5,298 1,748 0.330 729 379 132 0.347 5,677 1,880 0.331 Sengerema 9,881 2,411 2,083 0.864 155 28 15 0.549 2,439 2,099 0.860 Geita 23,723 7,758 4,170 0.537 164 67 0 0.000 7,825 4,170 0.533 Missungwi 8,441 2,249 883 0.392 259 76 10 0.134 2,325 893 0.384 Ilemela 334 42 13 0.296 0 0 0 0.000 42 13 0.296 Total 57,655 18,367 9,208 0.501 1,446 566 180 0.317 18,934 9,388 0.496 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Magu 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Sengerema 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Geita 315 66 28 0.430 0 0 0.000 0.000 66 28 0.430 Missungwi 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Ilemela 0 0 0 0.000 0 0 0.000 0.000 0 0 0.000 Total 315 66 28 0.430 0 0 0.000 0.000 66 28 0.430 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Short Season Long Season Total 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 179 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0 0 0 0 0.000 0 0 0.000 Magu 0 0 0 0 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0 0 0 0 0.000 0 0 0.000 Sengerema 0 0 0 0 0 0 0 0.000 0 0 0.000 Geita 0 0 0 0 169 10 68 6.587 10 68 6.587 Missungwi 0 0 0 0 0 0 0 0.000 0 0 0.000 Ilemela 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 169 10 68 6.587 10 68 6.587 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0 0 0 0 0 0 0 0 Magu 0 0 0 0 0 0 0 0 0 0 0 Kwimba 0 0 0 0 0 0 0 0 0 0 0 Sengerema 0 0 0 0 0 0 0 0 0 0 0 Geita 0 0 0 0 0 0 0 0 0 0 0 Missungwi 0 0 0 0 0 0 0 0 0 0 0 Ilemela 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year Tumeric District Short Season Long Season Total Long Season Total 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Short Season Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 180 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 83 8 2 0.247 8 2 0.247 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Sengerema 261 39 671 17.067 154 16 61 3.952 55 733 13.350 Geita 802 142 245 1.728 0 0 0 0.000 142 245 1.728 Missungwi 75 15 58 3.804 420 87 602 6.947 102 660 6.479 Ilemela 99 10 24 2.438 0 0 0 0.000 10 24 2.438 Total 1,237 206 998 4.845 656 110 666 6.054 316 1,664 5.266 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 325 38 60 1.594 321 36 148 4.053 74 208 2.801 Magu 489 173 428 2.479 628 100 52 0.521 273 481 1.760 Kwimba 202 61 259 4.253 300 71 463 6.472 132 722 5.451 Sengerema 983 214 1,808 8.434 1,038 221 2,118 9.569 436 3,926 9.011 Geita 747 143 1,188 8.338 840 74 253 3.417 217 1,441 6.654 Missungwi 1,107 265 1,631 6.164 1,015 185 648 3.499 450 2,279 5.066 Ilemela 1,163 154 682 4.435 1,258 181 975 5.391 335 1,657 4.952 Total 5,016 1,047 6,058 5.786 5,400 870 4,657 5.354 1,917 10,714 5.590 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Short Season Long Season Total 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 181 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Sengerema 0 0 0 0.000 133 13 36 2.668 13 36 2.668 Geita 0 0 0 0.000 338 20 134 6.729 20 134 6.729 Missungwi 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Ilemela 153 20 36 1.840 51 10 20 1.976 30 57 1.886 Total 153 20 36 1.840 521.9274735 43.593951 189.8112077 4.354 63 226 3.570 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0.000 0.000 0 0 0 0.000 0 0 0.000 Magu 0 0 0.000 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0.000 0.000 0 0 0 0.000 0 0 0.000 Sengerema 133 40 43.836 1.087 133 40 44 1.087 81 88 1.087 Geita 169 15 6.765 0.449 0 0 0 0.000 15 7 0.449 Missungwi 0 0 0.000 0.000 0 0 0 0.000 0 0 0.000 Ilemela 0 0 0.000 0.000 51 5 22 4.347 5 22 4.347 Total 302 55 50.600 0.913 184 45 66 1.456 101 117 1.158 Long Season Total 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Short Season 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year Carrot District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 182 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Sengerema 133 54 34 0.630 0 0 0 0.000 54 34 0.630 Geita 85 9 9 0.988 338 14 46 3.335 22 54 2.428 Missungwi 0 0 0 0.000 90 9 4 0.395 9 4 0.395 Ilemela 107 5 27 4.989 103 13 59 4.695 18 86 4.783 Total 325 68 69 1.023 531 35 108 3.066 103 178 1.723 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Ukerewe 168 20 52 2.552 83 17 12 0.741 37 64 1.732 Magu 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kwimba 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Sengerema 261 19 323 17.301 133 13 20 1.482 32 343 10.675 Geita 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Missungwi 0 0 0 0.000 76 8 9 1.186 8 9 1.186 Ilemela 369 30 156 5.167 267 35 132 3.783 65 287 4.425 Total 798 69 530 7.669 559 73 173 2.379 142 704 4.956 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Short Season Long Season Total 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year Chillies District Short Season Long Season Total Tanzania Agriculture Sample Census -2003 Mwanza 183 Appendix II 184 PERMANENT CROPS Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 185 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Palm Oil 31 8 871 114,659 Coconut 17 16 12 771 Coffee 97 24 260 10,872 Sugarcane 7 7 171 24,700 Banana 215 139 885 6,368 Mango 252 163 2,920 17,910 Pawpaw 55 53 289 5,429 Pineapple 18 17 42 2,447 Orange 1,010 780 17,522 22,458 Mandarine/Tangerine 40 38 195 5,132 Guava 708 22 18 809 Lime/Lemon 12 13 27 2,178 Total 2,480 1,280 23,214 18,139 Pigeon Pea 52 26 16 597 Sugarcane 12 12 728 60,001 Mango 9 6 83 13,336 Total 73 44 Sour Soup 533 254 1 2 Banana 59 19 87 4,624 Mango 53 20 308 15,748 Orange 16 4 26 6,916 Mandarine/Tangerine 28 4 23 6,175 Total 846 321 Sugarcane 112 18 243 13,173 Banana 644 393 2,988 7,610 Mango 695 151 21,055 139,564 Pawpaw 103 295 711 2,407 Pineapple 44 44 33 763 Orange 1,557 195 3,381 17,299 Lime/Lemon 12 12 89 7,259 Total 3,197 1,200 Sugarcane 89 77 2,526 32,936 Banana 1,189 841 7,547 8,971 Mango 5,118 263 23,488 89,326 Pawpaw 23 14 2,184 161,699 Pineapple 3,653 73 90 1,234 Orange 107 12 1,453 123,954 Total 10,383 1,279 Banana 110 68 688 10,050 Mango 134 7 3,704 510,611 Pawpaw 18 7 635 90,315 Orange 33 13 116 8,783 Total 390 117 Sugarcane 151 94 1,431 15,282 Mshelisheli 3 2 28 11,856 Banana 48 15 156 10,151 Mango 97 60 4,537 75,352 Pawpaw 3 30 120 3,934 Orange 132 18 238 13,216 Guava 3 2 93 45,234 Lime/Lemon 2 9 225 25,954 Total 451 231 District/Crop Ukerewe 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Mwanza. Magu Ilemela Kwimba Sengerema Geita Missungwi Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 186 Crop Area Planted % Mango 6,358 35.68 Orange 2,855 16.02 Banana 2,264.0 12.71 Guava 711 3.99 Total 17,819 100.00 District Area Planted with Orange Total Area Planted (Ha) % of Total Area Planted Households with Orange Average Planted Area per Household Ukerewe 1,010 2,480 35.4 9,641 0.1 Magu 0 0 0.0 0 0.0 Kwimba 16 846 0.6 191 0.08 Sengerema 1,557 3,197 54.5 3,197 0.49 Geita 107 10,383 3.7 1,651 0.06 Missungwi 33 390 1.2 248 0.13 Ilemela 132 451 4.6 518 0.25 Total 2,855 17,747 100 15,446 0.18 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Households with Banana Average Planted Area per Household Ukerewe 215 2,480 9.5 3,338.0 0.1 Magu 0.0 0 0.0 0 0.00 Kwimba 59 846 2.6 191.0 0.3 Sengerema 644 3,197 28.4 2,052.0 0.3 Geita 1,189 10,383 52.5 3,839.0 0.3 Missungwi 110 390 4.9 501.0 0.2 Ilemela 48 451 2.1 551.0 0.1 Total 2,265 17,747 100 10,472 0.6 Banana 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Mwanza Region Orange 7.3.3 PERMANENT CROPS: Area Planted with Oranges by District 7.3.4 PERMANENT CROPS: Area planted with Banana by District Tanzania Agriculture Sample Census -2003 Mwanza 187 Appendix II 188 AGROPROCESSING Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 189 Number % Number % Number % Ukerewe 31,029 94 1,879 6 32,909 100 Magu 50,316 89 6,045 11 56,360 100 Kwimba 43,050 94 2,763 6 45,813 100 Sengerema 63,542 98 1,120 2 64,661 100 Geita 91,814 98 1,472 2 93,286 100 Missungwi 33,111 97 1,022 3 34,132 100 Ilemela 12,403 96 519 4 12,922 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader Other Total Ukerewe 24,676 682 5,671 0 0 31,029 Magu 1,735 2,029 45,104 1,448 0 50,316 Kwimba 3,366 1,136 33,513 5,035 0 43,050 Sengerema 2,563 587 55,267 4,698 151 63,265 Geita 4,881 3,088 81,354 2,181 0 91,503 Missungwi 5,541 158 27,330 82 0 33,111 Ilemela 2,684 1,966 6,218 1,485 0 12,352 On Farm by Hand On Farm by Machine By Neighbour Machine By Trader On Large Scale Farm Other Total Maize 24,676 682 5,671 0 0 0 31,029 Paddy 1,735 2,029 45,104 1,448 0 0 50,316 Sorghum 3,366 1,136 33,513 5,035 0 0 43,050 Bulrush Millet 2,563 587 55,267 4,698 0 151 63,265 Cassava 4,881 3,088 81,354 2,181 152 0 91,655 Beans 5,541 158 27,330 82 0 0 33,111 Cowpeas 2,684 1,966 6,218 1,485 0 0 12,352 Bambaranut 45,446 9,644 254,456 14,929 152 151 324,778 8.1.1a AGRO PROCESSING: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Processed Products Households That did not Process Products Total 8.1.1b AGRO PROCESSING: Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing Method of Processing Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Mwanza Region Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 190 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 280,597 310 151 69 638 59 281,824 Paddy 111,195 397 1,686 0 727 0 114,005 Sorghum 22,447 90 165 0 0 0 22,702 Bulrush Millet 2,717 0 0 0 0 0 2,717 Finger Millet 1,092 0 269 0 0 0 1,361 Cassava 108,842 478 1,787 0 0 155 111,262 Sweet Potatoes 1,568 83 0 0 0 0 1,651 Beans 812 0 0 0 0 0 812 Cowpeas 298 0 0 0 0 0 298 Green Gram 633 0 0 0 0 0 633 Chick Peas 2,918 0 209 0 0 0 3,127 Simsim 296 0 0 0 0 0 296 Groundnut 2,374 0 209 0 0 0 2,583 Oil Palm 646 0 85 0 0 0 731 Coconut 133 0 0 0 0 0 133 Orange 83 0 0 0 0 0 83 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 1,239 7,527 0 382 690 550 974 5,376 265,087 281,824 Paddy 2,447 5,255 643 922 510 99 1,868 1,976 100,286 114,005 Sorghum 0 974 89 0 0 165 124 818 20,531 22,702 Bulrush Millet 0 0 0 0 0 0 0 0 2,717 2,717 Finger Millet 264 0 0 0 0 0 0 0 1,097 1,361 Cassava 2,844 5,074 159 0 389 219 1,461 969 100,148 111,262 Sweet Potatoes 0 0 0 0 0 0 0 89 1,563 1,651 Beans 0 167 0 0 0 0 0 0 645 812 Cowpeas 0 0 0 0 0 0 0 0 298 298 Green Gram 105 0 0 0 0 0 0 89 440 633 Chick Peas 0 447 90 0 0 0 0 0 2,591 3,127 Simsim 0 148 0 0 0 0 0 0 148 296 Groundnut 0 505 0 0 0 0 0 89 1,989 2,583 Oil Palm 0 0 0 0 0 0 0 0 731 731 Coconut 0 0 0 0 0 0 0 0 133 133 Orange 0 0 0 0 0 0 0 0 83 83 Flour / Meal Grain Oil Juice Fiber Other Total Ukerewe 28,491 2,455 0 83 0 0 31,029 Magu 46,312 3,867 0 137 0 0 50,316 Kwimba 31,697 11,353 0 0 0 0 43,050 Sengerema 58,236 5,306 0 0 0 0 63,542 Geita 86,228 5,431 155 0 0 0 91,814 Missungwi 28,405 4,705 0 0 0 0 33,111 Ilemela 11,146 1,208 48 0 0 0 12,403 Total 290,516 34,326 203 220 0 0 325,265 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Mwanza Region Where Sold 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Mwanza Region Crop 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Mwanza Region District Main Product Product Use Crop Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 191 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Total Ukerewe 30,547 171 311 0 0 31,029 Magu 49,903 135 0 0 278 50,316 Kwimba 42,328 0 409 0 314 43,050 Sengerema 63,089 0 300 0 154 63,542 Geita 91,323 0 304 0 187 91,814 Missungwi 32,952 90 0 69 0 33,111 Ilemela 12,240 0 59 0 104 12,403 Total 322,381 395 1,382 69 1,037 325,265 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Ukerewe 2,110 244 0 0 83 0 1,117 171 27,305 31,029 Magu 1,142 683 0 0 134 0 364 4,006 43,986 50,316 Kwimba 417 689 312 0 311 99 209 105 40,909 43,050 Sengerema 0 2,088 0 133 153 307 151 0 60,711 63,542 Geita 739 5,005 0 167 332 331 817 707 83,717 91,814 Missungwi 86 503 89 82 0 77 0 978 31,295 33,111 Ilemela 165 192 58 0 0 0 75 162 11,751 12,403 Total 4,659 9,404 460 382 1,012 814 2,732 6,130 299,673 325,265 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Ukerewe 2,943 0 1,919 0 85 83 147 0 25,853 0 31,029 Magu 2,487 0 9,535 0 0 483 0 278 37,532 0 50,316 Kwimba 4,206 209 19,251 0 0 711 0 523 18,150 0 43,050 Sengerema 1,118 0 20,448 0 0 303 0 0 41,672 0 63,542 Geita 11,236 0 17,717 1,154 163 0 0 133 61,411 0 91,814 Missungwi 2,109 90 13,174 0 0 170 0 0 17,568 0 33,111 Ilemela 1,121 0 3,907 1,602 0 0 0 141 5,633 0 12,403 Total 25,221 298 85,950 2,756 248 1,751 147 1,075 207,819 0 325,265 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Mwanza Region District Product Use District By Product 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Mwanza Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Mwanza Region Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 192 MARKETING Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 193 Number % Number % Ukerewe 23,124 70.3 9,785 29.7 32,909 Magu 43,178 76.6 13,182 23.4 56,360 Kwimba 28,366 61.9 17,447 38.1 45,813 Sengerema 50,648 78.3 14,014 21.7 64,661 Geita 67,156 72.0 26,131 28.0 93,286 Missungwi 22,882 67.0 11,251 33.0 34,132 Ilemela 7,847 60.7 5,075 39.3 12,922 Total 243,200 71.5 96,884 28.5 340,085 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Total Ukerewe 160 9729 239 0 80 251 0 761 11219 Magu 594 13951 0 0 0 139 260 418 15362 Kwimba 924 19358 208 0 100 0 0 616 21206 Sengerema 307 17605 153 0 0 1200 0 145 19411 Geita 970 30314 167 0 0 0 0 155 31606 Missungwi 420 18523 265 0 0 0 0 161 19369 Ilemela 164 5278 0 0 0 51 0 26 5519 Total 3539 114758 1032 0 180 1641 260 2282 123692 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Total Ukerewe 1 87 2 0 1 2 0 7 100 Magu 4 91 0 0 0 1 2 3 100 Kwimba 4 91 1 0 0 0 0 3 100 Sengerema 2 91 1 0 0 6 0 1 100 Geita 3 96 1 0 0 0 0 0 100 Missungwi 2 96 1 0 0 0 0 1 100 Ilemela 3 96 0 0 0 1 0 0 100 Total 3 93 1 0 0 1 0 2 100 10.1 MARKETING: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Mwanza Region Households that Sold Households that Did not Sell Total Number of households 10.2 MARKETING: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Mwanza Region District Main Reasons for Not Selling Crops Main Reasons for Not Selling Crops District 10.3 MARKETING: Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Mwanza Region Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 194 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 195 Number of Household % Number of Household % Number of Household % Ukerewe 879 3 32,029 97 32,909 100 Magu 1,121 2 55,240 98 56,360 100 Kwimba 711 2 45,102 98 45,813 100 Sengerema 1,869 3 62,792 97 64,661 100 Geita 4,174 4 89,113 96 93,286 100 Missungwi 2,785 8 31,347 92 34,132 100 Ilemela 3,085 24 9,837 76 12,922 100 Total 14,625 4 325,460 96 340,085 100 District Irrigatable Area (ha) Irrigated Land (ha) % Ukerewe 173 170 98.2 Magu 305 246 80.8 Kwimba 240 207 86.1 Sengerema 1,477 683 46.2 Geita 2,673 2,648 99.1 Missungwi 745 631 84.7 Ilemela 908 686 75.6 Total 6,521 5,272 80.9 River Lake Dam Well Borehole Canal Pipe water Total Ukerewe 225 407 0 247 0 0 0 879 Magu 120 369 0 500 0 132 0 1,121 Kwimba 306 105 0 300 0 0 0 711 Sengerema 308 831 155 576 0 0 0 1,869 Geita 1,505 166 153 839 0 1,511 0 4,174 Missungwi 179 308 858 1,203 0 161 76 2,785 Ilemela 438 258 536 1,286 55 512 0 3,085 Total 3,081 2,443 1,701 4,951 55 2,317 76 14,625 Gravity Hand Bucket Hand Pump Motor Pump Total Ukerewe 150 730 0 0 879 Magu 0 996 125 0 1,121 Kwimba 210 403 99 0 711 Sengerema 155 1,586 129 0 1,869 Geita 2,513 1,156 505 0 4,174 Missungwi 80 2,548 0 157 2,785 Ilemela 709 2,376 0 0 3,085 Total 3,817 9,795 857 157 14,625 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total District Method of Obtaining Water 11.4 IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 196 Flood Sprinkler Water Hose Bucket / Watering Can Total Ukerewe 150 0 0 730 879 Magu 0 249 0 872 1,121 Kwimba 210 0 99 403 711 Sengerema 0 0 129 1,740 1,869 Geita 2,682 169 335 987 4,174 Missungwi 161 69 162 2,392 2,785 Ilemela 543 52 0 2,490 3,085 Total 3,745 540 725 9,615 14,625 Number % Number % Ukerewe 3,222 10 29,687 90 32,909 Magu 13,398 24 42,962 76 56,360 Kwimba 5,278 12 40,535 88 45,813 Sengerema 3,690 6 60,971 94 64,661 Geita 923 1 92,364 99 93,286 Missungwi 1,815 5 32,317 95 34,132 Ilemela 527 4 12,396 96 12,922 Total 28,852 8 311,233 92 340,085 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Ukerewe 0 74,085 0 83 0 16,849 81 0 91,098 Magu 40,995 267,572 0 0 1,780 230,710 4,065 0 545,123 Kwimba 0 12,011 0 0 103 16,730 4,892 102 33,837 Sengerema 531 15,448 4,918 1,112 2,925 1,825 1,458 797 29,014 Geita 0 1,215 0 167 0 0 0 0 1,381 Missungwi 0 69,169 0 0 0 5,737 0 79 74,985 Ilemela 0 2,527 0 0 0 965 684 0 4,176 Total 41,527 442,027 4,918 1,362 4,808 272,816 11,179 978 779,614 District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6 IRRIGATION: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility Tanzania Agriculture Sample Census -2003 Mwanza 197 Appendix II 198 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 199 No of households % No of households % Ukerewe 158 0.5 32,750 99.5 32,909 Magu 873 1.5 55,488 98.5 56,360 Kwimba 398 0.9 45,415 99.1 45,813 Sengerema 2,142 3.3 62,519 96.7 64,661 Geita 2,005 2.1 91,282 97.9 93,286 Missungwi 1,958 5.7 32,174 94.3 34,132 Ilemela 1,926 14.9 10,997 85.1 12,922 Total 9,460 2.8 330,624 97.2 340,085 No of households % No of households % Ukerewe 16,575 50 16,334 50 32,909 Magu 18,224 32 38,136 68 56,360 Kwimba 10,773 24 35,040 76 45,813 Sengerema 22,548 35 42,113 65 64,661 Geita 18,098 19 75,467 81 93,566 Missungwi 10,605 31 23,528 69 34,132 Ilemela 6,437 50 6,486 50 12,922 Total 103,260 30 237,104 70 340,364 No of households % No of households % Ukerewe 2,375 7.2 30,534 92.8 32,909 Magu 2,875 5.1 53,485 94.9 56,360 Kwimba 1,287 2.8 44,526 97.2 45,813 Sengerema 1,667 2.6 62,995 97.4 64,661 Geita 3,284 3.5 89,832 96.5 93,116 Missungwi 407 1.2 33,726 98.8 34,132 Ilemela 1,001 7.7 11,921 92.3 12,922 Total 12,896 3.8 327,019 96.2 339,914 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 200 No of households % No of households % Ukerewe 491 1 32,418 99 32,909 Magu 14,986 27 41,375 73 56,360 Kwimba 1,750 4 44,063 96 45,813 Sengerema 11,457 18 53,205 82 64,661 Geita 21,230 23 71,948 77 93,178 Missungwi 4,775 14 29,357 86 34,132 Ilemela 2,572 20 10,350 80 12,922 Total 57,260 17 282,716 83 339,976 No of households % No of households % Ukerewe 0 0 32,909 100 32,909 Magu 278 0 56,083 100 56,360 Kwimba 0 0 45,813 100 45,813 Sengerema 306 0 64,356 100 64,661 Geita 252 0 93,035 100 93,286 Missungwi 176 1 33,957 99 34,132 Ilemela 43 0 12,879 100 12,922 Total 1,054 0 339,031 100 340,085 No of households % No of households % Ukerewe 3,639 11 29,270 89 32,909 Magu 34,228 61 22,133 39 56,360 Kwimba 12,752 28 33,061 72 45,813 Sengerema 26,873 42 37,788 58 64,661 Geita 32,372 35 60,915 65 93,286 Missungwi 11,577 34 22,556 66 34,132 Ilemela 6,542 51 6,381 49 12,922 Total 127,982 38 212,102 62 340,085 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 201 Number % Number % Number % Number % Ukerewe 158 0.5 0 0.0 0 0.0 32,750 99.5 32,909 Magu 873 1.5 0 0.0 0 0.0 55,488 98.5 56,360 Kwimba 398 0.9 0 0.0 0 0.0 45,415 99.1 45,813 Sengerema 2,142 3.3 0 0.0 0 0.0 62,519 96.7 64,661 Geita 1,869 2.0 136 0.1 0 0.0 91,282 97.9 93,286 Missungwi 1,958 5.7 0 0.0 0 0.0 32,174 94.3 34,132 Ilemela 1,926 14.9 0 0.0 0 0.0 10,997 85.1 12,922 Total 9,324 2.7 136 0.04 0 0.00 330,624 97.2 340,085 Number % Number % Number % Number % Number % Number % Ukerewe 158 0.5 0 0.0 155 0.5 0 0.0 0 0.0 166 0.5 Magu 276 0.5 0 0.0 681 1.2 124 0.2 0 0.0 0 0.0 Kwimba 0 0.0 0 0.0 0 0.0 0 0.0 98 0.2 0 0.0 Sengerema 152 0.2 153 0.2 0 0.0 0 0.0 0 0.0 0 0.0 Geita 681 0.7 0 0.0 319 0.3 0 0.0 0 0.0 0 0.0 Missungwi 0 0.0 246 0.7 75 0.2 0 0.0 0 0.0 0 0.0 Ilemela 59 0.5 0 0.0 336 2.6 0 0.0 59 0.5 0 0.0 Total 1,325 0.4 399 0.1 1,566 0.5 124 0.0 156 0.0 166 0.0 Total Number % Number % Number % Number % Number % Number Ukerewe 0 0.0 13,868 42.1 2,227 6.8 0 0.0 16,334 49.6 32,909 Magu 686 1.2 7,149 12.7 9,308 16.5 0 0.0 38,136 67.7 56,360 Kwimba 0 0.0 5,833 12.7 4,842 10.6 0 0.0 35,040 76.5 45,813 Sengerema 0 0.0 13,857 21.4 8,387 13.0 0 0.0 42,113 65.1 64,661 Geita 0 0.0 9,160 9.8 7,603 8.1 335 0.4 75,467 80.7 93,566 Missungwi 0 0.0 6,498 19.0 3,786 11.1 0 0.0 23,528 68.9 34,132 Ilemela 0 0.0 2,685 20.8 3,299 25.5 0 0.0 6,486 50.2 12,922 Total 686 0.2 59,051 17.3 39,453 11.6 335 0.1 237,104 69.7 340,364 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year cont….. Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Neighbour Other Not applicable District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Large Scale Farm Locally Produced by 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Local Market / Trade Store Local Farmers Neighbour Not applicable Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 202 Number % Number % Number % Number % Number % Ukerewe 0 0.0 0 0.0 1,715 5.2 577 1.8 30,534 92.8 32,826 Magu 666 1.2 111 0.2 1,711 3.0 0 0.0 53,485 94.9 55,973 Kwimba 0 0.0 0 0.0 1,287 2.8 0 0.0 44,526 97.2 45,813 Sengerema 0 0.0 0 0.0 1,230 1.9 436 0.7 62,995 97.4 64,661 Geita 0 0.0 0 0.0 1,363 1.5 1,813 1.9 89,832 96.5 93,007 Missungwi 0 0.0 0 0.0 330 1.0 76 0.2 33,726 98.8 34,132 Ilemela 0 0.0 59 0.5 782 6.1 0 0.0 11,921 92.3 12,762 Total 666 0.2 170 0.0 8,419 2.5 2,902 0.9 327,019 96.2 339,176 Number % Number % Number % Number % Number % Ukerewe 491 1.5 0 0.0 0 0.0 0 0.0 32,418 98.5 32,908.7 Magu 7,261 12.9 139 0.2 139 0.2 124 0.2 41,375 73.4 49,037.0 Kwimba 917 2.0 0 0.0 0 0.0 104 0.2 44,063 96.2 45,083.9 Sengerema 9,291 14.4 309 0.5 0 0.0 0 0.0 53,205 82.3 62,804.6 Geita 7,960 8.5 0 0.0 0 0.0 168 0.2 71,948 77.2 80,076.5 Missungwi 3,147 9.2 0 0.0 0 0.0 0 0.0 29,357 86.0 32,504.2 Ilemela 2,529 19.6 0 0.0 0 0.0 0 0.0 10,350 80.1 12,879.3 Total 31,595 9.3 448 0.1 139 0.0 397 0.1 282,716 83.2 315,294.2 Number % Number % Number % Ukerewe 0 0.0 0 0.0 32,909 100.0 32,908.7 Magu 0 0.0 0 0.0 56,083 99.5 56,082.6 Kwimba 0 0.0 0 0.0 45,813 100.0 45,812.9 Sengerema 151 0.2 155 0.2 64,356 99.5 64,661.4 Geita 252 0.3 0 0.0 93,035 99.7 93,286.5 Missungwi 176 0.5 0 0.0 33,957 99.5 34,132.3 Ilemela 43 0.3 0 0.0 12,879 99.7 12,922.4 Total 622 0.2 155 0.0 339,031 99.7 339,806.9 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year Total District Local Market / Trade Store Development Project District Local Market / Trade Store Neighbour Not applicable Secondary Market Not applicable Total Total 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Neighbour 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Co-operative Crop Buyers Locally Produced by Household Neighbour Not applicable District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 203 Number % Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 0 0.0 3,316 10.1 0 0.0 72 0.2 0 0.0 0 0.0 83 0.3 169 0.5 29,270 88.9 32,909 Magu 1,058 1.9 8,590 15.2 138 0.2 2,083 3.7 10,419 18.5 0 0.0 1,662 2.9 1,055 1.9 22,133 39.3 47,138 Kwimba 0 0.0 2,637 5.8 0 0.0 103 0.2 6,213 13.6 0 0.0 105 0.2 1,463 3.2 33,061 72.2 43,581 Sengerema 1,012 1.6 18,399 28.5 153 0.2 0 0.0 282 0.4 0 0.0 147 0.2 1,830 2.8 37,788 58.4 59,612 Geita 492 0.5 10,690 11.5 0 0.0 167 0.2 10,767 11.5 0 0.0 167 0.2 1,514 1.6 60,915 65.3 84,711 Missungwi 164 0.5 7,221 21.2 258 0.8 76 0.2 506 1.5 347 1.0 84 0.2 160 0.5 22,556 66.1 31,372 Ilemela 0 0.0 5,831 45.1 0 0.0 0 0.0 171 1.3 0 0.0 144 1.1 336 2.6 6,381 49.4 12,864 Total 2,726 0.8 56,683 16.7 549 0.2 2,501 0.7 28,358 8.3 347 0.1 2,393 0.7 6,526 1.9 212,102 62.4 312,185 Number % Number % Number % Number % Number % Ukerewe 0 0 0 0 0 0 83 53 75 47 158 Magu 0 0 385 44 120 14 367 42 0 0 873 Kwimba 0 0 93 23 104 26 103 26 99 25 398 Sengerema 415 19 133 6 860 40 302 14 433 20 2,142 Geita 164 8 136 7 908 45 133 7 664 33 2,005 Missungwi 139 7 787 40 344 18 352 18 337 17 1,958 Ilemela 320 17 430 22 334 17 438 23 405 21 1,926 Total 1,038 11 1,963 21 2,669 28 1,778 19 2,012 21 9,460 Number % Number % Number % Number % Number % Ukerewe 16,157 97 418 3 0 0 0 0 0 0 16,575 Magu 15,539 85 2,425 13 260 1 0 0 0 0 18,224 Kwimba 9,588 89 792 7 92 1 301 3 0 0 10,773 Sengerema 18,741 83 2,979 13 567 3 155 1 106 0 22,548 Geita 15,693 87 1,847 10 392 2 0 0 167 1 18,098 Missungwi 9,459 89 982 9 164 2 0 0 0 0 10,605 Ilemela 4,988 77 1,162 18 174 3 112 2 0 0 6,437 Total 90,165 87 10,605 10 1,649 2 568 1 273 0 103,260 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Total Not applicable District Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Large Scale Farm Locally Produced by Household Neighbour 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number Between 10 and 20 km 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 204 Number % Number % Ukerewe 2,061 86.8 0 0 2,061 Magu 2,606 90.6 0 0.0 2,605.8 Kwimba 1,183 91.9 0 0.0 1,183.1 Sengerema 1,386 83.2 155 9.3 1,541.0 Geita 3,284 100.0 0 0.0 3,284.4 Missungwi 329 81.0 0 0.0 329.3 Ilemela 841 84.0 53 5.3 894.0 Total 11,690 90.7 208 1.6 11,898.2 Number % Number % Number % Number % Number % Ukerewe 252 7 155 4 846 23 2,168 60 218 6 3,639 Magu 15,517 45 9,426 28 5,229 15 3,024 9 1,032 3 34,228 Kwimba 3,726 29 5,938 47 1,648 13 715 6 725 6 12,752 Sengerema 7,571 28 6,137 23 6,127 23 3,051 11 3,987 15 26,873 Geita 12,149 38 8,690 27 4,845 15 2,627 8 4,060 13 32,372 Missungwi 2,596 22 4,836 42 2,229 19 771 7 1,145 10 11,577 Ilemela 876 13 1,460 22 1,348 21 1,433 22 1,425 22 6,542 Total 42,687 33 36,642 29 22,273 17 13,790 11 12,591 10 127,982 Less than 1 km Number % Number % Number % Number % Number % Ukerewe 0 0 0 0 168 34 83 17 240 49 491 Magu 4,803 32 4,825 32 2,609 17 1,586 11 1,162 8 14,986 Kwimba 313 18 717 41 207 12 206 12 308 18 1,750 Sengerema 1,297 11 2,860 25 3,903 34 1,827 16 1,570 14 11,457 Geita 8,023 38 5,688 27 3,959 19 1,463 7 2,097 10 21,230 Missungwi 936 20 1,858 39 1,361 28 441 9 179 4 4,775 Ilemela 382 15 719 28 475 18 532 21 463 18 2,572 Total 15,754 28 16,667 29 12,681 22 6,138 11 6,020 11 57,260 Total Number 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 10 and 20 km Total Number 20 km and Above 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total Number 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 205 Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 7,502 23 22,085 67 418 1 0 0 1,065 3 1,107 3 0 0 574 2 32,750 Magu 18,390 33 32,894 59 494 1 265 0 1,475 3 1,626 3 0 0 345 1 55,488 Kwimba 17,739 39 24,093 53 277 1 0 0 2,580 6 621 1 105 0 0 0 45,415 Sengerema 15,155 24 43,320 69 287 0 303 0 1,355 2 1,950 3 0 0 149 0 62,519 Geita 23,641 26 63,937 70 876 1 0 0 951 1 1,876 2 0 0 0 0 91,282 Missungwi 7,664 24 19,943 62 480 1 142 0 2,389 7 1,467 5 0 0 89 0 32,174 Ilemela 578 5 9,508 86 106 1 57 1 189 2 457 4 0 0 102 1 10,997 Total 90,668 27 215,779 65 2,938 1 767 0 10,004 3 9,104 3 105 0 1,259 0 330,624 Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 7,502 23 22,085 67 418 1 0 0 1,065 3 1,107 3 0 0 574 2 32,750 Magu 18,390 33 32,894 59 494 1 265 0 1,475 3 1,626 3 0 0 345 1 55,488 Kwimba 17,739 39 24,093 53 277 1 0 0 2,580 6 621 1 105 0 0 0 45,415 Sengerema 15,155 24 43,320 69 287 0 303 0 1,355 2 1,950 3 0 0 149 0 62,519 Geita 23,641 26 63,937 70 876 1 0 0 951 1 1,876 2 0 0 0 0 91,282 Missungwi 7,664 24 19,943 62 480 1 142 0 2,389 7 1,467 5 0 0 89 0 32,174 Ilemela 578 5 9,508 86 106 1 57 1 189 2 457 4 0 0 102 1 10,997 Total 90,668 27 215,779 65 2,938 1 767 0 10,004 3 9,104 3 105 0 1,259 0 330,624 Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 4,508 15 3,584 12 14,874 49 2,163 7 1,807 6 2,761 9 167 1 670 2 30,534 Magu 1,751 3 3,902 7 18,389 34 8,197 15 18,321 34 2,435 5 138 0 352 1 53,485 Kwimba 3,531 8 4,696 11 17,091 38 3,407 8 13,745 31 1,449 3 209 0 396 1 44,526 Sengerema 2,936 5 4,325 7 32,364 51 2,626 4 15,480 25 4,671 7 445 1 149 0 62,995 Geita 6,527 7 12,776 14 35,341 39 3,153 4 29,316 33 1,719 2 170 0 830 1 89,832 Missungwi 3,621 11 1,389 4 9,783 29 928 3 15,818 47 1,945 6 0 0 241 1 33,726 Ilemela 1,542 13 1,211 10 6,228 52 368 3 1,861 16 627 5 83 1 0 0 11,921 Total 24,416 7 31,883 10 134,070 41 20,842 6 96,348 29 15,609 5 1,212 0 2,639 1 327,019 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Not Available Price Too High No Money to Buy Other Input is of No Use Locally Produced by Household Not Available Price Too High No Money to Buy Total Input is of No Use Locally Produced by Household Do not Know How to Use Input is of No Use 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Too Much Labour Required Too Much Labour Required Do not Know How to Use Total Locally Produced by Household Other Total Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 206 Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 6,184 19 23,165 71 572 2 0 0 886 3 1,111 3 0 0 499 2 32,418 Magu 2,488 6 31,405 76 675 2 80 0 1,976 5 4,400 11 0 0 349 1 41,375 Kwimba 10,022 23 26,187 59 783 2 312 1 3,948 9 2,811 6 0 0 0 0 44,063 Sengerema 7,271 14 39,891 75 590 1 152 0 3,118 6 2,035 4 0 0 149 0 53,205 Geita 7,528 10 57,462 80 1,414 2 482 1 1,428 2 3,464 5 0 0 170 0 71,948 Missungwi 5,723 19 17,107 58 317 1 0 0 3,859 13 2,270 8 0 0 80 0 29,357 Ilemela 400 4 8,625 83 289 3 43 0 439 4 554 5 0 0 0 0 10,350 Total 39,616 14 203,842 72 4,641 2 1,069 0 15,654 6 16,646 6 0 0 1,248 0 282,716 Number % Number % Number % Number % Number % Number % Number % Ukerewe 5,789 17.6 21,168 64.3 649 2.0 0 0.0 3,853 12 951 3 499 2 32,909 Magu 10,514 18.7 26,454 47.2 1,674 3.0 0 0.0 10,129 18 7,075 13 237 0 56,083 Kwimba 11,282 24.6 21,708 47.4 862 1.9 207 0.5 8,638 19 3,115 7 0 0 45,813 Sengerema 11,510 17.9 38,843 60.4 955 1.5 285 0.4 7,527 12 5,087 8 149 0 64,356 Geita 26,193 28.2 49,827 53.6 2,081 2.2 0 0.0 9,993 11 4,529 5 159 0 93,035 Missungwi 6,039 17.8 20,666 60.9 223 0.7 90 0.3 4,296 13 2,563 8 80 0 33,957 Ilemela 1,098 8.5 9,277 72.0 153 1.2 43 0.3 1,324 10 931 7 0 0 12,879 Total 72,425 21.4 187,944 55.4 6,597 1.9 624 0 45,760 13 24,249 7 1,124 0 339,031 Number % Number % Number % Number % Number % Number % Number % Number % Ukerewe 10,088 34 17,239 59 567 2 0 0 150 1 646 2 0 0 580 2 29,270 Magu 8,123 37 12,833 58 343 2 138 1 0 0 583 3 0 0 113 1 22,133 Kwimba 9,611 29 22,158 67 470 1 102 0 616 2 104 0 0 0 0 0 33,061 Sengerema 7,790 21 28,231 75 0 0 303 1 1,315 3 0 0 0 0 149 0 37,788 Geita 7,281 12 51,859 85 789 1 0 0 284 0 551 1 151 0 0 0 60,915 Missungwi 7,909 35 13,493 60 82 0 61 0 61 0 862 4 88 0 0 0 22,556 Ilemela 518 8 5,437 85 43 1 0 0 101 2 282 4 0 0 0 0 6,381 Total 51,319 24 151,250 71 2,294 1 605 0 2,526 1 3,029 1 238 0 841 0 212,102 Do not Know How to Use 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year Locally Produced by Household Input is of No Use Not Available Price Too High Total District Other No Money to Buy 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available No Money to Buy Too Much Labour Required Other Input is of No Use 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Total Total District Not Available Price Too High Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Other Input is of No Use Locally Produced by Household Too Much Labour Required Do not Know How to Use Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 207 Number % Number % Number % Ukerewe 83 53 75 47 0 0 158 Magu 240 27 633 73 0 0 873 Kwimba 103 26 191 48 104 26 398 Sengerema 886 41 839 39 418 20 2,142 Geita 324 16 1,681 84 0 0 2,005 Missungwi 1,396 71 474 24 0 0 1,870 Ilemela 250 13 1,405 73 271 14 1,926 Total 3,281 35 5,298 56 793 8 9,372 Number % Number % Number % Number % Number % Ukerewe 3,363 20 11,644 70 1,567 9 0 0 0 0 16,575 Magu 5,908 32 11,138 61 1,179 6 0 0 0 0 18,224 Kwimba 4,872 45 5,227 49 674 6 0 0 0 0 10,773 Sengerema 8,442 38 13,214 59 738 3 0 0 0 0 22,393 Geita 8,023 44 8,087 45 1,989 11 0 0 0 0 18,098 Missungwi 6,744 64 3,183 30 677 6 0 0 0 0 10,605 Ilemela 2,211 34 3,957 61 269 4 0 0 0 0 6,437 Total 39,563 38 56,449 55 7,093 7 0 0 0 0 103,105 Number % Number % Number % Number % Ukerewe 250 11 1,808 76 317 13 0 0 2,375 Magu 979 34 1,653 57 243 8 0 0 2,875 Kwimba 0 0 1,188 92 99 8 0 0 1,287 Sengerema 568 34 825 50 126 8 148 9 1,667 Geita 153 5 2,697 82 434 13 0 0 3,284 Missungwi 0 0 407 100 0 0 0 0 407 Ilemela 83 8 635 63 282 28 0 0 1,001 Total 2,033 16 9,214 71 1,501 12 148 1 12,896 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor District Excellent Good Does not Work Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Average Total Poor Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 District Excellent Good Average Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 208 Number % Number % Number % Number % Number % Ukerewe 85 17 405 83 0 0 0 0 0 0 491 Magu 2,630 18 10,566 71 1,666 11 124 1 0 0 14,986 Kwimba 418 24 1,124 64 208 12 0 0 0 0 1,750 Sengerema 2,711 24 7,918 69 827 7 0 0 0 0 11,457 Geita 4,672 22 12,942 61 3,283 15 332 2 0 0 21,230 Missungwi 2,766 58 1,843 39 76 2 0 0 90 2 4,775 Ilemela 402 16 1,877 73 293 11 0 0 0 0 2,572 Total 13,685 24 36,676 64 6,354 11 456 1 90 0 57,260 Number % Number % Ukerewe 0 0 0 0 0 Magu 0 0 139 50 139 Kwimba 0 0 306 100 306 Sengerema 0 0 85 34 85 Geita 176 100 0 0 176 Missungwi 0 0 43 100 43 Ilemela 176 17 573 54 749 Total 176 17 573 54 749 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Ukerewe 223 6 2,753 76 663 18 0 0 3,639 Ukerewe 3,462 11 29,447 89 32,909 Magu 3,087 9 24,700 72 3,767 11 2,674 8 34,228 Magu 13,108 23 43,252 77 56,360 Kwimba 4,303 34 6,894 54 1,242 10 313 2 12,752 Kwimba 5,060 11 40,753 89 45,813 Sengerema 7,361 27 16,863 63 2,380 9 269 1 26,873 Sengerema 17,432 27 47,229 73 64,661 Geita 6,820 21 16,373 51 8,064 25 1,115 3 32,372 Geita 18,238 20 75,048 80 93,286 Missungwi 5,113 44 5,875 51 589 5 0 0 11,577 Missungwi 6,177 18 27,956 82 34,132 Ilemela 1,655 25 4,234 65 653 10 0 0 6,542 Ilemela 4,738 37 8,185 63 12,922 Total 28,562 22 77,691 61 17,358 14 4,372 3 127,982 Total 68,215 20 271,869 80 340,085 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year Total District District Excellent Good Average Does not Work 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Total District Excellent Good 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Total Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year Total District Excellent Good Average Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 209 Number % Number % Number % Number % Ukerewe 24,160 73 8,749 27 32,909 Ukerewe 9,911 30 22,998 70 32,909 Magu 38,697 69 17,663 31 56,360 Magu 11,332 20 45,029 80 56,360 Kwimba 30,373 66 15,440 34 45,813 Kwimba 5,430 12 40,383 88 45,813 Sengerema 46,681 72 17,980 28 64,661 Sengerema 18,677 29 45,984 71 64,661 Geita 41,043 44 52,523 56 93,566 Geita 10,006 11 83,110 89 93,116 Missungwi 17,651 52 16,481 48 34,132 Missungwi 3,302 10 30,830 90 34,132 Ilemela 9,720 75 3,202 25 12,922 Ilemela 1,239 10 11,683 90 12,922 Total 208,324 61 132,039 39 340,364 Total 59,898 18 280,016 82 339,914 Number % Number % Number % Number % Ukerewe 2,815 9 30,094 91 32,909 Ukerewe 949 3 31,959 97 32,909 Magu 29,720 53 26,640 47 56,360 Magu 6,846 12 49,514 88 56,360 Kwimba 8,758 19 37,055 81 45,813 Kwimba 1,108 2 44,705 98 45,813 Sengerema 26,408 41 38,253 59 64,661 Sengerema 7,928 12 56,733 88 64,661 Geita 36,759 39 56,419 61 93,178 Geita 2,306 2 90,981 98 93,286 Missungwi 8,526 25 25,606 75 34,132 Missungwi 1,467 4 32,665 96 34,132 Ilemela 4,055 31 8,867 69 12,922 Ilemela 201 2 12,722 98 12,922 Total 117,042 34 222,934 66 339,976 Total 20,805 6 319,280 94 340,085 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Herbicides Next Year Agricultural Households With NO Plan to use Herbicides Next Year Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use COMPOST ManureNext Year Agricultural Households With NO Plan to use COMPOST Manure Next Year Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 210 Number % Number % Ukerewe 8,673 26 24,236 74 32,909 Magu 42,500 75 13,860 25 56,360 Kwimba 29,782 65 16,031 35 45,813 Sengerema 45,194 70 19,467 30 64,661 Geita 46,654 50 46,632 50 93,286 Missungwi 16,405 48 17,727 52 34,132 Ilemela 9,545 74 3,377 26 12,922 Total 198,754 58 141,331 42 340,085 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Improved Seeds Next Year Agricultural Households With NO Plan to use Improved Seeds Next Year Total Tanzania Agriculture Sample Census -2003 Mwanza 211 Appendix II 212 AGRICULTURE CREDIT Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 213 Number % Number % Ukerewe 0 0 0 0 0 Magu 3,659 71 1,527 29 5,187 Kwimba 920 69 409 31 1,329 Sengerema 761 71 308 29 1,070 Geita 460 100 0 0 460 Missungwi 1,059 86 179 14 1,238 Ilemela 498 70 209 30 707 Total 7,358 74 2,633 26 9,991 Family, Friend and Relative Commercial Bank Saving & Credit Society Religious Organisation / NGO / Project Ukerewe 0 0 0 0 0 Magu 1,275 139 137 2,560 4,110 Kwimba 720 103 0 506 1,329 Sengerema 305 0 310 301 916 Geita 291 0 0 169 460 Missungwi 179 0 0 709 888 Ilemela 494 53 0 107 654 Total 3,262 295 446 4,352 8,356 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year Source of Credit Total Total District Male Female Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 214 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Ukerewe 2,047 5,488 3,497 335 13,038 667 72 83 7,681 32,909 Magu 1,700 14,287 3,509 4,343 12,810 1,169 1,333 61 11,962 51,173 Kwimba 1,241 5,472 6,187 1,051 17,209 614 189 0 12,521 44,484 Sengerema 2,320 7,242 9,008 1,497 24,416 1,283 0 152 17,673 63,592 Geita 2,657 32,809 7,526 1,283 27,736 628 762 0 19,426 92,827 Missungwi 1,459 5,384 5,790 2,086 15,168 80 324 0 2,602 32,894 Ilemela 329 2,253 2,901 386 3,971 664 139 0 1,573 12,215 Total 11,752 72,934 38,419 10,983 114,347 5,106 2,819 296 73,437 330,094 District Labour Seeds Agro-chemicals Tools / Equipment Livestock Other Total Credits Ukerewe 0 0 0 0 0 0 0 Magu 1,904 1,464 536 1,145 539 1,053 6,641 Kwimba 401 101 0 101 0 928 1,530 Sengerema 303 457 155 463 154 0 1,532 Geita 460 169 169 305 0 155 1,258 Missungwi 1,151 0 0 177 264 0 1,592 Ilemela 279 322 220 102 0 0 923 Total 4,498 2,513 1,080 2,292 957 2,136 13,476 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census -2003 Mwanza 215 Appendix II 216 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 217 District Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Tectona Grandis Total Ukerewe 19 82 24 73 55 53 0 306 Magu 297 346 323 0 1,170 0 0 2,136 Kwimba 95 179 12 0 847 28 0 1,161 Sengerema 152 755 4 0 4,117 2,778 20 7,826 Geita 127 251 56 20 26 8 0 488 Missungwi 13 113 20 0 355 32 0 533 Ilemela 217 3,038 . 3 5,448 22 33 8,761 Total 920 4,764 439 96 12,018 2,921 53 21,211 % 4 22 2 0 57 14 0 100 District Terminalia Catapa Terminalia Ivorensis Maesopsis Berchemoides Leucena Spp Syszygium Spp Azadritacht a Spp Jakaranda Spp Trichilia Spp Total Ukerewe 2 5 1,747 0 9 32 0 10 1,803 Magu 8 2 0 255 1 1,848 0 100 2,206 Kwimba 0 0 0 0 0 801 0 0 801 Sengerema 1 0 2,327 127 0 14 10 0 2,478 Geita 0 0 455 0 0 0 0 600 1,055 Missungwi 0 0 3 30 6 102 0 0 141 Ilemela 15 0 142 1 52 65 0 0 260 Total 26 7 4,674 413 80 2,862 10 710 8,756 % 0.3 0.1 53.4 4.7 0.9 32.7 0.1 8.1 100.0 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mwanza Region cont… Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Mwanza Regiont Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 218 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Ukerewe 44 370 70 1,669 1 88 115 2,127 Magu 30 906 30 560 15 3,137 75 4,603 Kwimba 25 788 11 554 12 663 48 2,005 Sengerema 32 1,073 32 4,788 6 4,477 70 10,338 Geita 8 64 21 829 3 670 32 1,563 Missungwi 16 118 14 176 8 393 38 687 Ilemela 26 744 24 664 8 7,881 58 9,289 Total 181 4,063 202 9,240 53 17,309 436 30,612 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Ukerewe 110 7 0 4 2 1 2 126 Magu 67 21 2 47 10 15 1 163 Kwimba 30 11 0 27 10 2 0 80 Sengerema 98 3 2 10 4 2 0 119 Geita 35 2 0 2 1 7 0 47 Missungwi 25 4 0 12 7 2 1 51 Ilemela 60 5 0 24 1 2 1 93 Total 425 53 4 126 35 31 5 679 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Mwanza Region District Main Use 14.2 ON FARM TREE PLANTING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Mwanza Region Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 219 1-9 1-19 20-29 30-39 40-49 60+ Total Ukerewe 829 332 167 0 0 0 1,327 Magu 1,805 3,801 1,797 655 277 138 8,474 Kwimba 4,369 1,140 2,217 1,589 398 105 9,819 Sengerema 1,367 1,375 613 156 0 0 3,511 Geita 0 165 0 0 0 0 165 Missungwi 2,823 3,824 3,199 2,777 247 326 13,197 Ilemela 517 745 268 102 153 102 1,887 Total 11,711 11,382 8,262 5,279 1,076 671 38,379 % 31 30 22 14 3 2 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Ukerewe 8 27 0 79 7 5 2 128 Magu 23 14 6 80 23 14 3 163 Kwimba 9 18 1 37 4 11 0 80 Sengerema 12 6 0 96 5 0 0 119 Geita 1 11 0 23 5 0 7 47 Missungwi 4 12 0 19 11 3 2 51 Ilemela 7 22 0 55 9 1 0 94 Total 64 110 7 389 64 34 14 682 District Second Use 14.4 ON FARM TREE PLANTING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Mwanza Region District Distance to Community Planted Forest (km) 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Mwanza Region Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 220 CROP EXTENSION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 221 Number % Number % Ukerewe 7,379 22 25,529 78 32,909 Magu 22,455 40 33,906 60 56,360 Kwimba 8,327 18 37,486 82 45,813 Sengerema 9,897 15 54,764 85 64,661 Geita 7,110 8 86,177 92 93,286 Missungwi 7,965 23 26,168 77 34,132 Ilemela 8,389 65 4,533 35 12,922 Total 71,522 21 268,562 79 340,085 Number % Number % Number % Number % Number % Number % Ukerewe 799 11 4,586 62 1,995 27 0 0 0 0 7,379 100 Magu 2,381 11 16,052 72 3,399 15 359 2 0 0 22,191 100 Kwimba 1,952 23 5,395 65 980 12 0 0 0 0 8,327 100 Sengerema 1,420 14 7,657 77 694 7 126 1 0 0 9,897 100 Geita 2,504 35 3,030 43 1,576 22 0 0 0 0 7,110 100 Missungwi 3,031 38 3,498 44 1,435 18 0 0 0 0 7,965 100 Ilemela 1,284 15 5,181 62 1,722 21 101 1 101 1 8,389 100 Total 13,371 19 45,399 64 11,801 17 587 1 101 0 71,259 100 Number % Number % Number % Number % Number % Number % Ukerewe 6,887 97 164 2 83 1 0 0 0 0 7,134 100 Magu 16,410 74 5,394 24 138 1 0 0 0 0 22,316 100 Kwimba 8,226 99 0 0 0 0 0 0 0 0 8,327 100 Sengerema 9,026 91 0 0 737 7 135 1 0 0 9,897 100 Geita 6,286 90 169 2 507 7 0 0 0 0 6,963 100 Missungwi 7,707 97 258 3 0 0 0 0 0 0 7,965 100 Ilemela 7,190 86 769 9 226 3 0 0 97 1 8,330 100 Total 61,731 87 6,754 10 1,691 2 135 0 97 0 70,932 100 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Government NGO / Development Project Large Scale Farm Other Not applicable Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Mwanza Region Very Good Good Average Poor No Good Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Mwanza Region Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 222 Government NGO / Developme nt Project Large Scale Farm Other Not applicable Total % of total number of households Ukerewe 6,324 0 0 0 0 6,324 11 Magu 14,258 2,741 138 0 0 17,137 28 Kwimba 7,940 0 0 0 0 7,940 13 Sengerema 8,571 0 584 135 0 9,289 15 Geita 5,494 169 507 0 0 6,171 10 Missungwi 6,871 176 0 0 0 7,047 12 Ilemela 5,517 604 58 0 48 6,228 10 Total 54,975 3,690 1,287 135 48 60,136 100 Government NGO / Developme nt Project Cooperative Large Scale Farm Not applicable Ukerewe 3,482 0 0 0 0 3,482 10 Magu 10,274 1,080 0 138 0 11,492 32 Kwimba 4,205 185 102 0 0 4,493 12 Sengerema 4,477 0 0 0 0 4,477 12 Geita 3,889 169 0 0 0 4,058 11 Missungwi 3,281 935 0 0 0 4,217 12 Ilemela 2,886 667 0 216 140 3,910 11 Total 32494.43897 3037.2235 101.8443534 354.2820282 140.09703 36,128 100 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Ukerewe 4,799 0 0 83 0 4,882 12 Magu 6,383 8,200 254 134 0 14,972 38 Kwimba 5,746 0 0 0 0 5,746 15 Sengerema 5,416 0 0 433 0 5,849 15 Geita 1,806 0 0 0 0 1,806 5 Missungwi 2,303 330 0 0 0 2,634 7 Ilemela 2,765 606 0 58 257 3,686 9 Total 29,219 9,137 254 708 257 39,575 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Use of Agrochemicals Total Number of Households District District Spacing % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Erosion Control Total Number of Households District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 223 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Ukerewe 5,890 164 0 0 0 83 6,137 12,274 11 Magu 11,496 4,582 0 240 0 0 16,317 32,635 29 Kwimba 7,214 86 0 102 0 0 7,402 14,804 13 Sengerema 8,138 0 0 154 135 0 8,427 16,854 15 Geita 4,328 336 168 168 0 0 5,001 10,002 9 Missungwi 6,544 414 0 0 0 0 6,959 13,917 12 Ilemela 5,462 1,163 0 168 0 48 6,841 13,681 12 Total 49,072 6,745 168 832 135 131 57,083 114,166 100 Government NGO / Development Cooperative Large Scale Other Not applicable Total Ukerewe 2,052 0 0 0 0 85 2,137 4,275 10 Magu 2,197 120 120 111 0 126 2,674 5,348 12 Kwimba 4,215 0 0 0 0 0 4,215 8,429 19 Sengerema 3,374 0 0 0 0 0 3,374 6,747 15 Geita 2,146 336 0 493 0 0 2,974 5,949 14 Missungwi 2,467 510 0 0 0 123 3,100 6,199 14 Ilemela 2,698 494 0 58 58 118 3,427 6,854 16 Total 19,149 1,459 120 662 58 453 21,901 43,802 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Ukerewe 6,009 83 0 0 0 0 6,093 10 Magu 15,513 2,471 496 498 0 111 19,088 32 Kwimba 6,731 272 102 0 0 0 7,105 12 Sengerema 7,069 0 0 307 135 304 7,815 13 Geita 4,544 169 168 327 0 170 5,378 9 Missungwi 5,898 1,130 82 0 0 0 7,110 12 Ilemela 5,701 661 0 168 0 242 6,771 11 Total 51,464 4,786 848 1,299 135 827 59,360 100 District Total Number of Households % of total number of households % of total number of households % of total number of households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Total Number of Households Total Number of Households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 224 Government NGO / Development Project Large Scale Farm Not applicable Total % of total number of households Ukerewe 485 0 0 0 485 Magu 2,327 231 235 0 2,793 8 Kwimba 191 93 0 0 284 47 Sengerema 922 0 0 0 922 5 Geita 0 167 0 0 167 15 Missungwi 216 0 0 61 277 3 Ilemela 482 102 58 417 1,059 5 Total 4,622 592 293 479 5,986 18 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Ukerewe 3,137 0 0 0 0 0 3,137 16 Magu 4,158 329 231 244 0 139 5,100 25 Kwimba 3,103 0 0 0 0 201 3,304 16 Sengerema 581 0 0 0 0 0 581 3 Geita 2,119 169 0 158 0 341 2,786 14 Missungwi 1,198 61 0 0 0 0 1,260 6 Ilemela 2,670 807 0 109 58 359 4,004 20 Total 16,966 1,367 231 511 58 1,039 20,171 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Ukerewe 4,379 0 0 0 0 0 4,379 10 Magu 10,123 405 0 124 0 0 10,652 25 Kwimba 6,040 179 0 0 0 0 6,219 15 Sengerema 7,243 0 0 154 135 0 7,532 18 Geita 4,239 0 0 168 0 0 4,408 11 Missungwi 2,963 423 75 0 0 0 3,461 8 Ilemela 4,576 400 48 168 58 58 5,309 13 Total 39,563 1,408 124 614 193 58 41,959 100 District Total % of total number of households % of total number of households Crop Storage 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Dodoma Region 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Mechanisation / LST Irrigation Technology Total District District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 225 Government NGO / Development Project Large Scale Farm Other Not applicable Total Ukerewe 3,223 0 0 0 0 0 3,223 12 Magu 5,935 339 489 3,263 248 0 10,273 38 Kwimba 1,965 0 0 0 0 0 1,965 7 Sengerema 4,504 0 0 152 0 0 4,657 17 Geita 1,324 0 0 167 0 170 1,661 6 Missungwi 1,676 250 0 0 0 0 1,926 7 Ilemela 2,310 400 0 0 58 533 3,301 12 Total 20,937 989 489 3,582 306 703 27,005 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Ukerewe 3,649 0 0 82 0 85 3,816 13 Magu 6,093 273 0 2,544 248 0 9,158 31 Kwimba 599 0 0 0 0 0 599 2 Sengerema 5,404 0 0 152 0 0 5,557 19 Geita 1,300 0 0 335 0 828 2,463 8 Missungwi 1,837 783 82 0 0 0 2,702 9 Ilemela 4,666 268 48 109 58 268 5,419 18 Total 23,550 1,324 130 3,223 306 1,182 29,714 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Ukerewe 2,900 580 0 0 0 3,480 12 Magu 2,982 10,125 0 0 138 13,246 46 Kwimba 597 578 0 0 0 1,175 4 Sengerema 1,882 0 0 135 0 2,017 7 Geita 1,164 0 0 0 0 1,164 4 Missungwi 1,609 1,051 0 0 0 2,659 9 Ilemela 2,721 1,763 116 58 125 4,783 17 Total 13,855 14,097 116 193 263 28,524 100 Agro-forestry District District 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region % of total number of households Total Number of Households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region Total Number of Households % of total number of households % of total number of households Vermin Control District Agro-progressing Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 226 Government NGO / Development Project Not applicable Total % of total number of households Ukerewe 0 83 0 83 2 Magu 742 0 0 742 22 Kwimba 0 0 0 0 0 Sengerema 611 154 0 765 23 Geita 0 0 0 0 0 Missungwi 398 269 0 667 20 Ilemela 84 316 718 1,119 33 Total 1,835 822 718 3,376 100 Government NGO / Development Project Not applicable Total % of total number of households Ukerewe 0 0 0 0 0 Magu 518 0 0 518 31 Kwimba 99 0 0 99 6 Sengerema 0 0 0 0 0 Geita 0 0 0 0 0 Missungwi 177 0 0 177 11 Ilemela 0 155 611 766 47 Total 794 239 611 1,643 100 Received Adopted % Received Adopted % Received Adopted % Ukerewe 6,324 6,082 1.0 3,313 418 0.1 4,882 1,484 0.3 Magu 17,512 13,703 0.8 11,401 7,674 0.7 14,330 11,440 0.8 Kwimba 7,940 5,019 0.6 4,283 986 0.2 5,746 4,346 0.8 Sengerema 9,134 7,606 0.8 4,630 2,541 0.5 5,695 5,085 0.9 Geita 6,024 5,187 0.9 4,206 2,889 0.7 1,806 1,000 0.6 Missungwi 6,965 6,084 0.9 4,053 1,776 0.4 2,462 1,708 0.7 Ilemela 6,235 5,291 0.8 3,716 2,442 0.7 3,429 1,632 0.5 Total 60,133 48,972 0.8 35,602 18,727 0.5 38,351 26,694 0.7 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Mwanza Region District District Bee keeping Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Mwanza Region District Use of Agrochemicals Erosion Control Spacing Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 227 Received Adopted % Received Adopted % Received Adopted % Ukerewe 6,054 4,734 0.8 2,052 419 0.2 5,942 3,710 0.6 Magu 16,321 11,595 0.7 2,820 1,773 0.6 18,939 15,085 0.8 Kwimba 7,402 4,517 0.6 4,113 703 0.2 7,105 4,037 0.6 Sengerema 8,427 6,306 0.7 3,070 558 0.2 8,123 5,261 0.6 Geita 5,001 2,445 0.5 2,974 1,786 0.6 5,378 3,736 0.7 Missungwi 6,959 5,268 0.8 2,898 1,416 0.5 7,189 5,555 0.8 Ilemela 6,841 4,997 0.7 3,272 2,068 0.6 6,697 5,098 0.8 Total 57,004 39,862 0.7 21,200 8,723 0.4 59,373 42,481 0.7 Received Adopted % Received Adopted % Received Adopted % Ukerewe 243 236 1.0 2,888 238 0.1 4,382 3,557 0.8 Magu 2,515 0 0.0 3,764 2,138 0.6 9,891 8,446 0.9 Kwimba 284 99 0.3 3,102 492 0.2 6,210 5,591 0.9 Sengerema 771 0 0.0 430 282 0.7 7,532 7,249 1.0 Geita 167 147 0.9 2,446 1,990 0.8 4,408 4,106 0.9 Missungwi 216 61 0.3 1,335 710 0.5 3,461 3,027 0.9 Ilemela 261 414 1.6 3,360 2,588 0.8 5,250 5,033 1.0 Total 4,456 957 0.2 17,325 8,436 0.5 41,133 37,009 0.9 Received Adopted % Received Adopted % Received Adopted % Ukerewe 3,055 1,051 0.3 3,648 3,319 0.9 3,559 1,397 0.4 Magu 9,879 9,613 1.0 8,184 9,059 1.1 12,730 9,677 0.8 Kwimba 1,965 815 0.4 599 599 1.0 1,175 980 0.8 Sengerema 4,656 4,066 0.9 5,711 5,864 1.0 2,146 1,538 0.7 Geita 992 1,495 1.5 2,123 2,316 1.1 1,480 999 0.7 Missungwi 1,780 1,495 0.8 2,702 1,896 0.7 2,572 1,138 0.4 Ilemela 2,712 2,041 0.8 5,017 4,934 1.0 4,502 3,361 0.7 Total 25,038 20,575 0.8 27,983 27,986 1.0 28,162 19,092 0.7 District District District Organic Fertilizer Use Vermin Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Mwanza Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Mwanza Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Mwanza Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 228 Received Adopted % Received Adopted % Ukerewe 251 0 0 169 0 0 Magu 0 0 0 0 0 0 Kwimba 0 0 0 99 99 0 Sengerema 765 154 0 0 0 0 Geita 0 0 0 0 0 0 Missungwi 358 179 50 90 90 100 Ilemela 400 128 32 96 0 0 Total 1,775 461 26 453 188 41 Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Mwanza Region District Beekeeping Tanzania Agriculture Sample Census -2003 Mwanza 229 Appendix II 230 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 231 Number % Number % Ukerewe 0 0 32,909 100 32,909 Magu 23,088 41 33,272 59 56,360 Kwimba 31,837 69 13,976 31 45,813 Sengerema 5,899 9 58,763 91 64,661 Geita 16,044 17 77,243 83 93,286 Missungwi 16,838 49 17,294 51 34,132 Ilemela 161 1 12,761 99 12,922 Total 93,867 28 246,218 72 340,085 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Ukerewe 0 0 0 0 0 0 Magu 68,985 141,016 69,708 3,351 13,320 1,782 Kwimba 21,332 28,873 13,111 6,225 6,820 90 Sengerema 47,898 75,944 32,192 3,915 2,648 716 Geita 52,319 89,023 34,030 1,848 1,962 1,165 Missungwi 16,838 645 208 0 0 0 Total 207,373 335,501 149,249 15,339 24,749 3,754 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Ukerewe 0 0 0 0 0 0 0 0 0 Magu 7,378 0 0 0 0 0 7,378 0 0 Kwimba 953 105 21 1,662 105 118 2,615 209 140 Sengerema 5,570 5,038 0 0 0 0 5,570 5,038 0 Geita 6,406 2,044 0 0 0 0 6,406 2,044 0 Missungwi 0 0 0 0 0 0 0 0 0 Ilemela 0 0 0 0 0 0 0 0 0 Total 20,307 7,186 21 1,662 105 118 21,969 7,291 140 Number % Number % Number % Ukerewe 16,139 16 16,437 7 32,575 10 Magu 18,005 18 38,221 16 56,226 17 Kwimba 9,907 10 35,709 15 45,616 13 Sengerema 22,517 23 42,145 18 64,661 19 Geita 15,764 16 76,297 32 92,061 27 Missungwi 9,881 10 24,252 10 34,132 10 Ilemela 6,183 6 6,642 3 12,825 4 Total 98,394 100 239,702 100 338,096 100 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Mwanza Region 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mwanza Region cont… ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Mwanza Region District Oxen Bulls Type of Craft Households Using Draft Animals Household Not Using Draft Animals Total household s 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Mwanza Cows Donkeys District Type of Craft Total District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 232 Area (Ha) % Area (Ha) % Area (Ha) % Ukerewe 10,216 12 1,396 32 11,612 13 Magu 19,977 23 930 21 20,907 23 Kwimba 9,232 10 114 3 9,346 10 Sengerema 19,886 22 484 11 20,370 22 Geita 16,487 19 996 23 17,483 19 Missungwi 9,565 11 315 7 9,879 11 Ilemela 3,059 3 159 4 3,219 3 Total 88,421 100 4,393 100 92,815 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Mwanza Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census -2003 Mwanza 233 Appendix II 234 CATTLE PRODUCTION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 235 Number % Number % Ukerewe 17,422 53 15,487 47 32,909 17,422 Magu 18,008 32 38,353 68 56,360 18,008 Kwimba 17,025 37 28,788 63 45,813 17,025 Sengerema 23,676 37 40,985 63 64,661 23,676 Geita 25,008 27 68,278 73 93,286 25,008 Missungwi 13,370 39 20,763 61 34,132 13,370 Ilemela 3,553 27 9,369 73 12,922 3,553 Total 118,062 35 222,023 65 340,085 118,062 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Ukerewe 17,422 58,301 100 0 0 0.0 0 0 0.00 17,422 58,301 3.4 Magu 18,008 413,906 99 0 0 0.0 809 2,578 0.01 18,008 416,484 24.2 Kwimba 16,932 249,088 99 0 0 0.0 598 2,460 0.01 17,025 251,548 14.6 Sengerema 23,676 305,630 100 0 0 0.0 153 306 0.00 23,676 305,936 17.8 Geita 25,008 407,829 100 0 0 0.0 0 0 0.00 25,008 407,829 23.7 Missungwi 13,155 252,836 99 0 0 0.0 553 1,944 0.01 13,370 254,780 14.8 Ilemela 3,412 22,719 97.5 0 0 0.0 141 594 0.03 3,553 23,313 1.4 Total 117,613 1,710,309 99.5 0 0 0.0 2,254 7,882 0.005 118,062 1,718,190 100.0 Number % Number % 1-5 45,405 38 133,994 8 3 6-10 26,123 22 205,475 12 8 11-15 14,145 12 183,426 11 13 16-20 9,913 8 176,675 10 18 21-30 8,899 8 225,940 13 25 31-40 4,726 4 164,651 10 35 41-50 3,159 3 144,559 8 46 51-60 2,202 2 123,033 7 56 61-100 2,622 2 206,414 12 79 101-150 416 0 50,524 3 121 151+ 451 0 103,500 6 229 Total 118,062 100 1,718,190 100 15 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Mwanza Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture households Total livestock keeping households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 236 Number % Number % Number % Number % Bulls 192,575 100 0 0 578 0 193,153 11 Cows 575,324 99 0 0 3,774 1 579,098 34 Steers 290,586 100 0 0 819 0 291,405 17 Heifers 307,768 100 0 0 1,523 0 309,291 18 Male Calves 167,020 100 0 0 474 0 167,494 10 Female Calves 177,037 100 0 0 713 0 177,750 10 Total 1,710,309 100 0 0 7,882 0 1,718,190 100 Bulls Cows Steers Heifers Male Calves Female Calves Total Ukerewe 9,294 22,838 75 12,540 6,431 7,122 58,301 Magu 38,203 133,528 88,754 71,123 39,436 42,863 413,906 Kwimba 27,666 75,476 62,213 40,298 21,965 21,470 249,088 Sengerema 40,228 106,188 27,960 55,847 36,607 38,801 305,630 Geita 49,012 147,700 60,716 74,389 36,906 39,105 407,829 Missungwi 25,555 80,221 50,693 48,814 22,854 24,699 252,836 Ilemela 2,618 9,373 174 4,757 2,821 2,977 22,719 Total 192,575 575,324 290,586 307,768 167,020 177,037 1,710,309 Total 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Category of Cattle Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 237 Bulls Cows Steers Heifers Male Calves Female Calves Total Ukerewe 0 0 0 0 0 0 0 Magu 0 0 0 0 0 0 0 Kwimba 0 0 0 0 0 0 0 Sengerema 0 0 0 0 0 0 0 Geita 0 0 0 0 0 0 0 Missungwi 0 0 0 0 0 0 0 Ilemela 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 Bulls Cows Steers Heifers Male Calves Female Calves Total Ukerewe 9,294 22,838 75 12,540 6,431 7,122 58,301 Magu 38,471 134,200 89,572 71,941 39,436 42,863 416,484 Kwimba 27,758 77,750 62,213 40,298 22,058 21,470 251,548 Sengerema 40,228 106,188 27,960 55,847 36,607 39,106 305,936 Geita 49,012 147,700 60,716 74,389 36,906 39,105 407,829 Missungwi 25,694 80,857 50,693 49,237 23,192 25,107 254,780 Ilemela 2,696 9,564 174 5,038 2,864 2,977 23,313 Total 193,153 579,098 291,405 309,291 167,494 177,750 1,718,190 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 238 GOAT PRODUCTION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 239 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Ukerewe 16,280 59,472 100 0 0 0 0 0 0 16,280 59,472 7 Magu 15,281 146,289 100 124 619 4 0 0 0 15,281 146,908 18 Kwimba 13,699 107,509 100 0 0 0 0 0 0 13,699 107,509 13 Sengerema 26,813 168,935 100 106 106 0 0 0 0 26,813 169,042 20 Geita 35,254 228,731 98 432 3,069 9 166 665 0.3 35,254 232,464 28 Missungwi 12,867 95,249 100 0 0 0 0 0 0 12,867 95,249 11 Ilemela 4,056 19,354 100 0 0 0 0 0 0 4,056 19,354 2 Total 124,250 825,538 99 662 3,794 3 166 665 0.0 124,250 829,997 100 Number % Number % 1-4 57,552 46.3 151,031 18 3 5-9 40,896 32.9 269,263 32 7 10-14 14,906 12.0 167,465 20 11 15-19 5,386 4.3 86,328 10 16 20-24 2,302 1.9 47,776 6 21 25-29 1,380 1.1 35,148 4 25 30-39 1,073 0.9 35,022 4 33 40+ 755 0.6 37,965 5 50 Total 124,250 100.0 829,997 100 7 19.1 GOAT PRODUCTION: Number of Goats by Type and District as on 1st October, 2003 Total Goat District 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Herd Size Goat Rearing Households Head of Goats Average Number Per Household Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 240 Number % Number % Number % Number % Billy Goat 148,167 99 1,637 1.1 0 0.0 149,804 18.0 Castrated Goat 33,146 100 0 0.0 0 0.0 33,146 4.0 She Goat 438,038 100 102 0.0 333 0.1 438,472 52.8 Male Kid 101,825 98 1,578 1.5 333 0.3 103,735 12.5 She Kid 104,362 100 478 0.5 0 0.0 104,840 12.6 Total 825,538 99 3,794 0.5 665 0.1 829,997 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Ukerewe 12,607 1,128 34,382 5,684 5,670 59,472 Magu 25,609 7,591 74,301 18,698 20,089 146,289 Kwimba 19,119 9,102 50,949 13,897 14,442 107,509 Sengerema 30,726 3,909 88,503 23,254 22,543 168,935 Geita 40,258 6,198 127,754 26,694 27,827 228,731 Missungwi 16,879 4,476 51,822 11,018 11,054 95,249 Ilemela 2,969 741 10,327 2,579 2,738 19,354 Total 148,167 33,146 438,038 101,825 104,362 825,538 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Ukerewe 12,607 1,128 34,382 5,684 5,670 59,472 Magu 25,609 7,591 74,301 18,698 20,089 146,289 Kwimba 19,119 9,102 50,949 13,897 14,442 107,509 Sengerema 30,726 3,909 88,503 23,254 22,543 168,935 Geita 40,258 6,198 127,754 26,694 27,827 228,731 Missungwi 16,879 4,476 51,822 11,018 11,054 95,249 Ilemela 2,969 741 10,327 2,579 2,738 19,354 Total 148,167 33,146 438,038 101,825 104,362 825,538 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats District Number of Indigenous Goats 19.3 GOAT PRODUCTION:Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Total Category of Goats 19.4 GOAT PRODUCTION:Number of Indigenous Goat by Category and District as on 1st October, 2003 Improved Meat Goats Indigenous Goats Improved Dairy Goats Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 241 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Ukerewe 0 0 0 0 0 0 Magu 0 0 0 0 0 0 Kwimba 0 0 0 0 0 0 Sengerema 0 0 0 0 0 0 Geita 0 0 333 333 . 665 Missungwi 0 0 0 0 0 0 Ilemela 0 0 0 0 0 0 Total 0 0 333 333 0 665 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Ukerewe 12,607 1,128 34,382 5,684 5,670 59,472 Magu 25,609 7,591 74,301 18,945 20,460 146,908 Kwimba 19,119 9,102 50,949 13,897 14,442 107,509 Sengerema 30,726 3,909 88,503 23,254 22,649 169,042 Geita 41,895 6,198 128,188 28,356 27,827 232,464 Missungwi 16,879 4,476 51,822 11,018 11,054 95,249 Ilemela 2,969 741 10,327 2,579 2,738 19,354 Total 149,804 33,146 438,472 103,735 104,840 829,997 District Total Goat 19.6 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 GOAT PRODUCTION: Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 242 SHEEP PRODUCTION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 243 Number % Number % Number % Ram 25,668 100.0 0 0.0 25,668 21.0 Castrated Sheep 11,591 100.0 0 0.0 11,591 9.5 She Sheep 59,256 100.0 0 0.0 59,256 48.6 Male Lamb 11,764 99.5 58 0.5 11,822 9.7 She Lamb 13,640 100.0 0 0.0 13,640 11.2 Total 121,920 100.0 58 0.0 121,978 100.0 Number % Number % Ukerewe 83 0 32,826 100 32,909 83 Magu 4,366 8 51,994 92 56,360 4,366 Kwimba 6,356 14 39,457 86 45,813 6,356 Sengerema 2,781 4 61,880 96 64,661 2,781 Geita 4,940 5 88,346 95 93,286 4,940 Missungwi 5,411 16 28,722 84 34,132 5,411 Ilemela 497 4 12,426 96 12,922 497 Total 24,433 7 315,651 93 340,085 24,433 Number % Number % Number % Ukerewe 166 100 0 0 166 0.1 Magu 27,299 100 0 0 27,299 22.4 Kwimba 39,364 100 0 0 39,364 32.3 Sengerema 9,801 100 0 0 9,801 8.0 Geita 15,090 100 0 0 15,090 12.4 Missungwi 28,634 100 0 0 28,634 23.5 Ilemela 1,566 96 58 4 1,624 1.3 Total 121,920 100 58 0 121,978 100 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 14,502 60 35,087 29 2.4 5-9 7,362 30 48,010 39 6.5 10-14 1,611 7 17,801 15 11.1 15-19 381 2 6,386 5 16.8 20-24 120 0 2,636 2 22.0 25-29 0 0 0 0 0.0 30-39 0 0 0 0 0.0 40+ 227 1 12,058 10 53.2 Total 24,201 100 121,978 100 5.0 20.1 SHEEP PRODUCTION: Total Number of Sheep By Breed and on 1st October 2003 20.4 SHEEP PRODUCTION: Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 SHEEP PRODUCTION: Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Sheep keeping Households Breed Number of Indigenous District 20.3 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 244 Number of Households Average Number of Households Average Number of Households Average Ukerewe 32,909 0.5 32,909 0.00 32,909 0.0 Magu 56,360 48.4 56,360 0.00 56,360 0.5 Kwimba 45,813 85.9 45,813 0.00 45,813 0.9 Sengerema 64,661 15.2 64,661 0.00 64,661 0.2 Geita 93,286 16.2 93,286 0.00 93,286 0.2 Missungwi 34,132 83.9 34,132 0.00 34,132 0.8 Ilemela 12,922 12.1 12,922 0.45 12,922 0.1 Total 340,085 35.8 340,085 0.02 340,085 0.4 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Ukerewe 0 0 0 0 0 0 Magu 3,014 1,751 2,106 122 433 7,427 Kwimba 2,544 103 5,817 103 728 9,295 Sengerema 403 0 0 0 459 862 Geita 490 . 1,051 166 1,195 2,902 Missungwi 3,056 4,626 2,078 242 4,502 14,505 Ilemela 59 . 232 . . 291 Total 9,566 6,480 11,285 633 7,316 35,281 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Ukerewe 0 0 0 0 0 0 Magu 0 0 0 0 0 0 Kwimba 0 0 0 0 0 0 Sengerema 0 0 0 0 0 0 Geita 0 0 0 0 0 0 Missungwi 0 0 0 0 0 0 Ilemela 0 0 0 58 0 58 Total 0 0 0 58 0 58 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Ukerewe 0 0 166 0 0 166 Magu 5,461 3,934 11,364 3,460 3,079 27,299 Kwimba 8,119 7,105 16,342 3,894 3,905 39,364 Sengerema 3,231 153 4,738 612 1,067 9,801 Geita 2,906 139 9,162 637 2,247 15,090 Missungwi 5,779 203 16,456 3,004 3,192 28,634 Ilemela 173 57 1,029 215 150 1,624 Total 25,668 11,591 59,256 11,822 13,640 121,978 20.6 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 SHEEP PRODUCTION: Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 SHEEP PRODUCTION: Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 SHEEP PRODUCTION: Average Number of Sheep by Type of Sheep and District on 1st October 2003, Mwanza Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census -2003 Mwanza 245 Appendix II 246 PIG PRODUCTION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 247 Number % Number % 1-4 0 0 0 0 0 5-9 76 100 610 100 8 10-14 0 0 0 0 0 Total 76 100 610 100 8 District Number of Household Number of Pig Average Number Per Household Ukerewe 32,909 0 0.000 Magu 56,360 139 0.002 Kwimba 45,813 0 0.000 Sengerema 64,661 0 0.000 Geita 93,286 310 0.003 Missungwi 34,132 161 0.005 Ilemela 12,922 0 0.000 Total 340,085 610 0.002 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Ukerewe 0 0 0 0 0 0 Magu 0 0 0 0 0 0 Kwimba 0 0 0 0 0 0 Sengerema 0 0 0 0 0 0 Geita 0 0 0 0 0 0 Missungwi 0 229 76 76 229 610 Ilemela 0 0 0 0 0 0 Total 0 229 76 76 229 610 21.2 PIG PRODUCTION: Number of Households and Pigs by District on 1st October 2003 21.3 PIG PRODUCTION: Number of Pigs by Type and District on 1st October, 2003 21.1 PIG PRODUCTION: Number of Households and Pigs by Herd Size on 1st October Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 248 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 249 Number of Households % Number of Households % Ukerewe 6,476 35 11,929 65 18,405 Magu 11,390 55 9,366 45 20,755 Kwimba 6,094 31 13,363 69 19,457 Sengerema 15,749 58 11,257 42 27,007 Geita 14,825 46 17,355 54 32,179 Missungwi 8,241 52 7,461 48 15,701 Ilemela 2,443 55 1,987 45 4,430 Total 65,218 47 72,717 53 137,935 Number of Households % Number of Households % Number of Households % Number of Households % Ukerewe 2,260 9 4,624 9 0 0 0 0 Magu 4,202 16 9,225 18 2,705 49 2,209 30 Kwimba 1,396 5 5,220 10 707 13 1,198 16 Sengerema 7,870 30 12,950 25 148 3 432 6 Geita 4,676 18 11,843 23 164 3 2,202 30 Missungwi 4,123 16 6,655 13 1,667 30 254 3 Ilemela 1,399 5 1,897 4 175 3 28 0 Total 25,927 100 52,413 100 5,566 100 6,323 100 Number of Households % Number of Households % Ukerewe 13,014 77 3,992 23 17,006 Magu 15,670 74 5,366 26 21,036 Kwimba 11,263 60 7,472 40 18,736 Sengerema 19,831 81 4,656 19 24,488 Geita 18,718 60 12,241 40 30,960 Missungwi 12,589 81 3,030 19 15,619 Ilemela 2,590 63 1,497 37 4,087 Total 93,676 71 38,255 29 131,931 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Ukerewe 5,818 45 4,909 38 77 1 72 1 2,138 16 13,014 Magu 2,605 17 11,373 73 892 6 262 2 538 3 15,670 Kwimba 1,453 13 8,814 78 197 2 193 2 606 5 11,263 Sengerema 3,670 19 13,624 69 444 2 703 4 1,390 7 19,831 Geita 2,055 11 15,628 83 0 0 383 2 652 3 18,718 Missungwi 3,191 25 8,632 69 176 1 261 2 329 3 12,589 Ilemela 1,174 45 707 27 339 13 26 1 344 13 2,590 Total 19,968 21 63,686 68 2,125 2 1,900 2 5,997 6 93,676 Dipping Smearing Other 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year Method of Tick Control Total District None Spraying District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 250 Number of Households % Number of Households % Ukerewe 812 5 16,102 95 16,914 Magu 399 2 20,238 98 20,637 Kwimba 413 2 18,736 98 19,149 Sengerema 296 1 26,713 99 27,009 Geita 890 3 30,396 97 31,287 Missungwi 712 5 14,362 95 15,074 Ilemela 0 0 4,376 100 4,376 Total 3,523 3 130,922 97 134,445 Number of Households % Number of Households % Number of Households % Number of Households % Ukerewe 497 61 315 39 0 0 0 0 912 Magu 0 0 399 100 0 0 0 0 499 Kwimba 0 0 413 100 0 0 0 0 513 Sengerema 296 100 0 0 0 0 0 0 396 Geita 0 0 890 100 0 0 0 0 990 Missungwi 626 88 86 12 0 0 0 0 812 Ilemela 0 0 0 0 0 0 0 0 0 Total 1,419 249 2,103 351 0 0 0 0 4,123 Trapping Method of Tsetse Flies Control 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year Total District None Spray Dipping District Tsetse Flies Problems No Tsetse Flies Problems 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District Total Tanzania Agriculture Sample Census -2003 Mwanza 251 Appendix II 252 OTHER LIVESTOCK Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 253 Number % Type Number Indigenous 2,580,891 98.5 Ducks 152,904 Layer 29,446 1.1 Turkeys 9,786 Broiler 10,481 0.4 Donkeys 9,038 Total 2,620,818 100.0 171,728 Indigenous Chicken Layer Broiler Ducks Turkeys Donkeys Other Ukerewe 195,212 4,010 0 199,222 Ukerewe 54,204 232 0 0 Magu 339,669 2,912 0 342,581 Magu 10,683 4,972 0 0 Kwimba 399,645 0 0 399,645 Kwimba 2,465 0 6,271 0 Sengerema 565,343 2,945 9,182 577,470 Sengerema 49,784 4,354 0 1,461 Geita 805,676 0 1,299 806,975 Geita 25,237 0 2,415 1,299 Missungwi 230,751 18,885 0 249,636 Missungwi 5,248 229 353 0 Ilemela 44,595 695 0 45,290 Ilemela 5,283 0 0 0 Total 2,580,891 29,446 10,481 2,620,818 Total 152,904 9,786 9,038 2,760 Type of Livestock/Poultry 1995 1999 2003 Number % Cattle 2,450,396 2,163,997 1,718,190 1 - 4 60,907 25 167,268 3 Improved Cattle 0 1,700 7,882 5 - 9 72,432 30 476,437 7 Goats 764,260 863,640 829,997 10 - 19 70,807 30 897,803 13 Sheep 199,317 116,565 121,978 20 - 29 21,625 9 476,439 22 Pigs 0 22,486 610 30 - 39 8,389 4 272,062 32 Indigenous Chicken 2,623,825 2,873,622 2,620,818 40 - 49 2,667 1 115,708 43 Layers 0 92,228 29,446 50 - 99 2,185 1 133,911 61 Broilers 0 0 0 100+ 528 0 81,189 154 Total Chickens 2,623,825 2,965,850 2,650,264 Total 239,539 100 2,620,818 11 Chicken Type Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 District Type of Livestock 23c OTHER LIVESTOCK:Head Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e LIVESTOCK/POULTRY POPULATION TREND Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 254 FISH FARMING Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 255 Number % Number % Ukerewe 0 0.0 32,909 100.0 32,909 Magu 138 0.2 56,222 99.8 56,360 Kwimba 99 0.2 45,714 99.8 45,813 Sengerema 0 0.0 64,661 100.0 64,661 Geita 0 0.0 93,286 100.0 93,286 Missungwi 90 0.3 34,043 99.7 34,132 Ilemela 0 0.0 12,922 100.0 12,922 Total 326 0.1 339,758 99.9 340,085 Dug out Pond Total Kwimba 99 99 Total 99 99 NGOs / Project Number Kwimba 99 99 Total 99 99 Did not Sell Number Kwimba 99 99 Total 99 99 District Number of Tilapia Number of Carp Number of Others Kwimba 1,972 0 2,958 Total 1,972 0 2,958 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year District Fish Farming System 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year Total Total District Source of Fingerling 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 256 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 257 Number % Number % Ukerewe 4,854 14.8 28,054 85.2 32,909 17,422.0 28 Magu 9,476 16.8 46,884 83.2 56,360 18,008.0 53 Kwimba 3,451 7.5 42,362 92.5 45,813 17,025.0 20 Sengerema 5,960 9.2 58,701 90.8 64,661 23,676.0 25 Geita 2,359 2.5 90,927 97.5 93,286 25,008.0 9 Missungwi 5,412 15.9 28,720 84.1 34,132 13,370.0 40 Ilemela 2,748 21.3 10,174 78.7 12,922 3,553.0 77 Total 34,262 10.1 305,823 89.9 340,085 118,062.0 29 Number % Number % Number % Number % Number % Number % Ukerewe 4,854 20 4,769 20 4,769 20 4,769 20 4,769 20 23,930 100 Magu 9,476 20 9,476 20 9,476 20 9,339 20 9,339 20 47,107 100 Kwimba 3,451 20 3,354 20 3,354 20 3,354 20 3,354 20 16,866 100 Sengerema 5,960 20 5,960 20 5,960 20 5,960 20 5,960 20 29,801 100 Geita 2,359 22 2,108 20 2,108 20 2,108 20 2,108 20 10,790 100 Missungwi 5,412 20 5,412 20 5,412 20 5,412 20 5,412 20 27,062 100 Ilemela 2,748 20 2,748 20 2,748 20 2,748 20 2,748 20 13,741 100 Total 34,262 20.2 33,827 20.0 33,827 20.0 33,690 19.9 33,690 19.9 169,296 100 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Large Scale Farmer District Received Livestock Advice Did Not Receive Livestock Advice Total Total Total Number of households raising livestock % receiving advice out of total Source of extension advice Other 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 258 Government NGO / Development Project Total Government NGO / Developme nt Project Other Total Ukerewe 1,313 0 1,313 17,422 7.5 Ukerewe 2,921 0 0 2,921 17,422 16.8 Magu 2,829 0 2,829 18,008 15.7 Magu 5,322 0 111 5,433 18,008 30.2 Kwimba 697 0 697 17,025 4.1 Kwimba 1,602 0 0 1,602 17,025 9.4 Sengerema 2,837 0 2,837 23,676 12.0 Sengerema 4,184 0 0 4,184 23,676 17.7 Geita 419 0 419 25,008 1.7 Geita 837 0 0 837 25,008 3.3 Missungwi 1,652 179 1,832 13,370 13.7 Missungwi 3,138 151 0 3,289 13,370 24.6 Ilemela 1,345 0 1,345 3,553 37.9 Ilemela 1,459 43 0 1,503 3,553 42.3 Total 11,091 179 11,270 118,062 9.5 Total 19,463 195 111 19,768 118,062 16.7 % 98.4 1.6 100.0 % 98.5 1.0 0.6 100.0 Government NGO / Development Project Other Total Government NGO / Developme nt Project Total Ukerewe 1,916 0 0 0 17,422 0.0 Ukerewe 2,001 0 2,001 17,422 11.5 Magu 2,444 0 124 0 18,008 0.0 Magu 2,702 0 2,702 18,008 15.0 Kwimba 818 0 0 0 17,025 0.0 Kwimba 818 0 818 17,025 4.8 Sengerema 2,834 0 0 0 23,676 0.0 Sengerema 2,962 0 2,962 23,676 12.5 Geita 166 0 0 0 25,008 0.0 Geita 1,531 82 1,613 25,008 6.5 Missungwi 1,175 76 0 76 13,370 0.6 Missungwi 674 43 717 13,370 5.4 Ilemela 554 0 0 0 3,553 0.0 Ilemela 10,688 125 10,813 3,553 304.3 Total 9,908 76 124 76 118,062 0.1 Total 21,377 250 21,627 118,062 18.3 % 8.4 0.1 0.1 0.1 % 18.1 0.2 18.3 Total Number of households raising livestock % receiving advice out of total Source of Advice on Housing Total Number of households raising livestock % receiving advice out of total 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year Source of Advice on Feeds and Proper Feeding District Total Number of households raising livestock % receiving advice out of total 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District Source of Advice on Proper Milking District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 259 Government NGO / Development Project Other Total Ukerewe 4,028 0 0 4,028 17,422 23 Magu 7,996 0 0 7,996 18,008 44 Kwimba 2,935 0 0 2,935 17,025 17 Sengerema 4,950 0 135 5,085 23,676 21 Geita 1,167 0 0 1,167 25,008 5 Missungwi 4,238 166 87 4,491 13,370 34 Ilemela 1,754 69 0 1,823 3,553 51 Total 27,068 235 222 27,525 118,062 23 % 22.9 0.2 0.2 23.3 Government NGO / Development Project Large Scale Farmer Total Ukerewe 501 0 0 501 17,422 2.9 Magu 3,854 138 226 4,218 18,008 23.4 Kwimba 808 0 0 808 17,025 4.7 Sengerema 2,231 0 0 2,231 23,676 9.4 Geita 335 0 0 335 25,008 1.3 Missungwi 2,317 0 90 2,407 13,370 18.0 Ilemela 490 0 51 541 3,553 15.2 Total 10,536 138 366 11,040 118,062 9.4 % 95.4 1.3 3.3 100.0 Total Number of households raising livestock % receiving advice out of total % receiving advice out of total 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control District Source of Advice on Herd/Flock Size Total Number of households raising livestock Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 260 Government NGO / Development Project Large Scale Farmer not applicable Ukerewe 253 0 0 0 253 17,422 1.5 Magu 2,791 138 624 0 3,553 18,008 19.7 Kwimba 210 0 0 0 210 17,025 1.2 Sengerema 2,405 0 0 0 2,405 23,676 10.2 Geita 335 0 0 0 335 25,008 1.3 Missungwi 887 82 0 0 969 13,370 7.2 Ilemela 734 78 0 0 812 3,553 22.9 Total 7,614 298 624 0 8,537 118,062 7.2 % 89.2 3.5 7.3 0.0 100.0 Government NGO / Development Project o-operativ Total Ukerewe 585 0 0 585 17,422 3 Magu 3,368 402 258 4,029 18,008 22 Kwimba 805 93 0 898 17,025 5 Sengerema 2,051 0 0 2,051 23,676 9 Geita 587 0 0 587 25,008 2 Missungwi 2,165 90 82 2,336 13,370 17 Ilemela 496 35 0 531 3,553 15 Total 10,057 620 340 11,016 118,062 9 % 91.3 5.6 3.1 100.0 Total Number of households raising livestock Total Number of households raising livestock District 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Source of Advice on Pasture Establishment and Selection Total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Source of Advice on Group Formation and Strenghthening Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 261 Government NGO / Development Project Other Total Ukerewe 1,088 0 0 1,088 17,422 6.2 Magu 4,562 138 111 4,811 18,008 26.7 Kwimba 2,235 0 0 2,235 17,025 13.1 Sengerema 4,664 0 135 4,799 23,676 20.3 Geita 906 0 0 906 25,008 3.6 Missungwi 2,349 269 0 2,618 13,370 19.6 Ilemela 1,240 58 0 1,298 3,553 36.5 Total 17,043 465 246 17,754 118,062 15.0 % 96.0 2.6 1.4 100.0 Government NGO / Development Project Large Scale Farmer Total Ukerewe 1,332 0 0 1,332 17,422 8 Magu 2,574 138 292 3,004 18,008 17 Kwimba 1,024 0 0 1,024 17,025 6 Sengerema 3,142 0 0 3,142 23,676 13 Geita 1,098 0 0 1,098 25,008 4 Missungwi 1,450 242 0 1,692 13,370 13 Ilemela 524 0 0 524 3,553 15 Total 11,144 380 292 11,816 118,062 10 % 94.3 3.2 2.5 100.0 % receiving advice out of total % receiving advice out of total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice on Improved Bulls Total Number of households raising livestock Total Number of households raising livestock District Source of Advice on Calf Rearing Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 262 Number % Number % Number % Number % Number % Ukerewe 684 15 2,836 61 1,163 25 0 0 0 0 4,684 Magu 3,584 23 9,307 59 933 6 1,350 9 564 4 15,737 Kwimba 1,232 31 2,508 64 207 5 0 0 0 0 3,946 Sengerema 3,213 43 2,960 40 779 10 0 0 512 7 7,464 Geita 1,022 15 771 12 735 11 0 0 4,087 62 6,615 Missungwi 2,384 32 2,867 39 1,199 16 0 0 948 13 7,399 Ilemela 144 5 1,791 57 675 21 247 8 307 10 3,163 Total 12,263 25 23,039 47 5,690 12 1,597 3 6,417 13 49,007 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census -2003 Mwanza 263 Appendix II 264 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 265 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Ukerewe 17.9 1.1 0.9 0.8 18.3 4.1 70.0 5.8 11.8 21.5 22.7 Magu 12.5 3.1 3.0 2.0 25.5 7.3 79.0 5.0 19.3 30.4 14.5 Kwimba 9.6 2.5 4.7 1.7 26.5 4.8 85.6 8.2 11.9 28.8 27.4 Sengerema 12.1 1.6 4.3 0.6 29.6 6.3 64.7 4.1 34.9 33.5 59.8 Geita 13.5 3.4 5.6 1.4 45.1 7.1 136.4 3.9 23.9 65.1 110.5 Missungwi 11.1 2.0 5.3 1.2 26.4 4.3 63.8 6.9 15.6 55.0 19.6 Ilemela 10.8 1.8 1.7 1.0 16.5 5.0 20.9 6.9 11.5 17.4 9.7 Total 12.6 2.5 4.2 1.3 30.8 6.0 88.3 5.3 21.1 41.4 52.3 District Capital 88.3 Tarmac Roads 52.3 Tertiary Market 41.4 Hospitals 30.8 Secondary Schools 12.6 Secondary Market 21.1 Primary Markets 5.3 Health Clinics 6.0 All weather roads 4.2 Primary Schools 2.5 Feeder Roads 1.3 33.01a ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 266 No of households % No of households % No of households % No of households % No of households % Ukerewe 469 1 1,900 6 9,514 29 7,283 22 13,742 42 32,909 18 Magu 1,571 3 3,397 6 23,280 41 17,824 32 10,288 18 56,360 13 Kwimba 5,299 12 2,578 6 20,894 46 10,536 23 6,506 14 45,813 10 Sengerema 2,532 4 6,975 11 21,871 34 22,242 34 11,042 17 64,661 12 Geita 1,743 2 10,586 11 32,342 35 22,549 24 26,066 28 93,286 13 Missungwi 1,030 3 2,575 8 13,970 41 12,001 35 4,557 13 34,132 11 Ilemela 293 2 1,663 13 5,152 40 3,907 30 1,907 15 12,922 11 Total 12,937 4 29,674 9 127,022 37 96,343 28 74,109 22 340,085 13 No of households % No of households % No of households % No of households % No of households % Ukerewe 23,600 72 7,040 21 2,183 7 0 0 85 0 32,909 0.9 Magu 20,078 36 17,364 31 14,013 25 4,637 8 268 0 56,360 3.0 Kwimba 13,900 30 12,676 28 14,754 26 3,029 7 1,453 3 45,813 4.7 Sengerema 25,879 40 17,202 27 13,421 24 4,229 7 3,930 6 64,661 4.3 Geita 31,980 34 19,106 20 23,356 41 12,319 13 6,526 7 93,286 5.6 Missungwi 10,733 31 9,385 27 7,990 14 4,473 13 1,552 5 34,132 5.3 Ilemela 7,194 56 3,271 25 2,258 4 0 0 199 2 12,922 1.7 Total 133,363 39 86,043 25 77,976 138 28,687 8 14,015 4 340,085 4.2 No of households % No of households % No of households % No of households % No of households % Ukerewe 29,412 89.4 2,996 9.1 168 0.5 0 0.0 333 1.0 32,909 0.8 Magu 27,671 49.1 22,531 40.0 5,510 9.8 0 0.0 649 1.2 56,360 2.0 Kwimba 19,268 42.1 14,281 31.2 12,062 26.3 100 0.2 101 0.2 45,813 1.7 Sengerema 45,249 70.0 17,644 27.3 1,768 2.7 0 0.0 0 0.0 64,661 0.6 Geita 53,444 57.3 31,130 33.4 8,143 8.7 139 0.1 430 0.5 93,286 1.4 Missungwi 20,661 60.5 8,814 25.8 4,657 13.6 0 0.0 0 0.0 34,132 1.2 Ilemela 10,407 80.5 2,198 17.0 221 1.7 0 0.0 96 0.7 12,922 1.0 Total 206,111 60.6 99,595 29.3 32,529 9.6 239 0.1 1,610 0.5 340,085 1.3 33.01d ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of households Mean Distance Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km 33.01c ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01b ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year District Distance to Secondary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 267 No of households % No of households % No of households % No of households % No of households % Ukerewe 309 0.9 253 0.8 9,343 28.4 11,058 33.6 11,058 33.6 32,909 18.3 Magu 1,187 2.1 779 1.4 8,892 15.8 11,340 20.1 11,340 20.1 56,360 25.5 Kwimba 2,239 4.9 1,161 2.5 13,279 29.0 7,918 17.3 7,918 17.3 45,813 26.5 Sengerema 154 0.2 3,539 5.5 6,284 9.7 11,345 17.5 11,345 17.5 64,661 29.6 Geita 600 0.6 230 0.2 1,468 1.6 6,426 6.9 6,426 6.9 93,286 45.1 Missungwi 1,054 3.1 857 2.5 8,554 25.1 9,446 27.7 9,446 27.7 34,132 26.4 Ilemela 160 1.2 358 2.8 3,133 24.2 5,450 42.2 5,450 42.2 12,922 16.5 Total 5,704 1.7 7,177 2.1 50,952 15.0 62,983 18.5 62,983 18.5 340,085 30.8 No of households % No of households % No of households % No of households % No of households % Ukerewe 4,955 15.1 10,986 33.4 15,131 46.0 1,589 4.8 248 0.8 32,909 4.1 Magu 7,179 12.7 13,884 24.6 26,437 46.9 7,626 13.5 1,235 2.2 56,360 7.3 Kwimba 4,176 9.1 11,092 24.2 25,782 56.3 4,344 9.5 419 0.9 45,813 4.8 Sengerema 10,192 15.8 23,890 36.9 24,844 38.4 5,286 8.2 450 0.7 64,661 6.3 Geita 6,298 6.8 17,308 18.6 58,727 63.0 6,226 6.7 4,727 5.1 93,286 7.1 Missungwi 4,384 12.8 8,924 26.1 17,971 52.7 2,764 8.1 90 0.3 34,132 4.3 Ilemela 1,328 10.3 5,678 43.9 5,478 42.4 338 2.6 102 0.8 12,922 5.0 Total 38,510 11.3 91,761 27.0 174,370 51.3 28,172 8.3 7,271 2.1 340,085 6.0 No of households % No of households % No of households % No of households % No of households % Ukerewe 17,876 54.3 11,709 35.6 3,238 9.8 85 0.3 0 0.0 32,909 1.1 Magu 15,701 27.9 29,702 52.7 10,152 18.0 268 0.5 537 1.0 56,360 3.1 Kwimba 7,872 17.2 22,103 48.2 15,524 33.9 0 0.0 314 0.7 45,813 2.5 Sengerema 19,770 30.6 33,987 52.6 10,598 16.4 151 0.2 155 0.2 64,661 1.6 Geita 21,334 22.9 51,138 54.8 20,481 22.0 0 0.0 334 0.4 93,286 3.4 Missungwi 6,328 18.5 19,572 57.3 8,142 23.9 0 0.0 90 0.3 34,132 2.0 Ilemela 2,948 22.8 7,426 57.5 2,394 18.5 104 0.8 51 0.4 12,922 1.8 Total 91,828 27.0 175,637 51.6 70,529 20.7 609 0.2 1,481 0.4 340,085 2.5 Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total number of households 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School 10.0-19.9 33.01g ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES:Number of Households by distance to Primary School for 2002/03 agriculture year 33.01f ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Above 20 km Above 20 km 33.01e ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES:Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 268 No of households % No of households % No of households % No of households % No of households % Ukerewe 0 0.0 0 0 0 0.0 0 0.0 32,909 100.0 32,909 70.0 Magu 0 0.0 0 0 0 0.0 0 0.0 56,360 100.0 56,360 79.0 Kwimba 0 0.0 0 0 0 0.0 0 0.0 45,813 100.0 45,813 85.6 Sengerema 0 0.0 0 0 0 0.0 0 0.0 64,661 100.0 64,661 64.7 Geita 0 0.0 0 0 0 0.0 0 0.0 93,286 100.0 93,286 136.4 Missungwi 0 0.0 0 0 0 0.0 0 0.0 34,132 100.0 34,132 63.8 Ilemela 0 0.0 0 0 2,161 16.7 5,685 44.0 5,077 39.3 12,922 20.9 Total 0 0.0 0 0 7,081 2.1 9,457 2.8 319,915 94.1 340,085 88.3 No of households % No of households % No of households % No of households % No of households % Ukerewe 80 0.2 85 0.3 3,395 10.3 11,517 35.0 17,832 54.2 32,909 22.7 Magu 638 1.1 0 0.0 4,436 7.9 6,850 12.2 44,437 78.8 56,360 36.6 Kwimba 1,569 3.4 309 0.7 5,737 12.5 5,044 11.0 33,153 72.4 45,813 36.6 Sengerema 0 0.0 365 0.6 3,564 5.5 9,678 15.0 51,054 79.0 64,661 34.0 Geita 434 0.5 85 0.1 1,302 1.4 6,426 6.9 85,039 91.2 93,286 45.9 Missungwi 0 0.0 0 0.0 6,126 17.9 5,967 17.5 22,039 64.6 34,132 31.3 Ilemela 51 0.4 107 0.8 2,093 16.2 5,705 44.1 4,966 38.4 12,922 17.0 Total 2,772 0.8 952 0.3 26,653 7.8 51,187 15.1 258,521 76.0 340,085 36.0 No of households % No of households % No of households % No of households % No of households % Ukerewe 4,875 14.8 0 0.0 3,643 11.1 6,949 21.1 17,441 53.0 32,909 22.7 Magu 6,660 11.8 7,607 13.5 14,963 26.5 5,980 10.6 21,150 37.5 56,360 14.5 Kwimba 692 1.5 1,577 3.4 8,672 18.9 10,131 22.1 24,741 54.0 45,813 27.4 Sengerema 2,846 4.4 507 0.8 4,574 7.1 862 1.3 55,871 86.4 64,661 59.8 Geita 6,185 6.6 167 0.2 170 0.2 165 0.2 86,599 92.8 93,286 110.5 Missungwi 2,182 6.4 2,703 7.9 10,288 30.1 3,683 10.8 15,277 44.8 34,132 19.6 Ilemela 852 6.6 1,533 11.9 5,792 44.8 2,273 17.6 2,472 19.1 12,922 9.7 Total 24,294 7.1 14,094 4.1 48,102 14.1 30,043 8.8 223,551 65.7 340,085 52.3 33.01j ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01h ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 269 No of households % No of households % No of households % No of households % No of households % Ukerewe 3,377 10.3 6,569 20.0 18,082 54.9 18,082 54.9 730 2.2 32,909 5.8 Magu 7,992 14.2 14,823 26.3 27,384 48.6 27,384 48.6 1,334 2.4 56,360 5.0 Kwimba 4,060 8.9 6,336 13.8 24,595 53.7 24,595 53.7 2,484 5.4 45,813 8.2 Sengerema 11,424 17.7 26,332 40.7 24,905 38.5 24,905 38.5 605 0.9 64,661 4.1 Geita 18,231 19.5 25,608 27.5 41,933 45.0 41,933 45.0 983 1.1 93,286 3.9 Missungwi 3,531 10.3 5,157 15.1 17,652 51.7 17,652 51.7 969 2.8 34,132 6.9 Ilemela 351 2.7 1,296 10.0 7,552 58.4 7,552 58.4 187 1.5 12,922 6.9 Total 48,966 14.4 86,121 25.3 162,103 47.7 162,103 47.7 7,291 2.1 340,085 5 No of households % No of households % No of households % No of households % No of households % Ukerewe 3,112 9.5 729 2.2 4,723 14.4 9,930 30.2 14,414 43.8 32,909 21.5 Magu 916 1.6 2,888 5.1 11,056 19.6 7,297 12.9 34,203 60.7 56,360 30.4 Kwimba 3,525 7.7 3,382 7.4 12,376 27.0 6,477 14.1 20,053 43.8 45,813 28.8 Sengerema 1,739 2.7 4,476 6.9 11,734 18.1 7,735 12.0 38,977 60.3 64,661 33.5 Geita 1,507 1.6 4,205 4.5 9,242 9.9 8,099 8.7 70,233 75.3 93,286 65.1 Missungwi 306 0.9 565 1.7 1,554 4.6 3,292 9.6 28,415 83.2 34,132 55.0 Ilemela 0 0.0 51 0.4 2,276 17.6 6,242 48.3 4,353 33.7 12,922 17.4 Total 11,106 3.3 16,296 4.8 52,962 15.6 49,072 14.4 210,648 61.9 340,085 41.4 No of households % No of households % No of households % No of households % No of households % Ukerewe 10,826 33 2,459 7 6,391 19 10,585 32 2,648 8 32,909 12 Magu 2,133 4 5,254 9 11,831 21 12,253 22 24,889 44 56,360 19 Kwimba 1,303 3 1,109 2 19,644 43 18,662 41 5,095 11 45,813 12 Sengerema 408 1 620 1 3,598 6 10,298 16 49,737 77 64,661 35 Geita 643 1 1,425 2 25,954 28 28,077 30 37,187 40 93,286 24 Missungwi 327 1 1,006 3 11,929 35 11,543 34 9,327 27 34,132 16 Ilemela 54 0 863 7 6,367 49 2,908 23 2,730 21 12,922 11 Total 15,695 5 12,735 4 85,714 25 94,327 28 131,613 39 340,085 21 33.01m ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01k ACCESS TO INFRAUSTRACTURE AND OTHER SERVICES: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 270 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 139 1 12,959 58 8,463 38 827 4 250 1 22,388 Magu 3,612 6 13,447 22 19,052 31 24,642 41 8,880 15 60,753 Kwimba 600 3 4,290 22 5,008 26 9,418 49 4,680 24 19,316 Sengerema 743 4 6,065 36 4,783 28 5,397 32 432 3 16,989 Geita 5,428 14 1,476 4 3,254 8 29,081 74 33,566 86 39,239 Missungwi 2,672 18 4,312 29 6,866 47 857 6 10,344 70 14,708 Ilemela 224 6 1,310 35 700 19 1,461 40 333 9 3,695 Total 13,417 8 43,860 25 48,127 27 71,684 40 58,486 33 177,089 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 0 0 3,568 57 2,424 39 168 3 83 1 6,243 Magu 1,630 10 6,786 40 4,895 29 3,144 18 649 4 17,104 Kwimba 196 4 1,251 28 700 16 1,415 31 938 21 4,499 Sengerema 434 6 4,479 60 1,797 24 595 8 153 2 7,459 Geita 2,724 22 849 7 499 4 4,133 33 4,214 34 12,418 Missungwi 815 16 1,659 33 2,574 51 0 0 0 0 5,047 Ilemela 137 9 913 59 220 14 220 14 55 4 1,546 Total 5,935 11 19,504 36 13,108 24 9,675 18 6,092 11 54,315 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 0 0 769 46 758 45 152 9 0 0 1,679 Magu 261 3 1,024 11 2,328 24 4,726 49 1,404 14 9,744 Kwimba 0 0 208 7 394 13 1,681 56 730 24 3,012 Sengerema 0 0 133 8 436 28 1,005 64 0 0 1,573 Geita 608 5 0 0 0 0 5,115 42 6,598 54 12,320 Missungwi 808 17 1,045 22 263 5 172 4 2,502 52 4,789 Ilemela 0 0 59 12 107 23 248 53 55 12 469 Total 1,676 5 3,237 10 4,286 13 13,097 39 11,290 34 33,586 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 271 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 0 0.0 427 29.6 844 58.5 171 11.9 171 11.9 1,442 Magu 255 2.6 1,082 11.0 2,465 25.0 4,079 41.4 4,079 41.4 9,850 Kwimba 0 0.0 311 10.0 497 16.0 1,576 50.6 1,576 50.6 3,113 Sengerema 0 0.0 133 11.7 152 13.4 850 74.9 850 74.9 1,135 Geita 564 4.8 0 0.0 0 0.0 4,632 39.3 4,632 39.3 11,794 Missungwi 738 18.0 443 10.8 166 4.1 172 4.2 172 4.2 4,106 Ilemela 0 0.0 0 0.0 107 27.9 220 57.5 220 57.5 382 Total 1,558 4.9 2,395 7.5 4,231 13.3 11,700 36.8 11,700 36.8 31,823 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 72 1.7 2,688 62.9 1,261 29.5 252 5.9 0 0.0 4,271 Magu 541 5.3 892 8.7 2,328 22.7 4,079 39.7 2,431 23.7 10,271 Kwimba 301 6.0 409 8.1 2,012 40.0 1,483 29.5 823 16.4 5,028 Sengerema 155 5.8 281 10.5 974 36.6 974 36.6 279 10.5 2,663 Geita 795 6.0 136 1.0 867 6.5 4,784 36.0 6,707 50.5 13,289 Missungwi 84 2.7 0 0.0 174 5.6 255 8.2 2,587 83.4 3,100 Ilemela 0 0.0 223 32.2 107 15.4 306 44.3 55 8.0 691 Total 1,948 5 4,628 11.8 7,723 19.6 12,132 30.9 12,881 32.8 39,312 No of Households % No of Households % No of Households % No of Households % No of Households % Ukerewe 68 1.6 2,834 66.8 1,257 29.6 0 0.0 85 2.0 4,244 Magu 407 4.3 892 9.5 2,524 26.8 4,205 44.6 1,404 14.9 9,432 Kwimba 0 0.0 490 13.6 600 16.7 1,780 49.5 730 20.3 3,599 Sengerema 0 0.0 0 0.0 152 15.5 830 84.5 0 0.0 982 Geita 317 2.8 406 3.6 812 7.1 5,108 44.9 4,725 41.6 11,369 Missungwi 0 0.0 340 8.2 1,125 27.2 169 4.1 2,502 60.5 4,136 Ilemela 86 17.2 59 11.7 53 10.6 248 49.4 55 11.1 502 Total 879 2.6 5,021 14.7 6,523 19.0 12,340 36.0 9,502 27.7 34,264 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 272 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 273 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Ukerewe 2,585 1,483 28,183 657 32,909 Magu 3,442 2,639 49,225 1,054 56,360 Kwimba 6,016 1,215 37,481 1,101 45,813 Sengerema 5,714 0 57,233 1,714 64,661 Geita 10,861 4,724 75,838 1,863 93,286 Missungwi 1,883 311 31,504 435 34,132 Ilemela 864 945 10,774 339 12,922 Total 31,365 11,317 290,238 7,164 340,085 % 9.2 3.3 85.3 2.1 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total number of households Ukerewe 2 18,980 0 0 166 11,859 1,903 0 32,909 Magu 3 25,778 250 111 1,187 23,200 5,835 0 56,360 Kwimba 4 11,596 99 0 92 27,271 6,755 0 45,813 Sengerema 3 28,437 257 0 0 31,889 4,078 0 64,661 Geita 3 36,512 1,402 1,204 305 42,764 10,513 585 93,286 Missungwi 3 8,027 90 0 0 25,401 615 0 34,132 Ilemela 3 6,317 160 97 58 5,210 1,081 0 12,922 Total 3 135,648 2,257 1,412 1,809 167,594 30,779 585 340,085 % 39.9 0.7 0.4 0.5 49.3 9.1 0.2 100.0 34.1 HOUSEHOLD FACILITIES: Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year District 34.2 HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year Type of toilet Total number of households Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 274 Total Ukerewe Magu Kwimba Sengerema Geita Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 23,352 11 33,658 16 22,731 11 47,744 22 58,226 27 214,688 100 Landline phone 240 19 241 19 0 0 300 23 328 25 1,287 100 Mobile phone 776 12 849 13 604 9 996 16 2,587 40 6,398 100 Iron 4,659 8 10,440 18 5,894 10 14,869 26 13,088 23 56,529 100 Wheelbarrow 1,576 8 4,009 20 3,203 16 1,740 9 7,064 36 19,633 100 Bicycle 15,991 7 36,737 17 29,251 14 44,666 21 60,159 28 216,618 100 Vehicle 77 3 935 32 613 21 428 15 424 15 2,904 100 Television / Video 386 10 288 8 617 17 558 15 1,051 28 3,703 100 Total Number of Households 47,056 9 87,156 17 62,914 12 111,302 21 142,927 27 521,760 100 Number of Households % Number of Households % Number of Households % Radio 20,579 9.6 8,191 3.8 214,688 100.0 Landline phone 177 13.8 0 0.0 1,287 100.0 Mobile phone 443 6.9 135 2.1 6,398 100.0 Iron 4,903 8.7 2,600 4.6 56,529 100.0 Wheelbarrow 1,358 6.9 658 3.3 19,633 100.0 Bicycle 23,072 10.7 6,456 3.0 216,618 100.0 Vehicle 424 14.6 0 0.0 2,904 100.0 Television / Video 619 16.7 178 4.8 3,703 100.0 Households 51,575 9.9 18,216 3.5 521,760 100.0 34.3 HOUSEHOLD FACILITIES: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Type of Owned Asset District Total 34.4 HOUSEHOLD FACILITIES: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Missungwi Ilemela District Type of Owned Asset Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 275 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 401 15.7 736 0.0 202 0.0 155 0.0 406 0.0 659 0.0 0 0.0 2,559 0.0 Solar 0 0.0 134 17.6 0 0.0 431 56.6 168 22.0 0 0.0 28 3.7 761 100.0 Gas (Biogas) 0 0.0 0 0.0 0 0.0 0 0.0 318 0.0 0 0.0 28 0.0 0 0.0 Hurricane Lamp 13,211 18.9 13,085 18.7 8,577 12.3 14,503 20.8 12,090 17.3 4,798 6.9 3,595 5.1 69,859 100.0 Pressure Lamp 796 5.9 2,114 15.7 1,538 11.4 1,734 12.9 4,990 37.0 1,485 11.0 817 6.1 13,474 100.0 Wick Lamp 18,245 7.3 39,921 16.0 35,084 14.0 47,838 19.1 73,828 29.5 26,951 10.8 8,400 3.4 250,269 100.0 Candles 256 51.6 111 22.4 103 20.8 0 0.0 0 0.0 26,951 0.0 26 5.3 496 100.0 Firewood 0 0.0 0 0.0 0 0.0 0 0.0 1,486 71.1 240 11.5 55 2.7 2,090 100.0 Other 0 0.0 258 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 258 100.0 Total 32,909 10 56,361 16.6 45,504 13.4 64,661 19.0 93,286 27.5 61,084 18 12,951 3.8 339,766 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Solar 0 0.0 0 0.0 0 0.0 0 0.0 152 100.0 0 0.0 0 0.0 152 100.0 Gas (Biogas) 0 0.0 111 55.2 0 0.0 0 0.0 0 0.0 90 44.8 0 0.0 201 100.0 Bottled Gas 167 54.6 139 45.4 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 306 100.0 Parraffin / Kerocine 0 0.0 210 70.5 0 0.0 0 0.0 0 0.0 88 29.5 0 0.0 298 100.0 Charcoal 822 8.4 282 2.9 995 10.2 2,693 27.5 3,285 33.6 916 9.4 787 8.0 9,781 100.0 Firewood 31,776 9.7 54,943 16.7 44,716 13.6 61,968 18.9 89,703 27.3 32,832 10.0 12,085 3.7 328,022 100.0 Crop Residues 0 0.0 0 0.0 102 62.4 0 0.0 0 0.0 61 37.6 0 0.0 163 100.0 Livestock Dung 0 0.0 138 100.2 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 138 100.0 Total 32,765 9.7 55,823 16.5 45,813 13.5 64,661 19.1 93,140 27.5 33,987 10.0 12,872 3.8 339,061 100.0 34.5 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year 34.6 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Ukerewe Main Source of Energy for Lighting District Total Ukerewe Magu Total Missungwi Kwimba Geita Sengerema Ilemela Sengerema Missungwi Ilemela Kwimba Main Source of Energy for Cooking District Geita Magu Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 276 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela Total wet season 816 6,920 9,220 812 962 1,075 1,215 21,020 dry season 330 8,174 11,691 729 7,865 1,742 1,161 31,692 wet season 11,498 23,121 24,137 15,444 166 7,633 5,983 87,982 Dry season 9,594 24,259 19,302 13,913 8,530 8,697 5,823 90,118 wet season 1,363 1,853 610 2,647 64,351 1,377 1,054 73,254 Dry season 1,615 2,004 507 2,179 0 2,542 994 9,841 wet season 9,626 10,634 10,051 36,025 15,128 6,798 2,819 91,081 Dry season 9,367 11,336 5,210 36,025 64,375 14,094 2,723 143,130 wet season 3,139 1,727 4,604 4,220 1,711 954 305 16,660 Dry season 2,842 1,187 2,844 2,198 15,151 5,363 906 30,491 wet season 6,313 6,151 502 575 470 0 247 14,258 Dry season 9,083 7,893 1,010 7,482 2,010 1,456 510 29,444 wet season 0 691 206 575 2,319 3,641 442 7,874 Dry season 0 274 1,320 0 470 79 262 2,405 wet season 154 3,896 0 2,608 2,319 69 0 9,047 Dry season 77 693 210 592 1,657 69 0 3,299 wet season 0 0 0 0 315 0 0 315 Dry season 0 0 0 133 147 0 102 382 wet season 0 0 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 0 0 wet season 0 0 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 0 0 wet season 0 1,367 0 0 0 0 0 1,367 dry season 0 541 0 133 0 0 0 674 65,817 112,721 91,423 126,289 187,944 55,591 24,545 664,331 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela Total wet season 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.2 dry season 0.0 0.1 0.1 0.0 0.1 0.0 0.0 0.3 wet season 0.2 0.2 0.2 0.1 0.0 0.1 0.1 0.8 Dry season 0.1 0.2 0.2 0.1 0.1 0.1 0.1 0.8 wet season 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.6 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 wet season 0.1 0.1 0.1 0.3 0.1 0.1 0.0 0.8 Dry season 0.1 0.1 0.0 0.3 0.6 0.1 0.0 1.3 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 Dry season 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.3 wet season 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.1 Dry season 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.3 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 dry season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Bottled Water Other Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Tanker Truck Bottled Water Piped Water 34.7 HOUSEHOLD FACILITIES: Number of Agricultural Households by Main Source of Drinking Water by Season (LONG and Short) and District during 2002/03 Agricultural Year Protected Well Protected / Covered Spring Other District Source Season Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Total Agricultural Households per District 34.8 HOUSEHOLD FACILITIES: Proportion of Agricultural Households by Main Source of Drinking Water by Season (LONG and Short) and District during 2002/03 Agricultural Year Source Season District Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 277 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela wet season 250 6,521 600 3,222 1,706 735 180 Dry season 403 1,490 289 1,525 1,875 409 329 wet season 5,423 7,506 7,246 17,615 19,065 9,122 1,977 Dry season 5,011 6,273 4,372 14,250 15,707 6,152 1,691 wet season 10,742 5,817 3,915 7,430 12,656 7,064 1,416 Dry season 9,110 6,408 2,638 6,684 11,035 5,602 1,207 wet season 4,775 15,571 19,530 20,718 32,408 6,863 4,378 Dry season 4,530 15,744 16,056 16,753 29,162 5,291 4,239 wet season 6,891 2,499 4,302 3,636 5,524 3,859 1,072 Dry season 7,371 3,387 4,688 4,218 6,838 5,100 1,279 wet season 739 3,845 719 3,560 3,469 2,521 413 Dry season 729 2,580 617 2,693 3,403 1,982 322 wet season 4,089 14,601 9,501 8,479 18,458 3,968 3,486 Dry season 5,755 20,479 17,152 18,537 25,267 9,596 3,855 Ukerewe Magu Kwimba Sengerema Geita Missungwi Ilemela wet season 0.6 4.4 2.1 2.1 0.9 1.8 0.5 Dry season 0.1 0.2 0.0 0.1 0.1 0.0 0.2 wet season 1.1 1.2 1.7 1.2 1.2 1.5 1.2 Dry season 0.5 1.1 1.1 1.9 1.2 0.9 1.2 wet season 1.2 0.9 1.5 1.1 1.1 1.3 1.2 Dry season 1.9 0.4 0.1 0.3 0.3 0.8 0.3 wet season 1.1 1.0 1.2 1.2 1.1 1.3 1.0 Dry season 0.7 6.3 3.7 4.6 5.3 1.4 4.0 wet season 0.9 0.7 0.9 0.9 0.8 0.8 0.8 Dry season 10.0 0.9 6.5 1.2 2.0 2.0 3.1 wet season 1.0 1.5 1.2 1.3 1.0 1.3 1.3 Dry season 0.2 0.2 0.1 0.3 0.2 0.5 0.1 wet season 0.7 0.7 0.6 0.5 0.7 0.4 0.9 Dry season 0.7 0.7 0.6 0.5 0.7 0.4 0.9 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes District 34.9 HOUSEHOLD FACILITIES: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season District above one Hour 40 - 49 Minutes 50 - 59 Minutes above one Hour 34.10 HOUSEHOLD FACILITIES: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 278 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 83 0.3 1,488 2.6 206 0.4 304 0.5 2,123 2.3 574 1.7 468 3.6 5,246 1.5 Two 30,548 92.8 41,378 73.4 22,895 50.0 46,480 71.9 76,687 82.2 17,365 50.9 10,323 79.9 245,676 72.2 Three 2,125 6.5 13,246 23.5 22,612 49.4 17,877 27.6 13,843 14.8 15,787 46.3 2,132 16.5 87,622 25.8 Four 153 0.5 247 0.4 100 0.2 0 0.0 634 0.7 406 1.2 0 0.0 1,541 0.5 Total 32,909 100 56,360 100 45,813 100 64,662 100 93,287 100 34,132 100 12,923 100 340,085 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 12,883 39.1 24,621 43.7 18,731 40.9 25,602 39.6 28,904 31.0 13,598 20.0 4,523 35.0 128,863 37.9 One 9,668 29.4 20,003 35.5 17,957 39.2 17,667 27.3 33,828 36.3 12,927 19.0 4,897 37.9 116,948 34.4 Two 6,241 19.0 8,173 14.5 7,215 15.7 15,732 24.3 19,798 21.2 4,166 6.1 2,295 17.8 63,621 18.7 Three 2,773 8.4 1,917 3.4 1,497 3.3 3,819 5.9 5,911 6.3 2,353 3.5 801 6.2 19,072 5.6 Four 889 2.7 912 1.6 310 0.7 1,120 1.7 2,880 3.1 591 0.9 289 2.2 6,991 2.1 Five 301 0.9 262 0.5 0 0.0 308 0.5 1,192 1.3 407 0.6 117 0.9 2,588 0.8 Six 68 0.2 222 0.4 103 0.2 0 0.0 321 0.3 0 0.0 0 0.0 714 0.2 Seven 85 0.3 250 0.4 0 0.0 413 0.6 452 0.5 34,043 50.0 0 0.0 1,289 0.4 Total 32,909 100.0 56,360 100.0 45,813 100.0 64,661 100.0 93,286 100.0 68,086 100.0 12,922 100.0 340,085 100.0 34.11 HOUSEHOLD FACILITIES: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District 34.12 HOUSEHOLD FACILITIES: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Missungwi Sengerema Number of Meals per Day District Total Ukerewe Magu Kwimba Total Ukerewe Sengerema District Kwimba Missungwi Geita Magu Number of Days Ilemela Geita Ilemela Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 279 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 313 1.0 3,770 6.7 10,220 22.3 1,486 2.3 13,862 14.9 6,819 20.0 101 0.8 36,572 10.8 One 1,947 5.9 9,403 16.7 13,590 29.7 3,899 6.0 22,826 24.5 6,992 20.5 477 3.7 59,135 17.4 Two 2,311 7.0 12,882 22.9 7,921 17.3 7,137 11.0 19,924 21.4 7,742 22.7 1,883 14.6 59,801 17.6 Three 1,312 4.0 9,580 17.0 6,373 13.9 10,323 16.0 15,766 16.9 5,906 17.3 2,721 21.1 51,980 15.3 Four 5,263 16.0 6,316 11.2 3,439 7.5 10,306 15.9 8,868 9.5 3,035 8.9 3,529 27.3 40,755 12.0 Five 5,696 17.3 5,140 9.1 2,646 5.8 11,737 18.2 6,972 7.5 1,709 5.0 1,392 10.8 35,292 10.4 Six 6,463 19.6 3,058 5.4 912 2.0 5,910 9.1 3,082 3.3 419 1.2 1,389 10.8 21,234 6.2 Seven 9,604 29.2 6,210 11.0 713 1.6 13,863 21.4 1,985 2.1 1,510 4.4 1,430 11.1 35,316 10.4 Total 32,909 100.0 56,360 100.0 45,813 100.0 64,661 100.0 93,286 100.0 34,132 100.0 12,922 100.0 340,085 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 19,097 58.0 19,592 36.9 11,090 24.2 46,221 71.5 60,006 64.3 15,403 45.1 6,282 48.6 177,692 52.8 Seldom 8,175 24.8 21,084 39.8 15,932 34.8 12,964 20.0 20,892 22.4 8,330 24.4 4,723 36.5 92,100 27.3 Sometimes 1,439 4.4 4 0.0 3,821 8.3 1,403 2.2 4,110 4.4 1,352 4.0 484 3.7 12,614 3.7 Often 2,520 7.7 7,965 15.0 9,557 20.9 3,070 4.7 4,263 4.6 5,688 16.7 746 5.8 33,808 10.0 Always 1,677 5.1 4,379 8.3 5,414 11.8 1,003 1.6 4,016 4.3 3,358 9.8 688 5.3 20,534 6.1 Total 32,909 100.0 53,024 100.0 45,813 100.0 64,661 100.0 93,286 100.0 34,132 100.0 12,922 100.0 336,748 100.0 34.13 HOUSEHOLD FACILITIES: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District 34.14 HOUSEHOLD FACILITIES: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Total Number of Days District Ukerewe Magu Kwimba Geita Missungwi Ilemela Sengerema Total Geita Missungwi Ilemela Status of Food Satisfaction District Sengerema Magu Kwimba Ukerewe Tanzania Agriculture Sample Census -2003 Mwanza Appendix II 280 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 18,980 14 25,778 19 11,596 9 28,437 21 36,512 27 8,027 6 6,317 5 135,648 100 Tiles 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Concrete 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Asbestos 166 9 1,187 66 92 5 0 0 305 17 0 0 58 3 1,809 100 Grass / Leaves 11,859 7 23,200 14 27,271 16 31,889 19 42,764 26 25,401 15 5,210 3 167,594 100 Grass & Mud 1,903 6 5,835 19 6,755 22 4,078 13 10,513 34 615 2 1,081 4 30,779 100 Other 0 0 0 0 0 0 0 0 585 100 0 0 0 0 585 100 Total 32,909 10 56,000 17 45,714 14 64,404 0 90,680 27 34,043 10 12,665 4 336,415 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 10,905 12 7,649 8 13,633 15 17,764 19 29,946 32 10,367 11 2,348 3 92,612 100 Sale of Livestock 1,234 8 2,728 18 2,940 19 3,020 20 2,074 14 3,078 20 111 1 15,186 100 Sale of Livestock Products 340 6 1,330 22 0 0 1,562 26 1,575 26 879 14 406 7 6,092 100 Sales of Cash Crops 1,306 2 20,153 37 6,343 12 6,728 12 14,484 27 3,392 6 1,439 3 53,844 100 Sale of Forest Products 223 3 742 10 305 4 1,388 18 2,818 36 1,456 19 856 11 7,788 100 Business Income 2,529 8 1,350 4 3,283 10 10,340 31 9,414 28 4,269 13 2,343 7 33,528 100 Wages & Salaries in Cash 1,522 11 1,293 9 1,924 14 2,950 21 3,080 22 1,974 14 1,071 8 13,813 100 Other Casual Cash Earnings 3,934 6 14,540 20 15,043 21 6,935 10 21,931 31 6,679 9 2,102 3 71,164 100 Cash Remittance 1,781 12 3,564 25 2,342 16 3,902 27 2,028 14 341 2 444 3 14,404 100 Fishing 8,979 32 3,012 11 0 0 9,921 36 2,693 10 1,518 5 1,647 6 27,769 100 Other 157 4 0 0 45,813 1,206 3,158 83 179 5 179 5 155 4 3,800 100 Total 32,909 10 56,360 17 91,626 27 67,668 20 90,223 27 34,132 10 12,922 4 339,999 100 34.15 HOUSEHOLD FACILITIES: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year 34.16 HOUSEHOLD FACILITIES: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Missungwi Sengerema Total Roofing Materials District Total Ukerewe Magu Geita Ilemela Kwimba Main Source of Energy for Cooking District Geita Ukerewe Missungwi Kwimba Sengerema Magu Ilemela Tanzania Agriculture Sample Census -2003 Mwanza 281 APPENDIX III QUESTIONNAIRES Appendix III 282 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 283 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 284 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 285 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 286 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 287 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 288 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vemen Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farmin No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 289 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 290 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 290 291 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 292 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 293 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 294 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 295 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 296 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert HerbFun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 297 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 298 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 299 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 300 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 301 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 302 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method ofMethod of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 303 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 304 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 305 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 306 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 307 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 308 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importanceConstraint Order of least importanc Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 309 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 310 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 311 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 312 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 313 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 314 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 315 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 316 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 317 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 318 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 319 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 320 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Sourcefrequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 321 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 322 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick i Main Tick if Activity carrie respo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used forused for noCheck hh -ility in activitysubsistancesubsistenceTotal (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 323 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 324 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 325 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 326 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 327 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Mei 02 - 06, 2022 Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Apr 25 - 29, 2022 Wiki hii Mei 02 - 06, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 68,200 196,600 185,700 115,300 116,000 171,600 73,900 Wiki iliyopita 65,600 188,600 185,200 119,000 119,400 170,300 72,800 Badiliko ▲3.8% ▲4.1% ▲0.3% ▼3.2% ▼2.9% ▲0.8% ▲1.5% Wastani wa Nchi Ujumbe Mkuu Mazao makuu ya chakula: Bei za jumla zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za mchele mahindi, viazi mviringo, ulezi na maharage zimeongezeka kwa asilimia 4.1, 3.8, 1.5, 0.8 na 0.3 mtawalia, bei za mtama na uwele zimeshuka kwa asilimia 3.2 na 2.9 mtawalia. Mboga na matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za tango na vitunguu zimeongezeka kwa asilimia 5 na 1 mtawalia wakati bei za pilipilihoho, tikitimaji, nyanya na nanasi zimepungua kwa asilimia 13, 4, 1 na 1 mtawalia. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 2 Mei, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 8,310,150 zenye thamani ya Shilingi bilioni 40. Korosho: Hadi kufikia tarehe 27 Machi, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,155,915 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 5 Mei, 2022 wastani wa bei ya UREA katika soko la dunia umepungua kwa asilimia 0.36, wastani wa bei ya DAP katika soko la dunia hakubadilika ikilinganishwa na wiki iliyopita. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 67,100 192,500 191,500 68,400 66,500 146,000 77,300 Wiki iliyopita 66,500 190,100 185,600 68,600 66,000 141,800 77,000 Badiliko ▲0.9% ▲1.2% ▲3.1% ▼0.3% ▲0.8% ▲2.9% ▲0.4% Arusha Wiki hii 77,500 225,000 170,000 67,500 69,000 139,500 87,500 Wiki iliyopita 76,500 225,000 170,000 63,500 69,000 139,500 87,500 Badiliko ▲1.3% ►0.0% ►0.0% ▲5.9% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 97,500 190,000 260,000 110,000 110,000 185,000 59,000 Wiki iliyopita 82,800 212,500 237,500 115,000 102,500 185,000 57,600 Badiliko ▲15.1% ▼11.8% ▲8.7% ▼4.5% ▲6.8% ►0.0% ▲2.4% Morogoro Wiki hii 61,600 214,000 195,000 175,000 175,000 172,500 95,000 Wiki iliyopita 64,000 199,000 195,000 175,000 175,000 172,500 95,000 Badiliko ▼3.9% ▲7.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 64,500 205,000 185,000 100,000 100,000 175,000 65,000 Wiki iliyopita 64,500 205,000 185,000 100,000 100,000 175,000 65,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 65,000 195,000 177,500 NA NA 180,000 NA Wiki iliyopita 60,000 192,500 191,300 NA NA 180,000 NA Badiliko ▲7.7% ▲1.3% ▼7.8% ►0.0% Iringa Wiki hii 60,000 195,000 175,000 - NA - 68,800 Wiki iliyopita 61,000 175,000 195,000 110,000 NA 150,000 55,000 Badiliko ▼1.7% ▲10.3% ▼11.4% ▲20.1% Tabora Wiki hii 59,000 175,000 190,000 NA NA NA NA Wiki iliyopita 59,000 167,500 190,000 NA NA NA NA Badiliko ►0.0% ▲4.3% ►0.0% Rukwa Wiki hii 60,000 165,000 160,000 NA NA NA 65,000 Wiki iliyopita 55,000 165,000 170,000 NA NA NA 55,000 Badiliko ▲8.3% ►0.0% ▼6.3% ▲15.4% Kigoma Wiki hii 65,300 187,500 180,000 100,000 120,000 150,000 85,000 Wiki iliyopita 58,400 185,000 138,800 105,000 122,500 182,500 87,500 Badiliko ▲10.6% ▲1.3% ▲22.9% ▼5.0% ▼2.1% ▼21.7% ▼2.9% 3 Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: ✓ Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. ✓ N/A: bei haikupatikana Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 65,000 215,000 200,000 160,000 165,000 180,000 100,000 Wiki iliyopita 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Badiliko ►0.0% ▲11.6% ►0.0% ►0.0% ►0.0% ►0.0% ▲15.0% Kagera Wiki hii 78,000 190,000 160,000 130,000 145,000 160,000 67,500 Wiki iliyopita 67,500 187,500 155,000 130,000 137,500 150,000 67,500 Badiliko ▲13.5% ▲1.3% ▲3.1% ►0.0% ▲5.2% ▲6.3% ►0.0% Mara Wiki hii 82,500 - 210,000 82,500 235,000 235,000 - Wiki iliyopita 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Badiliko ▲21.2% ▼8.3% ▲24.2% ▲19.1% ▲19.1% Manyara Wiki hii 81,000 200,000 165,000 90,000 90,000 155,000 85,000 Wiki iliyopita 81,000 200,000 165,000 90,000 90,000 155,000 100,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼17.6% Njombe Wiki hii 58,000 225,000 185,000 NA NA 162,500 48,300 Wiki iliyopita 58,000 225,000 185,000 NA NA 162,500 48,300 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 48,500 175,000 167,500 185,000 NA 190,000 57,500 Wiki iliyopita 58,800 165,000 167,500 190,000 NA 190,000 57,500 Badiliko ▼21.2% ▲5.7% ►0.0% ▼2.7% ►0.0% ►0.0% 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 28 Aprili hadi 4 Mei 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 61,600 228,800 836 726 83,600 55,000 Mombasa 63,800 247,500 660 55,000 110,000 Dar es salaam 50,000 330,000 400 400 36,667 120,000 Morogoro 52,500 280,000 500 800 43,750 Dodoma 33,333 300,000 400 783 36,667 60,000 Shinyanga 35,000 208,333 500 500 29,167 60,000 Mwanza 33,333 261,111 617 1,017 26,000 45,333 Arusha 50,000 218,750 650 675 37,500 52,500 Tanga 44,500 212,500 675 700 36,250 72,500 Lindi 50,000 218,750 650 675 37,500 52,500 Mtwara 50,000 275,000 400 700 100,000 90,000 Mbeya 45,000 225,000 877 1,767 51,000 118,667 Wastani wiki hii 47,422 250,479 597 795 47,758 76,045 Wastani wiki iliyopita 48,114 249,136 624 800 54,637 72,590 Badiliko ▼1% ▲ 1% ▼4% ▼1% ▼13% ▲5% Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 2 Mei, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 6,323,140 1,468,220 518,790 8,310,150 4,744.71 38,850,171,970 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 27 Machi, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 711,187 1,700 1,610 1,250 1,200 1,137,802,010 JUMLA YA MAUZO YOTE 231,155,915 2,445 1,500 1,755 1,200 489,058,851,406 Chanzo: Bodi ya Korosho Tanzania, 2022 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 2022 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 05 Mei, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 05 Mei, 2022 7 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- ❖ USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo ❖ Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Mei 09 - 13, 2022 Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Ujumbe Mkuu Mazao makuu ya chakula: Bei za jumla zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za mchele, mtama, uwele, ulezi, mchele na viazi mviringo zimeongezeka kwa asilimia 7.4, 7.3, 5.4, 2.1 na 1.9 mtawalia, bei za mahindi na maharage zimeshuka kwa asilimia 4.3 na 0.5 mtawalia. Mboga na matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za pilipili hoho, nanasi na nyanya zimeongezeka kwa asilimia 38, 37 na 8 mtawalia wakati bei za vitunguu, tikitimaji na tango zimepungua kwa asilimia 2, 2, na 2 mtawalia. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 2 Mei, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 8,310,150 zenye thamani ya Shilingi bilioni 40. Korosho: Hadi kufikia tarehe 05 Mei, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,199,729 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 11 Mei, 2022 wastani wa bei ya UREA na DAP katika soko la dunia umepungua kwa asilimia 8 na 3 katika soko la dunia ikilinganishwa na wiki iliyopita. Wiki iliyopita Mei 02 - 06, 2022 Wiki hii Mei 09 - 13, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 65,400 200,800 184,800 124,500 137,700 181,400 75,300 Wiki iliyopita 68,200 196,600 185,700 115,300 127,600 171,600 73,900 Badiliko ▼4.3% ▲2.1% ▼0.5% ▲7.4% ▲7.3% ▲5.4% ▲1.9% Wastani wa Nchi 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 72,300 198,800 194,600 63,300 66,500 148,800 76,800 Wiki iliyopita 67,100 192,500 191,500 68,400 66,500 146,000 77,300 Badiliko ▲7.2% ▲3.2% ▲1.6% ▼8.1% ►0.0% ▲1.9% ▼0.7% Arusha Wiki hii 77,500 225,000 170,000 67,500 NA 139,500 87,500 Wiki iliyopita 77,500 225,000 170,000 67,500 69,000 139,500 87,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 76,300 222,500 230,000 130,000 105,000 207,500 62,800 Wiki iliyopita 97,500 190,000 260,000 110,000 110,000 185,000 59,000 Badiliko ▼27.8% ▲14.6% ▼13.0% ▲15.4% ▼4.8% ▲10.8% ▲6.1% Lindi Wiki hii 75,000 200,000 200,000 145,000 NA 225,000 77,500 Wiki iliyopita NA NA NA NA NA NA NA Badiliko Morogoro Wiki hii 62,500 215,000 207,500 175,000 175,000 177,500 97,500 Wiki iliyopita 61,600 214,000 195,000 175,000 175,000 172,500 95,000 Badiliko ▲1.4% ▲0.5% ▲6.0% ►0.0% ►0.0% ▲2.8% ▲2.6% Tanga Wiki hii 71,800 205,000 185,000 100,000 100,000 188,800 75,000 Wiki iliyopita 64,500 205,000 185,000 100,000 100,000 175,000 65,000 Badiliko ▲10.2% ►0.0% ►0.0% ►0.0% ►0.0% ▲7.3% ▲13.3% Mtwara Wiki hii 65,000 210,000 187,500 NA NA 180,000 NA Wiki iliyopita 65,000 195,000 177,500 NA NA 180,000 NA Badiliko ►0.0% ▲7.1% ▲5.3% ►0.0% Iringa Wiki hii 58,500 195,000 175,000 150,000 NA 190,000 55,000 Wiki iliyopita 60,000 195,000 175,000 NA NA NA 68,800 Badiliko ▼2.6% ►0.0% ►0.0% ▼25.1% Ruvuma Wiki hii 53,800 180,000 165,000 NA NA NA 77,500 Wiki iliyopita NA NA NA NA NA NA NA Badiliko Tabora Wiki hii 59,000 175,000 190,000 NA NA NA NA Wiki iliyopita 59,000 175,000 190,000 NA NA NA NA Badiliko ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 57,500 165,000 142,500 NA NA NA 67,500 Wiki iliyopita 60,000 165,000 160,000 NA NA NA 65,000 Badiliko ▼4.3% ►0.0% ▼12.3% ▲3.7% Shinyanga Wiki hii 61,000 170,000 175,000 95,000 95,000 NA 85,000 Wiki iliyopita NA NA NA NA NA NA NA Badiliko 3 Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 79,500 215,000 217,500 160,000 170,000 180,000 100,000 Wiki iliyopita 65,000 215,000 200,000 160,000 165,000 180,000 100,000 Badiliko ▲18.2% ►0.0% ▲8.0% ►0.0% ▲2.9% ►0.0% ►0.0% Kagera Wiki hii 79,500 190,000 165,000 130,000 165,000 162,500 67,500 Wiki iliyopita 78,000 190,000 160,000 130,000 145,000 160,000 67,500 Badiliko ▲1.9% ►0.0% ▲3.0% ►0.0% ▲12.1% ▲1.5% ►0.0% Mara Wiki hii 72,500 190,000 210,000 72,500 235,000 235,000 100,000 Wiki iliyopita 82,500 NA 210,000 82,500 235,000 235,000 NA Badiliko ▼13.8% ►0.0% ▼13.8% ►0.0% ►0.0% Manyara Wiki hii 74,500 205,000 165,000 90,000 90,000 155,000 80,000 Wiki iliyopita 81,000 200,000 165,000 90,000 90,000 155,000 85,000 Badiliko ▼8.7% ▲2.4% ►0.0% ►0.0% ►0.0% ►0.0% ▼6.3% Njombe Wiki hii 66,000 225,000 185,000 NA NA 210,000 48,300 Wiki iliyopita 58,000 225,000 185,000 NA NA 162,500 48,300 Badiliko ▲12.1% ►0.0% ►0.0% ▲22.6% ►0.0% Kilimanjaro Wiki hii 62,500 215,000 207,500 175,000 175,000 NA 97,500 Wiki iliyopita NA NA NA NA NA NA NA Badiliko Katavi Wiki hii 47,000 165,000 167,500 190,000 NA 190,000 57,500 Wiki iliyopita 48,500 175,000 167,500 185,000 NA 190,000 57,500 Badiliko ▼3.2% ▼6.1% ►0.0% ▲2.6% ►0.0% ►0.0% Mbeya Wiki hii 36,000 250,000 156,000 NA NA 132,000 42,000 Wiki iliyopita NA NA NA NA NA NA NA Badiliko Zingatia: Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. N/A: bei haikupatikana 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 5-11 Mei, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 61,600 220,000 792 726 335,500 66,000 Mombasa 55,000 220,000 660 69,667 73,333 Dar es salaam 53,333 276,667 733 733 106,667 70,000 Morogoro 38,333 250,000 400 400 94,444 116,000 Dodoma 56,000 268,333 500 800 44,444 Shinyanga 21,667 300,000 350 767 36,667 63,333 Mwanza 40,000 200,000 600 500 25,000 60,000 Arusha 36,000 216,667 650 4,917 22,667 50,000 Tanga 42,500 218,750 550 700 37,500 57,500 Lindi 46,600 246,000 700 800 42,000 74,000 Mtwara 42,500 218,750 550 700 37,500 57,500 Mbeya 92,500 255,000 500 650 100,000 105,000 Wastani wiki hii 36,000 162,222 610 1,460 49,000 125,333 Wastani wiki iliyopita 47,849 234,799 584 1,096 77,004 76,500 Badiliko ▲8% ▼ 2% ▼2% ▲37% ▲38% ▼2% Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 2 Mei, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 6,323,140 1,468,220 518,790 8,310,150 4,744.71 38,850,171,970 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 05 Aprili, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 731,287 1,700 1,610 1,250 1,200 1,161,922,010 CEAMCU 23,714 1,610 38,179,540.00 JUMLA YA MAUZO YOTE 231,199,729 2,445 1,500 1,755 1,200 489,121,150,946 Chanzo: Bodi ya Korosho Tanzania, 2022 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 2022 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 11 Mei, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 11 Mei, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 0 200 400 600 800 100005 Aug 202119 Aug 202102 Sep 202116 Sep 202130 Sep 202114 Oct 202128 Oct 202111 Nov 202125 Nov 202109 Dec 202123 Dec 202106 Jan 202220 Jan 202203 Feb 202217 Feb 202203 Mar 202217 Mar 202231 Mar 202214 Apr 202228 Apr 202212 May 2022 Bei (Dola za Marekani/Tani) Kipindi 0 200 400 600 800 1000 1200 140005 Aug 202119 Aug 202102 Sep 202116 Sep 202130 Sep 202114 Oct 202128 Oct 202111 Nov 202125 Nov 202109 Dec 202123 Dec 202106 Jan 202220 Jan 202203 Feb 202217 Feb 202203 Mar 202217 Mar 202231 Mar 202214 Apr 202228 Apr 202212 May 2022 Bei (Dola za Marekani/Tani) Kipindi 7 Habari Muhimu Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Aprili 11 - 15, 2022 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Apr 04 - 08, 2022 Wiki hii Apr 11 - 15, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 61,100 186,900 184,700 118,300 117,900 168,900 76,700 Wiki iliyopita 61,000 186,600 186,500 116,300 118,300 167,100 79,400 Badiliko ▲0.2% ▲0.2% ▼1.0% ▲1.7% ▼0.3% ▲1.1% ▼3.5% Wastani wa Nchi Ujumbe Mkuu Kwa wiki hii, wastani wa bei za mazao makuu ya chakula zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei ya mtama, ulezi, mahindi na mchele zimeongezeka kwa asilimia 1.7, 1.1, 0.2 na 0.2 wakati bei za viazi mviringo, maharage na uwele zimeshuka kwa asilimia 3.5, 1 na 0.3 mtawalia. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 11 Aprili, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 7,772,270 zenye thamani ya Shilingi bilioni 36.4. Korosho: Hadi kufikia tarehe 27 Machi, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,155,915 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 14 Aprili, 2022 wastani wa bei ya DAP katika soko la dunia umeongezeka kwa asilimia 1, wastani wa bei ya UREA katika soko la dunia umeshika kwa asilimia 3. Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaoanza Novemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 67,600 188,300 185,000 68,500 66,000 137,300 75,800 Wiki iliyopita 61,000 187,000 185,000 64,400 66,000 137,300 93,100 Badiliko ▲9.8% ▲0.7% ►0.0% ▲6.0% ►0.0% ►0.0% ▼22.8% Arusha Wiki hii 73,000 210,000 170,000 63,500 69,000 144,000 87,500 Wiki iliyopita 61,000 210,000 175,000 67,500 69,000 138,500 87,500 Badiliko ▲16.4% ►0.0% ▼2.9% ▼6.3% ►0.0% ▲3.8% ►0.0% Dar es Salaam Wiki hii 75,300 206,300 230,000 110,000 90,000 170,000 67,200 Wiki iliyopita 72,300 206,300 220,000 110,000 85,000 170,000 66,300 Badiliko ▲4.0% ►0.0% ▲4.3% ►0.0% ▲5.6% ►0.0% ▲1.3% Lindi Wiki hii 67,500 197,500 200,000 200,000 NA 200,000 85,000 Wiki iliyopita 75,000 205,000 195,000 175,000 NA 180,000 92,500 Badiliko ▼11.1% ▼3.8% ▲2.5% ▲12.5% ▲10.0% ▼8.8% Morogoro Wiki hii 57,500 214,000 205,000 175,000 175,000 175,000 97,500 Wiki iliyopita 57,800 197,500 215,000 175,000 175,000 172,500 98,000 Badiliko ▼0.5% ▲7.7% ▼4.9% ►0.0% ►0.0% ▲1.4% ▼0.5% Tanga Wiki hii 58,200 190,000 195,000 100,000 100,000 170,000 90,000 Wiki iliyopita 58,200 190,000 190,000 100,000 110,000 170,000 90,000 Badiliko ►0.0% ►0.0% ▲2.6% ►0.0% ▼10.0% ►0.0% ►0.0% Mtwara Wiki hii 55,000 190,000 205,000 NA NA 180,000 NA Wiki iliyopita 55,000 190,000 205,000 NA NA 180,000 NA Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Iringa Wiki hii 50,000 195,000 200,000 110,000 NA 150,000 55,000 Wiki iliyopita 49,300 210,000 205,000 110,000 NA 150,000 56,300 Badiliko ▲1.4% ▼7.7% ▼2.5% ►0.0% ►0.0% ▼2.4% Tabora Wiki hii 59,000 160,000 190,000 NA NA NA NA Wiki iliyopita NA NA NA NA NA NA NA Badiliko Rukwa Wiki hii 55,000 165,000 170,000 NA NA NA 55,000 Wiki iliyopita 55,000 165,000 170,000 NA NA NA 55,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Kigoma Wiki hii 53,000 180,000 110,000 100,000 125,000 190,000 90,000 Wiki iliyopita 57,000 175,000 110,000 95,000 125,000 190,000 95,000 Badiliko ▼7.5% ▲2.8% ►0.0% ▲5.0% ►0.0% ►0.0% ▼5.6% Shinyanga Wiki hii 57,500 170,000 175,000 95,000 95,000 NA 67,500 Wiki iliyopita 57,500 170,000 175,000 95,000 95,000 NA 67,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 3 Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Wiki iliyopita 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 57,500 185,000 150,000 130,000 130,000 140,000 74,400 Wiki iliyopita 56,500 171,300 150,000 130,000 130,000 140,000 70,300 Badiliko ▲1.7% ▲7.4% ►0.0% ►0.0% ►0.0% ►0.0% ▲5.5% Mara Wiki hii 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Wiki iliyopita 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 66,000 190,000 159,000 90,000 90,000 155,000 105,000 Wiki iliyopita 66,000 190,000 159,000 90,000 90,000 155,000 105,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Njombe Wiki hii 58,000 225,000 185,000 NA NA 162,500 48,300 Wiki iliyopita 58,000 220,000 185,000 NA NA 162,500 50,500 Badiliko ►0.0% ▲2.2% ►0.0% ►0.0% ▼4.6% Kilimanjaro Wiki hii 67,500 180,000 185,000 120,000 120,000 NA 70,000 Wiki iliyopita 67,500 180,000 185,000 120,000 120,000 NA 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 52,500 165,000 167,500 190,000 NA 190,000 57,500 Wiki iliyopita 60,500 152,500 205,000 190,000 NA 190,000 75,000 Badiliko ▼15.2% ▲7.6% ▼22.4% ►0.0% ►0.0% ▼30.4% Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. N/A: bei haikupatikana 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 07 hadi 13 Aprili, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 54,267 222,933 763 682 90,200 36,667 Mombasa 59,547 220,000 660 55,000 110,000 Zanzibar 60,000 280,000 800 1,000 125,000 70,000 Dar es salaam 54,167 330,000 400 400 42,361 126,667 Morogoro 50,000 196,000 500 833 41,667 66,667 Dodoma 35,000 300,000 400 767 33,056 56,667 Shinyanga 35,000 213,333 583 500 29,167 58,333 Mwanza 36,500 285,000 650 1,125 25,000 47,000 Arusha 50,000 222,917 675 575 37,500 52,500 Tanga 48,000 224,000 640 780 42,500 68,000 Lindi 50,000 222,917 675 575 37,500 52,500 Mtwara 46,667 280,000 367 600 100,000 80,000 Mbeya 46,333 241,667 1,000 1,767 51,333 118,667 Wastani 48,114 249,136 624 800 54,637 72,590 Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 11 Aprili, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 5,856,940 1,407,810 507,520 7,772,270 4,754 36,439,814,370 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 27 Machi, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 711,187 1,700 1,610 1,250 1,200 1,137,802,010 JUMLA YA MAUZO YOTE 231,155,915 2,445 1,500 1,755 1,200 489,058,851,406 Chanzo: Bodi ya Korosho Tanzania, 2022 NB: SG: Standard Grade UG: Under Grade Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 202 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 14 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 14 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 7 Habari Muhimu Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) Chanzo : Mamlaka ya Hali ya Hewa Tanzania | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Mei 16 - 20, 2022 Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Mei 09 - 13, 2022 Wiki hii Mei 16 - 20, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 71,000 201,300 187,700 118,900 112,400 167,200 70,800 Wiki iliyopita 65,400 200,800 184,800 124,500 137,700 181,400 75,300 Badiliko ▲7.9% ▲0.2% ▲1.5% ▼4.7% ▼22.5% ▼8.5% ▼6.4% Wastani wa Nchi Ujumbe Mkuu Mazao makuu ya chakula: Bei za jumla zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za mahindi, maharage na mchele zimeongezeka kwa asilimia 7.9, 1.5 na 0.2 mtawalia. Bei za uwele, ulezi, viazi mviringo na mtama zimeshuka kwa asilimia 22, 8.5, 6.4 na 4.7 mtawalia. Mboga na matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei ya tango imeongezeka kwa asilimia 4, wakati pilipili hoho, nanasi, nyanya na vitunguu zimepugua kwa asilimia 29, 25, 11 na 6 mtawalia, bei ya tikitimaji haijabadilika. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 18 Mei, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 8,673,030 zenye thamani ya Shilingi bilioni 40. Korosho: Hadi kufikia tarehe 05 Mei, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,199,729 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 19 Mei, 2022 wastani wa bei ya UREA na DAP katika soko la dunia umepungua kwa asilimia 0.4 na 0.5 katika soko la dunia ikilinganishwa na wiki iliyopita. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 74,800 203,300 197,000 65,200 66,500 149,000 76,800 Wiki iliyopita 72,300 198,800 194,600 63,300 66,500 148,800 76,800 Badiliko ▲3.3% ▲2.2% ▲1.2% ▲2.9% ►0.0% ▲0.1% ►0.0% Arusha Wiki hii 78,500 220,000 170,000 67,500 NA 139,500 87,500 Wiki iliyopita 77,500 225,000 170,000 67,500 NA 139,500 87,500 Badiliko ▲1.3% ▼2.3% ►0.0% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 89,800 217,500 222,500 130,000 97,500 175,000 60,800 Wiki iliyopita 76,300 222,500 230,000 130,000 105,000 207,500 62,800 Badiliko ▲15.0% ▼2.3% ▼3.4% ►0.0% ▼7.7% ▼18.6% ▼3.3% Lindi Wiki hii 90,000 225,000 225,000 145,000 NA 235,000 80,000 Wiki iliyopita 75,000 200,000 200,000 145,000 NA 225,000 77,500 Badiliko ▲16.7% ▲11.1% ▲11.1% ►0.0% ▲4.3% ▲3.1% Morogoro Wiki hii 62,500 215,000 185,000 175,000 175,000 177,500 82,500 Wiki iliyopita 62,500 215,000 207,500 175,000 175,000 177,500 97,500 Badiliko ►0.0% ►0.0% ▼12.2% ►0.0% ►0.0% ►0.0% ▼18.2% Tanga Wiki hii 79,300 190,000 195,000 100,000 100,000 183,000 65,000 Wiki iliyopita 71,800 205,000 185,000 100,000 100,000 188,800 75,000 Badiliko ▲9.5% ▼7.9% ▲5.1% ►0.0% ►0.0% ▼3.2% ▼15.4% Mtwara Wiki hii 65,000 210,000 177,500 NA NA 180,000 NA Wiki iliyopita 65,000 210,000 187,500 NA NA 180,000 NA Badiliko ►0.0% ►0.0% ▼5.6% ►0.0% Iringa Wiki hii 61,800 195,000 180,000 150,000 NA 180,000 55,000 Wiki iliyopita 58,500 195,000 175,000 150,000 NA 190,000 55,000 Badiliko ▲5.3% ►0.0% ▲2.8% ►0.0% ▼5.6% ►0.0% Ruvuma Wiki hii 50,000 190,000 170,000 NA NA NA 77,500 Wiki iliyopita 53,800 180,000 165,000 NA NA NA 77,500 Badiliko ▼7.6% ▲5.3% ▲2.9% ►0.0% Tabora Wiki hii 60,500 175,000 190,000 NA NA NA NA Wiki iliyopita 59,000 175,000 190,000 NA NA NA NA Badiliko ▲2.5% ►0.0% ►0.0% Rukwa Wiki hii 65,000 150,000 162,500 NA NA NA 67,500 Wiki iliyopita 57,500 165,000 142,500 NA NA NA 67,500 Badiliko ▲11.5% ▼10.0% ▲12.3% ►0.0% Shinyanga Wiki hii 66,300 196,300 175,300 92,500 87,500 115000 78,800 Wiki iliyopita 61,000 170,000 175,000 95,000 95,000 125,000 85,000 Badiliko ▲8.0% ▲13.4% ▲0.2% ▼2.7% ▼8.6% ▼8.7% ▼7.9% 3 Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. N/A: bei haikupatikana Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 81,000 215,000 210,000 160,000 170,000 170,000 87,500 Wiki iliyopita 79,500 215,000 217,500 160,000 170,000 180,000 100,000 Badiliko ▲1.9% ►0.0% ▼3.6% ►0.0% ►0.0% ▼5.9% ▼14.3% Manyara Wiki hii 74,500 205,000 165,000 110,000 90,000 155,000 72,500 Wiki iliyopita 74,500 205,000 165,000 90,000 90,000 155,000 80,000 Badiliko ►0.0% ►0.0% ►0.0% ▲18.2% ►0.0% ►0.0% ▼10.3% Kilimanjaro Wiki hii 85,000 210,000 NA 160,000 NA 160,000 NA Wiki iliyopita 62,500 215,000 207,500 175,000 175,000 177,500 97,500 Badiliko ▲26.5% ▼2.4% ▼9.4% ▼10.9% Katavi Wiki hii 51,000 170,000 180,000 190,000 NA 190,000 57,500 Wiki iliyopita 47,000 165,000 167,500 190,000 NA 190,000 57,500 Badiliko ▲7.8% ▲2.9% ▲6.9% ►0.0% ►0.0% ►0.0% Mbeya Wiki hii 72,000 235,000 198,000 NA NA 132,000 42,000 Wiki iliyopita 36,000 250,000 156,000 NA NA 132,000 42,000 Badiliko ▲50.0% ▼6.4% ▲21.2% ►0.0% ►0.0% 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 12- 18 Mei, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 57,200 211,200 741 689 72,600 69,667 Mombasa 53,350 176,458 660 60,500 71,500 Zanzibar 43,750 277,500 775 825 115,000 70,000 Dar es Salaam 43,000 242,500 440 400 70,833 120,000 Morogoro 270,000 500 800 41,667 Dodoma 20,000 287,500 238 825 36,667 63,750 Shinyanga 40,000 166,667 500 625 25,000 60,000 Mwanza 32,500 233,333 675 1,125 25,000 37,500 Arusha 45,000 214,583 650 750 37,500 82,500 Tanga 46,250 245,000 675 1,000 41,250 75,000 Lindi 45,000 214,583 650 750 37,500 82,500 Mtwara 48,333 210,000 500 700 100,000 100,000 Mbeya 37,000 128,889 597 1,383 49,333 122,667 Wastani wiki hii 42,615 221,401 585 823 54,835 79,590 Wastani wiki iliyopita 47,849 234,799 584 1,096 77,004 76,500 Badiliko ▼11% ▼ 6% 0 ► ▼25% ▼29% ▲4% Source: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 18 Mei, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 6,624,490 1,551,890 518,790 8,673,030 4,744.71 40,432,882,120 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 05 Aprili, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 731,287 1,700 1,610 1,250 1,200 1,161,922,010 CEAMCU 23,714 1,610 38,179,540.00 JUMLA YA MAUZO YOTE 231,199,729 2,445 1,500 1,755 1,200 489,121,150,946 Chanzo: Bodi ya Korosho Tanzania, 2022 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des – Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei – Des Feb- Machi Tangawizi Aprili- Julai Machi – Aug Des- Feb Chanzo: TAHA, 2022 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 19 Mei, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 19 Mei, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 1000.009 Sep 202123 Sep 202107 Oct 202121 Oct 202104 Nov 202118 Nov 202102 Dec 202116 Dec 202130 Dec 202113 Jan 202227 Jan 202210 Feb 202224 Feb 202210 Mar 202224 Mar 202207 Apr 202221 Apr 202205 May 202219 May 2022 Bei (Dola za Marekani/Tani) Kipindi 0.0 200.0 400.0 600.0 800.0 1000.0 1200.0 1400.0 09 Dec 2021 16 Dec 2021 23 Dec 2021 30 Dec 2021 06 Jan 2022 13 Jan 2022 20 Jan 2022 27 Jan 2022 03 Feb 2022 10 Feb 2022 17 Feb 2022 24 Feb 2022 03 Mar 2022 10 Mar 2022 17 Mar 2022 24 Mar 2022 31 Mar 2022 07 Apr 2022 14 Apr 2022 21 Apr 2022 28 Apr 2022 05 May 2022 12 May 2022 19 May 2022 Bei (Dola za Kimarekani/Tani) Kipindi 7 Habari Muhimu Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Aprili 19 - 22, 2022 Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Apr 11 - 15, 2022 Wiki hii Apr 19 - 22, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 61,900 188,700 184,600 118,300 117,900 169,300 75,000 Wiki iliyopita 61,100 186,900 184,700 118,300 117,900 168,900 76,700 Badiliko ▲1.3% ▲1.0% ▼0.1% ►0.0% ►0.0% ▲0.2% ▼2.3% Wastani wa Nchi Ujumbe Mkuu Mazao makuu ya chakula: Bei za jumla zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za mahindi, mchele na ulezi zimeongezeka kwa asilimia 1.3, 1.0 na 0.2 mtawalia, bei za viazi mviringo na maharage zimeshuka kwa asilimia 2.3 na 0.1 mtawalia wakati bei za mtama na uwele hazijabadilika. Mboga na matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za tango na vitunguu zimeongezeka kwa asilimia 5 na 1 mtawalia wakati bei za pilipilihoho, tikitimaji, nyanya na nanasi zimepungua kwa asilimia 13, 4, 1 na 1 mtawalia. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 18 Aprili, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 7,931,170 zenye thamani ya Shilingi bilioni 37. Korosho: Hadi kufikia tarehe 27 Machi, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,155,915 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 21 Aprili, 2022 wastani wa bei ya UREA katika soko la dunia umeongezeka kwa asilimia 0.2, wastani wa bei ya DAP katika soko la dunia umeshika kwa asilimia 0.5. Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaoanza Novemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 65,300 188,300 185,000 68,500 66,000 137,300 76,800 Wiki iliyopita 67,600 188,300 185,000 68,500 66,000 137,300 75,800 Badiliko ▼3.5% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲1.3% Arusha Wiki hii 76,500 225,000 170,000 63,500 69,000 144,000 87,500 Wiki iliyopita 73,000 210,000 170,000 63,500 69,000 144,000 87,500 Badiliko ▲4.6% ▲6.7% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 75,300 212,500 232,500 110,000 90,000 170,000 64,400 Wiki iliyopita 75,300 206,300 230,000 110,000 90,000 170,000 67,200 Badiliko ►0.0% ▲2.9% ▲1.1% ►0.0% ►0.0% ►0.0% ▼4.3% Lindi Wiki hii 70,000 200,000 200,000 200,000 NA 200,000 70,000 Wiki iliyopita 67,500 197,500 200,000 200,000 NA 200,000 85,000 Badiliko ▲3.6% ▲1.3% ►0.0% ►0.0% ►0.0% ▼21.4% Morogoro Wiki hii 63,600 214,000 199,000 175,000 175,000 175,000 97,500 Wiki iliyopita 57,500 214,000 205,000 175,000 175,000 175,000 97,500 Badiliko ▲9.6% ►0.0% ▼3.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 58,200 190,000 185,000 100,000 100,000 175,000 90,000 Wiki iliyopita 58,200 190,000 195,000 100,000 100,000 170,000 90,000 Badiliko ►0.0% ►0.0% ▼5.4% ►0.0% ►0.0% ▲2.9% ►0.0% Mtwara Wiki hii 55,000 190,000 205,000 NA NA 180,000 NA Wiki iliyopita 55,000 190,000 205,000 NA NA 180,000 NA Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Iringa Wiki hii 50,000 195,000 200,000 110,000 NA 150,000 55,000 Wiki iliyopita 50,000 195,000 200,000 110,000 NA 150,000 55,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tabora Wiki hii 59,000 160,000 190,000 NA NA NA NA Wiki iliyopita 59,000 160,000 190,000 NA NA NA NA Badiliko ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 55,000 165,000 170,000 NA NA NA 55,000 Wiki iliyopita 55,000 165,000 170,000 NA NA NA 55,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Kigoma Wiki hii 53,000 180,000 110,000 100,000 125,000 190,000 90,000 Wiki iliyopita 53,000 180,000 110,000 100,000 125,000 190,000 90,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Shinyanga Wiki hii 57,500 170,000 175,000 95,000 95,000 NA 67,500 Wiki iliyopita 57,500 170,000 175,000 95,000 95,000 NA 67,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 3 Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: ✓ Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. ✓ N/A: bei haikupatikana Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Wiki iliyopita 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 57,500 185,000 150,000 130,000 130,000 140,000 67,500 Wiki iliyopita 57,500 185,000 150,000 130,000 130,000 140,000 74,400 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼10.2% Mara Wiki hii 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Wiki iliyopita 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 71,500 200,000 171,000 90,000 90,000 155,000 100,000 Wiki iliyopita 66,000 190,000 159,000 90,000 90,000 155,000 105,000 Badiliko ▲7.7% ▲5.0% ▲7.0% ►0.0% ►0.0% ►0.0% ▼5.0% Njombe Wiki hii 58,000 225,000 185,000 NA NA 162,500 48,300 Wiki iliyopita 58,000 225,000 185,000 NA NA 162,500 48,300 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kilimanjaro Wiki hii 67,500 180,000 185,000 120,000 120,000 NA 70,000 Wiki iliyopita 67,500 180,000 185,000 120,000 120,000 NA 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 52,500 165,000 167,500 190,000 NA 190,000 57,500 Wiki iliyopita 52,500 165,000 167,500 190,000 NA 190,000 57,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 15 hadi 20 Aprili, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 61,600 228,800 836 726 83,600 55,000 Mombasa 63,800 247,500 660 55,000 110,000 Dar es salaam 50,000 330,000 400 400 36,667 120,000 Morogoro 52,500 280,000 500 800 43,750 Dodoma 33,333 300,000 400 783 36,667 60,000 Shinyanga 35,000 208,333 500 500 29,167 60,000 Mwanza 33,333 261,111 617 1,017 26,000 45,333 Arusha 50,000 218,750 650 675 37,500 52,500 Tanga 44,500 212,500 675 700 36,250 72,500 Lindi 50,000 218,750 650 675 37,500 52,500 Mtwara 50,000 275,000 400 700 100,000 90,000 Mbeya 45,000 225,000 877 1,767 51,000 118,667 Wastani wiki hii 47,422 250,479 597 795 47,758 76,045 Wastani wiki iliyopita 48,114 249,136 624 800 54,637 72,590 Badiliko ▼1% ▲1% ▼4% ▼1% ▼13% ▲5% Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 18 Aprili, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 5,989,450 1,429,510 512,210 7,931,170 4,753.63 37,157,883,470 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 27 Machi, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 711,187 1,700 1,610 1,250 1,200 1,137,802,010 JUMLA YA MAUZO YOTE 231,155,915 2,445 1,500 1,755 1,200 489,058,851,406 Chanzo: Bodi ya Korosho Tanzania, 2022 NB: SG: Standard Grade UG: Under Grade Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 2022 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 21 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 21 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 0.0 200.0 400.0 600.0 800.0 1,000.0 1,200.0 1,400.006 May 202120 May 202103 Jun 202117 Jun 202101 Jul 202115 Jul 202129 Jul 202112 Aug 202126 Aug 202109 Sep 202123 Sep 202107 Oct 202121 Oct 202104 Nov 202118 Nov 202102 Dec 202116 Dec 202130 Dec 202113 Jan 202227 Jan 202210 Feb 202224 Feb 202210 Mar 202224 Mar 202207 Apr 202221 Apr 2022 Bei (Dola za Marekani/Tani) Kipindi 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 1,000.006 May 202120 May 202103 Jun 202117 Jun 202101 Jul 202115 Jul 202129 Jul 202112 Aug 202126 Aug 202109 Sep 202123 Sep 202107 Oct 202121 Oct 202104 Nov 202118 Nov 202102 Dec 202116 Dec 202130 Dec 202113 Jan 202227 Jan 202210 Feb 202224 Feb 202210 Mar 202224 Mar 202207 Apr 202221 Apr 2022 Bei (Dola za Marekani/Tani) Kipindi 7 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- ❖ USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo ❖ Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Aprili 25 - 29, 2022 Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Apr 19 - 22, 2022 Wiki hii Apr 25 - 29, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 65,600 188,600 185,200 119,000 119,400 170,300 72,800 Wiki iliyopita 61,900 188,700 184,600 118,300 117,900 169,300 75,000 Badiliko ▲5.6% ▼0.1% ▲0.3% ▲0.6% ▲1.3% ▲0.6% ▼3.0% Wastani wa Nchi Ujumbe Mkuu Mazao makuu ya chakula: Bei za jumla zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za mahindi, uwele, mtama, ulezi na maharage zimeongezeka kwa asilimia 5.6, 1.3, 0.6, 0.6, na o.3 mtawalia, bei za viazi mviringo na mchele zimeshuka kwa asilimia 3.0 na 0.1 mtawalia. Mboga na matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za tango na vitunguu zimeongezeka kwa asilimia 5 na 1 mtawalia wakati bei za pilipilihoho, tikitimaji, nyanya na nanasi zimepungua kwa asilimia 13, 4, 1 na 1 mtawalia. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 25 Aprili, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 8,125,420 zenye thamani ya Shilingi bilioni 38. Korosho: Hadi kufikia tarehe 27 Machi, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,155,915 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 28 Aprili, 2022 wastani wa bei ya UREA katika soko la dunia umepungua kwa asilimia 0.1, wastani wa bei ya DAP katika soko la dunia umeshika kwa asilimia 0.04 ikilinganishwa na wiki iliyopita. Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaoanza Novemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 66,500 190,100 185,600 68,600 66,000 141,800 77,000 Wiki iliyopita 65,300 188,300 185,000 68,500 66,000 137,300 76,800 Badiliko ▲1.8% ▲0.9% ▲0.3% ▲0.1% ►0.0% ▲3.2% ▲0.3% Arusha Wiki hii 76,500 225,000 170,000 63,500 69,000 139,500 87,500 Wiki iliyopita 76,500 225,000 170,000 63,500 69,000 144,000 87,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼3.2% ►0.0% Dar es Salaam Wiki hii 82,800 212,500 237,500 115,000 102,500 185,000 57,600 Wiki iliyopita 75,300 212,500 232,500 110,000 90,000 170,000 64,400 Badiliko ▲9.1% ►0.0% ▲2.1% ▲4.3% ▲12.2% ▲8.1% ▼11.8% Lindi Wiki hii 70,000 200,000 200,000 200,000 NA 200,000 70,000 Wiki iliyopita 70,000 200,000 200,000 200,000 NA 200,000 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Morogoro Wiki hii 64,000 199,000 195,000 175,000 175,000 172,500 95,000 Wiki iliyopita 63,600 214,000 199,000 175,000 175,000 175,000 97,500 Badiliko ▲0.6% ▼7.5% ▼2.1% ►0.0% ►0.0% ▼1.4% ▼2.6% Tanga Wiki hii 64,500 205,000 185,000 100,000 100,000 175,000 65,000 Wiki iliyopita 58,200 190,000 185,000 100,000 100,000 175,000 90,000 Badiliko ▲9.8% ▲7.3% ►0.0% ►0.0% ►0.0% ►0.0% ▼38.5% Mtwara Wiki hii 60,000 192,500 191,300 NA NA 180,000 NA Wiki iliyopita 55,000 190,000 205,000 NA NA 180,000 NA Badiliko ▲8.3% ▲1.3% ▼7.2% ►0.0% Iringa Wiki hii 61,000 175,000 195,000 110,000 NA 150,000 55,000 Wiki iliyopita 50,000 195,000 200,000 110,000 NA 150,000 55,000 Badiliko ▲18.0% ▼11.4% ▼2.6% ►0.0% ►0.0% ►0.0% Tabora Wiki hii 59,000 167,500 190,000 NA NA NA NA Wiki iliyopita 59,000 160,000 190,000 NA NA NA NA Badiliko ►0.0% ▲4.5% ►0.0% Rukwa Wiki hii 55,000 165,000 170,000 NA NA NA 55,000 Wiki iliyopita 55,000 165,000 170,000 NA NA NA 55,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Kigoma Wiki hii 58,400 185,000 138,800 105,000 122,500 182,500 87,500 Wiki iliyopita 53,000 180,000 110,000 100,000 125,000 190,000 90,000 Badiliko ▲9.2% ▲2.7% ▲20.7% ▲4.8% ▼2.0% ▼4.1% ▼2.9% Shinyanga Wiki hii 57,500 170,000 175,000 95,000 95,000 NA 67,500 Wiki iliyopita 57,500 170,000 175,000 95,000 95,000 NA 67,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 3 Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: ✓ Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. ✓ N/A: bei haikupatikana Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Wiki iliyopita 65,000 190,000 200,000 160,000 165,000 180,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 67,500 187,500 155,000 130,000 137,500 150,000 67,500 Wiki iliyopita 57,500 185,000 150,000 130,000 130,000 140,000 67,500 Badiliko ▲14.8% ▲1.3% ▲3.2% ►0.0% ▲5.5% ▲6.7% ►0.0% Mara Wiki hii 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Wiki iliyopita 65,000 150,000 227,500 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 81,000 200,000 165,000 90,000 90,000 155,000 100,000 Wiki iliyopita 71,500 200,000 171,000 90,000 90,000 155,000 100,000 Badiliko ▲11.7% ►0.0% ▼3.6% ►0.0% ►0.0% ►0.0% ►0.0% Njombe Wiki hii 58,000 225,000 185,000 NA NA 162,500 48,300 Wiki iliyopita 58,000 225,000 185,000 NA NA 162,500 48,300 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kilimanjaro Wiki hii 76,300 180,000 185,000 120,000 120,000 NA 70,000 Wiki iliyopita 67,500 180,000 185,000 120,000 120,000 NA 70,000 Badiliko ▲11.5% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 58,800 165,000 167,500 190,000 NA 190,000 57,500 Wiki iliyopita 52,500 165,000 167,500 190,000 NA 190,000 57,500 Badiliko ▲10.7% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 15 hadi 20 Aprili, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 61,600 228,800 836 726 83,600 55,000 Mombasa 63,800 247,500 660 55,000 110,000 Dar es salaam 50,000 330,000 400 400 36,667 120,000 Morogoro 52,500 280,000 500 800 43,750 Dodoma 33,333 300,000 400 783 36,667 60,000 Shinyanga 35,000 208,333 500 500 29,167 60,000 Mwanza 33,333 261,111 617 1,017 26,000 45,333 Arusha 50,000 218,750 650 675 37,500 52,500 Tanga 44,500 212,500 675 700 36,250 72,500 Lindi 50,000 218,750 650 675 37,500 52,500 Mtwara 50,000 275,000 400 700 100,000 90,000 Mbeya 45,000 225,000 877 1,767 51,000 118,667 Wastani wiki hii 47,422 250,479 597 795 47,758 76,045 Wastani wiki iliyopita 48,114 249,136 624 800 54,637 72,590 Badiliko ▼1% ▲1% ▼4% ▼1% ▼13% ▲5% Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 25 Aprili, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 6,157,800 1,454,700 512,910 8,125,420 4,744.71 38,028,123,470 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 27 Machi, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 711,187 1,700 1,610 1,250 1,200 1,137,802,010 JUMLA YA MAUZO YOTE 231,155,915 2,445 1,500 1,755 1,200 489,058,851,406 Chanzo: Bodi ya Korosho Tanzania, 2022 NB: SG: Standard Grade UG: Under Grade Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 2022 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 28 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 28 Aprili, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 0 100 200 300 400 500 600 700 80022 Jul 202105 Aug 202119 Aug 202102 Sep 202116 Sep 202130 Sep 202114 Oct 202128 Oct 202111 Nov 202125 Nov 202109 Dec 202123 Dec 202106 Jan 202220 Jan 202203 Feb 202217 Feb 202203 Mar 202217 Mar 202231 Mar 202214 Apr 202228 Apr 2022 Bei (Dora za Marekani/T) Kipindi 0 200 400 600 800 100008 Jul 202122 Jul 202105 Aug 202119 Aug 202102 Sep 202116 Sep 202130 Sep 202114 Oct 202128 Oct 202111 Nov 202125 Nov 202109 Dec 202123 Dec 202106 Jan 202220 Jan 202203 Feb 202217 Feb 202203 Mar 202217 Mar 202231 Mar 202214 Apr 202228 Apr 2022 Bei (Dora za Marekani/T) Kipindi 7 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- ❖ USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo ❖ Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Machi 28 – Aprili 1, 2022 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Wiki iliyopita Mar 21 - 25, 2022 Wiki hii Mar 28 - Apr 1, 2022 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 62,500 185,600 186,800 120,400 118,800 167,100 79,400 Wiki iliyopita 60,600 188,300 185,500 120,400 113,400 165,100 76,700 Badiliko ▲3.0% ▼1.5% ▲0.7% ►0.0% ▲4.5% ▲1.2% ▲3.4% Wastani wa Nchi Ujumbe Mkuu Kwa wiki hii, wastani wa bei za mazao makuu ya chakula zimeongezeka na kushuka kwa viwango tofauti ikilinganishwa na viwango vya wastani wa bei wiki iliyopita. Bei za uwele, viazi mviringo, mahindi, ulezi na maharagwe zimeongezeka kwa asilimia 4.5, 3.4, 3.0, 1.2 na 0.7 mtawalia. Bei za mchele zimeshuka kwa asilimia 1.5, bei za mtama hazijabadilika. Kahawa safi: Hadi kufikia tarehe 30 Machi, 2022 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 63,904,458 zenye thamani ya Dola za Marekani milioni 196. Kakao: Hadi kufikia tarehe 28 Machi, 2022 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 7,502,070 zenye thamani ya Shilingi bilioni 35. Korosho: Hadi kufikia tarehe 27 Machi, 2022 korosho iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 231,155,915 zenye thamani ya Shilingi bilioni 489. Mbolea: Hadi kufikia tarehe 31 Machi, 2022 wastani wa bei ya DAP katika soko la dunia umeongezeka kwa asilimia 3, wastani wa bei ya UREA umepungua kwa asilimia 0.5 ikilinganishwa na bei za wiki iliyopita. Vita inayoendelea kati ya Urusi na Ukraine na athari za UVIKO-19, kwa pamoja zimechangia kupanda kwa bei ya mbolea katika soko la dunia. Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaoanza Novemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 53,300 187,000 187,500 63,300 66,000 137,300 93,100 Wiki iliyopita 51,800 187,000 187,000 62,900 66,000 138,500 81,800 Badiliko ▲2.8% ►0.0% ▲0.3% ▲0.6% ►0.0% ▼0.9% ▲12.1% Arusha Wiki hii 61,000 210,000 175,000 62,500 69,000 138,500 95,000 Wiki iliyopita 59,500 210,000 175,000 62,500 67,500 138,500 82,500 Badiliko ▲2.5% ►0.0% ►0.0% ►0.0% ▲2.2% ►0.0% ▲13.2% Dar es Salaam Wiki hii 79,000 210,000 230,000 110,000 85,000 170,000 61,300 Wiki iliyopita 67,000 205,000 235,000 110,000 80,000 170,000 61,900 Badiliko ▲15.2% ▲2.4% ▼2.2% ►0.0% ▲5.9% ►0.0% ▼1.0% Lindi Wiki hii 75,000 205,000 195,000 175,000 NA 180,000 92,500 Wiki iliyopita 75,000 205,000 195,000 175,000 NA 180,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Morogoro Wiki hii 58,800 198,500 195,000 175,000 175,000 172,500 92,500 Wiki iliyopita 58,800 198,500 195,000 175,000 175,000 172,500 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 77,500 190,000 195,000 100,000 110,000 170,000 87,800 Wiki iliyopita 65,000 190,000 195,000 100,000 110,000 170,000 85,600 Badiliko ▲16.1% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲2.5% Mtwara Wiki hii 55,000 190,000 205,000 NA NA 180,000 NA Wiki iliyopita 55,000 190,000 205,000 NA NA 180,000 NA Badiliko ►0.0% ►0.0% ►0.0% ►0.0% Iringa Wiki hii 49,000 210,000 205,000 110,000 NA 150,000 56,300 Wiki iliyopita 47,000 205,000 205,000 110,000 NA 150,000 56,300 Badiliko ▲4.1% ▲2.4% ►0.0% ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 55000 165000 170000 NA NA NA 55000 Wiki iliyopita 54,300 167,500 173,800 NA NA NA 62,500 Badiliko ▲1.3% ▼1.5% ▼2.2% ▼13.6% Kigoma Wiki hii 61,000 170,000 110,000 90,000 125,000 190,000 100,000 Wiki iliyopita 61,000 170,000 110,000 90,000 125,000 190,000 100,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Shinyanga Wiki hii 57500 170000 175000 95000 95000 NA 67500 Wiki iliyopita NA NA NA NA NA NA NA Badiliko 3 Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 69,000 177,500 192,500 150,000 170,000 180,000 92,500 Wiki iliyopita 69,000 177,500 192,500 150,000 170,000 180,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 56,500 167,500 150,000 130,000 130,000 140,000 62,500 Wiki iliyopita 56,500 167,500 150,000 130,000 130,000 140,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Mara Wiki hii 65000 150000 227500 62500 190000 190000 92500 Wiki iliyopita NA NA NA NA NA NA NA Badiliko Manyara Wiki hii 63,300 190,000 159,000 90,000 90,000 155,000 105,000 Wiki iliyopita 60,000 190,000 159,000 90,000 90,000 150,000 85,000 Badiliko ▲5.2% ►0.0% ►0.0% ►0.0% ►0.0% ▲3.2% ▲19.0% Njombe Wiki hii 58,000 220,000 185,000 NA NA 162,500 50,500 Wiki iliyopita 58,000 220,000 185,000 NA NA 162,500 50,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kilimanjaro Wiki hii 67,500 180,000 185,000 120,000 120,000 NA 70,000 Wiki iliyopita 67,500 180,000 185,000 120,000 120,000 NA 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 64,000 150,000 220,000 190,000 NA 190,000 75,000 Wiki iliyopita 64,000 150,000 220,000 190,000 NA 190,000 75,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Chanzo: Wizara ya Uwekezaji, Viwanda na Biashara Zingatia: ✓ Bei hizi ni wastani wa bei za jumla katika soko kuu la mkoa husika. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. ✓ N/A: bei haikupatikana 4 Jedwali 3: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 25 hadi 30 Machi, 2022 Mkoa Nyanya (Kreti 40Kg) Vitunguu (Gunia 100Kg) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (Gunia 50Kg) Tango (Gunia 100Kg) Nairobi 44,000 206,800 748 660 90,933 46,200 Mombasa 45,467 261,250 660 62,333 117,333 Dar es salaam 43,250 322,500 400 400 60,417 152,500 Morogoro 36,000 293,333 500 733 41,667 67,778 Dodoma 40,000 300,000 367 600 25,833 57,778 Shinyanga 30,000 179,167 625 500 27,083 55,000 Mwanza 36,000 233,333 533 917 26,667 50,000 Arusha 48,333 247,222 733 567 36,667 51,667 Tanga 35,000 188,750 525 675 32,500 77,500 Lindi 48,333 247,222 733 567 36,667 51,667 Mtwara 86,667 250,000 400 533 83,333 75,000 Mbeya 44,000 242,917 1,250 1,313 46,000 120,500 Wastani 44,754 247,708 623 679 47,508 76,910 Chanzo: TAHA, 2022 Jedwali 4: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 30 Machi, 2022 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 17,443,712 66,463,399 18,813,020 83,588,763 73,283 244,327.36 36,330,015 150,296,489 Arabika ngumu 15,760 38,814 665,385 1,446,056 5,400 4,320.00 686,545 1,489,190 Robusta 1,243,294 2,732,643 25,314,488 411,110,040 330,116 475,323.49 26,887,898 44,318,007 Jumla 18,702,766 69,234,856 44,792,893 126,144,856 408,799 723,970.85 63,904,458 196,108,686 Chanzo: Bodi ya Kahawa Tanzania, 2022 5 Jedwali 5: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 28 Machi, 2022 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 5,614,040 1,385,060 502,970 7,502,070 4,763.58 35,225,557,130 Chanzo: Tume ya Maendeleo ya Ushirika, 2022 Jedwali 6: Mauzo ya korosho kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 27 Machi, 2022 CHAMA KIASI KILICHOUZWA (KG) BEI YA JUU (TSH/KG) SG BEI YA CHINI (TSH/KG) SG BEI YA JUU (TSH/KG) UG BEI YA CHINI (TSH/KG) UG THAMANI (Shilingi) TANECU 56,897,028 2,445 1,615 1,705 1,305 122,053,954,954 MAMCU 69,065,290 2,400 1,350 1,715 1,200 147,755,070,189 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 46,372,299 2,352 1,400 102,113,318,103 CORECU 13,272,882 2,060 1,900 1,755 1,320 25,015,289,408 TAMCU 25,284,493 2,267 1,700 50,534,029,863 MOFACU 137,080 2,270 1,850 292,763,930 TACACU 711,187 1,700 1,610 1,250 1,200 1,137,802,010 JUMLA YA MAUZO YOTE 231,155,915 2,445 1,500 1,755 1,200 489,058,851,406 Chanzo: Bodi ya Korosho Tanzania, 2022 NB: SG: Standard Grade UG: Under Grade Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 202 6 Kielelezo 1: Mwenendo wa Wastani wa bei ya Mbolea aina ya DAP katika soko la dunia hadi kufikia tarehe 31 Machi, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 7 Kielelezo 2: Mwenendo wa Wastani wa bei ya mbolea aina ya UREA katika soko la dunia hadi kufikia tarehe 31 Machi, 2022 Chanzo: Mamlaka ya Mbolea Tanzania, 2022 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa huduma za masoko kwa wakulima na wafanyabiashara kupitia simu zao za mkononi, jinsi ya kupata huduma ;- ❖ USSD: Piga * 152*00# chagua Na. 7 kisha Na. 2 halafu fuata maelekezo ❖ Tovuti: fungua exts.kilimo.go.tz kisha chagua huduma Kwa maelezo zaidi wasiliana na: Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) Chanzo : Mamlaka ya Hali ya Hewa Tanzania | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao Desemba 27-31, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Jedwali 1: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Ujumbe Mkuu Kwa wiki hii, wastani wa bei za mazao makuu ya chakula zimeongezeka kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Bei za mahindi, mchele, viazi mviringo, ulezi na mtama zimeongezeka kwa wastani wa asilimia 8.7, 6.1, 5.3, 0.3 na 0.3 mtawalia. Kwa upande mwingine bei ya uwele na maharage zimepungia kwa asilimia 11.5 na 0.3 mtawalia. Kahawa safi: Hadi kufikia tarehe 13 Desemba, 2021 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 50,583,600 zenye thamani ya Dola za Marekani million 143. Kakao: Hadi kufikia tarehe 29 Desemba, 2021 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 6,367,830 zenye thamani ya Shilingi bilioni 30. Korosho: Hadi kufikia tarehe 24 Desemba, 2021 korosho iliyouzwa kwa msimu wa mauzo 2021/22 ni kilo 220,276,691 zenye thamani ya Shilingi bilioni 470. Mbolea: Hadi kufikia tarehe 23 Desemba, 2021 wastani wa bei za UREA na DAP katika soko la Dunia umepungua kwa asilimia 8.6 na 0.4 mtawalia ikilinganishwa na wastani wa bei kwa wiki iliyopita (kielelezo 1 na kielelezo 2). Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaoanza Novemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. Wiki iliyopita Dec 20-24 Wiki hii Dec 27-31 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 65,300 179,200 183,900 114,600 110,900 166,500 76,000 Wiki iliyopita 59,600 168,300 184,500 114,300 123,700 166,000 72,000 Badiliko ▲8.7% ▲6.1% ▼0.3% ▲0.3% ▼11.5% ▲0.3% ▲5.3% Wastani wa Nchi 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 59,700 197,500 198,800 56,600 54,300 140,000 63,600 Wiki iliyopita 57,400 168,300 213,800 56,800 54,300 140,000 55,400 Badiliko ▲3.9% ▲14.8% ▼7.5% ▼0.4% ►0.0% ►0.0% ▲12.9% Arusha Wiki hii 65,500 205,000 157,500 59,000 72,500 129,000 72,500 Wiki iliyopita 64,800 202,500 157,500 59,000 72,500 129,000 72,500 Badiliko ▲1.1% ▲1.2% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 64,000 185,000 220,000 65,000 72,500 160,000 78,100 Wiki iliyopita 64,000 180,000 220,000 65,000 72,500 160,000 62,500 Badiliko ►0.0% ▲2.7% ►0.0% ►0.0% ►0.0% ►0.0% ▲20.0% Lindi Wiki hii 90,000 177,500 225,000 175,000 180,000 215,000 100,000 Wiki iliyopita 95,000 175,000 225,000 175,000 240,000 227,500 100,000 Badiliko ▼5.6% ▲1.4% ►0.0% ►0.0% ▼33.3% ▼5.8% ►0.0% Morogoro Wiki hii 64,500 177,500 187,500 150,000 150,000 155,000 81,000 Wiki iliyopita 60,500 172,500 190,000 150,000 150,000 157,500 80,500 Badiliko ▲6.2% ▲2.8% ▼1.3% ►0.0% ►0.0% ▼1.6% ▲0.6% Tanga Wiki hii 68,300 165,000 177,500 95,000 80,000 170,000 80,000 Wiki iliyopita 66,700 167,500 177,500 95,000 80,000 170,000 70,000 Badiliko ▲2.3% ▼1.5% ►0.0% ►0.0% ►0.0% ►0.0% ▲12.5% Mtwara Wiki hii 68,000 170,000 185,000 NA NA 180,000 75,000 Wiki iliyopita 45,000 170,000 177,500 120,000 NA 180,000 70,000 Badiliko ▲33.8% ►0.0% ▲4.1% ►0.0% ►0.0% ▲6.7% Iringa Wiki hii 57,500 180,000 160,000 110,000 NA 150,000 75,000 Wiki iliyopita 57,500 177,500 160,000 110,000 NA 150,000 60,000 Badiliko ►0.0% ▲1.4% ►0.0% ►0.0% ►0.0% ▲20.0% Ruvuma Wiki hii 53,800 180,000 162,500 NA NA NA 75,000 Wiki iliyopita 52,500 180,000 162,500 NA NA NA 75,000 Badiliko ▲2.4% ►0.0% ►0.0% ►0.0% 3 Zingatia: ✓ Bei hizi ni wastani wa bei za jumla katika masoko. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko ya bei. ✓ N/A: bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Mwanza Wiki hii 78,500 205,000 220,000 185,000 200,000 200,000 100,000 Wiki iliyopita 74,000 207,500 225,000 185,000 200,000 200,000 90,000 Badiliko ▲5.7% ▼1.2% ▼2.3% ►0.0% ►0.0% ►0.0% ▲10.0% Kagera Wiki hii 70,000 165,000 125,000 100,000 110,000 165,000 64,700 Wiki iliyopita 70,000 162,500 125,000 100,000 110,000 165,000 57,500 Badiliko ►0.0% ▲1.5% ►0.0% ►0.0% ►0.0% ►0.0% ▲11.1% Manyara Wiki hii 62,500 175,000 159,000 70,000 70,000 150,000 85,000 Wiki iliyopita 59,000 175,000 159,000 70,000 70,000 150,000 90,000 Badiliko ▲5.6% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼5.9% Njombe Wiki hii 52,500 175,000 175,000 NA NA 160,000 56,600 Wiki iliyopita 50,000 175,000 175,000 NA NA 160,000 45,300 Badiliko ▲4.8% ►0.0% ►0.0% ►0.0% ▲20.0% Kilimanjaro Wiki hii 60,000 180,000 185,000 120,000 120,000 NA 70,000 Wiki iliyopita 60,000 180,000 185,000 120,000 120,000 NA 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Katavi Wiki hii 64,000 150,000 220,000 190,000 NA 190,000 63,100 Wiki iliyopita 48,000 145,000 220,000 190,000 NA 190,000 57,500 Badiliko ▲25.0% ▲3.3% ►0.0% ►0.0% ►0.0% ▲8.9% Kigoma Wiki hii 62,500 159,000 135,000 90,000 100,000 150,000 81,300 Wiki iliyopita 61,500 159,000 110,000 100,000 100,000 180,000 65,000 Badiliko ▲1.6% ►0.0% ▲18.5% ▼11.1% ►0.0% ▼20.0% ▲20.0% 4 Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Bei za jumla 1,820.88 1950.95 487.74 520.25 Bei za rejareja 1,950.95 2,276.11 845.41 910.44 Chanzo: https://farmgainafrica.org/ Tarehe 31 Desemba, 2021 Jedwali 4: Wastani wa Bei (TZS) za mazao ya Horticulture katika masoko mbalimbali kwa wiki ya tarehe 9-15 Desemba, 2021 Nyanya Vitunguu Tikitimaji Nanasi Pilipili hoho Tango Mkoa Nyanya (40 Kg Crate) Vitunguu (100 Kg Sack) Tikitimaji (Kilo) Nanasi (Kilo) Pilipili hoho (50 Kg Sack) Tango (100 Kg Sack) Nairobi 46,200 176,000 616 550 33,000 88,000 Mombasa 48,400 154,000 660 44,000 88,000 Zanzibar 40,000 200,000 700 600 32,500 65,000 Dar es salaam 42,500 220,000 325 250 50,000 120,000 Morogoro 55,000 170,000 475 1,000 41,667 70,833 Dodoma 40,000 180,000 300 275 33,333 60,000 Shinyanga 35,000 208,333 800 500 29,167 40,000 Mwanza 30,000 225,000 500 800 18,000 30,000 Arusha 41,000 200,000 515 500 27,500 55,000 Tanga 43,333 170,000 567 533 35,000 66,667 Lindi 45,000 172,917 700 550 37,500 52,500 Mtwara 42,500 166,667 500 400 75,000 90,000 Mbeya 50,000 105,000 615 840 53,000 107,000 Average 42,995 180,609 559 567 39,205 71,769 Chanzo: TAHA, 2021 5 Jedwali 5: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 13 Desemba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 15,269,311 57,577,564 10,804,230 45,976,523 31,536 114,494.50 26,105,077 103,668,581.07 Arabika Ngumu - - 192,865 493,286 - - 192,865 493,285.82 Robusta 848,920 1,869,678 23,151,562 36,726,395 285,176 408,441.68 24,285,658 39,004,514.60 Jumla 16,118,231 59,447,242 34,148,657 83,196,204 316,712 522,936.18 50,583,600 143,166,381.49 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 6: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 29 Desemba, 2021 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 4,616,650.00 1,278,240 472,940 6,367,830.00 4,981.79 30,135,229,660.00 Chanzo: Tume ya Maendeleo ya Ushirika, 2021 Jedwali 7: Mauzo ya korosho kwa msimu wa mwaka 2021/22 hadi kufikia tarehe 24 Desemba, 2021. CHAMA KIASI KILICHOUZWA BEI YA JUU YA SG BEI YA CHINI YA SG BEI YA JUU YA UG BEI YA CHINI YA UG THAMANI (Shilingi) TANECU 54,795,617 2,445 1,670 1,705 1,580 118,684,105,154 MAMCU 67,949,015 2,400 1,805 1,715 1,200 145,918,006,339 LINDI MWAMBAO 19,415,656 2,286 1,700 1,710 1,635 40,156,622,949 RUNALI 43,955,044 2,352 1,815 98,055,721,388 CORECU 13,065,121 2,060 1,900 1,755 1,320 24,747,831,958 TAMCU 21,096,238 2,267 1,811 43,224,648,301 JUMLA YA MAUZO YOTE 220,276,691 2,445 1,700 1,755 1,580 470,786,936,089 Chanzo: Bodi ya Korosho Tanzania, 2021 NB: SG: Standard Grade UG: Under Grade 6 Jedwali 8: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA, 2020 Kielelezo 1: Mwenendo wa Wastani wa bei ya DAP katika soko la dunia hadi kufikia tarehe 23 Desemba, 2021 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 1000.0 24 Jun 2021 01 Jul 2021 08 Jul 2021 15 Jul 2021 22 Jul 2021 29 Jul 2021 05 Aug 2021 12 Aug 2021 19 Aug 2021 26 Aug 2021 02 Sep 2021 09 Sep 2021 16 Sep 2021 23 Sep 2021 30 Sep 2021 07 Oct 2021 14 Oct 2021 21 Oct 2021 28 Oct 2021 04 Nov 2021 11 Nov 2021 18 Nov 2021 25 Nov 2021 02 Dec 2021 09 Dec 2021 Bei (Dola za Kimarekani/Tani) Kipindi Chanzo: Mamlaka ya Mbolea Tanzania, 2021 7 Kielelezo 2: Mwenendo wa Wastani wa bei ya UREA katika soko la dunia hadi kufikia tarehe 23 Desemba, 2021 Chanzo: Mamlaka ya Mbolea Tanzania, 2021 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) hanzo : Mamlaka ya Hali ya Hewa Tanzania | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao 18-22 Oktoba, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Wiki iliyopita Oct 11-15 Wiki hii Oct 18-22 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 43,500 141,700 158,100 89,600 111,600 148,700 59,900 Wiki iliyopita 46,200 149,600 165,600 98,700 111,500 157,700 61,600 Badiliko ▼6.2% ▼5.6% ▼4.7% ▼10.2% ▲0.1% ▼6.1% ▼2.8% Wastani wa Nchi Ujumbe Mkuu Bei za jumla kwa mazao ya chakula zimepungua kwa kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Bei za mtama, mahindi, ulezi, mchele, maharage, na viazi mviringo zimepungua kwa wastani wa asilimia 10.2, 6.2, 6.1, 5.6, 4.7, na 2.8 mtawalia, wakati huo bei ya uwele imeongezeka kwa asilimia 0.1. Pamba: Hadi kufikia tarehe 26 Septemba, 2021 pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 143,838,683. Kahawa safi: Hadi kufikia tarehe 15 Oktoba, 2021 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 32,534,107 zenye thamani ya Dola za Marekani million 78.7. Kakao: Hadi kufikia tarehe 18 Oktoba, 2021 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,966,570 zenye thamani ya Shilingi Bilioni 19.6 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Morogoro Wiki hii 47,300 175,000 180,000 120,000 120,000 180,000 79,000 Wiki iliyopita 46,900 175,000 180,000 120,000 120,000 177,500 79,000 Badiliko ▲0.8% ►0.0% ►0.0% ►0.0% ►0.0% ▲1.4% ►0.0% Tanga Wiki hii 48,600 145,000 170,000 85,000 100,000 170,000 50,000 Wiki iliyopita 48,600 132,500 170,000 85,000 100,000 170,000 44,500 Badiliko ►0.0% ▲8.6% ►0.0% ►0.0% ►0.0% ►0.0% ▲11.0% Mtwara Wiki hii 42,500 162,500 167,500 60,000 NA 180000 52,500 Wiki iliyopita 42,500 165,000 167,500 60,000 NA 180000 60,000 Badiliko ►0.0% ▼1.5% ►0.0% ►0.0% ►0.0% ▼14.3% Iringa Wiki hii 33,500 160,000 160,000 90,000 NA 150,000 45,000 Wiki iliyopita 33,500 160,000 165,000 90,000 NA 150,000 45,000 Badiliko ►0.0% ►0.0% ▼3.1% ►0.0% ►0.0% ►0.0% Ruvuma Wiki hii 29,000 170,000 140,000 NA NA NA 74,000 Wiki iliyopita 29,000 165,000 150,000 NA NA NA 70,000 Badiliko ►0.0% ▲2.9% ▼7.1% ▲5.4% Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 42,300 139,000 185,000 49,500 45,000 120,300 52,500 Wiki iliyopita 43,000 140,000 184,000 52,100 47,500 125,000 53,800 Badiliko ▼1.7% ▼0.7% ▲0.5% ▼5.3% ▼5.6% ▼3.9% ▼2.5% Arusha Wiki hii 50,500 165,000 155,000 67,500 67,500 132,500 52,500 Wiki iliyopita 50,300 162,500 155,000 62,500 63,500 135,500 52,500 Badiliko ▲0.4% ▲1.5% ►0.0% ▲7.4% ▲5.9% ▼2.3% ►0.0% Dar es Salaam Wiki hii 48,000 175,000 215,000 85,000 90,000 165,000 65,000 Wiki iliyopita 47,800 167,500 202,500 90,000 95,000 170,000 56,500 Badiliko ▲0.4% ▲4.3% ▲5.8% ▼5.9% ▼5.6% ▼3.0% ▲13.1% 3 Mwanza Wiki hii 64,000 180,000 180,000 190,000 190,000 200,000 85,000 Wiki iliyopita 64,000 180,000 180,000 190,000 190,000 200,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 62,500 147,000 132,500 105,000 110,000 170,000 60,000 Wiki iliyopita 60,800 145,000 133,800 83,800 107,500 162,500 57,500 Badiliko ▲2.7% ▲1.4% ▼1.0% ▲20.2% ▲2.3% ▲4.4% ▲4.2% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 55,000 155,000 151,500 70,000 90,000 125,000 67,500 Wiki iliyopita 48,500 150,000 135,000 75,000 90,000 125,000 52,000 Badiliko ▲11.8% ▲3.2% ▲10.9% ▼7.1% ►0.0% ►0.0% ▲23.0% Njombe Wiki hii 40,000 215,000 175,000 NA NA 160,000 42,800 Wiki iliyopita 40,000 215,000 175,000 NA NA 160,000 42,800 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Tabora Wiki hii 39,000 102,500 170,000 145,000 NA 175,000 52,500 Wiki iliyopita 39,000 102,500 170,000 145,000 NA 175,000 52,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 31,500 110,000 150,000 NA NA 125,000 57,500 Wiki iliyopita 33,000 107,500 142,500 NA NA 122,500 53,800 Badiliko ▼4.8% ▲2.3% ▲5.0% ▲2.0% ▲6.4% Kigoma Wiki hii 43,000 120,000 145,000 90,000 100,000 150,000 67,500 Wiki iliyopita 43,000 120,000 150,000 100000 70,000 145,000 65,000 Badiliko ►0.0% ►0.0% ▼3.4% ▼11.1% ▲30.0% ▲3.3% ▲3.7% Shinyanga Wiki hii 44,000 125,000 175,000 125,000 125,000 135,000 82,500 Wiki iliyopita 44,000 125,000 175,000 125,000 125,000 135,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼3.0% 4 Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Bei za jumla 1,800 1,950 480 510 Bei za rejareja 1,950 2,250 850 900 Chanzo: https://farmgainafrica.org/ Tarehe 22 Oktoba, 2021 Jedwali 4: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 20 kuishia tarehe 26 Septemba, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 143,196,869 532,605 143,729,474 143,305,637 533,046 143,838,683 Chanzo: Bodi ya Pamba, 2021 Jedwali 5: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 15 Oktoba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 8,206,626 29,203,277 4,800,931 19,008,892 13,007,557 48,212,170 Arabika Ngumu - 169,860 425,727 169,860 425,727 Robusta 313,770 686,812 18,757,744 28,992,725 285,176 408,442 19,356,890 30,087,979 Jumla 8,520,392 29,890,090 23,728,535 48,427,344 285,176 408,442 32,534,107 78,725,876 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 6: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 18 Oktoba, 2021 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 2,813,750 857,960 294,860 3,966,570 4,896 19,567,018,610 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan 5 Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority] Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo Taarifa ya Wiki ya Mwenendo wa Bei za Mazao 25-29 Oktoba, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Wiki iliyopita Oct 18-22 Wiki hii Oct 25-29 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 44,000 142,800 159,400 89,600 111,600 149,700 60,800 Wiki iliyopita 43,500 141,700 158,100 89,600 111,600 148,700 59,900 Badiliko ▲1.1% ▲0.8% ▲0.8% ►0.0% ►0.0% ▲0.7% ▲1.5% Wastani wa Nchi Ujumbe Mkuu Kwa wiki hii, bei za jumla kwa mazao ya chakula zimeongezeka kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Bei za viazi mviringo, mahindi, mchele, maharage na ulezi zimeongezeka kwa wastani wa asilimia 1.5, 1.1, 0.8. 0.8, na 0.7 mtawalia. Bei za mtama na uwele hazijabadilika. Pamba: Hadi kufikia tarehe 26 Septemba, 2021 pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 143,838,683. Kahawa safi: Hadi kufikia tarehe 22 Oktoba, 2021 kahawa safi iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 34,367,654 zenye thamani ya Dola za Marekani million 84.9. Kakao: Hadi kufikia tarehe 25 Oktoba, 2021 kakao iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 4,271,210 zenye thamani ya Shilingi Bilioni 21 Korosho: Hadi kufikia tarehe 24 Oktoba, 2021 korosho iliyouzwa kwa msimu wa mauzo 2021/22 ni kilo 41,401,086 zenye thamani ya shilingi bilioni 91.3. Taarifa ya hali ya hewa iliyotolewa na Mamlaka ya Hali ya Hewa inaonesha kuwepo kwa upungufu wa mvua kwa msimu unaonanza Nomvemba 2021 hadi Aprili 2022 katika mikoa mingi ya Tanzania (Kiambatisho 1). Hali hii inaweza kusababisha kupanda kwa bei za mazao ya chakula. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Morogoro Wiki hii 47,300 175,000 180,000 120,000 120,000 180,000 79,000 Wiki iliyopita 47,300 175,000 180,000 120,000 120,000 180,000 79,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 49,800 147,500 172,500 85,000 100,000 170,000 50,000 Wiki iliyopita 48,600 145,000 170,000 85,000 100,000 170,000 50,000 Badiliko ▲2.4% ▲1.7% ▲1.4% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 42,500 160,000 167,500 60,000 NA 180000 52,500 Wiki iliyopita 42,500 162,500 167,500 60,000 NA 180000 52,500 Badiliko ►0.0% ▼1.6% ►0.0% ►0.0% ►0.0% ►0.0% Iringa Wiki hii 33,500 160,000 160,000 90,000 NA 150,000 45,000 Wiki iliyopita 33,500 160,000 160,000 90,000 NA 150,000 45,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Ruvuma Wiki hii 28,500 175,000 145,000 NA NA NA 74,000 Wiki iliyopita 29,000 170,000 140,000 NA NA NA 74,000 Badiliko ▼1.8% ▲2.9% ▲3.4% ►0.0% Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 42,300 139,000 185,000 49,500 45,000 124,300 52,500 Wiki iliyopita 42,300 139,000 185,000 49,500 45,000 120,300 52,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲3.2% ►0.0% Arusha Wiki hii 49,500 170,000 155,000 67,500 67,500 132,500 52,500 Wiki iliyopita 50,500 165,000 155,000 67,500 67,500 132,500 52,500 Badiliko ▼2.0% ▲2.9% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 48,000 175,000 215,000 85,000 90,000 165,000 65,000 Wiki iliyopita 48,000 175,000 215,000 85,000 90,000 165,000 65,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 3 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Tabora Wiki hii 41,500 102,500 170,000 145,000 NA 175,000 58,800 Wiki iliyopita 39,000 102,500 170,000 145,000 NA 175,000 52,500 Badiliko ▲6.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲10.7% Rukwa Wiki hii 32,800 112,500 161,300 NA NA 138,800 66,300 Wiki iliyopita 31,500 110,000 150,000 NA NA 125,000 57,500 Badiliko ▲4.0% ▲2.2% ▲7.0% ▲9.9% ▲13.3% Kigoma Wiki hii 47,200 125,000 145,000 90,000 100,000 150,000 67,500 Wiki iliyopita 43,000 120,000 145,000 90,000 100,000 150,000 67,500 Badiliko ▲8.9% ▲4.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Shinyanga Wiki hii 44,000 125,000 175,000 125,000 125,000 135,000 83,800 Wiki iliyopita 44,000 125,000 175,000 125,000 125,000 135,000 82,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲1.6% Mwanza Wiki hii 64,000 180,000 180,000 190,000 190,000 200,000 85,000 Wiki iliyopita 64,000 180,000 180,000 190,000 190,000 200,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kagera Wiki hii 63,500 148,000 132,500 105,000 110,000 170,000 60,000 Wiki iliyopita 62,500 147,000 132,500 105,000 110,000 170,000 60,000 Badiliko ▲1.6% ▲0.7% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 55,000 155,000 156,000 70,000 90,000 125,000 67,500 Wiki iliyopita 55,000 155,000 151,500 70,000 90,000 125,000 67,500 Badiliko ►0.0% ►0.0% ▲2.9% ►0.0% ►0.0% ►0.0% ►0.0% Njombe Wiki hii 40,000 215,000 175,000 NA NA 160,000 42,800 Wiki iliyopita 40,000 215,000 175,000 NA NA 160,000 42,800 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Bei za jumla 1,824 1,954 489 521 Bei za rejareja 1,954 2,280 847 912 Chanzo: https://farmgainafrica.org/ Tarehe 29 Oktoba, 2021 Jedwali 4: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 20 kuishia tarehe 26 Septemba, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 143,196,869 532,605 143,729,474 143,305,637 533,046 143,838,683 Chanzo: Bodi ya Pamba, 2021 Jedwali 5: Mauzo ya kahawa kwa msimu wa mwaka 2021/2022 hadi kufikia tarehe 22 Oktoba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 9,505,023 34,258,160 4,800,931 19,008,892 14,305,954 53,267,052 Arabika Ngumu 12,640 32,624 169,860 425,727 182,500 458,351 Robusta 836,280 1,837,054 18,757,744 28,992,725 285,176 408,442 19,879,200 31,238,221 Jumla 10,353,943 36,127,838 23,728,535 48,427,344 285,176 408,442 34,367,654 84,963,624 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 6: Mauzo ya kakao kwa msimu wa 2021/2022 hadi kufikia tarehe 25 Oktoba, 2021 Halmashauri Kiasi kilichouzwa (Kilo) Wastani wa Bei (Shilingi/Kilo) Jumla (Shilingi) Kyela (Kilo) Busokelo (Kilo) Rungwe (Kilo) 3,020,390 929,990 320,830 4,271,210 4,900.89 21,087,476,850 Chanzo: Tume ya Maendeleo ya Ushirika, 2021 5 Jedwali 7: Mauzo ya korosho kwa msimu wa mwaka 2021/22 hadi kufikia tarehe 24 Oktoba, 2021. Tarehe Ya Mnada Chama Kiasi Kilichopelekwa Sokoni (Kilo) Kiasi Kilichouzwa (Kilo) Thamani (Sh.) Bei Ya Juu (Sh/Kilo) Bei Ya Chini (Sh/Kilo) 10/8/2021 TANECU 1,486,267.00 1,486,267.00 3,420,523,352.00 2,445 2,231 10/15/2021 MAMCU 5,098,878.00 5,098,878.00 11,542,628,036.00 2,400 2,220 10/15/2021 TANECU 3,124,930.00 3,124,930.00 7,120,118,097.00 2,401 2,320 10/16/2021 LINDI MWAMBAO 5,012,932.00 5,012,932.00 10,978,586,607.00 2,286 2,100 10/17/2021 RUNALI 2,730,716.00 2,730,716.00 6,150,411,553.00 2,282 2,235 10/20/2021 CORECU 3,007,185.00 3,007,185.00 5,481,706,438.00 1,955 1,600 10/22/2021 MAMCU 7,400,607.00 7,400,607.00 16,470,184,510.00 2,321 2,070 10/22/2021 TANECU 5,990,924.00 5,990,924.00 13,577,069,466.00 2,311 2,255 10/23/2021 LINDI MWAMBAO 3,242,589.00 3,242,589.00 6,756,999,080.00 2,260 2,020 10/24/2021 RUNALI 4,306,058.00 4,306,058.00 9,776,043,560.00 2,311 2,240 JUMLA YA MAUZO YOTE 41,401,086.00 41,401,086.00 91,274,270,699.00 2,445 1,600 Chanzo: Bodi ya Korosho Tanzania, 2021 Jedwali 8: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb 6 Kielelezo 1: Mwenendo wa Wastani wa Bei ya DAP katika Soko la Dunia Kielelezo 2: Mwenendo wa Wastani wa Bei ya UREA katika Soko la Dunia 0 100 200 300 400 500 600 700 800 04 Jun 2020 18 Jun 2020 02 Jul 2020 16 Jul 2020 30 Jul 2020 13 Aug 2020 27 Aug 2020 10 Sep 2020 24 Sep 2020 08 Oct 2020 22 Oct 2020 05 Nov 2020 19 Nov 2020 03 Dec 2020 17 Dec 2020 31 Dec 2020 14 Jan 2021 28 Jan 2021 11 Feb 2021 25 Feb 2021 11 Mar 2021 25 Mar 2021 08 Apr 2021 22 Apr 2021 06 May 2021 20 May 2021 03 Jun 2021 17 Jun 2021 01 Jul 2021 15 Jul 2021 29 Jul 2021 12 Aug 2021 26 Aug 2021 09 Sep 2021 23 Sep 2021 07 Oct 2021 21 Oct 2021 Bei (Dola za Marekani/Tani) Kipindi 0 100 200 300 400 500 600 700 800 04 Jun 2020 18 Jun 2020 02 Jul 2020 16 Jul 2020 30 Jul 2020 13 Aug 2020 27 Aug 2020 10 Sep 2020 24 Sep 2020 08 Oct 2020 22 Oct 2020 05 Nov 2020 19 Nov 2020 03 Dec 2020 17 Dec 2020 31 Dec 2020 14 Jan 2021 28 Jan 2021 11 Feb 2021 25 Feb 2021 11 Mar 2021 25 Mar 2021 08 Apr 2021 22 Apr 2021 06 May 2021 20 May 2021 03 Jun 2021 17 Jun 2021 01 Jul 2021 15 Jul 2021 29 Jul 2021 12 Aug 2021 26 Aug 2021 09 Sep 2021 23 Sep 2021 07 Oct 2021 21 Oct 2021 Bei (Dola za Marekani/ Tani) Kipindi 7 Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 8 Kiambatisho: Mwenendo wa Mvua za Msimu (Novemba 2021- Aprili 2022) Chanzo : Mamlaka ya Hali ya Hewa Tanzania | false |
# Extracted Content 1 Market Intelligence Unit Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO Septemba 13-17, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Wiki iliyopita Septemba 06-10 Wiki hii Septemba 13-17 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 40,000 128,300 155,400 81,400 102,300 140,900 56,300 Wiki iliyopita 42,700 136,600 164,800 91,800 116,000 154,000 61,700 Badiliko ▼6.8% ▼6.5% ▼6.0% ▼12.8% ▼13.4% ▼9.3% ▼9.6% Wastani wa Nchi Ujumbe Mkuu Kwa ujumla, bei za mazao makuu ya chakula zimepungua kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Bei za Uwele, mtama, viazi, ulezi, mahindi, mchele na maharage zimepungua kwa asilimia 13, 13, 10, 9, 7, 7 na 6 mtawalia. Bei za mazao makuu ya chakula zinategemewa kubadilika kwa viwango vidogo wiki inayofuata. Upatikanaji wa mazao katika masoko ni wa kuridhisha kutokana na kuendelea kwa msimu wa mavuno. Tumbaku: Hadi kufikia tarehe 22 Agosti, 2021 kiasi cha tumbaku kilichouzwa ni Kilo 68,571,838 zenye thamani ya Dola za Kimarekeni Milioni 86.4. Pamba: Hadi kufikia tarehe 12 Septemba, 2021 pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 142,537,273. Kahawa: Hadi kufikia tarehe 10 Septemba, 2021 kahawa iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 21,737,913 zenye thamani ya Dola za Kimarekani million 43.2. Mbaazi: Hadi kufikia tarehe 16 Septemba, 2021 mbaazi zilizouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,098,027 zenye thamani ya Shilingi Bilioni 4. 2 Market Intelligence Unit Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 39,800 145,000 185,000 49,300 50,000 120,000 52,500 Wiki iliyopita 38,700 142,500 185,000 50,200 49,500 122,500 62,000 Badiliko ▲2.8% ▲1.7% ►0.0% ▼1.8% ▲1.0% ▼2.1% ▼18.1% Arusha Wiki hii 47,500 160,000 185,000 67,500 70,000 NA 42,500 Wiki iliyopita 47,000 160,000 155,000 67,500 70,000 NA 42,500 Badiliko ▲1.1% ►0.0% ▲16.2% ►0.0% ►0.0% ►0.0% Dar es Salaam Wiki hii 52,300 152,500 212,500 87,500 82,500 157,500 58,500 Wiki iliyopita 50,300 155,000 211,700 85,000 80,000 157,500 52,300 Badiliko ▲3.8% ▼1.6% ▲0.4% ▲2.9% ▲3.0% ►0.0% ▲10.6% Morogoro Wiki hii 40,500 170,000 180,000 120,000 120,000 160,000 70,000 Wiki iliyopita 39,500 170,000 180,000 120,000 120,000 160,000 70,000 Badiliko ▲2.5% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 44,000 145,000 160,000 85,000 100,000 170,000 44,500 Wiki iliyopita 44,000 145,000 165,000 85,000 100,000 170,000 45,000 Badiliko ►0.0% ►0.0% ▼3.1% ►0.0% ►0.0% ▼1.1% Ruvuma Wiki hii 26,800 170,000 125,000 NA NA NA 73,000 Wiki iliyopita 26,000 170,000 120,000 NA NA NA 73,500 Badiliko ▲3.0% ►0.0% ▲4.0% ▼0.7% Iringa Wiki hii 32,500 160,000 165,000 90,000 NA 150000 65,000 Wiki iliyopita 34,000 160,000 145,000 90,000 NA 150000 50,000 Badiliko ▼4.6% ►0.0% ▲12.1% ►0.0% ►0.0% ▲23.1% Njombe Wiki hii 36,500 145,000 152,000 NA NA 125,500 31,300 Wiki iliyopita 36,500 145,000 152,000 NA NA 125,500 31,300 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 31,300 105,000 167,500 NA NA 137,500 65,000 Wiki iliyopita 31,500 105,000 170,000 NA NA 175,000 65,000 Badiliko ▼0.6% ►0.0% ▼1.5% ▼27.3% ►0.0% 3 Market Intelligence Unit Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Kagera Wiki hii 56,300 128,800 127,500 105,000 130,000 147,500 57,500 Wiki iliyopita 55,000 130,000 130,000 125,000 155,000 155,000 60,000 Badiliko ▲2.3% ▼0.9% ▼2.0% ▼19.0% ▼19.2% ▼5.1% ▼4.3% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 43,300 142,500 135,000 70,000 90,000 125,000 55,000 Wiki iliyopita 45,000 150,000 135,000 70,000 90,000 125,000 65,000 Badiliko ▼3.9% ▼5.3% ►0.0% ►0.0% ►0.0% ►0.0% ▼18.2% Shinyanga Wiki hii 43,500 110,000 175,000 115,000 105,000 115,000 85,000 Wiki iliyopita 43,500 110,000 175,000 115,000 105,000 115,000 85,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 40,000 145,000 167,500 57,500 NA 180,000 57,500 Wiki iliyopita 40,000 145,000 167,500 57,500 NA 180,000 57,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tabora Wiki hii 35,500 102,500 170,000 145,000 NA 175,000 62,500 Wiki iliyopita 35,500 102,500 170,000 145,000 NA 175,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Kigoma Wiki hii 47,200 95,000 140,000 85,000 85,000 160,000 45,000 Wiki iliyopita 47,200 93,500 125,000 80,000 NA 145,000 55,000 Badiliko ►0.0% ▲1.6% ▲10.7% ▲5.9% ▲9.4% ▼22.2% 4 Market Intelligence Unit Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Uganda (bei za jumla) 1,839 1,970 525 492 Uganda (bei za rejareja) 1,970 2,298 854 919 Chanzo: https://farmgainafrica.org/ Tarehe 17 Septemba, 2021 Jedwali 4A: Mauzo ya tumbaku katika msimu wa 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 kwa kampuni AINA YA TUMBAKU KAMPUNI KILO ZA MKATABA MASOKO YALIYOTHAMINISHWA MPAKA SASA (CUMMULATIVE) BELO KG THAMANI(USD) BEI YA WASITANI (USD/KG) (USD) VFC Alliance One Tobacco Tanzania Ltd 20,040,000 410,978 18,857,569 28,307,316 1.50 JTI Leaf Services Ltd 14,460,000 297,865 14,074,601 24,034,375 1.71 Premium Active Tanzania Ltd 16,000,000 287,194 13,488,012 20,740,505 1.54 Pachtec Company Ltd 4,461,838 57,284 2,609,127 3,627,934 1.39 Mo Green International Company Limited 2,800,000 36,017 1,677,408 2,545,870 1.52 Naile Leaf (T) Co. Ltd 2,535,000 43,336 1,851,806 2,775,124 1.50 Grand Tobacco Limited 1,815,000 Magefa Growers Ltd 4,400,000 40,179 1,755,989 2,414,887 1.38 Jespan Company Ltd 760,000 9,865 486,296 661,391 1.36 ENV Services Ltd 800,000 7,932 360,503 520,860 1.44 Biexen Company Limited 29,145 717 29,145 40,041 1.37 JUMLA NDOGO 68,071,838 1,191,367 55,190,456 85,668,303 1.55 DFC Premium Active Tanzania Ltd 500,000 11,022 531,792 698,768 1.31 JUMLA KUU 68,571,838 1,202,389 55,722,247 86,367,071 1.55 5 Market Intelligence Unit Jedwali 4B: Mauzo ya tumbaku (kimkoa) katika msimu wa masoko 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 Mkoa Kilo za Mkataba Kiasi cha tumbaku kilichonunuliwa Belo Kilo Katavi 7,350,000 141,785 6,229,618 Mbeya 10,280,000 167,660 8,067,643 Songwe 670,000 12,953 624,655 Kigoma 4,705,000 93,825 4,194,878 Tabora 32,546,838 575,479 26,682,758 Shinyanga 9,930,000 162,321 7,648,131 Geita 1,070,000 17,809 871,093 Kagera 70,000 1,180 58,557 Iringa 200,000 2,446 157,631 Singida 1,250,000 15,909 655,493 Jumla ya VFC 68,071,838 1,191,367 55,190,456 Ruvuma (DFC) 500,000 11,022 531,791.96 JUMLA KUU (DFC+VFC) 68,571,838 1,202,389 55,722,247 Jedwali 5: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 18 kuishia tarehe Septemba 12, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (KGS) KWA WIKI HII (KGS) JUMLA (KGS) JUMLA YA WIKI YA NYUMA (KGS) KWA WIKI HII (KGS) JUMLA (KGS) 141,371,266 1,166,007 142,537,273 141,371,266 1,262,536 142,633,802 Chanzo: Bodi ya Pamba, 2021 6 Market Intelligence Unit Jedwali :6 Mauzo ya mbaazi hadi tarehe 16 Septemba, 2021 Tarehe Wilaya Chama cha Ushirika Kampuni Kilo Shilingi/Kilo Jumla Ndogo (Shilingi) 11/08/2021 Namtumbo Ushirika B Afrisian Ginning 41,428 1,280 53,027,840 12/08/2021 Tunduru Mtetesi MeTL 150,000 1,300 195,000,000 Tunduru Mtetesi RBST 210,251 1,290 271,223,790 18/08/2021 Namtumbo Ushirika B MeTL 206,517 1,320 272,602,440 Namtumbo Ushirika B LENIC 200,000 1,320 264,000,000 19/08/2021 Tunduru Asema LENIC 300,000 1,344 403,200,000 Tunduru Asema LENIC 845,498 1,340 1,132,967,320 25/08/2021 Namtumbo Namtumbo LENIC 819,149 1,380 1,083,734,127 16/09/2021 Tunduru Mruji LENIC 325,184 1,110 360,954,240 JUMLA KUU 3,098,027 4,036,709,757 Jedwali 7: Mauzo ya kahawa kwa msimu wa mwaka 2021/22 hadi kufikia tarehe 10 Septemba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 4,197,431 14,886,829 722,118 2,817,919 4,919,549 17,704,748 Arabika Ngumu 96,420 208,218 96,420 208,218 Robusta 16,721,944 25,313,689 16,721,944 25,313,689 Jumla 4,197,431 14,886,829 17,540,482 28,339,827 21,737,913 43,226,655 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 8: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb 7 Market Intelligence Unit Habari Muhimu ✓ Wiki hii, Serikali ya Tanzania imetoa jumla ya shilingi bilioni 15 kwa Wakala wa Taifa wa Hifadhi ya Chakula (NFRA) kwa ajili ya ununuzi wa mahindi katika mikoa ya Nyanda za Juu Kusini. ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO Septemba 20-24, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Wiki iliyopita Septemba 13-17 Wiki hii Septemba 20-24 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 43,100 127,600 161,600 87,200 101,600 152,200 59,800 Wiki iliyopita 42,500 135,800 165,100 87,600 102,300 150,900 61,700 Badiliko ▲1.4% ▼6.4% ▼2.2% ▼0.5% ▼0.7% ▲0.9% ▼3.2% Wastani wa Nchi Ujumbe Mkuu Kwa ujumla, wastani wa bei za jumla za mazao makuu ya chakula zimepungua kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Hata hivyo bei za mazao katika masoko mbalimbali zimeongezeka na kupungua kwa viwango tofauti. Wakati bei za mchele, viazi mviringo, maharage, uwele na mtama zikipungua kwa wastani wa asilimia 6.4, 3.2, 2.2, 0.7 and 0.5 mtawalia, bei za mahindi na ulezi zimeongezeka kwa asilimia 1.4 na 0.9 mtawalia. Pamba: Hadi kufikia tarehe 19 Septemba, 2021 pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 144,011,169. Kahawa: Hadi kufikia tarehe 10 Septemba, 2021 kahawa iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 21,737,913 zenye thamani ya Dola za Kimarekani million 43.2. Mbaazi: Hadi kufikia tarehe 22 Septemba, 2021 mbaazi zilizouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,169,976 zenye thamani ya Shilingi Bilioni 4.2. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Rukwa Wiki hii 31,500 100,000 166,300 NA NA 140,000 60,000 Wiki iliyopita 31,300 105,000 167,500 NA NA 137,500 65,000 Badiliko ▲0.6% ▼5.0% ▼0.7% ▲1.8% ▼8.3% Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 44,500 144,300 185,300 49,000 53,500 121,300 53,000 Wiki iliyopita 39,800 145,000 185,000 49,300 50,000 120,000 52,500 Badiliko ▲10.6% ▼0.5% ▲0.2% ▼0.6% ▲6.5% ▲1.1% ▲0.9% Arusha Wiki hii 47,000 162,500 155,000 62,500 72,500 NA 42,500 Wiki iliyopita 47,500 160,000 185,000 67,500 70,000 NA 42,500 Badiliko ▼1.1% ▲1.5% ▼19.4% ▼8.0% ▲3.4% ►0.0% Dar es Salaam Wiki hii 49,300 151,700 201,700 87,500 82,500 162,500 55,000 Wiki iliyopita 52,300 152,500 212,500 87,500 82,500 157,500 58,500 Badiliko ▼6.1% ▼0.5% ▼5.4% ►0.0% ►0.0% ▲3.1% ▼6.4% Morogoro Wiki hii 40,500 170,000 180,000 120,000 120,000 160,000 70,000 Wiki iliyopita 40,500 170,000 180,000 120,000 120,000 160,000 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tanga Wiki hii 46,000 120,000 150,000 85,000 100,000 170,000 45,000 Wiki iliyopita 44,000 145,000 160,000 85,000 100,000 170,000 44,500 Badiliko ▲4.3% ▼20.8% ▼6.7% ►0.0% ►0.0% ►0.0% ▲1.1% Ruvuma Wiki hii 26,500 170,000 140,000 NA NA NA 75,000 Wiki iliyopita 26,800 170,000 125,000 NA NA NA 73,000 Badiliko ▼1.1% ►0.0% ▲10.7% ▲2.7% Iringa Wiki hii 32,300 160,000 162,500 90,000 NA 135000 55,000 Wiki iliyopita 32,500 160,000 165,000 90,000 NA 150000 65,000 Badiliko ▼0.6% ►0.0% ▼1.5% ►0.0% ▼11.1% ▼18.2% 3 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Kagera Wiki hii 57,500 125,000 125,000 86,300 105,000 155,000 57,500 Wiki iliyopita 56,300 128,800 127,500 105,000 130,000 147,500 57,500 Badiliko ▲2.1% ▼3.0% ▼2.0% ▼21.7% ▼23.8% ▲4.8% ►0.0% Mara Wiki hii 62,500 105,000 175,000 70,000 190,000 190,000 91,300 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 190,000 91,300 Badiliko ►0.0% ►0.0% ▼11.4% ▲10.7% ►0.0% ►0.0% ►0.0% Manyara Wiki hii 43,000 150,000 135,000 70,000 90,000 125,000 47,500 Wiki iliyopita 43,300 142,500 135,000 70,000 90,000 125,000 55,000 Badiliko ▼0.7% ▲5.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼15.8% Shinyanga Wiki hii 43,500 125,000 175,000 115,000 105,000 115,000 85,000 Wiki iliyopita 43,500 110,000 175,000 115,000 105,000 115,000 85,000 Badiliko ►0.0% ▲12.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 40,000 155,000 165,000 58,800 NA 180,000 57,500 Wiki iliyopita 40,000 145,000 167,500 57,500 NA 180,000 57,500 Badiliko ►0.0% ▲6.5% ▼1.5% ▲2.2% ►0.0% ►0.0% Tabora Wiki hii 37,300 102,500 170,000 145,000 NA 175,000 57,500 Wiki iliyopita 35,500 102,500 170,000 145,000 NA 175,000 62,500 Badiliko ▲4.8% ►0.0% ►0.0% ►0.0% ►0.0% ▼8.7% Kigoma Wiki hii 44,600 100,000 138,800 95,000 97,500 150,000 45,000 Wiki iliyopita 47,200 95,000 140,000 85,000 85,000 160,000 45,000 Badiliko ▼5.8% ▲5.0% ▼0.9% ▲10.5% ▲12.8% ▼6.7% ►0.0% 4 Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Bei za jumla 1,844 1,975 492 527 Bei za rejareja 1,975 2,305 856 922 Chanzo: https://farmgainafrica.org/ Tarehe 24 Septemba, 2021 Jedwali 5: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 19 kuishia tarehe Septemba 19, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 142,726,153 1,285,016 144,011,169 142,822,682 612,315 143,434,997 Chanzo: Bodi ya Pamba, 2021 Jedwali :6 Mauzo ya mbaazi hadi tarehe 22 Septemba, 2021 Tarehe Wilaya Chama cha Ushirika Kampuni Kilo Shilingi/Kilo Jumla Ndogo (Shilingi) 11/08/2021 Namtumbo Ushirika B Afrisian Ginning 41,428 1,280 53,027,840 12/08/2021 Tunduru Mtetesi MeTL 150,000 1,300 195,000,000 Tunduru Mtetesi RBST 210,251 1,290 271,223,790 18/08/2021 Namtumbo Ushirika B MeTL 206,517 1,320 272,602,440 Namtumbo Ushirika B LENIC 200,000 1,320 264,000,000 19/08/2021 Tunduru Asema LENIC 300,000 1,344 403,200,000 Tunduru Asema LENIC 845,498 1,340 1,132,967,320 25/08/2021 Namtumbo Namtumbo LENIC 819,149 1,380 1,083,734,127 16/09/2021 Tunduru Mruji LENIC 325,184 1,110 360,954,240 22/09/2021 Namtumbo Ushirika B LENIC 71,949 990 71,229,510 JUMLA KUU 3,169,976 4,154,630,760 5 Jedwali 7: Mauzo ya kahawa kwa msimu wa mwaka 2021/22 hadi kufikia tarehe 10 Septemba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 4,197,431 14,886,829 722,118 2,817,919 4,919,549 17,704,748 Arabika Ngumu 96,420 208,218 96,420 208,218 Robusta 16,721,944 25,313,689 16,721,944 25,313,689 Jumla 4,197,431 14,886,829 17,540,482 28,339,827 21,737,913 43,226,655 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 8: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority 6 Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO Septemba 27-Octoba 01, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/100 kg gunia) Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 44,900 145,400 162,800 93,900 112,200 155,100 58,800 Wiki iliyopita 43,700 138,500 160,900 89,600 105,100 152,200 61,300 Badiliko ▲2.7% ▲4.7% ▲1.2% ▲4.6% ▲6.3% ▲1.9% ▼4.3% Wastani wa Nchi Ujumbe Mkuu Kwa ujumla, wastani wa bei za jumla kitaifa zimeongezeka kiasi ikilinganishwa na viwango vya bei wiki iliyopita. Bei za mahindi, mchele, maharage, mtama, uwele, na ulezi zimeongezeka kwa wastani wa asilimia 2.7, 4.7, 1.2, 4.6, 6.3, na 1.9 mtawalia. Kwa upande mwingine bei za viazi mviringo zimepungua kwa asilimia 4.3. Pamba: Hadi kufikia tarehe 19 Septemba, 2021 pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 144,011,169. Kahawa: Hadi kufikia tarehe 24 Septemba, 2021 kahawa iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 26,653,288 zenye thamani ya Dola za Kimarekani million 57.9. Mbaazi: Hadi kufikia tarehe 22 Septemba, 2021 mbaazi zilizouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,169,976 zenye thamani ya Shilingi Bilioni 4.2. 2 Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/100 kg gunia) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 43,500 140,000 185,000 50,000 54,500 121,500 53,300 Wiki iliyopita 44,500 144,300 185,300 49,000 53,500 121,300 53,000 Badiliko ▼2.3% ▼3.1% ▼0.2% ▲2.0% ▲1.8% ▲0.2% ▲0.6% Arusha Wiki hii 47,500 162,500 160,000 63,500 72,500 132,500 42,500 Wiki iliyopita 47,000 162,500 155,000 62,500 72,500 NA 42,500 Badiliko ▲1.1% ►0.0% ▲3.1% ▲1.6% ►0.0% ►0.0% Dar es Salaam Wiki hii 51,800 166,700 205,000 87,500 82,500 162,500 55,200 Wiki iliyopita 49,300 151,700 201,700 87,500 82,500 162,500 55,000 Badiliko ▲4.8% ▲9.0% ▲1.6% ►0.0% ►0.0% ►0.0% ▲0.4% Rukwa Wiki hii 31,000 112,500 147,500 NA NA 125,000 52,500 Wiki iliyopita 31,500 100,000 166,300 NA NA 140,000 60,000 Badiliko ▼1.6% ▲11.1% ▼12.7% ▼12.0% ▼14.3% Tanga Wiki hii 50,000 120,000 150,000 85,000 100,000 170,000 43,000 Wiki iliyopita 46,000 120,000 150,000 85,000 100,000 170,000 45,000 Badiliko ▲8.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▼4.7% Ruvuma Wiki hii 27,500 170,000 140,000 NA NA NA 73,500 Wiki iliyopita 26,500 170,000 140,000 NA NA NA 75,000 Badiliko ▲3.6% ►0.0% ►0.0% ▼2.0% Iringa Wiki hii 32,000 160,000 145,000 90,000 NA 150000 45,000 Wiki iliyopita 32,300 160,000 162,500 90,000 NA 135000 55,000 Badiliko ▼0.9% ►0.0% ▼12.1% ►0.0% ▲10.0% ▼22.2% 3 Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Kagera Wiki hii 58,000 127,000 130,000 87,500 105,000 155,000 57,500 Wiki iliyopita 57,500 125,000 125,000 86,300 105,000 155,000 57,500 Badiliko ▲0.9% ▲1.6% ▲3.8% ▲1.4% ►0.0% ►0.0% ►0.0% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 175,000 70,000 190,000 190,000 91,300 Badiliko ►0.0% ►0.0% ▲10.3% ▼12.0% ►0.0% ►0.0% ▲1.3% Manyara Wiki hii 46,000 150,000 135,000 74,000 90,000 125,000 52,000 Wiki iliyopita 43,000 150,000 135,000 70,000 90,000 125,000 47,500 Badiliko ▲6.5% ►0.0% ►0.0% ▲5.4% ►0.0% ►0.0% ▲8.7% Shinyanga Wiki hii 45,500 125,000 175,000 125,000 125,000 135,000 85,000 Wiki iliyopita 43,500 125,000 175,000 115,000 105,000 115,000 85,000 Badiliko ▲4.4% ►0.0% ►0.0% ▲8.0% ▲16.0% ▲14.8% ▲14.8% Mtwara Wiki hii 40,000 165,000 162,500 60,000 NA 180,000 57,500 Wiki iliyopita 40,000 155,000 165,000 58,800 NA 180,000 57,500 Badiliko ►0.0% ▲6.1% ▼1.5% ▲2.0% ►0.0% ►0.0% Kilimanjaro Wiki hii 52,500 175,000 150,000 120,000 140,000 NA 70,000 Wiki iliyopita 52500 175000 150000 120000 140000 NA 70,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Kigoma Wiki hii 47,200 95,000 137,500 90,000 85,000 145,000 45,000 Wiki iliyopita 44,600 100,000 138,800 95,000 97,500 150,000 45,000 Badiliko ▲5.5% ▼5.3% ▼0.9% ▼5.6% ▼14.7% ▼3.4% ►0.0% Tabora Wiki hii 39,000 102,500 170,000 145,000 NA 175,000 52,500 Wiki iliyopita 37,300 102,500 170,000 145,000 NA 175,000 52,500 Badiliko ▲4.4% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Bei za jumla 1,831 1,961 490 523 Bei za rejareja 1,961 2,288 850 915 Chanzo: https://farmgainafrica.org/ Tarehe 01 Oktoba, 2021 Jedwali 5: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 19 kuishia tarehe Septemba 19, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 142,726,153 1,285,016 144,011,169 142,822,682 612,315 143,434,997 Chanzo: Bodi ya Pamba, 2021 Jedwali :6 Mauzo ya mbaazi hadi tarehe 22 Septemba, 2021 Tarehe Wilaya Chama cha Ushirika Kampuni Kilo Shilingi/Kilo Jumla Ndogo (Shilingi) 11/08/2021 Namtumbo Ushirika B Afrisian Ginning 41,428 1,280 53,027,840 12/08/2021 Tunduru Mtetesi MeTL 150,000 1,300 195,000,000 Tunduru Mtetesi RBST 210,251 1,290 271,223,790 18/08/2021 Namtumbo Ushirika B MeTL 206,517 1,320 272,602,440 Namtumbo Ushirika B LENIC 200,000 1,320 264,000,000 19/08/2021 Tunduru Asema LENIC 300,000 1,344 403,200,000 Tunduru Asema LENIC 845,498 1,340 1,132,967,320 25/08/2021 Namtumbo Namtumbo LENIC 819,149 1,380 1,083,734,127 16/09/2021 Tunduru Mruji LENIC 325,184 1,110 360,954,240 22/09/2021 Namtumbo Ushirika B LENIC 71,949 990 71,229,510 JUMLA KUU 3,169,976 4,154,630,760 5 Jedwali 7: Mauzo ya kahawa kwa msimu wa mwaka 2021/22 hadi kufikia tarehe 24 Septemba, 2021 Aina ya Kahawa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika Laini 6,747,280 24,006,847 1,259,628 5,052,981 - - 8,006,908 29,059,828.45 Arabika Ngumu - - 169,860 425,727 - - 169,860 425,727.12 Robusta - - 18,191,344 27,969,485 285,176 408,441.68 18,476,520 28,377,926.76 Jumla 6,747,280 24,006,847 19,620,832 33,448,193 285,176 408,441.68 26,653,288 57,863,482.33 Chanzo: Bodi ya Kahawa Tanzania, 2021 Jedwali 8: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Habari Muhimu ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority 6 Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 | false |
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# Extracted Content 1 UNITED REPUBLIC OF TANZANIA PRIME MINISTER’S OFFICE REGIONAL ADMINISTRATION AND LOCAL GOVERNMENT NGARA DISTRICT COUNCIL DISTRICT DASIP ANNUAL REPORT JULY 2009 - JUNE 2010 JULY 2010 DISTRICT EXECUTIVE DIRECTOR’S OFFICE P.O.BOX 30 NGARA TEL.028-2226025 FAX 028-2226152/028-2226025 E-mail [email protected] 2 CONTENTS PAGE 1. List and Abbreviation…………………………………………………………...3 2. Basic Data …………………….………………………………………………..4 3. Executive Summary……………………………………………………………..6 4. Introduction……………………………………………………………………..6 5. Approaches used to collect data / information…………………………………..8 6. The project implementation plan………………………………………………..8 7. Resources in terms of Finance………………….……………………………….9 8. Achievements as regards to implementation status……………………………11 10. Community Plan and Investment in Agriculture……………………………..13 11. The use of completed projects/structures…………………………………….14 12. Problems……………………………………………………………………..19 13. Recommendations……………………………………………………………19 11. Way Forward ……………………………………………………………….. 20 12. Conclusion…………………………………………………………………… 20 TABLES 1. Data Population census……………………………………………………………7 2. Summary of receipts and payments……………………………………………….9 3. Status of 2009/2010 PFGs ……………………………………………………….12 4. Project Implementation Status……………………………………………………17 5. Summary of Ngara DASIP Projects under DADPs for FY 2010/2011…………...21 6. Summary of data showing some Farmers who adopted from PFGs………………25 3 1. LIST OF ABBREVIATION AfDB African Development Bank BOQ Bill of Quantities DADP’s District Agricultural Development Plans DASIP District Agriculture Sector Investment Project DE District Engineer DED District Executive Director DFTs District Facilitation Team DMEO District Monitoring and Evaluation Officer DPO District Project Officer FFS Farmer Field School M&E Monitoring and Evaluation PFGs Participatory Farmer Groups WFTs Ward Facilitation Team 4 2. BASIC DATA COUNTRY WISE: Tanzania PROJECT TITLE: District Agriculture Sector Investment Project LOCATION: 28 District in Kagera, Kigoma,Mara,Mwanza and Shinyanga Regions of North West Tanzania EXECUTING AGENCY: Ministry of Agriculture, Food and Cooperatives BORROWER: The United Republic of Tanzania PROJECT ID NO: P-TZ-AAZ-001 PROJECT LOAN NO: 2100150008694 PROJECT SOURCES OF FINANCE: ADF (Loan) :UA 36.00 Million ADF (Loan) :UA 7.00 Million Government :UA 6.64 Million Beneficiaries :UA 8.37 Million TOTAL :UA 58.01 Million DATE OF APPROVAL: November 2004 PROJECT LAUNCHING DATE: 17 Jan 2005 PROJECT EXECUTING DATE: July 2005 for 6 years LOAN CLOSING DATE: June 2012 PROJECT COMPONENTS: (i) Farmers Capacity Building (ii) Community Planning and Investment in Agriculture (iii) Support to Rural Financial Services and Marketing (iv) Project Coordination and Management 5 DISTRICT WISE: NGARA PROJECT TITLE: District Agriculture Sector Investment Project EXECUTING BODY: Ngara District Council COORDINATING OFFICE: District Agriculture and Livestock Development Office LOCATION: 30 villages in 17 Wards EFFECTIVE COMMENCING PERIOD: 2006/2007 EXPECTED CLOSING PERIOD: 2011/2012 REPORT NO: VIII REPORTING PERIOD: January 2010 to March 2010 FINANCIAL CATEGORIES: (a) Medium Size Rural Infrastructures (i) Irrigation infrastructures: Tshs 225 Million (ii) Rural roads 10 km: Tshs 11 Million per Kilometer (b) Village Micro-projects Tshs 35 Million per Village (c) Agriculture Technology Tshs 10 Million per Village (d) Farmer Capacity Building (i) Farmer Training under FFS Methodology Tshs 500,000/=per PFG (ii) PFG Mini Grants Tshs 400,000/= per group 6 3.EXECUTIVE SUMMARY The Ngara district council is among 28 districts which implementing Agriculture Sector Development Strategies under support of District Agriculture Sector Investment which aims at increasing agricultural productivity and incomes of rural households, either the council’s mission towards agriculture sector is targeted to improve the economy which resulting into poverty reduction of its community. This report explains what have been done in executing project activities during the period of July 2009 to June 2010 as part of implementing District Agriculture Development Plan. The report is also highlighting what have been done since inception of the project and beneficial changes occurred for that period. Problems and challenges encountered during implementation period as well as recommendations to enhance performance during the reporting period are also given. 4. INTRODUCTION: Ngara District is one of the seven districts of Kagera Region in the very west of mainland Tanzania. It is bordering both the republics of Rwanda and Burundi. The distance from Ngara to Dar-es-Salaam is 1,600 Km and to Mwanza where is the DASIP headquarter is 400 Km, while to the regional headquarters Bukoba is 350 Km. Tarmac roads connect Ngara to Mwanza , Isaka (Kahama District), Kigali (Rwanda) and Bunjumbura (Burundi). Ngara District covers an area of approximately 3,744 Km2, it is divided into 4 divisions, township council, 19 wards and 68 villages. It is further subdivided into 359 sub villages (vitongoji) According to 2002 census, Ngara had 49,082 households with population of 334,409 people. Out of this 30 percent were refugees. Women comprised 52% of local Tanzanian population and 51% of the overall population (with refugees).The annual average growth rate indicated at inter census (1988-2002) was 2.7% for local population and 5.3% including the refugees population. The population density was 89 inhabitants per square kilometer and have been scaled down to 62 inhabitants per square kilometer after refugees repatriation. The average household size is 4.6 people. 7 TABLE.1 Data population census Ngara Aug 2002 Section Male Female Total Local population 110,824 122,047 232,871 69.6% Refugee population 51,490 50,048 101,538 30.4% Total 162,314 172,095 334,409 100% Source: 2002 National Census The district falls in a series of dissected landscapes of altitudes between 1,200 and 1,850 masl. The major landscapes comprise of hills, ridges and scarps, dissected pen plains, plateau, swamps, floods plains, river terraces and minor valleys. The district has two rainy seasons with progressive reduction of precipitation from North to South. Most of the rain falls between the months September/October and March to May. Annual rainfall ranges from 800mm in lowland to 1,400mm in highland. Land is mainly used for agriculture and to a lesser extent for livestock keeping. The main land use types are upland agriculture, wetland agriculture, silviculture, game reserves and livestock keeping. The main food crops that are grown include bananas, beans and maize. Cash crops is coffee. Land is intensively used in the northern part of the district, with smaller part parcels than in the southern part. In permanent settlements, land has been passed from one generation to the other creating defacto family ownership. In general there is a customary land use. Women do have access to land but do not own it. Several types of land use are identified within the inhabited areas as follows (a) Itongo Permanent field with perennial crops in which the homestead is located and is inherited within the clan. Crops grown are banana, coffee, beans, maize and yams. (b) Indimilo Is a cropping system near the Itongo which is composed of various fields of annual crops like maize, cassava, sweet potatoes, yams etc and are grown in rotation. In most cases this is in transition phase Itongo (deterioration) or vice versa (regeneration). (c) Amasebula This is the off season cultivation of valley bottoms swamps .In this system irrigation is a common practice. Crops cultivated are maize, beans, 8 vegetables, sweet potatoes and sometimes rice. These crops are cultivated continuously without fallow . (d) Umushike This is open grassland or bush land. Normally occur between villages far from fields of the Itongo and consists of permanently uncultivated areas, either unsuitable land or virgin land with deep and fertile soils and areas with grass fallow. 5. APPROACHES USED TO COLLECT DATA/INFORMATION In collection of information we usually rely upon the following sources: -Information gathered from Project committee’s progress report on project activities to village council on monthly basis. -Information by report writing from Extension Staff - Information collected during visits under normal routine of monitoring and evaluation in project sites through asking some questions and discussions -Information gathered from visual inspection of the infrastructure or any project There are some key issues that must be taken into consideration when preparing to collect information. These are: -Type of information required in relation to the type of activity monitored or evaluated. -Type of questions and ways of interviewing during face to face discussions with project implementers -Sometimes information may be collected through photographing -Information may require asking some questions or interviewing individuals, group members or project committee 6. THE PROJECT IMPLEMENTATION PLAN Activities planned to be implemented during the third quarter of 2009/10 are as follows: 6.1. Farmer Capacity Building. (a) Season long training of 180 PFGs (b) Facilitation of 180 PFGs undertake economic mini-enterprises (c) Close follow up on WFTs and FFs training programmes and their schedule for FFS trainings 9 6.2. Community Planning and Investment in Agriculture. (a) Consolidation of VADPs to get 2010/11 DADP (b) Continue with implementation of previous projects in progress (c) Monitoring and supervision of completed, on going and new project activities 7. RESOURCES IN TERMS OF FINANCE 7.1 DISBURSEMENT AND EXPENDITURE For the period of July 2009 to June, 2010 the district received 206,559,500/= for implementation of various activities such as construction of village micro projects, long season training, normal office operating expenses, motorcycle operating and maintenance expenses , field allowances and min grant for PFGs. TABLE.2- SUMMARY OF RECEIPTS AND PAYMENTS FOR 2009/2010 FIRST QUARTER DATE RECEIPTS PAYMENTS AMOUNT BALANCE AUGUST 3,042,500 FIELD ALLOWANCE 4,160,000 1,105,000 TRAINING 9,141,000 2,310,000 NANENANE 7,127,500 24,220,000 PFGs 2,800,000 2,300,000 STATIONERIES 110,000 90,000,000 OFFICE EXPENCES 840,000 MOTOR CYCLE ALLOWANCE 960,000 TOTAL 122,977,500 25,138,500 97,839,000 SECOND QUARTER DATE RECEIPT PAYMENTS AMOUNT BALANCE OCTOBER 6,745,000 AGR/OUTPUT 50,969,600 4,175,000 FIELD ALLOW 3,395,000 10 NOVEMBER 3,042,000 DTCs ALLOW 640,000 1,105,000 TRAINING 10,028,000 PFGs 3,800,000 STATIONERY 670,000 BALANCE B/D 97,839,000 MOTOR CYCLE ALLOWANCE 960,000 OFFICE EXP. 21,449,300 TOTAL 112,906,000 91,911,900 20,994,100 THIRD QUARTER DATE RECEIPT PAYMENTS AMOUNT BALANCE JANUARY 8,220,000 MICRO PROJECT 6,320,000 52,000,000 DADPs PLANS 8219,000 3,042,500 FIELD ALLOW 274,000 1,105,000 PFG 500,000 BALANCE B/D 20,994,100 STATIONERY 439,600 MOTOR CYCLE ALLOWANCE 960,000 OFFICE EXP. 270,000 TOTAL 85,361,600 16,982,600 68,379,000 FOURTH QUARTER DATE RECEIPT PAYMENTS AMOUNT BALANCE MAY 3,042,500 FIELD ALLOWANCE 2,590,000 1,105,000 DTCs ALLOWANCE 1,640,000 BALANCE B/D 68,379,000 PFGs 23,600,000 STATIONERY 160,000 11 MOTOR CYCLE ALLOWANCE 960,000 TOTAL 72,526,500 28,950,000 43,576,500 OPENING BALANCE 20,062,382 SUMMARY 63,638,882 PFG CANCELLED CHEQUE 3,200,000 5,000,000 POWER TILLER 1,800,000 BANK BALANCE 68,540,581 68,638,882 5,000,000 8. ACHIEVEMENTS AS REGARDS TO IMPLEMENTATION STATUS 8.1 PHYISICAL STATUS 8.1.1. Farmer Capacity Building. (a) Formation of PFGs. 180 PFGs with various enterprises were formed. The formed groups registered a total of 4206 members, out of whom 2112 were males and 2094 were females. The formed PFGs for 2009/2010 had various enterprises for season long training. The implementation status as per type of enterprise was as shown in the table below; 12 TABLE 3. STATUS OF 2009/2010 PFGs S/NO ENTERPRISES SELECTED NO. OF PFGs PER AN ENTERPRISE NO. OF PFGs UNDERGOING WITH TRAINING NO. OF PFGs NOT UNDERGOING WITH TRAINING REASONS FOR NOT UNDERGOING WITH TRAINIG 01 Groundnuts production 27 25 2 Delay in land preparation 02 Maize production 20 17 3 Delay in land preparation 03 Goat keeping 46 46 0 - 04 Beans production 5 5 0 - 05 Banana production 17 16 1 Delay in land preparation 06 Improved cassava varieties 5 5 0 - 07 Piggery production 9 9 0 - 08 Tree nursery 1 0 1 Delay in procurement of inputs 09 Tomato production 10 10 0 - 10 Onions production 4 4 0 - 11 Local chicken improvement 13 12 1 Shed not yet completed 12 Paddy production 9 7 2 Delay in land preparation 13 Cabbage production 3 3 0 - 14 Fish rearing 2 0 2 Due to lack of Fisheries technician 15 Pine apple production 1 1 0 - 16 Irish potatoes 1 1 0 - 17 Improvement of indigenous cattle 1 1 0 - 18 Dairy bull for changing pure indigenous generation breed to get improved generation 2 1 1 One PFG changed an enterprise from dairy bull to beef bull (Boran) 19 Dairy heifer for modern dairy keeping 4 4 0 - TOTAL 180 167 13 (b) Conducting training for WTFs and FFs on business plans. -Training of WTFs on business planning was conducted from 12/10/2009 to 16/10/2009. A total number of participants were 24. -Training of FF on business planning was carried out from 19/10/2009 to 24/10/2009. The number of participants were 30 13 Subject covered were business plan and agriculture business. No of facilitators were 6 including, 2 DTCs, 2 Co-op Officers, DPO and DMEO (c) Facilitation of 180 PFGs undertakes economic mini-enterprises; The total number of PFGs formed and undertake season long training in 2008/2009 was 176. The PFGs submitted timely their business plans was 130 out of 176. The funds disbursed for mini grants is 52,000,000/= for 130 PFGs each 400,000/=. Currently, only 51 PFGs out of 130 their cheques are in final touches before released to them. Some groups experienced problems with their bank accounts after being closed due to being dormant for a long time. (b) Facilitation of 180 PFGs undertakes economic mini-enterprises; The total number of PFGs formed and undertake season long training in 2008/2009 was 176. The PFGs submitted timely their business plans was 130 out of 176. The funds disbursed for mini grants is 52,000,000/= for 130 PFGs each 400,000/=. Currently only 51 PFGs out of 130 their cheques are in final touches before released to them. Some groups experienced problems with their bank accounts after being closed due to being dormant for a long time. (c) Close follow up on WFTs and FFs training programmes and their schedule for FFS Trainings; The DASIP staff (DPO, DMEO and DTCs) carried out various follow up and supervision purposely to ensure WFT and FFs adhered to their working schedules that aiming to facilitate farmer capacity building based on the enterprise selected and other interested/ cross cutting issues. 9. Community Planning and Investment in Agriculture. (a) Consolidation of VADPs to get 2010/11 DADP; The VADPs from all villages were consolidated to get the DADPs that governed by the budget ceiling. The VADPs had many interventions that needs a lot of money, therefore the interventions with high priorities are the ones included into DADPs for the 2010/2011 financial year. (b) Continue with implementation of previous projects in progress The villages with environmental conservation on areas prone to soil erosion were supervised and advised to accomplish planting tree seedlings before the end of long rains that starts from January to May, 2010. The villages with such projects are Mumilamila in Bugarama ward, Mukalinzi in Muganza ward and Nyabihanga in Bukiriro ward. 14 (c) Monitoring and supervision of completed, on going and new project activities Monitoring and supervision of completed and on going activities were always carried out by some of DTC members, other professional staff with related cadre to the ongoing and completed activities, DPO, DMEO and DTCs. 10.The use of completed projects. The use of completed projects by beneficiaries are under the following categories: (i) Permanent crushes. A total of 13 structures have been constructed in district by the project from 2006/07 – 2009/10. These structures are now effectively used whenever a need arises, for example we had vaccination exercise of all cattle in district in June 2010 where 21,818 cattle were vaccinated against CBPP disease. This is an achievement towards eradication of very notorious diseases in the district (ii) Slaughter slabs. A total of 2 structures constructed since inception of the project. Slaughtering of goats are done, and an average of 3-5 goats are slaughtered daily in each slab. These structures have enable the carcasses to be treated hygienically (iii) Cattle dips. A total of 8 dips have been rehabilitated and 1 dip was constructed since the inception of the project The Ministry of Livestock Development managed to give to the district a subsidized acaricide called Cyba dip. This tics killer were supplied by two companies called BAMBANA which allowed to supply 900lts and AMILEXIN which was given an allocation of supplying 400lts for Ngara cattle dips. So each dip that has been rehabilitated through assistance of DASIP was given 12.5lts. Each dip has the capacity of carrying 12500lts of water. The status of every dip is as follows-; - In Murutabo village at Kirushya Ward the dip is fully used where dipping is done every fortnight, and about 1358 cattle are usually dipped per dipping exercise. -The cattle dip in Bukiriro village, here dipping is done twice a month, and about 742 cattle are brought for dipping in every dipping exercise. -The cattle dip in Mbuba village is working and about 549 cattle are brought for dipping in every dipping exercise 15 -The cattle dip in Mukididili village is also working and dipping is done once in every two weeks. So far about 275 are brought for dipping. -The cattle dip in Nyakisasa village is in full swing and dipping is done twice a month. About 526 cattle are brought for dipping during the exercise. -The cattle dip in Rulenge is complete but, it is not yet working as it needs some minor technical corrections in dip tanks. Contractor has already told to correct and complete the defects so as to allow the dipping exercise to start. -The cattle dip in Murugarama village is working effectively and dipping is done twice a month. About 150 -200 cattle are brought for dipping during the exercise -The cattle dip in Rwinyana village is not yet working. There are some rectification required before the dipping commence. Contractor is already notified to do it very soon so as to let the exercise to start. Generally, the healthy of livestock is now changing and majority of livestock keepers are now enjoying the wealthy of their livestock, since they can sell at realized profitable price, which is about 400,000/= to 600,000/= for a cattle which is weighing 500 kg and above. (iv) Rural feeder roads. A total of 90.1km of feeder roads have been constructed since the beginning of the project. Rehabilitation of rural feeder roads in villages made these roads to be passable throughout a year and have made the communication link between the villages and the main market centers easier. Vehicles are now easily pass on these roads to carry products from community The beneficial villagers are from:- Nyakiziba, Shanga, Kirushya, Murutabo, Ntobeye, Ruganzo, Mukarehe, Murugarama, Mbuba, Kashinga, Djuruligwa, Mukalinzi Kanazi and Murutabo villages To make this rural network sustainable throughout a year, the District Engineer Office is usually include them in district rural feeder roads budget for periodic maintenance every year. (v).Market shed. A total of 2 structures were constructed. The sheds in Keza village in accesss 85 people and Mugoma accommodate 100 people . The structures are complete and are now used by community. 16 (vi).Crop storage structure. 1 structure was rehabilitated. The structure in Ntobeye village has capacity to accommodate 400mt. The structure is mostly used to store various types crops produced within the village. But in recent years the village has been facing serious long dry spell which have been affecting production in general. (v).Environmental conservation. The conservation is done in places where have been falling bear due to various human activities, Such areas are where village community have earmarked for rejuvenation and later to be the village forest reserved area for future use. So far about one hundred thousand tree seedlings have been planted in areas identified by community as mostly affected areas by erosion. These environmental conservation projects are in the following villages:- (i) Mukalinzi in Muganza Ward – in progress – about 10,000 seedlings is expected to be planted (ii) Chivu in Ntobeye Ward – (iii)Rulenge in Rulenge Ward - complete (iv) Nyamahwa in Nyakisasa Ward - complete (v) Mumiramila in Bugarama Ward – in progress, already 15,000 seedlings were planted last season, but this season gap filling is required to replace dead seedlings. But also in another area of about five acre, the community has decided to plant 2255 coffee seedlings. (vi) Nyabihanga in Bukiriro Ward – in progress. 40acres in total have been set aside for tree planting where these acreages have been divided in 10 acres per four sub villages. (vi).Oxenization centre This project is in Chivu village in Ntobeye ward. So far there are 3 ox ploughs 1 ox cart and twelve oxens (6 pairs) which are being used for ploughing. The villagers are benefit the service by a reasonable cost charges of 20,000/= per acre, but they also experience relief out of long time hand hoe drudgery. So far 41 acres of 35 farmers have been ploughed this season. It is there intention to extend the services to the neighboring village aim at increasing the income. 17 TABLE 4. PROJECT IMPLEMENTATION STATUS AS AT END OF JUNE 2010 NGARA DISTRICT FUNDS ISSUED 2006/07/08/09/10 IMPLEMENTATION STATUS WARD VILLAGE PROJECT NAME BEN. DASIP TOTAL complete on going not started Remarks Bukiriro Bukiriro Construction of a slaughter slab 1,660 6,650 8,310 √ Rehabilitation of a cattle dip 4,000 16,000 20,000 √ Nyabihanga Environmental conservation (tree planting) 5,100 20,400 25,500 √ Rusumo Kasulo Construction of a permanent cattle crush 1,580 6,340 7,920 √ Rusumo Rehabilitation cattle dip 2,500 10,000 12,500 √ Construction of a permanent cattle crash. 1,975 7,900 9,875 √ The village need to use all allocation of their funds to construct a new dip Nyamiaga Nyakiziba Construction of a permanent cattle crush 1,580 6,340 7,920 √ Rehabilitation of rural feeder roads 1,580 6,320 7,900 √ Nyamiaga Murukulazo Construction of a permanent cattle crash. 1,580 6,320 7,900 √ Mganza Mukalinzi Construction of a permanent cattle crush 1,580 6,340 7,920 √ Soil and water (environmental) conservation 800 3,200 4,000 Rehabilitation of rural feeder road . 3,000 12,000 15,000 √ Keza Keza Construction of a permanent cattle crush 1,580 6,340 7,920 √ Construction of market structure - godown 5,420 21,680 27,100 √ Mabawe Murugalama Construction of a permanent cattle crush 1,580 6,340 7,920 √ Rehabilitation of a cattle dip 4,000 16,000 20,000 √ Rehabilitation of rural feeder road . 5,000 20,000 25,000 √ Kanazi Kanazi Construction of a slaughter slab 1,660 6,650 8,310 √ Rehabilitation of rural feeder road . 5,000 20,000 25,000 √ Mukarehe Rehabilitation of rural feeder road . 5,000 20,000 25,000 √ Mrusagamba Magamba Construction of a permanent cattle crush 1,580 6,320 7,900 √ Kumubuga Construction of a permanent cattle crush 1,580 6,320 7,900 √ Kabanga Ngundusi Construction of a permanent cattle crush 1,580 6,320 7,900 √ Rehabilitation of rural feeder roads 3,000 12,000 15,000 Djululigwa Rehabilitation of rural feeder road . 5,340 21,360 26,700 √ Mugoma Shanga Rehabilitation of rural feeder roads 3,000 12,000 15,000 Mugoma Construction of a crop marketing shed 7,000 28,000 35,000 √ Kirushya Kirushya Rehabilitation of rural feeder roads 3,600 14,400 18,000 √ 18 Construction of a permanent cattle crash. 1,580 6,320 7,900 √ Murutabo Rehabilitation of a cattle dip. 2,000 8,000 10,000 √ PROJECT IMPLEMENTATION STATUS AS AT END OF JUNE 2010 NGARA DISTRICT FUNDS ISSUED 2006/07/08/09/10 IMPLEMENTATION STATUS WARD VILLAGE PROJECT NAME BEN. DASIP TOTAL complete on going not started Remarks Murutabo Rehabilitation of rural feeder roads 3,600 14,400 18,000 √ Ntobeye Ntobeye Rehabilitation of rural feeder roads 5,600 22,400 28,000 √ Rehabilitation of a crop storage structure. 1,400 5,600 7,000 √ Chivu Rehabilitation of an oxenization centre. 2,000 8,000 10,000 √ Environmental conservation (tree planting) 2,400 9,600 12,000 √ Oxen drawn implements 625 625 1,250 √ Soil and water (environmental) conservation 800 3,200 4,000 √ Rulenge Rulenge Soil and water (environmental) conservation 800 3,200 4,000 √ Construction of a cattle dip. 6,200 24,800 31,000 √ Mbuba Rehabilitation of a cattle dip. 2,000 8,000 10,000 √ Rehabilitation of rural feeder road . 5,000 20,000 25,000 √ Nyakisasa Nyamahwa Soil and water (environmental) conservation 800 3,200 4,000 Rehabilitation of a cattle dip. 2,000 8,000 10,000 √ Construction of a permanent cattle crash. 1,580 6,320 7,900 √ Kashinga Rehabilitation of rural feeder road . 7,000 28,000 35,000 √ Bugarama Rwinyama Rehabilitation of a cattle dip. 2,000 8,000 10,000 √ Need some minor rectification Mumiramila Environmental conservation (tree planting) 5,000 20,000 25000 √ Construction of a permanent cattle crash. 1,580 6,320 7,900 √ Ngara Mjini Mukididili Rehabilitation of a cattle dip. 2,000 8,000 10,000 √ Kibimba Ruganzo Rehabilitation of rural feeder road . 5,420 21,680 27,100 √ Construction of a permanent cattle crash. 1,580 6,320 7,900 √ NB:- Add any other projects that are not mentioned above TOTAL 145,820 581,525 ######## 19 11. PROBLEMS 11.1. PROBLEMS AND CHALLENGES ENCOUNTERED Some PFGs bank accounts closed after being dormant for a long time. Hence cause PFGs members lack a spirit of depositing money to their accounts. Failure by some 2008/09 PFGs to prepare business plan and submit them to the office in time caused delaying in implementing their projects, as well as acquiring mini grants from PCU in time. Failure by some PFGs to have the bank account though they have a business plan in our office, Caused failure to get their mini grants transferred through bank account. Some graduate farmers are eager to go back learning some technologies which were not part of last season long training. Some Contractors are not honesty in completion of their work efficiently especially when some faults are come to be realized during the use of that infrastructure. Failure for the Community to contribute 20% in time for the power tillers, due to some other 20% contribution in other sectors like water, health, education and TASAF projects etc which are going concurrently is an issue. But lying pledges from politicians that they would contribute some amount on power tillers have contributed to bad response. 12. RECOMMENDATIONS:- Capacity building on SACCOS formation and operational mechanism will increase the spirit of investing money through shares among the PFGs members. 20 Financial institutions regulation that force PFGs to open an account by 100,000/= is an obstacle to some vulnerable PFGs that can not afford to collect that some of money. It is a right time now for the PCU to communicate with banks to restore the situation. To advise the Community to be very vigilant in tendering process to get a faithful contractor Keep on insisting the advantage of acquiring the power tillers especially in increasing the farm acreage as well as production. 13. WAY FORWARD DPO, DMEO, DTCs, WFs and FFs continue to pay frequent visits to previous PFGs for encouragement of transfer of knowledge gained through FFS to PFGs’ member own farms and non PFG members’ farms. The team must asses the impact of the knowledge gained from the farmers’ field school among the PFGs members and other adopters. Make a regular follow up to previous PFGs to make sure the mini grants received are used as per plan in a beneficial way. Assisting community to use their power tillers efficiently. Assisting community on proper implementation of village micro projects. To make sure all projects are executed in time, and with quality 14. CONCLUSION:- The project is demand driven. The social benefit of the project include higher improved food security, better human nutrition and earning income that is economically viable to improve the whole welfare of the people and contribute to reduction of poverty. 21 TABLE 5 SUMMARY OF NGARA DASIP PROJECTS UNDER DADPs FOR FY 2010/11 TIME FRAME ACTIVITY TARGET ACTIVITY COST 1st QRT 2nd QRT 3rd QRT 4th QRT RESPONSBLE 1 Support to nanenane exhibition 2,500,000.00 2,500,000 DALDO 2 Support to PFGs economic Mini grants 72,000,000.00 72,000,000.00 DALDO 3 Support to O&OD 8,220,000.00 8,220,000.00 DALDO 4 Support to savings groups and SACCOS 6,120,000.00 6,120,000.00 DALDO 22 5 Training of WFTs and FFs 10,520,000.00 10,520,00.00 DALDO 6 Support office operations and field monitoring and evaluation for district staff 16,590,000.00 4,147,500.00 4,147,500.00 4,147,500.00 4 4,147,500.00 DALDO 7 Construction of Ward Resource Centers at Murugina and Bukiriro Villages 110,000,000.00 110,000,000.00 DALDO 8 Construction of 1 irrigation scheme at Rulenge Village 353,025,000.00 353,025,000.00 DALDO 9 Construction of cattle dip at Rusumo Village 23,000,000.00 23,000,000 DALDO 23 10 Construction of toilets at dip premises in Rusumo, Mukididili, Nyamahwa, Ngundusi, Rwinyana, Murutabo and Bukiriro Villages 35,000,000.00 35,000,000.00 DALDO 11 Construction of 2 cattle crush at Mukarehe and Shanga 20,000,000.00 20,000,000 DALDO 12 Construction of charcoal dam in Kasulo Village 22,000,000.00 22,000,000.00 DALDO 13 Construction of 2 fish ponds in Mumiramila and Bukiriro Villages 1,200,000.00 1,200,000.00 DALDO 14 Rehabilitation of access/ feeder roads at Murukulazo, Kumbuga and Magamba Villages 65,040,000.00 65,040,000.00 DALDO 24 15 Construction of 1 culvert in Nyamahwa Village 5,980,000.00 5,980,000.00 DALDO 16 Planting 123,030 tree seedlings on eroded areas in 4 villages of Bukiriro, Rwinyana, Kirushya and Murutabo 15,230,000.00 15,230,000.00 DALDO 25 TABLE 6. SUMMARY OF DATA SHOWING SOME FARMERS WHO ADOPTED FROM PFGs CROP DATA Ngara District: Data entry from for tracking adoption among farmers who adopted from among PFGs formed in 2008/2009 Village ID Village Farmer Name Six PFG membership PFG Name Crop used during FFS training in 08/09 Crop used in Adoption Field in 09/10 Area planted in Adoption Field in Ha in 09/10 Ha Total yield per Adoption Field in kg in 09/10 (Kg) Yield per Ha of Adoption Field in Kg in 09/10 (Kg) Yield per Ha in kg before adoption (Kg) Value in TZS of Total Yield from Adoption Field in 09/10 (TZS) Mbuba Julian Kaparaga M N Mkombozi Groundnut Groundnut 0.1012 45 450 15 54,000 Mbuba Julias Bachuga M M Mkombozi Groundnut Groundnut 0.2 85 425 35 102,000 Mbuba Clavery Rephael M N Mbiombio Groundnut Maize 0.4 380 1900 120 83,600 Mbuba Didace Ndayi M N Mbiombio Maize 0.4 340 850 90 74,800 Mbuba Tondi Raulian M N Mkombozi Groundnut Banana 0.1012 420 4200 120 126,000 Mbuba John Kabugita M N Majambele Cassava Banana 0.1012 230 2300 40 69,000 Mbuba Oliva Hamad F M Mkombozi Groundnut Maize 0.1012 98 98 45 21,560 Mbuba Joram Daniel M M Mbiombio Groundnut Maize 0.2 79 375 30 17,380 Mbuba Deveta John F M Majambele Cassava Maize 0.1012 85 850 41 18,700 Mbuba Lusia Prasid F M Mbiombio Groundnut Maize 0.4 330 575 110 72,600 Nyamahwa Paschal Machumi M M Umoja Maize Maize 0.81 2500 3086 2000 37,500.00 Nyamahwa Catherine Katama K M Muugano Group Groundnut Groundnut 0.2 200 1000 50 30,000 Bukirio S.Rusaku M M …………… Maize Maize 0.4 1080 6669 1010 324,000 Nyabihanga E. Mudende M M Tujitegemee Maize Maize 0.4 990 6113.3 810 297,000 Nyabihaga Z. Ambati F M Tujitegemee Maize Maize 0.2 450 5557.5 350 135,000 Bukirio D.Machumi M M Songambele Groundnut Groundnut 0.2 100 1235 85 100,000 Nyabihanga C. Mathias M M Tumaini Groundnut Groundnut 0.2 111 1370.9 100 111,000 26 Murugina Helman M M NM Nguvu kazi Banana Banana 0.2 1500 7500 1000 30,000 Murugina Natus N M NM Nguvu kazi Banana Banana 0.4 3000 7500 2000 60,000 Murugina Amon R. NM Umoja Banana Banana 0.4 3000 7500 2000 60,000 Murugina George R M Umoja Banana Banana 0.6 1500 2500 1000 30,000 Murugina Mabawe P/S Umoja Banana Banana 0.4 3000 7500 2000 60,000 Murugina Laurent M NM Nguvu kazi Banana Banana 0.4 3000 7500 2000 60,000 Murugina Mathon B M NM Nguvu kazi Coffee Coffee 0.2 1200 6000 800 840,000 Murugina Selestin M M M Nguvu kazi Banana Banana 0.8 4500 5625 3000 900,000 Murugina Neemiah S M M Tusaidiane Groundnut Groundnuts 0.6 1400 2333 800 1,400,000 Murugina Staford S M Juhudi Maize Maize 0.4 2000 5000 1500 800,000 Murugina Judith R F NM Juhudi Beans Beans 1.2 3000 2500 2000 1,200,000.00 Murugina Salomon N M M Ubumwe Coffee Coffee 0.2 1200 6000 1000 840,000.00 Murugina Edson N M NM Nguvu kazi Coffee Coffee 0.4 2400 6000 2000 1,680,000 Murugina William A M NM Nguvu kazi Banana Banana 1.2 9000 7500 2000 1,800,000 Mkaliza Peter M M M Umoja Rice Rice 0.8 2000 2500 1500 800,000 Mkaliza Philemon G M M Umoja Rice Rice 0.8 4000 5000 3000 3,200,000 Mkaliza Mathon B M M Nguvu kazi Rice Rice 0.4 2000 5000 1500 1,600,000 Mkaliza Ndikumana G. M NM Nguvu kazi Banana Banana 0.4 3000 7500 2500 600,000 Mkaliza Iman G M NM Nguvu kazi Banana Banana 0.4 3000 7500 2500 600,000 Mkaliza Pelus G F NM Tusaidiane Groundnut Groundnuts 0.2 4000 2000 300 400,000 Muhweza Syprian S M NM Nguvu kazi Banana Banana 0.4 3000 7500 2500 600,000 Muhweza Lusian M M NM Nguvu kazi Banana Banana 0.4 3000 7500 2500 600,000 Muhweza Coletha F NM Nguvu kazi Banana Banana 0.4 3000 7500 2000 600,000 Kumuzuza Felecian M NM Nguvu kazi Banana Banana 0.4 3000 7500 2000 600,000 Kumubuga Y. Jeremia M N Upendo Banana Banana 0.1 Not yet Not yet 2000 27 Nyakahula R. Ramadhan M M Mapambazuko Rice Rice 0.2 60 300 200 Kumubuga T. Mulende M M Upendo Banana Banana 0.1 Not yet Not yet 2000 Mzani G. Sylivanus M N Upendo Banana Banana 1.2 Not yet Not yet 2000 Mukarehe Elfazi Rugana M N Mumalanvya Maize Maize 0.8 600 750 150000 Mukarehe Stini Elfazo M N Mumalanvya Maize Maize 0.8 700 875 175,000 Mukarehe Zelda Stini F N Mumalanvya Maize Maize 0.2 350 1750 87,000 Mukarehe Daines F N Mumalanvya Maize Maize 0.3 400 1333 100,000 Mukarehe Patrick Paul M N Mumalanvya Maize Maize 1.2 1000 833 250,000 Mukarehe Jasson Paul M N Mumalanvya Maize Maize 1.2 1300 1083 325,000 Mukarehe Mchunge R. M N Mumalanvya Maize Maize 0.6 750 1250 187,500 Mukarehe Eliazari Israel M M Mumalanvya Maize Maize 0.6 600 1000 150,000 Mukarehe Shem Michael M M Mumalanvya Maize Maize 0.2 250 1250 625,000 Mukarehe Faitha Augustine F M Mumalanvya Maize Maize 1.2 1200 1000 300,000 Mukarehe Sauda Haldi F M Mumalanvya Maize Maize 1.2 1000 833 250,000 Mukarehe John Gabriel M M Mumalanvya Maize Maize 0.2 300 1500 75,000 Mukarehe Rudia Kanani F N Mumalanvya Maize Maize 0.3 350 1167 625,000 Mukarehe Joyce Jophat F N Mumalanvya Maize Maize 1.2 900 750 225,000 Mukarehe Methsela Gachocha M N Mumalanvya Maize Maize 1.2 850 708 75,000 Mukarehe Elia Erasto M N Mumalanvya Maize Maize 1.6 1400 875 625,000 Mukarehe Isaka William M N Mumalanvya Maize Maize 0.6 750 1250 212,500 Mukarehe Juma Phillipo M N Mumalanvya Maize Maize 0.8 700 875 350,000 Mukarehe Richard Sentozi M N Mumalanvya Maize Maize 1.0 900 900 825,000 Mukarehe Phillipo Sentozi M N Mumalanvya Maize Maize 1.1 1350 794 175,000 Chivu Nathan Naftari M M Hakunazungu Coffee Groundnuts 0.4 950 250 300 Chivu Zauda Bruan F M Umoja maize Groundnuts 0.2 210 12.5 105 28 Chivu Raban Mpita M M Tujikomboe Beans Maize 1.2 1500 125 600,000 Chivu Dionizi Peter M M Ngavu kazi maize Groundnuts 0.4 820 253 300,000 Ntobeye Sprian Nahonja M M Umoja Maize Maize 0.4 1000 600 200,000 Ntobeye Elina Sprian F M Tusaidiane Beans Beans 0.2 200 120 800,000 Ntobeye Jamhuri M M M Tusaidiane Beans Beans 0.2 500 200 206,000 Ntobeye Fredrick Devis M M Tusaidiane Beans Beans 0.4 270 200 220,000 Ntobeye Ndaisaba Stivin M M Tusaidiane Beans Beans 0.2 300 150 150,000 Ntobeye Shaban Stivin M M Ujamaa Maize Maize 5.7 9100 3900 2,275,000 Ntobeye Cyprian Senyambo M M Ujamaa Maize Maize 3.2 4480 1300 1,792,000 Ntobeye Josias Katoto M M Ujamaa Maize Maize 1.2 1700 9000 11,400,000 Kashinga James Bundende M M Yote sawa Groundnuts Groundnuts 0.81 600 740 250 900,000 Kashinga Mathayo M M Familia Groundnuts Groundnuts 0.4 300 750 300 450,000 Kashinga Wilybad Mbonye M M Yote sawa Beans Groundnuts 0.81 700 864 320 1,050,000 Kashinga Ruzalia Simon F M Tusongembele Maize Groundnuts 0.81 1800 2222 670 2,700,000 Nyakiziba Josephina F M Umoja group Maize Maize 0.4 300 750 200 120,000 Nyakiziba Eliakimu Yohana M M Umoja group Maize Maize 0.4 800 2000 600 160,000 Nyakiziba Jasson Ndaba M M Mukakugwa Gr. Maize Maize 0.8 1000 1250 500 300,000 Nyakiziba Shaban Bayanda M M Umoja group Maize Maize 0.2 500 1500 250 75,000 Nyakiziba Issa Hamis M M Nyakiziba Gr. Maize Maize 0.4 800 2000 600 200,000 Nyakiziba Obed Obadia M M Nguvu kazi Maize Maize 0.2 400 2000 1000 68,000 Nyakiziba Nahashon Bosevya M M Ushirika Maize Maize 0.8 500 625 200 150,000 Murukulazo Willison Bampiga M M Majambele Banana Banana 0.2 800 400 400 120,000 Murukulazo Ruth Mukiza F M Majambele Banana Banana 0.67 200 298 100 29 20,000 Murukulazo Abela John F M Majambele Banana Banana 0.52 200 389 100 65,000 Murukulazo Keren Jacob F M Majambele Banana Banana 0.056 160 285 900 12,000 Murukulazo Dauson Mihungo M M Majambele Banana Banana 0.02 500 25000 200 50,000 Murukulazo Erick Philimon M M Majambele Banana Banana 0.07 1700 24286 900 120,000 Murukulazo Joseph Kaguru M M Majambele Banana Banana 0.067 1200 17910.4 600 130,000 Murukulazo Jessca Jacob F M Majambele Banana Banana 0.045 750 166667 350 60,000 Murukulazo Magerth Mazige F M Majambele Banana Banana 0.06 1000 16667 400 150,000 Murukulazo Janet Idrisa F M Majambele Banana Banana 0.06 1600 26667 700 156,000 Murukulazo Shabani Jasson M M Tuinuane Maize Maize 0.5 600 1000 300 144,000 Murukulazo Shukuru John M N Tuinuane Maize Maize 1.2 800 667 450 112,500 Murukulazo Mary Elias F N Tuinuane Maize Maize 2 1200 600 100 300,000 Murukulazo Katabazi Mbunde M N Tuinuane Maize Maize 0.6 400 667 200 100,000 Murukulazo Elick Josias M N Tuinuane Maize Maize 0.6 450 750 200 11,200 Murukulazo Esther Gwassa F M Tuinuane Maize Maize 0.8 600 750 400 150,000 Murukulazo Joseph Baseka M M Tuinuane Maize Maize 0.5 500 833 300 125,000 Murukulazo Abdu Idrisa M N Tuinuane Maize Maize 0.4 300 120 200 75,000 Murukulazo Tomson Rukashula M N Tuinuane Maize Maize 0.4 300 120 200 75,000 Murukulazo Donatus Tomason M N Tuinuane Maize Maize 0.6 430 717 250 107,500 Murukulazo Yamungu Richard M N Tuinuane Maize Maize 0.4 300 750 200 75,000 Murukulazo Mapinduzi Misango M N Tuinuane Maize Maize 0.5 500 833 300 12,500 Murukulazo Anostha R. F N Tuinuane Maize Maize 0.4 400 1000 200 10,000 Murukulazo Chiza Sunzu M N Tuinuane Maize Maize 0.8 600 750 350 150,000 Murukulazo Yuliana Emmanuel M N Tuinuane Maize Maize 0.9 700 778 400 175,000 Murukulazo Herman Ntalamka M N Tuinuane Maize Maize 1.6 1100 687.5 600 275,000 Murukulazo Geofrey Ninga M N Tuinuane Maize Maize 1.2 1000 833 600 250,000 30 Murukulazo Tumaini M M Tuinuane Maize Maize 0.8 900 1125 500 225,000 Murukulazo Sospita Luka M M Tuinuane Maize Maize 0.2 360 1800 180 90,000 Murukulazo Today Eustace M M Tuinuane Maize Maize 0.2 380 1900 200 95,000 Murukulazo Keneth M M Tuinuane Maize Maize 1.6 500 312.5 300 125,000 Murukulazo Briton Yohana M N Tuinuane Maize Maize 1.2 1500 1250 800 375,000 Murukulazo Jakson Buhaga M N Tuinuane Maize Maize 0.6 1000 1667 450 250,000 Murukulazo Charles Senye M M Tuinuane Maize Maize 0.6 600 1000 350 150,000 Murukulazo Pendo T M N Tuinuane Maize Maize 0.6 600 1000 300 150,000 Murukulazo Joseph Msengo M N Tuinuane Maize Maize 0.4 500 1250 300 125,000 Murukulazo Amon Brasio M M Tuinuane Maize Maize 0.5 600 1200 450 150,000 Murukulazo Philbert Sadiki M N Tuinuane Maize Maize 0.2 400 2000 200 100,000 Murukulazo Fabian T M M Tuinuane Maize Maize 0.2 300 1500 200 75,000 Murukulazo Alfred Mbunde M N Tuinuane Maize Maize 1.2 800 667 400 200,000 Murukulazo Wizeye Jakamaya M N Tuinuane Maize Maize 0.6 500 833 250 125,000 Murukulazo Mary Joseph F N Tuinuane Maize Maize 0.6 400 667 200 100,000 Murukulazo Dangas Reoben M N Tuinuane Maize Maize 0.8 600 750 300 150,000 Murukulazo Foibe Brasio F N Tuinuane Maize Maize 1.2 700 583 300 175,000 Murukulazo Ernest Brasio M N Tuinuane Maize Maize 0.52 500 962 250 125,000 Murukulazo U. Josias M N Tuinuane Maize Maize 0.2 600 3000 300 150,000 Murukulazo Josias Bamenya M M Tuinuane Maize Maize 1.2 1500 1250 800 375,000 Murukulazo Roza Jekamaya F N Tuinuane Maize Maize 0.6 400 667 200 100,000 Murukulazo Tadeo Jekamaya M N Tuinuane Maize Maize 0.6 500 833.3 300 125,000 Mumilamira Simon Bahati M M Nguvu kazi Beans Groundnuts 0.18 700 3889 320 1,050,000 Mumilamira Mathias M M Mategemeo Groundnuts Groundnuts 0.4 300 750 300 450,000 Mumilamira Marianus M M Tuinuane Maize Maize 0.4 300 750 200 120,000 31 Mumilamira Clemence Angelo M M Tuinuane Maize Maize 0.6 600 1000 300 150,000 Mumilamira Charles Balimpaka M M Nguvu kazi Maize Maize 0.2 400 2000 200 100,000 Mumilamira Teonest Milenzo M M Tuinuane Maize Maize 1.2 800 667 400 200,000 Mumilamira Swedy Mohamed M M Tuinuane Maize Maize 0.5 600 1200 450 150,000 Rusumo M. Geofrey M M Juhudi Groundnuts Maize 0.404 1500 1800 1000 300,000 Rusumo S. Bonifasi M M Juhudi Groundnuts Maize 0.404 1500 1800 1000 300,000 Rusumo E. Kihata M M Juhudi Groundnuts Maize 0.404 1500 1700 1000 300,000 Rusumo E. Daud M M Nyota njema Tomato Maize 0.404 1500 1700 1000 300,000 Rusumo E. Thobias F M Umoja ni nguvu Groundnuts Groundnuts 0.404 400 600 200 600,000 Rusumo S. Rushatsi M N Nyota njema Tomato Maize 0.404 1500 1800 1000 300,000 Rusumo M. Aggrey M M Umoja ni nguvu Tomato Maize 0.404 1500 1700 800 300,000 Rusumo Juma Julius M M Juhudi Groundnuts Groundnuts 0.404 400 600 200 600,000 Rusumo B. Elizimus F N Juhudi Groundnuts Maize 0.404 1500 1700 1000 300,000 Rusumo M. Thobias F N Umoja ni nguvu Groundnuts Groundnuts 0.202 200 300 150 300,000 Rusumo M. Joseph M N Umoja ni nguvu Groundnuts Groundnuts 0.404 400 500 200 600,000 Rusumo Edina Fedrick F N Jitume Groundnuts Groundnuts 0.202 200 300 150 300,000 Rusumo David K M M Jitume Groundnuts Groundnuts 0.202 200 350 150 300,000 Rusumo Godeliva F M Umoja ni nguvu Maize Maize 0.404 1500 1800 1000 300,000 Rusumo Godi Vital M N Umoja ni nguvu Groundnuts Groundnuts 0.202 200 350 150 300,000 Rusumo M. Faustine F N Upendo Groundnuts Groundnuts 0.202 200 350 150 300,000 Rusumo Pili Juma F N Nyota njema Tomato Maize 0.404 1500 1800 1000 300,000 Rusumo H. Bonifasi F M Nyota njema Tomato Maize 0.404 1500 1800 1000 300,000 Rusumo Iman Makobwe M N Jitume Groundnuts Maize 0.101 375 400 250 50,000 Rusumo R. Ntangola M N Nyota njema Tomato Maize 0.202 750 1000 500 150,000 Rusumo T. Thomson M M Umoja ni nguvu Groundnuts Groundnuts 0.404 400 600 200 600,000 32 Rusumo W. James M M Upendo Groundnuts Groundnuts 0.404 400 600 150 300,000 Kanazi Matayo Lyaban M N Nguvu kazi Maize Maize 0.6 400 667 200 100,000 Kanazi Cesilia Rauben F N Nguvu kazi Maize Maize 1 1200 1200 0 300,000 Kanazi Miburo G. M N Nguvu kazi Maize Maize 1.1 1800 1636.4 466.8 360,000 Kanazi Nyamusi Mathayo M N Nguvu kazi Maize Maize 2.1 2200 10476 895.2 440,000 Kanazi Thomson Buhuhute M N Nguvu kazi Maize Maize 0.9 900 1000 800 225,000 Kanazi S. Abdallah M N Nguvu kazi Maize Maize 0.6 800 1333 267 200,000 Kanazi John Cyprian M N Nguvu kazi Maize Maize 0.4 200 750 150 600,000 Kanazi Yamungu Hiza M N Nguvu kazi Maize Maize 0.4 350 875 175 750,000 Kanazi Innocent Mbasha M N Nguvu kazi Maize Maize 0.8 750 1188 712 237,500 Kanazi James Nkolonka M M Nguvu kazi Maize Maize 0.7 800 1143 457 200,000 Kanazi Shaban Kayugi M N Ujamaa Maize Maize 0.5 500 1000 0 125,000 Kanazi Rama Kayugi M N Ujamaa Maize Maize 0.8 700 875 525 175,000 Kanazi Reverian G. M N Ujamaa Maize Maize 0.4 350 875 175 875,000 Kanazi Ben Ndyabanigwa M N Ujamaa Maize Maize 1 1600 1600 0 400,000 Kanazi Faith Eustace F N Ujamaa Maize Maize 0.9 850 944 300 170,000 Kanazi Birungila M N Ujamaa Maize Maize 0.6 850 1416 756 170,000 Kanazi Magreth Yustace F N Ujamaa Maize Maize 0.4 400 1000 200 100,000 Kanazi Kidende Yulian M N Ujamaa Maize Maize 0.5 550 1100 0 137,500 Kanazi Dominic M. M N Ujamaa Maize Maize 0.8 660 825 495 165,000 Kanazi G. Nicodem F N Ujamaa Maize Maize 0.8 480 600 300 125,000 Kanazi Belitha Nicolaus F N Ujamaa Maize Maize 0.9 840 944 756 212,500 Kanazi Filemon Bigabo M N Ujamaa Maize Maize 0.4 350 875 175 87,500 Kanazi James Bigabo M N Ujamaa Maize Maize 0.7 650 928 375 162,500 Kanazi Fareth M N Ujamaa Maize Maize 1.2 1300 1083 865 325,000 33 Ruganzo Obed .J M M Nguvu kazi Maize Maize 0.5 400kg 800kg 300kg 120,000 Ruganzo Kausawa A. M M Nguvu kazi Maize Maize 0.6 340kg 566kg 200kg 60,000 Ruganzo Karugila S M M Nguvu kazi Maize Maize 0.7 600kg 3371.4kg 350kg 105,000 Ruganzo Sadiki A. M M Nguvu kazi Maize Maize 1.2 1500kg 1250kg 800kg 240,000 Ruganzo Rauben O M M Nguvu kazi Maize Maize 0.8 900kg 875kg 3000kg 12,000 Ruganzo Mathayo S. M M Nguvu kazi Maize Maize 1.2 6000kg 500kg 350kg 105,000 Ruganzo Jenetha A F M Nguvu kazi Maize Maize 0.8 100kg 125kg 600kg 180,000 Ruganzo Nehemia R. M M Nguvu kazi Maize Maize 1.2 1500kg 1250kg 800kg 240,000 Ruganzo Betha O F M Nguvu kazi Maize Maize 0.5 340kg 680kg 200kg 60,000 Ruganzo Asia M. F M Nguvu kazi Maize Maize 0.6 380kg 633kg 300kg 90,000 Ruganzo Thomas M. M M Tujitahidi Maize Maize 0.5 450kg 900kg 400kg 120,000 Ruganzo Yohana S M N Tujitahidi Maize Maize 0.25 150kg 680kg 100kg 30,000 Ruganzo Baraka F M M Tujitahidi Maize Maize 0.6 150kg 250kg 250kg 75,000 Ruganzo Misago E M N Tujitahidi Maize Maize 0.2 150kg 1500kg 200kg 60,000 Ruganzo Pastory R M M Tujitahidi Maize Maize 0.25 300kg 2000kg 250kg 75,000 Ruganzo Joseph R M M Tujitahidi Maize Maize 0.6 500kg 1000kg 400kg 120,000 Ruganzo Elina G. F N Tujitahidi Maize Maize 1.2 600kg 333kg 300kg 120,000 Ruganzo Innocent M M M Tujitahidi Maize Maize 0.8 400kg 950kg 260kg 78,000 34 LIVESTOCK DATA Ngara District: Data entry from for tracking adoption among farmers whop adopted from among PFGs formed in 2008/2009 Village ID Village Farmer Name Six PFG membershi p PFG Name Livestoc k type used during FFS training in 08/09 Livestoc k type adopted in 09/10 Numbe r of animal s adopte d in 09/10 Name of Livestock product from adopted animal Productio n per animal in 09/10 Total livestock productio n before Adoption Total livestock productio n before Adoption Value in TZS of total livestock production in 09/10 (TZS) Murukulazo Richard Bigezehe M M Ujamaa Goat Goat 4 2 milk 1 7 0.5 150,000.00 Murukulazo Philipo Ruta M M Ujamaa Goat Goat 5 FM 2 3 10000 20,000.00 Murukulazo Julias Mshorogoto M M Ujamaa Goat Goat 2 FM 1 2 25000 40,000.00 Murukulazo Furaha William M M Ujamaa Goat Goat 1 FM 0 1 20000 30,000.00 Murukulazo Jackson Geofrey M M Ujamaa Goat Goat 15 FM 10 5 25000 40,000.00 Murukulazo Maendeleo Bucha M M Ujamaa Goat Goat 5 FM 2 5 25000 40,000.00 Murukulazo W. Mshorogoto M M Ujamaa Goat Goat 5 FM 0 3 20000 40,000.00 Murukulazo Pastory Nestory M M Ujamaa Goat Goat 7 FM 4 3 30000 30,000.00 Murukulazo A. Fabian M M Ujamaa Goat Goat 8 FM 4 3 30000 30,000.00 Murukulazo Syrivery Maromba M M Ujamaa Goat Goat 2 FM 7 0 25000 30,000.00 Murukulazo Jastine Bucha M M Ujamaa Goat Goat 2 FM 1 1 25000 30,000.00 Murukulazo Kevina Daniford F M Ujamaa Goat Goat 7 FM 2 5 25000 30,000.00 Murukulazo Agnes Philipo F M Ujamaa Goat Goat 6 FM 2 4 25000 30,000.00 Mukarehe Bahati Mchunge M M Migisha Goat Goat 8 FM 1 4 12 24,000 Mukarehe Heneriko Elisha M N Migisha Goat Goat 5 FM 2 3 13 125,000 35 Mukarehe Edmond Methusella M N Migisha Goat Goat 12 FM 1 6 18 30,000 Mukarehe Kwigize Basisingohe M N Amani Goat Goat 6 FM 1 3 9 180,000 Mukarehe Timothy M M Amani Goat Goat 6 FM 1 3 9 180,000 Mukarehe Mjinja God M N Amani Goat Goat 7 FM 1 3 10 17,500 Mukarehe Isack Mary M M Amani Goat Goat 3 FM 2 2 11 90,000 Mukarehe Dani God M M Amani Goat Goat 4 FM 2 2 12 120,000 Mukarehe Myambele Clemencia F M Amani Goat Goat 4 FM 2 2 12 120,000 Mukarehe Isack Tumaini M N Amani Goat Goat 10 FM 1 5 15 250,000 Mukarehe Japhet Daudi M N Amani Goat Goat 4 FM 2 2 10 120,000 Mukarehe Aniset Sunday M N Amani Goat Goat 5 FM 2 3 13 150,000 Mukarehe Josias Mchunge M N Amani Goat Goat 11 FM 1 5 16 275,000 Mukarehe Rushakigwa M N Amani Goat Goat FM Nyamahwa Evarista Gerad M M Chapuchap u Goats Goats 5 Goat IKID 3 13 390,000 Nyamahwa Alex Athanaz M M Umoja Group Goats Goats 2 Goat IKID 2 6 180,000 Nyamahwa Veronika Cyprian F N Tweyunge Group Goats Goats 4 Goat IKID 4 12 360,000 Keza Paul Kigongo M N Caprine Caprine 10 Meat 8-10Kg 8-10kg 14-16Kg 35,000 Keza Keza Bileba Ntuyenaba M N Caprine Caprine 5 Meat 10Kg @ 10kg@ 15Kg@ 36,000 Keza Keza Andrea Kiata M N Caprine Bovine 7 Meat/Milk 200kg 200kg 2500- 3000 650,000 Keza 2Lts 2Lt @ 2-3Lt Keza Goletha Michael M N Caprine Caprine 8 Meat 9Kg 13-15Kg 13-15kg 36 30,000 Murugina J. Ruhaga M M Rukundo Goat Goat 5 Goat 2 4 8 400,000 Murugina Suzana R F M Rukundo Goat Goat 5 Goat 2 4 8 400,000 Murugina Simon Z. M M Rukundo Goat Goat 5 Goat 2 4 8 400,000 Mrugarama Elias D M M Sharama Pigs Pigs 3 Pigs 7 2 40 800,000 Mrugarama Jasson. A M M Sharama Pigs Pigs 3 Pigs 7 2 40 800,000 Mrugarama Deus .J M M Sharama Pigs Pigs 3 Pigs 7 2 40 800,000 Murugina Evance .E M M Mshikaman o Goat Goat 5 Goat 2 4 8 400,000 Murugina Marko .E M M Mshikaman o Goat Goat 5 Goat 2 4 8 400,000 Murugina Dolas P F M Mshikaman o Goat Goat 5 Goat 2 4 8 400,000 Murugina Iman R. F NM Mshikaman o Goat Goat 2 Goat 2 2 4 200,000 Murugina Ezekia .J F NM Mshikaman o Pigs Pigs 2 Pigs 7 1 21 420,000 Murugina Bazompola S. M M Mshikaman o Goat Goat 5 Pigs 2 3 6 300,000 Murugaram a Bwilinde F NM Ushirika Goat Goat 2 Pigs 2 2 4 200,000 Murugaram a Philmon.M M NM Usalama Pigs Pigs 2 Goat 7 1 21 420,000 Murugaram a Kilula W. M NM Usalama Goat Goat 2 Goat 7 1 21 420,000 Murugina Kandida .D M NM Rukundo Goat Goat 2 Goat 2 2 4 200,000 Murugina Machumi.J M NM Muungano Goat Goat 2 Goat 7 2 6 120,000 Murugaram a Simon .M M M Ushirika Goat Goat 2 Goat 2 2 4 200,000 Murugina Fales .S M NM Rukundo Pigs Pigs 2 Pigs 2 2 4 200,000 Murugina Ignation .W. M M Rukundo Pigs Pigs 3 Pigs 2 3 6 300,000 Murugina Diana .D F M Rukundo Goat Goat 5 Goat 2 4 8 400,000 Murugina Paschal. W M M Muungano Goat Goat 3 Goat 7 2 40 800,000 Murugaram a Jaktan .J M M Sharama Goat Goat 3 Goat 7 2 40 800,000 Murugaram a Raban .A M M Sharama Goat Goat 3 Goat 7 2 40 800,000 Murugaram a Banyikwa M M M Ushirika Goat Goat 3 Goat 2 3 6 300,000 37 Murugaram a Helena B F NM Ushirika Goat Goat 2 Goat 2 1 2 100,000 Murugaram a Dora L. F NM Ushirika Goat Goat 2 Goat 2 1 2 100,000 Murugina Reverian M NM Muungano Goat Goat 1 Goat 1 1 1 50,000 Murugina Wilbard M NM Muungano Goat Goat 3 Goat 2 3 6 300,000 Murugina Deogratias M NM Muungano Goat Goat 2 Goat 2 2 4 200,000 Keza Levania Andrea F M Tegemeo Caprine Caprine 6 Meat 15kg 8 Keza John Winstone M M Tegemeo Caprine Caprine 8 Meat 14kg Keza Simon Ntakije M M Tegemeo Caprine Caprine 7 Meat 10 Keza Levania Andrea F M Tegemeo Caprine Putry 80 Eggs/Me at 120x20 Keza Julius Winstone M M Tegemeo Caprine Caprine 10 Meat 1.5kgx20 Keza Musa Amos M M _ Caprine Caprine 5 Meat 10kg Keza Juma Winstone M M Tegemeo Caprine Caprine 7 Meat 8kg Keza Alsen Kaman M NM _ Caprine Caprine 30 Meat 8kg Keza Bovine 15 Meat/milk 200kg Keza Juster Rugomora F NM _ Caprine Caprine 7 Meat 1-2Lts Putry 15 Meat 10kg Kanazi Gerald Isarel M N Ujamaa Goat Goat 4 FM 1 0 5 15,000 Kanazi Phillimon Nico M N Ujamaa Goat Goat 1 FM 2 1 4 140,000 Kanazi Agnes Bunuma M M Ujamaa Goat Goat 2 FM 3 1 4 100,000 Kanazi Patrick Nicolaus F N Ujamaa Goat Goat 4 FM 6 2 8 240,000 Kanazi Severian Godan M N Ujamaa Goat Goat 7 FM 1 1 9 270,000 Kanazi Grace Baranyikwa F N Ujamaa Goat Goat 2 FM 2 3 7 210,000 Kanazi KaburoJulius M N Ujamaa Goat Goat 2 FM 2 1 5 150,000 Kanazi Furaha Juliaus M N Ujamaa Goat Goat 4 FM 1 2 7 210,000 Kanazi Alfred Boniface M M Ujamaa Goat Goat 3 FM 3 0 6 180,000 Kanazi Patrick Nocolaus M N Ujamaa Goat Goat 0 FM 3 1 4 120,000 Kanazi Bahati Nicolaus M N Ujamaa Goat Goat 4 FM 2 2 8 240,000 Kanazi Minani Kaburo M N Ujamaa Goat Goat 2 FM 1 1 4 120,000 Kanazi Shukuru Syprian M N Ujamaa Goat Goat 1 FM 2 3 6 180,000 38 Kanazi John Msimbakule M N Ujamaa Goat Goat 4 FM 2 2 8 240,000 Kanazi Dan Mashahu M N Ujamaa Goat Goat 5 FM 1 1 7 210,000 Kanazi Muziki Andrea M N Ujamaa Goat Goat 3 FM 2 4 9 270,000 Kanazi Tereza Karoli M N Ujamaa Goat Goat 2 FM 1 1 4 120,000 Ruganzo Pendo M M M Mshikaman o Goat Goat 2 FM 2 2 4 75,000 Ruganzo Samwel Y M M Mshikaman o Goat Goat 3 FM 2 0 5 150,000 Ruganzo Obed M M Mshikaman o Goat Goat 4 FM 7 0 5 15,000 Ruganzo Sofia B F M Mshikaman o Goat Goat 2 Goat 3 2 5 15,000 Ruganzo Tonny J M M Mshikaman o Goat Goat 4 FM 2 4 8 240,000 Ruganzo Leath S F M Mshikaman o Goat Goat 2 FM 3 0 5 15,000 Ruganzo Andea M M Mshikaman o Goat Goat 7 FM 6 7 13 39,000 Ruganzo Simon R M M Mshikaman o Goat Goat 5 FM 2 5 7 210,000 | false |
# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA WIZARA YA KILIMO MAJINA YA WALIOCHAGULIWA KUJIUNGA NA MAFUNZO YA KILIMO KUPITIA PROGRAMU YA BBT-YIA FEBRUARI, 2023 Na MKOA ANAOTOKA HALMASHAURI ANAYOTOKA JINA KAMILI JINSIA 1 ARUSHA Arusha CC TIMOTHY SHIRIMA ME 2 ARUSHA Arusha CC RAMADHANI MGOMBA ME 3 ARUSHA Arusha CC SAMWEL SANDU ME 4 ARUSHA Arusha CC OMARI NCHASI ME 5 ARUSHA Arusha CC NEEMA MCHARO KE 6 ARUSHA Arusha CC DEBORA OLOMY KE 7 ARUSHA Arusha CC WILIAM SHEHEMBA ME 8 ARUSHA Arusha CC NELSON NZIRA ME 9 ARUSHA Arusha CC MARIAM HUSSEIN BONGI KE 10 ARUSHA Arusha CC JOYCE BHOKE GNONO KE 11 ARUSHA Arusha DC JOSEPH LUKUMAY ME 12 ARUSHA Arusha DC ABDIFATAH MUSSA LAIZER ME 13 ARUSHA Arusha DC EVA TANAKI KE 14 ARUSHA Arusha DC ANNA MCHOME KE 15 ARUSHA Karatu DC RICHARD MOLLEL ME 16 ARUSHA Karatu DC VERONICA KOMBA KE 17 ARUSHA Karatu DC EMANUEL SARWATT ME 18 ARUSHA Karatu DC EMMANUEL EDWARD ME 19 ARUSHA Longido DC ABDALAH NYANGE ME 20 ARUSHA Longido DC WILLIAM MOLLEL ME 21 ARUSHA Longido DC JUDITH LEMA KE 22 ARUSHA Meru DC NEREY MOSHA ME 23 ARUSHA Meru DC JUDITH MMASA KE 24 ARUSHA Meru DC HADIJA MWAKATAPANIA KE 25 ARUSHA Meru DC BAIRO KASSONE ME 26 ARUSHA Monduli DC NEEMA MOLLEL KE 27 ARUSHA Monduli DC MEPUKORI BARAKA ME 28 ARUSHA Monduli DC DAUDI LAIZER ME 29 ARUSHA Ngorongoro DC ESSAU MIGUNZU ME 30 ARUSHA Ngorongoro DC OPEN BALAGERERI ME 31 ARUSHA Ngorongoro DC ODES CHIZA KE 32 DAR ES SALAAM Dar es Salaam CC GEORGE YUNGA ME 33 DAR ES SALAAM Dar es Salaam CC SARAH HAULE KE 34 DAR ES SALAAM Dar es Salaam CC MORICE MORAND TIRUKAIZILE ME 35 DAR ES SALAAM Dar es Salaam CC ELLY ELIAS ME 36 DAR ES SALAAM Dar es Salaam CC CHARLES MASASSY ME 37 DAR ES SALAAM Dar es Salaam CC STANSILAUS MALLYA ME 38 DAR ES SALAAM Dar es Salaam CC MACDAUT SHAYO ME 39 DAR ES SALAAM Dar es Salaam CC TUMSIME EZRA BILAURI BILAURI ME 40 DAR ES SALAAM Dar es Salaam CC IDD MWEVI ME 41 DAR ES SALAAM Dar es Salaam CC PRACIDIA SIMEO KE 42 DAR ES SALAAM Dar es Salaam CC SHANI MAGUMBO KE 43 DAR ES SALAAM Dar es Salaam CC FATUMA HAJI KE 44 DAR ES SALAAM Dar es Salaam CC DISMAS MASSAWE ME 45 DAR ES SALAAM Kigamboni MC JERRY COSMAS MALIGANYA ME 46 DAR ES SALAAM Kigamboni MC MAMSANGA NGUZO KE 47 DAR ES SALAAM Kigamboni MC WOLFRAM LIGELELE ME 48 DAR ES SALAAM Kigamboni MC PATRICK KAZINJA ME 49 DAR ES SALAAM Kigamboni MC JOYCE MWAKASALA KE 50 DAR ES SALAAM Kigamboni MC JAQULINE MWAIGAGA KE 51 DAR ES SALAAM Kinondoni MC MICHAEL SANGA ME 52 DAR ES SALAAM Kinondoni MC LAZARO MIKOMANGWA ME 53 DAR ES SALAAM Kinondoni MC JOYCE NSEMWA KE 54 DAR ES SALAAM Kinondoni MC TAMRINAH BHANNE KE 55 DAR ES SALAAM Kinondoni MC AMINA KASSIM SAID MDEMU KE 56 DAR ES SALAAM Kinondoni MC RABIAH MTAGE AL-KARITTY KE 57 DAR ES SALAAM Kinondoni MC MAGDALENA CHUWA KE 58 DAR ES SALAAM Kinondoni MC JAMES NONGU ME 59 DAR ES SALAAM Kinondoni MC CHRISTIAN BRAYSON ME 60 DAR ES SALAAM Kinondoni MC EVANCE DANIEL MWAIPOPO ME 61 DAR ES SALAAM Kinondoni MC GABRIEL MHANDO ME 62 DAR ES SALAAM Kinondoni MC NICKSON MAKISHE ME 63 DAR ES SALAAM Temeke MC OMARI RAJABU ZIKATIMU ME 64 DAR ES SALAAM Temeke MC ANNETH MKETO KE 65 DAR ES SALAAM Temeke MC JOVIN MUTUNGI ME 66 DAR ES SALAAM Temeke MC NOURAH ALUOTCH KE 67 DAR ES SALAAM Temeke MC EMILLIAN MYALLA ME 68 DAR ES SALAAM Temeke MC GRACE KISAKA KE 69 DAR ES SALAAM Temeke MC MWANAIDI MBEKIYA KE 70 DAR ES SALAAM Temeke MC HOPE KABONA KE 71 DAR ES SALAAM Temeke MC SHEILA MZEE KE 72 DAR ES SALAAM Temeke MC MWAJUMA MAJALA KE 73 DAR ES SALAAM Temeke MC IBRAHIM SAID ME 74 DAR ES SALAAM Temeke MC ALLY DHAHABU ME 75 DAR ES SALAAM Ubungo MC NAOMI MALEMA KE 76 DAR ES SALAAM Ubungo MC MICHAEL MWAMBAGE ME 77 DAR ES SALAAM Ubungo MC MELAU MOLLEL ME 78 DAR ES SALAAM Ubungo MC RAMDHANI MBOGO ME 79 DAR ES SALAAM Ubungo MC STANSLAUS MSALIKE ME 80 DAR ES SALAAM Ubungo MC STEVEN YORAM ME 81 DAR ES SALAAM Ubungo MC JAMES VENANCE ME 82 DAR ES SALAAM Ubungo MC GOODLUCK MPONGO ME 83 DAR ES SALAAM Ubungo MC BILLY JOSEPH KADUMA ME 84 DAR ES SALAAM Ubungo MC MAGRETH NYAKUNGA KE 85 DAR ES SALAAM Ubungo MC FATUMA MHINA KE 86 DAR ES SALAAM Ubungo MC REHEMA MNKENI KE 87 DAR ES SALAAM Ubungo MC JENIPHA CHRISTIAN KE 88 DAR ES SALAAM Ubungo MC SWAHIBU REHANI ME 89 DODOMA Bahi DC NYAMBUYA NKAMBI ME 90 DODOMA Bahi DC KEZIA MKWAWI KE 91 DODOMA Bahi DC BATOROMAYO MDEMU ME 92 DODOMA Bahi DC EMMANUELA CHILALA KE 93 DODOMA Chamwino DC BENNO MTUNG'E ME 94 DODOMA Chamwino DC SADA MJIMBA KE 95 DODOMA Chamwino DC OTHUMAN THOMASI ME 96 DODOMA Chamwino DC EVEEREST MNZAVA ME 97 DODOMA Chamwino DC JANE MASIGATI KE 98 DODOMA Chemba DC OMBENI MBISE ME 99 DODOMA Chemba DC JOSEPH MSODOKI ME 100 DODOMA Chemba DC SHAKILA NYERERE KE 101 DODOMA Dodoma CC MOHAMED KOMBO ME 102 DODOMA Dodoma CC GENOVEVA MSUYA KE 103 DODOMA Dodoma CC DAVID MKONGWA ME 104 DODOMA Dodoma CC RAY MARK ME 105 DODOMA Dodoma CC ASHRAF SAID ME 106 DODOMA Dodoma CC EVANCE RWESHEMEZA ME 107 DODOMA Dodoma CC PHYLBERT RWEYEMAMU ME 108 DODOMA Dodoma CC DISMAS KIRIA ME 109 DODOMA Dodoma CC MORIS MAZENGO ME 110 DODOMA Dodoma CC FESTO LULU ME 111 DODOMA Dodoma CC MARIAM DADIA KE 112 DODOMA Dodoma CC JANETH JAMES KE 113 DODOMA Dodoma CC MWANAIDI HASHIM MAKANDA KE 114 DODOMA Dodoma CC PAMELA BETABULA KE 115 DODOMA Dodoma CC ROSEMARY SHANI KE 116 DODOMA Dodoma CC LABANUS EDWARD RICHARD ME 117 DODOMA Dodoma CC OMARY ALLY NGALLA ME 118 DODOMA Dodoma CC IS-HAQ SILVANUS BAGAMBI ME 119 DODOMA Dodoma CC PETER ALEX MABELE ME 120 DODOMA Dodoma CC JOSHUA GILBERT MNZAVA ME 121 DODOMA Dodoma CC AMAN JOSEPH MARANDU ME 122 DODOMA Dodoma CC AMADEUS IGNAS MROSO ME 123 DODOMA Dodoma CC JAMES JOHN NONGU ME 124 DODOMA Dodoma CC HENRY FESTO AFRAEL ME 125 DODOMA Dodoma CC KARIMU ALLY RASHID ME 126 DODOMA Dodoma CC MSHANGI BENEDICT MBAGIBA ME 127 DODOMA Dodoma CC RAZACK YOHANA WAHONE ME 128 DODOMA Kondoa DC SALIM MAALIM ME 129 DODOMA Kondoa DC SHARIFA ATHUMAN SHAKA KE 130 DODOMA Kondoa DC AMINA JUMANNE ISONDO KE 131 DODOMA Kondoa TC ZENATH GEMBE KE 132 DODOMA Kondoa TC RAMADHANI GAMAHA ME 133 DODOMA Kondoa TC DEOGRATIUS SADALA ME 134 DODOMA Kongwa DC HAWA ABDI JUMA KE 135 DODOMA Kongwa DC MICHAEL MAYALA ME 136 DODOMA Kongwa DC PENDO MWALUKO KE 137 DODOMA Kongwa DC AZIZA ABDI JUMA KE 138 DODOMA Mpwapwa DC JOHARI HAJI KILINYA KE 139 DODOMA Mpwapwa DC YOHANA SIJILA ME 140 DODOMA Mpwapwa DC SAMWELI SAMSON MBONDO ME 141 GEITA Bukombe DC LEVINA RUTTA KE 142 GEITA Bukombe DC ELISHA DAUD NTUMBA ME 143 GEITA Bukombe DC SALOME PHILBETH BUDIKA KE 144 GEITA Chato DC AMILTON CHAPUGA ME 145 GEITA Chato DC STANSLAUS KITENA ME 146 GEITA Chato DC HUDSON GIPOKO KE 147 GEITA Geita DC RICHARD NKANDA ME 148 GEITA Geita DC BENEDICTO KITULA ME 149 GEITA Geita DC PENDO LUGWISHA KE 150 GEITA Geita TC PETER SUMUNI ME 151 GEITA Geita TC ROWLINGS KAAYA ME 152 GEITA Geita TC NEEMA KASUMBI KE 153 GEITA Mbogwe DC FRANK MWESIGA SYMPHORIANI BUKOMBE ME 154 GEITA Mbogwe DC REBEKA JOHN KE 155 GEITA Mbogwe DC NEEMA LUGWISHA KE 156 GEITA Nyang'hwale DC AGNES DEUS MOHAMED KE 157 GEITA Nyang'hwale DC MAKELEMO DAUD ME 158 GEITA Nyang'hwale DC SAID MAKELELE ME 159 KAGERA Biharamulo DC JOHN JOHN ME 160 KAGERA Biharamulo DC MARRY KACHIRA KE 161 KAGERA Biharamulo DC AYUBU MSOKE ME 162 KAGERA Bukoba DC ANSILA KABOBO KE 163 KAGERA Bukoba DC PROSPER MUTASHABA ME 164 KAGERA Bukoba DC BEATHA ZACHARIA KE 165 KAGERA Bukoba MC ASHIMU ZUBERI ME 166 KAGERA Bukoba MC ANICIA MARTINE KE 167 KAGERA Bukoba MC DORICE JAPHES MKWENDA KE 168 KAGERA Bukoba MC ANOLD CHIBULA ME 169 KAGERA Karagwe DC KILANDO MANGI KE 170 KAGERA Karagwe DC SHARON UMUHETA KE 171 KAGERA Karagwe DC AMPHREY MULILO ME 172 KAGERA Karagwe DC SPERITONE MZUKA ME 173 KAGERA Karagwe DC VASIUS EVARISTER ME 174 KAGERA Karagwe DC REGINA MPANGALA KE 175 KAGERA Kyerwa DC SALVIUS SIMON ME 176 KAGERA Kyerwa DC FRANCE RUIZA ME 177 KAGERA Kyerwa DC MUGISHA BEGA ME 178 KAGERA Missenyi DC JOYCE CHARLES KE 179 KAGERA Missenyi DC JOHNSON ABASHOSI ME 180 KAGERA Missenyi DC EDWIGI MJUZI KE 181 KAGERA Missenyi DC KELVIN NAZAR ME 182 KAGERA Muleba DC KELVIN MUKIZA ME 183 KAGERA Muleba DC ELVIRA JOSUE KE 184 KAGERA Muleba DC DATIUS FAUSTIN ME 185 KAGERA Muleba DC SPERATUS CREOPHACE ME 186 KAGERA Muleba DC CLAUS THOMAS KAIZA ME 187 KAGERA Ngara DC ZAIDIA SAID KE 188 KAGERA Ngara DC NAMSIFU MBWAMBO KE 189 KAGERA Ngara DC JOSEPHAT MIGEMBE ME 190 KATAVI Mlele DC ANDREW MWINJIRA ME 191 KATAVI Mlele DC LAMBERT NANDI ME 192 KATAVI Mlele DC PAUL MHANDWA ME 193 KATAVI Mpanda MC GODFREY MBUKWA ME 194 KATAVI Mpanda MC SIFA SADOCK KADUGU KE 195 KATAVI Mpanda MC MAXIMILLIAN SIMBAO ME 196 KATAVI Mpanda MC PHARES CHACHA ME 197 KATAVI Mpanda MC PASCHAL SIMBASANA ME 198 KATAVI Mpanda MC INNOCENT ZELOTHE ME 199 KATAVI Mpanda MC HAPPYPHANIA MASELE KE 200 KATAVI Mpanda MC ANICIA MSHORA KE 201 KATAVI Mpimbwe DC HOFEMIA JUMAMISI KE 202 KATAVI Mpimbwe DC DAVID PONDA ME 203 KATAVI Mpimbwe DC EMMANUEL KAPINDI ME 204 KATAVI Nsimbo DC AGNES KAPUTA KE 205 KATAVI Nsimbo DC TATU ABDALA KE 206 KATAVI Nsimbo DC FREDY KIBAIBAI ME 207 KATAVI Tanganyika DC DAFROZA NDEMAZA KE 208 KATAVI Tanganyika DC ULIMWENGU LAMECK NDAVUM ME 209 KATAVI Tanganyika DC GACHEL NYANDA ME 210 KIGOMA Buhigwe DC TEODORA MIZUNGWE KE 211 KIGOMA Buhigwe DC DAVID SAMBIRO RUSEHEYE ME 212 KIGOMA Buhigwe DC PILI NTIBANYANKA ME 213 KIGOMA Kakonko DC ALPHONCE BISHIRANGONGA ME 214 KIGOMA Kakonko DC BLANDINA MUZI KE 215 KIGOMA Kakonko DC EZRA BANGUSHE ME 216 KIGOMA Kasulu DC ROBERT WATAMBO ME 217 KIGOMA Kasulu DC KASALINA STEPHANO KE 218 KIGOMA Kasulu DC SFTANLEY RAMBO ME 219 KIGOMA Kasulu TC ERICK NKWALE ME 220 KIGOMA Kasulu TC EVODIA NYABHU KE 221 KIGOMA Kasulu TC NAOMI CHABANDI KE 222 KIGOMA Kasulu TC SAMWEL MCHUNGA ME 223 KIGOMA Kibondo DC AKIBA NGARAMA ME 224 KIGOMA Kibondo DC SAIMONI NTAZINA ME 225 KIGOMA Kibondo DC MERISI RWEKIZA KE 226 KIGOMA Kibondo DC IBRAHIM KITANDALA ME 227 KIGOMA Kigoma DC ANANIA JOSEPH ZAKARIA ZAKARIA ME 228 KIGOMA Kigoma DC ISSA ALUFAN BUTEME ME 229 KIGOMA Kigoma DC ELIZABETH MWIGULU KE 230 KIGOMA Kigoma Ujiji MC VENAS MAGOBORA ME 231 KIGOMA Kigoma Ujiji MC MASUDI MLAGE ME 232 KIGOMA Kigoma Ujiji MC ENITHA EZEKIEL MANANGA KE 233 KIGOMA Kigoma Ujiji MC ABDALLAH ABDALLAH ME 234 KIGOMA Uvinza DC MUSSA HEMEDI HASHIRI ME 235 KIGOMA Uvinza DC FATUMA KASHELO KE 236 KIGOMA Uvinza DC COSMAS KAPUGWI ME 237 KIGOMA Uvinza DC AMISA SASILO KE 238 KIGOMA Uvinza DC KAREBO KILONDA ME 239 KIGOMA Uvinza DC MODESTA MBOGI KE 240 KIGOMA Uvinza DC HALIMA ABEDI KE 241 KILIMANJARO Hai DC THABIT SWALEH ME 242 KILIMANJARO Hai DC GRACE MASSAWE KE 243 KILIMANJARO Hai DC DAVID ABELI ME 244 KILIMANJARO Moshi DC IVON TEMBA KE 245 KILIMANJARO Moshi DC ANDREA MMBAGA ME 246 KILIMANJARO Moshi DC TUMAINI MSECHU ME 247 KILIMANJARO Moshi DC PROSPER MALLYA ME 248 KILIMANJARO Moshi DC EPIMARK FABIN MMASSI ME 249 KILIMANJARO Moshi MC EDITHA DWESSE KE 250 KILIMANJARO Moshi MC RASHID NACHAN ME 251 KILIMANJARO Moshi MC BENSON MGANGA ME 252 KILIMANJARO Moshi MC PETER BUNDALA MISAMO ME 253 KILIMANJARO Mwanga DC NAOMI MINAEL KE 254 KILIMANJARO Mwanga DC JAJI DAUDI ME 255 KILIMANJARO Mwanga DC ESTER CORNEL KE 256 KILIMANJARO Rombo DC REGINA LYAKURWA KE 257 KILIMANJARO Rombo DC STEPHEN VENDELINI ME 258 KILIMANJARO Rombo DC PASCAL MOSHI ME 259 KILIMANJARO Same DC DAVID KITAA ME 260 KILIMANJARO Same DC MACKDALENA MBONEA KE 261 KILIMANJARO Same DC IDD ISSA SELEMAN NYARUBONA ME 262 KILIMANJARO Siha DC ELIZABETH MSAKY KE 263 KILIMANJARO Siha DC COSMAS MREMA ME 264 KILIMANJARO Siha DC VEDASTO APOLINI KISHIA ME 265 KILIMANJARO Siha DC BENJAMIN KILEO ME 266 KILIMANJARO Siha DC SOPHIAELI MUNISHI KE 267 LINDI Kilwa DC MSAFIRI JUMA DIDI ME 268 LINDI Kilwa DC MARIAM KOPAKOPA KE 269 LINDI Kilwa DC YAHAYA SAID ME 270 LINDI Lindi MC RAZACK MBARAKA ME 271 LINDI Lindi MC ASHA MAKWITA KE 272 LINDI Lindi MC KENEDI MBAGWA ME 273 LINDI Liwale DC AMIDA CHANDE MKUWE KE 274 LINDI Liwale DC MUHIDINI LIOBITE ME 275 LINDI Liwale DC AWAZI MTEGITE ME 276 LINDI Mtama DC RAJABU ATHUMANI NAMKOKO ME 277 LINDI Mtama DC MWANAHAMISI KAUNDE KE 278 LINDI Mtama DC IDDI KAUNDE ME 279 LINDI Nachingwea DC PETER MADUKWA ME 280 LINDI Nachingwea DC MOHAMED HAMIS NYAGALI ME 281 LINDI Nachingwea DC HAMIDU MKUSA ME 282 LINDI Ruangwa DC JUMA SELEMANI MAROCHO ME 283 LINDI Ruangwa DC SALUM MBAKI ME 284 LINDI Ruangwa DC AMOS NGUYU ME 285 MANYARA Babati DC DANIELI MUHALE ME 286 MANYARA Babati DC JUMA ONNU ME 287 MANYARA Babati DC JANETH MOSHI KE 288 MANYARA Babati DC AMOS EMEDA TENGAA ME 289 MANYARA Babati TC DAUDI DUDIYECK ME 290 MANYARA Babati TC EDWARD BARAN ME 291 MANYARA Babati TC JACQUELINE MSUYA KE 292 MANYARA Babati TC ISMAILI HOMMA ME 293 MANYARA Hanang DC ELIA NJOKA ME 294 MANYARA Hanang DC MARY GWAMBU KE 295 MANYARA Hanang DC JONATHAN ZELLA RWEYONGEZA ME 296 MANYARA Kiteto DC RAPHAEL KIDAWA ME 297 MANYARA Kiteto DC ANDREA MNYANTUMBI ME 298 MANYARA Kiteto DC MARIA HOSEA KE 299 MANYARA Mbulu DC FANUEL BUU ME 300 MANYARA Mbulu DC JAMES SULE ME 301 MANYARA Mbulu DC ANGEL MARTIN PAUL SULLE KE 302 MANYARA Mbulu TC BERNADO BARAN ME 303 MANYARA Mbulu TC NIPA UTAGO KE 304 MANYARA Mbulu TC LAZARO GADIYE ME 305 MANYARA Simanjiro DC MARTIN CYPRIAN ME 306 MANYARA Simanjiro DC WELIMA MAKUNJA KE 307 MANYARA Simanjiro DC PAPAYE NJIDAY ME 308 MARA Bunda DC VUMI LUSATO ME 309 MARA Bunda DC GUDILA CASSIAN KUNDY KE 310 MARA Bunda DC EMILSON ELITABU ELINAZI ME 311 MARA Bunda TC GEOFRAY MASIGE ME 312 MARA Bunda TC AMOS IGESE ME 313 MARA Bunda TC LEAH NCHEYE KE 314 MARA Butiama DC EMMANUEL PAULO ME 315 MARA Butiama DC WARYOBA CHACHA ME 316 MARA Butiama DC LEAH MASALU KE 317 MARA Musoma DC ROSEMERY BWIRE KE 318 MARA Musoma DC DENISI TAGAYA ME 319 MARA Musoma DC ROBERT MANYASI ME 320 MARA Musoma MC KAGINA ZONGORI ME 321 MARA Musoma MC BINAISA MOTWE ME 322 MARA Musoma MC MARRY MASUBUGU KE 323 MARA Rorya DC MWANGAZA YAHAYA KABUTI KE 324 MARA Rorya DC GODFREY DALMAS ME 325 MARA Rorya DC BARAKA JANES ZABRON ME 326 MARA Serengeti DC REBEKA MONCHON KE 327 MARA Serengeti DC DOCHIVERY ROHURO ME 328 MARA Serengeti DC EZEKIEL MACHOME ME 329 MARA Tarime DC WINFRIDA MAITARYA KE 330 MARA Tarime DC UPENDO FARIJALA KE 331 MARA Tarime DC CHACHA BWANA ME 332 MARA Tarime TC BERNARD CHACHA ME 333 MARA Tarime TC JOHN MSHORA ME 334 MARA Tarime TC JOYCE MAGITA KE 335 MBEYA Busokelo DC FURAHA MWAKAJE ME 336 MBEYA Busokelo DC SARAH MWAKITALIMA KE 337 MBEYA Busokelo DC NEEMA SANDUNGILA KE 338 MBEYA Chunya DC JUMANNE MRINGI ME 339 MBEYA Chunya DC NELBATH RAPHAEL ME 340 MBEYA Chunya DC AUGUSTINE NJEGITE KE 341 MBEYA Kyela DC LOUIS LAWRENCE ELLY MWAIPOLA ME 342 MBEYA Kyela DC ABUBAKARI MWIULLAH ME 343 MBEYA Kyela DC ELICA MWAMESO KE 344 MBEYA Mbarali DC ALEX SAMBAGI ME 345 MBEYA Mbarali DC ALEXANDRON MSIGALA ME 346 MBEYA Mbarali DC WEMA WAITON MWAKISI KE 347 MBEYA Mbarali DC ALKAM MHETA ME 348 MBEYA Mbarali DC EVA BAKOMEGE KE 349 MBEYA Mbeya CC MAGAMBO MAGAMBO ME 350 MBEYA Mbeya CC GREGORY BUNDALA ME 351 MBEYA Mbeya CC AMINA MWAKALOBO KE 352 MBEYA Mbeya CC WISCOTY SIMFUKWE ME 353 MBEYA Mbeya CC AMINA MNUNGULI KE 354 MBEYA Mbeya CC NGASSA NDINGU ME 355 MBEYA Mbeya CC FARAJA CHAULA KE 356 MBEYA Mbeya CC FESTO KISONGA ME 357 MBEYA Mbeya CC BENARD MKOLIMWA ME 358 MBEYA Mbeya CC GIVEN MWAJEKA KE 359 MBEYA Mbeya CC HABILI MSHANI ME 360 MBEYA Mbeya DC JOSHUA NICHORAUS BASAMBUYE ME 361 MBEYA Mbeya DC JULIUS MWAIGAGA ME 362 MBEYA Mbeya DC JANE AMBONISYE KE 363 MBEYA Mbeya DC IBRAHIM MSHIKO ME 364 MBEYA Mbeya DC CECILIA JIGWA KE 365 MBEYA Rungwe DC ABIHU MWAMBETE ME 366 MBEYA Rungwe DC OKEN MWANGOMALE ME 367 MBEYA Rungwe DC GETRUDA LAWRENCE KE 368 MBEYA Rungwe DC HABAKUKI RAFAEL ME 369 MOROGORO Gairo DC PRISCA NJENDA KE 370 MOROGORO Gairo DC GOODLUCK MKUNDA ME 371 MOROGORO Gairo DC GREAD SAIDI ME 372 MOROGORO Ifakara TC HADIJA MANUMBA KE 373 MOROGORO Ifakara TC CASMIL CASTORY ME 374 MOROGORO Ifakara TC HALFANI ABDALLAH ME 375 MOROGORO Kilosa DC DAINES MUGETA KE 376 MOROGORO Kilosa DC AYUBU NYANGA ME 377 MOROGORO Kilosa DC ROBSON MNG'OME ME 378 MOROGORO Kilosa DC GRACE JEREMIAH KE 379 MOROGORO Malinyi DC DEOGRATIUS KINDANDA ME 380 MOROGORO Malinyi DC BEATRICE MAKUKULA KE 381 MOROGORO Malinyi DC EMMANUEL KHAMIS ME 382 MOROGORO Mlimba DC GRADIS CHAADA KE 383 MOROGORO Mlimba DC DITRICK MBIFILE ME 384 MOROGORO Mlimba DC GODFREY TIBENDA ME 385 MOROGORO Morogoro DC LATIFA CHANDE KE 386 MOROGORO Morogoro DC BONIFASI GIRABI ME 387 MOROGORO Morogoro DC JOEL JOSHUA ME 388 MOROGORO Morogoro MC ANITHA MWAISAKA KE 389 MOROGORO Morogoro MC SADICK KILINDO ME 390 MOROGORO Morogoro MC FREDRICK NGOWI ME 391 MOROGORO Morogoro MC LAZARO TIRRA ME 392 MOROGORO Morogoro MC IZACK SIRIKWA ME 393 MOROGORO Morogoro MC ELIAS NGUSU ME 394 MOROGORO Morogoro MC NICKSON MACHENJE ME 395 MOROGORO Morogoro MC ESTHER CHANIKA KE 396 MOROGORO Morogoro MC VEDIANA BYEMERWA KE 397 MOROGORO Morogoro MC ARON DEOGRATIAS MAHUNDI ME 398 MOROGORO Mvomero DC KIBIBI MATULA KE 399 MOROGORO Mvomero DC DICKSON JUMA ME 400 MOROGORO Mvomero DC GEORGE MAGANGA ME 401 MOROGORO Ulanga DC MAGE AMOSI JACKSONI KE 402 MOROGORO Ulanga DC JOSEPH MAPUNDA ME 403 MOROGORO Ulanga DC LENARD DIONEZIO ME 404 MTWARA Masasi DC RAMADHAN ERIYO ME 405 MTWARA Masasi DC GERLEFANS SAID ME 406 MTWARA Masasi DC MARIAM ISMAIL KE 407 MTWARA Masasi TC MWAJUMA MALINDI KE 408 MTWARA Masasi TC KARIMU MPANDO ME 409 MTWARA Masasi TC GEORGE JENKEN ME 410 MTWARA Mtwara DC MZEE BAKARI ME 411 MTWARA Mtwara DC ASHA LIKWANGWALA KE 412 MTWARA Mtwara DC MTENGWA MAGANGA ME 413 MTWARA Mtwara MC MOHAMMED JUMA ME 414 MTWARA Mtwara MC HALIMA DAFFA KE 415 MTWARA Mtwara MC AHMADI MKANJOPE ME 416 MTWARA Nanyamba TC SHAIBU KAPELA ME 417 MTWARA Nanyamba TC IBRAHIMU MCHENJE ME 418 MTWARA Nanyamba TC KALIMU LIKUDWALI ME 419 MTWARA Nanyumbu DC JOHN MWAHALENDE ME 420 MTWARA Nanyumbu DC TAUFIQ LIPULA ME 421 MTWARA Nanyumbu DC HAMADI ANGONDO ME 422 MTWARA Newala DC DHAHIRI MTENGO ME 423 MTWARA Newala DC SAIDI NANDONDE ME 424 MTWARA Newala DC HAMIDA ALLY KE 425 MTWARA Newala TC AMINA KAISI MBARAKA KE 426 MTWARA Newala TC HAMISI FAKIHI ME 427 MTWARA Newala TC RASHID HAMISI ME 428 MTWARA Tandahimba DC YAHAYA SAIDI NDEJA ME 429 MTWARA Tandahimba DC MARZUIK HUSSEIN MARZUIK ME 430 MTWARA Tandahimba DC JUMA NDAILE ME 431 MWANZA Buchosa DC PASCAL SESA ME 432 MWANZA Buchosa DC JEPHTER CHELELE ME 433 MWANZA Buchosa DC JURIANA MALENGO KE 434 MWANZA Ilemela MC ABELLA MUNISI KE 435 MWANZA Ilemela MC ELIZABETH MHENYA KE 436 MWANZA Ilemela MC SIGELA MUSSA MLUNJA ME 437 MWANZA Ilemela MC FAUSTIN WAMBURA ME 438 MWANZA Ilemela MC IRENE MUKOBA KE 439 MWANZA Ilemela MC NURU MTEBI ME 440 MWANZA Ilemela MC HUSSEIN KIRANGI ME 441 MWANZA Ilemela MC RAJABU MBOBOZI ME 442 MWANZA Ilemela MC FARAJA OKUMU KE 443 MWANZA Kwimba DC ANSELM BERNARD KASEZA ME 444 MWANZA Kwimba DC TUMAINI TIMOTHY KILEO KE 445 MWANZA Kwimba DC DAYSON MALEMO ME 446 MWANZA Magu DC AMOS ABELY ME 447 MWANZA Magu DC MSHIGWA JOHN MWENDESHA ME 448 MWANZA Magu DC SHIDA MANHYASIMA KE 449 MWANZA Misungwi DC ANDREW THOMAS ME 450 MWANZA Misungwi DC JACQUELINE LEONIDAS KE 451 MWANZA Misungwi DC REVINA MSONGARELI KE 452 MWANZA Misungwi DC LAWRENT MUSA ME 453 MWANZA Misungwi DC ZACHARIA BONIPHACE ME 454 MWANZA Mwanza CC LUCAS KABENGWE ME 455 MWANZA Mwanza CC FRANCISCO CHARLES ME 456 MWANZA Mwanza CC ANIFA MOHAMED KE 457 MWANZA Mwanza CC DOMINIC LUCAS ME 458 MWANZA Mwanza CC ISIHAKA AMIRI ME 459 MWANZA Mwanza CC BRASTUS KABENDE ME 460 MWANZA Mwanza CC ALICE BEDA KE 461 MWANZA Mwanza CC GODFREY KIRUMBE KE 462 MWANZA Sengerema DC FAUSTINE CHARLES ME 463 MWANZA Sengerema DC FRANK MAGAFU ME 464 MWANZA Sengerema DC ZAINABU MPIMA KE 465 MWANZA Sengerema DC SUNDAY LUYAGAZA KE 466 MWANZA Ukerewe DC STANSILAUS MUHILE ME 467 MWANZA Ukerewe DC PRIMANUEL MISANA ME 468 MWANZA Ukerewe DC GEORGE MASSAWE ME 469 PWANI Bagamoyo DC JUMA RAMADHANI ME 470 PWANI Bagamoyo DC DOTTO KIMUNGWI KE 471 PWANI Bagamoyo DC BAKARI MBELWA ME 472 PWANI Chalinze DC MBARAKA ROMAN ME 473 PWANI Chalinze DC SELEMANI PENDO ME 474 PWANI Chalinze DC SHARIFA MTUMWA MAKAMBA KE 475 PWANI Kibaha DC ABDULAZIZI PAZI ME 476 PWANI Kibaha DC SIKUDHANI MANENO ALLY KE 477 PWANI Kibaha DC SELELI BUNDI ME 478 PWANI Kibaha TC JAFFARI ALLY ME 479 PWANI Kibaha TC TUNU MWINYIMKUU KE 480 PWANI Kibaha TC ALLY MLALI ME 481 PWANI Kibiti DC YORANDA KABUMBILE KE 482 PWANI Kibiti DC SALIM MPILI ME 483 PWANI Kibiti DC ABDULKARIMU R.NDOMONDO ME 484 PWANI Kisarawe DC SALUM MODOKA ME 485 PWANI Kisarawe DC HABIBU MHODE ME 486 PWANI Kisarawe DC IRENE SABUNI KE 487 PWANI Mafia DC SHABANI MAULID ME 488 PWANI Mafia DC ALLY HUSSEIN LIKANDIKE ME 489 PWANI Mafia DC MWANAISHA MAPUNDA KE 490 PWANI Mkuranga DC HASHIMU NJAYO ME 491 PWANI Mkuranga DC HUSSEIN ABU NYAMKUNGA ME 492 PWANI Mkuranga DC ASIA JEREMIA MSUNGI KE 493 PWANI Rufiji DC SAIDI RAJABU ME 494 PWANI Rufiji DC SALAMA SAKOLO KE 495 PWANI Rufiji DC JUMA MBARUKU ME 496 RUKWA Kalambo DC ESTER NKANGA KE 497 RUKWA Kalambo DC FRANK SIMBUTA ME 498 RUKWA Kalambo DC DOMINICK KAIZILEGE ME 499 RUKWA Nkasi DC DORIS MSOMA KE 500 RUKWA Nkasi DC PHILBETH MWANALINZE ME 501 RUKWA Nkasi DC FREDRICK MWANANGELEL ME 502 RUKWA Sumbawanga DC PATRICK WAKUWILI ME 503 RUKWA Sumbawanga DC JOFREY JONAS ME 504 RUKWA Sumbawanga DC JENIMERY NAMANGA KE 505 RUKWA Sumbawanga DC THOMAS KIMILA ME 506 RUKWA Sumbawanga MC EMMANUEL MLUNGURA ME 507 RUKWA Sumbawanga MC JIMMY KASIKI ME 508 RUKWA Sumbawanga MC VAILETH KALEMERA KE 509 RUVUMA Madaba DC ABDALLAH MCHILA ME 510 RUVUMA Madaba DC HANS MLELWA ME 511 RUVUMA Madaba DC SECILIA SEZURA KE 512 RUVUMA Mbinga DC OSWIN NDUNGURU ME 513 RUVUMA Mbinga DC GIFT KUNULILO ME 514 RUVUMA Mbinga DC REGINA HAULE KE 515 RUVUMA Mbinga TC BASILIUS MAHUNDI ME 516 RUVUMA Mbinga TC MACARIUS KAPINGA ME 517 RUVUMA Mbinga TC BEATRICE KIGOMBE KE 518 RUVUMA Namtumbo DC OTILIA MPOMBO KE 519 RUVUMA Namtumbo DC OSWINI NJEREKELA ME 520 RUVUMA Namtumbo DC HIJA HATIBU SIWEA KE 521 RUVUMA Nyasa DC EMERICK NOMBO ME 522 RUVUMA Nyasa DC DEOKALA MWANKENJA KE 523 RUVUMA Nyasa DC SAMSON CHINDONGO ME 524 RUVUMA Songea DC PAULO KAPINGA ME 525 RUVUMA Songea DC FRANK KOMBA ME 526 RUVUMA Songea DC SELINA DITRICK ZULLU KE 527 RUVUMA Songea MC AGUSTA KOMBA KE 528 RUVUMA Songea MC LAURENT FAIDA ME 529 RUVUMA Songea MC ALLEN FREDRICK FUSSI ME 530 RUVUMA Tunduru DC PASKAZIA MGANWA KE 531 RUVUMA Tunduru DC MOHMED AROBAINI ME 532 RUVUMA Tunduru DC ERICK STEVEN KUMANDA ME 533 SHINYANGA Kahama MC EMMANUEL NYOMBELA ME 534 SHINYANGA Kahama MC KUYA MIKOBA ME 535 SHINYANGA Kahama MC NEEMA KILOMBA KE 536 SHINYANGA Kishapu DC MTWANGI MWINULA ME 537 SHINYANGA Kishapu DC THOMAS MALALE ME 538 SHINYANGA Kishapu DC JOSEPHINE GINDU KE 539 SHINYANGA Msalala DC MAYOMBO MPELWA MARASHI KE 540 SHINYANGA Msalala DC TWAHA KIULLAH ME 541 SHINYANGA Msalala DC THOMSON NYARACHA ME 542 SHINYANGA Shinyanga DC EMMANUEL BUSANDA ME 543 SHINYANGA Shinyanga DC GERALD NG`WISIJA ME 544 SHINYANGA Shinyanga DC LUCY ROBERT KE 545 SHINYANGA Shinyanga MC ANNASTAZIA MUSA KE 546 SHINYANGA Shinyanga MC RAHIM RASHID ME 547 SHINYANGA Shinyanga MC ADAM MASHIKU ME 548 SHINYANGA Ushetu DC GEORGE MAKARANGA ME 549 SHINYANGA Ushetu DC RAMADHANI SHEKWAVI ME 550 SHINYANGA Ushetu DC ROSE NTAGUZWA KE 551 SIMIYU Bariadi DC MAGILE DINDAYI ME 552 SIMIYU Bariadi DC NDAKI SHABULI ME 553 SIMIYU Bariadi DC ELIZABETH SAMSON KE 554 SIMIYU Bariadi TC ABDALLAH MAPUNDA ME 555 SIMIYU Bariadi TC EUNICE JOHN KE 556 SIMIYU Bariadi TC NTUBANGA MASANJA ME 557 SIMIYU Busega DC SALVATORY THOMAS NKUNU ME 558 SIMIYU Busega DC KULUTHUM MAIGA KE 559 SIMIYU Busega DC MAKULA WASHIMA ME 560 SIMIYU Itilima DC KENETH LALI ME 561 SIMIYU Itilima DC SULI SITTA KE 562 SIMIYU Itilima DC ENOCK EMMANUEL LUBAGO ME 563 SIMIYU Maswa DC ENOCK LUZWILO ME 564 SIMIYU Maswa DC WILLIAM NCHALUNGI ME 565 SIMIYU Maswa DC KELVIN EMMANUEL MACHUMU ME 566 SIMIYU Meatu DC SEIF ALI ME 567 SIMIYU Meatu DC HIGINI BAYYO ME 568 SIMIYU Meatu DC EMMANUEL MASABO ME 569 SINGIDA Ikungi DC FAHADI MOHAMEDI IDONA ME 570 SINGIDA Ikungi DC RIZIKI ABDALLAH MUSSA ME 571 SINGIDA Ikungi DC VERONICA LISSU KE 572 SINGIDA Iramba DC DAVID MZIGILI ME 573 SINGIDA Iramba DC SHABANI SELEMANI ME 574 SINGIDA Iramba DC MAGRETH SHANI KE 575 SINGIDA Itigi DC ALEXANDAR NSEMBA ME 576 SINGIDA Itigi DC SAID IDDI ME 577 SINGIDA Itigi DC ZEWANA MBEGA KE 578 SINGIDA Manyoni DC MIKIDADI MTAMIKE ME 579 SINGIDA Manyoni DC NASRA JUMA KE 580 SINGIDA Manyoni DC FESTO LEMELO ME 581 SINGIDA Mkalama DC RAMADHANI MWANJIKU ME 582 SINGIDA Mkalama DC PETER NALIGYA ME 583 SINGIDA Mkalama DC SOLOMON ABDALLAH ME 584 SINGIDA Singida DC SHARIFU ISSA ME 585 SINGIDA Singida DC SHABANI MTINDA ME 586 SINGIDA Singida DC ANIKE NDUHIRUBUSA KE 587 SINGIDA Singida MC YOHANA SIMION ME 588 SINGIDA Singida MC ATHUMAN MSENGI ME 589 SINGIDA Singida MC SHANANI MKONYI ME 590 SONGWE Ileje DC SIKUJUA ADAM CHEYO KE 591 SONGWE Ileje DC IMANUEL KANDONGA ME 592 SONGWE Ileje DC HEADMAN MSOKWA ME 593 SONGWE Mbozi DC YANGSON MNKONDYA ME 594 SONGWE Mbozi DC FADHILI SINKAMBA ME 595 SONGWE Mbozi DC RAHIM NZUNDA ME 596 SONGWE Momba DC TWALIB MTIKA ME 597 SONGWE Momba DC TYSON JENGELA ME 598 SONGWE Momba DC AMINA MKONDYA KE 599 SONGWE Songwe DC FADHILI MWAMASAGE ME 600 SONGWE Songwe DC RAJABU KATABE ME 601 SONGWE Songwe DC STAREHE NGABO ME 602 SONGWE 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# Extracted Content THE UNITED REPUBLIC OF TANZANIA AGRICULTURAL SECTOR DEVELOPMENT PROGRAMME PHASE II (ASDP II) November, 2017 “SEKTA YA KILIMO KWA MAENDELEO YA VIWANDA” “AGRICULTURAL SECTOR FOR INDUSTRIAL DEVELOPMENT” i Agricultural Sector for Industrial Development FOREWORD Agricultural sector development is very crucial in the growth of the national economy and development of industrial sector. Agricultural development is equally important for the provision of adequate food and guarantees nutrition security to the Tanzania population. Currently, the agricultural sector contributes about 29.1 % of the GDP 65.5% of employment, 65% of raw materials to the industrial sector and 30% of export earnings. The Agricultural Sector Development Programme phase two (ASDPII) has been developed to propel the country’s economic development and guide the implementation of prioritized interventions for the Tanzania Development Vision 2025 (TDV 2025). Long Term Perspective Plan (LTPP 2012-2021);’ Five Year Development Plan. phase two (FYDP 11 2011- 2021), Tanzania Agriculture and Food Security Investment Plan (TAFSIP) and the Agricultural Sector Development Strategy Phase Il (ASDS Il). The duration of (ASDP Il) is ten years starting from the year 2017/18 to 2027/28. The programme is to be implemented into two stages of five years each, the first starting from the year 2017/18. The main objective of ASDP Il is to transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and increase smallholder farmer income for improved livelihood and guarantee food and nutrition security. The Programme has four major components which are; (i) Sustainable Water and Land Use Management which aims at expanding sustainable water and land use management for crops, livestock and fisheries; (ii) Enhanced Agricultural Productivity and Profitability which will focus on increasing productivity, for some priority commodities; (iii) Commercialization and Value Addition which will focus on improved and expanded marketing, value addition promoted by a thriving competitive private sector and effective farmer organizations; and (iv) Sector Enablers, Coordination and Monitoring & Evaluation which will strengthen institutions, create enabling conditions and provide coordination framework. The expected benefit from the ASDP Il include (i) increased and sustainable productivity, production of food and non-food agricultural commodities to improve Tanzanians livelihoods, ensuring national level food security, and provide raw materials for the industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural agricultural sector by generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to increase resilience and adapt to climate change; (v) improved institutional capacity to mobilize and manage resources in support of agricultural sector development; (vi) improving the system of disaster risk management by exploring the use of innovative risk management tools; (vii) reduced gender related imbalances; (viii) rsduced child labour in the agricultural sector by promoting decent work and (ix) reduce the of agriculture to the environment and take into account climate change through promotion of Climate Smart Agriculture (CSA). In this respect, it gives me great pleasure to present the Second Phase of the Agricultural Sector Development Programme (ASDP Il) to all stakeholders. The Programme implementation will involve all stakeholders from public, private, development partners, financial institutions and non- state actors. ii Agricultural Sector Development Programme II (ASDP-II) I would like to urge all stakeholders in the sector to pull together our collective strength to make sure thät this agricultural transformation agenda which, without doubt will contribute significantly to the country’s development targets becomes a reality. It is necessary therefore that these initiatives and interventions are shared and supported by all stakeholders and each one of us in our different capacities. I thank you in advance for your cooperation and participation Hon. Dr. Charles Tizeba (MP), MINISTER FOR AGRICULTURE iii Agricultural Sector for Industrial Development Contents FOREWORD ........................................................................................................................................ i EXECUTIVE SUMMARY .................................................................................................................. 1 I. BACKGROUND....................................................................................................................7 A. Macroeconomic Indicators and Agriculture...............................................................................7 B. The Agriculture Sector.............................................................................................................8 C. Policy Environment............................................................................................................... 11 II. SECTOR PROGRAMMES, PROJECTS AND PUBLIC EXPENDITURE..........................14 A. Agriculture Sector Development Programme (ASDP phase 1)...................................................14 B. Other Related Agricultural Sector Initiatives............................................................................15 C. Agriculture Sector Review-Public Expenditure Review (ASR-PER)..........................................17 III. ASDP II-DESIGN PROCESS AND PRINCIPLES.............................................................22 A. Lessons Learned from ASDP-1..............................................................................................22 B. Key Agricultural System Challenges and Potential Drivers........................................................25 C. The Process Towards ASDP II................................................................................................27 D. Key Design Principles for ASDP II.........................................................................................30 E. Scope, Focus and Phasing of the Programme...........................................................................32 F. Priority setting and Focusing...................................................................................................36 G. Approaches and principles for the ASDP II design....................................................................37 H. The Theory of Change...........................................................................................................39 IV. PROGRAMME OBJECTIVE AND DESCRIPTION..........................................................40 A. Programme Objective............................................................................................................41 B. Priority Investment Areas (summary)......................................................................................45 C. Component 1: Sustainable Water & Land Use Management (crops, livestock and fisheries).........47 D. Component 2: Enhanced Agricultural Productivity and Profitability...........................................59 E. Component 3: Commercialization and Value Addition (building competitive commodity value chains).............................................................................86 F. Component 4: Strengthening Sector Enablers and Coordination...............................................104 V. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT.......................127 A. Overall Programme Cost......................................................................................................127 B. Financing Plan....................................................................................................................133 C. Financing Arrangements......................................................................................................134 VI. INSTITUTIONAL AND IMPLEMENTATION ARRANGEMENTS................................137 A. Implementation of ASDP II at National Level........................................................................137 B. Regional level.....................................................................................................................138 iv Agricultural Sector Development Programme II (ASDP-II) C. Local Level........................................................................................................................138 D. Coordination mechanisms and processes...............................................................................138 E. Management Information System and monitoring...................................................................140 F. Safeguard Aspects—Social and Environmental management...................................................141 VII. BENEFITS AND ECONOMIC AND FINANCIAL ANALYSIS (EFA).............................142 A. Summary of benefits............................................................................................................142 B. Economic and Financial Analysis.........................................................................................144 C. Economic Benefits..............................................................................................................147 D. Operation and maintence costs.............................................................................................147 E. Economic Viability and Sensitivity Analysis..........................................................................147 F. Programme Sustainability.....................................................................................................148 VIII. IMPLEMENTATION MODALITIES AND RISKS.......................................................149 A. Implementing agency and stakeholder assessment..................................................................149 B. Risks..................................................................................................................................150 ANNEX I: ASDP II Components Implementation Plan, Sequencing and Scheduling.............................152 ANNEX II: ASDP II: Results Framework and Monitoring (On-progress).............................................166 ANNEX III: Details of Coordination Mechanisms................................................................................192 APPENDIX IV: Program and Project budget Requirements................................................................203 ANNEX V Monitoring & Evaluation and Statistics...............................................................................213 ANNEX VI: Financial and Economic Analysis......................................................................................229 ANNEX VII: Risks assessment and Mitigation Strategies/Measures......................................................237 ANNEX VIII: Key Maps and Figures Figure........................................................................................240 ANNEX IX: Selection Criteria for Participating Districts.....................................................................246 ANNEX X: Climate Change and Action—Agriculture Climate Resilience Plan (ACRP).......................248 ANNEX XI: Strategic Options for Stimulating Investment in Improved Agricultural Inputs.................252 ANNEX XII: ASDP II Management, Coordination and Communication Structure: Composition and Process from Village to National Level..................................................................................................254 ANNEX XIII: Principles for responsible Investment in Agriculture (FAO, August 2014).......................260 ANNEX XIV: Key Reference Documents..............................................................................................260 v Agricultural Sector for Industrial Development List of Tables Table 1: MAFC and MLFD central level recurrent expenditure (TSh million)..................................... 19 Table 2: Routine expenditure on agriculture and as a proportion of agriculture GDP........................... 19 Table 3: Technology enhancing expenditure in MAFC (TSh million)................................................... 20 Table 4: Revenue collection and budget execution rates........................................................................ 21 Table 5: Key constraints and thematic drivers........................................................................................ 25 Table 6: Commodities coverage, agricultural production, trade and diet (2005–2010)......................... 33 Table 7: Priority commodities in the AEZs & potential commodities phasing by region...................... 34 Table 8: Priority Commodity Value Chains in Agro-Ecological Zones/ clusters................................... 35 Table 9: ASDS-2 Strategic Result Areas & mapping of proposed priority programme areas................ 37 Table 10: Typology of rural households active in the agricultural sector against holding size.............. 44 Table 11: ASDP II components and strategic objectives........................................................................ 45 Table 12:Agro-ecological zones and districts to be involved in ASDP II.............................................. 46 Table 13: ASDP II Component 1: Related ASDS-II specific objectives and outcomes......................... 48 Table 14: Priority activities in land use planning for crop and livestock development.......................... 50 Table 15: Summary of BRN and remaining ASDP-1 prioritized irrigation schemes (2015/2020)........ 54 Table 16: Priority actions for improved water management in rainfed agriculture................................ 55 Table 17: Priority activities livestock/fish access to water resources..................................................... 55 Table 18: ASDP II investment and action areas for improved resilience of farming systems................ 58 Table 19: Five Years Development budget/investment estimates for component 1 –at constant 2016 ..... Prices (TSh million)............................................................................................................... 58 Table 20: ASDP II Component 2: related ASDS-2 specific objectives and outcomes........................... 60 Table 21: Objectives for priority action in livestock and fish productivity development (10 years)..... 61 Table 22: Priority activities livestock extension..................................................................................... 68 Table 23: Priority intervention in fisheries extension............................................................................. 68 Table 24: Priority activities & investment areas in livestock and fisheries training............................... 69 Table 25: Priority activities livestock/fisheries access to inputs............................................................. 74 Table 26: Crop and livestock research institutes in AEZ........................................................................ 76 Table 27: Livestock and fisheries priority investment and action areas for research............................. 77 Table 28: Proposed action areas for food security and nutrition............................................................ 83 Table 29: Development budget/investment projection for component 2 (TSh million)......................... 85 Table 30: ASDP II Component 3: related specific ASDS-2 objectives and outcomes........................... 88 Table 31: Objectives for priority CVC and strategies to achieve expected results................................. 89 Table 32: Summary of action areas and activities in market enhancement at national/regional level... 93 Table 33:Priority activities livestock and fisheries quality control and safety assurance....................... 94 Table 34: Priority activities for CVC value addition and agroprocessing.............................................. 95 Table 35: Priority actions towards reduction of post-harvest losses....................................................... 97 Table 36: Proposed strategic action areas for agroprocessing and value addition.................................. 98 Table 37: Proposed strategic action areas for agroprocessing and value addition (livestock/fisheries).98 vi Agricultural Sector Development Programme II (ASDP-II) Table 38:Action areas and activities to improve rural/agricultural investments (draft)....................... 102 Table 39: Development budget/investment estimation for Component 3 (TSh million)......................103 Table 40: ASDP II Component 4: related specific ASDS-2 objectives and outcomes..........................104 Table 41: Key policy areas and related actions for agricultural sector growth (ASLM)......................105 Table 42: Farmer organizations, by category........................................................................................107 Table 43: Action areas for farmer empowerment and organization strengthening ..............................109 Table 44: Proposed ASDP II interventions into cooperative activities and operations.........................111 Table 45: ASDP II National Level coordination organs, mechanisms, and membership (summary)...112 Table 46: ASDP II PO-RALG Level coordination organs, mechanisms, and membership (summary).............................................................................................................................113 Table 47: Proposed interventions for CKM and ICT promotion..........................................................122 Table 48: Action areas and activities to improve rural/agricultural investments..................................125 Table 49: Five Years Development budget / investment projection for component 4 (TSh million)...126 Table 50: ASDP II Component Budget Requirements and Percentages for the first five years...........128. Table 51: Overall development budget for ASDP II.............................................................................128 Table 52: Proportions of the development budget expected to be financed by different funding sources...................................................................................................................................133 Table 53: Illustrative financing plan for ASDP-2 (summary of total costs in TSh million).................134 Table 54: Summary of ASDP II Sector National Coordination Organs, Membership and . Frequency of Meetings.......................................................................................................137 Table 55: Summary of ASDP II Sector at PO-RALG, Regional Secretariat, Local Government Authorities Coordination Organs, Membership and Frequency of Meetings....139 Table 56: Financial Crop Gross Margins in Present, Future Without and Future with Project............145 Table 57: Financial Livestock Gross Margins in Present, Future-without and Future-with project.....146 Table 58: Net Farm Incomes in Present, Future-without and Future-with project...............................146 Table 59: Economic viability and sensitivity analysis..........................................................................148 List of Figures Figure 1: GDP growth rate by sector (%, at 2007 constant prices).......................................................... 7 Figure 2. Agriculture share of GDP (%), 2001 prices............................................................................... 8 Figure 3: GDP by economic activity (at current prices—TSh billion)..................................................... 9 Figure 4: Percentage GDP by economic activity (in % of total GDP—at current TSh prices)................ 9 Figure 5: Main crop production in Tanzania (1961–2013, in tons)........................................................ 10 Figure 6: Evolution of average crop yields for main crops in Tanzania (1961–2013, in kg/ha)............ 10 Figure 7. Long & medium-term policy framework for the transformation of the agriculture sector..... 12 Figure 8. MAFC and MLFD Central-Level Recurrent Expenditure...................................................... 18 Figure 9. Recurrent Agricultural Expenditure as Proportion of Total Recurrent Expenditure............... 20 Figure 10. Agriculture Development Expenditure by Project – Foreign and Local............................... 22 Figure 11: Tanzania landscape for agricultural development (2015–2024)........................................... 28 vii Agricultural Sector for Industrial Development Figure 12: ASDP-II design and formulation framework........................................................................ 29 Figure 13: ASDP-II financing modalities............................................................................................... 29 Figure 14: Transformative Approach-Theory of Change....................................................................... 40 Figure 15: Framework for ASDP II results chain................................................................................... 41 Figure 16: ASDP II Objective, Strategy and Outcome........................................................................... 41 Figure 17: ASDP II Programme Objective and Components................................................................. 42 Figure 18: ASDP II Priority Investment Areas....................................................................................... 43 Figure 19: ASDP II components and sub-components........................................................................... 45 Figure 20: Value chain approach of ASDP II.......................................................................................... 87 Figure 21: ASDP M&E system for sector and programme performance (adapted for ASDP II)..........116 Figure 22: Flow of funds in ASDP II.................................................................................................... 135 Figure 23: ASDP II ProgrammeDecision Making Organs................................................................... 192 Figure A24: ASDP M&E system for sector and project performance (adapted for ASDP II)............. 216 Figure A25: Agriculture Routine Data System..................................................................................... 217 Figure A26: Development Partners’Contribution by Focus Area and Value Chains in Crop Sub-Sector........................................................................................................................ 226 Figure A27: Development Partners’Contribution by Focus Area and Value Chains in Livestock and ..... Fisheries Sub-Sector......................................................................................................... 227 Figure A28: Agro-ecological Zones...................................................................................................... 240 Figure A29: Tanzania Agricultural research zones and NARS institutes (Central, Eastern, Lake, Northern, Southern, Southern Highlands and Western zone)........................................... 243 Figure A30: Tanzania AEZ................................................................................................................... 243 Figure A31: Tanzania livelihood zones................................................................................................ 244 Figure A32: Map - Food insecure districts (2006-13).......................................................................... 244 Figure A33: Map – Tanzania Cattle Distibution by 2008..................................................................... 245 Figure A34: Maps ASDP II targeted priority districts.......................................................................... 247 List of Boxes Box 1: Key Principles of the ASDP II Design........................................................................................ 30 Box 2: Basic elements for better land husbandry—Integrated soil fertility management...................... 51 Box 3: The agenda for sustainable agricultural intensification and resilience....................................... 57 Box 4: Strengthening efficient extension (MAFC Workshop - January 2015)....................................... 63 Box 5: Technical training institutions..................................................................................................... 67 Box 6: Key issues in policy and institutional reform and support (updated from TAFSIP)................. 105 Box 7: Inclusion of off-budget projects.................................................................................................114 viii Agricultural Sector Development Programme II (ASDP-II) Acronyms AASS Annual Agricultural Sample Survey AEZ Agro-ecological zone AfDB African Development Bank AR4D ARDS ASA ASDP Agricultural research for development Agricultural Routine Data System Agricultural Seed Agency Agricultural Sector Development Programme (first and second phases) ASDS ASLMs ASR Agricultural Sector Development Strategy (first and second phase) Agriculture sector lead ministries Agriculture Sector Review ASSP Agricultural Statistics Strategic Plan ATI Agricultural training institute BRN Big Results Now CAADP Comprehensive Africa Agriculture Development Programme CKM Communication and knowledge management CVC Commodity value chain DADG DADP District Agriculture Development Grant District Agricultural Development Plan DAICO District Agricultural, Irrigation and Cooperative Officer DCP DED District CVC platform District Executive Director DLFO District Livestock and Fisheries Officer EAAPP East Africa Agricultural Productivity Project FAO Food and Agriculture Organization of the United Nations FFS Farmers field school FTC Farmer Training Centre ICT Information and Communication Technologies IFAD IPM International Fund for Agricultural Development Integrated Pest Management JICA Japan International Cooperation Agency JSR Joint Sector Review LGAs Local government authorities LITA Livestock Training Agency LITI Livestock Training Institute M&E Monitoring and evaluation MAFC Ministry of Agriculture Food Security and Cooperatives MIVARF Marketing Infrastructure Value Addition and Rural Finance MLFD Ministry of Livestock and Fisheries Development NAIVS National Agricultural Input Voucher Scheme NASSM National Agricultural Sector Stakeholders Meeting ix Agricultural Sector for Industrial Development NCU National Coordination Unit NEPAD New Partnership for Africa’s Development NSCA National Sample Census of Agriculture and Livestock PER Public Expenditure Review PMO- RALG Prime Minister’s Office- Regional Administration and Local Government PO- RALG President’s Office - Regional Administration and Local Government PPP Public Private Partnership PSP Private Service Providers RAS Regional Administrative Secretariat SACCOS Savings and Credit Cooperative Society SADC Southern Africa Development Community SAGCOT Southern Agriculture Growth Corridor of Tanzania SWAp Sector Wide Approach TAFSIP Tanzania Agriculture and Food Security Investment Plan TALIRI Tanzania Livestock Research Institute TARI Tanzania Agricultural Research Institute TCD Technical Committee of Directors TOSCI Tanzania Official Seed Certification Institute TTPU Technology Transfer and Partnership Units USAID United States Agency for International Development VAEO Village Agricultural Extension Officer WAEO Ward Agricultural Extension Officer WARC Ward Agricultural Resource Centre 1 Agricultural Sector for Industrial Development EXECUTIVE SUMMARY INTRODUCTION The government of Tanzania has finalized the formulation of Agriculture Sector Development Programme II (ASDP II). This is a ten-years programme that will be implemented in two (2) phases each divided into five-year implementation period. The First Phase will start in 2017/2018 – 2022/2023. The program is a follow up to the ASDP I implemented from 2006/2007 to 2013/2014. ASDP II has been designed based on the lessons learnt during the ASDP I implementation. The program aims at transforming the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food and nutrition security and contribution to the GDP. The program strategy is to transform gradually subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development. Preparation of the program has gone through a comprehensive consultative and stakeholder engagement at all levels. This document is a result of the views, comments and wishes of the various stakeholders including private sector, development partners, farmer organizations and non-governmental organizations and the public sector. The document is presented in eight sections: (i) the background; (ii) sector programmes, projects and public expenditure; (iii) ASDP II design process and principles; (iv) program objectives and description;(v) program costs, financing and financial management; (vi) institutional and implementation arrangements; (vii) benefits and economic and financial analysis (EFA) and (viii) Implementation Modalities and Risks. Below are the key highlights of the program. A. MACROECONOMIC INDICATORS AND CONTRIBUTION OF THE AGRICULTURAL SECTOR TO THE ECONOMY 1. Tanzania’s macroeconomic indicators showed robust growth in Gross Domestic Product (GDP) before and during implementation of the first phase of the Agricultural Sector Development Programme (ASDP I) which started in 2006. In recent years, Tanzania has maintained relatively stable, high growth over the last decade (averaging 6%–7% per annum). The GDP growth rate was 7% in 20161. The agriculture sector growth, except for 2008, is still far below GDP growth. The average growth rate for the agriculture sector during the period 2006–2014 was 3.9% per annum, and it decreased to 2.9% in 2015 and then increased to 3.0% in 20162 2. Agriculture contributes significantly to the socio-economic growth of Tanzania. Smallholder farmers (including livestock and fishery) dominate production, with more than 90% of cultivated land. The sector provides about 77.5 % of employment; provides livelihood to more than 70 % of population, 29% of GDP; 30% of exports and 65% of inputs to the industrial sector (URT 2014). However, in 2016/17, the sector contributed 29.1% of the country’s GDP (this is high as compared to 23% in 2014 (FYDP 2015/16), 65.5% of employment (NBS 2017) and food self-sufficient level decreased to 123% compared to 125% (2014/15). This shortfall could be contributed by scarcity of rainfall among other reasons. B. ASDP I KEY ACHIEVEMENTS ASDP was launched in 2006 to provide a sector-wide investment vehicle to deliver the Programme and to contribute to the targets of reducing rural poverty from 27% to 14% by 2010, and raising agricultural growth to 10% per year by 2010. Among ASDP I key achievements was realizing bottom up-planning approach which ensured participatory planning and 75% of budget spent at the LGAs, 20% at national and 5% at regional level. Other achievements include improvement of human and physical capacity at District, 1 http://www.worldbank.org/en/country/tanzania/overview, August 2017 2 Bank of Tanzania. Quarterly Economic Review, May 2017 2 Agricultural Sector Development Programme II (ASDP-II) Region and Nation levels, improved Agriculture Research Services including increased number of research conducted for crops, livestock for improved varieties etc. 3. ASDP I also improved support to agricultural inputs use. Although there still some challenges, some improved seeds were produced and used. The programme also increased agricultural fertilizer, farmer access and use of agricultural mechanization such as tractors, power tillers, oxen-plough, all of which resulted in increased area under cultivation by 148%. Under ASDP I irrigation also was improved. The rehabilitation, improvement and construction of a number of irrigation schemes- resulted in increased irrigated area from 264,338 hectares in year 2005/06 to 461,326 hectares in year 2014 4. Under ASDP I marketing infrastructure and marketing systems for commodity value addition were developed. They include rehabilitation of warehouses; developing crop and livestock markets and developing marketing systems for cash products- receipt systems. Food Self Sufficiency Ratio was improved from 103% in 2009/10 to 123% in 2015/16. 5. Food versus inflation: the food prices remained stable leading to declining inflation rate, 7.01% in year 2006 to 5.56% in year 2010, and 5.6% in 2015; by October 2016 inflation was 4.5%. The export volume and value also increased for cash crops (coffee, cotton, sisal, tea, tobacco and cashew nuts). C. ASDP I - KEY CHALLENGES 6. Several challenges were identified during the implementation of ASDP I. They include inadequate governance, management, and coordination (horizontal and vertical coordination). This resulted to unclear roles and responsibilities; inadequate accountability systems and failure to coordinate sector players/stakeholders. Consequently, there were fragmentation, thinly spread resources; and overcrowding in cases which led to low results/impact, generally difficult to measure programme attribution. 7. Other challenges include poor sector enablers. The programme was implemented in a constrained enabling environment with inconsistent policies and regulations. The inadequate data and data systems also hindered the sector and program monitoring and evaluation. The programme was also challenged with inadequate technical and financial capacity (particularly in irrigation schemes) and adequate capacity to plan, manage and deliver investments. This led to delayed disbursement and caused carry over of funds from year to year. D. LESSONS LEARNT FROM ASDP I 8. Unlike other sectors, public investment in the agricultural sector does not directly produce the expected results, but rather facilitates the private sector (farmers and commercial partners) to achieve the expected targets. Several lessons and experiences were drawn from the implementation of ASDP I which guided the design of ASDP II. (i) The Sector Wide Approach (SWAp) in agriculture is possible when there is sufficient leadership, commitment and well-resourced decentralization of agricultural development planning and implementation. (ii) Need for improved farmer empowerment and organization; (iii) Need for program focus and prioritization on high impact areas, which beyond productivity also strengthen upstream levels of targeted value chains. (iv) Need for good governance, management, coordination, and harmonized monitoring and evaluation of the program; (v) Need for improved sector enablers; (vi) Need more investments in agricultural sector (the government, private sector and development partners). Therefore, there is need for harmonization and coordination on how the public sector should facilitate and enhance private sector participation; development partners and other stakeholders’ involvement in the agricultural sector. E. ASDP II TRANSFORMATION AGENDA/FOCUS 9. The programme vision. Under ASDP II, the intervention will maintain a clear vision, of Poverty Reduction, Food and Nutrition security and GDP growth. In order to address critical constraints and challenges to sector performance and to speed up agriculture GDP, improve growth of smallholder incomes and ensure food security by 2025, the programme encompasses all national strategies (Tanzania Development Vision (TDV 2025); Long Term Perspective Plan (LTPP 2012-2021); Five Year Development Plan II (FYDP II 2016-21) and Agricultural Sector Development Strategy (ASDS 2015)). 3 Agricultural Sector for Industrial Development 10. Prioritized Value Chains and Agricultural Ecological Zones (AEZ). ASDP II will cover all regions in terms of public service delivery (basic support for capacity building, demand-driven advisory services, etc.); however, investment coverage will focus on prioritized high potential commodities along the Value Chain (VC) and Agricultural Ecological Zones (AEZ). The implementation approach will be based on- priority crop/product per AEZ. The selection criteria are; contribution to food and nutrition security, impact to smallholder farmers/livelihood improvement, availability of technology for improving productivity and profitability of the crop, contribution to the national development agenda (industrialization)- five years and local market and exportation potential. 11. The priority CVC selected for first five years for ASDP II includes crops, livestock and fishery value chains commodities these are: rice, maize, cassava, potatoes, banana, coffee, cotton, oil seeds crops (sunflower, coconut, sesame, and palm oil), cashew, tea, sugar/cane and horticulture. The livestock and fish are: dairy, beef, goat, poultry, fish, and sea weed. Regions are “clustered” in AEZs according to similarity of agro-ecological as well as administrative characteristics to drive agricultural transformation. The AEZ with highest comparative advantage over other AEZs in production of a specific VC or a set of priority commodities (crops, livestock, fisheries) and will be designated as a processing hub for that specific VC or a set of commodities. This however will depend on availability of relevant infrastructure. 12. Right Business Environment. ASDP II will build good business environment which will attract investments, incentivize private sector including farmers and increase their engagement in agriculture. The better business environment will protect and increase access to land by small-scale farmers, develop better market systems and use comparative advantage in some commodities which will lead to improved livelihoods of Tanzanians. 13. The programme also focuses on efficient and effective resources allocation and utilization to create value and impact. 14. ASDP II entails committed leadership structures. The focus of the programme is also on a sound and functioning coordination, governance, accountability, administrative management structures, systems, processes and procedures. F. ASDP II OBJECTIVE, STRATEGY AND OUTCOME 15. Objective: Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food and nutrition security. 16. Strategy: Transform subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development 17. Outcome: Increased productivity, enhance marketing level, value addition, farmer income, food and nutrition security and Gross Domestic Product (GDP). G. ASDP II PROGRAMME COMPONENTS AND INVESTMENT AREAS AND PROJECTS/ FRAMEWORKS 18. The programme entails four interlinked components under which a total of 23 priority investment areas were developed. The components and their relevant investment areas are as provided hereunder. Component 1 Sustainable Water and Land Use Management. The objective of this Component is the expanded sustainable water and land use management for crops, livestock and fisheries. Priority investment areas under this component are (i) Land use planning and watershed management; (ii) Irrigation infrastructure development; (iii) Irrigation scheme management & operation; (iv) Water sources development for livestock & fisheries; and (v) Promote Climate Smart Agriculture (CSA) technologies and practices. Component 2 Enhanced Agricultural Productivity and Profitability and its Objective is increased productivity growth rate for commercial market-oriented agriculture for priority commodities. Priority 4 Agricultural Sector Development Programme II (ASDP-II) investment areas are (i) Strengthening Agricultural extension, training and promotion/info services (crops, livestock and fisheries); (ii) Improvement Access to crops, livestock and fisheries inputs and health services; (iii) Research and development; (iv) Strengthening and promoting agricultural mechanization (crop, livestock and fisheries); and (v) Food and nutrition security improved. Component 3 Commercialization and Value Addition. The objective is improved and expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations. Priority investment areas are (i) Develop market access for all priority commodities; (ii) Develop market access for fisheries and livestock products; and (iii) Development of processing and value addition for Crop, livestock and fishery products. Component 4 Sector Enablers, Coordination and Monitoring and Evaluation. The objective of Component four is Strengthened institutions, enablers and coordination framework. Priority investment areas are (i) Policy and Regulatory Framework and Business Environment Improvement; (ii) Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing farmer organizations and cooperatives movement; (iii) Promote and strengthen gender inclusiveness in the agricultural sector; (iv) Improve and strengthen vertical (from PO-RALG to RSs and LGAs) and horizontal coordination between ASLMs. (v) Improved Capacity and agricultural data collection and management systems (vi) Management Capacities and Systems Improvement (vii) Develop Agricultural Sector M&E System (viii) Improvement of Capacity in all levels (ix) Improvement of ICT for Agricultural Information Services and Systems; and (x) Provide microfinance services 19. However, for ease of programme implementation, each investment area was also broken down into various projects/ frameworks for implementers, especially the LGAs. The programme therefore has a total of 56 implementable projects. For the same purposes, 56 projects concept notes were also prepared and can be improved to suit the situation during the implementation. At LGA level, projects/framework can also be broken into smaller projects as it may be necessary and link them to the District Development Plans (DADPs). Proposed projects were prepared in order to facilitate implementation at all levels and alignment with the Key Performance Indicators (KPIs). H. ASDP II IMPLEMENTATION PLAN, SEQUENCING AND SCHEDULING 20. For implementation ASDP II components and projects are sequenced and scheduled to create and bring greatest change and impact to the sector. The program implementation plan, sequencing, scheduling process considered the potential for components and projects which will address immediate sectoral challenges, take advantage of opportunities, and bring positive change. In view of the current challenges facing the private investors and small holder commercial farmers, there is need to implement projects that create the necessary enabling environment (“Unclog the pipe and let the water flow”). Hence, implementation emphasis will start with Component 4 which facilitates implementation of other components and creates the necessary enabling environment for both private and public sector to function including the small holder farmer. Then Component 3 (Commercialization and Value Addition) will create markets pull effect which will attract enhanced agricultural productivity and profitability under Component 2. The implementation of these components will necessitate sustainable water and land use management under Component 1. However, the proposed implementation sequence is meant to guide implementation of the programme depending on the availability of resources. Ideally, all projects should begin at the same time if the required funding is available; if not, the highest priority component, investment areas and projects can be implemented first and lower priority projects implemented later depending on availability of funds. I. GOVERNANCE AND INSTITUTIONAL FRAMEWORK UNDER ASDP II 21. Under ASDP I, there were a number of challenges on governance, institutional and management which led to several problems including unsatisfactory management and accountability systems of the program and project at all levels. Also, there was poor coordination (vertical and horizontal), fragmentation of projects, overcrowding and overlaps in some areas; limited funding on some areas3 and unclear roles, 3 Tanzania Agricultural Sector Investment Mapping (TAN-AIM, 2015/16) 5 Agricultural Sector for Industrial Development responsibilities and mandate of various stakeholders i. e Government to Government, Government to Development Partners (DP), Government to Non-State Actors (NSAs), DPs to DPs and NSA to NSAs. 22. Under ASDP II, the implementation will have a clear governance, institutional framework, coordination and management mechanism from the national to the Local Government Authorities (LGAs). These include: government leadership in the coordination of all stakeholders and effective stakeholder collaboration; clear roles and responsibilities; and authority and accountability of lead and implementing agencies including ASLMs; focus in achieving program/project objectives, outcomes, and KPIs through the Results Framework (RF); development and dissemination of proper program/project guidelines, procedures, and documentations for implementers; facilitate proper financial management and auditing systems for the program and projects; and ultimately all will be accountable to the Prime Minister. The ASDP II National Coordination Unit (NCU) will ensure effective planning, management and implementation of ASDP II projects in partnership with various key stakeholders. 23. The hierarchy of coordination organs under ASDP II at central level will include National Agricultural Sector Stakeholders Meeting (NASSM), Agricultural Steering Committee (ASC), and Agricultural Sector Consultative Group (ASCG), Technical Committee of Directors (TCD), Thematic Working Groups (TWGs) and ASDP II National Coordination Unit (NCU) lead by a National Program Coordinator. 24. Chaired by the Prime Minister, members of NASSM will include Ministers of ASLMS, other central Government Ministers Permanent Secretaries, DPPs from all ASLMs, and senior government officials, Component Leaders; RSs; DEDs; DAICOs, DLFOs; Research Officials; Training officials; Academia representatives; commodity boards; all DPs supporting Agriculture, Private sector etc. the agenda for this annual meeting may include policy guidelines to the agricultural transformation agenda, provide advice and guideline to the implementation of ASDP II etc. as directed by the Chairman. 25. Agricultural Steering Committee (ASC) will be chaired by the Minister of Agriculture (MoA). Members will include PSs and DPPs of Lead Components and related ASLMs; representatives of DPs, NGOs and NSAs. The agenda will include Review and approve ASDP II plans, budgets, monitoring and evaluation reports etc. 26. Agricultural Sector Consultative Group (ASCG) meeting will be chaired by the Permanent Secretary, MoA. The meeting will be attended by all stakeholders in the agricultural sector (GOT, Private Sector, DPs, and NGOs/NSA) and training and research institutions to provide advice on sector policies, plan, budgets, public and agricultural expenditure review, among others. 27. Technical Committee of Directors (TCD) meeting will be Chaired by PS-Ministry of Agriculture. Members will be Directors of ASLMS, Component Leaders, Chairs of Lead Components, PO-RALG, ASDP II Coordination and selected Ministries. The agenda for these meeting will include review, scrutinize and harmonize individual Lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports, etc. 28. Lead Agency Component Technical Meeting will be chaired by DPP of Lead Component. Members will include Chairperson(s) of the Thematic Working Group (TWG) and the agenda will include review submitted component plans, budgets; review and analyze reports. 29. Thematic Working Groups (TWGs) (Various groups) will be chaired by Component/Sub-Component Leaders and members will include selected technical experts of different ASLMs appointed by the Head of the Lead Agency etc. the agenda will include preparation and review of ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination meeting. 30. ASDP II National Coordination Unit (NCU) will also function as ASDP II Secretariat, chaired by National Program Coordinator. Members will include Experts in: Productivity and Commercialization; Planning and Budgeting, Markets and Value chains; Monitoring and Evaluation; Agricultural Economist, Researcher and Policy Analyst. The agenda will include providing a catalytic and supportive role to the agricultural transformation agenda etc. 31. For effective implementation coordination and management, there will also be a coordination unit at the Presidents-Office Regional Administration and Local Government Authorities (PO-RALG) which will be responsible for coordination and managing all ASDP II activities at the lower levels. 6 Agricultural Sector Development Programme II (ASDP-II) J. MONITORING AND EVALUATION OF ASDP II 32. Under ASDP II there will be both internal and external monitoring and evaluation. Immediate level within the GoT will carry the internal monitoring and evaluation e.g. Ward Executive Officer (WEO) will monitor and evaluate the Village Executive Officer (VEO). Monitoring and Evaluation Management system will be established at all coordination levels (National, PO-RALG, Regional, and District). National Coordination Unit (NCU) will coordinate National Joint Annual Reviews and Evaluations. Both at National and PO-RALG level there will be a common Monitoring and Evaluation Thematic Working Group (M &E-TWG). The frequency of the monitoring and evaluation has been set in order to attain the required results. K. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT 33. By combining the base development budgets for each component, the overall investment costs of ASDP II were derived the base cost of ASDP II is estimated at TZS 13.819 Trillion (USD 5.979 billion) and annual investment base costs range from TZS 2.284 Trillion (USD 988 million) to 3.238 Trillion (USD 1.400 million) over a 5-year period. The distribution of the funds will be 25% at National and Regional Secretariat and 75% for Local Government Authorities. 34. Component 1: Sustainable Water and Land Use Management is estimated at TZS 2.024 Trillion (USD 941 million) and a high proportion of this budget is allocated to irrigation development. Component 1 accounts for 15% of overall programme cost. The cost of Component 2: Enhanced Agricultural Productivity is estimated at TZS 8.081 Trillion (USD 3.758 million) or 58% of overall programme cost. Component 3: Commercialization and Value Addition (including investments to promote priority value chain development) is estimated to cost TZS 1.483 Trillion (USD 1.663 million) or 26 % of overall programme cost. Furthermore, the cost of Component 4: Strengthening Sector Enablers is estimated at TZS 137 billion (USD 67 million), or 1% of programme cost. 35. The main sources of financing of the development budgets for ASDP II, will include: the government, development partners and other stakeholders including private sector, NGOs and farmers. For each programme sub-component, the proportions of the budget for which the respective financiers would provide funds were determined to derive a tentative financing plan for ASDP II. 36. On the financing modality, the Government prefers Basket funding for ASDP II. However, standalone direct project financing will also be considered. It is important that there is clear communication, transparency, and coordination during the joint planning and budgeting and implementation of the program. L. SUMMARY OF THE BENEFITS 37. Agricultural transformation and accelerated rural development will make a major contribution to Tanzania’s national development aspirations. The principal benefits of the programme will be: (i) increased and sustainable productivity and production of food and non-food agricultural commodities to improve rural incomes, boost rural households and national level food security, and provide raw materials for the agro-industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural sector generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to adapt to climate change; and (v) improved institutional capacity to mobilize and manage resources in support of agriculture sector development. Above the program will contribute to Tanzania’s higher level national development goals as expressed in Vision 2025. 38. Other expected benefits include: (i) reduction in harvest and post-harvest losses; (ii) increased export earnings; (iii) diversification of production into higher value agricultural products; (iv) improved access to financial services by smallholder farmers and rural entrepreneurs; (v) reduced transaction costs and improved efficiency in pre- and post-farm gate value chains; (vi) increased participation in cooperatives 7 Agricultural Sector for Industrial Development and other forms of FO; (vii) improved access to markets through infrastructure development; (viii) increased rural employment; (ix) higher productivity and reduced vulnerability to droughts from expansion of irrigated agriculture; (x) maintenance of agricultural biodiversity; and (xi) improving the system of disaster risk management by exploring the use of innovative risk management tools; (xii) reduced gender related imbalances; (xiii) reduced child labour in agricultural sector by promoting decent work in accordance with ILO guidelines4; and reduce contribution of agriculture to climate change through promotion of CSA5Functional networks between production and markets. I. BACKGROUND6 A. Macroeconomic Indicators and Agriculture7 1. Tanzania’s macroeconomic indicators showed robust growth in Gross Domestic Product (GDP) before and during implementation of the first phase of the Agricultural Sector Development Programme (ASDP-1) which started in 2006. In recent years, GDP growth rate was between 6.0% and 8.1% between 2006 and 2014 at 2007 constant prices. These levels of GDP growth happened at a time when agriculture sector growth, except for 2008, was far below GDP growth (see Figure 1)8. On average, the service and industry sectors exhibited stronger growth rates than agriculture. The average growth rate for the agriculture sector during the period 2006–2014 was 3.9% per annum, and that of the service and industry sectors was respectively 8% and 7.8% for the same period. From 2006 to 2012, the share of the agriculture sector in total GDP decreased from 27.7% to 23.2%, while the shares of industry and service sectors increased from 20% to 22%, and from 46% to 49% respectively during this period 9. Figure 1: GDP growth rate by sector (%, at 2007 constant prices) Source: Bank of Tanzania. Quarterly economic review, May 2015 2. Given the decline in the agriculture sector’s share of GDP and its contribution to real GDP growth, it is apparent that the robust economic growth is not a shared prosperity. On the contrary, those who earn their livelihood from agriculture and who happen to live in rural areas are trapped in poverty. For example, in 1992 the rural population was 80% of the total population and the poverty rate was 40%. In 2007, after 15 years, the rural population was 74% of the total population and rural poverty rate 4 Conclusions of the “International Workers’ Symposium on Decent Work in Agriculture” Geneva, 15-18 September 2003 5 (Lipper et al. 2014) 6 The background (Chapters I and II) is adapted and building on the FAO-TCIA support to ASDP I-BF June 2013. 7 Tanzania Economic Update: Spreading the Wings, From Growth to Shared Poverty. World Bank, October 2012. 8 See also http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG/countries. 9 According to the World Bank (http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS/countries) the agriculture sector value added in % the country GDP is estimated at 28.1%, 27.7%, 28.7% and 28.4% for 2010, 2011, 2012 and 2013 respectively. In this case agriculture corresponds to ISIC divisions 1–5 and includes forestry, hunting and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. 8 Agricultural Sector Development Programme II (ASDP-II) was estimated at 37.8%. It is apparent that much has not changed in terms of both the share of rural population and rural poverty rates in Tanzania. The sectors that have driven economic growth, such as construction, finance, mining, services10, and telecommunications have not created jobs in rural areas and have not had a noticeable impact, direct or indirect, on the rural population. Moreover, the reason why the robust economic growth over the last decade has not been associated with poverty reduction is because the agriculture sector has been growing more slowly than other major sectors. Therefore, growth of the agriculture sector does not substantially influence GDP growth, as it did in the 1970s and 1980s when it contributed about 50% of total GDP; neither does it contribute significantly to poverty reduction in Tanzania11. 3. The 2012 Tanzania Economic Update12 highlights that “rapid economic growth and stability has generated high dividends for Tanzania in recent years, driving increases in per capita income of 70% over the past decade. However, these benefits have not been evenly shared. To fight rural poverty, successful economies have implemented systems to connect their farmers to markets. These economies encourage the cultivation of high-value, non-traditional crops and manage migration flows toward urban centres to facilitate growth and equity. Rather than minor adjustments, fighting rural poverty requires a major policy shift that involves: (i) agricultural commercialization; (ii) diversification; and (iii) urbanization. The paper concludes that the challenge for Tanzanian policy makers is to stimulate these three transformational forces and manage them appropriately over the long term” B. The Agriculture Sector 4. The relative contribution to agricultural GDP by crop, livestock, forestry and hunting, and fisheries in recent years averaged 18%, 5%, 3% and 1.4% respectively. Tanzania has a total of about 7.1 million ha of high and medium potential land (2.3 and 4.8 million ha respectively) suitable for irrigation, supported by rivers, lakes, wetlands and aquifers. Of the 2.3 million ha classified as high potential, only 461,326 ha had improved irrigation infrastructure in 2015, accounting for only 1.6% of the total land with irrigation potential (MAFC, 2015). An estimated 55% of the land could be used for agriculture, and more than 51% for pasture. However, only about 6% of the agricultural land is cultivated, and the practice of shifting cultivation causes deforestation and land degradation on pastoral land. Tanzania is one of the few countries in Africa that still has extensive wildlife resources and protected areas that account for about 25% of its total land area. Figure 2. Agriculture share of GDP (%), 2001 prices However, the growth of agriculture is hampered by low productivity of land and labour. Although numerous factors caused this situation, the key factors are, inter alia: (i) poor production techniques; (ii) 10 Including tourism. 11 Review of food and agricultural policies in the United Republic of Tanzania. MAFAP Country Report Series, 2013, FAO, Rome, Italy. 12 Spreading the Wings: from growth to prosperity. World Bank publications: http://www-wds.worldbank. org/external/default/WDSContentServer/WDSP/IB/2012/10/24/000386194_20121024053815/Rendered/ PDF/733460WP0P133400Box371944B00PUBLIC0.pdf. 9 Agricultural Sector for Industrial Development underdeveloped markets, market infrastructure and farm-level value addition; (iii) poor rural infrastructure, including rural roads, telecommunications and electricity; and (iv) inadequate agricultural finance, including public expenditure. Use of productivity enhancing agricultural inputs is also one of the lowest in the region. For example, Tanzanian farmers use about 8–10 kg of fertilizer per hectare (dolllubled from 2008 to 2013), compared with an average of 16 kg/ha for Southern African Development Community (SADC) countries while Malawi uses 27 kg/ha and China 279 kg/ha on average. However, in spite of these low levels of application, the Tanzanian market has failed to absorb all the fertilizer stocks supplied by traders, recording surpluses of between 15% and 30% during the 2007/2008 to 2009/2010 seasons. The annual supply of improved seeds is about 30,000 tons (75%maize seeds) or 25% of total estimated requirements of 120,000 tons per year. There has been a sharp increase in supplies, combined with a narrowing of the gap between supplies and purchases since 2007/2008, when the government increased funding for its National Agricultural Input Voucher System (NAIVS), suggesting that this system has been useful in enhancing input absorption by farmers. Figure 3: GDP by economic activity (at current prices—TSh billion)13 20% 25% 30% 35% 0 2500 5000 7500 10000 12500 2007 2008 2009 2010 2011 2012 2013 GDP by economic activity (TSh billion 2007/13 - current prices) Crops Livestock Forestry Fishing % GDP Agriculture Figure 4: Percentage GDP by economic activity (in % of total GDP—at current TSh prices) 24 26 28 30 32 0 2 4 6 8 10 12 14 16 18 20 2007 2008 2009 2010 2011 2012 2013 % Agric. in total GDP % of GDP GDP by economic activity (TSh billion 2007/13 - current prices) Crops Livestock Forestry Fishing % GDP Agriculture 5. Crop subsector. The production of main crop commodities over the past 50 years has been reported (FAOSTAT), as shown in Figure 5. The changing point seems to be in year 2000 with: (i) the total cereal (maize, rice, sorghum, millet) production out-yielding the annual cassava production (mainly linked to yield variations); (ii) sharp production increases are recorded for cereals, especially maize, banana, sugar and other root crops and to a lesser extend for oil crops. Farmer yields for the main food crops 13 Adapted from data sourced in Revised National Accounts Estimates for Tanzania Mainland (Base year 2007). National Bureau of Statistics, Ministry of Finance, November 2014. 10 Agricultural Sector Development Programme II (ASDP-II) doubled over the past 50 years reaching about 1.5 and 2.0 tons/ha for maize and rice respectively. For pulses and oil crops yields increased, but remain on average below 1.0 ton/ha per season as shown in Figure 5. Figure 5: Main crop production in Tanzania (1961–2013, in tons) Figure 6: Evolution of average crop yields for main crops in Tanzania (1961–2013, in kg/ha) 6. Livestock sub-sector. This sub-sector includes about 21.3 million cattle, 15.2 million goats and 6.4 million sheep. Other livestock kept in the country include 1.9 million pigs, 35.1 million indigenous and 23 million exotic chicken14. The country has the third largest cattle population in Africa after Ethiopia and Sudan. About 90% of the livestock population is of indigenous types which are known for their low genetic potential in milk and meat production. The livestock sub-sector growth rate averaged 4.2%, against 3.6% for the whole sector. The cattle population increased at an average rate of 1.4% and poultry recorded an impressive growth rate of 9.6% to reach 58 million chickens. 7. In meat processing. The Government has supported the private sector to invest in modern abattoirs and slaughterhouses in Sumbawanga, Dodoma, Arusha, Morogoro and Coast regions among others. The government has also sold some of its shares in former government owned companies such as National Ranching Company (NARCO) and Dodoma Abattoir. Although the number of milk processing plants increased from 22 to 39 over the 2001–2009 period, there is still huge potential to expand the 14 Ministry of Livestock and Fisheries Development (MLFD), Statistical Year Book, 2013. 11 Agricultural Sector for Industrial Development milk industry (1.5 billion litres/year), as only 20% is collected and processed. Private companies have also resumpted milk processing in Musoma, Arusha, Tanga, Dar es Salaam, Morogoro, Iringa, Mbeya and Njombe. Following improvement in business environment, the number of plants for processing hides and skins increased from 3 to 6 between 2001 and 2009, with a capacity to meet 52% of the total production (48.2 million square feet with TSh 12.8 billion in 2009). 8. Fisheries. Tanzania is endowed with fishery resources, both marine and inland. Marine water covers 64,000 square kilometres and a coastal line of 1,424 kilometres. The Exclusive Economic Zone (EEZ) is up to 200 nautical miles covering an area of 223,000 square kilometres providing the country with additional marine area and fisheries resources. Fresh water fisheries which cover 62,000 square kilometres include the shared waters of the great lakes, namely Victoria, Tanganyika and Nyasa. The country has also other small natural lakes, man-made lakes, river systems and many wetlands with fisheries potential. Despite the diverse fisheries potential, most are untapped including those in the EEZ. The industry has been dominated by small-scale fishers and fish farmers who normally use traditional technology. Hence, the fisheries sector is an area which, once effectively utilized, will improve the economy in an enormous way. The annual growth rate of the fisheries sector has been fluctuating annually. For example, in 2014 the growth rate was 2.0% and in 2013 it was 5.5%. The contribution of fishing activities to GDP has almost remained constant with a slight change of 0.1%. In 2010 the share of fishing activities was 1.5% before decreasing to 1.4% in 2011 and 2012; it further decreased to 1.3% in 2013 and 2014. 9. Private investment in agroprocessing. This sub-sector has the potential to generate employment, raise productivity, transfer skills and technology, increase competitiveness, substitute imports and enhance exports, and contribute to the long-term national economic development. Although increasing, the inflow of the foreign direct investment to the agriculture sector remains low with 2–3% of the total foreign direct investment (USD 31.4 million in 2011). Rapid urbanization and rising incomes have been contributing to increased demand for value-added products in the agriculture sector. However, on the supply side, the underdeveloped agroprocessing industry has so far failed to provide significant levels of import substitution for the urban food market. The mismatch between demand and supply for value- added food products resulted in tripling the country’s food import bill between 2006 and 2013 (USD 963.9 million). Globally, the pattern of growth of the economy is influenced by the transformation of the agriculture sector through value addition of primary products, thereby influencing investments in industry and service sectors. C. Policy Environment 10. Tanzania has a clear articulated long and medium-term policy frame for the economy in general and for the agriculture sector in particular. The long-term policy framework places agriculture at the centre and has evolved various sector and sub-sector policies. Related fields such as natural resources management are addressed and their complementarity in terms of achieving the long-term social and economic development objective of the country is articulated. The key policies that address the sector are discussed in the following sub-sections; 11. Tanzania Development Vision 2025. The Tanzania Development Vision (TDV) is a long-term vision that the Government of Tanzania issued to guide its development. The vision articulated in this policy document is that by 2025 Tanzanians will have created a substantially developed, people-centred, peaceful, stable and united society with high quality livelihood and high level of human development. The economy will have been: “transformed from a low productivity agricultural economy to a semi- industrialized one, led by modernized and highly productive agricultural activities which are effectively integrated and buttressed by supportive industrial and service activities in the rural and urban areas. A solid foundation for a highly productive, competitive and dynamic economy will have been laid”. The agriculture sector is identified as an important arena where strategic interventions will be implemented to contribute to the building of a strong solid foundation for a highly productive, competitive and dynamic economy15. 15 Government of URT. 1999a. The Tanzania Development Vision 2025. Dar es Salaam. 12 Agricultural Sector Development Programme II (ASDP-II) Figure 7. Long & medium-term policy framework for the transformation of the agriculture sector • Improved livelihoods, food security,extended life expectancy (Pillar 1); Building a strong & competitive economy (Pillar3) by raising agricultural productivity, engaging in commercial undertakings in value chains, genrating surplus household income & export earnings • Agriculture (core priority 2): Focusing on the transformation of agriculture for food self suffiency and export, development of irrigation particularly in selected agricultural corridors, and high value crops including horticulture, floriculture, spices, vineyards etc. • To have an agricultural sector by year 2025 that is modernized, commercial, highly productive, utilizes natural resources in an overall sustainable manner and acts as an effective basis for inter-sectoral linkages • To change the functions of central government from an executive role to a normative one; empowering local government and communties to reassume control of their planning processes and to establishing an enabling environment which attracts and encourages private sector investments in agriculture • To rationalize allocation of resources to achieve annual 6 percent agricultural GDP growth, consistent with national objectives to reduce rural poverty and improve household food and nutrition security • Joint GoT & private sector declaration on speeding up agenda for the modernization of agriculture to uplift agricultural growth from 4 to 10% within the time frame of the vision 2025 Vision 2025 NDP 2006- 2011 ASDS 2001 ASDP 2006-13 Kilimo Kwanza 2009 TAFSIP 2011-21 Source: Compiled from FAO/TCIA (2013). 12. The National Strategy for Growth and Reduction of Poverty I & II. This strategy is known as MKUKUTA I and II and is one of the national strategies aimed at moving the nation towards Vision 2025 and to achieve the Millennium Development Goals (MDGs). The essential features in developing both MKUKUTA I & II were national ownership and consultation with stakeholders, aiming to foster greater collaboration among all sectors and stakeholders. The strategy requires increased resource mobilization and that the national budget is aligned to MKUKUTA with direct links to the public expenditure review. A Joint Development Cooperation Framework (DCF) has been developed with development partners to increase the volume and effectiveness of aid, harmonization and alignment to achieve MKUKUTA objectives16. The MKUKUTA II strategic intervention cluster is Growth and Reduction of Income Poverty, focusing on equitable and employment generating growth, sustainable development principle, food security and affordable and reliable modern energy services and adequate infrastructures for production purposes. Agriculture is identified as one of the key growth areas and means to attain TDV 2025. 13. Agricultural Sector Development Strategy II (ASDS-2) of September 2015. This strategy reflects the changes in the overall economic environment and the policies and programmes that emerged over the years. ASDS-2 sets a new direction for the development of the sector, integrates the Comprehensive Africa Agriculture Development Programme (CAADP) objectives and reflects most of the vision and principles enunciated in the Tanzania Agriculture and Food Security Investment Plan (TAFSIP). It stresses the need to continue the pursuit of a sector-wide approach to plan, coordinate and harmonize the resources (public and private) required to accelerate implementation of existing initiatives and to incorporate new initiatives which address national, regional and sectoral development priorities. Largely along the line of TAFSIP, the ASDS-2 defines the sector-level monitoring and evaluation (M&E) framework and identifies strategic areas for public and private investment for achieving expected outcomes and impact. The ASDS-2 also details the policies, strategies and priority support areas for achieving agricultural and rural development, contributing to the goals of Vision 2025, as well as the economic growth and 16 Government of URT. 2010b. National Strategy for Growth and Reduction of Poverty II (NSGRP II).Dar es Salaam, Ministry of Finance and Economic Affairs. 13 Agricultural Sector for Industrial Development poverty reduction objectives specified in MKUKUTA/MKUZA strategies. Identified key priorities for ASDS-2 include: (i) the role of science and technology (research, extension, fertilizer use by small-scale commercial farmers); (ii) further priorities such as irrigation, finance, mechanization, agroprocessing and access to markets; and also (iii) strong articulation with other sector initiatives such as Southern Agricultural Growth Corridor of Tanzania (SAGCOT). 14. Kilimo Kwanza (KK). The global food price crisis of 2008/2009 gave rise to renewed interest in the agriculture sector by both continental leaders under the African Union framework and the international community. The government successfully launched plans for the active engagement of the private sector and in mainstreaming agriculture in all sectoral undertakings, emphasizing the importance of Kilimo Kwanza, which means “agriculture first”. Internationally, the country received support from the G8 to mobilize international private sector capital and technology transfer to revamp the agriculture sector. Most initiatives were designed to enhance technology uptake (e.g., seeds and fertilizer), market development and export promotion. The government, development partners and the private sector agreed to adopt a cluster approach to optimize human and financial resources in attaining maximum impact in the shortest time possible. SAGCOT is among the first programmes under this approach where partnership between government, small-scale farmers and large-scale commercial farmers/processors is emphasized. These developments channelled additional support for mainly parallel implemented projects to be ‘coordinated’ within the overall ASDP framework. 15. Tanzania Agriculture and Food Security Investment Plan. TAFSIP is Tanzania’s version to operationalize the CAADP17 framework formulated to assist achievement of TDV 2025. It is a 10-year road map for agricultural and rural development that identifies priority areas for public and private investments in the sector to promote agricultural growth, rural development, and food security and nutrition. It is a framework for the prioritization, planning, coordination, accountability, harmonization and alignment of investments that will drive Tanzania’s agricultural development over the next decade. To achieve the CAADP objectives, the investment plan is expressed in terms of seven thematic programme areas each with its own strategic objective and major investment programmes. The thematic areas are: (i) Irrigation Development, Sustainable Water Resources and Land Use Management; (ii) Agricultural productivity and Rural Commercialization; (iii) Rural Infrastructure, Market Access and Trade; (iv) Private Sector Development; (v) Food Security and Nutrition; (vi) Disaster Management, Climate Change Adaptation and Mitigation; and (vii) Policy Reform and Institutional Support. 16. The objectives of CAADP are to: (i) achieve an average of annual sectoral growth of 6% and government allocation of budget at 10%; (ii) attain food security and nutrition; (iii) develop regional and sub-regional agricultural markets; (iv) integrate farmers and pastoralists into the market economy; and (v) achieve a more equitable distribution of wealth. These objectives, as amplified by the Malabo Declaration (2014) anchores to: (i) allocate at least 10% of public expenditure to agriculture, and to ensure its efficiency and effectiveness; (ii) transform agriculture and ensure inclusive growth through doubling of agricultural productivity, enhance value chains and tripling intra-African trade in agricultural goods and services; and (iii) strengthening systematic capacity for transformation through capacity for planning, policies and institutions, leadership, coordination, partnerships and data and statistics. Through CAADP, African governments commit to providing technical and financial support for the transformation of the agriculture sector and the development of the agro-based private sector, as well as addressing trade issues18. CAADP includes a focus on: (i) changing perspectives and mind-sets to promote commercial agriculture; (ii) promoting policies that raise agricultural productivity; (iii) expanding markets at national, regional and international level; and (iv) encouraging and facilitating private investment to support the agricultural 17 Initiative of the African Union’s New Partnership for Africa’s Development (NEPAD), adopted by the Heads of State and the government in Maputo, Mozambique in 2003. 18 From 2008 to date, the CAADP Africa-owned policy narrative has been steadily sidelined by the US-led G8 mobilization of (support for) global agribusiness, with assistance pledged by aid agencies and philanthropies. The comprehensive nature of this transition to MNC-driven policy—which climaxed with the May 2012 NAFSN G8 meeting reflects the seriousness of the on-going global food crisis (Source: The Comprehensive Africa Agriculture Development Programme (CAADP) and agricultural policies in Tanzania: Going with or against the grain (B. Cooksey, 2013). 14 Agricultural Sector Development Programme II (ASDP-II) sector. Unlike the Maputo Declaration, the Malabo Declaration sets output indicators to be achieved with high level aspirations for sustainable and inclusive development, renewed commitments towards evidence based planning and accountability with view to conduct a biennial Agricultural Review Process that involves tracking, monitoring and reporting on progress. II. SECTOR PROGRAMMES, PROJECTS AND PUBLIC EXPENDITURE A. Agriculture Sector Development Programme (ASDP phase 1) 17. The Agriculture Sector Development Programme (ASDP) is one of the key instruments that the government uses to meet TDV 2025 and implement the ASDS. This programme had the following objectives: (i) to enable farmers to have better access to, and use of, agricultural knowledge, technologies, marketing systems and infrastructure, all of which contribute to higher productivity, profitability, and farm incomes; and (ii) to promote private investment based on an improved regulatory and policy environment. The objectives will be achieved through a set of complementary interventions aimed at: (i) improving the capacity of farmers, including food insecure and vulnerable groups, to more clearly articulate demand for agricultural services and to build partnerships with service providers; (ii) reforming and improving capacity of both public and private agricultural service providers to respond to demand and provide appropriate advice, services and technologies; (iii) improving the quality and quantity of public investment in physical infrastructure through more devolved technically-sound planning and appraisal; and (iv) improving market institutions, including strengthening the policy and regulatory frameworks and coordination capacity at national level. These results will be delivered through Local Level Support and National Level Support, as described in the following paragraphs; 18. ASDP was launched in 2006 to provide a sector-wide investment vehicle to deliver the Programme and to contribute to the targets of reducing rural poverty from 27% to 14% by 2010, and raising agricultural growth to 10% per year by 2010. ASDP was conceived and implemented as a bottom up approach delivered nationally, with 75% of development funds from a multi-donor Basket Fund allocated to local level support through a performance-based block grant mechanism. The Basket Fund represented an improvement in aid effectiveness away from fragmented projects to an on-budget, government- led approach underpinned by greater policy coherence and use of government planning and reporting systems. ASDP also envisaged greater pluralism in service delivery, an improved regulatory environment and stronger control of resources by beneficiaries. ASDP was conceived to have a 15-year horizon and a first phase of 7 years 2006/2007 to 2012/2013. 19. Despite initial delays in Basket Fund contributions and programme start-up, ASDP-1 implementation improved steadily over time. It succeeded in introducing the concept of a sector-wide approach in the agriculture sector. The ASDP process is now widely understood from national down to village level. It has created a mode of operation which has streamlined planning, financial management, monitoring and reporting systems, all of which have shown improvement. It has facilitated significant development of human and physical capacity, particularly at the Local Government Administration (LGA) level19; a capacity which can now support ASDP II activities, and which can also provide an environment for new initiatives to use and contribute to the higher-level sector goals. 20. ASDP-1 also faced challenges in the course of implementation. As for the government budgets, its wide thematic area coverage and its national scope resulted in a situation where limited resources were thinly spread, and results were fragmented and hard to assess, attribute and report. Challenges related to inadequate technical capacity, particularly at the level of LGAs in planning, prioritization and implementation were also experienced. Significant carryover of funds from year to year (e.g., about 30% of released funds in the case of irrigation) shows that capacity to plan, manage and deliver investments has been a challenge. Donor harmonization, as envisaged at the start of ASDP, weakened over time and proliferation of self-standing projects gradually emerged. Coalescing around both the Paris Declaration and the Accra Agenda for Action to make development assistance more effective has 19 See ASDP JIR and Evaluation report 2011. 15 Agricultural Sector for Industrial Development faced challenges in the agriculture sector in the absence of strong leadership. Other challenges and gaps include limited participation of agribusiness/private sector in programme activities; limited support to farmer organizations, especially on their role in marketing and value addition; incomplete irrigation schemes, which reduces achievement of optimum payoffs and sustainability. 21. District Agricultural Sector Investment Project (USD 83 million) financed by the African Development Bank from 2006 to 2013 was implemented parallel to ASDP-1 in 28 rural districts of Kagera, Kigoma, Mwanza, Mara and Shinyanga regions (about 0.57 million beneficiaries). The project was to increase productivity and incomes of rural households by: (i) farmers’ capacity building; (ii) community planning and investment in agriculture, especially in infrastructures; and (iii) support to rural microfinance and marketing. B. Other Related Agricultural Sector Initiatives 22. Besides ASDP-1, major ongoing projects in the agriculture sector, inter alia include: AFSP (Accelerated Food Security Programme: about USD 245 million, co-financed in 2009–2013 by the Government of Tanzania and the World Bank in parallel to ASDP). The objective was to contribute to higher food production and productivity in targeted high potential areas in Tanzania through improving maize and rice farmers’ access to the critical agricultural inputs (total number of beneficiaries are 1.75 million households). The AFSP had three main components: (i) improving access to maize and rice seeds and fertilizers, by strengthening the NAIVS; (ii) consolidating the agricultural input supply chains, by strengthening private agrodealer networks and national seeds systems; and (iii) project management, and monitoring and evaluation. AFSP also provided an additional financing for: (i) the ASDP-1 (USD 30 million), aimed to promote sustainable agricultural productivity growth, including support to small- scale irrigation and water management, integrated soil fertility management by strengthening research and advisory capacities for soil nutrient management and conservation farming; and (ii) for the second Tanzania Social Action Fund (AF-TASAF-2, USD 30 million), to strengthen the rural safety nets for food insecure and vulnerable people. 23. MIVARF: The Marketing Infrastructure, Value Addition and Rural Finance Support Programme (co- financed by the International Fund for Agricultural Development [IFAD] and AfDB for a total of USD 170 million, and coordinated by the Prime Minister’s Office [PMO]) is implemented in 26 regions of Tanzania, including the mainland (21 regions) and Zanzibar (5 regions) with a total of 141 rural districts. The programme is expected to directly benefit close to 500,000 rural households. The development objective is to enhance the incomes and food security of the target group sustainably through increased access to financial services and markets. The programme will focus on strengthening the marketing infrastructure and systems, and the rural finance sector. In particular, it aims at: (i) increasing access of poor rural people to a wider range of financial services for productivity-enhancing technologies, services and assets; and (ii) increasing access to sustainable agricultural input and output markets and opportunities for rural enterprise. 24. MUVI (The Rural Micro, Small and Medium Enterprise Support Programme): A total of USD 25 million, implemented through the Ministry of Industry Trade and Investment helps improve rural employment opportunities in 6 regions (Iringa, Manyara, Mwanza, Pwani, Ruvuma and Tanga). The programme provides selected medium and small-scale rural entrepreneurs with improved skills training, knowledge and access to markets, to help increase productivity, profitability and off-farm incomes. The programme has three goals: (i) to improve the awareness of rural entrepreneurs of market opportunities and how these can be exploited through the development and implementation of a communication strategy and the training of the entrepreneurs to improve their businesses; (ii) to improve the coordination and cohesion of selected value chains, through the creation and strengthening of backward and forward linkages for the selected chains; and (iii) to strengthen public and private sector institutions to provide efficient and effective support to rural enterprises. 25. SAGCOT (Southern Agricultural Growth Corridor of Tanzania): The goal of this initiative is to expand investment in agribusiness leading to income growth among smallholders and employment generation 16 Agricultural Sector Development Programme II (ASDP-II) across agribusiness value chains in the Southern Corridor. Its mandate is to mobilize private sector investments and partnerships by catalysing large volumes of responsible private investment, targeted at rapid and sustainable agricultural growth, with major benefits for food security, poverty reduction and reduced vulnerability to climate change. SAGCOT promotes ‘clusters’ of profitable agricultural farming and services businesses, with major benefits for smallholder farmers and local communities. The SAGCOT focus on value addition, infrastructure development, agricultural production and productivity and public–private partnership is consistent with the strategies and priorities of ASDS, complemented by KK.20 26. BRN (Big Results Now): The slow pace of implementing Vision 2025 had prompted the government to embark on a new model dubbed ‘Big Results Now’. This initiative was implemented through six sectors, namely agriculture, energy, education, resource mobilization, transport and water. Expert laboratories prepared priority implementation plans21 for the next two years. The objective of the agriculture BRN plan was to address critical sector constraints and challenges and to speed up agricultural GDP, improve smallholder incomes and ensure food security by 2015, mainly through smallholder aggregation models for main cereals and high potential crops contributing to import substitution, farm income and food security. Three programmes were prioritized including: (i) building a warehouse based trading system for maize (275 warehouses in 8 districts); (ii) building 78 professionally managed commercial rice irrigation schemes (in 10 districts); (iii) supporting 25 commercial farming (agribusiness) deals in the SAGCOT region. The target under 3 programmes is to have additional 150,000 tonnes of sugar22, 290,000 tonnes of rice and 100,000 tonnes of maize produced by June 2016. BRN provides important impetus in terms of political will, leadership and coordination across ministries, the financing of proposed activities and implementation modalities, coordinated through a Presidential Delivery Bureau (PDB) and Agricultural Delivery Division (ADD). 27. To ensure effective participation of private sector investment in the agriculture sector, through BRN, the Government has embarked on creating a conducive business environment. Among others, highlighted areas addressed as business environment challenges, especially for the micro-, small- and medium-scale enterprises, is both a strategically critical and urgent matter for the prospect of attaining TDV 2025. A Business Environment Lab was also conducted in early 2014, covering six (6) key work streams, namely: (i) access to land and security of tenure; (ii) contract enforcement, law and order; (iii) curbing corruption; (iv) labour laws and skillset; (v) aligning regulations and institutions; and (vi) taxation, multiplicity of levies, fees and charges. 28. EAAPP (The East Africa Agricultural Productivity Programme): This programme aimed at supporting the regional centres of excellence (RCoE) to contribute to increased agricultural productivity and growth by strengthening and scaling up regional cooperation in technology development, training, and dissemination programmes for four priority commodities (wheat, Ethiopia; rice, Tanzania; cassava, Uganda; and dairy, Kenya). Accordingly, EAAPP strives to enhance regional specialization in agricultural research for development (AR4D) and facilitate increased transfer of agricultural technology, information and knowledge within and across national boundaries. The main programme components are: (i) strengthening institutional capacities of RCoEs; (ii) technology generation, training, dissemination and scaling up, focused on regional priorities and using participatory strategies; (iii) improved availability of seeds and breeds, including strengthening the enabling environment for regional seed and breed exchange and trade; and (iv) programme coordination and management at national and regional levels. For the regional coordination activities, each participating country contributes about 2.7% of its budget to ASARECA23, for regional coordination activities. 20 ASDP and SAGCOT cover both the Southern Highland corridor area and target smallholder farmers, emphasizing commercialization by linking farmers with agribusiness to enhance competitiveness in domestic, regional and international markets. ASDP IIwill empower smallholder farmers so that they can increasingly benefit from support and services offered through SAGCOT, such as contract farming and out-grower schemes and matching grants under a catalytic fund. 21 More of a plan than actual programmes/projects as clarified by PMO and the Minister of the then MAFC. 22 To be supported by IFAD (USD 40 million) and co-financed by AfDB (USD 30 million) 23 ASARECA is a sub-regional organization aiming to enhance regional collective and harmonized action in AR4D, extension, training and education to promote economic growth, fight poverty, eradicate hunger and 17 Agricultural Sector for Industrial Development 29. FTF (Feed the Future): In Tanzania FTF is a USD 70 million annual off-budget contribution from the United States Agency for International Development (USAID), of which 80% is invested in SAGCOT; the rest targets Manyara and Dodoma regions and the Zanzibar islands. The FTF strategy, aligned to TAFSIP, is integral to the USAID strategic plan in both achieving sustained economic growth through agriculture and improving the nutritional status of all Tanzanians. Investments aim at improving economic opportunities and incomes through private sector led interventions and partnerships, including for women and youth. Expected outcomes are to increase yields (maize and rice), productivity and market access for horticulture producers and prevalence of children receiving a minimal acceptable diet, targeting about 100,000 smallholders (about 2% of the total number of smallholders). Furthermore, FTF is supporting the Tanzanian government to: (i) make informed policy decisions based on research and data, including quantifying the impact of rescinding the maize export ban, examining land compensation and leasing schemes and implementing a collateral registry system; and (ii) build human capacity and strengthen collaborative research capacity in national universities and institutions. FTF is also leveraging and scaling up local innovations, including food fortification, to improve access to nutritious foods and increase dietary diversity along the value chain. 30. ASDP-1 Financing: In the past 10 years, ASDS has been operationalized by ASDP with financing from the Government (central and local governments), the World Bank, AfDB, IFAD, the governments of Japan and Ireland, and the European Union. ASDS and ASDP emphasized sector-wide approach and Basket Funding as the preferred form of contribution from donors to foster harmonization of sector interventions, as opposed to the proliferation of ‘traditional’ projects. Overall, it appears that over the ASDP-1 implementation period, development partner funding support to the agriculture sector gradually moved towards increasing levels of earmarked basket funding, (back to) ‘traditional’ on-budget projects/ programmes implemented through different sector ministries, but also increased off-budget support. Although not always recognized24, several stand-alone projects were building on systems and capacities developed and maintained by ASDP-1, especially at LGA level: mutual levering is commendable, but non-earmarked financing of basic capacities, (Extension and Capacity Building Block Grants) have decreased to a critical level. Development partners have also made further investment commitment to BRN and/or specific local programmes, with high investment concentration on the SAGCOT area. ASDP II is open to a variety of financing modalities including the Basket Fund. C. Agriculture Sector Review-Public Expenditure Review (ASR-PER) 31. There is significant variability between sources of information relating to public expenditure in the agriculture sector. For example, the ASDP Secretariat often use budgets and expenditure of agriculture sector lead ministries (ASLMs). This approach excludes departments and agencies which undertake agricultural activities and is therefore prone to under-reporting of public expenditure. In contrast, the Ministry of Finance uses a broader definition of the agriculture sector than that reported by the ASDP. A more reliable source of information on public expenditure in agriculture are the series of annual reports on agricultural public expenditure, prepared since 2006, including the most recent Agriculture Sector Review-Public Expenditure Review (ASR-PER) (2014) issued in March 201525. The main aims of the ASR-PER are to: (i) present in-depth analyses on current issues of sector policy; and (ii) provide a standard database on key indicators of sector development, government interventions and public spending. 32. The ASR-PER compiles expenditure data by applying the standard Classification of Functions of Government (COFOG) which covers crops, livestock, fishing and production forestry. The statistics enhance sustainable use of resources in 11 participating countries. ASARECA focuses on generation and delivery of improved scientific knowledge, policy options and technologies as instruments to drive the sub-region towards meeting the NEPAD CAADP agenda and the MDGs, within a subsidiarity approach. 24 The IFAD Country Programme Evaluation (December 2014 final-unedited), recognized the high relevance, effectiveness, efficiency and sustainability of their ASDP investments when compared to alternative investments especially in agricultural marketing and value chain development. 25 Agriculture Sector and Public Expenditure Review 2014, MAFC, March 2015. 18 Agricultural Sector Development Programme II (ASDP-II) include expenditure from domestic budgetary sources (both national and sub-national) as well as from donor contributions in the category of “aid to government” and official loans. Expenditure on irrigation schemes is also included, but support for processing and marketing of agricultural products is not covered. The data collected by the annual ASR-PER is also used to monitor actual spending levels against the benchmark of the Maputo Declaration of 2003 and reaffirmed under the Malabo Declaration of 2014 in which the Heads of State of the African Union are committed to allocating 10% of total public expenditure to agricultural development. This commitment is primarily aimed at accelerating annual agricultural growth (target at 6%) to reduce poverty and enhance food security. 33. Public expenditure on agriculture appears in the central government budget mainly as recurrent and development spending of the Ministry of Agriculture Food Security and Cooperatives (MAFC) and the Ministry of Livestock and Fisheries Development (MLFD). However, services to farmers are primarily provided by LGAs and financed through grants from the central budget. The agriculture sector also receives development aid, but only the on-budget portion appears in budget estimates and financial statements. 34. Recurrent expenditure through MAFC and MLFD and agricultural spending by districts, have increased in recent years. However, this can to a large extent be attributed to the growth in input subsidies (2009–2012) and grants to the National Food Reserve Agency (NFRA). Expenditure on NFRA, input subsidies and other transfers to autonomous government institutions and international organizations, is shown in Figure 8. 35. In 2013/14, total recurrent expenditure through MAFC and MLFD was estimated at TSh 306.6 billion with special expenditure (i.e., NFRA grants, input subsidies and transfers to other government agencies) absorbing TSh 238.1 billion (78% of the total MAFC budget). In contrast, routine expenditure (i.e., personnel costs and operational charges) amounted to TSh 68.5 billion (22% of the total MAFC budget). However, while NFRA grants and input subsidies have increased since 2011/12, expenditure on personnel and operational charges has broadly remained unchanged and, in real terms, routine expenditure at central level has actually declined (Table 1). Figure 8. MAFC and MLFD Central-Level Recurrent Expenditure Source: ASR-PER, March 2015 (based on Budget Estimates for various years). 19 Agricultural Sector for Industrial Development Table 1: MAFC and MLFD central level recurrent expenditure (TSh million)26 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual Estimate Estimate Routine Expenditure Personnel Emoluments MAFC 16,953 18,490 21,659 25,167 26,328 27,169 MLFD 11,467 15,669 17,238 16,721 18,429 18,429 Operational Charges MAFC 11,673 9,781 7,174 16,368 14,516 14,916 MLFD 15,373 12,501 10,371 8,836 9,207 7,533 Total Routine Expenditure 55,465 56,441 56,442 67,091 68,479 68,047 Special Expenditure1 Input subsidies MAFC 54,963 56,902 39,893 47,858 97,014 96,900 Input Subsidies MLFD 332 149 26 127 106 37 NFRA Grant 54,657 74,383 28,134 42,423 110,400 111,254 Other Transfers 50,761 22,436 24,269 32,432 30,596 35,401 Total Special Expenditure 160,714 153,870 92,323 122,839 238,115 243,592 Total MAFC and MLFD Recurrent Expenditure 216,179 210,311 148,765 189,930 306,594 311,639 Source: ASR-PER, March 2015 (based on actual and budget estimates for various years). 36. With regard to LGA expenditure, Table 2 shows that the levels of district spending account for a significant proportion (above 60%) of total routine expenditure. However, when compared to agricultural GDP, total routine expenditure (i.e., spending at central level plus district level recurrent and development spending) amounts to only 1.2% to 1.7% of agricultural GDP. Furthermore, this proportion is declining because agriculture’s contribution to GDP is growing while public expenditure on agriculture stagnates. In addition, extension and technical services account for a substantial proportion of district spending. Table 2: Routine expenditure on agriculture and as a proportion of agriculture GDP 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual * Estimate Estimate Central recurrent routine expenditure 55,465 56,441 56,442 67,091 68,479 68,047 Districts—recurrent 37,098 48,365 58,652 Districts—development 69,631 56,227 34,909 Total (TSh million) 163,170 161,034 160,652 Agriculture GDP (TSh billion) 9,429 11,675 13,780 Recurrent routine expenditure as % of Agriculture GDP 1.7% 1.4% 1.2% Source: ASR-PER, 2015 (Budget Estimates for central level expenditure & PMO-RALG district spending). 37. Technology-enhancing expenditure is a significant component of the MAFC budget with expenditure on research, plant breeding, mechanization and irrigation services absorbing between 40% and 50% of the total expenditure excluding NFRA grants and input subsidies (Table 3). Nevertheless, technology- 26 ‘Special Expenditure’ is defined as grants to NFRA, spending on input subsidies, and transfers to other government agencies and international organizations. 20 Agricultural Sector Development Programme II (ASDP-II) enhancing expenditure is still very low and almost negligible (0.3%) in relation to the crops sector’s contribution to GDP. Table 3: Technology enhancing expenditure in MAFC (TSh million) 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual Approved Approved MAFC Personnel 16,953 18,490 21,659 25,167 26,328 27,169 MAFC Operation Charges excluding input subsidies 11,673 9,781 7,174 16,368 14,516 14,916 MAFC Transfers excluding NFRA grants 45,606 19,033 19,454 17,388 19,988 28,332 Total MAFC excluding input subsidies and NFRA grants 74,231 47,303 48,288 58,922 60,831 70,417 Of which technology enhancing 17,076 18,263 22,400 28,641 29,073 27,953 Technology enhancing as % of MAFC excluding input subsidies & NFRA grants 23.0% 38.6% 46.4% 48.6% 47.8% 39.7% Source: ASR-PER, March 2015 (based on Budget Estimates for various years). 38. With regard to the estimate of agricultural expenditure as a proportion of total government expenditure, the ASR-PER study was only able to determine ratios for recurrent expenditure. Due to lack of adequate and reliable data on spending by development partners, it was not possible to accurately estimate ratios for both capital and recurrent expenditure. The results of the ASR-PER analysis show that routine recurrent spending on agriculture amounts to around 2% of total recurrent spending by government. If expenditure on NFRA support and input subsidies are also included, spending on agriculture as a share of total recurrent expenditure ranged from 3.0% to 3.7% (excluding debt service) between 2010/11 to 2013/14 (Figure 9). The increase in the agricultural budget for 2013/14 is due entirely to increased spending on NFRA and input subsidies. Figure 9. Recurrent Agricultural Expenditure as Proportion of Total Recurrent Expenditure Source: ASR-PER, March 2015 39. Public expenditure on agriculture in Tanzania is therefore very low and, even if NFRA grants and input subsidies are included, agricultural spending as a proportion of total government budget is well below the target 10% envisaged in the 2003 Maputo Declaration. In addition, as a signatory of CAADP, Tanzania is expected to change both its investment pattern and meet some of the key principles of the programme, namely “pursuing an average of 6% annual agricultural sector growth at country level, and allocating 10% of the national budget to agricultural development”. To achieve these goals, a substantial increase in investments in sustainable agricultural development is therefore required, and it is anticipated that programmes such as ASDP II will provide a framework to facilitate rapid expansion of agricultural investment. 21 Agricultural Sector for Industrial Development 40. Revenue collection and budget execution (Table 4). In 2012/13 actual revenue collected amounted to 92% of the total estimate, while total recurrent expenditure was 95% of the planned budget. In 2013/14 the rates were even lower with revenue collection and budget execution achieving rates of only 88% and 87% respectively. With the exception of the MLFD execution rate for recurrent expenditure in 2013/14, the budget execution rates for MAFC and MLFD were generally lower than the overall execution rates. It should, however, be noted that the low budget execution rates for MAFC are highly influenced by the disbursement rate for NFRA grants and input subsidies which account for most MAFC recurrent spending. Execution rates for routine recurrent expenditure of MAFC are usually higher than the rates for special expenditure. Table 4: Revenue collection and budget execution rates Overall MAFC MLFD 2012/13 Domestic revenue 92% Recurrent expenditure 95% Agriculture Central Level: Recurrent expenditure 84% 80% Development expenditure: Local 41% 48% Foreign 97% 80% 2013/14 Domestic revenue 88% Recurrent expenditure 87% MAFC and MLFD: Recurrent 71% 90% Development 82% 40% Source: ASR-PER, March 2015 (from 4th Quarter Budget Execution Reports 2013 and 2014). Note: The 2013/14 Execution Report does not distinguish between domestic and foreign expenditure. 41. Development Expenditure. With regard to development expenditure, the ASR-PER (March 2015) noted that “records about development expenditure in the agricultural sector are utterly incomplete”. The two main sources of data are available: (i) government budget documentation; and (ii) the aid management platform, a database that donors supply with their respective information. 42. Overall, the coverage of development aid in the government budgets remains poor. Donors contribute substantial funds through development projects, but a significant proportion of expenditure is not recorded in government budgets as off-budget spending; Non-Governmental Organization (NGO) expenditure is also not captured. A list of agricultural projects and their respective donors are indicated in the budget book, but the list is not exhaustive and does not show annual expenditures. Based on available data, the on-budget development spending by international donors is presented in Figure 10: about TSh 183 billion was spent by donors in 2011/12, with ASDP and AFSP being the major contributors to development expenditure. In the past two years, on-budget spending by donors in the agriculture sector declined and, by 2014/15, it was estimated that development expenditure would be TSh 97 billion, considering that AFSP was terminated in 2013/14. With regard to local development expenditure within the agriculture sector, Figure 10 shows that only TSh 16 billion was spent in 2011/12, but this spending substantially increased in 2013/14 and was projected to rise to TSh 72 billion in 2014/15. Local development expenditure reflects the spending at central level and the contributions of LGAs towards agricultural development spending are not included, but remain limited. 22 Agricultural Sector Development Programme II (ASDP-II) Figure 10. Agriculture Development Expenditure by Project – Foreign and Local Source: ASR-PER, March 2015 (from Budget Estimates Vol. IV for 2013/14 and 2014/15) III. ASDP II-DESIGN PROCESS AND PRINCIPLES A. Lessons Learned from ASDP-1 43. Unlike other sectors, public investment in the agricultural sector does not direct produce the expected results, but rather facilitates the private sector (farmers and commercial partners) to achieve the expected targets. Several lessons and experiences have been drawn from the implementation of ASDP-1 (and other related programmes/projects) and will guide the design of ASDP II, including27: (i) the potential efficiency of a Sector Wide Approach (SWAp)28 in agriculture when sufficient leadership, commitment and well-resourced decentralization of agricultural development planning and implementation can be well anchored; (ii) results orientation of local and national development planning, implementation and M&E need to be strengthened to achieve sustained productivity growth—through technology adoption in value chains that offer competitiveness and most favourable market prospects; (iii) focus resources on high impact areas, which beyond productivity, also strengthen upstream levels of targeted value chains, such as market linkages and facilitating access to value addition facilities, involving strengthened farmer organizations and facilitation of their participation in marketing and value addition; (iv) sustainable irrigation development with robust planning and management systems throughout the cycle to aid 27 Adapted from ASDP-1 evaluation (June 2012) and other evaluations of other on- and off-budget agricultural sector support projects. Further elements are extracted from the ASDP Implementation Completion Report (Draft version early 2014). 28 IFAD Country Programme evaluation which recognized ‘reduced programme management costs as compared alternatives fielding separate projects and reduced transaction costs for the Government and development partners’ … allowing thus for a higher investment rate at farmer level. (Source: IFAD Country programme Evaluation Dec 2014 Unedited Final Version, p. 71). ASDP-1 also contributed to harmonized mechanisms and adhered to the principles of the Paris Declaration and the Accra Agenda for Action towards strengthened country ownership. 23 Agricultural Sector for Industrial Development appropriate infrastructure development, water resource management, professional and institutional management of the schemes and access to services and inputs; (v) champions at national and local level for adequate planning and funding mechanisms to promote private sector participation, supported by appropriate mechanisms; (vi) the design of the M&E framework should be based on national statistical surveys and the Agricultural Routine Data System (ARDS) enabled to produce timely information to measure programme achievements; (vii) improved access to seeds and fertilizers towards increased adoption rates and productivity and strengthened sustainability of productivity gains. 44. The following are some of the key lessons learned from ASDP-1 implementation over the last six years. The performance of the ASDP, though not without challenges, has shown that:29 a) A sector-wide approach in agriculture is possible where sufficient political and donor commitment is in place, and where a well-resourced decentralization policy is pursued on to which local level agricultural development planning and implementation can be attached. It also clearly demonstrated that successful implementation requires strong sector leadership at various levels and unwavering alignment of development aid to this approach. b) Thinly spread resources result in fragmented results/impacts, generally difficult to measure. ASDP was launched as a national programme covering all districts in Tanzania Mainland. Initially, one of the options considered was a phased implementation, covering a few districts at a time. In hindsight, because of the scale and complexity of implementing a new programme nationally, phasing may have been a better option. This would have allowed for better focus and complementarities between programme interventions, thus a better programme impact. c) Successful decentralization of agricultural sector support. The integration of the agricultural grants within the Local Government Development Grant (LGDG) and the decision to implement participatory district agricultural development plans (DADP) has been successful. The bottom-up planning processes has improved over time and has begun to provide a model for other sectors. Coordination between the then PMO-RALG and the ASLMs, and the efforts to conduct impartial annual assessments of the quality of DADPs has demonstrated that performance-based funding can be implemented using national planning and financing mechanisms. d) Increased productivity needs to be linked to value addition, marketing and increased farmer income. To date, ASDP-1 has focused mainly on basic production technology diffusion and processes. The lesson, based on field level studies, is that many farmers are already knowledgeable about basic production techniques, except perhaps for new crops and new practices that emerge periodically. What is lacking and gaining importance is focus on how farmers increase their incomes by engaging in more profitable activities including value addition and improved market efficiency. Generation and dissemination of basic technologies must be pursued together with greater consideration of supply chain linkages, especially expanded access to marketing. e) Little progress in farmer empowerment and organization strengthening. Creating and strengthening farmer organizations, or empowering farmers, is a topic covered in most projects and programmes, including ASDP. However, little qualitative or quantitative evidence exists of notable progress in this area, and thus achievement of limited progress in improving access to markets, as well as farmers’ productivity and incomes. In view of the focus on a value chain approach, this area deserves significantly higher levels of attention to overcome critical constraints along the value chain, through collective action. f) Lack of clarity about how the public sector should facilitate and enhance private sector involvement in the agricultural sector. Value chain development requires permanent consultation (from the design stage and on) and coordinated approaches with private sector actors (economic and associative) and with other international organizations. Coordination promotes joint efforts to develop private and public stakeholder involvement and cooperation, to enhance public capabilities for enabling strategic policy formulation and implementation. Furthermore, low participation of private agribusiness sector and private service providers (PSP) indicates the need for adequate planning and funding mechanisms at national and local level to support private sector involvement. 29 Adapted from: ASDP Evaluation June 2011 and follow-up studies on irrigation, extension etc.; ASDP ICR (Government report)—draft Jan 2014. 24 Agricultural Sector Development Programme II (ASDP-II) This should be done either within the ASDP II framework or through other emerging multi- donor initiatives, such as the Agricultural Marketing Development Trust or SAGCOT, etc. The involvement and capacity strengthening of private and associative (farmer organizations [FO], NGO and civil society organizations [CSO]) service providers would also allow for enhancing collaboration, alliances and increased efficiency30. g) Incomplete irrigation schemes and inadequate maintenance limit sustainability and farmers’ returns due to poor planning and management of irrigation development, inadequate resources and limited access to professional support services and productivity enhancing technologies. Irrigation is a major part of the ASDP-1 investment with about 112,500 ha upgraded and developed from 2006 to 2012 (18,920 ha per annum on average). Progress in this area has been significant and the capacity to implement larger investments has improved. Nevertheless, the irrigation schemes have encountered problems before, during and after construction and commissioning. These problems are documented and analysed, and lessons show that new investments need to be prioritized through feasibility studies to determine the most cost-effective irrigation infrastructure, area to be developed for irrigation and institutional organization and management of schemes. Most of the schemes supported by ASDP-1 were rehabilitation and improvement of existing schemes, but deferred maintenance, faulty designs and poor workmanship of irrigation schemes require corrections. Through careful planning and professional management, the prevailing vicious circle of build–deferred maintenance–rehabilitation can be broken. h) Harmonized sector M&E challenging to implement. The design of the ASDP M&E framework was based around costly national statistical surveys that were not timely in producing information about programme achievements. Equally, the planned annual services delivery surveys that would have given regular estimates of intermediate outcomes such as adoption of improved technologies were not implemented until 2008/9. In their absence, M&E reports were based on direct surveys of LGA authorities, and these have been incomplete and have contained inaccuracies. Finally, the set of short-list M&E indicators was modified over time and, while they reflect an active interest in regular results, the list now also fails to capture critical areas such as pace of empowerment, service reform and research outputs. There are several lessons to draw from the experience including: (i) the need to ensure that any national survey and ARDS has sufficient resources to provide necessary analysis and results on time; (ii) the importance of financing necessary planned annual surveys that provide critical annual performance assessments, for both outputs and outcomes; and (iii) above all the need to use M&E as a tool to track reform processes as well as measuring conventional benefits such as production and technology adoption. Overall, progress towards system alignment remained limited, while the broadening investment plan (TAFSIP) allowed for claiming policy/ strategic alignment. 45. Summary. The SWAp implemented through ASDP-1 appears as a strong case of effectiveness, impact and sustainability. The ASDP-1 Basket Fund was instrumental in setting in place a systems for delivery of infrastructure and extension services to smallholder farmers through LGAs, including for other stand-alone projects implemented. Interventions focusing on agricultural marketing and value chain development were hampered, constraining their effectiveness and efficiency and the sustainability of benefits. Furthermore, in recent years many donors and NGOs have supported several interventions in agricultural value chain development with the risk of inconsistent approaches and uncoordinated actions, which has limited their collective potential for rural transformation. There has been limited progress in supporting agricultural marketing and value chain development and the proliferation of uncoordinated activities in agricultural value chain development forms the risk of inconsistent approaches. Programmatic efficiency involves participative results-based programming and coordinated M&E systems to be streamlined into the agricultural sector statistics. Further investment in institutional capacity and methodology for enhancing outreach to farmers and other value chain stakeholders, and continuity and consistency in policies are key factors to ensure sustainability of results. 30 Adapted from IFAD-COSOP evaluation and analysis (Dec 2014). 25 Agricultural Sector for Industrial Development B. Key Agricultural System Challenges and Potential Drivers 46. Challenges and constraints to the implementation of ASDP II are summarized as follows: Table 5: Key constraints and thematic drivers Area Key constraints Thematic drivers Enablers - Poor implementation and coherence of existing policies - Inadequate coordination across agencies and weak links to regions and the local level - Inadequate data and data systems both for informing decisions and knowledge exchange - Inadequate infrastructure (crop and livestock production, energy, water, market access, etc.) - Inadequate land tenure systems, planning and enforcement - Weak link between public and private sector - Government to own, improve and effectively implement and monitor and evaluate appropriate policies Potential productivity - Ineffective national agricultural research systems and funding (insufficient personnel, qualification to respond to farmer needs) - Weak of adapted innovation products for farmers use (too generic and not farming systems and site-specific); - Weak links, mechanisms and mainstreaming of innovations between research–extension and stakeholders/implementers - Inadequate of improved genetics (livestock & fisheries) - Inadequate crop, livestock and fisheries research - Inadequate control of diseases and pests - Inadequate extension service equipment (transport, veterinary kits and services, extension kits) - Inadequate diagnostic capabilities (equipment and personnel) - High calf mortality rate for livestock due to tick and tick-borne diseases - Strengthen agricultural systems: • research and extension, and their linkages; • seeds, fertilizers, animal genetics and fingerlings • other input systems including mechanization • animal and plant health services • diagnostic laboratories (veterinary, etc.) Realized Produc-tivity - Inefficient seed and animal genetic systems - Inadequately staffed and capacitated extension systems - Low input use (fertilizer, seeds, machinery, feed fodder, vaccines, fingerlings, etc. - Inadequate rural platforms (Farmers Organization, Small and Medium Enterprises) to allow farmers to engage with governments and the private sector - Inadequate automated machinery for veterinary vaccine production - Inadequate development, use and monitoring of vaccines - Inadequate testing and quality monitoring of acaricides and other pesticides for vectors and pathogens control - strengthen the national livestock vaccine production - strengthen capabilities in testing and monitoring of acaricides and other pesticide Realized value - Huge post-harvest losses (25–35%, varying by crop and region) due to inadequate of agroprocessing expertise, facilities, storage and access to markets - Inadequate market information and research - low production indices for milk, meat and eggs - Low quality animals and animal products not able to compete on or access lucrative markets - Inadequate and weak enforcement of standards in food quality and safety. - Inadequate cooperative/union/farmer organization structures to ensure competitive pricing and reliable demand - Underdeveloped private sector, difficult regulatory system and weak market pull - Limited access to credit/finance and insurance - promote functioning input, output and credit markets - promote well functioning farmer organizations and cooperatives - strengthen enabling environment for private sector participation including promotion of PPP Cross-cutting: Gender, stakeholder improved governance, institutional capacity at various levels Adapted from BMGF (2014). 26 Agricultural Sector Development Programme II (ASDP-II) 47. Summary of Main Sectoral Constraints31 i. Inadequate policy environment and uneven policy implementation for achieving sustained and inclusive agricultural growth targets; ii. Low productivity levels and growth trends, including inadequate and sustainable access to key inputs (especially fertilizers and seeds, livestock genetic improvement (artificial insemination, embryo transfer), fingerlings, acaricides, vaccines and veterinary drugs); iii. Low genetic potential of the indigenous livestock and limited supply of improved breeds; iv. Weak delivery of agricultural support services for crops, livestock, fisheries, for improved technologies, crop and animal health services, regulatory services, etc.; v. Inadequate prioritized and quality public investments and low level of private sector investments in infrastructure (e.g., irrigation, rural roads, storage facilities, rural energy, market infrastructure); vi. Constraints to efficient and competitive agricultural marketing and agroprocessing, including limited value chain development; vii. Limited access to sustainable rural finance; viii. Inadequate land use planning allocation and secure tenure for land users; ix. Weak capacities to respond to climate change challenges; x. Weak institutional and human resource capacities and inadequate coordination among stakeholders, at national and local levels, including weak agricultural statistical system. 48. Strategic System “Drivers” for inclusive agricultural growth and reduced rural poverty32. To achieve the ASDS-2 goal, the programme objective for ASDP II will build on the lessons learned from ASDS-1 and ASDP-1 and focus on intensifying and operationalizing the following key drivers for sectoral growth transformation and rural poverty reduction: Policy and Regulatory Framework. Promoting effective multi-stakeholder formulation, consensus and effective implementation of key policy and regulatory reforms which can enable key productivity and value chain drivers of the sector transformation process. This process ensures expanded access to and efficient utilization of improved seeds, fertilizers, agrochemicals, vaccines, AI, fingerlings complying with sanitary and phytosanitary standards for ensuring competitive exports, marketing policies and regulations, enhanced value chain development, sustainable incentive structure for various actors, consistent with Tanzania’s market and competitive advantage. For the regulatory framework (legislation, institutional framework and human resources), the government is also working on, among others: (i) development of the conducive legal environment for strengthening farmers organizations and cooperatives societies; (ii) identification, demarcation and effective utilization of agricultural land; (iii) promotion of agricultural mechanization; (iv) facilitation contract farming for reliable markets; (v) price stabilization fund; and (vi) crop laws reforms. Production/Productivity and Trade. Increasing sustainable productivity of crop, livestock/fish and export commodities, would improve household nutrition and food security, but also marketable surplus. Increased competitiveness and farmer profitability will be enabled by: (i) sustainable productivity-enhancing technologies (including climate smart), facilitated through strengthened research–extension linkages; (ii) effective extension models using ICT; (iii) expanded and inclusive private sector role; (iv) sustainable access to rural financing; and (v) stronger and more effective farmer cooperatives and organizations which also would support and incentivize expanded marketed production, and value chain development. Inclusive Private Sector. Stimulating expanded and inclusive private sector-driven development and integration, facilitated by: (i) effective and viable public–private partnerships and public support services, and (ii) expanded rural infrastructure (especially small-scale irrigation, post- 31 The current ASDS-2 document includes a background subsection on a summarized SWOT for the agricultural sector. This assessment provides a rather homogeneous picture of the sector: an updated framework disaggregating constraint based on a typology of rural households would be most useful to further develop appropriate and differentiated strategies/measures. 32 To achieve inclusive agricultural growth and rural poverty reduction, relevant evidenced-based analyses need to be further sharpened and disaggregated, to better target specific farm household types, and/or agro-ecological zones articulated along key CVCs. 27 Agricultural Sector for Industrial Development harvest facilities veterinary infrastructure, storage facilities and rural feeder roads). This would contribute also to much needed expanded off-farm employment opportunities. Institutional Capacities and Coordination. Strengthening institutional development and effectiveness, including: (i) results-focused capacity development of key actors at national and local levels; (ii) more efficient, responsive transparent and accountable decentralization of key agricultural services and implementation; (iii) more effective and evidenced-based planning, budgetary and M&E systems at various levels, involving all stakeholders; (iv) enhanced nutrition and food security support services; and (v) enhanced processes and mechanisms for more effective coordination within ASLMs, other sector ministries/agencies, Development Partners, local government agencies/entities, private sector and other key stakeholders (including farmer and other commodity value chain organizations). C. The Process Towards ASDP II 49. Implementation of ASDP-1 has benefited from regular joint reviews that have led to a better understanding of the challenges as well as the strengths and weaknesses in the programme design and implementation performance. The annual Joint Implementation Reviews (JIR) involving ASLMs, development partners, agribusinesses, LGA representatives and farmer representatives at local and national levels have been used to track implementation progress and achievement of the programme objectives. This has allowed for timely removal of implementation bottlenecks and adapted programme adjustments. Information from regular contact between the supervising authorities and those responsible for the implementation is compiled by the ASDP Secretariat and PMO-RALG and this has informed design of ASDP II. Efforts have been made to incorporate the lessons learned in ASDP II design and to address the challenges encountered during implementation to avoid similar setbacks and impediments. ASDP evaluation carried out in 2011, the ASDP-1 Implementation Completion report (2014) and related studies and analysis were extensively used. Most of the reviews have made recommendations and elaborated ways to improve the relevance and effectiveness of the various interventions, as well as processes, procedures, guidelines used in the day-to-day implementation33. 33 Evaluation of the Performance and Achievement of the Agricultural Sector Development Programme, MAFC, 2011. 28 Agricultural Sector Development Programme II (ASDP-II) Figure 11: Tanzania landscape for agricultural development (2015–2024) Agric productivity & rural commercialization Irrigation, sustainable water & Land Use Management ASDS - 2 ASDP - II Examples of implementing initiatives Basket Fund AGRIC. SECTOR. DEVELOP. STRATEGY Sustainable Water and Land Use Management (NRM) Strengthening Sector Enablers at national, regional & local level Bread Basket Initiative NGO & Other initiatives Rural infrastructure, market access & trade Private sector development Food and nutrition security Disaster magmt, climate change and adaptation Policy & institutional reform & support Marketing infrastructure, Value Add & RuralFin. Support Prgm SAGCOT Commercialization and Value Addition (buil competitive CVC) Enhanced Agricultural Productivity and profitability ASDP II PROGRAMME/FRAMEWORK ASDS 2 KILIMO KWANZA TAFSIP Thematic Program Areas 50. Over the past years, extensive consultations were held with government officials, private sector representatives, civil society representatives, development partners and LGAs, to understand what worked and what did not work in the course of implementation. The overall ASDP-II framework encompasses all public funded (public good funded by the government, development partners and NGOs) activities in the agriculture sector, implemented under the guidance of the updated sector strategies (ASDS-II), taking into account relevant aspects of the TAFSIP framework. 51. The Basket Fund approach appeared rather challenging during ASDP-1; the clear separation of programm support from financing modalities encouraged most donors to earmark their contributions to specific activities. Although Basket Fund financing remains the preferred government financing modality, current non-earmarked contributions to a large extent originate from the Government of Tanzania, while all main donors have earmarked large parts of their on- and off-budget contributions. Earmarking appears to be a non-viable solution for financing core sector-wide functions within a harmonized and aligned investment programme, including coordination and M&E. 52. ASDP II is a results-oriented sector programme for public support delivery. It serves as not only the main vehicle for the implementation of the sector strategy (ASDS II), but also sub-sector policies and development programmes (crops, livestock, marketing, food security and nutrition, private sector, etc.). The formulation framework (Figure 12) and its financing modalities (Figure 13) include key elements, such as: (i) orientation towards leveraging and catalysing inclusive private investment; (ii) close coordination between public-private-partnership in areas of high potential (SAGCOT) , as pilots that can be up-scaled in the framework as a whole; (iii) strengthened sector coordination (common planning and budgeting, joint monitoring and evaluation) for increased accountability of all actors, at national and local levels; and (iv) integrating different aid modalities and progressively aligning planning and implementation, and M&E procedures to strengthened country systems. 29 Agricultural Sector for Industrial Development Figure 12: ASDP-II design and formulation framework. ASDP II - Design Framework PDO: Increase agricultural productivity and incomes of smallholder farmers for priority commodity chains Agri-business and Farmer linkage • Processors • Traders/Exporters/transporters • Enterprise development support • Private Sector Capacity Development Support • MIS • Quality management and certification Institutions/Regulations/ Laws • Land laws/tax regimes • Legislations and regulations • FO empowerment & capacity development • Entrepreneurial, business and management skill • Financial Service Market Infrastructure • Roads • Electric Connection • Irrigation • Warehouse Agr. technology and Advisory Services • New and improved varieties/breeds • Improved practices • Farm machinery • Agro processing technology • Knowlegde/Technical Skill transfer, Advisory Services • Inputs • Post harvest management Smallholder Agriculture Commercialization Figure 13: ASDP-II financing modalities 53. The key role of the ASLMs, led by Ministry of Agriculture , is to promote coordination and harmonization across all development and cooperating partners investments in the sector, to provide a viable pathway out of poverty for the nation’s millions of small‐scale farmers, and to facilitate the road towards improved sector harmonization and alignment of partners to drive equitable growth in a sound and common framework. Including by stimulating inclusive private sector role and investments (including public–private partnerships—PPPs)34. 34 The concept of PPP in productive sector and socio-economic services entails an arrangement between the public and private sector entities whereby the private entity renovates, constructs, operates, maintains, and/or manages a facility in whole or in part, in accordance with specified output specifications. The private entity assumes the associated risks for a significant period of time and in return, receives benefits and financial remuneration according to agreed terms (PPP, 2009). 30 Agricultural Sector Development Programme II (ASDP-II) D. Key Design Principles for ASDP II 54. Consistent within the key features of ASDS-2, the following principles underline the design of the ASDP II programme. Box 1: Key Principles of the ASDP II Design Key principles of the ASDP II design • Priority focus on commercialization of sustainable small-scale farmers production systems by market orientation; • Priority focus on high potential Commodity Value chains(CVCs) in Agro-Ecological Zones (AEZ) - implement investments and commodities that create the greatest impact -agricultural yields, profitability, farmer improved livelihood, commercialization and industrialization • Enhanced involvement of all stakeholders, including farmer organizations and the private sector at all levels for enhanced partnerships and increased ownerships. This includes increased control of public resources by all CVC stakeholders at all levels for improved relevance and efficiency; • Farmer and local CVC stakeholders’ empowerment by capacity strengthening, organization strengthening • Pluralism in service provision: ASDP aims to provide a wider choice in service providers to increase cost-effectiveness, competition responsiveness of services (de-linking of public funding from service delivery). • Results-based resource transfers. Resource allocations to LGAs will be more transparent and equitable through adopting and extending the local government grant system. The incentive for LGAs to use their funds effectively will be promoted through annual assessments. However, all LGAs will be eligible to qualify for basic additional support especially to strengthen operational and capacity building funding to demonstrate adequate performance and capacity to join investment flows • Focused support to enhance private investments and public–private partnerships (PPPs) under control of CVC MSIPs: propose matching grants/contributions based on performance scorecards and agreed priority areas. • Integration with government systems: existing government financing and planning systems (the Medium-Term Expenditure Framework (MTEF), DADP, grant transfers) will be used and through increasing integration will build sustainability, strengthen alignment with government priorities and avoid unharmonized, project-based approaches with parallel implementation mechanisms. 55. The second phase of the government’s 10-year ASDP programme (2017/2018–2027/2028) addresses the challenges and gaps experienced in ASDP-1. The aim of ASDP II is to address critical constraints and challenges to sector performance and to speed up agriculture GDP, improve growth of smallholder incomes and ensure food security by 2025. The programme builds on and strengthens successful investments under ASDP-1, Consistent with the long-term and medium-term policy frameworks, the sector development strategy developed in ASDS-1 (2001), the signed sector investment plan (TAFSIP, 2011), the revised ASDS-II (2015) and key lessons learned from ASDP-1 implementation, the following key principles were taken into account and streamlined into the design of the ASDP II programme. 56. The ASDP II design reinforces smallholder commercialization focus with the view to support farmers to graduate from subsistence farming to semi-subsistence/semi-commercial status, practising farming as a business. This recognizes that food security is a necessary condition for escaping poverty, but it is not sufficient—household cash incomes must also increase from their currently very low levels. Smallholder farmers have to begin producing for the market and be supported to forge strong and dynamic linkages with commercial input and output supply chains in order to connect with a growing agro-industrial sector and expanding food demand from urban consumers. Whilst the focus will be clearly on the smallholder sub-sector, greater inclusive private sector participation will also be 31 Agricultural Sector for Industrial Development encouraged, both in commercial agricultural production and in marketing, agroprocessing and farm input supply chains. Investment in rural roads/infrastructure, agroprocessing, especially in grain milling and packaging and sustainable utilization of natural resources will get special attention to expand the market, especially for priority crops. 57. Results-based focused support. Based on lessons learned from ASDP-1, key innovations integrated in ASDP II include, among others, impact orientation and concentration of resources on high potential CVC within agro-ecological zones and selected districts to achieve results, and scale-up. While targeting market-oriented smallholders35, a phased approach is being proposed to build and consolidate impact. A phased approach is being proposed by building and consolidating impact on priority CVC in a limited number of districts (clusters) before gradual scaling up of support activities, based on various milestones and performance indicators. Districts not covered in the first phase will be covered in subsequent phases and therefore growth-inducing interventions will reach all regions and districts over time. 58. Productivity increase for sustainable national food security and nutrition, farmer income and economic growth. ASDP II addresses the challenge of food deficit areas by promoting surplus food production and quality (crops, livestock and fish) in districts that have the potential to do so. Food deficit or low potential areas will benefit from the surplus generated from selected priority districts (see complementary government interventions, including social safety nets), enabled by enhanced marketing policies and private sector marketing. The focus of the programme is to maximize food self-sufficiency, but also export of commodities for which Tanzania has a comparative advantage in regional and international markets. Priority is given to investments focusing on expansion of irrigation, development of rangelands, control of livestock diseases, aquaculture development, mechanization, research and development, access to improved agricultural technologies and related inputs and appropriate support services. 59. Increasing management of resources by beneficiaries. The ASDP-1 stressed the importance of increasing the voice of farmers/fishers in local planning and implementation processes and in increasing their decision-making and management control in the design and implementation of investments, and over the kinds of services that they need. Although some progress has been made in this regard, much remains to be done and ASDP II reinforces this principle through a more structured planning, implementation and M&E arrangements and supporting financing mechanisms. The ASDP II places greater decision-making control over resource allocations in the hands of farmer groups, cooperatives and agribusinesses based on transparent processes. 60. Pluralism in service provision. A further analysis of the lessons learned from ASDP-1 and experiences in neighbouring countries would be useful to develop and implement a clear strategy for the promotion of private and associative (FO, CSO, NGOs) service providers at different levels of targeted activities. ASDP II aims to push for a wider choice in service providers to broaden knowledge support by integrating agribusiness services delivered by the PSPs. Performance-based contracts for private agribusiness advisory service provision will enable linking of public funding from service delivery and complementing public technical services implemented by local government services. 61. Sustainability and diversification. ASDS II emphasizes the need to diversify crop and livestock production to increase farm incomes and to reduce risks in light of both production and price fluctuations. Under ASDP II, there will be a commodity focus, but intertwined with strategic diversification. While focusing on priority CVC, crop rotations and promoting intensive animal husbandry systems to use efficiently crop residues, sustainable soil and water management systems and efficient use of irrigation systems will be promoted. Appropriate processes and mechanisms will be introduced and strengthened to achieve market-driven diversification and sustainability. The expansion in irrigated agriculture opens up an opportunity for crop intensification, one of which could be diversification into high value crops, such as horticulture. Focus will also be directed towards developing livestock diseases free zones, improve water availability for livestock, improving access to grazing lands, improvement of genetic potential 35 Support for and disadvantaged/vulnerable farmers is important and should be considered under alternative safety- net supports. 32 Agricultural Sector Development Programme II (ASDP-II) of the existing stock, increasing supply of improved stock, commercialization of the livestock industry and aquaculture and fisheries development. ASDP II will, therefore, encourage such diversification with the aim of increasing and diversifying farm incomes, to use natural resources, including water, more efficiently and meeting increasing local and export market demands. 62. Food and nutrition security. Although ASDP II focuses on a limited number of CVCs, nutrition remains an area of concern, as little progress has been recorded on nutritional status over the past decade, especially in rural areas. In complementing specialized support programmes, ASDP II will contribute to improved rural nutrition mainly by: (i) agricultural research, especially breeding for high quality and food safety, although for proposed priority value chains, the scope remains relatively limited (e.g., quality protein maize, enriched rice varieties, beef and dairy breeds (meat, milk) and fish); (ii) support participative advisory services (e.g., Farmer Field Schools (FFSs)) combined with farmer education and access to information (at ward resource centres and village level and intensive use of Information and Communication Technology (ICT) for information diffusion); (iii) expanded access to seed diversification (including horticultural seeds, livestock breeds, fingerlings) through strengthened agrodealer networks and competition, supported by appropriate regulation; and (iv) food processing for improved nutritive quality in the value addition part of the value chain. The programme has built- in flexibility to accommodate interventions to improve the nutritional status of rural households and protect them from the impact of natural disasters, along with improving the capacity of institutions that provide services for sustainable productivity growth and quality. 63. Gender and youth mainstreaming. While it is recognized that gender and youth is a cross-cutting area, which needs to be addressed at all levels, sectors, and in both technical and management areas, the ASDP II contributes its share by undertaking both socio-economic36 and gender/youth analysis. The strategy will also ensure these issues are adequately covered in the design and implementation of programme interventions and activities. This will be done by ensuring that gender and youth mainstreaming is operationalized in all ASDP II interventions. The tools for achieving this are at the strategic level (the gender/youth strategy), and at the operational level (the activity plans of each district), or implementing entity, which will outline what systems and processes will be targeted and how. Differentiation of groups by wealth, vulnerability, age and possibly other socio-economic characteristics is required to ensure that more vulnerable groups also benefit from the program. Based on the analysis and content of mainstreamed gender and youth activities, ASDP II will ensure adequate support, and explore synergies by collaborating with other projects and programmes. 64. Resilience, including to climate variability and change. ASDP II interventions will be undertaken with climate change considerations factored into the interventions, including climate smart agriculture in sustainable landscapes and appropriate climate change mitigation strategies. Extremes in temperature and precipitation will be the focus of research and technology development, since climate change tends to manifest itself in these forms most of the time. Farmers’ adaptive capacities will be strengthened to ensure the impact is understood and integrated into their farming systems/activities. A menu of response options to mitigate the impact of climate change on agriculture, including conservation37 agriculture, will be developed, tested and shared. Capacity building programmes for FFSs, extension officers and subject matter specialists on current climate related issues will be developed, implemented and periodically updated. E. Scope, Focus and Phasing of the Programme 65. The scope and focus of the programme under ASDP-1 was national wide and interventions were in almost all agricultural sub-sectors and scales, depending on LGA prioritization and investment decisions. 36 Differentiation of groups by wealth, vulnerability, age and possibly other socio-economic characteristics is required to ensure that more vulnerable groups also benefit and are provided with adapted support. However, the main target of ASDP II is to promote the gradual marketing capacities of the small-scale commercial farmers (SCF), while most vulnerable farmers (i.e., those who are unable to be auto-sufficient) need to benefit from safety net like support (TASAF and similar). 37 See also ‘Save and grow’. FAO 2012. 33 Agricultural Sector for Industrial Development Under the ASDP II, the intervention will cover all districts in terms of public service delivery (basic support for capacity building, demand-driven advisory services, etc.), The investment coverage will focus on selected priority commodities in agro-ecological zones. Focusing of investments will increase the likely contributions of planned investments to agricultural growth, import substitution and food security and nutrition. The reasons for moving in the direction of both commodity and area/zones specific interventions are to: (i) increase sustainably the productivity and competitiveness of the priority CVC production systems; (ii) increase the volume and value of produce that enter the market channels for both domestic and export markets, and reliable raw material supply for local industries; (iii) allow for significant impact of investments, especially in infrastructure and other interventions in priority areas; (iv) finish/complete priority investments started under ASDP-1 (especially irrigation and other value addition and marketing infrastructures); (v) enhance economies of scale by improved access of commodity producers’ to agricultural inputs and financial services, and lower transaction costs for input/ output supply chains, as volumes and competition increase; and (vi) promote expanded investments by private sector, at farm and off-farm levels, especially in priority value chains. 66. Institutional capacity strengthening. The programme will focus on: (i) empowering and strengthening small-scale farmer organizations, towards enabling farming as a business; (ii) supporting agribusinesses linked and integrated with farmer production systems for markets and value chain development; (iii) strengthened public and private support services for enhanced use of improved technologies and agribusiness; (iv) development of markets (policies and infrastructure) and productive infrastructure; and (v) institutional capacity building, at various levels, for state and non-state actors. 67. Priority commodity selection. Using38 contributions to national food security, the food import bill and export revenues, and contributions to the value of agricultural production as criteria, few commodities emerged as critical for economic growth and poverty reduction. In terms of contribution to kilocalories of food intake by Tanzanians, maize, cassava, rice and pulses contribute about 53%. In the area of agricultural trade, tobacco (17.6%), cotton (14.5%) and coffee (14.1%) contribute about 46% of the export value. Wheat (31.4%) and palm oil (27.3%) form the main share of total food import value as shown in table 6. Table 6: Commodities coverage, agricultural production, trade and diet (2005–2010) Commodity Share of production value Share of export value Share of import value Share of kcal intake* Cashew nuts 1.2 6.7 0.0 0.2 Coffee 0.8 14.1 0.0 0.0 Cow milk 7.3 0.0 0.6 2.6 Maize 6.5 0.8 2.9 24.3 Pulses 10.6 7.5 0.7 8.5 Rice 5.2 n.d. n.d. 9.1 Cotton 2.9 14.5 0.1 n.a. Sugar 1.2 1.6 8.6 4.0 Wheat 0.2 1.4 31.4 5.9 Cassava 8.2 0.0 0.0 10.5 Livestock 12.0 d 0.1 d 0.6 1.6 Sorghum/millet 2.4 0.1 0.2 3.8 Tea 0.5 6.3 0.0 0.0 Bananas 12.7 0.0 0.0 4.0 Palm oil 0.0 1.6 27.3 3.3 Tobacco 1.3 17.6 1.1 n.a. Source: MAFAP (2013). Review of food and agricultural policies in the United Republic of Tanzania. MAFAP Country Report Series, FAO, Rome, Italy, p 62. 38 Based on a recent FAO study (MAFAF/SPAAA, 2013). 34 Agricultural Sector Development Programme II (ASDP-II) 68. In addition to the above criteria, by applying criteria of possibility for commercialization, availability of technology for improving productivity and profitability, and possibilities for scaling up and scaling out, the list of commodities that make up the priority list narrows down to a few. Table 7: Priority commodities in the AEZs39 & potential commodities phasing by region40 Agro- Ecological zone (old2 zones) Priority commodities Nutritionb Market density Donor density Crops Livestock &fish Cash crops Centre Semi &arid-(Unimodal)- (Dodoma, Singida, Shinyanga, Tabora) Sunflower/maize/ sorghum/millet, rice, potatoes, horticulture3 Meat—beef, hides/skin, dairy, goat, Poultry, fish Cotton, Tobbaco Worst Moderate Moderate Lake (Unimodal/ bimodal) – (Mwanza, Kagera, Mara, Shinyanga, Geita, Simiyu) Rice, maize, cassava, banana, potatoes, sorghum/ millet, horticulture Meat—beef, hides/skin, dairy, goat, poultry, fish Cotton, Coffee, sugar cane OK Good Low- Moderate. Northern Highland(Bimodal) – (Arusha, Kilimanjaro, Manyara) Maize, rice, pulses/ beans, potatoes, horticulture, banana Meat—beef, hides/skin, dairy, goat, poultry, fish/ aquaculture Coffee, Wheat Worst Good Moderate. Eastern Coast-(Unimodal/ bimodal)- Tanga, Dar es Salaam, Pwani, Mtwara, Lindi) Cassava, rice, maize, potatoes, oil seeds4, horticulture Dairy, beef, fish, poultry, goat, skin/hides Cashew, Sugar cane, seaweed, sisal OK - Worst Moderate. Moderate- High Alluvial Plains (floods, swamp)- Morogoro (Kilombero, Wami),Pwani (Rufiji coast),Mbeya( Usangu) Rice Sugar cane Good Moderate- High West-SW Highland(Bimodal) Rukwa, Kigoma, Kagera(Karagwe, Misenyi,Ngara) Maize, Horticulture, banana, pulses, potatoes, rice Poultry, beef, dairy, goat, fish Coffee, wheat, sugar cane OK Bad None Low Southern Highland (Bimodal) Mbeya, Iringa, Njombe, Morogoro Maize, Rice, potatoes, Horticulture Meat—beef, goat poultry, dairy, fish Coffee, sisal, Cocoa, Tea Worse Good High Plateaux (Unimodal) Tabora, West Rukwa/ Katavi, Mbeya, North Ruvuma, Morogoro, South Mwanza,Simiyu,Geita South Semi-arid Lindi, Mtwara Coast Cassava, rice Goats, poultry, fish Cashew, seaweed Worse Bad Low a Horticulture41 promotion for household nutrition and market supply forms a diversification option in most irrigated areas, but also as small-scale counter-season activity. b Nutrition, market and donor density: Results from overall Meta-analysis (BMGF, 2014) c Total number of households for 2014 calculated on the basis of the demographic data provided in the 2012 national socio-economic profile (2012): about 70% of households are rural and an average HH size is about 5. 39 Based on geographical position 40 Oil seed crop includes sunflower, simsim, palm oil, coconut, groundnuts 41 Horticulture includes vegetable, fruit and spice crops 35 Agricultural Sector for Industrial Development Table 8: Priority Commodity Value Chains in Agro-Ecological Zones/ clusters Agro- Ecological Zone Regions Targeted HHs Priority commodities Crops Livestock & Fish Cash Crops Central 715,000 (8%) Maize Tobbaco Meat : Beef Meat: Goat Oil crops Sorghum &Millet Poultry Horticulture Coastal 2,300,000 (25%) Rice Dairy Cashew Maize Meat: Beef Sugar cane Cassava Fish Oil crops Beans Sea weeds Horticulture Lake 2,100,000 Rice Meat: Beef Cotton Coffee (23%) Northern Highlands 1,035,000 (11%) Maize Dairy Coffee Meat: Beef Horticulture Banana South 570,000 (6%) Cassava Meat: Goats Cashew Oil crops Maize Poultry Fish Southern Highlands 2,395,000 (26%) Dairy Maize Cassava Sugar cane Horticulture and Banana Meat- Goat Fish Legumes & Pulses: Beans Fish Meat: Beef Poultry Tea/ coffee Horticulture Sugar cane Maize Potatoes (Irish and sweet) Rice 36 Agricultural Sector Development Programme II (ASDP-II) 69. ASDP II implementation of prioritized investments and commodities under AEZ. ASDP II implementation approach will be a “one- priority crop/product – one AEZ”. Regions will be “clustered” 42 so that service provision and technological recommendations can be channelled to similar production systems and rural household types43. Public service delivery interventions will cover all districts and will be supported by other programmes and projects that are funded by various multilateral agencies, bilateral donors and NGOs. District coordination mechanisms established by ASDP II using DADP will improve local coordination among all sector interventions, including private sector. 70. AEZ/ Cluster Selection Criteria. Selection of the AEZ/ clusters considered five criteria starting with the zone’s production level and importance. Selection considered high production of prioritized value chains, as a percent of national production. The selection also looked at the potential market demand for raw and processed products within the region and zone. Other criteria include the processing level/ existing processing capacity within the zone, Sustainable systems or contribution to sustainable local production systems, to household food security and income generation and potential growth - for productivity and value addition improvements, including local agribusiness development and increased agricultural exports. 71. Commodity value chain selection criteria. The selection considered the value chain’s contribution to food security and nutrition, impact to smallholder farmers/livelihood improvement, cost effectiveness/ financial redness, on-going projects to be completed first, contribution to the national development agenda (industrialization)- five years’ development plan (phase II) and local market and exportation potential. F. Priority setting and Focusing 72. Approach. For the purpose of focusing on required services in upstream and downstream production, production clusters will be established for selected strategic commodities as growth poles within each AEZ. Tables 7 and 8 illustrate the potential AEZ and related districts’ and regions’ priority commodities: the choice of commodities will be revisited with all local value chain stakeholders at the start and during the mid-term review of the programme. The cluster approach enhances delivery of essential services, exploitation of economies of scale, development of required infrastructure, bulking of produce, agroprocessing and reduction of transaction costs. A commodity cluster will be a coherent area comprising districts with a proven potential for that specific commodity as well as the presence of value chain actors (e.g., producers, traders, processors and service providers) meeting in a Multi-Stakeholder Innovation Platform (MSIP), and availability of basic market infrastructure. The programme will target maize, rice, sorghum and millet, cassava, horticultural crops, oil seed crops, cotton, coffee, sugarcane, cashewnuts, tea, potatoes, pulses, fish, dairy, beef, goat and sheep, poultry, banana, and seaweed, all strategic commodities or food security, import substitution and /or for export to the regional markets. 73. The selection of the content focuses on an adapted Opportunities and Obstacles to Development process used for many years in ASDP-1 and familiar to the LGAs for local-level investments. Through a value- chain approach, the programme will support access to and utilization of yield enhancing technologies (improved seeds, fertilizers, mechanization and water crop, livestock and fish production) as well as infrastructure and agribusiness services for marketing and value addition. The capacity of private sector actors, including farmer organizations and cooperatives, will be strengthened to improve stakeholder access to the required inputs, agroprocessing and marketing services. Supporting efficient and integrated input use to complement enhanced research and advisory services is a cost-effective response for increased productivity and farm income and preventing unsustainable subsidies. Broader access to adapted varieties and seeds, integrated soil fertility management and timely land preparation will also help farmers move towards sustainable agriculture and overcome risks, including those induced by climate variability and change. Gradual adoption of appropriate mechanization technologies for 42 See further details in attachment 1 for operationalization of cluster approach 43 See also typology of rural households. 37 Agricultural Sector for Industrial Development production and post-harvest operations will not only increase rural labour productivity, but also attract young entrepreneurs in the sector. 74. Phasing in and out concept/approach. The programme will focus on the priority investment areas for key CVCs in AEZs considering selected priority crop, livestock and fish commodities. Based on gained experience, support will be expanded from mid-term on to gradually cover high potential CVCs in three to six districts (cluster) selected in each AEZ, on the basis of criteria such as: (i) agricultural production potential for target commodities; (ii) productivity and production levels of target crops, livestock and fish by category; (iii) access to productive and marketing infrastructures (road, railways, electricity44 etc.); (iv) annual performance assessment of district investments; (v) historical background of beneficiaries contribution/involvement in development initiatives; (vi) availability of private sector supporting target CVC(s); and (vii) other ongoing initiatives (projects such as FTF, MIVARF, MUVI, AFSIP) in the areas to avoid duplication and maximize synergies. G. Approaches and principles for the ASDP II design. 75. ASDS-2 and lessons learned from ASDP-1 form the main building blocks for ASDP II. Seven proposed ASDS-2 Strategic Result Areas were mapped within four programme areas for the agricultural sector (crops, livestock and fish) development programme (ASDP II), as shown in Table 8. Table 9: ASDS-2 Strategic Result Areas & mapping of proposed priority programme areas ASDS-2. Strategic Result Areas ASDP II. Priority programme areas (or SO) . Expanded Sustainable Water and Land Use management for crops, livestock and fish & system resilience to climate change; irrigation expanded). P1: Sustainable Water and land use management for crops, livestock and fish & system resilience to climate change. SO2. Improved Agricultural Productivity and Profitability (crop, livestock and fish, through research, extension, access to input, and mechanization) P2. Enhanced agricultural productivity and profitability (crop, livestock and fish), food and Nutrition security improved SO3. Strengthened and Promote Competitive Value Chain (farmers organizations empowered; agribusiness and value addition promoted; access to markets and rural infrastructure improved) P3. Commercialization and value addition (market access, value addition, trade & private sector development) SO4. Strengthened Institutions, enablers and coordination framework (policy, regulatory and institutional framework enhanced; institutional capacity, knowledge management and ICT strengthened; food and nutrition security, and safety net improved; sector coordination improved; M&E and agricultural statistics strengthened) P4. Strengthening sector enablers (including policies,, CKM, ICT, Coordination and M&E) Promote & strengthen gender inclusiveness in the agricultural sector. 76. ASDS-2 Strategic Objectives are defined as: (SO1) Expand sustainable water and land resource management (for crops, livestock and fisheries) and promotion of climate change smart agriculture; (SO2) Improve agricultural productivity and profitability driven by improved research, extension, input access and mechanization; (SO3) Strengthen and promote competitive value chain development in the agricultural sector (crops, livestock, fisheries), driven by empowered farmers organization, improved value addition and enhance access to markets, finance and rural infrastructure; and (SO4) Strengthen institutional performance, enablers (policy and regulatory framework) and effective coordination of public and private sector institutions in the agriculture sector at national and local levels. 77. All expected ASDS-2 outcomes have been reorganized along the proposed four programme areas and further enriched by team and inception workshop discussions. Cross-cutting and cross-sector elements were also included, such as: (i) gender, balanced and equitable participation of men and women in 44 Rural electrification is still very low as household lighting and cooking by electricity are only 20.7% and 1.7% respectively (Population and housing Census 2012). 38 Agricultural Sector Development Programme II (ASDP-II) agricultural development; (ii) rural youth self-employment; (iii) HIV/AIDS, to reduce the spread and mitigate its impact; and (iv) improved governance and accountability. 78. Major public investment/support areas across proposed components were identified as: (i) research; (ii) extension/training, information services and knowledge management; (ii) farmer/stakeholder organizations; (iii) access to inputs; (iv) rural infrastructures; (v) access to rural financing; (vi) policy and regulatory framework; and (vii) coordination and M&E. Using this double-entry framework, public (ASLM departments) and non-governmental stakeholders identified priority investment/support actions (group of activities) enabling achievement of expected outcomes of proposed PAs, at each the national and local level (including intermediate regional level to accommodate coordination requirements). 79. Based on extensive discussions with key public and private sector stakeholders and ‘practicalities’ the ASDP II sector programme was structured around four components: (P1) Sustainable water and land use management (crops livestock and fisheries); (P2) Enhanced agricultural productivity and profitability; (P3) Commercialization and value addition (building competitive value chains); and (iv) Strengthening sector enablers and coordination (at national, regional and local levels). The main changes against former Ps were to add a component for strengthening sector enablers (policies, food security and nutrition, capacity strengthening, coordination and M&E). 80. Priority actions were discussed and consolidated, and related budgets were estimated and compared to current on-budget recurrent and development investments, mainly at national level. Bulk estimates for local level DADP investments were consolidated. Although large parts of proposals were promoting increased investments in ongoing actions, Ministry of Agriculture departments identified priority investment areas considered as key drivers for the agricultural sector growth and rural poverty reduction. These key drivers for ASDP II implementation (and priority changes against ASDP-1) are summarized as follows: a. Committed leadership and changed mind-set at all levels will enhance program delivery. b. Sector-wide coordination (results-oriented sector-wide planning, implementing and M&E) including all ‘public good’ programme and projects in the agricultural sector: (i) at national level, efficient coordination within ASLMs and between government systems and other sector support programmes and projects; and (ii) at local level initiatives, through participatory planning/implementation systems, capacity building and focused investments; c. Focus of local investments targeting prioritized commodity value chains (CVCs) with improved balance between sub-sectors in line with their comparative advantage in each AEZ and focused supports to district clusters, with gradual out- and up-scaling (prioritization criteria) and phasing to be defined. ASDP II will gradually increase investments at local level. This will be based on the principles of: (i) maintaining participatory planning/implementation systems and strengthening human capacities; (ii) implementing irrigation investments (under the District Irrigation Development Fund) already identified to a large extent for the next five years under ASDP II and completing ASDP-1 started schemes; (iii) enhancing investments in availing water for livestock and aquaculture farming45; and (iv) implementing focused DADPs investments around priority CVCs in selected clusters with gradual upscaling. For livestock, targeted beef and/or dairy priorities require further use of quality breeds adapted to key production systems, including agro-pastoralism, pastoralism or tethering. High productivity will also depend on other factors such as diseases control, which requires strengthening of diseases detection capacities (veterinary laboratory diagnostic services) and access to vaccines (Tanzania Vaccine Institute -TVI). d. Key thematic investment areas identified as main sector drivers and benefiting from a higher growth of budget support, including: (i) irrigation—remains a priority as also identified in ASDP II; (ii) 45 For livestock and fish development, the LSDP (2011) identified the following priorities: (i) livestock infrastructure; (ii) grazing-land development for forage and water for livestock; (iii) production of pasture seeds and fodder trees; (iv) livestock research, training and extension services; (v) genetic improvement of cattle and chicken; (vi) animal diseases control and establishment of animal disease free zones to facilitate international trade; (vii) availability and utilization of inputs/implements for livestock; (viii) conducive environment for private sector investment in livestock; and (ix) livestock statistics and marketing information system. 39 Agricultural Sector for Industrial Development research–extension linkages, including zonal/district driven adaptive research and AR4D liaison units; (iii) farmers access to enhanced technical knowledge (improved technologies) expanded private sector- driven input distribution networks (seeds/breeds/fingerlings, fertilizer, feeds, vet drugs and vaccines, etc.); (iv) expanded access to competitive mechanization services for production and post-harvest processing/ value addition; (v) reduction of post-harvest losses for crops and livestock (calf mortality); (vi) providing specialized private sector-driven agribusiness support services at regional/zonal level; and (vii) detection capacities vectors/pests/pathogens and access to quality vaccines. e. Use of modern information and communication technologies for efficient coordination, data collection, processing, dissemination, but also stakeholders access to up/downwards information demand and supply flows (i.e., technical, markets, M&E). f. Farmer empowerment and (higher level) farmer organization strengthening to consolidate engagement and ownership of rural development, driving towards improved livelihood, including strengthened economic associations (e.g., around local warehouses), cooperatives, strengthened internal information and technical services to their members. g. Enhancing sustainable production systems and use of natural resources by promoting conservation agriculture/farming, integrated soil water and fertility management (soil health systems), integrated pest management, livestock husbandry, keeping livestock based on the carrying capacity, etc. h. Use of integrated sector level outcome and impact evaluation using national agricultural statistics services from the National Bureau of Statistics (NBS) for effective implementation of the National Agriculture and Livestock Sample Census (NASC implemented every 10 years) and the Annual Agricultural Sample Survey (AASS) and ensuring sound and timely analyses of this information; i. Strengthened support to policies and regulations to facilitate harmonization and expanded involvement of an inclusive private sector and continued support to strengthening decentralization and local level capacities and ownership advocacy of such policies to be understood and win stakeholder support. j. Flexible and harmonized financing modalities and management to integrate on-budget (budget support, BF (preferred), earmarked and ring-fenced programmes and projects) and off-budget programme and budgets. Core programme elements such as coordination (planning, implementation, M&E), capacity strengthening at national and local level will need to be financed either by the Basket Fund (government and non-earmarked development partner contributions) and/or ‘voluntary’ contributions (e.g., 5%) from each (on- and off-budget) programme and project in the sector. k. Functioning governance, accountability, and administrative structures, systems, processes and procedures. There is need to have clear roles and responsibilities and authorities at all levels, with accountability systems focused on delivery. H. The Theory of Change 81. Solving ASDP 1 Challenges. The program has 4 components and several projects to implement for 5 years. This objective will be achieved through prioritization, clustering and sequencing the projects and activities. The selected pathway by the government is to implement projects by creating an impact and bringing positive change. Firstly, the Government will create the necessary enabling environment by implementing Component 4 followed by Component 3, 2 and 1. This is because the implementation above sequence will address the following: - i. Solving most of the ASDP I challenges and immediate challenges, ii. Creating an enabling environment for other components to function, especially the industrialization agenda and value addition (demand and supply), and iii. Aligning and sequence components and project in line with the priorities. However, this prioritisation will not affect implementation of other initiatives. This means the initiatives may be implemented sequentially or concurrently. Figure 14 Shows prioritisation and the theory of change. 40 Agricultural Sector Development Programme II (ASDP-II) Figure 14: Transformative Approach-Theory of Change Sector Enablers and Coordi nation Commer cialization and Value Addition Productivity and Profitability Sustainable Water and Land Use Management Increased productivity growth rate for commercial market- oriented agriculture for priority commodities Expanded sustainable water and land use management for crops, livestock and fisheries Higher productivity, commercialization level and smallholder farmer income improved livelihood, food security and nutrition. C 4 C 3 C 2 C 1 Improved & expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations Strengthened institutions, enablers and coordination frame work Also the program will focus of local investments targeting prioritized commodity value chains (CVCs) in line with their comparative advantage in each AEZ and with consideration of clusters (district clusters46) 82. ASDP II implementation plan, Sequencing and Scheduling. For implementation ASDP II components, and projects are sequenced and scheduled to create and bring greatest change and impact. The implementation plan, sequencing, scheduling process considered the potential for components and projects which will address immediate sectoral challenges, take advantage of opportunities, and bring positive change. Also, there is need to implement projects that create the necessary enabling environment (“Unclog the pipe and let the water flow”). Implementation will start with component 4 which creates the necessary enabling environment for both private and public sector to function including the small holder farmer. The details of the implementation plan, sequencing and scheduling are covered under Annex I. IV. PROGRAMME OBJECTIVE AND DESCRIPTION 83. The ASDP II programme (2015/2016–2024/2025) is imbedded in the Tanzania Long Term Perspective Plan (LTPP)47, MKUKUTA and ASDS -II underlying results chain. Building on lessons learned from ASDS-1 and ASDP-1, the programme focuses on intensifying and operationalizing in a coordinated and sequenced manner the key ‘drivers’ of sectoral growth and transformation towards inclusive economic 46 Districts with the same commodity in the same EAZ will form a CVC or district cluster 47 The Tanzania Long Term Perspective Plan (2011/2012–2025/2026) outlines a development path that is cast in three five-year periods each with a specific development agenda. The first five-year period aims to remove the economy’s growth constraints in order to unleash the growth potential of the country. In the second five-year period, the focus will be on nurturing an industrial-based economy whilst developing the country’s agriculture and agro-processing sectors to enable Tanzania to become the regional food basket. In the third period focus will be to boost exports of manufactured goods with sharpened competitiveness. The three phases are inherently interconnected, with the successful implementation of one being an imperative for the implementation of the other. 41 Agricultural Sector for Industrial Development growth and rural poverty reduction. Building on lessons of the first phase and linking to national and continental higher-level goals, the overall framework for the results chain has been defined in Figure 1548. Figure 15: Framework for ASDP II results chain Level 4: Investment Sub-Components and Activities Level 3: ASDP-2: Prioritized Investment Programme CAADP: Comprehensive Africa Agriculture Development Programme Level 1: Vision 2025 / MKUKUTA OUTPUTS OUTCOME IMPACTS Level 2: ASDS-2 Figure 16: ASDP II Objective, Strategy and Outcome A. Programme Objective 84. ASDS-2 goal. In line with Tanzania Development Vision 2025, the higher-level sector goal is to “Contribute to the national economic growth, reduced rural poverty and improved food security and nutrition in Tanzania”. Key ASDS-2 strategic objectives are to: (i) create an enabling policy and institutional environment for enhancing modernized competitive agriculture sector, driven by inclusive and strengthened private sector participation; (ii) achieve sustainable increases in production, productivity, profitability and competitive value chain development of the agricultural sector driven by smallholders; and (iii) strengthen institutional performance and effective coordination of relevant public and private sector institutions in the agriculture sector at national and local levels, enabled by strengthened resilience. 85. ASDS-2 targets are to be achieved by 2024/2025: (i) inclusive and sustainable agricultural growth of 6% per annum; (ii) reduced rural poverty (per cent of rural population below the poverty line from 33.3% in 2011/2012 to 24% in 2025; and (iii) enhanced food security and nutrition (e.g., per cent of rural HHs below food poverty line: 11.3% in 2011/2012 to 5% in 2025. 48 Adapted from ASDS-2 42 Agricultural Sector Development Programme II (ASDP-II) 86. Programme Development Objective (PDO) for ASDP II. The objective of the ASDP II49 is to: ‘Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food security and nutrition’. Figure 17 below shows the ASDP II ‘building’ with the main objective as the ‘roof’ of the building, the ‘walls’representing Components 1, 2 and 3 and Component 4 as the base or ‘foundation’ of the building. Figure 17: ASDP II Programme Objective and Components Component 1: Sustainable Water and Land Use Management Component 2: Enhanced Agricultural productivity and Profitability Component 3: Commercialization and Value Addition Objective - Expanded sustainable water and land use management for crops, livestock and fisheries Objective - Increased productivity growth rate for commercial market- oriented agriculture for priority commodities Objective 4: Sector Enablers, Coordination and M&E Objective - Strengthened institutions, enablers and coordination framework Objective - Improved & expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations ASDP II Objective Transform the agricultural sector towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food security and nutrition. 49 ASDP II is a 10-year programme starting from 2017/2018 and ending in 2027/2028. 43 Agricultural Sector for Industrial Development Figure 18: ASDP II Priority Investment Areas Component 1: Sustainable Water and Land Use Management Component 2: Enhanced Agricultural Productivity and Profitability Component 3: Commercialization and Value Addition 1. Land use planning and watershed management 2. Irrigation infrastructure development 3. Irrigation scheme management & operation 4. Water sources development for livestock & fisheries 5. Promote Climate smart argiculture (CSA) technologies and practices (5 investment areas, 12 projects) 1. Policy and Regulatory Framework and Business Environment Improvement 2. Strengthening organizational and technical capacities of existing and new small scale producer, trade and processing farmer organizations and cooperatives movement 3. Promote and strengthen gender inclusiveness in the agricultural sector 4. Improve and strengthen vertical (from PO-RALG to RSs and LGAs) and horizontal coordination between ASLMs. 5. Improved capacity and agricultural data collection and management systems 6. Management Capacities and Systems Improvement 7. Develop Agricultural Sector M&E System 8. Improvement of Capacity in all levels 9. Improvement of ICT for Agricultural Information Services and Systems 10. Provide microfinance services (10 investment areas, 12 projects) 1. Strentherning Agricultural extension, training and promotion/info services (crops, livestock and fisheries) 2. Improvement Access to crops, livestock and fisheries inputs and health services 3. Research and development 4. Strengtherning and promote agricultural mechanization (crop, livestock and fisheries) 5. Food and nutrition security improved (5 investment areas, 19 projects) 1. Develop market access for all priority commodities. 2. Develop market access for fisheries and livestock products. 3. Development of processing and value addition for Crop, livestock and fishery products (3 investment areas, 13 projects) Component 4: Sector Enablers, Coordination and M&E 87. The strategy is to transform the subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development. 88. The PDO will be measured by the following preliminary indicators50: (i) Agricultural sector growth (crops, livestock and fisheries) (ii) Variation in annual average yield of target commodities (crops, livestock/fish products) (iii) Variation in crop, livestock/fisheries income of beneficiaries (men/women/youth) (iv) Average share of the consumer price kept by farmer or average farm gate (real) prices for selected commodities (v) Variation in volume and value of total output marketed for selected CVC (vi) Variation in number of food (and nutrition) insecure households in PAs (average Household Dietary Score) compared to other areas (vii) Number of beneficiaries (or per cent by social groups and gender); (viii) Increase in volume of agricultural exports (ix) Increase in farm incomes (by different rural household types) 89. The programme focus is on public investments that curb constraints and enhance the identified priority drivers towards increased sustainable productivity and farmers profitability growth, targeting high potential CVCs in selected districts (district clusters), while strengthening institutional capacities of public and private sector stakeholders (platforms), especially at local level. The proposed programme will initially focus on high potential commodities in selected (high potential) areas and subsequently scale-up to further commodities and district clusters across all AEZs, considering their respective priority CVC, as outlined in Chapter III sections E and F. To upgrade outputs and profitability of farming systems, the main thrust is to support priority CVC development, with an emphasis on building business 50 These are indicative indicators: a detailed results framework is provided in Annex II (Results framework and monitoring). Proposed indicators will be disaggregated by gender (and youth) as applicable. 44 Agricultural Sector Development Programme II (ASDP-II) partnerships between smallholders, markets and agribusinesses. This will involve interventions that support smallholder farmer transformation into more market-oriented (commercial) producers, through increased and sustainable productivity, resilience to climate variability/change and local value addition by improved market efficiency to enhance income growth by aggregating outputs (such as warehousing) and agroprocessing. Key investments at national and local level will include infrastructures, support services, farmer51 and other stakeholder empowerment and organization, capacity strengthening, policy and regulatory reforms, but also institutional strengthening towards strengthened coordination and consolidated M&E of the agricultural sector at various levels. Beneficiaries include smallholder crop, livestock and fish farmers/fisher folk and their organizations and agribusiness stakeholders (value adding and marketing) that form joint ventures in selected value chains, with special attention to women and youth engaged in the targeted priority CVCs. Smallholder farmers with potential for increasing their productivity and marketing levels will be supported with access to technologies, while being empowered through FOs for enhanced market orientation and partnering with agribusiness. The number of direct beneficiaries will grow in waves, as stakeholder institutions will be strengthened to develop sustainable support capacities for key sector drivers. Table 10: Typology of rural households active in the agricultural sector against holding size Holding size (ha) Crops only Livestock Crops and livestock Total Number of households % Number of households % Number of households % Number of households % A. 0.01–0.50 484,585 14 47,773 80 181,083 8 713,441 13 B1. 0.51–1.25 1,045,293 31 4,198 7 481,164 22 1,530,656 27 B2. 1.26–2.50 1,191,939 35 2,352 4 720,494 32 1,914,786 34 C. 2.51–5.00 493,775 14 2,059 3 482,001 22 977,833 17 D. Above 5.00 206,481 6 3,463 6 359,670 16 569,614 10 TOTAL 3,422,072 100 59,845 100 2,224,411 100 5,706,329 100 Source: Adapted from the Tanzania Agriculture Sample Census 2007/2008 90. While involving the already market-oriented producers (category C and D, in Table 9) for further intensification, the programme will concentrate its support on developing the potential for intensification and market contribution of category B, which represents about two-thirds of the farming community. Category A represents the poorest section of rural dwellers, mainly subsistence farmers, who are constrained by limited land and access to labour. As net food buyers, this category has little potential for market-orientated agricultural production (except for specialized horticulture) and needs to be supported by social safety net programmes (e.g., TASAF) and also through professional capacity building, especially of youth, for integration into other rural (agribusiness) and urban sectors of the economy. 91. Small-scale commercial farmers (above 1.0 ha cropped area) form up to two-thirds of rural farming households: their attitudinal, risk bearing and investment characteristics are different from those with smaller holdings. At the lower end, they sell at least one-third of what they produce and look for opportunities to increase their farm income as they are already profit oriented, by taking some risk. Furthermore, their expenditure on labour intensive goods and services increase local employment and raise incomes (and food security) of the rural non-farm families. 92. Programme components. The programme has four interlinked components (see Figure 19): (i) Sustainable Water and Land use Management, including mainstreaming resilience of sustainable and smart farming systems; (ii) Enhanced Agricultural Productivity and Profitability by sustainable technology generation, promotion/use, food security and nutrition; (iii) Commercialization and Value Addition to build competitive CVCs; and (iv) Strengthening Agricultural Sector Enablers, including policy framework, , institutional capacity and coordination, and sector-wide M&E. 51 Farmers include crop producers, livestock keepers and fish farmers. 45 Agricultural Sector for Industrial Development Figure 19: ASDP II components and sub-components B. Priority Investment Areas (summary) 93. Investments to increase farmers’ productivity for crops, livestock and fisheries are the first priority towards increasing opportunities for commercialization within the frame of sustainable utilization of natural resources. Expansion of research and development, extension services, irrigation, water for livestock, pasture development, mechanization and improved access to crop/livestock/fisheries inputs will enhance efforts to increase productivity across the sector. Investments in improving the capacity of institutions and rural infrastructure (roads, electricity, facilities) will be needed to expand markets and ensure efficient support services for transforming the sector. ASDP II also integrates specific interventions to improve food security and nutritional status of rural households and to enhance the resilience of rural livelihood systems to mitigate the impact of natural disasters, including climate change. 94. To stimulate growth in the agricultural sector to attain expected levels of 6% per annum, increased public and private investments are required. The best results in terms of economic growth, reduction of poverty and food security are likely to be generated by balanced support for both the commercial and smallholder sub-sectors, focusing on the main commodities that are largely produced and consumed by the local population, along with efforts to help subsistence smallholders graduate to the ranks of small-scale commercial farmers (IFPRI, 2011). For ASDP II, investment activities have been grouped into programmatic areas along components and sub-components. Strategic priority investment areas are depicted in Table 11: 46 Agricultural Sector Development Programme II (ASDP-II) Table 11: ASDP II components and strategic objectives Components/programme areas Strategic priority investments Component 1: Sustainable water & land use management Sustainable integrated land and water resources use and management and increased resilience (irrigation, charco-dams & boreholes, land use planning, soil fertility management, pasture development, ponds/cages) Component 2: Enhanced agricultural productivity and profitability Increased productivity growth rate for commercial market-oriented agriculture for priority commodities (crops, livestock and fisheries value chains) Component 3: COMMERCIALIZATION and value addition (build competitive CVC) Expanding farmer access to rural value addition and competitive marketing systems for priority commodity value chains, driven by an inclusive, strengthened and thriving private sector and effective farmer organizations. Component 4: Strengthening sector enablers at national, regional and local level Policy and regulatory framework Institutional capacity strengthening, communication & knowledge management. Food security and nutrition (including early warning and safety nets) Coordination (facilitate planning & implementation at all levels) Monitoring & evaluation (including agricultural statistics) 95. Implementation of prioritized investment in Agro-Ecological Zones (AEZ) and districts clusters. The program will focus on: (i) restoring basic agricultural capacity building and extension funds to prepare human and institutional (MSIP) capacities to sustain sector investments; and (ii) gradual building-up of focused local investments on priority commodity value chains (CVC) in ecological zones. The program will focus on investments that curb constraints and enhance the identified priority drivers towards increased sustainable productivity and farmers’ profitability growth. The program will target in high potential Commodity Value Chains (CVCs) in Agro ecological zones (AEZ)52. The agro- ecological zones and districts to be involved in ASDP II implementation are indicated in Table 12: Table 12: Agro-ecological zones and districts to be involved in ASDP II AEZ Regions Districts 1 Arid Lands (unimodal 400-900 mm) Mara (E) Musoma TC, Musoma DC, Serengeti, Bunda, Tarime, Rorya Dodoma (E) Masai Steppe, Tarangire, Mkomazi, Pangani and East Dodoma Simiyu Bariadi DC, Maswa, Meatu, Itilima, Busega Manyara (E) Kiteto, Simanjiro 2 Eastern coast Lindi Lindi DC, Lindi MC, Liwale, Ruangwa, Kilwa, Nachingwea. Mtwara Mtwara T.C, Mtwara DC, Masasi, Nanyumbu, Tandahimba, Newala Tanga Handeni, Kilindi, Korogwe DC, Lushoto, Muheza, Mkinga, Pangani, Tanga, Korogwe Pwani Kibaha TC, Kibaha DC, Bagamoyo, Mafia, Mkuranga, Kisarawe, Rufiji Dar-es-Sal. Ilala, Kinondoni, Temeke 3 Northern Highlands (bimodal) Arusha (S) Arusha DC, Meru, Arusha MC, Karatu, Monduli, Longido, Ngorongoro Kilimanjaro (N) Moshi DC., Hai, Siha, Moshi M. C, Mwanga, Rombo, Same Manyara (E) Babati TC, Babati DC , Hanang, Mbulu 52 The priority commodities per AEZ are as indicated in Table 7, 8 and 21 47 Agricultural Sector for Industrial Development AEZ Regions Districts 4 Plateaux (unimodal) W: Tabora, Rukwa/Katavi Tabora M C, Igunga, Nzega, Sikonge, Tabora (Uyui, Urambo Mpanda DC, Mpanda TC, Mlele Mbeya (N) Chunya (partie N) Ruvuma + Morogoro (S) Songea T. C, Songea D.C, Namtumbo, Mbinga, Tunduru, Ulanga (Mo) Mwanza Mwanza CC, Magu, Geita, Ukerewe, Missungwi, Sengerema, Kwimba Geita Geita DC, Chato, Bukombe, Nyang’wale, Mbogwe 5 Central semi-arid (unimodal) Dodoma (W) Kondoa, Dodoma MC, Mpwapwa, Kongwa, Bahi, Chamwino Singida Singida DC, Singida MC, Manyoni, Iramba, Ikungi, Mkalama Shinyanga Shinyanga M C Shinyanga DC, Kishapu, Kahama Morogoro Morogoro M C, Morogoro DC, Mvomero 6 Southern & highlands S-Mbeya Mbeya MC, Mbeya D. C, Mbarali, Kyela, Rungwe, Mbozi, Ileje, Chunya (S) S-Iringa Iringa DC, Kilolo DC, Iringa (S), Mufindi, Njombe Makete, Ludewa, Njombe TC, Njombe DC. Makambako, Morogoro NW Kilombero, Kilosa 7 South Western highlands Rukwa Sumbawanga DC, Sumbawanga TC, Nkasi, Mpanda DC, Mpanda TC 8 Western highland Kigoma Kasulu, Kibondo, Kigoma DC, Kigoma TC Kagera (bimodal) Biharamulo, Bukoba D. C, Misenyi, Bukoba T. C, Karagwe, Muleba, Ngara Source: ASDP II BF (2013) - ARD; Tanzania CSA Program (2015) and de Pawn, 1984 C. Component 1: Sustainable Water & Land Use Management (crops, livestock and fisheries) 96. Strategic objectives, outcomes and related indicators for the sustainable water and land use management component are defined as follows: 48 Agricultural Sector Development Programme II (ASDP-II) Table 13: ASDP II Component 1: Related ASDS-II specific objectives and outcomes Spec. objective Outcomes Outcome indicatorsa Comp 1. Improved and sustained integrated land and water resource use and management (E.g. for irrigation, water for livestock, cropped land, pastures, ponds/cages, and soil fertility Expanded sustainable water and land use - Percentage increase of schemes practicing sustainable irrigation - Percentage increase of livestock keepers with access to permanent water sources (natural or man-made) - Percentage of modernized irrigation facilities with professional management - Improved rangelands (ha) with sustainable pasture and water for livestock - Increased area (ha) under fish farming - Increased number of mariculture farmers - Percentage increase of stakeholders implementing CSA technologies Improved resources management for crops, livestock, and fisheries 1.1Improved Land Use Planning and sustainable Water Shed and Soil Management - Percentage increase of districts with land use plans - Percentage increase of villages with land use plans - Percentage increase of watersheds with integrated management plans - Additional area (ha) under improved agricultural production - Percentage increase in water quantity for agricultural production 1.2. Integrated Water Use and Management for Crops/Irrigation and Livestock/ Fishery Development - Additional area (ha) under improved irrigation - Cropping intensity for irrigated crops - Additional permanent water points for livestock - Increased area (ha) under fish farming - Increased number of mariculture farmers 1.3. Mainstreamed resilience for climate change/ variability and natural disasters - Percentage increase of farmers (crop, livestock and fisheries) adopting CSA technologies and practices - Proportion of LGAs with mainstreamed CSA in their DADPs - Proportion of ASLMs with mainstreamed CSA in their plans - Percentage decrease of households who are under the risk of floods or drought 97. Component 1 is sub-divided into 3 sub-components : Component 1. SUSTAINABLE WATER AND LAND USE MANAGEMENT S/c 1.1: Land use planning and sustainable watershed and soil management s/c 1.2: Integrated water use & management for crops/irrigation & livestock/fishery development S/c 1.3: Mainstreaming resilience for climate variability/change and natural disasters 49 Agricultural Sector for Industrial Development Sub-component 1.1: Land use planning and sustainable watershed and soil management 98. Increasing human and livestock populations Threatens land use. There has been an expansion in the cropped area in recent years and increasing conflict levels between farmers and livestock keepers hinder development of the sector. Promotion of land use plans and their enforcement is thus critical for sustainability of the sector. This strategic area requires a multi-stakeholder approach for sustainable land use for crops, livestock (pasture and rangeland) and fisheries: (i) country-wide national and village level land use plans in collaboration with the Ministry of Land, Housing and Settlements Developments, PO-RALG and the Tanzania Investment Centre (TIC—land banks); (ii) sustainable pasture and range management measures to prevent or minimize land degradation and desertification and mechanism for resolving land use disputes; (iii) improved soil fertility management by adapted land tillage and sustainable use of fertilizers; and (iv) enhanced fish farming by integrated inland aquaculture. 99. Although there are still areas of arable lands which are not used for crop and livestock or fish production, most of the incremental production from the smallholder sub-sector is expected to come from productivity improvements. Additionally, in the intensive commercial sector, investments to expand the utilization of land resources will also be a source of growth. Area expansion needs to be accompanied by measures to safeguard customary property rights. 100. ASDP II is expected to spearhead efforts to conserve and utilize Tanzania’s natural resources in a sustainable and productive manner, by adopting sustainable land and water management systems. Measures to strengthen the policy and legal framework for utilization of land and water resources utilization will also include developing institutional and technical capacity as priority areas. Equally important is the prevention and reversal of arable and rangeland degradation in the rainfed areas, which cover most of the country. Soil fertility depletion and erosion are already threatening the sustainability of arable agriculture. The damaged areas need to be rehabilitated to prevent further deterioration through better soil health management, introduction of soil conservation measures, reforestation, appropriate conservation agriculture and sustainable pasture management methods. Land use planning and watershed management 101. “Land use planning is a systematic and iterative procedure carried out in order to create an enabling environment for sustainable development of land resources which meets people’s needs and demands. It assesses the physical, socio-economic, institutional and legal potentials and constraints with respect to an optimal and sustainable use of land resources, and empowers people to make decisions about how to allocate those resources” (FAO/UNEP 1999: 14). 102. Increasing scarcity of land requires land use planning for diverse purposes, all aiming to optimize land resource uses to avoid deteriorations and land use conflicts as well as other consequential problems such as famines and wars. Land use planning can be applied to support sustainable development within given areas (territorial development) or specifically to ensure the protection of ecosystem services, biodiversity and high conservation values (natural resource management, national park management, and buffer zone management). It can also help mitigate climate change or adapt to it, to prevent disasters or to be prepared for them, to ensure food security, to develop areas in post- conflict situations or in drugs environments or specifically to reduce land conflicts and improve land governance. It will also contribute to address land/resource tenure issues, avoid land ‘grabbing’ and mitigate its consequences. 103. In response to current constraints and challenges of development, the aim of this programis to optimize land use planning and land access for respective local population activities, including cropping and grazing lands (connected to water availability). Land use planning is cross-sector elements between crop and livestock and other uses, which allows integrating participatory spatial planning into local development planning. Besides national level facilitation, policy adaptation and technical support, the implementation of land use planning activities will mainly be integrated into local level investments implemented under AR4D activities and DADPs. Priority national and local investments/ projects are shown in Table 14. 50 Agricultural Sector Development Programme II (ASDP-II) Table 14: Prioritized activities in land use planning for crop and livestock development Investment/action areas Priority activities Land use planning and watershed management - Participatory land use planning and watershed management - Development and enforcement of by-laws - Capacity building for land use management - On- and off-farm run-off management (including adapted mechanization) - Conservation of marginal land areas - Area protection (afforestation, terracing, etc.)—communal land - AR4D activities/studies for optimal land use determination Agricultural land use management - Demarcation and titling of farmlands to increase security and promote investment - Establish and implement sustainable crop land management plans. - Promote appropriate soil and water management technologies and improved cropping practices Grazing land development: improved rangeland management and use in livestock production - Develop and implement sustainable rangeland management plans - Pasture improvement (seed/hay production, demonstration plots) - Strengthen early warning systems for timely information & mitigation strategies - Support environmental conservation in pastoralist communities Pastures development & forage conservation - Promote production and use of improved pasture & fodder tree species - Enrichment of in situ pastures (seeds) - Forage conservation (hay, silage, etc.) Vector and vector-borne disease control in the rangelands - Area wide integrated pest management techniques (ticks, tsetse and other vectors of veterinary importance) Investment strategies follow-upa Assessment of impacts and efficiencies of irrigation and rainfed water management investments a project management to be integrated in comprehensive M&E (s/c 4.5) Sustainable soil management and upscaling conservation agriculture53 104. Declining soil fertility, due to continuous cropping (without fallow) and low levels of fertilizer use for soil nutrient restoring is believed to be a key cause of low crop yields. Rangeland degradation threatens the livelihoods of pastoral communities, calling for better rangeland management, including drought preparedness and response, but also alternative forms of income generation to reduce grazing pressure. Sector support initiatives should aim to increase both productivity and production while keeping a balance between adapted productivity investments in high and low potential areas to fight rural poverty. To increase productivity levels sustainably, there is a need to promote appropriate technologies, including soil and water conservation, integrated soil fertility management, agroforestry, conservation agriculture techniques and other related indigenous knowledge. Furthermore, trade-offs between productivity and resource management will be minimized within sustainable agricultural intensification of adapted farming systems. 105. Integrated soil health management. The best yields are achieved when nutrients come from a mix of mineral fertilizers and organic sources, such as nitrogen-fixing crops/trees and organic matter (manure, compost). Integrated soil fertility management ensures that nutrients reach the plant when required and do not pollute natural resources, and save farmers’ money. Policies to promote soil health should encourage conservation agriculture (see s/c 1.3) and mixed crop–livestock and agroforestry systems that enhance soil fertility and encourage ‘reasoned’ site-specific and precision nutrient management. Soils rich in organic matter and biota are the foundation of increased crop productivity. 53 See also ‘Save and grow’: http://www.fao.org/ag/save-and-grow/index_en.html 51 Agricultural Sector for Industrial Development Box 2: Basic elements for better land husbandry—Integrated soil fertility management Promotion of an integrated and synergistic resource management approach embracing locally appropriate combinations of the following technical options: • Build-up of soil organic matter and related biological activity to optimum sustainable levels (for improved moisture and nutrient supply and soil structure) through the use of compost, farmyard manure, green manures, surface mulch, enriched fallows, agroforestry, cover crops and better crop residue management • Integrated plant nutrition management with locally appropriate and cost-effective combinations of organic/ inorganic and on- and off-farm sources of plant nutrients • Better crop management with improved seeds of appropriate varieties, improved crop establishment at the beginning of the rains, weed management and integrated pest management • Better rainwater management to increase infiltration and reduce runoff (erosion) so as to improve soil moisture conditions within the rooting zone, thereby lessening the risk of moisture stress during dry spells, e.g., box ridges) • Improvement of soil rooting depth and permeability through breaking of a cultivation-induced compacted soil layer (hoe/plough pan) through conservation tillage practices (sub-soiling, chisel ploughing or inter- planting of deep rooted perennial crops/trees and shrubs) • Reclamation where appropriate (i.e., if technically feasible and cost effective), of arable land that has been severely degraded by such processes as gullying, loss of topsoil from sheet erosion, soil compaction, acidification, alkalinization and salinization • For irrigated crop production systems, also improving water use efficiency: improved water distribution to minimize channel seepage losses, and mulching to reduce evaporation losses, and minimizing the risk of salinization by following good irrigation and drainage practices • For livestock production systems, better integration of crop and livestock production in both the cereal based farming and agropastoral systems • Adoption of people-centred self-learning and investigating approaches • Community-based participatory approaches to planning and technology development • Better land husbandry that offer farmers tangible economic, social and environmental benefits. Source: Strategic Investment Programme for Sustainable Land Management in sub-Saharan Africa (FAO, 2007) 106. Upscaling Conservation Agriculture. Conservation Agriculture is a concept for resource-saving agricultural crop production that strives to achieve acceptable profits together with high and sustained production levels while concurrently conserving the environment (FAO, 2007). Conservation agriculture relies on three key principles: (i) practising minimum mechanical soil disturbance (minimum tillage); (ii) creating and maintaining a permanent organic soil cover; and (iii) practising crop rotation with more than two species. The main activities proposed are centred on: (i) creating awareness by information dissemination on integrated soil fertility management and conservation agriculture; (ii) building capacity of extension staff and farmers on conservation agriculture; and (iii) adapting policies and regulations for conservation agriculture, including for agricultural mechanization (equipment specifications in line with conservation agriculture). Besides national level facilitation, policy adaptation and technical support, conservation agriculture support activities will be integrated into local level investments implemented under DADPs. A range of extension tools will be deployed to train farmers and promote improved agricultural practices to sustainably increase staple crop yields by improved soil health and integrated soil fertility management. ASDP II will also facilitate farmers’ access to needed inputs (s/c 2.3), mechanization equipment for production and post-harvest (s/c 2.4) and related financial services (s/c 4.6.). Sub-component 1.2 Integrated water use and management for crops/irrigation and livestock/ fishery development 107. Efficient and inclusive water use for irrigation, livestock and fishery. Expected strategic interventions and innovations are: (i) investment in irrigation to increase productivity by targeting the prioritized areas with high return potential; (ii) strengthen irrigators organizations for better operation and management of the infrastructures and resources; (iii) further strengthen backstopping services for LGAs and Irrigators Organizations; (iv) implement coordinated water resource planning and management in watershed/catchment areas; (v) enhance efficiency of water utilization; (vi) encourage private sector to invest in irrigation development; (vii) enact and enforce laws and regulations which protect irrigation potential and irrigation developed areas; (viii) continued efforts to ensure sustainable 52 Agricultural Sector Development Programme II (ASDP-II) water resources management and utilization through enhance observation of existing Environmental and Social Management Framework (ESMF) and strengthened capacities for integrated water resources management. 108. Conservation and sustainable utilization of water resources is a high priority. This will be achieved through watershed management initiatives, water harvesting, and improved smallholder and commercial irrigation and drainage systems to increase water use efficiency and ensure the sustainability of investments. These capital-intensive investments include irrigation infrastructure, equipment and integrated water management services. Investments target the improvement of traditional irrigation schemes, rehabilitation of deteriorated schemes and expansion of irrigated area in the identified potential areas. Increasing the efficiency of irrigation schemes by professional management schemes will improve farmers’ returns and sustainability of investments. Besides crop irrigation, specific investments will facilitate improved access to quality water resources for livestock and fisheries. 109. Increasing resource competition towards sustainable use. Along with climate change, water demand by multiple sectors (agriculture, energy, human consumption, watershed and wildlife conservation, etc.) is becoming more and more competitive. There is no assurance of continuous water allocation for the agricultural sector, the largest user of water resources. Policies will need to eliminate perverse subsidies that encourage farmers to waste water. Globally, the management of water resources would require improved water use efficiency through sustainable extraction rates, maintenance of infrastructure, land use planning and tracking environmental impact. Sustainable intensification requires smarter, precision technologies for irrigation and farming practices that use ecosystem approaches to conserve water, rainwater harvesting and supplemental irrigation of rainfed crops. Despite its high productivity, irrigation is under growing pressure to reduce its environmental impact: knowledge-based precision irrigation that provides reliable and flexible water application and wastewater reuse will be a major platform for sustainable intensification. Increasing rainfed productivity will depend on the use of improved, drought tolerant crop varieties and management practices that save water. Crop Irrigation Development. 110. The objective of irrigation development is to improve crop productivity and sustainable returns for small- and medium-scale farmers on an expanded irrigated area. This support will include: (i) irrigation development planning and professional management for intensification; and (ii) irrigation infrastructure development, including rehabilitation and expansion of existing irrigation infrastructure. Under ASDP-1, irrigation was given high priority with a major budget share. As a result, the increase in developed irrigated area by about 100,000 ha was one of the main ASDP-1 outputs. At local level, demand-driven support for scheme development was incorporated into DADPs and funding was sourced from the benefiting farmers. In addition, the support was channelled through the ASDP- 1 District Irrigation Development Fund. At national level, larger and more complex inter-district irrigation infrastructure was funded using the National Irrigation Development Fund (NIDF). 111. Although the average cost per irrigated hectare appears comparable to or lower than corresponding costs in sub-Saharan Africa, there is room to reduce infrastructure costs and to increase water use efficiency. The impact assessment study54 for ASDP-1 pointed out that cost reduction is an issue that needs to be tackled under ASDP II. Hence, a comprehensive strategy should be adopted that will lead to improved design and completion of irrigation infrastructure, aiming at increased water use efficiency. The cropping intensity of the irrigation schemes was low, as only 25 per cent of the area irrigated during the rainy season was cultivated under irrigation during the dry season. Irrigator contributions for water fees and infrastructure maintenance were also low. 112. Strengthen technical support services for irrigation development. At the national level, this activity will strengthen the capacity of the National Irrigation Commission (NIC) and Zonal/Regional 54 See Impact Evaluation of the Irrigation Investment of the ASDP. April 2013. 53 Agricultural Sector for Industrial Development Irrigation Technical Units (ZITSU) in: (i) strategic planning and prioritization for sustainable irrigation development, including water resources management and environmental and feasibility assessments; (ii) provision of technical support to improve planning and designing for sustainable irrigation investments; and (iii) monitoring of performance and payoffs to existing irrigation investments, including routine data collection and management for critical aspects of irrigation development. 113. Participation of the private sector in ASDP II irrigation works and services will be enhanced by: (i) building capacity of local contractors/engineering companies in works/service provision for irrigation development by ZITSUs (construction and rehabilitation skills); and (ii) contracting out supervision services to private engineering companies, as from the first year of ASDP II. Information systems for irrigation schemes will be improved and a data management system established to allow for detailed prioritization, planning and budgeting of investments. The NIC Human Resources Development Plan will be consolidated and prioritized in view of strengthening all levels of irrigation players through recruiting required professionals. 114. Strengthen Irrigation Organizations (IOs) for professional irrigation management for sustainable productivity. This activity will strengthen capacities of IOs55 for effective development and management of irrigation schemes, within the frame of the NIP (2010) and the “Comprehensive Guidelines (CGL) for Irrigation Scheme Development”. In close collaboration with LGAs, ZITSUs and NIC and jointly with the irrigation scheme’s leadership, ASDP II will: (i) carry out a review of all existing IO constitutions and by-laws to identify gaps and provide necessary improvements linked to the approved template for IO by-laws, the NIP (2010), the CGL for irrigation schemes, Operation and Maintainance under DADPs and the National Irrigation Act (2013); (ii) identify knowledge and skills gaps in the IOs, describe training needs, prepare a training programme, and assist in carrying out the required training, using appropriate resource persons and service providers; (iii) train IOs and other stakeholders on the National Irrigation Act (2013) and its regulations; and (iv) develop framework guidelines for the IOs for implementation of the existing legislation and appropriate scheme management. 115. ASDP II will improve the management of existing schemes through contracting professional irrigation service providers56 to strengthen, for one or two years, the capacity of IOs and provide them with technical support in: (i) effective scheme development/upgrade and management of scheme operations, including potential crop diversification; (ii) maintenance and management of irrigation infrastructure; (iii) efficient water resources management, including water saving techniques; (iv) enhanced access to technologies (System of Rice Intensification (SRI), etc.), information and advisory services; and (v) strengthened linkages to inputs suppliers, mechanization services, processors, output markets and financial institutions. During the 2015–2020 period, interventions under this activity will target: (i) 78 irrigated rice schemes that cover about 56,000 ha under irrigation development, benefitting about 70,000 smallholders in the southern agricultural corridor; and (ii) finalize rehabilitation of high priority schemes supported under ASDP-1. During the remaining years (2021–2025) the programme will consider scaling up this approach to rehabilitate and develop further priority irrigation schemes. 116. Irrigation Infrastructure Development57. Building on ASDP-1 and BRN targeted priorities, through financed expansion of irrigation development through new construction of small- and medium-scale irrigation schemes or the expansion of existing ones, targeting priority commodities in high potential areas. Full system ownership and professional management by irrigators and their organizations (water user, marketing, etc.) will be pre-conditions for efficient investment with increased payoffs and sustainable use of infrastructures. The support will include three main investment areas summarized, as shown in Table 15. 55 Farmer participation at IOs is mandatory for sustainable irrigation infrastructure and water management and maintenance. Farmer empowerment and organization strengthening (including formation of cooperatives— AMCOS and SACCOS) for sustainable value chain development are outlined in Component 3. Strengthened farmer organizations are key for all sector activities (irrigated or not) and their membership, free farmer option. 56 Market support service providers are discussed in value chain and agribusiness development. 57 Adapted from Irrigation investments under ASDP IBF and BRN (FAO-TCIA 2013). 54 Agricultural Sector Development Programme II (ASDP-II) Table 15: Summary of BRN and remaining ASDP-1 prioritized irrigation schemes (2015/2020) Irrigation Schemes Total number of irrigation schemes Total number uncompleted schemes for ASDP-1 Number of uncompleted or new schemes Total new schemes Total area (ha) Earmarked by JICA Total BRN— initiative Total 367 280 120 78 87 162,122 (i) Ongoing implementations by JICA and USAID Earmarked by JICA 120 77 107 13 43 51,964 Earmarked Global Accelerated Food Security Programme (GAFSP) 4 3 4 10,000 Earmarked USAID—under review 5 0 0 2 5 18,600 (i) Completion, rehabilitation and upgrading of remaining 63 BRN irrigation schemes (World Bank) Part of BRN—initiative not overlap (i) 59 21 (13) 63 39 25,879 (i) Completion, rehabilitation and upgrading of 179 ASDP-1 prioritized irrigation schemes ASDP-1 priorities, not overlap (i) &(ii) 179 179 0 0 0 52,243 Total area (ha) 59,558 /l 117. Implementation. Two guideline documents exist already58, and will be improved to address the weaknesses noted during implementation of ASDP-1. The methodology agreed and explained in the “Comprehensive Guidelines (CGL) for Irrigation Scheme Development” will be used. NIDF will finance larger and more complex irrigation projects—extending over several districts. The strategy for coherent irrigation development will be implemented using ASDP II as a framework, while contributing also to the regulatory framework for sustainable land and water management. Improved water management in rainfed agriculture 118. Most farmers are engaged in rainfed agriculture. Better seasonal rainfall forecasting and improved (surface) water management within intensified and resilient production systems will reduce farmers’ production risks. Furthermore, crops and varieties adapted to exploit limited soil moisture, cropping practices increasing soil water storage capacity and water infiltration, deep-rooting crops in rotations, and minimizing evaporation through organic mulching will be promoted. Improving the productivity of rainfed agriculture depends largely on improving husbandry across all aspects of crop management. This entails capture of runoff, reduced tillage, organic mulching and use of natural and managed biodiversity which are fundamental to lengthening the duration of soil moisture availability. 119. On-farm runoff management can be achieved in different ways. For example, the use of water retaining bunds in cultivated areas has been used successfully in transitional climates to extend soil moisture availability (even ‘irrigation’) after each rain event. Another example is the concentration of overland flow into shallow groundwater or farmer-managed water storage, can allow for limited supplementary irrigation. However, both these interventions have an impact on downstream users and overall river basin water management is required. There is a need for reinforcement of advisory 58 “Comprehensive Guidelines (CGL) for Irrigation Scheme Development” (under DADPs – 01/2010) and “Guidelines for Operationalizing District Irrigation Development Fund and National Irrigation Development Fund” (under ASDP—Revised 04/2011. Like in ASDP-1, communities will contribute 20% of total costs for irrigation development, and annually at least 5% of average returns for O&M. 55 Agricultural Sector for Industrial Development services to farmers dependent on rainfed agriculture, including a sharper analysis of rainfall patterns and soil moisture deficits to stabilize production from existing rainfed systems under climate change impacts. Extending the positive environmental and soil moisture conservation benefits of ecosystem approaches will often depend on the level of adapted farm mechanization (see s/c 2.4), which is needed to take advantage of rainfall events (see also Conservation farming/agriculture, s/c 1.2). 120. Policies and investment priorities. The relative contributions of rainfed and irrigated production investments at national level need to be assessed for different production systems in targeted AEZ. If rainfed production can be stabilized by enhanced soil moisture storage, the physical and socio- economic circumstances under which this can occur need to be well identified. The respective merits of low-intensity investments in sustainable rainfed crop production intensification and high intensity localized investments in full irrigation need careful technical and socio-economic appraisal against development objectives59. Proposed key action areas are proposed in Table 16. Table 16: Priority actions for improved water management in rainfed agriculture Investment areas Priority activities Extension & AR4D - Improved cropping practices for improved soil and water management (land husbandry) - Promotion of conservation agriculture Farm level interventions - On- and off-farm run-off management (including support for adapted mechanization development) - Enhanced soil coverage and organic matter level Landscape level interventions - Off-farm run-off management (including upper catchment) Policies & investment strategies - Assessment of impacts and efficiencies of irrigation and rainfed water management investments Water resources for livestock and fisheries 121. Over 70% of the livestock population are kept in semi-arid areas in northern, central and western parts of Tanzania. Water supply in pastoral and agropastoral areas includes the management of: (i) ground water by springs, shallow wells and boreholes; and (ii) surface water from streams and rivers, earth dams and catchments of rainwater harvest. Under ASDP-1 about 1,060 charco-dams and 40 boreholes, constructed between 2001 and 2010 at local level, have improved the availability of water for livestock and minimized the movements of livestock farmers and their livestock while searching for water. 122. The aim is to further increase water availability for livestock and fish by developing and maintaining reliable water sources. Priority investments are given in Table 17. Table 17: Priority activities livestock/fish access to water resources Investment areas Priority activities Developing and maintaining reliable water sources for livestock - Construct and maintain (charco)-dams, boreholes, etc. (Participatory planning, implementation and management with livestock holder organizations). - Pasture improvement (seed/hay production, irrigated production demonstration plots) Fish and other seafood farming development - Facilitate construction of fish ponds - Fish cages in lakes - Other seafood production Seaweed farming development - Facilitate promotion of seaweed cultivation in ocean 59 See also Save and grow (FAO 2013) 56 Agricultural Sector Development Programme II (ASDP-II) Investment areas Priority activities Fisheries resources development - Facilitate sensitization among fisher folk on Ecosystem Approach to Fisheries (EAF) issues - Facilitate conduct of fisheries frame survey - Conduct of border patrol - Improve quality standard of fish and fisheries products Budget note: Construction of 10 dams at TSh 1 billion each Sub-component 1.3: Mainstreaming resilience for climate variability/ change and natural disasters 123. Climate variability/change presents Tanzanian farmers and pastoralists with a new set of challenges. Although uncertainties about the nature and extent of change in the different AEZ of the country, there are indications that the frequency of extreme events may increase. This calls for an adequate level of preparedness in order to manage risks and mitigate their impacts on vulnerable households, including loss of assets. Efforts to mitigate the impact of disasters and climate change have been facing challenges60, including among others: (i) inadequate capacities to produce and disseminate early warning information on disasters; (ii) limited emergency response and mitigation measures including facilities; (iii) weak meteorological information and set-ups; (iv) lack of well-organized disaster maps focusing on major sources of disasters in the country (v) weak institutional integration of early warning system disaster response and preparedness; and (vi) weak financial capacity to arrest the shocks. 124. Climate smart approach61 adds a further dimension to the natural resource management issue. Due to the high level of agroclimatic diversity in Tanzania, climate change is likely to affect agriculture in many and varied ways during and beyond the time horizon of the ASDP II. The high level of dependence on rainfed agriculture makes Tanzanian rural households particularly vulnerable to climate change, which could increase the frequency of drought. There is a need to enhance the development of more robust and resilient farming systems that are able to adapt to a range of possible climate change outcomes. This climate smart approach will include the promotion of integrated (and synergistic) crop, livestock and fish production systems for sustained use of available natural resources. 125. Climate Smart Agriculture (CSA)62 is an integrative approach to address interlinked challenges of food security and climate change through: (i) adapting and building resilience of agricultural and food security systems to climate change at multiple levels; and (ii) reducing greenhouse gas emissions from agriculture (including crops, livestock and fisheries). In response to a growing threat of climate change, the ASLMs will collaborate with related ministries and take mitigation and adaptation measures. The required interventions include: (i) undertake research and exchange information with other research institutions (regional and international); (ii) improve water use efficiency in agricultural production systems; (iii) promote integrated land and soil management; (iv) facilitate implementation of ESMPs by farmers and livestock keepers; and (v) create awareness, build policy frameworks, strategies and programmes, strengthen institutions and enhance financing towards implementing climate smart agriculture development. 126. Save and grow!63 Sustainable intensification means a productive agriculture that conserves and enhances natural resources. Increasing food demand remains a challenge made even more daunting by the combined effects of climate change and growing competition for land, water and energy. 60 Evidence of Impact: climate smart agriculture in Africa. CTA 2014. 61 See expected potential changes induced by climate change for Tanzania in ASARECA study on East African Agriculture and climate change: A comprehensive analysis—Tanzania http://www.ifpri.org/sites/default/files/ publications/aacccs_tanzania_note.pdf 62 Adapted from ASDS-2 (September 2015) and Tanzania Climate Smart Agriculture Programme, coordinated by Ministry of Agriculture and the Vice President’s Office (2015–2025). 63 See also SAVE and GROW: http://www.fao.org/ag/save-and-Grow/. In a broad sense involving crops, livestock, fish and natural resource (soils, water, vegetation) management. 57 Agricultural Sector for Industrial Development The new paradigm is ‘sustainable crop production intensification’, which produces more from the same area of land while conserving resources, reducing negative impacts on the environment and enhancing natural capital and the flow of ecosystem services. Key principles are: (i) farming systems that save resources and offer a range of productivity, socio-economic and environmental benefits to integrated crop and livestock producers; (ii) access to improved crop varieties/seeds, animal breeds and fingerlings; and (iii) good agricultural practices including soil health and integrated soil nutrient management, rainwater and irrigation water management and plant and animal health protection. To encourage smallholders to adopt sustainable crop production intensification, policies/regulations and institutions need to devise incentives for small-scale farmers to use natural resources wisely (i.e., environmental services), rebuild research and technology transfer capacities and reduce the transaction costs of access to credit for investment (remove barriers to adoption and scaling up!). Box 3: The agenda for sustainable agricultural intensification and resilience The agenda for sustainable agricultural intensification needs to respond to rising market demand for crop and livestock/fish products from a growing global (and urban) population, in the context of a weakened natural resource base, energy scarcities and climate change. Promoting a sustainable intensification agenda involves: • First, to increase resilience and promote environmental sustainability, while increasing productivity, it is of critical importance to address together the imperatives of producing more, more effectively, and of preserving or restoring the natural resource base to put tomorrow’s rural generations at the centre of a new agenda for rural growth and poverty reduction. • Second, to capitalize on farmers’ local knowledge and social capital as well as on scientific research to address context-specific problems, so as to develop responses that are rooted in local agro-ecological conditions. There is no blueprint for an agenda for sustainable intensification, but a systemic approach, context adaptation, and linking farmers’ own and scientific knowledge are part of agenda for change. • Third, to build resilience to stress (including climate change) into farming systems, thus strengthening small-scale farmers’ capacity to manage risk. Sustainable agricultural intensification should be taken as an approach to broaden woman and men farmers’ options to better capture market opportunities while reducing risks, or strengthening their capacity to manage them. • Fourth, to enhance policy and political support, including adequate incentives and risk mitigation measures for a shift to sustainable intensification to take place. This requires, in particular, more secure land tenure to encourage long-term investments, conducive pricing and regulations for the use of natural resources and agricultural inputs, and support for the development of PES opportunities and markets. Farmers need better education, adapted to their needs, new farmer-centred learning approaches and linking-up to sources of information and resources. Conducive environment for developing capabilities for sustainable intensification requires building coalitions, sharing responsibilities and creating synergies among governments, civil society, the private sector—and above all—farmers and their organizations. Source: Adapted from Tanzania—Agriculture Climate Resilience Plan (ACRP), 2014–2019 127. Besides national level facilitation, policy adaptation and technical support, the implementation of climate change activities will be mainstreamed in all ASDP II activities, including research, support to sustainable crop, livestock and fish production and post-harvest management towards increased resilience and synergies. Specific investments will be integrated into local level investments implemented under DADPs. The main action areas for ASDP II are outlined in Table 18. 58 Agricultural Sector Development Programme II (ASDP-II) Table 18: ASDP II investment and action areas for improved resilience of farming systems Investment/action areas Priority activities Policies/regulations - Impacts on vulnerable groups, identifying opportunities for adaptation and mitigation, including strategies derived from the East African Community Climate Change policy - Strengthen early warning and preparedness - Enhance risk management measures, including risk insurances Crops - Research & extension on new crops/varieties and sustainable farming systems suited to hotter/drier conditions (mainstreamed) - Promotion of conservation agriculture, including adapted mechanization - Short- and long-term weather forecasting and response farming Livestock/fisheries - Strengthening human and technical capacities and systems for early warning to provide timely information and response - Developing mitigation and adaptation strategies for climate variability and change towards sustainable livestock and fisheries production systems - Support livestock herders and their organizations to implement mitigation and adaptation measures 128. Component 1 investments at national and local levels. Table 19: Five Years Development budget/investment estimates for component 1 –at constant 2016 Prices (TSh million) COMPONENT 1: SUSTAINABLE WATER& LAND USE MANAGEMENT- BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development 29,759 31,014 34,532 0 0 95,305 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity. 14,132 14,517 13,715 13,501 16,284 72,149 1.1.1.3 Enhancing access to agricultural land for youth empowerment 4,464 4,150 5,753 4,534 6,321 25,222 1.1.1.4 Improving coordinatoin of watershed management and monitoring systems for sustainable resource utilization - 1,366 928 839 916 4,049 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,370 184,589 172,338 175,278 189,619 738,194 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity. 5,873 50,129 57,162 59,915 65,430 238,509 1.2.2.1 Strengthening Irrigation schemes management and operations. 1,823 1,652 2,250 1,787 2,592 10,104 1.2.3.1 Development of water infrastructures for livestock productivity. 2,856 66,582 77,456 76,103 85,464 308,461 59 Agricultural Sector for Industrial Development COMPONENT 1: SUSTAINABLE WATER& LAND USE MANAGEMENT- BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries. 42,069 79,875 111,447 158,157 88,773 480,321 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies. 1,905 13,984 8,745 6,345 10,445 41,424 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management. 1,090 1,045 1,730 795 1,329 5,989 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness. 1,960 1,052 1,009 396 501 4,918 TOTAL COMPONENT 1 122,301 449,955 487,065 497,648 467,674 2,024,643 D. Component 2: Enhanced Agricultural Productivity and Profitability 129. Strategic objectives, outcomes and related indicators for the ‘Enhanced agricultural productivity and profitability’ are defined in Table 20. 60 Agricultural Sector Development Programme II (ASDP-II) Table 20: ASDP II Component 2: related ASDS-2 specific objectives and outcomes Specific objective Outcomes Outcome Indicatorsa SO2. To increase productivity growth rate for commercial market- oriented agriculture for priority commodities Improved agricultural productivity - Changes of yields (MT/ha, Litres/cow/lactation, Eggs/hen/day, Live weight/cattle at market point, Kg/fish) for priority commodities’ value chains - Percentage change in labour efficiency (Tsh/farmer/season) - Percentage change in Malnutrition (stunting and under weight) Improved agricultural profitability - Change of gross margins (Tsh/ha, Tsh/dairy cow, Tsh/LU, etc.) for priority commodities’ value chains - Change of profitability/Net returns (Tshs/commodity or enteprise) of priority commodities - Net financial returns to farmers/livestock keeper/fisherman 2.1. Improved agricultural extension services - Percentage change of farmers visited by extension staff - Adoption of productivity enhancing technologies by farmers - Adoption of disseminated technologies - Farmers’ satisfaction with extension services (customer care) - Extension staff delivering quality extension services - Prevance of pest and diseases incidence of economic importance - Incomes of households/ farmers that adopted improved technologies 2.2. Improved access to agricultural inputs/health services - Farmers access quality inputs - Seed germination rates - Crop yields - Access to subsidies - Benefits from subsidies - Percentage change of farmers using fertilizer - Percentage change of farmers using improved seed - Percentage change of livestock keepers accessing AI servive 2.3. Improved agriculture research for development - New technologies tested, released and disseminated by research stations (e.g new varieties) - Capacity of research stations to generate high quality technologies - Recurrent and development budget allocations and disbursements 2.4 Improved access to mechanization services - Affordable mechanization services - Households access different mechanization services for priority commodity value chains - % change of households accessing processing facilities for priority commodities’ value chains - Post- harvest losses of along priority commodities’ value chains 2.5 Improved food and nutrition security - Rural households living above/below the poverty food line - National food self sufficiency - Malnutrition incidences (chronic and transitory) in Tanzania - Macro- and micro-nutrients deficiency in children and pregnant women - Households with access to nutritious and diverse food - Households practicing diversified farming systems for improved diets and reduced vulnerability to food shortages - Households accessing livestock and fish proteins. - District receiving food assistance from NFRA - Volume of public stocks held by NFRA - Households receiving emergency food relief Component 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY S/c 2.1: Extension training and information services S/c 2.2: Access to agricultural inputs and health services S/c 2.3: Agriculture Research for Development (AR4D) S/c 2.4: Access to mechanization services S/c 2.5: Food and nutrition security 130. The strategy aims to increase and sustain productivity of priority commodities (crops, livestock and fishery) by targeting the small-scale commercial farmer sub-sector towards consolidated household food security but also agricultural commercialization. There is a need to accelerate the adoption of yield-enhancing technologies and reduced on-farm and post-harvest losses, including use of improved seeds and fertilizers, through improved access to credit, livestock health services and adapted 61 Agricultural Sector for Industrial Development mechanization services. Component 2 is divided into five sub-components. The Government of Tanzania priority for the agricultural and agro-industrial sector is to achieve a sustainable production increase equivalent to a 6% annual compound growth rate64. The specific objective of this component is to enable increased productivity growth rate for commercial market-oriented agriculture for priority commodities (crops, livestock and fish value chains). Increased agricultural commodity productivity is a prerequisite for household food security and agricultural commercialization, while area extension should be considered under intensified production systems. The proposed objective and outcomes will be achieved by four interlinked sub-components: (i) extension/advisory, training and information services; (ii) access to agricultural inputs for crops, livestock and fisheries; (iii) research for development; (iv) access to production and post-harvest mechanization services and (v) food and nutrition security. 131. Targeting smallholder commercialization, the strategy of this component is to increase delivery and use of demand-driven technologies, enhancing the productivity of prioritized CVCs within sustainable production systems for crops, livestock and fish. This will be achieved through: (i) broader availability of technology options responding to commercial needs of CVC stakeholder; (ii) facilitated farmer access to adapted technical knowledge and options for use; (iii) enhanced farmer access to inputs through private agrodealers (i.e., adapted seeds, planting materials and livestock breeds, fertilizers, feed and agrochemicals); and (iv) other technology support services (such as mechanization, phyto- and zoo-sanitary services, etc.). Advisory and training services will include food and nutrition aspects, such as promotion of crop diversification and bio-fortified varieties, awareness on cross-cutting issues such as gender; youth, environment and sustainable NRM, climate change mitigation, risk resilience and governance, as required. 132. Sustainable intensive production systems include among others natural resource management (land and water), conservation agriculture, integrated soil fertility, integrated pest, diseases, and post-harvest management. These approaches will be fine-tuned and scaled up by strengthened national and zonal AR4D services, demand-responsive extension services and private input supply channels (improved seed/breeds/fingerlings, fertilizers, agrochemicals, veterinary drugs, vaccines, etc.). Support will also provide improved access to: (i) sustainable management of land and water resources; (ii) adapted mechanization for production and value addition; (iii) required production, processing and marketing facilities; and (iv) appropriate diagnostic laboratory services, control and prevention of pests and diseases. 133. Livestock development will make a significant contribution to the sector growth through use of improved genetic resources and feed practices, but also commercialization, increased processing capacity and improved marketing efficiency. Specific measures will also be undertaken to improve fisheries and aquaculture production and management including infrastructure (modern fisheries harbour) and targeted sanitary measures. Table 21: Objectives for priority action in livestock and fish productivity development (10 years) Sub-sectors Specific objectives/outcomes Subsector Livestock and Fisheries - Availability, access and use of inputs/implements - Strengthened research, extension and training activities (infrastructure) - Diversification of new potential revenue sources Meat production - Water and pasture for livestock and fisheries (infrastructures)—comp 1; - Improved meat productivity towards commercial production of quality meat, meeting standards for domestic and international market Milk production - Increased production to meet domestic demand and external markets (raise income) Eggs production - Meet domestic demand and raise income of poultry farmers 64 Raise sectoral GDP from TZS 9,600 billion (USD 6.4 billion) in 2010/11 to around TZS 30,600 billion (USD 20.4 billion) in 2030/31. GDP per capita among the rural population would increase from around USD 180 to USD 360 over the same period. 62 Agricultural Sector Development Programme II (ASDP-II) Hides & skins and other by-product development - Improved quality, collection and processing of hides and skins for domestic and export markets - Use for food, feed, pharmaceuticals and energy Animal draught - Increased return on agricultural labour and related small-scale production Promote market access of animals & animal products - Develop cooperative and other farmer-based organization - Improve zoo-sanitary inspectorate services (improve prevention and control) - Establishment of disease free zones and strengthen disease reporting & surveillance - Strengthen laboratory disease diagnostic services Aquaculture production and fish captures - Promoting fish farming and aquaculture production and services Feasibility study and a detailed design for construction of fishing port - Increased aquaculture productivity and raised income of aquaculture farmers - Fishing regulation updating/enforcement for sustainable fishing & fish production Source: Adapted from ‘Livestock Sector Development Programme’. December 2011. The Medium-Term Expenditure Framework (MTEF) for 2015/2016 takes into consideration of the National Five Year Development Plan (2011/12–2015/16) and the BRN. Subcomponent 2.1: Extension Training and Information Services 134. Smallholder productivity for both crop, livestock and fish commodities still remain low due to limited use of improved agricultural technologies, inadequate AR4D linkages and extension services (public and private), limited availability and farmer access to agro-inputs, and unreliable markets and value addition opportunities. Disharmonized legislation and weak inspectorate services are limiting the country’s access to potential regional and international niche markets, while inadequate capacity building and monitoring systems result into unsustainable natural resource (land and water) use management and intolerable pesticide use and residues to consumers and the environment. 135. Overall ASDP-1 was instrumental in setting in place a system for delivery of extension services to smallholder farmers through LGAs, although their coverage and service quality have been uneven, focusing mainly on production of crops, with less attention on livestock and fisheries and post-harvest handling and marketing. It contributed with substantial on-the-job and formal training and increases in total manpower65 of public extension systems, while focusing mainly on conventional production technologies. The current structure for crop and livestock extension services is heavily reliant on the public sector. Recent efforts to introduce PPP initiatives, FFSs and ward resource centres (WARC) show promises for more effective farmer support services. Further steps for piloting and up-scaling innovative and cost-effective approaches for technical services, provided and managed in close partnership with farmer organizations (e.g., farmer facilitators, community animal health workers (CAHW))66 or Private Service Providers (agribusiness services, veterinary services, etc.) should be undertaken. 136. Extension and training services play pivotal roles, as described in Box 4, in terms of linking farmers to new technologies, information and knowledge that are central to enhancing agricultural productivity. To meet farmers’ demand and ownership towards increasing sustainable agricultural productivity, there is a need to: (i) strengthen AR4D linkages; (ii) adopt the most modern participatory extension methodologies; (iii) use modern ICT, such as mobile phone and Internet, including for higher level backstopping; (iv) promote use of sustainable agricultural practices (conservation agriculture, good agricultural practices, IPM, etc.); (v) facilitate farmers access to quality inputs (seeds/germplasm, fertilizer, feed, vaccines, etc.); (vi) strengthen the pest monitoring and early warning surveillance system; (vii) harmonize institutional set-up for PPP, involving local CVC stakeholders (including FO); and (viii) strengthen laboratory capacities for detection of disease pathogens and vectors for newly emerging and re-emerging diseases. 65 Number of village/ward extension officers in June 2013 was 7,974 (Minister budget speech FY 2014/15). 66 Sustainable services that are provided by trained animal health services at community level (e.g., CAHW) in support of livestock holder groups/association/cooperatives services related to livestock such as dipping, water dams, breeding bulls, grazing land. 63 Agricultural Sector for Industrial Development Box 4: Strengthening efficient extension (MAFC Workshop - January 2015) Is the current model of extension still fit to serve diverse farmer needs? Government targets transformation for provision of quality commodity extension services with increased private sector participation. Within the government regulatory role, institutional framework reform, started with TARI, multipurpose WARCs, FFS, etc. ASDP II coordination framework will be more comprehensive to include all projects/programmes in the agriculture sector. Recommendations/ideas for strengthening provision of extension services: (i) Diversity of its clientele by gender, resource base, type of enterprise, AEZ, climate, market opportunities, social capital and access to credit, etc. (ii) Pluralism in the provision of extension services that include both public, FO/CSO and private entities (including ties with input supply). Promote private sector process in extension services (including PSP) and use diverse communication methods (ICT); leverage private sector service provision; (iii) Strengthen training–research–extension linkage to address real farmer issues (LGA-ASLM linkages, operational ZIELUs and district facilitation teams (DFTs)), joint planning and sector financial support. Integrate training institutions under one umbrella (Sokoine University of Agriculture, ATIs, LITAs, Fisheries Education and Training Agency) and strengthen their capacities and effectiveness. (iv) Number of extension staff (1 per village—need 9,139 more): staff deployment to every village or fewer staff to form ward technical teams (public/private). Continuous enhancement knowledge & practical skills of extension staff on the value chain approach (v) Participative approaches/models and methodologies used in the provision of extension services (system/commodity, reasonable cost): (i) multiple approaches/models to be used including VBA and RIPAT; (ii) guidelines/manuals for the extension implementation; (iii) use ICT; and (iv) lifting farmers to organize themselves into self-running/help entities (e.g., SACCOS, Farmer (Learning) Groups, Agriculture Marketing Cooperative Societies (AMCOS), etc. (vi) Institutional arrangements in the provision of extension services: professional organization for extension officers, retraining, regular performance evaluation; strengthened district extension teams to link with research/FO, implement/equip functional WARCs (ICT) and use the PPP policy/strategy to improve efficiency for extension delivery (guidelines?) (vii) Financing: pre-conditions for effective extension include increased budgetary allocations (Agriculture Extension Block Grant, Agriculture Capacity Building Grant), adequate motivation, conducive arrangements & change working culture. Way forward! Transformation of extension service is key for enhancing agricultural production and productivity by: (i) ensuring quality services by involvement of key players; (ii) taking cognizance of the diversity of farmers including gender; (iii) envisaging institutional reforms for research/training); (iv) accessing information involving ICT; (v) supporting & equipping of multifunctional WARCs to backstop VEOs; and (vi) coordinating all local extension supports with annual planning and evaluation meetings; and (vii) build professional capacities of extension staff. 137. The objective is to enhance improved technology dissemination delivery systems into farmer use, which will contribute to increased and sustained production, productivity and farmers’ profitability of priority commodities (crops, livestock and fisheries) responsive to smallholder constraints and market requirements. Building on the lessons learned from ASDP-1, this sub- component will provide support to strengthen delivery of demand-driven market-oriented advisory and information services for smallholder farmers, scaling out successful approaches such as FFS, farmer-to-farmer and use of modern ICT (mobile phone, Internet and other social media), but also provider increased service ownership to CVC stakeholders, especially FOs. Special attention will be given to mainstream cross-cutting issues such as women and youth in agriculture, nutrition (see also s/c 4.3), HIV/AIDS and good governance and professional management of farmer and CVC organizations, including cooperatives. 138. At national level, this sub-component focuses on policy and institutional reforms for implementing effective agricultural service strategy, support to local implementation, media (national level radio/ television programmes, newsletters, agricultural shows, networking with international agencies, etc.) and information technology (IT) support. ASDP II will also integrate support to training and additional technical services such as land use planning and management (see s/c 1.2), animal and plant health services; plant and animal production materials; mechanization (see s/c 2.4) and additional policy and regulatory support. 64 Agricultural Sector Development Programme II (ASDP-II) 139. At LGA level, the sub-component, will support efficient and effective extension approaches and services that will enhance farmers’ access to technology innovations for increased productivity of their priority crop/livestock value chains; and promote farming system diversification towards improved risk management and food security and nutrition. This sub-component will support the following strategic action areas: i. Reorient technical support services to commercial farming promotion focused on priority CVC, facilitated by DCPs. Public technical agricultural services will be complemented by private agribusiness advisory service providers to form integrated CVC support teams at district and ward levels. The support services will provide specialized training and coaching to the district and ward-level agricultural facilitation teams to allow for their involvement in promoting commercial agriculture and strengthen agribusiness partnerships. To complement farmer empowerment and farmer organization strengthening (see s/c 3.1), FFS and farmer-to- farmer extensions will be strengthened by training, motivating and supporting lead farmers to provide technical services to local farmer/cooperative groups. This approach will promote efficient demand-driven and market-oriented advisory services and enhanced AR4D flows. ii. Scale up on-farm technology testing and demonstration to allow farmers a wider choice of options by strengthening research–extension–farmer linkages through the client-oriented research and extension management framework developed during the ASDP-1. This would include: (a) supporting district crop and livestock AR4D officers to link district technical teams with TTPUs; (b) implementing demand-driven on-farm research trials for priority CVCs (two/ district/year); and (c) up-scaling technology tests (two/ward/year) and demonstrations (two/ village/year), focused on priority CVCs, to assure broader awareness and farmer access to improved technologies/inputs and post-harvest technologies. iii. Improve farmer access to technical and economic information by strengthening local stakeholder access to technical and market information through use of innovative technology dissemination pathways, including traditional communication and modern ICT (e.g., Internet and mobile phones). Based on established effective communication infrastructure and technical support from TTPUs (see s/c 2.1), activities aim to improve farmer and other CVC stakeholder access to relevant technical and economic information to develop their agribusiness. To this end, district technical subject matter specialists, ward/village extension teams and lead farmers will be equipped and connected for information exchange and technical help desk at all levels, using internet and mobile phones. However, access to traditional farmer information channels will also be promoted by means such as the diffusion of leaflets/technical notes, radio programmes and listener discussion groups and the establishment of basic Ward Agricultural Resource Centre (WARC) modules (20 m²), where not yet implemented. iv. Rehabilitating/strengthening capacities for agricultural training institute (ATI)/ livestock training institutes (LITIs) to enable their functions of: (i) education and production of new extension officers (diploma and certificate level); (ii) in-service training and upgrading to existing extension officers (including the upgrade from certificate to diploma); and (iii) contribution to technical service providers to LGAs and farmers (local level function). v. Strengthening of crop and animal health services, including regulatory functions of input and output quality control. 140. At national/zonal level, the extension sub-component will support the national agricultural extension services and the regional secretariats to develop strategies and provide technical backstopping to districts. This will cover capacity strengthening for innovative market oriented CVC and advisory services for sustainable farming systems, developing guidelines and specialized information and training material, enhancing methodological support and guidelines for pluralistic extension services and capacitating the LITI/ (ATI) to deliver quality training. At local level, technical services will be financed through respective components. District, ward and village extension staff, supported by private Agricultural Service Providers (APS), will play key roles in supporting testing and up-scaling of successful technologies/systems within and across districts. 65 Agricultural Sector for Industrial Development Crops Extension, Training and Promotion 141. Crop extension services department under the Ministry is mandated to: (i) advise on policy formulation and strategies; (ii) improve extension services methodologies for use in LGA; (iii) establish standards and monitor their implementation; (iv) provide technical guidelines to the Regional Secretariat (RS), LGAs on good agricultural practices and sustainable agriculture; (v) disseminate technical packages for use in RS and LGAs; (vi) facilitate research–extension–farmer linkages; (vii) coordinate and facilitate private extension services providers; (viii) facilitate in-service training and capacity building of extension workers; (ix) promote the use of ICT in extension; and (x) monitor and evaluate extension services provision. 142. ASDP-1 promoted agricultural extension service innovations, including the use of the FFS approach to enhance technology diffusion and use among small-scale farmers. The FFS approach has been recognized as efficient among public and private/NGO extension service providers, although its up- scaling requires further harmonization across public and PSPs, integration of all value chain segments and improved focus on women and youth. The FFS approach will be used in parallel with other approaches, such as farmer-to-farmer exchange visits, internal technical and market services of farmer organizations, etc., but also the establishment of effective technical and economic information services adapted to the different user needs (farmer, extension worker, district subject matter specialists, ministry level specialists, etc.). 143. At national level, the proposed key action areas for agricultural extension are: i. Strengthening human resources and working facilities for national extension support services, especially for methodological and institutional innovation & higher-level support. ii. Contributing to harmonization of the FFS approach(es) around priority value chains and focusing on women and youth, enhancing graduated FFS master farmers to set up new ones, promoting study/exchange visits for farmers and field staff. iii. Accelerating extension reforms towards effective modern agricultural extension by developing an extension strategy (and master plan), enhanced research and extension linkages, harmonization of public and private extension support, use of ICT (e-extension—see further details in s/c 4.5) in dissemination of technologies and market information along commodity value chains; As part of implementing the National Agricultural Policy (2013), the ministry is committed to develop a National Extension Strategy and a legal framework for extension services which will define amongst others: (i) the relationship of key players in the provision and financing of extension services; (ii) responsibilities the extension staff and clientele to be served; (iii) coordinating mechanisms between different organizations that undertake extension; and (iv) promoting dialogue forum for key stakeholders involved in extension. iv. Rehabilitating physical infrastructures and retool four farmer training centres67 and Farmers Education Unit (FEU) to disseminate improved technologies. v. Strengthening technical backstopping at local level and building capacity of extension services at regional administrative secretariats (RASs), districts and ward teams to increase efficiency of public and private service delivery and supervision of field activities (including by the use of ICT—s/c 4.5) 144. At local level priority investments are: i. Strengthening human resources and working facilities for extension services at district and ward level (technical knowledge-retraining and working gears—extension kit, transport). ii. Improving working and living environment at ward and village levels; building and consolidating ward extension teams. 67 Four farmer training centres under the ministry: Mkindo in Mvomero district; Bihawana in Dodoma District; Inyala in Mbeya district; and Ichenga Njombe District. 66 Agricultural Sector Development Programme II (ASDP-II) iii. Retooling and facilitate functioning of WARCs, including establishing technology demonstration plots. iv. Linking up with zonal research and extension liaison/partnership units (TTPU) and strengthening implementation of on-farm research and demonstration networks for new varieties and sustainable agricultural management practices along priority CVCs (see s/c 2.3). v. Widening technical and economic knowledge support to farmer empowerment and organization within integrated value chain development from production to marketing. vi. Developing efficient response systems to farmer technical needs/questions by developing ICT systems (see s/c 4.5) at local level for increased extension and advisory service efficiency. 145. Training. The ministry has 14 ATIs68 for the crop sub-sector. Most of the physical infrastructure needs rehabilitation to stimulate effective learning and staff efficiency and effectiveness. These institutes also lack teaching and most learning materials and/or training facilities. This negatively affects ‘learning by doing’ and the skills developed do not correspond to the current labour market requirements. The curricula used in the ATIs therefore needs to be reviewed. The capacities of human resources of the training division (195 tutors, 94 agricultural field officers and 119 support staff) need to be upgraded by specialized long and short course programmes. 146. The objective is to strengthen training capacities for agricultural technicians (certificate and diploma level, and on-the-job training for farmer leaders) to avail public institutions and private companies with high quality agricultural technicians, whose training is accredited by National Council for Technical Education (NACTE). Training cycles will also allow for youth empowerment on self-employment and enterprise creation in the commercial agriculture. Priority support areas include: (i) rehabilitating living and learning environment of 14 ATIs; (ii) retooling ATIs with training facilities, aids/materials/ library, transport facilities and furniture; (iii) development of practical training farms/demonstration plots for students/farmers in ATIs; (iv) capacity building of tutors (195), agricultural field officers (94) and supporting staff (119 in the ministry headquarters and ATIs) in long and short courses; (v) curricula development for training diploma and certificate programme and farmers (include marketing issues, M&E, business investment planning and budgeting, FO support, etc.). 68 ATI (14): Igurusi, Uyole, Inyala training centre (Southern highlands); Ilonga, Mlingano, National Sugar Institute (NSI), Kilombero Agriculture Training and Research Institute (KATRIN) — (Eastern zone); Maruku and Ukiriguru (Lake zone); Mtwara (Southern zone); Tumbi and Mubondo (Western zone); Horticultural research and training institute (HORTI), Kilimanjaro Agricultural Training Centre (KATC)—(Northern zone). Only 3 ATIs (Mtwara, Ukiriguru and Maruku) were rehabilitated in 2011. 67 Agricultural Sector for Industrial Development Box 5: Technical training institutions ATI/LITI form middle level technical institutions between ASLMs and LGAs, which primarily provide practical and theoretical training of agricultural technicians who can be employed in the public and private sector. ATI/ LITIs also undertake some short-term training for farmers (leaders). Approximately 1,600 and 2,700 students graduate annually from ATIs and LITIs respectively. ASDP II needs to strengthen the role of ATIs and LITIs (eight colleges) to achieve: (i) Well-trained agricultural extension professionals and technicians (diploma and certificate). The gap for crop extension workers is 6,244 (15,802 is total need), while at headquarters the gap is 142 + 372 for other cadres (approximately 2,700 students graduate annually from ATIs). The gap for livestock extension workers is about 10,000 (total need is 16,000). (ii) In-service training for VAEO/WAEO and upgrading capacities of existing extension manpower. (iii) In-service training and farmers training is provided in ATIs and LITIs mainly for farmer leaders and to strengthen farmer organizations in management, leadership and technical & economic services to their members. Therefore, these institutions require significant improvements in terms of tools and facilities for practical training in production and marketing, adapted to zonal farmer needs. Support to the running of these public institutions is generated from core public support, programmes/projects, CVC boards, private entrepreneurs and the students (fees and internal production). 147. Crop Promotion ‘Section’. To improve production, productivity and commercialization of crop sub-sectors through promotion of good agricultural practices and entrepreneurship skills such as ‘Farming as a Business’ to the smallholder farmers, especially in specialized window crops. The strategies to improve production and productivity and commercialization of the sub-sectors will include the following: (i) commercialize production of drought tolerant crops (especially cassava); (ii) develop programmes/plans and to operationalize horticultural strategy and infrastructure; (iii) training of horticultural subject matter specialists and lead farmers on good agricultural practice and value chain development; (iv) develop strategy and implement programme for organic produce promotion to capture increasing demand for organically grown products; (v) develop a national oil seed development strategy and implementation programme; and (vi) upgrade and maintain mother orchards in five potential areas so as to establish a reliable sources of quality scions for seedling production. The crop promotion section also provides technical support services to nine crop boards (tea, coffee, cotton, sisal, pyrethrum, tobacco, sugar, cashew nut and cereal and other produce boards). This support includes, among others: (i) the review and improvement of their development strategies; (ii) specialized technical backstopping of key value chain actors and lead farmers; and (iii) promoting contract farming. 148. Proposed priority investments include: (i) implementation of crops development strategies in nine crop boards69; and (ii) other activities related to cassava commercialization, operationalization of the horticultural development strategy, training and working facilities of LGA and the ministry staff, implementation of regulatory functions and monitoring. Strategic alignment of respective functions of crop boards, the Ministry of Agriculture and Ministry of Industry, Trade and Investment would be useful for increased efficiency of supports. Livestock and Fish Extension and Training 149. Livestock and fisheries extension services deal with transfer of knowledge and skills to farmers and sharing of technical and economic information and experiences amongst value chain stakeholders, to increase production and productivity and producers’ return. The extension service currently is mainly provided by public service providers with gradual increase of private sector participation in the delivery of the services through different interventions, especially for animal health services. Currently, livestock extension services include 4,172 livestock extension staff at district, ward and 69 Tea, Coffee, Cotton, Sisal, Pyrethrum, Tobacco, Sugar, Cashew nut and Cereal and Other Produce Board. 68 Agricultural Sector Development Programme II (ASDP-II) village levels70 (the staff deficit estimated at 16,000 technicians). 150. Under the extension system, the Livestock Identification and Traceability System (LITS) is an essential prerequisite to international livestock trade and marketing and guarantee food safety and sanitary assurance to consumers. The export of livestock and livestock products is compromised by the high prevalence of trans-boundary animal diseases and inadequate/low compliance with international markets sanitary and phytosanitary standards requirements, demanded by livestock and livestock products importing countries. The priority investment areas for the improvement of livestock/fisheries advisory and technical support services are, as established in Table 22: Table 22: Priority activities livestock extension Investment areas/priority activities At national and regional level: - Development of practical training farms/ demonstration plots for students/farmers - Coordinate livestock extension services providers and undertake technical backstopping - Training of 594 livestock extension staff at MSc level from all LGAs & headquarters - Rehabilitate four (4) and build three (3) livestock infrastructure in 7 zonal agricultural show grounds - Establish and equip TV and radio programmes recording studios at national level - Establish a Guarantee Support Fund for Livestock Identification Devices (LIDs) - Rollout of Tanzania National Livestock Identification and Traceability System (TANLITS), including a strengthened TANLITS Help Desk through provision of reliable internet and website connectivity - Conduct long- and short-term training to TANLITS managers/administrators, ICT & other experts on database management, computer programming, computer engineering and system management - Prepare and circulate public sensitization materials on TANLITS including print materials, radio and TV programmes and conduct sensitization meetings and workshops to target stakeholders in 25 regions At LGA level - Identify knowledge gaps for public/private livestock extension service providers in all LGAs, promote private technical services (animal husbandry, health services, etc.) - Provide extension kits, vehicles (147) and motor cycles (4,000) in 147 LGAs, training of 294,000 farmers on improved livestock production technologies in all LGAs - Establish 147 Livestock Resource Development Centres in all LGAs - Use ICT to inform and advise livestock keepers (see also s/c 4.5) - Facilitate 147 LGAs to sensitize formation and strengthening farmer groups, organizations, associations and cooperatives - Build capacity of 30,700 livestock farmers on management and entrepreneurship skills - Conduct training and provide backstopping on TANLITS application to 165 LGA Livestock Identification Traceability Officers & 25 Regional Livestock Officer; support 147 LGAs in TANLITS field operations & communication network - Support installation of TANLITS hardware and software to five accredited export abattoirs/slaughterhouses Table 23: Priority intervention in fisheries extension Investment areas/priority activities National/regional level 1. Improved collaboration among extension service providers 2. Increased expertise for fisheries extension officers and fishers/aqua farmers 3. Strengthen private quality feeds and seeds production 4. Rehabilitation of existing infrastructure 5. Capacity building on new technology and facilities operations 6. Construction of processing facilities for dagaa (Rastrineobola spp) from fresh and salt water 7. Strengthen preservation facilities (ice plant and cold room) along Lake Tanganyika 70 Overall there are about 12,111 villages, 3,383 wards and over 160 LGAs (all not having livestock extension services). 69 Agricultural Sector for Industrial Development Investment areas/priority activities LGA level 1. Support private sector participation in provision of fisheries/aquaculture extension services 2. Formulate and strengthen fisher folk and aqua-farmer (water and land user) organizations 3. Develop and strengthen infrastructure—resources centres for fisheries and aquaculture extension services 4. Strengthen technical backstopping for fishers/aqua farmers 151. Training. Livestock Training Agency (LITA) is among the three Agencies of the Ministry of Livestock and Fisheries. It was established in under the Executive Agency Act No 30 of 1997 and its amendments (RE 2009) in September 2011. LITA was formed by merging six Livestock Training Institutes (LITIs) which were Tengeru, Mpwapwa, Morogoro, Madaba, Buhuri and Temeke. In year 2013 and 2014 Mabuki and Kikulula Training Units were established respectively. The major role of LITA is to implement livestock development objectives as expressed in the National Livestock Policy 2006 and Ministry’s Strategic Plans. The core activity of LITA is to offer Diploma and certificate courses in Animal Health and Production at NTA Level 4 - 6 and also offers various specialized courses for various clients/farmers. Short courses include; Poultry Production, Dairy cattle husbandry, Milk processing, Beef cattle husbandry, Pasture production, Hides & skin management and Entrepreneurship. LITA’s training approach is Competence Based Education and Training (CBET) to ensure production of competent graduates who can be employed by the Government, Private Sector or self-employed and thus contribute to development of livestock sector and national economy. Strengthening of infrastructure, training facilities as well as improvement of curriculum are foundation for effective extension services. 152. Fisheries Education and Training Agency was established by merging the Mbegani Fisheries Development Centre and the Nyegezi Freshwater Fisheries Institute. The main role of Fisheries Education and Training Agency is to assist the Ministry in: (i) provision of fisheries education and training in aquaculture, fisheries technologies and management; and (ii) conduct applied research and consultancy in promoting sustainable development of fisheries and allied industries. This initiative will promote public and private service delivery to aqua-farmers, small-scale fisher folk and commercial enterprises and other stakeholders, which are mainly provision of quality fisheries education and training, improve extension services, develop appropriate fisheries technology and promote sustainable aquaculture through physical demonstration and practical advice. 153. Both LITA and Fisheries Education and Training Agency take over the functions of the livestock and fisheries training institutes (LITIs and FTIs) as well as other functions expressed in their respective framework document, including: (i) training, research and consultancy: manage and coordinate long- and short-course training, applied research and specialized consultancy services; (ii) production support services of livestock, livestock products and other farm produce; and (iii) business support services to the agency in areas such as administration, management of human and financial resources, marketing of agency services and products and estate management towards sustainability and meeting clients demands. Table 24: Priority activities & investment areas in livestock and fisheries training (a) LIVESTOCK: Train professionals for the development of the livestock industry 1. Develop human capacities, review curricula and training programmes and retooling of LITA to provide livestock training 2. Train 100,000 livestock keepers from 20 LGAs on livestock improvement technologies 3. Infrastructures: support, construct and rehabilitate 8 LITA training centres 4. Capacity building of the ministry staff: facilitate DRTE and LITA staff to attend long and short courses, study tours and training workshops annually 70 Agricultural Sector Development Programme II (ASDP-II) (b) FISHERIES: Train professionals for the development of the fisheries industry 1. Build capacity of training institutes 2. Strengthened up to date information and training materials 3. Support maintenance of training institution’s infrastructure 4. Strengthened training guidelines 5. Support the Fisheries Education and Training Agency programme on value chain analysis, identification of technological gaps, value addition possibilities and mitigation of marketing snags along sardine supply chain 6. Monitoring and evaluation of training activities 7. Promotion of artificial reefs for sustainable restoration of depleted fish stocks and enhanced seaweed farming in coastal area, Tanzania Subcomponent 2.2: Access to Agricultural Inputs 154. Government efforts through NAIVS for increased use of improved seed and fertilizer delivered by a strengthened network of private agrodealers has enhanced the use of improved seeds and fertilizer by smallholders and requires follow-up, including: (i) further targeted smart input subsidy; (ii) design agricultural input credit package adapted to smallholder needs; (iii) facilitate private agrodealers to enhance their business network for improved input offer and access; (iv) effective extension services and training for accelerated adoption of new technologies; (v) enhance integrated soil fertility management, especially the use of organic fertilizer along with livestock activities; and (vi) strengthen the national seed systems involving ARI, the Agriultural Seed Agency, the Tanzania Official Seed Certification Institute (TOSCI), private seed producers and agrodealers. 155. The experience of smart subsidies in promoting crop productivity could be scaled up to livestock technologies including: (i) increased access to artificial insemination (AI) for upgrading of local breeds; (ii) improving animal health through interventions for controlling and eradicating diseases and pests (e.g., vaccinations, cattle dips, veterinary drugs); and (iii) pasture seed dissemination for improved rangeland, prevention of erosion, etc. For enhanced aquaculture and access to fingerlings, smart subsidies for certified fingerlings and feed could be envisaged within PPP in fish seed and feed production. 156. The objective is to expand sustainable access to and efficient integrated use of adapted farming inputs (i.e., seeds, planting materials and livestock breeds, fish fingerlings, fertilizers, animal feed and agrochemicals) by increased proportion of smallholders, which will contribute to increased and sustained production and productivity of priority commodities for crops, livestock and fishery. As farmers seek to widen their use of technology options for increased efficiency, income and resilience, the availability and access to specific inputs needs to be ensured: to this end, public support will facilitate and regulate the multiplication of improved genetic material (seeds, breeds, etc.) and farmer access to quality production inputs commercialized through competitive private sector supply channels (agrodealers). 157. Specific support will focus on priority CVCs in the selected district clusters, and include the following action areas: i. Enhanced availability of high quality crop seeds by strengthening private sector participation (including farmer organizations) in seed supply chains. This support targets seed production/ multiplication and distribution for priority commodities (and their companion crops) to assure availability of adequate quantities of quality seed for users preferred varieties. Main support activities include: (a) enhancing breeder seed/breed supply and technical assistance to the private seed sector; (b) supporting the Tanzanian Seed Trader Association (TASTA) and its seed market information system (seed demand and offer by variety and prices); (c) consolidating the capacities of regulatory functions of TOSCI71; International Seed Testing Association (ISTA) accreditation and regional expansion); (d) supporting the ministry’s seed unit for monitoring of seed sector development strategy and organizing an annual seed sector planning and evaluation involving all 71 TOSCI: support in complement of EAAPP. 71 Agricultural Sector for Industrial Development stakeholders; (e) Agricultural Seed Agency production of foundation/basic seed for public-bred varieties; and (f) supporting private/farmer multiplication, including by Quality Declared Seed farmer groups, for specific non-commercial varieties of priority CVCs (maize/rice/oil seed) and responding to a specific demand (i.e., sunflower). ii. Improved access to quality crop inputs (seeds, fertilizer, agrochemicals and tools) by strengthening the national and local agricultural input supply systems implemented by the private agrodealer network. Activities will include: (a) technical, safeguard and business capacity strengthening for about 1,000 active agrodealers in the target areas; (b) local demonstrations of improved technologies by agrodealers and extension workers (5–10 agrodealers per target district); (c) consolidating the capacities of regulatory functions of Tanzania Fertilizer Regulatory Authority (TFRA); (d) stimulation of partnerships (contract farming, etc.) between farmer organizations and agribusiness engaged in targeted CVC for sustainable production and marketing systems (receipt systems); and (e) promote the use of conservation farming practices72 and include the distribution of starter packs of seeds and other inputs for production diversification, including nutritious crops such as pulses and horticultural crops. iii. Production of quality pasture seeds to increase productivity and production of quality feeds to cope with the increasing number of animals and related economic and environmental impacts. Investments in improved ruminants (e.g., dairy) requires parallel investments in pasture development adapted to respective AEZ to increase productivity and contribute to farmers return. Incorporating improved pasture development strategies in the farming system and hay/silage production technologies will contribute to adequate supply of supplementary feed throughout the year. iv. Production of quality bulls and semen for improvement of indigenous livestock. The breeding objective(s) (trait) for selected farmer research groups are to improve milk potential of the indigenous cattle populations through cross-breeding, while maintaining high levels of adaptation to local feed resources and environments in general. In response to increasing farmer demand, TALIRI distributed 640 improved Mpwapwa bulls and 780 cattle between 2006 and 2015, some of which are used in cross-breeding. Current needs are to: (a) develop a breed of cattle whose cows will regularly yield about 2,800 kg of good quality milk per year in the semi-arid areas in Tanzania; (b) increase production of improved heifers and bulls to meet the current farmer demand of Mpwapwa breed and their crosses; and (c) improve the production and distribution of semen for AI from the semen producing centres v. Fingerlings production for aquaculture. Farming of fish and other aquatic organisms in fresh and marine water environments is becoming an important contributor to the world’s food supply and nutritional security, but also to rural livelihoods and employment. With decreasing fish supply from capture and increasing population, economically viable and environmentally sustainable inland and marine aquaculture need to be developed in Tanzania. This implies increasing farmers’ access to critical aquaculture inputs (seed, feed, organic fertilizers), and promoting appropriate aquatic farming technologies, extension support and training. Priority support actions include: (a) hatcheries for Tilapia sp., catfish, milkfish, mud-crabs and trout; (b) feed and grow-out development for selected fish species; (c) prawn farming development for clustered coastal farmers; (d) cage fish culture in selected non-drip irrigation schemes; (e) promotion of indigenous species for fish culture development (O. tanganicae, grouper culture, and Nile perch); and (f) promotion of value addition in seaweed. 158. Input subsidies. The NAIVS/AFSP (2008–2014) programme implemented a targeted smart subsidy, which yielded an additional production of 2.5 million tons of grains, through increased yields of maize (+433 kg/acre) and paddy (+ 263 kg/acre)73. Besides multiple challenges, the final economic rate of return (ERR) of NAIVS was estimated at 53.5%. The evaluation showed that about two-thirds 72 Applying principles of: (i) minimum tillage; (ii) permanent soil coverage; and (iii) crop rotations/associations. 73 Source: AFSP ICR (December 2014) and Tanzania PER: NAIVS February 2014. 72 Agricultural Sector Development Programme II (ASDP-II) of the 2.5 million beneficiaries continued to buy seeds while one-third continued to buy fertilizer at commercial prices, once the subsidy was terminated. Furthermore, besides increased awareness and use of agricultural inputs, NAIVS also strengthened seed production systems and farmers relationship with trained agro- dealers and commercial agents for seed and input supply. 159. However, considering the high investments costs, the Government of Tanzania tried to organize a follow-up programme to provide subsidized credit74 to smallholder farmers by paying banks the difference between the commercial interest rate of 18% and the programme’s designated rate of 4%. In addition, the government has agreed to pay commercial banks 50% of the value of the credit upfront, as a guarantee against possible defaults. Farmers were expected to contribute 20% of the input cost (against 50% in NAIVS), leaving banks to bear the risk on the remaining 30% of the cost. Farmers are also expected to agree to market their produce through a designated trader or warehouse, allowing the banks to first be repaid. Several issues, including limited interest of local banks and delays in government’s advance funding of the programme slowed down the start-up and expected outreach. Crops inputs (seeds and fertilizers and agrochemicals) 160. Seeds. The effective potential market demand of improved seed in the country is estimated at about 60,000 tons per year, while the current availability of improved seeds (mainly maize and rice) is 35,352 tons. Only about 25% of farmers are using improved seeds, mainly due to inadequate availability and accessibility of improved seeds, but also low awareness on improved varieties/technologies adapted to their farming conditions. 161. Fertilizer and agrochemicals. Although fertilizer use was increased and private distribution networks developed by NAIVS support, the level of fertilizer use remains low, especially for basal fertilizer. Integrated soil fertility management needs to be fully integrated into AR4D as extension activities towards more efficient use of fertilizers while enhancing soil fertility and health. In addition, the use of agrochemicals (herbicides, pesticides, etc.) remains limited and intensive agrodealer and farmer training and technical advice is required to allow for efficient, sustainable and safe use of recommended pesticides. 162. Improved availability and use of improved seed and fertilizers by smallholder farmers. Building on former targeted actions, this objective will be achieved by: (i) strengthening farmers awareness on improved seed and fertilizer (flyers, leaflets, radio/TV, training, demonstrations, etc.); (ii) strengthening production of Quality Declared Seed (QDS), especially for species not (yet) considered by the private sector, by training, access to quality foundation seed and small equipment; (iii) strengthening the agrodealer network by annual technical, management and safeguard training; (iv) supporting ASA to enhance private/farmer seed business and the production of quality basic seed (collaboration with ARIs); (v) supporting the national seed committee and variety release committee; and (vi) facilitating the seed trader association and information exchange in the sector; and (vii) strengthening agricultural inputs regulatory services (i.e., TOSCI) for quality assurance. 163. Considering the economic efficiency of targeted (smart) subsidies, the Government of Tanzania is considering another cycle of time-framed input subsidies, but targets and modalities are not yet fully defined. Although electronic vouchers (e-voucher) simplify implementation (including decreasing subsidy levels over time), follow-up and governance of the operation75. Furthermore, a similar approach could be used for other inputs such as agrochemicals including veterinary drugs (e.g., acaricides), but also services such as mechanization services (land preparation, seeding, threshing, etc.) to enhance farmers’ access (demand) and business development (offer) for PSPs. Although LGAs will 74 Credit interest is subsidized, while farmer pay the full price, 20% at planting and 80% after harvest. 75 The Ministry of Agriculture will continue promoting input utilization by subsidy through bank loans (discussion with commercial banks are underway). Meanwhile, the ministry will also continue to promote input subsidy through the voucher scheme until the above is in place (i.e., parallel operations for some time). ASDP II is expected to target both farmer organizations and individual farmers, with a focus on FOs in connection with ‘priority commodity’ interventions. 73 Agricultural Sector for Industrial Development be final beneficiaries of subsidies, there is a need for technical support from the national and regional level to: (i) organize solid and harmonized subsidy systems; (ii) coordinate actions between public and private stakeholders at all levels, including linkages to other CVC supports; (iii) provide technical advisory and backstopping support for implementation; (iv) strengthened agricultural research and advisory services to increase efficiency of farmers’ input use within an integrated management approach; and (v) implement the M&E system of the subsidy system. 164. Strengthened Agricultural Input Regulatory Services to ensure availability of quality seeds and fertilizer. Seed regulation and quality control is carried out by TOSCI while fertilizer regulation and quality control is done by Tanzania Fertilizer Regulatory Authority (TFRA. Within a results-based agreement, TOSCI need to be further76 supported for: (i) the International Seed Testing Association (ISTA accreditation (by 2018) to ensure that seed produced and certified in the country meet international standards; (ii) establishment of new centres in Mtwara (South) and Tabora (Centre) by 2019; (iii) training of district seed inspectors and staff; and (iv) office and laboratory facilities. Furthermore, the support to TFRA will include: (i) office facilities within the Ministry of Agriculture premises to deliver its services; (ii) fertilizer testing laboratory or a memorandum of understanding with the specialized laboratory at the Mlingano Research Institute; (iii) training of TFRA staff and district fertilizer inspectors; and (iv) recruitment and on-the-job training of competent inspectors. 165. The regulatory framework needs to be strengthened to control quality and safe handling of products and their residues. Support activities should also cover the Office of Registrar of Pesticides and Plant Health Services (PHS) which is responsible for enforcing the Plant Protection Act dealing with pesticides management. Moreover, as part of ensuring stakeholders awareness on the existing ago- inputs legislation, it is expected that training of law enforcers should go together with stakeholders’ awareness creation and monitoring of legislative compliance. 166. The Plant Health Services mandate aims at minimizing crop losses at pre- and post-harvest levels mainly from outbreaks of pests such as the red locust and quelea birds. Control and surveys are conducted jointly by the government and international organizations. The mandate of PHS includes the management of pest outbreaks, promotion of IPM and enforcement of the Plant Protection Act (plant import/export control, plant quarantine and phytosanitary services, pesticide registration and management regulations). The existing capacity of the phytosanitary services in Tanzania has several gaps in terms of infrastructure and human resource capabilities that need to be addressed for improved compliance of crop standards. 167. The specific objective of proposed PHS activities include to: (i) control pests and diseases to minimize pre- and post-harvest crop losses; (ii) deploy pest management strategies and approaches that will enhance crop production and protect the environment; (iii) enforce regulatory measures that will limit introduction and spread of pests to promote production and sustainable internal and export market access; (iv) improve and strengthen pesticides management technologies for safeguarding human health and the environment; (v) provide technical contributions towards harmonization of the regional (East African Community (EAC)) phytosanitary law and regulation frameworks and their application; and (v) empower PHS staff with new skills to facilitate them for efficient service delivery. 168. Action areas for achieving these objectives are: (i) capacity building for PHS staff; (ii) strengthening the capacity of Plant Quarantine Inspectorate Services; (iii) strengthening procedure for pest listing and managing surveillance data; (iv) strengthening pesticide management system including residues; (v) development and use of IPM technologies; (vi) institutional reform to harmonize institutional set- up of legislation; (vii) strengthening early warning, management and monitoring of outbreak pests; (viii) strengthening the management of mycotoxins (e.g., aflatoxins in cereals for food and feed); and (ix) strengthening early warning and management of invasive species. Livestock and fish inputs 169. Overall, priority action areas for improved availability and farmer access to quality livestock and fish 76 Most of these supports were already provided under former programmes such as AFSP, EAAPP. 74 Agricultural Sector Development Programme II (ASDP-II) production factors, including breeds/fingerlings, production inputs and health/veterinary drugs have been summarized, as shown in Table 25. Table 25: Priority activities livestock/fisheries access to inputs Action/investment areas Priority activities ANIMAL/FISH FEEDS Animal feeds and additives for increased productivity - Promote quality animal feed production, processing and marketing - Quality control of animal feed (laboratory services) - Promote agro & industrial by-products as animal feed resources - Access to quality animal health/veterinary drugs/devices - Improve safety for animal product consumer - Control mycotoxins in animal feed and fish meal Quality/quantity fish feeds and seeds for increased productivity - Facilitate private sector to produce quality and quantity fingerlings - Update fish feeds and hatchery construction guidelines ACTIVITIES LIVESTOCK/FISH DISEASE CONTROL & VETERINARY PUBLIC HEALTH Trans-boundary animal diseases (TADs) controlled for sustainable industry - Facilitate livestock health certification - Equip zoo-sanitary check points - Strengthen capacity for epidemiological surveillance of TADs - Strengthen laboratory capacity for TADs detection - Public awareness & conduct vaccination campaigns of priority TADs - Capacity of early warning detection and response - Strengthening laboratory capacities for detection of TADs Parasitic & vector-borne diseases - Promote control of parasitic and tick-borne diseases (opportunity for targeted acaricide subsidy) - Promote East Coast Fever (ECF) vaccination - Acaricide subsidy for area-wide IPM - Control of tsetse and trypanosomiasis - Strengthen laboratory capacity for vectors and parasites detection Veterinary public health - Strengthen zoonotic control to safeguard human health - Increase public awareness on important zoonosis - Enhanced monitoring, surveillance of food-borne and zoonotic disease Farmed aquaculture products - Implement fish and other aquatic diseases surveillance - Monitoring of farmed fish and other aquatic diseases - Training on farmed aqua-products and fish feeds import risk analysis - Training on imposing biosecurity system in seaweed and fish farms Fish quality control and fisheries protection - Equipping Nyegezi quality control laboratory - Equipping fisheries protection outpost stations - Capacity building, including on early warning detection and response 170. Improved availability of acaricides, veterinary drugs and vaccines for livestock farmers to ensure improved disease prevention and resilience. The government established a vaccine production facility at Kibaha (Coast) in 2012. This facility currently produces three types of vaccines: (i) Newcastle disease vaccine strain I-2 (about 4 million doses/month or 50% of needs); and (ii) anthrax and blackquarter vaccine (10,000 doses/month each). The current production is low due to lack of automated equipment and qualified personnel. The production of vaccines will be supported by: (i) providing specialized equipment for vaccine production; (ii) specialized training of personnel; (iii) building and equipping the quality control unit; and (iv) developing infrastructures for vaccines research and production. Livestock vaccines are generally considered as a ‘public good’, and their use could be enhanced under well targeted subsidy programmes. 171. Strengthened veterinary services by establishing more veterinary service centres in each administrative division by: (i) encouraging private sector investments (innovative tax incentives and/ or grants) to complement the government’s efforts in providing livestock husbandry and veterinary services at local level to increase the number of cattle dips, artificial insemination centres, vaccination facilities and hatcheries (poultry); and (ii) promoting the establishment of community cells to share facilities for poultry hatcheries, cattle dips, improved bulls, insemination and vaccination facilities. 172. Sustainable fisheries development will be considered within an ‘ecosystem approach’ involving: (i) support services skill development for improved sustainable fisheries; (ii) sensitization and awareness 75 Agricultural Sector for Industrial Development creation among fisher folk; (iii) review of pelagic fishery management plan; (iv) conduct of MCS operation for licensing and registration of vessels; (v) value addition to fish/fisheries products; and (vi) registration and capacitation of all BMUs, fishery associations, etc. Subcomponent 2.3: Agricultural Research for Development (AR4D) 173. The specific objective under this subcomponent is to improve technology generation delivery systems responsive to farmer needs and market requirements, which will contribute to increased and sustained productivity and production of priority commodities (crops, livestock products and fishery). Targeted outcomes to be achieved are: (i) improved technology generation delivery systems responsive to farmer needs and market requirements which will contribute to increased and sustained production and productivity of priority commodities (crops, livestock, fishery); (ii) enhanced support to technology dissemination systems through strengthened research- extension linkages; (iii) build capacity of semi-autonomous research institutes in human and financial and physical (infrastructures, equipment) resources; (iv) consolidate participatory identification, implementation and evaluation of research involving a broad spectrum of stakeholders; and (v) enhanced collaboration with regional and international research institutes including the Consultative Group for International Agricultural Research (CGIAR) and the private sector. 174. Building on participatory approaches developed under ASDP-1, AR4D investments will include strategic and demand-driven adaptive research agenda/activities focused on priority CVCs for crops77, livestock and fish products within each AEZ. Further to a consultative role to the PPP for adaptive research and technical support, the sub-component will support adaptive research activities and address priority CVCs technology needs for productivity impact, within sustainable production systems based on: i. Enhanced client-oriented and demand-driven adaptive technology generation to broaden users’ technology options, with emphasis on crop and livestock78 breeding/selection, enhanced breeder seed/ breed supply, sustainable natural resource management (soil and water), climate smart production practices, integrated pest management (IPM), integrated disease management (IDM) and post-harvest practices, including client needs for value addition, nutrition issues (bio-fortification) and reduced post- harvest losses. Zonal Agricultural Research and Development Funds (ZARDEFs), established during ASDP-1, will be used to channel financial support to user-selected demand-driven adaptive agricultural research projects focused on local priority CVCs79. This competitive fund is open to public and private researchers for client-oriented research, based on zonal research priorities. ii. Strengthened coordination and networking for priority CVC research at national, regional and international levels to source adapted technologies. This will be achieved by enhanced networking with the Consultative Group for International Agricultural Research (CGIAR) and other international, regional (applying the subsidiarity principle) public and private (i.e., seed) research institutions to source technologies adapted to the needs of local systems and global changes. Furthermore, national level AR4D coordination and networking for targeted CVCs and cross-cutting thematic80 areas (food and nutrition, integrated NRM, climate change, gender -sensitivity, etc.) will be strengthened by regular information exchange and research platforms for targeted priority CVCs at zonal and national level, including annual AR4D planning, programme review with stakeholders and evaluation workshops. 77 Limited complementary support for rice, as this crop is already being supported by the EAAPP. 78 Including research for livestock, aquaculture, transformation/value-addition [TARI, TALIRI, etc. under the Ministry of Industry Trade and Investment (industrial research, TIRDO, etc.] as per identified zonal priority commodities. ASDP II will not cover all ASLM research needs, but rather adaptive research that directly/ indirectly supports the focus CVCs. 79 About five and three AR4D projects per AEZ per annum for crops and livestock respectively. 80 i.e., Sustainable crop/livestock production systems and technologies natural resource/land use management (conservation agriculture), climate smart agriculture, post-harvest losses and nutrition issues by breeding for nutrient rich varieties, etc.). 76 Agricultural Sector Development Programme II (ASDP-II) iii. Improved user access to adapted technology options by strengthened research–extension linkages and technical and economic81 information management and communication. This will be achieved by zonal Technology Transfer and Partnership Units (TTPU)82 and more effective agricultural information management and communication of available technologies. The TTPU teams (crop/livestock technical and information specialists) will be empowered to act as strong links between zonal research teams and District CVC stakeholder Platforms (DCP) and designated crop, livestock and fish AR4D liaison officers (see s/c extension). The delivery capacities of TTPU teams in each AEZ will be strengthened in terms of human and technical capacities to handle knowledge and linkages between AEZ research network and the district agricultural facilitation team83 for crops and livestock, as well as the stakeholder innovation platform for priority CVCs. The zonal technology inventory will be updated and diffused while on-farm research and demonstration programme will be up-scaled for targeted CVCs in focused district clusters. Socio-economic capacities will be integrated into the technical teams to generate further knowledge on socio-economic characterization of farming systems, micro-level policy options, market efficiency and modelling of impacts generated by broader farmer use of improved technologies. Table 26: Crop and livestock research institutes in AEZ AEZa Crop AR4D Livestock/fisheries AR4D TALIRI TAFIRI Arid Selian & HORTI Tengeru Mpwapwa, Mabuki & Kongwa Mwanza & Kigoma Semi-arid (N&S) Makutupora, Hombolo, Ilonga, Dakawa Mpwapwa Kongwa, Naliendele Eastern coast & alluvial plains Mlingano, Mikocheni, Kibaha, Naliendele, Uyole, Katrin Dakawa Tanga + TVLA DSM (Kibaha & Temeke) TAFIRI–DSM Plateaux Uyole, Ukiriguru, Tumbi (b) Mabuki and Uyole Mwanza & Mara Northern highlands (bi) Selian & HORTI Tengeru West Kilimanjaro Mwanza and Mara Southern highlands Uyole & Kifyulilo (c) Uyole Mbeya& Kigoma; Western and SW highlands Maruku & Tumbi (d) Mabuki Kigoma /a AEZ adapted from Sokoine University of Agriculture, 2014. The National Livestock Research and Development Agenda (2015), Fisheries and Development Research Agenda (2015). iv. Effective agricultural information management and communication of available technologies will be promoted, using modern ICT at national and local levels. AR4D will contribute by: (a) establishing a national innovation sharing platform between agricultural research and extension; (b) compiling an updated technology information database; (c) adapting available technical information to the user community needs (farmers, entrepreneurs, agricultural training institutions, NGOs and others); and (d) facilitating users access through modern ICT (internet and mobile) for information exchange and learning processes (e-learning). This will require investment in effective communication infrastructure and human resources for developing innovative technology adaptation and dissemination pathways. 81 Partial investment budget analysis for farmers to make informed choices. 82 An alternative zonal AR4D structure to be implemented under TARI: the TTPU would take over (and consolidate) the functions implemented by Zonal Information and Extension Liaison Units (ZIELU) under ASDP-1. This arrangement fits well under the proposed restructuring of Crop Research Department under MAFC into the TARI, where TTPUs will continue to use the current Department of Research and Development innovative participatory approaches to engage its stakeholders along the zonal priority CVC. Within each AEZ, the TTPUs will include all Agricultural Research Institutes based within the respective zone, and strengthen the AR4D linkage with districts focal person, promoting agricultural technology transfer, and users. 83 The District Agricultural Facilitation Team includes the DAICO/DLFO and the technical subject matter specialists for crops, livestock, fish and rural development active at district level. 77 Agricultural Sector for Industrial Development v. Upgrading selected AR4D institutions towards sustainable research and development support for priority CVCs by: (a) contributing the institutional strengthening of Tanzanian Agricultural Research Institution (TARI); Tanzania Veterinary Laboratory Agency (TVLA), Tanzania Livestock Research Institution (TALIRI) and Tanzania Fisheries Research Institute (TAFIRI); (b) strengthening human resources for research and technical staff for crops, livestock and fisheries, based on capacity gaps and needs for CVC to be identified through a training needs assessment; (c) targeted support for priority research infrastructure and field and laboratory facilities and equipment of selected zonal ARI, TVLA, TALIRI, Livestock Training Agency (LITA), Fisheries Education and Training Agency (FETA) and TAFIRI; (d) promoting public/private partnerships84 towards sustainable funding mechanisms for agricultural research through ZARDEF; and (e) strengthening efficient linkages between TTPUs and district agricultural support teams for crops, livestock and fish. Among others, biotechnology (marker assisted breeding, genetic engineering, diseases diagnostics, bioinformatics, genomics, proteomics, gene tilling and metabolomics) will be an important cutting-edge science and researchers capacities need to be built in this area and related biosafety and biosecurity issues. In this and other high-tech areas, regional cooperation (e.g., EAC) will be sought to enable for higher efficiency on solving common issues and sharing of results85. 175. Effective planning, implementation, monitoring, evaluation86 of AR4D are important prerequisites to effective and quality research. Stakeholder involvement in research agenda planning, but also monitoring/evaluation is key for high quality and relevance. Therefore, ASDP II will track and assess the extent of use and effectiveness of research outputs at sector level and get feedback on adoption and impact of proposed technologies. 176. Livestock and Fisheries Research. The Directorate of Research Coordination, Training and Extension (DRTE)87 coordinates livestock and fisheries research implemented in accordance to the mandates of the TALIRI, TAFIRI and other research institutions such as the TVLA, the Tanzania Commission of Science and Technology (COSTECH), Sokoine University of Agriculture (SUA), LGAs, Dairy and Meat Boards, NGOs/community based organizations (CBOs) and other relevant stakeholder where research is undertaken. The coordination is also extended to all collaborative livestock and fisheries research activities in international research institutions/organizations. The priorities for livestock/ fisheries research across AEZs’ were identified as shown in Table 27. Table 27: Livestock and fisheries priority investment and action areas for research Action areasa Priority actions/activities Dairy cattle - Improved technologies for dairy productivity by breeding - Promote selection, use and conservation of indigenous livestock - Disease diagnostics & prevention and control of disease vectors/pests and pathogens Beef cattle - Improved beef productivity by breeding/selection, conservation of indigenous germplasm— genetic resources - Disease diagnostics & prevention and control of disease vectors/pests and pathogens Sheep and goat - Improved sheep and goat productivity by breeding/selection, conservation of indigenous germplasm—genetic resources Pig - Diseases and feeding Poultry (meat/egg) - Prevention and control of diseases and testing for quality feeds 84 The district CVC platform facilitates the dialogue among major commodity actors (producers, traders, processors, etc., public and private service providers (including research and extension) to develop a common strategy and work plan to improve the performance of targeted CVCs) 85 See the achievements of the EAAPP and regional collaborations with ASARECA. 86 Output indicators to be developed in Programme implementation manual and linked to intermediate outcomes. 87 DRTE coordinates planning, implementation, monitoring, technology dissemination and impact assessment of technical and socio-economic livestock/fisheries research programmes (including animal health and disease management, maintains a livestock and fish research database and promotes the dissemination of innovations. 78 Agricultural Sector Development Programme II (ASDP-II) Feed resources - Research on pasture and forage production Animal disease - Research on disease prevention and control/quality of animal diseases vaccines - Research on vectors, parasites and disease pathogens; control livestock inputs/outputs - Development of diagnostic kits and other biologicals Fisheries - Research on stock and catchment assessment and frame survey - Impact of human activities to water resources, including illegal unreported and unregulated fishing (IUU) - Research on reduction of post-harvest losses in sardines - Improved fish handling, storage, processing & distribution technologies and facilities - Impact of different processing technologies on nutritional value of the fish - Fishing gear technology, methods and crafts - Research on restocking in minor waters - Marketing processes and study on fish consumption pattern within the country - Research-extension linkages Aquaculture - Fish feed production and quality assurance; potential farmed species - Fish breeding, genetics, and biotechnology, hatchery technologies & quality assurance - Aquaculture system modelling - Research–extension linkages a Main investment elements are rehabilitation and consolidation of infrastructures and research facilities (ponds, cold rooms, water catchments, vaccine production, smoking/processing facilities, etc.), short- and long-term capacity building, and purchase of parent stocks (breeding bulls, bucks, does, poultry, fingerlings). Subcomponent 2.4: Access to mechanization services 177. The low level of mechanization88 is a major constraint towards increased smallholder productivity and production. GoT efforts for promoting mechanization, include: (i) tax exemption for importation of farm machinery and spare parts; (ii) public finance from AGITF and TIB-Agricultural window and commercial banks to extend loans for purchase of tractors and machinery; while (iii) some active savings and credit cooperative societies (SACCOS) provide loans to its members for purchasing agricultural machinery. Within this framework, ASDS-2 proposes the following required interventions: (i) collaborate with private sector on promotion of mechanization through demonstrations of modern technology (tractors, power tillers, harvesters, etc.) and simple farming implements and tools such as weeder, seed-distributor, etc.; (ii) facilitate agricultural financing services for agricultural mechanization; (iii) support educational institutes for producing qualified mechanical engineers needed in the sector; and (iv) create favourable business environment for importing agricultural machinery and spare parts and for domestic marketing. 178. Mechanization is critical to addressing labour bottlenecks and low productivity (production and post-harvest) and poor timing of critical farming operations (seeding/planting, weeding) among smallholder farmers. Intensification and growing cropped areas require mechanization to allow for optimal timing of operations and reduced drudgery in production and in post-harvest operations. Mechanization will need to be adapted and sustainable, while gradually progressing with farmers’ technical level and the size of the farming enterprise. Based on supports initiated under ASDP-1, further investment in agricultural mechanization will be facilitated, including by farmer organizations and the establishment/strengthening of privately owned mechanization service providers (commercial services) for increased sustainability. In addition, there is need to enable smallholders to use labour saving technologies such as zero or minimum tillage. 179. The initial interventions on mechanization will focus on building the financial and economic case of mechanization and developing the regulatory enabling environment to facilitate the emergence and growth of private sector tractor and mechanization services. The programme will also ensure that legislation is in place to facilitate leasing and the ability to use non-fixed assets as collateral, so that the private sector has multiple instruments to facilitate their investments in agricultural mechanization. 88 14% using tractor (including 2-wheel tractor) services and about 24% oxen (Source: Agric. Policies 2013). 79 Agricultural Sector for Industrial Development 180. The objective is to facilitate access to adapted agricultural mechanization89 services to increase labour return towards sustainable productivity, value addition and farmer income. Support to private mechanization services (production, post-harvest and transport) will enable smallholder producers to increase their labour productivity, use sustainable soil management techniques, but also to increase the attractiveness of the sector for young entrepreneurs (‘agripreneurs’) and rural youth. Smallholder access to private mechanization services will be enhanced by updating the national strategy for sustainable agricultural mechanization90, including the regulatory framework for sustainable and profitable private service arrangements. Innovative approaches (including leasing), bringing together the tractor/equipment companies, commercial banks and mechanization service providers should be facilitated to allow for increasing the business of current service providers and allow for new entrants where opportunities exist. 181. Further to the policy and institutional framework for labour-saving technology (see s/c 4.1), ASDP II will promote improved farm and environmental management practices that reduce farm energy inputs and costs, protect the soils and environment and produce good crops, livestock, fish and other farm produce. Main activities will include: a. Strengthen the demand for mechanization services in agricultural production and post-harvest operations by demonstrations, sensitization campaign and smart subsidies (vouchers) to raise farmers’ awareness for sustainable agricultural production and productivity growth. b. Improved farmer group or cooperatives access to small-scale mechanization options, including two-wheel tractors and oxen-drawn equipment for production, post-harvest handling and transport. c. Enhancing supply of viable private mechanization services for increased productivity and production through strengthening existing successful contractors, building on business case/repeatable business model and new business models (leasing, triangular contracts between importers, financial institutions and mechanization service providers, etc. that encourage agricultural mechanization through leasing arrangements and other financial supports for leveraging private sector investments in technology innovations. d. Capacity development for equipment/machinery information acquisition and evaluation for sustainable agricultural mechanization (conservation agriculture tools) service provision, operation and maintenance (resource and training centre). 182. This strategy will be developed during the first year of the programme, and implemented from the second year onwards athrough axes: (i) stimulating private service offer by access for stakeholders in the mechanization chain to professional training and technical information on equipment/machinery operating a sustainable agricultural mechanization resource and training centre; and (ii) increasing demand for adapted agricultural mechanization services by subsidies (i.e., targeted vouchers) to facilitate the purchase of adapted implements for small-scale mechanization (oxen/two-wheel tractors) and to access to private mechanization services for production and postharvest operations. 183. Human resource development and setting-up a reference centre for agricultural mechanization could be implemented through a network of selected ATIs or a specialized training centre networking with selected ATIs for training mechanization technicians and tractor operators. This would allow for breaking the vicious cycle of poor operation capacities, breaking machines, little reparation capacity and lack of spare parts and finally no successful business for entrepreneurs. Developing business should allow for tractor importers to set-up regional selling and reparation units. Furthermore, from the beginning, mechanization service investors should be encouraged to equip themselves with conservation agriculture tools and equipment for sustainable soil management (see also s/c 1.1). 89 Sustainable mechanization is to increase the use of labor-saving technologies, including appropriate mechanization of production (conservation farming in s/c 1.3), value addition (see s/c 3.3 on agro-processing) and other farm management related operations. 90 Targeting sustainable soil management within the framework of conservation agriculture (see also ‘Save and grow’, FAO 2012) 80 Agricultural Sector Development Programme II (ASDP-II) Sub-component 2.5: Food and nutrition Security 184. Food security and nutrition91 takes several forms, all of which affect the quality of life and productivity of rural people. Chronic, transitory and emergency food insecurity due to poor agricultural productivity, food inaccessibility and natural disasters all play a role. The Comprehensive Food Security and Vulnerability Analysis in Tanzania (2012) found that in 2010–2011 about 730,000 households (8%) were vulnerable to food insecurity, of these around 150,000 households (or 2% of all households) were considered as chronically food insecure. Northern and central regions were the worst affected and the level of food insecurity in some areas was high as 45%. Food security is highly dependent on rainfed agriculture which also is susceptible to the vagaries of weather, especially poor rainfalls prompting for regional food shortages. Therefore, there is need to promote and embark on irrigated agriculture and diversification of crops (drought resistant crops) for greater reliability of food supplies. Malnutrition is one of the most serious constraints to human and economic development: chronic malnutrition in 2010 was very high with 42.0% stunting (DHS, 2010) of children younger than 5 years of age being stunted. Severe acute malnutrition is a rampant in Tanzania, especially among children under five and women of child bearing age. Child malnutrition is much worse in rural areas than in urban areas and much higher in the poorest quintiles, resulting from inadequate consumption and/or utilization of food. This is caused by inadequate knowledge on nutrition, food preparation and dietary practices, especially for children, and by women’s heavy workload. 185. The National Food Reserve Agency (NFRA) was initially set up as a food reserve. The NFRA now serves as a buffer stock in an attempt to keep farm gate prices up despite good92 harvests. NFRA buys significant quantities of maize (300,000 tons in 2014) frequently at above-market prices from farmers. NFRA is likely to introduce more distortions in the sector, leasing some storage capacity from the private sector and thereby be reducing the ability of the private sector to even out seasonal fluctuations93. 186. Policy measures94 to mitigate effects of possible food price spikes and food insecurity for vulnerable population segments will be increasingly important for stable socio-economic development. The Government of Tanzania will adopt measures to improve food access, including: (i) strengthen and improve the quality of Crop Forecast and Early Warning systems, within the overall framework of agricultural statistics; (ii) strengthen food reserve and distribution system by NFRA including improvement of storage facilities and effective collaboration with the private sector; (iii) regulate according to necessity food imports, with careful considerations on the food demand and supply; (iv) establish an active link with member countries in the EAC and SADC for monitoring regional food security situation, including use of Tanzania’s food for emergency operations in the region. 187. Safety nets. Natural disasters in the country include drought, heavy rain followed by flood, migration of disease and pests for crops and livestock, deforestation, soil degradation, among others. Crop and livestock production are directly affected by disasters, especially for smallholders at the limit of acute and/or chronic food insecurity and poverty. Impacts of climate variability and change are expected to become more significant in the future therefore immediate actions are required toward increased resilience in agriculture (see preventive measures in s/c 1.3). For preparedness and quality response to natural disasters, required interventions include: (i) improve the Crop Forecast and Early Warning system as well as pest and disease surveillance system for early detection; (ii) coordinate the country’s meteorological information collection and sharing system; (iii) respond effectively to the warnings and improve the preparedness for emergency disasters; (iv) strengthen the collaboration with relevant organizations on migratory diseases and pests for early detection and effective and coordinated response; and (v) coordinate safety net activities in the agriculture sector to ensure vulnerable households needs are addressed. 91 Food security means that all people at all times have physical and economic access to adequate amounts of nutritious, safe, and culturally appropriate foods, which are produced in an environmentally sustainable and socially just manner, and that people are able to make informed decisions about their food choices. 92 Source: Agriculture Sector and Public Expenditure Review—Tanzania Mainland 2014 (March 2015). 93 See further details in ASR-PER section. 94 See details in ASDS-2 (June 2015). 81 Agricultural Sector for Industrial Development 188. Nutrition Security. Malnutrition is often inherited from one generation to the next: maternal malnutrition negatively affects the consequent educational achievement and improved productivity in adulthood. The effects of malnutrition are also magnified by unsafe drinking water, poor hygiene, and lack of information and education on good nutrition and sanitation. Achieving nutrition security requires concerted multi-sector actions, including: (i) promote awareness among rural households, especially focusing on child and maternal malnutrition, good nutrition and sanitation; (ii) more effective use of nutrition officers at local level who can be part of agricultural extension service and training on nutrition aspect under the DFT; (iii) strengthen and scale up food fortification of micronutrient; (iv) provide effective social safety net programmes95 for vulnerable groups who chronically require protection against shocks (food/cash for work); and (v) enhance collaboration with related ministries on the school feeding programmes in rural areas where needed. 189. Food security and nutrition are mainstreamed in several sector policies, strategies and programmes (i.e., the Tanzania Agricultural Investment Plan, the Tanzania Social Action Fund (TASAF) or the Productive Social Safety Net, etc.). Within the Scaling Up Nutrition (SUN) movement, there is high level political attention to nutrition in Tanzania spearheaded by the High Level Steering Committee on Nutrition (HLSCN), which brings together permanent secretaries from nine relevant sectors, development partners, UN agencies, CSOs, university and business. A multi-sector Nutrition TWG chaired by the director of the Tanzanian Food and Nutrition Centre (TFNC) supports the HLSCN. All partners are fully engaged in scaling up nutrition efforts and participate in MSIP. 190. The objective of this sub-component is to ensure sustainable food security and nutrition in Tanzania by involving all stakeholders in implementing strategies geared at ensuring food security and nutrition at all levels. The focus will be on ensuring sustainable food availability96, food accessibility97 and proper food utilization to be achieved through food production, stock management, trade/markets and adaptive strategies/measures against negative effects of disasters. Main strategic sector supports are centred on 4 action areas: (i) crop/livestock monitoring and early warning for increased food security; (ii) strategic NFRA; (iii) post-harvest management for reduced food loss; and (iv) contributions to nutrition improvement. 191. Crop/Livestock monitoring and early warning98. Since 1992/1993, the then MAFC developed and operated the food security assessment procedure, initially seasonally using a sample survey questionnaire. This was later expanded into use of a routine data retrieval system. Over time, sample surveys using the National Master Sample (NMS) from NBS have been used to address the challenges in district estimates through the routine reporting system. Initial interest was on forecasting and informing the government and the public, through AGSTATS for Food Security documentation (preliminary and final forecasts), other monthly food security situation and decadal rainfall reports. However, the system has been instrumental in providing basic data for the management of food and for the agriculture sector as a whole. 192. The Integrated Food Security and Nutrition Assessment System (IFSNAS), which is known in Kiswahili as Mfumo wa Uchambuzi wa Uhakika wa Chakula na Lishe (MUCHALI), , is to: (i) ascertain the impact of the food production shortfall from the year (x-1) on the livelihoods and food security and nutrition among the populations in LGAs previously identified by the then MAFC, MLFD, and food security and nutrition agencies; (ii) identify the food insecure and vulnerable populations resulting from the food access problems in year (x) and establish the magnitude of the problem; and (iii) determine and recommend appropriate interventions for the affected populations. 95 For example, TASAF (Tanzania Social Action Fund) to be aligned with agricultural interventions for sustainability. 96 Food availability means ensuring sufficient food for all people through production, stocks and trade to be achieved through promoting food production, reducing post-harvest losses, ensuring appropriate food management at household level and strengthened coordinated food aid. 97 Food accessibility refers to the ability of household members to access food to meet their nutritional requirement, which depends on the food self-production and income level of the consumers. 98 Integrated Food Security and Nutrition Assessment System (IFSNAS), which is known in Kiswahili as “Mfumo wa Uchambuzi wa Uhakika wa Chakula na Lishe” (MUCHALI). 82 Agricultural Sector Development Programme II (ASDP-II) The methodology involves a comprehensive livelihood-based food security and nutrition (LFSN) approach using the Integrated Food Security Phase Classification to guide the analysis and report writing. The LFSN approach involves integrated broad livelihood-based indicators such as crop, livestock and fish production, supplies and prices, nutrition, access to water, livelihood assets and coping strategies, as well as weather parameters, particularly rainfall, and other livelihoods systems. In addition, the prevalence of severe acute malnutrition and global acute malnutrition is measured. Overall, the annual report is provided in a timely manner to the decision-making authorities, but some challenges in achieving appropriate levels of accuracy and reliability continue to be areas of concern to be addressed. Therefore, capacity building, rainfall data collection system, food security questionnaire1 (FSQ1), cooperation and technical meetings, and timely availability of funds, have been earmarked as critical issues to be tackled for improved implementation. 193. Safety net and resilience. A proportion of rural households will continue to need special support to help them achieve food security and protect them against shocks, principally droughts. It is expected that advancements in other areas of the ASDP II will progressively reduce the number of households requiring food aid and other forms of assistance to survive. The effectiveness of targeting social safety net programmes for vulnerable groups will be sharpened, and the prevalence of child and maternal malnutrition is expected to decline. As the size and cost of the safety net programme begins to decline, more resources will be available for disaster risk management including disaster preparedness and mitigation (see also resilience in component 1.3). Additional strategic interventions such as productive safety net and household asset protection will also be implemented to support productive investment through conditional transfers that provide pathways out of poverty via rural infrastructure development, market access, agricultural productivity improvement, education, health care and other services. 194. NFRA and capacity of strategic food reserves. The capacity of strategic food reserves (on recurrent government budget) needs to consider: (i) an appropriate level of stocks to hold; (ii) transparent protocols and rules for the acquisition and release of stocks, stock rotation, and the use of financial instruments to complement physical stockholding; and (iii) policies and procedures for dealing with food price spikes of the type currently being experienced. Furthermore, higher levels of production systems resilience, transparent food crops markets and contracts with the private sector should allow for gradually decreasing levels of physical NFRA food reserve stocks to the minimum required level. Finally, the linkages between NFRA and crop forecast/early warning (improvement of an integrated system)—accuracy of data including private sector and farmer stocks—need to be strengthened by an efficient information exchange and stakeholder decision-making system. 195. Develop Livestock Early Warning System. For the livestock and fisheries sector, early warning against potential shocks is key to enabling the government to take appropriate measures to mitigate major impacts, especially on small-scale farmers. This includes among others the implementation of priority actions such as: (i) awareness creation among pastoralists and agro-pastoralists on mitigation and adaption strategies; (ii) training of district and community monitors for data collection; (iii) resource mapping, selection and setting of livestock safety net zones and sites, and purchase of equipment and facilities; (iv) training for new staff, refreshment courses for ongoing staff at headquarters and local level (community livestock early warning); (v) retooling towards field efficiency, data processing and analytical capacity; and (vi) efficient and cost effective monitoring system of pasture, water and animal feed resources. 196. Livestock feed security and resilience against shocks (see also s/c 1.3) will gradually be improved by: (i) construction of 10 dams, 20 boreholes and 20 charcoal dams; (ii) rehabilitation of 4 dams, 20 boreholes and 50 charcoal dams; (iii) reinforce and strengthen animal feed inspectorate services; (iv) training of pastorals and agro-pastorals on feed conservation and utilization; and (v) grazing land management plans in demarcated grazing lands in 40 LGAs. 197. Post-harvest management for reduced food loss. Post-harvest management systems target to achieve effective and efficient food and nutritive supply by addressing key issues between production 83 Agricultural Sector for Industrial Development and consumption of agricultural commodities. High post-harvest losses remain a central concern, as different research studies demonstrate that farmers lose up to 40% of produced cereals, although losses vary by crop type and geographical zone. The main issues are physiological degradation and infestation by fungus, insects and rodents during transportation, storage and processing, especially for highly perishable products (see component 3.2). There is a need to harmonize and align functions and support between the ministry’s department responsible for Food Security and the Ministry of Industry Trade and Investment, especially for activities related to storage infrastructure and management, reduction of post-harvest losses, value addition and processing agricultural products. 198. Contribution to integrated nutrition improvement. The National Nutrition Strategy (NNS), finalized by the Tanzania National Food Centre (TNFC), addresses high levels of chronic malnutrition by working with multiple sectors and across government agencies. The NNS recognizes that increased food production does not necessarily translate into improved food security and nutrition outcomes, as households must also be provided with information and education about good nutrition and sanitation practices. Besides emergency support, additional interventions such as productive safety net and household asset protection will also be implemented by supporting productive investment and appropriate food preparation and utilization of nutrient rich food is key to improve food utilization levels. Within a cross-sectoral approach, better integration of dietary diversification and changes in nutrition behaviour will be integrated into all rural sector programmes, including education and health. In addition to producing more and better food, rural households, which are especially vulnerable, need to understand how to use the food that they have in the best possible way. 199. Better integration of dietary diversification and nutrition behaviour change into all agriculture sector programmes. Rural households need to understand the importance of diet in overall well- being and have the knowledge to use the food that they have in the best possible way. In this context, there are potential tensions between policies that encourage agricultural commercialization (often involving increased specialization) and the need to maintain diversification of farming systems and diets. Other aspects of food and nutrition policy include food safety and food fortification: current standards need to be improved including microbiology, pesticide residues, labelling standards and safe storage and transport. The food safety and new food fortification standards for oil, wheat and maize flour (and other food and indirectly feeds) need to be enforced: this is also important in accessing export markets and will be increasingly important in maintaining a competitive position in the high end of the domestic market. The summary of proposed interventions for food security and nutrition is given in Table 28. Table 28: Proposed action areas for food security and nutrition Action area Proposed activities & investments 1. Early Warning System for improved food security Strengthened institutional capacity to undertake crop and livestock forecasting tasks and improved working environment i. Long-term training for new staff, refreshment courses for ongoing staff and hands on training retreats for all ii. Retooling towards field efficiency, data processing and analytical capacity Rainfall data collection and crop monitoring i. Assessment and evaluation towards strengthening rainfall stations to fulfil early warning system interests (timeliness, reliability and accuracy) ii. Renovate critical rainfall stations (total of about 600) throughout the country (automatic rainfall and temperature gages) 84 Agricultural Sector Development Programme II (ASDP-II) Action area Proposed activities & investments 1. Early Warning System for improved food security Food Security Questionnaire1 (FSQ1) for crop forecasting with improved data accuracy and reliability i. Improve and re-install this tool countrywide following the national master sample established in collaboration with NBS ii. Further integration of AASS, ARDS and early warning information collection iii. NMS should be correctly sized to enable acquisition of district level estimates (current regional estimates) iv. Adapt and strengthen MUCHALI timeliness and reliability Reliability and accuracy of the information for policy decision- making i. Strengthen existing cooperation between NBS and the Ministry of Agriculture (collaboration in short-term surveys) ii. Hold technical meetings with district and regional staff, strengthening of LGA capacity with support from central level Livestock/fisheries early warning and mitigation i. Training of district and community monitors for data collection; retooling towards efficient data collection, processing and timely reporting ii. Resource mapping (effective monitoring system of pasture, water and animal feed resources) selection and setting of livestock safety net zones and sites, and purchase of equipment and facilities iii. Awareness creation among pastoralists and agro-pastoralists on mitigation and adaption strategies iv. Livestock feed security and resilience against shocks to be improved by construction/rehabilitation of dams, boreholes & charco dams v. Reinforce and strengthen animal feed inspectorate services vi. Training of pastorals and agro-pastorals on feed conservation and use vii. Grazing land management plans in demarcated grazing lands (40 LGAs). 2. National Food Reserve Agency (NFRA)—Safety-nets Food reserve management i. Store and manage minimum/appropriate level of national food reserve ii. Involve private sector in food reserve management iii. Promote community safety net systems for food, feed and seeds, where appropriate 3. Reduction of post-harvest losses (see also s/c 3.2: Value addition and agro-processing) Large post harvest losses due to poor support systems/ technologies and limited handling capacity i. Develop guidelines for appropriate post-harvest handling and storage practices for selected crops ii. Promote and disseminate technologies that promote better handling and improved storage and preservation of food and food products at all levels iii. Improved transformation/value addition and marketing support infrastructure for food quality and minimized food losses (see s/c 3.2) 4. Nutrition improvement Reduce malnutrition in Tanzania by improved food and nutrition availability, accessibility, stability and utilization (Five food insecure regions) i. Mainstream awareness on food security and nutrition security issues at all levels in the agricultural sector (mainstreamed in extension) ii. Strengthen the food security and nutrition information system, data quality/ relevance and mapping for providing timely warning signals iii. Promote diversify/multiple adaptive strategies for sustainable food security of households iv. Implement productive safety net and household asset protection by use of nutrient rich food for improved food utilization levels v. Promote consumption of protein-rich food for children & pregnant women vi. Promote food fortification and blending techniques of flour to improve nutrient contents (including bio-fortification—see research) vii. Encourage cost-effective technologies to reduce women’s workload for more time for food preparation and childcare viii. Improve basic food safety especially with respect to the control pesticide residues and mycotoxins including aflatoxins ix. To empower LGA staff on the Food Security and Nutrition Analysis System (district nutrition focal person/officer to coordination all ministries) 85 Agricultural Sector for Industrial Development 200. Investment summary for Component 2: COMPONENT 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY—BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Table 29: Development budget/investment projection for Component 2 (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,913 772,652 849,529 838,081 921,148 4,693,323 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,373 9,720 9,349 8,506 9,222 41,170 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389 136,695 150,284 164,670 181,057 782,095 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176 2,652 2,800 2,962 3,141 15,731 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664 93,408 768 1,099 987 97,926 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146 4,533 5,008 4,246 4,639 19,572 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,115 5,176 7,350 4,460 2,090 23,191 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,090 50,853 48,517 6,658 4,388 165,506 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources 2,537 2,134 2,199 2,147 2,319 11,336 2.2.1.8 Improvement of plant health services 13,322 11,191 7,608 1,389 478 33,988 2.2.1.9 Production of vaccines and drugs 44,570 36,191 39,700 3,705 4,380 128,546 2.2.1.10a Improvement of livestock health services 262,550 295,128 332,216 371,559 420,078 1,681,531 2.2.1.10b Improvement of aquatic health services 1,518 1,238 1,241 1,340 1,395 6,732 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,559 29,197 29,504 8,708 9,516 84,484 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,409 16,384 11,616 11,110 11,371 62,890 86 Agricultural Sector Development Programme II (ASDP-II) COMPONENT 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY—BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Table 29: Development budget/investment projection for Component 2 (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,833 3,895 2,683 2,738 3,011 17,160 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,250 5,753 5,699 5,707 5,717 32,126 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,153 11,722 12,960 14,297 10,394 63,526 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,538 22,167 23,955 25,921 28,084 120,665 TOTAL COMPONENT 2 1,925,105 1,510,689 1,542,986 1,479,303 1,623,415 8,081,498 E. Component 3: Commercialization and Value Addition (building competitive commodity value chains) 201. Under ASDP-1, limited progress was recorded in supporting agricultural marketing and value chain development. key constraints to value chain development include: (i) agriculture remains characterized by low crop and livestock productivity and commercialization levels; (ii) limited private sector involvement in agribusiness; (iii) policies that do not allow value chains to fully benefit from regional integration; and (iv) proliferation of uncoordinated activities in agricultural value chain development with a risk of inconsistent approaches. Furthermore, at implementation level, further issues were identified such as: (i) design and implementation flaws; (ii) insufficient value chain diagnostic and mapping at local, regional and national levels; (iii) weak implementation capacities in both the public and private sector; and (iv) limited internalization of past experiences, especially for market access and market information. 202. The commercialization initiative is expected to produce fundamental changes in the structure and functions of Tanzania’s agricultural sector including: (i) increased amount of quality agricultural produce entering in the domestic and export market channels; (ii) diversification of smallholder production (and income) from higher value (non-staple) crop and livestock products; (iii) increased supply of raw materials to the industrial sector; (iv) improved farmer access to inputs and financial services; (v) stronger farmer organizations; and (vi) improved infrastructures and communications. The higher levels of commercial activity are also expected to enlarge opportunities for rural non-farm business enterprises and both farm and non-farm employment, including for youth. 203. The Commodity Value Chain (CVC) Approach. Value chain development refers to the various stages from production, processing and marketing/distribution systems of key commodities, including value addition. The approach, schematically captured in Figure 16, shows the issues faced at each stage towards commercializing and professionalizing value chain characteristics and overall performance. There is a clear focus on smallholder producers and improving their role and relationships within the value chain(s) that they belong to. Particular attention will be given to the development of the institutional capacity of smallholder organizations to negotiate and manage new marketing arrangements with private sector actors, leading to productive alliances and viable commercialization partnerships. 87 Agricultural Sector for Industrial Development Figure 20: Value chain approach of ASDP II Constraints along the Value Chain Intevention Focus Areas for ASDP 2 Activities for Commercialisation Activities for Empowerment and Organisation ASDP 2 Competitive Funds for Stakeholder business, technology Uutake, enterprise support, commodity profile marketing and organisational support Organisational support to value chain smallholder and Stakeholder - business planning, rules of engagement,through existing structures Value Chain Support (all stakholders - private and public) through activities such as technology and equipment, storage, market development, infrastructure (markets, roads, electricification,irrigation), acces to financing and quality of produce Input Suppliers Producers Market Traders and Processors Input supply shortages, timely delivery and quality Production problems and productivity Processing problems for quality and quantity and consistency Markerting to consumer - awareness, price high prices, imported commodity 204. Towards building competitive value chains, ASDP II will support smallholders to graduate from subsistence towards farming as a business, by forging linkages with commercial input and output supply chains to connect with a growing agro-industrial and urban consumers demand. A diverse, inclusive, competitive and robust private sector will spearhead the development of agribusiness, driven by improved investment climate, trade capacity and business linkages and improved capacities for advocacy and service delivery within effective PPP. 205. The component aims at expanding farmer access to value addition and competitive marketing systems for priority commodity value chains, driven by an inclusive, strengthened and thriving private sector and effective farmer organizations. Strategic objectives, outcomes and related indicators are defined, as shown in Table 30. 88 Agricultural Sector Development Programme II (ASDP-II) Table 30: ASDP II Component 3: related specific ASDS-2 objectives and outcomes Objective Outcomes Outcome Indicatorsa Comp. 3. To improve and expand marketing and promote value addition by a thriving competitive private sector and effective farmer organizations h Strengthened and competitive commodity value chains - Value and monetary value of exports - Monetary value of new Foreign Direct Investments (FDI) and private capital flows to agricultural sector - Job creation by new and expanded investment in agribusiness - Volume and monetary value of food imports - Profitability of produce and products at farm and enterprise leves - Market share of products at all market levels - Product’s compliance to national and international standards - Standardized marketing infrastructures along the value chains - Participation of vulnerable groups (women, youth, and pastoralist) in value addition - Participation of vulnerable groups (women, youth, and pastoralist) in commercialization - Participation of vulnerable groups (women, youth, and pastoralist) in decision making along the value chain - Benefits accrued by vulnerable groups (women, youth, and pastoralist) from main ASDP II interventions along the value chain s/c 3.1 Access to farmers and rural infrastructure (markets/ storage) improved - % change in investment in market infrastructure - % farmer/ FO/ Traders using improved market infrastructure in rural areas s/c 3.2 Agribusiness and value addition promoted - % change of value added produce and products - % change in post harvest loss Policy, regulatory and institutional environment required to generate expanded participation of broad-based strengthened private sector actors in all aspects of the agriculture strategy and its effective implementation. 206. Component 3 is sub-divided into 2 sub-components: Component 3: COMMERCIALIZATION AND VALUE ADDITION (BUILDING COMPETITIVE CVCs) S/c 3.1: Marketing S/c 3.2: Agribusiness development: value addition & agro-processing 207. Engaging smallholders and fostering strategic partnerships between priority commodity value chain stakeholders, from producers to marketers and agro-processors, will drive the promotion of smallholder commercialization and lead to improved product quality and competitiveness in domestic and regional markets. The focus of this component is to enhance efficiency for farmers and their organizations, to access profitable input/output markets and value addition (including agro- processing) opportunities in priority CVCs, and by setting the environment for the private sector to invest. Within the appropriate policy framework (see s/c 4.1), this will happen through facilitation of the public sector, strong stakeholder (farmer, processors, marketers, etc.) organizations, provision of 89 Agricultural Sector for Industrial Development relevant information and advisory services, improved linkages and/or partnerships for investments along the target value chains, and the availability of critical infrastructures and other facilities. 208. Increased offer and demand for targeted commodities will be achieved through a combination of: (i) use of improved technologies, input market consolidation and mechanization services; (ii) irrigation development towards double cropping, mainly for rice and high value crops (horticulture); and (iii) reduced post-harvest losses and value addition; and (iv) improved marketing promoted by capacitated farmer organizations, alliances with other CVC stakeholders and adequate socio-economic infrastructures and facilities. 209. Prioritization. To avoid thin spreading support, the program will primarily target key CVCs in local farming systems, offering high potential for quantitative and qualitative growth: agro-ecological potential, importance in local farming system (see also ASDP-1 district priorities) and market demand will be key selection criteria. Within this line, SAGCOT concentrate solely on priority commodities (i.e., maize, rice and sugar), mainly in the Southern Highlands. As a national sector programme, ASDP II will initially focus on priority CVCs for crops, livestock and fish in each AEZ, and implement activities within a limited number of high potential district clusters to be determined by the regional stakeholder innovation platforms. Practically, based on the analysis of growth prospects/potentials for priority value chains in respective AEZs, specific strategies to achieve sustainable growth are summarized as follows: Table 31: Objectives for priority CVC and strategies to achieve expected results Outcomes Priority AEZ Strategies to achieve expected outcomes MAIZE: Tanzania becomes a major maize exporter in the region. Based on recent trends, Tanzania should aim to be exporting over 500,000 t of maize each year, mainly to neighbouring countries (Kenya) Southern Highlands West and south-west Northern highlands i. Incentives for increased productivity and production by more efficient use of available technologies (seed and fertilizers) ii. Warehousing for improving market incentives: could lift average farm gate prices as much as 50% iii. Better revenues would in turn facilitate more farmer investment in production (further broaden input markets) iv. Promotion of conservation agriculture for resilient sustainable production system v. Rotations maize/soya beans (nutrition and livestock) vi. Formation of cooperatives to earn economies of scale RICE: Tanzania achieves self-sufficiency in rice production (and starts to export these grains (potential to become a regular exporter) East All irrigated i. Increased productivity—efficient use of improved technologies ii. ‘Block farm’ management for improved irrigation efficiency iii. Irrigation infrastructure rehabilitation/extension iv. Warehousing/marketing and value addition linkages v. Counter-season irrigated vegetables vi. Strengthen management capacities of existing paddy schemes OIL CROPS: Tanzania food oil self-sufficiency (reducing by 50% dependence on palm oil imports) Semi-arid (N) (sunflower) i. Incentives for increased sunflower productivity using adapted hybrids and integrated soil & water management ii. Rotation/relay cropping with pulses iii. Grouping/grading and warehousing (farmer organizations) iv. Promotion of medium scale FO/private value-added industry Semi-arid (S) (sesame/sim sim) i. Productivity increase (varieties, fertility management) ii. Incentives for FOs for bulking, grading (varieties) & improved marketing/export of their produce (price increases up to 50%) MILK: Tanzania substitutes 25% of its milk product imports by local production Tanga Peri-urban i. Improved breeds, improved feeding and health management ii. Dairy farmer organizations / cooperatives; grouped marketing iii. Milk collection centres, quality control iv. Improved feeds (soya/maize, etc.) 90 Agricultural Sector Development Programme II (ASDP-II) Outcomes Priority AEZ Strategies to achieve expected outcomes MEAT: Satisfy local demand and export quality meat (Middle East) Arid Semi-arid West & Southern Highland i. Improve breeds of meat animals ii. Establish and Strengthen livestock stakeholders Associations along the meat value chain iii. Establish and strengthen feedlot cattle production for beef iv. Conducting and strengthening market information services Horticulture (fruits and vegetables). Production for consumption & export All peri- urban areas & highlands i. Controlled/greenhouse production ii. Irrigation for counter-season production iii. Input/output marketing organization Traditional cash crops (cashew, coffee, sisal etc.) Increased export quantity and quality i. Increased productivity and enhanced product quality ii. Target bio-product windows on international markets iii. Local value addition (cashew, coffee, tea, etc.) iv. Diversify traditional products Goat and chicken products. Contribute to improved HH FS/ nutrition and farm revenues All AEZ i. Access to improved breeds ii. Improved management skills, integrate in household farming systems iii. Strengthened animal health services (including vaccination) iv. Feeding strategies based on complemented farm residues v. Commercialization of chicken and goat meat and products Fish Become major fish producers and exporter along the coast of Indian ocean. Making sure that, fishing activities is sustainably done and contribute to livelihood of fishers and GDP Major lakes, (Victoria, Tanganyika, Nyasa and Rukwa). Also, rivers and coast of the Indian ocean waters i. Ecosystem approach to fisheries management skills improved ii. Establishment of registration of beach management units iii. Value addition to fisheries products iv. Reduction of post-harvest losses to zero v. Promotion of pond and cage culture farming in lakes/ocean vi. Facilitation private sector producing quality and quantity fish fingerlings and feed vii. Facilitate aquaculture training institutes to impart practical skills Source: Compiled by the FAO mission for ASDP-BF, 2013 210. Capacity building and Investment phasing. Institutional capacity building, promoting stakeholder organization and value chain MSIPs and agribusiness support services remain fundamental for CVC development (see also s/c 4.1). Agribusiness support services will be contracted-in to agribusiness PSPs, which will also provide specialized training to assist target beneficiaries to prepare investment plans, strengthen management capacities and improve access to finance. Activities will be piloted in each AEZ/clusters and be gradually (i) scaled out across a larger number of interested districts; and (ii) scaled up using complementary local CVC options for diversification. Regional commodity MSIPs will decide on the priority investment schedule, based on opportunities and available capacities to achieve expected impact. 211. Building on ongoing programmes, ASDP II will gradually expand and cover all AEZ with consideration and formation of district/CVC clusters. The range of priority commodities for crops, livestock and fisheries will be consolidated gradually, as per stakeholder choices, to achieve a broader-based growth for rural poverty reduction. Regional MSIPs for priority CVCs will allow for linking local specificities (DADP priorities) to zonal and national priorities towards focusing investments and economies of scale. 212. Financing at local level. A competitive matching grant will be made available under this component, as top-up fund through the existing DADG, for financing profitable CVC investments and building partnerships in local agribusiness development. 213. Strengthen local coordination mechanism. Continuous support to crop and livestock extension, along local priorities and capacity building for planning, implementation and follow-up of priority CVC activities. This includes support to district level MSIPs for prioritized CVCs, involving public and private stakeholders. 91 Agricultural Sector for Industrial Development 214. Integrated support involving innovations and capacities for production, value addition and marketing will induce required outcomes in performances of priority value chains towards sustainable changes in local production systems. Overall, the ‘Rural Commercialization and Value Addition’ component will support building competitive value chains through activities grouped in four sub-components: (i) farmer empowerment and organizational strengthening; (ii) value addition and agro-processing; (iii) access to markets; and (iv) access to rural financing. Subcomponent 3.1: Marketing 215. The adoption of the Agricultural Marketing Policy (AMP, 2008) paved the way to collaboration between the public and the private sector, such as MVIWATA, MUVI and the Rural Livelihood Development Company (RLDC) to empower producers and enhance market linkages. There have been several programmes/projects in recent years in support of agricultural marketing improvement: the largest being the Marketing Infrastructure, Value Addition and Rural Finance (MIVARF). Other programmes in support of market development include PADEP, DASIP, and some other projects supported by NGOs. 216. Domestic, Regional & International Trade. The Government of Tanzania will continue to promote domestic, regional (EAC99 and the Southern African Development Community (SADC)) and international trade for agricultural and food commodities. The required interventions include promoting and strengthening: (i) internal and external trade under the Tanzania Trade Development Authority (TANTRADE); (ii) campaigns to use “Made in Tanzania” products; (iii) key traditional cash crop exports including tobacco, coffee, tea, cashew nut, cotton and their processing; and (v) increasing export of fish and horticulture, but also strategic export of maize and rice to neighbouring countries. To this end, the government proposes to expand well-functioning export processing zones in the prioritized regions and to reinforce the current system of regular consultations with private sector stakeholder associations about procedures and regulations impacting trade benefits and profitability. 217. Market access. ASLMs will collaborate with various stakeholders to implement policies, enforce laws and regulations and create a favourable environment for domestic, regional and international marketing activities, including: (i) establish and operationalize the Agricultural Commodity Exchange for selected commodities; (ii) raise stakeholders awareness on the required marketing standards and quality and oversee implementation of grading and standard protocols for different commodities; (iii) continued review of existing legal and regulatory framework of agricultural marketing; (iv) improve the market information system and its use to support commercial decision-making; (v) strengthen the systems for enforcing food safety controls based on traceability (including barcodes) and proper handling; and (vi) improve enforcement of the regulations and procedures for appropriate treatment of agricultural traders and transporters to minimize non-tariff barriers. 218. Improved rural and marketing infrastructure (roads, markets, private and public storage facilities, electrification, telecommunication, etc.) is a high priority for efficient inputs and output marketing and to attract private investment in agricultural related activities such as agroprocessing, but also increasing producer prices, farmer incomes and rural employment opportunities. Improved transport infrastructure, dissemination of market information and easing of cross-border trade restrictions can all play a role. 219. The private sector is expected to take the lead in processing and marketing of agricultural commodities so that they satisfy consumer demand for quantity, quality and safety. As domestic and regional markets expand and become more discriminating in terms of quality and food safety the issue of sanitary and phytosanitary standards will become increasingly important, calling for improved regulation and certification services. The Government of Tanzania (see ASDS-2), through the ASLMs, will work closely with private sector and the development partners to continue its efforts 99 The East African Common Market, launched in 2010, opens up new regional trade opportunities, but also exposes Tanzania’s domestic market to increased competition. 92 Agricultural Sector Development Programme II (ASDP-II) to undertake: (i) improvement and maintenance of rural roads network, including by promoting private investment; (ii) roll out the operations of WRS100 for appropriate commodities by empowering farmers, increasing storage capacity at all levels; (iii) support increasing capacity of cold storage and cold chains, especially to service dairy, meat and fish products; (iv) close collaboration with the Rural Energy Agency (REA) to promote rural electrification; and (v) developing market facilities at village, ward and district levels, but also wholesale markets, border101 market places, to encourage trade with neighbouring countries. 220. The aim is to develop and promote access to profitable domestic and export markets for priority commodity value chains. This will be achieved by a gradual building process building on promoting sustainable collective warehouse marketing schemes (see COWABAMA in s/c 3.2) at village/farmer group level and supporting: (i) establishing and maintaining an effective market information system; (ii) enhancing the use of warehouse receipt systems and consolidating efficient marketing information system; and (iii) piloting and establishing a commodity exchange programme, including strategic warehouses when required, starting with major cash crop commodities (cashew nut, coffee, sesame, etc.). 221. Market access for beef dairy and fish. The main marketing infrastructure for livestock include, among others stock routes, night camps, holding grounds and dipping facilities. Both primary and secondary markets are equipped with auction rings, purchase pens and weigh bridges. About 300 primary livestock markets are administered by the LGAs and supply animals for local markets and for onward transfer to secondary and terminal markets located at Themi (Arusha), Weruweru (Moshi), Korogwe (Tanga), Lumecha (Songea) and Pugu (Dar-es-Salaam), which then supply to urban and export markets served by 10 border markets. 222. Market Information Services (MIS). To complement the agribusiness support services and competitive grants to promote agribusiness, timely access to adapted market information is crucial to improve decision-making. Market information comes in the form of prices, product quantities and qualities available for sale and purchase in specific locations. Currently, the availability of information is rather scattered, ineffectively collected and poorly disseminated. Developing a more robust system (facilitated by public investments and implement within PPP) using modern ICT (Internet, mobile phone, text messaging) for providing relevant market information will be an important support for improved linkages producers, buyers and other CVC stakeholders towards enhanced value chain efficiency. 223. Warehouse Receipt Systems (WRS) and market linkages. Successful market improvement efforts through WRS by various development and financial partners, in East and Southern Africa, allowing for common marketing (including contract selling to large buyers, auctioning, spot selling), improved farm-gate prices for inputs and outputs, reduced losses and reliable farmers cash flow. The implementation of ASDP II prioritizes in a first phase the promotion of village level storage facilities (see s/c 3.2 COWABAMA), while more formal WRS require storage facilities of at least 5,000 tons102 to cover the higher management and transaction costs involved in professional collateral management, infrastructure maintenance, insurances, licenses, etc., as per application of the ‘Warehouse Receipt Act’. Therefore, the WRS will be piloted in about 10 critical locations, and build on further grouping of village warehouses (average capacity of 300 tons each) to develop a critical mass, which would allow for working on a third aggregation level103, from mid-programme on. Gradually strengthened market linkages will lead to contractual agreements between cooperative unions, public and private service 100 Since 2007, the WRS has played an important role in improved marketing for some agricultural products (cotton, coffee, cashew, maize, rice, sunflower and sesame). A Commodity Exchange System is in preparation under the coordination of the Capital Market Security Authority (CMSA). 101 Complete the construction of international produce market places at Kibaigwa (maize, sorghum and beef), Segera (horticultural products—Tanga region) and Makambako (multi-purpose—Njombe region). Border markets are expected to support farmers in terms of price stabilization, as all stakeholders use same facilities. 102 In the range of 1,000–5,000 tons depending on the value of the commodity. 103 See proposed pilot Commodity Exchange activities in Table 39. 93 Agricultural Sector for Industrial Development providers, rural banks, input suppliers, and commercial farmers or aggregators who have linkages with agro-industries, commodity exchanges, wholesalers or exporters. To facilitate the development of these linkages, ASDP II will support exchanges, value chain consultation and specialized technical and economic assistance. 224. Pilot commodity exchange platform establishment. The initial step in this process is in generating a body of knowledge on the market, its opportunities, requirements, sources of information and the key players, particularly private companies. This will form the core of the market training courses. The Ministry of Industry Trade and Investment will maintain a Market Intelligence knowledge database including: (i) regional sources of information; (ii) updated listing of companies, agribusinesses, logistic companies, sources of equipment; and (iii) regulations, standards, trade data. Building on a critical number of functioning warehouses, commodity exchange markets will be established, starting with cash crops such as cashew and coffee, but maize and other exported food crops. Under the guidance of specialized Ministry of Industry Trade and Investment services, technical capacities will be developed, including by learning from experiences in neighbouring countries (Ethiopia, Malawi, South Africa, Uganda, etc.). ASDP II will support exchanges, value chain consultation and specialized technical assistance for developing priority commodity exchange platforms involving PPP. Table 32: Summary of action areas and activities in market enhancement at national/regional level Action areas Activities Market research (cost, competitively for priority crop/livestock CVC - Investment opportunities for local and export markets - Evaluate marketing costs in segments along value chain Market intelligence - Facilitate market access for Tanzanian products - Guaranty product quality and offer reliability Develop Warehouse Receipts System (WRS) - Facilitate warehouse rehabilitation and management (at least 5,000 tons); - Mapping of warehouses under WRS (needs and opportunities for WRS); - Create awareness and build user capacity by linking stakeholders (FO, banks, marketers, etc. at different levels; Facilitate the implementation of the pilot WRS - Follow up the implementation of the expanded WRS Pilot Commodity Exchange Market in Tanzania - Awareness and framework of collaboration between public and private sector - Create awareness and build capacity to key stakeholders - Enhance capacity of ‘Warehouse Licensing Board’ to implement the WRS to facilitate effective commodity exchange - Harmonize legal framework and redefine role of Marketing boards - Consider crop law reforms which resulted into Crop Laws (Miscellaneous Amendments) No., 20/2009 - Develop institutional framework for commodity exchange - Business plan for funding the commodity exchange market - Develop guidelines & enhance capacities of involved stakeholders - Facilitate the implementation of Commodity exchange market - Establish and operationalize an information exchange interface for commodity exchange market/platform Improved MIS - Enhance market information needs for priority CVCs - Strengthen existing MIS to fill the gaps (use ICT to get it efficient) - Promote effective market information diffusion and user access 94 Agricultural Sector Development Programme II (ASDP-II) Action areas Activities Promote agricultural products in domestic and regional/international markets - Participate at shows and exhibitions and expos - Encourage use and consumption of domestic products - Improve and maintain standards, quality and distribution of products - Promote market infrastructures including feeder roads, strategic functional warehouses, markets, abattoirs, milk collection centres and market centres - Strengthen regulatory functions of crop boards (see also s/c 2.2) - Traceability and safety of agricultural products Promote fisheries products - Participate in shows and exhibitions - Traceability and safety of fisheries and aquaculture products - Awareness and collaboration between public and private sector Source: Proposals from the Ministry of Industry Trade and Investment 225. Livestock and fisheries quality control and product safety assurance. Priority action areas and proposed investments include among others, at national/regional level (Table 34). Table 33:Priority activities livestock and fisheries quality control and safety assurance Action area Priority actions Livestock & products marketing - Empower livestock producers with basic knowledge & skills on product quality - Strengthen capacities of livestock regulatory boards (dairy, meat, hides and skins, and animal feeds boards) - Reinforcement and (regional) harmonization of laws/regulations on quality livestock products - Strengthen linkage between livestock producers and potential markets - Strengthen regulatory boards (TSh 500 million/year) Livestock marketing infrastructure - Investment in key livestock marketing infrastructures - Promote and enforce sector standards for safety and quality Livestock marketing information - Strengthen (integrated & sustainable) livestock marketing information system (data collection, processing/analysis and dissemination using modern ICT)— involving public and private sector stakeholders Facilitate marketing of quality livestock inputs and outputs to promote production & safeguard animal/public health - Create public awareness of locally produced veterinary vaccines (Newcastle disease, Anthrax, ‘Blackquarter’ vaccine, etc.) - Strengthen laboratory capacity for control (equipment, capacity strengthening) - Encouraging private laboratories for quality control - Support surveillance a quality livestock inputs and food of animal origin Fisheries products marketing - Improve the standard and quality of fish and fisheries products (regulations and their enforcement) Fisheries marketing infrastructure - Investment in key fisheries processing and marketing infrastructure & facilities - Promote and enforce sector standards for safety and quality Fisheries & aquaculture marketing information - Improve and strengthen (integrated & sustainable) fisheries, farmed fish and other aqua-product marketing information system (data collection, processing and dissemination using modern ICT)—with public/private sector stakeholders - Conduct seaweed and farmed fish value chain analysis Traceability, eco-labelling and animal welfare - LITS practiced increasing performance and quality - Promote animal welfare adherence Source: Proposals from the Ministry of Agriculture 226. At local level, main investments to promote priority CVC marketing are prioritized in participative district agricultural development plans and included in DADG. Key investments include, among others: (i) improvement of road/transport infrastructure; (ii) rehabilitation/construction of local— collection/grouping—markets, including cold storage, slaughterhouse, fish disembarkation facilities; and (iii) specialized agribusiness technical support and capacity building for quality product marketing development. Prioritization and follow-up of investments will be done in close collaboration with the DCP involving the participation of priority CVC stakeholders. 95 Agricultural Sector for Industrial Development Sub-component 3.2: Agribusiness Development: Value addition and agro-processing 227. Value addition and agro-processing are key elements of increased agricultural commercialization, revenue and employment generation in rural areas, but also use of by-products in agro-processing for animal feed. Although they have strong forward linkages by providing additional market opportunities responding to high demands for processed products, the level of agro-processing infrastructure and facilities remains rather low which in turn also contributes to high post-harvest losses. 228. Agribusiness and Private Sector Development. A diverse, competitive and robust private sector to spearhead the development of the agriculture sector is envisaged by way of increased flows of private investment and services in the sector. This will be achieved with public support towards improved conditions and systems in which the private sector operates, by promoting among others: (i) agro-processing to reduce post-harvest losses and for value addition; (ii) improvement on packaging, handling, cold chain and transporting agricultural products; (iii) environmentally responsible technology and hygiene measures, based on the relevant laws and regulations; and (iv) favourable business and investment environment for agro-processing. 229. The priority strategies and interventions recommended in ASDS- II include: (i) promoting private sector investment, especially through ongoing efforts of SAGCOT initiative.(ii) continued improvement of business environment with regard to trade policy, procedures/regulations on export and import, investment, taxation, and other related issues in collaboration with relevant organizations, such as TIC; (iii) establish and strengthen dialogue forum among the key public and private stakeholders, to discuss on the improvement of business environment; and (iv) expand agricultural finance services through TIB-Agricultural window and AGTIF, the Tanzania Agricultural Development Bank, but also commercial banks for medium- and long-term investment in the sector. 230. The aim of this sub-component is to enable smallholder farmers, their organizations and other value chain participants/stakeholders to invest in profitable value addition and agro-processing in priority value chains, to increase ‘enterprise’ profitability and ‘local’ incomes. Targeted agribusiness investments at local and inter-district/regional levels, require specialized support in both technical and management aspects of enterprise development, including: (i) agribusiness advisory and support services and capacity building; (ii) a financing mechanism for business development through competitive matching grants; and (iii) identifying and developing promising commercialization opportunities. Entrepreneurial skills enhancement for value addition is key to build entrepreneurship and self-employment in rural communities, especially among women and young farmers. Agro- processing must be undertaken in a socially and environmentally responsible manner, including decent working conditions and safety, gender equity and youth employment, preventing child labour. Table 34: Priority activities for CVC value addition and agro-processing. Action/investment areas Priority activities Key drivers and enablers for agribusiness development Institutional strengthening: - District/regional CVC agribusiness/ MSIPs - Agribusiness private support services (PSP)—regional level Post-harvest management systems - COWABAMA-BRN (smallholder collective commodity marketing schemes); village-level storage facilities and professional management Agribusiness (processing, value addition) investments along priority CVC - Agribusiness services including support to consolidate enterprise business plans (see agribusiness PSPs) - Improve required infrastructure in terms of access to facilities (electricity, water, etc.) - Support to local investments using competitive matching grants 231. Key drivers and enablers for agribusiness development. Institutional weakness and lack of agribusiness support capacities, especially at local level, have been identified and tackled through several pilot projects104. Actions will take place at district level while coordination and support 104 Rural Business Support Services for improving value chains had varying fortunes, largely depending on the 96 Agricultural Sector Development Programme II (ASDP-II) services centred on priority commodity value chains will be common at regional level, for efficiency and economies of scale reasons. Therefore, regional facilitation teams (to be established/contracted within a PPP framework) should provide results-based agribusiness support services to DCP and technical teams active in the agriculture sector. 232. District CVC Platforms (DCP)105 for improved coordination between stakeholders at LGA level. These stakeholder platforms bring major actors in priority local CVCs together to develop and drive the implementation of a strategy for sustainable productivity growth, value addition and efficient market access. These platforms develop mutually beneficial partnerships among actors along the value chain for increased production, quality, value addition and trade of the selected commodities. DCP will be critical in terms of establishing formal or even ad hoc mechanisms to encourage value chain connectivity between private and public stakeholders and drive innovations/changes towards higher levels of commercialization in targeted priority value chain (or group of complementary CVCs). These platforms will become the vehicles for strategic alliances and business partnerships that will create better understanding of the requirements of producers and processors, transporters and storage businesses and traders and the market. DCP will be involved in priority public support actions planning and evaluation. 233. Regional facilitation/support teams. Agribusiness support services remain a weak link at local/LGA level, as farmers and their organizations and other value chain actors need specialized support services and advice to achieve high returns from their respective activities of production, value addition and marketing in priority CVCs. Agribusiness PSPs are the essential instrument for the programme to engage all actors in the development of priority commodity value chains at local level. Where those support services do not exist or are weak, ASDP II will help promote their establishment and growth through training and capacity building initiatives. These services will be contracted by targeted regions (or district clusters) to deliver the capacity building and agribusiness support services farmer organizations and other CVC stakeholders in commercialized farming and agribusiness development for selected priority CVC. 234. Post-harvest management systems target to achieve effective and efficient food supply by addressing key issues between production and consumption of agricultural commodities. High post-harvest losses remain a central concern, as different research studies demonstrate that farmers lose up to 40% of produced cereals, although losses vary to a large extent by crop type and geographical zone. The main issues are to protect harvested products against physical (water, heat and dust) and biological (fungus, insects and rodents) degradation during transportation, storage and processing operations. From the institutional point of view, harmonization and alignment of functions between the Ministry of Agriculture and the Ministry of Industry Trade and Investment is needed, especially for activities related to storage infrastructures and management, reduction of post-harvest losses and value addition and agro-processing of agricultural products. performance of the PSPs (see IFAD programme evaluation, 2014). Only a few contracts have been facilitated between farmer groups and rural enterprises and between these enterprises and the market. The capacity building support for rural entrepreneurs and enterprises has been limited and of short duration. 105 There is already a “value chain stakeholder meeting” established along with the DADP which will be upgraded to DCP. The purpose of encouraging platforms is to get farmers/producers and agribusinesses to network and connect better, to understand requirements and issues and to see if there can be solutions developed to solve problems or perhaps improve the way business is conducted. The ‘District Commodity Platforms’ (e.g., Tanga), have contributed to bringing the value chain stakeholders together, identifying issues and problems and providing a framework for networking. Potentially, these platforms could contribute to improving value chain cohesion, but to do so they would need to be expanded beyond district boundaries (to cover i.e., clusters). 97 Agricultural Sector for Industrial Development Table 35: Priority actions towards reduction of post-harvest losses Reduction of post-harvest losses Action area Actions/proposed activities Large post-harvest losses due to poor support systems/ technologies and limited handling capacity i. Develop and disseminate guidelines for harvest and post-harvest handling of selected crops (special attention to aflatoxins on cereals) ii. Develop guidelines for appropriate post-harvest handling practices for meat, milk, hides & skins iii. Promote and disseminate technologies that promote better handling and improved storage and preservation of food and food products including livestock products (meat, milk, hides & skins) iv. Professional storage management (see COWABAMA) v. Improved market support infrastructure see s/c 3.3) Highly perishable products for crops (horticulture) and animal products (milk, meat, fish etc.) i. Cold chain infrastructures and marketing ii. Partnerships with private sector involved in transformation & marketing iii. Awareness of standards and compliance control Institutional alignment and harmonization Storage infrastructures and management, reduction of post-harvest losses and value addition between the Ministry of Agriculture, the Ministry of Industry Trade and Investment and LGAs Note: For meat, milk, hides and skins (50 million x 5Y = 250 million) and for livestock products (meat, milk, hides and skins; 100 million x 5Y = 500 million). 235. Village-level storage facilities for smallholder collective marketing schemes (COWABAMA). The objective of these investments, is to develop and promote smallholders’ access to more profitable markets for priority commodities through sustainable collective warehouse based marketing schemes. This will establish a network of commodity warehouses to be linked to large-scale buyers inside and outside the country. The initial investment will focus on 275 collective maize warehouses in SAGCOT, and 78 irrigation scheme warehouses for rice. Selected high potential districts encompass warehouses averaging 300 MT in size, benefiting about 165,000 households. Over time, the programme is expected to expand to other high maize potential districts and bring in additional commodities with promising commercialization opportunities, such as sunflower, diary and horticulture. 236. COWABAMA will involve the rehabilitation of existing village warehouses and the construction of additional ones. Overall, the support under this component will include: (i) improving (village) storage facilities and marketing infrastructures (feeder road connectivity); (ii) promoting management capacities for commodity bulking/assembly; (iii) creating favourable business environment for market activities of priority commodities by strengthening regulatory framework for quality and standards; (iv) supporting access to production enhancing interventions to ensure sufficient output supply for efficient utilization of storage capacity of warehouses; and (v) linking gradually with WRS, commodity exchange programme106 and value addition services. From Year 4 on, the support will expand to further districts (clusters), but also priority commodities (crop and livestock) of other AEZs. Building on achieved results, the programme will gradually expand to other AEZs and/or priority commodities such as sunflower and dairy/meat, trying to achieve broader based growth and rural poverty reduction in clusters of districts of each of the main AEZ, serving as focal point for gradual geographical expansion. 237. Agribusiness (processing, value addition) investments along priority CVC. Besides advisory and capacity building, ASDP II will promote targeted investment development at national and local level, including demand-driven agribusiness support services, improved infrastructures and facilities for increased commercialization, and support to private/associative agribusiness development investments. 238. At national level, public services will facilitate and provide technical support for the implementation of actions at LGA (and LGA cluster) level. Proposed priority action areas for agro-processing are outlined in Table 37. 106 See details in s/c 3.3 Marketing. 98 Agricultural Sector Development Programme II (ASDP-II) Table 36: Proposed strategic action areas for agro-processing and value addition107 Action areas Strategic activities5 Entrepreneur mapping - Mapping of entrepreneurs, their organizations and activities within targeted priority CVCs Training of entrepreneurs - Organize training of entrepreneurs in agro-processing business planning, especially value-addition for targeted priority CVC products within each AEZ. Packaging and branding - Needs assessment/awareness creation of entrepreneurs and producer associations - Promote product branding and quality - Link processors with packaging producers (study tours, grouping demand, etc.) Modernization of agro- processing industries for selected CVCs - Identify needs in priority CVC - Sensitization, diagnostic study, building capacity and provide technical agribusiness advisory services (PSP) - Facilitate modernization with technologies upgrading and financing plan (national level support & regulation) Promote mechanization of postharvest processes - Evaluation of use and quality of processing mechanization (dissemination) - Promote post-harvest farm tools - Prototypes for post-harvest handling in priority CVCs Improve product quality & traceability - Build capacity for product traceability - Laboratory accreditation for quality control NEDF - Promote National Entrepreneur Development Fund Establishment of SMEs Agricultural Exports Processing Zones - Identify areas for establishing export processing zones - Mobilize private sector to develop export processing zones - Follow up the implementation of EPZ development Establish & develop sunflower industrial cluster - Identify sites for developing sunflower clusters - Mobilize stakeholders to develop sunflower industrial clusters - Follow up the implementation of sunflower cluster development Source: Ministry of Industry Trade and Investment, 2015 239. For livestock and fisheries identified priority action in processing and value addition are shown in Table 37: Table 37: Proposed strategic action areas for agro-processing and value addition (livestock/fisheries) Action areas Strategic activities Milk processing - Promote milk collection and processing facilities and infrastructures in 20 dairy clusters (about TSh million each) - Compliance with standards (training quality and safe dairy products) Meat processing - Promote production of quality products by investment in meat processing, slaughter facilities, training in processing - Construct 5 abattoirs in key livestock marketing clusters (about TSh 3 billion each) Hides and skins processing - Promote production and value of quality hides and skins through improved collection and processing Other by-products - Promote production, processing and handling of other animal by-products Processing of Sardinella spp. from fresh water - Promote standard processing and value addition - Training on safety and quality products - Improve collection of ‘dagaa’ and proper fishing methods - (i.e., Lake Victoria, Tanganyika, Nyasa and Rukwa) Fishing and value addition for pelagic fish - Promote support value addition, processing, handling of by-products - Improve proper fishing methods; reduce post-harvest losses - Fish handling and improved quality of by-products 107 Detailed activities to be identified by commodities with involved stakeholders, during investment phase. 99 Agricultural Sector for Industrial Development Action areas Strategic activities Other fisheries products - Value addition to farmed seaweed Regulations - Animal product and by-product quality - Licensing and registration of fishing vessels 240. At local level, facilitation of agribusiness investments in priority CVC will be promoted by: (i) improving required infrastructure in terms of access to facilities (electricity, water, etc.); (ii) enhancing agribusiness services including support to consolidate enterprise business plans (see agribusiness PSPs); and (iii) supporting local investments using competitive matching grants. This infrastructure will facilitate further entrepreneur investments in agro-processing and value addition. 241. Public Agribusiness Investments108. As for ASDP-1, investment funding used the DADG window to support priority public good investments for the development of targeted infrastructures (roads, markets, etc.) and facilities (access to water and electricity, etc.) in support of CVC development at local level. Project selection and implementation will follow consolidated ASDP-1 implementation procedures109 while contributions of beneficiaries and LGA will be gradually increased with increasing returns from the selected priority CVCs. Sub-component 3.4: Expanded Access to Rural Finance 242. Background. Inadequate financial service for small-scale commercial farmers is a major constraint to agricultural growth and limits the level of investment and the pace of agricultural commercialization. Commercial banks are reluctant to lend to the sector and have limited outreach in rural areas. There are numerous microfinance institutions (MFIs) targeting farmers, but they have limited capacity to reach the large number of rural households due to lack of skilled personnel, branch networks and finance. Small- and medium-scale enterprises engaged in value addition are also constrained by access to financial resources. 243. Currently, government initiatives promote agricultural rural finance mechanism including among others: (i) the National Financial Inclusion Framework (Steering committee is chaired by the Bank of Tanzania, drawing members from the Ministry of Agriculture, CMSA, the Ministry of Finance and Planning, TIRA, TCRA, FSDT, TAMFI and mobile phone operators); (ii) SACCOS, channelling savings and finances borrowed from the commercial banks to the smallholder farmers who are members of the SACCOS, but also other similar arrangements through the SACCAS, VICOBA and the like; (iii) WRS for smallholder farmers to access financing of their agricultural activities (mostly in traditional cash crops); (iv) the National Cooperative Bank that envisages at financing cooperative societies (unions); (v) the agricultural lending window in the Tanzania Investment Bank; (vi) the Kilimanjaro Cooperative Bank and the Kagera Farmers’ Cooperative Bank; (vii) lending to youth to engage in income generating activities including agriculture (Ministry of Information Culture Artists and Sports); (viii) LGAs to set aside 10% of their own source revenues to be channeled to lending to youth and women in the respective LGAs area of jurisdiction; (ix) the Agricultural Inputs Trust Fund (AGITF) under the Ministry of Agriculture; (x) the National Social Security Fund (NSSF) issues individual and cooperative loans (Wakulima scheme); (xii) NAIVS and potential follow-up programmes; and (xiii) the Marketing Infrastructure, Value Addition, and Rural Finance (MIVARF) Programme110 issuing grants to Irrigators Organizations or Paddy Agricultural Marketing Cooperatives to acquire medium size rice milling machines. The government plans to establish and operationalize an Agricultural Development Bank to provide a specialized funding window for investment in the sector, while catalytic funds (see e.g., SACGOT) and credit guarantee schemes are some of several initiatives towards integrated rural commercialization. 244. The number of commercial banks is increasing (about 50 in 2014) and some of them extend services to agricultural sector and agro-processing. Agricultural financing (crops and livestock) from 108 To be included in local level investments within DADG. 109 To be updated in ASDP II Programme Implementation Manual (PIM). 110 For rural finance MIRVAF targets improved and sustainable financial and operational performance of: (i) informal grassroots associations, SACCOS and other MFIs; and (ii) rural small- and medium-scale entrepreneurs. 100 Agricultural Sector Development Programme II (ASDP-II) commercial banks in terms outstanding sector lending is gradually increasing at an equivalent of 10% of the total lending (about TSh 1 trillion). Private Agriculture Sector Support (PASS) Trust established in 2000 and funded by DANIDA through CRDB Bank Ltd. has been providing support for business planning and guarantees. Formal and informal MFIs, financing to SACCOS, also support the agricultural economy of the smallholders in rural areas. The initiative of the National Financial Inclusion Framework by MOF intends an implementation plan targeting 50% of the adult population to have access to formal financial services by 2016. 245. Overall, numerous public, project-related and finance institutions initiatives exist at national and local levels to promote access to rural financing of the public sector, but no clear strategy (and coherent and comprehensive action plan) promoting rural financial systems to up-scale stakeholders investment in the agricultural sector, within sustainable PPPs. Improving financial services to the sector is a key policy issue in order to facilitate private investment. 246. For ASDS-2, the required public interventions promoted by ASDS-2 include: (i) promote services of existing community banks and start-up of new ones at local level; (ii) design agricultural credit packages, appropriate to smallholder farmers; (iii) provide support to establish stronger and well capitalized grassroots MFIs such as SACCOS and Village Community Banks (VICOBA) as first- line financial services for small-scale commercial farmers; (iv) update the National Microfinance Policy in collaboration with other ministries to take into account recent developments in technology such as the use of mobile banking, pension schemes and insurance schemes, which are useful to rural households entering into commercial farming; (v) strengthen overseeing/regulatory functions of the Cooperative Department at local level as part of promotion of MFIs; (vi) accelerate efforts to expand agricultural finance services through TIB-Agricultural window, AGITF, the establishment of the Tanzania Agricultural Development Bank, for medium- and long-term investment in agricultural production and processing; and (vii) promote lending for agricultural investments from commercial banks. 247. Within ASDP II, priority action areas for expanded access of smallholder producers and transformers/exporters (SME/SMI) to rural financing, include among others to: i. Develop a comprehensive rural financing strategy and action programme for promoting business investments and profitability in agricultural commodity value chains development with all involved stakeholders. ii. Strengthen cooperatives and other economic associations and related SACCOS/SACCA (social control as guarantee) for providing sustainable (and stakeholder-owned) (micro) financial services at local level. iii. Enhance availability of and access to short- to medium-term agricultural financing sector within a PPP approach, involving among others an Agricultural Development Bank, private banks investing in the rural sector, etc. iv. Facilitate farmers access to agricultural investments, among others by: (a) promoting WRS to overcome the guarantee issue; (b) strengthening contract farming (contractual agreement between producer organizations, agrobusiness, exporters and banks/financiers); (c) establishing a legal framework policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers). 248. Comprehensive rural financing strategy and action programme. There is little coherence among number of public and private initiatives for promoting an agricultural rural finance mechanism, giving rise to the need to develop, consolidate and implement a multi-stakeholder strategy to promote agricultural investment. A strategy for improving rural financial linkages would include, among others, to: (i) encourage and strengthen the sector’s own control through network organizations for rural SACCOS; (ii) facilitate linkage of FOs (associations) with financial cooperatives, micro- credit institutions and/or commercial banks; (iii) enhance the bargaining power of producer, trader and processor organizations, associations and cooperatives through improved market information, 101 Agricultural Sector for Industrial Development aggregation of produce and the use of inventory financing opportunities; and (iv) strengthen the public sector support in its regulatory function of the financial sector. 249. Grassroots financial services111, aiming at building the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs to expand their rural outreach, and supporting selected community banks as alternative rural financial service providers. The sub-component also aims at supporting the Tanzania Cooperative Development to enhance the implementation of the Cooperative Reform and Modernization Programme. Action areas include improved financial and operational performance of informal grassroots associations, SACCOS and other MFIs (informal associations transformed to MFIs on a sustainable basis), but also strengthened operational linkages between MFI and formal financial/credit institutions. 250. Warehouse Receipt System (WRS)112 using stocks as guarantee for facilitating access to affordable credit in participating financial institutions (PFIs). The financial institutions would access eligibility of warehouse receipt operators to credit on the basis of checklists and benchmarks including: (i) governance and structure of membership; (ii) existence of by-laws, manuals and minutes of meetings; (iii) financial and income statements and balance sheets; (iv) assets; (v) credit history; and (vi) contractual agreements with buyers of produce. ASDP II will support PFIs in collateral management of warehousing, value chain analysis, agricultural risk management, and market research and intelligence, to minimize the risks of their ventures. To improve access of rural financial institutions to data on opportunities for value chain financing, detailed financial analyses will be undertaken for gross margins, profitability, repayment capacity, etc., of all actors in the value chains being supported, and develop training manuals and guidelines for applying the methodology to identify financing opportunities and analyse proposals. 251. The Food and Agriculture Organization of the United Nations (FAO) in collaboration with Rabobank/ NMB Foundation pilot project aims at building financial management capacity among producers and their organizations, creating sustainable linkages with local financial service providers and agricultural value chain agents and improving productivity practices. It will build linkages between FOs and financial service providers which will also provide room for development of a long-term market strategy. Smallholder paddy producer organizations will be formalized into agriculture marketing cooperative societies (AMCOS) to achieve scale and bargaining power, strengthening the commercial relationships between FOs and other rice value chain actors and building the capacity of smallholder farmers to manage loans and participate in the national WRS which will enable them to become creditworthy. 252. Availability of short- and medium-term financing for input provision and operating warehouses which would result in value addition, improvements of grain quality and bulking at the farmer association/cooperative enterprise scale is a key success factor. The improvement of value chain actors and farmers’ access to rural financial services113 by facilitating links to sound financial institutions, including commercial banks, but also partnerships with other initiatives in the rural finance sector114. During the first year, several participating financial institutions and financing models would be identified, so as to ensure availability of financial services in target clusters. 253. However, due to high interest rates and lack of credit guarantees, it remains difficult for farmer groups and private firms to borrow medium- to long-term loan for facilities/equipment investments. This hinders the agricultural investment significantly and appropriate mechanisms need to be developed. Even for seasonal credit, interest rates absorb large parts of supplementary net return on investment (inputs) due to low efficiency in productivity growth. Within this context, targeted subsidies (e.g, interest rates), specialized trust funds and other similar mechanisms need to be discussed between all 111 See also MIRVAF and lessons learned (IFAD). 112 See also ‘Professional warehouse management (COWABAMA initiative) in s/c 3.2. 113 See also National Entrepreneurship Development Fund—NEDF facilities. 114 The programme will collaborate with other initiatives engaged in classic and innovative financing to build an information base that could help streamline complementary financing through financial institutions at different levels. See also related supports by Rabobank initiative, etc. 102 Agricultural Sector Development Programme II (ASDP-II) stakeholders to facilitate sustainable access of sector stakeholders to financial services for agricultural investments, without competing with the financial system. 254. Key action areas and activities to improve sustainable rural/agricultural investments have been summarized, as shown in Table 38. Table 38: Action areas and activities to improve rural/agricultural investments (draft) Action areas Activities Comprehensive rural financing strategy and action programme - Draft and consolidate comprehensive agricultural investment financing strategy with all involved stakeholders - Develop and action programme for enhanced offer and access to rural financing, its financing and implementation modalities Strengthen organizational and technical capacity of existing and new small-scale producer, trade and processing farmer organization and cooperatives - Training and strengthen organizational and technical capacities of farmer organizations to enhance the bargaining power of producer, trader and processor - Facilitate linkage of farmer organizations/associations with financial cooperatives MFI, and/or commercial banks - Strengthen sector’s own control (audit) through network organizations for rural SACCOS - Support the up-scaling of WRS by expanding into new locations and adding new crops - Sensitize on the linkage between SACCOS and AMCOS; train FOs/AMCOS management and board members on good governance and supervision - Support outreach expansion of selected community banks as alternative rural financial service providers - Build the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs - Improve financial and operational performance of informal grassroots associations, SACCOS and other MFIs - Support the Tanzania Cooperative Development Commission to enhance the implementation of the cooperative reform and modernization programme Enhance availability of and access to short- to medium- term agricultural financing - Rural finance support aiming at increasing the access of rural producers and entrepreneurs to financial services by commercial banks, testing new approaches, methods and services in rural areas for the benefit of the target group, improving the legal and policy framework for rural microfinance, and integrating knowledge management into the programme - Improved access to financial services on a sustainable basis for rural small- and medium- scale entrepreneurs (increased number of farmers and SMEs obtaining loans from financial institutions) Facilitate farmers access to agricultural investments - Improved farmer organizations and cooperative input and output marketing by information systems, aggregation/grouping of produce and the use of inventory financing opportunities - Promoting WRS to overcome the guarantee issue - Consolidating and scaling up contract farming where applicable (contractual agreement between producer organizations, agrobusiness, exporters and financial institutions) - Design schemes that will enable smallholder access to loans financing along agriculture value chains (start with lessons learned from ongoing schemes) - Establishing a legal framework and policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers) 255. Implementation. The Tanzania Cooperative Development Commission under the Ministry of Agriculture should take the lead role in developing strategies and priority actions in close collaboration with all sector stakeholders, including departments of Policy and Planning in all ASLMs; departments responsible for Crop, Livestock and Fisheries Development in the ministry; Marketing Department (Ministry of Industry Trade and Investment), the Ministry of Finance and Planning; FOs; MFIs and private banks and development partners. 256. Summary of component 3: Preliminary costing of implementation of proposed action plan was proposed (Table 39). 103 Agricultural Sector for Industrial Development Table 39: Development budget/investment estimation for Component 3 (TSh million) COMPONENT 3: COMMERCIALIZATION AND VALUE ADDITION-BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,346 456,728 568,733 635,561 684,371 2,443,739 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847 9,466 156,458 171,750 368,188 713,709 3.1.2.2 Improving local and improved chicken market access 743 2,068 2,248 369 282 5,710 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,834 738 733 643 630 4,578 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,239 4,073 4,376 1,442 13,999 25,129 3.2.1.1 Strengthening and development of agro processing industries for value addition for all priority commodities 10,333 14,448 15,432 16,806 18,522 75,541 3.2.1.2 Improving milk value chain 8,886 8,536 8,014 4,213 4,571 34,220 3.2.1.3 Strengthening hides and skin value chain 13,915 10,119 19,594 5,972 5,307 54,907 3.2.1.4 Strengthening value chain for horticultural commodities 4,995 1,622 4,127 1,274 1,387 13,405 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,328 21,012 22,695 24,805 27,302 122,142 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,758 6,752 7,267 7,868 8,432 36,077 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,633 12,739 3,507 505 226 26,610 3.2.1.8 Improving Postharvest Management Along Food Supply Chain for sustainable food security and nutrition 1,088 2,710 12,534 2,324 1,080 19,736 TOTAL COMPONENT 3 190,945 551,009 825,718 873,532 1,134,297 3,575,501 104 Agricultural Sector Development Programme II (ASDP-II) F. Component 4: Strengthening Sector Enablers and Coordination 257. Strategic objectives, outcomes and related indicators for the programme enablers and coordination are defined in Table 40. Table 40: ASDP II Component 4: related specific ASDS-2 objectives and outcomes Objective Outcomes Outcome Indicators Comp. 4: Strengthening Sector Enablers, Coordination, and M&E Strengthened institutions, enablers, coordination, and M&E framework - Policy environment and regulatory framework - Business environment (Change in ranking in WB’s doing business and Enabling the Business in Agriculture-EBA) - Knowledge management - Efficient ICT use to support agricultural sector - Integrated and efficient sector monitoring and evaluation (M&E) systems - Empowerment of farmer organizations, women, and youth - Access to agricultural finance s/c. 4.1 Improved business environment through enhanced policy, regulatory, and institutional frameworks - Reviewed and harmonized agricultural sector related policies, laws, regulations and institutional frameworks - Extent of policy and regulation compliance (e.g. compliance rates) - Policy environment and regulatory frameworks - Business environment s/c 4.2 Empowered farmers and farmers’ organization and cooperatives - % of FOs and cooperative providing BDS - % of FOs and cooperatives mobilized own resources - Farmer and other value chain actors’ organizations are operated and managed by the members (Good Governance) s/c 4.3: Sector coordination improved - Quality and timely submitted quarterly reports at all levels - Coordination unit for planning and monitoring established and operational - Guidelines compliance rate at all levels s/c 4.4: M&E and agricultural statistics strengthened - AASS implemented - RS and LGAs to provide quality data through different M&E systems timely - Joint M&E systems established and operational s/c 4.5: Institutional capacity development, knowledge management, and ICT - Enhanced knowledge management and ICT systems s/c 4.6: Access to agricultural finance expanded - Provision for affordable interest rate by commercial bank in Tanzania to the farmer - Loan repayment rates (%) - % increase in branches of formal financial institutions in rural areas. Policies/institutional actions: focus on priority policies as outlined in the New Alliance on Food Security & Nutrition: (i) trade/marketing; (ii) enabling policy for private sector involvement; (iii) land tenure; (iv) access to financing; and (v) seed policies. knowledge management & ICT: Harmonized standards, mechanisms for collection, analysis and dissemination of agricultural identified and developed agricultural knowledge assets in the sector through use of ICT tools shall be strengthened to increase efficiency in decision making but also be a source and stimulant for future sector growth through innovation. Comp. 4: STRENGTHENING SECTOR ENABLERS & COORDINATION (national, regional, local) s/c 4.1: Policy and regulatory framework s/c 4.2: Stakeholder empowerment and organization s/c 4.3: ASDP II_sector coordination (planning & implementation at national, regional and LGA s/c 4.4: Monitoring & evaluation (incl. Agricultural statistics) s/c 4.5: Institutional capacity development, knowledge management, and ICT s/c 4.6: Access to rural financing 105 Agricultural Sector for Industrial Development 258. Component 4 is sub-divided into six sub-components: The success of ASDP II depends to a considerable extent on the capacities and effectiveness of the various institutions and participants in the sector to carry out the planned activities. Most of the institutions, e.g., policy makers, academia, services in research, extension, training and information technology that support the agriculture sector will need capacity to rationalize their functions to implement ASDP II. The institutional factors that hamper development of the agriculture sector are outlined in Box 6. Box 6: Key issues in policy and institutional reform and support (updated from TAFSIP) - Inadequate government development funding for research, extension, research extension linkage, planning and regulatory functions - Limited policy coordination and implementation leading to duplication of efforts and gaps in programme design, implementation and evaluation - Weak interface and synergy between academic institutions and government - Relative disconnect between farmers and cooperatives management structures - Inadequate financial, human and technical capacity to generate, manage and disseminate useful agricultural information, weak communication systems at all levels and the high cost of procuring improved Inputs; - Weak financial and asset management, records, reporting and M&E - Limited training facilities including farmer training centres and limited financing of agricultural training services - Shortcomings in the legal and regulatory framework including enforcement of laws and regulations - Inadequate good statistical base and analytical capacity for policy analysis and decision making Sub-component 4.1: Policy and regulatory framework 259. Effective policy formulation and institutional reforms necessary for policy implementation are the foundations for realizing the Strategic Objectives of ASDS-2. It is also one of the most important functions of the government. Whilst Tanzania’s policy framework for agricultural and rural development is comprehensive and stable, in several areas reviews, adjustments and refinements may be beneficial. 260. The aim is to harmonize, rationalize and align policies and regulatory framework which oversees the agricultural sector (across ASLMs) and related industry (crops, livestock/fish and natural resources) and to strengthen institutional capacity for effective development and management of the sector. Table 41: Key policy areas and related actions for agricultural sector growth (ASLM) Policy outcomes Priority actions (national level) Agricultural Input Policy Enable the private sector to develop, commercialize, and use improved inputs to increase smallholder productivity and incomes - Analysis and advocacy to promote policy options that encourage production and distribution of improved seed varieties - Work with EAC to implement harmonized standards and free trade in seeds Agricultural Trade Policy Reduce tariff and non-tariff trade barriers to increase trade and spur inclusive economic growth (import/export management) - Analysis of food security system capacity and needs, potential for regional trade in food crops, and impacts of export bans on poverty and growth - Advocacy efforts with Parliament and civil society to build support for alternatives - Promote fair & competitive agricultural markets - Align Tanzania’s trade policies with regional (EAC/SADC) policies Enabling Policy for Private Sector Investment 106 Agricultural Sector Development Programme II (ASDP-II) Policy outcomes Priority actions (national level) Agricultural Input Policy Reduce barriers to competitiveness, thereby increasing private agricultural investment and accelerating agricultural growth - Analysis and advocacy to offer alternatives to specific regulatory impediments – streamline the number of regulatory fees and processes - Implement a more simplified tax system on food crops, including the possible elimination of taxes - Promote a more transparent and robust policy environment conducive to establishing a successful commodity exchange - Policy incentives to promote value addition to mitigate rising food import & promote jobs creation - Analysis of agricultural investment incentives to promote domestic and foreign investment Land Tenure Policy Promote land tenure policy that strengthen land use rights with minimal disruption to pastoralists and the landless poor, to stimulate smallholder investment in both land-based and non-agricultural income- generating assets - Establish/implement clear policies and procedures for investors to access land relatively quickly and without conflict - Promote improved legislation and the formalization of land rights through titling - Promote Certificate of Customary Right of Occupancy (CCRO) - Re-organize and expand mandate of the Rufiji Basin Development Authority to act as a land bank for the region (for SAGCOT region only) - Mitigate conflicts in resource use through implementation and enforcement of land use plan Access to Capital and Financing Promote policy that enables development of innovative financial products that catalyse private sector investment, asset accumulation, and input access in key CVC. - Establish/implement modern collateral registry system with associated legal framework to protect lender’s claims to collateral in the case of default - Implement training and outreach to facilitate wide-spread use of Secured Transactions System by financial institutions - Design schemes that will enable smallholder access to loans financing along agriculture value chains Agriculture Sector Policy (including crop, livestock/fisheries and marketing) Support transparent, inclusive, evidence-based policy formulation that leads to increased and more effective public and private investment in agriculture - Strengthen and sustain regional integration (CAADP activities) - Invest in agricultural statistics capacity building - Enhance policy stability, predictability and transparency—streamline procedures and processes in policy reforms - Streamline policies to promote policy coherence - Scale-up and promote policies to promote inclusive growth particularly among youth, women and poorest Food security - Policy level recommendations: Within a coordinated cross sector approach within the TAFSIP framework - Strengthen existing programmes to boost agricultural productivity by focusing on the supply side of the agricultural value chain(s)—availability; - Focus food security specific policies and interventions on household livelihoods and income generation (improve access) - Reinforce disaster preparedness (incl. specialized studies) and response measures with focus on household coping and resilience - Scale up safety net schemes (school feeding, cash for work Nutrition - Legislation (and regulatory framework) on breastmilk substitutes, maternity leave, salt iodation and food fortification are in place - Policy dissemination and advocacy are needed to ensure operationalization and broaden audiences Source: Compiled from ‘Policy discussions G8’. Dar-es-Salaam (February 2015) and ASDS 2 (draft). *The actions for food and nutrition security can be seen clearly under component 2 107 Agricultural Sector for Industrial Development Sub-component 4.2: Farmer Empowerment and Organization 261. Profile of agricultural organization and service provision115. Traditionally, cooperative societies had been the only way farmers were organized to access various services. However, cooperatives emerged mostly for cash crops such as coffee, cotton and tobacco. Due to various economic and political factors, most cooperatives collapsed. To revitalize the registered cooperative societies and pre-cooperative groups the government devised Cooperative Reform and Modernization Programme (CRMP) and enacted the Cooperative Societies Act No. 6 of 2013 to regulate the cooperatives stakeholders in their economic activities of buying and selling services and commodities such as food and traditional and non-traditional cash crops. 262. Currently, a variety of organizations are emerging. Some are classic FO type groups whilst others are more professionalized and include associations such as the Tanzania Horticulture Association (TAHA) and the Agricultural Council of Tanzania (ACT). These NGOs provide services to their members, but many still depend on external technical and financial support. Such organizations need to be supported to mobilize internal resources and to develop their business skills, making them more effective private sector, business-oriented organizations, equipped to help smallholders move from subsistence to commercial practices. These organizations provide an opportunity for linking smallholder farmers with input suppliers, traders, financial and other service providers and for creating strong value chains around specific commodities. Existing farmer organizations have been categorized into several groups (Table 42). Table 42: Farmer organizations, by category FO typea Examples Strengths and weaknesses Commodity- based producer associations/ organizations/ groups Rice growers associations (total number of rice growers associations is not known) FBO and groups (COWABAMA) Most producer associations are poorly linked to input suppliers, financial and business services. In addition, many of them have inadequate management capacity which limits the benefits. However, these associations can be strengthened to negotiate for better policies and prices, possibility of linking better with buyers and other service providers for value chain actors. Apex organizations Rural and Urban Development Initiatives (RUDI) in Mbarali (7,000 members) and Kilombero (3,600 members); Sugar Cane Outgrowers Associations in Kilombero, Mtibwa and Kagera. Tanzania Milk Producers Association (TAMPRODA) Tanzania has no maize producers association unlike those for the other commodities, although many farmers in maize growing areas belong to farmer groups and networks of farmer groups. Some of these are members of MVIWATA, which does not focus on any particular commodity. Maize producers should be organized to facilitate linkages with other value chain actors (maize buyers) to facilitate bulking and warehousing. Livestock herder/fisheries organization. Cooperative societies (affiliated to cooperative unions) Lindi & Mtwara: simsim is marketed through Ilulu Coop Union in Lindi and Masasi-Mtwara Coop Union (MMCU) Still important in some areas, for the traditional cash crops as well as for new crops. For sim sim, it will be important to work through the primary cooperative societies and unions by strengthening their business and marketing operations. Water User Associations & Irrigator organizations Water User Associations in Mbarali Districts (from only a few members up to 3000 members (Madibira) They vary in size and capacity. However, they are a potential entry point for promoting diversification into horticultural crops during the off season after paddy has been harvested. 115 Drawn from TCIA/FAO contribution to ASDP I BF (Annexes-June 2013) 108 Agricultural Sector Development Programme II (ASDP-II) FO typea Examples Strengths and weaknesses Membership- based organizations open only to full-time farmers MVIWATA (Mtandao wa vikundi vya wakulima Tanzania) HODECT: Horticultural Development Council of Tanzania6 It is a network of farmer groups with over 5,000 active farmer groups in 25 regions. It currently represents about 70,000 farming households, though the exact figure is uncertain. Farmer groups are usually between 5 and 15 households and networks represent the groups within a village usually totalling 4–20 groups. Large-scale (commodity based) farmer organizations Tanganyika Farmers Association (TFA), Tanzania Chamber of Commerce Industry and Agriculture (TCCIA) or ACT The limited number of large-scale farmers means that they tend to interact informally. Large-scale farms, ranches and plantations have an important role in modernization, increased commercial production and as the focal point for out grower schemes and contract farming. They will have greater impact on overall Tanzania agriculture as well as position themselves for greater profit, if they were better organized. a Compiled from different sources.116 263. ASDP-1 contributed to the implementation of public policies by setting the stage for improving decentralized public systems for agricultural support, involving the grassroots farmers (and their organizations) to participate in shaping local agricultural development plans. There is evidence of positive effects on improving farmers’ participation (Opportunities and Obstacles to Development), capacity and knowledge building towards increased productivity and potential farmer returns. ASDP-1 also promoted the establishment of Farmer Fora (FF) at ward and district levels, but gained little understanding about their role. Overall, there is a lack of strategic framework for stakeholder empowerment initiatives and their organization along value chains at local and national level117. Suitable service providers with required skills and experience on farmer organization and empowerment are required to guide and enhance capacities of technical skills at local level. 264. Group formation and adoption of collective approach are indispensable steps for realizing agricultural growth and commercialization. The capacity of farmer organizations, as a key private sector player, requires significant improvements to be addressed (see ASDS-2) by the following public interventions: (i) building organizational and technical capacity of farmers organizations through public and private support; (ii) enhancing entrepreneurship and competitiveness of farmer organizations through capacity building in organizational management and leadership; (iii) promoting wide-ranged participation among women and young farmers into farmer organizations; and (iv) providing a clear framework for establishment and operation of farmer organizations. 265. The aim of this sub-component will be to support activities for empowering farmers and strengthening value chain stakeholder organizations, so that they can access services, knowledge, information, investment opportunities and markets more efficiently and effectively. This sub-component will enhance capacities of smallholder farmers and support their organizations to engage in transformative ‘commercial’ agriculture. Farmer groups/organizations/cooperatives will be strengthened and supported towards federating in higher-level organizations (along CVC), for increased leverage and benefit from internal and external support services to improve the profitability of their enterprises. FOs will serve as a focal point for learning, quality control and standardization, but also increased negotiation power and ownership. 266. Success of a smallholder, market-oriented development strategy rests on establishing a foundation of strong farmer organizations, capable of making and acting on decisions that affect their livelihoods. Key elements attracting farmers to associate within competitive agricultural value chains to access opportunities outside the reach of individuals, require at least: (i) a viable business model, consistent with agro-ecological conditions, farmers’ resource endowments and market opportunities; (ii) effective farmer organization governance and accountability; and (iii) access to appropriate technologies, information, production and processing, inputs and credit. 116 http://hodect.org/-(HODECT: Horticultural Development Council of Tanzania) 117 See ASDP-1 evaluation of performance and achievements (June 2011). 109 Agricultural Sector for Industrial Development 267. To achieve this, ASDP II will strategically empower farmers and support structuring of farmer and other CVC-based organizations, capitalizing on local experience in smallholder enterprise development, enhancing good governance structures (i.e., economic associations, cooperatives, companies, etc.) and saving and credit (e.g., SACCOs) facilities. The farmer- and CVC-based approach will serve as a focal point in the extension strategy (s/c 2.2) in responding to farmers’ needs for intensification technologies, access to markets and marketing information availed through strengthened support services and ICT-based systems (s/c 4.2), but also access to quality inputs and marketing strategies. Main action areas are summarized, as shown in Table 43. Table 43: Action areas for farmer empowerment and organization strengthening Action/investment areas Priority activities Assessment of FO capacities - Initial assessment of the capacities of FO in Tanzania. (including case study for success stories) - Develop a strategic framework for stakeholder empowerment initiatives and their organization along value chains Farmer empowerment - Group management training (e.g., support for registration, by-law formulation, leadership training, annual report writing, meeting organization) - Financial management training (e.g., financial record-keeping, auditing) - Business plan training (incl. access to financing services; see also s/c 3.4) - Support for acquiring Certificate of Customary Rights of Occupancy (CCROs) or land title deeds that can serve as collateral - Commodity specific FFS (technical networks) - Trainings for collective FO storage, sales & purchases (see s/c 3.2) Farmer organization strengthening Structuration and federation of farmer groups and unions Strengthening organizational and technical capacities of existing and new small- scale producer, trade and processing FOs/cooperatives - Enhance/support higher level farmer organizations (unions, federations and cooperatives) and their governance - Facilitate emergence and strengthen stakeholder economic entities and/or cooperatives - Strengthen dialogue with stakeholders (ministries, private sector, development partners, etc.) - Support the up-scaling of the Warehouse Receipt System (WRS) - Facilitate processing and marketing by farmer organizations and cooperatives with technical and management skills - Develop effective operational systems for input and output supply chains - Sensitize on the linkage between SACCOS and agriculture marketing cooperative societies (AMCOS) Strengthening commodity- wise stakeholder organizations (TAHA, etc.) - Regional multi-stakeholder innovation platforms for prioritized CVCs - Rice value chain stakeholder - CVC stakeholder organizations at district level - Commodity specific platforms - Strengthen dialogue with stakeholders (ministries) 268. Initial assessment of the capacities of FO in Tanzania. To ensure maximum and enduring impact of support to farmer organizational development, a detailed assessment of the operational capacities and needs of business-oriented farmer organizations will be implemented during the first year. This assessment will focus on: (i) the internal resources and capabilities of the organizations—staffing, management, quality of services, current and potential reach of field operations; (ii) needs for updating of internal trainings and field support materials; (iii) quality of tools used in value chain assessment, competiveness analysis and initial business development support; (iv) capabilities and needs, of linking with financial institutions; and (v) needs of the organizations in terms of headquarter support and field logistics. Based on the findings, a support framework for farmer empowerment and organization strengthening will be finalized. Furthermore, mapping of other CVC stakeholders/ entrepreneurs and their respective training needs towards MSIPs development in priority CVC intensification and diversification in targeted clusters will be performed. 110 Agricultural Sector Development Programme II (ASDP-II) 269. Farmer empowerment. Strengthening of capacities of producer marketing groups and higher-level FOs is critical to the long-term success of smallholder farmers’ participation in agricultural value chains. Key features of this sub-component are the focus on building the capacity of farmers (value chain actors) and their organizations (groups, unions, federation) to make informed choices and implement decisions that affect the businesses and livelihoods of members, but also enhance their capacity to negotiate with other actors in the priority CVCs. The FO-based approach will also serve as a focal point in the new extension strategy in responding to farmers’ needs for new technologies, market and other information availed through the ICT-based systems plan (s/c 4.5), but also the quality seed and inputs (s/c 2.2), agribusiness and value addition (s/c 3.2) and marketing strategy (s/c 3.1). 270. Three elements are required: (i) a viable business model, consistent with agro-ecological conditions, farmers’ resource endowments and market opportunities; (ii) effective group (organization) governance and accountability; and (iii) access to necessary technologies, information, production and processing inputs, and credit. To achieve this, and to complement public production/productivity oriented extension systems at district level, ASDP II will provide support to strategically strengthen partnerships with specialized agribusiness PSPs118 and other commodity-based organizations, capitalizing on local experience in smallholder enterprise development, establishing good governance structures (e.g., cooperatives, companies) and saving and credit (SACCOs) facilities, as required. 271. Strengthening of capacities of producer marketing groups and higher-level farmer organizations is critical to the long-term success and stakeholder ownership of sustainable growth in the agriculture sector. Specifically, assistance will be given to updating internal training and support materials, and the tools used in value chain market assessment, competiveness analysis and initial business development support. The sub-component will: (i) strengthen FOs to address demand-driven linkages with agribusiness partners for critical services such as input supply, output market and processing facilities; (ii) strengthen the roles and capacity of existing producer/market organization partnerships; and (iii) develop innovative ICT-based approaches for enhancing access to technical, market information and financial advisory services. This support will be gender sensitive and youth inclusive, giving particular attention to disadvantaged producer groups to access agrobusiness opportunities. Activities will complement and/or scale up complementary efforts and related initiatives in the sector. 272. Higher-level farmer organization enhancement (unions, apex organizations, cooperatives, etc.). Farmer institutional development is also critical to ensure that farmer organizations play the envisaged role in transforming subsistence into commercial farming, but also strengthening stakeholder ownership and organization governance. Farmer groups/cooperatives engaged in targeted commodity (crop, livestock, fish) production at village level will be supported to organize into a higher-level production and marketing association, acting as an economic entity (union, cooperative or company). In addition to technical advice, enhanced capacity for negotiations with other value chain actors will require training and awareness creation in different areas, including attention to quality of farm inputs, post-harvest handling, processing, transporting, utilization of market information, pricing, and marketing skills. This will involve strengthening existing FOs in business development skills, as well as facilitating the creation of farmer owned associations at village, ward and district levels, where these do not exist. Furthermore, linking smallholder famer organizations to larger-scale producers will be promoted where feasible to increase their access to inputs, agricultural advice and markets. Formal and transparent arrangements for contract farming relations is an important way forward to improve relationships and which will help attain fair prices and, in the long run, reduce supply uncertainties. 118 See also other experiences by MUVI-IFAD and NGO activities in value chain organization and promotion. 111 Agricultural Sector for Industrial Development Table 44: Proposed ASDP II interventions into cooperative activities and operations Intervention Activities 1.To enhance regulatory, institutional and supervisory framework of Tanzania Cooperatives Development Commission (TCDC) and Cooperative Societies 1.1. To conduct training of 95 cooperative inspectors annually in cooperative societies inspection, supervision, accounting & record keeping 1.2. To facilitate Registrar’s Office, execute regulatory functions at national, regional and district levels 1.3. To facilitate conduct cooperative societies special general meetings 1.4. To carry out inspection of the affairs and operations of the Tanzania Cooperative Federation; 5,500 AMCOS; 8,000 SACCOs; 45 Cooperative Unions and 4 Cooperative Joint Ventures 2. To strengthen cooperative movement (all levels) to take on responsibility of promotion and self-regulatory functions 2.1. Facilitate provision of cooperative education to Board members of cooperatives, management and ordinary members in 2,000 cooperative societies annually. 2.2. To develop and air mass media programmes on the cooperative values, undertakings and SACCOs strengthening campaigns 3.To build capacity and strengthen cooperative organizations on business management and leadership skills 3.1. To conduct training of trainers (TOT) to district and sectoral ministries promotion and sensitization teams 3.2. To offer advanced training to TCDC staff on entrepreneurship skills, negotiation skills, project planning and management plus business plans writing, skills mix and the like 4.Strengthen & operationalize Cooperative Data Management Systems (CODAS) 4.1. Strengthen regulatory reporting information for cooperative 4.2. To establish IT system centres as strategic tools for farmers produce value addition Source: Adapted from proposals developed by the Cooperative Agency. Sub-component 4.3: ASDP II Sector Coordination (Planning and Implementation at National, Regional and LGA) 273. The greatest ‘policy’ challenge in ASDP II is effective coordination of agricultural development interventions, which includes all public good support and investments, implemented on- or off- budget. This requires a consolidated coordination framework under the strengthened leadership of ASLMs for all the sector stakeholders at both national and local levels. This also implies the need for enhanced cooperation of all agriculture sector programmes/projects in complying with SWAp under ASDP II, whether they are on-budget or off-budget. ASDP II sector coordination will build on strengthened CKM at national, regional and local levels (see also s/c 4.5). 274. ASDP II will broaden the scope of coordination to include basket and non-basket funded activities. The sector strategy aims to have a more comprehensive approach to planning, budgeting, implementation and monitoring of activities in the agriculture sector, including activities of the private sector by: (i) establishing a coordination framework for all agricultural activities from planning, resource allocation, implementation and monitoring of activities; (ii) enhancing coordination of activities at national and local government level by enhancing engagement of Regional Administration as a link between the ministry and LGAs; and (iii) restructure some of the institutions for improved coordination, efficiency and effectiveness of service delivery in agriculture. 275. The strengthened ASDP II coordination framework will include: (i) widely disseminating clear common goals of ASDP II to all the sector stakeholders; (ii) consolidated efforts by all the sector stakeholders for achieving the goals of ASDP II based on better guidance by the ASLMs; (iii) sound M&E system with strong agricultural statistical data; (iv) sector performance review in which all sector stakeholders, including private sector, participate; (v) open dialogue system on critical policy issues and regulatory frameworks; (vi) well-established networking and information system on all the sector interventions; and (vii) strong capacity of the ASLMs for analytical and managerial aspects concerning the sector coordination. 112 Agricultural Sector Development Programme II (ASDP-II) 276. Institutional structures and coordination functions119. The implementation of ASDP II sector coordination will be mainstreamed and strengthened into the existing government systems and structures—while building on lessons learned from ASDP-1—to effectively support the implementation of the proposed operation. This will allow continuation of efforts to strengthen government systems at national and local levels for enhanced results and sustainability. However, ASDP II will also take account of off-budget programme components and the reporting system will be expanded to encompass such components that fall within the wider objectives of the programme. 277. Coordination at central level. The hierarchy of coordination organs and functions under ASDP II at central level includes: (i) National Agricultural Sector Stakeholders Meeting (NASSM); (ii) Agricultural Sector Steering Committee (ASC); (iii) Agricultural Sector Consultative Group(ASCG) (iv) Technical Committee of Directors (TCD); (v) Thematic Working Groups (TWGs); and (vi) National Coordination Unit (NCU). Table 45 shows the summary of ASDP II sector coordination components. Table 45: ASDP II National Level coordination organs, mechanisms, and membership (summary) Forum Chair Members National Agricultural Sector Stakeholder Meeting(NASSM) Prime Minister Ministers of Lead Components and Related Ministries (ASLMs and Others), Development Partners, and Private Sector, Non-State Actors(NSAs), RS, LGAs, District Executive Directors (DEDs); DAICOs, DLFOs; research officials; training officials; academia representatives; commodity boards;; financial institutions; farmer based organizations/associations and cooperatives, commodity associations, and successive agriculture associations and SACCOS; representatives of other related stakeholder organizations/ players in the agricultural sector Agricultural Sector Steering Committee(ASC) Minister Ministry of Agriculture Permanent Secretaries of Lead Components and Related Ministries (ASLMs and Others), Development Partners representatives and Private Sector Representatives/NSAs Agricultural Sector Consultative Group (ASCG) Permanent Secretary Ministry of Agriculture, Permanent Secretaries of Lead Components and Related Ministries (ASLMs and others), All Development Partners supporting agriculture and Private Sector, NGOs/CBOs, Farmer Based Organizations and Cooperatives,, Research and Training Institutions. Technical Committee of Directors Permanent Secretary Ministry of Agriculture, Directors of Lead Components ASDP II National Coordination Unit (NCU) National ASDP II Coordinator Members of National Coordination Unit (NCU) 119 See further details for institutional and implementation arrangements in Section VI. 113 Agricultural Sector for Industrial Development Forum Chair Members National Thematic Working Groups (TWGs) Component Leader Chairs of Components 278. PO-RALG. LGAs are overseen and directed by the PO-RALG: The Department of Sector Coordination is responsible for management and support to LGAs by collaboration with regional secretariats (RSs). Vertical coordination from PO-RALG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. 279. Coorination at the PO-RALG will start with the Annual Regional and Local Government Consultative Meeting to be chaired by the Minister. This will be followed by: (i) the Agricultural Sector Consultative Meeting chaired by the Permanent Secretary PO-RALG; (ii) the Technical Committee of Component Leaders (TCCL-PO_RALG) chaired by the Director of Sector Coordination, and (iii) the regional Consultative Committee (RCC) chaired by the Regional Commissioner. Table 46 presents the detailed levels from village to the PO-RALG. Table 46: ASDP II PO-RALG Level coordination organs, mechanisms, and membership (summary) Institution Chair Members Annual Regional and Local Government Consultative Meeting Minister PO- RALG Permanent Secretaries ASLMS, Directors (DPPs) of Agricultural Lead Ministries, Development Partners Supporting RS & LGAs, Private Sector, NGOs/CBOs; FBOs, DED, Ward, District, Regional Experts etc. Agricultural Sector Consultative Meeting Permanent Secretary-PO- RALG Directors (DPPs) of Agricultural Lead Ministries Technical Committee of Component Leaders(TCCL-PO- RALG) Director of Sector Coordination- PO- RALG Component Leaders of PO-RALG Plus other Directors at PO-RALG Regional Consultative Committee (RCC) Region Commissioner Administrative and Assistant Administrative Secretaries, Head of Units District Consultative Committee District Commissioner District Executive, Head of Departments Full Council Council Chairperson Members of Council, Management Team (CMT), DED Ward Development Council Councillor Members of WDC Village Council Meeting Village Chairperson Members of Council Meeting Village Assembly Village Chairperson All villagers above 18 years with sound mind 280. Regional Administrative Secretariats (RAS). The role of RAS is to assist the LGAs in preparation of the DADPs, backstopping and supportive supervision on the implementation of the DADPs, and assisting in the submission of quarterly and annual reports in compliance with the DADP Guidelines. The Assistant Administrative Secretary for Economics and Production section within RS is directly responsible for supporting development activities within the region and is assisted in the task by the ASDP Regional Coordinator and fellow officers dedicated to specific sub-sectors. These officers will 114 Agricultural Sector Development Programme II (ASDP-II) provide technical and managerial assistance to LGAs for ASDP II implementation. The RSs will closely work together with the relevant TWGs and the ASDP II National Coordination Unit as the need for consultation and assistance arises. 281. Coordination at local level. ASDP II will strengthen structures for local activities established under ASDP-1. DADP will continue to be the key instrument for agricultural development at local level. The District Executive Director (DED) will hold overall responsibility for activities and funds used at local level. The Council Management Team (CMT), which is chaired by the DED and attended by all the department heads including DAICO and DLFO, is informed on the agricultural development issues and status under DADP. 282. DADPs are derived from the grassroots by villagers through the Opportunities and Obstacles to Development (O&OD) process and summarized in Village Agricultural Development Plans (VADPs): this planning process is led by a Village Planning Committee, Village Agricultural Extension Officer (VAEO), Village Executive Officer (VEO) and supported by the District Facilitation Team according to the DADP guidelines. Proposals from individual villages are submitted to wards and consolidated by the by the Ward Development Committee, guided by the Ward Agricultural Extension Officer (WAEO) under supervision of the Ward Executive Officer (WEO), for submission to the District Executive Director (DED). Based on the submitted proposals, DADPs will be consolidated by DAICOs and DFLOs. The entire process will be guided by the DADP Guidelines and detailed instructions by ASLMs through PO-RALG, including alignment on ASDP II priorities. 283. As a key coordination mechanism at local level, District Component Platform (DCP) between sector stakeholders at LGA level/districts cluster will be in place (s/c 3.2). DCP brings major actors in priority local CVCs together to develop and drive the implementation of DADP activities that includes various aspects such as productivity improvement, value addition and market access. The stakeholders at local level include private sectors (traders, processors, transporters, financial institutions, etc.), NGOs, development partners as well as various public institutions that can provide various types of technical supports. It is therefore crucially important for a LGA to formulate a comprehensive DADP that includes on-budget and off-budget development activities within the LGA, with joint implementation management and follow-up. 284. Off-budget Projects. While the government anticipates that development, partners will continue to contribute to development funding through budgetary support, ring-fenced funds, earmarked funds, discrete projects and off-budget activities, it requires that all projects, funded by whatever means, should be aligned with the ASDP II. development partners should engage in the government framework to ensure alignment with national objectives and to share experience and lessons learned. The activities of off-budget projects and programmes should be subject to agreement between the project and the government, as enshrined in the memoranda of understanding that would stipulate implementation modalities, including activity planning and follow-up. Box 7: Inclusion of off-budget projects Inclusion of off-budget projects into ASDP II framework There is a view among government officials that NGOs perceive other development initiatives as a “threat” and are reluctant to talk to district authorities, resulting in lack of adequate effective communication in the planning, implementation and monitoring of development projects. This perception must be corrected by proactive involvement by NGOs with the development aspirations of ASDP II and other national programmes. NGO contribution to development will be enhanced by improved coordination with ASDP, and mutual lessons may be learned and capacity of ASLMs may gain advancement through greater cooperation. To this end, NGO projects should be obliged at registration and be committed by memoranda of understanding to participate in collaborative meetings and to contribute performance data to the M&E exercises. Development partner development activities in agriculture will also be included in M&E functions on behalf of ASDP II, as will those that may be undertaken by the development partner projects for the benefit of evaluation to meet the needs of the partner. 115 Agricultural Sector for Industrial Development Sub-component 4.4: Monitoring and Evaluation (M&E) and Agricultural Statistics 285. Data availability and reliability were major shortcomings experienced by the sector during ASDP- 1 implementation. According to the Agricultural Statistics Strategic Plan (AASP; 2014), National Sample Census of Agriculture (NSCA), Annual Agricultural Sample Survey (AASS), and Agriculture Routine Data Collection Systems (ARDS) need to be further consolidated and integrated towards an evidence-based decision-making and management tool. ASDS-2 intermediate result IR4.5 (M&E and Agricultural Statistics Strengthened) focuses priority areas on: (i) strengthening and rationalizing M&E to enhance evidence-based strategy development and design of programmes and projects; and (ii) improving the quality, cost effectiveness and timeliness of agricultural statistics. 286. The objective of this sub-component is to ensure that there is an improvement in the timeliness, quality and relevance of available statistics and routine data systems in the agriculture sector, to provide the data needed to monitor the performance of the ASDP II Support Programme, starting with the indicators contained in its results framework, as well as sector-wide statistical data. Under this sub-component, support will be divided in two thematic areas: (i) dedicated ASDP II M&E support; and (ii) support to agricultural statistics and sector M&E efforts120. 287. ASDP II Support Programme Monitoring and Evaluation. One of the lessons learned from ASDP-1 was that the delays in implementing key surveys led to a deficit in the information available to properly monitor and evaluate the results of the first phase. It was therefore easy to assert that ASDP-1 had not achieved its results, that there had been no “impact” and that resources were spread too thinly. Many key performance indicators under ASDP-1 relied on the National Sample Census of Agriculture being completed on time and its results disseminated rapidly121. There was confusion during the ASDP-1 monitoring between the project-specific and sector-wide outcomes data collection: because of clear connection to budgets, the former received in general more attention than the latter, resulting in relatively weak development of ASDP sector-wide monitoring. 288. ASDP II provides and implements a results-focused framework for the agriculture sector. As multiple actors implement their respective interventions and projects in ASDP II, M&E needs strong coordination, data collection, processing, analytical and reporting capabilities. The M&E capacities of the M&E sections in the ASLMs, M&E TWG and NCU will need to be strengthened under ASDP II for stronger M&E coordination and a small M&E team be tasked with day-to-day operation and data processing tasks at each ASLMs. Reports on the state of data collection and overall state/performance of the sector should be submitted to ASDP II decision-making levels, and also widely disseminated through websites or any other means for the accountability of the programme122. 289. A baseline survey will be conducted in 2016/17 complimented by secondary data available from different sources. The National Sample Census Survey of Agriculture (NSCA) to be implemented in 2016/2017 (thus the reference year is 2015/2016) and 10-year periodicity, in combination with AASS and TWG will also provide the consolidated baseline and final levels of outcome and impact indicators for the sector programme. At mid-term, an intermediate survey could be envisaged (as required) to allow for a revision of the results framework to adjust actual performance of the M&E of ASDP II. 290. To allow tracking of key performance indicators identified in the results framework (see Annex II), intermediate outcome indicators will be evaluated yearly to provide useful feedback regarding the implementation of the ASDP II and progress toward measurable strategic objectives. Given that AASS will focus mainly on crop, livestock and fisheries productivity and production statistics, the best options are to integrate programme specific indicators into AASS with data representative of districts; 120 Details for the proposed M&E system and RF are provided in Annex II and V. 121 The last National Sample Census of Agriculture and Livestock NSCA were held in 2002/2003, and then in 2007/2008. The results of the latter were made available in July 2012, while the 2012/2013 Sample Census has been postponed to 2014/2015. It is the main source of information for outcome indicators in the ASDP-1 M&E Framework. 122 Sourced from discussions with M&E TWG. 116 Agricultural Sector Development Programme II (ASDP-II) Not all intermediate outcome indicators will need to be assessed annually. The sampling frame should be the same as for the baseline and survey results should be representative at district level: to produce quality data in a shorter time frame (ideally 3–4 months), the use of portable electronic devices will be promoted. 291. The overall M&E framework for ASDP II including impact/outcome evaluations, output monitoring and quarterly physical and financial reporting of LGAs will be carried out through PO-RALG administrative123 channels. Figure 21: ASDP M&E system for sector and programme performance (adapted for ASDP II) ASDP 2 AGRICULTURAL STEERING COMMITEE ASDP M&E Baseline and Performance reports (ASDP indicators) ASDP 2 NATIONAL COORDINATION TEAM (NACOTE) SECTOR PERFORMANCE (national, regional, district, ward, village level) DADP Physical and finicial quarterly progress reports Outcomes: Production, yields,number farmers using improved technologies Outputs: Area under irrigation, number of VEO trained etc. District reporting Individual project activities and performance (at group level) Input Input Output Outcome Out put Out Come Other projects/interventions in agric (NGO,CSO, etc) Private investment in the agric sector Specific technical reports/studies (livertock/crop disease,price monitoring,food forecasting, etc. Agric. Routine Data System (ARDS) Integrated Data Collection Format (LGMD2) VAEO/WAEO format AGRICULTURAL SAMPLE SURVEYS National Sample Census for Agriculture (NSCA) - 10 years + Annual Agricultural Sample Survey (AASS - 1 year) + Other: National Panel Survey... Consolidation in Regional quaterly fin & phys. progress reports DADP (incl DIDF) Quaterly physical and financial progress report M&E TWG Main proposed actions. 292. Strengthening agricultural statistics, sector M&E and analytical capacity. Based on the Global Strategy to Improve Agricultural and Rural Statistics, promoted in Tanzania by the United States Department of Agriculture (USDA), FAO and AfDB, and based on the ASSP being developed by the Agriculture Statistics Task Force, this sub-component will include the following priority activities: (i) co-financing of the National Sample Census of Agriculture and Livestock (NSCA), foreseen to take place in 2016/2017 (reference year 2015/2016); (ii) financing of AASS during the period of ASDP II implementation (2015–2025); (iii) strengthening the Agricultural Routine Data System (ARDS) 123 The capacity of PO-RALG teams will be strengthened as required (see institutional capacity building in s/c 4.2). Incentives 117 Agricultural Sector for Industrial Development and support to the M&E departments and TWG; and (iv) improve analytical capacity of ASLMs for planning and policy analysis, sector performance reviews, annual budgetary cycle, and PERs. These investments are deemed necessary under ASDP II, given that it will be the largest public-sector financed programme in the sector, and that no other ongoing programme is providing financing in this area. 293. National Sample Census for Agriculture (NSCA). Given that ASDP II will be one of the few large-scale projects/programmes providing financing in agriculture through the public sector over the coming years, and given that financing for agricultural statistics is an ongoing discussion under the aegis of the Global Strategy to Improve Agricultural and Rural Statistics, several partners, including the government, have expressed willingness to participate in the financing of the NSCA. This is seen as the key survey and its regular implementation would go a long way in providing a common national system to all projects operating in the sector in Tanzania. It is envisaged that the NSCA will be held every 10 years, and will provide up to regional-level124 representative statistics on a wide range of variables, based on a sample size of 50,000 households. ASDP II will therefore co-finance the cost of the next NSCA, which is due to take place in 2016/2017. 294. Annual Agriculture Sample Survey (AASS). The Agricultural Statistics Strategic Plan developed by the Agriculture Statistics Task Force foresees that AASS will provide annual, regional level, production and productivity statistics for main crops and livestock species. The annual cost of AASS has not yet been fully defined and nor has the methodology125 been consolidated or the questionnaire been prepared. However, an annual survey is intended to capture necessary outcome indicators for monitoring the sector. Production and productivity are among those indicators, but there are some most necessary indicators like adoption of improved technologies and access to services. Under ASDP-1 these indicators were obtained from the National Sample Census of Agriculture which was conducted at 5-year intervals. Under ASSP, the NSCA has shifted from a 5-year interval to the global interval of 10 years. 295. Within Agricultural Statistics Task Force (NBS, ASLMs and technical assistance from USDA and FAO), there are ongoing methodological discussions regarding the sampling approach (area-based, list-based or a combination), the content of the questionnaire and the data representative level (regional and district), as there are concerns about the current statistical methodology being advocated by USDA. It is important that the integration of intermediate outcomes into the AASS questionnaire would fully streamline the ASDP II M&E into agricultural sector processes. 296. Agricultural Routine Data System (ARDS)126 is a key management information system that has been improved under ASDP-1. A lot of resources have also been invested to build a national database (known previously as LGMD2, but now called ARDS\LGMD2/ Web Portal) with information disaggregated at district level to clarify data flow, to develop data format, procedures for data collection at village and ward level and data dissemination from district to national level. The Japanese International Cooperation Agency (JICA) has provided long-term technical assistance and capacity building support to national ARDS roll-out127. This system provides data on the output performance of the agricultural sector, and relies on front-line extension staff to provide monthly, quarterly and annual information, which is compiled at district level and entered into a web-based database, and made available to ASLM through regional secretariats and PO-RALG. ARDS now has a window for users in the web portal, “ards.go.tz” where potential users can access information by obtaining the User ID from the M&E TWG. There is a need to readjust the scope of the ARDS with other data 124 FAO is planning to conduct “small area estimation method” study for Tanzania to utilize the results of NSCA and AASS and estimate district level data. For this calculation/model, ARDS data are expected to be used. 125 Methodologies for baseline and the final survey should be harmonized with NSCA as well as AASS so that data obtained can be comparable. For that matter, it is better to postpone an envisaged break from the normal list sampling frame to the area sampling frame and continue with the methodology which NBS and ASLMs are familiar with. The pilot conducted for the area frame method has so far indicated a lot of challenges that need to be tackled before rolling out. 126 ARDS needs to be aligned with AASS. 127 Agricultural Routine Data System (ARDS): National Roll-Out Plan, ASDP M&E TWG, 2010. 118 Agricultural Sector Development Programme II (ASDP-II) sources, such as AASS and NSCA, but also the quarterly physical and financial reporting to avoid duplications and improve data quality, reliability and timeliness. It is also necessary to strengthen coordination among ARDS, within the early warning and other administrative data collection systems to improve efficiency of overall data collection. 297. The M&E Thematic Working Group compiles the ASDP Annual Performance Report which provides an update on all key performance indicators, at impact, outcome and output level128 and participates in the JSR and PER (see s/c 4.4), which undertake an annual assessment of progress made under ASDP II. 298. Joint Sector Review. The JSR will comprise a key component of the M&E system and will be undertaken following finalization of the NBS Annual Agricultural Sample Survey (AASS) and immediately preceding the NASSM. It will be conducted by government, development partners and consultants to rigorously review the programme over several weeks on the basis of analysed national statistics as a professional annual evaluation exercise. It will include field visits in selected regions where the ASDP II is being implemented by way of sampling. JSR will be a forum for coordination and dialogue to enable shared vision and the opportunity to initiate corrective action in the management of projects. The conclusions of the JSR will be presented to the NASSM for discussion and corrective action. The report from this meeting will be summarized by the ASDP Coordination and Management Unit and forwarded to the National Steering Committee for action. 299. Finally, the Public Expenditure Review provides a further opportunity to monitor the progress and performance of the ASDP II in the wider context of the national economy. Results of the JSR/PER will be discussed at the ASCG, and then adopted by ASC for futher action implementation. Sub-component 4.5: Institutional Capacity Development, Knowledge Management (KM) and Information and Communication Technologies (ICT) 300. The agricultural sector involves many stakeholders and institutions at national and LGA levels to deliver various services required by farmers and other CVC actors. Therefore, it is imperative to ensure coordination and effective service delivery, to avoid duplication of efforts and wastage of resources. ASDS-2 targets strengthened institutional capacities, among others, for: (i) LGAs in overseeing implementation of agricultural activities, including Public Financial Management (PFM); (ii) PPP in agricultural investment and service (extension) delivery; (iii) human resources in ASLMs to guide implementation and promote innovations; (iv) knowledge management systems for institutional memory, sharing lessons learned and long-term monitoring of the sector performance; and (v) ICT use to improve efficiency of technical support, administration and management of resources and activities. 301. Agricultural transformation requires productive human resources for generation and diffusion of technology, value addition and marketing promotion and overall sector coordination and management. There is a need for a major shift towards introduction of a new generation of farmers who are equipped with the necessary skills to revitalize and modernize agriculture. While professionalism and expertise will be taken seriously, agricultural skills and knowledge will be imparted at various levels in the education system: investment in enhancing human resource capacity will be complemented by better use of ICT for efficient sector management, including on- and off-budget public good investments in the sector. 302. The challenges are to enhance institutional capacities of public (national and local) and private/ associative players (FOs, private sector and non-state actors) to support enhanced coordination of planning, implementation, policy analysis, research, technical support services, agroprocessing, financing and M&E in the agricultural sector, while ensuring that women and youth play a major role. The public sector will create an enabling environment including: setting up appropriate and 128 ASDP Annual Performance Report 2009/2010, March 2011; ASDP Annual Performance Report 2010/2011, November 2011; ASDP Annual Performance Report 2011/2012, draft in progress, April 2013. 119 Agricultural Sector for Industrial Development improved standards and regulations, providing public investments, negotiating on trade matters, organising safety nets for targeted stakeholders, defining sustainable access to and management of natural resources, and providing enhanced agricultural statistics. The private sector, including producer organizations, CBOs/NGOs and business enterprises, will participate in activities and also increase profitable investments in the agricultural sector for production, agroprocessing and/or commercialization. 303. Communication and Knowledge Management. Key communication and knowledge management (CKM) issues of the sector which will be addressed include: (i) inadequate capacity to produce, gather, analyse, document lessons learnt, disseminate and share information at all levels; (ii) inadequate understanding of stakeholders on ASDP II, ASLM policies, mandates and their roles in achieving ASDP II goals; (iii) long chain of communication between ministries and LGAs; (iv) WARC are few, have inadequate facilities that are not fully utilized; (v) low access, untimely and unavailability of agricultural information on inputs, credit facilities, markets, weather and other technologies; (vi) weak information sharing between district councils and ASLMs for immediate action on implementation of ASDP II; (vii) weak coordination and collaboration within and among Communication units in ASLMs and LGAs; and (viii) weak and untimely feedback mechanisms. Knowledge management issues were incorporated with the intention of taping the programme’s best practices, processes and successes for sharing with stakeholders in the country and beyond. 304. During implementation of ASDP-1, efforts were made to strengthen communication at all levels by establishing a Communication Thematic Working Group (TWG) with a mandate to coordinate communication and advocacy campaigns of ASDP. This TWG also established a CKM strategy aiming at using knowledge more effectively for improving the way of doing business to achieve greater impact. This strategy will continue to be implemented under ASDP II by ensuring that: (i) there is coordination of CKM activities in the sector; (ii) stakeholders receive appropriate messages through suitable channels; (iii) there is smooth two-way flow of information; and (iv) farmers are empowered in decision making and participate fully in formulation and implementation of the ASDP II. 305. The CKM objective is to improve information flow, knowledge management, sharing, and learning and create good relationship between actors to achieve programme goals and impacts. Specifically, the CKM intends to: (i) improve coordination of CKM activities among and within ASLMs and LGAs; (ii) strengthen institutional CKM capacity of sector ministries and LGAs; (iii) raise stakeholders’ awareness and understanding of ASDP and other agricultural development projects/programmes; and (iv) improve information flow, access, availability, knowledge management and sharing among stakeholders. Proposed strategies involve among others: (i) build capacity on CKM to ASLMs, regions and LGAs; (ii) establish strong functional linkages for planning, implementation and M&E system with CKM functions at national and local levels; (iii) promote and strengthen public–private sector participation in agricultural development interventions; (iv) strengthen documentation of ASDP formulation process, implementation, achievements and challenges for future reference; and (v) strengthen publicity of ASDP and other agricultural sector initiatives at all levels, working with the media. 306. Use of modern ICTs, including Internet, mobile phones etc., enhances economic and social development, through improved access to information, knowledge sharing and service payment. The Government of Tanzania has started to integrate ICT applications into key development policies and strategies including National Strategy for Growth and Reduction of Poverty (NSGRP) and Tanzania Development Vision 2025. The Vision 2025 clearly recognizes promotion of ICT as central for competitive socio-economic transformation and a driving force for the realization of the vision. 307. Objectives for Institutional Capacity strengthening. This action area will support the strengthening of public institutions to enable them to work as an effective facilitator of inclusive agricultural development.129 Where not covered under the other ASDP II components, non-state actors will 129 Under ASDP II it is envisaged that farmers and the private sector, including NGOs and producer organizations, 120 Agricultural Sector Development Programme II (ASDP-II) also receive capacity development support to encourage them to take a leading role in building commercialized agriculture in the selected commodities under the programme. Capacity building support is provided at local, regional and national levels. Continued support for capacity building is provided to all districts (at different levels) to build on ASDP-1 momentum and prepare districts to integrate ASDP II. 308. At local level, ASDP II will continue to strengthen the DADP planning processes established under ASDP-1. The programme will help districts to strengthen CVC approaches within consolidated and resilient farming and marketing systems. A top-up to the basic level of District Agricultural Capacity Building Grant130 support will also be provided under ASDP II to all districts to help maintain and improve their planning and implementation capacities and systems and capacity for local planning, coordination of implementation and follow-up, reporting and application of regulatory functions. 309. In line with the concentration of investments foreseen under ASDP II, capacity development support will be provided to 25, 50, 75, 100, 125 priority rural districts in ASDP II years 1 to 5 respectively, while all districts are expected to come on stream from Year 5 on. The districts will generate at least 20% of their capacity building budget from their own revenues. Districts not prioritized initially would receive a basic capacity building top-up under ASDP II until they join the investment mainstream, to strengthen their capacity to plan and implement CVC interventions for the district. Furthermore, these districts will also be able to receive support from other sources, including from revenues LGAs have raised locally, the general local government grant from central government, and from other agriculture-related projects funded outside ASDP II. 310. Support will be provided for: (i) capacity building of District and Ward Extension Teams and other stakeholders on comprehensive planning processes to identify critical challenges/ constraints to productivity and income growth and investments opportunities along priority CVCs; (ii) strengthening of institutional systems and capacity building at district level, targeting to improve analytical planning and M&E skills; (iii) enhancing the scope of DADP as a comprehensive sector coordination framework that integrates all projects and initiatives implemented at local level; and (iv) development of human resource capacity at LGA level for technical service delivery of agriculture professionals and other local service providers. 311. At national level, ASDP II targets staff within the ASDP II Coordination Team, the TWGs and other staff from ASLMs and from the regions, who require training to strengthen their understanding and potential support activities on different aspects, such as among others, commercialized agriculture, value chain approaches, participative extension and rural finance. Following identified requirements and demands of involved services, a training plan will be established and specialized short courses would be outsourced to suitable local institutes and universities who would prepare and deliver suitable subject matter on these topics, or sub-contracted to specialized local or international experts. 312. To build capacity to improve and adapt the DADP planning and reporting system, capacity building support will be provided to national and regional staff on data processing, analysis and report writing. Members of the ASDP Coordination Team, the TWGs would benefit, as would selected ASLM staff and staff from the priority regions. Support to policy analysis is another area that the programme will finance including through improved analytical capacity of ASLMs for planning and policy analysis, sector performance reviews and Public Expenditure Reviews (PERs)131. In conjunction with other government actions, the support will focus on improving value chain analysis and policy support, but also addressing policy and regulatory issues that affect related value chains. The Directors of Policy will undertake most of the investments, including investments for input provision, production, credit, marketing, processing and storage as well as extension services, in cooperation with public sector agencies. ADSP-2 public investments will nonetheless, align with government systems and procedures. 130 The Agriculture Capacity Building Grant will be a discretionary grant to support agricultural extension or other advisory services, capacity building, and to strengthen the planning and operational capacity of the LGA agricultural team at district, ward/village levels. 131 Complementing other initiatives such as MAFAP/FAO, the International Food Policy Research Institute (IFPRI) and Michigan State University (MSU). 121 Agricultural Sector for Industrial Development and Planning in the ASLMs will strengthen their work on analysing specific commodities and how to improve different areas of their respective value chains in close collaboration with other initiatives (MIRVAF and SAGCOT) and the private sector. 313. ICT. ASDP II support to the development and use of ICTs will require the involvement of specialized technical capacities to develop consolidated and effective systems to enable information exchange (forwarding and feedback) at all levels within ministries/institutions and across national, regional, district and local/village and final user levels. Technologies for open systems are improving fast while their costs are gradually reducing. The application domains for ICT in the agricultural sector are as follows; 314. Leveraging ICT tools and methodologies to support business operations and resource planning, management and practice along agricultural value chains. Under this activity, ASDP II will support the development and implementation of new systems that leverage use of ICT in providing services to stakeholders along the value chain to: (i) have better access to technical advice to improve farm management and farming practice; (ii) provide feedback and information to advisors and programme officers; (iii) establish marketing linkages with input suppliers and output purchasers through available information as made available; (iv) participate in potential e-services schemes (e.g., for input or mechanization services such as e-voucher, e-wallet, e-loans, etc.); and (v) improve business processes within government through use of ICT. Proposed ICT tools and methodologies will, among others: • Dramatically expand farmers and their advisors access to a broad array of practical knowledge and information including, but not limited to, agricultural input prices and availability, prices for farm products, local weather, agricultural and animal production practices, seed varieties and their characteristics, farm management practices and tools, etc. • Enable easy and systematic flow of information from farmers and/or their advisors to public programme officers—to facilitate collection of farm-level data for M&E purpose, but also allowing farmers to provide regular and timely feedback on the performance of public programmes. • Facilitate farmers in finding and establishing input/output marketing linkages with other farmers (bulking), potential suppliers and buyers. • Facilitate ‘automation’ of business processes within government so as to increase efficiency of public service delivery to the public through use of ICT tools. 315. Accordingly, ASDP II will support: (i) the development and implementation of the ICT system and its backbone architecture (comprehensive agricultural data, network services and integrated and optimized solutions); and (ii) the equipping of agricultural advisors/extension in selected areas with ICT tools (low-cost tablets for advisors, smartphones for lead farmers) and methodologies to enable enhanced access to technical and economic information and relevant information sharing networks. A backbone would include, inter alia, the following features: (i) consolidation of the government’s current agricultural data centres into one state-of-the-art facility; (ii) provision of the improved ICT infrastructure and standardized security services to external suppliers (i.e., firms) of e-services such as e-voucher and e-wallet; (iii) intercommunication between integrated solutions; and (iv) data collection, processing and cataloguing. 316. The ministry has designed an ICT Policy and Master Plan for the crops subsector, part of which is under early stages of implementation. To avoid duplication of efforts, this ICT Policy and Master Plan needs to be updated to incorporate other subsectors, particularly livestock and fisheries, but also marketing spearheaded by the Ministry of Industry Trade and Investment. Having a sector-wide ICT Policy and Master Plan will lead to sector-wide systems, addressing ICT needs of the sector. 317. Communication between all levels will be improved by supply of vehicles, motorbikes computers and related running expenses to the national coordination, RASs and district teams. Furthermore, communication tools (including low-cost mini-tablets or smartphones) will be piloted at ward level for programme management requirements, extension and marketing support, but also for the collection, receipt and dissemination of data for M&E. Arrangements with cell phone companies will be made to allow for forwarding technology or market related text messages to farmers, but also for dedicated 122 Agricultural Sector Development Programme II (ASDP-II) free call numbers allowing farmers to call their extension worker or technical specialist at district level. While ICT may not be applicable to all areas due to lack of connectivity it is anticipated that the network will continue to expand and offer opportunities to wider farming communities. 318. Proposed action areas for institutional capacity strengthening, CKM and ICT are summarized in Table 47. Table 47: Proposed interventions for CKM and ICT promotion Action area Proposed activities I n s t i t u t i o n a l strengthening i. Training of national coordination, RAS and district technical/facilitation teams ii. Capacity building block grant (including 20% local participation) iii. Continued support to WARC CKM action area i. Repackage technical information (e.g., research information) into user friendly information for it to be shared with different stakeholders ii. Conduct formal and regular meetings on CKM among ASLMs and LGAs (awareness and progress) iii. Conduct training programme on CKM and IT at different level iv. Prepare and disseminate guidelines on CKM strategy implementation v. Provide technical backstopping and guidance in KM and communication to regional and LGAs staff, vi. Conduct media forums, workshops & seminars on agricultural sector issues vii. Produce promotional/educational material for target audience viii. Document ASDP lessons learned and establish best practices under SWAp for sharing with stakeholders ix. Participate in local and national events for publicity of ASDP/DADPs and other agriculture sector initiatives and dissemination of new innovations x. Curricula of students Leveraging Strengthening use of ICT to improve efficiency in the sector i. Update crops subsector ICT policy and ICT Master Plan developed by the ministry to incorporate livestock and fisheries subsectors ii. Design and build National Agricultural Information System that will incorporates information on agricultural production, research and extension, land use management and agriculture output marketing information iii. Computerize ASLM internal business operations such as agricultural projects and programmes management, financial management, assets control and inventory management and documents and files management. The government has centralized financial and human resource management which does not fulfil all ASLMs business requirements in those areas, and use of ERP tools will be used here iv. Equipment provision, enhance quality of ICT service delivery and building capacity of ATIs ICT training capacities. v. Design and equipping of ASLMs mini-data centres for sector information management, establishing and equipping LANs for reliable internal and external communications. ASLMs will also facilitate connection of wards to the fibre optic backbone vi. Put in place risks management measures related to ICT use vii. Promote use of mass media (i.e., mobile phones) for sharing agricultural information viii. Free call numbers for personalized advisory services ix. Pilot electronic work plan and monitoring (ward level) x. Publicity for the sector promotion (successful farmers, investors, radio/TV, skype/video, etc.) Note: The overall ASDP II investment (hardware and software) for promoting agriculture sector involvement into use of modern ICT is included in sub-component 4.5. Sub-component 4.6: Expanded Access to Rural Finance 319. Background. Inadequate financial service for small-scale commercial farmers is a major constraint to agricultural growth and limits the level of investment and the pace of agricultural commercialization. Commercial banks are reluctant to lend to the sector and have limited outreach in rural areas. There are numerous microfinance institutions (MFIs) targeting farmers, but they have limited capacity to reach the large number of rural households due to lack of skilled personnel, branch networks and finance. Small- and medium-scale enterprises engaged in value addition are also constrained by access to financial resources. 123 Agricultural Sector for Industrial Development 320. Currently, government initiatives promote agricultural rural finance mechanism including among others: (i) the National Financial Inclusion Framework (Steering committee is chaired by the Bank of Tanzania, drawing members from the Ministry of Agriculture, CMSA, the Ministry of Finance and Planning, TIRA, TCRA, FSDT, TAMFI and mobile phone operators); (ii) SACCOS, channeling savings and finances borrowed from the commercial banks to the smallholder farmers who are members of the SACCOS, but also other similar arrangements through the SACCAS, VICOBA and the like; (iii) WRS for smallholder farmers to access financing of their agricultural activities (mostly in traditional cash crops); (iv) the National Cooperative Bank that envisages at financing cooperative societies (unions); (v) the agricultural lending window in the Tanzania Investment Bank; (vi) the Kilimanjaro Cooperative Bank and the Kagera Farmers’ Cooperative Bank; (vii) lending to youth to engage in income generating activities including agriculture (Ministry of Information Culture Artists and Sports); (viii) LGAs to set aside 10% of their own source revenues to be channeled to lending to youth and women in the respective LGAs area of jurisdiction; (ix) the Agricultural Inputs Trust Fund (AGITF) under the Ministry of Agriculture; (x) the National Social Security Fund (NSSF) issues individual and cooperative loans (Wakulima scheme); (xii) NAIVS and potential follow-up programmes; and (xiii) the Marketing Infrastructure, Value Addition, and Rural Finance (MIVARF) Programme132 issuing grants to Irrigators Organizations or Paddy Agricultural Marketing Cooperatives to acquire medium size rice milling machines. The government plans to establish and operationalize an Agricultural Development Bank to provide a specialized funding window for investment in the sector, while catalytic funds (see e.g., SACGOT) and credit guarantee schemes are some of several initiatives towards integrated rural commercialization. 321. The number of commercial banks is increasing (about 50 in 2014) and some of them extend services to agricultural sector and agroprocessing. Agricultural financing (crops and livestock) from commercial banks in terms outstanding sector lending is gradually increasing at an equivalent of 10% of the total lending (about TSh 1 trillion). Private Agriculture Sector Support (PASS) Trust established in 2000 and funded by DANIDA through CRDB Bank Ltd. has been providing support for business planning and guarantees. Formal and informal MFIs, financing to SACCOS, also support the agricultural economy of the smallholders in rural areas. The initiative of the National Financial Inclusion Framework by MOF intends an implementation plan targeting 50% of the adult population to have access to formal financial services by 2016. 322. Overall, numerous public, project-related and finance institutions initiatives exist at national and local levels to promote access to rural financing of the public sector, but no clear strategy (and coherent and comprehensive action plan) promoting rural financial systems to up-scale stakeholders investment in the agricultural sector, within sustainable PPPs. Improving financial services to the sector is a key policy issue in order to facilitate private investment. 323. For ASDS-2, the required public interventions promoted by ASDS-2 include: (i) promote services of existing community banks and start-up of new ones at local level; (ii) design agricultural credit packages, appropriate to smallholder farmers; (iii) provide support to establish stronger and well capitalized grassroots MFIs such as SACCOS and Village Community Banks (VICOBA) as first- line financial services for small-scale commercial farmers; (iv) update the National Microfinance Policy in collaboration with other ministries to take into account recent developments in technology such as the use of mobile banking, pension schemes and insurance schemes, which are useful to rural households entering into commercial farming; (v) strengthen overseeing/regulatory functions of the Cooperative Department at local level as part of promotion of MFIs; (vi) accelerate efforts to expand agricultural finance services through TIB-Agricultural window, AGITF, the establishment of the Tanzania Agricultural Development Bank, for medium- and long-term investment in agricultural production and processing; and (vii) promote lending for agricultural investments from commercial banks. 132 For rural finance MIRVAF targets improved and sustainable financial and operational performance of: (i) informal grassroots associations, SACCOS and other MFIs; and (ii) rural small- and medium-scale entrepreneurs. 124 Agricultural Sector Development Programme II (ASDP-II) 324. Within ASDP II, priority action areas for expanded access of smallholder producers and transformers/exporters (SME/SMI) to rural financing, include among others to: i. Develop a comprehensive rural financing strategy and action programme for promoting business investments and profitability in agricultural commodity value chains development with all involved stakeholders. ii. Strengthen cooperatives and other economic associations and related SACCOS/SACCA (social control as guarantee) for providing sustainable (and stakeholder-owned) (micro) financial services at local level. iii. Enhance availability of and access to short- to medium-term agricultural financing sector within a PPP approach, involving among others an Agricultural Development Bank, private banks investing in the rural sector, etc. iv. Facilitate farmers access to agricultural investments, among others by: (a) promoting WRS to overcome the guarantee issue; (b) strengthening contract farming (contractual agreement between producer organizations, agrobusiness, exporters and banks/financiers); (c) establishing a legal framework policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers). 325. Comprehensive rural financing strategy and action programme. There is little coherence among number of public and private initiatives for promoting an agricultural rural finance mechanism, giving rise to the need to develop, consolidate and implement a multi-stakeholder strategy to promote agricultural investment. A strategy for improving rural financial linkages would include, among others, to: (i) encourage and strengthen the sector’s own control through network organizations for rural SACCOS; (ii) facilitate linkage of FOs (associations) with financial cooperatives, micro- credit institutions and/or commercial banks; (iii) enhance the bargaining power of producer, trader and processor organizations, associations and cooperatives through improved market information, aggregation of produce and the use of inventory financing opportunities; and (iv) strengthen the public sector support in its regulatory function of the financial sector. 326. Grassroots financial services133, aiming at building the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs to expand their rural outreach, and supporting selected community banks as alternative rural financial service providers. The sub-component also aims at supporting the Tanzania Cooperative Development to enhance the implementation of the Cooperative Reform and Modernization Programme. Action areas include improved financial and operational performance of informal grassroots associations, SACCOS and other MFIs (informal associations transformed to MFIs on a sustainable basis), but also strengthened operational linkages between MFI and formal financial/credit institutions. 327. Warehouse Receipt System (WRS)134 using stocks as guarantee for facilitating access to affordable credit in participating financial institutions (PFIs). The financial institutions would access eligibility of warehouse receipt operators to credit on the basis of checklists and benchmarks including: (i) governance and structure of membership; (ii) existence of by-laws, manuals and minutes of meetings; (iii) financial and income statements and balance sheets; (iv) assets; (v) credit history; and (vi) contractual agreements with buyers of produce. ASDP II will support PFIs in collateral management of warehousing, value chain analysis, agricultural risk management, and market research and intelligence, to minimize the risks of their ventures. To improve access of rural financial institutions to data on opportunities for value chain financing, detailed financial analyses will be undertaken for gross margins, profitability, repayment capacity, etc., of all actors in the value chains being supported, and develop training manuals and guidelines for applying the methodology to identify financing opportunities and analyse proposals. 328. The Food and Agriculture Organziation of the United Nations (FAO) in collaboration with Rabobank/ 133 See also MIRVAF and lessons learned (IFAD). 134 See also ‘Professional warehouse management (COWABAMA initiative) in s/c 3.2. 125 Agricultural Sector for Industrial Development NMB Foundation pilot project aims at building financial management capacity among producers and their organizations, creating sustainable linkages with local financial service providers and agricultural value chain agents and improving productivity practices. It will build linkages between FOs and financial service providers which will also provide room for development of a long-term market strategy. Smallholder paddy producer organizations will be formalized into agriculture marketing cooperative societies (AMCOS) to achieve scale and bargaining power, strengthening the commercial relationships between FOs and other rice value chain actors and building the capacity of smallholder farmers to manage loans and participate in the national WRS which will enable them to become creditworthy. 329. Availability of short- and medium-term financing for input provision and operating warehouses which would result in value addition, improvements of grain quality and bulking at the farmer association/cooperative enterprise scale is a key success factor. The improvement of value chain actors and farmers’ access to rural financial services135 by facilitating links to sound financial institutions, including commercial banks, but also partnerships with other initiatives in the rural finance sector136. During the first year, several participating financial institutions and financing models would be identified, so as to ensure availability of financial services in target clusters. 330. However, due to high interest rates and lack of credit guarantees, it remains difficult for farmer groups and private firms to borrow medium- to long-term loan for facilities/equipment investments. This hinders the agricultural investment significantly and appropriate mechanisms need to be developed. Even for seasonal credit, interest rates absorb large parts of supplementary net return on investment (inputs) due to low efficiency in productivity growth. Within this context, targeted subsidies (e.g, interest rates), specialized trust funds and other similar mechanisms need to be discussed between all stakeholders to facilitate sustainable access of sector stakeholders to financial services for agricultural investments, without competing with the financial system. 331. Key action areas and activities to improve sustainable rural/agricultural investments have been summarized, as shown in Table 48. 135 See also National Entrepreneurship Development Fund—NEDF facilities. 136 The programme will collaborate with other initiatives engaged in classic and innovative financing to build an information base that could help streamline complementary financing through financial institutions at different levels. See also related supports by Rabobank initiative, etc. 126 Agricultural Sector Development Programme II (ASDP-II) Table 48: Action areas and activities to improve rural/agricultural investments Action areas Activities Comprehensive rural financing strategy and action programme - Draft and consolidate comprehensive agricultural investment financing strategy with all involved stakeholders - Develop and action programme for enhanced offer and access to rural financing, its financing and implementation modalities Strengthen organizational and technical capacity of existing and new small-scale producer, trade and processing farmer organization and cooperatives - Training and strengthen organizational and technical capacities of farmer organizations to enhance the bargaining power of producer, trader and processor - Facilitate linkage of farmer organizations/associations with financial cooperatives MFI, and/or commercial banks - Strengthen sector’s own control (audit) through network organizations for rural SACCOS - Support the up-scaling of WRS by expanding into new locations and adding new crops - Sensitize on the linkage between SACCOS and AMCOS; train FOs/AMCOS management and board members on good governance and supervision - Support outreach expansion of selected community banks as alternative rural financial service providers - Build the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs - Improve financial and operational performance of informal grassroots associations, SACCOS and other MFIs - Support the Tanzania Cooperative Development Commission to enhance the implementation of the cooperative reform and modernization programme Enhance availability of and access to short- to mediu- term agricultural financing - Rural finance support aiming at increasing the access of rural producers and entrepreneurs to financial services by commercial banks, testing new approaches, methods and services in rural areas for the benefit of the target group, improving the legal and policy framework for rural microfinance, and integrating knowledge management into the programme - Improved access to financial services on a sustainable basis for rural small- and medium- scale entrepreneurs (increased number of farmers and SMEs obtaining loans from financial institutions) Facilitate farmers access to agricultural investments - Improved farmer organizations and cooperative input and output marketing by information systems, aggregation/grouping of produce and the use of inventory financing opportunities - Promoting WRS to overcome the guarantee issue - Consolidating and scaling up contract farming where applicable (contractual agreement between producer organizations, agrobusiness, exporters and financial institutions) - Design schemes that will enable smallholder access to loans financing along agriculture value chains (start with lessons learned from ongoing schemes) - Establishing a legal framework and policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers) 332. Implementation. The Tanzania Cooperative Development Commission under the Ministry of Agriculture should take the lead role in developing strategies and priority actions in close collaboration with all sector stakeholders, including departments of Policy and Planning in all ASLMs; departments responsible for Crop, Livestock and Fisheries Development in the ministry; Marketing Department (Ministry of Industry Trade and Investment), the Ministry of Finance and Planning; FOs; MFIs and private banks and development partners. 127 Agricultural Sector for Industrial Development Summary of investments for Component 4. Table 49: Five Years Development budget / investment projection for component 4 (TSh million) COMPONENT 4: STRENGTHENING SECTOR ENABLERS - BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310 967 352 387 426 2442 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019 2,023 1,647 1,685 1,847 13221 4.1.1.4 Strengthening and control of child labour in Agriculture 1,585 1,050 1,094 808 684 5221 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587 933 427 - - 1947 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector 4,014 3,742 2,299 2,116 1,195 13366 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,025 3,238 2,779 852 930 10824 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872 6,673 4,280 2,115 2,197 22137 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425 6,998 2,879 2,591 2,196 19089 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,333 3,209 1,597 1,294 1,123 18556 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429 6,350 3,781 2,501 1,142 17203 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047 2,377 336 213 400 6373 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481 1,833 1,600 1,514 639 7067 TOTAL COMPONENT 4 46,127 39,393 23,071 16,076 12,779 137,446 128 Agricultural Sector Development Programme II (ASDP-II) V. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT A. Overall Programme Cost 333. By combining the base development budgets for each component, the overall investment costs of ASDP II were derived (Table 50). Data in Table 50 show that the base cost of ASDP II is estimated at TSh 13, 819 billion (USD 5, 979 million) and annual investment base costs range from TSh 2,284 billion (USD 988 million) to 3,238 billion (USD 1,400 million) over a 5-year period. However, the costs for NFRA grants and input subsidies are not included. 334. Component 1: Sustainable Water and Land Use Management is estimated at TSh 2,024 billion (USD 941 million) and a high proportion of this budget is allocated to irrigation development. Component 1 accounts for 15% of overall programme cost. The cost of Component 2: Enhanced Agricultural Productivity is estimated at TSh 8,081 billion (USD 3,758 million) or 58% of overall programme cost. Component 3: Commercialization and Value Addition (including investments to promote priority value chain development) is estimated to cost TSh 1,483 billion (USD 1,663 million) or 26 % of overall programme cost. Furthermore, the cost of Component 4: Strengthening Sector Enablers is estimated at TSh 137 billion (USD 67 million), or 1% of programme cost. The Tables 50 and 51 show details of the estimate investment costs by figures and percentage. Table 50: ASDP II Component Budget Requirements and Percentages for the first five years. Component Budget Requirement % Component 1 Sustainable Water and Land Use Management 2,024,646,012,085 15% Component 2 Enhanced Agricultural Productivity and Profitability 8,081,495,303,009 58% Component 3 Commercialization and value addition 3,575,493,642,854 26% Component 4 Sector Enablers, Coordination and Monitoring and Evaluation 137,442,668,522 1% Table 51: Overall development budget for ASDP II ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total Component 1: Sustainable Water & Land Use Management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones). 29,759 31,014 34,532 0 0 95,305 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity. 14,132 14,517 13,715 13,501 16,284 72,149 129 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.1.1.3 Enhancing access to agricultural land for youth empowerment. 4,464 4,150 5,753 4,534 6,321 25,222 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (All products). - 1,366 928 839 916 4,049 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,370 184,589 172,338 175,278 189,619 738,194 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity. 5,873 50,129 57,162 59,915 65,430 238,509 1.2.2.1 Strengthening Irrigation schemes management and operations. 1,823 1,652 2,250 1,787 2,592 10,104 1.2.3.1 Development of water infrastructures for livestock productivity. 2,856 66,582 77,456 76,103 85,464 308,461 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries. 42,069 79,875 111,447 158,157 88,773 480,321 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies. 1,905 13,984 8,745 6,345 10,445 41,424 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management. 1,090 1,045 1,730 795 1,329 5,989 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness. 1,960 1,052 1,009 396 501 4,918 sub-total 122,301 449,955 487,065 497,648 467,674 2,024,643 Component 2: Enhanced Agricultural Productivity and Profitability 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,913 772,652 849,529 838,081 921,148 4,693,323 130 Agricultural Sector Development Programme II (ASDP-II) ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,373 9,720 9,349 8,506 9,222 41,170 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389 136,695 150,284 164,670 181,057 782,095 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176 2,652 2,800 2,962 3,141 15,731 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664 93,408 768 1,099 987 97,926 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146 4,533 5,008 4,246 4,639 19,572 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,115 5,176 7,350 4,460 2,090 23,191 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,090 50,853 48,517 6,658 4,388 165,506 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources 2,537 2,134 2,199 2,147 2,319 11,336 2.2.1.8 Improvement of plant health services 13,322 11,191 7,608 1,389 478 33,988 2.2.1.9 Production of vaccines and drugs 44,570 36,191 39,700 3,705 4,380 128,546 2.2.1.10a Improvement of livestock health services 262,550 295,128 332,216 371,559 420,078 1,681,531 2.2.1.10b Improvement of aquatic health services 1,518 1,238 1,241 1,340 1,395 6,732 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,559 29,197 29,504 8,708 9,516 84,484 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,409 16,384 11,616 11,110 11,371 62,890 131 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,833 3,895 2,683 2,738 3,011 17,160 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,250 5,753 5,699 5,707 5,717 32,126 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,153 11,722 12,960 14,297 10,394 63,526 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,538 22,167 23,955 25,921 28,084 120,665 sub-total 1,925,105 1,510,689 1,542,986 1,479,303 1,623,415 8,081,498 Component 3: Commercialization and Value Addition 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,346 456,728 568,733 635,561 684,371 2,443,739 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847 9,466 156,458 171,750 368,188 713,709 3.1.2.2 Improving local and improved chicken market access 743 2,068 2,248 369 282 5,710 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,834 738 733 643 630 4,578 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,239 4,073 4,376 1,442 13,999 25,129 3.2.1.1 Strengthening and development of agro processing industries for value addition for all priority commodities 10,333 14,448 15,432 16,806 18,522 75,541 3.2.1.2 Improving milk value chain 8,886 8,536 8,014 4,213 4,571 34,220 3.2.1.3 Strengthening hides and skin value chain 13,915 10,119 19,594 5,972 5,307 54,907 132 Agricultural Sector Development Programme II (ASDP-II) ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 3.2.1.4 Strengthening value chain for horticultural commodities 4,995 1,622 4,127 1,274 1,387 13,405 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,328 21,012 22,695 24,805 27,302 122,142 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,758 6,752 7,267 7,868 8,432 36,077 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,633 12,739 3,507 505 226 26,610 3.2.1.8 Improving Postharvest Management Along Food Supply Chain for sustainable food security and nutrition 1,088 2,710 12,534 2,324 1,080 19,736 sub-total 190,945 551,009 825,718 873,532 1,134,297 3,575,501 Component 4: Strengthening Sector Enablers 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310 967 352 387 426 2,442 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019 2,023 1,647 1,685 1,847 13,221 4.1.1.4 Strengthening and control of child labour in Agriculture 1,585 1,050 1,094 808 684 5,221 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587 933 427 - - 1,947 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector 4,014 3,742 2,299 2,116 1,195 13,366 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,025 3,238 2,779 852 930 10,824 133 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872 6,673 4,280 2,115 2,197 22,137 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425 6,998 2,879 2,591 2,196 19,089 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,333 3,209 1,597 1,294 1,123 18,556 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429 6,350 3,781 2,501 1,142 17,203 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047 2,377 336 213 400 6,373 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481 1,833 1,600 1,514 639 7,067 sub-total 46,127 39,393 23,071 16,076 12,779 137,446 Total Baseline Cost in TSh million (constant prices) 2,284,478 2,551,046 2,878,840 2,866,561 3,238,165 13,819,090 Total Baseline Cost in USD million (constant prices) 988.4 1,103.70 1,245.50 1,240.20 1,400.90 5,979 B. Financing Plan 335. With regard to the financing of the development budgets for ASDP II, the main sources of funding will include the government, development partners and other stakeholders like private sector, NGOs and farmers. For each programme sub-component, the proportions of the budget for which the respective financiers would provide funds were determined to derive a tentative financing plan for ASDP II. The proportions of the development budgets financed by different sources are shown in Table 52. Table 52: Proportions of the development budget expected to be financed by different funding sources ASDP II CONTRIBUTION ESTIMATES - Proportion of budget financed by different sources (%) Cost Item Government Development partners Development partners Private sector/ Farmers Total (%) Investment level a on-budget off-budget National Local Component 1: Sustainable Water & Land Use Management 15 60 16 10 100 27 73 134 Agricultural Sector Development Programme II (ASDP-II) Component 2: Enhanced Agricultural Productivity 51 29 15 5 100 31 69 Component 3: Commercialization and Value Addition 33 40 22 5 100 31 69 Component 4: Strengthening Sector Enablers 51 23 25 1 100 52 48 a Government at national and local level (LGA) 336. Based on the above assumptions, the base and total development budget for ASDP II summarized by financier is presented in Table 53. The analysis shows that the government would finance about 41% of the programme while development partners would provide 53% (36% on-budget) and other stakeholders (private sector, NGOs and farmers/beneficiaries) about 6%. Table 53: Illustrative financing plan for ASDP-2 (summary of total costs in TSh million) Cost Item Govt Development partners Beneficiary Total on-budget off-budget Private sector/ Farmers Component 1: Sustainable Water & Land Use Management 302,067 1,205,008 316,732 200,835 2,024,643 Component 2: Enhanced Agricultural Productivity 4,096,501 2,368,697 1,212,225 404,075 8,081,498 Component 3: Commercialization & Value Addition 1,197,203 1,419,823 779,701 178,774 3,575,501 Component 4: Strengthening Sector Enablers 70,028 32,278 33,775 1,364 137,446 Total Cost in TSh million (contingencies included) 5,665,800 5,025,806 2,342,434 785,048 13,819,088 Total Cost in USD million (contingencies included) 2,451 2,174 1,013 340 5,979 % 41% 36% 17% 6% 100% C. Financing Arrangements 337. Under ASDP-1 programme financing was executed through a Basket Fund arrangement. The institutions responsible for implementation of the programme at national level component were MAFC, MLFD and MIT. Implementation at the local level was the responsibility of the then PMO- RALG and LGAs. The Basket Fund activities are coordinated through the ASDP Basket Fund Steering Committee, which comprises the permanent secretaries of all the ASLMs, the Vice President’s Office and the Ministry of Finance as well as representatives from development partners contributing to the Basket Fund. 338. The Basket Fund system contrasts with the traditional practice of establishing separate project accounts in which deposited funds are managed by project implementation units (PIUs). ASDP-1 financing arrangements were fully integrated into existing government financial structures, which include planning, budgeting, accounting, reporting and auditing services. The Agricultural Fund Steering Committee (AFSC), a sub-committee of the Agricultural Steering Committee (ASC) will review work plans and budgets submitted by the Planning and Budgeting Thematic Working Group (PBTWG), through the Technical Committee of Directors (TCD) to be financed by the ASDP II. Approved annual plans and budgets will be submitted to the ASC for approval and disbursements of funds against technical and financial reports submitted by Components Leaders for the local level plans and budgets, the Agricultural Fund Steering Committee will also approve plans and budgets for PO-RALG. Disbursements to RS and LGAS will be done through the Regional Administrative Secretary (RAS) for RS implemented activities, and District Executive Director (DED) for Local Government Authorities (LGAs). Basket Funds flow from the ASDP II holding account in the Bank of Tanzania, through an exchequer bank 135 Agricultural Sector for Industrial Development account to ASLMs, regional secretariats and LGAs. The Chief Accountants of the respective ministries are responsible for ensuring that the disbursements of funds and financial management of programme activities are undertaken in accordance with international accounting standards and the Memorandum of Understanding (MOU) between the government and development partners. 339. The Agricultural Fund Steering Committee (AFSC), through the advice of the TCD is also responsible for: (i) facilitating government and development partner contributions to ASDP II approved activities before the respective budget year; (ii) Approval of transferring resources from the Basket Fund to ASLMs based on validated technical and financial progress reports; (iii) policy directives governing the utilization and disbursement of Basket Fund; and (iv) identification of LGAs which qualify for the grants and agreeing changes to the formula for LGA allocations. The TCD is responsible for decisions on the LGA items, with the Agricultural Fund Steering Committee (AFSC), approving the submission of changes to the Agricultural Steering Committee through the agriculture representative on the LGDG Technical Committee. 340. At the local level, the ASDP II funds supports approved activities ASC. Specific activity funds such as capacity building, Extension and District Irrigation are approved by ASC through the recommendation of the TDC. These block grants are incorporated into the financing arrangements used by LGDG and are used to finance the local DADP. The flow of funds in ASDP II is presented in Figure 22. Figure 22: Flow of Funds in ASDP II GOT DPs NGOs/ NSAs R & LGAs ASLMs Exchequer Account Projects Private Sector Direct Financing ASDP2 Basket Fund General Budget Support (GBC) Pay Master General ASDP2 Holding Account Cash & D - Funds C - Funds Public investments (On-budget) Public investments (Off-budget) Private investments 341. In addition to the Basket Fund for ASDP II, agricultural projects can also be funded through on-budget financing whereby funds flow through the exchequer system. In addition, the projects can be directly funded by development partners through off-budget financing. However, off-budget financing is not recorded in the government’s agricultural expenditure accounts. 342. With regard to the financing of ASDP II activities, the government preference is to continue with the Basket Fund arrangement established under ASDP-1. This is the most integrated and expedient 136 Agricultural Sector Development Programme II (ASDP-II) financing mechanism to implement a comprehensive agricultural development programme, such as ASDP II. The mechanism also avoids a fragmented system of financing with separate projects being funded by a range of different development partners. It also reduces transaction costs. 343. Funds flow and disbursement mechanism for joint projects (JPs)/public private partnerships (PPPs) between the public and private sector are agreed during the signing of a contract and MOU between the parties involved in the project. It is important that all funds (general budget support, basket funding and direct project funding) supporting the ASDP II are accounted for during the planning and budgeting process. 344. ASDP-1 implementation demonstrated that the Basket Fund arrangement had been effective in implementing the LGDG system of delivering discretionary grants to LGAs (Agriculture Extension Block Grant, Agriculture Capacity Building Grant and DADG) which facilitated delivery of public support services and local investment through formula based approach. Therefore, the government preference is to continue with the Basket Fund arrangement to ensure effective delivery of support services (extension and research) and implementation of the Cluster Approach under ASDP II that is intended to promote priority CVC at zonal level. 345. In circumstances where development partner country policies are strictly not in favour of using the Basket Fund arrangement, the government would allow the flexibility in using ear-marked funds within the Basket Fund arrangement and stand-alone projects. 346. To integrate on-budget (budget support, Basket Fund, earmarked programmes and projects) and off- budget programme, core programme elements such as Programme Coordination and Management; Planning, and Budgeting; Monitoring and Evaluation (M&E) and capacity strengthening at national and local level will need to be financed either by the Basket Fund (government and non-earmarked development partner contributions) and/or contributions of 5% from each (on- and off-budget) programme and project in the sector. 347. In this regard development partners (both on-budget and off-budget) should contribute 5% of the funds towards coordination costs. The contributed fund would be channelled through a joint account. This account will be managed and coordinated by the National Coordination Unit (NCU) responsible for overall programme management and coordination to ensure that ASDP II activities take place according to schedule and reports are shared. The NCU which will serve as the ASDP II secretariat is an independent team would utilize a single financial management system for accounting, reporting and auditing. Staff serving NCU would be recruited on meritocracy basis. The Unit will have a good technical and professional mix including specific experts in crops, livestock and fisheries to serve the four ASDP components. Using an independent NCU provides significant scope to improve the existing government accountability and financial management systems through training and capacity building to mitigate many of the current weaknesses of the government’s planning, budgeting, accounting, reporting and auditing procedures. On the day to day management of ASDP II NCU will report to the PS-MoA. However, for program planning, budgeting, implementation, monitoring and evaluation NCU will report to TDC on quarterly basis. 348. Therefore, the government should establish a Basket Fund for ASDP II with support from participating development partners. In addition to the Basket Fund, the joint account will be established to allow participating development partners (both on-budget and off-budget) to contribute towards ASDP II management, coordination, monitoring, evaluation and auditing costs. These mechanisms would enable the government to capture all public, private and development partners’ investments in the sector. This will provide transparency and accountability and enable all stakeholders in the sector understand reasons and logic for contributing for the programme through the Basket Fund mechanism. 349. Fund flow: Funds flow for ASDP II funds will be as shown in Figure 18 for the other funding arrangement that will be mutually agreed between the government and development partners/other partners, funds would flow from designated account to the implementing agency. 137 Agricultural Sector for Industrial Development VI. INSTITUTIONAL AND IMPLEMENTATION ARRANGEMENTS A. Implementation of ASDP II at National Level 350. Implementation of ASDP II will be undertaken using existing government structures of the ASLMs137 that will be enhanced by further training and capacity building of staff. The interests associated with Natural Resources and Tourism, Land and Housing, Finance, Energy, Labour, Gender and Children Affairs, Water, Trade and Health and Social Affair, National Irrigation Commission, (NIRC), Bureau of Statistics (NBS) and Tanzania Cooperative Development Commission (TCDC) and other related key institutions will all be included. The implementation process is summarized in Table 54 and further details of the mechanisms and their roles and responsibilities are provided in Annex III. Table 54: Summary of ASDP II Sector National Coordination Organs, Membership and Frequency of Meetings Forum Chair Members Frequency of Meeting National Agricultural Sector Stakeholder Meeting(NASSM) Prime Minister Ministers of Lead Components and Related Ministries (ASLMs and Others), Development Partners, and Private Sector, Non-State Actors, RS, LGAs, Annual Agricultural Sector Steering Committee(ASC) Minister Ministry of Agriculture Permanent Secretary of Lead Components and Related Ministries (ASLMs and Others), Development Partners representatives and Private Sector Representatives Quarterly Agricultural Sector Consultative Group (ASCG) Meeting Permanent Secretary- Ministry of Agriculture All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/ Donors and NGOs/NSA) (local and International) Training and Research Institutions Quarterly Technical Committee of Directors Permanent Secretary Ministry of Agriculture Directors of Lead Components Quarterly ASDP II National Coordination Unit (NCU) National ASDP II Coordinator Members of National Coordination Management Team (NCU) Monthly Technical Committee of Component Leaders (TCCL)- PO- RALG Director Sector Coordination - PO- RALG Component Leaders at PO- RALG plus other Directors at PO-RALG Quarterly 137 ASLMs under ASDP II include the Ministry of Agriculture, Ministry of Livestock and Fisheries; the Ministry of Industry Trade and Investment; the Ministry of Water and Irrigation; the President’s Office—Regional Administration and Local Government; and the Ministry of Land, Housing and Settlement Development. 138 Agricultural Sector Development Programme II (ASDP-II) B. Regional level 351. LGAs will be coordinated by the PO-RALG in collaboration with other ASLMs through regional secretariats. The Department of Sector Coordination is responsible for management and support to LGAs by collaboration with RSs. Vertical coordination from the then PMO-RALG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. While during the ASDP I the Minister PO-RALG did not feature direct in the oversight role in the implementation of the program, under ASDP II the Minister PO- RALG will chair the Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). This will be a meeting of all representatives of stakeholders operating at the regional and local level. These will include Government, Private sector and Development Partners and NGOs/ CBOs. 352. For administrative aspect of ASDP II, coordination among RSs, TCD through NCU, TWGs will be constantly maintained to realize smooth flow of information on the status of development activities and performance under ASDP II. Detailed structure is presented in Annex III. C. Local Level 353. LGAs will be responsible for planning, designing and implementation of programme components under supervision of the RSs to promote social and economic development. They will ensure that laws and regulations are observed in implementation and maintenance and be responsible for the delivery of extension services and the administration of resources including land use planning in conjunction with private sector investors. It is important that the District Agricultural Development Plans (DADPs) are integrated into the district plans and budget. The districts will also form district thematic working groups to comprise District Experts (i.e. agriculture, trade, land, planning and budgeting, cooperatives, and community development, environment/conservation); district private sector representatives, and NGOs/CBOs operating in the region. D. Coordination mechanisms and processes 354. The hierarchy of coordination organs and functions under ASDP II at national level are summarized below and detailed further in Annex III. 355. The National Agricultural Sector Stakeholders Meeting (NASSM) will be held once a year following the annual JSR/PER performed by government, development partners, non-state actors, and the private sector to monitor sector progress. The report will be presented and adopted by the Agricultural Steering Committee and discussed at NASSM 356. The Agricultural Steering Committee (ASC) will be the key oversight and approval organ of ASDP-II implementation and coordination. It will aim to approve the annual work plan, budget, oversee the physical and financial progress, follow-up the audit results and discuss on key issues in regard to sector performance and coordination to guide the TDC and TWG. Oversee monitoring and evaluation of ASDP II. 357. Agricultural Sector Consultative Group Meeting (ASCG). The ASCG will provide a consultative and advisory forum for dialogue between the government (ASLMs), all interested development partners (as defined in the JAST), private sector and non-state actors (NGOs, CSO and PSO) in the agriculture sector. The ASCG will coordinate dialogue at two levels: regular dialogue on sector policies and regulations; annual plans, budgets, and the annual agriculture sector/public expenditure review (ASR/PER) reports. ASGC is an advisory group, while ASC is a decision-making organ. 358. Technical Committee of Directors (TCD). The TCD will provide technical advice to the Agricultural Steering Committee on technical issues in connection with the program components, sub components, investment areas and development projects. It will be supported by NCU and the TWGs of respective Lead Components 139 Agricultural Sector for Industrial Development 359. Thematic Working Groups (TWGs). Membership of TWGs will be drawn from experts within the relevant fields (i.e., departments/institutions) in each ASLM and should invite participation of development partner’s subject specialists. The TWGs will guide the programme on technical and/or managerial matters and advise the TCD and follow the progress of recommended actions as indicated in annual work plans. 360. The ASDP II National Coordination and Management Unit (NCU) will be directed by the National Programme Coordinator and will include independent appointed officials from the labour market and ASLMs/government institutions and will have executive and semi-autonomous powers to manage, monitor and call for meetings of other organs of the ASDP II structures and to direct implementation functions. The team will be a fulltime job, reporting to PS MoA for management and administrative issues and to TDC for program implementation. It will be exclusively engaged in the ASDP II processes for the duration of the programme. 361. The Agricultural Sector Consultative Group Meeting (ASCG Meeting) is not part of the ASDP II hierarchy, but an important stakeholder consultative meeting. It will provide a forum for dialogue between the government (ASLMs), active development partners and non-state actors in the agriculture sector and will coordinate regular dialogue on sector policies and budget, and on the annual agriculture sector/public expenditure review (ASR/PER). It will inform policy and review budgetary issues, facilitating sector dialogue on JAST and GBS. Table 55: Summary of ASDP II Sector at PO-RALG, Regional Secretariat, Local Government Authorities Coordination Organs, Membership and Frequency of Meetings Institution Chair Members Frequency of Meeting Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). Minister PO-RALG RC, RAS, DED, DAICOs, Private Sector, Development Partners, NGOs/CBOs and other stakeholders in respective Regions and LGAs. Annually. Agricultural Sector Consultative Group Meeting (ASCG) Permanent Secretary-PO- RALG Directors (DPPs) of Agricultural Lead Ministries Semi- Annual Technical Committee of Component Leaders(TCCL-PO- RALG) Director of Sector Coordination- PO-RALG Component Leaders of PO- RALG Plus other Directors at PO-RALG Quarterly Regional Consultative Committee (RCC) Regional Commissioner(RC) Regional Administrative Secretary (RAS), Administrative and Assistant Administrative Secretaries, Head of Units (As per Act) Quarterly District Consultative Committee District Commissioner (DC) District Executive, Head of Departments (As per Act) Quarterly Full Council Council Chairperson Members of Council, Management Team (CMT), DED (As per Act) Quarterly 140 Agricultural Sector Development Programme II (ASDP-II) Institution Chair Members Frequency of Meeting Ward Development Council Councillor Members of WDC Quarterly Village Council Meeting Village Chairperson Members of Council Meeting Monthly Village Assembly Village Chairperson All villagers above 18 years with sound mind Quarterly E. Management Information System and monitoring 362. M&E is a vital component for the effective management of a programme. It must be clearly defined and structured at the onset of the programme to inform all sector stakeholders on the expectations for performance indicators. ASDP II will utilize available advanced technology (ICT) to increase the delivery and analysis of information from the field. This will involve the use of tablets, smartphones and computers to increase the capabilities of officers at field, district and regional level for computer literacy and quality data management. 363. Design of the M&E instrument demands a professional approach if it is to effectively serve its purpose. Attention to accuracy by correspondents will be enhanced when they receive feedback from analysis, which also helps increase their awareness of their own performance and to maintain interest in their development. Exchange of views resulting from discussion over data and data analysis also helps enhance coordination and improve transparency of management systems, expectations and performance. 364. With these conditions in mind, NCU will apply an M&E framework and instrument template very early in the programme so as to be effective and efficient at guiding the programme. The framework must describe the pathway for information flow, the responsible parties in its execution, the timeframe, the analysis method in relation to the objectives of the process and the mechanism for response to the conditions that it reveals. Collaboration with the professionals in Natational Bureau of Statistics (NBS) will provide synergies and efficiencies in collection and analysis of data. 365. An M&E specialist will be recruited to work part of the NCU. The specialist will manage the process and ensure its relevance and effectiveness: quarterly reports will conform to a template to specify the information required. Responses should be formalized, brief, numerical and, as far as possible, simplified to yes/no answers. Narrative, if needed, should be structured, unambiguous and confined to brief explanation. Data provided must inform the NCU and all components of the ASDP II institutional hierarchy of the progress toward national goals as expressed in the ASDP II objectives, as well as progress of componennts, sub-components and priority investments areas and projects, the efficiency of implementation and the impact on production, food security, resilience, capacity or capability depending on the objective of the projects. The overall measure and impact assessment will be through the results framework (RF). 366. The purpose of data collection must be clear to those demanding it and to those providing it so as to improve the usefulness of the exercise and to inform the need for response. Conclusions from analysis must inform NBS, PO-RALG, ASLMs, RSs, districts, wards and villages. As part of the annual budgetary process, it should improve performance of programme implementation, stimulate interest and engender a concept of national connectivity and common purpose. 367. Under the terms of the memoranda of understanding, information on activities and their achievements will also be collected from NGO projects or off-budget development partner projects to cover sector- wide performance and indicators of progress towards national objectives. Data collected at village level will be delivered in hard copy (paper forms) until advances in access and use of ICT solutions allow for electronic collection and transmission. Village data will be delivered to wards and from wards to districts. 141 Agricultural Sector for Industrial Development 368. At district level, the results will be collated, consolidated and digitalized into a standardized format for electronic transmission to the RS. The RS will ‘clean’ the data by checking consistency and consolidate the information into standard format to form a local level consolidated report for transmission to PO- RALG, with a copy to NCU where further consolidation and analysis will contribute to national quarterly and annual reports. 369. Choice of indicators must be carefully considered and limited to useful information by key decision makers to avoid overburdening the generators of the information and creating superfluous and irrelevant data. Relevant results framework indicators should inform the progress towards project/programme objectives and accommodate information on efficiency, effectiveness, relevance and impact so as also to be interpreted in terms of cost/benefit ratio. Data should also inform the programme about compliance with cross-cutting considerations and targets including gender and environment. F. Safeguard Aspects—Social and Environmental management 370. Since “development” without considering environment or social advancement can be retrogressive in the long run it is important that thorough consideration of factors affecting them is entrenched in the process of project selection. 371. Environmental consideration may include a wide range of impacts including erosion, deforestation, air pollution, water-source contamination, flooding, soil degradation, noise, visual landscape deterioration, traffic congestion, health hazard from agrochemicals or accidents, rodent or pest infestation including malaria, schistosomiasis, trypanosomiasis etc. Social safeguards include gender equality, working conditions, family disruption, labour and child labour exploitation, disruption of schooling, personal security, nutrition, stress, exposure to accident and health hazard, civil strife due to wealth discrepancy, migration etc. 372. The safeguards are incorporated in a two-step process. First, by enumerating the criteria for selection of projects on the basis of environmental and social consideration. Second, for projects that may entail a risk, by undergoing Environmental and Social Impact Assessment (ESIA) by professional specialists in those fields before commitment to implementation. 373. Impact assessment specialists can be registered and dispatched to undertake the assessments as required under contract or, if there is sufficient demand, under long-term employment with the NCU. The cost of ESIAs, where it is necessary, must be included in the implementation cost of the project. 374. Regulatory Framework. The principal national environmental law in Tanzania is the Environmental Management Act 2004, which stipulates the need to carry out an environmental impact assessment study before commencement or financing a project. The most relevant regulations, which will be used to guide environmental and social management under ASDP II, are the Environmental Impact Assessment (EIA) and Audit Regulations of 2005. The regulations provide for the requirement and procedures for undertaking, reviewing, approval and auditing of EIA for different types of projects and their respective level of assessment required. The overall responsibility of overseeing environmental and social management at national level lies with the National Environment Management Council (NEMC) under the Vice President’s Office. The ministry has a full-fledged Environmental Management Unit, which coordinates and oversees the implementation of environmental and social management issues within the agriculture sector, including ASDP. At LGA level, environmental and social management will be coordinated by the District Environmental Management Officer (DEMO). 375. In accordance with Environmental and Social Impact Assessment (ESMF, RPF) and Audit Regulations, investments in the agriculture sector fall under Type A Projects, which are likely to have significant adverse environmental impacts. Therefore, EIA are mandatory for agricultural projects and include in-depth studies to determine the scale, extent and significance of expected impacts and the identification of appropriate mitigation measures. The ASDP II support to production intensification and commercialization for selected commodities in different AEZs is likely to generate both positive 142 Agricultural Sector Development Programme II (ASDP-II) and negative impacts, including by: (i) higher adoption of improved technologies and use of inputs; (ii) irrigation infrastructure development; and (iii) improved market efficiency by aggregating outputs (such as warehousing) and value addition to enhance income growth. 376. The positive socio-economic impacts envisaged from the ASDP II programme include: (i) increase in agriculture productivity and incomes to rural communities in selected districts in terms of creation of more and better entrepreneurship opportunities; (ii) reduced household vulnerability; and (iii) improved living standards and increased rural employment opportunities. These will lead to improved food security and nutritional status for participating districts, and improved livelihood conditions, including improved access to socio-economic services. The programme will further enhance the capacity to mainstream environmental and socio-economic issues into development activities and improve stakeholders’ environmental and social awareness in selected districts. 377. Potential negative impacts are likely to be associated with the implementation of commodity value chain (CVC) activities and irrigation infrastructure development and value addition sub-projects. Potential impacts may include: (i) point and non-point pollution of water sources, due to spillage of agrochemicals or waste water from processing facilities; (ii) soil erosion and increased loss of soil fertility and other issues from inappropriate use of agricultural inputs; (iii) noise and air pollution; (iv) spread of diseases (such as HIV/AIDS), especially during construction phase of sub-projects; and (v) land use conflicts, among others. Irrigation infrastructure rehabilitation and expansion appears most critical as it could lead to degradation of river catchments and riparian ecosystems/biodiversity, soil salinization, loss of forests and other vegetation diversity, reduction of environmental flows, degradation of ecologically sensitive areas in the wetlands, increased water borne diseases, and water contamination due to non-appropriate use of agrochemicals. Furthermore, infringement on property and access rights, population influx seeking employment or other livelihood opportunities, increased conflicts over water use within schemes and between upstream and downstream users also need to be considered. Strategic Environmental and Social Assessment (SESA) for the National Irrigation Master Plan (NIMP) and National Irrigation Policy of 2011 provides details of potential impacts and proposed mitigation measures for irrigation activities in the country. 378. Capacity for Environmental and Social Management. Over the years, capacity improvement to manage environmental and social issues has been done through implementation and training under several Bank-funded operations in the agriculture sector, such as ASDP-1, PADEP and AFSP. Nevertheless, institutional and technical capacity for environmental and social management at the district and lower levels of LGAs still need improvement. This deficiency will be addressed in detail during programme implementation at district level. 379. Under ASDP-1, a SESA was prepared. The SESA covers the country’s national irrigation policy and national irrigation master plan, and it provides specific guidance for investments in irrigation. The SESA identifies potentially adverse environmental and social impacts emanating from the implementation of the national irrigation policy/national irrigation master plan and identifies strategic guidance on how to minimize and mitigate those impacts when implementing irrigation development projects/programmes in the sector. An environmental and social audit for ASDP-1, which is underway, will provide more insight and lessons on the capacity in the key implementing institutions with regard to environmental and social management. VII. BENEFITS AND ECONOMIC AND FINANCIAL ANALYSIS (EFA) A. Summary of benefits 380. In line with the importance of the sector, agricultural transformation and accelerated rural development will make a major contribution to Tanzania’s national development aspirations. The principal benefits 143 Agricultural Sector for Industrial Development of the programme will be: (i) increased and sustainable productivity and production of food and non- food agricultural commodities to improve rural incomes, boost rural households and national level food security, and provide raw materials for the agro-industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural sector generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to adapt to climate change; and (v) improved institutional capacity to mobilize and manage resources in support of agriculture sector development. Not surprisingly, considering the size of the planned investment over a 5-year timeframe, and the scope of activities to be funded, the range of benefits will be extensive138. All of the above will contribute to Tanzania’s higher level national development goals as expressed in Vision 2025. 381. Several other benefits are also expected to accrue as the sector develops including: (i) reduction in harvest and post-harvest losses; (ii) increased export earnings; (iii) diversification of production into higher value agricultural products; (iv) improved access to financial services by smallholder farmers and rural entrepreneurs; (v) reduced transaction costs and improved efficiency in pre- and post-farm gate value chains; (vi) increased participation in cooperatives and other forms of FO; (vii) improved access to markets through infrastructure development; (viii) increased rural employment; (ix) higher productivity and reduced vulnerability to droughts from expansion of irrigated agriculture; (x) maintenance of agricultural biodiversity; and (xi) improving the system of disaster risk management by exploring the use of innovative risk management tools. The agricultural transformation will also ensure (xii) reduced gender related imbalances; (xiii) reduced child labour in agricultural sector by promoting decent work in accordance with ILO guidelines139; and reduce contribution of agriculture to climate change through promotion of CSA140Functional networks between production and markets. ASDP-1 emphasized generation and transfer and adoption of production technologies. Developing commercial skills and strengthening networks, linking farmers to markets were still limited. Therefore, the formulation of ASDP II has focused on developing a network of functional and market-driven value chains, involving key stakeholders (farmers, marketers and agroprocessors) who are aware of their mutual linkages, as well as complementary investments, make a deliberate effort to improve them, and organize themselves in such a way that they can benefit from participation in the CVC. The ASDP II intervention is aimed at reducing isolation and encouraging and strengthening collective action and networking among value chain participants to enhance willingness to invest in new technology, infrastructure, production and processing for higher income. 382. Economy of scale. Economy of scale in production is a limiting factor. Smallholder’s production and productivity relative to market opportunities in and outside the country is small. Scale of production is so small that buyers for large markets are not usually keen to form partnerships. Therefore, the emphasis given to strengthening cooperatives and FOs and to promoting production under the programme is to enable product aggregation and to increase productivity to reach a scale that would make economic sense to participate in a value chain. 383. Improved competitiveness. Interventions aimed at overcoming market failure and improving productivity, markets and competitiveness will provide substantial benefit to all the participants in the value chain. Broadly, the following critical factors that affect competitiveness will be addressed through the programme: technology constraints in production and post-production systems and poor infrastructure are addressed by Component 2; access to markets is addressed by Component 3; grants and information about credit; and paucity of effective FOs, producer associations, trade associations, 138 The results framework in Annex II shows the linkages between various interventions and their strategic outcomes. 139 Conclusions of the “International Workers’ Symposium on Decent Work in Agriculture” Geneva, 15-18 September 2003 140 (Lipper et al. 2014) 144 Agricultural Sector Development Programme II (ASDP-II) and coordination mechanisms among stakeholders are addressed by Component 4. Moreover, the programme interventions will yield direct benefits such as: (i) increased operating efficiency at farm level through improvements to production and marketing process, logistics, and market institutions; (ii) extended value addition at farm and/or post-farm level with greater integration between producers, traders and processors along the value chains; and (iii) increased market access. In addition, the project Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector’ will provide further indirect benefits in the form of: (i) stronger FOs that are able to actively and profitably engage with the market; (ii) more market-oriented and active agribusinesses with stronger links to producers; and (iii) more structured planning for value chain improvements at district, region and national levels. 384. Impact oriented implementation mechanism. The programme’s implementation mechanism, based on priority value chains which focuses on AEZs, together with a demand driven investment programme support is likely to result in substantial benefits. The program will target in high potential Commodity Value Chains (CVCs) in Agro ecological zones (AEZ); Through this model, the program will implement investments and commodities that create the greatest impact- Agricultural yields, profitability, farmer’s profitability growth, commercialization and industrialization potential 385. A pluralistic delivery system where private, public, and NGO service providers will participate in organizing the value chain participants, strengthening linkages and providing technical and business advisory services will have a sustainable positive impact. The construction of rural market infrastructure will be demand-based and financed jointly with the beneficiaries, leveraging substantial resource mobilization, including from the private sector. 386. Countering the impact of drought and climate change. The programme has a major irrigation development projects under Component 1. This is to counter the danger the agriculture sector and the Tanzanian economy at large face due to the unreliability of rainfed agriculture, which is the dominant mode of agriculture. Agriculture is affected by frequent drought, which leads to famine and has a significant negative impact on the country’s GDP. Climate change is also expected to decrease precipitation and increase its variability in arid and semi-arid regions of Tanzania. Further to irrigation development, the priority interventions are also promoting Promote Climate Smart Agriculture (CSA) technologies and practices. The programme ensures integrated soil and water management, conservation agriculture and agroforestry to overcome these challenges and sustainably improve the sectors productivity and resilience under rainfed conditions. 387. Benefits will also arise from several of the cross-cutting thematic areas of the ASDP II including: (i) improved institutional capacity and human resources at all levels; (ii) more balanced participation of women and men (old and young) in development and income-generating activities and both household and community level decision-making processes; (iii) recognition of the special needs of rural households affected by HIV/AIDS and/or poor nutrition and efforts to improve household nutrition and curb the spread of the disease; and (iv) improving the adaptability of the agricultural sector to climate change and reducing Tanzania’s contribution to global greenhouse gas emissions. A positive economic impact will be assured by requiring all proposed investments to be subject to thorough technical and financial feasibility studies to ensure that those likely to generate robust financial and economic returns are given high priority, and all proposed investments meet a minimum (hurdle) rate of return. B. Economic and Financial Analysis Introduction 388. An economic and financial analysis was undertaken to assess the viability of the investments proposed for ASDP II. The main economic benefits of these interventions are expected to be: (i) increased crop production through improved crop yields, higher cropping intensity, and diversification to higher 145 Agricultural Sector for Industrial Development value crops; (ii) enhanced livestock and fish production; (iii) higher farm incomes from agricultural production; (iv) increased income from agribusinesses and greater value addition; and (v) higher export earnings. 389. It is estimated that farmers on 2,000,000 hectares of non-irrigated land will benefit from improved agricultural support services, development of farmer organizations, and better access to markets and rural finance. Furthermore, investments in land and watershed management will help to ensure that increases in crop production are sustained in areas which are vulnerable to soil erosion and declining soil fertility. In addition, it is estimated that the improved irrigation infrastructure will benefit an irrigable area of 165,000 hectares, comprising 65,000 hectares of new and expanded irrigation schemes and 100,000 hectares of existing irrigation schemes which will be rehabilitated under ASDP II. 390. For irrigated land, cropping intensity is expected to rise to 135% while for non-irrigated land it is assumed to increase to 100%. It is also anticipated that the average yields of paddy rice would rise from 1.75 to 3.0 tons/ha. The corresponding increases for other crops are: 1.35 to 2.20 tons/ha (maize), 1.0 to 1.4 tons/ha (oilseeds/pulses) and 15.0 to 25.0 tons/ha (vegetables). 391. The development of water resources for livestock as well as the provision of support services are expected to result in an increase in livestock productivity and farm incomes. Increases in livestock productivity will primarily arise from the adoption of improved pasture management, enhanced nutrition and better animal health. The proposed fisheries interventions are primarily aimed at increasing aquaculture production through the expansion of fish ponds as well as improved support services. 392. ASDP II also includes measures to expand farmers’ access to rural markets, improve marketing systems and provide support to agribusinesses. These interventions are likely to provide significant economic benefits, such as enhancing CVCs, increasing value addition, and improving the income and employment opportunities of agribusinesses. However, the economic benefits of these interventions have not been quantified in the economic and financial analyses. Financial Analysis Crop Budgets 393. A financial analysis was undertaken to assess the likely impact of ASDP II interventions on farm incomes. Four budgets were prepared to represent the main crops grown in Tanzania, namely maize, rice, oilseeds/pulses and vegetables. Crop budgets were prepared for the present, future without project, and future with project situations. 394. The financial crop gross margins are summarized in Table 56 and it is evident that, in the future with project situation, there is a significant improvement in the net returns for all types of crop. This reflects the notably higher yield levels which generate incremental returns in excess of the additional production costs. It is also apparent that net returns from vegetables are substantially higher than returns from other crops. However, the high returns from horticultural crops are moderated by the risks associated with very large seasonal price fluctuations. Table 56: Financial Crop Gross Margins in Present, Future Without and Future with Project Gross margins (TSh per hectare) Present Future Without Project Future with Project Maize 67,088 119,831 216,550 Rice 322,500 423,844 709,375 Oilseeds/pulses 512,625 613,250 807,500 Vegetables 2,267,000 2,583,875 2,927,250 Source: Crop budget estimates 146 Agricultural Sector Development Programme II (ASDP-II) 395. It is envisaged that the future with project yield levels would be fully achieved within five years of completing the strengthening of agricultural support services, implementation of improved land and watershed management, as well as the construction of irrigation infrastructure envisaged under the programme. 396. In the financial analysis, budgets were also prepared for two livestock enterprises, namely dairy production and beef fattening (Table 57). In the future with project situation, the improvements in net returns primarily reflect the higher levels of productivity. Table 57: Financial Livestock Gross Margins in Present, Future-without and Future-with project Livestock Enterprise Financial gross margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 176,975 311,975 Beef Fattening 77,900 102,900 Source: Livestock budget estimates Cropping Patterns 397. In the existing irrigated area, it is anticipated that the areas of rice, oilseeds/pulses and vegetables will increase in both the wet and dry seasons. In the proposed irrigated area, there will be a significant change in cropping pattern with a major expansion in the area of rice in the wet season and the introduction of maize, rice, oilseeds/pulses and vegetables in the dry season. Cropping intensity is expected to increase from 125% to 135% while, on the proposed irrigated area, cropping intensity will rise from to 90% to 135%. For non-irrigated areas, cropping intensity in the future with project situation is estimated at 100%. Overall, cropping intensity in the ASDP II area is expected to increase from 92% to 103%. Farm Budget Analysis 398. Farm budgets were prepared for an average sized farm of 2.0 ha and a summary of the net farm incomes for the different ASDP II areas is given in Table 58. Comparing the present and future with project situations, net farm income in the existing irrigated area is expected to increase from TSh 900,568 to TSh 2,665,228 (before irrigation O&M costs) while, in the non-irrigated areas, net farm income is estimated to rise from TSh 367,385 to TSh 1,158,275. Overall net farm income is expected to increase from TSh 436,699 to TSh 1,655,569 per annum. 399. When irrigation O&M costs are included, net farm income in the irrigated areas falls to TSh 2,229,994 per annum in the irrigated areas. However, as irrigation costs only account for about 16% of net farm income, farmers will have the ability to meet annual O&M costs. Table 58: Net Farm Incomes in Present, Future-without and Future-with project Irrigation Status Net Farm Income (TSh per annum) Present Future Without Project Future with Project Excluding Irrigation O&M Costs Including Irrigation O&M Costs Rehabilitated irrigated area 900,568 1,138,498 2,665,228 2,229,994 New irrigated area 367,385 496,902 2,665,228 2,229,994 Non-irrigated area 367,385 496,902 1,158,275 Overall 436,699 580,309 1,655,569 Source: Farm budget estimates 147 Agricultural Sector for Industrial Development Economic Analysis Economic Pricing 400. Economic prices for internationally traded goods were derived from the World Bank commodity price projections for 2015. Local transport, handling, storage and processing costs were based on the current rates prevailing in Tanzania. However, these financial prices were converted to economic prices by applying the Standard Conversion Factor (SCF) of 0.95. Labour costs were based on rural wage rates. However, given the high levels of underemployment, a shadow wage rate of 0.65 was used to determine the economic value of labour. 401. The economic analysis was undertaken over a 50-year period in 2015 constant prices and a shadow discount rate of 12% was assumed. The Tanzania shilling was used as the unit of account and an exchange rate of TSh 2,150 to USD 1.0 (June 2015) was applied when converting to USD. It was anticipated that the programme would be implemented over a 10-year period. C. Economic Benefits 402. In the estimation of agricultural benefits, economic crop gross margins per hectare were calculated by valuing the physical input and output quantities in terms of their respective economic prices. The economic gross margins per hectare were then multiplied by the respective crop areas to estimate net crop benefits in the present, future with and future without project situations. Net livestock benefits were also estimated for the three project situations (based on the respective livestock populations and economic gross margins). 403. As a result of these increases in crop and livestock production, net agricultural benefits to farmers within the project area were estimated to rise by TSh 626,572 million per annum (from TSh 245,152 million to TSh 859,700 million per annum at full development). It is envisaged that the future with project agricultural benefits would be fully attained within two years of programme completion. Benefits from crop production are estimate to account for 81% of the overall agricultural benefits. D. Operation and maintenace costs 404. The long-term annual operation and maintenance costs of the irrigation infrastructure were also included in the economic analysis. These financial costs were then converted to economic values, and the annual economic O&M costs. In addition, the annual costs of support services were included in the analysis to ensure that agricultural production continues to grow after completion of ASDP II. E. Economic Viability and Sensitivity Analysis 405. The results of the economic analysis indicate that the IRR of ASDP II is 14.8%. These results show that the proposed project investment is justified on economic grounds. Sensitivity analysis was also undertaken to test the economic viability of the proposed interventions to various changes in the cost and benefit streams. This analysis indicated that ASDP II is fairly sensitive to changes in benefits and costs and becomes uneconomic with an increase in capital and recurrent costs of 21%. Similarly, an 18% decrease in incremental project benefits would result in the EIRR falling below 12%. 406. The results of the sensitivity analysis are given in Table 59 which shows that a decrease in capital and recurrent costs of 20% resulted in an EIRR of 18.8%, while a cost increase of 20% lowered the EIRR to 12.1%. Similarly, an increase in incremental benefits of 20% produced an EIRR of 18.0% and a benefit decrease of 20% reduced the EIRR to 11.6%. In addition, changes in the expected cropping intensity were also assessed and the analysis indicated that if a future with project cropping intensity of 100% is assumed (in comparison to 103% in the base case), the EIRR falls to 10.7%, while a cropping intensity of only 95% will further reduce the EIRR to 7.7%. 407. With regard to crop productivity, the analysis indicated that if yields of maize and rice only increased by 148 Agricultural Sector Development Programme II (ASDP-II) 50% (in comparison to 57% and 67% in the base case), the EIRR falls to 10.7% and ASDP II becomes uneconomic. It should therefore be emphasized that the adoption of improved cropping practices and expected increases in crop yields (to maintain economic viability) will only be achieved if adequate agricultural support services, including extension/training and input supply as well improved access to markets and rural finance, are made available to farmers in an effective and efficient manner. Table 59: Economic viability and sensitivity analysis Scenario EIRR (%) NPV (TSh million) Base Case 14.8% 370,009 Capital and Recurrent Costs -20% 18.8% 722,428 Capital and Recurrent Costs +20% 12.1% 17,589 Incremental Benefits +20% 18.0% 796,430 Incremental Benefits -20% 11.6% -56,413 Costs -20% and Incr. Agric Benefits +20% 22.6% 1,148,850 Costs + 20% and Inc. Agric Benefits -20% 9.3% -408,832 100% Cropping Intensity with Project 14.3% 299,966 95% Cropping Intensity with Project 11.8% -21,536 50% Increase in Crop Yields 10.7% -531,096 40% Increase in Crop Yields 7.7% -165,650 F. Programme Sustainability 408. Long-term sustainability of the programme will be determined by the extent to which it delivers results, i.e., improving agricultural and agribusiness service delivery for sustainable productivity growth and subsequent gains in farm production, income and resilience, especially in rainfed production systems for crops and livestock. Improving the responsiveness of key services to respond to farmers’ demand, together with supporting agribusiness investments, key infrastructure, professional services and adapted policy environment should improve the overall impact. In the medium term, smallholder farmer empowerment and the consolidation of their organizations will allow for strengthened voice and building-up of capacities for technical and economic service provision to their members. 409. ASDP II aims to achieve a sustainable increase in agricultural productivity and commercialization by most smallholders (at least 20%). This will be achieved through scaling up of technologies which are appropriate, affordable and profitable to smallholder farmers, and can be sustained without ongoing support in the long run. ASDP II will utilize the principles of sustainable agricultural intensification by enabling farmers to develop intensive diversified farming systems, and at the same time create an enabling environment for rural commercial development in which farmers can access commercial input and output markets, towards improved productivity and profitability of market-oriented farming. 410. ASDP II addresses the social dimension of sustainability through ensuring that household food and nutrition needs are satisfied and that rural people are protected from the impacts of natural disasters and acute food shortages, which can deplete household assets and reverse hard-won gains. Particularly, the programme addresses the high prevalence of under-nutrition and malnutrition, which limit productivity and threaten the sustainability of human development in rural households and communities. For Tanzania to achieve its development aspirations there is need to have a substantial upswing in the rate of investments in agriculture and food security. ASDP aims at providing additional resources for enhancing outcomes across all programme areas to achieve the programme development objective. 411. In summary, ASDP II sets out a clear roadmap for ongoing developments towards increased competitiveness and profitability of the sector and confirms government and donor responsibilities in meeting the challenges of transforming the agricultural sector within a coordinated approach. 149 Agricultural Sector for Industrial Development VIII. IMPLEMENTATION MODALITIES AND RISKS A. Implementing agency and stakeholder assessment 412. The implementation of ASDP II will follow the government structures/systems for procurement, financial management and environmental and social safeguards. The proposed programme will require enhanced reporting on results and impact: The M&E system will include and be aligned with the program results tracking system. Furthermore, the coordination of sector support under the ASDP II need to be aligned with the overall ASDP II framework at national and local levels for efficient implementation and effective delivery of results. 413. Building on ASDP-1. ASDP-II is building on experiences, achievements, capacities and systems developed during ASDP-1, in alignment with the government’s priority investments for achieving quick results. While the focus, approach and scope of the proposed ASDP II programme will significantly differ from ASDP-1, the delivery systems and structures will to a large extent remain the same, to be strengthened to enhance their capacity to deliver envisaged programme results. The design of the programme has integrated support for institutional strengthening of implementing agencies and capacity building activities for farmers and other key technical areas, including results monitoring and coordination. 414. Programme Stakeholder Assessment. Programme implementation will involve a range of sector stakeholders, partners and beneficiaries at different levels. This includes government institutions (national, regional and local levels), the private sector, namely input and output traders, PSPs, agro- industries/processors, FOs, NGO, financial institutions and others. The capacity of stakeholders varies across the implementation levels: the participation of the private sector in agriculture remains still weak and stakeholder coordination at local levels is inadequate. The sector-wide coordination framework currently under preparation will improve coordination among various players supporting the agricultural sector. There are also efforts to establish CVC platforms, especially at district (cluster) level, to enhance stakeholder coordination. 415. The institutional and human capacity developed during the first phase of ASDP will be utilized for implementation of the proposed operation. The ASLMs will be strengthened to improve its analytical skills and results orientation within strengthened programme management and coordination capacities. Fiduciary, M&E and other critical technical competencies, such as CVC analysis, need to be further strengthened for support effectiveness and sustainability. ASDP II will require much enhanced emphasis on real-time reporting on results and impact. The coordination of sector support under the Programme at the national and local levels needs to be clarified and made more efficient in order to enhance delivery. 416. Development Partners. Most of the development partners have expressed interest in supporting the government’s efforts towards agricultural development through a sector-wide approach such as ASDP II over the 2015/2016–2024/2025 period. However, some of these contributions are already earmarked or designed as stand-alone projects, such as contributions by JICA (mainly irrigation infrastructure and development), IFAD (Bagamoyo smallholder sugar project141) and IDA and Bill and Melinda Gates Foundation (BMGF). Therefore, non-earmarked basket funding is expected to originate from development partners and from the Government of Tanzania budget. A memorandum of understanding stipulating principles for managing the Basket Fund will be signed by all Basket Fund development partners, including the coordination and harmonization mechanisms for earmarked and non-earmarked funds. A framework for coordinating and harmonizing the Basket Fund with non- basket (off- and on-budget)142 funded projects/programmes and initiatives in the sector, including mutual contributions to the sector coordination and the common M&E. 141 The ongoing preparation of a loan to support an out-grower sugarcane scheme in Bagamoyo is an attempt by IFAD to engage in a public–private sector partnership in Tanzania, based on experiences from palm oil in Uganda and sugarcane in Swaziland. 142 Most bilateral donors and NGOs will provide off-budget funding, such as among others USAID through a direct agreement with the Roads Fund to develop the rural road infrastructure in key SAGCOT districts. 150 Agricultural Sector Development Programme II (ASDP-II) B. Risks 417. The key risks associated with the programme are: (i) The sector policy and economic environment has not been conducive for agribusiness partnerships. This situation may lead to poor participation of agribusiness partners in programme activities, especially their envisaged role in value chain development with smallholder farmers’ commercialization. To mitigate this risk, the programme has proposed introducing competitive matching grants for agribusiness to provide opportunities for district CVC stakeholders’ platforms and agribusinesses to participate in programme activities. These matching grants will be used to catalyse financing of agribusiness investments identified by FOs in partnership with agribusiness. The district CVC platforms will serve as incubators for partnerships at local level. While the performance of district CVC platforms is essential to engendering programme success, the CVC platform functions are inherently difficult to measure and monitor and incentivize. Furthermore, the policy environment needs also to change, especially in relation to export and local taxes on agriculture products, ad hoc interventions such as tariff waivers and export bans, etc., for improved sustainability. Inadequate policy incentives for participation of private agribusiness partners in programme activities, especially their envisaged role in value chain development will undermine achievement of programme objectives of commercialization. The ongoing dialogue on improving environment for private sector investment continues, and the government is committed to enhancing private investment in agriculture through initiatives like Kilimo Kwanza and SACGOT. (ii) The programme will be implemented under a complex institutional structure, multi-sectoral, multi-donor Basket Fund environment, in parallel with several stand-alone projects (on- and off-budget). This may lead to conflicting agenda and interests, and weaken local capacity to manage and coordinate programme activities. To mitigate this risk: (a) the programme activities have been aligned with a joint governments overall ASDP II programme/framework; (b) the sector-wide coordination framework, with supporting mechanisms at various levels, will enhance coordination and harmonization of projects and programmes in the sector; (c) the programme will support LGAs (under Component 4) to develop a comprehensive sector coordination framework that integrate activities of all projects in the sector at local level through DADPs; (d) a memorandum of understanding will be signed by all ASDP basket donors and the government to agree on principles for operating and managing support to the overall ASDP II programme/framework; and (e) institutional arrangements and coordination mechanisms for implementing agencies used in ASDP-1 will be strengthened. (iii) The declining rate of budget execution, delayed and incomplete releases of development funds, including foreign funds may result in cash flow problems to programme beneficiaries and thus undermine achievement of programme objectives. To address this challenge, the government has changed its budget cycle, to start earlier (in April) to enhance timely flow of funds and improve budget execution. However, the financial calendars of donor agencies are not always compatible with this timing and the release of donor funding may not always be in harmony with the execution of the national budget. Dialogue under the PRSC series includes these issues. (iv) Results monitoring remains a challenge in the sector due to weak capacity for data collection analyses and management. To mitigate this risk, the proposed programme includes support for institutional strengthening and capacity building to improve the M&E system for tracking, analysing and disseminating results. The programme should also be aligned in a common government M&E system that emphasizes results management, transparency and accountability. (v) The agricultural risk management perspective could be formally included in the ASDP II since it has become clear that the realization of production and price risks are determinants of food insecurity and monetary losses for participants along major CVCs. Introducing a risk lens 151 Agricultural Sector for Industrial Development will contribute to the sustainability of the investments on productivity. Potential areas to be included for risk management need to be identified for each AEZ and production system. Crop diversification, small-scale irrigation development, conservation farming, integrated soil and water management, and climate smart agriculture have already been included under research and advisory services, and warehousing linked with a commodity exchange programme under commercialization/agribusiness activities. All these elements will contribute to resilience and sustainability of agricultural production systems. 152 Agricultural Sector Development Programme II (ASDP-II) ANNEXES ANNEX I: ASDP II Components Implementation Plan, Sequencing and Scheduling COMPONENT 4 PROJECTS SEQUENCING (Sector Enablers, Coordination and Monitoring and Evaluation) Component Objective: Strengthening Sector Enablers, Coordination and M&E Outcome: Strengthened institutions, enablers, coordination and M&E frameworks Component Key Performance Indicators (KPIs): ● Reviewed and harmonized Agricultural sector related policies, laws, regulations and institutional procedures ● Improvement in ranking in WB’s doing business and Enabling the Business in Agriculture (EBA) ● Increased sector productivity, value/prices, profitability and growth potential relying on improved knowledge management and efficient ICT use ● Integrated Sector Monitoring and Evaluation (M&E) system SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.1 Policy and Regulatory Framework i) Reviewed and harmonized agricultural sector related policies, laws, regulations and institutional procedures 4.1.1 Policy and Regulatory Framework and Business Environment Improvement 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment Enabler to other components, Policy environment is dynamic 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) Continuous project ii) Extent (%) of policy and regulation compliance (e.g., “compliance rates”) 4.1.1.3 Developing of Fisheries Master Plan in Tanzania Main Land It’s a roadmap to fisheries sub sector 4.1.1.4 Strengthening and control of child labour in Agriculture It is dependent on review and harmonization of relevant policies and regulations 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector It is dependent on review and harmonization of relevant policies and regulations 153 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.2 Stakeholder empowerment & organization Enhanced knowledge management and ICT systems 4.2.1 Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing Farmer Organizations and cooperatives Movement 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector Central for implementation of the program Steering committee and consultative meetings held and resolutions implemented at national and local levels. • Business efficiency in delivering services to clients by government (e.g. faster response to problems and solution provision) Timely, relevant, accurate and user friendly cost effective information is available to stakeholders when and where needed DADPs that meet assessment criteria 4.2.2 Promote and strengthen gender inclusiveness in the agricultural sector 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) It cuts across all the implementation components (1,2,3) 4.3 ASDP II_sector coordination (planning & implementation at national, regional and LGA) Agric. investment coordinated under ASDP II (on/off budget) 4.3.1 Improved and strengthen vertical coordination (from PO-ALG to RSs and LGAs) and horizontal coordination between ASLMs 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication Central for implementation of the program Execution of allocated budget Quality and timely submitted quarterly reports at all levels Coordination unit for planning & monitoring established and operational • Guidelines compliance rate at all levels 154 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.4 Monitoring and Evaluation (including Agricultural statistics) • AASS implemented 4.4.1 Improved Capacity and agricultural data collection and management systems 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. Central for monitoring of the program RS and LGAs to provide quality data through different M&E systems timely. 4.4.2 Develop Agricultural Sector M&E System 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. Central for monitoring of the program Joint M&E systems established and operational 4.5 Institutional capacity development, and knowledge management and ICT 4.5.1 Improvement of Capacity in all levels 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels Central for implementation of the program 4.5.2 Improvement of ICT for Agricultural Information Services and Systems 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. It’s the key enabler for coordination 4.6. Access to rural financing 4.6.1 Provide microfinance services 4.6.1.1 Access to agricultural financing for improved commodity value chain Enabler for Agricultural Investments 155 Agricultural Sector for Industrial Development COMPONENT 3 PROJECTS SEQUENCING (Commercialization and value addition) Component Objective: Improved and expanded rural marketing and promote value addition by thriving competitive private sector and effective farmer organizations Outcome: Strengthened and competitive commodity value chains Component Key Performance Indicators (KPIs): ● % Increase in volume and monetary value of exports ● % Increase in Monetary value of Foreign Direct Investment (FDI) and private capital flow to agricultural sector ● % Increase in job creation by new and expanded investment in agribusiness ● % Reduction in volume and monetary value of food import ● % Increase in profitability of produce and products at a farmer and enterprise level ● % Increase in market share of products at all market levels ● % Increase in products compliance to national and international standards ● % Increase in standardized marketing infrastructure along the value chain ● % Increase in participation of vulnerable groups (Women, Youth, and Pastoralist) in rural commercialization and value addition in decision making and benefiting from main programs along the value chain 156 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 3.1 Marketing % change in investment in market infrastructure 3.1.1 Develop market access for all priority commodities. 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets storage facilities are a major concern’ high post harvest losses; quality issues; supply volume % Farmer/FO/ Traders using improved market infrastructure in rural areas 3.1.2 Develop market access for fisheries and livestock products 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market storage facilities are a major concern’ high post harvest losses; quality issues; supply volume 3.1.2.2 Improving local and improved chicken market access Quick win project which impacts majority of the rural community) 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing ensures quality/ safety; facilitate market penetration 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain key driver in the sector 3.1.2.5 Improving beef, cabrito and mutton market access Depends on improvement of livestock infrastructure 157 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 3.2 Agribusiness development: value addition and agro-processing % increase of value added produce and products 3.2.1 Development of processing and value addition for Crop, livestock and fishery products 3.2.1.1 Strengthening and development of agro-processing industries for value addition for all priority commodities Low exports; industrialization agenda % Decrease in post- harvest loss 3.2.1.2 Improving milk value chain Lack of infrastructures 3.2.1.3 Strengthening hides and skin value chain Limited basic facilities; not operational 3.2.1.4 Strengthening value chain for horticultural commodities On going initiative; promising future for Tanzania 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange To Increase market access and reduce post harvest losses. 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products There is available market for carcass 3.2.1.7 Enhancing beef, chevron, mutton value addition Raw material readily available 3.2.1.8 Improving Postharvest Management Along Food Supply Chain For sustainable food security and nutrition 158 Agricultural Sector Development Programme II (ASDP-II) COMPONENT 2 PROJECTS SEQUENCING (Enhanced Agricultural Productivity and Profitability) Component Objective: Increased productivity growth rate for commercial market-oriented agriculture for priority commodities Outcome: Improved agricultural productivity and profitability Component Key Performance Indicator (KPIs): ● Increase of Yields (MT/ha, litres/cow/lactation, eggs/hen/day, live weight/cattle at market point, kg/fish) for priority value chains ● Increase of Gross margins (TSh/ha, TSh/dairy cow, TSh/LU, etc.) for priority value chains ● Increase in Profitability/net return (TSh/commodity or enterprise) of priority commodities ● Increased labour efficiency (TSh/farmer/season) and net financial return to farmers ● Percentage decrease in malnutrition (stunting and under weight) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.1 Extension training and information services 1. % of farmers adopted productivity enhancing technologies 2.1.1 Strengthening agricultural extension, training and promotion/ information services (crops, livestock and fisheries) 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) In order to commercialize/ disseminate research outputs to smallholder farmers e.g. through private sectors engagement 2. % farmers satisfied [2] with extension services 2.1.1.2 Strengthening agricultural competence- based training and promotion (all commodities) Focus on smallholder farmers 3. % of disseminated technologies adopted 4. % of Extension staff delivering quality extension services 5. % decrease of pest and diseases incidence (frequency and loss) of economic importance 6. % increase of average household incomes for farmers who adopted technologies 159 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.2 Access to Agricultural Inputs and health services 1. % of farmers using quality agricultural inputs 2.2.1 Improved Access to Crops, Livestock and Fisheries Inputs and health services 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) For increased Productivity and Profitability % of farmers benefiting from inputs subsidy 2.2.1.2 Improving access and availability of quality Poultry inputs Lack of inputs and expensive 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity In Order to commercialize Deep Sea Fishing through private sector participation 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability Ongoing 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability Feasibility study is going on 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity Needed to increase productivity for small scale fishers by employing Fish Aggregating Devices (FADs) 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources Ongoing 160 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.2.1.8 Improvement of plant health services Disease and pests outbreaks as potential risks in the three sub sectors could affect livelihood and productivity growth. Generating high quality technologies through research and use of good agricultural practices will reduce the scale of threat. 2.2.1.9 Production of vaccines and drugs High importation cost 2.2.1.10 Improvement of aquatic and livestock health services 2.3 Agricultural Research for Development (AR4D) 1. % of new technologies released and disseminated by research stations 2.3.1 Strengthening AR4D (crops, livestock and fisheries) 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub- sectors) AR4D is instrumental in generating productivity enhancing technologies and innovations by demand-driven technology generation approach and by improving research- extension-farmer linkages to drive commercialization and dissemination of technologies. 161 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2. Improved capacity [1] of research stations to generate high quality technologies 2.3.2 Research and development 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) Technology is dynamic for increased production 3. % of budget allocated and disbursed (recurrent and development) for Research and Development 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies Ongoing 2.4 Access to Mechanization Services 1. % of households accessing mechanization services for priority commodity value chains 2.4.1 Strengthening and promote agricultural mechanization (crops, livestock and fisheries) 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain Mechanization in the entire value chain 2. % of households accessing processing facilities for priority commodity value chain 3. % reduction of post- harvest losses of commodity value chains 162 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.5 Food and nutrition security 1. % increase of rural households above the food poverty line 2.5.1 Food and nutrition Security improved 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 2. Increase in ratio of national food self sufficiency 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption Increasing demand of nutrition food and industries 3. % reduction of malnutrition incidences (chronic and transitory) 4. % of decrease in macro and micro-nutrients deficiency in children and pregnant women 5. % of households accessing nutritious and diverse food 6. % of households practicing diversified farming systems for improved diets and reduced vulnerability to food shortages 7. % of households accessing livestock and fish protein. 163 Agricultural Sector for Industrial Development COMPONENT 1 PROJECTS SEQUENCING (Sustainable Water and Land Use Management) Component Objective: Improved and sustained Integrated Land and Water Resources Use and Management (Irrigation, Water for Livestock, Cropped Land, Pastures, Ponds/Cage, Soil Fertility Management) Outcome: Expanded Sustainable Water and Land use, and improved Management for Crops, Livestock and Fisheries Component Key Performance Indicators (KPIs): ● Percentage increase of schemes practicing sustainable irrigation ● Percentage increase of livestock keepers with access to permanent water sources (natural or man-made) ● Percentage of modernized irrigation facilities with professional management ● Improved rangelands (ha) with sustainable pasture and water for livestock ● Increased area (ha) under fish farming ● Increased number of maricultural farmers ● Percentage increase of stakeholders implementing CSA technologies SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.1 Land Use Planning and sustainable Water Shed and Soil Management Percentage increase of districts with land use plans 1.1.1 Land use planning and watershed management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones) Land use plans are the basis for the smoothly implementation of other projects Percentage increase of villages with land use plans 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity Reducing conflicts through availability of pasture Percentage increase of watersheds with integrated management plans 1.1.1.3 Enhancing access to agricultural land for youth empowerment Improvement of enabling environment Additional area (ha) under improved agricultural production 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (all products) To ensure availability of water for agricultural activities Percentage increase in water quantity for agricultural production 164 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.2 Integrated Water Use and Management for Crops/ Irrigation and Livestock/ Fishery Development Additional area (ha) under improved irrigation 1.2.1 Irrigation infrastructure development 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity To cover ongoing projects and those remain under other initiatives Cropping intensity for irrigated crops 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity Increased demand of these technologies for water saving Additional permanent water points for livestock 1.2.2 Irrigation schemes management & operation 1.2.2.1 Strengthening Irrigation schemes management and operations To ensure sustainability of irrigation infrastructure Increased area (ha) under fish farming 1.2.3 Water sources development for livestock & fisheries 1.2.3.1 Development of water infrastructures for livestock productivity To ensure availability of water for livestock and reduce conflicts Increased number of mariculture farmers 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries Inclusiveness and on going projects 165 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.3 Mainstreaming resilience for Climate Variability/ Change and Natural Disasters Percentage increase of farmers (crop, livestock and fisheries) adopting CSA technologies and practices 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies 1. Mainstreaming CSA and CA for soil fertility Management and 2. Early warning systems. Proportion of LGAs with mainstreamed CSA in their DADPs 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management Increasing fish habitat destruction Proportion of ASLMs with mainstreamed CSA in their plans 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness Percentage decrease of households who are under the risk of floods or drought General Points taken into consideration in Sequencing Projects: Land use planning is placed first because it the basis for investment, followed by rehabilitation of ongoing irrigation infrastructures and development of new irrigation schemes. The third area is promotion of climate smart and conservation technologies for the purpose of mainstreaming CSA and CA technologies at early stages of planning. Agricultural Sector Development Programme II (ASDP-II) 166 ANNEX II: ASDP II: Results Framework and Monitoring (On-progress) Note: This results framework currently mentions only a few key commodities as an example. The selection of CVC will be adjusted as needed once the framework develops. The Framework covers the first five years of the programme. The framework was assessed and it was realised there was a substantial data gap from which the targets could be developed. Program Development Objective (PDO) or Goal: Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, competitiveness, and commercialization and improve smallholder farmers’ incomes, livelihoods, and food and nutrition security. PDO Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 1 Growth Rate Agricultural Sector Sustain annual agricultural GDP growth of at least 6%, from the year 2016 to the year 2025. 2.1 Percentage change of GDP of the sector ((Current GDP-baseline GDP)/baseline GDP)*100 Annual ASLMs /NBS Crop 6% 1.4 Percentage change of GDP of Crop sub-sector (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Livestock 6% 2.6 Percentage change of GDP of Livestock (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Fisheries 6% 4.2 Percentage change of GDP of Fisheries (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Agricultural Sector Development Programme II (ASDP-II) 167 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 2 Productivity Maize Double (100% increase) the current agricultural yields levels, by the year 2025 from the year 2016. 1.72 Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Paddy 100% increase in MT/ha 3.06 Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Sunflower 100% increase in MT/ha Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Milk 50% increase lt/cow/day 2.25 Production per animal per day (indigenous cattle) lt/cow/day Annually ARDS/AASS Beef 100% increase in Kg/animal 145 Production of carcass per animal Kg/animal Annually ARDS/AASS Goat 100% increase in Kg/animal 37 Production of carcass per animal Kg/animal Annually ARDS/AASS Mutton 100% increase in Kg/animal 40 Production of carcass per animal Kg/animal Annually ARDS/AASS Chicken 100% increase in Kg/bird 1.5 Production of carcass per bird Kg/bird Annually ARDS/AASS Marine fish Increase catch to 1,000,000 MT by 2025 362,000 Volume in MT of catch per year Catch per year Annually ASLMs- fisheries Agricultural Sector Development Programme II (ASDP-II) 168 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 3 Total annual production Maize Double (100% increase) maize production (MT) 6,100,000 Total production in MT Summation of production in the area Annually ARDS/AASS Paddy Double (100% increase) paddy production (MT) 3,400,000 Total production in MT Summation of production in the area Annually ARDS/AASS Milk (28% increase) milk production (litre) 2,087,000 Total production in litres per year (indigenous cattle) Summation of all litres of milk produced Annually ARDS/AASS Beef Double (100% increase) beef production (MT) 319,112 Total beef production in MT Summation of all beef produced in MT Annually ARDS/AASS Goat/sheep (50% increase) goat/sheep meat production (MT) 124,74 Total goat/sheep meat production in MT Summation of goat/sheep produced in MT Annually ARDS/AASS Chicken (50% increase) chicken meat production (MT) 104,292 Total chicken meat production in MT Summation of chicken produced in MT Annually ARDS/AASS 4 Percentage growth of agricultural exports (Value in USD) Maize Export the surplus to 100% by 2025 1,056,559 Harvest minus requirement (mainly for cereals) Annually TRA/ASLMs Rice Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Cotton Triple export by 2025 23.4 Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Horticulture (Round potato) Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Beef Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Marine fish Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Agricultural Sector Development Programme II (ASDP-II) 169 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 5 Volume of imported Rice Gradual decline of rice imports to 50% by 2025 1,277,296 Amount of rice imported in tons Current import minus baseline import Annually TRA Maize Gradual decline of maize imports to 50% by 2025 GAP Amount of maize imported in tons Current import minus baseline import Annually TRA 6 Reduction rate of the gap between the wholesale price and farm-gate price Maize Contribute to poverty reduction by reducing the gap between the wholesale price and farm-gate price, by 50% by the year 2025, from the year 2016. GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Rice Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Milk Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Beef Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI 7 Percent of rural population below the poverty line National poverty line Reduce poverty level by at least 50%, at national poverty line, from the year 2016 to the year 2025. 28.2 Rate of rural population below national poverty line, (Poverty headcount ratio at national 2016-poverty headcount ratio at national 2025)/ poverty headcount ratio at national 2016 * 100 Bi-annual HBS-NBS Agricultural Sector Development Programme II (ASDP-II) 170 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 8 National food self sufficiency Cereal and cereal equivalent Maintain Self Sufficient Ratio (SSR) in the range between 100% to 120% or above 124 The ratio of gross domestic food production is compared with the domestic food requirement. Total food production minus total food requirement over total food requirement Annually ASLMs(food security) 9 Proportion of household with low dietary diversity Household Dietary Diversity Score (HDDS) Reduce by half the communities that doesn’t have access to a diverse range of nutritious food annually from 2016 to 2025 Rural: (21.4%) Urban: (8.6%) Households that doesn’t have access to a diverse range of nutrition food Households that doesn’t have access to nutritious food divide by the total number of households Annually MoH (TFNC)/ MoA 10 Malnutrition incidences (chronic and transitory) in Tanzania Stunting Bring down child stunting to 10%, by the year 2025. 34 Prevalence of stunting (% of children under 5 years old) Annually MOH(TFNC)/ ASLMs Underweight Bring down underweight to 5% or less, by the year 2025. 14 Prevalence of underweight (% of children under 5 years old) Annually MOH(TFNC)/ ASLMs Wasting Bring down wasting to 5% or less, by the year 2025. 5 Prevalence of wasting (% of children under 5 old) Annually MOH(TFNC)/ ASLMs 11 Proportion of the population that is undernourished Bring down undernourishment to 5% or less, by the year 2025. 5.5 Proportion of the population that is undernourished (% of the country’s population) Annually MOH(TFNC)/ ASLMs Agricultural Sector Development Programme II (ASDP-II) 171 COMPONENT ONE Sustainable Water and Land Use Management Component Objective: Improved and Sustained Integrated Management of Land and Water Resources Use (for example, for Irrigation, Water for Livestock, Cropped Land, Pastures, Ponds/Cages and Soil Fertility). Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Land use planning and watershed management 1 Proportion of villages surveyed. Ensure that 100% of villages land is surveyed by 2025. GAP Percentage of villages that have been made with Land use plan in place marking area for agriculture, livestock fisheries, settlement and reserved land e.g. watersheds Total number of village with land use plan/total number of villages registered Annually National Land Use Planning Commission -Ministry of Land 2 Proportion of farm households (by gender) with ownership or secure land rights, Customary Certificates of Rights of Occupancy (CCROs) Ensure that 100% of farmers and agribusiness interested in agriculture have rights to access the required land by 2025. GAP Number of CCROs issued to farmers who own land Total number of CCROs issued to farm households over total number of farm households Annually National Land Use Planning Commision -Ministry of Land Title deed Ensure that 100% of farmers and agribusiness interested in agriculture have rights to access the required land by 2025. GAP Number of title deed issued to farmers who own land Total number of title deed issued to farm households over total number of farm households Annually National Land Use Planning Commission -Ministry of Land Agricultural Sector Development Programme II (ASDP-II) 172 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Water use for Crops, Livestock and Fishery 4 Number of schemes practicing irrigation Rice 549 irrigation schemes (276 for rehabilitation and 273 new ) operated sustainably by 2025 GAP Total number of scheme practicing irrigation sustainably (registered irrigators organization collecting annual fee from members, has bank account & maintenance plan) Summation of all developed schemes Annually AASS/ARDS/MOWI/NIC 5 Number of irrigation infrastructure developed fully 549 irrigation infrastructure fully developed by year 2025 GAP Total number of irrigation infrastructure developed fully Summation of all irrigation infrastructures developed Quarterly/ Annually ARDS/MOWI/NIC 6 Area under irrigation In Ha Expand area under irrigation to 1,000,000Ha by 2025 468,338 Developed area in Ha under irrigation Summation of area under irrigation Annually ARDS/AASS/ASLMs/ MOWI/NIC 7 Functional Irrigators’ organizations (IO) management committees Number of functional committee 549 functional irrigators organization management committees by 2025 GAP Total number of irrigators management committees Summation of the irrigators committees Annually AASS/WPWI/NIC 8 Number of access water points for livestock Charco dam and borehole 100% increase of water points within 3km by 2025 1443 total number of charco dams and bore-holes for livestock Summation of charco dams and bore-holes for livestock Annually ARDS/AASS 9 Land area under fish farming in square meter Tilapia and catfish Double area under fish farming by 2025 4,540,400 Area under fish farming Summation of area under fish farming in square meter Annually ARDS/ASLMs Mainstreaming resilience for Climate Variability/Change and Natural Disasters 10 Percentage of farm, pastoral, and fisher households that are resilient to climate and weather related shocks crops, livestock Ensure that at least 30% of HH are resilient to climate and weather risks, by the year 2025. GAP Number of farmers, pastoralist and fishers applying irrigation or water harvest, early maturity seeds or zero grazing Summation of all farmers who are resilient to climate change Annually ASLMs-Environment / AASS/MOWI Agricultural Sector Development Programme II (ASDP-II) 173 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 11 Share of agriculture land under Sustainable Land Management (SLM) practices Crops Ensure that at least 30% of agricultural land is placed under SLM practice. 5.40% SLM is land area under agricultural cultivation Calculated as: Agriculture area under SLM divide by total agriculture area Annually ARDS//ASLM 12 Proportion of LGAs with mainstreamed CSA in their DADPs Agricultural sector CSA mainstreamed in all LGA’s DADPs by 2025. GAP DADPs have budget for investment or promoting use of water harvesting technology, drip irrigation, and use of early manure seeds Summation of all LGAs that have mainstreamed CSA in their DADPs Annually ASLM/ ASLMs-DPP (DADPs assessment) 13 Existence of government budget- lines to respond to spending needs on resilience building initiatives. Create permanent investment budget-lines to respond to spending needs on resilience building initiatives, especially for disaster preparedness plans, functioning early warning and response systems, social safety nets, and weather-based index insurance, from 2015 to 2025. GAP Existence of budget-lines on disaster preparedness policy and strategy, EIRB1; Existence of government budget-lines on Early warning and response systems and social safety nets, EIRB2; budget for research and irrigation, EIRB3; Existence of government budget-lines to respond to spending needs on resilience building initiatives (in %), EIRB = average (EIRBi)i=1 to 3 Annually ASLM Agricultural Sector Development Programme II (ASDP-II) 174 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 14 Number of crop farmers, Livestock households (HH) and fish farmers Crop farmers Maintain preferable level relative to environmental degradation. GAP Number of livestock/ fish farmers Annually AASS/ARDS Livestock HH Maintain livestock farmers according to the land carrying capacity GAP Number of livestock/ fish farmers Annually AASS/ARDS Fish farmers Maintain preferable level relative to environmental degradation. 25,259 Fresh water (tilapia and catfish) and marine (seaweed, prawns and milk fish) Annually AASS/ARDS Agricultural Sector Development Programme II (ASDP-II) 175 COMPONENT TWO Component Title: Enhanced Agricultural Productivity and Profitability Component Objective: To increase agricultural productivity and profitability through commercial and market-oriented agriculture Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Production and Productivity 1 Growth rate of the yield of the priority commodity Maize, Paddy, sun-flower, milk, beef,goat/mutton and marine fish (refer PDO 2) Cassava 100% increase in MT/ha 5.95 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Pulses (common beans) 100% increase in MT/ha 1.11 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Sorghum/millet 100% increase in MT/ha 1 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Horticulture (Round potato) 100% increase in MT/ha 13 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Cotton 100% increase in MT/ha 1 Production per unit area Total production in tons per area in Ha Annually ARDS/Cotton Board Coffee 100% increase in MT/ha 25 Production per unit area Total production in tons per area in Ha Annually ARDS/Coffee Board Sugarcane 100% increase in MT/ha 40 Production per unit area Total production in tons per area in Ha Annually ARDS/Sugar Board Tea 100% increase in MT/ha 9 Production per unit area Total production in tons per area in Ha Annually ARDS/Tea Board Cashew 100% increase in MT/ha 3 Production per unit area Total production in tons per area in Ha Annually ARDS/Cashew Board Tilapia/catfish 100% increase (in kg/ m2) 1.11 Production per unit area Total production in Kg per square meter Annually ARDS/AASS Seaweed Double production GAP Production per unit area Total production in Kg per square meter Annually MLF-fisheries Agricultural Sector Development Programme II (ASDP-II) 176 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 2 Total annual production Maize, Paddy, sun-flower, milk, beef, goat/mutton and marine fish (refer PDO 3) Cassava Double cassava production (in MT) 6614.4 Total production in MT Summation of production in the area Annually ARDS/AASS Pulses-common beans Double beans production (in MT) 1306.5 Total production in MT Summation of production in the area Annually ARDS/AASS Sorghum/millet Double sorghum/ millet production (in MT) 729.5 Total production in MT Summation of production in the area Annually ARDS/AASS Horticulture (Round potato) Double potato production (in MT) 1342.2 Total production in MT Summation of production in the area Annually ARDS/AASS Cotton Double cotton production (in MT) 149.5 Total production in MT Summation of production in the area Annually ARDS/Cotton Board Coffee Double coffee production (in MT) 60.9 Total production in MT Summation of production in the area Annually ARDS/Coffee Board Sugarcane Double sugar production (in MT) 2839.2 Total production in MT Summation of production in the area Annually ARDS/Sugar Board Tea Double tea production (in MT) 32.6 Total production in MT Summation of production in the area Annually ARDS/Tea Board Cashew Double cashew production (in MT) 155.4 Total production in MT Summation of production in the area Annually ARDS/Cashew Board Tilapia/catfish 100% increase tilapia/catfish production in Kg GAP Total production in Kg Summation of production in the area Annually ARDS/AASS Agricultural Sector Development Programme II (ASDP-II) 177 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 3 Agricultural labor and land productivity Labor productivity Double (100% increase) the current agricultural labor productivity levels by 2025 GAP Total agricultural labor involved in agriculture Agriculture GDP divide by Agricultural worker Annually AASS/ ASLM/ MOW Land productivity Double (increase by 100%) the current agricultural land productivity levels, by 2025 GAP Total agricultural land under agriculture Agriculture GDP divide by Agricultural arable land (in Ha) Annually AASS/ASLM/ MOW Agricultural Extension services Agricultural Sector Development Programme II (ASDP-II) 178 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 4 Agricultural technologies adoption Chemical Fertilizer At least half of the farmers are using chemical fertilizer (N+P+K) GAP Rate at which farmers adopt fertilizer application technology Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Improved seeds At least half of the farmers use using improved seeds GAP Rate at which farmers use improved seeds Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Agro-chemicals (all crops) At least half of the farmers are apply agro-chemicals GAP Rate at which farmers apply agro-chemicals Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Farm machinery At least half of the farmers are using farm machinery GAP Rate at which farmers use agro-machine Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Integrated Pest Management (IPM) Double farmers who are practicing IPM technology GAP Rate at which farmers using IPM technology Farmers using fertilizer divide by total number of farmers Annually AASS System of Rice Intensification (SRI) Double smallholder farmers who are practicing SRI technology GAP Rate at which farmers are using SRI Farmers using fertilizer divide by total number of farmers Annually AASS/ ASLM Water harvesting At least half of the smallholder farmers are using improved seeds GAP Rate at which farmers are using water harvesting technology Farmers using fertilizer divide by total number of farmers Annually AASS Drip irrigation or sprinkler At least half of the smallholder farmers are using improved seeds GAP Rate at which farmers are using drip irrigation/ sprinkler technology Farmers using fertilizer divide by total number of farmers Annually AASS Solar drying (fish) Double (100% increase) 3600 Rate at which farmers are using solar drying Farmers using fertilizer divide by total number of farmers Annually AASS Agricultural Sector Development Programme II (ASDP-II) 179 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 5 Number of extension staff Crops Double public extension staff 11,000 All crops extension staff Summation of crops extension staff Annually ARDS/AASS Livestock Double public extension staff 8,725 All livestock extension staff Summation of livestock extension staff Annually ARDS/AASS Fisheries Double public extension staff 750 All fisheries extension staff Summation of fisheries extension staff Annually ARDS/AASS Private Existing are engaged in agriculture through PPP GAP All private extension staff Summation of private extension staff Annually ARDS/AASS/TPSF 6 Ward Resource Centers (WARC) Number of WARC At least one WARC in each ward by 2025, (total number of wards is estimated at 3927) 319 Number of existing WARC Summation of WARC Annually ARDS/AASS Operational WARC 3927 WARC are operational by 2025 208 (gap) WARC developed and operational Summation of operational WARC Annually ASLM 7 Number of farmers and extension staff trained Farmers All farmers trained by 2025 0 All farmers trained through FFS and others e.g. seminars, workshop, study tour, residential training etc. Summation of all farmers trained Annually ARDS/AASS Trained extension staff 50% of extension staff trained in tailor made courses by 2025 GAP Extension staff attended training both short and long courses Summation of trained extension staff Annually ARDS/AASS Access to Agricultural Inputs and health services Agricultural Sector Development Programme II (ASDP-II) 180 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 8 Farmers access to inputs Fertilizer consumption (kilogram of nutrients per hectare of arable land) At least 50 kilograms per hectare by 2025. 19 Total inorganic fertilizers consumption per unit cultivated area (N+P, N+P+K) Fertilizer applied divided by cultivated land (kilogram of nutrients per hectare of land) Annually ARDS/AASS Improved seeds (in tons) collectively for cereals, legume, and others except seedlings and cuttings (annual requirements is 120,000 tons) Double the current levels of improved seeds by 2025 28,000 Total amount of improved seeds (in tons) applied in the cultivated land Summation of improved seeds applied in the cultivated land (in Tons) Annually ARDS/AASS Agro-chemicals (in tons) Increase usage of agro-chemicals to 100% by 2025 GAP Total amount of agro- chemical applied Summation of agrochemical applied in crops and livestock Annually ARDS/AASS Fingerlings Double fingerlings GAP Total amount of fingerlings produced and raised Summation of fingerlings produced and raised Livestock Breed (AI)-(annual demand is 1,000,000) Increased AI to 100% by 2025 100,000 Artificial Insemination for livestock Breed Annually ARDS/AASS Agricultural Research and Development 9 Technologies disseminated At least 70% of agricultural technologies developed are disseminated by 2025 GAP Number of technologies disseminated Summation of all technologies disseminated Annually Research/DRD/ AASS Agricultural Sector Development Programme II (ASDP-II) 181 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 10 Total Agricultural Research Spending as a share of Agriculture GDP Research spending for crops/livestock and fisheries Increase the level of Investments in Agricultural Research and Development to at least 1% of the Agricultural GDP by 2025. 0.28 Percent of agricultural research spending from total Agricultural GDP Total Agricultural Research Spending divide by total Agriculture GDP times 100 Annually MoA/MLF/ASLM Access to Mechanization Services 11 Proportion of machines in agricultural production Farm machinery About 50% of agricultural land are cultivated using tractor/power tiller or animal drought by 2025 14: (tractor/ power tiller) 24: Animal draught: All land cultivated by using animal draught or tractor/power tiller Land cultivated using animal draught or tractor/ power tiller divide by total land cultivated times 100 Annually ARDS/AASS 12 Number of farm machinery (tractors, etc.) hiring centers providing services Farm machinery hiring centers At least two mechanization (tractor, power-tiller and animal traction) hiring centers established at each LGA by 2025 5: (1 Rukwa, 1 masasi, 1 Songea, 1 Arusha and 1 Singida) All farm machinery hiring centers established Summation of all farm machinery hiring centers Annually ARDS/AASS Food and Nutrition Security 13 National food self sufficiency FSSR refer PDO 10 14 Malnutrition incidences (chronic and transitory) in Tanzania Malnutrition incidences refer PDO 12 15 Proportion of the population that is undernourished Proportion of undernourished refer PDO 13 Agricultural Sector Development Programme II (ASDP-II) 182 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 16 Proportion of household with low dietary diversity Proportion of dietary diversity refer PDO 11 Agricultural Sector Development Programme II (ASDP-II) 183 COMPONENT THREE Commercialization and Value Addition Component Objective: To improve and expand marketing and promote value addition by thriving competitive private sector and effective farmer organizations Key Performance Indicators: Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source Competitive Commodity and Value Addition 1 Volume and monetary value of agricultural exports Maize, Rice, cotton, horticulture, beef, marine fish refer PDO 5 Sunflower Double sunflower export by 2025 GAP Percentage change of sunflower export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Milk Triple milk export by 2025 GAP Percentage change of milk export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Coffee Double coffee export by 2025 GAP Percentage change of coffee export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Sugarcane Triple sugarcane export by 2025 GAP Percentage change of rice export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Tea Double tea export by 2025 GAP Percentage change of tea export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Cashew Double cashew export by 2025 GAP Percentage change of cashew export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Goat Double goat export by 2025 GAP Percentage change of goat export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Mutton Double mutton export by 2025 GAP Percentage change of mutton export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Agricultural Sector Development Programme II (ASDP-II) 184 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 2 Volume and monetary value of agricultural imports Maize, rice refer PDO 6 Marine fish Double (100% increase) marine fish production (Kg) GAP Total production in Kg Summation of production in the area Annually TRA/ ASLM Edible Oil Double (100% increase) edible oil production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Milk Double (100% increase) milk production (Litres) GAP Total production in Litres Summation of production in the area Annually TRA/ ASLM Coffee Double (100% increase) coffee production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Sugarcane Double (100% increase) sugar production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Beef Double (100% increase) beef production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Agricultural Sector Development Programme II (ASDP-II) 185 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 3 Reduction rate of the gap between the wholesale price and farm- gate price for all priority commodity Maize, Paddy, milk refer PDO 7 Cassava Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Common beans Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Sorghum/ millet Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS HT (potato) Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual Sunflower Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Cotton Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Coffee Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Sugar cane Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Tea Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Cashew Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Beef Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Goat Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Mutton Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Agricultural Sector Development Programme II (ASDP-II) 186 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 4 Ratio of value of raw agricultural export and processed export Hides/skins At least 100% of hides and skins are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Cashew At least 100% of cashew are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Beef At least 100% of beef are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Access to markets and rural infrastructure 5 Number of operational marketing infrastructure and new investment Market structure 100% of market infrastructures developed are operational by 2025 GAP All agricultural marketing infrastructures Summation of operational marketing infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM Warehouse/ 100% of warehouses developed are operational GAP All agricultural warehouse infrastructures Summation of operational warehouses infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM Godowns 100% of godowns developed are operational GAP All agricultural godowns infrastructures Summation of operational godowns infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM 6 Volume of products marketed through warehouse receipt system (WHRS) Maize, rice, cashew 100% of agricultural produces are marketed through WHRS GAP Amount of maize, rice and cashew marketed through WHRS Summation of all produce marketed through WHRS Bi- annually MoA/ MITI/ ASLM Agricultural Sector Development Programme II (ASDP-II) 187 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 7 Reduction rate on Post- Harvest Losses for (at least) the 11 national priority commodities Cereals Halve (decrease by 50%) the current levels of Post-Harvest Losses (PHL), by the year 2025 from the year 2016. 30-40 Loss in tons Production (tons) of the commodity 1, Pd1; minus (Loss at Harvesting, LH; Loss at Storage, LS; Loss at Transport, LT; Loss at Processing, LP; Loss at Packaging, LPz; & Loss at Sales, LS); Loss=Pd1-(LH-LS-LT-LP- LPz-LS) in Tons Annually AASS/ MoA Root and tubers Decrease by 50% 45 Loss in Tons Annually AASS/ MoA Oil seeds Decrease by 50% 40-50 Loss in Tons Annually AASS/ MoA Horticulture Decrease by 50% Above 50 Loss in Tons Annually AASS/ MoA Fish and fishery product Decrease by 50% 70 Loss in Tons Annually AASS/ MLF Agricultural Sector Development Programme II (ASDP-II) 188 COMPONENT FOUR Sector Enablers, Coordination and M&E Component Objective: Strengthening Sector Enablers, Coordination and M&E Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Business Environment 1 Policy environment and regulation crop, livestock and fisheries Review/update/harmonize/ enforcement of policies, acts, regulations and legislation Crop (2013), Livestock (2006), Fisheries (2015), Marketing (2008) Agricultural policy environment Review, update, and harmonize as required Annually ASLMs/MOF 2 Institutional framework Agricultural stakeholders Review, update, harmonize of the institutional framework ASDP-I Institutional framework ASDP-II operational structure Review, update, and harmonize the existing framework Annually ASLMs/MOF Sector coordination (Vertical and Horizontal) 3 Timely submission of agricultural reports at all levels Crops, livestock and fisheries 100% submission rate by all LGA 90 Agricultural reports including quarterly, annually and ad- hoc Routine and non-routine Quarterly/ Annually/ periodic AASS/ARDS/ ASLMs 4 Agricultural guideline compliance rate Planning and implementation guideline 100% compliance GAP Rate at which the agricultural guidelines are complied by ASDP-II implementers DADPs preparation assessment index score Annually MoA-DADPs assessment 5 Budget allocations and disbursements Agricultural sector Recurrent 100% disbursement of the allocated budget 80.57 (crops), (livestock), (fisheries), (marketing), PO-RALG Budget approved, allocation and disbursement Records agricultural budget disbursement as per allocation Annually MOF/ASLMs Agricultural Sector Development Programme II (ASDP-II) 189 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Development 100% disbursement of the allocated budget 3.91 (crops), (livestock), (fisheries), (marketing), PO-RALG Budget approved, allocation and disbursement Records agricultural budget disbursement as per allocation Annually MOF/ASLMs 6 Public agriculture expenditure as share of total public expenditure Agricultural sector Increase public expenditures on agriculture as part of national expenditures, to at least 10% by 2025 5.30% Agricultural Sector Lead Ministries’ expenditure to the total public expenditure Public Agriculture Expenditure divide by total Public expenditure Annually MOF/ASLMs 7 Public Agriculture Expenditure as % of agriculture GDP Maintain public agriculture expenditure to not less than 19% of agricultural GDP by 2025 5.20% Agricultural Sector Lead Ministries’ expenditure to the agricultural GDP Public Agriculture Expenditure divide by Agriculture GDP Annually MOF/ASLMs 8 Official Development Assistance (ODA) disbursed to agriculture as % of commitments Agricultural sector 100% ODA disbursement annually from 2016 to 2025 Crops, livestock, fisheries, marketing DPs commitments in ASLMs ODA for agricultural sector (public, private, PPP, DPs, multispectral organization, NGOs, civil society, non-state actors, etc.) Annually ASLMs/MOF Agricultural Sector Development Programme II (ASDP-II) 190 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 9 Ratio of private sector investment to government investment in agriculture Ensure that government investment leverage at least 3 times domestic private investment in agriculture sector by 2025. GAP Private sector investment to the public investment in agriculture Private sector investment divide by public investment Annually MOF/ASLMs 10 Ratio of foreign private direct investment (FDI) to government investment in agriculture Ensure that government investment leverage at least 3 times foreign private direct investment in agriculture sector by 2025. GAP Foreign private direct investment to the government investment in agriculture Foreign private direct investment divide by government investment in agriculture ASLM/MOF ASLM/MOF Monitoring & evaluation and Agricultural statistics 11 Annual Agriculture Sample Survey (AASS) implemented Agricultural sector AASS implemented in annual basis and results are out within three months Conducted February 2015 Survey conducted annually Survey Annually AASS/ARDS Stakeholder Empowerment and Organization 12 Empowerment of farmers organizations, women and youth Youth At least 30% of youth are granted title deeds for agricultural land by 2025. GAP Percentage of youth that is engaged in agriculture and have land title deeds Total number of youth engaged in agriculture and have land title deeds Annually TIC/ASLMS/ MoW/ MLHSH Rural women At least 20% of rural women have access to productive assets by 2025. GAP Proportion of rural women that have access to productive assets e.g. land, credit, input (fertilizer and seeds), etc. Total number of women provided with productive assets in agriculture Annually ASLM/BOT 13 Proportion of farmers who are members of farmers’ organization and cooperatives SACCOS by gender Double members of SACCOS by 2025 GAP Proportion of farmers who are members of SACCOS Number of farmers who are members in the SACCOS divide by total number of farmers Annually AASS/ARDS Agricultural Sector Development Programme II (ASDP-II) 191 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Farmers Organization and cooperatives Double members in the cooperative organization by 2025 GAP Proportion of farmers who are members of the cooperative organization Number of farmers who are members in the cooperative organization divide by total number of farmers Annually ASLMs/ Access to Rural Financing 14 Proportion of women and men engaged in agriculture with access to financial services Formal services Double (100% increase) farmers accessing to agricultural loans GAP Total number of farmers that have access to financial services (loans) by gender Number of farmers accessing loans by gender divide by total number of farmers Annually BOT 15 Proportion of branches of formal financial institutions in the rural areas Formal institutions At least more than half of branches has to be instituted in rural area GAP Total number of branches of formal financial institutions in the rural area Bank branches in rural area divide by total number of bank branches in Tanzania Annually BOT 16 Share and value of financial sector lending to agricultural sector by sub-sector At least 50% of the share and value of financial sector lending be allocated to agriculture by 2025 GAP Proportion of loan allocated in the agricultural sector by financial institutions Share and value of lending to the agricultural sector divide by the total amount loaned Annually BOT 17 Loan repayment rates (%) by banks by sub-sector At least loan repayment rates more than 80% by 2025 GAP Proportion of loans paid back to financial institutions Number of loans paid back divide by total number of loans BOT Agricultural Sector Development Programme II (ASDP-II) 192 ANNEX III: Details of Coordination Mechanisms Figure A23: ASDP II Programme Coordination Mechanism 1. Program Coordination, Governance and Project Management a. Implementation Backstopping and Problem Solving b. Project Management: (Procurement, investment mapping, problem solving) 2. Program Planning, Budgeting, Financial Management and Auditing a. Planning and Budgeting: finalize consolidation of program annual work plan and budgets, Coordinate agriculture sector projects) b. Financial Management: (Maintenance of ASDP II financials, following up with Treasury to disburse funding, support ASC with financial progress and audit results of project implementation) c. Auditing: Facilitate and Coordinate ASDP II financial audit and follow-up on implementation of audit findings 3. Monitoring and Evaluation 4. Stakeholder Engagement, partnerships, dialogue and capacity building a. Capacity Building and Accountability b. Comunication and knowledge Management c. Marketing the Program and Projects: 5. Analytical support on agricultural policies and availability of markets • Chaired by PM; Secretariat - PS - MoA • Review implementation progress • Advisory to stakeholders • Corrective action guidance Pesident’s Office for Regional and Local Government (PORALG) Ministry of Agriculture (MoA) Regional secretariat District Council Management Team Ward Development Committee Village Planning Committees National Agricultural Sector Coordination Unit (NCU) National Agricultural sector Stakeholders Meeting (NASSM) Agricultural Sector Consultative Group (ASCG) Technical Working Groups (TWG) Lead Component Working Groups Technical Committee of Directors (TCD) Agricultural Steering Committee (ASC) • Assistant Administrative Secretary for Economics and Production, with support from regional ASDP Coordination support planning and provide technical advice • Implementation arm of the gov’t at LGA • Reviews and budgets District Agriculture Development Plans (DADPs) • DADPs are formulated based on VADPs by District Irrigation and Cooperative Officers and/or District Livestock and Fisheries Officers • Village Agriculture Development (VADP) are developed by Village Agricultural Extension Officers & Village Executive Officer • Chaired by Minister - MoA; Secretariat - NCU • Reviews & Approves annual workplans, budgets and M & E reports • Tack financial progress and audit results • Discuss key agricultural issues Chaired by PS - MoA/ASLMs • Chaired by Ps - MoA; Secretariat - NCU • Government only participation • Advices on technical issues • Develop and implement policy • Prepares workplans and budgets • TWGs include Monitoring and Evaluation TWG and Planning and Budgeting TWG • Each Lead Component will have a TWG, Leader of TWG will serve as secretariat • Flexible membership, size and purpose (meets monthly) • Provide technical and managerrial advice to TCD and LGAs • Members of DP-AWG and PSD are represented in the TWG • Dispatch national facilitation teams for project problem solving • Provide technical and managerial support to LGAs via District Value Chain Components (DVC), • Led by Ward Councilor • VADPs (~3-6) collected by Ward Agricultural Extension Officer • VADPs submitted to DED 193 Agricultural Sector for Industrial Development Coordination at central, national level 418. The hierarchy of coordination organs and functions under ASDP II at central level is as follows: (i) National Agricultural Sector Stakeholders Meeting (NASSM) (ii) Agricultural Steering Committee (ASC) (iii) Agricultural Sector Consultative Group (ASCG) (iv) Technical Committee of Directors (TCD) (v) Thematic Working Groups (TWGs) (vi) ASDP II National Coordination Unit (NCU) 419. The National Agricultural Sector Stakeholders Meeting (NASSM) is the highest coordination event in the programme hierarchy and will be instrumental in coordinating and guiding the whole sector. It will be held once a year over one or two days as the culmination of the JSR/PER, which will inform NASSM. The meeting will be held under the chairmanship of the Prime Minister to review the ASDP II sectorial achievement and its contribution to national development and poverty reduction. The purpose of the NASSM will be to: • Provide an open opportunity for all the stakeholder representatives to exchange their views and gain insights into the successes of the programme from the perspective of others • Review conclusions drawn by the JSR/PER on progress in implementation of the various agriculture projects within the programme towards achieving planned targets, outcomes and impact • Advise the various government organizations, development partners, non-state actors, and private sector stakeholders on opportunities to foster greater agricultural transformation and accelerate achievement of ASDP II objectives and desired impact • Review and discuss agricultural transformation issues and impact of the program to the sector. 420. The NASSM will be attended by: • Central government—Ministers, Permanent Secretaries and Directors of Policy and Planning from all ASLMs, Component Leaders; and other related high officials of the government • Development partners (DPs)—members of the Agriculture Working Group, Private Sector Development partners (PSD) working group and other DPs suppoting or have an interest in agriculture. • RS—selected regional officials • LGAs—DEDs, DAICOs, DLFOs, DLOs, DCOs,from selected LGAs • Research—selected officials from agricultural, livestock and fishery research institutions (ASLMs) • Training—selected officials from agricultural, livestock and fishery training institutions (ASLMs) • Academia—relevant heads of departments from Sokoine University and other academic institutes/ training institutions involved in research and training of agriculture • Commodity boards • Private sector representatives • Non-state actor/NGOs/CBOs representatives • Financial institutions concerned with agricultural activities and investments • Associations and cooperatives—representatives of cooperative unions, commodity-wise associations, and successive agriculture associations and SACCOS • Representatives of other related stakeholder organizations 421. Before any NASSM is held there will be a JSR/PER that will lead to an intensive working process performed by both government, development partners, non-state actors, and private sector annually to monitor the sector progress. It will be conducted by the government, development partners and hired consultants to rigorously review the programme over several weeks on the basis of analysed national statistics as a professional annual evaluation exercise. It may include field visits in selected 194 Agricultural Sector Development Programme II (ASDP-II) regions where the ASDP II is being implemented by way of sampling, similar to Joint Implementation Review under ASDP-1. The JSR/PER will be an activity to facilitate coordination and dialogue and enable shared vision and opportunity to initiate corrective action in the management of projects. The report from JSR/PER will be first submitted to ASCG meeting, and later to the Agricultural Steering Committee before it is submitted to NASSM. The conclusions of the JSR/PER will be presented to the NASSM for discussion and corrective actions. The timing of implementing JSR/PER needs to be carefully decided in consideration of ASCG, ASC, NASSM, government budget formulation cycle and other related events. 422. The Agricultural Steering Committee (ASC) will be the key oversight and decision-making organ of ASDP II implementation and coordination. The core functions will be to approve the annual work plan and budget, oversee the physical and financial progress, follow-up the audit results and discuss on key issues in regard to sector performance and coordination. The conclusion will guide the TDC and TWG on the subsequent actions. It will be held quarterly and chaired by the Minister Ministry of Agriculture. The members are the Permanent Secretaries (PSs) of ASLMs, collaborating ministries, and institutions, TDC members, representatives of development partners’ (chair and co-chairs of the Agriculture Working Group (AWG) members and Private Sector Development Partners (chair and co-chairs of the PSD), representatives of non-state actors, and representatives of private sectors. It will be facilitated by Director of Policy and Planning (DPP) MoA and NCU. 423. The ASC is an overall oversight body for the ASDP II. Main objectives are to: (i) Achieve sector objectives and results through dialogue and consultations to establish coherent agriculture sector policies, strategies and programmes in line with Long Term Development Plan, Five Year Development Plan and other national development frameworks (ii) Ensure that planning, budgeting and budget allocation, execution and expenditure are in line with the agriculture sector policies, priorities, strategies and programmes (iii) Improve public financial management and accountability in ASLMs (iv) Implement agriculture sector specific JAST commitments (v) Implement agriculture sector GBS commitments as outlined in the PAF matrix and GBS Partnership Framework Memorandum (vi) Enhance domestic and mutual accountability 424. Agricultural Sector Consultative Group (ASCG). ASCG will be a sector consultative meeting where by all stakeholders in the sector will be albe to meet on quarterly basis to discuss issues and implementation of ASDP II. This meeting is very important because the ASC will function as a board and only representatives will be sitting in the ASC. ASCG is open to all stakeholders. The sector Permanent Secretary, Ministry of Agriculture, (MoA) will have an opportunity to meet and discuss with key stakeholders in the sector. These include ASLMs, Development Partners, Private sector, NGOs/CBOs, Farmer Based Organizations/Cooperatives, research and training institutions, implementers and partners of ASDP II. 425. Technical Committee of Directors (TCD). The TCD will be maintained and will absorb some of the functions of the Inter-Ministerial Coordinating Committee (ICC)143, which it will replace. It will advise the Agricultural Steering Committee on technical issues in connection with development of component, sub-component, investment area and projects and will be chaired by the Permanent Secretary, Ministry of Agriculture supported by the National Coordination and Management Team (NCU). The TCD is a solely government committee and will comprise all Director of Policy and Planning (DPPs)/Directors of ASLMs and Lead Component Leaders and chairs of the Components, and other selected key officials/experts of related government organizations (e.g., NIRC, NBS, TCDC, Land Commission). The committee will be supported by NCU. 426. The TCD will meet quarterly and may be called for ad hoc meetings if need arises. The TCD will review quarterly reports and contribute to annual reports. They will provide oversight of implementation and 143 The Inter-Ministerial Coordinating Committee (ICC) that existed under ASDP-1 will not be retained. Its functions will be taken over by the TCD. 195 Agricultural Sector for Industrial Development monitoring of the performance of ASDP II to ensure achievement of the goals. The TCD will report and advise respective Permanent Secretaries of the ASLMs. The wider functions of the TCD will include: • Reviewing the progress of all ASDP II interventions to ensure compliance with policies, macro and sector strategies and adherence to schedules through summarized physical and financial progress reports and take necessary corrective action • Advising the Agricultural Steering Committee (ASC) on a regular basis on the progress of and requirements for implementation of the ASDP II • Overseeing the development and implementation of policy decisions underlying the ASDS-2 and ASDP II • Overseeing the preparation of the ASDP II Integrated Annual Work Plan and Budget • Reviewing and recommending the budgetary proposals to the Steering Committee for endorsement and subsequent onward submission to Treasury • Recommending to the Steering Committee the transfer of funds from the Exchequer Account to the implementing agencies • Defining eligibility criteria for support of new programmes and projects under ASDP II • Review reports from Direct Project Financing 427. Thematic Working Groups (TWGs) will be organized working groups based on the experience from ASDP-1. For ASDP II the thematic working groups will be based on the ASDP II components, sub-components and investment areas. The members of the group will be drawn from experts within the relevant fields (i.e., departments/institutions) in each ASLM or relevant institutions, private sector, development partners and non-state actors/NGOs. Although the groups may coalesce or be redistributed or expand and contract to meet the needs of the issues at hand, core membership will remain intact. To enhance the better coordination among the wider stakeholders under ASDP II, especially the private sector, TWGs should be expanded and invite participation of development partners experts who also support the thematic area, in addition to non-state and private sector actors involved in the thematic area. The TWGs will provide guidance to the programme on technical and/or managerial matters and advise the TCD. They will be called upon for periodic and ad hoc deliberation to manage overall activities under the TWG and resolve technical issues. They will meet at least monthly and the expanded meeting including development partners and the private sector could be held quarterly. They will refer to quarterly reports from the local level and other sources (including off- budget projects), and inform quarterly meetings of the TCD and Steering Committee of the progress of various interventions at a technical level. Another important function of TWGs will be to follow the progress of recommended actions agreed by the preceding JSR that should be indicated in their annual work plans. They will be required to ascertain whether actions directed by the TCD have been correctly and completely performed. 428. The range of TWGs will be at thre levels: Component Thematic Working Group: This is a group working on component level issues. These will be four. Members of the component TWG are chairs of the sub-component leaders, and NCU staff responsible for coordinating the component. Chair/Representative from the Monitoring and Evaluation (M&E) & TWG; Chair/Representative from the Planning and Budgeting (PB) TWG. The NCU staff will be the secretariat to the TWG. Depending situation and demand, components could be sub-divided or create lower level thematic working groups based on the sub-components and/or investment areas. TDC will approve formation of TWGs. All TWG will be coordinated through NCU. 429. Members of the TWG will act as facilitators of the actions and will be called upon to extend their technical and/or managerial support to activities upon request from LGAs. Each TWG will contribute technical expertise and advice according to the designation of the group and in response to demand. The core activities and duties of TWGs will include: • Provision of programme progress implementation reports to the TCD 196 Agricultural Sector Development Programme II (ASDP-II) • Provision of technical expertise to ASDP II planning and implementation processes • Providing solutions to implementation bottlenecks • Analysis on technical grounds of the outcome • Provide problem solving solutions to issues presented. 430. TWGs will also provide national facilitation teams (of one or more member) that will comprise members of the TWGs who will be dispatched on an ad hoc basis to assist in implementation or problem-solving missions at project level. 431. The ASDP II National Coordination Unit (NCU) will be directed by the National Programme Coordinator who will be directly answerable to the Permanent Secretary of the Ministry of Agriculture. It will constitute a professional management team with recruited officials from the labour market and ASLMs/government instituions and will have executive and semi autonomous powers to manage, monitor and call for meetings of other organs of the ASDP II structures and to direct implementation functions. The team will be a fulltime job, reporting to PS MoA for management and administrative issues and to TDC for program implementation. It will be exclusively engaged in the ASDP II processes for the duration of the programme. • The members will comprise Senior Coordinator with a high calibre of managerial and program management skills who will be the National Programme Coordinator, preferable with good agricultural background • Experts in: Productivity and Commercialization; Markets and Valuae chain; (for crops, livestock, and fisheries); • Policy Analyst with Agricultural/Economics background and wide experience of agribusiness • Monitoring and Evaluation specialist • Communications and knowledge management specialist • Financial Planning and budgeting specialist • Accounting and procurement specialist • Office Management staff with secretarial and personal assistant capabilities The detailed structure of NCU will be prepared separately to accommodate some of the restructuring in the ASLMs and government. 432. They will also be given access to advisers on a consultancy basis as the need arises. Such advisers may be on short-term contract and may include international consultants. 433. The To ensure accountability, NCU will be served with specific Terms of Reference and performance contracts that will focus on sector coordination and management of the program with a link to the delivery of ASDP II indicators ideally, the team will be exclusively engaged in the ASDP II processes for the duration of the programme. Team members will be provided with transport facilities and necessary office and communications equipment to enable them to perform their role effectively. It will be responsible for: • Provide catalytic and supportive role to the agricultural transformation agenda • Facilitate and serve as the secretariat to TCD, ASC, ASCG, and NASSM and attending all the meetings • Close communications and interactions with the TWGs on their key activities • Networking and information sharing among all the stakeholders on their interventions (including on- and off-budget activities); stakeholder mapping will be necessary • Coordinate the preparation of the ASDP II Integrated Annual Work Plan and Budget in close cooperation with the TWGs, development partners supporting on- and off-budget activities, and other stakeholders • Coordinate alignment, harmonization and implementation of agriculture sector projects and interventions within the framework of ASDP II • Manage, monitor, evaluate, harmonize and coordinate implementation of ASDP II activities. • Compile, analyse, coordinate, provide program logistical support; • Prepare and consolidated quarterly, semi-annual and annual ASDP II progress implementation 197 Agricultural Sector for Industrial Development reports for onward submission to TDC, ASC and other national forums. • Provide technical support on joint monitor and evaluate of the program • Provide analytical and problem-solving support to the components • Production of manuals, guidelines and publicity and communication materials for ASDP II; • Establish and share best practices & lessons learnt under Agricultural SWAp • Facilitate and coordinate ASDP II financial audit and submit the same to TDC and ASC • Maintenance of ASDP II financial and other implementation records and reports • Absorption and coordination of all stakeholders into programme activities • Developing mechanisms for collaboration and coordination across all stakeholders in ASDP II • Remaining fully informed of the progress of all ASDP II functions and proceedings • Identifying appropriate interventions in pursuit of the objectives of ASDP IIand government policies • Provide secretariat to ASDP II 434. Agricultural Sector Consultative Group Meeting (ASCG meeting). The ASCG will provide a consultative and advisory forum for dialogue between the government (ASLMs), all interested development partners (as defined in the JAST), private sector and non-state actors (CSO and PSO) in the agriculture sector. The ASCG will coordinate dialogue at two levels: regular dialogue on sector policies and regulations; annual plans, budgets, and the annual agriculture sector/public expenditure review (ASR/PER) reports. 435. Functions of the ASCG are more of advisory to the sector and need to be informed on: (1) policy (Long Term Development Plan (LTDP), Five Year Development Plan (5YDP), agriculture sector policies, GBS, JAST); and (2) budgetary (public expenditure) issues. ASCG meetings will remain one of the underlying structures for the two main national processes and provide advice to ASC on the: (i) The LTDP and 5YDP process (ii) The national budget/PER process 436. The group will facilitate sector dialogue on JAST and GBS issues, which are to be integrated as much as possible within the LTDP and 5YDP and national budget/PER processes. It will serve as a forum for: (i) policy dialogue (ii) information sharing (iii) advice on the budget discussions and prioritization (iv) consultations on sector priorities, strategies and programme implementation, including linkages with other sectors such as natural resources (v) joint analysis and assessment of the agriculture sector issues/performance and launching baseline and follow up studies (vi) provision of advice on strategic, budgetary and other issues 437. Table A1 provides a summary of ASDP II sector coordination components. Agricultural Sector Development Programme II (ASDP-II) 198 Table A1: Summary of ASDP II coordination organs, mechanisms, membership and functions Organ/mechanism Membership/participants Functions and purpose i) National Agricultural Sector Stakeholders Meeting (NASSM). Chaired by Prime Minister Ministers of ASLMS, Other Central Government Ministers Permanent Secretaries, DPPs from all ASLMs, and senior government officials; Component Leaders; RSs; DEDs; DAICOs, DLFOs; research officials; training officials; academia representatives; commodity boards; All Development Partners supporting and involved in Agriculture, Private sector representatives; non-state actors/NGOs, financial institutions; associations and cooperatives, commodity associations, and successive agriculture associations and SACCOS; representatives of other related stakeholder organizations DPP MoA-Secretariat NCU: Recorders The agenda will be determined by stakeholders: Issues to be discussed include: provide advice and policy guidelines to the agricultural transformation agenda; provide advice and guideline to the implementation of ASDP II; facilitate and provide support where needed, invite other important partners to the sector. Agricultural Steering Committee(ASC) Chair: Minister, Ministry of Agriculture Permanent Secretaries of Lead Components and related ASLMS; Representatives of Development Partners (AWG- Chairs) (2 members, PSD-chairs (2 members); Representatives of Private Sector (3 members); Representatives of NGOs,.NSAs (3 members); DPPs of Lead Components; DPPs-ASLMs (Crops, Livestock & Fisheries) NCU – Secretariat Review and approve ASDP II plans, budgets, monitoring and evaluation reports; Approve ToR for Joint Annual Reviews/Sector reviews/Public Expenditure reviews(JSR/ASR/PER) and Monitoring and Evaluation Facilitate and approve establishment of ASDP II funding mechanisms; Discuss issues of mutual concern and information sharing; Review and approve ASDP II financial and audit reports, Approve changes in policies and regulations for on-ward submission to parliament Recommend the National Agricultural Stakeholder Meeting (NASSM) meeting calendar and agenda Approve NCU governance, management, coordination and operational issues Agricultural Sector Consultative Group (ASCG) Meeting Chair: Permanent Secretary , MoA All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/Donors and NGOs/NSA) (local and International) Training and Research Institutions DPP- MoA Secretariat NCU- Recorder Provide Advise on sector policies, plan, budgets, public and agricultural expenditure review Coordinate stakeholders dialogue regularly on sector policies, Provide support (financial, material and others) to the sector Participate in the annual joint planning and budgeting meetings Dialogue and voice od development partner opinion, Private sector, NGOs/NSAs/CBOs. Agricultural Sector Development Programme II (ASDP-II) 199 Organ/mechanism Membership/participants Functions and purpose Technical Committee of Directors (TCD) Chair: PS-MoA Directors of ASLMS, Component Leaders, Chairs of Lead Components, PO-RALG ASDP II Coordination Head of NIRC Head of Tanzania Cooperatives Development Council Head Warehousing Licensing Board NBS Ministry of Finance and Planning Ministry of Lands and Human Settlement Tanzania Food and Nutrition Council Ministry Energy Ministry of Transport Ministry of Education Representative of Agricultural Research/Training Institutions National Coordination Unit(NCU) Secretariat Review, scrutinize and harmonize individual Lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports Recommend to ASC governance and management guidelines and procedures for implementation of ASDP II Recommend to ASC ToR for Joint Annual Reviews/Sector reviews/ Public Expenditure reviews(JSR/ASR/PER) Monitoring and Evaluation Prepare and review papers for presentation to the ASCGM and ASC Review and propose to ASC policy and regulatory changes for the sector Provide advisory and coordination role to the ASDP II thematic working group (TWG) Recommend to ASC on NCU governance, management, coordination and operational issues Lead Agency Component Technical Meeting Chair: DPP of Lead Component Chairperson(s) of the Thematic Working Group (TWG) Chair/Representative from the Monitoring and Evaluation (M&E) TWG Chair/Representative from the Planning and Budgeting (PB) TWG Representative from NCU Review submitted component plans, budgets; review and analyze reports; Coordinate, scrutinize, monitor and evaluate ASDP II component plans and budgets Submits to ASDP II National Coordination Unit(NCU) for compilation andonward submission to TDC Agricultural Sector Development Programme II (ASDP-II) 200 Organ/mechanism Membership/participants Functions and purpose Thematic Working Groups (TWGs) (Various groups) Chairs: Component/Sub- Component Leaders Component /Sub-Component Leaders Selected technical Experts of different ASLMs appointed by the Head of the Lead Agency, private sector, Experts from Development Partners, Non-State Actors and CAADP country team representatives Co-opted Members for Cross Cutting and emerging issues Prepare and review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination meeting Plan, compile, analyze, coordinate, monitor and evaluate implementation of ASDP II for the component/sub-component. Provide advice on troubleshooting of implementation process and guide and provide guidance to TCD, on a continuous basis Bring cross-cutting expertise to issues arising. ASDP II Secretariat ASDP II National Coordination Unit (NCU) National Program Coordinator Experts in: Productivity and Commercialization; Markets and Value chain;(for crops, livestock, and fisheries); Monitoring and Evaluation; Agricultural Policy Analyst; Provide a catalytic and supportive role to the agricultural transformation agenda Compile all interventions/ Project Plans and Budgets under ASDP II and develop draft consolidated annual work plans and budgets; Coordinate joint planning and budgeting; Manage, monitor, evaluate, harmonize and coordinate implementation of ASDP II. Compile, analyse, coordinate, provide program logistical support; Prepare and consolidated quarterly implementation reports for onward submission to TDC, ASC and other national forums. Provide technical support on joint monitor, and evaluate of the program for onward submission to the Technical Committee of Directors(TCD) Provide analytical and problem-solving support to the components Production of manuals, guidelines and publicity and communication materials for ASDP II; Manage M&E functions; establish and share best practices & lessons learnt under Agricultural SWAp Facilitate and coordinate ASDP II financial audit and submit the same to TDC Provide secretariat to ASDP II 201 Agricultural Sector for Industrial Development Coordination at local level 438. ASDP-1 structures for local activities will be strengthened and continue under ASDP II. District Agricultural Development Plan (DADP) will continue to be the key instrument for agricultural development at local level. The District Executive Director (DED) will hold overall responsibility for activities and funds used at local level. The Council Management Team (CMT), which is chaired by the DED and attended by all the department heads including District Agricultural Irrigation and Cooperative Office Officers (DAICO) and District Livestock and Fisheries Officer (DLFO), is informed on the agricultural development issues and status under the DADP. A detailed structure of the Coordination mechanism from the village to national level and different organs is presented in Annex III. 439. DADPs are derived from the grassroots by villagers through the O&OD process and are summarized in the form of Village Agricultural Development Plans. The village planning process is led by a Village Planning Committee, Village Agricultural Extension Officer (VAEO), Village Executive Officer (VEO) and is supported by the District Facilitation Team according to the DADP Guidelines. Proposals from individual villages are submitted to wards that encompass three to six villages, on average. The proposals are consolidated by the Ward Agricultural Extension Officer (WAEO) under the supervision of the Ward Executive Officer (WEO) and guided by the Ward Development Committee that is led by the elected Ward Councillor and submitted to the DED. Based on the submitted proposals, DADPs will be formulated by DAICOs and DFLOs. The entire process will be guided by the DADP Guidelines and detailed instructions by ASLMs through PO-RALG. The focus of DADP needs to be in line with ASDP II investment priority investments, and projects focused commodities along the value chain (CVC) and Agricultural Ecological zones (AEZ). These activities are supervised by the regional agricultural coordinators, the National Coordination Unit and the relevant TWGs. 440. As a key coordination mechanism at local level, District Value Chain Components (DVC) between sector stakeholders at LGA level will be in place (s/c 3.2). DVC brings major actors in priority local CVCs together to develop and drive the implementation of DADP activities that include various aspects such as productivity improvement, value addition and market access. The stakeholders at local level include the private sector (traders, processors, transporters, financial institutions, etc.), NGOs, development partners and various public institutions that can provide different types of technical support. 441. It is therefore crucial for LGAs to formulate comprehensive DADPs that include not only on-budget development activities but also off-budget development activities extended through various projects within the LGA. For this purpose, it is inevitable to develop a mechanism ensuring that the contribution of each and every actor in the sector is well captured by respective LGA. National Coordination at Local Government Authorities Level – PO-RALG 442. LGAs are overseen and directed by PO-RALG. The Department of Sector Coordination is responsible for management and support to LGAs in collaboration with Regional Secretariats (RSs). Vertical coordination from the then PMO-LARG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. At the regional level, there will be a Regional Consultative Committee (RCC) chaired by the Regional Commissioner (RC). The Committee provides advisory role to the districts, monitor and supervise districts activities including the DADPs. 443. Each RS is headed by a Regional Administrative Secretary (RAS). The role of RAS is to assist the LGAs to prepare DADPs, backstop and provide supervision support on the implementation of the DADPs. The RAS also assists in the submission of the quarterly and annual reports in compliance with the DADP Guidelines. 444. The Assistant Administrative Secretaryfor the Economics and Production section within RS is directly responsible for supporting development activities within the region and is assisted in the task by 202 Agricultural Sector Development Programme II (ASDP-II) the ASDP Regional Coordinator and fellow officers dedicated to specific sub-sectors. These officers will move around the region to provide technical, and managerial assistance to LGAs. The ASDP II regional coordinators will also be responsible for monitoring and evaluating district activities implemented under ASDP II. The RSs will work closely with the relevant TWGs and NCU as the need for consultation and assistance arises. For administrative aspects of ASDP II, coordination among RSs, TCD through NCU, and TWGs will be constantly maintained to realize smooth flow of information on the status of development activities and performance under ASDP II. Agricultural Sector Development Programme II (ASDP-II) 203 APPENDIX IV: Program and Project budget Requirements Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 Component 4 Budget (Sector Enablers, Coordination and Monitoring and Evaluation) Sector Enablers, Coordination and Monitoring and Evaluation 4.1 Policy and Regulatory Framework 4.1.1 Policy and Regulatory Framework and Business Environment Improvement 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310,300,000 967,330,000 352,038,000 387,241,800 425,965,980 2,442,875,780 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019,012,325 2,022,862,500 1,646,501,250 1,684,491,375 1,846,466,513 13,219,333,963 4.1.1.4 Strengthening and control of child labour in Agriculture 1,584,790,000 1,050,194,000 1,094,008,400 808,132,240 684,175,260 5,221,299,900 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587,350,000 932,655,000 426,593,000 - - 1,946,598,000 Total - SUB-COMPONENT 8,501,452,325 4,973,041,500 3,519,140,650 2,879,865,415 2,956,607,753 22,830,107,643 Agricultural Sector Development Programme II (ASDP-II) 204 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 4.2 Stakeholder empowerment & organization 4.2.1 Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing Farmer Organizations and cooperatives Movement 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors' associations in the agricultural sector 4,013,830,000 3,741,656,000 2,298,944,600 2,116,074,810 1,194,736,731 13,365,242,141 4.2.2 Promote and strengthen gender inclusiveness in the agricultural sector 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,024,921,667 3,238,193,500 2,779,148,100 852,268,200 930,673,180 10,825,204,647 Total - SUB-COMPONENT 7,038,751,667 6,979,849,500 5,078,092,700 2,968,343,010 2,125,409,911 24,190,446,788 4.3 ASDP II_sector coordination (planning & implementation at national, regional and LGA) 4.3.1 Improved and strengthen vertical coordination (from PO-ALG to RSs and LGAs) and horizontal coordination between ASLMs 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872,144,000 6,672,824,000 4,280,182,000 2,114,683,800 2,196,777,780 22,136,611,580 Total - SUB-COMPONENT 22,136,611,580 Agricultural Sector Development Programme II (ASDP-II) 205 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 4.4 Monitoring and Evaluation (incl. Agricultural statistics) 4.4.1 Improved Capacity and agricultural data collection and management systems 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425,342,000 6,997,451,125 2,879,056,270 2,591,046,637 2,195,567,312 19,088,463,344 4.4.2 Develop Agricultural Sector M&E System 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,332,900,000 3,208,586,000 1,596,941,100 1,293,583,000 1,122,429,763 18,554,439,863 Total - SUB-COMPONENT 15,758,242,000 10,206,037,125 4,475,997,370 3,884,629,637 3,317,997,074 37,642,903,206 4.5 Institutional capacity development, and knowledge management and ICT 4.5.1 Improvement of Capacity in all levels 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429,157,500 6,349,550,000 3,781,150,000 2,501,350,000 1,142,220,000 17,203,427,500 4.5.2 Improvement of ICT for Agricultural Information Services and Systems 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047,300,000 2,376,405,000 336,377,000 212,645,350 400,139,770 6,372,867,120 4.6. access to rural financing 4.6.1 Provide microfinance services 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481,305,000 1,833,055,000 1,599,616,600 1,513,723,796 638,604,290 7,066,304,686 Total - SUB-COMPONENT 7,957,762,500 10,559,010,000 5,717,143,600 4,227,719,146 2,180,964,060 30,642,599,306 Agricultural Sector Development Programme II (ASDP-II) 206 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 TOTAL -COMPONENT 39,256,208,492 32,717,938,125 18,790,374,320 13,960,557,208 10,580,978,798 137,442,668,522 Component 3 Budget (Commercialization and value addition) 3. Commercialisa- tion and value addition 3.1 Marketing 3.1.1 Develop market access for all priority commodities. 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,345,805,000 456,727,977,000 568,733,077,800 635,560,647,800 684,371,127,488 2,443,738,635,088 3.1.2 Develop market access for fisheries and livestock products 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847,305,000 9,464,598,000 156,458,314,800 171,750,092,140 368,188,102,190 713,708,412,130 3.1.2.2 Improving local and improved chicken market access 742,875,000 2,067,455,500 2,247,754,750 369,351,650 282,526,169 5,709,963,069 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,833,825,000 737,989,000 732,995,000 643,247,150 629,633,366 4,577,689,516 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,238,470,000 4,073,370,000 4,376,132,500 1,442,114,675 13,998,798,538 25,128,885,713 Total - SUB-COMPONENT 110,008,280,000 473,071,389,500 732,548,274,850 809,765,453,415 1,067,470,187,751 3,192,863,585,516 3.2 Agribusiness development: value addition and agro- processing 3.2.1 Development of processing and value addition for Crop, livestock and 3.2.1.1 Strengthening and development of agroprocessing industries for value addition for all priority commodities 10,332,690,000 14,447,726,000 15,432,309,800 16,806,037,745 18,521,995,935 75,540,759,480 Agricultural Sector Development Programme II (ASDP-II) 207 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 fishery products 3.2.1.2 Improving milk value chain 8,885,940,000 8,536,245,500 8,013,592,850 4,212,492,265 4,570,786,337 34,219,056,952 3.2.1.3 Strengthening hides and skin value chain 13,914,590,000 10,119,086,500 19,593,434,900 5,971,608,190 5,306,513,481 54,905,233,071 3.2.1.4 Strengthening value chain for horticultural commodities 4,994,890,000 1,621,794,000 4,126,542,200 1,273,611,645 1,386,890,047 13,403,727,892 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,327,700,000 21,011,437,000 22,694,470,650 24,804,587,300 27,302,251,665 122,140,446,615 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,757,355,000 6,752,314,000 7,266,361,600 7,867,464,680 8,431,888,328 36,075,383,608 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,632,790,000 12,738,732,000 3,507,122,200 504,939,770 225,448,930 26,609,032,900 3.2.1.8 Improving Postharvest Management Along Food Supply Chain For sustainable food security and nutrition 1,088,340,000 2,710,417,500 12,533,992,850 2,323,718,420 1,079,948,052 19,736,416,822 Total - Sub-Component 80,934,295,000 77,937,752,500 93,167,827,050 63,764,460,015 66,825,722,774 382,630,057,339 TOTAL- COMPONENT 190,942,575,000 551,009,142,000 825,716,101,900 873,529,913,430 1,134,295,910,524 3,575,493,642,854 Component 2 Budget (Enhanced Agricultural Productivity and Profitability) Agricultural Sector Development Programme II (ASDP-II) 208 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2. Enhanced Agricultural Productivity and Profitability 2.1 Extension training and information services 2.1.1 Strengthening agricultural extension, training and promotion/infor mation services (crops, livestock and fisheries) 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,912,630,000 772,651,750,500 849,529,380,050 838,081,042,930 921,147,859,276 4,693,322,662,756 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,372,604,150 9,719,504,500 9,349,112,950 8,505,972,245 9,221,909,470 41,169,103,315 Total - Sub-Component 1,316,285,234,150 782,371,255,000 858,878,493,000 846,587,015,175 930,369,768,745 4,734,491,766,070 2.2 Access to Agricultural Inputs and health services 2.2.1 Improved Access to Crops, Livestock and Fisheries Inputs and health services 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389,300,000 136,694,880,000 150,284,368,000 164,670,257,650 181,057,283,415 782,096,089,065 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176,191,250 2,652,218,625 2,799,882,488 2,962,312,736 3,140,986,010 15,731,591,109 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664,250,000 93,407,668,200 768,004,545 1,098,600,080 987,463,628 97,925,986,452 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146,337,500 4,533,411,750 5,008,172,925 4,245,593,993 4,638,653,392 19,572,169,559 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,114,772,384 5,175,475,000 7,350,242,000 4,460,007,000 2,090,273,670 23,190,770,054 Agricultural Sector Development Programme II (ASDP-II) 209 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,089,477,353 50,853,035,000 48,517,288,500 6,657,553,200 4,388,210,355 165,505,564,408 2.2.1.7 Strengthening Beach Management sustainable management, fisheries resources 2,537,220,000 2,134,277,250 2,199,129,975 2,146,830,473 2,319,001,645 11,336,459,342 2.2.1.8 Improvement of plant health services 13,322,105,000 11,190,853,500 7,608,436,004 1,388,679,306 477,989,282 33,988,063,092 2.2.1.9 Production of vaccines and drugs 44,569,605,614 36,191,315,000 39,699,992,500 3,705,147,750 4,379,467,025 128,545,527,889 2.2.1.10a Improvement of livestock health services 262,550,032,281 295,128,209,145 332,216,208,381 371,558,679,638 420,078,299,939 1,681,531,429,384 2.2.1.10b Improvement of aquatic health services 1,517,656,875 1,238,258,438 1,240,903,519 1,339,594,371 1,395,264,758 6,731,677,960 Total - Sub-Component 540,076,948,257 639,199,601,907 597,692,628,836 564,233,256,195 624,952,893,118 2,966,155,328,313 2.3 Agricultural Research for Development (AR4D) 2.3.1 Strengthening AR4D (crops, livestock and fisheries) 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,558,670,000 29,196,530,000 29,503,788,600 8,707,708,130 9,516,387,793 84,483,084,523 2.3.2 Research and development 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,408,638,000 16,383,957,425 11,615,699,430 11,110,318,211 11,371,090,422 62,889,703,487 Agricultural Sector Development Programme II (ASDP-II) 210 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,832,950,500 3,894,671,550 2,682,470,175 2,737,590,818 3,011,349,899 17,159,032,942 Total - Sub-Component 24,800,258,500 49,475,158,975 43,801,958,205 22,555,617,158 23,898,828,114 164,531,820,952 2.4 Access to Mechanization Services 2.4.1 Strengthening and promote agricultural mechanization (crops, livestock and fisheries) 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,249,492,000 5,753,278,650 5,698,585,515 5,707,520,942 5,717,349,911 32,126,227,017 Total - Sub -Component 32,126,227,017 2.5 Food and nutrition security 2.5.1 Food and nutrition Security improved 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,152,477,500 11,721,816,750 12,960,295,425 14,297,133,428 10,393,795,970 63,525,519,073 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,537,475,000 22,167,043,500 23,954,717,850 25,921,159,635 28,084,245,599 120,664,641,584 Total - sub- Component 34,689,952,500 33,888,860,250 36,915,013,275 40,218,293,063 38,478,041,569 184,190,160,656 TOTAL - COMPONENT 1,915,852,393,407 1,504,934,876,132 1,537,288,093,316 1,473,594,181,591 1,617,699,531,545 8,081,495,303,009 Component 1 Budget (Sustainable Water and Land Use Management) Agricultural Sector Development Programme II (ASDP-II) 211 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 Sustainable Water and Land Use Management 1.1 Land Use Planning and sustainable Water Shed and Soil Management 1.1.1 Land use planning and watershed management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones) 29,758,830,000 31,014,157,500 34,532,074,500 95,305,062,000 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity 14,132,350,000 14,517,360,000 13,715,440,000 13,501,214,000 16,283,985,400 72,150,349,400 1.1.1.3 Enhancing access to agricultural land for youth empowerment 4,464,055,000 4,149,595,000 5,753,069,750 4,533,911,000 6,321,240,750 25,221,871,500 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (all products) - 1,366,429,750 927,979,000 838,670,020 916,057,022 4,049,135,792 Total - Sub-Component 48,355,235,000 51,047,542,250 54,928,563,250 18,873,795,020 23,521,283,172 196,726,418,692 1.2 Integrated Water Use and Management for Crops/Irrigatio n and Livestock/Fishe ry Development 1.2.1 Irrigation infrastructure development 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,369,940,000 184,589,225,292 172,338,444,067 175,277,962,887 189,618,773,923 738,194,346,168 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity 5,873,183,333 50,128,619,250 57,162,204,550 59,915,108,463 65,430,495,378 238,509,610,973 Agricultural Sector Development Programme II (ASDP-II) 212 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 1.2.2 Irrigation schemes management & 1.2.2.1 Strengthening Irrigation schemes management and operations 1,822,835,000 1,651,922,500 2,249,454,750 1,786,470,225 2,592,437,428 10,103,119,903 1.2.3 Water sources development for livestock & fisheries 1.2.3.1 Development of water infrastructures for livestock productivity 2,855,560,000 66,582,431,000 77,456,128,600 76,102,476,900 85,464,005,000 308,460,601,500 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries 42,068,700,000 79,875,420,000 111,447,304,000 158,157,213,500 88,772,625,300 480,321,262,800 Total - Sub-Component 68,990,218,333 382,827,618,042 420,653,535,967 471,239,231,974 431,878,337,028 1,775,588,941,344 1.3 Mainstreaming resilience for Climate Variability/Cha nge and Natural Disasters 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies 1,905,425,000 13,984,275,833 8,745,740,917 6,345,077,933 10,444,742,727 41,425,262,410 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management 1,089,637,500 1,044,926,000 1,729,778,250 794,675,575 1,329,264,100 5,988,281,425 1.3 Mainstreaming resilience for Climate Variability/Cha nge and Natural Disasters 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness 1,959,756,667 1,051,870,333 1,008,738,867 395,675,420 501,066,927 4,917,108,214 Total - Sub-Component 4,954,819,167 16,081,072,167 11,484,258,033 7,535,428,928 12,275,073,754 52,330,652,049 TOTAL- COMPONENT 122,300,272,500 449,956,232,458 487,066,357,250 497,648,455,923 467,674,693,954 2,024,646,012,085 TOTAL PROGRAM BUDGET 2,268,351,449,399 2,538,618,188,716 2,868,860,926,786 2,858,733,108,151 3,230,251,114,821 13,819,077,626,470 operation 213 Agricultural Sector for Industrial Development ANNEX V Monitoring & Evaluation and Statistics144 Background 445. Under ASDP-1 (2006-2013), the ASLM established various TWGs, including one specializing in M&E TWG established in 2007. Its membership includes officials from planning departments in the various ASLMs and JICA technical assistants145. The objective of this group focuses on tracking and providing overall technical guidance on the implementation of this M&E framework, with the aim of monitoring the ASDP, collecting data on the sector through improving the routine data collection system, and strengthening M&E capacity in ASLMs and at regional and district level. 446. The M&E TWG prepared the M&E framework document in 2008. This document identifies the main impacts for the ASDP as a whole, by outcomes and by strategic area (physical infrastructure, agricultural services, marketing system, institutional framework and cross-cutting issues), as well as the outputs of various proposed interventions. The first list contained 100 indicators, which were later reduced to 20–25 key indicators as shown in Annex II. However, this list was modified over time to capture critical issues such as empowerment, service reform and research146. For ASDP II the key indicators are developed at the component, sub-component and priority investment area. Complete list of key indicators are as shown in the results framework (RF). 447. For effective planning, budgeting, monitoring and evaluation there will be two cross cutting technical working groups to support and facilitate planning, budgeting, monitoring and evaluation. These are the Monitoring and Evaluation TWIG (M&E-TWG) and the Planning and Budgeting TWG (PB- TWG). 448. One of the tasks of the M&E TWG is to prepare the annual ASDP II performance reports as well as sector impact evaluation. The annual performance report: provides an update on the shortlist of key indicators at the three levels: impact, outcome and output levels), compares target and actual figures, wherever possible; and assesses causes for shortcomings. Data collection was done using a conventional method: (i) for local data, a questionnaire was sent to all LGAs and filling-up and submission was transmitted by telephone and email communications; and (ii) for national data, inquiries were made by telephone or direct visits to the relevant office by members of the M&E TWG. Without being presented to the ASDP Basket Fund Steering Committee, the report has had limited use in the ASDP M&E. Past reports, in addition to the mid-term evaluation of ASDP-1, show that while there has been progress regarding selected outputs, the picture is mixed at outcome and impact levels. For example, at impact level, the indicators include agricultural growth, rural poverty and value of agricultural exports, and progress has been slower than was anticipated, particularly regarding poverty reduction. At outcome level, key indicators such as use of improved technologies (seed, fertilizer, irrigation and mechanization) have not shown the desired improvements. However, the picture is generally positive in terms of physical delivery of services (infrastructure and capacity building). 449. The conclusion of the ASDP evaluation (June 2011) was that ASDP outputs had yet to fully mature into all the intended outcomes and impacts that were foreseen during preparation. The report stresses the importance of careful and speedy measurement of higher level results, through holding surveys more regularly. 450. Under ASDP II the M &E-TWG will continue to play a similar role, however at each level of implementation (from project at the LGA to the National Level) some elements of M&E will be instituted. Each level will need to conduct both internal and external monitoring and evaluation. Joint annual sector review will be conduct in collaboration with all stakeholders. For efficiency and effectiveness, the immediate level within the government hirechical structure will carry the M &E. For example the Ward Executive Officer (WEO) will monitor and evaluate the Village Executive Office (VEO). A coherent and systematic M & E systems will be instituted from national to the 144 (Adapted from ASDP II proposal, 2013/14). 145 JICA is financing the second phase of a M&E capacity building project in the context of ASDP, which implemented by the International Development Centre of Japan (IDCJ). 146 Evaluation of the Performance and Achievements of the Agricultural Sector Development Programme, June 2011. 214 Agricultural Sector Development Programme II (ASDP-II) project level. Hence, M & E will be established at all coordination levels (National, PO-RALG, RS and District) and capacity building for the same will be ensured. At the national level, NCU will coordinate national joint annual reviews and evaluations. Tables 60 and 61 below present the internal and external monitoring and evaluation frequency for different levels in the government hierarchy. 451. The ASDP I Planning and Implementation Technical Working Group (P&I TWG) focuses on supporting districts with the preparation of their DADP, and with the implementation and reporting of ASDP activities through the DADP. The PO-RALG ensures that all districts follow the guidelines and fulfill the minimum conditions under the Local Government Development Grant (LGDG). The LGDG assessment conducted under supervision of the then PMO-RALG incorporates the specific results from the DADP assessment into the overall assessment of minimum conditions and performance measures147. A separate DADP Quality Assessment Report has been prepared for agriculture and could be used to illuminate indicators. This assessment was done by the P&I TWG together with regional ASDP coordinators. 452. During the ASDP II implementation there will be a Planning and Budgeting TWG (P &B-TWG). This will be responsible to coordinate all plans and budgets from the central, regional secretariat an LGA levels. At the Central level, all Lead Component budgets will be prepared and submitted to the P&B TWG for review, consolidation and harmonization. P&B TWG will ensure that here is consistency of the Lead Component plans and budgets to the overall ASDP II objectives and deliverables. The recommended plan and budget will be submitted to TDC and later approved by ASC. The GoT planning cycle will be upheld. The M&E TWG will also be able to monitor and evaluate implementation of the plans and budgets at all levels for the delivery of the ASDP II objectives and outcomes. 453. Due to its demand-driven nature, ASDP-1 promoted a decentralized and bottom-up approach, where farmer groups, cooperative societies and user associations, prepare a “project” based on clear guidelines and criteria, and request financing from one of the block grants available at district level.148 These projects (rehabilitate dip tanks and small irrigation scheme, etc.) are then monitored quarterly by district officials. This information was consolidated by the then PMO-RALG and shared with ASLM Technical Committee of Directors, and submitted to the ASDP Basket Fund Steering Committee for their review and approval (or rejection/further design work required). 454. All districts need to report quarterly on the physical and financial implementation of ASDP funds. A set of template tables will be prepared by the P&B TWG149. These tables will provide information by “project”, and focus on physical (output) and financial reporting, as well as providing information on the number of beneficiaries. An attempt will be made to capture outcome information at project level based on the project key performance indicators. The Joint Implementation Reviews (JIR) undertakes an annual assessment of progress made, and brings together stakeholders from ASLMs, development partners, non-state actors and the private sector to share and discuss implementation performance, and related issues and priority actions. The JIR report highlights areas where progress has been made, and provides recommendations regarding the various issues affecting ASDP implementation. Figure A1150 provides a summary overview of the M&E system established under the ASDP-1 and adapted for ASDP II towards monitoring both the performance of the ASDP itself, as well as that of the Agriculture Sector in Tanzania. 147 Annual Assessment of Minimum Conditions and Performance Measures for Local Councils under the LGDG System, PMO-RALG, May 2010. 148 District Agriculture Development Grant (DADG), Capacity Building Grant (CBG), Extension Building Grant (EBG) and District Irrigation Development Fund. 149 Strengthening the Backstopping Capacities for the DADP Planning and Implementation under the Agricultural Sector Development Programme (ASDP), International Development Centre of Japan (JICA). 150 Project for Capacity Development for the ASDP Monitoring and Evaluation System (phase 2), International Development Centre Japan, June 2012. There are two teams, one focusing on M&E for the whole of ASDP and the other focusing on planning and implementation at district level, which is supporting the PI TWG. 215 Agricultural Sector for Industrial Development 455. Under this system, sector outputs will be monitored through the Agricultural Routine Data System (see M&E section), and/or through specific reports. Sector outcomes will be monitored mainly through the NSCA, the AASS and/or the National Panel Survey (NPS) agriculture module (see statistics section). The NSCA was meant to inform many of the key outcome indicators identified in the list of key performance indicators for ASDP II. 456. The performance of the individual projects will be captured through DADP for LGA related projects for both physical and financial quarterly progress reports. While those related to the national level will be captured by NCU and those at RS will be captured by the regional ASDP II coordinator. Under ASDP-1 the system only captured projects implemented and financed under on-budget resources. Under ASDP II improved coordination within SWAp requires that all projects implemented in the sector are included in the integrated performance reporting, although non-budget projects have their own management and reporting system. The mechanisms to capture off-budget activities include: quarterly reports by each NGO project to be submitted according to requirements specified in memoranda of understanding with each NGO project, but excluding information on the source and application of funds unless volunteered to compare with projects within government programmes. Table 60: Monitoring Frequency at Different ASDP II Implementation Levels Monitoring Level Internal External Village Monthly Quarterly Ward Monthly Quarterly Division Quarterly Quarterly District Quarterly Quarterly Region Quarterly Quarterly National ( NCU) Quarterly Quarterly National (Joint Annual Implementation Reviews) Annual Annual Table 61: Evaluation Frequency at Different ASDP II Implementation Levels Evaluation Level Internal External Village Annual 1.5 years Ward Annual 1.5 years Division Annual 1.5 years District 1.5 years 2 years Region 1.5 years 2 years National and Joint Evaluations 2.5 years 2.5 years 216 Agricultural Sector Development Programme II (ASDP-II) Figure A24: ASDP M&E system for sector and project performance (adapted for ASDP II) ASDP 2 AGRICULTURAL STEERING COMMITEE ASDP M&E Baseline and Performance reports (ASDP indicators) ASDP 2 NATIONAL COORDINATION TEAM (NACOTE) SECTOR PERFORMANCE (national, regional, district, ward, village level) DADP Physical and finicial quarterly progress reports Outcomes: Production, yields,number farmers using improved technologies Outputs: Area under irrigation, number of VEO trained etc. District reporting Individual project activities and performance (at group level) Input Input Output Outcome Out put Out Come Other projects/interventions in agric (NGO,CSO, etc) Private investment in the agric sector Specific technical reports/studies (livertock/crop disease,price monitoring,food forecasting, etc. Agric. Routine Data System (ARDS) Integrated Data Collection Format (LGMD2) VAEO/WAEO format AGRICULTURAL SAMPLE SURVEYS National Sample Census for Agriculture (NSCA) - 10 years + Annual Agricultural Sample Survey (AASS - 1 year) + Other: National Panel Survey... Consolidation in Regional quaterly fin & phys. progress reports DADP (incl DIDF) Quaterly physical and financial progress report M&E TWG 457. One of the lessons learnt from ASDP-1 was that the delays in implementing key surveys, such as the NSCA, which was meant to inform many outcome indicators, led to a deficit in the information available to properly monitor and evaluate the results of the first phase. In consequence, it was ‘easy’ to assert that ASDP-1 had not achieved its results, that there had been no “impact” and that resources were spread too thinly. Equally, the planned annual services delivery surveys that would have given regular estimates of intermediate outcomes such as adoption of improved technologies were not implemented, and this proved to be a serious gap. This pointed to the need to ensure that national surveys have sufficient resources to provide necessary analysis and results on time, including annual surveys that provide critical annual performance assessments. It also points to the fact that there should be a clear separation of use of M&E as a tool to track reform processes, as well as measuring conventional benefits such as production and technology adoption. 217 Agricultural Sector for Industrial Development Monitoring and Evaluation 458. Monitoring. To monitor ASDP and performance of the agricultural sector, two data collection systems were developed under ASDP-1: (a) the Agriculture Routine Data System (ARDS) for monitoring the performance of the sector, and (b) the DADP physical and financial quarterly progress reports regarding Basket Fund resources. 459. The ARDS is designed to provide district and regional level agricultural data to ALSMs on a quarterly basis. Village and/or ward agricultural extension officers (VAEOs/WAEOs) are required to submit monthly, quarterly and annual reports to their district agriculture and livestock development officers (DAICOs and DLFOs). They review the reports and aggregate the data to the district level. District reports are forwarded to regional secretariats, where they are reviewed and approved by regional agricultural officers, before submission to ASLMs. Compliance with the reporting mechanism will be monitored by the M&E specialist of the CMT. With JICA support, the Routine Data System has been consolidated and linked to a web-based database, using custom-made software called Local Government Monitoring Database (LGMD 2)151 that allows the data to be entered electronically at the district level and forwarded through subsequent approvals process. The aim is to replace the many existing different reports at district level into a single integrated format. However, data at village and ward level is still collected manually on paper. Figure A24, sourced from ARDS review report). Figure A25: Agriculture Routine Data System Region District Ward Village ASLMs Flow of data Report format Means of data delivery Agricultural Routine Data System (ARDS) VAEO/ WAEO Format Format for Integrated Data Collection LGMD2 Hard Copy 460. While ARDS is supposed to deliver agricultural sector information from grassroots (village level) to districts and to ASLMs through regions every quarter, this system has not been functioning properly. However, the introduction of the LGMD2 is expected to improve this, as reporting forms, and flows are standardized and codified, through a web-based database. 461. With JICA support, guidelines have been prepared for VAEO and WAEO on how to systematically collect the data required152. However, one reason ARDS is too complex, is the fact that monthly, quarterly and annual reports monitor different variables. Monthly variables include weather conditions, 151 LGMD2 is new version of the former LGMD system that was developed by PMORALG as a single database to capture assets and activities for the key poverty sectors. LGMD has been abandoned by the other sectors. 152 Training guide for LGA, dated February 2011, includes training for VAEO and WAEO sector reports, and guide for district officers on data consolidation, analysis and feedback. 218 Agricultural Sector Development Programme II (ASDP-II) crops prices, crop disease report and pesticide applied, number of animals slaughtered, meat and milk inspections, animal health (vaccinations and treatments) and livestock services (Artificial insemination, etc.). Quarterly variables include number of farmer groups/members, number of farmers trained, area under irrigation, area cultivated and crop yield and production. Annual variables include population data, instances of contract farming, area irrigated, number of IO, asset inventory of agriculture machinery and tools, number of FFSs, use of fertilizer, chemical, seeds, livestock population, livestock infrastructure, information on grazing land area. The Monitoring responsibilities at local level are as shown in table A2. Table 62: Monitoring responsibilities at local level VAEO/WAEO Monthly Report VAEO/WAEO Quarterly Report VAEO/WAEO Annual Report 1. Introduction (weather condition, activity summary) 2. Crop: Planted Area, Yield, Production and Prices 3. Plant Health Services 4. Livestock Slaughtered 5. Meat Inspection 6. Livestock Products 7. Livestock Health 8. Achievements and Challenges 9. Visitors 1. Village Food Situation 2. Farmers Groups/ SACCOs 3. Extension Services 4. Biological Control Measures 5. Irrigation (planted area, production, etc.) 6. Soil Erosion 7. Area Cultivated and Means of Cultivation 1. Introduction (Population and number of households) 2. Irrigation (water source, area, IO members, etc.) 3. Contract Farming 4. Agricultural, Livestock and Fishery Machines 5. Extension Services (FFS) 6. Input Use 7. Livestock Population 8. Livestock Infrastructure 9. Rangeland 10. Pasture 11. Area covered by TV, Radio and Telecommunication 462. As can be seen, some of these variables (e.g., productivity and technology adoption) should not be captured by a decentralized administrative data collection system, given that the system is open to stakeholder influence in the results obtained from the various data collection efforts. ARDS relies on VAEO/WAEO to provide the information, yet many posts are currently vacant, and VAEO/WAEO often have mobility challenges, thereby relying on village headman to provide the information. 463. In view of the potential overlap between ARDS and some national agriculture surveys, regarding the performance of the agriculture sector (foremost the production and productivity figures), a recommendation was made by a visiting statistics mission that ARDS focuses on a reduced number of indicators that are best captured through an administrative system, on a “need to know”, and not “nice to know” basis153. While there is widespread consensus that the ARDS should focus on a reduced number of variables that can be easily captured at local level, this aspect was not satisfactorily addressed during the ARDS review conducted in late 2012154, before ARDS roll-out. Unfortunately, the list of indicators was left untouched. 464. The roll-out of the ARDS was completed in March 2014, covering all 25 regions. However, the reliance on heavy paper forms at ward/village level is costly and may prove unreliable. More modern techniques, such as hand-held computers are proposed under ASDP II to assist the system to serve its purpose. After completing the national roll-out, ARDS has been officially authorized as a data collection system for the agricultural sector through a notification from the then PMO-RALG to the District Council/Coordinator, with a request that an aggregated ARDS report be submitted electronically on a quarterly basis. 465. The DADP quarterly financial and physical progress reports have been supported by the ASDP P&I TWG. DADP preparation and implementation guidelines were prepared in June 2006, with support from the JICA-financed capacity development project. The objective of these guidelines is to serve 153 USDA Agricultural Statistics mission to Tanzania, Assessing Capacity for Agricultural Data Collection and Analysis in Support of Feed the Future July 2011. 154 Assessment of the Improved Agricultural Routine Data System, Arun Srivastava et al, December 2012. 219 Agricultural Sector for Industrial Development as an operational manual for the implementation of the Local Level Support Component of ASDP, for implementation of DADP. The TWG also prepares the Annual District Agricultural Development Plans (DADPs) Quality Assessment Report, which examines whether the DADP for the next three years has adhered to the established guidelines as well as the DADP Implementation Report using carried over funds. 466. A spreadsheet was prepared by PO-RALG to compile information disaggregated by district, regarding individual projects approved in each district and financed by ASDP. These projects are part of the DADP, which is a three-year rolling plan. District staff contact project beneficiaries or the extension officer to have updated information regarding the implementation of the project (interventions, output indicators, comparing targets and actual). Financial expenditure is captured at district level, since each “project” has its own bank account. 467. Projects include small irrigation schemes, dip tanks rehabilitation, FFSs, etc. The spreadsheet monitors 70 different types of projects and provides the number of beneficiaries for each project. The spreadsheet also tracks the unspent balance at the end of each year, and the carry over funds needed to complete a specific project. The information is consolidated into a summary sheet that allows tracking by type of intervention, and allows you to add-up the intended beneficiaries, as well as the financial support per type of intervention. 468. Although efforts have been made, DADPs contain a limited depth of strategic vision for agricultural development at district level and do not provide a comprehensive picture of agriculture sector activities implemented at district level. One reason for the limited nature of DADPs, especially for the second limitation would be that LGAs considered DADPs as a budget application tool for DADP funds. However, there have been attempts to provide a more comprehensive plan, including information from other government and non-government resources. 469. This system naturally focuses on outputs delivered through the various interventions, however, because of the view that it would be important to capture and aggregate outcome information at project level, to be able to show the results that ASDP is achieving. Based on this, a separate spreadsheet has been prepared to provide information on project/intervention at outcome level. 470. The outcome spread sheet focuses on crop and livestock productivity and production increase, crop and livestock value addition, and accessibility to financial services, all of this at individual “project” or intervention level, however, it has not been rolled-out yet. 471. It is questionable whether this approach would make sense. The same concerns regarding possible stakeholder influence on the results obtained from this data collection effort. Outcome level information is normally best captured through surveys or studies, and not through administrative reporting systems. There was confusion during the ASDP—monitoring between the project-specific and sector-wide outcomes data collection. Because of clear connection to budgets, the project-specific outcomes received in general more attention than sector-wide outcomes, resulting in relatively weak development of ASDP Sector-wide monitoring. However, it is recognized that the ASDP II M&E system must maintain a strong link to budgetary and allocation monitoring requirements. Statistics 472. The Tanzanian government uses various surveys and censuses to obtain information for agriculture and food security policy and planning decisions. The key institution is the National Bureau of Statics (NBS, www.nbs.go.tz). 473. The Tanzania Statistics Master Plan (TSMP) was prepared for the period 2010–2014, to ensure improved coordination, raise statistical awareness and produce good statistics. It provides a national framework for the development of the national statistics system in the country. Coordination includes sectoral working groups. It includes agricultural statistics component, which only covers the National Sample Census for Agriculture. The TSMP includes a budget of USD 64 million over 5 years and a Basket Fund mechanism supported by various donors (World Bank, Department for International 220 Agricultural Sector Development Programme II (ASDP-II) Development (DFID), Canadian International Development Agency (CIDA)). 474. Tanzania is one of the countries included in the FAO-led Country-STAT initiative. In this context, a TWG has been established and comprises national experts from various institutions to review and harmonize existing data. The major sources of agricultural data and their frequency are presented in Table A3: Table 63: Key surveys and census for agriculture data155 Name Characteristics Last conducted Expected frequency National Sample Census of Agriculture Covers a wide range of variables, including number of households engaged in Agriculture, sources of income, area planted to crop, crop and livestock production and productivity, marketing and storage, irrigation and input use, access to extension services and credit, inventory of assets, food consumption. Sample size of 50,000 households, provides data at district level. 2002/2003 2007/2008 5 years7 National Panel Survey Is in fact the Living Stands Measurement Study sponsored by the World Bank in many countries. Monitors progress on standards of living, and assesses impact of policies on households. Contains a module on agriculture and focuses on poverty. Sample size of 3,200 households, only allows for national estimates for rural Tanzania. Bridge between two Household Budget Surveys 2008/2009 2010/11 Every 2 years Household Budget Survey Data from the Household Budget Surveys is used to track progress resulting from the government’s poverty-reduction policies. Provides official source of poverty determination in Tanzania 2001/2002 2007/2008 2011/2012? 5 years National Population and Housing Census Provides the population figures, and includes some information on agriculture. Results are just being made available. Total population of Tanzania is 45 million. 2002/2003 2012/2013 10 years The above surveys provide the following strategic implications for enhancing the effective design and use of the M&E system to support ASDP II: 475. Due to funding limitations, the national surveys have been providing inconsistent results and at infrequent intervals. The NSCA 2007/2008 national and regional results were made available in July 2012 and the 2012/2013 edition has been postponed to 2015/2016. The results for NPS 2, conducted in 2011 were released in September 2012. 476. A recent USDA Agriculture Statistics mission mentioned that: ‘despite the importance of agriculture in the economy, agricultural statistics is not included in the core statistics, nor is it funded under the TSMP. Most of the data collection activities are donor-driven and donor-funded. Without adequate funding in the national budget to support key agricultural data collection activities, sustainability cannot be achieved’156. Additional constraints regarding the statistics system in Tanzania include unknown level of data accuracy, large inconsistencies in time series and discrepancies among various data sources, insufficient coordination and harmonization of data collection methods and instruments, lack of updated sampling frame, insufficient staff and lack of technical capacity and dependency on donor funding157. 477. In view of the above, USDA has been collaborating with FAO, the World Bank and other countries’ 155 The 5-year interval is the old setting for the National Sample Census of Agriculture. In the current ASSP it has been set to be 10 years. 156 USDA Agricultural Statistics mission to Tanzania, Assessing Capacity for Agricultural Data Collection and Analysis in Support of Feed the Future, July 2011. 157 Aide Memoire Joint FAO/USDA mission 26 March–05 April 2012. 221 Agricultural Sector for Industrial Development national statistical offices and ministries of agriculture on the development of the Global Strategy to Improve Agricultural and Rural Statistics158. An initiative of the UN Statistical Commission, the Global Strategy is a response to the declining quantity and quality of agricultural statistics worldwide. The Strategy provides a comprehensive framework to ensure the sustainability of agricultural statistics, and addresses emerging data needs. AfDB provides the RS for this initiative. 478. Two joint missions conducted by FAO, USDA and AfDB under the auspices of this initiative were fielded in January 2012 and March 2013159. The outcome of these missions was to develop a proposal to improve agricultural statistics in Tanzania, as defined in the Global Strategy. Elements of the proposal include: (i) update the ASSP; (ii) strengthen ARDS; (iii) develop sampling frame and sample design appropriate for generating agricultural statistics; (iv) design and implement an annual agricultural sample survey; and (v) build capacity to support agricultural statistics. 479. ASSP, which was prepared by the NBS in collaboration with ASLM, with technical support from FAO, defines the appropriate programme for fulfilling agricultural data needs using government resources, given due consideration to the frequency, level of aggregation, and level of precision required by data users. It also identifies appropriate data collection methods for each element of the system, then prioritize activities and identify resources needed for implementation. The resulting plan should link to the Global Strategy framework, and must be mainstreamed into the TSMP, and is contingent on GoT Resources being made available for implementation. 480. The AASS aims to provide timely and reliable crop and livestock production data on an annual basis. The recommendation from the joint mission was to focus on national and regional estimates for 8–10 crops and 3–5 livestock species. USDA is providing technical assistance to NBS and ASLM in this matter, and promoting an area-based sampling frame, using satellite imagery to identify spots, the higher the cropping intensity, the larger the number of spots, and then follow-up with interviews of the household farming that spot. The intent is to use GPS devices and hand-held electronic devices to speed up field data collection processes and ensure improved data accuracy. A first pilot survey was implemented in 2013, and a second one in 2014. The final report is expected to start rolling-out in 2015 or 2016 (depending on implementation of the National Agricultural Census). 481. The concern is to keep the questionnaire short; however, it is important to capture indicators of adoption of improved technology and access to strategic services (e.g., rural finance etc.), that should have been collected annually under ASDP-1 M&E framework. These will also be important outcome indicators in the Results Framework of the ASDP II. Another concern is whether an area sampling frame is the best approach for an African farming context characterized by small plots, multi-cropping and shifting cultivation and extensive livestock areas. This also represents a break from the normal list sampling frame, with enumeration areas, which NBS is familiar with. Moreover, the cost of this methodology is apparently likely to be high, given the sample that it is expected to cover. These aspects require further discussions with NBS, ASLM, FAO and USDA. 482. To prepare the ASSP, an Agriculture Statistics Task Force consisting of a team of agriculture statistics experts has been established under the coordination of the TSMP Sector Working Group on Agriculture. A coordinator from NBS has been designated, and other members include statisticians from ASLM, to be released under a formal memorandum of understanding mechanism to work on priority activities. FAO has recruited a national consultant to act as the resident officer to follow-up on all the elements of this programme and support the Task Force, as well as an international consultant to provide support specifically on the ASSP preparation. The TSMP Agriculture Sector Working Group will supervise the work of the Task Force. 483. Before investments are made to improve agricultural statistics, donors wanted to clarify whether the government considers agricultural statistics a priority by including these among the core economic indicators and making necessary provisions in the national budget. This point was clarified during the 158 More information on the Global Initiative to Improve Agriculture Statistics in Africa can be found at http://www. fao.org/fileadmin/templates/ess/documents/meetings_and_workshops/ICAS5/Ag_Statistics_Strategy_Final.pdf. 159 Aide Memoire Joint FAO/USDA/AfDB mission, 28 January–01 February 2013. 222 Agricultural Sector Development Programme II (ASDP-II) second mission, when various high-ranking officials from NBS, Ministry of Finance, and the PMO confirmed that the Government of Tanzania is fully committed to improving agricultural statistics and willing to provide all the support needed. All parties stressed that NBS should lead the process, in accordance with its mandate in the Statistics Act, with national staff in the driving seat. Additional support should be built around already existing systems and procedures. ASDP II Monitoring and Evaluation support under ASDP II. 484. The objective of this sub-component is to ensure that there is an improvement in the timeliness, quality and relevance of available statistics and data in the agriculture sector, to provide the data needed to monitor the performance of the ASDP II, starting with the indicators contained in its results framework. The results framework is provided in Annex II, and contains indicators such as farmers’ income, crop yields, value of produce/exports, area under improved technology, area irrigated, etc. Under this sub-component, support will be divided in two thematic areas: (i) dedicated ASDP II Agricultural Sector Monitoring and Evaluation support; and (ii) support to agricultural statistics and other sector related M&E efforts. The M&E specialist within the NCU will manage the M&E processes and ensure that they are conducted by NBS on schedule and in compliance with the terms of reference for the work. The M&E specialist will collaborate closely with the NBS on the construction of the monitoring templates to be used in the surveys. 485. Baseline and final survey. Given the uncertainty concerning the frequency, scope and funding of agricultural surveys, such as the NSCA, implemented through NBS, a specific baseline survey will be implemented aligned with 2014/2015 season to provide baseline data regarding the variables identified in the results framework. It will focus on ASDP II selected priority districts. 486. A total sample size of approximately 5,000 households is envisaged, in approximately 30 districts. This should be large enough to allow for information to be disaggregated by district. The sampling frame and questionnaire will be established in collaboration with the NBS, and will be based on the outcome of the Agricultural Statistics Strategic Plan, which foresees revisiting and improving current Sampling Frames & Sample Designs used for 2007/2008 NSCA and the 2012/2013 Population and Housing Census, to improve the definition and selection of enumerators areas. The use of a common sampling frame should allow comparison between the ASDP II baseline survey results, and the next NSCA results. 487. The sampling frame will also include non-beneficiary households with similar characteristics to those receiving ASDP II support, either in the same districts, or in neighbouring ones. This larger sampling frame will allow the completion of an impact evaluation, by comparing changes between households benefiting from ASDP II interventions, and those not benefiting from these changes. A final survey for the ASDP II will be harmonized with the NSCA and the AASS undertaken during the last year of the project, and will use the same sampling frame, and, to the extent possible, will try to visit the same households, through a panel survey. 488. It has been envisaged that the actual implementation of the baseline and final surveys would be contracted out to a reputable organization, either an academic institution or a private company through a competitive tender. However, the experience of ASLMs with contracted organizations has been disappointing and it is therefore proposed that the survey be conducted by NBS staff, but with oversight from an independent academic institution. Short-term enumerators will be hired for these two surveys, and will be supervised by NBS regional office staff. The use of portable electronic devices will be facilitated, so as to speed up data entry and cleaning, and disseminate the results rapidly. The questionnaire will be prepared in close collaboration with the Agriculture Statistics Task Force and the ASDP M&E Thematic Working Group. The baseline and final surveys are estimated to cost a total of TZS 4.8 billion (USD 3 million), or approximately USD 1.5 million each. 489. Intermediate outcome surveys. To allow tracking of key performance indicators identified in the 223 Agricultural Sector for Industrial Development results framework, intermediate outcome indicators will be evaluated yearly between the baseline and final surveys, so as to provide useful feedback regarding the implementation of the ASDP II. The intermediate outcome data will be derived from AASS, which will be expanded for the purpose from its exclusive collection of crop and livestock productivity and production statistics. The cost of the annual survey for intermediate outcome indicators is estimated to total TZS 2.4 billion. There should be a mid-term revision of the results framework (as part of ASDP II) to adjust actual performance of the M&E of ASDP II. Support to agricultural statistics and sector M&E efforts 490. Based on the Global Strategy to Improve Agricultural and Rural Statistics, promoted in Tanzania by USDA, FAO and AfDB, and based on the ASSP being developed by the Agriculture Statistics Task Force, this sub-component will include the following activities: (i) co-financing of the National Sample Census Survey for Agriculture (NSCA-2015/2025); (ii) financing of AASS during 2015–2024); (iii) strengthening the Agricultural Routine Data System (ARDS); and (iv) limited support to the M&E Technical Working Group, over the same period. 491. National Sample Census for Agriculture (NSCA). Given that ASDP II will be one of the few large- scale projects providing financing in agriculture through the public sector over the coming years, and given that financing for agricultural statistics is an ongoing discussion under the aegis of the Global Strategy to Improve Agricultural and Rural Statistics, several partners, including the government, have expressed their interest for the ASDP II to provide financing for the NSCA. NSCA is considered as the key survey for the sector and its regular implementation would go a long way in providing a common national system to all projects operating in the sector in Tanzania. 492. It is envisaged that the NSCA will be held every 10 years, and will provide district-level statistics on a wide range of variables, based on a sample size of 50,000 households. The next NSCA is due to take place in 2016 (for the agricultural season 2015/2016). Given its high cost, around 10 billion TZS, it is hereby proposed that ASDP II will contribute for about 50% of this cost, while the balance will be co-financed by the Tanzania Statistics Master Plan (TSMP) Budget Support Fund. 493. Annual Agriculture Sample Survey (AASS). The ASSP being developed by the Agriculture Statistics Task Force foresees that the AASS will provide annual, regional level, production and productivity statistics for main crops and livestock species. The annual cost and the final questionnaire of the AASS has not yet been finalized, but will be consolidated at the end of the programme piloting (2014). 494. There are ongoing methodological discussions regarding whether this will be an area-based sample or a list-based sample, or a combination of the two. These discussions are taking place in the framework of the Agricultural Statistics Task Force, between NBS, ASLM, and specialized technical assistance in statistics from USDA and FAO. This group includes statisticians from MAFC, and MLFD, is chaired by the NBS, and will also be responsible for preparing the questionnaire. Based on the cost of the pilot, which is foreseen to take place in 2013 and 2014, the AASS annual cost has been estimated at 1.6 billion TZS. 495. Given that the TSMP is unlikely to provide financing for this annual survey, and given that this annual survey would allow the sector to have reliable production and productivity estimates, albeit at regional level (discussions are ongoing to look at opportunities for enhancing data reliability to district level), the ASDP II should provide the financing for this annual survey. However, there are concerns about the current statistical methodology being advocated by USDA, which would need to be discussed with the ASDP M&E TWG and ASCG. 496. Agricultural Routine Data System (ARDS). One of the key Management Information Systems that has been developed under ASDP-1 is the ARDS. Many resources have been invested to build a national web-based database with information disaggregated at the district level, to clarify data flow 224 Agricultural Sector Development Programme II (ASDP-II) and approval, and to develop data format, procedures for data collection at village and ward level and data dissemination, from district to national level. JICA has provided long-term technical assistance and capacity building support to national ARDS rollout, which will lapse in 2015160. This system provides data on the performance of the agriculture sector, and relies on front-line extension staff to provide monthly, quarterly and annual information, which is compiled at district level and entered into a web-based database, and made available to ASLM through RSs and PO-RALG. 497. A recent review has identified which variable can be collected with some reliability at village and ward level161. However, this review fell short of ensuring that there is no overlap between the ARDS and other data sources, such as the AASS and NSCA, as recommended by the Joint USDA/FAO/ AfDB mission held in 2012. 498. The Agricultural Statistics Strategic Plan (ASSP) envisages that the ARDS should be further streamlined, and focus on information that can reliably be reported by front line extension staff, but recognizes the usefulness of having a Management Information System for the sector. ASDP II will finance an ARDS review, in year 1, to assist the M&E TWG in ensuring that it is better integrated to the other data collection systems, and that the information it provides is more comprehensive and accurate. In addition to this study, the ASDP II has made a provision to finance the implementation of the ARDS, while local governments make a provision in their budget to provide that type of recurrent expenditure. 499. Cost for routine implementation of the ARDS has been estimated to be approximately 6 million TZS/ district/year based on the assumption that one LGA has on average 15 wards. Recently, however, many LGAs increased the number of wards and thus have more than 20 wards per district. Under the assumption of 20 wards per LGA, expected costs for a LGA per year would be TZS 8 million. Total cost would thus be TZS 1.20 billion per year or TZS 6.00 billion over the 5 years (respectively USD 0.74 million/year and USD 3.7 million for the whole period). This budget includes allowances for the district M&E officer to travel (4 days a month), as well as fuel and bicycle maintenance for the WAEO and the VAEO respectively, stationery for both, distribution costs of the reports (bus fare), and printing and photocopying costs for the paper questionnaires used. 500. M&E Technical Working Group. The M&E TWG compiles the ASDP Annual Performance Report, which provides an update on all key performance indicators, at impact, outcome and output level162 and participates in the JIR, which undertakes an annual assessment of progress made under ASDP, and also results in a report163. ASDP II will make a provision to support the M&E TWG in its activities. This support has been budgeted at about TZS 100 million per year. Proposed mode of M&E coordination under ASDP II 501. Given the environment of ASDP II where multiple actors implement their respective interventions and projects, the ASDP II M&E needs strong coordination ability and data processing (collection, compilation, analysis and reporting) capability. 502. Although the institutional arrangement of ASDP-1, i.e., both M&E TWG and P&B TWG, may remain in ASDP II, two additional features must be added to strengthen their working capacity: (i) authority above both TWGs to manage them together; and (ii) small group (two to three officers) from M&E, Statistics and IT units at each ASLM who are committed to and are exclusively responsible for day- to-day operation and data processing tasks. The former assures efficient and effective coordination among various data collections, while the latter enables ASLMs to extract proper information out of wide range of data. 160 Agricultural Routine Data System (ARDS) National Roll-Out Plan, ASDP M&E TWG, 2010. 161 Assessment of the improved Agricultural Routine Data System, Arun Srivastava et al., December 2012. 162 ASDP Annual Performance Report 2009/10, March 2011; ASDP Annual Performance Report 2010/11, November 2011; ASDP Annual Performance Report 2011/12, Draft in progress, April 2013. 163 Seventh Joint Implementation Review Report, 5 May 2012–18 June 2012. 225 Agricultural Sector for Industrial Development 503. In the coordination at the central operational level, the scope of coordination will be greatly expanded in ASDP II by including NBS and representatives of parallel interventions/ projects/programmes. In order to secure effective M&E under ASDP II, regular (probably quarterly or by-monthly) coordination meeting is required, which would be facilitated by the M&E specialist of the CMT who would convene the meetings. These meetings should be attended by the dedicated Statistics and IT unit members of the ASLMs, and non-state actors such as farmer organizations, and MUVITA among others who should demand to be informed of progress. Reports on the state of data collection and overall state of the sector should be submitted to the coordination meeting to track the M&E activities under ASDP II. Such reports as well as actual M&E data should be widely disseminated through websites or any other means for the accountability of the programme. 504. In order to bridge the information gap on agricultural investments and improve coordination, in 2013 Bill and Melinda Gate Foundation (BMGF) contracted the University of Dar es Salaam Business School (UDBS) to collect comprehensive agricultural investments data under Tanzania Agricultural Investments Mapping (TAN-AIM) Phase 1 and II Project (2013 - 2017). The project focused on improving the information flow of all agricultural investments and closing the knowledge gap within the sector by understanding linkages between relevant stakeholders. The project was expected to: (i) close the information gap and improve information sharing; (ii) develop linkages, partnerships, create synergies, and avoid overlaps/duplications among stakeholders; (iii) improve coordination and collaboration among partners and stakeholders in the sector; (iv) enhance efficient and effective utilization of resources ad (vi)support in capacity building for GoT staff for sustainability. The project has provided data on who is doing what, where and with whom along the agricultural value chain. The project was expected to collect investment data from GoT, DPs, Private Sector and NGOs/NSAs. The project managed to develop TAN-AIM online mapping tool (TMT) with agricultural investments data collected from Development Partners (DPs) Agricultural Working Group (AWG) and Private Sector Development (PSD) and Trade working groups as well as the Government of Tanzania (GoT) through the implementation of ASDP I. Private sector and NGOs/NSA did not provide the data, Also agricultural investments data could not be collected at local level (LGAs) due to poor data record management and lack of integrated system to capture these information from village to district level which affects the quality and accuracy of data. To improve coordination, monitoring, and development of synegies and partenrships among stakeholders the Tanzania Agricultural Sector Mapping Tool (TANAIM) should be updated. Figure 25 below presents Development Partners (DPs) support in various value chains and commodities/products. Agricultural Sector Development Programme II (ASDP-II) 226 Figure A26: Development Partners’Contribution by Focus Area and Value Chains in Crop Sub-Sector. Agricultural Agricultural Productivity Maize Cotton Tea Coffee Paddy Cassava Sunflower Sugar Vegetables Fruits Pulses PostHarvest Safety Net Research and Ex tension Infrastructure Training & Capacity Building Agricultural Services Information Technology Emergency Preparedness Policy Reforms Nutrition Natural re source Management UNDP U USAID DFID FAO JICA WFP AfDB FAO DFID IFAD EU USAID Sweden D F I D EU AfDB AfDB DFID DFID SDC FAO c EU FAO AfDB SDC UNDP EU FAO DFID SDC UNDP SDC SDC SDC FAO SDC Sweden SDC DFID EU Sweden Sweden Sweden EU SDC SDC I r i s h A i d Irish Aid AfDB SDC SDC SDC AfDB AfDB UU S A I D AfDB AfDB AfDB AfDB IFAD SDC IFAD SDC AfDB AfDB I L O U S A I D Agricultural Sector Development Programme II (ASDP-II) 227 Figure A27: Development Partners’Contribution by Focus Area and Value Chains in Livestock and Fisheries Sub-Sector Agricultural Productivity Poultry Bee Keeping Cattle Fish Post Harvest Safety Net Research and Extension Infrastructure Training & Capacity Building Agricultural Services Information Technology Emergency Preparedness Policy Reforms Nutrition Natural resource Management AfDB AfDB AfDB DFID SDC SDC UNIDO ILO IFAD Irish Aid DFID SDC DFID EU JICA FAO FAO FAO 228 Agricultural Sector Development Programme II (ASDP-II) Table 65: Short-listed impact, outcome and output indicators for the ASDP-1 p , p Indicators Frequency Disaggregation Data source District Region National Impact (IM) 1. Real GDP growth rate per annum [MKUKUTA] Annual √ NBS 2. Headcount ratio in rural areas – basic needs poverty line [MKUKUTA] Periodical √ √ NBS (HBS) 3. Value of agricultural exports Annual √ TRA Outcome (OC) 1. Food self-sufficiency ratio [MKUKUTA] Annual l √ √ MAFC 2. Production and productivity of crops and livestock. Periodical √ √ √ NBS (NSCA) 3. Proportion of smallholder households using improved technologies Periodical √ √ √ NBS (NSCA) 4. Flow of private funds into agricultural and livestock sectors Annual √ √ TIC 5. Proportion of smallholder households using mechanization Periodical √ √ √ NBS (NSCA) 6. Ratio of processed exported agricultural products to total exported agricultural products Annual √ TRA 7. Proportion of smallholder households participating in contracting production and out- growers schemes [MKUKUTA] Annual √ √ √ LGAs 8. Proportion of LGAs that qualify to receive top- up grants Annual √ PMO-RALG 9. Proportion of LGAs that qualify to receive performance bonus Annual √ PMO-RALG Output (OP) 1. Number of agricultural production infrastructure Annual √ √ √ LGAs 2. Number of agricultural marketing infrastructure and machinery Annual √ √ √ LGAs 3. Number of extension officers trained on improved technological packages Annual √ √ √ LGAs 4. Value of loans provided by SACCOs for agriculture Annual √ √ √ LGAs 5. Number of agricultural marketing regulations and legislation in place Annual √ MITM, MAFC, MLDF 6. Number of markets where wholesale or retail prices are collected Annual √ MITM 7. Number of Inter-Ministerial Coordination Committee (ICC) meetings held Annual √ ASDP Secretariat 8. Proportion of quarterly progress reports submitted on time Annual √ √ √ Regions, ASLMs 9. Proportion of female members of Planning and Finance Committee Annual √ √ √ LGAs Note: Indicators with [MKUKUTA] are from the Poverty Monitoring Master Plan. 229 Agricultural Sector for Industrial Development ANNEX VI: Financial and Economic Analysis 1. Introduction 505. A financial and economic analysis was undertaken to assess the viability of the investments proposed for ASDP II. The main project interventions include: (i) rehabilitation and expansion of irrigation infrastructure; (ii) expansion of watershed management and conservation agriculture, (ii) development of water resources for livestock and fisheries, (iii) expansion and upgrading of agricultural research, extension and training services, (iv) improved access to agricultural inputs and machinery (including input subsidies); (v) development of farmer organizations and improved access to markets and rural finance; (vi) agribusiness development and enhanced value addition; and (vii) strengthening of policy/ regulatory framework and institutional capacity; (viii) improved food security and nutrition (including NFRA grants); and (ix) sector co-ordination and M&E. 506. The main economic benefits of these interventions are expected to be: (i) increased crop production through improved crop yields, higher cropping intensity, and diversification to higher value crops; (ii) enhanced livestock and fish production, (iii) higher farm incomes from agricultural production, (iv) increased income from agribusinesses and greater value addition, and (v) higher export earnings. Crop Production 507. Investments in land and watershed management, as well as conservation agriculture, will help to ensure that increases in crop production are sustained in areas which are vulnerable to soil erosion and declining soil fertility. In addition, it is estimated that the improved irrigation infrastructure will benefit an irrigable area of 461,326 hectares, and 100,000 hectares of existing irrigation schemes which will be rehabilitated under ASDP II. 508. Following the provision of agricultural support services, improved land and watershed management, as well as the expansion and rehabilitation of the irrigation infrastructure, the present overall cropping intensity of 92% is projected to rise to around 103% for 2,165,000 ha of cultivated land. For irrigated land, cropping intensity is expected to rise to 135% while, for non-irrigated land, the cropping intensity is assumed to increase from 90% to 100%. 509. With regard to improved crop productivity, it is anticipated that the average yields of paddy rice would rise from 1.75 tons/ha to 3.0 tons/ha. For maize, oilseeds/pulse and vegetables, the corresponding increases are 1.35 to 2.20 tons/ha (maize), 1.0 to 1.4 tons/ha (oilseeds/pulses), and from 15.0 to 20.0 tons/ha (vegetables). 510. This increase in overall crop production within the ASDP II area will lead to a notable improvement in the net farm incomes of smallholders. Furthermore, there will be an increase in income and employment opportunities resulting from an expansion of processing, transport and marketing of crops and crop by-products. Livestock and Fisheries 511. The development of water resources for livestock and the provision of support services are expected to result in an increase in livestock productivity. Currently, livestock are a source of a wide range of products including milk, meat, and manure as well as cash income, but productivity is very low. In the future with project situation, increases in livestock productivity will primarily arise from the adoption of improved pasture management and better livestock husbandry practices particularly with respect to nutrition and animal health. This will notably improve milk yields and enhance the efficiency of meat production through better live weight gains. The proposed fisheries interventions are primarily aimed increasing aquaculture production through the expansion of fish ponds as well as improved support services. This will enhance the livelihoods of rural communities engaged in fish production and marketing. 230 Agricultural Sector Development Programme II (ASDP-II) Farmer Organizations, Marketing and Agribusiness Support 512. ASDP II includes measures to expand farmers’ access to rural markets, improve marketing systems and provide support to agribusinesses. These interventions are likely to provide significant economic benefits, such as enhancing CVCs, increasing value addition, and improving the income and employment opportunities of agribusinesses engaged in the transport, storage, processing and marketing of agricultural produce. However, the economic benefits of these interventions have not been quantified in the economic analysis. 513. Furthermore, due to the large annual and seasonal variations in agricultural prices, the possible increase in farm gate prices (resulting from better access to markets and improved efficiency of the marketing systems) has not be taken into account in the financial analysis. 2. Financial Analysis Crop Budgets 514. A financial analysis was undertaken to assess the likely impact of ASDP II interventions on farm incomes. Four budgets were prepared to represent the main crops grown in Tanzania, namely maize, rice, oilseeds/pulses and vegetables. Crop budgets were prepared for the present, future without project, and future with project situations. 515. With regard to the future with project situation, the consultant estimated the expected crop yields and input usage, as well as the labour and machinery requirements for field activities. Increases in crop production will mainly arise from the provision of irrigation facilities as well as the adoption of improved crop production techniques by farmers on both irrigated and non-irrigated land. Furthermore, an increase in crop inputs is also anticipated, together with the adoption of improved farm machinery, which will significantly enhance crop production practices within the ASDP II area. 516. The average crop yields used in the analysis for the present, future without and future with project situations are summarised in Table A5. It is envisaged that the future with project yield levels would be fully achieved within two years of completing the strengthening of agricultural support services, implementation of improved land and watershed management, as well as the construction of irrigation infrastructure envisaged under the programme. To ensure that these long-term improvements are sustained, agricultural support services have also been included in the long-term recurrent costs. Table A5: Crop yields in present, future without and future with project Average Crop Yields (tons per hectare) Present Future Without Project Future With Project Maize 1.35 1.50 2.20 Rice 1.75 1.95 3.00 Oilseeds/Pulses 1.00 1.10 1.40 Vegetables 15.00 16.50 20.00 Source: Crops Sector National Report (2012) and consultant’s estimates 517. In the future without project situation, it is expected that crop yields will gradually increase due to the adoption of improved cropping practices. It is therefore anticipated that there will be an increase in crop yields at the rate of 1% per annum. The average crop yields in the future without project situation (given in Table A5) reflects the expected levels of productivity after 10 years. 518. On the basis of the crop yields, crop inputs, produce/input prices, wage rates, as well as labour, oxen and machinery requirements, financial crop budgets in the present, future without and with project situations were prepared. By deducting production costs from crop revenues, financial crop gross 231 Agricultural Sector for Industrial Development margins were determined for each selected crop. In both the future with and without project situations, it has been assumed that farm gate prices (in constant terms) will remain unchanged from their present values. The financial crop gross margins are summarized in Table A6. Table A6: Financial crop gross margins in present, future without and future with project Gross Margins (TSh per hectare) Present Future Without Project Future With Project Maize 67,088 119,831 216,550 Rice 322,500 423,844 709,375 Oilseeds/Pulses 512,625 613,250 807,500 Vegetables 2,267,000 2,583,875 2,927,250 Source: Crop budget estimates 519. It is evident from Table A6 that, in the future with project situation, there is a significant improvement in the net returns for all types of crop. This reflects the notably higher yield levels which generate incremental returns in excess of the additional production costs. It is also apparent that the net returns per hectare from vegetables are substantially higher than the returns from maize, rice and oilseeds/ pulses. However, the attractive returns from horticultural crops are moderated by the risks associated with very large seasonal price fluctuations. Cropping Patterns 520. Present cropping patterns were determined for: (i) existing irrigated area, (ii) proposed irrigated area, and (iii) non-irrigated area under the programme. These cropping patterns are not expected to alter significantly in the future without project situation as only a small increase in cropping intensity is likely without an improved supply of irrigation water. 521. In the existing irrigated area, it is anticipated that the areas of rice, oilseeds/pulses and vegetables will increase in the both the wet and dry seasons as a result of ASDP II interventions. In the proposed irrigated area, there will be a significant change in cropping pattern (from rainfed to irrigated) with a major expansion in the area of rice in the wet season and the introduction of maize, rice, oilseeds/ pulses and vegetables in the dry season. The cropping patterns used in the financial and economic analysis are presented in Table A7. 522. In the existing irrigated area, cropping intensity is expected to increase from 125% to 135% while, on the proposed irrigated area, cropping intensity will rise from to 90% to 135%. For non-irrigated areas, cropping intensity in the future with project situation is estimated at 100%. Overall, the cropping intensity in the ASDP II area is expected to increase from 92% to 103%. The lack of an adequate and reliable supply of irrigation water will probably limit further increases in the cropping intensity during the dry season. Table A7: Cropping patterns and cropping intensity Crop Enterprise Present and Future Without Project: Cropping Patterns (% of cultivated area) Rehabilitated Irrigated Area New Irrigated Area Non-irrigated Area Overall Wet Season Maize 45 63 63 62 Rice 40 5 5 7 Oilseeds/Pulses 5 20 20 19 Vegetables 5 2 2 2 sub-total 95 90 90 90 232 Agricultural Sector Development Programme II (ASDP-II) Crop Enterprise Present and Future Without Project: Cropping Patterns (% of cultivated area) Rehabilitated Irrigated Area New Irrigated Area Non-irrigated Area Overall Dry Season Maize 15 0 0 1 Rice 0 0 0 0 Oilseeds/Pulses 10 0 0 0 Vegetables 5 0 0 0 sub-total 30 0 0 1 Cropping Intensity 125 90 90 92 Crop Enterprise Future with Project: Cropping Patterns (% of cultivated area) Rehab. Irrigated Area New Irrigated Area Non-irrigated Area Overall Wet Season Maize 30 30 67 64 Rice 50 50 5 8 Oilseeds/pulses 10 10 25 24 Vegetables 10 10 3 4 100 100 100 100 Dry Season Maize 10 10 0 1 Rice 5 5 0 0 Oilseeds/pulses 10 10 0 1 Vegetables 10 10 0 1 35 35 0 3 Cropping Intensity 135 135 100 103 Source: Crops Sector National Report (2012) and consultant’s estimate Livestock 523. The livestock component of ASDP II is expected to improve the productivity of different types of livestock enterprises such as dairy cows and beef fattening. Increases in livestock productivity will primarily arise from the adoption of better livestock management practices and improved nutrition. 524. In the financial analysis, budgets were prepared for two livestock enterprises, namely dairy production and beef fattening. The livestock outputs and inputs were valued in 2015 farm gate prices to derive financial gross margins for each of the enterprises (Table A8). In the future with project situation, the improvements in net returns primarily reflect the higher levels of productivity. 233 Agricultural Sector for Industrial Development Table A8: Financial livestock gross margins in present, future without and future with project Livestock Enterprise Financial Gross Margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 176,975 311,975 Beef Fattening 77,900 102,900 Source: Livestock budget estimates Farm Budget Analysis 525. Farm budget analysis was undertaken to determine the impact of the project interventions on farm incomes. The farm budgets were prepared for an average sized farm of 2.0 ha. Based on the cropping patterns given in Table A7, the crop areas were calculated and then applied to the respective financial crop gross margins in order to derive the likely net returns to farmers in the present, future without and future with project situations. The net returns from the livestock enterprises were then added to determine an overall farm gross margin. Following the deduction of fixed costs (e.g. land rent, equipment/farm tools), net farm incomes were obtained. A summary of the net farm incomes for the different ASDP II areas is given in Table A9. 526. It is evident from Table A9 that there are likely to be very significant increases in net farm incomes. Comparing the present and future with project situations, net farm income in the existing irrigated area is expected to increase from TSh 900,568 to TSh 2,665,228 (before irrigation O&M costs) while, in the non-irrigated areas, net farm income is estimated to rise from TSh 367,385 to TSh 1,158,275. Overall net farm income is expected to increase from TSh 436,699 to TSh 1,655,569 per annum. 527. When irrigation O&M costs are included, net farm income for the irrigated areas falls to TSh 2,229,994 per annum in the irrigated areas. However, as irrigation costs only account for about 16% of net farm income, farmers will have the ability to meet annual O&M costs. Table A9: Net Farm Incomes in Present, Future Without and Future with Project Irrigation Status Net Farm Income (TSh per annum) Present Future Without Project Future with Project Excluding Irrigation O&M Costs Including Irrigation O&M Costs Rehab. Irrigated Area 900,568 1,138,498 2,665,228 2,229,994 New Irrigated Area 367,385 496,902 2,665,228 2,229,994 Non-irrigated Area 367,385 496,902 1,158,275 Overall 436,699 580,309 1,655,569 Source: Farm budget estimates 3. Economic Analysis Economic Pricing 528. Economic prices for internationally traded goods (such as rice, maize, soya bean and fertilizers) were derived from the World Bank commodity price projections for 2015. These world prices were adjusted for sea freight, insurance and border charges, as well as local transport, handling and, if applicable, processing costs, in order to determine economic farm gate prices. 529. Local transport, handling, storage and processing costs were based on the current rates prevailing in Tanzania. However, these financial prices were converted to economic prices by applying the standard conversion factor (SCF) of 0.95. The SCF reflects the shadow exchange rate in Tanzania which is at variance with the official exchange rate due to distortions in the foreign exchange market. Economic prices for other non-internationally traded agricultural goods, such as vegetables and straw, were taken from the 2015 financial prices prevailing within the project area. 234 Agricultural Sector Development Programme II (ASDP-II) 530. Labour costs were based on the rural wage rates which varied according to the type of farm activity but averaged around TSh 5,000 per day for most farm operations. However, given the high levels of underemployment within the project area, a shadow wage rate of 0.65 was used to determine the economic value of labour. 531. The economic analysis was undertaken over a 50-year period in 2015 constant prices and a shadow discount rate (opportunity cost of capital) of 12% was assumed. The Tanzania shilling was used as the unit of account and an exchange rate of TSh 2,150 to USD 1.0 (June 2015) was applied when converting to USD. It was anticipated that the project would be implemented over a 10-year period. Economic Benefits 532. In the estimation of agricultural benefits, economic crop gross margins per hectare were calculated by valuing the physical input and output quantities in terms of their respective economic prices. The economic crop gross margins in the present, FWO and FW project situations are summarized in Table A10. The economic gross margins per hectare were then multiplied by the respective crop areas in order to estimate net crop benefits in the present, future with and future without project situations. The differences between the net crop benefits were then calculated to determine the economic impact of the changes in cropping patterns and improved crop yields. Table A10: Economic crop gross margins in present, future without and future with project Crop Enterprise Economic Gross Margins (TSh per hectare) Present Future Without Project Future With Project Maize -80,084 -37,321 42,813 Rice 98,649 185,461 359,371 Oilseeds/Pulses 416,142 511,441 697,594 Vegetables 1,589,450 1,860,013 2,115,150 Source: Crop budget estimates 533. Net livestock benefits were also estimated for the present, future without and future with project situations (based on the respective livestock populations and economic gross margins). These benefits were then added to the net crop benefits. Economic livestock gross margins are summarized in Table A11. Table A11: Economic livestock gross margins in present, future without and with project Livestock Enterprise Economic Gross Margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 104,225 237,975 Beef Fattening 56,500 86,500 Source: Livestock budget estimates 534. As a result of these increases in crop and livestock production, net agricultural benefits to farmers within the project area were estimated to rise by TSh 626,572 million per annum (from TSh 245,152 million to TSh 859,700 million per annum at full development). It is envisaged that the future with project agricultural benefits would be fully attained within 2 years of programme completion. Benefits from crop production are estimate to account for 81% of the overall agricultural benefits. Capital and Recurrent Costs 535. The capital investment required for the implementation of the four ASDP II components, i.e., sustainable land and water management, enhanced agricultural productivity, rural commercialization/ value addition, and strengthening sector enablers, were compiled from the estimates made by the consultancy team. These capital costs were then distributed over a 10 year implementation period. 235 Agricultural Sector for Industrial Development 536. In financial terms, the base capital cost was estimated TSh 6,230,100 million (USD 2,898 million) and when physical contingencies were included, the project cost increased to TSh 7,882,948 million (USD 3,666 million). Physical contingencies were estimated at 10%. 537. In the derivation of economic costs, government taxes and duties as well as subsidies (e.g., farm input subsidies and NFRA grants) were first omitted from the financial costs, as these are transfer payments within the economy and so are not real resource costs. The standard conversion factor (SCF) of 0.95 was then applied to the financial costs of local materials, machinery/equipment and skilled labour. The cost of unskilled labour was also reduced by applying the shadow wage rate factor of 0.65. The financial cost of foreign goods and services remained unchanged. These economic conversion factors were then applied to the financial costs in order to determine the economic capital cost which was estimated at TSh 2,778,544 million (USD 1,292 million). The financial and economic capital costs of the ASDP II components are summarized in Table A12. Table A12: Financial and economic capital costs Programme Components Financial Cost (TSh million) Economic Cost (TSh million) Component 1: Sustainable Water & Land Use Management 1,450,593 1,233,004 Component 2: Enhanced Agricultural Productivity 1,517,960 607,184 Component 3: Commercialization and Value Addition 1,483,429 1,260,915 Component 4: Strengthening Sector Enablers 1,778,118 711,247 Base Cost 6,230,100 3,812,350 Physical & Financial contingencies 1,652,848 1,011,418 Total Capital Cost 7,882,948 4,823,768 538. The long-term annual operation and maintenance costs of the irrigation infrastructure were also included in the economic analysis, as these recurrent costs will have to be met if the future benefits of the capital investment are to be sustained. The annual O&M cost of the infrastructure was estimated at TSsh 38,915 million (USD 21.8 million). These financial costs were then converted to economic values, and the annual economic O&M costs were estimated at TSh 34,614 million (USD 16.1 million). 539. In addition, it was assumed that agricultural support services will also be required on an annual basis over a 50-year period. The annual costs of support services were therefore included in the analysis to ensure that agricultural production continues to grow after completion of ASDP II. In total, economic recurrent costs after programme completion amounted to TSsh 67,740 million per annum (USD 31.5 million per annum). Economic Viability and Sensitivity Analysis 540. By deducting the capital and recurrent costs from the economic benefit stream, an incremental net benefit stream for the programme was determined over a 50-year period (in constant 2015 prices). The incremental net benefit stream was then used to estimate the economic internal rate of return (EIRR) and net present value (NPV) calculated at a discount rate of 12%. The results of the economic analysis indicate that the EIRR of ASDP II is 14.8% with a NPV of TSsh 370,009 million (USD 172 million). These results show that the proposed project investment is justified on economic grounds. 541. Sensitivity analysis was also undertaken to test the economic viability of the proposed interventions to various changes in the cost and benefit streams. This analysis indicated that ASDP II is fairly sensitive to changes in benefits and costs and becomes uneconomic with an increase in capital and recurrent costs of 21%. Similarly, an 18% decrease in incremental project benefits would result in the EIRR falling below 12%. 236 Agricultural Sector Development Programme II (ASDP-II) 542. The results of the sensitivity analysis are given in Table A13 and it can be seen that a decrease in capital and recurrent costs of 20% resulted in an EIRR of 18.8%, while a cost increase of 20% lowered the EIRR to 12.1%. Similarly, an increase in incremental benefits of 20% produced an EIRR of 18.0% and a benefit decrease of 20% reduced the EIRR to 11.6%. The analysis also considered the possibility of a combination of a 20% benefit increase and a reduction in project costs of 20%. Under this scenario, the EIRR increases to 22.6%. In contrast, if a benefit reduction of 20% is combined with a 20% increase in costs, the EIRR falls to 9.3%. 543. In addition, changes in the expected cropping intensity were also assessed and the analysis indicated that if a future with project cropping intensity of 100% is assumed (in comparison to 103% in the base case), the EIRR falls to 14.3%, while a cropping intensity of only 95% will further reduce the EIRR to 11.8%. 544. With regard to crop productivity, the analysis indicated that if yields of maize and rice only increased by 50% (in comparison to 57% and 67% in the base case), the EIRR falls to 10.7% and ASDP II becomes uneconomic. Furthermore, if overall crop yields are only 40% higher after programme completion, the EIRR reduces to 7.7%. The economic viability of ASDPII is therefore very sensitive to achieving the expected yield levels. It should therefore be emphasized that the adoption of improved cropping practices and expected increases in crop yields (to maintain economic viability) will only be achieved if adequate agricultural support services, including extension/training and input supply as well improved access to markets and rural finance, are made available to farmers in an effective and efficient manner. Table A13: Economic viability and sensitivity analysis Scenario EIRR (%) NPV (TSh million) Base Case 14.8% 370,009 Capital and Recurrent Costs -20% 18.8% 722,428 Capital and Recurrent Costs +20% 12.1% 17,589 Incremental Benefits +20% 18.0% 796,430 Incremental Benefits −20% 11.6% −56,413 Costs -20% and Incr. Agric Benefits +20% 22.6% 1,148,850 Costs + 20% and Inc. Agric Benefits −20% 9.3% −408,832 100% Cropping Intensity with Project 14.3% 299,966 95% Cropping Intensity with Project 11.8% −21,536 50% Increase in Crop Yields 10.7% −531,096 40% Increase in Crop Yields 7.7% −165,650 237 Agricultural Sector for Industrial Development ANNEX VII: Risks assessment and Mitigation Strategies/Measures Programme stakeholder risks Inadequate policy incentives for participation of private agribusiness partners in programme activities, especially their envisaged role in value chain development will undermine achievement of programme objectives. Mod-erate Dialogue on improving environment for private sector investment continues, and Government is committed to enhance private investment in agriculture through initiatives like Kilimo Kwanza and the Southern Agricultural Grow Corridor for Tanzania. The proposed District Stakeholders Commodity Value Chain Platforms under the overall government’s programme will enhance the interactions and partnership among value chain stakeholders. Operating environment risks Country Tanzania’s growth remains vulnerable to external and domestic shocks that can be exacerbated by domestic structural constraints. There are continued risks of exogenous shocks from another global economic downturn and global fuel and food price hikes. Regional and domestic risks include droughts. The vulnerability risk against such exogenous shocks is compounded by the country’s dependency on foreign aid, making the country extremely vulnerable to changes. The fiscal framework is increasingly vulnerable to risks embedded in the strategic choices adopted by the Government, including increasing use of non-concessional financing for investment projects, unbalanced allocation of resources between infrastructure and social sectors, and internal pressures on wages. The level of public debt has increased dramatically over recent years, reaching, approximately 40% of GDP. Limited capacity in the government system and its staff to implement and manage the reform agenda represents another risk. This includes, most notably, capacity constraints in PFM, including budget planning and execution. Serious PFM capacity constraint in the local governments is of particular concern, as the Government pursues its decentralization policy. The PRSC series provides a platform from which the Bank can engage in a dialogue with the Government on macroeconomic and fiscal conditions so as to build resilience against external and domestic shocks, maintain fiscal sustainability and improvement of overall reform programme. This PRSC series, through its focuses on PIM and PFM including debt management, directly contribute to mitigation of risks related to use of excessive non- concessional lending, fiscal institutions, including debt management The dialogue process under the PRSC series, such as PER, addresses capacity constraints. Relevant knowledge work under the PRSC series to build analytical underpinnings will also maximize the participation of the Government and other national stakeholders, such as CSOs and the academic community, so as to enhance the analytical capacity and the knowledge-sharing environment in the country, which are essential to enhancing domestic accountability. Sector and multi-sector The programme will be implemented under a complex institutional structure−multi-sectoral, multi-donor environment, in parallel with several standalone projects. This may lead to conflicting agenda and interests, as well as inadequate capacity to effectively manage and coordinate several activities under different projects Moderate The programme is providing a framework for the implementation of the agreed government programme, using strengthened government systems. The sector- wide coordination framework will help to harmonize implementation various projects in the agricultural sector. A MoU will be signed between all donors supporting ASDP II (and the sector) to agree on principles for operating and managing support to the sector, in accordance to overall sector coordination framework. 238 Agricultural Sector Development Programme II (ASDP-II) Implementing agency risks Weak capacity on financial management, procurement, M&E and oversight of projects especially in local government may undermine accountability and tracking programme results. High The programme is aligned with (comprises) Government’s initiative which emphasizes results management and accountability. The Agricultural Delivery Unit will be established in the Ministry of Agriculture to enhance accountability and tracking of results in the sector. In addition, there are on-going efforts by government to strengthen FM and procurement capacity through recruitment/assignment of staff and training. The proposed programme includes support for institutional strengthening and capacity building to programme implementers. Efforts to improve agricultural statistics and M&E system; and establishment of MIS under the programme will enhance flow of information and accountability. The communication strategy prepared under the first phase will improve management of information flow at different levels, decision-making, and accountability and strengthen M&E and quality of information. Governance. Weak budget and accountability systems especially at local levels may undermine internal controls and funds may not be used efficiently and economically for intended purposes. Inadequate regulatory and unfavourable local tax regime could reduce programme benefits. Moderate Each ASLM has functional internal audit and audit committee. The programme coordination unit will provide oversight for allocation and utilization of programme resources to ensure that funds are used for the intended purposes. Recruitment of qualified accounting staff, internal auditors, and procurement staff at national level has been done, and efforts to strengthen capacity of LGAs in accounting, internal audit and procurement are underway. Governance risks, fraud & corruption There is potential for fraudulent bonus payment claims, especially on procurement activities, due to inadequate transparency and limited capacity to monitor and report fraud and corruption, especially at the local level. Moderate Internal auditors of implementing agencies have been trained in value-for-money auditing. Other oversight mechanisms will include regular performance reviews and regular public expenditure reviews. Social accountability mechanisms will strengthen transparency and the quality and accuracy of results. Programme risks Design. The national and local implementing agencies have inadequate capacity for value chain development and proposed commercialization models. This will affect the achievement of programme objectives. Limited capacity of private service providers and weak farmer organizations may impede commercialization of smallholder farmers, transfer of technologies and realization of optimal returns from value chain investments. High There are on-going efforts to develop capacity Value chain analysis/approach in ASLMs and LGAs. The overall programme will support capacity building of Agribusiness Service Providers. Additional support will be provided to strengthen farmer organizations and facilitate linkages with private service providers/ agribusiness. 239 Agricultural Sector for Industrial Development Social & environmental There is a risk of poor compliance with environmental and social safeguards policies related to implementation of programme activities, such as irrigation investments and use of fertilizers and other agrochemicals Moderate The government has established an environment unit at central level and District Environment Officers at local level and Local Government Authorities are being trained on safeguard issues. Progress made so far on integration of environmental and Social safeguards in programme implementation will be strengthened further to meet the needs of the proposed programme. The existing ESMF/RPF, IPMP and INMP will be revised to provide guidance for mitigating safeguards risks. The Government Authorities have appointed District Environment Management Officers (DEMOs) responsible for coordination and supervision of local investments to ensure integration of safeguards issues. The DEMOs have been trained on application of ESMF/ RPF principles, and the need to carry out Environmental and Social Impact Assessment (ESIAs) and preparation of Environmental and Social Management Plans (ESMPs) and/or Resettlement Action Plans (RAPs). Programme & donor The programme will be financed in parallel with other donors supporting Government programme and stand-alone projects and initiatives funded by other non ASDP II donors and private sector. Inadequate coordination of sector activities will overburden the implementing agencies with competing demands, duplications and thus undermine the achievement of the overall programme objective. High The programme will support the agreed Government Programme. A memorandum of understanding will be signed by all ASDP II donors to agree on respective financing principles towards enhancing coordination among donors. The Government programme also includes support to LGAs to improve coherent sector planning; a common framework for tracking results, including sector targets and outcome indicators. This coordination will be implemented under the ‘expanded’ SWAp. Delivery monitoring & sustainability. Long- term impact and sustainability of programme activities is likely to be constrained by limited capacity and low participation of private service providers in value chain development, limited M&E skills and inadequate community ownership of programme investments Moderate The programme will initially focus on high potential district clusters and enhance inclusive private sector investment at local level. The ASDP II programme includes support to capacity building on results monitoring. Agricultural Sector Development Programme II (ASDP-II) 240 ANNEX VIII: Key Maps and Figures Figure A28: Agro-ecological Zones 241 Agricultural Sector for Industrial Development Table A14: Agro-ecological zones (AEZ), priority commodities and potential focus districts (tentative) AEZ Priority Commodities Regions Districts Crops Livestock/ fisheries 1 Arid Lands (unimodal 400–900 mm) Sunflower/ maize/ sorghum/ millet, rice, potatoes, cassava, horticulture, Meat— beef, dairy, goat, Mara (E) Musoma TC, Musoma DC, Serengeti, Bunda, Tarime, Rorya Dodoma (E) Masai Steppe, Tarangire, Mkomazi, Pangani and East Dodoma Simiyu Bariadi DC, Maswa, Meatu, Itilima, Busega Manyara (E) Kiteto, Simanjiro 2 Eastern coast Cassava, rice, maize, cashew, cassava, beans, sugar cane, Oil crops, horticulture, seaweed. Goats, (unimodal) poultry, fish Lindi Lindi DC, Lindi MC, Liwale, Ruangwa, Kilwa, Nachingwea. Mtwara Mtwara T.C, Mtwara DC, Masasi, Nanyumbu, Tandahimba, Newala Dairy (bimodal), beef, poultry, goat, skin/ hides, fish, Tanga Handeni, Kilindi, Korogwe DC, Lushoto, Muheza, Mkinga, Pangani, Tanga, Korogwe Pwani Kibaha TC, Kibaha DC, Bagamoyo, Mafia, Mkuranga, Kisarawe, Rufiji Dar-es- Salaam Ilala, Kinondoni, Temeke Alluvial Plains floods,swamp)- Morogoro ( Kilombero,Wami),Pwani (Rufiji coast),Mbeya( Usangu) Rice, Sugar cane (Morogoro) Central clay plain with alluvial fans Mangrove swamp delta, alluvial soils, sandy upstream, loamy floodplain (Mbeya) Seasonally Flooded clay / alluvial soils (Morogoro) Moderate alkaline black soils, alluvial fans, well drained black loam (W) 3 Northern Highlands (bimodal) Maize, rice, pulses/beans, legumes horticulture, banana Meat— beef, ,dairy, goat, Arusha (S) Arusha DC, Meru, Arusha MC, Karatu, Monduli, Longido, Ngorongoro Kilimanjaro (N) Moshi D. C., Hai, Siha, Moshi M. C, Mwanga, Rombo, Same Manyara (E) Babati TC, Babati D.C Hanang, Mbulu 4 Plateaux (unimodal) Maize and pulses W: Tabora, Rukwa/ Katavi Tabora MC, Igunga, Nzega, Sikonge, Tabora(Uyui, Urambo Mpanda DC, Mpanda TC, Mlele Mbeya (N) Chunya (partie N) Ruvuma + Morogoro (S) Songea T. C, Songea D.C, Namtumbo, Mbinga, Tunduru, Ulanga (Mo) Mwanza Mwanza CC, Magu, Geita, Ukerewe, Misungwi, Sengerema, Kwimba Geita Geita DC, Chato, Bukombe, Nyang’wale, Mbogwe 5 Central semi-arid (unimodal) Oil seed maize/ sorghum/ millet, rice, horticulture, sugar cane Meat— beef, , dairy, goat, Poultry, Dodoma (W) Kondoa, Dodoma MC, Mpwapwa, Kongwa, Bahi, Chamwino Singida Singida DC, Singida MC, Manyoni, Iramba, Ikungi, Mkalama Shinyanga Shinyanga M C, Shinyanga D.C, Kishapu ,Kahama Morogoro Morogoro MC, Morogoro DC, Mvomero 242 Agricultural Sector Development Programme II (ASDP-II) AEZ Priority Commodities Regions Districts Crops Livestock/ fisheries 6 Southern & highlands Maize, Rice, potatoes, horticulture, Tea/Coffee, Sugar cane Meat— beef, goat, poultry, dairy. S-Mbeya Mbeya MC, Mbeya D. C, Mbarali, Kyela, Rungwe, Mbozi, Ileje, Chunya (S) S-Iringa Iringa DC, Kilolo DC, Iringa (S), Mufindi, Njombe Makete, Ludewa, Njombe TC, Njombe DC. Makambako, Morogoro NW Kilombero, Kilosa 7 South Western highlands Maize, Horticulture, pulses, potatoes, wheat, rice, oil seed Poultry, beef, dairy, goat, fish Rukwa Sumbawanga D.C, Sumbawanga TC, Nkasi, Mpanda DC, Mpanda TC 8 Western highland Cotton, Sugar cane, Rice, Maize, Cassava, oil seed/crop, banana, coffee Poultry, beef, goat, fish Kigoma Kasulu, Kibondo, Kigoma DC, Kigoma TC Kagera (bimodal) Biharamulo, Bukoba D. C, Misenyi, Bukoba T. C, Karagwe, Muleba, Ngara Source: ASDP II BF (2013)—ARD; Tanzania CSA Programme (2015) and de Pawn (1984) Table A15: Agricultural production—Food crops ’000 metric tons Year 2003/ 2004 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Maize 3,157 3,219 3,423 3,302 3,556 3,326 4,475 4,341 5,104 5,288 6,734 Sorghum 757 714 712 971 861 709 789 807 839 782 883 Millets 201 221 228 194 203 220 372 312 214 292 363 Rice 688 759 805 872 875 868 1,700 1,461 1,170 1,342 1,681 Wheat 67 102 110 83 92 95 62 113 109 102 167 Pulses 879 886 1,050 1,156 1,126 1,116 1,254 1,632 1,827 1,871 1,697 Cassava 1,480 1,846 2,053 1,733 1,797 1,972 1,464 1,549 1,821 1,878 1,664 Bananas 734 991 1,169 1,028 982 1,073 975 1,048 842 1,317 1,064 Potatoes 874 931 1,396 1,322 1,379 1,392 1,231 1,710 1,418 1,808 1,761 Table A16: Agricultural production—Cash crops (in metric tons) Year/VC 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Tea 32,000 30,000 34,446 32,698 34,165 33,160 35,000 33,000 33,700 33,000 Sugar cane 229,620 263,317 192,535 265,434 276,605 279,850 317,000 260,055 286,380 293,011 Tobacco 51,970 56,500 65,299 55,567 58,702 60,900 78,000 126,624 74,240 100,000 Cotton 344,210 376,591 130,565 200,662 368,229 267,004 260,000 225,938 351,151 246,767 Pyrethrum 1,000 2,800 1,500 2,800 3,280 3,320 5,000 5,700 6,100 7,000 Sisal 26,800 27,794 30,934 33,039 33,208 26,363 35,000 33,406 23,344 41,104 Coffee 54,000 34,334 48,869 43,000 62,345 40,000 60,575 33,219 71,200 48,599 Cashew 81,600 77,158 92,232 99,107 79,068 74,169 121,070 160,00 121,704 127,939 243 Agricultural Sector for Industrial Development Year/VC 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Fruits 557,400 3,297,910 3,751,170 3,938,730 4,096,280 4,416,690 Vegetables 602,000 766,570 858,740 901,680 937,750 1,005,305 Flowers 8,670 9,100 9,850 10,200 10,790 Spices 6,865 7,150 7,370 8,125 8,377 Figure A29: Tanzania Agricultural research zones and NARS institutes (Central, Eastern, Lake, Northern, Southern, Southern Highlands and Western zone) Figure A30: Tanzania AEZ 244 Agricultural Sector Development Programme II (ASDP-II) Figure A31: Tanzania livelihood zones Figure A32: Map - Food insecure districts (2006-13) 245 Agricultural Sector for Industrial Development Figure A33: Map – Tanzania Cattle Distibution by 2008 246 Agricultural Sector Development Programme II (ASDP-II) ANNEX IX: Selection Criteria for Participating Districts164 Criteria for selecting the targeted districts (within zonal commodities in AEZ165) a. AEZ (see table with primary and secondary value chain) b. Current per cent marketed for targeted CVC c. Per cent in their farming system (% of revenue) d. Food security and nutrition e. Investment absorption capacity over the past five years f. NGO support especially in value chain development g. FO structuring (strength?) Approach. For the purpose of focusing on required services in the upstream and downstream of production, production clusters (grouping three to six districts each) will be established for selected strategic commodities as growth poles within each agro-ecological zone (seven). The cluster approach enhances delivery of essential services, exploitation of economies of scale, development of required infrastructure, bulking of produce, agroprocessing and reduction of transaction costs. A commodity cluster will be a coherent area comprising of three to six districts, where there is already a proven potential for that specific commodity, as well as the presence of value chain actors (e.g., producers, traders, processors and service providers), a MSIP and basic market infrastructure. The project will target maize, rice, oilseeds and strategic commodities import substitution and /or for export to the regional markets. Through a value-chain approach, the programme will support access to and utilization of yield enhancing technologies (improved seeds, fertilizers, mechanization and water for agricultural production) as well as infrastructure and agribusiness services for marketing and value addition. The capacity of private sector actors, including farmers’ organizations and cooperatives, will be strengthened to improve stakeholders’ access to the required inputs, marketing and agroprocessing services. Supporting improved input use in complement to research and advisory services is a cost-effective response for increased productivity and farm income, but also a mean to prevent potential risks from climate change and land degradation. Broader access to adapted varieties and seeds, integrated soil fertility management and timely land preparation will also help farmers to move towards sustainable agriculture and overcome climate risks. Gradual adoption of appropriate mechanization technologies for production and post-harvest operations will not only increase rural labour productivity but also attract young entrepreneurs in the sector. Programme Scope and Focus. The programme will focus in one /or two priority commodities (crop and livestock) per agro-ecological zone. In each zone, potential districts (three to six) will be identified for programme implementation based on the agreed criteria. Proposed selection criteria 1. Agricultural production potential of the target commodities (arable land/arid/semi-arid/, rainfall spell period, etc.) 2. Access to productive and marketing infrastructures (road, railways, electricity, etc.) 3. District historical background of beneficiaries contribution/involvement in development initiatives 4. Availability of private sector supporting value chain of target commodity 5. Production levels of target crops/livestock population by category 6. Other ongoing initiatives (programmes) in the areas to avoid duplication 164 Note summarizing diverse contributions from ARD, Sokoine University of Agriculture, the Ministry of Agriculture —DPP, ASDP Coordination team, etc. 165 Some new developments consider eight and some nine AEZ, especially for crop research activities (adaptations to be done if needed). 247 Agricultural Sector for Industrial Development Figure A34: Maps ASDP II targeted priority districts Attachment 1: Operationalization of AEZ and clustering approach 1. ASDP II focuses on the AEZ and cluster approach. A commodity/district cluster comprises three to six districts with high potential CVC, as well as the presence of value chain actors (e.g., producers, traders, processors and service providers). 2. The DCP/MSIP will be formed to facilitate the operation of clusters under the supervision and coordination of the Region through the Economic and Productive Sectors Section. 3. If a cluster includes districts from more than one region, then the responsible regions will select a front-runner region to supervise and coordinate cluster activities. 4. The role of DCP will be to facilitate the dialogue among major commodity actors (Producers, Traders, Processors, Public and Private Service Providers- PSP) to develop a common strategy, work plan and M&E so as to improve the performance of targeted CVCs. 5. Moreover, DCP will be critical in terms of establishing formal or even ad hoc mechanisms to encourage value chain connectivity between private and public stakeholders and drive innovations/changes towards higher levels of commercialization in targeted priority value chain (or group of complementary CVCs). 248 Agricultural Sector Development Programme II (ASDP-II) ANNEX X: Climate Change and Action166—Agriculture Climate Resilience Plan (ACRP) The Ministry of Agriculture is taking action on climate change in Tanzania. In line with the National Climate Change Strategy (2013), which calls for all climate-sensitive sectors to develop action plans to implement the Strategy’s strategic interventions, The Ministry of Agriculture has prepared the Agriculture Climate Resilience Plan (ACRP) to identify and respond to the most urgent impacts posed by climate variability and climate change to the crop subsector. The ACRP will serve as a roadmap for mainstreaming climate change within current agricultural policies, plans, and practices, as well as identifying gaps were new investments may be needed. It will be the guiding framework for a more comprehensive and consistent approach for confronting one of the major risks to current crop productivity and future investments. Why is climate change a concern for crop agriculture? Agriculture is a dominant sector of the Tanzanian economy, generating 25% of GDP, 24% of exports, and is the mainstay of 75–80% of livelihoods in the country including the majority of the poor. It is a sector of contrasts: despite having a relatively rich base of land and water resources and a favourable climate in many areas for the majority of years, it is hampered by low productivity and persistent poverty. Crop diversity is high, but the majority of households engaged in the sector grow a limited number of food crops for subsistence, and despite the resource endowments these households are vulnerable to food security and economic shocks. Though the Tanzanian economy and in the agriculture sector have experienced economic gains, little has translated to the poor, who still depend on rudimentary technologies and erratic rainfall for their livelihood and food security. These factors influence the impact climate variability and climate change will have on the agriculture sector, as well as the capacity to adapt to current and changing conditions. The strategic direction of the agriculture sector is to modernize through promoting large-scale commercial farms, irrigation expansion, strengthening value chains, and improving linkages with smallholders. Rural poverty reduction, economic growth, and food self-sufficiency are anticipated, but this will add pressure on natural resources that already face high levels of inefficiency and degradation due to agriculture, as well as competing uses. Tanzania’s climate is highly variable and complex, and climate trends already indicate that temperatures are rising and rainfall is becoming more erratic. Recent models show that average annual temperatures will rise by 1ºC by 2050, and changes in rainfall patterns could cause dramatic shifts in agro-ecological zones, increase uncertainty in the onset of the rainy season, and increase the severity of droughts and floods. Other issues such as the emergence of pests and diseases moving into new geographic ranges are already suspected as indirect impacts of changing weather patterns. Weather-related risks are already cost the agriculture sector at least $200 million per year (World Bank, 2013), and without urgent adaptation these costs are likely to increase with rising climate variability. Most agriculture in Tanzania will continue to depend on rainfall in the foreseeable future. Looking ahead, rainfall decreases of 10% have been correlated with a 2% decrease in national GDP, 2 and temperature rise of 2°C could reduce maize yields by 13% and rice by over 7%, 3 both of which are probable in Tanzania over the next century. Climate risks will exacerbate the existing and projected pressures on water resources, soil erosion and health, and land degradation: water shortages and significantly reduced stream flows and water quality changes are already felt in key agricultural investment areas due to low water use efficiency and competing uses, and some climate models show that these are the same areas where rainfall is expected to decrease, yet these areas are slated for investment in water intensive crops such as rice and sugarcane as well as irrigation expansion. As a cross-sectoral issue with far reaching economic, social and environmental implications, climate change planning cannot happen in isolation. At the same time, a robust process must acknowledge more uncertainty, given long term time horizons and limitations of climate and crop models to predict the impacts of temperature rise combined with precipitation changes on crop yields. One way to address these limitations is to adopt a more participatory risk-based approach, as has been done for the ACRP. The ACRP process has involved experts in environment, climate change, land use planning, mechanization, hydrometeorology, soil science, water resource management, pest management, rural development and advocacy, among others, to work collaboratively to develop an action plan and investments that respond to the risks but are tailored to fit the Tanzanian context from the policy level to the farm level. 166 Source Tanzania: Agriculture Climate Resilience Plan 2014–19 (September 2014) 249 Agricultural Sector for Industrial Development How could a changing climate change Tanzania’s agriculture? Three risks emerged from the adaptation planning process, that are key to increase resiliency to climate variability in the short term and given long- term climate change scenarios: 1. First, climate change will amplify the existing pressures on water resources from poor management, degradation and competing uses. Irrigation alone will not be sufficient to adapt to climate change, and can indirectly drive vulnerability if water resources are not well managed. Adaptation measures for improved water, soil and land management are urgently needed to build resilience to current variability and future climate change by both smallholders and commercial farms. 2. Second, yields of key cereal crops are mostly likely to decline due to temperature rise and decreasing water availability, with significant implications for commercial investment, small- scale farmers, and food security. Adaptation measures should focus on boosting productivity of cereal crops, especially building capacity of smallholder farmers to increase yields to the point of “best management practice”, and researching the impact of temperature rise and rainfall variability on key crops. 3. Third, smallholder farmers are among the most vulnerable to even small variations in the climate, with major impacts on livelihoods and food security. Adaptation measures need to consider how to reduce climate shocks to smallholder farmers, promote agricultural practices that boost productivity and safeguard natural resources, and appropriately target vulnerable areas. These messages, reflecting stakeholder inputs, current climate science and analyses of agricultural risks in Tanzania, that were central to informing and prioritizing actions to build resilience to climate impacts. How can agriculture adapt to a changing climate? In order to mitigate the risks, priority actions and investments have been developed, to set the foundation for resilience over the next five years. These were identified as the areas with the highest level of vulnerability to risks, and the biggest payoffs for building resilience. Agricultural stakeholders recommended adaptation options that would help to integrate resilience in agricultural policy decisions, influence planning processes, and implement investments on the ground. 1. Action 1: Improve agricultural water and land management. Priority investments include water use efficiency and water storage, improvements in catchment management in agricultural planning, and adoption of sustainable agricultural land and water management to reduce degradation. 2. Action 2: Accelerate uptake of climate smart agriculture. Priority investments include building an evidence base for climate smart agricultural practices and incentives to offset the cost of adoption, promoting practices at the District level, and generating awareness and capacity for these practices. 3. Action 3: Protect the most vulnerable against climate-related shocks. Priority investments include measures to prepare for and respond to emergencies and weather-related shocks—and better integration of pests and diseases into these measures, building resilience through livelihood diversification activities targeted to the most vulnerable areas, and piloting risk management instruments such as finance instruments. 4. Action 4: Strengthen knowledge and systems to target climate action. Priority investments include filling key research gaps, undertaking a comprehensive climate change and agriculture vulnerability assessment, developing systems for information management and communication campaigns, especially more accurate and timely weather and climate information, and strengthening gender considerations into climate change action for agriculture. 250 Agricultural Sector Development Programme II (ASDP-II) Table A18: Action areas investments and priorities: ACRP (underlined considered as high priority) Priority action & investments Action areas Key investments/actions S/C 1. Improve agricultural land and water management (Sustainable Land and Water Management) Water use efficiency (irrigation efficiency, SRI etc.) 1. Guidelines for including climate change in irrigation expansion/rehabilit. designs 2. Update policies to improve water use efficiency and embed climate change 3. Stocktaking on water lifting, harvesting, storage techno. & use efficiency 4. Environ. assessment integrating water availability & climate change in irrigation plans 5. Promote sustainable use of groundwater for irrigation 6. Support traditional & modern rainwater harvesting 7. Support on farm water storage facilities 8. Promote sustainable irrigation & water use efficiency technologies, 9. Support innovative paddy rice production techniques Sc 1.3 Rainwater harvest & integrated soil & water manage-ment 10. Develop agricultural land/water coordination mechanism 11. Conservation management plans up- & downstream of irrigation schemes 12. Protect water catchment areas for agricultural intensification 13. Develop guidelines, curriculum and capacity building training for WUA 14. Increase uptake of soil & water conservation on irrigated &dry-land Land and catchment manage-ment 15. Develop guidelines on sustainable soil and water management. 16. Build local capacity to plan, implement & monitor Sustainable Land and Water Management 17. Village land management plans to guide sustainable land use 18. District land use planning & monitor of subsistence/commercial farming 19. Increase awareness of sustainable farmland and water management, 20. Promote appropriate agroforestry technologies 21. Promote sustainable farming systems, IK & initiatives under similar AEZ 2. Accelerate uptake of climate smart agriculture: increase yields, safeguard NRM and build resilience to climate change Farming practices conservation agriculture, Soil & water management; Resilient vars.: Cropland; Soil fertility Agroforestry 1. Build the evidence base to promote CSA 2. Develop guidelines and policy briefs for CSA technologies and practices 3. Establish an emissions baseline for the agriculture sector 4. Build district capacity to mainstream CSA in planning 5. Promote CSA in DADPs planning process 6. Establish a monitoring system for CSA interventions, 7. Develop incentives to offset CSA costs for smallholders 8. Increase awareness and train for CSA practice use 9. Demonstrate good CSA practices in the field 3. Protect the most vulnerable against climate/ weather related chocks Climate change risks for agricultural productivity & food security (risk mitigation transfer & coping) 1. Implement the TAFSIP disaster management plan 2. Integration of pests/diseases in monitoring and early warning systems 3. Communication of weather and early warning info to farmers 4. Draw lessons from EWS, DRM, and social safety net projects & scale up 5. Research on building resilience through postharvest value addition 6. Develop program to establish value adding industries for farm products 7. Develop program on risk management for smallholder agriculture 251 Agricultural Sector for Industrial Development Priority action & investments Action areas Key investments/actions S/C 4. Strengthen knowledge & systems to target climate action Evidence for climate smart strategies & communi- cate key messages to target stake- holders 1. Draft and implement a CC and agriculture research programme 2. Develop a framework to target climate adaptation in vulnerable areas 3. Comprehensive assessment on gender and CC in the agriculture 4. Develop/operationalize an MIS & web portal for CC in agriculture 5. Establish stakeholder engagement and communication networks. 6. Develop a gender and agriculture coordination mechanism in the Ministry of Agriculture 7. Raise awareness and disseminate targeted climate/weather info (ICT) Mainstream!! Integrate other ASMLs (livestock, fisheries, environment, Land) into strategy and action plan. Much is already being done to build resilience in the agriculture sector. The ACRP has identified many existing initiatives and investments that consider climate change either directly—however, these are generally small-scale, discrete interventions. The ACRP investments are geared to build on existing activities, significantly scale up successes, and fully mainstream climate change into the Ministry of Agriculture and activities at every level. Table A19: Intervention levels and strategic actions for climate smart interventions Intervention levels Strategic actions Adaptation strategic actions Crop vulnerability/resistance in different AEZ; assess comparative advantage of traditional export crops; promote appropriate irrigation systems; early maturing crops; enhance agro-infrastructural systems; KI, IPM, crop insurance; weather forecast; reduce crop loss & promote value addition; improved soil management Mitigation strategic actions Promote agroforestry, management of agric wastes, minimum tillage and efficient fertilizer use; promote good agricultural practices and conservation agriculture Strategic intervention for water resources for agriculture Protect/conserve water catchments, extraction of underground water, water recycling and reuse, rainwater harvesting Way forward: Strategies for Sustainable Agricultural Intensification ASDP II, promotes the development of farming systems, which are both more productive and more sustainable economic development. Main strategies are: 1. Institutional strengthening (and leadership) to implement the ACRP within ASDP II involving public (ASLM), private and associative stakeholders at national and local levels 2. The Ministry of Agriculture will need to leverage additional funds for building resilience, about an additional USD 25 million investment per year when compared to current losses estimated at USD 200 million. 3. Robust monitoring and evaluation will be key to demonstrating results (mainstreamed systems). 252 Agricultural Sector Development Programme II (ASDP-II) ANNEX XI: Strategic Options for Stimulating Investment in Improved Agricultural Inputs167 Despite more than a decade of subsidies supporting the delivery of agricultural inputs to smallholder farmers, the rates of adoption of improved seed, chemical fertilizer and related agricultural inputs remains relatively low, especially for fertilizer. Except for maize, most farm households still cultivate traditional varieties by hand using a hoe. Furthermore, some livestock inputs (vaccines) are provided free of charge as a public good. The National Agricultural Input Voucher Scheme (NAIVS), has proven that farmers desire to adopt improved technologies and can obtain significant productivity gains: while improving adoption rates for seed and chemical fertilizer, the scheme also contributed to strengthening of private input supply chains. Evidence indicates that some farmers are successfully graduating from subsidized to fully commercial input purchases (two-thrids of seed and one- third of fertilizer beneficiaries). However, while targeting mainly better off producers, farmers still complain that seed and chemical fertilizer are too expensive, in terms of access (initial payment), but also in terms of return (efficiency of use). Inputs to implement new/improved technologies include: (i) crops—seeds, fertilizer, agrochemicals, land preparation/ planting mechanization services; (ii) livestock—pasture seeds, feed, vaccines, veterinary drugs, mechanization for pasture maintenance, hay collection etc. and (iii) fisheries—fingerlings, feed, drugs, improved tools/nets, etc. The objectives of public support need to be clarified to identify best approaches for public supports (public good) to be provided while targeting specific objectives of input use knowledge, availability and farmer access: Specific objectives Priority action Stakeholders 1. Knowledge of new technology for improved productivity - Adaptive research (AE4D) - Extension (public and private) Research/extension (public & private) + Training & ICT 2. Availability: build commercial supply chains for inputs and service - Build professional agrodealer network Linkages between agrodealer, producer/ importers and banks 3. Farmer access to known technologies/inputs and services: - Access to credit - Accumulation of work capital - Farmer seed production? Contract farming Banks; cooperatives/SACCO Revolving 4. Sustainable (profitable) use of improved inputs: - Continued technical (AR4D) - In-/output market development Risk management (assurance?) Improve ability to apply efficiently for generating profitable return from intensification. Generally, farmers face some combination of technical, financial and marketing constraints, and adoption may be viewed as a two-step process of first learning about new technologies and second consistently applying these technologies in a commercial production system. The NAIVS was designed168 to promote the introduction of new seed and chemical fertilizer technologies for maize and rice to 2.5 million maize/rice smallholder farmers that did not yet apply, but who could afford to pay a 50% of the costs of seed and fertilizer. This involved a three-year graduation strategy, assuming that farmers would be knowledgeable but also capable of continuing purchases on their own (ability to reduce risks and to accumulate some capital from increased productivity). Options for future support actions along specific objectives/priorities are: Action 1. Speeding the introduction of new varieties for food security (and nutrition) – Targeted distribution of OPV and/or starter packs. Most of the 3.5 million farm households169 who have not been assisted by the NAIVS, (and even some of those who have been assisted), struggle to produce enough grain and other foods to meet their household food security and nutrition. Any supplementary production derived from improved adapted technologies offers the prospect of major gains in food security and nutrition but also ‘some’ marketing (reducing food aid when production falls short). The most obvious opportunity for assisting these households is to provide rapid access to improved open and self- pollinated improved varieties (OPV): improved seed offers a relatively cheap source of productivity gain. Released varieties need to be multiplied on a significant scale and distributed once for farmer testing, self-multiplication and use, 167 Sources: AFSP implementation documents and discussions (supervisions 2014) 168 The NAIVS was not designed to resolve farmers’ capital constraints nor the broader difficulties of assuring profitability of the commercial market (one of the main issues limiting the output). 169 These households are poor and without possible access to credit, given that most additional production will be consumed rather than marketed, thus not allowing for credit repayment. 253 Agricultural Sector for Industrial Development to generate many years of productivity gain. If rejected, farmers’ feedback would allow for better targeting of breeding programs to resolve farmers’ identified issues. The Ministry of Agriculture ought to: (i) complete an inventory of new open and self-pollinated varieties for all food crops, and (ii) organize a rapid multiplication and dissemination program aiming to assure all farmers in the country obtain access to varieties adapted to their AEZ and the opportunity to achieve sustained gains in productivity; (iii) monitoring effort linked back with national breeding efforts to assure that crop breeders integrate farmers needs and preferences; and (iv) enhance farmer training for seed selection and preservation. New varieties of non-hybrid seed may be provided for free (small starter packs) in order to speed farmer testing and adoption: administrative costs for farmer (partial) payment in most cases are higher than the potential revenue to be generated. Actions could evolve with a shifting set of new varieties each year, starting with a set of key grain varieties and continuing with other available varieties for legume seed, cassava, sweet potato and banana. Action 2. Speeding up the adoption of a wider array of new technologies towards intensive production systems. Farmers learn by seeing (demonstration, etc.) but generally get convinced by doing. The subsidy, in effect, offsets both the costs and the risks (including weather/climatic, sustainability) facing each individual farmer in trying a new technology. Three years of assistance in NAIVS helped farmers better understand the level of investment returns possible, and allow then to build a small capital base for investing on their own: the economic return for government investment in subsidies was very high. Furthermore, the multiyear support encouraged private commercial investment in building supply chains for the delivery of seed and fertilizer through a growing number of regional wholesalers and village retailers. The same logic may apply to many cropping technologies, such as mechanized soil preparation/planting, manure application, weed control, water harvesting, IPM etc. A subsidy could offset the risks underlying the investment and convince farmers about the investment return. This approach tries to solve knowledge and access constraints for farmers’ use of improved technologies/inputs: electronic vouchers would allow for improved targeting, gradual decrease of voucher value and improved scheme governance (M&E). Action 3. Sustaining the adoption of improved technology with credit and market support. Farmers are convinced of the value of a new technology, but experience difficulty obtaining the cash necessary to make the investment. Farmers’ perceptions of high input costs also reflect the high ratio of input to product prices. Possible support actions are: a) Reduced credit interest: subsidies on interest rates of commercial credit, further backed by loan guarantees, may be justified temporary until a critical mass of investment is achieved to assure sustained competitiveness or as income support for poor rural households (but credit for food insecure producers should be avoided). b. A loan guarantee to reduce risk estimated by banks for agricultural loans by commonly preferred strategies such as: (i) contract farming (mainly cash crop like tobacco, cotton, coffee or tea); (ii) group lending with collective liability (a significant level of selling of commodities is needed to allow for sustainable guarantee systems); and (iii) credit guarantee line. c. Bulk supply of inputs and services by apex farmer organizations, private sector, etc., to reduce transaction costs an input prices Agricultural Sector Development Programme II (ASDP-II) 254 ANNEX XII: ASDP II Management, Coordination and Communication Structure: Composition and Process from Village to National Level170 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Village Village Agricultural Extension Officer (VAEO) Supervise, Implement & prepare village report, planning, budgeting & monitor agricultural activities in the village Village project committee [10 members] None None Ward Ward Agricultural Extension Officers (WAEO) Supervise, Implement, Planning, Budgeting & Compile village reports, monitor agricultural activities in the ward None None None Ward Ward Executive Officer (WEO) Compile village reports8, Engage DAS as far as Developmental projects are concerned Ward Development Committee (WDC) • Chair: Voted Councilor • Ward Executive Officer • Councilors • Extension Officers • Village Chairpersons • Village Executive Officers • Scrutinize village development plans, progress reports. • Compile and forward village development plans, progress reports and by laws to District Council • Monitor Ward development programs Division Division Officer Supervise, Compile ward reports & monitor agricultural activities None None None 170 Not all Wards have WAEO in all sub sector specializations i.e. Crops, Livestock, Fisheries. DAICO-District Agricultural and Irrigation and Cooperative Officer DPLO-District Planning Office DCO-District Cooperative Officer DTO-District Trade officer DLFO-District Livestock and Fisheries Officer Agricultural Sector Development Programme II (ASDP-II) 255 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Districts District Agricultural, Irrigation and Cooperatives(DAICO), District Livestock and Fisheries Offices(DLFO) Compilation and Preparation of District Agricultural Development Plans(DADPs) and Budgets; Monitoring and Evaluation Reports, Advisory role on matters related to Agricultural activities District facilitation Team District Agricultural Working Groups Chair: DAICO/DLFO DLO(Land) DTO(Trade) DPLO District Private Sector Representative in agriculture DCOs District NGOs Representatives in Agriculture (+ other members of the environmental and conservation group) (CSA) • Compile, scrutinize, harmonize and coordinate plans and budgets, • Initiate, mobilize and support village and ward level planning, monitor performance and provide advisee to District Councils • Supporting land use planning and registration, • Oversee local authority agricultural activities District ASDP II/DADP Focal Person -Report to DAICO/ DLFO -Coordinate ASDP II Activities at District level None None None Districts Municipal/Town/District Executive Director Supervise development activities and reports to Municipal/Town District/ Council Council Management Team (CMT) District Consultative Committee (Regional Administration Act No.19 of 1997) Full Council (DC) • Chair: District Commissioner • DED • Heads of District Departments • Chair: Chairperson of the Council • Members as per Act 1982 • Scrutinize, compile reports and provide Advisory role to the District Council • Approval of development plans, budgets, performance reports and by-laws. Agenda to include district natural resource issues Region Assistant Administrative Secretary Economic & Productive Sector Provide Technical Backstopping to LGAs and Compile from LGAs & submit to Regional planning officer who will submit to RAS None None None Region Regional Planning Officer Compile all District Plans and Budgets for onwards submission to the Management Meeting Regional Management Meeting • Chair: Regional Commissioner(RC) • AASs (8 members) • Heads of Units • Members as per Act. Number 19 of 1997 • Review all regional plans and budget Agricultural Sector Development Programme II (ASDP-II) 256 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Region Regional Administrative Secretary (RAS) Secretary to Regional Consultative Committee (RCC), provide policy guidelines and Oversee districts (Regional) development activities Regional Consultative Committee (RCC) • Chair: Regional Administrative Secretary (RAS) • Members as per restructuring of Regional Administrative (June 2011) • Advisory role to the districts. • Monitor of district activities Agenda to include regional natural resource issues PO-RALG PO-RALG -Agricultural Sector Coordination Plan, Compile, Analyze, Coordinate, Monitor and evaluate all Regional & Ministerial Agricultural Plans and budgets (ASDP II) - and submits to ASLMs- DPP’s office Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). • Chair- Minister - PO-RALG) • RC, RAS, DED, DPP- ASLMs , DAICOs, Private Sector, Development Partners working in LGAs, NGOs/CBOs and other key stakeholders in respective Regions and LGAs • Advisory role to the PO-RALG, Regions, and LGAs • Consultations among stakeholders operating in the regions and LGAs Lead Agency Lead Agency-ASDP II Component Coordination Compile, Analyze, Coordinate, Monitor and Evaluate Implementation of ASDP II Prepare and Review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination Thematic Working Groups(TWG) Meeting • Chair: TWG Chair Appointed by Head of Lead Agency • Technical Experts in the area appointed by the Lead Agency to participate in the thematic Groups • Coopted Members for cross cutting and emerging issues • Discuss, Plan, Compile, Analyze, Coordinate, Monitor and Evaluate Implementation of ASDP II • Prepare and Review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination • Advice TDC on important issues related to ASDP II implementation Lead Agency Lead Agency-ASDP II Component Coordination Plan, Compile, Analyze Coordinate, Monitor and evaluate ASDP II component plans and budgets (ASDP II) - and submits to ASDP II National Coordination Unit (NCU) Lead Agency Component Technical Committee • Chair: Head Lead Agency • Chairperson(s) of the Thematic Working Group (TWG) • Chair/Representative from the M & E TWG • Chair/Representative form the Planning and Budgeting TWG • Representative from NCU • Review submitted component plans, budgets; review and analyze reports; • Coordinate, monitor and evaluate ASDP II component plans and budgets • Submits to ASDP II National Coordination Unit(NCU) Agricultural Sector Development Programme II (ASDP-II) 257 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National ASDP II Secretariat/ ASDP II National Coordination Unit (NCU) Plan, Manage, Monitor, evaluate, harmonize and coordinate ASDP II. NCU compiles all interventions/ Project Plans and Budgets under ASDP II and develop draft consolidated annual work plans and budgets; Compile, analyze, coordinate, provide program logistical support; joint monitor, and evaluate of the program for onward submission to the Technical Committee of Directors (TCD) Technical Committee of Directors(TCD)9 • Chair: PS-MoA-Agriculture • Directors of ASLMS • PO-RALG ASDP II Coordination • Head of NIC • Head of Cooperatives, • Head Warehousing Licensing Board • NBS • Ministry of Finance and Planning • Ministry of Lands and Human Settlement • Tanzania Food and Nutrition Council • Ministry Energy • Ministry of Transport • Ministry of Education • Representative of Agricultural Research/Training Institutions • National Coordination Unit (NCU) Secretariat • Review, scrutinize and harmonize individual lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports • Recommend to ASC governance and management guidelines and procedures for implementation of ASDP II • Recommend to ASC ToR for Joint Annual Reviews/Sector reviews/ Public Expenditure reviews (JSR/ASR/PER) Monitoring and Evaluation • Prepare and review papers for presentation to the ASCG and ASC • Review and propose to ASC policy and regulatory changes for the sector • Provide advisory and coordination role to the ASDP II thematic working groups. • Advice NCU on governance, management, coordination and operational issues Agricultural Sector Development Programme II (ASDP-II) 258 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National PS-MoA Plan, Manage, Monitor, evaluate, harmonize and coordinate ASDP II activities and organizes the TCD Agricultural Sector Consultative Group Meeting (ASCG) • Chair: Minister MoA • All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/Donors and NGOs/ NSA) (local and International) • Training and Research Institutions • DPP- MoA Secretariat • NCU- Recorder • Provide advice on sector issues • Provide support (financial, material and others) to the sector • Participate in Joint Planning and Budgeting Meetings • Advise on sector policies, • plan, budgets, public and agricultural expenditure review National Minister, Ministry of Agriculture (MoA) Agricultural Sector Steering Committee (ASC) • Chair: Minister MoA • Permanent Secretaries of ASLMs • Representatives of Development Partners (AWG- Chairs) (2 members) • Representatives of Private Sector (3 member) • Representatives of NGOs/ NSAs (3 members) • DPPs –ASLMs (Crops and Livestock • NCU-Secretariat • Review and approves ASDP II plans, budgets, monitoring and evaluation reports; • Approve ToR for Joint Annual Reviews/Sector reviews/Public Expenditure reviews(JSR/ ASR/PER) and Monitoring and Evaluation • Facilitate and approve establishment of ASDP II funding mechanisms; • Discuss issues of mutual concern and information sharing; • Review and approve ASDP II financial and audit reports, • Approve changes in policies and regulations for on ward submission to parliament • Recommend the National • Agricultural Stakeholder Meeting (NASSM) meeting calendar and agenda Agricultural Sector Development Programme II (ASDP-II) 259 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National PMO Oversee the performance of the sector by providing directives and advice on the transformation of the agricultural sector • National Agricultural Stakeholder Meeting (NASSM) • Chair: Prime Minister (PM) • ASLM Ministers, • PSs of ASLMs • All Development Partners supporting and involved in agriculture • All Private Sector supporting and participating in agriculture • NGOs/NSAs working in agriculture • DPPs ASLMs Secretariat • NCU- Recorder • Provide policy advice and guidelines to the agricultural transformational agenda • Provide advice and guidelines for the implementation of ASDP II • Facilitate and provide support where needed. Note on Technical Committee of Directors171 171 Respective Directors of Lead Agency /Component Leaders for specific ASDP II Components will be in attendance 260 Agricultural Sector Development Programme II (ASDP-II) ANNEX XIII: Principles for responsible Investment in Agriculture (FAO, August 2014) Principle 1: Contribute to food security and nutrition Principle 2: Contribute to sustainable and inclusive economic development and the eradication of poverty Principle 3: Foster gender equality and women’s empowerment Principle 4: Engage and empower youth by access to productive resources, services, education and innovation Principle 5: Respect tenure of land, fisheries, and forests and access to water Principle 6: Conserve and sustainably manage natural resources, increase resilience and reduce disaster risks Principle 7: Respect cultural heritage and traditional knowledge, and support diversity and innovation Principle 8: Promote safe and healthy agriculture and food systems Principle 9: Incorporate inclusive and transparent governance structures, processes and grievance mechanisms Principle 10: Assess and address impacts and promote accountability ANNEX XIV: Key Reference Documents 1-1 ASDS 2001 01-2 ASDS-2 Revised draft 2014 October 01-3 ASDS-2 Review of Implementation Indicators – Version 24 August 2013 (ESRF) 02-1 ASDP II Programme Document 02-2 ASDP-1 M&E_Framework_Revised_March 2011 03 TAFSIP Final version 2012 04 CAADP COMPACT Final 07 07 2010 05-1 National Agricultural Policy 2013 05-2 Livestock-Policy 2006 05-3 Agricultural Marketing Policy 2008 06-1 ASDP-1 Irrigation impact assessment 06-2 ASDP-1 Extension impact assessment 06-3 ASDP-1 Local Infrastructure impact assessment_ July 2014 06-4 ASDP-1 Final Report (Agricultural Support Service) TEAGASC Review Group 13-02-11 06-5 Final Environmental and Social Audit Report 2014 December 06-6 ASDP EVALUATION Final Report June 2011 06-7 ICR ASDP Draft Final July 2014 07-1 Agricultural BRN - Executive Summary 07-2 Agricultural BRN 2013 (6 June) Agric Lab (detailed report) 07-3 Agricultural BRN - PDB - Stakeholder engagement meeting 08-0 ASR-PER-2014_TZ-Mainland_v0 Annex1 08-1 ASR-PER 2011-12 Final Submitted 08-2 ASR-PER 2010-11 Final Report Edited and Submitted March 2011 (2) 09-0 RBA Agriculture 2014 Background Note 09-1 RBA Agriculture 2013 Background Note -Near Final Draft (2) 2013-11-05 09-2 RBA Agriculture 2012 Agriculture RBA2012_9 Jan2012 10-1 Tanzania Development Vision 2025 10-2 MKUKUTA_II_01 10-3 LTPP_2012-03-19_PRINT 10-4 5-Year Plan Draft (June 2011) 11-1 MAFAP Preliminary_Analysis_of_Public_Expenditures_in_Tanzania_Jan 2013 12-0 PHC-2012 National Socio-Economic Profile_ 26 APRIL 2014 12-1 PHC-2012 Census General Report - 29 March 2013_Combined_Final for Printing 13-1 NSCA v2 Final Crops National Report 11 June 2012 14-1 DGP-Macroeconomic data 15 ASDP Basket Fund 2 preparation 2013 June PD Draft 25 Jun-2013 Draft final - Main text PD Draft 25 Jun-2013 Draft final – Annexes 16 ASDP Basket Fund 2 preparation 2013 August revised ASDP II-BF version 5.2 Comments ASWG- 31-07 2013 response to comments 261 Agricultural Sector for Industrial Development Master 4 Annex ASDP II-BF-BRN 17 TZ Mainland ASDP IIworkshop report 2013 September 18 Bank of Tanzania report MER Monthly Economic Review October 2014 [1] QEB Quarterly Economic Bulletin June 2014 [1] 19 National Sample Census of Agriculture. 2007–2008 (from National Bureau of Statistics) 13-1 NSCA Final Crops National Report 11 JUNE 2012 Table 2.1.4 Types of Ag HH by types and size 1 Table 2.1.8 Types of Ag HH by types and size 2 Table 5.8 Crop production (short & long rainy season) by regions Table 5.11 Crop production by household Table 5.14 Crop production (yield in t/ha) 20 PER_NAIVS_ National Ag. Input Voucher System (NAIVS) Tanzania_Final_Report-March_2014Feb 21 Tanzania_NAIVS Agricultural PER 2013_4 22 2011-12 HBS Main Report (Household Budget Survey) 23-1 General Report on Donor Funded Projects 2011-12 23-2 General Report on Donor Funded Projects 2010-11 24-1 Donor Mapping List (AWG) 24-2 Donor Mapping List (TAN-AIM) 262 Agricultural Sector Development Programme II (ASDP-II) | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA AGRICULTURAL SECTOR DEVELOPMENT PROGRAMME PHASE II (ASDP II) November, 2017 “SEKTA YA KILIMO KWA MAENDELEO YA VIWANDA” “AGRICULTURAL SECTOR FOR INDUSTRIAL DEVELOPMENT” i Agricultural Sector for Industrial Development FOREWORD Agricultural sector development is very crucial in the growth of the national economy and development of industrial sector. Agricultural development is equally important for the provision of adequate food and guarantees nutrition security to the Tanzania population. Currently, the agricultural sector contributes about 29.1 % of the GDP 65.5% of employment, 65% of raw materials to the industrial sector and 30% of export earnings. The Agricultural Sector Development Programme phase two (ASDPII) has been developed to propel the country’s economic development and guide the implementation of prioritized interventions for the Tanzania Development Vision 2025 (TDV 2025). Long Term Perspective Plan (LTPP 2012-2021);’ Five Year Development Plan. phase two (FYDP 11 2011- 2021), Tanzania Agriculture and Food Security Investment Plan (TAFSIP) and the Agricultural Sector Development Strategy Phase Il (ASDS Il). The duration of (ASDP Il) is ten years starting from the year 2017/18 to 2027/28. The programme is to be implemented into two stages of five years each, the first starting from the year 2017/18. The main objective of ASDP Il is to transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and increase smallholder farmer income for improved livelihood and guarantee food and nutrition security. The Programme has four major components which are; (i) Sustainable Water and Land Use Management which aims at expanding sustainable water and land use management for crops, livestock and fisheries; (ii) Enhanced Agricultural Productivity and Profitability which will focus on increasing productivity, for some priority commodities; (iii) Commercialization and Value Addition which will focus on improved and expanded marketing, value addition promoted by a thriving competitive private sector and effective farmer organizations; and (iv) Sector Enablers, Coordination and Monitoring & Evaluation which will strengthen institutions, create enabling conditions and provide coordination framework. The expected benefit from the ASDP Il include (i) increased and sustainable productivity, production of food and non-food agricultural commodities to improve Tanzanians livelihoods, ensuring national level food security, and provide raw materials for the industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural agricultural sector by generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to increase resilience and adapt to climate change; (v) improved institutional capacity to mobilize and manage resources in support of agricultural sector development; (vi) improving the system of disaster risk management by exploring the use of innovative risk management tools; (vii) reduced gender related imbalances; (viii) rsduced child labour in the agricultural sector by promoting decent work and (ix) reduce the of agriculture to the environment and take into account climate change through promotion of Climate Smart Agriculture (CSA). In this respect, it gives me great pleasure to present the Second Phase of the Agricultural Sector Development Programme (ASDP Il) to all stakeholders. The Programme implementation will involve all stakeholders from public, private, development partners, financial institutions and non- state actors. ii Agricultural Sector Development Programme II (ASDP-II) I would like to urge all stakeholders in the sector to pull together our collective strength to make sure thät this agricultural transformation agenda which, without doubt will contribute significantly to the country’s development targets becomes a reality. It is necessary therefore that these initiatives and interventions are shared and supported by all stakeholders and each one of us in our different capacities. I thank you in advance for your cooperation and participation Hon. Dr. Charles Tizeba (MP), MINISTER FOR AGRICULTURE iii Agricultural Sector for Industrial Development Contents FOREWORD ........................................................................................................................................ i EXECUTIVE SUMMARY .................................................................................................................. 1 I. BACKGROUND....................................................................................................................7 A. Macroeconomic Indicators and Agriculture...............................................................................7 B. The Agriculture Sector.............................................................................................................8 C. Policy Environment............................................................................................................... 11 II. SECTOR PROGRAMMES, PROJECTS AND PUBLIC EXPENDITURE..........................14 A. Agriculture Sector Development Programme (ASDP phase 1)...................................................14 B. Other Related Agricultural Sector Initiatives............................................................................15 C. Agriculture Sector Review-Public Expenditure Review (ASR-PER)..........................................17 III. ASDP II-DESIGN PROCESS AND PRINCIPLES.............................................................22 A. Lessons Learned from ASDP-1..............................................................................................22 B. Key Agricultural System Challenges and Potential Drivers........................................................25 C. The Process Towards ASDP II................................................................................................27 D. Key Design Principles for ASDP II.........................................................................................30 E. Scope, Focus and Phasing of the Programme...........................................................................32 F. Priority setting and Focusing...................................................................................................36 G. Approaches and principles for the ASDP II design....................................................................37 H. The Theory of Change...........................................................................................................39 IV. PROGRAMME OBJECTIVE AND DESCRIPTION..........................................................40 A. Programme Objective............................................................................................................41 B. Priority Investment Areas (summary)......................................................................................45 C. Component 1: Sustainable Water & Land Use Management (crops, livestock and fisheries).........47 D. Component 2: Enhanced Agricultural Productivity and Profitability...........................................59 E. Component 3: Commercialization and Value Addition (building competitive commodity value chains).............................................................................86 F. Component 4: Strengthening Sector Enablers and Coordination...............................................104 V. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT.......................127 A. Overall Programme Cost......................................................................................................127 B. Financing Plan....................................................................................................................133 C. Financing Arrangements......................................................................................................134 VI. INSTITUTIONAL AND IMPLEMENTATION ARRANGEMENTS................................137 A. Implementation of ASDP II at National Level........................................................................137 B. Regional level.....................................................................................................................138 iv Agricultural Sector Development Programme II (ASDP-II) C. Local Level........................................................................................................................138 D. Coordination mechanisms and processes...............................................................................138 E. Management Information System and monitoring...................................................................140 F. Safeguard Aspects—Social and Environmental management...................................................141 VII. BENEFITS AND ECONOMIC AND FINANCIAL ANALYSIS (EFA).............................142 A. Summary of benefits............................................................................................................142 B. Economic and Financial Analysis.........................................................................................144 C. Economic Benefits..............................................................................................................147 D. Operation and maintence costs.............................................................................................147 E. Economic Viability and Sensitivity Analysis..........................................................................147 F. Programme Sustainability.....................................................................................................148 VIII. IMPLEMENTATION MODALITIES AND RISKS.......................................................149 A. Implementing agency and stakeholder assessment..................................................................149 B. Risks..................................................................................................................................150 ANNEX I: ASDP II Components Implementation Plan, Sequencing and Scheduling.............................152 ANNEX II: ASDP II: Results Framework and Monitoring (On-progress).............................................166 ANNEX III: Details of Coordination Mechanisms................................................................................192 APPENDIX IV: Program and Project budget Requirements................................................................203 ANNEX V Monitoring & Evaluation and Statistics...............................................................................213 ANNEX VI: Financial and Economic Analysis......................................................................................229 ANNEX VII: Risks assessment and Mitigation Strategies/Measures......................................................237 ANNEX VIII: Key Maps and Figures Figure........................................................................................240 ANNEX IX: Selection Criteria for Participating Districts.....................................................................246 ANNEX X: Climate Change and Action—Agriculture Climate Resilience Plan (ACRP).......................248 ANNEX XI: Strategic Options for Stimulating Investment in Improved Agricultural Inputs.................252 ANNEX XII: ASDP II Management, Coordination and Communication Structure: Composition and Process from Village to National Level..................................................................................................254 ANNEX XIII: Principles for responsible Investment in Agriculture (FAO, August 2014).......................260 ANNEX XIV: Key Reference Documents..............................................................................................260 v Agricultural Sector for Industrial Development List of Tables Table 1: MAFC and MLFD central level recurrent expenditure (TSh million)..................................... 19 Table 2: Routine expenditure on agriculture and as a proportion of agriculture GDP........................... 19 Table 3: Technology enhancing expenditure in MAFC (TSh million)................................................... 20 Table 4: Revenue collection and budget execution rates........................................................................ 21 Table 5: Key constraints and thematic drivers........................................................................................ 25 Table 6: Commodities coverage, agricultural production, trade and diet (2005–2010)......................... 33 Table 7: Priority commodities in the AEZs & potential commodities phasing by region...................... 34 Table 8: Priority Commodity Value Chains in Agro-Ecological Zones/ clusters................................... 35 Table 9: ASDS-2 Strategic Result Areas & mapping of proposed priority programme areas................ 37 Table 10: Typology of rural households active in the agricultural sector against holding size.............. 44 Table 11: ASDP II components and strategic objectives........................................................................ 45 Table 12:Agro-ecological zones and districts to be involved in ASDP II.............................................. 46 Table 13: ASDP II Component 1: Related ASDS-II specific objectives and outcomes......................... 48 Table 14: Priority activities in land use planning for crop and livestock development.......................... 50 Table 15: Summary of BRN and remaining ASDP-1 prioritized irrigation schemes (2015/2020)........ 54 Table 16: Priority actions for improved water management in rainfed agriculture................................ 55 Table 17: Priority activities livestock/fish access to water resources..................................................... 55 Table 18: ASDP II investment and action areas for improved resilience of farming systems................ 58 Table 19: Five Years Development budget/investment estimates for component 1 –at constant 2016 ..... Prices (TSh million)............................................................................................................... 58 Table 20: ASDP II Component 2: related ASDS-2 specific objectives and outcomes........................... 60 Table 21: Objectives for priority action in livestock and fish productivity development (10 years)..... 61 Table 22: Priority activities livestock extension..................................................................................... 68 Table 23: Priority intervention in fisheries extension............................................................................. 68 Table 24: Priority activities & investment areas in livestock and fisheries training............................... 69 Table 25: Priority activities livestock/fisheries access to inputs............................................................. 74 Table 26: Crop and livestock research institutes in AEZ........................................................................ 76 Table 27: Livestock and fisheries priority investment and action areas for research............................. 77 Table 28: Proposed action areas for food security and nutrition............................................................ 83 Table 29: Development budget/investment projection for component 2 (TSh million)......................... 85 Table 30: ASDP II Component 3: related specific ASDS-2 objectives and outcomes........................... 88 Table 31: Objectives for priority CVC and strategies to achieve expected results................................. 89 Table 32: Summary of action areas and activities in market enhancement at national/regional level... 93 Table 33:Priority activities livestock and fisheries quality control and safety assurance....................... 94 Table 34: Priority activities for CVC value addition and agroprocessing.............................................. 95 Table 35: Priority actions towards reduction of post-harvest losses....................................................... 97 Table 36: Proposed strategic action areas for agroprocessing and value addition.................................. 98 Table 37: Proposed strategic action areas for agroprocessing and value addition (livestock/fisheries).98 vi Agricultural Sector Development Programme II (ASDP-II) Table 38:Action areas and activities to improve rural/agricultural investments (draft)....................... 102 Table 39: Development budget/investment estimation for Component 3 (TSh million)......................103 Table 40: ASDP II Component 4: related specific ASDS-2 objectives and outcomes..........................104 Table 41: Key policy areas and related actions for agricultural sector growth (ASLM)......................105 Table 42: Farmer organizations, by category........................................................................................107 Table 43: Action areas for farmer empowerment and organization strengthening ..............................109 Table 44: Proposed ASDP II interventions into cooperative activities and operations.........................111 Table 45: ASDP II National Level coordination organs, mechanisms, and membership (summary)...112 Table 46: ASDP II PO-RALG Level coordination organs, mechanisms, and membership (summary).............................................................................................................................113 Table 47: Proposed interventions for CKM and ICT promotion..........................................................122 Table 48: Action areas and activities to improve rural/agricultural investments..................................125 Table 49: Five Years Development budget / investment projection for component 4 (TSh million)...126 Table 50: ASDP II Component Budget Requirements and Percentages for the first five years...........128. Table 51: Overall development budget for ASDP II.............................................................................128 Table 52: Proportions of the development budget expected to be financed by different funding sources...................................................................................................................................133 Table 53: Illustrative financing plan for ASDP-2 (summary of total costs in TSh million).................134 Table 54: Summary of ASDP II Sector National Coordination Organs, Membership and . Frequency of Meetings.......................................................................................................137 Table 55: Summary of ASDP II Sector at PO-RALG, Regional Secretariat, Local Government Authorities Coordination Organs, Membership and Frequency of Meetings....139 Table 56: Financial Crop Gross Margins in Present, Future Without and Future with Project............145 Table 57: Financial Livestock Gross Margins in Present, Future-without and Future-with project.....146 Table 58: Net Farm Incomes in Present, Future-without and Future-with project...............................146 Table 59: Economic viability and sensitivity analysis..........................................................................148 List of Figures Figure 1: GDP growth rate by sector (%, at 2007 constant prices).......................................................... 7 Figure 2. Agriculture share of GDP (%), 2001 prices............................................................................... 8 Figure 3: GDP by economic activity (at current prices—TSh billion)..................................................... 9 Figure 4: Percentage GDP by economic activity (in % of total GDP—at current TSh prices)................ 9 Figure 5: Main crop production in Tanzania (1961–2013, in tons)........................................................ 10 Figure 6: Evolution of average crop yields for main crops in Tanzania (1961–2013, in kg/ha)............ 10 Figure 7. Long & medium-term policy framework for the transformation of the agriculture sector..... 12 Figure 8. MAFC and MLFD Central-Level Recurrent Expenditure...................................................... 18 Figure 9. Recurrent Agricultural Expenditure as Proportion of Total Recurrent Expenditure............... 20 Figure 10. Agriculture Development Expenditure by Project – Foreign and Local............................... 22 Figure 11: Tanzania landscape for agricultural development (2015–2024)........................................... 28 vii Agricultural Sector for Industrial Development Figure 12: ASDP-II design and formulation framework........................................................................ 29 Figure 13: ASDP-II financing modalities............................................................................................... 29 Figure 14: Transformative Approach-Theory of Change....................................................................... 40 Figure 15: Framework for ASDP II results chain................................................................................... 41 Figure 16: ASDP II Objective, Strategy and Outcome........................................................................... 41 Figure 17: ASDP II Programme Objective and Components................................................................. 42 Figure 18: ASDP II Priority Investment Areas....................................................................................... 43 Figure 19: ASDP II components and sub-components........................................................................... 45 Figure 20: Value chain approach of ASDP II.......................................................................................... 87 Figure 21: ASDP M&E system for sector and programme performance (adapted for ASDP II)..........116 Figure 22: Flow of funds in ASDP II.................................................................................................... 135 Figure 23: ASDP II ProgrammeDecision Making Organs................................................................... 192 Figure A24: ASDP M&E system for sector and project performance (adapted for ASDP II)............. 216 Figure A25: Agriculture Routine Data System..................................................................................... 217 Figure A26: Development Partners’Contribution by Focus Area and Value Chains in Crop Sub-Sector........................................................................................................................ 226 Figure A27: Development Partners’Contribution by Focus Area and Value Chains in Livestock and ..... Fisheries Sub-Sector......................................................................................................... 227 Figure A28: Agro-ecological Zones...................................................................................................... 240 Figure A29: Tanzania Agricultural research zones and NARS institutes (Central, Eastern, Lake, Northern, Southern, Southern Highlands and Western zone)........................................... 243 Figure A30: Tanzania AEZ................................................................................................................... 243 Figure A31: Tanzania livelihood zones................................................................................................ 244 Figure A32: Map - Food insecure districts (2006-13).......................................................................... 244 Figure A33: Map – Tanzania Cattle Distibution by 2008..................................................................... 245 Figure A34: Maps ASDP II targeted priority districts.......................................................................... 247 List of Boxes Box 1: Key Principles of the ASDP II Design........................................................................................ 30 Box 2: Basic elements for better land husbandry—Integrated soil fertility management...................... 51 Box 3: The agenda for sustainable agricultural intensification and resilience....................................... 57 Box 4: Strengthening efficient extension (MAFC Workshop - January 2015)....................................... 63 Box 5: Technical training institutions..................................................................................................... 67 Box 6: Key issues in policy and institutional reform and support (updated from TAFSIP)................. 105 Box 7: Inclusion of off-budget projects.................................................................................................114 viii Agricultural Sector Development Programme II (ASDP-II) Acronyms AASS Annual Agricultural Sample Survey AEZ Agro-ecological zone AfDB African Development Bank AR4D ARDS ASA ASDP Agricultural research for development Agricultural Routine Data System Agricultural Seed Agency Agricultural Sector Development Programme (first and second phases) ASDS ASLMs ASR Agricultural Sector Development Strategy (first and second phase) Agriculture sector lead ministries Agriculture Sector Review ASSP Agricultural Statistics Strategic Plan ATI Agricultural training institute BRN Big Results Now CAADP Comprehensive Africa Agriculture Development Programme CKM Communication and knowledge management CVC Commodity value chain DADG DADP District Agriculture Development Grant District Agricultural Development Plan DAICO District Agricultural, Irrigation and Cooperative Officer DCP DED District CVC platform District Executive Director DLFO District Livestock and Fisheries Officer EAAPP East Africa Agricultural Productivity Project FAO Food and Agriculture Organization of the United Nations FFS Farmers field school FTC Farmer Training Centre ICT Information and Communication Technologies IFAD IPM International Fund for Agricultural Development Integrated Pest Management JICA Japan International Cooperation Agency JSR Joint Sector Review LGAs Local government authorities LITA Livestock Training Agency LITI Livestock Training Institute M&E Monitoring and evaluation MAFC Ministry of Agriculture Food Security and Cooperatives MIVARF Marketing Infrastructure Value Addition and Rural Finance MLFD Ministry of Livestock and Fisheries Development NAIVS National Agricultural Input Voucher Scheme NASSM National Agricultural Sector Stakeholders Meeting ix Agricultural Sector for Industrial Development NCU National Coordination Unit NEPAD New Partnership for Africa’s Development NSCA National Sample Census of Agriculture and Livestock PER Public Expenditure Review PMO- RALG Prime Minister’s Office- Regional Administration and Local Government PO- RALG President’s Office - Regional Administration and Local Government PPP Public Private Partnership PSP Private Service Providers RAS Regional Administrative Secretariat SACCOS Savings and Credit Cooperative Society SADC Southern Africa Development Community SAGCOT Southern Agriculture Growth Corridor of Tanzania SWAp Sector Wide Approach TAFSIP Tanzania Agriculture and Food Security Investment Plan TALIRI Tanzania Livestock Research Institute TARI Tanzania Agricultural Research Institute TCD Technical Committee of Directors TOSCI Tanzania Official Seed Certification Institute TTPU Technology Transfer and Partnership Units USAID United States Agency for International Development VAEO Village Agricultural Extension Officer WAEO Ward Agricultural Extension Officer WARC Ward Agricultural Resource Centre 1 Agricultural Sector for Industrial Development EXECUTIVE SUMMARY INTRODUCTION The government of Tanzania has finalized the formulation of Agriculture Sector Development Programme II (ASDP II). This is a ten-years programme that will be implemented in two (2) phases each divided into five-year implementation period. The First Phase will start in 2017/2018 – 2022/2023. The program is a follow up to the ASDP I implemented from 2006/2007 to 2013/2014. ASDP II has been designed based on the lessons learnt during the ASDP I implementation. The program aims at transforming the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food and nutrition security and contribution to the GDP. The program strategy is to transform gradually subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development. Preparation of the program has gone through a comprehensive consultative and stakeholder engagement at all levels. This document is a result of the views, comments and wishes of the various stakeholders including private sector, development partners, farmer organizations and non-governmental organizations and the public sector. The document is presented in eight sections: (i) the background; (ii) sector programmes, projects and public expenditure; (iii) ASDP II design process and principles; (iv) program objectives and description;(v) program costs, financing and financial management; (vi) institutional and implementation arrangements; (vii) benefits and economic and financial analysis (EFA) and (viii) Implementation Modalities and Risks. Below are the key highlights of the program. A. MACROECONOMIC INDICATORS AND CONTRIBUTION OF THE AGRICULTURAL SECTOR TO THE ECONOMY 1. Tanzania’s macroeconomic indicators showed robust growth in Gross Domestic Product (GDP) before and during implementation of the first phase of the Agricultural Sector Development Programme (ASDP I) which started in 2006. In recent years, Tanzania has maintained relatively stable, high growth over the last decade (averaging 6%–7% per annum). The GDP growth rate was 7% in 20161. The agriculture sector growth, except for 2008, is still far below GDP growth. The average growth rate for the agriculture sector during the period 2006–2014 was 3.9% per annum, and it decreased to 2.9% in 2015 and then increased to 3.0% in 20162 2. Agriculture contributes significantly to the socio-economic growth of Tanzania. Smallholder farmers (including livestock and fishery) dominate production, with more than 90% of cultivated land. The sector provides about 77.5 % of employment; provides livelihood to more than 70 % of population, 29% of GDP; 30% of exports and 65% of inputs to the industrial sector (URT 2014). However, in 2016/17, the sector contributed 29.1% of the country’s GDP (this is high as compared to 23% in 2014 (FYDP 2015/16), 65.5% of employment (NBS 2017) and food self-sufficient level decreased to 123% compared to 125% (2014/15). This shortfall could be contributed by scarcity of rainfall among other reasons. B. ASDP I KEY ACHIEVEMENTS ASDP was launched in 2006 to provide a sector-wide investment vehicle to deliver the Programme and to contribute to the targets of reducing rural poverty from 27% to 14% by 2010, and raising agricultural growth to 10% per year by 2010. Among ASDP I key achievements was realizing bottom up-planning approach which ensured participatory planning and 75% of budget spent at the LGAs, 20% at national and 5% at regional level. Other achievements include improvement of human and physical capacity at District, 1 http://www.worldbank.org/en/country/tanzania/overview, August 2017 2 Bank of Tanzania. Quarterly Economic Review, May 2017 2 Agricultural Sector Development Programme II (ASDP-II) Region and Nation levels, improved Agriculture Research Services including increased number of research conducted for crops, livestock for improved varieties etc. 3. ASDP I also improved support to agricultural inputs use. Although there still some challenges, some improved seeds were produced and used. The programme also increased agricultural fertilizer, farmer access and use of agricultural mechanization such as tractors, power tillers, oxen-plough, all of which resulted in increased area under cultivation by 148%. Under ASDP I irrigation also was improved. The rehabilitation, improvement and construction of a number of irrigation schemes- resulted in increased irrigated area from 264,338 hectares in year 2005/06 to 461,326 hectares in year 2014 4. Under ASDP I marketing infrastructure and marketing systems for commodity value addition were developed. They include rehabilitation of warehouses; developing crop and livestock markets and developing marketing systems for cash products- receipt systems. Food Self Sufficiency Ratio was improved from 103% in 2009/10 to 123% in 2015/16. 5. Food versus inflation: the food prices remained stable leading to declining inflation rate, 7.01% in year 2006 to 5.56% in year 2010, and 5.6% in 2015; by October 2016 inflation was 4.5%. The export volume and value also increased for cash crops (coffee, cotton, sisal, tea, tobacco and cashew nuts). C. ASDP I - KEY CHALLENGES 6. Several challenges were identified during the implementation of ASDP I. They include inadequate governance, management, and coordination (horizontal and vertical coordination). This resulted to unclear roles and responsibilities; inadequate accountability systems and failure to coordinate sector players/stakeholders. Consequently, there were fragmentation, thinly spread resources; and overcrowding in cases which led to low results/impact, generally difficult to measure programme attribution. 7. Other challenges include poor sector enablers. The programme was implemented in a constrained enabling environment with inconsistent policies and regulations. The inadequate data and data systems also hindered the sector and program monitoring and evaluation. The programme was also challenged with inadequate technical and financial capacity (particularly in irrigation schemes) and adequate capacity to plan, manage and deliver investments. This led to delayed disbursement and caused carry over of funds from year to year. D. LESSONS LEARNT FROM ASDP I 8. Unlike other sectors, public investment in the agricultural sector does not directly produce the expected results, but rather facilitates the private sector (farmers and commercial partners) to achieve the expected targets. Several lessons and experiences were drawn from the implementation of ASDP I which guided the design of ASDP II. (i) The Sector Wide Approach (SWAp) in agriculture is possible when there is sufficient leadership, commitment and well-resourced decentralization of agricultural development planning and implementation. (ii) Need for improved farmer empowerment and organization; (iii) Need for program focus and prioritization on high impact areas, which beyond productivity also strengthen upstream levels of targeted value chains. (iv) Need for good governance, management, coordination, and harmonized monitoring and evaluation of the program; (v) Need for improved sector enablers; (vi) Need more investments in agricultural sector (the government, private sector and development partners). Therefore, there is need for harmonization and coordination on how the public sector should facilitate and enhance private sector participation; development partners and other stakeholders’ involvement in the agricultural sector. E. ASDP II TRANSFORMATION AGENDA/FOCUS 9. The programme vision. Under ASDP II, the intervention will maintain a clear vision, of Poverty Reduction, Food and Nutrition security and GDP growth. In order to address critical constraints and challenges to sector performance and to speed up agriculture GDP, improve growth of smallholder incomes and ensure food security by 2025, the programme encompasses all national strategies (Tanzania Development Vision (TDV 2025); Long Term Perspective Plan (LTPP 2012-2021); Five Year Development Plan II (FYDP II 2016-21) and Agricultural Sector Development Strategy (ASDS 2015)). 3 Agricultural Sector for Industrial Development 10. Prioritized Value Chains and Agricultural Ecological Zones (AEZ). ASDP II will cover all regions in terms of public service delivery (basic support for capacity building, demand-driven advisory services, etc.); however, investment coverage will focus on prioritized high potential commodities along the Value Chain (VC) and Agricultural Ecological Zones (AEZ). The implementation approach will be based on- priority crop/product per AEZ. The selection criteria are; contribution to food and nutrition security, impact to smallholder farmers/livelihood improvement, availability of technology for improving productivity and profitability of the crop, contribution to the national development agenda (industrialization)- five years and local market and exportation potential. 11. The priority CVC selected for first five years for ASDP II includes crops, livestock and fishery value chains commodities these are: rice, maize, cassava, potatoes, banana, coffee, cotton, oil seeds crops (sunflower, coconut, sesame, and palm oil), cashew, tea, sugar/cane and horticulture. The livestock and fish are: dairy, beef, goat, poultry, fish, and sea weed. Regions are “clustered” in AEZs according to similarity of agro-ecological as well as administrative characteristics to drive agricultural transformation. The AEZ with highest comparative advantage over other AEZs in production of a specific VC or a set of priority commodities (crops, livestock, fisheries) and will be designated as a processing hub for that specific VC or a set of commodities. This however will depend on availability of relevant infrastructure. 12. Right Business Environment. ASDP II will build good business environment which will attract investments, incentivize private sector including farmers and increase their engagement in agriculture. The better business environment will protect and increase access to land by small-scale farmers, develop better market systems and use comparative advantage in some commodities which will lead to improved livelihoods of Tanzanians. 13. The programme also focuses on efficient and effective resources allocation and utilization to create value and impact. 14. ASDP II entails committed leadership structures. The focus of the programme is also on a sound and functioning coordination, governance, accountability, administrative management structures, systems, processes and procedures. F. ASDP II OBJECTIVE, STRATEGY AND OUTCOME 15. Objective: Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food and nutrition security. 16. Strategy: Transform subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development 17. Outcome: Increased productivity, enhance marketing level, value addition, farmer income, food and nutrition security and Gross Domestic Product (GDP). G. ASDP II PROGRAMME COMPONENTS AND INVESTMENT AREAS AND PROJECTS/ FRAMEWORKS 18. The programme entails four interlinked components under which a total of 23 priority investment areas were developed. The components and their relevant investment areas are as provided hereunder. Component 1 Sustainable Water and Land Use Management. The objective of this Component is the expanded sustainable water and land use management for crops, livestock and fisheries. Priority investment areas under this component are (i) Land use planning and watershed management; (ii) Irrigation infrastructure development; (iii) Irrigation scheme management & operation; (iv) Water sources development for livestock & fisheries; and (v) Promote Climate Smart Agriculture (CSA) technologies and practices. Component 2 Enhanced Agricultural Productivity and Profitability and its Objective is increased productivity growth rate for commercial market-oriented agriculture for priority commodities. Priority 4 Agricultural Sector Development Programme II (ASDP-II) investment areas are (i) Strengthening Agricultural extension, training and promotion/info services (crops, livestock and fisheries); (ii) Improvement Access to crops, livestock and fisheries inputs and health services; (iii) Research and development; (iv) Strengthening and promoting agricultural mechanization (crop, livestock and fisheries); and (v) Food and nutrition security improved. Component 3 Commercialization and Value Addition. The objective is improved and expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations. Priority investment areas are (i) Develop market access for all priority commodities; (ii) Develop market access for fisheries and livestock products; and (iii) Development of processing and value addition for Crop, livestock and fishery products. Component 4 Sector Enablers, Coordination and Monitoring and Evaluation. The objective of Component four is Strengthened institutions, enablers and coordination framework. Priority investment areas are (i) Policy and Regulatory Framework and Business Environment Improvement; (ii) Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing farmer organizations and cooperatives movement; (iii) Promote and strengthen gender inclusiveness in the agricultural sector; (iv) Improve and strengthen vertical (from PO-RALG to RSs and LGAs) and horizontal coordination between ASLMs. (v) Improved Capacity and agricultural data collection and management systems (vi) Management Capacities and Systems Improvement (vii) Develop Agricultural Sector M&E System (viii) Improvement of Capacity in all levels (ix) Improvement of ICT for Agricultural Information Services and Systems; and (x) Provide microfinance services 19. However, for ease of programme implementation, each investment area was also broken down into various projects/ frameworks for implementers, especially the LGAs. The programme therefore has a total of 56 implementable projects. For the same purposes, 56 projects concept notes were also prepared and can be improved to suit the situation during the implementation. At LGA level, projects/framework can also be broken into smaller projects as it may be necessary and link them to the District Development Plans (DADPs). Proposed projects were prepared in order to facilitate implementation at all levels and alignment with the Key Performance Indicators (KPIs). H. ASDP II IMPLEMENTATION PLAN, SEQUENCING AND SCHEDULING 20. For implementation ASDP II components and projects are sequenced and scheduled to create and bring greatest change and impact to the sector. The program implementation plan, sequencing, scheduling process considered the potential for components and projects which will address immediate sectoral challenges, take advantage of opportunities, and bring positive change. In view of the current challenges facing the private investors and small holder commercial farmers, there is need to implement projects that create the necessary enabling environment (“Unclog the pipe and let the water flow”). Hence, implementation emphasis will start with Component 4 which facilitates implementation of other components and creates the necessary enabling environment for both private and public sector to function including the small holder farmer. Then Component 3 (Commercialization and Value Addition) will create markets pull effect which will attract enhanced agricultural productivity and profitability under Component 2. The implementation of these components will necessitate sustainable water and land use management under Component 1. However, the proposed implementation sequence is meant to guide implementation of the programme depending on the availability of resources. Ideally, all projects should begin at the same time if the required funding is available; if not, the highest priority component, investment areas and projects can be implemented first and lower priority projects implemented later depending on availability of funds. I. GOVERNANCE AND INSTITUTIONAL FRAMEWORK UNDER ASDP II 21. Under ASDP I, there were a number of challenges on governance, institutional and management which led to several problems including unsatisfactory management and accountability systems of the program and project at all levels. Also, there was poor coordination (vertical and horizontal), fragmentation of projects, overcrowding and overlaps in some areas; limited funding on some areas3 and unclear roles, 3 Tanzania Agricultural Sector Investment Mapping (TAN-AIM, 2015/16) 5 Agricultural Sector for Industrial Development responsibilities and mandate of various stakeholders i. e Government to Government, Government to Development Partners (DP), Government to Non-State Actors (NSAs), DPs to DPs and NSA to NSAs. 22. Under ASDP II, the implementation will have a clear governance, institutional framework, coordination and management mechanism from the national to the Local Government Authorities (LGAs). These include: government leadership in the coordination of all stakeholders and effective stakeholder collaboration; clear roles and responsibilities; and authority and accountability of lead and implementing agencies including ASLMs; focus in achieving program/project objectives, outcomes, and KPIs through the Results Framework (RF); development and dissemination of proper program/project guidelines, procedures, and documentations for implementers; facilitate proper financial management and auditing systems for the program and projects; and ultimately all will be accountable to the Prime Minister. The ASDP II National Coordination Unit (NCU) will ensure effective planning, management and implementation of ASDP II projects in partnership with various key stakeholders. 23. The hierarchy of coordination organs under ASDP II at central level will include National Agricultural Sector Stakeholders Meeting (NASSM), Agricultural Steering Committee (ASC), and Agricultural Sector Consultative Group (ASCG), Technical Committee of Directors (TCD), Thematic Working Groups (TWGs) and ASDP II National Coordination Unit (NCU) lead by a National Program Coordinator. 24. Chaired by the Prime Minister, members of NASSM will include Ministers of ASLMS, other central Government Ministers Permanent Secretaries, DPPs from all ASLMs, and senior government officials, Component Leaders; RSs; DEDs; DAICOs, DLFOs; Research Officials; Training officials; Academia representatives; commodity boards; all DPs supporting Agriculture, Private sector etc. the agenda for this annual meeting may include policy guidelines to the agricultural transformation agenda, provide advice and guideline to the implementation of ASDP II etc. as directed by the Chairman. 25. Agricultural Steering Committee (ASC) will be chaired by the Minister of Agriculture (MoA). Members will include PSs and DPPs of Lead Components and related ASLMs; representatives of DPs, NGOs and NSAs. The agenda will include Review and approve ASDP II plans, budgets, monitoring and evaluation reports etc. 26. Agricultural Sector Consultative Group (ASCG) meeting will be chaired by the Permanent Secretary, MoA. The meeting will be attended by all stakeholders in the agricultural sector (GOT, Private Sector, DPs, and NGOs/NSA) and training and research institutions to provide advice on sector policies, plan, budgets, public and agricultural expenditure review, among others. 27. Technical Committee of Directors (TCD) meeting will be Chaired by PS-Ministry of Agriculture. Members will be Directors of ASLMS, Component Leaders, Chairs of Lead Components, PO-RALG, ASDP II Coordination and selected Ministries. The agenda for these meeting will include review, scrutinize and harmonize individual Lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports, etc. 28. Lead Agency Component Technical Meeting will be chaired by DPP of Lead Component. Members will include Chairperson(s) of the Thematic Working Group (TWG) and the agenda will include review submitted component plans, budgets; review and analyze reports. 29. Thematic Working Groups (TWGs) (Various groups) will be chaired by Component/Sub-Component Leaders and members will include selected technical experts of different ASLMs appointed by the Head of the Lead Agency etc. the agenda will include preparation and review of ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination meeting. 30. ASDP II National Coordination Unit (NCU) will also function as ASDP II Secretariat, chaired by National Program Coordinator. Members will include Experts in: Productivity and Commercialization; Planning and Budgeting, Markets and Value chains; Monitoring and Evaluation; Agricultural Economist, Researcher and Policy Analyst. The agenda will include providing a catalytic and supportive role to the agricultural transformation agenda etc. 31. For effective implementation coordination and management, there will also be a coordination unit at the Presidents-Office Regional Administration and Local Government Authorities (PO-RALG) which will be responsible for coordination and managing all ASDP II activities at the lower levels. 6 Agricultural Sector Development Programme II (ASDP-II) J. MONITORING AND EVALUATION OF ASDP II 32. Under ASDP II there will be both internal and external monitoring and evaluation. Immediate level within the GoT will carry the internal monitoring and evaluation e.g. Ward Executive Officer (WEO) will monitor and evaluate the Village Executive Officer (VEO). Monitoring and Evaluation Management system will be established at all coordination levels (National, PO-RALG, Regional, and District). National Coordination Unit (NCU) will coordinate National Joint Annual Reviews and Evaluations. Both at National and PO-RALG level there will be a common Monitoring and Evaluation Thematic Working Group (M &E-TWG). The frequency of the monitoring and evaluation has been set in order to attain the required results. K. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT 33. By combining the base development budgets for each component, the overall investment costs of ASDP II were derived the base cost of ASDP II is estimated at TZS 13.819 Trillion (USD 5.979 billion) and annual investment base costs range from TZS 2.284 Trillion (USD 988 million) to 3.238 Trillion (USD 1.400 million) over a 5-year period. The distribution of the funds will be 25% at National and Regional Secretariat and 75% for Local Government Authorities. 34. Component 1: Sustainable Water and Land Use Management is estimated at TZS 2.024 Trillion (USD 941 million) and a high proportion of this budget is allocated to irrigation development. Component 1 accounts for 15% of overall programme cost. The cost of Component 2: Enhanced Agricultural Productivity is estimated at TZS 8.081 Trillion (USD 3.758 million) or 58% of overall programme cost. Component 3: Commercialization and Value Addition (including investments to promote priority value chain development) is estimated to cost TZS 1.483 Trillion (USD 1.663 million) or 26 % of overall programme cost. Furthermore, the cost of Component 4: Strengthening Sector Enablers is estimated at TZS 137 billion (USD 67 million), or 1% of programme cost. 35. The main sources of financing of the development budgets for ASDP II, will include: the government, development partners and other stakeholders including private sector, NGOs and farmers. For each programme sub-component, the proportions of the budget for which the respective financiers would provide funds were determined to derive a tentative financing plan for ASDP II. 36. On the financing modality, the Government prefers Basket funding for ASDP II. However, standalone direct project financing will also be considered. It is important that there is clear communication, transparency, and coordination during the joint planning and budgeting and implementation of the program. L. SUMMARY OF THE BENEFITS 37. Agricultural transformation and accelerated rural development will make a major contribution to Tanzania’s national development aspirations. The principal benefits of the programme will be: (i) increased and sustainable productivity and production of food and non-food agricultural commodities to improve rural incomes, boost rural households and national level food security, and provide raw materials for the agro-industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural sector generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to adapt to climate change; and (v) improved institutional capacity to mobilize and manage resources in support of agriculture sector development. Above the program will contribute to Tanzania’s higher level national development goals as expressed in Vision 2025. 38. Other expected benefits include: (i) reduction in harvest and post-harvest losses; (ii) increased export earnings; (iii) diversification of production into higher value agricultural products; (iv) improved access to financial services by smallholder farmers and rural entrepreneurs; (v) reduced transaction costs and improved efficiency in pre- and post-farm gate value chains; (vi) increased participation in cooperatives 7 Agricultural Sector for Industrial Development and other forms of FO; (vii) improved access to markets through infrastructure development; (viii) increased rural employment; (ix) higher productivity and reduced vulnerability to droughts from expansion of irrigated agriculture; (x) maintenance of agricultural biodiversity; and (xi) improving the system of disaster risk management by exploring the use of innovative risk management tools; (xii) reduced gender related imbalances; (xiii) reduced child labour in agricultural sector by promoting decent work in accordance with ILO guidelines4; and reduce contribution of agriculture to climate change through promotion of CSA5Functional networks between production and markets. I. BACKGROUND6 A. Macroeconomic Indicators and Agriculture7 1. Tanzania’s macroeconomic indicators showed robust growth in Gross Domestic Product (GDP) before and during implementation of the first phase of the Agricultural Sector Development Programme (ASDP-1) which started in 2006. In recent years, GDP growth rate was between 6.0% and 8.1% between 2006 and 2014 at 2007 constant prices. These levels of GDP growth happened at a time when agriculture sector growth, except for 2008, was far below GDP growth (see Figure 1)8. On average, the service and industry sectors exhibited stronger growth rates than agriculture. The average growth rate for the agriculture sector during the period 2006–2014 was 3.9% per annum, and that of the service and industry sectors was respectively 8% and 7.8% for the same period. From 2006 to 2012, the share of the agriculture sector in total GDP decreased from 27.7% to 23.2%, while the shares of industry and service sectors increased from 20% to 22%, and from 46% to 49% respectively during this period 9. Figure 1: GDP growth rate by sector (%, at 2007 constant prices) Source: Bank of Tanzania. Quarterly economic review, May 2015 2. Given the decline in the agriculture sector’s share of GDP and its contribution to real GDP growth, it is apparent that the robust economic growth is not a shared prosperity. On the contrary, those who earn their livelihood from agriculture and who happen to live in rural areas are trapped in poverty. For example, in 1992 the rural population was 80% of the total population and the poverty rate was 40%. In 2007, after 15 years, the rural population was 74% of the total population and rural poverty rate 4 Conclusions of the “International Workers’ Symposium on Decent Work in Agriculture” Geneva, 15-18 September 2003 5 (Lipper et al. 2014) 6 The background (Chapters I and II) is adapted and building on the FAO-TCIA support to ASDP I-BF June 2013. 7 Tanzania Economic Update: Spreading the Wings, From Growth to Shared Poverty. World Bank, October 2012. 8 See also http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG/countries. 9 According to the World Bank (http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS/countries) the agriculture sector value added in % the country GDP is estimated at 28.1%, 27.7%, 28.7% and 28.4% for 2010, 2011, 2012 and 2013 respectively. In this case agriculture corresponds to ISIC divisions 1–5 and includes forestry, hunting and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. 8 Agricultural Sector Development Programme II (ASDP-II) was estimated at 37.8%. It is apparent that much has not changed in terms of both the share of rural population and rural poverty rates in Tanzania. The sectors that have driven economic growth, such as construction, finance, mining, services10, and telecommunications have not created jobs in rural areas and have not had a noticeable impact, direct or indirect, on the rural population. Moreover, the reason why the robust economic growth over the last decade has not been associated with poverty reduction is because the agriculture sector has been growing more slowly than other major sectors. Therefore, growth of the agriculture sector does not substantially influence GDP growth, as it did in the 1970s and 1980s when it contributed about 50% of total GDP; neither does it contribute significantly to poverty reduction in Tanzania11. 3. The 2012 Tanzania Economic Update12 highlights that “rapid economic growth and stability has generated high dividends for Tanzania in recent years, driving increases in per capita income of 70% over the past decade. However, these benefits have not been evenly shared. To fight rural poverty, successful economies have implemented systems to connect their farmers to markets. These economies encourage the cultivation of high-value, non-traditional crops and manage migration flows toward urban centres to facilitate growth and equity. Rather than minor adjustments, fighting rural poverty requires a major policy shift that involves: (i) agricultural commercialization; (ii) diversification; and (iii) urbanization. The paper concludes that the challenge for Tanzanian policy makers is to stimulate these three transformational forces and manage them appropriately over the long term” B. The Agriculture Sector 4. The relative contribution to agricultural GDP by crop, livestock, forestry and hunting, and fisheries in recent years averaged 18%, 5%, 3% and 1.4% respectively. Tanzania has a total of about 7.1 million ha of high and medium potential land (2.3 and 4.8 million ha respectively) suitable for irrigation, supported by rivers, lakes, wetlands and aquifers. Of the 2.3 million ha classified as high potential, only 461,326 ha had improved irrigation infrastructure in 2015, accounting for only 1.6% of the total land with irrigation potential (MAFC, 2015). An estimated 55% of the land could be used for agriculture, and more than 51% for pasture. However, only about 6% of the agricultural land is cultivated, and the practice of shifting cultivation causes deforestation and land degradation on pastoral land. Tanzania is one of the few countries in Africa that still has extensive wildlife resources and protected areas that account for about 25% of its total land area. Figure 2. Agriculture share of GDP (%), 2001 prices However, the growth of agriculture is hampered by low productivity of land and labour. Although numerous factors caused this situation, the key factors are, inter alia: (i) poor production techniques; (ii) 10 Including tourism. 11 Review of food and agricultural policies in the United Republic of Tanzania. MAFAP Country Report Series, 2013, FAO, Rome, Italy. 12 Spreading the Wings: from growth to prosperity. World Bank publications: http://www-wds.worldbank. org/external/default/WDSContentServer/WDSP/IB/2012/10/24/000386194_20121024053815/Rendered/ PDF/733460WP0P133400Box371944B00PUBLIC0.pdf. 9 Agricultural Sector for Industrial Development underdeveloped markets, market infrastructure and farm-level value addition; (iii) poor rural infrastructure, including rural roads, telecommunications and electricity; and (iv) inadequate agricultural finance, including public expenditure. Use of productivity enhancing agricultural inputs is also one of the lowest in the region. For example, Tanzanian farmers use about 8–10 kg of fertilizer per hectare (dolllubled from 2008 to 2013), compared with an average of 16 kg/ha for Southern African Development Community (SADC) countries while Malawi uses 27 kg/ha and China 279 kg/ha on average. However, in spite of these low levels of application, the Tanzanian market has failed to absorb all the fertilizer stocks supplied by traders, recording surpluses of between 15% and 30% during the 2007/2008 to 2009/2010 seasons. The annual supply of improved seeds is about 30,000 tons (75%maize seeds) or 25% of total estimated requirements of 120,000 tons per year. There has been a sharp increase in supplies, combined with a narrowing of the gap between supplies and purchases since 2007/2008, when the government increased funding for its National Agricultural Input Voucher System (NAIVS), suggesting that this system has been useful in enhancing input absorption by farmers. Figure 3: GDP by economic activity (at current prices—TSh billion)13 20% 25% 30% 35% 0 2500 5000 7500 10000 12500 2007 2008 2009 2010 2011 2012 2013 GDP by economic activity (TSh billion 2007/13 - current prices) Crops Livestock Forestry Fishing % GDP Agriculture Figure 4: Percentage GDP by economic activity (in % of total GDP—at current TSh prices) 24 26 28 30 32 0 2 4 6 8 10 12 14 16 18 20 2007 2008 2009 2010 2011 2012 2013 % Agric. in total GDP % of GDP GDP by economic activity (TSh billion 2007/13 - current prices) Crops Livestock Forestry Fishing % GDP Agriculture 5. Crop subsector. The production of main crop commodities over the past 50 years has been reported (FAOSTAT), as shown in Figure 5. The changing point seems to be in year 2000 with: (i) the total cereal (maize, rice, sorghum, millet) production out-yielding the annual cassava production (mainly linked to yield variations); (ii) sharp production increases are recorded for cereals, especially maize, banana, sugar and other root crops and to a lesser extend for oil crops. Farmer yields for the main food crops 13 Adapted from data sourced in Revised National Accounts Estimates for Tanzania Mainland (Base year 2007). National Bureau of Statistics, Ministry of Finance, November 2014. 10 Agricultural Sector Development Programme II (ASDP-II) doubled over the past 50 years reaching about 1.5 and 2.0 tons/ha for maize and rice respectively. For pulses and oil crops yields increased, but remain on average below 1.0 ton/ha per season as shown in Figure 5. Figure 5: Main crop production in Tanzania (1961–2013, in tons) Figure 6: Evolution of average crop yields for main crops in Tanzania (1961–2013, in kg/ha) 6. Livestock sub-sector. This sub-sector includes about 21.3 million cattle, 15.2 million goats and 6.4 million sheep. Other livestock kept in the country include 1.9 million pigs, 35.1 million indigenous and 23 million exotic chicken14. The country has the third largest cattle population in Africa after Ethiopia and Sudan. About 90% of the livestock population is of indigenous types which are known for their low genetic potential in milk and meat production. The livestock sub-sector growth rate averaged 4.2%, against 3.6% for the whole sector. The cattle population increased at an average rate of 1.4% and poultry recorded an impressive growth rate of 9.6% to reach 58 million chickens. 7. In meat processing. The Government has supported the private sector to invest in modern abattoirs and slaughterhouses in Sumbawanga, Dodoma, Arusha, Morogoro and Coast regions among others. The government has also sold some of its shares in former government owned companies such as National Ranching Company (NARCO) and Dodoma Abattoir. Although the number of milk processing plants increased from 22 to 39 over the 2001–2009 period, there is still huge potential to expand the 14 Ministry of Livestock and Fisheries Development (MLFD), Statistical Year Book, 2013. 11 Agricultural Sector for Industrial Development milk industry (1.5 billion litres/year), as only 20% is collected and processed. Private companies have also resumpted milk processing in Musoma, Arusha, Tanga, Dar es Salaam, Morogoro, Iringa, Mbeya and Njombe. Following improvement in business environment, the number of plants for processing hides and skins increased from 3 to 6 between 2001 and 2009, with a capacity to meet 52% of the total production (48.2 million square feet with TSh 12.8 billion in 2009). 8. Fisheries. Tanzania is endowed with fishery resources, both marine and inland. Marine water covers 64,000 square kilometres and a coastal line of 1,424 kilometres. The Exclusive Economic Zone (EEZ) is up to 200 nautical miles covering an area of 223,000 square kilometres providing the country with additional marine area and fisheries resources. Fresh water fisheries which cover 62,000 square kilometres include the shared waters of the great lakes, namely Victoria, Tanganyika and Nyasa. The country has also other small natural lakes, man-made lakes, river systems and many wetlands with fisheries potential. Despite the diverse fisheries potential, most are untapped including those in the EEZ. The industry has been dominated by small-scale fishers and fish farmers who normally use traditional technology. Hence, the fisheries sector is an area which, once effectively utilized, will improve the economy in an enormous way. The annual growth rate of the fisheries sector has been fluctuating annually. For example, in 2014 the growth rate was 2.0% and in 2013 it was 5.5%. The contribution of fishing activities to GDP has almost remained constant with a slight change of 0.1%. In 2010 the share of fishing activities was 1.5% before decreasing to 1.4% in 2011 and 2012; it further decreased to 1.3% in 2013 and 2014. 9. Private investment in agroprocessing. This sub-sector has the potential to generate employment, raise productivity, transfer skills and technology, increase competitiveness, substitute imports and enhance exports, and contribute to the long-term national economic development. Although increasing, the inflow of the foreign direct investment to the agriculture sector remains low with 2–3% of the total foreign direct investment (USD 31.4 million in 2011). Rapid urbanization and rising incomes have been contributing to increased demand for value-added products in the agriculture sector. However, on the supply side, the underdeveloped agroprocessing industry has so far failed to provide significant levels of import substitution for the urban food market. The mismatch between demand and supply for value- added food products resulted in tripling the country’s food import bill between 2006 and 2013 (USD 963.9 million). Globally, the pattern of growth of the economy is influenced by the transformation of the agriculture sector through value addition of primary products, thereby influencing investments in industry and service sectors. C. Policy Environment 10. Tanzania has a clear articulated long and medium-term policy frame for the economy in general and for the agriculture sector in particular. The long-term policy framework places agriculture at the centre and has evolved various sector and sub-sector policies. Related fields such as natural resources management are addressed and their complementarity in terms of achieving the long-term social and economic development objective of the country is articulated. The key policies that address the sector are discussed in the following sub-sections; 11. Tanzania Development Vision 2025. The Tanzania Development Vision (TDV) is a long-term vision that the Government of Tanzania issued to guide its development. The vision articulated in this policy document is that by 2025 Tanzanians will have created a substantially developed, people-centred, peaceful, stable and united society with high quality livelihood and high level of human development. The economy will have been: “transformed from a low productivity agricultural economy to a semi- industrialized one, led by modernized and highly productive agricultural activities which are effectively integrated and buttressed by supportive industrial and service activities in the rural and urban areas. A solid foundation for a highly productive, competitive and dynamic economy will have been laid”. The agriculture sector is identified as an important arena where strategic interventions will be implemented to contribute to the building of a strong solid foundation for a highly productive, competitive and dynamic economy15. 15 Government of URT. 1999a. The Tanzania Development Vision 2025. Dar es Salaam. 12 Agricultural Sector Development Programme II (ASDP-II) Figure 7. Long & medium-term policy framework for the transformation of the agriculture sector • Improved livelihoods, food security,extended life expectancy (Pillar 1); Building a strong & competitive economy (Pillar3) by raising agricultural productivity, engaging in commercial undertakings in value chains, genrating surplus household income & export earnings • Agriculture (core priority 2): Focusing on the transformation of agriculture for food self suffiency and export, development of irrigation particularly in selected agricultural corridors, and high value crops including horticulture, floriculture, spices, vineyards etc. • To have an agricultural sector by year 2025 that is modernized, commercial, highly productive, utilizes natural resources in an overall sustainable manner and acts as an effective basis for inter-sectoral linkages • To change the functions of central government from an executive role to a normative one; empowering local government and communties to reassume control of their planning processes and to establishing an enabling environment which attracts and encourages private sector investments in agriculture • To rationalize allocation of resources to achieve annual 6 percent agricultural GDP growth, consistent with national objectives to reduce rural poverty and improve household food and nutrition security • Joint GoT & private sector declaration on speeding up agenda for the modernization of agriculture to uplift agricultural growth from 4 to 10% within the time frame of the vision 2025 Vision 2025 NDP 2006- 2011 ASDS 2001 ASDP 2006-13 Kilimo Kwanza 2009 TAFSIP 2011-21 Source: Compiled from FAO/TCIA (2013). 12. The National Strategy for Growth and Reduction of Poverty I & II. This strategy is known as MKUKUTA I and II and is one of the national strategies aimed at moving the nation towards Vision 2025 and to achieve the Millennium Development Goals (MDGs). The essential features in developing both MKUKUTA I & II were national ownership and consultation with stakeholders, aiming to foster greater collaboration among all sectors and stakeholders. The strategy requires increased resource mobilization and that the national budget is aligned to MKUKUTA with direct links to the public expenditure review. A Joint Development Cooperation Framework (DCF) has been developed with development partners to increase the volume and effectiveness of aid, harmonization and alignment to achieve MKUKUTA objectives16. The MKUKUTA II strategic intervention cluster is Growth and Reduction of Income Poverty, focusing on equitable and employment generating growth, sustainable development principle, food security and affordable and reliable modern energy services and adequate infrastructures for production purposes. Agriculture is identified as one of the key growth areas and means to attain TDV 2025. 13. Agricultural Sector Development Strategy II (ASDS-2) of September 2015. This strategy reflects the changes in the overall economic environment and the policies and programmes that emerged over the years. ASDS-2 sets a new direction for the development of the sector, integrates the Comprehensive Africa Agriculture Development Programme (CAADP) objectives and reflects most of the vision and principles enunciated in the Tanzania Agriculture and Food Security Investment Plan (TAFSIP). It stresses the need to continue the pursuit of a sector-wide approach to plan, coordinate and harmonize the resources (public and private) required to accelerate implementation of existing initiatives and to incorporate new initiatives which address national, regional and sectoral development priorities. Largely along the line of TAFSIP, the ASDS-2 defines the sector-level monitoring and evaluation (M&E) framework and identifies strategic areas for public and private investment for achieving expected outcomes and impact. The ASDS-2 also details the policies, strategies and priority support areas for achieving agricultural and rural development, contributing to the goals of Vision 2025, as well as the economic growth and 16 Government of URT. 2010b. National Strategy for Growth and Reduction of Poverty II (NSGRP II).Dar es Salaam, Ministry of Finance and Economic Affairs. 13 Agricultural Sector for Industrial Development poverty reduction objectives specified in MKUKUTA/MKUZA strategies. Identified key priorities for ASDS-2 include: (i) the role of science and technology (research, extension, fertilizer use by small-scale commercial farmers); (ii) further priorities such as irrigation, finance, mechanization, agroprocessing and access to markets; and also (iii) strong articulation with other sector initiatives such as Southern Agricultural Growth Corridor of Tanzania (SAGCOT). 14. Kilimo Kwanza (KK). The global food price crisis of 2008/2009 gave rise to renewed interest in the agriculture sector by both continental leaders under the African Union framework and the international community. The government successfully launched plans for the active engagement of the private sector and in mainstreaming agriculture in all sectoral undertakings, emphasizing the importance of Kilimo Kwanza, which means “agriculture first”. Internationally, the country received support from the G8 to mobilize international private sector capital and technology transfer to revamp the agriculture sector. Most initiatives were designed to enhance technology uptake (e.g., seeds and fertilizer), market development and export promotion. The government, development partners and the private sector agreed to adopt a cluster approach to optimize human and financial resources in attaining maximum impact in the shortest time possible. SAGCOT is among the first programmes under this approach where partnership between government, small-scale farmers and large-scale commercial farmers/processors is emphasized. These developments channelled additional support for mainly parallel implemented projects to be ‘coordinated’ within the overall ASDP framework. 15. Tanzania Agriculture and Food Security Investment Plan. TAFSIP is Tanzania’s version to operationalize the CAADP17 framework formulated to assist achievement of TDV 2025. It is a 10-year road map for agricultural and rural development that identifies priority areas for public and private investments in the sector to promote agricultural growth, rural development, and food security and nutrition. It is a framework for the prioritization, planning, coordination, accountability, harmonization and alignment of investments that will drive Tanzania’s agricultural development over the next decade. To achieve the CAADP objectives, the investment plan is expressed in terms of seven thematic programme areas each with its own strategic objective and major investment programmes. The thematic areas are: (i) Irrigation Development, Sustainable Water Resources and Land Use Management; (ii) Agricultural productivity and Rural Commercialization; (iii) Rural Infrastructure, Market Access and Trade; (iv) Private Sector Development; (v) Food Security and Nutrition; (vi) Disaster Management, Climate Change Adaptation and Mitigation; and (vii) Policy Reform and Institutional Support. 16. The objectives of CAADP are to: (i) achieve an average of annual sectoral growth of 6% and government allocation of budget at 10%; (ii) attain food security and nutrition; (iii) develop regional and sub-regional agricultural markets; (iv) integrate farmers and pastoralists into the market economy; and (v) achieve a more equitable distribution of wealth. These objectives, as amplified by the Malabo Declaration (2014) anchores to: (i) allocate at least 10% of public expenditure to agriculture, and to ensure its efficiency and effectiveness; (ii) transform agriculture and ensure inclusive growth through doubling of agricultural productivity, enhance value chains and tripling intra-African trade in agricultural goods and services; and (iii) strengthening systematic capacity for transformation through capacity for planning, policies and institutions, leadership, coordination, partnerships and data and statistics. Through CAADP, African governments commit to providing technical and financial support for the transformation of the agriculture sector and the development of the agro-based private sector, as well as addressing trade issues18. CAADP includes a focus on: (i) changing perspectives and mind-sets to promote commercial agriculture; (ii) promoting policies that raise agricultural productivity; (iii) expanding markets at national, regional and international level; and (iv) encouraging and facilitating private investment to support the agricultural 17 Initiative of the African Union’s New Partnership for Africa’s Development (NEPAD), adopted by the Heads of State and the government in Maputo, Mozambique in 2003. 18 From 2008 to date, the CAADP Africa-owned policy narrative has been steadily sidelined by the US-led G8 mobilization of (support for) global agribusiness, with assistance pledged by aid agencies and philanthropies. The comprehensive nature of this transition to MNC-driven policy—which climaxed with the May 2012 NAFSN G8 meeting reflects the seriousness of the on-going global food crisis (Source: The Comprehensive Africa Agriculture Development Programme (CAADP) and agricultural policies in Tanzania: Going with or against the grain (B. Cooksey, 2013). 14 Agricultural Sector Development Programme II (ASDP-II) sector. Unlike the Maputo Declaration, the Malabo Declaration sets output indicators to be achieved with high level aspirations for sustainable and inclusive development, renewed commitments towards evidence based planning and accountability with view to conduct a biennial Agricultural Review Process that involves tracking, monitoring and reporting on progress. II. SECTOR PROGRAMMES, PROJECTS AND PUBLIC EXPENDITURE A. Agriculture Sector Development Programme (ASDP phase 1) 17. The Agriculture Sector Development Programme (ASDP) is one of the key instruments that the government uses to meet TDV 2025 and implement the ASDS. This programme had the following objectives: (i) to enable farmers to have better access to, and use of, agricultural knowledge, technologies, marketing systems and infrastructure, all of which contribute to higher productivity, profitability, and farm incomes; and (ii) to promote private investment based on an improved regulatory and policy environment. The objectives will be achieved through a set of complementary interventions aimed at: (i) improving the capacity of farmers, including food insecure and vulnerable groups, to more clearly articulate demand for agricultural services and to build partnerships with service providers; (ii) reforming and improving capacity of both public and private agricultural service providers to respond to demand and provide appropriate advice, services and technologies; (iii) improving the quality and quantity of public investment in physical infrastructure through more devolved technically-sound planning and appraisal; and (iv) improving market institutions, including strengthening the policy and regulatory frameworks and coordination capacity at national level. These results will be delivered through Local Level Support and National Level Support, as described in the following paragraphs; 18. ASDP was launched in 2006 to provide a sector-wide investment vehicle to deliver the Programme and to contribute to the targets of reducing rural poverty from 27% to 14% by 2010, and raising agricultural growth to 10% per year by 2010. ASDP was conceived and implemented as a bottom up approach delivered nationally, with 75% of development funds from a multi-donor Basket Fund allocated to local level support through a performance-based block grant mechanism. The Basket Fund represented an improvement in aid effectiveness away from fragmented projects to an on-budget, government- led approach underpinned by greater policy coherence and use of government planning and reporting systems. ASDP also envisaged greater pluralism in service delivery, an improved regulatory environment and stronger control of resources by beneficiaries. ASDP was conceived to have a 15-year horizon and a first phase of 7 years 2006/2007 to 2012/2013. 19. Despite initial delays in Basket Fund contributions and programme start-up, ASDP-1 implementation improved steadily over time. It succeeded in introducing the concept of a sector-wide approach in the agriculture sector. The ASDP process is now widely understood from national down to village level. It has created a mode of operation which has streamlined planning, financial management, monitoring and reporting systems, all of which have shown improvement. It has facilitated significant development of human and physical capacity, particularly at the Local Government Administration (LGA) level19; a capacity which can now support ASDP II activities, and which can also provide an environment for new initiatives to use and contribute to the higher-level sector goals. 20. ASDP-1 also faced challenges in the course of implementation. As for the government budgets, its wide thematic area coverage and its national scope resulted in a situation where limited resources were thinly spread, and results were fragmented and hard to assess, attribute and report. Challenges related to inadequate technical capacity, particularly at the level of LGAs in planning, prioritization and implementation were also experienced. Significant carryover of funds from year to year (e.g., about 30% of released funds in the case of irrigation) shows that capacity to plan, manage and deliver investments has been a challenge. Donor harmonization, as envisaged at the start of ASDP, weakened over time and proliferation of self-standing projects gradually emerged. Coalescing around both the Paris Declaration and the Accra Agenda for Action to make development assistance more effective has 19 See ASDP JIR and Evaluation report 2011. 15 Agricultural Sector for Industrial Development faced challenges in the agriculture sector in the absence of strong leadership. Other challenges and gaps include limited participation of agribusiness/private sector in programme activities; limited support to farmer organizations, especially on their role in marketing and value addition; incomplete irrigation schemes, which reduces achievement of optimum payoffs and sustainability. 21. District Agricultural Sector Investment Project (USD 83 million) financed by the African Development Bank from 2006 to 2013 was implemented parallel to ASDP-1 in 28 rural districts of Kagera, Kigoma, Mwanza, Mara and Shinyanga regions (about 0.57 million beneficiaries). The project was to increase productivity and incomes of rural households by: (i) farmers’ capacity building; (ii) community planning and investment in agriculture, especially in infrastructures; and (iii) support to rural microfinance and marketing. B. Other Related Agricultural Sector Initiatives 22. Besides ASDP-1, major ongoing projects in the agriculture sector, inter alia include: AFSP (Accelerated Food Security Programme: about USD 245 million, co-financed in 2009–2013 by the Government of Tanzania and the World Bank in parallel to ASDP). The objective was to contribute to higher food production and productivity in targeted high potential areas in Tanzania through improving maize and rice farmers’ access to the critical agricultural inputs (total number of beneficiaries are 1.75 million households). The AFSP had three main components: (i) improving access to maize and rice seeds and fertilizers, by strengthening the NAIVS; (ii) consolidating the agricultural input supply chains, by strengthening private agrodealer networks and national seeds systems; and (iii) project management, and monitoring and evaluation. AFSP also provided an additional financing for: (i) the ASDP-1 (USD 30 million), aimed to promote sustainable agricultural productivity growth, including support to small- scale irrigation and water management, integrated soil fertility management by strengthening research and advisory capacities for soil nutrient management and conservation farming; and (ii) for the second Tanzania Social Action Fund (AF-TASAF-2, USD 30 million), to strengthen the rural safety nets for food insecure and vulnerable people. 23. MIVARF: The Marketing Infrastructure, Value Addition and Rural Finance Support Programme (co- financed by the International Fund for Agricultural Development [IFAD] and AfDB for a total of USD 170 million, and coordinated by the Prime Minister’s Office [PMO]) is implemented in 26 regions of Tanzania, including the mainland (21 regions) and Zanzibar (5 regions) with a total of 141 rural districts. The programme is expected to directly benefit close to 500,000 rural households. The development objective is to enhance the incomes and food security of the target group sustainably through increased access to financial services and markets. The programme will focus on strengthening the marketing infrastructure and systems, and the rural finance sector. In particular, it aims at: (i) increasing access of poor rural people to a wider range of financial services for productivity-enhancing technologies, services and assets; and (ii) increasing access to sustainable agricultural input and output markets and opportunities for rural enterprise. 24. MUVI (The Rural Micro, Small and Medium Enterprise Support Programme): A total of USD 25 million, implemented through the Ministry of Industry Trade and Investment helps improve rural employment opportunities in 6 regions (Iringa, Manyara, Mwanza, Pwani, Ruvuma and Tanga). The programme provides selected medium and small-scale rural entrepreneurs with improved skills training, knowledge and access to markets, to help increase productivity, profitability and off-farm incomes. The programme has three goals: (i) to improve the awareness of rural entrepreneurs of market opportunities and how these can be exploited through the development and implementation of a communication strategy and the training of the entrepreneurs to improve their businesses; (ii) to improve the coordination and cohesion of selected value chains, through the creation and strengthening of backward and forward linkages for the selected chains; and (iii) to strengthen public and private sector institutions to provide efficient and effective support to rural enterprises. 25. SAGCOT (Southern Agricultural Growth Corridor of Tanzania): The goal of this initiative is to expand investment in agribusiness leading to income growth among smallholders and employment generation 16 Agricultural Sector Development Programme II (ASDP-II) across agribusiness value chains in the Southern Corridor. Its mandate is to mobilize private sector investments and partnerships by catalysing large volumes of responsible private investment, targeted at rapid and sustainable agricultural growth, with major benefits for food security, poverty reduction and reduced vulnerability to climate change. SAGCOT promotes ‘clusters’ of profitable agricultural farming and services businesses, with major benefits for smallholder farmers and local communities. The SAGCOT focus on value addition, infrastructure development, agricultural production and productivity and public–private partnership is consistent with the strategies and priorities of ASDS, complemented by KK.20 26. BRN (Big Results Now): The slow pace of implementing Vision 2025 had prompted the government to embark on a new model dubbed ‘Big Results Now’. This initiative was implemented through six sectors, namely agriculture, energy, education, resource mobilization, transport and water. Expert laboratories prepared priority implementation plans21 for the next two years. The objective of the agriculture BRN plan was to address critical sector constraints and challenges and to speed up agricultural GDP, improve smallholder incomes and ensure food security by 2015, mainly through smallholder aggregation models for main cereals and high potential crops contributing to import substitution, farm income and food security. Three programmes were prioritized including: (i) building a warehouse based trading system for maize (275 warehouses in 8 districts); (ii) building 78 professionally managed commercial rice irrigation schemes (in 10 districts); (iii) supporting 25 commercial farming (agribusiness) deals in the SAGCOT region. The target under 3 programmes is to have additional 150,000 tonnes of sugar22, 290,000 tonnes of rice and 100,000 tonnes of maize produced by June 2016. BRN provides important impetus in terms of political will, leadership and coordination across ministries, the financing of proposed activities and implementation modalities, coordinated through a Presidential Delivery Bureau (PDB) and Agricultural Delivery Division (ADD). 27. To ensure effective participation of private sector investment in the agriculture sector, through BRN, the Government has embarked on creating a conducive business environment. Among others, highlighted areas addressed as business environment challenges, especially for the micro-, small- and medium-scale enterprises, is both a strategically critical and urgent matter for the prospect of attaining TDV 2025. A Business Environment Lab was also conducted in early 2014, covering six (6) key work streams, namely: (i) access to land and security of tenure; (ii) contract enforcement, law and order; (iii) curbing corruption; (iv) labour laws and skillset; (v) aligning regulations and institutions; and (vi) taxation, multiplicity of levies, fees and charges. 28. EAAPP (The East Africa Agricultural Productivity Programme): This programme aimed at supporting the regional centres of excellence (RCoE) to contribute to increased agricultural productivity and growth by strengthening and scaling up regional cooperation in technology development, training, and dissemination programmes for four priority commodities (wheat, Ethiopia; rice, Tanzania; cassava, Uganda; and dairy, Kenya). Accordingly, EAAPP strives to enhance regional specialization in agricultural research for development (AR4D) and facilitate increased transfer of agricultural technology, information and knowledge within and across national boundaries. The main programme components are: (i) strengthening institutional capacities of RCoEs; (ii) technology generation, training, dissemination and scaling up, focused on regional priorities and using participatory strategies; (iii) improved availability of seeds and breeds, including strengthening the enabling environment for regional seed and breed exchange and trade; and (iv) programme coordination and management at national and regional levels. For the regional coordination activities, each participating country contributes about 2.7% of its budget to ASARECA23, for regional coordination activities. 20 ASDP and SAGCOT cover both the Southern Highland corridor area and target smallholder farmers, emphasizing commercialization by linking farmers with agribusiness to enhance competitiveness in domestic, regional and international markets. ASDP IIwill empower smallholder farmers so that they can increasingly benefit from support and services offered through SAGCOT, such as contract farming and out-grower schemes and matching grants under a catalytic fund. 21 More of a plan than actual programmes/projects as clarified by PMO and the Minister of the then MAFC. 22 To be supported by IFAD (USD 40 million) and co-financed by AfDB (USD 30 million) 23 ASARECA is a sub-regional organization aiming to enhance regional collective and harmonized action in AR4D, extension, training and education to promote economic growth, fight poverty, eradicate hunger and 17 Agricultural Sector for Industrial Development 29. FTF (Feed the Future): In Tanzania FTF is a USD 70 million annual off-budget contribution from the United States Agency for International Development (USAID), of which 80% is invested in SAGCOT; the rest targets Manyara and Dodoma regions and the Zanzibar islands. The FTF strategy, aligned to TAFSIP, is integral to the USAID strategic plan in both achieving sustained economic growth through agriculture and improving the nutritional status of all Tanzanians. Investments aim at improving economic opportunities and incomes through private sector led interventions and partnerships, including for women and youth. Expected outcomes are to increase yields (maize and rice), productivity and market access for horticulture producers and prevalence of children receiving a minimal acceptable diet, targeting about 100,000 smallholders (about 2% of the total number of smallholders). Furthermore, FTF is supporting the Tanzanian government to: (i) make informed policy decisions based on research and data, including quantifying the impact of rescinding the maize export ban, examining land compensation and leasing schemes and implementing a collateral registry system; and (ii) build human capacity and strengthen collaborative research capacity in national universities and institutions. FTF is also leveraging and scaling up local innovations, including food fortification, to improve access to nutritious foods and increase dietary diversity along the value chain. 30. ASDP-1 Financing: In the past 10 years, ASDS has been operationalized by ASDP with financing from the Government (central and local governments), the World Bank, AfDB, IFAD, the governments of Japan and Ireland, and the European Union. ASDS and ASDP emphasized sector-wide approach and Basket Funding as the preferred form of contribution from donors to foster harmonization of sector interventions, as opposed to the proliferation of ‘traditional’ projects. Overall, it appears that over the ASDP-1 implementation period, development partner funding support to the agriculture sector gradually moved towards increasing levels of earmarked basket funding, (back to) ‘traditional’ on-budget projects/ programmes implemented through different sector ministries, but also increased off-budget support. Although not always recognized24, several stand-alone projects were building on systems and capacities developed and maintained by ASDP-1, especially at LGA level: mutual levering is commendable, but non-earmarked financing of basic capacities, (Extension and Capacity Building Block Grants) have decreased to a critical level. Development partners have also made further investment commitment to BRN and/or specific local programmes, with high investment concentration on the SAGCOT area. ASDP II is open to a variety of financing modalities including the Basket Fund. C. Agriculture Sector Review-Public Expenditure Review (ASR-PER) 31. There is significant variability between sources of information relating to public expenditure in the agriculture sector. For example, the ASDP Secretariat often use budgets and expenditure of agriculture sector lead ministries (ASLMs). This approach excludes departments and agencies which undertake agricultural activities and is therefore prone to under-reporting of public expenditure. In contrast, the Ministry of Finance uses a broader definition of the agriculture sector than that reported by the ASDP. A more reliable source of information on public expenditure in agriculture are the series of annual reports on agricultural public expenditure, prepared since 2006, including the most recent Agriculture Sector Review-Public Expenditure Review (ASR-PER) (2014) issued in March 201525. The main aims of the ASR-PER are to: (i) present in-depth analyses on current issues of sector policy; and (ii) provide a standard database on key indicators of sector development, government interventions and public spending. 32. The ASR-PER compiles expenditure data by applying the standard Classification of Functions of Government (COFOG) which covers crops, livestock, fishing and production forestry. The statistics enhance sustainable use of resources in 11 participating countries. ASARECA focuses on generation and delivery of improved scientific knowledge, policy options and technologies as instruments to drive the sub-region towards meeting the NEPAD CAADP agenda and the MDGs, within a subsidiarity approach. 24 The IFAD Country Programme Evaluation (December 2014 final-unedited), recognized the high relevance, effectiveness, efficiency and sustainability of their ASDP investments when compared to alternative investments especially in agricultural marketing and value chain development. 25 Agriculture Sector and Public Expenditure Review 2014, MAFC, March 2015. 18 Agricultural Sector Development Programme II (ASDP-II) include expenditure from domestic budgetary sources (both national and sub-national) as well as from donor contributions in the category of “aid to government” and official loans. Expenditure on irrigation schemes is also included, but support for processing and marketing of agricultural products is not covered. The data collected by the annual ASR-PER is also used to monitor actual spending levels against the benchmark of the Maputo Declaration of 2003 and reaffirmed under the Malabo Declaration of 2014 in which the Heads of State of the African Union are committed to allocating 10% of total public expenditure to agricultural development. This commitment is primarily aimed at accelerating annual agricultural growth (target at 6%) to reduce poverty and enhance food security. 33. Public expenditure on agriculture appears in the central government budget mainly as recurrent and development spending of the Ministry of Agriculture Food Security and Cooperatives (MAFC) and the Ministry of Livestock and Fisheries Development (MLFD). However, services to farmers are primarily provided by LGAs and financed through grants from the central budget. The agriculture sector also receives development aid, but only the on-budget portion appears in budget estimates and financial statements. 34. Recurrent expenditure through MAFC and MLFD and agricultural spending by districts, have increased in recent years. However, this can to a large extent be attributed to the growth in input subsidies (2009–2012) and grants to the National Food Reserve Agency (NFRA). Expenditure on NFRA, input subsidies and other transfers to autonomous government institutions and international organizations, is shown in Figure 8. 35. In 2013/14, total recurrent expenditure through MAFC and MLFD was estimated at TSh 306.6 billion with special expenditure (i.e., NFRA grants, input subsidies and transfers to other government agencies) absorbing TSh 238.1 billion (78% of the total MAFC budget). In contrast, routine expenditure (i.e., personnel costs and operational charges) amounted to TSh 68.5 billion (22% of the total MAFC budget). However, while NFRA grants and input subsidies have increased since 2011/12, expenditure on personnel and operational charges has broadly remained unchanged and, in real terms, routine expenditure at central level has actually declined (Table 1). Figure 8. MAFC and MLFD Central-Level Recurrent Expenditure Source: ASR-PER, March 2015 (based on Budget Estimates for various years). 19 Agricultural Sector for Industrial Development Table 1: MAFC and MLFD central level recurrent expenditure (TSh million)26 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual Estimate Estimate Routine Expenditure Personnel Emoluments MAFC 16,953 18,490 21,659 25,167 26,328 27,169 MLFD 11,467 15,669 17,238 16,721 18,429 18,429 Operational Charges MAFC 11,673 9,781 7,174 16,368 14,516 14,916 MLFD 15,373 12,501 10,371 8,836 9,207 7,533 Total Routine Expenditure 55,465 56,441 56,442 67,091 68,479 68,047 Special Expenditure1 Input subsidies MAFC 54,963 56,902 39,893 47,858 97,014 96,900 Input Subsidies MLFD 332 149 26 127 106 37 NFRA Grant 54,657 74,383 28,134 42,423 110,400 111,254 Other Transfers 50,761 22,436 24,269 32,432 30,596 35,401 Total Special Expenditure 160,714 153,870 92,323 122,839 238,115 243,592 Total MAFC and MLFD Recurrent Expenditure 216,179 210,311 148,765 189,930 306,594 311,639 Source: ASR-PER, March 2015 (based on actual and budget estimates for various years). 36. With regard to LGA expenditure, Table 2 shows that the levels of district spending account for a significant proportion (above 60%) of total routine expenditure. However, when compared to agricultural GDP, total routine expenditure (i.e., spending at central level plus district level recurrent and development spending) amounts to only 1.2% to 1.7% of agricultural GDP. Furthermore, this proportion is declining because agriculture’s contribution to GDP is growing while public expenditure on agriculture stagnates. In addition, extension and technical services account for a substantial proportion of district spending. Table 2: Routine expenditure on agriculture and as a proportion of agriculture GDP 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual * Estimate Estimate Central recurrent routine expenditure 55,465 56,441 56,442 67,091 68,479 68,047 Districts—recurrent 37,098 48,365 58,652 Districts—development 69,631 56,227 34,909 Total (TSh million) 163,170 161,034 160,652 Agriculture GDP (TSh billion) 9,429 11,675 13,780 Recurrent routine expenditure as % of Agriculture GDP 1.7% 1.4% 1.2% Source: ASR-PER, 2015 (Budget Estimates for central level expenditure & PMO-RALG district spending). 37. Technology-enhancing expenditure is a significant component of the MAFC budget with expenditure on research, plant breeding, mechanization and irrigation services absorbing between 40% and 50% of the total expenditure excluding NFRA grants and input subsidies (Table 3). Nevertheless, technology- 26 ‘Special Expenditure’ is defined as grants to NFRA, spending on input subsidies, and transfers to other government agencies and international organizations. 20 Agricultural Sector Development Programme II (ASDP-II) enhancing expenditure is still very low and almost negligible (0.3%) in relation to the crops sector’s contribution to GDP. Table 3: Technology enhancing expenditure in MAFC (TSh million) 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 Actual Actual Actual Actual Approved Approved MAFC Personnel 16,953 18,490 21,659 25,167 26,328 27,169 MAFC Operation Charges excluding input subsidies 11,673 9,781 7,174 16,368 14,516 14,916 MAFC Transfers excluding NFRA grants 45,606 19,033 19,454 17,388 19,988 28,332 Total MAFC excluding input subsidies and NFRA grants 74,231 47,303 48,288 58,922 60,831 70,417 Of which technology enhancing 17,076 18,263 22,400 28,641 29,073 27,953 Technology enhancing as % of MAFC excluding input subsidies & NFRA grants 23.0% 38.6% 46.4% 48.6% 47.8% 39.7% Source: ASR-PER, March 2015 (based on Budget Estimates for various years). 38. With regard to the estimate of agricultural expenditure as a proportion of total government expenditure, the ASR-PER study was only able to determine ratios for recurrent expenditure. Due to lack of adequate and reliable data on spending by development partners, it was not possible to accurately estimate ratios for both capital and recurrent expenditure. The results of the ASR-PER analysis show that routine recurrent spending on agriculture amounts to around 2% of total recurrent spending by government. If expenditure on NFRA support and input subsidies are also included, spending on agriculture as a share of total recurrent expenditure ranged from 3.0% to 3.7% (excluding debt service) between 2010/11 to 2013/14 (Figure 9). The increase in the agricultural budget for 2013/14 is due entirely to increased spending on NFRA and input subsidies. Figure 9. Recurrent Agricultural Expenditure as Proportion of Total Recurrent Expenditure Source: ASR-PER, March 2015 39. Public expenditure on agriculture in Tanzania is therefore very low and, even if NFRA grants and input subsidies are included, agricultural spending as a proportion of total government budget is well below the target 10% envisaged in the 2003 Maputo Declaration. In addition, as a signatory of CAADP, Tanzania is expected to change both its investment pattern and meet some of the key principles of the programme, namely “pursuing an average of 6% annual agricultural sector growth at country level, and allocating 10% of the national budget to agricultural development”. To achieve these goals, a substantial increase in investments in sustainable agricultural development is therefore required, and it is anticipated that programmes such as ASDP II will provide a framework to facilitate rapid expansion of agricultural investment. 21 Agricultural Sector for Industrial Development 40. Revenue collection and budget execution (Table 4). In 2012/13 actual revenue collected amounted to 92% of the total estimate, while total recurrent expenditure was 95% of the planned budget. In 2013/14 the rates were even lower with revenue collection and budget execution achieving rates of only 88% and 87% respectively. With the exception of the MLFD execution rate for recurrent expenditure in 2013/14, the budget execution rates for MAFC and MLFD were generally lower than the overall execution rates. It should, however, be noted that the low budget execution rates for MAFC are highly influenced by the disbursement rate for NFRA grants and input subsidies which account for most MAFC recurrent spending. Execution rates for routine recurrent expenditure of MAFC are usually higher than the rates for special expenditure. Table 4: Revenue collection and budget execution rates Overall MAFC MLFD 2012/13 Domestic revenue 92% Recurrent expenditure 95% Agriculture Central Level: Recurrent expenditure 84% 80% Development expenditure: Local 41% 48% Foreign 97% 80% 2013/14 Domestic revenue 88% Recurrent expenditure 87% MAFC and MLFD: Recurrent 71% 90% Development 82% 40% Source: ASR-PER, March 2015 (from 4th Quarter Budget Execution Reports 2013 and 2014). Note: The 2013/14 Execution Report does not distinguish between domestic and foreign expenditure. 41. Development Expenditure. With regard to development expenditure, the ASR-PER (March 2015) noted that “records about development expenditure in the agricultural sector are utterly incomplete”. The two main sources of data are available: (i) government budget documentation; and (ii) the aid management platform, a database that donors supply with their respective information. 42. Overall, the coverage of development aid in the government budgets remains poor. Donors contribute substantial funds through development projects, but a significant proportion of expenditure is not recorded in government budgets as off-budget spending; Non-Governmental Organization (NGO) expenditure is also not captured. A list of agricultural projects and their respective donors are indicated in the budget book, but the list is not exhaustive and does not show annual expenditures. Based on available data, the on-budget development spending by international donors is presented in Figure 10: about TSh 183 billion was spent by donors in 2011/12, with ASDP and AFSP being the major contributors to development expenditure. In the past two years, on-budget spending by donors in the agriculture sector declined and, by 2014/15, it was estimated that development expenditure would be TSh 97 billion, considering that AFSP was terminated in 2013/14. With regard to local development expenditure within the agriculture sector, Figure 10 shows that only TSh 16 billion was spent in 2011/12, but this spending substantially increased in 2013/14 and was projected to rise to TSh 72 billion in 2014/15. Local development expenditure reflects the spending at central level and the contributions of LGAs towards agricultural development spending are not included, but remain limited. 22 Agricultural Sector Development Programme II (ASDP-II) Figure 10. Agriculture Development Expenditure by Project – Foreign and Local Source: ASR-PER, March 2015 (from Budget Estimates Vol. IV for 2013/14 and 2014/15) III. ASDP II-DESIGN PROCESS AND PRINCIPLES A. Lessons Learned from ASDP-1 43. Unlike other sectors, public investment in the agricultural sector does not direct produce the expected results, but rather facilitates the private sector (farmers and commercial partners) to achieve the expected targets. Several lessons and experiences have been drawn from the implementation of ASDP-1 (and other related programmes/projects) and will guide the design of ASDP II, including27: (i) the potential efficiency of a Sector Wide Approach (SWAp)28 in agriculture when sufficient leadership, commitment and well-resourced decentralization of agricultural development planning and implementation can be well anchored; (ii) results orientation of local and national development planning, implementation and M&E need to be strengthened to achieve sustained productivity growth—through technology adoption in value chains that offer competitiveness and most favourable market prospects; (iii) focus resources on high impact areas, which beyond productivity, also strengthen upstream levels of targeted value chains, such as market linkages and facilitating access to value addition facilities, involving strengthened farmer organizations and facilitation of their participation in marketing and value addition; (iv) sustainable irrigation development with robust planning and management systems throughout the cycle to aid 27 Adapted from ASDP-1 evaluation (June 2012) and other evaluations of other on- and off-budget agricultural sector support projects. Further elements are extracted from the ASDP Implementation Completion Report (Draft version early 2014). 28 IFAD Country Programme evaluation which recognized ‘reduced programme management costs as compared alternatives fielding separate projects and reduced transaction costs for the Government and development partners’ … allowing thus for a higher investment rate at farmer level. (Source: IFAD Country programme Evaluation Dec 2014 Unedited Final Version, p. 71). ASDP-1 also contributed to harmonized mechanisms and adhered to the principles of the Paris Declaration and the Accra Agenda for Action towards strengthened country ownership. 23 Agricultural Sector for Industrial Development appropriate infrastructure development, water resource management, professional and institutional management of the schemes and access to services and inputs; (v) champions at national and local level for adequate planning and funding mechanisms to promote private sector participation, supported by appropriate mechanisms; (vi) the design of the M&E framework should be based on national statistical surveys and the Agricultural Routine Data System (ARDS) enabled to produce timely information to measure programme achievements; (vii) improved access to seeds and fertilizers towards increased adoption rates and productivity and strengthened sustainability of productivity gains. 44. The following are some of the key lessons learned from ASDP-1 implementation over the last six years. The performance of the ASDP, though not without challenges, has shown that:29 a) A sector-wide approach in agriculture is possible where sufficient political and donor commitment is in place, and where a well-resourced decentralization policy is pursued on to which local level agricultural development planning and implementation can be attached. It also clearly demonstrated that successful implementation requires strong sector leadership at various levels and unwavering alignment of development aid to this approach. b) Thinly spread resources result in fragmented results/impacts, generally difficult to measure. ASDP was launched as a national programme covering all districts in Tanzania Mainland. Initially, one of the options considered was a phased implementation, covering a few districts at a time. In hindsight, because of the scale and complexity of implementing a new programme nationally, phasing may have been a better option. This would have allowed for better focus and complementarities between programme interventions, thus a better programme impact. c) Successful decentralization of agricultural sector support. The integration of the agricultural grants within the Local Government Development Grant (LGDG) and the decision to implement participatory district agricultural development plans (DADP) has been successful. The bottom-up planning processes has improved over time and has begun to provide a model for other sectors. Coordination between the then PMO-RALG and the ASLMs, and the efforts to conduct impartial annual assessments of the quality of DADPs has demonstrated that performance-based funding can be implemented using national planning and financing mechanisms. d) Increased productivity needs to be linked to value addition, marketing and increased farmer income. To date, ASDP-1 has focused mainly on basic production technology diffusion and processes. The lesson, based on field level studies, is that many farmers are already knowledgeable about basic production techniques, except perhaps for new crops and new practices that emerge periodically. What is lacking and gaining importance is focus on how farmers increase their incomes by engaging in more profitable activities including value addition and improved market efficiency. Generation and dissemination of basic technologies must be pursued together with greater consideration of supply chain linkages, especially expanded access to marketing. e) Little progress in farmer empowerment and organization strengthening. Creating and strengthening farmer organizations, or empowering farmers, is a topic covered in most projects and programmes, including ASDP. However, little qualitative or quantitative evidence exists of notable progress in this area, and thus achievement of limited progress in improving access to markets, as well as farmers’ productivity and incomes. In view of the focus on a value chain approach, this area deserves significantly higher levels of attention to overcome critical constraints along the value chain, through collective action. f) Lack of clarity about how the public sector should facilitate and enhance private sector involvement in the agricultural sector. Value chain development requires permanent consultation (from the design stage and on) and coordinated approaches with private sector actors (economic and associative) and with other international organizations. Coordination promotes joint efforts to develop private and public stakeholder involvement and cooperation, to enhance public capabilities for enabling strategic policy formulation and implementation. Furthermore, low participation of private agribusiness sector and private service providers (PSP) indicates the need for adequate planning and funding mechanisms at national and local level to support private sector involvement. 29 Adapted from: ASDP Evaluation June 2011 and follow-up studies on irrigation, extension etc.; ASDP ICR (Government report)—draft Jan 2014. 24 Agricultural Sector Development Programme II (ASDP-II) This should be done either within the ASDP II framework or through other emerging multi- donor initiatives, such as the Agricultural Marketing Development Trust or SAGCOT, etc. The involvement and capacity strengthening of private and associative (farmer organizations [FO], NGO and civil society organizations [CSO]) service providers would also allow for enhancing collaboration, alliances and increased efficiency30. g) Incomplete irrigation schemes and inadequate maintenance limit sustainability and farmers’ returns due to poor planning and management of irrigation development, inadequate resources and limited access to professional support services and productivity enhancing technologies. Irrigation is a major part of the ASDP-1 investment with about 112,500 ha upgraded and developed from 2006 to 2012 (18,920 ha per annum on average). Progress in this area has been significant and the capacity to implement larger investments has improved. Nevertheless, the irrigation schemes have encountered problems before, during and after construction and commissioning. These problems are documented and analysed, and lessons show that new investments need to be prioritized through feasibility studies to determine the most cost-effective irrigation infrastructure, area to be developed for irrigation and institutional organization and management of schemes. Most of the schemes supported by ASDP-1 were rehabilitation and improvement of existing schemes, but deferred maintenance, faulty designs and poor workmanship of irrigation schemes require corrections. Through careful planning and professional management, the prevailing vicious circle of build–deferred maintenance–rehabilitation can be broken. h) Harmonized sector M&E challenging to implement. The design of the ASDP M&E framework was based around costly national statistical surveys that were not timely in producing information about programme achievements. Equally, the planned annual services delivery surveys that would have given regular estimates of intermediate outcomes such as adoption of improved technologies were not implemented until 2008/9. In their absence, M&E reports were based on direct surveys of LGA authorities, and these have been incomplete and have contained inaccuracies. Finally, the set of short-list M&E indicators was modified over time and, while they reflect an active interest in regular results, the list now also fails to capture critical areas such as pace of empowerment, service reform and research outputs. There are several lessons to draw from the experience including: (i) the need to ensure that any national survey and ARDS has sufficient resources to provide necessary analysis and results on time; (ii) the importance of financing necessary planned annual surveys that provide critical annual performance assessments, for both outputs and outcomes; and (iii) above all the need to use M&E as a tool to track reform processes as well as measuring conventional benefits such as production and technology adoption. Overall, progress towards system alignment remained limited, while the broadening investment plan (TAFSIP) allowed for claiming policy/ strategic alignment. 45. Summary. The SWAp implemented through ASDP-1 appears as a strong case of effectiveness, impact and sustainability. The ASDP-1 Basket Fund was instrumental in setting in place a systems for delivery of infrastructure and extension services to smallholder farmers through LGAs, including for other stand-alone projects implemented. Interventions focusing on agricultural marketing and value chain development were hampered, constraining their effectiveness and efficiency and the sustainability of benefits. Furthermore, in recent years many donors and NGOs have supported several interventions in agricultural value chain development with the risk of inconsistent approaches and uncoordinated actions, which has limited their collective potential for rural transformation. There has been limited progress in supporting agricultural marketing and value chain development and the proliferation of uncoordinated activities in agricultural value chain development forms the risk of inconsistent approaches. Programmatic efficiency involves participative results-based programming and coordinated M&E systems to be streamlined into the agricultural sector statistics. Further investment in institutional capacity and methodology for enhancing outreach to farmers and other value chain stakeholders, and continuity and consistency in policies are key factors to ensure sustainability of results. 30 Adapted from IFAD-COSOP evaluation and analysis (Dec 2014). 25 Agricultural Sector for Industrial Development B. Key Agricultural System Challenges and Potential Drivers 46. Challenges and constraints to the implementation of ASDP II are summarized as follows: Table 5: Key constraints and thematic drivers Area Key constraints Thematic drivers Enablers - Poor implementation and coherence of existing policies - Inadequate coordination across agencies and weak links to regions and the local level - Inadequate data and data systems both for informing decisions and knowledge exchange - Inadequate infrastructure (crop and livestock production, energy, water, market access, etc.) - Inadequate land tenure systems, planning and enforcement - Weak link between public and private sector - Government to own, improve and effectively implement and monitor and evaluate appropriate policies Potential productivity - Ineffective national agricultural research systems and funding (insufficient personnel, qualification to respond to farmer needs) - Weak of adapted innovation products for farmers use (too generic and not farming systems and site-specific); - Weak links, mechanisms and mainstreaming of innovations between research–extension and stakeholders/implementers - Inadequate of improved genetics (livestock & fisheries) - Inadequate crop, livestock and fisheries research - Inadequate control of diseases and pests - Inadequate extension service equipment (transport, veterinary kits and services, extension kits) - Inadequate diagnostic capabilities (equipment and personnel) - High calf mortality rate for livestock due to tick and tick-borne diseases - Strengthen agricultural systems: • research and extension, and their linkages; • seeds, fertilizers, animal genetics and fingerlings • other input systems including mechanization • animal and plant health services • diagnostic laboratories (veterinary, etc.) Realized Produc-tivity - Inefficient seed and animal genetic systems - Inadequately staffed and capacitated extension systems - Low input use (fertilizer, seeds, machinery, feed fodder, vaccines, fingerlings, etc. - Inadequate rural platforms (Farmers Organization, Small and Medium Enterprises) to allow farmers to engage with governments and the private sector - Inadequate automated machinery for veterinary vaccine production - Inadequate development, use and monitoring of vaccines - Inadequate testing and quality monitoring of acaricides and other pesticides for vectors and pathogens control - strengthen the national livestock vaccine production - strengthen capabilities in testing and monitoring of acaricides and other pesticide Realized value - Huge post-harvest losses (25–35%, varying by crop and region) due to inadequate of agroprocessing expertise, facilities, storage and access to markets - Inadequate market information and research - low production indices for milk, meat and eggs - Low quality animals and animal products not able to compete on or access lucrative markets - Inadequate and weak enforcement of standards in food quality and safety. - Inadequate cooperative/union/farmer organization structures to ensure competitive pricing and reliable demand - Underdeveloped private sector, difficult regulatory system and weak market pull - Limited access to credit/finance and insurance - promote functioning input, output and credit markets - promote well functioning farmer organizations and cooperatives - strengthen enabling environment for private sector participation including promotion of PPP Cross-cutting: Gender, stakeholder improved governance, institutional capacity at various levels Adapted from BMGF (2014). 26 Agricultural Sector Development Programme II (ASDP-II) 47. Summary of Main Sectoral Constraints31 i. Inadequate policy environment and uneven policy implementation for achieving sustained and inclusive agricultural growth targets; ii. Low productivity levels and growth trends, including inadequate and sustainable access to key inputs (especially fertilizers and seeds, livestock genetic improvement (artificial insemination, embryo transfer), fingerlings, acaricides, vaccines and veterinary drugs); iii. Low genetic potential of the indigenous livestock and limited supply of improved breeds; iv. Weak delivery of agricultural support services for crops, livestock, fisheries, for improved technologies, crop and animal health services, regulatory services, etc.; v. Inadequate prioritized and quality public investments and low level of private sector investments in infrastructure (e.g., irrigation, rural roads, storage facilities, rural energy, market infrastructure); vi. Constraints to efficient and competitive agricultural marketing and agroprocessing, including limited value chain development; vii. Limited access to sustainable rural finance; viii. Inadequate land use planning allocation and secure tenure for land users; ix. Weak capacities to respond to climate change challenges; x. Weak institutional and human resource capacities and inadequate coordination among stakeholders, at national and local levels, including weak agricultural statistical system. 48. Strategic System “Drivers” for inclusive agricultural growth and reduced rural poverty32. To achieve the ASDS-2 goal, the programme objective for ASDP II will build on the lessons learned from ASDS-1 and ASDP-1 and focus on intensifying and operationalizing the following key drivers for sectoral growth transformation and rural poverty reduction: Policy and Regulatory Framework. Promoting effective multi-stakeholder formulation, consensus and effective implementation of key policy and regulatory reforms which can enable key productivity and value chain drivers of the sector transformation process. This process ensures expanded access to and efficient utilization of improved seeds, fertilizers, agrochemicals, vaccines, AI, fingerlings complying with sanitary and phytosanitary standards for ensuring competitive exports, marketing policies and regulations, enhanced value chain development, sustainable incentive structure for various actors, consistent with Tanzania’s market and competitive advantage. For the regulatory framework (legislation, institutional framework and human resources), the government is also working on, among others: (i) development of the conducive legal environment for strengthening farmers organizations and cooperatives societies; (ii) identification, demarcation and effective utilization of agricultural land; (iii) promotion of agricultural mechanization; (iv) facilitation contract farming for reliable markets; (v) price stabilization fund; and (vi) crop laws reforms. Production/Productivity and Trade. Increasing sustainable productivity of crop, livestock/fish and export commodities, would improve household nutrition and food security, but also marketable surplus. Increased competitiveness and farmer profitability will be enabled by: (i) sustainable productivity-enhancing technologies (including climate smart), facilitated through strengthened research–extension linkages; (ii) effective extension models using ICT; (iii) expanded and inclusive private sector role; (iv) sustainable access to rural financing; and (v) stronger and more effective farmer cooperatives and organizations which also would support and incentivize expanded marketed production, and value chain development. Inclusive Private Sector. Stimulating expanded and inclusive private sector-driven development and integration, facilitated by: (i) effective and viable public–private partnerships and public support services, and (ii) expanded rural infrastructure (especially small-scale irrigation, post- 31 The current ASDS-2 document includes a background subsection on a summarized SWOT for the agricultural sector. This assessment provides a rather homogeneous picture of the sector: an updated framework disaggregating constraint based on a typology of rural households would be most useful to further develop appropriate and differentiated strategies/measures. 32 To achieve inclusive agricultural growth and rural poverty reduction, relevant evidenced-based analyses need to be further sharpened and disaggregated, to better target specific farm household types, and/or agro-ecological zones articulated along key CVCs. 27 Agricultural Sector for Industrial Development harvest facilities veterinary infrastructure, storage facilities and rural feeder roads). This would contribute also to much needed expanded off-farm employment opportunities. Institutional Capacities and Coordination. Strengthening institutional development and effectiveness, including: (i) results-focused capacity development of key actors at national and local levels; (ii) more efficient, responsive transparent and accountable decentralization of key agricultural services and implementation; (iii) more effective and evidenced-based planning, budgetary and M&E systems at various levels, involving all stakeholders; (iv) enhanced nutrition and food security support services; and (v) enhanced processes and mechanisms for more effective coordination within ASLMs, other sector ministries/agencies, Development Partners, local government agencies/entities, private sector and other key stakeholders (including farmer and other commodity value chain organizations). C. The Process Towards ASDP II 49. Implementation of ASDP-1 has benefited from regular joint reviews that have led to a better understanding of the challenges as well as the strengths and weaknesses in the programme design and implementation performance. The annual Joint Implementation Reviews (JIR) involving ASLMs, development partners, agribusinesses, LGA representatives and farmer representatives at local and national levels have been used to track implementation progress and achievement of the programme objectives. This has allowed for timely removal of implementation bottlenecks and adapted programme adjustments. Information from regular contact between the supervising authorities and those responsible for the implementation is compiled by the ASDP Secretariat and PMO-RALG and this has informed design of ASDP II. Efforts have been made to incorporate the lessons learned in ASDP II design and to address the challenges encountered during implementation to avoid similar setbacks and impediments. ASDP evaluation carried out in 2011, the ASDP-1 Implementation Completion report (2014) and related studies and analysis were extensively used. Most of the reviews have made recommendations and elaborated ways to improve the relevance and effectiveness of the various interventions, as well as processes, procedures, guidelines used in the day-to-day implementation33. 33 Evaluation of the Performance and Achievement of the Agricultural Sector Development Programme, MAFC, 2011. 28 Agricultural Sector Development Programme II (ASDP-II) Figure 11: Tanzania landscape for agricultural development (2015–2024) Agric productivity & rural commercialization Irrigation, sustainable water & Land Use Management ASDS - 2 ASDP - II Examples of implementing initiatives Basket Fund AGRIC. SECTOR. DEVELOP. STRATEGY Sustainable Water and Land Use Management (NRM) Strengthening Sector Enablers at national, regional & local level Bread Basket Initiative NGO & Other initiatives Rural infrastructure, market access & trade Private sector development Food and nutrition security Disaster magmt, climate change and adaptation Policy & institutional reform & support Marketing infrastructure, Value Add & RuralFin. Support Prgm SAGCOT Commercialization and Value Addition (buil competitive CVC) Enhanced Agricultural Productivity and profitability ASDP II PROGRAMME/FRAMEWORK ASDS 2 KILIMO KWANZA TAFSIP Thematic Program Areas 50. Over the past years, extensive consultations were held with government officials, private sector representatives, civil society representatives, development partners and LGAs, to understand what worked and what did not work in the course of implementation. The overall ASDP-II framework encompasses all public funded (public good funded by the government, development partners and NGOs) activities in the agriculture sector, implemented under the guidance of the updated sector strategies (ASDS-II), taking into account relevant aspects of the TAFSIP framework. 51. The Basket Fund approach appeared rather challenging during ASDP-1; the clear separation of programm support from financing modalities encouraged most donors to earmark their contributions to specific activities. Although Basket Fund financing remains the preferred government financing modality, current non-earmarked contributions to a large extent originate from the Government of Tanzania, while all main donors have earmarked large parts of their on- and off-budget contributions. Earmarking appears to be a non-viable solution for financing core sector-wide functions within a harmonized and aligned investment programme, including coordination and M&E. 52. ASDP II is a results-oriented sector programme for public support delivery. It serves as not only the main vehicle for the implementation of the sector strategy (ASDS II), but also sub-sector policies and development programmes (crops, livestock, marketing, food security and nutrition, private sector, etc.). The formulation framework (Figure 12) and its financing modalities (Figure 13) include key elements, such as: (i) orientation towards leveraging and catalysing inclusive private investment; (ii) close coordination between public-private-partnership in areas of high potential (SAGCOT) , as pilots that can be up-scaled in the framework as a whole; (iii) strengthened sector coordination (common planning and budgeting, joint monitoring and evaluation) for increased accountability of all actors, at national and local levels; and (iv) integrating different aid modalities and progressively aligning planning and implementation, and M&E procedures to strengthened country systems. 29 Agricultural Sector for Industrial Development Figure 12: ASDP-II design and formulation framework. ASDP II - Design Framework PDO: Increase agricultural productivity and incomes of smallholder farmers for priority commodity chains Agri-business and Farmer linkage • Processors • Traders/Exporters/transporters • Enterprise development support • Private Sector Capacity Development Support • MIS • Quality management and certification Institutions/Regulations/ Laws • Land laws/tax regimes • Legislations and regulations • FO empowerment & capacity development • Entrepreneurial, business and management skill • Financial Service Market Infrastructure • Roads • Electric Connection • Irrigation • Warehouse Agr. technology and Advisory Services • New and improved varieties/breeds • Improved practices • Farm machinery • Agro processing technology • Knowlegde/Technical Skill transfer, Advisory Services • Inputs • Post harvest management Smallholder Agriculture Commercialization Figure 13: ASDP-II financing modalities 53. The key role of the ASLMs, led by Ministry of Agriculture , is to promote coordination and harmonization across all development and cooperating partners investments in the sector, to provide a viable pathway out of poverty for the nation’s millions of small‐scale farmers, and to facilitate the road towards improved sector harmonization and alignment of partners to drive equitable growth in a sound and common framework. Including by stimulating inclusive private sector role and investments (including public–private partnerships—PPPs)34. 34 The concept of PPP in productive sector and socio-economic services entails an arrangement between the public and private sector entities whereby the private entity renovates, constructs, operates, maintains, and/or manages a facility in whole or in part, in accordance with specified output specifications. The private entity assumes the associated risks for a significant period of time and in return, receives benefits and financial remuneration according to agreed terms (PPP, 2009). 30 Agricultural Sector Development Programme II (ASDP-II) D. Key Design Principles for ASDP II 54. Consistent within the key features of ASDS-2, the following principles underline the design of the ASDP II programme. Box 1: Key Principles of the ASDP II Design Key principles of the ASDP II design • Priority focus on commercialization of sustainable small-scale farmers production systems by market orientation; • Priority focus on high potential Commodity Value chains(CVCs) in Agro-Ecological Zones (AEZ) - implement investments and commodities that create the greatest impact -agricultural yields, profitability, farmer improved livelihood, commercialization and industrialization • Enhanced involvement of all stakeholders, including farmer organizations and the private sector at all levels for enhanced partnerships and increased ownerships. This includes increased control of public resources by all CVC stakeholders at all levels for improved relevance and efficiency; • Farmer and local CVC stakeholders’ empowerment by capacity strengthening, organization strengthening • Pluralism in service provision: ASDP aims to provide a wider choice in service providers to increase cost-effectiveness, competition responsiveness of services (de-linking of public funding from service delivery). • Results-based resource transfers. Resource allocations to LGAs will be more transparent and equitable through adopting and extending the local government grant system. The incentive for LGAs to use their funds effectively will be promoted through annual assessments. However, all LGAs will be eligible to qualify for basic additional support especially to strengthen operational and capacity building funding to demonstrate adequate performance and capacity to join investment flows • Focused support to enhance private investments and public–private partnerships (PPPs) under control of CVC MSIPs: propose matching grants/contributions based on performance scorecards and agreed priority areas. • Integration with government systems: existing government financing and planning systems (the Medium-Term Expenditure Framework (MTEF), DADP, grant transfers) will be used and through increasing integration will build sustainability, strengthen alignment with government priorities and avoid unharmonized, project-based approaches with parallel implementation mechanisms. 55. The second phase of the government’s 10-year ASDP programme (2017/2018–2027/2028) addresses the challenges and gaps experienced in ASDP-1. The aim of ASDP II is to address critical constraints and challenges to sector performance and to speed up agriculture GDP, improve growth of smallholder incomes and ensure food security by 2025. The programme builds on and strengthens successful investments under ASDP-1, Consistent with the long-term and medium-term policy frameworks, the sector development strategy developed in ASDS-1 (2001), the signed sector investment plan (TAFSIP, 2011), the revised ASDS-II (2015) and key lessons learned from ASDP-1 implementation, the following key principles were taken into account and streamlined into the design of the ASDP II programme. 56. The ASDP II design reinforces smallholder commercialization focus with the view to support farmers to graduate from subsistence farming to semi-subsistence/semi-commercial status, practising farming as a business. This recognizes that food security is a necessary condition for escaping poverty, but it is not sufficient—household cash incomes must also increase from their currently very low levels. Smallholder farmers have to begin producing for the market and be supported to forge strong and dynamic linkages with commercial input and output supply chains in order to connect with a growing agro-industrial sector and expanding food demand from urban consumers. Whilst the focus will be clearly on the smallholder sub-sector, greater inclusive private sector participation will also be 31 Agricultural Sector for Industrial Development encouraged, both in commercial agricultural production and in marketing, agroprocessing and farm input supply chains. Investment in rural roads/infrastructure, agroprocessing, especially in grain milling and packaging and sustainable utilization of natural resources will get special attention to expand the market, especially for priority crops. 57. Results-based focused support. Based on lessons learned from ASDP-1, key innovations integrated in ASDP II include, among others, impact orientation and concentration of resources on high potential CVC within agro-ecological zones and selected districts to achieve results, and scale-up. While targeting market-oriented smallholders35, a phased approach is being proposed to build and consolidate impact. A phased approach is being proposed by building and consolidating impact on priority CVC in a limited number of districts (clusters) before gradual scaling up of support activities, based on various milestones and performance indicators. Districts not covered in the first phase will be covered in subsequent phases and therefore growth-inducing interventions will reach all regions and districts over time. 58. Productivity increase for sustainable national food security and nutrition, farmer income and economic growth. ASDP II addresses the challenge of food deficit areas by promoting surplus food production and quality (crops, livestock and fish) in districts that have the potential to do so. Food deficit or low potential areas will benefit from the surplus generated from selected priority districts (see complementary government interventions, including social safety nets), enabled by enhanced marketing policies and private sector marketing. The focus of the programme is to maximize food self-sufficiency, but also export of commodities for which Tanzania has a comparative advantage in regional and international markets. Priority is given to investments focusing on expansion of irrigation, development of rangelands, control of livestock diseases, aquaculture development, mechanization, research and development, access to improved agricultural technologies and related inputs and appropriate support services. 59. Increasing management of resources by beneficiaries. The ASDP-1 stressed the importance of increasing the voice of farmers/fishers in local planning and implementation processes and in increasing their decision-making and management control in the design and implementation of investments, and over the kinds of services that they need. Although some progress has been made in this regard, much remains to be done and ASDP II reinforces this principle through a more structured planning, implementation and M&E arrangements and supporting financing mechanisms. The ASDP II places greater decision-making control over resource allocations in the hands of farmer groups, cooperatives and agribusinesses based on transparent processes. 60. Pluralism in service provision. A further analysis of the lessons learned from ASDP-1 and experiences in neighbouring countries would be useful to develop and implement a clear strategy for the promotion of private and associative (FO, CSO, NGOs) service providers at different levels of targeted activities. ASDP II aims to push for a wider choice in service providers to broaden knowledge support by integrating agribusiness services delivered by the PSPs. Performance-based contracts for private agribusiness advisory service provision will enable linking of public funding from service delivery and complementing public technical services implemented by local government services. 61. Sustainability and diversification. ASDS II emphasizes the need to diversify crop and livestock production to increase farm incomes and to reduce risks in light of both production and price fluctuations. Under ASDP II, there will be a commodity focus, but intertwined with strategic diversification. While focusing on priority CVC, crop rotations and promoting intensive animal husbandry systems to use efficiently crop residues, sustainable soil and water management systems and efficient use of irrigation systems will be promoted. Appropriate processes and mechanisms will be introduced and strengthened to achieve market-driven diversification and sustainability. The expansion in irrigated agriculture opens up an opportunity for crop intensification, one of which could be diversification into high value crops, such as horticulture. Focus will also be directed towards developing livestock diseases free zones, improve water availability for livestock, improving access to grazing lands, improvement of genetic potential 35 Support for and disadvantaged/vulnerable farmers is important and should be considered under alternative safety- net supports. 32 Agricultural Sector Development Programme II (ASDP-II) of the existing stock, increasing supply of improved stock, commercialization of the livestock industry and aquaculture and fisheries development. ASDP II will, therefore, encourage such diversification with the aim of increasing and diversifying farm incomes, to use natural resources, including water, more efficiently and meeting increasing local and export market demands. 62. Food and nutrition security. Although ASDP II focuses on a limited number of CVCs, nutrition remains an area of concern, as little progress has been recorded on nutritional status over the past decade, especially in rural areas. In complementing specialized support programmes, ASDP II will contribute to improved rural nutrition mainly by: (i) agricultural research, especially breeding for high quality and food safety, although for proposed priority value chains, the scope remains relatively limited (e.g., quality protein maize, enriched rice varieties, beef and dairy breeds (meat, milk) and fish); (ii) support participative advisory services (e.g., Farmer Field Schools (FFSs)) combined with farmer education and access to information (at ward resource centres and village level and intensive use of Information and Communication Technology (ICT) for information diffusion); (iii) expanded access to seed diversification (including horticultural seeds, livestock breeds, fingerlings) through strengthened agrodealer networks and competition, supported by appropriate regulation; and (iv) food processing for improved nutritive quality in the value addition part of the value chain. The programme has built- in flexibility to accommodate interventions to improve the nutritional status of rural households and protect them from the impact of natural disasters, along with improving the capacity of institutions that provide services for sustainable productivity growth and quality. 63. Gender and youth mainstreaming. While it is recognized that gender and youth is a cross-cutting area, which needs to be addressed at all levels, sectors, and in both technical and management areas, the ASDP II contributes its share by undertaking both socio-economic36 and gender/youth analysis. The strategy will also ensure these issues are adequately covered in the design and implementation of programme interventions and activities. This will be done by ensuring that gender and youth mainstreaming is operationalized in all ASDP II interventions. The tools for achieving this are at the strategic level (the gender/youth strategy), and at the operational level (the activity plans of each district), or implementing entity, which will outline what systems and processes will be targeted and how. Differentiation of groups by wealth, vulnerability, age and possibly other socio-economic characteristics is required to ensure that more vulnerable groups also benefit from the program. Based on the analysis and content of mainstreamed gender and youth activities, ASDP II will ensure adequate support, and explore synergies by collaborating with other projects and programmes. 64. Resilience, including to climate variability and change. ASDP II interventions will be undertaken with climate change considerations factored into the interventions, including climate smart agriculture in sustainable landscapes and appropriate climate change mitigation strategies. Extremes in temperature and precipitation will be the focus of research and technology development, since climate change tends to manifest itself in these forms most of the time. Farmers’ adaptive capacities will be strengthened to ensure the impact is understood and integrated into their farming systems/activities. A menu of response options to mitigate the impact of climate change on agriculture, including conservation37 agriculture, will be developed, tested and shared. Capacity building programmes for FFSs, extension officers and subject matter specialists on current climate related issues will be developed, implemented and periodically updated. E. Scope, Focus and Phasing of the Programme 65. The scope and focus of the programme under ASDP-1 was national wide and interventions were in almost all agricultural sub-sectors and scales, depending on LGA prioritization and investment decisions. 36 Differentiation of groups by wealth, vulnerability, age and possibly other socio-economic characteristics is required to ensure that more vulnerable groups also benefit and are provided with adapted support. However, the main target of ASDP II is to promote the gradual marketing capacities of the small-scale commercial farmers (SCF), while most vulnerable farmers (i.e., those who are unable to be auto-sufficient) need to benefit from safety net like support (TASAF and similar). 37 See also ‘Save and grow’. FAO 2012. 33 Agricultural Sector for Industrial Development Under the ASDP II, the intervention will cover all districts in terms of public service delivery (basic support for capacity building, demand-driven advisory services, etc.), The investment coverage will focus on selected priority commodities in agro-ecological zones. Focusing of investments will increase the likely contributions of planned investments to agricultural growth, import substitution and food security and nutrition. The reasons for moving in the direction of both commodity and area/zones specific interventions are to: (i) increase sustainably the productivity and competitiveness of the priority CVC production systems; (ii) increase the volume and value of produce that enter the market channels for both domestic and export markets, and reliable raw material supply for local industries; (iii) allow for significant impact of investments, especially in infrastructure and other interventions in priority areas; (iv) finish/complete priority investments started under ASDP-1 (especially irrigation and other value addition and marketing infrastructures); (v) enhance economies of scale by improved access of commodity producers’ to agricultural inputs and financial services, and lower transaction costs for input/ output supply chains, as volumes and competition increase; and (vi) promote expanded investments by private sector, at farm and off-farm levels, especially in priority value chains. 66. Institutional capacity strengthening. The programme will focus on: (i) empowering and strengthening small-scale farmer organizations, towards enabling farming as a business; (ii) supporting agribusinesses linked and integrated with farmer production systems for markets and value chain development; (iii) strengthened public and private support services for enhanced use of improved technologies and agribusiness; (iv) development of markets (policies and infrastructure) and productive infrastructure; and (v) institutional capacity building, at various levels, for state and non-state actors. 67. Priority commodity selection. Using38 contributions to national food security, the food import bill and export revenues, and contributions to the value of agricultural production as criteria, few commodities emerged as critical for economic growth and poverty reduction. In terms of contribution to kilocalories of food intake by Tanzanians, maize, cassava, rice and pulses contribute about 53%. In the area of agricultural trade, tobacco (17.6%), cotton (14.5%) and coffee (14.1%) contribute about 46% of the export value. Wheat (31.4%) and palm oil (27.3%) form the main share of total food import value as shown in table 6. Table 6: Commodities coverage, agricultural production, trade and diet (2005–2010) Commodity Share of production value Share of export value Share of import value Share of kcal intake* Cashew nuts 1.2 6.7 0.0 0.2 Coffee 0.8 14.1 0.0 0.0 Cow milk 7.3 0.0 0.6 2.6 Maize 6.5 0.8 2.9 24.3 Pulses 10.6 7.5 0.7 8.5 Rice 5.2 n.d. n.d. 9.1 Cotton 2.9 14.5 0.1 n.a. Sugar 1.2 1.6 8.6 4.0 Wheat 0.2 1.4 31.4 5.9 Cassava 8.2 0.0 0.0 10.5 Livestock 12.0 d 0.1 d 0.6 1.6 Sorghum/millet 2.4 0.1 0.2 3.8 Tea 0.5 6.3 0.0 0.0 Bananas 12.7 0.0 0.0 4.0 Palm oil 0.0 1.6 27.3 3.3 Tobacco 1.3 17.6 1.1 n.a. Source: MAFAP (2013). Review of food and agricultural policies in the United Republic of Tanzania. MAFAP Country Report Series, FAO, Rome, Italy, p 62. 38 Based on a recent FAO study (MAFAF/SPAAA, 2013). 34 Agricultural Sector Development Programme II (ASDP-II) 68. In addition to the above criteria, by applying criteria of possibility for commercialization, availability of technology for improving productivity and profitability, and possibilities for scaling up and scaling out, the list of commodities that make up the priority list narrows down to a few. Table 7: Priority commodities in the AEZs39 & potential commodities phasing by region40 Agro- Ecological zone (old2 zones) Priority commodities Nutritionb Market density Donor density Crops Livestock &fish Cash crops Centre Semi &arid-(Unimodal)- (Dodoma, Singida, Shinyanga, Tabora) Sunflower/maize/ sorghum/millet, rice, potatoes, horticulture3 Meat—beef, hides/skin, dairy, goat, Poultry, fish Cotton, Tobbaco Worst Moderate Moderate Lake (Unimodal/ bimodal) – (Mwanza, Kagera, Mara, Shinyanga, Geita, Simiyu) Rice, maize, cassava, banana, potatoes, sorghum/ millet, horticulture Meat—beef, hides/skin, dairy, goat, poultry, fish Cotton, Coffee, sugar cane OK Good Low- Moderate. Northern Highland(Bimodal) – (Arusha, Kilimanjaro, Manyara) Maize, rice, pulses/ beans, potatoes, horticulture, banana Meat—beef, hides/skin, dairy, goat, poultry, fish/ aquaculture Coffee, Wheat Worst Good Moderate. Eastern Coast-(Unimodal/ bimodal)- Tanga, Dar es Salaam, Pwani, Mtwara, Lindi) Cassava, rice, maize, potatoes, oil seeds4, horticulture Dairy, beef, fish, poultry, goat, skin/hides Cashew, Sugar cane, seaweed, sisal OK - Worst Moderate. Moderate- High Alluvial Plains (floods, swamp)- Morogoro (Kilombero, Wami),Pwani (Rufiji coast),Mbeya( Usangu) Rice Sugar cane Good Moderate- High West-SW Highland(Bimodal) Rukwa, Kigoma, Kagera(Karagwe, Misenyi,Ngara) Maize, Horticulture, banana, pulses, potatoes, rice Poultry, beef, dairy, goat, fish Coffee, wheat, sugar cane OK Bad None Low Southern Highland (Bimodal) Mbeya, Iringa, Njombe, Morogoro Maize, Rice, potatoes, Horticulture Meat—beef, goat poultry, dairy, fish Coffee, sisal, Cocoa, Tea Worse Good High Plateaux (Unimodal) Tabora, West Rukwa/ Katavi, Mbeya, North Ruvuma, Morogoro, South Mwanza,Simiyu,Geita South Semi-arid Lindi, Mtwara Coast Cassava, rice Goats, poultry, fish Cashew, seaweed Worse Bad Low a Horticulture41 promotion for household nutrition and market supply forms a diversification option in most irrigated areas, but also as small-scale counter-season activity. b Nutrition, market and donor density: Results from overall Meta-analysis (BMGF, 2014) c Total number of households for 2014 calculated on the basis of the demographic data provided in the 2012 national socio-economic profile (2012): about 70% of households are rural and an average HH size is about 5. 39 Based on geographical position 40 Oil seed crop includes sunflower, simsim, palm oil, coconut, groundnuts 41 Horticulture includes vegetable, fruit and spice crops 35 Agricultural Sector for Industrial Development Table 8: Priority Commodity Value Chains in Agro-Ecological Zones/ clusters Agro- Ecological Zone Regions Targeted HHs Priority commodities Crops Livestock & Fish Cash Crops Central 715,000 (8%) Maize Tobbaco Meat : Beef Meat: Goat Oil crops Sorghum &Millet Poultry Horticulture Coastal 2,300,000 (25%) Rice Dairy Cashew Maize Meat: Beef Sugar cane Cassava Fish Oil crops Beans Sea weeds Horticulture Lake 2,100,000 Rice Meat: Beef Cotton Coffee (23%) Northern Highlands 1,035,000 (11%) Maize Dairy Coffee Meat: Beef Horticulture Banana South 570,000 (6%) Cassava Meat: Goats Cashew Oil crops Maize Poultry Fish Southern Highlands 2,395,000 (26%) Dairy Maize Cassava Sugar cane Horticulture and Banana Meat- Goat Fish Legumes & Pulses: Beans Fish Meat: Beef Poultry Tea/ coffee Horticulture Sugar cane Maize Potatoes (Irish and sweet) Rice 36 Agricultural Sector Development Programme II (ASDP-II) 69. ASDP II implementation of prioritized investments and commodities under AEZ. ASDP II implementation approach will be a “one- priority crop/product – one AEZ”. Regions will be “clustered” 42 so that service provision and technological recommendations can be channelled to similar production systems and rural household types43. Public service delivery interventions will cover all districts and will be supported by other programmes and projects that are funded by various multilateral agencies, bilateral donors and NGOs. District coordination mechanisms established by ASDP II using DADP will improve local coordination among all sector interventions, including private sector. 70. AEZ/ Cluster Selection Criteria. Selection of the AEZ/ clusters considered five criteria starting with the zone’s production level and importance. Selection considered high production of prioritized value chains, as a percent of national production. The selection also looked at the potential market demand for raw and processed products within the region and zone. Other criteria include the processing level/ existing processing capacity within the zone, Sustainable systems or contribution to sustainable local production systems, to household food security and income generation and potential growth - for productivity and value addition improvements, including local agribusiness development and increased agricultural exports. 71. Commodity value chain selection criteria. The selection considered the value chain’s contribution to food security and nutrition, impact to smallholder farmers/livelihood improvement, cost effectiveness/ financial redness, on-going projects to be completed first, contribution to the national development agenda (industrialization)- five years’ development plan (phase II) and local market and exportation potential. F. Priority setting and Focusing 72. Approach. For the purpose of focusing on required services in upstream and downstream production, production clusters will be established for selected strategic commodities as growth poles within each AEZ. Tables 7 and 8 illustrate the potential AEZ and related districts’ and regions’ priority commodities: the choice of commodities will be revisited with all local value chain stakeholders at the start and during the mid-term review of the programme. The cluster approach enhances delivery of essential services, exploitation of economies of scale, development of required infrastructure, bulking of produce, agroprocessing and reduction of transaction costs. A commodity cluster will be a coherent area comprising districts with a proven potential for that specific commodity as well as the presence of value chain actors (e.g., producers, traders, processors and service providers) meeting in a Multi-Stakeholder Innovation Platform (MSIP), and availability of basic market infrastructure. The programme will target maize, rice, sorghum and millet, cassava, horticultural crops, oil seed crops, cotton, coffee, sugarcane, cashewnuts, tea, potatoes, pulses, fish, dairy, beef, goat and sheep, poultry, banana, and seaweed, all strategic commodities or food security, import substitution and /or for export to the regional markets. 73. The selection of the content focuses on an adapted Opportunities and Obstacles to Development process used for many years in ASDP-1 and familiar to the LGAs for local-level investments. Through a value- chain approach, the programme will support access to and utilization of yield enhancing technologies (improved seeds, fertilizers, mechanization and water crop, livestock and fish production) as well as infrastructure and agribusiness services for marketing and value addition. The capacity of private sector actors, including farmer organizations and cooperatives, will be strengthened to improve stakeholder access to the required inputs, agroprocessing and marketing services. Supporting efficient and integrated input use to complement enhanced research and advisory services is a cost-effective response for increased productivity and farm income and preventing unsustainable subsidies. Broader access to adapted varieties and seeds, integrated soil fertility management and timely land preparation will also help farmers move towards sustainable agriculture and overcome risks, including those induced by climate variability and change. Gradual adoption of appropriate mechanization technologies for 42 See further details in attachment 1 for operationalization of cluster approach 43 See also typology of rural households. 37 Agricultural Sector for Industrial Development production and post-harvest operations will not only increase rural labour productivity, but also attract young entrepreneurs in the sector. 74. Phasing in and out concept/approach. The programme will focus on the priority investment areas for key CVCs in AEZs considering selected priority crop, livestock and fish commodities. Based on gained experience, support will be expanded from mid-term on to gradually cover high potential CVCs in three to six districts (cluster) selected in each AEZ, on the basis of criteria such as: (i) agricultural production potential for target commodities; (ii) productivity and production levels of target crops, livestock and fish by category; (iii) access to productive and marketing infrastructures (road, railways, electricity44 etc.); (iv) annual performance assessment of district investments; (v) historical background of beneficiaries contribution/involvement in development initiatives; (vi) availability of private sector supporting target CVC(s); and (vii) other ongoing initiatives (projects such as FTF, MIVARF, MUVI, AFSIP) in the areas to avoid duplication and maximize synergies. G. Approaches and principles for the ASDP II design. 75. ASDS-2 and lessons learned from ASDP-1 form the main building blocks for ASDP II. Seven proposed ASDS-2 Strategic Result Areas were mapped within four programme areas for the agricultural sector (crops, livestock and fish) development programme (ASDP II), as shown in Table 8. Table 9: ASDS-2 Strategic Result Areas & mapping of proposed priority programme areas ASDS-2. Strategic Result Areas ASDP II. Priority programme areas (or SO) . Expanded Sustainable Water and Land Use management for crops, livestock and fish & system resilience to climate change; irrigation expanded). P1: Sustainable Water and land use management for crops, livestock and fish & system resilience to climate change. SO2. Improved Agricultural Productivity and Profitability (crop, livestock and fish, through research, extension, access to input, and mechanization) P2. Enhanced agricultural productivity and profitability (crop, livestock and fish), food and Nutrition security improved SO3. Strengthened and Promote Competitive Value Chain (farmers organizations empowered; agribusiness and value addition promoted; access to markets and rural infrastructure improved) P3. Commercialization and value addition (market access, value addition, trade & private sector development) SO4. Strengthened Institutions, enablers and coordination framework (policy, regulatory and institutional framework enhanced; institutional capacity, knowledge management and ICT strengthened; food and nutrition security, and safety net improved; sector coordination improved; M&E and agricultural statistics strengthened) P4. Strengthening sector enablers (including policies,, CKM, ICT, Coordination and M&E) Promote & strengthen gender inclusiveness in the agricultural sector. 76. ASDS-2 Strategic Objectives are defined as: (SO1) Expand sustainable water and land resource management (for crops, livestock and fisheries) and promotion of climate change smart agriculture; (SO2) Improve agricultural productivity and profitability driven by improved research, extension, input access and mechanization; (SO3) Strengthen and promote competitive value chain development in the agricultural sector (crops, livestock, fisheries), driven by empowered farmers organization, improved value addition and enhance access to markets, finance and rural infrastructure; and (SO4) Strengthen institutional performance, enablers (policy and regulatory framework) and effective coordination of public and private sector institutions in the agriculture sector at national and local levels. 77. All expected ASDS-2 outcomes have been reorganized along the proposed four programme areas and further enriched by team and inception workshop discussions. Cross-cutting and cross-sector elements were also included, such as: (i) gender, balanced and equitable participation of men and women in 44 Rural electrification is still very low as household lighting and cooking by electricity are only 20.7% and 1.7% respectively (Population and housing Census 2012). 38 Agricultural Sector Development Programme II (ASDP-II) agricultural development; (ii) rural youth self-employment; (iii) HIV/AIDS, to reduce the spread and mitigate its impact; and (iv) improved governance and accountability. 78. Major public investment/support areas across proposed components were identified as: (i) research; (ii) extension/training, information services and knowledge management; (ii) farmer/stakeholder organizations; (iii) access to inputs; (iv) rural infrastructures; (v) access to rural financing; (vi) policy and regulatory framework; and (vii) coordination and M&E. Using this double-entry framework, public (ASLM departments) and non-governmental stakeholders identified priority investment/support actions (group of activities) enabling achievement of expected outcomes of proposed PAs, at each the national and local level (including intermediate regional level to accommodate coordination requirements). 79. Based on extensive discussions with key public and private sector stakeholders and ‘practicalities’ the ASDP II sector programme was structured around four components: (P1) Sustainable water and land use management (crops livestock and fisheries); (P2) Enhanced agricultural productivity and profitability; (P3) Commercialization and value addition (building competitive value chains); and (iv) Strengthening sector enablers and coordination (at national, regional and local levels). The main changes against former Ps were to add a component for strengthening sector enablers (policies, food security and nutrition, capacity strengthening, coordination and M&E). 80. Priority actions were discussed and consolidated, and related budgets were estimated and compared to current on-budget recurrent and development investments, mainly at national level. Bulk estimates for local level DADP investments were consolidated. Although large parts of proposals were promoting increased investments in ongoing actions, Ministry of Agriculture departments identified priority investment areas considered as key drivers for the agricultural sector growth and rural poverty reduction. These key drivers for ASDP II implementation (and priority changes against ASDP-1) are summarized as follows: a. Committed leadership and changed mind-set at all levels will enhance program delivery. b. Sector-wide coordination (results-oriented sector-wide planning, implementing and M&E) including all ‘public good’ programme and projects in the agricultural sector: (i) at national level, efficient coordination within ASLMs and between government systems and other sector support programmes and projects; and (ii) at local level initiatives, through participatory planning/implementation systems, capacity building and focused investments; c. Focus of local investments targeting prioritized commodity value chains (CVCs) with improved balance between sub-sectors in line with their comparative advantage in each AEZ and focused supports to district clusters, with gradual out- and up-scaling (prioritization criteria) and phasing to be defined. ASDP II will gradually increase investments at local level. This will be based on the principles of: (i) maintaining participatory planning/implementation systems and strengthening human capacities; (ii) implementing irrigation investments (under the District Irrigation Development Fund) already identified to a large extent for the next five years under ASDP II and completing ASDP-1 started schemes; (iii) enhancing investments in availing water for livestock and aquaculture farming45; and (iv) implementing focused DADPs investments around priority CVCs in selected clusters with gradual upscaling. For livestock, targeted beef and/or dairy priorities require further use of quality breeds adapted to key production systems, including agro-pastoralism, pastoralism or tethering. High productivity will also depend on other factors such as diseases control, which requires strengthening of diseases detection capacities (veterinary laboratory diagnostic services) and access to vaccines (Tanzania Vaccine Institute -TVI). d. Key thematic investment areas identified as main sector drivers and benefiting from a higher growth of budget support, including: (i) irrigation—remains a priority as also identified in ASDP II; (ii) 45 For livestock and fish development, the LSDP (2011) identified the following priorities: (i) livestock infrastructure; (ii) grazing-land development for forage and water for livestock; (iii) production of pasture seeds and fodder trees; (iv) livestock research, training and extension services; (v) genetic improvement of cattle and chicken; (vi) animal diseases control and establishment of animal disease free zones to facilitate international trade; (vii) availability and utilization of inputs/implements for livestock; (viii) conducive environment for private sector investment in livestock; and (ix) livestock statistics and marketing information system. 39 Agricultural Sector for Industrial Development research–extension linkages, including zonal/district driven adaptive research and AR4D liaison units; (iii) farmers access to enhanced technical knowledge (improved technologies) expanded private sector- driven input distribution networks (seeds/breeds/fingerlings, fertilizer, feeds, vet drugs and vaccines, etc.); (iv) expanded access to competitive mechanization services for production and post-harvest processing/ value addition; (v) reduction of post-harvest losses for crops and livestock (calf mortality); (vi) providing specialized private sector-driven agribusiness support services at regional/zonal level; and (vii) detection capacities vectors/pests/pathogens and access to quality vaccines. e. Use of modern information and communication technologies for efficient coordination, data collection, processing, dissemination, but also stakeholders access to up/downwards information demand and supply flows (i.e., technical, markets, M&E). f. Farmer empowerment and (higher level) farmer organization strengthening to consolidate engagement and ownership of rural development, driving towards improved livelihood, including strengthened economic associations (e.g., around local warehouses), cooperatives, strengthened internal information and technical services to their members. g. Enhancing sustainable production systems and use of natural resources by promoting conservation agriculture/farming, integrated soil water and fertility management (soil health systems), integrated pest management, livestock husbandry, keeping livestock based on the carrying capacity, etc. h. Use of integrated sector level outcome and impact evaluation using national agricultural statistics services from the National Bureau of Statistics (NBS) for effective implementation of the National Agriculture and Livestock Sample Census (NASC implemented every 10 years) and the Annual Agricultural Sample Survey (AASS) and ensuring sound and timely analyses of this information; i. Strengthened support to policies and regulations to facilitate harmonization and expanded involvement of an inclusive private sector and continued support to strengthening decentralization and local level capacities and ownership advocacy of such policies to be understood and win stakeholder support. j. Flexible and harmonized financing modalities and management to integrate on-budget (budget support, BF (preferred), earmarked and ring-fenced programmes and projects) and off-budget programme and budgets. Core programme elements such as coordination (planning, implementation, M&E), capacity strengthening at national and local level will need to be financed either by the Basket Fund (government and non-earmarked development partner contributions) and/or ‘voluntary’ contributions (e.g., 5%) from each (on- and off-budget) programme and project in the sector. k. Functioning governance, accountability, and administrative structures, systems, processes and procedures. There is need to have clear roles and responsibilities and authorities at all levels, with accountability systems focused on delivery. H. The Theory of Change 81. Solving ASDP 1 Challenges. The program has 4 components and several projects to implement for 5 years. This objective will be achieved through prioritization, clustering and sequencing the projects and activities. The selected pathway by the government is to implement projects by creating an impact and bringing positive change. Firstly, the Government will create the necessary enabling environment by implementing Component 4 followed by Component 3, 2 and 1. This is because the implementation above sequence will address the following: - i. Solving most of the ASDP I challenges and immediate challenges, ii. Creating an enabling environment for other components to function, especially the industrialization agenda and value addition (demand and supply), and iii. Aligning and sequence components and project in line with the priorities. However, this prioritisation will not affect implementation of other initiatives. This means the initiatives may be implemented sequentially or concurrently. Figure 14 Shows prioritisation and the theory of change. 40 Agricultural Sector Development Programme II (ASDP-II) Figure 14: Transformative Approach-Theory of Change Sector Enablers and Coordi nation Commer cialization and Value Addition Productivity and Profitability Sustainable Water and Land Use Management Increased productivity growth rate for commercial market- oriented agriculture for priority commodities Expanded sustainable water and land use management for crops, livestock and fisheries Higher productivity, commercialization level and smallholder farmer income improved livelihood, food security and nutrition. C 4 C 3 C 2 C 1 Improved & expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations Strengthened institutions, enablers and coordination frame work Also the program will focus of local investments targeting prioritized commodity value chains (CVCs) in line with their comparative advantage in each AEZ and with consideration of clusters (district clusters46) 82. ASDP II implementation plan, Sequencing and Scheduling. For implementation ASDP II components, and projects are sequenced and scheduled to create and bring greatest change and impact. The implementation plan, sequencing, scheduling process considered the potential for components and projects which will address immediate sectoral challenges, take advantage of opportunities, and bring positive change. Also, there is need to implement projects that create the necessary enabling environment (“Unclog the pipe and let the water flow”). Implementation will start with component 4 which creates the necessary enabling environment for both private and public sector to function including the small holder farmer. The details of the implementation plan, sequencing and scheduling are covered under Annex I. IV. PROGRAMME OBJECTIVE AND DESCRIPTION 83. The ASDP II programme (2015/2016–2024/2025) is imbedded in the Tanzania Long Term Perspective Plan (LTPP)47, MKUKUTA and ASDS -II underlying results chain. Building on lessons learned from ASDS-1 and ASDP-1, the programme focuses on intensifying and operationalizing in a coordinated and sequenced manner the key ‘drivers’ of sectoral growth and transformation towards inclusive economic 46 Districts with the same commodity in the same EAZ will form a CVC or district cluster 47 The Tanzania Long Term Perspective Plan (2011/2012–2025/2026) outlines a development path that is cast in three five-year periods each with a specific development agenda. The first five-year period aims to remove the economy’s growth constraints in order to unleash the growth potential of the country. In the second five-year period, the focus will be on nurturing an industrial-based economy whilst developing the country’s agriculture and agro-processing sectors to enable Tanzania to become the regional food basket. In the third period focus will be to boost exports of manufactured goods with sharpened competitiveness. The three phases are inherently interconnected, with the successful implementation of one being an imperative for the implementation of the other. 41 Agricultural Sector for Industrial Development growth and rural poverty reduction. Building on lessons of the first phase and linking to national and continental higher-level goals, the overall framework for the results chain has been defined in Figure 1548. Figure 15: Framework for ASDP II results chain Level 4: Investment Sub-Components and Activities Level 3: ASDP-2: Prioritized Investment Programme CAADP: Comprehensive Africa Agriculture Development Programme Level 1: Vision 2025 / MKUKUTA OUTPUTS OUTCOME IMPACTS Level 2: ASDS-2 Figure 16: ASDP II Objective, Strategy and Outcome A. Programme Objective 84. ASDS-2 goal. In line with Tanzania Development Vision 2025, the higher-level sector goal is to “Contribute to the national economic growth, reduced rural poverty and improved food security and nutrition in Tanzania”. Key ASDS-2 strategic objectives are to: (i) create an enabling policy and institutional environment for enhancing modernized competitive agriculture sector, driven by inclusive and strengthened private sector participation; (ii) achieve sustainable increases in production, productivity, profitability and competitive value chain development of the agricultural sector driven by smallholders; and (iii) strengthen institutional performance and effective coordination of relevant public and private sector institutions in the agriculture sector at national and local levels, enabled by strengthened resilience. 85. ASDS-2 targets are to be achieved by 2024/2025: (i) inclusive and sustainable agricultural growth of 6% per annum; (ii) reduced rural poverty (per cent of rural population below the poverty line from 33.3% in 2011/2012 to 24% in 2025; and (iii) enhanced food security and nutrition (e.g., per cent of rural HHs below food poverty line: 11.3% in 2011/2012 to 5% in 2025. 48 Adapted from ASDS-2 42 Agricultural Sector Development Programme II (ASDP-II) 86. Programme Development Objective (PDO) for ASDP II. The objective of the ASDP II49 is to: ‘Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food security and nutrition’. Figure 17 below shows the ASDP II ‘building’ with the main objective as the ‘roof’ of the building, the ‘walls’representing Components 1, 2 and 3 and Component 4 as the base or ‘foundation’ of the building. Figure 17: ASDP II Programme Objective and Components Component 1: Sustainable Water and Land Use Management Component 2: Enhanced Agricultural productivity and Profitability Component 3: Commercialization and Value Addition Objective - Expanded sustainable water and land use management for crops, livestock and fisheries Objective - Increased productivity growth rate for commercial market- oriented agriculture for priority commodities Objective 4: Sector Enablers, Coordination and M&E Objective - Strengthened institutions, enablers and coordination framework Objective - Improved & expanded rural marketing and value addition promoted by a thriving competitive private sector and effective farmer organizations ASDP II Objective Transform the agricultural sector towards higher productivity, commercialization level and smallholder farmer income for improved livelihood, food security and nutrition. 49 ASDP II is a 10-year programme starting from 2017/2018 and ending in 2027/2028. 43 Agricultural Sector for Industrial Development Figure 18: ASDP II Priority Investment Areas Component 1: Sustainable Water and Land Use Management Component 2: Enhanced Agricultural Productivity and Profitability Component 3: Commercialization and Value Addition 1. Land use planning and watershed management 2. Irrigation infrastructure development 3. Irrigation scheme management & operation 4. Water sources development for livestock & fisheries 5. Promote Climate smart argiculture (CSA) technologies and practices (5 investment areas, 12 projects) 1. Policy and Regulatory Framework and Business Environment Improvement 2. Strengthening organizational and technical capacities of existing and new small scale producer, trade and processing farmer organizations and cooperatives movement 3. Promote and strengthen gender inclusiveness in the agricultural sector 4. Improve and strengthen vertical (from PO-RALG to RSs and LGAs) and horizontal coordination between ASLMs. 5. Improved capacity and agricultural data collection and management systems 6. Management Capacities and Systems Improvement 7. Develop Agricultural Sector M&E System 8. Improvement of Capacity in all levels 9. Improvement of ICT for Agricultural Information Services and Systems 10. Provide microfinance services (10 investment areas, 12 projects) 1. Strentherning Agricultural extension, training and promotion/info services (crops, livestock and fisheries) 2. Improvement Access to crops, livestock and fisheries inputs and health services 3. Research and development 4. Strengtherning and promote agricultural mechanization (crop, livestock and fisheries) 5. Food and nutrition security improved (5 investment areas, 19 projects) 1. Develop market access for all priority commodities. 2. Develop market access for fisheries and livestock products. 3. Development of processing and value addition for Crop, livestock and fishery products (3 investment areas, 13 projects) Component 4: Sector Enablers, Coordination and M&E 87. The strategy is to transform the subsistence smallholders into sustainable commercial farmers by enhancing and activating sector drivers and supporting smallholder farmers to increase productivity of target commodities within sustainable production systems and forge sustainable market linkages for competitive surplus commercialization and value chain development. 88. The PDO will be measured by the following preliminary indicators50: (i) Agricultural sector growth (crops, livestock and fisheries) (ii) Variation in annual average yield of target commodities (crops, livestock/fish products) (iii) Variation in crop, livestock/fisheries income of beneficiaries (men/women/youth) (iv) Average share of the consumer price kept by farmer or average farm gate (real) prices for selected commodities (v) Variation in volume and value of total output marketed for selected CVC (vi) Variation in number of food (and nutrition) insecure households in PAs (average Household Dietary Score) compared to other areas (vii) Number of beneficiaries (or per cent by social groups and gender); (viii) Increase in volume of agricultural exports (ix) Increase in farm incomes (by different rural household types) 89. The programme focus is on public investments that curb constraints and enhance the identified priority drivers towards increased sustainable productivity and farmers profitability growth, targeting high potential CVCs in selected districts (district clusters), while strengthening institutional capacities of public and private sector stakeholders (platforms), especially at local level. The proposed programme will initially focus on high potential commodities in selected (high potential) areas and subsequently scale-up to further commodities and district clusters across all AEZs, considering their respective priority CVC, as outlined in Chapter III sections E and F. To upgrade outputs and profitability of farming systems, the main thrust is to support priority CVC development, with an emphasis on building business 50 These are indicative indicators: a detailed results framework is provided in Annex II (Results framework and monitoring). Proposed indicators will be disaggregated by gender (and youth) as applicable. 44 Agricultural Sector Development Programme II (ASDP-II) partnerships between smallholders, markets and agribusinesses. This will involve interventions that support smallholder farmer transformation into more market-oriented (commercial) producers, through increased and sustainable productivity, resilience to climate variability/change and local value addition by improved market efficiency to enhance income growth by aggregating outputs (such as warehousing) and agroprocessing. Key investments at national and local level will include infrastructures, support services, farmer51 and other stakeholder empowerment and organization, capacity strengthening, policy and regulatory reforms, but also institutional strengthening towards strengthened coordination and consolidated M&E of the agricultural sector at various levels. Beneficiaries include smallholder crop, livestock and fish farmers/fisher folk and their organizations and agribusiness stakeholders (value adding and marketing) that form joint ventures in selected value chains, with special attention to women and youth engaged in the targeted priority CVCs. Smallholder farmers with potential for increasing their productivity and marketing levels will be supported with access to technologies, while being empowered through FOs for enhanced market orientation and partnering with agribusiness. The number of direct beneficiaries will grow in waves, as stakeholder institutions will be strengthened to develop sustainable support capacities for key sector drivers. Table 10: Typology of rural households active in the agricultural sector against holding size Holding size (ha) Crops only Livestock Crops and livestock Total Number of households % Number of households % Number of households % Number of households % A. 0.01–0.50 484,585 14 47,773 80 181,083 8 713,441 13 B1. 0.51–1.25 1,045,293 31 4,198 7 481,164 22 1,530,656 27 B2. 1.26–2.50 1,191,939 35 2,352 4 720,494 32 1,914,786 34 C. 2.51–5.00 493,775 14 2,059 3 482,001 22 977,833 17 D. Above 5.00 206,481 6 3,463 6 359,670 16 569,614 10 TOTAL 3,422,072 100 59,845 100 2,224,411 100 5,706,329 100 Source: Adapted from the Tanzania Agriculture Sample Census 2007/2008 90. While involving the already market-oriented producers (category C and D, in Table 9) for further intensification, the programme will concentrate its support on developing the potential for intensification and market contribution of category B, which represents about two-thirds of the farming community. Category A represents the poorest section of rural dwellers, mainly subsistence farmers, who are constrained by limited land and access to labour. As net food buyers, this category has little potential for market-orientated agricultural production (except for specialized horticulture) and needs to be supported by social safety net programmes (e.g., TASAF) and also through professional capacity building, especially of youth, for integration into other rural (agribusiness) and urban sectors of the economy. 91. Small-scale commercial farmers (above 1.0 ha cropped area) form up to two-thirds of rural farming households: their attitudinal, risk bearing and investment characteristics are different from those with smaller holdings. At the lower end, they sell at least one-third of what they produce and look for opportunities to increase their farm income as they are already profit oriented, by taking some risk. Furthermore, their expenditure on labour intensive goods and services increase local employment and raise incomes (and food security) of the rural non-farm families. 92. Programme components. The programme has four interlinked components (see Figure 19): (i) Sustainable Water and Land use Management, including mainstreaming resilience of sustainable and smart farming systems; (ii) Enhanced Agricultural Productivity and Profitability by sustainable technology generation, promotion/use, food security and nutrition; (iii) Commercialization and Value Addition to build competitive CVCs; and (iv) Strengthening Agricultural Sector Enablers, including policy framework, , institutional capacity and coordination, and sector-wide M&E. 51 Farmers include crop producers, livestock keepers and fish farmers. 45 Agricultural Sector for Industrial Development Figure 19: ASDP II components and sub-components B. Priority Investment Areas (summary) 93. Investments to increase farmers’ productivity for crops, livestock and fisheries are the first priority towards increasing opportunities for commercialization within the frame of sustainable utilization of natural resources. Expansion of research and development, extension services, irrigation, water for livestock, pasture development, mechanization and improved access to crop/livestock/fisheries inputs will enhance efforts to increase productivity across the sector. Investments in improving the capacity of institutions and rural infrastructure (roads, electricity, facilities) will be needed to expand markets and ensure efficient support services for transforming the sector. ASDP II also integrates specific interventions to improve food security and nutritional status of rural households and to enhance the resilience of rural livelihood systems to mitigate the impact of natural disasters, including climate change. 94. To stimulate growth in the agricultural sector to attain expected levels of 6% per annum, increased public and private investments are required. The best results in terms of economic growth, reduction of poverty and food security are likely to be generated by balanced support for both the commercial and smallholder sub-sectors, focusing on the main commodities that are largely produced and consumed by the local population, along with efforts to help subsistence smallholders graduate to the ranks of small-scale commercial farmers (IFPRI, 2011). For ASDP II, investment activities have been grouped into programmatic areas along components and sub-components. Strategic priority investment areas are depicted in Table 11: 46 Agricultural Sector Development Programme II (ASDP-II) Table 11: ASDP II components and strategic objectives Components/programme areas Strategic priority investments Component 1: Sustainable water & land use management Sustainable integrated land and water resources use and management and increased resilience (irrigation, charco-dams & boreholes, land use planning, soil fertility management, pasture development, ponds/cages) Component 2: Enhanced agricultural productivity and profitability Increased productivity growth rate for commercial market-oriented agriculture for priority commodities (crops, livestock and fisheries value chains) Component 3: COMMERCIALIZATION and value addition (build competitive CVC) Expanding farmer access to rural value addition and competitive marketing systems for priority commodity value chains, driven by an inclusive, strengthened and thriving private sector and effective farmer organizations. Component 4: Strengthening sector enablers at national, regional and local level Policy and regulatory framework Institutional capacity strengthening, communication & knowledge management. Food security and nutrition (including early warning and safety nets) Coordination (facilitate planning & implementation at all levels) Monitoring & evaluation (including agricultural statistics) 95. Implementation of prioritized investment in Agro-Ecological Zones (AEZ) and districts clusters. The program will focus on: (i) restoring basic agricultural capacity building and extension funds to prepare human and institutional (MSIP) capacities to sustain sector investments; and (ii) gradual building-up of focused local investments on priority commodity value chains (CVC) in ecological zones. The program will focus on investments that curb constraints and enhance the identified priority drivers towards increased sustainable productivity and farmers’ profitability growth. The program will target in high potential Commodity Value Chains (CVCs) in Agro ecological zones (AEZ)52. The agro- ecological zones and districts to be involved in ASDP II implementation are indicated in Table 12: Table 12: Agro-ecological zones and districts to be involved in ASDP II AEZ Regions Districts 1 Arid Lands (unimodal 400-900 mm) Mara (E) Musoma TC, Musoma DC, Serengeti, Bunda, Tarime, Rorya Dodoma (E) Masai Steppe, Tarangire, Mkomazi, Pangani and East Dodoma Simiyu Bariadi DC, Maswa, Meatu, Itilima, Busega Manyara (E) Kiteto, Simanjiro 2 Eastern coast Lindi Lindi DC, Lindi MC, Liwale, Ruangwa, Kilwa, Nachingwea. Mtwara Mtwara T.C, Mtwara DC, Masasi, Nanyumbu, Tandahimba, Newala Tanga Handeni, Kilindi, Korogwe DC, Lushoto, Muheza, Mkinga, Pangani, Tanga, Korogwe Pwani Kibaha TC, Kibaha DC, Bagamoyo, Mafia, Mkuranga, Kisarawe, Rufiji Dar-es-Sal. Ilala, Kinondoni, Temeke 3 Northern Highlands (bimodal) Arusha (S) Arusha DC, Meru, Arusha MC, Karatu, Monduli, Longido, Ngorongoro Kilimanjaro (N) Moshi DC., Hai, Siha, Moshi M. C, Mwanga, Rombo, Same Manyara (E) Babati TC, Babati DC , Hanang, Mbulu 52 The priority commodities per AEZ are as indicated in Table 7, 8 and 21 47 Agricultural Sector for Industrial Development AEZ Regions Districts 4 Plateaux (unimodal) W: Tabora, Rukwa/Katavi Tabora M C, Igunga, Nzega, Sikonge, Tabora (Uyui, Urambo Mpanda DC, Mpanda TC, Mlele Mbeya (N) Chunya (partie N) Ruvuma + Morogoro (S) Songea T. C, Songea D.C, Namtumbo, Mbinga, Tunduru, Ulanga (Mo) Mwanza Mwanza CC, Magu, Geita, Ukerewe, Missungwi, Sengerema, Kwimba Geita Geita DC, Chato, Bukombe, Nyang’wale, Mbogwe 5 Central semi-arid (unimodal) Dodoma (W) Kondoa, Dodoma MC, Mpwapwa, Kongwa, Bahi, Chamwino Singida Singida DC, Singida MC, Manyoni, Iramba, Ikungi, Mkalama Shinyanga Shinyanga M C Shinyanga DC, Kishapu, Kahama Morogoro Morogoro M C, Morogoro DC, Mvomero 6 Southern & highlands S-Mbeya Mbeya MC, Mbeya D. C, Mbarali, Kyela, Rungwe, Mbozi, Ileje, Chunya (S) S-Iringa Iringa DC, Kilolo DC, Iringa (S), Mufindi, Njombe Makete, Ludewa, Njombe TC, Njombe DC. Makambako, Morogoro NW Kilombero, Kilosa 7 South Western highlands Rukwa Sumbawanga DC, Sumbawanga TC, Nkasi, Mpanda DC, Mpanda TC 8 Western highland Kigoma Kasulu, Kibondo, Kigoma DC, Kigoma TC Kagera (bimodal) Biharamulo, Bukoba D. C, Misenyi, Bukoba T. C, Karagwe, Muleba, Ngara Source: ASDP II BF (2013) - ARD; Tanzania CSA Program (2015) and de Pawn, 1984 C. Component 1: Sustainable Water & Land Use Management (crops, livestock and fisheries) 96. Strategic objectives, outcomes and related indicators for the sustainable water and land use management component are defined as follows: 48 Agricultural Sector Development Programme II (ASDP-II) Table 13: ASDP II Component 1: Related ASDS-II specific objectives and outcomes Spec. objective Outcomes Outcome indicatorsa Comp 1. Improved and sustained integrated land and water resource use and management (E.g. for irrigation, water for livestock, cropped land, pastures, ponds/cages, and soil fertility Expanded sustainable water and land use - Percentage increase of schemes practicing sustainable irrigation - Percentage increase of livestock keepers with access to permanent water sources (natural or man-made) - Percentage of modernized irrigation facilities with professional management - Improved rangelands (ha) with sustainable pasture and water for livestock - Increased area (ha) under fish farming - Increased number of mariculture farmers - Percentage increase of stakeholders implementing CSA technologies Improved resources management for crops, livestock, and fisheries 1.1Improved Land Use Planning and sustainable Water Shed and Soil Management - Percentage increase of districts with land use plans - Percentage increase of villages with land use plans - Percentage increase of watersheds with integrated management plans - Additional area (ha) under improved agricultural production - Percentage increase in water quantity for agricultural production 1.2. Integrated Water Use and Management for Crops/Irrigation and Livestock/ Fishery Development - Additional area (ha) under improved irrigation - Cropping intensity for irrigated crops - Additional permanent water points for livestock - Increased area (ha) under fish farming - Increased number of mariculture farmers 1.3. Mainstreamed resilience for climate change/ variability and natural disasters - Percentage increase of farmers (crop, livestock and fisheries) adopting CSA technologies and practices - Proportion of LGAs with mainstreamed CSA in their DADPs - Proportion of ASLMs with mainstreamed CSA in their plans - Percentage decrease of households who are under the risk of floods or drought 97. Component 1 is sub-divided into 3 sub-components : Component 1. SUSTAINABLE WATER AND LAND USE MANAGEMENT S/c 1.1: Land use planning and sustainable watershed and soil management s/c 1.2: Integrated water use & management for crops/irrigation & livestock/fishery development S/c 1.3: Mainstreaming resilience for climate variability/change and natural disasters 49 Agricultural Sector for Industrial Development Sub-component 1.1: Land use planning and sustainable watershed and soil management 98. Increasing human and livestock populations Threatens land use. There has been an expansion in the cropped area in recent years and increasing conflict levels between farmers and livestock keepers hinder development of the sector. Promotion of land use plans and their enforcement is thus critical for sustainability of the sector. This strategic area requires a multi-stakeholder approach for sustainable land use for crops, livestock (pasture and rangeland) and fisheries: (i) country-wide national and village level land use plans in collaboration with the Ministry of Land, Housing and Settlements Developments, PO-RALG and the Tanzania Investment Centre (TIC—land banks); (ii) sustainable pasture and range management measures to prevent or minimize land degradation and desertification and mechanism for resolving land use disputes; (iii) improved soil fertility management by adapted land tillage and sustainable use of fertilizers; and (iv) enhanced fish farming by integrated inland aquaculture. 99. Although there are still areas of arable lands which are not used for crop and livestock or fish production, most of the incremental production from the smallholder sub-sector is expected to come from productivity improvements. Additionally, in the intensive commercial sector, investments to expand the utilization of land resources will also be a source of growth. Area expansion needs to be accompanied by measures to safeguard customary property rights. 100. ASDP II is expected to spearhead efforts to conserve and utilize Tanzania’s natural resources in a sustainable and productive manner, by adopting sustainable land and water management systems. Measures to strengthen the policy and legal framework for utilization of land and water resources utilization will also include developing institutional and technical capacity as priority areas. Equally important is the prevention and reversal of arable and rangeland degradation in the rainfed areas, which cover most of the country. Soil fertility depletion and erosion are already threatening the sustainability of arable agriculture. The damaged areas need to be rehabilitated to prevent further deterioration through better soil health management, introduction of soil conservation measures, reforestation, appropriate conservation agriculture and sustainable pasture management methods. Land use planning and watershed management 101. “Land use planning is a systematic and iterative procedure carried out in order to create an enabling environment for sustainable development of land resources which meets people’s needs and demands. It assesses the physical, socio-economic, institutional and legal potentials and constraints with respect to an optimal and sustainable use of land resources, and empowers people to make decisions about how to allocate those resources” (FAO/UNEP 1999: 14). 102. Increasing scarcity of land requires land use planning for diverse purposes, all aiming to optimize land resource uses to avoid deteriorations and land use conflicts as well as other consequential problems such as famines and wars. Land use planning can be applied to support sustainable development within given areas (territorial development) or specifically to ensure the protection of ecosystem services, biodiversity and high conservation values (natural resource management, national park management, and buffer zone management). It can also help mitigate climate change or adapt to it, to prevent disasters or to be prepared for them, to ensure food security, to develop areas in post- conflict situations or in drugs environments or specifically to reduce land conflicts and improve land governance. It will also contribute to address land/resource tenure issues, avoid land ‘grabbing’ and mitigate its consequences. 103. In response to current constraints and challenges of development, the aim of this programis to optimize land use planning and land access for respective local population activities, including cropping and grazing lands (connected to water availability). Land use planning is cross-sector elements between crop and livestock and other uses, which allows integrating participatory spatial planning into local development planning. Besides national level facilitation, policy adaptation and technical support, the implementation of land use planning activities will mainly be integrated into local level investments implemented under AR4D activities and DADPs. Priority national and local investments/ projects are shown in Table 14. 50 Agricultural Sector Development Programme II (ASDP-II) Table 14: Prioritized activities in land use planning for crop and livestock development Investment/action areas Priority activities Land use planning and watershed management - Participatory land use planning and watershed management - Development and enforcement of by-laws - Capacity building for land use management - On- and off-farm run-off management (including adapted mechanization) - Conservation of marginal land areas - Area protection (afforestation, terracing, etc.)—communal land - AR4D activities/studies for optimal land use determination Agricultural land use management - Demarcation and titling of farmlands to increase security and promote investment - Establish and implement sustainable crop land management plans. - Promote appropriate soil and water management technologies and improved cropping practices Grazing land development: improved rangeland management and use in livestock production - Develop and implement sustainable rangeland management plans - Pasture improvement (seed/hay production, demonstration plots) - Strengthen early warning systems for timely information & mitigation strategies - Support environmental conservation in pastoralist communities Pastures development & forage conservation - Promote production and use of improved pasture & fodder tree species - Enrichment of in situ pastures (seeds) - Forage conservation (hay, silage, etc.) Vector and vector-borne disease control in the rangelands - Area wide integrated pest management techniques (ticks, tsetse and other vectors of veterinary importance) Investment strategies follow-upa Assessment of impacts and efficiencies of irrigation and rainfed water management investments a project management to be integrated in comprehensive M&E (s/c 4.5) Sustainable soil management and upscaling conservation agriculture53 104. Declining soil fertility, due to continuous cropping (without fallow) and low levels of fertilizer use for soil nutrient restoring is believed to be a key cause of low crop yields. Rangeland degradation threatens the livelihoods of pastoral communities, calling for better rangeland management, including drought preparedness and response, but also alternative forms of income generation to reduce grazing pressure. Sector support initiatives should aim to increase both productivity and production while keeping a balance between adapted productivity investments in high and low potential areas to fight rural poverty. To increase productivity levels sustainably, there is a need to promote appropriate technologies, including soil and water conservation, integrated soil fertility management, agroforestry, conservation agriculture techniques and other related indigenous knowledge. Furthermore, trade-offs between productivity and resource management will be minimized within sustainable agricultural intensification of adapted farming systems. 105. Integrated soil health management. The best yields are achieved when nutrients come from a mix of mineral fertilizers and organic sources, such as nitrogen-fixing crops/trees and organic matter (manure, compost). Integrated soil fertility management ensures that nutrients reach the plant when required and do not pollute natural resources, and save farmers’ money. Policies to promote soil health should encourage conservation agriculture (see s/c 1.3) and mixed crop–livestock and agroforestry systems that enhance soil fertility and encourage ‘reasoned’ site-specific and precision nutrient management. Soils rich in organic matter and biota are the foundation of increased crop productivity. 53 See also ‘Save and grow’: http://www.fao.org/ag/save-and-grow/index_en.html 51 Agricultural Sector for Industrial Development Box 2: Basic elements for better land husbandry—Integrated soil fertility management Promotion of an integrated and synergistic resource management approach embracing locally appropriate combinations of the following technical options: • Build-up of soil organic matter and related biological activity to optimum sustainable levels (for improved moisture and nutrient supply and soil structure) through the use of compost, farmyard manure, green manures, surface mulch, enriched fallows, agroforestry, cover crops and better crop residue management • Integrated plant nutrition management with locally appropriate and cost-effective combinations of organic/ inorganic and on- and off-farm sources of plant nutrients • Better crop management with improved seeds of appropriate varieties, improved crop establishment at the beginning of the rains, weed management and integrated pest management • Better rainwater management to increase infiltration and reduce runoff (erosion) so as to improve soil moisture conditions within the rooting zone, thereby lessening the risk of moisture stress during dry spells, e.g., box ridges) • Improvement of soil rooting depth and permeability through breaking of a cultivation-induced compacted soil layer (hoe/plough pan) through conservation tillage practices (sub-soiling, chisel ploughing or inter- planting of deep rooted perennial crops/trees and shrubs) • Reclamation where appropriate (i.e., if technically feasible and cost effective), of arable land that has been severely degraded by such processes as gullying, loss of topsoil from sheet erosion, soil compaction, acidification, alkalinization and salinization • For irrigated crop production systems, also improving water use efficiency: improved water distribution to minimize channel seepage losses, and mulching to reduce evaporation losses, and minimizing the risk of salinization by following good irrigation and drainage practices • For livestock production systems, better integration of crop and livestock production in both the cereal based farming and agropastoral systems • Adoption of people-centred self-learning and investigating approaches • Community-based participatory approaches to planning and technology development • Better land husbandry that offer farmers tangible economic, social and environmental benefits. Source: Strategic Investment Programme for Sustainable Land Management in sub-Saharan Africa (FAO, 2007) 106. Upscaling Conservation Agriculture. Conservation Agriculture is a concept for resource-saving agricultural crop production that strives to achieve acceptable profits together with high and sustained production levels while concurrently conserving the environment (FAO, 2007). Conservation agriculture relies on three key principles: (i) practising minimum mechanical soil disturbance (minimum tillage); (ii) creating and maintaining a permanent organic soil cover; and (iii) practising crop rotation with more than two species. The main activities proposed are centred on: (i) creating awareness by information dissemination on integrated soil fertility management and conservation agriculture; (ii) building capacity of extension staff and farmers on conservation agriculture; and (iii) adapting policies and regulations for conservation agriculture, including for agricultural mechanization (equipment specifications in line with conservation agriculture). Besides national level facilitation, policy adaptation and technical support, conservation agriculture support activities will be integrated into local level investments implemented under DADPs. A range of extension tools will be deployed to train farmers and promote improved agricultural practices to sustainably increase staple crop yields by improved soil health and integrated soil fertility management. ASDP II will also facilitate farmers’ access to needed inputs (s/c 2.3), mechanization equipment for production and post-harvest (s/c 2.4) and related financial services (s/c 4.6.). Sub-component 1.2 Integrated water use and management for crops/irrigation and livestock/ fishery development 107. Efficient and inclusive water use for irrigation, livestock and fishery. Expected strategic interventions and innovations are: (i) investment in irrigation to increase productivity by targeting the prioritized areas with high return potential; (ii) strengthen irrigators organizations for better operation and management of the infrastructures and resources; (iii) further strengthen backstopping services for LGAs and Irrigators Organizations; (iv) implement coordinated water resource planning and management in watershed/catchment areas; (v) enhance efficiency of water utilization; (vi) encourage private sector to invest in irrigation development; (vii) enact and enforce laws and regulations which protect irrigation potential and irrigation developed areas; (viii) continued efforts to ensure sustainable 52 Agricultural Sector Development Programme II (ASDP-II) water resources management and utilization through enhance observation of existing Environmental and Social Management Framework (ESMF) and strengthened capacities for integrated water resources management. 108. Conservation and sustainable utilization of water resources is a high priority. This will be achieved through watershed management initiatives, water harvesting, and improved smallholder and commercial irrigation and drainage systems to increase water use efficiency and ensure the sustainability of investments. These capital-intensive investments include irrigation infrastructure, equipment and integrated water management services. Investments target the improvement of traditional irrigation schemes, rehabilitation of deteriorated schemes and expansion of irrigated area in the identified potential areas. Increasing the efficiency of irrigation schemes by professional management schemes will improve farmers’ returns and sustainability of investments. Besides crop irrigation, specific investments will facilitate improved access to quality water resources for livestock and fisheries. 109. Increasing resource competition towards sustainable use. Along with climate change, water demand by multiple sectors (agriculture, energy, human consumption, watershed and wildlife conservation, etc.) is becoming more and more competitive. There is no assurance of continuous water allocation for the agricultural sector, the largest user of water resources. Policies will need to eliminate perverse subsidies that encourage farmers to waste water. Globally, the management of water resources would require improved water use efficiency through sustainable extraction rates, maintenance of infrastructure, land use planning and tracking environmental impact. Sustainable intensification requires smarter, precision technologies for irrigation and farming practices that use ecosystem approaches to conserve water, rainwater harvesting and supplemental irrigation of rainfed crops. Despite its high productivity, irrigation is under growing pressure to reduce its environmental impact: knowledge-based precision irrigation that provides reliable and flexible water application and wastewater reuse will be a major platform for sustainable intensification. Increasing rainfed productivity will depend on the use of improved, drought tolerant crop varieties and management practices that save water. Crop Irrigation Development. 110. The objective of irrigation development is to improve crop productivity and sustainable returns for small- and medium-scale farmers on an expanded irrigated area. This support will include: (i) irrigation development planning and professional management for intensification; and (ii) irrigation infrastructure development, including rehabilitation and expansion of existing irrigation infrastructure. Under ASDP-1, irrigation was given high priority with a major budget share. As a result, the increase in developed irrigated area by about 100,000 ha was one of the main ASDP-1 outputs. At local level, demand-driven support for scheme development was incorporated into DADPs and funding was sourced from the benefiting farmers. In addition, the support was channelled through the ASDP- 1 District Irrigation Development Fund. At national level, larger and more complex inter-district irrigation infrastructure was funded using the National Irrigation Development Fund (NIDF). 111. Although the average cost per irrigated hectare appears comparable to or lower than corresponding costs in sub-Saharan Africa, there is room to reduce infrastructure costs and to increase water use efficiency. The impact assessment study54 for ASDP-1 pointed out that cost reduction is an issue that needs to be tackled under ASDP II. Hence, a comprehensive strategy should be adopted that will lead to improved design and completion of irrigation infrastructure, aiming at increased water use efficiency. The cropping intensity of the irrigation schemes was low, as only 25 per cent of the area irrigated during the rainy season was cultivated under irrigation during the dry season. Irrigator contributions for water fees and infrastructure maintenance were also low. 112. Strengthen technical support services for irrigation development. At the national level, this activity will strengthen the capacity of the National Irrigation Commission (NIC) and Zonal/Regional 54 See Impact Evaluation of the Irrigation Investment of the ASDP. April 2013. 53 Agricultural Sector for Industrial Development Irrigation Technical Units (ZITSU) in: (i) strategic planning and prioritization for sustainable irrigation development, including water resources management and environmental and feasibility assessments; (ii) provision of technical support to improve planning and designing for sustainable irrigation investments; and (iii) monitoring of performance and payoffs to existing irrigation investments, including routine data collection and management for critical aspects of irrigation development. 113. Participation of the private sector in ASDP II irrigation works and services will be enhanced by: (i) building capacity of local contractors/engineering companies in works/service provision for irrigation development by ZITSUs (construction and rehabilitation skills); and (ii) contracting out supervision services to private engineering companies, as from the first year of ASDP II. Information systems for irrigation schemes will be improved and a data management system established to allow for detailed prioritization, planning and budgeting of investments. The NIC Human Resources Development Plan will be consolidated and prioritized in view of strengthening all levels of irrigation players through recruiting required professionals. 114. Strengthen Irrigation Organizations (IOs) for professional irrigation management for sustainable productivity. This activity will strengthen capacities of IOs55 for effective development and management of irrigation schemes, within the frame of the NIP (2010) and the “Comprehensive Guidelines (CGL) for Irrigation Scheme Development”. In close collaboration with LGAs, ZITSUs and NIC and jointly with the irrigation scheme’s leadership, ASDP II will: (i) carry out a review of all existing IO constitutions and by-laws to identify gaps and provide necessary improvements linked to the approved template for IO by-laws, the NIP (2010), the CGL for irrigation schemes, Operation and Maintainance under DADPs and the National Irrigation Act (2013); (ii) identify knowledge and skills gaps in the IOs, describe training needs, prepare a training programme, and assist in carrying out the required training, using appropriate resource persons and service providers; (iii) train IOs and other stakeholders on the National Irrigation Act (2013) and its regulations; and (iv) develop framework guidelines for the IOs for implementation of the existing legislation and appropriate scheme management. 115. ASDP II will improve the management of existing schemes through contracting professional irrigation service providers56 to strengthen, for one or two years, the capacity of IOs and provide them with technical support in: (i) effective scheme development/upgrade and management of scheme operations, including potential crop diversification; (ii) maintenance and management of irrigation infrastructure; (iii) efficient water resources management, including water saving techniques; (iv) enhanced access to technologies (System of Rice Intensification (SRI), etc.), information and advisory services; and (v) strengthened linkages to inputs suppliers, mechanization services, processors, output markets and financial institutions. During the 2015–2020 period, interventions under this activity will target: (i) 78 irrigated rice schemes that cover about 56,000 ha under irrigation development, benefitting about 70,000 smallholders in the southern agricultural corridor; and (ii) finalize rehabilitation of high priority schemes supported under ASDP-1. During the remaining years (2021–2025) the programme will consider scaling up this approach to rehabilitate and develop further priority irrigation schemes. 116. Irrigation Infrastructure Development57. Building on ASDP-1 and BRN targeted priorities, through financed expansion of irrigation development through new construction of small- and medium-scale irrigation schemes or the expansion of existing ones, targeting priority commodities in high potential areas. Full system ownership and professional management by irrigators and their organizations (water user, marketing, etc.) will be pre-conditions for efficient investment with increased payoffs and sustainable use of infrastructures. The support will include three main investment areas summarized, as shown in Table 15. 55 Farmer participation at IOs is mandatory for sustainable irrigation infrastructure and water management and maintenance. Farmer empowerment and organization strengthening (including formation of cooperatives— AMCOS and SACCOS) for sustainable value chain development are outlined in Component 3. Strengthened farmer organizations are key for all sector activities (irrigated or not) and their membership, free farmer option. 56 Market support service providers are discussed in value chain and agribusiness development. 57 Adapted from Irrigation investments under ASDP IBF and BRN (FAO-TCIA 2013). 54 Agricultural Sector Development Programme II (ASDP-II) Table 15: Summary of BRN and remaining ASDP-1 prioritized irrigation schemes (2015/2020) Irrigation Schemes Total number of irrigation schemes Total number uncompleted schemes for ASDP-1 Number of uncompleted or new schemes Total new schemes Total area (ha) Earmarked by JICA Total BRN— initiative Total 367 280 120 78 87 162,122 (i) Ongoing implementations by JICA and USAID Earmarked by JICA 120 77 107 13 43 51,964 Earmarked Global Accelerated Food Security Programme (GAFSP) 4 3 4 10,000 Earmarked USAID—under review 5 0 0 2 5 18,600 (i) Completion, rehabilitation and upgrading of remaining 63 BRN irrigation schemes (World Bank) Part of BRN—initiative not overlap (i) 59 21 (13) 63 39 25,879 (i) Completion, rehabilitation and upgrading of 179 ASDP-1 prioritized irrigation schemes ASDP-1 priorities, not overlap (i) &(ii) 179 179 0 0 0 52,243 Total area (ha) 59,558 /l 117. Implementation. Two guideline documents exist already58, and will be improved to address the weaknesses noted during implementation of ASDP-1. The methodology agreed and explained in the “Comprehensive Guidelines (CGL) for Irrigation Scheme Development” will be used. NIDF will finance larger and more complex irrigation projects—extending over several districts. The strategy for coherent irrigation development will be implemented using ASDP II as a framework, while contributing also to the regulatory framework for sustainable land and water management. Improved water management in rainfed agriculture 118. Most farmers are engaged in rainfed agriculture. Better seasonal rainfall forecasting and improved (surface) water management within intensified and resilient production systems will reduce farmers’ production risks. Furthermore, crops and varieties adapted to exploit limited soil moisture, cropping practices increasing soil water storage capacity and water infiltration, deep-rooting crops in rotations, and minimizing evaporation through organic mulching will be promoted. Improving the productivity of rainfed agriculture depends largely on improving husbandry across all aspects of crop management. This entails capture of runoff, reduced tillage, organic mulching and use of natural and managed biodiversity which are fundamental to lengthening the duration of soil moisture availability. 119. On-farm runoff management can be achieved in different ways. For example, the use of water retaining bunds in cultivated areas has been used successfully in transitional climates to extend soil moisture availability (even ‘irrigation’) after each rain event. Another example is the concentration of overland flow into shallow groundwater or farmer-managed water storage, can allow for limited supplementary irrigation. However, both these interventions have an impact on downstream users and overall river basin water management is required. There is a need for reinforcement of advisory 58 “Comprehensive Guidelines (CGL) for Irrigation Scheme Development” (under DADPs – 01/2010) and “Guidelines for Operationalizing District Irrigation Development Fund and National Irrigation Development Fund” (under ASDP—Revised 04/2011. Like in ASDP-1, communities will contribute 20% of total costs for irrigation development, and annually at least 5% of average returns for O&M. 55 Agricultural Sector for Industrial Development services to farmers dependent on rainfed agriculture, including a sharper analysis of rainfall patterns and soil moisture deficits to stabilize production from existing rainfed systems under climate change impacts. Extending the positive environmental and soil moisture conservation benefits of ecosystem approaches will often depend on the level of adapted farm mechanization (see s/c 2.4), which is needed to take advantage of rainfall events (see also Conservation farming/agriculture, s/c 1.2). 120. Policies and investment priorities. The relative contributions of rainfed and irrigated production investments at national level need to be assessed for different production systems in targeted AEZ. If rainfed production can be stabilized by enhanced soil moisture storage, the physical and socio- economic circumstances under which this can occur need to be well identified. The respective merits of low-intensity investments in sustainable rainfed crop production intensification and high intensity localized investments in full irrigation need careful technical and socio-economic appraisal against development objectives59. Proposed key action areas are proposed in Table 16. Table 16: Priority actions for improved water management in rainfed agriculture Investment areas Priority activities Extension & AR4D - Improved cropping practices for improved soil and water management (land husbandry) - Promotion of conservation agriculture Farm level interventions - On- and off-farm run-off management (including support for adapted mechanization development) - Enhanced soil coverage and organic matter level Landscape level interventions - Off-farm run-off management (including upper catchment) Policies & investment strategies - Assessment of impacts and efficiencies of irrigation and rainfed water management investments Water resources for livestock and fisheries 121. Over 70% of the livestock population are kept in semi-arid areas in northern, central and western parts of Tanzania. Water supply in pastoral and agropastoral areas includes the management of: (i) ground water by springs, shallow wells and boreholes; and (ii) surface water from streams and rivers, earth dams and catchments of rainwater harvest. Under ASDP-1 about 1,060 charco-dams and 40 boreholes, constructed between 2001 and 2010 at local level, have improved the availability of water for livestock and minimized the movements of livestock farmers and their livestock while searching for water. 122. The aim is to further increase water availability for livestock and fish by developing and maintaining reliable water sources. Priority investments are given in Table 17. Table 17: Priority activities livestock/fish access to water resources Investment areas Priority activities Developing and maintaining reliable water sources for livestock - Construct and maintain (charco)-dams, boreholes, etc. (Participatory planning, implementation and management with livestock holder organizations). - Pasture improvement (seed/hay production, irrigated production demonstration plots) Fish and other seafood farming development - Facilitate construction of fish ponds - Fish cages in lakes - Other seafood production Seaweed farming development - Facilitate promotion of seaweed cultivation in ocean 59 See also Save and grow (FAO 2013) 56 Agricultural Sector Development Programme II (ASDP-II) Investment areas Priority activities Fisheries resources development - Facilitate sensitization among fisher folk on Ecosystem Approach to Fisheries (EAF) issues - Facilitate conduct of fisheries frame survey - Conduct of border patrol - Improve quality standard of fish and fisheries products Budget note: Construction of 10 dams at TSh 1 billion each Sub-component 1.3: Mainstreaming resilience for climate variability/ change and natural disasters 123. Climate variability/change presents Tanzanian farmers and pastoralists with a new set of challenges. Although uncertainties about the nature and extent of change in the different AEZ of the country, there are indications that the frequency of extreme events may increase. This calls for an adequate level of preparedness in order to manage risks and mitigate their impacts on vulnerable households, including loss of assets. Efforts to mitigate the impact of disasters and climate change have been facing challenges60, including among others: (i) inadequate capacities to produce and disseminate early warning information on disasters; (ii) limited emergency response and mitigation measures including facilities; (iii) weak meteorological information and set-ups; (iv) lack of well-organized disaster maps focusing on major sources of disasters in the country (v) weak institutional integration of early warning system disaster response and preparedness; and (vi) weak financial capacity to arrest the shocks. 124. Climate smart approach61 adds a further dimension to the natural resource management issue. Due to the high level of agroclimatic diversity in Tanzania, climate change is likely to affect agriculture in many and varied ways during and beyond the time horizon of the ASDP II. The high level of dependence on rainfed agriculture makes Tanzanian rural households particularly vulnerable to climate change, which could increase the frequency of drought. There is a need to enhance the development of more robust and resilient farming systems that are able to adapt to a range of possible climate change outcomes. This climate smart approach will include the promotion of integrated (and synergistic) crop, livestock and fish production systems for sustained use of available natural resources. 125. Climate Smart Agriculture (CSA)62 is an integrative approach to address interlinked challenges of food security and climate change through: (i) adapting and building resilience of agricultural and food security systems to climate change at multiple levels; and (ii) reducing greenhouse gas emissions from agriculture (including crops, livestock and fisheries). In response to a growing threat of climate change, the ASLMs will collaborate with related ministries and take mitigation and adaptation measures. The required interventions include: (i) undertake research and exchange information with other research institutions (regional and international); (ii) improve water use efficiency in agricultural production systems; (iii) promote integrated land and soil management; (iv) facilitate implementation of ESMPs by farmers and livestock keepers; and (v) create awareness, build policy frameworks, strategies and programmes, strengthen institutions and enhance financing towards implementing climate smart agriculture development. 126. Save and grow!63 Sustainable intensification means a productive agriculture that conserves and enhances natural resources. Increasing food demand remains a challenge made even more daunting by the combined effects of climate change and growing competition for land, water and energy. 60 Evidence of Impact: climate smart agriculture in Africa. CTA 2014. 61 See expected potential changes induced by climate change for Tanzania in ASARECA study on East African Agriculture and climate change: A comprehensive analysis—Tanzania http://www.ifpri.org/sites/default/files/ publications/aacccs_tanzania_note.pdf 62 Adapted from ASDS-2 (September 2015) and Tanzania Climate Smart Agriculture Programme, coordinated by Ministry of Agriculture and the Vice President’s Office (2015–2025). 63 See also SAVE and GROW: http://www.fao.org/ag/save-and-Grow/. In a broad sense involving crops, livestock, fish and natural resource (soils, water, vegetation) management. 57 Agricultural Sector for Industrial Development The new paradigm is ‘sustainable crop production intensification’, which produces more from the same area of land while conserving resources, reducing negative impacts on the environment and enhancing natural capital and the flow of ecosystem services. Key principles are: (i) farming systems that save resources and offer a range of productivity, socio-economic and environmental benefits to integrated crop and livestock producers; (ii) access to improved crop varieties/seeds, animal breeds and fingerlings; and (iii) good agricultural practices including soil health and integrated soil nutrient management, rainwater and irrigation water management and plant and animal health protection. To encourage smallholders to adopt sustainable crop production intensification, policies/regulations and institutions need to devise incentives for small-scale farmers to use natural resources wisely (i.e., environmental services), rebuild research and technology transfer capacities and reduce the transaction costs of access to credit for investment (remove barriers to adoption and scaling up!). Box 3: The agenda for sustainable agricultural intensification and resilience The agenda for sustainable agricultural intensification needs to respond to rising market demand for crop and livestock/fish products from a growing global (and urban) population, in the context of a weakened natural resource base, energy scarcities and climate change. Promoting a sustainable intensification agenda involves: • First, to increase resilience and promote environmental sustainability, while increasing productivity, it is of critical importance to address together the imperatives of producing more, more effectively, and of preserving or restoring the natural resource base to put tomorrow’s rural generations at the centre of a new agenda for rural growth and poverty reduction. • Second, to capitalize on farmers’ local knowledge and social capital as well as on scientific research to address context-specific problems, so as to develop responses that are rooted in local agro-ecological conditions. There is no blueprint for an agenda for sustainable intensification, but a systemic approach, context adaptation, and linking farmers’ own and scientific knowledge are part of agenda for change. • Third, to build resilience to stress (including climate change) into farming systems, thus strengthening small-scale farmers’ capacity to manage risk. Sustainable agricultural intensification should be taken as an approach to broaden woman and men farmers’ options to better capture market opportunities while reducing risks, or strengthening their capacity to manage them. • Fourth, to enhance policy and political support, including adequate incentives and risk mitigation measures for a shift to sustainable intensification to take place. This requires, in particular, more secure land tenure to encourage long-term investments, conducive pricing and regulations for the use of natural resources and agricultural inputs, and support for the development of PES opportunities and markets. Farmers need better education, adapted to their needs, new farmer-centred learning approaches and linking-up to sources of information and resources. Conducive environment for developing capabilities for sustainable intensification requires building coalitions, sharing responsibilities and creating synergies among governments, civil society, the private sector—and above all—farmers and their organizations. Source: Adapted from Tanzania—Agriculture Climate Resilience Plan (ACRP), 2014–2019 127. Besides national level facilitation, policy adaptation and technical support, the implementation of climate change activities will be mainstreamed in all ASDP II activities, including research, support to sustainable crop, livestock and fish production and post-harvest management towards increased resilience and synergies. Specific investments will be integrated into local level investments implemented under DADPs. The main action areas for ASDP II are outlined in Table 18. 58 Agricultural Sector Development Programme II (ASDP-II) Table 18: ASDP II investment and action areas for improved resilience of farming systems Investment/action areas Priority activities Policies/regulations - Impacts on vulnerable groups, identifying opportunities for adaptation and mitigation, including strategies derived from the East African Community Climate Change policy - Strengthen early warning and preparedness - Enhance risk management measures, including risk insurances Crops - Research & extension on new crops/varieties and sustainable farming systems suited to hotter/drier conditions (mainstreamed) - Promotion of conservation agriculture, including adapted mechanization - Short- and long-term weather forecasting and response farming Livestock/fisheries - Strengthening human and technical capacities and systems for early warning to provide timely information and response - Developing mitigation and adaptation strategies for climate variability and change towards sustainable livestock and fisheries production systems - Support livestock herders and their organizations to implement mitigation and adaptation measures 128. Component 1 investments at national and local levels. Table 19: Five Years Development budget/investment estimates for component 1 –at constant 2016 Prices (TSh million) COMPONENT 1: SUSTAINABLE WATER& LAND USE MANAGEMENT- BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development 29,759 31,014 34,532 0 0 95,305 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity. 14,132 14,517 13,715 13,501 16,284 72,149 1.1.1.3 Enhancing access to agricultural land for youth empowerment 4,464 4,150 5,753 4,534 6,321 25,222 1.1.1.4 Improving coordinatoin of watershed management and monitoring systems for sustainable resource utilization - 1,366 928 839 916 4,049 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,370 184,589 172,338 175,278 189,619 738,194 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity. 5,873 50,129 57,162 59,915 65,430 238,509 1.2.2.1 Strengthening Irrigation schemes management and operations. 1,823 1,652 2,250 1,787 2,592 10,104 1.2.3.1 Development of water infrastructures for livestock productivity. 2,856 66,582 77,456 76,103 85,464 308,461 59 Agricultural Sector for Industrial Development COMPONENT 1: SUSTAINABLE WATER& LAND USE MANAGEMENT- BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries. 42,069 79,875 111,447 158,157 88,773 480,321 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies. 1,905 13,984 8,745 6,345 10,445 41,424 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management. 1,090 1,045 1,730 795 1,329 5,989 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness. 1,960 1,052 1,009 396 501 4,918 TOTAL COMPONENT 1 122,301 449,955 487,065 497,648 467,674 2,024,643 D. Component 2: Enhanced Agricultural Productivity and Profitability 129. Strategic objectives, outcomes and related indicators for the ‘Enhanced agricultural productivity and profitability’ are defined in Table 20. 60 Agricultural Sector Development Programme II (ASDP-II) Table 20: ASDP II Component 2: related ASDS-2 specific objectives and outcomes Specific objective Outcomes Outcome Indicatorsa SO2. To increase productivity growth rate for commercial market- oriented agriculture for priority commodities Improved agricultural productivity - Changes of yields (MT/ha, Litres/cow/lactation, Eggs/hen/day, Live weight/cattle at market point, Kg/fish) for priority commodities’ value chains - Percentage change in labour efficiency (Tsh/farmer/season) - Percentage change in Malnutrition (stunting and under weight) Improved agricultural profitability - Change of gross margins (Tsh/ha, Tsh/dairy cow, Tsh/LU, etc.) for priority commodities’ value chains - Change of profitability/Net returns (Tshs/commodity or enteprise) of priority commodities - Net financial returns to farmers/livestock keeper/fisherman 2.1. Improved agricultural extension services - Percentage change of farmers visited by extension staff - Adoption of productivity enhancing technologies by farmers - Adoption of disseminated technologies - Farmers’ satisfaction with extension services (customer care) - Extension staff delivering quality extension services - Prevance of pest and diseases incidence of economic importance - Incomes of households/ farmers that adopted improved technologies 2.2. Improved access to agricultural inputs/health services - Farmers access quality inputs - Seed germination rates - Crop yields - Access to subsidies - Benefits from subsidies - Percentage change of farmers using fertilizer - Percentage change of farmers using improved seed - Percentage change of livestock keepers accessing AI servive 2.3. Improved agriculture research for development - New technologies tested, released and disseminated by research stations (e.g new varieties) - Capacity of research stations to generate high quality technologies - Recurrent and development budget allocations and disbursements 2.4 Improved access to mechanization services - Affordable mechanization services - Households access different mechanization services for priority commodity value chains - % change of households accessing processing facilities for priority commodities’ value chains - Post- harvest losses of along priority commodities’ value chains 2.5 Improved food and nutrition security - Rural households living above/below the poverty food line - National food self sufficiency - Malnutrition incidences (chronic and transitory) in Tanzania - Macro- and micro-nutrients deficiency in children and pregnant women - Households with access to nutritious and diverse food - Households practicing diversified farming systems for improved diets and reduced vulnerability to food shortages - Households accessing livestock and fish proteins. - District receiving food assistance from NFRA - Volume of public stocks held by NFRA - Households receiving emergency food relief Component 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY S/c 2.1: Extension training and information services S/c 2.2: Access to agricultural inputs and health services S/c 2.3: Agriculture Research for Development (AR4D) S/c 2.4: Access to mechanization services S/c 2.5: Food and nutrition security 130. The strategy aims to increase and sustain productivity of priority commodities (crops, livestock and fishery) by targeting the small-scale commercial farmer sub-sector towards consolidated household food security but also agricultural commercialization. There is a need to accelerate the adoption of yield-enhancing technologies and reduced on-farm and post-harvest losses, including use of improved seeds and fertilizers, through improved access to credit, livestock health services and adapted 61 Agricultural Sector for Industrial Development mechanization services. Component 2 is divided into five sub-components. The Government of Tanzania priority for the agricultural and agro-industrial sector is to achieve a sustainable production increase equivalent to a 6% annual compound growth rate64. The specific objective of this component is to enable increased productivity growth rate for commercial market-oriented agriculture for priority commodities (crops, livestock and fish value chains). Increased agricultural commodity productivity is a prerequisite for household food security and agricultural commercialization, while area extension should be considered under intensified production systems. The proposed objective and outcomes will be achieved by four interlinked sub-components: (i) extension/advisory, training and information services; (ii) access to agricultural inputs for crops, livestock and fisheries; (iii) research for development; (iv) access to production and post-harvest mechanization services and (v) food and nutrition security. 131. Targeting smallholder commercialization, the strategy of this component is to increase delivery and use of demand-driven technologies, enhancing the productivity of prioritized CVCs within sustainable production systems for crops, livestock and fish. This will be achieved through: (i) broader availability of technology options responding to commercial needs of CVC stakeholder; (ii) facilitated farmer access to adapted technical knowledge and options for use; (iii) enhanced farmer access to inputs through private agrodealers (i.e., adapted seeds, planting materials and livestock breeds, fertilizers, feed and agrochemicals); and (iv) other technology support services (such as mechanization, phyto- and zoo-sanitary services, etc.). Advisory and training services will include food and nutrition aspects, such as promotion of crop diversification and bio-fortified varieties, awareness on cross-cutting issues such as gender; youth, environment and sustainable NRM, climate change mitigation, risk resilience and governance, as required. 132. Sustainable intensive production systems include among others natural resource management (land and water), conservation agriculture, integrated soil fertility, integrated pest, diseases, and post-harvest management. These approaches will be fine-tuned and scaled up by strengthened national and zonal AR4D services, demand-responsive extension services and private input supply channels (improved seed/breeds/fingerlings, fertilizers, agrochemicals, veterinary drugs, vaccines, etc.). Support will also provide improved access to: (i) sustainable management of land and water resources; (ii) adapted mechanization for production and value addition; (iii) required production, processing and marketing facilities; and (iv) appropriate diagnostic laboratory services, control and prevention of pests and diseases. 133. Livestock development will make a significant contribution to the sector growth through use of improved genetic resources and feed practices, but also commercialization, increased processing capacity and improved marketing efficiency. Specific measures will also be undertaken to improve fisheries and aquaculture production and management including infrastructure (modern fisheries harbour) and targeted sanitary measures. Table 21: Objectives for priority action in livestock and fish productivity development (10 years) Sub-sectors Specific objectives/outcomes Subsector Livestock and Fisheries - Availability, access and use of inputs/implements - Strengthened research, extension and training activities (infrastructure) - Diversification of new potential revenue sources Meat production - Water and pasture for livestock and fisheries (infrastructures)—comp 1; - Improved meat productivity towards commercial production of quality meat, meeting standards for domestic and international market Milk production - Increased production to meet domestic demand and external markets (raise income) Eggs production - Meet domestic demand and raise income of poultry farmers 64 Raise sectoral GDP from TZS 9,600 billion (USD 6.4 billion) in 2010/11 to around TZS 30,600 billion (USD 20.4 billion) in 2030/31. GDP per capita among the rural population would increase from around USD 180 to USD 360 over the same period. 62 Agricultural Sector Development Programme II (ASDP-II) Hides & skins and other by-product development - Improved quality, collection and processing of hides and skins for domestic and export markets - Use for food, feed, pharmaceuticals and energy Animal draught - Increased return on agricultural labour and related small-scale production Promote market access of animals & animal products - Develop cooperative and other farmer-based organization - Improve zoo-sanitary inspectorate services (improve prevention and control) - Establishment of disease free zones and strengthen disease reporting & surveillance - Strengthen laboratory disease diagnostic services Aquaculture production and fish captures - Promoting fish farming and aquaculture production and services Feasibility study and a detailed design for construction of fishing port - Increased aquaculture productivity and raised income of aquaculture farmers - Fishing regulation updating/enforcement for sustainable fishing & fish production Source: Adapted from ‘Livestock Sector Development Programme’. December 2011. The Medium-Term Expenditure Framework (MTEF) for 2015/2016 takes into consideration of the National Five Year Development Plan (2011/12–2015/16) and the BRN. Subcomponent 2.1: Extension Training and Information Services 134. Smallholder productivity for both crop, livestock and fish commodities still remain low due to limited use of improved agricultural technologies, inadequate AR4D linkages and extension services (public and private), limited availability and farmer access to agro-inputs, and unreliable markets and value addition opportunities. Disharmonized legislation and weak inspectorate services are limiting the country’s access to potential regional and international niche markets, while inadequate capacity building and monitoring systems result into unsustainable natural resource (land and water) use management and intolerable pesticide use and residues to consumers and the environment. 135. Overall ASDP-1 was instrumental in setting in place a system for delivery of extension services to smallholder farmers through LGAs, although their coverage and service quality have been uneven, focusing mainly on production of crops, with less attention on livestock and fisheries and post-harvest handling and marketing. It contributed with substantial on-the-job and formal training and increases in total manpower65 of public extension systems, while focusing mainly on conventional production technologies. The current structure for crop and livestock extension services is heavily reliant on the public sector. Recent efforts to introduce PPP initiatives, FFSs and ward resource centres (WARC) show promises for more effective farmer support services. Further steps for piloting and up-scaling innovative and cost-effective approaches for technical services, provided and managed in close partnership with farmer organizations (e.g., farmer facilitators, community animal health workers (CAHW))66 or Private Service Providers (agribusiness services, veterinary services, etc.) should be undertaken. 136. Extension and training services play pivotal roles, as described in Box 4, in terms of linking farmers to new technologies, information and knowledge that are central to enhancing agricultural productivity. To meet farmers’ demand and ownership towards increasing sustainable agricultural productivity, there is a need to: (i) strengthen AR4D linkages; (ii) adopt the most modern participatory extension methodologies; (iii) use modern ICT, such as mobile phone and Internet, including for higher level backstopping; (iv) promote use of sustainable agricultural practices (conservation agriculture, good agricultural practices, IPM, etc.); (v) facilitate farmers access to quality inputs (seeds/germplasm, fertilizer, feed, vaccines, etc.); (vi) strengthen the pest monitoring and early warning surveillance system; (vii) harmonize institutional set-up for PPP, involving local CVC stakeholders (including FO); and (viii) strengthen laboratory capacities for detection of disease pathogens and vectors for newly emerging and re-emerging diseases. 65 Number of village/ward extension officers in June 2013 was 7,974 (Minister budget speech FY 2014/15). 66 Sustainable services that are provided by trained animal health services at community level (e.g., CAHW) in support of livestock holder groups/association/cooperatives services related to livestock such as dipping, water dams, breeding bulls, grazing land. 63 Agricultural Sector for Industrial Development Box 4: Strengthening efficient extension (MAFC Workshop - January 2015) Is the current model of extension still fit to serve diverse farmer needs? Government targets transformation for provision of quality commodity extension services with increased private sector participation. Within the government regulatory role, institutional framework reform, started with TARI, multipurpose WARCs, FFS, etc. ASDP II coordination framework will be more comprehensive to include all projects/programmes in the agriculture sector. Recommendations/ideas for strengthening provision of extension services: (i) Diversity of its clientele by gender, resource base, type of enterprise, AEZ, climate, market opportunities, social capital and access to credit, etc. (ii) Pluralism in the provision of extension services that include both public, FO/CSO and private entities (including ties with input supply). Promote private sector process in extension services (including PSP) and use diverse communication methods (ICT); leverage private sector service provision; (iii) Strengthen training–research–extension linkage to address real farmer issues (LGA-ASLM linkages, operational ZIELUs and district facilitation teams (DFTs)), joint planning and sector financial support. Integrate training institutions under one umbrella (Sokoine University of Agriculture, ATIs, LITAs, Fisheries Education and Training Agency) and strengthen their capacities and effectiveness. (iv) Number of extension staff (1 per village—need 9,139 more): staff deployment to every village or fewer staff to form ward technical teams (public/private). Continuous enhancement knowledge & practical skills of extension staff on the value chain approach (v) Participative approaches/models and methodologies used in the provision of extension services (system/commodity, reasonable cost): (i) multiple approaches/models to be used including VBA and RIPAT; (ii) guidelines/manuals for the extension implementation; (iii) use ICT; and (iv) lifting farmers to organize themselves into self-running/help entities (e.g., SACCOS, Farmer (Learning) Groups, Agriculture Marketing Cooperative Societies (AMCOS), etc. (vi) Institutional arrangements in the provision of extension services: professional organization for extension officers, retraining, regular performance evaluation; strengthened district extension teams to link with research/FO, implement/equip functional WARCs (ICT) and use the PPP policy/strategy to improve efficiency for extension delivery (guidelines?) (vii) Financing: pre-conditions for effective extension include increased budgetary allocations (Agriculture Extension Block Grant, Agriculture Capacity Building Grant), adequate motivation, conducive arrangements & change working culture. Way forward! Transformation of extension service is key for enhancing agricultural production and productivity by: (i) ensuring quality services by involvement of key players; (ii) taking cognizance of the diversity of farmers including gender; (iii) envisaging institutional reforms for research/training); (iv) accessing information involving ICT; (v) supporting & equipping of multifunctional WARCs to backstop VEOs; and (vi) coordinating all local extension supports with annual planning and evaluation meetings; and (vii) build professional capacities of extension staff. 137. The objective is to enhance improved technology dissemination delivery systems into farmer use, which will contribute to increased and sustained production, productivity and farmers’ profitability of priority commodities (crops, livestock and fisheries) responsive to smallholder constraints and market requirements. Building on the lessons learned from ASDP-1, this sub- component will provide support to strengthen delivery of demand-driven market-oriented advisory and information services for smallholder farmers, scaling out successful approaches such as FFS, farmer-to-farmer and use of modern ICT (mobile phone, Internet and other social media), but also provider increased service ownership to CVC stakeholders, especially FOs. Special attention will be given to mainstream cross-cutting issues such as women and youth in agriculture, nutrition (see also s/c 4.3), HIV/AIDS and good governance and professional management of farmer and CVC organizations, including cooperatives. 138. At national level, this sub-component focuses on policy and institutional reforms for implementing effective agricultural service strategy, support to local implementation, media (national level radio/ television programmes, newsletters, agricultural shows, networking with international agencies, etc.) and information technology (IT) support. ASDP II will also integrate support to training and additional technical services such as land use planning and management (see s/c 1.2), animal and plant health services; plant and animal production materials; mechanization (see s/c 2.4) and additional policy and regulatory support. 64 Agricultural Sector Development Programme II (ASDP-II) 139. At LGA level, the sub-component, will support efficient and effective extension approaches and services that will enhance farmers’ access to technology innovations for increased productivity of their priority crop/livestock value chains; and promote farming system diversification towards improved risk management and food security and nutrition. This sub-component will support the following strategic action areas: i. Reorient technical support services to commercial farming promotion focused on priority CVC, facilitated by DCPs. Public technical agricultural services will be complemented by private agribusiness advisory service providers to form integrated CVC support teams at district and ward levels. The support services will provide specialized training and coaching to the district and ward-level agricultural facilitation teams to allow for their involvement in promoting commercial agriculture and strengthen agribusiness partnerships. To complement farmer empowerment and farmer organization strengthening (see s/c 3.1), FFS and farmer-to- farmer extensions will be strengthened by training, motivating and supporting lead farmers to provide technical services to local farmer/cooperative groups. This approach will promote efficient demand-driven and market-oriented advisory services and enhanced AR4D flows. ii. Scale up on-farm technology testing and demonstration to allow farmers a wider choice of options by strengthening research–extension–farmer linkages through the client-oriented research and extension management framework developed during the ASDP-1. This would include: (a) supporting district crop and livestock AR4D officers to link district technical teams with TTPUs; (b) implementing demand-driven on-farm research trials for priority CVCs (two/ district/year); and (c) up-scaling technology tests (two/ward/year) and demonstrations (two/ village/year), focused on priority CVCs, to assure broader awareness and farmer access to improved technologies/inputs and post-harvest technologies. iii. Improve farmer access to technical and economic information by strengthening local stakeholder access to technical and market information through use of innovative technology dissemination pathways, including traditional communication and modern ICT (e.g., Internet and mobile phones). Based on established effective communication infrastructure and technical support from TTPUs (see s/c 2.1), activities aim to improve farmer and other CVC stakeholder access to relevant technical and economic information to develop their agribusiness. To this end, district technical subject matter specialists, ward/village extension teams and lead farmers will be equipped and connected for information exchange and technical help desk at all levels, using internet and mobile phones. However, access to traditional farmer information channels will also be promoted by means such as the diffusion of leaflets/technical notes, radio programmes and listener discussion groups and the establishment of basic Ward Agricultural Resource Centre (WARC) modules (20 m²), where not yet implemented. iv. Rehabilitating/strengthening capacities for agricultural training institute (ATI)/ livestock training institutes (LITIs) to enable their functions of: (i) education and production of new extension officers (diploma and certificate level); (ii) in-service training and upgrading to existing extension officers (including the upgrade from certificate to diploma); and (iii) contribution to technical service providers to LGAs and farmers (local level function). v. Strengthening of crop and animal health services, including regulatory functions of input and output quality control. 140. At national/zonal level, the extension sub-component will support the national agricultural extension services and the regional secretariats to develop strategies and provide technical backstopping to districts. This will cover capacity strengthening for innovative market oriented CVC and advisory services for sustainable farming systems, developing guidelines and specialized information and training material, enhancing methodological support and guidelines for pluralistic extension services and capacitating the LITI/ (ATI) to deliver quality training. At local level, technical services will be financed through respective components. District, ward and village extension staff, supported by private Agricultural Service Providers (APS), will play key roles in supporting testing and up-scaling of successful technologies/systems within and across districts. 65 Agricultural Sector for Industrial Development Crops Extension, Training and Promotion 141. Crop extension services department under the Ministry is mandated to: (i) advise on policy formulation and strategies; (ii) improve extension services methodologies for use in LGA; (iii) establish standards and monitor their implementation; (iv) provide technical guidelines to the Regional Secretariat (RS), LGAs on good agricultural practices and sustainable agriculture; (v) disseminate technical packages for use in RS and LGAs; (vi) facilitate research–extension–farmer linkages; (vii) coordinate and facilitate private extension services providers; (viii) facilitate in-service training and capacity building of extension workers; (ix) promote the use of ICT in extension; and (x) monitor and evaluate extension services provision. 142. ASDP-1 promoted agricultural extension service innovations, including the use of the FFS approach to enhance technology diffusion and use among small-scale farmers. The FFS approach has been recognized as efficient among public and private/NGO extension service providers, although its up- scaling requires further harmonization across public and PSPs, integration of all value chain segments and improved focus on women and youth. The FFS approach will be used in parallel with other approaches, such as farmer-to-farmer exchange visits, internal technical and market services of farmer organizations, etc., but also the establishment of effective technical and economic information services adapted to the different user needs (farmer, extension worker, district subject matter specialists, ministry level specialists, etc.). 143. At national level, the proposed key action areas for agricultural extension are: i. Strengthening human resources and working facilities for national extension support services, especially for methodological and institutional innovation & higher-level support. ii. Contributing to harmonization of the FFS approach(es) around priority value chains and focusing on women and youth, enhancing graduated FFS master farmers to set up new ones, promoting study/exchange visits for farmers and field staff. iii. Accelerating extension reforms towards effective modern agricultural extension by developing an extension strategy (and master plan), enhanced research and extension linkages, harmonization of public and private extension support, use of ICT (e-extension—see further details in s/c 4.5) in dissemination of technologies and market information along commodity value chains; As part of implementing the National Agricultural Policy (2013), the ministry is committed to develop a National Extension Strategy and a legal framework for extension services which will define amongst others: (i) the relationship of key players in the provision and financing of extension services; (ii) responsibilities the extension staff and clientele to be served; (iii) coordinating mechanisms between different organizations that undertake extension; and (iv) promoting dialogue forum for key stakeholders involved in extension. iv. Rehabilitating physical infrastructures and retool four farmer training centres67 and Farmers Education Unit (FEU) to disseminate improved technologies. v. Strengthening technical backstopping at local level and building capacity of extension services at regional administrative secretariats (RASs), districts and ward teams to increase efficiency of public and private service delivery and supervision of field activities (including by the use of ICT—s/c 4.5) 144. At local level priority investments are: i. Strengthening human resources and working facilities for extension services at district and ward level (technical knowledge-retraining and working gears—extension kit, transport). ii. Improving working and living environment at ward and village levels; building and consolidating ward extension teams. 67 Four farmer training centres under the ministry: Mkindo in Mvomero district; Bihawana in Dodoma District; Inyala in Mbeya district; and Ichenga Njombe District. 66 Agricultural Sector Development Programme II (ASDP-II) iii. Retooling and facilitate functioning of WARCs, including establishing technology demonstration plots. iv. Linking up with zonal research and extension liaison/partnership units (TTPU) and strengthening implementation of on-farm research and demonstration networks for new varieties and sustainable agricultural management practices along priority CVCs (see s/c 2.3). v. Widening technical and economic knowledge support to farmer empowerment and organization within integrated value chain development from production to marketing. vi. Developing efficient response systems to farmer technical needs/questions by developing ICT systems (see s/c 4.5) at local level for increased extension and advisory service efficiency. 145. Training. The ministry has 14 ATIs68 for the crop sub-sector. Most of the physical infrastructure needs rehabilitation to stimulate effective learning and staff efficiency and effectiveness. These institutes also lack teaching and most learning materials and/or training facilities. This negatively affects ‘learning by doing’ and the skills developed do not correspond to the current labour market requirements. The curricula used in the ATIs therefore needs to be reviewed. The capacities of human resources of the training division (195 tutors, 94 agricultural field officers and 119 support staff) need to be upgraded by specialized long and short course programmes. 146. The objective is to strengthen training capacities for agricultural technicians (certificate and diploma level, and on-the-job training for farmer leaders) to avail public institutions and private companies with high quality agricultural technicians, whose training is accredited by National Council for Technical Education (NACTE). Training cycles will also allow for youth empowerment on self-employment and enterprise creation in the commercial agriculture. Priority support areas include: (i) rehabilitating living and learning environment of 14 ATIs; (ii) retooling ATIs with training facilities, aids/materials/ library, transport facilities and furniture; (iii) development of practical training farms/demonstration plots for students/farmers in ATIs; (iv) capacity building of tutors (195), agricultural field officers (94) and supporting staff (119 in the ministry headquarters and ATIs) in long and short courses; (v) curricula development for training diploma and certificate programme and farmers (include marketing issues, M&E, business investment planning and budgeting, FO support, etc.). 68 ATI (14): Igurusi, Uyole, Inyala training centre (Southern highlands); Ilonga, Mlingano, National Sugar Institute (NSI), Kilombero Agriculture Training and Research Institute (KATRIN) — (Eastern zone); Maruku and Ukiriguru (Lake zone); Mtwara (Southern zone); Tumbi and Mubondo (Western zone); Horticultural research and training institute (HORTI), Kilimanjaro Agricultural Training Centre (KATC)—(Northern zone). Only 3 ATIs (Mtwara, Ukiriguru and Maruku) were rehabilitated in 2011. 67 Agricultural Sector for Industrial Development Box 5: Technical training institutions ATI/LITI form middle level technical institutions between ASLMs and LGAs, which primarily provide practical and theoretical training of agricultural technicians who can be employed in the public and private sector. ATI/ LITIs also undertake some short-term training for farmers (leaders). Approximately 1,600 and 2,700 students graduate annually from ATIs and LITIs respectively. ASDP II needs to strengthen the role of ATIs and LITIs (eight colleges) to achieve: (i) Well-trained agricultural extension professionals and technicians (diploma and certificate). The gap for crop extension workers is 6,244 (15,802 is total need), while at headquarters the gap is 142 + 372 for other cadres (approximately 2,700 students graduate annually from ATIs). The gap for livestock extension workers is about 10,000 (total need is 16,000). (ii) In-service training for VAEO/WAEO and upgrading capacities of existing extension manpower. (iii) In-service training and farmers training is provided in ATIs and LITIs mainly for farmer leaders and to strengthen farmer organizations in management, leadership and technical & economic services to their members. Therefore, these institutions require significant improvements in terms of tools and facilities for practical training in production and marketing, adapted to zonal farmer needs. Support to the running of these public institutions is generated from core public support, programmes/projects, CVC boards, private entrepreneurs and the students (fees and internal production). 147. Crop Promotion ‘Section’. To improve production, productivity and commercialization of crop sub-sectors through promotion of good agricultural practices and entrepreneurship skills such as ‘Farming as a Business’ to the smallholder farmers, especially in specialized window crops. The strategies to improve production and productivity and commercialization of the sub-sectors will include the following: (i) commercialize production of drought tolerant crops (especially cassava); (ii) develop programmes/plans and to operationalize horticultural strategy and infrastructure; (iii) training of horticultural subject matter specialists and lead farmers on good agricultural practice and value chain development; (iv) develop strategy and implement programme for organic produce promotion to capture increasing demand for organically grown products; (v) develop a national oil seed development strategy and implementation programme; and (vi) upgrade and maintain mother orchards in five potential areas so as to establish a reliable sources of quality scions for seedling production. The crop promotion section also provides technical support services to nine crop boards (tea, coffee, cotton, sisal, pyrethrum, tobacco, sugar, cashew nut and cereal and other produce boards). This support includes, among others: (i) the review and improvement of their development strategies; (ii) specialized technical backstopping of key value chain actors and lead farmers; and (iii) promoting contract farming. 148. Proposed priority investments include: (i) implementation of crops development strategies in nine crop boards69; and (ii) other activities related to cassava commercialization, operationalization of the horticultural development strategy, training and working facilities of LGA and the ministry staff, implementation of regulatory functions and monitoring. Strategic alignment of respective functions of crop boards, the Ministry of Agriculture and Ministry of Industry, Trade and Investment would be useful for increased efficiency of supports. Livestock and Fish Extension and Training 149. Livestock and fisheries extension services deal with transfer of knowledge and skills to farmers and sharing of technical and economic information and experiences amongst value chain stakeholders, to increase production and productivity and producers’ return. The extension service currently is mainly provided by public service providers with gradual increase of private sector participation in the delivery of the services through different interventions, especially for animal health services. Currently, livestock extension services include 4,172 livestock extension staff at district, ward and 69 Tea, Coffee, Cotton, Sisal, Pyrethrum, Tobacco, Sugar, Cashew nut and Cereal and Other Produce Board. 68 Agricultural Sector Development Programme II (ASDP-II) village levels70 (the staff deficit estimated at 16,000 technicians). 150. Under the extension system, the Livestock Identification and Traceability System (LITS) is an essential prerequisite to international livestock trade and marketing and guarantee food safety and sanitary assurance to consumers. The export of livestock and livestock products is compromised by the high prevalence of trans-boundary animal diseases and inadequate/low compliance with international markets sanitary and phytosanitary standards requirements, demanded by livestock and livestock products importing countries. The priority investment areas for the improvement of livestock/fisheries advisory and technical support services are, as established in Table 22: Table 22: Priority activities livestock extension Investment areas/priority activities At national and regional level: - Development of practical training farms/ demonstration plots for students/farmers - Coordinate livestock extension services providers and undertake technical backstopping - Training of 594 livestock extension staff at MSc level from all LGAs & headquarters - Rehabilitate four (4) and build three (3) livestock infrastructure in 7 zonal agricultural show grounds - Establish and equip TV and radio programmes recording studios at national level - Establish a Guarantee Support Fund for Livestock Identification Devices (LIDs) - Rollout of Tanzania National Livestock Identification and Traceability System (TANLITS), including a strengthened TANLITS Help Desk through provision of reliable internet and website connectivity - Conduct long- and short-term training to TANLITS managers/administrators, ICT & other experts on database management, computer programming, computer engineering and system management - Prepare and circulate public sensitization materials on TANLITS including print materials, radio and TV programmes and conduct sensitization meetings and workshops to target stakeholders in 25 regions At LGA level - Identify knowledge gaps for public/private livestock extension service providers in all LGAs, promote private technical services (animal husbandry, health services, etc.) - Provide extension kits, vehicles (147) and motor cycles (4,000) in 147 LGAs, training of 294,000 farmers on improved livestock production technologies in all LGAs - Establish 147 Livestock Resource Development Centres in all LGAs - Use ICT to inform and advise livestock keepers (see also s/c 4.5) - Facilitate 147 LGAs to sensitize formation and strengthening farmer groups, organizations, associations and cooperatives - Build capacity of 30,700 livestock farmers on management and entrepreneurship skills - Conduct training and provide backstopping on TANLITS application to 165 LGA Livestock Identification Traceability Officers & 25 Regional Livestock Officer; support 147 LGAs in TANLITS field operations & communication network - Support installation of TANLITS hardware and software to five accredited export abattoirs/slaughterhouses Table 23: Priority intervention in fisheries extension Investment areas/priority activities National/regional level 1. Improved collaboration among extension service providers 2. Increased expertise for fisheries extension officers and fishers/aqua farmers 3. Strengthen private quality feeds and seeds production 4. Rehabilitation of existing infrastructure 5. Capacity building on new technology and facilities operations 6. Construction of processing facilities for dagaa (Rastrineobola spp) from fresh and salt water 7. Strengthen preservation facilities (ice plant and cold room) along Lake Tanganyika 70 Overall there are about 12,111 villages, 3,383 wards and over 160 LGAs (all not having livestock extension services). 69 Agricultural Sector for Industrial Development Investment areas/priority activities LGA level 1. Support private sector participation in provision of fisheries/aquaculture extension services 2. Formulate and strengthen fisher folk and aqua-farmer (water and land user) organizations 3. Develop and strengthen infrastructure—resources centres for fisheries and aquaculture extension services 4. Strengthen technical backstopping for fishers/aqua farmers 151. Training. Livestock Training Agency (LITA) is among the three Agencies of the Ministry of Livestock and Fisheries. It was established in under the Executive Agency Act No 30 of 1997 and its amendments (RE 2009) in September 2011. LITA was formed by merging six Livestock Training Institutes (LITIs) which were Tengeru, Mpwapwa, Morogoro, Madaba, Buhuri and Temeke. In year 2013 and 2014 Mabuki and Kikulula Training Units were established respectively. The major role of LITA is to implement livestock development objectives as expressed in the National Livestock Policy 2006 and Ministry’s Strategic Plans. The core activity of LITA is to offer Diploma and certificate courses in Animal Health and Production at NTA Level 4 - 6 and also offers various specialized courses for various clients/farmers. Short courses include; Poultry Production, Dairy cattle husbandry, Milk processing, Beef cattle husbandry, Pasture production, Hides & skin management and Entrepreneurship. LITA’s training approach is Competence Based Education and Training (CBET) to ensure production of competent graduates who can be employed by the Government, Private Sector or self-employed and thus contribute to development of livestock sector and national economy. Strengthening of infrastructure, training facilities as well as improvement of curriculum are foundation for effective extension services. 152. Fisheries Education and Training Agency was established by merging the Mbegani Fisheries Development Centre and the Nyegezi Freshwater Fisheries Institute. The main role of Fisheries Education and Training Agency is to assist the Ministry in: (i) provision of fisheries education and training in aquaculture, fisheries technologies and management; and (ii) conduct applied research and consultancy in promoting sustainable development of fisheries and allied industries. This initiative will promote public and private service delivery to aqua-farmers, small-scale fisher folk and commercial enterprises and other stakeholders, which are mainly provision of quality fisheries education and training, improve extension services, develop appropriate fisheries technology and promote sustainable aquaculture through physical demonstration and practical advice. 153. Both LITA and Fisheries Education and Training Agency take over the functions of the livestock and fisheries training institutes (LITIs and FTIs) as well as other functions expressed in their respective framework document, including: (i) training, research and consultancy: manage and coordinate long- and short-course training, applied research and specialized consultancy services; (ii) production support services of livestock, livestock products and other farm produce; and (iii) business support services to the agency in areas such as administration, management of human and financial resources, marketing of agency services and products and estate management towards sustainability and meeting clients demands. Table 24: Priority activities & investment areas in livestock and fisheries training (a) LIVESTOCK: Train professionals for the development of the livestock industry 1. Develop human capacities, review curricula and training programmes and retooling of LITA to provide livestock training 2. Train 100,000 livestock keepers from 20 LGAs on livestock improvement technologies 3. Infrastructures: support, construct and rehabilitate 8 LITA training centres 4. Capacity building of the ministry staff: facilitate DRTE and LITA staff to attend long and short courses, study tours and training workshops annually 70 Agricultural Sector Development Programme II (ASDP-II) (b) FISHERIES: Train professionals for the development of the fisheries industry 1. Build capacity of training institutes 2. Strengthened up to date information and training materials 3. Support maintenance of training institution’s infrastructure 4. Strengthened training guidelines 5. Support the Fisheries Education and Training Agency programme on value chain analysis, identification of technological gaps, value addition possibilities and mitigation of marketing snags along sardine supply chain 6. Monitoring and evaluation of training activities 7. Promotion of artificial reefs for sustainable restoration of depleted fish stocks and enhanced seaweed farming in coastal area, Tanzania Subcomponent 2.2: Access to Agricultural Inputs 154. Government efforts through NAIVS for increased use of improved seed and fertilizer delivered by a strengthened network of private agrodealers has enhanced the use of improved seeds and fertilizer by smallholders and requires follow-up, including: (i) further targeted smart input subsidy; (ii) design agricultural input credit package adapted to smallholder needs; (iii) facilitate private agrodealers to enhance their business network for improved input offer and access; (iv) effective extension services and training for accelerated adoption of new technologies; (v) enhance integrated soil fertility management, especially the use of organic fertilizer along with livestock activities; and (vi) strengthen the national seed systems involving ARI, the Agriultural Seed Agency, the Tanzania Official Seed Certification Institute (TOSCI), private seed producers and agrodealers. 155. The experience of smart subsidies in promoting crop productivity could be scaled up to livestock technologies including: (i) increased access to artificial insemination (AI) for upgrading of local breeds; (ii) improving animal health through interventions for controlling and eradicating diseases and pests (e.g., vaccinations, cattle dips, veterinary drugs); and (iii) pasture seed dissemination for improved rangeland, prevention of erosion, etc. For enhanced aquaculture and access to fingerlings, smart subsidies for certified fingerlings and feed could be envisaged within PPP in fish seed and feed production. 156. The objective is to expand sustainable access to and efficient integrated use of adapted farming inputs (i.e., seeds, planting materials and livestock breeds, fish fingerlings, fertilizers, animal feed and agrochemicals) by increased proportion of smallholders, which will contribute to increased and sustained production and productivity of priority commodities for crops, livestock and fishery. As farmers seek to widen their use of technology options for increased efficiency, income and resilience, the availability and access to specific inputs needs to be ensured: to this end, public support will facilitate and regulate the multiplication of improved genetic material (seeds, breeds, etc.) and farmer access to quality production inputs commercialized through competitive private sector supply channels (agrodealers). 157. Specific support will focus on priority CVCs in the selected district clusters, and include the following action areas: i. Enhanced availability of high quality crop seeds by strengthening private sector participation (including farmer organizations) in seed supply chains. This support targets seed production/ multiplication and distribution for priority commodities (and their companion crops) to assure availability of adequate quantities of quality seed for users preferred varieties. Main support activities include: (a) enhancing breeder seed/breed supply and technical assistance to the private seed sector; (b) supporting the Tanzanian Seed Trader Association (TASTA) and its seed market information system (seed demand and offer by variety and prices); (c) consolidating the capacities of regulatory functions of TOSCI71; International Seed Testing Association (ISTA) accreditation and regional expansion); (d) supporting the ministry’s seed unit for monitoring of seed sector development strategy and organizing an annual seed sector planning and evaluation involving all 71 TOSCI: support in complement of EAAPP. 71 Agricultural Sector for Industrial Development stakeholders; (e) Agricultural Seed Agency production of foundation/basic seed for public-bred varieties; and (f) supporting private/farmer multiplication, including by Quality Declared Seed farmer groups, for specific non-commercial varieties of priority CVCs (maize/rice/oil seed) and responding to a specific demand (i.e., sunflower). ii. Improved access to quality crop inputs (seeds, fertilizer, agrochemicals and tools) by strengthening the national and local agricultural input supply systems implemented by the private agrodealer network. Activities will include: (a) technical, safeguard and business capacity strengthening for about 1,000 active agrodealers in the target areas; (b) local demonstrations of improved technologies by agrodealers and extension workers (5–10 agrodealers per target district); (c) consolidating the capacities of regulatory functions of Tanzania Fertilizer Regulatory Authority (TFRA); (d) stimulation of partnerships (contract farming, etc.) between farmer organizations and agribusiness engaged in targeted CVC for sustainable production and marketing systems (receipt systems); and (e) promote the use of conservation farming practices72 and include the distribution of starter packs of seeds and other inputs for production diversification, including nutritious crops such as pulses and horticultural crops. iii. Production of quality pasture seeds to increase productivity and production of quality feeds to cope with the increasing number of animals and related economic and environmental impacts. Investments in improved ruminants (e.g., dairy) requires parallel investments in pasture development adapted to respective AEZ to increase productivity and contribute to farmers return. Incorporating improved pasture development strategies in the farming system and hay/silage production technologies will contribute to adequate supply of supplementary feed throughout the year. iv. Production of quality bulls and semen for improvement of indigenous livestock. The breeding objective(s) (trait) for selected farmer research groups are to improve milk potential of the indigenous cattle populations through cross-breeding, while maintaining high levels of adaptation to local feed resources and environments in general. In response to increasing farmer demand, TALIRI distributed 640 improved Mpwapwa bulls and 780 cattle between 2006 and 2015, some of which are used in cross-breeding. Current needs are to: (a) develop a breed of cattle whose cows will regularly yield about 2,800 kg of good quality milk per year in the semi-arid areas in Tanzania; (b) increase production of improved heifers and bulls to meet the current farmer demand of Mpwapwa breed and their crosses; and (c) improve the production and distribution of semen for AI from the semen producing centres v. Fingerlings production for aquaculture. Farming of fish and other aquatic organisms in fresh and marine water environments is becoming an important contributor to the world’s food supply and nutritional security, but also to rural livelihoods and employment. With decreasing fish supply from capture and increasing population, economically viable and environmentally sustainable inland and marine aquaculture need to be developed in Tanzania. This implies increasing farmers’ access to critical aquaculture inputs (seed, feed, organic fertilizers), and promoting appropriate aquatic farming technologies, extension support and training. Priority support actions include: (a) hatcheries for Tilapia sp., catfish, milkfish, mud-crabs and trout; (b) feed and grow-out development for selected fish species; (c) prawn farming development for clustered coastal farmers; (d) cage fish culture in selected non-drip irrigation schemes; (e) promotion of indigenous species for fish culture development (O. tanganicae, grouper culture, and Nile perch); and (f) promotion of value addition in seaweed. 158. Input subsidies. The NAIVS/AFSP (2008–2014) programme implemented a targeted smart subsidy, which yielded an additional production of 2.5 million tons of grains, through increased yields of maize (+433 kg/acre) and paddy (+ 263 kg/acre)73. Besides multiple challenges, the final economic rate of return (ERR) of NAIVS was estimated at 53.5%. The evaluation showed that about two-thirds 72 Applying principles of: (i) minimum tillage; (ii) permanent soil coverage; and (iii) crop rotations/associations. 73 Source: AFSP ICR (December 2014) and Tanzania PER: NAIVS February 2014. 72 Agricultural Sector Development Programme II (ASDP-II) of the 2.5 million beneficiaries continued to buy seeds while one-third continued to buy fertilizer at commercial prices, once the subsidy was terminated. Furthermore, besides increased awareness and use of agricultural inputs, NAIVS also strengthened seed production systems and farmers relationship with trained agro- dealers and commercial agents for seed and input supply. 159. However, considering the high investments costs, the Government of Tanzania tried to organize a follow-up programme to provide subsidized credit74 to smallholder farmers by paying banks the difference between the commercial interest rate of 18% and the programme’s designated rate of 4%. In addition, the government has agreed to pay commercial banks 50% of the value of the credit upfront, as a guarantee against possible defaults. Farmers were expected to contribute 20% of the input cost (against 50% in NAIVS), leaving banks to bear the risk on the remaining 30% of the cost. Farmers are also expected to agree to market their produce through a designated trader or warehouse, allowing the banks to first be repaid. Several issues, including limited interest of local banks and delays in government’s advance funding of the programme slowed down the start-up and expected outreach. Crops inputs (seeds and fertilizers and agrochemicals) 160. Seeds. The effective potential market demand of improved seed in the country is estimated at about 60,000 tons per year, while the current availability of improved seeds (mainly maize and rice) is 35,352 tons. Only about 25% of farmers are using improved seeds, mainly due to inadequate availability and accessibility of improved seeds, but also low awareness on improved varieties/technologies adapted to their farming conditions. 161. Fertilizer and agrochemicals. Although fertilizer use was increased and private distribution networks developed by NAIVS support, the level of fertilizer use remains low, especially for basal fertilizer. Integrated soil fertility management needs to be fully integrated into AR4D as extension activities towards more efficient use of fertilizers while enhancing soil fertility and health. In addition, the use of agrochemicals (herbicides, pesticides, etc.) remains limited and intensive agrodealer and farmer training and technical advice is required to allow for efficient, sustainable and safe use of recommended pesticides. 162. Improved availability and use of improved seed and fertilizers by smallholder farmers. Building on former targeted actions, this objective will be achieved by: (i) strengthening farmers awareness on improved seed and fertilizer (flyers, leaflets, radio/TV, training, demonstrations, etc.); (ii) strengthening production of Quality Declared Seed (QDS), especially for species not (yet) considered by the private sector, by training, access to quality foundation seed and small equipment; (iii) strengthening the agrodealer network by annual technical, management and safeguard training; (iv) supporting ASA to enhance private/farmer seed business and the production of quality basic seed (collaboration with ARIs); (v) supporting the national seed committee and variety release committee; and (vi) facilitating the seed trader association and information exchange in the sector; and (vii) strengthening agricultural inputs regulatory services (i.e., TOSCI) for quality assurance. 163. Considering the economic efficiency of targeted (smart) subsidies, the Government of Tanzania is considering another cycle of time-framed input subsidies, but targets and modalities are not yet fully defined. Although electronic vouchers (e-voucher) simplify implementation (including decreasing subsidy levels over time), follow-up and governance of the operation75. Furthermore, a similar approach could be used for other inputs such as agrochemicals including veterinary drugs (e.g., acaricides), but also services such as mechanization services (land preparation, seeding, threshing, etc.) to enhance farmers’ access (demand) and business development (offer) for PSPs. Although LGAs will 74 Credit interest is subsidized, while farmer pay the full price, 20% at planting and 80% after harvest. 75 The Ministry of Agriculture will continue promoting input utilization by subsidy through bank loans (discussion with commercial banks are underway). Meanwhile, the ministry will also continue to promote input subsidy through the voucher scheme until the above is in place (i.e., parallel operations for some time). ASDP II is expected to target both farmer organizations and individual farmers, with a focus on FOs in connection with ‘priority commodity’ interventions. 73 Agricultural Sector for Industrial Development be final beneficiaries of subsidies, there is a need for technical support from the national and regional level to: (i) organize solid and harmonized subsidy systems; (ii) coordinate actions between public and private stakeholders at all levels, including linkages to other CVC supports; (iii) provide technical advisory and backstopping support for implementation; (iv) strengthened agricultural research and advisory services to increase efficiency of farmers’ input use within an integrated management approach; and (v) implement the M&E system of the subsidy system. 164. Strengthened Agricultural Input Regulatory Services to ensure availability of quality seeds and fertilizer. Seed regulation and quality control is carried out by TOSCI while fertilizer regulation and quality control is done by Tanzania Fertilizer Regulatory Authority (TFRA. Within a results-based agreement, TOSCI need to be further76 supported for: (i) the International Seed Testing Association (ISTA accreditation (by 2018) to ensure that seed produced and certified in the country meet international standards; (ii) establishment of new centres in Mtwara (South) and Tabora (Centre) by 2019; (iii) training of district seed inspectors and staff; and (iv) office and laboratory facilities. Furthermore, the support to TFRA will include: (i) office facilities within the Ministry of Agriculture premises to deliver its services; (ii) fertilizer testing laboratory or a memorandum of understanding with the specialized laboratory at the Mlingano Research Institute; (iii) training of TFRA staff and district fertilizer inspectors; and (iv) recruitment and on-the-job training of competent inspectors. 165. The regulatory framework needs to be strengthened to control quality and safe handling of products and their residues. Support activities should also cover the Office of Registrar of Pesticides and Plant Health Services (PHS) which is responsible for enforcing the Plant Protection Act dealing with pesticides management. Moreover, as part of ensuring stakeholders awareness on the existing ago- inputs legislation, it is expected that training of law enforcers should go together with stakeholders’ awareness creation and monitoring of legislative compliance. 166. The Plant Health Services mandate aims at minimizing crop losses at pre- and post-harvest levels mainly from outbreaks of pests such as the red locust and quelea birds. Control and surveys are conducted jointly by the government and international organizations. The mandate of PHS includes the management of pest outbreaks, promotion of IPM and enforcement of the Plant Protection Act (plant import/export control, plant quarantine and phytosanitary services, pesticide registration and management regulations). The existing capacity of the phytosanitary services in Tanzania has several gaps in terms of infrastructure and human resource capabilities that need to be addressed for improved compliance of crop standards. 167. The specific objective of proposed PHS activities include to: (i) control pests and diseases to minimize pre- and post-harvest crop losses; (ii) deploy pest management strategies and approaches that will enhance crop production and protect the environment; (iii) enforce regulatory measures that will limit introduction and spread of pests to promote production and sustainable internal and export market access; (iv) improve and strengthen pesticides management technologies for safeguarding human health and the environment; (v) provide technical contributions towards harmonization of the regional (East African Community (EAC)) phytosanitary law and regulation frameworks and their application; and (v) empower PHS staff with new skills to facilitate them for efficient service delivery. 168. Action areas for achieving these objectives are: (i) capacity building for PHS staff; (ii) strengthening the capacity of Plant Quarantine Inspectorate Services; (iii) strengthening procedure for pest listing and managing surveillance data; (iv) strengthening pesticide management system including residues; (v) development and use of IPM technologies; (vi) institutional reform to harmonize institutional set- up of legislation; (vii) strengthening early warning, management and monitoring of outbreak pests; (viii) strengthening the management of mycotoxins (e.g., aflatoxins in cereals for food and feed); and (ix) strengthening early warning and management of invasive species. Livestock and fish inputs 169. Overall, priority action areas for improved availability and farmer access to quality livestock and fish 76 Most of these supports were already provided under former programmes such as AFSP, EAAPP. 74 Agricultural Sector Development Programme II (ASDP-II) production factors, including breeds/fingerlings, production inputs and health/veterinary drugs have been summarized, as shown in Table 25. Table 25: Priority activities livestock/fisheries access to inputs Action/investment areas Priority activities ANIMAL/FISH FEEDS Animal feeds and additives for increased productivity - Promote quality animal feed production, processing and marketing - Quality control of animal feed (laboratory services) - Promote agro & industrial by-products as animal feed resources - Access to quality animal health/veterinary drugs/devices - Improve safety for animal product consumer - Control mycotoxins in animal feed and fish meal Quality/quantity fish feeds and seeds for increased productivity - Facilitate private sector to produce quality and quantity fingerlings - Update fish feeds and hatchery construction guidelines ACTIVITIES LIVESTOCK/FISH DISEASE CONTROL & VETERINARY PUBLIC HEALTH Trans-boundary animal diseases (TADs) controlled for sustainable industry - Facilitate livestock health certification - Equip zoo-sanitary check points - Strengthen capacity for epidemiological surveillance of TADs - Strengthen laboratory capacity for TADs detection - Public awareness & conduct vaccination campaigns of priority TADs - Capacity of early warning detection and response - Strengthening laboratory capacities for detection of TADs Parasitic & vector-borne diseases - Promote control of parasitic and tick-borne diseases (opportunity for targeted acaricide subsidy) - Promote East Coast Fever (ECF) vaccination - Acaricide subsidy for area-wide IPM - Control of tsetse and trypanosomiasis - Strengthen laboratory capacity for vectors and parasites detection Veterinary public health - Strengthen zoonotic control to safeguard human health - Increase public awareness on important zoonosis - Enhanced monitoring, surveillance of food-borne and zoonotic disease Farmed aquaculture products - Implement fish and other aquatic diseases surveillance - Monitoring of farmed fish and other aquatic diseases - Training on farmed aqua-products and fish feeds import risk analysis - Training on imposing biosecurity system in seaweed and fish farms Fish quality control and fisheries protection - Equipping Nyegezi quality control laboratory - Equipping fisheries protection outpost stations - Capacity building, including on early warning detection and response 170. Improved availability of acaricides, veterinary drugs and vaccines for livestock farmers to ensure improved disease prevention and resilience. The government established a vaccine production facility at Kibaha (Coast) in 2012. This facility currently produces three types of vaccines: (i) Newcastle disease vaccine strain I-2 (about 4 million doses/month or 50% of needs); and (ii) anthrax and blackquarter vaccine (10,000 doses/month each). The current production is low due to lack of automated equipment and qualified personnel. The production of vaccines will be supported by: (i) providing specialized equipment for vaccine production; (ii) specialized training of personnel; (iii) building and equipping the quality control unit; and (iv) developing infrastructures for vaccines research and production. Livestock vaccines are generally considered as a ‘public good’, and their use could be enhanced under well targeted subsidy programmes. 171. Strengthened veterinary services by establishing more veterinary service centres in each administrative division by: (i) encouraging private sector investments (innovative tax incentives and/ or grants) to complement the government’s efforts in providing livestock husbandry and veterinary services at local level to increase the number of cattle dips, artificial insemination centres, vaccination facilities and hatcheries (poultry); and (ii) promoting the establishment of community cells to share facilities for poultry hatcheries, cattle dips, improved bulls, insemination and vaccination facilities. 172. Sustainable fisheries development will be considered within an ‘ecosystem approach’ involving: (i) support services skill development for improved sustainable fisheries; (ii) sensitization and awareness 75 Agricultural Sector for Industrial Development creation among fisher folk; (iii) review of pelagic fishery management plan; (iv) conduct of MCS operation for licensing and registration of vessels; (v) value addition to fish/fisheries products; and (vi) registration and capacitation of all BMUs, fishery associations, etc. Subcomponent 2.3: Agricultural Research for Development (AR4D) 173. The specific objective under this subcomponent is to improve technology generation delivery systems responsive to farmer needs and market requirements, which will contribute to increased and sustained productivity and production of priority commodities (crops, livestock products and fishery). Targeted outcomes to be achieved are: (i) improved technology generation delivery systems responsive to farmer needs and market requirements which will contribute to increased and sustained production and productivity of priority commodities (crops, livestock, fishery); (ii) enhanced support to technology dissemination systems through strengthened research- extension linkages; (iii) build capacity of semi-autonomous research institutes in human and financial and physical (infrastructures, equipment) resources; (iv) consolidate participatory identification, implementation and evaluation of research involving a broad spectrum of stakeholders; and (v) enhanced collaboration with regional and international research institutes including the Consultative Group for International Agricultural Research (CGIAR) and the private sector. 174. Building on participatory approaches developed under ASDP-1, AR4D investments will include strategic and demand-driven adaptive research agenda/activities focused on priority CVCs for crops77, livestock and fish products within each AEZ. Further to a consultative role to the PPP for adaptive research and technical support, the sub-component will support adaptive research activities and address priority CVCs technology needs for productivity impact, within sustainable production systems based on: i. Enhanced client-oriented and demand-driven adaptive technology generation to broaden users’ technology options, with emphasis on crop and livestock78 breeding/selection, enhanced breeder seed/ breed supply, sustainable natural resource management (soil and water), climate smart production practices, integrated pest management (IPM), integrated disease management (IDM) and post-harvest practices, including client needs for value addition, nutrition issues (bio-fortification) and reduced post- harvest losses. Zonal Agricultural Research and Development Funds (ZARDEFs), established during ASDP-1, will be used to channel financial support to user-selected demand-driven adaptive agricultural research projects focused on local priority CVCs79. This competitive fund is open to public and private researchers for client-oriented research, based on zonal research priorities. ii. Strengthened coordination and networking for priority CVC research at national, regional and international levels to source adapted technologies. This will be achieved by enhanced networking with the Consultative Group for International Agricultural Research (CGIAR) and other international, regional (applying the subsidiarity principle) public and private (i.e., seed) research institutions to source technologies adapted to the needs of local systems and global changes. Furthermore, national level AR4D coordination and networking for targeted CVCs and cross-cutting thematic80 areas (food and nutrition, integrated NRM, climate change, gender -sensitivity, etc.) will be strengthened by regular information exchange and research platforms for targeted priority CVCs at zonal and national level, including annual AR4D planning, programme review with stakeholders and evaluation workshops. 77 Limited complementary support for rice, as this crop is already being supported by the EAAPP. 78 Including research for livestock, aquaculture, transformation/value-addition [TARI, TALIRI, etc. under the Ministry of Industry Trade and Investment (industrial research, TIRDO, etc.] as per identified zonal priority commodities. ASDP II will not cover all ASLM research needs, but rather adaptive research that directly/ indirectly supports the focus CVCs. 79 About five and three AR4D projects per AEZ per annum for crops and livestock respectively. 80 i.e., Sustainable crop/livestock production systems and technologies natural resource/land use management (conservation agriculture), climate smart agriculture, post-harvest losses and nutrition issues by breeding for nutrient rich varieties, etc.). 76 Agricultural Sector Development Programme II (ASDP-II) iii. Improved user access to adapted technology options by strengthened research–extension linkages and technical and economic81 information management and communication. This will be achieved by zonal Technology Transfer and Partnership Units (TTPU)82 and more effective agricultural information management and communication of available technologies. The TTPU teams (crop/livestock technical and information specialists) will be empowered to act as strong links between zonal research teams and District CVC stakeholder Platforms (DCP) and designated crop, livestock and fish AR4D liaison officers (see s/c extension). The delivery capacities of TTPU teams in each AEZ will be strengthened in terms of human and technical capacities to handle knowledge and linkages between AEZ research network and the district agricultural facilitation team83 for crops and livestock, as well as the stakeholder innovation platform for priority CVCs. The zonal technology inventory will be updated and diffused while on-farm research and demonstration programme will be up-scaled for targeted CVCs in focused district clusters. Socio-economic capacities will be integrated into the technical teams to generate further knowledge on socio-economic characterization of farming systems, micro-level policy options, market efficiency and modelling of impacts generated by broader farmer use of improved technologies. Table 26: Crop and livestock research institutes in AEZ AEZa Crop AR4D Livestock/fisheries AR4D TALIRI TAFIRI Arid Selian & HORTI Tengeru Mpwapwa, Mabuki & Kongwa Mwanza & Kigoma Semi-arid (N&S) Makutupora, Hombolo, Ilonga, Dakawa Mpwapwa Kongwa, Naliendele Eastern coast & alluvial plains Mlingano, Mikocheni, Kibaha, Naliendele, Uyole, Katrin Dakawa Tanga + TVLA DSM (Kibaha & Temeke) TAFIRI–DSM Plateaux Uyole, Ukiriguru, Tumbi (b) Mabuki and Uyole Mwanza & Mara Northern highlands (bi) Selian & HORTI Tengeru West Kilimanjaro Mwanza and Mara Southern highlands Uyole & Kifyulilo (c) Uyole Mbeya& Kigoma; Western and SW highlands Maruku & Tumbi (d) Mabuki Kigoma /a AEZ adapted from Sokoine University of Agriculture, 2014. The National Livestock Research and Development Agenda (2015), Fisheries and Development Research Agenda (2015). iv. Effective agricultural information management and communication of available technologies will be promoted, using modern ICT at national and local levels. AR4D will contribute by: (a) establishing a national innovation sharing platform between agricultural research and extension; (b) compiling an updated technology information database; (c) adapting available technical information to the user community needs (farmers, entrepreneurs, agricultural training institutions, NGOs and others); and (d) facilitating users access through modern ICT (internet and mobile) for information exchange and learning processes (e-learning). This will require investment in effective communication infrastructure and human resources for developing innovative technology adaptation and dissemination pathways. 81 Partial investment budget analysis for farmers to make informed choices. 82 An alternative zonal AR4D structure to be implemented under TARI: the TTPU would take over (and consolidate) the functions implemented by Zonal Information and Extension Liaison Units (ZIELU) under ASDP-1. This arrangement fits well under the proposed restructuring of Crop Research Department under MAFC into the TARI, where TTPUs will continue to use the current Department of Research and Development innovative participatory approaches to engage its stakeholders along the zonal priority CVC. Within each AEZ, the TTPUs will include all Agricultural Research Institutes based within the respective zone, and strengthen the AR4D linkage with districts focal person, promoting agricultural technology transfer, and users. 83 The District Agricultural Facilitation Team includes the DAICO/DLFO and the technical subject matter specialists for crops, livestock, fish and rural development active at district level. 77 Agricultural Sector for Industrial Development v. Upgrading selected AR4D institutions towards sustainable research and development support for priority CVCs by: (a) contributing the institutional strengthening of Tanzanian Agricultural Research Institution (TARI); Tanzania Veterinary Laboratory Agency (TVLA), Tanzania Livestock Research Institution (TALIRI) and Tanzania Fisheries Research Institute (TAFIRI); (b) strengthening human resources for research and technical staff for crops, livestock and fisheries, based on capacity gaps and needs for CVC to be identified through a training needs assessment; (c) targeted support for priority research infrastructure and field and laboratory facilities and equipment of selected zonal ARI, TVLA, TALIRI, Livestock Training Agency (LITA), Fisheries Education and Training Agency (FETA) and TAFIRI; (d) promoting public/private partnerships84 towards sustainable funding mechanisms for agricultural research through ZARDEF; and (e) strengthening efficient linkages between TTPUs and district agricultural support teams for crops, livestock and fish. Among others, biotechnology (marker assisted breeding, genetic engineering, diseases diagnostics, bioinformatics, genomics, proteomics, gene tilling and metabolomics) will be an important cutting-edge science and researchers capacities need to be built in this area and related biosafety and biosecurity issues. In this and other high-tech areas, regional cooperation (e.g., EAC) will be sought to enable for higher efficiency on solving common issues and sharing of results85. 175. Effective planning, implementation, monitoring, evaluation86 of AR4D are important prerequisites to effective and quality research. Stakeholder involvement in research agenda planning, but also monitoring/evaluation is key for high quality and relevance. Therefore, ASDP II will track and assess the extent of use and effectiveness of research outputs at sector level and get feedback on adoption and impact of proposed technologies. 176. Livestock and Fisheries Research. The Directorate of Research Coordination, Training and Extension (DRTE)87 coordinates livestock and fisheries research implemented in accordance to the mandates of the TALIRI, TAFIRI and other research institutions such as the TVLA, the Tanzania Commission of Science and Technology (COSTECH), Sokoine University of Agriculture (SUA), LGAs, Dairy and Meat Boards, NGOs/community based organizations (CBOs) and other relevant stakeholder where research is undertaken. The coordination is also extended to all collaborative livestock and fisheries research activities in international research institutions/organizations. The priorities for livestock/ fisheries research across AEZs’ were identified as shown in Table 27. Table 27: Livestock and fisheries priority investment and action areas for research Action areasa Priority actions/activities Dairy cattle - Improved technologies for dairy productivity by breeding - Promote selection, use and conservation of indigenous livestock - Disease diagnostics & prevention and control of disease vectors/pests and pathogens Beef cattle - Improved beef productivity by breeding/selection, conservation of indigenous germplasm— genetic resources - Disease diagnostics & prevention and control of disease vectors/pests and pathogens Sheep and goat - Improved sheep and goat productivity by breeding/selection, conservation of indigenous germplasm—genetic resources Pig - Diseases and feeding Poultry (meat/egg) - Prevention and control of diseases and testing for quality feeds 84 The district CVC platform facilitates the dialogue among major commodity actors (producers, traders, processors, etc., public and private service providers (including research and extension) to develop a common strategy and work plan to improve the performance of targeted CVCs) 85 See the achievements of the EAAPP and regional collaborations with ASARECA. 86 Output indicators to be developed in Programme implementation manual and linked to intermediate outcomes. 87 DRTE coordinates planning, implementation, monitoring, technology dissemination and impact assessment of technical and socio-economic livestock/fisheries research programmes (including animal health and disease management, maintains a livestock and fish research database and promotes the dissemination of innovations. 78 Agricultural Sector Development Programme II (ASDP-II) Feed resources - Research on pasture and forage production Animal disease - Research on disease prevention and control/quality of animal diseases vaccines - Research on vectors, parasites and disease pathogens; control livestock inputs/outputs - Development of diagnostic kits and other biologicals Fisheries - Research on stock and catchment assessment and frame survey - Impact of human activities to water resources, including illegal unreported and unregulated fishing (IUU) - Research on reduction of post-harvest losses in sardines - Improved fish handling, storage, processing & distribution technologies and facilities - Impact of different processing technologies on nutritional value of the fish - Fishing gear technology, methods and crafts - Research on restocking in minor waters - Marketing processes and study on fish consumption pattern within the country - Research-extension linkages Aquaculture - Fish feed production and quality assurance; potential farmed species - Fish breeding, genetics, and biotechnology, hatchery technologies & quality assurance - Aquaculture system modelling - Research–extension linkages a Main investment elements are rehabilitation and consolidation of infrastructures and research facilities (ponds, cold rooms, water catchments, vaccine production, smoking/processing facilities, etc.), short- and long-term capacity building, and purchase of parent stocks (breeding bulls, bucks, does, poultry, fingerlings). Subcomponent 2.4: Access to mechanization services 177. The low level of mechanization88 is a major constraint towards increased smallholder productivity and production. GoT efforts for promoting mechanization, include: (i) tax exemption for importation of farm machinery and spare parts; (ii) public finance from AGITF and TIB-Agricultural window and commercial banks to extend loans for purchase of tractors and machinery; while (iii) some active savings and credit cooperative societies (SACCOS) provide loans to its members for purchasing agricultural machinery. Within this framework, ASDS-2 proposes the following required interventions: (i) collaborate with private sector on promotion of mechanization through demonstrations of modern technology (tractors, power tillers, harvesters, etc.) and simple farming implements and tools such as weeder, seed-distributor, etc.; (ii) facilitate agricultural financing services for agricultural mechanization; (iii) support educational institutes for producing qualified mechanical engineers needed in the sector; and (iv) create favourable business environment for importing agricultural machinery and spare parts and for domestic marketing. 178. Mechanization is critical to addressing labour bottlenecks and low productivity (production and post-harvest) and poor timing of critical farming operations (seeding/planting, weeding) among smallholder farmers. Intensification and growing cropped areas require mechanization to allow for optimal timing of operations and reduced drudgery in production and in post-harvest operations. Mechanization will need to be adapted and sustainable, while gradually progressing with farmers’ technical level and the size of the farming enterprise. Based on supports initiated under ASDP-1, further investment in agricultural mechanization will be facilitated, including by farmer organizations and the establishment/strengthening of privately owned mechanization service providers (commercial services) for increased sustainability. In addition, there is need to enable smallholders to use labour saving technologies such as zero or minimum tillage. 179. The initial interventions on mechanization will focus on building the financial and economic case of mechanization and developing the regulatory enabling environment to facilitate the emergence and growth of private sector tractor and mechanization services. The programme will also ensure that legislation is in place to facilitate leasing and the ability to use non-fixed assets as collateral, so that the private sector has multiple instruments to facilitate their investments in agricultural mechanization. 88 14% using tractor (including 2-wheel tractor) services and about 24% oxen (Source: Agric. Policies 2013). 79 Agricultural Sector for Industrial Development 180. The objective is to facilitate access to adapted agricultural mechanization89 services to increase labour return towards sustainable productivity, value addition and farmer income. Support to private mechanization services (production, post-harvest and transport) will enable smallholder producers to increase their labour productivity, use sustainable soil management techniques, but also to increase the attractiveness of the sector for young entrepreneurs (‘agripreneurs’) and rural youth. Smallholder access to private mechanization services will be enhanced by updating the national strategy for sustainable agricultural mechanization90, including the regulatory framework for sustainable and profitable private service arrangements. Innovative approaches (including leasing), bringing together the tractor/equipment companies, commercial banks and mechanization service providers should be facilitated to allow for increasing the business of current service providers and allow for new entrants where opportunities exist. 181. Further to the policy and institutional framework for labour-saving technology (see s/c 4.1), ASDP II will promote improved farm and environmental management practices that reduce farm energy inputs and costs, protect the soils and environment and produce good crops, livestock, fish and other farm produce. Main activities will include: a. Strengthen the demand for mechanization services in agricultural production and post-harvest operations by demonstrations, sensitization campaign and smart subsidies (vouchers) to raise farmers’ awareness for sustainable agricultural production and productivity growth. b. Improved farmer group or cooperatives access to small-scale mechanization options, including two-wheel tractors and oxen-drawn equipment for production, post-harvest handling and transport. c. Enhancing supply of viable private mechanization services for increased productivity and production through strengthening existing successful contractors, building on business case/repeatable business model and new business models (leasing, triangular contracts between importers, financial institutions and mechanization service providers, etc. that encourage agricultural mechanization through leasing arrangements and other financial supports for leveraging private sector investments in technology innovations. d. Capacity development for equipment/machinery information acquisition and evaluation for sustainable agricultural mechanization (conservation agriculture tools) service provision, operation and maintenance (resource and training centre). 182. This strategy will be developed during the first year of the programme, and implemented from the second year onwards athrough axes: (i) stimulating private service offer by access for stakeholders in the mechanization chain to professional training and technical information on equipment/machinery operating a sustainable agricultural mechanization resource and training centre; and (ii) increasing demand for adapted agricultural mechanization services by subsidies (i.e., targeted vouchers) to facilitate the purchase of adapted implements for small-scale mechanization (oxen/two-wheel tractors) and to access to private mechanization services for production and postharvest operations. 183. Human resource development and setting-up a reference centre for agricultural mechanization could be implemented through a network of selected ATIs or a specialized training centre networking with selected ATIs for training mechanization technicians and tractor operators. This would allow for breaking the vicious cycle of poor operation capacities, breaking machines, little reparation capacity and lack of spare parts and finally no successful business for entrepreneurs. Developing business should allow for tractor importers to set-up regional selling and reparation units. Furthermore, from the beginning, mechanization service investors should be encouraged to equip themselves with conservation agriculture tools and equipment for sustainable soil management (see also s/c 1.1). 89 Sustainable mechanization is to increase the use of labor-saving technologies, including appropriate mechanization of production (conservation farming in s/c 1.3), value addition (see s/c 3.3 on agro-processing) and other farm management related operations. 90 Targeting sustainable soil management within the framework of conservation agriculture (see also ‘Save and grow’, FAO 2012) 80 Agricultural Sector Development Programme II (ASDP-II) Sub-component 2.5: Food and nutrition Security 184. Food security and nutrition91 takes several forms, all of which affect the quality of life and productivity of rural people. Chronic, transitory and emergency food insecurity due to poor agricultural productivity, food inaccessibility and natural disasters all play a role. The Comprehensive Food Security and Vulnerability Analysis in Tanzania (2012) found that in 2010–2011 about 730,000 households (8%) were vulnerable to food insecurity, of these around 150,000 households (or 2% of all households) were considered as chronically food insecure. Northern and central regions were the worst affected and the level of food insecurity in some areas was high as 45%. Food security is highly dependent on rainfed agriculture which also is susceptible to the vagaries of weather, especially poor rainfalls prompting for regional food shortages. Therefore, there is need to promote and embark on irrigated agriculture and diversification of crops (drought resistant crops) for greater reliability of food supplies. Malnutrition is one of the most serious constraints to human and economic development: chronic malnutrition in 2010 was very high with 42.0% stunting (DHS, 2010) of children younger than 5 years of age being stunted. Severe acute malnutrition is a rampant in Tanzania, especially among children under five and women of child bearing age. Child malnutrition is much worse in rural areas than in urban areas and much higher in the poorest quintiles, resulting from inadequate consumption and/or utilization of food. This is caused by inadequate knowledge on nutrition, food preparation and dietary practices, especially for children, and by women’s heavy workload. 185. The National Food Reserve Agency (NFRA) was initially set up as a food reserve. The NFRA now serves as a buffer stock in an attempt to keep farm gate prices up despite good92 harvests. NFRA buys significant quantities of maize (300,000 tons in 2014) frequently at above-market prices from farmers. NFRA is likely to introduce more distortions in the sector, leasing some storage capacity from the private sector and thereby be reducing the ability of the private sector to even out seasonal fluctuations93. 186. Policy measures94 to mitigate effects of possible food price spikes and food insecurity for vulnerable population segments will be increasingly important for stable socio-economic development. The Government of Tanzania will adopt measures to improve food access, including: (i) strengthen and improve the quality of Crop Forecast and Early Warning systems, within the overall framework of agricultural statistics; (ii) strengthen food reserve and distribution system by NFRA including improvement of storage facilities and effective collaboration with the private sector; (iii) regulate according to necessity food imports, with careful considerations on the food demand and supply; (iv) establish an active link with member countries in the EAC and SADC for monitoring regional food security situation, including use of Tanzania’s food for emergency operations in the region. 187. Safety nets. Natural disasters in the country include drought, heavy rain followed by flood, migration of disease and pests for crops and livestock, deforestation, soil degradation, among others. Crop and livestock production are directly affected by disasters, especially for smallholders at the limit of acute and/or chronic food insecurity and poverty. Impacts of climate variability and change are expected to become more significant in the future therefore immediate actions are required toward increased resilience in agriculture (see preventive measures in s/c 1.3). For preparedness and quality response to natural disasters, required interventions include: (i) improve the Crop Forecast and Early Warning system as well as pest and disease surveillance system for early detection; (ii) coordinate the country’s meteorological information collection and sharing system; (iii) respond effectively to the warnings and improve the preparedness for emergency disasters; (iv) strengthen the collaboration with relevant organizations on migratory diseases and pests for early detection and effective and coordinated response; and (v) coordinate safety net activities in the agriculture sector to ensure vulnerable households needs are addressed. 91 Food security means that all people at all times have physical and economic access to adequate amounts of nutritious, safe, and culturally appropriate foods, which are produced in an environmentally sustainable and socially just manner, and that people are able to make informed decisions about their food choices. 92 Source: Agriculture Sector and Public Expenditure Review—Tanzania Mainland 2014 (March 2015). 93 See further details in ASR-PER section. 94 See details in ASDS-2 (June 2015). 81 Agricultural Sector for Industrial Development 188. Nutrition Security. Malnutrition is often inherited from one generation to the next: maternal malnutrition negatively affects the consequent educational achievement and improved productivity in adulthood. The effects of malnutrition are also magnified by unsafe drinking water, poor hygiene, and lack of information and education on good nutrition and sanitation. Achieving nutrition security requires concerted multi-sector actions, including: (i) promote awareness among rural households, especially focusing on child and maternal malnutrition, good nutrition and sanitation; (ii) more effective use of nutrition officers at local level who can be part of agricultural extension service and training on nutrition aspect under the DFT; (iii) strengthen and scale up food fortification of micronutrient; (iv) provide effective social safety net programmes95 for vulnerable groups who chronically require protection against shocks (food/cash for work); and (v) enhance collaboration with related ministries on the school feeding programmes in rural areas where needed. 189. Food security and nutrition are mainstreamed in several sector policies, strategies and programmes (i.e., the Tanzania Agricultural Investment Plan, the Tanzania Social Action Fund (TASAF) or the Productive Social Safety Net, etc.). Within the Scaling Up Nutrition (SUN) movement, there is high level political attention to nutrition in Tanzania spearheaded by the High Level Steering Committee on Nutrition (HLSCN), which brings together permanent secretaries from nine relevant sectors, development partners, UN agencies, CSOs, university and business. A multi-sector Nutrition TWG chaired by the director of the Tanzanian Food and Nutrition Centre (TFNC) supports the HLSCN. All partners are fully engaged in scaling up nutrition efforts and participate in MSIP. 190. The objective of this sub-component is to ensure sustainable food security and nutrition in Tanzania by involving all stakeholders in implementing strategies geared at ensuring food security and nutrition at all levels. The focus will be on ensuring sustainable food availability96, food accessibility97 and proper food utilization to be achieved through food production, stock management, trade/markets and adaptive strategies/measures against negative effects of disasters. Main strategic sector supports are centred on 4 action areas: (i) crop/livestock monitoring and early warning for increased food security; (ii) strategic NFRA; (iii) post-harvest management for reduced food loss; and (iv) contributions to nutrition improvement. 191. Crop/Livestock monitoring and early warning98. Since 1992/1993, the then MAFC developed and operated the food security assessment procedure, initially seasonally using a sample survey questionnaire. This was later expanded into use of a routine data retrieval system. Over time, sample surveys using the National Master Sample (NMS) from NBS have been used to address the challenges in district estimates through the routine reporting system. Initial interest was on forecasting and informing the government and the public, through AGSTATS for Food Security documentation (preliminary and final forecasts), other monthly food security situation and decadal rainfall reports. However, the system has been instrumental in providing basic data for the management of food and for the agriculture sector as a whole. 192. The Integrated Food Security and Nutrition Assessment System (IFSNAS), which is known in Kiswahili as Mfumo wa Uchambuzi wa Uhakika wa Chakula na Lishe (MUCHALI), , is to: (i) ascertain the impact of the food production shortfall from the year (x-1) on the livelihoods and food security and nutrition among the populations in LGAs previously identified by the then MAFC, MLFD, and food security and nutrition agencies; (ii) identify the food insecure and vulnerable populations resulting from the food access problems in year (x) and establish the magnitude of the problem; and (iii) determine and recommend appropriate interventions for the affected populations. 95 For example, TASAF (Tanzania Social Action Fund) to be aligned with agricultural interventions for sustainability. 96 Food availability means ensuring sufficient food for all people through production, stocks and trade to be achieved through promoting food production, reducing post-harvest losses, ensuring appropriate food management at household level and strengthened coordinated food aid. 97 Food accessibility refers to the ability of household members to access food to meet their nutritional requirement, which depends on the food self-production and income level of the consumers. 98 Integrated Food Security and Nutrition Assessment System (IFSNAS), which is known in Kiswahili as “Mfumo wa Uchambuzi wa Uhakika wa Chakula na Lishe” (MUCHALI). 82 Agricultural Sector Development Programme II (ASDP-II) The methodology involves a comprehensive livelihood-based food security and nutrition (LFSN) approach using the Integrated Food Security Phase Classification to guide the analysis and report writing. The LFSN approach involves integrated broad livelihood-based indicators such as crop, livestock and fish production, supplies and prices, nutrition, access to water, livelihood assets and coping strategies, as well as weather parameters, particularly rainfall, and other livelihoods systems. In addition, the prevalence of severe acute malnutrition and global acute malnutrition is measured. Overall, the annual report is provided in a timely manner to the decision-making authorities, but some challenges in achieving appropriate levels of accuracy and reliability continue to be areas of concern to be addressed. Therefore, capacity building, rainfall data collection system, food security questionnaire1 (FSQ1), cooperation and technical meetings, and timely availability of funds, have been earmarked as critical issues to be tackled for improved implementation. 193. Safety net and resilience. A proportion of rural households will continue to need special support to help them achieve food security and protect them against shocks, principally droughts. It is expected that advancements in other areas of the ASDP II will progressively reduce the number of households requiring food aid and other forms of assistance to survive. The effectiveness of targeting social safety net programmes for vulnerable groups will be sharpened, and the prevalence of child and maternal malnutrition is expected to decline. As the size and cost of the safety net programme begins to decline, more resources will be available for disaster risk management including disaster preparedness and mitigation (see also resilience in component 1.3). Additional strategic interventions such as productive safety net and household asset protection will also be implemented to support productive investment through conditional transfers that provide pathways out of poverty via rural infrastructure development, market access, agricultural productivity improvement, education, health care and other services. 194. NFRA and capacity of strategic food reserves. The capacity of strategic food reserves (on recurrent government budget) needs to consider: (i) an appropriate level of stocks to hold; (ii) transparent protocols and rules for the acquisition and release of stocks, stock rotation, and the use of financial instruments to complement physical stockholding; and (iii) policies and procedures for dealing with food price spikes of the type currently being experienced. Furthermore, higher levels of production systems resilience, transparent food crops markets and contracts with the private sector should allow for gradually decreasing levels of physical NFRA food reserve stocks to the minimum required level. Finally, the linkages between NFRA and crop forecast/early warning (improvement of an integrated system)—accuracy of data including private sector and farmer stocks—need to be strengthened by an efficient information exchange and stakeholder decision-making system. 195. Develop Livestock Early Warning System. For the livestock and fisheries sector, early warning against potential shocks is key to enabling the government to take appropriate measures to mitigate major impacts, especially on small-scale farmers. This includes among others the implementation of priority actions such as: (i) awareness creation among pastoralists and agro-pastoralists on mitigation and adaption strategies; (ii) training of district and community monitors for data collection; (iii) resource mapping, selection and setting of livestock safety net zones and sites, and purchase of equipment and facilities; (iv) training for new staff, refreshment courses for ongoing staff at headquarters and local level (community livestock early warning); (v) retooling towards field efficiency, data processing and analytical capacity; and (vi) efficient and cost effective monitoring system of pasture, water and animal feed resources. 196. Livestock feed security and resilience against shocks (see also s/c 1.3) will gradually be improved by: (i) construction of 10 dams, 20 boreholes and 20 charcoal dams; (ii) rehabilitation of 4 dams, 20 boreholes and 50 charcoal dams; (iii) reinforce and strengthen animal feed inspectorate services; (iv) training of pastorals and agro-pastorals on feed conservation and utilization; and (v) grazing land management plans in demarcated grazing lands in 40 LGAs. 197. Post-harvest management for reduced food loss. Post-harvest management systems target to achieve effective and efficient food and nutritive supply by addressing key issues between production 83 Agricultural Sector for Industrial Development and consumption of agricultural commodities. High post-harvest losses remain a central concern, as different research studies demonstrate that farmers lose up to 40% of produced cereals, although losses vary by crop type and geographical zone. The main issues are physiological degradation and infestation by fungus, insects and rodents during transportation, storage and processing, especially for highly perishable products (see component 3.2). There is a need to harmonize and align functions and support between the ministry’s department responsible for Food Security and the Ministry of Industry Trade and Investment, especially for activities related to storage infrastructure and management, reduction of post-harvest losses, value addition and processing agricultural products. 198. Contribution to integrated nutrition improvement. The National Nutrition Strategy (NNS), finalized by the Tanzania National Food Centre (TNFC), addresses high levels of chronic malnutrition by working with multiple sectors and across government agencies. The NNS recognizes that increased food production does not necessarily translate into improved food security and nutrition outcomes, as households must also be provided with information and education about good nutrition and sanitation practices. Besides emergency support, additional interventions such as productive safety net and household asset protection will also be implemented by supporting productive investment and appropriate food preparation and utilization of nutrient rich food is key to improve food utilization levels. Within a cross-sectoral approach, better integration of dietary diversification and changes in nutrition behaviour will be integrated into all rural sector programmes, including education and health. In addition to producing more and better food, rural households, which are especially vulnerable, need to understand how to use the food that they have in the best possible way. 199. Better integration of dietary diversification and nutrition behaviour change into all agriculture sector programmes. Rural households need to understand the importance of diet in overall well- being and have the knowledge to use the food that they have in the best possible way. In this context, there are potential tensions between policies that encourage agricultural commercialization (often involving increased specialization) and the need to maintain diversification of farming systems and diets. Other aspects of food and nutrition policy include food safety and food fortification: current standards need to be improved including microbiology, pesticide residues, labelling standards and safe storage and transport. The food safety and new food fortification standards for oil, wheat and maize flour (and other food and indirectly feeds) need to be enforced: this is also important in accessing export markets and will be increasingly important in maintaining a competitive position in the high end of the domestic market. The summary of proposed interventions for food security and nutrition is given in Table 28. Table 28: Proposed action areas for food security and nutrition Action area Proposed activities & investments 1. Early Warning System for improved food security Strengthened institutional capacity to undertake crop and livestock forecasting tasks and improved working environment i. Long-term training for new staff, refreshment courses for ongoing staff and hands on training retreats for all ii. Retooling towards field efficiency, data processing and analytical capacity Rainfall data collection and crop monitoring i. Assessment and evaluation towards strengthening rainfall stations to fulfil early warning system interests (timeliness, reliability and accuracy) ii. Renovate critical rainfall stations (total of about 600) throughout the country (automatic rainfall and temperature gages) 84 Agricultural Sector Development Programme II (ASDP-II) Action area Proposed activities & investments 1. Early Warning System for improved food security Food Security Questionnaire1 (FSQ1) for crop forecasting with improved data accuracy and reliability i. Improve and re-install this tool countrywide following the national master sample established in collaboration with NBS ii. Further integration of AASS, ARDS and early warning information collection iii. NMS should be correctly sized to enable acquisition of district level estimates (current regional estimates) iv. Adapt and strengthen MUCHALI timeliness and reliability Reliability and accuracy of the information for policy decision- making i. Strengthen existing cooperation between NBS and the Ministry of Agriculture (collaboration in short-term surveys) ii. Hold technical meetings with district and regional staff, strengthening of LGA capacity with support from central level Livestock/fisheries early warning and mitigation i. Training of district and community monitors for data collection; retooling towards efficient data collection, processing and timely reporting ii. Resource mapping (effective monitoring system of pasture, water and animal feed resources) selection and setting of livestock safety net zones and sites, and purchase of equipment and facilities iii. Awareness creation among pastoralists and agro-pastoralists on mitigation and adaption strategies iv. Livestock feed security and resilience against shocks to be improved by construction/rehabilitation of dams, boreholes & charco dams v. Reinforce and strengthen animal feed inspectorate services vi. Training of pastorals and agro-pastorals on feed conservation and use vii. Grazing land management plans in demarcated grazing lands (40 LGAs). 2. National Food Reserve Agency (NFRA)—Safety-nets Food reserve management i. Store and manage minimum/appropriate level of national food reserve ii. Involve private sector in food reserve management iii. Promote community safety net systems for food, feed and seeds, where appropriate 3. Reduction of post-harvest losses (see also s/c 3.2: Value addition and agro-processing) Large post harvest losses due to poor support systems/ technologies and limited handling capacity i. Develop guidelines for appropriate post-harvest handling and storage practices for selected crops ii. Promote and disseminate technologies that promote better handling and improved storage and preservation of food and food products at all levels iii. Improved transformation/value addition and marketing support infrastructure for food quality and minimized food losses (see s/c 3.2) 4. Nutrition improvement Reduce malnutrition in Tanzania by improved food and nutrition availability, accessibility, stability and utilization (Five food insecure regions) i. Mainstream awareness on food security and nutrition security issues at all levels in the agricultural sector (mainstreamed in extension) ii. Strengthen the food security and nutrition information system, data quality/ relevance and mapping for providing timely warning signals iii. Promote diversify/multiple adaptive strategies for sustainable food security of households iv. Implement productive safety net and household asset protection by use of nutrient rich food for improved food utilization levels v. Promote consumption of protein-rich food for children & pregnant women vi. Promote food fortification and blending techniques of flour to improve nutrient contents (including bio-fortification—see research) vii. Encourage cost-effective technologies to reduce women’s workload for more time for food preparation and childcare viii. Improve basic food safety especially with respect to the control pesticide residues and mycotoxins including aflatoxins ix. To empower LGA staff on the Food Security and Nutrition Analysis System (district nutrition focal person/officer to coordination all ministries) 85 Agricultural Sector for Industrial Development 200. Investment summary for Component 2: COMPONENT 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY—BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Table 29: Development budget/investment projection for Component 2 (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,913 772,652 849,529 838,081 921,148 4,693,323 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,373 9,720 9,349 8,506 9,222 41,170 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389 136,695 150,284 164,670 181,057 782,095 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176 2,652 2,800 2,962 3,141 15,731 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664 93,408 768 1,099 987 97,926 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146 4,533 5,008 4,246 4,639 19,572 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,115 5,176 7,350 4,460 2,090 23,191 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,090 50,853 48,517 6,658 4,388 165,506 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources 2,537 2,134 2,199 2,147 2,319 11,336 2.2.1.8 Improvement of plant health services 13,322 11,191 7,608 1,389 478 33,988 2.2.1.9 Production of vaccines and drugs 44,570 36,191 39,700 3,705 4,380 128,546 2.2.1.10a Improvement of livestock health services 262,550 295,128 332,216 371,559 420,078 1,681,531 2.2.1.10b Improvement of aquatic health services 1,518 1,238 1,241 1,340 1,395 6,732 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,559 29,197 29,504 8,708 9,516 84,484 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,409 16,384 11,616 11,110 11,371 62,890 86 Agricultural Sector Development Programme II (ASDP-II) COMPONENT 2: ENHANCED AGRICULTURAL PRODUCTIVITY AND PROFITABILITY—BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Table 29: Development budget/investment projection for Component 2 (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,833 3,895 2,683 2,738 3,011 17,160 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,250 5,753 5,699 5,707 5,717 32,126 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,153 11,722 12,960 14,297 10,394 63,526 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,538 22,167 23,955 25,921 28,084 120,665 TOTAL COMPONENT 2 1,925,105 1,510,689 1,542,986 1,479,303 1,623,415 8,081,498 E. Component 3: Commercialization and Value Addition (building competitive commodity value chains) 201. Under ASDP-1, limited progress was recorded in supporting agricultural marketing and value chain development. key constraints to value chain development include: (i) agriculture remains characterized by low crop and livestock productivity and commercialization levels; (ii) limited private sector involvement in agribusiness; (iii) policies that do not allow value chains to fully benefit from regional integration; and (iv) proliferation of uncoordinated activities in agricultural value chain development with a risk of inconsistent approaches. Furthermore, at implementation level, further issues were identified such as: (i) design and implementation flaws; (ii) insufficient value chain diagnostic and mapping at local, regional and national levels; (iii) weak implementation capacities in both the public and private sector; and (iv) limited internalization of past experiences, especially for market access and market information. 202. The commercialization initiative is expected to produce fundamental changes in the structure and functions of Tanzania’s agricultural sector including: (i) increased amount of quality agricultural produce entering in the domestic and export market channels; (ii) diversification of smallholder production (and income) from higher value (non-staple) crop and livestock products; (iii) increased supply of raw materials to the industrial sector; (iv) improved farmer access to inputs and financial services; (v) stronger farmer organizations; and (vi) improved infrastructures and communications. The higher levels of commercial activity are also expected to enlarge opportunities for rural non-farm business enterprises and both farm and non-farm employment, including for youth. 203. The Commodity Value Chain (CVC) Approach. Value chain development refers to the various stages from production, processing and marketing/distribution systems of key commodities, including value addition. The approach, schematically captured in Figure 16, shows the issues faced at each stage towards commercializing and professionalizing value chain characteristics and overall performance. There is a clear focus on smallholder producers and improving their role and relationships within the value chain(s) that they belong to. Particular attention will be given to the development of the institutional capacity of smallholder organizations to negotiate and manage new marketing arrangements with private sector actors, leading to productive alliances and viable commercialization partnerships. 87 Agricultural Sector for Industrial Development Figure 20: Value chain approach of ASDP II Constraints along the Value Chain Intevention Focus Areas for ASDP 2 Activities for Commercialisation Activities for Empowerment and Organisation ASDP 2 Competitive Funds for Stakeholder business, technology Uutake, enterprise support, commodity profile marketing and organisational support Organisational support to value chain smallholder and Stakeholder - business planning, rules of engagement,through existing structures Value Chain Support (all stakholders - private and public) through activities such as technology and equipment, storage, market development, infrastructure (markets, roads, electricification,irrigation), acces to financing and quality of produce Input Suppliers Producers Market Traders and Processors Input supply shortages, timely delivery and quality Production problems and productivity Processing problems for quality and quantity and consistency Markerting to consumer - awareness, price high prices, imported commodity 204. Towards building competitive value chains, ASDP II will support smallholders to graduate from subsistence towards farming as a business, by forging linkages with commercial input and output supply chains to connect with a growing agro-industrial and urban consumers demand. A diverse, inclusive, competitive and robust private sector will spearhead the development of agribusiness, driven by improved investment climate, trade capacity and business linkages and improved capacities for advocacy and service delivery within effective PPP. 205. The component aims at expanding farmer access to value addition and competitive marketing systems for priority commodity value chains, driven by an inclusive, strengthened and thriving private sector and effective farmer organizations. Strategic objectives, outcomes and related indicators are defined, as shown in Table 30. 88 Agricultural Sector Development Programme II (ASDP-II) Table 30: ASDP II Component 3: related specific ASDS-2 objectives and outcomes Objective Outcomes Outcome Indicatorsa Comp. 3. To improve and expand marketing and promote value addition by a thriving competitive private sector and effective farmer organizations h Strengthened and competitive commodity value chains - Value and monetary value of exports - Monetary value of new Foreign Direct Investments (FDI) and private capital flows to agricultural sector - Job creation by new and expanded investment in agribusiness - Volume and monetary value of food imports - Profitability of produce and products at farm and enterprise leves - Market share of products at all market levels - Product’s compliance to national and international standards - Standardized marketing infrastructures along the value chains - Participation of vulnerable groups (women, youth, and pastoralist) in value addition - Participation of vulnerable groups (women, youth, and pastoralist) in commercialization - Participation of vulnerable groups (women, youth, and pastoralist) in decision making along the value chain - Benefits accrued by vulnerable groups (women, youth, and pastoralist) from main ASDP II interventions along the value chain s/c 3.1 Access to farmers and rural infrastructure (markets/ storage) improved - % change in investment in market infrastructure - % farmer/ FO/ Traders using improved market infrastructure in rural areas s/c 3.2 Agribusiness and value addition promoted - % change of value added produce and products - % change in post harvest loss Policy, regulatory and institutional environment required to generate expanded participation of broad-based strengthened private sector actors in all aspects of the agriculture strategy and its effective implementation. 206. Component 3 is sub-divided into 2 sub-components: Component 3: COMMERCIALIZATION AND VALUE ADDITION (BUILDING COMPETITIVE CVCs) S/c 3.1: Marketing S/c 3.2: Agribusiness development: value addition & agro-processing 207. Engaging smallholders and fostering strategic partnerships between priority commodity value chain stakeholders, from producers to marketers and agro-processors, will drive the promotion of smallholder commercialization and lead to improved product quality and competitiveness in domestic and regional markets. The focus of this component is to enhance efficiency for farmers and their organizations, to access profitable input/output markets and value addition (including agro- processing) opportunities in priority CVCs, and by setting the environment for the private sector to invest. Within the appropriate policy framework (see s/c 4.1), this will happen through facilitation of the public sector, strong stakeholder (farmer, processors, marketers, etc.) organizations, provision of 89 Agricultural Sector for Industrial Development relevant information and advisory services, improved linkages and/or partnerships for investments along the target value chains, and the availability of critical infrastructures and other facilities. 208. Increased offer and demand for targeted commodities will be achieved through a combination of: (i) use of improved technologies, input market consolidation and mechanization services; (ii) irrigation development towards double cropping, mainly for rice and high value crops (horticulture); and (iii) reduced post-harvest losses and value addition; and (iv) improved marketing promoted by capacitated farmer organizations, alliances with other CVC stakeholders and adequate socio-economic infrastructures and facilities. 209. Prioritization. To avoid thin spreading support, the program will primarily target key CVCs in local farming systems, offering high potential for quantitative and qualitative growth: agro-ecological potential, importance in local farming system (see also ASDP-1 district priorities) and market demand will be key selection criteria. Within this line, SAGCOT concentrate solely on priority commodities (i.e., maize, rice and sugar), mainly in the Southern Highlands. As a national sector programme, ASDP II will initially focus on priority CVCs for crops, livestock and fish in each AEZ, and implement activities within a limited number of high potential district clusters to be determined by the regional stakeholder innovation platforms. Practically, based on the analysis of growth prospects/potentials for priority value chains in respective AEZs, specific strategies to achieve sustainable growth are summarized as follows: Table 31: Objectives for priority CVC and strategies to achieve expected results Outcomes Priority AEZ Strategies to achieve expected outcomes MAIZE: Tanzania becomes a major maize exporter in the region. Based on recent trends, Tanzania should aim to be exporting over 500,000 t of maize each year, mainly to neighbouring countries (Kenya) Southern Highlands West and south-west Northern highlands i. Incentives for increased productivity and production by more efficient use of available technologies (seed and fertilizers) ii. Warehousing for improving market incentives: could lift average farm gate prices as much as 50% iii. Better revenues would in turn facilitate more farmer investment in production (further broaden input markets) iv. Promotion of conservation agriculture for resilient sustainable production system v. Rotations maize/soya beans (nutrition and livestock) vi. Formation of cooperatives to earn economies of scale RICE: Tanzania achieves self-sufficiency in rice production (and starts to export these grains (potential to become a regular exporter) East All irrigated i. Increased productivity—efficient use of improved technologies ii. ‘Block farm’ management for improved irrigation efficiency iii. Irrigation infrastructure rehabilitation/extension iv. Warehousing/marketing and value addition linkages v. Counter-season irrigated vegetables vi. Strengthen management capacities of existing paddy schemes OIL CROPS: Tanzania food oil self-sufficiency (reducing by 50% dependence on palm oil imports) Semi-arid (N) (sunflower) i. Incentives for increased sunflower productivity using adapted hybrids and integrated soil & water management ii. Rotation/relay cropping with pulses iii. Grouping/grading and warehousing (farmer organizations) iv. Promotion of medium scale FO/private value-added industry Semi-arid (S) (sesame/sim sim) i. Productivity increase (varieties, fertility management) ii. Incentives for FOs for bulking, grading (varieties) & improved marketing/export of their produce (price increases up to 50%) MILK: Tanzania substitutes 25% of its milk product imports by local production Tanga Peri-urban i. Improved breeds, improved feeding and health management ii. Dairy farmer organizations / cooperatives; grouped marketing iii. Milk collection centres, quality control iv. Improved feeds (soya/maize, etc.) 90 Agricultural Sector Development Programme II (ASDP-II) Outcomes Priority AEZ Strategies to achieve expected outcomes MEAT: Satisfy local demand and export quality meat (Middle East) Arid Semi-arid West & Southern Highland i. Improve breeds of meat animals ii. Establish and Strengthen livestock stakeholders Associations along the meat value chain iii. Establish and strengthen feedlot cattle production for beef iv. Conducting and strengthening market information services Horticulture (fruits and vegetables). Production for consumption & export All peri- urban areas & highlands i. Controlled/greenhouse production ii. Irrigation for counter-season production iii. Input/output marketing organization Traditional cash crops (cashew, coffee, sisal etc.) Increased export quantity and quality i. Increased productivity and enhanced product quality ii. Target bio-product windows on international markets iii. Local value addition (cashew, coffee, tea, etc.) iv. Diversify traditional products Goat and chicken products. Contribute to improved HH FS/ nutrition and farm revenues All AEZ i. Access to improved breeds ii. Improved management skills, integrate in household farming systems iii. Strengthened animal health services (including vaccination) iv. Feeding strategies based on complemented farm residues v. Commercialization of chicken and goat meat and products Fish Become major fish producers and exporter along the coast of Indian ocean. Making sure that, fishing activities is sustainably done and contribute to livelihood of fishers and GDP Major lakes, (Victoria, Tanganyika, Nyasa and Rukwa). Also, rivers and coast of the Indian ocean waters i. Ecosystem approach to fisheries management skills improved ii. Establishment of registration of beach management units iii. Value addition to fisheries products iv. Reduction of post-harvest losses to zero v. Promotion of pond and cage culture farming in lakes/ocean vi. Facilitation private sector producing quality and quantity fish fingerlings and feed vii. Facilitate aquaculture training institutes to impart practical skills Source: Compiled by the FAO mission for ASDP-BF, 2013 210. Capacity building and Investment phasing. Institutional capacity building, promoting stakeholder organization and value chain MSIPs and agribusiness support services remain fundamental for CVC development (see also s/c 4.1). Agribusiness support services will be contracted-in to agribusiness PSPs, which will also provide specialized training to assist target beneficiaries to prepare investment plans, strengthen management capacities and improve access to finance. Activities will be piloted in each AEZ/clusters and be gradually (i) scaled out across a larger number of interested districts; and (ii) scaled up using complementary local CVC options for diversification. Regional commodity MSIPs will decide on the priority investment schedule, based on opportunities and available capacities to achieve expected impact. 211. Building on ongoing programmes, ASDP II will gradually expand and cover all AEZ with consideration and formation of district/CVC clusters. The range of priority commodities for crops, livestock and fisheries will be consolidated gradually, as per stakeholder choices, to achieve a broader-based growth for rural poverty reduction. Regional MSIPs for priority CVCs will allow for linking local specificities (DADP priorities) to zonal and national priorities towards focusing investments and economies of scale. 212. Financing at local level. A competitive matching grant will be made available under this component, as top-up fund through the existing DADG, for financing profitable CVC investments and building partnerships in local agribusiness development. 213. Strengthen local coordination mechanism. Continuous support to crop and livestock extension, along local priorities and capacity building for planning, implementation and follow-up of priority CVC activities. This includes support to district level MSIPs for prioritized CVCs, involving public and private stakeholders. 91 Agricultural Sector for Industrial Development 214. Integrated support involving innovations and capacities for production, value addition and marketing will induce required outcomes in performances of priority value chains towards sustainable changes in local production systems. Overall, the ‘Rural Commercialization and Value Addition’ component will support building competitive value chains through activities grouped in four sub-components: (i) farmer empowerment and organizational strengthening; (ii) value addition and agro-processing; (iii) access to markets; and (iv) access to rural financing. Subcomponent 3.1: Marketing 215. The adoption of the Agricultural Marketing Policy (AMP, 2008) paved the way to collaboration between the public and the private sector, such as MVIWATA, MUVI and the Rural Livelihood Development Company (RLDC) to empower producers and enhance market linkages. There have been several programmes/projects in recent years in support of agricultural marketing improvement: the largest being the Marketing Infrastructure, Value Addition and Rural Finance (MIVARF). Other programmes in support of market development include PADEP, DASIP, and some other projects supported by NGOs. 216. Domestic, Regional & International Trade. The Government of Tanzania will continue to promote domestic, regional (EAC99 and the Southern African Development Community (SADC)) and international trade for agricultural and food commodities. The required interventions include promoting and strengthening: (i) internal and external trade under the Tanzania Trade Development Authority (TANTRADE); (ii) campaigns to use “Made in Tanzania” products; (iii) key traditional cash crop exports including tobacco, coffee, tea, cashew nut, cotton and their processing; and (v) increasing export of fish and horticulture, but also strategic export of maize and rice to neighbouring countries. To this end, the government proposes to expand well-functioning export processing zones in the prioritized regions and to reinforce the current system of regular consultations with private sector stakeholder associations about procedures and regulations impacting trade benefits and profitability. 217. Market access. ASLMs will collaborate with various stakeholders to implement policies, enforce laws and regulations and create a favourable environment for domestic, regional and international marketing activities, including: (i) establish and operationalize the Agricultural Commodity Exchange for selected commodities; (ii) raise stakeholders awareness on the required marketing standards and quality and oversee implementation of grading and standard protocols for different commodities; (iii) continued review of existing legal and regulatory framework of agricultural marketing; (iv) improve the market information system and its use to support commercial decision-making; (v) strengthen the systems for enforcing food safety controls based on traceability (including barcodes) and proper handling; and (vi) improve enforcement of the regulations and procedures for appropriate treatment of agricultural traders and transporters to minimize non-tariff barriers. 218. Improved rural and marketing infrastructure (roads, markets, private and public storage facilities, electrification, telecommunication, etc.) is a high priority for efficient inputs and output marketing and to attract private investment in agricultural related activities such as agroprocessing, but also increasing producer prices, farmer incomes and rural employment opportunities. Improved transport infrastructure, dissemination of market information and easing of cross-border trade restrictions can all play a role. 219. The private sector is expected to take the lead in processing and marketing of agricultural commodities so that they satisfy consumer demand for quantity, quality and safety. As domestic and regional markets expand and become more discriminating in terms of quality and food safety the issue of sanitary and phytosanitary standards will become increasingly important, calling for improved regulation and certification services. The Government of Tanzania (see ASDS-2), through the ASLMs, will work closely with private sector and the development partners to continue its efforts 99 The East African Common Market, launched in 2010, opens up new regional trade opportunities, but also exposes Tanzania’s domestic market to increased competition. 92 Agricultural Sector Development Programme II (ASDP-II) to undertake: (i) improvement and maintenance of rural roads network, including by promoting private investment; (ii) roll out the operations of WRS100 for appropriate commodities by empowering farmers, increasing storage capacity at all levels; (iii) support increasing capacity of cold storage and cold chains, especially to service dairy, meat and fish products; (iv) close collaboration with the Rural Energy Agency (REA) to promote rural electrification; and (v) developing market facilities at village, ward and district levels, but also wholesale markets, border101 market places, to encourage trade with neighbouring countries. 220. The aim is to develop and promote access to profitable domestic and export markets for priority commodity value chains. This will be achieved by a gradual building process building on promoting sustainable collective warehouse marketing schemes (see COWABAMA in s/c 3.2) at village/farmer group level and supporting: (i) establishing and maintaining an effective market information system; (ii) enhancing the use of warehouse receipt systems and consolidating efficient marketing information system; and (iii) piloting and establishing a commodity exchange programme, including strategic warehouses when required, starting with major cash crop commodities (cashew nut, coffee, sesame, etc.). 221. Market access for beef dairy and fish. The main marketing infrastructure for livestock include, among others stock routes, night camps, holding grounds and dipping facilities. Both primary and secondary markets are equipped with auction rings, purchase pens and weigh bridges. About 300 primary livestock markets are administered by the LGAs and supply animals for local markets and for onward transfer to secondary and terminal markets located at Themi (Arusha), Weruweru (Moshi), Korogwe (Tanga), Lumecha (Songea) and Pugu (Dar-es-Salaam), which then supply to urban and export markets served by 10 border markets. 222. Market Information Services (MIS). To complement the agribusiness support services and competitive grants to promote agribusiness, timely access to adapted market information is crucial to improve decision-making. Market information comes in the form of prices, product quantities and qualities available for sale and purchase in specific locations. Currently, the availability of information is rather scattered, ineffectively collected and poorly disseminated. Developing a more robust system (facilitated by public investments and implement within PPP) using modern ICT (Internet, mobile phone, text messaging) for providing relevant market information will be an important support for improved linkages producers, buyers and other CVC stakeholders towards enhanced value chain efficiency. 223. Warehouse Receipt Systems (WRS) and market linkages. Successful market improvement efforts through WRS by various development and financial partners, in East and Southern Africa, allowing for common marketing (including contract selling to large buyers, auctioning, spot selling), improved farm-gate prices for inputs and outputs, reduced losses and reliable farmers cash flow. The implementation of ASDP II prioritizes in a first phase the promotion of village level storage facilities (see s/c 3.2 COWABAMA), while more formal WRS require storage facilities of at least 5,000 tons102 to cover the higher management and transaction costs involved in professional collateral management, infrastructure maintenance, insurances, licenses, etc., as per application of the ‘Warehouse Receipt Act’. Therefore, the WRS will be piloted in about 10 critical locations, and build on further grouping of village warehouses (average capacity of 300 tons each) to develop a critical mass, which would allow for working on a third aggregation level103, from mid-programme on. Gradually strengthened market linkages will lead to contractual agreements between cooperative unions, public and private service 100 Since 2007, the WRS has played an important role in improved marketing for some agricultural products (cotton, coffee, cashew, maize, rice, sunflower and sesame). A Commodity Exchange System is in preparation under the coordination of the Capital Market Security Authority (CMSA). 101 Complete the construction of international produce market places at Kibaigwa (maize, sorghum and beef), Segera (horticultural products—Tanga region) and Makambako (multi-purpose—Njombe region). Border markets are expected to support farmers in terms of price stabilization, as all stakeholders use same facilities. 102 In the range of 1,000–5,000 tons depending on the value of the commodity. 103 See proposed pilot Commodity Exchange activities in Table 39. 93 Agricultural Sector for Industrial Development providers, rural banks, input suppliers, and commercial farmers or aggregators who have linkages with agro-industries, commodity exchanges, wholesalers or exporters. To facilitate the development of these linkages, ASDP II will support exchanges, value chain consultation and specialized technical and economic assistance. 224. Pilot commodity exchange platform establishment. The initial step in this process is in generating a body of knowledge on the market, its opportunities, requirements, sources of information and the key players, particularly private companies. This will form the core of the market training courses. The Ministry of Industry Trade and Investment will maintain a Market Intelligence knowledge database including: (i) regional sources of information; (ii) updated listing of companies, agribusinesses, logistic companies, sources of equipment; and (iii) regulations, standards, trade data. Building on a critical number of functioning warehouses, commodity exchange markets will be established, starting with cash crops such as cashew and coffee, but maize and other exported food crops. Under the guidance of specialized Ministry of Industry Trade and Investment services, technical capacities will be developed, including by learning from experiences in neighbouring countries (Ethiopia, Malawi, South Africa, Uganda, etc.). ASDP II will support exchanges, value chain consultation and specialized technical assistance for developing priority commodity exchange platforms involving PPP. Table 32: Summary of action areas and activities in market enhancement at national/regional level Action areas Activities Market research (cost, competitively for priority crop/livestock CVC - Investment opportunities for local and export markets - Evaluate marketing costs in segments along value chain Market intelligence - Facilitate market access for Tanzanian products - Guaranty product quality and offer reliability Develop Warehouse Receipts System (WRS) - Facilitate warehouse rehabilitation and management (at least 5,000 tons); - Mapping of warehouses under WRS (needs and opportunities for WRS); - Create awareness and build user capacity by linking stakeholders (FO, banks, marketers, etc. at different levels; Facilitate the implementation of the pilot WRS - Follow up the implementation of the expanded WRS Pilot Commodity Exchange Market in Tanzania - Awareness and framework of collaboration between public and private sector - Create awareness and build capacity to key stakeholders - Enhance capacity of ‘Warehouse Licensing Board’ to implement the WRS to facilitate effective commodity exchange - Harmonize legal framework and redefine role of Marketing boards - Consider crop law reforms which resulted into Crop Laws (Miscellaneous Amendments) No., 20/2009 - Develop institutional framework for commodity exchange - Business plan for funding the commodity exchange market - Develop guidelines & enhance capacities of involved stakeholders - Facilitate the implementation of Commodity exchange market - Establish and operationalize an information exchange interface for commodity exchange market/platform Improved MIS - Enhance market information needs for priority CVCs - Strengthen existing MIS to fill the gaps (use ICT to get it efficient) - Promote effective market information diffusion and user access 94 Agricultural Sector Development Programme II (ASDP-II) Action areas Activities Promote agricultural products in domestic and regional/international markets - Participate at shows and exhibitions and expos - Encourage use and consumption of domestic products - Improve and maintain standards, quality and distribution of products - Promote market infrastructures including feeder roads, strategic functional warehouses, markets, abattoirs, milk collection centres and market centres - Strengthen regulatory functions of crop boards (see also s/c 2.2) - Traceability and safety of agricultural products Promote fisheries products - Participate in shows and exhibitions - Traceability and safety of fisheries and aquaculture products - Awareness and collaboration between public and private sector Source: Proposals from the Ministry of Industry Trade and Investment 225. Livestock and fisheries quality control and product safety assurance. Priority action areas and proposed investments include among others, at national/regional level (Table 34). Table 33:Priority activities livestock and fisheries quality control and safety assurance Action area Priority actions Livestock & products marketing - Empower livestock producers with basic knowledge & skills on product quality - Strengthen capacities of livestock regulatory boards (dairy, meat, hides and skins, and animal feeds boards) - Reinforcement and (regional) harmonization of laws/regulations on quality livestock products - Strengthen linkage between livestock producers and potential markets - Strengthen regulatory boards (TSh 500 million/year) Livestock marketing infrastructure - Investment in key livestock marketing infrastructures - Promote and enforce sector standards for safety and quality Livestock marketing information - Strengthen (integrated & sustainable) livestock marketing information system (data collection, processing/analysis and dissemination using modern ICT)— involving public and private sector stakeholders Facilitate marketing of quality livestock inputs and outputs to promote production & safeguard animal/public health - Create public awareness of locally produced veterinary vaccines (Newcastle disease, Anthrax, ‘Blackquarter’ vaccine, etc.) - Strengthen laboratory capacity for control (equipment, capacity strengthening) - Encouraging private laboratories for quality control - Support surveillance a quality livestock inputs and food of animal origin Fisheries products marketing - Improve the standard and quality of fish and fisheries products (regulations and their enforcement) Fisheries marketing infrastructure - Investment in key fisheries processing and marketing infrastructure & facilities - Promote and enforce sector standards for safety and quality Fisheries & aquaculture marketing information - Improve and strengthen (integrated & sustainable) fisheries, farmed fish and other aqua-product marketing information system (data collection, processing and dissemination using modern ICT)—with public/private sector stakeholders - Conduct seaweed and farmed fish value chain analysis Traceability, eco-labelling and animal welfare - LITS practiced increasing performance and quality - Promote animal welfare adherence Source: Proposals from the Ministry of Agriculture 226. At local level, main investments to promote priority CVC marketing are prioritized in participative district agricultural development plans and included in DADG. Key investments include, among others: (i) improvement of road/transport infrastructure; (ii) rehabilitation/construction of local— collection/grouping—markets, including cold storage, slaughterhouse, fish disembarkation facilities; and (iii) specialized agribusiness technical support and capacity building for quality product marketing development. Prioritization and follow-up of investments will be done in close collaboration with the DCP involving the participation of priority CVC stakeholders. 95 Agricultural Sector for Industrial Development Sub-component 3.2: Agribusiness Development: Value addition and agro-processing 227. Value addition and agro-processing are key elements of increased agricultural commercialization, revenue and employment generation in rural areas, but also use of by-products in agro-processing for animal feed. Although they have strong forward linkages by providing additional market opportunities responding to high demands for processed products, the level of agro-processing infrastructure and facilities remains rather low which in turn also contributes to high post-harvest losses. 228. Agribusiness and Private Sector Development. A diverse, competitive and robust private sector to spearhead the development of the agriculture sector is envisaged by way of increased flows of private investment and services in the sector. This will be achieved with public support towards improved conditions and systems in which the private sector operates, by promoting among others: (i) agro-processing to reduce post-harvest losses and for value addition; (ii) improvement on packaging, handling, cold chain and transporting agricultural products; (iii) environmentally responsible technology and hygiene measures, based on the relevant laws and regulations; and (iv) favourable business and investment environment for agro-processing. 229. The priority strategies and interventions recommended in ASDS- II include: (i) promoting private sector investment, especially through ongoing efforts of SAGCOT initiative.(ii) continued improvement of business environment with regard to trade policy, procedures/regulations on export and import, investment, taxation, and other related issues in collaboration with relevant organizations, such as TIC; (iii) establish and strengthen dialogue forum among the key public and private stakeholders, to discuss on the improvement of business environment; and (iv) expand agricultural finance services through TIB-Agricultural window and AGTIF, the Tanzania Agricultural Development Bank, but also commercial banks for medium- and long-term investment in the sector. 230. The aim of this sub-component is to enable smallholder farmers, their organizations and other value chain participants/stakeholders to invest in profitable value addition and agro-processing in priority value chains, to increase ‘enterprise’ profitability and ‘local’ incomes. Targeted agribusiness investments at local and inter-district/regional levels, require specialized support in both technical and management aspects of enterprise development, including: (i) agribusiness advisory and support services and capacity building; (ii) a financing mechanism for business development through competitive matching grants; and (iii) identifying and developing promising commercialization opportunities. Entrepreneurial skills enhancement for value addition is key to build entrepreneurship and self-employment in rural communities, especially among women and young farmers. Agro- processing must be undertaken in a socially and environmentally responsible manner, including decent working conditions and safety, gender equity and youth employment, preventing child labour. Table 34: Priority activities for CVC value addition and agro-processing. Action/investment areas Priority activities Key drivers and enablers for agribusiness development Institutional strengthening: - District/regional CVC agribusiness/ MSIPs - Agribusiness private support services (PSP)—regional level Post-harvest management systems - COWABAMA-BRN (smallholder collective commodity marketing schemes); village-level storage facilities and professional management Agribusiness (processing, value addition) investments along priority CVC - Agribusiness services including support to consolidate enterprise business plans (see agribusiness PSPs) - Improve required infrastructure in terms of access to facilities (electricity, water, etc.) - Support to local investments using competitive matching grants 231. Key drivers and enablers for agribusiness development. Institutional weakness and lack of agribusiness support capacities, especially at local level, have been identified and tackled through several pilot projects104. Actions will take place at district level while coordination and support 104 Rural Business Support Services for improving value chains had varying fortunes, largely depending on the 96 Agricultural Sector Development Programme II (ASDP-II) services centred on priority commodity value chains will be common at regional level, for efficiency and economies of scale reasons. Therefore, regional facilitation teams (to be established/contracted within a PPP framework) should provide results-based agribusiness support services to DCP and technical teams active in the agriculture sector. 232. District CVC Platforms (DCP)105 for improved coordination between stakeholders at LGA level. These stakeholder platforms bring major actors in priority local CVCs together to develop and drive the implementation of a strategy for sustainable productivity growth, value addition and efficient market access. These platforms develop mutually beneficial partnerships among actors along the value chain for increased production, quality, value addition and trade of the selected commodities. DCP will be critical in terms of establishing formal or even ad hoc mechanisms to encourage value chain connectivity between private and public stakeholders and drive innovations/changes towards higher levels of commercialization in targeted priority value chain (or group of complementary CVCs). These platforms will become the vehicles for strategic alliances and business partnerships that will create better understanding of the requirements of producers and processors, transporters and storage businesses and traders and the market. DCP will be involved in priority public support actions planning and evaluation. 233. Regional facilitation/support teams. Agribusiness support services remain a weak link at local/LGA level, as farmers and their organizations and other value chain actors need specialized support services and advice to achieve high returns from their respective activities of production, value addition and marketing in priority CVCs. Agribusiness PSPs are the essential instrument for the programme to engage all actors in the development of priority commodity value chains at local level. Where those support services do not exist or are weak, ASDP II will help promote their establishment and growth through training and capacity building initiatives. These services will be contracted by targeted regions (or district clusters) to deliver the capacity building and agribusiness support services farmer organizations and other CVC stakeholders in commercialized farming and agribusiness development for selected priority CVC. 234. Post-harvest management systems target to achieve effective and efficient food supply by addressing key issues between production and consumption of agricultural commodities. High post-harvest losses remain a central concern, as different research studies demonstrate that farmers lose up to 40% of produced cereals, although losses vary to a large extent by crop type and geographical zone. The main issues are to protect harvested products against physical (water, heat and dust) and biological (fungus, insects and rodents) degradation during transportation, storage and processing operations. From the institutional point of view, harmonization and alignment of functions between the Ministry of Agriculture and the Ministry of Industry Trade and Investment is needed, especially for activities related to storage infrastructures and management, reduction of post-harvest losses and value addition and agro-processing of agricultural products. performance of the PSPs (see IFAD programme evaluation, 2014). Only a few contracts have been facilitated between farmer groups and rural enterprises and between these enterprises and the market. The capacity building support for rural entrepreneurs and enterprises has been limited and of short duration. 105 There is already a “value chain stakeholder meeting” established along with the DADP which will be upgraded to DCP. The purpose of encouraging platforms is to get farmers/producers and agribusinesses to network and connect better, to understand requirements and issues and to see if there can be solutions developed to solve problems or perhaps improve the way business is conducted. The ‘District Commodity Platforms’ (e.g., Tanga), have contributed to bringing the value chain stakeholders together, identifying issues and problems and providing a framework for networking. Potentially, these platforms could contribute to improving value chain cohesion, but to do so they would need to be expanded beyond district boundaries (to cover i.e., clusters). 97 Agricultural Sector for Industrial Development Table 35: Priority actions towards reduction of post-harvest losses Reduction of post-harvest losses Action area Actions/proposed activities Large post-harvest losses due to poor support systems/ technologies and limited handling capacity i. Develop and disseminate guidelines for harvest and post-harvest handling of selected crops (special attention to aflatoxins on cereals) ii. Develop guidelines for appropriate post-harvest handling practices for meat, milk, hides & skins iii. Promote and disseminate technologies that promote better handling and improved storage and preservation of food and food products including livestock products (meat, milk, hides & skins) iv. Professional storage management (see COWABAMA) v. Improved market support infrastructure see s/c 3.3) Highly perishable products for crops (horticulture) and animal products (milk, meat, fish etc.) i. Cold chain infrastructures and marketing ii. Partnerships with private sector involved in transformation & marketing iii. Awareness of standards and compliance control Institutional alignment and harmonization Storage infrastructures and management, reduction of post-harvest losses and value addition between the Ministry of Agriculture, the Ministry of Industry Trade and Investment and LGAs Note: For meat, milk, hides and skins (50 million x 5Y = 250 million) and for livestock products (meat, milk, hides and skins; 100 million x 5Y = 500 million). 235. Village-level storage facilities for smallholder collective marketing schemes (COWABAMA). The objective of these investments, is to develop and promote smallholders’ access to more profitable markets for priority commodities through sustainable collective warehouse based marketing schemes. This will establish a network of commodity warehouses to be linked to large-scale buyers inside and outside the country. The initial investment will focus on 275 collective maize warehouses in SAGCOT, and 78 irrigation scheme warehouses for rice. Selected high potential districts encompass warehouses averaging 300 MT in size, benefiting about 165,000 households. Over time, the programme is expected to expand to other high maize potential districts and bring in additional commodities with promising commercialization opportunities, such as sunflower, diary and horticulture. 236. COWABAMA will involve the rehabilitation of existing village warehouses and the construction of additional ones. Overall, the support under this component will include: (i) improving (village) storage facilities and marketing infrastructures (feeder road connectivity); (ii) promoting management capacities for commodity bulking/assembly; (iii) creating favourable business environment for market activities of priority commodities by strengthening regulatory framework for quality and standards; (iv) supporting access to production enhancing interventions to ensure sufficient output supply for efficient utilization of storage capacity of warehouses; and (v) linking gradually with WRS, commodity exchange programme106 and value addition services. From Year 4 on, the support will expand to further districts (clusters), but also priority commodities (crop and livestock) of other AEZs. Building on achieved results, the programme will gradually expand to other AEZs and/or priority commodities such as sunflower and dairy/meat, trying to achieve broader based growth and rural poverty reduction in clusters of districts of each of the main AEZ, serving as focal point for gradual geographical expansion. 237. Agribusiness (processing, value addition) investments along priority CVC. Besides advisory and capacity building, ASDP II will promote targeted investment development at national and local level, including demand-driven agribusiness support services, improved infrastructures and facilities for increased commercialization, and support to private/associative agribusiness development investments. 238. At national level, public services will facilitate and provide technical support for the implementation of actions at LGA (and LGA cluster) level. Proposed priority action areas for agro-processing are outlined in Table 37. 106 See details in s/c 3.3 Marketing. 98 Agricultural Sector Development Programme II (ASDP-II) Table 36: Proposed strategic action areas for agro-processing and value addition107 Action areas Strategic activities5 Entrepreneur mapping - Mapping of entrepreneurs, their organizations and activities within targeted priority CVCs Training of entrepreneurs - Organize training of entrepreneurs in agro-processing business planning, especially value-addition for targeted priority CVC products within each AEZ. Packaging and branding - Needs assessment/awareness creation of entrepreneurs and producer associations - Promote product branding and quality - Link processors with packaging producers (study tours, grouping demand, etc.) Modernization of agro- processing industries for selected CVCs - Identify needs in priority CVC - Sensitization, diagnostic study, building capacity and provide technical agribusiness advisory services (PSP) - Facilitate modernization with technologies upgrading and financing plan (national level support & regulation) Promote mechanization of postharvest processes - Evaluation of use and quality of processing mechanization (dissemination) - Promote post-harvest farm tools - Prototypes for post-harvest handling in priority CVCs Improve product quality & traceability - Build capacity for product traceability - Laboratory accreditation for quality control NEDF - Promote National Entrepreneur Development Fund Establishment of SMEs Agricultural Exports Processing Zones - Identify areas for establishing export processing zones - Mobilize private sector to develop export processing zones - Follow up the implementation of EPZ development Establish & develop sunflower industrial cluster - Identify sites for developing sunflower clusters - Mobilize stakeholders to develop sunflower industrial clusters - Follow up the implementation of sunflower cluster development Source: Ministry of Industry Trade and Investment, 2015 239. For livestock and fisheries identified priority action in processing and value addition are shown in Table 37: Table 37: Proposed strategic action areas for agro-processing and value addition (livestock/fisheries) Action areas Strategic activities Milk processing - Promote milk collection and processing facilities and infrastructures in 20 dairy clusters (about TSh million each) - Compliance with standards (training quality and safe dairy products) Meat processing - Promote production of quality products by investment in meat processing, slaughter facilities, training in processing - Construct 5 abattoirs in key livestock marketing clusters (about TSh 3 billion each) Hides and skins processing - Promote production and value of quality hides and skins through improved collection and processing Other by-products - Promote production, processing and handling of other animal by-products Processing of Sardinella spp. from fresh water - Promote standard processing and value addition - Training on safety and quality products - Improve collection of ‘dagaa’ and proper fishing methods - (i.e., Lake Victoria, Tanganyika, Nyasa and Rukwa) Fishing and value addition for pelagic fish - Promote support value addition, processing, handling of by-products - Improve proper fishing methods; reduce post-harvest losses - Fish handling and improved quality of by-products 107 Detailed activities to be identified by commodities with involved stakeholders, during investment phase. 99 Agricultural Sector for Industrial Development Action areas Strategic activities Other fisheries products - Value addition to farmed seaweed Regulations - Animal product and by-product quality - Licensing and registration of fishing vessels 240. At local level, facilitation of agribusiness investments in priority CVC will be promoted by: (i) improving required infrastructure in terms of access to facilities (electricity, water, etc.); (ii) enhancing agribusiness services including support to consolidate enterprise business plans (see agribusiness PSPs); and (iii) supporting local investments using competitive matching grants. This infrastructure will facilitate further entrepreneur investments in agro-processing and value addition. 241. Public Agribusiness Investments108. As for ASDP-1, investment funding used the DADG window to support priority public good investments for the development of targeted infrastructures (roads, markets, etc.) and facilities (access to water and electricity, etc.) in support of CVC development at local level. Project selection and implementation will follow consolidated ASDP-1 implementation procedures109 while contributions of beneficiaries and LGA will be gradually increased with increasing returns from the selected priority CVCs. Sub-component 3.4: Expanded Access to Rural Finance 242. Background. Inadequate financial service for small-scale commercial farmers is a major constraint to agricultural growth and limits the level of investment and the pace of agricultural commercialization. Commercial banks are reluctant to lend to the sector and have limited outreach in rural areas. There are numerous microfinance institutions (MFIs) targeting farmers, but they have limited capacity to reach the large number of rural households due to lack of skilled personnel, branch networks and finance. Small- and medium-scale enterprises engaged in value addition are also constrained by access to financial resources. 243. Currently, government initiatives promote agricultural rural finance mechanism including among others: (i) the National Financial Inclusion Framework (Steering committee is chaired by the Bank of Tanzania, drawing members from the Ministry of Agriculture, CMSA, the Ministry of Finance and Planning, TIRA, TCRA, FSDT, TAMFI and mobile phone operators); (ii) SACCOS, channelling savings and finances borrowed from the commercial banks to the smallholder farmers who are members of the SACCOS, but also other similar arrangements through the SACCAS, VICOBA and the like; (iii) WRS for smallholder farmers to access financing of their agricultural activities (mostly in traditional cash crops); (iv) the National Cooperative Bank that envisages at financing cooperative societies (unions); (v) the agricultural lending window in the Tanzania Investment Bank; (vi) the Kilimanjaro Cooperative Bank and the Kagera Farmers’ Cooperative Bank; (vii) lending to youth to engage in income generating activities including agriculture (Ministry of Information Culture Artists and Sports); (viii) LGAs to set aside 10% of their own source revenues to be channeled to lending to youth and women in the respective LGAs area of jurisdiction; (ix) the Agricultural Inputs Trust Fund (AGITF) under the Ministry of Agriculture; (x) the National Social Security Fund (NSSF) issues individual and cooperative loans (Wakulima scheme); (xii) NAIVS and potential follow-up programmes; and (xiii) the Marketing Infrastructure, Value Addition, and Rural Finance (MIVARF) Programme110 issuing grants to Irrigators Organizations or Paddy Agricultural Marketing Cooperatives to acquire medium size rice milling machines. The government plans to establish and operationalize an Agricultural Development Bank to provide a specialized funding window for investment in the sector, while catalytic funds (see e.g., SACGOT) and credit guarantee schemes are some of several initiatives towards integrated rural commercialization. 244. The number of commercial banks is increasing (about 50 in 2014) and some of them extend services to agricultural sector and agro-processing. Agricultural financing (crops and livestock) from 108 To be included in local level investments within DADG. 109 To be updated in ASDP II Programme Implementation Manual (PIM). 110 For rural finance MIRVAF targets improved and sustainable financial and operational performance of: (i) informal grassroots associations, SACCOS and other MFIs; and (ii) rural small- and medium-scale entrepreneurs. 100 Agricultural Sector Development Programme II (ASDP-II) commercial banks in terms outstanding sector lending is gradually increasing at an equivalent of 10% of the total lending (about TSh 1 trillion). Private Agriculture Sector Support (PASS) Trust established in 2000 and funded by DANIDA through CRDB Bank Ltd. has been providing support for business planning and guarantees. Formal and informal MFIs, financing to SACCOS, also support the agricultural economy of the smallholders in rural areas. The initiative of the National Financial Inclusion Framework by MOF intends an implementation plan targeting 50% of the adult population to have access to formal financial services by 2016. 245. Overall, numerous public, project-related and finance institutions initiatives exist at national and local levels to promote access to rural financing of the public sector, but no clear strategy (and coherent and comprehensive action plan) promoting rural financial systems to up-scale stakeholders investment in the agricultural sector, within sustainable PPPs. Improving financial services to the sector is a key policy issue in order to facilitate private investment. 246. For ASDS-2, the required public interventions promoted by ASDS-2 include: (i) promote services of existing community banks and start-up of new ones at local level; (ii) design agricultural credit packages, appropriate to smallholder farmers; (iii) provide support to establish stronger and well capitalized grassroots MFIs such as SACCOS and Village Community Banks (VICOBA) as first- line financial services for small-scale commercial farmers; (iv) update the National Microfinance Policy in collaboration with other ministries to take into account recent developments in technology such as the use of mobile banking, pension schemes and insurance schemes, which are useful to rural households entering into commercial farming; (v) strengthen overseeing/regulatory functions of the Cooperative Department at local level as part of promotion of MFIs; (vi) accelerate efforts to expand agricultural finance services through TIB-Agricultural window, AGITF, the establishment of the Tanzania Agricultural Development Bank, for medium- and long-term investment in agricultural production and processing; and (vii) promote lending for agricultural investments from commercial banks. 247. Within ASDP II, priority action areas for expanded access of smallholder producers and transformers/exporters (SME/SMI) to rural financing, include among others to: i. Develop a comprehensive rural financing strategy and action programme for promoting business investments and profitability in agricultural commodity value chains development with all involved stakeholders. ii. Strengthen cooperatives and other economic associations and related SACCOS/SACCA (social control as guarantee) for providing sustainable (and stakeholder-owned) (micro) financial services at local level. iii. Enhance availability of and access to short- to medium-term agricultural financing sector within a PPP approach, involving among others an Agricultural Development Bank, private banks investing in the rural sector, etc. iv. Facilitate farmers access to agricultural investments, among others by: (a) promoting WRS to overcome the guarantee issue; (b) strengthening contract farming (contractual agreement between producer organizations, agrobusiness, exporters and banks/financiers); (c) establishing a legal framework policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers). 248. Comprehensive rural financing strategy and action programme. There is little coherence among number of public and private initiatives for promoting an agricultural rural finance mechanism, giving rise to the need to develop, consolidate and implement a multi-stakeholder strategy to promote agricultural investment. A strategy for improving rural financial linkages would include, among others, to: (i) encourage and strengthen the sector’s own control through network organizations for rural SACCOS; (ii) facilitate linkage of FOs (associations) with financial cooperatives, micro- credit institutions and/or commercial banks; (iii) enhance the bargaining power of producer, trader and processor organizations, associations and cooperatives through improved market information, 101 Agricultural Sector for Industrial Development aggregation of produce and the use of inventory financing opportunities; and (iv) strengthen the public sector support in its regulatory function of the financial sector. 249. Grassroots financial services111, aiming at building the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs to expand their rural outreach, and supporting selected community banks as alternative rural financial service providers. The sub-component also aims at supporting the Tanzania Cooperative Development to enhance the implementation of the Cooperative Reform and Modernization Programme. Action areas include improved financial and operational performance of informal grassroots associations, SACCOS and other MFIs (informal associations transformed to MFIs on a sustainable basis), but also strengthened operational linkages between MFI and formal financial/credit institutions. 250. Warehouse Receipt System (WRS)112 using stocks as guarantee for facilitating access to affordable credit in participating financial institutions (PFIs). The financial institutions would access eligibility of warehouse receipt operators to credit on the basis of checklists and benchmarks including: (i) governance and structure of membership; (ii) existence of by-laws, manuals and minutes of meetings; (iii) financial and income statements and balance sheets; (iv) assets; (v) credit history; and (vi) contractual agreements with buyers of produce. ASDP II will support PFIs in collateral management of warehousing, value chain analysis, agricultural risk management, and market research and intelligence, to minimize the risks of their ventures. To improve access of rural financial institutions to data on opportunities for value chain financing, detailed financial analyses will be undertaken for gross margins, profitability, repayment capacity, etc., of all actors in the value chains being supported, and develop training manuals and guidelines for applying the methodology to identify financing opportunities and analyse proposals. 251. The Food and Agriculture Organization of the United Nations (FAO) in collaboration with Rabobank/ NMB Foundation pilot project aims at building financial management capacity among producers and their organizations, creating sustainable linkages with local financial service providers and agricultural value chain agents and improving productivity practices. It will build linkages between FOs and financial service providers which will also provide room for development of a long-term market strategy. Smallholder paddy producer organizations will be formalized into agriculture marketing cooperative societies (AMCOS) to achieve scale and bargaining power, strengthening the commercial relationships between FOs and other rice value chain actors and building the capacity of smallholder farmers to manage loans and participate in the national WRS which will enable them to become creditworthy. 252. Availability of short- and medium-term financing for input provision and operating warehouses which would result in value addition, improvements of grain quality and bulking at the farmer association/cooperative enterprise scale is a key success factor. The improvement of value chain actors and farmers’ access to rural financial services113 by facilitating links to sound financial institutions, including commercial banks, but also partnerships with other initiatives in the rural finance sector114. During the first year, several participating financial institutions and financing models would be identified, so as to ensure availability of financial services in target clusters. 253. However, due to high interest rates and lack of credit guarantees, it remains difficult for farmer groups and private firms to borrow medium- to long-term loan for facilities/equipment investments. This hinders the agricultural investment significantly and appropriate mechanisms need to be developed. Even for seasonal credit, interest rates absorb large parts of supplementary net return on investment (inputs) due to low efficiency in productivity growth. Within this context, targeted subsidies (e.g, interest rates), specialized trust funds and other similar mechanisms need to be discussed between all 111 See also MIRVAF and lessons learned (IFAD). 112 See also ‘Professional warehouse management (COWABAMA initiative) in s/c 3.2. 113 See also National Entrepreneurship Development Fund—NEDF facilities. 114 The programme will collaborate with other initiatives engaged in classic and innovative financing to build an information base that could help streamline complementary financing through financial institutions at different levels. See also related supports by Rabobank initiative, etc. 102 Agricultural Sector Development Programme II (ASDP-II) stakeholders to facilitate sustainable access of sector stakeholders to financial services for agricultural investments, without competing with the financial system. 254. Key action areas and activities to improve sustainable rural/agricultural investments have been summarized, as shown in Table 38. Table 38: Action areas and activities to improve rural/agricultural investments (draft) Action areas Activities Comprehensive rural financing strategy and action programme - Draft and consolidate comprehensive agricultural investment financing strategy with all involved stakeholders - Develop and action programme for enhanced offer and access to rural financing, its financing and implementation modalities Strengthen organizational and technical capacity of existing and new small-scale producer, trade and processing farmer organization and cooperatives - Training and strengthen organizational and technical capacities of farmer organizations to enhance the bargaining power of producer, trader and processor - Facilitate linkage of farmer organizations/associations with financial cooperatives MFI, and/or commercial banks - Strengthen sector’s own control (audit) through network organizations for rural SACCOS - Support the up-scaling of WRS by expanding into new locations and adding new crops - Sensitize on the linkage between SACCOS and AMCOS; train FOs/AMCOS management and board members on good governance and supervision - Support outreach expansion of selected community banks as alternative rural financial service providers - Build the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs - Improve financial and operational performance of informal grassroots associations, SACCOS and other MFIs - Support the Tanzania Cooperative Development Commission to enhance the implementation of the cooperative reform and modernization programme Enhance availability of and access to short- to medium- term agricultural financing - Rural finance support aiming at increasing the access of rural producers and entrepreneurs to financial services by commercial banks, testing new approaches, methods and services in rural areas for the benefit of the target group, improving the legal and policy framework for rural microfinance, and integrating knowledge management into the programme - Improved access to financial services on a sustainable basis for rural small- and medium- scale entrepreneurs (increased number of farmers and SMEs obtaining loans from financial institutions) Facilitate farmers access to agricultural investments - Improved farmer organizations and cooperative input and output marketing by information systems, aggregation/grouping of produce and the use of inventory financing opportunities - Promoting WRS to overcome the guarantee issue - Consolidating and scaling up contract farming where applicable (contractual agreement between producer organizations, agrobusiness, exporters and financial institutions) - Design schemes that will enable smallholder access to loans financing along agriculture value chains (start with lessons learned from ongoing schemes) - Establishing a legal framework and policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers) 255. Implementation. The Tanzania Cooperative Development Commission under the Ministry of Agriculture should take the lead role in developing strategies and priority actions in close collaboration with all sector stakeholders, including departments of Policy and Planning in all ASLMs; departments responsible for Crop, Livestock and Fisheries Development in the ministry; Marketing Department (Ministry of Industry Trade and Investment), the Ministry of Finance and Planning; FOs; MFIs and private banks and development partners. 256. Summary of component 3: Preliminary costing of implementation of proposed action plan was proposed (Table 39). 103 Agricultural Sector for Industrial Development Table 39: Development budget/investment estimation for Component 3 (TSh million) COMPONENT 3: COMMERCIALIZATION AND VALUE ADDITION-BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,346 456,728 568,733 635,561 684,371 2,443,739 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847 9,466 156,458 171,750 368,188 713,709 3.1.2.2 Improving local and improved chicken market access 743 2,068 2,248 369 282 5,710 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,834 738 733 643 630 4,578 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,239 4,073 4,376 1,442 13,999 25,129 3.2.1.1 Strengthening and development of agro processing industries for value addition for all priority commodities 10,333 14,448 15,432 16,806 18,522 75,541 3.2.1.2 Improving milk value chain 8,886 8,536 8,014 4,213 4,571 34,220 3.2.1.3 Strengthening hides and skin value chain 13,915 10,119 19,594 5,972 5,307 54,907 3.2.1.4 Strengthening value chain for horticultural commodities 4,995 1,622 4,127 1,274 1,387 13,405 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,328 21,012 22,695 24,805 27,302 122,142 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,758 6,752 7,267 7,868 8,432 36,077 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,633 12,739 3,507 505 226 26,610 3.2.1.8 Improving Postharvest Management Along Food Supply Chain for sustainable food security and nutrition 1,088 2,710 12,534 2,324 1,080 19,736 TOTAL COMPONENT 3 190,945 551,009 825,718 873,532 1,134,297 3,575,501 104 Agricultural Sector Development Programme II (ASDP-II) F. Component 4: Strengthening Sector Enablers and Coordination 257. Strategic objectives, outcomes and related indicators for the programme enablers and coordination are defined in Table 40. Table 40: ASDP II Component 4: related specific ASDS-2 objectives and outcomes Objective Outcomes Outcome Indicators Comp. 4: Strengthening Sector Enablers, Coordination, and M&E Strengthened institutions, enablers, coordination, and M&E framework - Policy environment and regulatory framework - Business environment (Change in ranking in WB’s doing business and Enabling the Business in Agriculture-EBA) - Knowledge management - Efficient ICT use to support agricultural sector - Integrated and efficient sector monitoring and evaluation (M&E) systems - Empowerment of farmer organizations, women, and youth - Access to agricultural finance s/c. 4.1 Improved business environment through enhanced policy, regulatory, and institutional frameworks - Reviewed and harmonized agricultural sector related policies, laws, regulations and institutional frameworks - Extent of policy and regulation compliance (e.g. compliance rates) - Policy environment and regulatory frameworks - Business environment s/c 4.2 Empowered farmers and farmers’ organization and cooperatives - % of FOs and cooperative providing BDS - % of FOs and cooperatives mobilized own resources - Farmer and other value chain actors’ organizations are operated and managed by the members (Good Governance) s/c 4.3: Sector coordination improved - Quality and timely submitted quarterly reports at all levels - Coordination unit for planning and monitoring established and operational - Guidelines compliance rate at all levels s/c 4.4: M&E and agricultural statistics strengthened - AASS implemented - RS and LGAs to provide quality data through different M&E systems timely - Joint M&E systems established and operational s/c 4.5: Institutional capacity development, knowledge management, and ICT - Enhanced knowledge management and ICT systems s/c 4.6: Access to agricultural finance expanded - Provision for affordable interest rate by commercial bank in Tanzania to the farmer - Loan repayment rates (%) - % increase in branches of formal financial institutions in rural areas. Policies/institutional actions: focus on priority policies as outlined in the New Alliance on Food Security & Nutrition: (i) trade/marketing; (ii) enabling policy for private sector involvement; (iii) land tenure; (iv) access to financing; and (v) seed policies. knowledge management & ICT: Harmonized standards, mechanisms for collection, analysis and dissemination of agricultural identified and developed agricultural knowledge assets in the sector through use of ICT tools shall be strengthened to increase efficiency in decision making but also be a source and stimulant for future sector growth through innovation. Comp. 4: STRENGTHENING SECTOR ENABLERS & COORDINATION (national, regional, local) s/c 4.1: Policy and regulatory framework s/c 4.2: Stakeholder empowerment and organization s/c 4.3: ASDP II_sector coordination (planning & implementation at national, regional and LGA s/c 4.4: Monitoring & evaluation (incl. Agricultural statistics) s/c 4.5: Institutional capacity development, knowledge management, and ICT s/c 4.6: Access to rural financing 105 Agricultural Sector for Industrial Development 258. Component 4 is sub-divided into six sub-components: The success of ASDP II depends to a considerable extent on the capacities and effectiveness of the various institutions and participants in the sector to carry out the planned activities. Most of the institutions, e.g., policy makers, academia, services in research, extension, training and information technology that support the agriculture sector will need capacity to rationalize their functions to implement ASDP II. The institutional factors that hamper development of the agriculture sector are outlined in Box 6. Box 6: Key issues in policy and institutional reform and support (updated from TAFSIP) - Inadequate government development funding for research, extension, research extension linkage, planning and regulatory functions - Limited policy coordination and implementation leading to duplication of efforts and gaps in programme design, implementation and evaluation - Weak interface and synergy between academic institutions and government - Relative disconnect between farmers and cooperatives management structures - Inadequate financial, human and technical capacity to generate, manage and disseminate useful agricultural information, weak communication systems at all levels and the high cost of procuring improved Inputs; - Weak financial and asset management, records, reporting and M&E - Limited training facilities including farmer training centres and limited financing of agricultural training services - Shortcomings in the legal and regulatory framework including enforcement of laws and regulations - Inadequate good statistical base and analytical capacity for policy analysis and decision making Sub-component 4.1: Policy and regulatory framework 259. Effective policy formulation and institutional reforms necessary for policy implementation are the foundations for realizing the Strategic Objectives of ASDS-2. It is also one of the most important functions of the government. Whilst Tanzania’s policy framework for agricultural and rural development is comprehensive and stable, in several areas reviews, adjustments and refinements may be beneficial. 260. The aim is to harmonize, rationalize and align policies and regulatory framework which oversees the agricultural sector (across ASLMs) and related industry (crops, livestock/fish and natural resources) and to strengthen institutional capacity for effective development and management of the sector. Table 41: Key policy areas and related actions for agricultural sector growth (ASLM) Policy outcomes Priority actions (national level) Agricultural Input Policy Enable the private sector to develop, commercialize, and use improved inputs to increase smallholder productivity and incomes - Analysis and advocacy to promote policy options that encourage production and distribution of improved seed varieties - Work with EAC to implement harmonized standards and free trade in seeds Agricultural Trade Policy Reduce tariff and non-tariff trade barriers to increase trade and spur inclusive economic growth (import/export management) - Analysis of food security system capacity and needs, potential for regional trade in food crops, and impacts of export bans on poverty and growth - Advocacy efforts with Parliament and civil society to build support for alternatives - Promote fair & competitive agricultural markets - Align Tanzania’s trade policies with regional (EAC/SADC) policies Enabling Policy for Private Sector Investment 106 Agricultural Sector Development Programme II (ASDP-II) Policy outcomes Priority actions (national level) Agricultural Input Policy Reduce barriers to competitiveness, thereby increasing private agricultural investment and accelerating agricultural growth - Analysis and advocacy to offer alternatives to specific regulatory impediments – streamline the number of regulatory fees and processes - Implement a more simplified tax system on food crops, including the possible elimination of taxes - Promote a more transparent and robust policy environment conducive to establishing a successful commodity exchange - Policy incentives to promote value addition to mitigate rising food import & promote jobs creation - Analysis of agricultural investment incentives to promote domestic and foreign investment Land Tenure Policy Promote land tenure policy that strengthen land use rights with minimal disruption to pastoralists and the landless poor, to stimulate smallholder investment in both land-based and non-agricultural income- generating assets - Establish/implement clear policies and procedures for investors to access land relatively quickly and without conflict - Promote improved legislation and the formalization of land rights through titling - Promote Certificate of Customary Right of Occupancy (CCRO) - Re-organize and expand mandate of the Rufiji Basin Development Authority to act as a land bank for the region (for SAGCOT region only) - Mitigate conflicts in resource use through implementation and enforcement of land use plan Access to Capital and Financing Promote policy that enables development of innovative financial products that catalyse private sector investment, asset accumulation, and input access in key CVC. - Establish/implement modern collateral registry system with associated legal framework to protect lender’s claims to collateral in the case of default - Implement training and outreach to facilitate wide-spread use of Secured Transactions System by financial institutions - Design schemes that will enable smallholder access to loans financing along agriculture value chains Agriculture Sector Policy (including crop, livestock/fisheries and marketing) Support transparent, inclusive, evidence-based policy formulation that leads to increased and more effective public and private investment in agriculture - Strengthen and sustain regional integration (CAADP activities) - Invest in agricultural statistics capacity building - Enhance policy stability, predictability and transparency—streamline procedures and processes in policy reforms - Streamline policies to promote policy coherence - Scale-up and promote policies to promote inclusive growth particularly among youth, women and poorest Food security - Policy level recommendations: Within a coordinated cross sector approach within the TAFSIP framework - Strengthen existing programmes to boost agricultural productivity by focusing on the supply side of the agricultural value chain(s)—availability; - Focus food security specific policies and interventions on household livelihoods and income generation (improve access) - Reinforce disaster preparedness (incl. specialized studies) and response measures with focus on household coping and resilience - Scale up safety net schemes (school feeding, cash for work Nutrition - Legislation (and regulatory framework) on breastmilk substitutes, maternity leave, salt iodation and food fortification are in place - Policy dissemination and advocacy are needed to ensure operationalization and broaden audiences Source: Compiled from ‘Policy discussions G8’. Dar-es-Salaam (February 2015) and ASDS 2 (draft). *The actions for food and nutrition security can be seen clearly under component 2 107 Agricultural Sector for Industrial Development Sub-component 4.2: Farmer Empowerment and Organization 261. Profile of agricultural organization and service provision115. Traditionally, cooperative societies had been the only way farmers were organized to access various services. However, cooperatives emerged mostly for cash crops such as coffee, cotton and tobacco. Due to various economic and political factors, most cooperatives collapsed. To revitalize the registered cooperative societies and pre-cooperative groups the government devised Cooperative Reform and Modernization Programme (CRMP) and enacted the Cooperative Societies Act No. 6 of 2013 to regulate the cooperatives stakeholders in their economic activities of buying and selling services and commodities such as food and traditional and non-traditional cash crops. 262. Currently, a variety of organizations are emerging. Some are classic FO type groups whilst others are more professionalized and include associations such as the Tanzania Horticulture Association (TAHA) and the Agricultural Council of Tanzania (ACT). These NGOs provide services to their members, but many still depend on external technical and financial support. Such organizations need to be supported to mobilize internal resources and to develop their business skills, making them more effective private sector, business-oriented organizations, equipped to help smallholders move from subsistence to commercial practices. These organizations provide an opportunity for linking smallholder farmers with input suppliers, traders, financial and other service providers and for creating strong value chains around specific commodities. Existing farmer organizations have been categorized into several groups (Table 42). Table 42: Farmer organizations, by category FO typea Examples Strengths and weaknesses Commodity- based producer associations/ organizations/ groups Rice growers associations (total number of rice growers associations is not known) FBO and groups (COWABAMA) Most producer associations are poorly linked to input suppliers, financial and business services. In addition, many of them have inadequate management capacity which limits the benefits. However, these associations can be strengthened to negotiate for better policies and prices, possibility of linking better with buyers and other service providers for value chain actors. Apex organizations Rural and Urban Development Initiatives (RUDI) in Mbarali (7,000 members) and Kilombero (3,600 members); Sugar Cane Outgrowers Associations in Kilombero, Mtibwa and Kagera. Tanzania Milk Producers Association (TAMPRODA) Tanzania has no maize producers association unlike those for the other commodities, although many farmers in maize growing areas belong to farmer groups and networks of farmer groups. Some of these are members of MVIWATA, which does not focus on any particular commodity. Maize producers should be organized to facilitate linkages with other value chain actors (maize buyers) to facilitate bulking and warehousing. Livestock herder/fisheries organization. Cooperative societies (affiliated to cooperative unions) Lindi & Mtwara: simsim is marketed through Ilulu Coop Union in Lindi and Masasi-Mtwara Coop Union (MMCU) Still important in some areas, for the traditional cash crops as well as for new crops. For sim sim, it will be important to work through the primary cooperative societies and unions by strengthening their business and marketing operations. Water User Associations & Irrigator organizations Water User Associations in Mbarali Districts (from only a few members up to 3000 members (Madibira) They vary in size and capacity. However, they are a potential entry point for promoting diversification into horticultural crops during the off season after paddy has been harvested. 115 Drawn from TCIA/FAO contribution to ASDP I BF (Annexes-June 2013) 108 Agricultural Sector Development Programme II (ASDP-II) FO typea Examples Strengths and weaknesses Membership- based organizations open only to full-time farmers MVIWATA (Mtandao wa vikundi vya wakulima Tanzania) HODECT: Horticultural Development Council of Tanzania6 It is a network of farmer groups with over 5,000 active farmer groups in 25 regions. It currently represents about 70,000 farming households, though the exact figure is uncertain. Farmer groups are usually between 5 and 15 households and networks represent the groups within a village usually totalling 4–20 groups. Large-scale (commodity based) farmer organizations Tanganyika Farmers Association (TFA), Tanzania Chamber of Commerce Industry and Agriculture (TCCIA) or ACT The limited number of large-scale farmers means that they tend to interact informally. Large-scale farms, ranches and plantations have an important role in modernization, increased commercial production and as the focal point for out grower schemes and contract farming. They will have greater impact on overall Tanzania agriculture as well as position themselves for greater profit, if they were better organized. a Compiled from different sources.116 263. ASDP-1 contributed to the implementation of public policies by setting the stage for improving decentralized public systems for agricultural support, involving the grassroots farmers (and their organizations) to participate in shaping local agricultural development plans. There is evidence of positive effects on improving farmers’ participation (Opportunities and Obstacles to Development), capacity and knowledge building towards increased productivity and potential farmer returns. ASDP-1 also promoted the establishment of Farmer Fora (FF) at ward and district levels, but gained little understanding about their role. Overall, there is a lack of strategic framework for stakeholder empowerment initiatives and their organization along value chains at local and national level117. Suitable service providers with required skills and experience on farmer organization and empowerment are required to guide and enhance capacities of technical skills at local level. 264. Group formation and adoption of collective approach are indispensable steps for realizing agricultural growth and commercialization. The capacity of farmer organizations, as a key private sector player, requires significant improvements to be addressed (see ASDS-2) by the following public interventions: (i) building organizational and technical capacity of farmers organizations through public and private support; (ii) enhancing entrepreneurship and competitiveness of farmer organizations through capacity building in organizational management and leadership; (iii) promoting wide-ranged participation among women and young farmers into farmer organizations; and (iv) providing a clear framework for establishment and operation of farmer organizations. 265. The aim of this sub-component will be to support activities for empowering farmers and strengthening value chain stakeholder organizations, so that they can access services, knowledge, information, investment opportunities and markets more efficiently and effectively. This sub-component will enhance capacities of smallholder farmers and support their organizations to engage in transformative ‘commercial’ agriculture. Farmer groups/organizations/cooperatives will be strengthened and supported towards federating in higher-level organizations (along CVC), for increased leverage and benefit from internal and external support services to improve the profitability of their enterprises. FOs will serve as a focal point for learning, quality control and standardization, but also increased negotiation power and ownership. 266. Success of a smallholder, market-oriented development strategy rests on establishing a foundation of strong farmer organizations, capable of making and acting on decisions that affect their livelihoods. Key elements attracting farmers to associate within competitive agricultural value chains to access opportunities outside the reach of individuals, require at least: (i) a viable business model, consistent with agro-ecological conditions, farmers’ resource endowments and market opportunities; (ii) effective farmer organization governance and accountability; and (iii) access to appropriate technologies, information, production and processing, inputs and credit. 116 http://hodect.org/-(HODECT: Horticultural Development Council of Tanzania) 117 See ASDP-1 evaluation of performance and achievements (June 2011). 109 Agricultural Sector for Industrial Development 267. To achieve this, ASDP II will strategically empower farmers and support structuring of farmer and other CVC-based organizations, capitalizing on local experience in smallholder enterprise development, enhancing good governance structures (i.e., economic associations, cooperatives, companies, etc.) and saving and credit (e.g., SACCOs) facilities. The farmer- and CVC-based approach will serve as a focal point in the extension strategy (s/c 2.2) in responding to farmers’ needs for intensification technologies, access to markets and marketing information availed through strengthened support services and ICT-based systems (s/c 4.2), but also access to quality inputs and marketing strategies. Main action areas are summarized, as shown in Table 43. Table 43: Action areas for farmer empowerment and organization strengthening Action/investment areas Priority activities Assessment of FO capacities - Initial assessment of the capacities of FO in Tanzania. (including case study for success stories) - Develop a strategic framework for stakeholder empowerment initiatives and their organization along value chains Farmer empowerment - Group management training (e.g., support for registration, by-law formulation, leadership training, annual report writing, meeting organization) - Financial management training (e.g., financial record-keeping, auditing) - Business plan training (incl. access to financing services; see also s/c 3.4) - Support for acquiring Certificate of Customary Rights of Occupancy (CCROs) or land title deeds that can serve as collateral - Commodity specific FFS (technical networks) - Trainings for collective FO storage, sales & purchases (see s/c 3.2) Farmer organization strengthening Structuration and federation of farmer groups and unions Strengthening organizational and technical capacities of existing and new small- scale producer, trade and processing FOs/cooperatives - Enhance/support higher level farmer organizations (unions, federations and cooperatives) and their governance - Facilitate emergence and strengthen stakeholder economic entities and/or cooperatives - Strengthen dialogue with stakeholders (ministries, private sector, development partners, etc.) - Support the up-scaling of the Warehouse Receipt System (WRS) - Facilitate processing and marketing by farmer organizations and cooperatives with technical and management skills - Develop effective operational systems for input and output supply chains - Sensitize on the linkage between SACCOS and agriculture marketing cooperative societies (AMCOS) Strengthening commodity- wise stakeholder organizations (TAHA, etc.) - Regional multi-stakeholder innovation platforms for prioritized CVCs - Rice value chain stakeholder - CVC stakeholder organizations at district level - Commodity specific platforms - Strengthen dialogue with stakeholders (ministries) 268. Initial assessment of the capacities of FO in Tanzania. To ensure maximum and enduring impact of support to farmer organizational development, a detailed assessment of the operational capacities and needs of business-oriented farmer organizations will be implemented during the first year. This assessment will focus on: (i) the internal resources and capabilities of the organizations—staffing, management, quality of services, current and potential reach of field operations; (ii) needs for updating of internal trainings and field support materials; (iii) quality of tools used in value chain assessment, competiveness analysis and initial business development support; (iv) capabilities and needs, of linking with financial institutions; and (v) needs of the organizations in terms of headquarter support and field logistics. Based on the findings, a support framework for farmer empowerment and organization strengthening will be finalized. Furthermore, mapping of other CVC stakeholders/ entrepreneurs and their respective training needs towards MSIPs development in priority CVC intensification and diversification in targeted clusters will be performed. 110 Agricultural Sector Development Programme II (ASDP-II) 269. Farmer empowerment. Strengthening of capacities of producer marketing groups and higher-level FOs is critical to the long-term success of smallholder farmers’ participation in agricultural value chains. Key features of this sub-component are the focus on building the capacity of farmers (value chain actors) and their organizations (groups, unions, federation) to make informed choices and implement decisions that affect the businesses and livelihoods of members, but also enhance their capacity to negotiate with other actors in the priority CVCs. The FO-based approach will also serve as a focal point in the new extension strategy in responding to farmers’ needs for new technologies, market and other information availed through the ICT-based systems plan (s/c 4.5), but also the quality seed and inputs (s/c 2.2), agribusiness and value addition (s/c 3.2) and marketing strategy (s/c 3.1). 270. Three elements are required: (i) a viable business model, consistent with agro-ecological conditions, farmers’ resource endowments and market opportunities; (ii) effective group (organization) governance and accountability; and (iii) access to necessary technologies, information, production and processing inputs, and credit. To achieve this, and to complement public production/productivity oriented extension systems at district level, ASDP II will provide support to strategically strengthen partnerships with specialized agribusiness PSPs118 and other commodity-based organizations, capitalizing on local experience in smallholder enterprise development, establishing good governance structures (e.g., cooperatives, companies) and saving and credit (SACCOs) facilities, as required. 271. Strengthening of capacities of producer marketing groups and higher-level farmer organizations is critical to the long-term success and stakeholder ownership of sustainable growth in the agriculture sector. Specifically, assistance will be given to updating internal training and support materials, and the tools used in value chain market assessment, competiveness analysis and initial business development support. The sub-component will: (i) strengthen FOs to address demand-driven linkages with agribusiness partners for critical services such as input supply, output market and processing facilities; (ii) strengthen the roles and capacity of existing producer/market organization partnerships; and (iii) develop innovative ICT-based approaches for enhancing access to technical, market information and financial advisory services. This support will be gender sensitive and youth inclusive, giving particular attention to disadvantaged producer groups to access agrobusiness opportunities. Activities will complement and/or scale up complementary efforts and related initiatives in the sector. 272. Higher-level farmer organization enhancement (unions, apex organizations, cooperatives, etc.). Farmer institutional development is also critical to ensure that farmer organizations play the envisaged role in transforming subsistence into commercial farming, but also strengthening stakeholder ownership and organization governance. Farmer groups/cooperatives engaged in targeted commodity (crop, livestock, fish) production at village level will be supported to organize into a higher-level production and marketing association, acting as an economic entity (union, cooperative or company). In addition to technical advice, enhanced capacity for negotiations with other value chain actors will require training and awareness creation in different areas, including attention to quality of farm inputs, post-harvest handling, processing, transporting, utilization of market information, pricing, and marketing skills. This will involve strengthening existing FOs in business development skills, as well as facilitating the creation of farmer owned associations at village, ward and district levels, where these do not exist. Furthermore, linking smallholder famer organizations to larger-scale producers will be promoted where feasible to increase their access to inputs, agricultural advice and markets. Formal and transparent arrangements for contract farming relations is an important way forward to improve relationships and which will help attain fair prices and, in the long run, reduce supply uncertainties. 118 See also other experiences by MUVI-IFAD and NGO activities in value chain organization and promotion. 111 Agricultural Sector for Industrial Development Table 44: Proposed ASDP II interventions into cooperative activities and operations Intervention Activities 1.To enhance regulatory, institutional and supervisory framework of Tanzania Cooperatives Development Commission (TCDC) and Cooperative Societies 1.1. To conduct training of 95 cooperative inspectors annually in cooperative societies inspection, supervision, accounting & record keeping 1.2. To facilitate Registrar’s Office, execute regulatory functions at national, regional and district levels 1.3. To facilitate conduct cooperative societies special general meetings 1.4. To carry out inspection of the affairs and operations of the Tanzania Cooperative Federation; 5,500 AMCOS; 8,000 SACCOs; 45 Cooperative Unions and 4 Cooperative Joint Ventures 2. To strengthen cooperative movement (all levels) to take on responsibility of promotion and self-regulatory functions 2.1. Facilitate provision of cooperative education to Board members of cooperatives, management and ordinary members in 2,000 cooperative societies annually. 2.2. To develop and air mass media programmes on the cooperative values, undertakings and SACCOs strengthening campaigns 3.To build capacity and strengthen cooperative organizations on business management and leadership skills 3.1. To conduct training of trainers (TOT) to district and sectoral ministries promotion and sensitization teams 3.2. To offer advanced training to TCDC staff on entrepreneurship skills, negotiation skills, project planning and management plus business plans writing, skills mix and the like 4.Strengthen & operationalize Cooperative Data Management Systems (CODAS) 4.1. Strengthen regulatory reporting information for cooperative 4.2. To establish IT system centres as strategic tools for farmers produce value addition Source: Adapted from proposals developed by the Cooperative Agency. Sub-component 4.3: ASDP II Sector Coordination (Planning and Implementation at National, Regional and LGA) 273. The greatest ‘policy’ challenge in ASDP II is effective coordination of agricultural development interventions, which includes all public good support and investments, implemented on- or off- budget. This requires a consolidated coordination framework under the strengthened leadership of ASLMs for all the sector stakeholders at both national and local levels. This also implies the need for enhanced cooperation of all agriculture sector programmes/projects in complying with SWAp under ASDP II, whether they are on-budget or off-budget. ASDP II sector coordination will build on strengthened CKM at national, regional and local levels (see also s/c 4.5). 274. ASDP II will broaden the scope of coordination to include basket and non-basket funded activities. The sector strategy aims to have a more comprehensive approach to planning, budgeting, implementation and monitoring of activities in the agriculture sector, including activities of the private sector by: (i) establishing a coordination framework for all agricultural activities from planning, resource allocation, implementation and monitoring of activities; (ii) enhancing coordination of activities at national and local government level by enhancing engagement of Regional Administration as a link between the ministry and LGAs; and (iii) restructure some of the institutions for improved coordination, efficiency and effectiveness of service delivery in agriculture. 275. The strengthened ASDP II coordination framework will include: (i) widely disseminating clear common goals of ASDP II to all the sector stakeholders; (ii) consolidated efforts by all the sector stakeholders for achieving the goals of ASDP II based on better guidance by the ASLMs; (iii) sound M&E system with strong agricultural statistical data; (iv) sector performance review in which all sector stakeholders, including private sector, participate; (v) open dialogue system on critical policy issues and regulatory frameworks; (vi) well-established networking and information system on all the sector interventions; and (vii) strong capacity of the ASLMs for analytical and managerial aspects concerning the sector coordination. 112 Agricultural Sector Development Programme II (ASDP-II) 276. Institutional structures and coordination functions119. The implementation of ASDP II sector coordination will be mainstreamed and strengthened into the existing government systems and structures—while building on lessons learned from ASDP-1—to effectively support the implementation of the proposed operation. This will allow continuation of efforts to strengthen government systems at national and local levels for enhanced results and sustainability. However, ASDP II will also take account of off-budget programme components and the reporting system will be expanded to encompass such components that fall within the wider objectives of the programme. 277. Coordination at central level. The hierarchy of coordination organs and functions under ASDP II at central level includes: (i) National Agricultural Sector Stakeholders Meeting (NASSM); (ii) Agricultural Sector Steering Committee (ASC); (iii) Agricultural Sector Consultative Group(ASCG) (iv) Technical Committee of Directors (TCD); (v) Thematic Working Groups (TWGs); and (vi) National Coordination Unit (NCU). Table 45 shows the summary of ASDP II sector coordination components. Table 45: ASDP II National Level coordination organs, mechanisms, and membership (summary) Forum Chair Members National Agricultural Sector Stakeholder Meeting(NASSM) Prime Minister Ministers of Lead Components and Related Ministries (ASLMs and Others), Development Partners, and Private Sector, Non-State Actors(NSAs), RS, LGAs, District Executive Directors (DEDs); DAICOs, DLFOs; research officials; training officials; academia representatives; commodity boards;; financial institutions; farmer based organizations/associations and cooperatives, commodity associations, and successive agriculture associations and SACCOS; representatives of other related stakeholder organizations/ players in the agricultural sector Agricultural Sector Steering Committee(ASC) Minister Ministry of Agriculture Permanent Secretaries of Lead Components and Related Ministries (ASLMs and Others), Development Partners representatives and Private Sector Representatives/NSAs Agricultural Sector Consultative Group (ASCG) Permanent Secretary Ministry of Agriculture, Permanent Secretaries of Lead Components and Related Ministries (ASLMs and others), All Development Partners supporting agriculture and Private Sector, NGOs/CBOs, Farmer Based Organizations and Cooperatives,, Research and Training Institutions. Technical Committee of Directors Permanent Secretary Ministry of Agriculture, Directors of Lead Components ASDP II National Coordination Unit (NCU) National ASDP II Coordinator Members of National Coordination Unit (NCU) 119 See further details for institutional and implementation arrangements in Section VI. 113 Agricultural Sector for Industrial Development Forum Chair Members National Thematic Working Groups (TWGs) Component Leader Chairs of Components 278. PO-RALG. LGAs are overseen and directed by the PO-RALG: The Department of Sector Coordination is responsible for management and support to LGAs by collaboration with regional secretariats (RSs). Vertical coordination from PO-RALG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. 279. Coorination at the PO-RALG will start with the Annual Regional and Local Government Consultative Meeting to be chaired by the Minister. This will be followed by: (i) the Agricultural Sector Consultative Meeting chaired by the Permanent Secretary PO-RALG; (ii) the Technical Committee of Component Leaders (TCCL-PO_RALG) chaired by the Director of Sector Coordination, and (iii) the regional Consultative Committee (RCC) chaired by the Regional Commissioner. Table 46 presents the detailed levels from village to the PO-RALG. Table 46: ASDP II PO-RALG Level coordination organs, mechanisms, and membership (summary) Institution Chair Members Annual Regional and Local Government Consultative Meeting Minister PO- RALG Permanent Secretaries ASLMS, Directors (DPPs) of Agricultural Lead Ministries, Development Partners Supporting RS & LGAs, Private Sector, NGOs/CBOs; FBOs, DED, Ward, District, Regional Experts etc. Agricultural Sector Consultative Meeting Permanent Secretary-PO- RALG Directors (DPPs) of Agricultural Lead Ministries Technical Committee of Component Leaders(TCCL-PO- RALG) Director of Sector Coordination- PO- RALG Component Leaders of PO-RALG Plus other Directors at PO-RALG Regional Consultative Committee (RCC) Region Commissioner Administrative and Assistant Administrative Secretaries, Head of Units District Consultative Committee District Commissioner District Executive, Head of Departments Full Council Council Chairperson Members of Council, Management Team (CMT), DED Ward Development Council Councillor Members of WDC Village Council Meeting Village Chairperson Members of Council Meeting Village Assembly Village Chairperson All villagers above 18 years with sound mind 280. Regional Administrative Secretariats (RAS). The role of RAS is to assist the LGAs in preparation of the DADPs, backstopping and supportive supervision on the implementation of the DADPs, and assisting in the submission of quarterly and annual reports in compliance with the DADP Guidelines. The Assistant Administrative Secretary for Economics and Production section within RS is directly responsible for supporting development activities within the region and is assisted in the task by the ASDP Regional Coordinator and fellow officers dedicated to specific sub-sectors. These officers will 114 Agricultural Sector Development Programme II (ASDP-II) provide technical and managerial assistance to LGAs for ASDP II implementation. The RSs will closely work together with the relevant TWGs and the ASDP II National Coordination Unit as the need for consultation and assistance arises. 281. Coordination at local level. ASDP II will strengthen structures for local activities established under ASDP-1. DADP will continue to be the key instrument for agricultural development at local level. The District Executive Director (DED) will hold overall responsibility for activities and funds used at local level. The Council Management Team (CMT), which is chaired by the DED and attended by all the department heads including DAICO and DLFO, is informed on the agricultural development issues and status under DADP. 282. DADPs are derived from the grassroots by villagers through the Opportunities and Obstacles to Development (O&OD) process and summarized in Village Agricultural Development Plans (VADPs): this planning process is led by a Village Planning Committee, Village Agricultural Extension Officer (VAEO), Village Executive Officer (VEO) and supported by the District Facilitation Team according to the DADP guidelines. Proposals from individual villages are submitted to wards and consolidated by the by the Ward Development Committee, guided by the Ward Agricultural Extension Officer (WAEO) under supervision of the Ward Executive Officer (WEO), for submission to the District Executive Director (DED). Based on the submitted proposals, DADPs will be consolidated by DAICOs and DFLOs. The entire process will be guided by the DADP Guidelines and detailed instructions by ASLMs through PO-RALG, including alignment on ASDP II priorities. 283. As a key coordination mechanism at local level, District Component Platform (DCP) between sector stakeholders at LGA level/districts cluster will be in place (s/c 3.2). DCP brings major actors in priority local CVCs together to develop and drive the implementation of DADP activities that includes various aspects such as productivity improvement, value addition and market access. The stakeholders at local level include private sectors (traders, processors, transporters, financial institutions, etc.), NGOs, development partners as well as various public institutions that can provide various types of technical supports. It is therefore crucially important for a LGA to formulate a comprehensive DADP that includes on-budget and off-budget development activities within the LGA, with joint implementation management and follow-up. 284. Off-budget Projects. While the government anticipates that development, partners will continue to contribute to development funding through budgetary support, ring-fenced funds, earmarked funds, discrete projects and off-budget activities, it requires that all projects, funded by whatever means, should be aligned with the ASDP II. development partners should engage in the government framework to ensure alignment with national objectives and to share experience and lessons learned. The activities of off-budget projects and programmes should be subject to agreement between the project and the government, as enshrined in the memoranda of understanding that would stipulate implementation modalities, including activity planning and follow-up. Box 7: Inclusion of off-budget projects Inclusion of off-budget projects into ASDP II framework There is a view among government officials that NGOs perceive other development initiatives as a “threat” and are reluctant to talk to district authorities, resulting in lack of adequate effective communication in the planning, implementation and monitoring of development projects. This perception must be corrected by proactive involvement by NGOs with the development aspirations of ASDP II and other national programmes. NGO contribution to development will be enhanced by improved coordination with ASDP, and mutual lessons may be learned and capacity of ASLMs may gain advancement through greater cooperation. To this end, NGO projects should be obliged at registration and be committed by memoranda of understanding to participate in collaborative meetings and to contribute performance data to the M&E exercises. Development partner development activities in agriculture will also be included in M&E functions on behalf of ASDP II, as will those that may be undertaken by the development partner projects for the benefit of evaluation to meet the needs of the partner. 115 Agricultural Sector for Industrial Development Sub-component 4.4: Monitoring and Evaluation (M&E) and Agricultural Statistics 285. Data availability and reliability were major shortcomings experienced by the sector during ASDP- 1 implementation. According to the Agricultural Statistics Strategic Plan (AASP; 2014), National Sample Census of Agriculture (NSCA), Annual Agricultural Sample Survey (AASS), and Agriculture Routine Data Collection Systems (ARDS) need to be further consolidated and integrated towards an evidence-based decision-making and management tool. ASDS-2 intermediate result IR4.5 (M&E and Agricultural Statistics Strengthened) focuses priority areas on: (i) strengthening and rationalizing M&E to enhance evidence-based strategy development and design of programmes and projects; and (ii) improving the quality, cost effectiveness and timeliness of agricultural statistics. 286. The objective of this sub-component is to ensure that there is an improvement in the timeliness, quality and relevance of available statistics and routine data systems in the agriculture sector, to provide the data needed to monitor the performance of the ASDP II Support Programme, starting with the indicators contained in its results framework, as well as sector-wide statistical data. Under this sub-component, support will be divided in two thematic areas: (i) dedicated ASDP II M&E support; and (ii) support to agricultural statistics and sector M&E efforts120. 287. ASDP II Support Programme Monitoring and Evaluation. One of the lessons learned from ASDP-1 was that the delays in implementing key surveys led to a deficit in the information available to properly monitor and evaluate the results of the first phase. It was therefore easy to assert that ASDP-1 had not achieved its results, that there had been no “impact” and that resources were spread too thinly. Many key performance indicators under ASDP-1 relied on the National Sample Census of Agriculture being completed on time and its results disseminated rapidly121. There was confusion during the ASDP-1 monitoring between the project-specific and sector-wide outcomes data collection: because of clear connection to budgets, the former received in general more attention than the latter, resulting in relatively weak development of ASDP sector-wide monitoring. 288. ASDP II provides and implements a results-focused framework for the agriculture sector. As multiple actors implement their respective interventions and projects in ASDP II, M&E needs strong coordination, data collection, processing, analytical and reporting capabilities. The M&E capacities of the M&E sections in the ASLMs, M&E TWG and NCU will need to be strengthened under ASDP II for stronger M&E coordination and a small M&E team be tasked with day-to-day operation and data processing tasks at each ASLMs. Reports on the state of data collection and overall state/performance of the sector should be submitted to ASDP II decision-making levels, and also widely disseminated through websites or any other means for the accountability of the programme122. 289. A baseline survey will be conducted in 2016/17 complimented by secondary data available from different sources. The National Sample Census Survey of Agriculture (NSCA) to be implemented in 2016/2017 (thus the reference year is 2015/2016) and 10-year periodicity, in combination with AASS and TWG will also provide the consolidated baseline and final levels of outcome and impact indicators for the sector programme. At mid-term, an intermediate survey could be envisaged (as required) to allow for a revision of the results framework to adjust actual performance of the M&E of ASDP II. 290. To allow tracking of key performance indicators identified in the results framework (see Annex II), intermediate outcome indicators will be evaluated yearly to provide useful feedback regarding the implementation of the ASDP II and progress toward measurable strategic objectives. Given that AASS will focus mainly on crop, livestock and fisheries productivity and production statistics, the best options are to integrate programme specific indicators into AASS with data representative of districts; 120 Details for the proposed M&E system and RF are provided in Annex II and V. 121 The last National Sample Census of Agriculture and Livestock NSCA were held in 2002/2003, and then in 2007/2008. The results of the latter were made available in July 2012, while the 2012/2013 Sample Census has been postponed to 2014/2015. It is the main source of information for outcome indicators in the ASDP-1 M&E Framework. 122 Sourced from discussions with M&E TWG. 116 Agricultural Sector Development Programme II (ASDP-II) Not all intermediate outcome indicators will need to be assessed annually. The sampling frame should be the same as for the baseline and survey results should be representative at district level: to produce quality data in a shorter time frame (ideally 3–4 months), the use of portable electronic devices will be promoted. 291. The overall M&E framework for ASDP II including impact/outcome evaluations, output monitoring and quarterly physical and financial reporting of LGAs will be carried out through PO-RALG administrative123 channels. Figure 21: ASDP M&E system for sector and programme performance (adapted for ASDP II) ASDP 2 AGRICULTURAL STEERING COMMITEE ASDP M&E Baseline and Performance reports (ASDP indicators) ASDP 2 NATIONAL COORDINATION TEAM (NACOTE) SECTOR PERFORMANCE (national, regional, district, ward, village level) DADP Physical and finicial quarterly progress reports Outcomes: Production, yields,number farmers using improved technologies Outputs: Area under irrigation, number of VEO trained etc. District reporting Individual project activities and performance (at group level) Input Input Output Outcome Out put Out Come Other projects/interventions in agric (NGO,CSO, etc) Private investment in the agric sector Specific technical reports/studies (livertock/crop disease,price monitoring,food forecasting, etc. Agric. Routine Data System (ARDS) Integrated Data Collection Format (LGMD2) VAEO/WAEO format AGRICULTURAL SAMPLE SURVEYS National Sample Census for Agriculture (NSCA) - 10 years + Annual Agricultural Sample Survey (AASS - 1 year) + Other: National Panel Survey... Consolidation in Regional quaterly fin & phys. progress reports DADP (incl DIDF) Quaterly physical and financial progress report M&E TWG Main proposed actions. 292. Strengthening agricultural statistics, sector M&E and analytical capacity. Based on the Global Strategy to Improve Agricultural and Rural Statistics, promoted in Tanzania by the United States Department of Agriculture (USDA), FAO and AfDB, and based on the ASSP being developed by the Agriculture Statistics Task Force, this sub-component will include the following priority activities: (i) co-financing of the National Sample Census of Agriculture and Livestock (NSCA), foreseen to take place in 2016/2017 (reference year 2015/2016); (ii) financing of AASS during the period of ASDP II implementation (2015–2025); (iii) strengthening the Agricultural Routine Data System (ARDS) 123 The capacity of PO-RALG teams will be strengthened as required (see institutional capacity building in s/c 4.2). Incentives 117 Agricultural Sector for Industrial Development and support to the M&E departments and TWG; and (iv) improve analytical capacity of ASLMs for planning and policy analysis, sector performance reviews, annual budgetary cycle, and PERs. These investments are deemed necessary under ASDP II, given that it will be the largest public-sector financed programme in the sector, and that no other ongoing programme is providing financing in this area. 293. National Sample Census for Agriculture (NSCA). Given that ASDP II will be one of the few large-scale projects/programmes providing financing in agriculture through the public sector over the coming years, and given that financing for agricultural statistics is an ongoing discussion under the aegis of the Global Strategy to Improve Agricultural and Rural Statistics, several partners, including the government, have expressed willingness to participate in the financing of the NSCA. This is seen as the key survey and its regular implementation would go a long way in providing a common national system to all projects operating in the sector in Tanzania. It is envisaged that the NSCA will be held every 10 years, and will provide up to regional-level124 representative statistics on a wide range of variables, based on a sample size of 50,000 households. ASDP II will therefore co-finance the cost of the next NSCA, which is due to take place in 2016/2017. 294. Annual Agriculture Sample Survey (AASS). The Agricultural Statistics Strategic Plan developed by the Agriculture Statistics Task Force foresees that AASS will provide annual, regional level, production and productivity statistics for main crops and livestock species. The annual cost of AASS has not yet been fully defined and nor has the methodology125 been consolidated or the questionnaire been prepared. However, an annual survey is intended to capture necessary outcome indicators for monitoring the sector. Production and productivity are among those indicators, but there are some most necessary indicators like adoption of improved technologies and access to services. Under ASDP-1 these indicators were obtained from the National Sample Census of Agriculture which was conducted at 5-year intervals. Under ASSP, the NSCA has shifted from a 5-year interval to the global interval of 10 years. 295. Within Agricultural Statistics Task Force (NBS, ASLMs and technical assistance from USDA and FAO), there are ongoing methodological discussions regarding the sampling approach (area-based, list-based or a combination), the content of the questionnaire and the data representative level (regional and district), as there are concerns about the current statistical methodology being advocated by USDA. It is important that the integration of intermediate outcomes into the AASS questionnaire would fully streamline the ASDP II M&E into agricultural sector processes. 296. Agricultural Routine Data System (ARDS)126 is a key management information system that has been improved under ASDP-1. A lot of resources have also been invested to build a national database (known previously as LGMD2, but now called ARDS\LGMD2/ Web Portal) with information disaggregated at district level to clarify data flow, to develop data format, procedures for data collection at village and ward level and data dissemination from district to national level. The Japanese International Cooperation Agency (JICA) has provided long-term technical assistance and capacity building support to national ARDS roll-out127. This system provides data on the output performance of the agricultural sector, and relies on front-line extension staff to provide monthly, quarterly and annual information, which is compiled at district level and entered into a web-based database, and made available to ASLM through regional secretariats and PO-RALG. ARDS now has a window for users in the web portal, “ards.go.tz” where potential users can access information by obtaining the User ID from the M&E TWG. There is a need to readjust the scope of the ARDS with other data 124 FAO is planning to conduct “small area estimation method” study for Tanzania to utilize the results of NSCA and AASS and estimate district level data. For this calculation/model, ARDS data are expected to be used. 125 Methodologies for baseline and the final survey should be harmonized with NSCA as well as AASS so that data obtained can be comparable. For that matter, it is better to postpone an envisaged break from the normal list sampling frame to the area sampling frame and continue with the methodology which NBS and ASLMs are familiar with. The pilot conducted for the area frame method has so far indicated a lot of challenges that need to be tackled before rolling out. 126 ARDS needs to be aligned with AASS. 127 Agricultural Routine Data System (ARDS): National Roll-Out Plan, ASDP M&E TWG, 2010. 118 Agricultural Sector Development Programme II (ASDP-II) sources, such as AASS and NSCA, but also the quarterly physical and financial reporting to avoid duplications and improve data quality, reliability and timeliness. It is also necessary to strengthen coordination among ARDS, within the early warning and other administrative data collection systems to improve efficiency of overall data collection. 297. The M&E Thematic Working Group compiles the ASDP Annual Performance Report which provides an update on all key performance indicators, at impact, outcome and output level128 and participates in the JSR and PER (see s/c 4.4), which undertake an annual assessment of progress made under ASDP II. 298. Joint Sector Review. The JSR will comprise a key component of the M&E system and will be undertaken following finalization of the NBS Annual Agricultural Sample Survey (AASS) and immediately preceding the NASSM. It will be conducted by government, development partners and consultants to rigorously review the programme over several weeks on the basis of analysed national statistics as a professional annual evaluation exercise. It will include field visits in selected regions where the ASDP II is being implemented by way of sampling. JSR will be a forum for coordination and dialogue to enable shared vision and the opportunity to initiate corrective action in the management of projects. The conclusions of the JSR will be presented to the NASSM for discussion and corrective action. The report from this meeting will be summarized by the ASDP Coordination and Management Unit and forwarded to the National Steering Committee for action. 299. Finally, the Public Expenditure Review provides a further opportunity to monitor the progress and performance of the ASDP II in the wider context of the national economy. Results of the JSR/PER will be discussed at the ASCG, and then adopted by ASC for futher action implementation. Sub-component 4.5: Institutional Capacity Development, Knowledge Management (KM) and Information and Communication Technologies (ICT) 300. The agricultural sector involves many stakeholders and institutions at national and LGA levels to deliver various services required by farmers and other CVC actors. Therefore, it is imperative to ensure coordination and effective service delivery, to avoid duplication of efforts and wastage of resources. ASDS-2 targets strengthened institutional capacities, among others, for: (i) LGAs in overseeing implementation of agricultural activities, including Public Financial Management (PFM); (ii) PPP in agricultural investment and service (extension) delivery; (iii) human resources in ASLMs to guide implementation and promote innovations; (iv) knowledge management systems for institutional memory, sharing lessons learned and long-term monitoring of the sector performance; and (v) ICT use to improve efficiency of technical support, administration and management of resources and activities. 301. Agricultural transformation requires productive human resources for generation and diffusion of technology, value addition and marketing promotion and overall sector coordination and management. There is a need for a major shift towards introduction of a new generation of farmers who are equipped with the necessary skills to revitalize and modernize agriculture. While professionalism and expertise will be taken seriously, agricultural skills and knowledge will be imparted at various levels in the education system: investment in enhancing human resource capacity will be complemented by better use of ICT for efficient sector management, including on- and off-budget public good investments in the sector. 302. The challenges are to enhance institutional capacities of public (national and local) and private/ associative players (FOs, private sector and non-state actors) to support enhanced coordination of planning, implementation, policy analysis, research, technical support services, agroprocessing, financing and M&E in the agricultural sector, while ensuring that women and youth play a major role. The public sector will create an enabling environment including: setting up appropriate and 128 ASDP Annual Performance Report 2009/2010, March 2011; ASDP Annual Performance Report 2010/2011, November 2011; ASDP Annual Performance Report 2011/2012, draft in progress, April 2013. 119 Agricultural Sector for Industrial Development improved standards and regulations, providing public investments, negotiating on trade matters, organising safety nets for targeted stakeholders, defining sustainable access to and management of natural resources, and providing enhanced agricultural statistics. The private sector, including producer organizations, CBOs/NGOs and business enterprises, will participate in activities and also increase profitable investments in the agricultural sector for production, agroprocessing and/or commercialization. 303. Communication and Knowledge Management. Key communication and knowledge management (CKM) issues of the sector which will be addressed include: (i) inadequate capacity to produce, gather, analyse, document lessons learnt, disseminate and share information at all levels; (ii) inadequate understanding of stakeholders on ASDP II, ASLM policies, mandates and their roles in achieving ASDP II goals; (iii) long chain of communication between ministries and LGAs; (iv) WARC are few, have inadequate facilities that are not fully utilized; (v) low access, untimely and unavailability of agricultural information on inputs, credit facilities, markets, weather and other technologies; (vi) weak information sharing between district councils and ASLMs for immediate action on implementation of ASDP II; (vii) weak coordination and collaboration within and among Communication units in ASLMs and LGAs; and (viii) weak and untimely feedback mechanisms. Knowledge management issues were incorporated with the intention of taping the programme’s best practices, processes and successes for sharing with stakeholders in the country and beyond. 304. During implementation of ASDP-1, efforts were made to strengthen communication at all levels by establishing a Communication Thematic Working Group (TWG) with a mandate to coordinate communication and advocacy campaigns of ASDP. This TWG also established a CKM strategy aiming at using knowledge more effectively for improving the way of doing business to achieve greater impact. This strategy will continue to be implemented under ASDP II by ensuring that: (i) there is coordination of CKM activities in the sector; (ii) stakeholders receive appropriate messages through suitable channels; (iii) there is smooth two-way flow of information; and (iv) farmers are empowered in decision making and participate fully in formulation and implementation of the ASDP II. 305. The CKM objective is to improve information flow, knowledge management, sharing, and learning and create good relationship between actors to achieve programme goals and impacts. Specifically, the CKM intends to: (i) improve coordination of CKM activities among and within ASLMs and LGAs; (ii) strengthen institutional CKM capacity of sector ministries and LGAs; (iii) raise stakeholders’ awareness and understanding of ASDP and other agricultural development projects/programmes; and (iv) improve information flow, access, availability, knowledge management and sharing among stakeholders. Proposed strategies involve among others: (i) build capacity on CKM to ASLMs, regions and LGAs; (ii) establish strong functional linkages for planning, implementation and M&E system with CKM functions at national and local levels; (iii) promote and strengthen public–private sector participation in agricultural development interventions; (iv) strengthen documentation of ASDP formulation process, implementation, achievements and challenges for future reference; and (v) strengthen publicity of ASDP and other agricultural sector initiatives at all levels, working with the media. 306. Use of modern ICTs, including Internet, mobile phones etc., enhances economic and social development, through improved access to information, knowledge sharing and service payment. The Government of Tanzania has started to integrate ICT applications into key development policies and strategies including National Strategy for Growth and Reduction of Poverty (NSGRP) and Tanzania Development Vision 2025. The Vision 2025 clearly recognizes promotion of ICT as central for competitive socio-economic transformation and a driving force for the realization of the vision. 307. Objectives for Institutional Capacity strengthening. This action area will support the strengthening of public institutions to enable them to work as an effective facilitator of inclusive agricultural development.129 Where not covered under the other ASDP II components, non-state actors will 129 Under ASDP II it is envisaged that farmers and the private sector, including NGOs and producer organizations, 120 Agricultural Sector Development Programme II (ASDP-II) also receive capacity development support to encourage them to take a leading role in building commercialized agriculture in the selected commodities under the programme. Capacity building support is provided at local, regional and national levels. Continued support for capacity building is provided to all districts (at different levels) to build on ASDP-1 momentum and prepare districts to integrate ASDP II. 308. At local level, ASDP II will continue to strengthen the DADP planning processes established under ASDP-1. The programme will help districts to strengthen CVC approaches within consolidated and resilient farming and marketing systems. A top-up to the basic level of District Agricultural Capacity Building Grant130 support will also be provided under ASDP II to all districts to help maintain and improve their planning and implementation capacities and systems and capacity for local planning, coordination of implementation and follow-up, reporting and application of regulatory functions. 309. In line with the concentration of investments foreseen under ASDP II, capacity development support will be provided to 25, 50, 75, 100, 125 priority rural districts in ASDP II years 1 to 5 respectively, while all districts are expected to come on stream from Year 5 on. The districts will generate at least 20% of their capacity building budget from their own revenues. Districts not prioritized initially would receive a basic capacity building top-up under ASDP II until they join the investment mainstream, to strengthen their capacity to plan and implement CVC interventions for the district. Furthermore, these districts will also be able to receive support from other sources, including from revenues LGAs have raised locally, the general local government grant from central government, and from other agriculture-related projects funded outside ASDP II. 310. Support will be provided for: (i) capacity building of District and Ward Extension Teams and other stakeholders on comprehensive planning processes to identify critical challenges/ constraints to productivity and income growth and investments opportunities along priority CVCs; (ii) strengthening of institutional systems and capacity building at district level, targeting to improve analytical planning and M&E skills; (iii) enhancing the scope of DADP as a comprehensive sector coordination framework that integrates all projects and initiatives implemented at local level; and (iv) development of human resource capacity at LGA level for technical service delivery of agriculture professionals and other local service providers. 311. At national level, ASDP II targets staff within the ASDP II Coordination Team, the TWGs and other staff from ASLMs and from the regions, who require training to strengthen their understanding and potential support activities on different aspects, such as among others, commercialized agriculture, value chain approaches, participative extension and rural finance. Following identified requirements and demands of involved services, a training plan will be established and specialized short courses would be outsourced to suitable local institutes and universities who would prepare and deliver suitable subject matter on these topics, or sub-contracted to specialized local or international experts. 312. To build capacity to improve and adapt the DADP planning and reporting system, capacity building support will be provided to national and regional staff on data processing, analysis and report writing. Members of the ASDP Coordination Team, the TWGs would benefit, as would selected ASLM staff and staff from the priority regions. Support to policy analysis is another area that the programme will finance including through improved analytical capacity of ASLMs for planning and policy analysis, sector performance reviews and Public Expenditure Reviews (PERs)131. In conjunction with other government actions, the support will focus on improving value chain analysis and policy support, but also addressing policy and regulatory issues that affect related value chains. The Directors of Policy will undertake most of the investments, including investments for input provision, production, credit, marketing, processing and storage as well as extension services, in cooperation with public sector agencies. ADSP-2 public investments will nonetheless, align with government systems and procedures. 130 The Agriculture Capacity Building Grant will be a discretionary grant to support agricultural extension or other advisory services, capacity building, and to strengthen the planning and operational capacity of the LGA agricultural team at district, ward/village levels. 131 Complementing other initiatives such as MAFAP/FAO, the International Food Policy Research Institute (IFPRI) and Michigan State University (MSU). 121 Agricultural Sector for Industrial Development and Planning in the ASLMs will strengthen their work on analysing specific commodities and how to improve different areas of their respective value chains in close collaboration with other initiatives (MIRVAF and SAGCOT) and the private sector. 313. ICT. ASDP II support to the development and use of ICTs will require the involvement of specialized technical capacities to develop consolidated and effective systems to enable information exchange (forwarding and feedback) at all levels within ministries/institutions and across national, regional, district and local/village and final user levels. Technologies for open systems are improving fast while their costs are gradually reducing. The application domains for ICT in the agricultural sector are as follows; 314. Leveraging ICT tools and methodologies to support business operations and resource planning, management and practice along agricultural value chains. Under this activity, ASDP II will support the development and implementation of new systems that leverage use of ICT in providing services to stakeholders along the value chain to: (i) have better access to technical advice to improve farm management and farming practice; (ii) provide feedback and information to advisors and programme officers; (iii) establish marketing linkages with input suppliers and output purchasers through available information as made available; (iv) participate in potential e-services schemes (e.g., for input or mechanization services such as e-voucher, e-wallet, e-loans, etc.); and (v) improve business processes within government through use of ICT. Proposed ICT tools and methodologies will, among others: • Dramatically expand farmers and their advisors access to a broad array of practical knowledge and information including, but not limited to, agricultural input prices and availability, prices for farm products, local weather, agricultural and animal production practices, seed varieties and their characteristics, farm management practices and tools, etc. • Enable easy and systematic flow of information from farmers and/or their advisors to public programme officers—to facilitate collection of farm-level data for M&E purpose, but also allowing farmers to provide regular and timely feedback on the performance of public programmes. • Facilitate farmers in finding and establishing input/output marketing linkages with other farmers (bulking), potential suppliers and buyers. • Facilitate ‘automation’ of business processes within government so as to increase efficiency of public service delivery to the public through use of ICT tools. 315. Accordingly, ASDP II will support: (i) the development and implementation of the ICT system and its backbone architecture (comprehensive agricultural data, network services and integrated and optimized solutions); and (ii) the equipping of agricultural advisors/extension in selected areas with ICT tools (low-cost tablets for advisors, smartphones for lead farmers) and methodologies to enable enhanced access to technical and economic information and relevant information sharing networks. A backbone would include, inter alia, the following features: (i) consolidation of the government’s current agricultural data centres into one state-of-the-art facility; (ii) provision of the improved ICT infrastructure and standardized security services to external suppliers (i.e., firms) of e-services such as e-voucher and e-wallet; (iii) intercommunication between integrated solutions; and (iv) data collection, processing and cataloguing. 316. The ministry has designed an ICT Policy and Master Plan for the crops subsector, part of which is under early stages of implementation. To avoid duplication of efforts, this ICT Policy and Master Plan needs to be updated to incorporate other subsectors, particularly livestock and fisheries, but also marketing spearheaded by the Ministry of Industry Trade and Investment. Having a sector-wide ICT Policy and Master Plan will lead to sector-wide systems, addressing ICT needs of the sector. 317. Communication between all levels will be improved by supply of vehicles, motorbikes computers and related running expenses to the national coordination, RASs and district teams. Furthermore, communication tools (including low-cost mini-tablets or smartphones) will be piloted at ward level for programme management requirements, extension and marketing support, but also for the collection, receipt and dissemination of data for M&E. Arrangements with cell phone companies will be made to allow for forwarding technology or market related text messages to farmers, but also for dedicated 122 Agricultural Sector Development Programme II (ASDP-II) free call numbers allowing farmers to call their extension worker or technical specialist at district level. While ICT may not be applicable to all areas due to lack of connectivity it is anticipated that the network will continue to expand and offer opportunities to wider farming communities. 318. Proposed action areas for institutional capacity strengthening, CKM and ICT are summarized in Table 47. Table 47: Proposed interventions for CKM and ICT promotion Action area Proposed activities I n s t i t u t i o n a l strengthening i. Training of national coordination, RAS and district technical/facilitation teams ii. Capacity building block grant (including 20% local participation) iii. Continued support to WARC CKM action area i. Repackage technical information (e.g., research information) into user friendly information for it to be shared with different stakeholders ii. Conduct formal and regular meetings on CKM among ASLMs and LGAs (awareness and progress) iii. Conduct training programme on CKM and IT at different level iv. Prepare and disseminate guidelines on CKM strategy implementation v. Provide technical backstopping and guidance in KM and communication to regional and LGAs staff, vi. Conduct media forums, workshops & seminars on agricultural sector issues vii. Produce promotional/educational material for target audience viii. Document ASDP lessons learned and establish best practices under SWAp for sharing with stakeholders ix. Participate in local and national events for publicity of ASDP/DADPs and other agriculture sector initiatives and dissemination of new innovations x. Curricula of students Leveraging Strengthening use of ICT to improve efficiency in the sector i. Update crops subsector ICT policy and ICT Master Plan developed by the ministry to incorporate livestock and fisheries subsectors ii. Design and build National Agricultural Information System that will incorporates information on agricultural production, research and extension, land use management and agriculture output marketing information iii. Computerize ASLM internal business operations such as agricultural projects and programmes management, financial management, assets control and inventory management and documents and files management. The government has centralized financial and human resource management which does not fulfil all ASLMs business requirements in those areas, and use of ERP tools will be used here iv. Equipment provision, enhance quality of ICT service delivery and building capacity of ATIs ICT training capacities. v. Design and equipping of ASLMs mini-data centres for sector information management, establishing and equipping LANs for reliable internal and external communications. ASLMs will also facilitate connection of wards to the fibre optic backbone vi. Put in place risks management measures related to ICT use vii. Promote use of mass media (i.e., mobile phones) for sharing agricultural information viii. Free call numbers for personalized advisory services ix. Pilot electronic work plan and monitoring (ward level) x. Publicity for the sector promotion (successful farmers, investors, radio/TV, skype/video, etc.) Note: The overall ASDP II investment (hardware and software) for promoting agriculture sector involvement into use of modern ICT is included in sub-component 4.5. Sub-component 4.6: Expanded Access to Rural Finance 319. Background. Inadequate financial service for small-scale commercial farmers is a major constraint to agricultural growth and limits the level of investment and the pace of agricultural commercialization. Commercial banks are reluctant to lend to the sector and have limited outreach in rural areas. There are numerous microfinance institutions (MFIs) targeting farmers, but they have limited capacity to reach the large number of rural households due to lack of skilled personnel, branch networks and finance. Small- and medium-scale enterprises engaged in value addition are also constrained by access to financial resources. 123 Agricultural Sector for Industrial Development 320. Currently, government initiatives promote agricultural rural finance mechanism including among others: (i) the National Financial Inclusion Framework (Steering committee is chaired by the Bank of Tanzania, drawing members from the Ministry of Agriculture, CMSA, the Ministry of Finance and Planning, TIRA, TCRA, FSDT, TAMFI and mobile phone operators); (ii) SACCOS, channeling savings and finances borrowed from the commercial banks to the smallholder farmers who are members of the SACCOS, but also other similar arrangements through the SACCAS, VICOBA and the like; (iii) WRS for smallholder farmers to access financing of their agricultural activities (mostly in traditional cash crops); (iv) the National Cooperative Bank that envisages at financing cooperative societies (unions); (v) the agricultural lending window in the Tanzania Investment Bank; (vi) the Kilimanjaro Cooperative Bank and the Kagera Farmers’ Cooperative Bank; (vii) lending to youth to engage in income generating activities including agriculture (Ministry of Information Culture Artists and Sports); (viii) LGAs to set aside 10% of their own source revenues to be channeled to lending to youth and women in the respective LGAs area of jurisdiction; (ix) the Agricultural Inputs Trust Fund (AGITF) under the Ministry of Agriculture; (x) the National Social Security Fund (NSSF) issues individual and cooperative loans (Wakulima scheme); (xii) NAIVS and potential follow-up programmes; and (xiii) the Marketing Infrastructure, Value Addition, and Rural Finance (MIVARF) Programme132 issuing grants to Irrigators Organizations or Paddy Agricultural Marketing Cooperatives to acquire medium size rice milling machines. The government plans to establish and operationalize an Agricultural Development Bank to provide a specialized funding window for investment in the sector, while catalytic funds (see e.g., SACGOT) and credit guarantee schemes are some of several initiatives towards integrated rural commercialization. 321. The number of commercial banks is increasing (about 50 in 2014) and some of them extend services to agricultural sector and agroprocessing. Agricultural financing (crops and livestock) from commercial banks in terms outstanding sector lending is gradually increasing at an equivalent of 10% of the total lending (about TSh 1 trillion). Private Agriculture Sector Support (PASS) Trust established in 2000 and funded by DANIDA through CRDB Bank Ltd. has been providing support for business planning and guarantees. Formal and informal MFIs, financing to SACCOS, also support the agricultural economy of the smallholders in rural areas. The initiative of the National Financial Inclusion Framework by MOF intends an implementation plan targeting 50% of the adult population to have access to formal financial services by 2016. 322. Overall, numerous public, project-related and finance institutions initiatives exist at national and local levels to promote access to rural financing of the public sector, but no clear strategy (and coherent and comprehensive action plan) promoting rural financial systems to up-scale stakeholders investment in the agricultural sector, within sustainable PPPs. Improving financial services to the sector is a key policy issue in order to facilitate private investment. 323. For ASDS-2, the required public interventions promoted by ASDS-2 include: (i) promote services of existing community banks and start-up of new ones at local level; (ii) design agricultural credit packages, appropriate to smallholder farmers; (iii) provide support to establish stronger and well capitalized grassroots MFIs such as SACCOS and Village Community Banks (VICOBA) as first- line financial services for small-scale commercial farmers; (iv) update the National Microfinance Policy in collaboration with other ministries to take into account recent developments in technology such as the use of mobile banking, pension schemes and insurance schemes, which are useful to rural households entering into commercial farming; (v) strengthen overseeing/regulatory functions of the Cooperative Department at local level as part of promotion of MFIs; (vi) accelerate efforts to expand agricultural finance services through TIB-Agricultural window, AGITF, the establishment of the Tanzania Agricultural Development Bank, for medium- and long-term investment in agricultural production and processing; and (vii) promote lending for agricultural investments from commercial banks. 132 For rural finance MIRVAF targets improved and sustainable financial and operational performance of: (i) informal grassroots associations, SACCOS and other MFIs; and (ii) rural small- and medium-scale entrepreneurs. 124 Agricultural Sector Development Programme II (ASDP-II) 324. Within ASDP II, priority action areas for expanded access of smallholder producers and transformers/exporters (SME/SMI) to rural financing, include among others to: i. Develop a comprehensive rural financing strategy and action programme for promoting business investments and profitability in agricultural commodity value chains development with all involved stakeholders. ii. Strengthen cooperatives and other economic associations and related SACCOS/SACCA (social control as guarantee) for providing sustainable (and stakeholder-owned) (micro) financial services at local level. iii. Enhance availability of and access to short- to medium-term agricultural financing sector within a PPP approach, involving among others an Agricultural Development Bank, private banks investing in the rural sector, etc. iv. Facilitate farmers access to agricultural investments, among others by: (a) promoting WRS to overcome the guarantee issue; (b) strengthening contract farming (contractual agreement between producer organizations, agrobusiness, exporters and banks/financiers); (c) establishing a legal framework policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers). 325. Comprehensive rural financing strategy and action programme. There is little coherence among number of public and private initiatives for promoting an agricultural rural finance mechanism, giving rise to the need to develop, consolidate and implement a multi-stakeholder strategy to promote agricultural investment. A strategy for improving rural financial linkages would include, among others, to: (i) encourage and strengthen the sector’s own control through network organizations for rural SACCOS; (ii) facilitate linkage of FOs (associations) with financial cooperatives, micro- credit institutions and/or commercial banks; (iii) enhance the bargaining power of producer, trader and processor organizations, associations and cooperatives through improved market information, aggregation of produce and the use of inventory financing opportunities; and (iv) strengthen the public sector support in its regulatory function of the financial sector. 326. Grassroots financial services133, aiming at building the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs to expand their rural outreach, and supporting selected community banks as alternative rural financial service providers. The sub-component also aims at supporting the Tanzania Cooperative Development to enhance the implementation of the Cooperative Reform and Modernization Programme. Action areas include improved financial and operational performance of informal grassroots associations, SACCOS and other MFIs (informal associations transformed to MFIs on a sustainable basis), but also strengthened operational linkages between MFI and formal financial/credit institutions. 327. Warehouse Receipt System (WRS)134 using stocks as guarantee for facilitating access to affordable credit in participating financial institutions (PFIs). The financial institutions would access eligibility of warehouse receipt operators to credit on the basis of checklists and benchmarks including: (i) governance and structure of membership; (ii) existence of by-laws, manuals and minutes of meetings; (iii) financial and income statements and balance sheets; (iv) assets; (v) credit history; and (vi) contractual agreements with buyers of produce. ASDP II will support PFIs in collateral management of warehousing, value chain analysis, agricultural risk management, and market research and intelligence, to minimize the risks of their ventures. To improve access of rural financial institutions to data on opportunities for value chain financing, detailed financial analyses will be undertaken for gross margins, profitability, repayment capacity, etc., of all actors in the value chains being supported, and develop training manuals and guidelines for applying the methodology to identify financing opportunities and analyse proposals. 328. The Food and Agriculture Organziation of the United Nations (FAO) in collaboration with Rabobank/ 133 See also MIRVAF and lessons learned (IFAD). 134 See also ‘Professional warehouse management (COWABAMA initiative) in s/c 3.2. 125 Agricultural Sector for Industrial Development NMB Foundation pilot project aims at building financial management capacity among producers and their organizations, creating sustainable linkages with local financial service providers and agricultural value chain agents and improving productivity practices. It will build linkages between FOs and financial service providers which will also provide room for development of a long-term market strategy. Smallholder paddy producer organizations will be formalized into agriculture marketing cooperative societies (AMCOS) to achieve scale and bargaining power, strengthening the commercial relationships between FOs and other rice value chain actors and building the capacity of smallholder farmers to manage loans and participate in the national WRS which will enable them to become creditworthy. 329. Availability of short- and medium-term financing for input provision and operating warehouses which would result in value addition, improvements of grain quality and bulking at the farmer association/cooperative enterprise scale is a key success factor. The improvement of value chain actors and farmers’ access to rural financial services135 by facilitating links to sound financial institutions, including commercial banks, but also partnerships with other initiatives in the rural finance sector136. During the first year, several participating financial institutions and financing models would be identified, so as to ensure availability of financial services in target clusters. 330. However, due to high interest rates and lack of credit guarantees, it remains difficult for farmer groups and private firms to borrow medium- to long-term loan for facilities/equipment investments. This hinders the agricultural investment significantly and appropriate mechanisms need to be developed. Even for seasonal credit, interest rates absorb large parts of supplementary net return on investment (inputs) due to low efficiency in productivity growth. Within this context, targeted subsidies (e.g, interest rates), specialized trust funds and other similar mechanisms need to be discussed between all stakeholders to facilitate sustainable access of sector stakeholders to financial services for agricultural investments, without competing with the financial system. 331. Key action areas and activities to improve sustainable rural/agricultural investments have been summarized, as shown in Table 48. 135 See also National Entrepreneurship Development Fund—NEDF facilities. 136 The programme will collaborate with other initiatives engaged in classic and innovative financing to build an information base that could help streamline complementary financing through financial institutions at different levels. See also related supports by Rabobank initiative, etc. 126 Agricultural Sector Development Programme II (ASDP-II) Table 48: Action areas and activities to improve rural/agricultural investments Action areas Activities Comprehensive rural financing strategy and action programme - Draft and consolidate comprehensive agricultural investment financing strategy with all involved stakeholders - Develop and action programme for enhanced offer and access to rural financing, its financing and implementation modalities Strengthen organizational and technical capacity of existing and new small-scale producer, trade and processing farmer organization and cooperatives - Training and strengthen organizational and technical capacities of farmer organizations to enhance the bargaining power of producer, trader and processor - Facilitate linkage of farmer organizations/associations with financial cooperatives MFI, and/or commercial banks - Strengthen sector’s own control (audit) through network organizations for rural SACCOS - Support the up-scaling of WRS by expanding into new locations and adding new crops - Sensitize on the linkage between SACCOS and AMCOS; train FOs/AMCOS management and board members on good governance and supervision - Support outreach expansion of selected community banks as alternative rural financial service providers - Build the capacity of informal financial institutions and SACCOS to consolidate them into viable, sustainable entities, supporting selected MFIs - Improve financial and operational performance of informal grassroots associations, SACCOS and other MFIs - Support the Tanzania Cooperative Development Commission to enhance the implementation of the cooperative reform and modernization programme Enhance availability of and access to short- to mediu- term agricultural financing - Rural finance support aiming at increasing the access of rural producers and entrepreneurs to financial services by commercial banks, testing new approaches, methods and services in rural areas for the benefit of the target group, improving the legal and policy framework for rural microfinance, and integrating knowledge management into the programme - Improved access to financial services on a sustainable basis for rural small- and medium- scale entrepreneurs (increased number of farmers and SMEs obtaining loans from financial institutions) Facilitate farmers access to agricultural investments - Improved farmer organizations and cooperative input and output marketing by information systems, aggregation/grouping of produce and the use of inventory financing opportunities - Promoting WRS to overcome the guarantee issue - Consolidating and scaling up contract farming where applicable (contractual agreement between producer organizations, agrobusiness, exporters and financial institutions) - Design schemes that will enable smallholder access to loans financing along agriculture value chains (start with lessons learned from ongoing schemes) - Establishing a legal framework and policy for ‘leasing’ contracts, especially for promotion of private mechanization services (contractual agreement between equipment importers, investment banks and mechanization service providers) 332. Implementation. The Tanzania Cooperative Development Commission under the Ministry of Agriculture should take the lead role in developing strategies and priority actions in close collaboration with all sector stakeholders, including departments of Policy and Planning in all ASLMs; departments responsible for Crop, Livestock and Fisheries Development in the ministry; Marketing Department (Ministry of Industry Trade and Investment), the Ministry of Finance and Planning; FOs; MFIs and private banks and development partners. 127 Agricultural Sector for Industrial Development Summary of investments for Component 4. Table 49: Five Years Development budget / investment projection for component 4 (TSh million) COMPONENT 4: STRENGTHENING SECTOR ENABLERS - BASE COST ESTIMATES AT CONSTANT 2016 PRICES (TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310 967 352 387 426 2442 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019 2,023 1,647 1,685 1,847 13221 4.1.1.4 Strengthening and control of child labour in Agriculture 1,585 1,050 1,094 808 684 5221 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587 933 427 - - 1947 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector 4,014 3,742 2,299 2,116 1,195 13366 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,025 3,238 2,779 852 930 10824 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872 6,673 4,280 2,115 2,197 22137 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425 6,998 2,879 2,591 2,196 19089 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,333 3,209 1,597 1,294 1,123 18556 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429 6,350 3,781 2,501 1,142 17203 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047 2,377 336 213 400 6373 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481 1,833 1,600 1,514 639 7067 TOTAL COMPONENT 4 46,127 39,393 23,071 16,076 12,779 137,446 128 Agricultural Sector Development Programme II (ASDP-II) V. PROGRAMME COST, FINANCING AND FINANCIAL MANAGEMENT A. Overall Programme Cost 333. By combining the base development budgets for each component, the overall investment costs of ASDP II were derived (Table 50). Data in Table 50 show that the base cost of ASDP II is estimated at TSh 13, 819 billion (USD 5, 979 million) and annual investment base costs range from TSh 2,284 billion (USD 988 million) to 3,238 billion (USD 1,400 million) over a 5-year period. However, the costs for NFRA grants and input subsidies are not included. 334. Component 1: Sustainable Water and Land Use Management is estimated at TSh 2,024 billion (USD 941 million) and a high proportion of this budget is allocated to irrigation development. Component 1 accounts for 15% of overall programme cost. The cost of Component 2: Enhanced Agricultural Productivity is estimated at TSh 8,081 billion (USD 3,758 million) or 58% of overall programme cost. Component 3: Commercialization and Value Addition (including investments to promote priority value chain development) is estimated to cost TSh 1,483 billion (USD 1,663 million) or 26 % of overall programme cost. Furthermore, the cost of Component 4: Strengthening Sector Enablers is estimated at TSh 137 billion (USD 67 million), or 1% of programme cost. The Tables 50 and 51 show details of the estimate investment costs by figures and percentage. Table 50: ASDP II Component Budget Requirements and Percentages for the first five years. Component Budget Requirement % Component 1 Sustainable Water and Land Use Management 2,024,646,012,085 15% Component 2 Enhanced Agricultural Productivity and Profitability 8,081,495,303,009 58% Component 3 Commercialization and value addition 3,575,493,642,854 26% Component 4 Sector Enablers, Coordination and Monitoring and Evaluation 137,442,668,522 1% Table 51: Overall development budget for ASDP II ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total Component 1: Sustainable Water & Land Use Management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones). 29,759 31,014 34,532 0 0 95,305 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity. 14,132 14,517 13,715 13,501 16,284 72,149 129 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 1.1.1.3 Enhancing access to agricultural land for youth empowerment. 4,464 4,150 5,753 4,534 6,321 25,222 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (All products). - 1,366 928 839 916 4,049 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,370 184,589 172,338 175,278 189,619 738,194 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity. 5,873 50,129 57,162 59,915 65,430 238,509 1.2.2.1 Strengthening Irrigation schemes management and operations. 1,823 1,652 2,250 1,787 2,592 10,104 1.2.3.1 Development of water infrastructures for livestock productivity. 2,856 66,582 77,456 76,103 85,464 308,461 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries. 42,069 79,875 111,447 158,157 88,773 480,321 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies. 1,905 13,984 8,745 6,345 10,445 41,424 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management. 1,090 1,045 1,730 795 1,329 5,989 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness. 1,960 1,052 1,009 396 501 4,918 sub-total 122,301 449,955 487,065 497,648 467,674 2,024,643 Component 2: Enhanced Agricultural Productivity and Profitability 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,913 772,652 849,529 838,081 921,148 4,693,323 130 Agricultural Sector Development Programme II (ASDP-II) ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,373 9,720 9,349 8,506 9,222 41,170 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389 136,695 150,284 164,670 181,057 782,095 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176 2,652 2,800 2,962 3,141 15,731 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664 93,408 768 1,099 987 97,926 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146 4,533 5,008 4,246 4,639 19,572 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,115 5,176 7,350 4,460 2,090 23,191 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,090 50,853 48,517 6,658 4,388 165,506 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources 2,537 2,134 2,199 2,147 2,319 11,336 2.2.1.8 Improvement of plant health services 13,322 11,191 7,608 1,389 478 33,988 2.2.1.9 Production of vaccines and drugs 44,570 36,191 39,700 3,705 4,380 128,546 2.2.1.10a Improvement of livestock health services 262,550 295,128 332,216 371,559 420,078 1,681,531 2.2.1.10b Improvement of aquatic health services 1,518 1,238 1,241 1,340 1,395 6,732 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,559 29,197 29,504 8,708 9,516 84,484 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,409 16,384 11,616 11,110 11,371 62,890 131 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,833 3,895 2,683 2,738 3,011 17,160 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,250 5,753 5,699 5,707 5,717 32,126 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,153 11,722 12,960 14,297 10,394 63,526 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,538 22,167 23,955 25,921 28,084 120,665 sub-total 1,925,105 1,510,689 1,542,986 1,479,303 1,623,415 8,081,498 Component 3: Commercialization and Value Addition 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,346 456,728 568,733 635,561 684,371 2,443,739 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847 9,466 156,458 171,750 368,188 713,709 3.1.2.2 Improving local and improved chicken market access 743 2,068 2,248 369 282 5,710 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,834 738 733 643 630 4,578 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,239 4,073 4,376 1,442 13,999 25,129 3.2.1.1 Strengthening and development of agro processing industries for value addition for all priority commodities 10,333 14,448 15,432 16,806 18,522 75,541 3.2.1.2 Improving milk value chain 8,886 8,536 8,014 4,213 4,571 34,220 3.2.1.3 Strengthening hides and skin value chain 13,915 10,119 19,594 5,972 5,307 54,907 132 Agricultural Sector Development Programme II (ASDP-II) ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 3.2.1.4 Strengthening value chain for horticultural commodities 4,995 1,622 4,127 1,274 1,387 13,405 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,328 21,012 22,695 24,805 27,302 122,142 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,758 6,752 7,267 7,868 8,432 36,077 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,633 12,739 3,507 505 226 26,610 3.2.1.8 Improving Postharvest Management Along Food Supply Chain for sustainable food security and nutrition 1,088 2,710 12,534 2,324 1,080 19,736 sub-total 190,945 551,009 825,718 873,532 1,134,297 3,575,501 Component 4: Strengthening Sector Enablers 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310 967 352 387 426 2,442 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019 2,023 1,647 1,685 1,847 13,221 4.1.1.4 Strengthening and control of child labour in Agriculture 1,585 1,050 1,094 808 684 5,221 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587 933 427 - - 1,947 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector 4,014 3,742 2,299 2,116 1,195 13,366 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,025 3,238 2,779 852 930 10,824 133 Agricultural Sector for Industrial Development ASDP II BASELINE COST ESTIMATES - at constant 2016 Prices (in TSh million) Cost Item Year 1 Year 2 Year 3 Year 4 Year 5 Total 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872 6,673 4,280 2,115 2,197 22,137 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425 6,998 2,879 2,591 2,196 19,089 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,333 3,209 1,597 1,294 1,123 18,556 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429 6,350 3,781 2,501 1,142 17,203 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047 2,377 336 213 400 6,373 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481 1,833 1,600 1,514 639 7,067 sub-total 46,127 39,393 23,071 16,076 12,779 137,446 Total Baseline Cost in TSh million (constant prices) 2,284,478 2,551,046 2,878,840 2,866,561 3,238,165 13,819,090 Total Baseline Cost in USD million (constant prices) 988.4 1,103.70 1,245.50 1,240.20 1,400.90 5,979 B. Financing Plan 335. With regard to the financing of the development budgets for ASDP II, the main sources of funding will include the government, development partners and other stakeholders like private sector, NGOs and farmers. For each programme sub-component, the proportions of the budget for which the respective financiers would provide funds were determined to derive a tentative financing plan for ASDP II. The proportions of the development budgets financed by different sources are shown in Table 52. Table 52: Proportions of the development budget expected to be financed by different funding sources ASDP II CONTRIBUTION ESTIMATES - Proportion of budget financed by different sources (%) Cost Item Government Development partners Development partners Private sector/ Farmers Total (%) Investment level a on-budget off-budget National Local Component 1: Sustainable Water & Land Use Management 15 60 16 10 100 27 73 134 Agricultural Sector Development Programme II (ASDP-II) Component 2: Enhanced Agricultural Productivity 51 29 15 5 100 31 69 Component 3: Commercialization and Value Addition 33 40 22 5 100 31 69 Component 4: Strengthening Sector Enablers 51 23 25 1 100 52 48 a Government at national and local level (LGA) 336. Based on the above assumptions, the base and total development budget for ASDP II summarized by financier is presented in Table 53. The analysis shows that the government would finance about 41% of the programme while development partners would provide 53% (36% on-budget) and other stakeholders (private sector, NGOs and farmers/beneficiaries) about 6%. Table 53: Illustrative financing plan for ASDP-2 (summary of total costs in TSh million) Cost Item Govt Development partners Beneficiary Total on-budget off-budget Private sector/ Farmers Component 1: Sustainable Water & Land Use Management 302,067 1,205,008 316,732 200,835 2,024,643 Component 2: Enhanced Agricultural Productivity 4,096,501 2,368,697 1,212,225 404,075 8,081,498 Component 3: Commercialization & Value Addition 1,197,203 1,419,823 779,701 178,774 3,575,501 Component 4: Strengthening Sector Enablers 70,028 32,278 33,775 1,364 137,446 Total Cost in TSh million (contingencies included) 5,665,800 5,025,806 2,342,434 785,048 13,819,088 Total Cost in USD million (contingencies included) 2,451 2,174 1,013 340 5,979 % 41% 36% 17% 6% 100% C. Financing Arrangements 337. Under ASDP-1 programme financing was executed through a Basket Fund arrangement. The institutions responsible for implementation of the programme at national level component were MAFC, MLFD and MIT. Implementation at the local level was the responsibility of the then PMO- RALG and LGAs. The Basket Fund activities are coordinated through the ASDP Basket Fund Steering Committee, which comprises the permanent secretaries of all the ASLMs, the Vice President’s Office and the Ministry of Finance as well as representatives from development partners contributing to the Basket Fund. 338. The Basket Fund system contrasts with the traditional practice of establishing separate project accounts in which deposited funds are managed by project implementation units (PIUs). ASDP-1 financing arrangements were fully integrated into existing government financial structures, which include planning, budgeting, accounting, reporting and auditing services. The Agricultural Fund Steering Committee (AFSC), a sub-committee of the Agricultural Steering Committee (ASC) will review work plans and budgets submitted by the Planning and Budgeting Thematic Working Group (PBTWG), through the Technical Committee of Directors (TCD) to be financed by the ASDP II. Approved annual plans and budgets will be submitted to the ASC for approval and disbursements of funds against technical and financial reports submitted by Components Leaders for the local level plans and budgets, the Agricultural Fund Steering Committee will also approve plans and budgets for PO-RALG. Disbursements to RS and LGAS will be done through the Regional Administrative Secretary (RAS) for RS implemented activities, and District Executive Director (DED) for Local Government Authorities (LGAs). Basket Funds flow from the ASDP II holding account in the Bank of Tanzania, through an exchequer bank 135 Agricultural Sector for Industrial Development account to ASLMs, regional secretariats and LGAs. The Chief Accountants of the respective ministries are responsible for ensuring that the disbursements of funds and financial management of programme activities are undertaken in accordance with international accounting standards and the Memorandum of Understanding (MOU) between the government and development partners. 339. The Agricultural Fund Steering Committee (AFSC), through the advice of the TCD is also responsible for: (i) facilitating government and development partner contributions to ASDP II approved activities before the respective budget year; (ii) Approval of transferring resources from the Basket Fund to ASLMs based on validated technical and financial progress reports; (iii) policy directives governing the utilization and disbursement of Basket Fund; and (iv) identification of LGAs which qualify for the grants and agreeing changes to the formula for LGA allocations. The TCD is responsible for decisions on the LGA items, with the Agricultural Fund Steering Committee (AFSC), approving the submission of changes to the Agricultural Steering Committee through the agriculture representative on the LGDG Technical Committee. 340. At the local level, the ASDP II funds supports approved activities ASC. Specific activity funds such as capacity building, Extension and District Irrigation are approved by ASC through the recommendation of the TDC. These block grants are incorporated into the financing arrangements used by LGDG and are used to finance the local DADP. The flow of funds in ASDP II is presented in Figure 22. Figure 22: Flow of Funds in ASDP II GOT DPs NGOs/ NSAs R & LGAs ASLMs Exchequer Account Projects Private Sector Direct Financing ASDP2 Basket Fund General Budget Support (GBC) Pay Master General ASDP2 Holding Account Cash & D - Funds C - Funds Public investments (On-budget) Public investments (Off-budget) Private investments 341. In addition to the Basket Fund for ASDP II, agricultural projects can also be funded through on-budget financing whereby funds flow through the exchequer system. In addition, the projects can be directly funded by development partners through off-budget financing. However, off-budget financing is not recorded in the government’s agricultural expenditure accounts. 342. With regard to the financing of ASDP II activities, the government preference is to continue with the Basket Fund arrangement established under ASDP-1. This is the most integrated and expedient 136 Agricultural Sector Development Programme II (ASDP-II) financing mechanism to implement a comprehensive agricultural development programme, such as ASDP II. The mechanism also avoids a fragmented system of financing with separate projects being funded by a range of different development partners. It also reduces transaction costs. 343. Funds flow and disbursement mechanism for joint projects (JPs)/public private partnerships (PPPs) between the public and private sector are agreed during the signing of a contract and MOU between the parties involved in the project. It is important that all funds (general budget support, basket funding and direct project funding) supporting the ASDP II are accounted for during the planning and budgeting process. 344. ASDP-1 implementation demonstrated that the Basket Fund arrangement had been effective in implementing the LGDG system of delivering discretionary grants to LGAs (Agriculture Extension Block Grant, Agriculture Capacity Building Grant and DADG) which facilitated delivery of public support services and local investment through formula based approach. Therefore, the government preference is to continue with the Basket Fund arrangement to ensure effective delivery of support services (extension and research) and implementation of the Cluster Approach under ASDP II that is intended to promote priority CVC at zonal level. 345. In circumstances where development partner country policies are strictly not in favour of using the Basket Fund arrangement, the government would allow the flexibility in using ear-marked funds within the Basket Fund arrangement and stand-alone projects. 346. To integrate on-budget (budget support, Basket Fund, earmarked programmes and projects) and off- budget programme, core programme elements such as Programme Coordination and Management; Planning, and Budgeting; Monitoring and Evaluation (M&E) and capacity strengthening at national and local level will need to be financed either by the Basket Fund (government and non-earmarked development partner contributions) and/or contributions of 5% from each (on- and off-budget) programme and project in the sector. 347. In this regard development partners (both on-budget and off-budget) should contribute 5% of the funds towards coordination costs. The contributed fund would be channelled through a joint account. This account will be managed and coordinated by the National Coordination Unit (NCU) responsible for overall programme management and coordination to ensure that ASDP II activities take place according to schedule and reports are shared. The NCU which will serve as the ASDP II secretariat is an independent team would utilize a single financial management system for accounting, reporting and auditing. Staff serving NCU would be recruited on meritocracy basis. The Unit will have a good technical and professional mix including specific experts in crops, livestock and fisheries to serve the four ASDP components. Using an independent NCU provides significant scope to improve the existing government accountability and financial management systems through training and capacity building to mitigate many of the current weaknesses of the government’s planning, budgeting, accounting, reporting and auditing procedures. On the day to day management of ASDP II NCU will report to the PS-MoA. However, for program planning, budgeting, implementation, monitoring and evaluation NCU will report to TDC on quarterly basis. 348. Therefore, the government should establish a Basket Fund for ASDP II with support from participating development partners. In addition to the Basket Fund, the joint account will be established to allow participating development partners (both on-budget and off-budget) to contribute towards ASDP II management, coordination, monitoring, evaluation and auditing costs. These mechanisms would enable the government to capture all public, private and development partners’ investments in the sector. This will provide transparency and accountability and enable all stakeholders in the sector understand reasons and logic for contributing for the programme through the Basket Fund mechanism. 349. Fund flow: Funds flow for ASDP II funds will be as shown in Figure 18 for the other funding arrangement that will be mutually agreed between the government and development partners/other partners, funds would flow from designated account to the implementing agency. 137 Agricultural Sector for Industrial Development VI. INSTITUTIONAL AND IMPLEMENTATION ARRANGEMENTS A. Implementation of ASDP II at National Level 350. Implementation of ASDP II will be undertaken using existing government structures of the ASLMs137 that will be enhanced by further training and capacity building of staff. The interests associated with Natural Resources and Tourism, Land and Housing, Finance, Energy, Labour, Gender and Children Affairs, Water, Trade and Health and Social Affair, National Irrigation Commission, (NIRC), Bureau of Statistics (NBS) and Tanzania Cooperative Development Commission (TCDC) and other related key institutions will all be included. The implementation process is summarized in Table 54 and further details of the mechanisms and their roles and responsibilities are provided in Annex III. Table 54: Summary of ASDP II Sector National Coordination Organs, Membership and Frequency of Meetings Forum Chair Members Frequency of Meeting National Agricultural Sector Stakeholder Meeting(NASSM) Prime Minister Ministers of Lead Components and Related Ministries (ASLMs and Others), Development Partners, and Private Sector, Non-State Actors, RS, LGAs, Annual Agricultural Sector Steering Committee(ASC) Minister Ministry of Agriculture Permanent Secretary of Lead Components and Related Ministries (ASLMs and Others), Development Partners representatives and Private Sector Representatives Quarterly Agricultural Sector Consultative Group (ASCG) Meeting Permanent Secretary- Ministry of Agriculture All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/ Donors and NGOs/NSA) (local and International) Training and Research Institutions Quarterly Technical Committee of Directors Permanent Secretary Ministry of Agriculture Directors of Lead Components Quarterly ASDP II National Coordination Unit (NCU) National ASDP II Coordinator Members of National Coordination Management Team (NCU) Monthly Technical Committee of Component Leaders (TCCL)- PO- RALG Director Sector Coordination - PO- RALG Component Leaders at PO- RALG plus other Directors at PO-RALG Quarterly 137 ASLMs under ASDP II include the Ministry of Agriculture, Ministry of Livestock and Fisheries; the Ministry of Industry Trade and Investment; the Ministry of Water and Irrigation; the President’s Office—Regional Administration and Local Government; and the Ministry of Land, Housing and Settlement Development. 138 Agricultural Sector Development Programme II (ASDP-II) B. Regional level 351. LGAs will be coordinated by the PO-RALG in collaboration with other ASLMs through regional secretariats. The Department of Sector Coordination is responsible for management and support to LGAs by collaboration with RSs. Vertical coordination from the then PMO-RALG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. While during the ASDP I the Minister PO-RALG did not feature direct in the oversight role in the implementation of the program, under ASDP II the Minister PO- RALG will chair the Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). This will be a meeting of all representatives of stakeholders operating at the regional and local level. These will include Government, Private sector and Development Partners and NGOs/ CBOs. 352. For administrative aspect of ASDP II, coordination among RSs, TCD through NCU, TWGs will be constantly maintained to realize smooth flow of information on the status of development activities and performance under ASDP II. Detailed structure is presented in Annex III. C. Local Level 353. LGAs will be responsible for planning, designing and implementation of programme components under supervision of the RSs to promote social and economic development. They will ensure that laws and regulations are observed in implementation and maintenance and be responsible for the delivery of extension services and the administration of resources including land use planning in conjunction with private sector investors. It is important that the District Agricultural Development Plans (DADPs) are integrated into the district plans and budget. The districts will also form district thematic working groups to comprise District Experts (i.e. agriculture, trade, land, planning and budgeting, cooperatives, and community development, environment/conservation); district private sector representatives, and NGOs/CBOs operating in the region. D. Coordination mechanisms and processes 354. The hierarchy of coordination organs and functions under ASDP II at national level are summarized below and detailed further in Annex III. 355. The National Agricultural Sector Stakeholders Meeting (NASSM) will be held once a year following the annual JSR/PER performed by government, development partners, non-state actors, and the private sector to monitor sector progress. The report will be presented and adopted by the Agricultural Steering Committee and discussed at NASSM 356. The Agricultural Steering Committee (ASC) will be the key oversight and approval organ of ASDP-II implementation and coordination. It will aim to approve the annual work plan, budget, oversee the physical and financial progress, follow-up the audit results and discuss on key issues in regard to sector performance and coordination to guide the TDC and TWG. Oversee monitoring and evaluation of ASDP II. 357. Agricultural Sector Consultative Group Meeting (ASCG). The ASCG will provide a consultative and advisory forum for dialogue between the government (ASLMs), all interested development partners (as defined in the JAST), private sector and non-state actors (NGOs, CSO and PSO) in the agriculture sector. The ASCG will coordinate dialogue at two levels: regular dialogue on sector policies and regulations; annual plans, budgets, and the annual agriculture sector/public expenditure review (ASR/PER) reports. ASGC is an advisory group, while ASC is a decision-making organ. 358. Technical Committee of Directors (TCD). The TCD will provide technical advice to the Agricultural Steering Committee on technical issues in connection with the program components, sub components, investment areas and development projects. It will be supported by NCU and the TWGs of respective Lead Components 139 Agricultural Sector for Industrial Development 359. Thematic Working Groups (TWGs). Membership of TWGs will be drawn from experts within the relevant fields (i.e., departments/institutions) in each ASLM and should invite participation of development partner’s subject specialists. The TWGs will guide the programme on technical and/or managerial matters and advise the TCD and follow the progress of recommended actions as indicated in annual work plans. 360. The ASDP II National Coordination and Management Unit (NCU) will be directed by the National Programme Coordinator and will include independent appointed officials from the labour market and ASLMs/government institutions and will have executive and semi-autonomous powers to manage, monitor and call for meetings of other organs of the ASDP II structures and to direct implementation functions. The team will be a fulltime job, reporting to PS MoA for management and administrative issues and to TDC for program implementation. It will be exclusively engaged in the ASDP II processes for the duration of the programme. 361. The Agricultural Sector Consultative Group Meeting (ASCG Meeting) is not part of the ASDP II hierarchy, but an important stakeholder consultative meeting. It will provide a forum for dialogue between the government (ASLMs), active development partners and non-state actors in the agriculture sector and will coordinate regular dialogue on sector policies and budget, and on the annual agriculture sector/public expenditure review (ASR/PER). It will inform policy and review budgetary issues, facilitating sector dialogue on JAST and GBS. Table 55: Summary of ASDP II Sector at PO-RALG, Regional Secretariat, Local Government Authorities Coordination Organs, Membership and Frequency of Meetings Institution Chair Members Frequency of Meeting Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). Minister PO-RALG RC, RAS, DED, DAICOs, Private Sector, Development Partners, NGOs/CBOs and other stakeholders in respective Regions and LGAs. Annually. Agricultural Sector Consultative Group Meeting (ASCG) Permanent Secretary-PO- RALG Directors (DPPs) of Agricultural Lead Ministries Semi- Annual Technical Committee of Component Leaders(TCCL-PO- RALG) Director of Sector Coordination- PO-RALG Component Leaders of PO- RALG Plus other Directors at PO-RALG Quarterly Regional Consultative Committee (RCC) Regional Commissioner(RC) Regional Administrative Secretary (RAS), Administrative and Assistant Administrative Secretaries, Head of Units (As per Act) Quarterly District Consultative Committee District Commissioner (DC) District Executive, Head of Departments (As per Act) Quarterly Full Council Council Chairperson Members of Council, Management Team (CMT), DED (As per Act) Quarterly 140 Agricultural Sector Development Programme II (ASDP-II) Institution Chair Members Frequency of Meeting Ward Development Council Councillor Members of WDC Quarterly Village Council Meeting Village Chairperson Members of Council Meeting Monthly Village Assembly Village Chairperson All villagers above 18 years with sound mind Quarterly E. Management Information System and monitoring 362. M&E is a vital component for the effective management of a programme. It must be clearly defined and structured at the onset of the programme to inform all sector stakeholders on the expectations for performance indicators. ASDP II will utilize available advanced technology (ICT) to increase the delivery and analysis of information from the field. This will involve the use of tablets, smartphones and computers to increase the capabilities of officers at field, district and regional level for computer literacy and quality data management. 363. Design of the M&E instrument demands a professional approach if it is to effectively serve its purpose. Attention to accuracy by correspondents will be enhanced when they receive feedback from analysis, which also helps increase their awareness of their own performance and to maintain interest in their development. Exchange of views resulting from discussion over data and data analysis also helps enhance coordination and improve transparency of management systems, expectations and performance. 364. With these conditions in mind, NCU will apply an M&E framework and instrument template very early in the programme so as to be effective and efficient at guiding the programme. The framework must describe the pathway for information flow, the responsible parties in its execution, the timeframe, the analysis method in relation to the objectives of the process and the mechanism for response to the conditions that it reveals. Collaboration with the professionals in Natational Bureau of Statistics (NBS) will provide synergies and efficiencies in collection and analysis of data. 365. An M&E specialist will be recruited to work part of the NCU. The specialist will manage the process and ensure its relevance and effectiveness: quarterly reports will conform to a template to specify the information required. Responses should be formalized, brief, numerical and, as far as possible, simplified to yes/no answers. Narrative, if needed, should be structured, unambiguous and confined to brief explanation. Data provided must inform the NCU and all components of the ASDP II institutional hierarchy of the progress toward national goals as expressed in the ASDP II objectives, as well as progress of componennts, sub-components and priority investments areas and projects, the efficiency of implementation and the impact on production, food security, resilience, capacity or capability depending on the objective of the projects. The overall measure and impact assessment will be through the results framework (RF). 366. The purpose of data collection must be clear to those demanding it and to those providing it so as to improve the usefulness of the exercise and to inform the need for response. Conclusions from analysis must inform NBS, PO-RALG, ASLMs, RSs, districts, wards and villages. As part of the annual budgetary process, it should improve performance of programme implementation, stimulate interest and engender a concept of national connectivity and common purpose. 367. Under the terms of the memoranda of understanding, information on activities and their achievements will also be collected from NGO projects or off-budget development partner projects to cover sector- wide performance and indicators of progress towards national objectives. Data collected at village level will be delivered in hard copy (paper forms) until advances in access and use of ICT solutions allow for electronic collection and transmission. Village data will be delivered to wards and from wards to districts. 141 Agricultural Sector for Industrial Development 368. At district level, the results will be collated, consolidated and digitalized into a standardized format for electronic transmission to the RS. The RS will ‘clean’ the data by checking consistency and consolidate the information into standard format to form a local level consolidated report for transmission to PO- RALG, with a copy to NCU where further consolidation and analysis will contribute to national quarterly and annual reports. 369. Choice of indicators must be carefully considered and limited to useful information by key decision makers to avoid overburdening the generators of the information and creating superfluous and irrelevant data. Relevant results framework indicators should inform the progress towards project/programme objectives and accommodate information on efficiency, effectiveness, relevance and impact so as also to be interpreted in terms of cost/benefit ratio. Data should also inform the programme about compliance with cross-cutting considerations and targets including gender and environment. F. Safeguard Aspects—Social and Environmental management 370. Since “development” without considering environment or social advancement can be retrogressive in the long run it is important that thorough consideration of factors affecting them is entrenched in the process of project selection. 371. Environmental consideration may include a wide range of impacts including erosion, deforestation, air pollution, water-source contamination, flooding, soil degradation, noise, visual landscape deterioration, traffic congestion, health hazard from agrochemicals or accidents, rodent or pest infestation including malaria, schistosomiasis, trypanosomiasis etc. Social safeguards include gender equality, working conditions, family disruption, labour and child labour exploitation, disruption of schooling, personal security, nutrition, stress, exposure to accident and health hazard, civil strife due to wealth discrepancy, migration etc. 372. The safeguards are incorporated in a two-step process. First, by enumerating the criteria for selection of projects on the basis of environmental and social consideration. Second, for projects that may entail a risk, by undergoing Environmental and Social Impact Assessment (ESIA) by professional specialists in those fields before commitment to implementation. 373. Impact assessment specialists can be registered and dispatched to undertake the assessments as required under contract or, if there is sufficient demand, under long-term employment with the NCU. The cost of ESIAs, where it is necessary, must be included in the implementation cost of the project. 374. Regulatory Framework. The principal national environmental law in Tanzania is the Environmental Management Act 2004, which stipulates the need to carry out an environmental impact assessment study before commencement or financing a project. The most relevant regulations, which will be used to guide environmental and social management under ASDP II, are the Environmental Impact Assessment (EIA) and Audit Regulations of 2005. The regulations provide for the requirement and procedures for undertaking, reviewing, approval and auditing of EIA for different types of projects and their respective level of assessment required. The overall responsibility of overseeing environmental and social management at national level lies with the National Environment Management Council (NEMC) under the Vice President’s Office. The ministry has a full-fledged Environmental Management Unit, which coordinates and oversees the implementation of environmental and social management issues within the agriculture sector, including ASDP. At LGA level, environmental and social management will be coordinated by the District Environmental Management Officer (DEMO). 375. In accordance with Environmental and Social Impact Assessment (ESMF, RPF) and Audit Regulations, investments in the agriculture sector fall under Type A Projects, which are likely to have significant adverse environmental impacts. Therefore, EIA are mandatory for agricultural projects and include in-depth studies to determine the scale, extent and significance of expected impacts and the identification of appropriate mitigation measures. The ASDP II support to production intensification and commercialization for selected commodities in different AEZs is likely to generate both positive 142 Agricultural Sector Development Programme II (ASDP-II) and negative impacts, including by: (i) higher adoption of improved technologies and use of inputs; (ii) irrigation infrastructure development; and (iii) improved market efficiency by aggregating outputs (such as warehousing) and value addition to enhance income growth. 376. The positive socio-economic impacts envisaged from the ASDP II programme include: (i) increase in agriculture productivity and incomes to rural communities in selected districts in terms of creation of more and better entrepreneurship opportunities; (ii) reduced household vulnerability; and (iii) improved living standards and increased rural employment opportunities. These will lead to improved food security and nutritional status for participating districts, and improved livelihood conditions, including improved access to socio-economic services. The programme will further enhance the capacity to mainstream environmental and socio-economic issues into development activities and improve stakeholders’ environmental and social awareness in selected districts. 377. Potential negative impacts are likely to be associated with the implementation of commodity value chain (CVC) activities and irrigation infrastructure development and value addition sub-projects. Potential impacts may include: (i) point and non-point pollution of water sources, due to spillage of agrochemicals or waste water from processing facilities; (ii) soil erosion and increased loss of soil fertility and other issues from inappropriate use of agricultural inputs; (iii) noise and air pollution; (iv) spread of diseases (such as HIV/AIDS), especially during construction phase of sub-projects; and (v) land use conflicts, among others. Irrigation infrastructure rehabilitation and expansion appears most critical as it could lead to degradation of river catchments and riparian ecosystems/biodiversity, soil salinization, loss of forests and other vegetation diversity, reduction of environmental flows, degradation of ecologically sensitive areas in the wetlands, increased water borne diseases, and water contamination due to non-appropriate use of agrochemicals. Furthermore, infringement on property and access rights, population influx seeking employment or other livelihood opportunities, increased conflicts over water use within schemes and between upstream and downstream users also need to be considered. Strategic Environmental and Social Assessment (SESA) for the National Irrigation Master Plan (NIMP) and National Irrigation Policy of 2011 provides details of potential impacts and proposed mitigation measures for irrigation activities in the country. 378. Capacity for Environmental and Social Management. Over the years, capacity improvement to manage environmental and social issues has been done through implementation and training under several Bank-funded operations in the agriculture sector, such as ASDP-1, PADEP and AFSP. Nevertheless, institutional and technical capacity for environmental and social management at the district and lower levels of LGAs still need improvement. This deficiency will be addressed in detail during programme implementation at district level. 379. Under ASDP-1, a SESA was prepared. The SESA covers the country’s national irrigation policy and national irrigation master plan, and it provides specific guidance for investments in irrigation. The SESA identifies potentially adverse environmental and social impacts emanating from the implementation of the national irrigation policy/national irrigation master plan and identifies strategic guidance on how to minimize and mitigate those impacts when implementing irrigation development projects/programmes in the sector. An environmental and social audit for ASDP-1, which is underway, will provide more insight and lessons on the capacity in the key implementing institutions with regard to environmental and social management. VII. BENEFITS AND ECONOMIC AND FINANCIAL ANALYSIS (EFA) A. Summary of benefits 380. In line with the importance of the sector, agricultural transformation and accelerated rural development will make a major contribution to Tanzania’s national development aspirations. The principal benefits 143 Agricultural Sector for Industrial Development of the programme will be: (i) increased and sustainable productivity and production of food and non- food agricultural commodities to improve rural incomes, boost rural households and national level food security, and provide raw materials for the agro-industrial sector; (ii) reduction in the prevalence of under-nutrition and malnutrition in rural communities and protection from the impact of natural disasters; (iii) accelerated commercialization of the rural sector generating increased cash incomes from farm and non-farm enterprises, especially by smallholders (comprising about 97.5% of rural households); (iv) protection and enhancement of the long-term productive capacity of Tanzania’s natural resource base through more sustainable land and water management practices and measures to adapt to climate change; and (v) improved institutional capacity to mobilize and manage resources in support of agriculture sector development. Not surprisingly, considering the size of the planned investment over a 5-year timeframe, and the scope of activities to be funded, the range of benefits will be extensive138. All of the above will contribute to Tanzania’s higher level national development goals as expressed in Vision 2025. 381. Several other benefits are also expected to accrue as the sector develops including: (i) reduction in harvest and post-harvest losses; (ii) increased export earnings; (iii) diversification of production into higher value agricultural products; (iv) improved access to financial services by smallholder farmers and rural entrepreneurs; (v) reduced transaction costs and improved efficiency in pre- and post-farm gate value chains; (vi) increased participation in cooperatives and other forms of FO; (vii) improved access to markets through infrastructure development; (viii) increased rural employment; (ix) higher productivity and reduced vulnerability to droughts from expansion of irrigated agriculture; (x) maintenance of agricultural biodiversity; and (xi) improving the system of disaster risk management by exploring the use of innovative risk management tools. The agricultural transformation will also ensure (xii) reduced gender related imbalances; (xiii) reduced child labour in agricultural sector by promoting decent work in accordance with ILO guidelines139; and reduce contribution of agriculture to climate change through promotion of CSA140Functional networks between production and markets. ASDP-1 emphasized generation and transfer and adoption of production technologies. Developing commercial skills and strengthening networks, linking farmers to markets were still limited. Therefore, the formulation of ASDP II has focused on developing a network of functional and market-driven value chains, involving key stakeholders (farmers, marketers and agroprocessors) who are aware of their mutual linkages, as well as complementary investments, make a deliberate effort to improve them, and organize themselves in such a way that they can benefit from participation in the CVC. The ASDP II intervention is aimed at reducing isolation and encouraging and strengthening collective action and networking among value chain participants to enhance willingness to invest in new technology, infrastructure, production and processing for higher income. 382. Economy of scale. Economy of scale in production is a limiting factor. Smallholder’s production and productivity relative to market opportunities in and outside the country is small. Scale of production is so small that buyers for large markets are not usually keen to form partnerships. Therefore, the emphasis given to strengthening cooperatives and FOs and to promoting production under the programme is to enable product aggregation and to increase productivity to reach a scale that would make economic sense to participate in a value chain. 383. Improved competitiveness. Interventions aimed at overcoming market failure and improving productivity, markets and competitiveness will provide substantial benefit to all the participants in the value chain. Broadly, the following critical factors that affect competitiveness will be addressed through the programme: technology constraints in production and post-production systems and poor infrastructure are addressed by Component 2; access to markets is addressed by Component 3; grants and information about credit; and paucity of effective FOs, producer associations, trade associations, 138 The results framework in Annex II shows the linkages between various interventions and their strategic outcomes. 139 Conclusions of the “International Workers’ Symposium on Decent Work in Agriculture” Geneva, 15-18 September 2003 140 (Lipper et al. 2014) 144 Agricultural Sector Development Programme II (ASDP-II) and coordination mechanisms among stakeholders are addressed by Component 4. Moreover, the programme interventions will yield direct benefits such as: (i) increased operating efficiency at farm level through improvements to production and marketing process, logistics, and market institutions; (ii) extended value addition at farm and/or post-farm level with greater integration between producers, traders and processors along the value chains; and (iii) increased market access. In addition, the project Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector’ will provide further indirect benefits in the form of: (i) stronger FOs that are able to actively and profitably engage with the market; (ii) more market-oriented and active agribusinesses with stronger links to producers; and (iii) more structured planning for value chain improvements at district, region and national levels. 384. Impact oriented implementation mechanism. The programme’s implementation mechanism, based on priority value chains which focuses on AEZs, together with a demand driven investment programme support is likely to result in substantial benefits. The program will target in high potential Commodity Value Chains (CVCs) in Agro ecological zones (AEZ); Through this model, the program will implement investments and commodities that create the greatest impact- Agricultural yields, profitability, farmer’s profitability growth, commercialization and industrialization potential 385. A pluralistic delivery system where private, public, and NGO service providers will participate in organizing the value chain participants, strengthening linkages and providing technical and business advisory services will have a sustainable positive impact. The construction of rural market infrastructure will be demand-based and financed jointly with the beneficiaries, leveraging substantial resource mobilization, including from the private sector. 386. Countering the impact of drought and climate change. The programme has a major irrigation development projects under Component 1. This is to counter the danger the agriculture sector and the Tanzanian economy at large face due to the unreliability of rainfed agriculture, which is the dominant mode of agriculture. Agriculture is affected by frequent drought, which leads to famine and has a significant negative impact on the country’s GDP. Climate change is also expected to decrease precipitation and increase its variability in arid and semi-arid regions of Tanzania. Further to irrigation development, the priority interventions are also promoting Promote Climate Smart Agriculture (CSA) technologies and practices. The programme ensures integrated soil and water management, conservation agriculture and agroforestry to overcome these challenges and sustainably improve the sectors productivity and resilience under rainfed conditions. 387. Benefits will also arise from several of the cross-cutting thematic areas of the ASDP II including: (i) improved institutional capacity and human resources at all levels; (ii) more balanced participation of women and men (old and young) in development and income-generating activities and both household and community level decision-making processes; (iii) recognition of the special needs of rural households affected by HIV/AIDS and/or poor nutrition and efforts to improve household nutrition and curb the spread of the disease; and (iv) improving the adaptability of the agricultural sector to climate change and reducing Tanzania’s contribution to global greenhouse gas emissions. A positive economic impact will be assured by requiring all proposed investments to be subject to thorough technical and financial feasibility studies to ensure that those likely to generate robust financial and economic returns are given high priority, and all proposed investments meet a minimum (hurdle) rate of return. B. Economic and Financial Analysis Introduction 388. An economic and financial analysis was undertaken to assess the viability of the investments proposed for ASDP II. The main economic benefits of these interventions are expected to be: (i) increased crop production through improved crop yields, higher cropping intensity, and diversification to higher 145 Agricultural Sector for Industrial Development value crops; (ii) enhanced livestock and fish production; (iii) higher farm incomes from agricultural production; (iv) increased income from agribusinesses and greater value addition; and (v) higher export earnings. 389. It is estimated that farmers on 2,000,000 hectares of non-irrigated land will benefit from improved agricultural support services, development of farmer organizations, and better access to markets and rural finance. Furthermore, investments in land and watershed management will help to ensure that increases in crop production are sustained in areas which are vulnerable to soil erosion and declining soil fertility. In addition, it is estimated that the improved irrigation infrastructure will benefit an irrigable area of 165,000 hectares, comprising 65,000 hectares of new and expanded irrigation schemes and 100,000 hectares of existing irrigation schemes which will be rehabilitated under ASDP II. 390. For irrigated land, cropping intensity is expected to rise to 135% while for non-irrigated land it is assumed to increase to 100%. It is also anticipated that the average yields of paddy rice would rise from 1.75 to 3.0 tons/ha. The corresponding increases for other crops are: 1.35 to 2.20 tons/ha (maize), 1.0 to 1.4 tons/ha (oilseeds/pulses) and 15.0 to 25.0 tons/ha (vegetables). 391. The development of water resources for livestock as well as the provision of support services are expected to result in an increase in livestock productivity and farm incomes. Increases in livestock productivity will primarily arise from the adoption of improved pasture management, enhanced nutrition and better animal health. The proposed fisheries interventions are primarily aimed at increasing aquaculture production through the expansion of fish ponds as well as improved support services. 392. ASDP II also includes measures to expand farmers’ access to rural markets, improve marketing systems and provide support to agribusinesses. These interventions are likely to provide significant economic benefits, such as enhancing CVCs, increasing value addition, and improving the income and employment opportunities of agribusinesses. However, the economic benefits of these interventions have not been quantified in the economic and financial analyses. Financial Analysis Crop Budgets 393. A financial analysis was undertaken to assess the likely impact of ASDP II interventions on farm incomes. Four budgets were prepared to represent the main crops grown in Tanzania, namely maize, rice, oilseeds/pulses and vegetables. Crop budgets were prepared for the present, future without project, and future with project situations. 394. The financial crop gross margins are summarized in Table 56 and it is evident that, in the future with project situation, there is a significant improvement in the net returns for all types of crop. This reflects the notably higher yield levels which generate incremental returns in excess of the additional production costs. It is also apparent that net returns from vegetables are substantially higher than returns from other crops. However, the high returns from horticultural crops are moderated by the risks associated with very large seasonal price fluctuations. Table 56: Financial Crop Gross Margins in Present, Future Without and Future with Project Gross margins (TSh per hectare) Present Future Without Project Future with Project Maize 67,088 119,831 216,550 Rice 322,500 423,844 709,375 Oilseeds/pulses 512,625 613,250 807,500 Vegetables 2,267,000 2,583,875 2,927,250 Source: Crop budget estimates 146 Agricultural Sector Development Programme II (ASDP-II) 395. It is envisaged that the future with project yield levels would be fully achieved within five years of completing the strengthening of agricultural support services, implementation of improved land and watershed management, as well as the construction of irrigation infrastructure envisaged under the programme. 396. In the financial analysis, budgets were also prepared for two livestock enterprises, namely dairy production and beef fattening (Table 57). In the future with project situation, the improvements in net returns primarily reflect the higher levels of productivity. Table 57: Financial Livestock Gross Margins in Present, Future-without and Future-with project Livestock Enterprise Financial gross margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 176,975 311,975 Beef Fattening 77,900 102,900 Source: Livestock budget estimates Cropping Patterns 397. In the existing irrigated area, it is anticipated that the areas of rice, oilseeds/pulses and vegetables will increase in both the wet and dry seasons. In the proposed irrigated area, there will be a significant change in cropping pattern with a major expansion in the area of rice in the wet season and the introduction of maize, rice, oilseeds/pulses and vegetables in the dry season. Cropping intensity is expected to increase from 125% to 135% while, on the proposed irrigated area, cropping intensity will rise from to 90% to 135%. For non-irrigated areas, cropping intensity in the future with project situation is estimated at 100%. Overall, cropping intensity in the ASDP II area is expected to increase from 92% to 103%. Farm Budget Analysis 398. Farm budgets were prepared for an average sized farm of 2.0 ha and a summary of the net farm incomes for the different ASDP II areas is given in Table 58. Comparing the present and future with project situations, net farm income in the existing irrigated area is expected to increase from TSh 900,568 to TSh 2,665,228 (before irrigation O&M costs) while, in the non-irrigated areas, net farm income is estimated to rise from TSh 367,385 to TSh 1,158,275. Overall net farm income is expected to increase from TSh 436,699 to TSh 1,655,569 per annum. 399. When irrigation O&M costs are included, net farm income in the irrigated areas falls to TSh 2,229,994 per annum in the irrigated areas. However, as irrigation costs only account for about 16% of net farm income, farmers will have the ability to meet annual O&M costs. Table 58: Net Farm Incomes in Present, Future-without and Future-with project Irrigation Status Net Farm Income (TSh per annum) Present Future Without Project Future with Project Excluding Irrigation O&M Costs Including Irrigation O&M Costs Rehabilitated irrigated area 900,568 1,138,498 2,665,228 2,229,994 New irrigated area 367,385 496,902 2,665,228 2,229,994 Non-irrigated area 367,385 496,902 1,158,275 Overall 436,699 580,309 1,655,569 Source: Farm budget estimates 147 Agricultural Sector for Industrial Development Economic Analysis Economic Pricing 400. Economic prices for internationally traded goods were derived from the World Bank commodity price projections for 2015. Local transport, handling, storage and processing costs were based on the current rates prevailing in Tanzania. However, these financial prices were converted to economic prices by applying the Standard Conversion Factor (SCF) of 0.95. Labour costs were based on rural wage rates. However, given the high levels of underemployment, a shadow wage rate of 0.65 was used to determine the economic value of labour. 401. The economic analysis was undertaken over a 50-year period in 2015 constant prices and a shadow discount rate of 12% was assumed. The Tanzania shilling was used as the unit of account and an exchange rate of TSh 2,150 to USD 1.0 (June 2015) was applied when converting to USD. It was anticipated that the programme would be implemented over a 10-year period. C. Economic Benefits 402. In the estimation of agricultural benefits, economic crop gross margins per hectare were calculated by valuing the physical input and output quantities in terms of their respective economic prices. The economic gross margins per hectare were then multiplied by the respective crop areas to estimate net crop benefits in the present, future with and future without project situations. Net livestock benefits were also estimated for the three project situations (based on the respective livestock populations and economic gross margins). 403. As a result of these increases in crop and livestock production, net agricultural benefits to farmers within the project area were estimated to rise by TSh 626,572 million per annum (from TSh 245,152 million to TSh 859,700 million per annum at full development). It is envisaged that the future with project agricultural benefits would be fully attained within two years of programme completion. Benefits from crop production are estimate to account for 81% of the overall agricultural benefits. D. Operation and maintenace costs 404. The long-term annual operation and maintenance costs of the irrigation infrastructure were also included in the economic analysis. These financial costs were then converted to economic values, and the annual economic O&M costs. In addition, the annual costs of support services were included in the analysis to ensure that agricultural production continues to grow after completion of ASDP II. E. Economic Viability and Sensitivity Analysis 405. The results of the economic analysis indicate that the IRR of ASDP II is 14.8%. These results show that the proposed project investment is justified on economic grounds. Sensitivity analysis was also undertaken to test the economic viability of the proposed interventions to various changes in the cost and benefit streams. This analysis indicated that ASDP II is fairly sensitive to changes in benefits and costs and becomes uneconomic with an increase in capital and recurrent costs of 21%. Similarly, an 18% decrease in incremental project benefits would result in the EIRR falling below 12%. 406. The results of the sensitivity analysis are given in Table 59 which shows that a decrease in capital and recurrent costs of 20% resulted in an EIRR of 18.8%, while a cost increase of 20% lowered the EIRR to 12.1%. Similarly, an increase in incremental benefits of 20% produced an EIRR of 18.0% and a benefit decrease of 20% reduced the EIRR to 11.6%. In addition, changes in the expected cropping intensity were also assessed and the analysis indicated that if a future with project cropping intensity of 100% is assumed (in comparison to 103% in the base case), the EIRR falls to 10.7%, while a cropping intensity of only 95% will further reduce the EIRR to 7.7%. 407. With regard to crop productivity, the analysis indicated that if yields of maize and rice only increased by 148 Agricultural Sector Development Programme II (ASDP-II) 50% (in comparison to 57% and 67% in the base case), the EIRR falls to 10.7% and ASDP II becomes uneconomic. It should therefore be emphasized that the adoption of improved cropping practices and expected increases in crop yields (to maintain economic viability) will only be achieved if adequate agricultural support services, including extension/training and input supply as well improved access to markets and rural finance, are made available to farmers in an effective and efficient manner. Table 59: Economic viability and sensitivity analysis Scenario EIRR (%) NPV (TSh million) Base Case 14.8% 370,009 Capital and Recurrent Costs -20% 18.8% 722,428 Capital and Recurrent Costs +20% 12.1% 17,589 Incremental Benefits +20% 18.0% 796,430 Incremental Benefits -20% 11.6% -56,413 Costs -20% and Incr. Agric Benefits +20% 22.6% 1,148,850 Costs + 20% and Inc. Agric Benefits -20% 9.3% -408,832 100% Cropping Intensity with Project 14.3% 299,966 95% Cropping Intensity with Project 11.8% -21,536 50% Increase in Crop Yields 10.7% -531,096 40% Increase in Crop Yields 7.7% -165,650 F. Programme Sustainability 408. Long-term sustainability of the programme will be determined by the extent to which it delivers results, i.e., improving agricultural and agribusiness service delivery for sustainable productivity growth and subsequent gains in farm production, income and resilience, especially in rainfed production systems for crops and livestock. Improving the responsiveness of key services to respond to farmers’ demand, together with supporting agribusiness investments, key infrastructure, professional services and adapted policy environment should improve the overall impact. In the medium term, smallholder farmer empowerment and the consolidation of their organizations will allow for strengthened voice and building-up of capacities for technical and economic service provision to their members. 409. ASDP II aims to achieve a sustainable increase in agricultural productivity and commercialization by most smallholders (at least 20%). This will be achieved through scaling up of technologies which are appropriate, affordable and profitable to smallholder farmers, and can be sustained without ongoing support in the long run. ASDP II will utilize the principles of sustainable agricultural intensification by enabling farmers to develop intensive diversified farming systems, and at the same time create an enabling environment for rural commercial development in which farmers can access commercial input and output markets, towards improved productivity and profitability of market-oriented farming. 410. ASDP II addresses the social dimension of sustainability through ensuring that household food and nutrition needs are satisfied and that rural people are protected from the impacts of natural disasters and acute food shortages, which can deplete household assets and reverse hard-won gains. Particularly, the programme addresses the high prevalence of under-nutrition and malnutrition, which limit productivity and threaten the sustainability of human development in rural households and communities. For Tanzania to achieve its development aspirations there is need to have a substantial upswing in the rate of investments in agriculture and food security. ASDP aims at providing additional resources for enhancing outcomes across all programme areas to achieve the programme development objective. 411. In summary, ASDP II sets out a clear roadmap for ongoing developments towards increased competitiveness and profitability of the sector and confirms government and donor responsibilities in meeting the challenges of transforming the agricultural sector within a coordinated approach. 149 Agricultural Sector for Industrial Development VIII. IMPLEMENTATION MODALITIES AND RISKS A. Implementing agency and stakeholder assessment 412. The implementation of ASDP II will follow the government structures/systems for procurement, financial management and environmental and social safeguards. The proposed programme will require enhanced reporting on results and impact: The M&E system will include and be aligned with the program results tracking system. Furthermore, the coordination of sector support under the ASDP II need to be aligned with the overall ASDP II framework at national and local levels for efficient implementation and effective delivery of results. 413. Building on ASDP-1. ASDP-II is building on experiences, achievements, capacities and systems developed during ASDP-1, in alignment with the government’s priority investments for achieving quick results. While the focus, approach and scope of the proposed ASDP II programme will significantly differ from ASDP-1, the delivery systems and structures will to a large extent remain the same, to be strengthened to enhance their capacity to deliver envisaged programme results. The design of the programme has integrated support for institutional strengthening of implementing agencies and capacity building activities for farmers and other key technical areas, including results monitoring and coordination. 414. Programme Stakeholder Assessment. Programme implementation will involve a range of sector stakeholders, partners and beneficiaries at different levels. This includes government institutions (national, regional and local levels), the private sector, namely input and output traders, PSPs, agro- industries/processors, FOs, NGO, financial institutions and others. The capacity of stakeholders varies across the implementation levels: the participation of the private sector in agriculture remains still weak and stakeholder coordination at local levels is inadequate. The sector-wide coordination framework currently under preparation will improve coordination among various players supporting the agricultural sector. There are also efforts to establish CVC platforms, especially at district (cluster) level, to enhance stakeholder coordination. 415. The institutional and human capacity developed during the first phase of ASDP will be utilized for implementation of the proposed operation. The ASLMs will be strengthened to improve its analytical skills and results orientation within strengthened programme management and coordination capacities. Fiduciary, M&E and other critical technical competencies, such as CVC analysis, need to be further strengthened for support effectiveness and sustainability. ASDP II will require much enhanced emphasis on real-time reporting on results and impact. The coordination of sector support under the Programme at the national and local levels needs to be clarified and made more efficient in order to enhance delivery. 416. Development Partners. Most of the development partners have expressed interest in supporting the government’s efforts towards agricultural development through a sector-wide approach such as ASDP II over the 2015/2016–2024/2025 period. However, some of these contributions are already earmarked or designed as stand-alone projects, such as contributions by JICA (mainly irrigation infrastructure and development), IFAD (Bagamoyo smallholder sugar project141) and IDA and Bill and Melinda Gates Foundation (BMGF). Therefore, non-earmarked basket funding is expected to originate from development partners and from the Government of Tanzania budget. A memorandum of understanding stipulating principles for managing the Basket Fund will be signed by all Basket Fund development partners, including the coordination and harmonization mechanisms for earmarked and non-earmarked funds. A framework for coordinating and harmonizing the Basket Fund with non- basket (off- and on-budget)142 funded projects/programmes and initiatives in the sector, including mutual contributions to the sector coordination and the common M&E. 141 The ongoing preparation of a loan to support an out-grower sugarcane scheme in Bagamoyo is an attempt by IFAD to engage in a public–private sector partnership in Tanzania, based on experiences from palm oil in Uganda and sugarcane in Swaziland. 142 Most bilateral donors and NGOs will provide off-budget funding, such as among others USAID through a direct agreement with the Roads Fund to develop the rural road infrastructure in key SAGCOT districts. 150 Agricultural Sector Development Programme II (ASDP-II) B. Risks 417. The key risks associated with the programme are: (i) The sector policy and economic environment has not been conducive for agribusiness partnerships. This situation may lead to poor participation of agribusiness partners in programme activities, especially their envisaged role in value chain development with smallholder farmers’ commercialization. To mitigate this risk, the programme has proposed introducing competitive matching grants for agribusiness to provide opportunities for district CVC stakeholders’ platforms and agribusinesses to participate in programme activities. These matching grants will be used to catalyse financing of agribusiness investments identified by FOs in partnership with agribusiness. The district CVC platforms will serve as incubators for partnerships at local level. While the performance of district CVC platforms is essential to engendering programme success, the CVC platform functions are inherently difficult to measure and monitor and incentivize. Furthermore, the policy environment needs also to change, especially in relation to export and local taxes on agriculture products, ad hoc interventions such as tariff waivers and export bans, etc., for improved sustainability. Inadequate policy incentives for participation of private agribusiness partners in programme activities, especially their envisaged role in value chain development will undermine achievement of programme objectives of commercialization. The ongoing dialogue on improving environment for private sector investment continues, and the government is committed to enhancing private investment in agriculture through initiatives like Kilimo Kwanza and SACGOT. (ii) The programme will be implemented under a complex institutional structure, multi-sectoral, multi-donor Basket Fund environment, in parallel with several stand-alone projects (on- and off-budget). This may lead to conflicting agenda and interests, and weaken local capacity to manage and coordinate programme activities. To mitigate this risk: (a) the programme activities have been aligned with a joint governments overall ASDP II programme/framework; (b) the sector-wide coordination framework, with supporting mechanisms at various levels, will enhance coordination and harmonization of projects and programmes in the sector; (c) the programme will support LGAs (under Component 4) to develop a comprehensive sector coordination framework that integrate activities of all projects in the sector at local level through DADPs; (d) a memorandum of understanding will be signed by all ASDP basket donors and the government to agree on principles for operating and managing support to the overall ASDP II programme/framework; and (e) institutional arrangements and coordination mechanisms for implementing agencies used in ASDP-1 will be strengthened. (iii) The declining rate of budget execution, delayed and incomplete releases of development funds, including foreign funds may result in cash flow problems to programme beneficiaries and thus undermine achievement of programme objectives. To address this challenge, the government has changed its budget cycle, to start earlier (in April) to enhance timely flow of funds and improve budget execution. However, the financial calendars of donor agencies are not always compatible with this timing and the release of donor funding may not always be in harmony with the execution of the national budget. Dialogue under the PRSC series includes these issues. (iv) Results monitoring remains a challenge in the sector due to weak capacity for data collection analyses and management. To mitigate this risk, the proposed programme includes support for institutional strengthening and capacity building to improve the M&E system for tracking, analysing and disseminating results. The programme should also be aligned in a common government M&E system that emphasizes results management, transparency and accountability. (v) The agricultural risk management perspective could be formally included in the ASDP II since it has become clear that the realization of production and price risks are determinants of food insecurity and monetary losses for participants along major CVCs. Introducing a risk lens 151 Agricultural Sector for Industrial Development will contribute to the sustainability of the investments on productivity. Potential areas to be included for risk management need to be identified for each AEZ and production system. Crop diversification, small-scale irrigation development, conservation farming, integrated soil and water management, and climate smart agriculture have already been included under research and advisory services, and warehousing linked with a commodity exchange programme under commercialization/agribusiness activities. All these elements will contribute to resilience and sustainability of agricultural production systems. 152 Agricultural Sector Development Programme II (ASDP-II) ANNEXES ANNEX I: ASDP II Components Implementation Plan, Sequencing and Scheduling COMPONENT 4 PROJECTS SEQUENCING (Sector Enablers, Coordination and Monitoring and Evaluation) Component Objective: Strengthening Sector Enablers, Coordination and M&E Outcome: Strengthened institutions, enablers, coordination and M&E frameworks Component Key Performance Indicators (KPIs): ● Reviewed and harmonized Agricultural sector related policies, laws, regulations and institutional procedures ● Improvement in ranking in WB’s doing business and Enabling the Business in Agriculture (EBA) ● Increased sector productivity, value/prices, profitability and growth potential relying on improved knowledge management and efficient ICT use ● Integrated Sector Monitoring and Evaluation (M&E) system SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.1 Policy and Regulatory Framework i) Reviewed and harmonized agricultural sector related policies, laws, regulations and institutional procedures 4.1.1 Policy and Regulatory Framework and Business Environment Improvement 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment Enabler to other components, Policy environment is dynamic 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) Continuous project ii) Extent (%) of policy and regulation compliance (e.g., “compliance rates”) 4.1.1.3 Developing of Fisheries Master Plan in Tanzania Main Land It’s a roadmap to fisheries sub sector 4.1.1.4 Strengthening and control of child labour in Agriculture It is dependent on review and harmonization of relevant policies and regulations 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector It is dependent on review and harmonization of relevant policies and regulations 153 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.2 Stakeholder empowerment & organization Enhanced knowledge management and ICT systems 4.2.1 Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing Farmer Organizations and cooperatives Movement 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors’ associations in the agricultural sector Central for implementation of the program Steering committee and consultative meetings held and resolutions implemented at national and local levels. • Business efficiency in delivering services to clients by government (e.g. faster response to problems and solution provision) Timely, relevant, accurate and user friendly cost effective information is available to stakeholders when and where needed DADPs that meet assessment criteria 4.2.2 Promote and strengthen gender inclusiveness in the agricultural sector 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) It cuts across all the implementation components (1,2,3) 4.3 ASDP II_sector coordination (planning & implementation at national, regional and LGA) Agric. investment coordinated under ASDP II (on/off budget) 4.3.1 Improved and strengthen vertical coordination (from PO-ALG to RSs and LGAs) and horizontal coordination between ASLMs 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication Central for implementation of the program Execution of allocated budget Quality and timely submitted quarterly reports at all levels Coordination unit for planning & monitoring established and operational • Guidelines compliance rate at all levels 154 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 4.4 Monitoring and Evaluation (including Agricultural statistics) • AASS implemented 4.4.1 Improved Capacity and agricultural data collection and management systems 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. Central for monitoring of the program RS and LGAs to provide quality data through different M&E systems timely. 4.4.2 Develop Agricultural Sector M&E System 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. Central for monitoring of the program Joint M&E systems established and operational 4.5 Institutional capacity development, and knowledge management and ICT 4.5.1 Improvement of Capacity in all levels 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels Central for implementation of the program 4.5.2 Improvement of ICT for Agricultural Information Services and Systems 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. It’s the key enabler for coordination 4.6. Access to rural financing 4.6.1 Provide microfinance services 4.6.1.1 Access to agricultural financing for improved commodity value chain Enabler for Agricultural Investments 155 Agricultural Sector for Industrial Development COMPONENT 3 PROJECTS SEQUENCING (Commercialization and value addition) Component Objective: Improved and expanded rural marketing and promote value addition by thriving competitive private sector and effective farmer organizations Outcome: Strengthened and competitive commodity value chains Component Key Performance Indicators (KPIs): ● % Increase in volume and monetary value of exports ● % Increase in Monetary value of Foreign Direct Investment (FDI) and private capital flow to agricultural sector ● % Increase in job creation by new and expanded investment in agribusiness ● % Reduction in volume and monetary value of food import ● % Increase in profitability of produce and products at a farmer and enterprise level ● % Increase in market share of products at all market levels ● % Increase in products compliance to national and international standards ● % Increase in standardized marketing infrastructure along the value chain ● % Increase in participation of vulnerable groups (Women, Youth, and Pastoralist) in rural commercialization and value addition in decision making and benefiting from main programs along the value chain 156 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 3.1 Marketing % change in investment in market infrastructure 3.1.1 Develop market access for all priority commodities. 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets storage facilities are a major concern’ high post harvest losses; quality issues; supply volume % Farmer/FO/ Traders using improved market infrastructure in rural areas 3.1.2 Develop market access for fisheries and livestock products 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market storage facilities are a major concern’ high post harvest losses; quality issues; supply volume 3.1.2.2 Improving local and improved chicken market access Quick win project which impacts majority of the rural community) 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing ensures quality/ safety; facilitate market penetration 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain key driver in the sector 3.1.2.5 Improving beef, cabrito and mutton market access Depends on improvement of livestock infrastructure 157 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 3.2 Agribusiness development: value addition and agro-processing % increase of value added produce and products 3.2.1 Development of processing and value addition for Crop, livestock and fishery products 3.2.1.1 Strengthening and development of agro-processing industries for value addition for all priority commodities Low exports; industrialization agenda % Decrease in post- harvest loss 3.2.1.2 Improving milk value chain Lack of infrastructures 3.2.1.3 Strengthening hides and skin value chain Limited basic facilities; not operational 3.2.1.4 Strengthening value chain for horticultural commodities On going initiative; promising future for Tanzania 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange To Increase market access and reduce post harvest losses. 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products There is available market for carcass 3.2.1.7 Enhancing beef, chevron, mutton value addition Raw material readily available 3.2.1.8 Improving Postharvest Management Along Food Supply Chain For sustainable food security and nutrition 158 Agricultural Sector Development Programme II (ASDP-II) COMPONENT 2 PROJECTS SEQUENCING (Enhanced Agricultural Productivity and Profitability) Component Objective: Increased productivity growth rate for commercial market-oriented agriculture for priority commodities Outcome: Improved agricultural productivity and profitability Component Key Performance Indicator (KPIs): ● Increase of Yields (MT/ha, litres/cow/lactation, eggs/hen/day, live weight/cattle at market point, kg/fish) for priority value chains ● Increase of Gross margins (TSh/ha, TSh/dairy cow, TSh/LU, etc.) for priority value chains ● Increase in Profitability/net return (TSh/commodity or enterprise) of priority commodities ● Increased labour efficiency (TSh/farmer/season) and net financial return to farmers ● Percentage decrease in malnutrition (stunting and under weight) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.1 Extension training and information services 1. % of farmers adopted productivity enhancing technologies 2.1.1 Strengthening agricultural extension, training and promotion/ information services (crops, livestock and fisheries) 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) In order to commercialize/ disseminate research outputs to smallholder farmers e.g. through private sectors engagement 2. % farmers satisfied [2] with extension services 2.1.1.2 Strengthening agricultural competence- based training and promotion (all commodities) Focus on smallholder farmers 3. % of disseminated technologies adopted 4. % of Extension staff delivering quality extension services 5. % decrease of pest and diseases incidence (frequency and loss) of economic importance 6. % increase of average household incomes for farmers who adopted technologies 159 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.2 Access to Agricultural Inputs and health services 1. % of farmers using quality agricultural inputs 2.2.1 Improved Access to Crops, Livestock and Fisheries Inputs and health services 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) For increased Productivity and Profitability % of farmers benefiting from inputs subsidy 2.2.1.2 Improving access and availability of quality Poultry inputs Lack of inputs and expensive 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity In Order to commercialize Deep Sea Fishing through private sector participation 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability Ongoing 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability Feasibility study is going on 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity Needed to increase productivity for small scale fishers by employing Fish Aggregating Devices (FADs) 2.2.1.7 Strengthening Beach Management Units (BMUs) for sustainable management, protection and conservation of fisheries resources Ongoing 160 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.2.1.8 Improvement of plant health services Disease and pests outbreaks as potential risks in the three sub sectors could affect livelihood and productivity growth. Generating high quality technologies through research and use of good agricultural practices will reduce the scale of threat. 2.2.1.9 Production of vaccines and drugs High importation cost 2.2.1.10 Improvement of aquatic and livestock health services 2.3 Agricultural Research for Development (AR4D) 1. % of new technologies released and disseminated by research stations 2.3.1 Strengthening AR4D (crops, livestock and fisheries) 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub- sectors) AR4D is instrumental in generating productivity enhancing technologies and innovations by demand-driven technology generation approach and by improving research- extension-farmer linkages to drive commercialization and dissemination of technologies. 161 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2. Improved capacity [1] of research stations to generate high quality technologies 2.3.2 Research and development 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) Technology is dynamic for increased production 3. % of budget allocated and disbursed (recurrent and development) for Research and Development 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies Ongoing 2.4 Access to Mechanization Services 1. % of households accessing mechanization services for priority commodity value chains 2.4.1 Strengthening and promote agricultural mechanization (crops, livestock and fisheries) 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain Mechanization in the entire value chain 2. % of households accessing processing facilities for priority commodity value chain 3. % reduction of post- harvest losses of commodity value chains 162 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 2.5 Food and nutrition security 1. % increase of rural households above the food poverty line 2.5.1 Food and nutrition Security improved 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 2. Increase in ratio of national food self sufficiency 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption Increasing demand of nutrition food and industries 3. % reduction of malnutrition incidences (chronic and transitory) 4. % of decrease in macro and micro-nutrients deficiency in children and pregnant women 5. % of households accessing nutritious and diverse food 6. % of households practicing diversified farming systems for improved diets and reduced vulnerability to food shortages 7. % of households accessing livestock and fish protein. 163 Agricultural Sector for Industrial Development COMPONENT 1 PROJECTS SEQUENCING (Sustainable Water and Land Use Management) Component Objective: Improved and sustained Integrated Land and Water Resources Use and Management (Irrigation, Water for Livestock, Cropped Land, Pastures, Ponds/Cage, Soil Fertility Management) Outcome: Expanded Sustainable Water and Land use, and improved Management for Crops, Livestock and Fisheries Component Key Performance Indicators (KPIs): ● Percentage increase of schemes practicing sustainable irrigation ● Percentage increase of livestock keepers with access to permanent water sources (natural or man-made) ● Percentage of modernized irrigation facilities with professional management ● Improved rangelands (ha) with sustainable pasture and water for livestock ● Increased area (ha) under fish farming ● Increased number of maricultural farmers ● Percentage increase of stakeholders implementing CSA technologies SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.1 Land Use Planning and sustainable Water Shed and Soil Management Percentage increase of districts with land use plans 1.1.1 Land use planning and watershed management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones) Land use plans are the basis for the smoothly implementation of other projects Percentage increase of villages with land use plans 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity Reducing conflicts through availability of pasture Percentage increase of watersheds with integrated management plans 1.1.1.3 Enhancing access to agricultural land for youth empowerment Improvement of enabling environment Additional area (ha) under improved agricultural production 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (all products) To ensure availability of water for agricultural activities Percentage increase in water quantity for agricultural production 164 Agricultural Sector Development Programme II (ASDP-II) SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.2 Integrated Water Use and Management for Crops/ Irrigation and Livestock/ Fishery Development Additional area (ha) under improved irrigation 1.2.1 Irrigation infrastructure development 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity To cover ongoing projects and those remain under other initiatives Cropping intensity for irrigated crops 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity Increased demand of these technologies for water saving Additional permanent water points for livestock 1.2.2 Irrigation schemes management & operation 1.2.2.1 Strengthening Irrigation schemes management and operations To ensure sustainability of irrigation infrastructure Increased area (ha) under fish farming 1.2.3 Water sources development for livestock & fisheries 1.2.3.1 Development of water infrastructures for livestock productivity To ensure availability of water for livestock and reduce conflicts Increased number of mariculture farmers 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries Inclusiveness and on going projects 165 Agricultural Sector for Industrial Development SUB- COMPONENT KEY PERFORMANCE AREAS (KPIs) PRIORITIZED INVESTMENT AREAS PROPOSED PROJECTS Sequencing SEQUENCE JUSTIFICATION Year 1 Year 2 Year 3 Year 4 Year 5 1.3 Mainstreaming resilience for Climate Variability/ Change and Natural Disasters Percentage increase of farmers (crop, livestock and fisheries) adopting CSA technologies and practices 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies 1. Mainstreaming CSA and CA for soil fertility Management and 2. Early warning systems. Proportion of LGAs with mainstreamed CSA in their DADPs 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management Increasing fish habitat destruction Proportion of ASLMs with mainstreamed CSA in their plans 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness Percentage decrease of households who are under the risk of floods or drought General Points taken into consideration in Sequencing Projects: Land use planning is placed first because it the basis for investment, followed by rehabilitation of ongoing irrigation infrastructures and development of new irrigation schemes. The third area is promotion of climate smart and conservation technologies for the purpose of mainstreaming CSA and CA technologies at early stages of planning. Agricultural Sector Development Programme II (ASDP-II) 166 ANNEX II: ASDP II: Results Framework and Monitoring (On-progress) Note: This results framework currently mentions only a few key commodities as an example. The selection of CVC will be adjusted as needed once the framework develops. The Framework covers the first five years of the programme. The framework was assessed and it was realised there was a substantial data gap from which the targets could be developed. Program Development Objective (PDO) or Goal: Transform the agricultural sector (crops, livestock & fisheries) towards higher productivity, competitiveness, and commercialization and improve smallholder farmers’ incomes, livelihoods, and food and nutrition security. PDO Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 1 Growth Rate Agricultural Sector Sustain annual agricultural GDP growth of at least 6%, from the year 2016 to the year 2025. 2.1 Percentage change of GDP of the sector ((Current GDP-baseline GDP)/baseline GDP)*100 Annual ASLMs /NBS Crop 6% 1.4 Percentage change of GDP of Crop sub-sector (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Livestock 6% 2.6 Percentage change of GDP of Livestock (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Fisheries 6% 4.2 Percentage change of GDP of Fisheries (Current GDP-baseline GDP/baseline GDP)*100 Annually ASLMs/NBS Agricultural Sector Development Programme II (ASDP-II) 167 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 2 Productivity Maize Double (100% increase) the current agricultural yields levels, by the year 2025 from the year 2016. 1.72 Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Paddy 100% increase in MT/ha 3.06 Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Sunflower 100% increase in MT/ha Production per unit area Total production in tons divide by area in Ha Annually ARDS/AASS Milk 50% increase lt/cow/day 2.25 Production per animal per day (indigenous cattle) lt/cow/day Annually ARDS/AASS Beef 100% increase in Kg/animal 145 Production of carcass per animal Kg/animal Annually ARDS/AASS Goat 100% increase in Kg/animal 37 Production of carcass per animal Kg/animal Annually ARDS/AASS Mutton 100% increase in Kg/animal 40 Production of carcass per animal Kg/animal Annually ARDS/AASS Chicken 100% increase in Kg/bird 1.5 Production of carcass per bird Kg/bird Annually ARDS/AASS Marine fish Increase catch to 1,000,000 MT by 2025 362,000 Volume in MT of catch per year Catch per year Annually ASLMs- fisheries Agricultural Sector Development Programme II (ASDP-II) 168 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 3 Total annual production Maize Double (100% increase) maize production (MT) 6,100,000 Total production in MT Summation of production in the area Annually ARDS/AASS Paddy Double (100% increase) paddy production (MT) 3,400,000 Total production in MT Summation of production in the area Annually ARDS/AASS Milk (28% increase) milk production (litre) 2,087,000 Total production in litres per year (indigenous cattle) Summation of all litres of milk produced Annually ARDS/AASS Beef Double (100% increase) beef production (MT) 319,112 Total beef production in MT Summation of all beef produced in MT Annually ARDS/AASS Goat/sheep (50% increase) goat/sheep meat production (MT) 124,74 Total goat/sheep meat production in MT Summation of goat/sheep produced in MT Annually ARDS/AASS Chicken (50% increase) chicken meat production (MT) 104,292 Total chicken meat production in MT Summation of chicken produced in MT Annually ARDS/AASS 4 Percentage growth of agricultural exports (Value in USD) Maize Export the surplus to 100% by 2025 1,056,559 Harvest minus requirement (mainly for cereals) Annually TRA/ASLMs Rice Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Cotton Triple export by 2025 23.4 Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Horticulture (Round potato) Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Beef Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Marine fish Triple export by 2025 GAP Percentage change of export Current GDP-baseline GDP/ baseline GDP)*100 Annually TRA Agricultural Sector Development Programme II (ASDP-II) 169 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 5 Volume of imported Rice Gradual decline of rice imports to 50% by 2025 1,277,296 Amount of rice imported in tons Current import minus baseline import Annually TRA Maize Gradual decline of maize imports to 50% by 2025 GAP Amount of maize imported in tons Current import minus baseline import Annually TRA 6 Reduction rate of the gap between the wholesale price and farm-gate price Maize Contribute to poverty reduction by reducing the gap between the wholesale price and farm-gate price, by 50% by the year 2025, from the year 2016. GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Rice Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Milk Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI Beef Ratio decline by 50% GAP Difference between wholesale price and farm-gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual MITI 7 Percent of rural population below the poverty line National poverty line Reduce poverty level by at least 50%, at national poverty line, from the year 2016 to the year 2025. 28.2 Rate of rural population below national poverty line, (Poverty headcount ratio at national 2016-poverty headcount ratio at national 2025)/ poverty headcount ratio at national 2016 * 100 Bi-annual HBS-NBS Agricultural Sector Development Programme II (ASDP-II) 170 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 8 National food self sufficiency Cereal and cereal equivalent Maintain Self Sufficient Ratio (SSR) in the range between 100% to 120% or above 124 The ratio of gross domestic food production is compared with the domestic food requirement. Total food production minus total food requirement over total food requirement Annually ASLMs(food security) 9 Proportion of household with low dietary diversity Household Dietary Diversity Score (HDDS) Reduce by half the communities that doesn’t have access to a diverse range of nutritious food annually from 2016 to 2025 Rural: (21.4%) Urban: (8.6%) Households that doesn’t have access to a diverse range of nutrition food Households that doesn’t have access to nutritious food divide by the total number of households Annually MoH (TFNC)/ MoA 10 Malnutrition incidences (chronic and transitory) in Tanzania Stunting Bring down child stunting to 10%, by the year 2025. 34 Prevalence of stunting (% of children under 5 years old) Annually MOH(TFNC)/ ASLMs Underweight Bring down underweight to 5% or less, by the year 2025. 14 Prevalence of underweight (% of children under 5 years old) Annually MOH(TFNC)/ ASLMs Wasting Bring down wasting to 5% or less, by the year 2025. 5 Prevalence of wasting (% of children under 5 old) Annually MOH(TFNC)/ ASLMs 11 Proportion of the population that is undernourished Bring down undernourishment to 5% or less, by the year 2025. 5.5 Proportion of the population that is undernourished (% of the country’s population) Annually MOH(TFNC)/ ASLMs Agricultural Sector Development Programme II (ASDP-II) 171 COMPONENT ONE Sustainable Water and Land Use Management Component Objective: Improved and Sustained Integrated Management of Land and Water Resources Use (for example, for Irrigation, Water for Livestock, Cropped Land, Pastures, Ponds/Cages and Soil Fertility). Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Land use planning and watershed management 1 Proportion of villages surveyed. Ensure that 100% of villages land is surveyed by 2025. GAP Percentage of villages that have been made with Land use plan in place marking area for agriculture, livestock fisheries, settlement and reserved land e.g. watersheds Total number of village with land use plan/total number of villages registered Annually National Land Use Planning Commission -Ministry of Land 2 Proportion of farm households (by gender) with ownership or secure land rights, Customary Certificates of Rights of Occupancy (CCROs) Ensure that 100% of farmers and agribusiness interested in agriculture have rights to access the required land by 2025. GAP Number of CCROs issued to farmers who own land Total number of CCROs issued to farm households over total number of farm households Annually National Land Use Planning Commision -Ministry of Land Title deed Ensure that 100% of farmers and agribusiness interested in agriculture have rights to access the required land by 2025. GAP Number of title deed issued to farmers who own land Total number of title deed issued to farm households over total number of farm households Annually National Land Use Planning Commission -Ministry of Land Agricultural Sector Development Programme II (ASDP-II) 172 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Water use for Crops, Livestock and Fishery 4 Number of schemes practicing irrigation Rice 549 irrigation schemes (276 for rehabilitation and 273 new ) operated sustainably by 2025 GAP Total number of scheme practicing irrigation sustainably (registered irrigators organization collecting annual fee from members, has bank account & maintenance plan) Summation of all developed schemes Annually AASS/ARDS/MOWI/NIC 5 Number of irrigation infrastructure developed fully 549 irrigation infrastructure fully developed by year 2025 GAP Total number of irrigation infrastructure developed fully Summation of all irrigation infrastructures developed Quarterly/ Annually ARDS/MOWI/NIC 6 Area under irrigation In Ha Expand area under irrigation to 1,000,000Ha by 2025 468,338 Developed area in Ha under irrigation Summation of area under irrigation Annually ARDS/AASS/ASLMs/ MOWI/NIC 7 Functional Irrigators’ organizations (IO) management committees Number of functional committee 549 functional irrigators organization management committees by 2025 GAP Total number of irrigators management committees Summation of the irrigators committees Annually AASS/WPWI/NIC 8 Number of access water points for livestock Charco dam and borehole 100% increase of water points within 3km by 2025 1443 total number of charco dams and bore-holes for livestock Summation of charco dams and bore-holes for livestock Annually ARDS/AASS 9 Land area under fish farming in square meter Tilapia and catfish Double area under fish farming by 2025 4,540,400 Area under fish farming Summation of area under fish farming in square meter Annually ARDS/ASLMs Mainstreaming resilience for Climate Variability/Change and Natural Disasters 10 Percentage of farm, pastoral, and fisher households that are resilient to climate and weather related shocks crops, livestock Ensure that at least 30% of HH are resilient to climate and weather risks, by the year 2025. GAP Number of farmers, pastoralist and fishers applying irrigation or water harvest, early maturity seeds or zero grazing Summation of all farmers who are resilient to climate change Annually ASLMs-Environment / AASS/MOWI Agricultural Sector Development Programme II (ASDP-II) 173 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 11 Share of agriculture land under Sustainable Land Management (SLM) practices Crops Ensure that at least 30% of agricultural land is placed under SLM practice. 5.40% SLM is land area under agricultural cultivation Calculated as: Agriculture area under SLM divide by total agriculture area Annually ARDS//ASLM 12 Proportion of LGAs with mainstreamed CSA in their DADPs Agricultural sector CSA mainstreamed in all LGA’s DADPs by 2025. GAP DADPs have budget for investment or promoting use of water harvesting technology, drip irrigation, and use of early manure seeds Summation of all LGAs that have mainstreamed CSA in their DADPs Annually ASLM/ ASLMs-DPP (DADPs assessment) 13 Existence of government budget- lines to respond to spending needs on resilience building initiatives. Create permanent investment budget-lines to respond to spending needs on resilience building initiatives, especially for disaster preparedness plans, functioning early warning and response systems, social safety nets, and weather-based index insurance, from 2015 to 2025. GAP Existence of budget-lines on disaster preparedness policy and strategy, EIRB1; Existence of government budget-lines on Early warning and response systems and social safety nets, EIRB2; budget for research and irrigation, EIRB3; Existence of government budget-lines to respond to spending needs on resilience building initiatives (in %), EIRB = average (EIRBi)i=1 to 3 Annually ASLM Agricultural Sector Development Programme II (ASDP-II) 174 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 14 Number of crop farmers, Livestock households (HH) and fish farmers Crop farmers Maintain preferable level relative to environmental degradation. GAP Number of livestock/ fish farmers Annually AASS/ARDS Livestock HH Maintain livestock farmers according to the land carrying capacity GAP Number of livestock/ fish farmers Annually AASS/ARDS Fish farmers Maintain preferable level relative to environmental degradation. 25,259 Fresh water (tilapia and catfish) and marine (seaweed, prawns and milk fish) Annually AASS/ARDS Agricultural Sector Development Programme II (ASDP-II) 175 COMPONENT TWO Component Title: Enhanced Agricultural Productivity and Profitability Component Objective: To increase agricultural productivity and profitability through commercial and market-oriented agriculture Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Production and Productivity 1 Growth rate of the yield of the priority commodity Maize, Paddy, sun-flower, milk, beef,goat/mutton and marine fish (refer PDO 2) Cassava 100% increase in MT/ha 5.95 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Pulses (common beans) 100% increase in MT/ha 1.11 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Sorghum/millet 100% increase in MT/ha 1 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Horticulture (Round potato) 100% increase in MT/ha 13 Production per unit area Total production in tons per area in Ha Annually ARDS/AASS Cotton 100% increase in MT/ha 1 Production per unit area Total production in tons per area in Ha Annually ARDS/Cotton Board Coffee 100% increase in MT/ha 25 Production per unit area Total production in tons per area in Ha Annually ARDS/Coffee Board Sugarcane 100% increase in MT/ha 40 Production per unit area Total production in tons per area in Ha Annually ARDS/Sugar Board Tea 100% increase in MT/ha 9 Production per unit area Total production in tons per area in Ha Annually ARDS/Tea Board Cashew 100% increase in MT/ha 3 Production per unit area Total production in tons per area in Ha Annually ARDS/Cashew Board Tilapia/catfish 100% increase (in kg/ m2) 1.11 Production per unit area Total production in Kg per square meter Annually ARDS/AASS Seaweed Double production GAP Production per unit area Total production in Kg per square meter Annually MLF-fisheries Agricultural Sector Development Programme II (ASDP-II) 176 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 2 Total annual production Maize, Paddy, sun-flower, milk, beef, goat/mutton and marine fish (refer PDO 3) Cassava Double cassava production (in MT) 6614.4 Total production in MT Summation of production in the area Annually ARDS/AASS Pulses-common beans Double beans production (in MT) 1306.5 Total production in MT Summation of production in the area Annually ARDS/AASS Sorghum/millet Double sorghum/ millet production (in MT) 729.5 Total production in MT Summation of production in the area Annually ARDS/AASS Horticulture (Round potato) Double potato production (in MT) 1342.2 Total production in MT Summation of production in the area Annually ARDS/AASS Cotton Double cotton production (in MT) 149.5 Total production in MT Summation of production in the area Annually ARDS/Cotton Board Coffee Double coffee production (in MT) 60.9 Total production in MT Summation of production in the area Annually ARDS/Coffee Board Sugarcane Double sugar production (in MT) 2839.2 Total production in MT Summation of production in the area Annually ARDS/Sugar Board Tea Double tea production (in MT) 32.6 Total production in MT Summation of production in the area Annually ARDS/Tea Board Cashew Double cashew production (in MT) 155.4 Total production in MT Summation of production in the area Annually ARDS/Cashew Board Tilapia/catfish 100% increase tilapia/catfish production in Kg GAP Total production in Kg Summation of production in the area Annually ARDS/AASS Agricultural Sector Development Programme II (ASDP-II) 177 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 3 Agricultural labor and land productivity Labor productivity Double (100% increase) the current agricultural labor productivity levels by 2025 GAP Total agricultural labor involved in agriculture Agriculture GDP divide by Agricultural worker Annually AASS/ ASLM/ MOW Land productivity Double (increase by 100%) the current agricultural land productivity levels, by 2025 GAP Total agricultural land under agriculture Agriculture GDP divide by Agricultural arable land (in Ha) Annually AASS/ASLM/ MOW Agricultural Extension services Agricultural Sector Development Programme II (ASDP-II) 178 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 4 Agricultural technologies adoption Chemical Fertilizer At least half of the farmers are using chemical fertilizer (N+P+K) GAP Rate at which farmers adopt fertilizer application technology Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Improved seeds At least half of the farmers use using improved seeds GAP Rate at which farmers use improved seeds Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Agro-chemicals (all crops) At least half of the farmers are apply agro-chemicals GAP Rate at which farmers apply agro-chemicals Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Farm machinery At least half of the farmers are using farm machinery GAP Rate at which farmers use agro-machine Farmers using fertilizer divide by total number of farmers Annually ARDS/AASS Integrated Pest Management (IPM) Double farmers who are practicing IPM technology GAP Rate at which farmers using IPM technology Farmers using fertilizer divide by total number of farmers Annually AASS System of Rice Intensification (SRI) Double smallholder farmers who are practicing SRI technology GAP Rate at which farmers are using SRI Farmers using fertilizer divide by total number of farmers Annually AASS/ ASLM Water harvesting At least half of the smallholder farmers are using improved seeds GAP Rate at which farmers are using water harvesting technology Farmers using fertilizer divide by total number of farmers Annually AASS Drip irrigation or sprinkler At least half of the smallholder farmers are using improved seeds GAP Rate at which farmers are using drip irrigation/ sprinkler technology Farmers using fertilizer divide by total number of farmers Annually AASS Solar drying (fish) Double (100% increase) 3600 Rate at which farmers are using solar drying Farmers using fertilizer divide by total number of farmers Annually AASS Agricultural Sector Development Programme II (ASDP-II) 179 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 5 Number of extension staff Crops Double public extension staff 11,000 All crops extension staff Summation of crops extension staff Annually ARDS/AASS Livestock Double public extension staff 8,725 All livestock extension staff Summation of livestock extension staff Annually ARDS/AASS Fisheries Double public extension staff 750 All fisheries extension staff Summation of fisheries extension staff Annually ARDS/AASS Private Existing are engaged in agriculture through PPP GAP All private extension staff Summation of private extension staff Annually ARDS/AASS/TPSF 6 Ward Resource Centers (WARC) Number of WARC At least one WARC in each ward by 2025, (total number of wards is estimated at 3927) 319 Number of existing WARC Summation of WARC Annually ARDS/AASS Operational WARC 3927 WARC are operational by 2025 208 (gap) WARC developed and operational Summation of operational WARC Annually ASLM 7 Number of farmers and extension staff trained Farmers All farmers trained by 2025 0 All farmers trained through FFS and others e.g. seminars, workshop, study tour, residential training etc. Summation of all farmers trained Annually ARDS/AASS Trained extension staff 50% of extension staff trained in tailor made courses by 2025 GAP Extension staff attended training both short and long courses Summation of trained extension staff Annually ARDS/AASS Access to Agricultural Inputs and health services Agricultural Sector Development Programme II (ASDP-II) 180 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 8 Farmers access to inputs Fertilizer consumption (kilogram of nutrients per hectare of arable land) At least 50 kilograms per hectare by 2025. 19 Total inorganic fertilizers consumption per unit cultivated area (N+P, N+P+K) Fertilizer applied divided by cultivated land (kilogram of nutrients per hectare of land) Annually ARDS/AASS Improved seeds (in tons) collectively for cereals, legume, and others except seedlings and cuttings (annual requirements is 120,000 tons) Double the current levels of improved seeds by 2025 28,000 Total amount of improved seeds (in tons) applied in the cultivated land Summation of improved seeds applied in the cultivated land (in Tons) Annually ARDS/AASS Agro-chemicals (in tons) Increase usage of agro-chemicals to 100% by 2025 GAP Total amount of agro- chemical applied Summation of agrochemical applied in crops and livestock Annually ARDS/AASS Fingerlings Double fingerlings GAP Total amount of fingerlings produced and raised Summation of fingerlings produced and raised Livestock Breed (AI)-(annual demand is 1,000,000) Increased AI to 100% by 2025 100,000 Artificial Insemination for livestock Breed Annually ARDS/AASS Agricultural Research and Development 9 Technologies disseminated At least 70% of agricultural technologies developed are disseminated by 2025 GAP Number of technologies disseminated Summation of all technologies disseminated Annually Research/DRD/ AASS Agricultural Sector Development Programme II (ASDP-II) 181 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 10 Total Agricultural Research Spending as a share of Agriculture GDP Research spending for crops/livestock and fisheries Increase the level of Investments in Agricultural Research and Development to at least 1% of the Agricultural GDP by 2025. 0.28 Percent of agricultural research spending from total Agricultural GDP Total Agricultural Research Spending divide by total Agriculture GDP times 100 Annually MoA/MLF/ASLM Access to Mechanization Services 11 Proportion of machines in agricultural production Farm machinery About 50% of agricultural land are cultivated using tractor/power tiller or animal drought by 2025 14: (tractor/ power tiller) 24: Animal draught: All land cultivated by using animal draught or tractor/power tiller Land cultivated using animal draught or tractor/ power tiller divide by total land cultivated times 100 Annually ARDS/AASS 12 Number of farm machinery (tractors, etc.) hiring centers providing services Farm machinery hiring centers At least two mechanization (tractor, power-tiller and animal traction) hiring centers established at each LGA by 2025 5: (1 Rukwa, 1 masasi, 1 Songea, 1 Arusha and 1 Singida) All farm machinery hiring centers established Summation of all farm machinery hiring centers Annually ARDS/AASS Food and Nutrition Security 13 National food self sufficiency FSSR refer PDO 10 14 Malnutrition incidences (chronic and transitory) in Tanzania Malnutrition incidences refer PDO 12 15 Proportion of the population that is undernourished Proportion of undernourished refer PDO 13 Agricultural Sector Development Programme II (ASDP-II) 182 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 16 Proportion of household with low dietary diversity Proportion of dietary diversity refer PDO 11 Agricultural Sector Development Programme II (ASDP-II) 183 COMPONENT THREE Commercialization and Value Addition Component Objective: To improve and expand marketing and promote value addition by thriving competitive private sector and effective farmer organizations Key Performance Indicators: Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source Competitive Commodity and Value Addition 1 Volume and monetary value of agricultural exports Maize, Rice, cotton, horticulture, beef, marine fish refer PDO 5 Sunflower Double sunflower export by 2025 GAP Percentage change of sunflower export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Milk Triple milk export by 2025 GAP Percentage change of milk export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Coffee Double coffee export by 2025 GAP Percentage change of coffee export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Sugarcane Triple sugarcane export by 2025 GAP Percentage change of rice export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Tea Double tea export by 2025 GAP Percentage change of tea export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Cashew Double cashew export by 2025 GAP Percentage change of cashew export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Goat Double goat export by 2025 GAP Percentage change of goat export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Mutton Double mutton export by 2025 GAP Percentage change of mutton export Current GDP-baseline GDP/baseline GDP)*100 Annually TRA/ ASLM Agricultural Sector Development Programme II (ASDP-II) 184 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 2 Volume and monetary value of agricultural imports Maize, rice refer PDO 6 Marine fish Double (100% increase) marine fish production (Kg) GAP Total production in Kg Summation of production in the area Annually TRA/ ASLM Edible Oil Double (100% increase) edible oil production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Milk Double (100% increase) milk production (Litres) GAP Total production in Litres Summation of production in the area Annually TRA/ ASLM Coffee Double (100% increase) coffee production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Sugarcane Double (100% increase) sugar production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Beef Double (100% increase) beef production (MT) GAP Total production in MT Summation of production in the area Annually TRA/ ASLM Agricultural Sector Development Programme II (ASDP-II) 185 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 3 Reduction rate of the gap between the wholesale price and farm- gate price for all priority commodity Maize, Paddy, milk refer PDO 7 Cassava Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Common beans Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Sorghum/ millet Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS HT (potato) Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual Sunflower Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Cotton Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Coffee Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Sugar cane Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Tea Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Cashew Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Beef Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Goat Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Mutton Ratio decline by 50% GAP Difference between wholesale price and farm- gate price (Wholesale price minus farm-gate price) divide by farm-gate * 100 Bi-annual ARDS/ AASS Agricultural Sector Development Programme II (ASDP-II) 186 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 4 Ratio of value of raw agricultural export and processed export Hides/skins At least 100% of hides and skins are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Cashew At least 100% of cashew are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Beef At least 100% of beef are processed for export by 2025 GAP Monetary value of raw agricultural export and processed Total agricultural processed export over total export Bi-annual AASS/ ARDS Access to markets and rural infrastructure 5 Number of operational marketing infrastructure and new investment Market structure 100% of market infrastructures developed are operational by 2025 GAP All agricultural marketing infrastructures Summation of operational marketing infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM Warehouse/ 100% of warehouses developed are operational GAP All agricultural warehouse infrastructures Summation of operational warehouses infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM Godowns 100% of godowns developed are operational GAP All agricultural godowns infrastructures Summation of operational godowns infrastructures Bi- annually MoA/ MLF/ MITI/ ASLM 6 Volume of products marketed through warehouse receipt system (WHRS) Maize, rice, cashew 100% of agricultural produces are marketed through WHRS GAP Amount of maize, rice and cashew marketed through WHRS Summation of all produce marketed through WHRS Bi- annually MoA/ MITI/ ASLM Agricultural Sector Development Programme II (ASDP-II) 187 Indicators Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of report Data source 7 Reduction rate on Post- Harvest Losses for (at least) the 11 national priority commodities Cereals Halve (decrease by 50%) the current levels of Post-Harvest Losses (PHL), by the year 2025 from the year 2016. 30-40 Loss in tons Production (tons) of the commodity 1, Pd1; minus (Loss at Harvesting, LH; Loss at Storage, LS; Loss at Transport, LT; Loss at Processing, LP; Loss at Packaging, LPz; & Loss at Sales, LS); Loss=Pd1-(LH-LS-LT-LP- LPz-LS) in Tons Annually AASS/ MoA Root and tubers Decrease by 50% 45 Loss in Tons Annually AASS/ MoA Oil seeds Decrease by 50% 40-50 Loss in Tons Annually AASS/ MoA Horticulture Decrease by 50% Above 50 Loss in Tons Annually AASS/ MoA Fish and fishery product Decrease by 50% 70 Loss in Tons Annually AASS/ MLF Agricultural Sector Development Programme II (ASDP-II) 188 COMPONENT FOUR Sector Enablers, Coordination and M&E Component Objective: Strengthening Sector Enablers, Coordination and M&E Key Performance Indicators: Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Business Environment 1 Policy environment and regulation crop, livestock and fisheries Review/update/harmonize/ enforcement of policies, acts, regulations and legislation Crop (2013), Livestock (2006), Fisheries (2015), Marketing (2008) Agricultural policy environment Review, update, and harmonize as required Annually ASLMs/MOF 2 Institutional framework Agricultural stakeholders Review, update, harmonize of the institutional framework ASDP-I Institutional framework ASDP-II operational structure Review, update, and harmonize the existing framework Annually ASLMs/MOF Sector coordination (Vertical and Horizontal) 3 Timely submission of agricultural reports at all levels Crops, livestock and fisheries 100% submission rate by all LGA 90 Agricultural reports including quarterly, annually and ad- hoc Routine and non-routine Quarterly/ Annually/ periodic AASS/ARDS/ ASLMs 4 Agricultural guideline compliance rate Planning and implementation guideline 100% compliance GAP Rate at which the agricultural guidelines are complied by ASDP-II implementers DADPs preparation assessment index score Annually MoA-DADPs assessment 5 Budget allocations and disbursements Agricultural sector Recurrent 100% disbursement of the allocated budget 80.57 (crops), (livestock), (fisheries), (marketing), PO-RALG Budget approved, allocation and disbursement Records agricultural budget disbursement as per allocation Annually MOF/ASLMs Agricultural Sector Development Programme II (ASDP-II) 189 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Development 100% disbursement of the allocated budget 3.91 (crops), (livestock), (fisheries), (marketing), PO-RALG Budget approved, allocation and disbursement Records agricultural budget disbursement as per allocation Annually MOF/ASLMs 6 Public agriculture expenditure as share of total public expenditure Agricultural sector Increase public expenditures on agriculture as part of national expenditures, to at least 10% by 2025 5.30% Agricultural Sector Lead Ministries’ expenditure to the total public expenditure Public Agriculture Expenditure divide by total Public expenditure Annually MOF/ASLMs 7 Public Agriculture Expenditure as % of agriculture GDP Maintain public agriculture expenditure to not less than 19% of agricultural GDP by 2025 5.20% Agricultural Sector Lead Ministries’ expenditure to the agricultural GDP Public Agriculture Expenditure divide by Agriculture GDP Annually MOF/ASLMs 8 Official Development Assistance (ODA) disbursed to agriculture as % of commitments Agricultural sector 100% ODA disbursement annually from 2016 to 2025 Crops, livestock, fisheries, marketing DPs commitments in ASLMs ODA for agricultural sector (public, private, PPP, DPs, multispectral organization, NGOs, civil society, non-state actors, etc.) Annually ASLMs/MOF Agricultural Sector Development Programme II (ASDP-II) 190 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source 9 Ratio of private sector investment to government investment in agriculture Ensure that government investment leverage at least 3 times domestic private investment in agriculture sector by 2025. GAP Private sector investment to the public investment in agriculture Private sector investment divide by public investment Annually MOF/ASLMs 10 Ratio of foreign private direct investment (FDI) to government investment in agriculture Ensure that government investment leverage at least 3 times foreign private direct investment in agriculture sector by 2025. GAP Foreign private direct investment to the government investment in agriculture Foreign private direct investment divide by government investment in agriculture ASLM/MOF ASLM/MOF Monitoring & evaluation and Agricultural statistics 11 Annual Agriculture Sample Survey (AASS) implemented Agricultural sector AASS implemented in annual basis and results are out within three months Conducted February 2015 Survey conducted annually Survey Annually AASS/ARDS Stakeholder Empowerment and Organization 12 Empowerment of farmers organizations, women and youth Youth At least 30% of youth are granted title deeds for agricultural land by 2025. GAP Percentage of youth that is engaged in agriculture and have land title deeds Total number of youth engaged in agriculture and have land title deeds Annually TIC/ASLMS/ MoW/ MLHSH Rural women At least 20% of rural women have access to productive assets by 2025. GAP Proportion of rural women that have access to productive assets e.g. land, credit, input (fertilizer and seeds), etc. Total number of women provided with productive assets in agriculture Annually ASLM/BOT 13 Proportion of farmers who are members of farmers’ organization and cooperatives SACCOS by gender Double members of SACCOS by 2025 GAP Proportion of farmers who are members of SACCOS Number of farmers who are members in the SACCOS divide by total number of farmers Annually AASS/ARDS Agricultural Sector Development Programme II (ASDP-II) 191 Indicator Category Target for each Indicator Baseline Value (2016) Data collection and reporting Definition Methodology Frequency of reports Data source Farmers Organization and cooperatives Double members in the cooperative organization by 2025 GAP Proportion of farmers who are members of the cooperative organization Number of farmers who are members in the cooperative organization divide by total number of farmers Annually ASLMs/ Access to Rural Financing 14 Proportion of women and men engaged in agriculture with access to financial services Formal services Double (100% increase) farmers accessing to agricultural loans GAP Total number of farmers that have access to financial services (loans) by gender Number of farmers accessing loans by gender divide by total number of farmers Annually BOT 15 Proportion of branches of formal financial institutions in the rural areas Formal institutions At least more than half of branches has to be instituted in rural area GAP Total number of branches of formal financial institutions in the rural area Bank branches in rural area divide by total number of bank branches in Tanzania Annually BOT 16 Share and value of financial sector lending to agricultural sector by sub-sector At least 50% of the share and value of financial sector lending be allocated to agriculture by 2025 GAP Proportion of loan allocated in the agricultural sector by financial institutions Share and value of lending to the agricultural sector divide by the total amount loaned Annually BOT 17 Loan repayment rates (%) by banks by sub-sector At least loan repayment rates more than 80% by 2025 GAP Proportion of loans paid back to financial institutions Number of loans paid back divide by total number of loans BOT Agricultural Sector Development Programme II (ASDP-II) 192 ANNEX III: Details of Coordination Mechanisms Figure A23: ASDP II Programme Coordination Mechanism 1. Program Coordination, Governance and Project Management a. Implementation Backstopping and Problem Solving b. Project Management: (Procurement, investment mapping, problem solving) 2. Program Planning, Budgeting, Financial Management and Auditing a. Planning and Budgeting: finalize consolidation of program annual work plan and budgets, Coordinate agriculture sector projects) b. Financial Management: (Maintenance of ASDP II financials, following up with Treasury to disburse funding, support ASC with financial progress and audit results of project implementation) c. Auditing: Facilitate and Coordinate ASDP II financial audit and follow-up on implementation of audit findings 3. Monitoring and Evaluation 4. Stakeholder Engagement, partnerships, dialogue and capacity building a. Capacity Building and Accountability b. Comunication and knowledge Management c. Marketing the Program and Projects: 5. Analytical support on agricultural policies and availability of markets • Chaired by PM; Secretariat - PS - MoA • Review implementation progress • Advisory to stakeholders • Corrective action guidance Pesident’s Office for Regional and Local Government (PORALG) Ministry of Agriculture (MoA) Regional secretariat District Council Management Team Ward Development Committee Village Planning Committees National Agricultural Sector Coordination Unit (NCU) National Agricultural sector Stakeholders Meeting (NASSM) Agricultural Sector Consultative Group (ASCG) Technical Working Groups (TWG) Lead Component Working Groups Technical Committee of Directors (TCD) Agricultural Steering Committee (ASC) • Assistant Administrative Secretary for Economics and Production, with support from regional ASDP Coordination support planning and provide technical advice • Implementation arm of the gov’t at LGA • Reviews and budgets District Agriculture Development Plans (DADPs) • DADPs are formulated based on VADPs by District Irrigation and Cooperative Officers and/or District Livestock and Fisheries Officers • Village Agriculture Development (VADP) are developed by Village Agricultural Extension Officers & Village Executive Officer • Chaired by Minister - MoA; Secretariat - NCU • Reviews & Approves annual workplans, budgets and M & E reports • Tack financial progress and audit results • Discuss key agricultural issues Chaired by PS - MoA/ASLMs • Chaired by Ps - MoA; Secretariat - NCU • Government only participation • Advices on technical issues • Develop and implement policy • Prepares workplans and budgets • TWGs include Monitoring and Evaluation TWG and Planning and Budgeting TWG • Each Lead Component will have a TWG, Leader of TWG will serve as secretariat • Flexible membership, size and purpose (meets monthly) • Provide technical and managerrial advice to TCD and LGAs • Members of DP-AWG and PSD are represented in the TWG • Dispatch national facilitation teams for project problem solving • Provide technical and managerial support to LGAs via District Value Chain Components (DVC), • Led by Ward Councilor • VADPs (~3-6) collected by Ward Agricultural Extension Officer • VADPs submitted to DED 193 Agricultural Sector for Industrial Development Coordination at central, national level 418. The hierarchy of coordination organs and functions under ASDP II at central level is as follows: (i) National Agricultural Sector Stakeholders Meeting (NASSM) (ii) Agricultural Steering Committee (ASC) (iii) Agricultural Sector Consultative Group (ASCG) (iv) Technical Committee of Directors (TCD) (v) Thematic Working Groups (TWGs) (vi) ASDP II National Coordination Unit (NCU) 419. The National Agricultural Sector Stakeholders Meeting (NASSM) is the highest coordination event in the programme hierarchy and will be instrumental in coordinating and guiding the whole sector. It will be held once a year over one or two days as the culmination of the JSR/PER, which will inform NASSM. The meeting will be held under the chairmanship of the Prime Minister to review the ASDP II sectorial achievement and its contribution to national development and poverty reduction. The purpose of the NASSM will be to: • Provide an open opportunity for all the stakeholder representatives to exchange their views and gain insights into the successes of the programme from the perspective of others • Review conclusions drawn by the JSR/PER on progress in implementation of the various agriculture projects within the programme towards achieving planned targets, outcomes and impact • Advise the various government organizations, development partners, non-state actors, and private sector stakeholders on opportunities to foster greater agricultural transformation and accelerate achievement of ASDP II objectives and desired impact • Review and discuss agricultural transformation issues and impact of the program to the sector. 420. The NASSM will be attended by: • Central government—Ministers, Permanent Secretaries and Directors of Policy and Planning from all ASLMs, Component Leaders; and other related high officials of the government • Development partners (DPs)—members of the Agriculture Working Group, Private Sector Development partners (PSD) working group and other DPs suppoting or have an interest in agriculture. • RS—selected regional officials • LGAs—DEDs, DAICOs, DLFOs, DLOs, DCOs,from selected LGAs • Research—selected officials from agricultural, livestock and fishery research institutions (ASLMs) • Training—selected officials from agricultural, livestock and fishery training institutions (ASLMs) • Academia—relevant heads of departments from Sokoine University and other academic institutes/ training institutions involved in research and training of agriculture • Commodity boards • Private sector representatives • Non-state actor/NGOs/CBOs representatives • Financial institutions concerned with agricultural activities and investments • Associations and cooperatives—representatives of cooperative unions, commodity-wise associations, and successive agriculture associations and SACCOS • Representatives of other related stakeholder organizations 421. Before any NASSM is held there will be a JSR/PER that will lead to an intensive working process performed by both government, development partners, non-state actors, and private sector annually to monitor the sector progress. It will be conducted by the government, development partners and hired consultants to rigorously review the programme over several weeks on the basis of analysed national statistics as a professional annual evaluation exercise. It may include field visits in selected 194 Agricultural Sector Development Programme II (ASDP-II) regions where the ASDP II is being implemented by way of sampling, similar to Joint Implementation Review under ASDP-1. The JSR/PER will be an activity to facilitate coordination and dialogue and enable shared vision and opportunity to initiate corrective action in the management of projects. The report from JSR/PER will be first submitted to ASCG meeting, and later to the Agricultural Steering Committee before it is submitted to NASSM. The conclusions of the JSR/PER will be presented to the NASSM for discussion and corrective actions. The timing of implementing JSR/PER needs to be carefully decided in consideration of ASCG, ASC, NASSM, government budget formulation cycle and other related events. 422. The Agricultural Steering Committee (ASC) will be the key oversight and decision-making organ of ASDP II implementation and coordination. The core functions will be to approve the annual work plan and budget, oversee the physical and financial progress, follow-up the audit results and discuss on key issues in regard to sector performance and coordination. The conclusion will guide the TDC and TWG on the subsequent actions. It will be held quarterly and chaired by the Minister Ministry of Agriculture. The members are the Permanent Secretaries (PSs) of ASLMs, collaborating ministries, and institutions, TDC members, representatives of development partners’ (chair and co-chairs of the Agriculture Working Group (AWG) members and Private Sector Development Partners (chair and co-chairs of the PSD), representatives of non-state actors, and representatives of private sectors. It will be facilitated by Director of Policy and Planning (DPP) MoA and NCU. 423. The ASC is an overall oversight body for the ASDP II. Main objectives are to: (i) Achieve sector objectives and results through dialogue and consultations to establish coherent agriculture sector policies, strategies and programmes in line with Long Term Development Plan, Five Year Development Plan and other national development frameworks (ii) Ensure that planning, budgeting and budget allocation, execution and expenditure are in line with the agriculture sector policies, priorities, strategies and programmes (iii) Improve public financial management and accountability in ASLMs (iv) Implement agriculture sector specific JAST commitments (v) Implement agriculture sector GBS commitments as outlined in the PAF matrix and GBS Partnership Framework Memorandum (vi) Enhance domestic and mutual accountability 424. Agricultural Sector Consultative Group (ASCG). ASCG will be a sector consultative meeting where by all stakeholders in the sector will be albe to meet on quarterly basis to discuss issues and implementation of ASDP II. This meeting is very important because the ASC will function as a board and only representatives will be sitting in the ASC. ASCG is open to all stakeholders. The sector Permanent Secretary, Ministry of Agriculture, (MoA) will have an opportunity to meet and discuss with key stakeholders in the sector. These include ASLMs, Development Partners, Private sector, NGOs/CBOs, Farmer Based Organizations/Cooperatives, research and training institutions, implementers and partners of ASDP II. 425. Technical Committee of Directors (TCD). The TCD will be maintained and will absorb some of the functions of the Inter-Ministerial Coordinating Committee (ICC)143, which it will replace. It will advise the Agricultural Steering Committee on technical issues in connection with development of component, sub-component, investment area and projects and will be chaired by the Permanent Secretary, Ministry of Agriculture supported by the National Coordination and Management Team (NCU). The TCD is a solely government committee and will comprise all Director of Policy and Planning (DPPs)/Directors of ASLMs and Lead Component Leaders and chairs of the Components, and other selected key officials/experts of related government organizations (e.g., NIRC, NBS, TCDC, Land Commission). The committee will be supported by NCU. 426. The TCD will meet quarterly and may be called for ad hoc meetings if need arises. The TCD will review quarterly reports and contribute to annual reports. They will provide oversight of implementation and 143 The Inter-Ministerial Coordinating Committee (ICC) that existed under ASDP-1 will not be retained. Its functions will be taken over by the TCD. 195 Agricultural Sector for Industrial Development monitoring of the performance of ASDP II to ensure achievement of the goals. The TCD will report and advise respective Permanent Secretaries of the ASLMs. The wider functions of the TCD will include: • Reviewing the progress of all ASDP II interventions to ensure compliance with policies, macro and sector strategies and adherence to schedules through summarized physical and financial progress reports and take necessary corrective action • Advising the Agricultural Steering Committee (ASC) on a regular basis on the progress of and requirements for implementation of the ASDP II • Overseeing the development and implementation of policy decisions underlying the ASDS-2 and ASDP II • Overseeing the preparation of the ASDP II Integrated Annual Work Plan and Budget • Reviewing and recommending the budgetary proposals to the Steering Committee for endorsement and subsequent onward submission to Treasury • Recommending to the Steering Committee the transfer of funds from the Exchequer Account to the implementing agencies • Defining eligibility criteria for support of new programmes and projects under ASDP II • Review reports from Direct Project Financing 427. Thematic Working Groups (TWGs) will be organized working groups based on the experience from ASDP-1. For ASDP II the thematic working groups will be based on the ASDP II components, sub-components and investment areas. The members of the group will be drawn from experts within the relevant fields (i.e., departments/institutions) in each ASLM or relevant institutions, private sector, development partners and non-state actors/NGOs. Although the groups may coalesce or be redistributed or expand and contract to meet the needs of the issues at hand, core membership will remain intact. To enhance the better coordination among the wider stakeholders under ASDP II, especially the private sector, TWGs should be expanded and invite participation of development partners experts who also support the thematic area, in addition to non-state and private sector actors involved in the thematic area. The TWGs will provide guidance to the programme on technical and/or managerial matters and advise the TCD. They will be called upon for periodic and ad hoc deliberation to manage overall activities under the TWG and resolve technical issues. They will meet at least monthly and the expanded meeting including development partners and the private sector could be held quarterly. They will refer to quarterly reports from the local level and other sources (including off- budget projects), and inform quarterly meetings of the TCD and Steering Committee of the progress of various interventions at a technical level. Another important function of TWGs will be to follow the progress of recommended actions agreed by the preceding JSR that should be indicated in their annual work plans. They will be required to ascertain whether actions directed by the TCD have been correctly and completely performed. 428. The range of TWGs will be at thre levels: Component Thematic Working Group: This is a group working on component level issues. These will be four. Members of the component TWG are chairs of the sub-component leaders, and NCU staff responsible for coordinating the component. Chair/Representative from the Monitoring and Evaluation (M&E) & TWG; Chair/Representative from the Planning and Budgeting (PB) TWG. The NCU staff will be the secretariat to the TWG. Depending situation and demand, components could be sub-divided or create lower level thematic working groups based on the sub-components and/or investment areas. TDC will approve formation of TWGs. All TWG will be coordinated through NCU. 429. Members of the TWG will act as facilitators of the actions and will be called upon to extend their technical and/or managerial support to activities upon request from LGAs. Each TWG will contribute technical expertise and advice according to the designation of the group and in response to demand. The core activities and duties of TWGs will include: • Provision of programme progress implementation reports to the TCD 196 Agricultural Sector Development Programme II (ASDP-II) • Provision of technical expertise to ASDP II planning and implementation processes • Providing solutions to implementation bottlenecks • Analysis on technical grounds of the outcome • Provide problem solving solutions to issues presented. 430. TWGs will also provide national facilitation teams (of one or more member) that will comprise members of the TWGs who will be dispatched on an ad hoc basis to assist in implementation or problem-solving missions at project level. 431. The ASDP II National Coordination Unit (NCU) will be directed by the National Programme Coordinator who will be directly answerable to the Permanent Secretary of the Ministry of Agriculture. It will constitute a professional management team with recruited officials from the labour market and ASLMs/government instituions and will have executive and semi autonomous powers to manage, monitor and call for meetings of other organs of the ASDP II structures and to direct implementation functions. The team will be a fulltime job, reporting to PS MoA for management and administrative issues and to TDC for program implementation. It will be exclusively engaged in the ASDP II processes for the duration of the programme. • The members will comprise Senior Coordinator with a high calibre of managerial and program management skills who will be the National Programme Coordinator, preferable with good agricultural background • Experts in: Productivity and Commercialization; Markets and Valuae chain; (for crops, livestock, and fisheries); • Policy Analyst with Agricultural/Economics background and wide experience of agribusiness • Monitoring and Evaluation specialist • Communications and knowledge management specialist • Financial Planning and budgeting specialist • Accounting and procurement specialist • Office Management staff with secretarial and personal assistant capabilities The detailed structure of NCU will be prepared separately to accommodate some of the restructuring in the ASLMs and government. 432. They will also be given access to advisers on a consultancy basis as the need arises. Such advisers may be on short-term contract and may include international consultants. 433. The To ensure accountability, NCU will be served with specific Terms of Reference and performance contracts that will focus on sector coordination and management of the program with a link to the delivery of ASDP II indicators ideally, the team will be exclusively engaged in the ASDP II processes for the duration of the programme. Team members will be provided with transport facilities and necessary office and communications equipment to enable them to perform their role effectively. It will be responsible for: • Provide catalytic and supportive role to the agricultural transformation agenda • Facilitate and serve as the secretariat to TCD, ASC, ASCG, and NASSM and attending all the meetings • Close communications and interactions with the TWGs on their key activities • Networking and information sharing among all the stakeholders on their interventions (including on- and off-budget activities); stakeholder mapping will be necessary • Coordinate the preparation of the ASDP II Integrated Annual Work Plan and Budget in close cooperation with the TWGs, development partners supporting on- and off-budget activities, and other stakeholders • Coordinate alignment, harmonization and implementation of agriculture sector projects and interventions within the framework of ASDP II • Manage, monitor, evaluate, harmonize and coordinate implementation of ASDP II activities. • Compile, analyse, coordinate, provide program logistical support; • Prepare and consolidated quarterly, semi-annual and annual ASDP II progress implementation 197 Agricultural Sector for Industrial Development reports for onward submission to TDC, ASC and other national forums. • Provide technical support on joint monitor and evaluate of the program • Provide analytical and problem-solving support to the components • Production of manuals, guidelines and publicity and communication materials for ASDP II; • Establish and share best practices & lessons learnt under Agricultural SWAp • Facilitate and coordinate ASDP II financial audit and submit the same to TDC and ASC • Maintenance of ASDP II financial and other implementation records and reports • Absorption and coordination of all stakeholders into programme activities • Developing mechanisms for collaboration and coordination across all stakeholders in ASDP II • Remaining fully informed of the progress of all ASDP II functions and proceedings • Identifying appropriate interventions in pursuit of the objectives of ASDP IIand government policies • Provide secretariat to ASDP II 434. Agricultural Sector Consultative Group Meeting (ASCG meeting). The ASCG will provide a consultative and advisory forum for dialogue between the government (ASLMs), all interested development partners (as defined in the JAST), private sector and non-state actors (CSO and PSO) in the agriculture sector. The ASCG will coordinate dialogue at two levels: regular dialogue on sector policies and regulations; annual plans, budgets, and the annual agriculture sector/public expenditure review (ASR/PER) reports. 435. Functions of the ASCG are more of advisory to the sector and need to be informed on: (1) policy (Long Term Development Plan (LTDP), Five Year Development Plan (5YDP), agriculture sector policies, GBS, JAST); and (2) budgetary (public expenditure) issues. ASCG meetings will remain one of the underlying structures for the two main national processes and provide advice to ASC on the: (i) The LTDP and 5YDP process (ii) The national budget/PER process 436. The group will facilitate sector dialogue on JAST and GBS issues, which are to be integrated as much as possible within the LTDP and 5YDP and national budget/PER processes. It will serve as a forum for: (i) policy dialogue (ii) information sharing (iii) advice on the budget discussions and prioritization (iv) consultations on sector priorities, strategies and programme implementation, including linkages with other sectors such as natural resources (v) joint analysis and assessment of the agriculture sector issues/performance and launching baseline and follow up studies (vi) provision of advice on strategic, budgetary and other issues 437. Table A1 provides a summary of ASDP II sector coordination components. Agricultural Sector Development Programme II (ASDP-II) 198 Table A1: Summary of ASDP II coordination organs, mechanisms, membership and functions Organ/mechanism Membership/participants Functions and purpose i) National Agricultural Sector Stakeholders Meeting (NASSM). Chaired by Prime Minister Ministers of ASLMS, Other Central Government Ministers Permanent Secretaries, DPPs from all ASLMs, and senior government officials; Component Leaders; RSs; DEDs; DAICOs, DLFOs; research officials; training officials; academia representatives; commodity boards; All Development Partners supporting and involved in Agriculture, Private sector representatives; non-state actors/NGOs, financial institutions; associations and cooperatives, commodity associations, and successive agriculture associations and SACCOS; representatives of other related stakeholder organizations DPP MoA-Secretariat NCU: Recorders The agenda will be determined by stakeholders: Issues to be discussed include: provide advice and policy guidelines to the agricultural transformation agenda; provide advice and guideline to the implementation of ASDP II; facilitate and provide support where needed, invite other important partners to the sector. Agricultural Steering Committee(ASC) Chair: Minister, Ministry of Agriculture Permanent Secretaries of Lead Components and related ASLMS; Representatives of Development Partners (AWG- Chairs) (2 members, PSD-chairs (2 members); Representatives of Private Sector (3 members); Representatives of NGOs,.NSAs (3 members); DPPs of Lead Components; DPPs-ASLMs (Crops, Livestock & Fisheries) NCU – Secretariat Review and approve ASDP II plans, budgets, monitoring and evaluation reports; Approve ToR for Joint Annual Reviews/Sector reviews/Public Expenditure reviews(JSR/ASR/PER) and Monitoring and Evaluation Facilitate and approve establishment of ASDP II funding mechanisms; Discuss issues of mutual concern and information sharing; Review and approve ASDP II financial and audit reports, Approve changes in policies and regulations for on-ward submission to parliament Recommend the National Agricultural Stakeholder Meeting (NASSM) meeting calendar and agenda Approve NCU governance, management, coordination and operational issues Agricultural Sector Consultative Group (ASCG) Meeting Chair: Permanent Secretary , MoA All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/Donors and NGOs/NSA) (local and International) Training and Research Institutions DPP- MoA Secretariat NCU- Recorder Provide Advise on sector policies, plan, budgets, public and agricultural expenditure review Coordinate stakeholders dialogue regularly on sector policies, Provide support (financial, material and others) to the sector Participate in the annual joint planning and budgeting meetings Dialogue and voice od development partner opinion, Private sector, NGOs/NSAs/CBOs. Agricultural Sector Development Programme II (ASDP-II) 199 Organ/mechanism Membership/participants Functions and purpose Technical Committee of Directors (TCD) Chair: PS-MoA Directors of ASLMS, Component Leaders, Chairs of Lead Components, PO-RALG ASDP II Coordination Head of NIRC Head of Tanzania Cooperatives Development Council Head Warehousing Licensing Board NBS Ministry of Finance and Planning Ministry of Lands and Human Settlement Tanzania Food and Nutrition Council Ministry Energy Ministry of Transport Ministry of Education Representative of Agricultural Research/Training Institutions National Coordination Unit(NCU) Secretariat Review, scrutinize and harmonize individual Lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports Recommend to ASC governance and management guidelines and procedures for implementation of ASDP II Recommend to ASC ToR for Joint Annual Reviews/Sector reviews/ Public Expenditure reviews(JSR/ASR/PER) Monitoring and Evaluation Prepare and review papers for presentation to the ASCGM and ASC Review and propose to ASC policy and regulatory changes for the sector Provide advisory and coordination role to the ASDP II thematic working group (TWG) Recommend to ASC on NCU governance, management, coordination and operational issues Lead Agency Component Technical Meeting Chair: DPP of Lead Component Chairperson(s) of the Thematic Working Group (TWG) Chair/Representative from the Monitoring and Evaluation (M&E) TWG Chair/Representative from the Planning and Budgeting (PB) TWG Representative from NCU Review submitted component plans, budgets; review and analyze reports; Coordinate, scrutinize, monitor and evaluate ASDP II component plans and budgets Submits to ASDP II National Coordination Unit(NCU) for compilation andonward submission to TDC Agricultural Sector Development Programme II (ASDP-II) 200 Organ/mechanism Membership/participants Functions and purpose Thematic Working Groups (TWGs) (Various groups) Chairs: Component/Sub- Component Leaders Component /Sub-Component Leaders Selected technical Experts of different ASLMs appointed by the Head of the Lead Agency, private sector, Experts from Development Partners, Non-State Actors and CAADP country team representatives Co-opted Members for Cross Cutting and emerging issues Prepare and review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination meeting Plan, compile, analyze, coordinate, monitor and evaluate implementation of ASDP II for the component/sub-component. Provide advice on troubleshooting of implementation process and guide and provide guidance to TCD, on a continuous basis Bring cross-cutting expertise to issues arising. ASDP II Secretariat ASDP II National Coordination Unit (NCU) National Program Coordinator Experts in: Productivity and Commercialization; Markets and Value chain;(for crops, livestock, and fisheries); Monitoring and Evaluation; Agricultural Policy Analyst; Provide a catalytic and supportive role to the agricultural transformation agenda Compile all interventions/ Project Plans and Budgets under ASDP II and develop draft consolidated annual work plans and budgets; Coordinate joint planning and budgeting; Manage, monitor, evaluate, harmonize and coordinate implementation of ASDP II. Compile, analyse, coordinate, provide program logistical support; Prepare and consolidated quarterly implementation reports for onward submission to TDC, ASC and other national forums. Provide technical support on joint monitor, and evaluate of the program for onward submission to the Technical Committee of Directors(TCD) Provide analytical and problem-solving support to the components Production of manuals, guidelines and publicity and communication materials for ASDP II; Manage M&E functions; establish and share best practices & lessons learnt under Agricultural SWAp Facilitate and coordinate ASDP II financial audit and submit the same to TDC Provide secretariat to ASDP II 201 Agricultural Sector for Industrial Development Coordination at local level 438. ASDP-1 structures for local activities will be strengthened and continue under ASDP II. District Agricultural Development Plan (DADP) will continue to be the key instrument for agricultural development at local level. The District Executive Director (DED) will hold overall responsibility for activities and funds used at local level. The Council Management Team (CMT), which is chaired by the DED and attended by all the department heads including District Agricultural Irrigation and Cooperative Office Officers (DAICO) and District Livestock and Fisheries Officer (DLFO), is informed on the agricultural development issues and status under the DADP. A detailed structure of the Coordination mechanism from the village to national level and different organs is presented in Annex III. 439. DADPs are derived from the grassroots by villagers through the O&OD process and are summarized in the form of Village Agricultural Development Plans. The village planning process is led by a Village Planning Committee, Village Agricultural Extension Officer (VAEO), Village Executive Officer (VEO) and is supported by the District Facilitation Team according to the DADP Guidelines. Proposals from individual villages are submitted to wards that encompass three to six villages, on average. The proposals are consolidated by the Ward Agricultural Extension Officer (WAEO) under the supervision of the Ward Executive Officer (WEO) and guided by the Ward Development Committee that is led by the elected Ward Councillor and submitted to the DED. Based on the submitted proposals, DADPs will be formulated by DAICOs and DFLOs. The entire process will be guided by the DADP Guidelines and detailed instructions by ASLMs through PO-RALG. The focus of DADP needs to be in line with ASDP II investment priority investments, and projects focused commodities along the value chain (CVC) and Agricultural Ecological zones (AEZ). These activities are supervised by the regional agricultural coordinators, the National Coordination Unit and the relevant TWGs. 440. As a key coordination mechanism at local level, District Value Chain Components (DVC) between sector stakeholders at LGA level will be in place (s/c 3.2). DVC brings major actors in priority local CVCs together to develop and drive the implementation of DADP activities that include various aspects such as productivity improvement, value addition and market access. The stakeholders at local level include the private sector (traders, processors, transporters, financial institutions, etc.), NGOs, development partners and various public institutions that can provide different types of technical support. 441. It is therefore crucial for LGAs to formulate comprehensive DADPs that include not only on-budget development activities but also off-budget development activities extended through various projects within the LGA. For this purpose, it is inevitable to develop a mechanism ensuring that the contribution of each and every actor in the sector is well captured by respective LGA. National Coordination at Local Government Authorities Level – PO-RALG 442. LGAs are overseen and directed by PO-RALG. The Department of Sector Coordination is responsible for management and support to LGAs in collaboration with Regional Secretariats (RSs). Vertical coordination from the then PMO-LARG to RSs and LGAs has been established and worked well under ASDP-1 and ASDP II will continue to strengthen the same functions of PO-RALG. At the regional level, there will be a Regional Consultative Committee (RCC) chaired by the Regional Commissioner (RC). The Committee provides advisory role to the districts, monitor and supervise districts activities including the DADPs. 443. Each RS is headed by a Regional Administrative Secretary (RAS). The role of RAS is to assist the LGAs to prepare DADPs, backstop and provide supervision support on the implementation of the DADPs. The RAS also assists in the submission of the quarterly and annual reports in compliance with the DADP Guidelines. 444. The Assistant Administrative Secretaryfor the Economics and Production section within RS is directly responsible for supporting development activities within the region and is assisted in the task by 202 Agricultural Sector Development Programme II (ASDP-II) the ASDP Regional Coordinator and fellow officers dedicated to specific sub-sectors. These officers will move around the region to provide technical, and managerial assistance to LGAs. The ASDP II regional coordinators will also be responsible for monitoring and evaluating district activities implemented under ASDP II. The RSs will work closely with the relevant TWGs and NCU as the need for consultation and assistance arises. For administrative aspects of ASDP II, coordination among RSs, TCD through NCU, and TWGs will be constantly maintained to realize smooth flow of information on the status of development activities and performance under ASDP II. Agricultural Sector Development Programme II (ASDP-II) 203 APPENDIX IV: Program and Project budget Requirements Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 Component 4 Budget (Sector Enablers, Coordination and Monitoring and Evaluation) Sector Enablers, Coordination and Monitoring and Evaluation 4.1 Policy and Regulatory Framework 4.1.1 Policy and Regulatory Framework and Business Environment Improvement 4.1.1.1 Review and harmonize agricultural sector related policy and regulatory frameworks for improved business environment 310,300,000 967,330,000 352,038,000 387,241,800 425,965,980 2,442,875,780 4.1.1.2 Enhancing Monitoring, Control and Surveillance (MCS) for mitigated Illegal, Unreported and Unregulated Fishing (IUU Fishing) 6,019,012,325 2,022,862,500 1,646,501,250 1,684,491,375 1,846,466,513 13,219,333,963 4.1.1.4 Strengthening and control of child labour in Agriculture 1,584,790,000 1,050,194,000 1,094,008,400 808,132,240 684,175,260 5,221,299,900 4.1.1.5 Promoting decent work, occupational health and safety in agricultural sector 587,350,000 932,655,000 426,593,000 - - 1,946,598,000 Total - SUB-COMPONENT 8,501,452,325 4,973,041,500 3,519,140,650 2,879,865,415 2,956,607,753 22,830,107,643 Agricultural Sector Development Programme II (ASDP-II) 204 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 4.2 Stakeholder empowerment & organization 4.2.1 Strengthening organizational and technical capacities of existing and new small-scale producer, trade and processing Farmer Organizations and cooperatives Movement 4.2.1.1 Strengthening Cooperatives, Farmer- based organisations and other value chain actors' associations in the agricultural sector 4,013,830,000 3,741,656,000 2,298,944,600 2,116,074,810 1,194,736,731 13,365,242,141 4.2.2 Promote and strengthen gender inclusiveness in the agricultural sector 4.2.2.1 Improving benefits of women and youth along agricultural commodity value chain (WAYA) 3,024,921,667 3,238,193,500 2,779,148,100 852,268,200 930,673,180 10,825,204,647 Total - SUB-COMPONENT 7,038,751,667 6,979,849,500 5,078,092,700 2,968,343,010 2,125,409,911 24,190,446,788 4.3 ASDP II_sector coordination (planning & implementation at national, regional and LGA) 4.3.1 Improved and strengthen vertical coordination (from PO-ALG to RSs and LGAs) and horizontal coordination between ASLMs 4.3.1.1 Strengthening agricultural sector institutional frameworks for improved vertical and horizontal coordination and communication 6,872,144,000 6,672,824,000 4,280,182,000 2,114,683,800 2,196,777,780 22,136,611,580 Total - SUB-COMPONENT 22,136,611,580 Agricultural Sector Development Programme II (ASDP-II) 205 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 4.4 Monitoring and Evaluation (incl. Agricultural statistics) 4.4.1 Improved Capacity and agricultural data collection and management systems 4.4.1.1 Capacity building and integration of agricultural data collection and management systems (e. g. ARDS, NSCA, AASS) for improved result based management at all levels. 4,425,342,000 6,997,451,125 2,879,056,270 2,591,046,637 2,195,567,312 19,088,463,344 4.4.2 Develop Agricultural Sector M&E System 4.4.2.1 Strengthening and integrating agricultural sector monitoring and evaluation systems for efficient and effective accountability at all levels. 11,332,900,000 3,208,586,000 1,596,941,100 1,293,583,000 1,122,429,763 18,554,439,863 Total - SUB-COMPONENT 15,758,242,000 10,206,037,125 4,475,997,370 3,884,629,637 3,317,997,074 37,642,903,206 4.5 Institutional capacity development, and knowledge management and ICT 4.5.1 Improvement of Capacity in all levels 4.5.1.1 Improving capacity at national, RS and LGAs (number and quality) for all levels 3,429,157,500 6,349,550,000 3,781,150,000 2,501,350,000 1,142,220,000 17,203,427,500 4.5.2 Improvement of ICT for Agricultural Information Services and Systems 4.5.2.1 Developing comprehensive knowledge management and ICT system at all levels. 3,047,300,000 2,376,405,000 336,377,000 212,645,350 400,139,770 6,372,867,120 4.6. access to rural financing 4.6.1 Provide microfinance services 4.6.1.1 Access to agricultural financing for improved commodity value chain 1,481,305,000 1,833,055,000 1,599,616,600 1,513,723,796 638,604,290 7,066,304,686 Total - SUB-COMPONENT 7,957,762,500 10,559,010,000 5,717,143,600 4,227,719,146 2,180,964,060 30,642,599,306 Agricultural Sector Development Programme II (ASDP-II) 206 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 TOTAL -COMPONENT 39,256,208,492 32,717,938,125 18,790,374,320 13,960,557,208 10,580,978,798 137,442,668,522 Component 3 Budget (Commercialization and value addition) 3. Commercialisa- tion and value addition 3.1 Marketing 3.1.1 Develop market access for all priority commodities. 3.1.1.1 Improving and development of market infrastructure for accessing domestic and export markets 98,345,805,000 456,727,977,000 568,733,077,800 635,560,647,800 684,371,127,488 2,443,738,635,088 3.1.2 Develop market access for fisheries and livestock products 3.1.2.1 Improving and developing livestock & fish market infrastructure for increased domestic revenues and expanded market 7,847,305,000 9,464,598,000 156,458,314,800 171,750,092,140 368,188,102,190 713,708,412,130 3.1.2.2 Improving local and improved chicken market access 742,875,000 2,067,455,500 2,247,754,750 369,351,650 282,526,169 5,709,963,069 3.1.2.3 Strengthening livestock & fisheries traceability (identification) system to promote trade and marketing 1,833,825,000 737,989,000 732,995,000 643,247,150 629,633,366 4,577,689,516 3.1.2.4 Promoting and enhancing involvement of private sector in the commodity value chain 1,238,470,000 4,073,370,000 4,376,132,500 1,442,114,675 13,998,798,538 25,128,885,713 Total - SUB-COMPONENT 110,008,280,000 473,071,389,500 732,548,274,850 809,765,453,415 1,067,470,187,751 3,192,863,585,516 3.2 Agribusiness development: value addition and agro- processing 3.2.1 Development of processing and value addition for Crop, livestock and 3.2.1.1 Strengthening and development of agroprocessing industries for value addition for all priority commodities 10,332,690,000 14,447,726,000 15,432,309,800 16,806,037,745 18,521,995,935 75,540,759,480 Agricultural Sector Development Programme II (ASDP-II) 207 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 fishery products 3.2.1.2 Improving milk value chain 8,885,940,000 8,536,245,500 8,013,592,850 4,212,492,265 4,570,786,337 34,219,056,952 3.2.1.3 Strengthening hides and skin value chain 13,914,590,000 10,119,086,500 19,593,434,900 5,971,608,190 5,306,513,481 54,905,233,071 3.2.1.4 Strengthening value chain for horticultural commodities 4,994,890,000 1,621,794,000 4,126,542,200 1,273,611,645 1,386,890,047 13,403,727,892 3.2.1.5 Developing strategic warehouse facilities to be linked to commodity warehouse exchange 26,327,700,000 21,011,437,000 22,694,470,650 24,804,587,300 27,302,251,665 122,140,446,615 3.2.1.6 Development and enhancement of value addition for priority fisheries and aquaculture products 5,757,355,000 6,752,314,000 7,266,361,600 7,867,464,680 8,431,888,328 36,075,383,608 3.2.1.7 Enhancing beef, chevron, mutton value addition 9,632,790,000 12,738,732,000 3,507,122,200 504,939,770 225,448,930 26,609,032,900 3.2.1.8 Improving Postharvest Management Along Food Supply Chain For sustainable food security and nutrition 1,088,340,000 2,710,417,500 12,533,992,850 2,323,718,420 1,079,948,052 19,736,416,822 Total - Sub-Component 80,934,295,000 77,937,752,500 93,167,827,050 63,764,460,015 66,825,722,774 382,630,057,339 TOTAL- COMPONENT 190,942,575,000 551,009,142,000 825,716,101,900 873,529,913,430 1,134,295,910,524 3,575,493,642,854 Component 2 Budget (Enhanced Agricultural Productivity and Profitability) Agricultural Sector Development Programme II (ASDP-II) 208 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2. Enhanced Agricultural Productivity and Profitability 2.1 Extension training and information services 2.1.1 Strengthening agricultural extension, training and promotion/infor mation services (crops, livestock and fisheries) 2.1.1.1 Strengthening agricultural extension and promotion (all commodities) 1,311,912,630,000 772,651,750,500 849,529,380,050 838,081,042,930 921,147,859,276 4,693,322,662,756 2.1.1.2 Strengthening agricultural competence-based training and promotion (all commodities) 4,372,604,150 9,719,504,500 9,349,112,950 8,505,972,245 9,221,909,470 41,169,103,315 Total - Sub-Component 1,316,285,234,150 782,371,255,000 858,878,493,000 846,587,015,175 930,369,768,745 4,734,491,766,070 2.2 Access to Agricultural Inputs and health services 2.2.1 Improved Access to Crops, Livestock and Fisheries Inputs and health services 2.2.1.1 Improving availability and access to quality and affordable agricultural inputs for increased productivity and profitability (all commodities) 149,389,300,000 136,694,880,000 150,284,368,000 164,670,257,650 181,057,283,415 782,096,089,065 2.2.1.2 Improving access and availability of quality Poultry inputs 4,176,191,250 2,652,218,625 2,799,882,488 2,962,312,736 3,140,986,010 15,731,591,109 2.2.1.3 Development of National Tuna Fishing Fleet for increased productivity 1,664,250,000 93,407,668,200 768,004,545 1,098,600,080 987,463,628 97,925,986,452 2.2.1.4 Strengthening and establishing landing sites for improved fishery profitability 1,146,337,500 4,533,411,750 5,008,172,925 4,245,593,993 4,638,653,392 19,572,169,559 2.2.1.5 Development of Marine Capture fishing harbour for increased profitability 4,114,772,384 5,175,475,000 7,350,242,000 4,460,007,000 2,090,273,670 23,190,770,054 Agricultural Sector Development Programme II (ASDP-II) 209 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2.2.1.6 Upgrading Artisanal Fishery to enhance Fish Production and Productivity 55,089,477,353 50,853,035,000 48,517,288,500 6,657,553,200 4,388,210,355 165,505,564,408 2.2.1.7 Strengthening Beach Management sustainable management, fisheries resources 2,537,220,000 2,134,277,250 2,199,129,975 2,146,830,473 2,319,001,645 11,336,459,342 2.2.1.8 Improvement of plant health services 13,322,105,000 11,190,853,500 7,608,436,004 1,388,679,306 477,989,282 33,988,063,092 2.2.1.9 Production of vaccines and drugs 44,569,605,614 36,191,315,000 39,699,992,500 3,705,147,750 4,379,467,025 128,545,527,889 2.2.1.10a Improvement of livestock health services 262,550,032,281 295,128,209,145 332,216,208,381 371,558,679,638 420,078,299,939 1,681,531,429,384 2.2.1.10b Improvement of aquatic health services 1,517,656,875 1,238,258,438 1,240,903,519 1,339,594,371 1,395,264,758 6,731,677,960 Total - Sub-Component 540,076,948,257 639,199,601,907 597,692,628,836 564,233,256,195 624,952,893,118 2,966,155,328,313 2.3 Agricultural Research for Development (AR4D) 2.3.1 Strengthening AR4D (crops, livestock and fisheries) 2.3.1.1 Strengthening agricultural research capacity for technologies development, industrial linkages and transfer of results (all sub-sectors) 7,558,670,000 29,196,530,000 29,503,788,600 8,707,708,130 9,516,387,793 84,483,084,523 2.3.2 Research and development 2.3.2.1 Integrated technologies development and dissemination for increased production and productivity (all commodities) 12,408,638,000 16,383,957,425 11,615,699,430 11,110,318,211 11,371,090,422 62,889,703,487 Agricultural Sector Development Programme II (ASDP-II) 210 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 2.3.2.2 Promoting and Strengthening livestock genetic potential through modern breeding technologies 4,832,950,500 3,894,671,550 2,682,470,175 2,737,590,818 3,011,349,899 17,159,032,942 Total - Sub-Component 24,800,258,500 49,475,158,975 43,801,958,205 22,555,617,158 23,898,828,114 164,531,820,952 2.4 Access to Mechanization Services 2.4.1 Strengthening and promote agricultural mechanization (crops, livestock and fisheries) 2.4.1.1 Strengthening and promote agricultural mechanization for improved value chain 9,249,492,000 5,753,278,650 5,698,585,515 5,707,520,942 5,717,349,911 32,126,227,017 Total - Sub -Component 32,126,227,017 2.5 Food and nutrition security 2.5.1 Food and nutrition Security improved 2.5.1.1 Improving availability, quality access and utilization of essential nutrient rich food sources (all commodities) 14,152,477,500 11,721,816,750 12,960,295,425 14,297,133,428 10,393,795,970 63,525,519,073 2.5.1.2 Increasing production and promoting sorghum and millet for food and local consumption 20,537,475,000 22,167,043,500 23,954,717,850 25,921,159,635 28,084,245,599 120,664,641,584 Total - sub- Component 34,689,952,500 33,888,860,250 36,915,013,275 40,218,293,063 38,478,041,569 184,190,160,656 TOTAL - COMPONENT 1,915,852,393,407 1,504,934,876,132 1,537,288,093,316 1,473,594,181,591 1,617,699,531,545 8,081,495,303,009 Component 1 Budget (Sustainable Water and Land Use Management) Agricultural Sector Development Programme II (ASDP-II) 211 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 Sustainable Water and Land Use Management 1.1 Land Use Planning and sustainable Water Shed and Soil Management 1.1.1 Land use planning and watershed management 1.1.1.1 Integrated land use planning and management for conflict resolution, sustainable agricultural production and industrial development (all products/all zones) 29,758,830,000 31,014,157,500 34,532,074,500 95,305,062,000 1.1.1.2 Strengthening pasture production and conservation for sustainable livestock productivity 14,132,350,000 14,517,360,000 13,715,440,000 13,501,214,000 16,283,985,400 72,150,349,400 1.1.1.3 Enhancing access to agricultural land for youth empowerment 4,464,055,000 4,149,595,000 5,753,069,750 4,533,911,000 6,321,240,750 25,221,871,500 1.1.1.4 Improving coordination of watershed management and monitoring systems for sustainable resource utilization. (all products) - 1,366,429,750 927,979,000 838,670,020 916,057,022 4,049,135,792 Total - Sub-Component 48,355,235,000 51,047,542,250 54,928,563,250 18,873,795,020 23,521,283,172 196,726,418,692 1.2 Integrated Water Use and Management for Crops/Irrigatio n and Livestock/Fishe ry Development 1.2.1 Irrigation infrastructure development 1.2.1.1 Rehabilitation and development of irrigation infrastructure for increased production and productivity 16,369,940,000 184,589,225,292 172,338,444,067 175,277,962,887 189,618,773,923 738,194,346,168 1.2.1.2 Promotion of micro irrigation systems for improved crop production and productivity 5,873,183,333 50,128,619,250 57,162,204,550 59,915,108,463 65,430,495,378 238,509,610,973 Agricultural Sector Development Programme II (ASDP-II) 212 Agricultural Sector Development Programme II (ASDP II) Budget 2017/2018 - 2021/2022 COMPONENT SUB- COMPONENT PRIORITIZED INVESTMENT AREAS PROJECTS Y1 Y2 Y3 Y4 Y5 Project Budget Estimates (5 Years) 2017/2018 2018/2019 2019/2020 2020/2021 2021/2022 1.2.2 Irrigation schemes management & 1.2.2.1 Strengthening Irrigation schemes management and operations 1,822,835,000 1,651,922,500 2,249,454,750 1,786,470,225 2,592,437,428 10,103,119,903 1.2.3 Water sources development for livestock & fisheries 1.2.3.1 Development of water infrastructures for livestock productivity 2,855,560,000 66,582,431,000 77,456,128,600 76,102,476,900 85,464,005,000 308,460,601,500 1.2.3.2 Promoting and construction of modern integrated water facilities for crop, livestock and fisheries 42,068,700,000 79,875,420,000 111,447,304,000 158,157,213,500 88,772,625,300 480,321,262,800 Total - Sub-Component 68,990,218,333 382,827,618,042 420,653,535,967 471,239,231,974 431,878,337,028 1,775,588,941,344 1.3 Mainstreaming resilience for Climate Variability/Cha nge and Natural Disasters 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.1 Promoting and developing Climate Smart Agriculture and Conservation Agriculture technologies 1,905,425,000 13,984,275,833 8,745,740,917 6,345,077,933 10,444,742,727 41,425,262,410 1.3.1.2 Promoting Ecosystem Approach to Fisheries and Aquaculture Management 1,089,637,500 1,044,926,000 1,729,778,250 794,675,575 1,329,264,100 5,988,281,425 1.3 Mainstreaming resilience for Climate Variability/Cha nge and Natural Disasters 1.3.1 Promote Climate smart agriculture (CSA) technologies and practices 1.3.1.3 Strengthen Comprehensive Agricultural Early Warning System and Emergency Preparedness 1,959,756,667 1,051,870,333 1,008,738,867 395,675,420 501,066,927 4,917,108,214 Total - Sub-Component 4,954,819,167 16,081,072,167 11,484,258,033 7,535,428,928 12,275,073,754 52,330,652,049 TOTAL- COMPONENT 122,300,272,500 449,956,232,458 487,066,357,250 497,648,455,923 467,674,693,954 2,024,646,012,085 TOTAL PROGRAM BUDGET 2,268,351,449,399 2,538,618,188,716 2,868,860,926,786 2,858,733,108,151 3,230,251,114,821 13,819,077,626,470 operation 213 Agricultural Sector for Industrial Development ANNEX V Monitoring & Evaluation and Statistics144 Background 445. Under ASDP-1 (2006-2013), the ASLM established various TWGs, including one specializing in M&E TWG established in 2007. Its membership includes officials from planning departments in the various ASLMs and JICA technical assistants145. The objective of this group focuses on tracking and providing overall technical guidance on the implementation of this M&E framework, with the aim of monitoring the ASDP, collecting data on the sector through improving the routine data collection system, and strengthening M&E capacity in ASLMs and at regional and district level. 446. The M&E TWG prepared the M&E framework document in 2008. This document identifies the main impacts for the ASDP as a whole, by outcomes and by strategic area (physical infrastructure, agricultural services, marketing system, institutional framework and cross-cutting issues), as well as the outputs of various proposed interventions. The first list contained 100 indicators, which were later reduced to 20–25 key indicators as shown in Annex II. However, this list was modified over time to capture critical issues such as empowerment, service reform and research146. For ASDP II the key indicators are developed at the component, sub-component and priority investment area. Complete list of key indicators are as shown in the results framework (RF). 447. For effective planning, budgeting, monitoring and evaluation there will be two cross cutting technical working groups to support and facilitate planning, budgeting, monitoring and evaluation. These are the Monitoring and Evaluation TWIG (M&E-TWG) and the Planning and Budgeting TWG (PB- TWG). 448. One of the tasks of the M&E TWG is to prepare the annual ASDP II performance reports as well as sector impact evaluation. The annual performance report: provides an update on the shortlist of key indicators at the three levels: impact, outcome and output levels), compares target and actual figures, wherever possible; and assesses causes for shortcomings. Data collection was done using a conventional method: (i) for local data, a questionnaire was sent to all LGAs and filling-up and submission was transmitted by telephone and email communications; and (ii) for national data, inquiries were made by telephone or direct visits to the relevant office by members of the M&E TWG. Without being presented to the ASDP Basket Fund Steering Committee, the report has had limited use in the ASDP M&E. Past reports, in addition to the mid-term evaluation of ASDP-1, show that while there has been progress regarding selected outputs, the picture is mixed at outcome and impact levels. For example, at impact level, the indicators include agricultural growth, rural poverty and value of agricultural exports, and progress has been slower than was anticipated, particularly regarding poverty reduction. At outcome level, key indicators such as use of improved technologies (seed, fertilizer, irrigation and mechanization) have not shown the desired improvements. However, the picture is generally positive in terms of physical delivery of services (infrastructure and capacity building). 449. The conclusion of the ASDP evaluation (June 2011) was that ASDP outputs had yet to fully mature into all the intended outcomes and impacts that were foreseen during preparation. The report stresses the importance of careful and speedy measurement of higher level results, through holding surveys more regularly. 450. Under ASDP II the M &E-TWG will continue to play a similar role, however at each level of implementation (from project at the LGA to the National Level) some elements of M&E will be instituted. Each level will need to conduct both internal and external monitoring and evaluation. Joint annual sector review will be conduct in collaboration with all stakeholders. For efficiency and effectiveness, the immediate level within the government hirechical structure will carry the M &E. For example the Ward Executive Officer (WEO) will monitor and evaluate the Village Executive Office (VEO). A coherent and systematic M & E systems will be instituted from national to the 144 (Adapted from ASDP II proposal, 2013/14). 145 JICA is financing the second phase of a M&E capacity building project in the context of ASDP, which implemented by the International Development Centre of Japan (IDCJ). 146 Evaluation of the Performance and Achievements of the Agricultural Sector Development Programme, June 2011. 214 Agricultural Sector Development Programme II (ASDP-II) project level. Hence, M & E will be established at all coordination levels (National, PO-RALG, RS and District) and capacity building for the same will be ensured. At the national level, NCU will coordinate national joint annual reviews and evaluations. Tables 60 and 61 below present the internal and external monitoring and evaluation frequency for different levels in the government hierarchy. 451. The ASDP I Planning and Implementation Technical Working Group (P&I TWG) focuses on supporting districts with the preparation of their DADP, and with the implementation and reporting of ASDP activities through the DADP. The PO-RALG ensures that all districts follow the guidelines and fulfill the minimum conditions under the Local Government Development Grant (LGDG). The LGDG assessment conducted under supervision of the then PMO-RALG incorporates the specific results from the DADP assessment into the overall assessment of minimum conditions and performance measures147. A separate DADP Quality Assessment Report has been prepared for agriculture and could be used to illuminate indicators. This assessment was done by the P&I TWG together with regional ASDP coordinators. 452. During the ASDP II implementation there will be a Planning and Budgeting TWG (P &B-TWG). This will be responsible to coordinate all plans and budgets from the central, regional secretariat an LGA levels. At the Central level, all Lead Component budgets will be prepared and submitted to the P&B TWG for review, consolidation and harmonization. P&B TWG will ensure that here is consistency of the Lead Component plans and budgets to the overall ASDP II objectives and deliverables. The recommended plan and budget will be submitted to TDC and later approved by ASC. The GoT planning cycle will be upheld. The M&E TWG will also be able to monitor and evaluate implementation of the plans and budgets at all levels for the delivery of the ASDP II objectives and outcomes. 453. Due to its demand-driven nature, ASDP-1 promoted a decentralized and bottom-up approach, where farmer groups, cooperative societies and user associations, prepare a “project” based on clear guidelines and criteria, and request financing from one of the block grants available at district level.148 These projects (rehabilitate dip tanks and small irrigation scheme, etc.) are then monitored quarterly by district officials. This information was consolidated by the then PMO-RALG and shared with ASLM Technical Committee of Directors, and submitted to the ASDP Basket Fund Steering Committee for their review and approval (or rejection/further design work required). 454. All districts need to report quarterly on the physical and financial implementation of ASDP funds. A set of template tables will be prepared by the P&B TWG149. These tables will provide information by “project”, and focus on physical (output) and financial reporting, as well as providing information on the number of beneficiaries. An attempt will be made to capture outcome information at project level based on the project key performance indicators. The Joint Implementation Reviews (JIR) undertakes an annual assessment of progress made, and brings together stakeholders from ASLMs, development partners, non-state actors and the private sector to share and discuss implementation performance, and related issues and priority actions. The JIR report highlights areas where progress has been made, and provides recommendations regarding the various issues affecting ASDP implementation. Figure A1150 provides a summary overview of the M&E system established under the ASDP-1 and adapted for ASDP II towards monitoring both the performance of the ASDP itself, as well as that of the Agriculture Sector in Tanzania. 147 Annual Assessment of Minimum Conditions and Performance Measures for Local Councils under the LGDG System, PMO-RALG, May 2010. 148 District Agriculture Development Grant (DADG), Capacity Building Grant (CBG), Extension Building Grant (EBG) and District Irrigation Development Fund. 149 Strengthening the Backstopping Capacities for the DADP Planning and Implementation under the Agricultural Sector Development Programme (ASDP), International Development Centre of Japan (JICA). 150 Project for Capacity Development for the ASDP Monitoring and Evaluation System (phase 2), International Development Centre Japan, June 2012. There are two teams, one focusing on M&E for the whole of ASDP and the other focusing on planning and implementation at district level, which is supporting the PI TWG. 215 Agricultural Sector for Industrial Development 455. Under this system, sector outputs will be monitored through the Agricultural Routine Data System (see M&E section), and/or through specific reports. Sector outcomes will be monitored mainly through the NSCA, the AASS and/or the National Panel Survey (NPS) agriculture module (see statistics section). The NSCA was meant to inform many of the key outcome indicators identified in the list of key performance indicators for ASDP II. 456. The performance of the individual projects will be captured through DADP for LGA related projects for both physical and financial quarterly progress reports. While those related to the national level will be captured by NCU and those at RS will be captured by the regional ASDP II coordinator. Under ASDP-1 the system only captured projects implemented and financed under on-budget resources. Under ASDP II improved coordination within SWAp requires that all projects implemented in the sector are included in the integrated performance reporting, although non-budget projects have their own management and reporting system. The mechanisms to capture off-budget activities include: quarterly reports by each NGO project to be submitted according to requirements specified in memoranda of understanding with each NGO project, but excluding information on the source and application of funds unless volunteered to compare with projects within government programmes. Table 60: Monitoring Frequency at Different ASDP II Implementation Levels Monitoring Level Internal External Village Monthly Quarterly Ward Monthly Quarterly Division Quarterly Quarterly District Quarterly Quarterly Region Quarterly Quarterly National ( NCU) Quarterly Quarterly National (Joint Annual Implementation Reviews) Annual Annual Table 61: Evaluation Frequency at Different ASDP II Implementation Levels Evaluation Level Internal External Village Annual 1.5 years Ward Annual 1.5 years Division Annual 1.5 years District 1.5 years 2 years Region 1.5 years 2 years National and Joint Evaluations 2.5 years 2.5 years 216 Agricultural Sector Development Programme II (ASDP-II) Figure A24: ASDP M&E system for sector and project performance (adapted for ASDP II) ASDP 2 AGRICULTURAL STEERING COMMITEE ASDP M&E Baseline and Performance reports (ASDP indicators) ASDP 2 NATIONAL COORDINATION TEAM (NACOTE) SECTOR PERFORMANCE (national, regional, district, ward, village level) DADP Physical and finicial quarterly progress reports Outcomes: Production, yields,number farmers using improved technologies Outputs: Area under irrigation, number of VEO trained etc. District reporting Individual project activities and performance (at group level) Input Input Output Outcome Out put Out Come Other projects/interventions in agric (NGO,CSO, etc) Private investment in the agric sector Specific technical reports/studies (livertock/crop disease,price monitoring,food forecasting, etc. Agric. Routine Data System (ARDS) Integrated Data Collection Format (LGMD2) VAEO/WAEO format AGRICULTURAL SAMPLE SURVEYS National Sample Census for Agriculture (NSCA) - 10 years + Annual Agricultural Sample Survey (AASS - 1 year) + Other: National Panel Survey... Consolidation in Regional quaterly fin & phys. progress reports DADP (incl DIDF) Quaterly physical and financial progress report M&E TWG 457. One of the lessons learnt from ASDP-1 was that the delays in implementing key surveys, such as the NSCA, which was meant to inform many outcome indicators, led to a deficit in the information available to properly monitor and evaluate the results of the first phase. In consequence, it was ‘easy’ to assert that ASDP-1 had not achieved its results, that there had been no “impact” and that resources were spread too thinly. Equally, the planned annual services delivery surveys that would have given regular estimates of intermediate outcomes such as adoption of improved technologies were not implemented, and this proved to be a serious gap. This pointed to the need to ensure that national surveys have sufficient resources to provide necessary analysis and results on time, including annual surveys that provide critical annual performance assessments. It also points to the fact that there should be a clear separation of use of M&E as a tool to track reform processes, as well as measuring conventional benefits such as production and technology adoption. 217 Agricultural Sector for Industrial Development Monitoring and Evaluation 458. Monitoring. To monitor ASDP and performance of the agricultural sector, two data collection systems were developed under ASDP-1: (a) the Agriculture Routine Data System (ARDS) for monitoring the performance of the sector, and (b) the DADP physical and financial quarterly progress reports regarding Basket Fund resources. 459. The ARDS is designed to provide district and regional level agricultural data to ALSMs on a quarterly basis. Village and/or ward agricultural extension officers (VAEOs/WAEOs) are required to submit monthly, quarterly and annual reports to their district agriculture and livestock development officers (DAICOs and DLFOs). They review the reports and aggregate the data to the district level. District reports are forwarded to regional secretariats, where they are reviewed and approved by regional agricultural officers, before submission to ASLMs. Compliance with the reporting mechanism will be monitored by the M&E specialist of the CMT. With JICA support, the Routine Data System has been consolidated and linked to a web-based database, using custom-made software called Local Government Monitoring Database (LGMD 2)151 that allows the data to be entered electronically at the district level and forwarded through subsequent approvals process. The aim is to replace the many existing different reports at district level into a single integrated format. However, data at village and ward level is still collected manually on paper. Figure A24, sourced from ARDS review report). Figure A25: Agriculture Routine Data System Region District Ward Village ASLMs Flow of data Report format Means of data delivery Agricultural Routine Data System (ARDS) VAEO/ WAEO Format Format for Integrated Data Collection LGMD2 Hard Copy 460. While ARDS is supposed to deliver agricultural sector information from grassroots (village level) to districts and to ASLMs through regions every quarter, this system has not been functioning properly. However, the introduction of the LGMD2 is expected to improve this, as reporting forms, and flows are standardized and codified, through a web-based database. 461. With JICA support, guidelines have been prepared for VAEO and WAEO on how to systematically collect the data required152. However, one reason ARDS is too complex, is the fact that monthly, quarterly and annual reports monitor different variables. Monthly variables include weather conditions, 151 LGMD2 is new version of the former LGMD system that was developed by PMORALG as a single database to capture assets and activities for the key poverty sectors. LGMD has been abandoned by the other sectors. 152 Training guide for LGA, dated February 2011, includes training for VAEO and WAEO sector reports, and guide for district officers on data consolidation, analysis and feedback. 218 Agricultural Sector Development Programme II (ASDP-II) crops prices, crop disease report and pesticide applied, number of animals slaughtered, meat and milk inspections, animal health (vaccinations and treatments) and livestock services (Artificial insemination, etc.). Quarterly variables include number of farmer groups/members, number of farmers trained, area under irrigation, area cultivated and crop yield and production. Annual variables include population data, instances of contract farming, area irrigated, number of IO, asset inventory of agriculture machinery and tools, number of FFSs, use of fertilizer, chemical, seeds, livestock population, livestock infrastructure, information on grazing land area. The Monitoring responsibilities at local level are as shown in table A2. Table 62: Monitoring responsibilities at local level VAEO/WAEO Monthly Report VAEO/WAEO Quarterly Report VAEO/WAEO Annual Report 1. Introduction (weather condition, activity summary) 2. Crop: Planted Area, Yield, Production and Prices 3. Plant Health Services 4. Livestock Slaughtered 5. Meat Inspection 6. Livestock Products 7. Livestock Health 8. Achievements and Challenges 9. Visitors 1. Village Food Situation 2. Farmers Groups/ SACCOs 3. Extension Services 4. Biological Control Measures 5. Irrigation (planted area, production, etc.) 6. Soil Erosion 7. Area Cultivated and Means of Cultivation 1. Introduction (Population and number of households) 2. Irrigation (water source, area, IO members, etc.) 3. Contract Farming 4. Agricultural, Livestock and Fishery Machines 5. Extension Services (FFS) 6. Input Use 7. Livestock Population 8. Livestock Infrastructure 9. Rangeland 10. Pasture 11. Area covered by TV, Radio and Telecommunication 462. As can be seen, some of these variables (e.g., productivity and technology adoption) should not be captured by a decentralized administrative data collection system, given that the system is open to stakeholder influence in the results obtained from the various data collection efforts. ARDS relies on VAEO/WAEO to provide the information, yet many posts are currently vacant, and VAEO/WAEO often have mobility challenges, thereby relying on village headman to provide the information. 463. In view of the potential overlap between ARDS and some national agriculture surveys, regarding the performance of the agriculture sector (foremost the production and productivity figures), a recommendation was made by a visiting statistics mission that ARDS focuses on a reduced number of indicators that are best captured through an administrative system, on a “need to know”, and not “nice to know” basis153. While there is widespread consensus that the ARDS should focus on a reduced number of variables that can be easily captured at local level, this aspect was not satisfactorily addressed during the ARDS review conducted in late 2012154, before ARDS roll-out. Unfortunately, the list of indicators was left untouched. 464. The roll-out of the ARDS was completed in March 2014, covering all 25 regions. However, the reliance on heavy paper forms at ward/village level is costly and may prove unreliable. More modern techniques, such as hand-held computers are proposed under ASDP II to assist the system to serve its purpose. After completing the national roll-out, ARDS has been officially authorized as a data collection system for the agricultural sector through a notification from the then PMO-RALG to the District Council/Coordinator, with a request that an aggregated ARDS report be submitted electronically on a quarterly basis. 465. The DADP quarterly financial and physical progress reports have been supported by the ASDP P&I TWG. DADP preparation and implementation guidelines were prepared in June 2006, with support from the JICA-financed capacity development project. The objective of these guidelines is to serve 153 USDA Agricultural Statistics mission to Tanzania, Assessing Capacity for Agricultural Data Collection and Analysis in Support of Feed the Future July 2011. 154 Assessment of the Improved Agricultural Routine Data System, Arun Srivastava et al, December 2012. 219 Agricultural Sector for Industrial Development as an operational manual for the implementation of the Local Level Support Component of ASDP, for implementation of DADP. The TWG also prepares the Annual District Agricultural Development Plans (DADPs) Quality Assessment Report, which examines whether the DADP for the next three years has adhered to the established guidelines as well as the DADP Implementation Report using carried over funds. 466. A spreadsheet was prepared by PO-RALG to compile information disaggregated by district, regarding individual projects approved in each district and financed by ASDP. These projects are part of the DADP, which is a three-year rolling plan. District staff contact project beneficiaries or the extension officer to have updated information regarding the implementation of the project (interventions, output indicators, comparing targets and actual). Financial expenditure is captured at district level, since each “project” has its own bank account. 467. Projects include small irrigation schemes, dip tanks rehabilitation, FFSs, etc. The spreadsheet monitors 70 different types of projects and provides the number of beneficiaries for each project. The spreadsheet also tracks the unspent balance at the end of each year, and the carry over funds needed to complete a specific project. The information is consolidated into a summary sheet that allows tracking by type of intervention, and allows you to add-up the intended beneficiaries, as well as the financial support per type of intervention. 468. Although efforts have been made, DADPs contain a limited depth of strategic vision for agricultural development at district level and do not provide a comprehensive picture of agriculture sector activities implemented at district level. One reason for the limited nature of DADPs, especially for the second limitation would be that LGAs considered DADPs as a budget application tool for DADP funds. However, there have been attempts to provide a more comprehensive plan, including information from other government and non-government resources. 469. This system naturally focuses on outputs delivered through the various interventions, however, because of the view that it would be important to capture and aggregate outcome information at project level, to be able to show the results that ASDP is achieving. Based on this, a separate spreadsheet has been prepared to provide information on project/intervention at outcome level. 470. The outcome spread sheet focuses on crop and livestock productivity and production increase, crop and livestock value addition, and accessibility to financial services, all of this at individual “project” or intervention level, however, it has not been rolled-out yet. 471. It is questionable whether this approach would make sense. The same concerns regarding possible stakeholder influence on the results obtained from this data collection effort. Outcome level information is normally best captured through surveys or studies, and not through administrative reporting systems. There was confusion during the ASDP—monitoring between the project-specific and sector-wide outcomes data collection. Because of clear connection to budgets, the project-specific outcomes received in general more attention than sector-wide outcomes, resulting in relatively weak development of ASDP Sector-wide monitoring. However, it is recognized that the ASDP II M&E system must maintain a strong link to budgetary and allocation monitoring requirements. Statistics 472. The Tanzanian government uses various surveys and censuses to obtain information for agriculture and food security policy and planning decisions. The key institution is the National Bureau of Statics (NBS, www.nbs.go.tz). 473. The Tanzania Statistics Master Plan (TSMP) was prepared for the period 2010–2014, to ensure improved coordination, raise statistical awareness and produce good statistics. It provides a national framework for the development of the national statistics system in the country. Coordination includes sectoral working groups. It includes agricultural statistics component, which only covers the National Sample Census for Agriculture. The TSMP includes a budget of USD 64 million over 5 years and a Basket Fund mechanism supported by various donors (World Bank, Department for International 220 Agricultural Sector Development Programme II (ASDP-II) Development (DFID), Canadian International Development Agency (CIDA)). 474. Tanzania is one of the countries included in the FAO-led Country-STAT initiative. In this context, a TWG has been established and comprises national experts from various institutions to review and harmonize existing data. The major sources of agricultural data and their frequency are presented in Table A3: Table 63: Key surveys and census for agriculture data155 Name Characteristics Last conducted Expected frequency National Sample Census of Agriculture Covers a wide range of variables, including number of households engaged in Agriculture, sources of income, area planted to crop, crop and livestock production and productivity, marketing and storage, irrigation and input use, access to extension services and credit, inventory of assets, food consumption. Sample size of 50,000 households, provides data at district level. 2002/2003 2007/2008 5 years7 National Panel Survey Is in fact the Living Stands Measurement Study sponsored by the World Bank in many countries. Monitors progress on standards of living, and assesses impact of policies on households. Contains a module on agriculture and focuses on poverty. Sample size of 3,200 households, only allows for national estimates for rural Tanzania. Bridge between two Household Budget Surveys 2008/2009 2010/11 Every 2 years Household Budget Survey Data from the Household Budget Surveys is used to track progress resulting from the government’s poverty-reduction policies. Provides official source of poverty determination in Tanzania 2001/2002 2007/2008 2011/2012? 5 years National Population and Housing Census Provides the population figures, and includes some information on agriculture. Results are just being made available. Total population of Tanzania is 45 million. 2002/2003 2012/2013 10 years The above surveys provide the following strategic implications for enhancing the effective design and use of the M&E system to support ASDP II: 475. Due to funding limitations, the national surveys have been providing inconsistent results and at infrequent intervals. The NSCA 2007/2008 national and regional results were made available in July 2012 and the 2012/2013 edition has been postponed to 2015/2016. The results for NPS 2, conducted in 2011 were released in September 2012. 476. A recent USDA Agriculture Statistics mission mentioned that: ‘despite the importance of agriculture in the economy, agricultural statistics is not included in the core statistics, nor is it funded under the TSMP. Most of the data collection activities are donor-driven and donor-funded. Without adequate funding in the national budget to support key agricultural data collection activities, sustainability cannot be achieved’156. Additional constraints regarding the statistics system in Tanzania include unknown level of data accuracy, large inconsistencies in time series and discrepancies among various data sources, insufficient coordination and harmonization of data collection methods and instruments, lack of updated sampling frame, insufficient staff and lack of technical capacity and dependency on donor funding157. 477. In view of the above, USDA has been collaborating with FAO, the World Bank and other countries’ 155 The 5-year interval is the old setting for the National Sample Census of Agriculture. In the current ASSP it has been set to be 10 years. 156 USDA Agricultural Statistics mission to Tanzania, Assessing Capacity for Agricultural Data Collection and Analysis in Support of Feed the Future, July 2011. 157 Aide Memoire Joint FAO/USDA mission 26 March–05 April 2012. 221 Agricultural Sector for Industrial Development national statistical offices and ministries of agriculture on the development of the Global Strategy to Improve Agricultural and Rural Statistics158. An initiative of the UN Statistical Commission, the Global Strategy is a response to the declining quantity and quality of agricultural statistics worldwide. The Strategy provides a comprehensive framework to ensure the sustainability of agricultural statistics, and addresses emerging data needs. AfDB provides the RS for this initiative. 478. Two joint missions conducted by FAO, USDA and AfDB under the auspices of this initiative were fielded in January 2012 and March 2013159. The outcome of these missions was to develop a proposal to improve agricultural statistics in Tanzania, as defined in the Global Strategy. Elements of the proposal include: (i) update the ASSP; (ii) strengthen ARDS; (iii) develop sampling frame and sample design appropriate for generating agricultural statistics; (iv) design and implement an annual agricultural sample survey; and (v) build capacity to support agricultural statistics. 479. ASSP, which was prepared by the NBS in collaboration with ASLM, with technical support from FAO, defines the appropriate programme for fulfilling agricultural data needs using government resources, given due consideration to the frequency, level of aggregation, and level of precision required by data users. It also identifies appropriate data collection methods for each element of the system, then prioritize activities and identify resources needed for implementation. The resulting plan should link to the Global Strategy framework, and must be mainstreamed into the TSMP, and is contingent on GoT Resources being made available for implementation. 480. The AASS aims to provide timely and reliable crop and livestock production data on an annual basis. The recommendation from the joint mission was to focus on national and regional estimates for 8–10 crops and 3–5 livestock species. USDA is providing technical assistance to NBS and ASLM in this matter, and promoting an area-based sampling frame, using satellite imagery to identify spots, the higher the cropping intensity, the larger the number of spots, and then follow-up with interviews of the household farming that spot. The intent is to use GPS devices and hand-held electronic devices to speed up field data collection processes and ensure improved data accuracy. A first pilot survey was implemented in 2013, and a second one in 2014. The final report is expected to start rolling-out in 2015 or 2016 (depending on implementation of the National Agricultural Census). 481. The concern is to keep the questionnaire short; however, it is important to capture indicators of adoption of improved technology and access to strategic services (e.g., rural finance etc.), that should have been collected annually under ASDP-1 M&E framework. These will also be important outcome indicators in the Results Framework of the ASDP II. Another concern is whether an area sampling frame is the best approach for an African farming context characterized by small plots, multi-cropping and shifting cultivation and extensive livestock areas. This also represents a break from the normal list sampling frame, with enumeration areas, which NBS is familiar with. Moreover, the cost of this methodology is apparently likely to be high, given the sample that it is expected to cover. These aspects require further discussions with NBS, ASLM, FAO and USDA. 482. To prepare the ASSP, an Agriculture Statistics Task Force consisting of a team of agriculture statistics experts has been established under the coordination of the TSMP Sector Working Group on Agriculture. A coordinator from NBS has been designated, and other members include statisticians from ASLM, to be released under a formal memorandum of understanding mechanism to work on priority activities. FAO has recruited a national consultant to act as the resident officer to follow-up on all the elements of this programme and support the Task Force, as well as an international consultant to provide support specifically on the ASSP preparation. The TSMP Agriculture Sector Working Group will supervise the work of the Task Force. 483. Before investments are made to improve agricultural statistics, donors wanted to clarify whether the government considers agricultural statistics a priority by including these among the core economic indicators and making necessary provisions in the national budget. This point was clarified during the 158 More information on the Global Initiative to Improve Agriculture Statistics in Africa can be found at http://www. fao.org/fileadmin/templates/ess/documents/meetings_and_workshops/ICAS5/Ag_Statistics_Strategy_Final.pdf. 159 Aide Memoire Joint FAO/USDA/AfDB mission, 28 January–01 February 2013. 222 Agricultural Sector Development Programme II (ASDP-II) second mission, when various high-ranking officials from NBS, Ministry of Finance, and the PMO confirmed that the Government of Tanzania is fully committed to improving agricultural statistics and willing to provide all the support needed. All parties stressed that NBS should lead the process, in accordance with its mandate in the Statistics Act, with national staff in the driving seat. Additional support should be built around already existing systems and procedures. ASDP II Monitoring and Evaluation support under ASDP II. 484. The objective of this sub-component is to ensure that there is an improvement in the timeliness, quality and relevance of available statistics and data in the agriculture sector, to provide the data needed to monitor the performance of the ASDP II, starting with the indicators contained in its results framework. The results framework is provided in Annex II, and contains indicators such as farmers’ income, crop yields, value of produce/exports, area under improved technology, area irrigated, etc. Under this sub-component, support will be divided in two thematic areas: (i) dedicated ASDP II Agricultural Sector Monitoring and Evaluation support; and (ii) support to agricultural statistics and other sector related M&E efforts. The M&E specialist within the NCU will manage the M&E processes and ensure that they are conducted by NBS on schedule and in compliance with the terms of reference for the work. The M&E specialist will collaborate closely with the NBS on the construction of the monitoring templates to be used in the surveys. 485. Baseline and final survey. Given the uncertainty concerning the frequency, scope and funding of agricultural surveys, such as the NSCA, implemented through NBS, a specific baseline survey will be implemented aligned with 2014/2015 season to provide baseline data regarding the variables identified in the results framework. It will focus on ASDP II selected priority districts. 486. A total sample size of approximately 5,000 households is envisaged, in approximately 30 districts. This should be large enough to allow for information to be disaggregated by district. The sampling frame and questionnaire will be established in collaboration with the NBS, and will be based on the outcome of the Agricultural Statistics Strategic Plan, which foresees revisiting and improving current Sampling Frames & Sample Designs used for 2007/2008 NSCA and the 2012/2013 Population and Housing Census, to improve the definition and selection of enumerators areas. The use of a common sampling frame should allow comparison between the ASDP II baseline survey results, and the next NSCA results. 487. The sampling frame will also include non-beneficiary households with similar characteristics to those receiving ASDP II support, either in the same districts, or in neighbouring ones. This larger sampling frame will allow the completion of an impact evaluation, by comparing changes between households benefiting from ASDP II interventions, and those not benefiting from these changes. A final survey for the ASDP II will be harmonized with the NSCA and the AASS undertaken during the last year of the project, and will use the same sampling frame, and, to the extent possible, will try to visit the same households, through a panel survey. 488. It has been envisaged that the actual implementation of the baseline and final surveys would be contracted out to a reputable organization, either an academic institution or a private company through a competitive tender. However, the experience of ASLMs with contracted organizations has been disappointing and it is therefore proposed that the survey be conducted by NBS staff, but with oversight from an independent academic institution. Short-term enumerators will be hired for these two surveys, and will be supervised by NBS regional office staff. The use of portable electronic devices will be facilitated, so as to speed up data entry and cleaning, and disseminate the results rapidly. The questionnaire will be prepared in close collaboration with the Agriculture Statistics Task Force and the ASDP M&E Thematic Working Group. The baseline and final surveys are estimated to cost a total of TZS 4.8 billion (USD 3 million), or approximately USD 1.5 million each. 489. Intermediate outcome surveys. To allow tracking of key performance indicators identified in the 223 Agricultural Sector for Industrial Development results framework, intermediate outcome indicators will be evaluated yearly between the baseline and final surveys, so as to provide useful feedback regarding the implementation of the ASDP II. The intermediate outcome data will be derived from AASS, which will be expanded for the purpose from its exclusive collection of crop and livestock productivity and production statistics. The cost of the annual survey for intermediate outcome indicators is estimated to total TZS 2.4 billion. There should be a mid-term revision of the results framework (as part of ASDP II) to adjust actual performance of the M&E of ASDP II. Support to agricultural statistics and sector M&E efforts 490. Based on the Global Strategy to Improve Agricultural and Rural Statistics, promoted in Tanzania by USDA, FAO and AfDB, and based on the ASSP being developed by the Agriculture Statistics Task Force, this sub-component will include the following activities: (i) co-financing of the National Sample Census Survey for Agriculture (NSCA-2015/2025); (ii) financing of AASS during 2015–2024); (iii) strengthening the Agricultural Routine Data System (ARDS); and (iv) limited support to the M&E Technical Working Group, over the same period. 491. National Sample Census for Agriculture (NSCA). Given that ASDP II will be one of the few large- scale projects providing financing in agriculture through the public sector over the coming years, and given that financing for agricultural statistics is an ongoing discussion under the aegis of the Global Strategy to Improve Agricultural and Rural Statistics, several partners, including the government, have expressed their interest for the ASDP II to provide financing for the NSCA. NSCA is considered as the key survey for the sector and its regular implementation would go a long way in providing a common national system to all projects operating in the sector in Tanzania. 492. It is envisaged that the NSCA will be held every 10 years, and will provide district-level statistics on a wide range of variables, based on a sample size of 50,000 households. The next NSCA is due to take place in 2016 (for the agricultural season 2015/2016). Given its high cost, around 10 billion TZS, it is hereby proposed that ASDP II will contribute for about 50% of this cost, while the balance will be co-financed by the Tanzania Statistics Master Plan (TSMP) Budget Support Fund. 493. Annual Agriculture Sample Survey (AASS). The ASSP being developed by the Agriculture Statistics Task Force foresees that the AASS will provide annual, regional level, production and productivity statistics for main crops and livestock species. The annual cost and the final questionnaire of the AASS has not yet been finalized, but will be consolidated at the end of the programme piloting (2014). 494. There are ongoing methodological discussions regarding whether this will be an area-based sample or a list-based sample, or a combination of the two. These discussions are taking place in the framework of the Agricultural Statistics Task Force, between NBS, ASLM, and specialized technical assistance in statistics from USDA and FAO. This group includes statisticians from MAFC, and MLFD, is chaired by the NBS, and will also be responsible for preparing the questionnaire. Based on the cost of the pilot, which is foreseen to take place in 2013 and 2014, the AASS annual cost has been estimated at 1.6 billion TZS. 495. Given that the TSMP is unlikely to provide financing for this annual survey, and given that this annual survey would allow the sector to have reliable production and productivity estimates, albeit at regional level (discussions are ongoing to look at opportunities for enhancing data reliability to district level), the ASDP II should provide the financing for this annual survey. However, there are concerns about the current statistical methodology being advocated by USDA, which would need to be discussed with the ASDP M&E TWG and ASCG. 496. Agricultural Routine Data System (ARDS). One of the key Management Information Systems that has been developed under ASDP-1 is the ARDS. Many resources have been invested to build a national web-based database with information disaggregated at the district level, to clarify data flow 224 Agricultural Sector Development Programme II (ASDP-II) and approval, and to develop data format, procedures for data collection at village and ward level and data dissemination, from district to national level. JICA has provided long-term technical assistance and capacity building support to national ARDS rollout, which will lapse in 2015160. This system provides data on the performance of the agriculture sector, and relies on front-line extension staff to provide monthly, quarterly and annual information, which is compiled at district level and entered into a web-based database, and made available to ASLM through RSs and PO-RALG. 497. A recent review has identified which variable can be collected with some reliability at village and ward level161. However, this review fell short of ensuring that there is no overlap between the ARDS and other data sources, such as the AASS and NSCA, as recommended by the Joint USDA/FAO/ AfDB mission held in 2012. 498. The Agricultural Statistics Strategic Plan (ASSP) envisages that the ARDS should be further streamlined, and focus on information that can reliably be reported by front line extension staff, but recognizes the usefulness of having a Management Information System for the sector. ASDP II will finance an ARDS review, in year 1, to assist the M&E TWG in ensuring that it is better integrated to the other data collection systems, and that the information it provides is more comprehensive and accurate. In addition to this study, the ASDP II has made a provision to finance the implementation of the ARDS, while local governments make a provision in their budget to provide that type of recurrent expenditure. 499. Cost for routine implementation of the ARDS has been estimated to be approximately 6 million TZS/ district/year based on the assumption that one LGA has on average 15 wards. Recently, however, many LGAs increased the number of wards and thus have more than 20 wards per district. Under the assumption of 20 wards per LGA, expected costs for a LGA per year would be TZS 8 million. Total cost would thus be TZS 1.20 billion per year or TZS 6.00 billion over the 5 years (respectively USD 0.74 million/year and USD 3.7 million for the whole period). This budget includes allowances for the district M&E officer to travel (4 days a month), as well as fuel and bicycle maintenance for the WAEO and the VAEO respectively, stationery for both, distribution costs of the reports (bus fare), and printing and photocopying costs for the paper questionnaires used. 500. M&E Technical Working Group. The M&E TWG compiles the ASDP Annual Performance Report, which provides an update on all key performance indicators, at impact, outcome and output level162 and participates in the JIR, which undertakes an annual assessment of progress made under ASDP, and also results in a report163. ASDP II will make a provision to support the M&E TWG in its activities. This support has been budgeted at about TZS 100 million per year. Proposed mode of M&E coordination under ASDP II 501. Given the environment of ASDP II where multiple actors implement their respective interventions and projects, the ASDP II M&E needs strong coordination ability and data processing (collection, compilation, analysis and reporting) capability. 502. Although the institutional arrangement of ASDP-1, i.e., both M&E TWG and P&B TWG, may remain in ASDP II, two additional features must be added to strengthen their working capacity: (i) authority above both TWGs to manage them together; and (ii) small group (two to three officers) from M&E, Statistics and IT units at each ASLM who are committed to and are exclusively responsible for day- to-day operation and data processing tasks. The former assures efficient and effective coordination among various data collections, while the latter enables ASLMs to extract proper information out of wide range of data. 160 Agricultural Routine Data System (ARDS) National Roll-Out Plan, ASDP M&E TWG, 2010. 161 Assessment of the improved Agricultural Routine Data System, Arun Srivastava et al., December 2012. 162 ASDP Annual Performance Report 2009/10, March 2011; ASDP Annual Performance Report 2010/11, November 2011; ASDP Annual Performance Report 2011/12, Draft in progress, April 2013. 163 Seventh Joint Implementation Review Report, 5 May 2012–18 June 2012. 225 Agricultural Sector for Industrial Development 503. In the coordination at the central operational level, the scope of coordination will be greatly expanded in ASDP II by including NBS and representatives of parallel interventions/ projects/programmes. In order to secure effective M&E under ASDP II, regular (probably quarterly or by-monthly) coordination meeting is required, which would be facilitated by the M&E specialist of the CMT who would convene the meetings. These meetings should be attended by the dedicated Statistics and IT unit members of the ASLMs, and non-state actors such as farmer organizations, and MUVITA among others who should demand to be informed of progress. Reports on the state of data collection and overall state of the sector should be submitted to the coordination meeting to track the M&E activities under ASDP II. Such reports as well as actual M&E data should be widely disseminated through websites or any other means for the accountability of the programme. 504. In order to bridge the information gap on agricultural investments and improve coordination, in 2013 Bill and Melinda Gate Foundation (BMGF) contracted the University of Dar es Salaam Business School (UDBS) to collect comprehensive agricultural investments data under Tanzania Agricultural Investments Mapping (TAN-AIM) Phase 1 and II Project (2013 - 2017). The project focused on improving the information flow of all agricultural investments and closing the knowledge gap within the sector by understanding linkages between relevant stakeholders. The project was expected to: (i) close the information gap and improve information sharing; (ii) develop linkages, partnerships, create synergies, and avoid overlaps/duplications among stakeholders; (iii) improve coordination and collaboration among partners and stakeholders in the sector; (iv) enhance efficient and effective utilization of resources ad (vi)support in capacity building for GoT staff for sustainability. The project has provided data on who is doing what, where and with whom along the agricultural value chain. The project was expected to collect investment data from GoT, DPs, Private Sector and NGOs/NSAs. The project managed to develop TAN-AIM online mapping tool (TMT) with agricultural investments data collected from Development Partners (DPs) Agricultural Working Group (AWG) and Private Sector Development (PSD) and Trade working groups as well as the Government of Tanzania (GoT) through the implementation of ASDP I. Private sector and NGOs/NSA did not provide the data, Also agricultural investments data could not be collected at local level (LGAs) due to poor data record management and lack of integrated system to capture these information from village to district level which affects the quality and accuracy of data. To improve coordination, monitoring, and development of synegies and partenrships among stakeholders the Tanzania Agricultural Sector Mapping Tool (TANAIM) should be updated. Figure 25 below presents Development Partners (DPs) support in various value chains and commodities/products. Agricultural Sector Development Programme II (ASDP-II) 226 Figure A26: Development Partners’Contribution by Focus Area and Value Chains in Crop Sub-Sector. Agricultural Agricultural Productivity Maize Cotton Tea Coffee Paddy Cassava Sunflower Sugar Vegetables Fruits Pulses PostHarvest Safety Net Research and Ex tension Infrastructure Training & Capacity Building Agricultural Services Information Technology Emergency Preparedness Policy Reforms Nutrition Natural re source Management UNDP U USAID DFID FAO JICA WFP AfDB FAO DFID IFAD EU USAID Sweden D F I D EU AfDB AfDB DFID DFID SDC FAO c EU FAO AfDB SDC UNDP EU FAO DFID SDC UNDP SDC SDC SDC FAO SDC Sweden SDC DFID EU Sweden Sweden Sweden EU SDC SDC I r i s h A i d Irish Aid AfDB SDC SDC SDC AfDB AfDB UU S A I D AfDB AfDB AfDB AfDB IFAD SDC IFAD SDC AfDB AfDB I L O U S A I D Agricultural Sector Development Programme II (ASDP-II) 227 Figure A27: Development Partners’Contribution by Focus Area and Value Chains in Livestock and Fisheries Sub-Sector Agricultural Productivity Poultry Bee Keeping Cattle Fish Post Harvest Safety Net Research and Extension Infrastructure Training & Capacity Building Agricultural Services Information Technology Emergency Preparedness Policy Reforms Nutrition Natural resource Management AfDB AfDB AfDB DFID SDC SDC UNIDO ILO IFAD Irish Aid DFID SDC DFID EU JICA FAO FAO FAO 228 Agricultural Sector Development Programme II (ASDP-II) Table 65: Short-listed impact, outcome and output indicators for the ASDP-1 p , p Indicators Frequency Disaggregation Data source District Region National Impact (IM) 1. Real GDP growth rate per annum [MKUKUTA] Annual √ NBS 2. Headcount ratio in rural areas – basic needs poverty line [MKUKUTA] Periodical √ √ NBS (HBS) 3. Value of agricultural exports Annual √ TRA Outcome (OC) 1. Food self-sufficiency ratio [MKUKUTA] Annual l √ √ MAFC 2. Production and productivity of crops and livestock. Periodical √ √ √ NBS (NSCA) 3. Proportion of smallholder households using improved technologies Periodical √ √ √ NBS (NSCA) 4. Flow of private funds into agricultural and livestock sectors Annual √ √ TIC 5. Proportion of smallholder households using mechanization Periodical √ √ √ NBS (NSCA) 6. Ratio of processed exported agricultural products to total exported agricultural products Annual √ TRA 7. Proportion of smallholder households participating in contracting production and out- growers schemes [MKUKUTA] Annual √ √ √ LGAs 8. Proportion of LGAs that qualify to receive top- up grants Annual √ PMO-RALG 9. Proportion of LGAs that qualify to receive performance bonus Annual √ PMO-RALG Output (OP) 1. Number of agricultural production infrastructure Annual √ √ √ LGAs 2. Number of agricultural marketing infrastructure and machinery Annual √ √ √ LGAs 3. Number of extension officers trained on improved technological packages Annual √ √ √ LGAs 4. Value of loans provided by SACCOs for agriculture Annual √ √ √ LGAs 5. Number of agricultural marketing regulations and legislation in place Annual √ MITM, MAFC, MLDF 6. Number of markets where wholesale or retail prices are collected Annual √ MITM 7. Number of Inter-Ministerial Coordination Committee (ICC) meetings held Annual √ ASDP Secretariat 8. Proportion of quarterly progress reports submitted on time Annual √ √ √ Regions, ASLMs 9. Proportion of female members of Planning and Finance Committee Annual √ √ √ LGAs Note: Indicators with [MKUKUTA] are from the Poverty Monitoring Master Plan. 229 Agricultural Sector for Industrial Development ANNEX VI: Financial and Economic Analysis 1. Introduction 505. A financial and economic analysis was undertaken to assess the viability of the investments proposed for ASDP II. The main project interventions include: (i) rehabilitation and expansion of irrigation infrastructure; (ii) expansion of watershed management and conservation agriculture, (ii) development of water resources for livestock and fisheries, (iii) expansion and upgrading of agricultural research, extension and training services, (iv) improved access to agricultural inputs and machinery (including input subsidies); (v) development of farmer organizations and improved access to markets and rural finance; (vi) agribusiness development and enhanced value addition; and (vii) strengthening of policy/ regulatory framework and institutional capacity; (viii) improved food security and nutrition (including NFRA grants); and (ix) sector co-ordination and M&E. 506. The main economic benefits of these interventions are expected to be: (i) increased crop production through improved crop yields, higher cropping intensity, and diversification to higher value crops; (ii) enhanced livestock and fish production, (iii) higher farm incomes from agricultural production, (iv) increased income from agribusinesses and greater value addition, and (v) higher export earnings. Crop Production 507. Investments in land and watershed management, as well as conservation agriculture, will help to ensure that increases in crop production are sustained in areas which are vulnerable to soil erosion and declining soil fertility. In addition, it is estimated that the improved irrigation infrastructure will benefit an irrigable area of 461,326 hectares, and 100,000 hectares of existing irrigation schemes which will be rehabilitated under ASDP II. 508. Following the provision of agricultural support services, improved land and watershed management, as well as the expansion and rehabilitation of the irrigation infrastructure, the present overall cropping intensity of 92% is projected to rise to around 103% for 2,165,000 ha of cultivated land. For irrigated land, cropping intensity is expected to rise to 135% while, for non-irrigated land, the cropping intensity is assumed to increase from 90% to 100%. 509. With regard to improved crop productivity, it is anticipated that the average yields of paddy rice would rise from 1.75 tons/ha to 3.0 tons/ha. For maize, oilseeds/pulse and vegetables, the corresponding increases are 1.35 to 2.20 tons/ha (maize), 1.0 to 1.4 tons/ha (oilseeds/pulses), and from 15.0 to 20.0 tons/ha (vegetables). 510. This increase in overall crop production within the ASDP II area will lead to a notable improvement in the net farm incomes of smallholders. Furthermore, there will be an increase in income and employment opportunities resulting from an expansion of processing, transport and marketing of crops and crop by-products. Livestock and Fisheries 511. The development of water resources for livestock and the provision of support services are expected to result in an increase in livestock productivity. Currently, livestock are a source of a wide range of products including milk, meat, and manure as well as cash income, but productivity is very low. In the future with project situation, increases in livestock productivity will primarily arise from the adoption of improved pasture management and better livestock husbandry practices particularly with respect to nutrition and animal health. This will notably improve milk yields and enhance the efficiency of meat production through better live weight gains. The proposed fisheries interventions are primarily aimed increasing aquaculture production through the expansion of fish ponds as well as improved support services. This will enhance the livelihoods of rural communities engaged in fish production and marketing. 230 Agricultural Sector Development Programme II (ASDP-II) Farmer Organizations, Marketing and Agribusiness Support 512. ASDP II includes measures to expand farmers’ access to rural markets, improve marketing systems and provide support to agribusinesses. These interventions are likely to provide significant economic benefits, such as enhancing CVCs, increasing value addition, and improving the income and employment opportunities of agribusinesses engaged in the transport, storage, processing and marketing of agricultural produce. However, the economic benefits of these interventions have not been quantified in the economic analysis. 513. Furthermore, due to the large annual and seasonal variations in agricultural prices, the possible increase in farm gate prices (resulting from better access to markets and improved efficiency of the marketing systems) has not be taken into account in the financial analysis. 2. Financial Analysis Crop Budgets 514. A financial analysis was undertaken to assess the likely impact of ASDP II interventions on farm incomes. Four budgets were prepared to represent the main crops grown in Tanzania, namely maize, rice, oilseeds/pulses and vegetables. Crop budgets were prepared for the present, future without project, and future with project situations. 515. With regard to the future with project situation, the consultant estimated the expected crop yields and input usage, as well as the labour and machinery requirements for field activities. Increases in crop production will mainly arise from the provision of irrigation facilities as well as the adoption of improved crop production techniques by farmers on both irrigated and non-irrigated land. Furthermore, an increase in crop inputs is also anticipated, together with the adoption of improved farm machinery, which will significantly enhance crop production practices within the ASDP II area. 516. The average crop yields used in the analysis for the present, future without and future with project situations are summarised in Table A5. It is envisaged that the future with project yield levels would be fully achieved within two years of completing the strengthening of agricultural support services, implementation of improved land and watershed management, as well as the construction of irrigation infrastructure envisaged under the programme. To ensure that these long-term improvements are sustained, agricultural support services have also been included in the long-term recurrent costs. Table A5: Crop yields in present, future without and future with project Average Crop Yields (tons per hectare) Present Future Without Project Future With Project Maize 1.35 1.50 2.20 Rice 1.75 1.95 3.00 Oilseeds/Pulses 1.00 1.10 1.40 Vegetables 15.00 16.50 20.00 Source: Crops Sector National Report (2012) and consultant’s estimates 517. In the future without project situation, it is expected that crop yields will gradually increase due to the adoption of improved cropping practices. It is therefore anticipated that there will be an increase in crop yields at the rate of 1% per annum. The average crop yields in the future without project situation (given in Table A5) reflects the expected levels of productivity after 10 years. 518. On the basis of the crop yields, crop inputs, produce/input prices, wage rates, as well as labour, oxen and machinery requirements, financial crop budgets in the present, future without and with project situations were prepared. By deducting production costs from crop revenues, financial crop gross 231 Agricultural Sector for Industrial Development margins were determined for each selected crop. In both the future with and without project situations, it has been assumed that farm gate prices (in constant terms) will remain unchanged from their present values. The financial crop gross margins are summarized in Table A6. Table A6: Financial crop gross margins in present, future without and future with project Gross Margins (TSh per hectare) Present Future Without Project Future With Project Maize 67,088 119,831 216,550 Rice 322,500 423,844 709,375 Oilseeds/Pulses 512,625 613,250 807,500 Vegetables 2,267,000 2,583,875 2,927,250 Source: Crop budget estimates 519. It is evident from Table A6 that, in the future with project situation, there is a significant improvement in the net returns for all types of crop. This reflects the notably higher yield levels which generate incremental returns in excess of the additional production costs. It is also apparent that the net returns per hectare from vegetables are substantially higher than the returns from maize, rice and oilseeds/ pulses. However, the attractive returns from horticultural crops are moderated by the risks associated with very large seasonal price fluctuations. Cropping Patterns 520. Present cropping patterns were determined for: (i) existing irrigated area, (ii) proposed irrigated area, and (iii) non-irrigated area under the programme. These cropping patterns are not expected to alter significantly in the future without project situation as only a small increase in cropping intensity is likely without an improved supply of irrigation water. 521. In the existing irrigated area, it is anticipated that the areas of rice, oilseeds/pulses and vegetables will increase in the both the wet and dry seasons as a result of ASDP II interventions. In the proposed irrigated area, there will be a significant change in cropping pattern (from rainfed to irrigated) with a major expansion in the area of rice in the wet season and the introduction of maize, rice, oilseeds/ pulses and vegetables in the dry season. The cropping patterns used in the financial and economic analysis are presented in Table A7. 522. In the existing irrigated area, cropping intensity is expected to increase from 125% to 135% while, on the proposed irrigated area, cropping intensity will rise from to 90% to 135%. For non-irrigated areas, cropping intensity in the future with project situation is estimated at 100%. Overall, the cropping intensity in the ASDP II area is expected to increase from 92% to 103%. The lack of an adequate and reliable supply of irrigation water will probably limit further increases in the cropping intensity during the dry season. Table A7: Cropping patterns and cropping intensity Crop Enterprise Present and Future Without Project: Cropping Patterns (% of cultivated area) Rehabilitated Irrigated Area New Irrigated Area Non-irrigated Area Overall Wet Season Maize 45 63 63 62 Rice 40 5 5 7 Oilseeds/Pulses 5 20 20 19 Vegetables 5 2 2 2 sub-total 95 90 90 90 232 Agricultural Sector Development Programme II (ASDP-II) Crop Enterprise Present and Future Without Project: Cropping Patterns (% of cultivated area) Rehabilitated Irrigated Area New Irrigated Area Non-irrigated Area Overall Dry Season Maize 15 0 0 1 Rice 0 0 0 0 Oilseeds/Pulses 10 0 0 0 Vegetables 5 0 0 0 sub-total 30 0 0 1 Cropping Intensity 125 90 90 92 Crop Enterprise Future with Project: Cropping Patterns (% of cultivated area) Rehab. Irrigated Area New Irrigated Area Non-irrigated Area Overall Wet Season Maize 30 30 67 64 Rice 50 50 5 8 Oilseeds/pulses 10 10 25 24 Vegetables 10 10 3 4 100 100 100 100 Dry Season Maize 10 10 0 1 Rice 5 5 0 0 Oilseeds/pulses 10 10 0 1 Vegetables 10 10 0 1 35 35 0 3 Cropping Intensity 135 135 100 103 Source: Crops Sector National Report (2012) and consultant’s estimate Livestock 523. The livestock component of ASDP II is expected to improve the productivity of different types of livestock enterprises such as dairy cows and beef fattening. Increases in livestock productivity will primarily arise from the adoption of better livestock management practices and improved nutrition. 524. In the financial analysis, budgets were prepared for two livestock enterprises, namely dairy production and beef fattening. The livestock outputs and inputs were valued in 2015 farm gate prices to derive financial gross margins for each of the enterprises (Table A8). In the future with project situation, the improvements in net returns primarily reflect the higher levels of productivity. 233 Agricultural Sector for Industrial Development Table A8: Financial livestock gross margins in present, future without and future with project Livestock Enterprise Financial Gross Margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 176,975 311,975 Beef Fattening 77,900 102,900 Source: Livestock budget estimates Farm Budget Analysis 525. Farm budget analysis was undertaken to determine the impact of the project interventions on farm incomes. The farm budgets were prepared for an average sized farm of 2.0 ha. Based on the cropping patterns given in Table A7, the crop areas were calculated and then applied to the respective financial crop gross margins in order to derive the likely net returns to farmers in the present, future without and future with project situations. The net returns from the livestock enterprises were then added to determine an overall farm gross margin. Following the deduction of fixed costs (e.g. land rent, equipment/farm tools), net farm incomes were obtained. A summary of the net farm incomes for the different ASDP II areas is given in Table A9. 526. It is evident from Table A9 that there are likely to be very significant increases in net farm incomes. Comparing the present and future with project situations, net farm income in the existing irrigated area is expected to increase from TSh 900,568 to TSh 2,665,228 (before irrigation O&M costs) while, in the non-irrigated areas, net farm income is estimated to rise from TSh 367,385 to TSh 1,158,275. Overall net farm income is expected to increase from TSh 436,699 to TSh 1,655,569 per annum. 527. When irrigation O&M costs are included, net farm income for the irrigated areas falls to TSh 2,229,994 per annum in the irrigated areas. However, as irrigation costs only account for about 16% of net farm income, farmers will have the ability to meet annual O&M costs. Table A9: Net Farm Incomes in Present, Future Without and Future with Project Irrigation Status Net Farm Income (TSh per annum) Present Future Without Project Future with Project Excluding Irrigation O&M Costs Including Irrigation O&M Costs Rehab. Irrigated Area 900,568 1,138,498 2,665,228 2,229,994 New Irrigated Area 367,385 496,902 2,665,228 2,229,994 Non-irrigated Area 367,385 496,902 1,158,275 Overall 436,699 580,309 1,655,569 Source: Farm budget estimates 3. Economic Analysis Economic Pricing 528. Economic prices for internationally traded goods (such as rice, maize, soya bean and fertilizers) were derived from the World Bank commodity price projections for 2015. These world prices were adjusted for sea freight, insurance and border charges, as well as local transport, handling and, if applicable, processing costs, in order to determine economic farm gate prices. 529. Local transport, handling, storage and processing costs were based on the current rates prevailing in Tanzania. However, these financial prices were converted to economic prices by applying the standard conversion factor (SCF) of 0.95. The SCF reflects the shadow exchange rate in Tanzania which is at variance with the official exchange rate due to distortions in the foreign exchange market. Economic prices for other non-internationally traded agricultural goods, such as vegetables and straw, were taken from the 2015 financial prices prevailing within the project area. 234 Agricultural Sector Development Programme II (ASDP-II) 530. Labour costs were based on the rural wage rates which varied according to the type of farm activity but averaged around TSh 5,000 per day for most farm operations. However, given the high levels of underemployment within the project area, a shadow wage rate of 0.65 was used to determine the economic value of labour. 531. The economic analysis was undertaken over a 50-year period in 2015 constant prices and a shadow discount rate (opportunity cost of capital) of 12% was assumed. The Tanzania shilling was used as the unit of account and an exchange rate of TSh 2,150 to USD 1.0 (June 2015) was applied when converting to USD. It was anticipated that the project would be implemented over a 10-year period. Economic Benefits 532. In the estimation of agricultural benefits, economic crop gross margins per hectare were calculated by valuing the physical input and output quantities in terms of their respective economic prices. The economic crop gross margins in the present, FWO and FW project situations are summarized in Table A10. The economic gross margins per hectare were then multiplied by the respective crop areas in order to estimate net crop benefits in the present, future with and future without project situations. The differences between the net crop benefits were then calculated to determine the economic impact of the changes in cropping patterns and improved crop yields. Table A10: Economic crop gross margins in present, future without and future with project Crop Enterprise Economic Gross Margins (TSh per hectare) Present Future Without Project Future With Project Maize -80,084 -37,321 42,813 Rice 98,649 185,461 359,371 Oilseeds/Pulses 416,142 511,441 697,594 Vegetables 1,589,450 1,860,013 2,115,150 Source: Crop budget estimates 533. Net livestock benefits were also estimated for the present, future without and future with project situations (based on the respective livestock populations and economic gross margins). These benefits were then added to the net crop benefits. Economic livestock gross margins are summarized in Table A11. Table A11: Economic livestock gross margins in present, future without and with project Livestock Enterprise Economic Gross Margins (TSh per head) Present and Future Without Project Future With Project Dairy Production 104,225 237,975 Beef Fattening 56,500 86,500 Source: Livestock budget estimates 534. As a result of these increases in crop and livestock production, net agricultural benefits to farmers within the project area were estimated to rise by TSh 626,572 million per annum (from TSh 245,152 million to TSh 859,700 million per annum at full development). It is envisaged that the future with project agricultural benefits would be fully attained within 2 years of programme completion. Benefits from crop production are estimate to account for 81% of the overall agricultural benefits. Capital and Recurrent Costs 535. The capital investment required for the implementation of the four ASDP II components, i.e., sustainable land and water management, enhanced agricultural productivity, rural commercialization/ value addition, and strengthening sector enablers, were compiled from the estimates made by the consultancy team. These capital costs were then distributed over a 10 year implementation period. 235 Agricultural Sector for Industrial Development 536. In financial terms, the base capital cost was estimated TSh 6,230,100 million (USD 2,898 million) and when physical contingencies were included, the project cost increased to TSh 7,882,948 million (USD 3,666 million). Physical contingencies were estimated at 10%. 537. In the derivation of economic costs, government taxes and duties as well as subsidies (e.g., farm input subsidies and NFRA grants) were first omitted from the financial costs, as these are transfer payments within the economy and so are not real resource costs. The standard conversion factor (SCF) of 0.95 was then applied to the financial costs of local materials, machinery/equipment and skilled labour. The cost of unskilled labour was also reduced by applying the shadow wage rate factor of 0.65. The financial cost of foreign goods and services remained unchanged. These economic conversion factors were then applied to the financial costs in order to determine the economic capital cost which was estimated at TSh 2,778,544 million (USD 1,292 million). The financial and economic capital costs of the ASDP II components are summarized in Table A12. Table A12: Financial and economic capital costs Programme Components Financial Cost (TSh million) Economic Cost (TSh million) Component 1: Sustainable Water & Land Use Management 1,450,593 1,233,004 Component 2: Enhanced Agricultural Productivity 1,517,960 607,184 Component 3: Commercialization and Value Addition 1,483,429 1,260,915 Component 4: Strengthening Sector Enablers 1,778,118 711,247 Base Cost 6,230,100 3,812,350 Physical & Financial contingencies 1,652,848 1,011,418 Total Capital Cost 7,882,948 4,823,768 538. The long-term annual operation and maintenance costs of the irrigation infrastructure were also included in the economic analysis, as these recurrent costs will have to be met if the future benefits of the capital investment are to be sustained. The annual O&M cost of the infrastructure was estimated at TSsh 38,915 million (USD 21.8 million). These financial costs were then converted to economic values, and the annual economic O&M costs were estimated at TSh 34,614 million (USD 16.1 million). 539. In addition, it was assumed that agricultural support services will also be required on an annual basis over a 50-year period. The annual costs of support services were therefore included in the analysis to ensure that agricultural production continues to grow after completion of ASDP II. In total, economic recurrent costs after programme completion amounted to TSsh 67,740 million per annum (USD 31.5 million per annum). Economic Viability and Sensitivity Analysis 540. By deducting the capital and recurrent costs from the economic benefit stream, an incremental net benefit stream for the programme was determined over a 50-year period (in constant 2015 prices). The incremental net benefit stream was then used to estimate the economic internal rate of return (EIRR) and net present value (NPV) calculated at a discount rate of 12%. The results of the economic analysis indicate that the EIRR of ASDP II is 14.8% with a NPV of TSsh 370,009 million (USD 172 million). These results show that the proposed project investment is justified on economic grounds. 541. Sensitivity analysis was also undertaken to test the economic viability of the proposed interventions to various changes in the cost and benefit streams. This analysis indicated that ASDP II is fairly sensitive to changes in benefits and costs and becomes uneconomic with an increase in capital and recurrent costs of 21%. Similarly, an 18% decrease in incremental project benefits would result in the EIRR falling below 12%. 236 Agricultural Sector Development Programme II (ASDP-II) 542. The results of the sensitivity analysis are given in Table A13 and it can be seen that a decrease in capital and recurrent costs of 20% resulted in an EIRR of 18.8%, while a cost increase of 20% lowered the EIRR to 12.1%. Similarly, an increase in incremental benefits of 20% produced an EIRR of 18.0% and a benefit decrease of 20% reduced the EIRR to 11.6%. The analysis also considered the possibility of a combination of a 20% benefit increase and a reduction in project costs of 20%. Under this scenario, the EIRR increases to 22.6%. In contrast, if a benefit reduction of 20% is combined with a 20% increase in costs, the EIRR falls to 9.3%. 543. In addition, changes in the expected cropping intensity were also assessed and the analysis indicated that if a future with project cropping intensity of 100% is assumed (in comparison to 103% in the base case), the EIRR falls to 14.3%, while a cropping intensity of only 95% will further reduce the EIRR to 11.8%. 544. With regard to crop productivity, the analysis indicated that if yields of maize and rice only increased by 50% (in comparison to 57% and 67% in the base case), the EIRR falls to 10.7% and ASDP II becomes uneconomic. Furthermore, if overall crop yields are only 40% higher after programme completion, the EIRR reduces to 7.7%. The economic viability of ASDPII is therefore very sensitive to achieving the expected yield levels. It should therefore be emphasized that the adoption of improved cropping practices and expected increases in crop yields (to maintain economic viability) will only be achieved if adequate agricultural support services, including extension/training and input supply as well improved access to markets and rural finance, are made available to farmers in an effective and efficient manner. Table A13: Economic viability and sensitivity analysis Scenario EIRR (%) NPV (TSh million) Base Case 14.8% 370,009 Capital and Recurrent Costs -20% 18.8% 722,428 Capital and Recurrent Costs +20% 12.1% 17,589 Incremental Benefits +20% 18.0% 796,430 Incremental Benefits −20% 11.6% −56,413 Costs -20% and Incr. Agric Benefits +20% 22.6% 1,148,850 Costs + 20% and Inc. Agric Benefits −20% 9.3% −408,832 100% Cropping Intensity with Project 14.3% 299,966 95% Cropping Intensity with Project 11.8% −21,536 50% Increase in Crop Yields 10.7% −531,096 40% Increase in Crop Yields 7.7% −165,650 237 Agricultural Sector for Industrial Development ANNEX VII: Risks assessment and Mitigation Strategies/Measures Programme stakeholder risks Inadequate policy incentives for participation of private agribusiness partners in programme activities, especially their envisaged role in value chain development will undermine achievement of programme objectives. Mod-erate Dialogue on improving environment for private sector investment continues, and Government is committed to enhance private investment in agriculture through initiatives like Kilimo Kwanza and the Southern Agricultural Grow Corridor for Tanzania. The proposed District Stakeholders Commodity Value Chain Platforms under the overall government’s programme will enhance the interactions and partnership among value chain stakeholders. Operating environment risks Country Tanzania’s growth remains vulnerable to external and domestic shocks that can be exacerbated by domestic structural constraints. There are continued risks of exogenous shocks from another global economic downturn and global fuel and food price hikes. Regional and domestic risks include droughts. The vulnerability risk against such exogenous shocks is compounded by the country’s dependency on foreign aid, making the country extremely vulnerable to changes. The fiscal framework is increasingly vulnerable to risks embedded in the strategic choices adopted by the Government, including increasing use of non-concessional financing for investment projects, unbalanced allocation of resources between infrastructure and social sectors, and internal pressures on wages. The level of public debt has increased dramatically over recent years, reaching, approximately 40% of GDP. Limited capacity in the government system and its staff to implement and manage the reform agenda represents another risk. This includes, most notably, capacity constraints in PFM, including budget planning and execution. Serious PFM capacity constraint in the local governments is of particular concern, as the Government pursues its decentralization policy. The PRSC series provides a platform from which the Bank can engage in a dialogue with the Government on macroeconomic and fiscal conditions so as to build resilience against external and domestic shocks, maintain fiscal sustainability and improvement of overall reform programme. This PRSC series, through its focuses on PIM and PFM including debt management, directly contribute to mitigation of risks related to use of excessive non- concessional lending, fiscal institutions, including debt management The dialogue process under the PRSC series, such as PER, addresses capacity constraints. Relevant knowledge work under the PRSC series to build analytical underpinnings will also maximize the participation of the Government and other national stakeholders, such as CSOs and the academic community, so as to enhance the analytical capacity and the knowledge-sharing environment in the country, which are essential to enhancing domestic accountability. Sector and multi-sector The programme will be implemented under a complex institutional structure−multi-sectoral, multi-donor environment, in parallel with several standalone projects. This may lead to conflicting agenda and interests, as well as inadequate capacity to effectively manage and coordinate several activities under different projects Moderate The programme is providing a framework for the implementation of the agreed government programme, using strengthened government systems. The sector- wide coordination framework will help to harmonize implementation various projects in the agricultural sector. A MoU will be signed between all donors supporting ASDP II (and the sector) to agree on principles for operating and managing support to the sector, in accordance to overall sector coordination framework. 238 Agricultural Sector Development Programme II (ASDP-II) Implementing agency risks Weak capacity on financial management, procurement, M&E and oversight of projects especially in local government may undermine accountability and tracking programme results. High The programme is aligned with (comprises) Government’s initiative which emphasizes results management and accountability. The Agricultural Delivery Unit will be established in the Ministry of Agriculture to enhance accountability and tracking of results in the sector. In addition, there are on-going efforts by government to strengthen FM and procurement capacity through recruitment/assignment of staff and training. The proposed programme includes support for institutional strengthening and capacity building to programme implementers. Efforts to improve agricultural statistics and M&E system; and establishment of MIS under the programme will enhance flow of information and accountability. The communication strategy prepared under the first phase will improve management of information flow at different levels, decision-making, and accountability and strengthen M&E and quality of information. Governance. Weak budget and accountability systems especially at local levels may undermine internal controls and funds may not be used efficiently and economically for intended purposes. Inadequate regulatory and unfavourable local tax regime could reduce programme benefits. Moderate Each ASLM has functional internal audit and audit committee. The programme coordination unit will provide oversight for allocation and utilization of programme resources to ensure that funds are used for the intended purposes. Recruitment of qualified accounting staff, internal auditors, and procurement staff at national level has been done, and efforts to strengthen capacity of LGAs in accounting, internal audit and procurement are underway. Governance risks, fraud & corruption There is potential for fraudulent bonus payment claims, especially on procurement activities, due to inadequate transparency and limited capacity to monitor and report fraud and corruption, especially at the local level. Moderate Internal auditors of implementing agencies have been trained in value-for-money auditing. Other oversight mechanisms will include regular performance reviews and regular public expenditure reviews. Social accountability mechanisms will strengthen transparency and the quality and accuracy of results. Programme risks Design. The national and local implementing agencies have inadequate capacity for value chain development and proposed commercialization models. This will affect the achievement of programme objectives. Limited capacity of private service providers and weak farmer organizations may impede commercialization of smallholder farmers, transfer of technologies and realization of optimal returns from value chain investments. High There are on-going efforts to develop capacity Value chain analysis/approach in ASLMs and LGAs. The overall programme will support capacity building of Agribusiness Service Providers. Additional support will be provided to strengthen farmer organizations and facilitate linkages with private service providers/ agribusiness. 239 Agricultural Sector for Industrial Development Social & environmental There is a risk of poor compliance with environmental and social safeguards policies related to implementation of programme activities, such as irrigation investments and use of fertilizers and other agrochemicals Moderate The government has established an environment unit at central level and District Environment Officers at local level and Local Government Authorities are being trained on safeguard issues. Progress made so far on integration of environmental and Social safeguards in programme implementation will be strengthened further to meet the needs of the proposed programme. The existing ESMF/RPF, IPMP and INMP will be revised to provide guidance for mitigating safeguards risks. The Government Authorities have appointed District Environment Management Officers (DEMOs) responsible for coordination and supervision of local investments to ensure integration of safeguards issues. The DEMOs have been trained on application of ESMF/ RPF principles, and the need to carry out Environmental and Social Impact Assessment (ESIAs) and preparation of Environmental and Social Management Plans (ESMPs) and/or Resettlement Action Plans (RAPs). Programme & donor The programme will be financed in parallel with other donors supporting Government programme and stand-alone projects and initiatives funded by other non ASDP II donors and private sector. Inadequate coordination of sector activities will overburden the implementing agencies with competing demands, duplications and thus undermine the achievement of the overall programme objective. High The programme will support the agreed Government Programme. A memorandum of understanding will be signed by all ASDP II donors to agree on respective financing principles towards enhancing coordination among donors. The Government programme also includes support to LGAs to improve coherent sector planning; a common framework for tracking results, including sector targets and outcome indicators. This coordination will be implemented under the ‘expanded’ SWAp. Delivery monitoring & sustainability. Long- term impact and sustainability of programme activities is likely to be constrained by limited capacity and low participation of private service providers in value chain development, limited M&E skills and inadequate community ownership of programme investments Moderate The programme will initially focus on high potential district clusters and enhance inclusive private sector investment at local level. The ASDP II programme includes support to capacity building on results monitoring. Agricultural Sector Development Programme II (ASDP-II) 240 ANNEX VIII: Key Maps and Figures Figure A28: Agro-ecological Zones 241 Agricultural Sector for Industrial Development Table A14: Agro-ecological zones (AEZ), priority commodities and potential focus districts (tentative) AEZ Priority Commodities Regions Districts Crops Livestock/ fisheries 1 Arid Lands (unimodal 400–900 mm) Sunflower/ maize/ sorghum/ millet, rice, potatoes, cassava, horticulture, Meat— beef, dairy, goat, Mara (E) Musoma TC, Musoma DC, Serengeti, Bunda, Tarime, Rorya Dodoma (E) Masai Steppe, Tarangire, Mkomazi, Pangani and East Dodoma Simiyu Bariadi DC, Maswa, Meatu, Itilima, Busega Manyara (E) Kiteto, Simanjiro 2 Eastern coast Cassava, rice, maize, cashew, cassava, beans, sugar cane, Oil crops, horticulture, seaweed. Goats, (unimodal) poultry, fish Lindi Lindi DC, Lindi MC, Liwale, Ruangwa, Kilwa, Nachingwea. Mtwara Mtwara T.C, Mtwara DC, Masasi, Nanyumbu, Tandahimba, Newala Dairy (bimodal), beef, poultry, goat, skin/ hides, fish, Tanga Handeni, Kilindi, Korogwe DC, Lushoto, Muheza, Mkinga, Pangani, Tanga, Korogwe Pwani Kibaha TC, Kibaha DC, Bagamoyo, Mafia, Mkuranga, Kisarawe, Rufiji Dar-es- Salaam Ilala, Kinondoni, Temeke Alluvial Plains floods,swamp)- Morogoro ( Kilombero,Wami),Pwani (Rufiji coast),Mbeya( Usangu) Rice, Sugar cane (Morogoro) Central clay plain with alluvial fans Mangrove swamp delta, alluvial soils, sandy upstream, loamy floodplain (Mbeya) Seasonally Flooded clay / alluvial soils (Morogoro) Moderate alkaline black soils, alluvial fans, well drained black loam (W) 3 Northern Highlands (bimodal) Maize, rice, pulses/beans, legumes horticulture, banana Meat— beef, ,dairy, goat, Arusha (S) Arusha DC, Meru, Arusha MC, Karatu, Monduli, Longido, Ngorongoro Kilimanjaro (N) Moshi D. C., Hai, Siha, Moshi M. C, Mwanga, Rombo, Same Manyara (E) Babati TC, Babati D.C Hanang, Mbulu 4 Plateaux (unimodal) Maize and pulses W: Tabora, Rukwa/ Katavi Tabora MC, Igunga, Nzega, Sikonge, Tabora(Uyui, Urambo Mpanda DC, Mpanda TC, Mlele Mbeya (N) Chunya (partie N) Ruvuma + Morogoro (S) Songea T. C, Songea D.C, Namtumbo, Mbinga, Tunduru, Ulanga (Mo) Mwanza Mwanza CC, Magu, Geita, Ukerewe, Misungwi, Sengerema, Kwimba Geita Geita DC, Chato, Bukombe, Nyang’wale, Mbogwe 5 Central semi-arid (unimodal) Oil seed maize/ sorghum/ millet, rice, horticulture, sugar cane Meat— beef, , dairy, goat, Poultry, Dodoma (W) Kondoa, Dodoma MC, Mpwapwa, Kongwa, Bahi, Chamwino Singida Singida DC, Singida MC, Manyoni, Iramba, Ikungi, Mkalama Shinyanga Shinyanga M C, Shinyanga D.C, Kishapu ,Kahama Morogoro Morogoro MC, Morogoro DC, Mvomero 242 Agricultural Sector Development Programme II (ASDP-II) AEZ Priority Commodities Regions Districts Crops Livestock/ fisheries 6 Southern & highlands Maize, Rice, potatoes, horticulture, Tea/Coffee, Sugar cane Meat— beef, goat, poultry, dairy. S-Mbeya Mbeya MC, Mbeya D. C, Mbarali, Kyela, Rungwe, Mbozi, Ileje, Chunya (S) S-Iringa Iringa DC, Kilolo DC, Iringa (S), Mufindi, Njombe Makete, Ludewa, Njombe TC, Njombe DC. Makambako, Morogoro NW Kilombero, Kilosa 7 South Western highlands Maize, Horticulture, pulses, potatoes, wheat, rice, oil seed Poultry, beef, dairy, goat, fish Rukwa Sumbawanga D.C, Sumbawanga TC, Nkasi, Mpanda DC, Mpanda TC 8 Western highland Cotton, Sugar cane, Rice, Maize, Cassava, oil seed/crop, banana, coffee Poultry, beef, goat, fish Kigoma Kasulu, Kibondo, Kigoma DC, Kigoma TC Kagera (bimodal) Biharamulo, Bukoba D. C, Misenyi, Bukoba T. C, Karagwe, Muleba, Ngara Source: ASDP II BF (2013)—ARD; Tanzania CSA Programme (2015) and de Pawn (1984) Table A15: Agricultural production—Food crops ’000 metric tons Year 2003/ 2004 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Maize 3,157 3,219 3,423 3,302 3,556 3,326 4,475 4,341 5,104 5,288 6,734 Sorghum 757 714 712 971 861 709 789 807 839 782 883 Millets 201 221 228 194 203 220 372 312 214 292 363 Rice 688 759 805 872 875 868 1,700 1,461 1,170 1,342 1,681 Wheat 67 102 110 83 92 95 62 113 109 102 167 Pulses 879 886 1,050 1,156 1,126 1,116 1,254 1,632 1,827 1,871 1,697 Cassava 1,480 1,846 2,053 1,733 1,797 1,972 1,464 1,549 1,821 1,878 1,664 Bananas 734 991 1,169 1,028 982 1,073 975 1,048 842 1,317 1,064 Potatoes 874 931 1,396 1,322 1,379 1,392 1,231 1,710 1,418 1,808 1,761 Table A16: Agricultural production—Cash crops (in metric tons) Year/VC 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Tea 32,000 30,000 34,446 32,698 34,165 33,160 35,000 33,000 33,700 33,000 Sugar cane 229,620 263,317 192,535 265,434 276,605 279,850 317,000 260,055 286,380 293,011 Tobacco 51,970 56,500 65,299 55,567 58,702 60,900 78,000 126,624 74,240 100,000 Cotton 344,210 376,591 130,565 200,662 368,229 267,004 260,000 225,938 351,151 246,767 Pyrethrum 1,000 2,800 1,500 2,800 3,280 3,320 5,000 5,700 6,100 7,000 Sisal 26,800 27,794 30,934 33,039 33,208 26,363 35,000 33,406 23,344 41,104 Coffee 54,000 34,334 48,869 43,000 62,345 40,000 60,575 33,219 71,200 48,599 Cashew 81,600 77,158 92,232 99,107 79,068 74,169 121,070 160,00 121,704 127,939 243 Agricultural Sector for Industrial Development Year/VC 2004/ 2005 2005/ 2006 2006/ 2007 2007/ 2008 2008/ 2009 2009/ 2010 2010/ 2011 2011/ 2012 2012/ 2013 2013/ 2014 Fruits 557,400 3,297,910 3,751,170 3,938,730 4,096,280 4,416,690 Vegetables 602,000 766,570 858,740 901,680 937,750 1,005,305 Flowers 8,670 9,100 9,850 10,200 10,790 Spices 6,865 7,150 7,370 8,125 8,377 Figure A29: Tanzania Agricultural research zones and NARS institutes (Central, Eastern, Lake, Northern, Southern, Southern Highlands and Western zone) Figure A30: Tanzania AEZ 244 Agricultural Sector Development Programme II (ASDP-II) Figure A31: Tanzania livelihood zones Figure A32: Map - Food insecure districts (2006-13) 245 Agricultural Sector for Industrial Development Figure A33: Map – Tanzania Cattle Distibution by 2008 246 Agricultural Sector Development Programme II (ASDP-II) ANNEX IX: Selection Criteria for Participating Districts164 Criteria for selecting the targeted districts (within zonal commodities in AEZ165) a. AEZ (see table with primary and secondary value chain) b. Current per cent marketed for targeted CVC c. Per cent in their farming system (% of revenue) d. Food security and nutrition e. Investment absorption capacity over the past five years f. NGO support especially in value chain development g. FO structuring (strength?) Approach. For the purpose of focusing on required services in the upstream and downstream of production, production clusters (grouping three to six districts each) will be established for selected strategic commodities as growth poles within each agro-ecological zone (seven). The cluster approach enhances delivery of essential services, exploitation of economies of scale, development of required infrastructure, bulking of produce, agroprocessing and reduction of transaction costs. A commodity cluster will be a coherent area comprising of three to six districts, where there is already a proven potential for that specific commodity, as well as the presence of value chain actors (e.g., producers, traders, processors and service providers), a MSIP and basic market infrastructure. The project will target maize, rice, oilseeds and strategic commodities import substitution and /or for export to the regional markets. Through a value-chain approach, the programme will support access to and utilization of yield enhancing technologies (improved seeds, fertilizers, mechanization and water for agricultural production) as well as infrastructure and agribusiness services for marketing and value addition. The capacity of private sector actors, including farmers’ organizations and cooperatives, will be strengthened to improve stakeholders’ access to the required inputs, marketing and agroprocessing services. Supporting improved input use in complement to research and advisory services is a cost-effective response for increased productivity and farm income, but also a mean to prevent potential risks from climate change and land degradation. Broader access to adapted varieties and seeds, integrated soil fertility management and timely land preparation will also help farmers to move towards sustainable agriculture and overcome climate risks. Gradual adoption of appropriate mechanization technologies for production and post-harvest operations will not only increase rural labour productivity but also attract young entrepreneurs in the sector. Programme Scope and Focus. The programme will focus in one /or two priority commodities (crop and livestock) per agro-ecological zone. In each zone, potential districts (three to six) will be identified for programme implementation based on the agreed criteria. Proposed selection criteria 1. Agricultural production potential of the target commodities (arable land/arid/semi-arid/, rainfall spell period, etc.) 2. Access to productive and marketing infrastructures (road, railways, electricity, etc.) 3. District historical background of beneficiaries contribution/involvement in development initiatives 4. Availability of private sector supporting value chain of target commodity 5. Production levels of target crops/livestock population by category 6. Other ongoing initiatives (programmes) in the areas to avoid duplication 164 Note summarizing diverse contributions from ARD, Sokoine University of Agriculture, the Ministry of Agriculture —DPP, ASDP Coordination team, etc. 165 Some new developments consider eight and some nine AEZ, especially for crop research activities (adaptations to be done if needed). 247 Agricultural Sector for Industrial Development Figure A34: Maps ASDP II targeted priority districts Attachment 1: Operationalization of AEZ and clustering approach 1. ASDP II focuses on the AEZ and cluster approach. A commodity/district cluster comprises three to six districts with high potential CVC, as well as the presence of value chain actors (e.g., producers, traders, processors and service providers). 2. The DCP/MSIP will be formed to facilitate the operation of clusters under the supervision and coordination of the Region through the Economic and Productive Sectors Section. 3. If a cluster includes districts from more than one region, then the responsible regions will select a front-runner region to supervise and coordinate cluster activities. 4. The role of DCP will be to facilitate the dialogue among major commodity actors (Producers, Traders, Processors, Public and Private Service Providers- PSP) to develop a common strategy, work plan and M&E so as to improve the performance of targeted CVCs. 5. Moreover, DCP will be critical in terms of establishing formal or even ad hoc mechanisms to encourage value chain connectivity between private and public stakeholders and drive innovations/changes towards higher levels of commercialization in targeted priority value chain (or group of complementary CVCs). 248 Agricultural Sector Development Programme II (ASDP-II) ANNEX X: Climate Change and Action166—Agriculture Climate Resilience Plan (ACRP) The Ministry of Agriculture is taking action on climate change in Tanzania. In line with the National Climate Change Strategy (2013), which calls for all climate-sensitive sectors to develop action plans to implement the Strategy’s strategic interventions, The Ministry of Agriculture has prepared the Agriculture Climate Resilience Plan (ACRP) to identify and respond to the most urgent impacts posed by climate variability and climate change to the crop subsector. The ACRP will serve as a roadmap for mainstreaming climate change within current agricultural policies, plans, and practices, as well as identifying gaps were new investments may be needed. It will be the guiding framework for a more comprehensive and consistent approach for confronting one of the major risks to current crop productivity and future investments. Why is climate change a concern for crop agriculture? Agriculture is a dominant sector of the Tanzanian economy, generating 25% of GDP, 24% of exports, and is the mainstay of 75–80% of livelihoods in the country including the majority of the poor. It is a sector of contrasts: despite having a relatively rich base of land and water resources and a favourable climate in many areas for the majority of years, it is hampered by low productivity and persistent poverty. Crop diversity is high, but the majority of households engaged in the sector grow a limited number of food crops for subsistence, and despite the resource endowments these households are vulnerable to food security and economic shocks. Though the Tanzanian economy and in the agriculture sector have experienced economic gains, little has translated to the poor, who still depend on rudimentary technologies and erratic rainfall for their livelihood and food security. These factors influence the impact climate variability and climate change will have on the agriculture sector, as well as the capacity to adapt to current and changing conditions. The strategic direction of the agriculture sector is to modernize through promoting large-scale commercial farms, irrigation expansion, strengthening value chains, and improving linkages with smallholders. Rural poverty reduction, economic growth, and food self-sufficiency are anticipated, but this will add pressure on natural resources that already face high levels of inefficiency and degradation due to agriculture, as well as competing uses. Tanzania’s climate is highly variable and complex, and climate trends already indicate that temperatures are rising and rainfall is becoming more erratic. Recent models show that average annual temperatures will rise by 1ºC by 2050, and changes in rainfall patterns could cause dramatic shifts in agro-ecological zones, increase uncertainty in the onset of the rainy season, and increase the severity of droughts and floods. Other issues such as the emergence of pests and diseases moving into new geographic ranges are already suspected as indirect impacts of changing weather patterns. Weather-related risks are already cost the agriculture sector at least $200 million per year (World Bank, 2013), and without urgent adaptation these costs are likely to increase with rising climate variability. Most agriculture in Tanzania will continue to depend on rainfall in the foreseeable future. Looking ahead, rainfall decreases of 10% have been correlated with a 2% decrease in national GDP, 2 and temperature rise of 2°C could reduce maize yields by 13% and rice by over 7%, 3 both of which are probable in Tanzania over the next century. Climate risks will exacerbate the existing and projected pressures on water resources, soil erosion and health, and land degradation: water shortages and significantly reduced stream flows and water quality changes are already felt in key agricultural investment areas due to low water use efficiency and competing uses, and some climate models show that these are the same areas where rainfall is expected to decrease, yet these areas are slated for investment in water intensive crops such as rice and sugarcane as well as irrigation expansion. As a cross-sectoral issue with far reaching economic, social and environmental implications, climate change planning cannot happen in isolation. At the same time, a robust process must acknowledge more uncertainty, given long term time horizons and limitations of climate and crop models to predict the impacts of temperature rise combined with precipitation changes on crop yields. One way to address these limitations is to adopt a more participatory risk-based approach, as has been done for the ACRP. The ACRP process has involved experts in environment, climate change, land use planning, mechanization, hydrometeorology, soil science, water resource management, pest management, rural development and advocacy, among others, to work collaboratively to develop an action plan and investments that respond to the risks but are tailored to fit the Tanzanian context from the policy level to the farm level. 166 Source Tanzania: Agriculture Climate Resilience Plan 2014–19 (September 2014) 249 Agricultural Sector for Industrial Development How could a changing climate change Tanzania’s agriculture? Three risks emerged from the adaptation planning process, that are key to increase resiliency to climate variability in the short term and given long- term climate change scenarios: 1. First, climate change will amplify the existing pressures on water resources from poor management, degradation and competing uses. Irrigation alone will not be sufficient to adapt to climate change, and can indirectly drive vulnerability if water resources are not well managed. Adaptation measures for improved water, soil and land management are urgently needed to build resilience to current variability and future climate change by both smallholders and commercial farms. 2. Second, yields of key cereal crops are mostly likely to decline due to temperature rise and decreasing water availability, with significant implications for commercial investment, small- scale farmers, and food security. Adaptation measures should focus on boosting productivity of cereal crops, especially building capacity of smallholder farmers to increase yields to the point of “best management practice”, and researching the impact of temperature rise and rainfall variability on key crops. 3. Third, smallholder farmers are among the most vulnerable to even small variations in the climate, with major impacts on livelihoods and food security. Adaptation measures need to consider how to reduce climate shocks to smallholder farmers, promote agricultural practices that boost productivity and safeguard natural resources, and appropriately target vulnerable areas. These messages, reflecting stakeholder inputs, current climate science and analyses of agricultural risks in Tanzania, that were central to informing and prioritizing actions to build resilience to climate impacts. How can agriculture adapt to a changing climate? In order to mitigate the risks, priority actions and investments have been developed, to set the foundation for resilience over the next five years. These were identified as the areas with the highest level of vulnerability to risks, and the biggest payoffs for building resilience. Agricultural stakeholders recommended adaptation options that would help to integrate resilience in agricultural policy decisions, influence planning processes, and implement investments on the ground. 1. Action 1: Improve agricultural water and land management. Priority investments include water use efficiency and water storage, improvements in catchment management in agricultural planning, and adoption of sustainable agricultural land and water management to reduce degradation. 2. Action 2: Accelerate uptake of climate smart agriculture. Priority investments include building an evidence base for climate smart agricultural practices and incentives to offset the cost of adoption, promoting practices at the District level, and generating awareness and capacity for these practices. 3. Action 3: Protect the most vulnerable against climate-related shocks. Priority investments include measures to prepare for and respond to emergencies and weather-related shocks—and better integration of pests and diseases into these measures, building resilience through livelihood diversification activities targeted to the most vulnerable areas, and piloting risk management instruments such as finance instruments. 4. Action 4: Strengthen knowledge and systems to target climate action. Priority investments include filling key research gaps, undertaking a comprehensive climate change and agriculture vulnerability assessment, developing systems for information management and communication campaigns, especially more accurate and timely weather and climate information, and strengthening gender considerations into climate change action for agriculture. 250 Agricultural Sector Development Programme II (ASDP-II) Table A18: Action areas investments and priorities: ACRP (underlined considered as high priority) Priority action & investments Action areas Key investments/actions S/C 1. Improve agricultural land and water management (Sustainable Land and Water Management) Water use efficiency (irrigation efficiency, SRI etc.) 1. Guidelines for including climate change in irrigation expansion/rehabilit. designs 2. Update policies to improve water use efficiency and embed climate change 3. Stocktaking on water lifting, harvesting, storage techno. & use efficiency 4. Environ. assessment integrating water availability & climate change in irrigation plans 5. Promote sustainable use of groundwater for irrigation 6. Support traditional & modern rainwater harvesting 7. Support on farm water storage facilities 8. Promote sustainable irrigation & water use efficiency technologies, 9. Support innovative paddy rice production techniques Sc 1.3 Rainwater harvest & integrated soil & water manage-ment 10. Develop agricultural land/water coordination mechanism 11. Conservation management plans up- & downstream of irrigation schemes 12. Protect water catchment areas for agricultural intensification 13. Develop guidelines, curriculum and capacity building training for WUA 14. Increase uptake of soil & water conservation on irrigated &dry-land Land and catchment manage-ment 15. Develop guidelines on sustainable soil and water management. 16. Build local capacity to plan, implement & monitor Sustainable Land and Water Management 17. Village land management plans to guide sustainable land use 18. District land use planning & monitor of subsistence/commercial farming 19. Increase awareness of sustainable farmland and water management, 20. Promote appropriate agroforestry technologies 21. Promote sustainable farming systems, IK & initiatives under similar AEZ 2. Accelerate uptake of climate smart agriculture: increase yields, safeguard NRM and build resilience to climate change Farming practices conservation agriculture, Soil & water management; Resilient vars.: Cropland; Soil fertility Agroforestry 1. Build the evidence base to promote CSA 2. Develop guidelines and policy briefs for CSA technologies and practices 3. Establish an emissions baseline for the agriculture sector 4. Build district capacity to mainstream CSA in planning 5. Promote CSA in DADPs planning process 6. Establish a monitoring system for CSA interventions, 7. Develop incentives to offset CSA costs for smallholders 8. Increase awareness and train for CSA practice use 9. Demonstrate good CSA practices in the field 3. Protect the most vulnerable against climate/ weather related chocks Climate change risks for agricultural productivity & food security (risk mitigation transfer & coping) 1. Implement the TAFSIP disaster management plan 2. Integration of pests/diseases in monitoring and early warning systems 3. Communication of weather and early warning info to farmers 4. Draw lessons from EWS, DRM, and social safety net projects & scale up 5. Research on building resilience through postharvest value addition 6. Develop program to establish value adding industries for farm products 7. Develop program on risk management for smallholder agriculture 251 Agricultural Sector for Industrial Development Priority action & investments Action areas Key investments/actions S/C 4. Strengthen knowledge & systems to target climate action Evidence for climate smart strategies & communi- cate key messages to target stake- holders 1. Draft and implement a CC and agriculture research programme 2. Develop a framework to target climate adaptation in vulnerable areas 3. Comprehensive assessment on gender and CC in the agriculture 4. Develop/operationalize an MIS & web portal for CC in agriculture 5. Establish stakeholder engagement and communication networks. 6. Develop a gender and agriculture coordination mechanism in the Ministry of Agriculture 7. Raise awareness and disseminate targeted climate/weather info (ICT) Mainstream!! Integrate other ASMLs (livestock, fisheries, environment, Land) into strategy and action plan. Much is already being done to build resilience in the agriculture sector. The ACRP has identified many existing initiatives and investments that consider climate change either directly—however, these are generally small-scale, discrete interventions. The ACRP investments are geared to build on existing activities, significantly scale up successes, and fully mainstream climate change into the Ministry of Agriculture and activities at every level. Table A19: Intervention levels and strategic actions for climate smart interventions Intervention levels Strategic actions Adaptation strategic actions Crop vulnerability/resistance in different AEZ; assess comparative advantage of traditional export crops; promote appropriate irrigation systems; early maturing crops; enhance agro-infrastructural systems; KI, IPM, crop insurance; weather forecast; reduce crop loss & promote value addition; improved soil management Mitigation strategic actions Promote agroforestry, management of agric wastes, minimum tillage and efficient fertilizer use; promote good agricultural practices and conservation agriculture Strategic intervention for water resources for agriculture Protect/conserve water catchments, extraction of underground water, water recycling and reuse, rainwater harvesting Way forward: Strategies for Sustainable Agricultural Intensification ASDP II, promotes the development of farming systems, which are both more productive and more sustainable economic development. Main strategies are: 1. Institutional strengthening (and leadership) to implement the ACRP within ASDP II involving public (ASLM), private and associative stakeholders at national and local levels 2. The Ministry of Agriculture will need to leverage additional funds for building resilience, about an additional USD 25 million investment per year when compared to current losses estimated at USD 200 million. 3. Robust monitoring and evaluation will be key to demonstrating results (mainstreamed systems). 252 Agricultural Sector Development Programme II (ASDP-II) ANNEX XI: Strategic Options for Stimulating Investment in Improved Agricultural Inputs167 Despite more than a decade of subsidies supporting the delivery of agricultural inputs to smallholder farmers, the rates of adoption of improved seed, chemical fertilizer and related agricultural inputs remains relatively low, especially for fertilizer. Except for maize, most farm households still cultivate traditional varieties by hand using a hoe. Furthermore, some livestock inputs (vaccines) are provided free of charge as a public good. The National Agricultural Input Voucher Scheme (NAIVS), has proven that farmers desire to adopt improved technologies and can obtain significant productivity gains: while improving adoption rates for seed and chemical fertilizer, the scheme also contributed to strengthening of private input supply chains. Evidence indicates that some farmers are successfully graduating from subsidized to fully commercial input purchases (two-thrids of seed and one- third of fertilizer beneficiaries). However, while targeting mainly better off producers, farmers still complain that seed and chemical fertilizer are too expensive, in terms of access (initial payment), but also in terms of return (efficiency of use). Inputs to implement new/improved technologies include: (i) crops—seeds, fertilizer, agrochemicals, land preparation/ planting mechanization services; (ii) livestock—pasture seeds, feed, vaccines, veterinary drugs, mechanization for pasture maintenance, hay collection etc. and (iii) fisheries—fingerlings, feed, drugs, improved tools/nets, etc. The objectives of public support need to be clarified to identify best approaches for public supports (public good) to be provided while targeting specific objectives of input use knowledge, availability and farmer access: Specific objectives Priority action Stakeholders 1. Knowledge of new technology for improved productivity - Adaptive research (AE4D) - Extension (public and private) Research/extension (public & private) + Training & ICT 2. Availability: build commercial supply chains for inputs and service - Build professional agrodealer network Linkages between agrodealer, producer/ importers and banks 3. Farmer access to known technologies/inputs and services: - Access to credit - Accumulation of work capital - Farmer seed production? Contract farming Banks; cooperatives/SACCO Revolving 4. Sustainable (profitable) use of improved inputs: - Continued technical (AR4D) - In-/output market development Risk management (assurance?) Improve ability to apply efficiently for generating profitable return from intensification. Generally, farmers face some combination of technical, financial and marketing constraints, and adoption may be viewed as a two-step process of first learning about new technologies and second consistently applying these technologies in a commercial production system. The NAIVS was designed168 to promote the introduction of new seed and chemical fertilizer technologies for maize and rice to 2.5 million maize/rice smallholder farmers that did not yet apply, but who could afford to pay a 50% of the costs of seed and fertilizer. This involved a three-year graduation strategy, assuming that farmers would be knowledgeable but also capable of continuing purchases on their own (ability to reduce risks and to accumulate some capital from increased productivity). Options for future support actions along specific objectives/priorities are: Action 1. Speeding the introduction of new varieties for food security (and nutrition) – Targeted distribution of OPV and/or starter packs. Most of the 3.5 million farm households169 who have not been assisted by the NAIVS, (and even some of those who have been assisted), struggle to produce enough grain and other foods to meet their household food security and nutrition. Any supplementary production derived from improved adapted technologies offers the prospect of major gains in food security and nutrition but also ‘some’ marketing (reducing food aid when production falls short). The most obvious opportunity for assisting these households is to provide rapid access to improved open and self- pollinated improved varieties (OPV): improved seed offers a relatively cheap source of productivity gain. Released varieties need to be multiplied on a significant scale and distributed once for farmer testing, self-multiplication and use, 167 Sources: AFSP implementation documents and discussions (supervisions 2014) 168 The NAIVS was not designed to resolve farmers’ capital constraints nor the broader difficulties of assuring profitability of the commercial market (one of the main issues limiting the output). 169 These households are poor and without possible access to credit, given that most additional production will be consumed rather than marketed, thus not allowing for credit repayment. 253 Agricultural Sector for Industrial Development to generate many years of productivity gain. If rejected, farmers’ feedback would allow for better targeting of breeding programs to resolve farmers’ identified issues. The Ministry of Agriculture ought to: (i) complete an inventory of new open and self-pollinated varieties for all food crops, and (ii) organize a rapid multiplication and dissemination program aiming to assure all farmers in the country obtain access to varieties adapted to their AEZ and the opportunity to achieve sustained gains in productivity; (iii) monitoring effort linked back with national breeding efforts to assure that crop breeders integrate farmers needs and preferences; and (iv) enhance farmer training for seed selection and preservation. New varieties of non-hybrid seed may be provided for free (small starter packs) in order to speed farmer testing and adoption: administrative costs for farmer (partial) payment in most cases are higher than the potential revenue to be generated. Actions could evolve with a shifting set of new varieties each year, starting with a set of key grain varieties and continuing with other available varieties for legume seed, cassava, sweet potato and banana. Action 2. Speeding up the adoption of a wider array of new technologies towards intensive production systems. Farmers learn by seeing (demonstration, etc.) but generally get convinced by doing. The subsidy, in effect, offsets both the costs and the risks (including weather/climatic, sustainability) facing each individual farmer in trying a new technology. Three years of assistance in NAIVS helped farmers better understand the level of investment returns possible, and allow then to build a small capital base for investing on their own: the economic return for government investment in subsidies was very high. Furthermore, the multiyear support encouraged private commercial investment in building supply chains for the delivery of seed and fertilizer through a growing number of regional wholesalers and village retailers. The same logic may apply to many cropping technologies, such as mechanized soil preparation/planting, manure application, weed control, water harvesting, IPM etc. A subsidy could offset the risks underlying the investment and convince farmers about the investment return. This approach tries to solve knowledge and access constraints for farmers’ use of improved technologies/inputs: electronic vouchers would allow for improved targeting, gradual decrease of voucher value and improved scheme governance (M&E). Action 3. Sustaining the adoption of improved technology with credit and market support. Farmers are convinced of the value of a new technology, but experience difficulty obtaining the cash necessary to make the investment. Farmers’ perceptions of high input costs also reflect the high ratio of input to product prices. Possible support actions are: a) Reduced credit interest: subsidies on interest rates of commercial credit, further backed by loan guarantees, may be justified temporary until a critical mass of investment is achieved to assure sustained competitiveness or as income support for poor rural households (but credit for food insecure producers should be avoided). b. A loan guarantee to reduce risk estimated by banks for agricultural loans by commonly preferred strategies such as: (i) contract farming (mainly cash crop like tobacco, cotton, coffee or tea); (ii) group lending with collective liability (a significant level of selling of commodities is needed to allow for sustainable guarantee systems); and (iii) credit guarantee line. c. Bulk supply of inputs and services by apex farmer organizations, private sector, etc., to reduce transaction costs an input prices Agricultural Sector Development Programme II (ASDP-II) 254 ANNEX XII: ASDP II Management, Coordination and Communication Structure: Composition and Process from Village to National Level170 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Village Village Agricultural Extension Officer (VAEO) Supervise, Implement & prepare village report, planning, budgeting & monitor agricultural activities in the village Village project committee [10 members] None None Ward Ward Agricultural Extension Officers (WAEO) Supervise, Implement, Planning, Budgeting & Compile village reports, monitor agricultural activities in the ward None None None Ward Ward Executive Officer (WEO) Compile village reports8, Engage DAS as far as Developmental projects are concerned Ward Development Committee (WDC) • Chair: Voted Councilor • Ward Executive Officer • Councilors • Extension Officers • Village Chairpersons • Village Executive Officers • Scrutinize village development plans, progress reports. • Compile and forward village development plans, progress reports and by laws to District Council • Monitor Ward development programs Division Division Officer Supervise, Compile ward reports & monitor agricultural activities None None None 170 Not all Wards have WAEO in all sub sector specializations i.e. Crops, Livestock, Fisheries. DAICO-District Agricultural and Irrigation and Cooperative Officer DPLO-District Planning Office DCO-District Cooperative Officer DTO-District Trade officer DLFO-District Livestock and Fisheries Officer Agricultural Sector Development Programme II (ASDP-II) 255 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Districts District Agricultural, Irrigation and Cooperatives(DAICO), District Livestock and Fisheries Offices(DLFO) Compilation and Preparation of District Agricultural Development Plans(DADPs) and Budgets; Monitoring and Evaluation Reports, Advisory role on matters related to Agricultural activities District facilitation Team District Agricultural Working Groups Chair: DAICO/DLFO DLO(Land) DTO(Trade) DPLO District Private Sector Representative in agriculture DCOs District NGOs Representatives in Agriculture (+ other members of the environmental and conservation group) (CSA) • Compile, scrutinize, harmonize and coordinate plans and budgets, • Initiate, mobilize and support village and ward level planning, monitor performance and provide advisee to District Councils • Supporting land use planning and registration, • Oversee local authority agricultural activities District ASDP II/DADP Focal Person -Report to DAICO/ DLFO -Coordinate ASDP II Activities at District level None None None Districts Municipal/Town/District Executive Director Supervise development activities and reports to Municipal/Town District/ Council Council Management Team (CMT) District Consultative Committee (Regional Administration Act No.19 of 1997) Full Council (DC) • Chair: District Commissioner • DED • Heads of District Departments • Chair: Chairperson of the Council • Members as per Act 1982 • Scrutinize, compile reports and provide Advisory role to the District Council • Approval of development plans, budgets, performance reports and by-laws. Agenda to include district natural resource issues Region Assistant Administrative Secretary Economic & Productive Sector Provide Technical Backstopping to LGAs and Compile from LGAs & submit to Regional planning officer who will submit to RAS None None None Region Regional Planning Officer Compile all District Plans and Budgets for onwards submission to the Management Meeting Regional Management Meeting • Chair: Regional Commissioner(RC) • AASs (8 members) • Heads of Units • Members as per Act. Number 19 of 1997 • Review all regional plans and budget Agricultural Sector Development Programme II (ASDP-II) 256 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility Region Regional Administrative Secretary (RAS) Secretary to Regional Consultative Committee (RCC), provide policy guidelines and Oversee districts (Regional) development activities Regional Consultative Committee (RCC) • Chair: Regional Administrative Secretary (RAS) • Members as per restructuring of Regional Administrative (June 2011) • Advisory role to the districts. • Monitor of district activities Agenda to include regional natural resource issues PO-RALG PO-RALG -Agricultural Sector Coordination Plan, Compile, Analyze, Coordinate, Monitor and evaluate all Regional & Ministerial Agricultural Plans and budgets (ASDP II) - and submits to ASLMs- DPP’s office Annual Regional and Local Government Agricultural Consultative Meeting (ARLGAC). • Chair- Minister - PO-RALG) • RC, RAS, DED, DPP- ASLMs , DAICOs, Private Sector, Development Partners working in LGAs, NGOs/CBOs and other key stakeholders in respective Regions and LGAs • Advisory role to the PO-RALG, Regions, and LGAs • Consultations among stakeholders operating in the regions and LGAs Lead Agency Lead Agency-ASDP II Component Coordination Compile, Analyze, Coordinate, Monitor and Evaluate Implementation of ASDP II Prepare and Review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination Thematic Working Groups(TWG) Meeting • Chair: TWG Chair Appointed by Head of Lead Agency • Technical Experts in the area appointed by the Lead Agency to participate in the thematic Groups • Coopted Members for cross cutting and emerging issues • Discuss, Plan, Compile, Analyze, Coordinate, Monitor and Evaluate Implementation of ASDP II • Prepare and Review ASDP II component plans and budgets and submits to Lead Agency-ASDP II Component Coordination • Advice TDC on important issues related to ASDP II implementation Lead Agency Lead Agency-ASDP II Component Coordination Plan, Compile, Analyze Coordinate, Monitor and evaluate ASDP II component plans and budgets (ASDP II) - and submits to ASDP II National Coordination Unit (NCU) Lead Agency Component Technical Committee • Chair: Head Lead Agency • Chairperson(s) of the Thematic Working Group (TWG) • Chair/Representative from the M & E TWG • Chair/Representative form the Planning and Budgeting TWG • Representative from NCU • Review submitted component plans, budgets; review and analyze reports; • Coordinate, monitor and evaluate ASDP II component plans and budgets • Submits to ASDP II National Coordination Unit(NCU) Agricultural Sector Development Programme II (ASDP-II) 257 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National ASDP II Secretariat/ ASDP II National Coordination Unit (NCU) Plan, Manage, Monitor, evaluate, harmonize and coordinate ASDP II. NCU compiles all interventions/ Project Plans and Budgets under ASDP II and develop draft consolidated annual work plans and budgets; Compile, analyze, coordinate, provide program logistical support; joint monitor, and evaluate of the program for onward submission to the Technical Committee of Directors (TCD) Technical Committee of Directors(TCD)9 • Chair: PS-MoA-Agriculture • Directors of ASLMS • PO-RALG ASDP II Coordination • Head of NIC • Head of Cooperatives, • Head Warehousing Licensing Board • NBS • Ministry of Finance and Planning • Ministry of Lands and Human Settlement • Tanzania Food and Nutrition Council • Ministry Energy • Ministry of Transport • Ministry of Education • Representative of Agricultural Research/Training Institutions • National Coordination Unit (NCU) Secretariat • Review, scrutinize and harmonize individual lead Agency Component ASDP II plans, budgets, monitoring and evaluation reports • Recommend to ASC governance and management guidelines and procedures for implementation of ASDP II • Recommend to ASC ToR for Joint Annual Reviews/Sector reviews/ Public Expenditure reviews (JSR/ASR/PER) Monitoring and Evaluation • Prepare and review papers for presentation to the ASCG and ASC • Review and propose to ASC policy and regulatory changes for the sector • Provide advisory and coordination role to the ASDP II thematic working groups. • Advice NCU on governance, management, coordination and operational issues Agricultural Sector Development Programme II (ASDP-II) 258 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National PS-MoA Plan, Manage, Monitor, evaluate, harmonize and coordinate ASDP II activities and organizes the TCD Agricultural Sector Consultative Group Meeting (ASCG) • Chair: Minister MoA • All Stakeholders in the Agricultural Sector (GoT, Private Sector, Development Partners/Donors and NGOs/ NSA) (local and International) • Training and Research Institutions • DPP- MoA Secretariat • NCU- Recorder • Provide advice on sector issues • Provide support (financial, material and others) to the sector • Participate in Joint Planning and Budgeting Meetings • Advise on sector policies, • plan, budgets, public and agricultural expenditure review National Minister, Ministry of Agriculture (MoA) Agricultural Sector Steering Committee (ASC) • Chair: Minister MoA • Permanent Secretaries of ASLMs • Representatives of Development Partners (AWG- Chairs) (2 members) • Representatives of Private Sector (3 member) • Representatives of NGOs/ NSAs (3 members) • DPPs –ASLMs (Crops and Livestock • NCU-Secretariat • Review and approves ASDP II plans, budgets, monitoring and evaluation reports; • Approve ToR for Joint Annual Reviews/Sector reviews/Public Expenditure reviews(JSR/ ASR/PER) and Monitoring and Evaluation • Facilitate and approve establishment of ASDP II funding mechanisms; • Discuss issues of mutual concern and information sharing; • Review and approve ASDP II financial and audit reports, • Approve changes in policies and regulations for on ward submission to parliament • Recommend the National • Agricultural Stakeholder Meeting (NASSM) meeting calendar and agenda Agricultural Sector Development Programme II (ASDP-II) 259 LEVEL Management Role and Responsibility Decision Making Organ Composition Role and Responsibility National PMO Oversee the performance of the sector by providing directives and advice on the transformation of the agricultural sector • National Agricultural Stakeholder Meeting (NASSM) • Chair: Prime Minister (PM) • ASLM Ministers, • PSs of ASLMs • All Development Partners supporting and involved in agriculture • All Private Sector supporting and participating in agriculture • NGOs/NSAs working in agriculture • DPPs ASLMs Secretariat • NCU- Recorder • Provide policy advice and guidelines to the agricultural transformational agenda • Provide advice and guidelines for the implementation of ASDP II • Facilitate and provide support where needed. Note on Technical Committee of Directors171 171 Respective Directors of Lead Agency /Component Leaders for specific ASDP II Components will be in attendance 260 Agricultural Sector Development Programme II (ASDP-II) ANNEX XIII: Principles for responsible Investment in Agriculture (FAO, August 2014) Principle 1: Contribute to food security and nutrition Principle 2: Contribute to sustainable and inclusive economic development and the eradication of poverty Principle 3: Foster gender equality and women’s empowerment Principle 4: Engage and empower youth by access to productive resources, services, education and innovation Principle 5: Respect tenure of land, fisheries, and forests and access to water Principle 6: Conserve and sustainably manage natural resources, increase resilience and reduce disaster risks Principle 7: Respect cultural heritage and traditional knowledge, and support diversity and innovation Principle 8: Promote safe and healthy agriculture and food systems Principle 9: Incorporate inclusive and transparent governance structures, processes and grievance mechanisms Principle 10: Assess and address impacts and promote accountability ANNEX XIV: Key Reference Documents 1-1 ASDS 2001 01-2 ASDS-2 Revised draft 2014 October 01-3 ASDS-2 Review of Implementation Indicators – Version 24 August 2013 (ESRF) 02-1 ASDP II Programme Document 02-2 ASDP-1 M&E_Framework_Revised_March 2011 03 TAFSIP Final version 2012 04 CAADP COMPACT Final 07 07 2010 05-1 National Agricultural Policy 2013 05-2 Livestock-Policy 2006 05-3 Agricultural Marketing Policy 2008 06-1 ASDP-1 Irrigation impact assessment 06-2 ASDP-1 Extension impact assessment 06-3 ASDP-1 Local Infrastructure impact assessment_ July 2014 06-4 ASDP-1 Final Report (Agricultural Support Service) TEAGASC Review Group 13-02-11 06-5 Final Environmental and Social Audit Report 2014 December 06-6 ASDP EVALUATION Final Report June 2011 06-7 ICR ASDP Draft Final July 2014 07-1 Agricultural BRN - Executive Summary 07-2 Agricultural BRN 2013 (6 June) Agric Lab (detailed report) 07-3 Agricultural BRN - PDB - Stakeholder engagement meeting 08-0 ASR-PER-2014_TZ-Mainland_v0 Annex1 08-1 ASR-PER 2011-12 Final Submitted 08-2 ASR-PER 2010-11 Final Report Edited and Submitted March 2011 (2) 09-0 RBA Agriculture 2014 Background Note 09-1 RBA Agriculture 2013 Background Note -Near Final Draft (2) 2013-11-05 09-2 RBA Agriculture 2012 Agriculture RBA2012_9 Jan2012 10-1 Tanzania Development Vision 2025 10-2 MKUKUTA_II_01 10-3 LTPP_2012-03-19_PRINT 10-4 5-Year Plan Draft (June 2011) 11-1 MAFAP Preliminary_Analysis_of_Public_Expenditures_in_Tanzania_Jan 2013 12-0 PHC-2012 National Socio-Economic Profile_ 26 APRIL 2014 12-1 PHC-2012 Census General Report - 29 March 2013_Combined_Final for Printing 13-1 NSCA v2 Final Crops National Report 11 June 2012 14-1 DGP-Macroeconomic data 15 ASDP Basket Fund 2 preparation 2013 June PD Draft 25 Jun-2013 Draft final - Main text PD Draft 25 Jun-2013 Draft final – Annexes 16 ASDP Basket Fund 2 preparation 2013 August revised ASDP II-BF version 5.2 Comments ASWG- 31-07 2013 response to comments 261 Agricultural Sector for Industrial Development Master 4 Annex ASDP II-BF-BRN 17 TZ Mainland ASDP IIworkshop report 2013 September 18 Bank of Tanzania report MER Monthly Economic Review October 2014 [1] QEB Quarterly Economic Bulletin June 2014 [1] 19 National Sample Census of Agriculture. 2007–2008 (from National Bureau of Statistics) 13-1 NSCA Final Crops National Report 11 JUNE 2012 Table 2.1.4 Types of Ag HH by types and size 1 Table 2.1.8 Types of Ag HH by types and size 2 Table 5.8 Crop production (short & long rainy season) by regions Table 5.11 Crop production by household Table 5.14 Crop production (yield in t/ha) 20 PER_NAIVS_ National Ag. Input Voucher System (NAIVS) Tanzania_Final_Report-March_2014Feb 21 Tanzania_NAIVS Agricultural PER 2013_4 22 2011-12 HBS Main Report (Household Budget Survey) 23-1 General Report on Donor Funded Projects 2011-12 23-2 General Report on Donor Funded Projects 2010-11 24-1 Donor Mapping List (AWG) 24-2 Donor Mapping List (TAN-AIM) 262 Agricultural Sector Development Programme II (ASDP-II) | false |
# Extracted Content TROPICAL PESTICIDES RESEARCH INSTITUTE - ARUSHA - TANZANIA 15th November, 2007 LIST OF PESTICIDES REGISTERED IN TANZANIA (Made under Section 18 of the Plant Protection Act, 1997 and Plant Protection Regulations GN 401 of 1999) 1. PESTICIDES REGISTERED FOR GENERAL USE FOR FIVE YEARS (FULL REGISTRATION) 1A: INSECTICIDES: ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Abiotic Abiothrin IN/0309 Permethrin+ Abiotic Systems control of mosquitoes and houseflies Trading Actara 25WG IN/0303 Thiamexotham Syngenta Crop against aphids and whiteflies in tobacco Protection AG Actellic Super IN/0002 Pirimiphosmethyl Syngenta Ltd Stored products against insect dust + Permethrin (UK) pests Akrimactin IN/0294 Abamectin Willowood Ltd against spidermites on roses Hongkong Antokil 5EC IN/0290 Chloropyrifos Equatorial Africa against tomato fruitworm Asafat 75 SP IN/0312 Acephate Osho Chemical Ind. Control of insect pests in French beans Attakan IN/0252 Imidacloprid Arysta LifeScience Control of aphids on roses 350 SC Bamethrin 2.5 EC IN/0323 Deltamethrin Bajuta General Vetagro control of aphids on cabbage Baygon multi- IN/0307 Imiprothrin+ Johnson Wax (EA) for mosquito control Purpose insect Cyfluthrin killer Bemistop IN/0226 Dioctyl Sodium Arysta LifeScience Control of white flies on tomatoes Succinate Bistar 10WP IN/0304 Bifenthrin FMC mosquito control indoors Confidor IN/0282 Imidacloprid Bayer(E.A) Ltd On ornamentals, vegetables, tobacco WG 70 against chewing and sucking inset pests Cruiser IN/0249 Thiamethoxam Syngenta Crop Seed dressing against seedling pests 350FS Protection AG in maize, wheat ,barley and cotton. Cyclone 505EC IN/035 Cypermethrin10%+ Osho Chem. Ind. Control of insect pests in roses Chlorpyrifos 35% Dasba 40EC IN/0321 Chlorpyrifos Bajuta General Vetagro control of tomato fruitworm ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Deltapaz IN/0212 Deltamethrin Balton (T) Maize against stalkborers 2.5EC Ltd Deltra 2.5EC IN/0279 Deltamethrin Invectra Agro control of tomato fruitworm Dimilin 25WP IN/0310 Diflubenzuron Crompton Control of mosquitoes and housefly larvae (Uni Chem) Dudual 450EC IN/0324 Cypermethrin+ Hangzhou Agrochemical control of cabbage webworm Cloropyrifos Industries Dynamec IN/0250 Abamectin Syngenta Spidermites on greenhouse roses 1.8 EC Crop Protection Dume 40EC IN/0319 Dimethoate Linkfoward Co. Ltd insect pests in tomatoes and roses Fastac IN/0306 Alphacyper- BASF control of tomato fruitworm/bollworm 10 EC methrin Fenom IN/260 Prophenophos + Syngenta Crop Control of insect pests on cotton, Plus 315 Lambdacyhalothrin Protection AG and vegetables Fenpa IN/0130 Esfenvalerate Sumitomo Cotton against chewing and sucking 2.5 EC pests Fighter IN/0276 cypermethrin Bytrade(T) Ltd against mosquitoes & cocroaches Aerosol +d-tetramethrin Fury 0.6% IN/0262 Zetacypermethrin Juanco Sps Ltd on cotton against cotton pests ULV Golan IN/0298 Acetamiprid Fluence Middle(EA) control of aphids on roses Helarat IN/0246 Lambdacyhalothrin Helm AG Control of Helicoverpa armigera 5 EC and Aphis gossypii on cotton Icon 10CS IN/0275 Lambdacyhalothrin Syngenta mosquito control Insectido 5EC IN/0300 lambda cyhalothrin Handelsgesellshaft control of insect pests in cotton Detlef von Appen mbH Keshet Super IN/0289 Deltamethrin+ Makhteshim control of insect pests in cotton and cabbage 312EC Chloropyrifos Chemical Works Kiboko Mosq. IN/0267 d-allethrin H.B. Worldwide mosquito control Coil Kombora aerosol IN/0325 tetramethrin+ 21st Century Holdings against mosquitoes Cypermethrin Ltd; DSM Kombora mosquito IN/0326 d-allethrin 21st Century Holding against mosquitoes Coil Ltd; DSM Kotkil 200EC IN/0291 Fenvalerate Equatorial Africa against tomato fruitworm ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ K-OTab123 IN/0284 Deltamethrin Bayer Env.Science bednet impregnation for control of RSA mosquitoes KungFu 5EC IN/0320 Lambda cyhalothrin Linkfoward Co. Ltd insect pests in roses and tomatoes Lambdacal IN/0261 Lambda- Arysta LifeScience Control of ABW on tomatoes 50EC cyhalothrin Lambdex 5EC IN/0295 lambda cyhalothrin Makhteshim Chemical control of insect pests in cotton,and Works aphids on roses. Lambdex Super IN/0296 lambda cyhalothrin+ Makhteshim control of insect pests in cotton and tomatoes 315EC chlorpyrifos Chemical Works Mortein Doom IN/0266 Imiprothrin+ Rekitt & control of crawing and flying Fastkill all insect phenothrin Benkiser E.A. Ltd insects Killer Mortein doom IN/0281 Imiprothrin+ Reckitt Benkisser control of mosquitoes Odourless all d-phenothrin Insect killer Mortein Doom IN/0265 cypermetrhin+ Rekitt & control of mosquitoes Fast knockdown imiprothrin + Benkiser E.A. Ltd Cockroach&ant killer d-allethrin Mosquiron 100EC IN/0293 Novaluron Makhteshim mosquito larvae control Mukpar-Dimethoate IN/0288 Dimethoate Equatoria Africa Ltd control of whiteflies on tomatoes 40 EC Neemraj Super IN/0283 Azadirachtin Neem-India bollworm on cotton Nimbecidine 0.03% IN/0311 Azadirachtin OSHO Chem. Industies control insect pests of French beans, Tomatoes and roses Oberon 240SC IN/0301 spiromesfen Bayer(E.A) Ltd control of spidermites on roses Olyset Net IN/0264 permethrin A-Z Textile bednet impregination Pegasus 500SC IN/0243 Diafenthiuron Syngenta Crop Control of spidermites and aphids on Protection AG greenhouse roses Permanet IN/0278 Deltamethrin Vestergaad Frandsen treatment of mosquito nets Profit 720EC IN/0299 Profenofos Handelsgesellschaft control of tomato fruitworm Detlef von Appen Hamburg,Ge rmany Pyagro™ 4EC IN/0286 Pyrethrins Pyrethrum Board diamond backmoth in cabbage of Kenya Pyrinex Quick IN/0297 Deltamethrin+ Makhteshim control of cabbage webworm 256ZC Chloropyrifos Chemical Works ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Raid Multipurpose IN/0308 Imiprothrin+ Johnson Wax (EA) for mosquitoes control Insect killer Prallethrin Risasi mosquito IN/0285 Pyrethrin Meghjis Sundries mosquito control Coil (Pyrethrin) Ridsect Chalk IN/0268 Deltamethrin SaraLee Household & Control cockroaches, ants and bedbugs Body Care (K) Ltd Rufast 075EW IN/0302 Acrinathrin Cheminova A/S spidermites on roses Denmark Skana Super IN/0318 malathion+ Osho Chemical Ind. Control of grain storage insect pests dust Permethrin Sevin IN/0305 Carbaryl Bayer Environmental against ectoparasites on dogs and poultry Dududust 7.5% Science Spintor IN/0273 Spinosad Dow Agro Control of grain borer, weevils and Dust other insects in stored grain and pulses Stocal IN/0235 Permethrin + Arysta LifeScience Control of LGB and maize weevils Super Dust Pirimiphos methyl Subachlo 48EC IN/0280 Chlorpyrifos Suba Agrotrading against tomato fruitworm Sumicidin IN/0126 Fenvalerate Sumitomo Cotton against American bollworms 20 EC spinybollworms Shumba Super In/0322 Fenitrothion Ecomark Ltd treatment of structrures ued for gein storage 50EC Sumicidin IN/0125 Fenvalerate Sumitomo Cotton against American bollworms 3 ULV spiny bollworms. Vertigo IN/0253 Abamectin Almandine spidermites on roses 1.8EC Tafogor 40EC IN/0317 Dimethoate OSHO Chem. Industies control of insect pests in roses Tata Alpha 10EC IN/0313 Alphamethrin OSHO Chem. Industies control of insect pests in French beans Tatamida IN/0314 Imidacloprid OSHO Chem. Industies control of insect pests in tomatoes 200g/L SL Tata Reeva 5EC IN/0316 lambda cyhalothrin OSHO Chem. Industies control of insect pests in roses Total Mosq IN/0270 d-allethrin Total(T) Ltd mosquito control Coil Total insecticide IN/0271 Pallethrin Total (T) Ltd mosquito control aerosol X-Pel IN/0131 Pyrethrins Mansoor Daya Household against mosquitoes. Trigard 75WG IN/0258 cyromazine Syngenta Crop Pr. Control of tomato leaf minor Zetabestox IN/287 Zeta-cypermetrhrin Juanco Sps on Cotton 10%EC ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ 1B: FUNGICIDES: April FU/0123 Tebuconazole Hamashbir Agri- control of powderly mildew on roses Culture Ltd.Israel Anchor 200FS FU/0127 carboxin and Crompton seed treatment on wheat Thiram (Uniroyal Chem) Apron Star FU/0095 Thiamethoxam + Syngenta Crop Control of soil borne pests and 42 WS Difenoconazole + Protection AG diseases in maize,beans ,sesame Metalaxyl and sorghum Ardent FU/0088 Kresoxim methyl Makhteshim Control of powdery mildew on roses. Banko FU/0120 Chlorothalonil Arysta LifeScience control of late blight in tomatoes 720 SC Champion FU/0038 Cupric Hydroxide Nufarm GmbH Coffee against leafrust and CBD, 50 WP tomatoes against bacteria leafspot and late blight and cucumber against alternaria and downy mildew. Cobox FU/0044 Copper BASF AG Coffee, Vegetables against CBD, 50 Oxychloride leafrust, downy mildew. Cuprozin FU/0100 Copper Oxychloride Spiess Urania Coffee against leaf rust and CBD 35WP Chemicals Defender 240EC FU/0119 Triadimenol Handelsgesellschaft powderly mildiew on roses Detlef von Appen mbH Dividend FU/0087 Difenoconazole Syngenta Crop Seed treatment fungicide in wheat and 030FS Protection AG barley Fungozeb 80WP FU/0118 Mancozeb Handelsgesellchaft control of late blight on tomatoes Helcozeb FU/0086 Mancozeb Helm AG Control of late blight on tomatoes 80 WP Impulse 500EC FU/0104 spiroxamine Bayer(E.A) Ltd powdery mildew in fluoriculture Indofil M-45 FU/0110 Mancozeb Equatorial Africa Ltd control of late blight in tomatoes Ivory FU/0090 Mancozeb Arysta LifeScience Control of late blight on tomatoes 80 WP Ivory M72 FU/0097 Mancozeb+ Arysta LifeScience early blight in potatoes Metalaxyl Kocide 101 FU/0045 Copper Hydroxide Du Pont de Coffee, tomatoes, beans and peanuts Nemours against CBD and various fungal diseases. ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Kwadris FU/0098 Azoxytrobin Syngenta CBD ,Coffee leaf rust,vegetables and grapes Linkmil72WP FU/0124 Mancozeb+ Linkfoward Co. Ltd late blight in tomatoes Metalaxyl Maxim XL 035FS FU/0128 Fludioxonil+ Syngenta maize seed treatment against soil borne Metalaxyl-M diseases Nimrod FU/0092 Bupirimate Makhteshim Control of powdery mildew of roses 25EC Chem under greenhouse conditions. Odeon 82.5 WDG FU/0113 Chlorothalonil Makhteshim control of late blight on tomatoes Orius FU/0089 Tebuconazole Irvita Control of powdery mildew on roses. 25 EC Pilarich 500SC FU/0108 Chlorothalonil Pilarquim (Shanghai) control of late blight diseases In tomatoes Pilarzeb 80WP FU/0109 Mancozeb Pilarquim (Shanghai) control of late blight diseases in tomatoes Rova 720SC FU/0122 Chlorothalonil Almandine corporation control of late blight diseases of tomatoes Royalcop FU/0099 copper oxychloride Mukpar(T) tomato late blight 50WP Subatil 250EC FU/0125 Propiconazole Suba Agro control of foliar diseases on barley Sunstar 72WP FU/0129 Metalaxyl Riyue Chemicals control of tomato blight + Mancozeb Ltd; DSM Suprano C FU/0112 Epoxyconazole+ Makteshim Agan control of foliar diseases of wheat Carbendazim and barley Swing FU/0117 Carbendazim+ BASF fungal diseases in wheat and barley epoxiconazole Tecto 500SC FU/0108 Thiobendazole Syngenta Crop powderly mildew in roses Protection AG Thiovit Jet FU/0033 Sulphur Syngenta Crop grapes,vegetables and ornamentals Protection AG against brown rot scab and mildew; Cashew against powderly mildew Ugonall 580WP FU/0126 Mancozeb+ Hangzhou Agrochem. Control of late blight in tomatoes Metalaxyl industries Victory 72WP FU/0111 Mancozeb+ Fluence Mid.East late blight in tomatoes Metalaxyl Zolfo Ventilato FU/0106 Sulfur Zolfindustria S.R.L powderly mildiew in cashew ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ 1C: HERBICIDES: Atranex 50 SC HE/0124 Atrazine Agan Chem weeds in sugarcane plantations Attribute 70 WG HE/0151 propoxycarbazone Bayer(E.A) Ltd perrenial and annual grass weeds -sodium in wheat Cottoran HE/0020 Fluometuron Makhteshim On cotton against 500 FLW Chem Works broad leaved weeds. FarmBase HE/0119 2,4 D FarmBase Broad leaf weed control in wheat 2 4 D Amine Fusilade Forte HE/0140 Fluazifopbutyl Syngenta control of grass weeds in beans and tobacco,and as a ripener in sugarcane Galigan 240EC HE/0125 Oxyfluorfen Agan Chem Weeds in sugarcane Plantations Gramoxone HE/0072 Paraquat Syngenta Ltd In maize,coffee, tea, (UK) sisal, cotton,, bananas, sugarcane against common leaves and annual weeds Hussar HE/0118 Iodosulfuron- Bayer(E.A) Ltd Broad leaf weed control in wheat Methyl-Sodium Krismat HE/0132 Trifloxysulfuron Syngenta Crop Control of cyperus, dicot and some 75 WG Sodium + Ametryn Protection AG grasses in sugarcane Lumax HE/0141 S-Metolachlor + Syngenta Crop weeds control in sugarcane and maize Mesotrione + Protection AG Triazine MSMA 720SL HE/0146 MSMA Dow AgroSciences On sugarcane against annual grasses and certain broad- leaved weeds Pencal 500EC HE/0133 Pendimethalin Arysta LifeScience weeds in sugarcane Quattro HE/0152 Bromoxynil octanoate + Nufarm BMBH Co. selective post emergency herbicide MCPA ester in wheat Puma Komplete HE/0143 Fenoxapropyl-p-ethyl Bayer E.Africa Ltd post emergency control of grasses +iodosulfuron methyl and broad leaved weeds and sedges in wheat Servian HE/0117 Halosulfuron- Syngenta Crop Control nutsedge in maize and 75WG Methyl Protection AG sugarcane Sancopax A HE/0126 ametryne+ Dow Agroscience weeds in sugarcane Atrazine plantations Sencal HE/0134 Metribuzin Arysta LifeScience weeds in sugarcane plantations 480 SC Sekator OD 375 HE/0155 Iodosulfuron-methyl Bayer (E.A)Ltd broad leaved weeds in wheat and barley + amidosulfuron ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Solito 320 EC HE/157 Pretilachlor+ Syngenta Crop Protection weed control in rice Pyribenzoxim Twiga amine HE/0144 2,4-D Amine Twiga Chemicals control of broad leaved weeds in wheat 720 g/L Volacet HE/0135 Acetochlor Volcano Agro Control weeds in sugarcane 900EC Tiara WG 60 HE/0142 Flufenacet Bayer E.Africa pre-emergeny weeds in wheat and barley Touchdown HE/0139 Glyphosate Syngenta Crop Pre-plant application for control of Forte Protection AG weeds in coffee,tea,cashew and cereals Triatril MC HE/0149 Bromoxynil+ Trade base Ltd(UK) some weed species in wheat MCPA Volazinone HE/0123 hexazinone Volcano Agroscience weeds in sugarcane Volbuzine HE/0122 Metribuzine Volcano Agroscience weeds in sugarcane Volmetra 500SC HE/0121 Ametryne+ Volcano Agroscience weeds in sugarcane Atrazine Voliuron 800SC HE/0127 Diuron Volcano Agroscience weeds in sugarcane plantations Volchlormuron HE/0137 Chlorimuron- Volcano Agro weeds in sugarcane plantations Ethyl Volmet HE/0129 Metolachlor Volcano Agroscience weeds in sugarcane plantations Volmethalin HE/0128 Pendimethalin Volcano Agroscience weeds in sugarcane plantations Volmsma HE/0145 MSMA Volcano Agro Against weeds in sugarcane 720 SL Volmuron HE/00130 Paraquat + Volcano Agrosciences for weed control in sugarcane Diuron Volsate 360 HE/0136 Glyphosate Volcano Agrosciences weeds in sugarcane Weedall 480SL HE/0156 Glyphosate Hangzhou Agrochemicals control of weeds in bananas Wildbees HE/0147 2,4 D Amine Volcano Agro Control of weeds in 720 SL sugarcane plantations 1D: PLANT GROWTH REGULATORS: Pix 50 GR/0001 Mepiquat BASF AG Growth regulator on Chloride cotton. Prime+125 GR/0002 Flumetralin Syngenta(UK) control of tobacco suckers ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ I E: RODENTICIDES Brodek RO/0006 Brodifacoum March Chem. Rodent control Raticide RO/0005 Bromadiolone FarmBase Control of field and household rodents IF: ACARICIDES Alphatix 12.5 EC AC/0028 Amitraz Ultravetis E.A Ltd control of cattle ticks Amitan 12.5EC AC/0034 Amitraz Biotec Laboratories control of cattle ticks Bamitraz 12.5 EC AC/0030 Amitraz Bajuta General Vetagro control of cattle ticks Cybadip 15EC AC/027 Cypermethrin Bajuta General Vetagro control of ticks and tsetseflieds Ecotix 100EC AC/0025 cypermethrin high cis Farmbase against ticks and tsetse Kupatix 12.5EC AC/0033 Amitraz Cooper K-Brands Ltd control of cattle ticks Notix AC/0032 Deltamethrin Rotam Agrochemical against cattle ticks Co;Hong-Kong Paratryn 15% AC/0024 Cypermethrin Merial R.S.A ticks control Paratraz 12.5EC AC/0027 Amitraz Merial R.S.A Control of ticks (Uniroyal Chem) Tixfix C/0019 Amitraz Twiga Chem Control of ticks on cattle. Tick buster 12.5EC AC/0031 Amitraz Chemplex Animal against cattle ticks & Public Health Tiktik 12.5EC AC/0026 Amitraz Farmbase against ticks and mange Vectocide EC AC/0023 Deltamethrin Ceva Sante ticks and tsetse II: PESTICIDES REGISTERED FOR GENERAL USE FOR TWO YEARS (PROVISIONAL REGISTRATION): IIA: INSECTICIDES: ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- ABC Mosquito IN/0171 d-Allethrin Alfa General Control of mosquitoes Coil Supplies Actellic IN/0224 Pirimiphosmethyl Syngenta Ltd disinfestations of storage 50 EC (UK) structures. Adonis IN/0179 Fipronil BASF Agro BV Against desert locusts 12.5 ULV Akheri Powder IN/0165 Carbaryl + FARMBASE Dogs and cats against, Cyhalothrin other household insects Alphaguard IN/0200 Alphacyper- Fertilizer Various crops against 0.8ULV methrin & Chem. insects pests. Amdro IN/0163 Hydramethyl BASF Against ants in Coconuts Attakan C IN/0277 Cypermethrin + Arysta LifeScience Control of bollworms and sucking pests 344 SE Imidacloprid on cotton Balton IN/0203 Abamectin Balton (T) Control of maize stalk Abamectin 1.8EC borers. Baygon IN/0015 Propoxur Johnson Wax (EA) Household against Aerosol cockroaches and flies. Baygon IN/0016 Propoxur Johnson Wax (EA) Household against 1% DP Cockroaches and flies. BigTox IN/0195 Fenitrothion + Star Import Mosquito control. Aerosol Permethrin & Export BigTox IN/0190 Pyrethrins Star Import Mosquito Control. Mosquito & Export Coil Black Jack IN/0197 Tetramethrin Safeguard Chem. Mosquito Control. Bolt Insect IN/0194 Pyrethrins + Ariman Mosquito control. Killer Permethrin Technologies ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- Bulldog IN/0214 Betacyfluthrin Bayer(E.A) Ltd On cotton against 2.5EC Helicoverpa amigera and Aphis gossypi in Eastern Tanzania Bulldog IN/0138 Betacyfluthrin Bayer(E.A) Ltd Cotton against bollworms, 005 ULV jassids, calidea and lygus Bulldock Star IN/0228 Betacyfluthrin Bayer(E.A) Ltd Control of sucking insects 262.5 on cotton. Callidim IN/0236 Dimethoate Arysta LifeScience Control of whiteflies in 400 tomatoes Callisulfan IN/0177 Endosulfan Arysta LifeScience On cotton against American 250ULV bollworms and aphid Commando IN/0181 Pyrethrins + H.B Worldwide Mosquito control. Aerosol DDVP Ltd Commando IN/0184 Pyrethrins H.B Worldwide Ltd Mosquito.control. Mosquito coil Confidor IN/0207 Imidacloprid Bayer(E.A) Ltd Control of aphids in 200SL greenhouse roses Confidor IN/0242 Imidacloprid Bayer Environmental Control of migratory locusts 010 ULV Sciences and grasshoppers. Crowned Crane IN/0185 Pyrethrins Mark Rays Mosquito control. Mosquito Coil E.A Ltd. Cypercal IN/0175 Cypermethrin + Arysta LifeScience Cotton against aphids,whitefly D15/120ULV Dimethoate whitefly, caterpillars and hemiptera. Cypercal IN/0178 Cypermethrin Arysta LifeScience Cotton against American 1.8ULV bollworms and aphids . Cyperguard IN/0201 Cypermethrin Fertilizer & Various crops against 1.8 ULV Chem. insect pests. DC Tron IN/0232 Paraffinic Oils Caltex (T) Ltd Control of major insect pests Plus of tomatoes, roses and citrus Trees Decis 25 EC IN/0032 Deltamethrin Bayer(E.A) Ltd Coffee, vegetables against chewing insect pests ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- Decis 0.5 IN/0030 Deltamethrin Bayer(E.A) Ltd Cotton against chewing ULV insects pests locust and grasshoppers Decitab IN/0167 Deltamethrin Bayer(E.A) Ltd Cotton against Heliothis armigera larvae Deltis IN/0248 Deltamethrin Almandine Control of Diamondback moth on 2.5% EC Corp. cabbage Diazol IN/0239 Diazinon Makhteshim Control of diamondback moth on 50 EW Chem cabbage. Dimepaz IN/0204 Dimethoate Balton (T) Maize against stalk borers 40EC Ltd Dursban IN/0042 Chloropyrifos Dow Agro Coffee and beans against 4E chewing and sucking insect. Mosquito and Subterranean termites control. Dursban IN/0041 Chlorpyrifos Dow Agro Coffee and beans against 24ULV chewing and sucking i nsect pests. Public health for mosquito control. Fendona IN/0143 Alpha- BASF Tsetsefly, bed net impregnation for 6 SC Cypermethrin mosquitoes control, cockroach, bedbugs, other biting and nuisance Fendona IN/0169 Alpha- BASF Against mosquitoes, Cockroaches 10SC Cypermethrin and bedbugs pests Fenkil IN/0263 Fenvalerate United Cotton against chewing & sucking 20 EC Phosphorus Ltd. insect pests. Fenom C IN/0145 Profenofos + Syngenta Crop Cotton against jassids calidea and 170 ULV Cypermethrin Protection AG judgus. Flak IN/0053 Pyrethrins Sapa Chem Household against domestic Aerosol insect pests. Flyex IN/0055 Pyrethrins Rose Lab. Household against domestic insect Aerosol Pests Flyex IN/0054 Pyrethrins + Rose Lab Household against domestic insect Solution Malathion pests Fyfanon IN/0057 Malathion Cheminova Cotton, tobacco and pasture against 500g/l A/S chewing and sucking pests. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ------------ Gaucho IN/0227 Imidacloprid Bayer(E.A) Ltd Control of sesame flea beetle 350FS Gladiator IN/0229 Chlorpyrifos Dow Control of subterranean termites 4TC AgroSciences Goodnight IN/0221 d-Allethrin Godrej Hi Care Household against mosquitoes Mosquito Coil Goodnight IN/0173 d-Allethrin Godrej Hi Household against mosquitoes. Mosquito Care Ltd. Mat Hatari IN/0172 d-Allethrin Star Import Household against mosquitoes Brand and Export Mosquito Coil Hatari IN/0166 Fenitrothion + Star Import Against flying and crawling insects Aerosol Tetramethrin and Export Icon IN/0147 Lambda Syngenta Ltd Mosquito control 10 WP Cyhalothrin (UK) Iconet IN/0213 Lambda Syngenta Ltd Bednet and curtains Cyhalothrin (UK) impregnation for mosquito control Karate IN/0245 Lambda- Syngenta Ltd against bollworms and aphids in 5 CS Cyhalothrin (UK) cotton and vegetables Karate IN/0148 Lambda Syngenta Ltd against bollworms and aphids 5 EC Cyhalothrin (UK) in cotton and vegetables Karate IN/0127 Lambda Syngenta Ltd Cotton against a wide range 2 ED Cyhalothrin (UK) of insects. Kasheshe IN/0220 d-Allethrin M & S Household against mosquitoes Mosq. Coil Intertrade Keshet IN/0211 Deltamethrin Makhteshim Maize against stalk borers 2.5EC Chem Works Kiboko IN/0159 Fenitrothion H.B. Worldwide Mosquitoes, cockroaches Aerosol Ltd and other household insect pests. Kilit IN/0202 Neo-pynamin MIMCO Mosquito control Inter (T) Ltd Kohinor IN/0292 Imidacloprid Makhteshim control of aphids in greenhouse roses K-Othrine IN/0216 Deltamethrin Bayer Environm. Scienc. Bednet impregnation for mosquito WP control ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- K-Othrine IN/0217 Deltamethrin Bayer Envir. Science Bednet impregnation for mosquito Mostiquarine conrtol 1% SC Lala Salama IN/0240 Allethrin SAJJAD Control of wild human-biting ALI LTD Anophelines and Culicines. Lebaycid IN/0063 Fenthion Bayer(E.A) Ltd Various crops against chewing and 50% EC sucking insects, termites and ants. Marshal IN/0209 Carbosulfan FMC Roses against aphids and mites 250EC Marshall IN/0158 Carbosulfan Incitec Int. For control of white SuScon grubs, cockroach, larvae and termites. Melcypermethrin IN/0150 Cypermethrin Melspring Cotton, coffee, tobacco, vine, 1.8ULV Intern. BV vegetables against berry borers, leaf miners and bollworms Mobil IN/0192 Tetramethrin + Mobil Oil Mosquito control. Insecticide D-Phenothrin + Tz. Ltd. Aerosol D-Allethrin Mosfly IN/0251 d-allethrin African Mosfly mosquito control Moskill IN/0199 Pyrethrins Coil Product Mosquito control. Mosquito (K) Ltd. Coil Motox IN/0160 Tetramethrin HVM INT. Against household insect Aerosol + Permethrin pests + Fenitrothion Mzinga IN/0255 Permethrin+ Sole Aero Ltd Mosquito control Tetramethrin Nafaka Super IN/0237 Fenitrothion + Ecomark Ltd Control of LGB and maize weevils Dust Permethrin Neocidol IN/0231 Diazinon Zagro Control of bedbugs and body lice 600 EW Ngao (K-Otab) IN/0215 Deltamethrin Bayer Envir. Science Bednet impregnation for mosquito control NK Diazinon IN/0034 Diazinon Nippon Kayaku livestock and pastureland ectopara- 60EC sites,chewing and sucking insects Novathion IN/0072 Fenitrothion Cheminova A/S Coffee against leaf miner, 500 EC chewing and sucking pests. Nuvan IN/0074 Dichlorvos AMVAC Crop storage and public 50 EC Corporation health against storage pests and household insects Orthene IN/0157 Acephate Arvesta Corp. Tobbaco, cotton, vegetables 75% SP against andsucking insect pests. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- Peropal IN/0206 Azocyclotin Bayer Greenhouse roses for control 25WP of spidermites Profecron IN/0233 Profenofos Agriscope (Africa) Control of diamondback moth in 720 EC Ltd cabbages Pyretox IN/0254 Pyrethrum Kibo Chemicals Post harvest pests on maize Raid IT IN/0234 Tetramethrin + Johnson Wax Mosquito control Cypermethrin + Propoxur Raid Mwananchi IN/0183 Pyrethrins Johns Wax Mosquito control. Mosquito Coil (E. A) Ltd. Redcans IN/0198 Pyrethrins Oasis Ltd. Mosquito control. Aerosol Ridsect IN/0193 Prallethrin + Kiwi Brand Mosquito control. D-Phenothrin Ltd. Rimon IN/0247 Novaluron Makhteshim Control of Diamondback moth 10 EC Chem. on cabbage. Risasi IN/0225 Tetramethrin + Meghji’s Household against mosquitoes Aerosol Cypermethrin Sundries Rungu IN/0162 Fenitrothion H.B Worldwide Mosquitoes, cockroaches, Aerosol + Permethrin Ltd houseflies and other + Tetramethrin household insect pests. Rungu IN/0186 Pyrethrins H.B. Worldwide. Mosquito control. Mosquito Ltd Coil Sapa BHC IN/0103 Lindane Sapa Chem Garden, hides & skins against 1% D chewing pests. Sapa Carbaryl IN/0090 Carbaryl Sapa Chem Crops, livestock, household 5% D against cutworms and beetles, animal ectoparasites, mosquitoes and cockroaches. Sapa Carbaryl IN/0091 Carbaryl Sapa Chem Cotton, against chewing and 85WP sucking pests. Sapa IN/0092 Cypermethrin Sapa Chem Coffee, tobacco, rice, Cypermethrin sugarcane against chewing 2.5%ULV and sucking pests. Sapa IN/0093 Diazinon Sapa Chem Coffee, tobacco, rice and Diazinon sugarcane against chewing 60 EC and sucking pests. Sapa IN/0096 Dimethoate Sapa Chem Various crops against aphids Dimethoate 40 EC and mites. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- Sapa IN/0097 Endosulfan Sapa Chem Maize, tobacco against stalk Endosulfan 4D borers and chewing pests. Sapa IN/0099 Endosulfan Sapa Chem Cotton against chewing Endosulfan and sucking pests. 25 ULV 35 EC Sapa IN/0101 Fenitrothion Sapa Chem Coffee, cashew, tobacco Fenitrothion storage against chewing 50 EC and sucking pests and pests of stored products. Selecron IN/0112 Profenofos Syngenta Crop Coffee, vegetables against 720 EC Protection AG chewing and sucking insects and cashew against mealy bugs. Sevin 85 WP IN/0113 Carbaryl Bayer Env. Science Crops, livestock, household against cutworms, beetles, ectoparasite and domestic insect pests Shumba IN/0238 Fenitrothion + Ecomark Control of LGB and maize weevils. Super Deltamethrin Simba IN/0191 Pyrethrins Coil Product Mosquito control. Mosquito (K) Ltd. Coil Solfac IN/0176 Cyfluthrin Bayer Environ. Science Against household pests and EW 050 bed net impregnation Suba Deltamethrin IN/0274 Deltamethrin Suba AgroTrading control of tomato fruit worm Sumicombi IN/0154 Fenvalerate + Sumitomo Against chewing and sucking 1.8 D Fenitrothion insects on various crops. Sumithion IN/0117 Fenitrothion Sumitomo Various crops against 50 EC chewing and sucking insect pests. Household against mosquitoes and flies and storage insects. Sumithion IN/0129 Fenitrothion Sumitomo Against mosquitoes 40 WP Supakill IN/0269 Pyrethrin+ Twiga Chemicals mosquito control Cypermethrin+ Tetramethrin Super Grain IN/0210 Bifenthrin Juanco SPS Ltd Stored grain insect pests Dust Control SuScon Blue IN/0137 Chlorpyrifos Incitec Int. Control of sugarcane grubs 140g/kg Talstar 100EC IN/0208 Bifenthrin FMC Roses against aphids and mites ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- Thiodan IN/0122 Endosulfan Bayer CropScience AG Various crops against 35 EC chewing and sucking pests. Thionex IN/0123 Endosulfan Makhteshim Various crops against 35 EC Agan chewing and sucking insect pests Tigaroda IN/0241 D-Allethrin Jan Holdings Control of wild human-biting Mosquito coil Anophelines and Culicines. Trig Aerosol IN/0187 Tetramethrin Chemipack Mosquito control. Tz. Ltd. Trig Mosquito IN/0188 d-Allethrin Chemipack Mosquito control. Coil Tz. Ltd. Ustaad IN/0170 Cypermethrin United On cotton against 1.8ULV Phosphorus sucking and chewing insects Ustaad IN/0174 Cypermethrin United On cotton against 10%EC Phosphorus sucking and chewing insects Vectron 10EW IN/0218 Etofenprox Mitsui Chemicals,Inc Bednet impregnation for Mosquito control Vectron 20EC IN/0219 Etofenprox Mitsui Chemicals,Inc Bednet impregnation for mosquito control White Crane IN/0189 Pyrethrins Mohamed Mosquito control. Mosquito Coil Enterprises Ltd Zap aerosol IN/272 tetramethrin+ Autoworld Trading Co mosquito control Cypermethrin Zapit IN/0256 s-bioallethrin+ SoleAero Ltd mosquito control bioresmethrin IIB: FUNGICIDES: Agrifos 400SL FU/0114 mono + dipotassium Agrichem PTY Ltd control of late blight in tomatoes phosphonate Australia Alto 100 SL FU/0048 Cyproconazole Syngenta Crop Coffee leaf rust. Protection AG Antracol FU/0001 Propineb Bayer (E.A)Ltd Tomatoes, potatoes, tobacco, 70% WP Blue ornamentals and coffee against various fungal d iseases. Anvil 5 SC FU/0050 Hexaconazole Syngenta Ltd Coffee against leaf rust and (UK) Cashew against powdery mildew .Banko 500 SC FU/0073 Chlorothalonil Arysta LifeScience Coffee against Coffee Berry ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- disease. Banko Plus FU/0080 Chlorothalonil + Arysta LifeScience Tomatoes against late blight. Carbendazim Baycor 300EC FU/0075 Bitertanol Bayer (E.A)Ltd Against foliage diseases in beans. Bayfidan FU/0051 Triadimenol Bayer (E.A)Ltd Coffee against leaf rust and 250 EC cashew against powdery mildew. Bayleton FU/0002 Triadimefon Bayer (E.A)Ltd Coffee and wheat against 25% WP leaf rust,and in cashew against powderly mildiew Benomilo FU/0093 Benomyl Makhteshim Control of powdery mildew 50 WP of roses under greenhouse conditions. Blue shield FU/0052 Copper Cuproquim S.A Coffee against CBD and Hydroxide other fungal diseases.. Bronocot FU/0040 Bronopol Mukpar(T) Ltd Cotton seed dressing 10WP Bronotak FU/0053 Bronopol Bayer CropScience AG Cotton Seed dressing. 10w/w Clortocaffaro FU/0055 Chlorothalonil Vischim Srl,Italy Coffee against leaf rust. 54 FLW Copper Nordox FU/0009 Cuprous Oxide Nordox A/S Coffee against CBD, leafrust. Copper Sandoz FU/0010 cuprous oxide Sandoz coffee against CBD and leaf rust Coprado FU/0084 Copper Oxychloride Helm AG Control of late blight on 50 WP tomatoes Cupravit 50 WP FU/0056 copper oxychloride Bayer (E.A)Ltd beans and groundnuts Against leafrust Cuprocaffaro FU/0054 Copper Isagro S.p.a Coffee against leaf rust. 50 WP Oxychloride Daconil FU/0091 Chlorothalonil Syngenta (UK) Coffee against CBD 720 SC Delan 75 WP FU/0013 Dithianon BASF Coffee against CBD and . leafrust. Dithane M-45 FU/0014 Mancozeb Dow Agrosciences Vegetables, beans, fruits against anthracnose scab, lateblight, rust, mildews. Farmerzeb FU/0102 Mancozeb Link Forward Co early blight and downy mildew In potatoes and tomatoes Folicur FU/0071 Tebuconazole Bayer (E.A)Ltd On wheat and barley 250EC against foliar diseases ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ---------------------------------------------------------------------------------------------------------- ----------- Folpan FU/0094 Folpet Makhteshim Control of lateblight of 50 WP tomatoes Funguran-OH FU/0061 Copper Urania Coffee against CBD and Hydroxide leafrust. Galben M FU/0083 Benalaxyl + Twiga Chem. Control of late blight on Mancozeb tomatoes. Helmonyl FU/0085 Chlorothalonil Helm AG Control of late blight on 500 tomatoes. Kocide DF FU/0064 Copper Du Pont de Coffee against fungal disease Hydroxide Nemours and CBD Kumulus DF FU/0018 sulphur BASF grapes,vegetables,cashewnuts,ornamentals against brownrot,scab,mildew,mites and scales Linkonil FU/0101 chlorothalonil Link Forward Co. Ltd against late blight in tomatoes and potatoes Milraz FU/0078 Propineb + Bayer (E.A)Ltd Tomatoes against late blight 76WP Cymoxanil disease Milthane Super FU/0082 Mancozeb Twiga Chem. Control of late blight on Tomatoes Nordox 75WG FU/0096 cuprous oxide Nordox A/S control of late blight on tomatoes Nordox FU/0023 Cuprous oxide Nordox A/S Seed dressing for cotton SD-45 against bacterial blight and damping off. Palm Brand FU/0069 Sulphur National Est. Cashew against powdery Dusting Sulphur mildew Perecopper FU/0058 Copper- Chemol Impex Coffee against CBD, 50% WP Oxychloride Hungarian leafrust. Trading Co. Ridomil Gold FU/0079 Mancozeb + Syngenta Crop against late blight disease 68WG Metalaxyl Protection AG in potatoes,tomatoes and grapes. Rido Super FU/0103 mancozeb+ Suba Agrotrading control of late blight in tomatoes 72 WP metalaxyl Rova 500 FU/0043 Chlorothalonil Vischim Srl,Italy Coffee against CBD. Sabcop 50WP FU/0076 Copper Koppa Against CBD and CLR Oxychloride in coffee. Sapa Copper FU/0030 Copper Sapa Chem Coffee, beans, Oxychloride oxychloride Chemicals Ltd vegetables, grapes against blights, mildew, brown rot Sancozeb FU/0081 Mancozeb Dow Agrosciences Tomatoes against late blight 800 WP Silvacur FU/0072 Fenetrazole + Bayer (E.A)Ltd On wheat and barley Terbutrazole + against foliar diseases Triadimenol ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- SeedPlus 20WS FU/0116 Imidacloprid+ Fluence Middle EA control of early insect pests and soil Metalaxyl+ + Balton(T) borne diseases in maize and beans Carbendazim TAFECO FU/0070 Sulphur TFC Control of powdery mildew Sulphur in cashew. Tankopa FU/0077 Copper Pesticide Coffee against CBD and CLR Oxychloride Manufacturers Tilt 250 EC FU/0034 Propiconazole Syngenta Crop Wheat, barley, sugarcane, Protection AG coffee, grapevine against rust blotch and mildew. Topsin-M FU/0035 Thiophanate Nippon Soda Rice, wheat, tobacco, 40 ULV vegetables against leafspot, powdery mildew, scab and blight. Topsin-M FU/0036 Thiophanate Nippon Soda Rice, wheat, tobacco, 70% WP methyl vegetables against blast leafspot, powdery mildew, scabs and blight. Trical FU/0105 Triadimefon Arysta LifeScience On roses against powdery 250 EC mildew. IIC: HERBICIDES: Actril DS HE/0001 Ioxynil + Bayer(E.A) Ltd Cereals against 2,4 - D broad leaved weeds. Agil 100EC HE/0150 propaquizafop Agan Chemical Manufac. annual and perrenial grasses in beans Ariane HE/0101 Fluroxypur + Dow Agrosciences Against broad- leaved EF 609 Chlorpyralid weeds in wheat and + MCPA barley. Atramet HE/0096 Atrazine + Agan Chem. Sugarcane against Combi 50SC Ametryne grasses and broad leaf weeds Atranex HE/0098 Atrazine Agan Chem. Maize against 80WP pre-emergence weeds. Badge HE/0148 MCPA+ Agan Chemical post emergency weed control Bromoxynil octanoate Manufacturers in maize Balton 2-4D HE/0102 2,4 D-Amine Balton (T) Wheat and barley against Ltd. broad leaved weeds. Basagran HE/0014 Bentazone BASF AG Rice, maize, beans against 480 g/l broad leaved weeds and sedges. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- Basagran PL2 HE/0016 Bentazone+ BASF AG Rice, beans, maize Propanil against broad leaved weeds, sedges and grasses. Basta 200g/l HE/0070 Glufosinate Bayer(E.A) Ltd Plantation crops Ammonium orchards, vineyards, against weeds in general. Buctril MC HE/0079 Bromoxynil Bayer(E.A) Ltd Barley, maize, oats, wheat and rice against broadleaf weeds. Derby HE/0110 Flurasulam + Dow AgroSciences Wheat and barley against 175 SC Flumetsulam broadleaf weeds Diurex HE/0106 Diuron Agan Chem Sugarcane against weeds 80SC Dual Gold HE/0097 S-metolachlor Syngenta Crop Maize,beans and sugarcane against 960EC Protection AG pre-emergence weeds. Fusilade Super HE/0076 Fluazifopbutyl Syngenta Ltd Various crops against 12.5% EC (UK) annual and perenial weeds. Gesapax combi HE/0030 Atrazine + Syngenta Crop Sugarcane, sisal, coffee, 500 FW Ametryne Protection AG bananas against weeds in general. Glean 75 DF HE/0082 Chlorsulfuron Bayer CropScience AG Wheat and barley against broad weeds. Glyphogan HE/0099 Glyphosate Agan Chem. Wheat against annual 480SL weeds. Helmamine HE/0003 2, 4-D Helm AG Cereals, sugarcane, sisal, 720 EC coffee against post- emergence weeds. Illoxan 36 EC HE/0038 Diclofop-methyl Bayer(E.A) Ltd Cereals against broad leaved and grass weeds. Kalachi HE/0112 Glyphosate Arysta LifeScience Control of annual and perennial 480 SL weeds. Lasso GD HE/0042 Alachlor + Monsanto Against grasses and broad- Atrazine leaved weeds in sugarcane, maize and sunflower Lasso GD HE/0153 Alachlor+ Monsanto preemergency weeds in maize,beans Microtech Atrazine and vegetables Lasso HE/0154 Alachlor Monsato (T) Ltd preemergency weeds in maize,beans Microtec and vegetables Mamba 360 HE/0095 Glyphosate Dow Agrosciences Wheat against annual SL and perennial grasses and broad leaved weeds. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- NABU 20% EC HE/0045 Sethoxydim Nippon Soda Various crops against weeds and grasses. Parapaz HE/0113 Paraquat Balton Tz. Ltd. Control of broadleaved weeds and grasses in maize. Primagram Gold HE/0116 Atrazine + Syngenta Crop Control of pre-emergence weeds 660 SC S-metolachlor Protection AG in maize,sorghum and sugarcane Puma Super HE/0109 Fenoxaprop- Bayer(E.A) Ltd Wheat against grass weeds 120EC p-ethyl Ralon Super HE/0088 Fenoxapro- Bayer (E.A)Ltd On wheat against weeds. 75EW P-ethyl Reglone HE/0052 Diquat Syngenta Ltd Various crops against 200g/l (UK) pre-planting and aquatic weeds. Rhone Poulenc HE/0043 2, 4-D Nufarm GmbH Various crops against 2, 4-D Amine broad leaved weeds. 72% Rondopaz HE/0100 Glyphosate Balton (T) Ltd. Wheat against annual weeds Ronstar 25 EC HE/0054 Oxadiazon Bayer (E.A)Ltd Rice, sunflower, against weeds in general. Roundup HE/0055 Glyphosate Monsanto Coffee, citrus, bananas 360 SC against all types of weeds particularly couch grass. Roundup Max HE/0115 Glyphosate Monsanto Control of weeds in maize Sanaphen 720SL HE/0114 2,4-D amine Dow AgroScience Control of broad leaved weeds in maize Sanduron 800SC HE/0120 Diuron Dow Agroscience weeds in sugarcane plantations Sapa Paraquat HE/0056 Paraquat Sapa Chem Plantation crops 20 EC against common broad leaved and annual weeds. Satunil HE/0077 Benthiocarb + Kumiai Chem Rice against 60EC Propanil gramineous cyeraceous weeds. Saturn HE/0078 Benthiocarb Kumiai Chem Rice against 50 EC gramineous cyperaceous weeds. Saturnvalor HE/0091 Thiobencarb/ Kumiai Chem Gramineous cyperaceous 55 EC Benthiocarb + and broad leaved weeds Prometryn in crop fields. Sencor HE/0108 Metribuzin Bayer (E.A)Ltd Sugarcane against weeds 480SC Sindax HE/0090 Bensulfuron + Du-Pont On irrigated rice against 10WP Metasulfuron broadleaf weeds and methyl grasses. Stam HE/0058 Propanil Dow Agroscience Wheat, rice, potatoes F-34 EC against post emergence ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- weeds. Stam HE/0059 Propanil + Dow Agroscience Rice against barnyard UT-8 EC Phenothol grass and cyperaceae (sedges). Stomp HE/0061 Pendimethalin BASF Sugarcane, cereals, 500 EC cotton, sisal, rice against grasses and broad leaved weeds. Topik HE/0104 Clodinafop- Syngenta Crop Wheat against annual broad leaved weeds. 080EC Propargyl Protection AG grass weeds Tordon 101 HE/0064 Pichloram Dow Agrosciences Bushes and trees against + 2,4-D broad leaved weeds Trifluralin HE/0065 Trifluralin Dow Agrosciences Various crops against annual 40EC Grasses and broad leaved Weeds Velpar HE/0107 Hexazinone Du Pont weeds in sugarcane 75DF Whipsuper HE/0093 Fenoxa-p-ethyl Bayer (E.A)Ltd For high volume spraying 120EW in beans against weeds. Wipeout HE/0094 Glyphosate Almandine For control of broad leaved 360 Corp. weeds and grasses in wheat. II D: ACARICIDES: Almatix 12.5EC AC/0016 Amitraz Almandine Against ticks and lice. Corp. Amitix AC/0020 Amitraz Alfan Intern. Control of cattle ticks. ectoparasites Cethion AC/0007 Ethion Cheminova Control of cattle ticks. 1010EC Ectoban AC/0021 Cymiazole + Novartis Control of cattle ticks. 200 EC Cypermethrin Norotraz AC/0022 Amitraz Norbrook Control of cattle ticks. 12.5% Laboratories Porect AC/0015 Phosmet Pfizer (Pty) Control of mange and Ltd. mites in pigs. Stelladone AC/0004 Chlorfenviphos Zagro Farm animal against 300 EC ectoparasites. Supona AC/0010 Chlorfenviphos Wyeth SA Cattle ticks and tse-tse. 100 EC (Pty) Ltd. Taktic AC/0013 Amitraz Hoechst Roussel Cattle ticks. Veterinar GmbH Taktic EC AC/0018 Amitraz Hoechst Roussel Cattle against mange, Veterinar GmbH mites, ticks and lice Triatix AC/0017 Amitraz Schering Plough Cattle against ticks, lice 12.5EC Animal Health and mange. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- II E: NEMATICIDES Basamid NE/0001 Dazomet Kanesho Tobacco, coffee, granular Soil Treatment vegetables, against soil pests i.e. nematodes, wireworms, and millipedes. Diafuran 5G NE/006 carbofuran Arysta LifeScience control of soil insects and nematodes Furadan 5G NE/003 Carbofuran FMC Bananas, coffee, tobacco, sugacane, rice, maize, non-leafy vegetables against soil insects, nematodes, foliar chewing, biting and sucking insects. soil insect pests. Mocap 10G NE/0005 Ethioprophos Bayer (E.A)Ltd Sugarcane, rice and maize against soil insects. II F: RODENTICIDES Racumin bait RO/0003 Coumatetralyl Bayer Crop Science AG Against rats and mice. Block Yasodion RO/0004 Diphacinone Ohtsuka Against rats and mice in Chem. Ind. Co. rice, sugarcane and maize. Ltd. II G: AVICIDES Cyanox L - 50 AV/0002 Cyanophos Sumitomo On quelea quelea birds. Queletox AV/0001 Fenthion Bayer CropScience AG Against grain eating 60% ULV birds in particular Quelea quelea. III: PESTICIDES REGISTERED UNDER RESTRICTED REGISTRATION IIIA: INSECTICIDES ------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Registrant Usage Restriction Name -------------------------------------------------------------------------------------------------------------------------------- Celphos 56% RE/0123 Aluminium phosphide Equatorial Africa control of grain storage insect pests Degesch Plate RE/0051 Magnesium Rentokil (T) Grain Storage use in godown Phosphide Ltd. storage. and silos. Detia Ex-B RE/0053 Aluminium Detia Grain storage. Storage use in godowns Phosphide Freyberg and silos. GmbH Ethylene RE/004 ethylene Sapa formulation formulation purpose Dibromide(tecn) dibromide purposes Ethylene RE/004 Ethylene Sapa Chem. Formulation formulation purpose only Dibromide dibromide (tech) Falfume RE/0118 aluminium Falcon International control of LGB and other storage Phosphide insect pests Fumaphos RE/0119 Aluminium phosphide National Fumigants(Pty) control of LGB and other storage Chamdor,S.Africa insect pests Kanamin RE/0055 d-allethrin African formulation formulation Mosfly Purposes only purposes only Locufen 96 ULV RE/0122 Fenitrothion AgriSpeciality,DSM against red locust control Phostoxin RE/0050 Aluminium Detia Grain storage Storage use in godowns Pellets Phosphide Freyberg an d silos. GmbH Phostoxin RE/0052 Aluminium Rentokil Grain storage Storage use in godowns Tablets Phosphide and silos. Pyrinex RE/0054 cchloropyrifos Balton on maize only against chewing and And sucking pests in maize Quickphos RE/0049 Aluminium United Grain storage Storage use in godowns Phosphide Phosphorus and silos. Ltd. Sapa Methyl RE/0024 Methyl Sapa Chem Tobacco, Soil use only. Bromide 98% Bromide nurseries against soil insect pests. Sapa ethylene RE/0023 ethylene Sapa against soil pests in soils only Dibromide 45% dibromide ------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Registrant Usage Restriction Name -------------------------------------------------------------------------------------------------------------------------------- Subaprid(tech) RE/0121 imidacloprid tech. Suba Agro for formulation activities only Twiga Gamma20 RE/0120 Lindane Twiga termites in construction industry only Vapona 500EC RE/0124 dichlorvos National Fumigants control of for treatment of structures used for (Pty),RSA grain storage III B: FUNGICIDES Impretect Oxide RE/0112 Copper Oxide + Duville On woods against insects and fungal 70TC Chromium Trioxide Woodworks decay Arsenic Pentoxide Celcure K33 RE/0030 Copper Oxide+ Rentokil Timber treatment against Chromium trioxide fungal decay Arsenic pentoxide Farmerzeb(techn) RE/0113 techn. Mancozeb Link Forward Co for formulation of Farmerzeb 80% only Osmose CCA C60 RE/0117 CCA Protim Solignum Osmose Wood Treatment Tanalith RE/0111 Copper oxide Arch Timber Timber and wood C3310 + Arsenic Protection ,UK treatment against Pentoxide+ fungal decay Chromium trioxide IIIC: HERBICIDES Volcano paraquat RE/0116 Metribuzin+ VolcanoAgrosciences weeds in sugarcane SL Paraquat plantations only III D: ACARICIDES Bayticol RE/0115 Flumethrin Bayer AG Cattle against tick To be used in ticks in 2% EC tsetse tsetse infested areas only. Bayticol RE/0012 Flumethrin Bayer AG Cattle against tick To be used in ticks in 6% EC tsetse tsetse infested areas only. Bayticol RE/0001 Flumethrin Bayer AG. Cattle against To be used in ticks Pour On ticks and and tsetse infested tsetse. areas only. Decatix 5% RE/0002 Deltamethrin Schering Cattle against To be used in ticks Plough Animal ticks and and tse-tse infested Health tse-tse. areas only Dominex 100EC RE/0006 Alphacyper- F.M.C Cattle ticks To be used in ticks anmethrin And and tsetse infested areas. Ecofleece 10EC RE/0011 Cypermethrin Bimeda Cattle ticks To be used in ticks and Chem tse-tse infested areas only. ----------------------------------------------------------------------------------------------------------------------------------------------- Trade Name Reg. No. Common Name Registrant Usage ----------------------------------------------------------------------------------------------------------------------------------------------- Ectomin 100EC RE/0008 Cypermethrin Novartis Cattle ticks To be used in ticks and SA (Pty) and tse-tse. tse-tse infested areas only. Ectopor 020AS RE/0004 Cypermethrin Novartis Cattle ticks To be used in ticks and SA (Pty) and tse-tse. tse-tse infested areas only. Grenade 5%EC RE/0010 Cyhalothrin Schering Cattle ticks To be used in ticks and Plough and tse-tse tse-tse infested areas only. Animal Health Paranex RE/0013 Alphacyper- FARMBASE Cattle ticks To be used in ticks and methrin and Tsetse tsetse infested areas only Pouracide RE/0009 Alphacyper- Smithkline Cattle ticks To be used in ticks and methrin + (Pty) Ltd. and tse-tse. tse-tse infested areas only. tetrachlovinphos Renegade RE/0007 Alphacyper- Wyeth SA Cattle ticks To be used in ticks and methrin (Pty) Ltd and tse-tse. tse-tse infested areas only. Spoton 1% RE/0005 Deltamethrin Schering Cattle ticks To be used in ticks and Plough and tse-tse. tse-tse infested areas only. Animal Health III F: NEMATICIDES Furadan 10 G RE/0028 Carbofuran F.M.C. Banana, Coffee Soil used only. and tobbaco. IV PESTICIDES REGISTERED FOR EXPERIMENTAL PURPOSES ONLY IV A: INSECTICIDES ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Abate 200 EC EXP/951 Temephos Tukuyu Vector against blackfly larvae Bioallethrin Adeal 1EC EXP/285 Pyriproxyfen Sumitomo On mosquitoes. Adeal 10EC EXP/286 Pyriproxyfen Sumitomo On mosquitoes. Adeal 0.5 G EXP/454 Pyriproxyfen Sumitomo On mosquitoes. Agro-Chloride EXP/626 Chloripyrifos Transagro Against insect pests. 500EC + Dimethoate Agita 10WG EXP/934 Thiamexothan Norvatis S.A control of houseflies Agita GBI EXP/935 Thiamex0than Norvatis S.A control of houseflies Agro-Cytrin EXP/624 Cypermethrin + Transagro Against insect pests in various crops. Plus 280EC Dimethoate Agro-Cytrin EXP/625 Cypermethrin Transagro Against insect pests in various crops. 112ULV Dimethoate Agro-Cytrin EXP/482 Cypermethrin Transagro Against insect pests in various crops. 10 EC Agro-Cytrin EXP/609 Cypermetherin Transagro Various crops against insect pests. 2.5ULV Agro-Cytrin EXP/606 Cypermethrin Transagro Against insect pests. 1.8ULV Agro-Detrin EXP/644 Deltamethrin Transagro Various crops against insect pests. 2.5 EC Agro-Detrin EXP/645 Cypermethrin Transagro various insect pests 0.5ULV . Agro-Thoate EXP/483 Dimethoate Transagro Sugarcane, sunflower, cotton and jute 40 EC against aphids, whiteflies, mites and thrips ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Agro-Trothion EXP/484 Fenitrothion Transagro On cotton, sugarcane, coffee and 50 EC tobacco against chewing and sucking pests. Agrozinon EXP/1101 Diazinon Aquatoria Africa Ltd various pests Agro-Valerate EXP/611 Fenvalerate Transagro Against insect pests. 20 EC Agro-Valerate EXP/610 Fenvalerate Transagro Against insect pests. 3.0 ULV Alarin-T EXP/956 Dicofol+Tetradifon Agan Chemicals Against mites on vegetables, cotton, Fruits and flowers Albaz 10EC EXP/1034 alphacypermethrin CMI Ltd;UK vs flying and crawling insects Alphadime 415DS EXP/1013 alpha-cypermethrin Onion E.Africa insect pests in cotton,cereals,horticultur + dimethoate Alphaguard EXP/678 Alphacyper- Fertilizer and On various crops against 48 EC methrin Chemicals insect pests. Asataf 75SP EXP/1022 Acephate OSHO Chem. Industies chewing and sucking insects in cotton, Rice,sunflower Aster Extrim 20SL EXP/1148 Acetamiprid+ Equatorial Africa Ltd insecticide on various crops Cypermethrin Avaunt 150SC EXP/665 Indoxacarb Du-Pont On cotton, brassicae, tomatoes, beans and vegetables against catepillars. Azocord EXP/695 Cypermethrin/ BASF. For control of mites and insects Monocrotophos in flowers and seedbeans. Bactivec EXP/958 Bt Jose A. Fraga mosquito control Baluphos EXP/1174 Al-phosphide Bajuta General Vetagro pests in stored grains Bamethrin 2.5 ULV EXP/1145 Deltamethrin Bajuta General Vetagro on cotton,coffee,maize,cereals Baroque 10SC EXP/1172 Etoxazole Chemtura (PTY) ltd spidermites on ornamentals Bathion 50EC EXP/1140 Fenthion Bajuta General Vetagro …. Baygon mosquito EXP/798 Pyrethrins Johnson Wax (EA) Against mosquitoes Coil ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Belt 480SC EXP/1151 Flubendiamide Bayer (e.A) insect pests in Brassica,and tobacco Black Cat EXP/830 Pyrethrin MSK Ind. Against mosquitoes Mosquito Coil Blue cross EXP/748 Malathion Nova Chem. Ltd On stored grains against insect pests. Bulldog EXP/594 Betacyfluthrin Bayer CropScience AG On maize against stalk borers. 0.05 GR Calrate EXP/879 Lambda Amiran (K) On tomato against ABW 50 EC Cyhalothrin Bug Oil EXP/1191 natural oil DVA; MBH,Germany on various insect pests Cascade 10 DC EXP/685 Flufenoxuron BASF Against mites in ornamentals. Casper Anti EXP/836 Allethrin ISM Agro Against mosquitoes Celcron 50% EC EXP/1167 Profenofos Equatorial Africa various insect pests in cotton Cereguard Super EXP/1044 Pyrethrins Farmbase various pests in agriculture,forestry Commando 80% EXP/1083 zinc phosphie Equatorial Africa against rodents Conquest C176 EC EXP/978 Acetamiprid+ Arysta Life Sciences bollworms and sucking pests in cotton Cypermethrin Crop Dust EXP/743 Bifenthrin Juanco SPS Against cutworm and stalk borer. Ltd. Cyhalothrin EXP/900 Cyhalothrin Syngenta Crop Control of migratory pests 7 ULV Protection AG Danitol 10 EC EXP/13 Fenpropathrin Sumitomo Fruit trees, vegetables and cotton against mite, aphids and whiteflies. Dasba 48EC EXP/1143 Chlorpyrifos Bajuta General Vetagro …………………… Deet EXP/1080 N,N-diethyl-m-toluamide Chemi and Cotex mosquito repellant Arusha Deltaphos 212EC EXP/1039 Deltametrhin+ Bayer(EA) Ltd on cotton against mites,thrips etc. Triazophos Doom Vermin EXP/306 Sevin Bayer CropScience AG Against cockroaches flies, lice, Powder bedbugs and other crawling ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Dragnet FT EXP/1204 Permethrin Juanco SPS termite control Duducyper 5EC EXP/1122 Cypermethrin Bukoola Chemical Ind chewing and sucking insect pests Duduthrin 5EC EXP/1016 lambda cyhalothrin Twiga Chemicals(T) …(insecticide)… insects. Duduethoate EXP/1123 dimethoate Bukoola Chemical Ind. Chewing and sucking insect pests Eksmin EXP/459 Permethrin Sumitomo For mosquito control. 10 EC Elsan EXP/165 Phenthoate Nissan Chem. Various crops against chewing and 50 EC sucking insects. Endocel 35EC EXP/1081 Endosulfan Equatorial Africa against chewing pests Endocid-40 EXP/1073 Endosulfan Handelsgesellschaft wide range of sucking and chewing Detlef von Appen mbH insects Endotaf 35EC EXP/1031 Endosulfan OSHO Chem. Industies stalkborers and chewing insects Ex-Pel super EXP/112 Bendiocarb + Mansoor Daya Household against cockroaches, cockroach Permethrin Chemicals Ltd. bedbugs and other insects. killer Falam 5% EC EXP/1163 Labda- Export Trading Co. ltd against various insects in ctton, cyhalothrin vegetables, etc Falpro 72 EXP/1165 profenophos Export Trading Co Ltd insects and mites in cotton,vegetable etc Farmprid EXP/1193 Imidacloprid Linkforward Co. Ltd against various insect pests Farmrifos EXP/1194 Chorpyrifos Linkforward Co. Lts various insect pests Fendona EXP/794 Alphacypermethrin BASF Bednet treatment and residual 150WP spray for mosquito control Fenkil 3%ULV EXP/167 Fenvalerate United Cotton, maize, sorghum against Phosphorus Ltd. Insect pests. Folimat EXP/766 Omethoate BASF On coffee against thrips, mealybugs, 500SL aphids; Ornamentals against scales, aphids, mites & catapillars Gaucho EXP/317 Imidacloprid Bayer CropScience AG Soil insects and aphids. 70 WS GC-340 EC EXP/1130 Garlic extracts Juanco SPS Ltd various insect pests Glossinex 200SC EXP/1146 Deltamethrin Ecomark Ltd use on tsetsefly Golden Pro 40EC EXP/1203 Profenophos+ Invectra Agro Ltd various chewing and sucking insect Cypermethrin Cyprus pests ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Goliath EXP/709 Fipronil BASF Agro BV Insecticidal gel for the control of Bait stations cockroaches. Goliath Gel EXP/802 Fipronil BASF Agro BV Against cockroaches Griselesf EXP/959 Bs Jose A. Fraga Against mosquitoes Hasafat 75% EXP/963 Acephate Agri Speciality Ltd against chewing and sucking insects in Tobacco,vegetables,fruits,flowers Hotshot 70WDG EXP/955 Imidacloprid Sulphur Mills Sucking insects on various crops Icon Life EXP/1185 Deltamethrin Syngenta Bednet treatment Icon Maxx 10CS EXP/1134 lambda cyhalothrin Syngenta Crop Protection bednets impregnation Jumbo mosquito EXP/831 Pyrethrin MSK Ind. Against Mosquitoes Coil Karate 3.75WG EXP/672 Lambda- Syngenta Ltd Vegetables against various insects. Cyhalothrin (UK) Kombat Stalk- EXP/649 Carbaryl Kombat (PTY) Maize against stalkborer. borer Granules Ltd. Komesha EXP/770 Asbiothrin + Truck Parts Ltd Against household insects Deltamethrin Luxan EXP/4 Diazinon B.V. Luxan Various crops against sucking Diazinon 60EC The Netherlands pests. Marshall EXP/468 Carbosulfan F M C For foliar and soil pests on maize, 350 STD cotton, wheat, barley and millet. Marshall EN EXP/636 Carbosulfan + F M C On coffee against leafminer, antestia, Endosulfan scales, berrymoth and borers. Maxforce Ic EXP/853 Imidacloprid Bayer (EA) Ltd Cockroach control Marvik 2F EXP/757 Tau-fluvalinate Syngenta Crop Vegetables, ornamentals and cereals Protection AG against insect pests. Mbukil EXP/790 Pyrethrin Sapa Chemicals Against mosquitoes and flies Melgel Cocroach EXP/1001 Fipronil Gutta and Mwilima cockroach control Gel Associates Metasystox EXP/789 Oxydemeton- Bayer CropScience AG Against aphids, leaf hoppers, whitefly 250EC methyl and other sucking pests Methomex EXP/886 Methomyl Makhteshim Chem Control of insect pests on vegetables, 90 SP coffee and ornamentals Mmbu Dawa net EXP/1179 Deltamethrin Sunflag(T)Ltd for mosquito net impregnation Mortein Doom EXP/1180 Metofluthrin Reckitt Benkiser Mosquito repellent Act. Air Repellent E.Africa Ltd Mortein Doom All EXP/1190 Imiprothrin+ Reckitt Benkiser against flying and crawling insects Insect killer with Esbiothrin+ E.Africa Ltd Dettol Gwerstop d-phenothrin ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Mortein Doom Fast EXP/1189 Imiprothrin+ Reckitt Benkiser cockroaches and other Knockdown CIK Cypermethrin E.Africa Ltd harmful insects Mortein doom EXP/1181 Esbiothrin Reckitt Benkiser cockroaches and other Mosq. Relellent E.Africa Ltd harmful insects Liquid Mortein Doom EXP/1182 Imiprothrin+ Reckitt Benkiser cockroaches and other Ultrafast AIK Esbiothrin+Permethrin Mortein Doom EXP/1183 Imiprothrin+ Reckitt Benkiser cockroaches and other Ultrafast AIK Esbiothrin+Permethrin E.Africa Ltd harmful insects Odourless Mosband EXP/822 N-N-diethyl- Redrose Man. Ltd Against mosquitoes Insect Repellent tolnamide Mosfly aerosol EXP/1201 d-tetramethrin+ African Mosfly household insecticide Permethrin+ Industries Ltd; Deltamethrin Moshi Moskill Aerosol EXP/810 Pyrethrum Coil Products (K) Against flying and crawling domestic pests Mospilan 20%SP EXP/638 Acetamiprid Nippon Soda On wheat, barley, beans, tobbaco, Co. Ltd. potatoes, vegetables, flowers and fruits against aphids, leaf hopper and fruits moth. Mospilan 3%EC EXP/639 Acetamiprid Nippon Soda Cereals, beans, tobbaco, potatoes, Co. Ltd. vegetables flowers and fruits against aphids, leaf hopper and fruit moths Motox Mosquito EXP/809 d-Allethrin HVM Products Ltd Mosquito control Coil Nagata EXP/1057 Ethion 40% + Osho Chem. Ind. American bollworm in cotton Cypermethrin 5% EC Mupa-alphacyper EXP/1147 alphercypermethrin Equatorial Africa Ltd control of various insect pests in 10EC cotton,vegetables,maize etc. Mupan 500EC EXP/1199 Dichlorvas Equatorial Africa Ltd mosquito control in public site Netto 1%SC EXP/1079 lambda cyhalothrin Fluence Middle East mosquito net impregnation Nissorun VEC EXP/463 Hexythiazox Nippon Soda Against spidemites, aphids on cotton, + Dichlorvos soyabeans fruits and vegetables. Ninja 5EC EXP/1156 Lambda cyhalothrin Equatorial Africa various insect pests No-bite EXP/832 Diethyl Mansoor Daya Against mosquitoes and flies Insect Repellent toluamide ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ NOK Aerosol EXP/698 Tetramethrin NOK Products For mosquitoes and other flying + Fenitrothion Limited and crawling insect Nova-Super EXP/1186 Malathion+ Nova Industries Ltd weevils and LGB in stored products Super Blue Cross Pyrethrins Nairobi Nova stalk borer EXP/1187 pyrethrins Nova Industries Ltd against maize stalkborers Dust Nairobi Nurelle D50/500EC EXP/1003 Cypermethrin+ Dow Agroscience insect pests in vegetables,beans,cotton Chloropyrifos and wheat Orthene 97 Pellets EXP/797 Acephate Arvesta Corp. Cotton against bollworm, aphids lygus, thrips and stainers Pali 2.5%WP EXP/985 Deltamethrin Twiga Chemicals against mosquitoes Pali 25 WT EXP/986 Deltamethrin Twiga Chemicals mosquito control Peripel 55 EXP/619 Permethrin Bayer CropScience AG As a contact repellent against biting insects and ticks. Pesguard EXP/333 d-Allethrin + Sumitomo On mosquitoes. Ps 201 Permethrin Phosphite 53SL EXP/1131 mono + dipotassium Juanco SPS ……………………….. phosphite Polytrin EXP/705 Profenofos + Syngenta Crop Foliar insectide with acaricidal 440EC Cypermethrin Protection AG properties for use in vegetable crops. Prevent EXP/1011 Pyrethrins+ Tanzania houseflies and mosquitoes Piperonyl butoxide Processing Prove 1.92 EC EXP/1159 Emamectin Benzoate Equatorial Africa Ltd inscet pests in cotton,egetables,brassica Pyegar 35EC EXP/1129 Natural pyrethrum+ Juanco SPS Ltd various insect pests Garlic extract Permethrin Raid Ant and EXP/827 Imiprothrin + Johnson Wax Against crawling insects Cockroach Killer Cypermethrin Raid Coil Perfumed EXP/824 Pyrethrum Johnson Wax Against mosquitoes Raid Coil Regular EXP/825 Pyrethrum Johnson Wax Against mosquitoes Raid Liquid Electric EXP/1127 Prallethrin Johnson Wax mosquito repellent Raid multipurpose EXP/1111 Imiprothrin+ Johnson Wax (EA) domestic and public health insects Insect killer Cyfluthrin Odourless Tetramethrin Regent 3GR EXP/640 Fipronil BASF Agro BV On rice against borers, gall midge and rice insects pest. Regent 50SC EXP/664 Fipronil BASF Agro BV Against bean flies, thrips and cabbage loopers ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Residex P25 EXP/961 Permethrin Tanzania Pyrethrum impregnation of mosquito nets MNR EC Ridsect Liquid EXP/796 Cyphenothrin + SaraLee Household & Control of mosquitoes and cockroaches Prallethrin Body Care (K) Ltd Ridsect Mosquito EXP/799 d-Allethrin SaraLee Household & Control of mosquitoes Coils Body Care (K) Ltd Ridsect EXP/808 Deltamethrin SaraLee Household and control of cockroaches,ants and Chalk Bodycare(K)Ltd bedbugs Risasi Mosquito Coil EXP/1138 D-allethrin Meghji Sundries mosquito control 0.2%w/w (d-allethrin) Riyazinon 60EC EXP/1121 Diazinon Riyue Chemical Ltd aphids,armyworm,mites,mealybugs etc DSM Royalnex 25CS EXP/1104 Chlorpyrifos Chemtura Corporation seed treatment for the control of soil Borne insectc pests,and early insect Pests in maize and other crops Sapa EXP/201 Cypermethrin Sapa Chem. On cotton , coffee, beans, maize, Cypermethrin tobacco against aphids, flies and ticks. 10 EC Secure EXP/686 Chlorfenapyr BASF On carnations against spidermites 36 SC and caterpillars. Septer 200SC EXP/1052 Imidacloprid Mukpar (T) Ltd insects in various crops;termites Sevin EXP/539 Carbaryl Bayer (EA) Ltd On maize against stalk 5 G borers. Success bait EXP/1116 Spinosard Dow Agrosciences control of fruit flies in various crops Sumicidin/ EXP/529 Fenvelerate/ Sumitomo On cotton and cereals Oncol ULV Benfuracarb against bolloworms, aphids, locust, armyworms etc. Sumicombi EXP/343 Fenvalerate Sumitomo Against chewing and sucking 30 EC insects on various crops. Sumithion EXP/202 Fenitrothion Sumitomo On maize against stalk 3% D borers. Sumithion EXP/203 Fenitrothion Sumitomo Public health against 80 EC mosquito Sumithion EXP/205 Fenitrothion Sumitomo Cereals, vegetables L 100 pasture against locust and armyworms Sumithion EXP/793 Fenitrothion Sumitomo Against locusts and armyworms 96ULV Sumithion EXP/206 Fenitrothion Sumitomo Red and desert locust 98% ULV control. Super Doom EXP/800 Cypermethrin + Reckitt Benckiser Against cockroaches Fast Knockdown Imiprothrin Cockroach Killer Supercelio EXP/919 d-allethrins MSK Industries Mosquito control Mosq. coil ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Super Pyblast EXP/987 Pyrethrin+ …………………. Houseflies and mosquitoes Piperonyl butoxide Supona aerosol EXP/1093 Chlorfenvinphos+ Fortdodge Animal ticks and maggots aerosol on wounds Dichlorvos+ Health ,South Africa Gentian violet Tabafan 48EC EXP/1059 Chlorpyrifos Osho Chem. Ind. Various insects in various crops,house household pests,ornamentals Tafethion 50EC EXP/1030 EthionOSHO Chem. Industies mites and sucking insects in various crops Talstar 12g/l EXP/584 Bifenthrin F M C Control of leafminers, mites scales and aphids on cotton beans and vegetable. Tatacyper 10EC EXP/1028 Cypermethrin OSHO Chem. Industies against various insect pests Tempo EXP/689 Beta-cyfluthrin Bayer Environm. Scien. For tse-tse fly target in impregnation 12.5SC and household pest control. Terraguard EXP/679 Chlorpyrifos Nova Ind. Ltd. On crops against chewing and 10 EC sucking insect pests and public health against mosquitoes. Termidor 25EC EXP/710 Fipronil BASF Agro BV Against termites. Thioba 95% tech EXP/1139 Fenitrothion Bajuta General Vetagro ……………………. Thunder OD145 EXP/1038 Imidacloprid+ Bayer (EA) Ltd on cotton against aphids,thrips etc Betacyfluthrin Titan 25EC EXP/979 Acetamiprid Arysta Lif Sciences tomatoes Vs liriomysa trifolii TOBECO-75WSP EXP/1198 Acephate Equatorial Africa Ltd control of various chewing and binting Insect pests Torque 550SC EXP/688 Fenbutatin BASF On beans and ornamentals against Oxide mites. Tracker EXP/814 Tralomethrin DuPont Against desert and red locusts larvae 16.5 ULV Tracer 480SL EXP/1035 Spinosyn A and B Dow Agroscience thrips and leafminers in horticulture Trigger Supper 10CS EXP/1158 lambda - Equatorial Africa Ltd various insect pests in crops and public Cyhalothrin health Twiga EXP/731 Carbaryl Twiga Chem Against fleas in poultry and chewing Carbaryl 5% D and sucking insect pests in horticultural crops Twiga primethyl EXP/1153 pirimiphos- Twiga Cheminal Ind. Certain pests in vegetables,storage structures 50EC methyl and public health Twiga Thiodan EXP/921 Endosulfan Twiga insect pests in tobacco and maize Ustaad EXP/220 Cypermethrin United On coffee against sucking and chewing 2.5ULV Phosphorus insects. ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Vantex EXP/871 gamma cyhalothrin Dow Agro Cotton, vegetables, beans and coffee against a wide range of pests. Vectobac WDG EXP/1004 B.thuringiensis City Medical Office mosquito larvae control (or Vectolex) ( or Bacillus sphaericus) DSM Vitashield 24ULV EXP/1102 Chlorpyrifos Equatorial Africa Ltd various pests Vitashield 48EC EXP/1100 Chlorpyrifos Equatoria Africa various pests X-pel EXP/833 Diethyl toluamide + Mansoor Daya Against mosquitoes Mosquito Dimethyl phthalate Repellent Zero-Bite Mosquito EXP/828 Essential Oils Shely Pharm. Against mosquitoes Repellent Zetabestox 10EW EXP/975 zetacypermethrin FMC against various pests in cotton IV B: FUNGICIDES Acrobat Mz EXP/724 Dimethomorph BASF On flowers, potatoes, tomatoes +Mancozeb and tobacco against downy/powdery mildew and blights Agro-Captan EXP/605 Captan Transagro On seeds and soil borne 50WP diseases. Agro-Copoxy EXP/631 Copper Transagro Control of CBD, leaf rust and other 50%WP Oxychloride fungal diseases. Agro-Zeb 80WP EXP/503 Mancozeb Transagro Control most fungal diseases on various crops. Aliette EXP/562 Fosetyl-Al Bayer (E.A)Ltd On avocado, pineapple, rubber and onion against fungal diseases. Amistar 250SC EXP/1087 Azoxystrobin Syngenta against plant fungal diseases Antiblue Select EXP/769 Benzalkonium Choride Arch Timber(UK) Against fungi and moulds on freshly + Iodo-propylbutyl felled and sown timber Carbamate + Disodium Octaborate Artea 330EC EXP/983 Cyproconazole+ Syngenta Crop Prot. Fungal diseases in cereals P{ropiconazole Bavistin DF EXP/765 Carbendazim BASF Against fungal diseases on agricultural, horticultural crops, vegetables and ornamentals. Bayleton EXP/567 Triadimefon Bayer (E.A)Ltd Control of coffee Leaf Rust 250EC (Hemileia vastatrix). ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Caramba EXP/729 Metconazole BASF Against rust septoria in cereals. 60 SL Contaf 5SC EXP/1026 Hexaconazole OSHO Chem. Industies powderly mildiew in various crops Delan EXP/712 Dithianon BASF Coffee against CBD and leaf rust 500SC Domark 40 EXP/805 Tetraconazole Isagro S.p.a control of powderly mildiew on roses Euparen M EXP/572 Tolyfluanid Bayer (E.A)Ltd Botrytis plasmopara on grapes 50WP ornamentals, Alternaria on vegetables. Falcom S-Dust EXP/1160 sulpur Export Trading Co Ltd powderly mildew in cashew Falcom 5% WP EXP/1162 Triadimenol Export Trading Co Ltd powderly mildew in various crops Falmenol 250EC EXP/1164 Triadimenol Export Trading Co Ltd broad spectrum systemic and foliar Fungicide Fer- EXP/656 Copper Fertilizer On coffee against CBD. Oxychloride Oxychloride & Chem. 50WP Flint 50WG EXP/995 Trifloxystrobin Bayer(EA) Ltd control of fungal diseases in roses Folpan 50SC EXP/953 Folpet Makhteshim on vegetables against early blight Mildew and anhracnose Ground EXP/620 Sulphur Solvary For mildew in Wineyards. Sulphur Catalyst Homai EXP/541 Thiophanate- Nippon Soda Wide spectrum seed disinfectant. 80% WP Methyl + Thiram . Korosho EXP/739 Sulphur TRADEP Ltd. Against cashew powdery Brand mildew Sulphur Labilite EXP/059 Thiophanate- Nippon Soda Wheat, vegetables, fruits methyl + Maneb against mildews, blights, leafspots and anthracuose Linkfonium EXP/1192 Fosetyl+Aluminium Linkforward against damping off and rot of plant Roots,stems and fruit Linkfozeb EXP/1195 Fosetyl-Aluminium Linkforward against a wide spectrum of fungal Mancozeb Co. Ltd diseases Liquicop EXP/792 Copper Ammonium Hydrotech On coffee against CBD Carbonate Int (PTY) Lotus 80Wp EXP/976 Mancozeb Shanghai Suceed Agro- vs downey mildiew in fruits and Chemical Co. horticultural crops Luxan EXP/641 Carbendazim B.V. Luxan, On cereal crops, fruit vines hops, Carbendazim The Netherlands vegetable, ornamentals, coffee, cotton, sugar cane, tobacco and other crops against fungal diseases Melody Duo WP 66.8 EXP/1091 Propineb+Provalicarb Bayer east Africa early and late blight in vegetables Meltatox EXP/763 Dodemorpha- BASF Powdery mildew on ornamentals. 400EC cetate ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Merpan EXP/910 Captan Makhteshim Control of late blight 50 WP Monceren GT EXP/1069 Imidacloprid+ Bayer (E.A) Ltd seed dressing against early sucking FS 390 Pencycuron+ insects and seedling diseases in Thiram cotton,beans,sunflower etc. Mosan SL EXP/741 Thiram + Pesticides On maize, groundnuts and bean seeds Lindane Manufacturers against dumping off, insect pests and Ltd. seedling blights. . Mupafidan EXP/1125 Triadimenol Equatorial Africa Ltd fungal diseases in various crops Mupavil 50EC EXP/1144 Hexaconazole Equatorial Africa fungal diseases in various crops Murtano EXP/746 Thiram + Crompton Seed dressing for maize, beans and 47WP Lindane (Uniroyal Chem) sorghum. Nordox Super EXP/747 Cuprous Oxide Nordox Coffee against CBD and leaf rust W75 Industrier As Opus EXP/845 Epoxiconazole BASF Against rusts and septoria in wheat and blotches on barley Polar EXP/931 Polyaxin Tivonchem control of powderly mildew on flowers Polyram DF EXP/240 Metiram Complex BASF AG. On beans, vegetables and fruits against fungi. Previcur Energy EXP/1070 Propamocarb+ Bayer (E.A) Ltd against downy mildiew in ornamentals SL840 Fosetyl Rav 500SC EXP/1154 Chlorothalonil Equatorial Africa Ltd various fungal diseases on a variety Of crops Raxil 025FS EXP/803 Tebuconazole Bayer (E.A)Ltd seed treatment in barley Raxil S 040FS EXP/804 Tebuconazole+ Bayer Bayer (E.A)Ltd seed treatment Triazoxide Real 200 FS EXP/563 Triticonazole Bayer (E.A)Ltd Seed treatment. Rovral Flo EXP/501 Iprodione Bayer (E.A)Ltd Beans, flowers, sunflowers, vegetables against fungal diseases. Saprol 20EC EXP/687 Triforine BASF On fruits, flowers, ornamentals and other crops against powdery mildew,rust and leaf spot Seedmax 30WS EXP/1105 Imidacloprid+ Chemtura Corporation seedtreatment for control of soil borne Metalaxyl+ Nairobi diseases and sucking insect pests Carbendazim Stroby DF EXP/764 Kresoxim- BASF On agricultural/horticultural crops, Methyl vegetables & ornamentals against fungal diseases. Sulfex 80% WP EXP/1168 Sulphur Equatorial Africa Ltd powderly mildew in grapes,cowpea,and Scab in apples Sulfex Gold EXP/1166 Sulphur Equatorial Africa Ltd powderly mildew in grapes,mango,apples 80% WDG and scab in apples ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Sulphur F-80 EXP/1161 sulphur Export Trading Co. Ltd Grapes, vegetables against brown rot, Scab and mildew Sumi - 8 EXP/122 Diniconazole Sumitomo Coffee and wheat against leaf rust and powdery mildews on cashewnuts. Tanalith CP EXP/502 Copper Arch Timber Wood destroying fungi insect Sulphate + Products and termites. Arsenic pentoxide Tata Master EXP/1025 Metalaxyl+ OSHO Chem. Industies against various fungal diseases Mancozeb Teldor WG50 EXP/1092 fenhexamid Bayer East Africa Botrytis in flowers and other horti crops Topas 100EC EXP/386 Penconazole Syngenta Vegetables, cashewnuts, grapevines and ornamentals. Verita EXP/997 Fenamidon+ Bayer(EA) Ltd against powderly mildiew in Fosetyl-Al flowers & ornamentals Wetsulf 80WP EXP/936 Sulfur National Estate against powderly mildew on Vegetables and cereals Xantho 5EC EXP/1109 Hexaconazole Atul Ltd;India powdery mildew, and leaf rust IV C: HERBICIDES Acenit 50EC EXP/535 Acetochlor Chemol Co Ltd On various weeds in coffee, sugarcane, maize and potatoes. Agro-2,4D EXP/643 2,4D Transagro On wheat, barley, rice, grassland Amine 720 SL pasture, maize and sugarcane against broad leaved weeds. Agro-Sate EXP/607 Glyphosate Transagro Weed control. 180g/l Agro-Sate EXP/517 Glyphosate Transagro Weed control. 360g/l Argold 10%EC EXP/668 Cinmethylin BASF Weed control in transplanted rice. Axial 45EC EXP/1137 Pinoxaden Syngenta Crop Prot. Grass weeds in wheat and barley Basagran KV-P EXP/509 Bentazon + BASF AG. Wheat and barley against broad Mecoprop-P leaved weeds. Boxer 800EC EXP/1136 Prosulfocarb Syngenta Crop Prot. Grasses and broad leaf weeds Cadre 24% SL EXP/669 Imidazolinone BASF AG On sugarcane against Pre- and Post emergence weeds. Calpen EXP/880 Pendimethalin Amiran (K) On sugarcane for control of grassweeds 500 EC and broadleaved weeds. ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Codal Gold EXP/1135 S-metalochlor+ Syngenta Crop Protection grasses and leaf weeds in cotton 412.5DC Prometryn Cossack EXP/941 Iodosulfuron methyl Bayer (E.A)Ltd control of grass and broad leaved Sodium+mesulfuron weeds in cereals methyl Clodex 100EC EXP/1202 Clodinafop Propargyl Invectra Agro Ltd control of wild oats Cyprus Ditex 50SC EXP/1049 Diuron Fluence Middle E.A pre-and post emergency herbicide Ltd;Cyprus in various crops Equation Pro EXP/1009 Famoxadone+ DuPont Nemours downy mildiew, early blight ,and late Gymoxanil blight in tomatoes,potataoes,&lettuce Fer-Amine EXP/648 2,4-D Fertilizer & On wheat, rice, maize and sorghum 720SL Chem. against pre- and post-emergence Focus ultra EXP/409 Cycloxydim BASF AG. On broad leaved crops to control annual and perennial grass weeds Gallant EXP/1002 Haloxyfop-R- Dow Agroscience broad leaved weeds and grasses Super methyl in rice Garil EXP/1065 Trichorpyr Dow agrosciences weeds in cotton,onions,rice,sugarcane Glifonex EXP/512 Glyphosate Monsanto Control of all weeds in coffee. 360 EC Glycel 41SL EXP/1063 Glyphosate Equatoria Africa annual and perrenial grasses and broad Leafe weeds Glyphon 360SL EXP/1196 Glyphosate Equatoria Africa control various weeds in beans,cereals etc. Gugusale 48SL EXP/1157 Glyphosate twiga Chemical Ind. Annual and perennial weeds Hyvar-X EXP/416 Bromacil Du Pont Weed control on sisal, pineapples , citrus, non crop areas and rail roads Hussar OD100 EXP/1152 Iodosulfuron- Bayer East Africa grasses and broad leaved weeds in Me-sodium cereals Hussar of EXP/1188 Fenoxaprop-p-ethyl Bayer East Africa grasses and broad leaved weeds in Evolution +Iodosulfuron-Me Na cereals Jumbo480EC EXP/964 Clomazone Agri Speciality Ltd weeds in sugarcane,tobacco,vegetables And rice Lasset GD EXP/1095 Acetochlor+Atrazine Monsanto,Nairobi various weeds +Terbuthylazine Lava 500 SC EXP/1075 Tebuthiuron Volcano Agrosciences weed control Mamba 480 SL EXP/1149 Glyphosate Dow Agroscience control of grass and broad leaved weeds Highload in coffee,wheat,tea, forestry MCPA 400SL EXP/1094 MCPA VolcanoAgrosciences broadleaved weeds and grasses in Various crops Metrix480EC EXP/1051 Metribuzin Fluence Middle E.A in maize,cereals,potatoes,tomatoes Ltd;Cyprus Merlin WG75 EXP/1090 Isofluote Bayer East Africa pre-early post emergency herbicide in sugarcane ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ MON 8439 EXP/954 Harness Monsanto control of grasses and broad leaved Weeds in maize,cotton,sugarcane Mupa 2,4-D amine EXP/1197 2,4-D amine Equatorial Africa Ltd post emergency weeds control in various pests Muparaxone 276 g/L EXP/1128 Paraquat dichloride Aquatorial Africa Ltd various weeds Nicanor 50WP EXP/801 Metsulfuron-methyl Quena Plant Cereals, pastures, rice and non-crop Areas against weeds Pantera 40EC EXP/1077 Quizalofop-p-tefuryl Chemtura Chemicals annual and perrenial grasses in beans And broad leaved crops Pursuit EXP/425 Imazethapyr BASF On beans and soya beans 200g/l against broad leaf weeds. Quartz Super EXP/513 Diflufenican Bayer (E.A)Ltd On barley and wheat against + Isoproturon broad leaf and grass weeds. Rainbow 25 EXP/1015 Penoxsulam Dow Agroscience broad leaved weeds and grasses In rice fields Rax Super 7.5EW EXP/1050 Fenoxapropyl-p-ethyl Fluence Middle E.A. wild oats and annual weeds in Ltd;Cyprus wheat and other crops Rondo 48SL EXP/1021 Glyphosate Handelgesellschaft Detlef annual and perrenial weeds including Von Appen mbH sedges ,grasses and woody plants Ronstar PL EXP/421 Oxadiazon + Bayer (E.A)Ltd Early post emergent propanil herbicide against grasses; weeds Ronstar2D EXP/427 Oxadiazon Bayer (E.A)Ltd Rice against grasses and broad leaved weeds. Ronstar EXP/564 Oxadiazon Bayer (E.A)Ltd On broadleaved weeds and 380 FLO grasses in rice, sunflower, vegetables, turf and various crops. Roundup EXP/937 glyphosate Monsanto weed control in various crops 450 Turbo Silcut 500SC EXP/1076 Bromacil Volcano Agrosciences weeds control Stigaway EXP/1184 Imazapyr BASF Agro BV against witchweed (striga spp.) in masize Tata Moto 70 WG EXP/1058 Metribuzin Osho Chem. Industr. Various grass and broad leaved weeds Tata Panida EXP/1056 Pendimethalin Osho Chemical annual grasses and some broad leafed Grande 43.5 EC Industries Ltd weeds Tebusan EXP/850 Tebuthiuron Dow AgroScience Control of herbaceous and woody Plants, annual weeds, perennial grass and broadleaf weeds. Triachlor-M EXP/1088 Metolachlor Trade base Ltd;UK grasses in broad leaf crops,such as beans, Mize,sugarcane,cotton Triclon EXP/946 Triclopyr Volcano various weeds ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ Uniquat EXP/622 Paraquat United For control of broad leaved weeds Phosphorus and grasses. Vapam HL EXP/990 Metam-sodium Field Produce Ltd various weeds Kadima;Israel Weedmaster EXP/1124 Glyphosate Bukoola Chem. Ind. Annual and perennial weeds in various crops Uganda IV D: ACARICIDES Ciperthion EXP/884 Ethion + Schering- Plough Control of Boophilus microplus and Cypermethrin Animal Health Haematobia irritants in cattle Dominex 15g/l EXP/543 Alpha- F M C Int. For use on cattle against ticks cypermethrin ticks, flies. Cypermethrin and flies Ecotix Pouron EXP/1045 cypermethrin high cis Farmbase ticks,fleas,and lice in livestock Omite 57E EXP/273 propargite Crompton mites control in horticulture Floramite 240SC EXP/1078 Bifenazate Chemtura chemicals, spidermites on ornamentals Nairobi Mupatix 12.5EC EXP/1200 Amitraz Equatorial Africa Ltd ticks on various animals Superdog Shampoo EXP/1043 Pyrethrins Farmbase ticks,fleas in dogs and cats Sypertix EC EXP/1118 Alpha-cypermethrin Norbrook ticks ,tsetse and nuisance flies Tedion V-18EC EXP/1108 Tetradifon Chemtura Corporation spidermites on citrus,cotton,vege etc IV E: NEMATICIDES Carbodan EXP/948 carbofuran Makhteshim insect pests in various crops Carbosan 10G EXP/653 Carbofuran Sanachem (PTY) Rice, maize, banana, against Ltd. sugarcane, tomato and tobacco aphids, caterpillar, leaf miner, nematodes and soil grub Cropguard EXP/1117 Furfural Illovo Sugar Ltd, nematodes on various crops RSA Oncol EXP/275 Benfuracarb Ohtsuka Various crops against borers, OK-174 Chem. Ltd wireworms, aphids, nematodes, weevils and maggots. Rugby 10 G EXP/276 Ebufos F M C On banana, coffee and sugarcane against nematodes and weevils. ------------------------------------------------------------------------------------------------------------------------------------------------ Trade Name Reg. No. Common Name Registrant Usage ------------------------------------------------------------------------------------------------------------------------------------------------ IV F: RODENTICIDES Biorat EXP/1000 biological Joe A. Faga rodent control rodenticide Bromatrol EXP/882 Bromadiolone Rentokil Initial Rodent control Caid EXP/447 Chlorophacinone Sumitomo Rodent control. Racumin Liquid EXP/784 Coumatetralyl Bayer (EA) Rodent control Rococide EXP/1037 Bromadiolone Rodent Control Centre rodent control Racumin Paste EXP/852 Coumatetralyl Bayer (EA) Rodent control Storm EXP/113 Flocoumafen BASF Rodent control. IV G: PLANT GROWTH REGULATORS Offshoot EXP/453 fatty alcohols Bayer AG Growth regulator on tobacco Royaltac EXP/452 1- decanol Crompton Growth regulator on tobacco Yamaotea EXP/962 Flumetralin Agri Speciality Ltd,DSM de-sucker in tobacco Yamaotea EXP/1173 Flumetralin+ Agri Speciality Ltd,DSM de-sucker in tobacco Super Butralin | false |
# Extracted Content Table 7.1: Quelea Quelea control INVADED REGIONS Tanzania Mainland COVERAGE (Ha) QUELEATOX (LITERS) Feb. 2004- to Dec.2004 Arusha,Kilimanjaro, Dodoma, Mbeya, Singida 3,447 2,466 101 Million Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives Table 7.2: Locust control Area coverage (Ha) Type of chemical used Amount (Lt) Wembere Plains (Tabora) Wembere Plains (Tabora) Malagarasi Basin (Kigoma) Malagarasi Basin (Kigoma) Iku/Katavi Plains (Rukwa) Iku/Katavi Plains (Rukwa) Bahi (Dodoma) Bahi (Dodoma) Wembere Plains (Tabora) Wembere Plains (Tabora) 4160 Fenitrothion 2080 Malagarasi Basin (Kigoma) Malagarasi Basin (Kigoma) 6,300 technical 3150 Iku/Katavi Plains (Rukwa) Iku/Katavi Plains (Rukwa) 3,540 - 1635 Bahi (Dodoma) Bahi (Dodoma 1840 - 880 Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives CHAPTER 7 PLANT HEALTH SERVICES 2003 - 2005 YEAR SPRAYED INVADED AREAS TREATMENT Feb.2005- August 2005 - 1,944 65 Million Arusha,Kilimanjaro, Dodoma, Mbeya, Singida Feb 2004- Sep-2004 RED LOCUST - - Fenitrothion technical INVESTIGATED AREAS YEAR TYPE Feb 2005- Sep- 2005 RED LOCUST 138 Table 7.3: Sanitary and Phytosanitary YEAR IMPORTS EXPORTS EXPORTS IMPORTS 583,134.46 2,763,869.92 3110 244 JUL 2004- JUNE 2005 1,227,871.94 1,137,927.17 7175 300 Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives Table 7.4: Rodent control Year Activity Area/region Chemical used (Kg) Rodenticides Other control measures Jan 2004- Dec 2004 Rodent control Mvomero, Morogoro rural, Kilosa, kilombero , Ulanga (Morogoro ), Dodoma, Lindi rural, Lindi urban, Kilwa, Nachingwea, Liwale, Ruangwa (Lindi region ) an Masasi (Mtwara), Moshi rural , Rombo (Kilimanjaro) and Bagamoyo (Coast) 76,5735 kg 20,985 farmers trained on rodent control strategies Jan- Sep, 2005 Rodent control Morogoro rural, Mvomero, Kilosa, Kilombero and ulanga (Morogoro region ), Dodoma rural, Lindi rural, Lindi urban, Kilwa, Nachingwea (Lindi region ) and Masasi (Mtwara region ). 22,273 11,062 farmers trained on rodent control strategies. Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives AGRICULTURAL PRODUCTS IN MT PHYTOSANITARY CERTIFICATES ISSUED JAN 2003- DEC 2003 - 139 Table 7.5: Armyworm Control Infested Regions Chemical Tanzania Mainland Distributed in regions (Lt) Affected - Dec 2004- 2005 Mbeya,Iringa, Dodoma, Morogoro, Kilimanjaro 980 - - - 4,500 78 Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives Table 7.6: Water Hyacinth Control Year Affected regions Coverage (Ha) Control measure(s) 12 centres of rearing of Water hyacinth weevils established water hyacinth infestation was reduced by 80 % Source: Plant Health Services, Ministry of Agriculture, Food Security and Cooperatives - Year Total infested Area in Ha. Sprayed Amount of chemical used (Lt) Number of Moth traps serviced 2 more centres established one at Rubafu , Kagera region and at Nyakalimo in Sengerema.All 124centers for rearing water hyacinth weevils were operational, a total of 155.1 million weevils were bred and implanted into lake Victoria and rivers- kagera, Mara, Kanoni , Kahororo and Ngogo. 2004 Mara, Kagera, Mwanza - Jan2005 – Sep 2005 Mara, Kagera, Mwanza 140 | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vf: REGIONAL REPORT: 1 National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vf: REGIONAL REPORT: PWANI REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary ........................................................................................................................................................ vi Illustrations .................................................................................................................................................................... xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries ........................................................................................................... 1 1.3 Land Area ........................................................................................................................................................ 1 1.4 Climate ............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall ............................................................................................................................................... 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators ............................................................................................................................. 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives ........................................................................................................................................... 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture ............................................................... 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization............................................................................................................................ 6 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign.......................................................... 8 2.6.8 Household Listing .............................................................................................................................. 8 2.6.9 Data Collection................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks....................................................................................... 9 2.6.11 Data Processing .................................................................................................................................. 9 - Manual Editing ............................................................................................................................. 9 - Data Entry..................................................................................................................................... 9 - Data Structure Formatting............................................................................................................ 9 - Batch Validation.......................................................................................................................... 10 - Tabulations................................................................................................................................... 10 - Analysis and Report Preparations ............................................................................................... 10 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS ................................................................................................ 11 3.1 Household Characteristics ........................................................................................................................... 11 3.1.1 Type of Household ........................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 15 3.1.4 Number and Age of Household Members ....................................................................................... 15 3.1.5 Level of Education ........................................................................................................................... 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Literacy Rates for Heads of Households.................................................................................... 16 - Educational Status ...................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................... 17 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised....................................................................................................................... 18 3.2.2 Types of Land Use............................................................................................................................ 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted ..................................................................................................................................... 19 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types ....................................................................................................................................... 20 3.3.4 Cereal Crop Production.................................................................................................................... 21 3.3.4.1 Maize.............................................................................................................................. 21 3.3.4.2 Paddy.............................................................................................................................. 24 3.3.4.3 Other Cereals.................................................................................................................. 27 3.3.5 Roots and Tuber Crops Production.................................................................................................. 28 3.3.5.1 Cassava........................................................................................................................... 28 3.3.5.2 Sweet Potatoes................................................................................................................ 29 3.3.6 Pulse Crops Production .................................................................................................................... 31 3.3.6.1 Cowpeas .......................................................................................................................... 31 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts..................................................................................................................... 34 3.3.8 Fruits and Vegetables........................................................................................................................ 34 3.3.8.1 Tomatoes ........................................................................................................................ 36 3.3.8.2 Water Mellon.................................................................................................................. 38 3.3.8.3 Pumpkins........................................................................................................................ 38 3.3.9 Other Annual Crops Production....................................................................................................... 39 3.3.9.1 Cotton .............................................................................................................................. 39 3.3.9.2 Seaweed........................................................................................................................... 39 3.4 Permanent Crops ........................................................................................................................................... 39 3.4.1 Cashew nuts...................................................................................................................................... 41 3.4.2 Coconuts ........................................................................................................................................ 43 3.4.3 Oranges ........................................................................................................................................ 43 3.4.4 Pineapples ........................................................................................................................................ 43 3.5 Inputs/Implements Use................................................................................................................................. 46 3.5.1 Methods of Land Clearing................................................................................................................. 46 3.5.2 Methods of Soil Preparation............................................................................................................. 46 3.5.3 Improved Seeds Use......................................................................................................................... 46 3.5.4 Fertilizers use.................................................................................................................................... 48 3.5.4.1 Farm Yard Manure Use.................................................................................................. 49 3.5.4.2 Inorganic Fertilizers Use................................................................................................ 50 3.5.4.3 Compost Use .................................................................................................................. 50 3.5.5 Pesticides Use................................................................................................................................... 51 3.5.5.1 Insecticides Use.............................................................................................................. 51 3.5.5.2 Herbicides Use ............................................................................................................... 53 3.5.5.3 Fungicides Use............................................................................................................... 54 3.5.6 Harvesting Methods ......................................................................................................................... 54 3.5.7 Threshing Methods .......................................................................................................................... 54 3.6 Irrigation .................................................................................................................................................... 55 3.6.1 Area Planted with Annual Crops and Under Irrigation................................................................... 55 3.6.2 Sources of Water Used for Irrigation............................................................................................... 57 3.6.3 Methods of Obtaining Water for Irrigation...................................................................................... 57 3.6.4 Methods of Water Application ........................................................................................................ 58 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing .................................................................................................. 58 3.7.1 Crop Storage..................................................................................................................................... 58 3.7.1.1 Method of Storage.......................................................................................................... 58 3.7.1.2 Duration of Storage........................................................................................................ 59 3.7.1.3 Purpose of Storage ......................................................................................................... 59 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 61 3.7.2 Agro-processing and By-products .................................................................................................... 61 3.7.2.1 Processing Methods ....................................................................................................... 61 3.7.2.2 Main Agro-processing Products .................................................................................... 62 3.7.2.3 Main Use of Primary Processed Products ..................................................................... 62 3.7.2.4 Outlet for Sale of Processed Products ........................................................................... 63 3.7.3 Crop Marketing ................................................................................................................................ 63 3.7.3.1 Main Marketing Problems ............................................................................................. 64 3.7.3.2 Reasons for Not Selling Crops....................................................................................... 64 3.8 Access to Crop Production Services............................................................................................................ 64 3.8.1 Access to Agricultural Credit........................................................................................................... 64 3.8.1.1 Source of Agricultural Credit......................................................................................... 64 3.8.1.2 Use of Agricultural Credit ............................................................................................. 65 3.8.1.3 Reasons for Not Using Agricultural Credit................................................................... 65 3.8.2 Crop Extension ................................................................................................................................. 65 3.8.2.1 Sources of Crop Extension Messages............................................................................ 67 3.8.2.2 Quality of Extension ...................................................................................................... 67 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.1 Inorganic Fertilisers .......................................................................................................................... 68 3.9.2 Improved Seeds ................................................................................................................................. 69 3.9.3 Insecticides and Fungicides............................................................................................................... 69 3.10 Tree Planting .................................................................................................................................................. 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population............................................................................................................ 73 3.12.1.2 Herd Size........................................................................................................................ 75 3.12.1.3 Cattle Population Trend ................................................................................................. 75 3.12.1.4 Improved Cattle Breeds ................................................................................................. 75 3.12.2 Goat Production................................................................................................................................ 75 3.12.2.1 Goat Population.............................................................................................................. 76 3.12.2.2 Goat Herd Size ............................................................................................................... 76 3.12.2.3 Goat Breeds.................................................................................................................... 76 3.12.2.4 Goat Population Trend................................................................................................... 76 3.12.3 Sheep Production.............................................................................................................................. 76 3.12.3.1 Sheep Population............................................................................................................ 76 3.12.3.2 Sheep Population Trend................................................................................................. 79 3.12.4 Pig Production .................................................................................................................................. 79 3.12.4.1 Pig Population Trend ..................................................................................................... 79 3.12.5 Chicken Production .......................................................................................................................... 81 TOC ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5.1 Chicken Population........................................................................................................ 81 3.12.5.2 Chicken Population Trend ............................................................................................. 81 3.12.5.3 Chicken Flock Size ........................................................................................................ 81 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 83 3.12.6 Other Livestock ................................................................................................................................ 83 3.12.7 Pests and Parasites Incidence and Control....................................................................................... 83 3.12.7.1 Deworming..................................................................................................................... 84 3.12.8 Access to Livestock Services........................................................................................................... 84 3.12.8.1 Access to Livestock Extension Services ....................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to Village Watering Points/dam ........................................................................ 85 3.12.9 Animal Contribution to Crop Production ........................................................................................ 85 3.12.9.1 Use of Draft Power......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 86 3.12.9.4 Use of Compost ............................................................................................................ 86 3.13 Poverty Indicators......................................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services.................................................................................... 89 3.13.2 Type of Toilets ................................................................................................................................. 89 3.13.3 Household’s Assets .......................................................................................................................... 91 3.13.4 Sources of Lighting Energy.............................................................................................................. 91 3.13.5 Sources of Energy for Cooking........................................................................................................ 91 3.13.6 Roofing Materials............................................................................................................................. 92 3.13.7 Access to Drinking Water ................................................................................................................ 92 3.13.8 Food Consumption Pattern............................................................................................................... 93 3.13.8.1 Number of Meals per Day.............................................................................................. 93 3.13.8.2 Meat Consumption Frequencies .................................................................................... 93 3.13.8.3 Fish Consumption Frequencies...................................................................................... 93 3.13.9 Food Security.................................................................................................................................... 96 3.13.10 Main Source of Cash Income........................................................................................................... 96 PART IV: PWANI PROFILES.................................................................................................................................. 98 4.1 Pwani Region Profile ..................................................................................................................................... 98 4.2 District Profiles............................................................................................................................................. 104 4.2.1 Bagamoyo........................................................................................................................................ 104 4.2.2. Kibaha.............................................................................................................................................. 106 4.2.3 Kisarawe .......................................................................................................................................... 108 4.2.4 Mkuranga......................................................................................................................................... 111 4.2.5 Rufiji................................................................................................................................................ 113 4.2.6 Mafia................................................................................................................................................ 115 ACRONYMS ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Pwani region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Pwani region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Pwani region. Included activities are indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Pwani region were 141,530 out of which 129,349 (91.4%) were involved in growing crops only, 2,086 (1.5%) rearing livestock only, 0 (0.0%) were pastoralist, and 10,094 (7.1%) were involved in crop production as well as livestock keeping. In summary, Pwani region had 139,444 households involved in crop production and 12,180 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, tree/forest resources, off farm income, livestock keeping/herding, remittances and fishing/hunting. The region has a literacy rate of 63 percent. The highest literacy rate is in Mafia district (74%) followed by Kibaha district (70%), and Kisarawe district (65%). Mkuranga and Rufiji districts had the lowest literacy rates of 63 and 58 percent respectively. The literacy rate for the heads of households in the region was 66 percent. The number of heads of agricultural households with formal education in Pwani region was 81,381 (58%), those without formal education were 53,472 (37.8%) and those with only adult education were 6,677 (4.7%). The majority of heads of agricultural households (54.2%) had primary level education whereas only 3.3 percent had post primary education. In Pwani region, of the households with at least one member engaged in off-farm income generating activities, 72,502 households (59%) had only one member involved in off-farm income generating activities, 32,643 (26%) had two members involved in off-farm income generating activities and 18,048 (15%) had more than two members involved in off- farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 312,996 ha. The regional average land utilised for agriculture per household was only 1.8 ha. This figure was below the national average of 2.0 hectares. It was highest in Mkuranga (2.1 ha.) and lowest in Mafia (1.4 ha.) EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii Planted Area The area planted with annual crops and vegetables was 177,672 hectares out of which 68,141 hectares (38.4%) were planted during short rainy season and 109,531 hectares (61.6%) during long rainy season. An estimated area of 103,559 ha (58.2% of the total planted area with annual and vegetable crops) was planted with cereals, followed by roots and tubers (51,159 ha., 28.8%), pulses (17,555ha., 9.9%), oil seed 2,920 ha., 1.6%), fruit and vegetables 2,097 ha., 1.2%) and cash crops (495ha., 1.2%) Maize Maize was the dominant annual crop in Pwani region and it had a planted area of 70,319. The area planted with maize constitutes 40 percent of the total area planted with annual crops. Other annual crops in order of their importance (based on area planted) were cassava, paddy, cowpeas, sorghum, simsim, sweet potatoes, green grams, tomatoes, seaweed, groundnuts, water melon, pumpkins, cotton, and okra. The total production of maize in 2002/03 was 22,991 tonnes. The average area planted with maize per household ranged from 0.8 hectares in Bagamoyo district to 0.2 hectares in Mafia district. Bagamoyo district had the largest planted area for maize (37,477 ha) followed by Rufiji (12,653 ha), Mkuranga (8,413 ha), Kisarawe (6,472 ha), Kibaha (5,215 ha) and Mafia (90 ha). Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Pwani region during the long rainy season was 30,542. This represented 43 percent of the total crop growing households in Pwani Region in the long rainy season. Cassava The area planted with cassava was larger than any other root and tuber crop in Pwani in terms of planted area (27.7% of the total area planted with annual crops and vegetables) and it accounted for 96 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 4,178 tonnes. The most cultivated fruit and vegetable crop was the tomato. The production for this crop was 1,944 tonnes, which amounts to 47 percent of the total fruit and vegetable production, followed by water melon 1,124 tonnes (26.9%) and pumpkins 225 tonnes (5.4%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 82,031 hectares which was 32 percent of the area planted with crops in the region. The most important permanent crop was cashew nuts which accounted for 52 percent of the total area planted with permanent crops followed by coconuts (21%), oranges (9.3%), pineapples (4.4%) and bananas (4.3%) Improved Seeds The planted area using improved seeds was 15,403 ha which represented 12 percent of the total planted area with the annual crops and vegetables. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Use of Fertilizers Most annual crop growing households did not use any fertilisers. The planted area without fertiliser for annual crops was 163,388 hectares representing 92 percent of the total area planted with annual crops. Of the planted area with fertiliser application, compost was applied to 8,040 ha which represented 4.5 percent of the total planted area (56.3 % of the area planted with fertiliser application). This was followed by farm yard manure (4,669 ha, 2.6%). Inorganic fertilizers were used on a very small area and represented only 0.9 percent of the area planted with fertilizers. Irrigation In Pwani region, the area of annual crops and vegetables under irrigation was 58,870 ha representing 33.1 percent of the total area planted. The area under irrigation during the short rainy season was 1,512 ha accounting for 2.6 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 52.4 percent compared with 2.2 percent in the short rainy season. Crop Storage There were 43,973 crop growing households (31.5% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 28,351 households storing 6,888 tonnes. This was followed by beans and other pulses (11,798 households and 208t), paddy (11,095 households and 1,538t), and sorghum and millet (2,466 households and 196 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 78,458 which represented 56 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Mafia (80%) followed by Kisarawe (61%), Rufiji (60%), Kibaha (47%), and Bagamoyo (33%). Agricultural Credit In Pwani region, few agricultural households (1,681, 1.2%) accessed credit, out of which 1,521 (90%) were male-headed households and 160 (10%) were female headed households. In Bagamoyo and Rufiji districts only male-headed households accessed credit (100%). In Mkuranga district both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 46,727 (37% of total crop growing households in the region). Some districts had more access to extension services than others. Kisarawe district had a relatively high proportion of households that received crop extension messages (61%), followed by Kibaha (43%), Bagamoyo (32%), Mkuranga (28%), Rufiji (25%) and Mafia (4%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 1,935. This number represents 1 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Kisarawe District (4%) followed by Mkuranga (2%), Mafia (2%), Kibaha (1%), Bagamoyo (1%) and none in Rufiji. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 122,308. Cattle was the dominant livestock type in the region followed by goats, sheep and pigs. The region had 0.7 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 110,360 head (90.2% of the total number of cattle in the region), 10,809 (8.8%) were dairy breeds and only 1,140 (0.9%) were beef breeds. Goats The number of goat-rearing-households in the region was 7,621 (5% of all agricultural households) with a total of 98,604 goats giving an average of 13 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 1,503 (1.06% of all agricultural households) with a total of 24,334 sheep giving an average of 16 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 353 (0.2% of the total agricultural households) rearing about 3,673 pigs. This gives an average of 10 pigs per pig-rearing household. Chicken The number of households keeping chicken was 79,507, raising 1,420,152 chicken. This gives an average of 18 chicken per chicken-rearing household. In terms of total number of chicken in the country Pwani ranked 13th out of the 21 Mainland regions. Use of Draft Power The region has 92 oxen and all in Mafia district. Pwani region has 0.002 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 19 hectares of land, also in Mafia district. Fish Farming Fish farming was not practiced in Pwani region. iv) Poverty Indicators Availability of Toilets It was estimated that 88.9 percent of all rural agricultural households used the traditional pit latrines, 1.7 percent used improved pit latrines and 3 percent had flush toilets. The remaining 0.02 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 6.3 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (69.8% of households) followed by bicycle (45%), iron (14.5%), wheelbarrow (3.1%), mobile phone (1.8%), television/video (1.2%), vehicle (1%) and landline phone (0.3%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 78.5 percent of the total rural households used this source of energy followed by hurricane lamp (15%), pressure lamp (3%), mains electricity (1.8%), firewood (1.3%), solar (0.2%), candle (0.3%) and other (0.02%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.8 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (4.5%). The rest of energy sources accounted for 0.7 percent. These were bottled gas (0.2%), crop residues (0.1%), solar (0.1%), livestock dung (0.1%), parrafin/kerosene (0.1%) and gas/biogas (0.1%) and none for mains electricity. Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 66 percent of the rural agricultural households however, this was followed by iron sheets (26.7%). Other roofing materials are grass/mud (6.5%), asbestos (0.4%), tiles (0.3%) and others (0.2%). Number of Meals per Day About 64.7 percent of the holders in the region took three meals per day, 28.1 percent took two meals, 5.4 percent took one meal and 1.8 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 38.1 percent of the total number of agriculture households in the region. Households which sometimes experienced food shortage problems represent 8.6 percent whereas those who often experienced problems represent 20.9 percent. About 6.3 percent of agriculture households always faced food shortages whilst 26.2 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of cash crops was the main cash income earning activity reported by 22.7 percent of all rural agricultural households. The second main cash income earning activity was sale of food crops (22.4%) followed by selling of forest products (19.2%), casual cash earnings (10.8%) and businesses (8.6%). Other income earnings were cash remittances (5.6%), fishing (4.5%), wages and salaries (2.9%), sale of livestock products (1.5%), unspecified sources (0.9%) and lastly, sale of livestock (0.9%). ILLUSTRATIONS ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ............................................................................................................................................... 7 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 21 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop ...................................... 28 3.4 Area, Quantity Harvested and Yield of Pulses by Season ................................................................................. 31 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season...................................................................... 36 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 38 3.8 Land Clearing Methods....................................................................................................................................... 46 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season...................................... 48 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizers Use and District - the Long Rainy Season..................................................................................................................................... 48 3.11 Number of Households Storing Crops by Estimated Storage Loss and District............................................... 61 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 64 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 64 3.14 Access to Inputs .................................................................................................................................................. 68 3.15 Total Number of Households and Chicken Raised by Flock Size...................................................................... 81 3.16 Number of Other Livestock by Type of Livestock and District ........................................................................ 88 3.17 Mean distances from holders dwellings to infrastructures and services by districts......................................... 89 3.18 Number of Households by Number of meals the Household normally has per Day and District.................... 93 List of Charts 3.1 Agricultural Households by Type of Holdings .................................................................................................. 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ............................................ 15 3.3 Percentage Distribution of Population by Age and Sex - PWANI .................................................................... 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates of Heads of Household by Sex and District............................................................................... 16 3.6 Percentage of Persons Aged 5 years and above by Educational Status............................................................. 16 3.7 Percentage of Population Aged 5 years and Above by District and Education Status ..................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Number of household Members with Off Farm Income – Pwani Region......................................................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities................................. 17 3.11 Utilized and Usable Land per Household by District ........................................................................................ 18 3.12 Land Area by Type of Land Use ........................................................................................................................ 18 3.13 Area Planted with Annual Crops (ha) by Season............................................................................................... 18 3.14 Area Planted with Annual Crops by Season and District .................................................................................. 19 3.15 Area Planted per household by Season and District .......................................................................................... 19 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................... 20 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type..................................................... 20 3.18 Area planted with Annual Crops by Type of Crops and Season ....................................................................... 20 3.19 Area Planted and Yield of Major Cereal Crops ................................................................................................. 21 3.20 Maize: Total Area Planted and Planted Area per Household by District.......................................................... 21 3.21 Time Series Data on Maize Production – Pwani Region................................................................................... 24 3.22 Time Series of Maize Planted Area and Yield – Pwani Region........................................................................ 24 3.23 Total Planted Area and Area of Paddy per Household by District.................................................................... 27 3.24 Time Series Data on Paddy Production – Pwani Region................................................................................... 27 3.25 Time Series of Paddy Planted Area and Yield – Pwani Region........................................................................ 27 3.26 Area Planted With Sorghum, Bulrush Millet and Finger Millet by District ..................................................... 27 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................... 28 3.28 Area planted with Cassava during the census/survey years................................................................................ 28 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District..................................... 29 3.30 Cassava Planted Area per Cassava Growing Households by District ............................................................... 29 3.31 Total Area Planted with Sweet Potatoes and Planted Area per Household by District .................................... 29 3.32 Area Planted and Yield of Major Pulse Crops ................................................................................................... 31 3.33 Percent of Cowpeas Planted Area and Percent of Total Land with Cowpeas by District................................. 31 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.34 Area Planted per Cowpeas Growing Household by District (Long Rainy Season Only)................................. 31 3.35 Time Series Data on Cowpeas Production – Pwani Region.............................................................................. 32 3.36 Time Series of Cowpeas Planted Area and Yield - Pwani................................................................................. 32 3.37 Area Planted and Yield of Major Oil Seed Crops.............................................................................................. 32 3.38 Time Series Data on Groundnut production – Pwani Region............................................................................ 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........................ 34 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) .............................. 34 3.42 Area Planted and Yield of Fruit and Vegetables................................................................................................ 34 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 36 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only)................................... 36 3.45 Percent of Water Mellon Planted Area and Percent of Total Land with Water Mellon by District................. 38 3.46 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District.............................. 38 3.47 Area planted with Annual Cash Crops ............................................................................................................... 39 3.48 Percent of Seaweeds Planted Area and Percent of Total Land with Seaweeds by District .............................. 39 3.49 Area Planted for Annual and Permanent Crops ................................................................................................. 39 3.50 Area Planted with the Main Permanent Crops ................................................................................................... 41 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District................................... 41 3.52 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District................... 41 3.53 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.54 Percent of Area Planted with Oranges and Average Planted Area per Household by District......................... 43 3.55 Percent of Area Planted with Pineapples and Average Planted Area per Household by District..................... 46 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season ..................................... 46 3.57 Area Cultivated by Cultivation Method .............................................................................................................. 46 3.58 Area Cultivated by Method of Cultivation and District..................................................................................... 47 3.59 Planted Area with Improved Seeds by Crop Type............................................................................................. 47 3.60 Percentage of Crop Type Planted Area with Improved Seeds – Annuals ......................................................... 47 3.61 Area of Fertilizer Application by Type of Fertilizers ......................................................................................... 47 3.62 Area of Fertilizer Application by Type of Fertilizers and District .................................................................... 48 3.63 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season..................................................... 48 3.64 Planted Area with Farm Yard Manure by Crop type – Annuals........................................................................ 49 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals.................................................... 49 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District ........................................................ 49 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals........................................................................ 49 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 50 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District ........................................................ 50 3.68a Planted Area with Compost by Crop Type......................................................................................................... 50 3.68b Percentage of Planted Area with Compost by Crop Type ................................................................................. 51 3.68c Proportion of Planted Area Applied with Compost by District......................................................................... 51 3.69 Planted area (ha) by Pesticides use..................................................................................................................... 51 3.70 Planted Area applied with Insecticides by Crop Type....................................................................................... 51 3.71 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 51 3.72 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season................... 53 3.73 Planted Area applied with herbicides by Crop Type.......................................................................................... 53 3.74 Percentage of Crop Type Planted Area applied with herbicides ....................................................................... 53 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season..................... 53 3.76 Planted Area applied with Fungicides by Crop Type ........................................................................................ 54 3.77 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 54 3.78 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season .................... 54 3.79 Planted Area With Irrigated Land....................................................................................................................... 55 3.80 Planted Area and Percentage of Planted Area with Irrigation by District......................................................... 55 3.81 Time Series of Households with Irrigation – Pwani .......................................................................................... 55 8.82 Number of Households with Irrigation by Source of Water.............................................................................. 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................... 57 3.84 Number of Households with Irrigation by Method of Field Application.......................................................... 57 3.85 Number of Households and Quantity Stored by Crop Type.............................................................................. 58 3.86 Number of households by Storage Methods ...................................................................................................... 58 3.87 Number of households by method of storage and District (based on the most important household crop)...... 58 3.88 Normal Length of Storage for Selected Crops ................................................................................................... 59 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District.................................................. 59 3.90 Number of Households by Purpose of Storage and Crop Type......................................................................... 59 3.91a Percentage of Households Processing Crops by District................................................................................... 61 3.91b Percent of Households Processing Crops by District......................................................................................... 61 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 61 3.93 Percent of Households by Type of Main Processed Product............................................................................. 62 3.94 Number of Households by Type of By-product................................................................................................. 62 3.95 Use of Processed Product.................................................................................................................................... 62 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 62 3.97 Location of Sale of Processed Products ............................................................................................................. 63 3.98 Percentage of Households Selling Processed Produce by Outlet for Sale and District..................................... 63 3.99 Number of Crop Growing Households Selling Crops by District..................................................................... 63 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 64 3.101 Percentage Distribution of Households that Received Credit by Main Sources............................................... 64 3.102 Number of Households Receiving Credit by Main Source of Credit and District............................................ 64 3.103 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 65 3.104 Reasons for Not using Credit.............................................................................................................................. 65 3.105 Number of Households Receiving Extension Advice........................................................................................ 67 3.106 Number of Households that Received Extension by District ............................................................................ 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 67 3.108 Number of Households that Received Extension by Reported Quality of Services ......................................... 67 3.109 Number of Households by Source of Inorganic Fertilisers................................................................................ 68 3.110 Number of Households Reporting Distance to Source of Inorganic Fertilisers................................................ 68 3.111 Number of Households by Source of Improved Seeds ...................................................................................... 69 3.112 Number of Households reporting Distance to Improved Seeds......................................................................... 69 3.113 Number of Households by Source of Insecticides/Fungicides .......................................................................... 69 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 69 3.115 Number of Households with Planted Trees by District ..................................................................................... 70 3.116 Number of Planted Trees by Species................................................................................................................... 70 3.117 Number of Trees Planted by Smallholders by Species and District.................................................................. 70 3.118 Number of Trees Planted by Location................................................................................................................ 71 3.119 Number of Households by purpose of Planted Trees......................................................................................... 71 3.120 Number of Households with Erosion Control/Water Harvesting Facilities...................................................... 71 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District........... 71 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................. 73 3.123 Total Number of Cattle ('000') by District.......................................................................................................... 73 3.124 Numbers of Cattle by Type and District............................................................................................................. 73 3.125 Cattle Population Trend ...................................................................................................................................... 75 3.126 Improved Cattle Population Trend ..................................................................................................................... 75 3.127 Total Number of Goats ('000') by District.......................................................................................................... 75 3.128 Goat Population Trend........................................................................................................................................ 76 3.129 Total Number of Sheep by District..................................................................................................................... 76 3.130 Sheep Population Trend...................................................................................................................................... 79 3.131 Total Number of Pigs by District........................................................................................................................ 79 3.132 Pig Population Trend .......................................................................................................................................... 79 3.133 Total Number of Chicken by District................................................................................................................. 81 3.134 Chicken Population Trend .................................................................................................................................. 81 3.135 Number of Improved Chicken by Type and District........................................................................................... 83 3.136 Improved Chicken Population Trend ................................................................................................................. 83 3.137 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District ..... 83 3.138 Percent of Livestock Rearing Households that De-wormed Livestock by Livestock Type and District ......... 84 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 84 3.140 Number of Households by Distance to Veterinary Clinic ................................................................................. 85 3.141 Number of Households by Distance to Veterinary Clinic and District ............................................................. 85 3.142 Number of Households by Distance to Village Watering Point........................................................................ 85 3.143 Number of Households by Distance to Watering Point and District................................................................. 85 3.144 Number of Households using Draft Animals..................................................................................................... 86 3.145 Number of Households using Draft Animals by District................................................................................... 86 3.146 Number of Households using Organic Fertilisers.............................................................................................. 86 3.147 Area of Application of Organic Fertilisers by District....................................................................................... 86 3.148 Agricultural Households by Type of Toilet Facility.......................................................................................... 89 3.149 Percentage Distribution of Households Owning the Assets .............................................................................. 91 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting .............................................. 91 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 91 3.152 Percentage Distribution of Households by Type of Roofing Material.............................................................. 92 3.153 Percentage Distribution of Households With Grass/Leaves Roofs by District................................................. 92 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.154 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season... 92 3.155 Percentage Distribution of the Number of Households by Main Source of Income......................................... 92 3.156 Number of Agriculture Households by Number of Meals per day.................................................................... 93 3.157 Number of Households by Frequency of Meat and Fish Consumption ............................................................. 93 3.158 Percent Distribution of the Number of Households by Main Source of Income .............................................. 96 List of Maps 3.01 Total Number of Agricultural Households by District....................................................................................12 3.02 Number of Agricultural Households per Square Km of Land by District......................................................12 3.03 Number of Crop Growing Households by District..........................................................................................13 3.04 Percent of Crop Growing Households by District...........................................................................................13 3.05 Number of Crop Growing Households per Square Kilometer of Land by District........................................14 3.06 Percent of Crop and Livestock Households by District ..................................................................................14 3.07 Utilized Land Area Expressed as a Percent of Available Land ......................................................................22 3.08 Total Planted Area (annual crops) by District .................................................................................................22 3.09 Area planted and Percentage During the Short Rainy Season by District......................................................23 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District................................23 3.11 Planted Area and Yield of Maize by District...................................................................................................25 3.12 Area Planted per Maize Growing Household .................................................................................................25 3.13 Planted Area and Yield of Paddy by District...................................................................................................26 3.14 Area Planted per Paddy Growing Household .................................................................................................26 3.15 Planted Area and Yield of Cassava by District ...............................................................................................30 3.16 Area Planted per Cassava Growing Household ..............................................................................................30 3.17 Planted Area and Yield of Beans by District...................................................................................................33 3.18 Area Planted per Beans Growing Household .................................................................................................33 3.19 Planted Area and Yield of Groundnuts by District..........................................................................................35 3.20 Area Planted per Groundnuts Growing Household ........................................................................................35 3.21 Planted Area and Yield of Tomatoes by District.............................................................................................37 3.22 Area Planted per Tomatoes Growing Household ...........................................................................................37 3.23 Planted Area and Yield of Cotton by District..................................................................................................40 3.24 Area Planted per Cotton Growing Household ................................................................................................40 3.25 Planted Area and Yield of Cashewnut by District...........................................................................................42 3.26 Area Planted per Cashewnut Growing Household .........................................................................................42 3.27 Planted Area and Yield of Coconuts by District .............................................................................................44 3.28 Area Planted per Coconuts Growing Household ............................................................................................44 3.29 Planted Area and Yield of Oranges by District ...............................................................................................45 3.30 Area Planted per Orange Growing Household ...............................................................................................45 3.31 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..............................52 3.32 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................56 3.33 Percent of households storing crops for 3 to 6 months by district..................................................................60 3.34 Number of Households and Percent of Total Households Selling Crops by District.....................................60 3.35 Number of Households and Percent of Total Households Receiving Crop....................................................66 3.36 Number and Percent of Crop Growing Households Using Improved Seeds..................................................66 3.37 Number and percent of smallholder planted trees by district..........................................................................72 3.38 Number and Percent of Households with water Harvesting Bunds by District..............................................72 3.39 Cattle population by District as of 1st October 2003 ......................................................................................74 3.40 Cattle Density by District as of 1st October 2003...........................................................................................74 3.41 Goat population by District as of 1st October 2003........................................................................................77 3.42 Goat Density by District as of 1st October 2003.............................................................................................77 3.43 Sheep population by District as of 1st October 2003......................................................................................78 3.44 Sheep Density by District as of 1st October 2003...........................................................................................78 3.45 Pig population by District as of 1st October 2003...........................................................................................80 3.46 Pig Density by District as of 1st October 2003 ...............................................................................................80 3.47 Number of Chicken by District as of 1st October 2003..................................................................................82 3.48 Density of Chicken by District as of 1st October 2003...................................................................................82 3.49 Number and Percent of Households Infected with Ticks by District..............................................................87 3.50 Number and Percent of Households Using Draft Animals by District...........................................................87 3.51 Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District .........................................................................................................................................................88 3.52 Planted Area and Percent of Total Planted Area with Compost application by District................................88 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.53 Number and Percent of Households Without Toilets by District....................................................................90 3.54 Number and Percent of Households using Grass/leaves for roofing material by District..............................94 3.55 Number and Percent of Households eating 3 meals per day by District.........................................................94 3.56 Number and Percent of Households eating Meat Once per Week by District................................................95 3.57 Number and Percent of Households eating Fish Once per Week by District.................................................95 3.58 Number and percent of Households Reporting food insufficiency by District ..............................................97 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Pwani region was officially established in July when the former Coast region whose headquarters was in Dar es Salaam was divided to form two regions namely Dar es Salaam and the present Pwani region. Pwani region is situated on the Eastern part of Tanzania Mainland along the Indian Ocean coastal belt, located between 60 and 80 South of the Equator and between 370 – 40010’ East of the Greenwich Meridian line. Pwani region shares boarders with Tanga region to the North, Morogoro regions to the West and Lindi region to the South. On the Eastern side the region shares boarders with Dar es Salaam and the Indian Ocean. The region comprises six districts of Bagamoyo, Kibaha, Kisarawe, Mkuranga, Rufiji, and Mafia. The headquarters of the new Pwani region remained to be Dar es Salaam until the year 1979 when it was shifted to Kibaha town located some 40km West of Dar es Salaam city along the highway to Morogoro. 1.3 Land Area The region has an area of 33,539 square kilometers, which is equivalent to 3.8% of the total area of Tanzania Mainland. Dry land area covers 32,407 square kilometers (97%) and the remaining 1,132 square kilometers (3%) is covered by water. 1.4 Climate 1.4.1 Temperature The region experiences a typical tropical climate with an average temperature of 280 Centigrade. 1.4.2 Rainfall The region has two rainy seasons, the short and the long rainy seasons. The short rainy season (Vuli) is between October and December and the Long rainy season (Masika) is between March and June, with an average of 1000 mm per year. 1.5 Population According to the 2002 Population and Housing Census, there were 889,154 inhabitants in Pwani region, of which 440,161 were males and 448,993 were females. The population of Pwani region ranked 20th of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at Current Prices for the year 2003 was estimated to be TShs 226,488 million with a per capita GDP income of shillings 250,843. The region held 21st position among regions on GDP and contributed about 2.3 percent to the national GDP1. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 Pwani region is well served with communication network with the rest of the regions by road and railway lines. There is one airport at Kilindoni in Mafia and one airstrip in Utete. In 1998 the region had about 2022 workers in the manufacturing industry and contributed a value added of Tshs. 2,051 million to national GDP. In 2002 the most important cash crop in Pwani region was the cashewnut. Other important permanent crops are coconuts, oranges and pineapples. The region is famous for producing both food and cash crops. The main food crops include maize, cassava, paddy, cowpeas, sorghum, simsim, sweet potatoes and green grams. The main annual cash crops produced in Pwani region include seaweeds and cotton. Livestock keeping is also an important economic activity in the region. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Pwani region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Pwani (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census for Pwani region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys, effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Pwani region was 141,530. The largest number of agriculture households was in Bagamoyo (37,290) followed by Mkuranga (34,744), Rufiji (30,906), Kisarawe (18,637) Kibaha, (14,029) and Mafia (5,924) (Map 3.1). The highest density of households was found in Mkuranga (32/km2) and Mafia (27%) (Map 3.2). Most households (129,349, 91.4%) were involved in growing crops only, 2,086 (1.5%) rearing livestock only, 0 (0.0%) pastoralists, and 10,094 (7.1%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Pwani region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by permanent crop farming, tree/forest resources, off farm income, livestock keeping/herding, remittances and fishing/hunting & gathering. (Table 3.1). Kisarawe and Mkuranga are the only districts whereby annual crop farming was not the most important source of livelihood, being replaced by permanent crop farming. Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remit tances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 1 4 5 3 6 7 2 Kibaha 1 3 5 2 6 7 4 Kisarawe 2 1 6 4 5 7 3 Mkuranga 2 1 5 3 6 7 4 Rufiji 1 3 7 4 6 5 2 Mafia 1 2 5 3 7 4 6 Total 1 2 5 4 6 7 3 Chart 3.1 Agriculture Households by Type - Pwani Crops and Livestock 7.1% Crops Only 91.4% Livestock Only 1.5% Pastoralists 0.0% Mkuranga Kisarawe Kibaha Bagamoyo Rufiji Mafia 34,744 18,637 14,029 37,290 30,906 5,924 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Kisarawe Bagamoyo Mkuranga Rufiji Mafia Kibaha 12 12 32 6 27 16 32 to 40 24 to 32 16 to 24 8 to 16 0 to 8 Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.1 PWANI Total Number of Agricultural Households by District Map 3.2 PWANI Number of Agricultural Households Per Square Kilometer of Land by District RESULTS 12 Bagamoyo Kibaha Kisarawe Rufiji Mafia 31,426 12,976 17,645 34,251 28,997 4,055 Mkuranga 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 84% 92% 95% 99% 94% 68% 92.8 to 99 86.6 to 92.8 80.4 to 86.6 74.2 to 80.4 68 to 74.2 Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.03 PWANI Number of Crop Growing Households by District Map 3.04 PWANI Percent of Crop Growing Households by District RESULTS 13 Kibaha Kisarawe Rufiji Mafia 12% 5% 1% 5% 5% 30% Mkuranga Bagamoyo 27.2 to 34 20.4 to 27.2 13.6 to 20.4 6.8 to 13.6 0 to 6.8 Bagamoyo Kisarawe Rufiji Mafia Kibaha 10 31 11 5 1 8 15 Mkuranga 24.8 to 31 18.6 to 24.8 12.4 to 18.6 6.2 to 12.4 0 to 6.2 Tanzania Agriculture Sample Census Number of Crop Growing Households Per Sq Km of Land Crop Growing Households Per Sq Km of Land Percent of Crop and Livestock Households Percent of Crop and Livestock Households Map 3.05 PWANI Number of Crop Growing Households Per Square Kilometer of Land by District Map 3.06 PWANI Percent of Crop and Livestock Households by District RESULTS 14 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Pwani region was 115,108 (81% of the total regional agricultural households) whilst the female-headed households were 26,422 (19% of the total regional agricultural households). The mean age of household heads was 49 years (48 years for male heads and 53 years for female heads) (Chart 3.2) . The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female heads. 3.1.4 Number and Age of Household Members Pwani region had a total rural agricultural population of 712,995 of which 354,379 (50%) were males and 358,616 (50%) were females. Whereas age group 0-14 constituted 42 percent of the total rural agricultural population, age group 15–64 (active population) was only 50 percent. Pwani region had an average household size of 5 with all districts having the same household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Pwani region had a total literacy rate of 63 percent. The highest literacy rate was found in Mafia district (74%) followed by Kibaha district (70%) and Kisarawe district (65%). Rufiji and Mkuranga districts had the lowest literacy rates of 58 and 63 percent respectively (Chart 3.4). Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Chart 3.3 Percent Distribution of Population by Age and Sex - Pwani 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literacy Level of Household Members by District 0 20 40 60 80 Mafia Kibaha Kisarawe Bagamoyo Mkuranga Rufiji District Percent RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 66 percent. The literacy rate for the maleheads was 72 percent and that of female heads of households was 38 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Mafia (74%) followed by Kibaha (70%), Mkuranga (69%), Bagamoyo (66%), Kisarawe (64%), and Rufiji (61%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 35.8 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 27.9 percent were still attending school. Those who have never attended school were 36.3 percent (Chart 3.6). Agricultural households in Kibaha district had the highest percentage (44.6%) of population aged 5 years and above who had completed different levels of education. This was followed by Mafia and Kisarawe districts with 42.9 and 38.3 percent respectively. Rufiji and Mkuranga districts had the lowest percentages of 29.9 and 33.7 respectively. The number of heads of agricultural households with formal education in Pwani region was 81,381 (58%), those without formal education were 53,472 (38%) and those with only adult education were 6,677 (5%). The majority of heads of agricultural households (54%) had primary level education whereas only 3 percent had post primary education. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Attending School 27.9% Never Attended 36.3% Completed 35.8% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Kibaha Mafia Kisarawe Bagamoyo Mkuranga Rufiji District Percent Attending School Completed Never Attended Chart 3.5 Literacy Rates of Head of Household by Sex and District - PWANI 0 25 50 75 100 Bagamoyo Kibaha Kisarawe Total Mkuranga Rufiji Mafia District Percent Male Female Total Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Post Primary Education 3% Adult Education 5% No Education 38% Primary Education 54% RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 With regard to the heads of agricultural households with primary or secondary education in Pwani region, Bagamoyo district had the highest percentages (29% for primary and 20% for secondary). This was followed by Mkuranga (22% primary and 33% secondary), Rufiji (21% primary and 16% secondary) and Kisarawe (14% primary and 10% secondary). Mafia had the lowest percentage of heads of agricultural households with both primary education (5%) and secondary education (6%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Pwani with 87 percent of households having at least one member with off-farm income. In Pwani region, of the 123,194 households with at least one member engaged in off-farm income generating activities, 72,502 households (59%) had only one member aged 5 and above involved in only one off-farm income generating activity, 32,643 households (26%) had two members involved in off-farm income generating activities and 18,048 households (15%) had more than two members involved in off-farm income generating activities. Kisarawe district had the highest percentage of agriculture households with off-farm income (98% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Bagamoyo (92%), Kibaha (90%), and Mkuranga (82%). Rufiji and Mafia districts had the lowest percent of agriculture households with off-farm income (81% and 79% respectively). (Chart 3.11). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country, but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Chart 3.9 Number of Household by Number of Members with Off-farm Income One, 72,502, 51% Two, 32,643, 23% More than two, 18,048, 13% None, 18,336, 13% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Districts Percent More than Two Two One No ne RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 312,996 ha. The regional average land area utilised for agriculture per household was only 1.8 ha. This figure is below the national average which is estimated at 2.0 hectares. Eighty percent of the total land available to smallholders was utilised. Only 20.0 percent of usable land available to smallholders was not used (Chart 3.11) Map 3.7. Large differences in land area utilised per household existed between districts with Bagamoyo and Mkuranga utilizing between 1.8 and 2.1 ha per household. The smallest land area utilised per household was found in Mafia (1.4 ha). The percentage utilized of the usable land per household was highest in Mafia (94%) and lowest in Bagamoyo (68%). 3.2.2 Types of Land Use The area of land under permanent/annual mix was the largest at 65,532 hectares (20.9% of the total land available to smallholders in Pwani), followed by temporary monocrop (59,468 ha, 19.0%), permanent mixed crop (43,438 ha, 13.9%), permanent monocrop (41,042 ha, 13.1%), uncultivated usable land (33,671 ha, 10.8%), temporary mixed crops (33,566 ha, 10.7%), area under fallow (14,787 ha, 4.7%), unusable area (7,702 ha, 2.5%), area under pasture (5,932 ha, 1.9%), area under natural bush (5,319 ha, 1.7%), area rented to others (1,818 ha, 0.6%) and area planted with (722 ha, 0.2%). 3.3 Annual Crops and Vegetable Production Pwani region has two rainy seasons, namely the short rainy season (October to November) and the long rainy season (April to May). The quantity of crops produced in both seasons will be used as a base in comparing with results from the past surveys and censuses. Chart 3.12 Land Area by Type of Use 19.0 20.9 13.9 13.1 10.8 10.7 4.7 2.5 1.9 1.7 0.6 0.2 0 50000 100000 150000 200000 Planted Trees Rented to Others Natural Bush Pasture Unusable Fallow Temporary Mixed Crops Uncultivated Usable Land Permanent Mono Crops Permanent Mixed Crops Temporary Mono Crops Permanent / Annual Mix Land Use Area (hectares) Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Districts Area/household 0 20 40 60 80 100 120 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 19 3.3.1 Area Planted The area planted with annual crops and vegetables was 177,672 hectares out of which 68,141 hectares (38.4%) were planted during short rainy season and 109,531 hectares (61.6%) during long rainy season. (Chart 3.13). The average areas planted per household during the short and long rainy seasons were 0.7 and 1.6 ha respectively The districts with the largest area planted per household (the average of the two seasons) were Mkuranga (1.5 ha) followed by Kisarawe and Rufiji (1.3 ha). The district with the smallest average area planted was Mafia (0.5ha). In all districts the average area planted during the long rainy season was higher than that of the short rainy season except Mafia district the average area planted during the short rainy season is the same as that of the long rainy season (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 103,560 ha (58.3% of the total area planted with annuals). This was followed by roots and tubers (51,158 hectares, 28.8%), pulses (17,552 hectares, 9.9%), oil seeds (2,920 hectares, 1.6%), fruit and vegetables (1,987 hectares, 1.1%), and cash crops (495 hectares, 0.3%). The average area planted per household during the long rainy season in Pwani region was 1.6 hectares, however, there were large district differences. The districts with the largest area planted per household (the average of the two seasons) were Mkuranga (1.5 ha) followed by Kisarawe and Rufiji (1.3 ha). The district with the smallest average area planted was Mafia (0.5ha). (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. Chart 3.14 Area Planted with Annual Crops by Season and Region - 20,000 40,000 60,000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Region Area Planted (ha) 0.00 20.00 40.00 60.00 Percentage Planted Short Rainy Season Long Rainy Season % Area planted in short rainy season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Short Rainy Season, 68141, 38% Long Rainy Season, 109531, 62% Short Rainy Season Long Rainy Season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 0.50 1.00 1.50 Bagamoyo Rufiji Mkuranga Kibaha Kisarawe Mafia District Area Planted (ha) Long Rainy Season Short Rainy Season RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 20 3.3.2 Crop Importance Maize is the dominant annual crop grown in Pwani region and it had a planted area 1.4 times greater than cassava, which had the second largest planted area. The area planted with maize and cassava constituted 67.3 percent of the total area planted with annual crops in the region. The area planted with maize only constituted 40 percent. Other crops in order of their importance (based on area planted) were paddy, cowpeas, sorghum, simsim, sweet potatoes and green grams. (Chart 3.16). Households that grew maize, cassava and green gram had larger planted areas per household than for other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Pwani region. The area planted with cereals was 103,097 ha (76.4% of the total planted area), followed by pulses with 17,497 ha (13.0%), root and tubers 9,028 ha (6.7%), oil seeds 2,920 ha (2.2%) and fruits and vegetables 1,987 ha (1.5%). Annual cash crops that are constituted of cotton and seaweed had got the least planted area of about 495 ha (0.4%) (Chart 3.17b). Cereals and pulses are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.17a Planted Area (ha) per Household by Selected Crop - PWANI 0.00 0.50 1.00 1.50 2.00 Maize Cassava Green Gram Cucumber Radish Water Mellon Finger Millet Seaweed Cowpeas Okra Paddy Sorghum Cotton Yams Groundnuts Pumpkins Tomatoes Crop Planted Area (ha) Chart 3.16 Planted Area (ha) for the Main Crops Pwani 0 25000 50000 75000 Maize Paddy Cowpeas Cassava Sorghum Simsim Sweet Potatoes Green Gram Tomatoes Seaweed Groundnuts Water Mellon Pumpkins Crop Planted Area (ha) Chart 3.17: Percentage Distribution of Area planted with Annual Crops by Crop Type Cereals, 76.4% Pulses, 13.0, % Cash crops, 0.4% Fruits & Vegetables, 1.5% Roots & Tubers, 6.7% Oil seeds & Oil nuts, 2.2% Cereals Ro o ts & Tubers P uls es Oil s eeds & Oil nuts Fruits & Vegetables Cas h cro ps 48768 3611 5417 5491 12006 2552 368 940 1046 243 252 0 25000 50000 75000 100000 Area (hecta res) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 21 3.3.4 Cereal Crop Production The total production of cereals was 31,358 tonnes. Maize was the dominant cereal crop at 22,991 tonnes which was 73 percent of total cereal crops produced, followed by paddy (23%) sorghum (4.1%), Finger millet (0.07%) and Bulrush millet (0.01%). Bagamoyo district had the largest planted area of Cereals in the region (44,590ha) followed by Rufiji, (24,499ha), Mkuranga (14,511ha), Kibaha (9,998ha), Kisarawe (8,442ha) and Mafia (1,521ha). (Map 3.10). The total area planted with cereals during the short and long rainy seasons was 103,560 ha out of which 48,939 ha (47.4%) were planted in short rainy season and 54,620 ha (52.4%) were planted during the long rainy season. The long rainy season accounts for 54 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 77.7 percent of the total area planted with cereals in that season followed by paddy (20.3%) and sorghum (1.6%) (Table 3.2). The area planted with maize was dominant and it represented 67.9 percent of the total area planted with cereal crops, then followed by paddy (27.59%), sorghum (4.32%), burley (0.11%), finger millet (0.10%) and bulrush millet (0.04%). The yield of maize was 327 kg/ha, followed by sorghum (286 kg/ha), paddy (248 kg/ha) and Bulrush millet (50 kg/ha). Wheat and barley were not grown in the region (Chart 3.19). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Pwani region during the long rainy season was 40,193, (57% of the total crop growing households in the region during the long rainy season). The total production of maize was 22,991 tonnes from a planted area of 70,319 hectares resulting in a yield of 0.3 t/ha. Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Maize 38,019 11,561 304 32,300 11,430 354 70,319 22,991 327 Paddy 9,937 2,305 232 18,574 4,756 256 28,511 7,062 248 Sorghum 798 425 533 3,675 855 233 4,473 1,280 286 Finger Millet 30 18 618 71 4 59 101 23 227 Bulrush Millet 41 2 50 0 0 0 41 2 50 Total 48,825 14,312 54,620 17,046 103,446 31,358 Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 25,000 50,000 75,000 Maize Paddy Sorghum Finger Millet Bulrush Millet Crop Area Planted (ha) 0.00 0.50 1.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 90 5,215 6,472 8,413 12,653 37,477 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Bagamoyo Rufiji Mkuranga Kisarawe Kibaha Mafia District Area (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Area Planted per Household Area planted (ha) Area planted/hh Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 91% 93% 91% 85% 79% 97% 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 60,763ha 19,284ha 20,920ha 37,566ha 36,033ha 3,106ha 56,000 to 70,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Tanzania Agriculture Sample Census Percent of Utilized Land Area Percent of Utilized Land Area Total Planted Area Total Planted Area Map 3.07 PWANI Utilized Land Area Expressed as a Percent of Available Land by District Map 3.08 PWANI Total Planted Area Annual Crops by District RESULTS 22 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 16,701 9,378 7,863 14,405 18,188 1,606 27 49 38 38 50 52 15,200 to 19,000 11,400 to 15,200 7,600 to 11,400 3,800 to 7,600 0 to 3,800 Mkuranga Rufiji Kisarawe Kibaha Bagamoyo Mafia 14,510 24,499 8,442 9,998 44,590 1,520 38.6 68 40.4 51.8 73.4 49 35,680 to 44,600 26,760 to 35,680 17,840 to 26,760 8,920 to 17,840 0 to 8,920 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Total Planted Area (ha) Total Planted Area Map 3.09 PWANI Area planted and Percentage During the Short Rainy Season by District Map 3.10 PWANI Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Percent of Planted Area Percent of Total Land Planted with Cereals RESULTS 23 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 24 Chart 3.20 indicates maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. With the exception of the year 1997/98 when the production dropped sharply, production of maize increased over the the period 1994/95 to 1999/2000. However, in 2002/2003 the maize production was much lower than that of 1999/2000. The average area planted with maize per household was 0.63 hectares, however it ranged from 0.2 hectares in Mafia district to 0.8 hectares in Bagamoyo district (Map 3.12). Bagamoyo district had the largest area of maize (37,477 ha) followed by Rufiji (12,653 ha), Mkuranga (8,413 ha), Kisarawe (6,472 ha), Kibaha (5,215 ha), and Mafia (90 ha) (Chart 3.21 and Map 3.11). Charts 3.20 and 3.22 show that, whilst the yield of maize dropped over the 8-year period from 1994/95 to 2002/2003, the quantity produced increased and this was due to a large increase in the planted area. The area planted with maize remained almost constant over the period from 1996 to 1998 it increased sharply. However, the general trend of the yield of maize has shown a decline over the period 1996 to 2003 (from 1.3t/ha in 1995 to 0.6 t/ha in 2003) except for a one-year sharp increase from 1997/98 to 1998/99. (Chart 3.22). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Pwani region during the long rainy season was 30,542. This represents 18 percent of the total crop growing households in Pwani region in the long rainy season. The total production of paddy was 7,062 tonnes from a planted area of 28,511 hectares resulting in a yield of 0.25 t/ha. The district with the largest area planted with paddy was Rufiji (10,516 ha) followed by Mkuranga (5,837 ha), Bagamoyo (5,226 ha), Kibaha (3,794 ha) Kisarawe (1,707 ha), and Mafia (1,431 ha). (Map 3.13). There are small insignificant variations in the average area planted per crop growing household among the districts ranging from 0.44 ha in Mafia to 0.69 ha in Kibaha (Chart 3.23 and Map 3.14). Chart 3.22 Time Series of Maize Planted Area & Yield -PWANI 0 25000 50000 75000 100000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Area Yield Chart 3.20: Time Series Data on Maize Production - PWANI 17 5 23 43 8 39 51 0 25 50 75 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Rufiji Kibaha Bagamoyo Mafia 0.6ha 0.5ha 0.4ha 0.6ha 0.8ha 0.2ha Kisarawe Mkuranga 0.6 > 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 Bagamoyo Kisarawe Kibaha Mkuranga Rufiji Mafia 37,477ha 5,215ha 12,653ha 6,472ha 8,413ha 90ha 0.4t/ha 0.1t/ha 0.4t/ha 0.3t/ha 0.2t/ha 0.5t/ha 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Tanzania Agriculture Sample Census Maize Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.11 PWANI Planted Area and Yield of Maize by District Map 3.12 PWANI Area Planted per Maize Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 25 Rufiji Kisarawe Kibaha Bagamoyo Mafia 0.6ha 0.5ha 0.5ha 0.7ha 0.6ha 0.4ha Mkuranga 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 5,226ha 3,794ha 1,707ha 5,837ha 10,516ha 1,431ha 0.1t/ha 0.1t/ha 0.4t/ha 0.2t/ha 0.4t/ha 0.5t/ha 8,480 to 10,600 6,360 to 8,480 4,240 to 6,360 2,120 to 4,240 0 to 2,120 Tanzania Agriculture Sample Census Paddy Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.13 PWANI Planted Area and Yield of Paddy by District Map 3.14 PWANI Area Planted per Paddy Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 26 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 There was a sharp rise in the production of paddy in 1995/96 compared to 1994/95. The production rose from 3,000 tonnes in 1994/95 to 34,000 tonnes in 1995/96 after which it dropped to 16,000 tonnes in 1996/97 and to 12,000 tonnes in the following year. Thereafter the yield increased gradually to 32,000 tonnes in 1999/2000 and this was followed by another decline in 2002/03 to 7,000 tonnes. Charts 3.23 and 3.25 show that, whilst the yield of paddy dropped dramatically over the 8-year period (1994/95 to 2002/2003), the quantity produced increased and this was due to a large increase in the planted area. The time series chart of paddy shows that the area planted with paddy remained constant over the period from 1995/96 to 1996/97 after which the area under production increased rapidly till year 1999/2000 then declined to 28,511 ha in 2003. The chart also shows that there was a general decline in yield over the period 1996 to 2003 (down to 0.7 t/ha) except for a one-year sharp increase from 1997/98 to 1998/99. (Chart 3.25). 3.3.4.3 Other Cereals Other cereals were produced in small quantities. A small quantity of sorghum was produced in Bagamoyo (1887 ha), Rufiji (1,114), Kibaha (962 ha), Kisarawe (263 ha) and Mkuranga (247 ha). fingermillet was produced in Rufiji district only (101 ha) and bulrush millet was produced in Kibaha and Mkuranga districts (28 ha and 14 ha respectively) (Chart 3.26). Chart 3.23 Total Planted Area and Area of Paddy per Household by District 1,431 1,707 3,794 5,226 5,837 10,516 0 2,000 4,000 6,000 8,000 10,000 12,000 Rufiji Mkuranga Bagamoyo Kibaha Kisarawe Mafia District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Area planted per household Area Planted (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - PWANI 32 16 12 30 7 3 34 0 10 20 30 40 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.25 Time Series of Paddy Planted Area and Yield - PWANI 0 10000 20000 30000 40000 50000 60000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 Yield (t/ha) Planted Area Yield 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 Area (Ha) Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.26 Area Planted with Sorghum, Bulrush millet and Finger Millet by District Sorghum Bulrush Millet Finger Millet RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 72,661 tonnes. Cassava production was the highest with a total production of 71,190 tonnes representing 98 percent of the total root and tuber crops production. This was followed by sweet potatoes with 1,408 tonnes (1.9%), Irish potatoes (41t, 0.1%) and yams (22t, 0.03%). (Table 3.3). The area planted with cassava was larger than any other root and tuber crops and it was the most important crop in Pwani in terms of planted area (27.7% of the total area planted with annual crops and vegetables) and it accounted for 96.3 percent of the area planted with roots and tubers, followed by sweet potatoes (3.5%), yams (0.1%), and Irish potatoes (0.05%). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava is reported under the long rainy season. However, excluding cassava, 0.3 percent of the area planted with roots and tubers was during the short rainy season with sweet potatoes having 99 percent of its production in the short rainy season. While a very low percent of yams (1%) was produced during the short rainy season, a slightly higher percentage of Irish potatoes (1.8%) was produced during the long rainy season. The percentage of yams produced during the long rainy season was estimated at 4.6 percent. There was a significant increase in area planted with cassava and sweet potatoes from 1994/95 to 2002/03. The areas for Irish potato and yams were insignificant. The estimated yield was highest for Irish potatoes (1.71t/ha) and cassava (1.45 t/ha), followed by sweet potatoes (0.8 t/ha) and yams (0.32 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 74,449. This represents 53 percent of the total crop growing households in the region. The total production of cassava during the census year was 71,190 tonnes from a planted area of 49,270 hectares resulting in a yield of 1.4 t/ha. Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 4970 4837 973 44301 66353 1498 49270 71190 1445 Sweet Potatoes 521 637 1223 1275 771 605 1796 1408 784 Irish Potatoes 0 0 0 24 41 1688 24 41 1708 Yams 5 22 4199 62 0 0 67 22 328 TOTAL 5,496 5,496 45,662 67,165 51,158 72,661 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10000 20000 30000 40000 50000 60000 Cassava Sweet Potatoes Irish Potatoes Yams Crop Area Planted (ha) 0 1000 2000 Yield (kg/ha) Yield (kg/ha) Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 10,000 20,000 30,000 40,000 50,000 60,000 1994/95 1995/ 96 1998/ 99 2002/ 03 Ye ar Cassava RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 Previous censuses and surveys indicate that the area planted with cassava increased over the period 1996 to 1999. Since 1999 the area planted with cassava dropped from 54,196 ha to 49,270 ha (Chart 3.28). The area planted with cassava accounted for 27.7 percent of the total area planted with annual crops and vegetables in the census year. Mkuranga district had the largest planted area for cassava (17,569 ha, 36% of the cassava planted area in the region), followed by Rufiji (9761 ha, 20%), Kisarawe (9411 ha, 19%), Bagamoyo (6199 ha, 13%), Kibaha (5314 ha, 11%) and Mafia (1,015 ha, 2%) (Map 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Mkuranga district (46.8%). This was followed by Kisarawe (45%), Mafia (32.7%), Kibaha (27.6%), Rufiji (27.1%) and Bagamoyo (10.2%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.7 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Rufiji (0.8 ha). This was followed by Mkuranga (0.7 ha), Kisarawe (0.6 ha), Kibaha (0.6 ha), Bagamoyo (0.5 ha) and Mafia (0.4 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Pwani region was 4,872 (1,835 in the short rainy season and 3,036 in the long rainy season). This was 7.1 percent of the total root and tuber crop growing households during the long rainy season. The total production of sweet potatoes during the census year was 1,408 tonnes from a planted area of 1,796 hectares resulting in a yield of 0.8t/ha. Kibaha district has the largest planted area for sweet potatoes (553 ha, 30.8%), followed by Mkuranga (488 ha, 27.2%), Bagamoyo (430 ha, 24%), Mafia (145 ha, 8.1%), Kisarawe (133 ha, 7.4%) and Rufiji (47 ha, 2.6%) (Chart 3.31). Other root and tuber crops were of minor importance in terms of area planted compared to cassava and sweet potatoes. Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 35.7 19.8 19.1 12.6 10.8 2.1 0 5 10 15 20 25 30 35 40 Mkuranga Rufiji Kisarawe Bagamoyo Kibaha Mafia District Percent of Total Area Planted 0 10 20 30 40 50 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.81 0.73 0.63 0.62 0.52 0.35 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Area per Household Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.31 Total Area Planted with Sweet Potatoes and Planted Area per Household by District 47 133 145 430 488 553 0 100 200 300 400 500 600 Kibaha Mkuranga Bagamoyo Mafia Kisarawe Rufiji District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area Planted per Household Planted Area (ha) Area per hh Mkuranga Rufiji Kisarawe Kibaha Bagamoyo Mafia 0.7ha 0.8ha 0.6 0.6ha 0.5ha 0.4ha 0.72 to 0.8 0.64 to 0.72 0.56 to 0.64 0.48 to 0.56 0.4 to 0.48 Bagamoyo Kibaha Kisarawe Rufiji Mafia Mkuranga 6,199ha 5,314ha 9,411ha 17,569ha 9,761ha 1,015ha 1.4t/ha 0.9t/ha 2.4t/ha 1t/ha 1.8t/ha 1.2t/ha 14,400 to 18,000 10,800 to 14,400 7,200 to 10,800 3,600 to 7,200 0 to 3,600 Tanzania Agriculture Sample Census Cassava Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.15 PWANI Planted Area and Yield of Cassava by District Map 3.16 PWANI Area Planted per Cassava Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 30 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 31 3.3.6 Pulse Crops Production The total area planted with pulses was 17,552 hectares out of which 16,223 ha were planted with cowpeas (92.4 percent of the total area planted with pulses), followed by green gram (1,265 ha, 7.2%), beans (18 ha, 0.1%), mung beans (16 ha, 0.1%) and bambaranuts (15 ha, 0.1%). Field peas crop was not cultivated in the region. The area planted with pulses in the short rainy season was 12,039 ha which represented 68.6 percent of total area planted with pulses during the year. Cowpeas was the most dominant crop during long rainy season with 5,167 ha (93.7 % of the total area planted with pulses in that particular season), followed only by green gram (345 ha, 6.3%). Other pulses were not grown during the long rainy season. The total production of pulses was 2,299 tonnes. Cowpeas were the most cultivated crop producing 2,208 tonnes which accounted for 96 percent of the total pulse production. Hence almost all pulses were cowpeas. This was followed by green gram (84t, 3.7%), beans (3t, 0.1%), chick peas (2t, 0.1%) and bambaranuts (1t, 0.06%). Chick peas and beans had relatively higher yields of 247 and 171 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were cowpeas 136 kgs/ha, bambaranuts 89 kgs/ha and green gram 67 kgs/ha. Although mung beans and pigeon peas had areas planted, no harvests were recorded. (Chart 3.32). 3.3.6.1 Cowpeas Cowpeas dominate the production of pulse crops in the region. The number of households growing cowpeas in Pwani region was 54,072. The total production of cowpeas in the region was 2,208 tonnes from a planted area of 16,223 hectares resulting in a yield of 0.1 t/ha. Table 3.4: Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 171 Cowpeas 11,056 1,681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick peas 10 2 247 0 0 0 10 2 247 Bambaranuts 15 1 89 0 0 0 15 1 89 TOTAL 12,039 1,747 5,513 552 17,552 2,299 Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Cowpeas Green Gram Beans Mung Beans Bambaranuts Chich Peas Pigeon Peas Crop Area Planted (ha) 0 50 100 150 200 250 300 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Cowpeas Planted Area and Percent of Total Land with Cowpeas by District 0 5 10 15 20 25 30 35 40 45 Bagamoyo Mkuranga Kisarawe Kibaha Rufiji Mafia District Percent of Land 0 2 4 6 8 10 12 14 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.55 0.48 0.38 0.29 0.24 0.18 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area per Household Rufiji Mkuranga Bagamoyo Kibaha Kisarawe Mafia District Chart 3.34 Area Planted per Cowpeas Growing Household by District (Long Rainy Season Only) RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 32 The largest area planted with cowpeas in the region was in Bagamoyo (6,622 ha, 40.8%) (Chart 3.33 and Map 3.17), however, the largest area planted with cowpeas per household was in Bagamoyo district (0.3 ha). The average area planted per household in the region during the long rainy season was 0.35 ha (Chart 3.34). With exception of Bagamoyo district, the variations in area planted with cowpeas for the rest of the districts were small ranging from 0.13 ha in Mafia district to 0.32 ha in Kibaha district (Map 3.18). In Pwani region, almost all pulses (96%) are cowpeas hence in these charts the time series data for cowpeas are represented by the time series for pulses which are available over a range of years. Other types of pulses are insignificant both in planted area and production rendering cowpeas highly significant for pulses over same range of years. Cowpeas (pulses) production increased rapidly over the period 1996 to 1999 from 800 tonnes in 1996 to 34,700 tonnes in 1999, then dropped drastically to about 2,200 tons in 2003. (Chart 3.35). Charts 3.35 and 3.36 show that within the period of those 7 years, the trend for yield of cowpeas was similar to that of production trend but was dropping gradually from its peak of 1.3t/ha in 1998 to 1t/ha in 2003. The quantity produced decreased due to a decrease in the area under production. (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 448 tonnes planted on an area of 2,920 hectares.. The total planted area of oilseeds in the long rainy season was 2,552 ha representing 87.4 percent of the total area planted with oil seeds. Simsim was the most important oilseed crop with 2,552 ha (87.4% of the total area planted with oil seeds), followed by groundnuts 11.7%), sunflower (0.7%) and soya beans (0.2%) (Chart 3.37). The yield of sunflower was moderate (449 kg/ha). Groundnuts had a yield of 316 kg/ha and simsim 129 kg/ha. In terms of production, simsim was 330 tonnes and accounted for 73.7 percent of the total production of oil seeds, followed by groundnuts (24%), sunflower (2%) and none for soya beans. Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 21 10 0 21 10 476 Simsim 166 18 109 2,386 312 0 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Total 368 113 2,552 335 2,920 448 Chart 3.35: Time Series Data on Cowpeas Production - PWANI 10.6 0.8 2.2 23 34.7 0 10 20 30 40 1996/97 1997/1998 1998/99 1999/00 2002/03 Year Production ('000') tons Chart 3.36 Time Series of Cowpeas Planted Area & Yield - PWANI 0 10 20 30 40 50 60 1996/97 1997/1998 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.3 0.6 0.9 Yield (t/ha) Area Yield Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 500 1,000 1,500 2,000 2,500 3,000 Simsim Groundnuts Sunflower Crop Area Planted (ha) 0 100 200 300 400 500 Yield (kg/ha) Yield (kg/ha) Bagamoyo Kibaha Mkuranga Kisarawe Rufiji Mafia 0ha 0.2ha 0ha 0.1ha 0ha 0ha 0.16 to 0.2 0.12 to 0.16 0.08 to 0.12 0.04 to 0.08 0 to 0.04 Rufiji Kisarawe Mkuranga Kibaha Bagamoyo Mafia 0ha 4ha 0ha 12ha 2ha 0ha 0t/ha 0t/ha 0t/ha 0.2t/ha 0.6t/ha 0t/ha 8 to 12 6 to 8 4 to 6 2 to 4 0 to 2 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.17 PWANI Planted Area and Yield of Beans by District Map 3.18 PWANI Area Planted per Beans Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 33 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 3.3.7.1 Groundnuts Groundnuts was the second most important oilseed crop in Pwani region. The number of households growing groundnuts was only 1,557. The total production of groundnuts in the region was 108 tonnes from a planted area of 342 hectares resulting in a yield of 0.3 t/ha. There has been a moderate increase in production of groundnuts over the period 1996 to 2003, from 105.5 tonnes in 1996/97 to 108.04 tonnes in 2002/03. (Chart 3.38). Thirty eight percent of the area planted with groundnuts was located in Kisarawe district (130 ha, 38%) followed by Mkuranga (122 ha, 35.7%), Kibaha (43 ha, 12.5%), Bagamoyo (26 ha, 7.7%), Rufiji (16 ha, 4.7%) and Mafia (5 ha, 1.3%). (Map 3.19). The highest proportion of land with groundnuts was found in Kisarawe followed by Mkuranga, Kibaha, Mafia, Rufiji and Bagamoyo (Chart 3.39 and Map 3.20). The largest area planted per groundnut growing household was found in Mkuranga district (0.4 ha) and the lowest was in Bagamoyo (0.1). In Kibaha no groundnuts were grown in the long rainy season; otherwise, the range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruits and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short rainy season is relatively important for fruit and vegetables production since 52.7 percent of the total area planted with fruit and vegetables was during the short rainy season. For chillies, onions, spinnach, okra, amaranths, cucumber and water melon Chart 3.38 Time Series Data on Groundnut Production - PWANI 0 108.04 0 105.5 0 500 1994/95 1996/97 1998/99 2002/03 Year Production ( tonnes) Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 Kisarawe Mkuranga Kibaha Bagamoyo Rufiji Mafia District Percent of Land 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 Area per Household (ha) Mkuranga Kisarawe Rufiji Mafia Bagamoyo Kibaha District Chart 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 100 200 300 400 500 600 700 800 900 1,000 Tomatoes Water Mellon Pumpkins Okra Amaranths Radish Cucumber Others Crop A rea Planted (ha) 0 1000 2000 3000 4000 Y ield (kg/ha) Rufiji Kisarawe Kibaha Mafia 0.2ha 0.2ha 0.2ha 0.1ha 0.2ha 0.3ha Mkuranga Bagamoyo 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 Rufiji Mkuranga Mafia Kibaha Bagamoyo 16ha 122ha 130ha 43ha 26ha 5ha 0t/ha 0.3t/ha 0.1t/ha 0.7t/ha 0.9t/ha 0.5t/ha Kisarawe 104 to 130 78 to 104 52 to 78 26 to 52 0 to 26 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.19 PWANI Planted Area and Yield of Groundnuts by District Map 3.20 PWANI Area Planted per Groundnuts Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 35 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 over 60 percent of the planted area of each crop was during the short rainy season. The planted areas for radish and egg plant in the long rainy season were abnormally large (100% of the total planted area was in the long rainy season). Reliable historical data for time series analysis of fruit and vegetables were not available. The total production of fruits and vegetables was 3,682 tonnes. The most cultivated fruit and vegetable crop was the tomato with a production of 1,944 tonnes (53% of the total fruit and vegetables produced) followed by water melon (1,124t, 31%) pumpkins (225t, 5%) and amaranths (115t, 3%). The production of the other fruits and vegetables crops was relatively small. (Table 3.6). The yield of water melon was 3,787 kg/ha, egg plant (3,073 kg/ha), tomatoes (2,172 kg/ha), okra (852 kg/ha), cucumber (989 kg/ha) and spinnach (218 kg/ha). (Chart 3.42). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 1,486 and 1,815 households in the short rainy season. This represented 2.1 percent of the total crop growing households in the region during the long rainy season and 1.9 percent during the short rainy season. Kibaha district had the largest planted area for tomatoes (51.2% of the total area planted with tomatoes in the region), followed by Mkuranga (26.4%), Bagamoyo (8.9%), Kisarawe (7.1%), Mafia (3.5%) and Rufiji (2.8%) (Map 3.21). The highest proportion of land with tomatoes was in Kibaha, followed by Mkuranga district. The rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Kibaha district (0.43 ha) followed by Kisarawe (0.23 ha), Mkuranga (0.19 ha), Mafia (0.14 ha), Rufiji (0.10 ha) and none for Bagamoyo. (Chart 3.44 and Map 3.22). The total area planted with Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 98 35 353 28 73 2,585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Onions 22 15 697 2 4 1,976 24 19 800 Cabbage 13 0 0 13 19 1,506 26 19 729 Tomatoes 404 840 2,077 491 1,104 2,250 895 1,944 2,172 Spinnach 24 2 93 6 4 726 30 6 218 Chillies 6 1 222 0 0 0 6 1 222 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1,328 264 225 853 Cucumber 57 45 794 29 39 1,378 86 85 989 Egg Plant 0 0 0 12 37 3,073 12 37 3,073 Water Mellon 183 921 5027 114 203 1,785 297 1,124 3,787 Total 1,046 2,019 940 1,664 1,987 3,682 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Kibaha Mkuranga Bagamoyo Kisarawe Mafia Rufiji District Percent of Land 0.00 0.50 1.00 1.50 2.00 2.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 0.50 Area per Household (ha Kibaha Kisarawe Mkuranga Mafia Rufiji Bagamoyo District Chart 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season) Kibaha Rufiji Mafia 0.2ha 0.4ha 0.2ha 0.2ha 0.1ha 0.2ha Kisarawe Mkuranga Bagamoyo 0.34 to 0.4 0.28 to 0.34 0.22 to 0.28 0.16 to 0.22 0.1 to 0.16 Mafia Kibaha Kisarawe 31ha 80ha 458ha 237ha 64ha 25ha 2t/ha 1.4t/ha 2.4t/ha 1.5t/ha 3.8t/ha 2t/ha Rufiji Mkuranga Bagamoyo 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.21 PWANI Planted Area and Yield of Tomatoes by District Map 3.22 PWANI Area Planted per Tomatoes Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 37 RESULTS – Annual Crop and Vegetable Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 tomatoes accounted for 0.5 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.2 Water Mellon The number of households growing water mellon in the region during the long rainy season was 246 and 794 in the short rainy season. This represented 0.35 percent of the total crop growing households in the region in the long rainy season and 0.84 percent in the short rainy season. Mkuranga district had the largest planted area for water mellon (242 ha, 81.5% of the total area planted with water mellon in the region), followed by Kisarawe (27 ha, 9.1%), Bagamoyo (20 ha, 6.7%), Kibaha (8 ha, 2.7%) and none for Rufiji and Mafia (Chart 3.45). The total area planted with water mellon accounted for 0.17 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Pumpkins The number of households growing pumpkins in the region during the long rainy season was 436 households and 1,007 in the short rainy season. This represents 0.62 percent of the total crop growing households in the region in the long rainy season and 1.05 percent in the short rainy season. Mkuranga district had the largest planted area for pumpkins (179 ha, 67.8% of the total area planted with pumpkins in the region), followed by Kibaha (30 ha, 11.4%), Rufiji (29 ha, 11%), Kisarawe (17ha, 6.4%) and Bagamoyo (9 ha, 3.4%) districts. Pumpkins were not produced in Mafia district. The largest proportion of the area planted with pumpkins was found in Mkuranga district (0.24%), followed by Kibaha (0.08%), Rufiji (0.05%), Kisarawe (0.03%) and Bagamoyo (0.01) (Chart 3.46). The total area planted with pumpkins accounted for 0.15 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 171 180 1,055 183 188 0 354 368 1,039 Cotton 82 0 0 59 117 1,976 141 117 832 TOTAL 252 180 243 305 495 485 Chart 3.45 Percent of Water mellon Planted Area and Percent of Total Land with Water mellon by District 0.0 25.0 50.0 75.0 100.0 Mkuranga Kisarawe Bagamoyo Kibaha Rufiji Mafia District Percent of Land 0.00 0.20 0.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Pumpkins Planted Area and Percent of Total Land with Pumpkins by District 0.0 20.0 40.0 60.0 80.0 Mkuranga Kibaha Rufiji Kisarawe Bagamoyo Mafia District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 39 3.3.9 Other Annual Crops Production Most of the other annual crops are cash crops. An area of 495ha was planted with other annual crops and seaweed was the most prominent crop followed by cotton. The area planted with annual cash crops in short rainy season was 252 ha which represented 50.9 percent of the total area planted with other annual cash crops in short and long rainy season. 3.3.9.1 Cotton Only 117 tonnes of cotton were produced in Pwani Region on a planted area of 141 ha. All production was during the long rainy season only. The crop was grown in Bagamoyo district only (Map 3.23) and an average of 0.5 ha was grown per household (Map 3.24). 3.3.9.2 Seaweed The quantity of seaweed produced was 368 tonnes. Seaweed had a planted area of 354 ha, most of which was planted in the long rainy season. Seaweed production was concentrated in 2 districts only, with Mafia having the largest planted area (72% of total area planted with seaweed in the region), followed by Bagamoyo (28%). (Chart 3.48) (Map 3.29 and 3.30). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 82,031 hectares (32% of the total area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area planted if crops planted more than once on it, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops could be higher than indicated in Chart 3.49. Chart 3.47 Area planted with Annual Cash Crops Seaweed, 354, 72% Cotton, 141, 28% Chart 3.48 Percent of Seaweed Planted Area and Percent of Total Land with Seaweed by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Mafia Bagamoyo Kibaha Kisarawe Mkuranga Rufiji District Percent of Land 0.00 2.00 4.00 6.00 8.00 10.00 12.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted for Annual and Permanent Crops Annual , 177,672, 68% Permanent , 82,031 32% Rufiji Mkuranga Kisarawe Kibaha Mafia 0ha 0ha 0ha 0ha 0.5ha 0ha Bagamoyo 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Kisarawe Mkuranga Rufiji Mafia Bagamoyo Kibaha 0ha 0ha 0ha 0ha 141ha 0ha 0t/ha 0t/ha 0t/ha 0t/ha 0.8t/ha 0t/ha 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.23 PWANI Planted Area and Yield of Cotton by District Map 3.24 PWANI Area Planted per Cotton Growing Household by District Yield (t/ha) Planted Area Per Household RESULTS 40 RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 The most important permanent crop in Pwani region is the cashewnut which had a planted area of 42,263 ha, (51.5% of the planted area of all permanent crops) followed by coconuts (17,300 ha, 21.1%), oranges (7,635 ha, 9.3%), pineapples (3,628 ha, 4.4%), banana (3,538 ha, 4.3%) and mango 2,244 ha, 2.7%). Each of the remaining permanent crops had an area of less than 2 percent of the total area planted with permanent crops (Chart 3.50). Mkuranga district had the largest area under smallholder permanent crops (29,168 ha, 36%). This is followed by Bagamoyo (15,810 ha, 19%), Rufiji (15,378 ha, 19%), Kisarawe (10,389 ha, 13%), Mafia (6,390 ha, 8%) and Kibaha (4,896 ha, 6%). However, Mafia had the largest area per permanent crop growing household (1.3 ha) followed by Kibaha (1.1 ha), Bagamoyo (0.9 ha), Rufiji (0.8 ha), Mkuranga (0.7 ha) and Kisarawe (0.4 ha) (Chart 3.51). 3.4.1 Cashewnuts The total production of cashewnuts by smallholders was 12,711 tonnes. In terms of area planted, cashewnuts was the most important permanent crop grown by smallholders in the region. They were grown by 40,199 households (28.8% of the total crop growing households). The average area planted with cashewnuts per household was relatively small at around 1.05 ha per cashewnut growing household and the average yield obtained by smallholders was 416 kg/ha from a harvest area of 30,529 hectares. Mkuranga had the largest area of cashewnuts in the region (19,636 ha, 46.5%) followed by Rufiji (10,591 ha, 25.1%), Bagamoyo (6,214 ha, 14.7%), Kisarawe (3,541 ha, 8.4%), Kibaha (2,062 ha, 4.9%) and Mafia (220 ha, 0.5%). (Map 3.25). However, the average area planted with cashew nuts per cashew nut growing household was highest in Bagamoyo (1.5 ha) followed by Rufiji (1.2 ha), Mkuranga (1.1 ha), Kibaha (0.7 ha) and Mafia (0.4 ha) (Chart 3.52 and Map 3.26). Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 19.3 18.7 12.7 7.8 6.0 35.6 0.0 10.0 20.0 30.0 40.0 Mkuranga Bagamoyo Rufiji Kisarawe Mafia Kibaha District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.50 Area Planted with the Main Perennial Crops Other, 511, 1% Pawpaw, 497, 0.6% Pigeon Pea, 1,513, 1.8% Manderine/Tangeri ne 1,395, 1.7% Mpesheni, 165, 0.2% Coconut, 17,300, 21.1% Lime/Lemon, 192, 0.2% Pineapple, 3,628, 4.4% Banana, 3,538, 4.3% Orange, 7,635, 9.3% Mango, 2,244, 2.7% Cashewnut, 42,263, 51.5% Jack Fruit, 1,149, 1.4% Chart 3.52 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.5 25.1 8.4 46.5 4.9 14.7 0.0 20.0 40.0 60.0 Mkuranga Rufiji Bagamoyo Kisarawe Kibaha Mafia District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 1.3 1.5 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 1.2ha 1.1ha 0.6ha 0.7ha 1.5ha 0.4ha 1.2 > 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 Mafia Rufiji Mkuranga Kisarawe Kibaha Bagamoyo 220ha 10,591ha 19,636ha 3,541ha 2,062ha 6,214ha 0.5t/ha 0.2t/ha 0.3t/ha 0.4t/ha 0.6t/hs 0.2t/ha 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area(ha) Planted Area(ha) Map 3.25 PWANI Planted Area and Yield of Cashewnut by District Yield (t/ha) Tanzania Agriculture Sample Census Area Planted Per Household Map 3.26 PWANI Area Planted per Cashewnut Growing Household by District Planted Area Per Household RESULTS 42 RESULTS – Input/Implement Use _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 3.4.2 Coconuts The total production of coconuts by smallholders was 30,732 tonnes. In terms of area planted, the coconut was the second most important permanent crop grown by smallholders in the region. It was grown by 24,094 households (17.3% of the total crop growing households). The average area planted with coconuts per household was relatively small at around 0.72 ha per coconut growing household and the average yield obtained by smallholders was 2,333 kg/ha from a harvest area of 13,171 hectares. Mafia had the largest area of coconuts in the region (4778 ha, 27.6%) followed by Mkuranga (4569 ha, 26.4%), Bagamoyo (3155 ha, 18.2%), Rufiji (1906 ha, 11%), Kisarawe (1575 ha, 9.1%) and Kibaha (1317 ha, 7.6%) (Map 3.28). However, the average area planted with coconuts per coconut planting household was highest in Kibaha (2.08 ha) followed by Mafia (1.34 ha), Bagamoyo (0.96 ha), Rufiji (0.78 ha), Mkuranga (0.52 ha) and Kisarawe (0.3 ha) (Chart 3.53 and Map 3.28). 3.4.3 Oranges The total production of oranges by smallholders was 18,807 tonnes. In terms of area planted, oranges were the third most important permanent crops grown by smallholders in the region. They were grown by 15,006 households (10.8% of the total crop growing households). The average area planted with oranges per household was 0.51 ha per orange growing household and the average yield obtained by smallholders was 5,266 kg/ha from a harvested area of 3,571 hectares. Bagamoyo had the largest planted area of oranges in the region (2,001 ha, 26.1%) followed by Kisarawe (1,937 ha, 25.4%), Rufiji (1,294 ha, 17%), Kibaha (1,201 ha, 15.7%), Mkuranga (1,162 ha, 15.2%) and Mafia (40 ha, 0.5%) (Map 3.29). However, the area planted with oranges per orange growing household was highest in Kibaha (6.58 ha), followed by Bagamoyo (0.96 ha), Rufiji (0.53 ha), Kisarawe (0.31 ha), Mkuranga (0.3 ha) and Mafia (0.2 ha) (Chart 3.54 and Map 3.30). 3.4.4 Pineapples The total production of pineapples by smallholders was 9,419 tonnes. In terms of area planted, pineapples were the fourth most important permanent crop grown by smallholders in the region. They were grown by 5,370 households (3.9% of the total crop growing households). The average area planted with pineapples per household was relatively small at around 0.68 ha per pineapples growing household and the average yield obtained by smallholders was 4,498 kg /ha from a harvest area of 2,094 hectares. Chart 3.53 Percent of Area Planted with Coconuts and Average Planted Area per Household by District 9.1 7.6 18.2 26.4 11.0 27.6 0.0 20.0 40.0 Mafia Mkuranga Bagamoyo Rufiji Kisarawe Kibaha District % of Total Area Planted -0.05 0.20 0.45 0.70 0.95 1.20 1.45 1.70 1.95 2.20 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.54 Percent of Area Planted with Oranges and Average Planted Area per Household by District 0.53 16.94 15.22 26.21 15.73 25.36 0.00 10.00 20.00 30.00 Bagamoyo Kisarawe Rufiji Kibaha Mkuranga Mafia District % of Total Area Planted 0.00 2.00 4.00 6.00 8.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 1ha 2.1ha 0.3ha 0.5ha 0.8ha 1.3ha 1.9 to 2.3 1.5 to 1.9 1.1 to 1.5 0.7 to 1.1 0.3 to 0.7 Kibaha Kisarawe Mkuranga Rufiji Bagamoyo Mafia 1,317ha 1,575ha 4,569ha 1,906ha 3,155ha 4,778ha 0.7t/ha 1.5t/ha 2.2t/ha 1.1t/ha 1.5t/ha 2.2t/ha 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.27 PWANI Planted Area and Yield of Coconuts by District Map 3.28 PWANI Area Planted per Coconut Growing Household by District Yield (t/ha) Planted Area Per Household (ha) RESULTS 44 Kisarawe Bagamoyo Kibaha Rufiji Mkuranga Mafia 0.3ha 1ha 6.6ha 0.5ha 0.3ha 0.2ha Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia 2,001ha 1,201ha 1,937ha 1,162ha 1,294ha 40ha 1.1t/ha 0.8t/ha 3.9t/ha 1.1t/ha 4.4t/ha 33t/ha Tanzania Agriculture Sample Census Planted Area(ha) Planted Area(ha) Area Planted Per Household Map 3.29 PWANI Planted Area and Yield of Oranges by District Map 3.30 PWANI Area Planted per Oranges Growing Household by District Yield (t/ha) Planted Area Per Household 2,000 to 2,500 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 5.4 to 6.7 4.1 to 5.4 2.8 to 4.1 1.5 to 2.8 0.2 to 1.5 RESULTS 45 RESULTS – Input/Implement Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 Bagamoyo has the largest area of pineapples in the region (1,762 ha, 48.6%) followed by Mkuranga (906 ha, 25%), Rufiji (533 ha, 14.7%), Mafia (372 ha, 10.3%), Kibaha (31 ha, 0.9%) and Kisarawe (23 ha, 0.6%) (Map 3.37). However, the average area planted per pineapple growing household was highest in Mafia (6.25 ha), followed by Bagamoyo (1.19 ha), Kisarawe (0.49 ha), Mkuranga (0.41 ha), Kibaha (0.39 ha), and Rufiji (0.36 ha), (Chart 3.55 and Map 3.38). Although Kisarawe had a planted area of 23 ha, the district reported no pineapples production. 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period, while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region during the long rainy season was 61,869 ha which represented 92.1 percent of the total planted area. Bush clearance, tractor slashing and burning are less important methods for land clearing and they represent 7.9 percent in total. (Table3.8). 3.5.2 Methods of Soil Preparation Hand cultivation is mostly used for soil preparation as it was used in an area of 128,353 ha which represented 95 percent of the total planted area, followed by ox-ploughing (4,137 ha, 3%) and tractor ploughing (3,132 ha, 2%). (Chart 3.57). Table 3.8: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 64,915 61,869 92 90,001 64,224 95 154,916 126,093 93 Mostly Bush Clearance 2,929 2,533 4 4,074 2,690 4 7,003 5,223 4 No Land Clearing 1,275 1,123 2 641 352 1 1,916 1,475 1 Mostly Tractor Slashing 458 731 1 154 71 0 612 802 1 Mostly Burning 410 928 1 986 531 1 1,396 1,460 1 Other 0 0 0 142 69 0 142 69 0 Total 69,986 67,185 100.0 95,998 67,937 100 165,985 135,122 100 Chart 3.55 Percent of Area Planted with Pineapples and Average Planted Area per Household by District 0.6 25.0 10.3 48.6 0.9 14.7 0.0 10.0 20.0 30.0 40.0 50.0 Bagamoyo Mkuranga Rufiji Mafia Kibaha Kisarawe District % of Total Area Planted 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 64,915 2,929 1,275 458 410 0 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Mostly Hand Slashing Mostly Bush Clearance No Land Clearing Mostly Tractor Slashing Mostly Burning Other Method of Land Clearing Number of Households Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 4,137, 3% Mostly Hand Hoe Ploughing, 128,353, 95% Mostly Tractor Ploughing, 3,132, 2% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 More hand cultivation was used during short rainy season at 96 percent against 94 percent for the long rainy season, whereas, oxen and tractor ploughing in the long rainy season were 3.4 percent and 3.0 percent respectively. For the short rainy season the corresponding percentages were 2.7 and 1.6 respectively. In Pwani region, Kibaha district had the largest planted area cultivated with oxen (1,157 hectares, 28%) followed by Bagamoyo (1,149 ha, 27.8%), Rufiji (1,099 ha, 26.6%), Kisarawe (336 ha, 8.1%), Mkuranga (333 ha, 8.0%) and Mafia (64 ha, 1.6%). During the long rainy season, 2.4 percent of the total area cultivated by using oxen was planted with cereals followed by roots and tubers (0.3%), pulses (0.3%), oil seeds (0.3%), fruit and vegetables (0%) and cash crops (0%). 3.5.3 Improved Seeds Use The planted area using improved seeds was estimated at 15,403 ha which represents 12 percent of the total planted with the annual crops and vegetables area. Cereals had the largest planted area with improved seeds (14,868 ha, 70% of the planted area with improved seeds) followed by pulses (2,443 ha, 12%), roots and tubers (1,815 ha, 9%), fruit and vegetables (1,345 ha, 6%), Oil seed (380 ha, 2%) and cash crops (374 ha, 2%). (Chart 3.60). However, the use of improved seeds in cash crops and fruit and vegetables is much greater than in other crop types (76% and 68% respectively), only 13 percent of the planted area for oil seed crops used improved seeds (Chart 3.61, Map 3.34). Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 1,815, 9% Pulses, 2,443, 12% Oilseeds , 380, 2% Fruits & Vegetables, 1,345, 6% Cereals, 14,868, 70% Cash Crops, 374, 2% 0 10 20 30 40 50 60 70 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals 0 10,000 20,000 30,000 40,000 50,000 60,000 Area Cultivated Bagamoyo Rufiji Mkuranga Kibaha Kisarawe Mafia District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.59 Planted Area of Improved Seeds - PWANI With Improved Seeds, 15,403 , 12% Without Improved Seeds, 114,829 , 88% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 3.5.4 Fertilizers Use The use of fertilisers on annual crops is very small with a planted area of only 14,284 ha (8% of the total planted area in the region). The planted area without fertiliser for annual crops was 163,388 hectares representing 92 percent of the total planted area with annual crops. Of the planted area with fertiliser application, compost was applied to 8,040 ha which represents 4.5 percent of the total planted area (59.3% of the area planted with fertiliser application in the region). This was followed by farm yard manure (4,669 ha, 2.6%). Inorganic fertilizers were used on a very small area and represented only 0.9 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizers (all types) was in Bagamoyo district (47.8%) followed by Mkuranga (25.4%), Kibaha (11.6%), Kisarawe (7.8%), Mafia (5.6%), and Rufiji (1.8%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 163,888 households, 90%) (Map 3.31). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (53% of the area planted with these fruit and vegetables during the long rainy season had an application of fertilizers). This was followed by cash crops (24%), oil seeds (20.2%), pulses (19.7%) cereals (10%) and roots and tubers (4%) Table3.9 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Bagamoyo 861 5,409 561 6,832 53,931 Kibaha 1,099 362 203 1,664 17,620 Kisarawe 337 706 68 1,112 19,808 Mkuranga 1,732 1,324 565 3,621 33,945 Rufiji 96 131 31 258 35,775 Mafia 543 107 148 797 2,308 Total 4,669 8,040 1,575 14,284 163,388 Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 560 624 2,403 4,105 451 417 29,270 32,856 32,684 44,062 Kibaha 559 670 265 204 106 42 8,090 8,723 9,019 9,905 Kisarawe 95 102 474 263 0 . 5,781 3,364 6,350 13,056 Mkuranga 385 425 834 439 158 98 7,965 4,872 9,342 23,162 Rufiji 0 . 72 52 0 . 10,008 8,782 10,080 17,846 Mafia 541 260 230 84 9 5 2,145 1,093 2,926 1,499 Total 2,141 2,081 4,277 5,147 724 562 63,258 59,691 70,400 109,531 Chart 3.62 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 163,388, 91% Mostly Compost, 8,040, 5% Mostly Inorganic Fertilizer, 1,575, 1% Mostly Farm Yard Manure, 4,669, 3% 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Area (ha) Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Pwani region was 4,810 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 4,690 and it was applied to 2,222 ha representing 2 percent of the total area planted during that season. (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (59%), followed by fruit and vegetables (18%), pulses (14%), roots and tubers (10%). For oil seeds and cash crops it was insignificant. However, fruit and vegetables had the highest percent of the planted area with farm yard manure (43% of the total area of fruit and vegetables in Pwani). This was followed by pulses (4%), cereals (3%), roots and tubers (1%), oil seeds (1%), and none for cash crops. (Chart 3.64 and Chart 3.65a). Farm yard manure is mostly used in Mafia (17.5% of the total planted area in the district), followed by Kibaha (5.7%), Mkuranga (4.6%), Kisarawe (1.6%), Bagamoyo (1.4%) and Rufiji (0.3%). (Chart 3.65b). For permanent crops, most farm yard manure is used for the production of cashew nuts (38.4%), followed by coconuts (32.8%), bananas (9.6%) and pawpaw (7.1%). Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - PWANI Cash Crops, 0, 0% Cereals, 2,817, 58% Fruits & Vegetables, 852, 18% Oilseeds, 21, 0% Pulses, 660, 14% Roots & Tubers, 460, 10% 0 5 10 15 20 25 30 35 40 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - PWANI Pulses, 218, 13.4% Oilseeds, 23, 1.4% Cereals, 1,031, 63.2% Roots & Tubers, 168, 10.3% Fruits & Vegetables, 192, 12.8% Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - PWANI 0.0 5.0 10.0 15.0 20.0 Mafia Kibaha Mkuranga Kisarawe Bagamoyo Rufiji District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Pwani region was 1,632 ha which represents 0.92 percent of the total planted area with annuals in the region and 10.2 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizers on their annual crops during the long rainy season was 1,291 and it was applied to 619 ha representing 1.2 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (63% of the total area applied with inorganic fertilizers), followed by pulses (13%), fruit and vegetables (12%) and roots and tubers (10%) (Chart 3.66). However, the proportion of fruits and vegetables with inorganic fertilizers was 10 percent, higher than other crop types, followed by pulses (1.2%), cereals (1%) and oil seeds (0.8%). (Chart 3.67a). Inorganic fertiliser is mostly used in Mafia (4.8% of the total planted area in the district), followed by Mkuranga (1.5%). Kibaha (1.1%), Bagamoyo (0.9%), Kisarawe (0.3%) and Rufiji (0.1%). (Chart 3.67b). In permanent crops inorganic fertiliser were used on cashew nuts (61%), followed by pineapples (21%), coconuts (13.2%), and pigeon peas (3.6%). 3.5.4.3 Compost Use The total planted area applied with compost was 9,553 ha which represents only 5.4 percent of the total planted area with annual crops in the region and 59.7 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 10,347 and it was applied to 6,660 ha representing 9.4 percent of the total area planted (Table 3.10). The proportion of area applied with compost was low for each type of crop (3 to 18%); however the distribution of the total area using compost manure shows that 59.5 percent of this area was cultivated with cereals, followed by roots & tubers (18.1%), pulses (15.4%), oil seeds (5.6%), fruits and vegetables (0.8%) and cash crops (0.6%). (Chart 3.68b). Compost is mostly used in Bagamoyo (8.9% of the total planted area in the district), and this is closely followed by Mkuranga (3.5%), Mafia (3.5%), Kisarawe (3.4%), Kibaha (1.9%), and Rufiji (0.4%). (Chart 3.68c). 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - PWANI Chart 3.68a Planted Area with Compost by Crop Type - PWANI Roots & Tubers 1,729, 18.1% Cereals, 5,679, 59.1% Fruits & Vegetables, 77, 0.8% Pulses, 1,475, 15.4% Oilseeds, 533, 5.6% Cash Crop, 59, 0.6% Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - PWANI 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Mafia Mkuranga Kibaha Bagamoyo Kisarawe Rufiji District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 In permanent crops, compost was mostly used for the production of cashew nuts (69%) followed by oranges (14.3%), coconuts (9.9%) and mango (2.4%). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 11,840 ha of annual crops and vegetables. Insecticides are the most common pesticides used in the region (44% of the total area applied with pesticides). This was followed by fungicides (33%) and herbicides (23%) (Chart 3.69). 3.5.5.1 Insecticides Use The planted area applied with insecticides represented 3.2 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (3,106 ha, 54% of the total planted area with insecticides) followed by fruit and vegetables (1,123 ha, 19.5%), pulses (791 ha, 13.7%), roots and tubers (658 ha, 11.4%), cash crops (59 ha, 1%) and oil seed (18 ha, 0.3%) (Chart 3.70). However, the percent of insecticides used in fruits and vegetables and 0 2 4 6 8 10 12 14 16 18 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type - PWANI Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 59, 1.0% Cereals, 3,106, 54.0% Fruits & Vegetables, 1,123, 19.5% Oil seeds & Oil nuts, 18, 0.3% Pulses, 791, 13.7% Roots & Tubers, 658 11.4% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.68c Proportion of Planted Area Applied with Compost by District - PWANI 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Bagamoyo Mkuranga Mafia Kisarawe Kibaha Rufiji District Percent Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 3,884, 33% Herbicides, 2,691, 23% Insecticides, 5,265, 44% Tanzania Agriculture Sample Census Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 35,672ha 32,567ha 19,777ha 17,490ha 53,864ha 2,306ha 99% 86.7% 94.5% 90.7% 88.6% 74.3% 44,000 to 55,000 33,000 to 44,000 22,000 to 33,000 11,000 to 22,000 0 to 11,000 Area Planted With no Fertilizer Applied Area Planted With no Fertilizer Applied Map 3.31 PWANI Planted Area and Percent of Planted Area With No Application of Fertilizer by District Percent of Area Planted With no Fertilizer Applied RESULTS 52 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 cash crops is much greater than in other crop types (56.5 and 12% respectively), while only 0.6 percent of oil seed crops were applied with insecticides (Chart 3.71). Although cereals had 54% insecticides use, only maize ranked highest with 36.6%. Hence, there were no annual crops with more than 50 percent insecticides use. Kibaha had the highest percent of planted area with insecticides (5.3% of the total planted area with annual crops in the district). This was closely followed by Mkuranga (3.1%) then Rufiji (3.0%), Bagamoyo (2.5%) and Kisarawe (2.2%). The smallest percentage use was recorded in Mafia district (0.1%) (Chart 3.72). 3.5.5.2 Herbicides Use The planted area applied with herbicides was 3,524 ha which represented 2.0 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (2,049 ha, 58%) followed by roots and tuber (877 ha, 25%), pulses (372 ha, 11%), fruits and vegetables (185 ha, 5%) and oil seed (41 ha, 1%). None for cash crops. (Chart 3.73). However, the percent of herbicides use on fruit and vegetables and pulses was much greater than in other crop types (9.3% and 2.1% respectively) while only 1.4 percent of oil seeds was applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (38%), cassava (25%), paddy (17%), cowpeas (9%), sorghum (4%) and water melon (2%). Rufiji had the highest percent of planted area with herbicides (2.5% of the total planted area with annual crops in the district). This was followed by Mkuranga (1.9%) then Mafia (1.4%), Bagamoyo (1.3%) and Kibaha (1%). The smallest percentage use was recorded in Kisarawe district (0.4%) (Chart 3.75). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Roots & Tubers 877, 25% Pulses, 372, 11% Oil seeds & Oil nuts, 41, 1% Fruits & Vegetables, 185, 5% Cereals, 2,049, 58% Cash crops, 0, 0% 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent of Planted Area Fruits & Vegetables Pulses Cereals Roots & Tubers Oil seeds & Oil nuts Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - PWANI 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Rufiji Mkuranga Mafia Bagamoyo Kibaha Kisarawe District Percent Chart 3.72 Percent of Planted Area Applied with Insecticides by District - PWANI 0.0 2.0 4.0 6.0 Kibaha Mkuranga Rufiji Bagamoyo Kisarawe Mafia District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 3.5.5.3 Fungicides Use The planted area applied with fungicides was 5,039 ha which represented 2.8 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (3.5%) was higher than the corresponding percentage for the long rainy season (2.4%). Cereals had the largest planted area applied with fungicides (2,606ha, 52%) followed by fruits and vegetables (1,062 ha, 21%), pulses (662 ha, 13%), roots and tubers (631 ha, 12.5%), cash crops (59 ha, 1%) and oil seeds (18 ha, 0.4%) (Chart 3.76). However, the percentage use of fungicides in fruits and vegetables and cash crops was much greater than in other crop types (53% and 12% respectively), while only 0.6 percent of oil seeds was applied with fungicides (Chart 3.77). Annual crops with more than 40 percent fungicides use were field peas (100%), tomatoes (81%), cotton (79%), cucumber (78%), Onions (74%), chillies (43%) and egg plants (42%). Mkuranga had the highest percent of planted area with fungicides (3.5% of the total planted area with annual crops in the district). This was closely followed by Kibaha (3.0%) and Rufiji (2.0%). The smallest percentage use was recorded in Mafia district (0.5%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (2.7%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 53 percent of the total area planted with cereals during the long rainy season being threshed by hand. Human powered tools and engine driven machines were only used on crops harvested from 0.4 percent and 2.3 percent of the total planted area respectively. No draft animals were used during threshing. Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 631, 13% Pulses, 662, 13% Oil seeds, 18, 0.4% Fruits & Vegetables, 1,062, 21% Cereals, 2,606, 52% Cash crops, 59, 1% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent of Planted Area Fruits & Vegetables Cash crops Pulses Cereals Roots & Tubers Oil seeds Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - PWANI 0.0 1.0 2.0 3.0 4.0 Mkuranga Kibaha Rufiji Bagamoyo Kisarawe Mafia District Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Pwani region, the area of annual crops under irrigation was 58,870 ha representing 33.1 percent of the total area planted (Chart 3.79). The area under irrigation during the short rainy season was 1,512 ha accounting for 2.6 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season, 64 percent of the area planted with vegetables was irrigated, whilst 57 percent of the vegetables were irrigated in the long rainy season. The district with the largest planted area under irrigation with annual crops was Mkuranga (18,275 ha, 40.7% of the total irrigated planted area with annual crops in the region). This is closely followed by Rufiji with (9,711 ha, 21.6%) and then Kisarawe (9,482 ha, 21.1%). The smallest is Mafia (117 ha, 0.3%). When expressed as a percentage of the total area planted in each district, Mkuranga had the highest with 49 percent of the planted area in the district under irrigation. This is followed by Kisarawe (45%), Rufiji (27%), Bagamoyo (10%), Kibaha (5%), and Mafia (4%) (Chart 3.80 and Map 3.32). edit chart title Of all the different crops and in terms of proportion of the irrigated planted area, onions, cabbage, chillies and spinach were the most irrigated crops with 100 percent irrigation followed by water melon (98%), amaranthus (89%), egg plant (83%) and cucumber (82%). In terms of crop type, the area under irrigation with roots and tubers was 41,916 ha (93% of the total area under irrigation), followed by cereals with 1,535 ha (3%), fruit and vegetables (1,210 ha, 3%) and pulses (255 ha, 0.6%). All of the irrigation on cereals was applied to sorghum, maize and paddy. Chart 3.79 Area of Irrigated Land Unirrigated Area, 132,752, 75% Irrigated Area, 44,920, 25% Chart 2.80 Planted Area with Irrigation by District - PWANI Region 0 4,000 8,000 12,000 16,000 20,000 Mkuranga Rufiji Kisarawe Bagamoyo Kibaha Mafia Region Irrigated A rea (h a) 0 10 20 30 40 50 60 Percen ta ge Irrigation Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation - PWANI 2,908 3,815 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 1995/96 2002/03 Agriculture Year Planted Area ubder Irrigation Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 9,711ha 18,275ha 9,482ha 984ha 6,351ha 117ha 26.9% 48.6% 45.3% 5.1% 10.5% 3.8% 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Planted Area With Irrigation Map 3.32 PWANI Area Planted and Percent of Total Planted Area With Irrigation by District Planted Area With Irrigation Percent of Total Planted Area With Irrigation RESULTS 56 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 Chart 3.82 Number of Households with Irrigation by Source of Water Borehole, 158, 3% Pipe water, 342, 6% Dam, 374, 7% Well, 2,132, 40% River, 1,871, 35% Canal, 432, 8% Canal River Well Dam Pipe water Borehole The area of fruit and vegetables under irrigation was 1,210 ha which represents 61 percent of the total planted area with fruit and vegetables. Onions, cabbages, chillies and spinach were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Pwani region appears to have increased over the 10 year intercensal period from 2,908 to 3,815 hectares. This may not be statically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from wells (40% of households with irrigation). This was followed by river (35%) and canal (8%). Only 3 percent of the households used water from boreholes and the proportion of households that used dams and pipe as a source of water for irrigation were very few (7% and 6% respectively). Most households using irrigation in Rufiji and Bagamoyo get their irrigation water from rivers (100 and 60 % respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common means of getting water for irrigation with 80.1 percent of households using this method. The remaining methods (hand pump, motor pump and gravity) were of minor importance (Chart 3.83). Hand bucket was used by most households with irrigation in Mkuranga (49.7%), followed by Kibaha (20.2%), Bagamoyo (16.3%), Kisarawe (7.6%), Rufiji (3.7%) and Mafia (2.5%). Gravity was more common in Bagamoyo with 41.1 percent of households using the method to get water for irrigation, followed by Mkuranga (35.2), Kibaha (17.2%), Mafia (6.5%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Bagamoyo and Mkuranga districts used some hand and motor pumps for obtaining water. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 238, 4.5% Hand Bucket, 4,251, 80.1% Motor Pump, 259, 4.9% Hand Pump, 262, 4.9% Other, 299, 5.6% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 98, 2% Bucket / Watering Can, 4,195, 79% Flood, 913, 17% Water Hose, 104, 2% Flood Bucket / Watering Can Sprinkler Water Hose RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.6.4 Methods of Water Application Most households used hand bucket/watering can irrigation (79% of households using irrigation) as a method of field application. This was closely followed by flood (17%). Water hose and Sprinklers were not widely used (2% and 1.8% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seeds for planting in the following season. The results for Pwani region show that there were 43,973 crop growing households (31.5% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 28,351 households storing 6,888 tonnes. This was followed by beans and other pulses (11,798 households, 208t), paddy (11,095 households, 1,538t) and sorghum & millet (2,466 households, 196t). Other crops were stored in very small amounts. 3.7.1.1 Methods of Storage The region had 25848 crop growing households storing their produce in locally made traditional structures (59% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 12,447 (28%). This was followed by: unprotected piles (1,740 households, 4%), improved locally made structures (1,538 households, 3%), air tight drums (795 households, 21%) and modern stores (138 households, 0.3%) and other methods (1,467 households, 3%). Locally made traditional structures were the dominant storage method in all districts, with the highest percent of households in Rufiji using this method (69% of the total number of households storing crop products). This was followed by Kisarawe (68%), Bagamoyo (63%), Mkuranga (47%), Mafia (28%) and Kibaha (23%). (Chart 3.87). The highest percent of households using sacks and open drum was in Mafia and Kibaha districts (68% and 63% of the total number of households storing crops), followed by Bagamoyo (27%), Kisarawe (27%), Mkuranga (23%), and Rufiji (11%). Chart 3.85 Number of Households and Quantity Stored by Crop Type - PWANI 0 5,000 10,000 15,000 20,000 25,000 30,000 Maize Beans & P uls es P addy Cas hewnut So rghum & MilletGro undnuts /Bambara Nuts Crop Number of households 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.86 Number of households by Storage Methods - PWANI Locally Made Traditional Crib, 25,848, 59% Sacks / Open Drum, 12,447, 28% Modern Store, 138, 0% Airtight Drum, 795, 2% Other, 1,467, 3% Improved Locally Made Crib, 1,538, 3% Unprotected Pile, 1,740, 4% Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.1.2 Duration of Storage Most households (51.0% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of less than 3 months (27%). The minority of households stored their crop for a period of over 6 months (22%). Most households that stored pulses stored them for a period of 3 to 6 months followed by less than 3 months. A small number of households stored pulses for the period of over 6 months (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Bagamoyo district (55%) followed by Rufiji (54%), Mkuranga (52%), Kibaha (48%), Mafia (46%) and Kisarawe (44%). (Map 3.33). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Kisarawe district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize with household consumption as the main purpose of storage was 88.2 percent followed by seeds for planting. A high percent of the stored permanent crops was for household consumption as was the case of cashew nuts (66.2%). This was followed by selling at a higher price (23.2%) (Chart 3.90). 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Quantity (tonnes) 0 5 10 15 20 25 30 35 40 45 % Stored Quantity harvested Quantity stored % stored 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of H o useho lds Maize Paddy Sorghum & Mi... Beans & Pulses Wheat Cashewnut G'nuts/BambNuts Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Rufiji Mkuranga Kisarawe Kibaha Mafia Bagamoyo 18,600 24,950 11,381 6,662 12,132 4,732 60% 72% 61% 47% 33% 80% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Rufiji Kibaha Mafia 9% 12% 5% 4% 19% 3% Kisarawe Mkuranga Bagamoyo 16 to 20 12 to 16 8 to 12 4 to 8 0 to 4 Tanzania Agriculture Sample Census Percent of Households Storing Crops Percent of Households Storing Crops Number of Households Selling Crops Map 3.33 PWANI Percent of households storing crops for 3 to 6 months by district Map 3.44 PWANI Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops Percent of Total Households Selling Crops RESULTS 60 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.7.1.4 The Magnitude of Storage Loss About 76.3 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as cashew nuts, groundnuts and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (0.025% of the total number of households that stored crops). This was followed by beans and pulses (0.024%), maize (0.018%), groundnuts and paddy (0.006%). Most households that stored cash crops such as cashew nuts had little or no loss (98.6%). All households storing wheat had no storage loss (100%) (Table 3.10). 3.7.2 Agro-processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Pwani region (55,704 households, 40% of the total crop growing households). (Chart 3.91a). The percent of households processing crops was low in most districts. Kisarawe and Kibaha had the highest percent of households processing crops (77% and 44% of crop growing households respectively). (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops on- farm by hand representing 72 percent (40,175 households). This was followed by those processing using neighbour’s machines (13,010 households, 23.4%), on-farm by machine (1,183 households, 2.1%) trader (586 households, 1.1%). The remaining methods of processing were used by very few households (each less than 1%). Although processing on-farm by hand was the most common processing method in all districts in Pwani region, district differences existed. Bagamoyo had a higher percent of processing using neighbour’s machine than other districts.(63%), followed by Kibaha (32%), Rufiji (21%) and Kisarawe (15%). Processing by trader was dominated by Bagamoyo (6%), whilst processing on farm by machine was more prevalent in Bagamoyo, Mkuranga and Rufiji. (Chart 3.92). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Bagamoyo 9,759 3,548 1,573 201 15,080 Kibaha 3,127 105 79 0 3,312 Kisarawe 7,261 426 1,265 145 9,098 Mkuranga 3,891 235 323 0 4,449 Rufiji 7,243 1,693 406 81 9,423 Mafia 2,281 272 43 17 2,614 Total 33,563 6,279 3,688 444 43,974 Chart 3.91a Households Processing Crops Households Processing, 55,704, 39% Households not Processing, 85,826, 61% 0 20 40 60 80 Percent of Households Processing Kisarawe Kibaha Mkuranga Rufiji Mafia Bagamoyo District Chart 3.91b Percentage of Households Processing Crops by District Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader Other By Factory RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is the secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 41,056 households processing crops into flour (74%) followed by grain with 8,234 households (15%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 75 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 24,692 households (57%) followed by shell (9,446 households, 22%), husk (3,807 households, 8%) and pulp (1,576 households, 3%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Bagamoyo was the only district that used primary products as fuel for cooking and all of it from maize crop. Out of 6,584 households that sold processed products, 3,799 were from Rufiji (57.7% of the total number of households selling processed products in the region), followed by Bagamoyo with 1,212 households (18.4%), Mkuranga with 805 households (12.2%), Kisarawe with 366 households (5.6%), Kibaha with 357 households (5.4%), and Mafia with 45 households (0.7%) (Chart 3.96). Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal 74% Pulp 0.1% Other 5% Juice 0.0% Oil 6% Grain 15% Chart 3.95 Use of Processed Product Household/ human consumption, 72,982, 98.2% Fuel for Cooking, 100, 0.1% Sale Only, 390, 1% Did Not Use, 583, 1% Animal Consumption, 173, 0.2% Chart 3.94 Number of Households by Type of By-product Husk, 3,807, 8% Bran, 24,692, 57% Pulp, 1,576, 3% Cake, 3,072, 7% Other, 1,081, 2% Shell, 9,446, 22% Juice, 87, 0% 0.00 10.00 20.00 30.00 40.00 50.00 60.00 Percentage of households Rufiji Bagamoyo Mkuranga Kisarawe Kibaha Mafia District Chart 3.96 Percentage of Households Selling Processed Crops by District RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold to other unspecified outlets (3664 households, 56% of households that sold crops). This was followed by selling to neighbours (1,571 households, 24%), trader at farm (529 households, 8%), local market and trade stores (377 households, 6%), marketing co-operatives (183 households, 3%), large scale farm (129 households, 2%) and farmers associations (44 households, 1%). (Chart 3.97). There were large differences between districts in the proportion of households selling processed products to neighbours with Mafia district having all the households in the district selling to neighbours (100%), whereas Bagamoyo had only 6 percent. Mkuranga had a higher percent of households relying on trader at farm than other outlets. Compared to other districts, Mkuranga had the highest percent of households selling processed products to local market and trade stores. In Kisarawe, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Kisarawe, Kibaha and Bagamoyo. (Chart 3.98). 3.7.3 Crop Marketing The number of households that reported selling crops was 78,458 which represented 56 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Mafia (80%) followed by Mkuranga (72%), Kisarawe (61%), Rufiji (60%), Kibaha (47%) and Bagamoyo (33%). (Chart 3.99 and Map 3.34). Chart 3.97 Location of Sale of Processed Products Neighbours, 1,571, 24% Local Market / Trade Store, 377, 6% Marketing Co- operative, 183, 3% Other, 3,750, 57% Trader at Farm, 529, 8% Large Scale Farm, 129, 2% Farmers Association, 44, 1% Chart 3.98 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Bagamoyo Kibaha Kisaraw e Mkuranga Rufiji Mafia District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 5,000 10,000 15,000 20,000 25,000 30,000 Mkuranga Rufiji Bagamoyo Kisarawe Kibaha Mafia District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (77% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (6%), lack of transport (4%), high transport costs (4%), lack of buyers (4%) other marketing problems (3%), and lack of market information (2%). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 54 percent of the smallholders, followed by other unspecified reasons (41%). The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts except for Kibaha and Rufiji where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (49% and 47% respectively). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census results show that in Pwani region very few agricultural households (1,681, 1.2%) accessed credit out of which 1,521 (90%) were male-headed households and 160 (10%) were female headed households. While no district had only female headed households getting agricultural credit whereas in Bagamoyo, and Rufiji districts only male households (100%) accessed credit. In Mkuranga district both male and female headed households accessed agricultural credit (Table 3.12). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Pwani region were cooperatives who collectively provided credit to 1,094 agricultural households (65% of the total number of households that accessed credit), followed by religious Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 34,380 54.4 Other 25,884 41.0 Price Too Low 914 1.4 Co-operative Problems 902 1.4 Trade Union Problems 497 0.8 Government Regulatory Board Problems 353 0.6 Market Too Far 124 0.2 Farmers Association Problems 108 0.2 Total 63,161 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Bagamoyo 98 100 0 0 98 Mkuranga 1,339 89 160 11 1,499 Rufiji 83 100 0 0 83 Total 1,521 90 160 10 1,681 Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Bagamoyo Mkuranga Rufiji District Percent of Households Family, Friend and Relative Commercial Banks Saving & Credit Society Trader/Trade Store Religious Organisation/NGO/Project Other Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Lack of Market Information 2% Other 3% Co-operative Problems 1% Market too Far 5% Transport Cost Too High 4% No Transport 4% Farmers Association Problems 1% No Buyer 4% Government Regulatory Board Problems 1% Open Market Price Too Low 77% Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 6% Religious Organisation / NGO / Project 37% Private Individual 5% Co-operative 65% Other 0% Trader / Trade Store 10% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 organizations/non governmental organizations/ projects (15%), trader/trade store (10%), commercial bank (6%), private individuals (5%) and none from other sources (0%). (Chart 3.101). Commercial banks were the sole source of credit in Bagamoyo district and savings and credit societies were found in Mkuranga district only. Trader/trader stores were credit providers in Mkuranga district only. Religious organizations, NGO’s and projects were more involved in funding a relatively great number of households in Mkuranga and Rufiji districts only. (Chart 3.102). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credits provided to agricultural households in the region were used on agro- chemicals (30%), followed by fertilizers (12%), irrigation structures (11%), livestock (11%), hiring labour (10%), and others (10%). (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting for 61 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (21%), followed by “not wanting to go into debt” (8.0%) The rest of the reasons were collectively less than 9 percent of the households. 3.8.2 Crop Extension The number of agricultural households that received crop extension was 46,727 (34% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Kisarawe having a relatively high proportion of households (61%) that received crop extension messages in the district followed by Kibaha (43%), Bagamoyo (32%), Mkuranga (28%), Rufiji (25%) and Mafia (4%). (Chart 3.106 and Map 4.35). Chart 3.104 Reasons for not Using Credit (% of Households) Not available, 29,261, 21% Did not want to go into debt, 11,805, 8.4% Difficult bureaucracy procedure, 4,227, 3% Not needed, 4,635, 3.3% Interest rate/cost too high, 3,410, 2% Credit granted too late, 620, 0.4% Other, 361, 0.3% Don't know about credit, 60,631, 43.4% Did not know how to get credit, 24,900, 17.8% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 11% Labour 10% Fertilizers 12% Other 10% Agro-chemicals 30% Irrigation Structures 11% Tools / Equipment 8% Seeds 8% Rufiji Mkuranga Kisarawe Kibaha Mafia 1,880 6,412 5,016 5,165 9,643 772 1% 4% 3% 3% 6% 0% Bagamoyo 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 7,603 9,560 11,435 6,049 11,835 245 24.6% 27.5% 61.4% 43.1% 31.7% 4.1% 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Number of Households Receiving Crop Extension Percent of Total Households Receiving Crop Extension Number Of Households Using Improved Seeds Map 3.35 PWANI Number of Households and Percent of Total Households Receiving Crop Extension Services by District Map 3.36 PWANI Number Of Households and Percent of Households Using Improved Seeds By District Percent of Households Using Improved Seeds Percent of Total Households Receiving Crop Extension Number Of Households Using Improved Seeds RESULTS 66 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the government provided the greatest proportion of the services (96.8%, 44,669 households) followed by large scale farms 1.6%, cooperatives 0.8%, NGOs provided 0.5%, and the remaining providers (0.3 percent (Chart 3.107). However district differences exist with the proportion of the households receiving advice from government services ranging from between 82.0 percent and 100 percent in Mafia and Rufiji respectively. 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 66 percent of the households receiving extension ranked the service as being good followed by average (16%), very good (16%), no good (1%) and poor (1%). (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 94,803, 67% Households Receiving Extension , 46,727, 33% Chart 3.106 Number of Households Receiving Extension by District 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 Kisarawe Kibaha Bagamoyo Mkuranga Rufiji Mafia District Number of Households 0 20 40 60 80 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 1.6% Cooperative 0.8% NGO / Development Project 0.5% Other 0.3% Government 96.8% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 30,499, 65.8% Average, 7,605, 16.4% Poor, 357, 0.8% No Good, 390, 0.8% Very Good, 7,474, 16.1% RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Pwani region regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm e.g. inorganic fertilizers, fungicides, and herbicides. In Pwani region, improved seeds were used by 21,121 households which represents 15 percent of the total number of crop growing households. This was followed by households using pesticides/fungicides (12%), compost (8.2%) farm yard manure (6.7%), inorganic fertilisers (2.7%), and herbicides (0.2%). (Table 3.14). 3.9.1 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Pwani mostly purchased them from the local market/trade store (93.2% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers were of minor importance. (Chart 3.109). Access to inorganic fertilisers was mainly more than 10 km from the household with most households residing more tha 20 km from the source (43.2%), followed by between 10 and 20 km (17.4%) and between 3 and 10 km (16.2%) (Chart 3.110). Due to the small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertilisers was not the main reason for not using it. Other reasons such as cost are more important with 70 percent of households responding to cost factors as the main reason for not using. In other words, if the cost was affordable the demand would be higher and inorganic fertilisers would be made more available. More smallholders use inorganic fertilisers in Mkuranga than in other districts in Pwani region (54% of households using inorganic fertilisers), followed by Bagamoyo (22%), and Kibaha (11%). While Mafia and Kisarawe districts use very little inorganic fertiliser, it is none for Rufiji. Table 3.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Improved seeds 21,121 15.1 118,323 84.9 Pestcides/Fungicide 17,019 12.2 122,425 87.8 Compost 11,417 8.2 128,027 91.8 Farm yard manure 9,311 6.7 130,133 93.3 Inorganic fertiliser 3,801 2.7 135,643 97.3 Herbicide 326 0.2 139,118 99.8 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 93.2 5.4 0.9 0.5 0.0 0.0 0 500 1000 1500 2000 2500 3000 3500 4000 Local Market / Trade Store Neighbour Co-operative Locally Produced by Household Large Scale Farm Development Project Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 3.9.2 Improved Seeds The percent of households that use improved seeds was 15 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (74%). Other but less important sources of improved seeds were neighbours (11.6%), development partners (5.3%), and locally produced by household (3%). Only 0.5 percent of households using improved seeds obtained them from large scale farms. (Chart 3.111). Access to improved seeds was slightly better than access to chemical inputs with 41 percent of households obtaining the input more than 20 km from the household. (Chart 3.112). This is in line with the higher use of improved seeds compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that used improved seeds most was Bagamoyo (28.8 percent of the total number of households using improved seeds in Pwani region), followed by Mkuranga (24.8%), Kisarawe (22.4%), and Kibaha (16.2%). Use of improved seeds in Rufiji and Mafia districts is of minor importance. 3.9.3 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (55% of the total number of fungicides users), followed by local farmers’ group (28%). Other sources of insecticides/ fungicides were of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticides/fungicides. The small number of households using insecticides/fungicides coupled with the 13 percent of Chart 3.111 Number of Households by Source of Improved Seed 0.7 0.5 1.1 0.9 1.4 1.4 3.0 5.3 11.6 74.0 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Local Market / Trade Store Neighbour Development Project Locally Produced by Household Crop Buyers Local Farmers Group Other Co-operative Secondary Market Large Scale Farm Source of Improved Seed Number of Households Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 5 10 15 20 25 30 35 40 45 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of H ouseholds Chart 3.113 Number of Households by Source of Insecticide/fungicide 54.9 27.9 8.7 3.6 2.2 1.5 0.5 0.7 0.0 0.0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Local Market / Trade Store Local Farmers Group Co-operative Neighbour Crop Buyers Development Project Other Large Scale Farm Locally Produced by Household Secondary Market Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 households responding to “not available” as the reason for not using them, it may be assumed that access was not the main reason for not using them. Other reasons such as cost were more important with 73 percent of households responding to cost factors as the main reason for not using. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were used more in Mkuranga district (58.7 percent of the total number of households that use fungicides in the region), followed by Rufiji (12.8%), Bagamoyo (11.9%) and Kibaha (11.1%). Insecticides/fungicides use in Kisarawe and Mafia districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 3,240 representing 2 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 351,510 trees. The average number of trees planted per household planting trees was 109 trees. The main species planted by smallholders is Melicia excelsa (124,182 trees, 35.3%), followed by Senna Spp (71,987, 20.5%), then Tectona Grandis (59,168, 16.8%), Acacia Spp (24,4791 trees, 7%), Eucalyptus Spp (15,570, 4.4%), Gravellis (14,480, 4.1%), Moringa Spp (12,936, 3.7%) and Cyprus Spp (11,693, 3.3%). The remaining trees species are planted in comparatively small numbers (Chart 3.116). Kibaha has the largest number of smallholders with planted trees than any other district (64.5%) and is dominated by Melicia excelsa. This is followed by Bagamoyo (11.6%) which is dominated by Tectona Grandis and Gravellis, Rufiji (11.2%) dominated by Tectona Grandis, Kisarawe (7.7%) which is mainly planted with Moringa Spp and Mkuranga (4.1%) which is dominated by Eucalyptus Spp. (Chart 3.117 and Map 3.37.). Smallholders mostly plant trees scattered around fields. The proportion of households that plant trees scattered around fields is 40 percent, followed by planted on boundary of fields (35%) and then trees planted in a plantation or coppice (25%) (Chart 3.118). Chart 3.115 Number of Households with Planted Trees Growing trees, 3,240, 2% Not growing trees, 138,290, 98% Chart 3.116 Number of Planted Trees by Species - PWANI 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Melicia excelsa Senna Spp Tectona Grandis Acacia Spp Eucalyptus Spp Gravellis Moringa Spp Cyprus Spp Azadritachta Spp Leucena Spp Casurina Equisetfilia Others Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and District 0 50,000 100,000 150,000 200,000 250,000 Kibaha Bagamoyo Rufiji Kisaraw e Mkuranga Mafia District N umber o f T rees Melicia excelsa Senna Spp Tectona Grandis Acacia Spp Eucalyptus Spp Gravellis Moringa Spp Cyprus Spp Azadritachta Spp Leucena Spp Casurina Equisetfilia Others RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 The main purpose of planting trees is to obtain planks/timber (46.2%). This is followed by wood for fuel (30.1%), shade (10.8%), poles (10.5%), other purposes (2.0%), and medicinal (0.6%). (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 1,935 which represents 1 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Kisarawe district (4%) followed by Mkuranga (2%), Mafia (2%), Kibaha (1%), Bagamoyo (1%) and none in Rufiji. (Chart 3.121). Erosion control bunds accounted for 39.5 percent of the total number of structures, followed by Tree belts (31.3%), water harvesting bunds (25%), Gabions (1.9%), Vetiver (1.0%), Dam (0.7%) and Terraces (0.6%). (Chart 3.122 and Map 3.38). Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 1,935, 1% Households Without Facilities, 139,595, 99% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 4 2 2 1 1 0 0 100 200 300 400 500 600 700 800 Kisarawe Mkuranga Mafia Kibaha Bagamoyo Rufiji District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.118 Number of Trees Planted by Location Field boundary, 123,290, 35% Scattered in field, 141,125, 40% Plantation, 86,947, 25% Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Wood for Fuel Shade Poles Other Medicinal Charcoal Use Percent of Households Rufiji Mkuranga Kisarawe Kibaha Mafia 508 182 575 8,418 428 122 5% 1.8% 5.6% 82.3% 4.2% 1.2% Bagamoyo 6,000 > 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 0 490 2,899 0 0 2,820 0% 2% 11.7% 0% 0% 11.4% Tanzania Agriculture Sample Census Number of Smallholder Planted Trees Number of Smallholder Planted Trees Number of Households with Water Harvesting Bunds Map 3.37 PWANI Number and Percent of Smallholder Planted Trees by District Map 3.38 PWANI Number and Percent of Households with Water Harvesting Bunds by District Percent of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Number of Households with Water Harvesting Bunds RESULTS 72 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 Erosion control bunds, tree belts and water harvesting bunds together had 23,758 structures. This represented 96 percent of the total structures in the region. The remaining 4 percentage were shared among the rest of the erosion control methods mentioned above. Mkuranga, Mafia and Kibaha districts had 19,049 erosion control structures (77 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 122,308. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 0.7 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Pwani region was 110,360 (90.2% of the total number of cattle in the region), 10,809 cattle (8.8%) were dairy breeds and 1,140 cattle (0.9%) were beef breeds. The census results show that 5,568 agricultural households in the region (4% of total agricultural households) kept 0.12 million cattle. This was equivalent to an average of 22 heads of cattle per cattle- keeping-household. The district with the largest number of cattle was Bagamoyo which had about 94,401cattle (77.2% of the total cattle in the region). This was followed by Mafia (11,781 cattle, 9.6%), Kibaha (9,144 cattle, 7.5%), Rufiji (3,503 cattle, 2.9%), and Kisarawe (3,190 cattle, 2.6%). Mkuranga district had the least number of cattle (289 cattle, 0.2%) (Chart 3.123 and Map 3.39). However Mafia district had the highest density (54 head per km2 ) (Map 3.40). Although Bagamoyo district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and no beef cattle were recorded. However, the district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (0.9%). (Chart 3.124). Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.6 0.7 1.0 1.9 25.1 31.3 39.5 0 2,000 4,000 6,000 8,000 10,000 12,000 Erosion Control Bunds Tree Belts Water Harvesting Bunds Gabions / Sandbag Vetiver Grass Dam Terraces Type of Facility Number of Structures 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Number of Cattle ('000') Bagamoyo Mafia Kibaha Rufiji Kisarawe Mkuranga Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Districts Number of Cattle Indigenous Beef Dairy Bagamoyo Kibaha Rufiji Mafia 29.8 10.4 0.3 2.1 0.6 53.7 Kisarawe Mkuranga 40 > 30 to 40 20 to 30 10 to 20 0 to 10 Rufiji Kibaha Bagamoyo Mafia 3,503 289 3,190 9,144 94,401 11,781 Kisarawe Mkuranga 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Number of Cattle Number of Cattle Number of Cattle Per Square Km Map 3.39 PWANI Cattle population by District as of 1st October 2003 Map 3.40 PWANI Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km RESULTS 74 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 75 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 N u m b er o f G o a ts ('0 0 0 '). Bagamoyo Rufiji Mkuranga Kibaha Kisarawe Mafia District Chart 3.127 Total Number of Goats ('000') by District 3.12.1.2 Herd Size Forty percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 23% percent of all cattle in the region. Only 17 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 79 percent of total cattle rearing households had herds of size 1-30 cattle and owned 28 percent of total cattle in the region, resulting in an average of 8 cattle per cattle rearing household. There were about 102 households with a herd size of more than 151 cattle each (23,405 cattle in total) resulting in an average of 229 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Pwani increased during the eight-year period from 40,490 in 1995 to 122,308 cattle in 2003. This trend depicts an overall annual positive growth rate of 14.8 percent. (Chart 3.125). There was a very sharp increase in number of cattle during the four-year period from 1995 to 1999 at the rate of 25.9 percent whereby the number increased from 40,490 to 101,594. Also, the number of cattle is estimated to have increased moderately from 101,594 in 1999 to 122,308 in 2003 at the rate of 4.7 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Pwani region was 11,948 (10,809 dairy and 1,140 improved beef). The dairy cattle constituted 8.8 percent of the total cattle and 90.5 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 9.5 percent of the total number of the improved cattle and 0.9 percent of the total cattle. The number of improved cattle increased drastically from 1,450 in 1999 to 11,948 in 2003 at an annual growth rate of 69.4 percent. (Chart 3.126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Pwani region ranked 20th out of the 21 regions with 0.8 percent of the total goats on the Mainland. 40,490 101,594 122,308 - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend - 1,450 11,948 - 2,000 4,000 6,000 8,000 10,000 12,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Improved Cattle Population Trend RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 3.12.2.1 Goat Population The number of goat-rearing-households in Pwani region was 7,621 (5% of all agricultural households in the region) with a total of 98,604 goats giving an average of 13 head of goats per goat-rearing-household. Bagamoyo had the largest number of goats (68,472 goats, 69.4% of all goats in the region), followed by Rufiji (13,406 goats, 13.6%), Mkuranga (5,714 goats, 5.8%), Kibaha (5,226 goats, 5.3%) and Kisarawe (4,847 goats, 5%). Mafia district had the least number of goats (940 goats, 1%). (Chart 3.127 and Map 3.41). However Bagamoyo district had the highest density (21.6 head per km2 ) (Map 3.42). 3.12.2.2 Goat Herd Size Thirty-three percent of the goat-rearing households had herds of 1-4 goats with an average of 2 goats per goat rearing household. Seventy-seven percent of total goat-rearing households had herds of 1-14 goats and owned 37 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 678 households (9%) with herds of 40 or more goats each (39,616 goats in total), resulting in an average of 58 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.7 percent of the total goats in Pwani region. Improved goats for meat and diary goats constituted 0.4 and 0.9 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 23.6 percent. This positive trend implies eight years of population increase from 18,152 in 1995 to 98,604 in 2003. The number of goats increased from 18,152 in 1995 at an estimated annual rate of 37.9 percent to 65,659 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 10.7 percent. (Chart 3.128). 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Pwani region after cattle and goats. The region ranked 19 out of 21 Mainland regions and had 0.6 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 1,503 (1.06% of all agricultural households in Pwani region) rearing 24,334 sheep, giving an average of 16 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Bagamoyo with 21,754 sheep (89.4%of total sheep in Pwani region) followed by Rufiji (1,492 sheep, 6.1%), Kibaha (719 sheep, 3%). Mkuranga District had the least number of sheep (369 sheep, 1.5%). (Chart 3.129 and Map 3.43). Bagamoyo district also had the highest density (7 head per km2 ) (Map 3.44). 18,152 65,659 98,604 - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 5000 10000 15000 20000 25000 N u m b er of sh eep Bagamoyo Rufiji Kibaha Mkuranga District Chart 3.129 Total Number of Sheep by District Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 2.5 5.2 3.1 5.9 21.6 4.3 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 13,406 5,714 4,847 5,226 68,472 940 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Goat Number of Goat Number of Goat Per Square Km Map 3.41 PWANI Goat population by District as of 1st October 2003 Map 3.42 PWANI Goat Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 77 Rufiji Kibaha Mkuranga Kisarawe Mafia 0.3 0 0.8 6.9 0.3 0 Bagamoyo 5.6 to 7 4.2 to 5.6 2.8 to 4.2 1.4 to 2.8 0 to 1.4 Rufiji Kisarawe Kibaha Bagamoyo Mafia 1,492 369 0 719 21,754 0 Mkuranga 18,000 to 22,500 13,500 to 18,000 9,000 to 13,500 4,500 to 9,000 0 to 4,500 Tanzania Agriculture Sample Census Number of Sheep Number of Sheep Number of Sheep Per Square Km Map 3.43 PWANI Sheep population by District as of 1st October 2003 Map 3.44 PWANI Sheep Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 78 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 Sheep rearing was dominated by indigenous breeds that accounted for all the sheep. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 was estimated at 51.9 percent. The population increased at an annual rate of 73.8 percent from 860 in 1995 to 7,845 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 32.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 18 out of 21 Mainland regions and had 0.4 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Pwani region was 353 (0.2% of the total agricultural households in the region) rearing 3,673 pigs. This gives an average of 10 pigs per pig-rearing household. The district with the largest number of pigs was Kisarawe with 2,226 pigs (61% of the total pig population in the region) followed by Mkuranga (761 pigs, 21%), Kibaha (392 pigs, 11%), Bagamoyo (294 pigs, 8%). (Chart 3.131 and Map 3.45). However Kisarawe district had the highest density (1.4 head per km2 ) (Map 3.46). There were no pigs in Mafia and Rufiji districts. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the period from 1999 to 2003 was 0.64 percent. During this period the population grew from 3,581 to 3,673. (Chart 3.132). 860 7,845 24,334 - 5,000 10,000 15,000 20,000 25,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend - 3,581 3,673 - 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 N um ber of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 500 1,000 1,500 2,000 2,500 N u m b er o f P ig s Kisarawe Mkuranga Kibaha Bagamoyo District Chart 3.131 Total Number of Pigs by District Rufiji Mkuranga Kisarawe Kibaha Mafia 0 0.7 1.4 0.4 0.1 0 Bagamoyo 1.12 to 1.4 0.84 to 1.12 0.56 to 0.84 0.28 to 0.56 0 to 0.28 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 0 761 2,226 392 294 0 1,800 to 2,250 1,350 to 1,800 900 to 1,350 450 to 900 0 to 450 Tanzania Agriculture Sample Census Number of Pig Number of Pig Number of Pig Per Square Km Map 3.45 PWANI Pig population by District as of 1st October 2003 Map 3.46 PWANI Pig Density by District as of 1st October 2003 Number of Pig Per Square Km RESULTS 80 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 81 3.12.5 Chicken Production The poultry sector in Pwani region was dominated by chicken production. The region contributed 4.3 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 79507 raising about 1,420,152 chicken. This gives an average of 18 chicken per chicken-rearing household. In terms of total number of chicken in the country, Pwani region was ranked 13th out of the 21 Mainland regions. The District with largest number of chicken was Bagamoyo (370,049 chicken, 26.1% of the total number of chicken in the region) followed by Mkuranga (322,132, 22.7%), Rufiji (311,759, 22%), Kisarawe (246,120, 17.3%), Kibaha (102,338, 7.2%). Mafia district had the smallest number of chicken (67,754, 4.8%). (Chart 3.133 and Map 3.47). However Mafia district had the highest density (308 head per km2 ) (Map 3.48). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 3.23 percent. The population decreased at a rate of - 7.2 percent from 1995 to 1999 after which it increased at the rate of 14.8 percent for the four year period from 1999 to 2003 (Chart 3.134). Eighty eight percent of all chicken in Pwani region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chicken in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 70.4 percent of all chicken-rearing households were keeping 1-19 chicken with an average of 9 chicken per holder. About 29.2 percent of holders were reported to be keeping the flock size of 20 to 99 chicken with an average of 32 chicken per holder. Only 0.4 percent of holders kept the flock sizes of more than 100 chicken at an average of 655 chicken per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 12,480 16 33,830 3 5-9 17,795 23 120,208 7 10-19 25,092 32 321,845 13 20-29 12,254 16 273,881 22 30-39 5,868 7 184,373 31 40-49 2,196 3 92,214 42 50-99 2,673 3 178,300 67 100+ 329 0 215,501 655 Total 78,687 100 1,420,152 18 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 N u m b er of C h ick en s Bagamoyo Mkuranga Rufiji Kisarawe Kibaha Mafia District Chart 3.133 Total Number of Chickens by District 1,101,377 816,765 1,420,152 - 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend Rufiji Kisarawe Kibaha Bagamoyo Mafia 293.7 116.5 57.5 159.4 116.9 308.6 Mkuranga 280 to 320 210 to 280 140 to 210 70 to 140 0 to 70 Bagamoyo Rufiji Kisarawe Kibaha Mafia 370,049 322,132 311,759 246,120 102,338 67,754 Mkuranga 320,000 to 400,000 240,000 to 320,000 160,000 to 240,000 80,000 to 160,000 0 to 80,000 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken Number of Chicken Per Square Km Map 3.47 PWANI Chicken population by District as of 1st October 2003 Map 3.48 PWANI Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km RESULTS 82 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 83 3.12.5.4 Improved Chicken Breeds (Layers and Broilers) Layers chicken population in Pwani Region increased at an annual rate of 111.3 percent during the period of four years from 6,306 in 1999 to 125,649 in 2003. The number of improved chicken was most significant in Kisarawe District followed by Rufiji District (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 7.9 percent during which the population grew from 22,005 to 40,358. The annual growth rate was negative (-45.9%) for the period of four years from 1995 to 1999. The broiler population exhibited an increasing trend at the rate of 115.02 percent per annum for the period of four years resulting at increase from 1,888 in 1999 to 40,358 in 2003 (Chart 3.136). 3.12.6. Other Livestock There were 53,420 ducks, 13,100 turkeys, 11,371 rabbits and 193 donkeys raised by the rural agricultural households in Pwani region. Table 3.16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Bagamoyo district (41% of all ducks in the region), followed by Mafia (32%), Rufiji (18.7%) and Kisarawe (5.2%). Kibaha district had the least number of ducks estimated to be 3 percent of total ducks in the region and no ducks were recorded in Mkuranga. Turkeys were reported only in Mafia and Mkuranga districts (97% and 3% respectively). (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 27 percent and 20 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were lowest in Rufiji district. However ticks problems were highest in Mafia followed by Kisarawe district (Map 3.49). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Bagamoyo 21,949 0 9,198 0 1,828 Kibaha 1,624 0 53 0 0 Kisarawe 2,784 0 1,409 0 0 Mkuranga 0 404 0 0 0 Rufiji 9,968 0 711 0 0 Mafia 17,094 12,696 0 193 65 Total 53,420 13,100 11,371 193 1,893 931 0 2852 7743 42523 30935 67879 0 11464 1679 0 10000 20000 30000 40000 50000 60000 70000 Number of Chickens Bagamoyo Kibaha Kisarawe Rufiji Mafia District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers - 30,000 60,000 90,000 120,000 150,000 Number of Improved Chicken 1995 1999 2003 Year Chart 3.136 Improved Chicken Population Trend Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 10 20 30 40 50 60 70 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Percent Ticks Tsetseflies RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 The most practiced method of tick controlling was spraying with 64 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (8%), smearing (6%) and other traditional methods like hand picking (12%). However, 9 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 45 percent of livestock-rearing households, followed by dipping (11%). However, 44 percent of the livestock rearing households did not use any of the two aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 4,657 (38.2% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 72 percent, goats (35%), sheep (7%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 10,168, representing 83.5 percent of the total livestock- rearing households and 7.2 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 97 percent of all households receiving livestock extension services. The rest of the households got services from Cooperatives (12%), NGOs/ development projects (1%) and large-scale farmers (0.4%). About 64 percent of livestock rearing households described the general quality of livestock extension services as being good, 21 percent said they were very good and 9 percent said they were average. However, 6 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor. (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Some veterinary clinics were not located far from livestock rearing households. About 51.6 percent of the livestock rearing households accessed the services, at a distance of less than 14 kms, while 48.4 percent of them accessed the services more than 14 kms from their dwellings (Chart 3.140). The most affected district was Bagamoyo district with more than half of livestock rearing households accessing the services at a distance of more than 14 kms. Mafia district was the most affected because almost all the livestock rearing households accessed the service at least a distance of 14 kms. from their dwellings. (Chart 3.141). 0 10 20 30 40 50 60 70 80 90 Percent Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 6% Very Good 21% Good, 64% Average, 9% Poor, 1% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 2,494 (71% of livestock rearing households in Pwani region) whilst 674 households (19%) resided between 5 and 14 kms. However, 358 households (10%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Rufiji and Mafia districts had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Kibaha and Bagamoyo districts. In Bagamoyo district about 37 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Pwani region was very limited with only 46 households (0.03% of the total crop growing households in the region) using them (Chart 3.144). Chart 3.142 Number of Households by Distance to Village Watering Points 15 or more kms, 358, 10% 5-14 kms, 674, 19% Less than 5 kms, 2,494, 71% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 200 400 600 800 1,000 1,200 1,400 1,600 Bagamoyo Kibaha Mafia Rufiji District Number of Households Less than 5 kms 5-14 kms 15 or more kms Chart 3.140 Number of Households by Distance to Verinary Clinic Less than 14km, 3,530, 52% More than 14km, 3,306, 48% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 200 400 600 800 1,000 1,200 1,400 1,600 Rufiji Bagamoyo Mafia Kibaha Kisarawe Mkuranga District Number of Households Less than 14 kms More than 14kms RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 86 The 46 households in Pwani region that used draft animals were all in Mafia district. Use of draft animals was not reported in the other districts (Chart 3.145 and Map 3.50). The region had 92 oxen (all in Mafia district) that were used to cultivate 19 hectares of land. This represents only 0.004 percent of the total oxen found on the Mainland. The area cultivated using oxen was found in Mafia district only. 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Pwani region was 15,882 (11% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 13,326 ha of which 4,772 hectares (36% of the total area applied with organic fertiliser or 4.4% of the area planted with annual crops and vegetables in Pwani region during the long rainy season) was applied with farm yard manure (Map 3.51). 3.12.9.4 Use of Compost Only 8,553 ha (64% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Bagamoyo district with 1,389 hectares (29% of the total area applied with farm yard manure) followed by Mkuranga (1,098 ha, 23%), Kibaha (923 ha, 19.4%), Mafia (757 ha, 16%), Kisarawe (421 ha, 8.8%), and Rufiji (183 ha, 3.8%) (Chart 3.147 and Map 3.52). 0 5 10 15 20 25 30 35 40 45 50 Number of Households Mafia Bagamoyo Kibaha Kisarawe Mkuranga Rufiji District Chart 3.145 Number of Households Using Draft Animals by District - PWANI Chart 3.146 Number of Households Using Organic Fertiliser Not Using Organic Fertilizer, 124,331, 89% Using Organic Fertilizer, 15,882, 11% Chart 3.147 Area of Application of Organic Fertiliser by District PWANI 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 Mkuranga Bagamo yo Kis arawe Kibaha Rufiji Mafia District Area of Fertiliser Application (ha) Farm Yard Manure Compost 3.144 Number of Households Using Draft Amimals Using draft animal, 46, 0.03% Not using draft animal, 141,398, 99.97% Rufiji Mkuranga Kisarawe Kibaha Mafia 0 0 0 0 0 46 0 0 0 0 0 0 Bagamoyo 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Rufiji Mkuranga Kisarawe Kibaha Mafia 305 197 422 216 1,112 1,061 2.8 1.8 3.9 2 10.3 9.8 Bagamoyo 950 to 1,200 700 to 950 500 to 700 250 to 500 0 to 250 Tanzania Agriculture Sample Census Number of Households Infected withTicks Number of Households Infected withTicks Number of Households Using Draft Animals Map 3.49 PWANI Number and Percent of Households Infected with Ticks by District Map 3.50 PWANI Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Percent of Households Infected withTicks Percent of Households Using Draft Animals RESULTS 87 Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 235 2,601 737 465 5,409 107 0.1 1.5 0.4 0.3 3 0.1 4,400 to 5,500 3,300 to 4,400 2,200 to 3,300 1,100 to 2,200 0 to 1,100 Rufiji Kisarawe Kibaha Bagamoyo Mafia 96 1,804 337 1,099 928 545 0.1 1 0.2 0.6 0.5 0.3 Mkuranga 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure application Planted Area with Farm Yard Manure application Planted Area with Compost application Map 3.51 PWANI Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District Map 3.52 PWANI Planted Area and Percent of Total Planted Area with Compost application by District Planted Area with Compost application Percent of Planted Area with Farm Yard Manure application Percent Planted Area with Compost application RESULTS 88 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 89 3.12.10 Fish Farming Fish farming was not practiced in Pwani region. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was a service that was located farthest from most of the household’s dwellings than any other service. It was located at an average distance of 130 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tertiary market (64.4), hospital (48.2), tarmac road (31.5), secondary market (31.1), secondary school (23.7), primary market (17.4), health clinic (7), all weather road (4.2), primary school (2.4) and feeder road (1.3). (Table 3.15). Only 9 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 20 percent reported them to be average. Seventeen percent of the agricultural households said the infrastructure and services were poor, and 21 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (125,877 households, 88.9% of all rural agricultural households) 2,463 households (1.7%) use improved pit latrine and 4,236 households (3%) use flush toilets. The remaining 23 household (0.02%) use other toilets facilities. However, 8,932 households (6.3%) in the region had no toilet facilities (Chart 3.148). The distribution of the households without toilets within the region indicates that 31.6 percent of them were found in Rufiji District and 25.4 percent were from Bagamoyo. The percentages of households without toilets in other districts were as follows Mafia (15.5%), Mkuranga (14.5%), Kisarawe (6.8%), and Kibaha (6.1%). Map 3.53). Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Bagamoyo 21.2 2.3 2.9 1.8 68.6 5.3 101.6 13.0 33.5 68.1 10.8 Kibaha 27.1 1.8 1.7 0.6 39.6 9.2 48.4 10.3 18.9 42.5 10.4 Kisarawe 17.4 1.9 4.5 0.6 43.7 6.9 97.3 17.4 26.2 61.2 51.6 Mkuranga 26.0 3.0 4.3 1.0 37.9 7.5 118.7 13.0 21.9 45.2 17.9 Rufiji 25.1 2.3 5.9 1.6 46.1 8.2 213.0 18.3 35.6 78.1 37.0 Mafia 30.1 2.6 8.4 2.2 26.6 2.7 238.6 82.9 90.3 143.6 200.5 Total 23.7 2.4 4.2 1.3 48.2 7.0 130.0 17.4 31.1 64.4 31.5 Chart 3.148 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 125,877, 88.9% Flush Toilet, 4,236, 3.0% No Toilet , 8,932, 6.3% Other Type, 23, 0.02% Improved Pit Latrine , 2,463, 1.7% Mkuranga Kisarawe Kibaha Mafia Rufiji 2,826 1,293 610 549 2,272 1,383 2 0.9 0.4 0.4 1.6 1 Bagamoyo 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Tanzania Agriculture Sample Census Number of Households Without Toilets Number of Households Without Toilets Map 3.53 PWANI Number and Percent of Households Without Toilets by District Percent of Households Without Toilets RESULTS 90 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Pwani region with 98,795 households (69.8% of the agriculture households in the region) owning the asset. followed by bicycle ( 63,644 households, 45%), iron (20,556 households, 14.5%), wheelbarrow (4,371 households, 3.1%), mobile phone (2,542 households, 1.8%), television/video (1,754 households, 1.2%), vehicle (1,354 households, 1%) and landline phone (415 households, 0.3%) (Chart 3.149). 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region. with 78.5 percent of the total rural households using this source of energy followed by hurricane lamp (15%), pressure lamp (3%), mains electricity (1.8%), firewood (1.3%), solar (0.2%), candle (0.3%) and other (0.02%). (Chart 3.150). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.8 percent of all rural agricultural households in Pwani region. This was followed by charcoal (4.5%). The rest of energy sources accounted for 0.7 percent. These were bottled gas (0.2%), crop residues (0.1%), solar (0.1%), livestock dung (0.1%), parrafin/kerosene (0.1%) and gas/biogas (0.1%). (Chart 3.151). Chart 3.149 Percentage Distribution of Households Owning the Assets 3.1 1.8 1.2 1.0 0.3 69.8 45.0 14.5 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 1,856, 1.3% Solar, 263, 0.2% Candles, 395, 0.3% Hurricane Lamp, 21,204, 15% Pressure Lamp, 4,243, 3% Mains Electricity, 2,481, 1.8% Other, 31, 0.02% Wick Lamp, 111,057, 78.5% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 305, 0.2% Crop Residues, 156, 0.1% Mains Electricity, 0, 0% Solar, 80, 0.1% Livestock Dung, 204, 0.1% Charcoal, 6,374, 4.5% Firewood, 134,132, 94.8% Parraffin / Kerosine, 197, 0.1% Gas (Biogas), 81, 0.1% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 3.13.6 Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 66 percent of the rural agricultural households. This was followed by iron sheets (26.7%), grass/mud (6.5%), asbestos (0.4%), tiles (0.3%), and others (0.2%). (Chart 3.152). Mafia district had the highest percentage of households with grass/leaves roofing material (91%) and was followed by Mkuranga district.(78%), Rufiji (71%), Kisarawe (65%), Bagamoyo (53%), and Kibaha (52%). (Chart 3.153) and Map 3.54). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Pwani region was the unprotected well (55 percent of households use unprotected wells during the wet season and 52.6 percent of the households during the dry seasons. This was followed by surface water (12% of households in the wet season and 16.5% during dry season), piped water (12% of households during the wet season and 13.7% in the dry season), protected well (8% of households during the wet season and 9.5% in the dry season) and uncovered rainwater with 8% of households during the wet season and 2.4% in the dry season. Unprotected spring was used as a main source by 3 percent of the households in the wet season and by 2.9 percent in the dry season . (Chart 3.154). About 62 percent of the rural agricultural households in Pwani region obtained drinking water within a distance of less than one kilometer during wet season compared to 43 percent of the households during the dry season. However, 37 percent of the agricultural households obtained drinking water from a Chart 3.152 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.4% Grass & Mud 6.5% Iron Sheets 26.7% Grass / Leaves 65.9% Tiles 0.3% Other 0.2% Concrete 0.0% Chart 3.153 Percentage Distribution of Households with Grassy/Leafy Roofs by District 52 53 65 71 78 91 0 25 50 75 100 Mafia Mkuranga Rufiji KisaraweBagamoyo Kibaha District Percent Chart 3.154 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 40 50 60 Upro tected Well Surface Water (Lake / Dam / River / Stream) P iped WaterP ro tected Well Unco vered Rainwater Catchment Unpro tected Spring Other Main source Percent of Households Wet Season Dry Season Chart 3.155 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and abo ve Distance Percent wet season Dry season RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 distance of one or more kilometers during wet compared to 56 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km. (Chart 3.155). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Pwani region normally have 3 meals per day (64.7 percent of the households in the region). This is followed by 2 meals per day (28.1 percent) and 1 meal per day (5.4 percent). Only 1.8 percent of the households have 4 meals per day (Chart 3.156). Kisarawe district had the largest percent of households eating one meal per day whilst Bagamoyo had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.55). 3.13.8.2 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 67,290 (47.5% of the agricultural households in Pwani region) with 34,327 households (51% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (29%). Very few households had meat three or more times during the respective week. About 52 percent of the agricultural households in Pwani region did not eat meat during the week preceding the census (Chart 3.157 and Map 356). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 114,687 (81% of the total agricultural households in Pwani region) with 26,216 households (22.9% of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish once a week (20%). The number of households that consumed fish twice or more during the week in Pwani region was 91,738 (80% of the agricultural households that ate fish in the region during the respective period). About 19 percent of the agricultural households in Pwani region did not eat fish during the week preceding the census. (Chart 3.157 and Map 3.57). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Bagamoyo 496 1.3 9801 26.3 26993 72.4 0 0.0 37290 Kibaha 1004 7.2 5554 39.6 6844 48.8 626 4.5 14029 Kisarawe 1627 8.7 7009 37.6 10002 53.7 0 0.0 18637 Mkuranga 2185 6.3 6586 19.0 24130 69.4 1844 5.3 34744 Rufiji 2017 6.5 9224 29.8 19589 63.4 75 0.2 30906 Mafia 324 5.5 1538 26.0 4063 68.6 0 0.0 5924 Total 7,653 5.4 39,711 28.1 91,620 64.7 2,545 1.8 141,530 Chart 3.156 Number of Agriculural Households by Number of Meals per Day Tw o Meals, 39,711, 28% One Meal, 7,653, 5% Four Meals, 2,545, 2% Three Meals, 91,620, 65% Chart 3.157 Number of Households by Frequency of Meat and Fish Consumption 0 5000 10000 15000 20000 25000 30000 35000 40000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Rufiji Mkuranga Kisarawe Kibaha Bagamoyo Mafia 21,830 27,014 12,050 7,237 19,768 5,371 15.4 19.1 8.5 5.1 14 3.8 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Bagamoyo Rufiji Mkuranga Kisarawe Kibaha Mafia 26,993 19,589 24,130 10,002 6,844 4,063 19 14 17 7 5 3 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tanzania Agriculture Sample Census Number of Households Using Grass/ Leaves for Roofing Number of Households Using Grass/ Leaves for Roofing Map 3.54 PWANI Number and Percent of Households Using Grass/Leaves for Roofing Material by District Percent of Households Using Grass/ Leaves for Roofing Number of Households Eating 3 Meals per Day Map 3.55 PWANI Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Percent of Households Eating 3 Meals per Day RESULTS 94 Kisarawe Rufiji Kibaha Bagamoyo Mafia 4,306 4,706 2,756 2,661 8,143 378 3 3 2 2 6 0 Mkuranga 6,800 to 8,500 5,100 to 6,800 3,400 to 5,100 1,700 to 3,400 0 to 1,700 Mafia Rufiji Kibaha Bagamoyo 8,385 1,480 8,863 7,702 3,727 4,171 5.9 1 6.3 5.4 2.6 2.9 Kisarawe Mkuranga 7,600 to 9,500 5,700 to 7,600 3,800 to 5,700 1,900 to 3,800 0 to 1,900 Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Map 3.56 PWANI Number and Percent of Households Eating Meat Once per Week by District Percent of Households Eating Meat Once per Week Number of Households Eating Fish Once per Week Map 3.57 PWANI Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Percent of Households Eating Fish Once per Week RESULTS 95 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 3.13.9 Food Security In Pwani region, 53,900 households (38.1% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 12,124 (8.6%) said they sometimes experience problems, 20.9 often experienced problems and 6.3 percent always had problems in satisfying the household food requirement. About 26.2 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.58). 3.13.10 Main Sources of Cash Income The main source of cash income of the households in Pwani region was from selling cash crops (22.7 percent of smallholder households), followed by sale of food crops (22.4%), selling of forest products (19.2%), casual cash earnings (10.8%), businesses (8.6%) and cash remittances (5.6%), fishing (4.5%), wages and salaries in cash (2.9%). Only 1.5% of smallholder households reported the sale of livestock products as their main source of income, followed by other unspecified sources (0.9%), and lastly, sale of livestock (0.9%). (Chart 3.158). Chart 3.158: Percentage Distribution of the Number of Households by Main Source of Income not applicable, 0% Other, 0.9% Livestock, 0.9% Livestock Products, 1.5% Forest Products, 19.2% Wages & Salaries, 2.9% Remittance, 5.6% Business Income, 8.6% Cash Crops, 22.7% Fishing, 4.5% Food Crops, 22.4% Other Casual Cash Earnings,10.8% Kisarawe Kibaha Bagamoyo Mafia 2,554 942 1,252 1,043 2,969 173 1.8 0.7 0.9 0.7 2.1 0.1 Rufiji Mkuranga 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Map 3.58 PWANI Number and Percent of Households Reporting Food Insufficiency by District Percent of Households Reporting Food Insufficiency RESULTS 97 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 4 PWANI PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Pwani Region Profile The region profile describes the status of the agriculture sector in the region and compares it with those of other regions in the country. Pwani region has a land area of around 250,700 hectares under crop production but had a small number of crop growing households and very few with livestock, compared to other regions. It ranked 15th in the number of crop growing households per square kilometer. The available planted land area per household was (1.8 ha/household) and almost all the land available to smallholders was utilized. The region has two rainy seasons with the long rainy season being more important. Cereal production is not important (ranked 19th among regions on Mainland) and it had one of the smallest planted areas of maize in the country. However paddy production was relatively important but sorghum was grown in small quantities. Cassava was moderately important; beans or groundnuts were insignificant in the region. Vegetable production was small compared to other regions. Pwani had the 4th largest planted area of cashew nuts but ranked first in the planted area for coconuts. It had the second largest area planted with oranges in the country. Compared to other regions, Pwani had a very small planted area under irrigation in the country. The number of households practicing irrigation appears to have increased over the period of 8 years prior to the census. The source of irrigation water was equally split between wells and rivers followed by dams. Use of buckets/watering cans was the most common method of obtaining irrigation water closely followed by unspecified means. Irrigation application was mostly by buckets/watering cans and to a lesser extent, the flood method. Water hose and sprinklers were not widely used. The method of cultivation in Pwani was almost entirely by hand and virtually no fertilizers or pesticides were used. Storage was predominantly in locally made traditional cribs. Pwani had little crop produce to sell and the percent of households selling was very low. Compared to other regions, the percentage of smallholder households processing crops was insignificant. However, it had the highest percent of households processing crops by hand. In the case of those who process crops, the region had the least number of households selling processed products compared to other regions. Compared to other regions, the percent of smallholders receiving extension services was moderate, most of them from the government followed by large scale farms. Pwani had a small number of planted trees by smallholders. Compared to other regions, the percent of households with erosion control/water harvesting facilities was insignificant to low, with erosion control bunds being one of the most prominent, followed by tree belts. Pwani was among the regions with the lowest livestock population and even lower in terms of cattle density, ranking 19th in the country. Most of the cattle kept were the indigenous type and cattle rearing came first in the region, followed by goats, sheep and pigs. Milk production was very low (ranking 18th in the country) and since the demand was very high, the farm gate price of milk was correspondingly high. Goats as well as sheep and pigs were few, in line with the fact that the region was among the last ranked regions in livestock rearing. Pwani ranked 13th in the population of chicken compared DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 to other regions, almost all was entirely made up of layer breed but it was among the three leading regions in layers population in the country. Its egg production was among the lowest in the country. The use of organic fertilizers was very low (ranked 17th) and percentage of area being applied per livestock rearing household was also low. Use of draft animals for cultivation in the region was very limited, with an insignificant percentage of households using them. The disease infection rate was moderate to high for most diseases. The region ranked 7th in the rate of helminthiosis infection compared to other regions. Access to livestock infrastructure and services was between average and poor. In relation to livestock population Pwani ranked 18th but received disproportionately more extension advice compared to other regions with much higher livestock populations such as Shinyanga, Arusha, Manyara, Mwanza and Tabora regions. It ranked 15th in the percentage of households receiving extension advice but was among the last in number of livestock kept. The Agricultural Census did not capture any fish farmers in Pwani region; hence no information is available on this in the report. Pwani region has the fourth smallest rural agriculture population in Tanzania (712,995 persons of which 354,379 are males and 358,616 females). It has a moderate number of rural households involved in agriculture (141,530) compared to other regions. It has 89.7 percent of rural households and 78.5 percent of total households in the region (including urban) that are involved in agriculture. The region has an average household size of 5 persons per household and it has a low percent of female headed households (19%) compared to other regions. Crop only farming dominates and there is virtually no pastoralists in the region. The number of households keeping livestock only is very small. Land under customary law is the predominant type of land ownership, accounting for 76 percent of the total rural smallholder owned land. There is a very small amount of land under official titles. The region has an average access to their fields with about 50 percent of the rural agriculture households having their nearest field less than 100 m from the homestead. Access from the field to the nearest road is relatively poor. Pwani region has comparatively low percent literate rural agriculture population in the country (63%) compared to other regions and the difference between the literacy rate of males and females is fourth highest with 13.4 percent more literate males than females. It has a comparatively low percent of the rural agriculture population that have completed school and a moderate percent of household heads with no education. The most important livelihood activity is crop farming followed by livestock keeping/rearing and tree/forest resources. Off farm income is the least important livelihood activity. The percent of the rural agriculture population working full time in farming is high (more than 75%). The main source of cash income for Pwani is from the sale of food crops followed by sale of cash crops and sale of forest products. Pwani has a low percent of households receiving credit mainly from cooperatives (65%). The region has a low percent of households that use modern roofing material (around 27%) and the rest is mainly with grass/leaves/mud. Almost all households in the region have toilet facilities (93.7%). Energy for lighting is mainly from wick lamps 78.5%) and about 15 percent of households use hurricane lamps. Most water used for drinking in Pwani is from unprotected wells (53%), however, 14 percent of households use piped drinking water. About 10 percent of households in Pwani region obtain drinking water from protected wells. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 100 Most rural agriculture smallholders in Pwani are living a subsistence existence with about 25 percent of the agriculture households using more than 50 percent of their livelihood activities for non subsistence purposes. Most households eat three per day (64.7). It has a low percent of households that do not eat animal protein in one week and a relatively high percent of households that eat animal protein every day. The region has the highest percent of households that face problems in satisfying the household food requirements. It has a moderate access to services and infrastructure in the country. About 36 percent of the households in the region reported insufficiency of land which is moderate in the country. Pwani Region has the same number of males and females (50% males and 50% females). The region has a very slender population pyramid over the ages 20 to 44 and this is more so for males than it is for females. This would suggest that there is a large out-migration from the region over this age range and that more males have the opportunity to leave than females. The result is a relatively moderate feminisation of the agriculture sector in this region. Over the 15 to 19 age range there are more males than females in the region. The region has an active agriculture population of 358,210 of which 168,746 are males and 189,464 are females and there is a small difference between the percent of total male and female active population in the region (47% and 53% respectively). The region has the 2nd lowest number of households in the country compared to other regions (141,530, out of which 115,108 are male headed and 26,422 are female headed). It also has the 11th highest percent of female headed households in the country. The average household size is the similar to the National average (5.3 members per household for male headed households and 4.1 for female headed households), resulting in a difference in the household size of 1.2 more members in male headed households compared to female headed households. Pwani region has the lowest percent of households keeping livestock and, whilst a higher percent of males keep livestock compared to females, the difference is the smallest in the country. There is a relatively large difference in the dependency ratio between male and female headed households (109 dependants for every 100 active members in male headed households and 121 dependants for every 100 active members in female headed households). The region has a large difference in sex ratio of the active agriculture population between male and female headed households (103:100 in male headed households compared to 50:100 in female headed households. Pwani has the 12th largest difference in literacy rates between male and female household heads with an illiteracy rate of 22 percent of male household heads and 54 percent of female household heads. Taking the overall population of male and female members in the region there are 13 percentage points more illiterate females than males and this is 2nd highest difference in the country Pwani has a moderate to low percent of orphans in the country and there is little difference between male and female headed households. No orphan heads of households were detected in Pwani. Pwani has around 10 percent of children with off farm income and this is more prevalent in female headed households (15% with off farm income) compared to male headed. As with all regions, Pwani has more land per household in male headed households than in female headed households. However the difference is small compared to other regions. Pwani region had one of the smallest percent of households reporting insufficiency of land (38%), however there is no difference between male and female headed households. Female headed households in Pwani have around 38 percentage points more female land holders compared to male headed households and this difference is moderate compared to other regions. Pwani has 38 percent of female headed households with female land holders. Assuming that male household members of female headed households do not have rights to land, this would imply that 62 percent of female headed households have insecure access to land in Pwani. Pwani has a DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 101 higher percent of female headed households using customary land compared to male headed households, whilst a higher percent of male headed households have land under certificate of ownership and bought land. Pwani has a low percent of households with cattle compared to other regions and differences between male and female headed households could not be detected. Pwani has the lowest percent of households with goats and the difference in the percent of male and female headed households keeping goats is relatively small. However the number of goats per household is high and there is a difference between male and female headed households with male headed households having 8 more goats per household compared to female headed households. Sheep keeping is not important in Pwani. Pig keeping in Pwani is also not important however it is important in female headed households with 26 percent of female headed households keeping compared to 1 percent in male headed households. Compared to other regions, a moderate percent of households use improved seeds in Pwani region and a higher percent female headed households use improved seed compared to male headed households (11 percentage points more female than male headed households) and this is the highest differential in favour of female headed households in the country. The region has one of the smallest usage of insecticides in the country. It also has one of the highest percent of households not using fertiliser and there is little difference between male and female headed households. Little farm yard manure is used and only by male headed households, however the region has the highest percent of households using compost with slightly more male headed households than female headed households. Very little inorganic fertiliser is used in Pwani region. The region has the 3rd smallest area under irrigation in and there is little difference in the percent area under irrigation in male headed households compared to female headed households, with only 3 percentage points more male headed households than female headed households having irrigation. About 25 percent of the households in Pwani region receive extension advice and the difference between male and female headed households is small. In terms of planted area, Pwani has a smaller short rainy season compared to the long rain season. In Pwani, 49.0 percent of male headed households plant crops compared to 52.8 percent of female headed households in the long rainy season and for those that do not plant the main reason is associated with rains. However a relatively high percent of households do not plant crops and this was followed by illness. There is little difference in the percent of male and female headed households planting during the short rainy season (3.2 percentage points more male than female headed households) and the main reason for not planting during this season was due to rains (60% male headed and 71% female headed households). Pwani has a high percent of planted area with maize in the country and there is no difference between male and female headed households. The yield of maize in the region is one of the lowest in the country and there is no difference between male and female headed households. Pwani has the third highest percent of households growing paddy in the country and there is no difference between male and female headed households and there is no difference in yield. Pwani has a small percent of households utilising secondary products and there is little difference between male and female headed households. Pwani has a high number of cattle sold per household (2.0/hh) compared to other regions and there is a large difference between male and female headed households (2.0 cattle sold per household in male headed households compared to 0.4 per female headed household). More female headed households consume cattle than male headed households. In Pwani region, a large number of goats are sold per household compared to other regions (2.2/hh) and male headed households sell 0.8 more goats per household than female headed households. The number consumed per household is higher than in any other region and it is almost entirely by male headed households. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 Pwani region has a moderate percent of active agriculture household members working full time on farm (60% of active members) and there is a small difference between male and female headed households (5 percentage points more are working full time in male headed households compared to female headed households). Of the most active agriculture population (18 to 44 years of age) 73 percent of males and 81 percent of females are mainly involved in agriculture. In male headed households, 75 percent of the male members and 81 percent of female members are mainly involved in agriculture, whilst in female headed households 63 percent of males and 76 percent of females are mainly involved in agriculture. Pwani region has one of the smallest percent of boys and girls involved in agriculture (9 percent of boys and girls). There is no difference in the percent of boys involved in agriculture in female headed households compared to male headed households and there is no difference in the percent of girls involved in agriculture between male and female headed households. Thirty percent more elderly males compared to elderly females in male headed households are involved in agriculture in the region. Pwani region has the smallest percent of households storing crops (25% of households) and there is no difference in the percent of households storing crops between male and female headed households. More female headed households store crops in locally made traditional cribs compared to male headed households and it has the highest percent difference in storage in modern stores in favour of female headed households. This is in contrast to male headed households where a higher percent of male headed households store crops in sacks/open drums and improved cribs compared to female headed households. Male headed households have 25 percentage points more households having up to a quarter loss compared to female headed households. A higher percent of male headed households process crops in Pwani region compared to female headed households. Very little credit is provided in Pwani region (1% of households) and slightly more is provided to male headed households, The main reason for not using credit is that they do not know how to access it followed by not available and don’t know about credit. The region has the one of the smallest percent of households with modern roofing material in the country (41% of households in the region) and there is no difference between male and female headed households. Most households use wick lamps/firewood and there is no difference between male and female headed households. Most households use firewood for cooking and there is no difference between male and female headed households. The region has a small percent of households with piped drinking water (10%) and there is little difference between male and female headed households. Nine percent of households have no toilets and female headed households have 3 percentage points more compared to male headed households. The difference in the ownership of assets (radio, iron and bicycle) between male and female households is high, in favour of male headed households, for all regions. Pwani has a moderate percent of households with radios and irons and it has a comparatively high percent of bicycles. In Pwani male headed households have 27 percentage points more radios, 7 percentage points more irons and 32 percentage points more bicycles than female headed households. There is no difference between male and female headed households in the number of meals household members eat per day in all regions. In Pwani region, a higher percent of male headed households eat meat more times per meek than female headed households and the difference is comparatively moderate. Pwani region has a small to moderate difference between male and female headed households in the percent of households facing food shortages (about 7 percentage points more female headed households face food shortage problems compared to male headed households). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 4.2 District Profiles The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Bagamoyo Bagamoyo district had the largest number of households in the region one quarter of which were involved in smallholder agriculture in the region. Most smallholders were either involved in crops only or crops and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bagamoyo district was annual crop farming, followed by tree/forest resources and off farm income activity. The district had the third highest percent of households with no off- farm activities and more than a ninety percent of its total households having more than one member with off-farm income. The percentage was second highest for the agricultural households with off farm income. Compared to other districts in the region, Bagamoyo had the second highest percent of female headed households (28%) but was ranked 5th in the average age of household heads (48.8 years). With an average household size of 5.1 members per household it had the third highest for the region. The district had the highest literacy rate among smallholder households and this was also reflected by the highest level of school attendance in the region. The literacy rate for the heads of household was high compared to most districts in the region. However the situation in the region is that the majority of heads of agricultural households (54%) had primary level education whereas only 3% had post primary education. Bagamoyo had the smallest percentage (68%) of utilized land area indicating that the available or usable land for agricultural activities was not fully utilized like that of Mafia which was highest (94%). The total planted area was the largest in the region due to the presence of good wet and dry seasons. It had the second highest planted area per household (1.8ha). Also Bagamoyo ranked 3rd highest in quantity harvested. The average areas planted with annual crops in small holdings during the short and long rainy seasons were 0.52ha and 0.59ha respectively. The planted area for cereals crops (maize, paddy, sorghum, finger millet and bulrush millet) and maize in particular ranked first in the region. Bagamoyo ranked first in planted area for maize with a planted area of 37,477 ha. Bagamoyo was also the leading district in regard to the size of planted area per maize-growing households in the region. Paddy production ranked 3rd with a planted area of only 5,226 hectares and the production of sorghum though on a planted area of 1,887 hectares was highest in the region. Area planted with cassava was the 4th largest and the production was moderate accounting for 12 percent of the total cassava harvested, and it was the region’s second favourite annual crop. Among the six grouped categories of annual crops, the production of pulses in Bagamoyo was the highest in the region with a planted area of 7,332ha (42%). In terms of planted area for oilseeds and oilnuts, Bagamoyo ranked first in the region accounting for 64.1% of the total planted area. However the district ranked 4th in groundnuts which was the region’s 14th crop in terms of planted area. Sunflower was grown only in Bagamoyo district, in the long rain season. Vegetable production was of moderate importance in the district as it was second lowest in terms of planted area. It ranked third in the area planted with tomatoes (80ha.) as well as for water mellon (20ha). Chillies production was insignificant even in the region except for Mkuranga’s 6ha planted area. Total traditional cash crops grown in Pwani were contributed by cotton in Bagamoyo (141ha.) and seaweed in Mafia district (354ha.). Compared to other districts in the region, Bagamoyo had the second largest planted area for permanent crops (19.3%) which were dominated by cashewnuts (6,214 ha), coconuts (3,155 ha), oranges (2001 ha), pineapples (1,762 ha), mango (1,261 ha), bananas (790 ha), pawpaw (207 ha) and pigeon peas (206 ha). Other permanent crops were either not grown or were grown in very small quantities. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 104 As with other districts in the region, most land clearing and preparation was done by bush clearance or leaving the land without clearing. Ploughing was mainly done using the traditional handhoe (94.7% of planted area during the long rainy season and 96% during the two combined seasons) followed by tractor and oxen ploughing. The use of inputs in the region was very small, however district differences existed. Bagamoyo had the largest planted area applied with improved seeds in the region and this was due to the highest planted area of cereals followed by pulses and had the largest number of households using improved seeds. The district had the largest planted area with fertilizers (farm yard manure, compost and inorganic fertilisers), however most of this was compost. Compared to other districts in the region, Bagamoyo district ranked 4th in the level of insecticides use as well as fungicides. It had the second largest area under irrigation compared to other districts. The most common sources of water for irrigation were rivers and wells. Bucket/watering cans and flood water were the most common means of irrigation water application and only a very small amount of sprinkler irrigation was used. Use of water hose was insignificant. The most common method of crop storage was in locally made traditional cribs followed by sacks and open drums. However the proportion of households storing crops in the district was third highest, with the highest quantity in tons of stored crops than other districts in the region. The district had the largest number of households selling crops. Regarding those who did not sell, the main reason for not selling was insufficient production followed by prices being too low. The district had the 4th highest percent of households processing crops in the region and almost all processing was done using neighbour’s machine. The district had the least percent of households selling processed crops and the portion sold was to other unspecified groups, followed by traders on farm. Although very small, credit in the district was only accessed by male headed households and the sole source was from commercial banks option. The largest number of households receiving extension services was in Bagamoyo and most of this was from the government (96%). The quality of extension services was rated between good and very good by the majority of the households. Tree farming was of low importance in Bagamoyo (with 40,698 or 11.6% planted trees) and most of these were tectona grandis spp. The households ranked fifth or 8% of those involved with erosion control and water harvesting structures in Pwani region. These structures were mostly erosion control bunds followed by tree belts. The district had the largest number of cattle in the region and they were almost all indigenous followed by dairy. The district also ranked first in the production of goats, sheep and chicken but had the least number of pigs. Although small, the district had the largest number of layers in the region but no broilers. It ranked first in number of ducks, rabbits and other unspecified livestock; but no turkeys or donkeys were found in the district. The largest number of households reporting tsetse and tick problems were recorded in Bagamoyo district and it had the largest number of households de- worming livestock (54% of the region’s households reporting on this). The use of draft animals in the district was absent; fish farming was not only absent in the district but also in the region. It had a second best access to secondary schools, primary schools, health clinics and primary markets compared to other districts . It also had a better access to tarmac roads, all weather roads and the regional capital. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 105 Bagamoyo district had the second highest percent of households with no toilet facilities (25.4%). It had the highest percent of households owning a radio, bicycle, iron, mobile phones, wheelbarrow, vehicle and tv/video but the lowest in landline phones. It ranked first in percentage (38%) of households using mains electricity. The most common source of energy for lighting was the wick lamp (ranked first though constituted a quarter of all households in the region using this lighting facility) and practically the district ranked first in households using firewood for cooking accounting for 25% of total households in the region who reported using this source of energy. The district had the smallest percent of households with grass roofs, ranking 5th although 53% of its households confirmed of grass roofs and 34% confirmed about iron sheet roofs ranking second in the region. The most common source of drinking water in the region in the wet season was from unprotected wells followed by piped water and surface water. Bagamoyo ranked first in households using piped water (58%) and also ranked first in use of surface water (lakes/dams/rivers/streams) accounting for 45% in the region. It had the highest percent of households in the district having three meals per day compared to other districts and one quarter of its households has 2 meals per day, ranking 4th in the region. The district had the highest percent of households that did not eat meat (27%) and highest percent (50%) who did not eat fish during the week prior to enumeration. However most households never had problems with food satisfaction, ranking second in the region. 4.2.2 Kibaha Kibaha district ranked 4th in the number of households in Pwani region and had the second smallest percent of households involved in smallholder agriculture. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households and no pastoralists. No pastoralists were captured by this Census in Pwani region. The most important livelihood activity for smallholder households in Kibaha district was annual crop farming, followed by off-farm income then permanent crop farming. The district had the 3rd lowest percent of households with no off-farm activities and had the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kibaha had the second highest percent of female headed households (20%) and it had a moderately high average age for the household heads in the region (49.1 years). Its average household size of 4.5 members per household was the lowest in the region. Next to Mafia, Kibaha had a significantly high literacy rate among smallholder households though not reflected the level of school attendance which was moderately low. It had the third largest utilized land area per household (1.7ha) and 77 percent of the available area was currently being utilised. The district had the second lowest planted area per household in the region, and the third highest in average planted area per household being 0.53ha. in the combined seasons or 0.65ha in the long rainy season and 0.31 in the short rainy season. The district ranked fifth in maize production in the region with a planted area of over 5,215ha, but the planted area per maize growing household came second in the region. The district had the third lowest planted area of paddy in the region with 3,794 hectares. The area planted per sorghum household came second. Although bulrush millet was grown no production was recorded. Finger millet, wheat and barley were not grown in the district. Cassava production was second lowest, accounting for 7 percent of the quantity harvested in the region. The production of beans in Kibaha district was highest with a planted area of 12ha., and also ranked highest in area planted per household (0.21ha.) Kibaha district had the second smallest oilseeds crops planted area in Pwani region with a planted area of 123 ha. The district came third in DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 106 groundnut crop planted area with a planted area per groundnut growing household of 0.2 ha an area which was close to the region’s average. Sunflower was not grown in Kibaha district. Vegetable production was of great importance in the district and had the largest planted area for tomatoes (458 ha) in the region but came fourth in production of water melon. No planted area was recorded for chillies, radish, onions, cabbage, spinnach and bitter aubergine although they were grown elsewhere in the region. Okra was grown but no production was recorded. Traditional cash crops (e.g. tobacco and cotton) were not grown in Kibaha district. Compared to other districts in the region, Kibaha had the smallest planted area for permanent crops (6%) which was dominated by cashewnuts (2,062 ha), coconuts 1,317 ha), oranges (1,201 ha), grapefruits (149 ha), and bananas (64 ha) and pigeon peas (46 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation were done by hand slashing, however a very small amount of land preparation was done by bush clearance followed by the option of no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Kibaha had the second largest area planted with improved seeds in the region and this was due to the dominance of cereals and pulses within the district. It had the third highest proportion of households using improved seeds. The district had the third largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), most of which was farm yard manure. Compared to other districts in the region, Kibaha district had the highest level of insecticides use. The use of fungicides was the second highest but it had the fourth application of herbicides in the region. With 467ha of irrigated land, it had the second largest area under irrigation. The most common source of water for irrigation were rivers using gravity as well as wells. Bucket/watering cans and water hose were the two most common means of irrigation water application in the district. The most common method of crop storage in Kibaha district was sacks/open drums followed by locally made cribs. Of the households storing crops in the district, it ranked second in quantity stored. Kibaha district had the second least number of households selling crops. Kibaha was among the districts with the lowest percent of households processing crops in Pwani region and this was almost all done on farm by hand. No agricultural households accessed credit in the district. The district had the second least number of households that received extension services and all of these were from the government (95%) and large scale farms. The quality of extension services was rated between good and average by the majority of the households. Tree farming was of highest importance in Kibaha (with 226,797 planted trees or 64.5%) and most trees were melicia excelsa, senna spp, acacia spp and eucalyptus spp. The 3rd highest proportion of households with erosion control and water harvesting structures was found in Kibaha district and these were mostly erosion control bunds and tree belts. Also Kibaha had use of terraces and dams not recorded in the other districts. The district had the 3rd largest number of cattle as well as sheep, goats and pigs in the region and about 77.4% of cattle were indigenous, followed by dairy cattle. It ranked fifth in the number of chicken in the region and most of those were broilers. Ducks, turkeys, rabbits and other livestock in the district were insignificant in number. It ranked fifth in the DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 107 number of households that reported tsetse and tick problems had the second highest percent of households de-worming livestock. The district had no households using draft animals or fish farming. It had the best access to secondary schools, primary schools, primary and secondary markets compared to other districts. It also had one the best accesses to all weather roads, regional capital, feeder roads and tarmac roads. The percentages of households without toilet facility in Kibaha district was 6 percent and this was the lowest in the region. Also it ranked fifth in percentage of households that owned various household assets and these were radios, bicycles, irons, mobile phones, wheelbarrows but had a moderate number of households owning landline phones, vehicles and tv/video. The most common source of energy for lighting was the wick lamp followed by the hurricane lamp and mains electricity. Practically all the agricultural households used firewood for cooking followed by charcoal. Within the district, roofing materials were grass/leaves (52% and ranked last in region), and iron sheets (46%, ranking first in region). The most common source of drinking water in the wet season was from piped water followed by unprotected wells and surface water. Though it ranked last, half of its households reported having three meals per day. However it ranked first in households having two meals compared to other districts. The district had the second lowest percent of households that did not eat meat but a higher percent of those that did not eat fish during the week prior to enumeration. A moderately low number of households seldom had problems with food satisfaction and ranked fourth accounting for 12% in the region regarding this aspect. 4.2.3 Kisarawe Kisarawe district had the second least number of households in the region and it had the fourth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Kisarawe district was permanent crop farming, followed by annual crop farming and then tree/forest resources. However, the district had the lowest percent of households with no off-farm activities and third lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kisarawe had the second lowest percent of female headed households (16%) but second highest average age of the household heads in the region. Its average household size of 4.6 members per household was below the average for the region. Kisarawe had a comparatively moderate literacy rate among smallholder households and this was reflected by the relatively moderate level of school attendance in the region. The literacy rate for the heads of household was the second in the region. It had the second least utilized land area per household (1.5ha) and lower than the regional average of 1.8ha. Ninety one percent of the allocated area was currently being utilised. The total planted area was 3rd lowest in the region due to the absence of good wet and dry seasons. Also it had the second lowest planted area per household (0.42ha). The district came fourth in maize production in the region with a planted area of over 6,472ha. The planted area per household was 0.4ha which was the second lowest in the region. In paddy production it came fifth in the region. with a planted area of 1,707 hectares. Bulrush millet, finger millet, wheat and barley were not produced in the district. The district had the third largest planted area for cassava accounting for 19.1 percent of the cassava planted area in the region but first in quantity harvested (31%). The production of beans in Kisarawe was important as it ranked second in planted area. Oilseed crops were important in Kisarawe with 38 percent of the region’s planted for groundnuts being in that DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 108 district. Sunflower was not grown in the district. Vegetable production was fairly important in the district and it had the fourth largest planted area for tomatoes and the second largest for water mellon (64 ha and 27 ha respectively) and accounted for 12 percent of the tomato production and 14 percent of the water mellon production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Kisarawe district. Permanent crops were fairly important in Kisarawe district as 12.7% of the total permanent crop planted area in Pwani region was found in the district. The most prominent permanent crops in the district were cashew nuts (3,541 ha), oranges (1,937 ha), coconuts (1,575 ha), bananas (1,100 ha), jackfruits (1,042 ha), pigeon peas (441 ha), mango (302 ha.) and pawpaws (170 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was also done by bush clearance followed by no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Kisarawe had the third largest planted with improved seeds and this was due to the dominance of cereals, roots and tubers crops. However, it had the fourth highest percentage of households using improved seeds. The district had the fourth largest area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), and most of this was compost. Compared to other districts in the region, Kisarawe district had the second least application of insecticides and fungicides, and it came last in the use of herbicides. It had the second least area under irrigation with 193 ha of irrigated land. The most common source of water for irrigation was the well, using hand bucket. Bucket/watering cans was the most common means of irrigation water application. The most common method of crop storage in Kisarawe was locally made traditional crib. However the proportion of households storing crops in the district was second highest in the region but the quantity stored was the least. The district had the fourth highest percent of households selling crops, however for those few that did not sell, the main reason for not selling was insufficient production followed by trade union problems. Kisarawe district ranked first in processing crops and almost all of it was done on farm by hand and to a lesser extent, using a neighbour’s machine. The district had the fourth highest percent of households selling processed crops and selling to neighbours ranking high in the district. No households accessed credit in the district. Kisarawe had the second largest number of households receiving crop extension services most of which were from the government (98%). The quality of extension services was rated between good and average by the majority of the households. Tree farming was of low priority in Kisarawe district (with 27,184 planted trees, 7.7%) and these were mostly cyprus spp, moringa spp, with some senna spp. The fourth highest proportion of households with water harvesting bunds and erosion control bunds were found in Kisarawe district. It also had the only recorded gabions/sandbags in the region as a measure against erosion in the region. The district had 2.6% of the total cattle in the region and ranked fifth. The cattle were almost all indigenous followed by the dairy breed. In regard to the number of goats it came fourth and there was no sheep production recorded. It had the least number of pigs in the region (2,226 or 61%) and one of the least number of chicken ranking fourth. Most of the chicken were of the indigenous breed followed by layers and broilers breeds. However, the district had around 14% of all the indigenous chicken in the region. As for improved breed, it ranked second in layers and highest in the number of broilers. The district had the fourth largest number of ducks, and no rabbits nor donkeys recorded but ranked second in rabbits. All DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 109 other unspecified types of other livestock category in the region were not recorded in Kisarawe . It had the third highest number of households reporting tsetse and tick problems. Though small, de-worming of livestock was moderately practiced as it ranked fifth. Kisarawe did not use draft animals to cultivate the land; also it did not practice fish farming. It had moderate access to secondary schools, primary schools, health clinics, feeder roads, all weather roads and primary markets compared to other districts. Also it had a moderate access to feeder roads and the regional capital. Kisarawe district had the second lowest percent (6.8%) of households with no toilet facilities and it was among the high percentages of households owning household facilities in general ranking fourth in the region. It owned radio, bicycles, iron, wheel barrows, Tv/video and vehicles; had the lowest percent of landlines and mobile phones. It had the second least number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp followed by hurricane lamp, firewood and pressure lamp. Practically all households used firewood for cooking. The district had the fourth highest percent of households with grass roofs (65%) and 26 percent of households having iron sheets roofing. The most common source of drinking water was the unprotected well followed by uncovered rainwater catchments. Thirty eight percent of the households in the district reported having one or two meals per day and it ranked first in households which reported having three meals per day at most. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration, however the district had the highest percentage of its households that often had problems with food satisfaction than the other categories. 4.2.4 Mkuranga Mkuranga district had the third largest number of households in the region and it had about one quarter of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had neither livestock only households nor pastoralists. The most important livelihood activity for smallholder households in Mkuranga district was permanent crop farming, followed by annual crop farming and off farm income. However, the district had the highest percent of households with no off-farm activities and one quarter of its total households with more than one member with off-farm income. Compared to other districts in the region, Mkuranga had the third highest percent of female headed households (22%) and was the first in average age of the household heads (50.8 years). With an average household size of 5.2 members per household it had the second highest for the region. Mkuranga had a comparatively high literacy rate among smallholder households and this was reflected by the concomitant high level of school attendance in the region.. The literacy rate for the heads of household was also higher than most of districts in the region. It had the highest utilized land area per household (2.12ha) and above the regional average of 1.8ha. indicating that the allocated area was almost fully utilized (86%). The total planted area was the second largest in the region due to the presence of good wet and dry seasons, however it had the fourth highest planted area per household (0.5ha) and ranks second highest in the number of smallholders in the district. The district ranked third in planted area for maize production in the region with a planted area of 8,413 ha, and the planted area per household was third lowest in the region. Paddy production was very important with a planted area of 5,837 hectares but the production of sorghum was insignificant. Cassava production was also very important accounting for 24 percent of the quantity harvested in the region. The district had the largest planted area of cassava, a crop which ranked second in the region (after maize) in terms of the area planted with annual crops (17,569 ha). The production of beans was DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 110 nil, were produced only in Kibaha, Kisarawe and Bagamoyo districts only. Oilseed crops were not important in Mkuranga and accounted for 7.1% of all oilseed crops planted area in the region. However it ranked second in the production of groundnuts which was the region’s 11th crop nationally in terms of planted area. Sunflower was not grown in Mkuranga district. Vegetable production was very important, ranking first in the region. It had the second largest area planted with tomatoes as well as water mellon (237 ha and 242 ha respectively). However, it was the only district with planted area for chillies and accounted for 100 percent of the chillies production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Mkuranga district. Compared to other districts in the region, Mkuranga ranked first in planted area with permanent crops (36%) which was dominated by cashewnuts (19,636 ha), coconuts (4,569 ha), mandarines/tangerines (1,190 ha), oranges (1,162 ha), pinaeapples (906 ha), pigeon peas (613 ha), and mangoes (457 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was done by bush clearance followed by option of no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Mkuranga had the third largest area planted with improved seeds in Pwani region and this was due to the high planted area of vegetables and ranked second in the number of households using improved seeds. The district had the second largest planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), most of which was compost. Compared to other districts in the region, Mkuranga district ranked second in the level of insecticides use. In the use of fungicides although small, it ranked first in the region and in the use of herbicides it ranked second. It had the largest area under irrigation compared to other districts with 1,974 ha of irrigated land. The most common sources of water for irrigation were wells and canals. Bucket/watering cans and flood water were the most common means of irrigation water application. The most common method of crop storage was locally made traditional cribs where it ranked fourth in the region, however the proportion of households storing crops in the district was moderate, with moderate quantities in tons of stored crops in the region. The district had the third largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. It was the second highest percent of households processing crops in Pwani region and almost all processing was done on farm by hand followed by on farm by machine. The district also had a high percentage of households selling processed crops to traders at farm and no sales were made to marketing cooperatives. The distribution of households accessing credit was 89% for male headed households and 11% for female headed households. The main sources were savings and credit, NGO’s traders/trade stores and lastly, family friends and relatives. Mkuranga had the third largest number of households receiving extension services and most of these were from the government (95%). The quality of extension services was rated between good and very good by the majority of the households. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 111 Tree farming was of low importance in Mkuranga (with 14,512 or 4.1% planted trees) and most of these were eucalyptus, azadritachta spp and cyprus spp. The highest proportion of households with erosion control and water harvesting structures were found in Mkuranga district and these were mostly tree belts and erosion control bunds. It had the highest number of vetiver grass, unlike other districts which had none. The district had the least number of cattle in the region and they were almost all improved dairy followed by indigenous. Goats and also sheep were among lowest. Pigs production ranked second compared to other districts in the region. It had a large number of chicken (all indigenous) and ranked second in turkeys, but no ducks, rabbits or donkeys were recorded. It had the least number of households reporting tsetse and tick problems and it also had the least number of households de- worming livestock. No draft animals were used in the district and there was also no fish farming. It had a better access to health clinics, hospitals and primary and secondary markets compared to other districts. It also had a better access to feeder roads and tarmac roads. Mkuranga district had 14.5% of households in the region with no toilet facilities and in this it ranked fourth in the region. It also ranked fourth in the percentage of households owning radios, bicycles, irons, wheelbarrows and tv/videos but the lowest in mobile phones, and vehicles. It had a low number of households (7%) using mains electricity in the region. The most common source of energy for lighting was the wick lamp followed by hurricane lamp and practically all households used firewood for cooking having a quarter of total households that used firewood in the region. The district had the second highest percent (78%) of households with grass roofs and 20 percent of households having iron sheets. The most common source of drinking water in the wet season was the unprotected well followed by unprotected springs. It had the highest percent of households having one meal per day compared to other districts and two thirds of its households have 3 meals per day. The district had the second highest percent of households that did not eat meat and second lowest percent (4%) who did not eat fish during the week prior to enumeration. However most households never had problems with food satisfaction, ranking first in the region. 4.2.5 Rufiji Rufiji district had the second largest number of households in the region and it had the second highest percent of households involved in smallholder agriculture. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Rufiji district was annual crop farming, followed by tree/forest resources and permanent crop farming. The district had the second highest percent of households with no off- farm activities and had the third highest percent of households with more than one member with off-farm income. Rufiji had very few households with more than one member having off farm income. Compared to other districts in the region, Rufiji had the second highest percent of female headed households (25%) and it had one of the high average age of the household head in the region (49 years). With a household size of 5.4 members per household it had the highest for the region. Rufiji had a low literacy rate among smallholder households and this was reflected by the district having a moderate level of school attendance and highest percentage of those who never attended school. It had the fourth largest utilized land area per household (1.6ha) and 86 percent of the allocated area was currently being utilised. The district had the third highest planted area in the region, and second highest in planted area per household either season (0.69ha in the long rainy season and 0.47ha in the short rainy season). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 112 The district was second in importance for maize production in the region with a planted area of over 12,653ha, and the planted area per maize growing household was also high for the region. The district had the largest planted area of paddy in the region with 10,516 hectares. Bulrush millet, and wheat were not grown in the district; however, sorghum was very important and it ranked second in planted area. Cassava production was important, accounting for 25 percent of the quantity harvested in the region. The production of beans in Rufiji district was insignificant. Rufiji district had the second largest planted area for oilseeds crops with a planted area of 559ha. The district was second least in groundnuts planted area and a planted area per groundnut growing household of 0.2ha an area which was lower than the region’s average. In Rufiji district, vegetable production ranked third in importance and it had the smallest planted area for tomatoes (25ha.) and no water mellon. No planted area was recorded for chillies, cucumbers, eggplants, onions and cabbages although they were grown elsewhere in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in Rufiji district. Compared to other districts in the region, Rufiji had third largest planted area for permanent crops (18.7%) which were dominated by cashewnuts (10,591 ha), coconuts (1,906 ha), oranges (1,294 ha), pineapples (533 ha), bananas (484 ha), pigeon peas (207 ha), and mangoes (160 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however a very small amount of land preparation was done by bush clearance followed by no land clearing. Ploughing was by hand hoe followed by oxen then tractor ploughing. The use of inputs in the region was very small, however district differences existed. Rufiji had second least area planted with improved seeds in the region and this was due to the moderate planted area of cereals and cassava. However, it had the second least proportion of households using improved seeds. The district had the least planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers) and most of this was compost. Compared to other districts in the region, Rufiji district ranked third in the level of insecticides use. In the use of fungicides it ranked third and in the application of herbicides it ranked first in the region. It had the third largest area under irrigation compared to other districts with 298 ha of irrigated land. The most common sources of water for irrigation were wells and rivers using gravity. Flood water and bucket/watering cans were the two means of irrigation water application in Rufiji district. The most common method of crop storage in Rufiji district was locally made traditional structure followed by sacks/open drums; however the quantity in tons of stored crops in the district ranked second. Rufiji district was second in the number of households selling crops in the region. Rufiji was among the districts with the highest percent of households processing crops in the region and almost all processing was done on farm by hand. Although very small, access to credit in the district was to male headed households only and the source was religious organisations/NGO’s/projects only. A moderately large number of households received extension services in Rufiji district and these were from the government (100%). The quality of extension services was rated between good and very good by the majority of the households. Tree farming was third highest in the region (with 39,439 planted trees or 11.2%) and most trees were tectona and leucena spp. There were no households with erosion control and water harvesting structures in Rufiji district The district had the fourth largest number of cattle in the region and they were mostly indigenous followed by improved beef. In goats and sheep production it ranked second but had no pigs. It had the third largest number of chicken mostly indigenous and layers but no broilers. In ducks and rabbits production it ranked third but no turkeys and donkeys were found in the district. It had the least number of households reporting tsetse and tick problems and the lowest percent of households de-worming livestock. The district had no households using draft animals or involved in fish farming. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 113 It had a fairly good access to secondary schools, primary schools, primary markets compared to other districts but also had one of the worst access to the regional capital. The percentage of households without toilet facility in Rufiji district was highest in the region (32 percent). It was among the districts with moderately high percent of households owning radios, tv/video and mobile phones and a moderate number owning bicycles but ranked first in wheelbarrows. Next to Bagamoyo, it ranked second highest in the number of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp. Rufiji ranked third and practically all households used firewood for cooking accounting for 22% of total households that used firewood in the region. The district had the third highest percent (71%) of its households with grass roofs and ranked fifth with 18 percent of its households having iron sheets. The common source of drinking water in the wet season was from unprotected wells and unprotected springs. It had moderate to low percent of households having one to two meals per day compared to other districts and two thirds of its households have 3 meals per day. The district had one of the highest percentages of households that did not eat meat but among lowest percentages of who did not eat fish during the week prior to enumeration. However most households never experienced problems with food satisfaction, ranking third in the region. 4.2.6 Mafia Mafia district had the smallest number of households in the region as well as the lowest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crops only, followed by crops and livestock. It had a very small number of livestock only households. The most important livelihood activity for smallholder households in Mafia district was annual crop farming, followed by permanent crop farming and off farm income. However, the district had the second lowest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mafia had the lowest percent of female headed households (3%) and also the lowest average age of the household head in the region (45 years). With an average household size of 4.5 members per household it almost had the average for the region. Mafia had the highest literacy rate among smallholder households members but this was not reflected by the low level of school attendance in the region. It also had the lowest percentage of heads of agricultural households with both primary education and secondary education. It had the least utilized land area per household (1.4ha) far below the regional average of 1.8ha but ranked first in percentage of the allocated area currently being utilized (94%). The total planted area was the lowest in the region due to the absence of good wet and dry seasons. Also it had the lowest planted area per household (0.37ha) attributed to the lowest in the region the number of smallholders in the district. The area planted per household was lowest in the long rainy season but ranked third lowest in the short rainy season. The district was not important for maize production in the region with a planted area of about 90ha. and the planted area per household was 0.2ha which was the lowest in the region. Paddy production an annual crop which came third in the region after cassava and maize was of low importance with a planted area of 1,431 hectares. Bulrush millet, sorghum, finger millet, wheat and barley were not produced in the district. The district had the smallest planted area of cassava accounting for 1.7 percent of the cassava production in the region. Beans were not produced in Mafia. Oilseed crops were of less importance in Mafia with less than 1 percent of the groundnuts grown in the district. Sunflower was not grown in the district. Vegetable production was less important in the district. It had the second least planted area for tomatoes and no water mellon (31 ha) than other districts in the region and accounted for 3.3 percent of the tomato production in the region. The only traditional cash crop grown in Mafia was seaweed (100%). DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 114 Permanent crops were of least importance in Mafia district and planted area with permanent crops (7.8%) were dominated by coconuts (4,778 ha), bananas (920 ha), pineapples (372 ha), cashewnuts (220 ha), mangoes (50 ha) and oranges (40 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation were done by hand, however a very small area of land preparation was done by bush clearance followed by no land clearing.. Ploughing was by hand hoe followed by oxen but no tractor ploughing. The use of inputs in the region was very small, however district differences existed. Mafia had the least area planted with improved seeds in Pwani region and this was due to limited agricultural activity. It also had the least percentage of households using improved seeds. The district had the second least planted area applied with fertilizers (farm yard manure, compost and inorganic fertilisers), however it ranked first in the use of farm yard manure and inorganic fertilizers. Compared to other districts in the region, Mafia district had the least application of insecticides and fungicides to its planted area and ranked third in herbicides. It had the least area under irrigation compared to other districts with 32 ha of irrigated land. The most common sources of water for irrigation were wells and rivers using hand bucket and gravity. Bucket/watering cans and flood water were the most common means of irrigation water application. The most common method of crop storage in Mafia was sacks and open drums, in which it ranked first followed by Kibaha. The proportion of households storing crops in the district was highest in the region and it ranked third in quantity in tons of crops stored in the region. The district had the least percent of households selling crops, however for those few that did not sell, the main reason for not selling was insufficient production followed by trade union problems. Mafia district was one of the districts in Pwani region with lowest percent (4%) of households processing crops and all processing was done on farm by hand. The district had the second least percent of households selling processed crops (35%) and all sales were to neighbours. There was no incidence of access to credit in the district. Mafia had the least number of households receiving crop extension services and most of these were from the government (82%). The quality of extension services was rated between good and average by the majority of the households. In tree farming it was last in the region (with 2,879 planted trees or 0.8%) and these were mostly moringa spp, with some melicia excelsa. The second highest proportion of households with water harvesting bunds and erosion control bunds. The district had the second largest number of cattle in the region though only one tenth of the total in region and these were 84% indigenous followed by dairy and beef. Goats and sheep production were notably absent in Mafia as was the case with Kisarawe. Mafia had no pigs and had the least number of chicken most of which were indigenous followed by layers. The district had a large number of ducks, turkeys (97% and highest in region), but no rabbits. All other unspecified types under other livestock were found in Mafia ranking second in the region or 3%. It had the second highest number of households reporting tsetse and tick problems. Although small, de-worming of livestock was moderately practiced. Mafia was the only district in the region using draft animals to cultivate the land. No fish farming was practiced in any district in Pwani region. It had a poor access to tarmac roads, tertiary markets, regional capital, secondary schools, primary schools, feeder roads, all weather roads and primary markets compared to other districts but it had a good access to health clinics. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 115 The percentage of households without toilet facility in Mafia district was third highest in the region (16 percent). Though it ranked first in radio ownership, it had the lowest percent (4%) of households owning assets in general and ranked last in wheelbarrows and bicycles. It ranked last in the percentage (3%) of households using mains electricity in the region. The most common source of energy for lighting was the wick lamp but Mafia was the least user of wick lamps and the hurricane lamps. Firewood was used in Mafia for cooking accounting for 4.2% of total households that used firewood in the region. The district had the highest percent (91%) of its households with grass roofs and lowest percent (9%) with iron sheets much below the region’s average of 27%. The common source of drinking water in the wet season was from unprotected wells followed by protected wells and uncovered rain-water catchments. It had moderate to low percent of households having two meals per day compared to other districts but among the highest with its households having 3 meals per day. The district had the least percentages of households that neither ate meat nor fish during the week prior to enumeration. Although almost half of the households (47%) within the district never experienced problems with food satisfaction, the district came last compared to other districts as it accounted for 8% of total households that never had such problems in the region. APPENDIX II 116 4. APPENDICES APPENDIX I Tabulation List ............................................................................................................................. 117 APPENDIX II Tables............................................................................................................................................. 132 APPENDIX III Questionnaires.............................................................................................................................. 273 APPENDIX II 117 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD....................................................................................................... 132 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 133 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year. 133 NUMBER OF AGRICULTURE HOUSEHOLDS............................................................................................... 134 3.0 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year .................................................................................. 135 3.1 The livelyhood Activities/Source of Income of the Households Ranked in Order of Importance by District.................................................................................................................. 135 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.......................................................................... 136 3.1a First Most Importance................................................................................................................................. 137 3.1b Second Most Importance ............................................................................................................................ 137 3.1c Third Most Importance ............................................................................................................................... 137 3.1d Fourth Most Importance ............................................................................................................................. 137 3.1e Fifth Most Importance ................................................................................................................................ 137 3.1f Sixth Most Importance................................................................................................................................ 138 3.1g Seventh Most Importance ........................................................................................................................... 138 HOUSEHOLDS DEMOGRAPHS......................................................................................................................... 140 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) ...................................................................................................................................................... 141 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (Column %)................................................................................................................................................ 141 3.4 Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year...... 142 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year ................................................ 142 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ......................................................................................................................... 142 3.7 Number of Agricultural Household Members by Main Activity and District ............................................ 142 cont… Number of Agricultural Household Members by Main Activity and District................................. 143 cont… Number of Agricultural Household Members by Main Activity and District................................. 143 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year .......................................................................................................................... 143 APPENDIX II 118 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year .......................................................................................................................... 144 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year..................................................................................................... 145 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year .................................................................. 145 3.12 Number of Heads of Agricultural Households by Maximum Education Level Attained and District, 2002/03 Agricultural Year`......................................................................................................................... 145 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District.......................................... 145 3.14 Time Series of Male and Female Headed Households ............................................................................... 146 3.15 Literacy Rate of Heads of Households by Sex and District........................................................................ 146 LAND USE............................................................................................................................................................... 148 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year149 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year ........................... 149 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year...................................................................................................... 149 5.4 Number of Agricultural Households by whether they consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year............................................................... 149 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year................................................... 149 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION SHORT AND LONG RAINY SEASONS.... 152 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District. .......................... 153 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District...................................... 153 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 154 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 – Short and Long Rainy Seasons, Pwani Region ....................................... 155 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Short and Long Rainy Season, Pwani ..................................................................................... 156 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season, Pwani ................................................. 156 APPENDIX II 119 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District Short and Long Rainy Season, 2002/03 Agriculture Year......................................................................... 156 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season. .......................................................... 157 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season............................................................. 157 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season Season................................................. 158 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Short and Long Rainy Season Season................................................. 158 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON ............................................. 160 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District – LONG RAINY SEASON, Pwani Region................................................................................... 161 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Pwani Region .............................. 161 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during LONG RAINY SEASON, 2002/03 Agriculture Year, Pwani Region................................ 161 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 162 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 162 7.2f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON....................................................... 163 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON ................................................................ 163 7.2h Planted Area and Number of Crop Growing Households During LONG RAINY SEASON by Method of Land Clearing and Crops; 2002/03 Agriculture Year............................................................................. 165 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 166 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year.......................................................... 166 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 166 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 166 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 167 APPENDIX II 120 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrush millet Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 167 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 167 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet Potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 167 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 168 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 169 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 169 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 169 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 169 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Pigeon peas Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 170 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 170 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Water melon Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 171 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ......................................................................................... 171 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 APPENDIX II 121 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 172 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year .......................................................................................... 173 PERMANENT CROPS .......................................................................................................................................... 174 7.3.1 Production of Permanent Crops by Crop Type and District – Pwani.......................................................... 175 7.3.2 Area Planted by Crop Type - Pwani Region............................................................................................... 178 7.3.3 Area Planted with Cashew nuts Coconuts by District................................................................................. 178 7.3.4 Area planted with Coconuts by District...................................................................................................... 178 7.3.5 Area planted with Orange by District ......................................................................................................... 179 7.3.6 Area Planted with Pineapples by District.................................................................................................... 179 7.3.7 Planted Area with Fertilizer by Fertilizer Type and Crop........................................................................... 179 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 180 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 180 cont… Planted Area with Fertilizer by Fertilizer Type and Crop............................................................... 181 AGROPROCESSING............................................................................................................................................. 182 8.1.1a Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year ............................................................................................................. 183 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year183 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Pwani Region .............................................................................................................. 183 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Pwani Region ........................................ 184 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Pwani Region.... 184 APPENDIX II 122 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Pwani Region....................................................................................... 185 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Pwani Region.......................................................................... 185 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Pwani Region................................................................................................... 185 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Pwani Region................................................................................................... 185 MARKETING ......................................................................................................................................................... 186 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Pwani Region...................................................................................................... 187 10.2 Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Pwani Region........................................................................ 187 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Pwani Region ...................................................................................... 187 IRRIGATION/EROSION CONTROL ................................................................................................................. 188 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District ....................................................................................................................... 189 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year ................... 189 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year............................................................................................ 189 11.4 Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year............................................................................................................... 189 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year ................................................................................ 190 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District....... 190 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year..................................................................................................... 190 ACCESS TO FARM INPUTS................................................................................................................................ 191 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year192 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year............................................................................................................... 192 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year.................................................................................................. 192 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year.................................................................................................. 193 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year .. 193 APPENDIX II 123 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year............................................................................................................... 193 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year...................................................................................................... 194 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year .......................................................................................................................... 194 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................... 195 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................... 195 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year.... 195 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.. 196 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ............................................................................................................ 196 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ......................................................................................................................... 197 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.17 Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................... 198 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................................................... 199 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................................... 199 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................................ 199 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ............................................................................................................ 200 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ............................................................................................................ 201 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................................................... 201 APPENDIX II 124 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................................ 201 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 202 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year ........................................................................................................... 203 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 203 12.1.35 Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year ............................................................................................................ 204 AGRICULTURE CREDIT .................................................................................................................................... 205 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year ......................................................................................................... 206 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year .......................................................................................................................... 206 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year ......................................................................................................... 207 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year ......................................................................................................... 207 TREE FARMING AND AGROFORESTRY ....................................................................................................... 209 14.1 Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Pwani Region.............................................................................................................................................. 210 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Pwani Region................................ 211 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 211 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Pwani Region.................................................................... 212 APPENDIX II 125 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 212 CROP EXTENSION............................................................................................................................................... 213 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Pwani Region.................................................................... 214 15.2 Number of Households by Quality of Extension Services and District During the 2002/03 Agricultural Year, Pwani Region........................................................................................... 214 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region................................................................................. 214 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 215 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................ 215 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............ 215 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 216 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 216 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................... 216 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region........................ 217 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............ 217 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 217 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 218 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 219 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region............................ 219 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Pwani Region ................................. 219 APPENDIX II 126 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Pwani Region ................................. 220 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Pwani Region ................................. 220 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Pwani Region.................... 220 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Pwani Region.................... 221 ANIMAL CONTRIBUTION TO CROP PRODUCTION .................................................................................. 223 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Pwani Region............................................................................. 224 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Pwani Region............................................................................. 224 cont… Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Pwani Region............................................................................. 224 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Pwani...................................................................................................... 224 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 225 CATTLE PRODUCTION...................................................................................................................................... 227 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Pwani Region.............................................................................................................................................. 228 18.2 Number of Cattle By Type and District as of 1st October, 2003 ................................................................ 228 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003............................................................................................................... 228 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003................................................... 229 18.5 Number of Indigenous Cattle by Category and District as on 1st October, 2003 ....................................... 229 18.6 Number of Improved Beef Cattle by Category and District as on 1st October, 2003................................. 229 18.7 Number of Improved Dairy Cattle by Category and District as on 1st October, 2003 ............................... 230 18.8 Number of Cattle by Category and District as on 1st October, 2003.......................................................... 230 GOATS PRODUCTION......................................................................................................................................... 231 19.1 Total Number of Goats by Type and District as on 1st October, 2003....................................................... 232 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ............................................... 232 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District .................... 233 APPENDIX II 127 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003................................ 233 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003 ............................ 233 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ..................................... 234 19.7 Total Number of Goats by Category and District on 1st October, 2003..................................................... 234 SHEEP PRODUCTION ......................................................................................................................................... 135 20.1 Total Number of Sheep by Breed and on 1st October 2003 ....................................................................... 136 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003.............................. 136 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03................................................. 136 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003........................................ 136 20.5 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003............................... 137 20.6 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Pwani Region ............... 137 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003............................... 137 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 ................................................. 137 PIGS PRODUCTION ............................................................................................................................................. 139 21.1 Number of Households and Pigs by Herd Size on 1st October 2003.......................................................... 240 21.2 Number of Households and Pigs by District on 1st October 2003.............................................................. 240 21.3 Number of Pigs by Type and District on 1st October, 2003....................................................................... 240 LIVESTOCK PESTS AND PARASITE CONTROL.......................................................................................... 241 22.1 Number of Livestock Rearing households de-worming Livestock by District during 2002/03 Agricultural Year............................................................................................................... 242 22.2 Number of Livestock Rearing Households that de-wormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year......................................................................................................... 242 22.3 Number and Percent of agricultural households reporting to have encountered tick problems ` during 2002/03 Agriculture Year by District.............................................................................................. 242 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year........................................................................................................ 242 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District.............................................................................................. 243 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year........................................................................................................ 243 OTHER LIVESTOCK............................................................................................................................................ 245 23a Total Number of Other Livestock by Type on 1st October 2003................................................................ 246 APPENDIX II 128 23b Number of Chicken by Category of Chicken and District on 1st October 2003......................................... 246 23c Head Number of Other Livestock by Type of Livestock and District ........................................................ 246 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 ......................... 246 23e Livestock/Poultry Population Trend ........................................................................................................... 246 FISH FARMING..................................................................................................................................................... 247 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year.. 248 28.2 Number of Agricultural Households by System of Farming and District during the 2002/03 Agricultural Year .................................................................................................................... 248 LIVESTOCK EXTENSION................................................................................................................................... 249 29.1a Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year .................................................................................................................... 250 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year .................................................................................................................... 250 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.3 Number of Agricultural Households Receiving Extension Advice on Housing by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking by Source and District, 2002/03 Agricultural Year......................................................................................... 251 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene by Source and District, 2002/03 Agricultural Year.......................................................................................... 251 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control by Source and District, 2002/03 Agricultural Year.......................................................................................... 252 29.7 Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection by Source and District, 2002/03 Agricultural Year.......................................................................................... 252 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection by Source and District, 2002/03 Agricultural Year.......................... 253 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening by Source and District, 2002/03 Agricultural Year ............................................................. 253 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing by Source and District, 2002/03 Agricultural Year.......................................................................................... 254 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls by Source and District, 2002/03 Agricultural Year.......................................................................................... 254 29.12 Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year .......................................................................................................................... 255 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES ........................................................................ 257 APPENDIX II 129 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts.......................... 258 33.01b Number of Households by Distance to Secondary School by District for 2002/03 agriculture year.......... 258 33.01c Number of Households by Distance to All Weather Road by District for 2002/03 agriculture year.......... 259 33.01d Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year................... 259 33.01e Number of Households by Distance to Hospital by District for 2002/03 agriculture year ......................... 259 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year ................ 260 33.01g Number of Households by distance to Primary School for 2002/03 agriculture year................................. 260 33.01h Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year............ 260 33.01i Number of Households by Distance to District Capital by District for 2002/03 agriculture year .............. 261 33.01j Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year ................ 261 33.01k Number of Households by Distance to Primary Market by District for 2002/03 agricultural year ............ 262 33.01l Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year ............ 262 33.01m Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year......... 262 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year……………………………………………………………………263 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year...................................................................................................... 263 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year...................................................................................................... 263 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Laboratories and District, 2002/03 Agricultural Year...................................................................................................... 264 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year...................................................................................................... 264 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year...................................................................................................... 264 HOUSEHOLD FACILITIES................................................................................................................................. 265 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year266 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ............................................................................................................ 266 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ........................................................................................................................ 266 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year ......................................................................................................................... 267 APPENDIX II 130 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year .......................................................................................................................... 267 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ........................................................................................... 268 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ........................................................................................... 268 34.8 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ................................................................ 269 34.9 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ................................................................ 269 34.10 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District ............................................................................................................................ 270 34.11 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ........................................................................................................................ 270 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ........................................................................................................................ 271 34.13 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.......................................................................................................................... 271 34.14 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .......................................................................................................................... 272 34.15 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year.. 272 APPENDIX II 131 APPENDIX II: CROP TABLES Type of Agriculture Household............................................................................................................................................ 132 Number of Agriculture Households ..................................................................................................................................... 134 Rank of Importance of Livelihood Activities....................................................................................................................... 136 Households Demography..................................................................................................................................................... 140 Land Access/Ownership....................................................................................................................................................... 146 Land Use……………… ...................................................................................................................................................... 148 Annual Crop and Vegetable Production Long Rainy Seasons............................................................................................. 160 Permanent Crop Production ................................................................................................................................................. 174 Agro-processing .......................................................................................................................................................... 182 Marketing .......................................................................................................................................................... 186 Irrigation/Erosion Control.................................................................................................................................................... 188 Access to Farm Inputs ......................................................................................................................................................... 191 Agriculture Credit .......................................................................................................................................................... 205 Tree Farming and Agro-forestry .......................................................................................................................................... 209 Crop Extension .......................................................................................................................................................... 213 Animal Contribution to Crop Production............................................................................................................................. 223 Cattle Production .......................................................................................................................................................... 228 Goat Production .......................................................................................................................................................... 231 Sheep Production .......................................................................................................................................................... 235 Pig Production .......................................................................................................................................................... 239 Livestock Pests and Parasite Control ................................................................................................................................... 241 Other Livestock .......................................................................................................................................................... 245 Fishing Farming .......................................................................................................................................................... 247 Livestock Extension .......................................................................................................................................................... 249 Access to Infrastructure and other services.......................................................................................................................... 257 Household Facilities .......................................................................................................................................................... 265 Appendix II 132 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 133 Rural Households Involved in Agriculture % of Total Rural Households Rural Households NOT Involved in Agriculture % of Total Rural Households Total Rural Households % of Total Households Urban Households % of Total Households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Bagamoyo 37,290 26 3,342 8 40,632 81 9,727 19 50,359 Kibaha 14,029 10 3,090 18 17,119 56 13,358 44 30,477 Kisarawe 18,637 13 1,014 5 19,651 86 3,298 14 22,949 Mkuranga 34,744 25 3,418 9 38,162 89 4,775 11 42,937 Rufiji 30,906 22 3,718 11 34,624 78 9,718 22 44,342 Mafia 5,924 4 1,599 21 7,523 76 2,332 24 9,855 Total 141,530 100 16,182 10 157,711 78 43,208 22 200,919 Number of Households % Number of Households % Number of Households % Bagamoyo 31,426 24 1,384 66 4,479 44 37,290 35,905 5,864 Kibaha 12,976 10 339 16 714 7 14,029 13,689 1,053 Kisarawe 17,645 14 47 2 945 9 18,637 18,590 992 Mkuranga 34,251 26 0 0 493 5 34,744 34,744 493 Rufiji 28,997 22 221 11 1,688 17 30,906 30,685 1,909 Mafia 4,055 3 94 5 1,775 18 5,924 5,830 1,869 Total 129,349 100 2,086 100 10,094 100 141,530 139,444 12,180 District Total Number of Households Growing Crops 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year District Agriculture, Non Agriculture and Urban Households Total Number of Households Rearing Livestock Crops Only Livestock Only Total Number of Agriculture Households Crops & Livestock 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year Type of Agriculture Household Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 134 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 135 Number % Average Household Size Number % Average Household Size Number % Bagamoyo 29,938 80 5 7,351 20 5 37,290 100 5 Kibaha 11,272 80 5 2,757 20 4 14,029 100 5 Kisarawe 15,622 84 5 3,015 16 4 18,637 100 5 Mkuranga 28,858 83 5 5,886 17 4 34,744 100 5 Rufiji 24,404 79 6 6,502 21 4 30,906 100 5 Mafia 5,013 85 5 911 15 5 5,924 100 5 Total 115,108 81 5 26,422 19 4 141,530 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 1 4 5 3 6 7 2 Kibaha 1 3 5 2 6 7 4 Kisarawe 2 1 6 4 5 7 3 Mkuranga 2 1 5 3 6 7 4 Rufiji 1 3 7 4 6 5 2 Mafia 1 2 5 3 7 4 6 Total 1 2 5 4 6 7 3 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size 3.1 The livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Male Female Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 136 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 137 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 10,286 3,869 1,920 10,439 2,020 974 7,381 Kibaha 7,990 1,607 362 2,559 912 0 600 Kisarawe 6,341 11,791 48 141 42 0 94 Mkuranga 13,455 14,318 79 3,250 824 865 1,500 Rufiji 22,916 3,351 72 1,876 302 1,141 1,093 Mafia 576 2,311 62 1,482 146 1,282 45 Total 61,564 37,247 2,542 19,747 4,246 4,262 10,714 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 16,035 5,478 1,786 5,623 1,605 100 6,477 Kibaha 3,379 4,258 656 3,026 703 520 1,473 Kisarawe 6,045 4,286 278 2,850 1,310 47 4,044 Mkuranga 12,456 14,684 1,341 3,474 899 377 1,510 Rufiji 5,372 9,784 446 4,163 2,063 3,147 5,386 Mafia 3,054 1,363 410 464 54 472 22 Total 46,341 39,852 4,919 19,601 6,634 4,663 18,911 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 7,087 5,454 3,977 5,943 2,621 301 10,863 Kibaha 1,334 2,370 1,177 2,750 806 62 3,546 Kisarawe 3,135 1,081 837 3,328 2,393 235 6,577 Mkuranga 3,363 2,776 3,352 8,727 3,473 698 8,986 Rufiji 1,612 4,799 2,495 4,280 1,952 1,040 9,654 Mafia 1,431 867 761 887 194 234 168 Total 17,961 17,347 12,598 25,915 11,439 2,570 39,794 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 1,677 4,845 3,969 3,875 2,596 367 7,647 Kibaha 382 1,000 1,581 1,418 585 155 3,499 Kisarawe 396 309 1,142 2,817 1,412 47 5,557 Mkuranga 2,010 1,270 4,599 5,675 1,561 688 7,090 Rufiji 345 2,236 2,281 1,998 817 878 6,289 Mafia 151 192 1,031 502 82 375 312 Total 4,962 9,853 14,603 16,286 7,054 2,510 30,392 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 194 1,244 1,363 1,135 556 76 3,189 Kibaha 42 236 899 323 364 0 1,378 Kisarawe 82 0 951 851 504 0 1,199 Mkuranga 1,376 815 2,294 1,568 912 472 2,704 Rufiji 58 945 515 593 538 153 2,166 Mafia 0 0 170 245 24 114 281 Total 1,753 3,240 6,193 4,715 2,898 815 10,916 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Important 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Important 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Important 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Important 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Important Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 138 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 85 76 403 199 153 0 273 Kibaha 0 81 205 80 82 0 0 Kisarawe 90 0 91 137 95 0 142 Mkuranga 230 124 378 293 365 174 585 Rufiji 0 164 158 152 223 0 53 Mafia 24 0 24 34 0 23 138 Total 428 445 1,258 896 917 197 1,191 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bagamoyo 0 0 0 0 91 91 0 Kibaha 0 0 0 0 0 0 0 Kisarawe 89 94 0 47 0 0 0 Mkuranga 0 0 45 0 0 79 0 Rufiji 154 0 72 0 83 0 164 Mafia 0 0 0 0 47 0 0 Total 243 94 117 47 221 170 164 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Important 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Important Tanzania Agriculture Sample Census - 2003 Pwani 139 Appendix II 140 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 141 Number % Number % Number % Less than 4 47,013 52 43,497 48 90,510 100 05 - 09 52,490 52 48,993 48 101,482 100 10 - 14 55,708 52 52,064 48 107,773 100 15 - 19 39,173 53 34,204 47 73,377 100 20 - 24 23,194 46 27,766 54 50,960 100 25 - 29 18,140 40 26,783 60 44,922 100 30 - 34 19,508 47 22,010 53 41,517 100 35 - 39 15,160 48 16,610 52 31,770 100 40 - 44 13,083 46 15,543 54 28,626 100 45 - 49 9,749 42 13,627 58 23,376 100 50 - 54 11,982 44 15,070 56 27,052 100 55 - 59 8,666 54 7,378 46 16,045 100 60 - 64 10,091 49 10,473 51 20,564 100 65 - 69 7,821 50 7,814 50 15,635 100 70 - 74 9,403 56 7,419 44 16,822 100 75 - 79 5,827 68 2,753 32 8,580 100 80 - 84 4,757 55 3,850 45 8,608 100 Above 85 2,614 49 2,762 51 5,376 100 Total 354,379 50 358,616 50 712,995 100 Number % Number % Number % Less than 4 47,013 13 43,497 12 90,510 13 05 - 09 52,490 15 48,993 14 101,482 14 10 - 14 55,708 16 52,064 15 107,773 15 15 - 19 39,173 11 34,204 10 73,377 10 20 - 24 23,194 7 27,766 8 50,960 7 25 - 29 18,140 5 26,783 7 44,922 6 30 - 34 19,508 6 22,010 6 41,517 6 35 - 39 15,160 4 16,610 5 31,770 4 40 - 44 13,083 4 15,543 4 28,626 4 45 - 49 9,749 3 13,627 4 23,376 3 50 - 54 11,982 3 15,070 4 27,052 4 55 - 59 8,666 2 7,378 2 16,045 2 60 - 64 10,091 3 10,473 3 20,564 3 65 - 69 7,821 2 7,814 2 15,635 2 70 - 74 9,403 3 7,419 2 16,822 2 75 - 79 5,827 2 2,753 1 8,580 1 80 - 84 4,757 1 3,850 1 8,608 1 Above 85 2,614 1 2,762 1 5,376 1 Total 354,379 100 358,616 100 712,995 100 3.2 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 142 Number % Number % Number % Bagamoyo 93,429 49 98,463 51 191,892 100 Kibaha 32,297 51 31,009 49 63,306 100 Kisarawe 43,332 50 42,783 50 86,115 100 Mkuranga 90,704 51 88,783 49 179,487 100 Rufiji 80,883 49 84,511 51 165,394 100 Mafia 13,734 51 13,068 49 26,802 100 Total 354,379 50 358,616 50 712,995 100 Number % Number % Number % Number % Number % Bagamoyo 104,236 63 2,482 1 196 0 59,412 36 166,326 100 Kibaha 38,208 66 2,348 4 0 0 17,132 30 57,687 100 Kisarawe 47,609 64 808 1 0 0 25,930 35 74,347 100 Mkuranga 89,154 57 6,469 4 2,415 2 57,752 37 155,790 100 Rufiji 78,610 54 4,521 3 589 0 60,881 42 144,600 100 Mafia 16,677 70 622 3 155 1 6,281 26 23,734 100 Total 374,493 60 17,250 3 3,354 1 227,388 37 622,485 100 Number % Number % Number % Number % Bagamoyo 48,081 29 62,518 38 55,728 34 166,326 100 Kibaha 15,021 26 25,720 45 16,945 29 57,687 100 Kisarawe 22,003 30 28,511 38 23,833 32 74,347 100 Mkuranga 40,476 26 52,431 34 62,883 40 155,790 100 Rufiji 41,279 29 43,206 30 60,116 42 144,600 100 Mafia 6,942 29 10,194 43 6,598 28 23,734 100 Total 173,802 28 222,580 36 226,104 36 622,485 100 Number % Number % Number % Number % Number % Bagamoyo 72,090 43 5,104 3 2,035 1 677 0 1,198 1 Kibaha 26,343 46 796 1 0 0 83 0 1,127 2 Kisarawe 37,353 50 238 0 0 0 94 0 313 0 Mkuranga 76,533 49 144 0 0 0 1,353 1 444 0 Rufiji 72,469 50 218 0 0 0 3,546 2 833 1 Mafia 10,231 43 46 0 0 0 1,788 8 252 1 Total 295,018 47 6,546 1 2,035 0 7,541 1 4,166 1 3.6 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members 5 Years and Above by School Attendance and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.5 HOUSEHOLDS DEMOGRAPHICS: Number of Agriculture Household Members 5 Years and Above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.7 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year Main Activity District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Fishing Government / Parastatal Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 143 Number % Number % Number % Number % Number % Bagamoyo 4,531 3 1,904 1 4,148 2 4,330 3 1,621 1 Kibaha 584 1 1,192 2 2,265 4 1,497 3 1,191 2 Kisarawe 377 1 1,133 2 665 1 2,743 4 690 1 Mkuranga 2,567 2 1,431 1 1,414 1 4,958 3 1,979 1 Rufiji 991 1 1,812 1 1,195 1 1,470 1 1,046 1 Mafia 1,111 5 250 1 72 0 184 1 199 1 Total 10,160 2 7,721 1 9,759 2 15,180 2 6,726 1 Number % Number % Number % Number % Number % Number % Bagamoyo 777 0 3,321 2 45,777 28 17,565 11 1,249 1 166,326 100 Kibaha 286 0 1,688 3 14,262 25 4,834 8 1,540 3 57,687 100 Kisarawe 138 0 1,743 2 20,967 28 6,776 9 1,117 2 74,347 100 Mkuranga 1,200 1 2,943 2 37,072 24 21,264 14 2,490 2 155,790 100 Rufiji 771 1 390 0 37,701 26 18,837 13 3,321 2 144,600 100 Mafia 23 0 427 2 6,474 27 2,217 9 463 2 23,734 100 Total 3,195 1 10,512 2 162,253 26 71,492 11 10,181 2 622,485 100 Number % Number % Number % Number % Number % Bagamoyo 35,941 22 10,559 6 71,308 43 48,518 29 166,326 100 Kibaha 25,593 44 4,307 7 10,708 19 17,078 30 57,687 100 Kisarawe 36,142 49 3,309 4 11,801 16 23,096 31 74,347 100 Mkuranga 64,407 41 7,870 5 31,402 20 52,112 33 155,790 100 Rufiji 65,224 45 5,922 4 23,481 16 49,974 35 144,600 100 Mafia 8,120 34 2,163 9 5,986 25 7,465 31 23,734 100 Total 235,426 38 34,130 5 154,686 25 198,242 32 622,485 100 District Not Working & Available Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Total Main Activity Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled cont... HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Unpaid Family Helper (Non Agriculture) 3.8 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members by Level of Involvement in Farming Activivty and District, 2002/03 Agricultural Year District Other District Involvement in Farming Works Full- time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 144 Number % Number % Number % Number % Number % Bagamoyo 377 1 476 1 1,463 2 1,931 3 7,785 12 Kibaha 344 1 34 0 303 1 484 2 2,720 11 Kisarawe 96 0 48 0 980 3 1,124 4 2,356 8 Mkuranga 484 1 370 1 1,438 3 1,232 2 5,247 10 Rufiji 616 1 340 1 1,166 3 1,279 3 4,895 11 Mafia 252 2 89 1 57 1 144 1 474 5 Total 2,168 1 1,357 1 5,406 2 6,194 3 23,478 11 Number % Number % Number % Number % Number % Bagamoyo 43,936 70 804 1 0 0 98 0 0 0 Kibaha 18,192 71 441 2 140 1 0 0 82 0 Kisarawe 19,191 67 659 2 189 1 48 0 0 0 Mkuranga 34,886 67 414 1 238 0 217 0 139 0 Rufiji 29,230 68 482 1 204 0 159 0 58 0 Mafia 7,754 76 42 0 11 0 0 0 0 0 Total 153,189 69 2,843 1 781 0 522 0 280 0 Number % Number % Number % Number % Number % Bagamoyo 96 0 0 0 767 1 0 0 98 0 Kibaha 212 1 23 0 658 3 76 0 364 1 Kisarawe 319 1 43 0 378 1 143 1 128 0 Mkuranga 302 1 0 0 1,148 2 168 0 0 0 Rufiji 153 0 0 0 475 1 0 0 72 0 Mafia 142 1 0 0 150 1 0 0 23 0 Total 1,224 1 66 0 3,576 2 387 0 685 0 Number % Number % Number % Bagamoyo 98 0 1,277 2 62,518 100 Kibaha 310 1 713 3 25,720 100 Kisarawe 47 0 1,293 5 28,511 100 Mkuranga 77 0 4,149 8 52,431 100 Rufiji 0 0 1,681 4 43,206 100 Mafia 5 0 634 6 10,194 100 Total 536 0 9,746 4 222,580 100 District cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Level of Formal Education Completed and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Level of Formal Education Completed and District, 2002/03 Agricultural Year District Total Form Six Training After Secondary Education University & Other Tertiary Education Education Level Adult Education 3.9 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Household Members By Level of Formal Education Completed and District, 2002/03 Agricultural Year cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completed and District, 2002/03 Agricultural Year District Under Standard One Standard One Standard Two Standard Three District Education Level Education Level Standard Four Education Level Form One Form Two Form Three Form Four Standard Seven Standard Eight Training After Primary Education Pre Form One Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 145 H/holds % Average Household Size H/holds % Average Household Size H/holds % Bagamoyo 29,938 80 5 7,351 20 5 37,290 100 5 Kibaha 11,272 80 5 2,757 20 4 14,029 100 5 Kisarawe 15,622 84 5 3,015 16 4 18,637 100 5 Mkuranga 28,858 83 5 5,886 17 4 34,744 100 5 Rufiji 24,404 79 6 6,502 21 4 30,906 100 5 Mafia 5,013 85 5 911 15 5 5,924 100 5 Total 115,108 81 5 26,422 19 4 141,530 100 5 Number Percent Number Percent Number Percent Number Percent Bagamoyo 16,813 49 10,042 29 7,389 22 34,244 100 Kibaha 6,736 53 3,577 28 2,291 18 12,604 100 Kisarawe 11,918 65 5,387 29 973 5 18,279 100 Mkuranga 17,474 61 6,935 24 4,025 14 28,434 100 Rufiji 17,284 69 5,134 21 2,551 10 24,970 100 Mafia 2,277 49 1,568 34 819 18 4,663 100 Total 72,502 59 32,643 26 18,048 15 123,194 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Bagamoyo 13,107 22,403 0 664 98 98 920 37,290 Kibaha 4,738 7,753 99 514 100 310 515 14,029 Kisarawe 6,642 10,424 48 326 86 47 1,063 18,637 Mkuranga 13,848 16,784 157 1,092 0 77 2,786 34,744 Rufiji 13,289 15,814 132 527 72 0 1,072 30,906 Mafia 1,847 3,527 33 192 0 5 321 5,924 Total 53,472 76,706 468 3,315 356 536 6,677 141,530 Mean Median Mode Mean Median Mode Mean Median Mode Bagamoyo 47 44 35 55 56 70 49 46 35 Kibaha 48 45 35 53 53 65 49 48 60 Kisarawe 48 45 30 57 58 80 49 48 60 Mkuranga 50 50 60 53 51 65 51 50 60 Rufiji 49 50 60 49 50 70 49 50 70 Mafia 43 40 30 55 59 60 45 42 30 Total 48 45 35 53 52 70 49 48 60 District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHICS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHICS: Mean, Median, Mode of Age of Head of Agricultural Household and District 3.11 HOUSEHOLD DEMOGRAPHICS: Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.10 HOUSEHOLDS DEMOGRAPHICS: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Household Size Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 146 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads (In Thousands) 175 179 192 204 124 115 Female Heads (In Thousands) 38 51 63 64 28 26 Total (In Thousands) 213 230 255 268 152 141 Male headed (Percentage) 81 81 81 81 82 81 Female headed (Percentage) 19 19 19 19 18 19 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Bagamoyo 74 31 66 26 69 34 100 100 100 Kibaha 76 41 70 24 59 30 100 100 100 Kisarawe 69 38 64 31 62 36 100 100 100 Mkuranga 74 44 69 26 56 31 100 100 100 Rufiji 66 41 61 34 59 39 100 100 100 Mafia 81 34 74 19 66 26 100 100 100 Total 72 38 66 28 62 34 100 100 100 Literacy Rate (%) 3.14 Time Series of Male and Female Headed Households Can Read and Write Cannot Read and Write Total 3.15 Literacy Rates of Heads of Households by Sex and District District Tanzania Agriculture Sample Census - 2003 Pwani 147 Appendix II 148 LAND USE Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 149 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture House holds with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Area of Land Utilized by Household Total Number of Househol ds Bagamoyo 25,160 8,428 8,884 6,808 5,543 1,463 4,457 1,182 682 278 1,541 11,620 76,965 37,290 Kibaha 7,249 4,388 2,440 2,160 4,740 151 977 122 150 94 420 3,082 25,062 14,029 Kisarawe 2,116 3,642 4,209 5,041 12,511 188 696 95 330 190 297 2,605 29,041 18,637 Mkuranga 13,116 5,658 10,515 12,684 18,302 144 3,195 498 375 332 1,073 3,463 75,310 34,744 Rufiji 12,005 13,316 9,295 4,535 7,160 0 1,559 293 381 156 956 3,765 51,539 30,906 Mafia 4,485 370 3,109 1,218 358 68 185 0 44 0 138 468 8,386 5,924 Total 64,131 35,802 38,452 32,444 48,613 2,014 11,069 2,190 1,961 1,051 4,425 25,003 266,304 141,530 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Bagamoyo 30,273 9,251 7,847 9,246 6,976 4,345 7,654 3,356 314 1,060 2,475 17,538 100,335 Kibaha 7,344 4,020 2,152 2,454 6,701 1,265 1,042 398 48 36 1,593 3,981 31,034 Kisarawe 1,338 2,727 2,765 6,064 14,850 265 623 497 138 271 243 2,362 32,143 Mkuranga 8,086 5,092 15,777 19,046 23,195 40 3,665 726 36 373 2,428 4,632 83,096 Rufiji 9,719 12,254 9,153 5,044 13,511 . 1,635 341 145 78 901 4,904 57,686 Mafia 2,709 222 3,348 1,583 300 16 169 41 61 253 8,701 Total 59,468 33,566 41,042 43,438 65,532 5,932 14,787 5,319 722 1,818 7,702 33,671 312,996 % 19.0 10.7 13.1 13.9 20.9 1.9 4.7 1.7 0.2 0.6 2.5 10.8 100.0 5.1 LAND USE: Number of Agricultural Households by Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts Type of Land Use 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 150 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Bagamoyo 17,842 50 18,063 50 35,905 100 Bagamoyo 24,616 69 11,289 31 35,905 100 Kibaha 8,352 61 5,337 39 13,689 100 Kibaha 8,621 63 5,069 37 13,689 100 Kisarawe 15,486 83 3,104 17 18,590 100 Kisarawe 13,261 71 5,329 29 18,590 100 Mkuranga 24,276 70 10,468 30 34,744 100 Mkuranga 22,621 65 12,123 35 34,744 100 Rufiji 22,569 74 8,115 26 30,685 100 Rufiji 16,704 54 13,981 46 30,685 100 Mafia 3,885 67 1,945 33 5,830 100 Mafia 3,035 52 2,795 48 5,830 100 Total 92,412 66 47,032 34 139,444 100 Total 88,856 64 50,587 36 139,444 100 Number Percent Number Percent Number Percent Bagamoyo 13,652 38 22,253 62 35,905 100 Kibaha 2,288 17 11,401 83 13,689 100 Kisarawe 4,816 26 13,774 74 18,590 100 Mkuranga 9,060 26 25,684 74 34,744 100 Rufiji 4,725 15 25,959 85 30,685 100 Mafia 2,259 39 3,571 61 5,830 100 Total 36,799 26 102,644 74 139,444 100 5.5: Number of Agricultural Households by Whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have Customary Right for Land? Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you Have Sufficient Land for the Hh? Yes No Total 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Pwani 151 Appendix II 152 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 153 Number of households Planted area (hectare) Number of Households Planted Area (hectare) Bagamoyo 21,024 16,701 32,684 44,062 60,763 27.48 Kibaha 10,492 9,378 9,019 9,905 19,284 48.63 Kisarawe 13,913 7,863 6,350 13,056 20,920 37.59 Mkuranga 23,721 14,405 9,342 23,162 37,566 38.34 Rufiji 23,774 18,188 10,080 17,846 36,033 50.47 Mafia 3,298 1,606 2,926 1,499 3,106 51.73 Total 96,222 68,141 70,400 109,531 177,672 38.35 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Bagamoyo 21,024 16,266 32,684 4,605 35,905 Kibaha 10,492 3,537 9,019 5,010 13,689 Kisarawe 13,913 4,724 6,350 12,287 18,590 Mkuranga 23,721 11,023 9,342 25,402 34,744 Rufiji 23,774 7,132 10,080 20,826 30,685 Mafia 3,298 2,626 2,926 2,999 5,830 Total 96,222 45,307 70,400 71,129 139,444 District Dry Season Wet Season Total Number of Crop Growing Households 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area Planted in Dry Season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Dry Season Wet Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 154 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 38,019 11,561 304 32,300 11,430 354 70,319 22,991 327 Paddy 9,937 2,305 232 18,574 4,756 256 28,511 7,062 248 Sorghum 798 425 533 3,675 855 233 4,473 1,280 286 Bulrush Millet 41 2 50 0 0 0 41 2 0 Finger Millet 30 18 618 71 4 59 101 23 224 Wheat 0 0 0 0 0 0 0 0 0 Barley 114 0 0 0 0 0 114 0 0 CEREALS 48,940 14,312 54,620 17,046 103,560 31,358 Cassava 4,970 4,837 973 44,301 66,353 1,498 49,270 71,190 1,445 Sweet Potatoe 521 637 1,223 1,275 771 605 1,796 1,408 784 Irish Potatoes 0 0 0 24 41 1,688 24 41 1,688 Yams 5 22 4,199 62 0 0 67 22 323 Cocoyam 0 0 0 0 0 0 0 0 0 ROOTS & TUB 5,496 5,496 45,662 67,165 51,158 72,661 Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 0 Cowpeas 11,056 1,681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick Peas 10 2 247 0 0 0 10 2 0 Bambaranuts 15 1 89 0 0 0 15 1 0 Field Peas 0 0 0 0 0 0 0 0 0 PULSES 12,039 1,747 5,513 552 100 17,552 2,299 Sunflower 0 0 0 21 10 449 21 10 449 Simsim 166 18 109 2,386 312 131 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & 368 113 2,552 335 131 2,920 448 Okra 98 35 353 28 73 2,585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergin 0 0 0 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 0 0 0 Onions 22 15 697 2 4 1,976 24 19 800 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 13 0 0 13 19 1,506 26 19 729 Tomatoes 404 840 2,077 491 1,104 2,250 895 1,944 2,172 Spinnach 24 2 93 6 4 726 30 6 218 Carrot 0 0 0 0 0 0 0 0 0 Chillies 6 1 222 0 0 0 6 1 0 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1,328 264 225 853 Cucumber 57 45 794 29 39 1,378 86 85 989 Egg Plant 0 0 0 12 37 3,073 12 37 3,073 Water Mellon 183 921 5,027 114 203 1,785 297 1,124 3,787 Cauliflower 0 0 0 0 0 0 0 0 0 FRUITS & VE 1,046 2,019 940 1,664 1,987 3,682 Seaweed 171 180 1,055 183 188 1,024 354 368 1,039 Cotton 82 0 0 59 117 1,976 141 117 832 Tobacco 0 0 0 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 CASH CROPS 252 180 243 305 495 485 Total 68,141 109,531 177,672 *The total area planted include the sum of the planted area for both Long and Short Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long Season to estimate physical land area under production to different crops. 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Pwani Region Crop Dry season Wet Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 155 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Maize 71,919 38,019 40,193 32,300 70,319 54 Paddy 19,136 9,937 30,542 18,574 28,511 35 Sorghum 2,443 798 6,090 3,675 4,473 18 Bulrush Millet 111 41 0 0 41 100 Finger Millet 74 30 84 71 101 30 Wheat 0 0 0 0 0 0 Barley 130 114 0 0 114 100 CEREALS 93,813 48,940 76,909 54,620 103,560 47.3 Cassava 8,988 4,970 65,461 44,301 49,270 10 Sweet 1,835 521 3,036 1,275 1,796 29 Irish Potatoes 0 0 130 24 24 0 Yams 67 5 98 62 67 8 Cocoyam 0 0 0 0 0 0 ROOTS & 10,891 5,496 68,725 45,662 51,158 10.7 Mung Beans 39 16 0 0 16 100 Beans 204 18 0 0 18 100 Cowpeas 39,454 11,056 14,618 5,167 16,223 68 Green Gram 3,406 920 951 345 1,265 73 Pigeon Peas 27 6 0 0 6 100 Chick Peas 82 10 0 0 10 100 Bambaranuts 72 15 0 0 15 100 Field Peas 0 0 0 0 0 0 PULSES 43,283 12,039 15,570 5,513 17,552 69 Sunflower 0 0 96 21 21 0 Simsim 574 166 4,894 2,386 2,552 6 Groundnuts 1,048 202 508 140 342 59 Soya Beans 0 0 47 5 5 0 Castor Seed 0 0 0 0 0 0 OIL SEEDS 1,622 368 5,546 2,552 2,920 13 Okra 232 98 119 28 126 78 Radish 0 0 84 101 101 0 Turmeric 0 0 0 0 0 0 Bitter 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 Onions 131 22 47 2 24 92 Ginger 0 0 0 0 0 0 Cabbage 47 13 192 13 26 52 Tomatoes 1,815 404 1,486 491 895 45 Spinnach 150 24 145 6 30 80 Carrot 0 0 0 0 0 0 Chillies 73 6 0 0 6 100 Amaranths 729 84 263 36 120 70 Pumpkins 1,007 155 436 109 264 59 Cucumber 237 57 65 29 86 67 Egg Plant 0 0 62 12 12 0 Water Mellon 794 183 246 114 297 62 Cauliflower 0 0 0 0 0 0 FRUITS & 5,215 1,046 3,145 940 1,987 53 Seaweed 316 171 316 183 354 48 Cotton 102 82 195 59 141 58 Tobacco 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 Jute 0 0 0 0 0 0 CASH 418 252 511 243 495 51.0 Total 155,243 68,141 170,406 109,531 177,672 38.4 % Area Planted in Dry Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Pwani Region Crop Dry season Wet Season Total Area Planted Short & Long Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 156 Number of Households Planted Area (ha) Number of Households Planted Area (ha) Number of Households Planted Area (ha) Number of Households Planted Area (ha) Bagamoyo 2,162 1,657 1,209 1,042 50,338 52,004 35,905 54,703 Kibaha 564 1,069 664 948 18,284 17,001 13,689 19,018 Kisarawe 43 6 648 360 19,572 11,227 18,590 11,593 Mkuranga 161 110 954 317 31,948 19,810 34,744 20,238 Rufiji 248 122 1,295 1,237 32,311 25,663 30,685 27,022 Mafia 0 0 188 64 6,035 2,984 5,830 3,048 Total 3,177 2,964 4,958 3,969 158,488 128,690 139,444 135,622 Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Number of Household Planted Area (ha) Bagamoyo 939 861 3,990 5,409 747 561 30,228 53,931 35,905 60,763 Kibaha 1,104 1,099 462 362 279 203 11,844 17,620 13,689 19,284 Kisarawe 425 337 1,275 706 138 68 16,752 19,808 18,590 20,920 Mkuranga 2,085 1,732 2,483 1,324 1,152 565 29,024 33,945 34,744 37,566 Rufiji 303 96 328 131 76 31 29,978 35,775 30,685 36,033 Mafia 1,150 543 299 107 267 148 4,114 2,308 5,830 3,106 Total 6,007 4,669 8,837 8,040 2,659 1,575 121,940 163,388 139,444 177,672 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Bagamoyo 457 447 53,251 54,256 35,905 60,763 0.7 Kibaha 847 718 18,664 18,300 13,689 19,284 3.7 Kisarawe 319 234 19,944 11,358 18,590 20,920 1.1 Mkuranga 1,419 1,006 31,644 19,232 34,744 37,566 2.7 Rufiji 631 699 33,222 26,323 30,685 36,033 1.9 Mafia 142 60 6,082 2,989 5,830 3,106 1.9 Total 3,815 3,164 162,808 132,458 139,444 177,672 1.8 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet & Dry Season, 2002/03 Agriculture Year 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Wet & Dry Season, Pwani Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Pwani Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,587 1,534 34,318 59,229 35,905 60,763 2.5 Kibaha 1,433 1,028 12,256 18,256 13,689 19,284 5.3 Kisarawe 609 456 17,981 20,464 18,590 20,920 2.2 Mkuranga 1,477 1,177 33,267 36,389 34,744 37,566 3.1 Rufiji 946 1,067 29,739 34,966 30,685 36,033 3.0 Mafia 15 3 5,815 3,103 5,830 3,106 0.1 Total 6,067 5,265 133,376 172,407 139,444 177,672 3.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 650 769 35,256 53,934 35,905 60,763 1.3 Kibaha 184 185 13,505 18,833 13,689 19,284 1.0 Kisarawe 228 90 18,362 11,503 18,590 20,920 0.4 Mkuranga 820 706 33,924 19,532 34,744 37,566 1.9 Rufiji 1,635 898 29,050 26,125 30,685 36,033 2.5 Mafia 101 43 5,729 3,006 5,830 3,106 1.4 Total 3,617 2,691 135,826 132,931 139,444 177,672 1.5 % 2.6 1.5 97.4 74.8 100 100 % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,033 1,003 52,675 53,700 35,905 60,763 1.7 Kibaha 893 581 18,619 18,437 13,689 19,284 3.0 Kisarawe 422 233 19,841 11,360 18,590 20,920 1.1 Mkuranga 1,769 1,332 31,294 18,906 34,744 37,566 3.5 Rufiji 845 719 33,008 26,303 30,685 36,033 2.0 Mafia 59 16 6,165 3,032 5,830 3,106 0.5 Total 5,021 3,884 161,602 131,738 139,444 177,672 2.2 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 9,643 8,409 44,065 46,294 35,905 54,703 15.4 Kibaha 5,165 5,123 14,347 13,895 13,689 19,018 26.9 Kisarawe 5,016 2,694 15,247 8,899 18,590 11,593 23.2 Mkuranga 6,412 3,359 26,651 16,879 34,744 20,238 16.6 Rufiji 1,880 1,218 31,973 25,804 30,685 27,022 4.5 Mafia 772 422 5,451 2,627 5,830 3,048 13.8 Total 28,888 21,224 137,734 114,398 139,444 135,622 15.6 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Improved Seeds District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Pwani 159 Appendix II 160 ANNUAL CROP & VEGETABLES PRODUCTION LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 161 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 1,335 1,186 778 879 30,572 35,938 32,684 44,062 Kibaha 340 696 399 617 8,281 8,326 9,019 9,905 Kisarawe 0 . 138 62 6,212 3,667 6,350 13,056 Mkuranga 82 33 557 193 8,703 5,607 9,342 23,162 Rufiji 0 . 250 432 9,830 8,403 10,080 17,846 Mafia 0 . 105 33 2,821 1,409 2,926 1,499 Total 1,756 1,915 2,226 2,216 66,418 63,350 70,400 109,531 % 2 2 3 2 94 58 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 560 624 2,403 4,105 451 417 29,270 32,856 32,684 44,062 Kibaha 559 670 265 204 106 42 8,090 8,723 9,019 9,905 Kisarawe 95 102 474 263 0 . 5,781 3,364 6,350 13,056 Mkuranga 385 425 834 439 158 98 7,965 4,872 9,342 23,162 Rufiji 0 . 72 52 0 . 10,008 8,782 10,080 17,846 Mafia 541 260 230 84 9 5 2,145 1,093 2,926 1,499 Total 2,141 2,081 4,277 5,147 724 562 63,258 59,691 70,400 109,531 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 276 382 32,408 37,620 32,684 44,062 0.87 Kibaha 527 368 8,492 9,272 9,019 9,905 3.71 Kisarawe 87 63 6,264 3,667 6,350 13,056 0.48 Mkuranga 229 288 9,113 5,545 9,342 23,162 1.25 Rufiji 238 406 9,842 8,428 10,080 17,846 2.28 Mafia 64 29 2,862 1,413 2,926 1,499 1.94 Total 1,420 1,536 68,981 65,945 70,400 109,531 1.40 % 2 1 98 60 100 100 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - LONG RAINY SEASON, Pwani Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - LONG RAINY SEASON, Pwani Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of Planted Area Under Irrigation in Dry Season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during LONG RAINY SEASON, 2002/03 Agriculture Year, Pwani Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 819 913 31,865 37,089 32,684 44,062 2.07 Kibaha 786 600 8,233 9,040 9,019 9,905 6.06 Kisarawe 186 128 6,164 3,602 6,350 13,056 0.98 Mkuranga 224 253 9,118 5,581 9,342 23,162 1.09 Rufiji 230 288 9,849 8,546 10,080 17,846 1.62 Mafia 15 3 2,910 1,439 2,926 1,499 0.21 Total 2,261 2,185 68,140 65,296 70,400 109,531 2.00 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 365 609 32,319 37,393 32,684 44,062 1.38 Kibaha 116 104 8,904 9,536 9,019 9,905 1.05 Kisarawe 133 32 6,217 3,698 6,350 13,056 0.24 Mkuranga 85 69 9,257 5,765 9,342 23,162 0.30 Rufiji 602 361 9,478 8,474 10,080 17,846 2.02 Mafia 40 23 2,886 1,419 2,926 1,499 1.52 Total 1,339 1,197 69,061 66,284 70,400 109,531 1.09 % 1.9 1.1 98.1 60.5 100.0 100.0 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 163 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Bagamoyo 733 763 31,951 37,240 32,684 44,062 1.73 Kibaha 496 370 8,524 9,269 9,019 9,905 3.74 Kisarawe 138 44 6,212 3,685 6,350 13,056 0.34 Mkuranga 393 302 8,949 5,532 9,342 23,162 1.30 Rufiji 75 31 10,004 8,804 10,080 17,846 0.17 Mafia 37 12 2,889 1,430 2,926 1,499 0.78 Total 1,872 1,522 68,528 65,960 70,400 109,531 1.39 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bagamoyo 5,765 6,238 26,919 31,764 32,684 38,002 16.42 Kibaha 2,483 2,393 6,537 7,246 9,019 9,640 24.83 Kisarawe 1,357 903 4,993 2,827 6,350 3,730 24.21 Mkuranga 1,720 1,063 7,621 4,771 9,342 5,833 18.22 Rufiji 559 339 9,520 8,496 10,080 8,835 3.84 Mafia 362 207 2,563 1,235 2,926 1,442 14.37 Total 12,246 11,144 58,155 56,338 70,400 67,481 16.51 % 17 17 83 83 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - LONG RAINY SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under irrigation in dry season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Pwani 164 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 38019 11561 304 32,300 11,430 354 70,319 22,991 327 Paddy 9937 2305 232 18,574 4,756 256 28,511 7,062 248 Sorghum 798 425 533 3,675 855 233 4,473 1,280 286 Bulrush Millet 41 2 50 0 0 0 41 2 0 Finger Millet 30 18 618 71 4 59 101 23 224 Wheat 0 0 0 0 0 0 0 0 0 Barley 114 0 0 0 0 0 114 0 0 CEREALS 48940 14312 54,620 17,046 103,560 31,358 Cassava 4970 4837 973 44,301 66,353 1498 49,270 71,190 1445 Sweet Potatoes 521 637 1223 1,275 771 605 1,796 1,408 784 Irish Potatoes 0 0 0 24 41 1688 24 41 1688 Yams 5 22 4199 62 0 0 67 22 323 Cocoyam 0 0 0 0 0 0 0 0 0 ROOTS & TUBERS 5496 5496 45,662 67,165 51,158 72,661 Mung Beans 16 0 0 0 0 0 16 0 0 Beans 18 3 171 0 0 0 18 3 0 Cowpeas 11056 1681 152 5,167 527 102 16,223 2,208 136 Green Gram 920 59 64 345 25 73 1,265 84 67 Pigeon Peas 6 0 0 0 0 0 6 0 0 Chick Peas 10 2 247 0 0 0 10 2 0 Bambaranuts 15 1 89 0 0 0 15 1 0 Field Peas 0 0 0 0 0 0 0 0 0 PULSES 12039 1747 5,513 552 100 17,552 2,299 Sunflower 0 0 0 21 10 449 21 10 449 Simsim 166 18 109 2,386 312 131 2,552 330 129 Groundnuts 202 95 470 140 13 92 342 108 316 Soya Beans 0 0 0 5 0 0 5 0 0 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 368 113 2,552 335 131 2,920 448 Okra 98 35 353 28 73 2585 126 107 852 Radish 0 0 0 101 0 0 101 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 0 0 0 Onions 22 15 697 2 4 1976 24 19 800 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 13 0 0 13 19 1506 26 19 729 Tomatoes 404 840 2077 491 1,104 2250 895 1,944 2172 Spinnach 24 2 93 6 4 726 30 6 218 Carrot 0 0 0 0 0 0 0 0 0 Chillies 6 1 222 0 0 0 6 1 0 Amaranths 84 79 943 36 35 979 120 115 954 Pumpkins 155 80 517 109 145 1328 264 225 853 Cucumber 57 45 794 29 39 1378 86 85 989 Egg Plant 0 0 0 12 37 3073 12 37 3073 Water Mellon 183 921 5027 114 203 1785 297 1,124 3787 Cauliflower 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 1046 2019 940 1,664 1,987 3,682 Seaweed 171 180 1055 183 188 1024 354 368 1039 Cotton 82 0 0 59 117 1976 141 117 832 Tobacco 0 0 0 0 0 0 0 0 0 Pyrethrum 0 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 0 CASH CROPS 252 180 243 305 495 485 Total 68,141 109,531 177,672 *The total area planted include the sum of the planted area for both Wet and Dry Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Wet Season to estimat 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Pwani Region Crop Dry season Wet Season Total Appendix II 165 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 1,951 51,346 516 404 112 0 54,329 Maize 1,416 990 37,900 30,593 119 333 350 213 182 49 0 . 39,967 32,177 Paddy 1,240 933 28,653 17,227 230 183 0 . 98 63 0 . 30,221 18,406 Sorghum 46 28 5,693 3,455 0 . 350 191 0 . 0 . 6,090 3,675 Bulrush Millet 0 . 0 . 0 . 0 . 0 . 0 . 0 . Finger Millet 0 . 84 71 0 . 0 . 0 . 0 . 84 71 Wheat 0 . 0 . 0 . 0 . 0 . 0 . 0 . Barley 0 . 0 . 0 . 0 . 0 . 0 . 0 . ROOTS & TUBERS 1,661 342 2,577 69 0 623 0 16,338 3,611 Cassava 254 122 3,193 1,527 0 . 0 . 685 602 0 . 4,132 2,251 Sweet Potatoes 369 203 2,411 980 122 69 0 . 114 21 0 . 3,016 1,274 Irish Potatoes 85 17 46 7 0 . 0 . 0 . 0 . 130 24 Yams 0 . 98 62 0 . 0 . 0 . 0 . 98 62 Cocoyam 0 . 0 . 0 . 0 . 0 . 0 . 0 . PULSES 2,655 201 5,052 40 0 198 0 5,491 Mung Beans 0 . 0 . 0 . 0 . 0 . 0 . 0 . Beans 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cowpeas 814 201 12,984 4,712 80 35 0 . 647 198 0 . 14,525 5,146 Green Gram 0 . 917 340 34 6 0 . 0 . 0 . 951 345 Pigeon Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chich Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bambaranuts 0 . 0 . 0 . 0 . 0 . 0 . 0 . Field Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . OIL SEEDS & OIL NUTS 0 2,531 0 21 0 0 2,552 Sunflower 0 . 96 21 0 . 0 . 0 . 0 . 96 21 Simsim 0 . 4,820 2,365 0 . 74 21 0 . 0 . 4,894 2,386 Groundnuts 0 . 508 140 0 . 0 . 0 . 0 . 508 140 Soya Beans 0 . 47 5 0 . 0 . 0 . 0 . 47 5 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 50 717 55 80 0 40 940 Okra 0 . 119 28 0 . 0 . 0 . 0 . 119 28 Radish 0 . 84 101 0 . 0 . 0 . 0 . 84 101 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 0 . 0 . 0 . 0 . 0 . 0 . Garlic 0 . 0 . 0 . 0 . 0 . 0 . 0 . Onions 0 . 47 2 0 . 0 . 0 . 0 . 47 2 Ginger 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cabbage 0 . 192 13 0 . 0 . 0 . 0 . 192 13 Tomatoes 82 50 1,273 347 34 55 0 . 0 . 98 40 1,486 491 Spinnach 0 . 145 6 0 . 0 . 0 . 0 . 145 6 Carrot 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chillies 0 . 0 . 0 . 0 . 0 . 0 . 0 . Amaranths 0 . 263 36 0 . 0 . 0 . 0 . 263 36 Pumpkins 0 . 436 109 0 . 0 . 0 . 0 . 436 109 Cucumber 0 . 65 29 0 . 0 . 0 . 0 . 65 29 Egg Plant 0 . 62 12 0 . 0 . 0 . 0 . 62 12 Water Mellon 0 . 186 34 0 . 60 80 0 . 0 . 246 114 Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 0 115 4 0 124 0 243 Seaweed 0 . 84 55 21 4 0 . 211 124 0 . 316 183 Cotton 0 . 195 59 0 . 0 . 0 . 0 . 195 59 Tobacco 0 . 0 . 0 . 0 . 0 . 0 . 0 . Pyrethrum 0 . 0 . 0 . 0 . 0 . 0 . 0 . Jute 0 . 0 . 0 . 0 . 0 . 0 . 0 . Total 2,545 62,338 684 505 1,056 40 67,168 % 4 93 1 1 2 0 100 Crop Table 7.2h: Planted Area and Number of Crop Growing Households During LONG RAINY SEASON by Method of Land Clearing and Crops; 2002/03 Agriculture Year Land Clearing Method Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Other Total Not Cleared Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 18,053 12,166 3,254 0.268 26,539 25,311 10,412 0.411 37,477 13,667 0.365 Kibaha 5,650 2,876 434 0.151 3,534 2,338 165 0.070 5,215 598 0.115 Kisarawe 12,570 4,722 1,751 0.371 4,438 1,750 309 0.176 6,472 2,059 0.318 Mkuranga 15,278 7,089 1,395 0.197 2,676 1,324 120 0.091 8,413 1,515 0.180 Rufiji 20,114 11,098 4,701 0.424 2,862 1,555 408 0.263 12,653 5,110 0.404 Mafia 253 68 26 0.380 143 21 16 0.744 90 42 0.466 Total 71,919 38,019 11,561 0.304 40,193 32,300 11,430 0.354 70,319 22,991 0.327 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 8,839 5,226 431 0.083 5,226 431 0.083 Kibaha 1,294 644 98 0.152 4,210 3,150 353 0.112 3,794 450 0.119 Kisarawe 1,717 747 485 0.649 1,858 960 138 0.144 1,707 623 0.365 Mkuranga 5,678 2,815 417 0.148 5,906 3,022 605 0.200 5,837 1,022 0.175 Rufiji 8,784 5,015 1,028 0.205 8,126 5,501 2,853 0.519 10,516 3,881 0.369 Mafia 1,664 716 278 0.389 1,603 715 376 0.526 1,431 654 0.457 Total 19,136 9,937 2,305 0.232 30,542 18,574 4,756 0.000 28,511 7,062 0.248 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 296 18 15 0.832 3,326 1,869 248 0.133 1,887 263 0.140 Kibaha 163 47 2 0.045 1,194 915 379 0.414 962 381 0.396 Kisarawe 460 103 25 0.241 354 159 0 0.001 263 25 0.095 Mkuranga 399 227 10 0.045 82 20 5 0.247 247 15 0.061 Rufiji 1,125 403 373 0.926 1,134 711 223 0.314 1,114 596 0.535 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 2,443 798 425 0.533 6,090 3,675 855 0.233 4,473 1,280 0.286 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 130 114 0 0.000 0 0 0 0.000 114 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 130 114 0 0.000 0 0 0 0.000 114 0 0.000 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Paddy District Short Rainy Season Long Rainy Season Total Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Sorghum District Short Rainy Season Long Rainy Season Total Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District;2002/03 Agricultural Year Barley District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year Maize District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 167 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 74 30 18 0.618 84 71 5 0.068 101 23 0.230 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 74 30 18 0.618 84 71 4 0.059 101 23 0.224 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 34 28 0 0.006 0 0 0 0.000 28 0 0.006 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 76 14 2 0.140 0 0 0 0.000 14 2 0.140 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 111 41 2 0.050 0 0 0 0.000 41 2 0.050 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 261 120 0 0.000 11,715 6,079 8,476 1.394 6,199 8,476 1.367 Kibaha 5,229 3,423 3,318 0.969 3,332 1,892 1,353 0.715 5,314 4,671 0.879 Kisarawe 142 48 14 0.296 14,779 9,362 22,400 2.393 9,411 22,414 2.382 Mkuranga 549 212 35 0.164 23,495 17,358 16,747 0.965 17,569 16,782 0.955 Rufiji 1,135 569 759 1.334 10,921 9,192 16,893 1.838 9,761 17,652 1.808 Mafia 1,672 597 711 1.190 1,219 418 484 1.158 1,015 1,195 1.177 Total 8,988 4,970 4,837 0.973 65,461 44,301 66,353 1.498 49,270 71,190 1.445 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 98 16 0 0.000 715 414 171 0.412 430 171 0.397 Kibaha 330 106 48 0.448 695 447 36 0.081 553 84 0.152 Kisarawe 323 102 206 2.021 313 31 42 1.377 133 248 1.872 Mkuranga 792 250 281 1.127 722 238 221 0.927 488 502 1.029 Rufiji 161 17 13 0.746 74 30 4 0.124 47 17 0.351 Mafia 132 30 89 2.967 516 115 297 2.585 145 386 2.664 Total 1,835 521 637 1.223 3,036 1,275 771 0.605 1,796 1,408 0.784 Long Rainy Season Total Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Short Rainy Season Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Short Rainy Season Long Rainy Season Total Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Short Rainy Season Long Rainy Season Total Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrush millet Harvested (tons) by Season and District;2002/03 Agricultural Year Bulrush millet District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 168 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 62 0 0.000 62 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 67 5 22 4.199 0 0 0 0.000 5 22 4.199 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 67 5 22 4.199 98 62 0 0.000 67 22 0.323 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 85 17 10 0.608 17 10 0.608 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 46 7 30 4.347 7 30 4.347 Total 0 0 0 0.000 130 24 41 1.688 24 41 1.688 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 11,834 3,846 483 0.126 7,311 2,776 267 0.096 6,622 750 0.113 Kibaha 5,785 1,884 201 0.107 2,256 664 25 0.037 2,548 226 0.089 Kisarawe 8,668 1,885 277 0.147 2,845 671 63 0.094 2,557 340 0.133 Mkuranga 10,467 2,713 434 0.160 1,815 866 41 0.048 3,580 475 0.133 Rufiji 2,675 727 287 0.394 325 177 129 0.728 904 416 0.460 Mafia 23 0 0 0.000 65 12 2 0.157 12 2 0.157 Total 39,454 11,056 1,681 0.152 14,618 5,167 527 0.102 16,223 2,208 0.136 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 1,051 432 12 0.027 647 277 11 0.040 708 23 0.032 Kibaha 449 118 3 0.028 115 30 4 0.127 149 7 0.048 Kisarawe 142 27 3 0.095 190 38 10 0.270 65 13 0.197 Mkuranga 1,764 343 41 0.121 0 0 0 0.000 343 41 0.121 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 3,406 920 59 0.064 951 345 25 0.073 1,265 84 0.067 Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Short Rainy Season Long Rainy Season Total Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Cow peas Harvested (tons) by Season and District;2002/03 Agricultural Year Cow peas District Short Rainy Season Long Rainy Season Total Table 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Yams District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 169 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 98 2 1 0.618 0 0 0 0.000 2 1 0.618 Kibaha 59 12 2 0.166 0 0 0 0.000 12 2 0.166 Kisarawe 47 4 0 0.000 0 0 0 0.000 4 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 204 18 3 0.171 0 0 0 0.000 18 3 0.171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 39 16 0 0.000 0 0 0 0.000 16 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 39 16 0 0.000 0 0 0 0.000 16 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 72 15 1 0.089 0 0 0 0.000 15 1 0.089 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 72 15 1 0.089 0 0 0 0.000 15 1 0.089 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 82 10 2 0.247 0 0 0 0.000 10 2 0.247 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 82 10 2 0.247 0 0 0 0.000 10 2 0.247 Long Rainy Season Total Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Short Rainy Season Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick Peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick Peas District Short Rainy Season Long Rainy Season Total Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Short Rainy Season Long Rainy Season Total Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung beans District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 170 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 27 6 0 0.000 0 0 0 0.000 6 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 27 6 0 0.000 0 0 0 0.000 6 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 3,824 1,824 265 0.145 1,824 265 0.145 Kibaha 0 0 0 0.000 243 81 1 0.010 81 1 0.010 Kisarawe 47 19 2 0.124 0 0 0 0.000 19 2 0.124 Mkuranga 316 86 6 0.066 0 0 0 0.000 86 6 0.066 Rufiji 211 61 10 0.164 828 482 46 0.097 543 57 0.104 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 574 166 18 0.109 4,894 2,386 312 0.131 2,552 330 0.129 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 102 16 20 1.267 100 10 3 0.247 26 23 0.873 Kibaha 210 43 31 0.721 0 0 0 0.000 43 31 0.721 Kisarawe 424 90 18 0.200 137 41 1 0.029 130 19 0.146 Mkuranga 312 54 26 0.483 169 68 7 0.101 122 33 0.269 Rufiji 0 0 0 0.000 80 16 0 0.000 16 0 0.000 Mafia 0 0 0 0.000 23 5 2 0.494 5 2 0.494 Total 1,048 202 95 0.470 508 140 13 0.092 342 108 0.316 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 96 21 10 0.449 21 10 0.449 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 96 21 10 0.449 21 10 0.449 Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Short Rainy Season Long Rainy Season Total Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Short Rainy Season Long Rainy Season Total Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Short Rainy Season Long Rainy Season Total Long Rainy Season Total Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Pigeon peas Harvested (tons) by Season and District;2002/03 Agricultural Year Pigeon peas District Short Rainy Season Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 171 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 47 5 0 0.000 5 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 47 5 0 0.000 5 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 397 80 112 1.401 80 112 1.401 Kibaha 323 140 315 2.247 788 318 797 2.506 458 1,112 2.427 Kisarawe 238 54 151 2.790 47 10 90 9.426 64 242 3.785 Mkuranga 901 170 285 1.678 166 67 79 1.189 237 364 1.540 Rufiji 242 25 49 1.987 0 0 0 0.000 25 49 1.987 Mafia 110 15 39 2.562 87 16 25 1.533 31 64 2.028 Total 1,815 404 840 2.077 1,486 491 1,104 2.250 895 1,944 2.172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 20 112 5.659 20 112 5.659 Kibaha 65 4 0 0.000 41 4 4 0.988 8 4 0.482 Kisarawe 95 17 135 7.770 47 10 20 2.100 27 155 5.750 Mkuranga 634 162 787 4.868 60 80 120 1.497 242 906 3.752 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 794 183 921 5.027 246 114 203 1.785 297 1,124 3.787 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 91 4 0 0.000 87 5 0 0.000 9 0 0.000 Kibaha 219 19 14 0.699 101 11 8 0.774 30 22 0.725 Kisarawe 48 17 0 0.000 0 0 0 0.000 17 0 0.000 Mkuranga 565 94 25 0.262 164 85 12 0.140 179 37 0.205 Rufiji 83 20 42 2.058 83 8 125 14.820 29 167 5.812 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 1,007 155 80 0.517 436 109 145 1.328 264 225 0.853 Long Rainy Season Total Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya beans District Short Rainy Season Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Pumpkins District Short Rainy Season Long Rainy Season Total Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Water melon Harvested (tons) by Season and District;2002/03 Agricultural Year Water melon District Short Rainy Season Long Rainy Season Total Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 172 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 34 11 0 0.000 11 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 158 23 35 1.499 85 17 73 4.248 40 107 2.671 Rufiji 74 75 0 0.000 0 0 0 0.000 75 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 232 98 35 0.353 119 28 73 2.585 126 107 0.852 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 20 0 0.000 20 0 0.000 Kibaha 31 2 3 1.900 31 5 2 0.380 6 5 0.760 Kisarawe 0 0 0 0.000 95 7 20 3.035 7 20 3.035 Mkuranga 464 55 63 1.146 0 0 0 0.000 55 63 1.146 Rufiji 158 18 7 0.393 0 0 0 0.000 18 7 0.393 Mafia 77 9 6 0.667 40 5 13 2.717 14 19 1.372 Total 729 84 79 0.943 263 36 35 0.979 120 115 0.954 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 84 101 0 0.000 101 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 84 101 0 0.000 101 0 0.000 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 34 11 16 1.520 65 29 39 1.378 39 56 1.417 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 203 46 29 0.626 0 0 0 0.000 46 29 0.626 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 237 57 45 0.794 65 29 39 1.378 86 85 0.989 Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Okra District Short Rainy Season Long Rainy Season Total Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Short Rainy Season Long Rainy Season Total Table 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Short Rainy Season Long Rainy Season Total Table 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Cucumber District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 173 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 4 0 0.000 4 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 47 2 4 2.223 2 4 2.223 Mkuranga 76 9 0 0.043 0 0 0 0.000 9 0 0.043 Rufiji 74 15 2 0.124 0 0 0 0.000 15 2 0.124 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 150 24 2 0.093 145 6 4 0.726 30 6 0.218 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 98 4 0 0.000 4 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 47 13 0 0.000 95 9 19 2.195 22 19 0.860 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 47 13 0 0.000 192 13 19 1.506 26 19 0.729 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 316 171 180 1.055 316 183 188 1.024 354 368 1.039 Total 316 171 180 1.055 316 183 188 1.024 354 368 1.039 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bagamoyo 102 82 0 0.000 195 59 117 1.976 141 117 0.832 Kibaha 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Kisarawe 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mkuranga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Rufiji 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mafia 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 102 82 0 0.000 195 59 117 1.976 141 117 0.832 Table 7.2.29: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinnach District Short Rainy Season Long Rainy Season Total Table 7.2.30: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Cabbage District Short Rainy Season Long Rainy Season Total Table 7.2.31: Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year Seaweed District Short Rainy Season Long Rainy Season Total Table 7.2.32: Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Cotton District Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 174 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 175 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Bagamoyo Pigeon Pea 206 173 65.07 316.1 Star Fruit 70 30 7.73 110.7 Coconut 3,155 2,772 4,659.34 1,476.7 Cashewnut 6,214 3,027 1,317.44 212.0 Wattle 0 0 0.00 0.0 Sugarcane 67 10 10.19 153.0 Jack Fruit 16 12 282.96 17,207.4 Banana 790 512 1,274.16 1,612.1 Avocado 0 32 34.12 0.0 Mango 1,261 577 12,710.48 10,080.9 Pawpaw 207 26 43.03 208.0 Pineapple 1,762 1,185 7,545.44 4,281.8 Orange 2,001 674 2,115.42 1,057.1 Mandarine/Tangerine 0 0 4.56 0.0 Guava 0 0 0.00 0.0 Lime/Lemon 60 60 48.56 805.6 Total 15,810 9,091 30,118.50 1,905.0 Kibaha Rubber Vine Fruit 0 0 0.00 0.0 Pigeon Pea 46 32 4.21 91.8 Palm Oil 0 1 4.13 0.0 Coconut 1,317 72 938.12 712.2 Cashewnut 2,062 819 1,199.08 581.6 Sugarcane 9 0 0.00 0.0 Mshelisheli 0 0 0.21 0.0 Jack Fruit 0 2 23.64 0.0 Mpesheni 0 0 0.74 16,666.7 Banana 64 27 262.32 4,084.4 Mango 14 44 240.67 17,501.9 Pawpaw 0 0 39.55 0.0 Pineapple 31 20 136.61 4,364.3 Orange 1,201 74 979.32 815.5 Grape Fruit 149 0 0.00 0.0 Mandarine/Tangerine 3 0 7.98 2,557.2 Guava 0 0 4.34 48,756.1 Lime/Lemon 0 0 6.63 0.0 Total 4,896 1,090 3,847.56 785.9 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 176 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Kisarawe Pigeon Pea 441 313 121.13 274.8 Star Fruit 21 18 688.26 32,559.1 Palm Oil 67 10 6.39 94.9 Coconut 1,575 1,284 2,358.02 1,497.1 Cashewnut 3,541 2,205 1,306.36 368.9 Jack Fruit 1,042 84 853.58 819.1 Mpesheni 4 4 0.00 0.0 Banana 1,100 901 3,133.89 2,849.4 Mango 302 277 1,132.63 3,752.1 Pawpaw 170 115 516.17 3,041.9 Pineapple 23 0 0.00 0.0 Orange 1,937 1,366 7,485.26 3,865.2 Mandarine/Tangerine 153 120 1,063.68 6,931.0 Lime/Lemon 13 8 8.10 619.6 Total 10,389 6,705 18,673.45 1,797.5 Mkuranga Pigeon Pea 613 533 99.85 162.8 Star Fruit 48 19 238.36 4,923.2 Palm Oil 20 20 42.92 2,175.9 Coconut 4,569 4,581 10,276.31 2,249.2 Cashewnut 19,636 17,137 6,339.61 322.9 Jack Fruit 71 46 126.75 1,777.7 Mpesheni 161 138 354.18 2,201.5 Banana 179 122 590.02 3,299.4 Mango 457 389 1,233.60 2,698.5 Pawpaw 59 59 137.41 2,325.1 Pineapple 906 599 823.92 909.0 Orange 1,162 824 1,240.73 1,067.3 Mandarine/Tangerine 1,190 149 116.34 97.8 Guava 4 4 3.62 950.0 Lime/Lemon 92 71 141.41 1,531.6 Total 29,168 24,692 21,765.03 746.2 Rufiji Pigeon Pea 207 79 19.50 94.1 Palm Oil 3 0 0.30 114.4 Coconut 1,906 1,223 2,130.23 1,117.9 Cashewnut 10,591 7,182 2,436.95 230.1 Jack Fruit 19 16 0.00 0.0 Banana 484 394 1,600.81 3,304.2 Avocado 19 9 5.85 308.8 Mango 160 0 279.10 1,739.1 Pawpaw 61 29 324.23 5,294.9 Pineapple 533 192 876.00 1,642.9 Orange 1,294 623 5,649.58 4,367.0 Mandarine/Tangerine 48 48 0.00 0.0 Guava 33 0 0.00 0.0 Lime/Lemon 20 3 23.58 1,188.1 Total 15,378 9,799 13,346.13 867.9 cont…. PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 177 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Mafia Star Fruit 2 2 2.63 1,315.0 Coconut 4,778 3,238 10,369.68 2,170.2 Cashewnut 220 159 111.38 507.1 Banana 920 313 727.72 790.6 Mango 50 38 334.41 6,675.3 Pineapple 372 98 36.61 98.3 Orange 40 9 1,337.11 33,037.7 Lime/Lemon 7 4 2.66 391.4 Total 6,390 3,861 12,922.20 2,022.2 Total Rubber Vine Fruit 0 0 0 0.0 Pigeon Pea 1,513 1,129 309.75 204.7 Star Fruit 141 69 936.98 6,627.8 Palm Oil 90 31 53.74 599.4 Coconut 17,300 13,171 30,731.70 1,776.4 Cashewnut 42,263 30,529 12,710.83 300.8 Wattle 0 0 0.00 0.0 Sugarcane 75 10 10.19 135.7 Mshelisheli 0 0 0.21 0.0 Jack Fruit 1,149 159 1,286.93 1,120.1 Mpesheni 165 142 354.92 2,153.5 Banana 3,538 2,268 7,588.92 2,144.8 Avocado 19 41 39.96 2,110.3 Mango 2,244 1,325 15,930.89 7,098.7 Pawpaw 497 230 1,060.39 2,134.0 Pineapple 3,628 2,094 9,418.57 2,595.8 Orange 7,635 3,571 18,807.42 2,463.2 Grape Fruit 149 0 0.00 0.0 Mandarine/Tangerine 1,395 317 1,192.55 855.0 Guava 36 4 7.96 218.7 Lime/Lemon 192 146 230.95 1,200.7 Total 82,031 55,237 100,672.88 1,227.3 cont…. PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 178 Crop Area Planted % Cashewnut 42,263 51.5 Coconut 17,300 21.1 Orange 7,635 9.3 Pineapple 3,628 4.4 Banana 3,538 4.3 Mango 2,244 2.7 Pigeon Pea 1,513 1.8 Mandarine/Tangerine 1,395 1.7 Jack Fruit 1,149 1.4 Pawpaw 497 0.6 Lime/Lemon 192 0.2 Mpesheni 165 0.2 Grape Fruit 149 0.2 Star Fruit 141 0.2 Palm Oil 90 0.1 Sugarcane 75 0.1 Guava 36 0.0 Avocado 19 0.0 Rubber Vine Fruit 0 0.0 Wattle 0 0.0 Mshelisheli 0 0.0 Total 82,031 100.0 District Area planted with cashewnuts(Ha) Total Area planted (ha) % of Total Area Planted hh with cashewnuts Average Planted Area per Household Bagamoyo 6,214 15,810 15 4,085 1.52 Kibaha 2,062 4,896 5 2,889 0.71 Kisarawe 3,541 10,389 8 6,254 0.57 Mkuranga 19,636 29,168 46 17,404 1.13 Rufiji 10,591 15,378 25 9,026 1.17 Mafia 220 6,390 1 542 0.41 Total 42,263 82,031 100 40,199 1.05 District Area planted with coconuts Total Area planted (ha) % of Total Area Planted hh with coconuts Average Planted Area per Household Bagamoyo 3,155 29,168 18 3,292 0.96 Kibaha 1,317 15,378 8 634 2.08 Kisarawe 1,575 15,810 9 5,302 0.30 Mkuranga 4,569 10,389 26 8,836 0.52 Rufiji 1,906 4,896 11 2,456 0.78 Mafia 4,778 6,390 28 3,572 1.34 Total 17,300 82,031 100 24,094 0.72 Coconuts 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Pwani Region Cashewnuts 7.3.3 PERMANENT CROPS: Area Planted with Cashewnuts by District 7.3.4 PERMANENT CROPS: Area planted with Coconuts by District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 179 District Area planted with oranges(Ha) Total Area planted (ha) % of Total Area Planted hh with oranges Average Planted Area per Household Bagamoyo 2,001 15,810 26 2,076 0.96 Kibaha 1,201 4,896 16 182 6.58 Kisarawe 1,937 10,389 25 6,226 0.31 Mkuranga 1,162 29,168 15 3,863 0.30 Rufiji 1,294 15,378 17 2,455 0.53 Mafia 40 6,390 1 203 0.20 Total 7,635 82,031 100 15,006 0.51 District Area planted with pineapples(Ha) Total Area planted (ha) % of Total Area Planted hh with pineapples Average Planted Area per Household Bagamoyo 1,762 15,810 49 1,486 1.19 Kibaha 31 4,896 1 79 0.39 Kisarawe 23 10,389 1 47 0.49 Mkuranga 906 29,168 25 2,213 0.41 Rufiji 533 15,378 15 1,485 0.36 Mafia 372 6,390 10 60 6.25 Total 3,628 82,031 100 5,370 0.68 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Rubber Vine Fruit . . . . . Pigeon Pea 8 . 59 1,426 1,493 Star Fruit . . . 141 141 Palm Oil . 26 . 63 90 Coconut 958 556 219 15,519 17,252 Cashewnut 1,122 3,834 1,011 35,069 41,036 Wattle . . . . . Sugarcane . . . 75 75 Mshelisheli . . . . . Jack Fruit . . . 1,145 1,145 Mpesheni . 53 . 112 165 Banana 279 120 . 3,138 3,538 Avocado . 19 . . 19 Mango 125 136 . 1,981 2,243 Pawpaw 207 . . 290 497 Pineapple 15 15 346 3,252 3,628 Orange 200 798 20 6,595 7,613 Grape Fruit . . . 149 149 Mandarine/Tangerine . . . 1,386 1,386 Guava . . . 36 36 Lime/Lemon 8 34 . 150 192 Total 2,922 5,592 1,655 70,531 80,699 7.3.7 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Fertilizer Use Crop 7.3.5 PERMANENT CROPS: Area planted with Oranges by District 7.3.6 PERMANENT CROPS: Area Planted with Pineapples by District Pineapples Oranges Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 180 Crop Mostly Farm Yard Manure Total % Sour Soup 0 0 0.0 Pigeon Pea 8 1,493 0.5 Star Fruit 0 141 0.0 Palm Oil 0 90 0.0 Coconut 958 17,252 5.6 Cashewnut 1,122 41,036 2.7 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 0 165 0.0 Avocado 279 3,538 7.9 Mango 0 19 0.0 Pawpaw 125 2,243 5.6 Pineapple 207 497 41.6 Orange 15 3,628 0.4 Grape 200 7,613 2.6 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 8 192 4.0 Total 2,922 80,699 3.6 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 0 0.0 Pigeon Pea 59 1,493 3.9 Star Fruit 0 141 0.0 Palm Oil 0 90 0.0 Coconut 219 17,252 1.3 Cashewnut 1,011 41,036 2.5 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 0 165 0.0 Avocado 0 3,538 0.0 Mango 0 19 0.0 Pawpaw 0 2,243 0.0 Pineapple 0 497 0.0 Orange 346 3,628 9.5 Grape 20 7,613 0.3 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 0 192 0.0 Total 1,655 80,699 2.1 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 181 Crop Mostly Compost Total % Sour Soup 0 0 0.0 Pigeon Pea 0 1,493 0.0 Star Fruit 0 141 0.0 Palm Oil 26 90 29.5 Coconut 556 17,252 3.2 Cashewnut 3,834 41,036 9.3 Sugarcane 0 0 0.0 Tamarin 0 75 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 1,145 0.0 Banana 53 165 32.0 Avocado 120 3,538 3.4 Mango 19 19 100.0 Pawpaw 136 2,243 6.1 Pineapple 0 497 0.0 Orange 15 3,628 0.4 Grape 798 7,613 10.5 Mandarine/Tangerine 0 149 0.0 Guava 0 1,386 0.0 Lime/Lemon 0 36 0.0 Bilimbi 34 192 17.8 Total 5,592 80,699 6.9 7.3.7 PERMANENT CROPS: (cont) Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 182 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 183 Number % Number % Number % Bagamoyo 10,153 27 27,137 73 37,290 100 Kibaha 6,210 44 7,819 56 14,029 100 Kisarawe 14,332 77 4,305 23 18,637 100 Mkuranga 12,179 35 22,565 65 34,744 100 Rufiji 10,781 35 20,124 65 30,906 100 Mafia 2,049 35 3,876 65 5,924 100 Total 55,704 39 85,826 61 141,530 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader Other By Factory Total Bagamoyo 2,317 584 6,377 99 190 586 0 0 10,153 Kibaha 4,122 84 2,003 0 0 0 0 0 6,210 Kisarawe 11,654 90 2,208 0 0 0 380 0 14,332 Mkuranga 11,811 224 145 0 0 0 0 0 12,179 Rufiji 8,222 202 2,277 0 0 0 0 81 10,781 Mafia 2,049 0 0 0 0 0 0 0 2,049 Total 40,175 1,183 13,010 99 190 586 380 81 55,704 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader Other By Factory Total Maize 11,079 1,087 12,408 99 190 586 0 0 25,448 Paddy 8,020 162 917 0 0 0 0 81 9,180 Sorghum 1,513 0 481 0 0 42 0 0 2,036 Cassava 25,938 141 982 0 0 0 380 0 27,442 Sweet Potatoes 88 0 0 0 0 0 0 0 88 Cowpeas 681 0 0 0 0 0 0 82 763 Pigeon Peas 40 0 0 0 0 0 0 0 40 Simsim 42 0 0 0 0 0 0 0 42 Groundnut 109 0 0 0 0 0 0 0 109 Oil Palm 351 0 0 0 0 0 0 0 351 Coconut 5,893 0 85 0 0 0 0 0 5,978 Cashewnut 2,513 0 85 0 0 0 0 0 2,598 Banana 72 0 0 0 0 0 0 0 72 Mango 61 0 0 0 0 0 0 0 61 Orange 105 0 0 0 0 0 0 0 105 Total 56,506 1,390 14,957 99 190 629 380 163 74,313 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Pwani Region Method of Processing Method of Processing 8.1.1a: Number of Crop Growing Households Reported to Have Processed Crops by District; 2002/03 Agriculture Year District Households that Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 184 Household / Human Consumption Fuel for Cooking Sale Only Animal Consump tion Did Not Use Other Total Maize 25,064 100 0 0 200 85 25,448 Paddy 9,078 0 0 33 70 0 9,180 Sorghum 2,036 0 0 0 0 0 2,036 Cassava 27,300 0 0 35 107 0 27,442 Sweet Potatoes 88 0 0 0 0 0 88 Cowpeas 689 0 0 0 74 0 763 Pigeon Peas 40 0 0 0 0 0 40 Simsim 0 0 42 0 0 0 42 Groundnut 109 0 0 0 0 0 109 Oil Palm 192 0 159 0 0 0 351 Coconut 5,688 0 53 105 133 0 5,978 Cashewnut 2,462 0 136 0 0 0 2,598 Banana 72 0 0 0 0 0 72 Mango 61 0 0 0 0 0 61 Orange 105 0 0 0 0 0 105 Total 72,982 100 390 173 583 85 74,313 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 161 48 0 145 0 129 98 2,050 22,817 25,448 Paddy 108 0 85 38 0 0 24 1,719 7,206 9,180 Sorghum 0 0 0 0 0 0 0 85 1,951 2,036 Cassava 776 244 0 47 141 0 380 916 24,937 27,442 Sweet Potatoes 0 0 0 0 0 0 0 0 88 88 Cowpeas 40 0 0 0 0 0 0 75 648 763 Pigeon Peas 0 0 0 0 0 0 0 0 40 40 Simsim 0 0 0 0 0 0 42 0 0 42 Groundnut 0 0 0 0 0 0 0 0 109 109 Oil Palm 0 0 0 0 0 0 159 0 192 351 Coconut 565 85 0 0 0 0 0 0 5,328 5,978 Cashewnut 96 0 0 0 0 0 40 0 2,462 2,598 Banana 0 0 0 0 0 0 0 0 72 72 Mango 0 0 0 0 0 0 0 0 61 61 Orange 0 0 0 0 0 0 0 0 105 105 Total 1,747 377 85 231 141 129 742 4,846 66,014 74,313 Crop 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing Crops During 2002/03 Agricultural Year by Use of Product and Crop, Pwani Region Crop Product Use 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing Crops During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Pwani Region Where Sold Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 185 Flour / Meal Grain Oil Juice Pulp Other Total Bagamoyo 9,159 993 0 0 0 0 10,153 Kibaha 4,461 1,080 102 0 0 566 6,210 Kisarawe 11,788 1,282 189 0 39 1,034 14,332 Mkuranga 8,060 1,277 2,044 0 0 799 12,179 Rufiji 7,563 2,540 678 0 0 0 10,781 Mafia 24 1,061 445 20 0 499 2,049 Total 41,056 8,234 3,457 20 39 2,898 55,704 Household / Human Consumptio n Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Other Total Bagamoyo 11,663 100 0 0 0 0 11,763 Kibaha 7,882 0 117 35 34 0 8,069 Kisarawe 21,336 0 39 0 193 0 21,568 Mkuranga 15,275 0 159 0 85 0 15,518 Rufiji 14,374 0 53 105 250 85 14,867 Mafia 2,452 0 22 33 22 0 2,528 Total 72,982 100 390 173 583 85 74,313 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Bagamoyo 76 0 0 98 0 0 98 941 8,941 10,153 Kibaha 276 0 0 38 0 0 42 0 5,853 6,210 Kisarawe 180 48 0 47 44 47 0 0 13,966 14,332 Mkuranga 157 250 0 0 0 82 315 0 11,375 12,179 Rufiji 837 79 85 0 0 0 74 2,724 6,983 10,781 Mafia 45 0 0 0 0 0 0 0 2,004 2,049 Total 1,571 377 85 183 44 129 529 3,664 49,120 55,704 Bran Cake Husk Juice Pulp Shell No by- product Other Total Bagamoyo 7,021 100 298 87 0 0 2,647 0 10,153 Kibaha 2,344 66 154 0 74 1,135 2,437 0 6,210 Kisarawe 5,020 331 0 0 0 6,899 1,985 97 14,332 Mkuranga 2,754 2,006 522 0 169 1,139 5,178 411 12,179 Rufiji 7,127 525 1,443 0 1,390 211 0 85 10,781 Mafia 425 45 1,028 0 0 63 0 487 2,049 Total 24,692 3,072 3,445 87 1,633 9,446 12,247 1,081 55,704 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Pwani Region 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Pwani Region District Main Product Product Use District 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Pwani Region District District By Product 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Pwani Region Where Sold Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 186 MARKETING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 187 Number % Number % Bagamoyo 12,132 33 25,158 67 37,290 Kibaha 6,662 47 7,367 53 14,029 Kisarawe 11,381 61 7,257 39 18,637 Mkuranga 24,950 72 9,794 28 34,744 Rufiji 18,600 60 12,305 40 30,906 Temeke 4,732 80 1,192 20 5,924 Total 78,458 55 63,072 45 141,530 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bagamoyo 302 13,648 0 0 298 96 0 8,468 11,246 34,058 Kibaha 243 2,809 20 20 0 0 59 3,065 6,750 12,967 Kisarawe 47 4,768 0 0 0 184 0 3,075 10,426 18,500 Mkuranga 134 5,355 81 0 327 169 82 4,808 20,856 31,810 Rufiji 143 6,577 0 72 278 0 213 6,346 16,179 29,808 Mafia 45 1,223 23 15 0 48 0 121 4,320 5,796 Total 914 34,380 124 108 902 497 353 25,884 69,778 132,939 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bagamoyo 0.9 40.1 0.0 0.0 0.9 0.3 0.0 24.9 33.0 100 Kibaha 1.9 21.7 0.2 0.2 0.0 0.0 0.5 23.6 52.1 100 Kisarawe 0.3 25.8 0.0 0.0 0.0 1.0 0.0 16.6 56.4 100 Mkuranga 0.4 16.8 0.3 0.0 1.0 0.5 0.3 15.1 65.6 100 Rufiji 0.5 22.1 0.0 0.2 0.9 0.0 0.7 21.3 54.3 100 Mafia 0.8 21.1 0.4 0.3 0.0 0.8 0.0 2.1 74.5 100 Total 0.7 25.9 0.1 0.1 0.7 0.4 0.3 19.5 52.5 100 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Pwani Region Main Reasons for Not Selling Crops District District Main Reasons for Not Selling Crops 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Pwani Region 10.1: Number of Crop Growing Households Reported to have Sold Agricultural Produce by District During 2002/03; Pwani Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 188 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 189 Number of Household % Number of Household % Number of Household % Bagamoyo 988 2.7 36301 97.3 37290 100.0 Kibaha 1045 7.4 12984 92.6 14029 100.0 Kisarawe 324 1.7 18313 98.3 18637 100.0 Mkuranga 2436 7.0 32308 93.0 34744 100.0 Rufiji 395 1.3 30510 98.7 30906 100.0 Mafia 121 2.0 5803 98.0 5924 100.0 Total 5309 3.8 136220 96.2 141530 100.0 District Irrigatable Area (ha) Irrigated Land (ha) % of Irrigatable land used Bagamoyo 240 172 71.7 Kibaha 467 363 77.7 Kisarawe 193 93 48.4 Mkuranga 1974 1608 81.4 Rufiji 298 298 100.0 Mafia 32 29 91.6 Total 3204 2563 80.0 River Dam Well Borehole Canal Pipe water Total Bagamoyo 595 98 198 0 98 0 988 Kibaha 604 111 204 0 23 102 1045 Kisarawe 0 0 324 0 0 0 324 Mkuranga 242 164 1321 158 311 240 2436 Rufiji 395 0 0 0 0 0 395 Mafia 35 0 86 0 0 0 121 Total 1871 374 2132 158 432 342 5309 Gravity Hand Bucket Hand Pump Motor Pump Other Total Bagamoyo 98 693 98 99 0 988 Kibaha 41 858 85 0 61 1045 Kisarawe 0 324 0 0 0 324 Mkuranga 84 2113 80 160 0 2436 Rufiji 0 158 0 0 238 395 Mafia 15 106 0 0 0 121 Total 238 4251 262 259 299 5309 Method of Obtaining Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total District 11.4: IRRIGATION: Number of Agriculture Households by Method Used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON Irrigated Land by District during 2002/03 Agriculture Year 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by Districts During the 2002/03 Agricultural Year Source of Irrigation Water District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 190 Flood Sprinkler Water Hose Bucket / Watering Can Total Bagamoyo 295 98 0 596 988 Kibaha 41 0 104 900 1,045 Kisarawe 0 0 0 324 324 Mkuranga 324 0 0 2,112 2,436 Rufiji 238 0 0 158 395 Mafia 15 0 0 106 121 Total 913 98 104 4,195 5,309 Number % Number % Bagamoyo 276 1 37,014 99 37,290 Kibaha 141 1 13,888 99 14,029 Kisarawe 666 4 17,972 96 18,637 Mkuranga 738 2 34,006 98 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 115 2 5,809 98 5,924 Total 1,935 1 139,595 99 141,530 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Bagamoyo . 1,529 . . 498 . . . 2,027 Kibaha 141 3,274 . . 1,590 . . 164 5,168 Kisarawe . 332 473 . . 2,899 . . 3,703 Mkuranga . 2,077 . 244 5,616 490 . . 8,428 Mafia . 2,587 . . 46 2,820 . . 5,453 Total 141 9,799 473 244 7,749 6,209 . 164 24,779 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 A Year District Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility Type of Erosion Control District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 191 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 192 No of households % No of households % Bagamoyo 840 2 36,450 98 37,290 Kibaha 424 3 13,605 97 14,029 Kisarawe 229 1 18,408 99 18,637 Mkuranga 2,046 6 32,698 94 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 262 4 5,662 96 5,924 Total 3,801 3 137,728 97 141,530 No of households % No of households % Bagamoyo 1,651 4 35,741 96 37,391 Kibaha 1,097 8 12,963 92 14,060 Kisarawe 889 5 17,749 95 18,637 Mkuranga 3,511 10 31,157 90 34,668 Rufiji 551 2 30,437 98 30,988 Mafia 1,613 27 4,311 73 5,924 Total 9,311 7 132,358 93 141,669 No of households % No of households % Bagamoyo 2,255 6 35,035 94 37,290 Kibaha 714 5 13,315 95 14,029 Kisarawe 896 5 17,741 95 18,637 Mkuranga 4,820 14 29,999 86 34,820 Rufiji 2,153 7 28,753 93 30,906 Mafia 578 10 5,346 90 5,924 Total 11,417 8 130,189 92 141,605 Table 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 193 No of households % No of households % Bagamoyo 2,023 5 35,367 95 37,390 Kibaha 1,888 13 12,141 87 14,029 Kisarawe 833 4 17,804 96 18,637 Mkuranga 9,990 29 24,754 71 34,744 Rufiji 2,185 7 28,638 93 30,823 Mafia 100 2 5,825 98 5,924 Total 17,019 12 124,528 88 141,548 No of households % No of households % Bagamoyo 183 0 37,107 100 37,290 Kibaha 42 0 13,987 100 14,029 Kisarawe 0 0 18,637 100 18,637 Mkuranga 79 0 34,665 100 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 22 0 5,903 100 5,924 Total 326 0 141,204 100 141,530 No of households % No of households % Bagamoyo 6,085 16 31,205 84 37,290 Kibaha 3,415 24 10,614 76 14,029 Kisarawe 4,722 25 13,915 75 18,637 Mkuranga 5,230 15 29,514 85 34,744 Rufiji 1,207 4 29,698 96 30,906 Mafia 462 8 5,462 92 5,924 Total 21,121 15 120,409 85 141,530 Table 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 194 Neighbour Not applicable Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 840 2 0 0 0 0 36,450 98 37,290 100 Kibaha 34 0 391 3 0 0 0 0 13,605 97 14,029 100 Kisarawe 0 0 229 1 0 0 0 0 18,408 99 18,637 100 Mkuranga 0 0 1,887 5 0 0 159 0 32,698 94 34,744 100 Rufiji 0 0 0 0 0 0 0 0 30,906 100 30,906 100 Mafia 0 0 196 3 21 0 46 1 5,662 96 5,924 100 Total 34 0 3,542 3 21 0 205 0 137,728 97 141,530 100 Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 0 0 0 0 0 0 0 0 Kibaha 0 0 23 0 109 1 118 1 0 0 34 0 Kisarawe 0 0 0 0 44 0 0 0 0 0 139 1 Mkuranga 162 0 0 0 73 0 0 0 85 0 693 2 Rufiji 0 0 0 0 0 0 0 0 0 0 0 0 Mafia 23 0 24 0 24 0 0 0 0 0 21 0 Total 185 0 48 0 250 0 118 0 85 0 887 1 Number % Number % Number % Number % Number % Bagamoyo 645 2 1,005 3 0 0 35,741 96 37,391 100 Kibaha 328 2 445 3 41 0 12,963 92 14,060 100 Kisarawe 520 3 186 1 0 0 17,749 95 18,637 100 Mkuranga 837 2 1,601 5 60 0 31,157 90 34,668 100 Rufiji 238 1 313 1 0 0 30,437 98 30,988 100 Mafia 1,168 20 329 6 24 0 4,311 73 5,924 100 Total 3,736 3 3,879 3 125 0 132,358 93 141,669 100 Local Market / Trade Store Not applicable Total Development Project Crop Buyers Total Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Locally Produced by Household Locally Produced by Household Neighbour Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Other District Co-operative Local Farmers Group Large Scale Farm Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 195 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 0 0 0 0 0 0 2,255 6 0 0 0 0 35,035 94 37,290 100 Kibaha 0 0 0 0 0 0 0 0 0 0 653 5 61 0 0 0 13,315 95 14,029 100 Kisarawe 0 0 0 0 0 0 0 0 0 0 896 5 0 0 0 0 17,741 95 18,637 100 Mkuranga 162 0 81 0 0 0 0 0 0 0 4,498 13 0 0 80 0 29,999 86 34,820 100 Rufiji 1,628 5 197 1 256 1 0 0 0 0 0 0 72 0 0 0 28,753 93 30,906 100 Mafia 140 2 94 2 24 0 70 1 23 0 228 4 0 0 0 0 5,346 90 5,924 100 Total 1,929 1 372 0 279 0 70 0 23 0 8,531 6 133 0 80 0 130,189 92 141,605 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 695 2 0 0 1,229 3 0 0 0 0 0 0 99 0 0 0 35,367 95 37,390 100 Kibaha 198 1 39 0 1,526 11 42 0 0 0 0 0 42 0 42 0 12,141 87 14,029 100 Kisarawe 233 1 276 1 281 2 44 0 0 0 0 0 0 0 0 0 17,804 96 18,637 100 Mkuranga 327 1 3,579 10 5,306 15 0 0 214 1 80 0 399 1 85 0 24,754 71 34,744 100 Rufiji 0 0 842 3 942 3 171 1 159 1 0 0 71 0 0 0 28,638 93 30,823 100 Mafia 23 0 20 0 57 1 0 0 0 0 0 0 0 0 0 0 5,825 98 5,924 100 Total 1,476 1 4,755 3 9,340 7 257 0 374 0 80 0 612 0 127 0 124,528 88 141,548 100 Number % Number % Number % Number % Number % Bagamoyo 0 0 0 0 183 0 37,107 100 37,290 100 Kibaha 42 0 0 0 0 0 13,987 100 14,029 100 Kisarawe 0 0 0 0 0 0 18,637 100 18,637 100 Mkuranga 0 0 79 0 0 0 34,665 100 34,744 100 Rufiji 0 0 0 0 0 0 30,906 100 30,906 100 Mafia 0 0 0 0 22 0 5,903 100 5,924 100 Total 42 0 79 0 205 0 141,204 100 141,530 100 Neighbour Other Not applicable Neighbour Other Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Co-operative Local Farmers Group Local Market / Trade Store District Locally Produced by Household Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Development Project Large Scale Farm Development Project Crop Buyers Local Farmers Group Local Market / Trade Store Local Farmers Group Crop Buyers Total Total Not applicable Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store District Co-operative Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 196 Crop Buyers Number % Number % Number % Number % Number % Number Number % Bagamoyo 195 1 201 1 3,811 10 98 0 0 0 0 102 0 Kibaha 0 0 0 0 3,384 24 0 0 0 0 31 0 0 Kisarawe 0 0 90 0 2,513 13 0 0 1,054 6 0 0 0 Mkuranga 0 0 0 0 4,706 14 60 0 0 0 0 0 0 Rufiji 0 0 0 0 1,051 3 0 0 74 0 0 0 0 Mafia 0 0 0 0 167 3 0 0 0 0 274 0 0 Total 195 0 290 0 15,632 11 157 0 1,128 1 305 102 0 Number % Number % Number % Number % Number % Bagamoyo 0 0 1,489 4 189 1 31,205 84 37,290 100 Kibaha 0 0 0 0 0 0 10,614 76 14,029 100 Kisarawe 325 2 696 4 45 0 13,915 75 18,637 100 Mkuranga 224 1 240 1 0 0 29,514 85 34,744 100 Rufiji 83 0 0 0 0 0 29,698 96 30,906 100 Mafia 0 0 21 0 0 0 5,462 92 5,924 100 Total 632 0 2,446 2 234 0 120,409 85 141,530 100 Number % Number % Number % Number % Number % Bagamoyo 0 0 95 11 196 23 198 24 351 42 840 Kibaha 72 17 102 24 143 34 84 20 23 6 424 Kisarawe 0 0 0 0 0 0 0 0 229 100 229 Mkuranga 479 23 85 4 233 11 303 15 946 46 2,046 Mafia 53 20 0 0 42 16 77 29 91 35 262 Total 603 16 281 7 614 16 662 17 1,641 43 3,801 District Locally Produced by Household Neighbour Other Not applicable Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number cont…...12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Large Scale Farm Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 197 Number % Number % Number % Number % Number % Bagamoyo 1,161 70 490 30 0 0 0 0 0 0 1,651 Kibaha 709 65 256 23 102 9 31 3 0 0 1,097 Kisarawe 616 69 91 10 91 10 0 0 91 10 889 Mkuranga 1,852 53 1,051 30 233 7 296 8 80 2 3,511 Rufiji 467 85 0 0 0 0 84 15 0 0 551 Mafia 1,515 94 21 1 67 4 0 0 11 1 1,613 Total 6,319 68 1,908 20 492 5 411 4 181 2 9,311 Between 10 and 20 km 20 km and Above Total 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 198 Number % Number % Number % Bagamoyo 2,255 100 0 0 0 0 2,255 Kibaha 678 95 36 5 0 0 714 Kisarawe 896 100 0 0 0 0 896 Mkuranga 4,738 98 0 0 83 2 4,820 Rufiji 2,153 100 0 0 0 0 2,153 Mafia 578 100 0 0 0 0 578 Total 11,298 99 36 0 83 1 11,417 Number % Number % Number % Number % Number % Bagamoyo 1,582 26 718 12 1,239 20 586 10 1,960 32 6,085 Kibaha 202 6 498 15 1,291 38 507 15 917 27 3,415 Kisarawe 982 21 599 13 289 6 522 11 2,330 49 4,722 Mkuranga 922 18 307 6 389 7 516 10 3,096 59 5,230 Rufiji 156 13 322 27 491 41 0 0 238 20 1,207 Mafia 190 41 15 3 0 0 40 9 217 47 462 Total 4,035 19 2,460 12 3,700 18 2,170 10 8,757 41 21,121 Less than 1 km Number % Number % Number % Number % Number % Bagamoyo 490 24 392 19 391 19 401 20 348 17 2,023 Kibaha 334 18 274 15 455 24 273 14 552 29 1,888 Kisarawe 229 27 184 22 96 11 0 0 324 39 833 Mkuranga 2,132 21 1,521 15 3,008 30 375 4 2,954 30 9,990 Rufiji 1,171 54 309 14 161 7 244 11 301 14 2,185 Mafia 0 0 0 0 20 20 43 43 37 37 100 Total 4,357 26 2,680 16 4,131 24 1,336 8 4,517 27 17,019 District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 10 and 20 km Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 199 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 8,063 22 17,986 49 890 2 76 0 1,680 5 6,325 17 100 0 1,328 4 36,450 100 Kibaha 663 5 9,351 69 126 1 0 0 265 2 2,493 18 0 0 706 5 13,605 100 Kisarawe 4,357 24 8,973 49 279 2 0 0 535 3 3,885 21 0 0 379 2 18,408 100 Mkuranga 2,987 9 21,458 66 662 2 81 0 2,311 7 4,763 15 79 0 358 1 32,698 100 Rufiji 12,176 39 12,939 42 1,030 3 71 0 1,680 5 2,604 8 85 0 321 1 30,906 100 Mafia 1,186 21 3,494 62 0 0 0 0 235 4 610 11 16 0 120 2 5,662 100 Total 29,432 21 74,200 54 2,987 2 229 0 6,706 5 20,681 15 281 0 3,212 2 137,728 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 14,109 39 2,980 8 7,683 21 1,684 5 2,258 6 5,781 16 199 1 1,046 3 35,741 100 Kibaha 4,781 37 1,578 12 3,568 28 385 3 422 3 1,912 15 0 0 318 2 12,963 100 Kisarawe 11,727 66 1,843 10 1,380 8 139 1 719 4 1,896 11 0 0 45 0 17,749 100 Mkuranga 17,585 56 5,718 18 1,338 4 970 3 2,935 9 2,247 7 79 0 285 1 31,157 100 Rufiji 17,909 59 757 2 5,293 17 295 1 3,000 10 3,013 10 85 0 85 0 30,437 100 Mafia 1,677 39 646 15 879 20 296 7 198 5 561 13 0 0 55 1 4,311 100 Total 67,788 51 13,521 10 20,141 15 3,768 3 9,531 7 15,410 12 364 0 1,834 1 132,358 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 3,037 9 3,692 11 9,608 27 893 3 11,976 34 4,538 13 522 1 769 2 35,035 100 Kibaha 2,327 17 2,145 16 3,589 27 982 7 1,603 12 1,888 14 170 1 611 5 13,315 100 Kisarawe 1,992 11 593 3 8,142 46 270 2 4,564 26 1,994 11 42 0 143 1 17,741 100 Mkuranga 3,138 10 4,255 14 5,513 18 537 2 13,538 45 2,252 8 79 0 686 2 29,999 100 Rufiji 9,454 33 771 3 5,447 19 1,277 4 8,537 30 3,096 11 85 0 85 0 28,753 100 Mafia 705 13 1,271 24 1,404 26 280 5 903 17 629 12 0 0 155 3 5,346 100 Total 20,653 16 12,728 10 33,702 26 4,239 3 41,121 32 14,399 11 898 1 2,449 2 130,189 100 Total Too Much Labour Required Too Much Labour Required Do not Know How to Use Locally Produced by Household Other Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Input is of No Use Locally Produced by Household Do not Know How to Use Input is of No Use 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Total Not Available Price Too High No Money to Buy Other Input is of No Use Locally Produced by Household 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 200 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 4,398 12 24,203 68 904 3 185 1 1,400 4 2,760 8 185 1 1,331 4 35,367 100 Kibaha 444 4 8,844 73 79 1 34 0 259 2 1,936 16 0 0 544 4 12,141 100 Kisarawe 2,196 12 13,516 76 187 1 0 0 1,256 7 510 3 0 0 140 1 17,804 100 Mkuranga 1,099 4 20,896 84 607 2 0 0 857 3 1,089 4 0 0 206 1 24,754 100 Rufiji 7,276 25 17,153 60 568 2 81 0 1,814 6 1,130 4 0 0 615 2 28,638 100 Mafia 521 9 3,580 61 142 2 22 0 650 11 776 13 0 0 134 2 5,825 100 Total 15,934 13 88,192 71 2,488 2 322 0 6,236 5 8,202 7 185 0 2,970 2 124,528 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 6,448 17 24,071 65 591 2 0 0 1,968 5 2,706 7 85 0 1,238 3 37,107 100 Kibaha 1,010 7 9,212 66 15 0 218 2 783 6 2,343 17 0 0 406 3 13,987 100 Kisarawe 2,109 11 13,350 72 233 1 0 0 2,616 14 233 1 0 0 95 1 18,637 100 Mkuranga 2,309 7 21,749 63 566 2 0 0 5,113 15 4,515 13 0 0 413 1 34,665 100 Rufiji 8,667 28 15,848 51 999 3 71 0 3,573 12 1,347 4 0 0 400 1 30,906 100 Mafia 398 7 3,707 63 95 2 22 0 716 12 846 14 0 0 118 2 5,903 100 Total 20,942 15 87,938 62 2,498 2 312 0 14,768 10 11,991 8 85 0 2,671 2 141,204 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 6,305 20 20,710 66 679 2 188 1 787 3 1,500 5 98 0 938 3 31,205 100 Kibaha 1,577 15 7,545 71 0 0 42 0 122 1 803 8 37 0 487 5 10,614 100 Kisarawe 4,114 30 9,076 65 48 0 0 0 225 2 362 3 46 0 45 0 13,915 100 Mkuranga 7,757 26 18,229 62 562 2 0 0 1,601 5 932 3 149 1 285 1 29,514 100 Rufiji 11,411 38 14,947 50 572 2 80 0 1,419 5 893 3 58 0 318 1 29,698 100 Mafia 2,101 38 2,748 50 96 2 46 1 141 3 212 4 0 0 118 2 5,462 100 Total 33,266 28 73,254 61 1,957 2 356 0 4,295 4 4,702 4 388 0 2,191 2 120,409 100 Too Much Labour Required Input is of No Use Price Too High Total Total Do not Know How to Use Locally Produced by Household Other Input is of No Use 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT Using Improved Seeds by District, 2002/03 Agricultural Year District Not Available No Money to Buy 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT Using Insecticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Input is of No Use Other Total Other 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Tanzania Agriculture Sample Census - 2003 Pwani 201 Number % Number % Number % Number % Number % Bagamoyo 565 67 174 21 0 0 100 12 840 100 Kibaha 31 7 353 83 41 10 0 0 424 100 Kisarawe 91 40 138 60 0 0 0 0 229 100 Mkuranga 605 30 1,278 62 163 8 0 0 2,046 100 Mafia 118 45 99 38 46 17 0 0 262 100 Total 1,410 37 2,041 54 250 7 100 3 3,801 100 Total 565 23 1,741 70 161 6 13 1 2,480 100 Number % Number % Number % Number % Number % Bagamoyo 690 42 803 49 158 10 0 0 1,651 100 Kibaha 255 23 698 64 103 9 41 4 1,097 100 Kisarawe 328 37 465 52 95 11 0 0 889 100 Mkuranga 929 26 2,254 64 328 9 0 0 3,511 100 Rufiji 84 15 467 85 0 0 0 0 551 100 Mafia 546 34 876 54 191 12 0 0 1,613 100 Total 2,831 30 5,564 60 875 9 41 0 9,311 100 Number % Number % Number % Number % Number % Number % Bagamoyo 1,266 56 646 29 179 8 82 4 82 4 2,255 100 Kibaha 0 0 450 63 264 37 0 0 0 0 714 100 Kisarawe 288 32 465 52 143 16 0 0 0 0 896 100 Mkuranga 974 20 1,510 31 2,252 47 85 2 0 0 4,820 100 Rufiji 1,073 50 1,008 47 72 3 0 0 0 0 2,153 100 Mafia 204 35 327 57 46 8 0 0 0 0 578 100 Total 3,806 33 4,406 39 2,957 26 166 1 82 1 11,417 100 Poor 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 District Excellent Good Average Does not Work Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Average Poor Total Total Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizers by District, 2002/03 Agricultural Year District Excellent Good Average Poor District Excellent Good Tanzania Agriculture Sample Census - 2003 Pwani 202 Number % Number % Number % Number % Number % Number % Bagamoyo 632 31 898 44 394 19 0 0 99 5 2,023 100 Kibaha 81 4 1,735 92 73 4 0 0 0 0 1,888 100 Kisarawe 376 45 267 32 142 17 48 6 0 0 833 100 Mkuranga 2,187 22 5,729 57 1,515 15 401 4 157 2 9,990 100 Rufiji 1,088 50 867 40 146 7 85 4 0 0 2,185 100 Mafia 60 60 20 20 20 20 0 0 0 0 100 100 Total 4,424 26 9,516 56 2,289 13 534 3 256 2 17,019 100 Number % Number % Number % Bagamoyo 0 0 183 100 183 100 Kibaha 0 0 42 100 42 100 Mkuranga 79 100 0 0 79 100 Mafia 22 100 0 0 22 100 Total 101 31 224 69 326 100 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Number % Number % Number % Bagamoyo 2,375 39 2,371 39 1,254 21 0 0 85 1 6,085 100 Bagamoyo 6,165 17 31,124 83 37,290 100 Kibaha 366 11 2,765 81 266 8 0 0 18 1 3,415 100 Kibaha 3,417 24 10,611 76 14,029 100 Kisarawe 1,350 29 2,990 63 383 8 0 0 0 0 4,722 100 Kisarawe 2,451 13 16,186 87 18,637 100 Mkuranga 1,883 36 3,008 58 339 6 0 0 0 0 5,230 100 Mkuranga 5,355 15 29,389 85 34,744 100 Rufiji 247 20 887 73 0 0 0 0 74 6 1,207 100 Rufiji 1,668 5 29,237 95 30,906 100 Mafia 316 68 102 22 23 5 21 5 0 0 462 100 Mafia 1,635 28 4,289 72 5,924 100 Total 6,536 31 12,123 57 2,265 11 21 0 176 1 21,121 100 Total 20,692 15 120,838 85 141,530 100 Total Does not Work Total Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Total District Excellent Good 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year District District Excellent Good Average Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 203 Number % Number % Number % Number % Bagamoyo 8,236 22 29,155 78 37,391 Bagamoyo 7,756 21 29,534 79 37,290 Kibaha 4,343 31 9,717 69 14,060 Kibaha 3,358 24 10,671 76 14,029 Kisarawe 2,260 12 16,377 88 18,637 Kisarawe 1,921 10 16,716 90 18,637 Mkuranga 9,499 27 25,169 73 34,668 Mkuranga 11,986 34 22,833 66 34,820 Rufiji 1,837 6 29,151 94 30,988 Rufiji 1,310 4 29,596 96 30,906 Mafia 2,416 41 3,509 59 5,924 Mafia 1,197 20 4,728 80 5,924 Total 28,591 20 113,078 80 141,669 Total 27,528 19 114,077 81 141,605 Number % Number % Number % Number % Bagamoyo 10,540 28 26,850 72 37,390 Bagamoyo 5,940 16 31,349 84 37,290 Kibaha 5,054 36 8,975 64 14,029 Kibaha 1,447 10 12,582 90 14,029 Kisarawe 3,649 20 14,988 80 18,637 Kisarawe 1,865 10 16,772 90 18,637 Mkuranga 16,392 47 18,352 53 34,744 Mkuranga 2,737 8 32,007 92 34,744 Rufiji 5,813 19 25,011 81 30,823 Rufiji 694 2 30,211 98 30,906 Mafia 900 15 5,024 85 5,924 Mafia 799 13 5,125 87 5,924 Total 42,349 30 99,199 70 141,548 Total 13,482 10 128,047 90 141,530 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Next Year Farm Yard Manure Agricultural Households With NO Plan to Use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use COMPOST ManureNext Year Agricultural Households With NO Plan to use Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With a Plan to Use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With a Plan to Use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Herbicides Next Year g Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 204 Number % Number % Bagamoyo 17,411 47 19,879 53 37,290 Kibaha 7,950 57 6,079 43 14,029 Kisarawe 7,657 41 10,980 59 18,637 Mkuranga 11,760 34 22,984 66 34,744 Rufiji 4,812 16 26,094 84 30,906 Mafia 1,844 31 4,080 69 5,924 Total 51,434 36 90,096 64 141,530 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With a Plan to Use Improved Seeds Next Year Agricultural Households With NO Plan to Use Improved Seeds Next Year Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 205 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 206 Number % Number % Bagamoyo 98 100 0 0 98 Mkuranga 1,339 89 160 11 1,499 Rufiji 83 100 0 0 83 Total 1,521 90 160 10 1,681 Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Bagamoyo 0 98 0 0 0 98 Mkuranga 80 0 1,094 162 163 1,499 Rufiji 0 0 0 0 83 83 Total 80 98 1,094 162 247 1,681 Total 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year. District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households Receiving Credit by Sex of Household Head and District During the 2002/03 Agriculture Year Total District Male Female Source of Credit Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 207 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Bagamoyo 1,139 8,064 3,848 764 14,888 1,474 0 102 6,913 37,192 Kibaha 704 4,575 1,485 475 4,261 318 413 84 1,715 14,029 Kisarawe 95 5,578 1,418 684 6,044 237 0 0 4,580 18,637 Mkuranga 1,643 3,058 3,090 1,097 17,279 1,367 85 0 5,625 33,245 Rufiji 626 7,233 1,625 147 15,323 592 75 154 5,046 30,822 Mafia 429 753 338 243 2,835 239 47 20 1,022 5,924 Total 4,635 29,261 11,805 3,410 60,631 4,227 620 361 24,900 139,849 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Bagamoyo 0 0 0 0 0 98 98 0 196 Mkuranga 478 400 554 1,424 400 400 400 400 4,455 Rufiji 0 0 0 0 0 0 0 83 83 Total Credits 478 400 554 1,424 400 498 498 483 4,734 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main Reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year District Credit Use Tanzania Agriculture Sample Census - 2003 Pwani 208 Appendix II 209 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 210 District Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Terminalia Ivorensis Leucena Spp Bagamoyo 1,292 13,666 . 613 . . . 24,471 . . . Kibaha 68,155 164 24,199 6,142 . 122,769 2,017 . . . 42 Kisarawe 2,461 237 280 1,184 9,520 95 . . . 947 1,895 Mkuranga 79 414 . 7,631 2,173 1,078 . . . . . Rufiji . . . . . . 1,260 34,697 . . 2,519 Mafia . . . . . 240 . . 240 . . Total 71,987 14,480 24,479 15,570 11,693 124,182 3,276 59,168 240 947 4,455 % 20.5 4.1 7.0 4.4 3.3 35.3 0.9 16.8 0.1 0.3 1.3 District Syszygium Spp Azadritacht a Spp Moringa Spp Saraca Spp Total Bagamoyo 91 565 . . 40,698 Kibaha 41 2,207 1,064 . 226,797 Kisarawe . 950 9,473 142 27,184 Mkuranga 79 2,724 . 335 14,512 Rufiji . 963 . . 39,439 Mafia . . 2,399 . 2,879 Total 211 7,409 12,936 477 351,509 % 0.1 2.1 3.7 0.1 100.0 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Specie and District During the 2002/03 Agriculture Year, Pwani Region cont. 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Specie and District During the 2002/03 Agriculture Year, Pwani Region Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 211 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Bagamoyo 656 40,698 0 . 0 . 656 40,698 Kibaha 71 64,006 231 130,526 20 32,265 322 226,797 Kisarawe 275 2,927 133 337 95 23,920 503 27,184 Mkuranga 714 4,309 466 10,056 0 . 1,181 14,365 Rufiji 310 10,700 0 . 151 28,739 461 39,439 Mafia 20 240 0 . 24 2,639 44 2,879 Total 2,045 122,881 831 140,919 290 87,563 3,166 351,362 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bagamoyo 8,931 1,148 9,152 1,595 144 0 20,971 Kibaha 3,685 425 845 945 0 504 6,403 Kisarawe 3,305 2,002 424 834 0 87 6,653 Mkuranga 0 0 0 77 0 0 77 Rufiji 106 0 106 318 0 0 530 Mafia 147 98 0 0 49 97 391 Total 16,214 3,785 10,527 3,870 193 735 35,324 14.3 ON FARM TREE PLANTING: Number of Responses by Main Use of Planted Trees and District for the 2002/03 agriculture year, Pwani Region District 14.2 TREE FARMING: Number of Households with Planted Trees on Their Land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Pwani Region Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Main Use Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 212 1-9 1-19 20-29 30-39 40-49 60+ Bagamoyo 89 182 0 0 0 0 Kibaha 0 0 15 0 0 0 Kisarawe 47 0 0 47 514 0 Mkuranga 394 208 85 0 0 299 Rufiji 420 0 0 0 0 0 Mafia 0 0 22 23 0 11 Total 949 390 121 70 514 309 % 40.3 16.6 5.1 3.0 21.8 13.1 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Bagamoyo 0 0 0 6 1 1 1 9 Kibaha 2 4 0 10 2 1 0 19 Kisarawe 2 5 0 7 0 2 1 17 Mkuranga 1 3 1 6 4 3 1 19 Rufiji 0 2 0 2 0 1 0 5 Mafia 1 0 0 0 1 0 1 3 Total 6 14 1 31 8 8 4 72 District 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Pwani Region District 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Pwani Region Distance to Community Planted Forest (km) Second Use Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 213 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 214 Number % Number % Bagamoyo 11,835 31.7 25,454 68.3 37,290 Kibaha 6,049 43.1 7,980 56.9 14,029 Kisarawe 11,435 61.4 7,202 38.6 18,637 Mkuranga 9,560 27.5 25,184 72.5 34,744 Rufiji 7,603 24.6 23,303 75.4 30,906 Mafia 245 4.1 5,680 95.9 5,924 Total 46,727 33.0 94,803 67.0 141,530 Number % Number % Number % Number % Number % Number % Bagamoyo 2,576 22.3 6,338 54.8 2,382 20.6 0 0.0 262 2.3 11,558 100.0 Kibaha 256 4.2 4,085 67.5 1,501 24.8 164 2.7 42 0.7 6,049 100.0 Kisarawe 617 5.4 9,354 82.2 1,415 12.4 0 0.0 0 0.0 11,386 100.0 Mkuranga 1,514 15.8 6,906 72.2 1,095 11.5 45 0.5 0 0.0 9,560 100.0 Rufiji 2,496 33.2 3,623 48.1 1,175 15.6 148 2.0 85 1.1 7,527 100.0 Mafia 15 6.3 192 78.5 37 15.2 0 0.0 0 0.0 245 100.0 Total 7,474 16.1 30,499 65.8 7,605 16.4 357 0.8 390 0.8 46,325 100.0 Number % Number % Number % Number % Number % Number % Number % Bagamoyo 11,256 95.9 0 0.0 197 1.7 286 2.4 0 0.0 0 0.0 11,739 100.0 Kibaha 5,711 95.0 42 0.7 0 0.0 220 3.7 42 0.7 0 0.0 6,015 100.0 Kisarawe 11,245 98.3 143 1.2 0 0.0 0 0.0 0 0.0 47 0.4 11,435 100.0 Mkuranga 8,730 94.5 0 0.0 160 1.7 249 2.7 98 1.1 0 0.0 9,237 100.0 Rufiji 7,541 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 7,541 100.0 Mafia 186 81.5 42 18.5 0 0.0 0 0.0 0 0.0 0 0.0 228 100.0 Total 44,669 96.7 227 0.5 357 0.8 755 1.6 140 0.3 47 0.1 46,195 100.0 Total 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Pwani Region Very Good Good Average Poor No Good Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Pwani Region Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 215 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 10,852 0 197 286 0 0 11,335 37,290 30.4 Kibaha 5,631 42 0 178 42 0 5,893 14,029 42.0 Kisarawe 11,061 143 0 0 0 47 11,250 18,637 60.4 Mkuranga 8,206 0 160 249 98 0 8,713 34,744 25.1 Rufiji 7,467 0 0 0 0 0 7,467 30,906 24.2 Mafia 154 22 0 0 0 0 176 5,924 3.0 Total 43,371 207 357 713 140 47 44,834 141,530 31.7 Government NGO / Developme nt Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 7,009 87 98 100 0 0 7,294 37,290 19.6 Kibaha 3,845 84 0 88 0 131 4,149 14,029 29.6 Kisarawe 4,601 183 0 0 0 48 4,832 18,637 25.9 Mkuranga 6,914 53 157 165 53 0 7,342 34,744 21.1 Rufiji 4,765 0 0 0 0 157 4,922 30,906 15.9 Mafia 49 20 0 0 0 42 111 5,924 1.9 Total 27,184 427 255 353 53 378 28,649 141,530 20.2 Government NGO / Developme nt Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 4,441 0 0 85 93 4,619 37,290 12.4 Kibaha 2,148 83 20 58 0 2,309 14,029 16.5 Kisarawe 2,012 474 0 0 95 2,582 18,637 13.9 Mkuranga 3,208 85 0 0 227 3,520 34,744 10.1 Rufiji 3,337 159 0 0 85 3,582 30,906 11.6 Mafia 9 22 0 0 20 51 5,924 0.9 Total 15,155 823 20 143 521 16,663 141,530 11.8 % of total number of households Spacing 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Use of Agrochemicals Total Number of Households District District Total Number of Households % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households District Erosion Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 216 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 6,098 0 98 0 0 146 6,342 37,290 17.0 Kibaha 3,398 76 0 130 0 62 3,666 14,029 26.1 Kisarawe 3,541 505 0 0 0 95 4,141 18,637 22.2 Mkuranga 5,929 85 160 147 0 81 6,401 34,744 18.4 Rufiji 4,128 0 0 0 0 85 4,214 30,906 13.6 Mafia 170 22 0 0 20 0 212 5,924 3.6 Total 23,265 688 258 276 20 469 24,976 141,530 17.6 Government NGO / Development Cooperative Large Scale Other Not applicable Total Bagamoyo 5,649 0 98 199 0 0 5,946 37,290 15.9 Kibaha 2,641 42 0 88 27 135 2,933 14,029 20.9 Kisarawe 2,512 131 47 0 0 231 2,922 18,637 15.7 Mkuranga 4,655 0 0 0 0 154 4,809 34,744 13.8 Rufiji 3,831 0 0 0 0 157 3,988 30,906 12.9 Mafia 69 0 0 0 0 20 89 5,924 1.5 Total 19,358 173 145 287 27 698 20,687 141,530 14.6 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 8,146 0 197 85 0 100 8,527 37,290 22.9 Kibaha 4,678 124 0 79 27 274 5,183 14,029 36.9 Kisarawe 7,216 994 0 89 0 225 8,525 18,637 45.7 Mkuranga 5,313 0 79 0 0 81 5,473 34,744 15.8 Rufiji 5,199 0 0 0 0 85 5,284 30,906 17.1 Mafia 75 0 0 0 20 41 135 5,924 2.3 Total 30,626 1,119 276 254 47 806 33,127 141,530 23.4 % of total number of households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Organic Fertilizer Use District District Use of Improved Seed Inorganic Fertilizer Use % of total number of households District Total Number of Households 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 217 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 5,490 0 0 85 0 227 5,803 37,290 15.9 Kibaha 2,124 40 0 0 0 192 2,356 14,029 20.9 Kisarawe 562 531 47 0 0 0 1,140 18,637 15.7 Mkuranga 608 0 0 0 0 81 689 34,744 13.8 Rufiji 3,521 0 0 0 72 146 3,739 30,906 12.9 Mafia 0 0 0 0 0 20 20 5,924 1.5 Total 12,306 571 47 85 72 666 13,747 141,530 14.6 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 3,061 99 98 98 282 3,638 37,290 9.8 Kibaha 2,346 110 0 80 58 2,594 14,029 18.5 Kisarawe 1,438 0 47 0 0 1,485 18,637 8.0 Mkuranga 4,298 0 0 0 0 4,298 34,744 12.4 Rufiji 3,044 72 0 0 0 3,116 30,906 10.1 Mafia 0 0 0 0 20 20 5,924 0.3 Total 14,187 281 145 178 360 15,151 141,530 10.7 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Bagamoyo 6,670 0 0 0 82 345 7,096 37,290 19.0 Kibaha 2,841 60 0 35 0 112 3,048 14,029 21.7 Kisarawe 4,238 48 0 0 0 46 4,332 18,637 23.2 Mkuranga 3,640 0 79 0 0 73 3,793 34,744 10.9 Rufiji 5,002 0 0 0 0 0 5,002 30,906 16.2 Mafia 24 0 0 0 0 20 44 5,924 0.7 Total 22,413 108 79 35 82 596 23,314 141,530 16.5 % of total number of households 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Household s Total Number of Households Crop Storage District District District Mechanisation / LST Total Number of Households % of total number of households % of total number of households Irrigation Technology Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 218 Government NGO / Development Project Large Scale Farm Not applicable Total Bagamoyo 7,341 0 435 0 7,777 37,290 20.9 Kibaha 4,637 15 98 239 4,989 14,029 35.6 Kisarawe 8,292 48 0 92 8,432 18,637 45.2 Mkuranga 5,059 80 205 0 5,345 34,744 15.4 Rufiji 4,987 0 0 74 5,061 30,906 16.4 Mafia 45 0 0 20 65 5,924 1.1 Total 30,363 143 739 424 31,669 141,530 22.4 Government NGO / Development Project Other Not applicable Total Bagamoyo 2,829 100 85 274 3,288 37,290 8.8 Kibaha 1,703 27 0 0 1,730 14,029 12.3 Kisarawe 2,634 740 0 0 3,374 18,637 18.1 Mkuranga 3,688 0 85 238 4,011 34,744 11.5 Rufiji 3,367 0 0 0 3,367 30,906 10.9 Mafia 0 0 0 20 20 5,924 0.3 Total 14,221 867 170 532 15,789 141,530 11.2 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Bagamoyo 1,624 82 0 0 0 1,706 37,290 4.6 Kibaha 2,186 200 20 35 0 2,441 14,029 17.4 Kisarawe 2,190 231 0 0 47 2,468 18,637 13.2 Mkuranga 3,644 1,220 160 0 73 5,097 34,744 14.7 Rufiji 2,656 0 0 0 0 2,656 30,906 8.6 Mafia 24 0 0 0 20 44 5,924 0.7 Total 12,324 1,733 180 35 141 14,412 141,530 10.2 District Agro-forestry District District Agro-progressing Total Number of Households % of total number of households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-forestry by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households % of total number of households Vermin Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 219 Government NGO / Development Project Not applicable Total Bagamoyo 223 96 93 412 37,290 1.1 Kibaha 252 47 23 322 14,029 2.3 Kisarawe 228 48 0 276 18,637 1.5 Mkuranga 147 132 79 357 34,744 1.0 Rufiji 2,511 62 0 2,573 30,906 8.3 Mafia 0 0 20 20 5,924 0.3 Total 3,361 385 215 3,960 141,530 2.8 Government NGO / Development Project Cooperative Not applicable Total Bagamoyo 223 96 0 93 412 37,290 1.1 Kibaha 142 62 0 0 204 14,029 1.5 Kisarawe 229 48 47 0 324 18,637 1.7 Mkuranga 302 0 0 0 302 34,744 0.9 Rufiji 2,131 0 0 0 2,131 30,906 6.9 Mafia 0 0 0 20 20 5,924 0.3 Total 3,027 206 47 113 3,392 141,530 2.4 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 11,335 10,883 96 6,942 2,534 37 4,106 1,742 42 Kibaha 5,818 5,007 86 4,056 1,363 34 2,078 593 29 Kisarawe 11,250 10,153 90 4,695 1,259 27 2,344 656 28 Mkuranga 8,713 7,937 91 7,342 5,004 68 3,212 965 30 Rufiji 7,386 6,223 84 4,628 1,039 22 3,135 290 9 Mafia 176 119 68 69 20 29 31 31 100 Total 44,677 40,322 90 27,732 11,219 40 14,906 4,278 29 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region District District Beekeeping Fish Farming 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Pwani Region District Use of Agrochemicals Erosion Control Spacing 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Pwani Region Total Number of Households % of total number of households Total Number of Households % of total number of households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 220 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 6,051 1,758 29 5,549 956 17 8,129 2,286 28 Kibaha 3,589 870 24 2,765 572 21 5,177 2,211 43 Kisarawe 3,950 1,199 30 2,459 234 10 8,521 4,423 52 Mkuranga 6,401 4,030 63 4,644 1,325 29 5,452 3,317 61 Rufiji 3,841 232 6 3,841 83 2 5,209 534 10 Mafia 208 184 89 69 28 40 95 25 26 Total 24,040 8,272 34 19,327 3,197 17 32,583 12,797 39 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 5,462 839 15 2,381 1,369 58 6,999 4,892 70 Kibaha 2,184 468 21 2,287 826 36 2,993 1,517 51 Kisarawe 806 0 0 1,357 329 24 4,337 2,519 58 Mkuranga 286 0 0 4,217 1,534 36 3,871 386 10 Rufiji 3,516 391 11 2,422 864 36 5,149 1,844 36 Mafia 0 0 0 0 0 0 24 24 100 Total 12,254 1,697 14 12,663 4,924 39 23,372 11,182 48 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 7,667 5,932 77 2,604 2,625 101 1,511 1,166 77 Kibaha 4,962 3,129 63 1,504 1,006 67 2,367 905 38 Kisarawe 8,432 7,966 94 3,334 2,799 84 2,372 902 38 Mkuranga 5,207 4,897 94 3,773 1,683 45 5,097 2,291 45 Rufiji 5,065 2,231 44 3,065 1,154 38 2,145 387 18 Mafia 45 45 100 0 0 0 0 0 0 Total 31,379 24,200 77 14,280 9,268 65 13,492 5,650 42 District District District Organic Fertilizer Use Vermin Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Pwani Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Pwani Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Pwani Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 221 Received Adopted % Received Adopted % Received Adopted % Bagamoyo 177 372 0 177 270 0 0 95 0 Kibaha 200 124 62 102 0 0 1,094 1,090 100 Kisarawe 182 39 22 142 87 61 179 95 53 Mkuranga 279 53 19 147 0 0 208 132 64 Rufiji 2,501 62 2 2,059 218 11 927 80 9 Mafia 0 0 0 0 0 0 0 0 0 Total 3,338 650 19 2,627 575 22 2,408 1,492 62 Other Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Pwani Region District Beekeeping Tanzania Agriculture Sample Census - 2003 Pwani 222 Appendix II 223 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 224 Number % Number % Bagamoyo 0 0 37,290 100 37,290 Kibaha 0 0 14,029 100 14,029 Kisarawe 0 0 18,637 100 18,637 Mkuranga 0 0 34,744 100 34,744 Rufiji 0 0 30,906 100 30,906 Mafia 46 1 5,878 99 5,924 Total 46 0 141,484 100 141,530 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Mafia 92 92 19 92 92 19 Total 92 92 19 92 92 19 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Mafia 92 92 45.9 92 92 45.9 Total 92 92 45.9 92 92 45.9 Number % Number % Number % Bagamoyo 3,524 22.2 33,234 26.7 36,758 26.2 Kibaha 1,040 6.5 12,834 10.3 13,874 9.9 Kisarawe 1,361 8.6 17,229 13.9 18,589 13.3 Mkuranga 5,847 36.8 28,816 23.2 34,663 24.7 Rufiji 2,352 14.8 28,142 22.6 30,494 21.7 Mafia 1,758 11.1 4,076 3.3 5,834 4.2 Total 15,882 100.0 124,331 100.0 140,213 100.0 Type of Craft 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 Agriculture Year, Pwani Region 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Agriculture Households Using Draft Animal to cultivate Land by District During 2002/03 Agriculture Year, Pwani Region Households Using Draft Animals Household Not Using Draft Animals Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft by Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 Agriculture Year, Pwani Region District Oxen Bulls 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer by District During 2002/03 Agriculture Year, Pwani Oxen District Total Type of Draft District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 225 Area (Ha) % Area (Ha) % Area (Ha) % Bagamoyo 1,389 29.1 2,982 34.9 4,371 32.8 Kibaha 923 19.4 204 2.4 1,127 8.5 Kisarawe 421 8.8 449 5.2 869 6.5 Mkuranga 1,098 23.0 4,621 54.0 5,719 42.9 Rufiji 183 3.8 171 2.0 355 2.7 Mafia 757 15.9 127 1.5 885 6.6 Total 4,772 100.0 8,553 100.0 13,326 100.0 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application by District during 2002/03 Agriculture Year, Pwani Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census - 2003 Pwani 226 Appendix II 227 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 228 Number % Number % Bagamoyo 2,132 5.7 35,158 94.3 37,290 5,864 Kibaha 621 4.4 13,408 95.6 14,029 1,053 Kisarawe 475 2.5 18,162 97.5 18,637 992 Mkuranga 144 0.4 34,600 99.6 34,744 493 Rufiji 612 2.0 30,294 98.0 30,906 1,909 Mafia 1,585 26.7 4,340 73.3 5,924 1,869 Total 5,568 3.9 135,961 96.1 141,530 12,180 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Bagamoyo 2,132 88,405 94 0 0 0 507 5,996 6 2,132 94,401 77 Kibaha 265 7,076 77 18 18 0 429 2,051 22 621 9,144 7 Kisarawe 428 2,331 73 0 0 0 95 859 27 475 3,190 3 Mkuranga 60 60 21 0 0 0 144 229 79 144 289 0 Rufiji 460 2,608 74 152 823 23 72 72 2 612 3,503 3 Mafia 1,520 9,880 84 161 299 3 340 1,602 14 1,585 11,781 10 Total 4,864 110,360 90 331 1,140 1 1,588 10,809 9 5,568 122,308 100 Number % Number % 1-5 2,224 40 6,161 5 3 6-10 907 16 7,176 6 8 11-15 472 8 6,040 5 13 16-20 544 10 9,692 8 18 21-30 228 4 5,625 5 25 31-40 252 5 8,762 7 35 41-50 249 4 11,277 9 45 51-60 102 2 5,315 4 52 61-100 349 6 25,177 21 72 101-150 99 2 12,587 10 127 151+ 102 2 23405 19 229 Total 5568 100 122308 100 22 18.1 CATTLE PRODUCTION: Total Number Households Rearing Cattle by District during 2002/03 Agriculture Year, Pwani Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture Households Total livestock Keeping Households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size ` Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 229 Number % Number % Number % Number % Bulls 9,617 80.0 526 4.4 1,882 15.7 12,025 9.8 Cows 30,337.0 91.9 284.8 0.9 2,394.6 7.3 33,016.4 27.0 Steers 7,691.4 98.8 24.2 0.3 65.6 0.8 7,781.3 6.4 Heifers 32,788.2 90.7 114.8 0.3 3,232.0 8.9 36,135.1 29.5 Male Calves 12,436.3 89.6 94.9 0.7 1,341.3 9.7 13,872.5 11.3 Female Calves 17,490 89.8 95 0.5 1,893 9.7 19,478 15.9 Total 110,360 90.2 1,140 0.9 10,809 8.8 122,308 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 7,760 21,731 6,579 28,753 9,419 14,165 88,405 Kibaha 468 2,306 779 1,406 809 1,309 7,076 Kisarawe 285 714 95 666 334 238 2,331 Mkuranga . 60 . . . . 60 Rufiji 429 1,173 . 177 428 401 2,608 Mafia 675 4,354 239 1,787 1,446 1,379 9,880 Total 9,617 30,337 7,691 32,788 12,436 17,490 110,360 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo . . . . . . . Kibaha 18 . . . . . 18 Kisarawe . . . . . . . Mkuranga . . . . . . . Rufiji 463 216 . . 72 72 823 Mafia 45 69 24 115 23 23 299 Total 526 285 24 115 95 95 1,140 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle Improved Beef Cattle Improved Dairy Cattle Category of Cattle 18.6 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 230 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 1,427 702 . 2,240 707 920 5,996 Kibaha 271 758 18 367 238 399 2,051 Kisarawe . 382 . 191 143 143 859 Mkuranga . 60 . 85 85 . 229 Rufiji . . . 72 . . 72 Mafia 185 492 48 277 169 431 1,602 Total 1,882 2,395 66 3,232 1,341 1,893 10,809 Bulls Cows Steers Heifers Male Calves Female Calves Total Bagamoyo 9,186 22,433 6,579 30,993 10,126 15,085 94,401 Kibaha 757 3,064 796 1,773 1,046 1,708 9,144 Kisarawe 285 1,096 95 857 477 380 3,190 Mkuranga . 120 . 85 85 . 289 Rufiji 892 1,389 . 249 500 473 3,503 Mafia 904 4,915 312 2,179 1,638 1,833 11,781 Total 12,025 33,016 7,781 36,135 13,873 19,478 122,308 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 231 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 232 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Bagamoyo 3,913 67,982 99.3 0 . 0.0 98 489 0.7 4,011 68,472 69.4 Kibaha 335 4,748 90.9 69 377 7.2 67 101 1.9 403 5,226 5.3 Kisarawe 748 4,847 100.0 0 . 0.0 0 . 0.0 748 4,847 4.9 Mkuranga 702 5,545 97.0 0 . 0.0 169 169 3.0 871 5,714 5.8 Rufiji 1,437 13,406 100.0 0 . 0.0 0 . 0.0 1,437 13,406 13.6 Mafia 130 810 86.2 0 . 0.0 22 130 13.8 152 940 1.0 Total 7,265 97,337 98.7 69 377 0.4 356 890 0.9 7,621 98,604 100.0 Number % Number % 1-4 2,491 33 6,113 6 2 5-9 1,879 25 12,668 13 7 10-14 1,484 19 17,335 18 12 15-19 746 10 13,481 14 18 20-24 155 2 3,407 3 22 30-39 187 2 5,984 6 32 40+ 678 9 39,616 40 58 Total 7,621 100 98,604 100 13 Total Goats District 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Goats Herd Size Goat Rearing Households Number of Goats Average Number Per Household Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 233 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 13,706 98.1 77 0.6 187 1.3 13,970 14.2 Castrated Goat 4,690 99.4 31 0.6 . 0.0 4,721 4.8 She Goat 50,501 98.9 192 0.4 379 0.7 51,072 51.8 Male Kid 13,762 98.6 77 0.6 120 0.9 13,958 14.2 She Kid 14,678 98.6 . 0.0 204 1.4 14,883 15.1 Total 97,337 98.7 377 0.4 890 0.9 98,604 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 9,416 3,301 34,270 9,952 11,044 67,982 Kibaha 509 371 2,401 732 735 4,748 Kisarawe 611 861 2,198 657 520 4,847 Mkuranga 982 . 3,075 617 871 5,545 Rufiji 2,091 158 8,046 1,703 1,409 13,406 Mafia 97 . 512 101 100 810 Total 13,706 4,690 50,501 13,762 14,678 97,337 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo . . . . . . Kibaha 77 31 192 77 . 377 Kisarawe . . . . . . Mkuranga . . . . . . Rufiji . . . . . . Mafia . . . . . . Total 77 31 192 77 . 377 Total Category of Goats 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Improved Dairy Goats 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 234 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 98 . 196 98 98 489 Kibaha 67 . 34 . . 101 Kisarawe . . . . . . Mkuranga . . 84 . 85 169 Rufiji . . . . . . Mafia 22 . 65 22 22 130 Total 187 . 379 120 204 890 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Bagamoyo 9,514 3,301 34,465 10,050 11,142 68,472 Kibaha 653 401 2,627 809 735 5,226 Kisarawe 611 861 2,198 657 520 4,847 Mkuranga 982 . 3,159 617 955 5,714 Rufiji 2,091 158 8,046 1,703 1,409 13,406 Mafia 118 . 577 122 122 940 Total 13,970 4,721 51,072 13,958 14,883 98,604 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 235 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 236 Number % Number % Number % Ram 3,345 100 . 0 3,345 23 Castrated Sheep 1,361 100 . 0 1,361 8 She Sheep 11,322 100 . 0 11,322 51 Male Lamb 4,416 100 . 0 4,416 10 She Lamb 3,891 100 . 0 3,891 8 Total 24,334 100 . 0 24,334 100 Number % Number % Bagamoyo 1,087 3 36,202 97 37,290 5,864 Kibaha 77 1 13,952 99 14,029 1,053 Kisarawe 0 0 18,637 100 18,637 992 Mkuranga 53 0 34,691 100 34,744 493 Rufiji 286 1 30,620 99 30,906 1,909 Mafia 0 0 5,924 100 5,924 1,869 Total 1,503 1 140,027 99 141,530 12,180 Number % Number % Number % Bagamoyo 21,754 100 0 0 21,754 89 Kibaha 719 100 0 0 719 3 Mkuranga 369 100 0 0 369 2 Rufiji 1,492 100 0 0 1,492 6 Total 24,334 100 0 0 24,334 100 Herd Size Number of Households % Number of Sheep % Average Number Per Household 1-4 434 29 1,474 6 3 5-9 483 32 3,032 12 6 10-14 197 13 2,477 10 13 15-19 99 7 1,487 6 15 25-29 102 7 2,555 11 25 40+ 187 12 13,309 55 71 Total 1,503 100 24,334 100 16 20.1 Total Number of Sheep By Breed and on 1st October 2003 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households Breed Number of Indigenous sheep District 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 237 Number of Households Average sheep Number of Households Average sheep Number of Households Average sheep Bagamoyo 205 4 0 0 205 4 Kibaha Kisarawe Mkuranga Rufiji 0 0 0 0 0 0 Mafia 80 5 0 0 80 5 Total 284 5 0 3 284 5 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 266 17 448 97 58 886 Kibaha Kisarawe Mkuranga Rufiji . . . . . . Mafia 35 83 208 33 45 404 Total 300 100 656 130 103 1,290 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 0 0 0 0 0 0 Kibaha 0 0 0 0 0 0 Kisarawe 0 0 0 0 0 0 Mkuranga 0 0 0 0 0 0 Rufiji 0 0 0 0 0 0 Mafia 0 0 0 0 0 0 Total 0 0 0 0 0 0 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Bagamoyo 2,523 1,361 9,833 4,257 3,779 21,754 Kibaha 74 . 459 74 112 719 Mkuranga 158 . 211 . . 369 Rufiji 590 . 818 84 . 1,492 Total 3,345 1,361 11,322 4,416 3,891 24,334 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Pwani Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Pwani 238 Appendix II 239 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 240 Number % Number % 1-4 121 34 317 9 3 5-9 185 52 1,367 37 7 40+ 47 13 1,989 54 42 Total 353 100 3,673 100 10 District Number of Households Number of Pigs Average Number Per Households Bagamoyo 98 294 3 Kibaha 76 392 5 Kisarawe 95 2,226 24 Mkuranga 85 761 9 Total 353 3,673 10 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Bagamoyo 294 . . . . 294 Kibaha 35 18 287 . 53 392 Kisarawe 142 332 474 568 710 2,226 Mkuranga 254 . 507 . . 761 Total 724 349 1,268 568 763 3,673 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 241 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 242 Number of Households % Number of Households % Bagamoyo 2,499 44 3,161 56 5,660 Kibaha 646 61 407 39 1,053 Kisarawe 285 30 660 70 945 Mkuranga 197 40 296 60 493 Rufiji 395 22 1,369 78 1,765 Mafia 635 39 978 61 1,613 Total 4,657 40 6,871 60 11,528 Number of Households % Number of Households % Number of Households % Number of Households % Bagamoyo 1,578 60 2,216 55 698 84 146 33 Kibaha 330 12 604 15 77 9 18 4 Kisarawe 237 9 285 7 0 0 95 21 Mkuranga 137 5 144 4 53 6 85 19 Rufiji 320 12 164 4 0 0 76 17 Mafia 40 2 619 15 0 0 24 5 Total 2,642 100 4,032 100 828 100 442 100 Number of Households % Number of Households % Bagamoyo 1,112 23 3,655 77 4,767 Kibaha 216 22 765 78 982 Kisarawe 422 43 570 57 992 Mkuranga 197 40 296 60 493 Rufiji 305 17 1,524 83 1,829 Mafia 1,061 62 649 38 1,709 Total 3,313 31 7,459 69 10,772 Spraying Dipping Number % age Number % age Number % age Number % age Number % age Number % age Bagamoyo 46 4 590 53 201 18 198 18 76 7 1,112 100 Kibaha 0 0 216 100 0 0 0 0 0 0 216 100 Kisarawe 0 0 333 79 0 0 0 0 90 21 422 100 Mkuranga 0 0 197 100 0 0 0 0 0 0 197 100 Rufiji 80 26 224 74 0 0 0 0 0 0 305 100 Mafia 184 17 560 53 70 7 15 1 232 22 1,061 100 Total 311 9 2,120 64 271 8 214 6 398 12 3,313 100 Other Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year District None Smearing Method of Tick Control District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tick Problems During 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that Dewormed Livestock by Type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing Households Deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 243 Number of Households % Number of Households % Bagamoyo 1,109 23 3,756 77 4,865 Kibaha 252 26 730 74 982 Kisarawe 375 38 618 62 992 Mkuranga 137 28 356 72 493 Rufiji 224 12 1,605 88 1,829 Mafia 311 19 1,325 81 1,636 Total 2,408 22 8,389 78 10,797 Number % age Number % age Number % age Bagamoyo 477 43 444 40 187 17 1,109 Kibaha 161 64 20 8 71 28 252 Kisarawe 90 24 285 76 0 0 375 Mkuranga 137 100 0 0 0 0 137 Rufiji 0 0 224 100 0 0 224 Mafia 204 65 108 35 0 0 311 Total 1,069 44 1,081 45 258 11 2,408 Total District None Dipping Spray Method of Tsetse Flies Control 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tsetse Flies Problems During 2002/03 Agriculture Year by District Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse Flies Control Use and District During the 2002/03 Agricultural Year District Tsetse Flies Problems No Tsetse Flies Problems Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 241 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 242 Number of Households % Number of Households % Bagamoyo 2,499 44 3,161 56 5,660 Kibaha 646 61 407 39 1,053 Kisarawe 285 30 660 70 945 Mkuranga 197 40 296 60 493 Rufiji 395 22 1,369 78 1,765 Mafia 635 39 978 61 1,613 Total 4,657 40 6,871 60 11,528 Number of Households % Number of Households % Number of Households % Number of Households % Bagamoyo 1,578 60 2,216 55 698 84 146 33 Kibaha 330 12 604 15 77 9 18 4 Kisarawe 237 9 285 7 0 0 95 21 Mkuranga 137 5 144 4 53 6 85 19 Rufiji 320 12 164 4 0 0 76 17 Mafia 40 2 619 15 0 0 24 5 Total 2,642 100 4,032 100 828 100 442 100 Number of Households % Number of Households % Bagamoyo 1,112 23 3,655 77 4,767 Kibaha 216 22 765 78 982 Kisarawe 422 43 570 57 992 Mkuranga 197 40 296 60 493 Rufiji 305 17 1,524 83 1,829 Mafia 1,061 62 649 38 1,709 Total 3,313 31 7,459 69 10,772 Spraying Dipping Number % age Number % age Number % age Number % age Number % age Number % age Bagamoyo 46 4 590 53 201 18 198 18 76 7 1,112 100 Kibaha 0 0 216 100 0 0 0 0 0 0 216 100 Kisarawe 0 0 333 79 0 0 0 0 90 21 422 100 Mkuranga 0 0 197 100 0 0 0 0 0 0 197 100 Rufiji 80 26 224 74 0 0 0 0 0 0 305 100 Mafia 184 17 560 53 70 7 15 1 232 22 1,061 100 Total 311 9 2,120 64 271 8 214 6 398 12 3,313 100 Other Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year District None Smearing Method of Tick Control District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tick Problems During 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that Dewormed Livestock by Type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing Households Deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 243 Number of Households % Number of Households % Bagamoyo 1,109 23 3,756 77 4,865 Kibaha 252 26 730 74 982 Kisarawe 375 38 618 62 992 Mkuranga 137 28 356 72 493 Rufiji 224 12 1,605 88 1,829 Mafia 311 19 1,325 81 1,636 Total 2,408 22 8,389 78 10,797 Number % age Number % age Number % age Bagamoyo 477 43 444 40 187 17 1,109 Kibaha 161 64 20 8 71 28 252 Kisarawe 90 24 285 76 0 0 375 Mkuranga 137 100 0 0 0 0 137 Rufiji 0 0 224 100 0 0 224 Mafia 204 65 108 35 0 0 311 Total 1,069 44 1,081 45 258 11 2,408 Total District None Dipping Spray Method of Tsetse Flies Control 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of Agricultural Households Reporting to Have Encountered Tsetse Flies Problems During 2002/03 Agriculture Year by District Total 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse Flies Control Use and District During the 2002/03 Agricultural Year District Tsetse Flies Problems No Tsetse Flies Problems Tanzania Agriculture Sample Census - 2003 Pwani 244 Appendix II 245 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 246 Number % Type Number Type Number Indigenous 1,254,145 88 Ducks 53,420 Donkeys 193 Layer 125,649 9 Turkeys 13,100 Horse 0 Broiler 40,358 3 Rabbits 11,371 Other 1,893 Total 1,420,152 100 Total 77,891 Total 2,086 Indigenous Chicken Layer Broiler Ducks Turkeys Rabbits Donkeys Other Bagamoyo 369,118 931 0 370,049 Bagamoyo 21,949 0 9,198 0 1,828 Kibaha 91,743 2,852 7,743 102,338 Kibaha 1,624 0 53 0 0 Kisarawe 172,662 42,523 30,935 246,120 Kisarawe 2,784 0 1,409 0 0 Mkuranga 322,132 0 0 322,132 Mkuranga 0 404 0 0 0 Rufiji 243,880 67,879 0 311,759 Rufiji 9,968 0 711 0 0 Mafia 54,610 11,464 1,679 67,754 Mafia 17,094 12,696 0 193 65 Total 1,254,145 125,649 40,358 1,420,152 Total 53,420 13,100 11,371 193 1,893 Type of Livestock/Poultry 1999 2003 Number % Cattle 101,594 122308 1 - 4 12,480 15.9 33,830 3 Improved cattle 1,450.0 11,948.0 5 - 9 17,795 22.6 120,208 7 Goats 65,659.0 98,604.0 10 - 19 25,092 31.9 321,845 13 Sheep 7,845.0 24,334.0 20 - 29 12,254 15.6 273,881 22 Pigs 3,581.0 3,673.0 30 - 39 5,868 7.5 184,373 31 Indigenous Chicken 808,574.0 1,254,145.0 40 - 49 2,196 2.8 92,214 42 Layers 6,306.0 125,649.0 50 - 99 2,673 3.4 178,300 67 Broilers 1,888.0 40,358.0 100+ 329 0.4 215,501 655 Total Chicken 816,765 1420152 Total 78,687 100 1,420,152 18 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e OTHER LIVESTOCK: Livestock/Poultry Population Trend Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household District 23c OTHER LIVESTOCK: Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 Type of Livestock Chicken Type Other Livestock 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 247 FISH FARMING Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 248 Number % Number % Bagamoyo 0 0.0 37,290 100 37,290 Kibaha 0 0.0 14,029 100 14,029 Kisarawe 0 0.0 18,637 100 18,637 Mkuranga 0 0.0 34,744 100 34,744 Rufiji 0 0.0 30,906 100 30,906 Mafia 0 0.0 5,924 100 5,924 Total 0 0.0 141,530 100 141,530 Dug out Pond Total Bagamoyo 0 0 Kibaha 0 0 Kisarawe 0 0 Mkuranga 0 0 Rufiji 0 0 Mafia 0 0 Total 0 0 28.2 FISH FARMING: Number of Agricultural Households by System of Fish Farming and District during the 2002/03 Agricultural Year District Fish Farming System 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 249 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 250 Number % Number % Bagamoyo 2,656 7 34,633 93 37,290 5,864 45 Kibaha 1,397 10 12,632 90 14,029 1,053 133 Kisarawe 2,032 11 16,605 89 18,637 992 205 Mkuranga 2,868 8 31,876 92 34,744 493 582 Rufiji 973 3 29,932 97 30,906 1,909 51 Mafia 242 4 5,683 96 5,924 1,869 13 Total 10,168 7 131,362 93 141,530 12,180 83 Number % Number % Number % Number % Number % Number % Bagamoyo 2,284 35 1,209 18 1,163 18 1,163 18 759 12 6,578 100 Kibaha 1,343 47 745 26 519 18 137 5 137 5 2,882 100 Kisarawe 2,032 49 828 20 650 16 608 15 42 1 4,160 100 Mkuranga 2,699 67 145 4 1,200 30 0 0 0 0 4,043 100 Rufiji 741 56 218 16 218 16 74 6 74 6 1,325 100 Mafia 198 30 134 20 115 17 130 19 93 14 669 100 Total 9,296 47 3,279 17 3,864 20 2,113 11 1,105 6 19,657 100 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year Total Total Total Number of Households Raising Livestock Source of extension advice Large Scale Farmer Other % receiving advice out of total District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households by Source of Extension Services and District during the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 251 Government NGO / Development Project Large Scale Farmer Total Government NGO / Development Project Large Scale Farmer Total Bagamoyo 1,477 0 0 1,477 5,864 25.2 Bagamoyo 2,002 0 0 2,002 5,864 34.1 Kibaha 1,001 54 27 1,082 1,053 102.7 Kibaha 1,010 89 27 1,125 1,053 106.8 Kisarawe 952 0 0 952 992 95.9 Kisarawe 1,108 47 0 1,155 992 116.4 Mkuranga 2,088 0 0 2,088 493 423.5 Mkuranga 2,141 0 0 2,141 493 434.2 Rufiji 302 0 0 302 1,909 15.8 Rufiji 669 0 0 669 1,909 35.0 Mafia 91 0 0 91 1,869 4.8 Mafia 81 23 0 104 1,869 5.6 Total 5,911 54 27 5,992 12,180 49.2 Total 7,011 159 27 7,196 12,180 59.1 % 98.7 0.9 0.4 100.0 % 97.4 2.2 0.4 100.0 Government NGO / Development Project Co-operative Total Government NGO / Development Project Co-operative Total Bagamoyo 404 46 102 553 5,864 9.4 Bagamoyo 504 46 102 652 5,864 11.1 Kibaha 264 20 0 284 1,053 27.0 Kibaha 264 20 0 284 1,053 27.0 Kisarawe 235 47 0 283 992 28.5 Kisarawe 236 47 0 284 992 28.6 Mkuranga 305 0 0 305 493 61.8 Mkuranga 225 0 0 225 493 45.6 Rufiji 222 0 0 222 1,909 11.6 Rufiji 226 0 0 226 1,909 11.8 Mafia 22 23 0 45 1,869 2.4 Mafia 0 23 0 23 1,869 1.2 Total 1,452 137 102 1,691 12,180 13.9 Total 1,454 137 102 1,693 12,180 13.9 % 85.9 8.1 6.0 100.0 % 85.9 8.1 6.0 100.0 % receiving advice out of total District District Source of Advice on Milk Hygiene Total Number of households raising livestock % receiving advice out of total Total Number of households raising livestock Source of Advice on Proper Milking 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene by Source and District, 2002/03 Agricultural Year District 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking by Source and District, 2002/03 Agricultural Year Total Number of households raising livestock Source of Advice on Feeds and Proper Feeding Total Number of households raising livestock Source of Advice on Housing % receiving advice out of total 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding by Source and District, 2002/03 Agricultural Year District % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 252 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Bagamoyo 1,514 0 102 0 0 1,616 5,864 27.6 Kibaha 435 89 0 27 0 551 1,053 52.3 Kisarawe 689 47 0 0 47 784 992 79.0 Mkuranga 2,140 0 0 0 0 2,140 493 434.1 Rufiji 593 0 0 0 0 593 1,909 31.1 Mafia 103 0 0 39 0 142 1,869 7.6 Total 5,475 136 102 66 47 5,827 12,180 47.8 % 94.0 2.3 1.8 0.8 100.0 Government NGO / Development Project Co-operative Total Bagamoyo 604 0 102 706 5,864 12 Kibaha 495 0 0 495 1,053 47 Kisarawe 92 0 0 92 992 9 Mkuranga 80 0 0 80 493 16 Rufiji 74 0 0 74 1,909 4 Mafia 0 23 0 23 1,869 1 Total 1,345 23 102 1,470 12,180 12 % 91.5 1.6 7.0 100 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District District Source of Advice on Herd/Flock Size % receiving advice out of total Total Number of households raising livestock Total Number of households raising livestock % receiving advice out of total Source of Advice on Disease Control Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 253 Government NGO / Development Project Total Bagamoyo 595 0 595 5,864 10 Kibaha 146 35 181 1,053 17 Kisarawe 189 47 236 992 24 Mkuranga 145 0 145 493 29 Rufiji 154 0 154 1,909 8 Total 1,229 82 1,311 12,180 11 % 93.7 6.3 100 Government NGO / Development Project Co-operative Total Bagamoyo 505 0 102 607 5,864 10.4 Kibaha 488 35 0 522 1,053 49.6 Kisarawe 413 173 0 586 992 59.1 Mkuranga 1,641 0 0 1,641 493 332.9 Rufiji 362 0 0 362 1,909 19.0 Mafia 0 23 0 23 1,869 1.2 Total 3,409 231 102 3,742 12,180 30.7 % 91.1 6.2 2.7 100.0 Total Number of households raising livestock Source of Advice on Pasture Establishment and Selection 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year Source of Advice on Group Formation and Strengthening Total Number of households raising livestock % receiving advice out of total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District % receiving advice out of total District Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 254 Government NGO / Development Project Co-operative Large Scale Farmer Total Bagamoyo 739 0 102 0 841 5,864 14.3 Kibaha 282 35 0 0 317 1,053 30.1 Kisarawe 237 47 0 0 284 992 28.6 Mkuranga 145 0 0 0 145 493 29.3 Rufiji 146 0 0 0 146 1,909 7.7 Mafia 27 0 0 15 43 1,869 2.3 Total 1,576 82 102 15 1,776 12,180 14.6 % 88.7 4.6 5.8 0.9 100.0 Government NGO / Development Project Large Scale Farmer Total Bagamoyo 1,022 0 0 1,022 5,864 17.4 Kibaha 295 35 0 330 1,053 31.3 Kisarawe 142 143 0 285 992 28.7 Mkuranga 60 85 0 145 493 29.3 Rufiji 218 0 0 218 1,909 11.4 Mafia 34 0 31 65 1,869 3.5 Total 1,771 263 31 2,065 12,180 16.9 % 85.8 12.7 1.5 100.0 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Total Number of households raising livestock 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock Source of Advice on Use of Improved Bulls District District Source of Advice on Calf Rearing Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 255 Number % Number % Number % Number % Number % Bagamoyo 1,686 55 753 25 100 3 0 0 517 17 3,055 Kibaha 85 3 1,922 76 448 18 82 3 0 0 2,536 Kisarawe 263 10 1,759 69 414 16 0 0 126 5 2,561 Mkuranga 120 3 3,552 91 132 3 0 0 85 2 3,888 Rufiji 662 41 879 54 0 0 0 0 72 4 1,613 Mafia 120 23 181 34 227 43 0 0 0 0 528 Total 2,935 21 9,044 64 1,320 9 82 1 799 6 14,180 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census - 2003 Pwani 256 Appendix II 257 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 258 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Bagamoyo 21.2 2.3 2.9 1.8 68.6 5.3 101.6 13.0 33.5 68.1 10.8 Kibaha 27.1 1.8 1.7 0.6 39.6 9.2 48.4 10.3 18.9 42.5 10.4 Kisarawe 17.4 1.9 4.5 0.6 43.7 6.9 97.3 17.4 26.2 61.2 51.6 Mkuranga 26.0 3.0 4.3 1.0 37.9 7.5 118.7 13.0 21.9 45.2 17.9 Rufiji 25.1 2.3 5.9 1.6 46.1 8.2 213.0 18.3 35.6 78.1 37.0 Mafia 30.1 2.6 8.4 2.2 26.6 2.7 238.6 82.9 90.3 143.6 200.5 Total 23.7 2.4 4.2 1.3 48.2 7.0 130.0 17.4 31.1 64.4 31.5 Regional Capital 130.0 Tertiary Market 64.4 Hospitals 48.2 Tarmac roads 31.5 Secondary Market 31.1 Secondary Schools 23.7 Primary Markets 17.4 Health Clinics 7.0 All weather roads 4.2 Primary Schools 2.4 Feeder roads 1.3 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 259 No of households % No of households % No of households % No of households % No of households % Bagamoyo 1159 3.1 1,745 4.7 8358 22.4 9793 26.3 16234 43.5 37290 21.2 Kibaha 321 2.3 1,344 9.6 5153 36.7 3649 26.0 3562 25.4 14029 27.1 Kisarawe 130 0.7 2,006 10.8 6593 35.4 3649 19.6 6259 33.6 18637 17.4 Mkuranga 339 1.0 1,038 3.0 7385 21.3 7611 21.9 18372 52.9 34744 26.0 Rufiji 265 0.9 1,538 5.0 3610 11.7 7236 23.4 18258 59.1 30906 25.1 Mafia 0 0.0 25 0.4 594 10.0 2075 35.0 3230 54.5 5924 30.1 Total 2214 1.6 7,695 5.4 31693 22.4 34013 24.0 65915 46.6 141530 23.7 No of households % No of households % No of households % No of households % No of households % Bagamoyo 21330 57.2 8,095 21.7 5677 15.2 541 1.4 1647 4.4 37290 2.9 Kibaha 8812 62.8 3,375 24.1 1665 11.9 57 0.4 119 0.9 14029 1.7 Kisarawe 7245 38.9 3,286 17.6 4989 26.8 2980 16.0 138 0.7 18637 4.5 Mkuranga 16469 47.4 7,652 22.0 6818 19.6 2565 7.4 1240 3.6 34744 4.3 Rufiji 16042 51.9 4,654 15.1 4865 15.7 2827 9.1 2519 8.1 30906 5.9 Mafia 1697 28.6 1,582 26.7 2074 35.0 200 3.4 372 6.3 5924 8.4 Total 71594 50.6 28,644 20.2 26088 18.4 9170 6.5 6035 4.3 141530 4.2 No of households % No of households % No of households % No of households % No of households % Bagamoyo 26,232 70.3 8,219 22.0 2182 5.9 170 0.5 488 1.3 37,290 1.8 Kibaha 10,768 76.8 2,705 19.3 445 3.2 111 0.8 0 0.0 14,029 0.6 Kisarawe 13,358 71.7 4,399 23.6 832 4.5 48 0.3 0 0.0 18,637 0.6 Mkuranga 21,419 61.6 10,224 29.4 3102 8.9 0 0.0 0 0.0 34,744 1.0 Rufiji 18,185 58.8 9,210 29.8 1871 6.1 828 2.7 811 2.6 30,906 1.6 Mafia 4,046 68.3 1,293 21.8 252 4.3 0 0.0 333 5.6 5,924 2.2 Total 94,006 66.4 36,050 25.5 8684 6.1 1157 0.8 1,632 1.2 141,530 1.3 Mean Distance Above 20 km 33.01b: Number of Households by Distance to Secondary School by District for 2002/03 Agriculture Year District Distance to Secondary School Total Number of Households Mean Distance Less than 1 km 1-2.9 km 10.0-19.9 3.0-9.9 Mean Distance Above 20 km 1-2.9 km Above 20 km 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 Agriculture Year District Distance to All Weather Road Total Number of Households Less than 1 km 1-2.9 km 3.0-9.9 3.0-9.9 10.0-19.9 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 Agriculture Year District Distance to Feeder Road Total Number of Households 10.0-19.9 Less than 1 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 260 No of households % No of households % No of households % No of households % No of households % Bagamoyo 102 0.3 102 0.3 1,354 3.6 5,016 13.5 30,716 82.4 37,290 68.6 Kibaha 100 0.7 577 4.1 1,737 12.4 3,532 25.2 8,083 57.6 14,029 39.6 Kisarawe 48 0.3 0 0.0 759 4.1 2,107 11.3 15,723 84.4 18,637 43.7 Mkuranga 82 0.2 623 1.8 2,543 7.3 5,405 15.6 26,090 75.1 34,744 37.9 Rufiji 336 1.1 642 2.1 2,379 7.7 2,829 9.2 24,719 80.0 30,906 46.1 Mafia 9 0.2 131 2.2 228 3.8 2,070 34.9 3,486 58.9 5,924 26.6 Total 677 0.5 2,075 1.5 9,000 6.4 20,960 14.8 108,817 76.9 141,530 48.2 No of households % No of households % No of households % No of households % No of households % Bagamoyo 5,636 15.1 12,438 33.4 12,734 34.1 5,748 15.4 734 2.0 37,290 5.3 Kibaha 1,813 12.9 3,654 26.0 5,550 39.6 1,792 12.8 1,220 8.7 14,029 9.2 Kisarawe 1,528 8.2 2,512 13.5 11,404 61.2 2,682 14.4 511 2.7 18,637 6.9 Mkuranga 1,878 5.4 3,673 10.6 18,802 54.1 9,156 26.4 1,235 3.6 34,744 7.5 Rufiji 7,281 23.6 6,916 22.4 8,309 26.9 3,022 9.8 5,377 17.4 30,906 8.2 Mafia 1,263 21.3 2,117 35.7 2,422 40.9 99 1.7 23 0.4 5,924 2.7 Total 19,399 13.7 31,310 22.1 59,221 41.8 22,500 15.9 9,100 6.4 141,530 7.0 No of households % No of households % No of households % No of households % No of households % Bagamoyo 10,008 26.8 16,101 43.2 10,000 26.8 1,092 2.9 89 0.2 37,290 2.3 Kibaha 2,777 19.8 7,834 55.8 3,376 24.1 42 0.3 0 0.0 14,029 1.8 Kisarawe 5,081 27.3 8,132 43.6 5,141 27.6 284 1.5 0 0.0 18,637 1.9 Mkuranga 7,256 20.9 13,482 38.8 12,076 34.8 1,851 5.3 79 0.2 34,744 3.0 Rufiji 12,927 41.8 8,678 28.1 7,213 23.3 1,928 6.2 159 0.5 30,906 2.3 Mafia 1,459 24.6 2,888 48.7 1,538 26.0 0 0.0 40 0.7 5,924 2.6 Total 39,508 27.9 57,115 40.4 39,342 27.8 5,197 3.7 367 0.3 141,530 2.4 Above 20 km Above 20 km 33.01e: Number of Households by Distance to Hospital by District for 2002/03 Agriculture Year District Distance to hospital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01g: Number of Households by distance to Primary School for 2002/03 Agriculture Year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 Agricultural Year District Health clinic Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total Number of Households Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 261 No of households % No of households % No of households % No of households % No of households % Bagamoyo 0 0.0 0 0.0 0 0.0 294 0.8 36,996 99.2 37,290 101.6 Kibaha 0 0.0 412 2.9 540 3.8 3,116 22.2 9,961 71.0 14,029 48.4 Kisarawe 0 0.0 0 0.0 0 0.0 759 4.1 17,878 95.9 18,637 97.3 Mkuranga 165 0.5 0 0.0 0 0.0 0 0.0 34,579 99.5 34,744 118.7 Rufiji 137 0.4 0 0.0 0 0.0 80 0.3 30,688 99.3 30,906 213.0 Mafia 0 0.0 0 0.0 0 0.0 0 0.0 5,924 100.0 5,924 238.6 Total 303 0.2 412 0.3 540 0.4 4,249 3.0 136,026 96.1 141,530 130.0 No of households % No of households % No of households % No of households % No of households % Bagamoyo 102 0.3 193 0.5 1,175 3.1 4,965 13.3 30,854 82.7 37,290 79.4 Kibaha 39 0.3 452 3.2 577 4.1 3,143 22.4 9,819 70.0 14,029 45.0 Kisarawe 0 0.0 0 0.0 711 3.8 777 4.2 17,150 92.0 18,637 51.1 Mkuranga 0 0.0 539 1.6 2,295 6.6 5,309 15.3 26,601 76.6 34,744 39.9 Rufiji 281 0.9 333 1.1 573 1.9 2,530 8.2 27,189 88.0 30,906 63.6 Mafia 18 0.3 57 1.0 235 4.0 2,070 34.9 3,543 59.8 5,924 27.9 Total 440 0.3 1,574 1.1 5,565 3.9 18,795 13.3 115,156 81.4 141,530 56.9 No of households % No of households % No of households % No of households % No of households % Bagamoyo 9,085 24.4 4,638 12.4 8,332 22.3 9,746 26.1 5,490 14.7 37,290 10.8 Kibaha 1,325 9.4 1,565 11.2 4,956 35.3 3,494 24.9 2,689 19.2 14,029 10.4 Kisarawe 95 0.5 0 0.0 1,711 9.2 1,733 9.3 15,098 81.0 18,637 51.6 Mkuranga 2,712 7.8 3,266 9.4 13,180 37.9 3,704 10.7 11,882 34.2 34,744 17.9 Rufiji 1,412 4.6 1,880 6.1 3,975 12.9 4,726 15.3 18,914 61.2 30,906 37.0 Mafia 0 0.0 22 0.4 0 0.0 0 0.0 5,902 99.6 5,924 200.5 Total 14,628 10.3 11,371 8.0 32,153 22.7 23,403 16.5 59,974 42.4 141,530 31.5 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 Agriculture Year District Distance to Regional Capital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 Agriculture Year District Distance to District Capital Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 Agricultural Year District Tarmac Road Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 262 No of households % No of households % No of households % No of households % No of households % Bagamoyo 3,979 10.7 5,981 16.0 11,678 31.3 7,989 21.4 7,663 20.5 37,290 13.0 Kibaha 624 4.4 2,180 15.5 5,427 38.7 3,777 26.9 2,021 14.4 14,029 10.3 Kisarawe 1,034 5.5 2,611 14.0 5,535 29.7 3,990 21.4 5,467 29.3 18,637 17.4 Mkuranga 3,460 10.0 6,215 17.9 11,434 32.9 5,905 17.0 7,730 22.2 34,744 13.0 Rufiji 9,674 31.3 3,631 11.7 4,234 13.7 1,620 5.2 11,747 38.0 30,906 18.3 Mafia 1,803 30.4 490 8.3 680 11.5 409 6.9 2,543 42.9 5,924 82.9 Total 20,572 14.5 21,108 14.9 38,989 27.5 23,689 16.7 37,171 26.3 141,530 17.4 No of households % No of households % No of households % No of households % No of households % Bagamoyo 833 2.2 1,339 3.6 5,369 14.4 5,079 13.6 24,669 66.2 37,290 68.1 Kibaha 352 2.5 1,348 9.6 3,243 23.1 3,795 27.1 5,291 37.7 14,029 42.5 Kisarawe 42 0.2 0 0.0 1,041 5.6 1,828 9.8 15,726 84.4 18,637 61.2 Mkuranga 1,338 3.9 1,370 3.9 5,417 15.6 4,361 12.6 22,258 64.1 34,744 45.2 Rufiji 4,337 14.0 1,567 5.1 2,127 6.9 3,432 11.1 19,442 62.9 30,906 78.1 Mafia 340 5.7 135 2.3 55 0.9 845 14.3 4,549 76.8 5,924 143.6 Total 7,242 5.1 5,757 4.1 17,253 12.2 19,341 13.7 91,936 65.0 141,530 64.4 No of households % No of households % No of households % No of households % No of households % Bagamoyo 2,536 6.8 1,753 4.7 8,567 23.0 6,545 17.6 17,888 48.0 37,290 33.5 Kibaha 875 6.2 1,352 9.6 3,872 27.6 4,213 30.0 3,717 26.5 14,029 18.9 Kisarawe 323 1.7 787 4.2 3,969 21.3 5,267 28.3 8,292 44.5 18,637 26.2 Mkuranga 1,246 3.6 1,520 4.4 11,661 33.6 4,268 12.3 16,049 46.2 34,744 21.9 Rufiji 6,251 20.2 1,616 5.2 3,459 11.2 3,021 9.8 16,558 53.6 30,906 35.6 Mafia 984 16.6 358 6.0 311 5.3 1,145 19.3 3,126 52.8 5,924 90.3 Total 12,216 8.6 7,386 5.2 31,839 22.5 24,459 17.3 65,630 46.4 141,530 31.1 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 Agricultural Year District Primary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 Agricultural Year District Tertiary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 Agricultural Year District Secondary Market Total Number of Households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 263 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 3,044 12.1 6,017 23.9 4,584 18.2 748 3.0 10,734 42.7 25,127 Kibaha 419 3.8 2,803 25.8 2,574 23.7 4,179 38.4 904 8.3 10,879 Kisarawe 371 15.9 1,114 47.9 428 18.4 271 11.7 142 6.1 2,327 Mkuranga 180 2.8 4,447 70.2 290 4.6 1,418 22.4 0 0.0 6,335 Rufiji 811 14.0 2,561 44.3 1,265 21.9 1,064 18.4 79 0.0 5,780 Mafia 154 2.7 1,006 17.5 1,848 32.2 2,290 39.8 449 7.8 5,746 Total 4,978 8.9 17,948 31.9 10,989 19.6 9,970 17.7 12,308 21.9 56,194 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 1,786 17.3 4,649 45.0 2,258 21.8 319 3.1 1,327 12.8 10,339 Kibaha 0 0.0 2,144 47.5 1,404 31.1 806 17.8 162 3.6 4,516 Kisarawe 235 16.9 785 56.3 285 20.4 90 6.5 0 0.0 1,396 Mkuranga 60 1.3 4,314 92.3 85 1.8 217 4.6 0 0.0 4,675 Rufiji 229 8.7 1,440 54.3 566 21.3 416 15.7 0 0.0 2,651 Mafia 68 3.8 639 35.2 495 27.2 569 31.3 46 2.5 1,816 Total 2,379 9.4 13,970 55.0 5,092 20.1 2,417 9.5 1,535 6.0 25,393 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 100 3.6 292 10.4 13 496 0 0.0 1,910 68.3 2,798 Kibaha 118 11.1 20 1.9 82 760 71.6 82 7.7 1,062 Kisarawe 45 19.1 47 20.1 0 0 0.0 142 60.8 234 Mkuranga 0 0.0 73 30.8 0 164 69.2 0 0.0 238 Rufiji 85 8.6 486 49.1 763 336 83 8.4 0 0.0 990 Mafia 0 0.0 22 5.9 122 48 229 62.3 69 18.7 368 Total 348 6.1 940 16.5 898 962 1,237 21.7 2,203 38.7 5,691 Satisfaction of Using Veterinary Clinic 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Total Number of Households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total Number of Households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total Number of Households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 264 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 455 15.9 0 0.0 577 20 76 2.7 1,747 61.2 2,855 Kibaha 107 8.8 56 4.6 298 24 674 55.3 82 6.7 1,218 Kisarawe 45 33.3 47 34.9 0 0 43 31.8 0 0.0 134 Mkuranga 0 0.0 0 0.0 0 0 349 100.0 0 0.0 349 Rufiji 0 0.0 374 56.0 83 12 132 19.8 79 11.8 668 Mafia 0 0.0 0 0.0 45 16 163 58.8 69 24.8 277 Total 607 3.5 477 7.1 1,003 30 1,437 49.0 1,976 10.0 5,500 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 301 10.4 198 6.8 396 14 95 3.3 1,910 65.8 2,901 Kibaha 81 4.1 178 9.1 468 24 790 40.5 435 22.3 1,951 Kisarawe 0 0.0 94 25.1 143 38 138 36.8 0 0.0 375 Mkuranga 0 0.0 60 13.4 126 28 262 58.5 0 0.0 448 Rufiji 295 40.9 128 17.8 219 30 79 10.9 0 0.0 721 Mafia 54 3.5 39 2.5 678 44 620 40.2 150 9.7 1,541 Total 731 9.2 697 8.8 2,031 26 1,984 25.0 2,496 31.4 7,938 No of Households % No of Households % No of Households % No of Households % No of Households % Bagamoyo 200 6.3 499 15.8 460 15 162 5.1 1,828 58.1 3,149 Kibaha 112 12.2 84 9.1 101 11 577 63.1 41 4.5 915 Kisarawe 46 33.0 94 67.0 0 0 0 0.0 0 0.0 140 Mkuranga 60 19.7 0 0.0 79 26 164 54.2 0 0.0 303 Rufiji 202 58.4 0 0.0 62 18 83 23.8 0 0.0 347 Mafia 31 2.4 280 21.1 553 42 415 31.3 46 3.5 1,325 Total 651 10.5 956 15.5 1,255 20 1,400 22.7 1,915 31.0 6,178 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total Number of Households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total Number of Households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total Number of Households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 265 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 266 No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Bagamoyo 2,272 1,658 33,099 260 0 37,290 Kibaha 549 661 11,790 1,029 0 14,029 Kisarawe 610 230 17,152 646 0 18,637 Mkuranga 1,293 162 32,985 305 0 34,744 Rufiji 2,826 1,454 26,457 168 0 30,906 Mafia 1,383 70 4,394 55 23 5,924 Total 8,932 4,236 125,877 2,463 23 141,530 % 6.3 3.0 88.9 1.7 0.0 100.0 District Average Number of Rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Number of Households Bagamoyo 3 12,815 99 0 440 19,768 3,878 289 37,290 Kibaha 2 6,465 99 0 0 7,237 227 0 14,029 Kisarawe 3 4,874 44 0 0 12,050 1,670 0 18,637 Mkuranga 3 7,570 79 0 0 27,014 81 0 34,744 Rufiji 3 5,494 58 53 62 21,830 3,409 0 30,906 Mafia 3 531 0 0 22 5,371 0 0 5,924 Total 3 37,749 380 53 524 93,270 9,265 289 141,530 % 26.7 0.3 0.0 0.4 65.9 6.5 0.2 100 Number of Households % Number of Households % Number of Households % Number of Households % Radio 25,965 26 10,086 10 11,902 12 25,934 26 Bicycle 18,686 29 6,194 10 7,445 12 16,109 25 Iron 5,276 26 3,478 17 2,253 11 5,605 27 Wheelbarrow 1,033 24 436 10 286 7 1,214 28 Mobile phone 1,103 43 741 29 0 0 564 22 Television / Video 185 11 358 20 143 8 327 19 Vehicle 369 27 383 28 234 17 213 16 Landline phone 98 24 162 39 0 0 79 19 Total Number of Households 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Radio 20,164 20 4,743 5 98,795 69.8 Bicycle 12,928 20 2,282 4 63,644 45.0 Iron 3,135 15 809 4 20,556 14.5 Wheelbarrow 1,273 29 129 3 4,371 3.1 Mobile phone 134 5 0 0 2,542 1.8 Television / Video 673 38 68 4 1,754 1.2 Vehicle 155 11 0 0 1,354 1.0 Landline phone 76 18 0 0 415 0.3 Total Number of Households 30,906 22 5,924 4 141,530 100.0 Rufiji Mafia District 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Cont. 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Kisarawe Type of Owned Asset 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year 34.2 Number of Agriculture Households by type of Roofing Material and District, 2002/03 Agricultural Year District TOTAL Type of toilet Type of Owned Asset Bagamoyo District Mkuranga Kibaha Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 267 Number of Households % Number of Households % Number of Households % Number of Households % Wick Lamp 27,954 25 10,485 9 15,938 14 26,650 24 Hurricane Lamp 7,230 34 2,364 11 1,393 7 5,894 28 Pressure Lamp 958 23 494 12 417 10 1,309 31 Mains Electricity 946 38 591 24 95 4 165 7 Firewood 202 11 37 2 700 38 399 22 Candles 0 0 27 7 94 24 79 20 Solar 0 0 0 0 0 0 247 94 Other 0 0 31 100 0 0 0 0 Total 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Wick Lamp 26,201 24 3,830 3 111,057 78.5 Hurricane Lamp 2,603 12 1,719 8 21,204 15.0 Pressure Lamp 879 21 186 4 4,243 3.0 Mains Electricity 616 25 68 3 2,481 1.8 Firewood 449 24 70 4 1,856 1.3 Candles 158 40 36 9 395 0.3 Solar 0 0 16 6 263 0.2 Other 0 0 0 0 31 0.0 Total 30,906 22 5,924 4 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Firewood 34,782 26 12,507 9 18,193 14 33,234 25 Charcoal 2,054 32 1,522 24 353 6 1,149 18 Bottled Gas 96 32 0 0 47 16 162 53 Livestock Dung 204 100 0 0 0 0 0 0 Parraffin / Kerocine 76 39 0 0 44 22 60 30 Crop Residues 76 49 0 0 0 0 79 51 Gas (Biogas) 0 0 0 0 0 0 60 74 Solar 0 0 0 0 0 0 0 0 Total 37,290 26 14,029 10 18,637 13 34,744 25 Number of Households % Number of Households % Number of Households % Firewood 29,723 22 5,693 4 134,132 94.8 Charcoal 1,102 17 193 3 6,374 4.5 Bottled Gas 0 0 0 0 305 0.2 Livestock Dung 0 0 0 0 204 0.1 Parraffin / Kerocine 0 0 17 9 197 0.1 Crop Residues 0 0 0 0 156 0.1 Gas (Biogas) 0 0 21 26 81 0.1 Solar 80 100 0 0 80 0.1 Total 30,906 22 5,924 4 141,530 100.0 Cont. 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Cooking Rufiji Mafia District TOTAL Mkuranga District 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Lighting Rufiji Mafia Main Source of Energy for Cooking Bagamoyo Kibaha Kisarawe Mkuranga 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year District District TOTAL Cont. 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year Main Source of Energy for Lighting Bagamoyo Kibaha Kisarawe Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 268 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Total wet season 9,488 4,021 752 302 1,559 272 16,394 dry season 10,579 4,866 1,663 457 1,539 248 19,353 wet season 2,275 790 2,198 3,517 1,860 1,232 11,872 Dry season 2,556 1,479 3,466 3,173 1,185 1,611 13,470 wet season 298 267 284 128 305 71 1,353 Dry season 196 94 415 76 160 110 1,051 wet season 10,600 3,944 13,209 27,762 19,300 2,868 77,684 Dry season 7,194 2,887 11,883 28,921 20,345 3,215 74,445 wet season 1,531 584 598 1,166 328 119 4,327 Dry season 1,158 550 648 1,405 256 119 4,137 wet season 7,958 3,433 378 759 4,685 363 17,575 Dry season 13,871 3,524 515 507 4,893 23 23,334 wet season 0 0 0 351 0 26 377 Dry season 82 0 47 79 80 16 304 wet season 4,001 990 1,128 759 2,869 930 10,677 Dry season 102 205 0 82 2,445 514 3,348 wet season 89 0 90 0 0 0 179 Dry season 832 71 0 45 0 21 969 wet season 0 0 0 0 0 0 0 Dry season 195 0 0 0 0 5 200 wet season 1,050 0 0 0 0 42 1,092 Dry season 525 352 0 0 0 42 919 37,290 14,029 18,637 34,744 30,906 5,924 141,530 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Total wet season 25.4 28.7 4.0 0.9 5.0 4.6 11.6 dry season 28.4 34.7 8.9 1.3 5.0 4.2 13.7 wet season 6.1 5.6 11.8 10.1 6.0 20.8 8.4 Dry season 6.9 10.5 18.6 9.1 3.8 27.2 9.5 wet season 0.8 1.9 1.5 0.4 1.0 1.2 1.0 Dry season 0.5 0.7 2.2 0.2 0.5 1.9 0.7 wet season 28.4 28.1 70.9 79.9 62.4 48.4 54.9 Dry season 19.3 20.6 63.8 83.2 65.8 54.3 52.6 wet season 4.1 4.2 3.2 3.4 1.1 2.0 3.1 Dry season 3.1 3.9 3.5 4.0 0.8 2.0 2.9 wet season 21.3 24.5 2.0 2.2 15.2 6.1 12.4 Dry season 37.2 25.1 2.8 1.5 15.8 0.4 16.5 wet season 0.0 0.0 0.0 1.0 0.0 0.4 0.3 Dry season 0.2 0.0 0.3 0.2 0.3 0.3 0.2 wet season 10.7 7.1 6.1 2.2 9.3 15.7 7.5 Dry season 0.3 1.5 0.0 0.2 7.9 8.7 2.4 wet season 0.2 0.0 0.5 0.0 0.0 0.0 0.1 Dry season 2.2 0.5 0.0 0.1 0.0 0.4 0.7 wet season 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Dry season 0.5 0.0 0.0 0.0 0.0 0.1 0.1 wet season 2.8 0.0 0.0 0.0 0.0 0.7 0.8 Dry season 1.4 2.5 0.0 0.0 0.0 0.7 0.6 g District Source Season District Source Season Surface Water (Lake / Dam / River / Stream) District Other Piped Water Protected Well Protected / Covered Spring Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Other 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Tanker Truck Tanker Truck Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 269 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia wet season 3,495 712 427 489 3,112 523 Dry season 2,673 631 236 81 2,343 360 wet season 8,680 4,944 4,302 12,000 7,296 2,440 Dry season 5,229 2,484 3,063 6,677 4,750 1,758 wet season 3,964 1,648 898 4,120 3,711 667 Dry season 2,489 1,003 642 3,101 3,213 799 wet season 9,236 2,845 4,792 9,095 7,177 1,051 Dry season 5,690 1,791 2,322 8,603 5,680 1,279 wet season 1,920 930 1,447 1,022 758 149 Dry season 1,342 474 682 1,471 1,084 212 wet season 5,330 1,003 1,357 3,092 1,402 452 Dry season 3,616 828 491 1,944 1,087 325 wet season 4,664 1,948 5,415 4,926 7,449 643 Dry season 16,251 6,817 11,201 12,867 12,749 1,191 37,290 14,029 18,637 34,744 30,906 5,924 Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia wet season 9 5 2 1 10 9 Dry season 7 4 1 0 8 6 wet season 23 35 23 35 24 41 Dry season 14 18 16 19 15 30 wet season 11 12 5 12 12 11 Dry season 7 7 3 9 10 13 wet season 25 20 26 26 23 18 Dry season 15 13 12 25 18 22 wet season 5 7 8 3 2 3 Dry season 4 3 4 4 4 4 wet season 14 7 7 9 5 8 Dry season 10 6 3 6 4 5 wet season 13 14 29 14 24 11 Dry season 44 49 60 37 41 20 Total Agricultural Households per District above one Hour 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes District 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 Agriculture Year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season above one Hour 40 - 49 Minutes 50 - 59 Minutes District 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 Agriculture Year 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 270 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 496 6.5 1,004 13.1 1,627 21.3 2,185 28.5 2,017 26.4 324 4.2 7,653 5.4 Two 9,801 24.7 5,554 14.0 7,009 17.6 6,586 16.6 9,224 23.2 1,538 3.9 39,711 28.1 Three 26,993 29.5 6,844 7.5 10,002 10.9 24,130 26.3 19,589 21.4 4,063 4.4 91,620 64.7 Four 0 0.0 626 24.6 0 0.0 1,844 72.5 75 3.0 0 0.0 2,545 1.8 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 19,728 26.6 6,281 8.5 10,051 13.5 17,441 23.5 17,436 23.5 3,304 4.5 74,240 52.5 One 8,385 24.4 4,171 12.2 3,727 10.9 8,863 25.8 7,702 22.4 1,480 4.3 34,327 24.3 Two 5,392 27.4 2,254 11.4 2,578 13.1 5,168 26.2 3,703 18.8 595 3.0 19,689 13.9 Three 1,811 27.1 730 10.9 1,311 19.6 1,446 21.6 1,314 19.6 82 1.2 6,694 4.7 Four 1,232 42.4 240 8.3 418 14.4 632 21.8 320 11.0 64 2.2 2,906 2.1 Five 481 23.1 186 9.0 370 17.8 714 34.4 137 6.6 189 9.1 2,077 1.5 Six 100 9.8 64 6.4 47 4.7 481 47.4 138 13.6 184 18.1 1,014 0.7 Seven 162 27.8 103 17.7 135 23.2 0 0.0 155 26.6 28 4.7 582 0.4 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District Mkuranga Rufiji Mafia Bagamoyo Kibaha Kisarawe District Total Number of Meals per Day Total District 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Kibaha Kisarawe Mkuranga Bagamoyo Rufiji Mafia Number of Days Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 271 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 13,351 49.7 3,606 13.4 5,906 22.0 1,137 4.2 2,819 10.5 23 0.1 26,843 19.0 One 8,143 35.5 2,661 11.6 4,306 18.8 2,756 12.0 4,706 20.5 378 1.6 22,950 16.2 Two 7,460 28.5 2,993 11.4 4,109 15.7 5,108 19.5 6,232 23.8 314 1.2 26,216 18.5 Three 3,714 21.5 2,419 14.0 2,441 14.1 4,545 26.3 3,768 21.8 405 2.3 17,293 12.2 Four 1,465 9.9 1,281 8.6 936 6.3 5,943 40.0 4,848 32.7 374 2.5 14,847 10.5 Five 1,100 11.1 441 4.5 562 5.7 3,930 39.6 3,119 31.5 762 7.7 9,915 7.0 Six 277 7.3 305 8.0 95 2.5 1,420 37.2 875 22.9 844 22.1 3,814 2.7 Seven 1,778 9.0 322 1.6 283 1.4 9,907 50.4 4,539 23.1 2,824 14.4 19,653 13.9 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 7,492 20.2 4,307 11.6 3,640 9.8 12,586 34.0 6,207 16.8 2,785 7.5 37,016 26.2 Seldom 14,542 27.0 4,498 8.3 6,238 11.6 13,836 25.7 12,909 23.9 1,877 3.5 53,900 38.1 Sometimes 4,964 40.9 1,545 12.7 998 8.2 2,553 21.1 1,480 12.2 585 4.8 12,124 8.6 Often 7,323 24.8 2,636 8.9 6,510 22.0 4,827 16.3 7,756 26.2 504 1.7 29,557 20.9 Always 2,969 33.2 1,043 11.7 1,252 14.0 942 10.5 2,554 28.6 173 1.9 8,933 6.3 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Number of Days Bagamoyo Kibaha Kisarawe District Total Mkuranga Rufiji Mafia Status of Food Satisfaction District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Tanzania Agriculture Sample Census - 2003 Pwani Appendix II 272 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 12,815 33.9 6,465 17.1 4,874 12.9 7,570 20.1 5,494 14.6 531 1.4 37,749 26.7 Tiles 99 26.1 99 26.2 44 11.5 79 20.9 58 15.4 0 0.0 380 0.3 Concrete 0 0.0 0 0.0 0 0.0 0 0.0 53 100.0 0 0.0 53 0.0 Asbestos 440 84.0 0 0.0 0 0.0 0 0.0 62 11.8 22 4.2 524 0.4 Grass / Leaves 19,768 21.2 7,237 7.8 12,050 12.9 27,014 29.0 21,830 23.4 5,371 5.8 93,270 65.9 Grass & Mud 3,878 41.9 227 2.5 1,670 18.0 81 0.9 3,409 36.8 0 0.0 9,265 6.5 Other 289 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 289 0.2 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 2,234 7.0 4,524 14.3 1,391 4.4 4,982 15.7 18,280 57.7 283 0.9 31,695 22.4 Sale of Livestock 876 66.2 278 21.0 0 0.0 0 0.0 148 11.2 21 1.6 1,323 0.9 Sale of Livestock Products 1,334 63.3 281 13.3 95 4.5 313 14.9 0 0.0 83 4.0 2,106 1.5 Sales of Cash Crops 5,334 16.6 2,009 6.3 4,554 14.2 14,528 45.2 3,237 10.1 2,447 7.6 32,109 22.7 Sale of Forest Products 10,593 39.0 1,685 6.2 7,490 27.6 5,448 20.1 1,820 6.7 113 0.4 27,149 19.2 Business Income 3,550 29.2 1,142 9.4 1,386 11.4 3,954 32.6 1,633 13.4 477 3.9 12,141 8.6 Wages & Salaries in Cash 1,015 24.7 713 17.3 462 11.2 657 16.0 702 17.1 566 13.8 4,116 2.9 Other Casual Cash Earning 8,473 55.5 2,045 13.4 1,627 10.7 2,162 14.2 547 3.6 399 2.6 15,254 10.8 Cash Remittance 2,334 29.6 1,082 13.7 1,539 19.5 1,626 20.6 1,115 14.2 186 2.4 7,882 5.6 Fishing 1,073 16.7 160 2.5 47 0.7 949 14.8 2,900 45.2 1,289 20.1 6,418 4.5 Other 473 35.4 110 8.2 46 3.5 125 9.3 524 39.2 59 4.4 1,336 0.9 Total 37,290 26.3 14,029 9.9 18,637 13.2 34,744 24.5 30,906 21.8 5,924 4.2 141,530 100.0 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Roofing Materials District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Main Source of Cash Income District Total Bagamoyo Kibaha Kisarawe Mkuranga Rufiji Mafia Tanzania Agriculture Sample Census - 2003 Pwani 273 APPENDIX III QUESTIONNAIRES Appendix III 274 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 275 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 276 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 277 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 278 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 279 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 280 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 281 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 282 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 283 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 284 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 285 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 286 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 287 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 288 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 289 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 290 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 291 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 292 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 293 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 294 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 295 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 296 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source "a" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 297 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 298 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 299 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 300 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 301 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 302 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 303 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 304 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 305 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 306 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 307 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 308 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 309 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 310 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 311 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 312 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 313 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 314 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 315 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 316 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 317 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 318 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 319 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content CHAPTER 3 RAINFALL DISTRIBUTION Table 3.1 : Monthly Rainfall (in mm) at selected stations for the year 1997 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 95.4 20.5 163.2 340.7 170.3 2.2 17.1 62.6 101.6 252.3 408.4 352.4 1,986.7 Mwanza 166.1 23.7 170.6 334.6 93.0 48.1 2.0 1.2 1.0 145.7 238.7 181.2 1,405.9 Musoma 56.9 26.2 126.3 269.7 74.6 34.8 14.0 18.6 2.0 104.2 294.4 205.5 1,227.2 Shinyanga 74.9 157.2 62.7 174.1 175.9 0.0 0.0 0.0 0.0 0.0 92.0 475.4 1,212.2 Arusha 17.4 8.8 82.0 177.1 139.2 31.9 12.6 0.0 0.0 74.8 180.3 425.3 1,149.4 Kilimanjaro 4.2 0.0 58.1 330.5 196.3 38.0 11.1 0.0 0.0 49.2 72.3 144.5 904.2 Moshi 0.0 12.6 126.9 375.3 177.1 26.2 14.7 0.6 1.0 125.5 108.8 67.1 1,035.8 Tanga 0.0 1.7 97.1 254.3 194.3 152.6 13.7 55.6 44.5 805.5 271.2 75.4 1,965.9 Karume 0.4 0.0 296.7 479.5 77.2 159.8 149.0 7.8 0.7 372.0 142.0 245.8 1,930.9 Dar es salaam 1.7 0.3 232.8 167.0 98.8 173.5 5.6 5.8 2.9 244.7 164.7 184.3 1,282.1 Morogoro 13.8 55.6 156.6 246.5 35.7 39.5 4.4 2.0 0.0 88.5 93.9 252.3 988.8 Mtwara 45.2 122.9 342.1 136.3 44.6 45.5 11.6 1.0 5.0 13.1 160.8 194.3 1,122.4 Dodoma 46.4 82.5 22.0 26.7 52.6 0.0 0.0 0.0 0.0 1.8 89.5 310.4 631.9 Tabora 178.6 152.9 139.4 179.7 68.3 7.2 0.0 0.0 0.0 0.0 49.8 462.0 1,237.9 Kigoma 150.6 6.2 107.9 118.2 111.1 0.0 0.0 0.0 0.0 224.1 111.0 173.2 1,002.3 Iringa A/P 75.7 176.7 29.6 75.1 67.2 0.0 0.0 0.0 0.0 1.1 47.3 287.6 760.3 Mbeya A/P 134.9 182.1 51.4 192.1 0.0 0.0 1.4 0.0 0.0 22.7 158.5 481.2 1,224.3 Songea 185.3 316.0 49.5 66.6 0.0 10.7 0.0 0.0 0.0 2.7 6.5 258.9 896.2 Mahenge 149.3 168.6 476.6 566.8 24.9 149.2 16.4 0.0 0.0 110.9 227.2 413.1 2,303.0 Source : Directorate of Meteorology, Ministry of Communications and Transport A/P= Air Port Table 3.2: Monthly Rainfall (in mm) at selected Stations with full Data for the Year 1998 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 251.6 178.6 205.8 367.4 213.7 132.4 76.8 0.0 140.0 136.1 159.0 97.7 2057.2 Mwanza 151.5 115.8 94.4 234.2 24.2 80.1 1.2 0.0 16.5 45.4 86.2 27.4 876.9 Arusha 171.1 87.3 152.1 261.6 170.1 12.5 9.6 0.3 2.5 0.4 17.7 14.8 900.0 Sumbawanga 245.5 105.7 121.4 181.6 37.8 0.0 0.0 0.3 0.0 0.5 57.8 77.8 828.4 Iringa 199.5 170.1 91.1 108.0 98.9 0.0 0.0 0.0 0.0 0.0 0.7 18.9 687.2 Mbeya 191.5 352.0 124.2 86.9 8.8 0.0 0.0 0.0 0.0 16.5 8.6 76.6 865.1 Tabora 279.0 96.4 112.5 97.8 55.5 0.0 0.0 0.0 29.2 - 26.2 114.8 811.4 NB: Figure for October for Tabora region was not obtained Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.3: Monthly Rainfall (in mm) at selected Stations for the Year 1999 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 212.4 43.8 311.0 222.4 279.6 11.6 9.6 58.8 148.4 75.7 208.1 243.4 1,824.8 Mwanza 94.1 0.1 184.0 169.8 18.6 0.0 0.0 59.2 5.4 68.4 228.0 227.7 1,055.3 Musoma 93.9 12.8 343.5 136.3 64.1 0.0 0.0 4.9 11.1 31.4 181.1 33.4 912.5 Shinyanga 116.0 58.7 108.3 229.6 0.5 0.0 0.0 0.2 4.6 0.0 100.1 91.2 709.2 Arusha 35.1 13.5 176.2 95.8 75.2 15.2 8.2 6.7 1.1 0.7 130.0 29.6 587.3 Kilimanjaro 3.0 0.8 250.4 165.7 113.9 50.8 10.7 15.3 5.8 1.6 37.3 4.2 659.5 Moshi 20.8 0.6 229.8 393.4 91.7 72.8 14.9 24.9 13.6 1.7 71.4 23.1 958.7 Tanga 5.5 8.8 208.2 227.3 274.3 145.3 127.3 118.8 69.0 71.3 102.7 8.6 1,367.1 Same 28.2 15.8 127.1 77.0 40.7 27.5 7.2 27.5 2.7 5.7 182.0 25.3 566.7 Karume 58.3 1.5 271.6 514.6 502.0 186.6 78.3 59.8 28.0 36.4 67.2 60.4 1,864.7 Kisauni 65.8 51.1 194.0 311.5 179.5 158.3 55.4 80.9 31.3 17.0 249.4 120.3 1,514.5 Dar es salaam 26.4 112.6 220.6 267.1 148.0 79.8 60.8 22.2 13.5 27.2 115.0 173.8 1,267.0 Morogoro 8.3 29.0 186.2 202.7 89.8 27.5 38.7 21.6 16.1 11.5 33.6 60.7 725.7 Mtwara 180.3 170.3 168.7 240.5 48.5 31.5 7.8 2.1 23.3 1.1 52.1 74.3 1,000.5 Dodoma 137.2 49.9 226.2 73.3 0.1 0.0 0.0 0.0 0.1 0.0 0.0 114.8 601.6 Tabora 137.4 50.3 301.1 34.8 2.4 0.0 0.0 1.8 3.0 0.0 203.5 46.7 781.0 Kigoma 88.6 46.7 191.9 114.0 0.0 0.0 0.0 21.9 0.8 71.6 273.9 113.3 922.7 Sumbawanga 137.7 86.3 219.8 105.1 7.4 1.1 0.0 9.6 0.0 10.7 25.2 96.9 699.8 Iringa 115.4 104.8 190.4 35.7 0.0 0.5 0.0 0.0 0.0 0.0 1.0 70.5 518.3 Mbeya 327.0 116.1 330.3 125.2 52.6 2.5 0.0 4.9 2.1 3.1 12.1 144.7 1,120.6 Songea 128.1 125.1 396.3 168.4 15.3 0.0 0.0 2.0 2.7 2.8 10.0 83.9 934.6 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.4: Monthly Rainfall (in mm) for the Year 2000 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 52.2 90.7 115.7 199.2 212.8 39.2 48.2 69.8 77.7 130.2 234.2 223.4 1493.3 Mwanza 88.7 41.0 51.0 67.6 14.1 5.9 0.0 0.0 0.0 69.9 129.8 - 468.0 Musoma 11.8 37.1 122.7 106.4 41.9 9.4 0.0 43.8 15.2 39.2 88.6 190.3 706.4 Arusha 38.2 26.7 44.3 144.3 30.8 10.5 3.3 15.8 4.0 0.0 101.4 104.3 523.6 Kilimanjaro A/P 10.0 3.1 13.8 41.4 52.0 22.2 4.2 15.9 11.5 1.1 123.3 46.4 344.9 Moshi A/P 1.4 2.0 121.4 121.9 54.1 27.0 4.4 15.3 2.2 6.0 16.9 29.0 401.6 Same 0.0 0.4 104.3 60.2 38.5 40.1 1.1 4.9 17.6 2.1 56.5 26.4 352.1 Karume 7.4 0.0 157.5 369.9 19.9 82.7 35.4 0.7 13.6 14.7 76.6 104.0 882.4 Zanzibar 1.4 0.0 270.9 352.0 86.9 195.9 40.6 4.4 35.3 6.2 191.1 217.0 1401.7 Dar es salaam 1.8 3.5 108.4 261.2 70.0 126.9 18.7 24.0 3.2 6.2 79.2 220.0 923.1 Morogoro 68.8 37.9 183.0 110.3 47.8 48.0 5.2 0.3 4.9 0.0 49.5 205.0 760.7 Mtwara 127.6 60.3 360.5 72.4 54.9 25.1 28.7 16.6 20.3 10.1 97.1 154.1 1027.7 Dodoma 126.0 85.9 172.5 35.8 0.0 0.0 0.0 0.0 0.0 0.0 60.7 274.0 754.9 Tabora A/P 94.4 97.8 178.3 126.4 0.0 0.0 0.0 0.0 1.0 23.5 239.3 192.0 952.7 Kigoma 44.7 58.9 140.2 59.9 32.8 0.0 0.0 0.0 2.0 4.0 204.1 - 546.6 Iringa A/P 97.8 52.8 87.3 50.4 0.0 0.0 0.0 0.0 0.0 0.0 199.0 90.0 577.3 Mbeya A/P 147.3 174.0 205.5 70.1 0.0 0.0 0.0 0.0 0.0 0.0 163.0 259.0 1018.9 Songea A/P 191.4 162.7 189.3 120.6 11.4 1.0 0.0 3.1 0.0 0.0 111.8 248.0 1039.3 Tanga A/P - 0.0 109.3 164.4 246.6 266.1 80.7 35.5 34.1 44.7 35.3 51.7 1068.4 Source: Food Security Department (Meteorological Unit), Ministry of Agriculture and Food Security 'A/P (Air Port) Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Table 3.5: Monthly Rainfall (in mm) for the Year 2001 Bukoba 181.4 210.0 140.8 284.4 287.7 125.3 41.9 9.0 41.5 147.9 139.0 164.8 1773.7 Mwanza 210.6 113.5 72.3 164.2 25.2 1.6 25.4 38.3 31.1 104.7 219.6 139.6 1146.1 Musoma 74.0 34.9 271.2 207.7 129.1 21.8 32.7 19.0 16.2 98.5 89.7 24.3 1019.1 Arusha 225.1 23.5 178.9 108.5 47.7 16.9 0.0 3.0 0.4 0.2 43.3 55.7 703.2 Kilimanjaro A/P107.4 45.6 169.9 107.2 31.4 10.5 0.0 2.7 0.2 0.0 21.7 1.8 498.4 Moshi A/P 136.4 30.1 182.9 294.0 145.4 14.8 1.0 0.3 7.0 11.5 63.0 3.9 890.3 Same 121.9 14.4 42.4 127.0 15.0 62.6 0.0 0.0 0.2 0.0 45.7 42.6 471.8 Zanzibar 88.2 47.0 63.5 642.8 290.3 34.6 26.8 16.2 17.3 9.3 31.4 64.2 1331.6 Dar es salaam 64.5 71.3 139.0 296.6 162.5 14.0 19.6 3.9 5.0 6.7 15.5 82.2 880.8 Morogoro 104.3 99.0 172.5 224.6 90.4 4.6 5.8 0.0 0.0 11.1 0.0 71.7 784.0 Mtwara 298.9 155.6 244.7 124.8 11.0 0.0 7.2 9.9 5.0 56.4 12.8 99.4 1025.7 Dodoma 312.5 45.4 47.0 85.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 103.0 593.3 Tabora A/P 175.9 201.2 171.5 92.0 18.1 0.0 27.7 0.3 0.6 40.1 66.4 285.1 1078.9 Kigoma 161.5 59.6 228.3 31.0 39.0 17.7 0.5 22.0 30.6 64.1 71.4 91.0 816.7 Iringa A/P 437.6 247.4 184.4 33.6 6.0 0.0 0.0 1.3 4.2 0.0 6.2 229.2 1149.9 Mbeya A/P 451.3 106.5 103.0 95.6 24.1 0.0 0.0 0.0 8.6 21.6 33.3 175.4 1019.4 Songea A/P 269.1 118.5 290.5 52.4 20.4 0.0 0.0 0.0 1.3 0.0 10.4 127.9 890.5 Tanga A/P 39.1 28.5 53.4 157.7 204.7 122.6 17.1 25.0 7.2 24.3 57.9 76.3 813.8 Pemba 44.9 44.2 50.1 755.9 226.1 86.4 35.1 20.5 0.5 3.5 19.2 100.2 1386.6 Shinyanga 109.4 100.8 140.1 84.8 25.6 0.0 1.4 0.0 8.3 55.0 44.1 177.5 747.0 Sumbawanga 302.8 159.3 186.4 110.6 54.3 2.1 0.0 0.0 15.6 10.5 49.1 152.1 1042.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 97.5 103.3 440.8 428.3 62.3 23.5 14.2 28.5 92.0 175.0 267.5 174.5 1907.4 Mwanza 140.4 68.0 240.5 206.1 122.6 0.0 0.0 0.0 1.1 61.1 143.0 299.2 1282.0 Musoma 64.7 19.4 165.2 167.1 164.6 18.2 17.2 5.5 24.5 49.1 165.3 209.0 1069.8 Arusha 124.8 136.3 151.6 220.2 42.3 7.6 1.6 15.8 43.0 97.8 36.8 131.9 1009.7 Kilimanjaro A/P 89.4 66.3 101.6 162.4 27.1 2.5 0.7 25.6 19.2 110.3 49.0 134.2 788.3 Moshi A/P 69.5 21.7 177.8 490.0 71.8 1.6 3.7 39.8 116.2 72.3 27.1 129.0 1220.5 Same 67.7 55.5 88.8 58.1 4.8 0.0 0.0 28.9 30.8 171.0 48.4 114.0 668.0 Zanzibar 123.1 144.6 109.6 705.4 78.3 19.4 87.6 104.6 77.7 133.8 204.9 176.4 1965.4 Dar es salaam 97.5 103.3 440.8 428.3 62.3 23.5 14.2 28.5 92.0 175.0 267.5 174.5 1907.4 Morogoro 35.6 116.8 187.4 264.6 24.6 1.1 4.9 8.7 13.6 70.2 60.5 157.1 945.1 Mtwara 361.3 193.1 332.3 176.7 4.0 7.6 2.4 40.8 48.4 4.5 172.6 245.6 1589.3 Dodoma 285.0 97.6 71.3 4.6 2.5 0.0 0.0 0.0 0.0 1.5 0.0 187.5 650.0 Tabora A/P 145.7 100.8 224.9 142.4 80.2 0.0 0.0 0.0 0.0 39.5 66.4 228.5 1028.4 Kigoma 289.7 26.3 167.8 233.0 4.3 0.0 0.0 0.0 0.0 29.0 186.4 106.3 1042.8 Iringa A/P 170.6 92.0 178.0 20.1 3.8 0.0 0.0 0.0 0.0 0.0 4.4 141.4 610.3 Mbeya A/P 191.5 182.7 152.0 61.4 0.0 0.0 0.0 0.0 0.8 3.2 21.4 153.9 766.9 Songea A/P 360.0 192.8 298.0 116.3 1.7 2.0 0.0 0.0 0.2 1.1 87.2 198.3 1257.6 Tanga A/P 41.8 23.5 94.3 312.6 160.5 16.7 47.8 143.8 168.9 205.6 144.2 159.2 1518.9 Pemba 49.7 7.6 68.4 472.7 108.2 53.9 67.8 55.7 121.6 68.5 79.9 160.4 1314.4 Shinyanga 200.1 96.5 185.3 125.5 31.5 0.0 0.0 8.0 0.0 79.9 134.6 109.7 971.1 Sumbawanga 236.2 110.2 170.6 91.5 4.3 0.0 0.0 0.0 0.0 0.0 89.3 116.7 818.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.6: Monthly Rainfall (in mm) for the Year 2002 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 118.5 33.0 240.5 237.5 185.7 120.0 99.0 81.4 117.4 92.2 241.1 108.7 1675.0 Mwanza 44.7 20.1 186.0 154.1 86.2 0.5 13.0 21.1 6.4 21.8 85.8 251.3 891.0 Musoma 0.4 0.7 93.8 180.3 130.5 38.8 18.3 33.1 16.1 19.7 59.6 60.3 651.6 Arusha 33.0 49.2 53.0 39.4 128.3 17.3 2.8 0.1 7.3 22.9 18.1 77.2 448.6 Kilimanjaro A/P 9.7 14.6 18.4 40.8 188.9 12.2 3.8 0.0 5.0 2.1 0.0 43.1 338.6 Moshi A/P 3.7 10.1 62.0 159.4 191.4 53.8 9.7 2.8 0.4 0.0 1.1 19.0 513.4 Same 8.5 66.2 56.1 31.3 85.5 11.6 0.0 1.8 0.0 0.5 47.4 23.5 332.4 Zanzibar 4.1 3.0 44.7 32.4 209.7 38.4 42.3 15.3 17.2 108.7 88.5 75.1 679.4 Dar es salaam 20.1 22.2 122.4 13.7 130.8 109.5 26.1 0.9 3.5 22.4 89.2 24.6 585.4 Morogoro 63.0 30.5 162.3 54.5 51.2 13.2 11.4 0.0 0.0 55.2 4.3 50.1 495.7 Mtwara 141.3 111.5 92.2 51.8 32.4 0.0 0.0 2.4 1.5 2.2 6.5 39.8 481.6 Dodoma 90.4 68.2 51.9 7.7 17.8 0.0 0.0 0.0 0.0 76.2 0.6 175.5 488.3 Tabora A/P 186.7 113.2 80.0 159.4 38.7 0.0 0.0 0.0 13.0 32.5 76.8 136.1 836.4 Kigoma 164.7 153.1 161.0 170.9 6.5 8.3 0.0 3.8 22.0 73.0 91.8 84.8 939.9 Iringa A/P 156.9 93.6 58.1 44.0 14.3 0.0 0.0 0.0 0.0 13.5 2.4 93.5 476.3 Mbeya A/P 247.7 111.2 167.0 43.5 0.0 0.0 3.4 0.0 0.0 16.6 80.7 146.3 816.4 Songea A/P 160.3 226.1 254.6 67.2 12.8 0.0 0.0 0.0 0.0 0.0 22.9 217.5 961.4 Tanga A/P 0.6 0.0 6.1 43.2 285.8 36.9 27.0 53.3 39.3 104.0 86.2 10.4 692.8 Pemba 17.6 1.5 45.2 130.6 472.3 49.7 71.3 28.1 23.8 92.9 3.1 22.0 958.1 Shinyanga 159.7 14.4 106.9 171.6 58.5 0.0 0.0 2.7 3.8 27.1 24.2 86.1 655.0 Sumbawanga 172.2 24.2 112.7 62.0 10.9 3.3 4.1 0.0 0.0 0.0 28.1 203.0 620.5 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.8: Total Monthly Rainfall (in mm) for selected stations 2004 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 211.0 171.1 251.2 327.1 223.8 10.1 43.1 47.3 118.8 161.1 121.3 165.3 1851.2 Musoma 88.6 76.8 139.7 191.3 145.9 3.3 0.0 0.0 4.1 12.7 83.3 96.5 842.2 Mwanza 91.3 84.0 122.5 115.7 32.4 26.2 0.0 2.4 25.7 147.5 183.3 198.1 1029.1 Shinyanga 138.7 84.4 159.9 170.0 4.3 0.0 0.0 0.9 30.1 17.3 75.8 177.0 858.4 Kigoma 126.1 139.6 85.2 54.4 0.0 0.0 0.0 10.2 47.9 38.3 83.4 164.9 750.0 Tabora 145.8 134.7 164.8 92.8 0.0 0.0 0.0 11.4 36.3 24.8 102.5 473.9 1187.0 Dodoma 112.9 148.2 161.9 56.9 0.0 0.0 0.0 0.0 0.0 0.0 90.4 177.3 747.6 Mbeya 269 184.0 214.0 135.7 0.0 0.0 0.0 0.0 8.0 7.4 28.5 283.4 1130.0 Iringa 197.5 168.1 248.2 89.2 0.0 0.0 0.0 0.0 0.0 0.2 22.8 95.4 821.4 Sumbawanga 195.7 127.4 109.2 63.8 0.0 0.0 0.0 0.0 20.5 0.0 81.6 289.1 887.3 Morogoro 142.3 196.3 127.7 215.8 1.5 2.8 1.2 0.0 0.0 38.4 56.3 38.9 821.2 Songea 264.2 174.5 199.8 128.2 0.0 0.0 0.0 0.0 0.0 1.7 59.9 236.4 1064.7 Mahenge 287.9 298.6 311.5 369.3 53.5 26.8 0.0 10.2 26.3 92.8 156.8 351.9 1985.6 Arusha 86.3 72.2 57.2 97.7 0.0 10.2 0.0 0.0 7.3 30.7 25.0 80.4 467.0 Kilimanjaro 36.4 27.9 48.2 91.9 9.5 7.5 0.0 0.0 1.9 18.9 28.6 86.5 357.3 Moshi 41.4 31.4 55.9 196.0 65.8 0.0 2.4 0.0 0.0 61.1 27.6 39.6 521.2 Same 0.0 44 80.2 47.8 11.3 5.9 2.2 0.0 0.0 29.4 70.3 50.8 341.9 Tanga 148.0 82.4 62.9 209.2 46.2 128.4 2.2 11.8 24.3 97.8 185.4 103.0 1101.6 Dar es salaam 77.2 149.8 131.2 297.6 19.3 42.2 0.0 13.6 31.1 93.5 47.4 181.3 1084.2 Table 3.7: Monthly Rainfall (in mm) for the Year 2003 Mtwara 205.8 273.6 96.7 152.4 0.0 2.9 0.0 0.0 0.0 105 135.8 354.7 1326.9 Singida 56.7 275.7 160.0 85.7 0.0 0.0 0.0 0.0 0.0 0.0 80.4 73.2 731.7 Handeni 203.5 124.0 177.4 195.3 2.4 29.7 4.2 0.0 0.0 141.4 76.7 41.2 995.8 Source : Directorate of Meteorology, Ministry of Communications and Transport Table 3.9: Total Monthly Rainfall (in mm) for selected stations 2005 Station/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Bukoba 156.3 103.2 281.5 308.2 125.9 76.3 42.5 56.8 83.2 67.8 105.9 102.9 1510.5 Musoma 161.9 73.7 183.8 117.8 62.4 39.7 10.3 23.1 25.5 49.9 53.2 28.1 829.4 Mwanza 169.2 8.1 232.8 117.6 87.5 0.8 11.0 19.2 170.6 86.8 34.5 101.6 1039.7 Shinyanga 90.3 44.3 141.9 67.3 38.6 0.2 0.0 0.8 2.2 13.9 27.0 76.8 503.3 Kigoma 265.4 29.6 80.3 35.1 10.5 0.0 0.0 2.5 0.0 22.7 153.7 31.0 630.8 Tabora 177.6 34.7 184.2 89.8 41.0 0.0 0.0 0.0 0.0 6.2 34.6 86.9 655 Dodoma 33.1 58.6 129 17.2 0.0 0.0 0.0 0.0 0.0 36.0 8.7 45.7 328.3 Mbeya 165.0 70.9 141.7 56.3 0.0 0.0 0.0 0.0 0.0 1.5 45.8 116.6 597.8 Iringa 175.2 105 83 19.2 0.0 0.0 0.0 0.0 0.0 0.7 4.0 10.5 397.6 Sumbawanga 174.2 78.8 165.1 29.4 1.8 0.0 0.0 0.0 2.0 1.0 6.9 148.2 607.4 Morogoro 115.1 51.9 131.3 102.2 28.6 11.2 0.0 0.0 0.0 4.6 23.3 11.2 479.4 Songea 129.8 65.5 254.5 55.9 1.9 0.0 0.0 0.0 0.0 0.0 0.0 86.8 594.4 Mahenge 221.3 463.7 389.1 450.9 118.3 30.3 1.1 1.3 10.2 4.4 14.8 99.1 1804.5 Arusha 13.4 6.2 120 130.1 56.2 10.7 0.0 0.2 2.9 58.7 86.5 23.0 507.9 Kilimanjaro 23.7 9.2 96.5 123.4 49.5 11.1 0.0 0.0 2.2 10.3 12.2 2.0 340.1 Moshi 0.0 2.8 55.2 150 40.1 26.8 0.0 1.4 1.9 30.5 23.7 0.3 332.7 Same 31.7 0.5 39.1 108.7 42.2 12.8 0.0 0.0 10.8 24.6 15.8 5.8 292 Tanga 35.7 0.1 19.1 192.2 81.5 40.7 11.4 25.1 15.5 48.9 107.0 3.7 580.9 Dar es salaam 55.5 174.1 70.2 119.5 63.0 11.7 2.3 0.0 10.5 91.6 24.5 13.4 636.3 Mtwara 290.0 55.7 219.5 118.7 37.6 0.0 0.0 0.0 18.1 8.9 1.4 27.6 777.5 Singida 82.4 45.3 145.7 60.6 18.6 0.0 0.0 0.0 0.0 20.1 8.1 17.9 398.7 Handeni 30.1 0.2 295.6 130.6 33.7 0.8 0.0 0.0 45.0 16.6 16.5 0.0 569.1 Source : Directorate of Meteorology, Ministry of Communications and Transport | false |
# Extracted Content CHAPTER 8 RESEARCH AND TRAINING Table 8.1: Agricultural Research Zones in Tanzania Zone Regions Covered Zonal Centre Research Stations Research Mandate CENTRAL Dodoma, Singida Mpwapwa Hombolo, Makutupora Sorghum, Millet and Grapes EASTERN Dar es Salaam, Pwani, Morogoro, Tanga ARI-Ilonga Ilonga, KATRIN,Cholim a/Dakawa, Mlingano, Kibaha, Mikocheni Maize, rice, sorghum and millet, grainlegumes, horticulture, soil and water management, horticulture,sugarcane, root and tubers, spices, coconut, biotechnology LAKE Kagera, Mwanza, Shinyanga, Mara ARI-Ukiriguru Ukiriguru, Maruku Phaseolus Beans, Grain legumes,Root and Tubers, sorghum and millets, rice, bananas, NORTHERN Kilimanjaro, Arusha, Manyara ARI-Selian Selian, Hort- Tengeru Wheat and Barley, Bananas, Horticulture,Maize, Phaseolus beans, irish potatoes, sweet potatoes SOUTHERN Mtwara, Lindi ARI-Naliendele Naliendele Cashewnut, Oilseeds, cassava SOUTHERN HIGHLANDS Mbeya, Iringa, Rukwa, Ruvuma ARI-Uyole Uyole, Kifyulilo Maize, Phaseolus beans,wheat, pyrethrum,horticulture,ric e, irish potatoes WESTERN Tabora, Kigoma ARI-Tumbi Tumbi, Seatondale Agroforestry Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives 141 Table 8.2: Number of Research Scientists by Qualifications as of January 2006 ZONE Station BA/BSc MA/MSc PhD CENTRAL MAKUTUPORA 1 2 1 HOMBOLO 1 2 0 Sub-Total Central 2 4 1 EASTERN ILONGA 9 10 6 MLINGANO 5 13 6 MIKOCHENI 5 11 5 KATRIN 2 3 0 KIBAHA 4 5 2 CHOLIMA/DAKAWA 2 7 0 Sub-Total Eastern 27 49 19 LAKE UKIRIGURU 10 19 3 MARUKU 6 5 1 Sub-Total Lake 16 24 4 NORTHERN SELIAN 8 27 9 HORT-TENGERU 6 7 1 Sub-Total Northern 14 34 10 SOUTHERN NALIENDELE 9 9 8 Sub-Total Southern 9 9 8 SOUTHERN HIGHLANDS UYOLE 9 29 8 KIFYULILO 0 2 0 Sub-Total Southern Highlands 9 31 8 WESTERN TUMBI 10 9 3 Sub-Total Western 10 9 3 DRT-DSM DRT-HQ 2 17 5 Sub-Total DRT-HQ Temeke 2 17 5 Total 89 177 58 Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives Table 8.3: Number of research Scientists by Gender by Qualifications Qualification Female Male Total PhD 11 47 58 MSc/MA 34 144 178 BSc/BA 28 61 89 Total 73 252 325 Source: Directorate of Research and Training, Ministry of Agriculture, Food Security and Cooperatives 142 | false |
# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE Government City-Mtumba P. O BOX 2182 40487 DODOMA Email: [email protected] BUILDING A BETTER TOMORROW: YOUTH INITIATIVES FOR AGRIBUSINESS (BBT-YIA) THE PROPOSED ESTABLISHMENT OF CHINANGALI II BLOCK FARM LOCATED AT MWEGAMILE VILLAGE, BUIGIRI WARD, CHAMWINO DISTRICT COUNCIL IN DODOMA REGION RESETTLEMENT ACTION PLAN CONSULTANT Eng. Lait A.Simukanga Registered Environmental Consultant, Reg. No NEMC/EIA/0032 Practicing License No. NEMC/PC/EIA/2021/0020 Kimara Street Plot No. 0095, P.O. Box 13033, DAR ES SALAAM, Email: [email protected] Mobile: +255 754 271175 Date of Submission: 01 May 2024 RAP for Chinangali II Block Farm May, 2024 ii EXECUTIVE SUMMARY The Ministry of Agriculture is in the process of developing Chinangali II Block Farms in Chamwino district Council Dodoma Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm followed by the Resettlement Action Plan (April 2024) The community in the proposed BBT farm occupied the land through customary land ownership which includes inheritance from the ancestors and purchasing from neighbours. The Village Council in collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of the block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. A series of village assembly and village council meetings were conducted since March 2023 with staffs from Chamwino District Council along with visiting the proposed project area site on regular basis. These meetings came out with the decision that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village. Based on the assessments and negotiations carried out within the context of the resettlement for the works (development/construction) of the project, and by mutual agreement, the PAP receives the sum of Tsh. 1,000,000/= per acre. The Total land acquired through purchasing is estimated to be 1,552 acres. Considering the economic importance required for development of Chinangali II BBT farm and the people that were using the land for subsistence farming located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. This requires preparation of a RAP to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: Nature and category of impacts S/N Property Category of Impact Number of PAPs 1 Purchased Land Loss of agricultural land 1,552 acres Number of PAPs Livelihood 226 2 Residential Structure Temporary Houses 0 3 Entire residential structures House owners 0 Residential tenants 0 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners 7 Amount of funds set aside for land purchase 1,152,000,000 RAP for Chinangali II Block Farm May, 2024 iii 8 Number of PAPs paid and Amount 210 PAPs Tsh. 1,074,690,000 9 Number of PAPs not paid and Amount 16 PAPs Tsh. 77,610,000 Evidences of remittance for payment to RAP are attached as Appendix III and a full list of remittance payment is attached as a separate document. Reason for not being paid is due to bank transfer logistics challenges for 16 PAPs. The District Council is liasing with the banks to resolve the problem for payments to the remaining PAPs. The Cost of RAP implementation including payments to the remaining PAPs, monitoring and follow up is estimated to be Tsh 103,610,000/=. The funds for RAP implementation are available. RAP for Chinangali II Block Farm May, 2024 iv Contents EXECUTIVE SUMMARY .......................................................................................................................................... ii LIST OF TABLES ....................................................................................................................................................... v LIST OF PLATES ........................................................................................................................................................ v ABBREVIATIONS ..................................................................................................................................................... vi 1.0 INTRODUCTION .................................................................................................................................................. 1 1.1Project Background ............................................................................................................................................. 1 1.2 Objective of the project ...................................................................................................................................... 1 1.3 Project Justification ............................................................................................................................................ 2 1.4 Project Beneficiaries ........................................................................................................................................... 2 1.5 Need for Resettlement Action Plan .................................................................................................................... 3 1.6 Objective of Resettlement Action Plan............................................................................................................... 4 1.7 Methodology for Preparation of RAP ................................................................................................................ 4 1.7.1 Conducting Literature Review ......................................................................................................................... 4 2.0 PROJECT DESCRIPTION .................................................................................................................................... 5 2.1 Location .............................................................................................................................................................. 5 2.1.1 General project location .......................................................................................................................... 5 2.2.2 Specific project Location ............................................................................................................................. 5 2.2 Overview of the project affected area ................................................................................................................. 5 2.2.1 Characteristics of PAPs in Chinangali II BBT farm .................................................................................... 6 2.2.3 House conditions ......................................................................................................................................... 6 3.0 LAND ACQUISITION PROCESS ........................................................................................................................ 7 3.1 Land purchase and price ..................................................................................................................................... 7 3.2 Land Tittle Deed ................................................................................................................................................. 8 4.0 LEGAL AND INSTITUTION PRAMEWORK FOR LAND ACQUISITION IN TANZANIA........................... 9 4.1 Land Tenure and Ownership in Tanzania ........................................................................................................... 9 4.2 Land categories in Tanzania ............................................................................................................................... 9 4.2.1 General land ................................................................................................................................................ 9 4.2.2 Village land ................................................................................................................................................. 9 4.2.3 Reserved land .............................................................................................................................................. 9 4.3 Land acquisition process for Chinangali II Block Farms ..................................................................................10 4.4 Method of Land acquisition ...............................................................................................................................10 4.5 Lively Hood Restoration mechanism ................................................................................................................10 5.0 CUT-OFF DATE ................................................................................................................................................11 6.0 GRIVANCES AND DISPUTE RESOLUTION ...................................................................................................12 6.1 Grievances Procedures ......................................................................................................................................12 6.2 Proposed Grievance Management and Redress Mechanism .........................................................................13 6.2.1 Grievance Redress Committees ..................................................................................................................13 6.2.2 Apeal ..........................................................................................................................................................13 6.2.3 Eligibility ....................................................................................................................................................14 7.0 IMPLEMENTATION SCHEDULE ......................................................................................................................15 RAP for Chinangali II Block Farm May, 2024 v 8.0 MONITORING PROGRAMME ...........................................................................................................................16 9.0 RAP BUDGET AND SCHEDULE .......................................................................................................................17 APPENDICES .............................................................................................................................................................18 Appendix I: Consent Letter from DED-Chamwino and Minutes of agreements with Community who sold land for Chinangali II Block Farm ............................................................................................................................................18 Appendix II: Land Tittle Deed for Chinangali II block farm ......................................................................................26 Appendix III: Sale Agreement between Chamwino District Council and Mega Beverage Limited ...........................30 Appendix IV: Sample Contract with PAPs on sale of Land ........................................................................................34 Appendix V(a): Letter from Chamwino District Council-Submission of Land Purchases report to the Ministry of Agriculture ..................................................................................................................................................................42 Appendix V(b): Names of PAPs who has received payments .....................................................................................43 Appendix V(c): Names of PAPs who have not received payments .............................................................................48 Appendix VI: Report on Funds Remittances to PAP ..................................................................................................49 LIST OF TABLES Table 1: Population at Chinangali II block farm and surrounding villages .................................................................. 5 Table 2: Population at Buigiri ward and Surrounding village ...................................................................................... 6 Table 3: PAPs within Chinangali II BBT farm ............................................................................................................ 8 Table 4: Budget for RAP Implementation ...................................................................................................................17 LIST OF PLATES Plate 1: Current land use .............................................................................................................................................. 6 RAP for Chinangali II Block Farm May, 2024 vi ABBREVIATIONS AfDB African Development Bank BBT-YIA Building a Better Tomorrow: Youth Initiatives for Agribusiness Program CDOs Community Development Organizations CSA Climate Smart Agriculture DPs Development Partners EIA Environmental Impact Assessment GDP Gross Domestic Product GOT Government of Tanzania LGA Local Government Authority MLHHSD Ministry of Land, Housing and Human Settlements Development MoA Ministry of Agriculture MoFP Ministry of Finance and Planning NEMC National Environment Management Council NGO Non-Governmental Organization PAP Project Affected Person NGOs Non-Governmental Organizations PO-RALG President’s Office - Regional Administration and Local Governments RAP Resettlement Action Plan ( RSs Regional Secretariats URT United Republic of Tanzania VEO Village Executive Officer RAP for Chinangali II Block Farm May, 2024 1 1.0 INTRODUCTION 1.1Project Background The Ministry of Agriculture is in the process of developing Chinangali II Block Farm in Chamwino district Council Dodoma Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm. The EIA documents indicated that the project will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. The important undertakings, land acquisition, farm clearing infrastructure development such as borehole drilling and water storage reservoir will ensure sustainable development of the farm in terms of water supply and crop production. Moreover, smallholder farmers in the surrounding villages will benefit from modern farming technologies and operations. The block farm is intended to support youth farmers aged between 18 and 40 years and they will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. Furthermore, the project will be advantageous to the private sector investors’ who have the insights knowledge of farm's operations. In addition, the government will enhance its tax base and benefit from tax collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Block Farms will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.2 Objective of the project The overall project objective is to promote the engagement of the identified Tanzanian youth in agriculture and agribusiness for sustainable improved livelihoods. This will be achieved through attaining the following strategic objectives: i) Youth to engage in agribusiness through effective communication for changing their negative behavior and attitude toward agriculture and agribusiness; ii) Youth through practical and hands on agribusiness and entrepreneurship skills development and access to new technologies; iii) Enhancing the youth in agribusiness through facilitating their access to productive resources, finance and markets; and iv) Facilitating and monitoring (M&E) of youth agribusiness for enhancing learning, partnerships/synergy, and efficient and effective utilization of resources. The Specific Objectives of Chinangali II projects are to: i) Engage up to 310 youths for training in agricultural production and agribusiness; ii) Develop a 1,552 acres block farm for various crop value chains; iii) Construct 38 Shamba houses and RAP for Chinangali II Block Farm May, 2024 2 iv) provide models for production and productivity enhancement through collaborative efforts of large farmers working together with youth 1.3 Project Justification The Government of Tanzania is encouraging large scale cultivation in order to boost the agricultural sector which is the backbone of the country’s economy. The initiative of block farming and value chain infrastructure development is linked to private sector initiatives to invest in the agricultural and rural development. Chinangali II Block Farm will provide models for production and productivity enhancement through collaborative efforts of large farmers working together for mutual benefits of youth. Participation of potential investors in new large scale commercial block farms is in line with the Ministry of Agriculture’s efforts to encourage private sector involvement in commercial agricultural development which is now taking place at a high pace. The poor response of private investors and the youth involvement in agriculture has mainly been due to the potential risks associated with the business. Among the risks are the possibility of not recovering the capital investment due to several factors such as crop failure due to poor rains, crop failure due to pests and diseases; the assurance on availability of water, land title deeds and poor market infrastructure. Since the involvement of the private sector investing in agriculture is very important for assurance of food security, significant contribution to national income and employment, the Ministry of Agriculture has taken a bold measure to leverage the youth and private sector as an incentive to invest in large scale commercial farming blocks. The establishment of Chinangali II block farm will have a number of significant positive impacts compared to the possible negative impacts. Borehole drilling and water storage reservoir development is one of the important undertakings to provide reliable water supply for crop production. Also, the crop will add value to the crops for better competitive market price within and outside the country. The smallholder farmers surrounding the project area will also benefit from the farm technology and operations. Youth farmers will access improved agricultural services like supply of inputs, farmers training, formation and strengthening of organizations and networks, processing of agricultural produce, and provision of loans and microfinance services. Technologies that will be disseminated to the identified youth include the use of improved seeds and varieties, water management systems, agro-mechanization, value addition techniques, and modern crop husbandry such as improved seeding, planting, weeding and fertilizer application. Value addition activities such as vegetables and fruits sorting and packagingwill encourage other youth and neighboring farmers to invest in crop production for increased income and food security. 1.4 Project Beneficiaries The primary beneficiaries of Chinangali II block farm are youth aged between 18 to 40 years old up to 310 youth (217 Male and 93 Female) will directly benefit from Chinangali II block farm. RAP for Chinangali II Block Farm May, 2024 3 Others beneficiaries include service providers both public and private sectors. For the case of private sector beneficiaries will include processors, input suppliers, traders, financial institutions, and communities in neighboring villages where the project will be implemented. On the other hand, for public sector beneficiaries of the project comprise research and academic institutions. The government will also benefit from the tax collection on the sale of the products from the farm. 1.5 Need for Resettlement Action Plan At Chinangali II the community in the proposed BBT farm occupied the land through customary land ownership which includes inheritance from the ancestors and purchasing from neighbours. The Village Council in Collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of the block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. This gave an opportunity for the community to sell their land for public use and obtained their concerns. A series of village assembly and village council meetings were conducted since March 2023 (Minutes in Appendix 1) with staff from Chamwino District Council along with visiting the proposed project area site on regular bases. These meetings came out with the decision that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village which was Tsh. 1,000,000/= per acre. The Total land acquired through purchasing is estimated to be 1,552 acres. The Ministry of Agriculture in collaboration with Chamwino district council prepared land purchasing contracts which were signed by each individual who volunteered to sell his/her land for BBT use at a market price. After purchasing processes were completed, the Land for BBT block farm at Chinangali II block farm was entitled to the right of occupancy to the Ministry of Agriculture in January 2024 for a term of ninety-nine (99) years. The Land is known as Plot No. 3 Block “c” situated at Chinangali II village in Chamwino District. The Land Title deed granted is No 91072 -DIR containing an area of 579.8 Hectares. According to the Urban Planning (Use Groups and Use Classes) Regulations, 2018. The land shall be used for urban farm purposes under user group “R” Use class “c”. However as of April 2024 some few community members 16 in number were yet to be paid. The AfDB mission which was in the Country from 3rd -12th April 2024 indicated the need to prepare a Resettlement Action Plan (RAP) for Chinangali II block farms to regularize and document the process for the resettlement of the Project Affected People (PAPs). The RAP will provide a road map for the manner in which displacement and resettlement issues were dealt with. Among the activities that would be undertaken for developing Resettlement Action Plan (RAP) include the following: RAP for Chinangali II Block Farm May, 2024 4 i) Assessment of the possible land acquisition process /resettlement impacts for the proposed block farms in accordance with national policies and legislations and AfDB’s Integrated Safeguards System (ISS 2023). ii) Consultation with the communities and project affected persons whenever necessary; iii) Assessing whether the land was purchased at the land market value iv) Compile documents on the land purchased contracts and the reasons for few PAPs who have not yet been compensated. 1.6 Objective of Resettlement Action Plan Considering the economic importance required for development of Chinangali II BBT farm and the people that were using the land for subsistence farming located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. The main objective of this RAP is to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: i) Lay down the agreed principles that were applied to the resettlement of the community ii) Document as far as possible, those people who sold their land for use by BBT project; iii) Identify if there are physical and /or economic displacement losses; iv) Describe the legal and institutional framework for dealing with displacement; v) Provide a general socio-economic profile of the affected persons living in areas where displacement is likely to occur; vi) Set out the criteria used to determine market price for purchase of Land vii) Identify and document Project Affected Persons (PAPs); 1.7 Methodology for Preparation of RAP The main methodology involved in preparation of this RAP, is based on data obtained from Chamwino district council, the Ministry of Agriculture, census, observation and consultation. The data from the project area were collected by the Consultant for the purpose of RAP preparation. The preparation of RAP involved various activities. The philosophical underpinning of the plan preparation is the use of a participatory approach of stakeholders including affected communities and PAPs. Among others, the methods and activities employed in the process of developing the RAP include: 1.7.1 Conducting Literature Review The filed visits were complemented by reviewing the existing literatures related to the resettlement. The literature review involved the identification of the applicable legal and administrative frameworks and policies of the United Republic of Tanzania, AfDB and the Environmental and Social Impact Assessment Report for the Chinangali II block farm 2024 RAP for Chinangali II Block Farm May, 2024 5 2.0 PROJECT DESCRIPTION 2.1 Location 2.1.1 General project location The project is located in Chamwino District which is one of the seven districts of Dodoma region. It lies on the central plateau of Tanzania in the western bearing along Dar es Salaam Road. The district lies between latitudes 40° S and 80° S and between longitudes 35° E and 37° E of Greenwich meridians. The district has a total area of 8,056 km. square. The District borders Dodoma City on the western front, Chemba, Kondoa District on the North Kongwa and Kiteto Districts on the East and Mpwapwa District and Iringa rural on the Southwest, also, Bahi District on south east front. Administratively the district council is divided into 5 divisions 36 wards, 107 villages and 814 hamlets. 2.2.2 Specific project Location Specifically, the proposed Chinangali II block farm is located at Mwegamile Village Buigiri ward in Chamwino District in Dodoma Region. The site is accessible through Dodoma-Dar es salaam highway, 56km from Dodoma City Center and 1.5km from the main road on the left side on the way to Morogoro. It is adjacent to the CHABUMA AMCOS grape farm and a private investor known as Mega Beverage Company Limited producing grapes as well. Table 1: Population at Chinangali II block farm and surrounding villages S/N Ward Villages Number of household Population 2022 Buigiri Buigiri 1,124 6,440 Chinangali II 750 2,308 Mwegamile 834 2,130 TOTAL 2,708 10,878 2.2 Overview of the project affected area The vegetation of the Project area is characterised by scattered woodland trees especially dominated by baobab trees (Adansonia), umbrella thorn tree (Acacia tortillis) and open grassland with very few miombo trees. The major food crops grown at Chinangali II village are sorghum, maize and finger millet. Cash crops are groundnuts, sunflower, sesame, and finger millet. At the project area, there are very few indigeneous tree species which might be endangered, however it is an ecological important to consider these vegetation cover species during construction phase. RAP for Chinangali II Block Farm May, 2024 6 Plate 1: Current land use 2.2.1 Characteristics of PAPs in Chinangali II BBT farm The population of Chinangali II village is dominated by Gogo ethnic group which covers about 95% of the village population while the remaining 5% is Kagulu and other small ethnic groups. Youth within the age between 15 and 35 are 506 (male 223 and female 286) which is 27% of the village population (Village population). Table 2: Population at Buigiri ward and Surrounding village Ward Villages Number of household 2012 population Projected 2022 population Buigiri Buigiri 1,124 4,915 6,440 Chinangali II 750 1,873 2,308 Mwegamile 834 2,085 2,130 TOTAL 2,708 8,873 10,878 2.2.3 House conditions There are no settlements in the project area. The settlement is concentrated at the village center. RAP for Chinangali II Block Farm May, 2024 7 3.0 LAND ACQUISITION PROCESS The Ministry of Agriculture requested the President’s Office Regional Administration and Local Government (PO-RALG) to identify areas suitable for establishment of large farms to be used for Building a Better Tomorrow Block Farms for youth. The PO-RALG further liaised with Chamwino District Council to identify suitable land for BBT Block Farms. Chamwino District Councils in collaboration with Buigiri Ward and Mwegamile Village Council in consultation with the Ministry of Lands, Housing and Human Settlements earmarked and allocated arable land for Chinangali II block farm. However; the land allocated for Chinangali II block farm was owned by individuals through inheritance from ancestors, rented or purchased which is common for most of village land ownership in Tanzania. The Land Act and Village Land Act (1999) create three categories of land namely i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. The Land within the proposed Chinangali II block farm falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chamwino District Council Land Officer there was no Certificates of Customary Rights of Occupancy (CCROs) within the project area. The Village Council in Collaboration with Chamwino District Council adopted negotiations and persuasion in acquiring land for establishment of Chinangali II block farm. The process included investigation of the land to see if it is suitable for crop production and notification to the customary landowners to inform them on the intension of the Ministry of Agriculture in collaboration with Chamwino district council to purchase their land for BBT farm. This gave an opportunity to village leaders to meet the people who will be interested to sell their land for public use and to obtain their concerns. The Ministry of Agriculture in collaboration with Chamwino district council prepared land purchasing contracts which were signed by each individual who all volunteered to sell their land for BBT use (Refer attached contract samples in Appendix 1V). 3.1 Land purchase and price A series of village assembly and village council meetings were conducted since March 2023 (Minutes in Appendix 1) with staff from Chamwino District Council along with visiting the proposed project area site on regular basis. These meetings came out with an agreement that the people who will sell their land for the benefits of BBT must be paid according to the prevailing land market value at the village which was Tsh. 1,000,000/= per acre. The list of people who sold their land is 226 and the total land acquired through purchasing is estimated to be 1,552.3 acres. The list of people and their land sizes is attached as Appendix V (a) –(c). A comparative price check was also made with the private company who purchased land adjacent to the BBT project area in 2019. The MEGA BEVERAGE COMPANY bought the land at a price of Tsh. 500,000/= per acre. RAP for Chinangali II Block Farm May, 2024 8 3.2 Land Tittle Deed After fulfilling these requirements, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture for a term of ninety nine years (99) from January 2024. The Land is known as Plot No. 3 situated at Chinangali II Village in Chamwino District. The Land Title deed granted is No. 91072 DRL containing an area of 579.80 Hectares (Appendix II Certificate of Occupancy). According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for Urban Agriculture under user group “R” Use class “c”. Therefore, the proposed Chinangali II Block Farms are located in an area designated for agricultural production. Table 3: PAPs within Chinangali II BBT farm S/N Property Category of Impact Number of PAPs 1 Purchased Land Loss of agricultural land 1,552 acres Number of PAPs Livelihood 226 2 Residential Structure Temporary Houses 0 3 Entire residential structures House owners 0 Residential tenants 0 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners 7 Amount of funds set aside for land purchase 1,152,300,000 8 Number of PAPs paid and Amount 210 PAPs Tsh. 1,074,690,000 9 Number of PAPs not paid and Amount 16 PAPs Tsh. 77,610,000 Reason for not being paid is due to bank transfer logistic challenges for 16 PAPs. The District Council is liaising with the banks to solve the problem for payments to the remaining PAPs (Refer Appendix II for list of PAPs paid and not paid). Evidences of remittance are attached as Appendix III and a full list of remittance payment is attached as a separate document. RAP for Chinangali II Block Farm May, 2024 9 4.0 LEGAL AND INSTITUTIONAL FRAMEWORK FOR LAND ACQUISITION IN TANZANIA 4.1 Land Tenure and Ownership in Tanzania Land tenure and ownership in Tanzania is governed by statutes such as the 1977 Constitution, National Land Act No. 4 of 1999, Village Land Act No. 5 of 1999, Land Acquisition Act 1967, and Land Ordinance, 1923 Cap. 113. Land in Tanzania is owned by the state (vested in the President as a trustee). For the purpose of management of land under the land Act No. 4 of 1999 and all other laws applicable to land, public land in Tanzania is either categorised as:i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. 4.2 Land categories in Tanzania 4.2.1 General land The general Land in Tanzania is described as consisting of all land, which is neither village land nor reserved land. All urban land falls under this category, except land, which is covered by laws constituting reserved land, or that which is considered hazard land. General land is governed by the Land Act and, hence, is under the control and jurisdiction of the Commissioner for Lands. This ministerial key person has delegated much of the powers to local government land officers. Property rights can be created over general land in terms of a granted Rights of Occupancy for a period of 33, 66 or 99 years confirmed by a Certificate of Title. Longstanding occupation of land except on government land is recognized as conferring property rights. In the case of land acquisition all occupiers of land irrespective of whether they have a granted right of occupancy or not, are eligible to compensation. Granted rights of occupancy carry conditions including land development and the payment of land rent. Failure to abide with these conditions can lead to the loss of the right. 4.2.2 Village land This is defined as being the land falling under the jurisdiction and management of a registered village. As Tanzania consists of a vast countryside with only a few urban areas, most land in the country is village land. Village land is held under customary tenure and the government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. Customary tenure is akin to freehold. 4.2.3 Reserved land This is defined as land being reserved areas including environmental protection areas, such as national parks, forest reserves, wildlife reserves, and marine parks as well as areas intended and set aside for spatial planning and (future) infrastructure development. The Commissioner for Lands can convert land from one category to the other. By far the majority of land occupiers have no certificates of Land title deed in part because land has to be surveyed before it can be issued with a title deed. However, there is a lot of "de facto" recognition of property rights for the majority of land occupiers. RAP for Chinangali II Block Farm May, 2024 10 4.3 Land acquisition process for Chinangali II Block Farms The Land within the proposed Chinangali block farms falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chamwino District Council Land Officers there were no Certificates of Customary Rights of Occupancy (CCROs) within the proposed block farms. 4.4 Method of Land acquisition The Land was purchased from the community at a Market price 4.5 Lively Hood Restoration mechanism There is neither legal requirement nor regulation for restoring livelihoods or providing assistance towards the restoration of such livelihoods in Tanzania. Those who sold their land will continue to sustain their lively hood through other land they occupy within the village. The land which was purchased was not fully utilized by the owners as there were few farm plots within the proposed BBT area. RAP for Chinangali II Block Farm May, 2024 11 5.0 CUT-OFF DATE The actual number of affected PAPs and their land sizes was identified within the land to be acquired for the Chinangali II BBT farm. The cut-off date for PAPs is the date the respective PAPs receive the remittance payments of the funds according to the agreed market price and the size of the land owned. Therefore, the overall cut of date was July 2023 which was communicated to PAPs during land size determination and sales agreement signed. Any person who undertakes any development activity in the demarcated project area after the cut-off date will not be eligible for payments. It should, however be noted that the implementation of the cut-off date should also be observed by project implementer who is required to pay PAPs once the land holding size has been approved and sale agreement signed. This RAP recommends that the project implementer needs to have frequent communication with PAPs through Chinangali Village Government Officials to update PAPs on when they should expect to receive their funds. or any other changes associated with implementation of the project. RAP for Chinangali II Block Farm May, 2024 12 6.0 GRIVANCES AND DISPUTE RESOLUTION 6.1 Grievances Procedures The RAP will be made available to the public, the appeal structures at various levels, specifying the responsible parties and their response time. Before starting with the grievance sequence and where appropriate (i.e. in case of complaints of minor entity), aggrieved parties will take their complaints to the community or traditional meetings for dispute resolution. If need arises, the local NGOs will be contracted and involved to hear complaints and attempt to affect a resolution before they enter the legal and administrative appeals hierarchy. In normal circumstances, grievances will be dealt with either statutory through courts and tribunals, or administratively using government or traditional institutions. Using the courts in determining grievances related to and resettlement is not the best option as it is tedious, costly and lengthy. The simple and affordable procedures in place to lodge complaints or claims are as elaborated hereunder. Local authorities could handle the disputes and grievances in the first place. In summary those seeking redress will have to notify local government and ward offices. If this fails, disputes can be referred to district level. Resolution of disputes shall be speedy, just and fair and local NGOs that are conversant with these issues could be engaged by the project. The first stop, the Village Grievance Redress Committee (VGRC), has one week to resolve the dispute. If a given dispute is not resolved in one week it will go to the District Grievance Redress Committee (DGRC), which has two weeks to resolve the dispute. Unresolved disputes shall be referred to appropriate level of land courts established by law. If local courts are unable to resolve the disputes application can be made to the High Court of Appeal of Tanzania, this is the highest appellate judge in the system and its decision will be final. Potential grievances and disputes that arise during the course of implementation of the resettlement and compensation programme are often related to the following issues: i) Inventory mistakes made during census survey as well as inadequate valuation of properties; ii) Mistakes related to identification and disagreements on boundaries between affected iii) individual(s) and specifying their land parcels and associated development; iv) Divorces, successor and the family issues resulting into ownership dispute or dispute share between in heirs or family; v) Disputed ownership of given Assets (two or more affected individual(s) claim on the same); RAP for Chinangali II Block Farm May, 2024 13 6.2 Proposed Grievance Management and Redress Mechanism The mechanisms for grievance management and redressed mechanisms are to be "affordable and accessible," and third parties independent of the implementers should be available at the appropriate point in the process. The grievance procedure will be simple, administered in the first instance at the local level to facilitate access, flexibility and open to various proofs taking into account the need for speedy, just and fair resolution of their grievances. The process suggested for resolving individual grievances is presented below. 6.2.1 Grievance Redress Committees There are two committees which will be involved in redressing grievances arising from the PAPs in the project area; a) Village Grievance Redress Committee (VGRC) and, District Grievance Redress Committee (DGRC) known as Social Service Committee (SSC) Composition of VGRC VGRC is comprised of: i) Village Chairperson, ii) Village Executive Officer (VEO), iii) Representative from the PAPs, iv) Community Development Officer from the Ward, Representative from NGO to be identified b) District Grievance Redress Committee (DGRC) Composition of DGRC DGRC is comprised of: i) District Commissioner Chairman ii) District Land office Member, iii) District Valuer; iv) RAP Implementing Agency Member v) PAP representative/ local NGO Member vi) Representative of Regional Secretariat Member 6.2.2 Apeal Land related grievances shall be resolved using the land courts established under the Land Disputes Courts Act. No. 2 of 2002 with its regulations. That is Village Land Council; the Ward Tribunal; the District Land and Housing Tribunal; the High Court (Land Division) and The Court of Appeal of Tanzania. RAP for Chinangali II Block Farm May, 2024 14 6.2.3 Eligibility The eligible individual(s) are those who sold their land to the Ministry of Agriculture and were directly affected through Chinangali II BBT farm development and they had to have land plots within the boundaries of the farm. The PAPs were considered irrespective of their tenure status, with respect to land that they occupy or use provided they occupy or use the affected land prior to the cut-off-date. Cut-off date for eligibility to payments settlement. RAP for Chinangali II Block Farm May, 2024 15 7.0 IMPLEMENTATION SCHEDULE Implementation of RAP consists of several resettlement activities. Efficient implementation of RAP activities requires several measures to be taken prior to startup of implementation. These include setting up of relevant committees at district level, hiring of NGO or consultant etc. In principle project civil works may not start until all PAPs determined to be entitled for ressettlement are duly fully paid out. The land acquisition took place after payments were received by the PAPs prior to land take for BBT only 16 PAPs have not received their payouts due. The time frame of 3 months on the implementation schedule ensures that all PAPs will have received their funds . • Finalization and payements to the remaining 16 PAPs • RAP disclosure and circulation; • Grievance Redress Mechanisms set at Mtaa and District Levels (Grievances Redress Process) • Monitoring and evaluation. RAP for Chinangali II Block Farm May, 2024 16 8.0 MONITORING PROGRAMME RAP implementation is one of the central components of this project its monitoring is critical to solve challenges or obstacles in the areas of PAPs relocation. The monitoring and evaluation procedures will include external and internal evaluation of the compliance of the actual implementation with objectives and methods as agreed, and monitoring of specific situations. 8.1 Internal Monitoring The Project implementation unit will be responsible for internal monitoring while the Consultants may provide technical assistance in implementing RAP. At the conclusion of the RAP implementation the full information on every individual impacted by the project will provide the evaluation of status of PAPs and measuring Resettlement Plans (RAP) performance. Several indicators are used to measure these impacts, namely: a comparison of income levels before-and-after the project; changes in standards of housing and living conditions; access to various social services i.e. health care, education, water supply, road, markets etc. and improvements in level of participation in sub-project activities. Measures to verify these basic indicators would be mainly to compare these new conditions with pre-project conditions. Monitoring will ensure the following: • Verification of payments to the remaining 16 PAPs; • Information dissemination has been carried out; • Effective operation of grievances Committee; • BBT Secretariat shall be responsible for monitoring day to day RAP activities; • The Consultants shall be responsible for overall project level monitoring. RAP for Chinangali II Block Farm May, 2024 17 9.0 RAP BUDGET AND SCHEDULE Table 4: Budget for RAP Implementation S/N Resettlement Activity Activity Cost (Tsh) Source of fund/ Responsibility Timeline/ Deadlines 1. Payments to remaining PAPs 77,610,000 MoA May 2024 2 Grievance handling 1,000,000 MoA Through RAP implementation 3. Management & administration 5,000,000 MoA Through RAP implementation 4 Monitoring & evaluation 10,000,000 MoA Through RAP implementation TOTAL 103,610,000 RAP for Chinangali II Block Farm May, 2024 18 APPENDICES Appendix I: Consent Letter from DED-Chamwino and Minutes of agreements with Community who sold land for Chinangali II Block Farm RAP for Chinangali II Block Farm May, 2024 19 RAP for Chinangali II Block Farm May, 2024 20 RAP for Chinangali II Block Farm May, 2024 21 RAP for Chinangali II Block Farm May, 2024 22 RAP for Chinangali II Block Farm May, 2024 23 RAP for Chinangali II Block Farm May, 2024 24 RAP for Chinangali II Block Farm May, 2024 25 RAP for Chinangali II Block Farm May, 2024 26 Appendix II: Land Tittle Deed for Chinangali II block farm RAP for Chinangali II Block Farm May, 2024 27 RAP for Chinangali II Block Farm May, 2024 28 RAP for Chinangali II Block Farm May, 2024 29 RAP for Chinangali II Block Farm May, 2024 30 Appendix III: Sale Agreement between Chamwino District Council and Mega Beverage Limited RAP for Chinangali II Block Farm May, 2024 31 RAP for Chinangali II Block Farm May, 2024 32 RAP for Chinangali II Block Farm May, 2024 33 RAP for Chinangali II Block Farm May, 2024 34 Appendix IV: Sample Contract with PAPs on sale of Land RAP for Chinangali II Block Farm May, 2024 35 RAP for Chinangali II Block Farm May, 2024 36 RAP for Chinangali II Block Farm May, 2024 37 RAP for Chinangali II Block Farm May, 2024 38 RAP for Chinangali II Block Farm May, 2024 39 RAP for Chinangali II Block Farm May, 2024 40 RAP for Chinangali II Block Farm May, 2024 41 RAP for Chinangali II Block Farm May, 2024 42 Appendix V(a): Letter from Chamwino District Council-Submission of Land Purchases report to the Ministry of Agriculture RAP for Chinangali II Block Farm May, 2024 43 Appendix V(b): Names of PAPs who has received payments RAP for Chinangali II Block Farm May, 2024 44 RAP for Chinangali II Block Farm May, 2024 45 RAP for Chinangali II Block Farm May, 2024 46 RAP for Chinangali II Block Farm May, 2024 47 RAP for Chinangali II Block Farm May, 2024 48 Appendix V(c): Names of PAPs who have not received payments RAP for Chinangali II Block Farm May, 2024 49 Appendix VI: Report on Funds Remittances to PAP RAP for Chinangali II Block Farm May, 2024 50 RAP for Chinangali II Block Farm May, 2024 51 RAP for Chinangali II Block Farm May, 2024 52 RAP for Chinangali II Block Farm May, 2024 53 RAP for Chinangali II Block Farm May, 2024 54 RAP for Chinangali II Block Farm May, 2024 55 RAP for Chinangali II Block Farm May, 2024 56 RAP for Chinangali II Block Farm May, 2024 57 RAP for Chinangali II Block Farm May, 2024 9 | false |
# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE Government City-Mtumba P. O BOX 2182 40487 DODOMA Email: [email protected] BUILDING A BETTER TOMORROW: YOUTH INITIATIVES FOR AGRIBUSINESS (BBT-YIA) THE PROPOSED ESTABLISHMENT OF MAPOGORO BLOCK FARM No. 59569 - MBYLR LOCATED AT MAPOGORO VILLAGE, CHOKAA WARD, CHUNYA DISTRICT COUNCIL IN MBEYA REGION RESETTLEMENT ACTION PLAN CONSULTANT Eng. Lait A.Simukanga Registered Environmental Consultant, Reg. No NEMC/EIA/0032 Practicing License No. NEMC/PC/EIA/2021/0020 Kimara Street Plot No. 0095, P.O. Box 13033, DAR ES SALAAM, Email: [email protected] Mobile: +255 754 271175 Date of Submission: 1 May 2024 RAP Mapogoro BBT farm April 2024 i TABLE OF CONTENT LIST OF TABLES\ ........................................................................................................................ ii LIST OF PLATES .......................................................................................................................... ii ABBREVIATIONS ....................................................................................................................... iii 1.0 INTRODUCTION ..................................................................................................................... 1 1.1 Project Background ................................................................................................................ 1 1.2 Objective of Resettlement Action Plan .................................................................................. 1 1.3 Project Rationale .................................................................................................................... 2 1.4 Project Beneficiaries .............................................................................................................. 2 1.5 Need for Resettlement Action Plan........................................................................................ 3 1.6 Methodology for Preparation of RAP .................................................................................... 3 1.6.1 Conducting Field Visits ...................................................................................................... 3 1.6.2 Conducting Literature Review ............................................................................................ 4 2.0 PROJECT DESCRIPTION ....................................................................................................... 5 2.1 Location ................................................................................................................................. 5 2.1.1 General project location ................................................................................................ 5 2.1.2 Specific Location of the project....................................................................................... 5 2.2 Overview of the project affected area .................................................................................... 5 2.2.1 Characteristics of PAPs in Mapogoro BBT farm ............................................................ 5 2.2.2 Ethinic groups .................................................................................................................. 5 2.2.3 House conditions ............................................................................................................. 6 2.3 Potential impacts .................................................................................................................... 7 2.3.1 Loss of land rights ............................................................................................................. 7 2.3.2 Loss of Utilities ............................................................................................................... 7 3.0 CONSULTATION WITH PAPs AND COMMUNITY PARTICIPATION ............................ 8 3.1 Identification of PAPs for Consultation ................................................................................. 8 3.2 Methods of Stakeholder Participation .................................................................................... 8 3.2.1 Notification to PAPs ........................................................................................................ 9 3.2.2 Official meetings with Village leaders ............................................................................ 9 3.2.3 Meetings with District officials ....................................................................................... 9 4.0 COMPENSATION OF PAPs.................................................................................................. 10 5.0 LEGAL AND INSTITUTION PRAMEWORK FOR LAND ACQUISITION IN TANZANIA .................................................................................................................................. 11 5.1 Land Tenure and Ownership in Tanzania ............................................................................ 11 5.2 Land categories in Tanzania ................................................................................................ 11 5.2.1 General land ................................................................................................................... 11 RAP Mapogoro BBT farm April 2024 ii 5.2.2 Village land ................................................................................................................... 11 5.2.3 Reserved land ................................................................................................................ 11 5.3 Land acquisition process for Mapogoro Block Farms ......................................................... 12 5.4 Method of Compensation ..................................................................................................... 12 6.0 GRIVANCES AND DISPUTE RESOLUTION ................................................................. 14 6.1 Grievances Procedures ......................................................................................................... 14 6.2 Proposed Grievance Management and Redress Mechanism ............................................ 15 6.2.1 Grievance Redress Committees ..................................................................................... 15 6.2.2 Apeal .............................................................................................................................. 15 6.2.3 Eligibility ....................................................................................................................... 15 7.0 LIVELY HOOD RESTORATION .................................................................................... 16 8.0 CUT-OFF DATE .................................................................................................................. 17 9.0 IMPLEMENTATION SCHEDULE ....................................................................................... 18 10.0 MONITORING PROGRAMME .......................................................................................... 19 11.0 RAP BUDGET AND SCHEDULE ...................................................................................... 20 APPENDICES ............................................................................................................................... 21 Appendix I: Map indicating Location of PAPs within the Mapogoro BBT farm ......................... 21 Appendix II: List of PAPS with thir signatures who agreed to be re-settled at Mapogoro BBT farm ............................................................................................................................................... 22 Appendix III: Map indicating area for re-settlement of PAPs ...................................................... 26 Appendix IV: Report on PAP Households Inventory at Mapogoro BBT Farm ........................... 27 Appendix V: Names of PAPs, Number of Tenants, Year encroached the land and land method of Land acquisition (Typed) .............................................................................................................. 29 Appendix VI: Translations of Appendix IV .................................................................................. 31 Appendix VII: Proposal for Land Range Clusters for PAPs ......................................................... 33 Appendix VII: Map indicating Areas where PAPs will be re-located .......................................... 37 LIST OF TABLES\ Table 1: Identification of individula PAPs ...................................................................................... 6 Table 2: Areas identified and allocated for re-settlement of agro-pastoralists .................................... 10 Table 3: Budget for RAP Implementation .................................................................................... 20 LIST OF PLATES Plate 1: Typical Sukuma and Mang’ati settlement at the middle of Mapogoro BBT farm ............ 6 RAP Mapogoro BBT farm April 2024 iii ABBREVIATIONS AfDB African Development Bank BBT-YIA Building a Better Tomorrow: Youth Initiatives for Agribusiness Program CDOs Community Development Organizations CSA Climate Smart Agriculture DPs Development Partners EIA Environmental Impact Assessment GDP Gross Domestic Product GOT Government of Tanzania LGA Local Government Authority MLHHSD Ministry of Land Housing and Human Settlement Development MLHHSD Ministry of Land, Housing and Human Settlements Development MoA Ministry of Agriculture MoFP Ministry of Finance and Planning NEMC National Environment Management Council NGO Non-Governmental Organization OP/BP Operation Policy/Bank Policy PAP Project Affected Person NGOs Non-Governmental Organizations PO-RALG President’s Office - Regional Administration and Local Governments RAP Resettlement Action Plan ( RSs Regional Secretariats URT United Republic of Tanzania VEO Village Executive Officer RAP Mapogoro BBT farm April 2024 1 1.0 INTRODUCTION 1.1 Project Background The Ministry of Agriculture is in the process of developing Mapogoro Block Farms in Chunya district Mbeya Region. As part of the project preparations the Environmental and Social Impact Assessment was carried out in 2023 for the block farm. The EIA documents indicated that the projects will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. The important undertakings, land acquisition, farm clearing infrastructure development such as borehole drilling and water storage reservoir will ensure sustainable development of the farm in terms of water supply and crop production. Moreover, smallholder farmers in the surrounding villages will benefit from modern farming technologies and operations. The block farm is intended to support for youth farmers aged between 18 and 40 years and they will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. Furthermore, the project will be advantageous for the private sector investors’ who have the insights knowledge of farm's operations. In addition, the government will enhance its tax base and benefit from tax collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Block Farms will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.2 Objective of Resettlement Action Plan Considering the economic importance required for development of Mapogoro BBT Farm and few settlement that are located within the proposed core project area will have to be moved out to pave the way for the development of the BBT farm. The main objective of this RAP is to develop a plan which would entail agreed plan for the resettlement, issues resulting from implementation of the proposed project. Specific objectives of the RAP include: i) Identification of Project Affected Persons (PAPs); ii) Identification of land parcels to be acquired for development of project infrastructure; iii) Collection of qualitative and quantitative baseline socio-economic data of PAPs; iv) Establishment of entitlements to PAPs; v) Collection of preference for resettlement; vi) Collection of comments and perceptions of the PAPs with regard to the project; vii) Involve PAPs and other stakeholders in developing a plan for physical relocation viii) Provide information that will be used to implement the resettlement plan; and ix) Outline institutional arrangements for the implementation of the RAP; and x) Development of a Resettlement Action Plan (RAP) RAP Mapogoro BBT farm April 2024 2 1.3 Project Rationale The Government of Tanzania is making concerted efforts to boost the country's economy by encouraging large-scale cultivation in the agricultural sector, which serves as its backbone. To facilitate this, the introduction of block farming and the development of value chain infrastructure are linked to private sector initiatives aimed at investing in agricultural and rural development. The Mapogoro Block Farm represents a model for production and productivity enhancement, emphasizing collaborative efforts among large farmers to benefit the youth. Encouraging potential investors to participate in new large-scale commercial block farms aligns with the Ministry of Agriculture's mission which is to promote private sector involvement in commercial agricultural development, which is rapidly gaining momentum. The low response from private investors and youth engagement in agriculture can be attributed to the perceived risks associated with the business. Such risks include capital investment, assurance of water availability, land availability, and the availability of marketing infrastructure. Recognizing the critical importance of the private sector involvement in agriculture for ensuring food security, contributing significantly to national income, and generating employment opportunities, the Ministry of Agriculture has taken decisive action to leverage the participation of the youth and the private sector by providing incentives for investing in large-scale commercial farming blocks. The Mapogoro Block Farm Project will have several significant positive impacts, outweighing the negative impacts that will be associated with the project. Important undertakings, such as borehole drilling and water storage reservoir development, will ensure a reliable supply of water for crop production. Moreover, smallholder farmers in Mapogoro will benefit from modern farming technologies and operations. Youth farmers will have access to enhanced agricultural services, including the supply of inputs, farmers' training, the formation and strengthening of organizations and networks, agricultural produce processing, and the provision of loans and microfinance services. These efforts collectively contribute to the sustainable growth and development of the agricultural sector and the prosperity of Tanzanian youth. 1.4 Project Beneficiaries The main beneficiaries of Mapogoro block farm are the youth and women aged between 18 to 40 years old. About 1,000 to 4,000 youths (1400-2800 Male and 600-1200 Female) will be engaged at Mapogoro BBT Farm through direct and indirect employment. Various service providers from both the public and the private sectors will benefit from the project through availability of the market for their services. The private sector beneficiaries will include processors, input suppliers, traders, financial institutions, and communities in neighboring villages where the project will be implemented. These entities will experience positive effects such as improved incomes from the project's activities and outcomes. Furthermore, the project will be advantageous for the public sector beneficiaries, particularly research and academic institutions, as they can gain valuable insights and knowledge from the farm's operations. In addition, the government will enhance its tax base and benefit from tax RAP Mapogoro BBT farm April 2024 3 collection on the sale of the products produced from the farm, contributing to revenue generation and supporting public services and infrastructure development. Overall, the Mapogoro Block Farm will serve as a significant catalyst for empowering the youth in the region, while also fostering growth and prosperity for various stakeholders in both the private and public sectors. 1.5 Need for Resettlement Action Plan At Mapogoro block farm in Chunya district the land is open and dominated by Miombo wood land under the village government council. Since the land was planned for Agriculture, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture and Chunya District Council as occupies of the Land in common and equal shares for a term of ninety nine years (99) from 6th March 2023. The Land is known as Plot No. 1573 situated at Mapogoro Village in Chunya District. The Land Title deed granted is No. 59568 MBYLR containing an area of 11,007 Hectares. According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for farm purposes under user group “R” Use class “C”. Therefore, the proposed Mapogoro block farms is located in an area designated for agricultural activities. Within the proposed Mapogoro block farm there are few Agro-Pastoralist -about 51 households invaded the land by clearing and established settlement known as “bomas”. The AfDB mission which was in the Country from 3rd -12th April 2024 indicated the need to prepare Resettlement Action Plan (RAP) for Mapogoro block farm which would entail agreed plan for the resettlement for Project Affected People (PAPs). The RAP will provide a road map for the manner in which displacement and resettlement issues were resolved. 1.6 Methodology for Preparation of RAP The Resettlement Action Plan (RAP) covers relocation and replacement (in kind,) of the agro- pastoralist who will be affected by the project implementation. The methodology involved in preparation of this RAP, is based on data obtained from the study, census, observation and consultation. The data from the project area were collected by the Ministry of Agriculture, Mbeya Regional Secretariat and Chunya District Council (Land Officer and Agricultural Officer) for preparation of RAP. The preparation of RAP involved various activities. The philosophical underpinning of the plan preparation is the use of a participatory approach of stakeholders including affected communities and PAPs. Among others, the methods and activities employed in the process of developing the RAP included: 1.6.1 Conducting Field Visits The field visit to project area was done from 8-17 April 2024 and RAP was finalized towards the end of April 2024. The field visits were essential to fully visualize the project site capture RAP Mapogoro BBT farm April 2024 4 biophysical environment and the socio-economic conditions in the project area. In the field, among others, the project informations were collected from various sources including Mbeya Regional Secretariat and Chunya District Executive Director’s Officer. The field visits were conducted to identify the people to be affected by the project. During the field visits, the following tasks were performed: Observation of social and physical setting of the PAPs; i) Inventory and confirmation of number of PAPs in the project area (Name of head of household, number of residents); ii) Status of land ownership; iii) Structures within the proposed block farm iv) Held interviews and discussions with officials from the project area and local government including Village Government officials; v) Held interviews with the affected people and other community members in the project area; vi) Observed people's activities and learn their perception on the proposed project; and vii) Pick Coordinates of the settlements 1.6.2 Conducting Literature Review The filed visits were complemented by reviewing the existing literatures related to the resettlement. The literature review involved the identification of the applicable legal and administrative frameworks and policies of the United Republic of Tanzania, AfDB and the Environmental and Social Impact Assessment Report for the Mapogoro farm 2024. RAP Mapogoro BBT farm April 2024 5 2.0 PROJECT DESCRIPTION 2.1 Location 2.1.1 General project location The project is loacted in Chunya District council which is one of the seven (7) district councils of Mbeya region of Tanzania. Other councils are Mbarali, Rungwe, Kyela, Mbeya Rural, Busokelo and Mbeya City. It is situated in the North-Western part of Mbeya Regional Headquarter and it lies between latitudes 7° and 9° South of the Equator and 32° and 34° Longitudes East of Greenwich Meridians. The total area of the district covers 13,149 square kilometers. The district is bordered by Singida and Tabora regions to the North; Iringa region and Mbarali district to the East; Songwe and Mbeya districts to the South; Rukwa region and lake Rukwa to the West. Administratively, the district council is subdivided into 2 divisions namely Kiwanja and Kipembawe, 20 wards, 43 Villages, and 233 hamlets. This organizational structure ensures effective governance and service delivery to various communities within the district. 2.1.2 Specific Location of the project The proposed Mapogoro block farm is situated at Wafugaji hamlet within Mapogoro Village, Chokaa ward, Chunya District in Mbeya Region. The site is accessible through Chunya - Tabora highway, being located approximately 13 kilometers from Chunya bus stand and 19 kilometers from Mapogoro Village center to Mapogoro BBT farm. 2.2 Overview of the project affected area 2.2.1 Characteristics of PAPs in Mapogoro BBT farm Thorough investigation was done in the project are by picking co-oridnates of each PAPs settelement in the project area. A total number of 51 Households were identified and recording on a Map (Appendix I.). These PAPs invaded/encroched the area at different time from 1998 to 2021 (Attachement in Appendix V). All PAPs identified were pastrolalist with temporaly shelters as indicated in the photographs below. Their main activities is grazing and growing subsistance crops such as sweet potaotes, sughum and maize in small plots. 2.2.2 Ethinic groups Keeping large number of livestock is not a native tribes’ practice in the area. It is a practice of the new tribes who come with large herds from other places of the country and settled in the area mainly the Mang’ati, Mbulu, and Sukuma in search for grazing land and water. They keep different types of livestock including cattle, goats, donkeys and sheep which are largely kept on the peripheral of the Village agricultural lands to avoid conflict between farmers and pastoralists and ensure sustainable grazing practices. Indeed, the Village has land use planning being utilized firmly. Other animals kept in small numbers include pigs and domesticated birds - chicken and ducks kept for meat or eggs or both. The Sukuma are agro-pastoralists i.e. they concurrently grow crops for food production and livestock for income generation and sustenance while the Mang’ati and Mbulu ethnic groups are RAP Mapogoro BBT farm April 2024 6 pastoralists majorly. Livestock keeping is mainly carried out through freely or continuous grazing practices, where the animals are allowed to move from one area to another in search of pasture and water. During wet seasons, livestock graze on fallow fields amongst the cultivated ones while on dry seasons when natural grasses become scarce, animals feed on any remaining crop residues in the harvested farms or moved to Usangu plain and Lake Rukwa basin to meet their dietary needs. This is a coping livelihood strategy to livestock keepers for better management of livestock during times of limited resources. 2.2.3 House conditions There are no permanent settlement in the project area. The habitations are temporaly made of timber and thatched with grass. There are no toilet facilites as the agro-pastoralist take the advantage of bushes. The settelement is sparcely located ranging from 500m to 1km apart. Plate 1: Typical Sukuma and Mang’ati settlement at the middle of Mapogoro BBT farm Table 1: Identification of individual PAPs S/N Property Category of Impact Number of PAPs 1 Land Encroached/Invaded land 2 Residential Structure Temporary Houses 51 3 Business owners 0 4 Shops or business buildings 0 5 Religious buildings Mosques 0 Churches 0 6 Impacts on trees/crops Individual owners RAP Mapogoro BBT farm April 2024 7 2.3 Potential impacts Social dislocation and displacement will occur due to land needed for development of Mapogoro BBT farm. The agro-pastoralist livelihoods will be affected in one way or another. The houses to be affected in the project area, most of them are temporary built with locally available materials such as grass, poles and timber. No burnt bricks, blocks or and corrugated iron sheets. The affected houses/structures are used as shelters by the pastoralist can be easily erected once relocated. 2.3.1 Loss of land rights For the project implementation, 51 households/ PAPs in the proposed BBT farm will be affected by the project implementation. Preference shall be given to land-based resettlement strategies for displaced persons whose livelihoods are land-based. These strategies will include resettlement on public land, acquired for resettlement at Masiano hamlet for residence and Shoga and Mapogoro grazing cluster. Whenever replacement land is offered, the PAPs will be provided with land which has a combination of productivity potential, pasture, water and other factors that are at least equivalent to the advantages of the land acquired for BBT farm. Adequate land for compensation was demonstrated and documented (Appendix III), the PAPs were satisfied with the proposed compensation arrangements. 2.3.2 Loss of Utilities There are no utilities such as water supply pipes, electricity reticulation poles, telephone cables and fibers in the project area. The PAPs were using natural water course to get water and dug shallow wells on dry water ways. RAP Mapogoro BBT farm April 2024 8 3.0 CONSULTATION WITH PAPs AND COMMUNITY PARTICIPATION Preparation of Resettlement Action Plan requires regular consultation with PAPs. PAPs in this case are defined as stakeholders including any individual or group affected by the project negatively including the host community. PAPs were identified through survey and demarcation of BBT farm required to be cleared-off human activities during farm preparation these were further confirmed through consultations with the village administrations who keep registers of all village members. These PAPs were notified and were consulted on site one by one and signed an agreement to be re-settled to three identified areas known as Shoga and Mapogoro Mazimbo, Mafyeko and Butimanyanga, Supa and Kambi Katoto (See Table 2 below The objectives of PAP participation and consultation were: to i) Ensure transparency in all activities related to the resettlement and its potential impacts; ii) Share fully the information about the proposed project, its components and activities; iii) Obtain information about the needs and priorities of the various stakeholders, as well as information about their reactions; iv) Minimize conflicts and delays in implementation in relation to resettlement; v) Involve PAP at large together with their responsible institutions and organizations in the project design and planning; vi) Information dissemination to the PAPs about the project and resettlement; and vii) Understanding perceptions of PAPs towards the project 3.1 Identification of PAPs for Consultation The site visits were carried out in December 2023 where preliminary identification of PAPs falling within the demarcated farm boundaries were identified. Adequate information on the site issues related to the Resettlement Action Plan were collected, identification of spatial boundaries and identification of all stakeholders who will be affected by the project were done in April 2024. The following stakeholders were identified and consulted: i) Local governments; ii) Chunya District Council; iii) Chokaa Wards; and iv) Mapogoro Village government Officials 3.2 Methods of Stakeholder Participation PAPs interviews and consultations were the main methods followed during the process of this Resettlement Action Plan. The team involved the key identified stakeholders in order to generate issues of concern in relation to project implementation. In respect of the intended project activities, the PAPs that were consulted raised one major concern on availability of alternative land for their livestock. The concerns were addressed adequately by authorities in charge and local leadership who indicated that a Land-Use plan had been developed to guide proper landuse and minimize conflicts while maximizing benefits. Proposed grazing/ranching zones had been identified in several areas that the PAPs will be relocated. RAP Mapogoro BBT farm April 2024 9 3.2.1 Notification to PAPs PAPs were notified prior meeting with them. Notifications were through use of mobile phone communication and physical visits. 3.2.2 Official meetings with Village leaders Village officials including Chairperson, Village Executive Officer (VEO) and committee members were invited and participated effectively. 3.2.3 Meetings with District officials The Chunya District Council officials were notified and consulted. Open discussions were applied during meeting with them. RAP Mapogoro BBT farm April 2024 10 4.0 COMPENSATION OF PAPs Land-for-land replacement or compensation was the PAP’s preference. Land-for-land replacement shall be of maximum plot of acceptable size under the relevant law(s) or a plot of equivalent size, whichever is larger, in the nearby allocated land for agro-pastoralists. Resettlement area with adequate physical infrastructure systems for livestock keeping such as cattle troughs and cattle dips. Table 2: Areas identified and allocated for re-settlement of agro-pastoralists S/N Name of allocated grazing land Size (Ha) 1 Shoga and Mapogoro 23,563.24 2 Mazimbo,Mafyeko and Butimanyanga 49.626.36 3 Supa and Kambi Katoto 37.626.36 RAP Mapogoro BBT farm April 2024 11 5.0 LEGAL AND INSTITUTION FRAMEWORK FOR LAND ACQUISITION IN TANZANIA 5.1 Land Tenure and Ownership in Tanzania Land tenure and ownership in Tanzania is governed by statutes such as the 1977 Constitution, National Land Act No. 4 of 1999, Village Land Act No. 5 of 1999, Land Acquisition Act 1967, and Land Ordinance, 1923 Cap. 113. Land in Tanzania is owned by the state (vested in the President as a trustee). For the purpose of management of land under the land Act No. 4 of 1999 and all other laws applicable to land, public land in Tanzania is either categorised as:i) General Land, ii) Village Land and iii) Reserved Land. Besides, there is a category of hazard land. 5.2 Land categories in Tanzania 5.2.1 General land The general Land in Tanzania is described as consisting of all land, which is neither village land nor reserved land. All urban land falls under this category, except land, which is covered by laws constituting reserved land, or that which is considered hazard land. General land is governed by the Land Act and, hence, is under the control and jurisdiction of the Commissioner for Lands. This ministerial key person has delegated much of the powers to local government land officers. Property rights can be created over general land in terms of a granted Rights of Occupancy for a period of 33, 66 or 99 years confirmed by a Certificate of Title. Longstanding occupation of land except on government land is recognized as conferring property rights. In the case of land acquisition all occupiers of land irrespective of whether they have a granted right of occupancy or not, are eligible to compensation. Granted rights of occupancy carry conditions including land development and the payment of land rent. Failure to abide with these conditions can lead to the loss of the right. 5.2.2 Village land This is defined as being the land falling under the jurisdiction and management of a registered village. As Tanzania consists of a vast countryside with only a few urban areas, most land in the country is village land. Village land is held under customary tenure and the government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. Customary tenure is akin to freehold. 5.2.3 Reserved land This is defined as land being reserved areas including environmental protection areas, such as national parks, forest reserves, wildlife reserves, and marine parks as well as areas intended and set aside for spatial planning and (future) infrastructure development The Commissioner for Lands can convert land from one category to the other. By far the majority of land occupiers have no certificates of Land title deed in part because land has to be surveyed before it can be issued with a title deed. However, there is a lot of "de facto" recognition of property rights for the majority of land occupiers RAP Mapogoro BBT farm April 2024 12 5.3 Land acquisition process for Mapogoro Block Farms The Land within the proposed Mapogoro block farms falls under the Village Land which is defined as being the land falling under the jurisdiction and management of the Village Council. Under the Land Act and Village Land Act of 1999 the Village government can issue customary certificates of tenure to individuals or communities where the village is surveyed and has a Certificate of Village Land. According to Chunya District Council Land Officers there were no Certificates of Customary Rights of Occupancy (CCROs) within the proposed block farms. The Ministry of Agriculture requested the President’s Office through the Regional Administration and Local Government (PO-RALG) to identify areas suitable for establishment of a large farm to be used for Building Better Tomorrow Block Farms for the youth. The PO- RALG further liased with Chunya District Council to identify suitable land for BBT Block Farms within the district. Chunya District Council in collaboration with Mapogoro Village Government in consultation with the Ministry of Lands, Housing and Human Settlements earmarked and allocated arable land for Mapogoro Block Farm. After fulfilling these requirements, the Ministry of Lands, Housing and Human Settlement Development entitled to the right of occupancy the Ministry of Agriculture and Chunya District Council as occupies of the Land in common and equal shares for a term of ninety nine years (99) from 6th March 2023. The Land is known as Plot No. 1573 situated at Mapogoro Village in Chunya District. The Land Title deed granted is No. 59568 MBYLR containing an area of 11,007 Hectares (Appendix IV Certificate of Occupancy). According to the Urban Planning (Use Groups and Use Classes) Regulations of 2018, it was stated that the land shall be used for farm purposes under user group “R” Use class “c”. Therefore, the proposed Mapogoro block farms is located in an area designated for agricultural production. 5.4 Method of Compensation Compensation for PAPs depending on agro-pastrol activities will be land-based compensations. Land-based strategies include the provision of replacement land, ensuring greater security of tenure, and/or upgrading livelihoods of people to be resettled without legal land titles. The replacement land will address the need of PAPs who are mainly livestock keepers. Therefore access to grazing land and subsistance farming will contnue in the newly established resettlement land. Also, the traditional rights of the Sukuma, Mangati and Masai will be maintained. The replacement lands, for PAPs, is within the vicinity of the affected lands and is of comparable productive capacity and potential as the previously occupied land. The residential and farming land is at Masiano hamlet and livestock will be grazed at Shoga and Mapogoro ranch. The site for resettlement was identified so that it minimizes the social disruption of those affected; the lands have access to social and economic services and facilities that were unavailable in the RAP Mapogoro BBT farm April 2024 13 lands affected. The PAPs were involved in the process of developing and expected too in the implementing of the resettlement plan. RAP Mapogoro BBT farm April 2024 14 6.0 GRIVANCES AND DISPUTE RESOLUTION 6.1 Grievances Procedures The RAP will be made available to the public, the appeal structures at various levels, specifying the responsible parties and their response time. Before starting with the grievance sequence and where appropriate (i.e. in case of complaints of minor entity), aggrieved parties will take their complaints to the community or traditional meetings for dispute resolution. If need arises, the local NGOs will be contracted and involved to hear complaints and attempt to affect a resolution before they enter the legal and administrative appeals hierarchy. In normal circumstances, grievances will be dealt with either statutory through courts and tribunals, or administratively using government or traditional institutions. Using the courts in determining grievances related to and resettlement is not the best option as it is tedious, costly and lengthy. The simple and affordable procedures in place to lodge complaints or claims are as elaborated hereunder. Local authorities could handle the disputes and grievances in the first place. In summary those seeking redress will have to notify local government and ward offices. If this fails, disputes can be referred to district level. Resolution of disputes shall be speedy, just and fair and local NGOs that are conversant with these issues could be engaged by the project. The first stop, the Village Grievance Redress Committee (VGRC), has one week to resolve the dispute. If a given dispute is not resolved in one week it will go to the District Grievance Redress Committee (DGRC), which has two weeks to resolve the dispute. Unresolved disputes shall be referred to appropriate level of land courts established by law. If local courts are unable to resolve the disputes application can be made to the High Court of Appeal of Tanzania, this is the highest appellate judge in the system and its decision will be final. Potential grievances and disputes that arise during the course of implementation of the resettlement and compensation programme are often related to the following issues: i) Inventory mistakes made during census survey as well as inadequate valuation of properties; ii) Mistakes related to identification and disagreements on boundaries between affected iii) individual(s) and specifying their land parcels and associated development; iv) Divorces, successor and the family issues resulting into ownership dispute or dispute share between in heirs or family; v) Disputed ownership of given Assets (two or more affected individual(s) claim on the same); RAP Mapogoro BBT farm April 2024 15 6.2 Proposed Grievance Management and Redress Mechanism The mechanisms for grievance management and redressed mechanisms are to be "affordable and accessible," and third parties independent of the implementers should be available at the appropriate point in the process. The grievance procedure will be simple, administered in the first instance at the local level to facilitate access, flexibility and open to various proofs taking into account the need for speedy, just and fair resolution of their grievances. The process suggested for resolving individual grievances is presented below. 6.2.1 Grievance Redress Committees There are two committees which will be involved in redressing grievances arising from the PAPs in the project area; a) Village Grievance Redress Committee (VGRC) and, District Grievance Redress Committee (DGRC) known as Social Service Committee (SSC) Composition of VGRC VGRC is comprised of: i) Village Chairperson, ii) Village Executive Officer (VEO), iii) Representative from the PAPs, iv) Community Development Officer from the Ward, Representative from NGO to be identified b) District Grievance Redress Committee (DGRC) Composition of DGRC DGRC is comprised of: i) District Commissioner Chairman ii) District Land office Member, iii) District Valuer; iv) RAP Implementing Agency Member v) PAP representative/ local NGO Member vi) Representative of Regional Secretariat Member 6.2.2 Appeal Land related grievances shall be resolved using the land courts established under the Land Disputes Courts Act. No. 2 of 2002 with its regulations. That is Village Land Council; the Ward Tribunal; the District Land and Housing Tribunal; the High Court (Land Division) and The Court of Appeal of Tanzania. 6.2.3 Eligibility The eligible individual(s) are those who will be directly affected through Mapogoro BBT farm development and are staying within the boundaries of the farm: RAP Mapogoro BBT farm April 2024 16 The PAPs were considered irrespective of their tenure status, with respect to land that they occupy or use provided they occupy or use the affected land prior to the cut-off-date. Cut-off date for eligibility to resettlement entitlements for the project was when the survey of affected properties was completed (i.e. 16" April 2024). 7.0 LIVELIHOOD RESTORATION There is neither legal requirement nor regulation for restoring livelihoods or aiding towards the restoration of such livelihoods in Tanzania, the Livelihood Restoration Program (LRP) for those affected people. As such, the PAPs requested land to land compensation as their livelihood depends more on livestock keeping. Therefore, suitable land for livestock grazing was their preference. The government has allocated settlement and farming land for the PAPs at Masiano hamlet and range land for their livestock at Shoga and Mapogoro ranch. (Appendix III). RAP Mapogoro BBT farm April 2024 17 8.0 CUT-OFF DATE The actual identification of affected PAPs has been carried within the land to be acquired for the Mapogoro BBT farm. The cut-off date was set as 16 April, 2024 and communicated with each PAP during property identification and meeting. Any person who undertakes any development activity in the demarcated project area after the cut-off date will not be eligible for land to land compensation. It should, however be noted that the implementation of the cut-off date should also be observed by project implementer who is required to locate land for PAPs Six (6) months after the RAP has been approved. This RAP recommends that the project implementer needs to have frequent communication with PAPs through Mapogoro Village Government Officials to update PAPs on when they should expect to move or any other changes associated with implementation of the project. RAP Mapogoro BBT farm April 2024 18 9.0 IMPLEMENTATION SCHEDULE Implementation of RAP consists of several resettlement activities. Efficient implementation of RAP activities requires several measures to be taken prior to startup of implementation. These include setting up of relevant committees at district level, hiring of NGO or consultant etc. In principle project civil works may not start until all PAPs determined to be entitled for ressettlement are resettled. The time frame of 12 months on the implementation schedule ensures that no PAP or affected household will be displaced due to civil works activity before ressetlemnt is done and is undertaken when all necessary approvals have been obtained. • Finalization and Approval of RAP; • RAP disclosure and circulation; • Grievance Redress Mechanisms set at Mtaa and District Levels (Grievances Redress • Process) • Provision of notice period for relocation of property (public meetings) • Monitoring and evaluation. RAP Mapogoro BBT farm April 2024 19 10.0 MONITORING PROGRAMME RAP implementation is one of the central components of this project its monitoring is critical to solve challenges or obstacles in the areas of PAPs relocation. The monitoring and evaluation procedures will include external and internal evaluation of the compliance of the actual implementation with objectives and methods as agreed, and monitoring of specific situations. 10.1 Internal Monitoring The Project implementation unit will be responsible for internal monitoring while the Consultants may provide technical assistance in implementing RAP. At the conclusion of the RAP implementation the full information on every individual impacted by the project will provide the evaluation of status of PAPs and measuring Resettlement Plans (RAP) performance. Several indicators are used to measure these impacts, namely: a comparison of income levels before-and-after the project; changes in standards of housing and living conditions; access to various social services i.e. health care, education, water supply, road, markets etc. and improvements in level of participation in sub-project activities. Measures to verify these basic indicators would be mainly to compare these new conditions with pre-project conditions. Monitoring will ensure the following: • Verification of land set aside for PAPs been carried out as planned; • Information dissemination has been carried out; • Status of new land preparation for PAPs • Relocation of PAPs if applicable; • Effective operation of grievances Committee; • Funds for preparation of grazing land are available in timely manner, are sufficient for the purpose and spent according to Plan; • The Consultants shall submit reports on monthly basis documenting the RAP progress implementation; • Project Unit shall be responsible for monitoring day to day resettlement activities; • Performance data sheet shall be developed to monitor at the field level; and • The Consultants shall be responsible for overall project level monitoring. RAP Mapogoro BBT farm April 2024 20 11.0 RAP BUDGET AND SCHEDULE Table 3: Budget for RAP Implementation S/N Resettlement Activity Activity Cost (Tsh) Source of fund/ Responsibili t Timeline/ Deadlines 1. Grievance handling 15,000,000 MoA Through RAP implementation 2. Management & administration 20,000,000 MoA Through RAP implementation 3 Monitoring & evaluation 100,000,000 MoA Through RAP implementation TOTAL 135,000,000 RAP Mapogoro BBT farm April 2024 21 APPENDICES Appendix I: Map indicating Location of PAPs within the Mapogoro BBT farm RAP Mapogoro BBT farm April 2024 22 Appendix II: List of PAPS with thir signatures who agreed to be re-settled at Mapogoro BBT farm RAP Mapogoro BBT farm April 2024 23 RAP Mapogoro BBT farm April 2024 24 RAP Mapogoro BBT farm April 2024 25 RAP Mapogoro BBT farm April 2024 26 Appendix III: Map indicating area for re-settlement of PAPs RAP Mapogoro BBT farm April 2024 27 Appendix IV: Report on PAP Households Inventory at Mapogoro BBT Farm RAP Mapogoro BBT farm April 2024 28 RAP Mapogoro BBT farm April 2024 29 Appendix V: Names of PAPs, Number of Tenants, Year encroached the land and land method of Land acquisition (Typed) RAP Mapogoro BBT farm April 2024 30 RAP Mapogoro BBT farm April 2024 31 Appendix VI: Translations of Appendix IV CHUNYA DISTRICT COUNCIL HOUSEHOLD VERIFICATION REPORT AT MAPOGORO FARM AREA 1. INTRODUCTION In 2021, Chunya District Council surveyed farms for investment in the village areas of Mapogoro, Lualaje, and Nkungungu, including issuing land title deed. These farm areas have been found to be invaded by people who are farming and establishing settlements while continuing with other various human activities. In implementing the development of these farms, Chunya District Council Executive Director formed a team to inspect the households within the Mapogoro farm area to verify the number of households and residents living there, and to get their signatures from those who agreed to leave the farm area to make way for the BBT project. The team officially started working on April 6, 2024 for the verification of households within the BBT Mapogoro farm. 2. TEAM STRUCTURE The director of the Chunya District Council formed a five-person team with the following structure: i) Lameck Matukulu - Agricultural Officer - Chairman ii) Abdallah Msenga - Land Surveyor - Secretary iii) Shaban Kawambwa - Mapping Expert - Member iv) Zebedayo Geofrey - Land Surveyor - Member v) Ambokile Samson - Land Surveyor - Member 3. TEAM RESPONSIBILITIES To monitor the number of households within the BBT Mapogoro area, the team used the following terms of reference: i) Name of the head of the household and the number of household members in each home. ii) The land ownership status. iii) Inspection of citizen identification within the area, including NIDA identification or voter ID iv) Coordinates of each household to determine its geographical location within the farm area 4. IMPLEMENTATION OF THE TERMS OF REFERENCE The team officially started working on April 6, 2024 adhering to the terms of reference. RAP Mapogoro BBT farm April 2024 32 4.1 IDENTIFYING THE NUMBER OF HOUSEHOLDS WITHIN THE FARM The team successfully identified a total of 51 households within the BBT Mapogoro area who had invaded at different times, engaging in activities such as livestock keeping and farming for food. A list of the heads of these households is attached to this report. STATUS OF LAND OWNERSHIP BY RESIDENTS WITHIN THE FARM AREA i) The team discovered that some invaders had begun illegally selling the land, whereby seven households sold land areas to each other and started livestock keeping and crop cultivation. ii) The team received information about only two people who exchanged land to establish household farms. iii) The team found that the heads of 38 households, representing 75%, entered the area without the consent of the village government or any other person. iv) The team also found that the households that entered through buying or receiving land did not have any documents to verify this. HOUSEHOLDS DISTRIBUTION WITHIN THE BBT MAPOGORO AREA The community living in these areas consists of the Sukuma and Mang'ati community, whose main activities within the area are agriculture and livestock keeping. Their households are distributed ranging from one household to another at distances of 500 meters to 1 kilometer. CONCLUSION Considering that these residents are not legally in the specified area and since the village has a plan for better land use which we are continuing to implement, we have reached an agreement, and they have consented to move to the allocated areas for living and farming in the Masiano hamlet, and their livestock will be moved to the Shoga and Mapogoro grazing areas where all services will be provided. Along with this report, I have attached a sketch map of the residential and agricultural areas and a list of the heads of all 51 households that will be relocated to these areas for essential life activities. I submit. Cuthbert G. Mwinuka For District’s Executive Director RAP Mapogoro BBT farm April 2024 33 Appendix VII: Proposal for Land Range Clusters for PAPs RAP Mapogoro BBT farm April 2024 34 RAP Mapogoro BBT farm April 2024 35 RAP Mapogoro BBT farm April 2024 36 RAP Mapogoro BBT farm April 2024 37 Appendix VII: Map indicating Areas where PAPs will be re-located | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA PRIME MINISTER’S OFFICE Southern Agricultural Growth Corridor of Tanzania (SAGCOT) Investment Project INTEGRATED PEST MANAGEMENT PLAN (IPMP) MARCH 2014 Page i of 110 TABLE OF CONTENTS TABLE OF CONTENTS ........................................................................................................................ i LIST OF TABLES ................................................................................................................................. iii ABBREVIATIONS AND ACRONYMS.............................................................................................. iv EXECUTIVE SUMMARY ................................................................................................................... vi 1. BACKGROUND ............................................................................................................................. 1 1.1. INTRODUCTION ..................................................................................................................... 1 1.2. METHODOLOGY .................................................................................................................... 2 2. DESCRIPTION OF PROPOSED PROJECT .............................................................................. 4 2.1. INTRODUCTION ..................................................................................................................... 4 2.2. PROJECT COMPONENTS ...................................................................................................... 4 2.3. PROJECT IMPLEMENTATION ARRANGEMENTS ............................................................... 5 2.3.1 The Catalytic Fund ......................................................................................................... 5 2.3.2 The SAGCOT Centre ..................................................................................................... 5 2.3.3 Tanzania Investment Centre ......................................................................................... 6 3. THE GENESIS OF AGRICULTURAL PEST MANAGEMENT PRACTICES ..................... 8 3.1. INTRODUCTION ..................................................................................................................... 8 3.2. THE MEANING AND IMPORTANCE OF IPM ....................................................................... 8 3.3. FUNDAMENTALS OF IPM ..................................................................................................... 9 3.4. KEY CHARACTERISTICS OF AN IPM APPROACH .............................................................. 9 3.5. THE PRINCIPLES OF AN IPM ............................................................................................. 10 4. EXISTING AND ANTICIPATED PEST PROBLEMS ............................................................ 11 4.1 FOOD CROPS ........................................................................................................................ 11 4.2 CASH CROPS ......................................................................................................................... 28 4.3 HORTICULTURAL CROPS ................................................................................................... 38 4.4 MIGRATORY AND OUTBREAK PESTS ................................................................................ 50 5. POLICY, REGULATORY AND INSTITUTIONAL FRAMEWORK ................................... 55 5.1 INTRODUCTION ................................................................................................................... 55 5.2 POLICIES AND STRATEGIES ............................................................................................... 55 5.3 PROGRAMMES AND STRATEGIES ..................................................................................... 57 5.3.1 Africa Stockpiles Programme (ASP) ........................................................................... 57 5.3.2 Empty Pesticides Container Management Strategy .................................................. 57 6. PEST CONTROL AND MANAGEMENT OPTIONS ............................................................. 59 6.1 INTRODUCTION ................................................................................................................... 59 6.2 BIOLOGICAL CONTROL ...................................................................................................... 59 6.3 CULTURAL AND CROP SANITATION PRACTICES ........................................................... 61 6.4 PHYSICAL AND MECHANICAL CONTROL ........................................................................ 62 Page ii of 110 6.5 CHEMICAL CONTROL ......................................................................................................... 62 6.6 BOTANICAL PESTICIDES .................................................................................................... 64 7. EXPERIENCES ON IPM IN TANZANIA ................................................................................ 66 7.1 INTRODUCTION ................................................................................................................... 66 7.2 GTZ/PHS-IPM ........................................................................................................................ 66 7.3 KAGERA AGRICULTURAL AND ENVIRONMENTAL MANAGEMENT PROGRAMME (KAEMP) ............................................................................................................................................ 68 7.4 MARA REGION FARMER INITIAITIVE PROJECT (MARAFIP) ......................................... 69 7.5 MBEYA: SOUTHERN HIGHLANDS EXTENSION & RURAL FINANCIAL SERVICES PROJECT/IFAD ................................................................................................................................. 70 7.6 MOROGORO SPECIAL PROGRAMME FOR FOOD SECURITY (SPFS) /FAO PROJECT 70 7.7 LESSONS AND GENERAL DISCUSSION ............................................................................. 71 7.7.1 Approach ....................................................................................................................... 71 7.7.2 Capacity Building ......................................................................................................... 71 7.7.3 Institutional Collaboration .......................................................................................... 72 7.7.4 Funding and Logistical Support .................................................................................. 72 7.7.5 Political support ............................................................................................................ 72 8. IMPLEMENTATION STRATEGY ........................................................................................... 73 8.1 INTRODUCTION ................................................................................................................... 73 8.2 INSTITUTIONAL ROLES AND RESPONSIBILILTIES ......................................................... 73 8.2.1 MGF Applicant/ Recipient ........................................................................................... 73 8.2.2 Catalytic Fund............................................................................................................... 74 8.2.3 Ministry of Health and Social Welfare ....................................................................... 74 8.2.4 Ministry of Agriculture, Food Security and Cooperatives ........................................ 74 8.3 PROMOTION OF IPM UNDER SAGCOT ............................................................................ 74 8.3.1 Specific PMP for Sub-Projects .................................................................................... 74 8.3.2 IPM to be Part of Environmental and Social Management Plan ............................. 75 8.3.3 The IPM Strategies for Promoting its Adoption ........................................................ 75 8.3.4 SAGCOT to Advice Investors on IPM Practices ....................................................... 76 8.3.5 SAGCOT to Support IPM Training in Research and Training Institutions ........... 76 8.3.6 SAGCOT to Support IPM Training and National Policy ......................................... 76 8.4 SPECIFIC PEST MANAGEMENT MEASURES .................................................................... 77 8.4.1 Rules for Safe Handling of Pesticides.......................................................................... 77 8.4.2 Recommended Pesticides in Tanzania ........................................................................ 77 8.4.3 Pesticides Banned in Tanzania .................................................................................... 79 8.5 MONITORING AND EVALUATION ARRANGEMENT......................................................... 80 8.6 WORKPLAN AND BUDGET ................................................................................................. 81 9. RECOMMENDAITONS ............................................................................................................. 84 REFERENCES ..................................................................................................................................... 85 APPENDICES ...................................................................................................................................... 90 Appendix 1: Names of Experts Involved in Preparing This IPMP for SAGCOT ................................ 90 Appendix 2: Persons Consulted During the Preparation of IPMP for ASDP .................................... 90 Appendix 3: An IPM Checklist for Planning and Implementing Pest Control on Crops .................... 94 Appendix 4: Pesticide Classification List – WHO .............................................................................. 97 Appendix 5: SAGCOT Corridor and Clusters .................................................................................. 103 Page iii of 110 LIST OF TABLES Table 3.1: Zone, Altitude and rainfall classes Table 4.1: Summary of major food, cash and horticulture crops grown in different agro-ecological zone of Tanzania Table 4.2: Major maize pest problems and recommended management practices Table 4.3: List of pesticides recommended for use on maize in all zones Table 4.4: Important weeds in Tanzania Table 4.5: Major pests of rice and recommended management practices Table 4.6: Sorghum major pests and recommended management practices Table 4.7 The major pests of pearl millet and recommended management practices Table 4.8: Banana major pest problems and recommended management practices for Lake and Northern Zones Table 4.9 Cassava major pests and recommended management practices Table 4.10 The major pest problems of beans and recommended management practices Table 4.11 The major pests of sweet potato and recommended management practices Table 4.12 Coffee pest problems and recommended management practices Table 4.13 List of recommended pesticides for use in coffee Table 4.14 Cotton pest problems and recommended management practices in the WCGA Table 4.15 List of pesticides recommended for use on cotton in the WCGA Table 4.16 Cotton pest problems and recommended management practices in the ECGA Table 4.17 List of pesticides recommended for use on cotton in the ECGA Table 4.18 Major pests and recommended management practices in cashew Table 4.19 Pesticides recommended for use on cashew Table 4.20 Major pests and recommended control practices for coconut Table 4.21 Key pests of mangoes and current farmer practices to reduce losses Table 4.22 Major pest problems of citrus and recommended management practices Table 4.23 Major pest problems of pineapples and recommended management practices Table 4.24 Major pests of tomatoes and recommended management practices for northern zone Table 4.25 List of pesticides recommended for use on tomatoes Table 4.26 Major pest problems and recommended management practices Table 4.27 Major pests of brassicas and recommended practices Table 4.28 Rodent control 2003 Table 4.29 Quelea Quelea invaded regions year 2003 Table 4.30 Quelea quelea outbreaks and cereal damage in some regions of Tanzania, 1998-2002 Table 4.31 Invaded area and treatment used Table 4.32 Armywork outbreaks in Tanzania Table 4.33 Damage of various crops by armyworms during the 2001/2002 cropping seasons in some region of Tanzania Table 5.1 List of recommended and TPRI registered pesticides for crop production in Tanzania Table 5.2 List of potential plants that can be used to prepare botanical extracts for pre and post harvest pest control Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania Table 8.2 List of pesticides whose use are subject to the Prior Informed Consent (PIC) procedure in Tanzania Table 8.3: Workplan and Budget for IPM implantation Page iv of 110 ABBREVIATIONS AND ACRONYMS AIDS Acquired Immunodeficiency Syndrome ASDP Agricultural Sector Development Programme ASDS Agriculture Sector Development Strategy ASP Agriculture Services Providers ASSP Agricultural Services Support Programme CF AVRDC Catalytic Fund Asian Vegetable Research Development Centre CBB Coffee Berry Borer CBD Coffee Berry Disease CBO Community Based Organisation CBSD Cassava Brown Streak Disease CLR Coffee Leaf Rust CMD Cassava Mosaic Disease CORMA Client-Oriented Research and Development Management Approach DADP District Agriculture Development Plans DGIC Directorate General for International Cooperation DPPO District Plant Protection Officer DRDP District Rural Development Programme ECGA Eastern Cotton Growing Area ESMF Environmental Social Management Framework ESMP Environmental and Social Management Plan EMP Environmental Monitoring Plan FFS Farmers Field Schools FM Fund Manager GLS Grey Leaf Spot GTZ Gesellschaft fur Technische Zusammenarbeit HPR Host Plant Resistance ICIPE International Centre of Insect Physiology and Ecology IDA International Development Agency IFAD International Fund for Agricultural Development IPM Integrated Pest Management IPN Integrated Plant Nutrition IPM Integrated Pest Management IPMP Integrated Pest Management Plan JICA Japan International Cooperation Agency KAEMP Kagera Agricultural Environmental Management Project LGA Local government authority LGB Larger Grain Borer LVEMP Lake Victoria Environmental Management Project LZARDI Lake Zone Agricultural Research and Development Institute M&E Monitoring and Evaluation MAFC Ministry of Agriculture, Food Security and Cooperatives MANREC Ministry of Agriculture, Natural Resources, Environmental and Cooperatives MARA-FIP Mara Region—Farmers’ Initiative Project MGF Matching Grant Fund MOA Memorandum Of Agreement MSV Maize Streak Virus MWLD Ministry of Water and Livestock Development NAEP National Agricultural Extension Programme NALP National Agricultural and Livestock Policy NARS National Agricultural Research Systems NEMC National Environment Management Council NGO NPPAC Non Governmental Organizations National Plant Protection Advisory Committee NPV Nucleopolyhedrovirus OPEC Organization of Petroleum Cooperation PADEP Participatory Agriculture Empowerment Project Page v of 110 PCS Pest Control Services PHS Plant Health Services PMD Powder Mildew Disease PMP Pesticides Management Plan POP Persistent Organic Pollutants PPD Plant Protection Division PRA Participatory Rural Appraisals RAS Regional Administrative Secretary RPF Resettlement Policy Framework RGZ Revolutionary Government of Zanzibar RYMV Rice Yellow Mottle Virus SAGCOT Southern Agricultural Growth Corridor of Tanzania SVCF Social Venture Capital Fund SGR Strategic Grain Reserve SIIC Smallholder Irrigation Improvement Component SMS Subject Matter Specialist SPFMV Sweet potato feathery mottle virus SPFS Special Programme for Food Security SPSVV Sweet potato sunken vein virus SPVD Sweet Potato Virus Disease SUA Sokoine University of Agriculture SRESA Strategic Regional Environmental and Social Assessment URT United Republic of Tanzania TIC Tanzania Investment Centre TPRI Tropical Pesticides Research Institute UDSM University of Dar es Salaam ULV Ultra Low Volume USD United States Dollars VEO Village Extension Officer WCGA Western cotton growing areas WFF Ward Farmers Forum WHO World Health Organization ZARDEF Zonal Agricultural Research and Development Funds ZARDI Zonal Agriculture Research and Development Institutes ZEC Zonal Executive Committees Page vi of 110 EXECUTIVE SUMMARY This integrated pest management plan (IPMP) addresses the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) Investment Project’s need to monitor and mitigate negative environmental impacts of the project by promoting biological and ecosystem based pest management. The overall SAGCOT Program is broadly identified as a public-private partnership intended to improve the incomes, employment opportunities and food security of smallholder farmers across the southern corridor of Tanzania. This will be done by linking them to internationally competitive supply chains and accelerating commercial agricultural development, in particular by using foreign direct investment attracted by the removal of policy and infrastructural constraints to competitiveness and by facilitated access to land. SAGCOT lies along an existing road, rail and power corridor running from Dar es Salaam west through Iringa to Mbeya and beyond. Initially investments will be focused on six areas with high potential for quick agricultural development ("clusters"), including the Kilombero Valley. Over the next 20 years, the initiative aims to bring 350,000 hectare of land into commercial production, increase annual farming revenues by US$1.2 billion, and lift some 450,000 farming households out of poverty. The Project will promote intensive commercial agriculture in tropical and subtropical environments with significant pest and disease control challenges. Pesticide use and management will be guided by Tanzanian law, the World Bank policy OP 4.09 (Pest Management), international best practice, and experience with Integrated Pest Management (IPM) in the agricultural sector in Tanzania. It specifically draws heavily from related work done to prepare for the Agricultural Sector Dvelopment Program (ASDP) which the Government of Tanzania (GoT) has been implementing since 2006. The management aspects of pests and diseases of the key major crops have been discussed in detail. These include food crops such as maize, sorghum, beans, banana, sweet potatoes, finger millet, rice; cash crops: coffe, cotton, cashewnuts, etc. horticultural crops: coconuts, mangoes, citrus, pineapples, tomatoes, onions and brasiccas (cabbages and kale) and migratory and outbreak pests: rodents, birds (quelea quelea spp) and armyworms. The GoT have taken deliberate measures for promotion of IPM in all crop production systems. In 1997, the GoT formulated and introduced the Agriculture and Livestock Policy and the National Environmental Policy. In line with these two policies, a Plant Protection Legislation was encacted in 1997 followed by its regulations of 1999. Umbrella framework legislation, the Environmental Management Act No. 20 of 2004 is in place. All these policies and legislation emphasise use of sustainable production approaches particularly IPM. The IPMP for SAGCOT is based on the experiences gained during the implementation of IPM experience in Tanzania Mainland and information obtained through review of published materials and discussion with crop experts, researchers, farmers and extension workers. It provides a framework for the development of IPM programme for food, cash and horticultural crops in the SAGCOT Programme to identify, understand and manage pest problems in the components, reduce human and environmental health risks associated with pesticides use, and protect ecosystem by conserving beneficial agents such as natural enemies of pests and pollinators to increase productivity. The IPMP also provides guidelines for pest management in accordance to the IPM approach. It augments the biological, chemical and cultural control aspects of the management of pests and diseases. An outline of the specific pest management measures to be incorporated (including a "positive list" for procurement, rules for safe handling of pesticides, and promotion of IPM); and an implementable workplan outlining those specific measures (e.g. budget, timeline, institutional roles and responsibilities) are given in this IPMP. Page 1 of 110 1. BACKGROUND 1.1. INTRODUCTION The overall SAGCOT Program is broadly identified as a public-private partnership intended to improve the incomes, employment opportunities and food security of smallholder farmers across the southern corridor of Tanzania. This will be done by linking them to internationally competitive supply chains and accelerating commercial agricultural development, in particular by using foreign direct investment attracted by the removal of policy and infrastructural constraints to competitiveness and by facilitated access to land. SAGCOT lies along an existing road, rail and power corridor running from Dar es Salaam west through Iringa to Mbeya and beyond. Initially investments will be focused on six areas with high potential for quick agricultural development ("clusters"), including the Kilombero Valley (see Appendix 5: SAGCOT Corridor and Clusters). Over the next 20 years the initiative aims to bring 350,000 ha of land into commercial production, increase annual farming revenues by US$1.2 billion, and lift some 450,000 farming households out of poverty. The Government of Tanzania (GoT) has requested support from the International Development Agency (IDA, part of the World Bank) to assist in implementation of the SAGCOT concept. The proposed World Bank support ("the Project") will be in the form of a Specific Investment Loan (SIL). The World Bank Operational Policy 4.09 Pest Managetment is triggered as the Project will promote intensive commercial agriculture in tropical and subtropical environments with significant pest and disease control challenges. Although the Catalytic Fund will not directly support purchase of any pesticides, in the field improvements envisioned under the MGF and SCVF could increase the use of inputs - particularly chemical fertilisers, improved seeds and irrigation facilities. This may lead to an increase in the use of synthetic pesticides, and associated potential human and environmental hazards, and hence the requirements for mitigation plan. Pesticides Management Plan (PMP) identifies and addresses changes in pest management practices and concerns that may arise out any increase in chemical pesticides use and propose mitigation in compliance with the World Bank Safeguard Policy on Pest Management (OP 4.09). Pesticide use and management will be guided by Tanzanian law, World Bank policy (including OP 4.09), international best practice, and experience with IPM in the agricultural sector in Tanzania. It specifically draws heavily from related work done to prepare for the Agricultural Sector Dvelopment Project (ASDP). To support such efforts, SAGCOT will also apply the standards set under the International Code of Conduct on the Distribution and Use of Pesticides which encourages responsible and generally accepted trade practices and sets out the “conduct for public and private entities engaged or associated with the distribution and use of pesticides.” The Code is designed for use within the context of national legislation as a basis whereby government authorities, pesticide manufacturers, those engaged in trade and any citizens concerned may judge whether their proposed actions and the actions of others constitute acceptable practices. In addition, it describes the shared responsibility of many sectors of society to work together so that the benefits to be derived from the necessary and acceptable use of pesticides are achieved without significant adverse effects on human health or the environment. The main purpose of preparing this Integrated Pest Management Plan (IPMP) is to: (i) assess the current and anticipate pest problems in the programme areas; (ii) review the country experiences on IPMP; (iii) develop a pest management plans (IPMPs) using recommended best-practices; (v) develop monitoring and evaluation systems for the various pest management practices of the IPMPs based on the government laws and the World Bank policy. It draws upon experience with other IPMPs in Tanzania, including that of the Agricultural Sector Development Project (ASDP). Page 2 of 110 1.2. METHODOLOGY Preparation of this IPMP builds on the following approach and methods that were used to gather information from relevant stakeholders for ASDP IPMP: (i) Participatory approach The preparation of the IPM guidelines used a participatory process aimed at facilitating a broad based dialogue and transparency in identification of key pesticides problems and management issues. Moreover, the extensive consultations with farmers, district staff, communities, lead IPM researchers and practitioners, crop specialists, etc. in Tanzania Mainland and Zanzibar helped to solicit relevant information on pest management. (ii) Review of literature and checklists of documentation Relevant SAGCOT program/ project documents; Policy and legal documents used in Tanzania pesticide industry, namely Plant Protection Act 1997, Pesticide Regulations 2002, Agriculture Policy 1997, National Environmental Policy 1996 and the Environmental Management Act No. 20 of 2004. In Zanzibar the following documents were consulted: Agriculture Policy of 2002, Environmental Management for Sustainable Development Act of 1996 and Plant protection Act of 1997; and World Bank Safeguard Policies in particular OP 4.09 (iii) Questionnaires and checklists for guiding consultative meetings with following stakeholders: ASSP preparation team The ASDP Secretariat Ministry of Agriculture and Food Security, namely Department of Research and Development, Departments of Crop Production, Plant Health Services, Agricultural Extension Services, Participatory Agriculture Empowerment Project (PADEP), Smallholder Irrigation Improvement Component (SIIC), etc. Ministry of Water and Livestock Development, namely Veterinary services Zonal Research and Development Institutes, namely Lake Zone, Northern Zone, Eastern Zone, Western Zone, Southern Highland Zone Ministry of Agriculture, Environment, Natural Resources and Cooperatives, Zanzibar and Zanzibar Agriculture Research Institute in Kizimbani Tanzania Pesticides Research Institute Sokoine University of Agriculture, namely Pest Management Research Centre Division of Environment, Vice-President Office National Environmental Management Council District Councils Farmers representatives NGOs IPM, bird control and armyworm projects (iv) Questionnaires and checklists for guiding consultative meetings with following stakeholders: Ministry of Agriculture and Food Security, namely Department of Research and Development, Departments of Crop Production, Plant Health Services, Agricultural Extension Services, Participatory Agriculture Empowerment Project (PADEP), Smallholder Irrigation Improvement Component (SIIC), etc. Ministry of Water and Livestock Development, namely Veterinary services Page 3 of 110 Zonal Research and Development Institutes, namely Lake Zone, Northern Zone, Eastern Zone, Western Zone, Southern Highland Zone Ministry of Agriculture, Environment, Natural Resources and Cooperatives, Zanzibar and Zanzibar Agriculture Research Institute in Kizimbani Tanzania Pesticides Research Institute Sokoine University of Agriculture, namely Pest Management Research Centre Division of Environment, Vice-President Office National Environmental Management Council District Councils Farmers representatives Page 4 of 110 2. DESCRIPTION OF PROPOSED PROJECT 2.1. INTRODUCTION The proposed Project Development Objective (PDO) will be to: create and expand partnerships between smallholder farmers and agribusinesses in the Southern Corridor leading to adoption of new technologies and improved market access by smallholders. 2.2. PROJECT COMPONENTS The SAGCOT Project comprises three components that will be implemented over a five year period: Component 1: Strengthening of SAGCOT Support Institutions (total USD15.99 million, IDA USD8.67 million). The objective of this component will be to strengthen the capacity of the main SAGCOT support institutions in order to pursue their functions of information and data provision, support of investment planning and guidance, government/private sector intermediation, business enabling environment and investment promotion. The component will support two institutions under the following sub-components: o SAGCOT Centre (total USD10.82 million, IDA USD3.50 million): under this sub-component the Project will jointly with other donors support the SAGCOT-Centre, which was established as a public private partnership entity in 2011 to: (i) Facilitate agri-business and partnership development; (ii) Ensure inclusive and sustainable investment and development; and (iii) Advocate for an improved enabling environment. The Project will support the Centre by providing financing for staff and operational costs, studies and consulting services to be contracted by the Centre. o Tanzanian Investment Centre (Government institution) (total USD5.17 million, IDA USD5.17 million): under this sub-component the Project will support the TIC which was established as a public sector entity in 1977 and designated as the first point of call and a “one-stop facilitation centre” for all potential investors coming into the country. The Project will support TIC to reform its processes with the aim to: (i) strengthen its capacity to leverage high quality, responsible, inclusive and sustainable commercial investments (ii) provide a competitive framework for tendering and (iii) monitor and evaluate investments. The Project will finance incremental equipment, technical assistance and consultancies. Component 2: Strengthening Smallholder Business Linkages (total USD77.68 million, IDA USD45.00 million): The objective of this component will be to link smallholder farmers to agricultural value chains. The component will (a) expand the number of smallholders linked to agribusinesses in successful commercial partnerships and (b) improve the revenues derived by smallholders and rural communities from these partnerships in the form of growth in agricultural productivity, income and employment. This component will comprise two sub-components: o Fund Management (total USD13.00 million, IDA USD6.50 million): under this sub-component the Project will jointly with other donors support a management structure responsible for the implementation of the Catalytic Trust Fund (including Board, Secretariat and Fund Manager). Project support will include fees and salaries, goods and equipment, office operational costs, meetings and workshops, communications and technical assistance. o Matching Grants (total USD64.68 million, IDA USD38.50 million): Matching Grants (MG) at a size of USD250,000 up to USD1.5 million with a matching contribution of 30 percent (national businesses) and 40 percent (international business operators) will be awarded to existing agribusiness operators with undisputed land rights following a defined process of application, evaluation and competitive selection. The grants can be used for operational cost Page 5 of 110 and capital costs directly related to expanding smallholder participation in competitive agricultural supply chains. Component 3: Project Management and Evaluation (total USD6.33 million, (of which USD3.00 million were provided as Project Preparation Advance) IDA USD6.33 million): The component will establish project management and M&E systems and provide financing for salaries, office equipment, transportation and technical assistance services. It will support the coordination between implementation agencies at all levels and with other government programs and institutions. Pesticide issues are considered to be most relevant in the Matching Grants included in Component 2, as such grants will support expansion of outgrower activities that are likely to involve expanded use of pesticides. As such, the IPMP focuses on incorporating measures to ensure necessary capacity, tools (including safety equipment) and monitoring are in place for subprojects supported through the Matching Grants window. 2.3. PROJECT IMPLEMENTATION ARRANGEMENTS The implementation of SAGCOT will take place through the use of existing government structures as well as the SAGCOT Centre, through their mandates to implement the SAGCOT programme. These institutions and their SAGCOT responsibilities are described below. 2.3.1 The Catalytic Fund The Fund Manager(s) of the Catalytic Fund (CF) will identify, finance, and develop viable investments across the value chain in the Corridor. It will also assist in the process of raising third-party commercial finance once the opportunities are “investment ready”. In the process, the Fund Manager(s) will ensure that projects are developed in ways that maximise a range of financial, economic, social and commercial developmental impacts. The Fund Manager(s) shall have the mandate and function of: (a) raising additional Funds subject to the consent of the Board; (b) preparing the investment pricing policy of the Social Venture Capital Fund for approval by the Board; (c) marketing the Funds, (d) approval of applications and (e) operational management of the Funds. The bulk of World Bank support will go to the Catalytic Fund via the Matching Grant Facility. Therefore, the CF must have in place a set of procedures that assure compliance with both GoT environmental regulations and World Bank safeguards, including those of World Bank OP 4.09 Pest Management. 2.3.2 The SAGCOT Centre The SAGCOT Centre is the key coordinator of the SAGCOT programme with numerous cross-cutting roles. The SAGCOT Centre has been established to facilitate investment and manage the coordination of the partnership to ensure the successful achievement of its objectives. Its activities include: (i). Managing and expanding the SAGCOT Partnership; (ii). Information provision & Market intelligence; (iii). Facilitating introductions; (iv). Facilitating access to finance; (v). Coordination of cluster and corridor development; Page 6 of 110 (vi). Identification of enabling environment obstructions and helping to address these; and (vii). Monitoring and evaluating progress. With this remit, the SAGCOT Centre will be instrumental in communicating the principals of sustainable investment across stakeholders in both the public and private sectors. To accomplish this mandate, the SAGCOT Centre will need to have the capacity to undertake the following; (i). keep stakeholders updated on environmental and social issues surrounding development in the Corridor, including those associated with pest management; (ii). communicate to potential investors, in collaboration with TIC, the sustainable and green investment principles which SAGCOT will promote; (iii). be the first “stop” for all investments regarding transparent land transfer requirements; (iv). provide preliminary information on clean technology and reduced carbon footprint opportunities for investors. (v). Finally, the SAGCOT Centre will also be the focal point for annual reporting on safeguard progress across the implementing agencies and organizations to the World Bank. 2.3.3 Tanzania Investment Centre The Tanzania Investment Centre (TIC) was established under the provisions of the Tanzania Investment Act, Cap 38 (Act No 26 of 1997). The Centre is designated to be a one-stop shop for investors and is mandated to co-ordinate, encourage, promote and facilitate investment in Tanzania and to advise the Government on investment policy and related matters. Within this remit, the TIC has the authority to: (i). identify investment sites, estates or land together with associated facilities on these, for the purposes of investors and investments in general; (ii). assist investors to obtain permits, licence approvals consents, authorisations, registrations and other matters required by law for a person to set up and investment; and (iii). enable certificates issued by the Centre to have full effect. TIC will assist in incorporation and registration of enterprises; promote both foreign and local investment activities, and grant certificates of incentives. As the first port of call, the TIC will need to develop a set of guidelines for potential investors that detail the principles of sound sustainable agriculture development in the Corridor, including those for resettlement. These principles should cover the following topics: (i). reliable information on land availability with maps (in a modern format (GIS)); (ii). information linking land suitability to potential crop production; (iii). transparent methods for land transfer, registration and leasing arrangements; (iv). land lease revenue options or equivalents; (v). corporate social responsibility and community development funds, including those related to resettlement and livelihood restoration programmes; Page 7 of 110 (vi). the role of grievance mechanisms, tribunal or adjudication assurance for investors and villagers, and (vii). potential “road blocks” and ways to navigate around these complex issues. The guidelines will be developed using technical information from the Ministry of Lands, Housing and Human Settlements Development and also the Rufiji Basin Development Authority (RUBADA)1. 1 RUBADA is not receiving support under the World Bank Specific Investment Loan, but it is an institution that is relevant to implementation of SAGCOT Page 8 of 110 3. THE GENESIS OF AGRICULTURAL PEST MANAGEMENT PRACTICES 3.1. INTRODUCTION The pest management practices have existed for quite long in the history of agricultural systems having a key drive on human population trends. Until half a century ago crop protection practices were integral parts of any cropping system. Growing world population required dramatic increases of agricultural production. From the 1940’s to the 1970’s, a spectacular increase in yield was obtained with the aid of an intensive development of technology, including the development of a variety of agro-pesticides. In many countries this advancement was coupled with the development of education of farmers and efficient extension services. In many development countries, however, this foreign technology was dumped without adequate support systems. Agro-pesticides were often used injudiciously. Misuse and over-use was stimulated by heavy subsidies on agro-chemicals. Many developing countries adopted a system of technology transfer in which a research apparatus developed or adapted technology that was transferred to farmers by an extension unit. Crop protection measures were often reduced to easy-to-use pesticide application recipes, aimed at immediate and complete destruction of the causal organism. In places where the use of improved varieties was propagated, packages of high-yielding varieties with high inputs of agro-pesticides and fertilisers made farmers dependent on high external inputs. Recently, it was realised that this conventional approach has its disadvantages. Conspicuous drawbacks are undesirable side-effects of pesticides which includes the following: human toxicity; poisoning and residue problems; destruction of natural enemies and other non-target organisms; development of resistance in target organisms; and environmental pollution and degradation. Pesticides are expensive and good management of their use requires skills and knowledge. For various reasons the (Research-Extension–Farmers) transfer of technology often does not work well. The technology is frequently inadequate and not adapted to the specific local needs. Based on above, it can be revealed that; relying on the use of pesticides in not sustainable as their unjudicial use is not human and environmental friendly. Thereby the need to improve the development and transfer of technology down to end users. 3.2. THE MEANING AND IMPORTANCE OF IPM What is IPM? Integrated Pest Management (IPM) could be defined as a comprehensive approach to pest control that uses combined means to reduce the status of pests to tolerable levels while maintaining a quality environment. In OP 4.09, the definition of IPM uses the same principles but emphasizes the following points: 1. The IPM approach must be ecologically-based (making use of the ecosystem ‘s ability to regulate pest populations); 2. Emphasis is on Pest Management as opposed to Pest Eradication; and 3. Reliance on multiple tactics as opposed to the “Silver bullet” approach (Chemical pesticides) The definition is the policy allows for selecting and applying pesticides, in a way that minimizes adverse effects on beneficial organisms, humans, and the environment. Page 9 of 110 Why IPM? The experience on drawbacks in the agricultural pest management systems, necesitated a crop protection approach that is centred on local farmer needs that are sustainable, appropriate, environmentally sound and economically viable. Such approach is called Integrated Pest Management (IPM). It should also be noted that when pesticides are applied in a given crop its only 1% hits direct the targed pest the rest 99% it becomes a burden to the environment and human health. The IPM approach encourages; the use all available, suitable methods of prevention and control, including resistant varieties, cultural methods such as planting time, intercropping and crop rotation, biological control. Pesticides will only be used as a last resort when plant protection decisions are made based on the damage/economic thresholds. Thus the soft and selective pesticides are used to minimise detrimental effects on humans, natural enemies and other non-target organisms. The philosophy of IPM is layed on the; no total eradication of all noxious organisms, but keeping them at levels below injury and conservation of the ecosystem that stimulate the presence of natural enemies. The technology can widely be since it has to be developed by farmers in collaboration with researchers and extensionists. Compliance: the integrated pest management approach is in line with the WB OP 4.09, whereby the policy supports safe, effective, and environmentally sound pest management aspects, such as the use of biological and environmental friendly control methods. As outlined in the Environmental Social Management Framework (ESMF) for SAGCOT. Since the IPM approach is location and crop specific, most sub-projects under the program may need a specific pest management plans for addressing the concerns on board. More importantly, the IPMP for the SAGCOT Project will serve as a guidance and reference document for the preparation of specific subprojects PMP. 3.3. FUNDAMENTALS OF IPM An understanding of the ecological interrelationships within a farming system; crop, plant, pests organisms and factors influencing their development; An understanding of economical factors within a production system; infestation: loss ratio, market potential and product prices; An understanding of socio-cultural decision-making behaviour of the farmers; traditional preferences, risk behaviour, etc; The involvement of the farmers in the analysis of the plant protection problems and in the elaboration of solutions; and The successive creation of a legislative and agricultural policy framework conducive to a sustainable IPM strategy; plant protection and pesticides legislation; pesticides registration and price policy. 3.4. KEY CHARACTERISTICS OF AN IPM APPROACH Use all available, suitable methods of prevention and control, including resistant varieties, cultural methods such as planting time, intercropping and crop rotation, biological control. Pesticides will only be used as a last resort, but preferably selective ones, or used in a selective way to prevent detrimental effects on natural enemies and other non-target organisms. Conservation of the ecosystem, stimulate the presence of natural enemies No total eradication of all noxious organisms, but keeping them at a low level Technology is developed by farmers in close co-operation with researchers and extensionists Farmers make their own decisions and carry them out. Page 10 of 110 3.5. THE PRINCIPLES OF AN IPM Grow a healthy crop; Recognise pests, diseases, and natural enemies; Carry out regular observations; and Make the right crop protection decisions, through discussion with fellow farmers. Page 11 of 110 4. EXISTING AND ANTICIPATED PEST PROBLEMS The existing and anticipated pest problems in the SAGCOT Project Area are described in this chapter. A list on food, cash and horticultural crops and migratory and outbreak pests is presented and an analysis is made on existing and anticipated pest problems and their management practices. 4.1 FOOD CROPS The major food crops shown in Table 4.1 which are grown in the target project areas are maize, rice, sorghum, millet, beans, cassava, and banana. The importance of each crop varies from one area to another and the priority list varies depending on the source of information. However, maize is the most popular staple of many Tanzanians, and is a major cash and food crop in many parts of the Southern Highlands. This is followed by rice, sorghum, millet, bananas, beans, cassava, sweet potato, wheat and legumes. Some of these crops such as rice, maize, beans, sorghum and millet are regarded as food and cash crops depending on the area. Table 4.1: Summary of major food, cash and horticulture crops grown in the SAGCOT Project Area Zone Regions Major crops Horticultural crops Food Cash Eastern Morogoro Coast Tanga Dar es Salaam Maize Rice Beans Cassava Round potatoes Sorghum Banana Coffee Cotton Cashew Sugarcane Tea Citrus fruits Pineapples Brassicas Tomatoes Mangoes Coconuts Southern Highlands Iringa Mbeya Ruvuma Rukwa Maize Sorghum Fingermillet Rice Beans Cassava Sweet Found potatoes Tea Tobacco Coffee Rice Cotton Sunflower Wheat Cashew Pyrethrum Palm oil Bananas Tomatoes Mangoes Pineapples Potatoes Peas Brassicas Maize Maize is the major staple food crop and it is grown in all the agro-ecological zones. It can be grown over a wide range of altitude ranging from 0-2400m a.s.l. Maize requires an optimum rainfall of 1800 mm. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 1,564,000 ha and 2,810,490 ha were put under maize cultivation in 1995/6-2002/03 respectively with overall production of 1,831,200 and 3,415,600 tons. In terms of percentage contribution in 2002/03, the Southern Highlands produce 45%, followed by Lake Zone (20%), Northern Zone (11.0%), Western Zone (10%), Eastern Zone (8%), Central Zone (4%), and Southern Zone (2.5%). The southern highlands supplies 90% of the strategic grain reserve (SGR), thus making it the national grain basket. The major insect pests of maize are: African maize stakeborer (Bossuela fusca), pink stalkborer (Sesamia calamistis), spotted stalkborer (chilo partellus), American bollworm (Helicoverpa armigera), cutworms- greasy cutworm (Agrotis ipsilion), and maize leafhopper (Cecadulina mbila). The major diseases of maize are: leaf rusts (Puccinia sorghi and P.polysora), leaf blights (Helminghtosporium turcicum and maydis), Maydis leaf blight (Helminthosparium maydis), maize streak disease (maize streak virus), grey leaf spot (GLS) (Cerospora zaea-maydis), Gibberella Ear Rots, common sut. Page 12 of 110 Because the crop is grown under different agro-ecological zones, pest problems (pre and post harvest) associated with it and the recommended management options vary accordingly (Table 4.2). Table 4.2: Major maize pest problems and recommended management practices Zone Pest Recommended management practices Southern Highlands Insects Pre-harvest Stalk borers (Busseola fusca) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Use the extract of Neuratanenia mitis, a botanical pesticide African armyworm (Spodoptera exempta) Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical extract timely (Table 4.3) Seedling weevils (Tanymecus spp. & Mesokeuvus spp) Timely planting to escape damage Scout the crop Apply lambda cyhalothrin if necessary (Table 4.3) Page 13 of 110 Zone Pest Recommended management practices Post harvest Larger grain borer (LGB) Weevils Moths Selection of tolerant varieties Timely harvest Dehusking and shelling Proper drying Sorting and cleaning of the produce Cleaning & repair of the storage facilities Use rodent guards in areas with rat problems Use improved granaries Use appropriate natural grain protectants e.g. where applicable or Use recommended insecticides at recommended dosage (Table 4.3) and/or Keep the grain in air tight containers and store these in a shady place, preferably in-doors Carry out regular inspection of the store and produce. Timely detection of any damage to the grain and/or storage structure is essential to minimise potential loss or damage Promote biological control of LGB using Teretriosoma nigrescens (Tn) to minimise infestation from wild sources. This is the task of the national plant protection services because the agents have to be reared and released in strategic sites. However, the farmers will benefit from this strategy. Diseases Grey leaf spots (GLS) Crop rotation Plant recommended resistant varieties e.g. H6302, UH6010, TMV-2 Observe recommended time of planting Removal of infected plant debris by deep ploughing Maize streak virus Early planting Plant recommended resistant varieties e.g. TMV-1 in areas below 1500m above sea level, Kilima ST and Katumani ST and Staha Northern leaf blight Rotation Deep plough of the crop residues Plant recommended resistant varieties e.g. H6302, UH6010, TMV-2, H614 Page 14 of 110 Zone Pest Recommended management practices Weeds All types See Table 3.4 Hand pulling and hoe weeding Intercropping Use resistant/tolerant varieties Improvement of soil fertility Tillage Proper land preparation Timely weeding (at 2 and 5-6 weeks after planting) Apply recommended herbicides Eastern Insects Pre harvest Stalk borers Follow recommended time of planting Proper disposal of crop residue Armyworms Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 4.3) Post harvest Larger grain borer (LGB), Weevils, Moths As Northern Diseases Maize streak virus Observe recommended planting dates Plant recommended tolerant varieties e.g. Kito-ST, Staha-ST, Kilima-ST Weeds All types Proper land preparation Timely weeding (at 2 and 4 weeks after planting) Use recommended herbicide (Table 4.3) Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000; Mbwaga et.al. 1993. Table 4.3: List of pesticides recommended for use on maize Chemical Common name Formulatio n Application rate Target pest Comments Insecticides Post harvest Cypermethrin 0.5% D 100gm/100kgs LGB Permethrin 0.5%D 100gm/100kgs LGB Pirimiphos methyl 2% D 200- 500gm/100kgs All storage insect pests for all grains Not good enough against LGB Pirimiphos methyl + permethrin 1.6% + 0.3%D 100gm/100kgs All storage insect pests for all grains Herbicides Atrazine + metalochlor 50% FW 4l/ha All types Apply pre-emergence Atrazine 80% WP 2.5 to 3.0 l/ha All types Pre/post emergence Notes: 1. All herbicides are applied using knapsack sprayers. Page 15 of 110 2. All the insecticides for storage pests are in dust form and therefore used as supplied without mixing with anything else. 3. The pre-harvest insecticides are used without mixing. 4. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn in the market. Therefore always consult the nearest plant protection extension worker if in doubt. Rice In Tanzania rice is considered to be cash and food crop. Almost half of the world population use rice as its staple food in Asia and Africa. Tanzania is the largest producer and consumer of rice in the East, Central and Southern African region after Madagascar (Banwo (2001). According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 439,300 ha and 626,300 ha were put under rice cultivation in 1996/97-2002/03 respectively with overall production of 549,700 and 1,283,700 tons. The major rice production areas are the coastal zone, western zone up to Lake Victoria, areas around the lakes and other area with enough water such as Kilombero valley and southern plains. The crop is grown under different agro-ecological areas (upland, lowland and irrigated environments) and therefore, the pest pressure varies accordingly (Table 4.5). Overall, upland rice contributes 80% while lowland rice is only 20% of the total production (Kanyeka, et.al.1995). Locally, the economic value of rice depends largely on where it is grown. In Mwanza and Shinyanga regions, it is grown mostly for cash whereas in Morogoro, it is a cash-food crop (Table 4.1). Because it is grown in many parts of the country and under different management systems (rain-fed and under irrigation), the pest problems and management tactics also vary (Table 4.5). Unfortunately and until recently, issues related to pest management in rice production were given low priority (Banwo et al.2001), and therefore, available information on pest control options is scanty (Table 4.5). The most devastating pest of rice in Tanzania is the rice yellow mottle virus (RYMV). Although indigenous to Africa, the disease was reported in Tanzania in 1980s and now has spread to all the major growing areas notably in Morogoro, Mbeya and Mwanza (Banwo, et al. 2001). The disease can cause up to 92% yield loss on "super", the most popular rice variety in Tanzania (Banwo, 2003). The only viable control option for the disease is by planting resistant varieties). Unfortunately, only a few of the local varieties in the SSD-1, SSD-3, SSD-5, SSD-7, SSD-35 series have same level of resistance to the disease. Table 4.5: Major pests of rice and recommended management practices Pests Recommended management practices Insects Stem borers (Chilo partellus, C. orichalcociliellus, Maliarpha separatella, Sesamia calamistis) Plant recommended early maturing varieties Destruction of eggs in the seedbeds Early planting Proper fertilisation Use recommended plant spacing Observe simultaneous planting Destruction of stubble after harvest Clean weeding Plough after harvest to expose the eggs to natural enemies Stalk-eyed fly (Diopsis spp) African rice gall midge (Orseolia oryzivora) Small rice grasshoppers (Oxya spp.) (Senene) African armyworm (Spodoptera exempta) Resistance varieties Stalk management in dry season Flea beetles (Chaetocnema varicornis) Suspected to be the key vector of RYMV (Banwo, et al. in press; Kibanda, 2001). No known control measures. Rice hispa (Dicladispa sp) Page 16 of 110 Pests Recommended management practices Weeds Cyperus rotandus, striga All types (see Table 4.5) Early clean weeding Use recommended herbicides if necessary Diseases Rice yellow mottle virus Field sanitation including buring of crop residues and removal of volunteer plants Use of resistant varieties Rice blast (Pyricularia oryzae) Destruction of crop residues Clean seeds Avoid use of excessive nitrogen fertilizers Use of wide spacing to avoid overcrowding Use resistance varieties Appropriate crop rotation Timely planting Burying crop debris Brown leaf spot (Helminthosporium spp) Sheath rot (Acrocylindrium oryzae) Vermines Birds Wild pigs Hippopotamus Rats Scaring Bush clearing Early weeding Early harvesting Spraying against Quelea Queleas Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 Sorghum Sorghum is an important subsistence food crop in Tanzania that is grown mainly in Morogoro, Lindi, Tabora, Dodoma, Singida, Mwanza, Shinyanga and Mara regions. Sorghum is a drought resistant crop. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 622,400 ha and 557,323 ha were put under sorghum cultivation in 1996/97-2002/03 respectively with overall production of 498,500 and 461,400 tons. Sorghum needs a minimum of 300-380 mm of rainfall during growth and has a wide range of pests (Table4.6). The recommended pest management strategies are summarised in Table 4.6. Table 4.6: Sorghum major pests and recommended management practices Pest Recommended management practices Insects Pre harvest Shootfly (Atherigoma soccata) Observe recommended time of planting to avoid the pest Plant recommended varieties Destroy infected crop residues by burying Apply recommended insecticides if necessary e.g. endosulfan or fenitrothion Stalk borers (Busseola fusca & Chilo partellus) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Use the extract of Neuratanenia mitis, a botanical pesticide Page 17 of 110 Pest Recommended management practices African armyworm ((Spodoptera exempta) Cutworms (agrotis ipsilon) Plough a month before sowing Rapid seedling growth Weeding early Use of plant treated seeds Treat the seed bed with wood ash Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 3.3) Post harvest LGB, weevils and moths Use of botanicals, e.g. Neem or pili-pili Bio-control (use of natural enemies) Diseases Grain moulds Plant recommended tolerant/resistant varieties e.g. IS 9470, IS23599, IS24995, cv. Framida and cv. Serena Observe recommended time of planting Field sanitation Practice good crop rotation Grey leaf spot (Cercospora sorghi) Observe recommended time of planting Field sanitation Practice good crop rotation Use clean planting material Anthracnose (Colletotrichum graminiocola) Plant recommended tolerant varieties e.g. Tegemeo, Serena, Framida and Segaolane Observe recommended time of planting Field sanitation Rust (Puccinia purpurea) Use disease free seeds and follow recommended spacing Plough in crops immediately after harvesting Crop rotation Observe recommended time of planting Field sanitation Leaf blight (Exserohilum turcicum) Plant recommended tolerant varieties e.g. Tegemeo and Serena Observe recommended time of planting Field sanitation Ladder leaf spot (Cercospora fusimaculans) Observe recommended time of planting Field sanitation Practice good crop rotation Use clean planting material Sooty stripe (Ramulispora sorghi) Zonate leaf spot (Gleocercospora sorghi) Weeds Witchweed (Striga asiatica) As for maize in Kagera region Page 18 of 110 Pest Recommended management practices Vermines Quelea quelea spp Warthog Hippopotamus Scaring Bird trapping Farmers to scout potential breeding sites and destroy nests Monitoring and organised aerial spraying using fenthion 60%ULV at the rate of 2.0l/ha Spot spraying, targeting roosting sites Source: LZARDI-Ukiriguru 2000; Mbwaga, et.al. (1993) and MAFS: Plant Pests Field Book: A guide to management, 2002 Pearl millet Pearl millet (burlush millet) is one of the indigenous subsistence food crops which grow well in areas with reliable rainfall such as those found in central Tanzania. The crop has many advantages over other cereal crops in that it is drought tolerant and therefore suitable for the semi-arid areas of the country (Mbwaga et.al. 1993). Pearl millet grows best on reasonably fertile soils but they have the ability to give satisfactory yields on infertile soils. It is one of the most import food crops in the dry semi-arid regions, mainly Dodoma and Singida. Significant quantities of pearly millet are also produced in Shinyanga, Mwanza and Tabora regions. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 353,360 ha and 242,100 ha were put under millet (bulrush and finger millet) cultivation in 1995/6-2002/03 respectively with overall production of 347,700 and 118,200 tons. There has been limited local research work on the crop and therefore available information on its major pest problems and management options is scanty (Table 4.7). Table 4.7 The major pests of pearl millet and recommended management practices Pest Recommended management practices Insects Pre harvest Shootfly (Atherigoma soccata) Observe recommended time of planting to avoid the pest Plant recommended varieties Destroy infected crop residues by burying Apply recommended insecticides if necessary e.g. fenitrothion Stalk borers (Busseola fusca & Chilo partellus) Stalks are buried or burned to eliminate diapausing larvae Early sowing reduces infestation Intercropping with pulses (except rice) Neem(arobani) powder (4-5 gm i.e. pinch of 3 fingers) per funnel Neem ssed cake (4 gm/hole) during planting Carbofuran and carbaryl are effective insecticides Use the extract of Neuratanenia mitis, a botanical pesticide Page 19 of 110 Pest Recommended management practices African armyworm ((Spodoptera exempta) Cutworms (agrotis ipsilon) Plough a month before sowing Rapid seedling growth Weeding early Use of plant treated seeds Treat the seed bed with wood ash Scout the crop immediately the forecast warns of expected outbreak in the area Apply recommended insecticide or botanical pesticide timely (Table 3.3) Leaf spot No recommendation Rust (Puccinia penniseti) Observe recommended time of planting Field sanitation Plant recommended tolerant varieties if available Smut (Moesziomyce bullatus) Plant resistant varieties e.g. ICMV 82132, ICMPS 900-9-3 & ICMPS 1500-7-3-2 Downy mildew (Sclerospora graminicola) Early sowing Use of disease free seed Transplanting the crop suffers less from the disease Roughing of infected plants to avoid secondary infection Weeds Witchweed (Striga spp) Farm yard manure Weeding Birds Quelea quelea spp Scaring Bird trapping Farmers to scout potential breeding sites and destroy nests Monitoring and organised aerial spraying using fenthion 60%ULV at the rate of 2.0l/ha Spot spraying, targeting roosting sites Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 Mbwaga et.al. 1993. Banana Banana is a major food crop for about 4.0 million people in Kilimanjaro, Arusha, Kagera, Mbeya and Kigoma (Table 4.1 and maps). The produce has various uses but it is mostly used as a fruit and/or vegetable. It is therefore eaten either cooked, or as desert when ripe. Bananas are of great importance to the rural population in the Chagga homegardening and to those living in the Pare and Usambara mountains. The crop provides households with both food and income, while its produce includes leaves for thatching houses and pseudostema to feed livestock (although of poor nutritional value). Bananas are growing in association with various other crops, such as coffee, beans, maize, cocoyams and fruit trees. Farmers apply no chemical control measures to protect the crop. According to Basic Data Agriculture Sector 1996/97- 2002/2003 (MAFS 2004), it is estimated that 241,400 ha and 390,200 ha were put under banana cultivation in 1996/7-2002/03 respectively with overall production of 604.100 and 1,898,800 tons. The major disease to bananas is Panama wilt (Fusarium), while balck S igatoka or balck leaf streak disease is of lesser importance. Both diseases are caused by fungi and can destroy all susceptible varities within a large area. Panama disease are caused is soil borne and spreads through soil and infected planting materials. Black Sigatoka is soil borne and spreads by wind, water dripping or splashing, but also by infected planting materials. Farmers’ control of both diseases is limited to removal of diseased plants, application of large Page 20 of 110 quantities of farmyard manure and avoidance of planting susceptible varieties. Options for their control by IPM include field sanitation (such as rotation), use of clean suckers and planting of resistant varieties. Application of farmyard manure reduces the damaging effect of the two diseases. Two important pests causing great loss of harvest are banana weevils and nematodes. The latter cause toppling of the plants because the rooting system is seriously weakened. Weevils cause snapping at ground level of the bananas. Both pests may be present in planting materials and hence infect new fields. The extent of damage by weevils and nematodes is further enhanced by poor soil fertility management. Weevils can be trapped and removed by using split pseudo stems and corns, but application of botanicals, such as Tephrosia, tobacco and Mexican marigold can also be tried. The key pests and their management options for the northern zone and Kagera regions are summarised in Tables 4.8. It has to be noted that, local agronomic practices and agro-ecological conditions influence the pest types and pressure. Therefore, farmers in other banana growing areas should be advised to select and experiment with the options developed for the northern zone where similar pest problems are experienced. Table 4.8: Banana major pest problems and recommended management practices for Lake and Northern Zones Pest Recommended management practices Insects Banana weevil (Cosmopolites sordidus) (Temnoschoita delumbrata) Kiswahili name: Funza ya migomba Practice crop rotation Intercropping with legume which reduce weevil movement Sanitation/crop hygiene Use healthy planting material (use a combination of corm paring and hot water (at 550C for 20 minutes or solarisation ) treatment Sequential planting to avoid nematode infested areas Rational use of weevil trapping with using bate (split pseudostems or discs and corns) Use of repellent botanicals, such as Tephrosia, tobacco, Mexican marigold, Neem and Iboza multiflora Improved soil fertility management and crop husbandry Mulching Deep planting to discourage egg-laying Application of high quantities of manure to improve soil fertility Harvest hygiene Ants Trapping Diseases Panama disease or Fusarium wilt (Fusarium oxysporum f.sp. cubense) Kiswahili name: Mnyauko panama Grow banana cultivars with resistance to pest and disease like the East African Highland bananas (Matoke) Fallow or rotation Sanitation/crop hygiene Planting of clean suckers Establish new crop on disease free sites Mulching Application of high quantities of manure Destroy debris of wilted plants by burning Black and yellow sigatoka (Mycosphaerella fijiensis) Kiswahili name: Sigatoka Resistant cultivars Uproot and burn the affected parts Page 21 of 110 Pest Recommended management practices nyeusi Use of large quantities of farmyard manure Pland and field sanitation Use disease free seeds Prune, remove suckers and weed frequently Avoid close spacing Avoid transfer of seeds from affected areas to unaffected areas Nematodes Burrowing nematodes, e.g. Pratylenchus goodeyi, Radophilus similis, Meloidogyne spp. and Helichotylenchus multicintus Improved farm management, including sequential replanting and soil fertility Practice crop rotation Sanitation/crop hygiene Farmer training in disease identification and control measures Use healthy planting material Establish new crop on disease free sites Mulching to enhance beneficial soil organisms to suppress nematodes Treatment of infested suckers with hot water Application of high quantities of manure Sterilise planting material through solarization and/or the hot water method as for weevil control Vermines Rodents Trapping by using local methods Cleanliness of the farm Source: MAFS: Plant Pests Field Book: A guide to management, 2003, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000; Anania & Sayi (2001), Paul, et.al. (2000) Cassava Cassava is one of the major food crops in all areas except in the northern zone. Increased production is affected by pre-harvest and post harvest pest problems. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it is estimated that 1,426,000 ha and 2,503,500 ha were put under casava cultivation in 1996/7-2002/03 respectively with overall production of 2,149,100 and 2,833,200 tons. Table 4.9: Cassava major pests and recommended management practices Pest Recommended management practices Insects Pre harvest Cassava mealybugs (Phenococcus manihot) Improve the soil fertility by manuring, mulching and intercropping Practice crop rotation Use clean planting material Resistant varieties Plant health stem cuttings Plant as the beginning of the wet season Cassava green mites (Mononychellus tanajaa) Improve the soil fertility by manuring, mulching and intercropping Practice crop rotation Use clean planting material Resistant varieties Plant health stem cuttings Plant as the beginning of the wet season Page 22 of 110 Pest Recommended management practices Cassava root scale (Stictococus vayssierra) Plant health stem cuttings Plant as the beginning of the wet season Cassave white scale (Aonidomytilus albus) Plant health stem cuttings Plant as the beginning of the wet season Variegated grasshopper (Zonocerus variegates) Destructing the breeding sites Dig egg-laying sites of variegates grasshopper in the wet season to expose and destroy egg pod of the pest Biological control: use fungal pathogens, e.g. Metarlizium spp Spiralling whitefly (Aleurodicus dispersus) Crop rotation Plant health stem cuttings Plant as the beginning of the wet season White fly (Bemisia tabaci) Eliminate the sources of the virus Plant health stem cuttings Plant as the beginning of the wet season Post harvest LGB, Weevils and Red flour beetle Use of botanicals, e.g. Neem or pili-pili Bio-control (use of natural enemies) Diseases Cassava mosaic disease (CMD) Improve the soil by manuring, mulching and intercrops Plant health stem cuttings After harvesting destroy infected cassava stems Use resistance varieties that tolerate CMD like Kibaha, Msitu Zanzibar, Aipin Valencia, Kigoma nyekundu and Mzungu Manipulate sowing date and planting spacing to reduce incidence of the disease Plan resistance varities against TMS 4(2)1425, TMS 81983, TMS 83/01762 Cassava bacterial blight (Xanthomorias ampestris) Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Avoid growing cassava consecutively on the same field Check field regularly Fallow practice Use of resistant varieties Rogue and destroy plants Page 23 of 110 Pest Recommended management practices Cassava Anthracnose (Colletotrichum graminiocola) Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Avoid growing cassava consecutively on the same field Check field regularly Rogue and destroy plants Cassava brown streak disease Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Crop rotation Harvest early Grow resistance varieties like Mzungu Cassava root rot disease (Phytophtora, Pithium and Fusarium spp) Harvest early Plant cuttings from health plants without leaf chlorosis After harvesting destroy discarded infected cassava stems Cleansing of farmers tools Weeds Acanthospermum spp Cultural methods Vermines Baboons, Monkeys and rats (Lake Zone) Hunting farmer groups Use of traps Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru 2000; Pre-harvest Cassava mealybugs (Phenococcus manihot) The pest is widespread with frequent outbreaks in Ruvuma, Kigoma, Dodoma and Mara regions. Effective control is achieved through biological control using a wasp (Apoanagrus lopezi). This wasp has reduced the population significantly in most parts of Tanzania (Anon, 1999). However, in parts of Mara, Mwanza, Iringa and Kigoma, the pest is still devastating cassava. In these areas, another bio-control agent, (Hyperapsis notata), a predator, was released to compliment the wasp. Because of limited funding, the predator has been released in a few areas only (Anon, 1999). Page 24 of 110 Cassava Green mites (Mononychellus tanajoa) This pest is also widespread but is more devastating in the Lake zone. The pest can cause 60% to 80% crop loss if left uncontrolled (Anon, 1999). Like the case of the mealybugs, effective control can be achieved through biological control. To affect this, an exotic predatory mite, Tyhlodromallus aripo, was imported and first released 1998 (Anon, 1999). The agent has spread too many areas including the southern zone, parts of Coast, Lake and S. Highlands. Where the agent has established, the pest population has been reduced considerably (Anon, 1999). Cassava white mites This is a major pest in the Lake zone. Currently, the only recommended management option is uprooting and burning of infected plants. However, some local selections are known to be tolerant to the pest. Such varieties should be identified, popularised, multiplied and distributed to farmers. Cassava mosaic disease (East AfricaCMV, ACMV) The disease is widespread but is more devastating in Mwanza, Mara, Kigoma and Coast regions where an incidence of 60% to 80% has been recorded (Dr. Rose Mohamed, personal communication). Farmers in affected areas are advised to uproot and burn infected plants and encouraged to plant resistant varieties. Currently, multiplication of resistant varieties (TMS 60142, TMS 30337, TMS 4(2) 1425, TMS 30572) is being done at Lake Zone Research and Development Institute in Maruku and Ukiriguru in collaboration with IITA. In addition, TMS 4(2) 1425 and TMS83/01762 (6) were multiplied in Mara region in collaboration with MARAFIP for distribution to farmers. An open quarantine site at Maruku, Bukoba was established in 1999 to further facilitate efforts to introduce resistant varieties from neighbouring countries (Anon, 2000). Cassava mosaic disease Uganda variant (UgV) The disease is devastating in the Lake zone, particularly in Shinyanga, Kagera, Geita district and Kigoma (R. Mohamed, personal communication). Use of resistant varieties is the only suitable management strategy. Such varieties are not available in the country. Through the East African cassava disease control programme, a resistant variety, Serere selection 4 (SS4), has been identified in Uganda. This material has been brought in the country for multiplication under the CMD East African programme. Cassava brown streak disease The problem is common along the coast (from 0-500m above sea level, from Tanga to Mtwara and around Lake Nyasa. The only viable management option is through planting of tolerant/resistant varieties. Some resistant varieties have already been identified in Kenya. These varieties will be imported through Mwele- Tanga open quarantine for multiplication and distribution to farmers. The work has not yet started due to lack of funds. It is estimated that the national programme will need about US$ 20,000 for two seasons to facilitate importation, multiplication and distribution of clean cuttings to affected areas. Post harvest The larger grain borer (LGB) is the most damaging pest of dried cassava. Loss of about 35% can occur in a period of 4-6 months if uncontrolled (Mallya, 1999). Rodents, particularly the multi-mammate rat (Mastomys natalensis) attacks dried cassava chips and can cause high losses (quality and quantity) and therefore farmers should adopt and use recommended strategies to minimise potential attack. The current integrated stored products guidelines (Nyakunga & Riwa, undated) if adopted, will go a long way in reducing potential losses due to LGB and rodents on dried cassava. Page 25 of 110 Common Beans (Phaseolus) Common beans or phaseolus may be regarded as on e of the principal sources of protein as well as income to most farmers in Tanzania. According to Basic Data Agriculture Sector 2001/2002-2002/2003 (MAFS 2004), it is estimated that 732.200 ha and 651,000 ha were put under rice cultivation in 2001/2002-2002/03 respectively with overall production of 562,200 and 603,200 tons. Beans are grown throughout the country with major production in the southern highlands, northern, eastern and some parts of Lake Zone Consequently, the pest pressure and type varies due to agro-ecological and management differences. Small-scale farmers grow beans mainly as intercrop with maize, while large-scale farmers grow them as monocrop. In contract to large-scale farmers, who apply a wide spectrum of chemicals, small scale farmers mainly apply cultural practices, and storage insecticides to control pests and disease in beans. The most common diseases in beans are angular leaf spot disease, anthracnose, bean rust, and root rots. These are disease transmitted by fungi. One of the common causes of sever damage is the intensive cultivation of beans without sufficient rotation, the cultivation of resistant varieties and seed dressing are potential IPM control measures, but farmers have also to be trained in the proper diagnosis of the diseases. Common pests in beans are stem maggots, brochids and foliage beetles. Maggots of the bean fly and foliate beetles cause damage to the beans while in the field. Brochids are storage insects that may cause severe loss of crop. Storage hygiene, improved storage structures and the application of ash, vegetable oil and botanicals, such as Neem and Tephrosia, are among the potential IPM control measures of bean bruchids. Maggots and foliage beetles may be controlled by seed dressing or spraying with botanicals, or by cultural practices, including rotation, post harvest tillage and earthing-up mulching. Overall, some of the major diseases have been taken care of through breeding and selection for tolerance/resistance (Table 4.10). Farmers in different parts of the country already grow some of the disease tolerant/resistant varieties. The pest management options as summarised in Table 4.10 have been developed for the southern zone but can also be used by farmers in other areas. However, since this is not a blue print, farmers should be advised to select and try them out before full adoption. Table 4.10: The major pest problems of beans and recommended management practices Zone Pest Recommended management practices Southern Highlands Insects Pre- harvest Bean stem maggot (Ophiomyia spp) Seed dressing Apply recommended insecticide or botanical extracts within five days after emergence Plant tolerant/resistant varieties if available Improvement of soil fertility through application of manure and/or fertilisers Bean aphids (Aphis fabae) Practice early planting Apply recommended insecticides or botanical extracts if necessary Bean leaf beetle (Ootheca benningseni) Observe recommended time of planting Practice good crop rotation Post harvest ploughing where possible Apply recommended insecticides Bean pod borer (Helicoverpa armigera) Apply recommended insecticides or botanical extracts Page 26 of 110 Zone Pest Recommended management practices Post harvest Bean bruchids (Acanthoscelides obtectus) Ensure the beans are dry and well cleaned before storage Apply recommended storage insecticide/ botanical extracts Diseases Bean anthracnose Practice good crop rotation Sanitation and crop hygiene Use certified seed Observe recommended time of planting Plant tolerant/resistant varieties e.g. Uyole 98, Uyole 84 & Kabanima Angular leaf spot As above Rust (Uromyces appendiculatus) Avoid planting beans in high altitude areas Practice good crop rotation Sanitation and crop hygiene Plant tolerant/resistant varieties e.g. Ilomba, & Uyole 90 Observe recommended time of planting Spray with recommended fungicide when necessary Haloblight (Pseudomonas sp) Plant tolerant/resistant varieties e.g. Uyole 84 Spray with recommended fungicide when necessary Use certified seed Ascochyta (Phoma sp) Avoid planting beans in high altitude areas Spray with recommended fungicide when necessary Plant tolerant/resistant varieties e.g. Ilomba & Uyole 98 Sanitation and crop hygiene Bean common mosaic virus (BCMV) Plant tolerant/resistant varieties if available Effect good control of aphids Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru 2000; IPM working group in the Northern Zone 2001; Anania, et.al. (2001); Paul, et.al (2000), Madata, et.al. (2001). Sweet Potato The food crop is mainly grown in most small scale farming system. Cultivated areas under sweet potatoes in 2002/2003 were in Mbeya (69,000 ha), Kigoma (27,800 ha), Shinyanga (73,800 ha) and Mwanza (90,200 ha) regions. In 2002/2003 sweet potatoes production was as follows: Kigoma (233,400 tonnes), Shinyanga (164,100 tonnes), Mwanza (150,800 tonnes), Rukwa (87,900 tonnes), Kagera (69,000) and Mbeya (47,000 tonnes). According to Basic Data Agriculture Sector 1996/7/2002-2002/2003 (MAFS 2004), it is estimated that 287,000 ha and 470,600 ha were put under sweet potatoes cultivation in respectively with overall production of 477,700 and 957,500 tons. Sweet potatoes plan an important role during periods of food scarcity and are part of the survival strategies employed by rural households. The crop suffers from two major pests, which reduce significantly its yield: mole rats and may provoke other Page 27 of 110 pathogens to enter and cause rotting. Factors that contribute to the presence of these pests include monocropping, use of infested planting materials (weevils), drought and late harvesting. Table 4.11 presents pests and management practices. Table 4.11 : The major pests of sweet potato and recommended management practices Pest Recommended management practices Insects Sweet potato weevil (Cylas brnneus) Kiswahili name: Fukuzi wa viazi (adult) and Funza wa viazi (larva) Sanitation Use of clean materials Crop rotation Plant varieties that form tubers at a greater depth Early harvesting of tubers; as soon as weevil damage is observed on tuber tips, harvesting should begin Keeping distance (at least 500m) between successive sweet potatoes plots Destroy infected crop residues by burying Planting of repellent species, such as Tephrosia, tobacco and Mexican Hilling up twice (at 4th and 8th week after planting) in the season to cover soil cracks and exposed to minimize eggs laying Traps with pheromones Rough sweet potato weevil (Blosyrus sp) Crop rotation Sanitation Planting of repellent species Botanical pesticide Striped sweet potato weevil (Alcidodes dentipes) Sanitation Use of clean materials Crop rotation Plant varieties that form tubers at a greater depth Early harvesting of tubers; as soon as weevil damage is observed on tuber tips, harvesting should begin Diseases Sweet potato feathery mottle virus (SPFMV) Use of resistant varieties Crop rotation Sanitation Sweet potato sunken vein virus (SPSVV) Avoid disease plants as a source of planting materials Use of resistant varieties Sweet potato virus disease (SPVD) Sanitation Use of resistant varieties Crop rotation Page 28 of 110 Pest Recommended management practices Vermin’s Mole rats (Tachyoryctes splendens) Kiswahili name: fuko Planting of repellent species, such as Tephrosia, tobacco, onion, garlic and Mexican marigold in the field and its boundaries Insert pars of repellent plant species into tunnels Monkeys, wild pigs Local scaring Source: MAFS: Plant Pests Field Book: A guide to management, 2002; LZARDI-Ukiriguru, 2000 4.2 CASH CROPS The major cash and export crops grown in the target project areas include coffee, cotton, cashew, tea, sisal and tobacco. Coffee, cotton, cashew and tobacco are largely small holder crops. The cash crops have special agro-ecological requirements and therefore are grown in specific zones and areas within the Corridor. Similarly, the pest pressure and management tactics recommended for the crop varies between zones. Coffee In Tanzania coffee is one of main export crops and leading foreign exchange earner. It accounts for about 20% of total domestic export. It is predominantly a small scale crop grown by about 420,000 farmers who produce over 90% of the crop and depend on it for their income and hence social welfare (Nyange 1999). There are two major types of coffee grown in the country. Arabica coffee (Coffee arabica) is grown in all coffee zones (Northern, S. Highlands, Lake and Eastern) while the robusta coffee (Coffee canefora) is mainly grown in Kagera with small amounts in Tanga and Morogoro regions. ). According to Basic Data Agriculture Sector 1996/97-2002/2003 MAFS 2004), it was estimated that overall production in the country was 52,220 and 53,220 in 1997 and 2003 tons respectively. Coffee production for mild, hard arabica and robusta was 29,835, 2,383 and 17,184 tonnes in 2002/2002. Moreover, the bulk of the crop is grown in the northern zone. Coffee insects and other coffee pests are some of the major factors that undermine coffee productivity by direct reduction of crop yield and quality to coffee growers. There are about 850 species of insect pest known (Le Pelly 1973). In Tanzania there are more than 25 insect pests which attach coffee and pests of economic importance. Arabica coffee is much affected by pests, of which the most important species Antesia bug and white stem borer. Of less importance are leaf miner, coffee berry moth, scale insects, mealy bugs, coffee berry borer and rood-knot nematodes. Table 4.12: Coffee pest problems and recommended management practices Zone Pest Recommended management practices Ruvuma sub-zone Insects Antestia bugs (Antestiopsis spp.) Pruning Mbuni stripping Apply recommended insecticides at recommended dosage if necessary Page 29 of 110 Zone Pest Recommended management practices White stem borer and yellow headed stem borer Sanitation and crop hygiene Stem cleaning Mechanical (hook the larvae out if possible) Mealybugs and scale insects Proper planting depth Build the plant "skirt" soon after the first harvest to deter ants from climbing through branches to enhance build up of natural enemies Diseases CBD & CLR Management as for the northern zone Fusarium wilt Plant recommended tolerant varieties e.g. KP 423 (locally known as "nylon" Field sanitation Proper pruning Weeds All types Clean hand weeding Apply herbicide if necessary. Use recommended herbicides (Table 4.13) Southern Highlands Insects As for Ruvuma sub-zone As for Ruvuma sub-zone Diseases CBD & CLR As for northern zone Fusarium wilt Plant recommended varieties e.g. N36, which should be obtained from certified seed multiplication farms only. Field sanitation Maintain good drainage Uproot and burn any diseased plants and avoid replanting in the same hole for 2 years Source: MAFS: Plant Pests Field Book: A guide to management, 2003; LZARDI-Ukiriguru 2000; IPM working group in the Northern Zone 2001 Table 4.13: List of recommended pesticides for use in coffee Chemical Chemical common name Formulation Lts product/ha Comments Insecticides Diazinon 600EW 1.0 -1.5 Deltamethrin 25%EC 0.5 Chlorpyrifos 4 EC 1.25-2.0 Carbofuran 5%G 60gm/plant Spread the granules around the plant when the soil is wet and rake it into the soil Page 30 of 110 Chemical Chemical common name Formulation Lts product/ha Comments Fenitrothion 50%EC 1.0 -2.0 Profenophos 720EC 0.2 - 0.7 Endosulfan 35%EC 1.0 - 1.5 Fungicides Cyproconazole 100SL 1.0 - 2.0 kg Hexaconazole 5% FL 25-100ml/100l of water CLR Triadimefon 25%EC 1.0 CLR Propineb 25%EC 1.0kg CLR chlorothalonil 50% FW 2.0 - 5.0 CBD & CLR W75 4.5 CBD & CLR 54%FW 4.5 CLR Cupric hydroxide 50WP 7.0 - 8.0kg CBD Cuprous oxide 50WP CBD & CLR Copper oxychloride 50WP 7.0 - 8.0 kg CDB & CLR Herbicides Gyphosate 36% SC 3-6l/ha All types, post emergence Paraquat 20%EC 1-3l/ha All types, post emergence Notes: 1. All pesticides except carbofuran are applied with a knapsack sprayer. 2. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt Cotton Cotton in Tanzania is purely a smallholder crop. The crop is grown in two major zones based on agro- ecological difference. The western cotton growing area (WCGA) include Mwanza, Shinyanga, Mara, Kigoma, Tabora, parts of Kagera, Singida and Kigoma regions, while the eastern cotton growing areas [ECGA] cover Morogoro, parts of Kilimanjaro, Coast and Iringa regions. According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it was estimated that overall production of cotton was 221,280 and 188,200 tons in 1997 and 2003 respectively. Similar to coffee, the pest problems and the recommended management options vary depending on location (Tables 4.14, 4.15 & 4.16). The recommended current cotton pest management strategies emphasises integration of several aspects of IPM (Tables 4.14 & 4.15). However not all farmers in all the cotton growing areas are aware and informed about the approaches. Page 31 of 110 A cotton quarantine established in 1946 (Cotton plant quarantine GN 265 of 1946: quarantine areas: Southern Province) is meant to prevent the entry of the red bollworm (Diparopsis castanea) from the neighbouring countries in the south (Malawi, Zambia & Mozambique) to the major traditional cotton area (the WCGA & ECGA). The quarantine has been effective in preventing the entry of the pest in the cotton area to date, and must therefore be maintained. Any attempt to grow cotton in the quarantine area should therefore be strongly discouraged. Should the pest enter the traditional cotton areas, the pest management strategies must be changed, and will probably lead to more use of pesticides, increased health and environmental problems in the traditional cotton growing areas. Crop scouting (regular crop inspection) was recommended in the late 1980s as another IPM component to optimise insecticide cotton spraying in the WCGA. However, to date, only a few farmers in Shinyanga, Kagera and Mara regions practice it. Only the IPM farmer groups and their immediate neighbours practice crop scouting before spraying. It is important to recognise that scouting for a pest is a prerequisite for good crop pest management and judicious use of pesticides. There is therefore a need to mobilise farmers through appropriate training, to inform and enhance wider use of regular crop inspection as a means to optimise the benefits of pesticide use if they have to be used. Crop scouting guidelines have not yet been developed for the ECGA but the approach developed for the WCGA could be tested and fine-tuned by farmers for adoption. Traditionally, spraying against aphids in the WCGA was discouraged for two major reasons. First, it is not economically justified in most seasons. Secondly, aphids are usually controlled by a wide range of its indigenous natural enemies (predators and parasitoids) that builds up in the crop early in the season. In addition, the aphid populations are often washed away by the heavy rains in March/April. Occasionally, the population can build up to damaging levels (resulting to sooty mould, which can damage the quality of the crop). When this occurs, insecticides recommended for the bollworms can be used effectively. The indigenous aphid natural enemies are polyphagous and will also feed on the eggs and larvae of H. armigera, the key pest of cotton in the area. Insecticide mixtures e.g. profenophos + cypermethrin (Table 4.14) were discouraged to safeguard and promote the build up of the natural enemies to further extend integration of bio-control agents in the cotton systems. Table 4.14: Cotton pest problems and recommended management practices in the WCGA Pest Recommended management practices Insects Jassids (Empoasca sp) Plant recommended UK varieties (resistant plant varieties) Spray in case of a severe attack at seedling stage American bollworm (Helicoverpa armigera) The host plants should be inspected regularly Souting Encourage natural enemies Use botanical pesticides like neem and Utupa Plant recommended UK varieties (inditerminant varieties) Early planting Spray with recommended insecticides after scouting (Table 3.13) Page 32 of 110 Pest Recommended management practices Aphids (Aphis gossypii) No spraying. Encourage build up of natural enemies like birds Populations often washed off by rain Spiny bollworm (Earias insulana and E.biplaga) The host plants should be inspected regularly Scouting Encourage natural enemies like birds Use botanical pesticides like neem and Utupa Early planting Lygus (Lygus vosseleri) Spray with insecticides in case of an early season attack Cotton stainers (Dysdercus spp) Observe the close season Early and frequent picking avoid build-up of stainers Sanitation in and around cotton ginneries and buying posts Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Blue bugs (Calidea dregii) Observe the close season Early and frequent picking avoid build-up of stainers Sanitation in and around cotton ginneries and buying posts Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Diseases Bacterial blight (Xanthomonas malvacearum) Rotation Plant recommended UK 82 varieties (resistant plant varieties) Observe the close season Crop sanitation Fusarium wilt (Fusarium oxysporum f.sp. vasinfectum) Rotation Crop sanitation Plant recommended UK 77 or 91 varieties (resistant plant varieties) Alternaria leafspot (Alternaria macrospora) Rotation Field sanitation Page 33 of 110 Pest Recommended management practices Weeds All types (See Table 3.4) Proper land preparation Early clean weeding Use recommended herbicides (Table 12) Vermines Field rats, monkeys and baboons Scaring Trapping Source: MAFS: Plant Pests Field Book: A guide to management, 2003; LZARDI-Ukiriguru 2000 Table 4.15: List of pesticides recommended for use on cotton in the WCGA Chemical Chemical common name Formulation Application rate g a.i./ha Comments Insecticides Endosulfan 25% ULV 625 Cypermethrin 1.8% ULV 45 Fenvalerate 3% ULV 75 Flucythrinate 1.7% ULV 42.5 Lambda cyhalothrin 0.6% ULV 15 Esfenvalerate 0.5% ULV 12.5 Alpha cypermethrin 0.8% ULV 20 Biphenthrin 2%ULV 50 Betacyfluthrin 0.5%ULV 12.5 *Profenofos + cypermethrin 1% + 16% ULV 400+ 25 *Deltamethrin + dimethoate 0.3+ 12 % ULV 7.5 + 300 Flucythrinate 1.33% Me/ULV 33.25 Fungicides Bronopol 10% dust 5/100kg Cuprous oxide 45% dust 5/100kg Herbicides Diuron 80W 1000 For use on light soils only Fluometuron 500FW 2000 For use in light soils only Metalachlor + Dipropetrin 400EC 800+1200 For use in light soils only Page 34 of 110 Notes: All the insecticides are applied using ULV pumps at the rate of 2.5l/ha at a swath width of 4.5 meters. The target pest is the American bollworm and farmers are advised to scout the crop starting from when the first buds are formed or 10 weeks after planting until first boll split before spraying. Early season (before first flower) spraying is strongly discouraged, as this will interfere with the build up of indigenous natural enemies of aphids and the bollworms. All herbicides should be applied pre-emergence. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt *These pesticides are unnecessary for the WCGA as continued use will jeopardise conservation and use on natural bio-control in the cropping system. Table 4.16: Cotton pest problems and recommended management practices in the ECGA Pest Recommended management practices Insects Jassids (Empoasca sp) Plant recommended IL varieties (resistant plant varieties) Spray in case of a severe attack at seedling stage American bollworm (Helicoverpa armigera) Plant recommended IL varieties Early planting Aphids (Aphis gossypii) Spray using recommended insecticides (Table 14) Cotton stainers (Dysdercus spp) Observe the close season (mid-September to early November) Early frequent picking Apply 1 to 2 sprays of recommended insecticides if necessary (inspect the crop before spraying) Sanitation in and around cotton ginneries and buying posts Pink bollworm (Pectinophora gossypiella) Early planting and early picking Close season Diseases Bacterial blight (Xanthomonas malvacearum) Plant recommended IL varieties (resistant varieties) Observe close season Alternaria leafspot (Alternaria macrospora) Plant dressed seed only (Table 14) Weeds All types see Table 3.4 Cultural control Good land preparation Early hand weeding Use recommended herbicides (Table 14) Page 35 of 110 Table 4.17: List of pesticides recommended for use on cotton in the ECGA Chemical Chemical common name Formulation Application rate g a.i./ha Lts product/ha Comments Insecticides Cypermethrin 1.8% ULV 45 2.5 Cypermethrin 10%EC 45 0.45 Fenvalerate 20% EC 75 0.375 Flucythrinate 10% EC 42.5 0.425 Lambda cyhalothrin 0.6% ULV 15 2.5 5% EC 20 0.4 Esfenvalerate 2.5% EC 20 0.8 Deltamethrin 0.3% ULV 7.5 2.5 0.5% ULV 12.5 2.5 2.5%EC 7.5 0.2 Fluvalinate 2%EC 100 0.2 Fungicides Bronopol 10% dust 5/100kg Cuprous oxide 45% dust 5/100kg Herbicides Fluometuron 500W 2500-3000 3500 5.0 - 6.0 7.0 Light and medium soils Heavy soils Notes: The herbicides should be applied pre-emergence only. All ULV formulations are applied using the ULV pump at a swath width of 4.5 m. Spraying is done once a week beginning 8 weeks after planting and should continue until boll split. All the EC formulations are applied by knapsack sprayers at the rate of 120l/ha The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt Cashewnuts In the southern zone widespread planting of cashew was carried out after 1945 and in a relatively short period of time, it developed into an important cash crop for smallholders. It appears that expansion first started on the Western Makonde Plateau and then spread northwards into Lindi and Coast regions and eastwards into Ruvuma. Cashew is mostly grown on poor soils in the coastal districts and the south of the country; Mtwara, Lindi and Ruvuma produce about 70% of the crop. By 1960, the region gave 40,000 tonnes of nuts which were being exported and it had become Tanzania’s fourth most valuable export. Production continued to increase and reached a peak of 145,000 tonnes in 1973/4. From the peak year there was a catastrophic decline in production to a low of 16,500 tonnes in 1986/7. Some of the reasons for such a dramatic fall in production were due to a complex of socio-economic and biological factors (Brown, et. al. 1984). The biological factors which are relevant in the context of this report: The onset of powdery mildew disease (Oidium anacardii Noack) Overcrowding of trees According to Basic Data Agriculture Sector 1996/97-2002/2003 (MAFS 2004), it was estimated overall production of cashewnuts was 65,400 and 92,200 in 1997 and 2003 respectively. Powder mildew disease (PMD) Oldium anacardii Page 36 of 110 The most serious biological constraint to cashew production in East and Southern Africa is powdery mildew disease, Oldium anacardii. In East Africa, PMD develops on young growing tissue, e.g. new shoots with tender leaves, panicles from the very young to the mature, apples and young nuts. The infected parts look as though they are covered in a white/grey powder. Severely infected young leaves change colour from green to brown, become deformed and eventually drop off prematurely. Mature, older leaves, with a well-developed cucile, are not attached. Prior to early 1970’s, PMP was not a problem in East and Southern Africa. It was first officially reported in Tanzania and for that matter, Africa, in 1979 (Casuli 1979). PMD was one of the factors responsible for the catastrophic decline in cashew production with tool place in Tanzania from 1973 to 1986. A range of different control measures against PMD were developed by research, to try and cater for different farmer types and address various environmental concerns. Very fine sulphur dust (usually 99% pure) has been used in Tanzania for more than 15 years to control PMD; the dust is blown on the trees using motorized blowers. However, only 22% of the dust is deposited on the tree and if dew is absent at the time of application, the percentage deposited on the tree drops off dramatically (Smith at.al1995). Most of sulphur ends up on the soil, where in the longer term, it has caused soil acidification in various parties on the Makonde plateau in Mtwara region (Ngatunga, 2001). Other diseases but of less economic importance in Tanzania include anthracnose (Colletrotrichum gloeosporides Penz), dieback (Phomopsis anacardii Punith), cercospora leaf spot (Pseudocercospora anacardii Nova), pestalotia leaf spot (Pestalotia hetercornis Guba) and wilting syndrome which causes shedding of leaves and sometimes death, is a minor, sporadic problems (Sijaona 1997). Sucking Pests (Helopeltis and Pseudotheraptus) The sucking pests Helopeltis and Pseudotheraptus Miller (Hemiptera: Miridae), H. schoutedenii Reuter and Pseudotheraptus way (Hemiptra: Corediae) are the main insect pests of cashew in East Africa. Sucking pest damage can be very variable from year to year and place and place. In Tanzania, Helopetis populations tend to build up on cashew from May/June to September/Octover, coincind with the period of leaf flush and panicle development (Topper 1998). Sucking pest leaf damage can stake the form of black lesions on petioles or on the leaf midrib, or black angular spots on the leaf surface. The presence of the weaver ant, Oecophyla longinoda (Hymenoptera: Fromicidae) has been shown to have a significant effect in reducing sucking pest damage. It is possible to assist these predators in colonising new trees and thereby enhance their capacity for control of sucking pests. Other less important insect pests are trunk borer (Mecocorynus loripes, Coleoptera, Curculionidae) – the larvae of this large weevil bore through the sapwood of branches and trunks, which result in the death of the infected part of the whole tree. This is the main cash crop of the southern zone and along the coast in the eastern zone. The pest problems and respective recommended management approaches are similar in all cashew-growing areas. Although the current pest management options advocate use of IPM approaches (Table 3.14), there is evidence to show that there is an increase in insect pest pressure due to excessive use of sulphur to control powdery mildew (Anon, 2000). Alternative pesticides have been identified and registered since 1994 (Anon, 2000) but the new products have not yet been popularised among growers. Education and mobilisation of farmers is needed to promote wide adoption and use of the recommended disease tolerant/resistant clones and cultural practices (Table 15) to reduce over reliance on chemical pesticides (Table 4.17) for the control of the major diseases. Table 4.18: Major pests and recommended management practices in cashew Page 37 of 110 Pest Recommended management practices Insects Coreid bugs (Pseudotheraptus wayi) Biological control using the African weaver ant (Oecophilla longinoda). T o enhance effectiveness of the bio-control agents, farmers are advised to do the following: 1- Apply Hydramethyl to control Brown house ants (Pheidole megasephala) when necessary 2- Interplant coconut with recommended suitable host trees of weaver ants 3- Construct artificial aerial bridges to facilitate mobility of weaver ants between trees 4- Plant weaver ant nests in areas where they do not occur naturally Apply recommended insecticide at recommended dosage (Table 16) in case of severe outbreaks Holopetlis bugs (Helopeltis anacardi) Kiswahili name: Mbu wa mikorosho Biological control using the African weaver ant (Oecophilla longinoda). (Maji Moto) Not intercropping pigeon pea with cashew Apply recommended insecticide at recommended dosage (Table 16) in case of severe outbreaks Cashew mealybugs (Pseudococcus longispinus) Crop sanitation (removal & proper disposal of affected plant parts) Biological control Thrips (Selenothrips rubrocinctus) Control should mainly target larvae stage during early stages of flowering Stem borers, Weevils, (Mecocorynus loripes) Adults should be collected and destroyed by hand Mechanical, using a recommended hooks If the tree is severely attacked, cut and dispose properly Diseases Powdery mildew (Oidium anacardii) Prune to provide good ventilation and aeration within trees making microclimate not conducive to the pathogen multiplication Scouting For established plantations, practice selective thinning Remove off-season young shoots which can be sources of fresh innoculum during the season Sanitation Thin densely populated trees and leave them well spaced, to reduce or delay mildew epidemic due to changes in microclimate in the field Plant recommended tolerant clones e.g. AC4, AC10/220, AZA2 and at recommended spacing Apply recommended fungicides as appropriate (Table 16) Anthracnose (Colletotrichum gloeosporioides) Remove and burning of all infected organs before the start of the cashew season. Plant recommended tolerant clones e.g. AC4, AC10/220, AZA2 and at recommended spacing Apply at recommended pesticide at correct rate and time (Table 16) Dieback (Phonopsis anacardii) Remove and burning of all infected organs before the start of the cashew season. Apply at recommended pesticide at correct rate and time (Table 16) Wilt syndrome Source: MAFS: Plant Pests Field Book: A guide to management, 2003; Topper, et, al, 2003 Page 38 of 110 Table 4.19: Pesticides recommended for use on cashew Chemical Chemical common name Formulation Application rate Target pest Comments Insecticide Fenitrothion 50% EC 17ml/tree Thrips Profenofos 48%EC Cashew mealybugs lambda cyhalothrin 5%EC 5ml in 1 l of water per tree Helopeltis & Coreid bugs Hydamethyl Brown house ants (Table 11) Fungicides Sulphur D 250gm/tree Powdery mildew Apply with motorised blower Hexaconazole 5%FL 10-15 ml in 0.75 - 1.25 l of water, three sprays at 21 days interval Penconazole 10%EC Triadimenol 25%EC Copper hydroxide 50%WP Anthracnose Note: 1. All the pesticides except for sulphur, are applied using a knapsack sprayer or with a mist blower (Sijaona, & Anthony, 1998; Sijaona & Barbanas, 1998) 2. The list of pesticides can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt. 4.3 HORTICULTURAL CROPS A wide range of horticultural crops are grown in Tanzania (Table 4.1). However, the sub-sector is still under developed and poorly exploited for several main reasons. First, the resources allocated for research and development to the sub sector has always been inadequate. At the national level, the sub sector has been accorded only medium to low priority. IPM research on vegetable and fruit crops has a very low profile as reflected by the state of inadequate funding for research and development as well as lack of staff continuity in the sub sector. On-going research activities are patchy and uncoordinated. Consequently, local information on appropriate pest management tactics for the major horticultural crops is scanty except for coconut and tomatoes. The coconut programme based at ARI Mikocheni has done commendable work by developing appropriate IPM approaches for coconut cropping systems that can be extended to farming communities in the coconut growing areas (Table 4.17). Effort to improve tomato production through breeding and selection for tolerance and/or resistance to key pests, particularly diseases, in the country has been facilitated by the AVRDC Arusha station beginning in 1994. For the majority of crops, e.g. mangoes, farmers are experimenting with borrowed ideas and fine-tuning them to solve pertinent pest problems. The cut flower industry, which is a domain of large-scale growers, operates independent of the national system, and therefore, each grower has in-house capacity and capability to address pest problems. Coconuts Coconut production is basically a smallholder crop largely confined to the coastal belt from Tanga to Mtwara, mostly in Eastern and Southern regions. The agro-ecological conditions and the management practices of the crop are similar in all the growing areas and therefore, the pest problems and recommended control options are the same (Table 4.17). Page 39 of 110 The research and development programme at ARI Mikocheni through support by the GTZ, has developed and formulated appropriate farmer friendly IPM approaches for the coconut cropping system. However, extension of the knowledge to farmers has been hampered by a lack of adequate funding. Table 4.20: Major pests and recommended control practices for coconut Pest Recommended management practices Insects Coreid bugs (Pseudotheraptus wayi) Biological control using the African weaver ant (Oecophilla longinoda). To enhance the effectiveness of the weaver ants, farmers are advised to do the following: 1- Apply Hydramethyl to control brown house ants (Pheidole megasephala) when necessary 2- Interplant coconut with recommended suitable host trees of weaver ants 3- Construct artificial aerial bridges to facilitate mobility of weaver ants between trees 4- Plant weaver ant nests in areas where they do not occur naturally African rhinoceros beetle (Orytes monoceros) Cultural removal of breeding sites of the pest Mechanical, using recommended hooks Coconut mites (Aceria guerreronis) This is a new pest and therefore no control measures available Coconut termites (Macrotermes spp.) For species living above ground, the termitarium can be destroyed physically Apply recommended insecticides at the recommended dosage rates Diseases Lethal Disease caused by phytoplasma Plant recommended tolerant/resistant varieties. E.g. East African Tall sub populations Proper destruction of diseased plants Avoid movement of seedlings from infested to non infested areas Location specific replanting Source: Source: MAFS: Plant Pests Field Book: A guide to management, 2003 The only pesticide recommended for use on coconut is hydramethyl for the control of the brown house ants, which interfere with the effectiveness of the weaver ants. Mango Mangoes are grown for the local and export market, mostly as a smallholder crop. Despite its popularity, there has been limited research on its major pest problems and producers develop pest control tactics on a need basis (Table 4.18). Therefore, much need to be done to improve the crop, and also to address the key pest problems as summarised below. Table 4.21: Key pests of mangoes and current farmer practices to reduce losses Pest Farmer practices Insects Fruit flies (Ceratitis spp) Harvest as much fruit as possible; sort out the edible fruit and bury all those that are infested Apply chlorpyrifos when necessary Use toxic bait sprays e.g. yeast products mixed with malathion or fenthion around the tree base Removal of infested fruits and proper disposal (collect and bury Page 40 of 110 Pest Farmer practices at least 10 feet deep) Mango weevils (Sternochetus mangifera) Removal of infested fruits at least twice a week and proper disposal (collect and bury at least 10 feet deep) Selected less sucsceptibe varieties , such as Ngowe, Kitovu or Boribo Maintain field sanitation at the end of the season by clearing all seeds under the tree canopy Mango mealybug Spray contact/systemic insecticides Control of attendant ants to reduce spread of the pest Diseases Mango anthracnose (Colletratrichum gloesporiodes) Apply available registered fungicides Proper pruning to reduce excessive and minimise disease build- up Use the recommended post-harvesting treatment Powdery mildew (Oidium spp) Apply recommended fungicides Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Citrus Like mangoes, citrus fruits are produced for the local and export markets but resources allocated for research and development are insufficient and therefore, the pest management strategies used by farmers to date have been borrowed from elsewhere and fine-tuned for local use on a need basis. Table 19 is a summary of the key pest problems and some of the available management options. The biological control of the woolly whitefly, which is a new pest of citrus in Africa south of Sahara, is a recent good example. The programme, a collaborative initiative between PHS and GTZ-IPM, was embarked on after promising results were reported in Uganda and Kenya where successful initial releases were done. The biological control of the citrus black flies is a spill-over from releases done on the Kenya coast in the 1970s. The efficacy of this bio-control agent has to be facilitated by controlling the attendant ants, which facilitate the spread of the pest and also interfere with the efficacy of the wasps (Dr. Z. Seguni, personal communication). Farmers in the coconut and cashew cropping systems can benefit from the technology already developed for the management of attendant ants on respective crops. Overall, local information on sustainable management of citrus, particularly pest problems, are lacking (Table 4.22). Adequate resources must be allocated to enhance development and promotion of the crop. Table 4.22: Major pest problems of citrus and recommended management practices Pest Recommended management practices Insects Scale insects Normally ants protect aphids against natural enemies Mealybugs (Planococus citri-Risso) Trees with dead brown leaves should be uprooted and replaced Aphids (Toxptera citricidus) Normally ants protect aphids against natural enemies Page 41 of 110 Pest Recommended management practices False codling moth (Cryptophlebia leucotrata) Field sanitation (collect all fallen fruits and bury them at least 50 cm deep) Remove wild castor (“Mbarika”) around the orchard Orange dog (Pappilio demodercus) Regular scouting and hand picking of caterpillars Apply contact insecticides in case of a severe attack The wooly white fly (Aleurothrixus flocossus) Biological control using imported parasitic wasps Management of attendant ants to reduce spread and facilitate the efficacy of natural bio-control agents Black flies (Aleurocanthus sp) Management of attendant ants to reduce spread and facilitate the efficacy of natural bio-control agents Giant coreid bug (Anoplenemis curvipes) New pest but farmers are encouraged to introduce and enhance the activity of weaver ants (refer to cashew & coconut approach) Citrus leafminer Crop sanitation and mulching Apply recommended systemic insecticides when necessary Diseases Greening disease (Liberobacter africana) Propogation of disease free planting materials Eliminate all infested trees Strict quarantine measures Natural enemies Hymenopterous chalcids such as Tetrastichus spp and Diaphorencytrus aligarhenses Use clean planting material Good plant nutrition Gummosis (Phytophthora spp) Budded at least 20cm from ground should be chosen Cut infected trees Affected orchards should not be excessively irrigated Tristeza (Virus localized in phlorm tissue) Use disease free budwood Green moulds (Pencillium italicum) Handle fruit carefully to reduce skin injury Treat bruches, graders, etc Use the recommended post harvesting treatment Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Pineapple Pineapples are largely grown for the domestic market and have few known major pest problems in Tanzania. These include the pineapple mealybugs (Dysmicoccus brevipes & D. neobrevipes and pineapple wilt disease, which are transmitted by Dysmicoccus brevipes. The recommended pest management tactics therefore target the control of Dysmicoccus brevipes, the vector. The only viable approach is through effective management of attendant ants to reduce spread and build up of mealybugs in the crop. Table 4.23: Major pest problems of pineapples and recommended management practices Pest Recommended management practices Mealybugs (Pseodococcus brevipes) Use clean planting materials Trees with dead brown leaves should be uprooted and replaced Diseases Top and root rot (Phytophthora spp) Use well-drained soils from pineapple growing Plant on raised beds at least 23 cm high after settling Provide drainage system to get rid of excess water without causing soil erosion Deep-trip down the slope before hilling if subsurface soil compaction is evident Source: MAFS: Plant Pests Field Book: A guide to management, 2002 Tomato Page 42 of 110 Tomato is most important horticultural crop, grown by almost all small farmers in northern and southern Tanzania. There are two types of tomatoes grown in Tanzania. These are the tall or intermediate varieties e.g. Money maker and Maglobe, and the dwarf varieties e.g. Roma Vf and Tanya. Both types are grown across the country although consumer preference also influences local production. Tomatoes are grown for cash and domestic use mostly by women and youths in Kilimanjaro, Arusha, Tanga, Iringa, Dodoma, Mbeya, Morogoro and Mwanza regions. It is also important for local processing, with processing plants in Iringa and Arusha. Some of the products from these plants are sold on the local market while the bulk is exported. In some areas, e.g. in the northern zone, more resources are invested in tomato production than in coffee production because tomatoes gives better and fast returns (personal observation). Farmers use fungicide or insecticide available at the rural markets and often do not respect proper timing and dosage instructions. Moreover, they do not wear protective gear when applying the chemicals and do not use the proper equipment (e.g. application by using naps in stead of sprayers). Tomato production is seriously hampered by diseases, i.e. late blight, yellow leaf curl virus, powdery mildew and various wilts. The yellow leaf curl virus is transmitted by white flies, while late blight is caused by the Phytophthora infestans air borne fungus. Powdery mildew is a result of infestation by the obligate parasite Oidium lycopersici. Yellow leaf curl virus results in stunted plants with chlorotic leaves. Late blight causes leaf lesions and rotting of affected fruits. Powdery mildew causes discoloration of foliage that eventually dies. Year round cultivation of tomatoes without proper rotation is one of the major causes of the spread of these diseases. Later blight and bacterial spot develop under moist conditions, while dry weather conditions are favourable to yellow leaf curl virus and powdery mildew. Cultural practices, such as rotation and field hygiene, can be applied to reduce the effect of the diseases. Botanicals, such as Tephrosia, Neem and Mexican marigold, should be tested on their effect on white flies. New, tolerant tomato varieties may contribute to the IPM control of the diseases. Farmer Field Schools would be effective tools to improve farmers’ knowledge about the diseases and their IPM control. A specific category of diseases affecting tomato nurseries are damping of pathogens, such as Pythium, Fusarium, Rhizoctonia, Phytophthora and Alternaria. These pathogens cause damping off, wilting and rotting of the nursery plants. The spread of the rot fungi is enhanced by excessive moisture, continuous cultivation of tomatoes and the presence of volunteer plants. Seedbed hygiene (sterilization by fire or polythene sheets, removal of crop debris, rotation) is the best IPM control measure that should be promoted amongst tomato growers. Various species of root-knot nematodes and red spider mites are among the major pests affecting tomato yield. Red spider mites are sucking insects that appear under dry weather conditions. Root-knot nematodes damage plants by devitalizing root tips and either stopping their growth or causing excessive root production and root are swelling. Major causes to both pests are lack of rotation or fallow and year round cultivation of tomatoes. Root-knot nematodes can be controlled by cultural practices, such as field sanitation, deep ploughing, and the use of clean planting materials and tolerant or resistant varieties. Red spider mites may also be controlled by botanicals, such as Mexican marigold, Tephrosia and Neem. However, the effect of these botanicals has to be confirmed. Farmers must be informed of the currently recommended control measures, including safe handling of chemicals. Page 43 of 110 Table 4.24: Major pests of tomatoes and recommended management practices for northern zone Pest Recommended management practices Insects American bollworm (Helicoverpa armigera) Destroy infected crop residues and fruit after harvesting Encourage natural enemies (parasites, ants, Anghocorid-bugs and egg predators) Use maize ads a trap crop (timing of crop stage; tasseling stage coincides with attack) Inspect the crop regularly for new infestations Use botanicals like Neem extract Apply recommended insecticides at recommended dosage rate Cutworms (Agrotis spp) Early ploughing to expose cutworms to predators Apply wood ash around plants Inspect the crop regularly soon after transplanting because this is the most susceptible stage of the crop Mechanical (hand collect and crush them) Use appropriate trapping methods. Crush the caterpillars or feed them to chicken Use repellent botanicals Spray with recommended insecticide if necessary (Table 21) Nematodes Root knot nematodes (Meloidogyne) Kiswahili: Mnyauko nyanya Optima rotation and fallow Deep ploughing Avoid contaminated water Plant tolerant/resistant varieties Sterilise the seedbed before sowing Avoid planting a new crop on infested areas Mites Red spider mites (Tetranychus spp) Kiswahili name: Utitiri wekundu Rogue infected plants Avoid dusty conditions during extreme dry season Encourage moist microclimate by frequent irrigation Hedge planting to reduce dust, invasion by mites blown by wind Encourage natural enemies by mulching and hedging Use neem as alternative sprays Observe recommended time of planting Application of irrigation Plant tolerant/resistant varieties e.g. ARP 367-2 or Rossol Sanitation and crop hygiene Use healthy planting material Frequent weeding Inspect the crop regularly for new infestations Use neem oil with cow urine (mfori) Apply a recommended miticide if necessary (Table 21) Page 44 of 110 Pest Recommended management practices Diseases Late blight (Phytophthora infestants) Kiswahili name: Baka jani chelewa Regular crop scouting to detect early attack Field sanitation after harvest by removal of infected plant parts Crop rotation Avoid moist microclimate at shady places Use wide spacing (wet season) Observe recommended time of planting Plant at correct spacing Shade management Decrease humidity through pruning, desuckering, staking and weeding Avoiding the humid season and mulch to avoid rain splash causing infections Early blight (Alternaria solani) Remove infected plants staring from nursery Weed out Solanacea plants Try botanicals and other natural pesticides Observe recommended time of planting Regular crop scouting to detect early attack Apply recommended fungicide if necessary Powdery mildew (Oidium lycopersicum) Sanitation , remove infested leaves and plants Practice crop rotation Use botanical and other natural pesticides Regular crop scouting to detect early attack Apply recommended fungicide if necessary (Table 21) Bacterial wilt (Pseudomonas solanacearum) Practice good crop rotation Practice deep ploughing/post harvesting cultivation to expose soil to sun Add organic matter to the soil (cow dung, mulch, green manure) Rogue affected crops and weed-hosts, destroy or bury outside the field Avoid transferring infested soil including soil on roots of plants Do not irrigate with contaminated water from infested areas Choose seedbed in clean uninfected area Page 45 of 110 Pest Recommended management practices Fusarium wilt (Fusarium oxysporum) Kiswahili: Mnyauko nyanya Use resistant varieties (like Tengeru 97) are the best practical measure to manage the disease in the field. Tengeru 97 is resistant to both fusarim wilt races 1 and 2 Practice good crop rotation Sanitation and crop hygiene Deep ploughing Avoid transferring infested soil including soil on roots of plants Do not irrigate with contaminated water from infested areas Add organic matter to the soil (cow dung, mulch, green manure) Bactoria spot (Xanthomonas compestris pv. Vesicatoria) Kiswahili name: Madoa bakteria Use clean seed Three year crop rotation Avoid working in fields under wet conditions Avoiding of injuries to fruits Tomato yellow leaf curl (TYLC)-virus transmitted by whitefly (Bemisia tabaci) Kiswahili names: Rasta, Ngumi, Bondia Use disease free planting materials Time of planting Scouting of the disease and removal of affected plants Intercrop with onion. This also reduces aphids in tomatoes Intercrop with eggplants as traps to draw whiteflies away from less tolant and virus prone crops like tomatoes Use repellent botanicals, such as Tephrosia and Mexican marigold Regular crop scouting to detect early attack Good management of irrigation water Remove and destroy crop residues immediately after the final harvest Avoid planting Lantana camara near tomatoes Encourage beneficial insects, such as Encasis Spray if necessary but use recommended insecticides (Table 21) Source: MAFS: Plant Pests Field Book: A guide to management, 2003, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Table 4.25: List of pesticides recommended for use on tomatoes Chemical Chemical common name Formulation Application rate Target pest Comments Insecticides Pirimiphos methyl 50%EC fruit worms Profenofos 72%EC Whitefly Miticide Azocyclotin 25%WP Red spider mites Registered for use on greenhouse roses for spider mite control Page 46 of 110 Chemical Chemical common name Formulation Application rate Target pest Comments Fungicides Metalaxyl + mancozeb 7.5% + 56%WP 3.0 to 3.5 kg/ha Early & late blight Mancozeb 80% WP 1.5 to 2.5 kg/ha Chlorothalonil 50%FW 2.0 to 5.0 l/ha Copper hydroxide 50%WP 4.0 to 5.0 kg/ha Source: Paul, Mwaiko & Mwangi, 2000 All pesticides on tomatoes are applied using a knapsack sprayer. The list of pesticides (Table 3.21) can change as new products are recommended and/or some of the chemicals are withdrawn. Therefore always consult the nearest plant protection extension worker if in doubt. Onion Onion cultivation takes place throughout the Northern Zone and the Central Zone, but most production is located in the cooler, higher altitude areas, such as the mountains of Mbulu, Lushoto, Pare and Usambara and the foot slopes of Mount Meru and Mount Kilimanjaro. Most onions are cultivated under irrigation during the dry season. The crop is often grown year after year on the same field without sufficient rotation, a practice that encourages the build-up of pest and disease epidemics. Downy mildew and storage rots are among the most important diseases affecting onions. Downy mildew can be controlled by field sanitation, wide spacing and weed control, rotation and use of tolerant varieties. Storage rots, such as Botrytis, Erwinia, Mucor and Fusarium can be controlled by ventilation and storage of onions on racks, use of polypropylene or netted bamboo baskets, drying of onions before storage and removal of tops. These control measures are applicable by all categories of farmers and can be disseminated through leaflets and brochures. Onion thrips are the most common insect pest affecting onion production. Development of thrips populations is encouraged by insufficient rotation and presence of crop debris. Cultural control measures include deep ploughing, field sanitation, crop rotation, timely planting, mulching and irrigation. Botanicals, such as Neem oil, and other control agents should be identified and tested on their effect on thrips. Information on major pest problems in the central agro-ecological zone is scanty, and therefore Table 4.25 gives a summary of the major pests and respective management options for some parts of the northern zone only. However, these pest management options (Table 4.25) can also be refined and adopted by farmers in other areas. Table 4.26 : Major pest problems and recommended management practices Pest Recommended management practices Insects Onion thrips (Thrips tabaci) Kiswahili name: Vithripi Sanitation Scouting Separate seed bed and field to reduce danger of carrying over thrips from one site to the other Crop rotation Mixed cropping of carrots and onions Observe recommended time of planting Field sanitation and crop hygiene Transplant clean seedlings Mulching reduces thrips infestation considerably Plough deep after the harvest to bury the pupae Irrigation/adequate watering Enhance beneficials (predatory mits, bugs, fungal pathogens like Page 47 of 110 Pest Recommended management practices Metarhizium) Inspect the crop regularly Use botanical extract like Neem oil, Tephrosia, tobacco, etc. Diseases Downy mildew (Peronospora destructor) Kiswahili name: Ubwiri unyoya Use resistant varieties (red creole) and crop rotation for at least five years Sanitation: remove crop remains after harvest, do no leave volunteer plants in the field and avoid over fertilization Wide spacing and good drainage to decrease humidity in the plant stand Apply mulch to avoid rain splash Inspect the crop regularly Purple blotch (Alternaria porri) Sanitation: remove crop remains after harvest, do not leave volunteer plants in the field Crop rotation Mulching to avoid rain splash Plant at recommended spacing Inspect the crop regularly Apply recommended fungicide at correct dosage Storage rots (Bortytis, Erwinia, Mucor, Fusarium) Kiswahili name: Uozo ghalani Use of netted bamboo baskets Avoid heaps exceeding 30 cm depth and use racks of 1m high Ventilated stores Minimize damage during handling Drying of onions before storage Remove tops Avoid thick neck/split Source: MAFS: Plant Pests Field Book: A guide to management, 2002, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Brassicas (cabbages and kale) Cabbages and kale are grown in the cool highlands. It is a valuable relish for urban dwellers where it is used as vegetable salad and as stew to accompany the starchy foods (rice, ugali, cassava etc.). To date, the crop has few major pest problems whenever it is grown in the country (Table 3.23). The crop is mainly grown for income generation. Like tomatoes, farmers apply available chemicals mainly to control insect pests. The most common disease affecting cabbage is black rot. The disease can reduce yield by 90% during the rainy season. Black rot is caused by the Xanthomonas campestris bacteria which are spread by infested seed and through crop debris. Wet warm weather conditions encourage the development of bacteria populations. Cultural control measures, such as deep ploughing, crop rotation and field sanitation considerably reduce the damage by blank rot. Other potential IPM control techniques include seed dressing with Bacillus bacteria, seed treatment with hot water or antibiotics, and resistant varieties. Diamond back moth and cabbage head worm (in lowland areas) are the most devastating insect pests affecting cabbages. The pests may yield by 60% if no control measures are taken. Dry and hot weather conditions and the presence of host plants encourage the insect populations to develop. Farmers apply insecticides or cow dung and urine to control the pests. Application of Neem oil has proven to be effective, while the effect of natural enemies and other botanicals, such as Diadegma, Tephrosia and Annona seeds Page 48 of 110 should be verified. An alternative control agent is Bt-Bacillus thuringiensis. Farmer Field Schools would be helpful instruments in training farmers in pest identification and evaluation of control measures. Few pesticides are recommended for use in the production of cabbages, mainly for insect pest control. However, since cabbage and kale are grown in coffee cropping systems, farmers tend to use pesticides recommended for use on coffee to control brassica pests. Table 4.27: Major pests of brassicas and recommended practices Pest Recommended management practices Insects Diamondback moth (Plutella xylostella) Kiswahili names: Nondo mgono and Almasi Scouting Use botanical and other control agents Observe recommended time of planting Transplant healthy seedlings Inspect the crop regularly to detect early attacks Encourage natural enemies (predatory hoverfly larvae, coccinellids, parasitic wasps) by enhancing diversity Use botanicals (Neem oil, chillies, etc.) Aphids (Brevicoryne brassicae) Sawflies Cabbage webworms Diseases Blackrot (Xanthomonas compestris) Kiswahili name: Uozo mweusi Seed dressing with Bacillus bacteria Seed treatment with hot water Mulching Deep ploughing 3-year crop rotation Field and crop hygiene Transplant only healthy seedlings Plant certified seeds Plant tolerant/resistant varieties like Glory, Amigo FI Sterilise the seed bed before sowing Good drainage, and mulch to avoid infections from rain splash Downy mildew (Peronospora destructor) Kiswahili name: Ubwiri unyoya Practice good crop rotation Observe recommended time of planting Transplant only healthy seedlings Plant at recommended spacing Alternaria leaf spot (Alternatira spp) Avoid overhead irrigation Practice good crop rotation Observe recommended time of planting Transplant only healthy seedlings Plant at recommended spacing Cabbage club rot (Plasmodiaphora brassicae) Crop rotation Plant in well drained soils Adjust soil pH to alkaline by adding hydrated lime Page 49 of 110 Pest Recommended management practices Black rot (Xanthomonos compestris pv. Compestris) Crop rotation Use of pathogen free seeds Avoid overhead irrigation Use of resistance cultivars (Glory FA, Amigo F1) Sanitation: remove crop residues – plough under, compost or feed to animals Good drainage, and mulch to avoid infections from rain splash Cauliflower mosaic virus (CaMV) Remove brassica weeds Rogue young plants showing disease symptoms and immediately burns them Dumpting off (Fusarium Spp, Rhizoctonia spp. Pytium spp and Phytophotra spp) Provide good soil structure and drainage Avoid overwatering Apply wood ash in seedbed Sterilise seedbed Use treated beds Pricking excessive seedlings (thinning) Bacterial soft rot (Erwinia carotovora var. carotovora, Pseudomonas spp) Avoid harvesting when the whether is wet Handle produce carefully and store in cool, well-ventilated areas Plough in crops immediately after harvesting Practice crop rotation and provide good drainage Timely planting to coincide with dry season Source: MAFS: Plant Pests Field Book: A guide to management, 2002, IPM working group in the Northern Zone 2001; LZARDI-Ukiriguru 2000 Deltamethrin 25%EC, diazinon 60% EC and profenopos 72%EC are recommended for use on cabbage and kales but the pesticides are also recommended for use on coffee. Page 50 of 110 4.4 MIGRATORY AND OUTBREAK PESTS The key migratory and outbreak pests of economic significance in Tanzania are armyworm (Spodoptera exempta), birds, notably the Quelea (Quelea quelea spp), the red locust, rodents (particularly the field rats) and the elegant grasshopper (Zenocerus elagans). With an exception of the elegant grasshopper, the management of the rest of the pests under this heading is co-ordinated by the Plant Health Service of the Ministry of Agriculture and Food Security. Rodents Rodents, particularly the multi-mammate shamba rat, (Mastomys natalensis), are major pests of food crops. The most affected crops are maize, millets, paddy and cassava. Virtually all regions are affected with more frequent outbreaks in Lindi, Mtwara, Coast, Tanga, Rukwa (Lake Rukwa valley) and in the cotton areas of Shinyanga regions. Maize is the most susceptible of all the crops. At the pre-harvest stage, maize is attacked at planting (the rodents retrieve sown seeds from the soil causing spatial germination). In some cases, as much as 100% of the seeds are destroyed, this forcing farmers to replant (Anon, 1999). Losses of cereals are usually quite high and are in average about 15%. This loss of cereals could provide enough food for 2.3 of population for a whole year. Annual control costs for rodents are approximately 217 million Tanzanians Shillings (MAFS 2004). Farmers in outbreak areas are strongly advised to do the following (Mwanjabe & Leirs, 1997; Bell, undated) to reduce potential damage to crops and the environment: 1. Regular surveillance. The earlier the presence of rodents is observed, the cheaper and simpler any subsequent action will be and losses will remain negligible 2. Sanitation. It is much easier to notice the presence of rodents if the store is clean and tidy 3. Proofing i.e. making the store rat-proof in order to discourage rodents from entering 4. Trapping. Place the traps in strategic positions 5. Use recommended rodenticide. However, bait poisons should be used only if rats are present. In stores or buildings, use single-dose anticoagulant poisons, preferably as ready-made baits. 6. Encourage team approach for effectiveness. The larger the area managed or controlled with poison, the more effective the impact 7. Predation. Keep cats in stores and homesteads. In the cotton growing areas of Shinyanga, rats are a serious problem in cotton at planting and harvesting. At planting, the rodents pick out the seeds after planting, this leading to uneven germination and poor establishment. At harvesting, the rats feed on the seeds, leaving the farmer with lint only. Through feeding the rats not only reduce the value of the crop but also affect its quality by contamination by faeces and urine. To reduce rat damage on cotton during harvesting, farmers are advised to pick the crop frequently and to sale it immediately after picking. Birds (Quelea quelea spp) Birds are serious migratory pests of cereal crops, namely wheat, rice, sorghum and millet across the country. The quelea birds, which in Tanzania occur are swarms ranging from thousands to a few millions, have been responsible for famines of varying proportions in some areas. In 2001, total loss (100%) in 700 ha of wheat was experienced in Basuto wheat farms, Hanang District (MAFS 2001). Similarly, about 25% loss of rice was experienced on 1125 has in the Lower Moshi Irrigation Rice Project in 1997/8 due to quelea birds (MAFS 1998). Table 3.25 shows quelea invaded regions in 2003. Page 51 of 110 Table 4.29: Quelea Quelea invaded regions year 2003 Year Invaded regions Sprayed Coverage (Ha) Queleatox (l) Number of birds killed January 2003 to December 2003 Arusha Kilimanjaro Dodoma, Mbeya, Singida, Shinyanga, Manyara 2,123.50 7,654 191.8 million Source: MAFS (2004): Basic data agriculture sector 1995/96-2002/2003 Table 4.30: Quelea quelea outbreaks and cereal damage in some regions of Tanzania, 1998-2002 Region Number of hectares destroyed per year 1998 1999 2000 2001 2002 Manyara 320.5 167 0 0 288 Dodoma 145 600 430 186 230 Mbeya 170 522 573 342 190 Mwanza 24 370 110 80 0 Shinyanga 56 0 350 48 357 Singida 150 0 41 194 123 Kilimanjaro 0 102 0 0 0 Mara 0 500 125 0 73 Morogoro 0 254.5 36 202.5 191 Tabora 0 215 663 0 127 Total hectares 865.5 2730.5 2328 1052.5 1579 Source: Ministry of Agriculture and Food Security Report, 1998-2002 Bird pest problems in agriculture have proved difficult to resolve due in large part to the behavioural versatility associated with flocking. The array of food choices available to birds is also complex, hence forth; necessary information is needed for successful control strategies. The total damaged per bird per day, if the bird is exclusively feeding on cereal crops, has been estimated at 8 g (Winkfield, 1989) and 10 g (Elloitt, 1989). The control of migrant pests such as Quelea is a major concern to most farmers and the Ministry of Agriculture and Food Security. Several techniques have been tried to reduce bird populations to levels where crop damage is minimal. Traditional methods, slings, bird scares, and scarecrows, are still being used in many parts. Modern techniques of frightening devices, chemical repellents, less preferred crop varities and alternative cultural practices have been evaluated. All the methods have minimal value in situations where bird pressure is high and where habitation is likely to develop through repetitive repellent use and other methods, which may alleviate damage in small plots or in large fields for a short time. The aerial spraying of chemical (fenthion) on nesting and roosting sites, the most widely used technique to date. Currently, only fenthion 60%ULV aerial formulation is being used. Fenthion is registered under restricted use category such that the pesticide is recommended to be used at the rate of 2.0l/ha. The concerns over possible human health problems and environmental damage resulting from the large- scale application of chemical pesticide for quelea control have let to a proposal for alternative non-lethal control strategy. Chemical pesticide applied for quelea control represent a risk for human, terrestrial, non- target fauna and aquatic ecosystems. The chemical pose risk by directly poisoning or by food contamination/depletion. Among the terrestrial non-target invertebrates, there are beneficial species. Some are responsible for organic matter cycling; others are predators, and parasitoids of crop pests. Some assure pollination of crops and wild plants, while others again produce honey and silk. The fact that non-target Page 52 of 110 birds and, occasionally, other vertebrates may be killed by quelea control operations is well-established (Keita, et.al. 1994; van der Walt et.al. 1998; Verdoorn, 1998) The risk of human health problems and environmental damage can be mitigated considerably by development of integrated environmentally sound control strategies including Net-Catching. These methods will educate farmers become custodians of the environment. A new emphasis is the possibility of harvesting quelea for food. Since quelea is a good source of protein and preferred by many people. This method offers more rapid prospects for implementation which enable farmers to continue making their own decisions important for the control of quelea in their area. While present indications are that harvesting is probably not an option as a crop protection technique, it offers the possibility of providing income to rural populations in compensation for crop losses. (T. N. Mtobesya, pers.comm). A sustainable and environmentally sound control strategy for quelea in Tanzania undated research document by B.Mtobesya). In respect of quelea birds, FAO is currently encouraging the use of IPM approaches to the problem of bird attacks on cereal crops. This means working with farmers in examing all aspects of farming practice in relation to quelea damage, and seeking to minimise external inputs, especially pesticides. In includes modifying crop husbandry, planting time, week reduction, crop substitution, bird scaring, exclusion neeting, etc. and only using lethal control for birds directly threatening crops when the other methods have failed. It is also important for farmers to be aware of the costs of control using pesticides, and in the case of commericial farmers, for them to bear some or all of the costs. A major likely benefit of IPM is reduced environmental side-effects resulting from decreased pesticide use. Although some elements of IPM have been tried in bird pest management, a major effort has yet to be made, for quelea, to focus on farmers in all aspects of the problem (Elloit, 2000). Locust Locusts live and breed in numerous grassland plains, the best ecologically favourable ones are known as outbreak areas. During periods with favourable weather, locust multiply rapidly and form large swarms which escape and may result into a plagau. There are eight known red locusts outbreak in East and Central Africa, four of these are found in Tanzania. The include the Rukewa Valley and Iku/Katavi plains in the Southern West, the Malagarasi River basin in the West and Wembere Plains in the Centre. They cover a total of 8000 km2. The strategy for red locust control combines regular monitoring of breeding sites followed by aerial application of fenitrothion 96.8% ULV to eliminate potential threatening hopper populations. Table 4.30 shows invaded area and treatment used for red locust. Table 4.31: Invaded area and treatment used Year Type Investigated areas Invaded area Treatment Area coverage (Ha) Type of chemical used Remarks January 2003 to December 2003 Red locust Wembere Plains (Tabora) Malagarasi Basin (Kigoma) Iku/Katasi Plains (Rukwa) 1. Iku/Kutanvi Plains (Rukwa) 2. Wembere Plains (Tabora) 2,600 600 4500 Metarhizium anisopline Fenitrothion technical Fenitrothion technical Observation, shows Metarhizium anisophiae as a more effective chemical in controllong the spread of Red Locusts Source: MAFS (2004): Basic data agriculture sector 1995/96-2002/2003 Recently, the red locust regional programme has started to investigate the viability Metarhizium anisopliae, a biopesticide, for locust control. This is a collaborative initiative funded by DFID between NRI-UK, Tanzania and Zambia Governments. If viable, the agent can also be used as an option in the management of the elegant grasshopper and the edible grasshopper (locally known as nsenene). Page 53 of 110 The edible grasshopper (Ruspolia nitidula, Scopoli) has become increasingly damaging on cereal crops (maize, wheat sorghum, rice and millets) in parts of the country, notably northern, eastern and lake zones in recent years (PHS, pers.comm.). There being no research done on the management of the pest, farmers have been forced to use any recommended insecticide as in the interim. Armyworm The African armyworm (Spodoptera exempta) is a major threat to basic food production in a number of east and southern African countries Armyworm is a major pest of cereal crops (maize, rice, sorghum and millets) as well as pasture (grass family) and therefore a threat to food security and livestock. Overall losses of 30% for crops have been estimated though in major outbreak years losses in maize of up to 92% are recorded. Armyworm outbreaks vary from year to year but serious outbreaks occur frequentely as depicted in Table 4.31. Table 4.32: Armywork outbreaks in Tanzania Seasonal Year Area Invesed (Hactres) 1989/90 28,768 1990/91 15,214 1991/92 517,233 1992/3 34,844 1993/94 45,504 1994/95 4,798 1995/96 3,187 1996/97 577 1997/8 35,174 1998/9 311,560 1999/2000 50 2001/2002 157,942 Table 4.33: Damage of various croups by armyworms during the 2001/2002 cropping seasons in some region of Tanzania Region District Crops damaged Hectares infested Arusha Hanang Maize, sorghum, millet, pasture 25,910 Kiteto Maize, millet, pasture 15,570 Karatu Maize, sorghum, millet 2,500 Monduli Maize 100 Babati Maize 3,090 Arumeru Maize, pasture 2,500 Simanjiro Maize, pasture 2,230 Dodoma Dodoma Rural Maize, sorghum, millet, pasture 21,300 Page 54 of 110 Region District Crops damaged Hectares infested Dodoma Urban Maize, sorghum, millet 6,613 Mpwapwa Maize, sorghum, millet, pasture 5,906 Kondoa Maize, sorghum, millet, pasture 17,268 Kongwa Maize, sorghum, millet, pasture 21,328 Kilimanjaro Hai Maize, paddy, pasture 3,500 Rombo Maize 110 Mwanga Maize, pasture 281 Same Maize, paddy, pasture 251 Moshi Maize, paddy, pasture 15,000 Tanga Korogwe Maize, paddy, pasture 1,050 Handeni Maize, pasture 6,445 Morogoro Morogoro Rural Maize, paddy, sugarcane 5,483 Iringa Kilosa Maize, paddy 617 Kilombero Maize, paddy, sugarcane 747 Iringa Rural Maize 9 Ludewa Maize 113 Mbeya Mbozi Maize 22 Total hectares infested 157,943 Source: Ministry of Agriculture and Food Security Report, 2001-2002 Due to its economic significance, management and control is centrally co-ordinated by PHS. Its control combines monitoring in identified breeding areas, forecasting and early warning of potential outbreaks. The national armyworm control programme based at Tengeru-Arusha, runs a network of 100 traps distributed throughout the country (Anon, 1999). The traps are placed at district offices, research stations and in large- scale farms. Weekly returns from these traps are used in forecasting potential outbreaks for the following week (Anon, 1999). The information about potential outbreaks is passed to the regions and districts from where it is further passed to farming communities through the extension system. Farmers are advised to inspect their fields for signs of infestation. If the crop is attacked, farmers should spray with diazinon, fenitrothion or chlorpyrifos, whichever is available at the nearest pesticide store. Both ULV and knapsack sprayers can be used depending on available formulation in the outbreak areas. This service could be improved through a better monitoring and reporting system that empowers farmers to be partners in a co-ordinated network. This will require the following activities: Development of community based monitoring and early warning approaches Formulating and implementing appropriate training for district plant protection officers (DPPOs), village extension officers (VEOs) and farmers to impart simple reliable monitoring skills Formulating and implementing a reliable community based early warning network This approach is likely to have a number of benefits. One, less pesticides will be used because farmers will be able to identify and apply control measures on the most vulnerable stage of the pest, which is not possible in the current set-up. Secondly, farmers can use less toxic and environmentally friendly proven alternatives to pesticides e.g. botanical extracts and/or biopesticides at relatively low cost with minimum environmental hazards. Thirdly, if well co-ordinated, the information generated by farming communities can be integrated in the nation monitoring and early warning system to improve the quality of the information at national and international level. A new natural control for armyworm is being developed by using a natural disease of the armyworm as biological control in place of toxic chemeak insecticides (W. Mushobozi, pers.comm.). This disease of armyworm is caused by specific agent, the Spodoptera exempta nucleopolyhedrovirus (or NPV). It has been observed since the early 1960s the late in the season many armmworm outbreaks collapse due to the occurrence of a disease that killed up to 98% of caterpillars. NPV can be sprayed like chemicals onto pest outbreaks causing epidemics of NPV desease that kill off the pests, effectively acting as a natural insecticide. What is more, the killed insects produce more NPV Page 55 of 110 spreading the disease further. The NPV produced by dying insects can infect later generations of armyworms so that the effect is longer lasting than chemical insecticdes (Mushobozi, et.al. undated). 5. POLICY, REGULATORY AND INSTITUTIONAL FRAMEWORK 5.1 INTRODUCTION Tanzania’s legislation on plant protection and pesticides dates back to 1997. Accordingly, though the review of previous legislation was primarily based on IPM applications, these laws have not taken into account the New Revised Text of the 1997 International Plant Protection Convention (IPPC), which is cited by the World Trade Organization (WTO) Sanitary and Phytosanitary Agreement (SPS Agreement) as the authoritative standard setting body for plant protection. One of the purposes of the legal component is to ensure the compliance of Tanzanian legislation with these standards. As a member of the WTO, Tanzania is required to comply with the international standards within the WTO framework. Phytosanitary measures include all relevant laws, decrees, regulations, requirements and procedures taken by a state in order to protect plant health and prevent the spread of diseases and pests. However, in order to prevent such measures becoming disguised restrictions on trade, the WTO SPS Agreement requires harmonizing such measures at international level. Conversely, such standards can be argued to be an important way of ensuring market access for Tanzania’s international exports. Also Maximum Residue Levels (MRL) set by large target export markets such as the EU, US and Japan require that agricultural products do not have pesticides residues that exceed established quantities. Pesticides control is also a considerable concern nationally, with unacceptable MRLs on some agricultural crops for the domestic market. Greater regulation through strengthened legislation will contribute to the judicious application and safe use of pesticides. 5.2 POLICIES AND STRATEGIES National Environmental Management Policy (1997) The National Environmental Management Policy (NEM) is set to achieve the following in terms of environmental management: “Integrated multisectoral approaches necessary in addressing the totality of the environment; Fostering government-wide commitment to the integration of environmental concerns in the sectoral policies, strategies and investment decisions; Creating the context for planning and coordination at a multisectoral level, to ensure a more systematic approach, focus and consistency, for the ever-increasing variety of players and intensity of environmental activities”. The policy has identified six key major environmental issues in the country. These are land degradation, water pollution, air pollution, loss of wildlife habitats, deterioration of aquatic systems and deforestation. Hence the policy has the following objectives with respect to environmental management in agriculture: ensure sustainability, security and equitable and sustainable use of natural resources; prevent and control degradation of land, water, vegetation, and air; conserve biological diversity of the unique ecosystems the country; raise public awareness and understanding of the essential linkages between environment and development, and to promote individual and community participation in environmental action. National Agricultural and Livestock Policy (1997) The ultimate goal of having this Policy is to improve the well being of the population whose principal occupation is based on agriculture. The focus of the policy is to commercialise agriculture so as to increase the livelihood of the smallholder farmers/livestock keepers. The policy’s main objectives include: ensure basic food security for the nation and to improve national standards of nutrition, by increasing output, quality and availability of food commodities; improve standards of living in the rural areas through increased income generation from agricultural and livestock production; increase foreign exchange earnings for the nation by encouraging production and increased exportation of agricultural and livestock products; Page 56 of 110 promote integrated and sustainable use and management of natural resources such as land, soil, water and vegetation in order to conserve the environment; provide support services to the agricultural sector, which cannot be provided efficiently by the private sector. Plant Protection Act No. 13 (1997) This Act has made provisions for consolidation of plant protection to prevent introduction and spread of harmful organisms, to ensure sustainable plant and environmental protection, to control the importation and use of plant protection substances, to regulate export and imports of plant and plant products and ensure fulfilment of international commitments, and to entrust all plant protection regulatory functions to the government and for matters incidental thereto or connected therewith. The activities of Tanzania Pesticides Research Institute (TPRI) are incorporated into the Act. In relation to IPM, importation of biological control agents is not allowed unless under the prescribed permit by the Ministry. Environmental Management Act of 2004 This Act requires establishment of sector environmental management Units at each Ministry, with the responsibility of ensuring compliance on environmental matters. The sector environmental Units have, among others, the responsibilities of Advising and implementing policies of the government on the protection and management of environment Coordinating activities related to the environment of all persons within the Ministry Ensure that environmental concerns are integrated into the Ministry development planning and project implementation in a way which protects the environment To prepare and coordinate the implementation of environmental action plans at the national and local levels as required under this Act To refer to the council any matter related to the enforcement of the purposes of this Act To ensure that sectoral environmental standards are environmentally sound In relation to the Management of dangerous materials and processes, of which agricultural chemicals may fall, the Minister shall have the power to make regulations pertaining to persistent organic pollutants (POP) and pesticides issues, to ensure that they are in compliance with the Stockholm Convention on POP of 2001 and Rotterdam Convention on the Prior Informed Consent Procedure for Certain Hazardous Chemicals and Pesticides in International Trade of 1998. The Minister shall also have the powers to make regulations regarding the prevention and control of pollution. However, this mainly relates to the discharge of hazardous substances such as chemicals or mixtures containing oil in water or any other segment of the environment, except in accordance with guidelines prescribed under this Act or any other written law. It is an offence punishable by law to discharge such chemicals, and in this regard there is payment on the costs of removal, and those incurred during the restoration of environment. The Institution/organisation is expected to give immediate notice of the discharge to the Council or relevant sector Ministry, and commence clean up operations using the best available clean-up methods, and comply with such directions as the Council may prescribe. In this context, services that relate to the regulation of agricultural chemicals in the Ministry of Agriculture and Food Security shall be at the forefront to ensure the judicial use of agropesticides. In relation to Plant Health Services the Ministry has taken measures to improve and strengthen Plant health services in order to minimise crop losses resulting from pests and diseases. Hence the Ministry strongly advocates using IPM approaches to be disseminated to farmers through the agricultural extension services. On the aspects of migratory pests and diseases, the Ministry cooperates fully with the neighbouring countries (through regional initiatives on outbreak pest control) in the collective effort to control the damage of such pests. The Ministry also has in place supervisory and regulatory instruments to register, license, monitor and supervise manufacturers, importers, distributors and users of agricultural inputs such as pesticides, fertilizers and herbicides. Page 57 of 110 5.3 PROGRAMMES AND STRATEGIES 5.3.1 Africa Stockpiles Programme (ASP) Although the Africa Stockpiles Programme (ASP) focused on obsolete pesticides and their associated waste, the Prevention component carried out legislative review under this project for the United Republic of Tanzania (URT) including plant protection matters for both mainland Tanzania legislation and Zanzibar. Through consultative meetings with the pesticide industry stakeholders, International trade requirements and harmonisation of the sanitary and phytosanitary systems. The Plant protection Act 1997 was split into two legislations: The Pesticide Management Act 2013 (Draft) and The Plant Protection Act 2013 (Draft). The programme also addressed the major issues in prevention of accumulation of obsolete pesticides and its associated wastes by putting in place an empty pesticides container maintenance strategy and the ASP sustainability Roadmap. The Plant Protection Act 2013 (Draft) The main objective of this Act is to prevent the introduction or spread of plant disease or pests; provide for phytosanitary control measures; facilitate trade in plants and plant products and to regulate other matters connected thereto. The Act is meant to establish a National Plant Protection Organization (NPPO). The NPPO core function will serve as a national contact point for the IPPC and shall develop mechanisms for consultation between responsible authorities for enforcement of the phytosanitary legislation for Tanzania and Promotion of integrated pest management and control. A cabinet paper for this Act has been presented to the cabinet first sitting, issues raised from this seating has been addressed ready for the second sitting later this year (2014) before the Act is tabled by the Attorney general - Chief Draftsmen to the Parliament. The Pesticide Management Act 2013 (Draft) An Act to provide for the life-cycle management of pesticides, regulating the manufacture, formulation, importation into and exportation from the country, transport, storage, distribution, sale, use and disposal of pesticides and to regulate other matters connected thereto. This Act will establish the Tanzania Pesticides Control Authority (TPCA) responsible for monitoring the trade and use of pesticides, and collecting statistical and other information concerning the import, export, manufacture, distribution, sale and use of pesticides, about pesticide residues and safe use. The act prohibits the importation, manufacturing, formulating, transportation, distribution, exportation or sell of banned, obsolete pesticides under: PIC and POPs and any other pesticide banned or severely restricted in the country of origin under any circumstances within the country or any pesticide for which is not in the category/group currently under use. In relation to IPM the authority suggests development and availability of safer alternatives to existing pesticides as per latest global research and development without compromising the importation of biological control agents as allowed in the Biological control agents protocol developed within the Plant Protection Act of 1997. Like “The Plant Protection Act 2013 (Draft)”, a cabinet paper for “The Pesticide Management Act 2013 (Draft)” has been presented to the cabinet first sitting, issues raised from this seating has been addressed ready for the second sitting later this year (2014) before the Act is tabled by the Attorney general - Chief Draftsmen to the Parliament. 5.3.2 Empty Pesticides Container Management Strategy Pesticide use by small scale farmers has been on the increase in the recent years. This has been attributed by availability of affordable convenient packaging. The bulk of the pesticides distributed in Tanzania are in small packs resulting to increased number of empty pesticide containers. This has resulted in the accumulation of empty pesticide containers in the farming environment. The greatest challenge facing the use of pesticides is recovery and disposal of empty pesticide containers. Currently there is no legal framework mechanism to guide on the disposal of the containers. Also the absence of organized disposal Page 58 of 110 system has rendered farmers and other users of pesticides dispose containers by throwing them away or putting them in the solid waste system in urban areas. In addition, the absence of information to rural communities on the risks pertaining to reuse of empty containers has created a major challenge. The strategy identifies the mechanism of dealing with empty pesticide containers and provided the framework of up-scaling the process through the stakeholder partnership and cost sharing initiatives. If not streamlined in the Good Agricultural Practices, the export market of agricultural produce will give a negative impact internationally. The strategy addressed the following critical issues: (i) increase awareness amongst pesticide users on the best practice of handling pest containers; (ii) sensitize the communities on risks of reusing empty pesticide containers for other purposes; (iii) provision of training and support of local agricultural authorities to promote safer use of pesticides; (iv) The quantification of the build-up of empty pesticide containers in the government stores and the farming communities; and (v) establishment of the recycling facilities of the pesticide packaging for which sustainable disposal/recycling options is needed. The stakeholders and target beneficiaries of the strategy are: (i) farmers who benefit from the disposal of containers (ii) rural communities who benefit from tighter controls on pesticide container disposal mechanisms (iii) policy makers at several government departments and agencies with regard to improved pesticide use and management; and (iv) recycling industry benefit from availability of raw materials. Page 59 of 110 6. PEST CONTROL AND MANAGEMENT OPTIONS 6.1 INTRODUCTION Insect control techniques for IPM have been known and are in use for along time. Some of the most effective non-chemical techniques such as biological control, host plant resistance, crop rotation, etc were widely used before the synthetic insecticides appear in scene. Recent problems of insecticide resistance in insect pests, other side effects and increasing cost of the insecticides have renewed interest in the non-chemical techniques. The techniques can be conveniently categorized in order of preference in IPM as biological control, the use of attractant, pheremones, repellents, genetic manipulation, insect growth regulators and the use of plant extracts. In this section biological control, cultural control, chemical control, quarantine and physical or mechanical control, chemical control and botanical control are presented. Biological control should not confused with natural control which is collective action of environmental factors that maintain the population of pests within certain upper and lower limits over a period of time (van den Bosch, 1982). 6.2 BIOLOGICAL CONTROL Every living organism has its natural enemies and diseases which kept its population at equilibrium. The natural enemies include predators, parasitoids, nematodes, fungi, bacteria, viruses etc. The use of predators, parasitoids, nematodes, fungi, bacteria and viruses for to maintain the population density of pests at a lowest level than would occur in their absence is called biological control (bio-control). Tanzania has some experience based on the successful control of the cassava mealy bug, the cassava green mite and the water hyacinth (Anon, 1999). The National Plant Protection Policy is also conducive to the promotion and use of bio-control as a strong IPM component. However, at national level, the capacity and capability to implement an effective nation-wide programme is limited. Approaches to biological control There are three approaches are used in biological control. These include conservation/enhancement, augmentation and introduction. Conservation/enhancement This refers to optimization of the impact of living agents that already exist in the ecosystem Augmentation This refers to as an artificially increasing the numbers of natural enemies in the agroecosystem Introduction This refers as importing new natural enemies’ species in the system where they were not found before. Host Plant Resistance The IPM concept stresses the need to use multiple tactics to maintain pest populations and damage below levels of economic significance. Thus a major advantage of the use of pest resistance crop varieties is its compatibility with other methods of direct control. Pest resistant cultivars allow a synergy of the effects of cultural, biological and even chemical pest control tactics. Host plant resistance (HPR) is of particular importance in developing countries where farmers lack the resources for other control measures. There are many examples of resistant varieties significantly increases crops productivity. However, farmers continue to grow varieties which are susceptible because resistant varieties can reduce the burden of pest control by using chemicals. Resistance to pests is the rule rather than the exception the plant kingdom. In the co-evolution of pests and host, plants have evolved defense mechanism. Such mechanism may be either physical (waxy surface, hairly leaves etc) or chemical (production of secondary metabolites) in nature. Pest-resistant crop varieties either suppress pest abundance or elevate the damage Page 60 of 110 tolerance level of the plant. In other words, genetic resistance alters the relationship between pest and host. The functional of the pest to the resistance may be non preference or antibiosis (early death, abnormal development). Also genetic transformation of the plant (expression of the bacillus thuringiensis toxins, protease inhibitors). The development of transgenic plants that are resistance plants that are resistant to viruses and insects has been more successful than for resistance to bacteria and fungi, but this gap is readily closing. Resistance genes for fungal and bacterial genes have now been cloned and there is a greater molecular understanding of plant pathogen interactions. The inherent genetically based resistance of a plant can protect it against pests or diseases without resource to pesticides. Moreover to use it the farmer has no need to buy extra equipment or learn new techniques. For example on farm in some parts of Kenya, up to 80% of plants exhibit symptoms of diseases in banana fields, but the use of plant resistance in bananas is the most effective approach to management of fusarium wilt and is the most economic and practical long term option for small scale farmers in Africa. Different Institutions in Nigeria and Uganda have developed banana cultivars with resistance to pests and diseases. Another example of varieties which are resistance to pest attack are maize varieties (TMVI, Staha, Kilima) which are either resistant or tolerant to maize streak the viral disease that cause significant yield loss to late planted maize. Other examples of resistant varieties are coffee clones (MS1, MS2, MS3 and MS6) against coffee leaf rust, banana varieties FHIAs which are resistant to Nematodes, Panama and Black Sigatoka. In cotton, host plant has been of the importance especially for small scale farmers who has low income. Great losses have been observed in cotton production due to insects like bollworm, aphids, leaf miner, jassids and diseases like fusarium wilt and bacterial blight. For pests like jassids though there is a means of spraying but it seems to be expensive because of high prices in buying chemicals and low farmers income to buy the chemicals. Thus all of varieties produced at Ukiriguru had resistance to jassids since they have hairs to interfere sucking insect pests. Also in the control of bollworm up to now still is a problem but in other countries the genetic transformation is used to transfer Bacillus thuringiensis to cottone plants in order to improve insect resistance in cotton cultivars. Cotton cultivars produced already showed success and had good response from farmers. The disease like fusarium wilt and bacterial blight, have the ability to reduce cotton yield to a high percentage. The effort to combat this situation is done on producing cultivars with resistance to these diseases. All Ukiriguru cotton varieties are resistant to bacterial blight and UK91 and UK77 varieties are resistant to fusarium wilt. In other crops like sweet potato to avoid the weevils’ infestation, other varieties are producing their tubers far away from the soil surface. Also sorghum to avoid bird attack some varieties have gooseneck that the bird can’t reach grains easily. For rice some varieties have awns to prevent themselves from bird attack. With host plant, the rate of spread and the rate of symptom development can be very slow. Also this tends to reduce the cost of pests and disease controls through buying chemicals also time consuming in bird scaring. Since pests and diseases reduce the quality of the produce thus the use of the host resistance materials assures the good quality for home consumption as well as for marketing where you are able to fetch a lot of income. All these efforts are made to reduce the costs involved in pests and disease control as well as to safe guide the environment. Pest resistance genes are predominantly found in wild species within the same genus or family as the crop plant. Because such plants are in dynamic equilibrium with the pests, the resistance genes are present in a high frequency to be readily found. Unfortunately resistance genes from wild species are often combined in linkages with undesirable genes and many recombination and selection steps are require incorporating them into useful cultivars. Another source of resistance genes is primitive cultivars or landraces, although this is much smaller reservoir diversity than wild species. For example, in potato, high levels of resistance to the green peach (Myzus persicae) has been identified in about 6% of examined accessions of wild Solunum species (Flanders, et al. 1992). Wild crop relatives have yielded pathogen resistance in, amongst Page 61 of 110 others, rice, wheat, barley, cassava, sweet potato, tomato, sunflower, grapes, tobacco, cacao, sugarcane and Musa. Host plant resistance (HPR) is also recognised in the new Plant Protection Policy as an invaluable component in IPM. Breeding and selecting for resistance to serious pest problems is an issue mandated to the National Agricultural Research programmes. These programmes have produced substantial results in terms of releasing varieties with necessary qualities and tolerance/resistance to a wide range of otherwise devastating pests of cotton, maize, sorghum, beans and cassava. Therefore, the Directorate of Research and Development in MAFS has the capacity and infrastructure to contribute HPR materials to farmers given the necessary logistical support. Considering the scope of the proposed programme, it will be appropriate for the project to provide logistical support for the multiplication, popularisation and distribution of crop varieties already proven to posses acceptable levels of tolerance/resistance to pests of economic importance. The issue of the grey leaf spot disease of maize, cassava mosaic diseases and rice yellow mottle virus must be given priority to ensure household and national food security. Rapid multiplication and distribution of cassava varieties with proven tolerance/resistance to cassava mosaic diseases and cassava streak diseases is equally important. Programme should allocate adequate funding to facilitate this activity. In addition, logistical support to facilitate the multiplication and distribution of the earmarked coffee varieties with resistance to CBD and CLR will be required as soon as Tanzania Coffee Research Institute releases them. Fast multiplication and distribution of the material is essential to speed up reduced use of copper-based fungicides in the coffee cropping systems in the northern zone. 6.3 CULTURAL AND CROP SANITATION PRACTICES This is one of the IPM components, which is used by farmers in controlling/reducing pests and diseases in crops. The cultural practices modify/destruct the environmental of crop pests and diseases by depressing their breeding/growing areas. The cultural practices are the same/different in single/groups. These practices are: Crop rotation: This practice is used to depress weeds and/insect pests and diseases in some crops. Example: A weed Striga in sorghum and millet can be controlled/reduced by planting a trap crop like groundnuts, cotton Intercropping: The field is used to grow two or more crops at the same time. Relay cropping: Example: Banana relayed with mucuna to reduce the infestation of weevils. Fallow: The field is not cultivated for some years in order to control various parasitic weeds. Cover crops: These are leguminous crops, which are grown to suppress weeds in the field. They can be intercropped or not and they prostrate and cover the field e.g pumpkins, canavallia etc. Trap crops: These induce the germination of a pest. The trap crop can be intercropped or rotated with a susceptible host (e.g groundnuts, bambaranuts, cotton etc). Mulching: This is covering of crop fields by dry grasses to control weeds and conserve soil moisture (e.g in coffee, banana, tomato field etc). Hand pulling and hoes weeding: These practices are the most common and being used by small-scale farmers. Burning: Land clearing and destroying infected plants/crops. Page 62 of 110 Fertilizer/manure application: The application of nutrients in the form of either inorganic fertilizer or farm-yard manure reduces both the infestation of fields by weeds (e.g Striga) and losses in crop yield. Use of disease free planting material e.g: cassava cuttings, sweet potato vines etc. Pruning: Done in coffee, tea orange tree etc. to reduce insect pests and diseases that might infest the crop. Thinning: Done to reduce plant population in the field (e.g in maize, sorghum and millet, cotton etc). Other cultural methods include spacing, desuckering, which is done in bananas; use of local tolerant varieties, sun drying to reduce moisture content of the material to be stored; and use of traditional storage method e.g ‘Vihenge’, banana sheaths, botanicals, clay soils etc. 6.4 PHYSICAL AND MECHANICAL CONTROL Physical and mechanical controls are the measures kill the insect pest, disrupt its physiological or adversely the environment of the insect pest. These differ from cultural control in that the devices or actions are directed against the insect pest instead of modifying agricultural practices. For examples, hand picking of cotton stainers from cotton plants, banana weevils from banana pseudostems, tailed caterpillars from coffee, killing stem borers in coffee or American bollworm from tomato plants are the forms of physical control while use of a fly swatter against annoying flies is a form of mechanical control. Common physical and mechanical control methods include the utilization of high and low temperature for instant hot water treatment of banana planting materials for control of nematodes, sun drying of stored grains, cool storage of maize grain, reducing humidity, utilizing insect attraction to light traps (lepidopteran insect pests viz. Armyworm and cotton bollworm). 6.5 CHEMICAL CONTROL It is important to recognise that, all the registered pesticides (Table 5.1 below) are recommended as part of IPM components in all production/cropping systems as indicated in the previous sections of this report. All the pesticides included on the list above are registered by TPRI Act, 1979 and Pesticides Control Regulations GN 193 of 1984) [Anon, 2001b], and this is why some pesticides e.g. paraquat, one of the 'dirty dozen', is still officially registered and allowed to be used in Tanzania. It is therefore strongly recommended that, the pesticide registrar ban all further importation and subsequent use of paraquat in Tanzania and others in the same category, with immediate effect. Those pesticides in WHO class Ib, namely endosulfan, chlorpyrifos, quinalphos, carbofuran, and isazophos, should be deregistered with immediate effect and phased out by year three of the programme and encourage use of less toxic and more IPM friendly pesticides. Both WHO class I and II are still featuring on the list of registered pesticides mostly because, the WHO class III, which are new generation pesticides known to be less toxic and therefore more environmentally and IPM friendly, are relatively more expensive and therefore beyond the means of most smallholder agricultural producers in Tanzania. In addition, the majority of such pesticides are not locally available. Therefore, judicious use of through integrated use of other pest management options is recommended to ensure reduction of potential health and environmental hazards. It is evident, albeit from Table 5.1, that, the current list of registered pesticides is outdated and also not in line with international standards. It is therefore strongly recommended that, the registrar of pesticides must review the current list of registered pesticides in line with the WHO guidelines immediately. The current list of pesticides registered in Tanzania indicates trade name, registration number, common name, registrant and usage. This is not informative enough given the wide range of its users. It is therefore recommended that, the proposed revised list should include the WHO class, oral LD50, active ingredient, and application rate. Page 63 of 110 Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania: Oral LD50 and WHO classification Chemical Common name *Oral LD50/kg WHO class Comments Insecticides Betacyfluthrin 500-800 II Biphenthrin Carbaryl 850 II Chlorpyrifos 135-163 Ib Deregister & Phaseout Cypemethrin 251-4125 III Cypermethrin + Dimethoate 251-4125 + 2350 III Deltamethrin 153-5000 III Dealtamethrin + Dimethoate 153-5000+2350 III Diazinon 220 II Dimethoate 2350 III Endosulfan 55-110 Ib Deregister & Phaseout Esfenvalerate 451 II Fenitrothion 800 II Fenvalerate 451 II Fenvalerate + Fenitrothion 451+ 800 II Flucythrinate Hydrmethyl Lambda cyhalothrin 243 II Permethrin 430-4000 III Pirimiphos methyl 2050 III Pirimiphos methyl + permethrin 2050 + 430-4000 III Profenophos 358 II Profenophos + cypermethrin 358 + 251-4123 II Quinalphos 62-137 Ib Deregister & Phaseout Nematicides Carbofuran 8-14 Ib Dazomet 520 II Isazophos 40-60 Ib Deregister & Phaseout Herbicides Atrazine Diuron Fluometuron Glyphosate Metolachlor + Atrazine Metalachlor + Dipropetrin Paraquat Dirty Dozen: should be banned with immediate effect Chemical Common name *Oral LD50/kg WHO class Comments Avicides Fenthion Cyanophos Rodenticides Bromodiolone Coumatetralyl Page 64 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Diphacinone Fungicides Bronopol Chlorothalonil 10,000+ III Copper hydroxide 1,000 II Copper oxychloride 70-800 II Cupric hydroxide 1,000 II Cuprous oxide Cyproconazole 1,000 II Hexaconazole 2189 III Mancozeb 5000+ III Metalaxyl + Mancozeb 633 + 5000+ III Penconazole Propineb 1,000 II Triadimefon 1,000 II Sulfur Sources: TPRI: List of Pesticides Registered in Tanzania, May 2004 and Nyambo 2002 It may be noticed that Tanzania has ratified the Convention on Persistent Organic Pollutants (POPs) in April 2004 (pers.comm. A.Madate, Division of Environment and National POPs Project Coordinator), but has not yet banned the highly harardous pesticides (WHO classes Ia, Ib, II). However, projects involving use of chemical pesticides under WHO Class Ia, Ib and Class II will not be financed under the proposed SAGCOT Investment Project. Appendix 3 provides WHO classification of chemical pesticides. 6.6 BOTANICAL PESTICIDES Assessment of botanical pesticides for pre and post harvest is being done by a number of institutions in the country and some of the potential ones have been recommended for use in crop production (Paul et al. 2001). In beans, extracts of Tephrosia vogelii and Neuratanenia mitis have been recommended and farmers are using them because they are easily available and less costly. Where these do not occur naturally, farmers have also established the plants in their home gardens to ensure availability when needed. The GTZ-IPM project in Arusha in collaboration with IPM farmer groups and the extension staff has compiled a list of useful botanical pesticides (Table 5.2) that could be used on a wide range of vegetables and other food crops. The information is useful but has to be used with caution. Most of the botanical extracts are already in use by small-scale farmers as crude in-house preparations. However, they should be used with caution. It has to be remembered that not all botanical extracts are safe. Tobacco extract is one of the deadly substances and should therefore not be promoted for use on vegetable production. Tephrosia spp extract and leaves are toxic to fish (local fishermen use the leaves for fishing) and therefore should be used with caution. None of the suggested botanical extracts (Table 5.2) are registered in Tanzania because they have not been researched enough. In particular, information on dosage rate, mammalian toxicity (LD50), side effects on non-target organisms especially potential bio-control agents, biodegradation and reduce analysis data, is not available. However, 3 neem-based and 2 pyrethrum-based commercial formulations are being processed for registration. These two botanicals have been researched and registered in Kenya and elsewhere. Page 65 of 110 Table 8.2 List of potential plants that can be used to prepare botanical extracts for pre and post harvest pest control Kiswahili name English name Scientific name Mustafeli Soursoap Annona muricata Mtopetope Bull-oxheart A. reticulata. Mtopetope mdogo Custard apple A. squamosa Vitunguu saumu Garlic Allium sativa Mwarobaini Neem Azadirachta indica Kishonanguo Black Jack Bidens pilosa Pilipili kali Chili Capsicum frutenscens Mpapai Pawpaw Carica papaya Mnanaa Thorn apple Datura stramonium Mnyaa/utupa Milk bush Euphorbia tirucalii Mchunga kaburi Barbados nut Jatropha curcas Mwingajini Wild sage Lantana camara Tumbaku Tobacco Nicotiana spp Kivumbasi Mosquito bush Ocimum suave Mbagi mwitu Mexican marigold Tagetes spp Alizeti mwitu Wild sunflower Tithonia diversifolia Utupa Tephrosia Tephosia vogelii Source: Paul (2000) and Madata (2001). Page 66 of 110 7. EXPERIENCES ON IPM IN TANZANIA 7.1 INTRODUCTION During her study Nyambo (2002) gave a comprehensive analysis of the Tanzania Mainland experience on participatory IPM. Information from the analysis and visit to key stakeholders, namely the Minsitry of Agriculture and Food Security’s Plant Health Services, Zonal Agriculture Research and Development Institutes (ZARDI), Sokoin University of Agriculture, districts and farmers are summarized in this section. The national research institutions have developed IPM approaches for a wide range of key pests of the major crops mentioned earlier. Some of the information is locality specific e.g. in cotton, maize, coffee and beans. Unfortunately, a lot of the information has not reached target farmers. The information that has filtered through to farmers is not user friendly and/or not appropriately formulated and therefore farmers are unable to optimise the benefits of such options (Nyambo, Masaba & Hakiza, 1996). This is a result of the "top-down" syndrome, which dominates the national research and extension systems. A change in attitude in the national research and extension system is needed to pave way for participatory knowledge development and transfer. Researchers, extension workers, farmers and other stakeholders must work as partners to achieve effective and sustainable technology development and transfer. Farmers must be active participants in the process of problem identification, development and formulation of appropriate solutions to identified pest problems in the context of other production constraints. In recognition of the shortcomings of the traditional top down extension system in promoting sustainable IPM approaches and to prepare a foundation to facilitate and enhance grass-root based system of extension, the Ministry of Agriculture and Food Security, in collaboration with GTZ, FAO and IFAD, had implemented IPM pilot projects to promote farmer participatory integrated pest management approaches in different parts of the country and cropping systems. The lessons from the above projects will be integrated in the IPMP to support decision making in the dissemination and promotion of appropriate IPM options in different cropping systems under SAGCOT. 7.2 GTZ/PHS-IPM The IPM project was initatied in 1992 by the Ministry of Agriculture and Food Security, namely Plant Health Services (PHS) and the German Agency for Technical Cooperation (GTZ). The IPM pilot area was the western growing zone (Shinynanga). This was the area using a lot of pesticides to redcue losses emanating from pests. The IPM project was resource intensive with the GTZ granting Tshs 500 million which is 90% of the budget allocated for IPM implementation annually and the counterpar funding by MAFS was Tshs 50 million per annum. The project operated for 11 years under the following phases: Baseline and diagnostic surveys, training of counterpart staff, introducing IPM concept at farmers’ level, etc. Phase I (1992-1994) Developmemnt, testing and dissemination of the IPM technical packages on priority crops in the pilot area of the western zone Dissemination and extension of IPM technical packages to other regions in the western and northern zones respectively: Tabora, Kigoma, Kagera, Mara, Mwanza, Arusha, Kilimanjaro, Tanga. Phase II (1997-2002) Handing over and consolidating the achievements. The project came to end in September 2003. IPM recommendations accomplished by the project indlcude: 6 recommendations in cereals (maize and sorghum) 4 recommendations in cassava 12 recommendations in beans 8 recommendations in onions 3 recommendations in cotton 2 recommendations in sweet potato 5 recommendations in vegitables and fruits 2 recommendations on weed management Page 67 of 110 The project was also instrumental to the production of the Plant Protection Act 1997, which was operationalized in July 2001. The knowledge base and capacity of the project is centred in PHS HQ and its plant health services zonal offices in the country. Approach and Organizational structure: The project used a modified farming systems approach for planning, development and field evaluation of IPM options. This is a mixture of participatory and exploratory methods, as deemed appropriate depending on the level of training of the extension workers and the problem to be addressed. The key elements in the approach include socio-economic baseline (knowledge, attitude & practices) and diagnostic technical plant protection surveys done by experts. These surveys generated a wide range of background information and a basis for M&E. This was followed by participatory technology development and transfer through farmer groups, referred to as IPM Working Groups, in different agro-ecological areas in respective regions. The baseline information was later used in the extrapolation of data and options to other areas in the project areas. In this approach, the IPM Working Groups are equivalent to the Farmers Research Groups used in the farming systems approach. Group formation: The IPM Working Groups (self formed groups) were initiated by the project with assistance from VEOs and local community development officers for purposes of training and promoting IPM. However, if there were already existing self-formed farmer groups in the village, these were also considered for collaboration. After clarification of the expectations and roles of the partners, the groups were recruited. Group management and promotion of IPM: The project technical staff visited the IPM Working Groups frequently (several times a week at the beginning of the project) to establish rapport with the group members, to set-up on-farm trials and demonstrations, test extension materials as well as plan and evaluate group activities. The project provides technical information on IPM options, training and group facilitation (moderation). The role of the groups is testing and fine-tuning of IPM options and other extension recommendations. Once the IPM Working Groups have approved a technology, the group results are disseminated to other farmers in other similar agro-ecological areas. After several seasons of training, the IPM Working Group is transformed to an IPM Farmer Training Group and a new IPM Working Group is initiated in another village and the process continues. Participatory Group Training approach: The IPM Working Group in collaboration with the project technical staff identified key limiting pest problems and other production constraints for each crop in the area. The project technical staff provides a range of recommended relevant solutions for testing by farmer groups. For selected crops, individual members in the group tested the options in demonstration plots, one crop per farmer. The members make joint visits and analysis of the demonstration plots throughout the growing period until harvest. During the training sessions, farmers are facilitated to recognise the major pest problems, potential damage, management options, insect pest's natural enemies and good post harvest practices with emphasis on IPM. Essentially, group training involved four stages that are summarised as follows: 1. Capacity building to impart knowledge on IPM and participatory methods of technology transfer, group formation and management to selected project technical staff. 2. Demonstration within groups whereby the technology or information is tested for the first time by a farmer within the group under close supervision by the project technical staff. All group members make continuous visits and observations and participate in the analysis of the results. 3. Adaptations in farmer own plots by group members. Farmers are encouraged to keep field records, share the information with group members and carry out joint analysis of the results. 4. Village cycle spill-over whereby the technology is applied by non-IPM farmer groups in the same village. Page 68 of 110 5. The technology was finally approved for dissemination to other areas with similar crops/pests and agro-ecological similarities. Participatory evaluation of results and practices: At the end of each crop season, the project technical staff guides the group members to evaluate the trial results using simple PRA tools. To motivate the groups, a meeting of representatives from all IPM Working Groups was convened once a year for joint evaluation of results. Internal M & E: The project has an established continuous internal M & E to assess project impact and spill-over. The project was using an evaluation form, which was supported by regular field visits for verification. Spill-over and role model effects: KAEMP and MARAFIP have copied the project approach. Capacity Building: The project has trained 999 VEOs/DPPOs in IPM within the project area, i.e. 697 in the Western and 302 in the Northern Zones. The IPM project and the District Councils through their respective support programmes, i.e. MARA-FIP, KAEMP, Care, Farmafrica, DRDPs, Faida, Ecotrust, World Vision, LVEMP, etc. have jointly financed the training. The VEO have in turn trained 484,825 farmers in IPM, i.e. 421,487 in the Western and 63,338 in the Northern Zones. The VEOs were also facilitated formation of 44 IPM working groups, each with an average of 15 farmers (14 IPM groups in the Western and 30 IPM groups in the Northern Zones). These groups play a role model for IPM development, testing of recommendations, validating, implementing and disseminating. Impacts: The extent of impact achievement with regard to the benefits of IPM such as environmental conservation, restoration of beneficial organisms, etc. has not been evaluated. The following impacts have observed (Nyakunga 2003): The use of conventional pesticides in cotton in Shinyanga has been reduced from 6 calender sprays to maximum 3 sprays without negatively affecting production. The evidence of this is the increased cotton production in the Western Zone from 38,000 tons in 1994/95 to 69,900 tons in 2000/01 Safety of users against conventional pesticides: The National Plant Protection Advisory Committee has been instituted in line with the Plant Protection Act of 1997 and is actively guiding and monitoring implementation of plant protection activities in Tanzania. A cost recovery system for the services rendered under the PPA of 1997 is in place with the PHS is able to strengthening the phytosanitary and quarantine measures at the major entry points. The IPM has also been integrated in the Agriculture and Livestock Policy as a national policy on plant protectin and the ASDP has provided that IPM should be disseminated country wide. The success of the GTZ/PHS-IPM initiative was a result of team approach, institutional collaboration (NGOs, national research and extension institutions, and international institutions) harmonisation of technical information between collaborators, adequate flow of funds, good organisational and supervisory skills and staff continuity. 7.3 KAGERA AGRICULTURAL AND ENVIRONMENTAL MANAGEMENT PROGRAMME (KAEMP) KAEMP was a multi-sectoral initiative of the Kagera region (Lake Zone) jointly funded by IFAD, BSF/JP and OPEC with contributions from the beneficiaries. The project was implemented by RAS Kagera and managed by the local government machinery. Its main focus was on improvement of food security and poverty elevation, and therefore, has a holistic approach (addresses agriculture, health, livestock, environment management, rural access roads and marketing) to rural development. In this setup, IPM has been embraced as the key pest management in all crops. To support gradual and sustainable adaptation of IPM and integrated plant nutrition (IPN) by resource poor farmers, the project promoted validated and recommended technologies from national and international agricultural research institution. Selected technologies must be applicable, economically viable and environmentally friendly. Page 69 of 110 The major crops grown in the region are cotton, coffee, banana, cassava and beans. As mentioned above, KAEMP borrowed the IPM approach (baseline studies, group formation and training, internal M & E etc.) from the GTZ/PHS-IPM Shinyanga project. In addition, the linkage between the two projects was strong. GTZ/PHS-IPM technical staff were used as resource persons by KAEMP while Kagera farmers visits the IPM Farmer Training Groups in Shinyanga for learning purposes. However, due to the nature of the KAEMP set-up, some modifications of the Shinyanga approach were deemed necessary in order to accommodate the overall goals of the project. In crop production, declining crop yields, soils fertility and increased pest pressure were identified as major constraints. To address the issues, the project farmer groups were known as IPM/IPN groups (integrated pests management/integrated plant nutrition groups). Capacity building: Since the project is an integral part of the regional development plan, all extension staff (from the district to the village level) were given training in IPM, IPN, and participatory methods of technology transfer with emphasis on group approaches. In this approach, the district extension officer was the foci for new extension messages. It was the responsibility of each district extension officer to ensure proper technology transfer to end-users and hence the need for them to be well informed about participatory methods of extension. In summary, capacity building in KAEMP was implemented in several stages 1. District technology transfer manager (master trainer) was trained in IPM/IPN concepts and approaches including participatory methods of technology transfer through farmer groups; 2. The master trainer trains the VEOs; and 3. The VEOs train farmer groups. To enhance the learning process between groups, the project facilitated farmer-farmer learning through group exchange visits between groups within and between villages and districts. A few farmer representatives visited the Shinyanga IPM farmer training groups. To promote spillover, KAEMP organised and facilitated field days. The IPM/IPN farmer groups were also used for the transfer of other development messages e.g health, water, environmental management etc. and therefore were foci for all extension messages. The KAEMP initiative started in September 1999. By May 2001, the adoption of IPM/IPN within groups was 60% whereas the spillover (diffusion) after 20 months of operation was 1:3, which is quite impressive (J. B. Anania, E. A. M. Anyosisye, personal communication). KAEMP owes much of its success to the GTZ/PHS-IPM Shinyanga experience. The entire stakeholders at regional, district, village and farm level has received the approach with enthusiasm. Successes:The achievements of the project was a result of good political support at regional level, team spirit, sufficient funding, effective capacity building, institutional collaboration, good organisational abilities and focused selection of appropriate technology for transfer to target clients. 7.4 MARA REGION FARMER INITIAITIVE PROJECT (MARAFIP) MARFIP was an initiative of Mara region whose main objective was poverty alleviation through strengthening of capacity of the local institutions to respond to farmer's felt needs related to food, agriculture and livestock. The project was organised and implemented by RAS and funded by IFAD. As mentioned above, MARAFIP was another offspring of the GTZ/PHS-IPM project (S. O. Y. Sassi, personal communication) and therefore, has many common features. However, MARAFIP used the FAO IPM-FFS approach of group training and technology transfer. Capacity building: All district plant protection officers and VEOs were given training in IPM concepts to raise awareness about IPM to facilitate their supervisory role. Five VEOs (project staff) of selected villages Page 70 of 110 for FFS pilot groups were given one-month split course in IPM, group management and participatory technology transfer methods to provide them the capacity to organise and conduct IPM-FFS. There were 5 IPM-FFS groups in the region, one per district. The main focus crops were cassava, cotton, maize, sorghum, legumes (cowpeas, field beans) and sweet potato. The IPM messages/technologies introduced to the FFS groups were borrowed from the Shinyanga IPM project without further refinement. In one case, the "broken telephone message syndrome" was noted with concern. At farmer level, the approach has been received with enthusiasm and adoption of some messages among group members was estimated to be about 25% (one year after IPM training). The IPM-FFS groups were also used as entry points for other extension messages e.g. soil and water management, livestock management and community health, which is in line with the regional objectives. However, funding to facilitate technical support to farmer groups was a constraint, and scheduled activities have been shelved. 7.5 MBEYA: SOUTHERN HIGHLANDS EXTENSION & RURAL FINANCIAL SERVICES PROJECT/IFAD This initiative started with organised extension farmer groups in 1996/97 using a modified T&V extension method to enhance technology transfer at farm level. Essentially, the approach was still strongly based on the traditional "top-down" extension method (E.D. Y. Kiranga and A. H. Urio, personal communication). In 1998/99 the project introduced IPM-FFS pilots in Mbeya (focused on tomatoes, cabbage, round potatoes and wheat) and Ruvuma (focused on coffee and maize) regions. The IPM-FFS and extension groups ran parallel in the same villages. IPM-FFS capacity building (IFAD/FAO initiative): Two VEOs (master trainers) attended a 3 months course in Zimbabawe under the sponsorship of FAO. The project supervisors visited IPM-FFS groups in Kenya for two weeks to gain some basic experience on how to organise and conduct IPM-FFS. This was followed by 2-weeks residential training course in IPM and farmer participatory methods of technology transfer for 25 VEOs in Mbeya and Mbinga districts. The graduates reported back to their duty stations to organise and conduct IPM-FFS in their respective villages. Similar to the GTZ/PHS-IPM project, farmer-farmer learning through exchange visits between farmer groups and within group members was facilitated. Like in the other initiatives, organised field days and exchange visits were used to encourage spillover to non-group members. Institutional collaboration was also emphasised during the project implementation phase. The IPM-FFS approach was highly appreciated by farmers and the VEOs because it was participatory and learning by doing. 7.6 MOROGORO SPECIAL PROGRAMME FOR FOOD SECURITY (SPFS) /FAO PROJECT This was an initiative of the Ministry of Agriculture and Food Security in collaboration with FAO that targets Morogoro and Kilombero districts, with a focus on maize and rice (the major crops in the area) and promotion of small livestock (poultry, milk goats and chicken). The project started in 1996 and ended in1998. The initiative promoted farmer participatory group approaches of technology transfer. Because this capacity was not within the project staff, training in participatory approaches was organised and provided by the Co-operative College Moshi for the project core staff (E. Shayo, personal communication). Baseline surveys and group formation was the same as for the GTZ/PHS-IPM project detailed above. Although the project benefited from the southern highlands initiative, there was limited integration of the IPM-FFS approaches in the Morogoro farmer groups. At the time of the visit, seleceted VEOs were being given a course in IPM-FFS. Page 71 of 110 Capacity building 1. Master trainers were trained by Co-operative College Moshi to impart participatory methods of technology transfer to selected extension workers. 2. Selected VEOs and farmers from targeted farmer groups were given whole season training at one training site on selected crop and extension messages that included aspects of plant protection. The graduates were used for field demonstrations of identified and proven extension messages in target groups in their villages. This stage has some attributes of IPM-FFS. 3. The demonstration farmers in collaboration with the VEO trained group members. Once the technology is approved by the group, it is ready for dispersion to the whole village. This approach has many attributes of the GTZ/PHS-IPM and KAEMP approaches. As in the other projects, the training groups in SPFS/FAO project were also used as entry points to transfer other extension information e.g. water control and management, exploitation of groundwater in crop production, marketing (input supply), credit system, record keeping, diversification of farm enterprises, shallow wells etc. In the first year, the project provided free inputs to the demonstration farmers as motivation. In the second year, inputs were provided on credit with 50% advance payment to wean them off. There was some adoption by group members and spillover particularly of those technologies that directly addressed farmer felt needs. Farmers, village leadership, VEOs, district and regional leadership also appreciated participatory group training as a means to effect quick and efficient technology transfer. However, due to a lack of logistical support, new training groups have not been formed. 7.7 LESSONS AND GENERAL DISCUSSION 7.7.1 Approach All the projects discussed in the previous sections above were actively promoting participatory technology transfer to increase food security and cash income at farm level through self formed farmer groups. Some of these groups are now officially registered. All the initiatives emphasised IPM in their farmer groups. The groups were used as entry points for other innovations on a felt need basis irrespective of the original purpose. The IPM farmer groups were used as foci for the extension of a wide range relevant and appropriate technology and knowledge, this enhancing group cohesion and overall development. The participatory group approach to technology transfer was received with enthusiasm by all the farmers and VEOs in all the visited projects. This is because it involved hands-on-learning, an observation made by all the farmers visited. 7.7.2 Capacity Building These model projects have a lot in common. Capacity building with emphasis on participatory methods of technology transfer, group formation and management were deemed necessary and essential for the project technical staff before training farmer groups. Collaboration and sharing of experiences between projects was key to the success of new initiatives in different parts of the country. The GTZ/PHS-IPM project played a major role in the set up and organisation of KAEMP and MARAFIP, whereas the Morogoro region initiative benefited from the experiences of the southern highlands project. Page 72 of 110 7.7.3 Institutional Collaboration This was observed as key input in the success of the entire visited pilot projects. Institutional collaboration (as indicated in the GTZ/PHS-IPM initiative) ensured harmonisation of technical information, optimisation of scarce resources and ensured farmers of the best remedies to priority problems. As indicated above, collaboration between projects within the country was a healthy avenue for sharing experiences that facilitated speedy setup of new initiatives. 7.7.4 Funding and Logistical Support This is very crucial in all the projects. Adequate and timely release of funds determined the progress of the projects. Currently, and in particular where donor funding has been phased out, project activities have been constrained by a lack of continuous flow of funds, this resulting to infrequent visit and training of established farmer groups. Scheduled activities have been affected in most areas and technical input in existing farmer groups have been curtailed. Fund flow from district councils to support extension services, particularly the farmer groups, after decentralisation is minimal and/or non-existence. The lack of logistical support from the district councils is purported to be largely due to lack of awareness among district decision makers on the significance of promoting participatory group approaches in extension. 7.7.5 Political support Local political support is also crucial in the implementation and sustainability of group approach to IPM promotion. KAEMP is the only initiative that seems to have stronger support. This is most likely a result of the project set-up and its holistic approach that addresses the broader needs of the region. Page 73 of 110 8. IMPLEMENTATION STRATEGY 8.1 INTRODUCTION Implementation of PMP in the project area of SAGCOT is highly recommended. This PMP will address the project needs to monitor and mitigate negative impact of any increase in the use of agrochemicals, particularly chemical pesticides by promoting ecological and biological control of pest management. The PMP shall provide an information basis for stakeholder groups to establish functional mechanism enabling selected farmers to identify, understand and manage pest problems in the further development of community and farmer groups agriculture, reduce personal and environmental health risks associated with pesticide use, and protect beneficial biodiversity such as natural enemies of pests in the farmers’ efforts to increase productivity. The PMP also raises the need of stakeholders to understand and respond to the situations where introduction of alien invasive species necessitates quarantine and stringent minimum pesticide residue levels. The PMP also proposes collaboration with national and international IPM institutions (plant protection organisations -research-extension- private partners) strengthening policy and institional framework and building capacity. The main objectives of the PMP is to enable SAGCOT to oversee in holistic the implementation of the IPM as a tool for pest management including monitoring of pests and disease vectors and mitigate negative environmental impacts associated with pest control in the project area and promote agro-ecosystem management. The plan provides decision-makers, key stakeholders and investors under SAGCOT with clearer guidelines on IPM approaches and options to reduce crop and livestock losses while protecting human and environmental risks. For all sub-projects which triggers OP 4.09 the MGF recipient must adhere to the provisions and recommendations of this IPMP. It is also recommended that the requirements indicated in the IPMP be incorporated by binding references in the project legal agreement. Further to this the SAGCOT Investment Project’s Operational Manual should include the list of pesticide products authorised for procurement under the sub-project (table 8.1 and 8.2) as well as the WHO pesticides classification lists which dictates pesticides that are not permissible in the Project (Appendix 3). 8.2 INSTITUTIONAL ROLES AND RESPONSIBILILTIES Various stakeholders will be critical for the implementation of the IPMP. The roles and responsibilities of these stakeholders are described below. 8.2.1 MGF Applicant/ Recipient As part of the MGF application the MGF Applicant should include basic information on current use of pesticides, potential impacts from the proposed sub-project on pesticides use, any existing pest management systems used by the Applicant, and the Applicant’s proposed approach to address potential impacts. Appendix 2 contains an IPM checklist to guide the planning and implementation of pest controls on crops. For category A and B sub-projects the MGF Applicant is responsible for preparing an Environmental and Social Management Plan (ESMP). The ESMP will outline Environmental & Social actions to be implemented by the MGF Applicant against a proposed timeframe, and this will be reviewed by the FM and discussed with the Applicant to ensure the adequacy of the ESAP. The ESMP should consolidate actions from all required safeguard studies which must be prepared and submitted along with the grant application (e.g. PMP if applicable). If the sub-project intends to introduce new pest management practices or expand the use of pesticides or other agrochemicals, and a Pest Management Plan is required (as determined by screening, scoping and/or the EIA), the MGF applicant will have to include in the grant application (in the text or in an annex) a list of pesticide products authorised for procurement under the sub-project2, or an indication of when and how 2 The World Bank does not finance formulated products that fall in WHO classes IA and IB, or formulations of products in Class II, if (a) the country lacks restrictions on their distribution and use; (b) they are likely to be used by, or be accessible to, lay personnel, Page 74 of 110 this list will be developed and agreed on. This authorised list will also be referenced in the ESAP. In the case where a proposed sub-project has been approved the implementation of the PMP will be the responsibility of the MGF Applicant (now the project implementing entity). The project implementing entity shall also cover all costs associated with the implementation of the PMP including training and awareness activities and submit regular status report on the E&S performance (including pest management performance and pest use) to the FM. 8.2.2 Catalytic Fund The Fund Manager (FM) will undertake a preliminary screening of proposed sub-projects based on the inherent environmental and social risks associated with the sub-project type and requirements (location, size, etc.), using the Screening form in Annex 8 of the ESMF. The results of the preliminary screening form exercise will be used to determine (i) the eligibility of the sub-project for further processing, (ii) the environmental category of the proposed sub-project, and (iii) the environmental and social due diligence work required in order to prepare a detailed application (including preparation of safeguard instruments such as a PMP). If the sub-project intends to introduce or expand the use of pesticides or other agrochemicals the FM will trigger OP 4.09 and require the MGF Applicant to prepare a PMP which will be reviewed and approved by the FM. OP 4.09 should also be triggered if sub-projects plans introduce new cropping methods or diversify into new crops, particularly those that require intensive pest control. The FM will be responsible for carrying out compliance monitoring by visiting selected sub-projects on a regular basis and reviewing the effectiveness of implementation of the activities specified in the sub-project ESAP including mitigation measures related to pest management. 8.2.3 Ministry of Health and Social Welfare Health facilities (hospitals, health centres and dispensaries) in the SAGCOT area should set up databases on incidence of data on poisining, effect of pesticides on human health and environmental contamination. This data will then be used to measure and validate the ameliorating effects of IPM adoption and pilot PMP implementation that is expected to reduce risks to pesticides exposure. Considering the number of Class II pesticides that might be used and Rodent control products (Ia), it would be wise to strenghthen the poison centers or units of the hospital and equipe them with key antidotes (vitamin K in case Rodenticide poisoning and Atropine for Organophosphate poisoning. 8.2.4 Ministry of Agriculture, Food Security and Cooperatives The Ministry of Agriculture, Food Security and Cooperatives (MAFC) is key stakeholder responsible for ensuring that promotion of IPM as standard practice for SAGCOT investors and associated smallholder/outgrower operations. 8.3 PROMOTION OF IPM UNDER SAGCOT 8.3.1 Specific PMP for Sub-Projects As mentioned, all sub-projects which triggeres OP. 4.09 are required to prepare a detailed PMP. The PMP should address those aspects of a chemical pesticide’s life cycle that are part of project activities, from pesticide production to distribution, handling, transport, storage, and application, to its final disposal. The plan should also include provisions to supply necessary safety equipment and training for their use. For all PMP activities detailed budget lines must be specified and included in the overall budget for the sub- project. farmers, or others without training, equipment, and facilities to handle, store, and apply these products properly. Therefore, in compliance with this requirement, under SAGCOT, sub-projects involving use of chemical pesticides under WHO Class IA, IB and Class II will not be financed. Page 75 of 110 In cases where MGF recipients during project implementation wish to procure or use pesticides which are not included in the list of pesticide products authorised for procurement the pesticide product is subject to a screening and approval done by the FM. The criteria for the selection and use of pesticides specifically require that: “(i) They must have negligible adverse human health effects; (ii) They must be shown to be effective against the target species; (iii) They must have minimal effect on non-target species and the natural environment. The methods, timing, and frequency of pesticide application are aimed to minimize damage to natural enemies. Pesticides used in public health programs must be demonstrated to be safe for inhabitants and domestic animals in the treated areas, as well as for personnel applying them; and (iv) Their use must take into account the need to prevent the development of resistance in pests. 8.3.2 IPM to be Part of Environmental and Social Management Plan Each of the subprojects to be financed through the SAGCOT Investment Project will be subject to environmental and social screening, assessment, and approval process as required by SAGCOT’s Environmental and Social Management Framework (ESMF). The process complies with both the World Bank’s safeguard policies and Tanzanian EIA regulations and related guidelines. It is also consistent with the Investment Policies and Operating Guidelines for the Matching Grants Facility and Social Venture Capital Fund outlined in the Trust Deed of the SAGCOT Catalytic Trust Fund (which includes Environmental and Social Review Procedures). For category A subprojects a site specific Environmental and Social Impact Assessment (ESIA) will be conducted. For both category A and B sub-projects grant applications must include an Environmental and Social Action Plan (ESMP). The ESMP include activities, impacts, mitigation and enhancement measures, time schedule, costs, responsibilities and commitments proposed. Subsequently, the ESMP will inform the environmental management system (EMS) of the project through: (a) Ensuring that its activities are in line with applicable environmental laws and regulations; (b) Determining priorities and set objectives and targets to be met by the EMS. A reporting mechanism shall also be established so as to determine whether the targets are met or not, and for record purposes; (c) Identify training needs vis-à-vis the environmental and social objectives and targets, and put a plan for capacity building among staff in place; and (d) Establish environmental and social management programs to be undertaken within given time frames and by particular persons to take corrective measures. As such, roles and responsibilities shall be defined, documented and communicated for effective environmental and social management. In essence, where the use of pesticides is considered necessary, ESIA studies will dwell around the following information which must be obtainedas minimum:- Pest and beneficial populations in the field crop; Assessment of economic pest damage; Target crops and possibly growth stages; Recommended pesticides for the crop and its problem, their price and where obtainable; Pests and beneficials spectrum covered, including growth stages of the target organisms; Dose rates, dilution, timing and frequency of application; Waiting period (particularly for vegetables and stored produce); Method of application and equipment; Costs of application; Precautions to be taken (safety gears and measures); and Storage conditions and shelf life. 8.3.3 The IPM Strategies for Promoting its Adoption The main strategy to promote IPM in the project area could be embedded as: “Sensitize-Capacitate-Adapt and Scale Out”. All key stakeholders are sensitized on the benefits of IPM, and the necessary capacity provided at different levels. This is mainly; training, provision of resources and logistic support. Page 76 of 110 Technological options are then tested in collaboration with Research Extension and farmers and those proven to work are adopted and spread by farmers among themselves. As the process becomes dynamic and self-propelling, the technical team continues into new areas and the extension agents continue to backstop. Participatory approaches and tools (IPM working groups, Farmer Field Schools (FFS) etc) are the hub of the strategy, and where necessary, the strategy avoids duplication of efforts by consolidating outputs and experiences from the previous pilot IPM Tanzania/GTZ project and other IPM/ FFS projects. Since the IPM strategy has not been widely adopted, the SAGCOT could adequately mainstream the IPM policy directives, organize and coordinate IPM platform nationally and or regionally. The strategy could bring on board other non-government IPM initiatives (Private Sector, NGOs and Development projects) whose approaches and strategies are not integrated into the national strategy. For some reasons of lack of adequate and sustainable resource allocation, popularization of IPM strategy outside the former pilot area has been limited, and therefore use of technologies and experiences from previous projects has not been fully exploited. SAGCOT could therefore make use of this experience where applicable. However, SAGCOT project initiatives and operational procedures on IPM could be the fundamental process through which IPM can be popularized. The strategies and operational procedures could also be complemented by strategies from elsewhere in Africa. 8.3.4 SAGCOT to Advice Investors on IPM Practices As a rule of thumb, Farmers practicing IPM are regularly advised by the agricultural extensionists who could receive training on IPM from projects and elsewhere. This is part of their day-to-day activities but due to problems of transport and other logistic support, advice to farmers throughout the cropping cycle cannot be guaranteed. SAGCOT could harmonize with the local government authorities to organize field days for IPM farmer groups where many farmers are advised at a time. Moreover, SAGCOT could fund the preparation and printing of extension material and be provided to the extension services. Other avenues for disseminating information could include the use of mass media, particularly the radios, TVs and annual agricultural shows at district and regional levels. 8.3.5 SAGCOT to Support IPM Training in Research and Training Institutions Currently, in the curriculum of MAFC agricultural colleges, IPM is a subtopic under a major topic of Insect Pest Control Methods, and it is the last on the list of these subtopics. Other topics include methods of controlling field and storage pests, physical and mechanical control, biological control, legislative control, cultural control, host plant resistance and chemical control. Students are only made aware of IPM but nothing detailed. The learning objective in the curriculum states that students should be able to explain the importance of IPM in conserving biodiversity. Sokoine University of Agriculture has a pest management centre. The centre provides tailor made training on IPM on request. In the faculty of agriculture, IPM is a subject in pathology, entomology and weed science. At master’s degree, IPM is one of the optional research subjects (personal communication). Generally, there is not a common understanding of IPM among training institutes at different levels due to misconceptions reflected in some of the curricula. Lack of policy direction with regard to IPM research and training is a limitation in integrating IPM training in academic and research institutions. However, the aforementioned inclusion of IPM in the curricula at different levels of training and research institutions is an opportunity to capitalize on in capacity building and mainstreaming of IPM training. 8.3.6 SAGCOT to Support IPM Training and National Policy Since Farmer Field Schools have been embraced within the extension service as participatory approach of choice, in support of this, MAFC has designated four farmer training centres in the country (Mkindo– Morogoro; Bihawana- Dodoma; Inyala- Mbeya, and Ichenga- Iringa). The SAGCOT project could support by putting efforts to facilitate development of sustainable capacity to research and disseminate different options for testing/validation and adoption by farmers in the different agro ecological settings. In the FFS, farmers are very enthusiastic on the concept of biological control. They are good at scouting to identify the beneficial organisms but they may not tell why they are beneficial nor which pests the natural organisms Page 77 of 110 can control unless are given adequate trainings. In part this interest in biological control stems from their experience of various national biological control programs. The notable one is the classical biological control of cassava mealybug (Phenacoccus manihoti) by use of a wasp (Apoanagrus lopezi), an experience known by almost every Tanzania cassava farmer. Others include control of water hyacinth (Eichhorniae crassipes) using Neochetina bruchi and N. Eichhorniae and citrus woolly white fly using Encarsia haipiaensis. 8.4 SPECIFIC PEST MANAGEMENT MEASURES 8.4.1 Rules for Safe Handling of Pesticides All pesticides are poisonous and thus rules have to be observed to avoid human health impairment and environmental pollution. In addition to material safety data sheet (MSDS) accompanied with any given pesticide, the following general rules will have to be observed: Keep only closed original containers with labels. Keep pesticides under lock and key in a cool, dry and ventilated place away from fire, food, feed, water and out of reach of children. In the same room also the spraying equipment can be stored. Pesticides should be shelved and the floor be of cement to be able to detect leakage and clean it early enough where applicable. Equipment for weighing and mixing pesticides should only be used for this purpose and be locked in the store. Protective clothing should be used only for spraying purposes. Absorb spillage immediately with sawdust or earth; sweep up, burn or bury. Have cement floor for better cleaning. Do not re-use empty containers. Empty containers should be burnt if possible or crushed and bury in a sanitary landfill. Use a well aerated store and sales room. Instruct your personnel on safety precautions before (!) it is too late. Make contacts to a qualified physician for emergencies. In view of the above, the use of protective equipment and capacity building on pesticide management aspects, which would be the responsibility of the Matching Grant applicant/ recipient, will be critical. 8.4.2 Recommended Pesticides in Tanzania Table 8.1 List of recommended and TPRI registered pesticides for crop production in Tanzania3 Chemical Common name *Oral LD50/kg WHO class Comments Insecticides Betacyfluthrin 500-800 II Biphenthrin Chlorpyrifos 135-163 Ib Deregister & Phaseout Cypemethrin 251-4125 III Cypermethrin + Dimethoate 251-4125 + 2350 III 3 This table has been slightly updated. Important notice is that an extraordinary meeting of the National Plant Protection Advisory Committee (NPPAC), a body responsible for review of the pesticide list, took place in February 2014; the new list has been approved and the Pesticide Registrar’s Office is expected to publish the list before June 2014. Page 78 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Deltamethrin 153-5000 III Dealtamethrin + Dimethoate 153-5000+2350 III Diazinon 220 II Dimethoate 2350 III Esfenvalerate 451 II Fenitrothion 800 II Fenvalerate 451 II Fenvalerate + Fenitrothion 451+ 800 II Flucythrinate Hydrmethyl Lambda cyhalothrin 243 II Permethrin 430-4000 III Pirimiphos methyl 2050 III Pirimiphos methyl + permethrin 2050 + 430-4000 III Profenophos 358 II Profenophos + cypermethrin 358 + 251-4123 II Quinalphos 62-137 Ib Deregister & Phaseout Nematicides Dazomet 520 II Isazophos 40-60 Obsolete Deregister & Phaseout Herbicides Atrazine Diuron Fluometuron Glyphosate Metolachlor + Atrazine Metalachlor + Dipropetrin Paraquat Dirty Dozen: should be banned with immediate effect Chemical Common name *Oral LD50/kg WHO class Comments Avicides Fenthion II Cyanophos II Rodenticides Bromodiolone Ia Coumatetralyl Ia Diphacinone Ia Fungicides Bronopol Chlorothalonil 10,000+ III Copper hydroxide 1,000 II Copper oxychloride 70-800 II Cupric hydroxide 1,000 II Cuprous oxide Cyproconazole 1,000 II Hexaconazole 2189 III Mancozeb 5000+ III Metalaxyl + Mancozeb 633 + 5000+ III Page 79 of 110 Chemical Common name *Oral LD50/kg WHO class Comments Penconazole Propineb 1,000 II Triadimefon 1,000 II Sulfur As expressed in the footnote 3 above, the above list is subject to review by relevant authorities in Tanzania. SAGCOT Investment Project will adhere to reviewed list(s) that will be released by such authorities any time during the implementation of the project. As part of monitoring and evaluation (Section 8.5), the project will also inform the authorities of pesticides required to be phased out for reported health concerns. 8.4.3 Pesticides Banned in Tanzania The following pesticides considered as persistent organic polluntants (POPs) are banned in Tanzania and will therefore not recommended for use by any investor under SAGCOT: Aldrin, Camphechlor; Chlordane; Ddt; Dibenzofurans (Chlorinated); Dieldrin; Endrin; Heptachlor; Hexachlorobenzene; Mirex; Polychlorinated Biphenyls; and Polychlorinated Dibenzo-P-Dioxins. On the other hand, the importation and use of chemicals indicated in the table below are Subject to the Prior Informed Consent (PIC) procedure in Tanzania. Table 8.2 List of pesticides whose use are subject to the Prior Informed Consent (PIC) procedure in Tanzania Chemical Category Registration Status in Tanzania Import Decision 2,4,5-T and its salts and esters Pesticide Not registered No consent Aldrin Pesticide Restricted registration for use in soil against termites Consent Binapacryl Pesticide Not registered No consent Captafol Pesticide Banned since 1986 No consent Chlordane Pesticide Restricted registration for use in soil against grubs, termites, ants and crickets Consent Chlordimeform Pesticide Not registered No consent Chlorobenzilate Pesticide Not registered No consent DDT Pesticide Banned for agricultural use, restricted for public health Consent for public health Dieldrin Pesticide Restricted registration for emergency cases in limited amount consent Dinitro-ortho-cresol (DNOC) and its salts (such as ammonium salt, potassium salt and sodium salt) Pesticide Not registered No consent Dinoseb and its salts and esters Pesticide Not registered No consent 1,2-dibromoethane(EDB) Pesticide Restricted registration for fumigation application on soil consent Ethylene dichloride Pesticide Not registered No consent Ethylene oxide Pesticide Not registered No consent Fluoroacetamide Pesticide Not registered No consent HCH (mixed isomers) Pesticide Not registered No consent Chemical Category Registration Status in Tanzania Import Decision Heptachlor Pesticide Registered for use in various crops against termites and other soil pests consent Hexachlorobenzene Pesticide Not Registered No consent Lindane Pesticide Registered hides and skins Consent Mercury compounds, including inorganic mercury compounds, alkyl mercury compounds and alkyloxyalkyl and aryl mercury compounds Pesticide Not Registered No consent Monocrotophos Pesticide Not registered No consent Page 80 of 110 Chemical Category Registration Status in Tanzania Import Decision Parathion Pesticide Banned in 1986 No consent Pentachlorophenol and its salts and esters Pesticide Not registered No consent Toxaphene Pesticide Banned in 1986 No consent Dustable powder formulations containing a combination of: - Benomyl at or above 7 per cent, - Carbofuran at or above 10 per cent,& - Thiram at or above 15 per cent Severely hazardous pesticide formulation Not registered No consent Monocrotophos (Soluble liquid formulations of the substance that exceed 600 g active ingredient/l) Severely hazardous pesticide Not registered No consent Methamidophos (Soluble liquid formulations of the substance that exceed 600 g active ingredient/l) Severely hazardous pesticide Not registered No consent Phosphamidon (Soluble liquid formulations of the substance that exceed 1000 g active ingredient/l) Severely hazardous pesticide Not registered No consent Methyl-parathion (emulsifiable concentrates (EC) at or above 19.5% active ingredient and dusts at or above 1.5% active ingredient) Severely hazardous pesticide Banned in 1986 No consent Parathion (all formulations – aero-sols, dustable powder (DP), emulsifiable concentrate (EC), granules (GR) and wettable powders (WP) - of this subs- tance are included, except capsule suspensions (CS)) Severely hazardous pesticide formulation Not registered No consent Source: Designated National Authority - Prio Informed Consent Procedure (DNA PIC) 8.5 MONITORING AND EVALUATION ARRANGEMENT Successful implementation of IPMP will require regular monitoring and evaluaton of activities undertaken by individual SAGCOT investors. It is also crucial to evaluate the prevailing trends in the benefits of reducing pesticide distribution, application and misues as well as the progress in national policy reform regarding IPM implementation and regulatory control on handling and use of pesticides. New situations on pesticides risks that arise during project implementation should also be monitored. The indicators that require regular monitoring and evaluation during the programme implementation include the following: The IPM capacity building SAGCOT investors; Numbers of investors who have adopted IPM practices as crop protection strategy in their crop production efforts; evaluate the rate of IPM adoption; How many investors have adopted IPM and improved the production derived from adopting IPM; Economic benefits: increase in crop productivity due to adoption of IPM practices; increase in revenue resulting from adoption of IPM practices, compared with conventional practices; Numbers of IPM networks operational and types of activities undertaken; Extent to which pesticides are used for crop production; Effeciency of pesticide use and handling and reduction in pesticide poisoning and environmental contamination; Levels of reduction of pesticide use and handling and reduction in pesticide poisoning and environmental contamination; Number of IPM participatory research project completed; Pesticide residues in groundwater or in surface water downstream from irrigation schemes; Pesticide residues in food (e.g.: crops, drinking water, fodder, livestock); Impact on non-target organisms (e.g.: beneficial insects, fish and other aquatic life, wildlife, non- target crops and plants through herbicide drift). Page 81 of 110 Influence of the results of IPM participatory research on implementation of IPM and crop production; and Overall assessment of activities that are on-going according to plans; activities that need improvement; and remedial actions required. The above indicators will have to be appropriately made part of Environmental and Social Management Plan (ESMP) and Environmental Monitoring Plan (EMP) for any individual category A or B subproject. The ESMP include monitoring measures, parameters to be measured, sampling methods to be used, sampling locations, analytical techniques to be used, frequency of measurements, recording of data, data analysis, and dissemination of information collected and decision reached. The ESMP and EMP will define thresholds that will signal the need for corrective actions. 8.6 WORKPLAN AND BUDGET The SAGCOT Centre will be responsible in the implementation of this IPMP and estimated costs for the various activities under this program will be build in the budget. Most funds would be provided by the Matching Grants applicants as part of their co-financing. The core activities will include capacity building, advisory services, environmental management, and project management. Annual workplan will be developed by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre in consultation with all key stakeholders. Approximately USD 1,375,000.00 will be required to effectively implement the IPMP over a five-year period (Table 8.3 below). Page 82 of 110 Table 8.3: Workplan and Budget for IPM implantation Line item Year 1 Year 2 Year 3 Year 4 Year 5 Total (USD) 1. Capacity Building 1.1 IPM orientation workshop for MGF recipients/ beneficieries 50,000 0 0 0 0 50,000 1.2 Annual workshops on progress and reviews are held by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre 0 30,000 30,000 30,000 30,000 120,000 1.3 Hiring of Project IPM Advisor responsible for capacity building, coordinanation, monitoring and evaluation 25,000 25,000 25,000 25,000 25,000 125,000 Sub-total 75,000 55,000 55,000 55,000 55,000 295,000 2. Advisory Services 2.1 IPM diagnostic baseline surveys are undertaken at the beginning of the Project 50,000 0 0 0 0 50,000 2.2 IPM technologies are developed (field guides/IPM materials) and made available for MGF applicants and recepients 10,000 10,000 10,000 10,000 10,000 50,000 2.3 Create and promote public awareness programes and advocacy 15,000 10,000 5,000 5,000 5,000 40,000 2.4 Undertaking regular pest/ vector surveillance 0 30,000 30,000 30,000 30,000 120,000 Sub-total 75,000 50,000 45,000 45,000 45,000 260,000 3. Environmental Management 3.1 Pesticides risk reduction through IPM implementation are integrated and streamlined into ESMPs and EMP of SAGCOT’s specific invetments 70,000 50,000 0 0 0 120,000 3.2 Support to IPM research and development in the project area 100,000 0 100,000 0 100,000 300,000 Sub-total 170,000 50,000 100,000 0 100,000 420,000 4. Project Management 4.1 IPMP implementation coordination 30,000 30,000 30,000 30,000 30,000 150,000 4.2 Monitoring and evaluation of IPMP implementation 50,000 50,000 50,000 50,000 50,000 250,000 Sub-total 80,000 80,000 80,000 80,000 80,000 400,000 Grand Total 400,000 235,000 280,000 180,000 280,000 1,375,000 Page 83 of 110 Workplan Notes 1. Capacity Building Notes 1.1 IPM orientation workshop for MGF recipients/ beneficieries This workshop is recommended to be done in the first year of project implementation. It could as well be scheduled to be done alongside all other safeguard tools (SRESA, ESMF and RPF) to all MGF recipients and other key stakeholders. 1.2 Annual workshops on progress and reviews are held by SAGCOT Catalytic Fund in collaboration with SAGCOT Centre These will be workshops for disseminating progress made and challenges encountered in the implementation of IPM requirements. 1.3 Hiring of Project IPM Advisor responsible for capacity building, coordinanation, monitoring and evaluation Given the nature and the size of the project, and the expected magnitude of pesticide use in the entire project area, a local national IPM advisor is being proposed to coordinate all matters related to IPM. It should be noted that it could be appropriate to get an advisor who can cover for SRESA, ESMF and RPF but IPM needs an expert with specialized knowledge and skills. 2. Advisory Services 2.1 IPM diagnostic baseline surveys are undertaken at the beginning of the Project These surveys would give current baseline data in specific project areas which could also be included in EIA studies. 2.2 IPM technologies are developed (field guides/IPM materials) and made available for MGF applicants and recepients Field guides could be needed for some specific pesticides 2.3 Create and promote public awareness programs and advocacy The programs could be in form of TV and radio jingles, posters, and sensitization workshops. 2.4 Undertaking regular pest/ vector surveillance Field assessment and sample collection as monitoring/ control studies. 3. Environmental Management 3.1 Pesticides risk reduction through IPM implementation are integrated and streamlined into ESMPs and EMP of SAGCOT’s specific invetments Refer to activity 2.1 above 3.2 Support to IPM research and development in the project area SAGCOT centre could work with relevant research institutions such as Tanzania Pesticide Reserach Institute (TPRI) and Sokoine University of Agriculture (SUA) to undertake adaptation research and development in SAGCOT project area. 4. Project Management 4.1 IPMP implementation coordination Supervison and general coordination responsibilities. 4.2 Monitoring and evaluation of IPMP implementation For routine and ad hoc vfield visits for monitoring and evaluation missions. Page 84 of 110 9. RECOMMENDAITONS In order for the SAGCOT to ensure compliance with OP 4.09 and adopt ecologically-based IPM as the standard approach to pest management, the following are recommended: (i). Promote IPM by following the ways presented in this document; (ii). Establish ecologically-based IPM as a guiding principle for development at SAGCOT and realign relevant activities and strategies to support rather than undermine IPM and OP 4.09; (iii). Discourage conflicts of interest by screening out inappropriate SAGCOT partnerships that threaten to undermine IPM; (iv). Encourage effective collaboration across IPM projects, sectors and departments to support the integration of IPM and sustainable agriculture into SAGCOT; (v). Make better use of locally and regionally available knowledge and expertise in IPM and improve collaboration with farmers groups, NGOs, national and international institutions with expertise in participatory and environmentally sustainable approaches to agriculture; and (vi). A new/ reviewed list of approved pesticides is expected to be published before June 2014. This will have to be observed by the SAGCOT Invetsment Project management for adoption. 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Page 90 of 110 APPENDICES Appendix 1: Names of Experts Involved in Preparing This IPMP for SAGCOT Expert 1: Team Leader Expert 2 Expert 3 Kayonko Juma Kayonko, Registered Environmental Expert, (NEMC/EIA/0162 and NEMC /EA/0034), 10th FL, Mawasiliano Towers, 20 Sam Nujoma Road, P. O. Box 30, Dar es Salaam, Tanzania Mobile: (+255) 0787/ 0754 616 700 Email: [email protected] Skype: juma.kayonko Gasana Damian Rwabufigiri. Officer In Charge PQPS Dar es salaam Port Field officer Outbreak pest control. Ministry of Agriculture Food Security and Cooperatives. Plant Health Services P. O. Box 9071, Dar es Salaam, Tanzania Mobile:+255784410184. +255762787336 E-mail [email protected], [email protected] Lazaro W. Kitandu, National IPM Coordinator, Ministry of Agriculture, Food Security and Cooperatives, Plant Health Services, P. O. Box 54802, Dar Es Salaam Phone: +255 22 286 5641/2 Cell: +255 754 673 154 Email: [email protected] Skype: lazaro.kitandu Appendix 2: Persons Consulted During the Preparation of IPMP for ASDP Ministry of Agriculture and Food Security Dr. George Sempeho, DED Mr. Chacha Nyakomari, ASDP Mr. Muro, PADEP Mr. Masija, SIIP Mr. Maro, FAO/Food Security Mr. S. Semgelewe, Planning Dr. L. Ngatunga, DED Ministry of Water and Livestock Development Mr. D. Shirima Principal Economics Planner Policy and Planning Division Dr. H. Mjengera Director Water Laboratories Unit Mr. J. Mihayo Director Water Resources Division Dr.. R. Mngodo Head Hydrology and Geographic Information Systems (GIS) Unit Water Resources Division Division of Environmental, Vice President Office Ms. Angelina Madate Assistant Director, Pollution Control Mr. Muungi Assistant Director, EIA National Environmental Management Council Ms. E.Kerario Director, EIA Mr. P. Kijazi Pollution Control Officer Agricultural Research Institute Ukiriguru Mr. Peter Kapingu ZDRD – Lake Mr. Robert Kileo Zonal Research Coordinator Ms. Epihania Temu Zonal Information Liaison Officer Musingwe District Council Mr. Michael Fundo District Agriculture and Livestock Officer Mr. Gerald Krange SMS Mechanization Mr. Kachrima Manager, Participatory Irrigation Development Project Page 91 of 110 Kwimba District Council Mr. Stephen M. Solo District Extension Officer Mr. John Enock Extension Officer Agricultural Research Institute Selian Director of Zonal Research NP Massawa - Zonal Research Coordinator A.K.Kissiwa - Zonal Extension Liaison Officer Roma Ngatoluwa - Head of Special Program Hussein Mansoor - Scientist Special Programme F.Ngulu - Phytopathologist S.Sluma - Entomologist Kitgenge - Breeder Matovo - Agronomist Mbaga - Entomologist Peter Xavery - Socio-economist/database management Phillemon Mushi - Computer Manager and NZARDI Website Manager Horti-Tengeru Research Institute Mr. Safamali Tengeru – Division of Plant Health Services Mwangi Jubilant - IPM – Technical Adviser (Northern Zone) M.S. Marawit - Plant Health Service Inspector K.K Mngara Post-Harvesting Management Coordinator Steven Mirau - Bird Control Unit Wilferd Mushobzi - Arm worms – National Control Center Coordinator Tanzania Pesticides Research Institute Charles J. Mkangirwa Director of Research Jonathan Ak’habuhaya Registrar of Pesticides Arusha Municipal Council Joseph Y. Mkwizu Coordinator- SCAPA Aremeru District Council District Planning Officer Mwihayo SMS - Irrigation Tanzania Coffee Research Institute Grace Chipangohelo Prinicipal Research Officer Msonjo Humphrey Temu Extension Agronomist Muheza District Council Manpower officer Planning officer Isipor Mweumpya DALDO Mzirya Agriculture Extension Officer Agriculture Research Institute Mlingano Dr. Adolf Nyaki Depute Director – Eastern Zone Ms. Catherine Senkoro Information Liaison Officer Joseph D.J. Mbogoni GIS Unit Shabani Hamisi Coordinator for Sisal Research Mrs Lady Swai Plant Pathologist Page 92 of 110 Agriculture Research Institute Ilonga Joseph Asenga – Breeder Sokoine University of Agriculture Professor Ludovick Kinabo - Project Coordinator TARP II – SUA Project Professor A.J.P Tarimo - Extension services and linkage specialist Professor LLL Lulandala - Agroforestery researcher Profesor Vicent Nsoloma - Coordinator – Mushroom research Dr. A. Massawe - Pest Management Centre Dr. L.S Mulungu - Pest Management Centre Professor K.P Sibuga - Project Coordinator - ICE Dr. Gaspar Ashimogo - Entrepreneurship and Agribusiness Manager – The Focal Programme Tabora District LGA Ms. R Elipenda - District Executive Director Uyui District Council Mr. F. Kashiridye - District Livestock Devt Office Uyui District Council Mr. M. Ndunguru - Plant Protection Office Uyui District Council Mr. T. Toziri - Livestock Ward Extension Officer Magiri Uyui District Council Mr. H. Ikandilo - Ward Executive Office Magiri Uyui District Council ZARDI Western Zone Dr.B. Mbaga Zonal Director – Tumbi Mr B. Gama Zonal Research Liason Coordinator Mr. R. Shenkalwa Head, Crop Sciences Mr. J. Chiligati Head Research Extension Officer Mr. M. Kusekwa Head Livestock Research Program Dr. D. Byamungu Ag. Head, Crop Research Program District staff Mr. L. Muliahela Ag. District Executive Director and District Agricultural & Livestock officer Mbeya (Rural) Mr. M. Mwandiga Ag. District Planning Offier Mbeya (Rural) Mr. M. Matambi IPM Specialist District Agr & Livestock Devt Mbeya (Rural) Page 93 of 110 Mr. G. Lihemula Land use Planner District Agr. & Livestock Office Mr. C. Mtono District Agr. & Livestock Office Mbeya (Rural) Ms. S. Msemwa District Agr. & Livestock Extension Office Mbeya (Rural) Southern Highlands Zone staff Dr. M Msabaha Zonal Director – Uyole Dr. R. Mbwile Ag. Zonal Research Coordinator and Head, Livestock Research Programme Dr. Z. Malley Head, Special Research Programme Mr. E. Kiranga Zonal Research Extension & Liason Officer Mr. C. Madata Head, Crop Research Program Ms. C. Kabungo Ag. Head, Socio-economic Unit Page 94 of 110 Appendix 3: An IPM Checklist for Planning and Implementing Pest Control on Crops I. Is Pest Control Necessary? A pest is an unwanted organism - animal, plant, bacteria, fungus or virus. What pest problem do you have? What collections are affected? ___________________________________ II. Will Your Pest Control Be Effective? What chemical or non-chemical treatment are you using? __________________________________ Is the problem persisting? __________________________________ Does the pest return? How often? __________________________________ Where is the pest problem? __________________________________ What is the original source of the pest? __________________________________ What does it like to eat? __________________________________ What is the pest's life cycle? __________________________________ What does it need to survive? (food, light, temperature, humidity, habitat) __________________________________ Integrated pest management uses biological and non-chemical methods to reduce and eliminate pest problems in the following steps: 1. Inspection (a) Pre-harvesting. Does the crop invite pests into the farm via the soil, other crops, wind, bad sanitation, etc. (b) Post-harvesting. Do storage facilities attract pests, or make the storage a better place for the pests to live? 2. Diagnosis & Reporting (a) Catch pest examples (do not squish); use sticky baited and/or unbaited traps. Lures might include pheromones or black (UV) lights. Page 95 of 110 Note: Some insects will not be attracted to baits or traps. (b) Collect examples of pest damage and waste. (c) Have an entomologist identify the pest. (d) Learn the pest's preferred diet, life cycle and habitat. (e) Record the location and date pests were found to determine what areas of the collection are infested. 3. Planning Integrated Pest Management Match the pest control treatment to the particular pest: to where it lives and what it eats, to the crop.. (a) Mechanical and physical control. These constitute the physical collection and subsequent destruction of pests. (b) Cultural control. These constitute sanitation and farm hygiene, selection of planting sites and selection of planting dates (avoids pest attack) and intercropping/strip cropping/ crop rotation, trapping/pseudostem and mulching/solarization (suppress pest population) (c) Use of pest resistant plants. This is genetically inherited ability of plant species to withstand or tolerate pests or diseases. Have you used pest resistant plants? (d) Biological control. These use natural occurring organisms to regulate pest population to acceptable levels. Will another organism solve the problem or combines with other control measures? (e) Chemical control. This is the use of pesticides to control pests. Try to avoid use of pesticides or try local treatment, specific to the habits of the pest. 4. Implementing Pest Management Plan (a) Inform everyone in the village, ward and districts why changes must be made and how they can change their habits. (b) Record what you have done, the date it was done, and where it was done. (c) Investigate any IPM method you plan to use: or pesticides use is it legal and the least invasive or least toxic method available? (d) Apply biological pest control methods properly. (e) Know what dosage (concentration) to use and in what form of botanic pesticides. (f) Know how long a treatment lasts at the temperature and relative humidity of your climate (g) Be certain that a pesticide will not affect vegetation or groundwater. Know how safe it is for humans. 5. Evaluate the Results (a) Monitor with sticky traps, baits, pheromone traps, or black light traps; document numbers, location, Page 96 of 110 and date. Check traps on a regular basis (every week or every month). (b) Survey a sample of the susceptible collection. For example, look in a different part of your farm every month to inspect different pests. III. How Toxic is a Pesticide to You? Toxic means poisonous. Types of toxicity include: (1) Acute poisoning is measured as LD50, meaning the lethal dosage for 50 percent of the animals tested. Sometimes it is measured as LC50 meaning the lethal dosage in the air for 50 percent of the animals tested. The lower the LD50 or the LC50, the more poisonous the pesticide. (2) Chronic poisoning affects an animal or human over a long period of time after small, repeated doses. There is no widely recognized measure of chronic toxicity. Poisons enter the body in three, measurable, ways: (1) Dermal toxicity refers to poison absorbed through the skin. Some areas of the body are more susceptible than others. (2) Oral toxicity refers to poison that is ingested. Pesticides on hands can be ingested while eating, drinking or smoking. (3) Inhalation refers to poisons breathed through your nose. Breathing the vapor of the pesticide can cause harm. A pesticide is a chemical or other agent that will destroy a pest or protect something from a pest. There are two types: (1) A residual pesticide destroys pests and keeps them from causing damage for long periods of time after it is applied. (2) A short-term pesticide breaks down almost immediately after application into nontoxic by- products. For example, a fumigant is a poisonous gas that kills when absorbed or inhaled. Most are highly toxic but have no residual effects. IV. Will Farmer Field School approach to IPM be useful? This approach should be promoted by ASSP and IPM Farmer Groups play key role in dissemination of ecological based pest management. Is IPM integrated into the Programme activities of each component and is it in compliance with OP 4.12? . Page 97 of 110 Appendix 4: Pesticide Classification List – WHO Table1: Extremely hazardous (Class 1a) technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Aldicarb Difethialone Parathion – methyl 1 Brodifacoum Diphacinone Phenylmercury acetate Bromadiolone Disulfoton Phorate Bromethalin Ethoprophos Phosphamidon Calcium cyanide Flocoumafen Sodium fluoroacetate Captafol Fonofos Sulfotep Chlorethoxyfos Hexachlorobenzene Tebupirimfos Chlormephos Mercuric chloride Terbufos Chlorophacinone Meviphos Difenacoum Parathion Table 2: Highly hazardous (Class 1b) technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Acrolein Ethionfencarb Omethoate Ally alcohol Famphur Oxamyl Azinphos – methyl Fenamiphos Oxydemeton-methyl Azinphos- methyl Flucythrinate Paris green (C) Blasticidin – S Fluoroacetamide Pentachlorophenol Butocarboxim Forrmetanate Pindone Butoxycarboxim Furathiocarb Pirimiphos-ethyl Cadusafos Heptenophos Propaphos Calcium arsenate Isazofos Propetamphos Carbofuran Isofenphos Sodium arsenate Chlorfenvinphos Isoxathion Sodium cyanide 3-chloro-1,2-propanediol Lead arsenate Strychnine Coumaphos Mecarban Tefluthrin Coumatetralyl Mercuric oxide Thallium sulfate Zeta-cypermethrin Methamidophos Thiometon Demeton-S-methyl Methidathion Thiometon Dichlorvos Methidocarb Triazophos Dicrotophos Methomyl Vamidothion Dinoterb Monocrotophos Warfarin Edinofenphos Nicotine Zinc phosphide Table 3: Moderately hazardous (Class II technical grade active ingredients of pesticides (common name) – not permissible in the SAGCOT Investment Project Alanycarb Endosulfan Paraguat Anilofos Endothal-sodium Pebulate Azaconazole Esfenvalerate Permethrin Azocyclotin Ethion Phenthoate Bendiocarb Etrimfos Phosalone Bensulide Fenitrothion Phoxin Bifenthrin Fenobucarb Piperophos Bilanafos Fepropidin Pirimicarb Bioallethrin Fenpropathrin Prallethrin Bromoxynil Fenthion Profenofos Brobuconazole Fentin acetate Propiconazole Page 98 of 110 Bronopol Fentin hydroxide Propoxur Butamifos Fenvalerate Prosulfocarb Butymine Fipronil Prothiofos Carbaryl Fluxofenim Pyraclofos Carbosulfan Formothion Pyrazophos Cartap Pyrethrnis Fuberidazole Chloralose Gamma-HCH Pyroquilon Cholordane Guazatine Quinalphos Chlofenapyr Haloxyfop Quizalofop-p-tefuryl Chlorphonium chloride Heptachlor Rotenone Chlorpyrifos Imazalil Sodium fluoride Clomazone Imidacloprid Sodium hexafluorosilicate Copper sulfate Iminoctadine Spriroxamine Cuprous oxide Ioxynil Sulprofos Cyanazine Ioxynil octanoate Terbumeton Cyanophos Isoprocarb Tetraconazole Cyfluthrin Lambda-cynalothrin Thiacloprid Beta-cyfluthrin Merchurous chloride Thiobencarb Cynalothrn Metaldehyde Thiocylam Cypermethrin Metam-sodium Thiodicarb Alpha-cypermethrin Methacrifos Triazamate Cyphermethrin Methasulfocarb Trichlorfon Deltamethrin Methyl isothiocyanate Tricyclazole Diazinon Metolcarb Tridemorph Difenzoquat Metribuzin Vernlate Dimethoate Molinate Xylylcarb Dinobuton Naban Diquat Naled Table 4: Slightly hazardous (Class III) technical grade active ingredients of pesticides (common name) – Permissible in the SAGCOT Investment Project under IPM Acephate Chlormequat (chloride) Dichlorbenzene Acetochlor Chloracetic acid Dichlorophen Acifluorfen Chlorthiamid Dichlorprop Alachlor Copper hydroxide Diclofop Allethrin Copper oxychloride Dienochlor Ametryn Cucloate Diethyltoluamide Amitryn Cyhexatin Difenoconazole Azamethiphos Cymoxanil Dimepiperate Bensultap Cyproconazole Dimetethachlor Bentazone Dazomet Dimethamethryn Bromofenoxim Desmethryn Dimethipin Butroxydim Dicamba Dimethylarsinic acid Chinomethionat Dichlormid Diniconazole Page 99 of 110 Table 5: Technical grade active ingredients of pesticides unlikely to present acute hazard in normal use (Common name) – Permissible in the SAGCOT Investment Project Acephate Mecoprop Bentazone Acetochlor Mecoprop-P Bromofenoxim Acifluorfen Mefluidide Butroxydim Alachlor Mepiquat Chinomethionat Allthrin Metalaxyl Chlormequat (chloride) Dinocap Metamitron Chloracetic acid Diphenamid Metconazole Chloracetiamid Dithianon Methylarsonic acid Copper hydroxide Dodine Metolachlor Copper oxychloride Emphenthrin Myclobutanil Nuarimole Esrocarb 2-Napthyloxyacetic acid Octhilinone Etridiazole Nitrapyrin N-octylbicycloheptene Fenothiocarb Ametryn Dicarboximide Ferimzone Amitraz Oxadixyl Fluazifop-p-butyl Azamethiphos Paclobutrazol Fluchloralin Bensultap Pendimethalin Flufenacet Mecoprop Pimaricin Fluoroglycofen Mecoprop-P Pirimiphos-methyl Flurprimidol Mefluidide Prochloraz Flusilazole Mepiquat Propachlor Flutriafol Metalaxyl Propanil Fomesafen Metamitron Propargite Furalaxyl Metchnazole Pyrazoxyfen Glufosinate Methylarsonic acid Pyridaben Hexazinone Metolachlor Pyridaphenthion Hydramethylnon Myclobutanil Pyridate Iprobenfos 2-Napthyloxyacetic acid Pyrifenox Isoprothiolane Nitrapyrin Quinoclamine Isoproturon Ametryn Quizalofop Isouron Amitraz Resmthrin Malathion Azamethiphos Sethoxydim MCPA – thioethyl Bensultap Simetryn Sodium Dithianon Nuarimole Dodine Octhilinone Sulfluramid Empenthrin N-octylbicycloheptene Tebuconazole Tebufenpyrad Esrocarb Dicarboximide Tebuthiuron Etridiazole Oxadixyl Thiram Fenothocarb Paclobutrazol Tralkoxydim Ferimzone Pendimethalin Triadimefon Fluazifop-p-butyl Pimaricin Triadimenol Fluchloralin Pirimiphos-methyl Tri-allate Flufenacet Prochloraz Triclopyr Fluoroglycofen Propachlor Triflumizole Flurprimidol Propanil Undecan-2-one Flusilazole Propargite Uniconazole Flutriafol Pyrazonxyfen Ziram Fomesafen Pyridaben Furalaxyl Pyridaphenthion Cycloate Glufosinate Pyridate Page 100 of 110 Cyhexatin Hexazinone Pyrifenox Cyproconazole Hydramethylnon Quinoclamine Cymoxanil Iprobenfos Quizalofop Dazomet Isoprothiolane Resmethrin Desmetryn Isoproturon Sethoxydim Dichlormid Isouron Simetryn Dichlorbenzene Malathion Sodium chlorate Dichlorophen MCPA-thioethyl Sulfluramid Dichlorprop Mecoprop Tebuconazole Diclofop Mecoprop-P Tebufenpyrad Dienochlor Mefluidide Tebuthiuron Diethyltoluamide Mepiquat Thiram Difenoconazole Metalaxyl Tralkoxydim Dimepiperate Metamitron Triadimefon Dimethachlor Metconazole Triadimenol Dimethamethryn Methylarsonic acid Tri-allate Dimethipin Metolachlor Triclopyr Dimethylarsinic acid Myclobutanil Triflumizole Diniconazole 2-Napthyloxyacetic acid Undecan-2-one Dinocap Nitrapyrin Uniconazole Diphenamid Ziram Table 6: Technical grade ingredients of pesticides unlikely to present acute hazard in normal use (common name) – Permissible in the SAGCOT Investment Project Aclonifen Chlorthal-dimethyl Fenhexamid Acrinathrin Chlozolinate Fenoxycarb Alloxydin Cinmethylin Fenpiclonil Amitrole Cinosulfuron Fenpropimorph Ammonium sulfamate Clofentezine Fenuron Ancymidol Clomeprop Fenuron-TCA Anthraquinone Clopyralid Ferbam Asulam Cloxyfonac Flamprop Atrazine Cryolite (c) Flucarbazone-sodium Azimsulfuron Cycloprothrin Flucycloxuron Azoxystrobine Cyclosulfamuron Flufenoxuron Benalaxyl Cycloxydim Flumetralin Benafluralin Cyhalofop Flumetsulam Benfuresate Cyromazine Fluometuron Benomyl Daimuron Flupropanate Benoxacor Dalapon Flupyrsulfuron Benuslfuron-methyl Daminozide Flurenol Bifenox Desmedipham Fluridone Bioresmethrin Diafenthiuron Flurochloridone Biphenyl Dichlobenil Fluroxypyr Bispyribac Dichlofluanid Fluthiacet Bitertanol Diclomezine Flutolanil Borax Dicloran Tau-fluvalinate Page 101 of 110 Bromacil Diclosulam Folpet Bromobutide Diethofencarb Fosamine Bromopropylate Diflubenzuron Fosetyl Bupirimate Diflufenican Gibberellic acid Buprofezin Dikeculac Glyphosate Butachlor Dimefuron Hexaconazole Butralin Dimethirimol Hexaflumuron Butylate Dimethomorph Hexythiazox Captan Dimethyl phtalate Hydroprene Carbendazim Dinitramine Hymexazol Carbetamid Dipropil isocinchomerate Imazamethabenzmethyl Carboxin Dithiopyr Imazapyr Carpropamid Diuron Imazaquin Chlomethoxyfen Dodemorph Imazethapyr Chloramben Ethalfluralin Imebenconazole Chloransulam methyl Ethefon Inabenfide Chlorbromuron Ethirimol Iprodione Chlorfluazuron Ethofumesate Iprovalicarb Chloridazon Etofenprox Isoxaben Chlorimuron Famoxadone Kasugamycin Chlorothalonil Fenarimol Lenacil Chlorotoluron Fenbutatin oxide Linuron Chlorpropham Fenchlorazole Maleic hydrazide Chlorpyrifos methyl Fenchlorim Mancozeb Chlorsulfuron Fenfuram Maneb Mefenacet Pentanochlor Rimsulfuron Mepanipyrim Phenmedipham Siduron Mepronil Phenothrin Simazine Metazachlor Phnylphenol Spinosad Methabenzthiazuron Phosphorus acid Sulfometuron Methoprene Phtalide Sulphur Methoxychlor Picloram Tebutam Methyldymron Piperonyl butoxide Tecnazene Metiram Pretilachlor Teflubenzuron Metobromuron Promisulfuron Temphos Metosulam Probenazole Terbacil Metoxuron Procymidone Terbuthylazine Metsulfuron methyl Prodiamine Terbutryn Monolinuron Prometon Tetrachlorvinphos 2-(1-Naphthyl) acetamide Prometryn Tetradifon 1-naphthylacetic acid Propamocarb Tetramethrin Napropamide Propaquizafop Thiabendazole Naptalam Propazine Thidiazuron Neburon Propham Thifensulfuron-methyl Niclosamide Propineb Thiophanate-methyl Nicosulfuron Propyzamide Thiocarbazil Nitrothal-isopropyl Pyrazolynate Tolclofos-methyl Norfluzaron Pyrazosulfuron Tolyfluanid Ofurace Pyrimethanil Transfluthrin Page 102 of 110 Oryzalin Pyriminobac Triasulfuron Oxadiazon Pyripoxyfen Tribenuron Oxine-copper Pyrithiobac sodium Trietazine Oxycarboxyn Quinclorac Triflumuron Oxyfluorfen Quinmerac Trifluralin Penconazole Quinoxyfen Trifulusulfuron-methyl Pencycuron Quintozene Triforine Triticonazole Validamycin Vinclozolin Zine Page 103 of 110 Appendix 5: SAGCOT Corridor and Clusters Note: International border shown for Lake Malawi is the median boundary: this is not accepted by all riparian states. | false |
# Extracted Content CHAPTER 138 THE RUFIJI BASIN DEVELOPMENT AUTHORITY ACT [PRINCIPAL LEGISLATION] ARRANGEMENT OF SECTIONS Section Title PART I PRELIMINARY PROVISIONS 1. Short title. 2. Interpretation. PART II RUFIJI BASIN DEVELOPMENT AUTHORITY 3. Development Area. 4. Establishment of Authority. 5. Board of Directors. 6. Functions of the Authority. 7. President may give directions. PART III POWERS OF THE AUTHORITY 8. Powers in relation to generation of electricity. 9. President may transfer to Authority certain additional powers. PART IV ADMINISTRATION AND FINANCIAL PROVISIONS 10. Appointment of employees. 11. Remuneration and allowances of members of Board. 12. Superannuation benefits. 13. Agents and contractors. 14. Power of Board to delegate. 15. Funds and resources of the Authority. 16. Annual and supplementary budget. 17. Reserve and special funds. 18. Investment. 19. Power to borrow. 20. Accounts and audit. 21. Report by Board. PART V MISCELLANEOUS PROVISIONS 22. Liability of members. 23. By-laws. SCHEDULE CHAPTER 138 THE RUFIJI BASIN DEVELOPMENT AUTHORITY ACT An Act to establish Rufiji Basin Development Authority, to provide for the functions and powers of the Authority and for related matters. [1st July, 1975] [G.N. No. 146 of 1975] Act No. 5 of 1975 PART I PRELIMINARY PROVISIONS 1. Short title This Act may be cited as the Rufiji Basin Development Authority Act. 2. Interpretation In this Act, unless the context otherwise requires– "Authority" means the Rufiji Basin Development Authority established by section 4; "Board" means the Board of Directors of the Authority established under section 5; "Development Area" means the Rufiji Basin Development Area the boundaries of which are defined in accordance with the provisions of section 3; "Minister" means the Minister for the time being responsible for development planning; "Rufiji River" includes each and every tributary of that river. PART II RUFIJI BASIN DEVELOPMENT AUTHORITY 3. Development Area (1) For the purposes of this Act, the Rufiji Basin Development Area shall be an area of land through or along which the Rufiji River flows as and defined in accordance with the provisions of subsection (2). (2) The President may, by proclamation, define the boundaries of the Rufiji Basin Development Area and may, from time to time, by proclamation, vary the boundaries as so defined. 4. Establishment of Authority (1) There is hereby established an authority which shall be known as the Rufiji Basin Development Authority. (2) The Authority shall be a body corporate with perpetual succession and a common seal and shall be capable in law of suing and being sued in its corporate name, of purchasing, holding, alienating, managing and disposing of any property, whether movable or immovable and, whether by way of investment or otherwise, and capable of entering into any such contract as may be necessary or expedient for the performance of its functions under this Act or under any other written law. 5. Board of Directors (1) The management and functions of the Authority shall vest in a Board of Directors. (2) The provisions of the Schedule to this Act shall have effect as to the constitution and proceedings of, and otherwise in relation to, the Board of Directors. (3) The President may by order in the Gazette, amend, add to, vary or replace the Schedule to this Act. 6. Functions of the Authority The functions of the Authority shall be– (a) to generate electricity by means of hydro-electric works in the Development Area and to supply, on such terms and conditions as the Board may, subject to the provisions of this Act, approve, electricity so generated for the promotion of industries and the general welfare of the people of the United Republic; (b) to undertake measures for flood control; (c) to promote and regulate industrial activities within the Development Area; (d) to promote and regulate agricultural activities within the Development Area; (e) to promote and regulate the development of forestry within the Development Area and to take measures to ensure the prevention or minimisation of soil erosion; (f) to promote and regulate fishing industry in the rivers, lakes and dams within the Development Area; (g) to promote and regulate public inland water and road transport systems within the Development Area; (h) to promote tourism within the Development Area and to provide for or encourage the provision of facilities necessary or expedient for the promotion of tourism; (i) to do all such acts and things as, in the opinion of the Board may be necessary to uphold and support the credit of the Authority and to obtain and justify public confidence and, to avert and minimise any loss to the Authority; and (j) to do anything or enter into any transaction which, in the opinion of the Board, is calculated to facilitate the proper and efficient exercise by the Authority of its functions under this Act, including– (i) the carrying on of any of the activities of the Authority in collaboration with any other person; (ii) the acquisition by agreement, of interests in companies and firms engaged in activities in which the Authority may lawfully be engaged under this Act and the management of the affairs or the continuance of the business of such companies and firms; (iii) the establishment of branches within the United Republic and elsewhere. 7. President may give directions The President may give to the Authority directions of a general or specific character as to the exercise by the Authority, of any of its functions under this Act and the Authority shall give effect to every such direction. PART III POWERS OF THE AUTHORITY 8. Powers in relation to generation of electricity (1) For the purposes of performing its function of generating electricity by means of hydro- electric works in the Development Area, the Authority shall have power to construct, maintain, operate, protect, manage and control works– (a) for the collection, diversion and storage of water in the Development Area; (b) for the generation and transmission of electricity; and (c) incidental or related to the construction, maintenance, operation, protection, management or control, of any works specified in paragraph (a) or (b). (2) The Authority shall have power to construct, maintain, operate, protect, manage and control, works which, in the opinion of the Board, are necessary or desirable for the purpose of preventing or mitigating injurious effects of any works referred to in subsection (1). 9. President may transfer to Authority certain additional powers (1) Where the President is satisfied that for the proper and efficient performance by the Authority of any of its functions under this Act, it is necessary or desirable that the Authority enjoy, in relation to the Development Area, any power which is by any other written law, conferred upon any other person, whether generally or in relation to any specified area, whether or not such specified area includes the Development Area or any part of it, the President may, by order in the Gazette, provide that, subject to such limitations and restrictions as he may in such order specify, the Authority may exercise such power in relation to the Development Area as if such power, were, in relation to the Development Area, conferred upon the Authority by such other written law. (2) Where the President makes an order under subsection (1) conferring upon the Authority any power provided for in any other written law, he may, by the same or by any subsequent order, modify such other written law to such extent as he may deem necessary for the avoidance of any inconsistency or conflict between the provisions of such other written law and the provisions of the order made under subsection (1) or for providing for an appeal against the decision of the Authority in the exercise of such power or for any matter incidental to or connected with the exercise by the Authority of such power. (3) The provisions of any order made under subsection (2) shall have the same effect as if such provisions were made by and set out in this Act. PART IV ADMINISTRATION AND FINANCIAL PROVISIONS 10. Appointment of employees (1) The Board may from time to time appoint at such salaries and upon such terms and conditions as it may think fit, such officers and employees of the Authority as it may deem necessary for the proper and efficient conduct of the business and activities of the Authority. (2) The President shall appoint a Director-General of the Authority who shall be the chief executive officer of the Authority. 11. Remuneration and allowances of members of Board The members of the Board shall be entitled to receive such remuneration, allowances and other benefits as the Minister may direct. 12. Superannuation benefits The Board may– (a) grant gratuities or other retirement allowances or benefits to the officers and employees of the Authority; (b) establish and contribute to a superannuation fund and a medical benefits fund for the officers and employees of the Authority; (c) require any officer or employee of the Authority to contribute to any such superannuation fund or medical benefits fund and fix the amounts and method of payment of such contribution. 13. Agents and contractors The Board may, from time to time, appoint and employ upon such terms and conditions as it thinks fit, such agents and contractors of the Authority as the Board may deem necessary. 14. Power of Board to delegate (1) Subject to subsection (6), the Board may from time to time, in writing under the seal of the Authority delegate, subject to such terms, conditions or restrictions as it may specify, to any committee of the Board or to any officer or employee of the Authority, all or any of the functions, powers, authorities or duties conferred by or under this Act upon the Authority or upon the Board, and where any delegation is so made the delegated function, power, authority or duty may be performed or, as the case may be, exercised by the delegatee subject to the terms, conditions or restrictions specified in the writing. (2) Any delegation under subsection (1) may be made to the holder of an office under the Authority specifying the office but without naming the holder and in every case each successive holder of the office in question and each person who occupies or performs the duties of that office may, without any further authority, perform or, as the case may be, exercise the delegated function, power, authority or duty in accordance with the delegation made. (3) The Board may revoke a delegation made by it under this section. (4) No delegation made under this section shall prevent the Authority or the Board from itself performing or exercising the function, power, authority or duty delegated. (5) Any delegation made under this section may be published in the Gazette, and upon such publication shall be judicially noticed and shall be presumed to be in force unless the contrary is proved. (6) The Board shall not have power under this section to delegate– (a) its power of delegation; or (b) any power conferred upon the Authority or the Board by an order under section 9 except where such order expressly allows such delegation; (c) the power to approve the annual budget or any supplementary budget or receipts and expenditure, the annual balance sheet or any statement of account. 15. Funds and resources of the Authority The funds and resources of the Authority shall consist of– (a) such sums as may be provided for the purposes of the Authority by Parliament, either by way of grant or loan; (b) any loan or subsidy granted to the Authority by the Government or any other person; (c) any sum or property which may in any manner become vested in the Authority as a result of the performance by the Authority of any of its functions. 16. Annual and supplementary budget (1) In this Act "financial year" means any period not exceeding twelve consecutive months designated in that behalf by the Board: Provided that the first financial year after the commencement of this Act, shall commence on the date of the commencement of this Act and may be of a period longer or shorter than twelve months. (2) Not less than two months before the beginning of any financial year, other than the first financial year, the Board shall, at its meeting specially convened for that purpose, pass a detailed budget in this Act called the annual budget, of the amounts respectively– (a) expected to be received; and (b) expected to be disbursed, by the Authority during that financial year. (3) If in any financial year the Authority requires to make any disbursement not provided for or of an amount in excess of the amount provided for, in the annual budget for the year, the Board shall, at a meeting, pass a supplementary budget detailing such disbursement. (4) The annual budget and every supplementary budget shall be in such form and include such details as the Minister may direct. (5) Immediately upon the passing of any annual budget or any supplementary budget the Board shall submit the same to the Minister for approval. (6) The Minister shall, upon receipt of the annual budget or any supplementary budget, approve or disapprove the same or may approve subject to such amendment as he may deem fit. (7) Where the Minister has approved with or without amendment, any annual budget or supplementary budget, the budget, as approved by him, shall be binding on the Authority which, subject to the provisions of subsection (8), shall confine its disbursements within the items and the amounts contained in the applicable estimates as approved by the Minister. (8) The Board may– (a) with the sanction in writing of the Minister, make a disbursement notwithstanding that such disbursement is not provided for in any budget; (b) from the amount of expenditure provided for in any budget in respect of any item, transfer a sum not exceeding fifty thousand shillings to any other item contained in such budget; (c) adjust expenditure limits to take account of circumstances not reasonably foreseeable at the time the budget was prepared, subject to submitting a supplementary budget to the Minister within two months of such alteration of expenditure limits becoming necessary. 17. Reserve and special funds The Board may, and shall, if so directed by the Minister, establish and maintain such reserve or special funds of the Authority as the Board or the Minister may consider necessary or expedient and shall make into or from any such funds, such payments as the Board may deem fit or, in the case of a fund established pursuant to a direction by the Minister, as the Minister may direct. 18. Investment (1) With the prior approval of the Minister, the Board may, from time to time, invest any part of the moneys available in any fund of the Authority, in such manner as the Board may deem fit. (2) The Minister may, after consultation with the Minister for the time being responsible for Finance, give the Board directions as to the disposal of the Authority's surplus funds and the Board shall give effect to every such direction. 19. Power to borrow (1) With the prior approval of the Minister, the Board may, from time to time borrow moneys for the purposes of the Authority, by way of loan or overdraft and upon such security and such terms and conditions relating to the repayment of the principal and the payment of interest as, subject to any direction by the Minister, the Board may deem fit. (2) A person lending money to the Authority shall not be bound to enquire whether the borrowing of that money by the Authority has been approved by the Minister. 20. Accounts and audit (1) The Board shall cause to be provided and kept proper books of accounts and records with respect to– (a) the receipt and expenditure of moneys by, and other financial transactions of the Authority; (b) the assets and liabilities of the Authority, and shall cause to be made out for every financial year a balance sheet and a statement showing details of the income and expenditure of the Authority and all its assets and liabilities. (2) Not later than six months after the close of every financial year the accounts including the balance sheet of the Authority relating to that financial year, shall be audited by the Tanzania Audit Corporation established by the Tanzania Audit Corporation Act. (3) As soon as the accounts of the Authority have been audited, and in any case not later than six months after such audit, the Board shall submit to the Minister a copy of the audited statement of accounts together with a copy of the report made by the auditors. (4) As soon as practicable after receipt by him of the copy of the statement together with the copy of the report submitted pursuant to subsection (3), the Minister shall lay a copy of the statement together with a copy of the auditors' report before the National Assembly. 21. Report by Board The Board shall, within six months after the end of each financial year, make a report to the Minister on the conduct of the Authority's business during that financial year and the Minister shall lay a copy of such report before the National Assembly, together with a copy of the statement of accounts required by section 20, to be laid before the National Assembly. PART V MISCELLANEOUS PROVISIONS 22. Liability of members Without prejudice to the provisions of section 284A of the Penal Code or of the Public Officers (Recovery of Debts) Act, no act or thing done or omitted to be done, by any member of the Board or by any officer, employee or agent of the Authority shall, if done or omitted bona fide in the execution or purported execution of his duties as such member, officer, employee or agent, subject any such person to any action, liability or demand. 23. By-laws (1) The Authority may, with the consent of the Minister make by-laws– (a) providing for the protection of hydro-electric and other works within the Development Area; (b) prohibiting or regulating access to any part or parts of the Development Area by unauthorised persons; (c) regulating the use of waters from the Rufiji River, lakes and dams within the Development Area; (d) designed to minimising pollution of the waters of any river, lake or dam within the Development Area; (e) providing for the safety of persons employed in the construction, maintenance, operation, protection, management or control of hydro-electric and other works within the Development Area; (f) generally in relation to any matter or thing which in the opinion of the Board it is necessary, expedient or desirable to make by-laws in order to enable the Authority to perform its functions under this Act or to exercise any power conferred upon it by or under this Act, efficiently. (2) There may be annexed to the breach of any by-law made under this section a penalty not exceeding a fine of twenty thousand shillings or a term of imprisonment not exceeding three years or both. (3) Where by an order made under section 9 any power to make regulations under any other written law in relation to any matter provided for in such written law is conferred upon the Authority, the Authority may exercise such power by making by-laws in relation to such matter as if such matter were a matter in relation to which the Authority is empowered by subsection (1) to make by-laws, and unless a contrary intention is expressed in the order under section 9, the Authority may annex to the breach of any such by-law a penalties specified in subsection (2), notwithstanding that, but for the provisions of this subsection, the provisions of subsection (2) would not have applied in relation to the breach of such by-law. SCHEDULE (Section 5(2)) 1. Constitution (1) The Board shall consist of the following members– (a) a Chairman appointed by the President; (b) the Director-General; (c) not less than eight and not more than ten other members appointed by the President. (2) The members of the Board shall, from among their number, elect a Vice-Chairman, who shall hold office for so long as he remains a member of the Board. (3) A member of the Board shall, unless his appointment is sooner determined by the Presidents or he otherwise ceases to be a member, hold office for such period as the President may specify in his appointment or if no period is so specified, for a period of three years from the date of appointment and shall be eligible for reappointment: Provided that a member who is a member by virtue of holding some other office, shall cease to be a member upon ceasing to hold that office. (4) Any member of the Board may at any time resign by giving notice in writing to the Permanent Secretary to the President's Office and from the date specified by the notice or, if no date is specified, from the date of the receipt of the notice by the Permanent Secretary, shall cease to be a member. 2. Secretary The Board may appoint any member of the Board or officer of the Authority or a public officer to be the Secretary of the Board. 3. Casual vacancies Where any member ceases to be a member for any reason before the expiration of the term of office, the President shall appoint another person and the person so appointed shall hold office for the remainder of the term of office of the predecessor. 4. Meetings (1) An ordinary meeting of the Board shall be convened by the Chairman and the notice specifying the place, date and time of the meeting shall be sent to each member at his usual place of business or residence not less than fourteen days before the date of such meeting and in case the Chairman is unable to act by reason of illness, absence from the United Republic or other sufficient cause, the Vice-Chairman may convene such meeting. (2) The Chairman or in his absence, the Vice-Chairman shall be bound to convene a special meeting of the Board upon receipt of a request in writing in that behalf signed by not less than five members of the Board: Provided that not less than fourteen days' notice of such meeting shall be given to all members of the Board in the manner prescribed in subparagraph (1). (3) The Chairman, the Vice-Chairman, or a temporary Chairman elected in accordance with the provisions of subparagraph (2) of paragraph 5 presiding at any meeting of the Board may invite any person who is not a member to participate in the deliberations of the Board, but any such person shall not be entitled to vote. 5. Procedure (1) One-half of the total number of the members of the Board or five members, whichever is the lesser number, shall form a quorum for a meeting of the Board. (2) In the absence of the Chairman from a meeting of the Board, the Vice-Chairman shall preside and in the absence of both the Chairman and the Vice-Chairman, the members present shall elect one of their number to be a temporary Chairman of that meeting. (3) At any meeting of the Board a decision of the majority of the members present and voting shall be deemed to be a decision of the Board and. In the event of an equality of votes, the Chairman of the meeting shall have a casting vote in addition to the deliberative vote. 6. Decision by circulation of papers Notwithstanding the provisions of paragraph 5, where the Chairman so directs, a decision may be made by the Board without a meeting by circulation of the relevant papers among all the members and the expression in writing of their views, but any member shall be entitled to require that any such decision is deferred until the subject matter shall be considered at a meeting of the Board. 7. Minutes of meetings Minutes of each meeting of the Board shall be kept and shall be confirmed by the Board at the next meeting and signed by the Chairman of the meeting. 8. The seal of Authority The seal of the Authority shall not be affixed to any instrument except in the presence of the Director-General or of the Secretary and one member of the Board. 9. Vacancies not to invalidate proceedings Subject to the provisions of paragraph 5 relating to quorum, the Board may act notwithstanding any vacancy in the membership and no act or proceeding of the Board shall be invalid by reason only of some defect in the appointment of a person who purports to be a member. 10. Signing of documents All orders, by-laws, regulations, directions, notices or documents made or issued by the Authority or by the Board shall be signed by– (a) the Director-General; or (b) any member of the Board or other officer of the Authority authorised in writing by the Director-General in that behalf. 11. Board may regulate its own proceedings Subject to the provisions of this Schedule, the Board shall have power to regulate its own proceedings. | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vo: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vi: REGIONAL REPORT: RUKWA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary......................................................................................................................................................... vi Illustrations..................................................................................................................................................................... xii CENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ....................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area .......................................................................................................................................................... 1 1.4 Climate............................................................................................................................................................... 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population.......................................................................................................................................................... 1 1.6 Socio-economic Indicators................................................................................................................................ 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture.................................................... 3 2.2 Census Objectives ............................................................................................................................................. 3 2.3 Census Coverage and Scope ............................................................................................................................. 4 2.4 Legal Authority of the National Sample Census of Agriculture...................................................................... 5 2.5 Reference Period ............................................................................................................................................... 5 2.6 Census Methodology......................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Holding Characteristics................................................................................................................................ 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Literacy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 23 3.3.4.3 Other Cereals.................................................................................................................. 26 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava........................................................................................................................... 27 3.3.5.2 Irish Potatoes .................................................................................................................. 28 3.3.6 Pulse Crops Production .................................................................................................................... 28 3.3.6.1 Beans............................................................................................................................... 30 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts ..................................................................................................................... 32 3.3.8 Fruits and Vegetables ........................................................................................................................ 33 3.3.8.1 Tomatoes ........................................................................................................................ 35 3.3.8.2 Cabbage .......................................................................................................................... 37 3.3.8.3 Chillies............................................................................................................................ 37 3.3.9 Other Annual Crops Production....................................................................................................... 40 3.3.9.1 Cotton .............................................................................................................................. 40 3.3.9.2 Tobacco .......................................................................................................................... 40 3.4 Permanent Crops........................................................................................................................................... 40 3.4.1 Coconuts ........................................................................................................................................ 43 3.4.2 Oranges ........................................................................................................................................ 45 3.4.3 Banana ........................................................................................................................................ 45 3.4.4 Cashew Nuts ..................................................................................................................................... 45 3.5 Inputs/Implements Use................................................................................................................................. 48 3.5.1 Methods of land clearing................................................................................................................... 48 3.5.2 Methods of soil preparation.............................................................................................................. 48 3.5.3 Improved seeds use........................................................................................................................... 50 3.5.4 Fertilizers use.................................................................................................................................... 51 3.5.4.1 Farm Yard Manure Use.................................................................................................. 51 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 52 3.5.4.3 Compost Use .................................................................................................................. 53 3.5.5 Pesticide Use..................................................................................................................................... 54 3.5.5.1 Insecticide Use................................................................................................................ 54 3.5.5.2 Herbicide Use................................................................................................................. 55 3.5.5.3 Fungicide Use................................................................................................................. 55 3.5.6 Harvesting Methods.......................................................................................................................... 56 3.5.7 Threshing Methods .......................................................................................................................... 56 3.6 Irrigation .................................................................................................................................................... 56 3.6.1 Area planted with annual crops and under irrigation....................................................................... 56 3.6.2 Sources of water used for irrigation................................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................................ 59 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iii 3.6.4 Methods of water application .......................................................................................................... 59 3.7 Crop Storage, Processing and Marketing .................................................................................................. 59 3.7.1 Crop Storage ..................................................................................................................................... 59 3.7.1.1 Method of Storage.......................................................................................................... 60 3.7.1.2 Duration of Storage ........................................................................................................ 60 3.7.1.3 Purpose of Storage.......................................................................................................... 61 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 61 3.7.2 Agro processing and by-products...................................................................................................... 62 3.7.2.1 Processing Methods........................................................................................................ 62 3.7.2.2 Main Agro-processing Products..................................................................................... 62 3.7.2.3 Main use of primary processed Products....................................................................... 63 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 63 3.7.3 Crop Marketing................................................................................................................................. 64 3.7.3.1 Main Marketing Problems.............................................................................................. 64 3.7.3.2 Reasons for Not Selling.................................................................................................. 64 3.8 Access to Crop Production Services............................................................................................................ 65 3.8.1 Access to Agricultural Credits ......................................................................................................... 65 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits............................................................................................ 65 3.8.1.3 Reasons for not using agricultural credits...................................................................... 66 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of crop extension messages.............................................................................. 66 3.8.2.2 Quality of extension ....................................................................................................... 68 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.2 Inorganic Fertilisers .......................................................................................................................... 68 3.9.3 Improved Seeds ................................................................................................................................. 69 3.9.4 Insecticides and Fungicide ................................................................................................................ 69 3.10 Tree Planting................................................................................................................................................... 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population....................................................................................................................... 73 3.12.1.2 Herd size......................................................................................................................... 73 3.12.1.3 Cattle Population Trend ................................................................................................. 75 3.12.1.4 Improved Cattle Breeds.................................................................................................. 75 3.12.2 Goat Production................................................................................................................................ 75 3.12.2.1 Goat Population.............................................................................................................. 75 3.12.2.2 Goat Herd Size ............................................................................................................... 77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 79 3.12.4 Pig Production .................................................................................................................................. 79 3.12.4.1 Pig Population Trend...................................................................................................... 79 TOC __________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iv 3.12.5 Chicken Production .......................................................................................................................... 81 3.12.5.1 Chicken Population ........................................................................................................ 81 3.12.5.2 Chicken Population Trend.............................................................................................. 81 3.12.5.3 Chicken Flock Size......................................................................................................... 81 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 82 3.12.6 Other Livestock ................................................................................................................................ 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming..................................................................................................................... 82 3.12.8 Access to Livestock Services ........................................................................................................... 84 3.12.8.1 Access to livestock extension Services.......................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to village watering points/dam .......................................................................... 85 3.12.9 Animal Contribution to Crop Production......................................................................................... 85 3.12.9.1 Use of Draft Power......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 86 3.12.9.4 Use of Compost ............................................................................................................ 86 3.12.10 Fish Farming..................................................................................................................................... 86 3.6.0 Access to Infrastructure and Other Services.................................................................................... 89 3.13 Poverty Indicators......................................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services.................................................................................... 89 3.13.2 Type of Toilets.................................................................................................................................. 90 3.13.3 Household’s assets............................................................................................................................ 90 3.13.4 Sources of Light Energy................................................................................................................... 90 3.13.5 Sources of Energy for Cooking........................................................................................................ 90 3.13.6 Roofing Materials............................................................................................................................. 91 3.13.7 Access to Drink Water...................................................................................................................... 91 3.13.8 Food Consumption Pattern............................................................................................................... 92 3.13.8.1 Number of Meals per Day.............................................................................................. 92 3.13.8.2 Meat Consumption Frequencies..................................................................................... 92 3.13.8.3 Fish Consumption Frequencies...................................................................................... 92 3.13.9 Food Security.................................................................................................................................... 92 3.13.10 Main Source of Cash Income........................................................................................................... 93 PART IV: RUKWA PROFILES................................................................................................................................ 95 4.1 Region Profile ................................................................................................................................................. 96 4.2 District Profiles............................................................................................................................................... 96 4.2.1 Mpanda .............................................................................................................................................. 96 4.2.2. Sumbawanga Rural............................................................................................................................ 98 4.2.3 Nkasi ................................................................................................................................................100 4.2.4 Sumbawanga Urban.........................................................................................................................102 ACRONYMS __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Rukwa region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A. Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Rukwa region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Rukwa region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Rukwa region were 172,261 out of which 114,069 (67.3%) were involved in growing crops only, 416 (0.2%) rearing livestock only and 57,776 (33.5%) were involved in crop production as well as livestock. However, there was no pastoralist which was found in the region. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off-farm income, livestock keeping/herding, permanent crops remittances and fishing/hunting and gathering. The region has a literacy rate of 72 percent. The highest literacy rate was found in Sumbawanga Rural and Sumbawanga Urban districts with (75%) followed by Nkasi district (71%) and Mpanda district (70%). The number of heads of agricultural households with formal education in Rukwa region was 118,763 (67%), those without formal education were 53,498 (31%) and those with only adult education were 6,019 (4%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Rukwa region 59,888 household members (35%) were involved in one off-farm income generating activity, 53,457 (31%) involved in two off-farm income generating activities and 18,456 (11%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 574,291 ha. The regional average land area utilised for crop production per crop growing household was only 2.4 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 303,393 hectares out of which 1,049 hectares (0.3%) were planted during short rainy season and 302,345 hectares (99.7%) during long rainy season. An estimated area of 203,500 ha (67.3% of the total planted area with annual and vegetable crops) was with cereals, followed by 77,017 hectares (18.0%) of pulses, (37,551 hectares, 12.4%), of roots and tubers, (28,595 hectares, 9.5%), oil seeds (28,178 hectares, 9.3%), cash crops (3,295 hectares (1.1%) and fruits and vegetables, (1,225 hectares (0.4%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii Cereal Crop Production The total production of cereals was 240,623 tonnes from a total planted area of 203,928 hectares. These cereal crops include: Maize, Paddy, Finger Millet, Sorghum, Wheat and Bulrush Millet Maize Maize is the dominant annual crop grown in Rukwa region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 73.6 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) are paddy, finger millet, sorghum, wheat, bulrush millets. Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Rukwa region during the long rainy season was 30,132. This represented 17.6 percent of the total crop growing households in Rukwa Region in the long rainy season. • Roots and Tuber Crops Production The total production of roots and tubers crops was 45,702 tonnes from planted area of 28,594 hectares. These root and tuber crops included: cassava, sweet potatoes, irish potatoes, yams and cocoyam. Cassava The area planted with cassava was larger than any other root and tuber crop in Rukwa in terms of planted area (8.3% of the total area planted with annual crops and vegetables) and it accounted for 87 percent of the area planted with roots and tubers. Oil Seed Production The total production of oilseed crops was 17,419 tonnes planted on an area of 28,520 hectares. These oil crops included groundnuts, sunflowers, soya beans and simsim. Pulse Crops Production The total area planted with pulses was 37,831 hectares. This area was planted with beans, bambaranuts, green grams, cowpeas and field peas. Fruit and Vegetables The total production of fruit and vegetables was 4,211 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 2,136 tonnes, which amounts to 48 percent of the total fruit and vegetable production, followed by cabbage 3,472 tonnes (18%) and chilies 1,973 tonnes (10%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 62,403 hectares which is 13 percent of the area planted with annual crops in the region. The most important permanent crop is coconuts which accounts for 24 percent of the total area planted with permanent crops followed by oranges (15%), banana (13%) and cashew (13%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Improved Seeds The planted area using improved seeds was 52,089 ha which represents 13 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was 13.4 percent which is slightly higher than the corresponding percentage use for the long rainy season (12.73%). Use of Fertilizers Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 367,237 hectares representing 85.6 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 45,411 ha which represented 10.6 percent of the total planted area (73.3 % of the area planted with fertiliser application). This was followed by compost (12,491 ha, 20.1%). Inorganic fertilizers were used on a very small area and represented only 6.6 percent of the area planted with fertilizers. Irrigation In Rukwa region, the area of annual crops and vegetables under irrigation was 41,089 ha representing 9.6 percent of the total area planted. The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 12.3 percent compared with 5 percent in the short rainy season. Crop Storage There were 228,187 crop growing households (87% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and pulses (104,155 households and 1,914 tonnes), paddy (14,828 households and 827 tonnes) and groundnuts and bambara nuts (1,674 households and 54 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 197,168 which represents 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Rukwa (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%). Agricultural Credit In Rukwa region, few agricultural households (1,022, 0.4%) accessed credit, out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got credit for agriculture purposes, whereas in Korogwe, Rukwa and Handeni districts only male households accessed credit. In Muheza district both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.96). Korogwe district had a relatively high proportion of households that received crop extension messages (84%), followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Rukwa (14%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 30,288. This number represents 11 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Lushoto District (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Rukwa (1%) Pangani (0.5%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 378,338. Cattle rearing is the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 350,210 head (92.6% of the total number of cattle in the region), 27,829 (7%) were dairy breeds and only 298 (1.4%) were beef breeds. Goats The number of goat-rearing-households in the region was 68,764 (26% of all agricultural households) with a total of 514,620 goats giving an average of 7 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 35,381 (13% of all agricultural households) with a total of 164,209 sheep giving an average of 5 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 176,806, raising 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Rukwa ranked eighth out of the 21 Mainland regions. Use of Draft Power The region has 738 oxen and they were only found in two districts, Korogwe and Kilindi with 592 and 146 head respectively. Rukwa region has 0.03 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 2,653 hectares of land. Fish Farming The number of households involved in fish farming was 1,423 (0.5 percent of the total agricultural households in the region). Korogwe was the leading district with 634 agricultural households involved in fish farming (1.4%) followed by Lushoto 430 (0.5%), Muheza 336 (0.7%) and Rukwa 23 (0.3%). Fish farming was not practiced in Pangani and Handeni districts. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x iv) Poverty Indicators Availability of Toilets It was estimated that 86.5 percent of all rural agricultural households used the traditional pit latrines, 1.8 percent used improved pit latrine and 0.7 percent had flush toilets. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 11 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (61.3% of households) followed by bicycle (32.1%), iron (18.9%), wheelbarrow (3.4%), mobile phone (1.9%), television/video (1.0%), vehicle (0.9%) and landline phone (0.5%). Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. About 77 percent of the total rural households used this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), parrafin/kerosene (0.03%) and gas/biogas (0.01%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households however, this was closely followed by iron sheets (43.6%). Other roofing materials are grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%). Number of Meals per Day About 72.3 percent of the holders in the region took three meals per day, 25.2 percent took two meals, 2.4 percent took one meal and 0.1 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 42 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 8.3 percent whereas those with little problems represent 7.6 percent. About 7 percent of agriculture households always faced food shortages whilst 35 percent had not experienced any food shortage problems. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 25.5 percent of all rural agricultural households. The second main cash income earning activity was casual labour (20.9%) followed by selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Other income earning activities were employment (5.0%), sale of livestock (4.0%), sale of forest products (2.5%), sale of livestock products (1.7%) and fishing (0.9%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ............................................................................................................................................ 10 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 22 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 25 3.3 Area Planted and Quantity Harvested by Season and Type of Root and Tuber Crop....................................... 27 3.4 Area, Quantity Harvested and Yield of Pulses by Season ..................................................................................30 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 37 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 37 3.8 Land Clearing Methods....................................................................................................................................... 43 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season...................................... 56 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ............................................... 61 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 61 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 64 3.15 Total Number of Households and Chickens Raised by Flock Size ....................................................................77 3.16 Head Number of Other Livestock by Type of Livestock and District............................................................... 80 3.17 Mean distances from holders dwellings to infrastructure and services by districts .......................................... 88 3.18 Number of Households by Number of meals the Household normally has per Day and District .................... 93 List of Charts 3.1 Agricultural Households by Type of Holdings....................................................................................................10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head..............................................11 3.3 Percentage Distribution of Population by Age and Sex in 2003.........................................................................11 3.4 Percentage Literacy Level of Household Members by District..........................................................................11 3.5 Literacy Rates for Heads of Household by Sex and District...............................................................................15 3.6 Percentage of Persons Aged 5 years and above by District and Educational Status..........................................15 3.7 Percentage of Persons Aged 5 years and Above in Agricultural Households by Education Status .................15 3.8 Percentage Distribution of Heads of Household by Educational Attainment ....................................................15 3.9 Number of Household by Number of Members with Off-Farm Income – Rukwa Region ...............................16 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities..................................16 3.11 Utilized and Usable Land per Household by District..........................................................................................17 3.12 Land Area by Type of Land Use..........................................................................................................................17 3.13 Area Planted (ha) with Annual Crops by Season................................................................................................17 3.14 Area Planted with Annual Crops by Season and District....................................................................................18 3.15 Area Planted with Annual Crops per Household by Season and District...........................................................18 3.16 Planted Area (ha) for the Main Annual Crops.....................................................................................................21 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type......................................................21 3.18 Area planted with Annual Crops by Type of Crops and Season.........................................................................21 3.19 Area Planted and Yield of Major Cereal Crops...................................................................................................21 3.20 Time Series Data on Maize Production – Rukwa Region...................................................................................22 3.21 Maize: Total Area Planted and Planted Area per Household by District ...........................................................22 3.22 Time Series of Maize Planted Area and Yield – Rukwa Region........................................................................22 3.23 Total Planted Area and Area of Paddy per Household by District .....................................................................23 3.24 Time Series Data on Paddy Production – Rukwa Region...................................................................................23 3.25 Time Series of Paddy Planted Area and Yield – Rukwa Region........................................................................23 3.26 Area Planted With Sorghum, Finger Millet, Bulrush Millet and Wheat by District..........................................25 3.27 Area Planted and Yield of Major Root and Tuber Crops....................................................................................25 3.28 Area planted with Cassava during the Census/Survey Years .............................................................................25 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................27 3.30 Cassava Planted Area per Cassava Growing Households by District ................................................................27 3.31 Sweet Potatoes: Total area and Planted Area per Household by District...........................................................27 3.32 Area Planted and Yield of Major Pulse Crops ....................................................................................................28 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District .............................................28 3.34 Area Planted per Bean Growing Household by District (Wet Season) ..............................................................28 3.35 Time Series Data on Beans Production – Rukwa Region.................................................................................. 28 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiii 3.36 Time Series of Beans Planted Area and Yield - Rukwa......................................................................................28 3.37 Area Planted and Yield of Major Oil Seed Crops...............................................................................................30 3.38 Time Series Data on Groundnut production – Rukwa Region ...........................................................................30 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District .........................30 3.40 Area Planted per Groundnut Growing Household by District (Wet Season).....................................................31 3.42 Area Planted and Yield of Fruit and Vegetables.................................................................................................31 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ......................................34 3.44 Area Planted per Tomato Growing Household by District (Wet Season ).........................................................34 3.45 Percent of Onions Planted Area and Percent of Total Land with Cabbage by District......................................34 3.46 Percent of Cabbage Planted Area and Percent of Total Land with Chillies by District.....................................34 3.47 Area planted with Annual Cash Crops ................................................................................................................37 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................37 3.49 Area Planted for Annual and Permanent Crops...................................................................................................37 3.50 Area Planted with the Main Perennial Crops ......................................................................................................38 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District ...................................38 3.52 Percent of Area Planted with Lime/Lemon and Average Planted Area per Household by District ..................38 3.53 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District.......................54 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District ...........................54 3.55 Percent of Area Planted with Mangoes and Average Planted Area per Household by District.........................43 3.56 Number of Households by Method of Land Clearing During the Wet Season..................................................43 3.57 Area Cultivated by Cultivation Method...............................................................................................................44 3.58 Area Cultivated by Method of Cultivation and District......................................................................................44 3.59 Planted Area with Improved Seed by Crop Type................................................................................................44 3.60 Planted Area with Improved Seed by Crop Type................................................................................................44 3.61 Percentage of Crop Type by planted Area with Improved Seeds- Annuals .......................................................45 3.62 Area of Fertilizer Application by Type of Fertilizer and District.......................................................................46 3.63 Area of fertilizer Application by Type of Fertiliser and District ........................................................................46 3.64 Planted Area with Farm Yard Manure by Crop type .........................................................................................46 3.65a Percentage of Planted Area with Farm Yard Manure by Crop Type................................................................46 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District .........................................................46 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals.........................................................................47 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type..................................................................47 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District..........................................................47 3.68a Planted Area with Compost by Crop Type......................................................................................................... 47 3.68b Percentage of Planted Area with Compost by Crop Type ..................................................................................49 3.68c Proportion of Planted Area Applied with Compost by District..........................................................................49 3.69 Planted area (ha) by Pesticide Use.......................................................................................................................49 3.70 Planted Area applied with Insecticides by Crop Type ........................................................................................50 3.71 Percentage of Crop Type Planted Area applied with Insecticides......................................................................50 3.72 Proportion of Planted Area applied with Insecticides by District.......................................................................50 3.73 Planted Area applied with Herbicides by Crop Type..........................................................................................50 3.74 Percentage of Crop Type Planted Area Applied with Herbicides.......................................................................51 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season......................51 3.76 Planted Area applied with Fungicides by Crop Type..........................................................................................51 3.77 Percentage of Crop Type Planted Area Applied with Fungicides ......................................................................51 3.78 Proportion of Planted Area Applied with Fungicides by District.......................................................................52 3.79 Area of Irrigated Land..........................................................................................................................................52 3.80 Planted Area Irrigation by District.......................................................................................................................52 3.81 Time Series of Households with Irrigation Practices – Rukwa ..........................................................................53 8.82 Number of Households with Irrigation by Source of Water...............................................................................53 3.83 Number of Households by Method of Obtaining Irrigation Water.....................................................................53 3.84 Number of Households with Irrigation by Method of Field Application...........................................................54 3.85 Number of Households and Quantity Stored by Crop Type...............................................................................54 3.86 Number of Households by Storage Methods.......................................................................................................55 3.87 Number of Households by Method of Storage and District (Based on the Mo.st important Household Crop) 55 3.88 Normal Length of Storage for Selected Crops ....................................................................................................55 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ...................................................55 3.90 Number of Households by Purpose of Storage and Crop Type..........................................................................56 3.91a Households Processing Crops..............................................................................................................................58 3.91b Percent of Households Processing Crops by District..........................................................................................58 3.92 Percent of Crop Processing Households by Method of Processing....................................................................58 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xiv 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 58 3.94 Number of Households by Type of By-product..................................................................................................59 3.95 Use of Processed Product.....................................................................................................................................59 3.96 Percentage of Households Selling Processed Crops by District.........................................................................59 3.97 Location of Sale of Processed Products...............................................................................................................59 3.98 Percentage of Households Selling Processed Products by Outlet for sale and District .....................................60 3.99 Number of Crop Growing Households that Selling Crops by District ...............................................................60 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ....................60 3.101 Percentage Distribution of Households that Received Credit by Main Sources ................................................62 3.102 Number of Households Receiving Credit by Main Source of Credit and District .............................................62 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit .....................................................62 3.104 Reasons for Not using Credit (% of Households) ...............................................................................................62 3.105 Number of Households Receiving Extension Advice.........................................................................................63 3.106 Number of Households that Received Extension by District..............................................................................63 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider..................................63 3.108 Number of Households Receiving Extension by Reported Quality of Services ................................................63 3.109 Number of Households by Source of Inorganic Fertiliser ..................................................................................64 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser...................................................66 3.111 Number of Households by Source of Improved Seed.........................................................................................66 3.112 Number of Households reporting Distance to Improved Seed ...........................................................................66 3.113 Number of Households by Source of Insecticide/Fungicide...............................................................................67 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides............................................67 3.115 Number of Households with Planted Trees by District.......................................................................................67 3.116 Number of Planted Trees by Species...................................................................................................................69 3.117 Number of Trees Planted by Smallholders by Species and District ...................................................................69 3.118 Number of Trees Planted by Location.................................................................................................................69 3.119 Number of Households by purpose of Planted Trees..........................................................................................69 3.120 Number of Households with Erosion Control/Water Harvesting Facilities .......................................................69 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............70 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility...................................................70 3.123 Total Number of Cattle ('000') by District...........................................................................................................71 3.124 Numbers of Cattle by Type and District..............................................................................................................71 3.125 Cattle Population Trend .......................................................................................................................................72 3.126 Dairy Cattle Population Trend.............................................................................................................................72 3.127 Total Number of Goats ('000') by District...........................................................................................................72 3.128 Goat Population Trend........................................................................................................................................ 73 3.129 Total Number of Sheep by District......................................................................................................................73 3.130 Sheep Population Trend.......................................................................................................................................76 3.131 Total Number of Pigs by District.........................................................................................................................76 3.132 Pig Population Trend............................................................................................................................................76 3.133 Total Number of Chicken by District ..................................................................................................................77 3.134 Chicken Population Trend ...................................................................................................................................77 3.135 Number of Improved Chicken by Type and District...........................................................................................80 3.136 Layer Population Trend........................................................................................................................................80 3.137 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District.......80 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............82 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........82 3.140 Number of Households by Distance to Veterinary Clinic...................................................................................82 3.141 Number of Households by Distance to Veterinary Clinic and District...............................................................82 3.142 Number of Households by Distance to Village Watering Point .........................................................................83 3.143 Number of Households by Distance to Watering Point and District..................................................................83 3.144 Number of Households using Draft Animals ......................................................................................................83 3.145 Number of Households using Draft Animals by District....................................................................................84 3.146 Number of Households using Organic Fertiliser.................................................................................................84 3.147 Area of Application of Organic Fertiliser by District .........................................................................................84 3.148 Number of Households Practicing Fish Farming – Rukwa.................................................................................84 3.149 Number of Households Practicing Fish Farming by District – Rukwa ..............................................................87 3.150 Fish Production.....................................................................................................................................................87 3.151 Agricultural Households by Type of Toilet Facility ...........................................................................................87 3.152 Percentage Distribution of Households Owning the Assets................................................................................88 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................88 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xv 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 90 3.155 Percentage Distribution of Households by Type of Roofing Material ...............................................................90 Percentage Distribution of Households With Grass/Leaves Roofs by District ..................................................92 3.157 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season....92 3.158 Percentage Distribution of the Number of Households by Main Source of Income..........................................92 3.159 Number of Agriculture Households by Number of Meals per day.....................................................................92 3.160 Number of Households by Frequency of Meat and Fish Consumption..............................................................93 3.161 Percent Distribution of the Number of Households by Main Source of Income................................................93 List of Maps 3.1 Total Number of Agricultural Households by District........................................................................................12 3.2 Number of Agricultural Households per Square Km of Land by District..........................................................12 3.3 Number of Crop Growing Households by District..............................................................................................13 3.4 Percent of Crop Growing Households by District...............................................................................................13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................14 3.6 Percent of Crop and Livestock Households by District ......................................................................................14 3.7 Utilized Land Area Expressed as a Percent of Available Land ..........................................................................19 3.8 Total Planted Area (annual crops) by District.....................................................................................................19 3.9 Area planted and Percentage During the Short Rainy Season by District..........................................................20 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................20 3.11 Planted Area and Yield of Maize by District ......................................................................................................24 3.12 Area Planted per Maize Growing Household......................................................................................................24 3.13 Planted Area and Yield of Paddy by District ......................................................................................................26 3.14 Area Planted per Paddy Growing Household......................................................................................................26 3.15 Planted Area and Yield of Cassava by District ...................................................................................................26 3.16 Area Planted per Cassava Growing Household....................................................................................................... 3.27 Planted Area and Yield of Onion by District ......................................................................................................35 3.28 Planted Area and Yield of Onion by District .....................................................................................................35 3.29 Planted Area and Yield of Tobbaco by District ..................................................................................................40 3.30 Area Planted per Tobacco Growing Household..................................................................................................40 3.24 Area Planted per Cabbage Growing Household..................................................................................................36 3.23 Planted Area and Yield of Cabbage by District ..................................................................................................36 3.19 Planted Area and Yield of Groundnuts by District .............................................................................................32 3.20 Area Planted per Groundnuts Growing Household.............................................................................................32 3.25 Planted Area and Yield of Tomatoes by District................................................................................................33 3.26 Area Planted per Tomatoeso Growing Household..............................................................................................33 3.23 Planted Area and Yield of Cabbage by District ..................................................................................................36 3.24 Area Planted per Cabbage Growing Household..................................................................................................36 3.27 Planted Area and Yield of Cotton by District......................................................................................................39 3.28 Area Planted per Cotton Growing Household.....................................................................................................39 3.33 Planted Area and Yield of Oranges by District...................................................................................................57 3.34 Area Planted per Orange Growing Household....................................................................................................57 3.35 Planted Area and Yield of Banana by District ....................................................................................................42 3.36 Area Planted per Banana Growing Household....................................................................................................42 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..................................48 3.41 Percent of households storing crops for 3 to 6 weeks by district........................................................................57 3.42 Number of Households and Percent of Total Households Selling Crops by District.........................................57 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .....65 3.44 Number and Percent of Crop Growing Households using Improved Seed by District .....................................65 3.45 Number and percent of smallholder planted trees by district..............................................................................68 3.47 Cattle population by District as of 1st Octobers 2003.........................................................................................74 3.48 Cattle Density by District as of 1st October 2003...............................................................................................74 3.49 Goat population by District as of 1st Octobers 2003 ..........................................................................................75 3.50 Goat Density by District as of 1st October 2003.................................................................................................75 3.51 Sheep population by District as of 1st Octobers 2003 ........................................................................................78 3.52 Sheep Density by District as of 1st October 2003...............................................................................................78 3.53 Pig population by District as of 1st Octobers 2003.............................................................................................79 3.54 Pig Density by District as of 1st October 2003 ...................................................................................................79 3.55 Number of Chickens by District as of 1st October 2003 ....................................................................................81 3.56 Density of Chickens by District as of 1st October 2003.....................................................................................81 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xvi 3.57 Number and Percent of Households Infected with Ticks by District .................................................................85 3.58 Number and Percent of Households Using Draft Animals by District...............................................................85 3.59 Number and Percent of Households Using Farm Yard Manure by District.......................................................86 3.60 Number and Percent of Households using Compost by District.........................................................................86 3.61 Number and Percent of Households Practicing Fish Farming by District..........................................................89 3.62 Number and Percent of Households Without Toilets by District .......................................................................89 3.63 Number and Percent of Households using Grass/Leaves for roofing material by District ................................91 3.64 Number and Percent of Households eating 3 meals per day by District ............................................................91 3.65 Number and Percent of Households eating Meat Once per Week by District ...................................................94 3.66 Number and Percent of Households eating Fish Once per Week by District.....................................................94 3.67 Number and percent of Households Reporting food insufficiency by District ................................................. 95 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Rukwa region is situated in the South West of the country between Latitude 50 and 90degrees south of Equartor and between Longitudes 300 and 33 degrees East. A good part of Rukwa region lies within the Western branch of east African Rift Valley known as the “ Western rift Land Province” Rukwa region, with an area of 75,240 sq. km, (68,635 sq. km. of land and 6,605sq. km. of inland water), takes up abouit 8% of the total land of Tanzania Mainland. The region is borded by Zambia in the South West, Lake Tanganyika in the west, Ki8goma region in the North west, Tabora region in the North East and Mbeya region in the East. The region comprises four districts namely Mpanda Sumbawanga Rural, Nkasi and Sumbawanga Urban. Land Area The region has an area of over 340,000 square kilometers, of which 28,695 square kilometers are arable land. 1.4 Climate The region enjoys favourable climate conditions, varying from a dry sub-humid climate. Rainfall: Rukwa region has an average rainfall ranging from 800mm. to 1,300mm The region has one main rainy season; from mid November to mid May, that is long rains (Wet) season Temperature: The Mean annual maximum temperature in the region varies between 240C and 270C and the minimum temperature between 130C and 160C. 1.5 Population According to the 2002 Population and Housing Census, there were 1,642,015 inhabitants in Rukwa region. The population of Rukwa region ranked 10th out of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 348,926 millions with a per capita income of shillings 236,115. The region held 10th position among regions on GDP and contributed about 4.3 percent to the national GDP1 Rukwa region is famous for limestone and gypsum mineral deposits, all of which are used in the cement factory situated in the region. The region is famous for producing both food crops. The main food crops produced in Rukwa region include: maize, paddy, beans and sorghum. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Rukwa region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field protesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc-View and Freehand. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS This part of the report presents the census results for Rukwa region based on the data tables in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Survey, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators compared to previous censuses and surveys, more effort has been made in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Rukwa region was 172,261. The largest number of agriculture households was in Sumbawanga Rural (68,935) followed by Mpanda (59,533), Nkasi (30,483) and Sumbawanga Urban (13,309) (Map 3.1). The highest density of households was found in Sumbawanga Urban (22 households/km2) and Sumbawanga Rural (13 households/ km2 ) (Map 3.2). Most households (114,069 66.2%) were involved in growing crops only, 416 households (0.2%) rearing livestock only and 57,776 (33.5%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Rukwa region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, ff-farm income, livestock keeping/herding, permanent crops, remittances, and fishing/hunting and gathering. (Table 3.1) Sumbawanga Rural and Sumbawanga Urban were the only districts where remittances were the fifty most important source of livelihood. Moreover, Nkasi was the only district where fishing/hunting and gathering was the fifth most important source of livelihood. Table. 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Annual Crop Farmin g Permanent Crop Farming Lives tock Keep ing / Herdi ng Off Farm Inco me Remittances Fishing / Hunting & Gatherin g Tree / Forest Resource s Mpanda 1 5 4 3 6 7 2 Sumbawanga R 1 6 4 3 5 7 2 Nkasi 1 7 4 3 6 5 2 Sumbawanga U 1 6 4 3 5 7 2 Total 1 5 4 3 6 7 2 Chart 3.1 Agriculture Households by Type - Rukwa Pastoralists, 0, 0% Livestock Only, 416, 0.2% Crops Only, 114,069, 66.2% Crops and Livestock, 57,776, 33.5% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Rukwa region was 150, 902 (88% of the total regional agricultural households) whilst the female-headed households were 21,359 12% of the total regional agricultural households). The mean age of household heads was 41 years (40 years for male heads and 46 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Rukwa region had a total rural agricultural population of 942,269 of which 476,244 (51%) were males and 466,024 (49%) were females. Whereas age group 0-14 constituted 48 percent of the total rural agricultural population, age group 15–64 (active population) was only 46 percent. Rukwa region had an average household size of 5.5 with Sumbawanga Rural district having the lowest household size of 5. (Chart 3.3) 3.1.5 Level of Education In order to obtain information on the level of education, data was gathered from all persons aged five years and above in all selected households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Chart 3.3 Percent Distribution of Population by Age and Sex - RUKWA 0 6 12 18 Age Group Percen t Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 19 9 4 /9 5 EAS 19 9 5/9 6 EAS 19 9 6 /9 7 IAS 19 9 7/9 8 DIAS 19 9 8 /9 9 NSCA 2 0 0 2 /0 3 Year Percent of Households Male headed households Female headed households Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 Sumbawanga Urban Nkasi Sumbawanga Rural Mpanda District Percen t Sumbawanga Urban Sumbawanga Rural 22 13 6 3 Mpanda Nkasi 30 to 40 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 13,309 68,935 30,483 59,533 Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Agricultural Households Total Number of Agricultural Households by District MAP 3.1 RUKWA MAP 3.2 RUKWA Number of Agricultural Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer 12 RESULT Sumbawanga Urban Sumbawanga Rural 100% 99% 100% 100% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Sumbawanga Urban Sumbawanga Rural 13,309 68,520 30,483 59,533 Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Crop Growing Household Number of Crop Growing Households by District MAP 3.3 RUKWA MAP 3.4 RUKWA Percent of Crop Growing Households by District Tanzania Agriculture Sample Census Percent of Crop Growing Household Number of Crop Growing Household Percent of Crop Growing Household RESULT 13 Sumbawanga Rural Sumbawanga Urban 43.2% 42.8% 35.1% 19.5% Mpanda Nkasi 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 22 13 6 3 Mpanda Nkasi 30 to 40 30 to 40 20 to 30 10 to 20 0 to 10 Number of Crop Growing Household per Square Km Number of Crop Growing Households per Square Kilometer of Land by District MAP 3.5 RUKWA MAP 3.6 RUKWA Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census Percent of Crop and Livestock Household Number of Crop Growing Household per Square Kilometer Percent of Crop and Livestock Household RESULT 14 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 Literacy Level for Household Members Rukwa region had a total literacy rate of 61 percent. The highest literacy rate was found in Sumbawanga Urban (66%) followed by Nkasi district (62%) and Sumbawanga Rural district (65%). Mpanda district had the lowest literacy rates of (60%) (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 72 percent. The literacy rates among the male and female heads of households were 78 and 36 percent respectively. The literacy rate for male headed of households was higher than that of females in all districts. However, Sumbawanga Rural and Sumbawanga Urban districts had the highest literacy rate amongst heads of households which was (75%) each followed by Nkasi (71%) and Mpanda (70% (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 38 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 28 percent were still attending school. Those who have never attended school were 34 percent (Chart 3.6). Agricultural households in Sumbawanga Urban district had the highest percentage (40%) of population aged 5 years and above who had completed different levels of education. This was followed by Nkasi district with (39%) while Sumbawanga Rural and Mpanda had the lowest percentages of (38%) Chart 3.7) The number of heads of agricultural households with formal education in Rukwa region was 118,763 (68.9%) and those Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.2% Never Attended 34.1% Attending School 27.7% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District P ercent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Post Primary 3.9% Adult Educ. 3.5% NO education 27.6% Primary Education 65.0% Chart 3.5 Literacy Rates of Head of Household by Sex and District - RUKWA 0 25 50 75 100 Sumbawanga Rural Sumbawanga Urban Nkasi Mpanda District Percent Male Female Total RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 without formal education were 53,498 (31.1%) and those with only adult education who were 6,019 (3.5%). The majority of heads of agricultural households (65.0%) had primary level education whereas only (3.9%) had post primary education. With regard to the heads of agricultural households with primary or secondary education in Rukwa region, Sumbawanga Urban district had the highest percentages (69.2% for primary and 2.8% for secondary). This was followed by Sumbawanga Rural (67.0% primary and 4.8% secondary), Nkasi (65.4% primary and 3.7% secondary) and Mpanda (61.6% primary and 3.3% secondary). (Chart 3.8) 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Rukwa with 76.5 percent of households having at least one member with off-farm income. In Rukwa region there were 59,888 households (34.8%) with only one member aged 5 and above involved in only one off-farm income generating activity, 53,457 households (31.0%) had two members involved in off-farm income generating activities and 18,456 households (10.7 %) had more than two members involved in off-farm income generating activities. Nkasi district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with higher percent of agriculture households with off-farm income were Sumbawanga Urban (81%) and Sumbawanga Rural (75%) while Mpanda district had the lowest percent of agriculture households with off-farm income (67%). The district with the highest percent of agriculture households with more than one member with off-farm income was Nkasi (65 %) followed by Sumbawanga Urban (49%), Sumbawanga Rural (43%) and Mpanda (27%) 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income One, 59,888, 35% NO Off-farm, 40,459, 23% Mo re than Two , 18,456, 11% Two , 53,457, 31% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb Districts Percent One Two Mo re Than Two NONE RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 country, however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 574,291 ha. The regional average land area utilised for agriculture per household was only 2.4 ha. This figure is slightly above the national average which is estimated at 2.0 hectares. Seventy three percent of the total land available to smallholders was utilised. Only 27.1 percent of usable land available to smallholders was not used (Chart 3.11). Small differences in land area utilised per household exist between districts with Sumbawanga Rural and Nkasi utilizing 2.7 and 2.5 ha per household respectively. The smallest land area utilised per household was found in Mpanda and Sumbawanga Urban with (2.0 ha) each. The percentage utilized of the usable land per household was highest in Sumbawanga Urban (86.2%) and lowest in Mpanda (63.2%). Seventy three percent of the total land available to smallholders was utilised. Only 27 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 226,716 hectares (39.5% of the total land available to smallholders in Rukwa), followed by uncultivated usable land (134,711 ha, 23.5%), temporary mixed crops (76,412 ha, 13.3%), area under fallow (55,734 ha, 9.5%), under natural bush (17,243 ha, 3.0%), permanent/annual mix/area rented to others/unusable area had (2,2%) each and permanent mono crop/permanent mixed crop/area under pasture/area under planted trees had (1%) each (chart 3.12) 3.3 Annual Crop and Vegetable Production Rukwa region has one rainy seasons, namely the wet season or the long rainy season (October to March). The quantity of crops produced in the wet season will be used as a base for comparison with the past surveys and censuses. Chart 3.12 Land Area by Type of Use 23.5 39.5 13.3 9.7 3.0 2.2 2.2 1.8 1.5 1.4 1.1 0.9 0 100,000 200,000 300,000 Area under Permanent Mono Crops Area under Planted Trees Area under Permanent Mixed Crops Area under Pasture Area Rented to Others Area under Permanent / Annual Mix Area Unusable Area under Natural Bush Area under Fallow Area under Temporary Mixed Crops Area of Uncultivated Usable Land Area under Temporary Mono Crops Land Use Area (hectares) Chart 3.11 Utilized and Usable Land per household by district 0.0 1.0 2.0 3.0 4.0 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Districts Area/household 0.0 20.0 40.0 60.0 80.0 100.0 Percentage utilized Area utilis ed (Ha ) To tal Us able Area ava ilable (ha) P e rcent Utilis atio n Chart 3.13 Area Planted (Ha) with Annual Crops by Season Dry Season, 1,049, 0.3% Wet Season, 302,345, 99.7% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 3.3.1 Area Planted The area planted with annual crops and vegetables was 303,393 hectares out of which 1,049 hectares (0.3%) were planted during dry season and 302,345 hectares (99.7%) during wet season. The average areas planted per household during the dry and wet rainy seasons was (1.4 ha) and (1.8 ha) respectively (Chart 3.13). The districts with dry season cultivation were Sumbawanga Rural with the average planted area of 1.8 ha per household followed with Nkasi (0.8 ha) and Sumbawanga Urban (0.5 ha). The district with the largest area planted per household in wet season was Sumbawanga Rural (2.0 ha), Nkasi (1.8ha), Mpanda (1.5 ha) and Sumbawanga Urban (1.5 ha). The district with the smallest average area planted in both dry and wet rainy seasons was Sumbawanga Urban with (56 ha and 20,109 ha ). Therefore, it can be concluded that Rukwa Region had mono- agricultural season which is wet season (Chart 3.14 and Map 3.8). The planted area occupied by cereals during the wet season was 203,500 ha (67.3% of the total area planted with annuals). This was followed by pulses (37,551 hectares, 12.4%), roots and tubers (28,595 hectares, 9.5%), oil seeds (28,178 hectares, 9.3%) cash crops (3,295 hectares (1.1%) and fruits and vegetables (1,225 hectares (0.4%). The average area planted per household during the wet season in Rukwa region was 1.8 hectares, however, there were large district differences. Sumbawanga Rural had the largest planted area per household (2.0 ha) followed by Nkasi (1.8 ha), Mpanda (1.6 ha) and Sumbawanga Urban (1.5 ha) each. (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. Chart 3.15 Area Planted with Annual C rops per Household by Season and District 0.000 1.000 2.000 3.000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Area Planted (ha) Wet Seas o n Wet Seas o n Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Sumbawanga Urban Sumbawanga Rural Nkansi Mpanda District Area Planted (ha) 0.00 0.50 1.00 1.50 2.00 Percentage Planted Wet Season Dry Season % Area planted in Dry season Sumbawanga Urban Sumbawanga Rural 20,109 ha 132,698 ha 53,306 ha 96,231 ha Mpanda Nkasi 160,000 to 200,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Sumbawanga Urban Sumbawanga Rural 63.2% 86.2% 79.1% 72.2% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Utilized Land Area Utilized Land Area Expressed as a Percent of Available Land by District MAP 3.7 RUKWA MAP 3.8 RUKWA Total Planted Area (Annual Crops) by District Tanzania Agriculture Sample Census Area Planted Annual Crop Utilized Land Area Expressed as a Percent Area Planted Annual Crop RESULT 19 Sumbawanga Urban Sumbawanga Rural 42ha 0ha 97ha 288ha 0.21% 0% 0.22% 0.18% Mpanda Nkasi 240 to 290 180 to 240 120 to 180 60 to 120 0 to 60 Sumbawanga Urban Sumbawanga Rural 1,047ha 17,901ha 1,446ha 8,741ha 5.2% 13.5% 2.7% 9.1% Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Area Planted and Percentage During the Short Rainy Season by District MAP 3.9 RUKWA MAP 3.10 RUKWA Area Planted with Cereals and Percent of Total Land Planted With Cereals by District Tanzania Agriculture Sample Census Planted Area (ha) Percent of Total Land Planted With Cereals Crop Percentage of Area Planted During the Short Rainy Season Planted Area (ha) Planted Area (ha) RESULT 20 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 21 3.3.2 Crop Importance Maize is the dominant annual crop grown in Rukwa region and it had a planted area 4.6 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 94.8 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are beans, cassava, paddy, finger millet, groundnuts, sunflower, sorghum, tobacco, sweet potatoes, wheat and tomatoes. (Chart 3.16) Households that grow finger millet, maize, paddy wheat and sorghum had larger planted areas per household than those growing other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Rukwa region. The area planted with cereals during the wet season was 203,500 hectares (67.3% of the total planted area), followed by pulses with (37,551 ha, 12.4%), root and tubers 28,595 hectares (9.5%), oil seeds 28,178 hectares (9.3%), cash crops 3 295 hectares (1.1%) and fruits and vegetables 1,225 hectares (0.4%) (Chart 3.17b). Cereals and pulses are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because dry season production was very small compared to wet season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.17b Percentage Distribution of Planted Area with Annual Crops by Crop Type Cash Crops 1.1% Fruits & Vegetables 0.4% Oil Seess & Oil Nuts 9.3% Roots & Tubers 9.5% Pulses 12.4% Cereals 67.3% Chart 3.17a Planted Area (ha) per Household by Selected Crop - RUKWA 0.00 0.35 0.70 1.05 Finger Millet Maize Paddy Wheat Sorghum Tobacco Sunflower Cowpeas Beans Cassava Yams Bambaranuts Groundnuts Cotton Sweet Potatoes Soya Beans Irish Potatoes Cocoyam Field Peas Bulrush Millet Simsim Crop Planted Area (ha) 4 2 7 3 7,551 2 79 2 8 ,59 5 0 2 8 ,178 3 4 3 3 ,2 9 5 0 1,2 2 5 0 0 50,000 100,000 150,000 200,000 Area (hectares) Cereals Pulses Roots & T ubers Oil Seeds & Oil Nuts Cash Crops Fruits & Vegetables Crop Type C hart 3.18 Are a Planted with Annual C rops by C rop Type and Se ason Wet Season Dry Season Chart 3.16 Planted Area (ha) for the Main Crops - RUKWA 0 60000 120000 Maize Beans Cassava Paddy Finger Millet Groundnuts Sunflower Sorghum Tobacco Sweet Potatoes Wheat Tomatoes Crop Planted Area (ha) RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 22 3.3.4 Cereal Crop Production The total production of cereals was 240,623 tonnes. Maize was the dominant cereal crop with the production of 163,432 tonnes which was 67.9 percent of total cereal crops produced, followed by paddy (20.6%), finger millet (6.6%) sorghum (4.1%), wheat (0.8%) and) bulrush millet (0.01). (Map 3.10). The area planted with maize was dominant and it represented 73.6 percent of the total area planted with cereal crops, followed by paddy (12.5%), finger millet (9.3%), Sorghum (3.6%), wheat 1.0%), and bulrush millet (0.01%). Paddy had the highest yield of (1940kg/ha), followed by sorghum (1,343 kg/ha), bulrush millet (1,186 kg/ha), maize (1,089 kg/ha), wheat (966 kg/ha) and finer millet (833 kg/ha) (Chart 3.19). 3.3.4.1 Maize Maize dominated the production of cereal crops in the region. The number of households growing maize in Rukwa region during the wet season was 159,160 (72.0% of the total crop growing households in the region during the wet season). The total production of maize during wet season was 163,277 tonnes from a planted area of 149,606 hectares resulting in a yield of (1.09 t/ha). (Chart 3.20) indicates the maize production trend (in thousand metric tonnes) for the wet season. There was a sharp decrease in maize production over the period of 1996 to 1998 after which the production increased sharply by the year 1998. In the year 1999 to 2000 the production was almost stable after which the production increased steadily up to the year 2003. The average area planted with maize per household was 0.94 hectares; however it ranged from 0.78 hectares in Mpanda district to 1.04 hectares in both Sumbawanga rural and Nkasi. (Map 3.21). Sumbawanga Rural district had the largest area for maize (66,238 ha) followed by Mpanda (43,301 ha), Nkasi (28,111 ha). Sumbawanga Urban district had the smallest planted area (12,382 ha) (Chart 3.21 and Map 3.11). Table 3.2: Area, Production and Yield of Cereal Crops by Season Wet Season Crop Area Planted (ha) Quantity harvested (tonnes) Yield (kg/ha) Maize 150,033 163,432 1,089 Paddy 25,526 49,520 1,940 Finger Millet 18,967 15,798 833 Sorghum 7,405 9,942 1,343 Wheat 1,979 1,911 966 Bulrush Millet 17 20 1,176 Total 203,928 240,623 Chart 3.20: Time Series Data on Maize Production - RUKWA 126 172 136 163 126 70 120 0 50 100 150 200 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 66,238 43,301 28,111 12,383 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Sumbawanga Rural Mpanda Nkansi Sumbawanga Urban District Area (Ha) 0.00 0.20 0.40 0.60 0.80 1.00 1.20 Area Planted per Household Planted Area (ha) are/hh RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 Charts (3.20 and 3.22) show that, both production and yield of maize dropped sharply from 1995/96 to 1997/98 after which both increased gradually up to 2002/03. On the other hand the planted area was almost stable from 1994/95 to 1996/97 and after increasing rapidly in the year 1997/98 but the exceeding years from 1998 to 2003 the yield remained almost constant the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 2000 and the area has remained constant ever since. (Chart 3.22) 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Rukwa region during the wet season was 30,132. This represented 17.6 percent of the total annual crop growing households in Rukwa region in the wet season. The total production of paddy was 49,520 tonnes from a planted area of 25,526 hectares resulting in a yield of (1.9 t/ha). The district with the largest area planted with Paddy was Sumbawanga Rural (12,505 ha) followed by Nkasi (11,605 ha). Mpanda and Sumbawanga Urban did not grow any paddy. (Map 3.13) There was a small insignificant variation in the average planted area per crop growing household between the two districts of Nkasi and Sumbawanga Rural ranging from 0.85 hectares to 0.95 hectares respectively (Chart 3.23 and Map 3.14) . There was a sharp decrease in the production of paddy from 1994/95 to 1995/96. From 1997/98 and 1998/99 the production increased. The production dropped from 7,941 tons in 1995/96 to 3642 tonnes in 1997/98 after which it rose to over 6,000 tonnes in the following two years of 1998/99 and 1999/2000. Thereafter the yield had been almost stable fluctuating between (2500 kg/ha ) and 900kg/ha) Charts 3.23 and 3.25 Chart 3.22 Time Series of Maize Planted Area & Yield - RUKWA 0 40,000 80,000 120,000 160,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 1.2 2.3 Yield (t/ha) Area Yield Chart 3.25 Time Series of Paddy Planted Area and Yield - RUKWA 0 2500 5000 7500 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Agriculture Year Area (hectares) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Yield (t/ha) Area Planted Yield 0 Chart 3.23 Total Planted Area and Area of Paddy per Household by District 12,505 11,605 0 0 4,000 8,000 12,000 16,000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Area (Ha) 0.00 0.50 1.00 Area planted per household Planted Area (ha) Area /hh Chart 3.24 Time Series Data on Paddy Production - TANGA 8 7 7 13 5 26 16 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Sumbawanga Urban Sumbawanga Rural 0.9ha 0.8ha 1ha 1ha Mpanda Nkasi 0.96 to 1 0.92 to 0.96 0.88 to 0.92 0.84 to 0.88 0.8 to 0.84 Sumbawanga Urban Sumbawanga Rural 12,383ha 66,238ha 28,111ha 43,301ha 1.1t/ha 0.9t/ha 1.3t/ha 1.0t/ha Mpanda Nkasi 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Planted Area (ha) Planted Area and Yield of Maize by District MAP 3.11 RUKWA MAP 3.12 RUKWA Area Planted per Maize Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 24 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 25 3.3.4.3 Other Cereals Other cereals produced in Rukwa Region included: sorghum (7,405 ha), finger millet (18,967 ha), bulrush millet (17 ha) and wheat (1,979 ha). While bulrush millet was grown in Nkasi district only, wheat was produced in all districts except Mpanda. (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 45,702 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 39,818 tonnes representing 87 percent of the total root and tuber crops production. This was followed by sweet potatoes (4,699 tonnes, 10%), Irish potatoes with 1,031 tonnes (2%), yams (127t, 0.3%) and coco yams (27t, 0.06%) (Table 3.3) The area planted with cassava was therefore larger than any other root and tuber crops and it was the most important root and tuber crop in Rukwa in terms of planted area. It accounted for 89.6 percent of the area planted with roots and tubers, followed by sweet potatoes (9.4%), Irish potatoes 1.0%), cocoyam (0.05%). and cocoyam (0.02%) There was a significant increase in the area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potatoes and yams remained more or less constant. The estimated yield was high for yams (9.7 t/ha) and cocoyam (3.9t/ha). Irish potatoes (3.7t/ha), sweet potatoes (1.8 t/ha) and cassava (1.6 t/ha) 3.3.5.1 Cassava The number of households growing cassava in the region was 53,929. This represents 31.4 percent of the total crop growing households in the region. The total production of cassava during the census year was 39,818 tonnes from a planted area of 25,611 hectares resulting in a yield of (1.6t/ha). Table 3.3: Area, Production and Yield of Roots & Tuber Crops Crops by Season Wet Season Crop Area Planted (ha) Quantity harvested (tonnes) Yield (kg/ha) Cassava 25,611 39,818 1,555 Sweet Potatoes 2,681 4,699 1,753 Irish Potatoes 282 1,031 3,656 Yams 13 127 9,669 Cocoyam 7 27 3,857 Total 28,594 45,702 Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10,000 20,000 30,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 2,000 4,000 6,000 8,000 10,000 Yield (kg/ha) Yield (kg/ha) Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Y e ar Cassava 0 3,000 6,000 9,000 12,000 Area (Ha) S umbawanga Rural Mpanda Nkasi S umbawanga Urban District Chart 3.26 Area Planted with Sorghum, Finger Millet, Bulrush Millet and Wheat by District Sorghum Finger Millet Bulrush Millet Wheat Sumbawanga Urban Sumbawanga Rural 0.3ha 0.5ha 0.6ha 0.4ha Mpanda Nkasi 0.54 to 0.61 0.48 to 0.54 0.42 to 0.48 0.36 to 0.42 0.3 to 0.36 Sumbawanga Urban Sumbawanga Rural 6,817ha 146ha 6,165ha 12,483ha 1.5t/ha 1.6t/ha 2.3t/ha 1.2t/ha Mpanda Nkasi 12,000 to 13,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Planted Area (ha) Planted Area and Yield of Cassava by District MAP 3.15 RUKWA MAP 3.15 RUKWA Area Planted per Cassava Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 26 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 27 Previous censuses and surveys indicate that the area planted with cassava increased from 1995/96 to 2002/03 (3.28). The planted area with cassava accounted for 8.5 percent of the total planted with annual crops. Sumbawanga Rural district had the largest planted area of cassava (12,483 ha, 48.7% of the total cassava planted area in the region) followed by Nkasi (6,817 ha, 26.6%), Mpanda ( 6,165 ha, 24.1%) and Sumbawanga Urban (146 ha, 0.6%). (Map 3.15). However, the district with the highest proportion of land planted with cassava was Sumbawanga Rural district (23.4%) followed by Mpanda (6.4%), Nkasi (5.1%) and Sumbawanga Urban (0.7%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.47 hectares. There were small district variations. The area planted per cassava growing household was greatest in Nkasi (0.57 ha), this was followed by Sumbawanga Rural (0.53 ha), Mpanda (0.42 ha) and Sumbawanga Urban (0.27ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Rukwa region was 9,530. This was 14.7 percent of the total root and tuber crop growing households during the wet season. The total production of sweet potatoes during the census year was 4,699 tonnes from a planted area of 2,681 hectares resulting in a yield of (1.75t/ha). Mpanda District has the largest planted area for sweet potatoes (1,400 ha, 52.2%), followed by Sumbawanga Rural (728 ha, 27.1%), Nkasi (469 ha, 17.5%) and Sumbawanga Urban (85 ha, 3.2%). 3.3.6 Pulse Crops Production The total area planted with pulses was 37,831 hectares out of which 37,530 ha were planted with beans (99.2 percent of the total area planted with pulses), followed by bambaranuts (108 ha, 0.29%), green grams (102 ha, 0.27%), cowpeas (68 ha, 0.18%) and field peas (23 ha, 0.06). Mung beans, pigeon peas and chick peas were not grown in the region. Table 3.4: Area, Production and Yield of Pulses by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 37,251 17,265 463 37,530 17,308 461 Bambaranuts 108 93 861 108 93 861 Green Gram 102 151 1,480 102 151 1,480 Cowpeas 68 47 691 68 47 691 Field Peas 23 11 478 23 11 478 Total 37,552 17,567 37,831 17,610 0.57 0.53 0.42 0.27 0.00 0.20 0.40 0.60 Area per Household Nkasi Sumbawanga Rur Mpanda Sumbawanga Urb District Chart 3.30: Cassava Planted Area per Cassava Growing Households by District Chart 3.31: Sweet Potatoes: Total Area Planted and Planted Area Per Household 0 500 1,000 1,500 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Area Planted (ha) 0.00 0.18 0.36 0.54 Area Planted per Household Area Planted Area per Household Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 48.7 26.6 24.1 0.6 0.0 25.0 50.0 Sumbawanga Rural Nkasi Mpanda Sumbawanga Urban District Percent of Total Area Planted 0 10 20 30 Percent Area Planted of Total Land Area % o f Area P lanted with Cas s ava P ro po rtio n o f Land Area RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 28 The total production of pulses was 17,610 tonnes. Beans were the most cultivated crop producing 17,308 tonnes which accounted for 98.3 percent of the total pulse production. This was followed by green grams (151t, 0.86%), bambaranuts (93t, 0.53%), cowpeas (47t, 0.27%) and field peas (11t, 0.06%). Green grams and bambaranuts had relatively higher yields of 1,480 and 861 kgs/ha) respectively. The yields of the rest of the pulses in kilograms per hectare were cowpeas (691 kgs/ha), field peas (478 kgs/ha) and beans (461 kgs/ha) (Chart 3.32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Rukwa region during the wet season was 78,216. The total production of beans in the region was 17,265 tonnes from a planted area of 37,251 hectares resulting in a yield of (0.46 t/ha).The largest area planted with beans in the region was in Sumbawanga Rural district (17,142 ha, 46.0%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per beans growing household was in Sumbawanga Rural district (0.56 ha) (Chart 3.34). The average area planted per household in the region during the wet season was (0.48 ha). The variations in area planted with beans per household among districts in the region was not significant important as it ranged from (0.37 ha) in Sumbawanga Urban to (0.45 ha) in Mpanda. (Map 3.18). Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 8,000 16,000 24,000 32,000 40,000 Beans Bambaranuts Green Gram Cowpeas Field Peas Crop Area Planted (ha) 0 400 800 1,200 1,600 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 6 12 18 Sumbawanga Urb Sumbawanga Rur Nkasi Mpanda District Percent of Land 0 2 4 6 Percent Area Planted of Total Land Area % of area planted with beans Proportion of land Chart 3.35: Time Series Data on Beans Production - RUKWA 16 2 53 16 17 46 37 0 10 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Prod u ction ('000') ton s 0.56 0.45 0.42 0.37 0.00 0.15 0.30 0.45 0.60 Area per Household Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District Chart 3.34 Area Planted per Bean Growing Household by District Wet Season Chart 3.36: Time Series of Beans Planted Area & Yield - RUKWA 0 14,000 28,000 42,000 1996/97 1998/99 1999/2000 2002/03 Agriculture Year A rea (hecta res) 0.00 0.15 0.30 0.45 Y ield (t/ha ) Beans (Ha) Yild (kg/ha Sumbawanga Urban Sumbawanga Rural 0.6ha 0.4ha 0.5ha 0.4ha Mpanda Nkasi 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Sumbawanga Urban Sumbawanga Rural 3,043ha 17,142ha 6,810ha 10,255ha 0.4t/ha 0.5t/ha 0.4t/ha 0.5t/ha Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Planted Area and Yield of Beans by District MAP 3.17 RUKWA MAP 3.18 RUKWA Area Planted per Beans Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 29 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 In Rukwa region, bean production was fluctuating from the year 1995/96 to 1998/99 after which the production increased steadily over the period 1998/99 to 2003 from 16,000 tonnes in 1998/99 to 17,000 tonnes in 2002/2003 (Chart 3.35). Charts 3.35 and 3.36 shows that whilst the yield of beans remained fairly constant in the last 3 years, the quantity produced had remained stable ranging between 40,000 in the year 1998 to 37,000 tonnes tin 2003 (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 17,419 tonnes planted on an area of 28,520 hectares. Groundnuts were most important oilseed crop with 16,570 hectares (58.1% of the total area planted with oil seeds), followed by sunflower (11,758 ha, 41.2%), soya beans (127 ha, 0.45%) and simsim (65 ha, 0.23%). The production of groundnuts was 11,126 tonnes which accounted for 63.9 percent of the total production of oil seeds, followed by sunflower (35.0%), soya beans (0.88%) and simsim (0.20%). 3.3.7.1 Groundnuts During the wet season the number of households growing groundnuts in that season was 44,997. The total production of groundnuts in the region was 11,055 tonnes from a planted area of 16,522 hectares resulting in a yield of (0.67 t/ha). Area planted had been increased from 1,292 hectares in 1994/95 to 16,570 hectares in 2002/03 (Chart 3.38) Table 3.5: Area, Quantity Harvested and Yield of Oil Crops by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Groundnuts 16,522 11,126 16,570 11,126 671 Sunflower 11,758 6,103 11,758 6,103 519 Soya Beans 127 154 127 154 1208 Simsim 65 35 65 35 540 Total 28,520 17,419 28,520 17,419 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 5,000 10,000 15,000 Groundnuts Sunflower Soya Beans Simsim Crop Area Planted (ha) -200 200 600 1000 1400 Yield (kg/ha) Yield (kg/ha) 1,292 3,178 8,703 16,570 0 5,000 10,000 15,000 20,000 Planted Area 1994/95 1995/96 1998/99 2002/03 Year Chart 3.38 Time Series Data on Groundnuts Planted Area Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 5.0 10.0 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District P ercent o f La nd 0.00 0.40 0.80 1.20 P ercent A rea P la nted o f To ta l La nd A rea Percent of Land Proportion of Land RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 31 Sixty percent of the area planted with groundnuts was located in Mpanda district (9,874 ha) followed by Sumbawanga Rural (5,136 ha, 31%), Nkasi (1,333 ha, 8%) and Sumbawanga Urban (180 ha, 1%). (Map 3.19) The district with the highest proportion of land with groundnuts was Sumbawanga Rural, followed by Mpanda, Sumbawanga Urban and Nkasi. (Chart 3.39 and Map 3.20) The largest area planted per groundnut growing household was found in Mpanda district (0.48 ha) and the lowest was in Sumbawanga Urban (0.20 ha). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. The total production of fruits and vegetables was 4,211 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 2,136 tonnes (48% of the total fruit and vegetables produced) followed by onions (1,139t, 22%), Cabbage (739t, 14%) and Amaranths (110t, 10%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 3,665 kg/ha, onions (4,279 kg/ha), cabbage (4,212 kg/ha), Amaranths (879 kg/ha), spinach (1,336 kg/ha), pumpkins (540 kg/ha) and carrot (2kg/ha) (Chart 3.42). 3.3.8.1 Tomatoes Sumbawanga Rural district had the largest planted area of tomatoes (42% of the total area planted with tomatoes in the region), followed by Mpanda (29%), Sumbawanga Urban (22%) and Nkasi (6%) (Map 3.21). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tomatoes 583 2,136 3,665 583 2,136 3,665 Onions 266 1,139 4,279 266 1,139 4,279 Cabbage 176 739 4,212 176 739 4,212 Amaranths 125 110 879 125 110 879 Spinnach 51 68 1,336 51 68 1,336 Pumpkins 22 12 540 22 12 540 Carrot 3 7 2 3 7 2 Total 1,225 4,211 1,225 4,211 Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 300 600 Tomatoes Onions Cabbage Amaranths Spinnach Pumpkins Carrot Crop A rea P la n ted (h a ) 0 1,000 2,000 3,000 4,000 5,000 Y ield (k g /h a ) 0.48 0.29 0.27 0.20 0.00 0.20 0.40 0.60 A rea p er H o u seh o ld (h a ) Mpanda Nkasi Sumbawanga Rur Sumbawanga Urb District Chart 3.40 Area Planted per Groundnut Growing Households by District (Wet Season ) Sumbawanga Urban Sumbawanga Rural 0.3ha 0.2ha 0.3ha 0.5ha Mpanda Nkasi 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Sumbawanga Urban Sumbawanga Rural 5,136ha 180ha 1,333ha 9,874ha 0.5t/ha 0.5t/ha 1.2t/ha 0.7t/ha Mpanda Nkasi 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Planted Area (ha) Planted Area and Yield of Groundnuts by District MAP 3.19 RUKWA MAP 3.20 RUKWA Area Planted per Groundnuts Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 32 Sumbawanga Urban Sumbawanga Rural 0.1ha 0.2ha 0.2ha 0.2ha Mpanda Nkasi 0.18 to 0.2 0.16 to 0.18 0.14 to 0.16 0.12 to 0.14 0.1 to 0.12 Sumbawanga Urban Sumbawanga Rural 129ha 35ha 173ha 245ha 5t/ha 0.9t/ha 1.9t/ha 4.6t/ha Mpanda Nkasi 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 Planted Area (ha) Planted Area and Yield of Tomatoes by District MAP 3.21 RUKWA MAP 3.22 RUKWA Area Planted per Tomatoes Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 33 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 The district with the highest proportion of land with tomatoes was Sumbawanga Rural followed by Sumbawanga Urban district. With exception of Sumbawanga Rural district, the rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Mpanda district (0.22 ha) followed by Nkasi (0.21 ha), Sumbawanga Urban (0.16 ha) and Sumbawanga Rural (0.14 ha) (Chart 3.44 and Map 3.22). The total area planted with tomatoes accounted for 0.19 percent of the total area planted with annual crops and vegetables during the wet season. 3.3.8.2 Onions The number of households growing onions in the region during the wet season was 1,718. This represented 1.0 percent of the total crop growing households in the region. The district with the largest planted area with onions was Sumbawanga Urban (110 ha, 41.3% of the total area planted with onions in the region), followed by Mpanda (68 ha, 25.6%), Sumbawanga Rural (68 ha, 25.6%) and Nkasi (20 ha, 7.4%) (Chart 3.45 and Map 3.23 and 2,24). The total area planted with onions accounted for 0.09 percent of the total area planted with annual crops and vegetables during the wet seasons. 3.3.8.3 Cabbage The number of households growing cabbages in the region during the wet season was 1,032 households in the wet season. This represents 0.6 percent of the total crop growing households in the region. Nkasi district had the largest planted area of cabbage (60 ha, 34.2% of the total area planted with cabbage in the region), followed by Sumbawanga Rural (59.6 ha, 33.9.9%), Sumbawanga Urban (42.2 ha, 24.1%) and Mpanda (13.6 ha, 7.8%) (Map 3.25 and 3.26) The district with the largest proportion of the area planted with cabbage was Nkasi district (0.101 ha), followed by Sumbawanga Rural (0.012 ha), Mpanda (0.003%) and Sumbawanga Urban (0.002) (Chart 3.46). The total area planted with cabbage accounted for 0.06 percent of the total area planted with annual crops and vegetables during the wet seasons. Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0 15 30 45 60 Sumbawanga Rur Mpanda Sumbawanga Urb Nkasi District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area P ercent of Land P ropo rtio n o f land 0.22 0.21 0.16 0.14 0.00 0.08 0.16 0.24 Area per Household (ha).. Mpanda Nkasi Sumbawanga Urb Sumbawanga Rur District Chart 3.44 Area Planted per Tomato Growing Household by District (Wet Season ) Chart 3.46 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 10.0 20.0 30.0 40.0 Nkasi Sumbawanga Rur Sumbawanga Urb Mpanda District Percent of Land -0.015 0.040 0.095 0.150 Percent Area Planted of Total Land Area P ercent o f Land P ro po rtio n o f Land Chart 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District 0.00 0.15 0.30 0.45 Mpanda Sumbawanga Urb Sumbawanga Rur Nkasi District Percent of Land 0.000 0.020 0.040 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Sumbawanga Rural Sumbawanga Urban 0.3ha 0.2ha 0.1ha 0.1ha Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 60ha 42ha 60ha 14ha 7.6t/ha 4.5t/ha 1t/ha 3t/ha Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Planted Area (ha) Planted Area and Yield of Cabbage by District MAP 3.23 RUKWA MAP 3.24 RUKWA Area Planted per Cabbage Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 RESULT 35 Sumbawanga Rural Sumbawanga Urban 0.1ha 0.3ha 0.2ha 0.1ha Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 20ha 68ha 68ha 110ha 3.7t/ha 6.5t/ha 5.4t/ha 2.3t/ha Mpanda Nkasi 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Planted Area (ha) Planted Area and Yield of Onions by District MAP 3.25 RUKWA MAP 3.26 RUKWA Area Planted per Onions Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household 0.26 to 0.31 0.22 to 0.26 0.18 to 0.22 0.14 to 0.18 0.1 to 0.14 RESULT 36 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 37 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 3,295 ha was planted with cash crops and tobacco was the most prominent followed by cotton. 3.3.9.1 Tobacco The quantity of tobacco produced was 3,251 tonnes. Tobacco had a planted area of 3,256 hectares with all of being planted in the wet season. Tobacco production was concentrated in two districts with Nkasi having the largest planted area (99.3% of total area planted with tobacco in the region) and Sumbawanga Rural had (0.7%). (Chart 3.43) (Map 3.29 and 3.30). 3.3.9.2 Cotton The production of cotton in Rukwa Region was only 13 tonnes from the planted area of 39 ha. It was produced during the wet season. The crop was only grown in Mpanda district (Map 3.27) with an average planted area of 0.3 hectares per cotton growing household (Map 3.28) (Chart 3.48) 3.4 Permanent Crops Permanent crops (sometimes referred as permanent crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature but survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Wet Season Total Crop Area Planted (ha) Quantity harvested (Tons) Yield Area Planted (ha) Quantity harvested (Tons) Yield Tobacco 3,256 3,251 998 3,256 3,251 998 Cotton 39 13 333 39 13 333 Pyrethrum 0 0 0 0 0 0 Jute 0 0 0 0 0 0 Total 3,295 3,264 3,295 3,264 Chart 3.47 Area planted with Annual Cash Crops Tobacco 98.8% cotton 1.2% Pyrethrum 0% Jute 0% Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.00 0.04 0.08 Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Percent of Land 0.0000 0.0010 0.0020 0.0030 0.0040 0.0050 Percent Area Planted of Total Land Area Percent of Land Percent of Land Chart 3.49: Area Planted for Annual and Permanent Crops Permanent, 8,810, 2.8% Annual , 302,344, 97.2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 The area of smallholders planted with permanent crops was 8,810 hectares (2.8% of the area planted with both annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it double counts the area planted more than once in the same year whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in (Chart 3.49). The most important permanent crop in Rukwa region is lime/lemon accounts for a planted area of 3,877 ha, (43% of the planted area of all permanent crops) followed by sugarcane (1,797 ha, 21%), banana (1,490 ha, 21%), mangoes (547 ha, 6%),orange (190 ha, 2%), pigeon pea (162 ha, 2%), guava (152 ha, 2%),palm oil (138 ha, 2%) and coconuts (60 ha, 1%). The remaining permanent crops are produced in very small quantities (Chart 3.50). The district with the largest area planted with permanent crops by smallholders was Sumbawanga Rural district (4,635 ha, 52.2%). This is followed by Nkasi (2,187 ha, 24.6%), Mpanda (1,554 ha, 17.5%) and Sumbawanga Urban (5.3 ha, 5.7%). However, Sumbawanga Rural district had the largest area planted per permanent crop growing household (0.57 ha) followed by Nkasi (0.28 ha), Sumbawanga Urban (0.18 ha) and Mpanda (0.17 ha) (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Sumbawanga Rural had the highest (23%) followed by Mpanda (3%), Nkasi (2%) and Sumbawanga Urban (0.4%). 3.4.1 Lime/lemon The total production of lime/lemon by smallholders was 133 tonnes. In terms of area planted, lime/lemon was the most important permanent crop grown by smallholders in the region. There were 401 lime/lemon growing households (0.23% of the total crop growing households). The average area planted with lime/lemon per household was relatively small at around 9.7 ha per lime/lemon growing household and the average yield obtained by smallholders was (7,389 kg/ha) from a harvest area of 18 hectares. Chart 3.50: Area Planted with the Main Perennial Crops Lime/Lemon, 3,877, 43% Sugarcane, 1,797, 21% Banana, 1,790, 21% Orange, 190, 2% Mango, 547, 6% Guava, 155, 2% Coconut, 60, 1% Palm Oil, 138, 2% Pigeon Pea, 162, 2% Chart 3.52 Percent of Area Planted with Lime/Lemon and Average Planted Area per Household by District 0.1 50.0 0.0 49.9 0.0 20.0 40.0 60.0 Sumbawanga Urban Mpanda Nkasi Sumbawanga Rural District % of Total Area Planted 0.00 4.00 8.00 12.00 16.00 20.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 25 18 6 52 0 20 40 60 Sumbawanga Rural Nkasi Mpanda Sumbawanga Urban District % of Total Area Planted 0.0 1.5 3.0 4.5 Average Planted Area per H ousehold % of T otal Area Planted Average Planted Area per Household Sumbawanga Rural Sumbawanga Urban 0ha 0ha 0ha 0.3ha Mpanda Nkasi 0.24 to 0.31 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Sumbawanga Urban Sumbawanga Rural Nkasi 0ha 0ha 39ha 0ha 0t/ha 0t/ha 0.3t/ha 0t/ha Mpanda 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Planted Area (ha) Planted Area and Yield of Cotton by District MAP 3.27 RUKWA MAP 3.28 RUKWA Area Planted per Cotton Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Planted Area per Household Yield (t/ha) Planted Area Per Household RESULT 39 Sumbawanga Urban Sumbawanga Rural 0ha 24ha 0ha 3,233ha 0t/ha 1.7t/ha 0t/ha 1t/ha Mpanda Nkasi 2,800 to 3,300 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Sumbawanga Urban Sumbawanga Rural 0ha 0.2ha 0ha 0.7hhhha Mpanda Nkasi 0.56 to 0.7 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Planted Area (ha) Planted Area and Yield of Tobbaco by District MAP 3.29 RUKWA MAP 3.30 RUKWA Area Planted per Tobbaco Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Household Planted Area Per Household RESULT 40 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 41 Sumbawanga Urban district had the largest area planted with lime/lemon (3,877 ha, 50.0%) followed closely by Mpanda (3,866 ha, 49.9%) and Nkasi (11 ha, (0.1%). Sumbawanga Rural did not grow any lime/lemon. (Map 3.31). However, the average area planted with lime/lemon per growing household was highest in Mpanda (14.4 ha) followed by Sumbawanga Urban (9.7 ha) and Nkasi (0.08 ha) (Chart 3.52 and Map 3.32). 3.4.2 Sugarcane The total production of sugarcane by smallholders was 54,638 tonnes. In terms of area planted, sugarcane was the second most important permanent crop grown by smallholders in the region. There were 4,327 households (2.5% of the total crop growing households). The average area planted with sugarcane per household was relatively small at around 0.9 ha per sugarcane growing household and the average yield obtained by smallholders was (13,381 kg/ha) from a harvest area of 4,083 hectares. Sumbawanga Rural district had the largest area planted with sugarcane (1,356 ha, 75%) followed by Nkasi (346 ha, 19%), Sumbawanga Urban (74 ha, 4%) and Mpanda (22 ha, 1%) (Map 3.31). However, the average area planted with sugarcane per growing household was highest in Nkasi district (1.43 ha) followed by Sumbawanga Rural (0.43 ha), Mpanda (0.16 ha) Sumbawanga Urban (0.06 ha) (Chart 3.52 and Map 3.32).ha) (Chart 3.53 and Map 3.34). 3.4.3 Banana The total production of banana by smallholders was 11,471 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 7,261 households (4.2% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.25 ha per banana growing household and the average yield obtained by smallholders was 11,357 kg/ha from a harvested area of 1010 hectares. Sumbawanga Rural district had the largest planted area of bananas in the region (758 ha, 42%) followed closely by Mpanda (694 ha, 39%), Sumbawanga Urban (272 ha, 15%) and Nkasi (66ha, 4%) (Map 3.35). The districts with largest area planted with banana per banana growing household were Sumbawanga Rural and Nkasi having (0.27ha) each followed by Sumbawanga Urban (0.25 ha) and Mpanda (0.23 ha) (Chart 3.49 and Map 3.36). Chart 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District 38.79 3.66 42.35 15.20 0.00 20.00 40.00 Sumbawanga Rural Mpanda Sumbawanga Urban Nkasi District % of Total Area Planted 0.00 0.15 0.30 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Sugarcane and Average Planted Area per Household by District 19 1 75 4 0 20 40 60 80 Sumbawanga Rural Nkasi Sumbawanga Urban Mpanda District % o f To ta l A rea P la nted -0.40 0.20 0.80 1.40 2.00 A v era g e P la nted A rea per H o useho ld % of Total Area Planted Average Planted Area per Household Sumbawanga Rural Sumbawanga Urban 0.27ha 0.24ha 0.27ha 0.23ha Mpanda Nkasi 0.262 to 0.27 0.254 to 0.262 0.246 to 0.254 0.238 to 0.246 0.23 to 0.238 Sumbawanga Rural Sumbawanga Urban 758ha 272ha 66ha 694ha 8.2t/ha 6.1t/ha 7.3t/ha 2t/ha Mpanda Nkasi 800 to 800 600 to 800 400 to 600 200 to 400 0 to 200 Planted Area (ha) Planted Area and Yield of Banana by District MAP 3.31 RUKWA MAP 3.32 RUKWA Area Planted per Banana Growing Household by District Tanzania Agriculture Sample Census Planted Area (ha) Yield (t/ha) Planted Area per Household Planted Area Per Household RESULT 42 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 3 .4.4 Mangoes The total production of mangoes by smallholders was 15,571 tonnes. In terms of area planted, mangoes were the fourth most important permanent crop grown by smallholders in the region. It was grown by 4,033 households (2.3% of the total crop growing households). The average area planted with mangoe per household was relatively small at around 0.4 ha per mangoes growing household and the average yield obtained by smallholders was (6,537 kg/ha) from a harvested area of (2,382 ha). Nkasi has the largest area of mangoes in the region (2,020 ha, 78.7%) followed by Mpanda (392 ha, 15.3%) and Sumbawanga Rural (155 ha, 6.0%). However, Sumbawanga Urban district did not grow any mango (Map 3.37). Moreover, Nkasi district had the highest average area planted per mangoes growing household of (1.9 ha), Sumbawanga Rural (0.14 ha) and Mpanda (0.13 ha) (Map 3.38). 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the wet season was 266,794 ha which represented 88.2 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 6.4, 3.08 and 0.9 percent respectively (Chart 3.56 and Table 3.8 ). Table 3.8: Land Clearing Methods Wet Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 150,853 266,794 88.2 150,853 266,794 88.2 No Land Clearing 2,075 3,557 1.2 2,075 3,557 1.2 Mostly Bush Clearance 10,293 19,399 6.4 10,293 19,399 6.4 Mostly Burning 7,257 9,070 3.0 7,257 9,070 3.0 Mostly Tractor Slashing 499 789 0.3 499 789 0.3 Other 1,283 2,735 0.9 1,283 2,735 0.9 Total 172,261 302,344 100 172,261 302,344 100.0 Chart 3.56: Number of Households by Method of Land Clearing During the Wet Season 499 1,283 2,075 7,257 10,293 150,853 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Other Mostly Tractor Slashing Method of Land Clearing Number of Households Chart 3.55 Percent of Area Planted with Mangoes and Average Planted Area per Household by District 6.04 78.69 0.00 15.26 0.00 20.00 40.00 60.00 80.00 Nkasi Mpanda Sumbawanga Rural Sumbawanga Urban District % of Total Area Planted 0.00 0.25 0.50 Average Planted Area per Household % of T otal Area Planted Average Planted Area per Household RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 44 3.5.2 Methods of Soil Preparation Oxen ploughing was the most used method for soil preparation as it was used in an area of 181,141 ha which represented 60.2 percent of the total prepared area, followed by hand hoe ploughing (119,096 ha, 39.6%) and tractor ploughing (583 ha, 0.2%) (Chart 3.57). In Rukwa region, Sumbawanga Rural district has the largest planted area cultivated with oxen (106,662 hectares, 58.7%) followed by Nkasi (37,412 ha, 20.6%), Mpanda (19,499, 10.7%) and Sumbawanga Urban (18,070 ha, 9.9%). 3.5.3 Improved Seed Use-* The planted area using improved seeds during the wet season was estimated at 29,135 ha which represents 9.6 percent of the total planted with the annual crops and vegetables during the season. The area planted without using improved seeds was (273,210 ha, 90.4%) Chart 3.57 Area Cultivated by Cultivation Method Mostly Oxen Ploughing, 181,643, 60.6% Mostly Hand Hoe Ploughing, 117,273, 39.1% Mostly Tractor Ploughing, 855, 0.3% Chart 3.60 Planted Area with Improved Seed by Crop Type Pulses, 2,654, 9% Roots &Tubers, 1,836, 6% Oil seeds, 3,404, 12% Fruits & Vegetables, 541, 2% Cash crop, 2,919, 10% Cereals, 17,781, 61% 0 20,000 40,000 60,000 80,000 100,000 120,000 Area Cultivated Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostly T ractor Ploughing Chart 3.59 Area Planted with Improved Seeds - RUKWA With Improved Seeds, 29,135, 9.60% Without Improved Seeds, 273,210, 90.4% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 Cereals had the largest area planted with improved seeds (17,781 ha, 61% of the planted area with improved seeds) followed by oil seed (3,404 ha, 12%) cash crops (2,919 ha, 10%) pulses (2,654 ha, 9%), roots and tubers (1,836 ha, 6%) and fruit and vegetables (541 ha, 2%), (Chart 3.54). However, of all crop types fruits and vegetables had the largest proportion of its planted area under improved seeds. with improved seeds (Chart 3.55). 3.5.4 Fertilizers Use The use of fertilisers on annual crops was very small with a planted area of only 42,191 ha (14% of the total planted area in the region). The planted area without fertiliser for annual crops was 260,153 hectares representing 86 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 26,741 ha which represents 8.8 percent of the total planted area (63.3% of the area planted with fertiliser application in the region). This was followed by Inorganic fertilizers 11,968 ha, 3.9 percent of total area planted (28.3 of the area planted with fertiliser application) compost was used on a very small area (3,518 ha, 1.2%) of the total planted area and 8.3 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Sumbawanga Urban district (37.3%) followed by Nkasi (12.7%), Sumbawanga Rural (12.3%) and Mpanda (12.0%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households used different fertilisers (approximately 171,578 households, 99.6%) (Map 3.39). The percentage of the planted area with applied fertilisers was highest for cereals (89.3% of the area planted with fertilizers). This was far followed by pulses (4.9%), oilseeds & oil nuts together with fruits & vegetables had (2.1%) each and cash crops had (0.4%) (Table 3.9) Table3.9 Planted Area by Type of Fertiliser Use and District - Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Planted Area Planted Area Planted Area Planted Area Planted Area Mpanda 2,746 762 8,030 84,693 96,231 Sumbawanga Rural 12,857 1,974 1,555 116,312 132,698 Nkasi 6,028 308 459 46,511 53,306 Sumbawanga Urban 5,110 475 1,923 12,601 20,109 Total 26,741 3,518 11,968 260,117 302,344 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 46 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Rukwa region during wet season was 26,741 hectares, this is equivalent to 8.8 percent of the total area planted during that season. The number of households that applied farm yard in their annual crops during the wet season was 18,756. (Table 3.9). Cereals had the largest area applied with farm yard manure (89.3%), followed by pulses (4.9%). Oil seeds and oil nuts together with fruits and vegetables had (2.1%), roots and tubers (1.3%) and cash crops (0.4%) (Chart 3.64a). Sumbawanga Rural district had the largest area applied with farm yard manure (48.1% of the total planted area in the region) followed by Nkasi (22.5%), Nkasi (6.9%) Sumbawanga Urban (19.1%) and Mpanda (10.3%) (Table 3.9). Chart 3.62 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 260,117, 86% Mostly Inorganic Fertilizer, 11,968, 4% Mostly Compost, 3,518, 1% Mostly Farm Yard Manure, 26,741, 9% 0 30,000 60,000 90,000 Area (ha) Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - RUKW A 0.0 10.0 20.0 30.0 Sumbawanga Urban Nkasi Sumbawanga Rural Mpanda District Percent Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - RUKWA Roots & Tubers, 340, 1% Pulses, 1,300, 5% Cerals, 23,776, 89% Oil & Oil Nuts, 552, 2% Fruits & Vegetables, 552, 2% Cash Crops, 108, 0% 0 20 40 60 80 100 Percent of Planted Area Cerals Roots & Tubers Pulses Oil Seeds Fruits & Vegetables Cash Crops Crop Type Chart 3.65a Percentage of Planted Area with Farm Yard Manure by Crop Type - RUKWA RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 47 The proportion of planted area applied with farm yard manure was highest for cereals (89.3%), followed by pulses (4.9%), fruits and vegetables together with oil seeds and oil nuts had (2.1%) each, roots and tubers and cash crops (0.4%) (Chart 3.65a). Proportionally, farm yard manure was mostly used in Sumbawanga urban by (25.4% of the total planted area in the district) followed by Nkasi (11.3%), Sumbawanga Rural (9.7%), and Mpanda (2.9%) (Chart 3.65b). For permanent crops, most farm yard manure was used in the production of sugarcane (72.7%), followed by banana (19.8%), coconut (6.9%) and guava (0.5%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Rukwa region was 11,968 hectares which represents 3.9 percent of the total planted area with annuals in the region and 28.3 percent of the total planted area with fertilisers. The number of households that applied inorganic fertilizer on their annual crops during the wet season was 8,412 Cereals had the largest area applied with inorganic fertilizers was on cereals (69.5% of the total area applied with inorganic fertilizers), followed by cash crops (25%), pulses (4.2%), oil seeds (0.8%), roots and tubers (0.3%) and fruit and vegetables (0.2%) (Chart 3.66). However, the proportion of planted area applied with inorganic fertilizers was highest for fruits and vegetables at 12.7 percent followed by roots and tubers (1.1%), pulses (0.8%) and cereals (0.3%) (Chart 3.67a). Inorganic fertiliser is mostly used in Mpanda (8.3% of the total planted area in the district) followed by Sumbawanga Rural (2.9%), Nkasi (2.3%) and Sumbawanga Urban (1.4%) (Chart 3.67b). In permanent crops inorganic fertiliser were used on coconut (70%), sugarcane (25.6%), banana (6.8%) and guavas (1.9%). 0.0 20.0 40.0 60.0 80.0 Percent of Planted Area Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - RUKW A Chart 3.66 Planted Area with Inorganic by Crop Type - RUKWA Cash Crops, 2,990, 25% Fruits & Vegetables, 29, 0.2% Oil Seeds , 91, 0.8% Pulses, 504, 4.2% Roots & Tubers, 32, 0.3% Cereals, 8,323, 69.5 Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - RUKWA 0.0 3.0 6.0 9.0 Mpanda S,mbawanga Rural Nkasi S,mbawanga Urban District Percen t Chart 3.68a Planted Area with Compost by Crop Type - RUKWA Roots & Tubers, 126, 4% Pulses, 373, 11% Cash Crops, 0, 0% Fruits & Vegetables, 15, 0.4% Oil Seeds & Oil Nuts, 68, 2% Cereals, 2,936, 83% Sumbawanga Urban Sumbawanga Rural 1,146ha 1,138ha 9,983ha 7.5% 14.1% 2.1% 1.2% Mpanda Nkasi 2,830ha 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Nkasi Sumbawanga Urban Sumbawanga Rural Mpanda 85,095ha 49,234ha 113,529ha 11,383ha 88.4% 85.6% 56.6% 92.4% 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Planted Area with no Fertilizer Applied Planted Area and Percent of Planted Area with No Application of Fertilizer by District MAP 3.35 RUKWA MAP 3.36 RUKWA Area Planted and Percent of Total Planted Area With Irrigation by District Tanzania Agriculture Sample Census Planted Area with no Fertilizer Applied Percent of Planted Area with no Fertilizer Applied Percent of Planted Area with Irrigation Applied Planted Area with Irrigation Applied Planted Area with Irrigation Applied RESULT 48 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 3.5.4.3 Compost Use The total planted area applied with compost was 3,518 hectares; this represents only 1.2 percent of the total planted area with annual crops in the region and 8.3 percent of the total planted area with fertiliser in the region. The number of households that applied compost on their annual crops during the wet season was 3,131 which is equivalent to 1.8 percent of the total crop growing households in the region during the wet season (Table 3.9 and Chart 3.68a). The proportion of area applied with compost was very low for each type of crop (0 to 8.3%); however the distribution of the total area using compost shows that 83 percent of this area was cultivated with cereals, followed by pulses (10.6%), roots & tubers (3.6%), oil seeds & oil nuts (1.9%) and fruits & vegetables (0.4%). No compost manure was applied on cash crops Chart 3.68a). Compost was mostly used in Sumbawanga Urban (2.4% of the total planted area in the district), and this is closely followed by Sumbawanga Rural (1.5%), Mpanda (0.8%) and Nkasi (0.6%) (Chart 3.68b). In permanent crops, compost was mostly used to sugarcane (100.0%) 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 25,121 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (81% of the total area applied with pesticides). This was followed by fungicides (11%) and herbicides (8%) (Chart 3.69). Chart 3.69 Planted Area (ha) by Pesticide Use Insecticides, 27,634, 81% Herbicides, 2,578, 8% Fungicides, 3,782, 11% 0.0 25.0 50.0 75.0 100.0 P e r c e n t o f P la n t e d A r e a Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type - RUKWA Chart 3.68c Proportion of Planted Area Applied with Compost Fertiliser by District - RUKWA 0.0 1.0 2.0 3.0 Sumbawanga Urban Sumbawanga Rural Mpanda Nkasi District Percen t RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.5.1 Insecticide Use The planted area applied with insecticides during the wet season was estimated at 27,634 hectares which represented 9.1 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (22,004 ha, 79.6% of the total planted area with insecticides) followed by cash crops (2,444 ha, 8.8%), pulses (1,864 ha, 6.7%), oil seed (583 ha, 2.1%) fruit and vegetables (378 ha, 1.4%) and roots and tubers (362 ha, 1.3%) (Chart 3.70). However, the proportion of area applied with insecticides was highest for cash crops and fruits and vegetables being (74 and 31% respectively, while in cereals the proportion was (11%), pulses (5%), oil seeds 2%) and roots and tubers (1%) (Chart 3.71). The annual crops with more than 50 percent insecticide use was maize (76.9%). The remaining annual crops used insecticides on less than 50 percent of the planted area Sumbawanga Urban had the highest percent of planted area with insecticides (40.4% of the total planted area with annual crops in the district). This was far followed by Sumbawanga Rural (8.3%), Nkasi (6.9%) and Mpanda (5.0%) (Chart 3.72). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 2,578 hectares which represented 0.85 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,664 ha, 64.6%) followed by roots & tubers (427 ha, 16.6%), pulses (257 ha, 10.0%) oil seeds & oil nuts (189 ha, 7.3%) and fruits & vegetables (41 ha, 1.6%). No herbicides were applied on cash crops (Chart 3.73). Chart 3.70 Planted Area Applied with Insecticides by Crop Type Oil Seeds & Oil Nuts, 583, 2.1% Fruits & Vegetables, 378, 1.4% Cash Crops, 2,444, 8.8% Roots & T ubers, 362, 1% Pulses, 1,864, 6.7% Cereals, 22,004, 79.6% 0 5 10 15 20 P ercent o f P la nted A rea Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - RUKW A 0.0 15.0 30.0 45.0 Saumbawanga Urban Sumbawanga rural Nkasi Mpanda District Percent Chart 3.73 Planted Area Applied with Herbicides by Crop Type Roots & T ubers, 427, 17% Pulses, 257, 10% Oil Seeds & Oil Nuts, 189, 7% Fruits & Vegetables, 41, 2% Cash Crops, 0, 0% Cereals, 1,664, 64% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 However, the proportion of planted area applied with herbicides was highest for fruits and vegetables and roots and tubers being (3.3% and 1.5% respectively). The proportion of cereals ( 0.8%) and for oil seeds and oil nuts it was (0.7%) (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were maize (55%), cassava (16.6%), beans (10%), sunflower (6.5%), sorghum (3.6%) and groundnuts (0.9%). Sumbawanga Rural had the highest percent of planted area applied with herbicides (1.3% of the total planted area with annual crops in the district). It was followed by Nkasi (0.8%) then Sumbawanga Urban and Mpanda had (0.4%) each (Chart 3.75). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 3,782 hectares which represented 1.3 percent of the total planted area for annual crops and vegetables. Cash crops had the largest planted area applied with fungicides (1,905ha, 50.4%) followed by cereals (909 ha, 24.0%), roots and tubers (340 ha, 9.0%), fruits and vegetables (276 ha, 7.3%), pulses (260 ha, 6.9%) and oil seeds (93 ha, 2.5%) (Chart 3.76). However, the proportion of planted area applied with fungicides was highest for cash crops and fruits and vegetables being 57.8% and 22.5% respectively. The proportion for roots and tubers was (1.2%), pulses (0.7%), cereals (0.4%) and oil seeds (0.3%). (Chart 3.77). 0.0 1.5 3.0 4.5 P ercent of Planted Area Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - TANGA 0.00 0.30 0.60 0.90 1.20 1.50 Sumbawanga Rural Nkasi Sumbawanga Urban Mpanda District Percent Chart 3.76 Planted Area Applied with Fungicides by Crop Type Cereals, 909, 24% Roots & T ubers, 340, 9% Pulses, 260, 7% Oil Seeds & Oil Nuts, 93, 2% Fruits & Vegetables, 276, 7% Cash Crops, 1,905, 51% 0.0 20.0 40.0 60.0 P ercent o f P la nted A rea Cereals Roots & T ubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 52 The annual crop with more than 40 percent fungicide use was tobacco (59%).Tomatoes had (34.4%), cassava (1.3%), beans (0.7%), maize (0.6%) and groundnuts (0.4%). Mpanda had the highest percent of planted area with fungicides (2.8% of the total planted area with annual crops in the district). This was followed by Sumbawanga Urban (2.2%). The smallest percentage use was recorded in Sumbawanga Rural and Nkasi districts being (0.2% and 0.7% respectively) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.2%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 89 percent of the total area planted with cereals during the long rainy season being threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1%, 0.1 percent and 0.2 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Rukwa region, the area of annual crops under irrigation was (7,523 ha) representing 2 percent of the total area planted (Chart 3.79). Some cereal crops such as maize and paddy were predominantly irrigated The district with the largest planted area under irrigation for annual crops was Sumbawanga Rural (5,487 ha, 73% of the total irrigated planted area with annual crops in the region). This was followed by Mpanda (844 ha, 11%), Sumbawanga Urban (730 ha, 10%) and Nkasi (462 ha, 6%). Chart 3.78 Proportion of Planted Area with Fungicides by District - RUKWA 0.0 0.6 1.2 1.8 2.4 3.0 Mpanda Sumbawanga Urban Nkasi Sumbawanga Rural District Percent Chart 2.80 Planted Area with Irrigation by District - RUKWA Region 0 2,000 4,000 6,000 Sumbawanga Rural Mpanda Sumbawanga Urban Nkansi District Ir r ig a t e d A r e a ( h a ) 0.0 1.6 3.2 4.8 P e r c e n t a g e Ir r ig a t io n Area Irrigated Land this Year Percentage of Irrigated Land Chart 3.79 Area of Irrigated Land Non-Irigated area, 294,921, 98% Irrigated Area, 7,523, 2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 When expressed as a percentage of the total area planted in each district Sumbawanga Rural had the largest area under irrigation at (4.1%). This was followed by Sumbawanga Urban (3.6%). Mpanda and Nkasi districts had (0.9%) each (Chart 3.80 and Map 3.40). Of all the different crops and in terms of proportion of the irrigated planted area, paddy was the most irrigated crop with 35 percent irrigation followed by maize (28%), cassava (17%), beans (5%) and tomatoes (2%). In terms of crop type, the area under irrigation for cereals was 10,470 hectares (69.4% of the total area under irrigation), followed by roots and tubers with 2,782 hectares (18.4%), pulses (754 ha, 5%), fruits and vegetables (601 ha, 4%), cash crops (273 ha, 1.8%) and oil seeds (218 ha, 1.4%). All of the irrigation for cereals was applied to paddy and maize The number of agricultural households practicing irrigation in Rukwa region appears to have decreased by (26.8%) from 8,958 agricultural households in 1995/96 to 6,561 agricultural households in 2002/03. This may not be statically significant due to the small number of households sampled with irrigation (Chart 3.81) 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from rivers (66% of households with irrigation). This was followed by wells (19%), canal (9%), boreholes (3%), dams (2%) and lake (1%). 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 65 percent of households using this method. This was far followed by hand bucket with 29 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.76). Gravity was used by most households with irrigation in Sumbawanga Rural (66%), followed by Sumbawanga Urban Chart 3.82 Number of Households with Irrigation by Source of Water Borehole, 435, 3% Dam, 344, 2% Lake, 148, 1% Well, 3,137, 19% Canal, 1,593, 9% River, 11,225, 66% River Well Canal Borehole Dam Lake Chart 3.81 Time Series of Households with Irrigation - RUKW A 6,561 8,958 0 3,000 6,000 9,000 12,000 1995/96 2002/03 Agriculture Year P la nted A rea ubder Irrig a tio n Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 4,974, 29% Gravity, 11,028, 65% Hand Pump, 133, 1% Other, 602, 4% Motor Pump, 146, 1% Gravity Hand Bucket Other Motor P ump Hand P ump RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 (13%), Mpanda (11%) and Nkasi (10%). Hand bucket was more common in Mpanda with 40 percent of households using the method to obtain water for irrigation, followed by Sumbawanga Urban (26), Sumbawanga Rural (23%) and Nkasi (11%). While the method of obtaining irrigation water by hand pumps was the most common method in Mpanda district, motor pump was the most common method of obtaining irigation water in Nkasi and Sumbawanga Urban. 3.6.4 Methods of Water Application Most households used flooding (67.4% of households using irrigation) as a method of field application. This was followed by hand bucket/watering can (30.3%). Water hose and sprinklers were not widely used as they were 1.5% and 0.8% of the households respectively. 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Rukwa region show that there were 164,147 crop growing households (95.3% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 152,974 households storing 43,758 tonnes as of 1st January 2004. This was followed by sorghum/millets (24,085 households, 9,873 tons), paddy (26,058 households, 5,923t), beans/pulses (70,698 households, 5,339t) and groundnuts/bambaranuts (32,955 households, 3,463t). Other crops were stored in very small amounts. Chart 3.84 Number of Households with Irrigation by Method of Field Application Flood, 11,381, 67.0% Sprinkler, 143, 0.8% Water Hose, 248, 1.5% Bucket / Watering Can, 5,111, 30.3% Flood Bucket / Watering Can Water Hose Sprinkler Chart 3.85 Number of Households and Q uantity Stored by Crop Type - RUKWA 0 40,000 80,000 120,000 160,000 M aize Sorghum & M illet Paddy Beans & Pulses G'nuts/B amb Nut W h eat Cottton Co ffee Cashewnut Tob acco Crop N u m b e r o f h o u s e h o ld s 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 Q u a n t it y ( t ) Number of households Quantity stored (Tons) RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.7.1.1 Methods of Storage The region had 120,769 crop growing households storing their produce in sacks/open drums (73.6% of households that stored crops in the region). The number of households that stored their produce in locally made traditional cribs was 41,282 (25.1%). This was followed by those that stored their produce in improved locally made cribs (765 households, 0.5%), unprotected piles (651 households, 0.4%), air tight drums (276 households, 0.2%), modern store (203 households 0.1%) and other (201 households, 0.1%). Sacks/open drums were the dominant storage method in all districts, with the highest percent of households in Sumbawanga Urban using this method (89% of the total number of households storing crop products). This is followed by Nkasi (81%), Sumbawanga Rural (74%) and Mpanda (66%) (Chart 3.80). The highest percent of households using locally made structures were in Mpanda and Sumbawanga Rural districts (32% and 25% of the total number of households storing crops respectively), followed by Nkasi (18.9%) and Sumbawanga Urban (8%) 3.7.1.2 Duration of Storage Most households (49.3% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (45.6%) and those households who stored the crop for the period of less than 3 months were (5.1%) (Chart 3.88) Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0.00 10.00 20.00 30.00 40.00 50.00 Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Quantity (tonnes) 0 5 10 15 20 25 30 35 % Stored Quantity Harvested Quantity Stored % stored Chart 3.86 Number of households by Storage Methods - RUKWA Sacks / Open Drum, 120,769, 73.6% Unprotected Pile, 651, 0.4% Airtight Drum, 276, 0.2% Modern Store, 203, 0.1% Other, 201, 0.1% Improved Locally Made Structure, 765, 0.5% Locally Made Traditional Structure, 41,282, 25% 0 20,000 40,000 60,000 80,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 Months 3 to 6 Months Over 6 Months RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mpanda district (58%) followed by Nkasi (49%), Sumbawanga Urban (46.2%) and Sumbawanga Rural (41.5%) (Map 3.41). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Sumbawanga Urban district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was probably determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 88.6 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at higher price (Chart 3.10). 3.7.1.4 The Magnitude of Storage Loss About 86.4 percent of households that stored crops had little or no loss; however the proportion of households that experienced a loss up to a quarter was 11.1 percent. (Table 3.10) The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (9.3% of the total number of households that stored crops). This was followed by maize (9.1%), groundnuts and bambaranut (5.4%), beans and pulses (2.9%) and paddy (1.1%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (94%) 3.10: Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Mpanda 54,498 3,163 402 269 58,332 Sumbawanga Rural 53,339 9,491 1,168 712 64,708 Nkansi 23,714 3,746 709 78 28,247 Sumbawanga Urban 10,228 1,885 577 169 12,859 Total 141,778 18,285 2,856 1,228 164,147 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses G'Nuts/Bamb Nuts Wheat Cottton Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other Sumbawanga Rural Sumbawanga Urban 46,242 59,911 24,110 81.47% 86.97% 79.17% 77.7% Mpanda Nkasi 10,835 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Sumbawanga Urban Sumbawanga Rural 41.5% 46.2% 48.8% 57.9% Mpanda Nkasi 54.7 to 57.9 51.4 to 54.7 48.1 to 51.4 44.8 to 48.1 41.5 to 44.8 Percent of Household Storing Crops Percent of Households Storing Crops For 3 to 6 Months by District MAP 3.37 RUKWA MAP 3.38 RUKWA Number of Households and Percent of Total Households Selling Crops by District Tanzania Agriculture Sample Census Percent of Household Storing Crops Percent of Households Selling Crops Number of Households Selling Crops Number of Households Selling Crops RESULT 57 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Rukwa region (167,155 households, 97% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 80%). Mpanda and Sumbawanga Rural had the lowest percent of households processing crops (96% and 97% of crop growing households respectively) (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households (133,195 households) processed their crops using neighbour’s machines, this representing 80 percent This was followed by those processing on-farm by hand (20,209 households, 12.1%), trader (9,585 households, 5.2%) and on-farm by machine (3,397 households, 2%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Rukwa region, however district differences existed. Mpanda has a higher percent of hand processing than other districts (17%), followed by Nkasi (14%), Sumbawanga Rural (9%) and Sumbaweanga Urban (2%). Processing by trader was more common in Sumbawanga Rurasl and Sumbawanga Urban (14.3% and 0.3% respectively), whilst processing on farm by machine was more prevalent in all four districts of Nkasi, Sumbawanga Urban, Sumbawanga rural and Mpanda (Chart 3.92). 0 20 40 60 80 100 Percent of Households Processing Nkansi Sumbawanga Urban Sumbawanga Rural Mpanda District Chart 3.91b: Percentage of Households Processing Crops by District Chart 3.92: Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Co-operative Union By Trader Other By Factory Chart 3.93 Percent of Households by Type of Main Processed Product Flour / M eal 92.8% Juice 0.1% Oil 1.7% Rubber 0.04% Grain 5.4% Chart 3.91a : Households Processing Crops Households Processing, 167,155, 97% Households Not Processing, 4,690, 3% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 155,071 households processing crops into flour (92.8%) followed by grain with 9,077 households (5.4%) and oil 2,751 households (1.7%). The remaining products such as juice and rubber were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 33.6 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 29,934 households (53.5%) followed by Husks (13,429 households, 23.9%), cake (7,281 households, 13%) and shell (4,131 households, 7.4%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Mpanda and Sumbawanga Rural were the only districts that used primary products as fuel for cooking. Chart 3.94 Number of Households by Type of By-product Fiber, 205, 0% Juice, 34, 0% Pulp, 484, 1% Husk, 13,429, 24% Cake, 7,281, 13% Oil, 201, 0% Shell, 4,131, 7% Other, 284, 1% Bran, 29,934, 54% Chart 3.95 Use of Processed Product Animal Consumption, 451, 0.2% Did Not Use, 710, 0.3% Sale Only, 3,510, 1.2% Fuel for Cooking, 912, 0.4% Household/ human consumption, 277,966, 97.7% 0.00 2.00 4.00 6.00 8.00 10.00 Percentage of households Mpanda Sumbawanga Rural Sumbawanga Urban Nkansi District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Secondary Market, 823, 7.7% Farmers Association, 568, 5.3% Local Market / Trade Store, 596, 5.6% Neighbours, 6,568, 61.5% Marketing Co- operative, 132, 1.2% Large Scale Farm, 34, 0.3% Trader at Farm, 1,851, 17.3% Other, 115, 1.1% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 Out of 10,687 households that sold processed products, 6,158 were from Mpanda (57.6% of the total number of households selling processed products in the region), followed by Sumbawanga Rural with 3,529 households (33%), Nkasi with 654 households (6.1%) and Sumbawanga Urban with 345 households (3.2%) (Chart 3.96). Compared to other districts in Rukwa region, Mpanga had the highest percent of households (10.8%) that sold processed products. This is followed by Sumbawanga Rural (5.3%), Sumbawanga Urban (2.6%), and Nkasi (2.2%). 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold them to neighbours (7,582 households, 35%), local market and trade stores (6,568 households, 61.5% of households that sold crops). This was followed by selling to trader at farm (1,851 households, 17.3%), secondary market (823 households, 7.7%), local market trade store (596 households, 5.6%), farm associations (568 households (5.3%), marketing co-operatives (132 households, 1.2%), other (115 households, 1.1%) and larege scale farms (34 households, 0.3%) and other places (115 households, 1.1%)(Chart 3.97). There are large differences between districts in the proportion of households selling processed products to neighbours with Mpanda district having the largest percentage (57.4%) and Sumbawanga Urban having the lowest (0.5%). Compared to other districts, Sumbawanga Rural had the highest percent of households selling processed products to traders at farm. Both Sumbawanga Rural and Urban districts sold processed produce to farmer associations most. The district which had the highest proportion of households selling processed products to marketing cooperative was Nkansi. 3.7.3 Crop Marketing The number of households that reported selling crops was 141,097 which represent 81.9 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Sumbawanga Rural (42%) followed by Mpanda (33%), Nkasi (17.1%) and Sumbawanga Urban (8%) (Chart 3.99 and Map 3.42) Chart 3.98 Percent of Households S elling Processed Products by Outlet for S ale and District 0% 20% 40% 60% 80% 100% Mpanda Sumbaw anga Rural Nkansi Sumbaw anga Urban District Percent of Households Selling Neighbours Local Market / T rade Store Marketing Co-operative Farmers Association Large Scale Farm T rader at Farm Secondary Market Other Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of roblem Open Market P rice Too Low 79% Other 0% No Transport 3% Farmers Association P roblems 0% Co-operative P roblems 0% No Buyer 0% Lack of Market Information 2% Transport Cost Too High 6% Market too Far, 9624, 10% Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 Sumbawanga Rural Mpanda Nkansi Sumbawanga Urban District Number of Households 0.0 30.0 60.0 90.0 Percent Number o f Ho us eho lds Selling Cro ps Percentage of Householdss Slling crops RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.7.3.1 Main Marketing Problems Open market price too low for agricultural produce was the main marketing problem reported by most households (78.1% of crop growing households) followed by longer distances to the markets (10.1%), high transport costs (5.7%), lack of transport (5.7%), lack of market information (2.1%) and other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell” which accounted for 90 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts in Rukwa region. 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Rukwa region very few agricultural households (7,365, 4.3%) accessed credit out of which 6,833 (93%) were male-headed households and 533 (7%) were female-headed households. In Nkasi district only female-headed households got agricultural credit whereas in Mpanda, Sumbawanga Rural and Sumbawanga Urban districts both male and female headed households accessed credit. (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Rukwa region were co-operatives 2,685 agricultural households (35.8% of the total number of households that accessed credit) this was followed by traders/trade stores (34.9%), family, friends and relatives (25.9%), private individuals (2.1%) and religious organization, NGO and projects (1.3%) (Chart 3.101). Co- operative and religious organization, NGO and projects were the sole source of agricultural credit in Mpanda and Sumbawanga Urban districts respectively. Family, Friends and Relatives provided agricultural credits in all four districts in the region (Chart 3.102). Table 3.12 Reasons for Not Selling Crop Produce Number of Household % Production Insufficient to Sell 96,997 90.0 Price Too Low 6,450 6.0 Other 2,652 2.5 Market Too Far 992 0.9 Trade Union Problems 303 0.3 Government Regulatory Board Problems 198 0.2 Farmers Association Problems 134 0.1 Total 107,725 100 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male % Female % Total District 4,552 94 270 6 4,821 Sumbawanga Rural 2,146 95 116 5 2,261 Nkansi 0 0 80 100 80 Sumbawanga Urban 135 67 67 33 202 Total 6,833 93 533 7 7,365 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 62 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on buying fertilizers (30%), this was followed by hiring labour (20%), buying seeds (18%) and agro-chemicals (17%). The proportion of agricultural credits intended to be used for buying tools/equipments, irrigation structures, and others was very low (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was that, credits were not available accounting to 31 percent of the agricultural households. This was followed by households reporting the lack of credit awareness (27%), the knowledge of credit (19%). Also other households did not want to go into debits (13%). The rest of the reasons were collectively less than 8 percent of the households. C hart 3.102: Num ber of Households Receiving C re dit by Main Source of C re dit and District 0% 20% 40% 60% 80% 100% Nkansi Sumbawanga Rural Sumbawanga Urban Mpanda District Percent of Households Family, Friend and Relative Co-operative T rader / T rade Store Private Individual Religious Organisation / NGO / Project C hart 3.101: Percentage Distribution of Households RecievingC redit by Main Source Co-operative 36% Trader / Trade Store 35% Private Individual 2% Religious Organisation / NGO / Project 1% Family, Friend and Relative 26% Chart 3.104 Reasons for not Using Credit (% of Households) Did not want to go into debt 13% Interest rate- cost too high 3% Did not know how to get credit 26% Difficult bureaucracy procedure 3% Credit granted- too late 0% Not available 32% Not needed 4% Don't know about credit 19% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Other, 270, 2% Irrigation Structures, 537, 4% Agro-chemicals, 2,210, 17% Fertilizers, 3,966, 30% Seeds, 2,353, 18% Labour, 2,594, 20% Tools / Equipment, 1,178, 9% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 63 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 9,046 (17% of total crop growing households in the region) (Chart 3.105). Some districts had more access to extension services than others, with Sumbawanga Rural having a relatively high proportion of households (20%) that received crop extension messages in the district followed by Mpanda (19%), Sumbawanga Urban (15%) and Nkasi (6%) (Chart 3.106 and Map 4.43). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (85%, 24,535 households). NGO/Development projects provided (10.3%), large scale farms (3%), co-operatives (1.1%).The remaining extension source of extension provided only (0.6%) Chart 3.107). However, district differences exist with the proportion of the households receiving extension advices from government services ranging from between 73 percent and 100 percent in Mpanda to 90 percent in Sumbawanga Urban. Chart 3.105 Number of Households Receiving Extension Advice Households Receiving Extension 9,046, 17% Households Not Receiving Extension 3,215, 83% Chart 3.106 Number of Households Receiving Extension by District 0 3,000 6,000 9,000 12,000 15,000 Sumbawanga Rural Mpanda Sumbawanga Urban Nkansi District Number of H ouseholds 0 10 20 30 Percent of Households Number of Households Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Other 1% Government 85% NGO / Development Project 10% Cooperative 1% Large Scale Farm 3% Chart 3.108 Number of Households Receiving Extension by Quality of Services Very Good, 2,657, 9.2% Poor, 1,675, 5.8% Average, 8,059, 27.9% Good, 16,539, 57.2% RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.8.2.2 Quality of Extension An assessment of the quality of extension indicated that 57.2 percent of the households receiving extension ranked the service as being good followed by average (27.9 %), very good (9.2%) and poor (5.8%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops. Because of this, some of the figures presented in this section may be slightly different from those in previous section on insecticides inputs use (Section 3.5). Data on sources of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Rukwa region farm yard manure was used by 19,966 households which represent 12 percent of the total number of crop growing households. This was followed by households using insecticides/fungicides (11.3%), inorganic fertilisers had (6.5%), improved seeds (5.2%) compost (1.9%) and herbicide (0.2%) (Table 2.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Rukwa mostly purchase from the local market/trade store (58.8% of the total number of inorganic fertiliser users) followed by co-operatives (24.3%) and crop buyers (12.1%). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Table 2.13 Use of Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm yard manure 19,966 11.6 152,375 88.4 Improved seeds 9,018 5.2 163,243 94.8 Pestcides/Fungicide 19,503 11.3 152,758 88.7 Inorganic fertiliser 11,103 6.5 160,960 93.5 Compost 11,103 6.5 160,960 93.5 Herbicide 269 0.2 171,991 99.8 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 58.8 24.3 12.1 3.5 1.2 0 2,000 4,000 6,000 8,000 Local Market / Trade Store Co-operative Crop Buyers Local Farmers Group Secondary Market S o u r c e o f I n o r g a n ic F e r t ilis e r Number of Households Sumbawanga Rural Sumbawanga Urban 19,434 1,964 11,454 1,911 14.87% 19.27% 6.37% 28.27% Mpanda Nkasi 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Sumbawanga Urban Sumbawanga Rural 2,002 11,351 13,859 1,834 157% 20.17% 67% 19.17% Mpanda Nkasi 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Household Receiving Crop Extension Services Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.39 RUKWA MAP 3.40 RUKWA Number and Percent of Crop Growing Households Using Improved Seed by District Tanzania Agriculture Sample Census Number of Household Receiving Crop Extension Services Percent of Number of Household Receiving Crop Extension Services Percent of Households Growing Crops Using Improved Seed Number of Households Growing Crops Using Improved Seed Number of Households Growing Crops Using Improved Seed RESULT 65 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 The source of inorganic fertiliser was mainly more than 10 km from the household with most households residing between 10 and 20 km from the source (29%), followed by between 3 and 10 km (28%), 20 km and above (20%), between 1 km and 3km (14%) and less than 1 km (9%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 69 percent of households responding to cost factors as the main reason for not using. In other words, it may be assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. More smallholders use inorganic fertilisers in Mpanda than in other districts in Rukwa region (83.4% of households using inorganic fertilisers), followed by Sumbawanga Urban (8.5%). Other districts use very little inorganic fertiliser. 3.9.3 Improved Seeds The percentage of households that used improved seeds was 5.2 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (55.9%) followed by co-operatives (20.9%) and crop buyers (12.3%). Other less important sources of improved seed are from neighbours (5.7%), local farmers groups (2.9%), development partners (1.4%) and large scale farms (0.9%) (Chart 3.111). Access to improved seed is better than access to chemical inputs with 30 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly used improved seeds are Mpanda (66.3 percent of the total number of households using improved seeds in Rukwa region), followed by Sumbawanga Rural (20.7%) and Sumbawanga Urban (8.7%) and Nkasi (4.3%) (Map 3.44). C hart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111 Number of Households by Source of Improved Seed 0.9 1.4 2.9 5.7 12.3 20.9 55.8 0 1,500 3,000 4,500 6,000 Local Market / T rade Store Co-operative Crop Buyers Neighbour Local Farmers Group Development Project Large Scale Farm Source of Improved Seed Number of Households RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 Insecticides and Fungicides Most smallholder households using insecticides and fungicides mainly purchased them from locally produced by households’ (41.9% of the total number of fungicide users) and local farmers group (26.7%). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). However, Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 7 percent of households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 66 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Sumbawanga Urban district (36.1 percent of the total number of households that use fungicide in the region), followed by Sumbawanga Rural 32.1%), Mpanda (24.1%) and Nkasi (7.7%). 3.9 Tree Planting The number of households involved in tree farming was 29,439 representing 17.1 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allocated land was 2,101,632 trees. The average number of trees planted per household planting trees was 71 trees Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of H ouseholds Chart 3.113 Number of Households by Source of Insecticide/fungicide 41.9 26.7 8.6 8.5 7.5 5.8 1.0 0 1,000 2,000 3,000 4,000 Locally Produced by Household Local Farmers Group Crop Buyers Neighbour Secondary Market Local Market / Trade Store Large Scale Farm Source of Insecticide/fungicide Number of Households Chart 3.115 Number of Households with Planted Trees - RUKWA Households without Planted Trees, 142822, 83% Households with Planted Trees, 29439, 17% Sumbawanga Urban Sumbawanga Rural 2,830 1,138 1,146 9,983 14.1% 7.5% 2.1% 1.2% Mpanda Nkasi 120 to 150 90 to 120 60 to 90 30 to 60 0 to 30 Number of Smallhohders Planted Trees Number and Percent of Smallholder Planted Trees by District MAP 3.41 RUKWA Tanzania Agriculture Sample Census Number of Smallhohders Planted Trees Percent of Smallhohders Planted Trees RESULT 68 RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 The main species planted by smallholders is Eucalyptus (1,778,915, 85%), senna spp (222,188, 11%), Gravellia spp (58,385 trees, 3%), jacaranda spp (17,556 trees, 1% and afzelia quanzensis ( 10,399 trees, 0.5%). The remaining trees species are planted in comparatively small numbers (Chart116.). Sumbawanga Urban district has the largest number of planted trees than any other district (79.3%) and is dominated by Eucalyptus species. This is followed by Sumbawanga Rural (8.2%) which is dominated by Eucalyptus species, Nkasi (7.3%) and Mpanda (5.2%) which is mainly planted with Eucalyptus (Chart 3.117 and Map 3.45.). Smallholders mostly plant trees on the plantation or coppices. The proportion of trees that planted on field plantation or copies was 78 percent, followed by scattered around fields (12%) and then trees planted in a field or plot boundaries (10%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (35.9%). This is followed by wood for fuel (30.1%), shade (22.7%) and poles (9.8%), medicinal (1.1%), charcoal and other had (0.26%) each (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 16,883 which represent 10 percent of the total number of agricultural households in the region (Chart 3.120). C hart 3.118 Number of Trees Planted by Location Mostly on Field / Plot Boundaries, 4,272, 9.9% Mostly Scattered in Field, 5,027, 11.7% Mostly in Plantation / Coppice, 33,850, 78.4% Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Household Without Facilities, 155,378, 90% Household With Facilities, 16,883, 10% Chart 2.116 Number of Planted Trees by Species - RUKWA 0 400,000 800,000 1,200,000 1,600,000 2,000,000 Eucalyptus Spp Senna Spp Gravellis Jakaranda Spp Afzelia Quanzensis Cyprus Spp Acacia Spp Pinus Spp Azadritachta Spp Trichilia Spp Melicia excelsa Casurina Tectona Grandis Syszygium Spp Leucena Spp Calophylum Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and Region 0 180,000 360,000 540,000 720,000 900,000 1,080,000 Sumbawanga Urban Sumbawanga Rural Nkansi Mpanda District Number of Trees Eucalyptus Spp Senna Spp Gravellis Afzelia Quanzens is Cyprus Spp Acacia Spp P inus Spp Melicia excels a Cas urina Equis etfilia Tecto na Grandis J akaranda Spp Chart 3.119 Number of Households by Purpose of Planted Trees 0.00 10.00 20.00 30.00 40.00 Planks / T imber Fuel for Wood Shade Poles Medicinal Charcoal Other Use Percent of Households RESULTS – Tree Planting and Erosion Control _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 70 The proportion of households with soil erosion control and water harvesting facilities was highest in Sumbawanga Urban district (16%) followed by Mpanda (12%) and Sumbawanga Rural (8%). Nkasi district had the lowest proportion of (5%) (Chart 3.121). Erosion control bunds accounted for 82.5 percent of the total number of structures, followed by water harvesting bunds (14%), drainage ditches (2.5%), tree belts (0.5%), dam (0.4%), terraces and vetiver grass had (0.1%) each. However, gabions/sandbags were not used in the district (Chart 3.122) and Map 3.46 Erosion control bunds and water harvesting bunds together had 261,070 structures. This represented 96.5 percent of the total structures in the region. The remaining 3.5 percentages were shared among the rest of the erosion control methods mentioned above. Mpanda and Sumbawanga Rural districts had 260,332 erosion control structures which is equivalent to 96.2 percent of the total erosion structures in the region. Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.0 0.1 0.1 0.4 0.5 2.5 14.0 82.5 0 50000 100000 150000 200000 250000 Erosion Control Bunds Water Harvesting Bunds Drainage Ditches Tree Belts Dam Vetiver Grass Terraces Gabions / Sandbag T y p e o f F a c ilit y Number of Structures Chart 3.121 Number of Households With Erosion Control/Water Harvesting Facilities 12 8 16 5 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Mpanda Sumbawanga Rural Sumbawanga Urban Nkansi District Number of Households 0 5 10 15 20 Percent No of Households Percent RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 71 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 504,727. Cattle were the most dominant livestock type in the region followed by goats, sheep and pigs. The region had 3.0 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Rukwa region was 504,345 (99.7 % of the total number of cattle in the region), 1,107 cattle (0.2%) were dairy breeds and 274 cattle (0.1%) were beef breeds. The census results show that 43,551 agricultural households in the region (25.3% of total agricultural households) kept 0.5 million cattle. Therefore, the average number of cattle per household was 12 (Chart 3.123 and Map 3.47). However Sumbawanga Urban district had the highest density (61 head per km2) (Map 3.48). Although Sumbawanga Rural district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle was very small and there was no beef cattle kept in the respective district. Mpanda district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Thirteen percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 37 percent of all cattle in the region. Only 14 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 50.2 percent of total cattle rearing households had herds of size 1-30 cattle and owns 50.1 percent of total cattle in the region, resulting in an average of 6 cattle per cattle rearing household. There were about 463 households with a herd size of more than 151 cattle each (123,239 cattle in total) resulting in an average of 266 cattle per household. 0 50,000 100,000 150,000 200,000 250,000 Number of Cattle ('000') Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 110,000 220,000 Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban Districts N u m b e r o f C a t t le Indigenous Improved Beef Improved Dairy RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.12.1.3 Cattle Population Trend Cattle population in Rukwa decreased during the period of eight years from 426,329 in 1995 to 378,338 cattle in 2003. This trend depicts an overall annual negative growth rate of -1.48 percent (Chart 3.125). However, there was a very sharp decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –2.55 percent whereby the number dropped from 426,329 to 384,410. Moreover, the number of cattle was estimated to have slightly decreased from 384,410 in 1999 to 378,338in 2003 at the rate of -1.48 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Rukwa region was 1,328 (1,107 dairy and 274 improved beef). The diary cattle constituted 0.2 percent of the total cattle and 88.4 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 20.6 percent of the total number of the improved cattle and 0.1 percent of the total cattle. The number of improved cattle increased from 448 in 1995 to 1,107 in 2003 at an annual growth rate of 12.10. The growth rate was higher for the period from 1995 to 1999 (63.54%) than from 1999 to 2003 when it dropped by -23.16 percent (Chart 126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Rukwa region ranked 16 out of the 21 regions with 2.5 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Rukwa region was 43,150 (25% of all agricultural households in the region) with a total of 292,849 goats giving an average of 7 head of goats per goat-rearing-household. Sumbawanga Rural district had the largest number of goats (118,607 goats, 40.5% of all goats in the region) followed by Mpanda (118,261 goats, 40.4%) and Nkasi (42,696 goats, 14.6%). Sumbawanga Urban district had the least number of goats (13,285 goats, 4.5%) (Chart 3.127 and Map 3.49) However both Sumbawanga Urban and Sumbawanga Rural districts had the highest density of goats (22 head per km2 ) each (Map 3.50). 426,329 384,410 378,338 - 150,000 300,000 450,000 N u m b er of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 448 3,176 1,107 - 1,500 3,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend 0 30,000 60,000 90,000 N u m b e r o f G o a t s ( '0 0 0 ') . Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Chart 3.127 Total Number of Goats ('000') by District RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 3.12.2.2 Goat Herd Size Forty nine percent of the goat-rearing households had herd size of 1-4 goats with an average of 2 goats per goat rearing household. Sixty six percent of total goat-rearing households had herd size of 1-14 goats and owned 66.3 percent of the total goats in the region resulting in an average of 5 goats per goat-rearing households. The region had 321 households (0.7%) with herd sizes of 40 or more goats each (16,877 goats in total), resulting in an average of 53 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.6 percent of the total goats in the region. Improved goats for meat and diary goats constituted 0.8 and 0.6 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 6.05 percent. This positive trend implies eight years of population increase from 183,041 in 1995 to 292,849 in 2003. The number of goats increased from 183,041 in 1995 at an estimated annual rate of 7.18 percent to 241,546 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 4.93 percent (Chart 128). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Rukwa region after cattle and goats. The region ranked 16 out of 21 Mainland regions and had 0.9 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 4,770 (2.8 % of all agricultural households in Rukwa region) rearing 36,073 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Mpanda with 13,967 sheep (38.7% of total sheep in Rukwa region) followed by Sumbawanga Rural (10,953 sheep, 30.4%) and Nkasi (10,756 sheep, 29.8%). Sumbawanga Urban district had the least number of sheep (397 sheep, 1.1%) (Chart 3.129 and Map 3.51). Sumbawanga Rural and Nkasi districts also had the highest density (2 head per km2 ) (Map 3.52) each.All sheep kept were indigenous breed 183,041 241,546 292,849 - 120,000 240,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 5,000 10,000 15,000 N u m b er o f s h eep Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban District Chart 3.129 Total Number of Sheep by District Sumbawanga Rural Sumbawanga Urban 44 61 29 5 Mpanda Nkasi 49.8 to 61 38.6 to 49.8 27.4 to 38.6 16.2 to 27.4 5 to 16.2 Sumbawanga Urban Nkasi Mpanda Sumbawanga Rural 36,156 149,080 82,871 236,620 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Number of Cattle Cattle Population by District as of 1st Octobers 2003 MAP 3.42 RUKWA MAP 3.43 RUKWA Cattle Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Cattle Population Number of Cattle of per Square Km Cattle Density RESULT 74 Sumbawanga Rural Sumbawanga Urban 8 7 22 22 Mpanda Nkasi 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Sumbawanga Urban Sumbawanga Rural 13,285 118,607 42,696 118,261 Mpanda Nkasi 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Number of Goats Goats Population by District as of 1st Octobers 2003 MAP 3.44 RUKWA MAP 3.45 RUKWA Goats Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Goats Population Number of Goats of per Square Km Goats Density RESULT 75 RESULTS – Livestock Production _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 76 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at 22.92 percent. The population increased at an annual rate of 17.11 percent from 6,923 in 1995 to 13,021 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 22.92 percent (Chart 3.130). 3.12.4. Pig Production Piggery was the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 16 out of 21 Mainland regions and is 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Rukwa region was 12,101 (7% of the total agricultural households in the region) rearing 51,840 pigs. This gives an average of 4 pigs per pig-rearing household. The district with the largest number of pigs was Sumbawanga Rural with 36,455 pigs (70.3% of the total pig population in the region) followed by Nkansi (8,396 pigs, 16.2%), Mpanda (4,837 pigs, 9.3%) Sumbawanga Urban (2,152 pigs, 4.2%) (Chart 3.131 and Map 3.53). However Sumbawanga Urban district had the highest density (3.6 head per km2 ) (Map 3.54). 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population over the eight years period from 1995 to 2003 was 20.33 percent. During this period the population grew from 11,794 to 51,840. The pig population increased from 11,794 in 1995 to 22,341 in 1999 at a rate of 17.32 percent. The growth rate increased to 23.42 percent during the following four years from 1999 to 2003 in which pig population increased from 22,341 to 51,840 (Chart 3.132). 6,923 13,021 36,073 - 15,000 30,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 11,794 22,341 51,840 - 30,000 60,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 15,000 30,000 N u m b e r o f P ig s Sumbawanga Rural Nkansi Mpanda Sumbawanga Urban District Chart 3.131 Total Number of Pigs by District DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 77 3.12.5 Chicken Production The poultry sector in Rukwa region was dominated by chicken production. The region contributed 3.4 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 109,912 raising about 1,122,432 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Rukwa region was ranked eighth out of the 21 Mainland regions. The District with largest number of chickens was Mpanda (492,601 chickens, 43.9% of the total number of chickens in the region) followed by Sumbawanga Rural (445,939 39.7%) and Nkasi (130,643, 11.6%). Sumbawanga Urban district had the smallest number of chickens (53,250, 4.7%) (Chart 3.133 and Map 3.55). However Sumbawanga Urban district had the highest density (90 chicken per km2 ) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 2.24 percent. The population decreased at a rate of - 2.15 percent from 1995 to 1999 after which it increased at a rate of 6.83 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Rukwa region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 86.5 percent of all chicken- rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 13.3 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 32chickens per holder. Only 0.22 percent of holders kept the flock sizes of 100 chickens or more at an average of 150 chickens per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 38,452 35.0 92,665 2 5-9 31,281 28.5 204,580 7 10 -19 25,278 23.0 321,753 13 20-29 6,961 6.3 155,776 22 30-39 4,248 3.9 136,546 32 40-49 2,087 1.9 87,172 42 50-99 1,365 1.2 87,994 64 100+ 240 0.2 35,946 150 Total 109,912 100 1,122,432 10 428,055 392,442 511,221 - 300,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 N u m b er o f C h ick en s Mpanda Sumbawanga Rur Nkasi Sumbawanga Urb District Chart 3.133 Total Number of Chickens by District Sumbawanga Rural Sumbawanga Urban 2 0.7 2.1 0.8 Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 10,756 13,967 397 10,953 Mpanda Nkasi 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Sheep Sheep Population by District as of 1st Octobers 2003 MAP 3.46 RUKWA MAP 3.47 RUKWA Sheep Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Sheep Population Number of Sheep of per Square Km Sheep Density 1.9 to 2.1 1.6 to 1.9 1.3 to 1.6 1 to 1.3 0.7 to 1 RESULT 78 Sumbawanga Urban Sumbawanga Rural 3.6 6.8 1.6 0.3 Mpanda Nkasi 5.2 to 6.8 3.9 to 5.2 2.6 to 3.9 1.3 to 2.6 0 to 1.3 Sumbawanga Urban Sumbawanga Rural 2,152 36,455 8,396 4,837 Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Pig Pig Population by District as of 1st Octobers 2003 MAP 3.48 RUKWA MAP 3.49 RUKWA Pig Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Pig Population Number of Pig of per Square Km Pig Density RESULT 79 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Rukwa Region increased at an annual rate of 72.35 percent for the period of four years from 823 in 1999 to 7,261 in 2003. The number of improved chicken was most significant in Nkasi district followed by Sumbawanga Rural and Sumbawanga Urban districts (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 33.38 percent during which the population grew from 725 to 7,261. The annual growth rate was (72.35%) for the period of four years from 1995 to 1999. The broiler population exhibited an increasing trend at the rate of 63.59 percent per annum for the period of four years from 1995 to 1999 before decreasing at an annual rate of -50.67 from 1999 to 2003. The overall annual growth rate for broilers was -10.17 during the eight-years period from 1,450 chicken in 1995 to 615 chicken in 2003 (Chart 3.136). 3.12.6. Other Livestock There were 88,647 ducks, 2,686 turkeys, 17,876 rabbits and 11,190 donkeys raised by rural agricultural households in Rukwa region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Sumbawanga Rural district (45.5% of all ducks in the region), followed by Mpanda (43.3%) and Nkansi (10.5%). Sumbawanga Urban district had the least number of ducks estimated at 0.7 percent of total ducks in the region. Turkeys were reported in Sumbawanga Rural and Sumbawanga Urban districts only (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 64 percent and 11 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. (Chart 3.137) shows that there was a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Mpanda district but lowest in Sumbawanga Rural district (Map 3.57). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Mpanda 38,381 0 5,650 4,265 0 Sumbawanga Rural 40,326 2,516 5,263 3,578 7,644 Nkasi 9,294 0 3,561 2,629 9,765 Sumbawanga Urban 646 170 3,402 718 0 Total 88,647 2,686 17,,876 11,190 17,409 725 1,450 823 10,385 7,261 615 - 4,000 8,000 12,000 N um ber o f la y ers 1995 1999 2003 Year Chart 3.136 Improved Chicken Population Trend 0 0 2,414 213 1,144 402 3,703 0 0 1,200 2,400 3,600 N u m b er o f C h ick en s Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 15 30 45 60 75 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Percent T icks T setseflies Sumbawanga Urban Sumbawanga Rural 89.7 83.2 25.7 27.9 Mpanda Nkasi Sumbawanga Urban Sumbawanga Rural 53,250 492,601 130,643 445,939 Mpanda Nkasi 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Number of Chicken Chicken Population by District as of 1st Octobers 2003 MAP 3.50 RUKWA MAP 3.50 RUKWA Chicken Density by District as of 1st October 2003 Tanzania Agriculture Sample Census Chicken Population Number of Chicken of per Square Km Chicken Density 70 to 90 60 to 70 40 to 60 20 to 40 0 to 20 RESULT 81 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 The most practiced method of tick controlling was spraying with 35 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (4%), smearing (2%) and other traditional methods like hand picking (10%). However, 49 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 11 percent of livestock- rearing households This was followed by dipping (6%) and trapping (2%). However, 81 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 48,587 (57% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 38 percent, goats (32%), sheep (17%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 17,928, representing 30.8 percent of the total livestock-rearing households and 10.4 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 93.9 percent of all households receiving livestock extension services. The rest of the households got services from large-scale farmers (3.58%), Co- operatives and others provided (1%) each and NGO/developing Projects had (0.3). 0 20 40 60 P ercen t Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Average 23% Poor 4% No Good 3% Very Good 4% Good 66% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 6,000 12,000 Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District N u m b e r o f H o u se h o ld s Less than 14km More than 14km Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 34,807, 73% Less than 14km, 12,808, 27% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 83 About 66 percent of livestock rearing households described the general quality of livestock extension services as being good, 23 percent said they were average and 4 percent said they were very good and also 4 percent of livestock rearing households said the service was poor. Moreover, 3 percent of the livestock rearing households said the quality was not good (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 73.1 percent of the livestock rearing households accessed the services, at a distance of more than 14 kilometers. Only 26.9 percent of them accessed the services within 14 kilometers from their dwellings (Chart 3.140). The most affected district was Sumbawanga Rural with almost all livestock rearing households (89%) accessing the services at a distance of more than 14 kms. Sumbawanga Urban district was the least affected because about 36 percent of the households could access the service at a distance of more than 14 kilometers. (Chart 3.141). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 7,525 (78.8% of livestock rearing households in Rukwa region) whilst 443 households (4.6%) resided between 5 and 14 kms. However, 1,587 households (16.6%) had to travel a distance of 15 or more kms to f the nearest watering point (Chart 3.142). Mpanda and Nkansi districts had the best livestock water supply with all of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Sumbawanga Rural then Sumbawanga Urban districts. In Sumbawanga rural district about 38 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 6,000 12,000 Sumbawanga Rur Mpanda Nkasi Sumbawanga Urb District N u m b e r o f H o u se h o ld s Less than 14km More than 14km Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 34,807, 73% Less than 14km, 12,808, 27% Chart 3.142 Number of Households by Distance to Village W atering Points 15 or more kms, 1587, 16.6% 5-14 kms, 444, 4.6% Less than 5 kms, 7,525, 78.8% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 1,500 3,000 4,500 Mpanda Sumbawanga Rural Sumbawanga Urban Nkasi District Number of H ouseholds Less than 5 kms 5-14 kms 15 or more kms DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Rukwa region was relatively important with 79,406 households (46% of the total households in the region) using them (Chart 3.144). The number of households that used draft animals in Sumbawanga Rural was 47,115 representing 59 percent of the households using draft animals in the region, this was followed by Nkasi (16,622 households, 21%), Sumbawanga Urban (11,547 households, 15%) and Mpanda (4,121 households, 5%) (Chart 3.145 and Map 3.58). Proportionally, the district whose households used more draft animals was Sumbawanga Urban by (87%) followed by Sumbawanga Rural 68%) and Nkansi (55%). Mpanda district made the least use of draft animals (7%) of households only. The region used 247,856 oxen that cultivated 178,167 hectares. This represents only 5.9 percent of the total number of oxen found on the Mainland. Out of this (140, 521 oxen) were used in sumbawanga rural, Nkasi (55,435 oxen), Sumbawanga Urban (29,683 oxen) and Mpanda (22,217 oxen) The largest area cultivated using oxen was found in Sumbawanga Rural district (259,293 ha, 58.9% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of households using organic fertilizers in Rukwa region was 18,756 (11% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 30,877 hectares or (73.9% of the total area applied with fertilisers or (10.2 %) of the area planted with annual crops and vegetables in Rukwa region during the wet season) was applied with farm yard manure (Map 3.59). 0 16,000 32,000 48,000 N um ber o f H o useho lds Sumbawanga Rural Nkansi Sumbawanga Urban Mpanda District Chart 3.145 Number of Households Using Draft Animals by District - RUKWA 3.144 Number of Households Using Draft Amimals Using Draft Animals, 79,406, 46% Not Using Draft Animals, 92,855, 54% Chart 3.146 Number of Households Using O rganic Fertilisers Not Using Organic fertilisers, 158,442, 92% Using Organic fertilisers, 13819, 8% Chart 3.147 Area planted with the Application of Fertilisers - RUKWA 0 7,000 14,000 Sumbawanga Rural Sumbawanga Urban Nkasi Mpanda District A rea (H a ) o f F ertiliser A pplica tio n Farm Yard Manure Compost Sumbawanga Urban Sumbawanga Rural 11,547 47,115 4,121 16,622 86.8% 68.3% 54.5% 6.9% Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Sumbawanga Urban Sumbawanga Rural Nkasi 4,663 21,579 6,637 4,616 82.9% 62.5% 72.8% 41.1% Mpanda 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Household Infected with Ticks Number and Percent of Households Infected with Ticks by District MAP 3.52 RUKWA MAP 3.53 RUKWA Number and Percent of Households Using Draft Animals by District Tanzania Agriculture Sample Census Number of Household Infected with Ticks Percent of Household Infected with Ticks Percent of Households Using Draft Animal Number of Households Using Animal Draft Number of Households Using Animal Draft RESULT 85 Sumbawanga Urban Sumbawanga Rural 762 308 475 1,974 0.8% 0.6% 2.4% 1.5% Mpanda Nkasi 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Sumbawanga Urban Sumbawanga Rural 12,857 6,028 2,746 9.7% 25.4% 11.3% 2.9% Mpanda Nkasi 5,110 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Planted Area with Farm Yard Manure Applied Planted Area and Percent of Planted Area With Farm Yard Manure Application by District MAP 3.54 RUKWA MAP 3.55 RUKWA Planted Area and Percent of Planted Area With Compost Manure Application by District Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure Applied Percent of Planted Area with Farm Yard Manure Applied Percent of Planted Area with Compost Manure Applied Planted Area with Compost Manure Applied Planted Area with Compost Manure Applied RESULT 86 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 87 3.12.9.4 Use of Compost Only 1,721 hectares (5.4% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost manure was found in Sumbawanga Rural district with 16,082 hectares (67% of the total area applied with compost manure) followed by Sumbawanga urban (3,941 ha, 17%), Nkasi (313 ha, 12%) and Mpanda (109 ha, 4%) (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Rukwa region was 80, representing 0.05 percent of the total agricultural households in the region (Chart 3.148 and Map 3.61). Fish farming was practiced in Nkasi district only. No fish farming was practiced in any other district of Rukwa region. (Chart 3.149). The main source of fingerings was from the neighbours. All fish farming households in the region used the natural ponds. The number of fish harvested in Rukwa region was 8,018 all of them being tilapia by type. Eighty (80) fish were sold to traders at farm. Chart 3.148 Number of Households Practicing Fish Farming - RUKWA Households Not Practicing Fish Farmining, 172181, 99.9% Households Practicing Fish Farmining, 80, 0.05% 0 25 50 75 100 N umber of Households Nkasi Mpanda Sumbawanga Rural Sumbawanga Urban District Chart 3.149 Number of Households Practicing Fish Farming by District - RUKW A Chart 3.150 Fish Production Number of T ilapia, 8,018, 100% Number of Carp, 0, 0% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, tarmac roads were a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 185.2 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were regional capital (155.5 km), hospitals (71.6 km), tertiary markets (65.5 km), secondary schools (25.1 km), secondary market (22.4 km), primary markets (16.3 km), health clinics (8 km), all weather roads (5 km), primary school (2.1) and feeder road (1.1) (Table 3.15). Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Mpanda 27.7 2.9 4.3 1.1 74.4 7.0 283.7 23.3 27.3 70.2 303.4 Sumbawanga Rural 20.9 1.7 5.6 0.9 90.3 9.7 92.4 8.4 19.1 81.4 129.1 Nkasi 36.9 1.9 6.7 1.5 48.6 6.8 109.2 22.6 24.6 42.9 145.8 Sumbawanga Urban 8.2 1.1 1.0 1.1 15.1 5.7 15.4 10.9 12.2 14.3 37.0 Total 25.1 2.1 5.0 1.1 71.6 8.0 155.5 16.3 22.4 65.5 185.2 Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 29 percent reported them to be average. Twenty four percent of the agricultural households said the infrastructure and services were poor were , and 20 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households used traditional pit latrines (159,267 households, 92.5% of all rural agricultural households). Other types of toilets were used as follows: flush toilets (4,395 households (2.6%), improved pit latrines (1,376 households, 0.8%) and other toilets facilities (34 households, 0.02%). However, 7,189 households or (4.2%) had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicated that 67.6 percent of them were found in Sumbawanga Rural district and 20.5 percent were from Mpanda. The percentages of households without toilets in other districts were as follows Nkasi (6.7%) and Sumbawanga Urban (5.2%) Map 3.62). Chart 3.152 Percentage Distribution of Households Owning the Assets 3.0 0.6 0.5 0.5 0.2 13.7 37.5 41.8 0.0 15.0 30.0 45.0 Radio Bicycle Iron Wheelbarrow Vehicle Television / Video Mobile phone Landline phone Assets P ercent Chart 3.151 Agricultural Households by Type of Toilet Facility No Toilet / Bush, 7,189, 4.2% Improved Pit Latrine - hh Owned, 1,376, 0.8% Other Type, 34, 0.02% Flush Toilet, 4,395, 2.6% Traditional Pit Latrine, 159,267, 92.5% Sumbawanga Urban Sumbawanga Rural 480 1,477 371 4,861 1.6% 2.5% 7.1% 2.8% Mpanda Nkasi 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Sumbawanga Rural Sumbawanga Urban 80 0 0 0 0.3% 0% 0% 0% Mpanda Nkasi 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Households Practicing Fish Farming Number and Percent of Households Practicing Fish Farming by District MAP 3.56 RUKWA MAP 3.57 RUKWA Number and Percent of Households Without Toilets by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming Percent of Households Without Toilets Number of Households Without Toilets Number of Households Without Toilets RESULT 89 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Rukwa region with 72,043 households (41.8% of the agriculture households in the region) owning the asset this was followed by bicycle ( 64,577 households, 37.5%), iron (23,642 households, 13.7%), wheelbarrows (5,199 households, 3.0%), vehicles (1,070 households, 0.6%), television/video (849 households, 0.5%), mobile phones (784 households, 0.5%) and landline phones (267 households, 0.2%) (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 76.6 percent of the total rural households using this source of energy followed by hurricane lamp (16.9%), pressure lamp (3.4%), firewood (2.6%), mains electricity (0.3%), candle (0.1%) and others (0.1%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.8 percent of all rural agricultural households in Rukwa region. This was followed by charcoal (3.0%), crop residues (0.2%) and livestock dung (0.02%) (Chart 3.154). 3.13.6 Roofing Materials The most common material for roofing for the main dwelling was grass and/or leaves which used by 75.4 percent of the rural agricultural households. This was far followed by iron sheets (18.6%), grass/mud (4.0%), asbestos (1.3%), tiles (0.6%) and concrete (0.1%) (Chart 3.155). Proportionally, Mpanda and Nkasi districts had the highest percentage of households with grass/leaves roofing (80.5%) each followed by Sumbawanga Rural district (71.6%). Sumbawanga Urban district had the lowest percentage (60.7%) of households with grass/leaves as rooting material (23%) (Chart 3.156 and Map 3.63) Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Grass/Mud 4% Grass/Leaves 75% Tiles 1% Concrete 0% Asbestos 1% Iron Sheets 19% Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 38.0 36.9 18.9 6.2 0.0 18.0 36.0 Sumbawanga Rural Mpanda Nkasi Sumbawanga Urban D is t ric t Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 131,944, 76.6% Firewood, 4,542, 2.6% Mains Electricity, 440, 0.3% Candles, 187, 0.1% Other, 154, 0.1% Pressure Lamp, 5,922, 3.4% Hurricane Lamp, 29,072, 16.9% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Charcoal, 5,185, 3.0% Crop Residues, 385, 0.2% Livestock Dung, 35, 0.02% Firewood, 166,657, 96.8% Sumbawanga Urban Sumbawanga Rural 3,684 11,368 468 4,052 5.9% 3.5% 12.1% 19.1% Mpanda Nkasi 8,000 to 12,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Sumbawanga Urban Sumbawanga Rural 24,538 47,907 8,078 49,355 80.5% 80.5% 71.6% 60.7% Mpanda Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Using Grass or Leaves for Roofing Material Number and Percent of Households Using Grass/Leaves for Roofing Material by District MAP 3.58 RUKWA MAP 3.59 RUKWA Number and Percent of Households Eating 3 Meals per Day by District Tanzania Agriculture Sample Census Number of Households Using Grass or Leaves for Roofing Material Percent of Households Using Grass or Leaves for Roofing Material Percent of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day RESULT 91 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Rukwa region was protected wells which were used by 25 percent of the households during both the wet and dry seasons. This was followed by unprotected wells (24% of households during wet season and 26 percent during dry season), surface water (20% of households during the wet season) and 15% in the dry season), piped water (17% of households in the wet season and 15% during dry season) and unprotected spring water (10% of households in both the wet and dry seasons, protected/covered spring (2.4% of households in wet season and 2.5% of households in dry season. The remaining sources had below 1 percent of households in both wet and dry seasons respectively. Chart 3.157) About 55 percent of the rural agricultural households in Rukwa region obtained drinking water within a distance of less than one kilometer during wet season compared to 46 percent of the households during the dry season. However, 45 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 54 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Rukwa region normally had two (2) meals per day (81.8 percent of the households in the region). This was followed by three (3) meals per day (11.4%) and one (1) meal per day (6.7 percent). Only 0.05 percent of the households had (4) meals per day (Chart 3.159). Chart 3.158 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Distance P ercent Wet Seas o n Dry Seas o n Chart 3.159 Number of Agriculural Households by Number of Meals per Day One Meal, 11,622, 7% T hree Meals, 19,573, 11% Four meals, 82, 0.05% T wo Meals, 140,983, 82% Chart 3.157 Percent of Households by Main Source of Drinking Water and Season 0 10 20 30 P rotected Well Uprotected Well Surface Water (Lake / Dam / River / Stream) P iped WaterUnprotected Spring P rotected / Covered Spring Uncovered Rainwater Catchment Covered Rainwater Catchment Tanker Truck Other M a in s o urc e We t S e a s o n D ry S e a s o n DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 Sumbawanga Urban district had the largest percent of households eating one meal per day whilst Mpanda district had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.64) 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 93,105 (54.0% of the agricultural households in Rukwa region) out of which 49,584 households (53.3 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week 27,198 (29.2%). Very few households (16,323 households, 12.5%) had meat three or more times during the respective week. However, 79,156 (46.0 percent of the agricultural households in Rukwa region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 122,835 (71.3% of the total agricultural households in Rukwa region) of which 30,971 households (25.2% of those who consumed fish twice during the respective week. This was followed by those who had fish three times 17,793 (14.5%). In general, the percentage of households that consumed fish twice or more during the week in Rukwa region was 85,452 (69.6% of the agricultural households that ate fish in the region during the respective period). Moreover, 49,425 (28.7%) of the agricultural households in Rukwa region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66). 3.13.9 Food Security In Rukwa region, 55,848 households (32.4% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 11,957 (6.9%) said they sometimes experience problems, 13,212 (7.7%) often experienced problems and 8,509 (4.9%) always had problems in satisfying the household food requirement. However, 82,734 (48%) agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main source of cash income for the households in Rukwa region was from selling food crops (48.9 percent of smallholder households), followed by businesses income (16.0%), other casual cash earnings (14.2%), fishing (5.4%), sales of forest products (4.6%) and selling of cash crops (4.2%). Only (2.5%) of smallholder households reported the cash remittances as their main source of income, this was then followed by wages and salaries in cash (2.3%), sales of livestock (1.1%), other sales (0.5%) and sales of livestock products (0.2%) (Chart 3.161). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Mpanda 2,412 4.1 45,753 76.9 11,368 19.1 0 0 59,533 Sumbawanga Rural 5,766 8.4 59,117 85.8 4,052 5.9 0 0 68,935 Nkasi 950 3.1 25,767 84.5 3,684 12.1 82 0.3 30,483 Sumbawanga Urban 2,495 18.7 10,346 77.7 468 3.5 0 0.0 13,309 Total 11,622 6.7 140,983 81.8 19,573 11.4 82 0.05 172,261 Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 15,000 30,000 45,000 60,000 Once T wice T hree T imes Four T imes Five T imes Six T imes Seven T imes Frequency Number of Households Meat Fish Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Other 0% Livestock 1% Livestock Products 0% Cash Remittance 3% Forest Products 5% Cash Crops 4% Wages & Salaries 2% not applicable 0% Food Crops 50% Fishing 5% Other Casual Cash Earnings 14% Business Income 16% Sumbawanga Urban Sumbawanga Rural 13,023 3,645 13,719 6,996 21.9% 27.4% 19.9% 23% Mpanda Nkasi 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Sumbawanga Urban Sumbawanga Rural 4,117 7,828 19,522 18,118 5.9% 3.5% 12.1% 19.1% Mpanda Nkasi 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Number of Households Eating Meat Once per Week Number and Percent of Households Eating Meat Once per Week by District MAP 3.60 RUKWA MAP 3.61 RUKWA Number and Percent of Households Eating Fish Once per Week by District Tanzania Agriculture Sample Census Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week RESULT 94 Mpanda Sumbawanga Urban Sumbawanga Rural 7,821 32,599 14,873 31,883 48.2% 56.6% 55.6% 53.5% Nkasi 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Reporting Food Insufficiency Number and Percent of Households Reporting Food Insufficiency by District MAP 3.62 RUKWA Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency RESULT 95 DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 RUKWA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Rukwa Rukwa has over 340,000 hectares of land under crops and is dominated by annual cropping. It has one a moderate to high available land area per crop growing household and the smallest percent utilized. Of the 3.0 ha per crop growing household land available only 2 ha was utilized. The number of crop growing households is moderate to low. The region has no short rainy season. Rukwa has a moderate planted area of cereals the majority of which is maize, however it is the fifth most important region in terms of the quantity produced. Beans and groundnuts are planted in moderate amounts and the region is the fourth most important in terms of quantity produced. Paddy is produced in moderate to small amounts compared to other regions and a small amount of sorghum is also produced. Cassava is produced in moderate to low amounts. Rukwa is not important for vegetable production; however a small amount of tobacco is grown. Rukwa has the smallest percentage of the total planted area of permanent crops in the country. The area under irrigation in Rukwa is moderate to low compared to other regions and the number of households with irrigation has not changed for 10 years. For the small number of households with irrigation, the source of irrigation water is mostly from rivers, the method of obtaining water is largely by gravity and application of the irrigation water is mostly by flood. More than half of the land cultivation is done by oxen and the region is one of the few regions using non manual cultivation methods. Fertilizer application is almost non existent and little pesticides are used. Rukwa stores a relatively large amount of maize mostly in sacks/open drums. A high percent of households in the region sells crops. Most processing is by neighbours machine and it also has one of the highest percentages of processing done by traders. Few households sell their processed crops, mostly to neighbours. Rukwa receives the second least amount of extension services per household. The region has a small number of planted trees by smallholder households, and most of these are eucalyptus. It has a moderate number of households with erosion control/water harvesting facilities and most of them are for erosion control. 4.2.1 Mpanda Mpanda district has a comparative large number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has no livestock only households or pastoralists. The most important livelihood activity for smallholder households in Mpanda district is Annual Crop Farming, followed by tree/forest resources, off-farm income, livestock keeping, Permanent crops, remittances and fishing/hunting and gathering. However, the district has the lowest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mpanda has a relatively high percent of female headed households (49%) and it has the highest average ages of the household head. With an average household size of 6 members per household it is slightly above the average for the region. Mpanda has a DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 comparatively low literacy rate among smallholder households and this is reflected by the concomitant relatively low level of school attendance in the region. The literacy rates for the heads of household is also slightly lower than most of districts in the region. It has the smallest utilized land area per household (2.0 ha) and the allocated area is not fully utilized indicating that there is -low level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (1.5ha) attributed to the high number of smallholders in the district. The district is moderately important for maize production in the region with a planted area of over 43,000 ha, however the planted area per household is the lowest in the region. Paddy production is not important as it was not grown in the district and the production of sorghum is very small. Mpanda is the only district in the region which did not grow wheat. Cassava production though small but it is higher accounting for 39 percent of the quantity harvested in the region. Mpanda is the only district in the region that did not grow Irish potatoes. The production of beans in Mpanda is the second highest in the region with a planted area of 10,255 ha. Oilseed crops are important in Mpanda and groundnuts were grown in the district. Vegetable production is important in the district. It has the second largest planted area with tomatoes but lowest in cabbage production, chilies were not grown in the district, it accounts for 27 percent of the tomato production, 8 percent of the cabbage production. Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. Compared to other districts in the region, Mpanda has a moderate planted area with permanent crops which is dominated by Lime/lemon (3,866 ha), banana (694 ha) and mangoes (392 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is very small, however district differences exist. Mpanda has the second largest planted area with improved seed in Rukwa region and this is due to the higher planted area of vegetables. The district has moderate to low planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is inorganic manure. Compared to other districts in the region, Mpanda district has a lowest level of insecticide use. The use of fungicides, although small, was the highest compared to other districts. Virtually no herbicide was used. It has the smallest area with irrigation compared to other districts with 1,138 hectares of irrigated land. The most common source of water for irrigation is from rivers using hand buckets. Bucket and flood and are the most common means of irrigation water application and a very small amount of water hose irrigation is used. No sprinkler used for irrigation. The most common method of crop storage is in sacks/open drums; however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the largest number of households not selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The lowest percent of households processing crops in Rukwa region is found in Mpanda district and is almost all done by using by neighbours Machines. The district also has a higher percent of households selling processed crops to neighbours than other districts and no sales are neither to market co-operatives, farmer’s associations nor large scale farms. Although very small, access DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 98 to credit in the district is to both men and women and the main sources are co-operatives, traders/trade stores, and family friends and relatives. A comparatively larger number of households receive extension services in Mpanda and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Mpanda district by having planted 2,251 trees only and is mostly senna spp with some eucalyptus and gravellis. The highest proportion of households with erosion control and water harvesting structures is found in Mpanda district and is mostly erosion control bunds however it also has the highest number of water harvesting bunds than other districts. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat production is the highest when compared to other districts; also, it has the largest population of sheep in the region. It has the second smallest number of pigs in the region but highest number of chickens. Mpanda is the only district in the region which did not have layers. Big number of ducks but small number of rabbits and donkeys both are found in the district. The largest number of households reporting Tsetse and tick problems was in Mpanda district and it had the largest number of households de-worming livestock. The use of draft animals in the district is very small. There was no any household in the district who did practice fish farming. It has amongst the worst access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to all weather roads and regional capital. Mpanda district has the second lowest percent of households with no toilet facilities and it has the highest percent of households owning bicycles, vehicles and tv/video and mobile phones. It has the second lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the largest percent of households with grass roofs with 16.4 percent of households having iron sheets. The most common source of drinking water is from protected wells. It has the lowest percent of households having two and second lowest district with households having one meal per day compared to other districts and the highest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat but highest number of households that did not eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.2 Sumbawanga Rural Sumbawanga Rural district has the largest number of households in the region and it has a high percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very large number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Sumbawanga Rural district is Annual Crop Farming, followed by tree/forest resources. The district has the fourth highest percent of households with no off-farm activities although it has the fourth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sumbawanga Rural has a relatively high percent of female headed households (23%) and it has DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 99 one of the lowest average age of the household head in the region. With a household size of 5 members per household it is average for the region. Sumbawanga Rural has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. It has a highest utilized land area per household (2.7 ha) and 79.1 percent of the allocated area is currently being utilized. The district has the largest planted area in the region and the largest planted area per household (0.8ha in the wet season. The district is very important for maize production in the region with a planted area of over 65,900 ha, and the planted area per maize growing household is also moderate for the region. The district has the second largest planted area of paddy in the region with 11,605 hectares. Sorghum is also grown in the district. Cassava production is moderate to high, accounting for 25.2 percent of the quantity harvested in the region. The district has a very small planted area of Irish potatoes (49 ha). The production of beans in Sumbawanga Rural district is higher with a planted area of 17,142 ha. Sumbawanga Rural district has the second largest groundnut planted area in Rukwa region with a planted area per groundnut growing household of 0.27 ha. Vegetable production is moderately important in the district. Although small, it has the largest planted area with tomatoes and cabbage and chilies (245 ha and 60 ha respectively). A traditional cash crop (e.g. tobacco) was grown in very small quantities. No cultivation of cotton in the district Compared to other districts in the region, Sumbawanga Rural has the largest planted area with permanent crops which is dominated by sugarcane (1,356 ha), banana (758 ha) and Mango (155 ha). As with other districts in the region, most land clearing is done by hand slashing; however there is a substantial area with no land clearing indicating bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Sumbawanga Rural has the largest planted area with improved seed in the region as well as the highest proportion of households using improved seeds. Though small, the district has the second highest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts in the region, Sumbawanga Rural district has a moderate level of insecticide use. The use of fungicides and herbicides is low. It has the largest area with irrigation compared to other districts with 9,983 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity methods. Flood is the most common means of irrigation water application followed by bucket/watering can and a very small amount of water hose is used. The most common method of crop storage in Sumbawanga Rural district is in sacks/open drums, however the proportion of households not storing crops is slightly above for the region. Sumbawanga Rural has the highest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Sumbawanga Rural is among the districts with the lowest percent of households processing crops in Rukwa region and is almost all done by neighbours machine. The district also has the second highest percent of households selling processed crops to neighbours as well as to traders at farm than other districts and no sales is to marketing co-operatives or large scale farms. Access to credit in the district though small but it was second in the region. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 100 A comparatively larger number of households receive extension services in Sumbawanga Rural district and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is relative important in Sumbawanga Rural (with 3,551 planted trees) and is mostly Eucalyptus, jacaranda and senna spp. The highest proportion of households with erosion control and water harvesting structures is found in Sumbawanga Rural district and is mostly erosion control bunds and water harvesting bunds, however it also has the a number of drainage ditches, tree belts dams terraces and vetiver grasses. The district has the largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts; however it has the second largest population of sheep in the region. It has the largest number of pigs in the region and a moderate number of chickens. Some ducks, rabbits and donkeys are also found in the district. A number of households reported tsetse and tick problems and it has the second largest number of households de-worming livestock. A small number of households use draft animals, however it is the highest in the region. No any households in the district who did practice fish farming. It has amongst the best access to feeder roads, primary schools, all weather roads, primary markets and health clinics compared to other districts. However, it has one of the worst accesses to tarmac roads. The percentage of households without toilet facility in Sumbawanga Rural district is comparatively low. It is amongst the districts with the highest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is grass/leaves (72%), however it has the second highest percent of households with iron sheet roofing (19%) compared to most other districts. The most common source of drinking water is from unprotected springs. It is one of the districts with the moderate percent of households having three meals per day. The district had one of the lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Nkasi Nkasi district has the third largest number of households in the region and it has moderate to higher percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It one of the districts with very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Njkasi district is Annual Crop Farming, followed by tree/forest resources, off-farm income, livestock keeping, fishing/hunting/gathering, remittances and permanent crops. However, the district has the highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Nkasi a relatively high percent of female headed households (13%) and it has one of the highest averages of the household head in the region. With an average household size of 5 members per household it is the average for the region. Nkasi has a comparatively DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 101 high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The land area utilized per household (2.4 ha) is above the average for the region which is estimated at 2.0 hectares.75 percent of the allocated area is currently being utilized which is moderate to high for the region. Sumbawanga Rural and Nkasi utilizing 2.7 and 2.5 ha per household respectively. The smallest land area utilised per household was found in Mpanda and Sumbawanga Urban with (2.0 ha) each. The percentage utilized of the usable land per household was highest in Sumbawanga Urban (86.2%) and lowest in Mpanda (63.2%). Seventy three percent of the total land available to smallholders was utilised. Only 27 percent of usable land available to smallholders was not The district is moderately important for maize production in the region with a planted area of over 28,000 ha and the planted area per household is 1.03 ha which is slightly above of average for the region. Paddy production is not important with a planted area of only 1,416 hectares; however it is the third highest in the region. Sorghum, Irish potatoes and wheat are all produced in the district. The district has the second largest planted area of cassava accounting for 27 percent of the cassava planted area in the region. The production of beans in Nkasi is second lower in the region with a planted area of 6,810ha. Oilseed crops are relative important in Nkasi with 8.1 percent of the groundnuts grown in the district. Vegetable production is not important and tobacco was grown in the district. Permanent crops are very important in Nkasi district (24.6% of the total permanent crop planted area in Rukwa region ) and are more important than any other district in the region. The most prominent permanent crops in the district include mangoes (2,020 ha), sugarcane (74 ha), bananas (66 ha) and coconuts (16 ha). It has one of the lowest area with oranges in the region (4 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is very small, however district differences exist. Muheza has the smallest planted area with improved seed in Rukwa region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and practically all is with farm yard manure. Compared to other districts in the region, Muheza district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively small. It has one the smallest area with irrigation in the region with 1,146 ha of irrigated land. The most common source of water for irrigation is from rivers and wells and almost all water application is by using flood and hand buckets. The most common method of crop storage is in Nkasi is by using sacks or open drums and locally made traditional cribs, and the proportion of households not storing crops in the district is moderate to low for the region. The district has the third highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Nkasi district has a high percent of households processing crops in the region and is almost all done by neighbour machines; however, there was no any household in the district who did process crops by trader. Small quantities of processed crops are sold and very few households have access to credit. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 102 A moderate number of households receive extension services in Nkasi district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Nkasi district (with 3,148 planted trees) and is mostly Eucalyptus spp with some Senna Spp and Jacaranda Spp. The lowest proportion of households with water harvesting bunds is found in Nkasi district and it also has the third highest number of erosion control bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the second largest number of pigs in the region and the second lowest number of chickens, all of which are indigenous. Virtually no broilers chicken was found in the district. The district has one of the smallest number of ducks, and a small number of rabbits and turkeys are found in the district. A moderate number of households reported tsetse and problems in Nkasi district. A relative small amount of de-worming of livestock is practiced in the district. Draft animals are used in the district. Fish farming is practiced by a small number of households; however it is the only district which did practice fish farming in the region. It has amongst the best access to feeder roads, all weather roads, and health clinics compared to other districts. However, it has one of the worst accesses to tarmac roads and the regional capital. The percentage of households without toilet facility in Nkasi district is below the average for the region; however it has the lowest percent of households with no toilet facilities. It has the lowest percent of households owning vehicles and second highest owing tvs/video but NO land line phones. It has the second highest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has one of the highest percent of households with grass roofs (81%) and only 16 percent of households have iron sheet roofing. The most common source of drinking water is from unprotected wells. Forty four percent of the households in the district reported having one or two meals per day and virtually 82 household reported having more than three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Sumbawanga Urban Sumbawanga Urban district has an average number of households for the region and it has the smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Sumbawanga Urban district is annual crop farming followed by trees/forest resources. It has the second highest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sumbawanga Urban district has a relatively high percent of female headed households (13%) and it has one of the highest average ages of the household head. With an average household size of 5.4 members per household it is average for the region. Sumbawanga Urban district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 103 It has the second smallest utilized land area per household (2.0 ha) and only 86.2 percent of the allocated land area is utilized. The total planted area is the smallest in the region however it has the second lowest planted area per household (0.61ha in the wet season. Sumbawanga Urban district is not important for maize production in the region with a planted area of only 12,341 ha, and the planted area per household is among the lowest in the region. Paddy production is also not important as there was no any cultivation of paddy in the district hectares and the production of sorghum is small. Cassava and bean production in Rukwa district was small and Irish potato and wheat are also grown. Oilseed crops and vegetables are not important in the district however, whist the district has one of the smallest planted area with tomatoes it is the first in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Sumbawanga Urban district has the smallest planted area with permanent crops (5.7% of total permanent crop planted area) which is dominated by sugarcane (346 ha), banana (272ha), A small area of orange and coconut are grown. Apart from a minor amount of coffee, lime/lemon and guavas no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. The use of inputs in the region is very small, however district differences exist. Sumbawanga Urban district has the smallest planted area with improved seed; however it has the lowest planted area per household in the region. The district also has the second smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), and most of this is with farm yard manure. Compared to other districts in the region, Sumbawanga Urban district has the second highest area planted with insecticide but has the lowest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the lowest for herbicides. It has one of the largest areas of irrigation 2,830 ha. The most common source of water for irrigation is from rivers using gravity. Floods and watering cans are the most common means of irrigation water application. The most common method of crop storage is in sacks/open drums; however the proportion of households not storing crops in Sumbawanga Urban district is one of the highest in the region. The number of households selling crops in the district is also among the biggest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The second biggest percent of households processing crops in the region is found in Sumbawanga Urban district and processing is mostly done by neighbours machine. The district has the smallest number of households processing crops on farm by machine. It also has the lowest number of households processing crops on farm by hand. Most households that sell crops sell to farmers association, traders on farm and large scale farms, but, no sales on local market/trade stores, secondary market nor marketing co-operatives. Access to credit in the district is very small. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 104 A very small number of households receive extension services in Sumbawanga Urban district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming though small but it is important in Sumbawanga Urban district (with 34,199 planted trees) and almost all of them are Eucalyptus Spp. The largest proportion of households in Sumbawanga Urban district use terraces for erosion control. Sumbawanga Urban district has the smallest number of cattle in the region and most of them are indigenous. It is one of the districts with the least number of goats in the region, however the district has the highest density (87 head per km2) Rukwa is also one of the districts with the smallest number of sheep, pigs and chicken, however it has the largest number of improved chickens (layers) in the region, broilers are not raised in the district. Small numbers of ducks, rabbits, turkeys and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Sumbawanga Urban district and it had one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and very few households practice fish farming. It is amongst the districts with the best access to secondary schools, primary schools, feeder roads, all weather roads, health clinics, hospitals, regional capital, tarmac roads and tertiary markets compared to other districts. However, it has the worst access to primary and secondary markets. Sumbawanga Urban district has though small number of households with no toilet facilities but it is the second highest in the region. The district has the highest percent of households owning wheel barrows, vehicles and television/video, land line and mobile phones and it has the second highest percent of households with radio, bicycles and irons. It has one of the smallest numbers of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the lowest percent of households with grass roofs with 33 percent of households having iron sheets. The most common source of drinking water is piped water and it has the highest percent of households having one meal per day and third with households having two meals per day compared to other districts and the fourth lowest percent with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration but has the second lowest percent of households that did not eat fish. Most households seldom had problems with food satisfaction. APPENDIX II 105 4. APPENDICES APPENDIX I TABULATION LIST...................................................................................................................106 APPENDIX II TABLES..........................................................................................................................................123 APPENDIX III QUESTIONNAIRES....................................................................................................................267 APPENDIX II 106 NUMBER OF AGRICULTURAL HOUSEHOLDS...............................................................123 2.1 Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year..............................................................................................................124 2.2 Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year.............................................................................................................124 HOUSEHOLDS DEMOGRAPHS............................................................................................125 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year........................................................126 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District.....................................................................................................126 3.2 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year.............................................................................................................127 3.3 Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year.............................................................................................................127 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year .................................................................................................................................128 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year..........128 3.6 Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year.........................................................................128 3.7 Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year.............................................................................................................128 cont…. Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year.............................................................................................................129 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year..........................................................129 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year..........................................................................130 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.............................................131 3.1a First Most Importance .....................................................................................................132 3.1b Second Most Importance.................................................................................................132 3.1c Third Most Importance....................................................................................................132 APPENDIX II 107 3.1d Fourth Most Importance..................................................................................................132 3.1e: Fifth Most Importance.....................................................................................................133 3.1f: Sixth Most Importance ....................................................................................................133 3.1g Seventh Most Importance................................................................................................133 LAND ACCESS/OWNERSHIP................................................................................................135 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year...............................................................................................136 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year .................................................................................................................................136 LAND USE..................................................................................................................................137 5.1 Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year.............................................................................................................138 5.2 Area of Land (ha) by type of Land Use and District for 2002/03 Agricultural Year......138 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.........................................................139 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ...........................................139 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year ...........................................139 ANNUAL CROP AND VEGE PRODUCTION ....................................................................141 7.1 & 7.2a Number of Crop Growing Households and Planted Area (ha) by season and District 142 7.1 & 7.2b Number of Crop Growing Households Planting Crops By Season and District ........142 7.1 & 7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year ......................................................................................................143 7.1 & 7.2d: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year ......................................................................................................144 7.1 & 7.2h Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region...................145 7.1 & 7.2e Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Wet & Dry Seasons- Rukwa Region...............................145 APPENDIX II 108 7.1 & 7.2f Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region.............146 7.1 & 7.2g Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region............146 7.1 $ 7.2j: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year WET SEASON ................................................147 7.1&7.2k: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - WET & DRY SEASONS ........................147 7.1a Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Rukwa Region......................148 7.1b Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - DRY SEASON,Rukwa Region.................................................................148 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, DRY SEASON, Rukwa Region. ........................................................................148 7.1d Number of Crop Growing Households and Planted Area By Pesticide Use and District, DRY SEASON, Rukwa Region. .......................................................................149 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District, DRY SEASON, Ruwa Region ..........................................................................149 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District DRY SEASON, Rukwa Region. .......................................................................150 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, DRY SEASON..................................................................................................150 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, WET SEASON, Rukwa Region..............................................151 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District WET SEASON, Rukwa Region........................................................................151 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During WET SEASON ......................................................................................151 7.2d Number of Crop Growing Households and Planted Area By Insecticide Use and District WET SEASON, Rukwa Region.........................................................................152 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District WET SEASON, Rukwa Region.........................................................................152 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03..............................................................................................................152 APPENDIX II 109 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 WET SEASON, Rukwa Region........................................................................153 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District, WET SEASON, Rukwa Region.......................................................................153 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year154 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year................................................155 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year................................................157 7.2.5 Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year...............................158 7.2.6 Number of Crop Growing Households, Planted Area (ha) and Wheat Harevsted (tons) by season and District 2002/03 Agricultural Year................................................158 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 Agricultural Year................................................158 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year...............................158 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year...............................159 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year................................................159 7.2.13 Number of Crop Growing Households, Planted Area (ha) and Cowpeas Harevsted (tons) by season and District 2002/03 Agricultural Year................................................160 7.2.14 Number of Crop Growing Households, Planted Area (ha) and Green Gram Harevsted (tons) by season and District 2002/03 Agricultural Year...............................160 APPENDIX II 110 7.2.15 Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year...............................160 7.2.16 Number of Crop Growing Households, Planted Area (ha) and Field Peas Harevsted (tons) by season and District 2002/03 Agricultural Year................................................160 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.20 Number of Crop Growing Households, Planted Area (ha) and Soya Beans Harevsted (tons) by season and District 2002/03 Agricultural Year................................................161 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year................................................162 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year................................................163 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year...............................163 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year...............................163 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year................................................163 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year...............................164 PERMANENT CROPS .................................................................................................................165 7.3 Production of Permanent Crops by Crop Type and District, Rukwa Region..................166 APPENDIX II 111 AGROPROCESSING ...................................................................................................................171 8.0a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year..............................................................................172 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District......172 8.1.1 Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop ....................................173 8.1.1a Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop ....................................174 8.1.1 Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop....................175 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop176 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District .............................................................................................................178 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District, Rukwa Region. .................................................178 8.1.1f Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District..........................................................................................179 8.1.1g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District, Rukwa Region....................................................................................179 MARKETING ...........................................................................................................................................181 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03, Rukwa Region.........................................................................182 10.2 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District ......................................182 10.3 Proportion of Households who Reported Not Selling Their Crops by District During 2002/03 Agricultural Year, Rukwa Region.....................................................................182 IRRIGATION/EROSION CONTROL ...................................................................................................183 11.1: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year By District ...........................................................................................184 11.2: Area (ha)of Irrigated and Non Irriga (ha) Land By District............................................184 APPENDIX II 112 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District................................................................184 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District.............................................................................................................184 11.5 Number of Households Using Irrigation By Method of Irrigation Application By District.............................................................................................................................185 11.6: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District..............................................................................................................185 11.7 Number of Erosion Control Harvesting Structures By Type and District.......................185 ACCESS TO FARM INPUTS .................................................................................................................187 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year.............................................................................................................188 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year.............................................................................................................189 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year .................................................................................................................................189 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................189 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year...............................................................................................190 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year...............................................................................................190 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year...............................................................................................190 12.1.10 Number of Agricultural Households and Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year...............................................................................................191 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year.............................................................................................................191 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................191 APPENDIX II 113 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................192 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................192 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year............................................................................193 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year.................................................................................193 12.1.16 Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year............................................................................193 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................194 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................194 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ..............................................................194 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year............................................................................195 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year............................................................................195 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year .................................................................195 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year............................................................................196 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year............................................................................196 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year............................................................................196 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year...............................................................................................197 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year.............................................................................................................197 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year.................................................................................197 APPENDIX II 114 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year...........................................................197 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ..............................................................198 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ..............................................................198 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides /Fungicides by District, 2002/03 Agricultural Year........................................................199 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year............................................................................199 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year.............................................................................................................199 AGRICULTURE CREDITS .....................................................................................................201 13.2a: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District .......................................................................................................................202 13.2c: Number of Households Receiving Credit By Source of Credit By District ....................202 13.1a: Number of Households Receiving Credit By Reason for Not Using Credit By District203 13.1b: Number of Credits Received By Main Purpose of Credit and District ............................203 TREE FARMING AND AGROFORESTRY ..........................................................................205 14.1: Number of Planted Trees By Species and District, Rukwa Region ................................205 14.2 Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District.........................................................................................205 14.3: Main Use of Trees By District.........................................................................................205 14.4: Number of Households By Distance to Community Planted Forest (Km) By District...207 14.5: Number of responses by second use of planted trees and District for the 2002/03.........207 14.6 Number of responses by main use of planted trees and District for the 2002/03 agricultural year, Rukwa Region.....................................................................................207 CROP EXTENSION ..................................................................................................................209 15.1 Number of Households Receiving Extension Messages By District ..............................210 APPENDIX II 115 15.1 Number of Households By Quality of Extension Services By District During the 2002/03 agricultural year, Rukwa Region.......................................................................210 15.3 Number of Households By Source of Crop Extension Messages By District During 2002/03 Agricultural Year, Rukwa Region.....................................................................210 15.4 Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................211 15.5: Number of Households By Receivingf Advice on the Use of Agro-chemicals By Source of Messages By District Rukwa Region..............................................................211 15.6: Number of Households By Receivingf Advice on the Erosion Control By Source of Messages By District Rukwa Region..............................................................................211 15.7: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................212 158: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........212 15.9: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........212 15.9: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Rukwa Region....................213 15.11: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........213 15.12: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Rukwa Region........213 15.13: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Rukwa Region.........................................214 15.14: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .......................214 15.15: Number of Households By Receivingf Advice on Agro-Forestry By Source of Messages By District during 2002/03 agricultural year, Rukwa Region.........................................214 15.16: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .............................................215 15.17: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. .......................215 15.18: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Rukwa Region..............................215 APPENDIX II 116 15.19: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Rukwa Region...............216 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Rukwa Region...............216 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 4) During the 2002/03 Agricultural Year, Rukwa Region...............217 15.20: Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Rukwa Region. ...............217 ANIMAL CONTRIBUTION TO CROP PRODUCTION .....................................................219 17.1: Number of Households Using Draft Animal to Cultivate Land By District During 2002/03 agricultural year, Rukwa Region.......................................................................220 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year................................................................................................220 17.3 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year................................................................................................221 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year..............................................................................................................221 CATTLE PRODUCTION .........................................................................................................223 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Rukwa Region .......................................................................................................224 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03...........................................................................224 18.4.1 Number of Cattle by Category and Type of Cattle as of 1st October 2003.....................224 18.2 Number of Cattle By Type and District as of 1st October, 2003 ....................................225 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003..................................................................................................................225 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................225 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................226 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003 .......................226 GOAT PRODUCTION..............................................................................................................227 19.1: Total Number of Goats by Type and District as of 2st October, 2003............................228 APPENDIX II 117 19.2: Total Number of Households Rearing Goats and Heads of Goats by Herd size on 1st October 2003...................................................................................................................228 19.:3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District.............................................................................................................................229 19.4 Number of Indigenous Goat by Category and District as of 1st October, 2003..............229 19.5: Number of Improved Meat Goat by Category and District as of 1st October, 2003.......229 19.6: Number of Improved Dairy Goat by Category and District as of 1st October, 2003......230 19.7: Number of Total Goat by Category and District as of 1st October, 2003.......................230 SHEEP PRODUCTION.............................................................................................................231 20.1: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year..............232 20.2: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year .................................................................................................................................232 20.3: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03.................232 20.4: Number of Sheep per Household by Category and district as of 1st October 2003........232 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003............233 20.6: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year................................................................................................233 20.8 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year..............................................................................................................233 PIGS PRODUCTION ................................................................................................................235 21.1 Number of Households Raising Pig by District during 2002/03 Agriculture Year.........236 21.2: Number of Households Raising Pig by District during 2002/03 Agriculture Year.........236 21.3: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003............236 LIVESTOCK PESTS AND PARASITE CONTROL .............................................................237 22.1 Number of Livestock Rearing Households deworming Livestock by District during 2002/03 Agricultural Year............................................................................................. 238` 22.2: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock............238 APPENDIX II 118 22.3: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ......238 22.4: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year ....................238 OTHER LIVESTOCK...............................................................................................................239 23a: Total number of Other Livestock by Type as of 1st October 2003.................................240 23b: Number of chicken by Category of Chicken and District as of 1st October, 2003 .........240 23d: Number of households with chicken and Category of Chicken by Flock Size ...............240 23c: Number of Households Rearing and number of Other Livestock by Type and District .240 FISH FARMING ........................................................................................................................241 28.1a: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year.............................................................................................................242 28.2a: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year.............................................................................................................242 28.2b Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year.............................................................................................................242 28.2c: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year.............................................................................................................242 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year.......242 LIVESTOCK EXTENSION......................................................................................................243 29.1a: Number of Agricultural Households Receiving Advice By District during the 2002/03 Agricultural Year.............................................................................................................244 29.1b Number of Households By Source of Extension and District, 2002/03 Agricultural Year244 29.1c Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year..............................................................244 29.1d Number of Agricultural Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year..........................................................................245 29.1e Number of Agricultural Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year..............................................................245 29.1f Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year..................................245 APPENDIX II 119 29.1g Number of Agricultural Households Receiving Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ........................................246 29.1h Number of Agricultural Households Receiving Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year ...............................246 29.1i Number of Agricultural Households Receiving Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.................................................................................246 29.1j Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year...............................................247 29.1j Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year...............................................................................................247 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES...........................................249 33.01a: Mean distances from horders dwellings to Infrastructures and services by District ......250 33.01b: Mean distance from holders dwellings to infrastrures and services by District.............251 33.01c: Mean distance from holders dwellings to all Weather roads by District........................251 33.01d: Mean distance from holders dwellings to Feeder Roads by District..............................251 33.01e: Mean distance from holders dwellings to Hospital by District ......................................252 33.01f: Mean distance from holders dwellings to Health Clinic by District...............................252 33.01g: Mean distance from holders dwellings to Primary School by District...........................252 33.1h: Number of Households to Regional Capital....................................................................252 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year.............................................................................................................253 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year .................................................................................................................................253 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year .................................................................................................................................253 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year .................................................................................................................................253 SATISFACTION OF USING VETERINARY CLINIC............................................................... 33.19b Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year.............................................................................................................254 APPENDIX II 120 33.19c Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year.............................................................................................................254 33.19d Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year...............................................................................................255 33.19e Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year...............................................................................................255 33.19f Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year ..........................................256 33.19G Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year.............................................................................................................256 HOUSEHOLD FACILITIES ...................................................................................................................257 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year..............................................................................................................258 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year............................................................................258 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year .............................................................................................258 34.4 Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year..............................................................................................259 34.5 Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year...............................................................................................259 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.................................................260 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.........................................260 34.8 Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year.....................261 34.9 Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year.....................261 34.10 Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District.................................................................................................262 34.11 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District.............................................................................................262 APPENDIX II 121 34.12 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District.............................................................................................263 34.13 Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.............................................................................263 34.14 Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year...............................................................................................264 34.15.1 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year..............................................................................................................264 34-16 Number of Households by Main Source of Income and District, 2002/03 Agricultural Year ................................................................................................................................265 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year.............................................................................................................266 APPENDIX II 122 APPENDIX II: CROPS Type of Agriculture Household.................................................................................................................. 121 Number of Agriculture Households ............................................................................................................123 Rank of Importance of Livelihood Activities..............................................................................................125 Households Demography ............................................................................................................................129 Land Access/Ownership..............................................................................................................................137 Land Use………………..............................................................................................................................139 Total Annual Crop and Vege Production Long and short Seasons.............................................................143 Annual Crop and Vege Production Long Rainy Seasons............................................................................151 Permanent Crop Production.........................................................................................................................167 Agro-processing .................................................................................................................................177 Marketing .................................................................................................................................181 Irrigation/Erosion Control ...........................................................................................................................183 Access to Farm Inputs ................................................................................................................................ 187 Agriculture Credit .................................................................................................................................203 Tree Farming and Agro-forestry..................................................................................................................207 Crop Extension .................................................................................................................................211 Animal Contribution to Crop Production ....................................................................................................221 Cattle Production .................................................................................................................................225 Goat Production .................................................................................................................................229 Sheep Production .................................................................................................................................233 Pig Production .................................................................................................................................237 Livestock Pests and Parasite Control...........................................................................................................239 Other Livestock .................................................................................................................................243 Fishing Farming .................................................................................................................................245 Livestock Extension .................................................................................................................................247 Access to Infrastructure and other services .................................................................................................255 Household Facilities .................................................................................................................................263 Appendix II 123 NUMBER OF AGRICULTURAL HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 124 Mpanda 59,533 80 1,212 2 60,745 82 13,476 18 74,221 Sumbawanga 68,935 90 2,874 4 71,809 94 4,892 6 76,701 Nkasi 30,483 73 4,048 10 34,531 83 6,945 17 41,476 Sumbawanga 13,309 44 336 1 13,645 45 16,825 55 30,470 Total 172,261 77 8,469 4 180,730 81 42,138 19 222,868 Number % Number % Number % Number % Mpanda 47,900 42 0 0 11,633 20 59,533 35 59,533 59,533 0 Sumbawanga 38,769 34 416 100 29,751 51 68,935 40 68,935 68,520 416 Nkasi 19,786 17 0 0 10,697 19 30,483 18 30,483 30,483 0 Sumbawanga 7,614 7 0 0 5,695 10 13,309 8 13,309 13,309 0 Total 114,069 100 416 100 57,776 100 172,261 100 172,261 171,845 416 Total % of Total Rural Households Total Number of Households (From 2002 Pop Census) 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year District Type of Agriculture Household Total Number of Agricultural Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock Crops Only Livestock Only % of Total Rural Households Total Rural Households Crops & Livestock 2.1 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agricultural Households by type of household and District, the 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households % of Total Rural Households Urban Households District Rural Households Involved in Agriculture % of Total Rural Households Rural Households NOT Involved in Agriculture Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 125 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 126 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Mpanda 327,178 52,383 6 30,191 7,150 4 357,369 59,533 6 Sumbawanga Rural 321,441 60,260 5 33,267 8,675 4 354,708 68,935 5 Nkasi 145,125 26,660 5 13,259 3,824 3 158,384 30,483 5 Sumbawanga Urban 65,457 11,599 6 6,351 1,710 4 71,808 13,309 5 Total 859,201 150,902 6 83,068 21,359 4 942,269 172,261 5 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 1 5 4 3 6 7 2 Sumbawanga Rural 1 6 4 3 5 7 2 Nkasi 1 7 4 3 6 5 2 Sumbawanga Urban 1 6 4 3 5 7 2 Total 1 7 4 6 3 5 2 Table. 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture sample Census - 2003 Rukwa Appendix II 127 Number % Number % Number % Less than 4 84,200 50 84,323 50 168,523 100 05 - 09 78,168 50 78,480 50 156,649 100 10 - 14 68,091 51 65,523 49 133,614 100 15 - 19 50,935 51 48,417 49 99,352 100 20 - 24 36,308 47 41,500 53 77,808 100 25 - 29 34,203 47 38,194 53 72,397 100 30 - 34 29,158 54 24,656 46 53,814 100 35 - 39 20,352 47 22,881 53 43,234 100 40 - 44 20,166 53 18,053 47 38,219 100 45 - 49 17,029 55 13,959 45 30,988 100 50 - 54 11,148 55 8,976 45 20,123 100 55 - 59 7,123 55 5,779 45 12,902 100 60 - 64 6,290 63 3,721 37 10,010 100 65 - 69 3,878 39 6,170 61 10,048 100 70 - 74 3,314 53 2,944 47 6,258 100 75 - 79 2,943 69 1,329 31 4,272 100 80 - 84 2,274 80 560 20 2,834 100 Above 85 664 54 559 46 1,223 100 Total 476,244 51 466,024 49 942,269 100 Number % Number % Number % Less than 4 84,200 18 84,323 18 168,523 18 05 - 09 78,168 16 78,480 17 156,649 17 10 - 14 68,091 14 65,523 14 133,614 14 15 - 19 50,935 11 48,417 10 99,352 11 20 - 24 36,308 8 41,500 9 77,808 8 25 - 29 34,203 7 38,194 8 72,397 8 30 - 34 29,158 6 24,656 5 53,814 6 35 - 39 20,352 4 22,881 5 43,234 5 40 - 44 20,166 4 18,053 4 38,219 4 45 - 49 17,029 4 13,959 3 30,988 3 50 - 54 11,148 2 8,976 2 20,123 2 55 - 59 7,123 1 5,779 1 12,902 1 60 - 64 6,290 1 3,721 1 10,010 1 65 - 69 3,878 1 6,170 1 10,048 1 70 - 74 3,314 1 2,944 1 6,258 1 75 - 79 2,943 1 1,329 0 4,272 0 80 - 84 2,274 0 560 0 2,834 0 Above 85 664 0 559 0 1,223 0 Total 476,244 100 466,024 100 942,269 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 128 Number % Number % Number % Mpanda 181,669 51 175,700 49 357,369 100 Sumbawanga Rur 180,938 51 173,770 49 354,708 100 Nkasi 78,286 49 80,098 51 158,384 100 Sumbawanga Urb 35,352 49 36,456 51 71,808 100 Total 476,244 51 466,024 49 942,269 100 Number % Number % Number % Number % Number % Mpanda 170,079 58 6,374 2 133 0 118,192 40 294,777 100 Sumbawanga Rur 161,987 56 12,498 4 357 0 113,807 39 288,649 100 Nkasi 74,949 57 6,426 5 80 0 49,956 38 131,411 100 Sumbawanga Urb 36,843 63 2,087 4 63 0 19,916 34 58,909 100 Total 443,857 57 27,385 4 634 0 301,870 39 773,745 100 Number % Number % Number % Number % Mpanda 85,137 29 112,331 38 97,309 33 294,777 100 Sumbawanga Rur 76,336 26 108,360 38 103,952 36 288,649 100 Nkasi 34,921 27 51,883 39 44,606 34 131,411 100 Sumbawanga Urb 17,898 30 23,288 40 17,724 30 58,909 100 Total 214,292 28 295,862 38 263,591 34 773,745 100 Number % Number % Number % Number % Mpanda 159,510 54 5,653 2 0 0 2,168 1 Sumbawanga Rur 159,114 55 4,927 2 0 0 4,441 2 Nkasi 69,264 53 3,084 2 80 0 4,085 3 Sumbawanga Urb 29,198 50 642 1 0 0 70 0 Total 417,086 54 14,306 2 80 0 10,764 1 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed School Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English y Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Fishing 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District p Farming Keeping / Pastoralist Main Activity Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 129 Self Employed (Non Farmimg) without Unpaid Family Helper (Non Agriculture) Not Working & Available Not Working & Unavailable Housemaker / Housewife Number % Number % Number % Number % Number % Mpanda 4,945 2 6,049 2 133 0 132 0 1,077 0 Sumbawanga Rural 3,053 1 7,261 3 100 0 112 0 538 0 Nkasi 2,288 2 554 0 0 0 0 0 71 0 Sumbawanga Urban 1,080 2 1,453 2 0 0 0 0 307 1 Total 11,365 1 15,317 2 233 0 244 0 1,993 0 Number % Number % Number % Number % Mpanda 83,953 28 23,434 8 134 0 294,777 100 Sumbawanga Rural 73,975 26 29,323 10 226 0 288,649 100 Nkasi 33,226 25 17,600 13 92 0 131,411 100 Sumbawanga Urban 17,383 30 7,486 13 34 0 58,909 100 Total 208,537 27 77,843 10 486 0 773,745 100 Number % Number % Number % Number % Number % Mpanda 141,045 48 5,710 2 102,728 35 45,295 15 294,777 100 Sumbawanga Rural 151,379 52 12,759 4 75,999 26 48,511 17 288,649 100 Nkasi 66,110 50 7,032 5 31,508 24 26,761 20 131,411 100 Sumbawanga Urban 27,383 46 1,197 2 22,139 38 8,190 14 58,909 100 Total 385,917 50 26,698 3 232,375 30 128,756 17 773,745 100 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Student Unable to Work / Too Old / Retired Other Total cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 130 Number % Number % Number % Number % Mpanda 269 0 1,077 1 5,312 5 4,661 4 Sumbawanga Rural 0 0 456 0 2,482 2 4,011 4 Nkasi 0 0 695 1 1,144 2 1,410 3 Sumbawanga Urban 104 0 238 1 982 4 747 3 Total 374 0 2,466 1 9,920 3 10,829 4 Number % Number % Number % Number % Number % Mpanda 73,010 65 535 0 937 1 390 0 0 0 Sumbawanga Rural 82,194 76 338 0 340 0 0 0 235 0 Nkasi 35,628 69 455 1 222 0 82 0 70 0 Sumbawanga Urban 16,180 69 69 0 101 0 0 0 34 0 Total 207,011 70 1,398 0 1,600 1 472 0 339 0 Number % Number % Number % Number % Number % Mpanda 269 0 0 0 1,708 2 0 0 135 0 Sumbawanga Rural 682 1 223 0 2,466 2 241 0 89 0 Nkasi 283 1 70 0 545 1 0 0 217 0 Sumbawanga Urban 135 1 0 0 202 1 0 0 34 0 Total 1,369 0 293 0 4,922 2 241 0 476 0 Number % Number % Number % Mpanda 0 0 6,044 5 112,331 100 Sumbawanga Rural 0 0 1,471 1 108,360 100 Nkasi 72 0 2,020 4 51,883 100 Sumbawanga Urban 33 0 717 3 23,288 100 Total 105 0 10,252 3 295,862 100 cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Form Six Training After Secondary Education cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Form Two Form Three Form Four University & Other Tertiary Education Adult Education Total District Form One cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Standard Three 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Standard Seven Standard Eight Training After Primary Education Pre Form One District Under Standard One Standard One Standard Two Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 131 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 132 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 50923 134 269 6285 918 354 926 Sumbawanga Rural 56737 101 699 7005 454 3190 617 Nkasi 25570 82 247 1650 222 2420 152 Sumbawanga Urban 9947 166 301 2188 443 69 233 Total 143176 483 1516 17128 2037 6033 1928 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 7,688 7,799 8,388 21,165 1,589 892 12,822 Sumbawanga Rural 11,340 2,461 18,179 15,049 3,077 2,225 16,708 Nkasi 3,972 715 7,213 12,696 879 1,895 3,421 Sumbawanga Urban 2,794 743 3,374 3,999 336 35 2,270 Total 25,794 11,717 37,154 52,909 5,881 5,047 35,222 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 521 6,842 7,574 8,417 1,067 1,045 29,510 Sumbawanga Rural 429 4,188 10,528 11,035 5,462 453 33,603 Nkasi 708 390 3,473 9,129 1,572 138 14,288 Sumbawanga Urban 437 745 1,906 2,704 710 35 5,983 Total 2,095 12,166 23,482 31,285 8,811 1,671 83,384 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 0 4,356 7,754 2,536 1,180 647 13,111 Sumbawanga Rural 210 5,111 7,900 11,754 5,311 1,068 13,694 Nkasi 151 1,349 5,192 3,947 1,112 292 10,663 Sumbawanga Urban 97 1,028 1,614 1,328 1,407 0 3,469 Total 459 11,844 22,459 19,565 9,011 2,007 40,937 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 133 District Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 748 2,677 917 0 110 2,494 Sumbawanga Rural 3,377 2,981 4,597 2,837 1,059 2,267 Nkasi 1,485 1,707 610 705 0 1,635 Sumbawanga Urban 652 578 443 674 0 1,019 Total 6,262 7,942 6,567 4,216 1,169 7,415 District Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 0 244 244 0 0 0 Sumbawanga Rural 1,170 239 334 701 223 111 Nkasi 244 227 46 0 73 82 Sumbawanga Urban 102 0 69 370 0 134 Total 1,516 710 693 1,072 295 327 District Annual Crop Farming Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Mpanda 266 0 0 132 0 Sumbawanga Rural 0 111 0 118 119 Nkasi 0 0 0 73 0 Sumbawanga Urban 0 33 35 35 0 Total 266 144 35 358 119 3.1e: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f: RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Sample Census - 2003 Rukwa 134 Appendix II 135 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 136 Households with Area Owned Under Customary Law Households with Area Bought From Others Households with Area Rented From Others Households with Area Borrowed From Others Households with Area Shared Croped From Others Households with Area under Other Forms of Tenure Total Number of Households No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % % Mpanda 1,476 2 44,634 75 12,473 21 5,225 9 4,886 8 536 1 1,330 2 59,533 Sumbawanga Rural 1,119 2 55,844 81 20,170 29 8,505 12 7,183 10 240 0 2,336 3 68,935 Nkasi 471 2 25,449 83 6,969 23 713 2 3,735 12 322 1 740 2 30,483 Sumbawanga Urban 239 2 11,267 85 3,819 29 655 5 954 7 139 1 665 5 13,309 Total 3,305 2 137,194 80 43,431 25 15,099 9 16,758 10 1,238 1 5,072 3 172,261 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Mpanda 3,939 133,807 38,583 5,601 4,323 639 1,810 188,703 Sumbawanga Rural 3,245 162,802 50,391 12,332 8,478 85 4,202 241,535 Nkasi 927 85,792 14,801 1,546 7,377 1,215 682 112,339 Sumbawanga Urban 264 22,409 6,112 930 805 140 441 31,102 Total 8,376 404,810 109,887 20,409 20,983 2,079 7,135 573,679 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Land Access District Land Access/ Ownership (Hectare) 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Households with Area Leased/Certificate of Ownership Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 137 LAND USE Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 138 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households Fallow Households with Natural Bush Households with Planted Trees Households with Rented to Others Households with Unusable Households with Uncultivated Usable Land Total Number of Households Mpanda 45,386 35,834 2,219 4,819 6,373 1,052 7,942 5,732 5,498 1,736 3,873 32,355 59,533 Sumbawanga Rural 62,466 15,414 7,672 3,297 2,652 1,052 15,549 2,927 3,371 3,093 2,894 27,258 68,935 Nkasi 22,834 12,502 1,025 787 968 736 6,658 896 2,590 1,395 3,352 13,406 30,483 Sumbawanga Urban 11,239 6,488 1,799 309 639 300 2,179 517 3,846 337 859 4,008 13,309 Total 141,925 70,239 12,714 9,212 10,632 3,140 32,328 10,071 15,306 6,562 10,978 77,028 172,261 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Mpanda 55,296 36,591 452 2,369 5,973 2,319 9,225 10,678 2,341 2,299 3,702 57,458 188,703 Sumbawanga Rural 117,391 19,238 3,419 4,179 4,539 1,667 32,616 5,155 1,209 4,943 3,058 44,733 242,146 Nkasi 39,362 14,666 314 1,511 1,851 4,131 11,735 1,127 1,501 2,274 5,267 28,600 112,339 Sumbawanga Urban 14,667 5,917 712 105 260 324 2,159 282 987 1,056 713 3,920 31,102 Total 226,716 76,412 4,897 8,164 12,623 8,441 55,734 17,243 6,038 10,572 12,739 134,711 574,291 % 39 13 1 1 2 1 10 3 1 2 2 23 100 District Land Use Area 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Type of Land Use 5.2 LAND USE: Area of Land (ha) by type of Land Use and District for 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 139 Total Total Number % Number % Number Number Percent Number Percent Number Mpanda 17,480 29 42,054 71 59,533 Mpanda 41,743 70 17,790 30 59,533 Sumbawanga Rural 27,846 41 40,674 59 68,520 Sumbawanga Rural 43,553 64 24,966 36 68,520 Nkasi 11,375 37 19,109 63 30,483 Nkasi 18,324 60 12,160 40 30,483 Sumbawanga Urban 6,850 51 6,459 49 13,309 Sumbawanga Urban 5,302 40 8,007 60 13,309 Total 63,550 37 108,295 63 171,845 Total 108,922 63 62,923 37 171,845 Number % Number % Number Percent Mpanda 41,743 70 17,790 30 59,533 100 Sumbawanga Rural 43,553 64 24,966 36 68,520 100 Nkasi 18,324 60 12,160 40 30,483 100 Sumbawanga Urban 5,302 40 8,007 60 13,309 100 Total 108,922 63 62,923 37 171,845 100 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Yes No Was all Land Available to the Hh Used During 2002/03? 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total Tanzania Agriculture Sample Census - 2003 Rukwa 140 Appendix II 141 ANNUAL CROP AND VEGETABLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 142 Dry Season Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 158400 96231 96231 0.0 Sumbawanga Rural 474 863 177594 132698 133561 0.6 Nkansi 160 130 74856 53306 53436 0.2 Sumbawanga Urban 104 56 32727 20109 20166 0.3 Total 738 1049 443,577 302,344 303,393 0.3 Households Growing Crops Households NOT Growing Crops Number of Households Growing Crops Number of Households NOT Growing Crops Mpanda 0 59533 59533 0 59533 Sumbawanga Rural 118 68817 67939 996 68935 Nkansi 80 30403 30403 80 30483 Sumbawanga Urban 35 13274 13240 69 13309 Total 233 172027 171,116 1,145 172,261 District 7.1 & 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District Total Number of Crop Growing Households Wet Season Dry Season 7.1 & 7.2a: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) by season and District District Total Area Planted (hectare) % Area planted in Dry season Wet Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 143 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 427 155 363 203,500 240,468 1,182 203,928 240,623 1,180 Maize 427 155 363 149,606 163,277 1,091 150,033 163,432 1,089 Paddy 0 0 0 25,526 49,520 1,940 25,526 49,520 1,940 Sorghum 0 0 0 7,405 9,942 1,343 7,405 9,942 1,343 Bulrush Millet 0 0 0 17 20 1,186 17 20 1,186 Finger Millet 0 18,967 15,798 833 18,967 15,798 833 Wheat 0 0 0 1,979 1,911 966 1,979 1,911 966 ROOTS & TUBERS 0 0 28,595 45,702 1,598 28,595 45,702 1,598 Cassava 0 0 0 25,611 39,818 1,555 25,611 39,818 1,555 Sweet Potatoes 0 0 0 2,681 4,699 1,753 2,681 4,699 1,753 Irish Potatoes 0 0 0 282 1,031 3,653 282 1,031 3,653 Yams 0 0 0 13 127 9,485 13 127 9,485 Cocoyam 0 0 0 7 27 3,952 7 27 3,952 PULSES 279 44 156 37,551 17,567 468 37,831 17,610 466 Mung Beans 0 0 0 0 0 0 0 0 0 Beans 279 44 37,251 17,265 463 37,530 17,308 461 Cowpeas 0 0 0 68 47 687 68 47 687 Green Gram 0 0 0 102 151 1,482 102 151 1,482 Chich Peas 0 0 0 0 0 0 0 0 0 Bambaranuts 0 0 0 108 93 865 108 93 865 Field Peas 0 0 0 23 11 494 23 11 494 OIL SEEDS & OIL NUTS 343 217 634 28,178 17,201 610 28,520 17,419 611 Sunflower 295 146 11,463 5,957 520 11,758 6,103 519 Simsim 0 0 0 65 35 540 65 35 540 Groundnuts 48 71 16,522 11,055 669 16,570 11,126 671 Soya Beans 0 0 0 127 154 1,208 127 154 1,208 Castor Seed 0 0 0 0 0 0 0 0 0 FRUITS & VEGETABLES 0 0 0 1,225 4,211 3,437 1,225 4,211 3,437 Okra 0 0 0 0 0 0 0 0 0 Radish 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 0 0 0 Onions 0 0 0 266 1,139 0 266 1,139 4,279 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 176 739 0 176 739 4,212 Tomatoes 0 0 0 583 2,136 0 583 2,136 3,665 Spinnach 0 0 0 51 68 0 51 68 1,336 Carrot 0 0 0 3 7 0 3 7 2,134 Chillies 0 0 0 0 0 0 0 Amaranths 0 0 0 125 110 0 125 110 879 Pumpkins 0 0 0 22 12 0 22 12 540 Cucumber 0 0 0 0 0 0 0 0 0 Egg Plant 0 0 0 0 0 0 0 0 0 Water Mellon 0 0 0 0 0 0 0 0 0 CASH CROPS 0 0 0 3,295 3,263 990 3,295 3,263 990 Pyrethrum 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 39 13 0 39 13 329 Tobacco 0 0 0 3,256 3,251 0 3,256 3,251 998 Jute 0 0 0 0 0 0 0 0 0 Total 1,049 302,344 303,393 Table 7.1 & 7.2c: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Crop Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Number of Households Area Planted (ha) Number of Households Area Planted (ha) CEREALS 233 427 220,959 203500 203,928 0.2 Maize 233 427 159160 149606 150033 0.3 Paddy 0 0 30132 25526 25526 0.0 Sorghum 0 0 10613 7405 7405 0.0 Bulrush Millet 0 0 82 17 17 0.0 Finger Millet 0 0 18635 18967 18967 0.0 Wheat 0 0 2337 1979 1979 0.0 ROOTS & TUBERS 0 0 64889 28595 28595 0.0 Cassava 0 0 53929 25611 25611 0.0 Sweet Potatoes 0 0 9530 2681 2681 0.0 Irish Potatoes 0 0 1364 282 282 0.0 Yams 0 0 33 13 13 0.0 Cocoyam 0 0 34 7 7 0.0 PULSES 233 279 78866 37551 37831 0.7 Mung Beans 0 0 78216 0 0 0.0 Beans 233 279 151 37251 37530 0.7 Cowpeas 0 0 120 68 68 0.0 Green Gram 0 0 0 102 102 0.0 Chich Peas 0 0 0 0 0 0.0 Bambaranuts 0 0 266 108 108 0.0 Field Peas 0 0 112 23 23 0.0 OIL SEEDS & OIL NUTS 272 343 65842 28178 28520 1.2 Sunflower 153 295 19960 11463 11758 2.5 Simsim 0 0 357 65 65 0.0 Groundnuts 118 48 44997 16522 16570 0.3 Soya Beans 0 0 528 127 127 0.0 Castor Seed 0 0 0 0 0 0.0 FRUITS & VEGETABLES 0 0 1225 1225 0.0 Okra 0 0 0 0 0 0.0 Radish 0 0 0 0 0 0.0 Bitter Aubergine 0 0 0 0 0 0.0 Onions 0 0 0 266 266 0.0 Ginger 0 0 0 0 0 0.0 Cabbage 0 0 1032 176 176 0.0 Tomatoes 0 0 3499 583 583 0.0 Spinnach 0 0 420 51 51 0.0 Carrot 0 0 34 3 3 0.0 Chillies 0 0 0 0 0.0 Amaranths 0 0 1157 125 125 0.0 Pumpkins 0 0 215 22 22 0.0 Cucumber 0 0 0 0 0 0.0 Egg Plant 0 0 0 0 0 0.0 Water Mellon 0 0 0 0 0 0.0 CASH CROPS 0 0 0 3295 3295 0.0 Pyrethrum 0 0 0 0 0 0.0 Cotton 0 0 128 39 39 0.0 Tobacco 0 0 4818 3256 3256 0.0 Jute 0 0 0 0 0 0.0 Total 1,049 4,945 302,344 303,393 0.0 Table 7.1 & 7.2d: TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agricultural Year Crop Wet Season Dry Season Total Area Planted Dry & Wet seasons % Area Planted in Dry Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 145 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 5,092 11,021 158,400 96,231 11.5 Sumbawanga Rural 0 0 7,774 19,216 177,594 132,698 14.5 Nkansi 0 0 1,696 6,698 74,856 53,306 12.6 Sumbawanga Urban 35 56 7,736 12,832 32,727 20,109 63.8 Total 35 56 22,298 49,767 443,577 302,344 16.5 District Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 403 571 59,533 96,231 0.6 Sumbawanga Rural 0 0 460 918 68,401 132,698 0.7 Nkansi 0 0 80 422 30,403 53,306 0.8 Sumbawanga Urban 0 0 70 120 13,240 20,109 0.6 Total 0 0 1,013 2,031 171,578 302,344 0.7 7.1 & 7.2h TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region. Insecticide Use % of Planted Area using Insecticide Insecticide Use Insecticide Use Total District 7.1 & 7.2iTOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households and Planted Area By Insecticide Use and District for the 2002/03 agricultural year - Wet & Dry Seasons- Rukwa region. % of Planted Area using Insecticide Total Herbicide Use Insecticide Use Insecticide Use Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 146 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 129 679 0 303,101 53,421 75,999 53,550 192,461 Sumbawanga Rural 119 72 0 177,758 21,908 23,611 22,027 133,561 Nkansi 0 0 0 77,974 14,606 15,748 14,606 53,436 Sumbawanga Urban 69 104 0 21,476 1,968 1,915 2,037 20,166 Total 316 855 0 580,309 91,903 117,273 92,219 303,393 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Total Planted Area Mpanda 1,200 3,089 134 109 3,894 7,937 113,838 181,326 192,461 Sumbawanga Rural 5,532 16,068 924 1,682 117 1,420 61,947 114,392 133,561 Nkansi 1,426 3,671 391 313 145 88 28,522 49,364 53,436 Sumbawanga Urban 3,941 6,550 272 421 781 1,755 8,282 11,439 20,166 Total 12,098 29,379 1,721 2,524 4,937 11,200 153,055 260,290 303,393 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 1,071 1,980 3,050 5,030 4,121 7,009 28 Sumbawanga Rural 5,971 10,422 16,393 26,815 22,364 37,237 28 Nkansi 948 2,521 3,469 5,991 4,417 8,512 30 Sumbawanga Urban 2,355 4,284 6,639 10,922 8,993 15,206 28 Total 10,344 19,207 29,551 48,758 39,895 67,965 28 Household Using Irrigation Household NOT Using Irrigation Total 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Irrigation Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region. District Irrigation Use % of Planted Area using Insecticide District Fertilisers Use y Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District for 2002/03 agricultural year Wet & Dry season - Rukwa Region. 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Means of Soil Preparation and District - Wet & Dry Seasons- Rukwa Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 147 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,227 6,178 56,306 90,053 59,533 96,231 3.4 Sumbawanga Rural 680 597 67,721 132,101 68,401 132,698 0.5 Nkasi 315 705 30,089 52,601 30,403 53,306 0.6 Sumbawanga Urban 583 1,286 12,657 18,823 13,240 20,109 2.9 Total 4,805 8,766 166,773 293,578 171,578 302,344 1.6 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,082 5,507 56,451 90,670 59,533 96,178 5.7 Sumbawanga Rural 6,712 18,377 61,227 111,967 67,939 130,345 14.1 Nkansi 569 1,183 29,834 51,977 30,403 53,160 2.2 Sumbawanga Urban 694 1,990 12,564 18,961 13,258 22,078 9.0 Total 11,057 27,058 160,077 273,576 171,133 302,400 8.9 7.1&7.2k: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - WET & DRY SEASONS District Improved Seed Use % of area planted using Improved Seeds Households Using Improved Seed Households Not Using Improved Seed Total 7.1 $ 7.2j: ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year WET SEASON District Fungicide Use % of area planted using Fungicides Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Rukwa Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 0 0 118 863 Nkansi 0 0 80 130 0 0 80 130 Sumbawanga Urban 0 0 35 56 0 0 35 56 Total 0 0 233 1,049 0 0 233 1,049 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 0 0 0 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 118 863 118 863 Nkansi 0 0 0 0 0 0 80 130 80 130 Sumbawanga Urban 0 0 0 0 0 0 35 56 35 56 Total 0 0 0 0 0 0 233 1,049 233 1,049 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 Household Using Irrigation Mostly Farm Yard Manure Household NOT Using Irrigation Total 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and Distric, DRY SEASON, Rukwa Region. Irrigation Use % of Planted Area using Insecticide District Total Fertilisers Use Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-DRY SEASON, Rukwa Region 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total number of agriculture Households and Planted Area (ha) By Fertiliser Use and District - DRY SEASON,Rukwa Region. District District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Compost Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 149 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 Nkansi 0 0 80 130 80 130 Sumbawanga Urban 35 56 0 0 35 56 Total 35 56 199 993 233 1,049 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 % Planted Area using Herbicide Household NOT Using Irrigation Total 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Pesticide Use and District, DRY SEASON, Rukwa Region. District Herbicide Use Household Using Irrigation Household NOT Using Irrigation Total 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District, DRY SEASON, Ruwa Region District Insecticide Use Household Using Irrigation Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 150 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 118 863 118 863 0 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 0 0 233 1,049 233 1,049 0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 118 863 0 0 118 863 100 Nkansi 0 0 80 130 80 130 0 Sumbawanga Urban 0 0 35 56 35 56 0 Total 118 863 115 186 233 1,049 82 % 51 82 49 18 100 100 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District DRY SEASON, Rukwa Region. District Improved Seed Use % Planted Area using Herbicide Household Using Irrigation Household NOT Using Irrigation Total 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, DRY SEASON District Fungicide Use % Planted Area using Herbicide Household Using Irrigation Household NOT Using Irrigation Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 151 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Mpanda 129 679 5,984 19,499 53,421 75,999 59,533 96,178 Sumbawanga Rural 119 72 45,912 106,662 21,908 23,611 67,939 130,345 Nkansi 0 0 15,797 37,412 14,606 15,748 30,403 53,160 Sumbawanga Urban 69 104 11,204 18,069 1,968 1,915 13,240 20,088 Total 316 855 78,897 181,643 91,903 117,273 171,116 299,771 % 0.2 0.3 46.1 60.6 53.7 39.1 160.9 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Total Planted Area Mpanda 1,200 3,089 134 109 3,894 7,937 54,305 85,095 59,533 96,231 Sumbawanga Rural 5,532 16,068 924 1,682 117 1,420 61,828 113,529 68,401 132,698 Nkansi 1,426 3,671 391 313 145 88 28,442 49,234 30,403 53,306 Sumbawanga Urban 3,941 6,550 272 421 781 1,755 8,247 11,383 13,240 20,109 Total 12,098 29,379 1,721 2,524 4,937 11,200 152,822 259,241 171,578 302,344 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Mpanda 1,071 1,980 58,463 94,251 59,533 96,231 2.1 Sumbawanga Rural 5,971 10,422 62,430 122,276 68,401 132,698 8 Nkasi 948 2,521 29,455 50,785 30,403 53,306 5 Sumbawanga Urban 2,355 4,284 10,886 15,826 13,240 20,109 21 Total 10,344 19,207 161,234 283,137 171,578 302,344 6.4 % 6 6 94 94 100 100 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District WET SEASON, Rukwa Region Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During WET SEASON District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of Area Planted Under Irrigation in Wet Season District Fertilisers Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District, WET SEASON, Rukwa Region District Soil Preparation Mostly Tractor Ploughing Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 152 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 5,092 11,021 54,441 85,210 59,533 96,231 Sumbawanga Rural 7,774 19,216 60,627 113,482 68,401 132,698 Nkasi 1,696 6,698 28,707 46,608 30,403 53,306 Sumbawanga Urban 7,736 12,832 5,504 7,277 13,240 20,109 Total 22,298 49,767 149,280 252,577 171,578 302,344 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 403 571 59,130 95,659 59,533 96,231 0.6 Sumbawanga Rural 460 918 67,941 131,781 68,401 132,698 0.7 Nkasi 80 422 30,323 52,884 30,403 53,306 0.8 Sumbawanga Urban 70 120 13,171 19,990 13,240 20,109 0.6 Total 1,013 2,031 170,565 300,314 171,578 302,344 0.7 % 0.6 0.7 99.4 99.3 100.0 100.0 Total Number of Households Number % Number % Number Mpanda 46,242 78 13,292 22 59,533 Sumbawanga Rural 59,911 87 9,024 13 68,935 Nkansi 24,110 79 6,374 21 30,483 Sumbawanga Urban 10,835 81 2,474 19 13,309 Total 141,097 82 31,164 18 172,261 Households that Sold Produce Households that Did not Sold Produce District % of Area Planted Using Herbicide 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District WET SEASON, Rukwa Region. 7.2j Number of Crop Producing Households Reporting Selling Agricultural Products by District, 2002/03 District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District WET SEASON, Rukwa Region District Insecticide Use Households Using Pesticide Households Not Using Pesticide Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 153 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,227 6,178 56,306 90,053 59,533 96,231 6.4 Sumbawanga Rural 680 597 67,721 132,101 68,401 132,698 0.4 Nkasi 315 705 30,089 52,601 30,403 53,306 1.3 Sumbawanga Urban 583 1,286 12,657 18,823 13,240 20,109 6.4 Total 4,805 8,766 166,773 293,578 171,578 302,344 2.9 % 3 3 97 97 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Mpanda 3,082 5,507 56,451 90,670 59,533 96,178 5.7 Sumbawanga Rural 6,712 18,377 61,227 111,967 67,939 130,345 14.1 Nkansi 569 1,183 29,834 51,977 30,403 53,160 2.2 Sumbawanga Urban 676 1,127 12,564 18,961 13,240 20,088 5.6 Total 11,039 26,195 160,077 273,576 171,116 299,771 8.7 % 6 9 94 91 100 100 % of Planted Area Using Improved Seed 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District, WET SEASON, Rukwa Region District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted Area Using Fungicide 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District 2002/03 WET SEASON, Rukwa Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Maize 3,884 1,604 51,453 41,568 0 . 129 47 0 . 55,467 43,219 Paddy 402 136 12,576 12,071 120 194 129 105 0 . 13,227 12,505 Sorghum 0 . 1,568 2,048 0 . 0 . 0 . 1,568 2,048 Finger Millet 0 . 1,464 545 0 . 0 . 0 . 1,464 545 CEREALS 4,286 1,739 67,061 56,232 120 194 258 152 0 . 71,726 58,316 Cassava 3,756 1,488 25,745 10,942 0 . 0 . 0 . 29,501 12,430 Sweet Potatoes 0 . 4,555 1,400 0 . 0 . 0 . 4,555 1,400 ROOTS & TUBERS 3,756 1,488 30,300 12,342 0 . 0 . 0 . 34,056 13,830 Beans 3,085 1,569 20,928 8,655 0 . 129 31 0 . 24,142 10,255 Bambaranuts 133 54 133 54 0 . 0 . 0 . 266 108 PULSES 3,218 1,622 21,061 8,709 0 . 129 31 0 . 24,408 10,363 Sunflower 134 27 0 . 0 . 0 . 0 . 134 27 Simsim 0 . 135 16 0 . 0 . 0 . 135 16 Groundnuts 2,277 841 18,292 9,007 0 . 133 27 0 . 20,702 9,874 Soya Beans 0 . 269 68 0 . 0 . 0 . 269 68 OIL SEEDS & OIL NUTS 2,411 868 18,696 9,091 0 . 133 27 0 . 21,240 9,986 Onions 0 . 270 68 0 . 0 . 0 . 270 68 Cabbage 0 . 135 14 0 . 0 . 0 . 135 14 Tomatoes 0 . 803 173 0 . 0 . 0 . 803 173 Spinnach 0 . 134 22 0 . 0 . 0 . 134 22 Amaranths 0 . 536 52 0 . 0 . 0 . 536 52 FRUITS & VEGETABLES 0 . 1,878 329 0 . 0 . 0 . 1,878 329 Cotton 0 . 128 39 0 . 0 . 0 . 128 39 Tobacco 134 54 4,566 3,178 0 . 0 . 0 . 4,700 3,233 CASH CROPS 134 54 4,693 3,217 0 . 0 . 0 . 4,827 3,271 Total 13,805 5,772 143,689 89,920 120 194 520 210 0 . 158,135 96,096 Sumbawanga Rural Maize 4,642 5,881 53,555 56,992 345 207 4,287 2,623 581 248 63,410 65,951 Paddy 728 736 10,358 8,978 113 46 1,029 649 1,294 1,104 13,522 11,514 Sorghum 355 605 5,958 3,907 0 . 1,078 461 0 . 7,391 4,973 Finger Millet 1,717 2,098 8,410 9,362 0 . 826 407 0 . 10,953 11,867 Wheat 0 . 224 91 0 . 0 . 0 . 224 91 CEREALS 7,441 9,320 78,505 79,331 458 253 7,220 4,140 1,875 1,351 95,500 94,395 Cassava 566 357 8,471 4,107 0 . 0 . 0 . 9,037 4,464 Sweet Potatoes 117 47 2,897 664 111 11 0 . 117 5 3,242 728 Irish Potatoes 101 20 230 28 0 . 0 . 0 . 331 49 ROOTS & TUBERS 784 424 11,598 4,799 111 11 0 . 117 5 12,610 5,240 Beans 2,085 1,278 26,551 14,897 121 98 1,835 791 230 79 30,821 17,142 Sumbawanga Rural Green Gram 0 . 120 102 0 . 0 . 0 . 120 102 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Mpanda Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Field Peas 0 . 112 23 0 . 0 . 0 . 112 23 PULSES 2,085 1,278 26,783 15,022 121 98 1,835 791 230 79 31,053 17,266 Sunflower 443 220 10,552 6,997 0 . 918 429 0 . 11,912 7,646 Simsim 0 . 118 24 0 . 0 . 0 . 118 24 Groundnuts 1,126 247 17,249 4,841 111 11 241 37 0 . 18,728 5,136 Soya Beans 0 . 225 46 0 . 0 . 0 . 225 46 OIL SEEDS & OIL NUTS 1,570 467 28,144 11,907 111 11 1,159 466 0 . 30,983 12,851 Onions 0 . 451 68 0 . 0 . 0 . 451 68 Cabbage 0 . 326 60 0 . 0 . 0 . 326 60 Tomatoes 0 . 1,598 241 0 . 0 . 117 5 1,715 245 Spinnach 0 . 218 22 0 . 0 . 0 . 218 22 Amaranths 0 . 452 60 0 . 0 . 0 . 452 60 Pumpkins 0 . 100 10 0 . 115 12 0 . 215 22 FRUITS & VEGETABLES 0 . 3,145 461 0 . 115 12 117 5 3,377 477 Tobacco 0 . 118 24 0 . 0 . 0 . 118 24 CASH CROPS 0 . 118 24 0 . 0 . 0 . 118 24 Total 11,880 11,490 148,293 111,543 801 373 10,329 5,407 2,338 1,439 173,641 130,253 Nkansi Maize 365 361 26,206 26,943 0 . 506 695 73 15 27,149 28,014 Paddy 0 . 3,197 1,409 0 . 0 . 73 7 3,270 1,416 Sorghum 60 7 1,425 359 0 . 0 . 0 . 1,485 366 Bulrush Millet 0 . 82 17 0 . 0 . 0 . 82 17 Finger Millet 165 167 5,375 6,154 0 . 0 . 0 . 5,540 6,321 Wheat 0 . 239 129 80 32 0 . 0 . 319 161 CEREALS 589 535 36,524 35,010 80 32 506 695 145 22 37,845 36,294 Cassava 666 291 9,615 5,681 0 . 60 18 145 29 10,486 6,020 Sweet Potatoes 0 . 1,525 469 0 . 0 . 0 . 1,525 469 Irish Potatoes 0 . 409 149 0 . 0 . 0 . 409 149 ROOTS & TUBERS 666 291 11,549 6,299 0 . 60 18 145 29 12,420 6,638 Beans 163 75 14,524 6,566 0 . 294 167 76 3 15,056 6,810 Cowpeas 82 33 0 . 0 . 0 . 0 . 82 33 PULSES 245 108 14,524 6,566 0 . 294 167 76 3 15,138 6,844 Sunflower 165 75 3,522 1,806 0 . 70 57 0 . 3,757 1,938 Groundnuts 82 8 4,422 1,202 80 65 70 57 0 . 4,654 1,333 OIL SEEDS & OIL NUTS 247 83 7,944 3,008 80 65 141 114 0 . 8,412 3,270 Onions 0 . 244 20 0 . 0 . 0 . 244 20 Cabbage 0 . 234 60 0 . 0 . 0 . 234 60 Tomatoes 0 . 164 35 0 . 0 . 0 . 164 35 FRUITS & VEGETABLES 0 . 642 115 0 . 0 . 0 . 642 115 Total 1,747 1,017 71,183 50,997 160 97 1,000 994 367 55 74,457 53,160 Tanzania Agriculture Sample Census - 2003 Rukwa Total Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area 7.2h Planted Area and Number of Crop Growing Households in WET SEASON During 2002/03 Crop Year By Method of Land Clearing By Crops 2002/03 Agricultural Year Land Clearing District Crop No Land Clearing Mostly Burning Mostly Tractor Slashing Mostly Hand Slashing Mostly Bush Clearance Sumbawanga Urban Maize 238 264 9,409 8,601 35 72 2,310 1,885 870 1,404 12,861 12,226 Sorghum 0 . 137 12 0 . 32 7 0 . 169 18 Finger Millet 70 28 470 143 0 . 105 57 0 . 644 228 Wheat 0 . 1,725 1,586 35 70 35 71 0 . 1,794 1,728 CEREALS 308 292 11,740 10,342 69 142 2,482 2,019 870 1,404 15,469 14,199 Cassava 35 28 364 83 0 . 32 13 0 . 431 125 Sweet Potatoes 0 . 69 11 0 . 139 74 0 . 208 85 Irish Potatoes 0 . 589 81 0 . 0 . 35 4 624 85 Yams 0 . 33 13 0 . 0 . 0 . 33 13 Cocoyam 0 . 0 . 0 . 34 7 0 . 34 7 ROOTS & TUBERS 35 28 1,055 188 0 . 205 94 35 4 1,330 314 Beans 69 24 6,460 2,147 35 13 1,008 329 625 531 8,197 3,043 Cowpeas 0 . 69 35 0 . 0 . 0 . 69 35 PULSES 69 24 6,529 2,182 35 13 1,008 329 625 531 8,266 3,078 Sunflower 136 55 3,035 1,353 0 . 846 395 139 49 4,156 1,852 Simsim 0 . 69 11 0 . 0 . 35 14 104 25 Groundnuts 0 . 671 127 0 . 171 31 70 21 913 180 Soya Beans 0 . 34 14 0 . 0 . 0 . 34 14 OIL SEEDS & OIL NUTS 136 55 3,810 1,505 0 . 1,017 426 244 85 5,207 2,070 Onions 0 . 720 107 0 . 34 3 0 . 754 110 Cabbage 33 3 271 32 0 . 34 7 0 . 338 42 Tomatoes 33 3 785 126 0 . 0 . 0 . 818 129 Spinnach 0 . 68 7 0 . 0 . 0 . 68 7 Carrot 0 . 34 3 0 . 0 . 0 . 34 3 Amaranths 0 . 135 10 0 . 34 3 0 . 169 13 FRUITS & VEGETABLES 66 7 2,013 284 0 . 101 14 0 . 2,180 305 Total 613 406 25,147 14,502 104 155 4,813 2,881 1,773 2,023 32,451 19,966 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 157 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 55,602 43,301 38,976 0.9 43,301 38,976 0.9 Sumbawanga Rural 118 288 118 0.4 63,410 65,951 84,223 1.3 66,238 84,342 1.3 Nkansi 80 97 19 0.2 27,149 28,014 27,028 1.0 28,111 27,047 1.0 Sumbawanga Urban 35 42 17 0.4 12,999 12,341 13,050 1.1 12,383 13,068 1.1 Total 233 427 155 0.4 159,160 149,606 163,277 1.1 150,033 163,432 1.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 13,227 12,505 26,729 2.1 12,505 26,729 2.1 Nkansi 0 0 0 0.0 13,635 11,605 20,209 1.7 11,605 20,209 1.7 Sumbawanga Urban 0 0 0 0.0 0 0 0 0 0 0.0 Total 0 0 0 0.0 3,270 1,416 2,583 1.8 1,416 2,583 1.8 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 1,568 2,048 4,645 2.3 2,048 4,645 2.3 Sumbawanga Rural 0 0 0 0.0 7,391 4,973 5,108 1.0 4,973 5,108 1.0 Nkansi 0 0 0 0.0 1,485 366 181 0.5 366 181 0.5 Sumbawanga Urban 0 0 0 0.0 169 18 8 0.5 18 8 0.5 Total 0 0 0 0.0 10,613 7,405 9,942 1.3 7,405 9,942 1.3 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 1,464 545 690 1.3 545 690 1.3 Sumbawanga Rural 0 0 0 0.0 10,953 11,867 9,746 0.8 11,867 9,746 0.8 Nkansi 0 0 0 0.0 5,540 6,321 5,087 0.8 6,321 5,087 0.8 Sumbawanga Urban 0 0 0 0.0 679 235 276 1.2 235 276 1.2 Total 0 0 0 0.0 18,635 18,967 15,798 0.8 18,967 15,798 0.8 7.2.4 Number of Crop Growing Households, Planted Area (ha) and Finger millet Harevsted (tons) by season and District 2002/03 Agricultural Year. District Finger millet Dry Season Wet Season Total 7.2.3 Number of Crop Growing Households, Planted Area (ha) and Sorghum Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sorghum Dry Season Wet Season Total District Paddy Dry Season Wet Season Total 7.2.2 Number of Crop Growing Households, Planted Area (ha) and Paddy Harevsted (tons) by season and District 2002/03 Agricultural Year. 7.2.1 Number of Crop Growing Households, Planted Area (ha) and Maize Harevsted (tons) by season and District 2002/03 Agricultural Year. District Maize Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 158 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 82 17 20 1.2 17 20 1.2 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 82 17 20 1.2 17 20 1.2 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 224 91 57 0.6 91 57 0.6 Nkansi 0 0 0 0.0 319 161 58 0.4 161 58 0.4 Sumbawanga Urban 0 0 0 0.0 1,794 1,728 1,796 1.0 1,728 1,796 1.0 Total 0 0 0 0.0 2,337 1,979 1,911 1.0 1,979 1,911 1.0 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 29,632 12,483 15,556 1.2 12,483 15,556 1.2 Sumbawanga Rural 0 0 0 0.0 12,877 6,817 10,050 1.5 6,817 10,050 1.5 Nkansi 0 0 0 0.0 10,885 6,165 13,975 2.3 6,165 13,975 2.3 Sumbawanga Urban 0 0 0 0.0 535 146 238 1.6 146 238 1.6 Total 0 0 0 0.0 53,929 25,611 39,818 1.6 25,611 39,818 1.6 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 4,555 1,400 2,548 1.8 1,400 2,548 1.8 Sumbawanga Rural 0 0 0 0.0 3,242 728 1,468 2.0 728 1,468 2.0 Nkansi 0 0 0 0.0 1,525 469 614 1.3 469 614 1.3 Sumbawanga Urban 0 0 0 0.0 208 85 69 0.8 85 69 0.8 Total 0 0 0 0.0 9,530 2,681 4,699 1.8 2,681 4,699 1.8 Dry Season Wet Season Total District Cassava Dry Season Wet Season Total 7.2.8 Number of Crop Growing Households, Planted Area (ha) and Sweet Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sweet Poatatoes 7.2.6 Number of Crop Growing Households, Planted Area (ha) and Wheat Harevsted (tons) by season and District 2002/03 Agricultural Year. District Wheat Dry Season Wet Season Total 7.2.7 Number of Crop Growing Households, Planted Area (ha) and Cassava Harevsted (tons) by season and District 2002/03 7.2.5 Number of Crop Growing Households, Planted Area (ha) and Bulrush Millet Harevsted (tons) by season and District 2002/03 Agricultural Year. District Bulrush Millet Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 159 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 331 49 70 1.4 49 70 1.4 Nkansi 0 0 0 0.0 409 149 618 4.1 149 618 4.1 Sumbawanga Urban 0 0 0 0.0 624 85 343 4.1 85 343 4.1 Total 0 0 0 0.0 1,364 282 1,031 3.7 282 1,031 3.7 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 33 13 127 9.5 13 127 9.5 Total 0 0 0 0.0 33 13 127 9.5 13 127 9.5 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 7 27 4.0 7 27 4.0 Total 0 0 0 0.0 34 7 27 4.0 7 27 4.0 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 24,142 10,255 5,210 0.0 0 0 0.0 Sumbawanga Rural 118 240 24 0.1 30,821 17,142 8,029 0.5 17,382 8,053 0.5 Nkansi 80 32 19 0.6 15,056 6,810 2,747 0.4 6,843 2,767 0.4 Sumbawanga Urban 35 7 1 0.1 8,197 3,043 1,278 0.4 3,050 1,279 0.4 Total 233 279 44 0.2 78,216 37,251 17,265 0.5 37,530 17,308 0.5 7.2.12 Number of Crop Growing Households, Planted Area (ha) and Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Beans Dry Season Wet Season Total Coco Yams Dry Season Wet Season Total Yams Dry Season Wet Season Total 7.2.11 Number of Crop Growing Households, Planted Area (ha) and Coco Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District 7.2.9 Number of Crop Growing Households, Planted Area (ha) andIrish Potatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Irish Poatatoes Dry Season Wet Season Total 7.2.10 Number of Crop Growing Households, Planted Area (ha) and Yams Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 160 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 82 33 30 0.5 33 30 0.5 Sumbawanga Urban 0 0 0 0.0 69 35 17 1.3 35 17 1.3 Total 0 0 0 0.0 151 68 47 0.7 68 47 0.7 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 120 102 151 1.5 102 151 1.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 1.5 0 0 1.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 266 108 93 0.9 108 93 0.9 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 266 108 93 0.9 108 93 0.9 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 112 23 11 0.5 23 11 0.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 112 23 11 0.5 23 11 0.5 Dry Season Bambaranuts 7.2.13 Number of Crop Growing Households, Planted Area (ha) and Cowpeas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cowpeas Dry Season Wet Season Total Total 7.2.14 Number of Crop Growing Households, Planted Area (ha) and Green Gram Harevsted (tons) by season and District 2002/03 Agricultural Year. District Green gram Dry Season Wet Season Total 7.2.15 Number of Crop Growing Households, Planted Area (ha) and Bambaranuts Harevsted (tons) by season and District 2002/03 Agricultural Year. District Wet Season Total 7.2.16 Number of Crop Growing Households, Planted Area (ha) and Field Peas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Field Peas Dry Season Wet Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 161 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 27 24 0.9 27 24 0.9 Sumbawanga Rural 118 288 142 0.5 11,912 7,646 3,976 0.5 7,934 4,118 0.5 Nkansi 0 0 0 0.0 3,757 1,938 973 0.5 1,938 973 0.5 Sumbawanga Urban 35 7 4 0.6 4,156 1,852 984 0.5 1,859 988 0.5 Total 153 295 146 0.5 19,960 11,463 5,957 0.5 11,758 6,103 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 27 24 0.9 27 24 0.9 Sumbawanga Rural 118 288 142 0.5 11,912 7,646 3,976 0.5 7,934 4,118 0.5 Nkansi 0 0 0 0.0 3,757 1,938 973 0.5 1,938 973 0.5 Sumbawanga Urban 35 7 4 0.6 4,156 1,852 984 0.5 1,859 988 0.5 Total 153 295 146 0.5 19,960 11,463 5,957 0.5 11,758 6,103 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 20,702 9,874 6,617 0.7 9,874 6,617 0.7 Sumbawanga Rural 118 48 71 1.5 18,728 5,136 2,820 0.5 5,184 2,891 0.6 Nkansi 0 0 0 0.0 4,654 1,333 1,535 1.2 1,333 1,535 1.2 Sumbawanga Urban 0 0 0 0.0 913 180 84 0.5 180 84 0.5 Total 118 48 71 1.5 44,997 16,522 11,055 0.7 16,570 11,126 0.7 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 269 68 139 2.0 68 139 2.0 Sumbawanga Rural 0 0 0 0.0 225 46 5 0.1 46 5 0.1 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 14 10 0.7 14 10 0.7 Total 0 0 0 0.0 528 127 154 1.2 127 154 1.2 7.2.17 Number of Crop Growing Households, Planted Area (ha) and Sunflower Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.18 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.19 Number of Crop Growing Households, Planted Area (ha) and Simsim Harevsted (tons) by season and District 2002/03 Agricultural Year. District Sunflower Dry Season Wet Season Total 7.2.20 Number of Crop Growing Households, Planted Area (ha) and Soya Beans Harevsted (tons) by season and District 2002/03 Agricultural Year. District Soya Beans Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 162 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 270 68 443 6.5 68 443 6.5 Sumbawanga Rural 0 0 0 0.0 451 68 365 5.4 68 365 5.4 Nkansi 0 0 0 0.0 244 20 74 3.7 20 74 3.7 Sumbawanga Urban 0 0 0 0.0 754 110 257 2.3 110 257 2.3 Total 0 0 0 0.0 1,718 266 1,139 4.3 266 1,139 4.3 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 135 14 40 3.0 14 40 3.0 Sumbawanga Rural 0 0 0 0.0 326 60 451 7.6 60 451 7.6 Nkansi 0 0 0 0.0 234 60 59 1.0 60 59 1.0 Sumbawanga Urban 0 0 0 0.0 338 42 189 4.5 42 189 4.5 Total 0 0 0 0.0 1,032 176 739 4.2 176 739 4.2 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 803 173 331 1.9 173 331 1.9 Sumbawanga Rural 0 0 0 0.0 1,715 245 1,122 4.6 245 1,122 4.6 Nkansi 0 0 0 0.0 164 35 33 0.9 35 33 0.9 Sumbawanga Urban 0 0 0 0.0 818 129 651 5.0 129 651 5.0 Total 0 0 0 0.0 3,499 583 2,136 3.7 583 2,136 3.7 No.of H/holds Planted Area (ha) Quantity Harveste d (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 134 22 61 2.8 22 61 2.8 Sumbawanga Rural 0 0 0 0.0 218 22 4 0.2 22 4 0.2 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 68 7 3 0.4 7 3 0.4 Total 0 0 0 0.0 420 51 68 1.3 51 68 1.3 7.2.21 Number of Crop Growing Households, Planted Area (ha) and Onions Harevsted (tons) by season and District 2002/03 Agricultural Year. District Onions Dry Season Wet Season Total 7.2.22 Number of Crop Growing Households, Planted Area (ha) and Cabbage Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cabbage Dry Season Wet Season Total 7.2.23 Number of Crop Growing Households, Planted Area (ha) and Tomatoes Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tomatoes Dry Season Wet Season Total 7.2.24 Number of Crop Growing Households, Planted Area (ha) and Spinach Harevsted (tons) by season and District 2002/03 Agricultural Year. District Spinach Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 34 3 7 2.1 3 7 2.1 Total 0 0 0 0.0 34 3 7 2.1 3 7 2.1 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 536 52 87 1.7 52 87 1.7 Sumbawanga Rural 0 0 0 0.0 452 60 11 0.2 60 11 0.2 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 169 13 11 0.9 13 11 0.9 Total 0 0 0 0.0 1,157 125 110 0.9 125 110 0.9 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Rural 0 0 0 0.0 215 22 12 0.5 22 12 0.5 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 215 22 12 0.5 22 12 0.5 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 128 39 13 0.3 39 13 0.3 Sumbawanga Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 128 39 13 0.3 39 13 0.3 7.2.25 Number of Crop Growing Households, Planted Area (ha) and Carrot Harevsted (tons) by season and District 2002/03 Agricultural Year. District Carrot Dry Season Wet Season Total 7.2.26 Number of Crop Growing Households, Planted Area (ha) and Amaranthas Harevsted (tons) by season and District 2002/03 Agricultural Year. District Amaranthas Dry Season Wet Season Total 7.2.27 Number of Crop Growing Households, Planted Area (ha) and Pumpkins Harevsted (tons) by season and District 2002/03 Agricultural Year. District Pumpkins Dry Season Wet Season Total 7.2.28 Number of Crop Growing Households, Planted Area (ha) and Cotton Harevsted (tons) by season and District 2002/03 Agricultural Year. District Cotton Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 164 No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) No.of H/holds Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Planted Area (ha) Quantity Harvested (tons) Yield (ton/ha) Mpanda 0 0 0 0.0 4,700 3,233 3,209 1.0 3,233 3,209 1.0 Sumbawanga Rural 0 0 0 0.0 118 24 41 1.7 24 41 1.7 Nkansi 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Sumbawanga Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 4,818 3,256 3,251 1.0 3,256 3,251 1.0 7.2.29 Number of Crop Growing Households, Planted Area (ha) and Tobacco Harevsted (tons) by season and District 2002/03 Agricultural Year. District Tobacco Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 165 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 166 District/Crop Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Mangostine . . 12 Pigeon Pea 162 162 40 247 Palm Oil 138 72 2,063 28,598 Coconut . . . 0 Rubber . . 72 0 Sugarcane 22 22 16 741 Mpesheni . . 83 0 Banana 694 299 5,978 20,005 Avocado . . 9 0 Mango 392 283 10,753 38,048 Pawpaw 21 43 1,236 28,751 Orange 81 630 1,343 2,133 Grape Fruit 22 . . 0 Mandarine/Tangerine . . 32 0 Guava 29 38 363 9,512 Lime/Lemon 3,866 5 41 7,581 Total 5,429 1,554 22,040 14,182 Pigeon Pea . 48 57 1,200 Star Fruit . 0 207 0 Palm Oil . . 289 0 Coconut 2 0 37 0 Coffee 24 24 7 296 Sugarcane 1,356 3,946 43,680 11,069 Banana 758 506 4,132 8,168 Avocado . . 15 0 Mango 155 79 4,180 52,749 Pawpaw . . 12 0 Pineapple . . 2 0 Orange 36 26 160 6,072 Mandarine/Tangerine . . . 0 Guava 120 0 173 0 Pears 6 5 1 247 Lime/Lemon . . . 0 Total 2,456 4,635 52,954 11,426 Palm Oil . 8 54 7,008 Coconut 16 16 14 911 Sugarcane 74 57 681 11,873 Jack Fruit . . 4 0 Banana 66 82 602 7,338 Mango . 2,020 638 316 Pawpaw . 0 9 0 Orange . 4 61 15,385 Guava . 0 85 0 Lime/Lemon . . 7 0 Total 155 2,187 2,156 986 Nkansi 7.3 Production of Permanent Crops by Crop Type and District, Rukwa Region Mpanda Sumbawanga Rural Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 167 Sour Soup 7 0 . 0 Coconut 42 42 10 247 Coffee 10 . . 0 Sugarcane 346 301 10,261 34,060 Cardamon 3 3 2 504 Mpesheni . 0 0 0 Banana 272 124 759 6,138 Avocado . . 1 0 Orange 73 10 4 364 Guava 5 8 28 3,438 Plums . 0 3 0 Pitches . 1 5 3,952 Lime/Lemon 11 12 85 7,002 Total 770 503 11,159 22,189 Sour Soup 7 0 . 0 Mangostine . . 12 0 Pigeon Pea 162 210 98 464 Star Fruit . 0 207 0 Palm Oil 138 80 2,405 30,144 Coconut 60 58 62 1,064 Coffee 35 24 7 296 Rubber . . 72 0 Sugarcane 1,797 4,327 54,638 12,628 Cardamon 3 3 2 504 Jack Fruit . . 4 0 Mpesheni . 0 83 0 Banana 1,790 1,010 11,471 11,353 Avocado . . 25 0 Mango 547 2,382 15,571 6,537 Pawpaw 21 43 1,257 29,248 Pineapple . . 2 0 Orange 190 671 1,569 2,339 Grape Fruit 22 . . 0 Mandarine/Ta. . 32 0 Guava 155 46 649 14,025 Plums . 0 3 0 Pears 6 5 1 247 Pitches . 1 5 3,952 Lime/Lemon 3,877 18 133 7,554 Total 8,810 8,879 88,310 9,946 Sumbawanga Urban Total cont……… Production of Permanent Crops by Crop Type and District, Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 168 Crop Area Planted % Lime/Lemon 3,877 44 Sugarcane 1,797 20 Banana 1,790 20 Mango 547 6 Orange 190 2 Pigeon Pea 162 2 Guava 155 2 Palm Oil 138 2 Coconut 60 1 Coffee 35 0 Grape Fruit 22 0 Pawpaw 21 0 Sour Soup 7 0 Pears 6 0 Cardamon 3 0 Mangostine 0 0 Star Fruit 0 0 Rubber 0 0 Jack Fruit 0 0 Mpesheni 0 0 Avocado 0 0 Pineapple 0 0 Mandarine/Tangerine 0 0 Plums 0 0 Pitches 0 0 Total 8,810 100 cont…..Area Planted by crop Type - Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 169 cont…Planted Area with Fertiliser by Fertiliser Type and crop Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0 0 0 7 7 Pigeon Pea 0 0 0 162 162 Palm Oil 0 0 0 138 138 Coconut 42 0 0 17 60 Coffee 0 0 0 35 35 Sugarcane 444 4 0 1,349 1,797 Cardamon 0 . 0 3 3 Banana 121 3 0 1,665 1,790 Mango 0 0 0 547 547 Pawpaw 0 0 0 21 21 Orange 0 0 0 190 190 Grape Fruit 0 0 0 22 22 Guava 3 0 0 152 155 Pears 0 0 0 6 6 Lime/Lemon 0 0 0 3,877 3,877 Total 611 7 0 8,192 8,810 Mostly Farm Yard Manure Total % Sour Soup 0 7 0.0 Pigeon Pea 0 162 0.0 Palm Oil 0 138 0.0 Coconut 42 60 70.9 Coffee 0 35 0.0 Sugarcane 444 1,797 24.7 Cardamon 0 3 0.0 Banana 121 1,790 6.8 Mango 0 547 0.0 Pawpaw 0 21 0.0 Orange 0 190 0.0 Grape Fruit 0 22 0.0 Guava 3 155 2.2 Pears 0 6 0.0 Lime/Lemon 0 3,877 0.0 Total 611 8,810 6.9 Mostly Compost Total % Sour Soup 0 7 0.0 Pigeon Pea 0 162 0.0 Palm Oil 0 138 0.0 Coconut 0 60 0 Coffee 0 35 0 Sugarcane 4 1,797 0 Cardamon . 3 0 Banana 3 1,790 0 Mango 0 547 0 Pawpaw 0 21 0 Orange 0 190 0 Grape Fruit 0 22 0 Guava 0 155 0 Pears 0 6 0 Lime/Lemon 0 3,877 0.0 Total 7 8,810 0.08 cont…Planted Area with Fertiliser by Fertiliser Type and crop cont…Planted Area with Fertiliser by Fertiliser Type and crop Tanzania Agriculture Sample Census - 2003 Rukwa 170 Appendix II 171 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 172 Number % Number % Number % Mpanda 57,127 96 2,407 4 59,533 100 Sumbawanga Rural 66,890 97 2,045 3 68,935 100 Nkansi 30,037 99 446 1 30,483 100 Sumbawanga Urban 13,101 98 208 2 13,309 100 Total 167,155 97 5,106 3 172,261 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Other By Factory Total Mpanda 9,773 400 46,954 0 0 0 0 57,127 Sumbawanga Rural 6,092 1,396 49,404 119 9,550 331 0 66,890 Nkansi 4,073 1,227 24,416 0 0 0 321 30,037 Sumbawanga Urban 270 375 12,422 0 35 0 0 13,101 Total 20,209 3,397 133,195 119 9,585 331 321 167,155 8.0b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agriculture Year By Method of Processing and District District Method of Processing 8.0a Number of Crop Growing Households reported to have Processed Farm Products by District, 2002/03 agricultural year. Households That Households That Did Not Total District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 173 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 4,956 400 48,099 0 0 0 0 0 53,454 Paddy 3,948 130 8,240 0 0 0 0 0 12,318 Sorghum 261 0 1,173 0 0 0 0 0 1,434 Finger Millet 0 0 798 0 0 0 0 0 798 Cassava 12,313 135 3,861 0 0 0 0 0 16,310 Beans 134 0 0 0 0 0 0 0 134 Sunflower 0 0 134 0 0 0 0 0 134 Groundnut 2,745 0 673 0 0 0 0 0 3,417 Soya Beans 0 0 269 0 0 0 0 0 269 Maize 2,989 1,637 47,050 119 9,441 0 230 0 61,466 Paddy 5,213 929 3,127 0 0 0 316 0 9,584 Sorghum 481 120 5,829 0 109 0 0 0 6,538 Finger Millet 801 118 3,570 0 1,482 0 0 0 5,970 Wheat 0 0 115 0 109 0 0 0 224 Cassava 3,564 229 3,463 0 0 0 0 0 7,257 Sweet Potato 691 0 0 0 0 0 0 0 691 Beans 205 0 119 0 0 0 0 0 324 Sunflower 466 0 1,042 0 3,090 0 0 117 4,714 Groundnut 2,671 0 121 0 0 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 0 0 121 Banana 111 0 0 0 0 0 0 0 111 Maize 1,091 1,238 23,775 0 0 0 0 0 26,104 Paddy 1,035 81 2,078 0 0 0 0 0 3,194 Sorghum 148 208 1,046 0 0 0 0 0 1,402 Finger Millet 813 0 3,775 0 0 0 0 0 4,588 Wheat 0 0 78 0 0 0 0 0 78 Cassava 3,776 126 4,961 0 0 0 0 0 8,864 Sweet Potato 158 0 82 0 0 0 0 0 240 Sunflower 78 80 1,274 0 211 0 0 767 2,411 Groundnut 3,556 0 473 0 0 0 0 0 4,030 Maize 270 375 12,285 0 0 0 0 0 12,930 Sorghum 0 0 99 0 0 0 0 0 99 Finger Millet 68 0 310 0 0 0 0 0 378 Wheat 0 102 621 0 0 0 0 0 723 Cassava 65 0 98 0 0 0 0 0 162 Cocoyams 34 0 0 0 0 0 0 0 34 Sunflower 0 34 676 0 136 34 35 103 1,017 Groundnut 65 0 0 0 0 0 0 0 65 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop Crop Method of Processing Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 174 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,769 120 253 0 0 0 1,070 0 48,243 53,454 Paddy 534 254 954 0 0 0 1,409 110 9,057 12,318 Sorghum 0 0 0 0 0 0 0 0 1,434 1,434 Finger Millet 403 0 0 0 0 0 0 0 394 798 Cassava 1,347 0 0 0 0 0 268 0 14,695 16,310 Beans 134 0 0 0 0 0 0 0 0 134 Sunflower 0 0 0 0 0 0 0 0 134 134 Groundnut 539 134 0 0 0 0 0 0 2,744 3,417 Soya Beans 134 0 0 0 0 0 0 0 135 269 Total 6,862 508 1,207 0 0 0 2,746 110 76,836 88,269 Maize 2,044 121 230 0 353 0 115 0 58,602 61,466 Paddy 593 357 111 0 0 0 0 0 8,522 9,584 Sorghum 0 0 0 0 0 0 0 0 6,538 6,538 Finger Millet 0 0 0 0 0 0 115 0 5,855 5,970 Wheat 0 0 0 0 0 0 0 0 224 224 Cassava 239 0 118 0 0 0 89 0 6,810 7,257 Sweet Potato 0 0 0 0 0 0 0 0 691 691 Beans 0 0 0 0 0 0 0 0 324 324 Sunflower 921 462 0 0 0 0 349 0 2,982 4,714 Groundnut 353 118 0 0 0 0 236 0 2,086 2,792 Oil Palm 0 0 0 0 0 0 0 0 121 121 Banana 111 0 0 0 0 0 0 0 0 111 Total 4,262 1,058 460 0 353 0 905 0 92,754 99,792 Maize 165 0 0 72 76 0 69 0 25,723 26,104 Paddy 148 0 0 0 76 0 0 0 2,970 3,194 Sorghum 0 0 0 0 0 0 0 0 1,402 1,402 Finger Millet 82 0 0 0 0 0 78 0 4,428 4,588 Wheat 78 0 0 0 0 0 0 0 0 78 Cassava 129 0 0 60 0 0 0 0 8,675 8,864 Sweet Potato 0 0 0 0 0 0 0 0 240 240 Sunflower 453 0 0 0 0 0 70 80 1,807 2,411 Groundnut 152 0 0 0 0 0 0 0 3,877 4,030 Total 1,208 0 0 132 151 0 217 80 49,123 50,912 Maize 0 0 0 0 139 34 104 34 12,618 12,930 Sorghum 0 0 0 0 0 0 0 0 99 99 Finger Millet 0 0 0 0 0 0 34 0 344 378 Wheat 0 0 0 0 0 0 0 0 723 723 Cassava 0 0 0 0 0 0 0 0 162 162 Cocoyams 0 0 0 0 0 0 0 0 34 34 Sunflower 172 34 0 35 0 0 34 33 709 1,017 Groundnut 0 32 0 0 0 0 0 0 34 65 Total 172 66 0 35 139 34 172 67 14,724 15,409 Maize 5,978 240 484 72 568 34 1,358 34 145,186 153,954 Paddy 1,276 611 1,065 0 76 0 1,409 110 20,550 25,097 Sorghum 0 0 0 0 0 0 0 0 9,474 9,474 Finger Millet 486 0 0 0 0 0 227 0 11,021 11,734 Wheat 78 0 0 0 0 0 0 0 948 1,026 Cassava 1,715 0 118 60 0 0 357 0 30,342 32,592 Sweet Potato 0 0 0 0 0 0 0 0 931 931 Cocoyams 0 0 0 0 0 0 0 0 34 34 Beans 134 0 0 0 0 0 0 0 324 458 Sunflower 1,547 496 0 35 0 0 454 113 5,632 8,276 Groundnut 1,045 284 0 0 0 0 236 0 8,740 10,305 Oil Palm 0 0 0 0 0 0 0 0 121 121 Soya Beans 134 0 0 0 0 0 0 0 135 269 Banana 111 0 0 0 0 0 0 0 0 111 Total 12,505 1,631 1,667 167 643 34 4,040 257 233,437 254,382 Where Sold Mpanda Sumbawanga Rural 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Nkansi Sumbawanga Urban Total Crop Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 175 District Crop On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 4,956 400 48,099 0 0 0 0 0 53,454 Paddy 3,948 130 8,240 0 0 0 0 0 12,318 Sorghum 261 0 1,173 0 0 0 0 0 1,434 Finger Millet 0 0 798 0 0 0 0 0 798 Cassava 12,313 135 3,861 0 0 0 0 0 16,310 Beans 134 0 0 0 0 0 0 0 134 Sunflower 0 0 134 0 0 0 0 0 134 Groundnut 2,745 0 673 0 0 0 0 0 3,417 Soya Beans 0 0 269 0 0 0 0 0 269 Maize 2,989 1,637 47,050 119 9,441 0 230 0 61,466 Paddy 5,213 929 3,127 0 0 0 316 0 9,584 Sorghum 481 120 5,829 0 109 0 0 0 6,538 Finger Millet 801 118 3,570 0 1,482 0 0 0 5,970 Wheat 0 0 115 0 109 0 0 0 224 Cassava 3,564 229 3,463 0 0 0 0 0 7,257 Sweet Potatoes 691 0 0 0 0 0 0 0 691 Beans 205 0 119 0 0 0 0 0 324 Sunflower 466 0 1,042 0 3,090 0 0 117 4,714 Groundnut 2,671 0 121 0 0 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 0 0 121 Banana 111 0 0 0 0 0 0 0 111 Maize 1,091 1,238 23,775 0 0 0 0 0 26,104 Paddy 1,035 81 2,078 0 0 0 0 0 3,194 Sorghum 148 208 1,046 0 0 0 0 0 1,402 Finger Millet 813 0 3,775 0 0 0 0 0 4,588 Wheat 0 0 78 0 0 0 0 0 78 Cassava 3,776 126 4,961 0 0 0 0 0 8,864 Sweet Potatoes 158 0 82 0 0 0 0 0 240 Sunflower 78 80 1,274 0 211 0 0 767 2,411 Groundnut 3,556 0 473 0 0 0 0 0 4,030 Maize 270 375 12,285 0 0 0 0 0 12,930 Sorghum 0 0 99 0 0 0 0 0 99 Finger Millet 68 0 310 0 0 0 0 0 378 Wheat 0 102 621 0 0 0 0 0 723 Cassava 65 0 98 0 0 0 0 0 162 Cocoyams 34 0 0 0 0 0 0 0 34 Sunflower 0 34 676 0 136 34 35 103 1,017 Groundnut 65 0 0 0 0 0 0 0 65 8.1.1a AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 By Location of Processing and Crop Method of Processing Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 176 d / Human Consumpt ion Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 53,454 0 0 0 0 0 53,454 Paddy 12,318 0 0 0 0 0 12,318 Sorghum 1,434 0 0 0 0 0 1,434 Finger Millet 798 0 0 0 0 0 798 Cassava 16,175 0 0 0 135 0 16,310 Beans 134 0 0 0 0 0 134 Sunflower 134 0 0 0 0 0 134 Groundnut 2,878 539 0 0 0 0 3,417 Soya Beans 135 134 0 0 0 0 269 Total 87,461 674 0 0 135 0 88,269 Maize 60,298 0 582 238 233 115 61,466 Paddy 8,658 122 704 100 0 0 9,584 Sorghum 6,425 0 0 113 0 0 6,538 Finger Millet 5,735 0 235 0 0 0 5,970 Wheat 224 0 0 0 0 0 224 Cassava 6,897 0 239 0 121 0 7,257 Sweet Potatoes 691 0 0 0 0 0 691 Beans 324 0 0 0 0 0 324 Sunflower 3,542 117 940 0 116 0 4,714 Groundnut 2,203 0 589 0 0 0 2,792 Oil Palm 121 0 0 0 0 0 121 Banana 111 0 0 0 0 0 111 Total 95,228 239 3,290 451 469 115 99,792 Maize 26,104 0 0 0 0 0 26,104 Paddy 3,049 0 73 0 73 0 3,194 Sorghum 1,402 0 0 0 0 0 1,402 Finger Millet 4,506 0 0 0 0 82 4,588 Wheat 78 0 0 0 0 0 78 Cassava 8,864 0 0 0 0 0 8,864 Sweet Potatoes 240 0 0 0 0 0 240 Sunflower 2,331 0 80 0 0 0 2,411 Groundnut 4,030 0 0 0 0 0 4,030 Total 50,604 0 153 0 73 82 50,912 Maize 12,930 0 0 0 0 0 12,930 Sorghum 99 0 0 0 0 0 99 Finger Millet 378 0 0 0 0 0 378 Wheat 723 0 0 0 0 0 723 Cassava 162 0 0 0 0 0 162 Cocoyams 0 0 0 0 34 0 34 Sunflower 949 0 68 0 0 0 1,017 Groundnut 65 0 0 0 0 0 65 Total 15,307 0 68 0 34 0 15,409 Maize 152,786 0 582 238 233 115 153,954 Paddy 24,025 122 777 100 73 0 25,097 Sorghum 9,361 0 0 113 0 0 9,474 Finger Millet 11,416 0 235 0 0 82 11,734 Wheat 1,026 0 0 0 0 0 1,026 Cassava 32,098 0 239 0 255 0 32,592 Sweet Potatoes 931 0 0 0 0 0 931 Cocoyams 0 0 0 0 34 0 34 Beans 458 0 0 0 0 0 458 Sunflower 6,956 117 1,088 0 116 0 8,276 Groundnut 9,177 539 589 0 0 0 10,305 Oil Palm 121 0 0 0 0 0 121 Soya Beans 135 134 0 0 0 0 269 Banana 111 0 0 0 0 0 111 Total 248,601 912 3,510 451 710 198 254,382 8.1.1 AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop Product Use Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Total Crop Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 177 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,769 120 253 0 0 0 1,070 0 48,243 53,454 Paddy 534 254 954 0 0 0 1,409 110 9,057 12,318 Sorghum 0 0 0 0 0 0 0 0 1,434 1,434 Finger Millet 403 0 0 0 0 0 0 0 394 798 Cassava 1,347 0 0 0 0 0 268 0 14,695 16,310 Beans 134 0 0 0 0 0 0 0 0 134 Sunflower 0 0 0 0 0 0 0 0 134 134 Groundnut 539 134 0 0 0 0 0 0 2,744 3,417 Soya Beans 134 0 0 0 0 0 0 0 135 269 Total 6,862 508 1,207 0 0 0 2,746 110 76,836 88,269 Maize 2,044 121 230 0 353 0 115 0 58,602 61,466 Paddy 593 357 111 0 0 0 0 0 8,522 9,584 Sorghum 0 0 0 0 0 0 0 0 6,538 6,538 Finger Millet 0 0 0 0 0 0 115 0 5,855 5,970 Wheat 0 0 0 0 0 0 0 0 224 224 Cassava 239 0 118 0 0 0 89 0 6,810 7,257 Sweet Potatoes 0 0 0 0 0 0 0 0 691 691 Beans 0 0 0 0 0 0 0 0 324 324 Sunflower 921 462 0 0 0 0 349 0 2,982 4,714 Groundnut 353 118 0 0 0 0 236 0 2,086 2,792 Oil Palm 0 0 0 0 0 0 0 0 121 121 Banana 111 0 0 0 0 0 0 0 0 111 Total 4,262 1,058 460 0 353 0 905 0 92,754 99,792 Maize 165 0 0 72 76 0 69 0 25,723 26,104 Paddy 148 0 0 0 76 0 0 0 2,970 3,194 Sorghum 0 0 0 0 0 0 0 0 1,402 1,402 Finger Millet 82 0 0 0 0 0 78 0 4,428 4,588 Wheat 78 0 0 0 0 0 0 0 0 78 Cassava 129 0 0 60 0 0 0 0 8,675 8,864 Sweet Potatoes 0 0 0 0 0 0 0 0 240 240 Sunflower 453 0 0 0 0 0 70 80 1,807 2,411 Groundnut 152 0 0 0 0 0 0 0 3,877 4,030 Total 1,208 0 0 132 151 0 217 80 49,123 50,912 Maize 0 0 0 0 139 34 104 34 12,618 12,930 Sorghum 0 0 0 0 0 0 0 0 99 99 Finger Millet 0 0 0 0 0 0 34 0 344 378 Wheat 0 0 0 0 0 0 0 0 723 723 Cassava 0 0 0 0 0 0 0 0 162 162 Cocoyams 0 0 0 0 0 0 0 0 34 34 Sunflower 172 34 0 35 0 0 34 33 709 1,017 Groundnut 0 32 0 0 0 0 0 0 34 65 Total 172 66 0 35 139 34 172 67 14,724 15,409 Maize 5,978 240 484 72 568 34 1,358 34 145,186 153,954 Paddy 1,276 611 1,065 0 76 0 1,409 110 20,550 25,097 Sorghum 0 0 0 0 0 0 0 0 9,474 9,474 Finger Millet 486 0 0 0 0 0 227 0 11,021 11,734 Wheat 78 0 0 0 0 0 0 0 948 1,026 Cassava 1,715 0 118 60 0 0 357 0 30,342 32,592 Sweet Potatoes 0 0 0 0 0 0 0 0 931 931 Cocoyams 0 0 0 0 0 0 0 0 34 34 Beans 134 0 0 0 0 0 0 0 324 458 Sunflower 1,547 496 0 35 0 0 454 113 5,632 8,276 Groundnut 1,045 284 0 0 0 0 236 0 8,740 10,305 Oil Palm 0 0 0 0 0 0 0 0 121 121 Soya Beans 134 0 0 0 0 0 0 0 135 269 Banana 111 0 0 0 0 0 0 0 0 111 Total 12,505 1,631 1,667 167 643 34 4,040 257 233,437 254,382 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop Crop Where Sold Mpanda Sumbawanga Rural Nkansi Sumbawanga Urban Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 178 Flour / Meal Grain Oil Juice Rubber Total Mpanda 53,178 3,949 0 0 0 57,127 Sumbawanga Rural 61,492 3,148 2,135 116 0 66,890 Nkansi 27,574 1,911 481 0 71 30,037 Sumbawanga Urban 12,827 69 135 69 0 13,101 Total 155,071 9,077 2,751 185 71 167,155 Household / Human Consumption Sale Only Animal Consumption Did Not Use Other Total Mpanda 57,127 0 0 0 0 57,127 Sumbawanga Rural 65,380 691 351 354 115 66,890 Nkansi 29,892 73 0 73 0 30,037 Sumbawanga Urban 13,101 0 0 0 0 13,101 Total 165,499 764 351 426 115 167,155 District Product Use 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 179 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Mpanda 3,769 254 593 0 0 0 1,543 0 50,968 57,127 Sumbawanga Rural 2,398 342 230 0 353 0 205 0 63,362 66,890 Nkansi 366 0 0 132 76 0 0 80 29,383 30,037 Sumbawanga Urban 34 0 0 0 139 34 104 34 12,756 13,101 Total 6,568 596 823 132 568 34 1,851 115 156,468 167,155 Bran Cake Husk Juice Fiber Pulp Oil Shell No by- product Other Total Mpanda 19,440 134 6,481 0 133 134 0 1,209 29,461 134 57,127 Sumbawanga Rural 9,309 3,907 4,360 0 0 350 121 817 48,028 0 66,890 Nkansi 658 2,389 2,588 0 72 0 80 2,105 21,995 150 30,037 Sumbawanga Urban 528 851 0 34 0 0 0 0 11,688 0 13,101 Total 29,934 7,281 13,429 34 205 484 201 4,131 111,172 284 167,155 District By Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District, Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa 180 Appendix II 181 MARKETING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 182 Total Number % Number % Number Mpanda 46,242 78 13,292 22 59,533 Sumbawanga Rural 59,911 87 9,024 13 68,935 Nkansi 24,110 79 6,374 21 30,483 Sumbawanga Urban 10,835 81 2,474 19 13,309 Total 141,097 81.9 31,164 18.1 172,261 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Trade Union Problems Regulatory Board Problems Other Not applicable Total Mpanda 1,200 44,338 535 134 0 0 537 12,788 59,533 Sumbawanga Rural 3,294 30,710 456 0 233 115 1,123 32,085 68,016 Nkansi 1,408 15,404 0 0 0 82 958 12,510 30,362 Sumbawanga Urban 547 6,545 0 0 69 0 35 6,078 13,275 Total 6,450 96,997 992 134 303 198 2,652 63,461 171,186 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Trade Union Problems Regulatory Board Problems Other Not applicable Total Mpanda 2.02 74.48 0.90 0.23 0.00 0.00 0.90 21.48 100.00 Sumbawanga Rural 4.84 45.15 0.67 0.00 0.34 0.17 1.65 47.17 100.00 Nkansi 4.64 50.73 0.00 0.00 0.00 0.27 3.15 41.20 100.00 Sumbawanga Urban 4.12 49.30 0.00 0.00 0.52 0.00 0.26 45.79 100.00 Total 3.77 56.66 0.58 0.08 0.18 0.12 1.55 37.07 100.00 10.1 Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03, Rukwa Region Households that sold Number of Households that Did not Sell District 10.2 Number of Crop Producing Households Reporting Not Selling Agricultural Products During 2003/04 By Reason for Not Selling Crops By District District Main Reasons for Not Selling Crops District Main Reasons for Not Selling Crops 10.3 Proportion of Households who Reported Not Selling Their Crops by District During 2002/03 Agricultural Year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 183 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 184 Total Number of Household % Number of Household % Number of Household Mpanda 3,343 6 56,190 94 59,533 Sumbawanga Rural 8,564 12 60,371 88 68,935 Nkansi 1,718 6 28,766 94 30,483 Sumbawanga Urban 3,258 24 10,051 76 13,309 Total 16,883 10 155,378 90 172,261 District Irrigated Area Area Irrigated Land this Year % Mpanda 915 844 92 Sumbawanga Rural 9,278 5,487 59 Nkansi 799 462 58 Sumbawanga Urban 1,588 730 46 Total 12,578 7,523 60 River Lake Dam Well Borehole Canal Total Mpanda 1,877 0 0 1,065 401 0 3,343 Sumbawanga Rural 7,058 0 344 592 0 571 8,564 Nkansi 788 148 0 474 0 307 1,718 Sumbawanga Urban 1,502 0 0 1,005 35 715 3,258 Total 11,225 148 344 3,137 435 1,593 16,883 Gravity Hand Bucket Hand Pump Motor Pump Other Total Mpanda 1,204 2,006 133 0 0 3,343 Sumbawanga Rural 7,296 1,150 0 0 118 8,564 Nkansi 1,099 541 0 78 0 1,718 Sumbawanga Urban 1,429 1,277 0 68 484 3,258 Total 11,028 4,974 133 146 602 16,883 Table 11.1: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year By District Households Practicing Irrigation Households not Practicing Irrigation 11.4: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District District Method of Obtaining Water 11.2: Area (ha)of Irrigated and Non Irrigatable (ha) Land By District 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 185 Flood Sprinkler Water Hose Bucket / Watering Can Total Mpanda 1,206 0 133 2,004 3,343 Sumbawanga Rural 7,305 0 115 1,144 8,564 Nkansi 1,027 76 0 615 1,718 Sumbawanga Urban 1,843 67 0 1,348 3,258 Total 11,381 143 248 5,111 16,883 % 67 1 1 30 100 Number % Number % Number % Mpanda 6,967 12 52,566 88 59,533 100 Sumbawanga Rural 5,546 8 63,389 92 68,935 100 Nkansi 1,549 5 28,934 95 30,483 100 Sumbawanga Urban 2,143 16 11,166 84 13,309 100 Total 16,206 9 156,055 91 172,261 100 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Mpanda . 105,686 . . 532 28,191 2,000 . 136,409 Sumbawanga Rural . 111,614 . . 595 8,675 2,315 723 123,923 Nkansi 0 3,452 . . . 73 606 234 4,365 Sumbawanga Urban 136 2,414 . 299 208 964 1,783 . 5,804 Total 136 223,167 . 299 1,336 37,903 6,705 957 270,502 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control 11.5 IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District District Method of Application Total 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District District Does the Household Have Any Erosion Control/Water Harvesting Have facility Does Not Have Tanzania Agriculture Sample Census - 2003 Rukwa 186 Appendix II 187 ACCESS TO INPUTS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 188 No. of Households % No. of Households % Mpanda 9,261 16 50,273 84 59,533 Sumbawanga Rural 454 1 68,363 99 68,817 Nkasi 439 1 29,964 99 30,403 Sumbawanga Urban 949 7 12,360 93 13,309 Total 11,103 6 160,960 94 172,063 No. of Households % No. of Households % Mpanda 2,273 4 57,260 96 59,533 Sumbawanga Rur 9,319 14 59,616 86 68,935 Nkasi 2,940 10 27,623 90 30,563 Sumbawanga Urb 5,434 41 7,875 59 13,309 Total 19,966 12 152,375 88 172,341 No. of Households % No. of Households % Mpanda 666 1 58,867 99 59,533 Sumbawanga Rur 1,406 2 67,529 98 68,935 Nkasi 686 2 29,797 98 30,483 Sumbawanga Urb 540 4 12,769 96 13,309 Total 3,298 2 168,962 98 172,261 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Total Crop Growing Households Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year NOT Using Chemical Fertilizers Using Chemical Fertilizers District Farm Yard Manure NOT Using Farm Yard Manure Total Crop Growing Households Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Using COMPOST Manure NOT Using COMPOST Manure Total Crop Growing Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 189 No. of Households % No. of Households % Mpanda 4,699 8 54,834 92 59,533 Sumbawanga Rural 6,263 9 62,672 91 68,935 Nkasi 1,504 5 28,980 95 30,483 Sumbawanga Urban 7,038 53 6,271 47 13,309 Total 19,503 11 152,758 89 172,261 No. of Households % No. of Households % Mpanda 269 0 59,264 100 59,533 Sumbawanga Rur 0 0 68,935 100 68,935 Nkasi 0 0 30,483 100 30,483 Sumbawanga Urb 0 0 13,309 100 13,309 Total 269 0 171,991 100 172,261 No. of Households % No. of Households % Mpanda 5,977 10 53,556 90 59,533 Sumbawanga Rur 1,869 3 67,067 97 68,935 Nkasi 388 1 30,096 99 30,483 Sumbawanga Urb 784 6 12,525 94 13,309 Total 9,018 5 163,243 95 172,261 Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Using Improved SeedsNOT Using Improved Seed Total number of Growing Households Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Using Herbicides Number of Agricultural Households NOT Using Herbicides Total number of Growing Households Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Using Insecticide/Fungicides NOT Using Pesticides/Fungicides Total number of Growing Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 190 Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Not applicable Total Number % Number % Number % Number % Number % Number % Number Mpanda 2,694 5 395 1 4,691 8 134 0 1,347 2 50,273 84 59,533 Sumbawanga Rural 0 0 0 0 454 1 0 0 0 0 68,363 99 68,817 Nkasi 0 0 0 0 439 1 0 0 0 0 29,964 99 30,403 Sumbawanga Urban 0 0 0 0 949 7 0 0 0 0 12,360 93 13,309 Total 2,694 2 395 0 6,533 4 134 0 1,347 1 160,960 94 172,063 Local Market / Trade Store Secondary Market Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 135 0 0 0 0 0 0 0 0 0 1,735 3 403 1 0 0 57,260 96 59,533 Sumbawanga Rural 233 0 224 0 121 0 0 0 0 0 4,334 6 4,408 6 0 0 59,616 86 68,935 Nkasi 0 0 0 0 0 0 0 0 78 0 1,422 5 1,283 4 157 1 27,623 90 30,563 Sumbawanga Urb 0 0 35 0 70 1 34 0 0 0 3,114 23 2,182 16 0 0 7,875 59 13,309 Total 368 0 258 0 190 0 34 0 78 0 10,605 6 8,275 5 157 0 152,375 88 172,341 Local Market / Trade Store Locally Produce d by Neighbour Not applicable Number % Number % Number % Number % Mpanda 134 0 532 1 0 0 58,867 99 59,533 Sumbawanga Rural 476 1 692 1 238 0 67,529 98 68,935 Nkasi 0 0 611 2 76 0 29,797 98 30,483 Sumbawanga Urb 68 1 472 4 0 0 12,769 96 13,309 Total 679 0 2,306 1 314 0 168,962 98 172,261 Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year District Total Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Local Farmers Group Large Scale Farm Locally Produced by Household Co-operative Neighbour Other Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 191 District Co- operative Local Farmers Group Local Market / Trade Store Secondary Market Crop Buyers Large Scale Farm Locally Produced by Household Neighbour Not applicable Total Number % Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 2,155 4 261 0 1,611 3 0 0 672 1 0 0 0 0 0 0 54,834 92 59,533 Sumbawanga Rur 0 0 115 0 4,141 6 230 0 0 0 0 0 1,186 2 591 1 62,672 91 68,935 Nkasi 0 0 0 0 1,106 4 316 1 0 0 82 0 0 0 0 0 28,980 95 30,483 Sumbawanga Urb 34 0 101 1 4,445 33 69 1 35 0 0 0 2,250 17 103 1 6,271 47 13,309 Total 2,190 1 477 0 11,303 7 616 0 706 0 82 0 3,436 2 694 0 152,758 89 172,261 District Local Market / Trade Store Crop Buyers Not applicable Total Number % Number % Number % Number Mpanda 135 0 135 0 59,264 100 59,533 Sumbawanga Rur 0 0 0 0 68,935 100 68,935 Nkasi 0 0 0 0 30,483 100 30,483 Sumbawanga Urb 0 0 0 0 13,309 100 13,309 Total 135 0 135 0 171,991 100 172,261 District Co- operative Local Farmers Group Local Market / Trade Store Development Project Crop Buyers Large Scale Farm Neighbour Not applicable Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,886 3 261 0 2,626 4 128 0 1,077 2 0 0 0 0 53,556 90 59,533 Sumbawanga Rur 0 0 0 0 1,354 2 0 0 0 0 0 0 515 1 67,067 97 68,935 Nkasi 0 0 0 0 306 1 0 0 0 0 82 0 0 0 30,096 99 30,483 Sumbawanga Urb 0 0 0 0 750 6 0 0 35 0 0 0 0 0 12,525 94 13,309 Total 1,886 1 261 0 5,036 3 128 0 1,111 1 82 0 515 0 163,243 95 172,261 Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 192 District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 941 10 1,209 13 2,551 28 2,955 32 1,605 17 9,261 Sumbawanga Rural 0 0 0 0 0 0 0 0 454 100 454 Nkasi 0 0 297 68 0 0 72 16 70 16 439 Sumbawanga Urban 67 7 69 7 543 57 169 18 100 11 949 Total 1,008 9 1,576 14 3,094 28 3,195 29 2,230 20 11,103 District Less than 1 km Between 1 and 3 km Between 3 and 10 km 20 km and Above Total Number % Number % Number % Number % Number Mpanda 2,004 88 135 6 0 0 134 6 2,273 Sumbawanga Rural 6,441 69 1,848 20 1,031 11 0 0 9,319 Nkasi 2,453 83 243 8 165 6 78 3 2,940 Sumbawanga Urban 4,385 81 612 11 437 8 0 0 5,434 Total 15,283 77 2,838 14 1,632 8 213 1 19,966 Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertil Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 193 Less than 1 km Between 1 and 3 km Number % Number % Mpanda 666 100 0 0 666 Sumbawanga Rural 1,297 92 0 0 1,297 Nkasi 611 89 76 11 686 Sumbawanga Urban 371 69 33 6 405 Total 2,946 89 109 3 3,054 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 135 2 940 16 1,210 20 1,471 25 2,221 37 5,977 Sumbawanga Rur 317 17 107 6 542 29 0 0 903 48 1,869 Nkasi 0 0 0 0 0 0 153 40 234 60 388 Sumbawanga Urb 0 0 34 4 475 61 68 9 208 27 784 Total 452 5 1,081 12 2,226 25 1,693 19 3,566 40 9,018 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number % Number % Number % Number % Number % Number Mpanda 135 3 1,209 26 809 17 1,345 29 1,201 26 4,699 Sumbawanga Rur 1,296 21 460 7 471 8 468 7 3,569 57 6,263 Nkasi 149 10 82 5 407 27 0 0 867 58 1,504 Sumbawanga Urb 1,734 25 581 8 2,447 35 862 12 1,414 20 7,038 Total 3,313 17 2,332 12 4,134 21 2,675 14 7,050 36 19,503 District Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Total Number District Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 194 Total Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,574 3 36,226 72 778 1.5 0 0.0 269 0.5 11,299 22.5 128 0.3 50,273 Sumbawanga Rural 10,835 16 43,471 64 1,204 1.8 109 0.2 1,769 2.6 10,540 15.4 435 0.6 68,363 Nkasi 6,028 20 19,705 66 78 0.3 0 0.0 1,935 6.5 2,218 7.4 0 0.0 29,964 Sumbawanga Urban 311 3 11,614 94 34 0.3 0 0.0 70 0.6 297 2.4 34 0.3 12,360 Total 18,748 12 111,016 69 2,094 1.3 109 0.1 4,043 2.5 24,353 15.1 597 0.4 160,960 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 26,484 46 3,994 7 11,704 20 1,210 2 2,945 5 10,520 18 135 0 270 0 57,260 Sumbawanga Rural 5,333 9 4,586 8 28,681 48 10,556 18 2,454 4 6,848 11 0 0 1,158 2 59,616 Nkasi 4,938 18 2,021 7 14,055 51 1,538 6 2,251 8 2,494 9 0 0 327 1 27,623 Sumbawanga Urban 2,676 34 912 12 2,297 29 1,853 24 69 1 0 0 0 0 68 1 7,875 Total 39,431 26 11,513 8 56,736 37 15,157 10 7,719 5 19,861 13 135 0 1,823 1 152,375 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 1,733 3 4,137 7 18,643 32 2,273 4 20,896 35 10,916 19 0 0 269 0 58,867 Sumbawanga Rur 2,950 4 2,838 4 20,937 31 7,945 12 24,297 36 6,822 10 1,049 2 691 1 67,529 Nkasi 3,751 13 1,761 6 8,556 29 384 1 12,490 42 2,691 9 0 0 163 1 29,797 Sumbawanga Urb 2,011 16 905 7 3,002 24 1,411 11 5,239 41 202 2 0 0 0 0 12,769 Total 10,445 6 9,642 6 51,138 30 12,013 7 62,922 37 20,631 12 1,049 1 1,123 1 168,962 Input is of No Use Locally Produced by Household Other Other Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 195 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 8,422 15 40,479 74 1,040 2 245 0 269 0 4,252 8 0 0 128 0 54,834 Sumbawanga Rural 14,759 24 38,491 61 1,169 2 352 1 3,005 5 4,212 7 0 0 683 1 62,672 Nkasi 7,282 25 17,512 60 235 1 242 1 2,347 8 1,363 5 0 0 0 0 28,980 Sumbawanga Urban 1,142 18 4,489 72 103 2 0 0 66 1 403 6 35 1 34 1 6,271 Total 31,605 21 100,971 66 2,547 2 838 1 5,687 4 10,230 7 35 0 845 1 152,758 Total Number % Number % Number % Number % Number % Number % Number % Number Mpanda 12,565 21 40,102 68 1,042 2 0 0 674 1 4,500 8 381 1 59,264 Sumbawanga Rural 18,549 27 28,428 41 941 1 235 0 15,179 22 5,032 7 571 1 68,935 Nkasi 8,833 29 17,691 58 244 1 0 0 2,262 7 1,453 5 0 0 30,483 Sumbawanga Urban 173 1 9,195 69 208 2 0 0 2,359 18 1,339 10 34 0 13,309 Total 40,121 23 95,416 55 2,435 1 235 0 20,475 12 12,324 7 986 1 171,991 Total Number % Number % Number % Number % Number % Number % Number % Number % Number Mpanda 8,739 16 40,567 76 638 1 0 0 134 0 3,082 6 134 0 262 0 53,556 Sumbawanga Rural 23,987 36 37,828 56 934 1 235 0 1,861 3 1,757 3 0 0 464 1 67,067 Nkasi 6,799 23 19,916 66 395 1 240 1 1,483 5 1,102 4 161 1 0 0 30,096 Sumbawanga Urban 2,640 21 9,302 74 172 1 35 0 69 1 169 1 70 1 69 1 12,525 Total 42,165 26 107,613 66 2,138 1 510 0 3,547 2 6,109 4 365 0 796 0 163,243 Locally Produced by Household Other Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Locally Produced by Household Other Input is of No Use Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 196 Total Number % Number % Number % Number % Number Mpanda 3,086 33 5,639 61 536 6 0 0 9,261 Sumbawanga Rural 117 26 117 26 220 49 0 0 454 Nkasi 70 16 369 84 0 0 0 0 439 Sumbawanga Urban 239 25 576 61 68 7 66 7 949 Total 3,512 32 6,701 60 824 7 66 1 11,103 Total Number % Number % Number % Number % Number Mpanda 1,208 53 930 41 135 6 0 0 2,273 Sumbawanga Rural 3,141 34 5,423 58 648 7 107 1 9,319 Nkasi 1,039 35 1,822 62 78 3 0 0 2,940 Sumbawanga Urban 1,844 34 3,452 64 138 3 0 0 5,434 Total 7,233 36 11,627 58 999 5 107 1 19,966 Total Number % Number % Number % Number % Number Mpanda 0 0 539 81 0 0 128 19 666 Sumbawanga Rural 0 0 1,182 84 224 16 0 0 1,406 Nkasi 0 0 611 89 76 11 0 0 686 Sumbawanga Urban 35 6 370 69 135 25 0 0 540 Total 35 1 2,702 82 434 13 128 4 3,298 Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 197 Total Number % Number % Number % Number Mpanda 1,744 37 2,955 63 0 0 4,699 Sumbawanga Rural 1,024 16 4,293 69 946 15 6,263 Nkasi 230 15 1,274 85 0 0 1,504 Sumbawanga Urban 2,239 32 4,595 65 204 3 7,038 Total 5,236 27 13,116 67 1,150 6 19,503 Total Number % Number Mpanda 269 100 269 Total 269 100 269 Total Total Number % Number % Number % Number % Number Number % Number % Number Mpanda 932 16 5,045 84 0 0 0 0 5,977 Mpanda 14,215 24 45,319 76 59,533 Sumbawanga Rural 352 19 1,277 68 120 6 120 6 1,869 Sumbawanga Rural 10,256 15 58,561 85 68,817 Nkasi 70 18 317 82 0 0 0 0 388 Nkasi 3,265 11 27,139 89 30,403 Sumbawanga Urban 309 39 440 56 35 4 0 0 784 Sumbawanga Urban 1,847 14 11,462 86 13,309 Total 1,665 18 7,079 78 155 2 120 1 9,018 Total 29,582 17 142,480 83 172,063 Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Number of Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average District Excellent Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Poor District Excellent Good Average Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 198 Total Number % Number % Number Mpanda 2,794 5 56,739 95 59,533 Sumbawanga Rural 19,435 28 49,500 72 68,935 Nkasi 6,710 22 23,854 78 30,563 Sumbawanga Urban 7,162 54 6,147 46 13,309 Total 36,102 21 136,239 79 172,341 Total Number % Number % Number Mpanda 1,060 2 58,474 98 59,533 Sumbawanga Rural 4,615 7 64,321 93 68,935 Nkasi 1,470 5 29,013 95 30,483 Sumbawanga Urban 813 6 12,496 94 13,309 Total 7,958 5 164,302 95 172,261 Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year COMPOST Manure Agricultural Households With NO Plan to use Next Year COMPOST Manure Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 199 Total Number % Number % Number Mpanda 6,152 10 53,381 90 59,533 Sumbawanga Rural 15,043 22 53,892 78 68,935 Nkasi 3,496 11 26,987 89 30,483 Sumbawanga Urban 8,071 61 5,238 39 13,309 Total 32,762 19 139,499 81 172,261 Total Number % Number % Number Mpanda 1,185 2 58,348 98 59,533 Sumbawanga Rural 1,624 2 67,312 98 68,935 Nkasi 705 2 29,779 98 30,483 Sumbawanga Urban 35 0 13,274 100 13,309 Total 3,549 2 168,712 98 172,261 Total Number % Number % Number Mpanda 7,039 12 52,494 88 59,533 Sumbawanga Rural 9,022 13 59,913 87 68,935 Nkasi 2,291 8 28,192 92 30,483 Sumbawanga Urban 1,821 14 11,488 86 13,309 Total 20,175 12 152,086 88 172,261 Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved District Agricultural Households With Plan to use Next Year Improved Seeds Agricultural Households With NO Plan to use Next Year Improved Seeds Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Pesticides/Fungicides Agricultural Households With NO Plan to use Next Year Pesticides/Fungicides Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Herbicides Agricultural Households With NO Plan to use Next Year Herbicides Tanzania Agriculture Sample Census - 2003 Rukwa 200 Appendix II 201 AGRICULTURE CREDITS Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 202 Number % Number % Mpanda 4,552 94 270 6 4,821 Sumbawanga Rural 2,146 95 116 5 2,261 Nkansi 0 0 80 100 80 Sumbawanga Urban 135 67 67 33 202 Total 6,833 93 533 7 7,365 % 93 7 District Family, Friend and Relative Co- operative Trader / Trade Store Private Individual Religious Organisation / NGO / Project Total Mpanda 653 2,685 1,616 0 0 4,954 Sumbawanga Rural 1,174 0 966 121 0 2,261 Nkansi 80 0 0 0 0 80 Sumbawanga Urban 34 0 34 34 101 202 Total 1,941 2,685 2,616 155 101 7,499 % 26 36 35 2 1 100 13.2c: AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District Total 13.2a: AGRICULTURE CREDIT: Number of Households Receiving Credit By Sex of Household Member Receiving Credit By District District Male Female Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 203 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucrac y procedure Credit granted too late Don't know about credit Total Mpanda 2,395 10,223 5,567 2,355 19,074 3,151 0 11,814 54,579 Sumbawanga Rural 2,296 27,400 11,635 1,772 11,677 567 115 11,211 66,674 Nkansi 999 9,302 2,750 881 9,917 313 76 6,165 30,403 Sumbawanga Urban 508 4,732 1,947 654 2,912 444 202 1,706 13,107 Total 6,198 51,657 21,899 5,662 43,580 4,476 393 30,897 164,762 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Other Mpanda 388 2,285 3,898 2,143 1,078 537 0 Sumbawanga Rural 2,025 0 0 0 0 0 237 Nkansi 80 0 0 0 0 0 0 Sumbawanga Urban 101 68 68 67 101 0 34 Total Credits 2,594 2,353 3,966 2,210 1,178 537 270 13.1a: AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District 13.1b: AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District Tanzania Agriculture Sample Census - 2003 Rukwa 204 Appendix II 205 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 206 Eucalyptus Spp Senna Spp Gravellis Afzelia Quanzensi s Jakaranda Spp Acacia Spp Cyprus Spp Trichilia Spp Pinus Spp Azadrit achta Spp Melicia excelsa Casuri na Equiset filia Tectona Grandis Leucena Spp Syszygiu m Spp Calophylum Inophyllum Total 342 1,480 419 . 3 . . . . 2 5 . . . . . 2,251 3,487 22 . . 23 8 . . 3 6 . . . . 2 . 3,551 2,593 276 24 . 152 . 69 10 10 . . 5 5 2 . 2 3,148 33,724 . 10 300 67 82 16 . . . . . . . . . 34,199 40,146 1,778 453 300 245 90 85 10 13 8 5 5 5 2 2 2 43,149 93 4 1 1 1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 Number of Househol ds Number of Trees Number of Household s Number of Trees Number of Househol ds Number of Trees Number of Househ olds Number of Trees Mpanda 61 925 43 1,016 2 310 106 2,251 Sumbawanga Rural 33 531 11 1,813 11 1,207 55 3,551 Nkansi 39 462 5 107 11 2,579 55 3,148 Sumbawanga Urban 49 2,354 22 2,091 65 29,754 136 34,199 Total 182 4,272 81 5,027 89 33,850 352 43,149 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 9 0 41 60 1 0 112 Sumbawanga Rural 34 11 0 4 9 2 0 60 Nkansi 17 1 0 27 15 1 1 62 Sumbawanga Urban 84 16 1 42 2 0 0 145 Total 136 37 1 114 86 4 1 379 14.3: ON FARM TREE PLANTING: Main Use of Trees By District District Main Use 14.1: ON FARM TREE PLANTING: Number of Planted Trees By Species and District, Rukwa Region 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 207 0-9 1-19 20-29 30-39 40-49 60+ Total Mpanda 2,281 3,198 2,618 378 0 131 8,606 Sumbawanga Rural 4,364 1,339 1,554 628 0 2,555 10,440 Nkansi 6,357 619 81 493 329 326 8,205 Sumbawanga Urban 5,592 1,950 996 611 136 0 9,285 Total 18,593 7,105 5,250 2,110 465 3,012 36,536 % 51 19 14 6 1 8 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 11 4 59 35 0 2 112 Sumbawanga Rural 6 21 1 26 5 2 0 61 Nkansi 12 10 0 19 18 2 1 62 Sumbawanga Urban 29 30 0 81 3 2 0 145 Total 48 72 5 185 61 6 3 380 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Mpanda 1 9 0 41 60 1 0 112 Sumbawanga Rural 34 11 0 4 9 2 0 60 Nkansi 17 1 0 27 15 1 1 62 Sumbawanga Urban 84 16 1 42 2 0 0 145 Total 136 37 1 114 86 4 1 379 14.6: TREE FARMING: Number of responses by main use of planted trees and District for the 2002/03 agricultural year, Rukwa Region District Main Use 14.5: TREE FARMING: Number of responses by second use of planted trees and District for the 2002/03 District Second Use 14.4: TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) Tanzania Agriculture Sample Census - 2003 Rukwa 208 Appendix II 209 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 210 Total Number of Households Number % Number % Number Mpanda 11,351 19 48,182 81 59,533 Sumbawanga Rural 13,859 20 55,076 80 68,935 Nkansi 1,834 6 28,649 94 30,483 Sumbawanga Urban 2,002 15 11,307 85 13,309 Total 29,046 17 143,215 83 172,261 Total Number % Number % Number % Number % Number Mpanda 667 6 6,021 53 3,023 27 1,640 14 11,351 Sumbawanga Rural 1,661 12 7,930 58 4,151 30 0 0 13,742 Nkansi 225 12 927 51 682 37 0 0 1,834 Sumbawanga Urban 103 5 1,660 83 203 10 35 2 2,002 Total 2,657 9 16,539 57 8,059 28 1,675 6 28,930 Total Number % Number % Number % Number % Number % Number % Number Mpanda 8,141 73 2,405 21 135 1 401 4 135 1 11,217 81 11,217 Sumbawanga Rural 13,037 94 350 3 117 1 355 3 0 0 13,859 80 13,859 Nkansi 1,596 87 82 4 78 4 78 4 0 0 1,834 94 1,834 Sumbawanga Urban 1,761 90 138 7 0 0 33 2 35 2 1,967 85 1,967 Total 24,535 85 2,975 10 330 1 867 3 170 1 28,877 83 28,877 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District District District 15.1 CROP EXTENSION: Number of Households By Quality of Extension Services By District During the 2002/03 agricultural year, Rukwa Region Households Receiving Extension Advice Households Not Receiving Extension Advice Very Good Good Average Poor District 15.3: EXTENSION MESSAGES: Number of Households By Source of Crop Extension Messages By District During 2002/03 Agricultural Year, Rukwa Region Government NGO / Development Project Cooperative Large Scale Farm Other Not Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 211 Government NGO / Development Project Cooperative Large Scale Farm Other Total Househol ds receiving advice Total Number of Households % of total number of households Mpanda 6,231 2,151 135 133 135 8,785 59,533 15 Sumbawanga Rural 11,794 238 0 120 0 12,152 68,935 18 Nkansi 1,362 82 78 78 0 1,601 30,483 5 Sumbawanga Urban 1,693 138 0 33 0 1,864 13,309 14 Total 21,080 2,610 213 364 135 24,402 172,261 14 Government NGO / Development Project Cooperative Large Scale Farm Not applica ble Total Total Number of Households % of total number of households Mpanda 2,112 1,346 134 0 0 3,591 59,533 6 Sumbawanga Rural 8,108 119 117 116 120 8,579 68,935 12 Nkansi 387 82 78 0 70 618 30,483 2 Sumbawanga Urban 1,218 241 0 33 0 1,492 13,309 11 Total 11,825 1,787 329 149 190 14,280 172,261 8 Government NGO / Development Project Cooperative Large Scale Farm Not applica ble Total Total Number of Households % of total number of households Mpanda 1,587 269 0 0 0 1,857 59,533 3 Sumbawanga Rural 7,115 119 117 116 115 7,580 68,935 11 Nkansi 527 82 78 0 0 687 30,483 2 Sumbawanga Urban 881 207 0 0 0 1,088 13,309 8 Total 10,110 676 195 116 115 11,212 172,261 7 15.4: EXTENSION MESSAGES: Number of Households By Receiving Advice on Plant Spacing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District Erosion Control 15.6: EXTENSION MESSAGES: Number of Households By Receiving Advice on the Erosion Control By Source of Messages By District Rukwa Region District Use of Agrochemicals District Spacing 15.5: EXTENSION MESSAGES: Number of Households By Receiving Advice on the Use of Agro-chemicals By Source of Messages By District Rukwa Region Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 212 Government NGO / Development Project Cooperative Large Scale Farm Other Total Total Number of Households % of total number of households Mpanda 1,460 0 135 0 0 1,594 59,533 3 Sumbawanga Rural 10,561 357 0 361 0 11,279 68,935 16 Nkansi 452 82 78 0 0 612 30,483 2 Sumbawanga Urban 1,217 308 0 35 35 1,594 13,309 12 Total 13,689 746 213 396 35 15,080 172,261 9 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 1,998 2,019 133 0 135 4,285 59,533 7 Sumbawanga Rural 5,735 348 0 0 120 6,203 68,935 9 Nkansi 446 82 78 0 0 606 30,483 2 Sumbawanga Urban 1,213 103 0 67 0 1,384 13,309 10 Total 9,392 2,553 212 67 255 12,478 172,261 7 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 5,516 1,616 0 0 135 7,267 59,533 12 Sumbawanga Rural 8,837 822 115 0 120 9,893 68,935 14 Nkansi 820 82 0 78 0 980 30,483 3 Sumbawanga Urban 1,384 103 0 0 68 1,555 13,309 12 Total 16,557 2,623 115 78 323 19,696 172,261 11 15.7: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of OrganicFertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Improved seeds By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.8: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Inorganic Fertilisers By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 213 Government NGO / Development Project Not applicable Total Total Number of Households % of total number of households Mpanda 402 0 0 402 59,533 1 Sumbawanga Rural 1,559 0 122 1,681 68,935 2 Nkansi 152 70 0 222 30,483 1 Sumbawanga Urban 0 35 33 68 13,309 1 Total 2,113 105 155 2,373 172,261 1 Government NGO / Development Project Cooperative Large Scale Farm Other Total Total Number of Households % of total number of households Mpanda 529 404 0 133 0 1,066 59,533 2 Sumbawanga Rural 4,520 119 0 120 0 4,758 68,935 7 Nkansi 451 0 78 0 0 529 30,483 2 Sumbawanga Urban 341 104 0 0 35 480 13,309 4 Total 5,840 628 78 253 35 6,834 172,261 4 Government NGO / Development Project Cooperative Large Scale Farm Total Total Number of Households % of total number of households Mpanda 6,548 270 0 0 6,818 59,533 11 Sumbawanga Rural 10,437 119 109 121 10,785 68,935 16 Nkansi 992 0 78 78 1,149 30,483 4 Sumbawanga Urban 1,148 206 0 0 1,354 13,309 10 Total 19,125 595 187 199 20,106 172,261 12 Mechanisation / LST Irrigation Technology 15.9: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Mechanisation By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Crop Storage District District District 15.11: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of Irrigation Technology By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.12: EXTENSION MESSAGES: Number of Households By Receivingf Advice on the use of use of Crop storage By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 214 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Households % of total number of households Mpanda 803 0 0 135 0 938 59,533 2 Sumbawanga Rural 3,700 118 121 121 0 4,060 68,935 6 Nkansi 379 0 78 78 0 536 30,483 2 Sumbawanga Urban 342 35 0 0 35 412 13,309 3 Total 5,225 153 199 334 35 5,946 172,261 3 % 88 3 3 6 1 100 Government NGO / Development Project Other Not applicable Total Total Number of Households % of total number of households Mpanda 1,467 0 135 0 1,602 59,533 3 Sumbawanga Rural 4,820 119 0 0 4,939 68,935 7 Nkansi 299 0 0 0 299 30,483 1 Sumbawanga Urban 207 136 0 35 378 13,309 3 Total 6,793 255 135 35 7,218 172,261 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Mpanda 132 390 135 135 133 0 924 59,533 2 Sumbawanga Rural 3,813 119 121 121 0 121 4,293 68,935 6 Nkansi 377 78 0 0 0 0 455 30,483 1 Sumbawanga Urban 847 237 0 33 0 0 1,116 13,309 8 Total 5,168 823 255 289 133 121 6,789 172,261 4 % 76 12 4 4 2 2 100 District Vermin Control Agro-progressing Agro-Forestry 15.13: EXTENSION MESSAGES: Number of Households By Receivingf Advice on vermin control By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.15: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-Forestry By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. 15.14: EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 215 Government Total Total Number of Households % of total number of households Mpanda 0 0 59,533 0 Sumbawanga Rural 602 602 68,935 1 Nkansi 0 0 30,483 0 Sumbawanga Urban 0 0 13,309 0 Total 602 602 172,261 0 % 100 100 Government Total Total Number of Households % of total number of households Mpanda 0 0 59,533 0.0 Sumbawanga Rural 241 241 68,935 0.4 Nkansi 0 0 30,483 0.0 Sumbawanga Urban 0 0 13,309 0.0 Total 241 241 172,261 0.0 Received Adopted % Received Adopted % Received Adopted % Mpanda 8,785 6,538 74 3,591 2,386 66 1,857 803 43 Sumbawanga Rural 12,152 11,556 95 8,579 3,184 37 7,461 3,331 45 Nkansi 1,601 1,530 96 548 322 59 687 534 78 Sumbawanga Urban 1,864 1,629 87 1,492 1,188 80 1,088 685 63 Total 24,402 21,252 87 14,209 7,080 50 11,093 5,352 48 15.16: EXTENSION MESSAGES: Number of Households By Receiving Advice on Beekeeping By Source of Messages By District during Beekeeping Fish Farming 15.17: EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District during 2002/03 agricultural year, Rukwa Region. District District 15.18: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 1) During the 2002/03 Agricultural Year, Rukwa Region. Spacing Use of Agrochemicals District Erosion Control Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 216 Received Adopted % Received Adopted % Received Adopted % Mpanda 1,594 531 33 4,153 3,225 78 7,267 2,922 40 Sumbawanga Rural 11,286 5,040 45 5,972 932 16 9,893 2,548 26 Nkansi 612 310 51 606 70 12 980 305 31 Sumbawanga Urban 1,525 1,221 80 1,314 405 31 1,554 372 24 Total 15,017 7,101 47 12,045 4,633 38 19,694 6,147 31 Received Adopted % Received Adopted % Received Adopted % Mpanda 135 0 0 800 671 84 6,818 4,829 71 Sumbawanga Rural 1,442 0 0 4,530 1,539 34 10,785 10,659 99 Nkansi 222 153 69 459 236 52 1,149 1,149 100 Sumbawanga Urban 35 103 296 380 309 81 1,319 1,253 95 Total 1,833 255 14 6,169 2,755 45 20,071 17,889 89 15.19: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 2) During the 2002/03 Agricultural Year, Rukwa Region. Inorganic Fertilizer Use Use of Improved Seed Organic Fertilizer Use District 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 3) During the 2002/03 Agricultural Year, Rukwa Region. District Crop Storage Irrigation Technology Mechanisation / LST Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 217 Received Adopted % Received Adopted % Received Adopted % Mpanda 804 670 83 1,602 1,468 92 924 536 58 Sumbawanga Rural 4,060 3,346 82 4,707 4,467 95 4,293 2,870 67 Nkansi 536 536 100 299 299 100 373 225 60 Sumbawanga Urban 174 277 159 343 276 81 1,116 716 64 Total 5,573 4,830 87 6,951 6,510 94 6,707 4,347 65 Received Adopted % Received Adopted % Received Adopted % Mpanda 924 536 58 0 0 0 0 0 Sumbawanga Rural 4,293 2,870 67 481 240 50 241 0 0 Nkansi 373 225 60 0 0 0 0 0 0 Sumbawanga Urban 1,116 716 64 0 0 0 34 0 0 Total 6,707 4,347 65 481 240 50 241 34 0 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 4) During the 2002/03 Agricultural Year, Rukwa Region. District 15.20: CROP EXTENSION" Number of Households Receiving and Adapting Extension Messages by Type of Message and (Part 5 During the 2002/03 Agricultural Year, Rukwa Region. District Vermin Control Agro-progressing Agro-forestry Agro-forestry Beekeeping Fish Farming Tanzania Agriculture Sample Census - 2003 Rukwa 218 Appendix II 219 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 220 No. of Households % No. of Households % Mpanda 4,121 7 55,412 93 59,533 Sumbawanga Rural 47,115 68 21,820 32 68,935 Nkansi 16,622 55 13,861 45 30,483 Sumbawanga Urban 11,547 87 1,762 13 13,309 Total 79,406 46 92,855 54 172,261 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Mpanda 15,523 22,217 38,844 8,368 0 0 35,062 0 0 392 392 1,308 59,346 22,609 40,152 Sumbawanga Rural 60,728 140,521 259,293 35,116 333 0 86,142 3,684 0 2,493 116 0 184,479 144,654 259,293 Nkansi 30,126 55,435 97,932 16,222 3,150 23 28,090 0 0 5,708 0 0 80,146 58,585 97,955 Sumbawanga Urban 13,079 29,683 44,003 5,342 2,255 51 17,338 1,469 17 6,535 336 0 42,294 33,743 44,071 Total 119,456 247,856 440,072 65,048 5,738 74 166,631 5,153 17 15,128 844 1,308 366,264 259,592 441,471 17.1: ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District During 2002/03 agricultural year, Rukwa Region Households Using Draft Animals Household Not Using Draft Animals District Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 221 Total Number % Number % Number Mpanda 2,401 12 56,864 38 59,266 Sumbawanga Rural 9,358 45 59,577 39 68,935 Nkansi 3,476 17 27,007 18 30,483 Sumbawanga Urban 5,361 26 7,948 5 13,309 Total 20,597 100 151,397 100 171,993 Area (%) % Area (%) % Area (%) % Mpanda 1,063 7 357 65 1,420 9 Sumbawanga Rural 7,851 50 63 11 7,914 49 Nkansi 3,398 22 80 15 3,478 22 Sumbawanga Urban 3,286 21 52 9 3,338 21 Total 15,598 100 551 100 16,150 100 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost District Farm Yard Manure Area Applied Compost Area Applied Total District Using Organic Fertilizer Not Using Organic Fertilizer Did you apply organic fertilizer during 2002/03? Tanzania Agriculture Sample Census - 2003 Rukwa 222 Appendix II 223 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 224 Total Agricultural Households Total Livestock Keeping Households Number % Number % Mpanda 4,580 8 54,954 92 59,533 0 Sumbawanga Rural 24,593 36 44,342 64 68,935 416 Nkansi 9,021 30 21,463 70 30,483 0 Sumbawanga Urban 5,357 40 7,952 60 13,309 0 Total 43,551 25 128,710 75 172,261 416 Number of Household % Number of Cattle % Average Number Per Household Number % Number % Number 1-5 25,854 59 66,582 13 3 6-10 7,656 18 58,255 12 8 11-15 3,971 9 51,045 10 13 16-20 1,471 3 26,283 5 18 21-30 2,033 5 51,019 10 25 31-40 650 1 23,832 5 37 41-50 573 1 27,494 5 48 51-60 347 1 20,178 4 58 61-100 233 1 18,672 4 80 101-150 299 1 38,128 8 127 151+ 463 1 123,239 24 266 Total 43,551 100 504,727 100 12 Type Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total Cattle % Bulls 36,029 99 171 0 214 1 36,413 7 Cows 170,403 100 0 0 504 0 170,907 34 Steers 124,331 100 0 0 0 0 124,331 25 Heifers 68,310 100 104 0 213 0 68,627 14 Male Calves 42,726 100 0 0 142 0 42,868 8 Female Calves 61,546 100 0 0 33 0 61,580 12 Total 503,345 100 274 0 1,107 0 504,727 100 18.4.1 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 Herd Size 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Rukwa Region District Households Rearing Cattle Households Not Rearing Cattle Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 225 Improved Beef Improved Dairy Total Cattle Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Mpanda 4,447 82,470 100 0.0 0 0 401 401 0.5 4,580 82,871 16.41898276 Sumbawanga Rural 24,593 236,511 100 0.0 0 0 109 109 0.0 24,593 236,620 46.88081187 Nkansi 8,949 148,683 100 0.0 0 0 235 397 0.3 9,021 149,080 29.5367702 Sumbawanga Urban 5,357 35,682 99 69 274 1 133 200 0.6 5,357 36,156 7.163435173 Total 43,345 503,345 100 69 274 0.1 878 1,107 0.2 43,551 504,727 100 Bulls Cows Steers Heifers Male Calves Female Total Mpanda 6,334 24,220 18,083 17,232 7,648 8,952 82,470 Sumbawanga Rural 18,228 89,268 60,245 22,211 17,518 29,041 236,511 Nkansi 8,757 46,112 34,172 25,138 14,651 19,852 148,683 Sumbawanga Urban 2,709 10,802 11,831 3,730 2,908 3,701 35,682 Total 36,029 170,403 124,331 68,310 42,726 61,546 503,345 Bulls Cows Steers Heifers Male Calves Female Total Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 0 Nkansi 0 0 0 0 0 0 0 Sumbawanga Urban 171 0 0 104 0 0 274 Total 171 0 0 104 0 0 274 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Number - Improved Beef Cattle 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 226 Bulls Cows Steers Heifers Male Calvesemale Calves Total Mpanda 0 0 0 0 0 0 0 Sumbawanga Rural 0 0 0 0 0 0 0 Nkansi 0 0 0 0 0 0 0 Sumbawanga Urban 171 0 0 104 0 0 274 Total 171 0 0 104 0 0 274 Bulls Cows Steers Heifers Male Calvesemale Calves Total Mpanda 6,468 24,354 18,083 17,365 7,648 8,952 82,871 Sumbawanga Rural 18,228 89,268 60,245 22,211 17,627 29,041 236,620 Nkansi 8,838 46,349 34,172 25,218 14,651 19,852 149,080 Sumbawanga Urban 2,880 10,935 11,831 3,834 2,942 3,734 36,156 Total 36,413 170,907 124,331 68,627 42,868 61,580 504,727 District Category - Total Cattle 18.7CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Beef Cattle 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 227 GOAT PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 228 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Mpanda 16,384 116,377 98 134 806 1 269 1,077 1 16,384 118,261 Sumbawanga 16,895 116,919 99 346 1,044 1 107 645 1 16,895 118,607 Nkansi 6,538 42,696 100 0 0 0 0 0 0 6,538 42,696 Sumbawanga 3,334 12,869 97 104 416 3 0 0 0 3,334 13,285 Total 43,150 288,862 99 584 2,265 1 377 1,722 1 43,150 292,849 Herd Size Number of Household % Number of Goat % Average Number Per Household 1-4 20,967 48.6 51,397 17.6 2 5-9 12,819 29.7 82,580 28.2 6 10-14 5,226 12.1 60,060 20.5 11 15-19 1,578 3.7 26,125 8.9 17 20-24 1,199 2.8 24,764 8.5 21 25-29 558 1.3 15,316 5.2 27 30-39 482 1.1 15,731 5.4 33 40+ 321 0.7 16,877 5.8 53 Total 43,150 100.0 292,849 100.0 7 19.2: GOAT PRODUCTION: Total Number of Households Rearing Goats and Heads of Goats by Herd size on 1st October 2003 19.1: GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Total Goat Improved Dairy Improved for Meat Indigenous Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 229 Number % Number % Number % Number % Billy Goat 45,529 95 1,775 4 645 1 47,949 16 Castrated Goat 4,372 94 0 0 269 6 4,641 2 She Goat 149,160 100 70 0 0 0 149,229 51 Male Kid 45,118 98 109 0 808 2 46,035 16 She Kid 44,684 99 311 1 0 0 44,995 15 Total 288,862 99 2,265 1 1,722 1 292,849 100 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 19,821 1,679 60,811 17,727 16,339 116,377 Sumbawanga Rural 16,410 1,944 59,624 18,309 20,632 116,919 Nkansi 7,557 618 21,169 7,358 5,994 42,696 Sumbawanga Urban 1,741 130 7,555 1,724 1,719 12,869 Total 45,529 4,372 149,160 45,118 44,684 288,862 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 806 0 0 0 0 806 Sumbawanga Rural 691 0 0 109 243 1,044 Nkansi 0 0 0 0 0 0 Sumbawanga Urban 278 0 70 0 68 416 Total 1,775 0 70 109 311 2,265 District Number of Improved for Meat 19.4 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Type 19.5: GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 19.:3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Category of Goats Total Goat Number of Improved Dairy Number of Improved for Meat Number of Indigenous Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 230 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda . 269 . 808 . 1,077 Sumbawanga Rural 645 . . . . 645 Nkansi . . . . . . Sumbawanga Urban . . . . . . Total 645 269 . 808 . 1,722 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Mpanda 20,627 1,948 60,811 18,535 16,339 118,261 Sumbawanga Rural 17,746 1,944 59,624 18,418 20,876 118,607 Nkansi 7,557 618 21,169 7,358 5,994 42,696 Sumbawanga Urban 2,019 130 7,625 1,724 1,787 13,285 Total 47,949 4,641 149,229 46,035 44,995 292,849 District Total Goat 19.6: GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, District Number of Improved Dairy 19.7: GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 231 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 232 Breed Number of Indigenous % Number of Improved for Mutton % Total Sheep % Ram 6,365 100 0 0 6,365 18 Castrated Sheep 134 100 0 0 134 0 She Sheep 18,517 100 0 0 18,517 51 Male Lamb 5,311 100 0 0 5,311 15 She Lamb 5,746 100 0 0 5,746 16 Total 36,073 100 0 0 36,073 100 District Total Livestock Keeping Households Number % Number % Mpanda 1,955 3 57,579 97 59,533 0 Sumbawanga Rural 1,478 2 67,457 98 68,935 416 Nkansi 1,237 4 29,246 96 30,483 0 Sumbawanga Urban 99 1 13,210 99 13,309 0 Total 4,770 3 167,491 97 172,261 416 Number % Number % Number % Mpanda 13,967 100 0 0 13,967 39 Sumbawanga Rural 10,953 100 0 0 10,953 30 Nkansi 10,756 100 0 0 10,756 30 Sumbawanga Urban 397 100 0 0 397 1 Total 36,073 100 0 0 36,073 100 Number of Households Average Sheep Number of Households Average Sheep Mpanda 1,955 0 0 0 1,955 7 Sumbawanga Rural 1,478 0 0 0 1,478 7 Nkansi 1,237 0 0 0 1,237 9 Sumbawanga Urban 99 0 0 0 99 4 Total 4,770 0 0 0 4,770 8 Total Numbver of Households Number of Indigenous Number of Improved for Mutton Total Sheep 20.3: SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 District Total Households Raising Sheep Average Sheep 20.4: Number of Sheep per Household by Category and district as of 1st October 2003. 20.1: SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year District Number of Indigenous Number of Improved for Mutton 20.2: SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002/03 Agriculture Year Households Raising Sheep Households Not Raising Sheep Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 233 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 2,021 42 5,313 15 3 5-9 1,574 33 11,157 31 7 10-14 448 9 4,833 13 11 15-19 442 9 7,296 20 17 20-24 130 3 2,608 7 20 30-39 154 3 4,866 13 32 Total 4,770 100 36,073 100 8 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Number of Indigenous Mpanda 1,801 134 7,073 2,216 2,743 13,967 Sumbawanga Rural 2,184 0 5,422 1,734 1,613 10,953 Nkansi 2,281 0 5,756 1,361 1,357 10,756 Sumbawanga Urban 99 0 265 0 33 397 Total 6,365 134 18,517 5,311 5,746 36,073 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Sheep Mpanda 1,801 134 7,073 2,216 2,743 13,967 Sumbawanga Rural 2,184 . 5,422 1,734 1,613 10,953 Nkansi 2,281 . 5,756 1,361 1,357 10,756 Sumbawanga Urban 99 . 265 . 33 397 Total 6,365 134 18,517 5,311 5,746 36,073 20.5: Number of Households and Heads of Sheep by Herd Size on 1st October 2003. 20.8 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep 20.6: SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Sheep Tanzania Agriculture Sample Census - 2003 Rukwa 234 Appendix II 235 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 236 Number % Number % 1-4 8,000 66 13,781 27 2 5-9 2,769 23 19,645 38 7 10-14 859 7 9,228 18 11 15-19 163 1 2,526 5 16 30-39 194 2 5,968 12 31 40+ 115 1 691 1 6 Total 12,101 100 51,840 100 4 District Number of Household Number of Pig Average Number Per Household Mpanda 1,343 4,837 4 Sumbawanga Rural 8,350 36,455 4 Nkansi 1,007 8,396 8 Sumbawanga Urban 1,400 2,152 2 Total 12,101 51,840 4 Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Mpanda 804 . 1,074 1,076 1,883 4,837 Sumbawanga Rural 3,968 334 11,131 10,305 10,716 36,455 Nkansi 608 80 1,722 3,557 2,428 8,396 Sumbawanga Urban 373 35 1,508 136 101 2,152 Total 5,753 449 15,435 15,074 15,128 51,840 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year District 21.2: PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.3: PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Pigs Type District Households Raising Pig Herds of Pigs Average Number Per Household Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 237 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 238 Total Number % age Number % age Number Mpanda 6,198 53 5,435 47 11,633 Sumbawanga Rural 8,564 28 21,602 72 30,166 Nkasi 3,538 33 7,159 67 10,697 Sumbawanga Urban 2,720 48 2,975 52 5,695 Total 21,021 36 37,171 64 58,192 Number of Households % Number of Households % Number of Households % Number of Households % Mpanda 3,163 53 4,357 27 130 10 803 25 Sumbawanga Rural 1,754 29 5,881 37 930 72 1,661 53 Nkasi 768 13 3,147 20 226 18 317 10 Sumbawanga Urban 265 4 2,583 16 0 0 380 12 Total 5,950 100 15,968 100 1,286 100 3,161 100 Total No. of Households % age No. of Households % age No. of Households Mpanda 1,604 14 9,493 86 11,097 Sumbawanga Rur 3,226 11 25,665 89 28,891 Nkasi 1,668 16 9,028 84 10,697 Sumbawanga Urb 100 2 5,527 98 5,627 Total 6,598 12 49,714 88 56,312 Total No. of Households % age No. of Households % age No. of Households % age No. of Households % age No. of Households Mpanda 531 33 539 34 401 25 134 8 1,604 Sumbawanga Rur 3,226 100 0 0 0 0 0 0 3,226 Nkasi 1,514 91 154 9 0 0 0 0 1,668 Sumbawanga Urb 65 65 35 35 0 0 0 0 100 Total 5,336 81 727 11 401 6 134 2 6,598 Trapping Method of Tsetse Flies Control Spray NO Tsetse Flies Problems 22.4: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Dipping District None Tsetse Flies Problems 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households deworming Livestock by District during 2002/03 Agricultural Year District No. of Households Demworming Livestock No. of Households NOT Demworming their animals 22.2: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock Dewormed Goats Dewormed Cattles 22.3: LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year Dewormed Sheep Dewormed Pigs District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 239 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 240 Number % Type Number Indigenous Chicken 1,114,556 99 Ducks 88,647 Layer 7,261 1 Turkeys 2,686 Broiler 615 0 Rabbits 17,876 0 Donkeys 11,190 Total 1,122,432 100 120,399 Indigenous Chicken Layer Broiler Total Ducks Turkeys Rabbits Donkeys Other Mpanda 492,601 . 0 492,601 Mpanda 38,381 0 5,650 4,265 0 Sumbawanga Rural 443,312 2,414 213 445,939 Sumbawanga Rural 40,326 2,516 5,263 3,578 7,644 Nkasi 129,096 1,144 402 130,643 Nkasi 9,294 0 3,561 2,629 9,765 Sumbawanga Urban 49,547 3,703 0 53,250 Sumbawanga Urban 646 170 3,402 718 0 Total 1,114,556 7,261 615 1,122,432 Total 88,647 2,686 17,876 11,190 17,409 1,122,432 Number % 1 - 4 38,452 35 92,665 2 5 - 9 31,281 28 204,580 7 10 - 19 25,278 23 321,753 13 20 - 29 6,961 6 155,776 22 30 - 39 4,248 4 136,546 32 40 - 49 2,087 2 87,172 42 50 - 99 1,365 1 87,994 64 100+ 240 0 35,946 150 Total 109,912 100 1,122,432 10 23a: OTHER LIVESTOCK: Total number of Other Livestock by Type as of 1st October 2003 Type Number of Chicken 23b: OTHER LIVESTOCK: Number of chicken by Category of Chicken and District as of 1st October, 2003 Chicken Number of chicken Average chicken per household Flock Size Others Chicken rearing Households 23d: OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size 23c: OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Type of Livestock District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 241 FISH FARMING Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 242 Total Number % Number % Number Mpanda 0 0.0 59,533 100.0 59,533 Sumbawanga Rural 0 0.0 68,935 100.0 68,935 Nkasi 80 0.3 30,403 99.7 30,483 Sumbawanga Urban 0 0.0 13,309 100.0 13,309 Total 80 0.0 172,181 100.0 172,261 Natural Pond Total Nkasi 80.2 80.2 Total 80.2 80.2 Source of Fingerlings Neighbour Total Number Number Nkasi 80 80 Total 80 80 Where sold Trader at Farm Total Number Number Nkasi 80 80 Total 80 80 District Number of Tilapia Number of Carp Number of Others Nkasi 8,018 0 0 Total 8,018 0 0 District 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.2b FISH FARMING: Number of Agricultural Households By Source of Fingerings and District, 2002/03 Agricultural Year District 28.2c: FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District, 2002/03 Agricultural Year District System of Fish Farming Was fish farming carried out by this household during 2002/03? District 28.1a: FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year Yes No 28.2a: FISH FARMING: Number of Agricultural Households By System of Farming and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 243 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 244 District Number % Number % Mpanda 3,632 6 55,901 94 59,533 11,633 31.2 Sumbawanga Rural 9,265 13 59,671 87 68,935 29,751 31.1 Nkasi 1,999 7 28,485 93 30,483 10,697 18.7 Sumbawanga Urban 2,170 16 11,139 84 13,309 5,695 38.1 Total 17,065 10 155,195 90 172,261 57,776 29.5 Governmen t NGO / Development Project Co- operative Large Scale Farmer Other Mpanda 2,565 0 0 134 0 Sumbawanga Rur 5,522 0 121 120 120 Nkasi 1,399 0 0 78 0 Sumbawanga Urb 1,967 35 0 134 0 Total 11,452 35 121 466 120 Advice Governmen t NGO / Development Project Mpanda 135 0 135 11,633 1 Sumbawanga Rur 1,425 0 1,425 29,751 5 Nkasi 0 0 0 10,697 0 Sumbawanga Urb 169 33 202 5,695 4 Total 1,729 33 1,762 % receiving advice out of total Total 29.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Total Number of households raising livestock % 29.1a: LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By District during the 2002/03 Agricultural Year 29.1b Livestock Extension Providers: Number of Households By Source of Extension and District, 2002/03 Agricultural Year District Source of Advice Received Livestock Advice Did NOT Receiving Livestock Advice Total Number of households raising livestock Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 245 Governmen t NGO / Development Project Other Mpanda 135 0 0 135 11,633 1.2 Sumbawanga Rural 1,662 0 0 1,662 29,751 5.6 Nkansi 0 0 0 0 10,697 0.0 Sumbawanga Urban 238 33 0 271 5,695 4.8 Total 2,035 33 0 2,068 57,776 3.6 % 98 2 0 100 Governmen t NGO / Development Project Co-operative Large Scale Farmer Other Total Mpanda 2,565 0 0 134 0 2,699 11,633 23 Sumbawanga Rur 5,522 0 121 120 120 5,882 29,751 20 Nkasi 1,399 0 0 78 0 1,477 10,697 14 Sumbawanga Urb 1,967 35 0 134 0 2,135 5,695 37 Total 11,452 35 121 466 120 12,193 57,776 21 % 93.9 0.3 1.0 3.8 1.0 100.0 Governmen t NGO / Development Project Other Total Mpanda 403 0 0 403 11,633 3 Sumbawanga Rur 1,556 0 120 1,676 29,751 6 Nkasi 153 0 0 153 10,697 1 Sumbawanga Urb 69 35 0 104 5,695 2 Total 2,182 35 120 2,337 57,776 4 % 93.4 1.5 5.1 100 % receiving advice out of total Total Number of households raising livestock % receiving advice out of total 29.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice on Milk Hygene Total Number of households raising livestock District Source of Advice on Herd Flock/Flock Size Total Number of households raising livestock 29.1f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 246 Governmen t NGO / Development Project Other Mpanda 134 0 0 134 11,633 1 Sumbawanga Rural 1,302 117 0 1,419 29,751 5 Nkansi 0 0 0 0 10,697 0 Sumbawanga Urban 170 100 0 270 5,695 5 Total 1,606 216 0 1,823 57,776 3 % 88 12 0 100 Governmen t NGO / Development Project Co-operative Mpanda 267 0 0 267 11,633 2 Sumbawanga Rural 2,934 0 240 3,174 29,751 11 Nkasi 150 0 0 150 10,697 1 Sumbawanga Urban 337 234 0 571 5,695 10 Total 3,688 234 240 4,163 57,776 7 % 89 6 6 100 Governmen t NGO / Development Project Other Mpanda 404 0 0 404 11,633 3 Sumbawanga Rural 2,143 0 0 2,143 29,751 7 Nkasi 78 82 0 160 10,697 1 Sumbawanga Urban 205 101 0 306 5,695 5 Total 2,830 183 0 3,013 57,776 5 % 94 6 0 100 Source of Advice on Group Formation Total District Source of Advice on Calf Rearing Total Number of households raising livestock Source of Advice on Pasture Establishment Total 29.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total District 29.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total Number of households raising livestock % receiving advice out of total District Total 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 247 Government NGO / Development Project Co- operative Total Mpanda 269 0 0 269 11,633 2 Sumbawanga Rural 1,782 0 121 1,902 29,751 6 Nkasi 162 0 0 162 10,697 2 Sumbawanga Urban 169 101 0 270 5,695 5 Total 2,382 101 121 2,604 57,776 5 % 91 4 5 100 Number % Number % Number % Number % Number % Number Mpanda 130 3 1,734 44 1,309 33 742 19 0 0 3,916 Sumbawanga Rural 362 4 6,295 66 2,284 24 0 0 600 6 9,542 Nkasi 78 4 1,618 81 302 15 0 0 0 0 1,999 Sumbawanga Urban 69 3 2,097 85 305 12 0 0 0 0 2,472 Total 641 4 11,745 66 4,200 23 742 4 600 3 17,928 Total District Very Good Good Average Poor No Good Quality of Service 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District Source of Advice on the Use of Improved Bulls 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Rukwa 248 Appendix II 249 ACCESS TO INTRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 250 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Mpanda 28 3 4 1 74 7 284 23 27 70 303 Sumbawanga Rural 21 2 6 1 90 10 92 8 19 81 129 Nkasi 37 2 7 2 49 7 109 23 25 43 146 Sumbawanga Urban 8 1 1 1 15 6 15 11 12 14 37 Total 25 2 5 1 72 8 156 16 22 66 185 Regional Capital 75 All Weather Roads 5 Tarmac Roads 185 Hospitals 72 Tertiary Markets 66 Secondary Market 22 Secondary Schools 25 Primary Markets 16 Health Clinics 8 Primary Schools 2 Feeder Roads 1 Table 33.01a: Mean distances from horders dwellings to Infrastructures and services by District District Mean Distance to Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 251 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % % Mpanda 934 2 1,601 3 11,759 20 15,719 26 29,520 50 59,533 28 Sumbawanga Rural 4,649 7 1,376 2 12,239 18 14,916 22 35,755 52 68,935 21 Nkasi 0 0 162 1 7,603 25 8,571 28 14,147 46 30,483 37 Sumbawanga Urban 138 1 1,889 14 6,894 52 4,077 31 311 2 13,309 8 Total 5,721 3 5,029 3 38,495 22 43,283 25 79,733 46 172,261 25 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households %f households % Mpanda 29,251 49 9,341 16 13,400 23 4,877 8 2,664 4 59,533 4 Sumbawanga Rural 34,480 50 9,650 14 9,880 14 6,289 9 8,636 13 68,935 6 Nkasi 13,091 43 2,678 9 6,953 23 4,475 15 3,287 11 30,483 7 Sumbawanga Urban 9,369 70 2,289 17 1,583 12 68 1 0 0 13,309 1 Total 86,191 50 23,957 14 31,816 18 15,709 9 14,587 8 172,261 5 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % Number of h% Mpanda 38,481 65 11,972 20 8,281 14 800 1 0 0 59,533 1 Sumbawanga Rural 52,920 77 9,216 13 5,452 8 1,025 1 322 0 68,935 1 Nkasi 20,915 69 4,101 13 3,958 13 1,509 5 0 0 30,483 2 Sumbawanga Urban 10,323 78 2,400 18 550 4 0 0 35 0 13,309 1 Total 122,639 71 27,690 16 18,242 11 3,333 2 357 0 172,261 1 Total Number of Households 33.01c: Mean distance from holders dwellings to all Weather roads by District District Distance to All Weather Roads Total Number of Households Mean Distance 33.01b: Mean distance from holders dwellings to infrastrures and services by District District Distance to Feeder Road Total Number of Households Mean Distance Mean Distance Distance to Secondary School District 33.01d: Mean distance from holders dwellings to Feeder Roads by District Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 252 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % f households % Mpanda 134 0.2 134 0.2 1,302 2 9,918 17 48,045 81 59,533 74 Sumbawanga Rural 119 0.2 120 0.2 566 1 669 1 67,462 98 68,935 90 Nkasi 71 0.2 513 1.7 4,196 14 4,765 16 20,939 69 30,483 49 Sumbawanga Urban 68 0.5 0 0.0 4,669 35 5,993 45 2,579 19 13,309 15 Total 392 0.2 767 0.4 10,732 6 21,344 12 139,025 81 172,261 72 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % Number of households % f households % Mpanda 7,488 13 7,807 13 27,274 46 13,941 23 3,023 5 59,533 7 Sumbawanga Rural 19,914 29 10,046 15 19,684 29 10,335 15 8,957 13 68,935 10 Nkasi 3,950 13 2,872 9 16,362 54 5,859 19 1,440 5 30,483 7 Sumbawanga Urban 3,342 25 2,512 19 6,166 46 1,254 9 35 0 13,309 6 Total 34,694 20 23,236 13 69,486 40 31,390 18 13,455 8 172,261 8 Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Number of households % Number of households % Number of households % No of households % No of households % Mpanda 16,818 28 20,799 35 19,800 33 1,060 2 1,056 2 59,533 Sumbawanga Rural 34,714 50 21,967 32 10,886 16 1,246 2 122 0 68,935 Nkasi 19,494 64 5,768 19 4,927 16 82 0 212 1 30,483 Sumbawanga Urban 7,602 57 4,372 33 1,266 10 68 1 0 0 13,309 Total 78,629 46 52,906 31 36,880 21 2,456 1 1,389 1 172,261 District Less than 1 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Mean Distance Mpanda 0 0 135 59,398 59,533 283.7 Sumbawanga Rural 0 111 0 68,824 68,935 92.4 Nkasi 162 155 0 30,167 30,483 109.2 Sumbawanga Urban 35 4,532 6,128 2,614 13,309 15.4 Total 196 4,798 6,263 161,003 172,261 155.5 33.1h: Number of Households to Regional Capital 33.01g: Mean distance from holders dwellings to Primary School by District District Total Number of Households Distance to Primary School 33.01f: Mean distance from holders dwellings to Health Clinic by District District Distance to Health Clinic Total Number of Households Mean Distance 33.01e: Mean distance from holders dwellings to Hospital by District District Distance to Hospital Total Number of Households Mean Distance Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 253 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 135 132 0 135 59,131 59,533 303 Sumbawanga Rural 716 0 119 120 67,980 68,935 129 Nkasi 78 0 0 81 30,323 30,483 146 Sumbawanga Urban 225 0 4,205 5,504 3,375 13,309 37 Total 1,155 132 4,324 5,840 160,809 172,261 185 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 4,917 12,259 9,400 14,247 18,711 59,533 23 Sumbawanga Rural 20,032 9,266 16,216 10,622 12,800 68,935 8 Nkasi 8,131 664 7,436 5,989 8,262 30,483 23 Sumbawanga Urban 3,764 2,184 3,140 2,655 1,566 13,309 11 Total 36,844 24,373 36,192 33,513 41,338 172,261 16 District Less than 1km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 267 398 4,384 9,254 45,230 59,533 70 Sumbawanga Rural 1,736 1,838 1,068 2,235 62,058 68,935 81 Nkasi 1,030 954 4,988 4,565 18,946 30,483 43 Sumbawanga Urban 67 0 4,671 5,992 2,579 13,309 14 Total 3,100 3,191 15,111 22,047 128,813 172,261 66 District Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Total Households Mean Distance Mpanda 3,637 2,932 12,910 15,920 24,135 59,533 27 Sumbawanga Rural 7,399 4,489 11,568 15,679 29,801 68,935 19 Nkasi 1,849 1,442 11,843 6,901 8,448 30,483 25 Sumbawanga Urban 1,299 581 5,190 3,695 2,544 13,309 12 Total 14,184 9,443 41,510 42,195 64,928 172,261 22 33.01m: Number of Households by Distance to Secondary Market for the 2002/03 Agricultural Year 33.01l: Number of Households by Distance to Tertiary Market for the 2002/03 Agricultural Year 33.01j : Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year 33.01k: Number of Households by Distance to Primary Marketfor the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 254 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 1,200 0.3 1,458 0.4 1,304 0.4 1,197 0.3 132 0.0 357,200 Sumbawanga Rural 0 0.0 1,148 0.3 2,639 0.6 2,754 0.7 6,552 1.6 413,611 Nkasi 158 0.1 2,800 1.5 2,815 1.5 2,973 1.6 1,032 0.6 182,900 Sumbawanga Urban 0 0.0 752 0.9 276 0.3 570 0.7 35 0.0 79,854 Total 1,358 0.1 6,158 0.6 7,035 0.7 7,494 0.7 7,751 0.7 1,033,565 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 399 22 791 43 257 14 401 22 0 0 1,848 Sumbawanga Rural 0 0 117 6 689 33 363 18 905 44 2,073 Nkasi 80 2 1,307 38 1,162 34 687 20 219 6 3,454 Sumbawanga Urban 0 0 35 52 0 0 32 48 0 0 67 Total 479 6 2,250 30 2,107 28 1,483 20 1,123 15 7,442 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 0 0 0 0 265 100 0 0 265 Sumbawanga Rural 0 0 112 6 0 0 363 21 1,244 72 1,718 Nkasi 78 5 157 9 862 51 442 26 147 9 1,686 Sumbawanga Urban 0 0 70 34 0 0 134 66 0 0 203 Total 78 2 338 9 862 22 1,204 31 1,391 36 3,873 District Research Station Total Number of Households 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Satisfaction of Using Veterinary Clinic District 33.19c TYPE OF SERVICE: Number of Households by Satisfaction of Using Research Centre and District, 2002/03 Agricultural Year Total Number of Households 33.19b TYPE OF SERVICE: Number of Households by Satisfaction of Using Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total Number of Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 255 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 0 0 135 100 0 0 0 0 135 Sumbawanga Rural 0 0 0 0 0 0 482 25 1,463 75 1,945 Nkasi 0 0 0 0 0 0 522 78 147 22 669 Sumbawanga Urban 0 0 0 0 0 0 32 100 0 0 32 Total 0 0 0 0 135 0 1,036 37 1,610 58 2,781 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 532 40 269 20 135 10 262 20 132 10 1,330 Sumbawanga Rural 0 0 0 0 808 33 601 25 1,018 42 2,426 Nkasi 0 0 0 0 0 0 369 71 147 29 516 Sumbawanga Urban 0 0 205 30 208 30 238 35 35 5 686 Total 532 11 474 10 1,150 23 1,470 30 1,332 27 4,958 33.19e TYPE OF SERVICE: Number of Households by Satisfaction of using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total Number of Households 33.19d TYPE OF SERVICE: Number of Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year District Plant Protection Lab. Total Number of Households Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 256 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Mpanda 0 0 135 35 120 31 135 35 0 389 Sumbawanga Rural 0 0 688 23 1,143 38 583 20 565 19 2,979 Nkasi 0 0 0 0 78 12 442 66 147 22 667 Sumbawanga Urban 0 0 103 76 0 0 32 24 0 0 135 Total 0 0 925 22 1,341 32 1,191 29 713 17 4,170 Very Good Good Average Poor No good No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Veterinary Clinic 1,358 0 6,158 1 7,035 1 7,494 1 7,751 1 1,033,565 Extension Services 479 6 2,250 30 2,107 28 1,483 20 1,123 15 7,442 Research Station 78 2 338 9 862 22 1,204 31 1,391 36 3,873 Plant Protection Lab 0 0 0 0 135 5 1,036 37 1,610 58 2,781 Land Registration Office 532 11 474 10 1,150 23 1,470 30 1,332 27 4,958 Livestock Development Centre 0 925 22 1,341 32 1,191 29 713 17 4,170 33.19f TYPE OF SERVICE: Number of Households by Satisfaction of using Livestock Development centre and Registration Office and District, 2002/03 Agricultural Year District Livestock Development Centre Total Number of Households Total Number of Households LEVEL OF SATISFACTION OF THE SERVICE TYPE OF SERVICE 33.19G TYPE OF SERVICE: Number of Households by Level of satisfaction of the Service and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 257 HOUSEHOLDS FACILITIES Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 258 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Number of Househol ds Mpanda 1,477 1,749 55,910 397 0 59,533 Sumbawanga Rural 4,861 2,426 61,307 341 0 68,935 Nkasi 480 150 29,316 538 0 30,483 Sumbawanga Urban 371 69 12,734 101 34 13,309 Total 7,189 4,395 159,267 1,376 34 172,261 % 4 3 92 1 0 100 Average Number of rooms per Household Iron sheet Tiles Concreat e Asbestos Grass/Le aves Grass & Mud Other Total Number of Households Mpanda 3 9,757 270 135 536 47,907 929 0 59,533 Sumbawanga Rur 2 12,882 445 0 1,371 49,355 4,883 0 68,935 Nkasi 2 5,006 213 82 278 24,538 367 0 30,483 Sumbawanga Urb 2 4,437 35 0 0 8,078 759 0 13,309 Total 2 32,082 962 216 2,186 129,877 6,937 0 172,261 % 19 1 0 1 75 4 0 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 29,457 41 23,873 33 14,229 20 4,484 6 72,043 42 Landline phones 267 100 0 0 0 0 0 0 267 0 Mobile Phones 134 17 359 46 290 37 0 0 784 0 Iron 9,486 40 7,846 33 4,613 20 1,698 7 23,642 14 Wheelbarrow 1,570 30 2,793 54 397 8 439 8 5,199 3 Bicycles 34,455 53 17,544 27 7,564 12 5,014 8 64,577 37 Vehicles 529 49 459 43 82 8 0 0 1,070 1 Television/Video 535 63 107 13 207 24 0 0 849 0 Total Number of Households 76,433 44 52,980 31 27,383 16 11,635 7 172,261 100 34-1: Number of Agricultural Households by Type of TOILET by Districtduring the 2002/03 Agricultural Year Type of Toilet District 34-2: Number of Agricultural Households Reported Average Number of Rooms and Type of Roofing Materials by District for the 2002/03 Agricultural Year District Type of Owned Asset Total Type of Roofing materials District Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.3: Number of Agricultural Households by Type of Owned Assets and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 259 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 133 30 235 53 72 16 0 0 440 0 Hurricane Lamp 11,300 39 9,321 32 7,648 26 803 3 29,072 17 Pressure Lamp 2,239 38 2,410 41 1,064 18 209 4 5,922 3 Wick Lamp 45,056 34 53,197 40 21,462 16 12,228 9 131,944 77 Candles 0 0 115 61 72 39 0 0 187 0 Firewood 806 18 3,538 78 164 4 34 1 4,542 3 Other 0 0 120 78 0 0 34 22 154 0 Total Number of Households 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Charcoal 1,877 36 1,526 29 1,620 31 162 3 5,185 3 Firewood 57,657 35 67,095 40 28,793 17 13,112 8 166,657 97 Crop Residues 0 0 314 82 70 18 0 0 385 0 Livestock dung 0 0 0 0 0 0 35 100 35 0 Total Number of Households 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Sumbawanga Urban Mpanda Sumbawanga Rural Nkasi Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.4 Number of Agricultural Households by Main Source of Energe Used for Lighting and District, 2002/03 Agricultural Year District Main Source of Energe for Lighting Total 34.5: Number of Agricultural Households by Main Source of Energe Used for Cooking and District, 2002/03 Agricultural Year Main Source of Energe for Lighting District Total Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 260 Source Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Piped Water Wet 11,669 11,568 2,105 4,523 Dry 11,012 9,437 2,176 3,977 Protected Well Wet 14,432 12,777 14,981 1,468 Dry 15,098 12,462 14,115 1,367 Protected / Covered Spring Wet 940 2,066 141 970 Dry 805 2,421 141 935 Uprotected Well Wet 13,336 18,799 4,796 3,534 Dry 14,894 21,297 4,797 3,669 Unprotected Spring Wet 6,247 5,363 3,995 1,779 Dry 5,985 5,837 3,637 1,877 Surface Water (Lake / Dam / River / Stream Wet 12,392 17,780 4,068 551 Dry 11,215 17,021 5,373 1,067 Covered Rainwater Catchment Wet 0 0 152 0 Dry 0 0 80 0 Uncovered Rainwater Catchment Wet 383 583 165 452 Dry 389 460 82 417 Tanker Truck Wet 134 0 0 0 Dry 134 0 0 0 Other Wet 0 0 81 32 Dry 0 0 81 0 Total Agricultural Households per District 59,533 68,935 30,483 13,309 Source Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Piped Water Wet 20 17 7 34 Dry 18 14 7 30 Protected Well Wet 24 19 49 11 Dry 25 18 46 10 Protected / Covered Spring Wet 2 3 0 7 Dry 1 4 0 7 Uprotected Well Wet 22 27 16 27 Dry 25 31 16 28 Unprotected Spring Wet 10 8 13 13 Dry 10 8 12 14 Surface Water (Lake / Dam / River / Stream Wet 21 26 13 4 Dry 19 25 18 8 Covered Rainwater Catchment Wet 0 0 0 0 Dry 0 0 0 0 Wet 1 1 1 3 Dry 1 1 0 3 Wet 0 0 0 0 Dry 0 0 0 0 Wet 0 0 0 0 Dry 0 0 0 0 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season ( Wet and Dry) and District, 2002/03 Agricultural Year Season District Other Tanker Truck Uncovered Rainwater Catchment District Season Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 261 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Less than 100m Wet 2,257 6,975 960 232 Dry 1,860 6,855 984 100 100 - 299 m Wet 13,639 13,807 9,151 2,842 Dry 12,599 12,188 8,889 2,809 300 - 499 m Wet 6,570 6,549 5,759 2,044 Dry 6,307 5,480 5,462 1,979 500 - 999 m Wet 16,234 14,640 9,572 4,718 Dry 16,231 15,700 9,364 4,682 1 - 1.99 Km Wet 12,611 18,849 3,994 2,383 Dry 11,672 15,726 4,269 2,276 2 - 2.99 Km Wet 4,103 5,700 966 918 Dry 5,414 8,134 1,471 1,259 3 - 4.99 Km Wet 3,449 2,072 0 102 Dry 4,244 3,582 0 134 5 - 9.99 Km Wet 671 343 82 69 Dry 1,206 1,270 46 69 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Less than 100m Wet 4 10 3 2 Dry 3 10 3 1 100 - 299 m Wet 23 20 30 21 Dry 21 18 29 21 300 - 499 m Wet 11 9 19 15 Dry 11 8 18 15 500 - 999 m Wet 27 21 31 35 Dry 27 23 31 35 1 - 1.99 Km Wet 21 27 13 18 Dry 20 23 14 17 2 - 2.99 Km Wet 7 8 3 7 Dry 9 12 5 9 3 - 4.99 Km Wet 6 3 0 1 Dry 7 5 0 1 5 - 9.99 Km Wet 1 0 0 1 Dry 2 2 0 1 Distance to main Source of Drinking Water Season District 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year District Distance to main Source of Drinking Water Season 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 262 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Wet 808 1,687 151 132 Dry 672 1,330 151 136 Wet 12,900 12,596 12,451 3,315 Dry 11,843 12,142 12,136 3,349 Wet 6,191 9,872 5,629 2,420 Dry 5,925 8,218 5,617 2,420 Wet 15,369 21,137 5,495 3,730 Dry 15,105 20,338 5,601 3,285 Wet 4,598 5,824 1,212 1,157 Dry 4,456 6,273 1,080 1,159 Wet 5,052 3,156 3,267 883 Dry 4,521 3,281 3,229 852 Wet 14,615 14,663 2,279 1,672 Dry 17,011 17,354 2,670 2,109 Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Wet 1 2 0 1 Dry 1 2 0 1 Wet 22 18 41 25 Dry 20 18 40 25 Wet 10 14 18 18 Dry 10 12 18 18 Wet 26 31 18 28 Dry 25 30 18 25 Wet 8 8 4 9 Dry 7 9 4 9 Wet 8 5 11 7 Dry 8 5 11 6 Wet 25 21 7 13 Dry 29 25 9 16 Distance to main Source of Drinking Water Season District 34.10: Number of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Distance to main Source of Drinking Water Season District 34.11: Proportion of Agricultural Households by Time spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District, 2002/03 Agricultural Year Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 263 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % One 2,412 21 5,766 50 950 8 2,495 19 11,622 7 Two 45,753 32 59,117 42 25,767 18 10,346 78 140,983 82 Three 11,368 58 4,052 21 3,684 19 468 4 19,573 11 Four 0 0 0 0 82 100 0 0 82 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 24,155 31 36,652 46 12,615 16 5,733 7 79,156 46 One 19,522 39 18,118 37 7,828 16 4,117 8 49,584 29 Two 10,142 37 9,995 37 4,699 17 2,362 9 27,198 16 Three 3,326 31 2,993 28 3,630 34 722 7 10,671 6 Four 1,852 48 707 18 1,014 26 275 7 3,848 2 Five 269 32 122 15 407 49 35 4 833 0 Six 135 65 0 0 72 35 0 0 207 0 Seven 133 17 348 46 217 28 65 9 763 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Days District Total Number of Meals per Day Total Nkasi Sumbawanga 34.12: Number of Households by Number of Meals the Household Normally Took per Day by District District Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34.13: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Mpanda Sumbawanga Rural Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 264 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Not Eaten 22,709 46 18,803 38 5,145 10 2,768 6 49,425 29 One 13,023 35 13,719 37 6,996 19 3,645 10 37,383 22 Two 11,770 38 10,652 34 4,573 15 3,976 13 30,971 18 Three 5,460 31 7,596 43 2,936 17 1,801 10 17,793 10 Four 2,535 25 4,907 48 1,998 20 687 7 10,127 6 Five 669 11 3,053 49 2,215 35 332 5 6,268 4 Six 255 7 2,235 59 1,275 34 0 0 3,766 2 Seven 3,113 19 7,970 48 5,345 32 100 1 16,528 10 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Never 27,693 33 35,734 43 13,537 16 5,770 7 82,734 48 Seldom 20,904 37 21,058 38 9,689 17 4,198 8 55,848 32 Sometimes 3,196 27 5,964 50 1,777 15 1,020 9 11,957 7 Often 5,207 39 4,221 32 2,376 18 1,408 11 13,212 8 Always 2,533 30 1,958 23 3,105 36 914 11 8,509 5 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Number of Days District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban 34-15: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceeding Year by District Status of Food Satisfaction District Total Mpanda Sumbawanga Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Sales of Food Crops 30,051 36 36,355 43 12,760 15 5,141 6 84,309 49 Sale of Livestock 370 20 902 48 325 17 267 14 1,864 1 Sale of Livestock Products 134 32 0 0 82 20 204 48 420 0 Sales of Cash Crops 6,437 90 237 3 76 1 439 6 7,189 4 Sale of Forest Products 6,462 23 12,781 46 5,615 20 2,761 10 27,620 16 Business Income 6,462 23 12,781 46 5,615 20 2,761 10 27,620 16 Wages & Salaries in Cash 1,204 31 1,435 37 889 23 403 10 3,931 2 Other Casual Cash Earnings 9,401 38 7,637 31 4,707 19 2,743 11 24,488 14 Cash Remittance 1,028 24 1,938 45 856 20 509 12 4,331 3 Fishing 329 4 4,708 50 4,298 46 35 0 9,370 5 Other 383 48 0 0 79 10 335 42 796 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34-16: Number of Households by Main Source of Income and District, 2002/03 Agricultural Year Main Source of Cash Income District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa Appendix II 266 Number of Households % Number of Households % Number of Households % Number of Households % Number of Household % Iron Sheets 9,757 30 12,882 40 5,006 16 4,437 14 32,082 19 Tiles 270 28 445 46 213 22 35 4 962 1 Concreate 135 62 0 0 82 38 0 0 216 0 Asbestos 536 25 1,371 63 278 13 0 0 2,186 1 Grass/leaves 47,907 37 49,355 38 24,538 19 8,078 6 129,877 75 Grass & Mud 929 13 4,883 70 367 5 759 11 6,937 4 Other 0 0 0 0 0 0 0 0 0 0 Total 59,533 35 68,935 40 30,483 18 13,309 8 172,261 100 34.17: Number of hoseholds BY Type of Roofing Materials and District during 2002/03 Agricultural Year Roofing Materials District Total Mpanda Sumbawanga Rural Nkasi Sumbawanga Urban Tanzania Agriculture Sample Census - 2003 Rukwa 267 APPENDIX III QUESTIONNAIRES Appendix III 268 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 269 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 270 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 271 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 272 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 273 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 274 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 275 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 276 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 277 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 278 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 279 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 280 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 281 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 282 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 283 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 284 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 285 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 286 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 287 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 288 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 289 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 290 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 291 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 292 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 293 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 294 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 295 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 296 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 297 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 298 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 299 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 300 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 301 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 302 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 303 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 304 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 305 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 306 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 307 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 308 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 309 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 310 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 311 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 312 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 313 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vj: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vk: REGIONAL REPORT: RUVUMA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents............................................................................................................................................................... i Acronyms......................................................................................................................................................................... v Preface ..........................................................................................................................................................................vi Executive summary........................................................................................................................................................ vii Illustrations..................................................................................................................................................................... xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 1 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Household Characteristics ........................................................................................................................... 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Litaracy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Paddy .............................................................................................................................. 23 3.3.4.3 Other Cereals.................................................................................................................. 26 3.3.5 Roots and Tuber Crops Production.................................................................................................. 26 3.3.5.1 Cassava........................................................................................................................... 27 3.3.5.2 Sweet Potatoes................................................................................................................ 28 3.3.6 Pulse Crops Production .................................................................................................................... 28 3.3.6.1 Beans............................................................................................................................... 30 3.3.7 Oil Seed Production.......................................................................................................................... 32 3.3.7.1 Groundnuts ..................................................................................................................... 32 3.3.8 Fruits and Vegetables ........................................................................................................................ 33 3.3.8.1 Tomatoes ........................................................................................................................ 35 3.3.8.2 Cabbage .......................................................................................................................... 37 3.3.8.3 Onions............................................................................................................................. 37 3.3.9 Other Annual Crops Production....................................................................................................... 40 3.3.9.1 Tobacco .......................................................................................................................... 40 3.4 Permanent Crops........................................................................................................................................... 40 3.4.1 Cashewnuts....................................................................................................................................... 43 3.4.2 Coffee ........................................................................................................................................ 45 3.4.3 Banana ........................................................................................................................................ 45 3.4.4 Pigeon peas ....................................................................................................................................... 45 3.5 Inputs/Implements Use................................................................................................................................. 48 3.5.1 Methods of land clearing................................................................................................................... 48 3.5.2 Methods of soil preparation.............................................................................................................. 48 3.5.3 Improved seeds use........................................................................................................................... 50 3.5.4 Fertilizers use.................................................................................................................................... 51 3.5.4.1 Farm Yard Manure Use.................................................................................................. 51 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 52 3.5.4.3 Compost Use .................................................................................................................. 53 3.5.5 Pesticide Use..................................................................................................................................... 54 3.5.5.1 Insecticide Use................................................................................................................ 54 3.5.5.2 Herbicide Use................................................................................................................. 55 3.5.5.3 Fungicide Use................................................................................................................. 55 3.5.6 Harvesting Methods.......................................................................................................................... 56 3.5.7 Threshing Methods .......................................................................................................................... 56 3.6 Irrigation .................................................................................................................................................... 56 3.6.1 Area planted with annual crops and under irrigation....................................................................... 56 3.6.2 Sources of water used for irrigation................................................................................................. 57 3.6.3 Methods of obtaining water for irrigation........................................................................................ 59 3.6.4 Methods of water application .......................................................................................................... 59 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing .................................................................................................. 59 3.7.1 Crop Storage ..................................................................................................................................... 59 3.7.1.1 Method of Storage.......................................................................................................... 60 3.7.1.2 Duration of Storage ........................................................................................................ 60 3.7.1.3 Purpose of Storage.......................................................................................................... 61 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 61 3.7.2 Agro processing and by-products...................................................................................................... 62 3.7.2.1 Processing Methods........................................................................................................ 62 3.7.2.2 Main Agro-processing Products..................................................................................... 62 3.7.2.3 Main use of primary processed Products....................................................................... 63 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 63 3.7.3 Crop Marketing................................................................................................................................. 64 3.7.3.1 Main Marketing Problems.............................................................................................. 64 3.7.3.2 Reasons for Not Selling.................................................................................................. 64 3.8 Access to Crop Production Services............................................................................................................ 65 3.8.1 Access to Agricultural Credits ......................................................................................................... 65 3.8.1.1 Source of Agricultural Credits ....................................................................................... 65 3.8.1.2 Use of Agricultural Credits............................................................................................ 65 3.8.1.3 Reasons for not using agricultural credits...................................................................... 66 3.8.2 Crop Extension ................................................................................................................................. 66 3.8.2.1 Sources of crop extension messages.............................................................................. 66 3.8.2.2 Quality of extension ....................................................................................................... 68 3.9 Access to Inputs ............................................................................................................................................. 68 3.9.2 Inorganic Fertilisers .......................................................................................................................... 68 3.9.3 Improved Seeds ................................................................................................................................. 69 3.9.4 Insecticides and Fungicide ................................................................................................................ 69 3.10 Tree Planting................................................................................................................................................... 70 3.11 Irrigation and Erosion Control Facilities .................................................................................................. 71 3.12 Livestock Results........................................................................................................................................... 73 3.12.1 Cattle Production .............................................................................................................................. 73 3.12.1.1 Cattle Population............................................................................................................ 73 3.12.1.2 Herd size......................................................................................................................... 73 3.12.1.3 Cattle Population Trend ................................................................................................. 75 3.12.1.4 Improved Cattle Breeds.................................................................................................. 75 3.12.2 Goat Production................................................................................................................................ 75 3.12.2.1 Goat Population.............................................................................................................. 75 3.12.2.2 Goat Herd Size ............................................................................................................... 77 3.12.2.3 Goat Breeds .................................................................................................................... 77 3.12.2.4 Goat Population Trend ................................................................................................... 77 3.12.3 Sheep Production.............................................................................................................................. 77 3.12.3.1 Sheep Population............................................................................................................ 77 3.12.3.2 Sheep Population Trend ................................................................................................. 79 3.12.4 Pig Production .................................................................................................................................. 79 3.12.4.1 Pig Population Trend...................................................................................................... 79 TOC __________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census iv 3.12.5 Chicken Production .......................................................................................................................... 81 3.12.5.1 Chicken Population ........................................................................................................ 81 3.12.5.2 Chicken Population Trend.............................................................................................. 81 3.12.5.3 Chicken Flock Size......................................................................................................... 81 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 82 3.12.6 Other Livestock ................................................................................................................................ 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming..................................................................................................................... 82 3.12.8 Access to Livestock Services ........................................................................................................... 84 3.12.8.1 Access to livestock extension Services.......................................................................... 84 3.12.8.2 Access to Veterinary Clinic ........................................................................................... 84 3.12.8.3 Access to village watering points/dam .......................................................................... 85 3.12.9 Animal Contribution to Crop Production......................................................................................... 85 3.12.9.1 Use of Draft Power......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 86 3.12.9.4 Use of Compost ............................................................................................................. 86 3.12.10 Fish Farming..................................................................................................................................... 86 3.13 Poverty Indicators......................................................................................................................................... 89 3.13.1 Access to Infrastructure and Other Services.................................................................................... 89 3.13.2 Type of Toilets.................................................................................................................................. 90 3.13.3 Household’s assets............................................................................................................................ 90 3.13.4 Sources of Light Energy................................................................................................................... 90 3.13.5 Sources of Energy for Cooking........................................................................................................ 90 3.13.6 Roofing Materials............................................................................................................................. 91 3.13.7 Access to Drinking Water ................................................................................................................ 91 3.13.8 Food Consumption Pattern............................................................................................................... 92 3.13.8.1 Number of Meals per Day.............................................................................................. 92 3.13.8.2 Meat Consumption Frequencies..................................................................................... 92 3.13.8.3 Fish Consumption Frequencies...................................................................................... 92 3.13.9 Food Security.................................................................................................................................... 92 3.13.10 Main Source of Cash Income........................................................................................................... 93 PART IV: RUVUMA PROFILES ............................................................................................................................. 95 4.1 Region Profile ................................................................................................................................................. 95 4.2 District Profiles................................................................................................................................................... 4.2.1 Tunduru.............................................................................................................................................. 96 4.2.2. Songea Rural...................................................................................................................................... 98 4.2.3 Mbinga.............................................................................................................................................100 4.2.4 Songea Urban...................................................................................................................................102 4.2.5 Namtumbo .......................................................................................................................................104 ACRONYMS _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Ruvuma region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in th e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina Chuwa The Director General National Bureau of Statistics ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Ruvuma region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Ruvuma region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Ruvuma region was 191,175 out of which 141,619 (74.1%) were involved in growing crops only, 132 (0.1%) rearing livestock only, and 49,424 (25.9%) were involved in crop production as well as livestock keeping. In summary, Ruvuma region had 191,043 households involved in crop production and 49,556 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provided most of their cash income followed by permanent crop farming, off-farm income, livestock keeping/herding, remittances, fish/hunting/gathering and tree/forest resources. The region has a literacy rate of 75 percent. The highest literacy rate was found in Songea Urban district (83%) followed by Mbinga district (80%) and Songea Rural district (78%). Tunduru and Namtumbo districts had the lowest literacy rates of 64 and 75 percent respectively. The literacy rate for the heads of households in the region was 83 percent. The number of heads of agricultural households with formal education in Ruvuma region was 157,638 (82%), those without education were 30,529 (16%) and those with only adult education were 3,007 (2%). The majority of heads of agricultural households (77%) had primary level education whereas only 5 percent had post primary education. In Ruvuma region 74,141 households (39%) had only one member aged 5 and above involved in only one off-farm income generating activity, 40,234 households (21%) had two members involved in off-farm income generating activities and 11,565 households (6%) had more than two members involved in off-farm income generating activities ii) Crop Production Land Area The total area of land available to smallholders was 799,230 ha. The Regional average land area utilised for agriculture per household was only 3.0 ha. This figure is above the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 358,203 hectares out of which 110 hectares (0.03%) were planted during dry season and 358,093 hectares (99.97%) during wet season. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census viii An estimated area of 194,211 ha (54.2% of the total planted area with annuals) was with cereals, followed by roots and tubers (94,522 hectares, 26.4%), pulses (39,697 hectares, 11.1%), oil seeds (17,464 hectares, 4.9%), cash crops (7,169 hectares, 2.0%) and fruit and vegetables (5,140 hectares, 1.4%). Maize Maize was the dominant cereal crop grown in Ruvuma region. The area planted with maize represented 71.9 percent of the total area planted with cereal crops. The total production of maize was 179,283 tonnes from a planted area of 139,505 hectares resulting in a yield of 1.3 t/ha. There was a sharp increase in maize production (48%) in 1999 after which the production leveled in 2000 and then it declined during the year 2003. The average area planted with maize per household was 0.8 hectares, however it ranged from 0.6 hectares in Tunduru district to 1.0 hectares in Namtumbo district. In the wet season, Mbinga district had the largest area of maize (50,346 ha) followed by Namtumbo (28,809 ha), Songera Rural (28,503 ha), Tunduru (27,246 ha), and Songea Urban (4,600 ha). Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Ruvuma region was 81,184. This represented 42 percent of the total crop growing households in Ruvuma region. The total production of paddy was 39,510 tonnes from a planted area of 38,178 hectares resulting in a yield of 1.03 t/ha. Cassava The area planted with cassava was larger than any other root and tuber crop in Ruvuma region. It accounted for 87.0 percent of the total roots and tubers production. The total production of cassava during the census year was 101,965 tonnes from a planted area of 87,522 hectares resulting in a yield of 1.2t/ha Fruit and Vegetables The total production of fruits and vegetables was 16,087 tonnes. The most cultivated fruit and vegetable crop was the tomato crop with a production of 7,328 tonnes (46% of the total fruit and vegetables produced) followed by cabbage (4,119t, 26%) and onions (1,704t, 11%). The production of other fruit and vegetable crops were relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 124,910 hectares which is 35 percent of the area planted with annual crops in the region. The most important permanent crop in Ruvuma region is cashewnut which had a planted area of 74,124 ha, (61% of the planted area of all permanent crops) followed by coffee (29,961 ha, 24%), and banana (7,751 ha, 6%). Improved Seeds The planted area using improved seeds was estimated at 35,208 ha which represents 8 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the dry season was 13.6 percent, slightly higher than the corresponding percentage use in the wet season (9.8%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census ix Use of Fertilizers The planted area without fertiliser for annual crops was 281,740 hectares representing 78.7 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertilizers were applied to 43,402 ha which represents 12.1 percent of the total planted area (56.8% of the area planted with fertiliser application in the region). This was followed by farm yard manure (29,470 ha, 38.5%). Compost fertilizers were used on a very small area which represented only 47 percent of the area planted with fertilizers. Irrigation In Ruvuma region, the area of annual crops under irrigation was 9,104 ha representing 3 percent of the total area planted. The area under irrigation during the wet season was 15 ha accounting for 0.16 percent of the total area under irrigation. The district with the largest planted area under irrigation with annual crops was Mbinga (2,731 ha, 30% of the total irrigated planted area with annual crops in the region). This was followed by Namtumbo with (2,122 ha, 23%) and then Tunduru (2,025 ha, 22%). When expressed as a percentage of the total area planted in each district, Songea Urban had the highest with 10.8% of the planted area in the district under irrigation. This is followed by Namtumbo (3.0%), Tunduru (2.4%), Mbinga (2.1%) and Songea Rural (1.7%) Crop Storage There were 181,775 crop growing households (95.1% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 172,771 households storing 34,081 tonnes as of 1st January 2004. This was followed by paddy (72,495 households, 3,273t), beans and other pulses (86,592 households, 2,599), sorghum and millet (27,879 households, 910t), groundnuts and bambara nuts (21,827 households, 469t) and seeweed (8,550 households, 461t). Other crops were stored in very small quantities. Crop Marketing The number of households that reported selling crops was 176,924 which represent 92.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Tunduru (96%) followed by Namtumbo (94%), Mbinga (91%), Songea Rural (91%) and Songea Urban (82%) Agricultural Credit The census result shows that in Ruvuma region a considerable number of agricultural households (38,567, 18.6%) accessed credit out of which 32,939 (85%) were male-headed households and 5,628 (15%) were female headed households. In all districts both male and female headed households accessed agricultural credit. Crop Extension Services The number of Agricultural households that received crop extension was 67,199 (35% of total crop growing households in the region). Some districts had more access to extension services than others, with Namtumbo having a relatively high proportion of households (55%) that received crop extension messages followed by Songea Urban (40%), Mbinga (35%), Tunduru(30%) and Songea Rural (23%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census x Soil Erosion and Water Harvesting Facilities The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 12,403 which represent 6 percent of the total number of agricultural households in the region. The proportion of households with soil erosion control and water harvesting facilities was highest in Mbinga district (12%) followed by Songea Urban (11%), Songea Rural (3%), Namtumbo (1%) and Tunduru (1%) iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 121,175. Cattle were the dominant livestock type in the region followed by goats, pigs and sheep. The region had 0.7 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Ruvuma region was 105,884 (87.4 % of the total number of cattle in the region), 15,111 cattle (12.5%) were dairy breeds and 181 cattle (0.1%) were beef breeds. Goats The number of goat-rearing-households in Ruvuma region was 68,381 (36% of all agricultural households in the region) with a total of 309,595 goats giving an average of 5 head of goats per goat-rearing-household. Sheep The number of sheep-rearing households was 7,390 (4% of all agricultural households in Ruvuma region) rearing 24,458 sheep, giving an average of 3 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chicken was 139,284 raising about 1,555,617 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Ruvuma region was ranked eighth out of the 11 Mainland regions. Use of Draft Power The region had 55 oxen. Only Songea Urban had 55 oxen which were used to cultivate 33 hectares of land. This represented only 0.001 percent of the total oxen found on the Mainland Fish Farming The number of households involved in fish farming in Ruvuma region was 4,035, representing 2 percent of the total agricultural households in the region. Songea Rural was the leading district with 1,294 households (32.1% of agricultural households involved in fish farming. In the region).This was followed by Namtumbo (933 households, 23.1%), Mbinga (910 households, 22.5%), Songea Urban (610 households, 14.9%) and Tunduru (298 households, 7.4%). ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xi iv) Poverty Indicators Availability of Toilets It was estimated that 96 percent of all rural agricultural households used the traditional pit latrines, 1 percent used improved pit latrine and 2 percent had flush toilets. Households with no toilet facilities represented 1 percent of the total agriculture households in the region. Household Assets Radios were owned by most rural agricultural households in Ruvuma region with 109,159 households (57.1% of the agriculture households in the region) owning the asset, followed bicycles (69,706 households, 36.5%), irons (49,616 households, 26.0%), wheelbarrows (7,944 households, 4.2%), mobile phones (2,460 households, 1.3%), vehicles (2,284 households, 1.2%), TVs/Videos (1,549 households, 0.8%) and landline phones (1,496 households, 0.8%) Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 50.7 percent of the total rural households using this source of energy followed by hurricane lamp (44.2%), pressure lamp (3.0%), firewood (1.0%), gas or biogas (0.3%) mains electricity (0.3%), candle (0.3%) and solar (0.2%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.1 percent of all rural agricultural households in Ruvuma region. This was followed by charcoal (1.9%). The rest of energy sources accounted for 1.0 percent. Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 69.2 percent of the rural agricultural households. This was followed by iron sheets (33.4%), grass/mud (4.0%), tiles (0.6%), concrete (0.2%) and asbestos (0.0%). Number of Meals per Day About 64.5 percent of the holders in the region took three meals per day, 33.4 percent took two meals and 1.9 percent took one meal. Only 0.2 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 25.2 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 6.6 percent whereas those with little problems represent 2.5 percent. About 3.2 percent of agriculture households always faced food shortages whilst 62.5 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 49.5 percent of all rural agricultural households. The second main cash income earning activity was selling of cash crops (26%) followed by other casual cash earnings (8%), business income (4%), wages and salaries (4%), fishing (3%), and remittance (3%). Only 1% of smallholder households reported the sale of livestock as their main source of cash income. ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .............................................................................................................................................. 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 23 3.3 Area, Production and Yield of Root and Tuber Crops by Season................................................................................ 29 3.4 Area, Quantity Harvested and Yield of Pulses by Season ................................................................................. 34 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season................................................................... 34 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 38 3.8 Land Clearing Methods....................................................................................................................................... 44 3.9 Planted Area by Type of Fertilizer Use and District – Wet and Dry Rainy Season.......................................... 46 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during Wet Season ...............................................................................................................................................46 3.11 Number of Households Storing Crops by Estimated Storage Loss and Crop ................................................... 11 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 61 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 62 3.14 Access to Inputs................................................................................................................................................... 64 3.15 Total Number of Households and Chickens Raised by Flock Size ....................................................................75 3.16 Head Number of Other Livestock by Type of Livestock and District............................................................... 78 3.17 Mean distances from holders dwellings to infrastructure and services by districts ...........................................86 3.18 Number of Households by Number of meals the Household normally takes per Day and District ................. 90 List of Charts 3.1 Agricultural Households by Type of Holdings................................................................................................... 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 15 3.3 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District.............................................................................. 16 3.6 Percentage of Persons Aged 5 Years and Above by Education Status.............................................................. 16 3.7 Percentage of Population Aged 5 years and Above by District and Educational Status........................................................................................................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Number of Households by Number of Members with Off-farm Income Generating Activities ...................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Members with Off-farm Income Generating Activities ............................................................................................................................. 17 3.11 Utilized and Usable Land per Household by District..........................................................................................18 3.12 Percentage Distribution of Land Area by Type of Land Use............................................................................. 18 3.13 Area Planted with Annual Crops (ha) by Season ............................................................................................... 20 3.14 Area Planted with Annual Crops by Season and District................................................................................... 20 3.15 Area Planted per household by Season and District........................................................................................... 20 3.16 Planted Area for the Main Annual Crops (ha).................................................................................................... 21 3.17a Planted Area per Household by Selected Crops 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type..................................................... 21 3.18 Area planted with Annual Crops by Type of Crops and Season........................................................................ 21 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 23 3.20 Time Series Data on Maize Production ............................................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 25 3.22 Time Series of Maize Planted Area and Yield – Ruvuma Region..................................................................... 25 3.23 Total Planted Area and Area of Paddy per Household by District .................................................................... 25 3.24 Time Series Data on Paddy Production – Ruvuma Region ............................................................................... 25 3.25 Time Series of Paddy Planted Area and Yield – Ruvuma Region..................................................................... 27 3.26 Area Planted With Sorghum, Bulrush Millet, Finger Millet and Wheat and Barley by District ...................... 27 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................... 27 3.28 Area planted with Cassava during the census/survey years................................................................................29 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................29 3.30 Cassava Planted Area per Cassava Growing Households by District ............................................................... 29 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xiii 3.31 Total Area Planted with Irish Potatoes and Planted Area per Household by District....................................... 30 3.32 Area Planted and Yield of Major Pulse Crops ................................................................................................... 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 32 3.34 Area Planted per Bean Growing Household by District (Wer Season Only).................................................... 32 3.35 Time Series Data on Bean Production – Ruvuma Region ................................................................................. 32 3.36 Time Series of Beans Planted Area and Yield - Ruvuma .................................................................................. 32 3.37 Area Planted and Yield of Major Oil Seed Crops.............................................................................................. 34 3.38 Time Series Data on Groundnut production – Ruvuma Region ........................................................................ 34 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District ........................ 34 3.40 Area Planted per Groundnut Growing Household by District (Wet Season Only)........................................... 34 3.41 Area Planted and Yield of Fruit and Vegetables................................................................................................ 35 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District ..................................... 36 3.43 Area Planted per Tomato Growing Household by District (Wet Season Only)................................................ 36 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District .................................. 36 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District ....................................... 38 3.46 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................38 3.47 Area Planted for Annual and Permanent Crops.................................................................................................. 38 3.48 Area Planted with the Main Permanent Crops ................................................................................................... 39 3.49 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 39 3.50 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District................... 39 3.51 Percent of Area Planted with Coffee and Average Planted Area per Household by District ........................... 41 3.52 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 41 3.53 Percent of Area Planted with Pigeon peas and Average Planted Area per Household by District................... 41 3.54 Number of Households by Method of Land Clearing during Wet Season........................................................ 44 3.55 Area Cultivated by Cultivation Method...............................................................................................................44 3.56 Area Cultivated by Method of Cultivation and District..................................................................................... 44 3.57 Planted Area with Improved Seed ...................................................................................................................... 44 3.58 Planted Area with Improved Seed by Crop Type............................................................................................... 46 3.59 Percentage of Crop Type Planted Area with Improved Seeds........................................................................... 46 3.60 Area of Fertilizer Application by Type of Fertilizer .......................................................................................... 47 3.61 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 47 3.62 Planted Area with Farm Yard Manure by Crop type ......................................................................................... 47 3.63a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 47 3.63b Proportion of Planted Area Applied with Farm Yard Manure by District ........................................................ 47 3.64 Planted Area with Inorganic Fertiliser by Crop type – Annuals........................................................................ 50 3.65a Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 50 3.65b Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 50 3.66a Planted Area with Compost by Crop Type......................................................................................................... 50 3.66b Percentage of Planted Area with Compost by Crop Type ................................................................................. 51 3.66c Proportion of Planted Area Applied with Compost by District......................................................................... 51 3.67 Planted area (ha) by Pesticide use....................................................................................................................... 51 3.68 Planted Area applied with Insecticides by Crop Type ....................................................................................... 51 3.69 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 51 3.70 Percent of Planted Area Applied with Insecticides by District - Ruvuma......................................................... 53 3.71 Planted Area applied with herbicides by Crop Type.......................................................................................... 53 3.72 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 53 3.73 Proportion of Planted Area applied with Herbicides by District ...................................................................... 53 3.74 Planted Area applied with Fungicides by Crop Type......................................................................................... 54 3.75 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 54 3.76 Proportion of Planted Area applied with Fungicides by District....................................................................... 54 3.77 Area of Irrigated Land......................................................................................................................................... 55 3.78 Planted Area and Percentage of Planted Area with Irrigation by District......................................................... 55 3.79 Time Series of Households with Irrigation – Ruvuma....................................................................................... 55 8.80 Number of Households with Irrigation by Source of Water.............................................................................. 56 3.81 Number of Households by Method of Obtaining Irrigation Water.................................................................... 56 3.82 Number of Households with Irrigation by Method of Field Application.......................................................... 56 3.83 Number of Households and Quantity Stored by Crop Type.............................................................................. 56 3.84 Number of households by Storage Methods....................................................................................................... 57 3.85 Number of households by method of storage and District (based on the most important household crop)..... 57 3.86 Normal Length of Storage for Selected Crops ................................................................................................... 57 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District .................................................. 58 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xiv 3.88 Number of Households by Purpose of Storage and Crop Type......................................................................... 58 3.89a Percentage of Households Processing Crops...................................................................................................... 59 3.89b Percent of Households Processing Crops by District......................................................................................... 59 3.90 Percent of Crop Processing Households by Method of Processing....................................................................59 3.91 Percent of Households by Type of Main Processed Product ............................................................................. 59 3.92 Number of Households by Type of Bi-product.................................................................................................. 60 3.93 Use of Processed Product.................................................................................................................................... 60 3.94 Percentage of Households Selling Processed Crops by District........................................................................ 60 3.95 Location of Sale of Processed Products.............................................................................................................. 60 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District ......................................... 61 3.97 Number of Crop Growing Households Selling Crops by District ..................................................................... 61 3.98 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 61 3.99 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 62 3.100 Proportion of Households who Received Credit by Main Source of Credit and District ................................. 62 3.101 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 62 3.102 Reasons for Not using Credit.............................................................................................................................. 62 3.103 Number of Households Receiving Extension Advice........................................................................................ 63 3.104 Number of Households that Received Extension by District............................................................................. 63 3.105 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 64 3.106 Number of Households that Received Extension by Reported Quality of Services.......................................... 64 3.107 Number of Households by Source of Inorganic Fertilizers................................................................................ 64 3.108 Number of Households Reporting Distance to Source of Inorganic Fertilizers................................................ 66 3.109 Number of Households by Source of Improved Seed........................................................................................ 66 3.110 Number of Households reporting Distance to Source of Improved Seeds........................................................ 66 3.111 Number of Households by Source of Insecticides/Fungicides........................................................................... 67 3.112 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 67 3.113 Number of Households with Planted Trees........................................................................................................ 67 3.114 Number of Planted Trees by Species...................................................................................................................68 3.115 Number of Trees Planted by Smallholders by Species and District .................................................................. 68 3.116 Number of Trees Planted by Location................................................................................................................ 68 3.117 Number of Households by purpose of Planted Trees......................................................................................... 68 3.118 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 68 3.119 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District........... 69 3.120 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 69 3.121 Total Number of Cattle ('000') by District.......................................................................................................... 71 3.122 Numbers of Cattle by Type and District............................................................................................................. 71 3.123 Cattle Population Trend ...................................................................................................................................... 72 3.124 Dairy Cattle Population Trend............................................................................................................................ 72 3.125 Total Number of Goats ('000') by District.......................................................................................................... 72 3.126 Goat Population Trend........................................................................................................................................ 73 3.127 Total Number of Sheep by District..................................................................................................................... 73 3.128 Sheep Population Trend...................................................................................................................................... 74 3.129 Total Number of Pigs by District........................................................................................................................ 74 3.130 Pig Population Trend........................................................................................................................................... 74 3.131 Total Number of Chicken by District ................................................................................................................. 75 3.132 Chicken Population Trend .................................................................................................................................. 75 3.133 Number of Improved Chicken by Type and District...........................................................................................75 3.134 Layer Population Trend....................................................................................................................................... 78 3.135 Proportion of Livestock Keeping Households that Reported Tsetse flies and Ticks Problems by District...... 78 3.136 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............79 3.137 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services........ 79 3.138 Number of Households by Distance to Veterinary Clinic.................................................................................. 79 3.139 Number of Households by Distance to Veterinary Clinic and District.............................................................. 79 3.140 Number of Households by Distance to Village Watering Point ........................................................................ 82 3.141 Number of Households by Distance to Watering Point and District................................................................. 82 3.142 Number of Households using Draft Animals ..................................................................................................... 82 3.143 Number of Households using Draft Animals by District................................................................................... 82 3.144 Number of Households using Organic Fertilizers.............................................................................................. 84 3.145 Area of Application of Organic Fertilizers by District....................................................................................... 84 3.146 Number of Households Practicing Fish Farming – Ruvuma ............................................................................. 84 3.147 Number of Households Practicing Fish Farming by District – Ruvuma........................................................... 85 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xv 3.148 Fish Production.................................................................................................................................................... 85 3.149 Agricultural Households by Type of Toilet Facility .......................................................................................... 86 3.150 Percentage Distribution of Households Owning the Assets............................................................................... 86 3.151 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................86 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................. 87 3.153 Percentage Distribution of Households by Type of Roofing Material .............................................................. 87 3.154 Percentage Distribution of Households With Grass/Leaves Roofs by District ................................................. 87 3.155 Percentage Distribution of Households Reporting Main Source of Drinking Water and Season..................... 87 3.156 Percentage Distribution of Households by Distance to Main Source Drinking Water and Season.................. 90 3.157 Number of Agriculture Households by Number of Meals per day.................................................................... 90 3.158 Number of Households by Frequency of Meat and Fish Consumption..............................................................91 3.159 Percent Distribution of the Number of Households by Main Source of Income............................................... 91 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................... 19 3.9 Area planted and Percentage During Wet Season by District............................................................................ 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District .................................. 22 3.11 Area Planted per Maize Growing Household..................................................................................................... 24 3.12 Planted Area and Yield of Maize by District ..................................................................................................... 24 3.13 Planted Area and Yield of Paddy by District ..................................................................................................... 26 3.14 Area Planted per Paddy Growing Household..................................................................................................... 26 3.15 Planted Area and Yield of Cassava by District .................................................................................................. 28 3.16 Area Planted per Cassava Growing Household.................................................................................................. 28 3.17 Planted Area and Yield of Beans by District...................................................................................................... 31 3.18 Area Planted per Beans Growing Household..................................................................................................... 31 3.19 Planted Area and Yield of Groundnuts by District ............................................................................................ 33 3.20 Area Planted per Groundnuts Growing Household............................................................................................ 33 3.24 Planted Area and Yield of Onions by District.................................................................................................... 39 3.25 Planted Area and Yield of Tobacco by District.................................................................................................. 40 3.26 Area Planted per Tobacco Growing Household................................................................................................. 40 3.27 Planted Area and Yield of Cashewnuts by District............................................................................................ 41 3.28 Area Planted per Cashewnut Growing Household............................................................................................. 41 3.31 Planted Area and Yield of Coffee by District..................................................................................................... 42 3.32 Area Planted per Coffee Growing Household.................................................................................................... 42 3.33 Planted Area and Yield of Banana by District ................................................................................................... 43 3.34 Area Planted per Banana Growing Household................................................................................................... 43 3.35 Planted Area and Yield of Pigeon Peas by District............................................................................................ 45 3.36 Area Planted per Pigeon Peas Growing Household ........................................................................................... 45 3.41 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 48 3.42 Number and Percent of Crop Growing Households using Improved Seed by District .....................................48 3.35 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 49 3.36 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 49 3.56 Planted Area and Percent of Planted Area with Farm Yard Manure application by District.............................52 3.57 Planted Area and Percent of Planted Area with Compost application by District ............................................ 52 3.37 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 65 3.38 Number of Households and Percent of Total Households Selling Crops by District........................................ 65 3.42 Number and Percent of Households with water Harvesting Bunds by District................................................. 70 3.43 Cattle population by District as of 1st Octobers 2003.........................................................................................76 3.44 Cattle Density by District as of 1st October 2003...............................................................................................76 3.45 Goat population by District as of 1st Octobers 2003 ......................................................................................... 77 3.46 Goat Density by District as of 1st October 2003................................................................................................ 77 3.47 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 80 3.48 Sheep Density by District as of 1st October 2003.............................................................................................. 80 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _______________________________________________________________________________________________ ___ Tanzania Agriculture Sample Census xvi 3.49 Pig population by District as of 1st Octobers 2003............................................................................................ 81 3.50 Pig Density by District as of 1st October 2003 .................................................................................................. 81 3.51 Number of Chickens by District as of 1st October 2003 ................................................................................... 83 3.52 Density of Chickens by District as of 1st October 2003.................................................................................... 83 3.59 Number and Percent of Households Practicing Fish Farming by District......................................................... 88 3.60 Number and Percent of Households Without Toilets by District ...................................................................... 88 3.61 Number and Percent of Households using Grass/Leaves for roofing material by District ............................... 92 3.62 Number and Percent of Households eating 3 meals per day by District ........................................................... 92 3.63 Number and percent of Households Reporting food insufficiency by District ................................................. 93 3.62 Number and Percent of Households eating Meat Once per Week by District .................................................. 93 3.63 Number and Percent of Households eating Fish Once per Week by District.................................................... 96 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Ruvuma region is situated in the southern part of the country along with Mtwara and Lindi regions. It borders the Republic of Mozambique in the south, Lake Nyasa in the west and Iringa and Morogoro regions in the north. The region comprises five districts of Tunduru, Songea Rural, Mbinga, Songea Urban and Namtumbo. The region headquarters is located in Songea Urban District. 1.3 Land Area The region has an area of 66,477 square kilometers, of which about 50,540 square kilometers are arable land. Also out of the total area 2,979 square kilometers are under water bodies while 63,498 square kilometers are land area. The forest reserves cover 6,958 square kilometers. 1.4 Climate 1.4.1 Temperature The temperature in the region is moderately mild at an average temperature of 23oC depending on the altitude and season. The months of June, July and August are chilly with the temperature dropping to 13oC , particularly in the areas surrounding Matengo highlands in Mbinga district. October and November are the hottest months with an average temperature of 30oC in the lowlands. 1.4.2 Rainfall The region has two seasons, the dry and the wet seasons. The dry season (vuli) is from October to November and the wet season (Masika) from April to May. The average rainfall is between 800 and 1,800 millimeters. The amount varies from one district to another. Mbinga district has the highest average annual rainfall of 1,225 millimeters while Tunduru district has the lowest rainfall which is usually less than 900 millimeters per year. 1.5 Population According to the 2002 Population and Housing Census, there were 1,117,166 inhabitants in Ruvuma region. The population of Ruvuma region ranked 17th of the 21 regions of Tanzania Mainland. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 376,616 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 Million with a per capita income of shillings 337,117. The region held 10th position among regions on GDP and contributed about 3.8 percent of the national GDP1 . The region is famous for producing both food and cash crops. The main food crops produced in Ruvuma region include: maize, beans, sorghum, cassava, millet, paddy, wheat, sweet potatoes, irish potatoes, yams, sunflower, simsim and grounnuts. The main cash crops include cashew nut, tobacco and coffee. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 4 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 141 villages were from Ruvuma region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 5 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 6 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three Urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census for Ruvuma region. based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Ruvuma region was 191,175. The largest number of agriculture households was in Mbinga (79,589) followed by Tunduru (45,053), Songea Rural (28,109), Namtumbo (27,456) and Songea Urban (5,717) (Map 3.1). The highest density of households was found in Songea Urban (45/km2) followed by Mbinga (18/ km2) (Map 3.2). Most households 141,619 (74.1%) were involved in growing crops only, 132 (0.1%) were rearing livestock only, and 49,424 (25.9%) were involved in crop production as well as livestock keeping. There were no pastoralists in the region (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income In Ruvuma region most of the agricultural households ranked annual crop farming as the activity that provides most of their cash income followed by permanent crop farming, off farm income, livestock keeping/herding, remittances, fishing/hunting & gathering and tree/forest resources (Table 3.1). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittanc es Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 1 2 4 3 5 6 7 Songea Rural 1 2 4 3 5 6 7 Mbinga 1 2 3 4 5 6 7 Songea Urban 1 3 4 2 5 6 7 Namtumbo 1 2 3 4 5 6 7 Total 1 2 4 3 5 6 7 Chart 3.1 Agriculture Households by Type - Ruvuma Crops and livestock only 25.9% Livestock only 0.1% Crops only 74.1% Songea Urban Namtumbo Songea Rural 29,115 30,772 6,943 46,898 77,447 Mbinga Tunduru Namtumbo Songea Urban Songea Rural 3 45 6 7 18 Mbinga Tunduru 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 80,000 to 80,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Number of Agricultural Households Total Number of Agricultural Households by District MAP 3.01 RUVUMA MAP 3.02 RUVUMA Number of Agricultural Households Per Square Kilometer of Land by District Number of Agricultural Households Per Square Kilometer Number of Agricultural Households Number of Agricultural Households Per Square Kilometer RESULTS 12 Songea Urban Mbinga Namtumbo Songea Rural 6,943 29,115 30,772 77,315 46,898 Tunduru Namtumbo Songea Urban Songea Rural 100% 100% 100% 100% 99.8% Mbinga Tunduru Number of Crop Growing Households by District MAP 3.03 RUVUMA MAP 3.04 RUVUMA Percent of Crop Growing Households by District Percent of Crop Growing Households Tanzania Agriculture Sample Census 80,000 to 80,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Number of Crop Growing Households 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Crop Growing Households Percent of Crop Growing Households RESULTS 13 Songea Rural Songea Urban Namtumbo 6 45 3 7 17 Mbinga Tunduru Songea Rural Songea Urban Namtumbo 17% 17% 11% 4% 51% Mbinga Tunduru Number of Crop Growing Households Per Square Kilometer of Land by District MAP 3.05 RUVUMA Percent of Crop and Livestock Households MAP 3.06 RUVUMA Percent of Crop and Livestock Households by District Tanzania Agriculture Sample Census Number of Crop Growing Households Per Square Kilometer 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 40 to 60 30 to 40 20 to 30 10 to 20 0 to 10 Number of Crop Growing Households Per Square Kilometer Percent of Crop and Livestock Households RESULTS 14 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Ruvuma region was 169,347 (86% of the total regional agricultural households) while the female-headed households were 26,828 (14% of the total regional agricultural households). The mean age of household heads was 45 years (44 years for male heads and 49 years for female heads) (Chart 3.2). The results from six censuses/surveys years show that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Ruvuma region had a total rural agricultural population of 891,662 of which 438,796 (49%) were males and 452,866 (51%) were females. Whereas age group 0-14 constituted 43 percent of the total rural agricultural population, age group 15–64 (active population) was only 53 percent (Chart 3.3). Ruvuma region had an average household size of 4.7 with Mbinga district having the lowest household size of 4.4. 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Ruvuma region had a total literacy rate of 75 percent. The highest literacy rate was found in Songea Urban district (83%) followed by Mbinga district (80%) and Songea Rural district (78%). Tunduru and Namtumbo districts had the lowest literacy rates of 64 and 75 percent respectively (Chart 3.4). Chart 3.3 Percent Distribution of Population by Age and Sex - RUVUMA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Figure 3.4 Percentage LiterateLevel of Household Members by District 0 20 40 60 80 100 Songea Urb Mbinga Songea Rur Namtumbo Tunduru Districts Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 83 percent. The literacy rates for the male male heads was 85% and that of female heads of households was 68 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Songea Urban (89.4%) followed by Mbinga (87.6%), Songea Rural (85.2%), Namtumbo (83.8%) and Tunduru (72.8%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 50 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 30 percent were still attending school. Those who have never attended school were 20 percent (Chart 3.6). Agricultural households in Mbinga district had the highest percentage (55%) of population aged 5 years and above who had completed different levels of education. It was followed by Songea Rural and Songea Urban districts each with 53 percent. Tunduru and Namtumbo districts had the lowest percentages of 42 and 49 respectively. The number of heads of agricultural households with formal education in Ruvuma region was 157,638 (82%), those without education were 30,529 (16%) and those with only adult education were 3,007 (2%). The majority of heads of agricultural households (77%) had primary level education whereas only 5 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Ruvuma region, Mbinga had the highest percentages (43% for primary and 59% for secondary). This was followed by Tunduru (21% primary and 9% Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Attending School 30.0% Never Attended 20.0% Completed 50.0% Chart 3.5 Literacy Rates of Head of Household by Sex and District - RUVUMA 0.0 25.0 50.0 75.0 100.0 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent Male Female Total Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 2% Post Primary Education 5% No Education 16% Primary Education 77% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent Attending School Completed Never Attended RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 secondary), Songea Rural (17% primary and 11% secondary) and Namtumbo (16% primary and 15% secondary). Songea Urban had the lowest percentage of heads of agricultural households with primary education (4%) and secondary education (6%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important in agriculture households in Ruvuma with 66 percent of househiolds having at least one member with off-farm income. In Ruvuma region, of the households with a member engaged in off-farm income generating activities, 74,141 households (39%) had only one member aged 5 and above involved in only one off-farm income generating activity, 40,234 households (21%) had two members involved in off-farm income generating activities and 11,565 households (6%) had more than two members involved in off-farm income generating activities Songea Urban district had the highest percentage of agriculture households with their members engaged in off-farm income generating activities (over 55% of total agriculture households in the district). Other districts with high percentages were Songea Rural (74%) and Mbinga (69%). Namtumbo and Tunduru districts had the lowest percentages of agriculture households with off-farm income (63% and 56% respectively). The district with the highest percent of agriculture households having more than one member involved in off-farm income was Songea Urban (36%). Tunduru district had very few households with more than one member having off-farm income (18%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income None, 65,230, 65,230, 34% One, 74,141, 74,141, 39% Two, 40,239, 40,239, 21% More than Two, 11,565, 11,565, 6% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo Districts Percent More than Two Two One None RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 country, but the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 799,230 ha. The Regional average land area utilised for agriculture per household was only 3.0 ha. This figure is above the national average which is estimated at 2.0 hectares. Seventy five percent of the total land available to smallholders was utilised. Only 25 percent of usable land available to smallholders was not used (Chart 3.11). Large differences in land area utilised per household exist between districts with Songea Urban and Tunduru utilizing between 2.0 and 3.6 ha per household. The smallest land area utilised per household was found in Songea Urban (2.0 ha). The percentage utilized of the usable land per household was highest in Tunduru (82%) and lowest in Namtumbo (63%). (Map 3.7) 3.2.2 Types of Land Use The area of land under temporary monocrops was 204,996 hectares (25.6% of the total land available to smallholders in Ruvuma), followed by permanent/ monocrops (120,484 ha, 15.1%), uncultivatable usable land (115,091 ha, 14.4%), natural bush (79,522 ha, 9.9%), area under fallow (71,887 ha, 9.0%), permanent/annual mixed crops (66,045, ha, 8.3%), temporary mixed crops (46,471 ha, 5.8%), permanent mixed crops (39,451, ha, 4.9%), unusable area (24,297 ha, 3.0%), area planted with trees (10,991 ha, 1.4%), area rented to others (10,766 ha, 1.3%), and area under pasture (9,228 ha, 1.2%). 3.3 Annual Crop and Vegetable Production Ruvuma region has two seasons, namely the dry season (October to November) and the wet season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Districts Area/household 0 10 20 30 40 50 60 70 80 90 Percentage utilized Total Usable Area available (ha) Area utilised (ha) Percent Utilisation Chart 3.12 Land Area by Type of Use 15.0 26.0 14.0 10.0 9.0 8.0 6.0 5.0 3.0 1.0 1.0 1.0 0 50,000 100,000 150,000 200,000 250,000 Pasture Planted Trees Rented to Others Unusable Permanent Mixed Crops Temporary Mixed Crops Permanent / Annual Mix Fallow Natural Bush Uncultivated Usable Land Permanent Mono Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (hectares) Wet Season, 358,093, 99.97% Dry Season, 110, 0.03% Wet Season Dry Season Songea Urban Namtumbo Songea Rural 10,920ha 61,969ha 70,385ha 84,544ha 130,386ha Mbinga Tunduru Songea Urban Songea Rural Namtumbo 76.9% 68.1% 63.3% 81.6% 79.4% Mbinga Tunduru Utilized Land Area Expressed as a Percent of Available Land by District Total Planted Area (Annual Crops) MAP 3.08 RUVUMA Total Planted Area (Annual Crops) by District Percent of Utilized Land Area MAP 3.07 RUVUMA 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Percent of Utilized Land Area Total Planted Area (Annual Crops) Tanzania Agriculture Sample Census RESULTS 19 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 3.3.1 Area Planted The area planted with annual crops and vegetables was 358,203 hectares out of which 110 hectares (0.03%) were planted during dry season and 358,093 hectares (99.97%) during wet season (Chart 3.13). Mbinga had the largest area planted with annual crop and vegetables (130,386ha, 36.4%) followed by Tunduru (84,544 ha, 23.6%), Namtumbo (70, 385 ha, 19.6%), Songea Rural (61,969 ha, 17.3%) and Songea Urban (10,920 ha, 3.0%) (Chart 3.14 and Map 3.8). The average areas planted per household during the dry and wet seasons were 1.5 and 1.9 ha respectively. The districts with the largest planted area per household (the average of the two seasons) were Namtumbo (2.4 ha) followed by Songea Rural (2.0 ha) The district with the smallest average area planted was Songea Urban (1.6ha). The planted area occupied by cereals was 194,211 ha (54.2%of the total area planted with annuals). This was followed by roots and tubers (94,522 hectares, 26.4%), pulses (39,697 hectares, 11.1%), oil seeds (17,464 hectares, 4.9%), cash crops (7,169 hectares, 2.0%) and fruit and vegetables (5,140 hectares, 1.4%). The average area planted per household during the wet season in Ruvuma region was 1.9 hectares, however, there were small district differences. Namtumbo had the largest planted area per household (2.43 ha) followed by Songea Rural (2.02 ha) and Tunduru (1.81 ha). The smallest planted area per household was in Songea Urban (1.57 ha). In Namtumbo the area planted per household in the dry season represents 100 percent of the total planted area per household, whereas in the remaining districts the corresponding figure is 0 percent (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether it is annual or permanent. The second section contains an analysis on production based on crop types. Chart 3.14 Area Planted with Annual Crops by Season and District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Region Area Planted (ha) 0.00 0.04 0.08 0.12 0.16 0.20 Percentage Planted Dry Season Wet Season % Area planted in Dry Season Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0 1 2 3 4 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Area Planted (ha) Wet Season Dry Season RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 21 3.3.2 Crop Importance Maize was the dominant annual crop grown in Ruvuma region and it had a planted area 1.59 times greater than cassava, which had the second largest planted area. The area planted with maize constituted 39 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) were paddy, beans, finger millet, groundnuts, tobacco and sweet potatoes (Chart 3.16). Households that grew maize, soya beans and cassava had larger planted areas per household than other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Ruvuma region. The area planted with cereals was 194,211 ha (54.2% of the total planted area), followed by root and tubers with 94,522 ha (26.4%), pulses 39,697 ha (11.1%), oil seeds 17,464 ha (4.9%), cash crops 7,169 ha (2.0%). Fruits and vegetables had the least planted area of about 5,140 ha (1.4%) (Chart 3.17b). Cereals and pulses were the dominant crops in both seasons and other crop types were of minor importance in comparison. There was little difference in the proportions of the different crop types grown between seasons and because the production in the dry season was very small compared to that of the wet season, it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). Chart 3.16 Planted Area (ha) for the Main Crops Ruvuma 0 50,000 100,000 150,000 Maize Cassava Paddy Beans Finger Millet Groundnuts Tobacco Sweet Potatoes Simsim Wheat Bambaranuts Cow Peas Sorghum Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - RUVUMA 0.00 0.20 0.40 0.60 0.80 Maize Soya Beans Cassava Carrot Tobacco Mung Beans Paddy Wheat Beans Pigeon Peas Finger Millet Simsim Sorghum Field Peas Groundnuts Sunflower Barley Crop Planted Area (ha) Chart 3.17b: Percentage Distribution of Area planted with Annual Crops by Crop Type Pulses 11.1% Cereal 54.2% Cash Crops 2.0% Oil seeds & Oil nuts 4.9% Fruits and Veg 1.4% Roots and Tubers 26.4% 66 94,522 0 39,697 0 17,435 29 7,169 0 5,125 15 0 50,000 100,000 150,000 200,000 A r e a ( h e c t a r e s) Cereal Roots and Tubers Pulses Oil seeds & Oil nuts Cash Crops Fruits and Veg Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Wet Season Dry Season Songea Urban Songea Rural Mbinga 0ha 110ha 0ha 0ha 0ha 0% 0% 0.2% 0% 0% Namtumbo Tunduru 88 to 110 66 to 88 44 to 66 22 to 44 0 to 22 Mbinga Namtumbo Songea Urban Songea Rural 48,989ha 61,595ha 40,018ha 37,655ha 5,953ha 57.9% 47.2% 56.9% 60.8% 54.5% Tunduru Area planted and Percentage During the Short Rainy Season by District MAP 3.09 RUVUMA Area Planted (ha) MAP 3.10 RUVUMA Area Planted With Cereals and Percent of Total Land Planted With Cereals by District 40,000 to 70,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Area planted (ha) Area Planted During the Short Rainy Season Percentage of Area Planted and During the Short Rainy Season Area Planted With Cereals Crops Percent of Total Land Planted With Cereals Crops Tanzania Agriculture Sample Census RESULTS 22 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.4 Cereal Crop Production The total production of cereals was 227,514 tonnes. Maize was the dominant cereal crop with 179,312 tonnes which was 79 percent of total cereal production, followed by paddy (17%), finger millet (2.66%), wheat (0.73%), sorghum (0.42%) and barley (0.01%). Mbinga district had the largest planted area of cereals in the region (61,595ha) followed by Tunduru (48,989ha), Namtumbo (40,018ha), Songea Rural (37,655) and Songea Urban 5,953) (Map 3.10). The total area planted with cereals during the dry and wet seasons was 194,211 ha out of which 66 ha (0.03%) were planted in the dry season and 194,145 ha (99.97%) were planted during the wet season. The wet season accounted for 99.98 percent of the total cereals produced in both seasons. The area planted with maize during the dry season was 56.1 percent of the total area planted with cereals in that season followed by Paddy (43.9%) (Table 3.2). The area planted with maize was dominant and it represented 71.9 percent of the total area planted with cereal crops, then followed by paddy (19.67%), finger millet (5.30%), wheat (2.08), Sorghum (1.07%), bulrush millet (0.02%) and barley (0.01%) . The yield of maize was 1,285 kg/ha, followed by paddy (1,034 kg/ha), barley (741 kg/ha), finger millet (588 kg/ha), sorghum (462 kg/ha), wheat (409 kg/ha) and bulrush (345 kg/ha). (Chart 3.19). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Ruvuma region during was 178,837 (94% of the total crop growing households in the region). The total production of maize was 179,283 tonnes from a planted area of 139,505 hectares resulting in a yield of 1.3 t/ha. Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 37 29 790 139,505 179,283 1,285 139,541 179,312 1,285 Paddy 29 4 124 38,178 39,510 1,035 38,207 39,514 1,034 Sorghum 0 0 0 2,079 961 462 2,079 961 462 Bulrush Millet 0 0 0 38 13 345 38 13 345 Finger Millet 0 0 0 10,287 6,046 588 10,287 6,046 588 Wheat 0 0 0 4,036 1,652 409 4,036 1,652 409 Barley 0 0 0 22 16 741 22 16 741 Total 66 33 194,145 227,482 194,211 227,514 Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 Maize Paddy Finger Millet Wheat Sorghum Bulrush Millet Barley Crop Area Planted (ha) 0.00 1.00 2.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.20: Time Series Data on Maize Production - RUVUMA 234 177 158 234 179 203 189 0 100 200 300 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Census/Survey year Production ('000') tonnes Tanzania Agriculture Sample Census Mbinga Namtumbo Songea Rural Songea Urban 0.6ha 0.7ha 1ha 0.9ha 0.7ha Tunduru Songea Urban Songea Rural Tunduru Namtumbo Mbinga 4,600ha 28,809ha 50,346ha 28,503ha 27,246ha 1.4t/ha 1.4t/ha 1.3t/ha 1.7t/ha 0.7t/ha Planted Area and Yield of Maize by District MAP 3.11 RUVUMA Planted Area Per Household MAP 3.12 RUVUMA Area Planted Per Maize Growing Household by District 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Planted Area Per Household RESULTS 24 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 25 Chart 3.20 indicates production trend (in thousand metric tonnes) for maize. There was a sharp increase in maize production (48%) in 1999 after which the production leveled in 2000 and then it declined during the year 2003. The average area planted with maize per household was 0.8 hectares, however it ranged from 0.6 hectares in Tunduru district to 1.0 hectares in Namtumbo district (Map 3.11). In the wet season, Mbinga district had the largest area of maize (50,346 ha) followed by Namtumbo (28,809 ha), Songera Rural (28,503 ha), Tunduru (27,246 ha), and Songea Urban (4,600 ha) (Chart 3.21 and Chart 3.22)(Map 3.12). Charts 3.20 and 3.22 shows that, with exception of the year 2003, there was a positive relationship between the quantity of maize produced and the yield. The area planted with maize remained constant over the two different period whereby the first period was from 1995 to 1997 the second one which was higher than the first one started from 1998 to 2000. Then the area under production dropped from the year 2000 to 2003. However, the yield of maize has shown a decline over the period 1996 to 2003 (from 1.9 t/ha in 1995 to 1.3 t/ha in 2003) (Chart 3.22). 3.3.4.2 Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Ruvuma region was 81,184. This represented 42 percent of the total crop growing households in Ruvuma region . The total production of paddy was 39,510 tonnes from a planted area of 38,178 hectares resulting in a yield of 1.03 t/ha. The district with the largest area planted with Paddy was Tunduru (19,750 ha) followed by Namtumbo (7,440 ha), Songea Rural(6,187 ha), Mbinga (3,721 ha), and Songea Urban (1,080 ha) (Map 3.15). There were small variations in the average area planted per crop growing household among the districts with the areas ranging from 0.36 ha in Songea Urban to 0.53 ha in Tunduru (Chart 3.23 and Map 3.16). Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 50,346 28,809 28,503 27,246 4,600 0 10,000 20,000 30,000 40,000 50,000 60,000 Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Area Planted per Household Area Planted (ha) Area Planted/hh Chart 3.22 Time Series of Maize Planted Area & Yield -RUVUMA 0 100,000 200,000 300,000 400,000 500,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 Yield (t/ha) Area Yield Chart 3.23 Total Planted Area and Area of Paddy per Household by District 1,080 3,721 6,187 7,440 19,750 0 5,000 10,000 15,000 20,000 25,000 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - RUVUMA 28 9 55 28 40 27 32 0 10 20 30 40 50 60 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Census/Survey year Production ('000') tons Namtumbo Songea Urban Songea Rural Mbinga 0.5ha 0.4ha 0.4ha 0.3ha 0.3ha Tunduru Songea Urban Namtumbo Songea Rural Mbinga 1,080ha 7,440ha 19,750ha 6,187ha 3,721ha 1t/ha 1.2t/ha 1.6t/ha 0.8t/ha 0.8t/ha Tunduru Planted Area and Yield of Paddy by District MAP 3.15 RUVUMA Area Planted Per Household MAP 3.16 RUVUMA Area Planted Per Paddy Growing Household by Distict Planted Area (ha) 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 26 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 There was a decline in the production of paddy from 1995/96 (32,000 tons) to 1996/97 (9,000 tons) there after a sharp rise in production from 1996/97 to 1997/98 (55,000 tons). Then a drop between 1997/98 and 1998/99 (28,000 tons) observed after that a constant production from 1998/99 to 1999/2000 (28,000 tons) followed by a rise to 2002/2003 (40,000 tons). Charts 3.24 and 3.25 show that, whilst the yield of paddy has dropped dramatically over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with paddy remained constant over the period from 1995 to 1997 after which the area under production expanded rapidly until 1999 after which it declined to 38,178 ha in 2003. Over the period 1995 to 1997 the yield of paddy fluctuated at around 2t/ha. However, there was a decline in yield over the period 1997 to 1999 (down to 0.5 t/ha) and it has then increased up to 1.0 t/ha in 2003 (Chart 3.25). 3.3.4.3 Other Cereals Other cereals were produced in small quantities. Sorghum was produced in Tunduru (1,845 ha), Namtumbo (180 ha), Mbinga (38 ha) and Songea Rural (15 ha). Fingermillet was produced in Mbinga (3,504 ha), Namtumbo (3,497 ha), Songea Rural (2,941 ha), Songea Urban (272 ha) and Tunduru (72 ha). Wheat was produced in Mbinga (3,986 ha), Tunduru (43 ha) and Songea Rural (8 ha). Bulrush millet was produced in Tunduru ( 13 ha ) and Namtumbo (25 ha) and barley was produced in Tunduru only (22 ha) (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 117,187 tonnes. Cassava production was higher than that of any other root and tuber crop in the region with a total production of 101,965 tonnes representing 87.0 percent of the total root and tuber crops production. This was followed by Sweet potatoes with 13,950 tonnes (11%), coco yam (876t, 0.8%), Chart 3.25 Time Series of Paddy Planted Area and Yield - RUVUMA 0 10,000 20,000 30,000 40,000 50,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.5 1.0 1.5 2.0 2.5 Yield (t/ha) Planted Area (ha) Yield (t/ha) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Area (Ha) Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.26 Area Planted with Sorghum, Bulrush Millet, Finger Millet, Wheat and Barley by District Sorghum Bulrush Millet Finger Millet Wheat Barley Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 30,000 60,000 90,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Mbinga Namtumbo Songea Urban Songea Rural 0.8ha 0.6ha 0.5ha 0.5ha 0.4ha Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Songea Urban Songea Rural Tunduru Mbinga Namtumbo 2,175ha 39,712ha 11,465ha 22,565ha 11,605ha 1.5t/ha 1.1t/ha 1.1 1.3t/ha 1.1t/ha 40,000 to 40,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Planted Area and Yield of Cassava by District MAP 3.13 RUVUMA MAP 3.14 RUVUMA Area Planted Per Cassava Growing Household by District Area Planted Per Household Planted Area (ha) Planted Area(ha) Yield(t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 28 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 29 Irish potatoes (223t, 0.2%) and yams (173t, 0.1%) (Table 3.3). For the area under roots and tubers, the area planted with cassava was the largest in the region. Its planted area accounted for 92.6 percent of the area planted with roots and tubers, followed by sweet potatoes (6.7%), coco yams (0.5%), Irish potatoes (0.2%), and yams (0.1%). It is difficult to determine the total planted area and production for the dry and wet seasons for roots and tubers as the total production of cassava has been reported under the wet season. However, there was no area planted with roots and tubers during the dry season hence no crop production. There was a significant increase in area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potato remained more or less constant while there was a decrease in the area of yams from 1998/99 to 2002/03. The total production of roots and tubers was estimated at 117,187 tonnes. Cassava with an estimate of 101,965 tonnes was the most important root and tuber crop. It accounted for 87.0 percent of the total roots and tubers production, followed by sweet potatoes with 13,950 tonnes (11.9%), coco yams with 876 tonnes (0.7%) Irish potatoes with 223 tonnes (0.2%) and yams with 173 tonnes (0.1%). estimated yield was high for sweet potatoes (2.2 and t/ha) coco yams (2.0 t/ha), followed by yams (1.8 t/ha, Irish potatoes (1.6 t/ha and cassava (1.2 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 137,409. This represents 72 percent of the total crop growing households in the region. The total production of cassava during the census year was 101,965 tonnes from a planted area of 87,522 hectares resulting in a yield of 1.2t/ha. Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 0 0 0 87,522 101,965 1,165 87,522 101,965 1,165 Sweet Potatoes 0 0 0 6,316 13,950 2,209 6,316 13,950 2,209 Irish Potatoes 0 0 0 143 223 1,559 143 223 1,559 Yams 0 0 0 96 173 1,802 96 173 1,802 Cocoyam 0 0 0 446 876 1,964 446 876 1,964 TOTAL 0 0 94,522 117,187 94,522 117,187 Note: Cassava is produced in both the wet and dry season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the wet season only. Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 20,000 40,000 60,000 80,000 100,000 1994/95 1995/96 1998/99 2002/03 Ye ar Cassava Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 45.4 25.8 13.3 13.1 2.5 0.0 20.0 40.0 60.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent of Total Area Planted 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.76 0.64 0.53 0.51 0.41 0.00 0.20 0.40 0.60 0.80 Area per Household Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 Previous censuses and surveys indicate that the area planted with cassava was increasing for the period 1995 to 1999. Since 1999 the area planted with cassava dropped from 96,039 ha in 1988 to 87,522 ha in 2003 (Chart 3.28). The area planted with cassava accounted for 24 percent of the total area planted with annual crops and vegetables in the census year. Mbinga district had the largest planted area of cassava (39,712 ha, 45.4% of the cassava planted area in the region), followed by Tunduru (22,565 ha, 25.8%), Namtumbo (11,605 ha, 13.3%), Songea Rural (11,465 ha, 13.1%) and Songea Urban (2,175 ha, 2.5%) (Map 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Mbinga district (30.5%). This was followed by Tunduru (26.7%), Songea Urban (19.9%), Songea Rural (18.5%) and Namtumbo (16.5%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.64 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Mbinga (0.76 ha). This was followed by Tunduru (0.64 ha), Namtumbo (0.53 ha), Songea Rural (0.51 ha) and Songea Urban (0.41 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Ruvuma region was 35,326. The total production of sweet potatoes during the census year was 13,950 tonnes from a planted area of 6,316 hectares resulting in a yield of 2.2t/ha. Mbinga District has the largest planted area for sweet potatoes (3,648 ha, 58%), followed by Songea Rural (817 ha, 13%), Tunduru (711, 11%), Songea Urban (639, 10%) and Namtumbo (501 ha, 8%) (Chart 3.31).Other root and tuber crops were of minor importance in terms of area planted compared to cassava and sweet potatoes. 3.3.6 Pulse Crops Production The total area planted with pulses was 39,697 hectares out of which 34,237 ha were planted with beans (86 percent of the total area planted with pulses), followed by bambaranuts ( 2,570 ha, 6.5%), cow peas (2,438 ha, 6.1%), field peas (189 ha, 0.5%), green gram (138 ha, 0.3%), mung beans (73 ha, 0.2%) and pigeon peas (51 ha, 0.1%). Chick peas were not cultivated in the region. Pulses were not grown during the dry season. The total production of pulses was 17,234 tonnes. Beans were the most cultivated crop producing 15,059 tonnes which accounted for 87 percent of the total pulse production. This was followed by bambaranuts (1,126t, 6.5%), cow peas (821t, 4.8%), field peas (154t, 0.9%), green gram and (each 37t, 0.2%), mung beans (34t, 0.1%) and pigeon peas (3t, 0.02%). Table 3.4: Area, Production and Yield of Pulses by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 73 34 466 73 34 466 Beans 0 0 0 34,237 15,059 440 34,237 15,059 440 Cowpeas 0 0 0 2,438 821 337 2,438 821 337 Green Gram 0 0 0 138 37 268 138 37 268 Pigeon Peas 0 0 0 51 3 59 51 3 59 Bambaranuts 0 0 0 2,570 1,126 438 2,570 1,126 438 Field Peas 0 0 0 189 154 815 189 154 815 TOTAL 0 0 39,697 17,234 39,697 17,234 Chart 3.31 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 501 639 3,648 817 711 0 1,000 2,000 3,000 4,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Area (Ha) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Area Planted per Household Planted Area (ha) Planted Area per hh Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 10,000 20,000 30,000 40,000 Beans Bambaranuts Cowpeas Field Peas Green Gram Mung Beans Pigeon Peas Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) Songea Urban Mbinga Songea Rural Namtumbo 0.2ha 0.4ha 0.4ha 0.3ha 0.5ha Tunduru Songea Urban Tunduru Namtumbo Songea Rural Mbinga 897ha 1,812ha 20,544ha 4,877ha 6,108ha 0.3t/ha 0.6t/ha 0.4t/ha 0.4t/ha 0.5t/ha 16,000 to 21,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area and Yield of Beans by District MAP 3.17 RUVUMA Area Planted Per Beans Growing Household MAP 3.18 RUVUMA Area Planted Per Beans Growing Household by District Planted Area and Yield of Beans Planted Area(ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Beans Growing Household Tanzania Agriculture Sample Census RESULTS 31 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 Chick peas were not grown in the region. Field peas had the highest yield of 815 kgs/ha. The yields of the rest of the pulses in kilograms per hectare were mung beans 466 kgs/ha, beans 440 kgs/ha, bambaranuts 438 kgs/ha, cowpeas 337 kgs/ha and green gram 268 kgs/ha. Pigeon peas had the lowest yield of 59 kgs/ha (Chart 3,32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Ruvuma region was 86,699. The total production of beans in the region was 15,059 tonnes from a planted area of 34,237 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Mbinga district (20,544 ha, 60%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per household was in Tunduru district (0.48 ha) (Chart 3.34). The average area planted per household in the region during the wet season was 0.39 ha. The variations in area planted with beans for the rest of the districts were small with the areas ranging from 0.21 ha in Songea Urban district to 0.48 ha in Tunduru district (Map 3.18). In Ruvuma region, bean production over the period 1995 to 2003 was normally about 10,000 tonnes except for the year 1998 where the production was highest at 62,267 tonnes (Chart 3.35). Charts 3.35 and 3.36 show that, the yield of beans remained fairly constant the previous 8 years and the quantity produced also remained generally constant. The area planted with beans has decreased over the period from 1986 to 2003. Over the period 1997 to 2003 the yield of beans remained constant at around 0.3 t/ha. (Chart 3.36). Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 80 Mbinga Songea Rural Namtumbo Tunduru Songea Urban District Percent of Land 0 10 20 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.48 0.44 0.36 0.33 0.21 0.00 0.15 0.30 0.45 0.60 Area per Household Tunduru Mbinga Songea Rural Namtumbo Songea Urban District Chart 3.34 Area Planted per Bean Growing Household by District (Wet Season Only) Chart 3.35: Time Series Data on Beans Production - RUVUMA 10 8 7 15 10 62 13 0 15 30 45 60 75 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Chart 3.36 Time Series of Beans Planted Area & Yield - RUVUMA 0 20,000 40,000 60,000 80,000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 0.8 Yield (t/ha) Area Yield Mbinga Namtumbo Songea Urban Songea Rural 0.2ha 0.3ha 0.2ha 0.3ha 0.2ha Tunduru 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0 to 0.2 Songea Urban Songea Rural Tunduru Namtumbo Mbinga 225ha 1,980ha 4,088ha 2,046ha 1,193ha 1t/ha 0.5 0.5t/ha 0.5t/ha 0.4t/ha Planted Area and Yield of Groundnuts by District MAP 3.21 RUVUMA Area Planted Per Household MAP 3.22 RUVUMA Area Planted Per Groundnuts Growing Household by District 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 33 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.7 Oil Seed Production The total production of oilseed crops was 7,752 tonnes planted on an area of 17,464 hectares. The total planted area of oilseeds in the wet season was 17,435 ha representing 99.8 percent of the total area planted with oil seeds. Groundnuts were the most important oilseed crop with 9,561 ha (55% of the total area planted with oil seeds), followed by simsim (36%), soya beans (5%) and sunflower (5%) (Chart 3.37). The yield of sunflower was moderate (501 kg/ha). Groundnuts had a yield of 496 kg/ha, simsim of 378 kg /ha and soya beans 297 kg/ha. In terms of production, groundnuts was 4,732 tonnes and accounted for 61 percent of the total production of oil seeds, followed by simsim (31%), sunflower (5%) and soya beans (3%). 3.3.7.1 Groundnuts The number of households growing groundnuts in Ruvuma region was only 39,911. The total production of groundnuts in the region was 4,732 tonnes from a planted area of 9,561 hectares resulting in a yield of 0.5 t/ha. There was a sharp increase in production of groundnuts over the period 1995 to 1996, from 78 tonnes in 1994/95 to 100,417 tonnes in 1995/96, and then a sharp decrease to 4732 tonnes in 2002/03. The area planted dropped from 5,129.27 hectares in 1994/95 to 3,359.82 hectares in 1995/96 after which it increased to 9,561 hectares in 2002/03 (Chart 3.38). With 4,117 ha of groundnuts, 43.1% of the total area planted with groundnuts in the region, Tunduru had the largest planted area followed by Namtumbo (2,046 ha, 21.2%), Songea Rural (1,980 ha, 20.8%), Mbinga (1,193 ha, 12.5%) and Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 796 399 501 796 399 501 Simsim 0 0 0 6,279 2,376 378 6,279 2,376 378 Groundnuts 29 1 49 9,532 4,731 496 9,561 4,732 495 Soya Beans 0 0 0 828 246 297 828 246 297 Total 29 1 17,435 7,751 17,464 7,752 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 2,500 5,000 7,500 10,000 Groundnuts Simsim Sunflower Soya Beans Crop Area Planted (ha) 0 200 400 600 800 1000 Yield (kg/ha) Yield (kg/ha) Chart 3.38 Time Series Data on Groundnut Production - RUVUMA 4,731 78 100,417 0 20,000 40,000 60,000 80,000 100,000 1994/95 1995/96 2002/03 Year Production ( tonnes) 0 0.1 0.2 0.3 Area per Household (ha) Tunduru Songea Urban Songea Rural Namtumbo Mbinga District Chart 3.40 Area Planted per Groundnut Growing Households by District (Wet Season Only) Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 10.0 20.0 30.0 40.0 50.0 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District Percent of Land 0.0 1.0 2.0 3.0 4.0 5.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 Songea Urban (225 ha, 2.4%) (Map 3.19). The highest proportion of land with groundnuts was found in Tunduru (4.8%) followed by Songea Rural (3.2%), Namtumbo (2.9%), Songea Urban (2.1%) and Mbinga (0.9%) (Chart 3.39). The largest area planted per groundnut growing household was found in Tunduru District (0.27 ha) and the smallest was in Mbinga (0.18). The range between the district with the highest and the lowest area planted per household indicates small variations in area planted among the districts (Chart 3.40 and Map 3.20). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The dry season is relatively not important for fruit and vegetables production since 0.3 percent of the total area planted with fruit and vegetables was during the dry season. For cabbage and amaranths below 3 percent of the planted area of each crop was during the dry season. Excluding cabbage and amaranths, the planted area for each crop in the wet season was abnormally large (100% of the total planted area was in the wet season). Reliable historical data for the time series analysis of fruit and vegetables were not available. The total production of fruits and vegetables was 16,087 tonnes. The most cultivated fruit and vegetable crop was the tomato crop with a production of 7,328 tonnes (46% of the total fruit and vegetables produced) followed by cabbage (4,119t, 26%) and onions (1,704t, 11%). The production of other fruit and vegetable crops were relatively small (Table 3.6). The yield of okra was 16,134 kg/ha, tomatoes (3,804 kg/ha), cabbage (3,386 kg/ha), and onion (2,915 kg/ha). Radish and carrot had yields of 267 and 294 kg/ha respectively (Chart 3.41). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during wet was 13,606 and no household grew tomatoes during dry season. This represented 7.1 percent of the total crop growing households during wet season. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Dry season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Okra 0 0 0 3 45 16,134 3 45 16,134 Radish 0 0 0 7 2 267 7 2 267 Onions 0 0 0 585 1,704 2,915 585 1,704 2,915 Cabbage 7 11 1,482 1,209 4,109 3,397 1,217 4,119 3,386 Tomatoes 0 0 0 1,927 7,328 3,804 1,927 7,328 3,804 Spinnach 0 0 0 465 854 1,837 465 854 1,837 Carrot 0 0 0 72 21 294 72 21 294 Chillies 0 0 0 27 28 1,007 27 28 1,007 Amaranths 7 8 1,087 349 854 2,449 356 862 2,421 Pumpkins 0 0 0 448 1,048 2,342 448 1,048 2,342 Cucumber 0 0 0 22 27 1,219 22 27 1,219 Egg Plant 0 0 0 12 48 3,987 12 48 3,987 Total 15 19 5,125 16,068 5,139 16,087 Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 500 1,000 1,500 2,000 Tomatoes Cabbage Onions Spinnach Pumpkins Amaranths Others Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 36 Mbinga district had the largest planted area of tomatoes (33% of the total area planted with tomatoes in the region), followed by Tunduru (29%), Songea Urban (15%), Namtumbo (14%) and Songea Rural (10%) (Chart 3.42 and Map 21). The highest proportion of land with tomatoes was found in Songea Urban, followed by Tunduru district. The rest of the districts had low proportions of land used for tomato production (Chart 3.42). The largest area planted per tomato growing household was found in Tunduru district (0.20 ha) followed by Songea Urban (0.15 ha), Mbinga (0.13 ha), Namtumbo (0.12 ha) and Songea Rural (0.08 ha) (Chart 3.43 and Map 3.22). The total area planted with tomatoes accounted for 0.5 percent of the total area planted with annual crops and vegetables during the dry and wet seasons . 3.3.8.2 Cabbage The number of households growing cabbages in the region during wet season was 10,900 and 72 in the dry season. This represented 5.7 percent of the total crop growing households in the region in the wet season and 0.04 percent in the dry season. Mbinga district had the largest planted area of cabbage (432 ha, 35.5% of the total area planted with cabbage in the region), followed by Namtumbo (260 ha, 21.4%), Songea Rural (248 ha, 20.4%), Songea Urban (201 ha, 16.5%) and Tunduru (75 ha, 6.2%) (Chart 3.44 and Map 3.23). The total area planted with cabbages accounted for 0.3 percent of the total area planted with annual crops and vegetables during the dry and wet season. 3.3.8.3 Onions The number of households growing onions in the region during the wet season was 4,075 households and there were no households growing onions in the dry season. This represents 2.1 percent of the total crop growing households in the region in the wet season and zero percent in the dry season. Namtumbo district had the largest planted area of onions (186 ha, 31.9% of the total area planted with onions in the region), followed by Mbinga (158 ha, 27.0%), Tunduru (135 ha, 23.1%), Songea Urban (54ha, 9.2%) and Songea Rural (51 ha, 8.8%) districts (Map 3.24). Chart 3.42 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0 10 20 30 40 Mbinga Tunduru Songea Urban Namtumbo Songea Rural District Percent of Land 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 Area per Household (ha) Tunduru Songea Urban Mbinga Namtumbo Songea Rural District Chart 3.43 Area Planted per Tomato Growing Household by District (Wet Season) Chart 3.44 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 10.0 20.0 30.0 40.0 Mbinga Namtumbo Songea Rural Songea Urban Tunduru District Percent of Land 0.00 0.50 1.00 1.50 2.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Namtumbo Songea Urban Songea Rural Mbinga 72ha 3,497ha 3,504ha 272ha 2,941ha 0.2t/ha 0.5t/ha 0.7t/ha 0.8t/ha 0.6t/ha Tunduru Mbinga Songea Rural Songea Urban Namtumbo 0.4ha 0.3ha 0.3ha 0.2ha 0.3ha Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 2,800 to 3,600 2,100 to 2,800 1,400 to 2,100 700 to 1,400 0 to 700 Planted Area and Yield of Finger Millet by District MAP 3.19 RUVUMA Area Planted Per Household MAP 3.20 RUVUMA Area Planted Per Finger Millet Growing Household by District Planted Area (ha) Planted Area (ha) Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 37 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 38 The largest proportion of the area planted with onions was found in Songea Urban district (0.49%), followed by Namtumbo (0.26%), Tunduru (0.16%), Mbinga (0.12%) and Songea Rural (0.08) (Chart 3.45). The total area planted with onions accounted for 0.16 percent of the total area planted with annual crops and vegetables during the dry and wet seasons. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 7,169 ha was planted with other annual crops and tobacco was the only annual cash crop grown in the region. No area was planted with tobacco during the dry season. 3.3.9.1 Tobacco The quantity of tobacco produced was 4,371 tonnes. Tobacco had a planted area of 7,169 ha, all of which was planted in the wet season. Namtumbo had the largest planted area (78.1% of total area planted with tobacco in the region), followed by Tunduru (9.2%), Songea Rural (8.7%), Mbinga (2.4%) and Songea Urban (1.5%) (Chart 3.46) (Map 3.25 and 3.26). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 124,910 hectares (35% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops should be higher than indicated in Chart 3.47. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Tobacco 0 0 0 7,169 4,371 610 7,169 4,371 610 TOTAL 0 0 7,169 4,371 7,169 4,371 Chart 3.45 Percent of Onions Planted Area and Percent of Total Land with Onions by District 0.0 10.0 20.0 30.0 40.0 Namtumbo Mbinga Tunduru Songea Urban Songea Rural District Percent of Land 0.00 0.15 0.30 0.45 0.60 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 30.0 60.0 90.0 Namtumbo Tunduru Songea Rural Mbinga Songea Urban District Percent of Land 0.00 3.00 6.00 9.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.47 Area Planted for Annual and Permanent Crops Annual Crops, 358,203, 74% Permanent Crops, 124,910, 26% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 The most important permanent crop in Ruvuma region is cashewnut which had a planted area of 74,124 ha, (61% of the planted area of all permanent crops) followed by coffee (29,961 ha, 24%), and banana (7,751 ha, 6%). The remaining permanent crops accounted for 10 percent of the total area planted with permanent crops (Chart 3.48). Tunduru district had the largest area under smallholder permanent crops (79,226 ha, 63.4%). This was followed by Mbinga (33,195 ha, 26.6%), Songea Rural (5,655 ha, 4.5%), Namtumbo (5,233 ha, 4.2%) and Songea Urban (1,603 ha, 1.3%). However, Tunduru had the largest area per permanent crop growing household (1.58 ha) followed by Mbinga (0.58 ha), Songea Urban (0.46 ha), Songea Rural (0.42 ha) and Namtumbo (0.39) (Chart 3.49). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Tuduru had the highest (48%) followed by Songea Urban (20%), Songea Rural (13%), Mbinga (8%), and Namtumbo (7%). 3.4.1 Cashewnut The total production of cashewnut by smallholders was 9,278 tonnes. In terms of area planted, cashewnut was the most important permanent crop grown by smallholders in the region. They were grown by 39,985 households (20.9% of the total crop growing households). The average area planted with cashewnut per household per cashew nut growing household was 1.85 ha and the average yield obtained by smallholders was 176 kg/ha from a harvest area of 52,08 hectares. Tunduru had the largest area of cashewnut in the region (71,527 ha, 96.5%) followed by Namtumbo (1.228 ha, 1.7%), Mbinga (917 ha, 1.2%), Songea Rural (451 ha, 0.6%) and Songea Urban (1 ha, 0.0%) (Map 3.27). However, the average area planted with cashewnut per cashewnut growing household was highest in Tunduru (1.99 ha) followed by Songea Rural (0.86 ha), Namtumbo (0.83 ha), Mbinga (0.45 ha) and Songea Urban (0.04 ha) (Chart 3.50 and Map 3.28). Chart 3.49 Percent of Area Planted and Average Planted Area with Permanent Crops by District 26.6 1.3 4.5 4.2 63.4 0.0 30.0 60.0 Tunduru Mbinga Songea Urban Songea Rural Namtumbo District % of Total Area Planted 0.00 0.30 0.60 0.90 1.20 1.50 1.80 Average Planted Area per Household % of Area Area per Hh Chart 3.48 Area Planted with the Main Perennial Crops Sugarcane, 1,482, 1% Mango, 1,359, 1% Cashewnut, 74,124, 61% Coffee, 29,961, 24% Banana, 7,751, 6% Pigeon Pea, 5,159, 4% Orange, 2,827, 2% Coconut, 989, 1% Avocado, 249, 0% Sour Soup, 252, 0% Chart 3.50 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 96.5 1.2 0.6 1.7 0.0 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Tunduru Songea Rural Namtumbo Mbinga Songea Urban District % of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Songea Urban Songea Rural 0.4ha 0.6ha 0.4ha 0.5ha 0.4ha Mbinga Namtumbo Tunduru Namtumbo Songea Urban Songea Rural 0.6t/ha 0.5t/ha 0.5t/ha 0.8t/ha 0.4t/ha 5,602ha 110ha 623ha 174ha 660ha Mbinga Tunduru Planted Area and Yield of Tobacco by District MAP 3.23 RUVUMA Area Planted Per Household MAP 3.24 RUVUMA Area Planted Per Tobacco Growing Household by District Planted Area (ha) 6,000 to 7,500 4,500 to 6,000 3,000 to 4,500 1,500 to 3,000 0 to 1,500 Planted Area (ha) Yield (t/ha) 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 40 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 3.4.2 Coffee The total production of coffee by smallholders was 12,388 tonnes. In terms of area planted, coffee was the second most important permanent crop grown by smallholders in the region. It was grown by 41,347 households (21.6% of the total crop growing households). The average area planted with coffee per household was relatively small at around 0.73 ha per coffee growing household and the average yield obtained by smallholders was 475 kg/ha from a harvest area of 26,030 hectares. Mbinga had the largest area of coffee in the region (29,312 ha, 97.8%) followed by Songea Rural (582 ha, 1.9%), Songea Urban (42 ha, 0.1%) and Tunduru (25 ha, 0.08%). Coffee was not grown in Namtumbo district (Map 3.29). However, the average area planted with coffee per coffee planting household was highest in Mbinga (0.7 ha) followed by Songea Rural (0.5 ha), Songea Urban (0.4 ha) and Tunduru (0.2 ha) (Chart 3.51 and Map 3.30). 3.4.3 Banana The total production of banana by smallholders was 37,890 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 24,420 households (12.8% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.32 ha per banana growing household and the average yield obtained by smallholders was 4,888 kg/ha from a harvested area of 7,751 hectares. Namtumbo had the largest planted area of bananas in the region (2,704 ha, 35%) followed by Songea Rural (1,622 ha, 21%), Songea Urban (1,307 ha, 17%), Mbinga (1,096 ha, 14%) and Tunduru (1,022 ha, 13%) (Map 3.31). However, the area planted with banana per banana growing household was highest in Songea Urban (0.68 ha), followed by Tunduru (0.51 ha), Namtumbo (0.40 ha), Songea Rural (0.23 ha) and Mbinga (0.17 (Chart 3.52 and Map 3.32). 3.4.4 Pigeon Peas The total production of pigeon peas by smallholders was 515 tonnes. In terms of area planted, pigeon peas was the fourth most important permanent crop grown by smallholders in the region. It was grown by 9,069 households (4.7% of the total crop growing households). The average area planted with pigeon peas per household was relatively small at around 0.57 ha per pigeon peas growing household and the average yield obtained by smallholders was 100 kg /ha from a harvest area of 5,159hectares. Chart 3.51 Percent of Area Planted with Coffee and Average Planted Area per Household by District 0.14 0.00 97.83 0.08 1.94 0.00 20.00 40.00 60.00 80.00 100.00 Mbinga Songea Rural Songea Urban Tunduru Namtumbo District % of Total Area Planted 0.0 0.3 0.5 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Banana and Average Planted Area per Household by District 21 14 35 13 17 0 10 20 30 40 Namtumbo Songea Rural Songea Urban Mbinga Tunduru District % of Total Area Planted 0.00 0.20 0.40 0.60 0.80 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.53 Percent of Area Planted with Pegeon peas and Average Planted Area per Household by District 7.52 0.00 92.19 0.00 0.29 0.00 20.00 40.00 60.00 80.00 100.00 Tunduru Namtumbo Songea Rural Mbinga Songea Urban District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Songea Urban Namtumbo Songea Rural 0.4ha 0.2ha 0ha 0.5ha 0.7ha Mbinga Tunduru 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Songea Rural Songea Urban Namtumbo 0.5 0.2t/ha 0.4t/ha 0t/ha 0.1t/ha 582ha 42ha 29,312ha 0ha 25ha Mbinga Tunduru Planted Area and Yield of Coffee by District MAP 3.31 RUVUMA Area Planted Per Household MAP 3.32 RUVUMA Area Planted Per Coffee Growing Household by District Planted Area (ha) Planted Area (ha) Yield (t/ha) 20,000 to 50,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 42 Songea Urban Namtumbo Songea Rural Mbinga 0.7ha 0.5ha 0.4ha 0.2ha 0.2ha Tunduru Namtumbo Songea Urban Songea Rural 2,704ha 1,022ha 1,307ha 1,622ha 1,096ha 2.2t/ha 1.6t/ha 1.7t/ha 3.2t/ha 20.7t/ha Mbinga Tunduru Planted Area and Yield of Banana by District MAP 3.33 RUVUMA Area Planted Per Household MAP 3.34 RUVUMA Area Planted Per Banana Growing Household by District Planted Area and (ha) Planted Area (ha) Yield (t/ha) 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 43 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 44 Tunduru had the largest area of pigeon peas in the region (4,758 ha, 92.19%) followed by Namtumbo (388 ha, 7.52%) and Songea Rural (15 ha, 0.29%). Pigeon peas was not grown in Mbinga and Songea Urban (Map 3.33). However, the average area planted per pigeon peas growing household was highest in Tunduru (0.62 ha), followed by Namtumbo (0.28 ha) and Songea Rural (Chart 53 and Map 3.34). 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region during the wet season was 196,846 ha which represented 72.8 percent of the total area cleared. Bush clearance, burning and tractor slashing are less important methods for land clearing and they accounted 16.8, 9.3 and 1.1 percent of the area cleared respectively (Chart 3.54 and Table 3.8). 3.5.2 Methods of Soil Preparation Hand cultivation is the most used method for soil preparation and was used in an area of 255,944 ha which represented 94 percent of the total planted area, followed by ox-ploughing (10,809 ha, 4%) and tractor ploughing (4,525 ha, 2%) (Chart 3.55). Table 3.8: Land Clearing Methods Wet Season Dry Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 136,593 196,846 72.8 145 15 13.6 136,738 196,86 1 72.8 Mostly Bush Clearance 31,923 45,315 16.8 217 95 86.4 32,140 45,410 16.8 Mostly Burning 15,927 25,069 9.3 0 0 0.0 15,927 25,069 9.3 No Land Clearing 2,084 2,875 1.1 0 0 0.0 2,084 2,875 1.1 Mostly Tractor Slashing 181 245 0.1 0 0 0.0 181 245 0.1 Other 0 0 0.0 0.0 0 0 0.0 Total 186,708 270,350 100.0 362 110 100.0 187,070 270,460 100.0 Chart 3.54 Number of Households by Method of Land Clearing during the Wet Season 136,593 31,923 15,927 2,084 181 0 0 100,000 200,000 Mostly Hand Slashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.57 Planted Area of Improved Seeds - RUVUMA Without Improved Seeds, 236,071, 87% With Improved Seeds, 35,208, 13% Chart 3.55 Area Cultivated by Cultivation Method Mostly Hand Cultivation, 255,944, 94% Mostly Oxen Ploughing, 10,809, 4% Mostlly Tractor Ploughing, 4,525, 2% 0 20,000 40,000 60,000 80,000 100,000 Area Cultivated (ha) Tunduru Songea Urban Songea Rural Namtumbo Mbinga District Chart 3.56 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostlly Tractor Ploughing Songea Urban Tunduru Namtumbo Songea Rural Mbinga 0ha 4,756ha 388ha 15ha 0ha 0t/ha 0.2t/ha 0.1t/ha 0.2t/ha 0t/ha 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Songea Urban Songea Rural 0ha 0ha 0.2ha 0.3ha 0.6ha Mbinga Namtumbo Tunduru Planted Area and Yield of Pigeon Peas by District MAP 3.35 RUVUMA Area Planted Per Household MAP 3.36 RUVUMA Area Planted Per Pigeon Peas Growing Household by District Planted Area and Yield of Pigeon Peas Planted Area of Pigeon Peas Yield of Pigeon Peas 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 45 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 46 While all land preparation was done by hand during the dry season, the area so was 72% of the total planted area during the wet season. All preparation by oxen and tractor was done during the wet season. In Ruvuma region, Tunduru district had the largest planted area cultivated with oxen (4,907 hectares, 45.4%) followed by Songea Urban (2,268 ha, 21.0%), Songea Rural (2,095 ha, 19.4%), Namtumbo (1,405 ha, 13.0%) and Mbinga (134 ha, 1.2%). During the wet season, 76.6 percent of the total area cultivated by using oxen was planted with cereals followed by pulses (11.5%), oil seeds (6.2%), fruits and vegetables (2.4%), cash crops (1.9%) and roots and tubers (1.4%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 35,208 ha which represents 8 percent of the total area planted with the annual crops and vegetables. The percentage use of improved seed in the dry season was 13.6 percent, slightly higher than the corresponding percentage use in the wet season (9.8%). Cereals had the largest planted area with improved seeds (21,034 ha, 60% of the planted area with improved seeds) followed by roots and tubers (6,755 ha, 19%), fruit and vegetables (2,975 ha, 8%) , cash crops (2,665 ha, 8%), pulses (1,206 ha, 3%) and Oil seed (593 ha, 2%) (Chart 3.58). However, the use of improved seed in roots and tubers and fruits and vegetables is much greater than in other crop types (89% and 59% respectively), only 3 percent of the planted area for oil seed crops used improved seed (Chart 3.59). 3.5.4 Fertilizer Use The use of fertilisers on annual crops was small with its application on a planted area of only 76,463 ha (21.3% of the total planted area in the region). The planted area without fertiliser for annual crops was 281,740 hectares representing 78.7 percent of the total planted area with annual crops. Of the planted area with fertiliser application, inorganic fertilizers were applied to 43,402 ha which represents 12.1 percent of the total planted area (56.8% of the area planted with fertiliser application in the region). This was followed by farm yard manure (29,470 ha, 38.5%). Compost fertilizers were used on a very small area which represented only 47 percent of the area planted with fertilizers. Table3.9 Planted Area by Type of Fertilizer Use and District – Wet and Dry Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total applied No Fertilizer Applied Tunduru 1,163 649 5,457 7,269 77,275 Songea Rural 5,952 829 9,312 16,094 45,875 Mbinga 17,981 1,561 12,325 31,867 98,519 Songea Urban 2,098 159 3,857 6,114 4,806 Namtumbo 2,277 394 12,449 15,120 55,265 Total 29,470 3,591 43,402 76,463 281,740 Table 3.10: Number of Crop Growing Households and Planted Area By Type of Fertilizer Use and District – Wet Season Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 Namtumbo 1,150 2,277 143 394 5,540 12,340 22,282 55,265 29,115 70,275 Total 13,938 29,470 1,671 3,591 23,638 43,292 151,614 281,740 190,861 358,093 Chart 3.58 Planted Area with Improved Seed by Crop Type Roots & Tubers, 6,755, 19% Oilseeds , 593, 2% Cereals, 21,034, 60% Pulses, 1,206, 3% Cash Crops, 2,663, 8% Fruits & Vegetables, 2,975, 8% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Fruits & Vegetables Cash Crops Pulses Oilseeds Crop Type Chart 3.59 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 47 The highest percentage of the area planted with fertilizers (all types) was in Mbinga district (41.7%) followed by Songea Rural (21%), Namtumbo (20%), Tunduru (10%) and Songea Urban (8%) (Table 3.9 and Charts 3.60 and 3.61). Most annual crop growing households do not use any fertiliser (approximately 39,247 households, 20.6%) (Map 3.35). The percentage of the planted area with applied fertilizer was highest for cereals (75.1% of the area planted with these creals during the wet season had an application of fertilizers). This was followed by pulses (6.7%), roots and tubers (6.6%), cash crops (5.7%), fruits and vegetables (3.7%) and oil seeds (2.1%) (Table 3.10). 3.5.4.1 Farm Yard Manure Use The planted area applied with farm yard manure in Ruvuma region during wet season was 29,470 ha representing 8.2% of the total planted area during that season. The number of households that applied farm yard manure in their annual crops during wet season was 13,938. (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (65%), followed by fruit and vegetables (14%), roots and tubers (11%), pulses (9%), oil seeds (1%) and cash crops (0.3%). Fruit and vegetables had the highest percent of the planted area with farm yard manure (84.5% of the total area planted with fruit and vegetables in Ruvuma). This was followed by roots and tubers (53%), pulses (46%), cereals (35%), oil seeds (21%) and cash crops (1%) (Charts 3.62 and 3.63a). Farm yard manure is mostly used in Songea Urban (19.2% of the total planted area in the district), followed by Mbinga (13.8%), Songea Rural (9.6%), Namtumbo (3.2%) and Tunduru (1.4%) (Chart 3.63b). Chart 3.60 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 281,740, 79% Mostly Compost, 3,591, 1% Mostly Inorganic Fertilizer, 43,402, 12% Mostly Farm Yard Manure, 29,470, 8% Chart 3.63b Proportion of Planted Area Applied with Farm Yard Manure by District - RUVUMA 0.0 5.0 10.0 15.0 20.0 Songea Urban Mbinga Songea Rural Namtumbo Tunduru District Percent Chart 3.62 Planted Area with Farm Yard Manure by Crop Type - RUVUMA Fruits & Vegetables, 4,055, 14% Cash Crop, 95, 0% Oilseeds, 288, 1% Pulses, 2,602, 9% Roots & Tubers, 3,269, 11% Cereals, 19,162, 65% 0 25 50 75 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.63a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals 0 50,000 100,000 150,000 Area (ha) Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Chart 3.61 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Mbinga Tunduru Namtumbo Songea Urban Songea Rural 10,036 2,164 4,963 2,625 6,857 13% 4.6% 17% 37.8% 22.3% Namtumbo Songea Urban Songea Rural 15,958 2,805 7,223 27,165 14,048 54.8% 23.5% 40.4% 35.1% 30% Mbinga Tunduru Number of Households and Percent of Total Households Receiving Crop Extension Services by District MAP 3.41 RUVUMA Number of Crop Growing Households Using Improved Seed MAP 3.42 RUVUMA Number and Percent of Crop Growing Households Using Improved Seed by District Number of Households Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services Percent of Crop Growing Households Using Improved Seed 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Number of Households Crop Growing Using Improved Seed Tanzania Agriculture Sample Census RESULTS 48 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Songea Urban Songea Rural 8,774ha 44,231ha 73,755ha 49,669ha 60,879ha 80% 71% 57% 71% 72% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 4,806ha 45,875ha 98,519ha 55,265ha 77,275ha 44% 74% 76% 79% 91% Mbinga Namtumbo Tunduru Planted Area and Percent of Planted Area With No Application of Fertilizer by District MAP 3.37 RUVUMA Area Planted With Irrigation Application MAP 3.38 RUVUMA Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area With no Fertilizer Applied Planted Area With no Fertilizer Applied Percent of Planted Area With no Fertilizer Applied 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Area Planted With Irrigation Application Percent of Area Planted With Irrigation Application Tanzania Agriculture Sample Census RESULTS 49 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 For permanent crops, most farm yard manure is used for the production of coffee (89.5%), followed by banana (6.6%) and cashewnut (1.0%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Ruvuma region during wet season was 43,292 ha which represented 12.1 percent of the total planted area with annuals in the region and 56.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 23,638 and it was applied to 43,292 ha representing 12.1 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (79% of the total area applied with inorganic fertilizers), followed by cash crop (7%), pulses (5%), roots and tubers (5%), oil seeds (2%) and fruit and vegetables (2%) and (Chart 3.64). However, the proportion of cash crop with inorganic fertilizers was higher than other crop types (96%), followed by oil crops (75%), cereals (62%), Pulses (40%), roots and tubers (33%) and fruits and vegetables (15%) (Chart 3.65a). Inorganic fertiliser is mostly used in Songea Urban (35.3% of the total planted area in the district), followed by Namtumbo (17.7%), Songea Rural (15.0%), Mbinga (9.5%) and Tunduru (6.5%) Chart 3.65b). In permanent crops inorganic fertiliser were mostly used on passion fruits (90.6%), followed by pineapple (18.0%), coffee (17.8%), sugarcane (10.5%), mangoes (9.6%), coconut (3.0%), cashew (1.8%), pigeon peas (1.6%) and banana (1.4%). 3.5.4.3 Compost Use he total planted area applied with compost was 3,591 ha which represents only 1.0 percent of the total planted area with annual crops in the region and 5 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the wet season was 1,671 and it was applied to 3,591 ha representing 1.4 percent of the total area planted (Table 3.10 and Chart 3.66a). The proportion of area applied with compost was very low for each type of crop (0 to 14%); however the distribution of the total area using compost manure shows that 52.9 percent of this area was cultivated with cereals, followed Chart 3.65b Proportion of Planted Area Applied with Inorganic Fertiliser by District - RUVUMA 0.0 10.0 20.0 30.0 40.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent Chart 3.64 Planted Area with Inorganic Fertilizer by Crop Type - RUVUMA Pulses, 2,295, 5% Oilseeds, 1,041, 2% Fruits & Vegetables, 722, 2% Cash Crop, 3,126, 7% Roots & Tubers, 2,034, 5% Cereals, 34,074, 79% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.65a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - RUVUMA Chart 3.66a Planted Area with Compost by Crop Type - RUVUMA Cash Crop, 19, 1% Oilseeds, 62, 2% Fruits & Vegetables, 20, 1% Pulses, 774, 22% Roots & Tubers, 816, 22% Cereals, 1,900, 52% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 by roots & tubers (22.7%), pulses (21.5%), oil seed (1.7%), fruit and vegetables (0.6%) and cash crop (0.5%) (Chart 3.66b). Compost is mostly used in Songea Urban (1.5% of the total planted area in the district), and this is closely followed by Songea Rural (1.3%), Mbinga (1.2%), Tunduru (0.8%) and Namtumbo (0.6%) (Chart 3.66b). In permanent crops, compost was mostly used to banana (6.8%) followed by sugarcane (2.1%), coffee (1.2%), mango (0.6%) and cashewnut (0.1%). 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 102,510 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (77% of the total area applied with pesticides). This was followed by fungicides (17%) and herbicides (6%) (Chart 3.67). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 78,958 ha which represented 22.0 percent of the total planted area for annual crops and vegetables. 0 5 10 15 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.66b Percentage of Planted Area with Compost by Crop Type - RUVUMA Chart 3.66c Proportion of Planted Area Applied with Compost by District - RUVUMA 0.0 0.5 1.0 1.5 2.0 Songea Urban Songea Rural Mbinga Tunduru Namtumbo District Percent Chart 3.67 Planted Area (ha) by Pesticide Use Insecticide, 78,958, 77% Herbicide, 6,121, 6% Fungicide, 17,431, 17% Chart 3.68 Planted Area Applied with Insecticides by Crop Type Roots & Tubers, 3,844, 5% Cash crops, 2,451, 3% Oil seeds & Oil nuts, 1,168, 1% Pulses, 3,374, 4% Fruits & Vegetables, 4,665, 6% Cereals, 63,465, 81% 0.0 20.0 40.0 60.0 80.0 100.0 Percent of Planted Area Fruits & Vegetables Cereals Pulses Oil seeds & Oil nuts Cash crops Roots & Tubers Crop Type Chart 3.69 Percentage of Crop Type Planted Area Applied with Insecticides Songea Urban Songea Rural 159ha 829ha 1,561ha 394ha 649ha 1.5% 1.3% 1.2% 0.6% 0.8% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 2,098ha 5,952ha 17,981ha 2,277ha 1,163ha 19.2% 9.6% 13.8% 3.2% 1.4% Mbinga Namtumbo Tunduru 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Planted Area and Percent of Planted Manure Applied by District MAP 3.57 RUVUMA Planted Area (ha) MAP 3.58 RUVUMA Planted Area and Percent of Planted Area with Compost Application by District Planted Area (ha) Planted Area with Farm Yard Manure Applied Percent of Planted Area with Farm Yard Manure Applied 1,200 to 1,600 900 to 1,200 600 to 900 300 to 600 0 to 300 Tanzania Agriculture Sample Census Area Planted with Farm Yard Planted Area with Compost Manure Applied Percent of Planted Area with Compost Yard Manure Applied RESULTS 52 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 Cereals had the largest planted area applied with insecticides (63,465 ha, 81% of the total planted area with insecticides) followed by fruit and vegetables (4,665 ha, 6%), roots and tubers (3,844 ha, 5%), pulses (3,374 ha, 4%), cash crops (2,451 ha, 3%) and oil crops (1,168 ha, 1%)(Chart 3.68). However, the percent of insecticides used in fruits and vegetables is much greater than in other crop types (90.8%), while only 4.1 percent of roots and tubers crops were applied with insecticides (Chart 3.69). Annual Crops with more than 50 percent insecticide use were spinach (60.3%) and egg plant (55.0%). Songea Urban had the highest percent of planted area with insecticides (47.9% of the total planted area with annual crops in the district). This was followed Mbinga (33.3%) then Songea Rural (17.3%) and Namtumbo (15.8%). The smallest percentage use was recorded in Tunduru district (9.9%) (Chart 3.70). 5. 5.2 Herbicide Use The planted area applied with herbicides was 6,121 ha which represented 1.7 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (3,334 ha, 55%) followed by roots and tuber (1,336 ha, 22%), pulses (907 ha, 15%), oil crops (316 ha, 5%), fruits and vegetables (143 ha, 2%) and cash crops (84 ha, 1%) (Chart 3.71). However, the percent of herbicide use on fruit and vegetables and pulses was much greater than in other crop types (2.8% and 2.3% respectively) while only 1.4 percent of roots and tubers was applied with herbicides (Chart 3.72). The top six annual crops with highest percentage use of herbicides in terms of planted area were spinach (5.4%), tomatoes (4.3%), simsim (3.7%), sunflower (3.3%), beans (2.4%) and cabbages (2.0%). Tunduru had the highest percent of planted area with herbicides (2.7% of the total planted area with annual crops in the district). This was followed by Mbinga (2.5%) then Songea Urban (1.8%) and Namtumbo (0.4%). The smallest percentage use was recorded in Songea Rural district (0.3%) (Chart 3.73). Chart 3.70 Percent of Planted Area Applied with Insecticides by District - RUVUMA 0.0 20.0 40.0 60.0 Songea Urban Mbinga Songea Rural Namtumbo Tunduru District Percent Chart 3.71 Planted Area Applied with Herbicides by Crop Type Fruits and Vegetables, 143, 2% Cash crops, 84, 1% Oil Seeds & Nuts, 316, 5% Pulses, 907, 15% Roots and Tubers, 1,336, 22% Cereals, 3,334, 55% 0.0 1.0 2.0 3.0 Percent of Planted Area Cereals Roots and Tubers Pulses Oil Seeds & Nuts Fruits and Vegetables Cash crops Crop Type Chart 3.72 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.73 Proportion of Planted Area Applied with Herbicides by District - RUVUMA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Tunduru Mbinga Songea Urban Namtumbo Songea Rural District Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 3.5.5.3 Fungicide Use The planted area applied with fungicides was 17,431 ha which represented 4.9 percent of the total planted area for annual crops and vegetables. There was no fungicide use during the dry season. Cereals had the largest planted area applied with fungicides (9,263ha, 53%) followed by fruits and vegetables (3,251 ha, 18%), roots and tubers (2,502 ha, 14%), pulses (2,502 ha, 12%) and oil crops (488 ha, 3%). The lowest was cash crops (10 ha,0.1% )(Chart 3.74). However, the percentage use of fungicide in fruits and vegetables and pulses was much greater than in other crop types (34.2% and 2.8% respectively), while only 1.4 percent of roots and tubers was applied with fungicides (Chart 3.75). There was no more than 40 percent fungicide use in Ruvuma region. Mbinga had the highest percent of planted area with insecticides (5.3% of the total planted area with annual crops in the district). This was followed by Tunduru (3.5%) and Namtumbo (2.1%). The smallest percentage use was recorded in Songea Urban district (0.7%) (Chart 3.76). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.01%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 73 percent of the total area planted with cereals during the wet season being threshed by hand. Draft animals, engine driven machines and human powered tools were only used on crops harvested from 0.1 percent and 2.4 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. Chart 3.76 Proportion of Planted Area with Fungicides by District - RUVUMA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Mbinga Tunduru Namtumbo Songea Rural Songea Urban District Percent Chart 3.74 Planted Area Applied with Fungicides by Crop Type Oil Seeds and Nuts, 488, 3% Pulses, 2,094, 12% Roots and Tubers, 2,502, 14% Fruits and Vegetables, 3,251, 18% Cash Crops, 10, 0% Cereals, 9,263, 53% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Percent of Planted A rea Cereals Roots and Tubers Pulses Oil Seeds and Nuts Fruits and Vegetables Cash Crops Crop Type Chart 3.75 Percentage of Crop Type Planted Area Applied with Fungicides RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 3.6.1 Area Planted with Annual Crops and Under Irrigation In Ruvuma region, the area of annual crops under irrigation was 9,104 ha representing 3 percent of the total area planted (Chart 3.77). The area under irrigation during the wet season was 15 ha accounting for 0.16 percent of the total area under irrigation. The district with the largest planted area under irrigation with annual crops was Mbinga (2,731 ha, 30% of the total irrigated planted area with annual crops in the region). This is followed by Namtumbo with (2,122 ha, 23%) and then Tunduru (2,025 ha, 22%). When expressed as a percentage of the total area planted in each district, Songea Urban had the highest with 10.8% of the planted area in the district under irrigation. This is followed by Namtumbo (3.0%), Tunduru (2.4%), Mbinga (2.1%) and Songea Rural (1.7%) (Chart 3.78 and Map 3.36). Of all the different crops and in terms of proportion of the irrigated planted area, egg plant was the most irrigated crop with 100 percent irrigation followed by carrot (99%), chillies (98%), cabbage (91%) and amaranths (77%). In terms of crop type, the area under irrigation with cereals was 3,880 ha (4% of the total area under irrigation), followed by fruit and vegetables (3,580 ha,4%) pulses (772 ha, 1%) and roots and tubers (171 ha, 0.05%. All of the irrigation on cereals was applied to maize, paddy, sorghum and finger millet. The area of fruit and vegetables under irrigation was 3,580 ha which represents 70 percent of the total planted area with fruit and vegetables. Tomatoes, cabbages and onions were the most irrigated crops. The number of households practicing irrigation in Ruvuma region appears to have increased over the 10 year intercensal period from 3,319 households in 1995/96 to 3,942 households in 2002/03. This may not be statically significant due to the small number of households sampled with irrigation. Chart 3.79 Time Series of Households with Irrigation - RUVUMA 3,319 3,942 0 1,000 2,000 3,000 4,000 5,000 1995/96 2002/03 Agriculture Year Planted Area under Irrigation Chart 3.77 Area of Irrigated Land Unirrigated Area, 349,099, 97% Irrigated Area, 9,104, 3% Chart 3.78 Planted Area with Irrigation by District-RUVUMA Region 0 600 1200 1800 2400 3000 Mbinga Namtumbo Tunduru Songea Urban Songea Rural District Irrigated Area (ha) 0 3 6 9 12 Percentage with Irrigation Irrigated Land (ha) Percentage of Irrigated Land RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was obtained from river (64% of households with irrigation). This was followed by canals (23%) and wells (7%). Only 0.3 percent of the households used water from boreholes and the percents of households that used dams, pipe water and lakes as a source of water for irrigation were (3%, 2% and 1% respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common method of getting water for irrigation with 57.2 percent of households using this method. This was closely followed by gravity with 41.3 percent of households. The remaining methods (motor pump and others) were of minor importance (Chart 3.81). Hand bucket was used by most households with irrigation in Mbinga (43.9%), followed by Tunduru (19.9%), Songea Rural (16.8%), Songea Urban (10.7%) and Namtumbo (8.7%). Gravity was more common in Namtumbo with 30.5 percent of households using the method to get water for irrigation, followed by Mbinga (26.9), Songea Rural (19.5%), Songea Urban (13.5%) and Tunduru (9.5%). 3.6.4 Methods of Water Application Most households used bucket/watering can irrigation (64% of households using irrigation) as a method of field application. This was followed by flood (30%) Sprinklers (5%) and water hose (1%). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Ruvuma region show that there were 181,775 crop growing households that stored various agricultural products in the region. Chart 3.80 Number of Households with Irrigation by Source of Water Lake, 234, 1% Borehole, 72, 0% Pipe water, 406, 2% Dam, 774, 3% Well, 1,646, 7% Canal, 5,744, 23% River, 15,798, 64% River Canal Well Dam Pipe water Lake Borehole Chart 3.82 Number of Households with Irrigation by Method of Field Application Sprinkler, 1,245, 5% Flood, 7,419, 30% Bucket / Watering Can, 15,691, 64% Water Hose, 205, 1% Bucket / Watering Can Flood Sprinkler Water Hose Chart 3.83 Number of Households and Quantity Stored by Crop Type - RUVUMA 0 40,000 80,000 120,000 160,000 200,000 Maize Beans & Pulses Paddy Sorghum & Millet Groundnuts/Bambara Nuts Seaweed Cashewnut Cloves Crop Number of households 0 10,000 20,000 30,000 40,000 Quantity (t) Number of Households Quantity Stored(Tons) Chart 3.81 Number of Households by Method of Obtaining Irrigation Water Gravity, 10,137, 41% Motor Pump, 250, 1% Other, 132, 1% Hand Bucket, 14,040, 57% Hand Bucket Gravity Motor Pump Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 The most important stored crop was maize with 172,771 households storing 34,081 tonnes as of 1st January 2004. This was followed by paddy (72,495 households, 3,273t), beans and other pulses (86,592 households, 2,599), sorghum and millet (27,879 households, 910t), groundnuts and bambara nuts (21,827 households, 469t) and seeweed (8,550 households, 461t). Other crops were stored in very small quantities. 3.7.1.1 Methods of Storage The region had 108,032 crop growing households storing their produce in sacks/open drum (60% of households that stored crops in the region). The number of households that stored their produce in locally made traditional structure was 66,102 (36%). This was followed by : improved locally made structures (3,702households, 2%) other ( 1,821 households, 1%) unprotected piles (1,490 households, 1%), , modern stores (381 households, recorded 0%), air tight drums (247 households, also recorded 0%). Sacks/open drum were the dominant storage method in all districts, with the highest percent of households in Mbinga using this method (86% of the total number of households storing crop products). This was followed by Songea Urban (67%), Songea Rural (60%), Namtumbo (36%) and Tunduru (30%) (Chart 3.85). The highest percent of households using locally made traditional structure were in Tunduru (66 % of households storing crops) and Namtubo (62%), followed by Songea Rural (36%), Songea Urban (31%) and Mbinga (8%). 3.7.1.2 Duration of Storage Most households (49% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored them for a period of over 6 months. The minority of households stored their crops for a period of less than 3 months (12%). Most households that stored pulses stored them for a period of 3 to 6 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.86). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Mbinga district (58%) followed by Tunduru (52%), Namtumbo (39%), Songea Rural (37%) and Songea Urban (36%) (Map 3.37). Chart 3.84 Number of households by Storage Methods - RUVUMA Locally Made Traditional Crib, 66,102, 36% Improved Locally made Crib, 3,702, 2% Other, 1,821, 1% Airtight Drum, 247, 0% Unprotected Pile, 1,490, 1% Sacks/Open Drum, 108,032, 60% Modern Store, 381, 0% Chart 3.85 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 30,000 60,000 90,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.86 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.87). 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 92.4 percent followed by seed for planting. Practically all stored cash crops, were stored for selling at higher price. A high percent of the stored permanent crops was for selling at higher price, in case of cloves (100%) and seed for planting in case of cashewnuts (68.4%). In case of cashewnuts it was followed by selling at higher price (31.6%) (Chart 3.88). 3.7.1.4 The Magnitude of Storage Loss About 86 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for maize (3.1% of the total number of households that stored crops). This was followed by beans and pulses (2.4%), paddy (1.5%) and groundnuts and bambaranuts (1.0%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (88%) (Table 3.11). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and Crop Estimate Storage Loss Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Number of Households % Number of Households % Number of Households % Number of Households % Total Number of Households Maize 147,610 85.4 19,919 11.5 3,654 2.1 1,661 1.0 172,844 Paddy 66,700 91.6 5,056 6.9 1,067 1.5 0 0.0 72,823 Sorghum & Millet 26,626 95.3 1,069 3.8 255 0.9 0 0.0 27,950 Beans & Pulses 78,470 90.5 6,177 7.1 1,636 1.9 412 0.5 86,695 Seaweed 8,473 99.1 77 0.9 0 0.0 0 0.0 8,550 Cloves 128 100.0 0 0.0 0 0.0 0 0.0 128 Cashewnut 337 100.0 0 0.0 0 0.0 0 0.0 337 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 Coconut 0 0.0 0 0.0 0 0.0 0 0.0 0 Groundnuts/Bambara Nuts 19,457 88.8 2,234 10.2 209 1.0 0 0.0 21,900 Chart 3.87 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 40,000 80,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Quantity (tonnes) 0 4 8 12 16 20 24 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum/Millet Beans & Pulses Seaweed Cloves Cashewnut Coconut Gnuts/Bamb... Crop Type Chart 3.88 Number of Households by Purpose of Storage and Crop Type Food for the Household To Sell for Higher Price Seeds for Planting Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Ruvuma region (188,975 households, 99% of the total crop growing households) (Chart 3.89a). The percent of households processing crops was very high in most districts (above 98%). Songea Urban had the lowest percent of households processing crops (98% of crop growing households) (Chart 3.89b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 66 percent (125,177 households). This was followed by those processing on-farm by hand (48,305 households, 26%), on-farm by machine (10,442 households, 6%) and by trader (4,328 households, 2%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Ruvuma region, district differences existed. Tunduru had a higher percent of hand processing than other districts (52%), followed by Mbinga (21%) and Namtumbo (14%). Processing by on farm by machine was more common in Mbinga and Namtumbo (10% and 4% respectively), whilst processing on farm by trader was more prevalent in Mbinga and Songea Rural (Chart 3.90). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, the main product and the by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. 0 20 40 60 80 100 Percent of Households Processing Songea Rural Namtumbo Tunduru Mbinga Songea Urban District Chart 3.89b Percentage of Households Processing Crops by District Chart 3.90 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.89a Households Processing Crops Households Processing, 188,975, 99% Households not Processing, 2,068, 1% Chart 3.91 Percent of Households by Type of Main Processed Product Grain 11% Oil 0.1% Juice 0.1% Other 0% Pulp 0.0% Flour / Meal 89% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 The main processed product was flour/meal with 168,023 households processing crops into flour (89%) followed by grain with 20,713 households (11%). The remaining products were produced and by a small numbers of households (Chart 3.91). The number of households producing by-products accounted for 91.8 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 152,339 households (88%) followed by Husks (20,484 households, 12%). The remaining by-products were produced by a small numbers of households (Chart 3.92). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most main use was household/human consumption which accounted for 99 percent of the total households that used primary processed product (Chart 3.93). Mbinga was the only district that used primary products as fuel for cooking. Out of 854 households that sold processed products, 386 were from Mbinga (45% of the total number of households selling processed products in the region), followed by Songea Rural with 231 households (27.0%), Tunduru with 210 households (24.6%) and Songea Urban with 27 households (3.1%) (Chart 3.94). Compared to other districts in Ruvuma region, Mbinga had the highest percent of households that sold processed products. This is followed by Songea Rural (0.76), Songea Urban (0.39%) and Tunduru (0.28%). 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to others (10,412 households, 56% of households that sold crops). This was followed by selling to neighbours (5,114 households, 27%), trader at farm (1,263 households, 7%), local market and trade stores (907 households, 5% of households that sold crops), marketing co-operatives (465 households, 2%), large scale farm (365 households, 2%) and Farmers Associations (105 households, 1%) (Chart 3.95). Chart 3.92 Number of Households by Type of By-product Cake, 212, 0% Shell, 213, 0% Juice, 212, 0% Pulp, 0, 0% Other, 0, 0% Husk, 20,484, 12% Bran, 152,339, 88% Chart 3.93 Use of Processed Product Fuel for Cooking, 521, 0% Other, 575, 0% Did Not Use, 517, 0% Animal Consumption, 587, 0% Sale Only, 3,919, 1% Household / Human Consumption, 412,092, 99% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of households Mbinga Songea Rural Tunduru Songea Urban Namtumbo District Chart 3.94 Percentage of Households Selling Processed Crops by District Chart 3.95 Location of Sale of Processed Products Neighbours, 5,114, 27% Local Market / Trade Store, 907, 5% Marketing Co-operative, 465, 2% Other, 10,412, 56% Trader at Farm, 1,263, 7% Large Scale Farm, 365, 2% Farmers Association, 105, 1% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 There are large differences between districts in the proportion of households selling processed products to neighbours with Songea Urban district having the largest percent of households in the district selling to neighbours (62%), whereas Namtumbo had only 9 percent. Songea Urban had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Songea Rural had the highest percent of households selling processed products to traders at farm. In Tunduru, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Namtumbo and Tunduru. 3.7.3 Crop Marketing The number of households that reported selling crops was 176,924 which represent 92.6 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Tunduru (96%) followed by Namtumbo (94%), Mbinga (91%), Songea Rural (91%) and Songea Urban (82%) (Chart 3.97 and Map 3.38). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (84% of crop growing households). Apart from low market prices, other problems were high transport costs (6%), longer distances to the markets (5%), lack of transport (1%), lack of market information (1%) and lack of buyers (1%) and. Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 89 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts except for Songea Rural and Tunduru where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (2.4% and 1.9% respectively). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 26,823 88.5 Price Too Low 1,156 3.8 Trade Union Problems 942 3.1 Market Too Far 518 1.7 Co-operative Problems 498 1.6 Other 303 1.0 Farmers Association Problems 72 0.2 Total 30,314 100.0 Chart 3.96 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Chart 3.97 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Mbinga Tunduru Songea Rural Namtumbo Songea Urban District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.98 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Lack of Market Information 1% Market too Far 5% Transport Cost Too High 6% No Buyer 1% No Transport 2% Other 0% Open Market Price Too Low 84% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Ruvuma region a considerable number of agricultural households (38,567, 18.6%) accessed credit out of which 32,939 (85%) were male-headed households and 5,628 (15%) were female headed households. In all districts both male and female headed households accessed agricultural credit (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Ruvuma region were family, friends and relatives which collectively provided credit to 15,355 agricultural households (39% of the total number of households that accessed credit), followed by co- operative (39%), trader/trade store (7%), saving and credit society (6%), religious organizations/non governmental organizations/ projects (5% ), private individual (2%), commercial bank (1%) and other sources (1%) (Chart 3.99). Commercial banks provided credit to very few households in Songea Rural and Mbinga. Savings and credit societies provided credits in all districts except Namtumbo. Trader/trader store privided credits to a small numbe of households in Tunduru, Songea Rural and Namtumbo districts. Religious organization, cooperative provided credit in all districts while private individuals provided credit mainly in Songea Rural district. NGOs and projects funded a relatively large number of households in Songea Rural disrtict (Chart 3.100). 3.8.1.2 Use of Agricultural Credit Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Tunduru 2,992 93 212 7 3,204 Songea Rural 4,149 70 1,813 30 5,962 Mbinga 12,568 91 1,302 9 13,870 Songea Urban 566 78 161 22 727 Namtumbo 12,664 86 2,140 14 14,804 Total 32,939 85 5,628 15 38,567 Chart 3.99 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 1% Other 1% Private Individual 2% Family, Friend and Relative 39% Co-operative 39% Trader / Trade Store 7% Saving & Credit Society 6% Religious Organisation / NGO / Project 5% Chart 3.101 Proportion of Households Receiving Credit by Main Purpose of the Credit Other 8% Seeds 7% Fertilizers 43% Labour 16% Livestock 4% Irrigation Structures 0% Tools / Equipment 5% Agro-chemicals 17% Chart 3.102 Reasons for not Using Credit (% of Households) Credit granted too late, 797, 1% Don't know about credit, 24,187, 16% Other, 506, 0% Difficult bureaucracy procedure, 5,694, 4% Did not know how to get credit, 47,344, 31% Interest rate/cost too high, 8,916, 6% Did not want to go into debt, 16,752, 11% Not available, 43,069, 28% Not needed, 5,238, 3% Chart 3.100 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Percent of Households Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader/Trade Store Private Individual Religious Organisation/NGO/Project Other RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 A large proportion of the agricultural credit provided to agricultural households in the region was used on fertilizers (43%), followed by agro-chemicals (17%) and hiring labour (16%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment, seeds and unspecified was very low (Chart 3.101). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 31 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (28%), “not wanting to go into debt” (11%) and interest too high (6%). The rest of the reasons were given by 8 percent of the households. Chart 3.104 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Number of Househo 0 20 40 60 Percent of Househol Households Receiving Extension Percentage of Households Receiving Extension Chart 3.103 Number of Households Receiving Extension Advice Households Receiving Extension , 67,199, 35% Households Not Receiving Extension , 123,844, 65% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 67,199 (35% of total crop growing households in the region) (Chart 3.103). Some districts had more access to extension services than others, with Namtumbo having a relatively high proportion of households (55%) that received crop extension messages followed by Songea Urban (40%), Mbinga (35%), Tunduru(30%) and Songea Rural (23%) (Chart 3.104 and Map 3.39). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (89.1%, 59,075 households). Large scale farms 3.8 percent and cooperative 2.9 pecent and the remaining sources provided 4.2 percent (Chart 3.105), however district differences did exist with the proportion of the households receiving advice from government services ranging from 83.3 percent in Mbinga to 93.6 percent in Tunduru. 3.8.2.2 Quality of Extension On the quality of extension, 69percent of the households receiving extension ranked the service as being good followed by average (18 %), very good (11%), poor (1%) and no good (1%) (Chart 3.106). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Ruvuma Region regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households used inputs and this was particularly true for inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertilisers and herbicides. In Ruvuma region inorganic fertiliser were used by 91,930 households which Table 2.14 Access to Inputs Households With Access to Inputs Households Without Access to Inputs Type of Input Number % Number % Farm yard manure 61,064 31.9 129,979 68.0 Improved seeds 26,646 13.9 164,397 86.1 Insecticides/Fungicide 65,929 34.5 125,114 65.5 Compost 6,305 3.3 184,738 96.7 Inorganic fertilizers 91,930 48.1 99,113 51.9 Herbicide 2,011 1.1 189,032 98.9 Chart 3.105 Number of Households Receiving Extension Messages by Type of Extension Provider Government 89.1% Other 1.5% NGO / Development Project 2.7% Cooperative 2.9% Large Scale Farm 3.8% Chart 3.106 Number of Households Receiving Extension by Quality of Services Very Good, 7,192, 10.8% No Good, 668, 1.0% Poor, 1,068, 1.6% Average, 11,967, 17.9% Good, 45,969, 68.8% Chart 3.107 Number of Households by Source of Inorganic Fertiliser 0.1 0.2 0.2 0.6 0.8 1.9 2.3 16.9 77.0 0 20,000 40,000 60,000 80,000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Crop Buyers Secondary Market Other Locally Produced by Household Large Scale Farm Source of Inorganic Fertiliser Number of Households Songea Urban Songea Rural 5,717 28,109 70,589 27,456 45,053 82.3% 91.3% 91.1% 94.3% 96.1% Mbinga Namtumbo Tunduru Songea Rural Namtumbo Songea Urban 37% 39% 36% 58% 52% Mbinga Tunduru Percent of Households Storing Crops for 3 to 6 Months by District MAP 3.39 RUVUMA Number of Households Selling Crops MAP 3.40 RUVUMA Number of Households and Percent of Total Households Selling Crops by District Percent of Households Storing Crops for 3 to 6 Months Percent of Households Storing Crops for 3 to 6 Months Number of Households Selling Crops Percent of Total Households Selling Crops 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census RESULTS 65 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 represents 48.1 percent of the total number of crop growing households. This was followed by households using fungicides (34.5%), farm yard manure (31.9%), improved seeds (13.9%), compost (3.3%) and herbicide (1.1%) (Table 2.14). 3.9.2 Inorganic Fertilisers Smallholders that used inorganic fertilisers in Ruvuma, mostly purchased them from the local market/trade store (77.0% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.107). Access to inorganic fertiliser was mainly above 3 km from the household with most households residing above 20 km from the source (28%), followed by less than 1 km (24%) and between 10 and 20 km (20%) (Chart 3.108). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (6% ) as the reason for not using, it may be assumed that access to inorganic fertiliser was not the main reason for not using them. Other reasons such as cost were more important. In other words, if the cost was affordable the demand would be higher and inorganic fertiliser would be made more available. More smallholders used inorganic fertilisers in Songea Rural than in other districts in Ruvuma region (28% of households using inorganic fertilisers), followed by Namtumbo (26%), Mbinga (23%), Tunduru (16%) and Songea Urban (7.1%). 3.9.3 Improved Seeds The percent of households that use improved seeds was 14 percent of the total number of crop growing households. Most of the improved seeds were obtained from the local market/trade store (78.8%). Other less important sources of improved seeds were cooperative (9.6%), neighbours (7.6%) and local farmers group (0.9%). Only 0.9 percent of households using improved seed obtained them from crop buyers (Chart 3.109). Access to improved seeds was poorer than access to chemical inputs with 31 percent of households obtaining from 20 km and above from the household (Chart 3.110). This is in line with the higher use of chemical inputs compared to other improved seed, which further supports the contention that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. Chart 3.108 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.109 Number of Households by Source of Improved Seed 78.8 9.6 7.6 0.9 0.9 0.8 0.4 0.6 0.1 0.4 0 10,000 20,000 30,000 Local Market / Trade Store Co-operative Neighbour Local Farmers Group Crop Buyers Development Project Other Secondary Market Large Scale Farm Locally Produced by Household Source of Improved Seed Number of Households Chart 3.110 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 The districts that used improved seeds most was Mbinga (37.7 percent of the total number of households using improved seeds in Ruvuma region), followed by Songea Rural (25.7%) and Namtumbo (18.6%). Use of improved seeds in other districts is of minor importance (Map 3.40). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchased them from local markets/trade stores (49.6% of the total number of fungicide users). This was followed by cooperative (25.7%), local farmers group (16.1%), neighbour (4.6%) and crop buyers (3.1%). Other sources of insecticides/ fungicides are of minor importance (Chart 3.111). Chart 3.112 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. From the small number of households using insecticides/fungicides, coupled with the 34 percent of households responding to “not available” as the reason for not using it may be assumed that access was not the main reason for not using Them. Other reasons such as cost were more important with 74 percent of households responding to cost factors as the main reason for not using them. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were used more in Mbinga district (57.9 percent of the total number of households that use fungicide in the region), followed by Tunduru (29.2%). Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 43,315 representing 23 percent of the total number of agriculture households (Chart 3.113 and Map 3.41). Chart 3.111 Number of Households by Source of Insecticide/fungicide 0.2 0.2 0.5 3.1 4.6 16.1 25.7 49.6 0 6,000 12,000 18,000 24,000 30,000 Local Market / Trade Store Co-operative Local Farmers Group Neighbour Crop Buyers Locally Produced by Household Other Development Project Source of Insecticide/Fungicide Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.113 Number of Households with Planted Trees hh growing trees, 43,336, 23% Not growing trees, 147,839, 77% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 The number of trees planted by smallholders on their allotted land was 10,594,983 trees. The average number of trees planted per household planting trees was 245 trees. The main specie planted by smallholders is eucalyptus spp (7,638,602 trees, 72.1%), followed by Cyprus spp (1,298,088 trees, 12.3%) and gravellis (714,902 trees, 6.7%), senna (243,200 trees, 2.3%), pinnus (224,651 trees, 2.1%), acacia (210,757 trees, 2.0%) and calophylum inophylum (173,727 trees, 1.6%). The remaining trees species are planted in comparatively small numbers (Chart114.). Mbinga has the largest number of smallholders with planted trees than any other district (92.5%) and is dominated by eucalyptus species. This is followed by Songea Urban (3.2%) which is dominated by eucalyptus. Then Songea Rural (3.0%) which is mainly planted with calophylum inophylum species and Namtumbo (1.2%) which is planted with senna species (Chart 3.115). Most trees were planted on plantations or coppice. The proportion of trees that were planted on plantations was 69 percent, followed trees scattered around fields (17%) and then trees planted on the boundaries (14%) (Chart 3.116). The main purpose of planting trees was to obtain planks/timber (37.2%). This is followed by shade (29.5%), wood for fuel (24.5%) and poles (7.6%) (Chart 3.117). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and Chart 3.118 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 178,772, 94% Households with facilities, 12,403, 6% Chart 3.116 Number of Trees Planted by Location Field boundary, 1,436,584, 14% Scattered in field, 1,758,712, 17% Plantation, 7,399,687, 69% Chart 3.117 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 P lanks / Timber Shade Wo o d fo r Fuel P o les Medicinal Other Charco al Use Percent of Households Chart 3.114 Number of Planted Trees by Species - RUVUMA 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 8,000,000 Eucalyptus Spp Cyprus Spp Gravellis Senna Spp Pinus Spp Acacia Spp Calophylum Inophyllum Albizia Spp Kyaya Spp Jakaranda Spp Melicia excelsa Others Tree Species Number of Trees Chart 3.115 Number of Trees Planted by Smallholders by Species and Region 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 Songea Rural Mbinga Songea Urban Namtumbo Thousands Region Number of Trees Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Senna Spp P inus Spp Albizia Spp Calo phylum Ino phyllum J akaranda Spp Kyaya Spp Melicia excels a Others RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 water harvesting facilities on their farms was 12,403 which represent 6 percent of the total number of agricultural households in the region (Chart 3.118). The proportion of households with soil erosion control and water harvesting facilities was highest in Mbinga district (12%) followed by Songea Urban (11%), Songea Rural (3%), Namtumbo (1%) and Tunduru (1%) (Chart 3.119 and Map 3.42). Terraces accounted for 42.6 percent of the total number of structures, followed by erosion control bunds (28.8%), water harvesting bunds (18.7%), tree belts (3.7%), drainage ditches (3.7%), vetiver grass (2.0%), dams (0.3%) and gabions/sandsbags (0.1%) (Chart 3.120). Erosion control by terraces, erosion control bunds and water harvesting bunds together had 179,029 structures. This represented 90 percent of the total structures in the region. The remaining 10 percent was shared among the rest of the erosion control methods mentioned above. Mbinga and Songea Rural districts had 10,617 erosion control structures (86 percent of the total erosion structures in the region). Chart 3.120 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0.1 0.3 2.0 3.7 3.7 18.7 28.8 42.6 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Terraces Erosion Control Bunds Water Harvesting Bunds Tree Belts Drainage Ditches Vetiver Grass Dam Gabions / Sandbag T y p e o f F a c ilit y Number of Structures Chart 3.119 Number of Households with Erosion Control/Water Harvesting Facilities 12 3 11 1 1 0 2,000 4,000 6,000 8,000 10,000 12,000 Mbinga Songea Rural Songea Urban Tunduru Namtumbo District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Songea Urban Songea Rural Tunduru 1,840 2,868 215 0 32,259 21.9% 56.8% 12% 0% 17.8% Mbinga Namtumbo Songea Rural Songea Urban 8,048 3,572 28,452 3,243 0 26.2% 51.4% 36.7% 11.1% 0% Mbinga Namtumbo Tunduru Number and Percent of Smallholder Planted Trees by District MAP 3.43 RUVUMA Number of Households With Water Harvesting Bunds MAP 3.44 RUVUMA Number and Percent of Households With Water Harvesting Bunds by District Number and Percent of Smallholder Planted Trees Number of Smallholder Planted Trees Percent of Smallholder Planted Trees Percent of Households With Water Harvesting Bunds Number and Percent of Households With Water Harvesting Bunds 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census RESULTS 70 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 121,175. Cattle were the dominant livestock type in the region followed by goats, pigs and sheep. The region had 0.7 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Ruvuma region was 105,884 (87.4 % of the total number of cattle in the region), 15,111 cattle (12.5%) were dairy breeds and 181 cattle (0.1%) were beef breeds. The census results show that 16,887 agricultural households in the region (8.8% of total agricultural households) kept 0.1 million cattle. This was equivalent to an average of 7 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Mbinga which had about 100,907 (83.3% of the total cattle in the region). This was followed by Songea Rural (11,164 cattle, 9.2%), Tunduru (4,040 cattle, 3.3%) and Namtumbo (2,815 cattle, 2.3%). Songea Urban district had the least number of cattle (2,250 cattle, 1.9%) (Chart 3.121 and Map 3.43). However Mbinga district had the highest density (23 head per km2 ) (Map 3.44). Although Mbinga district had the largest number of cattle in the region, most of them were indigenous. The number of dairy cattle was very small and there were no beef cattle. However, Mbinga district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.122). 3.12.1.2 Herd Size Ninety percent of the cattle-rearing households had herds of size 1-5 cattle with an average of two cattle per household. Herd sizes of 6-30 accounted for about 13 percent of all cattle in the region. Only 1 percent of the cattle rearing households had herd sizes of 31- 151 and above cattle. About 98.8 percent of total cattle rearing households had herds of size 1-30 cattle and owns 43 percent of total cattle in the region, resulting in an average of 3 cattle per cattle rearing household. There were about 129 households with a herd size of more than 151 cattle each (66,366 cattle in total) resulting in an average of 513 cattle per household. 0 20 40 60 80 100 120 Number of Cattle ('000') Mbinga Songea Rural Tunduru Namtumbo Songea Urban Districts Chart 3.121 Total Number of Cattle ('000') by District Chart 3.122 Number of Cattle by Type and District 0 40,000 80,000 120,000 Mbinga Songea Rural Tunduru Songea Urban Namtumbo Districts Number of Cattle Indigenous Beef Dairy RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.12.1.3 CattlePopulation Trend Cattle population in Ruvuma increased during the eight-year period from 75,027 in 1995 to 121,175 cattle in 2003. This implies an overall positive average annual growth rate of 6.2 percent (Chart 3.123). There was a small increase in number of cattle during the five-year period from 1995 to 1999 at the rate of 1.6 percent whereby the number increased from 75,027 to 79,969. Moreover, the number of cattle is estimated to have increased from 79,969 in 1999 to 121,175 in 2003at the rate of 10.9 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Ruvuma region was 15,292 (15,111 dairy and 181 improved beef). The diary cattle constituted 12.5 percent of the total cattle and 99 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 1 percent of the total number of the improved cattle and 0.2 percent of the total cattle. The number of improved cattle increased from 1,325 in 1995 to 15,111 in 2003 at an average annual growth rate of 35.6 percent. The growth rate was lower from 1995 to 1999 (35.6%) than from 1999 to 2003 (41.8%) (Chart 124). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by pig and sheep rearing. In terms of total number of goats on the Mainland, Ruvuma region ranked 15 out of the 21 regions with 2.6 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Ruvuma region was 68,381 (36% of all agricultural households in the region) with a total of 309,595 goats giving an average of 5 head of goats per goat- rearing-household. Mbinga had the largest number of goats (122,564 goats, 40% of all goats in the region), followed by Namtumbo (72,649 goats, 23%) and Songea Rural (60,790 goats, 20%). Tunduru and Songea Urban districts had the 75,027 79,969 121,175 - 40,000 80,000 120,000 160,000 Number of cattle 1995 1999 2003 Year Chart 3.123 Cattle Population Trend 1,325 3,738 15,111 - 10,000 20,000 Number of cattle 1995 1999 2003 Year Chart 3.124 Dairy Cattle Population Trend 0 40 80 120 160 Number of Goats ('000') Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Chart 3.125 Total Number of Goats ('000') by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 least number of goats (43,548 goats, 14% and 10,044 goats, 3% respectively) (Chart 3.125 and Map 3.45). However Songea Urban district had the highest density (62 head per km2 ) (Map 3.46) 3.12.2.2 Goat Herd Size Sixty two percent of the goat-rearing households had herd sizes of 1-4 goats with an average of 2 goats per goat rearing household. Ninety seven percent of total goat-rearing households had herd sizes of 1-14 goats and owned 97 percent of the total goats in the region resulting in an average of 4 goats per goat-rearing households. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98 percent of the total goats in Ruvuma region. Both improved goats for meat and diary goats constituted 1 percent each of total goats in the region. 3.12.2.4 Goat Population Trend The overall average annual growth rate of goat population from 1995 to 2003 was -1.5 percent. This negative trend implies eight years of population decrease from 348,509 in 1995 to 309,595 in 2003. The number of goats increased from 348,509 in 1995 at an estimated annual rate of 11.5 percent to 537,843 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -12.9percent (Chart 126). 3.12.3. Sheep Production Sheep rearing was the fourth important livestock keeping activity in Ruvuma region after cattle goats and pigs. The region ranked 18 out of 21 Mainland regions and had 1 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 7,390 (4% of all agricultural households in Ruvuma region) rearing 24,458 sheep, giving an average of 3 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Mbinga with 13,073 sheep (53%of total sheep in Ruvuma region) followed by Tunduru (5,671 sheep, 23%), Songea Rural (4,070 sheep, 17%) and Namtumbo (1,371, 6%). Songea Urban District had the least number of sheep (275 sheep, 1%) (Chart 3.127and Map 3.47). Mbinga district also had the highest density (3 head per km2 ) (Map 3.48). Sheep rearing was dominated by indigenous breeds that constituted 96 percent of all sheep kept in the region. Only 4 percent of the total sheep in the region were improved breeds. 348,509 537,843 309,595 - 200,000 400,000 600,000 Number of goats 1995 1999 2003 Year Chart 3.126 Goat Population Trend 0 5,000 10,000 15,000 Number of sheep Mbinga Tunduru Songea Rural Namtumbo Songea Urban District Chart 3.127 Total Number of Sheep by District RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight-year period from 1995 to 2003 was estimated at -6.5 percent. The population increased at an annual rate of 4.4 percent from 41,890 in 1995 to 49,801 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -16.3 percent (Chart 3.128). 3.12.4. Pig Production Piggery was the third most important livestock keeping activity in the region after cattle and goats. The region ranks 5 out of 21 Mainland regions and had 14.0 percent of the total pigs on Tanzania. The number of pig-rearing agricultural households in Ruvuma region was 54,852(29% of the total agricultural households in the region) rearing 134,951 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Mbinga with 102,373 pigs (76% of the total pig population in the region) followed by Songea Rural (20,763 pigs, 15%), Namtumbo (6,909 pigs, 5%) , Songea Urban (3,308 pigs, 2%) and Tunduru (1,598 pigs, 1%) (Chart 3.129 and Map 3.49). Mbinga district had the highest density (23 head per km2 ) (Map 3.50). 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 5.3 percent. During this period the population grew from 89,600 to 134,951. The pig population increased from 89,600 in 1995 to 182,347 in 1999 at the rate of 19.4 percent. The growth rate dropped to -7.2 percent during the following four years from 1999 to 2003 in which pig population decreased from 182,347 to 134,951 (Chart 3.130). 41,890 49,801 24,458 - 20,000 40,000 60,000 Number of sheep 1995 1999 2003 Year Chart 3.128 Sheep Population Trend 0 40,000 80,000 120,000 Number of Pigs Mbinga Songea Rural Namtumbo Songea Urban Tunduru District Chart 3.129 Total Number of Pigs by District 89,600 182,347 134,951 - 40,000 80,000 120,000 Number of pigs 1995 1999 2003 Year Chart 3.130 Pig Population Trend RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 75 3.12.5 Chicken Production The poultry sector in Ruvuma region was dominated by chicken production. The region contributed 4.7 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 139,284 raising about 1,555,617 chickens. This gives an average of 11 chickens per chicken-rearing household. In terms of total number of chickens in the country, Ruvuma region was ranked eighth out of the 11 Mainland regions. The District with largest number of chickens was Mbinga (647,834 chickens, 42% of the total number of chickens in the region) followed by Namtumbo (304,763, 20%), Songea Rural (279,909, 18%) and Tunduru (257,329, 17%). Songea Urban district had the smallest number of chickens (65,782, 4%) (Chart 3.133 and Map 3.51). However Songea Urban district had the highest density (422 head per km2 ) (Map 3.52). 3.12.5.2 Chicken Population Trend The overall annual population growth rate for chicken during the eight-year period from 1995 to 2003 was 4.5 percent. The population increased at a rate of 13.3 percent from 1995 to 1999 after which it decreased at -3.6 percent for the four-year period from 1999 to 2003 (Chart 3.132). Ninety nine percent of all chicken in Ruvuma region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 85 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 15 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 41 chickens per holder (Table 3.15). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 36,278 26 96,787 3 5 - 9 40,716 29 268,983 7 10 - 19 41,041 29 546,003 13 20 - 29 12,834 9 287,289 22 30 - 39 4,822 3 156,927 33 40 - 49 1,490 1 66,756 45 50 - 99 2,103 2 132,872 63 Total 139,284 100 1,555,617 11 1,092,234 1,799,158 1,555,617 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.132 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Number of Chickens Mbinga Namtumbo Songea Rural Tunduru Songea Urban District Chart 3.131 Total Number of Chickens by District Songea Urban Songea Rural Mbinga Namtumbo 14.4 2 22.8 0.3 0.6 Tunduru 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Songea Urban Tunduru Namtumbo Songea Rural 2,250 100,907 4,040 2,815 11,164 Mbinga Cattle population as of 1st Octobers 2003 by District MAP 3.45 RUVUMA Number of Cattle per Square Km MAP 3.46 RUVUMA Cattle Density as of 1st October 2003 by District Number of Cattle 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 Number of Population Cattle Density Tanzania Agriculture Sample Census RESULTS 76 Songea Urban Songea Rural 64.4 11 27.7 8.5 6.2 Mbinga Namtumbo Tunduru Songea Urban Songea Rural 10,044 60,790 122,564 72,649 43,548 Mbinga Namtumbo Tunduru Goat population as of 1st Octobers 2003 by District MAP 3.47 RUVUMA Number of mGoat per Square Km MAP 3.48 RUVUMA Goat Density as of 1st October 2003 by District Goat Population 100,000 to 125,000 75,000 to 100,000 50,000 to 75,000 25,000 to 50,000 0 to 25,000 60 to 75 45 to 60 30 to 45 15 to 30 0 to 15 Goat Density Goat Population Tanzania Agriculture Sample Census RESULTS 77 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Ruvuma region increased at an annual rate of 15.3 percent for the four-year period from 11,709 in 1999 to 6,037 in 2003. The number of improved chicken was most significant in Songea Urban district followed by Songea Rural district (Chart 3.133). The overall average annual growth rate for broilers during the eight-year period from 1995 to 2003 was 38.6 percent during which the population grew from 974 to 13,250. The annual growth rate was higher (135.7%) for the first four-year (1995 to 1999). The broiler population exhibited a decreasing trend at the rate of -18.5 percent per annum for the period of four years resulting at increase from 30,064 in 1999 to 13,250 in 2003 (Chart 3.134). 3.12.6. Other Livestock There were 42,163 rabbits, 868 turkeys, 38,878 ducks and 4,600 donkeys raised by rural agricultural households in Ruvuma region. Table 3-32 indicates the number of livestock kept in each district. The biggest number of rabbits in the region was found in Mbinga district (74% of all rabbits in the region), followed by Namtumbo (11%), Songea Rural (7%) and Songea Urban (6%). Tunduru district had the least number of rabbits estimated at 2 percent of total rabbits in the region. Ducks were reported mainly in Tunduru and Mbinga districts (Table 3.16). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 32 percent and 15 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.135 shows that there was a predominance of tick related diseases over tsetse related diseases. While tick incidences were highest in Mbinga and lowest in Tunduru, tsetse incidences were highest in Tunduru and lowest in Songea Urban.(Chart 3.135 and Map 3.53). Table 3.16 Number of Other Livestock by Type of Livestock and District Types of Livestock District Rabbits Turkeys Ducks Donkeys Other Tunduru 984 0 15,865 984 14,460 Songea Rural 2,963 689 3,422 0 0 Mbinga 31,130 124 10,426 3,616 1,580 Songea Urban 2,472 55 2,970 0 408 Namtumbo 4,614 0 6,195 0 576 Total 42,163 868 38,878 4,600 17,025 0 640 0 5,318 2,749 646 2,499 2,884 788 3,762 0 1,000 2,000 3,000 4,000 5,000 6,000 Number of Chickens Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.133 Number of Improved Chicken by Type and District Layer Broiler - 974 11,709 30,064 6,037 13,250 - 10,000 20,000 30,000 40,000 Number of layers 1995 1999 2003 Year Chart 3.134 Layers Population Trend Layers Broilers Chart 3.135 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 10 20 30 40 Mbinga Songea Rural Namtumbo Songea Urban Tunduru District Percent Ticks Tsetseflies RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 79 The most practiced method of tick controlling was spraying with 43 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (7%), smearing (2%) and other traditional methods like hand picking (19%). However, 29 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 31 percent of livestock-rearing households This was followed by dipping (2%) and trapping (1%). However,66 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 21,145 (43% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 65 percent, goats (7%), sheep (29%) and pigs (23%) (Chart 3.136). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 30,585 representing 62 percent of the total livestock-rearing households and 16.0 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 79.4 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (9.5%), large-scale farmers (5.1%) and cooperatives (3.7%). About 66 percent of livestock rearing households described the general quality of livestock extension services as being good, 16 percent said they were very good and 14 percent said they were average. However, 3 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.137). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 68 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 32 percent of them accessed the services within 0 20 40 60 Percent Tunduru Songea Rural Mbinga Songea Urban Namtumbo District Chart 3.136 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.137 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good 66% Very Good 16% Poor 1% No good 3% Average 14% Chart 3.138 Number of Households by Distance to Verinary Clinic More than 14 km, 26,298, 68% Less than 14 km, 12,466, 32% Chart 3.139 Number of Households by Distance to Verterinary Clinic and District 0 5,000 10,000 15,000 Tunduru Namtumbo Songea Rural Mbinga Songea District Number of Households Less than 14 kms More than 14 kms Mbinga Songea Rural Songea Urban Namtumbo Tunduru 3 0.7 1.8 0.8 0.2 Songea Urban Songea Rural 275 13,073 4,070 1,371 5,671 Mbinga Namtumbo Tunduru Sheep population as of 1st Octobers 2003 by District MAP 3.49 RUVUMA Sheep Density MAP 3.50 RUVUMA Sheep Density as of 1st October 2003 by District Number of Sheep 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 3.2 to 4 2.4 to 3.2 1.6 to 2.4 0.8 to 1.6 0 to 0.8 Number of Sheep pe Square Km Sheep Population Tanzania Agriculture Sample Census RESULTS 80 Songea Urban Mbinga Namtumbo Songea Rural 21.2 23.1 0.2 0.8 3.7 Tunduru 20 to 25 15 to 20 10 to 15 5 to 10 0 to 5 Songea Urban Tunduru Namtumbo Songea Rural 3,308 20,763 1,598 6,909 102,373 Mbinga Pig population as of 1st Octobers 2003 by District MAP 3.51 RUVUMA MAP 3.52 RUVUMA Pig Density as of 1st October 2003 by District Number of Pig 80,000 to 120,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Pig Density Number of Pig per Square Km Pig Population Tanzania Agriculture Sample Census RESULTS 81 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 14 kms from their dwellings (Chart 3.138). The most affected district was Songea Urban district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Mbinga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.139). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 10,626 (93% of livestock rearing households in Ruvuma region) whilst 584 households (5%) resided between 5 and 29 kms. However, 201 households (2%) had to travel a distance of 30 or more kms to f the nearest watering point (Chart 3.140). Tunduru district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This was followed by Mbinga, Songea Rural and Songea Urban districts. In Namtumbo district about 43 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.141). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Ruvuma region was very limited with only 172 households (0.09% of the total households in the region) using them (Chart 3.142). The large number of households that used draft animals were in Songea Rural ( 76 households, 44%), followed by Namtumbo (69 households,40%) and Songea Urban (27 households, 16%). whilst in Kilindi only 49 households (11%) used draft animals. Use of draft animals was not reported in the other districts (Chart 3.143 and Map 3.54). 3.142 Number of Households Using Draft Amimals Not Using Draft Animals, 191,003, 99.9% Using Draft Animals, 172, 0.1% 0 20 40 60 80 Number of Household Songea Rural Namtumbo Songea Urban Tunduru Mbinga District Chart 3.143 Number of Households Using Draft Animals by District - RUVUMA Chart 3.140 Number of Households by Distance to Village Watering Points 30 or more kms, 201, 2% 5-29 kms, 584, 5% Less than 5 kms, 10,626, 93% Chart 3.141 Number of Households by Distance to Village Watering Point and District 0 1,000 2,000 3,000 4,000 5,000 Tunduru Mbinga Songea Rural Songea Urban Namtumbo District Number of Households Less than 5 kms 5-29 kms 30 or more kms Mbinga Namtumbo Songea Rural Songea Urban 146.4 36.6 35.8 50.5 422.1 Tunduru Tunduru Namtumbo Songea Urban Songea Rural 257,329 304,763 65,782 279,909 647,834 Mbinga Chicken Density Number of Chicken by District as of 1st October 2003 MAP 3.53 RUVUMA MAP 3.54 RUVUMA Density of Chicken by District as of 1st October 2003 Number of Chicken per Square Km Tanzania Agriculture Sample Census Number of Chicken Chicken Population 600,000 to 750,000 450,000 to 600,000 300,000 to 450,000 150,000 to 300,000 0 to 150,000 400 to 500 300 to 400 200 to 300 100 to 200 0 to 100 RESULTS 83 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 The region had 55 oxen. Only Songea Urban had 55 oxen which were used to cultivate 33 hectares of land. This represented only 0.001 percent of the total oxen found on the Mainland. 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Ruvuma region was 54,534 (29% of total crop growing households in the region) (Chart 3.144). The total area applied with with farm yard manure was 22,227 hectares (95% of the total area applied with organic fertiliser and 6.2% of the area planted with annual crops and vegetables in Ruvuma region in the wet season). The largest area applied with farm yard manure was found in Mbinga district with 17,255 hectares (78% of the total area applied with farm yard manure) followed by Songea Rural (1,842 ha, 8%), Tunduru (1,439 ha, 6%), Namtumbo (1,108 ha, 5%) and Songea Urban (585 ha, 3%) (Chart 3.145and Map 3.55). 3.12.9.4 Use of Compost Only 3,591 ha (5% of the area of organic fertilizer application) was applied with compost. Mbinga had the largest planted area with compost application (1,561 ha, 43.5% of the total area applied with compost in the region), followed by Songea Rural (829 ha, 23.1%), Tunduru (649 ha, 18.1%), Namtumbo (394 ha, 11.0%) and Songea Urban (394 ha, 4.4%) (Map 3.56) 3.12.10 Fish Farming The number of households involved in fish farming in Ruvuma region was 4,035, representing 2 percent of the total agricultural households in the region (Chart 3.146). Songea Rural was the leading district with 1,294 households (32.1% of agricultural households involved in fish farming. In the region).This was followed by Namtumbo (933 households, 23.1%), Mbinga (910 households, 22.5%), Songea Urban (610 households, 14.9%) and Tunduru (298 households, 7.4%). (Chart 3.147 and Map 3.57). Chart 3.144 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 54,534, 29% Not Using Organic Fertilizer, 134,261, 71% Chart 3.145 Area of Application of Organic Fertiliser by District RUVUMA 0 6,000 12,000 18,000 Mbinga Songea Rural Tunduru Namtumbo Songea Urban District Farm Yard Manure Area Applied Compost Area Applied Chart 3.146 Number of Households Practicing Fish Farming - RUVUMA Households NOT Practicing Fish Farming, 187,140, 98% Households Practicing Fish Farming, 4,035, 2% RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 The main source of fingerings was the neighbours which provided fingering to 76 percent of the fish farming households. About 12 percent of households practicing fish farming got fingerings from government institutions and 9 percent got them from non governmental organizations and/or projects. The fish farming households in the region used various fish farming systems (natural pond, dug out pond, water reservoir and others not identified) and the main fish species planted was Tilapia. The number of fish harvested in Ruvuma region was 758,065 of which 691,048 fish (91.2%) were tilapia, 22,353 (2.9%) were carp and 44,663 (5.9%) were not identified (Chart 3.148). About 36 percent of the fish farming households sold their fish to neighbours, those who sold to traders were 4%, and selling to others were 2% while 57 percent did not sell. Chart 3.148 Fish Production Number of Carp, 22,353, 3.1% Number of Tilapia, 691,048, 96.9% 0 200 400 600 800 1,000 1,200 1,400 Number of Households Songea Rural Namtumbo Mbinga Songea Urban Tunduru District Chart 3.147 Number of Households Practicing Fish Farming by District - Ruvuma RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services Table 3.17 Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather Roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Markets Tertiary Markets Tarmac Roads Tunduru 18.7 1.5 10.9 3.0 32.0 7.6 288.3 4.5 22.7 43.9 274.1 Songea Rural 18.0 1.5 3.2 0.5 46.6 8.5 54.2 14.6 44.6 40.8 23.6 Mbinga 14.9 2.7 8.6 2.5 27.0 6.1 125.0 8.8 34.8 43.3 106.4 Songea Urban 5.0 4.3 1.3 0.9 10.8 8.3 7.6 5.1 9.1 7.8 4.4 Namtumbo 15.4 1.3 19.8 3.6 70.5 6.6 79.7 7.6 56.6 62.3 73.4 Total 16.0 2.1 9.7 2.4 37.4 7.0 142.5 8.4 35.8 44.6 125.5 The results indicate that among the evaluated services, regional capital was a service located farthest from most of the household’s dwellings. It was located at an average distance of 143 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (126), tertiary market (45), hospital (37), secondary market (36), secondary school (16), all weather road (10), primary market (8), health clinic (7), feeder road 2) and primary school (2) (Table 3.17). 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (181,572 households, 96% of all rural agricultural households) 4767 households (2%) use flush toilets and 2,745 households (1%) use improved pit latrine. However, 2,090 households (1%) had no toilet facilities (Chart 3.119). The distribution of the households without toilets within the region indicates that 49.6 percent of them were found in Tunduru District and 3.3 percent were from Namtumbo. The percentages of households without toilets in other districts were as follows Mbinga (25.1%), Songea Rural (18.1%) and Songea Urban (3.9%) (2.5%) (Map 3.58). 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Ruvuma region with 109,159 households (57.1% of the agriculture households in the region) owning the asset, followed bicycles (69,706 households, 36.5%), irons (49,616 households, 26.0%), wheelbarrows (7,944 households, 4.2%), mobile phones (2,460 households, 1.3%), vehicles (2,284 households, 1.2%), TVs/Videos (1,549 households, 0.8%) and landline phones (1,496 households, 0.8%) (Chart 3.150). Chart 3.149 Agricultural Households by Type of Toilet Facility No Toilet , 2,090, 1% Improved Pit Latrine , 2,745, 1% Flush Toilet, 4,767, 2% Traditional Pit Latrine, 181,572, 96% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Lighting Pressure Lamp, 5,722, 3.0% Gas (Biogas), 564, 0.3% Mains Electricity, 559, 0.3% Solar, 438, 0.2% Firewood, 1,926, 1.0% Candles, 479, 0.3% Hurricane Lamp, 84,477, 44.2% Wick Lamp, 97,011, 50.7% Chart 3.150 Percentage Distribution of Households Owning the Assets 4.2 1.3 1.2 0.8 0.8 57.1 36.5 26.0 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Vehicle Television / Video Landline phone Assets Percent RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 50.7 percent of the total rural households using this source of energy followed by hurricane lamp (44.2%), pressure lamp (3.0%), firewood (1.0%), gas or biogas (0.3%) mains electricity (0.3%), candle (0.3%) and solar (0.2%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 97.1 percent of all rural agricultural households in Ruvuma region. This was followed by charcoal (1.9%). The rest of energy sources accounted for 1.0 percent. These were solar (0.4%), bottled gas (0.2%), crop residues (0.1%), mains electricity (0.1%), solar (0.1%), livestock dung (0.1%), gas/biogas (0.1%), parrafin/kerosene (0.0%) and others (0.0%) (Chart 3.152). 3.13.6 Roofing Materials The most common roofing material for the main dwelling was grass and/or leaves which was used by 69.2 percent of the rural agricultural households. This was followed by iron sheets (33.4%), grass/mud (4.0%), tiles (0.6%), concrete (0.2%) and asbestos (0.0%) (Chart 3.153). Namtumbo district had the highest percentage of households with grass/leaves roofing (34.3%) followed by Mbinga district (31.4%), Songea Urban (16.8%), Tunduru (14.2%) and Songea Rural (3.2%) (Chart 3.154 and Map 3.59). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Ruvuma region was unprotected well (28 percent of households use unprotected wells during the wet season and 29 percent of the households during the dry seasons. This is followed by piped water (27% of households during the wet season and 26 percent during dry season), unprotected spring (18 % of households during the wet season and 19% in the dry season), protected well (15% of households for each season), lake/river (6 % of households in wet season and 8 % in dry season) and protected spring (4% of households in each season) Chart 3.155) Chart 3.152 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 185,686, 97.13% Others, 72, 0.04% Gas (Biogas), 227, 0.12% Parraffin / Kerocine, 77, 0.04% Livestock Dung, 174, 0.09% Solar, 698, 0.37% Mains Electricity, 225, 0.12% Crop Residues, 149, 0.08% Bottled Gas, 312, 0.16% Charcoal, 3,555, 1.86% Chart 3.153 Percentage Distribution of Households by Type of Roofing Material Tiles 0.6% Grass & Mud 4.0% Iron Sheets 33.4% Grass/Leaves 61.7% Concrete 0.2% Asbestos 0.0% Chart 3.154 Percentage Distribution of Households with Grassy/Leafy Roofs by District 34.3 31.4 16.8 14.2 3.2 0.0 25.0 50.0 Namtumbo Mbinga Songea Urban Tunduru Songea Rural D is t ric t Chart 3.155 Percent of Households by Main Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Upro tected Well P iped Water Unpro tected Spring P ro tected Well Lake/River P ro tected Spring Other Main source Percent of Households Wet Season Dry Season Songea Urban Songea Rural 82 379 524 69 1,036 1.2% 1.2% 0.7% 0.2% 2.2% Mbinga Namtumbo Tunduru Songea Urban Songea Rural 601 1,294 910 933 298 8.7% 4.2% 1.2% 3.2% 0.6% Mbinga Namtumbo Tunduru Number and Percent of Households Practicing Fish Farming by District MAP 3.59 RUVUMA Number of Households Without Toilets MAP 3.60 RUVUMA Number and Percent of Households Leaving Without Toilets by District Number Households Practicing Fish Farming 1,200 to 1,500 900 to 1,200 600 to 900 300 to 600 0 to 300 1,000 to 1,250 750 to 1,000 500 to 750 250 to 500 0 to 250 Tanzania Agriculture Sample Census Number of Households Leaving Without Toilets Percent of Number of Households Leaving Without Toilets Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming RESULTS 88 Songea Urban Songea Rural Mbinga 27 76 69 0 0.2 0.4 0 0.2 0 Namtumbo Tunduru Songea Urban Namtumbo Songea Rural 9,358 906 302 1,661 2,814 19.1 20.9 33.4 21.1 Mbinga Tunduru Number and Percent of Households Infected with Ticks by District MAP 3.55 RUVUMA Number and Percent of Households Using Draft Animals- MAP 3.56 RUVUMA Number and Percent of Households Using Draft Animals by District Number of Households Infected with Ticks Number of Households Infected with Ticks Percent of Households Infected with Ticks Number of Households Using Draft Animals Percent of Households Using Draft Animals 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Tanzania Agriculture Sample Census RESULTS 89 RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 90 About 88 percent of the rural agricultural households in Ruvuma region obtained drinking water within a distance of less than one kilometer during wet season compared to 86 percent of the households during the dry season. However, 12 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 16 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.156). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Ruvuma region normally have 3 meals per day (64.5 percent of the households in the region). This is followed by 2 meals per day (33.4 percent) and 1 meal per day (1.9 percent). Only 0.2 percent of the households have 4 meals per day (Chart 3.157). Songea Urban district had the largest percent of households eating one meal per day whilst Tunduru had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.60). 3.13.8.2 Meat Consumption Frequencies The number of agricultural households that consumed meat during the week preceding the census was 125,147 (65% of the agricultural households in Ruvuma region) with 52,566 households (42 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (32%). Very few households had meat three or more times during the respective week. About 35 percent of the agricultural households in Ruvuma region did not eat meat during the week preceding the census (Chart 3.159 and Map 3.61). Table 3.18 Number of Households by Number of Meals the Household Normally Takes per Day and District Number of Meals per Day District One % Two % Three % Four % Total Tunduru 318 0.7 7537 16.1 39043 83.3 0 0.0 46898 Songea Rural 0 0.0 12028 39.1 18668 60.7 76 0.2 30772 Mbinga 2,325 3.0 35,417 45.7 39,440 50.9 265 0.3 77,447 Songea Urban 409 5.9 1992 28.7 4542 65.4 0 0.0 6943 Namtumbo 553 1.9 6895 23.7 21598 74.2 69 0.2 29115 Total 3,605 1.9 63,869 33.4 123,291 64.5 409 0.2 191,175 Chart 3.157 Number of Agriculural Households by Number of Meals per Day One, 3,605, 2% Four, 409, 0% Two, 63,869, 33% Three, 123,291, 65% Chart 3.156 Percentof Households by Distance to Main Source of Water and Season 0 10 20 30 40 < 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance P er ce nt wet season Dry season RESULTS _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 159,245 (83% of the total agricultural households in Ruvuma region) with 43,373 households (27 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (25%). In general, the percentage of households that consumed fish twice or more during the week in Ruvuma region was 115,872 (72.8% of the agricultural households that ate fish in the region during the respective period). About 16.7 percent of the agricultural households in Ruvuma region did not eat fish during the week preceding the census (Chart 3.158 and Map 3.62). 3.13.9 Food Security In Ruvuma region, 48,168 households (25% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirements. However 12,550 (6.6%) said they sometimes experienced problems, 2.5 often experienced problems and 3.2 percent always had problems in satisfying the household food requirements. About 63 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.63). 3.13.10 Main Sources of Cash Income The main cash income of the households in Ruvuma region was from selling food crops (49.5 percent of smallholder households), followed by selling of cash crops (26%), other casual cash earnings (8%), business income (4%), wages and salaries (4%), fishing (3%), and remittance (3%). Only 1% of smallholder households reported the sale of livestock as their main source of income, followed by other (1%), forest products (1%) and livestock products (0%) (Chart3.159). Chart 3.158 Number of Households by Frequency of Meat and Fish Cosumption 0 15,000 30,000 45,000 60,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Chart 3.159: Percentage Distribution of the Number of Households by Main Source of Income Cash Crops, 26.2 Food Crops, 49.5 Other Casual Cash Earnings, 7.6 Business Income, 4.1 Wages & Salaries, 3.6 Livestock, 1.3 Livestock Products, 0.3 Forest Products, 0.8 Remittance, 2.6 Fishing, 2.7 Other, 1.2 Namtumbo Songea Urban Mbinga Songea Rural 21,598 39,043 4,542 39,440 18,668 74.2% 83.3% 65.4% 60.7% 50.9% Tunduru Songea Urban Songea Rural 55 3,099 2,501 419 1,492 10.1% 0.8% 3.2% 1.4% 3.2% Mbinga Namtumbo Tunduru 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Number and Percent of Households Using Grass/Mud for Roofing Material by District MAP 3.61 RUVUMA MAP 3.62 RUVUMA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Tanzania Agriculture Sample Census Number of Households Using Grass/Mud for Roofing Material Number of Households Using Grass/Mud for Roofing Material Number of Households Eating 3 Meals per Day Percent of Households Using Grass/Mud for Roofing Material Percent of Households Eating 3 Meals per Day 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 92 Namtumbo Songea Urban Mbinga Songea Rural 8,553 27,777 1,720 10,566 23,020 29.4% 35.9% 24.8% 34.3% 49.1% Tunduru Number and percent of Households Reporting food insufficiency by District MAP 3.65 RUVUMA Tanzania Agriculture Sample Census Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Ruvuma region RESULTS 93 DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 RUVUMA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Ruvuma Region Profile Ruvuma had a land area of 575,000 hectares under crop production. Although it had a moderate number of crop farming households compared to other regions, it had one of the lowest number of crop growing households per square kilometre. The available land area per household is 4.1 hectares. Of the total available land in the region, it had one of the lowest land utilisation percentages in Tanzania and this is reflected by the lowest number of households responding to insufficient land. Ruvuma has no short rainy season. Compared to other regions, the average planted area of annual crops per household was above average. Cereal production in the region was moderate and it was mostly maize and paddy production with one of the smallest areas of sorghum in the country. Cassava was an important crop in the region and the planted area of tobacco was the second largest in the country. Beans and groundnuts were produced in moderate to low quantities, however the region was important for vegetables production. Ruvuma was the second most important region for the production of cashew nuts, fourth for coffee and fifth for oranges. sugar cane and pigeon peas were also grown in the region. The region had a small but moderate level of irrigation compared to other regions. There was a slight change in the number of households using irrigation for a period of 10 years. The main source of water for irrigation was rivers and the method of obtaining irrigation water was mostly by buckets/watering cans, closely followed by gravity. Buckets/watering cans were also the most common methods of applying irrigation water. Practically all land was cultivated by hand. Almost 50 percent of the planted area in Ruvuma was applied with fertilisers and it had the highest percent of inorganic fertilisers application in the country. It had a low to moderate application of pesticides compared to other regions in the country. Most storage was in sacks/open drums and this was closely followed by locally made traditional structures. The region has the highest percent of households selling crops in the country. Most processing is done by neighbours machine and very little of the processed crops is sold. The number of households receiving extension is moderate to low. The predominant implement used in the region was the hand hoe, however it had the highest percent of hand powered sprayers and the second highest percent of threshers/shellers. Ruvuma was the fourth region with largest number of planted trees mostly eucalyptus. The number of households with erosion control/water harvesting structures was low, however it had a moderate number of terraces compared to other regions. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 4.2 District Profiles Thee following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Tunduru Tundura district had the second largest number of households in the region as the highest percent of households in the district that are involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock. It had very few livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Tunduru district is annual crop farming, followed by permanent crop farming, then off farm income. The district has the highest percent of households without off-farm activities and lowest percent households with more than one member with off-farm income. Compared to other districts in the region, Tunduru had one of the lowest percent of female headed households (13%) and it had one of the lowest average ages of the household head. With an average household size of 4.7 members per household it was average for the region. Tunduru has a comparatively low literacy rate among smallholder households and this is reflected by the high percent of household members that have not attended school. The literacy rates for the heads of household was also lowest in the region. The district has the largest utilized land area per household (3.2 ha) and it has the highest percent of allocated land that is utilized (82%) in the region, indicating a higher level of land pressure. The total planted area is second largest than in other districts in the region. Compared to other districts in the region, Tunduru had a moderate production of maize with a planted area of 27,246 hectares, however the planted area per household is the lowest in the region. Tunduru is very important for rice production compared to other districts in the region with planted area of 19,760 hectares it is almost three times more than the other districts in the region. It has also the largest planted area per household compared to other districts in the region. A small amount of sorghum was grown in the Ruvuma region and most of this was grown in Tundudu district (1,845 ha). Cassava production is important in the region accounting for 26 percent of the area planted in the region. The largest planted area with groundnuts was in Tunduru (9.561 ha) and it also had the largest planted area per household. Other oilseed crops were not important in the district. Tomatoes, onions, cabbage and pumpkin were grown in the district, however tomatoes were the most important. A traditional cash crop (e.g. tobacco or cotton) were not important in the district.. Compared to other districts in the region, Tunduri has the highest planted area with permanent crops (79,226), which is dominated by Cashewnuts (71,527 ha). Pigeon peas are also important with a planted area of 4,758 hectares and is highest in the region. Other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The use of inputs in the district is small. The district has one of the lowest planted areas with fertilizers however, of the small area with fertilizer most was with inorganic fertilizer. Compared to other districts in the region, Tunduru district has the smallest level of insecticide use, however it had the highest herbicide use and the second highest fungicide use in the DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 96 region. The district had a moderate to high planted area under irrigation compared to other districts with around 2,100ha of irrigated land. The most common source of water for irrigation is from rivers using hand bucket. Bucket/watering can is the most common means of application. The most common method of crop storage is in locally made traditional cribs. Tundura had stored the smallest proportion of its crop. Tunduru has the highest percent of households processing on farm by hand and it sold practically none of its processed products. Although very small, access to credit in the district is mainly to men and the main sources are from Co-operative and saving and credit societies. Tundura had one of the lowest percent of households receiving extension and all of this is from the government. Tree farming in Tunduru was not reported and erosion control/water harvesting facilities were not common. Tunduru district has a small number of cattle (4,040 head)e in the region and they are all indigenous. Goat production is the second smallest compared to other districts, however it has the second largest population of sheep in the region. It has the smallest number of pigs in the region and the second smallest number of chickens. The district has the no layers, but a small number of broilers. It has the largest number of ducks in the region and small numbers of rabbits and donkeys are kept. The highest percent of households reporting tsetse fly problems was in Tunduru district while the percent of households reporting tick problems in the district was the smallest. It had the fourth largest percent of households de- worming livestock. The use of draft animals in the district was almost absent, Tunduru had the least number of households practicing fish farming. It has the one of the best access to primary schools and and primary markets compared to other districts. However, it has the worst access to Secondary schools, tarmac roads, feeder roads and regional capital. Tunduru district has the highest percent of households with no toilet facilities and it the second highest percent of households owning a radio. The most common form of energy for lighting is the wick lamp followed by hurricane lamp. A small number of farmers use mains electricity and practically all households use firewood for cooking. The district has the second smallest percent of households with grass roofs. The most common source of drinking water is from unprotected wells. It has the highest percent of households having three meals per day compared to other districts and one of the lowest percent with two meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2 Songea Rural Songea Rural district had the second smallest number of households in the region and the third highest percentage of households in the district that were involved in smallholder agriculture compared to other districts in the region. Most smallholders were involved in crop farming only, followed crop and livestock. It has no livestock only households or pastoralists. The most important livelihood activity for smallholder households Songea Rural district is annual crop farming, followed by permanent crop farming and off farm income. It had the lowest percent of households with no off-farm activities and it had the highest percent of households with more than two members with off-farm income. Compared to other districts in DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 the region, Songea Rural had the highest percent of female headed households (18%) and it had one of the highest average ages of the household head in the region. With an average household size of 4.6 members per household it was almost average for the region. It has a moderate utilized land area per household (1.9 ha) and only 69 percent of the allocated area is currently being utilized. The district has the third largest planted area in the region. The district is moderately important for maize production in the region with a planted area of 28,503 hectares, however the planted area per household is high for the region. Paddy production is low to moderate with a planted area of 6,187 hectares. Finger millet is grown in moderate amounts (2,941 ha) and cereals are not important in the district. Songea Rural had a planted area of 11,465 hectares under cassava (second lowest in the region) and the production of sweet potatoes was small. The district had a small planted area of groundnuts. The district is one of the least important for vegetable production and the most important are tomatoes, cabbage and onions. Compared to other districts in the region, Songea Rural has a small to moderate area with permanent crops of with 5,655 hectares. This is dominated by bananas (1,622 ha) and a small area of pigeon peas (582 ha). Other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The use of inputs in the district is moderate. The district has a moderate planted area with fertilisers (Farm yard manure, compost and inorganic fertilizer and most of this is inorganic fertiliser. Compared to other districts in the region, Songea Rural district has one of the highest levels of insecticide use. It has the smallest use of herbicides in the region and one of the smallest uses of fungicides. It has the smallest area with irrigation compared to other districts with 3,377 ha of irrigated land. Although the district has the second largest number of cattle in the region it only has a small number and they are mostly indigenous with some dairy. Goat and sheep production is moderate compared to other districts in the region. It has a small number of pigs and a moderate number of chickens. Some ducks, rabbits and turkeys are also found in the district, however donkeys are absent. A percent of households reporting tick problems in Songea Rural district is second highest compared to other districts in the region and it had moderate percent of households reporting tsetse problems. It had the second highest percent of households de-worming livestock. The district has a small number of households using draft animals. It has the largest number of households practicing fish farming. It has one of the worst access to secondary schools, hospitals, health clinics and primary and secondary markets, however it has good access to primary schools and feeder roads compared to other districts. The percentages of households without toilet facility in Songea Rural district is 18.1 percent. It has very few households using mains electricity. The most common source of energy for lighting is the hurricane lamp followed by wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 grass/leaves (55%) and iron sheets (34%). The most common source of drinking water is from protected wells. It has the highest percent of households having two meals per day. The district had the second lowest percent of households that did not eat meat or fish during the week prior to enumeration and it has a low to moderate percent of households that always had problems with food satisfaction. 4.3 Mbinga Mbinga district had the largest number of households in the region and it has the forth largest percent of households in the district involved in smallholder agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by both crop and livestock. It has a small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Mbinga district is annual crop farming, followed by permanent crop farming. The district has the third highest percent of households with no off-farm income activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Mbinga has the third highest percent of female headed households (15%). With an average household size of 4.6 members per household it is around average for the region. Mbinga has the second highest literacy rate among smallholder households and the second lowest number household members that have never attended school in the region. The land area utilized per household (2.9ha) is around the average for the region of 3.0 hectares and 80 percent of the allocated area is currently being utilized which is moderate for the region. The district has the highest planted area in the region, and the second smallest planted area per household. Mbinga is the most important district in the region maize production planted area of 50,346 ha and the planted area per household of 0.74 hectares which is equal to the average for the region (0.8 ha). Paddy production is not important with a planted area of only 3,721 hectares and it is second lowest in the region. Wheat and finger millet were grown in the region. The district had the largest planted area of cassava accounting for 45 percent of the cassava planted area in the region. The district also had the largest planted area of beans (3,648 ha) Groundnut production was not important in the district and a small area of vegetables are grown (tomatoes, cabbage and onions). Mbinga has the second highest area planted with permanent crops (33,295 ha) and this is dominated by coffee (29,312 ha) which is the highest in the region. Bananas were also grown (1,096 ha) and other permanent crops are either not grown or are grown in small quantities. As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the largest number of cattle in the region and they are almost all indigenous apart from a small number of dairy cattle. It has the largest number of goat, sheep, pigs and chickens compared to other districts in the region. It has the second largest number of pigs in the region and the largest number of chickens. The district has the largest number of rabbits and donkeys in the region and second highest number of ducks. The district had the highest percent of households reporting tick problems in the region. Mbinga had the highest percent of households deworming livestock. The use of draft DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 animals in the district is very small. A small number of households practice fish farming, however the district has the third largest number in the region. Compared to other districts, it has a moderate access to infrastructure and services. Mbinga district has a moderate percent of households with no toilet facilities compared to other districts in the region and it has a high number of households owning radios and irons. Very few households use mains electricity in the region. The most common source of energy for lighting is the hurricane lamp followed by wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (52%) with 44 percent of households having iron sheets. The most common source of drinking water is from unprotected springs and wells. Fifty percent of the households in the district reported having three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration; however a large percent of households never had problems with food satisfaction. 4.4 Songea Urban Songea Urban district had the lowest number of households in the region and the third lowest percent of households in the district that were involved in smallholder agriculture compared to other districts in the region. Most smallholders were involved in crop farming only, followed by crop and livestock. It had no livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Songea Urban district is annual crop farming followed off farm income and permanent crop farming. It has the lowest percent of households with no off-farm income activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Songea Urban district has the second highest percent of female headed households in the district (28%). With an average household size of 4.8 members per household it is slightly above average for the region. Songea Urban district has the highest literacy rate among smallholder households in the region and this is reflected by the lowest percent of household members that have never attended schools in the region. It has the smallest utilized land area per household (2 ha) and 78 percent of the allocated land area was utilized. The total planted area was very low compared to other districts in the region and it had the smallest planted area per household. Maize production is the most important crop in the district with a planted area of (4,600 ha,) and a planted area per household of 0.64 ha. However the area planted is the lowest in the region. Paddy production is not important in the district and other cereals were either not grown or were grown in very small quantities. Roots and tubers are not important in the district in the region and beans were grown in moderate to small quantities. Oilseed crops are not important, however vegetables are important in terms of the percent of the area of land in the district with vegetables. Cash crops are not important in the district. Compared to other districts in the region, Songeo Urban district is not important for permanent crops (1,603 ha) with practically all being under bananas (1,307 ha). DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however it has the highest proportion of its planted area with fertilizer application and most of this is with inorganic fertilizer. Compared to other districts in the region, Songea Urban district has the percent of its planted area with insecticide, a comparatively moderate percent with herbicides and a low percent with fungicides. It has one of the smallest areas of irrigation in the region. The most common method of obtaining and applying water is by hand buckets/Bucket Songea Urban has the smallest number of cattle in the region and all of them are dairy. It has the least number of goats and sheep and the second lowest number of pigs in the region. It has also the smallest number of chickens. Small numbers of ducks and rabbits are also found in the district. A small percent of households reported Tsetse and tick problems and it had the lowest percent of households de-worming livestock. The use of draft animals in the district is very small. Very small number of households practice fish farming in the district. It has the best access to infrastructure and services in the region. Songea Urban district has the smallest percent of households with no toilet facilities in the region. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp followed by hurricane lamp and most households use firewood for cooking, however it had the highest percent using charcoal. The district has the highest percent of households with using iron sheet roofing (45%) with 55 percent of households using grass. The most common source of drinking water is unprotected well. Three meals per day is the most common and it has the third highest percent of households that did not eat meat during the week prior to enumeration. However most households never or seldom have problems with food satisfaction. 4.5 Namtumbo Namtumbo district has the third highest number of households in the region and it has the forth highest percent of households in the district involved in agriculture compared to other districts in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a relatively small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Namtumbo district is Annual Crop Farming followed by Permanent Crop Farming, Livestock Keeping/Herding and Off-Farm Income. The district has the second highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Namtumbo has the lowest percent of female headed households (9%). With an average household size of 5.3 members per household it is higher than the regional average of 4.7 members. Namtumbo has the second lowest literacy rate among smallholder households in the region. It has the second highest utilized land area per household (3.2 ha) which is the same as the regional average. Around 95 percent of the allocated land is utilized. The district only has one season. DISTRICT PROFILES _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 The district has the second largest planted area of maize compared to other districts in the region (28,809ha) and the planted area per household is among the highest in the region. Paddy production is moderately important with a planted area of 7,440 hectares. Finger Millet is also grown in the district with a planted area of 3,497 hectares. Other cereals are grown in minor quantities. Namtumbo has the third largest planted area of Cassava (11,605ha) in the region. Other root and tuber crops were grown in small quantities. The production of beans in the district is moderate to low (4,877 ha) and groundnut production was also low (2,046 ha). Vegetable production is not very important, however tobacco is an important cash crop in the district with a planted area of 5,602 hectares. Compared to other districts in the region, Namtumbo district is not important for permanent crops (5,233 ha) with bananas being the most important (2,704 ha) and is the highest in the region. As with other districts in the region, practically all land clearing and preparation is done by hand. The district has the largest planted area with inorganic fertilizer and one of the smallest planted areas with farm yard manure. Namtumbo has one of the smallest percent of its planted area applied with insecticides and herbicides. The district has the second largest planted area and gravity is the most common means of conveying water and field application by flood was most common. The district has the second smallest number of cattle in the region and they are mostly dairy. It has the second highest number of goats and second lowest number of sheep. It has a the second highest number of chickens. Ducks and rabbits found in the district in small numbers. A moderate number of households reported Tsetse and tick problems in the district. The use of draft animals in the district is small however it has the second d highest number of households practicing fish farming in the region It is amongst the districts with the best access to primary schools and health clinics, however it has one of the worst access to all weather roads, feeder roads, hospitals, secondary markets and tertiary markets. Namtumbo district has the second highest percent of households with no toilet facilities. It has the second largest number of households using mains electricity in the region. The most common source of energy for lighting is the hurricane lamp followed by the wick lamp and practically all households use firewood for cooking. The district has one of the largest percent of households with grass roofs (68%) and only 29 percent of households have iron sheets. The most common source of drinking water is piped water. It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a high percent of households with 3 meals per day. Most households in the district n ever have problems with food satisfaction. APPENDIX II 102 4. APPENDICES APPENDIX I TABULATION LIST.........................................................................................103 APPENDIX II TABLES............................................................................................................121 APPENDIX III QUESTIONNAIRES.......................................................................................271 APPENDIX II 103 TYPE OF AGRICULTURE HOUSEHOLD ...............................................................................121 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year ..........................................................................................................122 2.2 Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year .........................................................................................................122 NUMBER OF AGRICULTURE HOUSEHOLDS..................................................................123 3.0: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year................................................124 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District..................................................................................................124 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES.............................................125 3.1a First Most Importance..................................................................................................126 3.1b Second Most Importance..............................................................................................126 3.1c Third Most Importance ................................................................................................126 3.1d Fourth Most Importance...............................................................................................126 3.1e Fifth Most Importance..................................................................................................127 3.1f Sixth Most Importance.................................................................................................127 HOUSEHOLDS DEMOGRAPHS............................................................................................129 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) ...........................................................................................130 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) .....................................................................................130 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year .........................................................................................................131 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year .......131 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District , 2002/03 Agricultural Year......................................................................131 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year .........................................................................................................131 APPENDIX II 104 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year.......................................................132 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year...................................................133 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.......................................134 3.11 Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year.......134 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year........................................................134 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District...........134 3.14 Time Series of Male and Female Headed Households ................................................135 3.15 Literacy Rate of Heads of Households by Sex and District.........................................135 LAND ACCESS/OWNERSHIP................................................................................................137 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year .....................................................................................138 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year .........................................................................................................138 LAND USE..................................................................................................................................139 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year .........................................................................................................140 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year .........................................................................................................140 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year ..................................141 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year..............141 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year.......141 APPENDIX II 105 TOTAL ANNUAL CROP & VEGES PRODUCTION WET & DRY SEASONS ...............143 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District. .........................................................................................144 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District.........144 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Ruvuma Region .............................................................................145 7.1 & 7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Ruvuma Region .............................................146 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Ruvuma.................................................147 7.1 & 7.2gTotal Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year ...............................................147 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................147 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................148 7.1 & 7.2j Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. .................................148 7.1 & 7.2k Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season............................148 ANNUAL CROP & VEGES PRODUCTION DRY SEASON...............................................151 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - DRY SEASON, Ruvuma Region.................................................................................152 7.1b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - DRY SEASON, Ruvuma Region.........................152 7.1c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Dry Season, 2002/03 Agriculture Year, Ruvuma Region.................................152 7.1d ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Dry Season. .........................................................................................................................153 7.1e ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Dry Season. .........................................................................................................................153 APPENDIX II 106 7.1f ANNUAL CROP & VEGE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season .........................................................................................................................154. 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - DRY SEASON ..............................................................154 ANNUAL CROP & VEGES PRODUCTION WET SEASON ..............................................155 7.2a Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, Ruvuma Region. ................................................................156 7.2b Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, Ruvuma Region............156 7.2c Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, Ruvuma Region ...................156 7.2d Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season..............................................157 7.2e Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season..............................................157 7.2f Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET SEASON........................................158 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON .................................................158 7.2h: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops; 2002/03 Agriculture Year ................................159 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year...........................160 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 APPENDIX II 107 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................161 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year...........................162 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year...........................163 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year...........................164 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year............................................164 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year...........................165 APPENDIX II 108 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year...........................166 PERMANENT CROPS..............................................................................................................167 7.3.1 Production of Permanent Crops by Crop Type and District – Ruvuma Region ..........168 7.3.2 Area Planted by Crop Type - Ruvuma Region ............................................................171 7.3.3 Area Planted with Cashewnut by District ....................................................................171 7.3.4 Area planted with Coffee by District ...........................................................................173 7.3.5 Area planted with Banana by District ..........................................................................173 7.3.6 Area Planted with Pigeon by District...........................................................................173 7.3.7 Planted Area with Fertilizer by Fertilizer Type and Crop............................................174 AGROPROCESSING................................................................................................................177 8.1.1a: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year ..............................................................................178 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year .........................................................................................................178 8.1.1c Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Ruvuma Region.......................................................................178 8.1.1d Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Ruvuma Region..........................................................................................................................179 8.1.1e Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Ruvuma Region............................................................................................................179 8.1.1f Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Ruvuma Region ..............................................................................180 APPENDIX II 109 8.1.1g Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Ruvuma Region .......................................180 8.1.1h Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Ruvuma Region ................................................................180 8.1.1i Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Ruvuma Region ................................................................180 MARKETING ............................................................................................................................181 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Ruvuma Region ..............................................................182 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Ruvuma Region .....................................182 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Ruvuma Region.......................................182 IRRIGATION/EROSION CONTROL ....................................................................................183 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District ........................................................................................184 11.2 Area (ha) of Irriga and NON irrigated land by district during 2002/03 agriculture year.. 11.3: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year ............................................................184 11.4: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year ...........................................................................................184 11.5 Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year .................................................185 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District....................................................................................................................185 11.7 Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year ...........................................................................................185 ACCESS TO FARM INPUTS...................................................................................................187 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year .........................................................................................................188 12.1.2 Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year ...........................................................................................188 APPENDIX II 110 12.1.3 Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year ...........................................................................................188 12.1.4 Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year ...........................................................................................189 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year .........................................................................................................189 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year ...........................................................................................189 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year ...........................................................................................190 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ...........................................................................................190 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year ...........................................................................................191 12.1.10 Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year .............................................................................191 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year .........................................................................................................192 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year .........................................................................................................193 cont.Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................193 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................193 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ........................................................................194 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year...........................................................194 12.1.16 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .............................................................................194 12.1.17a Number of Agricultural Households and Distance to Source of Insecticide /Fungicides by District, 2002/03 Agricultural Year.....................................................195 12.1.17b Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year .............................................................................195 APPENDIX II 111 12.1.18 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................196 12.1.19 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year...........................................................196 12.1.20 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................196 12.1.21 Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year..................................197 12.1.22 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year ........................................................................197 12.1.23 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ..............................................................197 12.1.24 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year ........................................................................198 12.1.25 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ...........................................................................................198 12.1.26 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year ........................................................................198 12.1.27 Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year ........................................................................199 12.1.28 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year ...........................................................................................199 12.1.29 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year ...........................................................................................199 12.1.30 Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year.......................................................200 12.1.31 Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year......................................................200 12.1.32 Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ........................................................................200 12.1.33 Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year...............................................................200 12.1.34 Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year .............................................................................201 APPENDIX II 112 AGRICULTURE CREDIT........................................................................................................203 13.1a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year ............................................................204 13.1b Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year ............................................................................................204 13.2a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year ........................................................205 13.2b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year ............................................................................................205 TREE FARMING AND AGROFORESTRY ..........................................................................207 14.1 Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................208 Cont Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region..................................................................................................208 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Ruvuma Region..................................................................................................209 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region ................................................................................209 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Ruvuma Region.......210 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region ................................................................................210 CROP EXTENSION ..................................................................................................................211 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Ruvuma Region .................................212 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Ruvuma Region ...............................................................212 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region...........................212 APPENDIX II 113 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................213 15.5 Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................213 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................213 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................214 15.10 Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................215 15.11 Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................215 15.12 Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................215 15.13 Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region............................................................................................................216 15.14 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................216 15.15 Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................216 APPENDIX II 114 15.16 Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.17 Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................217 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................218 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Ruvuma Region ..............................................................................219 ANIMAL CONTRIBUTION TO CROP PRODUCTION .....................................................221 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Ruvuma Region.....................................222 17.2 Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region ....................................222 cont… Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region...................222 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Ruvuma Region ..................................................................222 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Ruvuma Region ................................................................................223 CATTLE PRODUCTION .........................................................................................................225 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Ruvuma Region............................................................................................................226 18.2 Number of Cattle By Type and District as of 1st October, 2003 .................................226 APPENDIX II 115 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 ........................................................226 18.4 Number of Cattle by Category and Type of Cattle; on 1st October 2003....................267 18.5 Number of Indigenous Cattle By Category and District as on 1st October, 2003 .......227 18.6 Number of Improved Beef Cattle By Category and District as on 1st October, 2003.227 18.7 Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 .........................................................................................................228 18.8 Number of Cattle By Category and District as on 1st October, 2003..........................228 GOATS PRODUCTION............................................................................................................229 19.1 Total Number of Goats by Type and District as on 1st October, 2003........................230 19.2 Number of Households Rearing Goats by Herd Size on 1st October, 2003 ................230 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District..........................................................................................................................231 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 .........................................................................................................231 19.5 Number of Improved Goat for Meat by Category and District as on 1st October, 2003 .........................................................................................................231 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 ......232 19.7 Total Number of Goats by Category and District on 1st October, 2003.....................232 SHEEP PRODUCTION.............................................................................................................233 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03..................234 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 ........234 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Ruvuma Region............................................................................................................235 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 ..........................................................................................................235 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ..........................................................................................................235 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003..................235 APPENDIX II 116 PIGS PRODUCTION ................................................................................................................137 21.1 Number of Households and Pigs by Herd Size on 1st October 2003...........................138 21.2 Number of Households and Pigs by District on 1st October 2003 ..............................138 21.3 Number of Pigs by Type and District on 1st October, 2003........................................138 LIVESTOCK PESTS AND PARASITE CONTROL .............................................................139 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. .......................................240 22.4 Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year ............................................................240 22.5 Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District ...........................241 22.6 Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year ..............................................241 OTHER LIVESTOCK...............................................................................................................243 23a Total Number of Other Livestock by Type on 1st October 2003 ................................244 23b Number of Chicken by Category of Chicken and District on 1st October 2003..........244 23c Head Number of Other Livestock by Type of Livestock and District .........................244 23d Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 ..........................................................................................................244 23e LIVESTOCK/POULTRY POPULATION TREND .............................................................244 FISH FARMING ........................................................................................................................245 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year ...........................................................................................246 28.2 Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year..........................................................................246 28.3 Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year..........................................................................246 28.4 Number of Agricultural Households By Location of Selling Fish and District during the 2002/03 Agricultural Year..........................................................................246 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year....246 APPENDIX II 117 LIVESTOCK EXTENSION......................................................................................................247 29.1a Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year ...........................................................................................248 29.1b Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year..........................................................................248 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year.....................................................250 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year........................................251 29.7 Number of Agricultural Households Receiving Extension Advice on Herd / Flock Size and Selection By Source and District, 2002/03 Agricultural Year ............251 29.8 Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year.......252 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year .....252 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year .......................................253 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year.......................253 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year ...........................................................................................254 ACCESS TO INFRASRUCTURE AND OTHER SERVICES..............................................255 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts ...................................................................................................................256 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year ............................................................................................................257 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year ............................................................................................................257 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year ............................................................................................................257 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year ............................................................................................................258 APPENDIX II 118 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year ...........................................................................................................258 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year ...........................................................................................................258 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year ............................................................................................................259 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year ............................................................................................................259 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year ...........................................................................................................259 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year ...........................................................................................................260 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................261 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year .............................................................................261 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year .............................................................................261 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ..............................................................262 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ...........................................................262 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year .....................................262 HOUSEHOLD FACILITIES ....................................................................................................263 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year.......................................................................................264 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year ........................................................264 APPENDIX II 119 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ...........................................................................................264 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year................................................................................265 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year................................................................................265 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year .........................266 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ....................266 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year..................267 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year ............................................................................................................267 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District..............................................................................................268 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ........................................................................268 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District ........................................................................269 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District .......................................................269 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year .....................................................................................270 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year ............................................................................................270 APPENDIX II 120 APPENDIX II: CROPS Type of Agriculture Household.................................................................................................................. 121 Number of Agriculture Households ............................................................................................................123 Rank of Importance of Livelihood Activities..............................................................................................125 Households Demography ............................................................................................................................129 Land Access/Ownership..............................................................................................................................137 Land Use………………..............................................................................................................................139 Total Annual Crop and Vege Production Long and short Seasons.............................................................143 Annual Crop and Vege Production Long Rainy Seasons............................................................................155 Permanent Crop Production.........................................................................................................................167 Agro-processing .................................................................................................................................177 Marketing .................................................................................................................................181 Irrigation/Erosion Control ...........................................................................................................................183 Access to Farm Inputs ................................................................................................................................ 187 Agriculture Credit .................................................................................................................................203 Tree Farming and Agro-forestry..................................................................................................................207 Crop Extension .................................................................................................................................211 Animal Contribution to Crop Production ....................................................................................................221 Cattle Production .................................................................................................................................225 Goat Production .................................................................................................................................229 Sheep Production .................................................................................................................................233 Pig Production .................................................................................................................................237 Livestock Pests and Parasite Control...........................................................................................................239 Other Livestock .................................................................................................................................243 Fishing Farming .................................................................................................................................245 Livestock Extension .................................................................................................................................247 Access to Infrastructure and other services .................................................................................................255 Household Facilities....................................................................................................................................263 Appendix II 121 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census-2003 Ruvuma Appendix II 122 Rural households involved in Agriculture % of Total rural households Rural households NOT involved in Agriculture % of Total Rural households Total Rural Households % of Total households Urban Households % of Total households Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Tunduru 46,898 98 1,094 2 47,992 90 5,065 10 53,057 Songea Rural 30,772 99 386 1 31,158 99 356 1 31,514 Mbinga 77,447 98 1,929 2 79,376 94 5,293 6 84,669 Songea Urban 6,943 99 61 1 7,004 23 23,098 77 30,102 Namtumbo 29,115 99 269 1 29,384 89 3,614 11 32,998 Total 191,175 98 3,739 2 194,914 84 37,426 16 232,340 Number of households % Number of households % Number of households % Number of households % Tunduru 41,622 29 0 0 5,276 11 46,898 25 46,898 46,898 5,276 Songea Rural 22,195 16 0 0 8,578 17 30,772 16 30,772 30,772 8,578 Mbinga 52,111 37 132 100 25,204 77,447 41 77,447 77,315 25,335 Songea Urban 5,144 4 0 0 1,799 4 6,943 4 6,943 6,943 1,799 Namtumbo 20,548 15 0 0 8,567 17 29,115 15 29,115 29,115 8,567 Total 141,619 100 132 100 49,424 100 191,175 100 191,175 191,043 49,556 Total Number of Households Rearing Livestock Crops Only Livestock Only 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Crops & Livestock Total District Agriculture, Non Agriculture and Urban Households 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District during 2002/03 Agricultural Year District Type of Agriculture Household Total Number of Agriculture Households Total Number of Households Growing Crops Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 123 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 124 Number % Average Household Size Number % Average Household Size Number % Tunduru 40,976 87 5 5,922 13 4 46,898 100 5 Songea Rural 25,232 82 5 5,540 18 4 30,772 100 5 Mbinga 65,745 85 5 11,701 15 4 77,447 100 4 Songea Urban 5,852 84 5 1,090 16 4 6,943 100 5 Namtumbo 26,542 91 5 2,573 9 4 29,115 100 5 Total 164,347 86 5 26,827 14 4 191,175 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 1 2 4 3 5 6 7 Songea Rural 1 2 4 3 5 6 7 Mbinga 1 2 3 4 5 6 7 Songea Urban 1 3 4 2 5 6 7 Namtumbo 1 2 3 4 5 6 7 Total 1 2 4 3 5 6 7 Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of District Livelihood Activity 3.0: HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of District Male Female Total Average Household Size Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 125 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 126 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 25,225 15,535 318 4,772 522 98 421 Songea Rural 23,860 680 530 4,485 841 227 303 Mbinga 26,035 33,408 2,303 8,352 2,473 4,993 0 Songea Urban 3,573 431 245 2,446 220 0 82 Namtumbo 26,033 1,360 0 1,146 286 142 434 Total 104,726 51,415 3,396 21,201 4,341 5,460 1,241 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 17,901 21,111 1,028 4,335 422 107 2,317 Songea Rural 5,850 7,005 5,692 9,945 758 380 1,672 Mbinga 32,750 17,986 12,877 10,934 1,926 875 1,017 Songea Urban 2,554 2,372 628 1,120 134 0 241 Namtumbo 2,432 12,389 4,466 6,613 861 145 2,281 Total 61,487 60,862 24,691 32,948 4,101 1,507 7,528 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 2,932 4,029 5,919 9,302 1,220 960 21,581 Songea Rural 835 8,345 8,443 4,261 1,127 380 7,229 Mbinga 11,287 10,217 27,135 14,607 2,577 1,270 5,915 Songea Urban 569 2,458 1,445 1,034 189 27 1,004 Namtumbo 361 5,675 8,289 4,453 1,290 360 7,326 Total 15,983 30,724 51,231 33,657 6,404 2,997 43,055 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 2,059 5,138 3,337 2,071 213 16,809 Songea Rural 152 6,385 6,469 2,356 1,287 303 11,619 Mbinga 3,372 6,082 16,348 12,283 2,860 2,323 11,656 Songea Urban 136 706 2,071 870 439 54 1,990 Namtumbo 218 3,162 4,509 4,163 720 429 10,947 Total 3,877 18,394 34,536 23,009 7,377 3,322 53,021 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 127 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 1,026 2,595 1,024 1,233 318 3,789 Songea Rural 0 4,872 2,591 1,682 534 0 6,915 Mbinga 2,063 1,396 3,726 4,286 3,120 645 11,879 Songea Urban 82 190 573 191 220 137 2,530 Namtumbo 73 1,648 2,443 1,144 217 214 6,905 Total 2,218 9,132 11,927 8,328 5,324 1,314 32,018 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tunduru 0 0 320 0 107 0 318 Songea Rural 0 306 229 154 0 76 382 Mbinga 248 381 380 521 785 132 2,326 Songea Urban 0 0 54 27 0 0 218 Namtumbo 0 0 71 73 0 0 290 Total 248 687 1,053 775 892 208 3,535 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES:Sixth Most Importance Tanzania Agriculture Sample Census - 2003 Ruvuma 128 Appendix II 129 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 130 Number % Number % Number % Less than 4 62,317 49 64,189 51 126,506 100 05 - 09 63,411 50 63,734 50 127,146 100 10 - 14 65,022 51 63,131 49 128,153 100 15 - 19 47,274 50 47,037 50 94,311 100 20 - 24 33,005 44 42,356 56 75,361 100 25 - 29 29,388 45 35,733 55 65,121 100 30 - 34 28,779 48 31,479 52 60,259 100 35 - 39 23,264 48 25,396 52 48,660 100 40 - 44 20,803 53 18,285 47 39,087 100 45 - 49 14,503 51 14,002 49 28,504 100 50 - 54 11,783 47 13,401 53 25,184 100 55 - 59 9,615 51 9,352 49 18,968 100 60 - 64 8,432 51 8,191 49 16,624 100 65 - 69 7,675 52 7,201 48 14,876 100 70 - 74 6,752 59 4,701 41 11,453 100 75 - 79 3,187 63 1,865 37 5,052 100 80 - 84 2,365 66 1,241 34 3,606 100 Above 85 1,221 44 1,571 56 2,792 100 Total 438,796 49 452,866 51 891,662 100 Number % Number % Number % Less than 4 62,317 14 64,189 14 126,506 14 05 - 09 63,411 14 63,734 14 127,146 14 10 - 14 65,022 15 63,131 14 128,153 14 15 - 19 47,274 11 47,037 10 94,311 11 20 - 24 33,005 8 42,356 9 75,361 8 25 - 29 29,388 7 35,733 8 65,121 7 30 - 34 28,779 7 31,479 7 60,259 7 35 - 39 23,264 5 25,396 6 48,660 5 40 - 44 20,803 5 18,285 4 39,087 4 45 - 49 14,503 3 14,002 3 28,504 3 50 - 54 11,783 3 13,401 3 25,184 3 55 - 59 9,615 2 9,352 2 18,968 2 60 - 64 8,432 2 8,191 2 16,624 2 65 - 69 7,675 2 7,201 2 14,876 2 70 - 74 6,752 2 4,701 1 11,453 1 75 - 79 3,187 1 1,865 0 5,052 1 80 - 84 2,365 1 1,241 0 3,606 0 Above 85 1,221 0 1,571 0 2,792 0 Total 438,796 100 452,866 100 891,662 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 131 Number % Number % Number % Tunduru 107,710 49 110,626 51 218,336 100 Songea Rural 71,487 50 70,183 50 141,670 100 Mbinga 167,019 49 176,141 51 343,160 100 Songea Urban 16,819 50 16,549 50 33,368 100 Namtumbo 75,761 49 79,367 51 155,128 100 Total 438,796 49 452,866 51 891,662 100 Number % Number % Number % Number % Number % Tunduru 119,349 63.3 1,460 0.8 105 0.1 67,557 35.8 188,472 100 Songea Rural 90,934 74.5 4,435 3.6 77 0.1 26,688 21.9 122,134 100 Mbinga 217,425 73.7 18,116 6.1 0 0.0 59,370 20.1 294,911 100 Songea Urban 23,106 78.7 1,337 4.6 0 0.0 4,904 16.7 29,347 100 Namtumbo 92,540 71.0 4,902 3.8 145 0.1 32,706 25.1 130,292 100 Total 543,354 71.0 30,250 4.0 327 0.0 191,226 25.0 765,156 100 Number % Number % Number % Number % Tunduru 48,507 26 79,091 42 60,873 32 188,472 100 Songea Rural 37,861 31 65,226 53 19,047 16 122,134 100 Mbinga 90,889 31 160,895 55 43,127 15 294,911 100 Songea Urban 10,688 36 15,502 53 3,157 11 29,347 100 Namtumbo 39,758 31 64,470 49 26,065 20 130,292 100 Total 227,703 30 385,184 50 152,269 20 765,156 100 Number % Number % Number % Number % Number % Tunduru 111,709 59 0 0 0 0 0 0 1,215 1 Songea Rural 68,463 56 1,213 1 0 0 0 0 905 1 Mbinga 167,881 57 1,343 0 259 0 3,480 1 2,624 1 Songea Urban 13,452 46 80 0 0 0 0 0 490 2 Namtumbo 76,107 58 217 0 0 0 69 0 718 1 Total 437,613 57 2,854 0 259 0 3,550 0 5,953 1 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By District School Attendancy Attending School Completed School Total 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members by Main Activity and District, District Main Activity p Farming p g Herding Livestock Pastoralist Fishing Parastatal Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 132 Number % Number % Number % Number % Number % Tunduru 1,237 1 660 0 1,328 1 1,739 1 422 0 Songea Rural 1,367 1 1,218 1 994 1 454 0 304 0 Mbinga 2,713 1 129 0 1,799 1 500 0 626 0 Songea Urban 648 2 627 2 1,027 4 216 1 109 0 Namtumbo 644 0 575 0 72 0 285 0 141 0 Total 6,609 1 3,207 0 5,221 1 3,195 0 1,603 0 Number % Number % Number % Number % Number % Number % Tunduru 315 0 703 0 46,197 25 21,921 12 1,024 1 188,472 100 Songea Rural 228 0 230 0 36,642 30 10,042 8 73 0 122,134 100 Mbinga 388 0 1,543 1 85,860 29 25,248 9 518 0 294,911 100 Songea Urban 27 0 511 2 10,121 34 1,956 7 82 0 29,347 100 Namtumbo 72 0 284 0 37,392 29 13,357 10 358 0 130,292 100 Total 1,031 0 3,270 0 216,213 28 72,523 9 2,055 0 765,156 100 Number % Number % Number % Number % Number % Tunduru 106,478 56 4,442 2 51,740 27 25,812 14 188,472 100 Songea Rural 68,155 56 4,258 3 37,943 31 11,777 10 122,134 100 Mbinga 168,834 57 4,769 2 84,808 29 36,500 12 294,911 100 Songea Urban 13,312 45 2,248 8 11,854 40 1,933 7 29,347 100 Namtumbo 74,736 57 1,646 1 40,593 31 13,316 10 130,292 100 Total 431,515 56 17,363 2 226,938 30 89,339 12 765,156 100 cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Not Working & Available cont… Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Other Total 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 133 Number % Number % Number % Number % Number % Tunduru 106 0 0 0 1,250 2 1,879 2 7,452 9 Songea Rural 306 0 378 1 989 2 2,198 3 12,839 20 Mbinga 503 0 1,011 1 4,146 3 2,606 2 23,293 14 Songea Urban 27 0 55 0 355 2 300 2 2,070 13 Namtumbo 217 0 359 1 648 1 1,078 2 7,831 12 Total 1,159 0 1,803 0 7,388 2 8,061 2 53,485 14 Number % Number % Number % Number % Number % Tunduru 2,008 3 2,583 3 59,324 75 213 0 103 0 Songea Rural 1,130 2 832 1 43,151 66 760 1 669 1 Mbinga 2,050 1 1,670 1 114,611 71 1,580 1 503 0 Songea Urban 82 1 270 2 11,061 71 356 2 107 1 Namtumbo 864 1 1,369 2 48,363 75 355 1 363 1 Total 6,134 2 6,725 2 276,511 72 3,264 1 1,745 0 Pre-Form One Number % Number % Number % Number % Number % Tunduru 0 0 0 0 105 0 105 0 924 1 Songea Rural 0 0 76 0 226 0 0 0 1,211 2 Mbinga 781 0 512 0 1,410 1 386 0 4,360 3 Songea Urban 0 0 55 0 55 0 81 1 408 3 Namtumbo 72 0 215 0 357 1 362 1 1,005 2 Total 853 0 858 0 2,154 1 934 0 7,908 2 Number % Number % Number % Number % Number % Tunduru 0 0 107 0 621 1 2,311 3 79,091 100 Songea Rural 0 0 0 0 77 0 384 1 65,226 100 Mbinga 132 0 237 0 840 1 264 0 160,895 100 Songea Urban 0 0 82 1 27 0 109 1 15,502 100 Namtumbo 0 0 69 0 217 0 724 1 64,470 100 Total 132 0 496 0 1,783 0 3,791 1 385,184 100 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Under Standard One Standard One Standard Two Standard Three Standard Four cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Standard Five Standard Six Standard Seven Standard Eight Training After Primary Education cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Form One Form Two Form Three Form Four cont... HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Education Level Form Five Form Six Training After Secondary Education Adult Education Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 134 Number % Average Household Size Number % Average Household Size Number % Tunduru 40,976 87 5 5,922 13 4 46,898 100 5 Songea Rural 25,232 82 5 5,540 18 4 30,772 100 5 Mbinga 65,745 85 5 11,701 15 4 77,447 100 4 Songea Urban 5,852 84 5 1,090 16 4 6,943 100 5 Namtumbo 26,542 91 5 2,573 9 4 29,115 100 5 Total 164,347 86 5 26,827 14 4 191,175 100 5 Number Percent Number Percent Number Percent Number Percent Tunduru 17,359 67 6,511 25 2,164 8 26,034 100 Songea Rural 13,452 59 7,221 32 2,135 9 22,808 100 Mbinga 30,267 57 18,378 35 4,452 8 53,097 100 Songea Urban 3,209 56 1,742 31 740 13 5,691 100 Namtumbo 9,853 54 6,388 35 2,074 11 18,315 100 Total 74,141 59 40,239 32 11,565 9 125,945 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Tunduru 12,755 31,110 0 729 311 1,993 46,898 Songea Rural 4,024 24,943 519 902 77 307 30,772 Mbinga 8,676 62,636 503 4,638 730 264 77,447 Songea Urban 706 5,666 27 435 27 81 6,943 Namtumbo 4,367 22,873 218 1,151 145 362 29,115 Total 30,529 147,227 1,267 7,854 1,290 3,007 191,175 Mean Median Mode Mean Median Mode Mean Median Mode Tunduru 43 40 30 44 42 45 43.4 40 30 Songea Rural 44 41 30 48 44 40 45.0 42 30 Mbinga 40 37 28 49 49 50 41.2 38 28 Songea Urban 44 42 35 48 48 50 44.9 43 35 Namtumbo 42 39 30 44 41 35 42.6 40 30 Total 42 39 30 47 45 40 42.7 40 30 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Average Househol d Size 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households By Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Number of household members with Off farm income One Two More than Two Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Median, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 135 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Heads 147,966 153,884 159,880 193,242 189,665 164,347 Female Heads 14,109 22,335 22,286 23,024 22,692 26,827 Total 162,075 176,219 182,166 216,266 212,357 191,175 Male headed (Percentage) 91 87 88 89 89 86 Female headed (Percentage) 9 13 12 11 11 14 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Tunduru 31,049 3,103 34,151 9,927 2,820 12,746 40,976 5,922 46,898 Songea Rural 22,267 3,951 26,218 2,965 1,589 4,554 25,232 5,540 30,772 Mbinga 58,988 8,887 67,875 6,758 2,814 9,572 65,745 11,701 77,447 Songea Urban 5,501 709 6,210 352 381 733 5,852 1,090 6,943 Namtumbo 22,666 1,721 24,388 3,876 852 4,728 26,542 2,573 29,115 Total 140,471 18,371 158,841 23,877 8,457 32,333 164,347 26,827 191,175 3.14 Time Series of Male and Female Headed Households 3.15 Literacy Rate of Heads of Households by Sex and District Literacy District Know Don't know Total Tanzania Agriculture Sample Census - 2003 Ruvuma 136 Appendix II 137 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 138 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 1,583 3 43,448 76 6,799 12 793 1 2,881 5 311 1 1,136 2 57,050 Songea Rural 4,028 10 27,214 69 2,719 7 1,208 3 2,350 6 230 1 1,526 4 39,372 Mbinga 2,376 2 68,928 64 14,257 13 7,009 6 8,513 8 384 0 6,341 6 107,903 Songea Urban 567 5 5,751 53 1,498 14 540 5 867 8 409 4 1,178 11 10,898 Namtumbo 217 1 27,171 85 1,289 4 288 1 1,580 5 289 1 1,151 4 32,080 Total 8,770 4 172,512 70 26,563 11 9,839 4 16,190 7 1,624 1 11,332 5 246,926 Area Leased/Certific ate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Tunduru 6,850 180,902 16,512 1,526 3,320 452 1,182 210,743 Songea Rural 12,201 109,889 5,974 1,183 1,704 93 968 132,013 Mbinga 9,375 220,227 28,460 4,495 6,078 129 13,839 282,603 Songea Urban 728 13,191 1,997 381 677 210 835 18,019 Namtumbo 702 140,892 4,088 468 2,629 387 6,726 155,891 Total 29,855 665,101 57,032 8,052 14,408 1,270 23,550 799,269 % 4 83 7 1 2 0 3 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year District Land Access Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Total Number of Households 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 139 LAND USE Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 140 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Rented to Others Households Unusable Households of Uncultivated Usable Land Total Number of Households Tunduru 40,827 9,497 29,504 6,632 29,622 316 8,616 3,748 103 413 735 14,390 144,403 Songea Rural 27,886 10,123 16,167 3,486 11,674 1,520 13,483 10,167 9,887 2,105 2,735 11,780 121,013 Mbinga 66,798 20,913 51,788 33,488 6,657 7,438 31,030 14,906 25,154 5,536 8,787 25,251 297,744 Songea Urban 5,748 3,718 3,019 1,614 2,805 190 355 272 2,865 217 299 3,267 24,368 Namtumbo 27,764 10,419 18,865 3,089 6,077 999 11,350 10,491 2,357 1,663 3,669 17,477 114,220 Total 169,022 54,671 119,342 48,308 56,836 10,463 64,835 39,584 40,366 9,933 16,224 72,165 701,748 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Tunduru 35,322 10,806 60,306 10,426 42,189 299 10,944 10,999 125 357 1,296 27,636 210,704 Songea Rural 38,149 7,409 8,107 1,901 9,735 1,891 15,741 24,025 2,108 2,544 3,344 17,060 132,013 Mbinga 78,902 14,927 40,236 24,198 6,631 5,494 30,558 21,625 6,472 5,002 14,919 33,637 282,603 Songea Urban 5,463 2,458 1,405 595 1,992 145 277 191 1,023 368 173 3,930 18,019 Namtumbo 47,161 10,871 10,431 2,329 5,499 1,399 14,368 22,682 1,264 2,495 4,565 32,827 155,891 Total 204,996 46,471 120,484 39,451 66,045 9,228 71,887 79,522 10,991 10,766 24,297 115,091 799,230 % 26 6 15 5 8 1 9 10 1 1 3 14 100 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Land use area Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year District Type of Land Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 141 Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent Tunduru 22,329 48 24,569 52 46,898 100 Tunduru 39,708 85 7,190 15 46,898 100 Songea Rural 4,790 16 25,982 84 30,772 100 Songea Rural 24,176 79 6,596 21 30,772 100 Mbinga 24,824 32 52,491 68 77,315 100 Mbinga 52,305 68 25,010 32 77,315 100 Songea Urban 3,051 44 3,891 56 6,943 100 Songea Urban 4,482 65 2,461 35 6,943 100 Namtumbo 4,447 15 24,668 85 29,115 100 Namtumbo 23,749 82 5,366 18 29,115 100 Total 59,442 31 131,601 69 191,043 100 Total 144,421 76 46,622 24 191,043 100 Number Percent Number Percent Number Percent Tunduru 9,341 20 37,557 80 46,898 100 Songea Rural 5,306 17 25,466 83 30,772 100 Mbinga 10,647 14 66,668 86 77,315 100 Songea Urban 1,037 15 5,906 85 6,943 100 Namtumbo 2,862 10 26,253 90 29,115 100 Total 29,192 15 161,851 85 191,043 100 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Do any Female Members of the Hh own or have customary right Yes No Total 5.4: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District, 2002/03 Agricultural Year District Do you Consider that you have sufficient land for the Hh? Yes No Total 5.3: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year District Was all Land Available to the Hh Used During 2002/03? Yes No Total Tanzania Agriculture Sample Census - 2003 Ruvuma 142 Appendix II 143 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION WET & DRY SEASONS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 144 Number of household Planted area (hectare) Number of household Planted Area (hectare) Tunduru 0 0 46,589 84,544 84,544 0.00 Songea Rural 0 0 30,696 61,969 61,969 0.00 Mbinga 0 0 73,950 130,386 130,386 0.00 Songea Urban 0 0 6,943 10,920 10,920 0.00 Namtumbo 72 110 28,970 70,275 70,385 0.16 Total 72 110 187,149 358,093 358,203 0.03 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Tunduru 0 46,589 46,589 0 46,589 Songea Rural 0 30,696 30,696 0 30,696 Mbinga 0 73,950 73,950 0 73,950 Songea Urban 0 6,943 6,943 0 6,943 Namtumbo 72 28,970 28,970 72 29,043 Total 72 187,149 187,149 72 187,221 District Dry Season Wet Season Total Number of Crop Growing Households 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District. District Dry Season Wet Season 7.1 & 7.2b TOTAL ANNUAL CROPS AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops by Season and District. Total Area Planted (Hectare) % Area planted in Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 145 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Maize 37 29 790 139,505 179,283 1,285 139,541 179,312 1,285 Paddy 29 4 124 38,178 39,510 1,035 38,207 39,514 1,034 Sorghum 0 0 0 2,079 961 462 2,079 961 462 Bulrush Millet 0 0 0 38 13 345 38 13 345 Finger Millet 0 0 0 10,287 6,046 588 10,287 6,046 588 Wheat 0 0 0 4,036 1,652 409 4,036 1,652 409 Barley 0 0 0 22 16 741 22 16 741 CEREALS 66 33 494 194,145 227,482 1,172 194,211 227,514 1,171 Cassava 0 0 0 87,522 101,965 1,165 87,522 101,965 1,165 Sweet Potatoes 0 0 0 6,316 13,950 2,209 6,316 13,950 2,209 Irish Potatoes 0 0 0 143 223 1,563 143 223 1,563 Yams 0 0 0 96 173 1,803 96 173 1,803 Cocoyam 0 0 0 446 876 1,965 446 876 1,965 ROOTS & TUBERS 0 0 94,522 117,187 1,240 94,522 117,187 1,240 Mung Beans 0 0 0 73 34 458 73 34 458 Beans 0 0 0 34,237 15,059 440 34,237 15,059 440 Cowpeas 0 0 0 2,438 821 337 2,438 821 337 Green Gram 0 0 0 138 37 270 138 37 270 Pigeon Peas 0 0 0 51 3 51 51 3 51 Chich Peas 0 0 0 . . 0 . . 0 Bambaranuts 0 0 2,570 1,126 438 2,570 1,126 438 Field Peas 0 0 0 189 154 814 189 154 814 PULSES 0 0 0 39,697 17,234 434 39,697 17,234 434 Sunflower 0 0 49 796 399 501 796 399 501 Simsim 0 0 0 6,279 2,376 378 6,279 2,376 378 Groundnuts 29 1 49 9,532 4,731 496 9,561 4,732 495 Soya Beans 0 0 0 828 246 297 828 246 297 Castor Seed 0 0 0 0 0 0 0 0 0 OIL SEEDS & OIL NUTS 29 1 49 17,435 7,751 17,464 7,752 444 Okra 0 0 0 3 45 16,134 3 45 16,134 Radish 0 0 0 7 2 267 7 2 267 Onions 0 0 0 585 1,704 2,915 585 1,704 2,915 Cabbage 7 11 1,482 1,209 4,109 3,397 1,217 4,119 3,386 Tomatoes 0 0 0 1,927 7,328 3,804 1,927 7,328 3,804 Spinnach 0 0 0 465 854 1,837 465 854 1,837 Carrot 0 0 0 72 21 294 72 21 294 Chillies 0 0 0 27 28 1,007 27 28 1,007 Amaranths 7 8 1,087 349 854 2,449 356 862 2,421 Pumpkins 0 0 0 448 1,048 2,342 448 1,048 2,342 Cucumber 0 0 0 22 27 1,219 22 27 1,219 Egg Plant 0 0 0 12 48 3,987 12 48 3,987 FRUITS & VEGETABLES 15 19 1,284 5,125 16,068 3,135 5,139 16,087 3,130 Seaweed 0 0 0 0 0 0 0 0 Cotton 0 0 0 0 0 0 0 0 Tobacco 0 0 0 7,169 4,371 610 7,169 4,371 Pyrethrum 0 0 0 0 0 0 0 0 Jute 0 0 0 0 0 0 0 0 CASH CROPS 0 0 0 7,169 4,371 610 7,169 4,371 Total 110 1,725 1,761 358,093 258,478 393 358,203 260,203 395 *The total area planted include the sum of the planted area for both Wet and Dry Season and it is an overestimation of the actual area due to being produced on the same land during the two seasons. Previous surveys have used the Long/Wet Season to estimate physical land area under production to different crops 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Ruvuma Region Crop Dry season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 146 Number of Households Planted area (ha) Number of Households Planted area (ha) CEREALS 145 66 308,200 194,145 194,211 Maize 72 37 178,837 139,505 139,541 0 Paddy 72 29 81,184 38,178 38,207 0 Sorghum 0 0 7,711 2,079 2,079 0 Bulrush Millet 0 0 313 38 38 0 Finger Millet 0 0 30,738 10,287 10,287 0 Wheat 0 0 9,309 4,036 4,036 0 Barley 0 0 107 22 22 0 ROOTS & TUBERS 0 0 179,886 94,522 94,522 0 Cassava 0 0 137,409 87,522 87,522 0 Sweet Potatoes 0 0 35,326 6,316 6,316 0 Irish Potatoes 0 0 1,618 143 143 0 Yams 0 0 952 96 96 0 Cocoyam 0 0 4,582 446 446 0 PULSES 0 0 117,582 39,697 39,697 0 Mung Beans 0 0 145 73 73 0 Beans 0 0 86,699 34,237 34,237 0 Cowpeas 0 0 12,806 2,438 2,438 0 Green Gram 0 0 1,027 138 138 0 Pigeon Peas 0 0 145 51 51 0 Chich Peas 0 0 0 . 0 0 Bambaranuts 0 0 16,049 2,570 2,570 0 Field Peas 0 0 711 189 189 0 OIL SEEDS & OIL NUTS 72 29 66,052 17,435 17,464 0.2 Sunflower 0 0 3,537 796 796 0.0 Simsim 0 0 21,421 6,279 6,279 0.0 Groundnuts 72 29 39,839 9,532 9,561 0.3 Soya Beans 0 0 1,255 828 828 0.0 Castor Seed 0 0 0 . 0 0.0 FRUITS & VEGETABLES 145 15 42,583 5,125 5,140 0 Okra 0 0 27 3 3 0 Radish 0 0 73 7 7 0 Turmeric 0 0 0 0 0 0 Bitter Aubergine 0 0 0 0 0 0 Garlic 0 0 0 0 0 0 Onions 0 0 4,075 585 585 0 Ginger 0 0 0 0 0 0 Cabbage 72 7 10,900 1,209 1,217 1 Tomatoes 0 0 13,606 1,927 1,927 0 Spinnach 0 0 4,367 465 465 0 Carrot 0 0 130 72 72 0 Chillies 0 0 241 27 27 0 Amaranths 72 7 3,950 349 356 2 Pumpkins 0 0 4,866 448 448 0 Cucumber 0 0 221 22 22 0 Egg Plant 0 0 127 12 12 0 Water Mellon 0 0 0 0 0 0 Cauliflower 0 0 0 0 0 0 Total 72 110 763,656 358,093 358,203 0 Total Area Planted Dry & Wet Season % Area Planted in Dry Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03 - Wet and Dry Seasons, Ruvuma Region Wet Season Dry Season Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 147 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 203 173 829 1,405 45,558 60,541 46,589 62,119 Songea Rural 460 435 1,438 2,095 28,798 48,170 30,696 50,700 Mbinga 2,840 3,408 3,471 4,907 67,639 82,466 73,950 90,781 Songea Urban 357 292 162 134 6,423 8,326 6,943 8,752 o 72 217 1,003 2,268 27,968 56,441 29,042 58,927 Total 3,931 4,525 6,903 10,809 176,387 255,944 187,221 271,279 % 2 4 94 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 o 1,150 2,277 143 394 5,612 12,450 22,282 55,265 29,187 70,385 Total 13,938 29,470 1,671 3,591 23,710 43,402 151,614 281,740 190,933 358,203 Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Number of Household Planted Area (Ha) Tunduru 30,899 60,879 15,893 23,665 46,792 84,544 72.01 Songea Rural 20,996 44,231 9,700 17,738 30,696 61,969 71.38 Mbinga 43,932 73,755 33,383 56,630 77,315 130,386 56.57 Songea Urban 5,154 8,774 1,788 2,146 6,943 10,920 80.35 Namtumb o 18,971 49,669 10,145 20,606 29,115 70,275 70.68 Total 119,953 237,308 70,909 120,785 190,861 358,093 66.27 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Agriculture Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year % of Area Planted Under Irrigation District Irrigation Use Households Using Households not Using Total 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Wet & Dry Season, Ruvuma District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 Agriculture Year - Wet & Dry Season, Ruvuma District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 148 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 3,526 8,397 43,267 76,147 46,792 84,544 9.93 Songea Rural 4,462 10,713 26,234 51,256 30,696 61,969 17.29 Mbinga 22,527 43,482 54,788 86,903 77,315 130,386 33.35 Songea Urban 2,486 5,236 4,457 5,684 6,943 10,920 47.95 Namtumbo 4,254 11,130 24,934 59,255 29,187 70,385 15.81 Total 37,254 78,958 153,679 279,245 190,933 358,203 22.04 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 636 2,244 46,156 82,300 46,792 84,544 2.65 Songea Rural 76 170 30,620 61,799 30,696 61,969 0.27 Mbinga 1,531 3,264 75,784 127,121 77,315 130,386 2.50 Songea Urban 82 195 6,860 10,725 6,943 10,920 1.78 Namtumbo 145 248 29,042 70,137 29,187 70,385 0.35 Total 2,471 6,121 188,462 352,082 190,933 358,203 1.71 % 1.3 1.7 98.7 98.3 100 100 % of Planted Area Using Herbicides District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted Area Using Insecticides 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. District Insecticide Use Households Using Insecticides Households Not Using Insecticides Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 149 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 2,273 4,588 44,519 79,956 46,792 84,544 5.43 Songea Rural 909 2,335 29,787 59,634 30,696 61,969 3.77 Mbinga 3,377 6,915 73,937 123,470 77,315 130,386 5.30 Songea Urban 411 904 6,532 10,015 6,943 10,920 8.28 Namtumbo 939 2,689 28,248 67,697 29,187 70,385 3.82 Total 7,910 17,431 183,024 340,772 190,933 358,203 4.87 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 1,973 3,088 44,616 59,141 46,589 62,119 4.97 Songea Rural 5,254 11,165 25,442 39,535 30,696 50,700 22.02 Mbinga 7,487 11,609 66,463 79,172 73,950 90,781 12.79 Songea Urban 1,394 1,993 5,549 6,760 6,943 8,752 22.77 Namtumbo 2,809 7,354 26,305 51,683 29,114 59,037 12.46 Total 18,917 35,208 168,376 236,181 187,293 271,388 12.97 7.1 & 7.2j TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicides Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Fungicides District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1 & 7.2k TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Improved Seed Use and District for the 2002/03 Agriculture Year - Wet & Dry Season. % of Planted Area Using Improved Seeds District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census - 2003 Ruvuma 150 Appendix II 151 ANNUAL CROP & VEGETABLES PRODUCTION DRY SEASON Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 152 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 72 110 72 110 Total 0 0 0 0 72 110 72 110 % 0 0 0 0 100 100 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 72 110 0 0 72 110 Total 72 110 0 0 72 110 % 0 0 0 0 100 100 0 0 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 % 0 0 100 100 100 100 Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - DRY SEASON, Ruvuma Region. District Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Tractor Ploughing Soil Preparation 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - DRY SEASON, Ruvuma Region District % of planted area under irrigation in dry season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Dry Season, 2002/03 Agriculture Year, Ruvuma Region Irrigation Use Households Using Irrigation Households Not Using Irrigation Total District Fertilizer Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 153 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 72 110 72 110 0 % of Planted Area Using Insecticides Household Using Insecticides 7.1d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Dry Season. Households Not Using Insecticides Total Insecticide Use Households Not Using Herbicidess Total 7.1e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicides Use and District for the 2002/03 Agriculture Year - Dry Season. Herbicide Use % of Planted Area Using Herbicides Household Using Herbicidess Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 0 72 110 72 110 0 Total 0 0 72 110 72 110 0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 Namtumbo 0 . 72 110 72 110 0 Total 0 . 72 110 72 110 0 % 0 0 100 100 100 100 0 7.1f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - Dry Season. Fungicide Use % of Planted Area Using Fungicides Household Using Fungicides Households Not Using Fungicides Total % of Planted Area Using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - DRY SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 155 ANNUAL CROP & VEGETABLES PRODUCTION WET SEASON Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 156 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 203 173 829 1,405 45,558 60,541 46,589 62,119 Songea Rural 460 435 1,438 2,095 28,798 48,170 30,696 50,700 Mbinga 2,840 3,408 3,471 4,907 67,639 82,466 73,950 90,781 Songea Urban 357 292 162 134 6,423 8,326 6,943 8,752 Namtumbo 72 217 1,003 2,268 27,896 56,331 28,970 58,817 Total 3,931 4,525 6,903 10,809 176,315 255,834 187,149 271,169 % 2 2 4 4 94 94 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 604 1,163 318 649 3,128 5,457 42,742 77,275 46,792 84,544 Songea Rural 2,723 5,952 460 829 4,836 9,312 22,677 45,875 30,696 61,969 Mbinga 8,451 17,981 641 1,561 7,714 12,325 60,509 98,519 77,315 130,386 Songea Urban 1,010 2,098 109 159 2,419 3,857 3,404 4,806 6,943 10,920 Namtumbo 1,150 2,277 143 394 5,540 12,340 22,282 55,265 29,115 70,275 Total 13,938 29,470 1,671 3,591 23,638 43,292 151,614 281,740 190,861 358,093 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 30,899 60,879 15,893 23,665 46,792 84,544 72 Songea Rural 20,996 44,231 9,700 17,738 30,696 61,969 71 Mbinga 43,932 73,755 33,383 56,630 77,315 130,386 57 Songea Urban 5,154 8,774 1,788 2,146 6,943 10,920 80 Namtumbo 18,971 49,669 10,145 20,606 29,115 70,275 71 Total 119,953 237,308 70,909 120,785 190,861 358,093 66 % 63 66 37 34 100 100 66 Mostly Farm Yard Manure Mostly Compost 7.2b ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Crop Growing Households and Planted Area by Fertilizer Use and District during 2002/03 Agriculture Year - WET SEASON, Ruvuma Region Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - WET SEASON, Ruvuma Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total % of planted area under irrigation in dry season 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION:Total Number of Crop Growing Households and Planted Area by Irrigation Use and District during Wet Season, 2002/03 Agriculture Year, Ruvuma Region Fertilizer Use District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Mostly Inorganic Fertilizer No Fertilizer Applied Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 3,526 8,397 43,267 76,147 46,792 84,544 10 Songea Rural 4,462 10,713 26,234 51,256 30,696 61,969 17 Mbinga 22,527 43,482 54,788 86,903 77,315 130,386 33 Songea Urban 2,486 5,236 4,457 5,684 6,943 10,920 48 Namtumbo 4,254 11,130 24,862 59,145 29,115 70,275 16 Total 37,254 78,958 153,607 279,135 190,861 358,093 22 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 636 2,244 46,156 82,300 46,792 84,544 2.65 Songea Rural 76 170 30,620 61,799 30,696 61,969 0.27 Mbinga 1,531 3,264 75,784 127,121 77,315 130,386 2.50 Songea Urban 82 195 6,860 10,725 6,943 10,920 1.78 Namtumbo 145 248 28,970 70,027 29,115 70,275 0.35 Total 2,471 6,121 188,390 351,972 190,861 358,093 1.71 % 1.3 1.7 98.7 98.3 100 100 7.2d ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture Year - Wet Season. District Insecticide Use % of Planted Area Using Insecticides Households Using Insecticides Households Not Using Insecticides Total 7.2e ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture Year - Wet Season. District Herbicide Use % of Planted Area Using Herbicides Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Tunduru 2,273 4,588 44,519 79,956 46,792 84,544 5 Songea Rural 909 2,335 29,787 59,634 30,696 61,969 4 Mbinga 3,377 6,915 73,937 123,470 77,315 130,386 5 Songea Urban 411 904 6,532 10,015 6,943 10,920 8 Namtumbo 939 2,689 28,176 67,587 29,115 70,275 4 Total 7,910 17,431 182,952 340,662 190,861 358,093 5 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Tunduru 1,973 3,088 44,616 59,141 46,589 62,119 5 Songea Rural 5,254 11,165 25,442 39,535 30,696 50,700 22 Mbinga 7,487 11,609 66,463 79,172 73,950 90,781 13 Songea Urban 1,394 1,993 5,549 6,760 6,943 8,752 23 Namtumbo 2,809 7,354 26,233 51,573 29,042 58,927 12 Total 18,917 35,208 168,304 236,071 187,221 271,278 13 % 10 13 90 87 100 100 7.2f ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fungicide Use and District for the 2002/03 Agriculture Year - WET SEASON District Fungicide Use % of Planted Area Using Fungicides Households Using Fungicide Households Not Using Fungicide Total % of planted area under irrigation in dry season 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - WET SEASON District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 159 Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area Number of House- holds Planted Area CEREALS 44,152 31,867 320,540 140,886 3,444 203 87,597 18,312 15,889 2,346 471,622 193,613 Maize 34,027 23,928 126,531 100,018 77 76 16,064 13,801 1,725 1,249 178,423 139,073 Paddy 7,506 4,424 65,147 29,681 104 127 6,568 2,966 1,728 946 81,054 38,143 Sorghum 4,023 1,238 3,518 795 0 . 171 46 0 . 7,711 2,079 Bulrush Millet 0 . 313 38 0 . 0 . 0 . 313 38 Finger Millet 5,460 2,198 19,749 6,382 0 . 4,751 1,490 438 151 30,397 10,222 Wheat 128 78 9,104 3,950 0 . 77 8 0 . 9,309 4,036 Barley 0 . 107 22 0 . 0 . 0 . 107 22 ROOTS & TUBERS 1,661 514 10,730 6,732 0 0 3,244 277 703 21 16,338 7,544 Cassava 132 107 1,075 474 0 . 148 16 0 . 1,355 598 Sweet Potatoes 1,729 403 31,790 5,595 0 . 1,414 256 155 21 35,087 6,275 Irish Potatoes 77 3 1,541 139 0 . 0 . 0 . 1,618 143 Yams 0 . 845 91 0 . 107 5 0 . 952 96 Cocoyam 0 . 4,450 432 0 . 0 . 0 . 4,450 432 PULSES 2,655 5,469 40,432 30,934 228 81 10,548 2,818 2,179 160 56,043 39,461 Mung Beans 0 . 145 73 0 . 0 . 0 . 145 73 Beans 6,884 3,092 71,823 28,030 205 81 7,261 2,681 206 118 86,378 34,001 Cowpeas 6,578 1,342 5,955 1,057 0 . 171 19 103 21 12,806 2,438 Green Gram 0 . 1,027 138 0 . 0 . 0 . 1,027 138 Pigeon Peas 0 . 145 51 0 . 0 . 0 . 145 51 Chich Peas 0 . 0 . 0 . 0 . 0 . 0 . Bambaranuts 6,362 1,036 8,852 1,407 0 . 732 107 103 21 16,049 2,570 Field Peas 0 . 683 178 0 . 27 11 0 . 711 189 OIL SEEDS & OIL NUTS 3,540 12,044 44 1,716 27 17,371 Sunflower 153 22 2,777 669 0 . 295 59 74 7 3,299 757 Simsim 2,585 633 14,924 4,545 145 44 3,489 1,011 98 20 21,240 6,254 Groundnuts 11,188 2,855 26,462 6,241 0 . 2,189 436 0 . 39,839 9,532 Soya Beans 75 30 644 588 0 . 536 209 0 . 1,255 828 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 220 4,639 0 236 0 5,095 Okra 0 . 27 3 0 . 0 . 0 . 27 3 Radish 0 . 73 7 0 . 0 . 0 . 73 7 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 0 . 0 . 0 . 0 . 0 . Garlic 0 . 0 . 0 . 0 . 0 . 0 . Onions 324 45 3,647 530 0 . 103 10 0 . 4,075 585 Ginger 0 . 0 . 0 . 0 . 0 . 0 . Cabbage 311 19 10,178 1,147 0 . 273 28 0 . 10,763 1,193 Tomatoes 437 87 12,395 1,738 0 . 719 88 0 . 13,551 1,913 Spinnach 273 22 3,558 365 0 . 536 78 0 . 4,367 465 Carrot 76 2 55 70 0 . 0 . 0 . 130 72 Chillies 0 . 241 27 0 . 0 . 0 . 241 27 Amaranths 176 8 3,697 333 0 . 77 8 0 . 3,950 349 Pumpkins 318 39 4,244 383 0 . 305 26 0 . 4,866 448 Cucumber 0 . 221 22 0 . 0 . 0 . 221 22 Egg Plant 0 . 127 12 0 . 0 . 0 . 127 12 Water Mellon 0 . 0 . 0 . 0 . 0 . 0 . Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 2,285 4,390 0 465 14 7,154 Seaweed 0 . 0 . 0 . 0 . 0 . 0 . Cotton 0 . 0 . 0 . 0 . 0 . 0 . Tobacco 4,287 2,285 8,184 4,390 0 . 1,122 465 71 14 13,664 7,154 Pyrethrum 0 . 0 . 0 . 0 . 0 . 0 . Jute 0 . 0 . 0 . 0 . 0 . 0 . Total 65,890 43,895 512,020 199,624 5,294 327 143,652 23,824 27,829 2,568 754,685 270,238 % 16 74 0 9 1 100 Crop Table 7.2h: Planted Area and Number of Crop Growing Households During Wet Season by Method of Land Clearing and Crops 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 160 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 43,774 27,246 18,891 0.693 27,246 18,891 0.693 Songea Rural 0 0 0 0.000 30,316 28,503 47,070 1.651 28,503 47,070 1.651 Mbinga 0 0 0 0.000 69,226 50,346 65,950 1.310 50,346 65,950 1.310 Songea Urban 0 0 0 0.000 6,833 4,600 6,655 1.447 4,600 6,655 1.447 Namtumbo 72 37 29 0.790 28,688 28,809 40,718 1.413 28,846 40,747 1.413 Total 72 37 29 0.790 178,837 139,505 179,283 1.285 139,541 179,312 1.285 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 107 13 3 0.222 13 3 0.222 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 206 25 10 0.409 25 10 0.409 Total 0 0 0 0.000 313 38 13 0.345 38 13 0.345 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 36,922 19,750 15,811 0.801 19,750 15,811 0.801 Songea Rural 0 0 0 0.000 14,641 6,187 7,676 1.241 6,187 7,676 1.591 Mbinga 0 0 0 0.000 9,753 3,721 3,037 0.816 3,721 3,037 1.591 Songea Urban 0 0 0 0.000 3,033 1,080 1,105 1.023 1,080 1,105 1.023 Namtumbo 72 29 4 0.000 16,835 7,440 11,881 1.597 7,470 11,884 1.591 Total 72 29 4 0.000 81,184 38,178 39,510 1.035 38,207 39,514 1.034 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 6,168 1,845 850 0.461 1,845 850 0.461 Songea Rural 0 0 0 0.000 150 15 3 0.220 15 3 0.220 Mbinga 0 0 0 0.000 255 38 42 1.092 38 42 1.092 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 1,139 180 65 0.363 180 65 0.363 Total 0 0 0 0.000 7,711 2,079 961 0.462 2,079 961 0.462 Table 7.2.2: Number of Agricultural Households, Area Planted (ha) and Quantity of Burlush millet Harvested (tons) by Burlush millet District Dry Season Wet Season Total Table 7.2.3: Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and Paddy District Dry Season Wet Season Total Table 7.2.4: Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season Sorghum District Dry Season Wet Season Total Wet Season Total Table 7.2.1: Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and Maize District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 161 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 422 72 15 0.208 72 15 0.208 Songea Rural 0 0 0 0.000 10,031 2,941 1,752 0.771 2,941 1,752 0.596 Mbinga 0 0 0 0.000 7,854 3,504 2,404 0.771 3,504 2,404 0.686 Songea Urban 0 0 0 0.000 984 272 210 0.771 272 210 0.771 Namtumbo 0 0 0 0.000 11,447 3,497 1,665 0.476 3,497 1,665 0.476 Total 0 0 0 0.000 30,738 10,287 6,046 0.588 10,287 6,046 0.588 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 3,756 1,812 706 0.389 1,812 706 0.389 Songea Rural 0 0 0 0.000 16,963 6,108 3,416 0.559 6,108 3,416 0.559 Mbinga 0 0 0 0.000 47,031 20,544 8,272 0.403 20,544 8,272 0.403 Songea Urban 0 0 0 0.000 4,205 897 305 0.340 897 305 0.340 Namtumbo 0 0 0 0.000 14,744 4,877 2,360 0.484 4,877 2,360 0.484 Total 0 0 0 0.000 86,699 34,237 15,059 0.440 34,237 15,059 0.440 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 1,027 138 37 0.270 138 37 0.270 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Total 0 0 0 0.000 1,027 138 37 0.270 138 37 0.270 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0.000 145 73 34 0.458 73 34 0.458 Total 0 0 0 0.000 145 73 34 0.458 73 34 0.458 Wet Season Total Table 7.2.5: Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District;2002/03 Agricultural Year Finger millet District Dry Season Table 7.2.8: Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Mung beans District Dry Season Wet Season Total Table 7.2.7: Number of Agricultural Households, Area Planted (ha) and Quantity of Green gram Harvested (tons) by Season and District;2002/03 Agricultural Year Green gram District Dry Season Wet Season Total Table 7.2.6: Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Beans District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 162 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 10,419 2,099 693 0.330 2,099 693 0.330 Songea Rural 0 0 0 0 305 39 13 0.321 39 13 0.321 Mbinga 0 0 0 0 132 13 3 0.198 13 3 0.198 Songea Urban 0 0 0 0 27 4 1 0.247 4 1 0.247 Namtumbo 0 0 0 0 1,923 282 112 0.397 282 112 0.397 Total 0 0 0 0 12,806 2,438 821 0.337 2,438 821 0.337 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 10,324 1,819 744 0.409 1,819 744 0.409 Songea Rural 0 0 0 0 1,809 256 118 0.462 256 118 0.462 Mbinga 0 0 0 0 1,424 158 75 0.474 158 75 0.474 Songea Urban 0 0 0 0 137 22 8 0.369 22 8 0.369 Namtumbo 0 0 0 0 2,354 314 180 0.574 314 180 0.574 Total 0 0 0 0 16,049 2,570 1,126 0.438 2,570 1,126 0.438 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 35,486 22,565 28,658 1.270 22,565 28,658 1.270 Songea Rural 0 0 0 0 22,595 11,465 12,309 1.074 11,465 12,309 1.074 Mbinga 0 0 0 0 51,931 39,712 45,044 1.134 39,712 45,044 1.134 Songea Urban 0 0 0 0 5,320 2,175 3,159 1.452 2,175 3,159 1.452 Namtumbo 0 0 0 0 22,077 11,605 12,795 1.103 11,605 12,795 1.103 Total 0 0 0 0 137,409 87,522 101,965 1.165 87,522 101,965 1.165 Table 7.2.10: Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Bambaranuts District Dry Season Wet Season Total Table 7.2.11: Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Chick peas District Dry Season Wet Season Total Table 7.2.12: Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Cassava District Dry Season Wet Season Total Wet Season Total Table 7.2.9: Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Cowpeas District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 163 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 3,066 711 1,711 2.407 711 1,711 2.407 Songea Rural 0 0 0 0.000 5,249 817 2,640 3.231 817 2,640 3.231 Mbinga 0 0 0 0.000 23,166 3,648 6,763 0.000 3,648 6,763 1.854 Songea Urban 0 0 0 0.000 2,051 639 2,203 3.449 639 2,203 3.449 Namtumbo 0 0 0 0.000 1,794 501 634 1.265 501 634 1.265 Total 0 0 0 0.000 35,326 6,316 13,950 2.209 6,316 13,950 2.209 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 229 34 52 1.530 34 52 1.530 Mbinga 0 0 0 0.000 1,289 94 162 1.730 94 162 1.730 Songea Urban 0 0 0 0.000 27 7 4 0.545 7 4 0.545 Namtumbo 0 0 0 0.000 73 7 4 0.593 7 4 0.593 Total 0 0 0 0.000 1,618 143 223 1.563 143 223 1.563 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 15,342 4,088 2,001 0.489 4,088 2,001 0.489 Songea Rural 0 0 0 0.000 7,974 1,980 908 0.458 22,540 8,899 0.395 Mbinga 0 0 0 0.000 6,780 1,193 522 0.438 16,091 5,074 0.315 Songea Urban 0 0 0 0.000 849 225 227 1.009 28,042 12,472 0.445 Namtumbo 72 29 1 0.049 8,894 2,046 1,072 0.524 8,513 2,908 0.342 Total 72 29 1 0.049 39,839 9,532 4,731 0.496 79,274 31,353 0.396 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Tunduru 0 0 0 0.000 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0.000 831 174 119 0.684 174 119 0.684 Mbinga 0 0 0 0.000 1,924 404 176 0.436 404 176 0.436 Songea Urban 0 0 0 0.000 137 29 48 1.635 29 48 1.635 Namtumbo 0 0 0 0.000 645 189 56 0.296 189 56 0.296 Total 0 0 0 0.000 3,537 796 399 0.501 796 399 0.501 Wet Season Total Table 7.2.13: Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Sweet potatoes District Dry Season Table 7.2.16: Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Sunflower District Dry Season Wet Season Total Table 7.2.15: Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Groundnuts District Dry Season Wet Season Total Table 7.2.14: Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Irish potatoes District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 164 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 2,619 747 264 0.354 747 264 0.354 Songea Rural 0 0 0 0 6,317 1,522 524 0.345 1,522 524 0.345 Mbinga 0 0 0 0 1,512 472 141 0.299 472 141 0.299 Songea Urban 0 0 0 0 82 11 5 0.418 11 5 0.418 Namtumbo 0 0 0 0 10,891 3,527 1,442 0.409 3,527 1,442 0.409 Total 0 0 0 0 21,421 6,279 2,376 0.378 6,279 2,376 0.378 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0 989 363 184 0.508 363 184 0.508 Mbinga 0 0 0 0 122 407 15 0.038 407 15 0.038 Songea Urban 0 0 0 0 0 0 0 0.000 0 0 0.000 Namtumbo 0 0 0 0 144 58 46 0.786 58 46 0.786 Total 0 0 0 0 1,255 828 246 0.297 828 246 0.297 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 801 75 163 2.177 75 163 2.177 Songea Rural 0 0 0 0 2,883 248 476 1.920 248 476 1.920 Mbinga 0 0 0 0 3,059 432 1,381 3.197 432 1,381 3.197 Songea Urban 0 0 0 0 1,782 201 1,181 5.872 201 1,181 5.872 Namtumbo 72 7 11 0 2,375 253 907 3.580 261 918 3.521 Total 72 7 11 0 10,900 1,209 4,109 3.397 1,217 4,119 3.386 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 27 3 45 16 3 45 16.134 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 27 3 45 16 3 45 16.134 Table 7.2.18: Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District;2002/03 Agricultural Year Soya beans District Dry Season Wet Season Total Table 7.2.19: Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Cabbage District Dry Season Wet Season Total Table 7.2.20: Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Okra District Dry Season Wet Season Total Wet Season Total Table 7.2.17: Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Simsim District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 165 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 73 7 2 0.267 7 2 0.267 Total 0 0 0 0 73 7 2 0.267 7 2 0.267 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0 0 0 0 Songea Rural 0 0 0 0 0 0 0 0 0 0 0 Mbinga 0 0 0 0 0 0 0 0 0 0 0 Songea Urban 0 0 0 0 0 0 0 0 0 0 0 Namtumbo 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 0 0 0 0 0 0 0 0 0 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 821 135 291 2.154 135 291 2.154 Songea Rural 0 0 0 0 686 51 204 3.975 51 204 3.975 Mbinga 0 0 0 0 757 158 93 0.589 158 93 0.589 Songea Urban 0 0 0 0 438 54 107 1.977 54 107 1.977 Namtumbo 0 0 0 0 1,372 186 1,010 5.418 186 1,010 5.418 Total 0 0 0 0 4,075 585 1,704 2.915 585 1,704 2.915 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 2,770 551 1,186 2.150 551 1,186 2.150 Songea Rural 0 0 0 0 1,898 202 681 3.376 202 681 3.376 Mbinga 0 0 0 0 4,799 632 2,207 3.491 632 2,207 3.491 Songea Urban 0 0 0 0 1,915 280 1,251 4.475 280 1,251 4.475 Namtumbo 0 0 0 0 2,224 262 2,004 7.652 262 2,004 7.652 Total 0 0 0 0 13,606 1,927 7,328 3.804 1,927 7,328 3.804 Wet Season Total Table 7.2.21: Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Radish District Dry Season Table 7.2.24: Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Tomatoes District Dry Season Wet Season Total Table 7.2.23: Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Onions District Dry Season Wet Season Total Table 7.2.22: Number of Agricultural Households, Area Planted (ha) and Quantity of Tumeric Harvested (tons) by Season and District;2002/03 Agricultural Year Tumeric District Dry Season Wet Season Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 166 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 104 8 7 0.865 8 7 0.865 Songea Rural 0 0 0 0 1,223 130 147 1.127 130 147 1.127 Mbinga 0 0 0 0 1,164 111 279 2.508 111 279 2.508 Songea Urban 0 0 0 0 298 53 53 0.995 53 53 0.995 Namtumbo 0 0 0 0 1,578 162 368 2.276 162 368 2.276 Total 0 0 0 0 4,367 465 854 1.837 465 854 1.837 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Rural 0 0 0 0 76 2 4 2.470 2 4 2.470 Mbinga 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0 55 70 17 0.247 70 17 0.247 Namtumbo 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 130 72 21 0.294 72 21 0.294 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 104 11 4 0.395 11 4 0.395 Songea Rural 0 0 0 0 0 0 0 0.000 0 0 0.000 Mbinga 0 0 0 0 0 0 0 0.000 0 0 0.000 Songea Urban 0 0 0 0 137 17 23 1.388 17 23 1.388 Namtumbo 0 0 0 0 0 0 0 0.000 0 0 0.000 Total 0 0 0 0 241 27 28 1.007 27 28 1.007 Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ ha) Number of Households Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/h a) Tunduru 0 0 0 0 1,011 102 116 1.131 102 116 1.131 Songea Rural 0 0 0 0 607 49 62 1.261 49 62 1.261 Mbinga 0 0 0 0 1,025 76 97 1.281 76 97 1.281 Songea Urban 0 0 0 0 516 45 217 4.839 45 217 4.839 Namtumbo 72 7 8 0 791 77 362 4.731 84 370 4.413 Total 72 7 8 0 3,950 349 854 2.449 356 862 2.421 Table 7.2.26: Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District;2002/03 Agricultural Year Carrot District Dry Season Wet Season Total Table 7.2.27: Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District;2002/03 Agricultural Year Chillies District Dry Season Wet Season Total Table 7.2.28: Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District;2002/03 Agricultural Year Amaranths District Dry Season Wet Season Total Wet Season Total Table 7.2.25: Number of Agricultural Households, Area Planted (ha) and Quantity of Spinach Harvested (tons) by Season and District;2002/03 Agricultural Year Spinach District Dry Season Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 167 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 168 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Sour Soup 252 252 21 82 Pigeon Pea 4,756 1,223 442 361 Star Fruit 20 20 18 889 Coconut 668 177 407 2,305 Cashewnut 71,527 51,947 8,827 170 Coffee 25 16 3 200 Sugarcane 373 152 4,467 29,423 Banana 1,022 604 1,684 2,789 Mango 401 132 824 6,233 Pawpaw 0 0 5 0 Orange 153 179 1,173 6,544 Mandarine/Tangerine 20 20 8 395 Guava 4 4 3 844 Lime/Lemon 6 6 5 906 Total 79,226 54,731 17,888 327 Pigeon Pea 15 15 3 221 Coconut 48 15 2 163 Cashewnut 451 19 8 420 Coffee 582 334 288 862 Sugarcane 238 386 2,980 7,722 Cinamon 12 12 3 278 Jack Fruit 0 0 0 0 Mpesheni 3 3 9 2,964 Banana 1,622 844 5,267 6,238 Avocado 0 0 50 0 Mango 340 159 10,904 68,477 Pawpaw 12 12 46 3,871 Pineapple 13 5 13 2,683 Orange 2,309 17 418 24,725 Grape Fruit 0 0 . 0 Mandarine/Tangerine 1 0 12 0 Guava 8 3 46 15,016 Plums 0 0 0 0 Lime/Lemon 0 0 16 0 Bilimbi 0 0 3 0 Total 5,655 1,825 20,070 10,994 Black Pepper 0 0 0 0 Malay Apple 0 0 2 0 Palm Oil 73 72 159 2,198 Coconut 186 20 120 6,125 Cashewnut 917 268 36 133 Sisal 104 104 71 679 Coffee 29,312 25,652 12,087 471 Kapok 0 0 . 0 Sugarcane 479 159 5,186 32,621 Jack Fruit 0 . 19 0 Banana 1,096 942 22,721 24,130 Avocado 249 43 95 2,229 Mango 449 470 6,136 13,064 Pawpaw 26 26 459 17,380 Pineapple 82 56 214 3,818 Orange 173 113 886 7,842 Grape 0 0 . 0 Mandarine/Tangerine 42 42 63 1,524 Guava 0 1 184 356,784 Plums 0 0 14 0 Apples 0 0 . 0 Pears 0 0 12 0 Pitches 0 0 278 0 District/Crop Songea Rural 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Tunduru Mbinga Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 169 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) District/Crop 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Lime/Lemon 0 0 4 0 Bilimbi 6 0 . 0 Total 33,195 27,966 48,746 1,743 Pigeon Pea 0 0 0 0 Star Fruit 3 3 10 3,444 Cashewnut 1 0 . 0 Coffee 42 28 10 343 Sugarcane 82 46 456 9,965 Cardamon 0 0 0 0 Jack Fruit 0 0 0 0 Banana 1,307 291 2,239 7,696 Avocado 0 0 5 0 Mango 82 93 2,891 30,952 Pawpaw 12 12 83 6,799 Pineapple 22 14 49 3,468 Orange 19 75 143 1,910 Grape 0 0 0 0 Mandarine/Tangerine 0 0 39 0 Guava 30 25 243 9,901 Plums 0 0 1 0 Apples 2 2 12 5,558 Pears 0 0 0 0 Lime/Lemon 0 0 78 0 Bilimbi 0 0 149 0 Total 1,603 589 6,410 10,879 Pigeon Pea 388 391 69 176 Palm Oil 59 29 2 62 Coconut 87 47 137 2,935 Cashewnut 1,228 473 407 861 Wattle 7 0 . 0 Sugarcane 310 440 2,173 4,937 Mpesheni 29 0 . 0 Banana 2,704 1,025 5,979 5,832 Avocado . . 9 0 Mango 87 247 3,445 13,955 Pawpaw 82 64 92 1,426 Pineapple 44 19 235 12,295 Orange 172 118 798 6,770 Grape Fruit 15 0 . 0 Guava 20 3 222 75,547 Total 5,233 2,857 13,567 4,749 Sour Soup 252 252 21 82 Black Pepper 0 0 0 0 Pigeon Pea 5,159 1,630 515 316 Malay Apple 0 0 2 0 Star Fruit 23 23 27 1,202 Palm Oil 132 102 161 1,583 Coconut 989 258 666 2,585 Cashewnut 74,124 52,708 9,278 176 Sisal 104 104 71 679 Coffee 29,961 26,030 12,388 476 Wattle 7 0 0 0 Kapok 0 0 0 0 Sugarcane 1,482 1,183 15,262 12,906 Cardamon 0 0 0 0 Cinamon 12 12 3 278 Jack Fruit 0 0 20 0 Mpesheni 32 3 9 2,964 Banana 7,751 3,706 37,890 10,225 Songea Urban Namtumbo Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 170 Area planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) District/Crop 7.3.1 PERMANENT CROPS: Production of Permanent Crops by Crop Type and District - Ruvuma Avocado 249 43 159 3,718 Mango 1,359 1,101 24,200 21,973 Pawpaw 133 115 685 5,959 Pineapple 161 94 511 5,422 Orange 2,827 502 3,418 6,809 Grape Fruit 15 0 0 0 Grape 0 0 0 0 Mandarine/Tangerine 62 62 123 1,991 Guava 62 35 699 19,939 Plums 0 0 15 0 Apples 2 2 12 5,558 Pears 0 0 12 0 Pitches 0 0 278 0 Lime/Lemon 6 6 103 17,273 Bilimbi 6 0 152 0 Total 124,910 87,969 106,681 1,213 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 171 Crop Area Planted % Cashewnut 74,124 59.34 Coffee 29,961 23.99 Banana 7,751 6.21 Pigeon Pea 5,159 4.13 Orange 2,827 2.26 Sugarcane 1,482 1.19 Mango 1,359 1.09 Coconut 989 0.79 Sour Soup 252 0.20 Avocado 249 0.20 Pineapple 161 0.13 Pawpaw 133 0.11 Palm Oil 132 0.11 Sisal 104 0.08 Mandarine/Tangerine 62 0.05 Guava 62 0.05 Mpesheni 32 0.03 Star Fruit 23 0.02 Grape Fruit 15 0.01 Cinamon 12 0.01 Wattle 7 0.01 Lime/Lemon 6 0.00 Bilimbi 6 0.00 Apples 2 0.00 Pears 0 0.00 Black Pepper 0 0.00 Malay Apple 0 0.00 Kapok 0 0.00 Cardamon 0 0.00 Jack Fruit 0 0.00 Grape 0 0.00 Plums 0 0.00 Pitches 0 0.00 Total 124,910 100.00 District Area Planted with Cashewnut Total Area Planted (Ha) % of Total Area Planted Households with Cashewnut Average Planted Area per Household Tunduru 71,527 79,226 90.3 35,899 2.0 Songea Rural 451 5,655 8.0 527 0.9 Mbinga 917 33,195 2.8 2,050 0.4 Songea Urban 1 1,603 0.1 27 0.0 Namtumbo 1,228 5,233 23.5 1,482 0.8 Total 74,124 124,910 59.3 39,985 1.9 7.3.2 PERMANENT CROP: Area Planted by Crop Type - Ruvuma Region Cashewnut 7.3.3 PERMANENT CROPS: Area Planted with Cashewnut by District Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 172 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 173 District Area Planted with Coffee Total Area Planted (Ha) % of Total Area Planted Households with Coffee Average Planted Area per Household Tunduru 25 79,226 0.03 104 0.2 Songea Rural 582 5,655 10.29 1,227 0.5 Mbinga 29,312 33,195 88.30 39,846 0.7 Songea Urban 42 1,603 2.62 109 0.4 Namtumbo 0 5,233 0.00 0 0.0 Total 29,961 124,910 23.99 41,286 0.7 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Households with Banana Average Planted Area per Household Tunduru 1022 79,226 1.3 1987 0.5 Songea Rural 1622 5,655 28.7 7151 0.2 Mbinga 1096 33,195 3.3 6565 0.2 Songea Urban 1307 1,603 81.6 1935 0.7 Namtumbo 2704 5,233 51.7 6782 0.4 Total 7751 124,910 6.2 24420 0.3 District Area Planted with Pigeon Peas Total Area Planted (Ha) % of Total Area Planted Households with Pigeon Peas Average Planted Area per Household Tunduru 4,756 79,226 6.00 7,625 0.62 Songea Rural 15 5,655 0.27 77 0.19 Mbinga 0 33,195 0.00 0 0.00 Songea Urban 0 1,603 0.00 0 0.00 Namtumbo 388 5,233 7.41 1,368 0.28 Total 5,159 124,910 4.13 9,070 0.57 Coffee 7.3.4 PERMANENT CROPS: Area planted with Coffee by District 7.3.5 PERMANENT CROPS: Area planted with Banana by District Banana 7.3.6 PERMANENT CROPS: Area Planted with Pigeon by District Pigeon Peas Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 174 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Sour Soup 0 0 0 252 252 Black Pepper 0 0 0 0 0 Pigeon Pea 0 0 80 5,011 5,092 Malay Apple 0 0 0 0 0 Star Fruit 23 0 0 0 23 Palm Oil 0 0 0 132 132 Coconut 0 0 30 959 989 Cashewnut 202 106 1,342 71,467 73,116 Sisal 104 0 0 0 104 Coffee 18,375 346 5,322 5,784 29,827 Wattle 0 0 0 7 7 Kapok 0 0 0 0 0 Sugarcane 157 31 152 1,142 1,482 Cardamon 0 0 0 0 0 Cinamon 0 0 0 12 12 Jack Fruit 0 0 0 0 0 Mpesheni 0 0 29 3 32 Banana 1,348 530 110 5,758 7,745 Avocado 43 0 0 207 249 Mango 3 8 131 1,172 1,314 Pawpaw 9 0 0 123 133 Pineapple 44 0 29 88 161 Orange 141 0 0 2,683 2,824 Grape Fruit 0 0 0 15 15 Grape 0 0 0 0 0 Mandarine/Tanger 62 0 0 0 62 Guava 10 0 0 44 54 Plums 0 0 0 0 0 Apples 0 0 0 2 2 Pears 0 0 0 0 0 Pitches 0 0 0 0 0 Lime/Lemon 6 0 0 0 6 Bilimbi 0 0 0 6 6 Total 20,526 1,021 7,226 94,867 123,640 7.3.7 PERMANENT CROPS: Planted Area with Fertilizer by Fertilizer Type and Crop Fertilizer Use Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 175 Crop Mostly Farm Yard Manure Total % Sour Soup 0 252 0.0 Black Pepper 0 0 0.0 Pigeon Pea 0 5,092 0.0 Malay Apple 0 0 0.0 Star Fruit 23 23 100.0 Palm Oil 0 132 0.0 Coconut 0 989 0.0 Cashewnut 202 73,116 0.3 Sisal 104 104 100.0 Coffee 18,375 29,827 61.6 Wattle 0 7 0.0 Kapok 0 0 0.0 Sugarcane 157 1,482 10.6 Cardamon 0 0 0.0 Cinamon 0 12 0.0 Jack Fruit 0 0 0.0 Mpesheni 0 32 0.0 Banana 1,348 7,745 17.4 Avocado 43 249 17.1 Mango 3 1,314 0.2 Pawpaw 9 133 7.1 Pineapple 44 161 27.4 Orange 141 2,824 5.0 Grape Fruit 0 15 0.0 Grape 0 0 0.0 Mandarine/Tangerine 62 62 99.4 Guava 10 54 18.5 Plums 0 0 0.0 Apples 0 2 0.0 Pears 0 0 0.0 Pitches 0 0 0.0 Lime/Lemon 6 6 100.0 Bilimbi 0 6 0.0 Total 20,526 123,640 16.6 cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 176 Crop Mostly Inorganic Fertilizer Total % Sour Soup 0 252 0.0 Black Pepper 0 0 0.0 Pigeon Pea 80 5,092 1.6 Malay Apple 0 0 0.0 Star Fruit 0 23 0.0 Palm Oil 0 132 0.0 Coconut 30 989 3.0 Cashewnut 1,342 73,116 1.8 Sisal 0 104 0.0 Coffee 5,322 29,827 17.8 Wattle 0 7 0.0 Kapok 0 0 0.0 Sugarcane 152 1,482 10.3 Cardamon 0 0 0.0 Cinamon 0 12 0.0 Jack Fruit 0 0 0.0 Mpesheni 29 32 90.5 Banana 110 7,745 1.4 Avocado 0 249 0.0 Mango 131 1,314 10.0 Pawpaw 0 133 0.0 Pineapple 29 161 18.2 Orange 0 2,824 0.0 Grape Fruit 0 15 0.0 Grape 0 0 0.0 Mandarine/Tangerine 0 62 0.0 Guava 0 54 0.0 Plums 0 0 0.0 Apples 0 2 0.0 Pears 0 0 0.0 Pitches 0 0 0.0 Lime/Lemon 0 6 0.0 Bilimbi 0 6 0.0 Total 7,226 123,640 5.8 cont… Planted Area with Fertilizer by Fertilizer Type and Crop Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 177 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 178 Number % Number % Number % Tunduru 46,378 99 520 1 46,898 100 Songea Rural 30,547 99 226 1 30,772 100 Mbinga 76,416 99 1,031 1 77,447 100 Songea Urban 6,806 98 137 2 6,943 100 Namtumbo 28,829 99 286 1 29,115 100 Total 188,975 99 2,200 1 191,175 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- opertaive Union By Trader On Large Scale Farm Other Total Tunduru 24,319 918 21,035 0 0 0 0 105 46,378 Songea Rural 3,724 307 25,478 0 76 886 76 0 30,547 Mbinga 15,884 7,736 49,059 132 132 3,343 129 0 76,416 Songea Urban 244 188 6,346 0 0 27 0 0 6,806 Namtumbo 4,134 1,294 23,258 0 72 72 0 0 28,829 Total 48,305 10,442 125,177 132 280 4,328 206 105 188,975 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- opertaive Union By Trader On Large Scale Farm Other Total Maize 20,297 10,338 130,475 132 280 4,280 206 0 172,139 Paddy 43,016 1,382 24,048 0 149 666 103 416 73,214 Sorghum 4,850 107 1,433 0 0 74 0 0 6,463 Bulrush Millet 244 0 0 0 0 0 0 0 244 Finger Millet 3,676 430 12,555 0 76 74 0 0 17,314 Cassava 40,092 997 39,600 0 153 0 0 358 101,622 Beans 1,905 0 27 0 0 129 0 0 2,193 Cowpeas 179 0 0 0 0 0 0 0 179 Bambaranut 675 0 0 0 0 0 0 0 675 Simsim 8,927 0 323 0 0 0 0 0 9,379 Groundnut 20,801 0 141 0 0 0 0 0 22,080 Coconut 1,505 0 0 0 0 0 0 0 1,633 Cashewnut 333 0 107 0 0 0 0 0 440 Soya Beans 225 0 0 0 0 0 0 0 225 Coffee 0 76 529 0 0 0 0 0 737 Banana 217 0 622 0 0 0 0 72 910 Cabbage 76 0 0 0 0 0 0 0 76 Sweet Potatoes 0 0 54 0 0 74 0 0 128 Sunflower 254 0 0 0 0 0 0 0 1,034 Wheat 0 660 4,951 0 128 129 0 0 7,056 Sugarcane 0 0 26 0 0 0 0 0 26 Tomatoes 69 0 0 0 0 0 0 27 95 Irish Potatoes 73 0 0 0 0 0 0 0 73 Pumpkins 3,467 307 25,556 0 76 886 76 0 30,368 Method of Processing 8.1.1b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Crop 8.1.1c AGRO PROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year by Location and Crop, Ruvuma Region Method of Processing 8.1.1a: Number of Crop Growing Households Reported to have Processed Products by District; 2002/03 Agriculture Year Households That Processed Crops Households That did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 179 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 171,419 0 233 280 207 0 172,139 Paddy 70,980 178 1,623 149 283 0 73,214 Sorghum 6,359 0 0 104 0 0 6,463 Bulrush Millet 244 0 0 0 0 0 244 Finger Millet 16,414 72 402 0 0 427 17,314 Wheat 7,056 0 0 0 0 0 7,056 Cassava 101,115 128 226 54 27 72 101,622 Sweet Potatoes 128 0 0 0 0 0 128 Irish Potatoes 73 0 0 0 0 0 73 Beans 2,121 0 73 0 0 0 2,193 Cowpeas 179 0 0 0 0 0 179 Bambaranut 675 0 0 0 0 0 675 Sunflower 1,034 0 0 0 0 0 1,034 Simsim 9,163 0 216 0 0 0 9,379 Groundnut 21,282 144 576 0 0 77 22,080 Coconut 1,633 0 0 0 0 0 1,633 Cashewnut 440 0 0 0 0 0 440 Soya Beans 153 0 72 0 0 0 225 Coffee 265 0 472 0 0 0 737 Sugarcane 0 0 26 0 0 0 26 Banana 910 0 0 0 0 0 910 Cabbage 76 0 0 0 0 0 76 Tomatoes 95 0 0 0 0 0 95 Pumpkins 278 0 0 0 0 0 278 Total 412,092 521 3,919 587 517 575 418,212 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 3,321 551 488 0 132 934 9,505 157,208 172,139 Paddy 3,147 505 134 284 358 977 3,861 63,947 73,214 Sorghum 107 0 0 0 0 0 640 5,716 6,463 Bulrush Millet 0 0 0 0 0 0 0 244 244 Finger Millet 220 0 72 0 0 145 1,333 15,544 17,314 Wheat 132 0 0 0 128 0 0 6,795 7,056 Cassava 3,564 146 0 75 325 0 6,414 91,097 101,622 Sweet Potatoes 0 0 0 0 0 0 0 128 128 Irish Potatoes 0 0 0 0 0 0 0 73 73 Beans 286 0 286 0 0 73 724 824 2,193 Cowpeas 0 0 0 0 0 0 73 107 179 Bambaranut 0 0 0 0 0 0 73 603 675 Sunflower 0 0 0 0 0 0 0 1,034 1,034 Simsim 0 0 143 0 0 72 723 8,441 9,379 Groundnut 787 73 0 0 105 359 1,340 19,417 22,080 Coconut 0 0 0 0 0 0 0 1,633 1,633 Cashewnut 0 0 0 0 0 0 0 440 440 Soya Beans 0 0 72 0 0 0 0 153 225 Coffee 0 0 208 132 0 0 132 265 737 Sugarcane 0 0 0 0 0 0 0 26 26 Banana 0 0 0 0 0 0 217 693 910 Cabbage 0 0 0 0 0 0 0 76 76 Tomatoes 0 0 0 0 0 0 0 95 95 Pumpkins 0 0 0 0 0 0 0 278 278 Total 11,564 1,275 1,403 492 1,049 2,560 25,033 374,836 418,212 Crop Where Sold Product Use Crop 8.1.1d AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Use of Product and Crop, Ruvuma Region 8.1.1e AGRO PROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year by Location of Sale of Product and Crop, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 180 Flour / Meal Grain Oil Juice Total Tunduru 31,588 14,578 106 106 46,378 Songea Rural 28,644 1,902 0 0 30,547 Mbinga 73,255 3,161 0 0 76,416 Songea Urban 6,424 354 0 27 6,806 Namtumbo 28,111 718 0 0 28,829 Total 168,023 20,713 106 133 188,975 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Tunduru 46,168 0 210 0 0 46,378 Songea Rural 30,165 0 231 76 76 30,547 Mbinga 75,638 128 386 132 131 76,416 Songea Urban 6,779 0 27 0 0 6,806 Namtumbo 28,757 0 0 72 0 28,829 Total 187,506 128 854 280 207 188,975 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Tunduru 740 107 107 105 105 106 1,366 43,742 46,378 Songea Rural 303 77 0 0 0 384 1,436 28,347 30,547 Mbinga 3,081 615 0 0 260 257 794 71,408 76,416 Songea Urban 271 109 0 0 0 27 27 6,371 6,806 Namtumbo 718 0 358 0 0 489 6,789 20,475 28,829 Total 5,114 907 465 105 365 1,263 10,412 170,343 188,975 Bran Cake Husk Juice Fiber Shell No by- product Total Tunduru 23,674 212 16,138 212 105 213 5,824 46,378 Songea Rural 29,020 0 458 0 0 0 1,069 30,547 Mbinga 64,462 0 3,665 0 0 0 8,289 76,416 Songea Urban 6,641 0 82 0 0 0 82 6,806 Namtumbo 28,543 0 141 0 0 0 145 28,829 Total 152,339 212 20,484 212 105 213 15,410 188,975 District Product Use District 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Ruvuma Region Main Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Ruvuma Region District By Product 8.1.1h AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Ruvuma Region District Where Sold 8.1.1i AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 181 MARKETING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 182 Number % Number % Tunduru 45,053 96.1 1,845 3.9 46,898 Songea Rural 28,109 91.3 2,663 8.7 30,772 Mbinga 70,589 91.1 6,857 8.9 77,447 Songea Urban 5,717 82.3 1,226 17.7 6,943 Namtumbo 27,456 94.3 1,659 5.7 29,115 Total 176,924 92.5 14,250 7.5 191,175 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Other Not Applicabl e Total Tunduru 745 3,612 0 0 105 942 106 40,557 46,067 Songea Rural 77 2,966 0 0 0 0 73 27,120 30,236 Mbinga 254 16,843 518 0 393 0 123 56,858 74,989 Songea Urban 81 1,390 0 0 0 0 0 5,362 6,833 Namtumbo 0 2,014 0 72 0 0 0 26,741 28,827 Total 1,156 26,823 518 72 498 942 303 156,637 186,951 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co-operative Problems Trade Union Problems Other Not Applicabl e Total Tunduru 1.62 7.84 0.00 0.00 0.23 2.05 0.23 88.04 100.00 Songea Rural 0.25 9.81 0.00 0.00 0.00 0.00 0.24 89.69 100.00 Mbinga 0.34 22.46 0.69 0.00 0.52 0.00 0.16 75.82 100.00 Songea Urban 1.19 20.34 0.00 0.00 0.00 0.00 0.00 78.47 100.00 Namtumbo 0.00 6.99 0.00 0.25 0.00 0.00 0.00 92.76 100.00 Total 0.62 14.35 0.28 0.04 0.27 0.50 0.16 83.79 100.00 10.2: Number of Households who Reported Main Reasons for Not Selling their Crops by District During 2002/03Agriccultural Year, Ruvuma Region District Main Reasons for Not Selling Crops Main Reasons for Not Selling Crops District 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year, Ruvuma Region 10.1: Number of Crop Producing Households Reported to have Sold Agricultural Produce by District During 2002/03; Ruvuma Region Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 183 IRRIGATION/EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 184 Number of Household % Number of Household % Number of Household % Tunduru 3,871 8 43,027 92 46,898 100 Songea Rural 4,485 15 26,287 85 30,772 100 Mbinga 9,024 12 68,422 88 77,447 100 Songea Urban 2,865 41 4,078 59 6,943 100 Namtumbo 4,314 15 24,801 85 29,115 100 Total 24,560 13 166,615 87 191,175 100 District Irrigatable Area (ha) Irrigated Land (ha) % Tunduru 2,126 1,298 61.0 Songea Rural 2,708 785 29.0 Mbinga 2,464 1,555 63.1 Songea Urban 1,229 866 70.4 Namtumbo 3,984 1,549 38.9 Total 12,510 6,052 48.4 River Lake Dam Well Borehole Canal Pipe water Total Tunduru 2,516 106 529 317 0 299 104 3,871 Songea Rural 3,798 0 76 534 0 77 0 4,485 Mbinga 3,689 128 0 129 0 4,948 132 9,024 Songea Urban 2,266 0 54 381 0 136 27 2,865 Namtumbo 3,529 0 0 285 72 284 143 4,314 Total 15,798 234 660 1,646 72 5,744 406 24,560 Gravity Hand Bucket Motor Pump Other Total Tunduru 968 2,800 104 0 3,871 Songea Rural 1,980 2,358 147 0 4,485 Mbinga 2,726 6,166 0 132 9,024 Songea Urban 1,366 1,499 0 0 2,865 Namtumbo 3,097 1,217 0 0 4,314 Total 10,137 14,040 250 132 24,560 District Method of Obtaining Water 11.4: IRRIGATION: Number of Agriculture Households by Method used to obtain water and District during 2002/03 Agricultural Year 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.3: IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District Households Practicing Irrigation Households not Practicing Irrigation Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 185 Flood Sprinkler Water Hose Bucket / Watering Can Total Tunduru 969 104 205 2,593 3,871 Songea Rural 1,438 229 0 2,818 4,485 Mbinga 2,060 393 0 6,571 9,024 Songea Urban 789 520 0 1,556 2,865 Namtumbo 2,162 0 0 2,152 4,314 Total 7,419 1,245 205 15,691 24,560 Number % Number % Tunduru 615 1 46,283 99 46,898 Songea Rural 1,063 3 29,709 97 30,772 Mbinga 9,554 12 67,893 88 77,447 Songea Urban 739 11 6,204 89 6,943 Namtumbo 432 1 28,684 99 29,115 Total 12,403 6 178,772 94 191,175 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Tunduru 0 1,036 0 977 0 0 0 0 2,014 Songea Rural 0 537 0 456 1,115 2,868 76 0 5,052 Mbinga 84,628 54,132 0 1,159 2,451 32,259 6,294 386 181,309 Songea Urban 27 1,125 137 1,201 3,479 1,840 577 0 8,387 Namtumbo 0 360 0 215 361 215 361 287 1,799 Total 84,655 57,191 137 4,008 7,407 37,183 7,307 672 198,561 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures By Type and District as of 2002/03 Agricultural Year District Type of Erosion Control Presence of Erosion Control/Water Harvesting Facilities Number of Households District Have Facility Does Not Have Facility District Method of Application 11.5 IRRIGATION: Number of Agricultulture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year 11.6: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District Tanzania Agriculture Sample Census - 2003 Ruvuma 186 Appendix II 187 ACCESS TO FARM INPUTS Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 188 No of households % No of households % Songea Rural 25,515 82.9 5,257 17.1 30,772 Namtumbo 23,957 82.3 5,158 17.7 29,115 Mbinga 20,791 26.8 56,656 73.2 77,447 Tunduru 15,104 32.2 31,793 67.8 46,898 Songea Urban 6,562 94.5 380 5.5 6,943 Total 91,930 48.1 99,245 51.9 191,175 No of households % No of households % Tunduru 4,103 9 42,795 91 46,898 Songea Rural 9,789 32 20,983 68 30,772 Mbinga 38,666 50 38,780 50 77,447 Songea Urban 2,751 40 4,192 60 6,943 Namtumbo 5,755 20 23,360 80 29,115 Total 61,064 32 130,111 68 191,175 No of households % No of households % Tunduru 296 0.6 46,602 99.4 46,898 Songea Rural 1,145 3.7 29,628 96.3 30,772 Mbinga 3,740 4.8 73,707 95.2 77,447 Songea Urban 269 3.9 6,674 96.1 6,943 Namtumbo 855 2.9 28,260 97.1 29,115 Total 6,305 3.3 184,870 96.7 191,175 Table 12.1.3 ACCESS TO INPUTS: Number of Crop Growing Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Table 12.1.2 ACCESS TO INPUTS: Number of Crop Growing Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer NOT Using Chemical Fertilizer Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 189 No of households % No of households % Mbinga 38,195 49 39,252 51 77,447 Tunduru 19,224 41 27,674 59 46,898 Songea Rural 3,934 13 26,838 87 30,772 Songea Urban 2,130 31 4,812 69 6,943 Namtumbo 2,445 8 26,670 92 29,115 Total 65,929 34 125,245 66 191,175 No of households % No of households % Tunduru 0 0 46,898 100 46,898 Songea Rural 228 1 30,544 99 30,772 Mbinga 1,701 2 75,746 98 77,447 Songea Urban 82 1 6,860 99 6,943 Namtumbo 0 0 29,115 100 29,115 Total 2,011 1 189,163 99 191,175 No of households % No of households % Tunduru 2,164 5 44,734 95 46,898 Songea Rural 6,857 22 23,915 78 30,772 Mbinga 10,036 13 67,411 87 77,447 Songea Urban 2,625 38 4,318 62 6,943 Namtumbo 4,963 17 24,152 83 29,115 Total 26,646 14 164,529 86 191,175 Table 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticide/Fungicides by District during 2002/03 Agricultural Year District Using Insecticides/Fungicide Not Using Insecticide/Fungi Total Number of Crop growing households Table 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households Table 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 190 Number % Number % Number % Number % Number % Tunduru 1,381 2.9 719 1.5 12,060 25.7 0 0.0 309 0.7 107 0.2 Songea Rural 1,438 4.7 0 0.0 23,250 75.6 150 0.5 150 0.5 0 0.0 Mbinga 2,238 2.9 1,304 1.7 16,589 21.4 0 0.0 132 0.2 0 0.0 Songea Urban 27 0.4 53 0.8 6,454 93.0 27 0.4 0 0.0 0 0.0 Namtumbo 10,459 35.9 72 0.2 12,422 42.7 358 1.2 143 0.5 0 0.0 Total 15,544 8.1 2,148 1.1 70,774 37.0 535 0.3 735 0.4 107 0.1 Total Number % Number % Number % Number % Number Tunduru 0 0.0 423 0.9 105 0.2 31793 67.8 46,898 Songea Rural 147 0.5 303 0.9 77 0.3 5256.9 17.1 30,772 Mbinga 0 0.0 527 0.9 0 0.0 56656 73.2 77,447 Songea Urban 0 0.0 0 0.9 0 0.0 380.41 5.5 6,943 Namtumbo 0 0.0 504 0.9 0 0.0 5158.4 17.7 29,115 Total 147 0.1 1,757 0.9 182 0.1 99245 51.9 191,175 Number % Number % Number % Number % Number % Tunduru 107 0.2 0 0.0 107 0.2 0 0.0 0 0.0 0 0.0 Songea Rural 0 0.0 0 0.0 76 0.2 0 0.0 74 0.2 0 0.0 Mbinga 0 0.0 0 0.0 0 0.0 0 0.0 128 0.2 132 0.2 Songea Urban 0 0.0 81 1.2 82 1.2 27 0.4 27 0.4 0 0.0 Namtumbo 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 107 0.1 81 0.0 265 0.1 27 0.0 229 0.1 132 0.1 Crop Buyers Local Market/Trade Sotre Secondary Market Secondary Market Development Project District Large Scale Farm Crop Buyers District Cooperatives Local Farmers Group Local Market/Trade Sotre Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year cont...Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year Locally Produced by Household Neighbour Other Not applicable District Cooperatives Local Farmers Group Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 191 Total Number % Number % Number % Number % Number % Number Tunduru 0 0.0 1,216 2.6 2,673 5.7 0 0.0 42,795 91.3 46,898 Songea Rural 226 0.7 6,296 20.5 2,964 9.6 153 0.5 20,983 68.2 30,772 Mbinga 397 0.5 33,984 43.9 4,025 5.2 0 0.0 38,780 50.1 77,447 Songea Urban 0 0.0 2,043 29.4 491 7.1 0 0.0 4,192 60.4 6,943 Namtumbo 434 1.5 3,308 11.4 1,942 6.7 72 0.2 23,360 80.2 29,115 Total 1,057 0.6 46,848 24.5 12,095 6.3 224 0.1 130,111 68.1 191,175 Total Number % Number % Number % Number % Number % Number % Tunduru 0 0.0 0 0.0 208 0.4 0 0.0 89 0.2 46,602 99.4 46,898 Songea Rural 0 0.0 0 0.0 991 3.2 154 0.5 0 0.0 29,628 96.3 30,772 Mbinga 0 0.0 254 0.3 3,230 4.2 256 0.3 0 0.0 73,707 95.2 77,447 Songea Urban 27 0.4 27 0.4 215 3.1 0 0.0 0 0.0 6,646 96.1 6,915 Namtumbo 0 0.0 0 0.0 783 2.7 72 0.2 0 0.0 28,260 97.1 29,115 Total 27 0.0 281 0.1 5,426 2.8 482 0.3 89 0.0 184,842 96.7 191,147 Number % Number % Number % Number % Number % Tunduru 6,744 14.4 5,744 12.2 6,005 12.8 103 0.2 107 0.2 Songea Rural 757 2.5 0 0.0 2,880 9.4 0 0.0 0 0.0 Mbinga 9,317 12.0 4,190 5.4 20,118 26.0 0 0.0 1,960 2.5 Songea Urban 0 0.0 27 0.4 2,103 30.3 0 0.0 0 0.0 Namtumbo 141 0.5 644 2.2 1,589 5.5 0 0.0 0 0.0 Total 16,959 8.9 10,605 5.5 32,694 17.1 103 0.1 2,067 1.1 Not applicable Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Local Farmers Group Local Market/Trade Store Locally Produced by Household Neighbour Other District Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year Development Project Crop Buyers District Cooperatives Local Market/Trade Store Local Farmers Group cont…..Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Large Scale Farm Locally Produced by Household Neighbour Other Not applicable Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 192 Total Number % Number % Number % Number % Number Tunduru 0 0.0 420 0.9 103 0.2 27,674 59.0 46,898 Songea Rural 76 0.2 223 0.7 0 0.0 26,838 87.2 30,772 Mbinga 264 0.3 2,346 3.0 0 0.0 39,252 50.7 77,447 Songea Urban 0 0.0 0 0.0 0 0.0 4,812 69.3 6,943 Namtumbo 0 0.0 72 0.2 0 0.0 26,670 91.6 29,115 Total 340 0.2 3,060 1.6 103 0.1 125,245 65.5 191,175 Total Number % Number % Number % Number % Number % Number Tunduru 0 0.0 0 0.0 0 0.0 0 0.0 46,898 100.0 46,898 Songea Rural 76 0.2 0 0.0 76 0.2 77 0.3 30,544 99.3 30,772 Mbinga 394 0.5 1,046 1.4 0 0.0 260 0.3 75,746 97.8 77,447 Songea Urban 0 0.0 82 1.2 0 0.0 0 0.0 6,833 98.8 6,915 Namtumbo 0 0.0 0 0.0 0 0.0 0 0.0 29,115 100.0 29,115 Total 470 0.2 1,128 0.6 76 0.0 337 0.2 189,136 98.9 191,147 Neighbour Not applicable Other Not applicable cont...Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Cooperative Local Market/Trade Store Locally Produced by Household Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year District Locally Produced by Household Neighbour Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 193 Number % Number % Number % Number % Number % Number % Number % Tunduru 205 0.4 0 0.0 1,035 2.2 0 0.0 0 0.0 105 0.2 107 0.2 Songea Rural 914 3.0 0 0.0 5,641 18.3 0 0.0 0 0.0 0 0.0 0 0.0 Mbinga 132 0.2 128 0.2 8,765 11.3 110 0.1 129 0.2 0 0.0 0 0.0 Songea Urban 0 0.0 110 1.6 2,378 34.2 0 0.0 0 0.0 55 0.8 0 0.0 Namtumbo 1,298 4.5 0 0.0 3,166 10.9 0 0.0 73 0.2 72 0.2 0 0.0 Total 2,549 1.3 237 0.1 20,984 11.0 110 0.1 201 0.1 232 0.1 107 0.1 Total Number % Number % Number % Number % Number Tunduru 0 0.0 610 1.3 103 0.22 44,734 95.39 46,898 Songea Rural 0 0.0 303 1.0 0 0 23,915 77.72 30,772 Mbinga 0 0.0 773 1.0 0 0 67,411 87.04 77,447 Songea Urban 27 0.4 55 0.8 0 0 4,318 62.19 6,943 Namtumbo 0 0.0 285 1.0 69 0.24 24,152 82.95 29,115 Total 27 0.0 2,026 1.1 171 0.09 164,529 86.06 191,175 Number % Number % Number % Number % Number % Tunduru 4,445 29 816 5 2,520 17 1,681 11 5,642 37 15,104 Songea Rural 3,248 13 1,206 5 3,164 12 8,551 34 9,346 37 25,515 Mbinga 3,209 15 2,709 13 4,792 23 4,525 22 5,555 27 20,791 Songea Urban 240 4 748 11 3,522 54 1,944 30 109 2 6,562 Namtumbo 10,923 46 4,316 18 2,510 10 1,444 6 4,764 20 23,957 Total 22,065 24 9,794 11 16,509 18 18,145 20 25,416 28 91,930 Not applicable Between 10 and 20 km 20 km and Above Total Number District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Large Scale Farm cont...12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Locally Produced by Household Neighbour Other 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year District Cooperative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 194 Number % Number % Number % Number % Number % Tunduru 3,793 92 105 3 205 5 0 0 0 0 4,103 Songea Rural 9,030 92 455 5 304 3 0 0 0 0 9,789 Mbinga 37,360 97 261 1 393 1 520 1 132 0 38,666 Songea Urban 2,504 91 82 3 165 6 0 0 0 0 2,751 Namtumbo 4,959 86 362 6 72 1 362 6 0 0 5,755 Total 57,646 94 1,265 2 1,139 2 882 1 132 0 61,064 Total Number % Number % Number % Number % Number Tunduru 296 100 0 0 0 0 0 0 296 Songea Rural 1,145 100 0 0 0 0 0 0 1,145 Mbinga 3,611 97 0 0 129 3 0 0 3,740 Songea Urban 242 90 27 10 0 0 0 0 269 Namtumbo 642 75 72 8 69 8 72 8 855 Total 5,935 94 100 2 198 3 72 1 6,305 Number % Number % Number % Number % Number % Tunduru 1,023 47 0 0 213 10 0 0 928 43 2,164 Songea Rural 1,135 17 77 1 836 12 1,987 29 2,824 41 6,857 Mbinga 1,603 16 774 8 2,596 26 2,491 25 2,573 26 10,036 Songea Urban 162 6 188 7 1,562 60 685 26 27 1 2,625 Namtumbo 1,578 32 648 13 434 9 362 7 1,941 39 4,963 Total 5,501 21 1,686 6 5,641 21 5,524 21 8,293 31 26,646 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number Between 10 and 20 km 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 195 Less than 1 km Number % Number % Number % Number % Number % Tunduru 11,190 58 1,658 9 1,741 9 2,009 10 2,627 14 19,224 Songea Rural 377 10 302 8 679 17 686 17 1,890 48 3,934 Mbinga 9,191 24 7,858 21 6,113 16 8,522 22 6,511 17 38,195 Songea Urban 0 0 162 8 1,149 54 820 38 0 0 2,130 Namtumbo 854 35 217 9 0 0 218 9 1,156 47 2,445 Total 21,612 33 10,198 15 9,681 15 12,255 19 12,184 18 65,929 Total Number % Number % Number % Number % Number Songea Rural 152 66 0 0 0 0 77 34 228 Mbinga 523 31 391 23 526 31 260 15 1,701 Songea Urban 0 0 82 100 0 0 0 0 82 Total 675 34 474 24 526 26 337 17 2,011 Between 10 and 20 km 20 km and Above Table 12.1.17(b) ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above District Less than 1 km Between 3 and 10 km 12.1.17(a) ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticide/Fungicides by District, 2002/03 Agricultural Year Total Number Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 196 Input is of No Use Number % Number % Number % Number % Number % Number % Number % Tunduru 1,032 3 29,722 93 318 1 106 0 402 1 0 0 213 1 31,793 Songea Rural 832 16 3,965 75 0 0 76 1 154 3 0 0 230 4 5,257 Mbinga 3,504 6 43,769 77 378 1 521 1 8,220 15 263 0 0 0 56,656 Songea Urban 0 0 353 93 0 0 0 0 27 7 0 0 0 0 380 Namtumbo 217 4 4,725 92 144 3 0 0 0 0 0 0 72 1 5,158 Total 5,586 6 82,534 83 840 1 703 1 8,804 9 263 0 515 1 99,245 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 19,156 45 1,355 3 10,661 25 210 0 10,484 24 525 1 104 0 300 1 42,795 Songea Rural 10,527 50 2,444 12 3,129 15 458 2 2,822 13 1,147 5 76 0 381 2 20,983 Mbinga 17,535 45 2,428 6 8,813 23 1,043 3 1,658 4 4,821 12 0 0 2,482 6 38,780 Songea Urban 2,481 59 461 11 1,087 26 54 1 0 0 27 1 0 0 82 2 4,192 Namtumbo 11,503 49 937 4 7,045 30 143 1 3,732 16 0 0 0 0 0 0 23,360 Total 61,202 47 7,625 6 30,736 24 1,908 1 18,696 14 6,520 5 179 0 3,245 2 130,111 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 3,785 8 1,475 3 22,360 48 104 0 17,843 38 413 1 416 1 205 0 46,602 Songea Rural 1,214 4 2,745 9 10,638 36 978 3 11,146 38 1,606 5 228 1 1,072 4 29,628 Mbinga 10,325 14 1,919 3 38,109 52 1,296 2 13,583 18 6,257 8 784 1 1,434 2 73,707 Songea Urban 1,632 24 488 7 3,604 54 55 1 759 11 81 1 0 0 54 1 6,674 Namtumbo 3,900 14 1,446 5 11,821 42 144 1 10,805 38 0 0 73 0 72 0 28,260 Total 20,856 11 8,073 4 86,534 47 2,576 1 54,136 29 8,358 5 1,500 1 2,836 2 184,870 No Money to Buy Total Other 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Input is of No Use Not Available Price Too High Do not Know How to Use Input is of No Use Too Much Labour Required Too Much Labour Required Do not Know How to Use Total Locally Produced by Household Other Other No Money to Buy 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Price Too High 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Locally Produced by Household District Not Available Price Too High No Money to Buy Do not Know How to Use Not Available Total Locally Produced by Household Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 197 Number % Number % Number % Number % Number % Number % Number % Tunduru 2,734 10 23,191 84 211 1 0 0 845 3 692 3 0 0 27,674 Songea Rural 1,900 7 19,069 71 153 1 153 1 2,130 8 3,129 12 304 1 26,838 Mbinga 5,146 13 28,036 71 633 2 132 0 387 1 4,792 12 124 0 39,252 Songea Urban 27 1 3,838 80 160 3 27 1 82 2 677 14 0 0 4,812 Namtumbo 927 3 22,353 84 1,014 4 0 0 1,651 6 652 2 72 0 26,670 Total 10,735 9 96,487 77 2,171 2 313 0 5,096 4 9,942 8 501 0 125,245 Number % Number % Number % Number % Number % Number % Number % Tunduru 7,822 17 30,276 65 106 0 0 0 7,683 16 904 2 107 46,898 Songea Rural 1,897 6 18,002 59 151 0 77 0 4,322 14 5,712 19 383 30,544 Mbinga 6,335 8 51,180 68 886 1 263 0 1,790 2 15,167 20 124 75,746 Songea Urban 242 4 4,304 63 409 6 27 0 680 10 1,171 17 27 6,860 Namtumbo 1,649 6 21,495 74 722 2 0 0 2,082 7 3,168 11 0 29,115 Total 17,946 9 125,257 66 2,274 1 367 0 16,557 9 26,122 14 641 189,163 Number % Number % Number % Number % Number % Number % Number % Number % Tunduru 12,404 28 30,996 69 0 0 0 0 932 2 193 0 105 0 104 0 44,734 Songea Rural 2,276 10 20,346 85 381 2 0 0 533 2 302 1 0 0 76 0 23,915 Mbinga 14,358 21 49,558 74 500 1 132 0 782 1 2,080 3 0 0 0 0 67,411 Songea Urban 134 3 4,046 94 27 1 0 0 0 0 27 1 0 0 82 2 4,318 Namtumbo 2,069 9 20,420 85 579 2 0 0 939 4 145 1 0 0 0 0 24,152 Total 31,242 19 125,367 76 1,488 1 132 0 3,185 2 2,748 2 105 0 262 0 164,529 Other Input is of No Use Total Total 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Other Other Input is of No Use Input is of No Use Locally Produced by Household 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High Too Much Labour Required Do not Know How to Use 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Insecticides/Fungicides by District, 2002/03 Agricultural Year No Money to Buy Total Too Much Labour Required Do not Know How to Use District Not Available Price Too High No Money to Buy Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 198 Number % Number % Number % Number % Tunduru 5,567 37 8,263 55 1,170 8 105 1 15,104 Songea Rural 8,806 35 15,716 62 841 3 152 1 25,515 Mbinga 4,647 22 13,757 66 2,265 11 122 1 20,791 Songea Urban 872 13 5,041 77 543 8 106 2 6,562 Namtumbo 6,419 27 16,965 71 572 2 0 0 23,957 Total 26,311 29 59,743 65 5,392 6 485 1 91,930 Number % Number % Number % Number % Tunduru 1,118 27 2,771 68 213 5 0 0 4,103 Songea Rural 2,806 29 6,219 64 763 8 0 0 9,789 Mbinga 15,310 40 19,689 51 3,668 9 0 0 38,666 Songea Urban 431 16 1,992 72 273 10 55 2 2,751 Namtumbo 1,223 21 3,958 69 503 9 72 1 5,755 Total 20,888 34 34,629 57 5,420 9 127 0 61,064 Number % Number % Number % Songea Rural 0 0 228 100 0 0 228 Mbinga 520 31 921 54 260 15 1,701 Songea Urban 0 0 82 100 0 0 82 Total 520 26 1,231 61 260 13 2,011 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total Average Total Poor Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor District Excellent Good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 199 Number % Number % Number % Number % Number % Tunduru 4,103 21 11,140 58 3,771 20 105 1 105 1 19,224 Songea Rural 1,059 27 2,799 71 77 2 0 0 0 0 3,934 Mbinga 6,531 17 28,542 75 2,342 6 780 2 0 0 38,195 Songea Urban 328 15 1,638 77 110 5 55 3 0 0 2,130 Namtumbo 641 26 1,659 68 145 6 0 0 0 0 2,445 Total 12,661 19 45,778 69 6,444 10 941 1 105 0 65,929 Number % Number % Number % Songea Rural 0 0 228 100 0 0 228 Mbinga 520 31 921 54 260 15 1,701 Songea Urban 0 0 82 100 0 0 82 Total 520 26 1,231 61 260 13 2,011 Agricultural Households With Plan to use Chemical Fertilizers Next Year Agricultural Households With NO Plan to use Next Year Chemical Fertilizers Number % Number % Number % Number % Number % Number % Tunduru 838 39 1,222 56 104 5 0 0 2,164 Tunduru 25,472 54 21,425 46 46,898 Songea Rural 1,830 27 4,797 70 230 3 0 0 6,857 Songea Rural 27,346 89 3,426 11 30,772 Mbinga 3,075 31 6,307 63 522 5 131 1 10,036 Mbinga 35,197 45 42,250 55 77,447 Songea Urban 383 15 2,025 77 190 7 27 1 2,625 Songea Urban 6,725 97 218 3 6,943 Namtumbo 569 11 4,322 87 72 1 0 0 4,963 Namtumbo 26,692 92 2,424 8 29,115 Total 6,695 25 18,673 70 1,118 4 159 1 26,646 Total 121,432 64 69,742 36 191,175 Poor Does not Work 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Insecticides/Fungicides by District, 2002/03 Agricultural Year Total District Excellent Good Average Total District Excellent Good Average Total 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizer Next Year by District, 2002/03 Agricultural Year Total District District Excellent Good Average Poor 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 200 Number % Number % Number % Number % Tunduru 5,253 11 41,644 89 46,898 Tunduru 1,563 3 45,334 97 46,898 Songea Rural 10,793 35 19,979 65 30,772 Songea Rural 2,134 7 28,639 93 30,772 Mbinga 46,041 59 31,405 41 77,447 Mbinga 8,553 11 68,894 89 77,447 Songea Urban 3,079 44 3,864 56 6,943 Songea Urban 516 7 6,427 93 6,943 Namtumbo 7,194 25 21,921 75 29,115 Namtumbo 1,065 4 28,050 96 29,115 Total 72,361 38 118,814 62 191,175 Total 13,832 7 177,343 93 191,175 Number % Number % Number % Number % Tunduru 24,030 51 22,868 49 46,898 Tunduru 1,153 2 45,745 98 46,898 Songea Rural 5,238 17 25,535 83 30,772 Songea Rural 993 3 29,780 97 30,772 Mbinga 42,719 55 34,728 45 77,447 Mbinga 4,445 6 73,002 94 77,447 Songea Urban 2,159 31 4,784 69 6,943 Songea Urban 165 2 6,778 98 6,943 Namtumbo 3,093 11 26,023 89 29,115 Namtumbo 647 2 28,468 98 29,115 Total 77,237 40 113,938 60 191,175 Total 7,403 4 183,772 96 191,175 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Farm Yard Manure Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use COMPOST ManureNext Year Agricultural Households With NO Plan to use COMPOST Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Pesticides/Fungicides Next Year Agricultural Households With NO Plan to use Pesticides/FungicidesNe xt Year Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Insecticides/Fungicides Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Herbicides Next Year g Households With NO Plan to use Herbicides Next Year Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 201 Number % Number % Tunduru 6,578 14 40,320 86 46,898 Songea Rural 8,753 28 22,019 72 30,772 Mbinga 23,214 30 54,233 70 77,447 Songea Urban 2,734 39 4,209 61 6,943 Namtumbo 6,764 23 22,351 77 29,115 Total 48,043 25 143,132 75 191,175 Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households with Plan to Use Improved Seeds Next Year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Improved Seeds Next Year Agricultural Households With NO Plan to use Improved Seeds Next Year Total Tanzania Agriculture Sample Census - 2003 Ruvuma 202 Appendix II 203 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 204 Number % Number % Tunduru 2,992 93 212 7 3,204 Songea Rural 4,149 70 1,813 30 5,962 Mbinga 12,568 91 1,302 9 13,870 Songea Urban 566 78 161 22 727 Namtumbo 12,664 86 2,140 14 14,804 Total 32,939 85 5,628 15 38,567 Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Trader / Trade Store Private Individual Religious Organisati on / NGO / Project Other Total Tunduru 609 0 1,244 1,246 105 0 0 0 3,204 Songea Rural 2,621 77 1,137 678 150 380 920 0 5,962 Mbinga 7,228 260 3,550 390 1,693 378 239 132 13,870 Songea Urban 399 0 54 27 165 53 27 0 727 Namtumbo 4,498 72 8,868 73 433 141 650 69 14,804 Total 15,355 408 14,853 2,414 2,547 953 1,836 201 38,567 District 13.1a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year Total District Male Female Source of Credit 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Main Source of Credit and District; 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 205 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Tunduru 98 14,650 2,479 931 15,586 1,576 104 204 7,960 43,587 Songea Rural 841 6,926 3,345 1,978 6,687 1,746 77 76 3,134 24,810 Mbinga 3,117 19,364 5,403 2,223 20,840 1,279 517 0 10,834 63,577 Songea Urban 246 684 1,137 330 2,077 515 27 81 1,119 6,216 Namtumbo 937 1,445 4,388 3,454 2,153 577 72 145 1,140 14,311 Total 5,238 43,069 16,752 8,916 47,344 5,694 797 506 24,187 152,501 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Tunduru 507 0 726 2,274 0 0 98 0 3,606 Songea Rural 1,049 611 4,383 454 305 77 227 226 7,331 Mbinga 2,951 634 3,375 4,195 1,699 0 1,435 1,547 15,837 Songea Urban 187 136 512 54 0 0 53 27 971 Namtumbo 2,422 1,484 9,734 214 71 0 0 1,661 15,586 Total Credits 7,117 2,866 18,730 7,191 2,075 77 1,814 3,462 43,331 13.2a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year District Credit Use 13.2b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Ruvuma 206 Appendix II 207 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 208 District Senna Spp Gravellis Afzelia Quanzensi s Acacia Spp Pinus Spp Eucalyptu s Spp Cyprus Spp Calophylu m Inophyllu m Melicia excelsa Casurina Equisetfili a Terminalia Catapa Songea Rural 245 341 . 181 1422 352 44 1058 60 . . Mbinga 1046 5220 . 1342 900 58739 9865 40 10 . 59 Songea Urban 164 55 5 760 3 7638 322 3230 61 16 25 Namtumbo 1195 60 20 . . 114 130 . 35 . . Total 2650 5676 25 2283 2325 66843 10361 4328 166 16 84 % 3 6 0 2 2 70 11 5 0 0 0 District Terminalia Ivorensis Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Albizia Spp Kyaya Spp Sesbania Spp Calliandra Spp Trichilia Spp Total Songea Rural . 71 . 1 10 267 166 . 10 . 4228 Mbinga 50 6 . 13 . 4 . . . 11 77305 Songea Urban . . 55 2 . 19 . 3 . . 12358 Namtumbo . . . 113 146 . . . . . 1813 Total 50 77 55 129 156 290 166 3 10 11 95704 % 0 0 0 0 0 0 0 0 0 0 100 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Region cont… ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Ruvuma Regiont Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 209 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Songea Rural 62 1,393 32 687 13 2,148 107 4,228 Mbinga 35 9,505 93 12,643 91 55,157 219 77,305 Songea Urban 74 1,769 38 1,979 16 8,590 128 12,338 Namtumbo 32 904 8 209 5 700 45 1,813 Total 203 13,571 171 15,518 125 66,595 499 95,684 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Total Songea Rural 114 4 0 8 3 2 264 Mbinga 52 31 1 85 120 1 582 Songea Urban 136 2 0 36 15 1 382 Namtumbo 30 0 0 19 8 0 114 Total 332 37 1 148 146 4 1,342 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region District 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Ruvuma Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Main Use Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 210 1-9 1-19 20-29 30-39 40-49 60+ Total Tunduru 0 104 0 0 0 0 104 Songea Rural 4,641 1,141 1,607 672 381 606 9,047 Mbinga 7,314 3,892 3,109 2,345 1,559 1,034 19,252 Songea Urban 165 247 275 55 27 0 769 Namtumbo 862 354 502 837 142 72 2,768 Total 12,982 5,738 5,492 3,908 2,109 1,712 31,940 % 41 18 17 12 7 5 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Songea Rural 11 5 0 106 8 0 2 132 Mbinga 63 64 5 137 9 1 12 291 Songea Urban 20 10 1 131 19 1 9 191 Namtumbo 8 7 0 19 21 0 2 57 Total 102 86 6 393 57 2 25 671 District Second Use 14.4TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Ruvuma Region District Distance to Community Planted Forest (km) 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture year, Ruvuma Region Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 211 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 212 Number % Number % Tunduru 14,048 30 32,849 70 46,898 Songea Rural 7,223 23 23,549 77 30,772 Mbinga 27,165 35 50,281 65 77,447 Songea Urban 2,805 40 4,138 60 6,943 Namtumbo 15,958 55 13,158 45 29,115 Total 67,199 35 123,975 65 191,175 Number % Number % Number % Number % Number % Number % Tunduru 529 4 9,313 66 4,100 29 106 1 0 0 14,048 100 Songea Rural 228 3 5,317 74 1,678 23 0 0 0 0 7,223 100 Mbinga 3,638 14 18,592 69 3,762 14 385 1 525 2 26,901 100 Songea Urban 215 8 2,398 85 192 7 0 0 0 0 2,805 100 Namtumbo 2,581 16 10,349 65 2,235 14 577 4 143 1 15,886 100 Total 7,192 11 45,969 69 11,967 18 1,068 2 668 1 66,864 100 Number % Number % Number % Number % Number % Number % Number % Tunduru 13,146 94 213 2 98 1 291 2 300 2 0 0 14,048 100 Songea Rural 6,696 93 299 4 153 2 76 1 0 0 0 0 7,223 100 Mbinga 22,524 83 780 3 767 3 1,695 6 480 2 790 3 27,037 100 Songea Urban 2,618 93 0 0 27 1 0 0 160 6 0 0 2,805 100 Namtumbo 14,093 88 499 3 861 5 432 3 72 0 0 0 15,958 100 Total 59,075 88 1,791 3 1,907 3 2,495 4 1,013 2 790 1 67,071 100 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region District Source of Crop Extension 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Ruvuma Region Very Good Good Average Poor No Good Total 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Ruvuma Region District Households Receiving Extension Households Not Receiving Extension Total Number of Households Other Not applicable Total Government NGO / Development Project Cooperative Large Scale Farm Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 213 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Tunduru 11,058 213 98 98 212 0 11,679 46,898 24.9 Songea Rural 5,557 223 153 76 0 0 6,009 30,772 19.5 Mbinga 15,456 396 378 1,431 480 790 18,931 77,447 24.4 Songea Urban 2,482 0 27 0 133 0 2,643 6,943 38.1 Namtumbo 13,230 358 789 72 72 0 14,522 29,115 49.9 Total 47,783 1,189 1,446 1,677 898 790 53,783 191,175 28.1 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 8,511 106 203 208 89 104 9,221 46,898 19.7 Songea Rural 1,605 754 76 76 0 0 2,510 30,772 8.2 Mbinga 14,516 772 642 392 0 132 16,454 77,447 21.2 Songea Urban 1,337 0 0 27 0 0 1,364 6,943 19.7 Namtumbo 7,277 72 649 72 0 0 8,070 29,115 27.7 Total 33,246 1,703 1,569 776 89 236 37,619 191,175 19.7 Government NGO / Developmen t Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 1,375 0 0 98 0 0 1,473 46,898 3.1 Songea Rural 1,458 151 0 0 0 76 1,684 30,772 5.5 Mbinga 8,328 252 124 521 131 656 10,014 77,447 12.9 Songea Urban 795 0 0 27 55 0 877 6,943 12.6 Namtumbo 5,332 72 72 72 0 145 5,692 29,115 19.6 Total 17,287 475 196 719 186 877 19,741 191,175 10.3 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Use of Agrochemicals Total Number of Households District District Spacing Total Total Number of Households % of total number of households % of total number of households % of total number of households 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agrochemicals by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Erosion Control Total Number of Households District Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 214 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,790 0 203 104 0 0 4,097 46,898 9 Songea Rural 3,428 831 0 0 0 0 4,259 30,772 14 Mbinga 17,833 513 775 791 131 128 20,172 77,447 26 Songea Urban 1,552 55 0 0 137 0 1,744 6,943 25 Namtumbo 8,694 72 72 360 0 142 9,341 29,115 32 Total 35,298 1,471 1,050 1,256 268 270 39,612 191,175 21 Government NGO / Development Cooperative Large Scale Other Not applicable Total Tunduru 7,873 213 0 210 0 0 8,296 46,898 18 Songea Rural 4,269 754 151 77 0 76 5,327 30,772 17 Mbinga 11,851 265 630 790 0 260 13,796 77,447 18 Songea Urban 2,014 27 0 0 27 0 2,069 6,943 30 Namtumbo 11,354 505 2,448 0 142 0 14,448 29,115 50 Total 37,362 1,763 3,229 1,076 170 336 43,936 191,175 23 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,466 213 0 0 0 0 3,678 46,898 8 Songea Rural 3,500 601 153 153 0 0 4,407 30,772 14 Mbinga 11,574 132 373 0 0 265 12,344 77,447 16 Songea Urban 1,828 0 0 55 82 0 1,965 6,943 28 Namtumbo 9,270 789 575 216 72 0 10,921 29,115 38 Total 29,638 1,735 1,101 423 154 265 33,316 191,175 17 Total Number of Households 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Organic Fertilizer Use Inorganic Fertilizer Use District % of total number of households Use of Improved Seed District District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households Total Number of Households % of total number of households % of total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 215 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Tunduru 723 104 0 106 0 934 46,898 2 Songea Rural 308 153 0 76 0 537 30,772 2 Mbinga 1,022 0 0 0 643 1,665 77,447 2 Songea Urban 27 0 0 0 0 27 6,943 0 Namtumbo 4,467 0 72 0 145 4,683 29,115 16 Total 6,547 257 72 182 788 7,846 191,175 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 2,952 0 0 89 0 105 3,146 46,898 7 Songea Rural 1,987 0 0 0 0 0 1,987 30,772 6 Mbinga 4,695 128 124 124 131 529 5,732 77,447 7 Songea Urban 1,172 0 0 0 110 0 1,281 6,943 18 Namtumbo 7,421 72 0 287 0 0 7,780 29,115 27 Total 18,226 200 124 501 241 634 19,926 191,175 10 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 5,500 0 0 0 212 0 5,712 46,898 12 Songea Rural 2,967 151 0 76 0 0 3,194 30,772 10 Mbinga 9,626 128 124 260 260 917 11,315 77,447 15 Songea Urban 1,823 0 0 0 192 27 2,043 6,943 29 Namtumbo 8,993 145 215 0 71 0 9,424 29,115 32 Total 28,910 424 339 335 735 945 31,688 191,175 17 Crop Storage District District District Mechanisation / LST Total Number of Households 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Mechanization/LST by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region % of total number of households % of total number of households 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Irrigation Technology by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Crop Storage by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region % of total number of households Total Number of Households Total Number of Households Irrigation Technology Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 216 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tunduru 1,155 0 0 0 105 0 46,898 0.00 Songea Rural 1,760 227 0 0 0 0 30,772 0.00 Mbinga 5,971 0 124 128 0 657 77,447 0.85 Songea Urban 876 0 0 0 55 0 6,943 0.00 Namtumbo 7,200 72 215 288 71 69 29,115 0.24 Total 16,962 298 340 416 231 726 191,175 0.38 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 3,806 0 98 0 0 0 3,905 46,898 8 Songea Rural 1,683 152 0 0 0 0 1,835 30,772 6 Mbinga 4,578 0 385 260 131 917 6,272 77,447 8 Songea Urban 814 0 0 0 247 27 1,089 6,943 16 Namtumbo 6,905 72 144 72 0 0 7,193 29,115 25 Total 17,787 224 628 332 379 945 20,294 191,175 11 Government NGO / Development Project Cooperative Other Not applicable Total Tunduru 312 0 0 0 0 312 46,898 1 Songea Rural 999 149 0 0 0 1,148 30,772 4 Mbinga 5,595 256 124 260 397 6,632 77,447 9 Songea Urban 653 82 0 27 0 762 6,943 11 Namtumbo 6,331 215 0 0 0 6,546 29,115 22 Total 13,889 702 124 287 397 15,400 191,175 8 % of total number of households District Agro-progressing Agro-forestry District District Total Number of Households % of total number of households 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Vermin Control by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Agro-processing by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households % of total number of households Total Number of Households Vermin Control Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 217 Government NGO / Development Project Large Scale Farm Other Not applicable Total Tunduru 105 0 0 0 0 105 46,898 0 Songea Rural 308 0 0 0 0 308 30,772 1 Mbinga 785 256 0 0 265 1,306 77,447 2 Songea Urban 191 165 27 27 0 411 6,943 6 Namtumbo 5,331 359 0 0 0 5,690 29,115 20 Total 6,720 780 27 27 265 7,819 191,175 4 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Tunduru 0 0 0 0 0 0 0 46898 0 Songea Rural 536 153 74 0 0 0 763 30772 2 Mbinga 1,313 128 0 0 0 265 1,706 77447 2 Songea Urban 301 302 0 0 27 0 631 6943 9 Namtumbo 5,268 216 0 69 73 72 5,698 29115 20 Total 7,419 798 74 69 100 336 8,797 191175 5 Received Adopted % Received Adopted % Received Adopted % Tunduru 11,679 11,581 99 9,117 6,259 69 1,369 0 0 Songea Rural 5,932 5,702 96 2,433 1,674 69 1,608 1,610 100 Mbinga 18,008 17,888 99 15,804 13,718 87 9,355 6,234 67 Songea Urban 2,670 2,507 94 1,419 1,118 79 877 713 81 Namtumbo 14,522 14,235 98 7,784 2,885 37 5,185 2,162 42 Total 52,811 51,912 98 36,557 25,653 70 18,394 10,719 58 Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Fish Farming by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region Beekeeping District District 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee keeping by Source of Extension Messages and District During the 2002/03 Agriculture Year, Ruvuma Region District Use of Agrochemicals Erosion Control Spacing 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Ruvuma Region Total Number of Households % of total number of households Total Number of Households % of total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 218 Received Adopted % Received Adopted % Received Adopted % Tunduru 3,780 1,359 36 8,189 5,757 70 3,678 1,356 37 Songea Rural 3,800 3,193 84 5,480 5,252 96 4,407 2,652 60 Mbinga 20,036 17,308 86 13,381 10,882 81 11,946 6,071 51 Songea Urban 1,689 1,444 85 2,124 2,015 95 1,965 1,503 76 Namtumbo 8,479 3,167 37 14,594 14,233 98 10,994 5,398 49 Total 37,782 26,472 70 43,768 38,140 87 32,991 16,980 51 Received Adopted % Received Adopted % Received Adopted % Tunduru 410 0 0 2,619 822 31 5,712 4,759 83 Songea Rural 613 0 0 1,987 1,068 54 3,194 2,965 93 Mbinga 388 1,171 302 4,155 3,374 81 10,778 10,657 99 Songea Urban 27 27 100 1,281 1,118 87 2,070 1,907 92 Namtumbo 4,393 216 5 7,780 3,892 50 9,208 8,850 96 Total 5,832 1,415 24 17,821 10,275 58 30,963 29,139 94 Received Adopted % Received Adopted % Received Adopted % Tunduru 1,155 1,045 90 3,691 3,697 100 104 0 0 Songea Rural 1,987 1,759 89 1,835 1,610 88 1,148 1,148 100 Mbinga 5,055 5,839 115 5,865 6,387 109 6,231 4,141 66 Songea Urban 960 0 1,062 1,062 100 790 653 83 Namtumbo 7,842 6,843 87 7,051 6,325 90 6,546 2,006 31 Total 16,999 16,254 96 19,504 19,080 98 14,819 7,947 54 District District District Organic Fertilizer Use Vermin Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Ruvuma Region Agro-progressing Use of Improved Seed Crop Storage Agro-forestry 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Ruvuma Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Ruvuma Region Inorganic Fertilizer Use Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 219 Received Adopted % Received Adopted % Tunduru 0 0 0 0 0 0 Songea Rural 308 0 0 610 302 50 Mbinga 1,041 909 87 1,309 649 50 Songea Urban 357 0 0 658 191 29 Namtumbo 5,546 506 9 5,554 866 16 Total 7,252 1,415 20 8,131 2,009 25 Fish Farming 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Ruvuma Region District Beekeeping Tanzania Agriculture Sample Census - 2003 Ruvuma 220 Appendix II 221 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 222 Number % Number % Tunduru 0 0 46,898 100 46,898 Songea Rural 76 0 30,697 100 30,772 Mbinga 0 0 77,447 100 77,447 Songea Urban 27 0 6,915 100 6,943 Namtumbo 69 0 29,046 100 29,115 Total 172 0 191,003 100 191,175 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Songea Rural . . . . . . Songea Urban 55 55 33 . . . Namtumbo . . . . 757 Total 55 55 33 . 757 . Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Songea Rural 227 151 0 227 151 0 Songea Urban . . . 55 55 33 Namtumbo . . . . 757 . Total 227 151 0 282 963 33 Number % Number % Number % Tunduru 3,668 7 43,230 32 46,898 25 Songea Rural 8,799 16 20,903 16 29,701 16 Mbinga 35,657 65 41,299 31 76,956 41 Songea Urban 1,878 3 5,038 4 6,915 4 Namtumbo 4,532 8 23,792 18 28,325 15 Total 54,534 100 134,261 100 188,795 100 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Ruvuma Region Households Using Draft Animals Household Not Using Draft Animals Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region District Oxen Type of Craft Bulls Type of Craft District cont… ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (Hectares) By District during 2002/03 agriculture year, Ruvuma Region 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Ruvuma Region Cows Total District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 223 Area (Ha) % Area (Ha) % Area (Ha) % Tunduru 1,439 6 56 5 1,495 6 Songea Rural 1,842 8 117 10 1,959 8 Mbinga 17,255 78 835 74 18,089 77 Songea Urban 585 3 17 2 602 3 Namtumbo 1,108 5 99 9 1,207 5 Total 22,227 100 1,124 100 23,351 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Ruvuma Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census - 2003 Ruvuma 224 Appendix II 225 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 226 Number % Number % Tunduru 501 1 46,397 99 46,898 5,276 Songea Rural 2,269 7 28,503 93 30,772 8,578 Mbinga 12,325 16 65,122 84 77,447 25,335 Songea Urban 734 11 6,209 89 6,943 1,799 Namtumbo 1,008 3 28,107 97 29,115 8,567 Total 16,837 9 174,338 91 191,175 49,556 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Tunduru 205 3,536 87.5 0 . 0.00 296 504 12.5 501 4,040 3.3 Songea Rural 1,293 7,853 70.3 153 153 0.00 1,204 3,157 0.0 2,269 11,164 9.2 Mbinga 10,797 93,097 92.3 0 . 0.00 2,575 7,810 7.7 12,325 100,907 83.3 Songea Urban 325 894 39.7 27 27 0.00 462 1,329 59.1 734 2,250 1.9 Namtumbo 289 504 17.9 0 . 0.00 864 2,311 82.1 1,008 2,815 2.3 Total 12,909 105,884 87.4 181 181 0.15 5,401 15,111 12.5 16,837 121,175 100.0 Number % Number % 1-5 15,088 90 36,610 30 2 6-10 1,009 6 7,464 6 7 11-15 297 2 3,667 3 12 16-20 130 1 2,076 2 16 21-30 107 1 2,453 2 23 31-40 77 0 2,539 2 33 151+ 129 1 66,366 55 513 Total 16,837 100 121,175 100 7 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Ruvuma Region Distcrict Households Rearing Cattle Households Not Rearing Cattle Total Agriculture households Total livestock keeping households 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Dairy Total Cattle Improved Beef 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 1st October, 2003 Cattle Rearing Households Heads of Cattle Average Number Per Household Herd Size Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 227 Number % Number % Number % Number % Bulls 6,792 78.3 27 0.3 1,853 21.4 8,673 7.2 Cows 18,705 76.5 76 0.3 5,658 23.2 24,440 20.2 Steers 187 71.2 . 0.0 76 0.0 263 0.2 Heifers 70,178 95.8 . 0.0 3,077 4.2 73,256 60.5 Male Calves 5,362 68.3 77 1.0 2,414 30.7 7,853 6.5 Female Calves 4,658 69.6 . 0.0 2,033 30.4 6,691 5.5 Total 105,884 87.4 181 0.1 15,111 12.5 121,175 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru 312 1,879 . 107 632 607 3,536 Songea Rural 1,611 2,831 . 1,815 909 687 7,853 Mbinga 4,789 13,508 132 67,922 3,643 3,102 93,097 Songea Urban 80 272 55 190 107 191 894 Namtumbo . 216 . 144 72 72 504 Total 6,792 18,705 187 70,178 5,362 4,658 105,884 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru . . . . . . . Songea Rural . 76 . . 77 . 153 Mbinga . . . . . . . Songea Urban 27 . . . . . 27 Namtumbo . . . . . . . Total 27 76 . . 77 . 181 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Cattle mproved Beef Cattle Improved Dairy Cattle Category of Cattle 18.6 CATTLE PRODUCTION: Number of Improved Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 228 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru . 207 . 89 104 103 504 Songea Rural 299 1,201 76 380 747 455 3,157 Mbinga 874 2,924 . 1,948 1,022 1,043 7,810 Songea Urban 245 459 . 301 107 216 1,329 Namtumbo 435 866 . 360 434 216 2,311 Total 1,853 5,658 76 3,077 2,414 2,033 15,111 Bulls Cows Steers Heifers Male Calves Female Calves Total Tunduru 312 2,086 . 195 736 710 4,040 Songea Rural 1,910 4,109 76 2,195 1,733 1,142 11,164 Mbinga 5,663 16,432 132 69,870 4,664 4,145 100,907 Songea Urban 353 731 55 491 214 407 2,250 Namtumbo 435 1,082 . 504 505 288 2,815 Total 8,673 24,440 263 73,256 7,853 6,691 121,175 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Improved Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 229 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 230 Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Number of Households Number of Goats % Tunduru 6,145 42,927 98.6 104 622 1.4 0 . 0.0 6,145 43,548 14.1 Songea Rural 13,477 57,045 93.8 229 1,221 0.0 460 2,524 4.2 13,477 60,790 19.6 Mbinga 32,782 121,530 99.2 394 527 0.0 250 508 0.4 32,782 122,564 39.6 Songea Urban 2,428 9,720 96.8 81 108 1.1 81 216 2.1 2,455 10,044 3.2 Namtumbo 13,450 71,144 97.9 289 1,006 1.4 286 499 0.7 13,522 72,649 23.5 Total 68,282 302,365 97.7 1,097 3,483 1.1 1,078 3,747 1.2 68,381 309,595 100.0 Number % Number % 1-4 42,519 62 104,318 34 2 5-9 20,673 30 129,592 42 6 10-14 2,948 4 32,845 11 11 15-19 1,435 2 23,169 7 16 20-24 418 1 8,552 3 20 25-29 212 0 5,835 2 27 30-39 176 0 5,285 2 30 Total 68,381 100 309,595 100 5 Total Goat District 19.1 GOAT PRODUCTION: Total Number of Goats by Type and District as on 1st October, 2003 19.2 GOAT PRODUCTION: Number of Households Rearing Goats by Herd Size on 1st October, 2003 Improved Dairy Improved for Meat Indigenous Herd Size Goat Rearing Households Head of Goats Average Number Per Household Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 231 19.3 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District Number % Number % Number % Number % Billy Goat 46,354 97.3 507 1.1 779 1.6 47,640 15.4 Castrated Goat 2,805 77.5 427 0.0 386 0.0 3,617 1.2 She Goat 175,170 99.5 492 0.3 446 0.3 176,108 56.9 Male Kid 34,555 96.3 591 1.6 719 2.0 35,865 11.6 She Kid 43,481 93.8 1,466 3.2 1,417 3.1 46,365 15.0 Total 302,365 97.7 3,483 1.1 3,747 1.2 309,595 100.0 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru 6,252 422 21,475 6,927 7,851 42,927 Songea Rural 8,826 154 34,332 5,999 7,734 57,045 Mbinga 18,493 1,529 74,987 12,801 13,719 121,530 Songea Urban 1,528 . 5,354 1,035 1,803 9,720 Namtumbo 11,255 701 39,022 7,792 12,374 71,144 Total 46,354 2,805 175,170 34,555 43,481 302,365 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru . . . . 622 622 Songea Rural . . 228 461 533 1,221 Mbinga . . 265 131 131 527 Songea Urban . . . . 108 108 Namtumbo 507 427 . . 73 1,006 Total 507 427 492 591 1,466 3,483 Improved Dairy Goats 19.5 GOAT PRODUCTION: Number of Improved Goat for Meat by Category and District as on 1st October, 2003 District Number of Improved Meat Goats Total Category of Goats 19.4 Total Number of Indigenous Goat by Category and District as on 1st October, 2003 District Number of Indigenous Goats Improved Meat Goats Indigenous Goats Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 232 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru . . . . . . Songea Rural 537 . 77 692 1,218 2,524 Mbinga . 386 122 . . 508 Songea Urban 27 . 108 27 54 216 Namtumbo 215 . 139 . 145 499 Total 779 386 446 719 1,417 3,747 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Tunduru 6,252 422 21,475 6,927 8,472 43,548 Songea Rural 9,362 154 34,636 7,152 9,486 60,790 Mbinga 18,493 1,915 75,373 12,932 13,851 122,564 Songea Urban 1,555 . 5,462 1,062 1,965 10,044 Namtumbo 11,977 1,127 39,161 7,792 12,591 72,649 Total 47,640 3,617 176,108 35,865 46,365 309,595 District Total Goat 19.6 Number of Improved Dairy Goat by Category and District on 1st October, 2003 District Number of Improved Dairy Goats 19.7 Total Number of Goats by Category and District on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 233 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 234 Number % Number % Number % Ram 3,840 100 . 0 3,840 16 Castrated Sheep 179 100 . 0 179 1 She Sheep 14,616 100 . 0 14,616 60 Male Lamb 1,918 67 924 0 2,842 12 She Lamb 2,980 100 . 0 2,980 12 Total 23,534 96 924 4 24,458 100 Number % Number % Tunduru 1,446 3 45,452 97 46,898 5,276 Songea Rural 1,135 4 29,637 96 30,772 8,578 Mbinga 4,438 6 73,008 94 77,447 25,335 Songea Urban 82 1 6,860 99 6,943 1,799 Namtumbo 288 1 28,827 99 29,115 8,567 Total 7,390 4 183,785 96 191,175 49,556 Number % Number % Number % Tunduru 5,671 100 . 0 5,671 23 Songea Rural 4,070 100 . 0 4,070 17 Mbinga 12,148 93 924 7 13,073 53 Songea Urban 275 100 . 0 275 1 Namtumbo 1,371 100 . 0 1,371 6 Total 23,534 96 924 4 24,458 100 Herd Size Number of Household % Number of Sheep % Average Number Per Household 1-4 5,621 77 13,430 55 2 5-9 1,506 21 9,705 40 6 10-14 132 2 1,323 5 10 Total 7,258 100 24,458 100 3 20.1 Total Number of Sheep By Breed and on 1st October 2003 20.4 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October, 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agricultural Households Total Livestock keeping Households Breed Number of Indigenous District 20.3 Number of Sheep by Type of Sheep and District as 1st October, 2002/03 Number of Improved for Mutton Total Sheep Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 235 Number of Households Average Number of Households Average Number of Households Average Tunduru 1,446 4 0 . 1,446 4 Songea Rural 1,135 4 0 . 1,135 4 Mbinga 4,176 3 263 4 4,307 3 Songea Urban 82 3 0 . 82 3 Namtumbo 288 5 0 . 288 5 Total 7,128 3 263 4 7,258 3 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru 799 . 3,301 628 943 5,671 Songea Rural 830 . 2,639 303 299 4,070 Mbinga 1,969 124 7,718 915 1,421 12,148 Songea Urban 27 55 165 . 27 275 Namtumbo 216 . 794 72 289 1,371 Total 3,840 179 14,616 1,918 2,980 23,534 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru . . . . . . Songea Rural . . . . . . Mbinga . . . 924 . 924 Songea Urban . . . . . . Namtumbo . . . . . . Total . . . 924 . 924 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Tunduru 799 . 3,301 628 943 5,671 Songea Rural 830 . 2,639 303 299 4,070 Mbinga 1,969 124 7,718 1,840 1,421 13,073 Songea Urban 27 55 165 . 27 275 Namtumbo 216 . 794 72 289 1,371 Total 3,840 179 14,616 2,842 2,980 24,458 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Ruvuma Region District Number of Indigenous Number of Improved for Mutton Total Sheep Tanzania Agriculture Sample Census - 2003 Ruvuma 236 Appendix II 237 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 238 Number % Number % 1-4 45,332 86 80,159 59 2 5-9 5,941 11 37,676 28 6 10-14 1,262 2 13,447 10 11 15-19 211 0 3,669 3 17 Total 52,746 100 134,951 100 3 District Number of Household Number of Pig Average Number Per Household Mbinga 40,973 102,373 2 Songea Rural 8,397 20,763 2 Namtumbo 2,439 6,909 3 Songea Urban 849 3,308 4 Tunduru 89 1,598 18 Total 52,746 134,951 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Tunduru 89 . 621 355 533 1,598 Songea Rural 2,677 2,217 7,630 2,596 5,642 20,763 Mbinga 15,232 5,861 39,488 16,512 25,280 102,373 Songea Urban 899 218 901 494 796 3,308 Namtumbo 1,006 576 3,450 650 1,228 6,909 Total 19,903 8,872 52,090 20,607 33,479 134,951 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type and District on 1st October, 2003 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 Average Number Per Household Herd Size Pig Rearing Households Heads of Pigs Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 239 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 240 Number of Households % Number of Households % Tunduru 1,310 26 3,756 74 5,066 Songea Rural 4,495 52 4,082 48 8,578 Mbinga 11,855 47 13,349 53 25,203 Songea Urban 820 49 845 51 1,664 Namtumbo 2,666 31 5,902 69 8,567 Total 21,145 43 27,933 57 49,078 Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 826 17 404 4 396 18 193 2 Songea Rural 1,221 26 2,434 22 381 18 2,444 20 Mbinga 1,674 35 6,046 55 1,028 47 8,248 67 Songea Urban 329 7 354 3 82 4 438 4 Namtumbo 719 15 1,804 16 287 13 1,008 8 Total 4,770 100 11,042 100 2,175 100 12,331 100 Number of Households % Number of Households % Tunduru 906 19 3,845 81 4,751 Songea Rural 2,814 33 5,611 67 8,425 Mbinga 9,358 39 14,594 61 23,952 Songea Urban 302 20.9 1,146 79 1,448 Namtumbo 1,661 21.1 6,201 79 7,863 Total 15,041 32 31,397 68 46,438 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 510 56 194 21 98 11 103 11 0 0 906 Songea Rural 917 33 1,209 43 153 5 0 0 536 19 2,814 Mbinga 2,212 24 4,156 44 789 8 132 1 2,069 22 9,358 Songea Urban 55 18 220 73 0 0 0 0 27 9 302 Namtumbo 723 44 649 39 0 0 0 0 289 17 1,661 Total 4,417 29 6,428 43 1,041 7 235 2 2,921 19 15,041 Dipping Smearing Other 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Ticks Control Use and District During the 2002/03 Agricultural Year Method of Tick Control Total District None Spraying District Ticks Problems No Ticks Problems Total 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District. 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year District Goats Cattle Sheep Pigs 22.1 PESTS AND PARASITE: Number of Livestock Rearing households deworming Livestock by District during 2002/03 Agricultural Year District Deworming Livestock Not Deworming Livestock Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 241 Number of Households % Number of Households % Tunduru 1,023 20 4,042 80 5,066 Songea Rural 1,220 14 7,358 86 8,578 Mbinga 3,350 14 20,327 86 23,677 Songea Urban 110 7 1,393 93 1,503 Namtumbo 1,230 15 6,848 85 8,078 Total 6,933 15 39,968 85 46,902 Number of Households % Number of Households % Number of Households % Number of Households % Tunduru 611 60 308 30 0 0 104 10 1,023 Songea Rural 764 63 456 37 0 0 0 0 1,220 Mbinga 2,303 69 916 27 132 4 0 0 3,350 Songea Urban 27 25 82 75 0 0 0 0 110 Namtumbo 868 71 362 29 0 0 0 0 1,230 Total 4,574 66 2,124 31 132 2 104 1 6,933 Trapping Method of Tsetse Flies Control 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number of Livestock Rearing Households by Methods of Tsetse flies Control Use and District During the 2002/03 Agricultural Year Total District None Spray Dipping District Tsetse Flies Problems No Tsetse Flies Problems 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered Tsetse Flies problems during 2002/03 Agriculture Year by District Total Tanzania Agriculture Sample Census - 2003 Ruvuma 242 Appendix II 243 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 244 Number % Type Number Indigenous 1,536,330 99 Ducks 38,878 Layer 6,037 0 Turkeys 868 Broiler 13,250 1 Rabbits 42,163 . . . Donkeys 4,600 . . . Horse 0 . . . Other 17,025 Total 1,555,617 100 103,534 Indigenous Chicken Layer Broiler Ducks Turkeys Rabbits Donkeys Other Tunduru 256,689 . 640 257,329 Tunduru 15,865 . 984 984 14,460 Songea Rural 274,591 . 5,318 279,909 Songea Rural 3,422 689 2,963 . . Mbinga 644,439 2,749 646 647,834 Mbinga 10,426 124 31,130 3,616 1,580 Songea Urban 60,398 2,499 2,884 65,782 Songea Urban 2,970 55 2,472 . 408 Namtumbo 300,212 788 3,762 304,763 Namtumbo 6,195 . 4,614 . 576 Total 1,536,330 6,037 13,250 1,555,617 Total 38,878 868 42,163 4,600 17,025 Type of Livestock/Poultry 1995 1999 2003 Number % Cattle 75,027 79,969 121,175 1 - 4 36,278 26 96,787 3 Improved Cattle 1,325 3,738 15,292 5 - 9 40,716 29 268,983 7 Goats 348,509 537,843 309,595 10 - 19 41,041 29 546,003 13 Sheep 41,890 49,801 24,458 20 - 29 12,834 9 287,289 22 Pigs 89,600 182,347 134,951 30 - 39 4,822 3 156,927 33 Indigenous Chicken 1,091,260 1,757,385 1,536,330 40 - 49 1,490 1 66,756 45 Layers - 11,709 6,037 50 - 99 2,103 2 132,872 63 Broilers 974 30,064 13,250 Total 139,284 100 1,555,617 11 Total Chickens 1,092,234 1,799,158 1,555,617 23d OTHER LIVESTOCK: Total Number of Households and Chicken Raised by Flock Size as of 1st October 2003 23e LIVESTOCK/POULTRY POPULATION TREND Flock Size Chicken Rearing Households Number of Chicken Average Chicken per Household District 23c Head Number of Other Livestock by Type of Livestock and District District Total Number of Chicken Number of Chicken 23b OTHER LIVESTOCK: Number of Chicken by Category of Chicken and District on 1st October 2003 Type of Livestock Chicken Type Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 245 FISH FARMING Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 246 Number % Number % Tunduru 298 0.6 46,600 99.4 46,898 Songea Rural 1,294 4.2 29,479 95.8 30,772 Mbinga 910 1.2 76,537 98.8 77,447 Songea Urban 601 8.7 6,342 91.3 6,943 Namtumbo 933 3.2 28,182 96.8 29,115 Total 4,035 2.1 187,140 97.9 191,175 Natural Pond Dug out PonWater ResevOther Total Tunduru 0 298 0 0 298 Songea Rural 77 1,369 0 0 1,446 Mbinga 0 910 132 0 1,042 Songea Urban 0 792 0 27 819 Namtumbo 361 789 0 72 1,222 Total 438 4,158 132 100 4,827 Own Pond Governmen t Institution NGOs / Project Neighbour Other Total Number Number Number Number Number Number Tunduru 0 0 89 209 0 298 Songea Rural 77 77 227 1,065 0 1,446 Mbinga 0 0 132 910 0 1,042 Songea Urban 0 137 0 682 0 819 Namtumbo 0 361 0 788 73 1,222 Total 77 575 448 3,654 73 4,827 Neighbor Trader at Farm Did not Sell Other Total Number Number Number Number Number Tunduru 0 0 209 89 298 Songea Rural 612 77 684 0 1,372 Mbinga 0 0 918 124 1,042 Songea Urban 435 27 357 0 819 Namtumbo 720 0 641 0 1,361 Total 1,767 104 2,808 213 4,893 District Number of Tilapia Number of Carp Number of Others Tunduru 27,263 0 0 Songea Rural 169,846 2,923 0 Mbinga 49,022 0 5,159 Songea Urban 197,054 439 19,282 Namtumbo 247,863 18,990 20,222 Total 691,048 22,353 44,663 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year District 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District during the District Source of Fingerling 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District during the 2002/03 Agricultural Year District 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerlings and District during the 2002/03 Agricultural Year Fish Farming System 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Agricultural Households Doing Fish Farming Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 247 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 248 Number % Number % Tunduru 3,918 8.4 42,980 91.6 46,898 5,276 74 Songea Rural 5,527 18.0 25,245 82.0 30,772 8,578 64 Mbinga 14,420 18.6 63,027 81.4 77,447 25,335 57 Songea Urban 1,336 19.2 5,606 80.8 6,943 1,799 74 Namtumbo 5,384 18.5 23,731 81.5 29,115 8,567 63 Total 30,585 16.0 160,590 84.0 191,175 49,556 62 Number % Number % Number % Number % Number % Tunduru 3,623 100.0 0 0.0 0 0.0 0 0.0 0 0.0 Songea Rural 5,377 75.0 675 9.4 448 6.2 522 7.3 149 2.1 Mbinga 13,366 80.3 1,832 11.0 395 2.4 781 4.7 263 1.6 Songea Urban 1,282 45.4 515 18.2 432 15.3 350 12.4 247 8.7 Namtumbo 5,167 85.8 429 7.1 71 1.2 214 3.6 143 2.4 Total 28,815 79.4 3,450 9.5 1,346 3.7 1,868 5.1 802 2.2 Other Source of extension advice Total Total Number of households raising livestock % receiving advice out of total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension by District During the 2002/03 Agricultural Year District Government NGO / Development Project Co-operative Large Scale Farmer District Received Livestock Advice Did Not Receive Livestock Advice 29.1b LIVESTOCK EXTENSION SERVICE PROVIDERS: Number of Agricultural Households By Source of Extension Services and District during the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 249 Government NGO / Development Project Large Scale Farmer Total Tunduru 2,276 0 0 2,276 5,276 43.1 Songea Rural 2,130 152 74 2,356 8,578 27.5 Mbinga 7,262 0 129 7,391 25,335 29.2 Songea Urban 682 110 0 791 1,799 44.0 Namtumbo 2,723 0 72 2,796 8,567 32.6 Total 15,073 261 275 15,609 49,556 31.5 % 96.6 1.7 1.8 100 Government NGO / Development Project Large Scale Farmer Other(forme r coding) Other Total Tunduru 1,847 0 0 0 0 1,847 5,276 35.0 Songea Rural 2,439 227 0 0 0 2,667 8,578 31.1 Mbinga 10,149 128 394 123 0 10,794 25,335 42.6 Songea Urban 677 82 0 0 27 787 1,799 43.7 Namtumbo 3,223 0 72 0 0 3,295 8,567 38.5 Total 18,336 437 465 123 27 19,390 49,556 39.1 % 95 2 2 1 0 100 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District District Total Number of households raising livestock % receiving advice out of total Source of Advice on Feeds and Proper Feeding Total Number of households raising livestock % receiving advice out of total Source of Advice on Housing Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 250 Government NGO / Development Project Large Scale Farmer Other Total Tunduru 202 0 0 0 202 5,276 3.8 Songea Rural 532 76 76 0 684 8,578 8.0 Mbinga 2,311 0 0 0 2,311 25,335 9.1 Songea Urban 245 136 0 27 408 1,799 22.7 Namtumbo 1,298 0 0 0 1,298 8,567 15.1 Total 4,588 212 76 27 4,903 49,556 9.9 % 93.6 4.3 1.5 0.5 100.0 Government NGO / Development Project Total Tunduru 103 0 103 5,276 2.0 Songea Rural 530 76 605 8,578 7.1 Mbinga 2,047 0 2,047 25,335 8.1 Songea Urban 299 82 381 1,799 21.2 Namtumbo 1,298 0 1,298 8,567 15.1 Total 4,276 158 4,434 49,556 8.9 % 96.4 3.6 100 District District % receiving advice out of total Source of Advice on Milk Hygene Total Number of households raising livestock 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygiene By Source and District, 2002/03 Agricultural Year % receiving advice out of total Total Number of households raising livestock Source of Advice on Proper Milking Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 251 Government NGO / Development Project Large scale Farmer Total Tunduru 1,146 0 0 1,146 5,276 22 Songea Rural 3,170 76 0 3,246 8,578 38 Mbinga 9,057 128 129 9,314 25,335 37 Songea Urban 761 110 0 871 1,799 48 Namtumbo 3,736 0 72 3,808 8,567 44 Total 17,871 314 201 18,385 49,556 37 % 97.2 1.7 1.1 100 Government Total Songea Rural 302 302 8,578 4 Mbinga 2,084 2,084 25,335 8 Songea Urban 135 135 1,799 8 Namtumbo 358 358 8,567 4 Total 2,879 2,879 44,280 7 % 100.0 100.0 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year District Source of Advice on Disease Control District Total Number of households raising livestock Source of Advice on Herd/Flock Size 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year Total Number of households raising livestock % receiving advice out of total % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 252 Government NGO / Development Project Large Scale Farmer Other Songea Rural 379 0 0 0 379 8,578 4 Mbinga 2,332 128 129 0 2,589 25,335 10 Songea Urban 163 55 0 27 246 1,799 14 Namtumbo 1,649 0 0 0 1,649 8,567 19 Total 4,524 183 129 27 4,863 44,280 11 % 93.0 3.8 2.7 0.6 100 Government NGO / Development Project Co-operative Total Songea Rural 685 76 76 836 8,578 10 Mbinga 4,944 132 265 5,341 25,335 21 Songea Urban 436 27 0 463 1,799 26 Namtumbo 1,938 72 217 2,227 8,567 26 Total 8,003 308 557 8,868 44,280 20 % 90.2 3.5 6.3 100 District 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year % receiving advice out of total % receiving advice out of total Source of Advice on Pasture Establishment and Selection Total 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengthening By Source and District, 2002/03 Agricultural Year District Source of Advice on Group Formation and Strenghthening Total Number of households raising livestock Total Number of households raising livestock Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 253 Government NGO / Development Project Large Scale Farmer Total Tunduru 104 0 0 104 5,276 2 Songea Rural 532 76 0 608 8,578 7 Mbinga 2,325 0 129 2,454 25,335 10 Songea Urban 268 110 0 378 1,799 21 Namtumbo 1,515 0 0 1,515 8,567 18 Total 4,745 186 129 5,059 49,556 10 % 93.8 3.7 2.5 100 Government NGO / Development Project Large Scale Farmer Other Total Tunduru 203 0 0 0 203 5,276 3.8 Songea Rural 831 76 0 0 907 8,578 10.6 Mbinga 3,636 0 0 0 3,636 25,335 14.4 Songea Urban 216 55 27 27 326 1,799 18.1 Namtumbo 1,798 0 0 0 1,798 8,567 21.0 Total 6,684 131 27 27 6,870 49,556 13.9 % 97.3 1.9 0.4 0.4 100.0 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Total Number of households raising livestock Total Number of households raising livestock District Source of Advice on Calf Rearing % receiving advice out of total Source of Advice on Improved Bulls % receiving advice out of total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 254 Number % Number % Number % Number % Number % Tunduru 624 17 2,783 75 319 9 0 0 0 0 3,727 Songea Rural 450 8 3,321 61 1,602 29 76 1 0 0 5,449 Mbinga 2,708 18 9,892 65 1,681 11 129 1 787 5 15,197 Songea Urban 355 19 1,038 54 493 26 27 1 0 0 1,914 Namtumbo 710 18 3,008 75 216 5 0 0 71 2 4,005 Total 4,848 16 20,043 66 4,311 14 232 1 858 3 30,292 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year Total Quality of Service District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 255 ACCESS TO INFRASRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 256 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads District Capital Tunduru 18.7 1.5 10.9 3.0 32.0 7.6 288.3 4.5 22.7 43.9 274.1 53.8 Songea Rural 18.0 1.5 3.2 0.5 46.6 8.5 54.2 14.6 44.6 40.8 23.6 54.2 Mbinga 14.9 2.7 8.6 2.5 27.0 6.1 125.0 8.8 34.8 43.3 106.4 47.8 Songea Urban 5.0 4.3 1.3 0.9 10.8 8.3 7.6 5.1 9.1 7.8 4.4 7.8 Namtumbo 15.4 1.3 19.8 3.6 70.5 6.6 79.7 7.6 56.6 62.3 73.4 56.9 Total 16.0 2.1 9.7 2.4 37.4 7.0 142.5 8.4 35.8 44.6 125.5 50.2 Regional Capital 142.5 Tarmac Roads 125.5 District Capital 50.2 Tertiary Market 44.6 Hospitals 37.4 Secondary Market 35.8 Secondary Schools 16.0 All weather roads 9.7 Primary Markets 8.4 Health Clinics 7.0 Feeder Roads 2.4 Primary Schools 2.1 33.01a Mean Distances from Household Dwellings to Infrastructures and Services by Districts District Mean Distance to Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 257 No of households % No of households % No of households % No of households % No of households % Tunduru 1,401 3.0 2,421 5.2 11,261 24.0 14,773 31.5 17,042 36.3 46,898 18.7 Songea Rural 380 1.2 1,819 5.9 9,718 31.6 10,103 32.8 8,752 28.4 30,772 18.0 Mbinga 3,621 4.7 10,340 13.4 23,756 30.7 23,386 30.2 16,344 21.1 77,447 14.9 Songea Urban 541 7.8 1,377 19.8 3,985 57.4 1,040 15.0 0 0.0 6,943 5.0 Namtumbo 780 2.7 3,694 12.7 9,555 32.8 7,865 27.0 7,222 24.8 29,115 15.4 Total 6,723 3.5 19,651 10.3 58,274 30.5 57,167 29.9 49,360 25.8 191,175 16.0 No of households % No of households % No of households % No of households % No of households % Tunduru 24,121 51.4 2,719 5.8 8,103 17.3 2,560 5.5 9,395 20.0 46,898 10.9 Songea Rural 21,474 69.8 4,876 15.8 2,752 8.9 230 0.7 1,440 4.7 30,772 3.2 Mbinga 29,271 37.8 15,930 20.6 11,907 15.4 11,040 14.3 9,299 12.0 77,447 8.6 Songea Urban 4,425 63.7 1,668 24.0 795 11.4 0 0.0 55 0.8 6,943 1.3 Namtumbo 19,601 67.3 3,076 10.6 714 2.5 1,734 6.0 3,990 13.7 29,115 19.8 Total 98,892 51.7 28,269 14.8 24,271 12.7 15,564 8.1 24,179 12.6 191,175 9.7 No of households % No of households % No of households % No of households % No of households % Tunduru 28,261 60.3 10,812 23.1 6,975 14.9 213 0.5 638 1.4 46,898 3.0 Songea Rural 27,646 89.8 2,131 6.9 919 3.0 0 0.0 77 0.3 30,772 0.5 Mbinga 48,059 62.1 18,317 23.7 7,018 9.1 1,830 2.4 2,223 2.9 77,447 2.5 Songea Urban 5,602 80.7 930 13.4 301 4.3 0 0.0 110 1.6 6,943 0.9 Namtumbo 24,395 83.8 1,855 6.4 701 2.4 1,445 5.0 719 2.5 29,115 3.6 Total 133,962 70.1 34,045 17.8 15,914 8.3 3,488 1.8 3,766 2.0 191,175 2.4 33.01b: Number of Households By Distance to Secondary School by District for 2002/03 agriculture year District Distance to Secondary School Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01c: Number of Households By Distance to All Weather Road by District for 2002/03 agriculture year District Distance to All Weather Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District Distance to Feeder Road Total number of households Mean Distance Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 258 No of households % No of households % No of households % No of households % No of households % Tunduru 1,040 2.2 1,409 3.0 4,372 9.3 10,625 22.7 29,451 62.8 46,898 32.0 Songea Rural 0 0.0 76 0.2 5,237 17.0 6,869 22.3 18,590 60.4 30,772 46.6 Mbinga 3,060 4.0 5,692 7.3 14,968 19.3 20,386 26.3 33,341 43.1 77,447 27.0 Songea Urban 0 0.0 531 7.6 4,304 62.0 1,807 26.0 302 4.3 6,943 10.8 Namtumbo 72 0.2 0 0.0 144 0.5 574 2.0 28,325 97.3 29,115 70.5 Total 4,172 2.2 7,708 4.0 29,026 15.2 40,261 21.1 110,008 57.5 191,175 37.4 No of households % No of households % No of households % No of households % No of households % Tunduru 14,108 30.1 6,937 14.8 20,475 43.7 4,547 9.7 831 1.8 46,898 7.6 Songea Rural 4,865 15.8 6,702 21.8 13,943 45.3 3,596 11.7 1,666 5.4 30,772 8.5 Mbinga 9,284 12.0 26,766 34.6 28,584 36.9 10,076 13.0 2,737 3.5 77,447 6.1 Songea Urban 548 7.9 1,482 21.3 3,487 50.2 1,290 18.6 136 2.0 6,943 8.3 Namtumbo 4,591 15.8 8,903 30.6 7,618 26.2 4,237 14.6 3,766 12.9 29,115 6.6 Total 33,396 17.5 50,790 26.6 74,107 38.8 23,745 12.4 9,137 4.8 191,175 7.0 No of households % No of households % No of households % No of households % No of households % Tunduru 27,318 58.2 14,200 30.3 5,065 10.8 107 0.2 209 0.4 46,898 1.5 Songea Rural 11,077 36.0 15,770 51.2 3,772 12.3 77 0.3 77 0.2 30,772 1.5 Mbinga 28,312 36.6 38,270 49.4 9,969 12.9 527 0.7 369 0.5 77,447 2.7 Songea Urban 2,421 34.9 2,915 42.0 1,525 22.0 0 0.0 82 1.2 6,943 4.3 Namtumbo 11,929 41.0 14,823 50.9 1,932 6.6 287 1.0 144 0.5 29,115 1.3 Total 81,057 42.4 85,977 45.0 22,263 11.6 997 0.5 881 0.5 191,175 2.1 Above 20 km Above 20 km 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year District Distance to hospital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year District Health clinic Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 1-2.9 km Less than 1 km District Distance to Primary School Mean Distance Above 20 km 10.0-19.9 3.0-9.9 Total number of households Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 259 No of households % No of households % No of households % No of households % No of households % Tunduru 0 0.0 0 0.0 0 0.0 418 0.9 46,480 99.1 46,898 288.3 Songea Rural 76 0.2 0 0.0 228 0.7 5,871 19.1 24,598 79.9 30,772 54.2 Mbinga 748 1.0 0 0.0 380 0.5 110 0.1 76,209 98.4 77,447 125.0 Songea Urban 55 0.8 505 7.3 4,494 64.7 1,834 26.4 55 0.8 6,943 7.6 Namtumbo 216 0.7 0 0.0 0 0.0 72 0.2 28,827 99.0 29,115 79.7 Total 1,095 0.6 505 0.3 5,102 2.7 8,306 4.3 176,168 92.2 191,175 142.5 No of households % No of households % No of households % No of households % No of households % Tunduru 0 0.0 994 2.1 2,478 5.3 3,389 7.2 40,037 85.4 46,898 53.8 Songea Rural 77 0.3 0 0.0 152 0.5 5,794 18.8 24,749 80.4 30,772 54.2 Mbinga 110 0.1 1,425 1.8 6,485 8.4 16,056 20.7 53,371 68.9 77,447 47.8 Songea Urban 0 0.0 505 7.3 4,522 65.1 1,834 26.4 82 1.2 6,943 7.8 Namtumbo 0 0.0 1,012 3.5 1,589 5.5 2,316 8.0 24,198 83.1 29,115 56.9 Total 187 0.1 3,936 2.1 15,225 8.0 29,389 15.4 142,438 74.5 191,175 50.2 No of households % No of households % No of households % No of households % No of households % Tunduru 603 1.3 0 0.0 98 0.2 0 0.0 46,196 98.5 46,898 274.1 Songea Rural 4,078 13.3 2,714 8.8 5,768 18.7 6,203 20.2 12,010 39.0 30,772 23.6 Mbinga 2,060 2.7 264 0.3 380 0.5 393 0.5 74,349 96.0 77,447 106.4 Songea Urban 1,121 16.1 1,570 22.6 3,377 48.6 848 12.2 27 0.4 6,943 4.4 Namtumbo 1,499 5.1 0 0.0 215 0.7 2,163 7.4 25,238 86.7 29,115 73.4 Total 9,362 4.9 4,548 2.4 9,838 5.1 9,607 5.0 157,821 82.6 191,175 125.5 33.01h: Number of Households by Distance to Regional Capital by District for 2002/03 agriculture year District Distance to Regional Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01i: Number of Households by Distance to District Capital by District for 2002/03 agriculture year District Distance to District Capital Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01j: Number of Households by Distance to Tarmac Road by District for 2002/03 agricultural year District Tarmac Road Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 260 No of households % No of households % No of households % No of households % No of households % Tunduru 21,190 45.2 4,948 10.6 17,147 36.6 3,293 7.0 320 0.7 46,898 4.5 Songea Rural 3,598 11.7 1,658 5.4 7,491 24.3 10,172 33.1 7,853 25.5 30,772 14.6 Mbinga 14,702 19.0 15,512 20.0 26,743 34.5 11,692 15.1 8,799 11.4 77,447 8.8 Songea Urban 788 11.3 1,347 19.4 4,177 60.2 603 8.7 27 0.4 6,943 5.1 Namtumbo 5,887 20.2 8,040 27.6 6,824 23.4 6,349 21.8 2,015 6.9 29,115 7.6 Total 46,164 24.1 31,504 16.5 62,382 32.6 32,110 16.8 19,015 9.9 191,175 8.4 No of households % No of households % No of households % No of households % No of households % Tunduru 2,828 6.0 568 1.2 2,674 5.7 5,201 11.1 35,625 76.0 46,898 43.9 Songea Rural 1,935 6.3 761 2.5 3,548 11.5 5,791 18.8 18,738 60.9 30,772 40.8 Mbinga 2,963 3.8 1,534 2.0 8,059 10.4 18,425 23.8 46,466 60.0 77,447 43.3 Songea Urban 82 1.2 611 8.8 4,252 61.2 1,916 27.6 82 1.2 6,943 7.8 Namtumbo 788 2.7 1,299 4.5 1,377 4.7 2,388 8.2 23,264 79.9 29,115 62.3 Total 8,597 4.5 4,773 2.5 19,910 10.4 33,721 17.6 124,175 65.0 191,175 44.6 No of households % No of households % No of households % No of households % No of households % Tunduru 13,925 29.7 213 0.5 1,906 4.1 2,008 4.3 28,846 61.5 46,898 22.7 Songea Rural 2,091 6.8 0 0.0 4,783 15.5 6,788 22.1 17,110 55.6 30,772 44.6 Mbinga 9,061 11.7 699 0.9 2,105 2.7 6,348 8.2 59,234 76.5 77,447 34.8 Songea Urban 1,296 18.7 433 6.2 2,882 41.5 1,619 23.3 713 10.3 6,943 9.1 Namtumbo 1,772 6.1 1,217 4.2 1,303 4.5 1,663 5.7 23,160 79.5 29,115 56.6 Total 28,146 14.7 2,563 1.3 12,979 6.8 18,425 9.6 129,063 67.5 191,175 35.8 33.01k: Number of Households by Distance to Primary Market by District for 2002/03 agricultural year District Primary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01l: Number of Households by Distance to Tertiary Market by District for 2002/03 agricultural year District Tertiary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km 33.01m: Number of Households by Distance to Secondary Market by District for 2002/03 agricultural year District Secondary Market Total number of households Mean Distance Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 261 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 3,141 1 13,881 5 7,107 3 4,854 2 2,671 1 249,734 89 281,387 Songea Rural 1,966 1 11,710 6 5,086 3 1,442 1 1,061 1 163,368 88 184,633 Mbinga 3,252 1 18,515 4 21,961 5 11,930 3 3,548 1 405,472 87 464,680 Songea Urban 327 1 2,404 6 713 2 189 0 54 0 37,969 91 41,657 Namtumbo 1,943 1 13,169 8 10,169 6 862 0 504 0 148,044 85 174,692 Total 10,629 1 59,679 5 45,037 4 19,278 2 7,838 1 1,004,587 88 1,147,049 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 716 6 8,573 68 1,986 16 950 8 308 2 12,532 Songea Rural 222 2 8,364 73 2,137 19 682 6 76 1 11,480 Mbinga 2,348 10 14,881 62 4,831 20 1,568 7 263 1 23,892 Songea Urban 137 7 1,500 75 302 15 53 3 0 0 1,992 Namtumbo 1,436 10 10,938 78 1,652 12 72 1 0 0 14,098 Total 4,859 8 44,255 69 10,909 17 3,325 5 647 1 63,994 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 0 0 618 31 408 21 532 27 410 21 1,968 Songea Rural 227 75 0 0 0 0 76 25 0 0 303 Mbinga 648 5 2,430 18 5,367 39 4,272 31 1,134 8 13,851 Songea Urban 0 0 0 0 0 0 54 100 0 0 54 Namtumbo 0 0 1,438 39 2,026 55 72 2 144 4 3,680 Total 875 4 4,486 23 7,800 39 5,006 25 1,689 9 19,856 Total number of households Satisfaction of Using Veterinary Clinic Not Applicable 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 262 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 0 0 213 15 498 35 319 22 410 28 1,441 Songea Rural 758 91 0 0 0 0 76 9 0 0 834 Mbinga 0 0 0 0 264 50 261 50 0 0 525 Songea Urban 54 50 0 0 0 0 55 50 0 0 109 Namtumbo 289 45 0 0 360 55 0 0 0 0 649 Total 1,100 31 213 6 1,122 32 711 20 410 12 3,557 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 2,001 27 2,059 28 2,156 29 722 10 410 6 7,348 Songea Rural 77 2 455 15 1,655 53 229 7 682 22 3,098 Mbinga 124 1 808 7 5,868 49 4,413 37 755 6 11,968 Songea Urban 0 0 301 48 274 44 0 0 54 9 628 Namtumbo 0 0 649 15 2,741 63 575 13 360 8 4,325 Total 2,202 8 4,270 16 12,694 46 5,940 22 2,261 8 27,367 No of Households % No of Households % No of Households % No of Households % No of Households % Tunduru 213 5 1,570 39 817 20 956 23 517 13 4,073 Songea Rural 302 67 0 0 76 17 74 16 0 0 452 Mbinga 132 2 396 5 5,366 66 1,155 14 1,134 14 8,184 Songea Urban 54 66 27 34 0 0 0 0 0 0 82 Namtumbo 73 14 0 0 360 71 72 14 0 0 504 Total 773 6 1,994 15 6,619 50 2,257 17 1,651 12 13,294 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 263 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 264 Table 34.1 Number of Agriculture Households by Type of Toilet and District During the 2002/03 Agriculture Year No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Total number of households Tunduru 1,036 1,049 44,724 89 46,898 Songea Rural 379 76 29,789 528 30,772 Mbinga 524 2,732 73,108 1,082 77,447 Songea Urban 82 191 6,128 542 6,943 Namtumbo 69 718 27,824 504 29,115 Total 2,090 4,767 181,572 2,745 191,175 % 1.1 2.5 95.0 1.4 100.0 District Average Number of rooms per Household Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Total number of household s Tunduru 4 7,929 103 320 0 37,054 1,492 46,898 Songea Rural 3 10,485 306 76 0 16,807 3,099 30,772 Mbinga 3 33,950 524 0 0 40,472 2,501 77,447 Songea Urban 3 3,097 0 0 0 3,791 55 6,943 Namtumbo 4 8,485 218 73 73 19,849 419 29,115 Total 3 63,946 1,150 468 73 117,971 7,566 191,175 % 33.4 0.6 0.2 0.0 61.7 4.0 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 21,532 20 20,803 19 43,081 39 4,740 4 19,003 17 109,159 44.7 Landline phone 404 27 77 5 851 57 165 11 0 0 1,496 0.6 Mobile phone 309 13 302 12 1,224 50 487 20 138 6 2,460 1.0 Iron 8,238 17 8,490 17 22,196 45 2,126 4 8,566 17 49,616 20.3 Wheelbarrow 1,031 13 759 10 4,412 56 757 10 985 12 7,944 3.3 Bicycle 69,706 28.5 Vehicle 207 9 383 17 1,394 61 82 4 218 10 2,284 0.9 Television / Video 1,549 0.6 Total Number of Households 31,721 30,814 13 73,157 30 8,357 3 28,910 12 244,215 100.0 34.2 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year District District Table 34.3: Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year Type of Owned Asset Total Tunduru Type of toilet Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 265 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 104 18.58 0 0 372 66.67 82 14.75 0 0 559 0.3 Solar 98 22.46 0 0 240 54.87 27 6.214 72 16.455 438 0.2 Gas (Biogas) 105 18.56 0 0 388 68.83 0 0.0 71 12.612 564 0.3 Hurricane Lamp 12,077 14.3 16,492 19.52 38,763 45.89 3,046 3.605 14,099 16.69 84,477 44.2 Pressure Lamp 1,053 18.4 909 15.89 2,612 45.65 220 3.84 928 16.223 5,722 3.0 Wick Lamp 32,404 33.4 13,069 13.47 34,589 35.66 3,568 3.678 13,381 13.793 97,011 50.7 Candles 107 22.26 0 0 228 47.65 0 0.0 144 30.099 479 0.3 Firewood 951 49.36 302 15.7 253 13.14 0 0.0 420 21.796 1,926 1.0 Total 46,898 25 30,772 16 77,447 41 6,943 3.6 29,115 15 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 0.0 153 68.0 0 0.0 0 0.0 72 32.0 225 0.1 Solar 104 14.9 150 21.5 389 55.7 55 7.9 0 0.0 698 0.4 Gas (Biogas) 104 45.9 0 0.0 123 54.1 0 0.0 0 0.0 227 0.1 Bottled Gas 104 33.4 76 24.3 132 42.4 0 0.0 0 0.0 312 0.2 Parraffin / Kerocine 0 0.0 77 99.4 0 0.0 0 0.0 0 0.0 77 0.0 Charcoal 500 14.1 532 15.0 1,894 53.3 487 13.7 143 4.0 3,555 1.9 Firewood 45,987 24.8 29,633 16.0 74,909 40.3 6,401 3.4 28,756 15.5 185,686 97.1 Crop Residues 0 0.0 77 51.4 0 0.0 0 0.0 72 48.6 149 0.1 Livestock Dung 98 56.5 76 43.5 0 0.0 0 0.0 0 0.0 174 0.1 Others 0.0 0.0 0.0 0.0 72 100.0 72 0.0 Total 46,898 24.5 30,772 16.1 77,447 40.5 6,943 3.6 29,115 15.2 191,175 100.0 34.5: Number of Agricultural Households by Main Source of Energy Used for Cooking during 2002/03 Agricultural Year Main Source of Energy for Cooking District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting during 2002/03 Agricultural Year Main Source of Energy for Lighting District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 266 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Total wet season 10,361 8,842 17,766 734 14,491 52,195 dry season 10,379 7,851 16,618 680 13,336 48,864 wet season 10,585 10,150 1,140 1,339 5,723 28,937 Dry season 9,859 10,147 1,399 1,366 5,723 28,493 wet season 417 4,391 1,928 273 1,301 8,311 Dry season 311 4,394 1,796 273 1,301 8,075 wet season 15,684 4,257 23,192 3,148 6,591 52,871 Dry season 15,860 5,171 23,432 3,010 7,458 54,932 wet season 5,982 2,297 24,468 1,340 434 34,520 Dry season 6,503 2,373 24,602 1,423 434 35,335 wet season 2,272 835 8,218 82 430 11,837 Dry season 3,986 835 9,125 110 430 14,487 wet season 0 0 0 27 0 27 Dry season 0 0 0 27 0 27 wet season 1,597 0 0 0 0 1,597 Dry season - - - - - - wet season 0 0 132 0 0 132 Dry season 0 0 0 27 72 100 wet season 0 0 475 0 0 475 Dry season 0 0 475 27 216 718 wet season 0 0 128 0 145 273 dry season 0 0 0 0 145 145 46,898 30,772 77,447 6,943 29,115 191,175 Tunduru Songea Rural Mbinga Songea Urban Namtumbo Total wet season 22 29 23 11 50 27 dry season 22 26 21 10 46 26 wet season 23 33 1 19 20 15 Dry season 21 33 2 20 20 15 wet season 1 14 2 4 4 4 Dry season 1 14 2 4 4 4 wet season 33 14 30 45 23 28 Dry season 34 17 30 43 26 29 wet season 13 7 32 19 1 18 Dry season 14 8 32 20 1 18 wet season 5 3 11 1 1 6 Dry season 8 3 12 2 1 8 wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 3 0 0 0 0 1 Dry season - - - - - - wet season 0 0 0 0 0 0 Dry season 0 0 0 0 0 0 wet season 0 0 1 0 0 0 Dry season 0 0 1 0 1 0 wet season 0 0 0 0 0 0 dry season 0 0 0 0 0 0 Total Agricultural Households per District 34.7: Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season District Other District Source Season Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Uprotected Well Unprotected Spring Tanker Truck Piped Water 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Protected Well Protected / Covered Spring Unprotected Spring Surface Water (Lake / Dam / River / Stream) Piped Water Protected Well Protected / Covered Spring Uprotected Well Other Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Tanker Truck Tanzania Agriculture sample Census - 2003 Ruvuma Region Appendix II 267 Tunduru Songea Rural Mbinga Songea Urban Namtumbo wet season 924 688 5,971 134 4,324 Dry season 840 610 6,073 159 4,542 wet season 13,670 13,505 28,655 2,504 10,619 Dry season 10,044 12,590 27,873 2,449 9,985 wet season 8,057 6,848 16,936 1,365 4,172 Dry season 8,453 6,847 16,927 1,394 4,098 wet season 10,262 5,861 11,269 1,066 2,793 Dry season 9,884 6,627 11,407 1,093 2,658 wet season 4,841 529 2,458 137 867 Dry season 5,455 529 2,206 110 852 wet season 4,825 2,654 6,843 1,273 3,087 Dry season 3,861 2,350 7,102 1,273 3,230 wet season 4,320 686 5,315 464 3,253 Dry season 8,361 1,219 5,859 465 3,750 Tunduru Songea Rural Mbinga Songea Urban Namtumbo wet season 2 2 8 2 15 Dry season 2 2 8 2 16 wet season 29 44 37 36 36 Dry season 21 41 36 35 34 wet season 17 22 22 20 14 Dry season 18 22 22 20 14 wet season 22 19 15 15 10 Dry season 21 22 15 16 9 wet season 10 2 3 2 3 Dry season 12 2 3 2 3 wet season 10 9 9 18 11 Dry season 8 8 9 18 11 wet season 9 2 7 7 11 Dry season 18 4 8 7 13 above one Hour 34.9: Proportion of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes District 34.8: Number of Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) by District for 2002/03 agriculture year Less than 10 10 - 19 Minutes Time Spent to and from Main Source of Drinking Water Season District above one Hour 40 - 49 Minutes 50 - 59 Minutes 20 - 29 Minutes 30 - 39 Minutes Time Spent to and from Main Source of Drinking Water Season Less than 10 10 - 19 Minutes Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 268 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 318 1 0 0 2,325 3 409 6 553 2 3,605 1.9 Two 7,537 16 12,028 39 35,417 46 1,992 29 6,895 24 63,869 33.4 Three 39,043 83 0 39,440 51 4,542 65 21,598 74 123,291 64.5 Four 0 0 76 0 265 0 0 0 69 0 409 0.2 Total 46,898 100 30,772 100 77,447 100 6,943 100 29,115 100 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 26,776 57 8,968 29 20,819 27 1,911 28 7,554 26 66,028 35 One 9,702 21 10,484 34 20,819 27 2,207 32 9,354 32 52,566 27 Two 5,758 12 6,774 22 19,147 25 1,711 25 6,904 24 40,294 21 Three 2,896 6 2,881 9 10,653 14 706 10 3,938 14 21,074 11 Four 1,256 3 531 2 3,714 5 380 5 860 3 6,741 4 Five 210 0 681 2 1,422 2 27 0 361 1 2,702 1 Six 89 0 151 0 241 0 0 0 0 0 480 0 Seven 211 0 302 1 631 1 0 0 144 0 1,289 1 Total 46,898 100 30,772 100 77,447 100 6,943 100 29,115 100 191,175 100 34.11: Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.10: Number of Agricultural Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 269 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 10,069 32 5,326 17 9,519 30 822 3 6,194 19 31,930 17 One 6,863 16 9,520 22 17,299 40 1,798 4 7,892 18 43,373 23 Two 8,167 21 6,768 17 15,283 39 1,499 4 7,344 19 39,061 20 Three 7,166 24 5,243 17 12,406 41 1,301 4 4,082 14 30,198 16 Four 6,150 34 1,965 11 7,432 41 949 5 1,801 10 18,297 10 Five 4,369 34 1,420 11 5,637 43 464 4 1,082 8 12,971 7 Six 1,578 39 229 6 1,914 47 82 2 289 7 4,091 2 Seven 2,536 23 302 3 7,956 71 27 0 432 4 11,254 6 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 23,878 20 20,206 17 49,669 42 5,223 4 20,562 17 119,538 62.5 Seldom 14,136 29 6,626 14 19,938 41 1,204 2 6,264 13 48,168 25.2 Sometimes 4,044 32 2,808 22 4,367 35 192 2 1,138 9 12,550 6.6 Often 1,762 37 456 10 1,675 35 107 2 791 17 4,790 2.5 Always 3,078 50 677 11 1,797 29 217 4 360 6 6,129 3.2 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 34.13: Number of Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Status of Food Satisfaction District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.12: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Number of Days District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma Appendix II 270 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 7,929 12 10,485 16 33,950 53 3,097 5 8,485 13 63,946 33.4 Tiles 103 9 306 27 524 46 0 0 218 19 1,150 0.6 Concrete 320 68 76 16 0 0 0 0 73 15 468 0.2 Asbestos 0 0 0 0 0 0 0 0 73 100 73 0.0 Grass / Leaves 37,054 31 16,807 14 40,472 34 3,791 3 19,849 17 117,971 61.7 Grass & Mud 1,492 20 3,099 41 2,501 33 55 1 419 6 7,566 4.0 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 19,525 21 22,344 24 29,869 32 3,106 3 19,741 21 94,585 49.5 Sale of Livestock 98 4 379 16 1,671 69 191 8 72 3 2,412 1.3 Sale of Livestock Products 0 0 152 29 260 50 108 21 0 0 520 0.3 Sales of Cash Crops 15,144 30 906 2 27,586 55 244 0 6,282 13 50,162 26.2 Sale of Forest Products 844 52 227 14 0 0 110 7 434 27 1,615 0.8 Business Income 2,548 32 760 10 3,138 40 816 10 650 8 7,912 4.1 Wages & Salaries in Cash 1,306 19 1,284 19 2,978 43 761 11 574 8 6,903 3.6 Other Casual Cash Earnings 5,261 36 3,119 21 4,333 30 1,006 7 791 5 14,510 7.6 Cash Remittance 841 17 917 18 2,606 52 220 4 428 9 5,011 2.6 Fishing 213 4 227 4 4,751 91 27 1 0 0 5,217 2.7 Other 1,116 48 459 20 254 11 354 15 144 6 2,327 1.2 Total 46,898 25 30,772 16 77,447 41 6,943 4 29,115 15 191,175 100.0 34.15: Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Energy for Cooking District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo 34.14: Number of Households by Type of Roofing Materials and District during the 2002/03 Agricultural Year Roofing Materials District Total Tunduru Songea Rural Mbinga Songea Urban Namtumbo Tanzania Agriculture Sample Census - 2003 Ruvuma 271 APPENDIX III QUESTIONNAIRES Appendix III 272 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 273 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 274 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 275 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 276 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 277 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 278 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 279 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 280 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 281 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 282 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 283 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 284 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 285 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 286 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 287 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 288 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 289 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 290 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 291 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 292 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 293 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 294 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 295 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 296 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 297 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 298 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 299 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 300 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 301 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 302 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 303 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 304 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 305 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 306 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 307 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 308 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 309 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 310 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 311 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 312 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 313 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 314 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 315 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 316 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 317 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Page 69 AGREEMENT ON THE APPLICATION OF SANITARY AND PHYTOSANITARY MEASURES Members, Reaffirming that no Member should be prevented from adopting or enforcing measures necessary to protect human, animal or plant life or health, subject to the requirement that these measures are not applied in a manner which would constitute a means of arbitrary or unjustifiable discrimination between Members where the same conditions prevail or a disguised restriction on international trade; Desiring to improve the human health, animal health and phytosanitary situation in all Members; Noting that sanitary and phytosanitary measures are often applied on the basis of bilateral agreements or protocols; Desiring the establishment of a multilateral framework of rules and disciplines to guide the development, adoption and enforcement of sanitary and phytosanitary measures in order to minimize their negative effects on trade; Recognizing the important contribution that international standards, guidelines and recommendations can make in this regard; Desiring to further the use of harmonized sanitary and phytosanitary measures between Members, on the basis of international standards, guidelines and recommendations developed by the relevant international organizations, including the Codex Alimentarius Commission, the International Office of Epizootics, and the relevant international and regional organizations operating within the framework of the International Plant Protection Convention, without requiring Members to change their appropriate level of protection of human, animal or plant life or health; Recognizing that developing country Members may encounter special difficulties in complying with the sanitary or phytosanitary measures of importing Members, and as a consequence in access to markets, and also in the formulation and application of sanitary or phytosanitary measures in their own territories, and desiring to assist them in their endeavours in this regard; Desiring therefore to elaborate rules for the application of the provisions of GATT 1994 which relate to the use of sanitary or phytosanitary measures, in particular the provisions of Article XX(b)1; Hereby agree as follows: Article 1 General Provisions 1. This Agreement applies to all sanitary and phytosanitary measures which may, directly or indirectly, affect international trade. Such measures shall be developed and applied in accordance with the provisions of this Agreement. 1In this Agreement, reference to Article XX(b) includes also the chapeau of that Article. Page 70 2. For the purposes of this Agreement, the definitions provided in Annex A shall apply. 3. The annexes are an integral part of this Agreement. 4. Nothing in this Agreement shall affect the rights of Members under the Agreement on Technical Barriers to Trade with respect to measures not within the scope of this Agreement. Article 2 Basic Rights and Obligations 1. Members have the right to take sanitary and phytosanitary measures necessary for the protection of human, animal or plant life or health, provided that such measures are not inconsistent with the provisions of this Agreement. 2. Members shall ensure that any sanitary or phytosanitary measure is applied only to the extent necessary to protect human, animal or plant life or health, is based on scientific principles and is not maintained without sufficient scientific evidence, except as provided for in paragraph 7 of Article 5. 3. Members shall ensure that their sanitary and phytosanitary measures do not arbitrarily or unjustifiably discriminate between Members where identical or similar conditions prevail, including between their own territory and that of other Members. Sanitary and phytosanitary measures shall not be applied in a manner which would constitute a disguised restriction on international trade. 4. Sanitary or phytosanitary measures which conform to the relevant provisions of this Agreement shall be presumed to be in accordance with the obligations of the Members under the provisions of GATT 1994 which relate to the use of sanitary or phytosanitary measures, in particular the provisions of Article XX(b). Article 3 Harmonization 1. To harmonize sanitary and phytosanitary measures on as wide a basis as possible, Members shall base their sanitary or phytosanitary measures on international standards, guidelines or recommendations, where they exist, except as otherwise provided for in this Agreement, and in particular in paragraph 3. 2. Sanitary or phytosanitary measures which conform to international standards, guidelines or recommendations shall be deemed to be necessary to protect human, animal or plant life or health, and presumed to be consistent with the relevant provisions of this Agreement and of GATT 1994. 3. Members may introduce or maintain sanitary or phytosanitary measures which result in a higher level of sanitary or phytosanitary protection than would be achieved by measures based on the relevant international standards, guidelines or recommendations, if there is a scientific justification, or as a consequence of the level of sanitary or phytosanitary protection a Member determines to be appropriate Page 71 in accordance with the relevant provisions of paragraphs 1 through 8 of Article 5.2 Notwithstanding the above, all measures which result in a level of sanitary or phytosanitary protection different from that which would be achieved by measures based on international standards, guidelines or recommendations shall not be inconsistent with any other provision of this Agreement. 4. Members shall play a full part, within the limits of their resources, in the relevant international organizations and their subsidiary bodies, in particular the Codex Alimentarius Commission, the International Office of Epizootics, and the international and regional organizations operating within the framework of the International Plant Protection Convention, to promote within these organizations the development and periodic review of standards, guidelines and recommendations with respect to all aspects of sanitary and phytosanitary measures. 5. The Committee on Sanitary and Phytosanitary Measures provided for in paragraphs 1 and 4 of Article 12 (referred to in this Agreement as the "Committee") shall develop a procedure to monitor the process of international harmonization and coordinate efforts in this regard with the relevant international organizations. Article 4 Equivalence 1. Members shall accept the sanitary or phytosanitary measures of other Members as equivalent, even if these measures differ from their own or from those used by other Members trading in the same product, if the exporting Member objectively demonstrates to the importing Member that its measures achieve the importing Member's appropriate level of sanitary or phytosanitary protection. For this purpose, reasonable access shall be given, upon request, to the importing Member for inspection, testing and other relevant procedures. 2. Members shall, upon request, enter into consultations with the aim of achieving bilateral and multilateral agreements on recognition of the equivalence of specified sanitary or phytosanitary measures. Article 5 Assessment of Risk and Determination of the Appropriate Level of Sanitary or Phytosanitary Protection 1. Members shall ensure that their sanitary or phytosanitary measures are based on an assessment, as appropriate to the circumstances, of the risks to human, animal or plant life or health, taking into account risk assessment techniques developed by the relevant international organizations. 2. In the assessment of risks, Members shall take into account available scientific evidence; relevant processes and production methods; relevant inspection, sampling and testing methods; prevalence 2For the purposes of paragraph 3 of Article 3, there is a scientific justification if, on the basis of an examination and evaluation of available scientific information in conformity with the relevant provisions of this Agreement, a Member determines that the relevant international standards, guidelines or recommendations are not sufficient to achieve its appropriate level of sanitary or phytosanitary protection. Page 72 of specific diseases or pests; existence of pest- or disease-free areas; relevant ecological and environmental conditions; and quarantine or other treatment. 3. In assessing the risk to animal or plant life or health and determining the measure to be applied for achieving the appropriate level of sanitary or phytosanitary protection from such risk, Members shall take into account as relevant economic factors: the potential damage in terms of loss of production or sales in the event of the entry, establishment or spread of a pest or disease; the costs of control or eradication in the territory of the importing Member; and the relative cost-effectiveness of alternative approaches to limiting risks. 4. Members should, when determining the appropriate level of sanitary or phytosanitary protection, take into account the objective of minimizing negative trade effects. 5. With the objective of achieving consistency in the application of the concept of appropriate level of sanitary or phytosanitary protection against risks to human life or health, or to animal and plant life or health, each Member shall avoid arbitrary or unjustifiable distinctions in the levels it considers to be appropriate in different situations, if such distinctions result in discrimination or a disguised restriction on international trade. Members shall cooperate in the Committee, in accordance with paragraphs 1, 2 and 3 of Article 12, to develop guidelines to further the practical implementation of this provision. In developing the guidelines, the Committee shall take into account all relevant factors, including the exceptional character of human health risks to which people voluntarily expose themselves. 6. Without prejudice to paragraph 2 of Article 3, when establishing or maintaining sanitary or phytosanitary measures to achieve the appropriate level of sanitary or phytosanitary protection, Members shall ensure that such measures are not more trade-restrictive than required to achieve their appropriate level of sanitary or phytosanitary protection, taking into account technical and economic feasibility.3 7. In cases where relevant scientific evidence is insufficient, a Member may provisionally adopt sanitary or phytosanitary measures on the basis of available pertinent information, including that from the relevant international organizations as well as from sanitary or phytosanitary measures applied by other Members. In such circumstances, Members shall seek to obtain the additional information necessary for a more objective assessment of risk and review the sanitary or phytosanitary measure accordingly within a reasonable period of time. 8. When a Member has reason to believe that a specific sanitary or phytosanitary measure introduced or maintained by another Member is constraining, or has the potential to constrain, its exports and the measure is not based on the relevant international standards, guidelines or recommendations, or such standards, guidelines or recommendations do not exist, an explanation of the reasons for such sanitary or phytosanitary measure may be requested and shall be provided by the Member maintaining the measure. 3For purposes of paragraph 6 of Article 5, a measure is not more trade-restrictive than required unless there is another measure, reasonably available taking into account technical and economic feasibility, that achieves the appropriate level of sanitary or phytosanitary protection and is significantly less restrictive to trade. Page 73 Article 6 Adaptation to Regional Conditions, Including Pest- or Disease-Free Areas and Areas of Low Pest or Disease Prevalence 1. Members shall ensure that their sanitary or phytosanitary measures are adapted to the sanitary or phytosanitary characteristics of the area - whether all of a country, part of a country, or all or parts of several countries - from which the product originated and to which the product is destined. In assessing the sanitary or phytosanitary characteristics of a region, Members shall take into account, inter alia, the level of prevalence of specific diseases or pests, the existence of eradication or control programmes, and appropriate criteria or guidelines which may be developed by the relevant international organizations. 2. Members shall, in particular, recognize the concepts of pest- or disease-free areas and areas of low pest or disease prevalence. Determination of such areas shall be based on factors such as geography, ecosystems, epidemiological surveillance, and the effectiveness of sanitary or phytosanitary controls. 3. Exporting Members claiming that areas within their territories are pest- or disease-free areas or areas of low pest or disease prevalence shall provide the necessary evidence thereof in order to objectively demonstrate to the importing Member that such areas are, and are likely to remain, pest- or disease-free areas or areas of low pest or disease prevalence, respectively. For this purpose, reasonable access shall be given, upon request, to the importing Member for inspection, testing and other relevant procedures. Article 7 Transparency Members shall notify changes in their sanitary or phytosanitary measures and shall provide information on their sanitary or phytosanitary measures in accordance with the provisions of Annex B. Article 8 Control, Inspection and Approval Procedures Members shall observe the provisions of Annex C in the operation of control, inspection and approval procedures, including national systems for approving the use of additives or for establishing tolerances for contaminants in foods, beverages or feedstuffs, and otherwise ensure that their procedures are not inconsistent with the provisions of this Agreement. Page 74 Article 9 Technical Assistance 1. Members agree to facilitate the provision of technical assistance to other Members, especially developing country Members, either bilaterally or through the appropriate international organizations. Such assistance may be, inter alia, in the areas of processing technologies, research and infrastructure, including in the establishment of national regulatory bodies, and may take the form of advice, credits, donations and grants, including for the purpose of seeking technical expertise, training and equipment to allow such countries to adjust to, and comply with, sanitary or phytosanitary measures necessary to achieve the appropriate level of sanitary or phytosanitary protection in their export markets. 2. Where substantial investments are required in order for an exporting developing country Member to fulfil the sanitary or phytosanitary requirements of an importing Member, the latter shall consider providing such technical assistance as will permit the developing country Member to maintain and expand its market access opportunities for the product involved. Article 10 Special and Differential Treatment 1. In the preparation and application of sanitary or phytosanitary measures, Members shall take account of the special needs of developing country Members, and in particular of the least-developed country Members. 2. Where the appropriate level of sanitary or phytosanitary protection allows scope for the phased introduction of new sanitary or phytosanitary measures, longer time-frames for compliance should be accorded on products of interest to developing country Members so as to maintain opportunities for their exports. 3. With a view to ensuring that developing country Members are able to comply with the provisions of this Agreement, the Committee is enabled to grant to such countries, upon request, specified, time- limited exceptions in whole or in part from obligations under this Agreement, taking into account their financial, trade and development needs. 4. Members should encourage and facilitate the active participation of developing country Members in the relevant international organizations. Article 11 Consultations and Dispute Settlement 1. The provisions of Articles XXII and XXIII of GATT 1994 as elaborated and applied by the Dispute Settlement Understanding shall apply to consultations and the settlement of disputes under this Agreement, except as otherwise specifically provided herein. 2. In a dispute under this Agreement involving scientific or technical issues, a panel should seek advice from experts chosen by the panel in consultation with the parties to the dispute. To this end, Page 75 the panel may, when it deems it appropriate, establish an advisory technical experts group, or consult the relevant international organizations, at the request of either party to the dispute or on its own initiative. 3. Nothing in this Agreement shall impair the rights of Members under other international agreements, including the right to resort to the good offices or dispute settlement mechanisms of other international organizations or established under any international agreement. Article 12 Administration 1. A Committee on Sanitary and Phytosanitary Measures is hereby established to provide a regular forum for consultations. It shall carry out the functions necessary to implement the provisions of this Agreement and the furtherance of its objectives, in particular with respect to harmonization. The Committee shall reach its decisions by consensus. 2. The Committee shall encourage and facilitate ad hoc consultations or negotiations among Members on specific sanitary or phytosanitary issues. The Committee shall encourage the use of international standards, guidelines or recommendations by all Members and, in this regard, shall sponsor technical consultation and study with the objective of increasing coordination and integration between international and national systems and approaches for approving the use of food additives or for establishing tolerances for contaminants in foods, beverages or feedstuffs. 3. The Committee shall maintain close contact with the relevant international organizations in the field of sanitary and phytosanitary protection, especially with the Codex Alimentarius Commission, the International Office of Epizootics, and the Secretariat of the International Plant Protection Convention, with the objective of securing the best available scientific and technical advice for the administration of this Agreement and in order to ensure that unnecessary duplication of effort is avoided. 4. The Committee shall develop a procedure to monitor the process of international harmonization and the use of international standards, guidelines or recommendations. For this purpose, the Committee should, in conjunction with the relevant international organizations, establish a list of international standards, guidelines or recommendations relating to sanitary or phytosanitary measures which the Committee determines to have a major trade impact. The list should include an indication by Members of those international standards, guidelines or recommendations which they apply as conditions for import or on the basis of which imported products conforming to these standards can enjoy access to their markets. For those cases in which a Member does not apply an international standard, guideline or recommendation as a condition for import, the Member should provide an indication of the reason therefor, and, in particular, whether it considers that the standard is not stringent enough to provide the appropriate level of sanitary or phytosanitary protection. If a Member revises its position, following its indication of the use of a standard, guideline or recommendation as a condition for import, it should provide an explanation for its change and so inform the Secretariat as well as the relevant international organizations, unless such notification and explanation is given according to the procedures of Annex B. 5. In order to avoid unnecessary duplication, the Committee may decide, as appropriate, to use the information generated by the procedures, particularly for notification, which are in operation in the relevant international organizations. Page 76 6. The Committee may, on the basis of an initiative from one of the Members, through appropriate channels invite the relevant international organizations or their subsidiary bodies to examine specific matters with respect to a particular standard, guideline or recommendation, including the basis of explanations for non-use given according to paragraph 4. 7. The Committee shall review the operation and implementation of this Agreement three years after the date of entry into force of the WTO Agreement, and thereafter as the need arises. Where appropriate, the Committee may submit to the Council for Trade in Goods proposals to amend the text of this Agreement having regard, inter alia, to the experience gained in its implementation. Article 13 Implementation Members are fully responsible under this Agreement for the observance of all obligations set forth herein. Members shall formulate and implement positive measures and mechanisms in support of the observance of the provisions of this Agreement by other than central government bodies. Members shall take such reasonable measures as may be available to them to ensure that non-governmental entities within their territories, as well as regional bodies in which relevant entities within their territories are members, comply with the relevant provisions of this Agreement. In addition, Members shall not take measures which have the effect of, directly or indirectly, requiring or encouraging such regional or non-governmental entities, or local governmental bodies, to act in a manner inconsistent with the provisions of this Agreement. Members shall ensure that they rely on the services of non-governmental entities for implementing sanitary or phytosanitary measures only if these entities comply with the provisions of this Agreement. Article 14 Final Provisions The least-developed country Members may delay application of the provisions of this Agreement for a period of five years following the date of entry into force of the WTO Agreement with respect to their sanitary or phytosanitary measures affecting importation or imported products. Other developing country Members may delay application of the provisions of this Agreement, other than paragraph 8 of Article 5 and Article 7, for two years following the date of entry into force of the WTO Agreement with respect to their existing sanitary or phytosanitary measures affecting importation or imported products, where such application is prevented by a lack of technical expertise, technical infrastructure or resources. Page 77 ANNEX A DEFINITIONS4 1. Sanitary or phytosanitary measure - Any measure applied: (a) to protect animal or plant life or health within the territory of the Member from risks arising from the entry, establishment or spread of pests, diseases, disease-carrying organisms or disease-causing organisms; (b) to protect human or animal life or health within the territory of the Member from risks arising from additives, contaminants, toxins or disease-causing organisms in foods, beverages or feedstuffs; (c) to protect human life or health within the territory of the Member from risks arising from diseases carried by animals, plants or products thereof, or from the entry, establishment or spread of pests; or (d) to prevent or limit other damage within the territory of the Member from the entry, establishment or spread of pests. Sanitary or phytosanitary measures include all relevant laws, decrees, regulations, requirements and procedures including, inter alia, end product criteria; processes and production methods; testing, inspection, certification and approval procedures; quarantine treatments including relevant requirements associated with the transport of animals or plants, or with the materials necessary for their survival during transport; provisions on relevant statistical methods, sampling procedures and methods of risk assessment; and packaging and labelling requirements directly related to food safety. 2. Harmonization - The establishment, recognition and application of common sanitary and phytosanitary measures by different Members. 3. International standards, guidelines and recommendations (a) for food safety, the standards, guidelines and recommendations established by the Codex Alimentarius Commission relating to food additives, veterinary drug and pesticide residues, contaminants, methods of analysis and sampling, and codes and guidelines of hygienic practice; (b) for animal health and zoonoses, the standards, guidelines and recommendations developed under the auspices of the International Office of Epizootics; (c) for plant health, the international standards, guidelines and recommendations developed under the auspices of the Secretariat of the International Plant Protection Convention in cooperation with regional organizations operating within the framework of the International Plant Protection Convention; and 4For the purpose of these definitions, "animal" includes fish and wild fauna; "plant" includes forests and wild flora; "pests" include weeds; and "contaminants" include pesticide and veterinary drug residues and extraneous matter. Page 78 (d) for matters not covered by the above organizations, appropriate standards, guidelines and recommendations promulgated by other relevant international organizations open for membership to all Members, as identified by the Committee. 4. Risk assessment - The evaluation of the likelihood of entry, establishment or spread of a pest or disease within the territory of an importing Member according to the sanitary or phytosanitary measures which might be applied, and of the associated potential biological and economic consequences; or the evaluation of the potential for adverse effects on human or animal health arising from the presence of additives, contaminants, toxins or disease-causing organisms in food, beverages or feedstuffs. 5. Appropriate level of sanitary or phytosanitary protection - The level of protection deemed appropriate by the Member establishing a sanitary or phytosanitary measure to protect human, animal or plant life or health within its territory. NOTE: Many Members otherwise refer to this concept as the "acceptable level of risk". 6. Pest- or disease-free area - An area, whether all of a country, part of a country, or all or parts of several countries, as identified by the competent authorities, in which a specific pest or disease does not occur. NOTE: A pest- or disease-free area may surround, be surrounded by, or be adjacent to an area - whether within part of a country or in a geographic region which includes parts of or all of several countries - in which a specific pest or disease is known to occur but is subject to regional control measures such as the establishment of protection, surveillance and buffer zones which will confine or eradicate the pest or disease in question. 7. Area of low pest or disease prevalence - An area, whether all of a country, part of a country, or all or parts of several countries, as identified by the competent authorities, in which a specific pest or disease occurs at low levels and which is subject to effective surveillance, control or eradication measures. Page 79 ANNEX B TRANSPARENCY OF SANITARY AND PHYTOSANITARY REGULATIONS Publication of regulations 1. Members shall ensure that all sanitary and phytosanitary regulations5 which have been adopted are published promptly in such a manner as to enable interested Members to become acquainted with them. 2. Except in urgent circumstances, Members shall allow a reasonable interval between the publication of a sanitary or phytosanitary regulation and its entry into force in order to allow time for producers in exporting Members, and particularly in developing country Members, to adapt their products and methods of production to the requirements of the importing Member. Enquiry points 3. Each Member shall ensure that one enquiry point exists which is responsible for the provision of answers to all reasonable questions from interested Members as well as for the provision of relevant documents regarding: (a) any sanitary or phytosanitary regulations adopted or proposed within its territory; (b) any control and inspection procedures, production and quarantine treatment, pesticide tolerance and food additive approval procedures, which are operated within its territory; (c) risk assessment procedures, factors taken into consideration, as well as the determination of the appropriate level of sanitary or phytosanitary protection; (d) the membership and participation of the Member, or of relevant bodies within its territory, in international and regional sanitary and phytosanitary organizations and systems, as well as in bilateral and multilateral agreements and arrangements within the scope of this Agreement, and the texts of such agreements and arrangements. 4. Members shall ensure that where copies of documents are requested by interested Members, they are supplied at the same price (if any), apart from the cost of delivery, as to the nationals6 of the Member concerned. 5Sanitary and phytosanitary measures such as laws, decrees or ordinances which are applicable generally. 6When "nationals" are referred to in this Agreement, the term shall be deemed, in the case of a separate customs territory Member of the WTO, to mean persons, natural or legal, who are domiciled or who have a real and effective industrial or commercial establishment in that customs territory. Page 80 Notification procedures 5. Whenever an international standard, guideline or recommendation does not exist or the content of a proposed sanitary or phytosanitary regulation is not substantially the same as the content of an international standard, guideline or recommendation, and if the regulation may have a significant effect on trade of other Members, Members shall: (a) publish a notice at an early stage in such a manner as to enable interested Members to become acquainted with the proposal to introduce a particular regulation; (b) notify other Members, through the Secretariat, of the products to be covered by the regulation together with a brief indication of the objective and rationale of the proposed regulation. Such notifications shall take place at an early stage, when amendments can still be introduced and comments taken into account; (c) provide upon request to other Members copies of the proposed regulation and, whenever possible, identify the parts which in substance deviate from international standards, guidelines or recommendations; (d) without discrimination, allow reasonable time for other Members to make comments in writing, discuss these comments upon request, and take the comments and the results of the discussions into account. 6. However, where urgent problems of health protection arise or threaten to arise for a Member, that Member may omit such of the steps enumerated in paragraph 5 of this Annex as it finds necessary, provided that the Member: (a) immediately notifies other Members, through the Secretariat, of the particular regulation and the products covered, with a brief indication of the objective and the rationale of the regulation, including the nature of the urgent problem(s); (b) provides, upon request, copies of the regulation to other Members; (c) allows other Members to make comments in writing, discusses these comments upon request, and takes the comments and the results of the discussions into account. 7. Notifications to the Secretariat shall be in English, French or Spanish. 8. Developed country Members shall, if requested by other Members, provide copies of the documents or, in case of voluminous documents, summaries of the documents covered by a specific notification in English, French or Spanish. 9. The Secretariat shall promptly circulate copies of the notification to all Members and interested international organizations and draw the attention of developing country Members to any notifications relating to products of particular interest to them. 10. Members shall designate a single central government authority as responsible for the implementation, on the national level, of the provisions concerning notification procedures according to paragraphs 5, 6, 7 and 8 of this Annex. Page 81 General reservations 11. Nothing in this Agreement shall be construed as requiring: (a) the provision of particulars or copies of drafts or the publication of texts other than in the language of the Member except as stated in paragraph 8 of this Annex; or (b) Members to disclose confidential information which would impede enforcement of sanitary or phytosanitary legislation or which would prejudice the legitimate commercial interests of particular enterprises. Page 82 ANNEX C CONTROL, INSPECTION AND APPROVAL PROCEDURES7 1. Members shall ensure, with respect to any procedure to check and ensure the fulfilment of sanitary or phytosanitary measures, that: (a) such procedures are undertaken and completed without undue delay and in no less favourable manner for imported products than for like domestic products; (b) the standard processing period of each procedure is published or that the anticipated processing period is communicated to the applicant upon request; when receiving an application, the competent body promptly examines the completeness of the documentation and informs the applicant in a precise and complete manner of all deficiencies; the competent body transmits as soon as possible the results of the procedure in a precise and complete manner to the applicant so that corrective action may be taken if necessary; even when the application has deficiencies, the competent body proceeds as far as practicable with the procedure if the applicant so requests; and that upon request, the applicant is informed of the stage of the procedure, with any delay being explained; (c) information requirements are limited to what is necessary for appropriate control, inspection and approval procedures, including for approval of the use of additives or for the establishment of tolerances for contaminants in food, beverages or feedstuffs; (d) the confidentiality of information about imported products arising from or supplied in connection with control, inspection and approval is respected in a way no less favourable than for domestic products and in such a manner that legitimate commercial interests are protected; (e) any requirements for control, inspection and approval of individual specimens of a product are limited to what is reasonable and necessary; (f) any fees imposed for the procedures on imported products are equitable in relation to any fees charged on like domestic products or products originating in any other Member and should be no higher than the actual cost of the service; (g) the same criteria should be used in the siting of facilities used in the procedures and the selection of samples of imported products as for domestic products so as to minimize the inconvenience to applicants, importers, exporters or their agents; (h) whenever specifications of a product are changed subsequent to its control and inspection in light of the applicable regulations, the procedure for the modified product is limited to what is necessary to determine whether adequate confidence exists that the product still meets the regulations concerned; and 7Control, inspection and approval procedures include, inter alia, procedures for sampling, testing and certification. Page 83 (i) a procedure exists to review complaints concerning the operation of such procedures and to take corrective action when a complaint is justified. Where an importing Member operates a system for the approval of the use of food additives or for the establishment of tolerances for contaminants in food, beverages or feedstuffs which prohibits or restricts access to its domestic markets for products based on the absence of an approval, the importing Member shall consider the use of a relevant international standard as the basis for access until a final determination is made. 2. Where a sanitary or phytosanitary measure specifies control at the level of production, the Member in whose territory the production takes place shall provide the necessary assistance to facilitate such control and the work of the controlling authorities. 3. Nothing in this Agreement shall prevent Members from carrying out reasonable inspection within their own territories. | false |
# Extracted Content THE SEEDS ACT, 2003 ARRANGEMENT OF SECTIONS Section Title PART I PRELIMINARY PROVISIONS 1. Short title and commencement. 2 Interpretation. PART II ESTABLISHMENT OF THE NATIONAL SEEDS COMMITTEE 3. Establishment of the National Seeds Committee. 4. Committee membership. 5. Functions of the Committee. 6. Meeting of the Committee. 7. Establishment of the Sub-Committee. 8. Appointment of other staff. 9. Issuance of Permit. 10. Establishment of the Seed Certification Institute. 11. Delegation of Powers of the Minister. 12. Minister to make orders. PART III IMPORTATION, EXPORTATION, AND SALES OF SEEDS 13. Condition for Importation, Exportation and Sale of seeds. 14. Restriction on sale importation or exportation of seeds. PART IV REGISTRATION OF SEEDS DEALERS 15. Registration of seeds dealers. 16. Issuance of certificate of registration. 17. Cancellation of certificate of registration. 18. Appeals. 19. Prohibition. 20. Duty to keep records. 21. Approval and listing of varieties. 1 2003 Seeds No. 18 2 22. Powers of Inspectors. 23. Obstruction of Inspectors. 24. Analysis of a sample. 25. Tempering with samples. PART V MISCELLANEOUS PROVISIONS 26. Offences and Penalties. 27. Offences by a body corporate or firm. 28. Evidence. 29. Limitation. 30. Indemnity. 31. Exempted sales. 32. Repeal and Savings. 33. Power to make regulations. SCHEDULE Seeds 2003 No. 18 4 and identity to provide a source for the initial and recurring increase of seeds;or if of foreign origin, that the seed is certified by a recognised certification agency or by the Chief Seed Quality Controller as being of basic grade; ''breeders grade'' means approved seed of a variety that has been produced by the breeder responsible for breeding and maintanance of that variety under condition which ensure that the specific characteristics of the variety are mantained and which provide the source for the initial land recurent increases of seeds of the pedigree grades; or if of foreign origin, that the seed is certified by a recognised certification agency as being of breeders grade; ''Certification Agency'' means an agency appointed by the Minister pursuant to section 10; ''certified grade'' means the approved progeny of breeder, foundation, registered or certified seed managed to mantain satisfactory genetic identity and purity the production of which is supervised and approved by the Institute and which provides the source of the initial and recurring increase of seeds; or if of foreign origin, that the seed is certified by a recognised certification agency or by the Chief Quality Controller as being of certified grade; ''Committee'' means the National Seed Committee established under section 3 of this Act; "class name'' includes any mark, description or designation of a class; ''inspector'' means a person appointed or designated as an inspector pursuant to section 8; ''Director'' means a person responsible for Agricultural Development; ''label'' includes any legend, word, mark, symbol or design applied or attached to, included in, belonging to or accompanying any seed or package; ''Minister'' means the Minister responsible for agriculture; "noxious weed seed'' means any seed potentially injurious to agriculture so declared by the Minister by notice published in the Gazette to be noxious weed seed for the purposes of this Act; ''package'' includes a sack, bag, barrel, case or any other container in which seed is placed or packed; "place'' includes any building, vehicle, vessel, railway, car or aircraft; "person'' includes an individual, corporation, society, association, enterprise, trustee, receiver, or any other institution; ''Quality Declared Seed'' means seed produced by a registered smallholder farmer which conforms to the specified standards for crop 4 2003 No. 18 2003 5 Seeds species concerned and which has been subject to the quality control I measures prescribed in the regulations to be made under this Act; ''Recognised Certification Agency'' means a registered certification agency of a country, which is a member to an International Seed Organization to which Tanzania is also a member or an official seed certification agency from a country, whose seed quality standards have been approved by the Director to be similar or higher than those prescribed under this Act or Regulations; ''standard seed'' means emergency seed authorized for use by the Minister; ''seed'' means that part of plant which is or is intended to be used for propagation and includes any true seed, any vegetative material including seedling, corm, cutting, bulb, bulbil, layer, marcott, root, runner, scion, set, split, stem, stock, stump, sucker or tuber so used or intended to be so used; "seed dealer'' include importers, exporters, processors, producers, sellers and distributors of seeds and owners of seed testing laboratories or any other person dealing with seed under this Act; "sell'' includes sell, offer for sell expose for sell, have in possesion for sale, and distribution or give away; ''Subcommittee'' means the Seed Sub-Committee established under section 7; ''Tanzania Pedigree Class'' means a class that contains one of the words ''Breeders'', ''Basic'', ''Certified 1 '', ''Certified 2'', where 1 means first generation 2 means second generation; ''Variety'' means plant variety. ''weed seed'' means any plant injurious to agriculture, which is declared to be so by the Minister for the purpose of the Plant Protection Act. PART II ESTABLISHMENT OF THE NATIONAL SEEDS COMMITTEE 3. There is hereby established a technical Committee to be known as the National Seeds Committee. Establi- shment of the Seeds commi- ttee 2003 No. 18 6 Seeds 4.-(l) The National Seeds Commitee shall be composed of the Commi- following members- ttee Member- (a) the Permanent Secretary to the Ministry for the time being ship responsible for agriculture who shall be the chairperson of the committee; (b) the officer responsible for co-ordination and supervision of the seeds industry in the Ministry and shall be the secretary to the Committee; (c) the head of the division in the Ministry for the time being responsible for crop research; (d) the head of the division in the Ministry for the time being responsible for crop development; (e) the Chief Seed Quality Controller; and (f) the Registrar of Plant Varieties. (2) The Minister shall appoint the following to be members of the National Seeds Committee- (a) a representative from the Tanzania Seed Trade Association; (b) a representative from higher learning institution responsible for agriculture; and (c) a representative from seed consumers'association;'' (3) The Chairperson of the Committee may after consultation with members co-op other members, to attend and speak on any matter at any meeting of the Committee, but a person so co-opted shall not have the right to vote. 5.-(1) The National Seeds Committee shall be a Stakeholders' Forum responsible for advising the Government on all matters relating to the Functions of the Committee development of the Tanzania seed industry.''; (2) Without prejedice to the generality of subsection (1), the functions of the National Seeds Committee shall include: - (a) to advise the Ministry on formulation and implementation of the seed industry policy and implementation of guidelines; (b) to advise the Ministry on the implementation and amendment of the seeds legislation; (c) to advise the Minister on all matters relating to seeds; (d) to give general advice in the co-ordination and supervision of the seed industry; (e) to advise the Minister on approval of plant varieties. No. 18 2003 7 Seeds 6. The Committee shall regulate its own procedures of conducting its Meetings of the meetings. Committee 7. The National Seeds Committee may, for the purpose of effective Establish- implementation of the functions of the Committee establish such number ment of Sub- of sub-Committees to perform specific functions as it may deem necessary. Committees 8.-(1) The Minister may, by notice published in the Gazette, appoint Appoint- or designate, from time to time, qualified persons to be Inspectors and ment of analysts who shall have and exercise powers generally respecting seeds other staff in accordance with the provisions of this Act or as may be prescribed. (2) The Director or any other person appointed by him shall be the Chief Seed Quality Controller and the head of the national seed quality control service. (3) Every person appointed or designated as Chief Quality Controller, analyst or Inspector under sub-section (1) shall be given a certificate, identity card or a document as a proof of his appointment or designation which shall be produced on entering any place in the exercise of his powers under this Act. (4) The Chief Seed Quality Controller may permit an analyst to perform internal seed quality control for a private specified producer, processor, seller or as the case may be, distributor of seed. (5) No person shall, while holding the office of Seed Quality Controller, Inspector, or Analyst engage in any business connected with the production, processing, sale or importation of seed. 9. The Chief Seed Quality Controller may permit a private specified producer, processor, seller or distributor to employ an analyst appointed under section 8 to effect the internal seed quality control. Issuance of permits Establish- 10.-(1) There is hereby established a body cooperate to be known as ment of the Tanzania Official Seeds Certification Institute (TOSCI), which shall- Seed (a) have perpetual succession and a common seal; (b) be capable of entering into contracts in its own name; Certifi- cation Institute 2003 8 No. 18 Seeds (c) be capable of purchasing or acquiring any movable and immovable property. (2) Any proceedings against the Institute in contract may only be instituted by or against the Government in accordance with the Government Proceedings Act, 1967. (3) The provisions of the First Schedule to this Act shall have effect as to the constitution, tenure of office, management and proceedings of and other matters relating to the Governing Council of the Institute. Delega- 11.-(1) The Minister may, with the exception of his power of tion of delegation, assign or delegate some or all of his powers under this Act to powers any competent institution or individual. of the Minister (2) Every assignment or delegation shall be revocable at will, and no delegation shall prevent the exercise of any power by the Minister. (3) In exercising the powers of delegation, assignment or appointment, the Minister may enter into contracts with competent institutions or individuals under such terms and conditions as the Minister may determine. 12. The Minister may make orders: Minister (a) prescribing the varieties of the seeds of which may be sold in to make orders Tanzania or imported into Tanzania; (b) classifying the species of plants the seeds of which he deems are weed seeds or noxious seed weed in relation to seed classes under this Act; (c) in respect of the detention of anything seized or placed under stop sale under the provisions of this Act and for the preservation or safeguarding anything so detained; (d) in respect of the disposition of anything forfeited to the Government under this Act. Seeds 2003 9 No. 18 PART III IMPORTATION, EXPORTATION AND SALES OF SEEDS 13.-(1) Any person, who intends to deal with importation, exportation, production, processing, distribution, sale or advertisement for sale of seeds shall obtain a permit from the Director or any other person authorized by the Director in that behalf Condi- tion for impor- tation, expor- tation and sale of seeds (2) The Director shall, before granting the permit or licence required under subsection(l) ensure that the standards and conditions for importation, production, processing, distribution sale or advertisement for sale of seeds, as provided for in the Plant Protection Act and in this Act, have been complied with. Act No.13 of 1997 (3) The Minister shall for the purpose of this Act, prescribe the plant varieties and standards of the seeds for importation, exportation, production, processing and distribution. (4) Any person who contravenes or fails to comply with a provision of this section, Orders or Regulations made under this Act in respect of matters specified in this section, commits an offence. 14.-(1) Any person who - (a) sells, import, exports any seed under a grade name or designation so closely resembling a grade name prescribed under the provision of this Act as likely to be mistaken therefor; or (b) applies, to any seed or package containing seed, a grade name prescribed under the provision of this Act as likely to be mistaken therefor, shall have the duty to ensure that, the seed meets the requirement prescribed for the grade and is marked, packed and labelled as required by Regulations or Orders made under this Act. (2) The Minister may prescribe classes of seeds which shall be exempted from the requirements of subsection (1). (3) Any person, who contravenes the provisions of subsection (1), commits an offence. Restri- ction on sale, importa- tion or exporta- tion of seeds Seeds 2003 No. 18 10 PART IV REGISTRATION OF SEEDS DEALERS 15.-(1) Any seed importer, exporter, producer, processor, distributor or seller shall, before operating, register with the Director or any other person appointed by him in that behalf Registra- tion of seeds dealers (2) Any owner or operator of a seed processing factory or seed testing laboratory shall be required to obtain registration of his factory or laboratory from the Director. (3) Every application for registration under subsection (1) shall be, submitted to the Director in the prescribed manner and shall be accompanied by the prescribed registration fee. (4) The Director may, after receiving an application for registration- (a) grant registration if he is satisfied with the contents of application; or (b) refuse an application. 16.-(l) The Director shall after granting the registration, issue a Issuance certificate of registration to a seed dealer subject to such terms and of certificate conditions as may be determined by the Minister. of registra- tion (2) A registration certificate granted shall be conspicuously displayed on the business premises of a registered seed dealer. 17.-(l) The Director may, if he is satisfied that any conditions subject to which a seed dealer was registered have not been complied with, cancel the certificate of registration issued to a seed dealer. Cancella- (2) The Director shall not cancel the registration of a seed dealer under this section unless the dealer has been given an opportunity to show cause as to why the registration should not be cancelled. 18. Any person who is not satisfied by the decision of the Director for refusal of registration, cancellation of registration or permit under the provisions of this Act may, within thirty days appeal to the Minister whose decision shall be final. Appeals tion of certificate of registra- tion No. 18 2003 11 Seeds 19.-(1) No person shall- Prohibi- . (a) import, export, produce, process, distribute or sell seeds unless he is registered as such under this Act; or (b) test, process or multiply seeds otherwise than in a registered laboratory seed processing factory or, as the case may be, a seed multiplication farm. (2) Notwithstanding subsection (1), nothing in this Act shall, be construed as preventing the sale of quality declared seeds as such to a neighbour fanner, whereby such seeds are grown by a smallholder fanner for use as seeds in his own farm. (3) Where a registered Seed Dealer contracts any person to import, export, produce, process, distribute or sell seeds, that person shall be bound by the terms and conditions provided for under this Act. 20.-(1) Every producer, processor, seller or distributor of seeds shall have the duty to keep within his premises, detailed records, by lot, of seed produced, purchased, sold, tested, and labelled or treated as the case may be and such records shall be provided to the Inspector whenever requested. (2) Any person who contravenes the provisions of this section, commits an offence and is liable on conviction to a fine not exceeding one million shillings or to imprisonment for a term not exceeding three months, or to both such fine and imprisonment. 21.-(l) The Minister shall upon advice by the National. Seeds Approval Committee approve any new plant variety. and listing of varieties (2) The Director shall establish and maintain a national catalogue of approved plant varieties and shall cause to be entered therein varieties imported, sold or distributed in Tanzania. (3) Subject to the recommendations of the National Seeds Committee, the Director shall publish in the Gazette the seed varietties entered in the national catalogue. 22.-(l) Any Inspector may, at any reasonable time, enter any place where he reasonably believes there is any seed to which this Act applies tion Duty to keeps records Re- consider- ation of dispute by the Public Service Joint Powers of Staff Inspectors Council Seeds 2003 12 No. 18 and may open any package found therein that he has reasons to believe contains such seed and may sample the same for the purpose of ensuring that the provisions of this Act, or of any regulations or orders made under this Act are being complied with. (2) An Inspector may, for the purposes of securing compliance with the provisions of this Act or of any Regulations or Orders made under this Act or for the purposes of detecting and establishing any breach of any such provisions - (a) conduct field inspection and or take samples of any seed found in any package or place and submit such samples to the official seeds testing laboratory for testing; or (b) require any person to produce for inspection or for the purpose of obtaining copies thereof or extracts therefrom, any books, shipping bills, bills of lading or other documents or papers relating to any seed to which this Act applies. (3) The owner or person in charge of any premises described under this section and every person found therein, shall give to an Inspector all reasonable assistance in his power to enable the Inspector to carry out his duties and functions under this Act. (4) An Inspector may if he has reasonable grounds, that any of the provisions of this Act, or Regulations or Orders made under this Act has been violated, seize, issue or stop sale of the seeds or package by means of or in relation to which the violation was committed. Provided that, any seeds or package seized or placed under stop sale pursuant to this subsection shall not be detained after- (a) the provisions of this Act and the regulations and orders have, in the opinion of the Inspector, been complied with; or (b) the expiration of three months from the day of seizure or stop sale, unless before that date proceedings have been instituted in respect of the violation, in which event the seeds or package may be detained until the proceedings are finally concluded. (5) An Inspector shall before inspection of the premises, take such steps as are reasonably practical to afford the owner of any seeds an opportunity to be present while an inspection under this Act is being carried out. Seeds No. 18 2003 13 Obstru- 23. Any person, being the owner or person entrusted with the charge ction of and custody of any seed lot who- Inspec- (a) refuses to allow the Inspector to take a sample of the seed tors from any premises which he is authorised under this Act to take a sample, or who otherwise wilfully delays or obstructs the Inspector; or (b) wilfully makes false or misleading statement either verbally or in writing to the Inspector or other official engaged in carrying out his duties or functions under this Act; commits an offence. 24. An analyst, who receives a sample taken under the provisions of Analysis of a this Act from an Inspector, shall as soon as is practicable analyse the same, and shall give a report in the prescribed form specifying the result of the analysis. sample Tempe- 25. Any person, who fraudulently tampers or interferes with any seed lot that any sample of it is taken or submitted for analysis under this Act does not correctly represent the seed lot, or fraudulently tampers or interferes with any sample taken or submitted for analysis under this Act, commits an offence. ring with samples PART V MISCELLANEOUS PROVISIONS 26.-(1) Any person, who contravenes a provision of this Actor of any subsidiary legislation made under this Act, commits an offence and shall, Penalties except as otherwise provided, be liable on conviction to a fine of not less than one million shillings but not exceeding five million shillings or to imprisonment for a term not exceeding one year, or to both such fine and imprisonment. (2) The court may in addition to any penalty imposed under this Act, order any article in respect of which such offence has been committed or which has been used for the commission of such offence to be forfeited. (3) The Minister shall be responsible for the disposal of anything forfeited to the Government under subsection (2). Offences and 2003 14 No. 18 Seeds (4) Where an offence has been committed and by reason of that commission a person has suffered a direct damage or loss of his property, the court may, in addition to the penalty provided for under subsection (1), order the offender to compensate the person who has suffered such loss or damage. (5) The court may in the case of a persistent offender, order, in addition to penalties provided for under this section, the withdrawal of any permit or, certificate of registration or any other right held by the offender under this Act. 27.-(1) Any act which if done by an individual would be an offence against this Act or any regulations or orders made under this Act shall, if done by a body corporate, be an offence by every Director, Secretary and Manager thereof unless he proves that the offence was committed without his consent or connivance and that he exercised all such diligence to prevent the commission of the offence as he ought to have exercised having regard to the nature of his functions in that capacity and to all circumstances. Offences by a body corporate or firm (2) Where an offence against this Act or any regulations or orders made under this Act has been committed by a partner in a firm, every person who at the time of the commission of the offence was partner in that firm, or was purporting to act in that capacity, shall be deemed to have committed that offence unless he proves that the offence was committed without his consent and or connivance and he exercised all such diligence to prevent the commission of the offence as he ought to have exercised having regard to the nature of his functions in that capacity and to all the circumstances. 28.-(l) Any document purporting to be a report under the hand of an analyst appointed under the provisions of this Act, on any sample duly submitted to him for analysis and report, may be admitted in evidence in any civil or criminal proceedings relating to the seed sampled without further proof, and shall be sufficient evidence of the facts stated therein unless the defendant or person charged requires that the analyst be called as a witness. Evidence (2) Where the defendant or person charged requires that the analyst be called as a witness he shall pay any reasonable costs incurred by such analyst in attending the trial. 15 2003 No. 18 Seeds (3) Any sample which has been taken in the prescribed manner by an Inspector shall, unless proved otherwise be deemed to be of the same composition, to have the same qualities and to possess in all other respects the same properties of the seed lot from which it was drawn. 29. No proceedings in respect of an offence under this Act or under Limita- any subsidiary legislation made under this Act shall be instituted after tion the expiry of two years from the date when the subject matter of the proceedings arose, if the offence is a misrepresentation of the plant variety name or purity of the plant variety. 30. Without prejudice to the provisions of section 284A of the Penal Code, no matter done by any person exercising or purporting to exercise any function under this Act or under any subsidiary legislation made under this Act shall, if done in good faith in the execution or purported execution of the functions under any of the provisions of this Act or such subsidiary legislation, subject any such person to any action liability, claim or demand whatsoever. Indemnity Cap. 16 31.-(l) The provisions of this Act shall not apply to a sale, offer or exposure for sell, where such sale is made by a bailiff, court broker or other officer in the course of executing any order or process of a court. Exempted sales (2) The term ''sell'' under sub-section (1) shall not be construed to mean selling of seeds or anything, which otherwise does not meet quality standards prescribed under this Act or Regulations made under this Act. 32.-(l) Subject to the provisions of subsection (2), the Seed (Regulations of Standards) Act, 1973, is hereby repealed. Repeal and savings Act,No.29 (2) Notwithstanding subsection (1), any applicable Regulations, Rules, Order or Notice made under the Seed (Regulation of Standards) Act, 1973, shall remain in force until such time as it is revoked cancelled or replaced. of 1973 33.-(l) The Minister may, after consultation with the Committee, make regulations for the better carrying into effect of the provisions of this Act. Power to make regula- tions 33.-(l) The Minister may, after consultation with the Committee, make regulations for the better carrying into effect of the provisions of this Act. 16 No. 18 Seeds 2003 (2) Without prejudice to the generality of subsection (1), the Minister may make regulations - (a) prescribing various forms to be applied under various provisions of this Act; (b) prescribing the manner in which - (i) returns and information shall be rendered or furnished; (ii) seeds intended for sale shall be packed, labelled, marked and sealed, and the manner in which seeds may be advertised or exposed for sale; (iii) seed samples are to be taken and dealt with; (c) prescribing the methods by which analyses are to be carried out by analysts under the provisions of this Act; (d) prescribing the terms and conditions and the manner in which seed may be inspected, classified and tested; (e) prescribing the minimum field and seed standards for breeders', basic, certified 1, certified 2, quality declared seed and also seed standards for standard seed class; (f) prescribing standards for a seed testing laboratory, processing factory, seed warehouses, seed selling or distribution points shops; (g) prescribing procedures for the establishment of quality declared seed production; (h) respecting the fees that may be charged for any services rendered under this Act; (i) generally prescribing anything which requires to be prescribed under this Act. (3) The Minister may restrict the application of any of the regulations made under the provisions of subsection (1) to specialised areas or to any group or groups of people or premises. (4) Regulations made under this section may provide for penalties for the breach thereof not in excess of the penalties mentioned in this Act. (5) All regulations made under this section shall be published in the Government Gazette. 2003 16 17 2003 No. 18 Seeds SCHEDULE (under section 10) CONSTITUTION, FUNCTIONS AND MANAGEMENT OF THE SEED CERTIFCATION INSTITUTE 1. The power to carry out the functions and management of the business and affairs of the Institute shall be vested in the Institute's Management Committee. Manage- ment of the Agency Constituion 2.-(1) The Management Committee of the Institute shall comprise of the following of the members- Manage- (a) one member from the Crop Development Division of the Ministry of ment Agriculture responsible for seed issues; Committee (b) the Head of the National Post-entry Plant Quarantine Station; (c) one member from the Reseach and Development Division of the Ministry of Agriculture, responsible for biotechnology issues; (d) the Chief Seed Certification Officer who is the head of the Tanzania Official Seed Certification Institute. (2) The Minister shall appoint the Chairperson of the Management Committee and one member from the Tanzania Seed Trade Association to be a member of the Management Committee: 3. Members of the Management Committee shall hold office for a period of three The Term of years and shall be eligible for re-appointment. 4.-(1) Three members of the Management Committee shall constitute a quorum at any meeting and all decisions to be arrived at by the Management Committee shall be decided by a simple majority of the members present. (2) Each member of the Management Committee shall have one vote and in the event of equality of votes, the Chairperson of the meeting shall have a second or casting vote in addition to his deliberative vote. 5. Minutes in proper form of each meeting of the Management Committee have to be property kept and shall be confirmed by the Management Committee at its next sitting and signed by the Chairperson of the meeting. 6. The Management Committee shall have power to regulate its procedures in respect of meetings and proper conduct of its business. 7.-(1) The Institute shall have the following duties: (a) to conduct seed field inspections; (b) to effect sampling and testing; the manage- ment Commi- ttee Members Quorum Minutes of Manage- ment Committee Procedures Functions of the Institution 18 No. 18 2003 Seeds (c) to conduct seed inspections; (d) to accredit seed sampling and seed testing laboratories; to charge fees or otherwise generate revenue from the services rendered; to ensure that the revenue accruing from the fees or any other charge (e) (f) guarantees sustainable and quality services; to train seed producers, seed inspectors and seed analysts; to liaise with other International Organizations such as the International Seed Testing Association (ISTA) on seed related issues; to carry out variety performance tests; and (g) (h) (i) (j) to carry out pre and post control tests. (2) The Institute shall not engage itself, directly or indirectly in any trade or business connected with the production, processing, importation, sale or distribution for sale of any seed. 8. The Minister in consultation with the Management Committee shall appoint the Chief Certification Officer. 9. The Management Committee may, appoint at such salaries and upon such terms and conditions such officers and employees, for the proper and efficient performance of necessary. 10.-(1) There shall be a Common Seal of the Institute which shall be of such shape, size and form as the Management Committee may determine. (2) The Seal of the Institute shall not be affixed to any instrument except in the presence of the Principal and one Management Committee member. 11. The Institute shall keep and maintain proper books of accounts and records relating to its transactions in accordance with acceptable accounting standards: (a) the financial year of the Institute shall end on 30th June of each year; (b) the books of accounts shall be audited at the end of each financial year by an authorized auditor duly registered under the Auditors and Accountants (Registration ) Act, 1972. The auditors shall be appointed by the Management Committee; (c) the accounts and reports of the auditors shall be submitted to the Management Committee not later than four months after the end of each financial year, and the Management Committee shall submit a copy of the audit report to the Institute within two months after they have been audited; Seal of the Institute Management Committee may appoint employees of the Institute Appoint - ment of the Institute's Chief Certification Officer Accounts and audit Act No. 33 of 1972 | false |
# Extracted Content 1 GOVERNMENT NOTICE NO. 37 published on 9/2/2007 THE SEEDS ACT, 2003 (No. 18 of 2003) ______ THE SEEDS REGULATIONS, 2007 _______ Made under section 33 _______ ARRANGEMENT OF SECTIONS PART I PRELIMINARY PROVISIONS Regulation Title 1. Short title and commencement date. 2. Interpretation. PART II REGISTRATION OF SEED DEALERS 3. Submission of application PART III VARIETY REALEASE, REGISTRATION AND DEREGISTRATION 4. Restriction for variety release. 5. Establishment of the sub-Committees. 6. Composition and meeting of the NVRC and NPT-TC. 7. Application for the variety release and procedure for conducting NPT. 8. Variety registration. 9. Variety deregistration. PART IV SEED CLASSES AND STANDARD 10. Class name and standards. 11. Additional requirements with respect to standard. 2 PART V MARKING AND LABELING 12. Restriction to use variety name. 13. Necessary information in marking and labeling. 14. General labeling requirements. 15. Application of labeling requirements. 16. Labeling of the seeds specified in Tables of the First Schedule. 17. Labeling of mixture of seed. 18. Labeling of roots, tubers, and pyrethrum seed. 19. Labeling of onion sets and multiplier onions. 20. Labeling of forage seed. 21. Labeling of mixtures of seed specified in Tables 8 and 9 of the First Schedule. 22. Official Tag. 23. Inter-agency labels. 24. General provision with respect to official and inter-agency labels. 25. Chief Seeds Certification Officer to authorize use of official or interagency certification tags. PART VI SEED CERTIFICATION 26. Restriction on uncertified seed. 27. Seed crop inspection. 28. Appeal against results of field inspection. 29. Harvesting of seed. 30. Seed processing. 31. Storage of processed seed. 32. Seed for sale. 33. Seed importation. 34. Seed exportation. 35. Pre and post control plots. PART VII SEED SAMPLING AND TESTING 36. Sampling of seeds. 37. Sampling intensity. 38. Seeds testing. 39. Exemption. 40. Fees. 41. Appeals. 42. Authorization of Inspectors, Samplers and Analysts. 43. Suspension or cancellation of authorization. 44. Change of variety name. 45. Detention and stop sale order. 3 46. Offences. 47. Retention. 48. Prohibited, restricted and noxious seeds. 49. Revocation. 4 GOVERNMENT NOTICE NO. 37 published on 9/2/2007 THE SEEDS ACT, 2003 (No. 18 of 2003) ______ THE SEEDS REGULATIONS, 2006 _______ Made under section 33 _______ PART I PRELIMINARY PROVISIONS Short title and commencement date 1. These Regulations may be cited as the Seeds Regulations, 2006 and shall come into operation on the date of their publication. Interpretation 2. -(1) In these Regulations, unless the context otherwise requires – Act. No 18 “Act” means the Seed Act, 2003; “authentic sample” means a sample for the released variety kept or maintained by a recognized gene bank for future reference; “authorisation” means a formal of a person or organization as specified in these Regulations; "authorized Analyst" means a person who has been authorized to undertake testing of seeds by the Tanzania Official Seed Certification Institute for the purposes of analyzing seeds; "authorized field Inspector " means a person authorized to undertake field inspection by the Tanzania Official Seed Certification Institute; "authorized Inspector " means a person authorized to undertake inspection of seeds by the Tanzania Official Seed Certification Institute; "authorized laboratory " means a laboratory authorized by the Tanzania Official Seed Certification Institute for purposes of testing seeds; "authorized sampler" means a person who has been authorized to undertake sampling of seeds by the Tanzania Official Seed Certification Institute for purposes of sampling seeds; "authorized seeds Inspector" means a person authorized to undertake seeds inspection by the Tanzania Official Seed Certification Institute; Act No.22 of 2002 “breeder” shall have a meaning ascribed to it under the Plant Breeders’ Rights 5 Act; "certificate of registration" means a certificate issued by the Director certifying that the holder of the said certificate is registered as a seeds dealer pursuant to section 16 of the Act; “Chief Seed Certification Officer” means a person appointed and designated as Chief Seeds Certification Officer pursuant to paragraph 8 of the Schedule to the Act, and shall head the Tanzania Official Seed Certification Institute; “Chief Seed Quality Controller” means the Director or any other person appointed by him under section 8 (2) of the Act; “composite sample” means a combination of primary samples drawn from the same seed lot and placed in a suitable container; “DUS” means Distinctness, Uniformity and Stability; “fasten” with respect to package means sealing in such a manner that it is impossible to open the package, without leaving evidence of it having been opened; “germination in respect to seed” means the emergency and development of the seedling to a stage where the aspect of its essential structures indicates whether or not it is able to develop further into a satisfactory plant under favorable condition; “inert matter” means all seed-like structures from both crop and weed plants and other matter which is not defined as pure seed or other seeds; "Institute" means the Tanzania Official Seed Certification Institute established by section 10 of the Act; "inter-agency certification tag" means an official tag in respect of seeds that are certified by a Recognized Certification Agency; “ ISTA” refers to International Seed Testing Association; "lot number or designation" means a number, mark, symbol or test number that identifies a seeds lot; “Ministry” means the Ministry responsible for agriculture; “NPT” means the National Performance Trial; “NPT-TC” means the National Performance Trial Technical Committee; “NVRC” means the National Variety Release Committee; “OECD” means Organization of Economic Cooperation and Development; "official laboratory" means a seed testing laboratory under the management of the Tanzania Official Seed Certification Institute; "official sample" means a sample of seeds that has been drawn by an Inspector in the prescribed manner; "official tag" means a tag in respect of seed that is derived from a crop grown in Tanzania and classified by the Tanzania Official Seed Certification Institute; “ other seed” ,means seed units of any plant species other than that of pure seed ; “Permanent Secretary” means the permanent secretary in the Ministry for the time being responsible for agriculture; “primary sample” means each probe, handful of Seeds drawn from a seeds lot as a sample and when a seeds lot is sampled either in containers or bulk, several primary samples are drawn from different containers or from 6 different places in the bulk; “pure seed” means the species stated by applicant or found to predominate in the test and shall include all botanical varieties and cultivars of that species ; “ release” means discharge for commercial multiplication, production or sale of seed or plant varieties; "seed conditioning” means preparation by cleaning, processing, packing, treating or changing in any other manner the nature of a seeds lot; "seed lot" means a specified quantity of seeds, each portion of which is within reasonable limits, uniform with respect to species, variety, purity, germination, and other quality requirements; "Seed Testing Certificate" means a document issued by Tanzania Official Seed Certification or authorized seeds testing laboratory or a recognized seeds certification agency, certifying that the seeds identified therein meets the specified laboratory standards; “seed certification” means a legally sanctioned system for quality control in the process of producing, processing and marketing of seed for the purposes of maintaining and ensuring quality and genetic purity; “seed processing” means treatment of seed other than testing which the seeds is subjected to after harvesting; “seed production” means operations leading up to and including harvesting of the seeds from the seeds field; “Seed Testing Report” means a document issued by an official or authorize seed testing laboratory stating the results of the laboratory analysis requested; “seed testing” means the examination of sample of seeds with a view to determine its quality; “submitted sample” means a composite sample or portion of a composite sample of a size appropriate for tests submitted to a testing station for quality tests; “TOSCI” means Tanzania Official Seed Certification Institute established under section 10 of the Act; “undesirable seed” means seeds that are light, undersized, off-colour, shrunken, immature, damaged, diseased, injured, sprouted or frosted seed; “UPOV” means Union for Convention on Protection for New Varieties; "varietal blend" means a mixture seed that contains two or more varieties of the same plant species; "variety name" includes a word, a number or a letter or combination of number and letter used to designate a variety; and “working sample” means a portion of a submitted sample on which a quality test is made. PART II REGISTRATION OF SEED DEALERS Submission of application 3.-(1) An application for the registration as seed dealer shall be submitted to the Director on Form SR I set out in the Fifth Schedule to these Regulations. 7 (2) Each application shall be accompanied by the appropriate fees as set out in the Sixth Schedule to these Regulations. (3) The Director shall register the applicant and issue a registration certificate contained as set out in Form SR II in the Fifth Schedule to these Regulations upon being satisfied that the applicant has complied with the requirements for registration. PART III VARIETY RELEASE, REGISTRATION AND DEREGISTRATION Restriction for variety release 4. No variety shall be released in Tanzania unless it has passed DUS test, evaluated through the National Performance Trial and recommended for release by the National Seed Committee. Establishment of sub- Committees 5.-(1) There are hereby established sub-Committees of the National Seed Committee to be known as the National Variety Release Committee (NVRC) and the National Performance Trial Technical Committee (NPT-TC). (2) The National Variety Release Committee shall be responsible for reviewing recommendations from the National Performance Trial Technical Committee and recommend for variety release to the National Seed Committee. Composition and meetings of the NVRC and NPT- TC 6.-(1) The National Variety Release Committee shall be composed of the following members:- (a) the Director for the time being responsible for crop development who shall be the Chairman; (b) the Director for the time being responsible for research in the Ministry; (c) one officer responsible for co-ordination and supervision of plant quarantine services in the country; (d) one officer responsible for co-ordination and supervision of seeds industry in the Ministry, who shall be the Secretary; (e) Chief Seed Certification Officer; (f) Curator of the gene bank at the National Plant Genetic Resources Centre; (g) head of section responsible for National Performance Trial within the TOSCI; (h) one plant breeder from agricultural universities to be appointed by the Permanent Secretary; (i) one pathologist from research institute within the Ministry responsible for agriculture to be appointed by the Permanent Secretary; (j) Registrar of Plant Breeders’ Rights; (k) a representative from Tanzania Seed Trade Association to be appointed by the Permanent Secretary upon recommendation by the respective association; (l) Chief Executive Officer responsible for Agricultural Seed Agency 8 (m) a representative from the Plant Breeders’ Association to be appointed by the Permanent Secretary upon recommendation by the respective association; and (n) a representative from farmers association to be appointed by the Permanent Secretary upon recommendation by the respective association. (2) The National Performance Trial Technical Committee shall be composed of the following members :- (a) Chief Seed Certification Officer, who shall be the Chairman; (b) one Seed technologist from department responsible for co- ordination and supervision of seeds industry in the Ministry to be appointed by the Permanent Secretary; (c) one plant breeder from the department responsible for research in the Ministry to be appointed by the Permanent Secretary; (d) head of section responsible for National Performance Trial within TOSCI, who shall be the Secretary; (e) one plant pathologist from an agricultural university to be appointed by the Permanent Secretary, upon consultation with agricultural universities; (f) one plant entomologist from any higher learning institution to be appointed by the Permanent Secretary, upon consultation with higher learning institutions; (g) one plant breeder from plantation crops research institution to be appointed by the Permanent Secretary, upon consultation with respective institutions; and (h) one seed producer representing Tanzania Seeds Trade Association to be appointed by the Permanent Secretary, upon consultation with respective associations; (3) The National Variety Release Committee and the National Performance Trial Technical Committee may co-opt any person to attend its meetings. (4) The National Variety Release Committee and the National Performance Trial Technical Committee shall regulate their own procedures for conducting meetings. Application for variety release and procedure for conducting NPT 7.-(1) Any person who intends to release a variety shall be required to submit to the Tanzania Official Seed Certification Institute an application for DUS test and NPT, on Form SR IIIA and SR IIIB respectively, as set out in the Fifth Schedule to these Regulations. (2) An application for DUS test shall be made one season prior to the application for NPT and shall be supported by the following:- (a) sufficient seed sample for the first season DUS test; (b) variety description; (c) application fees and DUS testing fees as set out in the Sixth Schedule to these Regulations; and (d) on-farm trial and farmers assessment data. 9 (3) Upon receiving the application and materials, TOSCI shall conduct a DUS test, repot the results to the applicant and issue the DUS test certificate for the qualified application on Form SR IV as set out in the Fifth Schedule to these Regulations. (4) The application for NPT test shall be supported with the following:- (a) a minimum of two recent previous seasons advanced yield trial data from not less than three recognized testing sites in Tanzania or any other country which is in agreement for harmonization of seeds policy and legislations with Tanzania, as set out in the Seventh Schedule to these Regulations; (b) sufficient seed sample for conducting NPT and second DUS test; (c) fees for the NPT and second DUS test; and (d) any other additional information that may be required for determination of the merits of the candidate variety. (5) TOSCI shall conduct NPT for a minimum of one season in at least three sites as set out in the Seventh Schedule to these Regulations, and shall conduct second DUS test and submit the report to NPT-TC for review. (6) TOSCI shall develop procedures and conditions for conducting DUS test and NPT for perennial crops. (7) Upon completion of review of the NPT report, NPT-TC Secretary shall report the results to the applicant and present the NPT data and the recommendations of the NPT-TC to the NVRC on Form SR V as set out in the Fifth Schedule to these Regulations. (8) The National Variety Release Committee shall review the recommendations of the NPT-TC and advise the National Seed Committee. (9) In order for a candidate variety to be recommended for release to the National Seeds Committee, a breeder shall be required to submit to TOSCI an authentic sample of pre- basic seed for reference purpose. (10) The amount of authentic sample referred to in sub- regulation (9) shall be:- (a) four kilograms for cereals, pulses or any other big seed crops; or (b) one hundred grams for small seed crops species (11) TOSCI shall have discretion to determine the amount of authentic sample needed for plant species other than those referred under sub-regulation (10). (12) A breeder shall be required to replenish the authentic sample as it may be required by TOSCI. Variety registration 8.-(1) The Director shall register and issue a Certificate of Registration to the Applicant once his variety is approved by Minister pursuant to Section 21 of the Act. (2) The Certificate of Registration of the varieties shall be on Form SR VI as set out in Fifth Schedule to these Regulations. (3) The Director shall enter the information hereunder in the National Variety Catalogue upon registration:- (a) name of registrant; (b) variety name; 10 (c) plant species; (d) registration number, (e) registration date; (f) date of release; (g) name of breeder; (h) origin of the variety; (i) any other characteristics; (j) area of adaptation; (k) duration of maturity; (l) yield potential; (m) tolerance to insect pest; (n) disease tolerance; (o) end use; (p) agency responsible for maintenance; and (q) any other information deemed necessary. Variety deregistration 9.-(1) the Director may, in consultation with the National Seeds Committee, deregister a variety upon proof that the variety is no longer conforming to its original description or has lost its qualitative and quantitative attributes for which it was released. (2) Authentic seed sample of deregistered variety shall be sent to the national gene bank for conservation. PART IV SEED CLASSES AND STANDARDS Class names and standards 10. Seed classes and standards for plant species for the purposes of these Regulations shall be as set out in the tables of class standard set out in the First Schedule to these Regulations. Additional requirements with respect to standards 11.-(1) In addition to conditions set out under regulation 10, requirements prescribed by sub- regulation, (2), (3) and (4) of this regulation shall apply with respect to the standards of the appropriate plant species specified in the tables of class standards set out in the First Schedule to these Regulations. (2) Seed of every plant species shall: - (a) not contain any objectionable weed seed as provided in the Eight Schedule to these Regulations; (b) if classified with the name of Tanzania seed class, not be mixed with any other seed class; and (c) for each seed lot sold as “Pre- basic seed”, “Basic seed”, ”Certified 1” or “Certified 2: (i) be uniform; (ii) not containing moisture in excess of thirteen percent or such greater percentage as the Chief Seed Certification Officer may, prescribe for seed of a specified plant species; and 11 (iii) be free from undesirable seed and inert matter within the percentage allowed under these Regulations. (3) Any seeds offered for sale shall be subjected to a test or tests after seven months from the date on which the last test was performed to determine the percentage of germination required to be shown on the label thereof; (4) Without prejudice to the provision of sub-regulation (3), the Chief Seed Certification Officer may, prescribe longer or shorter periods for re-testing. (5) It shall be the responsibility of seed dealer to call an Inspector for re- sampling for the purposes of re-testing and re-sealing of seed lots whose validity of germination test results have expired. (6) Any seed dealer who contravenes the provisions of this regulation commits an offence. PART V MARKING AND LABELING Restrictions to use variety name 12.-(1) No person shall mark or label a package of seed with a variety name unless that seed is of the variety to which the variety name refers. (2) No person shall alter the name of a variety on the label of any seed container. (3) Except for the mixture of lawn, turf grass or forage seed as specified in Tables 8, 9 and 11 set out in First Schedule to these Regulations, no person shall label a package of a mixture of seed with a variety name unless he is authorized in that behalf by the Chief Seed Certification Officer pursuant to Regulation 23, and the seeds to which the variety name refers is one of Tanzania seed class. Necessary information in marking and labeling 13.-(1) The information required by these Regulations on the label or outside of a package of seed shall be conspicuously, legibly and indelibly written or printed in both English and Swahili, and shall appear on one exposed face of the package or label and shall be of a size and colour that can be easily read. (2) No label shall contain any incorrect or misleading information, mark or brand name that might be construed as a variety name. (3) For purposes of these Regulations, the seed certification seal and the tag colours described under this sub- regulation shall be used as follows- (a) the seed certification seal shall be applied on all tags relating to seed of “Pre- basic”, “Basic”, “Certified 1” or “Certified 2” classes as classified in the Second Schedule to these Regulations; (b) in the case of tag on a package containing Pre- basic Seeds, white with diagonal violet colour shall be used, with the word “Pre-basic” conspicuously applied across one side of the tag; (c) in the case of tag on a package containing Basic seed, white colour shall be used, with the word “Basic” conspicuously applied across one side of the tag; (d) in the case of a tag on a package containing “Certified 1” seed, Blue colour shall be used, with the word ”Certified 1”or “C1” 12 conspicuously applied across one side of the tag; (e) in the case of a tag on a package containing “Certified 2” seed, Red colour shall be used, with the word “Certified 2” or “C2” conspicuously applied across one side of the tag; (f) in the case of label on a package containing standard seed, the tag shall be yellow with the word “ Standard” conspicuously applied across one side of the tag; (4) The seed certification seal referred to in sub- regulation (3), shall be printed words thereon “Tanzania Certified Seeds” and for standard seed, the seal shall be printed with the words “Tanzania Standard Seed” and shall be of such material, shape, size as the Minister may approve. General labeling requirements 14.-(1) Every package of seed marked with a class name shall have on its label a description that specifies the seed standard as provided for in these Regulations. (2) Where the seed is a mixture or blend of two or more original seed lot of certified seed, the word “BLEND” preceded by the two digit seed year designation; (3) Whenever seed is treated with a poisonous material it shall be thoroughly stained with a conspicuous contrasting colour to show that the seed has been treated and the container of such seed shall be marked or attached a conspicuous label reading as follows:- “POISONOUS: DO NOT USE AS FOOD, FEED OR OIL; or SUMU: MBEGU HIZI SIO KWA MATUMIZI YA CHAKULA CHA BINADAMU AU WANYAMA. “TREATED WITH………or “IMEWEKWA SUMU YA…….:- (Name of poisonous material or substance in bold letters in Swahili and English). (4) Seed for sale shall be packed in packages unless- (a) it is delivered in a bulk container that is labeled in accordance with these Regulations and accompanied with other relevant information for importation of seed as provided under regulation 33; or (b) it meets the following conditions:- (i) it is of one of the Tanzania seed classes and is on transit within Tanzania and accompanied by a transport order issued by Tanzania Official Seed Certification Institute or an authorized Inspector on Form SR IX as set out in the Fifth Schedule to these Regulations; and (ii) it bears an inter-agency certification label pursuant to Regulation 23. (5) No person, other than the ultimate user, shall remove label, seal or open mechanically sewn or closed package of the seed. (6) Where certified seed lots are re- packaged, the re-packing shall be done only with the approval of the Chief Seed Certification Officer. Application of labeling requirements 15. The labeling requirements prescribed under regulations, 10, 11, 12, 13 and 14 shall apply to seed of all plant species specified in these Regulations. Labeling of seed specified in 16.-(1) Every package of seed, offered for sale, of the plant species 13 Tables of the First Schedule specified in Tables 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, or 15, 18 and 19 set out in the First Schedule to these Regulations shall be labeled with the following information- (a) the name and address of the seed dealer; (b) the name of the plant species; (c) the name of the variety of the seed; (d) seed class; (e) lot number; (f) weight of the package; (g) month and year of germination test; (h) in the case of seed that is imported, the name of the country of production; and in the case of seed that is a blend of two or more varieties, the name of each of the component varieties. (2) For the purpose of sub - regulation (1), seeds provided hereunder shall be kind of seeds for purposes of these Regulations: (a) “open pollinated”, is a seed produced by means other than controlled and selective breeding; (b) “varietal cross”, is a seed of the first generation of a cross between two named open pollinated varieties, or an open pollinated variety and a hybrid; (c) “top cross”, being seed of the first generation of a controlled cross between a named open pollinated variety and an inbred line; (d) “hybrid”, is a seed of the first generation of a cross between two or more inbred lines or their combination including single crosses, double crosses and three-way crosses; (e) “composite variety”, is a seed derived from selected strains which have been allowed to freely inter-pollinate; (f) “inbred line”, is a seed derived from a relatively homogeneous line produced by inbreeding and selection; (g) “synthetic variety”, is a seed produced through a combination of several intercrosses of genotypes which have been previously tested for their combining ability; (h) “single cross hybrid”, is a seed obtained by crossing two unrelated homozygous strains to obtain uniform and enhanced trait expression in the first generation; (i) “a three way cross hybrid”, is a seed obtained by crossing three unrelated homozygous stains to obtain uniform and enhanced trait expression in the first generation heterozygote; and (j) “a double cross hybrid”, is a seed obtained by crossing four unrelated homozygous strains or two unrelated single cross hybrids to obtain uniform and enhanced trait expression in the first generation heterozygote. Labeling of mixtures of seed 17. Every package of a mixture of seed, offered for sale, of the specified in the Table 11 set out in the First Schedule of these Regulations shall be labeled with: (a) the name and address of the dealer; 14 (b) seed class; (c) the name and percentage by weight of each in the mixture, in order of its predominance; (d) the name of the variety of each plant species in the mixture. (e) germination percentage of each component of the mixture, in order of its predominance; (f) month and year of germination test; and (g) in the case of seed that is imported, the name of the country of production; Labeling of roots, tubers, and pyrethrum seed 18. Every package of seed, offered for sale, of the plant species specified on Table 16 set out in the First Schedule to these Regulations shall be labeled with: (a) the name and address of the dealer; (b) the name of the plant species; (c) the name of the variety roots or cuttings, as the case may be; (d) seed class and year of production; (e) germination or sprouting percentage if applicable; (f) month and year of germination or sprouting test; and (g) lot number. Labeling of onion sets and multiplier onions 19. Every package of onion sets and multiplier onions offered for sale shall be labeled with: (a) the name and address of the dealer; (b) the term “onion sets” or “multiplier onions”; (c) class of the onion sets and multiplier onions as set out in Table 17 of the First Schedule to these Regulations; (d) germination or sprouting percentage; (e) lot number; (f) month and year of germination test; and (g) in the case imported, the name of the country of production. Labeling of forage seed 20. Every package of seed, offered for sale, of plant species specified in Tables 8 and 9 set out in the First Schedule to these Regulations, shall be labeled with: (a) the name and address of the dealer; (b) the name of the plant species; (c) seed class; (d) variety name; (e) country of production if it is imported; (f) germination percentage; (g) lot number; and (h) month and year of germination test. Labeling mixtures of Seed specified in Tables 8 and 9 of First Schedule 21.-(1) Every package of a mixture of forage seed offered for sale, of the plant species specified in Tables 8 and 9 set out in First Schedule to these 15 Regulations shall be labeled with: (i) the name and address of the dealer; (ii) seed class; (iii) the name and percentage by weight of each in the mixture, in order of its predominance; (iv) the name of the variety of each plant species in the mixture. (v) germination percentage of each component of the mixture, in order of its predominance; (vi) month and year of germination test; and (vii) in the case of seed that is imported, the name of the country of production; (2) The information stated on a package or label pursuant to paragraphs (b), (c) and (d) of sub regulation (1) of this regulation shall be on the same face of the package or label and shall be of the same type of printing or lettering. Official tag 22.-(1) Every package of seed produced in Tanzania and classified with the name of one of the Tanzania seed class shall be fastened and tagged with an official tag authorized by the Chief Seed Certification Officer. (2) The domestic tag referred to under sub-regulation (1) shall contain the: (a) name of the plant species; (b) name of the variety; (c) seed class; (d) serial number of the label or tag; (e) seed certificate number; and (f) lot number. (3) The tags referred to under sub-regulation (1) shall be supplied only to seed dealers applying for these tags and furnishing an Inspector with- (a) a declaration of the grower declaring that the seed to which the tags are to be applied is derived from the crop in respect of which the final field inspection results specified in form SR VIII B set out in the Fifth Schedule to these Regulations; and (b) a declaration of the applicant, if the applicant is not the grower, declaring that the seed referred to in the grower’s declaration is the seed to which the labels are to be applied and that the seed has not been mixed or contaminated while in the possession of the applicant. (4) The tag for standard seed, shall contain the: (a) name of the seed; (b) name of the variety of the seed; (c) name of the class of the seed; (d) serial number of the tag; and (e) lot number. Inter-agency labels 23.–(1) Every package of seed of foreign origin classified with the name of the Tanzania seed class shall be fastened and tagged with an inter-agency certification tag authorized by the Chief Seed Certification Officer; 16 Provided that, for any package of seed which originates from an East African Community member country, grey colour shall be used. (2) The inter-agency certification tag referred under sub-regulation (1) shall contain the: (a) name of the plant specie; (b) name of the variety; (c) seed class; (d) name of the country of production; (e) serial number of the tag; and (f) lot number. (3) Inter-agency certification tags referred to under sub-regulation (1) shall be supplied only if the seed dealer applying for these tags furnishes an Inspector with- (a) seed inspection report from a certification agency recognized by the Tanzania Seed Certification Institute; and (b) particulars of the information on the tag of the foreign certification agency. General provisions with respect to official and inter-agency labels 24.-(1) An official tag or inter-agency certification tag shall only be applied to containers for which the tags were issued. (2) Except where the Chief Seed Certification Officer directs otherwise, an official or inter-agency certification tag shall not contain anything other than the information required by regulations 18 or 19. (3) An official tag or inter-agency certification label shall be affixed to a seed container by an Inspector Chief Seeds Certification Officer to authorize use of official or inter- agency certification tags 25.-(1) The Chief Seed Certification Officer may, authorize any seed dealer to affix an official tag to seed of one of the Tanzania seed class, if that person:- (a) has seed processing equipment and facilities adequate for the proper processing of seed; (b) has adequate facilities to maintain the identity of different seed lots; and shall return to the Chief Seed Certification Officer on request by him any label supplied pursuant to regulations 18 or 19. (2) Where the Chief Seed Certification Officer is of the opinion that the seed dealer authorized to affix official labels pursuant to sub-regulation (1) is not complying with the provisions of regulations 18, 19 and 20 of these Regulations, the Chief Seed Certification Officer may withdraw the authority granted under sub-regulation (1). PART VI SEED CERTIFICATION Restrictions 26.-(1) No seed shall be certified unless, it has been produced, inspected, 17 on uncertified seed sampled, tested, and complied with the standards set out in the First Schedule to these Regulations. (2) Varieties released in Tanzania pursuant to regulation 4 shall be eligible for certification. (3) Seed shall be classified in four classes as set out in the Second Schedule of these Regulations. (4) Minister may make rules and procedures for certification and control of Quality Declared Seed and tree seed. Seed crop inspection 27.-(1) Every seed grower or his agent shall, within thirty days after a seed crop is planted, apply for field inspection by completing Form SR VII set out in Fifth Schedule of these Regulations upon payment of fees set out in Sixth Schedule to these Regulations. (2) An application of field inspection may be refused by the Tanzania Official Seed Certification Institute if it is made thirty days after planting. (3) A field inspection for the purpose of certification shall be conducted by the field inspector or authorized Inspector and shall be confined to the field of a registered seed producer. (4) In inspecting the field, the Inspector or the authorized inspector shall ensure that all field standards as provided in Part II set out in the First Schedule to these Regulations are complied with. (5) The Field Inspector or authorized inspector shall have powers to enter into any field registered for inspection and shall not approve any field or part thereof if satisfied that it does not meet the prescribed field standards. (6) The Field Inspector or the Authorized Inspector shall visit each unit of certification and conduct at least a minimum number of inspections required for each seed crop. (7) The Field Inspector or Authorized Inspector shall make proper counts of plants or heads of plants as deemed necessary fit and the minimum counting shall be: (a) up to two hectares, five counts shall be used; and (b) for each addition of two hectares up to fifty hectares, one more count shall be needed, beyond fifty hectares, one additional count shall be needed for every four hectares. (8) The minimum number of plants or heads per count required for each crop shall be as set out in the Fourth Schedule to these Regulations. (9) Inspection may include pre-planting, nursery, pre-harvest, post harvest and storage facilities. (10) It shall be the responsibility of the seed grower to observe the recommended cultural practices at every stage of seed production for each unit of certification. (11) Upon completion of every field inspection, the Inspector or Authorised Inspector may advise the seed grower on any non- compliance of the inspection and in case there is a need to undertake re- inspection, the seed grower shall bear the cost of such re- inspection. (12) The result of each field inspection shall be issued on Form SR VIIIA set out in the Fifth Schedule to these Regulations; and shall be signed by both the 18 Inspector and the grower or his representative. (13) Upon completion of the field inspection, the Inspector shall accord appropriate class any seed crop which meets the standards and fill in a Final Inspection Result in Form SR VIIIB as set out in the Fifth Schedule to these Regulations and the results shall be signed by both field inspector and the grower or his dully authorized representative. Appeal against the result of field inspection 28-(1) Where a registered grower or his agent disagrees with the results of any field inspection, he may appeal within seven days from the date of the issuance of the results of the inspection to the Chief Seed Certification Officer. (2) The Chief Seed Certification Officer shall determine the appeal and issue his decision in writing within fourteen days from the date of receipt of the appeal. (3) Where the Chief Seed Certification Officer is satisfied with the grounds of appeal, he shall approve for a re-inspection. (4) Re-inspection shall be carried out by the team comprising of – (a) one senior Inspector; (b) one breeder; and (c) the aggrieved seed producer or his dully appointed representative. (5) The aggrieved grower shall pay the re- inspection fee which shall be refunded to him in case the re-inspection is proved to be in his favour. Harvesting of seed 29.-(1) The seed grower shall ensure that the seed quality is maintained during harvesting and transportation to the processing plants. (2) Where the processing plant is located far from the seed field, seed grower shall ensure that transportation of seed is done under close supervision of an Inspector or Authorised Field Inspector and after obtaining a transport order in Form SR IX as set out in the Fifth Schedule to these Regulations. (3) Before seeds are transported the Inspector or a person authorised shall mark the container with indelible ink. Seed processing 30.-(1) A registered seed processor shall processes only seeds from the approved fields or seeds permitted to be imported into Tanzania. (2) Every seed processor shall notify the Chief Seed Certification Officer or any authorized officer before processing any seed lots and upon such notification, the Chief Seed Certification Officer or authorized officer shall issue a work order to the dealer in Form SR X set out in the Fifth Schedule to these Regulations. (3) The Seed Inspector or authorized Seed Inspector may enter and inspect the premises for seed processing. (4) The processed seed shall be properly marked and stored separately in identifiable seed lots. Storage of processed seed 31.–(1) Each container or bag of processed seed in every lot shall be properly labeled and identified. (2) Seed lot shall be kept in a way to ensure the limits set for moisture and other quality attributes. Seed for sale 32.-(1) No seed shall be offered for sale unless it is certified in accordance to 19 these Regulations or rules made under regulation 26(4). (2) Every seed dealer shall be responsible for the quality of any seed he sells or offers for sale. (3) A seed dealer may appoint an agent or a stockist with knowledge, ability and appropriate facilities to maintain the quality and viability of the seed offered for sale. (4) The agent or stockist appointed pursuant to sub-regulation (3), shall have a valid registration certificate for dealing with seed business issued by the Director pursuant to Section 16 of the Act. (5) Where a Seed Inspector or an authorized inspector has reasonable grounds to believe that any seed or seed lots is being sold without having reached minimum prescribed standards or in violation of any provisions of the Act and these Regulations, may immediately issue a stop sale order on Form SR XI set out in the Fifth Schedule to these Regulations. Seed importation 33.-(1) Every seed dealer who, intends to import seed into Tanzania, shall submit to the Director a notice of intention to import such seed on Form SR XII set out in the Fifth Schedule to these Regulations. (2) the notice under sub-regulation (1) shall specify:- (a) name and address of importer; (b) country of origin; (c) name and address of importer; (d) the quantity of seed; (e) expected date of arrival of consignment; and (f) the species and the cultivar. (3) Upon receipt of such notice, the Director shall issue a seed import permit in Form SR XIII set out in the Fifth Schedule to these Regulations. (4) Any seed imported under this regulation shall not be sold unless its quality has been examined and approved by TOSCI or any other certification agency which is in bilateral agreement with Tanzania as regard to seed certification. (5) Any imported seed shall be accompanied by certificate of quality issued by a Recognized Certification Agency, phytosanitary certificate and shall meet Tanzanian quarantine requirements as provided in the Plant Protection Act. Seed exportation 34.-(1) Any seed dealer who intends to export seed from Tanzania, shall submit to the Director a notice of intention to export on Form SR XIV set out in the Fifth Schedule to these Regulations. (2) The notice under sub -regulation (1) shall be accompanied with an import permit from the country to which seed is exported and shall specify the quantity, plant species and variety to be exported. (3) Upon receipt of such notice, the Director shall issue seed export permit on Form SR XV set out in the Fifth Schedule to these Regulations. (4) The exporter shall ensure compliance with all conditions for export of seed as provided in the Plant Protection Act. Pre and post control plots 35.- (1) Any seed lots officially sampled and tested pursuant to these Regulations shall be grown in post control plots in accordance with OECD seed 20 scheme. (2) Control plots referred to under sub-regulations (1) shall be open for examination and assessment by all parties interested in the seed industry. (3) Upon completion of the examination and assessment of control plots, the Field Inspector or Authorized Inspector shall write a report on the number of off- types, other varieties, variety identity, purity, diseased plants and other diversions observed in the plots. PART VII SEED SAMPLING AND TESTING Sampling of Seeds 36.-(1) Any seed sample for testing shall be taken by a Seed Inspector or Authorised Inspector in accordance with the requirements prescribed under these Regulations. (2) The sample referred to under sub- regulation (1) shall be provided to the Seed Inspector or Authorized Inspector free of charge for purposes of laboratory seed testing and post control planting and examination. (3) Where an Inspector requires a larger amount of seed sample as he considers it necessary for satisfactory testing, re-testing or analysis, the size of each sample shall comply with the particulars set out in the Third Schedule to these Regulations. (4) Each seed sample shall bear a unique sample number for reference. (5) Seed lots shall be created at the time of sampling and shall not exceed the maximum weights prescribed in these Regulations. (6) Where automatic samplers have not been installed, a seed dealer shall arrange the packages in such a way to enable the seed Inspector or Authorized Inspector to reach all packages and draw samples. (7) Sampling of seed lots shall be conducted in accordance with the current Rules of ISTA. (8) Seed from different fields of the same class, species and variety which have passed field inspection and which can be traceable, may be blended and bulked to constitute one seed lot. (9) The seed dealer shall provide reliable scales for ascertaining the weight of a seed lot. (10) The seed dealer shall pay appropriate fees for seed sampling as set out in the Sixth Schedule to these Regulations. Sampling intensity 37.-(1) When sampling seed lots in a container that can be sealed, the sampling intensity hereunder shall be taken as the minimum requirements:- (a) seed not exceeding 500 kg.- five primary samples shall be taken except that for small lots not exceeding 50 kg. three or four samples may be taken; (b) seed exceeding 500 kg. – but not exceeding 3,000 kg. – one primary sample for every 300 kg. shall be taken, so however, that not less than five primary samples shall be taken; (c) seed exceeding 3,000 kg but not exceeding 20,000 kg. – one primary sample for every 500 kg. shall be taken, so however, that not less than 21 10 primary samples shall be taken; and (d) seed in bulk shall be sampled at random locations and the samples shall be drawn from varying depths. (2) For seeds lots in bags or other containers up to 100kg capacity, samples shall be taken at random locations and the intensity hereunder shall be taken as the minimum requirements:- (a) from 1 – 4 containers , three primary samples from each container; (b) from 5 – 8 containers, two primary samples from each container; (c) from 9 -15 containers, one primary sample from each container; (d) from 16 -30 containers, 15 primary samples total; (e) from 31 -59 containers, 20 primary samples total; (f) from 60 or more containers, 30 primary samples total. Seeds testing 38.-(1) Seed testing for the purpose of certification shall be conducted by an official seed testing laboratory or any authorized laboratory. (2) Any sample drawn or by the Seed Inspector or Authorized Inspector or taken by any private individual shall be submitted to the seed testing laboratory together with Form SR XVI set out in the Fifth Schedule to these Regulations. (3) Seed testing laboratory shall:- (a) test seed in accordance with the ISTA Rules; (b) in case for samples submitted by the Seed Inspector or Authorized Inspector, record results of the seed test on a certificate in Form SR XVII set out in the Fifth Schedule to these Regulations; (c) in case of samples submitted by the private individual, record results of seed testing report on Form SR XVIII set out in the same Schedule; and (d) store the sample under optimal storage conditions for at least twelve months from the date the test results certificate was issued. (4) Notwithstanding the provision of sub- regulation 3(d), the testing laboratory shall not be held responsible for any deterioration of the sample that may occur. PART VIII MISCELLANEOUS Exemption 39. The Minister may by order published in the Gazette, exempt some seed or class of seeds from the provisions of these Regulations. Fees 40.-(1) The fees set out in the Sixth Schedule to these Regulations shall be payable in respect of all services as provided therein. (2) The fee for any service shall be paid at the time when the application for a particular service is made. (3) The Minister may, by notice in the Gazette, remit in whole or in part any fees payable by any person in respect of any service, if he is satisfied that it is in the public interest to do so. Appeals 41.-(1) Any person who is aggrieved by the decision of any officer or the National Performance Trial-Technical Committee or National Variety Release Committee in the administration of the Act or these Regulations, may appeal to the 22 National Seed Committee. (2) Any person who is aggrieved by the decision of the National Seed Committee may appeal to the Minister within fourteen days upon receipt of such decision. (3) Any appeal whose time limit has not been specifically provided under the Act or these Regulations shall be made to the Minister within fourteen days from the date of receiving of a particular decision. Authorisatio n of Inspectors, Samplers and Analysts 42.-(1) Any person who wishes to be authorized as seed testing laboratory, an Inspector, Seed Sampler, or Analyst for the purposes of these Regulations, shall apply in writing to the Chief Seed Certification Officer to that effect. (2) The application made under sub-regulation (1) shall be accompanied with documentary evidence showing that the Applicant is knowledgeable of the principles and practices of seed testing, field or seed inspection, seed conditioning or seed sampling. (3) The application under sub-regulation (1) shall be accompanied with appropriate fees as set out in Sixth Schedule to these Regulations. (4) The Chief seed Certification Officer may after recommendation of the Management Committee of TOSCI and upon satisfied that the Applicant is capable to be authorised as an Inspector, Sampler or Analyst issue an authorisation Certificate on Form SR XIX set out in Fifth Schedule to these Regulations. (5) TOSCI shall from time to time issue guidelines and other requirements as regard to the authorisation of Inspectors, Samplers, Analysts and seed laboratories. (6) The Chief Seed Certification Officer shall renew annually the authorisation upon payment of the prescribed annual fees as set out in Sixth Schedule to these Regulations. (7) Authorisation referred under this regulation shall be limited to the activities for which the authority has been granted. Suspension or cancellation of authorisation 43.-(1) The Chief Seeds Certification Officer may suspend or cancel the authorisation issued under regulation 42, if:- (a) a false or misleading information has been submitted in support of the application for the authorisation; or (b) the authorised person has not complied with the provisions of the Act or these Regulations; or (c) the authorised person has not paid the applicable annual fee before 1st January of the year in respect of which the authorisation is to be renewed; or (d) the authorised person has provided or maintained false or misleading records or samples in respect of any seed. (2) The Chief Seed Certification Officer shall not suspend or cancel the authorisation under this regulation unless:- (a) the authorized person has been informed in writing the reasons for suspension or cancellation; (b) the authorized person has been given an opportunity to be heard, either 23 by written or oral representations, in respect of the suspension or cancellation; and (c) the authorized person has been issued with a fourteen days prior notice of intention to suspend or cancel the authorisation. (3) A suspension of an authorisation shall remain in effect until:- (a) the Chief Seeds Certification Officer has been satisfied that the suspended person has taken corrective measures; and (b) the Chief Seeds Certification Officer notifies the suspend person in writing that the suspension has been lifted. Change of variety name 44.-(1) The Director may after consultation with the National Seed Committee, approve change in variety name. (2) the variety name may be changed pursuant to this regulation, if the Director is satisfied by the information received from the breeder that justifies change in variety name. (3) Change of variety name shall come into effect on the date on which the Director approves. Detentions and stop sale order 45.-(1) Any seed or package seized pursuant to subsection (4) of section 22 of the Act may be detained by an Inspector at any place by attaching a detention tag or mark to:- (a) where only the seed is seized, the package provided by the institute and in which the seed is placed; (b) where only the package is seized, the package; (c) where the package and the seed are seized, the package; and (d) where a seed lot in packages is seized, at least one package of the seed lot. (2) On attaching a detention tag or mark to the appropriate package referred to in sub-regulation (1), the Seed Inspector or an authorised inspector shall issue a stop sale order as provide under regulation 32 (5) to the person entitled to possession, at the time of seizure, of the seed or package, as the case may be. (3) No person shall alter or remove a detention tag or mark attached to a package or sells any seed or package detained pursuant to these Regulations. (4) No person shall move any seed or package detained pursuant to sub- regulation (1), except where an inspector issues a written authorization indicating that the seed or package shall be placed in a safer or more convenient location. (5) Upon issuance of detention order, an inspector shall take or cause to be taken a sample of each seed lot that has been detained. (6) Where any seed has been placed under detention or stop sale by an inspector under this regulation, the owner or the person in possession of that seed may apply to the inspector for the release of the seed. (7) No seed under detention or stop sale order shall be released unless the person applying for the release has fulfilled to the satisfaction of the Chief Seed Certification Officer all the requirements of the Act and these Regulations. (8) On release from detention of the seed or package, an inspector shall issue a notice of release to the person who was in the possession of the detained seed. (9) Any Seeds or package forfeited to the Government under the provisions 24 of the Act or these Regulations shall be disposed of in such manner as the Chief Seeds Quality Controller may, with the approval of the Minister, direct. (10) Costs incidental to the detention shall be payable and recoverable from the person whose seed have been detained. Offence 46. Any person who contravenes the provision of these Regulations commits an offence, except as otherwise provided, be liable upon conviction to a fine not less than one million shillings but not exceeding five million shillings or to imprisonment for a term not exceeding one year or to both. Retention 47. The Minister may, after consulting the Minister for Finance determine the amount of money to be retained for TOSCI from collections made by TOSCI in discharging its duties under the Act and these Regulations. Prohibited, restricted and noxious seeds 48. The seeds set out in the Eighth Schedule to these Regulations shall be deemed as prohibited, restricted and noxious weed seeds for the purpose of these Regulations. Revocation of GN.No.29 of 1976 49. The Seed Regulations 1976, are hereby revoked 25 ____________ FIRST SCHEDULE ____________ (Made under Regulations 10) ____________ TABLES OF STANDARDS SEED ____________ PART I: LABORATORY STANDARDS TABLE 1 Applicable to: (a) Wheat including hybrid – Triticum aestivum L. and (b) Wheat durum – Triticum durum Desf. Factor Class Basic Certified1 Certified2” % % % Pure Seed (Minimum) … … … … … … … ……... 99.0 99.0 99.0 Other Seed (Maximum) … … … … …. ….. …… 0.9 0.9 0.9 Inert Matter (Maximum) … … … … … … …… .. 0.9 0.9 1.0 Moisture Content (Maximum) … … … … ... …… 13.0 13.0 15.0 Germination (Minimum) … … … … … … …... 85 85 85 Objectionable Weed Seed (Maximum) … … … … …. …. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… …. …… …. …. 4 per kg. 4 per kg. 4 per kg. TABLE 2 Applicable to: (a) Barley – Hordeum vulgare L, H. distichon L. (b) Oat – Avena sativa L.A. nuda L. Standard Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … .. .. … 99.0 99.0 99.0 Total Seed other (Maximum) … … … … …. … … 0.1 0.1 0.1 Other Crop Seed (Maximum) … … … … … … 0.0 0.0 0.0 Inert Matter (Maximum) … … … … … ... …… 0.9 0.9 0.9 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg Moisture Content (Maximum) … … … … … … ... 13.0 13.0 15.0 Germination (Minimum) … … … … … …. .. 85 85 85 26 TABLE 3 Applicable to: Rice (Paddy) – Oryza sativa L. TABLE 4 Applicable to: Sorghum (includes hybrid sorghum) – Sorghum bicolor (L.) Moench Factor Class Basic Certified 1 Certified 2 % % Pure seed(maximum) 98.0 98.0 98.0 Other Seed (Maximum) … … … … …. …. … …. 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … ….. …. 11.0 11.0 11.0 Germination (Minimum) … … … … … …. …. ... 75 75 75 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg Factor Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … … … 80 80 80 Blast – Pyricularia oryzae (Maximum) 1.0 0.2 0.2 Bacterial Leaf Blight – Xanthomonas oryzae (Maximum) 1.0 2.0 2.0 White Tip Nematode – Alphelenchoides besseyi (maximum) 0.0 0.0 0.0 Objectionable Weed Seed (Maximum) … … .. ... ….. 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … …... 4 per kg. 4 per kg 4 per kg 27 TABLE 5 Applicable to: (a) Maize open-pollinated - Zea mays L . (b) Maize (hybrid) TABLE 6 Applicable to: Soybean – Glycine max. Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... …… 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 14.0 14.0 14.0 Germination (Minimum) …. …. ….. ….. … … … 75 75 75 Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... 0.9 0.9 0.9 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … … … 90.0 90 90 Factor Class Basic Certified 1 % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 Inert Matter (Maximum) … … … … … 0.9 0.9 Moisture Content (Maximum) … … … … 13.0 13.0 Germination (Minimum) … … … … … 90 90 28 TABLE 7 Applicable to: Millet (a) Pearl Millet,– Pennisetum glaucum (L.) R. Br. Emend Stuntz Standard Class Basic Certified 1 Certified 2” % % % Pure Seeds (Minimum) … … … … … … 98.0 98.0 98.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … ... 1.9 1.9 1.9 Moisture Content (Maximum) … … … … 12.0 12.0 12.0 Germination (Minimum) … … … … … 75 75 75 (b) Finger Millet, – Eleusine carocana Factor Standards for each Class Basic Certified 1 Certified2”” % % % Pure Seeds (Minimum) … … … … … 97.0 97.0 97.0 Other Seed (Maximum) … … … … 0.2 0.2 0.2 Inert Matter (Maximum) … … … … … ... 2.8 2.8 2.8 Germination (Minimum) … … … … … 75 75 75 Objectionable Weed Seed (Maximum) … … .. ... … 0.0 0.0 0.0 Restricted Noxious Weed Seed (Maximum)… … … ….. 4 per kg. 4 per kg 4 per kg 29 TABLE 8 Applicable to: (a) Alfalfa – Medicago sativa (b) White Clover, incl. Ladino – Trifolium repens (c) Glycine – Glycine javanica (d) Lance Crotalaria – Crotalaria lanceolata. (e) Showy Crotalaria – Crotalaria spectabilis (f) Slender Crotalaria – Crotalaria intermedia (g) Striate Clotalaria – Crotalaria mucronata var. striata (h) Sunn Crotalaria - Crotalaria juncea (i) Kudzu – Pueraria phaseloides (j) Lupines – Lupinus spp. (k) Seradella – Ornithopus sativus. (l) Tall Tick Clover (Kuru vine) – Desmodium spp. (m) Siratro – Phaseolus atropurpureus. Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … 98.0 98.0 97.0 Other Seed (Maximum) … … … … 0.2 0.2 0.2 Inert Matter (Maximum) … … … … 1.8 1.8 2.8 Moisture Content (Maximum) … … … … 13.0 13.0 13.0 Germination (Minimum) … … … 50 50 50 TABLE 9 STANDARDS FOR EACH SEED CLASS Applicable to: Forage Crops and Grasses Percent Inert Matter Percent Weed Seeds Percent Pure Seeds Percent Germination Basic and Certified1 Certi fied 2 Basic and Certified 1 Certifi ed2 Basic and Certifi ed1 Certified 2 Basic, “Certified1” and Certified2 Pennisetum clandestinum 3.8 4.5 0.2 0.5 96.0 95.0 75 Rhodes Grass – Chloris gayana 34.8 39.5 0.2 0.5 65.0 60.0 65 Dolichos spp. … … … 9.8 11.5 0.2 0.5 90.0 88.0 75 Stylo – Stylosanthos gracilis 2.8 3.5 0.2 0.5 97.0 96.0 65 Hypanheris rhufa … 4.8 6.5 0.2 0.5 95.0 93.0 75 African foxtail grass – Cenchrus ciliaris 9.8 14.5 0.2 0.5 90.0 85.0 65 Teff Grass – Eragrostis teff 1.8 2.5 0.2 0.4 98.0 97.0 75 Sand Lovegrass – Eragrostis trichoide … … 1.8 2.5 0.2 0.5 98.0 97.0 75 Euchleana mecinana … 7.8 9.5 0.2 0.5 92.0 90.0 75 Digitaria smutsii … … 2.8 4.5 0.2 0.5 97.0 95.0 65 Eragrostis chloromelas 1.8 2.5 0.2 0.5 98.0 97.0 75 Weeping Lovegrass – 1.8 2.5 0.2 0.5 98.0 97.0 75 30 Eragrostis urvula Bothriochloa insulpta … 9.8 14.5 0.2 0.5 90.0 85.0 60 Guines Grass – Panicum maximum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Blue panicgrass – Panicum antidotale … 4.8 7.5 0.2 0.5 95.0 92.0 60 Green panicgrass – Panicum maximum var trichoglume 4.8 7.5 0.2 0.5 95.0 92.0 60 Panicum coloratum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Vine mesquite – Panicum obtusum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Switchgrass – Panicum virgatum … 4.8 7.5 0.2 0.5 95.0 92.0 60 Melinis minufiflora … … 4.8 9.5 0.2 0.5 95.0 90.0 60 Pennisetum typhoida … 3.8 4.5 0.2 0.5 96.0 95.0 75 Setaria sphacelate … … 9.8 14.5 0.2 0.5 90.0 85.0 60 Setaria splendida … … 9.8 14.5 0.2 0.5 90.0 85.0 60 Columbus grass – Sorghum alum … 3.8 7.5 0.2 0.5 96.0 92.0 75 Napier grass – Pennisetum purpureum … … 3.8 4.5 0.2 0.5 96.0 95.0 75 Bermuda grass – Cynodon dactylon … 3.8 4.5 0.2 0.5 96.0 95.0 75 Themeda triandra … … 4.8 7.5 0.2 0.5 95.0 92.0 60 Lovegrass – Eragrostis superba … 1.8 2.5 0.2 0.5 98.0 97.0 75 Cynodon plectostachyus … … 3.8 4.5 0.2 0.5 96.0 95.0 75 Lovegrass – Brachiaria brizantha … 4.8 7.5 0.2 0.5 95.0 92.0 70 Trypsacum laxum … … 4.8 7.5 0.2 0.5 95.0 92.0 70 Brachiaria ruziziensis … 4.8 7.5 0.2 0.5 95.0 92.0 70 Centro – Centrosema pubescens … 1.8 2.5 0.2 0.5 98.0 97.0 65 Stylosanthes humilis… … 2.8 3.5 0.2 0.5 97.0 96.0 65 Stylosanthes mucronata … 2.8 3.5 0.2 0.5 97.0 96.0 65 Clitoria ternatea … … 3.8 5.5 0.2 0.5 96.0 94.0 65 Note: Other crop seed contents shall not exceed as follows:- For Basic and”Certified1” class … … … … … 0.5 For Certified 2 class … … … … 1.0 31 TABLE 10 Applicable to: (a) Sunflower – Helianthus annuus. (b) Safflower – Carthamus tinctorius. Factor Class Basic Certified1 Certified2 % % % Pure Seed (Minimum) … … … … … … 99.0 99.0 99.0 Other Seed (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … 0.9 0.9 0.9 Moisture Content (Maximum) … … … … 10.0 10.0 10.0 Germination (Minimum) … … … … … 85 85 85 TABLE 11 Applicable to mixture of forage seed of two or more of the seed listed in Table 8 and 9 of this Schedule. “Mixture” means each component present in excess of 5 per cent of the whole. Maximum number of seed per Kg. except where otherwise stated Minimum percentage germination Class Name Objectionable Restricted Weed seed Each ingredient % % Certified 1, Certified 2 .… … None 4 per kg 1.5 60 Note:- 1. Mixtures of grass seed not designated by the sender as lawn or turf grass mixtures shall be classified under this table. 2. Percentage purity and germination of each component in the order of predominance shall be stated on the seed label. TABLE 12 Applicable to: (a) Cotton – Gossypium spp. (b) Kenaf – Hibiscus cannabinus (c) Roselle – Hibiscus sabdariffa Factor Class Basic Certified 1 Certified 2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 98.0 Total Weed Seed (Maximum) … … … … None 0.0 0.1 Other Crop Seeds (Maximum) … … … … 0.0 0.1 0.1 Inert Matter (Maximum) … … … … … 2.0 0.9 0.9 Objectionable Weed Seed (Maximum) … … None None None 32 Restricted Noxious Weed Seed (Maximum) … … None None 4 per kg Moisture Content (Maximum) … … … … … 10.0 10.0 10.0 Germination (Minimum) … … … 70 70 70 Bacteria Blight – Xanthomonas malvacearum (Maximum) 0.5 1.0 2.0 TABLE 13 Applicable to: (a) Groundnut – Arachis hypogaea (b) Bambara Nut – Voandzeia subterranea Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … 98.0 97.0 97.0 Other Seeds (Maximum) … … … … 0.1 0.1 0.1 Inert Matter (shelled) (Maximum) … … … … 1.9 2.9 2.9 Moisture Content (Maximum)… … … … … … 12.0 12.0 12.0 Germination (minimum) … … … … … … 75 75 75 TABLE 14 Applicable to: (a) Sesame – Sesamum indicum Factor Class Basic Certified1 Certified2 % % % Pure Seed (Minimum) … … … … … … 98.0 98.0 97.0 Total Weed Seed (Maximum) … … … … 0.1 0.2 0.3 Other Crop Seed (Maximum) … … … … 0.1 0.2 0.3 Inert Matter (Maximum) … … … … … … 1.9 2.9 2.8 Objectionable Weed Seed (Maximum) … … … None None None Restricted Noxious Weed Seed (Maximum) … … 4 per kg 4 per kg 4 per kg Moisture Content (Maximum)… … … … … 10.0 10.0 10.0 Germination (Minimum). ……… …… ……. … 80 80 80 (b) Tobacco – Nicotiana tabacu - Nicotiana rustica. Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … … 98.0 97.0 97.0 Other Seed (Maximum) … … … … 0.1 0.1 0.2 Inert Matter (Maximum) … … … … … 2.0 2.0 3.0 Moisture Content (Maximum)… … … … … 12.0 12.0 12.0 Germination (Minimum) … … 80 80 80 Anthracnose (Maximum) … … … … … None None None Angullar Leaf Spot – Pseudomonas angulata (Maximum)… None None None Frog-Eye or Green Spot – Cercospora nicotianae (Maximum) None None None Tobacco Mosaic Virus (Maximum) … … … … … None None None TABLE 15 33 Applicable to: (a) Bean, common – Phaseolus vulgaris (b) Bean, broad – Vicia faba (c) Bean, Lima – Phaseolus lunatis var. macrocarpus (d) Bean, runner – Phaseolus cocecineus (e) Chick pea – Cicer arietinum (f) Cowpea – Vigna unguiculata (g) Mung Bean – Phaseolus aureus (h) Banavist Bean – Dolichos lablab (i) Hyacinth Bean –Lablab niger (j) Sword Bean – Canavalia ensiformis (k) Blackgram – Phaseolus mungo (l) Greengram – Phaseolus aureus (m) Pigeon pea – Cajanus cajan (n) Pea – perennial – Lathyrus spp (o) Castor bean – Ricinus communis 34 Factor Class Basic Certified1 Certified2 % % % Pure Seeds (Minimum) … … … … … … 99.0 99.0 99.0 Other Seeds (Maximum) … … … … … 0.1 0.1 0.1 Inert Matter (Maximum) … … … … … … 0.9 0.9 0.9 Moisture Content (Maximum)… … … … … … … 10.0 10.0 10.0 Germination (Minimum) … … … 80 80 80 Common Bacteria Blight – Xanthomonas phaseoli (Maximum None None None Anthracnose – Coletotrichum lindemunthianum (Maximum)… None None None Bean Common Mosaic Virus (B.C.M.V.) … … … 0.1 0.1 0.1 Halo Blight – Pseudomonas phaseoli … … … … 0.1 0.1 0.1 TABLE 16 A: Applicable to: Irish potatoes - Solanum tuberosum Factor Class Basic Certified 1 Certified 2 % % % Pure Seeds (Minimum) … … … 99.0 98.0 97.0 Soft rot – Sclerotium rolfsii 0.0 0.1 0.1 Dry rot – Fusarium wilt … … … … … 0.5 1.0 1.0 Common scab – Streptomyes scabies*coverage of tuber in 50kg bag 1.0 2.0 2.0 Black scurf - Rhizoctonia solani** 1.0 5.0 5.0 1. *Even if a single tuber in a lot is detected to have standard scab the entire seed lot shall be treated with the recommended chemical before declaring it fit for certification. Any Seeds lot having more than 5% scabbed tubers will not be certified even after treatment. 2. **A tuber is considered having black scurfed if 10% or more of its surface in scurfed. If more than 5% of the tubers are scurfed the total lot is rejected. Seeds lots carrying scurf, should be treated with recommended chemicals before being considered fit for certification purposes. Seed potato shall be classified into 3 sizes for the different/classes of seeds***. Measurements in mm Hill seed potato Plain seed potato Small **** 30-40 25-35 Medium 41-50 36-45 Large Above 51 Above 46 3. ***Size of the tuber will be decided on the basis of mean of two width of tuber at the middle and that of length. 4. **** In a seed lot tuber not conforming to specific size of seed should not be more than 5% by number. The seed material shall be reasonably clean, health, firm and shall conform to the characteristics of the variety, cut, bruised, misshaped, cracked tubers or those damaged by insects, slugs or worms shall not exceed 1% by weight; Tubers showing greenish pigment are best for seed purposes. Total number of diseased tubers shall not be more than 5% by number in each case. B: Applicable to: (a) Ginger – Zingiber officinalis (b) Cardamom – Elittaria cardamomum (c) Pyrethrum – Chysanthemum cinerarieafolium Factor Class 35 Basic Certified1 Certified2’ % % % Pure Living splits or cuttings (Minimum) … … … 98 98 97 Total Weeds (Maximum) … … … … … None None None Other Living Plants (Maximum) … … … … 1.0 1.0 2.0 Germination (Minimum) … … … … … 95 95 95 Bacterial Fascial – Corynebacterium fascians … … 2.0 2.0 2.0 Bright Gray Mold – Botrytis cinerea … … … 2.0 2.0 2.0 Damping off – Gloesporium spp … … … … 2.0 2.0 2.0 Root Rot – Pythium spp 2.0 2.0 2.0 Phymatotrichum omnivorum (Text) or Rhizoctonia solani 2.0 2.0 2.0 Stem Rot – Sclerotinia screlerotiorum … … … … 2.0 2.0 2.0 Aster Yellow – Chlorogenus callistephi … … … 2.0 2.0 2.0 Leaf Nematode – Alphelenchoides ritzema – bosi … None None None Root Knot Nematode – Meloidogyne hapla … … None None None C: Applicable to: Cassava Manihot utilisima Sweet potato Ipomea batatas Factor Class Basic Certified1 Certified 2 % % % Other varieties (Maximum)… … … … 0.1 0.2 0.2 Storage rot… … … … … …. … … …… None None None Black rot - Ceratocystis fumbriata … … … … … None None None Pure living cutting (Minimum)… … … … … 95 95 95 Scurf - Monilochaetes unfuscans … … … … … None 0.1 0.1 Wilt (vascular wilt) - Fusarium oxysporum… … … None 0.1 0.1 Nematode … … … … … … … … …… 0.2 0.5 0.5 Wire worm … … … … … … … … … … 1 5 5 Sweet potato weevil - Cylasfor micarius … … None None None Foot rot – Plenodomus destruens … … …. …. …… …. None None None Leaf spot - Ercospora bataticala… …. ….. …… ….. …. None None None Soft rot - Rhizopus stoloniferi… … … … … …. .. None None None Cassava mealybug … … … … … …. …. …. None None None Cassava mosaic … ….. ….. …… … …. …. …… …. None None None TABLE 17 Applicable to: Onion Sets and Multiplier Onions (including Garlic). 1 2 3 4 Class Name Size in diameter Purity General Quality 1. Standard seeds 10 – 20 mm 98 per cent Mature, well cured sound, free from decay and dry, free from tops, dirt leaves, free from other foreign matter, disease, moulds, insect, mechanical, frost damage, sprouted and soft bulbs when classified. Note: The size standards under Column 2 do not apply to multiplier onions, 36 2. Onion sets may be labeled “pin-head” onion sets when they conform to the standards specified in this table and when the diameter of the sets is not more than 20 mm”. 3. The following are the generally accepted identification and distinction between onion sets and onion multipliers. Onion sets: (Allium cepa) small bulbs or “sets” grown from Seeds used to plant for the production of mature onions. Since A. cepa is perennial, in the temperate zone, the sets are produced one season for planting in the next season. They are in practical sense just very small onions. Onion multipliers: (A. cepa, var: varagratum). The example variety produces branching at the base of the bulb which, when divided, can be used as propagating material for planting. The practical example in Tanzania is the Spring onion. In the general Allium there are at least four basic means of propagation: Seeds, Cloves, Topsets, and Multipliers. Seeds: to produce mature onions, or for the production of transplants or sets. (Allium cepa). Bulb segments or cloves: (A. sativum) – Garlic. The separation of segments of the garlic bulb provides the usual propagation material. Seldom is garlic Seeds used. Top sets are the small bulb-like planting material produced in the flower cluster, sometimes in conjunction with Seeds. (A. cepa, var. vivaparum). Multipliers are the division of the branching at the base of the crown, which are used for propagation. (A cepa, var; aggregatum) Spring onions. 37 TABLE 18 Applicable to: Vegetable Crops. MINIMUM STANDARDS APPLICABLE TO SEED CLASSSES 1. Objectionable Weed Seed: None 2. Restricted Noxious Weed Seed: Maximum allowed shall be 4 Seed per kg 3. Total Weed Seed: The maximum by weight shall not exceed 1 per cent. Purity (Minimum) Germination (Minimum) % % African Cabbage… … … … … … … … … 98.0 70 African Eggplant… … … … … … … … … 98.0 70 Amaranths… … … … … … … … … … 95.0 70 Beans (all types) … … … … … … … … … 98.0 80 Beet (Incl. Swiss chard) … … … … … … … 98.0 65 Broccoli … … … … … … … … … … 98.0 75 Brussels Sprouts … … … … … … … … … 98.0 80 Cabbage … … … … … … … … … … 98.0 80 Carrot … … … … … … … … … … 98.0 60 Cauliflower… … … … … … … … … … 98.0 70 Celery … … … … … … … … … … … 99.0 60 Cucumber … … … … … … … … … … 98.0 70 Eggplant … … … … … … … … … … 98.0 70 Kale … … … … … … … … … … … 98.0 70 Kohlrabi … … … … … … … … … … 98.0 80 Leek … … … … … … … … … … 98.0 70 Lettuce … … … … … … … … … … 98.0 75 Marrow … … … … … … … … … … 98.0 75 Muskmelon … … … … … … … … … 98.0 75 Nightshade… … … … … … … … … … 98.0 60 Okra … … … … … … … … … … 98.0 70 Onion … … … … … … … … … … 98.0 70 Parsley … … … … … … … … … … 98.0 70 Parsnip … … … … … … … … … … 98.0 60 Peas … … … … … … … … … … … 99.0 80 Pepper … … … … … … … … … … 98.0 60 Pumpkin … … … … … … … … … … 99.0 60 Radish … … … … … … … … … … 98.0 70 Spinach … … … … … … … … … … 98.0 60 Squash … … … … … … … … … … 99.0 75 Sweet Corn … … … … … … … … … 98.0 80 Tomato … … … … … … … … … … 98.0 75 Turnip … … … … … … … … … … 98.0 70 Watermelon … … … … … … … … … 98.0 60 38 TABLE 19 Applicable to: Standard seed 1. Objectionable Weed Seed: None 2. Restricted Noxious Weed Seed: Maximum allowed shall be 10 Seed per kg 3. Total Weed Seed: The maximum by weight shall not exceed 1.5 per cent. 4. Minimum Seeds Standards shall be as follows:- Minimum Purity Minimum Germination % % A. CEREAL CROPS: Maize (open pollinated) … … … … … … 95.0 80 Wheat … … … … … … … … … … 95.0 80 Sorghum… … … … … … … … … … 95.0 65 Rice … … … … … … … … … … 95.0 70 Oats … … … … … … … … … … 95.0 80 Barley … … … … … … … … … … 95.0 80 Millet … … … … … … … … … … 95.0 65 B. GRAIN LEGUME AND PULSES: . Cow peas … … … … … … … … … 97.0 70 Bean, Mung … … … … … … … … … 97.0 70 Bean, Broad … … … … … … … … … 97.0 70 Bean, Banavist … … … … … … … … 97.0 70 Bean, Hyacinth … … … … … … … … 97.0 70 Bean, Sword … … … … … … … … … 97.0 70 Bean – Other s … … … … … … … … 97.0 70 Pigeon Pea … … … … … … … … … 97.0 70 Pea – Lathyrus spp. … … … … … … … 97.0 70 Pea – Field and Garden … … … … … … … 97.0 70 Bambara Nut … … … … … … … … ... 97.0 70 Greengram … … … … … … … … … 97.0 70 Blackgram … … … … … … … … … 97.0 70 Chickpea … … … … … … … … … 97.0 70 Lentil … … … … … … … … … 97.0 70 Lupines … … … … … … … … … 95.0 70 Minimum Purity Minimum Germination % % C. OIL CROPS: Soybean … … … … … … … … … 97.0 70 Groundnut … … … … … … … … … 97.0 70 Sesame… … … … … … … … … … 95.0 70 Sunflower … … … … … … … … … 95.0 65 Safflower … … … … … … … … … 95.0 65 Castor Bean … … … … … … … … … 97.0 75 Rape … … … … … … … … … 95.0 65 LinSeeds … … … … … … … … … 95.0 65 Cashew Nuts … … … … … … … … … 99.0 80 Macadamia Nuts… … … … … … … … … 99.0 80 Coconuts … … … … … … … … … 99.0 80 Oil Palm … … … … … … … … … 98.0 80 Dram Stick … … … … … … … … … 98.0 80 D. FIBRE CROPS: Cotton … … … … … … … … … 95.0 75 Kenaf … … … … … … … … … 95.0 75 Roselle… … … … … … … … … … 95.0 75 E. DRUG/STIMULANT CROPS: Pyrethrum … … … … … … … … … 97.0 85 39 Tobacco …… … … … … … … … ... Coffee … … … … … … … … … ….. Tea … … … … … … … … …. …. ….. .. 97.0 99.0 97.0 75 80 75 F. VEGETABLE CROPS: Tomato … … … … … … … … … 97.0 70 African Cabbage… … … … … … … … 97.0 70 African Eggplant… … … … … … … … 97.0 70 Amaranths… … … … … … … … … 95.0 70 Nightshade… … … … … … … … … .. 97.0 60 Onion … … … … … … … … … … 97.0 60 Eggplant … … … … … … … … … 97.0 65 Okra … … … … … … … … … 97.0 70 Cabbage … … … … … … … … … 95.0 75 Cauliflower … … … … … … … … … 95.0 75 Collards… … … … … … … … … 95.0 75 Broccoli… … … … … … … … … 95.0 75 Brussels Sprout … … … … … … … … 95.0 75 Pepper … … … … … … … … … … 97.0 55 Celery … … … … … … … … … … 95.0 50 Cucumber … … … … … … … … … 95.0 70 Squash, Pumpkin … … … … … … … … 95.0 70 Spinach … … … … … … … … … 95.0 55 Carrot … … … … … … … … … 95.0 55 Turnip … … … … … … … … … 95.0 75 Watermelon … … … … … … … … 95.0 60 Muskmelon … … … … … … … … 95.0 60 Radish (including beet) … … … … … … 95.0 65 Swiss Chard … … … … … … … … … 95.0 60 G. FRUIT CROPS Sweet Oranges – Citrus sinensis 98.0 80 Mandarine - C. reticulata 98.0 80 Lemon - C. limon 98.0 80 Lime - C. aurantifolia 98.0 80 Grapefruit - C. paradisi 98.0 80 Pummelo - C. grandis 98.0 80 Peaches - Prunus persica 98.0 75 Plums - P. domestica 98.0 75 Apricot - P. armenica 98.0 75 Custard Apple - Annona reticulata 98.0 80 Sweetsop A. squamosa 98.0 80 Mango - Mangifera indica 99.0 75 Avocado - Persea americana 99.0 80 Guava - Psidium guajava 97.0 75 Pineapple - Ananas comosus 98.0 70 Banana - Musa spp. 98.0 95 Apple - Malus sylvestris 98.0 90 Pears - Pyrus communis 98.0 90 Grapes - Vitis vinifera 98.0 90 Papaya - Carica papaya 95.0 70 Passion Fruit - Passiflora edulis 97.0 70 Jackfruit - Artocarpus heterophyllus 95.0 70 Breadfruit - A. altilis 95.0 70 Kumquat - Fortunella japonica 97.0 75 Litchi/Lychee - Litchi chinensis 95.0 70 Longan - Euphoria longana 90.0 70 Loquat - Eriobotrya japonica 90.0 70 Pomegranate – Punica granatum 95.0 80 Raspberry - Rubus spp. 95.0 80 Rose Apple - Syzygium jambos 95.0 80 Tree Tomato - Cyphomandra betacea 98.0 70 Tamarind - Tamarindus indica 98.0 70 Straw Berry - Fragaria ananassa 95.0 80 40 Carambora - Averrhoa carambola 90.0 70 Fig - Ficus spp. 95.0 70 H. GRASSES,FORAGE AND GREEN MANURE CROPS : African Foxtail Grass – Cenchrus ciliaris … … … 80.0 50 Centro – Centrsema pubescens … … … … … 950 50 Columbus Grass – Sorghum almum … … … … … 95.0 70 Guinea Grass – Panicum maximum … … … … … 90.0 50 Kuru vine – Desmodium intatum … … … … … 95.0 50 . Rhode Grass – Chloris gayana … … … … … 60.0 50 Siratro – Phaseolus atropurpureus … … … … 95.0 50 Stylo – Stylosanthes gayanensis … … … … … 95.0 50 Lance Crotalaria – Crotalaria lanceolata … … … … 95.0 70 Striate Crotalaria - Crotalaria mucronate var, Striata … 95.0 70 Showy Crotalaria – Crotalaria spectabilis … … … 95.0 70 Kudzu – Pueraria phaseoloides … … … … … 95.0 50 Teff Grass – Eragrostis teff … … … … … 95.0 50 Weeping – Eragrostis teff … … … … … … 95.0 50 Pennisetum clandestinum … … … … … … 95.0 60 Dolichos spp… … … ... … … … … … 85.0 60 Hyparenia rufa … … … … … … … … 90.0 50 Sand Lovegrass – Eragrostis trichoides … … 90.0 50 Euchleana mecinana … … … … … … … 90.0 50 Digitaria smutsii … … … … … … … 90.0 50 Eragrostis chloromelas … … … … … … … 90.0 50 Bothriochloa insulpta … … … … … … … 80.0 50 Blue panicgrass – Panicum antidotale … … … 90.0 50 Green Panicgrass – Panicum maximum var. trichoglume … 90.0 50 Panicum coloratum … … … … … … … 85.0 40 Vine Mesquite – Panicum obtusum … … … … ... 80.0 50 Switchgrass – Pancicum virgatum … … … … 85.0 50 Melinis minufiflora … … … … … … … .. . 85.0 50 Pennisetum typhoides … … … … … … 95.0 50 Setaria sphacelate … … … … … … … 80.0 50 Setaria splendida … … … … … … … 85.0 50 Napier Grass – Pennisetum purpureum … … … … 90.0 50 Bermuda Grass – Cynodon dactylon … … … … … 90.0 50 Cyndon plectostachyus … … … … … … … 90.0 50 Themeda triandra … … … … … … … 90.0 50 Lovegrass – Eragrostis superba … … … … 90.0 50 Brachiaria brizantha … … … … … … … 90.0 50 Trypsacum laxum … … … … … … … 90.0 50 Brachiaria ruziziensis … … … … … … … 90.0 50 Stylosanthes humilis … … … … … … … 90.0 50 Clitoria ternatea … … … … … … … … 90.0 50 Alfafa – Medicago sativa … … … … … … 95.0 70 Glycine – Glycine favanica … … … … … … 95.0 60 Lupine spp. … … … … … … … … … 95.0 70 White Clover incl. Ladino – Trifolium repens … … 95.0 70 Serradella – Ornithopus sativus … … … … … 95.0 70 Slender Leaf Crotalaria – Crotalaris intermedia … … 95.0 70 Sunn Crotalaria – Crotalaria juncea … … … … … 95.0 70 TABLE 20 CERTIFIED TREE AND SHRUB SEED Basic Seed of tree shall be Seed from trees of proven genetic superiority as defined under the Act and Rules made by the Minister under Regulation 26 (4) herein. (a) “Certified 1” tree and shrub Seed shall be the Seeds progeny grown from basic tree or trees and shrubs. 41 (b) “Certified 2” Seeds shall be the Seeds progeny grown from either “Certified1” or basic tree Seed. 42 PART II: FIELD STANDARDS TABLE 1 Applicable to: (a) Wheat including hybrid – Triticum aestivum L. (b) Wheat durum – Triticum durum Desf. (c) Barley – Hodeum vulgare L.H. distichon (d) Oats – Avena sativa L., A. nuda L. Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… … 2 2 2 Off- type (count in 100m2)… … … … …. ….. 1 6 6 Other crop (inseparable) (%) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … … …… 0 0 0 Diseases – (number per 100m2) - Kernel Bunt (plant) …. - Loose smut (plant) ….. - Ear cockle (percentage).... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 TABLE 2 Applicable to: Lowland Rice (Paddy) – Oryza sativa Factor Class Basic Certified1 Certified2 Land (seasons before) … … … …… … … 2 2 2 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… … 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.1 0.1 Other Crop (inseparable) (%) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … …… … 0 0 0 Red rice / Wild rice (%)… … … … …… … 0 0.1 0.1 Diseases – (number per 100m2) – Rice Blast (plant) …. - Bacterial leaf blight (plant) ….. - White tip Nematode (percentage) .... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 43 TABLE 3 Applicable to: Upland Rice (Paddy) – Oryza sativa Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 5 5 5 No. of inspection (minimum) … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.1 0.1 Other Crop (inseparable) (%.) … … … … 0 0.05 0.05 Objectionable Weed Seed (no.)… … … … …… 0 0 0 Diseases – (number per 100m2) – Rice Blast (plant) …. - Bacterial leaf blight (plant) ….. - White tip Nematode (percentage).... 0 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 1/100 m2 TABLE 4 Applicable to: Sorghum (includes hybrid sorghum) – Sorghum bicolor (L.) Moench Factor Class Basic Certified1 Certified2 Land (seasons before) … … … … …… … 2 2 2 Isolation (m) … … … …… … …… 400 200 200 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.0 0.5 0.5 Diseases -Bunt 1/1000plants 2/1000plants 2/1000plants -Mildew 1/1000plants 2/1000plants 2/1000plants -Ergot 0 0 0 -Head/covered smut 1/1000plants /2/1000plants 2/1000plants -Kernel smut 1/1000plants 2/1000plants 2/1000plants 44 TABLE 5 Applicable to: (a) Maize open-pollinated - Zea mays L. Factor Class Basic Certified1 Certifie2” Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… 400 200 200 No. of inspection (minimum)… … … … …… 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 0.5 0.5 (b) Maize (hybrid) Factor Cross Class Certified1 Land (seasons before) ……. … … … …… … 1 1 Isolation (m) … … … …… … …… …. 400 200 No. of inspection (minimum) … … … …… ….. 5 3 Seeds parent shedding pollen (Selfing) (%) … … …. 0 1 Silk of first pollen control inspection (%)…. ….. … … … 2 2 Seeds parent at any one inspection (%)….. …. …. ….. … 0.5 Seeds parent at any three inspections (%)…. …. ….. … … 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0 0.1 TABLE 6 Applicable to: Soybean – Glycine max. Factor Basic Certified1 Certified2 Land (seasons before) … … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 5 4 4 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 1.0 1.0 Diseases – (number per 100 m2) – Soya Bean Mosaic….. ….. …. … ….. ... Bacterial Pustule (plant) ….. ….. …. … ….. Bacterial Blight (percentage) ….. ….. …. … Leaf spot (plants) ….. ….. …. … ….. ….. Anthracnose (plants) ….. ….. …. … ….. …. Charcoal rot (plant) ….. ….. …. … ….. … 0 1.0 2 0 0 0 0 0 0 1 2 2 1 2 2 1 2 2 45 TABLE 7 Applicable to: Millet (a) Millet, pearl – Pennisetum glaucum (L.) R. Br. Emend Stuntz Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 500 300 300 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.5 1.0 1.0 Diseases – (%) – Green ear…. … ... …. … - Ergot (plant) ….. … …. - Green smut (percentage) 0.05 0.1 0.1 0.02 0.05 0.05 0.05 0.1 0.1 (b) Millet, Finger – Eleusine carocana Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 25 10 10 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.05 0.1 0.1 TABLE 8 Applicable to: (n) Alfalfa – Medicago sativa (o) Clover, White, incl. Ladino – Trifolium repens (p) Glycine – Glycine javanica (q) Lance Crotalaria – Crotalaria lanceolata. (r) Showy Crotalaria – Crotalaria spectabilis (s) Slender Crotalaria – Crotalaria intermedia (t) Striate Clotalaria – Crotalaria mucronata var. striata (u) Sunn Crotalaria - Crotalaria juncea (v) Kudzu – Pueraria phaseloides (w) Lupines – Lupinus spp. (x) Seradella – Ornithopus sativus. (y) Tall Tick Clover (Kuru vine) – Desmodium spp. (z) Siratro – Phaseolus atropurpureus. Factor Basic Certified1 Certified2 % % % Land (seasons before) … … … … …… … … 2 1 1 Isolation (m) … … … …… … …… … 5 4 4 No. of inspection (minimum) … … … … …… …. 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 2.0 3.0 3.0 TABLE 9 STANDARDS FOR EACH SEED CLASS Applicable to: Forage Grasses and Crops Factor Basic Certified1 Certified2 46 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 400 200 200 No. of inspection (minimum) … … … … …… …. 3 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 2.0 3.0 3.0 TABLE 10 Applicable to: (a) Sunflower – Helianthus annuus. (b) Safflower – Carthamus tinctorius. Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 1700 1000 1000 No. of inspection (minimum) … … … … …. … 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. . 0.1 0.2 0.3 TABLE 11 Applicable to: (a) Cotton – Gossypium spp. (b) Kenaf – Hibiscus cannabinus (c) Roselle – Hibiscus sabdariffa Factor Class Basic Certified 1 Certified 2 Land (seasons before) … … … … … …… … 2 2 2 Isolation (m) (if contaminating source is of same species) ….. 200 100 100 Isolation (m) (if contaminating source is of different species) ….. ….. 450 300 300 No. of inspection (minimum) … … … … …… 3 3 3 Off- type (%)… … … … …. ….. ….. …. … ….. 0.01 0.02 0.05 Bacterial Blight (Minimum) ….. ….. …. …. …… ……… 0.5 1.0 2.0 47 TABLE 12 Applicable to: (a) Groundnut – Arachis hypogaea (b) Bambara Nut – Voandzeia subterranea Factor Class Basic Certified1 Certified2 Land (seasons before) . ……. …… ……. …… 1 1 1 Isolation (m) … …. … .. .. … … … … …. ….. …… 5 3 3 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … 0.1 0.5 0.5 TABLE 13 Applicable to: (a) Sesame – Sesamum indicum Factor Class Basic Certified1 Certified2 Land (seasons before) …. …… ……. …… … …. ….. 1 1 1 Isolation (m) ……. …… ……. …… … …. ….. 5 3 3 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … 0.2 0.5 0.5 (b) Tobacco – Nicotiana tabacum - Nicotiana rustica. Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … 1 1 1 Isolation (m) … … … …… … …… 100 50 50 No. of inspection (minimum) … … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … none 0.05 0.1 TABLE 14 Applicable to: (a) Bean, Common – Phaseolus vulgaris (b) Bean, Broad – Vicia faba (c) Bean, Lima – Phaseolus lunatis var. macrocarpus (d) Bean, Runner – Phaseolus cocecineus (e) Chick Pea – Cicer arietinum (f) Cow Pea – Vigna unguiculata (L) walp. (g) Mung Bean – Phaseolus aureus (h) Banavist Bean – Dolichos lablab (i) Hyacinth Bean –Lablab niger (j) Sword Bean – Canavalia ensiformis (k) Blackgram –Phaseolus mungo (l) Greengram –Phaseolus aureus (m) Pigeon Pea – Cajanus cajan (n) Pea – perennial – Lathyrus spp (o) Castor Bean – Ricinus communis 48 Factor Basic Certified1 Certified2 Land (seasons before) … … … … …… … … 1 1 1 Isolation (m) … … … …… … …… … 25 10 10 No. of inspection (minimum)… … … … …… 2 2 2 Off- type (%)… … … … …. ….. ….. …. … ….. 0.1 0.5 0.5 Diseases – (%) - Mosaic virus … …. ….. ….. …. … - Anthracnose ….. …. ….. ….. …. - Halo Blight .... …. ….. ….. …. … - Common Blight…. ….. ….. …. … 0.1 1.0 1.0 0.02 0.02 0.02 0.01 0.01 0.01 0.02 0.02 0.02 TABLE 15 A: Applicable to: Irish potatoes - Solanum tuberosum Factor Basic Certified 1 Certified2 Land (seasons before) … … … … … …… … … 5 3 3 Isolation (m) … … … …… … …… … 100 50 50 No. of inspection (minimum)… … … … …… 4 4 4 Off- type (number in 100 plants)… … … … …. 0 2 2 Diseases (%) Bacterial wilt …. …… … 0 0 0 Wart … ….. …. …. … …. 0 0 0 Golden Nematode …. 0 0 0 Ring rot ….. ….. …. … 0 0 0 Potato spindle … … … …. . 0 0 0 Mycoplasma… … … … 1:1000 1:100 1:100 Black leg …… …. …. . 0 0 0 Potato Virus Y …. …. ... 2 per 1000 plants 10 per 1000 plants 10 per 1000 plants Spindle Mottle Virus …… 13 per 100 plants 13 per 1000 plants 13 per 100 0plants Fusarium wilt …. … … 0 2 per 1000 plants 2 per 1000 plants Verticilium wilt ….. … .. 0 2 per 1000 plants 3 per 1000 plants 49 ___________ SECOND SCHEDULE ____________ (Made under Regulation 26(3)) ____________ SEED CLASSES Code Classes Seeds parents Colour of labels Pb Pre- basic Progeny of parent stock white with diagonal violet B Basic Progeny of certified pre- basic Seeds or certified pre- basic Seeds …. ….. ….. White C1 Cert.1st gen. Progeny of certified pre- basic Seeds or certified basic Seeds …. ….. ….. ….. … Blue C2 Cert. 2nd gen. Progeny of certified basic Seeds or certified 1st generation Seeds …. …. …. Red N.B: On authorization of the Minister, Standard seed may be labeled yellow and its code shall be Std. Seed THIRD SCHEDULE _____________ (Made under Regulation 36 (3)) _____________ (SAMPLE WEIGHTS FOR ALL CLASSES) Minimum weight for submitted sample (gm) Minimum weight for purity analysis(gm) Minimum weight for examination for other Seeds (gm) A CEREAL CROPS: Maize - Zea mays … … … … … … … 1,000 900 1,000 Wheat - Triticum aestivum … … … … 1,000 120 1,000 Wheat - Triticum durum … … … … … 1,000 120 1,000 Sorghum - Sorghum bicolor … … … … … 900 90 900 Rice - Oryza sativa … … … … … … … 700 70 700 Barley - Hordeum vulgare … … … … … 1,000 120 1,000 Millet- Eleusine carocana … … … … … 60 6 60 Oats - Avena sativa … … … … … … … 1,000 120 1,000 B GRAIN LEGUME AND PULSES: Cow peas- Vigna unguiculata … … … … … 1,000 400 1,000 -V. sinensis, V.catiag … … … 1,000 700 1,000 Field/ Common beans - Phaseolus vulgaris … … 1,000 700 1,000 Mung bean - Vigna aureus … … … … … 1,000 250 1,000 Phaseolus angularis … … … … … 1,000 400 1,000 Banavist beans - Dolichos lablab … … … 1,000 700 1,000 Hyacinth beans- Lablab niger … … … … 1,000 900 1,000 Sword beans - Canavalia ensiformis … … … 1,000 400 1,000 Pigeon pea - Cajanus cajan … … … … 1,000 300 1,000 Chickpea - Cicer arietinum … … … … 1,000 1,000 1,000 Broad beans - Vicia faba … … … … … 1,000 1000 1,000 50 Garden pea - Pisum sativum . … … … … 1000 900 1000 Bambara nut - Voandzeia subterranean … … 1,000 400 1,000 Greengram - Phaseolus aureus … … … 1,000 400 1,000 Blackgram - Phaseolus mungo … … … 1,000 700 1,000 C OIL CROPS: Soya beans - Glycine max … … … … … 1,000 500 1,000 Groundnut - Arachia hypogaea … … … … 1,000 1000 1,000 Sesame - Sesamum indicum … … … … … … 70 7 70 Sunflower - Helianthus annuus … … … … 1,000 200 1,000 Safflower - Carthamus tinctorius … … … … 900 90 900 Castor - Ricinus communis … … … … … 1,000 500 1,000 Cashew nuts – Anacardium occidentale 1,000 1,000 1,000 Macadamia nuts – Macadamia integrifolia … … … … . 1,000 1,000 1,000 Oil palm … … … … … … … …. … … …. … . 500 400 500 Coconuts …. … … … … … … … … … …. … … …. 20 15 20 Gram stick – Moringa oleifera…. … … … … … …... 200 150 200 D FIBRE CROPS: Cotton - Gossypium spp … … … … … 1,000 350 1,000 Kenaf - Hibiscus cannabinus … … … … … 700 70 700 Roselle - Hibiscus sabdariffa … … … … 700 70 700 E DRUG/STIMULANT CROPS: Pyrethrum - Chysanthemum cinerariaefolium … 100 10 100 Tobacco - Nicotiana tabacum … … … … 5 0.5 5 - Nicotiana rustica … … … … … 25 0.5 25 Coffee – Coffea spp. 1,000 400 1,000 Tea – Camellia sinensis Cocoa – Theobroma cacao … … … … …. … … …. 1,000 400 1,000 F VEGETABLE CROPS: African eggplant - Solanum macrocarpum… … … 15 7 10 Amaranth - Amaranthus spp. … … … … … 5 0.5 5 African cabbage – Brassica carinata… … … … 100 10 100 Nightshade - Solanum vilosum… … … … … 5 0.5 5 Tomato - Lycopersicon lycopersicum … … … 15 7 10 Onion - Allium cepa … … … … … 80 8 80 Egg plant - Solanum melongena … … … … … 150 15 150 Okra - Abelmoschus esculentus L. … … … 1,000 140 1,000 Cabbage - Brassica oleracea var. capitata … … … 100 10 100 Cauliflower - Brassica oleracea var. botrytis …. … 100 10 100 Sprouting brocoli -Brassica oleracea var. italica … ... 100 10 100 Brussels Sprout - Brassica oleracea var. germifera … 100 10 100 Chinese Cabbage - Brassica campestris sub-var. pekinensis … …… … … …. … 40 4 40 Chinese Cabbage Brassica campestris sub-var. chinensis … … … … … ….. …. …. …. 40 4 40 Pepper - Capsicum spp. … … … … … 150 15 150 Celery - Apium graveolens … … … … … … 25 2 25 Cucumber -Cucumis sativus… … … … … 150 70 150 Squash /Pumpkin -Cucurbita spp … … … … 1,000 700 1,000 Lettuce - Lectuca sativa … … … … … 30 3 30 Spinach - Spinach oleracea … … … … … … 250 25 250 Carrot - Daucus carota … … … … … 30 3 30 Turnip - Brassica campestris sub-var. rapa … … 70 7 70 Watermelon - Citrullus lanatus … … … … 1,000 250 1,000 Muskmelon - Cucumis melo … … … … … 150 15 150 Radish - Raphanus sativus … … … … … 300 30 300 Swiss chard - Beta vulgaris var, gilla … … … 500 50 500 51 G FRUIT CROPS Sweet oranges – Citrus sinensis 300 200 300 Mandarine - C. reticulata 300 200 300 Lemon - C. limon 300 200 300 Lime - C. aurantifolia 300 200 300 Grapefruit - C. paradisi 300 200 300 Pummelo - C. grandis 300 200 300 Peaches - Prunus persica 500 300 500 Plums - P. domestica 500 300 500 Apricot - P. armenica 500 300 500 Custard apple - Annona reticulata 300 200 300 Sweetsop A. squamosa 300 200 300 Mango - Mangifera indica 1,000 1,000 1,000 Avocado - Persea americana 1,000 1,000 1,000 Guava - Psidium guajava 200 200 200 Pineapple - Ananas comosus 10 (suckers) 10 (suckers) 10 (suckers) Banana - Musa spp. 10 (suckers) 10 (suckers) 10 (suckers) Apple - Malus sylvestris 30 (cuttings) 20 (cuttings) 30 (cuttings) Pears - Pyrus communis 30 (cuttings) 20 (cuttings) 30 (cuttings) Grapes - Vitis vinifera 30 (cuttings) 20 (cuttings) 30 (cuttings) Papaya - Carica papaya 300 300 300 Passion fruit - Passiflora edulis 200 200 200 Jackfruit - Artocarpus heterophyllus 500 300 500 Breadfruit - A. altilis 500 300 500 Kumquat - Fortunella japonica 500 200 500 Litchi/lychee - Litchi chinensis 20 (cuttings) 20 (cuttings) 20 (cuttings) Longan - Euphoria longana 20 (cuttings) 20 (cuttings) 20 (cuttings) Loquat - Eriobotrya japonica 20 (cuttings) 20 (cuttings) 20 (cuttings) Pomegranate – Punica granatum 300 200 300 Raspberry - Rubus spp. 20 (cuttings) 20 (cuttings) 20 (cuttings) Rose apple - Syzygium jambos 20 (cuttings) 20 (cuttings) 20 (cuttings) Tree tomato - Cyphomandra betacea 200 150 200 Tamarind - Tamarindus indica 200 150 200 Straw berry - Fragaria ananassa 30 (cuttings) 20 (cuttings) 30 (cuttings) Carambora - Averrhoa carambola 300 200 300 Fig - Ficus spp. 30 (cuttings) 20 (cuttings) 30 (cuttings) H GRASSES, FORAGE AND GREEN MANURE CROPS: Pennisetum clandestinum … … … … … 70 7 70 Desmodium spp. … … … … … … … 50 5 50 Glycine javanica … … … … … … … 250 20 200 Medicago sativa … … … … 50 5 55 Phaseolus atropurpure … … … … … … 75 7 75 Chloris gayana … … … … … … 25 1 20 Dolichos spp. … … … … … … … 75 7 75 Sylobanthas gracilis … … … … … … 25 5 25 Hyparenia rhufa … … … … … … 30 3 30 Cenchurus ciliaris … … … … … … 25 5 25 Eragrostis teff … … … … … … … 25 1 10 Eragrotis trichodes … … … … … … 25 1 10 Euchleana mecinana … … … … … … … 30 3 30 Digitoria smutsii … … … … … … … 25 2 20 Eragrostis chloromelas … … … … … 25 2 20 Eragrostics curvula … … … … … … 30 3 30 Bothriochloa insulpta … … … … … … 30 3 30 Panicum maximum … … … … … … … 25 2 20 Panicum antidotale … … … … … … 25 2 20 Panicum maximum va., trichoglume … … … 25 2 25 52 Panicum coloratum … … … … … … 25 2 25 Panicum obtusum … … … … … … 25 2 20 Panicum virgatum … … … … … … 30 3 30 Melinis minufilora … … … … … … 5 0.5 5 Lupinus spp. … … … … … … … 1,000 450 1,000 Pannisetum typhoides … … … … … … 60 6 60 Seteria splendida … … … … … … … 90 9 90 Seteria sphacelate … … … … … … 90 9 90 Sorghum alum … … … … … … 700 20 200 Pennisetum purpureum … … … … … … 60 6 60 Sorghum sudanense … … … … … … 250 25 250 Trifolium repens … … … … … … … 25 2 20 Ornithopusstivus spp. … … … … … … 90 9 90 Crotalaria intermedia … … … … … … 150 15 150 Crotalaria juncea … … … … … … … 700 70 700 Crotalaria lanceolata … … … … … … 70 7 70 Crotalaria mueronate … … … … … 150 15 150 Crotalaria spectabilis … … … … … … 350 35 350 Cynodon dactylon … … … … … … … 25 1 10 Themeda triandra … … … … … … … 25 2 25 Eragrostis superba … … … … … … 25 2 25 Cynodon plectostachyus … … … … … 25 1 10 Brachiaris brizantha … … … … … 30 3 30 Trysacum laxum … … … … … … 30 3 30 Brachiaria ruziziensis … … … … … … 30 3 30 Centrosema pubescens … … … … … 150 15 150 Pueraria phaseoloides … … … … … … 350 35 350 Stylosanthes humilis … … … … … 100 10 100 Stylosanthes mucronata … … … … … 50 5 50 Clitoria ternatea … … … … … … 100 10 100 H ROOT CROPS AND SPICES: Potato (Irish) - Solanum tuberosum.(no. of tubers) … 50 30 50 Garlic – Allium sativum(no. of sets)… … … … 50 20 50 Ginger – Zingiber officinalis(no. of rhizomes)… … 50 20 50 Cardamon –Elittalia cardamomum(gm) … … … 50 20 50 Cinnamon – Cinnamomum zeylanicum(cuttings)… … . 50 20 50 Cassava – Manihot esculentum (no. of cuttings) … 50 20 50 Sweet potatoes –Ipomea batatas (no. of vines) … 50 20 50 Yams – Dioscorea spp.(no. of tubers) 20 10 20 _________ FOURTH SCHEDULE ___________ (Made under Regulation 27 (8)) ____________ THE MINIMUM NUMBER OF PLANTS OR HEADS REQUIRED PER COUNT FOR EACH CROP ___________ S/no. Crop Number of counts required 1. Maize (hybrids/composite) … …. …. … …. 100 2. Sunflower castor… …. …. … … … … . 100 3. Beans and peas, cowpeas, groundnuts chickpeas and green gram … … .., …... 500 4. Sesame, groundnut, kenaf, cotton, okra, amaranths…. 500 53 5. Sorghum/millets… …. …. ….. … … . 1000 6. Wheat, rice, oats barley, critical … ….,. 2000 7. Peppers, eggplant, tomato … …………… 200 8. Cabbage, cauliflower … ………………… 200 9. Cucurbits… …. …. …… …. …. …… Almost every plant 10. Onions… …. …. …… …. …. …… ….. 2000 bulbs 54 ___________ FIFTH SCHEDULE ___________ (Made under regulation…..) ______________ APPLICATION FORMS/CERTIFICATES _____________ THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT (No. 18 of 2003) S/N………… Form SR I APPLICATION FOR RFGISTRATION AS A SEED DEALER (Made under Regulation 3(1)) (To be filled in Triplicate) To: Director for Crop Development Ministry of Agriculture, Food Security and Cooperatives P.O.Box 9192 DAR ES SALAAM. I/We hereby apply to be registered as seed dealer :- Name ………………………………………………………………………… Postal Address ……………………………………………………………….. Telephone Number ……………………………………………………….….. Email Address………………………………………………………………… Location of the premises …………………………………………….………. I/we wish to deal in (Please tick where applicable) ( i) Production (ii) Processing (iii) Importation (iv) Exportation (v) Distribution (vi) Sale * For a legal person like a company, please attach Memorandum/Articles of association/ registration certificate/ and or constitution _________________________________________________________________________________________________________ PART A: TO BE FILLED BY APPLICANTS WHO WISH TO PRODUCE/GROW SEED _________________________________________________________________________________________________________ 1. Mention class/class (s) of Seed to be produced: ……………………………………………………………………………………………… 2. What mode of production do you intend to use :- (fill where appropriate) (a) own land , hectares of production land ……………………………………………… Location:………………………………………….… (b) contract grower (c) give details of land and equipment:……………………………………………………………..………………………………….….....…..… 3. Provide number and qualification of the personnel who are conversant with Seeds production that are in your possession or possession of your contract grower ……………………………………………………………………………………………………………………….………….... 4. For how long have you been engaged in Seeds business?....................................................................................................................................... (attach business profile) 55 PART B: TO BE FILLED BY APPLICANTS WHO WISH TO PROCESS SEED 1. Do you have adequate equipments and machinery to process Seed? Yes /No If “ YES” provide the list and capacity of each equipment/machinery :………………………………………………………………………… 2. Are equipment/machinery own or hired?.................................................................................................................................................................. 3. Describe your storage facilities: …………………………………………………………………………………………………………………… 4. Do you have a capacity to mark or label packets /containers as required by Seed Regulations? Yes /No 5. Do you have adequate and knowledgeable personnel who are conversant with Seeds processing and storage? Yes/No. if “YES”, provide number and qualification of the said personnel ………………………………………………………………………………………………………………………………………………………….. ………………………………………………………………………………………………………………………………………………………….. ………………………………………………………………………………………………………………………………………………………….. _____________________________________________________________________________________________________________________ PART C: TO BE FILLED BY APPLICANTS WHO WISH TO IMPORT/ EXPORT SEED _____________________________________________________________________________________________________________________ 1. Mention class/class (s) of Seed to be imported/exported: ……………………… ……………………………………………………………… 2. Do you have adequate and knowledgeable personnel who are conversant with Seeds matters? Yes/No. if “YES”, provide number and qualification of the said personnel:…………………………………………………………………...…………………… 3. What is estimated tonnage of Seed to be imported/exported annually:…………………………………………………………………………… 4. Where are proposed sources for import/ export:…………………………………………………………………………………………………... 5. Describe your storage facilities:………………………………………………………………………….……………………………...………… _____________________________________________________________________________________________________________________ PART D: TO BE FILLED BY APPLICANTS WHO WISH TO SELL/DISTRIBUTE SEED _____________________________________________________________________________________________________________________ 1 What are your distribution centres in the country………………………………………………………………………………………………… 2 Do you have enough storage facilities? YES/ NO. If “YES” state their capacity and conditions…………………………………………….… 3 Do you have any agreements with agents or stockist to distribute Seed on your behalf ? YES/ NO . 4 If you have agents or stockist, do they have any identity to recognize them? YES/ NO if “YES” state their identity. ……………………………………………………………………………………………………………………………………………...… 5 Do your agents or stockist have any knowledge on Seeds business YES/ NO . 6 How will you ensure that your agents or stockist comply with the Seeds law?....................................................................................................... ……………………………………………………………………………………………………………………………………………………. _____________________________________________________________________________________________________________________ PART E: TO BE FILLED BY SEED STOCKIST _____________________________________________________________________________________________________________________ 1. location of shop …………………………………………village/street…………………………………………ward/town……………….…… 2. Do you have any agreements with any seed dealer to distribute seed on his behalf ? YES/ NO ………………………………………………... 3. if the answer in 2 is “YES”, mention them ……………………………………………………………,………………………………………… 4. If you have any identity ? YES/ NO if “YES” state the identity. ………………………………………………………………………………... 5. Do you have enough storage facilities? YES/ NO. If “YES” state their capacity and conditions?........................................................................ ………………………………………………………………………………………………………………………………………………………… …………………………………………………………………………………………………………………… 56 Declaration : I/We declare that all information provided herein above is true to the best of my/ our knowledge. Signed at……………………………………this…………..day of…………………20…… Signature:………………………………………………………………. _____________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY _______________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………..…………………… Fees Receipt No: …………………………………………………………………………………………………………………………………….. Date Approved/Rejected: …………………………………………………………………………………………………………..………………… If approved: Reg No.…………………........................................................................................................................................................................ If rejection, reasons for rejection….………………….................................................................................................................................................. Dated:……………………………….Signature of the responsible officer:………………………………...…………………………………………… 57 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR II Registration No. ………… CEERTIFICATE OF REGISTRATION AS SEEDS DEALER ( Made under Regulation 3(3)) This is to certify that……………………………………………………………………… of………………………………...……………………… (Name and address of Registrant ) has been registered as Seeds producer/processor/importer/exporter/ distributor ( delete where applicable) for category of……………………….. …………………………………………………………………………………………………………………………………………………………. (state of crop and class) his farm /premises for business is located at ……………………………………………………………………………………………………….…. (village/ town/district/ region) This registration shall be valid for the period of ……………………from………………………to …………………………and may be cancelled if the registrant fails to comply with terms and conditions for registration as set out in the Seeds Act, 2003 and Regulations made thereto. Issued at …………………………this………….day of …………………….200………. Signature:………………………………………………………….. Director of Crop Development. 58 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IIIA ______________ APPLICATION FOR DUS TEST ______________ (Made under Regulation 7(1)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute 1. Full name of the Applicant/Pre- basic: ………………………………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3. Tel. No. ……………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………………. 5.Name of the crop ………………………………………………………….6. Botanical Name:……………………………………………………... 7. Family Name:……………………………………………………………...8. Chromosome Number………………………………………………. 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:……………………………………………………………………………………………………………………………. 11.Name under which it is tested:………………………………………………………………………………………………………………………. 12. Proposed elevation:…………………………………………………………………………………………………………………………………. 13.Major distinguishing merits from other released varieties:……………………………………………………………………………………… 14. Variety descriptor attached/Not attached (cross where necessary) 15. Test fee paid by………………………………………P.O.BOX…………………………………………………………………..…………… Dated:……………………………………………………….Signed:………………………………………………………………....………………… ______________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY: ______________________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………………………………. Fees Receipt No: …………………………..…………………………………………………………………………………………………………… Amount of sample received for DUS test : first season:…………………………………………………second season…………………………….… Date Approved/Rejected: ………………………………………………………………………………………………………………………………. If rejection, reasons for rejection. …………………........................................................................................................................................................ Dated:……………………………….Signature of the responsible officer:……………………………………………………….…………………… 59 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IIIB ______________ APPLICATION FOR NATIONAL PERFORMANCE TRIAL ______________ (Made under Regulation 4(1)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute. 1. Full name of the Applicant: ………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3.Tel. No. ………………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………………. 5.Name of crop ………………………………………………………….…………………………………………………………………..………. 6. Botanical Name:…………………………………………………….. ……………………………………………………………………….……… 7. Family Name:……………………………………………………………... ………………………………………………………………………… 8. Chromosome Number……………………………………………….……………………………………………………………………………….. 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:………………………………………………………………………………………………………………..…………… 11. Proposed Name:……………………………………………………………………………………………………………………... ..…………… 12.Name under which it is tested:………………………………………………………………………………………………………. ..……………. 13. Agency responsible for development :……………………………………………………………………………………………… ..…………… 14.Cutivar Pedigree:…………………………………………………………………………………………………………………… ..…………….. 15. proposed area for release:………………………………………………………………………………………………………… ..…………….... 16.Proposed elevation:………………………………………………………………………………………………………………… ..……………... 17. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………. ..………… 18. Agency responsible for maintenance:………………………………………………… ..…………….……………………… ..……………. ..….. 19. Distinguishing characteristics (describe fully) (a)growth habit:………………………………..(b) leaf:…………………………………..(c) stem:………………………..……………………… (d) flower:……………………………………...(e) pods:…………………………………………………………………………………………... (f) Seeds:………………………………………...(g) Seed size:…………………………………………………………………………………..… (h)Seeds shape and colour:……………………...(i) time to flowering:…………………… (j) growth habit:…………………………………...... (k) others: ………………………………………………………………. 20. Major distinguishing merits from other released varieties:……………………………………………………………………………………... 21.Points of merits, drought tolerance, disease resistance, lodging resistance, etc…………………………………………………………………….. 22.Economical and quality attributes:…………………………………………………………………………………………………………………… 23.Agronomic characters (optimal):……………………………………………………………………………………………………........................ (a) Sowing date:………………………………………………..(b) Seeds rates:……………………...……...……………………………………... (c) Plant population :………………………………………….(d) Maturity:………………………………...........................................................… (e) Fertilizer:…………………………………………………...(f) Crop height:………………………..................................................................... (g) Irrigation need :…………………………………………………….……………..................................…………………………...…………….. (h Consumer acceptability :…………………………(i) Others:……………...……………………………………………………………………... 24. Yield data/comparison/trial (Attach) (a) Yield compared to check:……………………………………..(b) Yield in farmers field:………………………………………………………… 25. Name and address of Pre- basic if deferent from the Applicant…...…………………………………….................................................................. I/We certify that the information given above is correct to the best of my/our knowledge. I/We hereby enclose a cheque for:…………………………………………………………………………..being the payment of the application fee. 60 Date: ………………………………………… Signature: ………………………………………………………………………………………………..… * ______________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY ______________________________________________________________________________________________________________________ Application No: …………………………… Date Received: …………………………………………………………………………………………. Fees Receipt No: ………………………….. Advanced yield trial data (Accepted/Not accepted)………………………………….….. Amount of sample received:…………………………………………………………... Date Approved/Rejected: …………………………...……… If rejection, reasons for rejection. …………………........................................................................................................................................................ I………………………………… …………title………… …………………,certify that the information given above is correct to the best of my knowledge using the information and scientific data available to me. Date: ……………………………………………… Signature: …………………………………………………………………… 61 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR IV ______________ CERTIFICATE FOR DISTINCTINESS,UNIFORMITY AND STABILITY TEST ______________ (Made under Regulation .7(3) This is to certify that the candidate variety whose particulars referred herein has been passed test for Distinctness, Uniformity and Stability (DUS) Name / number under which it was tested: …………………………………………………………………………….….. Plant species: ……………………………………………………………………………………………………….………. Botanical Name: ……………………………………………………………………………………….………………….... Name and Address of Applicant/ Certificate holder …………………………………………………………………….…. Certificate Number. ………………………………………………………………………………………….……………. Issued this……………………day of …………………………………………………200……. Signature & stamp: ……………………………………………. Chief Seed Certification Officer 62 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR V ______________ RE: RECOMMENDATION FOR THE RELEASE OF NEW VARIETY ______________ (Made under Regulation 7(7)) (To be filled in Triplicate) To: National Variety Release Committee This is to notify that the variety whose particulars set herein below had been submitted for NPT this ………………day of…………………….200………… The review of application was conducted by NPT- TC on ……………………day of…………………….200………… 1. Full name of the Applicant/Pre- basic: ………………………………………………………………………………………………………………… 2. Postal Address ………………………………………………………….3.Tel. No. …………………………………………………………… 4. Email. ……………………………………………………………. Fax No…………………………………………………………………… 5.Name of crop ………………………………………………………….…………………………………………………………………..…… 6. Botanical Name:…………………………………………………….. ……………………………………………………………………….……… 7. Family Name:……………………………………………………………... …………………………………………………………………… 8. Chromosome Number……………………………………………….………………………………………………………………………… 9: Mode of Pollination:…………………………………………………………………………………………………………………………………. 10.Other basic information:…………………………………………………Pre- basic………………………………………………………………...... 11. Proposed Name:…………………………………………………………………………………………………………………...………………... 12.Name under which it is tested:………………………………………………………………………………………………………………… 13. Agency responsible for development:……………………………………………………………………………………………… ..……… 14. Cutivar pedigree:…………………………………………………………………………………………………………………… ..……… 15. Proposed area for release:…………………………………………………………………………………………………………………….. 16.Proposed elevation:………………………………………………………………………………………………………………… ..……………... 17. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………. ..……………. 18. Agency responsible for maintenance:………………………………………………… ..…………….……………………… ..……………. ..….. 19. Distinguishing characteristics (describe fully) (a) growth habit:……………………………….(b) leaf:………………………….(c) Stem:……………………………………………………... (d) flower:……………………………………...(e) pods:…………………………………………………………………………………………... (f) Seeds:………………………………………...(g) Seeds 63 size:…………………………………………………………………………………… (h) Seeds shape and colour:……………………...(i) time to flowering:………………………………………………………………………… 20. Major distinguishing characters from other released varieties:…………………………………………………………………………………….. 21.Points of merits, drought tolerance, disease resistance, lodging resistance, etc…………………………………………………………………….. 22.Economical and quality attributes:………………………………………………………………………………………………………………...… 23.Agronomic characters (optimal):……………………………………………………………………………………………………....................... (a) Sowing date:………………………………………………..(b) Seeds rates:……………………...……...………………………………….…... (c) Plant population :………………………………………….(d) maturity:………………………………...........................................................… (e) Fertilizer:…………………………………………………...(f) plant height:………………………..................................................................... (g) Irrigation need :……………………………………………………..……………..................................…………………………...……………. (h) Consumer acceptability :…………………………( i) Others:……………...……………………………………………………………………. 25. Yield data/comparison/trial (a)Yield compared to check:…………………………(b) Yield in farmers field :……………………….………… 26. Any other information:……………………………………………………………………........................................................................................ The following are the results of NPT:- 1: Mode of Pollination:…………………………………………………………………………………………………………………………………. 2. Proposed Name:………………………………………… 3.Name under which it is tested:………………………………………………………... 4. Agency responsible for development: ……………………………………………………………………………………………………………….. 5. Cultivar Pedigree: …………………………………………………………………………………………………………………………………… 6. Name of Pre- basic: ……………………………………………………………………………………………………………………………………. 7. Proposed area for Release:…………………………………………………………………………………………………………………………… 8.Proposed elevation:…………………………………………………………………………………………………………………………………… 9. Agency responsible for supply of pre- basic Seeds:……………………………………………………………………………………………………... 10. Agency responsible for maintenance:………………………………………………………………………………………………………………. 11. Distinguishing characteristics: (a) growth habit:……………………………………….(b) leaf:…………………………………………….(c) Stem:…………………………… (d) flower:…………………………………………......(e)pods:…………………………………………………………………...……………….. (f) Seeds:……………………………………………… (g) Seeds size:…………………………………………………………...…………………. (h) Seeds shape and colour:……………………………..(i) time to flowering:………………………………………………………….…………. 12. Major distinguishing characters from other released varieties:…………………………………………………………………………………….. 14. Economical and quality attributes:………………………………………………………………………………………………………………… 15. Agronomic characters (optimal):………………………………………… (a) Sowing date:……………………………………..……………… (b) Seeds Rates:……………………...……...(c) Plant population:…………………………………….(d)Maturity:………………………………. 64 (e) Fertilizer:………………………………………………………..(f)crop height:………………………................................................................ (g) Irrigation need :…………………………………………………( h)Harvest index:…………….............................................................…......... (i) Consumer acceptability :………………………………………..( j)Others:……………...……………………………………………..………. 16. Yield data (a)Yield on NPT :…………………………………….(b) Yield on farm :…………………………………………………………… Based on the above results, NPT-TC recommends that:- (a) the variety be release (………)* (b) the variety should not be release (………)* Signature and Stamp:…………………………………………………… date:……………………………………………………………………………………….. *Please tick where applicable Secretary – NPT-TC ………………………………….. Attached: DUS results, NPT report, on farm trial report advanced yield trial 65 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR VI ______________ VARIETY REGISTRATION CERTIFICATE ______________ (made under Regulation 8(2)) This is to certify that the variety whose particulars referred herein has been approved and registered for use and commercialization in Tanzania. Name of Variety: …………………………………………………………………………….….. Plant species: ……………………………………………………………………………………. Botanical Name: ……………………………………………………………………………….... Name and Address of Registrant …………………………………………………………….…. Registration Number. …………………………………………………………………………… Issued this……………………day of …………………………………………………200……. Signature and Seal: ……………………………………………. Director 66 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR VII ______________ APPLICATION FOR INSPECTION OF SEED FIELD CROP ______________ (Made under Regulation 27(1)) (To be completed in triplicate) To: Tanzania Official Seed Certification Institute Note: Separate application form must be submitted for each crop and variety grown for certification and must be submitted within 30 days after planting. A map giving clear instruction on how to reach the farm as well as the location of the field unit within the farm must be drawn overleaf. 1. Full name of Applicant: .........................................................Address:................................................... Telephone: .............…………... 2. Name of Contract grower (if any)*:......................................................Address: ......................................Telephone: ............................. 3. Person to be Contacted for field inspection: ...........................……………Address: ................................. Telephone: ...............………. 4. Location of the field from the nearest town: ...................................… ………………………………………....................................... 5. Location of the field within the farm: ..................................................................................……………………………………….…...... 6. Details of crop to be produced/grown: Crop Variety Class Lot No. of Seeds used Hectarage: Source of Seeds use (Supplier/Seller Planting date 7. Estimated flowering/Tasselling date: ………………………….........................................................……………................................. 8. Quantity of Seeds Used: ...................... kgs No. of Containers:..............................................Weight of each container: .....................kgs 9. Estimated date of Harvesting (Approximate): ............................................……………………………………………………………… 10. Previous crops and varieties grown in this field for the last two growing seasons……………………………………………………… * a separate application form should be filled for each contract grower. Declaration: I hereby declare that all information provided here is true to the best of my knowledge and belief and I shall always observe all conditions governing Seeds production as provided in the Seeds Act and Regulations. Enclosed herewith is a cheque of the sum of shillings…………………… being payment of the inspection. Date: ................……... ………………………Signature of Applicant: ………………………..……………………….................................. Designation: ......................................................................................................................................................................................................... 67 FOR OFFICIAL USE ONLY Date received:…………………… ……..Appication No…………………………………………………………………………………..… Application accepted/rejected: ..................................................................……………....................................................................................... If rejected, state reasons for rejection:...................................................……………. .......................................................…............................... Field Registration No: ………………………………………………………….….…................................................................................... Date: ..................….... Signature: ...................……………...... Designation:.................................................................................................................... 68 Form SR. VIIIA THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… ______________ FIELD INSPECTION RESULTS ______________ (Made under Regulations 27(12)) (to be filled after every inspection) Applicant name………………………………………………………………….Address………………………………………………………..… Grower name………………………………………………………………….Address………………………………………………………..… Crop ………………………………………..Variety:…………………………………………………………………………………….. Class:……………………………………………...hectares:…………………………………………………………..……………………...… Does the crop have proper cutivar characteristics…………………………………………………………………………………………………….. Count Off - types Diseases Other features Objectionable weeds Other crop weeds 1. 2. 3. 4. 5. 6. Total Average percentage Identity The isolation distance /time of ……………………………………………………………days/meters is adquate/inadquate and should be corrected. General conditions of crop e.g drought, crop husbandry, etc…………………………………………………………………………………………... ………………………………………………………………………………………………………………………………………………………….. Further remarks…………………………………………………………………………………………………………………………………………. ………………………………………………………………………………………………………………………………………………………….. Estimated yield …………………………………………………………………………………bags/hectares……………………………………….. Comments: This crop is approved/rejected. If rejected state reasons:……………………………………………………………………………………………………………………………….... ………………………………………………………………………………………………………………………………………………………….. Signature of Seeds Grower or representative of the Grower ………………………Date…………………………...………………………………… Name of the Inspector: ………………………………………………………….……………………………………………………………………… Signature…………………………………………………………..Date………………………………………………………….…………………… Inspector 69 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR. VIIIB ______________ FINAL FIELD INSPECTION RESULT ______________ (Made under Regulation 27(13)) Applicant name………………………………………………………………….Address………………………………………………………..… Grower name………………………………………………………………….Address……………………………………………………..…..… Crop ………………………………………..Variety:…………………………………………………………………………………………….. Class:……………………………………………...hectares:…………………………………………………………..…………………….......… Factor 1st inspection 2nd Inspection 3rd Inspection Total No. or % Off - types Diseases Tassels Weeds Other crops Other (specify) Remarks………………………………………………………………………………………………………………………………………. ………………………………………………………………………………………………………………………………………………… ………………………………………………………………………………………………………………………………………………… This Crop is approved/rejected. If rejected, state reasons:…………………………………………………………………... Signature ……………………………………………………………………………………. Seed grower Signature…………………………………………………………..Date………………………………………………………….……………. Filed Inspector Copy to: Grower. Chief Seed Certification Officer 70 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR IX SEED TRANSPORT ORDER (Made under Regulation 29(2)) To:………………………………………………………….of …………………………………………………………………………... This order is issued to authorize transportation for processing of …………………………………bags/tones of seed crop from …………………to ………………………………………………on…………………….200……………………………. Crop : ……………………………………………………….…………. Variety: ………………………………………………………….....…. Class: ……………………………………………………………..…... Mode of transportation :…………………………………………….…. Vessel Registration No:. ……………………………………………… Type of the identification:………………………………………………………………………………………… ) ………………………………… Seeds Inspector 71 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE S/N………… Form SR X ______________ WORK ORDER ______________ (Made under Regulation 30(2)) This work order is issued at …………………………………………this ……………………. day of ……………………………………200…………. Name and address of Seeds producer : ……………………………………………………… ……………………………………...................................... Crop : ……………………………………… variety ………………………………………………………………………………...…………………….. Name and address of Seeds processor: …………………………………………………………………….…...………………………...…………………. Location of processing plant………………… ……………………………………………………………………………………....................................… Class …………………………………………….Weight of lot before processing…………………………………………………kg Lot No…………………………………………………..Provisional germination………………………………………………… % No. of Labels Serial Nos. of labels Issued No. of unused Labels Date of Sealing Nos. of Seals used No. Container Sample No. Remarks if any ……………………………………………………………………………………………………………………………………….……… ………………………………………………………………………………………………………………………………………...… ………………………………………………………………………………………………………………………………………..……… ……………………………………………………………………………………………………………………………………………... Name of Inspector:………………………………… Signature: …………………………………………. Cc: Chief Seed Certification Officer 72 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEEDS CERTIFICATION INSTITUTE S/No FORM SR XI _________ STOP SALE ORDER _________ (Made under Regulation 32(5)) (to be filled in dublicate) Date:……………………………………….. To: .. ………………………………………………………………………………………………………………………………………………..……… (Name of Seeds Dealer) Address:………………………………………………………………………………………………………………………………………………… Businness Licence No……………………………………………………………………………………………............ You are hereby informed that the following lots of Seeds are found to be in violation of Seeds Act and Regulations : Crop Variety Lot No. No. of containers Quantity in Kg. Nature of violation Sampled Yes No By this Notice you are ordered to hold these lot/ lots of Seeds intact at:……………………………………………………………………………... until compliance with the law has been achieved and the Seeds has been released from this order . Once you comply with the relevant violated provision of the Seed Act or Regulations, please contact Chief Seeds Certification Office. Other instruction: ………………………………………………………………………………………………………….................................................. Name of Inspector: ……………………………………………………………… ..Name of seed dealer …………………………………....................... Signature: ………………………………………………………………………… Signature: ………………………....................................................... Date: ……………………………………………………………………………… Signature: ………………………………........................................... 73 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/No FORM SR XII ____________________ NOTICE TO IMPORT SEED ____________________ (Made under Regulation 33(1)) To: The Director, Ministry of Agriculture, Food Security and Cooperatives P.O.BOX 9192 Dar Es Salaam I/ We hereby apply to Import Seed described herein below in accordance with the terms and conditions laid down in the Seed Act and the Regulations made thereto. 1. Full Name of Applicant: ………………………………………………………………………………………………………………………. 2. Address:………………………………………………………………Tel:……………………………………………………………………. 3. Registration No………………………………………………………………………………………………………………………………… 4. Previous permit No. (if any )……………………Location of the store/godown where the Seeds will be kept after arrival :………………… 5. Quantity of the Seeds of the same variety in stock (if any)……………………………………………………………………………………. 6. Country of Origin………………………………………………………………………………………………………………………………. 7. Name and address of the Supplier:…………………………………………………………………………………………………………...… 8. Expected date of arrival of the consignment…………………………………………………………………………………………………… 9. Mode of transport ……………………………………………………………………………………………………………………………… 10.Point of entry…………………………………………………………………………………………………………………….…………….. 11.Particulars of seed ……………………………………………………………………………..………………………….…………………… Crop Variety Name Class Quantity in Kg. Declaration: I declare that all information provided herein is true and I do undertake to observe all terms and conditions for importation/ exportation as provided in the Seeds Act and its Regulations. Signed this……………………………day of ………………………………200……………………………………………… Signature:……………………………………………………………….. _________________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY Date Received:………………………………………………………….. Application Fees paid …………………………………………………………………………………………………………………………………….… Action taken : Considered for permit/ Not considered for Permit* Date: …………………………………………………………………….. Signature:………………………………………………………………… Director *please delete where necessary 74 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR XIII ____________________ SEED IMPORT PERMIT ____________________ (Made under Regulation 33(3)) Permit No. ……………………………………Date issued ………………………………………...………………………………...…….. Permission is hereby granted to …………………………………………………………… of Postal Address Office……………………... (Name and of the Seeds dealer) ………………………………………………………………………………, Registration No. ………………………………………….. to import from. …………………………………………………………………………………………………………………………….. the following Seed: _ Species Variety Class Weight in kg This permit is issued subject to the following conditions: 1. The consignment of Seeds shall be accompanied by- (a) Phytosanitary certificate. (b) Certificate of quality issued by a Recognized Certification Agency 2. The consignment shall be subjected to Tanzania Plant Protection Act and Regulations made thereof and on arrival in the country, the Seeds shall be inspected in accordance with the Seed Act and Regulations made thereto. 3. The Seed shall not be distributed prior to the outcome of the results of sample. 4. The Permit holder shall be required to pay all fees as stipulated in the Seeds Regulations. 5. The permit holder shall be required to fulfill all conditions for importation as provided in the relevant law of Tanzania. 6. This permit is not transferable and may be revoked if the holder fails to comply with the terms and condition for conditions as provide in the Seed Act and the Regulations made thereto. 7. The permit shall be for ………………………….months only. Signature : ……………………………………………………………………………………………………………………………….. Director cc. Chief Seeds Certification Officer. 75 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/No FORM SR XIV ____________________ NOTICE TO EXPORT SEED ____________________ (Made under Regulation 34(1)) To: The Director Ministry of Agriculture, Food Security and Cooperatives P.O.BOX 9192 Dar Es Salaam I/ We hereby apply to export Seed described herein below in accordance with the terms and conditions laid down in the Seed Act and the Regulations made thereto. 1. Full Name of Applicant: ………………………………………………………………………………………………………………………. 2. Address:……………………Tel:………………………………………………………………………………………………………………. 3. Registration No………………………………………………………………………………………………………………………………… 4. Previous permit No. (if any )……………………Location of the store/godown where the Seeds will be kept after arrival :………………… 5. Quantity of the Seeds of the same variety in stock (if any)……………………………………………………………………………………. 6. Country of Origin……………………………………………………………………………………………………………………………..…. 7. Name and address of the Supplier:…………………………………………………………………………………………………………...… 8. Expected date of arrival of the consignment…………………………………………………………………………………………………… 9. Mode of transport ……………………………………………………………………………………………………………………………… 10. .Point of entry…………………………………………………………………………………………………………………….…………….. 11. Particulars of seed ……………………………………………………………………………..………………………….…………………… Crop Variety Name Class Quantity in Kg. Declaration: I declare that all information provided herein is true and I do undertake to observe all terms and conditions for Importation/ exportation as provided in the Seeds Act and its Regulations. Signed this……………………………day of ………………………………200……………………………………………… Signature:……………………………………………………………….. _________________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY Date Received:………………………………………………………….. Application Fees paid …………………………………………………………………………………………………………………………………….… Action taken : Considered for permit/ Not considered for Permit* Date: …………………………………………………………………….. Signature:………………………………………………………………… Director *please delete where necessary 76 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… Form SR XV ____________________ SEED EXPORT PERMIT ____________________ (Made under Regulation 34(3)) Permit No. ……………………………………Date issued ………………………………………...………………………………...…….. Permission is hereby granted to …………………………………………………………… of Postal Address Office……………………... (Name and of the Seeds dealer) ………………………………………………………………………………, Registration No. ………………………………………….. to import from. …………………………………………………………………………………………………………………………….. the following Seed: _ Species Variety Class Weight in kg This permit is issued subject to the following conditions: 1. The consignment of Seeds shall be accompanied by- (a) Certificate of quality issued by Tanzania Official Seed Certification Institute. (b) Phytosanitary certificate and other relevant document governing exportation issued by relevant authorities. 2. The Permit holder shall be required to pay all fees as stipulated in the Seeds Regulations. 3. The permit holder shall be required to fulfill all conditions for exportation as provided in the relevant law of Tanzania and the country which seeds are exported. 4. This permit is not transferable and may be revoked if the holder fails to comply with the terms and condition for conditions as provide in the Seed Act and the Regulations made thereto. 5. The permit shall be for ………………………….months only. Signature : ……………………………………………………………………………………………………………………………….. Director cc. Chief Seeds Certification Officer. 77 FORM SR XVI THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) S/N………… ______________ APPLICATION FOR SEED TESTING ______________ (Made under Regulation 38(2)) (To be filled in Triplicate) To: Tanzania Official Seed Certification Institute1. Full name of the Applicant: …………………………............................... 2. Postal Address …………………………………………………………………………… (3) Tel. No. .......................................................... 4. Email. …..............................................Fax No……………………………………………............................................................................. 5. Crop …………………………………………………………………………………………………........................................................ 6. Variety .............................................................Class ………………………………………………………………………………...……. 7. Lot No. ………………………………………….Ref. ……………………………………………………………………...…………… 8. Seeds Import Permit No. ………………………………….. of ………………………………………Date ……………………………… 9. Weight of Lot……………………………………………………………………………………………………………………………… 10. Seeds dressing……………………………………………………………………………………………………………………...…….. 11. Date of Sampling:………………………………………………………………………………………………………………………………………… 12. Tests required……………………………………………………………………………………………………………………………… (purity/germination/moisture/injurious weeds/diseases/) * 13. Testing fee paid ………………………………………………………… Payment Voucher/ Cheque No ……………………………..). I certify that the sample was drawn by me in the prescribes manner this …………………………..day of ………………………………... Name of Sampler:…………………………………………….Address…………………………………………..………………………… Signature:…………………………………………………………………………… * delete as necessary ________________________________________________________________________________________________________________ FOR OFFICIAL USE ONLY: Application No: …………………………… Date Received:…………………………………………………………………………………… Fees Receipt No: ………………………….. Amount of sample received for testing :………………………………………………………………………..…. ………………………… Test requested:………………..………………………………………………………………………..…. …………………………………… Test results: Dated:……………………………….Signature of the responsible officer:……………………………………… 78 FORM SR XVII S/N………… THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE ______________ SEEDS TESTING CERTIFICATE ______________ (Made under Regulation 38(3)(b)) ((To be filled in Triplicate) OFFICIAL SAMPLE NO. Date received: TEST NUMBER Lot Number: Weight of lot: Crop and variety: Class of Seeds : Country of origin: RESULT OF ANALYSIS Purity Germination Pure Seeds (P) % Inert matter % Other Seed % Weed Seed % Capacity (G) Hard % Fresh ungerminated Seed % Abnormal Seedslings % Pure germinating Seed P x G 100 % Moisture % % Types of : (1) Inert matte ……………………………………………………………………………………………………………………………… (2) Other Seed……………………………………………………………………………………………………………………………… (3) Weed Seed: (a) objectionable …………………………………………………………………………………………………….………… (b) restricted ………………………………………………….……………………………………………………………… Special test:……………………………………………………………………………………………………………………………….. ………………………………………………………………………………………… ………………………………………………….. Remarks: It is hereby certified that the Seeds lot described above has met/ has not met minimum Seed standards for ……………………….class Signature……………………………………. Seeds Analyst Date:…………………………………………… Signature……………………………………. Chief Seeds Certification Officer 79 FORM XVIII S/N………… THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES THE SEED ACT, 2003 (No. 18 of 2003) TANZANIA OFFICIAL SEED CERTIFICATION INSTITUTE ______________ SEED TESTING REPORT ______________ (Made under Regulation 38(3)(c)) PRIVATE SAMPLE NO. Date received: TEST NUMBER Lot Number: Weight of lot: Crop and variety: Class of Seeds: Country of origin: RESULT OF ANALYSIS Purity Germination Pure Seeds (P) % Inert matter % Other Seed % Weed Seed % Capacity (G) Hard % Fresh ungerminated Seed % Abnormal Seedslings % Pure germinating Seed P x G 100 % Moisture % % Types of : (1) Inert matte ……………………………………………………………………………………………………………………………………… (2) Other Seed………………………………………………………………………………………………………………………………………… Signature……………………………………. Seeds Analyst Date:…………………………………………… Signature……………………………………. Chief Seed Certification Office 80 THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE AND FOOD SECURITY THE SEEDS ACT, 2003 (No. 18 of 2003) S/N………… Form SR - XIX Registration No. ………… ______________ CEERTIFICATE OF AUTHORISATION AS INSPECTOR/SAMPLER/ANALYST* ______________ ([Made under Regulation 42(4)) This is to certify that……………………………………………………………………… of………………………………...…………………… (Name and address of Registrant ) has been registered and authorized as … ………………………………………………..………………………………………………………. This authorization shall be valid for the period of ……………………from………………………to …………………………and may be cancelled if the registrant fails to comply with terms and conditions for authorisation and the provisions of the Seed Act and Regulations. Issued at ………………………………………this………………..………….….day of ……………….………………….200………. Signature and seal :………………………………………………………….. Chief Seed Certification Officer * delete where not applicable CC: Director 81 __________ SIXTH SCHEDULE __________ FEES FOR SERVICES ____________ (Made under Regulation 40 (1)) ____________ Service Fee in TShs. I. Charges based on the services rendered for each operation: A: Seed field inspection made to determine the eligibility of a crop for pedigree status for each inspection: (1) for hybrid maize per hectare inspected … … … … … … …… 3150 (2) vegetables/pastures, up to one hectare inspected … … … … … 5000 (3) vegetables/pastures, for every exceeding unit above one hectare inspected … 4000 (3) for all other s of Seeds crops, per hectare inspected … … …… … 2150 (4) minimum fee per field where inspected total field is less than 10 hectares,… …. 20,000 B: Seed inspection and sampling: (1) agricultural crops per 100kg or part thereof … … … …… …… … 1,500 (2) vegetable crops per 5 kg … …… … … …… …… …… … 2000 (3) root crops per hectare or part thereof … … … … … … … … 2000 (4) minimum fee for each lot inspected (maximum of 10 tones per lot) … … 10,000 C: Seed testing for germination, purity and moisture: (1). charges for one kg for field crops of pedigree class … … … … … .. ... 15 (2). charges for 100gm for vegetable crops of pedigree class … … … . …. … 20 (3). charges on one kg for standard class Seed… … … . .. …. …. …. …. … 5 (4). charges on one kg of Seed for export … … … . .. … … … . .. …. 20 D: Seed health testing: (1) charges per sample for local market Seed … … … . .. … … … . .. 20,000 (2) charges per sample for export Seed… … … . .. … … … . .. …. … 50,000 F: Certificate and Tags (1) registration of Seed dealer… … … … … … … ... …. …. … 2500 (2) variety registration … … … … … … … ... …. …. ……. … 10,000 (3) certificate of Seed testing … … … … … … … ... …. 1000 (4) certificate for Seed import/ export … … … … … … … … 10,000 (5) certified copy of a Seed testing certificate … … … … … … ….. 500 (6) label /seal per each label /seal … … … … … … …. …. …. ….. .. 500 (7) DUS test certificate… … … … … … … ... …. ….… … 5000 E: Non refundable fees for various application forms (1) Registration as a Seeds dealer… … … … ... …. ….… … … … 2000 (2) DUS test… … … … … … … ... …. ….… … … … 2000 (3) NPT … … … … … … … ... …. ….… … … … … 2000 (4) Seed field inspection… … … … … … … ... …. ….… … 3000 (5) Seed testing (per Seeds lot) … … … ... …. ….… … … … 1000 (6) Seed transport order… … … … … … … ... …. ….… … 2000 (7) Notice to import/export Seed… … … … … … … ... …. … 2000 F: Other charges (1) Conducting DUS test (for two seasons)… … … … ... …. ….… … 500,000 (2) Conducting NPT( for one season)… … … … … ... …. ….… … 600,000 (8) Authorisation / licensing of Seeds sampler or Analyst … … … … 20,000 Note: Fees for inspect, sampling , testing shall apply mutatis mutandis on re- inspection re- sampling or testing. 82 ___________ SEVENTH SCHEDULE ____________ (Made under Regulations 7(4)(a)) ____________ APPROVED TESTING SITES FOR NATIONAL PERFORMANCE TRIAL Crop Type High Altitude Mid Altitude Low Altitude A: Compulsory certification crops Hybrid Maize Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) ,Machame or Marangu AFSF or Selian, Lambo, Gairo, Mbimba, Babati, Laela Msimba or Ilonga, KATRIN, SUA, Maramba or Mwele, Uchira, Nachingwea Sweet Corn Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Miwaleni, Gairo Msimba or Ilonga, KATRIN, Kibaha, SUA, Maramba or Mwele Open Pollinated Maize Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Lambo, Gairo Ukiriguru Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA, Nachingwea Maramba or Mwele Common dry beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Lambo, Gairo, Mbimba Msimba or Ilonga, KATRIN, SUA Snap beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF, Horti-Tengeru Soya beans Dabaga, Njombe, Uyole, Nkundi (Sumbawanga) AFSF or Selian, Horti- Tengeru, Laela (Sumbawanga), Maruku Msimba or Ilonga, KATRIN, Naliendele or Nachingwea, SUA Hybrid sorghum Uyole, Mbozi, Dabaga, Nkundi (Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA Open Pol. s or ghum AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Kibaha, Naliendele, SUA Wheat or Barley Dabaga, Njombe, Uyole, Basuto (Hanang) Nkundi(Sumbawanga) AFSF or Selian, Karatu, West Kilimanjaro Rice (Lowland) Ukiriguru, KATC (Moshi), Mbarali Dakawa, KATRIN, Ruvu, SUA, Kyela, Kitere, Kinyope (Lindi) Mkwaya (Lindi) Rice (Upland) Matombo, Mahenge Kyela,Kitaya Hybrid sunflower Dabaga, Njombe, Uyole, Nkundi(Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Maramba or Mwele Naliendele or Nachingwea, SUA Open pol. Sunflower Dabaga, Njombe, Uyole, Nkundi(Sumbawanga) AFSF or Selian, Miwaleni, Ukiriguru, Hombolo Msimba or Ilonga, KATRIN, Naliendele or Nachingwea SUA, Maramba or Mwele Irish potato Dabaga, Njombe, Uyole, Kifyulilo HORTI-Tengeru, Miwaleni, West Kilimanjaro Groundnuts Ukiriguru, Hombolo, Tumbi (Tabora), Gairo Naliendele or Nachingwea, Ilonga or Msimba, Chambezi, Masasi, Chambezi B:Voluntary certification crops Cassava* Ukiriguru, Hombolo Tumbi (Tabora) HORTI- Tengeru Kibaha, Mlingano, Chambezi, Naliendele or Nachingwea, Masasi, Mtopwa (Newala) Sweet potato Gairo, Hombolo, Miwaleni, Hort Tengeru, Ukiriguru, Tumbi (Tabora) SUA Naliendele or Nachingwea Carrots Dabaga, Njombe, Uyole HORTI-Tengeru, Miwaleni, West Kilimanjaro Green gram AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Tumbi (Tabora) Kibaha, Mlingano, Msimba or Ilonga , Maramba or Mwele Naliendele or Nachingwea, SUA, Msimba or Ilonga 83 Pigeon pea (Long duration) AFSF or Selian, Miwaleni, Ukiriguru, Isimani, Tumbi (Tabora) Hombolo Karatu Msimba or Ilonga, KATRIN, SUA, Masasi Pigeon pea (Mid. & short duration) AFSF or Selian, Miwaleni, Ukiriguru, Isimani, Tumbi (Tabora), Hombolo, Karatu Kibaha, Mlingano, Msimba or Ilonga, Naliendele or Nachingwea, SUA Cowpea AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Ismani, Tumbi (Tabora) Msimba or Ilonga, Naliendele or Nachingwea, SUA, Mlingano or Maramba, Masasi Sesame AFSF or Selian, Miwaleni, Ukiriguru, Hombolo, Kibaha, Mlingano, Msimba or Ilonga, Naliendele or Nachingwea, SUA,Kilwa Tomato Uyole, Dabaga, Njombe Seatondale (Iringa) HORTI-Tengeru, Ukiriguru, Lushoto, Makutop or a Dakawa or SUA, Kibaha, Mlingano, Maramba or Mwele Onion Uyole, Dabaga, Njombe, Seatondale (Iringa) HORTI-Tengeru, Ukiriguru, Mbarali Makutop or a, Karatu Dakawa or SUA, Kibaha, Mlingano, Maramba or Mwele Key to the abbreviations on the table: AFSF = Arusha Faundation Seeds farm SUA = Sokoine University of Agriculture KATC = Kilimanjaro agricultural Training Centre Horti - Tengeru = Horticultural Research Institute Tengeru KATRIN = Kilombero Agricultural Training and Research Institute EXPERIMENTAL DESIGNS AND DATA COLLECTION (a) Experimental design, plot size and number of replications for NPT CROP DESIGN MINIMUM GROSS PLOT SIZE MINIMUM REPLICATIONS ROW LENGTH (Meters) NUMBER OF ROWS Maize RCBD 5 4 3 Dry Beans RCBD 5 4 3 Snap Beans RCBD 5 4 3 S or ghum RCBD 5 4 3 Wheat or Barley RCBD 3 12 3 Rice RCBD 5 20 3 Sunflower RCBD 5 4 3 Irish Potato RCBD 5 4 3 Carrots RCBD 3 6 3 Cassava RCBD 5 4 3 Pigeon Peas RCBD 5 4 3 Cow peas RCBD 5 4 3 Green gram RCBD 5 4 3 Groundnut RCBD 5 4 3 Sweet potato RCBD 5 4 3 Sesame RCBD 5 4 3 Tomato RCBD 6 2 3 Onion RCBD 3 6 3 (b) BASIC INFORMATION ON MANAGEMENT OF NPTs 1. Planting Date 2. Fertilizer rate 3. Weeding regime or herbicide application 4. Plant spacing 5. Pesticides application (if any) 6. Weather (rainfall and temperature) 84 ________ EIGHTH SCHEDULE __________ PROHIBITED, RESTRICTED AND NOXIOUS WEED SEEDS __________ (Made under Regulation 48) The seed of the species of plants specified in this Schedule are hereby prescribed as weed seed for the purpose of establishing class standards under the Act. Class 1: Objectionable Weed Seed Objectionable weed seeds are weed seed not allowed in any seed at all, that is to say, a sample of seed may not contain any objectionable weed seed. However, if any objectionable weed seed is found in a sample, the tolerance shall be one seed per kilogram. If two or more seed are found in a kilogram the seed shall be placed under stop sale until it has been re-cleaned and retested. When one objectionable weed seed is found it will be considered within the tolerance none. The following are objectionable weed seed:- 1. Witch weed………………………………………………. Striga spp 2. Dodder…………………………………………………… Cascuta spp 3. Field bind wood…………………………………………. Convolvus arvensis L. 4. Hemp………………………………………… ….. ……. Marijuana spp. 5. True Hemp (in Swahili Bhangi) ………………… ……. Cannabis Sativa 6. Cocaine plant …………………………………… …….. Erythrosylum spp. 7. Sudan grass……………………………………… ……. Sorghum sudanese 8. Thorn apple…………………………………… ……….. Datura spramondum L. 9. Wild oats …………………………………………. …… Avena spp. Class 2: Restricted Noxious Weed Seed The following are restricted noxious weed seed:- 1. Couch grass …………………………………………… Digitaria scalarum (Schweinf.) Chiov. 2. Nutgrass, Watergrass…………………………………. Cyperus spp. 3. Perennial sowthistle…………………………………. Sonchus arvensis L. 4. Wild mustard…………………………………. . …… Brassica campestris L 5. Mexican poppy …………………………………. ….. Argemone mexicana L. 6. Darnel…………………………………. …………… Lolium temulentum L. 7. Guinea-fowl grass……………………………………. Rottboelia exaltata L.f. 8. Love grass …………………………………. ……… Setaria verticiltata (L.) Beauv. 9. Wild rice …………………………………. ………… Oryza barthii A. Chev. The presence of restricted noxious weed seed in any sample of seed shall be restricted. Where any restricted noxious weed seed are found in any sample of seed the maximum allowed shall not exceed four weed seed per kilogram, whether the four weed seed are of the same or a combination of two or more s of weed seed, the name and number of each must be stated on the label. Class 3: Common Noxious Weed Seed. Common Noxious Weed Seed are seed bulblets or tubers or pieces thereof specified as weed seed under the Seed, Regulations 2006 or recognized as weed seed by general usage. The presence of standard noxious weed seed in any sample of seed shall be restricted. Where any standard noxious weed Seed are found in any sample of seed the maximum allowed shall not exceed 1.5% by weight. Common noxious weed seed include, but not restricted to, the following seed:- 1. Cleavers…………………………………………… Galium spurium L. 2. Dock …………………………………. …………. Ramex crispus L. 3 Chickweed …………………………………. …… Stellaria media (L.) Vill. 4. Mexican marigold …………………………………. Tagetes minuta L. 5. Chinese lantern …………………………………… Nicandra physalodes (L.) Gaertn. 6. Oxalis ………………………………….………… Oxalis latifolia H.B.K. 7. Blackjack ………………………………….……… Bidens pilosa L. 8. Pigweed…………………………………. ………. Amaranthus spp.. 9. Goosefoot…………………………………. …….. Chenopodium spp. 10. Crabgrass………………………………………… Digitaria velutina (Forsk.) Beauv. 11. Macdonaldi, Gallant soldier …………………….. Galinsoga paarviflora. Cav. Dar Es Salaam, STEPHEN M. WASIRA (MP) ………, 2007 Minister for Agriculture Food Security and Cooperatives 85 | false |
# Extracted Content SOURCES OF FUNDS DASIP BENEFICIARY BARIADI SOMANDA NYAUMATA Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 DUTWA MWAMONDI Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 SAPIWI NYAMIKOMA Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 MWAMAPALALA ISAKANG'HWALE Construction of 3 shallow wells for irrigation. 15,000 12,000 3,000 MHANGO NGALLA Rehabilitation of rural feeder roads 16,324 13,059 3,265 BUNAMHALA BUNAMHALA Construction of a market shed. 25,000 20,000 5,000 LUGURU NHOBOLA Rehabilitation of rural feeder roads 19,290 15,432 3,858 NKOLOLO MWASHAGATA Rehabilitation of a cattle dip. 15,000 12,000 3,000 SAKWE IBULYU Rehabilitation of a cattle dip. 15,000 12,000 3,000 MWASWALE LUG'WA Construction of a crop storage structure. 35,000 28,000 7,000 NKUYU Purchase of Oxen drawn implements 10,000 5,000 5,000 BUNAMHALA GIRIKU Construction of a cattle dip. 27,500 22,000 5,500 MWAUBINGI GASUMA Construction of a cattle dip. 27,500 22,000 5,500 MWADOBANA KILABELA Construction of a cattle dip. 27,500 22,000 5,500 LAGANGABILILI NG'HESHA Construction of a cattle dip. 27,500 22,000 5,500 305,614 241,491 64,123 BUKOMBE IYOGELO BUGELANGA Rehabilitation of rural feeder roads 26,000 20,800 5,200 USHIROMBO NGANZO Construction of a crop storage facility 33,200 26,560 6,640 Nyitundu Construction of a crop storage facility 33,200 26,560 6,640 92,400 73,920 18,480 KAHAMA MPUNZE IPONYAHOLO Construction of a crop storage structure. 28,180 22,544 5,636 Procurement of hulling machine 5,500 2,750 2,750 SABASABINI Procurement of hulling machine 5,500 2,750 2,750 KINAMAPULA BUNASANI Construction of a crop storage structure. 28,180 22,544 5,636 BUTIBU Procurement of hulling machine 5,500 2,750 2,750 NGONGWA NGULU Construction of a crop storage structure. 28,180 22,544 5,636 ISAGEHE MONDO Construction of a crop storage structure. 28,180 22,544 5,636 MWANDEKULIMA KISUKE Procurement of hulling machine 5,500 2,750 2,750 TOTAL BARIADI DISTRICT TOTAL BUKOMBE DISTRICT SHINYANGA REGION DISTRICT WARD VILLAGE NAME OF PROJECT TOTAL COST (in '000) DISTRICT AGRICULTURAL SECTOR INVESTMENT PROJECT (DASIP) ALLOCATION OF INVESTMENT FUNDS - 1st QRT 2008/09 KAGERA , SHINYANGA, MARA, KIGOMA AND MWANZA REGIONS BUGARAMA BUYANGE Procurement of hulling machine 5,500 2,750 2,750 UKUNE IGUNDA Rehabilitation of a cattle dip. 8,890 7,112 1,778 KUNDIKILI Construction of a charco dam. 28,536 22,829 5,707 KINAGU MWAKUHENGA Construction of a charco dam. 28,536 22,829 5,707 MALUNGA KITWANA Construction of a charco dam. 28,536 22,829 5,707 MHONGOLO NYASHIMBI Construction of a charco dam. 28,536 22,829 5,707 KILANGO WAME Construction of a charco dam. 28,536 22,829 5,707 291,790 225,182 66,608 KISHAPU MONDO MWIGUMBI Construction of a crop storage structure. 35,000 28,000 7,000 KABILA Procurement of a grain milling machine 10,000 5,000 5,000 SHAGIHILU MWALATA Construction of a charco dam. 35,000 28,000 7,000 TALAGA KIJONGO Construction of a charco dam. 35,000 28,000 7,000 LAGANA LAGANA Construction of a charco dam. 35,000 28,000 7,000 UKENYENGE BULIMBA Procurement of an agric processing machine 10,000 5,000 5,000 SONGWA MPUMBULA Construction of a cattle dip. 25,457 20,366 5,091 185,457 142,366 43,091 MASWA DAKAMA MWANDETE Construction of a cattle dip. 26,000 20,800 5,200 BUSILILI BUHUNGUKILA Construction of a crop storage facility 28,800 23,040 5,760 MPINDO SENANI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 Construction of 2 shallow wells for irrigation. 12,000 9,600 2,400 NGULIGULI MWASHEGESHI Construction of a crop storage facility 4,000 3,200 800 MALAMPAKA NYABUBINZA Procurement of rice hulling(grain milling) machine. 5,000 2,500 2,500 SUKUMA MWABAYANDA (m) Procurement of a ground nut sheller. 4,000 2,000 2,000 Construction of a shallow well for irrigation. 4,800 3,840 960 KULIMI MWABAYANDA (s) Construction of a shallow well for irrigation. 4,800 3,840 960 Construction of a crop storage facility 4,000 3,200 800 BADI IKUNGU Construction of a crop storage facility 4,000 3,200 800 NYASHIMBA Rehabilitation of a cattle dip. 15,000 12,000 3,000 Construction of a crop storage facility 4,000 3,200 800 ISANGA ISANGA Procurement of 2 ground nut shellers. 8,000 4,000 4,000 SHISHIYU IGUNYA Procurement of a paddy processing machine. 10,000 5,000 5,000 NYABUBINZA MWABAGALU Procurement of 20 oxen weeders 8,000 4,000 4,000 Construction of a shallow well for irrigation. 4,800 3,840 960 MASELA MANDELA Procurement of an oil processing machine. 5,000 2,500 2,500 Construction of a shallow well for irrigation. 4,800 3,840 960 TOTAL KAHAMA DISTRICT TOTAL KISHAPU DISTRICT 167,000 118,600 48,400 MEATU NG'HOBOKO MINYANDA/MWAFUGULI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 ITINJE ISENGWA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 LUBIGA LUBIGA Construction of a cattle dip. 35,000 28,000 7,000 MWAMALOLE USIULIZE Construction of a cattle dip. 35,000 28,000 7,000 MWAMANONGU MWAMANONGU Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 KIMALI PAJI Construction of a crop storage facility 35,000 28,000 7,000 KISESA KISESA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 SAKASAKA SAKASAKA Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 MWAMISHALI MWAMBITI Procurement of rice hulling(grain milling) machine. 10,000 5,000 5,000 165,000 114,000 51,000 SHINYANGA SAMUYE NG'WANG'HALANGA Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 MWANTINI JIMONDOLL Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 IMESELA MWAMANYUDA Rehabilitation of irrigation infrastructure. 35,000 28,000 7,000 ITWANGI NYIDA Construction of a crop storage facility 35,000 28,000 7,000 MWAMALA BUGOGO Construction of a crop storage facility 35,000 28,000 7,000 TINDE WELEZO Construction of a crop storage facility 35,000 28,000 7,000 210,000 168,000 42,000 1,417,261 1,083,559 333,702 TOTAL SHINYANGA REGION TOTAL MASWA DISTRICT TOTAL MEATU DISTRICT TOTAL SHINYANGA DISTRICT | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vq: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 ACRONYMS i TABLE OF CONTENTS Table of contents........................................................................................................................................................... i Acronyms..................................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive summary.................................................................................................................................................... vii Illustrations................................................................................................................................................................. xii ENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION .................................................................................................... 1 1.1 Introduction.................................................................................................................................................. 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area..................................................................................................................................................... 1 1.4 Climate.......................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Population..................................................................................................................................................... 1 1.6 Socio-economic Indicators........................................................................................................................... 2 PART II: INTRODUCTION.................................................................................................................................. 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture........................................... 3 2.2 Census Objectives ........................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................ 4 2.4 Legal Authority of the National Sample Census of Agriculture.............................................................. 5 2.5 Reference Period.......................................................................................................................................... 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 5 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 7 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparations.............................................................................................. 9 - Data Quality............................................................................................................................. 10 2.7 Funding Arrangements........................................................................................................................ 10 PART III: CENSUS RESULTS AND ANALYSIS .............................................................................................. 11 3.1 Household Characteristics ........................................................................................................................ 11 3.1.1 Type of Household ........................................................................................................................ 11 3.1.2 Livelihood Activities/Source of Income........................................................................................ 11 3.1.3 Sex and Age of Heads of Households ........................................................................................... 11 3.1.4 Number and age of Household Members ...................................................................................... 15 3.1.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 - Literacy Rates for Heads of Households.................................................................................. 15 - Educational Status.................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................ 16 ACRONYMS ii 3.2 Land Use ................................................................................................................................................. 17 3.2.1 Area of Land Utilised .................................................................................................................... 17 3.2.2 Types of Land use.......................................................................................................................... 18 3.3 Annual Crops and Vegetable Production ................................................................................................ 18 3.3.1 Area Planted .................................................................................................................................. 18 3.3.2 Crop Importance............................................................................................................................ 20 3.3.3 Crop Types .................................................................................................................................... 20 3.3.4 Cereal Crop Production ................................................................................................................. 22 3.3.4.1 Maize ........................................................................................................................... 23 3.3.4.2 Paddy ........................................................................................................................... 23 3.3.4.3 Sorghum....................................................................................................................... 26 3.3.4.4 Other Cereals .................................................................................................................... 3.3.5 Roots and Tuber Crops Production................................................................................................ 26 3.3.5.1 Cassava........................................................................................................................ 27 3.3.5.2 Sweet Potatoes............................................................................................................. 28 3.3.6 Pulse Crops Production ................................................................................................................. 28 3.3.6.1 Chick Peas ................................................................................................................... 30 3.3.7 Oil Seed Production....................................................................................................................... 32 3.3.7.1 Groundnuts .................................................................................................................. 32 3.3.8 Fruits and Vegetables ..................................................................................................................... 33 3.3.8.1 Tomatoes ..................................................................................................................... 35 3.3.8.2 Onions.......................................................................................................................... 37 3.3.9 Other Annual Crops Production .................................................................................................... 40 3.3.9.1 Cotton ........................................................................................................................... 40 3.3.9.2 Tobacco ....................................................................................................................... 40 3.4 Permanent Crops....................................................................................................................................... 40 3.4.1 Mango ..................................................................................................................................... 43 3.5 Inputs/Implements Use.............................................................................................................................. 48 3.5.1 Methods of Land Clearing.............................................................................................................. 48 3.5.2 Methods of Soil Preparation.......................................................................................................... 48 3.5.3 Improved Seeds Use...................................................................................................................... 50 3.5.4 Fertilizers Use................................................................................................................................ 51 3.5.4.1 Farm Yard Manure Use ............................................................................................... 51 3.5.4.2 Inorganic Fertilizer Use ............................................................................................... 52 3.5.4.3 Compost Use................................................................................................................ 53 3.5.5 Pesticide Use ................................................................................................................................. 54 3.5.5.1 Insecticide Use............................................................................................................. 54 3.5.5.2 Herbicide Use .............................................................................................................. 55 3.5.5.3 Fungicide Use.............................................................................................................. 55 3.5.6 Harvesting Methods....................................................................................................................... 56 3.5.7 Threshing Methods ....................................................................................................................... 56 3.6 Irrigation ................................................................................................................................................. 56 3.6.1 Area Planted with Annual Crops and Under Irrigation.................................................................. 56 3.6.2 Sources of Water Used for Irrigation............................................................................................. 57 3.6.3 Methods of obtaining water for irrigation...................................................................................... 59 3.6.4 Methods of Water Application ..................................................................................................... 59 ACRONYMS iii 3.7 Crop Storage, Processing and Marketing................................................................................................ 59 3.7.1 Crop Storage.................................................................................................................................. 59 3.7.1.1 Method of Storage ....................................................................................................... 60 3.7.1.2 Duration of Storage...................................................................................................... 60 3.7.1.3 Purpose of Storage....................................................................................................... 62 3.7.1.4 The Magnitude of Storage Loss................................................................................... 62 3.7.2 Agro processing and By-products .................................................................................................. 63 3.7.2.1 Processing Methods..................................................................................................... 63 3.7.2.2 Main Agro-processing Products .................................................................................. 63 3.7.2.3 Main use of primary processed Products..................................................................... 64 3.7.2.4 Outlet for Sale of Processed Products.......................................................................... 64 3.7.3 Crop Marketing ............................................................................................................................. 65 3.7.3.1 Main Marketing Problems ........................................................................................... 65 3.7.3.2 Reasons for Not Selling............................................................................................... 65 3.8 Access to Crop Production Services......................................................................................................... 66 3.8.1 Access to Agricultural Credits....................................................................................................... 66 3.8.1.1 Source of Agricultural Credits..................................................................................... 66 3.8.1.2 Use of Agricultural Credits.......................................................................................... 66 3.8.1.3 Reasons for not using agricultural credits.................................................................... 67 3.8.2 Crop Extension .............................................................................................................................. 67 3.8.2.1 Sources of Crop Extension Messages.......................................................................... 67 3.8.2.2 Quality of Extension.................................................................................................... 69 3.9 Access to Inputs .......................................................................................................................................... 69 3.9.2 Inorganic Fertilizers ....................................................................................................................... 69 3.9.3 Improved Seeds .............................................................................................................................. 70 3.9.4 Insecticides and Fungicide.............................................................................................................. 70 3.10 Tree Planting............................................................................................................................................... 71 3.11 Irrigation and Erosion Control Facilities ............................................................................................... 72 3.12 Livestock Results........................................................................................................................................ 74 3.12.1 Cattle Production ........................................................................................................................... 74 3.12.1.1 Cattle Population ......................................................................................................... 74 3.12.1.2 Herd size...................................................................................................................... 74 3.12.1.3 Cattle Population Trend............................................................................................... 76 3.12.1.4 Improved Cattle Breeds ............................................................................................... 76 3.12.2 Goat Production............................................................................................................................. 76 3.12.2.1 Goat Population ........................................................................................................... 76 3.12.2.2 Goat Herd Size............................................................................................................. 78 3.12.2.3 Goat Breeds ................................................................................................................. 78 3.12.2.4 Goat Population Trend................................................................................................. 78 3.12.3 Sheep Production........................................................................................................................... 78 3.12.3.1 Sheep Population ......................................................................................................... 78 3.12.3.2 Sheep Population Trend............................................................................................... 80 3.12.4 Pig Production ............................................................................................................................... 80 3.12.4.1 Pig Population Trend ................................................................................................... 80 ACRONYMS iv 3.12.5 Chicken Production ....................................................................................................................... 82 3.12.5.1 Chicken Population...................................................................................................... 82 3.12.5.2 Chicken Population Trend ........................................................................................... 82 3.12.5.3 Chicken Flock Size...................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers) .......................................................... 84 3.12.6 Other Livestock ............................................................................................................................. 84 3.12.7 Pests and Parasites Incidences and Control ................................................................................... 84 3.12.7.1 Deworming .................................................................................................................. 86 3.12.8 Access to Livestock Services......................................................................................................... 86 3.12.8.1 Access to livestock extension Services........................................................................ 86 3.12.8.2 Access to Veterinary Clinic......................................................................................... 86 3.12.8.3 Access to village watering points/dam ........................................................................ 87 3.12.9 Animal Contribution to Crop Production ...................................................................................... 87 3.12.9.1 Use of Draft Power ...................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure........................................................................................... 88 3.12.9.3 Use of Compost ......................................................................................................... 88 3.12.10 Fish Farming.................................................................................................................................. 88 3.13 Poverty Indicators...................................................................................................................................... 91 3.13.1 Access to Infrastructure and Other Services.................................................................................. 91 3.13.2 Type of Toilets .............................................................................................................................. 91 3.13.3 Household’s Assets........................................................................................................................ 91 3.13.4 Sources of Light for Energy .......................................................................................................... 91 3.13.5 Sources of Energy for Cooking ..................................................................................................... 91 3.13.6 Roofing Materials.......................................................................................................................... 94 3.13.7 Access to Drink Water................................................................................................................... 94 3.13.8 Food Consumption Pattern ............................................................................................................ 95 3.13.8.1 Number of Meals per Day ........................................................................................... 95 3.13.8.2 Meat Consumption Frequencies .................................................................................. 95 3.13.8.3 Fish Consumption Frequencies.................................................................................... 95 3.13.9 Food Security................................................................................................................................. 97 3.13.10 Main Source of Cash Income ........................................................................................................ 97 PART IV: SHINYANGA PROFILES.................................................................................................................... 99 4.1 Region Profile.............................................................................................................................................. 99 4.2 District Profiles ......................................................................................................................................... 100 4.2.1 Bariadi .......................................................................................................................................... 100 4.2.2. Maswa .......................................................................................................................................... 102 4.2.3 Shinyanga Rural ........................................................................................................................... 104 4.2.4 Kahama......................................................................................................................................... 104 4.2.5 Bukombe....................................................................................................................................... 106 4.2.6 Meatu............................................................................................................................................ 108 4.2.7 Shinyanga Urban .......................................................................................................................... 110 4.2.8 Kishapu......................................................................................................................................... 111 ACRONYMS v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Wety Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Dry Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics, Tanzania Mainland and the Office of the Chief Government Statistician, Tanzania Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the President’s Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (data on household characteristics and livestock count were collected in 1993/1994 while data on crop area and production were collected in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Shinyanga region data disaggregated to district level. Due to numerous variables collected, the analysis is based on the most important smallholder variables. More variables can be found in the table of results annex. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Special thanks should go to all those who in one-way or the other contributed to the success of the survey. In particular, I would like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician, Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Finally, let me extend my sincere gratitude to all professional staff of the National Bureau of Statistics and Office of the Chief Government Statistician, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. I am also indepted to the respondents, particularly the heads of households, for spending much of their valuable time in providing data and all necessary information during enumeration. Certainly without their dedication, the census would not have been successful. Albina A. Chuwa Director General, National Bureau of Statistics EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Shinyanga region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Shinyanga region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Shinyanga region were 377,857 out of which 201,316 (53%) were involved in growing crops only, 2,310 (1%) rearing livestock only and 174,232 (46%) were involved in crop production as well as livestock keeping. In summary, Shinyanga region had 375,547 households involved in crop production and 176,542 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances. The region has a literacy rate of 59 percent. The highest literacy rate is in District Kishapu (65%), Shinyanga Urban (64%), Maswa (61%), Bukombe (60%), Shinyanga Rural (60%) and Meatu (60%). Kahama na Baridi districts have the lowest literacy rates of 59 and 56 percent Respectively. The literacy rate for the heads of households in the region was 59 percent. The number of heads of agricultural households with formal education in Shinyanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Shinyanga region 113,528 household members (59%) were involved in one off-farm income generating activity, 50,868 (26%) involved in two off-farm income generating activities and 28,310 (15%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 1,299,023 ha. The regional average land area utilised for crop production per crop growing household was only 3.4 ha. This figure is above the national average of 2.0 hectares. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ viii Planted Area The area planted with annual crops and vegetables was 960,250 hectares out of which 2,826 hectares (0.29%) were planted during Dry season and 957,423 hectares (99.71%) during Wety season. An estimated area of 591,416 ha (60% of the total planted area with annual and vegetable crops) was with cereals, followed by 67,809 hectares (7%) of pulses, 66,153 ha (7%) of oil seeds and nuts, 48,081 ha (5%) of roots and tubers, 1,421 ha (0.1%) of fruit and vegetables, 205,020 ha (21%) of cash crops. Maize Maize is the dominant annual crop grown in Shinyanga region and it had a planted area 3.4 times greater than Paddy, which had the second largest planted area. The area planted with maize constitutes 68 percent of the total area planted with annual food crops. Other crops in order of their importance (based on area planted) are Cotton, Paddy, Sorghum, Ground nuts, Beans, cassava, cowpeas, tomatoes, green gram, groundnuts and sweet potatoes. There was a decrease in maize production over the period 1995 to 1996 (52%), after which the production almost remained constant over the period 1996 to 97. Production gradually increased over the period 1997 to 1998 and remained constant over the period from 1998 to 1999 and thereafter declined over the period 1999 to 2003. The average area planted with maize per household was 1.06 hectares; however it ranged from 0.7 hectares in Shinyanga Urban district to 1.31 hectares in Bariadi district. Bariadi had the largest planted area of maize (101,952 ha) followed by Kahama (79,905 ha), Bukombe (64,833 ha), Shinyanga Rural (44,228 ha) , Maswa (35,159), Meatu (31,192) and Shinyanga Urban (7,505 ha) Paddy Paddy is the Second dominant cereal crop in terms of production in the region. The number of households growing Paddy in Shinyanga region during the wet season was 136,046 (36% of the total crop growing households in the region during the wet season). The total production of Paddy was 104,847 tonnes from a planted area of 118,916 hectares resulting in a yield of 0.88 t/ha • Sorghum Sorghum is the third most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Shinyanga region during the wet season was 59,619. This represents 16 percent of the total crop growing households in Shinyanga region. The total production of sorghum was 17,286 tonnes from a planted area of 65,868 hectares resulting in a yield of 0.26 t/ha. The district with the largest planted area of sorghum was Meatu (24,353 ha) followed by Kishapu (21,030 ha), Bariadi (9,971 ha) and Maswa (7,950 ha) (Map 3.15). The Largest planted area per household for sorghum was observed in Meatu (0.77 ha) and Kishapu (0.59 ha). There was a large reduction in the production of sorghum from 114,000 tonnes in 1995/96 to 17,000 tonnes in 2002/03 EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ ix • Roots and Tuber Crops Production The Common Roots and Tuber Crops grown in Shinyanga Region were Sweet Potatoes and Cassava. The total production of both Cassava and Sweet Potatoes was 39,658 tonnes. Sweet Potatoes production was higher than that of Cassava in the region with a total production of 25,059 tonnes representing 63 percent of the total root and tuber crop production • Pulse Crops Production The total area planted with pulses was 66,153 hectares, of which 23,933ha were planted with Chick Peas (36% of the total area planted with pulses), followed by Beans (16,396 ha, 25%), Cow Peas (3,376 ha, 5%), Green Gram (2,898ha 4%) and Bambaranuts (1,382 ha, 2%). • Oil Seed Production The total production of oilseed crops was 31,568 tonnes, planted on an area of 65,985 hectares. Groundnuts was the most important oilseed crop with 64,188 ha (97% of the total area planted with oil seeds), followed by sunflower (2%) and simsim (1%). Fruit and Vegetables The total production of vegetables was 3,381 tonnes. The most cultivated vegetable crop was tomatoes with a production of 1,977 tonnes (58% of the total vegetables produced) followed by onions (503t, 15%) and Cabbages (461t, 14%). The production of the other vegetable crops was relatively small. Permanent Crops The planted area of smallholders with permanent crops was 53,420 hectares (5.2% of the area planted with annual and permanent crops in the region). The most important permanent crop in Shinyanga region is Mango which accounts for a planted area of 28,067.0 ha, (53% of the planted area of all permanent crops) followed by Pawpaw (6,337 ha, 12%), Sisal (5,719 ha, 11%), and Banana (3,763 ha, 11%). • Improved Seeds Use The planted area with improved seeds was 261,066 ha which represents 27 percent of the total area planted with the annual crops and vegetables. Cash Crops had the largest planted area with improved seeds (159,104 ha, 69% of the planted area with improved seeds) followed by Cereals crops (57,738 ha, 25%). Other crop types had insignificant area planted with improved seeds (Chart 3.42). Among the Cash Crops Cotton had the largest area of improved seeds application which was 155,842 ha 98% of area planted by cash crops. • Fertilizer Use The use of fertilisers on annual crops was very small with a planted area of only 171,943 ha (18% of the total planted area in the region). The planted area without fertiliser for annual crops was 785,481 hectares representing 82 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 137,161 ha which represents 14 percent of the total planted area (80% of the area planted with fertiliser application in the region). This was followed by Inorganic Fertilizers (20,380ha, 12% of the planted area with fertiliser and 2% of the total EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ x planted area in the region), Compost (14,404ha, 8% of the planted area with fertiliser and 2% of the total planted area in the region). The largest planted area with fertiliser (all types) was in Kahama district (60154 ha, 35.0% of the total planted area with fertilizer in the region, followed by Bariadi (27,350, 16%), Shinyanga Rural (20,901 12%), Bukombe (20,582 12%), Maswa (14,692 9%), Kishapu (14,010 8%) and Shinyanga Urban (4,188, 2%) Table 3.8 and (Charts 3.60 and 3.61). Irrigation The district with the highest proportion of area under irrigation with annual crops was Shinyanga Urban 5.5 percent of the planted area with annual crops in the District. This is followed by Kahama (3.2%), Shinyanga Rural (3.1%), Bariadi (2.7%) and Kishapu 2.1%. Other Districts had lower than 2% of the proportion of area under Irrigation Crop Storage The most important stored crop was maize with 284,899 households storing 101,693 tonnes as of 1st January 2004. This was followed by Paddy (112,839 households, 55,481t), Groundnuts/Bambaranuts (63,962 households, 10,223t) and Beans/Pulses (50,197 households, 5,247t). Other crops were stored in very small amounts Crop Marketing The number of households that reported selling crops was 219,317 which represents 58 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Maswa (79%) followed by Bariadi (66%), Meatu (59%), Kahama (59%), Bukombe (54%), Kishapu (59%), Shinyanga Rural (44%) and Shinyanga Urban (8%) (Chart 3.99 and Map 3.40). Agricultural Credit The census results shows that very few agricultural households (7,054, 2%) in Shinyanga region accessed credit, of which 5,402 (77%) were male-headed households and 1,651 (24%) were female headed households. The number of those who accessed credits was higher in Bariadi (31%) followed by Kahama (31%), Bukombe (12%) and Maswa (12%). Other Districts have less than 10% of those who accessed credits, ( Crop Extension Services The number of agricultural households that received crop extension was 104,252 (28% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Kishapu having a relatively high proportion of households that received crop extension messages (51%) followed by Meatu (47%), Kahama (36%), Shinyanga Urban (33%), Shinyanga Rural (27%), Bariadi (21%), and Bukombe (14%. Soil Erosion and Water Harvesting Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms in Shinyanga region was 15,199 which represent 4 percent of the total number of agricultural households in the region EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xi iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 2,604,105 which the largest population of Livestock in the Country regional wise. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 15.4 percent of the total cattle population on Tanzania Mainland. The number of indigenous cattle in Shinyanga region was 2,591,532 (92.6 % of the total number of cattle in the region), 1,375 cattle (0.1%) were dairy breeds and 11,198 cattle (7.3%) were beef breeds. Goats Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Shinyanga region ranked 11 out of the 21 regions with 4.4 percent of the total goats on the Mainland. The number of goat-rearing-households in Shinyanga region was 124,019 (33% of all agricultural households in the region) with a total of 1,277,929 goats giving an average of 10 head of goats per goat- rearing-household. Sheep Sheep rearing was the third important livestock keeping activity in Shinyanga region after cattle and goats. The region ranked 9 out of 21 Mainland regions and had 4 percent of all sheep on Tanzania Mainland. The number of sheep-rearing households was 58,545 (15% of all agricultural households in Shinyanga region) rearing 517,144 sheep, giving an average of 9 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 656 (0.2% of the total agricultural households) rearing about 3,266 pigs. This gives an average of 5 pigs per pig-rearing household. • Chicken The number of households keeping chicken was 257,044 raising about 2,979,590 chickens. This gives an average of 12 chickens per chicken-rearing household. In terms of total number of chickens in the country, Shinyanga region was ranked first for having the largest number of chicken out of the 21 Mainland regions. Use of Draft Power Use of draft animals to cultivate land in Shinyanga region is highly practiced with a total 246,196 (65%) agricultural households Practicing it. Kishapu, Shinyanga Rural and Bariadi Districts are the best in use of draft animals in farming practices with over 80% of all agricultural households in these districts using the method. The Percent of Agricultural households using this method in Maswa, Meatu and Shinyanga Urban was 79%, 78% and 86% respectively. The method is scarcely practiced in Kahama and Bukombe Districts. Fish Farming The number of households involved in fish farming in Shinyanga region was very small which was 430, representing 0.1 percent of the total agricultural households in the region. This Practice was only reported in Kahama District. EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xii iv) Poverty Indicators • Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were Tarmac Road (68), Hospital (41), District Capital (39, Tertiary Market (34) Secondary School (19) Secondary Market (17), Primary Market (8), Health Clinic / Dispensary (8), All weather Road (7), Primary School (2), Feeder Road (2) Availability of Toilets A large number of rural agricultural households use traditional pit latrines (318,745 households, 84% of all rural agricultural households) 12,686 households (3%) use Flush Toilets and 2,450 households (1%) use Improved Pit Latrine. The remaining 474 household (0.13%) use other toilets facilities. However, 12,686 households (12%) in the region had no toilet facilities. Household Assets Bicycles are owned by most rural agricultural households in Shinyanga region with 246,531 households (65% of the agriculture households in the region) owning the asset. followed by Radios ( 192,251 households, 51%), iron (64,449 households, 17%), wheelbarrow (39,393 households, 10%), mobile phone (5,725 households, 2%), television/video (3,692 households, 0.96), vehicle (4,236 households, 1.1%) and landline phone (858 households, 0.23%) (Chart 3.152). • Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 81 percent of the total rural households using this source of energy followed by hurricane lamp (14%), Pressure lamp (3%), Firewood and Electricity (1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95 percent of all rural agricultural households in Shinyanga region. This is followed by charcoal (4%). The rest of energy sources accounted for 1 percent. These were bottled gas (0.05%), crop residues (0.64%), mains electricity (0.15%), livestock dung (0.26%), paraffin/kerosene (0.1%) and gas/biogas (0.05%) Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 35 percent of the rural agricultural households. This was closely followed by iron sheets (33%) and grass/mud (30%). Tiles (0.54%), (0.28%) and Concrete (0.06%) roofing style were scarcely used in the region. • Access to Drinking Water The main source of drinking water for rural agricultural households in Shinyanga region was unprotected Wells (33 percent of households use unprotected wells during the wet season and 31 percent of the households during the dry seasons). This is followed by protected wells (26% and 28% of households for wet and dry seasons respectively), Surface water (16% of households during the wet season and 19% in the dry season), Piped water (12% of households in the wet season and 13% EXECUTIVE SUMMARY ________________________________________________________________________________________________________________________ xiii during dry season). Other sources of drinking water like uncovered rain water catchments, Unprotected/protected Spring, Bottled Water, Water vendor and Tank truck are scarcely used in the region Number of Meals per Day The majority of households in Shinyanga region normally have 3 meals per day (54 percent of the households in the region). This is followed by 2 meals per day (44 percent) and 1 meal per day (2 percent). A small number of Agricultural Households 0.27 percent normally have 4 meals per day. • Food Security In Shinyanga region, 134,001 households (35% of the total agricultural households in the region) said they seldom experienced problems in satisfying the household food requirement. However 55,062 (14%) said they often experience problems, 38,789 always experienced problems and 6.4 percent sometimes had problems in satisfying the household food requirement. About 33 percent of the agricultural households said they did not experience any food sufficiency problems. Main Source of Cash Income The main cash income of the households in Shinyanga region was from selling food crops (39.2 percent of smallholder households), followed by Sales of Cash Crops (31.8), Casual Cash earnings 13%), businesses income and Sales of Livestock each 4.9%. Other Means of income were Wages and Salaries (2.1%), Cash Remittances (1.1%), Sales of Forestry Products (1%), Sales of Livestock Products (1%) a and cash remittances (1%) and Fishing (1%)., ILLUSTRATIONS ________________________________________________________________________________________________________________________ xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size........................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season.................................................................................... 22 3.3 Area, Production and Yield of Root and Tuber Crops by Season.................................................................... 27 3.4 Area, Production and Yield of Pulse by Season .............................................................................................. 28 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season ................................................................. 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season..................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season........................................................................ 37 3.8 Land Clearing Methods.................................................................................................................................... 48 3.9 Planted Area by Type of Fertiliser Use and District – Long and Dry Season.................................................. 51 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Wety Season ................................................................................................................................... 51 3.11 Number of Households Storing Crops by Estimated Storage Loss and District.............................................. 62 3.12 Reasons for Not Selling Crop Produce ............................................................................................................ 65 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 66 3.14 Access to Inputs............................................................................................................................................... 69 3.15 Number of Households and Chickens Raised by Flock Size............................................................................82 3.16 Number of Other Livestock by Type of Livestock and District....................................................................... 84 3.17 Mean distances from dwellings to infrastructure and services by districts...................................................... 91 3.18 Number of Households by Number of meals the Household normally takes per Day and District................. 95 List of Charts 3.1 Agricultural Households by Type of Holdings ................................................................................................ 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ........................................... 11 3.3 Percentage Distribution of Population by Age and Sex in 2003...................................................................... 15 3.4 Percentage Literacy Level of Household Members by District ....................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District............................................................................ 15 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status ................................................................................................. 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment .................................................. 16 3.9 Number of Households by number of members with Off Farm Income – Shinyanga Region ........................ 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ................................ 17 3.11 Utilized and Usable Land per Household by District ...................................................................................... 17 3.12 Land Area by Type of Land Use...................................................................................................................... 18 3.13 Area Planted with Annual Crops (ha) by Season............................................................................................. 18 3.14 Area Planted with Annual Crops by Season and Region................................................................................. 18 3.15 Area Planted with Annual Crops per Household by Season and District ........................................................ 20 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................. 20 3.17a Planted Area per Household by Selected Crops................................................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type.................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season...................................................................... 22 3.19 Area Planted and Yield of Major Cereal Crops ............................................................................................... 22 3.20 Time Series Data on Maize Production – Shinyanga Region .......................................................................... 23 3.21 Maize: Total Area Planted and Planted Area per Household by District......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Shinyanga Region................................................................ 23 3.23 Total Planted Area and Area of Paddy per Household by District................................................................... 26 3.24 Time Series Data on Paddy Production – Shinyanga Region .......................................................................... 26 3.25 Time Series of Paddy Planted Area and Yield – Shinyanga Region................................................................ 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District ................................................................. 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................. 26 3.28 Area planted with Cassava during the census/survey years..............................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District ....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District.............................................................. 28 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xiii 3.31 Total Area Planted and Planted Area per Household by District..................................................................... 28 3.32 Area Planted and Yield of Major Pulse Crops................................................................................................. 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ........................................... 30 3.34 Area Planted per Bean Growing Household by District (Wety Season Only)................................................. 30 3.35 Time Series Data on Bean Production – Shinyanga Region............................................................................ 30 3.36 Time Series of Beans Planted Area and Yield - Shinyanga............................................................................. 32 3.37 Area Planted and Yield of Major Oil Seed Crops............................................................................................ 32 3.38 Time Series Data on Groundnut planted area – Shinyanga Region................................................................. 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Wety Season Only)........................................ 33 3.42 Area Planted and Yield of Fruit and Vegetables.............................................................................................. 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District .................................... 35 3.44 Area Planted per Tomato Growing Household by District (Dry Season Only) ............................................... 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District .................................... 37 3.47 Area planted with Annual Cash Crops............................................................................................................. 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District.................................. 40 3.49 Area Planted for Annual and Permanent Crops ............................................................................................... 40 3.50 Area Planted with the Main Permanent Crops................................................................................................. 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District ........................ 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District.......................... 45 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District ................. 48 3.56 Number of Households by Method of Land Clearing during the Wety Season............................................... 48 3.57 Area Cultivated by Cultivation Method............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District................................................................................... 50 3.59 Planted Area of Improved Seeds – Shinyanga..................................................................................................50 3.60 Planted Area with Improved Seed by Crop Type ............................................................................................ 50 3.61 Percentage of Crop Type Planted Area with Improved Seed – Annuals.......................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer........................................................................................ 51 3.63 Area of Fertilizer Application by Type of Fertilizer and District .................................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop Type - Wety Season.............................................................. 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District....................................................... 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals ...................................................................... 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type ............................................................... 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District ....................................................... 53 3.68a Planted Area with Compost by Crop Type ...................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type................................................................................ 53 3.68c Proportion of Planted Area Applied with Compost by District ....................................................................... 53 3.69 Planted area (ha) by Pesticide use.................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type..................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides.................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Wety Season............................. 54 3.73 Planted Area applied with herbicides by Crop Type........................................................................................ 55 3.74 Percentage of Crop Type Planted Area applied with herbicides...................................................................... 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Wety Season............................... 55 3.76 Planted Area applied with Fungicides by Crop Type ...................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides..................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Wety Season .............................. 56 3.79 Area of Irrigated Land ..................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District........................................................ 57 3.81 Time Series of Households with Irrigation – Shinyanga ................................................................................. 57 8.82 Number of Households with Irrigation by Source of Water ............................................................................ 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................. 57 3.84 Number of Households with Irrigation by Method of Field Application......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type ............................................................................ 59 3.86 Number of households by Storage Methods.................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xiv 3.88 Normal Length of Storage for Selected Crops................................................................................................. 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District................................................. 62 3.90 Number of Households by Purpose of Storage and Crop Type ....................................................................... 62 3.91a Percentage of Households Processing Crops by District ................................................................................. 63 3.91b Percent of Households Processing Crops by District....................................................................................... 63 3.92 Percent of Crop Processing Households by Method of Processing ................................................................. 63 3.93 Percent of Households by Type of Main Processed Product ........................................................................... 63 3.94 Number of Households by Type of By-product............................................................................................... 64 3.95 Use of Processed Product................................................................................................................................. 64 3.96 Percentage of Households Selling Processed Crops by District ...................................................................... 64 3.97 Location of Sale of Processed Products........................................................................................................... 64 3.98 Percent of Household selling Processed Products by Outlets for Sale and Distance........................................65 3.99 Number of Crop Growing Households Selling Crops by District.................................................................... 65 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 65 3.101 Percentage Distribution of Households Receiving Credit by Main Sources.................................................... 66 3.102 Number of Households Receiving Credit by Main Source of Credit and District........................................... 66 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit................................................... 66 3.104 Reasons for Not using Credit (% of Household).............................................................................................. 66 3.105 Number of Households Receiving Extension Advice...................................................................................... 67 3.106 Number of Households Receiving Extension by District ................................................................................ 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................ 67 3.108 Number of Households Receiving Extension by Quality of Services.............................................................. 67 3.109 Number of Households by Source of Inorganic Fertiliser ............................................................................... 69 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser................................................. 69 3.111 Number of Households by Source of Improved Seed...................................................................................... 70 3.112 Number of Households reporting Distance to Source of Improved Seed ........................................................ 70 3.113 Number of Households by Source of Insecticide/Fungicide............................................................................ 70 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides.......................................... 70 3.115 Number of Households with Planted Trees by District.................................................................................... 71 3.116 Number of Planted Trees by Species ................................................................................................................71 3.117 Number of Trees Planted by Smallholders by Species and District................................................................. 71 3.118 Number of Trees Planted by Location ............................................................................................................. 71 3.119 Number of Households by purpose of Planted Trees....................................................................................... 72 3.120 Number of Households with Erosion Control/Water Harvesting Facilities..................................................... 72 3.121 Number of Households with Erosion Control/Water Harvesting Facilities by District................................... 72 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................ 72 3.123 Total Number of Cattle ('000') by District ....................................................................................................... 74 3.124 Numbers of Cattle by Type and District .......................................................................................................... 74 3.125 Cattle Population Trend................................................................................................................................... 76 3.126 Improved Cattle Population Trend................................................................................................................... 76 3.127 Total Number of Goats ('000') by District ....................................................................................................... 76 3.128 Goat Population Trend..................................................................................................................................... 78 3.129 Total Number of Sheep by District.................................................................................................................. 78 3.130 Sheep Population Trend................................................................................................................................... 80 3.131 Total Number of Pigs by District..................................................................................................................... 80 3.132 Pig Population Trend ....................................................................................................................................... 80 3.133 Total Number of Chicken by District .............................................................................................................. 82 3.134 Chicken Population Trend ............................................................................................................................... 82 3.135 Number of Improved Chicken by Type and District.........................................................................................84 3.136 Improved Chicken Population Trend............................................................................................................... 84 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 84 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 86 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 86 3.140 Number of Households by Distance to Veterinary Clinic................................................................................ 87 3.141 Number of Households by Distance to Veterinary Clinic and District............................................................ 87 3.142 Number of Households by Distance to Village Watering Point ...................................................................... 87 3.143 Number of Households by Distance to Watering Point and District................................................................ 87 3.144 Number of Households using Draft Animals................................................................................................... 87 3.145 Number of Households using Draft Animals by District................................................................................. 87 3.146 Number of Households using Organic Fertiliser.............................................................................................. 88 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xv 3.147 Area of Application of Organic Fertiliser by District ...................................................................................... 88 3.148 Number of Households Practicing Fish Farming – Shinyanga ........................................................................ 88 3.149 Number of Households Practicing Fish Farming by District – Shinyanga ...................................................... 91 3.150 Fish Production................................................................................................................................................ 91 3.151 Agricultural Households by Type of Toilet Facility ........................................................................................ 92 3.152 Percentage Distribution of Households Owning the Assets............................................................................. 92 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting .............................................92 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................ 92 3.155 Percentage Distribution of Households by Type of Roofing Material............................................................. 94 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District................................................. 94 3.157 Percentage of Households by Main Source of Drinking Water and Season .................................................... 94 3.158 Percentage of Households by Distance to Main Source of Water and Season................................................. 94 3.159 Number of Agriculture Households by Number of Meals per day .................................................................. 95 3.160 Number of Households by Frequency of Meat and Fish Consumption............................................................95 3.161 Percentage Distribution of the Number of Households by Main Source of Income........................................ 97 List of Maps 3.1 Total Number of Agricultural Households by District..................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District........................................................ 12 3.3 Number of Crop Growing Households by District .......................................................................................... 13 3.4 Percent of Crop Growing Households by District ........................................................................................... 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District.......................................... 14 3.6 Percent of Crop and Livestock Households by District ................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ....................................................................... 22 3.8 Total Planted Area (annual crops) by District...................................................................................................22 3.9 Area planted and Percentage During the Dry Season by District .................................................................... 23 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.................................. 23 3.11 Planted Area and Yield of Maize by District................................................................................................... 26 3.12 Area Planted per Maize Growing Household .................................................................................................. 26 3.13 Planted Area and Yield of Beans by District ................................................................................................... 27 3.14 Area Planted per Beans Growing Household................................................................................................... 27 3.15 Planted Area and Yield of Sorghum by District .............................................................................................. 28 3.16 Area Planted per Sorghum Growing Household.............................................................................................. 28 3.17 Planted Area and Yield of Groundnuts by District .......................................................................................... 32 3.18 Area Planted per Groundnuts Growing Household.......................................................................................... 32 3.19 Planted Area and Yield of Tomato by District................................................................................................. 33 3.20 Area Planted per Tomato Growing Household................................................................................................ 33 3.21 Planted Area and Yield of Cassava by District................................................................................................ 35 3.22 Area Planted per Cassava Growing Household ............................................................................................... 35 3.23 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................ 49 3.24 Area Planted and Percent of Total Planted Area with Irrigation by District.................................................... 49 3.25 Percent of households storing crops for 3 to 6 weeks by district..................................................................... 50 3.26 Number of Households and Percent of Total Households Selling Crops by District....................................... 50 3.27 Number of Households and Percent of Total Households Receiving Crop Extension Services by District.... 57 3.28 Number and Percent of Crop Growing Households using Improved Seed by District ....................................57 3.29 Number and percent of smallholder planted trees by district........................................................................... 58 3.30 Cattle population by District as of 1st Octobers 2003 ......................................................................................62 3.31 Cattle Density by District as of 1st October 2003.............................................................................................62 3.32 Goat population by District as of 1st Octobers 2003 ....................................................................................... 63 3.33 Goat Density by District as of 1st October 2003 ............................................................................................. 63 3.34 Sheep population by District as of 1st Octobers 2003 ..................................................................................... 67 3.35 Sheep Density by District as of 1st October 2003 ........................................................................................... 67 3.36 Pig population by District as of 1st Octobers 2003.......................................................................................... 68 3.37 Pig Density by District as of 1st October 2003.................................................................................................68 3.38 Number of Chickens by District as of 1st October 2003 ................................................................................. 69 3.39 Density of Chickens by District as of 1st October 2003.................................................................................. 69 3.40 Number and Percent of Households Infected with Ticks by District............................................................... 74 3.41 Number and Percent of Households Using Draft Animals by District ............................................................ 74 3.42 Number and Percent of Households Using Farm Yard Manure by District..................................................... 75 ILLUSTRATIONS ________________________________________________________________________________________________________________________ xvi 3.43 Number and Percent of Households using Compost by District...................................................................... 75 3.44 Number and Percent of Households Practicing Fish Farming by District ........................................................77 3.45 Number and Percent of Households without Toilets by District...................................................................... 77 3.46 Number and Percent of Households using Grass/Leaves for roofing material by District .............................. 83 3.47 Number and Percent of Households eating 3 meals per day by District...........................................................83 3.48 Number and Percent of Households eating Meat Once per Week by District ..................................................84 3.49 Number and Percent of Households eating Fish Once per Week by District................................................... 84 3.50 Number and percent of Households Reporting food insufficiency by District ................................................ 85 INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Shinyanga region is situated at the North of Tanzania between 20 and 30degrees below the Equator and 310 – 350 degrees East of the Greenwich Meridian. Shinyanga shares borders with Mwanza Region to the North, Tabora and Singida regions to the South, Kigoma region to the West and the Arusha region to the East. The region comprises eight districts namely Bariadi, Maswa, Kishapu, Shinyanga Rural, Shinyanga Urban, Meatu, Kahama, and Bukombe. The region headquarters is located in Shinyanga District. 1.3 Land Area The region has an area of 19,483 square kilometers 1.4 Climate 1.4.1 Temperature The dominant climate is tropical type of climate with clearly distinguished rainy and dry seasons. The average rainfall ranges from 600mm to 900mm. The rainy season usually starts between mid – October and December, and ends in May. 1.4.2 Rainfall Shinyanga Region has a tropical type of Climate with clearly distinguished rainy and dry seasons. The average rainfall ranged from 600mm to 900mm. The rainy season usually starts between mid October and December and ends in May. 1.5 Population According to the 2002 Population and Housing Census, there were 2,805,580 inhabitants in Shinyanga region. The population of Shinyanga region ranked 2nd of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators The Economy of Shinyanga is predominantly based on subsistence agriculture and livestock rearing. The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 667,886 million with a per capita income of shillings 238,056. The region held 3rd position among regions on GDP and contributed about 6.80 percent to the national GDP1 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 2 Shinyanga region has mineral deposits of Diamond and Gold situated at Mwadui Village and Kahama District Respectively. The Main cash crops are cotton and tobacco while the main food crops are maize, paddy, sorghum, millet, Cassava, beans and sweet potatoes. Livestock reared are Cattle, sheep and goats, with chicken mostly dominated by indigenous bread. Modern diary farming and poultry keeping are confined to urban centers. Industrial activities mostly include cotton ginning, cotton seed oil extraction and small scale industries. Shinyanga Region is well served with communication network with the rest of the country by road and railway lines. There is an airport which is situated in shinyanga municipality. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 237 villages were from Shinyanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 5 • Livestock • Livestock products • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 6 Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 7 In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Shinyanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 8 training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff was used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 9 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. INTRODUCTION ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 10 Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Household Characteristics _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 11 3. CENSUS RESULTS This part of the report presents the results of the census for Shinyanga region, based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results for establishment of trend and time series analysis. This include comparison with the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Survey, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation is divided into four main sections which are household characteristics, crop results, livestock results and Poverty indicators. Comparison to previous census and surveys has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Shinyanga region was 377,857. The largest number of agriculture households was in Kahama (81,217) followed by Bariadi (77,572), Bukombe (53,240), Shinyanga Rural (45,263) Maswa (43,252) Kishapu (35,624), Meatu (31,492) and Shinyanga Urban (10,198) (Map 3.1). Most households (201,316, 53.3%) were involved in growing crops only, 174,232 (46%) were involved in crop production as well as livestock keeping and 2,310 (0.6%) rearing livestock only (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Shinyanga region indicates that most of the agricultural households in all districts ranked annual crop farming as an activity that contributes to most of their livelihood followed by Livestock Keeping and Off-farm income (Table 3.1). Other activities with low contribution to livelihood were Tree/forest resources (4), Permanent crop Farming (5), Remittances (6) and Fishing/ Hunting (7) Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 1 6 3 2 4 7 5 Maswa 1 4 2 3 6 7 5 Shinyanga Ru 1 4 3 2 5 7 6 Kahama 1 5 2 3 6 7 4 Bukombe 1 4 2 3 5 7 6 Meatu 1 6 2 3 5 7 4 Shinyanga Urb 1 4 2 3 5 7 6 Kishapu 1 6 2 4 5 7 3 Total 1 5 2 3 6 7 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity Chart 3.1 Agriculture Households by Type - Shinyanga Crops and Livestock, 174,231.6, 46% Livestock Only, 2,310.1, 1% Crops Only, 201,315.6, 53% Shinyanga Urban Shinyanga Rural Bukombe Kishapu Bariadi Meatu Maswa Kahama 13 18 21 11 27 33 23 45 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Shinyanga Rural Shinyanga Urban Kahama Kishapu Bukombe Maswa Meatu Bariadi 81,217 45,263 53,240 35,624 31,492 43,252 77,572 10,198 64,000 > 48,000 to 64,000 32,000 to 48,000 16,000 to 32,000 0 to 16,000 Map 3.01 SHINYANGA Toatal Number of Agricultural Households by District Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.02 SHINYANGA Number of Agricultural Households Per Square Kilometer of Land by District RESULTS 12 Shinyanga Rural Shinyanga Urban Kishapu Kahama Maswa Bariadi Meatu Bukombe 46.8% 45.2% 52.7% 50.9% 43.9% 60.6% 64.9% 41.1% 60 to 80 45 to 60 30 to 45 15 to 30 0 to 15 Shinyanga Rural Shinyanga Urban Kishapu Maswa Kahama Meatu Bariadi Bukombe 21,182 16,108 13,820 22,774 39,487 34,546 49,208 4,190 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.03 SHINYANGA Number of Crop Growing Households by District Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.04 SHINYANGA Percent of Crop Growing Households by District RESULTS 13 Shinyanga Rural Shinyanga Urban Kishapu Bukombe 53% 48.9% 46.6% 56% 53.4% 39.2% 34.7% Kahama Maswa Meatu Bariadi 51.2% 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 Shinyanga Rural Shinyanga Urban Kahama Bariadi Maswa Kishapu Bukombe 15 11 14 5 8 14 8 Meatu 18 16 to 20 12 to 16 8 to 12 4 to 8 0 to 4 Map 3.05 SHINYANGA Number of Crop Growing Households Per Square Kilometer of Land by District Tanzania Agriculture Sample Census Number of Crop Growing Households Number of Crop Growing Households Per square Km Percent of Crop and Livestock Households Percent of Crop and Livestock Households Map 3.06 SHINYANGA Percent of Crop and Livestock Households by District RESULTS 14 RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 15 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Shinyanga region was 323,921 (86%) of the total regional agricultural households) whilst the female-headed households were 53,936 (14%) of the total regional agricultural households). The mean age for household heads was 46 years (42 years for male heads and 51 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys ‘years shows that there has been no significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Shinganga region had a total rural agricultural population of 2,426,406 of which 1,240,1827 (51%) were males and 1,186,224 (49%) were females. Whereas age group 0-14 constituted 46 percent of the total rural agricultural population, age group 15–64 (active population) was only 50 percent. Shinyanga region had an average household size of 4 with Shinyanga Urban district having the lowest household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy was based on the ability to read and write Swahili, English or both. Chart 3.3 Percent Distribution of Population by Age and Sex - Shinyanga 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head - 25 50 75 100 Type of Holding (000') NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 Year Percent of Househol Male Headed (%) Female Headed (%) RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 16 Literacy Level for Household Members Shinyanga region had a total literacy rate of 59 percent. The highest literacy rate was found in Kishapu district (64.6%) followed by Shinyanga Urban district (64.2%) and Maswa district (61%). Bariadi and Kahama districts had the lowest literacy rates of 55 and 58 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 59 percent. The literacy rates for the male heads was 65 percent and that of female heads was 26 percent. Literacy rate of Male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst heads of households was Bariadi (68%) followed by Maswa (60%). Shinyanga Rural, Kahama and Bukombe had a literacy rate of 59%). The lowest literacy rates among heads of households were recorded in Kishapu (54%), Shinyanga Urban (54%) and Meatu (56%) districts (Chart 3.5). Chart 3.4 Percent Literatecy Level of Household Members by District - 10 20 30 40 50 60 70 80 90 100 Kishapu Shinyanga Urb Maswa Bukombe Shinyanga Rural Meatu Kahama Bariadi District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Shinyanga - 10 20 30 40 50 60 70 80 90 100 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percen Male Female Total Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent Attending School Completed Never Attended to School Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 36% Attending School 27% Never Attended to School 37% RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 17 Educational Status Information on educational status was collected from individual agricultural households. The results show that 36 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 27 percent were still attending school. Those who have never attended school were 37 percent (Chart 3.6). Agricultural households in Kishapu district had the highest percentage (38%) of population aged 5 years and above who had completed different levels of education. This was followed by Shinyanga Rural and Bukombe districts with 37.4 and 37.3 percent respectively. Meatu and Shinyanga Urban districts had the lowest percentages of 34.1 and 34.2 respectively (Chart 3.7). The number of heads of agricultural households with Primary education in Shinyanga region was 210,174 (56%), those with Post Primary education were 10,525 (3%) and those with only adult education were 4,332 (1%). The number of those who were reported to have no education at all was 152,825 (40%) (Chart 3.8). With regard to the heads of agricultural households with no education in Shinyanga Region, Kahama district had the highest percentages (22.6%). This was followed by Bariadi (20%), Maswa (13%), Shinyanga Rural (12%) and Bukombe, Meatu, Kishapu, both with (10%) of agricultural households with no education. The least number of households with no education was found in Shinyanga Urban (3%). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. In Shinyanga region 112,528 households (59%) had only one member aged 5 and above involved in off-farm income generating activity, 50,868 households (26%) had two members involved in off- Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment No Education, 152,826, 40% Primary Education, 210,174, 56% Post Primary Education, 10,525, 3% Adult Education, 4,332, 1% Chart 3.9 Number of Households by Number of Members with Off-farm income generating activities Two Members, 50,868 , 26% One Member 113,528 , 59% More than Two Members, 28,310 , 15% Chart 3.10 Percentage Distribution of Agricultural Households by Number of household members with Off- farm Activities 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Maswa Kahama Meatu Bariadi Shinyanga Urb Bukombe Kishapu Shinyanga Rur Percent More Than Two Two One None RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 18 Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Kishapu Meatu Maswa Bukombe Kahama Bariadi Shinyanga Rural Shinyanga Urban Districts Area/household (ha) 84 85 86 87 88 89 90 91 92 93 94 Percentage utilized Area utilised (Ha) Total usable area Percent Utilisation farm income generating activities and 28,310 households (15%) had more than two members involved in off-farm income generating activities (Chart 3.9). Shinyanga Rural district had the highest percentage of agriculture households with off-farm income (over 70% of total agriculture households in the district). Other districts with high percents of agriculture households with off-farm income were Kahama (60%), Bariadi (85%) and Shinyanga Urban (58%). Bukombe and Meatu districts had the lowest percent of agriculture households with off-farm income (31% and 33% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Kahama (30%). Kishapu and Bukombe districts had very few households with more than one member having off-farm income (14% and 13% respectively) (Chart (chart 3.10). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 1,468,142 ha. The regional average land area utilised for agriculture per household was 3.4 ha. This figure is above the national average which is estimated at 2.0 hectares. About ninety percent of the total land available to smallholders was utilised. Only 7.5 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). RESULTS AND ANALYSIS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 19 There were large differences in land area utilised per household between districts with Kishapu and Shinyanga Urban utilizing between 5.6 and 2.2 ha per household. The percentage utilized of the usable land per household was highest in Maswa (93%) and lowest in Kahama (87%). 3.2.2 Types of Land Use The area of land under temporary monocrop was 753,616 hectares (51% of the total land available to smallholders in Shinyanga), followed by temporary mixed crops (233,347 ha, 16%), area under pasture (121,381 ha, 8%), area of uncultivated usable land 108,572 ha, 7%) and area under fallow 105,297 ha 7%. The area under permanent mono and permanent mixed crops was very small about 1% of the total land area. (Chart 3.12) 3.3 Annual Crop and Vegetable Production Shinyanga region has a unimodal rainfall pattern with the rain starting in November and ending in March. With the exception of some irrigated annual crops and vegetables grown in the dry season, the rest of the crops are grown during the wet season. The quantity of crops produced in both seasons will be used as a basis for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 960,250 hectares out of which 957,423 hectares (99.71%) were planted during Wet season and 2,826 hectares (0.29%) during Dry season. The Wet Season is the most important agricultural season in the region for agricultural productivity. Because of this, the analysis in this report will be restricted to the information on Wet season, (Chart 3.13). The average area planted per household was 2.5 ha (Chart 3.14). Chart 3.12 Land Area by Type of Use 0.2 0.4 0.8 1.4 1.8 2.3 2.9 7.2 7.4 8.3 51.3 15.9 - 200,000 400,000 600,000 800,000 Area under P lanted Trees Area under P ermanent Mono Crops Area under P ermanent Mixed Crops Area Rented to Ot hers Area Unusable Area under Nat ural Bush Area under P ermanent / Annual Mix Area under Fallow Area of Uncultivat ed Usable Land Area under P asture Area under Temporary Mixed Crops Area under Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (Hectares) Wet Season, 957,423.30 , 99.71% Dry Season, 2,826.30 , 0.29% Chart 3.14 Average Area Planted per household by District 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Shinyanga Urban Kahama Bariadi Shinyanga Rural Meatu Bukombe Maswa Kishapu Planted Area (ha) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 20 The districts with the largest area planted per household were Kishapu (3.4 ha) followed by Maswa (3.0 ha), Bukombe (2.6 ha), Meatu (2.5 ha), Shinyanga Rural (2.4 ha), Bariadi (2.4 ha) and Kahama (2.2 ha). The district with the smallest average area planted per household was Shinyanga Urban (1.5 ha). The crop type with the largest planted area was cereals 591,416 ha (62% of the total area planted with annuals). This was followed by cash crops (205,020 hectares, 21%), oil Seeds and oil nuts (66,153 hectares, 6.7%), pulses (48,130 hectares, 5%), roots and tubers (48,081 hectares, 5%) and fruit and vegetables (1,421 hectares, 0.1%). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether it is annual or permanent. The second section contains a more detailed analysis of production based on crop types. 3.3.2 Crop Importance Maize was the dominant food crop grown in Shinyanga region and it had a planted area 3.4 times greater than Paddy. The area planted with maize constitutes 41.7 percent of the total area planted with annual crops in the region. Other annual crops in order of their relative importance in the region (based on area planted) include Cotton 199,390 ha, Sorghum 65,917 ha, Groundnuts 64,355 ha, and Beans 38,944 ha. Other crops planted in Shinyanga Region were Sweet Potatoes 27,601 ha, Chick Peas 23,933 ha, Cassava 19,235 ha, Bulrush Millet 6,024 ha, Tobacco 5,630 ha, Cowpeas 3,376 ha, Green Gram 2,898 ha, Sunflower 1,434 ha, Bambaranuts 1,382 ha. A small amount of Yams 641 ha, Irish Potatoes 562 ha, Tomatoes 524 ha, Simsim 364 ha, Finger Millet 289 ha, Onions 57 ha, Egg Plant 203 ha, Radish 199 ha, Cabbage 104 ha, Amaranths 74 ha, Mung Beans 64 ha, Cocoyam 41 ha, Pumpkins 26 ha, Chart 3.16 Planted Area (ha) for the Main Crops, SHINYANGA 0 100,000 200,000 300,000 400,000 Maize Cotton Paddy Sorghum Groundnuts Beans Sweet Potatoes Chich Peas Cassava Bulrush Millet Tobacco Cowpeas Sunflower Bambaranuts Crop Planted Area. (ha) Chart 3.18: Percentage Distribution of Area Planted with annual crops by Crop types Fruit & Vegetables 0% Cereals 60% Roots & Tubers 5% Oil Seeds & Oil Nuts 7% Pulses 7% Cash Crops 21% Chart 3.17 Planted Area (ha) per Household by Selected Crop - Shinyanga - 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 Chich Peas Bulrush Millet Cotton Maize Sorghum Tobacco Paddy Sunflower Cassava Groundnuts Green Gram Beans Cowpeas Bambaranuts Crop Planted Area (ha) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 21 Cucumber 23 ha and Chillies 10 ha are also grown in the region (Chart 3.16). Other annual crops are grown in minor quantities. Chart 3.17 shows the area planted per household growing selected crops. Households that grew Chick Peas, Bulrush Millet and Cotton have a larger planted area per household than those growing other crops. Vegetable crops have smaller planted areas per household than cereals, roots and tubers and oilseed crops. 3.3.3 Crop Types Cereals are the main crops grown in Shinyanga region. The area planted with cereals was 591,416 ha (60% of the total planted area), followed by Cash Crops with 205,898 ha (21%), Pulses 67,809 ha (6.9%), Oil Seeds & Nuts 66,153 (6.8%) and Roots and Tubers 48,081 ha (4.9%). Fruits and Vegetables were scarcely grown in Shinyanga, having 1,421 ha 0.1 % of the total Planted Area. The main cash crop was cotton but a small amount of tobacco (5,630 ha) was also grown (Chart 3.18). Almost all crops are grown in the wet season and only a few crops are also grown in dry season. The dry season production was therefore very small, it is inappropriate to make detailed comparisons between the two seasons. 3.3.4 Cereal Crop Production The total production of cereals was 316,187 tonnes. Maize was the dominant cereal crop at 191,402 tonnes which was 61 percent of total cereal crops produced, followed by paddy 104,847 tonnes (33%), sorghum 17,269 tonnes (5%), Bulrush Millet (0.8%) and finger millet (0.04%). The total area planted with cereals during the year was 591,416 ha, of which 589,543 ha (99.7%) was planted during the wet season and 1,873 ha (0.3%) was planted in dry season. The Wet season accounts for 99.6 percent of the total cereals produced in both seasons. Maize was dominant and it represented 67.6 percent of the total area planted with cereal crops, then followed by Paddy (20%), sorghum (11%), bulrush millet (1%) and finger millet (0.4%) (Chart 3.19A, Table 3.2). The yield of paddy was 882 kg/ha, followed by Finger Millet 481Kg/ha, Maize 478Kg/ha, Bulrush Millet 430kg/ha and Sorghum 262 kg/ha, (Chart 3.19B). Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 1,541 647 420 398,729 190,755 478 400,270 191,402 478 Paddy 244 439 1,802 118,673 104,408 880 118,916 104,847 882 Sorghum 63 14 228 65,854 17,255 262 65,917 17,269 262 Bulrush Millet 26 38 1,482 5,998 2,491 415 6,024 2,530 420 Finger Millet 0 0 0 289 139 481 289 139 481 Total 1,873 1,139 589,543 315,047 591,416 316,187 Chart 3.19A Area Planted of Major Cereal Crops 0 150,000 300,000 450,000 Maize Paddy Sorghum Bulrush Millet Finger Millet Area Planted (h Chart 3.19B Yield of Major Cereal Crops 0 300 600 900 Maize Paddy Sorghum Bulrush Millet Finger Millet Yield (Kg/ha) . Kahama Shinyanga Urban Meatu Maswa Kishapu Shinyanga Rural Bariadi Bukombe 86.9% 92.1% 92.7% 91.1% 89.7% 90.1% 90.2% 90.4% 91.7 to 92.7 90.5 to 91.7 89.3 to 90.5 88.1 to 89.3 86.9 to 88.1 Shinyanga Rural Maswa Bariadi Meatu Kishapu Kahama Shinyanga Urban Bukombe 197,060ha 94,952ha 182,648ha 134,521ha 121,691ha 101,227ha 112,392ha 15,759ha 160,000 to 200,000 120,000 to 160,000 80,000 to 120,000 40,000 to 80,000 0 to 40,000 Map 3.07 SHINYANGA Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Area Tanzania Agriculture Sample Census Percent of Utilized Land Area Planted Area (ha) Planted Area (ha) Map 3.08 SHINYANGA Total Planted Area With Annual Crops by District RESULTS 22 Shinyanga Urban Kishapu Bariadi Maswa Shinyanga Rural Kahama Bukombe 11,720ha 66,491ha 119,017ha 55,971ha 53,105 65,240ha 109,652ha 86,432ha 2.1% 11.7% 21% 9.9% 11.5% 9.4% 19.3% 15.2% Meatu 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Shinyanga Rural Shinyanga Urban Maswa Kishapu Bariadi Meatu Kahama Bukombe 195ha 109ha 119,017ha 1,651ha 0ha 0ha 291ha 580ha 1.2% 0.1% 0% 1.2% 0% 0% 0.3% 0.5% 96,000 to 120,000 72,000 to 96,000 48,000 to 72,000 24,000 to 48,000 0 to 24,000 Map 3.09 SHINYANGA Area planted and Percentage During the Short Rainy Season by District Tanzania Agriculture Sample Census Area Planted (ha) Percent of Area Planted Planted Area (ha) Planted Area Cereal Crops Map 3.10 SHINYANGA Area Planted with Cereals and Percent of Total Land Planted With Cereals by District Area Planted (ha) Percent of Planted Area Cereal Crops RESULTS 23 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 24 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Shinyanga region during the wet season was 351,234 (93.7% of the total number of households growing annual crops in the region during the wet season). The total production of maize was 191,402 tonnes from a planted area of 400,270 hectares resulting in a yield of 0.48 t/ha. Chart 3.20 presents the maize production trend. The yield declined over the entire eight year period from 1995 to 2003. Alongside the decrease in yield the production also more or less declined over the entire period except in 1999 when production increased somewhat and remained the same level up to the year 2000 before declining over the remaining period up to the year 2003. The mentioned increase in production was due to a substantial increase in the planted area over the period 1997 to 2000 after which it also declined over the remaining period up to the year 2003, (Chart 3.20). The average area planted with maize per household was 1.1 hectares; however it ranged from 0.7 hectares in Shinyanga Urban district to 1.31 hectares in Bariadi district (Map 3.11). Bariadi had the largest planted area of maize (101,952 ha) followed by Kahama (79,905 ha), Bukombe (64,833 ha), Shinyanga Rural (44,228 ha), Kishapu (35,496 ha), Maswa (35,159), Meatu (31,192) and Shinyanga Urban (7,505 ha) (Chart 3.21 and Map 3.12) . 3.3.4.1 Paddy Paddy was the Second dominant cereal crop in terms of production in the region. The number of households growing Paddy in Shinyanga region during the wet season was 136,046 (36% of the total households growing annual crops in the region during the wet season). The total production of Paddy was 104,847 tonnes from a planted area of 118,916 hectares resulting in a yield of 0.88 t/ha. Chart 3.22 presents Paddy production trend. The chart shows that there was a decrease in Paddy production over the period 1996 to 1997, after which the production stabilized over the period 1997 to 2000. Production gradually increased sharply over the period 2000 to 2003 (Chart 3.22). Chart 3.22 Timeseries of Paddy Production, Area Planted and Yield - 50,000 100,000 150,000 200,000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 - 1.00 2.00 3.00 4.00 Paddy Yield (T/ha) Paddy Production (Tonnes) Paddy Planted Area (ha) Chart 3.21 Maize: Total Area Planted and Planted Area Per Household by District 0 30,000 60,000 90,000 120,000 Bariadi Bukombe Kishapu Meatu Kahama Shinyanga Rural Maswa Shinyanga Urban - 0.50 1.00 1.50 Planted Area (ha) Area Planted Per Household (ha) Chart 3.20 Timeseries of Maize Production, Area Planted and Yield - 100,000 200,000 300,000 400,000 500,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 - 0.50 1.00 1.50 2.00 Maize Yield Maize Production Maize Planted Area RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 25 Chart 3.22 also shows that the planted area of Paddy increased sharply between 1997 and 1998 and has remained almost constant since then. Conversely, the yield declined constantly between 1994 and 2002 and has remained at this low level since then. Whilst Chart 3.22 shows that, there has been a slight increase in the production of Paddy over the last 10 years, this can be explained by the increase in the planted area. (Chart 3.22). The average area planted with Paddy per household was 0.87 hectares; however it ranged from 1.19 hectares in Shinyanga Rural district to 0.27 hectares in Meatu district (Map 3.11). Kahama had the largest planted area of Paddy (53,283 ha) followed by Bukombe (21,371 ha), Shinyanga Rural (20,937 ha), Maswa (9,975 ha), Bariadi (6,914 ha), Kishapu (4,459 ha), Shinyanga Urban (1,628 ha) and Meatu (349 ha) (Chart 3.23 and Map 3.12). 3.3.4.3 Sorghum Sorghum was the third most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Shinyanga region during the wet season was 59,619. This represented 16 percent of the total households growing annual crops in Shinyanga region during the wet season. The total production of sorghum was 17,269 tonnes from a planted area of 65,917 hectares resulting in a yield of 0.26 t/ha. The district with the largest planted area of sorghum was Meatu (24,353 ha) followed by Kishapu (21,030 ha), Bariadi (9,971 ha) and Maswa (7,950 ha) (Map 3.15). The Largest planted area per household for sorghum was found in Meatu (0.77 ha) and Kishapu (0.59 ha). Shinyanga Rural had the smallest planted area per household (0.03 ha) (Chart 3.25 and Map 3.16). There was a large reduction in the production of sorghum from 114,000 tonnes in 1994/95 to 17,000 tonnes in 2002/03 (Chart 3.24). Chart 3.24 also shows that there was a gradual reduction in the area planted with sorghum and a persistent Chart 3.24 Timeseries of Sorghum Production, Area Planted and Yield - 50,000 100,000 150,000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 - 0.20 0.40 0.60 0.80 1.00 1.20 Sorghum Yield Sorghum Production Sorghum Area Chart 3.23 Paddy: Total Area Planted and Planted Area Per Household by District 0 15,000 30,000 45,000 Kahama Shinyanga Rural Bukombe Maswa Shinyanga Urban Kishapu Bariadi Meatu - 0.20 0.40 0.60 0.80 1.00 1.20 1.40 Planted Area (ha) Area Planted Per Household (ha) Chart 3.25 Sorghum: Total Area Planted and Planted Area Per Household by District 0 10,000 20,000 Meatu Kishapu Maswa Bariadi Shinyanga Urban Shinyanga Rural Bukombe Kahama 0.00 0.30 0.60 0.90 Planted Area (ha) Area Planted Per Household (ha) Shinyanga Urban Shinyanga Rural Maswa Bariadi Kishapu Meatu Bukombe 1 0.9 1.4 1.3 1.2 1 1.3 Kahama 0.9 1.3 to 1.4 1.2 to 1.3 1.1 to 1.2 1 to 1.1 0.9 to 1 Kishapu Shinyanga Urban Shinyanga Rural Maswa Bariadi Meatu Bukombe 35,494ha 7,505ha 44,228ha 79,905ha 35,159ha 101,952ha 31,193ha 64,833ha 0.2t/ha 0.3t/ha 0.4t/ha 0.4t/ha 0.4t/ha 0.3t/ha 0.6t/ha 0.7t/ha Kahama 80,000 to 110,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Map 3.11 SHINYANGA Planted Area and Yield of Maize by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.12 SHINYANGA Area Planted Per Maize Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 26 Shinyanga Rural Shinyanga Urban Maswa Kishapu Meatu Bariadi Kahama Bukombe 0.3ha 0.5ha 0ha 0ha 0.5ha 0.5ha 0.9ha 0.3ha 1.6 to 2 1.2 to 1.6 0.8 to 1.2 0.4 to 0.8 0 to 0.4 Maswa Shinyanga Rural Kishapu Bariadi Shinyanga Urban Kahama Bukombe 8,718ha 1ha 372ha 339ha 114ha 17ha 100ha 22ha 0.3t/ha 0.2t/ha 0.3t/ha 0.4t/ha 0.5t/ha 0t/ha 0.1t/ha 1.2t/ha Meatu 7,200 to 8,800 5,400 to 7,200 3,600 to 5,400 1,800 to 3,600 0 to 1,800 Map 3.13 SHINYANGA Planted Area and Yield of Beans by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.14 SHINYANGA Area Planted per Beans Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 27 Shinyanga Rural Kishapu Shinyanga Urban Bukombe Maswa Bariadi 21,030ha 917ha 1,326ha 227ha 101ha 7,950ha 24,395ha 9,971ha 0t/ha 0t/ha 0t/ha 0.34t/ha 0.61t/ha 0t/ha 0.17t/ha 0.42t/ha Kahama Meatu 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Kishapu Shinyanga Urban Kahama Shinyanga Rural Bariadi Meatu Bukombe 1.5ha 0.8ha 0.5ha 0.7ha 1.6ha 0.2ha 0.4ha Maswa 0.7ha 1.4 to 1.7 1.1 to 1.4 0.8 to 1.1 0.5 to 0.8 0.2 to 0.5 Map 3.15 SHINYANGA Planted Area and Yield of Sorghum by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.16 SHINYANGA RESULTS 28 Area Planted per Sorghum Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 29 decline in yield. This implies that the dramatic reduction in the quantity of sorghum production over the reported period was due to both reductions in area planted as well as declining yields. 3.3.4.4 Other Cereals Other cereals that were produced in small quantities were Bulrush Millet and finger millet. The district with the largest area planted with Bulrush Millet was Kishapu (4,256 ha) and Shinyanga Urban (1,645 ha) with other districts having small planted areas. The largest area planted with finger millet was in Bariadi district (180 ha). Other districts had insignificant planted areas of finger millet. 3.3.5 Roots and Tuber Crops Production The Common Roots and Tuber Crops grown in Shinyanga Region were Sweet Potatoes and Cassava. The total production of both Cassava and Sweet Potatoes was 39,975 tonnes. Sweet Potatoes production was higher than that of Cassava in the region with a total production of 25,376 tonnes representing 63 percent of the total root and tuber crop production. (Chart 3.26 and Table 3.3). The area planted with Sweet Potatoes was the largest and therefore sweet potatoes was the most important root and tuber crop in Shinyanga in terms of planted area. 3.3.5.1 Sweet Potatoes The number of households growing Sweet Potatoes in the region was 95,342. This represented 25 percent of the total households growing crops during the wet season in the region. The total production of Sweet Potatoes during the census year was 25,376 tonnes from a planted area of 27,601 hectares resulting in a yield of 0.92t/ha. Previous censuses and surveys indicate that the area planted with Sweet Potatoes increased gradually over the period 1992/93 to 1997/98 (Chart 3.27) and thereafter decreased gradually up to 2002/03. The area planted with Sweet Potatoes accounted for 2.82 percent of the total area planted with annual crops and vegetables in the census year. Table 3.3: Area, Production and Yield of Roots and Tuber Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Cassava 0 0 0 19,235 14,599 759 19,235 14,599 759 Sweet Potatoes 45 317 7120 27,556 25,059 909 27,601 25,376 919 TOTAL 45 317 7120 46,791 39,658 800 46,836 39,975 800 Note: Cassava is produced in both the Wet and Dry Season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the Wet Season only. Chart 3.27 Area Planted with Sweet Potatoes during the Census/ Survey Year - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Sweet Potatoes Planted Area (ha) Chart 3.26 Area and Production for Major Root Crops in Shinyanga Region by type of Crop 0 5,000 10,000 15,000 20,000 25,000 30,000 Cassava Sweet Potatoes Crop Production/Area ' Area Planted (ha) Quantity Harvested (tons) RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 30 Shinyanga Rural district had the largest planted area of Sweet Potatoes (6,310 ha, 23% of the Sweet Potatoes planted area in the region), followed by Kishapu (5,971 ha, 22%), Maswa (5,729 ha, 21%) , Kahama (2,471ha, 9%), Bariadi (2,384 ha, 9%), Meatu (2,378 ha, 9%) Shinyanga Urban (1,368 ha, 5%) and Bukombe (989 ha, 3%) (Map 3.17). However, the highest proportion of land planted with Sweet Potatoes, expressed as a percent of the total planted area was in Shinyanga Urban district (18.8%). This was followed by Kishapu (17%), Maswa (16%) Shinyanga rural (14%) and Meatu (7.6%) (Chart 3.28). The average Sweet Potatoes planted area per Sweet Potatoes growing households was 0.07 hectares. The area planted per Sweet Potatoes growing household was greatest in Kishapu (0.17 ha), followed by Shinyanga Rural (.17ha), Shinyanga Urban (0.13 ha), Maswa (0.13 ha), Meatu (0.08 ha), Bariadi (0.03 ha), Kahama (0.03 ha) and Bukombe (0.02 ha) (Map 3.18). 3.3.5 Pulse Crops Production The total area planted with pulses was 47,984 hectares, of which 23,933ha were planted with Chick Peas (50% of the total area planted with pulses), followed by Beans (16,396 ha, 34%), Cow Peas (3,376 ha, 7%), Green Gram (2,898ha 6%) and Bambaranuts (1,382 ha, 3%). The total production of pulses was 18,500 tonnes. Chick Peas was the highest producing pulse crop (10,315 tonnes) and accounted for 56 percent of the total pulse production. This was followed by Beans (5,408t, 29%), Bambaranuts (1,296t, 7%), Cowpeas (851t, 5%) and green gram (630t, 3%). The Highest Yield was recorded on Bambaranuts (938 kg/ha) followed by Chick Peas (431kg/ha,), Beans 330 Kg/ha, Cow Peas 252kg/ha and Green gram 217 kg/ha, (Table 3.4). 3.3.5.3 Chick Peas Chick Peas dominate the production of pulse crops in the region. The number of households growing Chick Peas in Shinyanga region was 15,333 (4% of all crop growing households in the region). The total production of Chick Peas in the region was 10,315 tonnes from a planted area of 23,933 hectares resulting in yield of 0.4 t/ha. The largest area planted with Table 3.4 Area, Production and Yield of Pulses by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Beans 101 25 248 16,295 5,383 330 16,396 5,408 330 Cowpeas - - - 3,376 851 252 3,376 851 252 Green Gram - - - 2,898 630 217 2,898 630 217 Chich Peas - - - 23,933 10,315 431 23,933 10,315 431 Bambaranuts 3 2 533 1,379 1,295 939 1,382 1,296 938 Total 104 32 47,880 18,473 47,984 18,500 0 5 10 15 20 Proportion of Area Planted , Shinyanga Urban Kishapu Maswa Shinyanga Rural Meatu Kahama Bariadi Bukombe District . Chart 3.28 Propotion of Area Planted with Sweetpotatoes by District Chart 3.29 Area Planted with Chick Peas as a Percent of Area Planted with Oil Seeds & Nuts 0 20 40 60 80 100 Meatu Bukombe Kahama Maswa Shinyanga Urb Bariadi Kishapu Shinyanga Rur District Proportion of Area . RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 31 Chick Peas in the region was in Shinyanga Rural district with 8,927 ha (37% of the total area planted with Chick Peas in the region). Of the total area Planted with Pulses the highest proportion of area planted with chick peas was recorded in Shinyanga rural (77%), followed by Kishapu (76%) and Bariadi (69%) districts (Chart 3.29). 3.3.6 Oil Seed Production The total production of oilseed crops was 31,561 tonnes, planted on an area of 66,057 hectares. Groundnuts was the most important oilseed crop with 64,355 ha (97% of the total area planted with oil seeds), followed by sunflower (2%) and simsim (1%), (Table 3.5). The yield of Simsim was the highest for oil seed crops (578 kg/ha) followed by Ground nuts (481 kg/ha) and sunflower (317 kg/ha). The total production of groundnuts was 30,951 tonnes, accounting for 98 percent of the total production of oil seeds, followed by simsim and sunflower (1% each), (Chart 3.30). 3.3.7 Vegetables The collection of fruit and vegetable production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not for household consumption. Most fruit production is from permanent crops. Reliable historical data for time series analysis of fruit and vegetables was not available. The total production of vegetables was 3,381 tonnes. The most cultivated vegetable crop was tomatoes with a production of 1,977 tonnes (58% of the total vegetables produced) followed by onions (503t, 15%) and Cabbages (461t, 14%). The production of the other vegetable crops was relatively small (Chart 3.31, Table 3.6). Chillies had the highest yield (5,039 kg/ha) followed by Cabbages (4,443kg/ha), Tomatoes 3,773kg/ha and onions (1,956kg/ha). Pumpkins, Egg plant and Radish had the lowest yields of 55, 408 and 609 kg/ha respectively (Table 3.6). Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Sunflower 0 - 0 1,434 455 317 1,434 455 317 Simsim 0 - 0 268 155 578 268 155 578 Groundnuts 167 32 482 64,188 30,919 482 64,355 30,951 482 Total 167 32 65,890 31,529 66,057 31,561 Table 3.6: Area, Production and Yield of Fruit and vegetables by Season Dry Season Wet Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity harvested (tons) Yield (Kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (Kg/ha) Tomatoes 0 0 0 524 1,977 3,773 524 1,977 3,773 Onions 0 0 0 257 503 1,956 257 503 1,956 Egg Plant 0 0 0 203 83 408 203 83 408 Radish 0 0 0 199 121 609 199 121 609 Cabbage 0 0 0 104 461 4,443 104 461 4,443 Amaranths 0 0 0 74 140 1,880 74 140 1,880 Pumpkins 0 0 0 26 1 55 26 1 55 Cucumber 0 0 0 23 43 1,878 23 43 1,878 Chillies 0 0 0 10 51 5,039 10 51 5,039 Total 0 0 1,421 3,381 1,421 3,381 Chart 3.31 Area Planted with Vegetables by type of vegetable 0 100 200 300 400 500 600 Tomatoes Onions Egg Plant Radish Cabbage Amaranths Pumpkins Cucumber Chillies Type of Vegetable Area Chart 3.30 Area Planted with Ground Nuts as a Percent of Area Planted with Oil S eeds & Nuts 0 25 50 75 100 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Proportion of Area . Shinyanga Rural Maswa Kishapu Shinyanga Urban Kahama Bukombe Meatu Bariadi 0.4ha 0.5ha 0.3ha 0.6ha 0.5ha 0.6ha 0.4ha 0.5ha 0.6 to 0.7 0.6 to 0.7 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 Shinyanga Urban Kahama Bukombe Maswa Shinyanga Rural Kishapu Bariadi 1,547ha 19,995ha 11,299ha 6,427ha 2,845ha 3,035ha 9,441ha 9,766ha 0.6t/ha 0.6t/ha 0.6t/ha 0.4t/ha 0t/ha 0.2t/ha 0.2t/ha 0.6t/ha Meatu 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Map 3.17 SHINYANGA Planted Area and Yield of Groundnuts by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.18 SHINYANGA Area Planted per Groundnuts Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS 32 Kishapu Shinyanga Urban Kahama Shinyanga Rural Bariadi Meatu Bukombe 0.3ha 0ha 0.2ha 0.1ha 0.2ha 0.2ha 0.1ha Maswa 0.3ha 0.24 to 0.3 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Shinyanga Urban Maswa Kishapu Shinyanga Rural Bariadi Bukombe 1,547ha 9,766ha 6,427ha 2,845ha 3,035ha 9,441ha 19,996ha 11,299ha 4t/ha 3.7t/ha 2.5t/ha 0t/ha 4.2t/ha 2.2t/ha 4.5t/ha 17.5t/ha Kahama Meatu 17,000 to 20,000 13,000 to 17,000 9,000 to 13,000 5,000 to 9,000 1,000 to 5,000 Map 3.19 SHINYANGA Planted Area and Yield of Tomatoes by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.20 SHINYANGA RESULTS 33 Area Planted per Tomatoes Growing Household by District Area Planted (ha) Planted Area Per Household RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 34 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report, the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore time series analysis cannot be made in this section. For small holders the planted area with permanent crops was 53,420 hectares (5.2% of the area planted with annual and permanent crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst the planted area for permanent crops is the same as the physical planted land area. So the percentage of the physical area planted with permanent crops would be higher than indicated in Chart 3.34. The most important permanent crop in Shinyanga region is Mango which accounts for a planted area of 28,067.0 ha, (53% of the planted area of all permanent crops) followed by Pawpaw (6,337 ha, 12%), Sisal (5,719 ha, 11%), and Banana (3,763 ha, 11%). Each of the remaining permanent crops had an area of less than 5 percent of the total area planted with permanent crops (Chart 3.35). Kahama district had the largest area under smallholder permanent crops (41,573 ha, 78%). This is followed by Bukombe (6,738 ha, 13%). With the exception of these two districts, other districts have relatively low percentages, less than 5% of land allocated to permanent crops farming (Chart 3.36). Table 3.7 Land Clearing Methods Method of Land Clearing Number of Households Area Planted % Mostly Bush Clearance 25,886 73,450 8 Mostly Hand Slashing 306,419 786,468 82 Mostly Tractor Slashing 1,215 2,251 0 Mostly Burning 10,135 19,590 2 No Land Clearing 30,424 73,327 8 Total 374,078 955,086 100 Chart 3.34 Area Planted for Annual and Permanent Crops Permernent, 53,420 , 5% Annual, 960,219 , 95% Annual Permernent Chart 3.35 Area Planted with main Perennial Crops Other, 9,536, 18% Banana, 3,763, 7% Sisal, 5,719, 11% Pawpaw, 6,337, 12% Mango, 28,065, 52% Mango Pawpaw Sisal Banana Other 0 10,000 20,000 30,000 40,000 50,000 Planted Area Kahama Bukombe Bariadi Shinyanga Rural Maswa Kishapu Meatu Shinyanga Urban District . Chart 3.36 Planted Area with Permanent crops by District Shinyanga Urban Shinyanga Rural Meatu Bariadi Bukombe 0.3 0.3ha 0.5ha 0ha 0.5ha 0.5ha 0.9ha Kahama Maswa Kishapu 0ha 0.72 to 0.9 0.54 to 0.72 0.36 to 0.54 0.18 to 0.36 0 to 0.18 Shinyanga Rural Shinyanga Urban Kishapu Bariadi Meatu Kahama Bukombe 174ha 335ha 523ha 0ha 3,755ha 7,752ha 6,697ha 3.1t/ha 0t/ha 3t/ha 1.6t/ha 2.8t/ha 2.4t/ha 2.6t/ha 1.8t/ha Maswa 0ha 6,400 to 7,800 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 Map 3.21 SHINYANGA Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Area Planted (ha) Yield (t/ha) Planted Area Per Household Map 3.22 SHINYANGA Area Planted per Cassava Growing Household by District Area Planted (ha) Planted Area Per Household ha RESULTS 35 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 36 0 40,000 80,000 120,000 160,000 200,000 Area Cultivated Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District . Chart 3.40 Area Cultivated by Method of Cultivation and District Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories; bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region was 786,468 ha which represents 82 percent of the total planted area. Burning, bush clearance and tractor slashing are less important methods of land clearing and they represent 2, 0.3 and 7.7 percents respectively (Table 3.7, Chart 3.38) 3.5.2 Methods of Soil Preparation Oxen Ploughing is mostly used for soil preparation as it has been used in an area of 629,516 ha which represents 66 percent of the total planted area, followed by Hand Cultivation (294,648 ha, 31%) and tractor ploughing (3,509 ha, 1%) (Chart 3.40). In Shinyanga region, Bariadi district has the largest planted area cultivated using oxen (164,355 hectares, 40.6%) followed by Kishapu (112,432 ha, 18%), Maswa (89,475 ha, 14%) and Shinyanga Rural (86,690 ha, 14%), Meatu (82,344 ha, 13%), Kahama (49,833 ha, 8%), Bukombe (32,312 ha, 5%) and Shinyanga Urban (12,077 ha, 2%) (Chart 3.40, 3.40A). Tractor ploughing was more prominent in Maswa district with 29 percent of the area cultivated using tractors in the region followed by Kahama District 19 %, Bariadi District 17%, Meatu District and Kishapu District 10%. Chart 3.38 Number of Households by Method of Land Claring in Shinyanga Region 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Method of Land Clear Number of Household Chart 3.40A Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 3509.1, 1% Mostly Hand Cultivation, 294,648, 31% Mostly Oxen Ploughing, 629,516, 66% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 37 3.5.3 Improved Seeds Use The planted area with improved seeds was 261,066 ha which represents 27 percent of the total area planted with the annual crops and vegetables. Cash Crops had the largest planted area with improved seeds (159,104 ha, 69% of the planted area with improved seeds) followed by Cereals crops (57,738 ha, 25%). Other crop types had insignificant area planted with improved seeds (Chart 3.41, 3.42). Among the Cash Crops Cotton had the largest area of improved seeds application which was 155,842 ha 98% of area planted by cash crops. 3.5.4 Fertilizer Use The use of fertilisers on annual crops was very small with a planted area of only 171,943 ha (18% of the total planted area in the region). The planted area without fertiliser for annual crops was 785,481 hectares representing 82 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 137,161 ha which represents 14 percent of the total planted area (80% of the area planted with fertiliser application in the region). This was followed by Inorganic Fertilizers (20,380ha, 12% of the planted area with fertiliser and 2% of the total planted area in the region), Compost (14,404ha, 8% of the planted area with fertiliser and 2% of the total planted area in the region), Chart 3.43. Chart3.42 Planted Area with Improved Seeds by Crop type Roots & Tubers, 2,701, 1% Cash Crops, 155,842, 69% Fruits & Vegetables, 652, 0% Oil Seeds & Oil Nuts, 4,554, 2% Pulses, 48,025, 5% Cereals, 57,738, 26% Chart 3.43 Area of Fertilizer Application by type of Fertlizer Mostly Compost, 14,402, 2% Mostly Farm Yard Manure, 137,161, 14% Mostly Inorganic Fertilizer, 20,380, 2% No Fertilizer Applied, 785,481, 82% Chart 3.41 Planted Area of Improved Seeds - Shinyanga Without Improved Seeds, 697,741, 73% With Improved Seeds, 261,066, 27% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 38 Table 3.8 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Area Planted with Fertilizer (ALL TYPES) Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Planted Area Number of Households Planted Area Bariadi 6,857 25,192 1,064 2,158 0 27,350 77,393 182,648 Maswa 4,374 13,327 420 1,190 216 175 14,692 42,935 111,811 Shinyanga Rural 8,776 20,436 569 465 0 20,901 45,161 100,937 Kahama 14,913 38,280 2,314 3,538 6,722 18,336 60,154 81,074 197,060 Bukombe 4,611 16,482 1,553 3,169 358 931 20,582 52,643 132,870 Meatu 2,335 9,394 83 671 0 10,065 31,111 94,843 Shinyanga Urban 2,584 3,252 294 826 32 110 4,188 9,260 15,564 Kishapu 3,266 10,798 567 2,386 79 827 14,011 35,124 121,691 Total 47,716 137,161 6,864 14,402 7,407 20,380 171,943 374,699 957,423 The largest planted area with fertiliser (all types) was in Kahama district (60,154 ha, 35.0% of the total planted area with fertilizer in the region, followed by Bariadi (27,350, 16%), Shinyanga Rural (20,901 12%), Bukombe (20,582 12%), Maswa (14,692 9%), Kishapu (14,010 8%) and Shinyanga Urban (4,188, 2%) Table 3.8 and (Charts 3.60 and 3.61). Most annual crop growing households in Shinyanga do not use any fertiliser (312,714 households, 83%) (Map 3.37). The percentage of the planted area with applied fertilizer was highest for Cereals (73% of the planted area with fertilizer application. This was followed by Cash Crops (17%), Oil seeds and Nuts (6%) and Pulses (3%), (Chart 3.44). Other Crop types had insignificant area under fertilizer application. 3.5.4.1 Farm Yard Manure Use The number of households that applied farm yard manure in their annual crops was 47,716 and it was applied to 137,161 ha representing 14 percent of the total area planted during that season and 80 percent of the total planted area with fertiliser in the region. Cereals had the highest percent of the planted area applied with farm yard manure (73%), followed by Cash Crops 16%), Oil Seeds (6%), pulses (3%), fruits & vegetables (0.4%) and roots and tubers (1%) (Chart 3.44). The Proportion of area planted with farm yard manure show that, farm yard manure is mostly used in Shunyanga Urban (21%), of the total planted area in the district), followed by Shinyanga Rural and 20% other districts have lower than 15% of their total area planted with farm yard manure (Chart 3.45). 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.44 Percent of Crop type Planted Area with Farm yard Manure - Annual Crops Chart 3 45 Propotion of Planted Area Applied with Farm Yard Manure by District - SHINYANGA 0 20 40 60 80 100 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 39 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Shinyanga region was 20,389 ha which represents 2 percent of the total planted area with annuals in the region and 2.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertiliser on their annual crops was 7,407. The largest area applied with inorganic fertilisers was on Cereals (51% of the total area applied with inorganic fertilisers), followed by Cash Crops (41%). The proportion of the area applied with Inorganic Fertilizer at district level was very low ranging from 0 to 9% in Kahama district; (Chart 3.49). Chart 3.47 Planted Area with Inorganic Fertilizer by Crop type - SHINYANGA Cereals, 7,541, 51% Fruits & Vegetables, 104, 1% Oil Seeds & Oil Nuts, 393, 3% Pulses, 587, 4% Cash Crops, 6,015, 41% Roots & Tubers, 33, 0% 0 20 40 60 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.48 Percent of Crop type Planted Area with Inorganic Fertilizer - Annual Crops Chart 3 49 Propotion of Planted Area Applied with Inorganic Fertilizer by District - SHINYANGA 0 20 40 60 80 100 Bariadi Maswa Shinyanga Ru Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 40 3.5.4.3 Compost Use The total planted area applied with compost was 14,402 ha which represents only 2 percent of the total planted area with annual crops in the region and 8 percent of the total planted area with fertiliser in the region. The number of households that applied Compost on their annual crops was 6,864 (Table 3.8). Cereals had the highest percent of the planted area applied with Compost (73%), followed by Cash Crops 13%), Oil Seeds (5%), roots and tubers (5%) pulses (3%) and fruits & vegetables (1%) (Chart 3.50, 3.51). The proportion of the area applied with compost was very low for each district ranging from 0.5% lowest in Shinyanga Rural to 5.3% highest in Shinyanga Urban Districts (Chart 3.52). 3.5.5 Pesticides Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in Shinyanga region. Insecticides are the most common pesticide used in the region (85% of the total area applied with pesticides). This was followed by fungicides (11%) and herbicides (4%) (Chart 3.53). Chart 3.50 Planted Area with Compost by Crop type - SHINYANGA Cereals, 9,391, 73% Fruits & Vegetables, 100, 1% Oil Seeds & Oil Nuts, 668, 5% Pulses, 393, 3% Cash Crops, 1,609, 13% Roots & Tubers, 596, 5% 0 20 40 60 80 Percent of Planted Area . Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop type Chart 3.51 Percent of Crop type Planted Area with Compost - Annual Crops Chart 3 52 Propotion of Planted Area Applied with Compost by District - SHINYANGA 0.0 20.0 40.0 60.0 80.0 100.0 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Percent ' Chart 3.53 Planted Area (ha) by Pesticides Use Fungicide, 42,435, 11% Herbicide, 17,521, 4% Insecticides, 330,893, 85% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 41 Chart 3.54 Area of Irrigated Land Un- Irrigated Area, 947,157, 99% Irrigated Area, 10,266, 1% Chart 3.55 Proportion of Planted Area with Irrigation by District 0.0 25.0 50.0 75.0 100.0 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Percentage . 3.5.6 Harvesting Methods The main harvesting method for cereals was by hand. All other cereals (Maize Paddy, Sorghum, Bulrush Millet, and Finger Millet) were mainly harvested by hand. Like cereals, other annual Crops were also mainly harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 96 percent of the total area planted with cereals being threshed by hand. Draft animals, human powered tools and engine driven machines were scarcely used on threshing crops and the percentage area utilized was 1,1 and 3 respectively. 3.6 Irrigation Water is the limiting fact or to crop prod uction in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Shinyanga region, the area of annual crops under irrigation was 10,266 ha representing 1.1 percent of the total area planted (Chart 3.54). The district with the highest proportion of area under irrigation with annual crops was Shinyanga Urban 2 percent of the planted area with annual crops in the District. This is followed by Maswa (1.7%) and Bariadi (1.5%). Other districts had insignificant areas planted under Irrigation. (Chart 3.55 and Map 3.38). RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 42 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The most important stored crop was maize with 284,899 households storing 101,693 tonnes as of 1st October 2003. This was followed by Paddy (112,839 households, 55,481t), Groundnuts/ Bambaranuts (63,962 households, 10,223t) and Beans/Pulses (50,197 households, 5,247t). Other crops were stored in very small quantities (Chart 3.60). 3.7.1.1 Methods of Storage The region had 172,157 crop growing households storing their produce in sacks and/or open drums (55% of households that stored crops in the region). The number of households that stored their produce in locally made traditional structures was 132,594 (42%). This was followed by improved locally made structure (4,668 households, 1.5%), airtight drum (204 households, 0.1%), unprotected piles (1,801 households, 0.6%) and modern stores (936 households, 0.3%) (Chart 3.61). Storage in sacks and/or open drum was the dominant storage method in most districts, with kahama having the highest percent of households using this method (36% of the total number of households storing crop products). This was followed by Shinyanga Rural (18%), Bukombe (17%), Bariadi (11%), Kishapu (7%), Maswa (5%), Meatu (4%) and Shinyanga Urban (3%). The highest percent of households using improved locally made structures was in Bariadi and Bukombe districts (57% and 20% of the total number of households storing crops respectively), other districts had relatively small numbers of households using the method, (less than 10% each). (Chart 3.61). . Chart 3.60 Number of Households and Quantity stored by by crop type - Shinyanga 0 50,000 100,000 150,000 200,000 250,000 300,000 Maize Paddy Groundnuts/Bambara Nu Beans & Pulses Sorghum & Mille Cottton Crop Quantity Stored Number of Households Quantity stored (tons) Chart 3.61 Number of Households by Method of Storage and District (Based on the Most important household Crop) 0 10 20 30 40 50 60 70 80 90 100 Kahama Shinyanga Rural Buko mbe Bariadi Kis hapu Mas wa Meatu Shinyanga Urban District Number of Households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 43 3.7.1.2 Duration of `Storage Most households stored their produce for a period of 3 to 6 months (52% of the households storing crops) followed by those who stored for a period of Less than three months (26%) and those who stored their crop for a period of more than six months (22%), Chart 3.62). Most households stored Maize for a period of 3 to 6 months (52% of the households storing crops) followed by those who stored crops for a period of less than three months and those who stored their for a period of more than six months. The proportion of number of households that stored their produce for the duration of 3 to 6 months was highest in Bukombe district (64%) followed by Shinyanga Urban (58%), Shinyanga Rural (57%), Bariadi (52%), Kahama (52%), Meatu (44%), Maswa (42%) and Kishapu (38%) (Chart 3.63, Map 3.39). District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.64). However, households in Bariadi, Maswa and Bukombe Districts had proportionally stored little maize in comparison to the total quantity produced. Chart 3.62 Percent of Agricultural Households and Length of Storage of Crops by District 0 25 50 75 100 Less than 3 Months Between 3 and 6 Months Over 6 Months Length of Storage Percent Chart 3.63 Proportiont of Agricultural Households storing crops for a period of 3 to 6 Months by District 0 10 20 30 40 50 60 70 80 90 100 Bukombe Shinyanga Urba Shinyanga Rura Bariadi Kahama Meatu Maswa Kishapu District Percent Chart 3.64 Qunatity Stored and Propotion of Maize Stored to total production 0 10,000 20,000 30,000 40,000 50,000 60,000 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Quntity stored 0 10 20 30 40 50 60 70 80 90 100 Proportion Maize Production (tons) Proportion of Maize stored to Production ` RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 44 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet,) are mainly stored for household consumption. The percent of households that stored Crops for household consumption as the main purpose of storage was 95 percent, followed by seed for planting (3%) and selling at higher price (2%). A high percent of the households that stored pulses and groundnuts was for planting purpose (seeds) (8.5% and 12.8 respectively), Table 3.09. 3.7.1.4 The Magnitude of Storage Loss About 86 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are stored for seeds such as groundnut and bambara nuts. The proportion of households that reported a storage loss of more than a quarter was greatest for Maize and millets (4% of the total number of households that stored crops). This was followed by Beans & Pulses (2%), Paddy and Groundnuts both had scored 1% (Table 3.10). Table 3.09: Number of Households Storing Crops By Main Purpose of Storage and District Main Purpose District Food for the Household To Sell for Higher Price Seeds for Planting Other Total Bariadi 64,018 1,224 0 0 65,243 Maswa 24,475 209 1,188 0 25,873 Shinyanga Rural 40,721 203 605 0 41,528 Kahama 75,633 928 1,237 0 77,798 Bukombe 42,354 2,179 2,809 0 47,342 Meatu 23,048 273 388 81 23,791 Shinyanga Urban 6,216 52 250 32 6,550 Kishapu 22,398 0 3,003 0 25,401 Total 298,864 5,068 9,480 113 313,525 % 95 2 3 0 100 Table 3.10: Number of Households Storing Crops by Estimated Storage Loss and Crop Estimated Storage Loss Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Crop Number of House holds % Number of House holds % Number of House holds % Number of House holds % Total Maize 243,033 85.3 31,313 11.0 8,708 3.1 1,845 0.6 284,899 Paddy 108,487 95.9 3,067 2.7 1,529 1.4 0 0.0 113,083 Sorghum & Millet 35,913 82.6 5,858 13.5 1,448 3.3 272 0.6 43,490 Beans & Pulses 47,291 92.6 2,828 5.5 677 1.3 251 0.5 51,047 Groundnuts/Bambara Nuts 60,951 94.9 2,344 3.6 840 1.3 95 0.1 64,230 Chart 3.91a Households Processing Crops Households not Processing, 49,026, 13% Households Processing, 328,832 , 87% Chart 3.91b Percentage of Households Processing Crops by District 0 20 40 60 80 100 120 Kahama Shinyanga Rural Bukombe Bariadi Meatu Kishapu Maswa Shinyanga Urban District Percent of Households Processing RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 45 3.7.2 Agro-processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Shinyanga region (328,832 households, 87% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high (above 80%) in most districts except Kishapu (79%), Maswa (75%) and Shunyanga Urban 42% (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines (221,237 households, 67% of households processing crops). This was followed by those processing on-farm by hand (51,589 households, 16%), by trader (42,017 households, 13%) and on farm by machine (10,071 households, 3%). Although processing by neighbours machine was the most common processing method in all districts in Shinyanga region, district differences existed. Kahama had a higher percent of hand processing on farm than other districts (43%), followed by Meatu (17%), Shinyanga Rural (13%) and Bariadi (12%). Processing by trader was mostly practised in Shinyanga Rural (39%) , Bukombe (32%), Bariadi (15%) and Maswa (12%), whilst processing on farm by machine though small, was more prevalent in Bariadi and Kishapu (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, main product and by-product. The main product is the major product after processing and the by- product is secondary product after processing. For example the main product after processing maize is normally flour whilst the by-product is the bran. Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District ' Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Chart 3.93 Percent of Households by Type of Main Processed Product Grain, 103,903 , 32% Oil, 2,929 , 1% Juice, 161 , 0% Other, 81 , 0% Pulp, 175 , 0% Flour / Meal, 218,022 , 67% Chart 3.94 Number of Households by Type of By- product Fiber, 362 , 0% Other, 313 , 0% Husk, 3,807, 8% Bran, 101,742 , 63% Pulp, 1,576, 3% Shell, 12,174 , 7% Oil, 473 , 0% Pulp, 590 , 0% Juice, 531 , 0% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 46 The main processed product was flour/meal with 218,022 households processing crops into flour (67%) followed by grain with 103,903 households (32%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 50 percent of the households processing crops. The most common by-product produced by crop processing households was bran (101,742) households 62%), followed by Husk (46,899 households, 29%), shell 12,174 households, 7%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were mainly used for household/human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which was reported by 98 percent of the total households that used primary processed product (Chart 3.95). Out of 15,132 households that sold processed products, 5,424 (36% of the total number of households selling processed products in the region) were from Kahama followed by Meatu (2,606 households, 17%), Bukombe (2,106 households, 14%), Maswa (1,826 Households, 12%), Shinyanga Rural (1,105 households, 7%), Bariadi districts (1,058 households, 7%), Kishapu (722 households, 5%) and Shinyanga Urban (403 households, 2%) (Chart 3.96). Compared to other districts in Shinyanga region, Meatu district had the highest proportion of households that sold processed products (10%). This is followed by Kahama, 7%, Shninyanga Urban, 7% and Maswa (6%). Other districts had lower that 5% of the number of agricultural households selling processed products.. 0.00 10.00 20.00 30.00 40.00 Percentage of household Kahama Meatu Bukombe Maswa Shinyanga Rural Bariadi Kishapu Shinyanga Urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.95 Number of Households and use of processed product Did Not Use, 1,806 , 1% Fuel for Cooking, 898 , 0% Animal Consumption, 819 , 0% Sale Only, 2,352 , 1% Household /Human Consumption, 322,958 , 98% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 47 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (5,874 households, 38% of households that sold processed crops). This was followed by selling to Local Markets/ Trade Store (3,453 households, 23%), Marketing Cooperatives (2,118 households, 14), Famers Association (1,091 households, 7%), Trade at Farm (1,020 households, 7%), Other unspecified Markets (594 households, 4%), Secondary Markets (531 households, 4%) and large scale farms (451 households, 3%) (Chart 3.97). There were large differences between districts in t he proportion of households selling processed products with Kahama district having the largest percent of households in the region selling to neighbours (51%) as well as selling to local markets or trade stores. Maswa district had a higher percent of households relying on secondary markets. (Chart 3.98). 3.7.3 Crop Marketing The number of households that reported selling crops was 219,317 which represents 58 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Maswa (79%) followed by Bariadi (66%), Meatu (59%), Kahama (59%), Bukombe (54%), Kishapu (59%), Shinyanga Rural (44%) and Shinyanga Urban (8%) (Chart 3.99 and Map 3.40). Chart 3.97 Location of Sale of Processed Products Farmers Association, 1,091 , 7% Trader at Farm, 1,020 , 7% Other, 594 , 4% Secondary Market, 531 , 4% Marketing Co- operative, 2,118 , 14% Local Market / Trade Store, 3,453 , 23% Neighbours, 5,874 , 38% Large Scale Farm, 451 , 3% Chart 3.98 Number of households Selling Processed Products by Main outlet sale and District 0 800 1,600 2,400 3,200 Kahama Bukombe Maswa Bariadi Shinyanga Rural Kishapu Shinyanga Urban Meatu District . Number of Households Neighbours Local Market / Trade Store Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 15,000 30,000 45,000 60,000 Bariadi Kahama Maswa Bukombe Shinyanga Rural Meatu Kishapu Shinyanga Urban District Number of Househo 0.0 20.0 40.0 60.0 80.0 100.0 Percent Number of Households Selling Crops Percent of Households Selling Crops RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 48 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketin g problem reported by households (75% of crop growing households that reported main marketing problems). Apart from low market prices, other problems were long distances to the markets (7%), high transport costs (6%), lack of transport (4%), lack of market information (2%), Trade union Problems (2%) and the government regulatory Boards problems (1%). Other marketing problems are minor, representing less than 1 percent of the total reported problems (Chart 3.100). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 87 percent of the smallholders. The proportion of households reporting other reasons for not selling were extremely low (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credits The census results shows that very few agricultural households (7,054, 2%) in Shinyanga region accessed credit, of which 5,402 (77%) were male-headed households and 1,651 (24%) were female headed households. The number of those who accessed credits was higher in Bariadi (31%) followed by Kahama (31%), Bukombe (12%) and Maswa (12%). Other Districts have less than 10% of those who accessed credits, (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 160,445 87 Other 12,481 7 Price Too Low 7,925 4 Trade Union Problems 1,503 1 Co-operative Problems 1,427 1 Government Regulatory Board Problems 905 0 Market Too Far 442 0 Total 149,005 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Bariadi 1,733 77 525 23 2,258 Maswa 650 75 217 25 867 Shinyanga Rural 100 25 302 75 401 Kahama 2,040 94 137 6 2,177 Bukombe 716 86 119 14 836 Meatu 81 33 165 67 246 Shinyanga Urban 0 0 23 100 23 Kishapu 82 33 164 67 245 Total 5,402 77 1,651 23 7,054 Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Open Market Price Too Low 74% Co-operative Problems 1% No Transport 4% Trade Union Problems 2% Market too Far 6% Transport Cost Too High 6% Other 4% Lack of Market Information 2% Farmers Association Problems 0% Government Regulatory Board Problems 1% Bukombe Kahama Shinyanga Urban Bariadi Maswa Kishapu Shinyanga Rural Meatu 299ha 291ha 302ha 1,505ha 157ha 66ha 646ha 589ha 96.9% 70.7% 91.3% 93.2% 50% 62.9% 84.8% 66.5% 1,200 > 900 to 1,200 600 to 900 300 to 600 0 to 300 Bariadi Maswa Shinyanga Rural Kishapu Meatu Shinyanga Urban Bukombe 155,298ha 97,119ha 11,430ha 86,259ha 107,681ha 80,035ha 136,906ha 112,530ha 85% 86.9% 89.4% 88.5% 73.1% 79.3% 69.5% 84.5% Kahama 120,000 > 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Map 3.23 SHINYANGA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Tanzania Agriculture Sample Census Planted Area with No Fertilizer Applied Percent of Planted Area with No Fertilizer Applied Planted Area With Irrigation Map 3.24 SHINYANGA RESULTS 49 Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area with No Fertilizer Applied Percent of Planted Area With Irrigation Planted Area With Irrigation Shinyanga Urban Bariadi Maswa Kishapu Shinyanga Rural Meatu Kahama Bukombe 770 51,136 34,296 18,658 17,952 19,829 47,924 28,751 7.6 65.9 79.3 59.2 50.4 43.8 59 54 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Selling Crops Map 3.25 SHINYANGA Number of Households and Percent of Total Households Selling Crops by District Percent of Total Households Selling Crops Number of Households Selling Crops RESULTS 50 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 51 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Shinyanga region were Family, Friends and relatives Religious which collectively provided credit to 2,233 agricultural households (32% of the total number of households that accessed credit), followed by Savings and Credit Society (21%), Religious Organisations (20%), Traders/ Trade Store (15%) and Commercial Banks (1%). (Chart 3.101). (Chart 3.102). 3.8.1.2 Use of Agricultural Credits A large proportion of the agricultural credit provided to agricultural households in the region was used on purchase of Agrochemicals (28%), followed by purchasing Seeds (21%), hiring labour (16%), Purchasing tools and Equipment (12%), and on purchasing fertilizers (12%) (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credits The main reason for not using agricultural credit as a source of finance was little credit awareness accounting for 57 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by “non-availability of credit” reported by 20 percent of households and “not wanting to go into debt” (11%), Credit not wanted (6%). The rest of the reasons collectively accounted for less than 10 percent of the agricultural households (chart 3.104). Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Commercial Bank 27% Religious Organisation / NGO / Project 36% Family, Friend and Relative 30% Saving & Credit Society 7% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 16% Labour 35% Other 16% Agro-chemicals 4% Tools / Equipment 13% Seeds 16% Chart 3.104 Reasons for not Using Credit (% of Households) Did not know how to get credit, 132,023, 41% Don't know about credit, 69,551, 22% Not available, 64,325, 20% Did not w ant to go into debt, 27,138, 8% Difficult bureaucracy procedure, 7,190, 2% Not needed, 8,910, 3% Credit granted too late, 2,657, 1% Other, 2,465, 1% Interest rate/cost too high, 7,702, 2% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 52 3.8.2 Crop Extension The number of agricultural households that received crop extension was 104,252 (28% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Kishapu having a relatively high proportion of households that received crop extension messages (51%) followed by Meatu (47%), Kahama (36%), Shinyanga Urban (33%), Shinyanga Rural (27%), Bariadi (21%), and Bukombe (14%), (Chart 3.106 and Map 3.41). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (97%). NGOs provided 2.43 percent, large scale farms 0.33 percent and the remaining providers less than 0.24 percent (Chart 3.107), however district differences exist with the proportion of the households receiving advice from government services ranging from 98 percent in Shinyanga Urban, Kahama and Bukombe districts to 87 percent in Maswa district. 3.8.2.2 Quality of Extension29/01/2007 An assessment of the quality of extension indicates that 64 percent of the households receiving extension ranked the service as being “good” followed by “Average” (20%) and “very good (13%). Very few households reported the services to be “poor” (2.7%) and “no good” (0.3%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Receiving Extension , 132,389, 41% Households Not Receiving Extension , 191,331, 59% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 60,000 Dodoma Rural Kongwa Dodoma Urban Mpwapwa Kondoa District Number of Households 0 20 40 60 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Government 98.5% Other 0.6% NGO / Development Project 0.8% Large Scale Farm 0.2% Chart 3.108 Number of Households Receiving Extension by Quality of Services Very Good, 20,687, 15.8% No Good, 1,528, 1.2% Poor, 2,731, 2.1% Average, 19,865, 15.2% Good, 86,304, 65.8% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 53 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Shinyanga regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, the figures presented in this section may be different from the previous section on inputs (Section 2.6). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Shinyanga region, improved seeds is used by 118,404 households which represents 31 percent of the total number of crop growing households. This is followed by households using farm yard manure (23%), pesticide/fungicide (21%), compost (4%) and inorganic fertiliser (3%). The number of Households with access to herbicides was very small which is 3 for every 1000 agricultural households (Table 3.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Shinyanga region mostly purchase it from Cooperative Unions (59%) and local markets/trade stores (38% of the total number of households using inorganic fertiliser). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Most households access inorganic fertilizers from a distance of less than 1 kilometres (39%), followed by between 1 and 3 km (21%), between 3 and 10 km (18%), between 10 and 20 km (11%) and those who reside at distance of more than 20 km were 1,121 (10%), (Chart 3.110). Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 88,413 23 289,758 77 Improved Seeds 118,404 31 259,372 69 Pestcides/Fungicide 81,034 21 296,824 79 Compost 14,316 4 363,429 96 Inorganic Fertiliser 10,730 3 367,127 97 Herbicide 1,188 0 376,549 100 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 1,526 388 382 0 400 800 1,200 1,600 Local Market / Trade Store Locally Produced by Household Neighbour Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 54 Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “non available” (31%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using. Other reasons such as costs are more important with 60 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and fertiliser would become more accessible. More smallholders use inorganic fertilisers in Kahama than in other districts in Shinyanga region possibly because of the predominance of tobacco farming in the district, (79% of households using inorganic fertilisers). 3.9.3 Improved Seeds The percent of households that used improved seeds was 31 percent of the total number of crop growing households. Most of the improved seeds are from Cooperatives (41%). Other less important sources of improved seed are Local Market/ Store (27%) and Crop Buyers (22%). Other Sources of Improved Seeds are not significant (Chart 3.111). Access to improved seeds is equally same situation as access to chemical inputs with 35 percent of households obtaining the input within 1 km of the homestead (Chart 3.112) compared to 39 percent for chemical inputs. The higher use of improved seeds (31%) compared to other inputs is an indication that the availability is not the main prohibiting factor for the use of inputs but rather other factors such as cost. The district that mostly uses improved seeds is Bariadi with 29 percent of the total number of households using improved seeds in Shinyanga region, followed by Maswa (18%), Kahama (16%), and Kishapu (14%). Percents of the crop growing households in Bukombe, Meatu, Shinyanga Rural and Shinyanga Urban districts that used improved seeds were 9,4 and 1 percent respectively (Map 3.42). Chart 3.111 Number of Households by Source of Improved Seeds 57.5 22.0 12.9 3.3 1.9 1.1 0.7 0.6 0 5,000 10,000 15,000 20,000 Local Market / Trade Store Development Project Neighbour Locally Produced by Household Secondary Market Local Farmers Group Large Scale Farm Crop Buyers Source of Improved Seeds Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Improved Seeds 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 55 3.9.4 Insecticides and Fungicides The percent of households that used Insecticides/Fungicides was 21 percent of the total number of crop growing households. Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (60% of the total number of households using insecticides/fungicides), followed by Cooperatives (29%). Other sources of insecticides/Fungicides were not significant (Chart 3.113). Chart 3.114 shows that the number of agricultural households (31% of the crop growing households which used insecticides and fungicides) obtained the inputs from the distance of 3 to 20 kilometres. The small number of households using insecticides/fungicides coupled with the 8 percent of households responding to “non availability” as the reason for not using fungicides, may lead to the assumption that access is not the main reason for not using. Other reasons such as costs are more important with 76 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be improved. Fungicide is mostly used in Bariadi district with 36 percent of the total number of households using fungicide, followed by Kahama (22%), Bukombe (15%), Meatu (11%), Maswa (6%) and Kishapu (6%). Shinyanga Rural and Urban Districts had the smallest number of households using Insecticides/ Fungicides which was 3 and 1 Percent Respectively. Chart 3.113 Number of Households by Source of Insecticide/fungicide 58.5 34.0 6.0 1.4 0 2,000 4,000 6,000 Local Market / Trade Store Development Project Neighbour Secondary Market Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0.0 15.0 30.0 45.0 60.0 75.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 56 Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 5 4 3 4 28 0 5,000 10,000 15,000 20,000 25,000 Kondoa Mpwapwa Dodoma Urban Dodoma Rural Kongwa District Number of Households 0 6 12 18 24 30 Percent Number of Households Percent 3.10 Tree Planting The number of households involved in tree farming was 13,645 representing 4 percent of the total number of agriculture households (Chart 3.115). The Common tree species planted by smallholders on their allotted land were Leucena Sp (51%), Gravelli (21%), Acacia (12%) and Azadritachta Spp. In Shinyanga Region Smallholders plant trees mostly scattered on Field. The proportion of trees that are planted Scattered on field is 53 percent, followed by trees planted on field boundaries 38% and tress in Plantation accounted for 9% of all planted trees in the region. 3.11 Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms in Shinyanga region was 15,199 which represent 4 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Shinyanga Rural (7%) followed by Shyinyanga Urban (7%), Bariadi (5%), Kahama (4%), Kishapu (3%), Maswa (3%), Meatu (2%) and Bukombe (1%) (Chart 3.121 and Map 3.44). Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 33,336, 10% Households Without Facilities, 290,383, 90% Chart 3.115 Number of Households with Planted Trees - DODOMA Households without Planted Trees, 301,411, 93% Households withPlanted Trees, 22,308, 7% Bariadi Meatu Maswa Kishapu Shinyanga Rural Shinyanga Urban Kahama Bukombe 34,676 11,043 21,630 1,182 16,184 4,475 18,491 10,723 44.7% 35.1% 50% 45.5% 11.6% 9.9% 22.8% 20.1% 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Kishapu Meatu Bariadi Maswa Shinyanga Rural Shinyanga Urban Kahama Bukombe 18,190 3,364 14,761 16,641 2,469 12,421 29,021 7,386 51.1% 46.9% 21.5% 5.7% 33% 27.4% 35.7% 13.9% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.26 SHINYANGA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Tanzania Agriculture Sample Census Number of Households Percent of Households Receiving Crop Extension Services Crop Growing Households Using Improved Seed Map 3.27 SHINYANGA Number and Percent of Crop Growing Households using Improved Seed by District Percent of Crop Growing Households Using Improved Seed Growing Households Using Improved Seed Number of Households Receiving Crop Extension Services RESULTS 57 Maswa Kishapu Shinyanga Rural Bariadi Meatu Shinyanga Urban Kahama Bukombe 9 24 9 10 37 26 11 13 6.5% 17.3% 6.5% 7.2% 26.6% 18.7% 7.9% 9.4% Map 3.28 SHINYANGA Number and Percent of Smallholder Planted Trees by District Tanzania Agriculture Sample Census Number of Households Planted Trees Percent of Smallholder PlantedTrees Number of Smallholder Planted Trees 32 to 40 24 to 32 16 to 24 8 to 16 0 to 8 RESULTS 58 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 59 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 2,604,105 which has the largest cattle population in the Country regional wise. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region ranked 1st out of 21 Mainland regions and had 15.5 percent of all cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Shinyanga region was 2,591,532 (99.5 % of the total number of cattle in the region), 1,375 cattle (0.1%) were Beef breeds and 11,198 cattle (0.4%) were Diary breeds. The census results show that 148,216 agricultural households in the region (39% of total agricultural households) kept 2.6 million cattle. This was equivalent to an average of 17.6 heads of cattle per cattle-keeping- household. The district with the largest number of cattle was Bariadi which had about 544, 496 heads of cattle (21% of the total cattle in the region). This was followed by Kahama (409,991 cattle, 16%), Meatu (334,099 cattle, 13%), Bukombe (332,685 cattle, 13%), Shinyanga Rural (317,785 cattle, 12%), Maswa (312,274, 12%) and Kishapu (292,978 11%). Shinyanga Urban district with 59,788 cattle, 2% had the least number of cattle in the Region. However Shinyanga Urban district had the highest density (1,467 head per km2 ) (Chart 3.123, Map 3.48). The Region was mostly dominated by indigenous breeds and had a small number of improved cattle which was 12,573 (0.48%) or 5 in every 1,000 heads of cattle. A small number of improved dairy (3,039) and beef (537) cattle was found in Bariadi district. The number of dairy and beef cattle was insignificant in other Districts. (Chart 3.124). - 100 200 300 400 500 600 Number of Cattle ('000' Bariadi Kahama Meatu Bukombe Shinyanga Rural Maswa Kishapu Shinyanga Urban Districts Chart 3.123 Total Number of Cattle ('000') by District 0 100,000 200,000 300,000 400,000 500,000 600,000 Number of Cattle ('000') Bariadi Kahama Bukombe Meatu Shinyanga Rural Maswa Kishapu Shinyanga Urban Districts Chart 3.124 Total Number of Cattle ('000') by District Indigenous Beef Dairy RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 60 3.12.1.2 Herd Size Twenty three percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 27 percent of all cattle in the region. Only 13 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 87 percent of total cattle rearing households had herds of size 1- 30 cattle and owns 63 percent of total cattle in the region, resulting in an average of 11 cattle per cattle rearing household. There were about 610 households with a herd size of more than 151 cattle each (200,121 cattle in total) resulting in an average of 328 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Shinyanga increased during the eight years period from 2,262,809 in 1995 to 2,604,105 cattle in 2003. This trend depicts an overall annual positive growth rate of 1.77 percent (Chart 3.125). There was a very sharp increase in number of cattle for the period of four years from 1995 to 1999 at the rate of 13.67 percent whereby the number increased from 2,262,809 to 3,778,255. However, the number of cattle decreased from 3,778,255 in 1999 to 2,604,105 in 2003 at the negative decrease rate of - 8.88 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Shinyanga region was 12,573 (11,198 dairy and 1,375 improved beef). The diary cattle constituted 0.43 percent of the total cattle and 90 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 10 percent of the total number of improved cattle and 0.05 percent of the total cattle. The time series information to facilitate time series analysis for this category of cattle is not available. 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, the region ranked 2 out of 21 Mainland regions and had 11 percent of all Goat on Tanzania Mainland. 2,262,809 3,778,255 2,604,105 - 1,000,000 2,000,000 3,000,000 4,000,000 Number of Cattle ' 1995 1999 2003 Year Chart 3.125 Cattle Population Trend RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 61 3.12.2.1 Goat Population The number of goat-rearing-households in Shinyanga region was 124,019 (33% of all agricultural households in the region) with a total of 1,277,929 goats giving an average of 10 head of goats per goat-rearing-household. Bariadi had the largest number of goats (229,817 goats, 18% of all goats in the region), followed by Meatu (215,670 goats, 17%), Maswa (209,359 goats, 16%), Kishapu (189,543 goats, 15%), Shinyanga Rural (154,348 goats, 12%), Kahama (140,846 goats, 11%) and Bukombe (106,926, 8%). Shinyanga Urban district had the least number of goats (31,434 goats, 2%) (Chart 3.127 and Map 3.49). However Shinyanga Urban district had the highest density (471 head per km2 ) (Map 3.50). 3.12.2.2 Goat Herd Size Twenty nine percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Seventy eight percent of total goat-rearing households had herd size of 1-14 goats and owned 46 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 2,914 households (2.4%) with herd sizes of 40 goats or more each (183,695 goats in total), resulting in an average of 63 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 99.4 percent of the total goats in Shinyanga region. Improved goats for meat and diary goats constituted 0.5 and 0.1 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 0.92 percent. The positive rate of increase indicates goat population increase from 1,187,706 in 1995 to 1,277,929 in 2003. The number of goats increased from 1,187,706 in 1995 at an estimated annual rate of 14.30 percent to 2,026,929 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -10.89 percent (Chart 128). Chart 3.127 Total Number of Goats ('000') by District - 50 100 150 200 250 Bariadi Meatu Maswa Kishapu Shinyanga Rural Kahama Bukombe Shinyanga Urban District Number of Goats ('000') 1,187,706 2,026,845 1,277,929 - 1,000,000 2,000,000 3,000,000 Number of Goatas ' 1994/95 1998/99 2002/03 Year Chart 3.128 Goat Population Trend Bukombe Meatu Maswa Shinyanga Rural Bariadi Kishapu Shinyanga Urban Kahama 81.1 113.1 195.3 232.5 149.3 144.2 115.4 263.6 190,000 to 230,000 150,000 to 190,000 110,000 to 150,000 70,000 to 110,000 30,000 to 70,000 Maswa Bariadi Meatu Kishapu Shinyanga Urban Shinyanga Rural Bukombe Kahama 312,274 59,788 544,496 334,099 292,987 317,785 409,991 332,685 400,000 > 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Map 3.29 SHINYANGA Cattle population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Cattle Number of Cattle Number of Cattle Per Square Km Map 3.30 SHINYANGA Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km RESULTS 62 Shinyanga Urban Shinyanga Rural Maswa Bariadi Kishapu Kahama Bukombe 189,543 31,434 229,817 106,926 215,670 140,846 154,334 209,359 Meatu 184,000 to 230,000 138,000 to 184,000 92,000 to 138,000 46,000 to 92,000 0 to 46,000 Kahama Bukombe Bariadi Meatu Kishapu Shinyanga Urban Shinyanga Rural 43.4 51 63 66.9 73 69.3 23 Maswa 835.6 680 to 850 510 to 680 340 to 510 170 to 340 0 to 170 Map 3.31 SHINYANGA Goat population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Goat Number of Goat Number of Goat Per Square Km Map 3.32 SHINYANGA Goat Density by District as of 1st October 2003 Number of Goat Per Square Km RESULTS 63 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 64 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Shinyanga region after cattle and goats. The region ranked 2 out of 21 Mainland regions and had 13 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 58,545 (15% of all agricultural households in Shinyanga region) rearing 517,144 sheep, giving an average of 9 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Kishapu with 131,296 sheep (25% of total sheep in Shinyanga region) followed by Maswa (106,969 sheep, 21%), Meatu (95,895 sheep, 19%), Bariadi (78,539 sheep, 15%), Shinyanga Rural (53,163 sheep, 10%), Kahama (30,133 sheep, 6%). Shinyanga Urban and Bukombe Districts had the least number of sheep in the region which was 12,403, 2% and 8,745, 2% sheep respectively (Chart 3.129 and Map 3.51). Maswa district also had the highest density (67 head per km2 ) (Map 3.52). Sheep rearing was dominated by indigenous breeds that constituted 100 percent of all sheep kept in the region. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the shee p population for the eight year period from 1995 to 2003 is estimated at 0.72 percent. The population increased at an annual rate of 14.11 percent from 488,267 in 1995 to 517,144 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -11.10 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 19 out of 21 Mainland regions and is 0.3 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Shinyanga region was 656 (1% of the total agricultural households in the region) rearing 3,266 pigs. This gives 488,267 827,930 517,144 - 200,000 400,000 600,000 800,000 1,000,000 Number of Sheep ' 1994/95 1998/99 2002/03 Year Chart 3.130 Sheep Population Trend Chart 3.129 Total Number of Sheep ('000') by District 0 30 60 90 120 150 Kishapu Maswa Meatu Bariadi Shinyanga Rural Kahama Shinyanga Urban Bukombe District Number of Sheep ('000') Chart 3.131 Total Number of Pigs by District 0 300 600 900 1,200 1,500 1,800 2,100 Bariadi Kahama Meatu Shinyanga Urban Kishapu District Number of Pigs RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 65 2,771,534 3,747,129 2,979,590 - 1,000,000 2,000,000 3,000,000 4,000,000 Number of Chicken 1994/95 1998/99 2002/03 Year Chart 3.134 Chicken Population Trend an average of 5 pigs per pig-rearing household. The district with the largest number of pigs was Shinyanga Urban with 1,931 pigs (59% of the total pig population in the region) followed by Meatu (736 pigs, 23%). Other District (Bariadi, Kahama and Kishapu) had insignificant number of Pigs. However, Shinyanga Urban district had the highest density (9 head per km2) (Map 3.54). The Sample Census could not enumerate any pigs from Maswa, Bukombe and Shinyanga Rural Districts, (chart 3.131). 3.12.5 Chicken Production The poultry sector in Shinyanga region was dominated by chicken. The region contributed 9 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 257 ,044 raising about 2,979,590 chickens. This gives an average of 12 chickens per chicken-rearing household. In terms of total number of chickens in the country, Shinyanga region was ranked first for having the largest number of chicken out of the 21 Mainland regions. The District with largest number of chickens was Bariadi (872,294 chickens, 29% of the total number of chickens in the region) followed by Shinyanga Rural (551,354, 19%), Maswa (405,569, 14%), Shinyanga Urban (383,126 13%), Meatu, (309,349, 10%), Bukombe, (229,146, 8%) and Kishapu, (187,361, 6%). Kahama district had the smallest number of chickens (40,890, 1%) (Chart 3.133 and Map 3.55). However Shinyanga Urban district had the highest density (1,689 head per km2) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 0.91 percent. The population increased at a rate of 7.83 percent from 1995 to 1999 after which it decreased to -5.57 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Shinyanga region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. Chart 3.133 Total Number of Chicken ('000') by District 0 100 200 300 400 500 600 700 800 900 1,000 Bariadi Shinyanga Rural Maswa Shinyanga Urban Meatu Bukombe Kishapu Kahama District Number of Chicken ('000') RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 66 3.12.5.3 Chicken Flock Size The results indicate that about 83 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 7 chickens per holder. About 16.8 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 39 chickens per holder. Only 0.2 percent of holders kept the flock sizes of more than 100 chickens at an average of 117 chickens per holder (Table 3.14). 3.12.5.4 Improved Chickens (layers and broilers) The number of Layers and Broiler chicken population in Shinyanga Region was 11,276 and 32,934 respectively. In comparison to the total human population of the region the number of improved chicken is not significant. 3.12.6. Other Livestock There were 94,783 ducks, 708 turkeys, 5,263 rabbits and 4,421 donkeys raised by rural agricultural households in Shinyanga region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Bariadi District (56% of all ducks in the region), followed by Shinyanga Rural (14%), Maswa (10%), Kishapu (5%) and Kahama (5%). Meatu and Shinyanga Urban Districts district had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Meatu , Bariadi and Shinyanga Urban districts only. Rabbits were only reported in Bariadi District and the number was 5,263. Donkeys were mostly reported in Bariadi 49%, Kahama 22%, Shinyanga Rural 14% and the least number donkeys was found in Kishapu and Shinyanga Urban (Table 3.15). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 68 percent and 9 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Meatu district. (Map 3.57). The most practiced method of tick controlling was spraying with 77 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (2%), smearing (1%) and other traditional methods like hand picking (8%). However, 13 percent of livestock- keeping households did not use any method. Table 3.14 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 54,834 21 156,753 3 5-9 82,532 32 546,340 7 10-19 77,801 30 999,425 13 20-29 25,519 10 564,268 22 30-39 9,060 4 285,517 32 40-49 2,448 1 105,425 43 50-99 4,350 2 263,212 61 100+ 501 0.19 58,649 117 Total 257,044 100 2,979,590 12 Table 3.15 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Bariadi 53,587 179 5,263 2,170 . Maswa 9,193 . . . 1,734 Shinyanga Rural 13,516 . . 612 1,487 Kahama 5,165 . . 981 1,715 Bukombe 4,063 . . . 3,734 Meatu 2,249 497 . . 2,637 Shinyanga Urban 1,851 32 . 415 . Kishapu 5,160 . . 244 632 Total 94,783 708 5,263 4,421 11,938 Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Bariadi Kahama Shinyanga Rural Meatu Maswa Kishapu Shinyanga Urban Bukombe District P ercent Tick problems Tsetse flies problems Maswa Kishapu Shinyanga Urban Shinyanga Rural Bukombe Meatu Bariadi 5.5 14.8 9.1 26.1 15 32.5 21.5 Kahama 578.8 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Kishapu Maswa Shinyanga Rural Bariadi Shinyanga Urban Bukombe 30,133 131,296 8,745 78,539 95,895 12,403 53,163 106,969 Kahama Meatu 120,000 to 140,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Map 3.33 SHINYANGA Sheep Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Sheep Number of Sheep Number of Sheep Per Square Km Map 3.34 SHINYANGA Sheep Density by District as of 1st October 2003 Number of Sheep Per Square Km RESULTS 67 Bariadi Kishapu Shinyanga Urban Shinyanga Rural Kahama Bukombe 0.1 0.2 0 0 0 0.1 0 Maswa Meatu 8.5 6.8 to 8.5 5.1 to 6.8 3.4 to 5.1 1.7 to 3.4 0 to 1.7 Bariadi Kishapu Shinyanga Urban Shinyanga Rural Bukombe 296 736 0 82 0 221 0 Kahama Maswa Meatu 1,931 1,600 to 2,000 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Map 3.35 SHINYANGA Pig Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Pig Number of Pig Number of Pig Per Square Km Map 3.36 SHINYANGA Pig Density by District as of 1st October 2003 Number of Pig Per Square Km RESULTS 68 Kahama Shinyanga Urban Maswa Kishapu Shinyanga Rural Bukombe 11.5 253.7 239.2 104.7 92.2 403.4 55.8 Meatu Bariadi 1,689 26,000 to 30,000 20,000 to 26,000 14,000 to 20,000 8,000 to 14,000 2,000 to 8,000 Maswa Shinyanga Rural Bukombe Meatu Kishapu Shinyanga Urban 405,569 551,354 383,126 229,146 40,890 872,794 309,349 187,361 Kahama Bariadi Map 3.37 SHINYANGA Chicken Population by District as of 1st Octobers 2003 Tanzania Agriculture Sample Census Number of Chicken Number of Chicken Number of Chicken Per Square Km Map 3.38 SHINYANGA Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km 800,000 to 1,000,000 600,000 to 800,000 400,000 to 600,000 200,000 to 400,000 0 to 200,000 RESULTS 69 RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 70 The most common method used to control tsetse flies was spraying which was practiced by 42 percent of livestock-rearing households This was followed by dipping (9%) and trapping (3%). However, 36 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 72,356 (43% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 13 percent, goats (37%) and sheep (5%), (chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 49,733 representing 28 percent of the total livestock-rearing households and 13 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 94 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (4%), Cooperatives (2%) and large-scale farmers (2%),. About 62 percent of livestock rearing households described the general quality of livestock extension services as being good, 19 percent said they were average and 17 percent said they were very good. However, 1 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Veterinary clinics were located very far from livestock rearing households. About 84 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 16 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected district was Bariadi district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Shinyanga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.141). 0 10 20 30 Percen Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Poor 1% Average 19% Very Good 17% No Good 1% Good 62% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 71 Chart 3.142 Number of Households by Distance to Village Watering Points 15 or more Kms 2% Less than 5 Kms 85% 5 - 14 Kms 13% 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 84,182 (85% of livestock rearing households in Shinyanga region) whilst 12,569 households (13%) resided between 5 and 14 kms. However, 1,555 households (2%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Shinyaga Urban district had the best livestock water supply with the majority of livestock rearing households (97%) residing within 5 kms from the nearest watering point. This is followed by Kahama (93%), Maswa (92%), Bukombe (92%), Shinyanga Rural (90%). Kishapu (83%), Bariadi (75%) and Meatu (66%). In Kishapu, Bariadi and Meatu districts there is a considerable number of households accessing water points at a distance of more than five kilometers from their residences, which is about 17, 25 and 34 percent respectively (Chart 3.143). Chart 3.141 Number of households by Distance to Veterinary Clinic and District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Bariadi Maswa Shinyanga Rur Kahama Bukombe Meatu Shinyanga Urb Kishapu District Number of Households Less than 14 Km More than 14 Km Chart 3.140 Percent of households by Distance to Veterinary Clinic More than 14 Km 84% Less than 14 Km 16% Chart 3.143 Percent of households by Distance to Village Watering Points and District 0 10 20 30 40 50 60 70 80 90 100 Shinyanga Urb Kahama Maswa Bukombe Shinyanga Rur Kishapu Bariadi Meatu District Number of Households Less than 5 Kms 5 - 14 Kms 15 or more Kms RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 72 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Shinyanga region was highly practiced with a total 246,196 (65%) agricultural households Practicing it (Chart 3.144). Kishapu, Shinyanga Rural and Bariadi Districts are the best in use of draft animals in farming practices with over 80% of all agricultural households in these districts using the method. The Percent of Agricultural households using this method in Maswa, Meatu and Shinyanga Urban was 79%, 78% and 86% respectively. The method was scarcely practiced in Kahama and Bukombe Districts (Chart 3.145 and Map 3.58). The region had 1,247,888 oxen (Bariadi 344,077 oxen, Shinyanga Rural 205,171 oxen, Kishapu 164,453 oxen, Maswa 162,943 oxen, Kahama 156,129 oxen, Meatu 137,537 oxen, Bukombe 44,749 oxen, Shinyanga Urban 32,829 oxen). This represents only 27 percent of the total oxen found on the Mainland. The total Area Cultivated by using oxen was 630,546 hectares of land (Bariadi 157,648 ha, Kishapu 103,484 ha, Maswa 94,038 ha, Shinyanga Rural 80,035 ha, Meatu 77,393 ha, Kahama 69,368 ha, Bukombe 36,302 ha, Shinyanga Urban 12,277 ha). The largest area cultivated using oxen was found in Bariadi district (157,648 ha, 25% of the total area cultivated using oxen in the region). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Shinyanga region was 83,843 (22% of total crop growing households in the region) (Chart 3.146). 3.144 Number of Households Using Draft Amimals Using Draft Animals, 246,196, 65.2% Not Using Draft Animals, 131,662, 35% 0 10 20 30 40 50 60 70 80 90 Number of Households Kishapu Shinyanga Rural Bariadi Maswa Meatu Shinyanga Urban Kahama Bukombe Chart 3.145 Number of Households Using and NOT using Draft Animals by District - SHINYANGA Using Draft Animals Not Using Draft Animals ` Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 83,843, 22% Not Using Organic Fertilizer, 291,423, 78% RESULTS – Livestock Production ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 73 The total area applied with organic fertiliser was 87,950 ha of which 82,243 hectares (94% of the total area applied with organic fertiliser) was applied with farm yard manure (Map 3.59). Farm Yard Manure was mostly applied in Kahama, Shinyanga Rural, Bariadi, Maswa and Bukombe Districts. 3.12.9.3 Use of Compost Only 5,707 ha (6% of the area of organic fertilizer application) was applied with compost. The largest area applied with Composit manure was found in Kahama district with 2,875 hectares followed by Bukombe (1,301 ha, 11%), (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Shinyanga region was very small (insignificant) which was 430, representing 0.1 percent of the total agricultural households in the region and fish farming was only reported in Kahama District. Chart 3.147 Area of Application of Organic Fertiliser by District - SHINYANGA 0 5,000 10,000 15,000 20,000 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu District Area of Fertiliser Applicatio Farm Yard Manure Compost Shinyanga Rural Bariadi Maswa Kishapu Meatu Shinyanga Urban Bukombe 39,760 6,894 67,493 34,293 31,630 32,470 8,972 87.8% 67.6% 87% 79.3% 78.4% 88.8% 40% 16.9% Kahama 24,684 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Bariadi Meatu Maswa Kishapu Shinyanga Rural Shinyanga Urban Kahama Bukombe 29,822 10,954 12,964 2,770 11,744 14,079 22,402 7,564 83.7% 70.8% 64% 60.9% 46.1% 70.9% 73.5% 42.1% 40,000 > 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.39 SHINYANGA Number and Percent of Households Infected with Ticks by District Tanzania Agriculture Sample Census Number of Households Infected with Ticks Number of Households Infected with Ticks Number of Households Using Draft Animals Map 3.40 SHINYANGA Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Percent of Households Infected with Ticks Percent of Households Using Draft Animals RESULTS 74 Shinyanga Urban Maswa Kishapu Shinyanga Rural Meatu Bariadi Kahama Bukombe 263ha 214ha 41ha 7ha 585ha 421ha 2,875ha 1,301ha 0.7% 4.6% 10.2% 3.7% 0.1% 7.4% 50.4% 22.8% 2,000 to 2500 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Bariadi Maswa Meatu Kishapu Shinyanga Urban Shinyanga Rural Kahama Bukombe 11,100ha 6,643ha 10,298ha 3,217ha 5,134ha 14,035ha 21,123ha 10,693ha 13.5% 8.1% 12.5% 6.2% 3.9% 17.1% 25.7% 13% 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Map 3.41 SHINYANGA Planted Area and Percent of Total Planted Area with Farm Yard Manure Application by District Tanzania Agriculture Sample Census Planted Area with Farm Yard Manure applied Planted Area with Farm Yard Manure applied Planted Area with Compost Manure Application Map 3.42 SHINYANGA Planted Area and Percent of Total Planted Area with Compost Manure Application by District Planted Area with Compost Manure Application Percent of Area Planted with Farm Yard Manure applied Percent of Area Planted with Compost Manure Application RESULTS 75 RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 76 Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 318,745 , 84% Flush Toilet, 12,686 , 3% No Toilet , 43,503 , 12% Other Type, 474 , 0% Improved Pit Latrine , 2,450 , 1% 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were Tarmac Road (68), Hospital (41), District Capital (39, Tertiary Market (34) Secondary School (19) Secondary Market (17), Primary Market (8), Health Clinic / Dispensary (8), All weather Road (7), Primary School (2), Feeder Road (2) Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 20 percent reported them to be average. Thirty percent of the agricultural households said the infrastructure and services were poor , and 25 percent said they were ‘no good’. 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (318,745 households, 84% of all rural agricultural households) 12,686 households (3%) use Flush Toilets and 2,450 households (1%) use Improved Pit Latrine. The remaining 474 household (0.13%) use other toilets facilities. However, 12,686 households (12%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 37 percent of them were found in Kahama District and 1 percent were from Shinyanga Urban District. The percentages of households without toilets in other districts were as follows Bariadi (21%), Maswa (12%), Shinyanga Rural and Bukombe Districts (10%), Kishapu (6%), and Bukombe (2%). Table 3.17: Mean distance from household dwelings to Infrastructures and services by District District Primary School Secondary School Health Clinic / Dispensar y Hospital District Capital Regional Capital Feeder Road All weather Road Tarmac Road Primary Market Secondary Market Tertiary Market Bariadi 3.1 14.9 5.2 31.7 34.0 163.9 2.4 13.9 114.0 8.5 20.7 27.9 Maswa 2.4 16.3 6.1 32.5 32.0 102.4 3.3 3.5 98.8 6.5 14.1 22.6 Shinyanga Rur 1.8 19.5 4.4 46.7 47.1 49.1 1.4 5.8 43.0 7.5 12.4 43.5 Kahama 2.1 21.0 11.2 44.7 44.6 147.7 1.7 8.0 35.9 6.4 15.7 40.4 Bukombe 2.4 18.7 10.7 52.2 40.3 196.3 2.0 3.9 14.8 7.2 13.5 23.3 Meatu 2.9 22.1 8.3 42.7 46.1 174.7 2.3 5.6 169.4 9.1 13.7 54.1 Shinyanga Urb 1.7 7.6 5.1 10.0 11.1 14.9 1.3 2.7 13.1 6.2 9.0 9.4 Kishapu 2.1 23.2 7.4 45.2 38.3 52.8 2.8 3.6 43.9 12.6 26.1 41.3 Total 2.4 18.6 7.7 40.9 39.3 130.6 2.2 7.1 68.3 7.9 16.5 34.2 Meatu Kishapu Maswa Bariadi Shinyanga Rural Shinyanga Urban Kahama Bukombe 0 0 0 0 0 0 430 0 0% 0% 0% 0% 0% 0% 0.5% 0% 360 to 430 270 to 360 180 to 270 90 to 180 0 to 90 Kishapu Bariadi Maswa Shinyanga Rural Meatu Shinyanga Urban Kahama Bukombe 2,714 9,310 5,344 473 892 4,145 16,227 4,398 7.6% 12% 12.4% 2.8% 4.6% 9.2% 20% 8.3% 12,000 > 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Map 3.43 SHINYANGA Number and Percent of Households Practicing Fish Farming by District Tanzania Agriculture Sample Census Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Number of Households Without Toilets Facilities Map 3.44 SHINYANGA Number and Percent of Households Without Toilets Facilities by District Number of Households Without Toilets Facilities Percent of Households Practicing Fish Farming Percent of Households Without Toilets Facilities RESULTS 77 RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 78 3.13.3 Household’s Assets Bicycles were owned by most rural agricultural households in Shinyanga region with 246,531 households (65% of the agriculture households in the region) owning the asset. followed by Radios ( 192,251 households, 51%), iron (64,449 households, 17%), wheelbarrow (39,393 households, 10%), mobile phone (5,725 households, 2%), television/video (3,692 households, 0.96), vehicle (4,236 households, 1.1%) and landline phone (858 households, 0.23%), (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting en ergy in the region. with 81 percent of the total rural households using this source of energy followed by hurricane lamp (14%), Pressure lamp (3%), Firewood and Electricity (1%). Other Means of lighting using Candles and Biogas are scarcely used in the region (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95 percent of all rural agricultural households in Shinyanga region. This is followed by charcoal (4%). The rest of energy sources accounted for 1 percent. These were bottled gas (0.05%), crop residues (0.64%), mains electricity (0.15%), livestock dung (0.26%), parrafin/kerosene (0.1%) and gas/biogas (0.05%), (Chart 3.154). 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 35 percent of the rural agricultural households. This was closely followed by iron sheets (33%) and grass/mud (30%), (Chart 3.155). Chart 3.155 Percentage Distribution of Households by Type of Roofing Material Concrete 0.1% Asbestos 0.3% Other 0.4% Grass / Leaves 35.1% Iron Sheets 33.2% Grass & Mud 30.4% Tiles 0.5% Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Wick Lamp, 302,123 , 81% Firewood, 5,044 , 1% Solar, 443 , 0% Candles, 785 , 0% Gas (Biogas), 498 , 0% Mains Electricity, 2,485 , 1% Hurricane Lamp, 54,233 , 14% Pressure Lamp, 12,214 , 3% Chart 3.152 Percentage Distribution of Households Owning the Assets 10 2 1 1 0 17 51 65 0 20 40 60 Bicycle Radio Iron W heelbarrow M obile phone V ehicle Television / V ideo Landline phone Assets Percent RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 79 Tiles (0.54%), os (0.28%) and Concrete (0.06%) roofing style were scarcely used in the region (Chart 3.155). Kishapu district had the highest percentage of households with grass/leaves roofing (83%) followed by Shinyanga Rural district (82%), Shinyanga Urban (76%), Maswa (75%), Kahama (71%), Meatu (70%), Bukombe (65%) and Bariadi (34%) (Chart 3.156 and Map 3.63). Bariadi district had the highest percentage of households with Iron Sheets roofing (64%) followed by Bukombe district (34%), Kahama District (28%), Meatu (28%), Maswa (25%), Shinyanga Urban (24%), Shimyanga Rural (17%) and Kishapu (14%) (Chart 3.156B and Map 3.63) Chart 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District 0 20 40 60 80 100 Kishapu Shinyanga Rural Shinyanga Urban Maswa Kahama Meatu Bukombe Bariadi District Percen Chart 3.156B Percentage Distribution of Households with Iron Sheets Roofs by District - 20 40 60 80 100 Bariadi Bukombe Kahama Meatu Maswa Shinyanga Urban Shinyanga Rural Kishapu District Percen RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 80 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Shinyanga region was unprotected Wells (33 percent of households use unprotected wells during the wet season and 31 percent of the households during the dry seasons). This is followed by protected wells (26% and 28% of households for wet and dry seasons respectively), Surface water (16% of households during the wet season and 19% in the dry season), Piped water (12% of households in the wet season and 13% during dry season). Other sources of drinking water like uncovered rain water catchments, Unprotected/protected Spring, Bottled Water, Water vendor and Tank truck are scarcely used in the region Chart 3.157) Bukombe District had the highest percent of Agricultural Households whose main source of drinking water was Unprotected wells (61% of households during the wet season and same number during dry season), followed by Kahama District 47% of households during the wet season and 48% in the dry season). About 44 percent of the rural agricultural households in Shinyanga region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 56 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). Chart 3.157 Percent of Households by Main Source of Drinking Water and Season - 10 20 30 40 Uprotected Well Protected Well Surface Water Piped Water Uncovered Rainwater Unprotected Spring Protected / Covered Bottled Water Covered Rainwater Water Vendor Tanker Truck Main source Percent of Household Wet Dry Chart 3.158 Percentof Households by Distance to Main Source of Drinking Water and Season - 10 20 30 40 Less than 100m 500 - 999 m 5 - 9.99 Km 300 - 499 m 3 - 4.99 Km 2 - 2.99 Km 10Km and above 100 - 299 m 1 - 1.99 Km Distance Percent Wet Serason Dry Season RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 81 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Shinyanga region normally have 3 meals per day (54 percent of the households in the region). This is followed by 2 meals per day (44 percent) and 1 meal per day (2 percent). A small number of Agricultural Households 0.27 percent normally have 4 meals per day (Chart 3.159). Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District One % Two % Three % Four % Total Bariadi 714 9 48,466 29 28,038 14 353 34 77,572 Maswa 1,607 20 13,758 8 27,886 14 - - 43,252 Shinyanga Rural 1,715 21 14,494 9 28,952 14 102 10 45,263 Kahama 561 7 34,903 21 45,609 23 144 14 81,217 Bukombe 956 12 38,793 23 13,492 7 - - 53,240 Meatu 2,310 28 9,744 6 19,229 10 209 20 31,492 Shinyanga Urban 71 1 2,537 2 7,527 4 64 6 10,198 Kishapu 239 3 4,352 3 30,870 15 163 16 35,624 Total 8,173 100 167,046 100 201,603 100 1,035 100 377,857 Number of Meals per day District Meatu district had the largest percent of households eating one meal per day whilst Kahama had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.64). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 214,120 (57% of the agricultural households in Shinyanga region) with 86,741 households (57% of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31%). Very few households had meat three or more times during the respective week. About 43 percent of the agricultural households in Shinyanga region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). Chart 3.159 Number of Agricultural Housedholds by Number of Meals per Day Three, 201,603 , 54% Two, 167,046 , 44% One, 8,173 , 2% Four, 1,035 , 0% Chart 3.160 Number of Households by Frequency of Meat and Fish Cosumption 0 25,000 50,000 75,000 100,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Househ Meat Fish RESULTS – Poverty Indicators ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 82 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 175,529 (46% of the total agricultural households in Shinyanga region) with 90,113 households (51 % of those who consumed fish) consuming fish only once during the respective week. This was followed by those who had fish twice (27%). In general, the percentage of households that consumed fish three times or more during the week in Shinyanga region was 38,375 (23% of the agricultural households that ate fish in the region during the respective period). About 54 percent of the agricultural households in Shinyanga region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66) 3.13.9 Food Security In Shinyanga region, 134,001 households (35% of the total agricultural households in the region) said they seldom experienced problems in satisfying the household food requirement. However 55,062 (14%) said they often experience problems, 38,789 always experienced problems and 6.4 percent sometimes had problems in satisfying the household food requirement. About 33 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main cash income of the households in Shinyanga region was from selling food crops (39.2 percent of smallholder households), followed by Sales of Cash Crops (31.8), Casual Cash earnings 13%), businesses income and Sales of Livestock each 4.9%. Other Means of income were Wages and Salaries (2.1%), Cash Remittances (1.1%), Sales of Forestry Products (1%), Sales of Livestock Products (1%) a and cash remittances (1%) and Fishing (1%)., (Chart 3.161) Chart 3.161: Percentage Distribution of the Number of Households by Main Source of Income Fishing, 0.2, 0% Sales of Food Crops, 39.2, 39% Other Casual Cash Earnings, 13.3, 13% Sales of Cash Crops, 31.8, 32% Business Income, 4.9, 5% Sale of Livestock, 4.9, 5% Wages & Salaries in Cash, 2.1, 2% Sale of Livestock Products, 0.9, 1% Sale of Forest Products, 1.0, 1% not applicable, 0.5, 1% Cash Remittance, 1.1, 1% Shinyanga Rural Shinyanga Urban Bariadi Maswa Kishapu Kahama Bukombe 7,527 28,952 28,038 27,886 19,229 30,870 45,609 13,492 4% 14% 14% 10% 15% 14% 23% 7% Meatu 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Shinyanga Urban Kahama Shinyanga Rural Kishapu Maswa Bariadi Bukombe 2,405 7,831 23,036 5,055 10,796 8,751 49,428 18,127 23.6% 17.3% 28.4% 14.2% 25% 27.8% 63.7% 34% Meatu 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.45 SHINYANGA Number and Percent of Households Using Grass/Leaves for Roofing RESULTS 83 Material by District Tanzania Agriculture Sample Census Households Using Iron Sheets for Roofing Material Households Using Iron Sheets for Roofing Material Households Eating 3 Meals per Day Map 3.46 SHINYANGA Number and Percent of Households Eating 3 Meals per Day by District Households Eating 3 Meals per Day Percent of Households Using Iron Sheets for Roofing Material Percent of Households Eating 3 Meals per Day Shinyanga Urban Kahama Shinyanga Rural Kishapu Maswa Bukombe Meatu Bariadi 3,351 7,786 7,779 6,223 24,634 18,589 6,311 15,442 10.9% 11.9% 10.9% 13.5% 1.9% 1.8% 14.6% 45.4% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Shinyanga Urban Shinyanga Rural Bukombe 3,547 16,218 11,315 26,425 24,736 10,575 9,431 18,863 2.9% 13.4% 9.3% 20.4% 21.8% 8.7% 7.8% 15.6% Kahama Maswa Kishapu Meatu Bariadi 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.47 SHINYANGA Number and Percent of Households Eating Meat Once per Week by District Tanzania Agriculture Sample Census Number of Households eating Meat Once per Week Number of Households eating Meat Once per Week Number of Households eating Fish Once per Week Map 3.48 SHINYANGA Number and Percent of Households Eating Fish Once Per Week by District Number of Households eating Fish Once per Week Percent of Households eating Meat Once per Week Percent of Households eating Fish Once per Week RESULTS 84 Kishapu Shinyanga Urban Maswa Shinyanga Rural Bariadi Meatu Bukombe 1,093 43,252 77,572 31,492 35,624 45,263 81,217 53,240 11.4% 2.7% 20.5% 8.3% 9.4% 12% 21.5% 14.1% Kahama Map 3.49 SHINYANGA Number and Percent of Households Reporting Food Insufficiency by District Tanzania Agriculture Sample Census Number of Households Reporting food insufficiency Number of Households Reporting food insufficiency Percent of Households Reporting food insufficiency 80,000 to 90,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 85 DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 86 4 SHINYANGA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Shinyanga Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. Shinyanga has the largest rural agriculture population in Tanzania (2,426,406 persons of which 1,240,181 are male and 1,186,224 female). It also has the highest number of rural agriculture households (377,857) which represents 96.4 percent of the number of rural households and 84.9 percent of the total number of households in the region (includes urban households). The region has the highest number of persons per household (6.4 per household) and one of the lowest percent of female headed households (14%). The crop farming only and mixed crop and livestock farming are equally important. The region has no pastoralists, however it has a moderate number of households involved in livestock herding only. Shinyanga region has similar number of males and females (51% males and 49% females). The region has a normal population pyramid with a wider base compared to other regions. The region has an active agriculture population of 1,209,803 of which 608,972 are males and 600,832 are females resulting in a moderate difference between the percent of total male and female active population in the region 50.3% and 49.7% respectively). The region has the highest number of households in the country compared to other regions (377,857 out of which 323,921 are male headed and 53,936 are female headed) and it has the 3rd lowest percent of female headed households compared to other regions in the country. The average household size is larger than the National average (6.7 members per household for male headed households and 4.8 for female headed households), resulting in a difference in the household size of 1.9 more members in male headed households compared to female headed households. There is no difference in the dependency ratio between male and female headed households (111 dependants for every 100 active members in male headed households and 112 dependants for every 100 active members in female headed households). The region has a small difference in sex ratio of the active agriculture population between male and female headed households compared to most other regions (109:100 in male headed households compared to 57:100 in female headed households). Shinyanga has the 18th largest difference in illiteracy rate between male and female household heads with an illiteracy rate of 31 percent of male household heads and 70 percent of female household heads. Taking the overall population of male and female members in the region there are 13 percentage points more illiterate females than males and this is the 4th largest difference in the country. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 87 Shinyanga has a moderate percent of orphans in the country compared to other regions and it has a higher percent of orphans in male headed households compared to female headed households. No orphan headed households were detected in Shinyanga. Shinyanga has around 4 percent of children with off farm income and there is no difference between male and female headed households. Shinyanga has the largest area of land under cultivation (over 1,250,000 ha) and has the highest land utilisation per household (over 2.6 hectares for annual crops). Virtually no permanent crops are grown and it has the largest area of pasture to supports the high population of cattle in the region. A large proportion of smallholder households in the region felt that they did not have sufficient land. The region has the largest planted area of maize and second largest for paddy and sorghum than other regions in Tanzania, however it had one of the lowest yields for maize during the census year. During the Census year planting was largely during the Wet season. The region is not important for cassava, beans and fruit and vegetable production but, it has the third largest planted area of groundnuts in the Tanzania. In terms of cash crops, Shinyanga is the most important region for cotton production. Considering Shinyanga has the largest planted area of crops, it has one of the smallest areas of irrigation. It also has the largest planted area cleared by hand but most soil preparation is done by oxen. Most of the planted area is without fertiliser and the small area that has, it is with farm yard manure. Low fertiliser use and lack of irrigation facilities may have contributed to the low yields for this region. Although small, it has the largest planted area with insecticide and fungicide application. Over half of the crops stored are in sacks or open drums with the remainder in locally made traditional structures. Crop processing is predominantly done by neighbours’ machines and the processed production is for home consumption. Considering Shinyanga is one of the most important crop growing regions, it only has moderate contact with extension services. The region relies more on animal draft than most other regions. The region has one of the smallest areas of planted trees per household and lowest percent of erosion control facilities in Tanzania. Shinyanga has the largest population of livestock in the country. It has the highest number of cattle and second highest head of goats with small sheep numbers and virtually no pigs (very small number compared to actual number of agricultural households). The region has the second highest density of cattle and the density of goats is moderate compared to Mwanza, Arusha, Kilimanjaro and Mara. It is the second largest milk producing region in the country and it has one of the lowest farm gate prices for milk. Very low numbers of improved livestock are found in the region. Shinyanga region has the 6th highest percent of households keeping livestock and also the largest difference between male and female headed households, with 19 percentage point more male headed households keeping livestock compared to female headed households. It has the highest chicken population with the highest density in the country. Most of the chickens are indigenous with very few improved types and the number of layers is very low compared to many other regions. A small number of eggs are produced indicating that most of the chickens are used for meat. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 88 The area cultivated by draft animals in Shinyanga is much higher than in any other region which supports the predominance of mixed farming in the region. The region has one of the highest areas of organic fertiliser application and the area applied per household is comparatively high. Considering the high livestock population, the region had moderate to low rates of disease infection. In general the access to livestock infrastructure and services is poor to moderate. Practically all extension was provided by the government. A small amount of fish farming is practiced in the region. As with all regions, Shinyanga has more land per household in male headed households than in female headed households. It has a large difference between male and female headed households with 1.7ha more in male headed households compared to female headed households. Shinyanga region has a high percent of households reporting insufficiency of land (56%) and a slightly higher percent of female headed households have insufficient land compared to male headed households. Female headed households in the region have around 19 percentage points more female land holders compared to male headed households and this difference is one of the largest compared to other regions. In Shinyanga, 42 percent of female headed households have female land holders. Assuming that male household members of female headed households do not have rights to land, this would imply that 58 percent of female headed households have insecure access to land. Shinyanga has a higher percent of female headed households using land under customary law and bought compared to male headed households, whilst a higher percent of male headed households have bought land than female headed households. Shinyanga has a high percent of households keeping cattle (42%) and 19 percentage points more male headed households keep cattle than female headed households. Male headed households keep around 5 more cattle per household than female headed households. Goats are moderately important in the region with 34 percent of households keeping them and 11 percentage points more households keep goats compared to female headed households. Male headed households keep slightly more goats per household that female headed households. Shinyanga has the 3rd highest number of households with sheep and slightly more sheep are kept per household in male headed households than in female headed households. Compared to other regions, Shinyanga has a moderate to high percent of households using improved seeds (3rd highest) and there is little difference between male and female headed households. Compared to other regions Shinyanga, has a moderate to high percent of households using insecticides (15%) and 7 percentage points more male headed households use it compared to female headed households. The region has a moderate to high percent of households not using fertilisers (76%). It has a moderate to high percent of households using farm yard manure (17% of households in the region) with 7 percentage point more male headed households using farm yard manure than female headed households. Inorganic fertiliser is used by a small percent of households in the region and there is no difference between male and female headed households. The region has a very small area of land under irrigation (0.5%) and male headed households have a slightly higher percent of households with irrigation compared to female headed households. Shinyanga region has a low percent of households receiving extension advice and there is little difference between male headed households and female headed households. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 89 The region has a Wety season only. In the region, 99.2 percent of male headed households and 99.1 percent of female headed households plant crops. Shinyanga has the 7th lowest percent of its planted area with maize and a higher percent of female headed households planted area is with maize compared to male headed households. The yield of maize in the region is low (0.5t/ha) and male headed households have 0.15t/ha more than female headed households. A moderate to high percent of households grow paddy in the region (12%) and there is no difference between male and female headed households. Shinyanga has a moderate to high percent of households utilising secondary products (35 percent of households) and there is little difference in utilisation between male and female headed households. Shinyanga region has the highest percent of active agriculture household members working full time on farm (90% of active members) and there is no difference between male and female headed households. Of the most active agriculture population (18 to 44 years of age) 94 percent of males and 96 percent of females are mainly involved in agriculture. In male headed households, 94 percent of the male members and 96 percent of female members are mainly involved in agriculture, whilst in female headed households 90 percent of males and 95 percent of females are mainly involved in agriculture. Shinyanga region has one of the highest percent of boys and girls involved in agriculture (26% of boys and 21% of girls). A higher percent of boys are involved in female headed households compared to male headed households, however there is no difference in the percent of girls involved in agriculture between male and female headed households. Around 38 percent more elderly males are involved in agriculture compared to elderly females. Shinyanga region has one of the highest percent of households storing crops (85% of households) compared to other regions with more male headed households storing crops than female headed households. There is no difference between male and female headed households in the percent of households storing for consumption. The region has slightly more male headed households facing storage losses compared to female headed households. A higher percent of male headed households store crops in locally made traditional cribs, whilst more female headed households store crops in sacks/open drum. Shinyanga has a small percent of the households in the region receiving credit (2%) and more there is no difference between male and female headed households. The main reason for not using credit is that they do not know how to access it, followed by don’t know about credit and not available and there is no difference between male and female headed households. The region has a moderate percent of households with modern roofing material in the country (35% of households in the region) and there is little difference between male and female headed households. It has one of the lowest percent of households using hurricane/pressure lamps for lighting and there is little difference between male and female headed households. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 90 Compared to other regions, Shinyanga has a low percent of households using piped drinking water (11%) and there is no difference between male and female headed households. The region has a moderate percent of households without toilets compared to other regions and more female headed households have no toilets than male headed households. The difference in the ownership of assets (radio, iron and bicycle) between male and female households is high, in favour of male headed households, for all regions. Shinyanga has a moderate to low percent of households with radios, a moderate percent of households with irons, and one of the highest percent of households with bicycles in the country. Male headed households have 26 percentage points more radios, 9 percentage points more irons and 33 percentage points more bicycles than female headed households. Household members in Shinyanga region have a moderate to high number of meals per day in the country. And there is no difference between male and female headed households. The region has the fifth lowest number of time the household members eat meat in a week and this is lower in female headed households than in male headed households, with male headed households eating meat around 0.9 times per week, whilst female headed households eat meat 0.4 times per week. Shinyanga has a large difference in the percentage of male and female headed households facing food shortages. Eleven percentage points more female headed households often or always face food shortages compared to male headed households. Right to land is mostly by customary law (60% of total land area under agriculture), however a moderate to high proportion is bought land. It has one of the lowest percent of households with official certificates of ownership. Access to fields is moderate compared to other regions with 50% of the households having their nearest field less than 100m from the Homestead. However the distance from the field to the nearest road is one of the farthest in the country. Shinyanga has the fourth lowest percent of literate rural agriculture population in the country and the difference between the literacy rate of males and females is amongst the highest. It has a comparatively low percent of the rural agriculture population that have completed school and the third highest percent of household heads with no education. The most important livelihood activity is crop farming followed by remittances. The percent of the rural agriculture population working full time in farming is fifth lowest in the country, however it has one of the highest percent working part time in agriculture. The main source of cash is from the sale of food crops, the second most important source of cash income is from the sale of cash crops. Other sources are of minor importance. Very small amount of credit is available in the region. Around 30 percent of households have the roof of the main dwelling made of modern material (mainly iron sheets) and the rest is mainly with grass/leaves/mud and only 11 percent of the households have no toilet facility. Energy for lighting is mainly from wick lamps and a very small proportion from hurricane lamps. Shinyanga has one of the lowest percent of piped drinking water supply and most is from unprotected or protected wells Most rural agriculture smallholders are living a subsistence existence with only 5 percent of households using their livelihood activities for non subsistence purposes. The region has the highest percent of households that do not eat animal DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 91 protein in a week and the smallest number that eat animal protein every day. It has a low percent of households that never face food shortage and a high proportion that often or always face shortages. In general access to services is worse than most other regions. About 55.4 percent of the households in the region reported insufficiency of land which is relatively high when compared to some of the regions in the country. 4.2 District Profile The following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Kahama Kahama district has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Kahama district is Annual Crop Farming, followed by Livestock Keeping/ Herding. However, the district has the second highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Kahama has a relatively low levels of female headed households (14%) and it has one of the lowest average age of the household head. With an average household size of 6.1 members per household it is average for the region. Kahama has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household is also slightly higher than most of districts in the region. It has the moderate utilized land area per household (3.2 ha) and the allocated area is 87% utilized. The District has low area planted per household which is 2.2 compared to other districts. Paddy production is much higher than other districts with a planted area of 53,283 hectares and the area planted per household is 0.66 ha. The district is moderately important for maize production in the region with a planted area of 79,905ha and the planted area per household is 0.98ha. The Production of sorghum is very small. Cassava production is moderate accounting for 24 percent of the quantity harvested in the region. The district has a large planted area of Sweet Potatoes (2,471 ha) accounting for 9 percent of the area planted with the crop in the region. As with other districts in the region, most land clearing and preparation is done by hand, however there is also a moderate practice of using tractor and oxen in the district. The use of inputs in the region is very small, however district differences exist. Kahama has the moderate planted area with improved seed in Shinyanga region. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. The district has also the largest area planted with inorganic fertilizers (90%) probably because of tobacco which widely grown in the district. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 92 Compared to other districts in the region, Kahama district has the highest level of insecticide use, which records 7.1% of the total planted area in the district. Herbicides was also used in the district though not widely, recoding 1.4% of the total planted area in the district. Kahama district has larger area with irrigation compared to other districts with 6,309ha of irrigated land. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage is in sacks or open drums, however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. The highest percent of households processing crops in Shinyanga region is found in Kahama district and is is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 77% and the main sources of credits are Savings and Credit Society and family friends and relatives. Although a very small number of households receive extension service in the region (28%), Kahama district had a moderate proportion of households receiving the service (36%) and the main service provider was from the government. The quality of extension services was rated between Very good and average by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; however it has the smaller number of pigs and chicken in the region. The smallest number of households reporting Tsetse and tick problems was in Kahama district and it had the large number of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Kahama recording 74%. The use of draft animals in the district is moderate to lower having only 40% of households, second from lowest, A small number of households practice fish farming (0.5%), which is only found in the district. The District has amongst the worst access to secondary schools, health clinics, Hospitals, District and regional capitals, tarmac road and terially markets. However the district has amongst the beast access to and primary schools, feeder roads, all wealther roads and secondary markets. Saturday Kahama district has the highest proportion of households with no toilet facilities (20%) and it has the highest percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 0.17% or 17 out 0f 1000 households. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (6%) The district has the highest percent of households with grass roofs (65%) in the region, with 28 percent of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most of the households access source of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 93 drinking water within a distance of less than one kilometer. It has the moderate proportion of households having two or one meal per day compared to other districts. The district had higher percent of households that did not eat meat or fish during the week prior to enumeration, second from top; however about one third of households seldom had problems with food satisfaction. 4.2.2 Bariadi Bariadi district has the larger number of households in the region, second from the top and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bariadi district is Annual Crop Farming, followed by off-farm income. Compared to other districts in the region, Bariadi has a relatively low levels of female headed households (14%) and it has one of the lowest average age of the household head. With an average household size of 6.7 members per household it is highest for the region. Bariadi has a comparatively moderate literacy rate (75.3%) for agricultural household members and the number of heads of agricultural households who have never attended school was moderate (40%), equal to the regional proportion. The literacy rate for the heads of household is also moderate, about the same as the regional proportion (41%). Compared to other district in the region, Bariadi has lower utilized land area per household (2.7 ha) and the average usable land per household is 2.9 ha, which indicate an impeding land pressure. Allocated area is also 91% utilized in the district and the District has low area planted per household which is 2.4 marking a third position from bottom when compared to other districts. The district is important for maize production in the region with a planted area of 101,952ha and the planted area per household is 1.35ha. Paddy production is not very significant in the district when compared to other districts with a planted area of 6,914hectares and the area planted per household is 0.40 ha. Sorghum production is also important in the district with a planted area of 4,175 hectares and the district ranks third from top in the region in terms of area planted. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas and Chick Peas. The district has a large planted area of Cotton (53,882ha), and ranks first in the region in terms of area and production and the average planted are per cotton growing household is 1.1 hectare. About 90% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil prepararion (3%) which is about the same as regional average. The use of inputs in the region is very small, however district differences exist. Bariadi has the higher planted area with improved seed in Shinyanga region. The district has larger planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser) and it ranks second from top when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has smallest area, almost none planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 94 Compared to other districts in the region, Bariadi district has the highest level of insecticide use, which records 31% of the total planted area in the district. However looking at the propotions of area under insecticide use in the region Bariadi ranks first (56.55%). Herbicides was also used in the district though not widely, recoding 18% of the total planted area with herbicides in the district. Bariadi district has larger area with irrigation compared to other districts with 4,966 ha of irrigated land. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is 16% same as the regional proportion. The district has the higher number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (86%) of households processing crops is found in Bariadi district and is mostly all done by neighbouring machine. Although very small, access to credit in the district is mainly to male headed households, which is 77% and the main sources of credits are Religious Organisation / NGO / Project and family friends/ relatives. Although a very small number of households receive extension service in the region, Bariadi district had a lower proportion of households receiving the service (21%) and the main service provider was from the government. The quality of extension services was rated between Very good and Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 6% of all agricultural households reporting to have planted trees. The district has 12.2% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is highest compared to other districts; however a very small number of pigs was kept in rural agricultural households in Bariadi District. It has the highest number of chicken in the region. Higher number of households report Tsetse and tick problems in Bariadi district and it had the largest number of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Bariadi recording 84%. The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, All Weather Road, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, feeder roads, and Primary markets. Saturday Bariadi district has higher proportion of households with no toilet facilities (12%), which is second from highest when compared to other districts and it has higher percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 0.10% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (97%) and very few use charcoal (1%) The district has lower percent of households with grass roofs (23%) in the region, with 64 percent of households having iron sheets roofing. The most common source of drinking water is from Protected Well and most of the households access source of drinking water within a distance of less than two kilometer. It has very low (1%) proportion of households having one meal per day compared to other districts. The district had the DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 95 highest percent of households that did not eat meat or fish during the week prior to enumeration (62%); however about one third of households always and often had problems with food satisfaction. 4.2.3 Maswa Maswa district has larger number of households in the region, fifth from the top and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only, 1% (or 10 households in every 1000 households) households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Maswa district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Maswa has the highest levels of female headed households (20%) and it has one of the highest average age of the household head (48). With an average household size of 6.3 members per household it is moderate for the region, a bit lower than the regional average which is 6.4. Maswa has a comparatively moderate literacy rate (71.3%) for agricultural household members and the number of heads of agricultural households who have never attended school was moderate (45%), above the regional proportion. The literacy rate for the heads of household was 45, above the regional proportion (41%). Compared to other district in the region, Maswa has moderate utilized land area per household (3.7 ha) higher than the regional average which is 3.4. The total usable land per household is 4.0 ha, which indicate an impeding land pressure. Allocated area is also 93% utilized in the district and the District has higher area planted per household which is 3.0 marking a second position from top when compared to other districts. Production of maize is moderately to lower compared to other districts in the region with a planted area of 35,159ha and the planted area per household is 0.92ha. Paddy production is also not higher enough when compared to other districts with a total planted area of 9,975hectares and the area planted per household is 0.40 ha. Sorghum production is also lower in the district with a planted area of 3,098hectares and the district ranks fourth from top in the region in terms of area planted. Sorghum is also grown in the district with an area of 7,950 hectares and area planted per sorghum growing household being 0.8 hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a large planted area with Cotton (44,650ha), and ranks second in the region in terms of area and production and the average planted are per cotton growing household is 1.35 hectare a little higher than the regional average which is 1.31 ha. About 80% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil preparation (8%) which is considerably higher than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Maswa has the higher planted area with improved seed in Shinyanga region. The district has larger planted area with fertilizers (Farm yard manure, compost) and it ranks second from top when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has smaller area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 96 Compared to other districts in the region, Maswa district has lower level of insecticide use, which is 23% of the total planted area in the district , lower than the regional average which is 34.5%. Fungicides was used in the district though not widely, recoding 7.8% of the total planted area with Fungicides in the district. Herbicides was also used in the district though not widely, recoding 0.94% of the total planted area with herbicides in the district. Irrigation was also pracriced in the district though not widely applied on 1,580ha of irrigated land or 1.4% of total planted area. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is higher than other districts in the region. The district has the highest number of households selling crops (79%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (75%) of households processing crops is found in Maswa district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 75% and the main sources of credits is Family, Friend and Relative. Although a very small number of households receive extension service in the region, Maswa district had a lowest proportion of households receiving the service (6%) and the main service provider was from the government. The quality of extension services was rated to Good by the majority of the households (665) that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.0% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; however no pigs were kept in rural agricultural households in Maswa District. The District had moderate number of chicken (14%) in the region. Lower number of households (1%) report Tsetse and tick problems in Maswa district and it had lower proportion of households de-worming livestock. The Incidence of Tick problem is almost commonly spread in all districts in the region with Maswa recording 64% which is a little bit lower than the regional average (68%). The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and terially markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Maswa district has higher proportion of households with no toilet facilities (12%), which is second from highest when compared to other districts and it has higher percent of households owning bicycles, radio and Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 100 households. Practically a large number of households use firewood for cooking (93%) and very few use charcoal (6%) The district has lower percent of households with grass roofs (15%) and higher percent of households with Mud Roofs (59%) in the region, low percent (25% ) of households having iron sheets roofing. The most common source of drinking water is from Protected Well and most households access source of drinking water within a distance of less than two kilometer. It has low (4%) proportion of households having one meal per day compared to other districts. The district had higher percent of households that did not eat meat or fish during the week prior to enumeration (57%); however about one third of households always and often had problems with food satisfaction. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 97 4.2.4 Meatu Meatu district has smaller number of households in the region, second from the lowest and the proportion of households involved in smallholder agriculture is 92%, lower than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. . The most important livelihood activity for smallholder households in Meatu district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Meatu has relatively lower levels of female headed households (13%), compared to the regional average, 14%, it has the moderate average age of the household head (46). With an average household size of 7.4 members per household, higher than the regional average which is 6.4. Meatu has a comparatively lower literacy rate (63.9%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was higher (46%), above the regional proportion, 40%. The literacy rate for the heads of household was 54, lower than the regional proportion (59%). Compared to other district in the region, Meatu has higher rate of utilized land area per household (5.1 ha) higher than the regional average which is 3.4. The total usable land per household is 5.6 ha, which indicate a scorching land pressure. Allocated area is also 92% utilized in the district and the District has moderate area planted per household which is 2.5 same as the regional average. Production of maize is lower compared to other districts in the region with a planted area of 31,193ha and the planted area per household is 0.29ha. Paddy production is also lowest when compared to other districts with a total planted area of 349hectares and the area planted per household is 0.27 ha. Sorghum production is highest in the district with a planted area of 24,395hectares and the district ranks First in the region in terms of area planted. The area planted per sorghum growing household is 1.57 hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a large planted area with Cotton (34,028ha), and ranks third in the region in terms of area and production and the average planted are per cotton growing household is 1.35 hectare a little higher than the regional average which is 1.31 ha. About 87% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil prepararion (5%) which is considerably higher than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Meatu has the low planted area with improved seed in Shinyanga region which is only 7% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) and it ranks second from bottom when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal or no area planted with inorganic fertilizers. Compared to other districts in the region, Meatu district has moderate level of insecticide use, which is 36% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 98 district, recoding 0.8% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 0.92% of the total planted area with herbicides in the district. Irrigation was also practiced in the district though not widely applied on 641ha of irrigated land or 0.7% of total planted area. The most common method of crop storage is in locally made traditional cribs, however the proportion of households not storing crops in the district is moderate. The district has the moderate number of households selling crops (59%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (84%) of households processing crops is found in Meatu district and is mostly all done by neighboring machine and by hand. Although very small, access to credit in the district is mainly to male headed households, which is 33% and the main sources of credits is Family, Friend and Relative, Commercial Bank and Trade store. Although a very small number of households receive extension service in the region, Meatu district had higher proportion of households receiving the service (47%), second from top and above from the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good and averge by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is higher compared to other districts; Very few pigs were reported in rural agricultural households (736) in Meatu District with an average of 4 pigs per pig rearing household. The District had moderate number of chicken (10%) in the region. Higher number of households (41%) report Tsetse fly problems in Meatu district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Meatu recording 71% which is a little bit lower than the regional average (68%). The District had moderate proportion of households (47%) de-worming livestock. The proportion of draft animals usage is higher in the district recoding 87% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Meatu district has the lowest proportion of households with no toilet facilities (3%), and it has moderate percent of households owning bicycles and radio and higher percent of households owning Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 100 households. Practically a large number of households use firewood for cooking (92%) and very few use charcoal (6%) and Crop Residues. The district has lower percent of households with grass roofs (12%) and higher percent of households with Mud Roofs (57%) and, low percent (28% ) of households having iron sheets roofing. The most common source of drinking water is from surface water (Lake/Dam/River/Stream) and most households access source of drinking water within a distance of less than three kilometer. It has the highest (7%) proportion of households having one meal per day compared to other districts. The district had Moderate percent of households that did not eat meat DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 99 or fish during the week prior to enumeration (42%); however about one third of households always and often had problems with food satisfaction. 4.2.5 Bukombe Bukombe district has moderate number of households in the region, and the proportion of households involved in smallholder agriculture is 99%, higher than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Bukombe district is Annual Crop Farming, followed by Livestock keeping and off-farm income. Compared to other districts in the region, Bukombe has relatively the lowest levels of female headed households 9%, lower than the regional average, 14%, it has the moderate average age of the household head 42, lower than the regional average 46. the District has an average household size of 6.4 members per household, same as the regional average which is also 6.4. Bukombe has a comparatively higher literacy rate (76.5%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was higher (30%), below the regional proportion, 40%. The literacy rate for the heads of household was 68, higher than the regional proportion (59%). Compared to other district in the region, Bukombe has lower rate of utilized land area per household (3.2 ha) lower than the regional average which is 3.4. The total usable land per household is 3.6 ha, which indicate a scorching land pressure. Allocated area is also 90% utilized in the district and the District has moderate area planted per household which is 2.6 a little higher than the regional average which is 2.5. Production of maize is moderate compared to other districts in the region with a planted area of 64,833ha and the planted area per household is 1.25ha. Paddy production is also moderate when compared to other districts with a total planted area of 21,371hectares and the area planted per household is 1.19ha. Sorghum production is lowest in the district with a planted area of 227hectares and the district ranks last but one in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.38hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a moderate area planted area with Cotton (14,798ha), and ranks sixth in the region in terms of area and production and the average planted are per cotton growing household is 1.15 hectare lower than the regional average which is 1.31ha. About 74% of the total planted area was cleared and soil prepared by hand, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Bukombe has the higher planted area with improved seed in Shinyanga region which is 25% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) and it ranks second from bottom when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 100 Compared to other districts in the region, Bukombe district has moderate level of insecticide use, which is 35% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 4.6% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 1.23% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 641ha of irrigated land or 1% of total planted area. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the moderate number of households selling crops (59%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (93%) of households processing crops is found in Bukombe district and is mostly all done by neighboring machine and by trader. Although very small, access to credit in the district is mainly to male headed households, which is 86% and the main sources of credits is Family, Friend and Relative, Trade store. Although a very small number of households receive extension service in the region, Bukombe district had low proportion of households receiving the service (14%), second from bottom and lower than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 3% of all agricultural households reporting to have planted trees. The district has 12.8% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is lowest compared to other districts; among enumerated rural agricultural households for Bukombe District no pigs were reported. The District had lower number of chicken (8%) in the region. Low number of households (5%) report Tsetse fly problems in Bukombe district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Bukombe recording 42% which is a little bit lower than the regional average (68%). The District had lower proportion of households (34%) de-worming livestock. The proportion of draft animals usage is lowest for the region recoding 17% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and terially markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Bukombe district has lower proportion of households with no toilet facilities (8%) as compared to the regional average which is 11%, and it has the highest percent of households owning bicycles and radio and lowest percent of households owning Iron. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (3%) and Crop Residues. The district has moderate percent of households with grass roofs (44%) and lower percent of households with Mud Roofs (22%) and, moderate percent (34% ) of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most households access source of drinking water within a distance of half a kilometer to less than three kilometer. It has lower (2%) proportion of households having one meal per day compared to other districts. The district had lower DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 101 percent of households that did not eat meat or fish during the week prior to enumeration (24%); however about less than a quarter agricultural households always and often had problems with food satisfaction. 4.2.6 Shinyanga Rural Shinyanga Rural district has moderate number of households in the region, and the proportion of households involved in smallholder agriculture is 99%, higher than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There are no agricultural households with livestock only in the district and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Shinyanga Rural district is Annual Crop Farming, followed by Off farms income and Livestock keeping. Compared to other districts in the region, Shinyanga Rural has the moderate level of female headed households 14%, equal to the regional average, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 6.2 members per household, lower than the regional average which is also 6.4. Shinyanga Rural has a comparatively higher literacy rate (73.5%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 39%, below the regional proportion, 40%. The literacy rate for the heads of household was 59, same as the regional proportion. Compared to other district in the region, Shinyanga Rural has lower rate of utilized land area per household (2.5 ha) lower than the regional average which is 3.4. The total usable land per household is 2.8 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 2.4 a little lower than the regional average which is 2.5. Production of maize is moderate compared to other districts in the region with a planted area of 44,228ha and the planted area per household is 1.00ha. Paddy production is also moderate when compared to other districts with a total planted area of 20,937hectares and the area planted per household is 0.73ha. Sorghum production is lower with a planted area of 1,329hectares and the district ranks fifth in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.53hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Chick peas, Ground nuts and Chick Peas. The district has a lower cotton production with a total of 2,105hectares planted with cotton. About 86% of the total planted area was cleared and soil prepared by oxen ploughing, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Shinyanga Rural has the lower planted area with improved seed in Shinyanga region which is 11% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost) . Most of the fertilizer under use is farm yard manure. The district has minimal or no area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 102 Compared to other districts in the region, Shinyanga Rural district has lower level of insecticide use, which is 10% of the total planted area in the district, lower than the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 3.5% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 2.71% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 3,152ha of irrigated land or 3.1% of total planted area. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the moderate number of households selling crops (43.8%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (94%) of households processing crops is found in Shinyanga Rural district and is mostly all done by neighboring machine and by trader. Although very small, access to credit in the district is mainly to female headed households, which is 75% and the main sources of credits are others or unspecified sources apart from family fried and relative, Commercial banks, Savings and credits, trade and religious organisations. Although a very small number of households receive extension service in the region, Shinyanga Rural district had a moderate proportion of households receiving the service (27%), a bit lower than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to very Good and Good by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 6% of all agricultural households reporting to have planted trees. The district has 12.2% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is moderate compared to other districts; Among enumerated households in rural agricultural households for Shinyanga Rural District no pigs were reported. The District had higher number of chicken (19%) in the region, second from top. No incidences of Tsetse fly problems were reported among the enumerated agricultural households.. The Incidence of Tick problem is almost commonly spread in all districts in the region with Shinyanga Rural recording 71% which is higher than the regional average (68%). The District had a moderate proportion of households (45%) de-worming livestock. The proportion of draft animals usage is lowest for the region recoding 17% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, and Primary markets. Shinyanga Rural district has lower proportion of households with no toilet facilities (9%) as compared to the regional average which is 11%, and it has the highest percent of households owning bicycles, radio and wheelbarrow. The main source of energy for lighting in the district is Wick Lamp and very few households reported their main source of lighting being electricity which was 1% or 10 out of 1000 households. Practically a large number of households use firewood for cooking (98%) and very few use charcoal (2%). The district has moderate percent of households with grass roofs (55%) and lower percent of households with Mud Roofs (28%) and, lower percent (17% ) of households having iron sheets roofing. The most common source of drinking water is from unprotected well and most households access source of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 103 drinking water within a distance of half a kilometer to less than three kilometer. It has the highest (4%) proportion of households having one meal per day. The district had moderate number of households that did not eat meat or fish during the week prior to enumeration (44%); however about less than a quarter agricultural households always and often had problems with food satisfaction. 4.2.7 Shinyanga Urban Shinyanga Urban district has the smallest number of households in the region, and the proportion of households involved in smallholder agriculture is 92%, lower than the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There is a small number of agricultural households with livestock only in the district (8%) and no pastoralists were recorded in the district. The most important livelihood activity for smallholder households in Shinyanga Urban district is Annual Crop Farming, followed by Livestock keeping and off farms income. Compared to other districts in the region, Shinyanga Urban has higher level of female headed households 19%, above the regional average which is 14%, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 5.4 members per household, lower than the regional average which is also 6.4. Shinyanga Urban has a comparatively lower literacy rate (52.2%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 45%, above regional proportion, 40%. The literacy rate for the heads of household was 56%, lower than the regional proportion which is 59%. Compared to other district in the region, Shinyanga Urban has lower rate of utilized land area per household (2.2 ha) lower than the regional average which is 3.4. The total usable land per household is 2.4 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 1.5 lower than the regional average which is 2.5. Production of maize is lower compared to other districts in the region with a planted area of 7,505ha and the planted area per household is 0.90ha. Paddy production is also lower when compared to other districts with a total planted area of 1,628hectares and the area planted per household is 0.48ha. Sorghum production is lower with a planted area of 917hectares and the district ranks fifth in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 0.72hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Cow peas, Chick peas, Ground nuts and Chick Peas. The district has the lowest cotton production in the region with a total of 385hectares planted with cotton. About 77% of the total planted area was cleared and soil prepared by hand, There is also a practice of using tractor in land and soil preparation (1%) which is considerably lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Shinyanga Urban has the lower planted area with improved seed in Shinyanga region which is 14% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard manure, compost). Most of the fertilizer under use is farm yard manure. The district has smaller area planted with inorganic fertilizers. DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 104 Compared to other districts in the region, Shinyanga Urban district has moderate level of insecticide use, which is 10% of the total planted area in the district, lower than the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 4.3% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 1.64% of the total planted area with herbicides in the Region. Irrigation was also practiced in the district though not widely applied on 863ha of irrigated land or 5.5% of total planted area, higher number than that recorded on other districts. The most common method of crop storage is in Sacks or open drum and locally made traditional cribs. The district has the lowest number of households selling crops (7.6%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. The lowest proportion (42%) of households processing crops is found in Shinyanga Urban district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to female headed households, which is 100% and the main sources of credits is Trade store. Although a very small number of households receive extension service in the region, Shinyanga Urban district had a moderate proportion of households receiving the service (33%), higher than the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated between Good and average by the majority of the households that received extension service. Tree farming was practiced in the district with 11% of all agricultural households reporting to have planted trees during the agricultural year this number is higher that that recorded for other districts. The district has 2.3% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is lowest compared to other districts. Very few pigs were reported in rural agricultural households (1,931) in Shinyanga Urban District with an average of 10 pigs per pig rearing household. The District had lower number of chicken (13%) in the region. Low number of households (3%) report Tsetse fly problems in Shinyanga Urban district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Shinyanga Urban recording 46% which is a lower than the regional average (68%). The District had lower proportion of households (33%) de-worming livestock. The proportion of draft animals usage is moderate for the region recoding 68% of households. No rural agricultural households practice fish farming in the district. The District has amongst the worst access to tarmac road. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, feeder roads, Primary markets, secondary schools, Hospitals, District and regional capitals, Secondary Market and tertiary markets. Shinyanga Urban district has lower proportion of households with no toilet facilities (5%) as compared to the regional average which is 12%, and it has higher number of households owning bicycles, radio, and Iron. The main source of energy for lighting in the district is Wick Lamp and hurricane lamp, very few households reported their main source of lighting being electricity which was 2% or 20 out of 1000 households. Practically a large number of households use firewood for cooking (88%) and very few use charcoal (10%) ,Crop Residues (1%) and bottled gas (1%). The district has a small number of households with grass roofs (15%) and higher percent of households with Mud Roofs (61%) and a small DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 105 percent (24%) of households having iron sheets roofing. The most common source of drinking water is from protected well and most households access source of drinking water within a distance of half a kilometer to less than two kilometer. It has lower (1%) proportion of households having one meal per day compared to other districts. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration (44%); however about one quarter of agricultural households always and often had problems with food satisfaction in the district. 4.2.8 Kishapu Kishapu district has smaller number of agricultural households compared to other districts in the in the region. The proportion of households involved in smallholder agriculture is 97%, above the regional proportion which is 96%. Most smallholders are involved in crop farming only, followed by crop and livestock farming. There is a small number of agricultural households with livestock only in the district (1%) and no pastoralists were recorded in the district. The most important livelihood activity for smallholder households in Kishapu district is Annual Crop Farming, followed by Livestock keeping. Compared to other districts in the region, Kishapu has moderate level of female headed households 15%, above the regional average which is 14%, it has the moderate average age of the household head 47, a little bit above the regional average 46. The District has an average household size of 6.4 members per household, same as the regional average which is also 6.4. Kishapu has a comparatively lower literacy rate (65%) for agricultural household members as compared to the regional number which is 70.1%. The number of heads of agricultural households who have never attended school was 41%, above the regional proportion which is 40%. The literacy rate for the heads of household was 60%, a bit above the regional proportion which is 59%. Compared to other district in the region, Kishapu has the highest rate of utilized land per household (5.6 ha) above the regional average which is 3.4. The total usable land per household is 6.3 ha, which indicate an approaching land pressure. Allocated area is also 90% utilized and the District has moderate area planted per household which is 3.4 higher than the regional average which is 2.5 and is the highest average planted area for the region. Production of maize is moderate compared to other districts in the region with a planted area of 35,494ha and the planted area per household is 1.17ha. Paddy production is lower when compared to other districts with a total planted area of 4,459hectares and the area planted per household is 0.63ha. Sorghum production is higher with a planted area of 21,030hectares and the district ranks second from top in the region in terms of area planted with sorghum. The area planted per sorghum growing household is 1.49hectares. Other food crops which are significantly produced in the district include Cassava, Sweet potatoes, Beans, Cow peas, Ground nuts and Chick Peas. The district has a moderate area planted area with Cotton 32,748hectares, and ranks fourth in the region in terms of area and production and the average planted are per cotton growing household is 1.70 hectare higher than the regional average which is 1.31ha. About 92% of the total planted area was cleared and soil prepared by oxen, there is also a practice of using tractor in land and soil preparation (3%) which is considerably a bit lower than the regional average which is 3%. The use of inputs in the region is very small, however district differences exist. Kishapu has the higher planted area with improved seed in Shinyanga region which is 48% of the total Planted Area. The district has smaller planted area with fertilizers (Farm yard DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 106 manure, compost) when compared to other districts. Most of the fertilizer under use is farm yard manure. The district has minimal area planted with inorganic fertilizers. Compared to other districts in the region, Kishapu district has moderate level of insecticide use, which is 33% of the total planted area in the district, about the same as the regional average which is 34.5%. Fungicides were scarcely used in the district, recoding 2.8% of the total planted area with Fungicides in the district. Herbicides were also scarcely used in the district, recoding 4.15% of the total planted area with herbicides in the district. Irrigation was also practiced in the district though not widely applied on 2,597ha of irrigated land or 2.1% of total planted area. The most common method of crop storage is in locally made traditional cribs and in sacks or open drums; The district has the moderate number of households selling crops (50.4%), however for those who did not sell, the main reason for not selling is insufficient production. The district also has a higher percent of households reporting Open Market Price Too Low as the major marketing problem. Higher proportion (97%) of households processing crops is found in Kishapu district and is mostly all done by neighboring machine. Although very small, access to credit in the district is mainly to male headed households, which is 33% and the main sources of credits is Family, Friend and Relative. Although a very small number of households receive extension service in the region, Kishapu district had higher proportion of households receiving the service (51%), ranking first from top and above the regional average which is 28% and the main service provider was from the government. The quality of extension services was rated to Good and average by the majority of the households that received extension service. Tree farming was scarcely practiced in the district with only 2% of all agricultural households reporting to have planted trees. The district has 11.3% of all cattle kept in the region and is mostly dominated by indigenous breeds. Goat and sheep production is higher compared to other districts; Very few pigs were reported in rural agricultural households (82) in Kishapu District with an average of 1 pigs per pig rearing household. The District had moderate number of chicken (6%) in the region. Low number of households (7%) report Tsetse fly problems in Kishapu district. The Incidence of Tick problem is almost commonly spread in all districts in the region with Kishapu recording 61% which is a little bit lower than the regional average (68%). The District had the lowest proportion of households (26%) de-worming livestock. The proportion of draft animals usage is higher in the district recoding 89% of households. No rural agricultural households reported to practice fish farming. The District has amongst the worst access to secondary schools, Hospitals, District and regional capitals, tarmac road, Primary Market, Secondary Market and tertiary markets. However the district has amongst the beast access to primary schools, Health Clinic, All Weather Road, and feeder roads. Kishapu district has the lower proportion of households with no toilet facilities (8%), and it is one of the districts with highest percent of households owning bicycles and radio. The main source of energy for lighting in the district is Wick Lamp and no households reported their main source of lighting being electricity. Practically a large number of households use firewood for cooking (96%) and very few use charcoal (3%) and Crop Residues (1%). The district has lower percent of households with grass roofs (5%) and higher percent of households with Mud Roofs (79%) and, low percent (14% ) of DISTRICT PROFILES. ______________________________________________________________________________________ ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census – Shinyanga Regional Report 107 households having iron sheets roofing. The most common source of drinking water is from surface water (Lake/Dam/River/Stream) and most households access source of drinking water within a distance of half a kilometer to less than three kilometer. It has lower (1%) proportion of households having one meal per day. The district had Moderate percent of households that did not eat meat or fish during the week prior to enumeration (35%); however about one third of households always and often had problems with food satisfaction. APPENDIX II 108 4. APPENDICES Appendix I Tabulation List...............................................................................................................................109 Appendix II Tables .............................................................................................................................................128 Appendix III Questionnaires...................................................................................................................................254 APPENDIX II 109 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD…………………………………...………………………………...128 2.1 Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year 129 2.2 Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year.......129 NUMBER OF AGRICULTURE HOUSEHOLDS .................................................................................................130 3.0 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year......................................................................................131 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District..................................................................................................................................131 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES............................................................................132 3.1a First Most Importance....................................................................................................................................133 3.1b Second Most Importance................................................................................................................................133 3.1c Third Most Importance ..................................................................................................................................133 3.1d Fourth Most Importance.................................................................................................................................133 HOUSEHOLDS DEMOGRAPHS............................................................................................................................134 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) .............................................................................................................................135 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (column %) .......................................................................................................................135 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year.......136 3.5A Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages by Type of Language and District, 2002/03 Agricultural Year ......................................136 3.5B Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year.................................................136 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ............................................................................................................................136 3.7 Number of Agricultural Household Members by Main Activity and District, 2002/03 Agricultural Year.137 cont… Number of Agricultural Household Members By Main Activity and District.................................137 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ........................................................................................................138 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................ 138 cont… Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ........................................................................................................139 APPENDIX II 110 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.................................................................................................140 3.11 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year..........................................................................................................................141 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year.............................................................................................................................141 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year..........................................................................................................................141 3.14 Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ............................................142 3.15A Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year........................................................................................142 3.15B Percent of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year .......................................................................................142 3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year.............................................................................................................................143 3.17 Time Series of Male and Female Headed Households: Shinyanga..........................................................................144 3.18 Literacy Rate of Heads of Households by Sex and District .....................................................................................144 LAND ACCESS/OWNERSHIP...........................................................................................................................................146 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year ..................................................................................................................................147 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year .....................147 LAND USE..............................................................................................................................................................................148 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ........149 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year.......................................149 5.3 Number of Households by type of household and District during 2002/03 Agricultural Year .............................150 5.4 Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year ......................................................................................150 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year ...............................................................150 TOTAL ANNUAL CROP & VEGETABLES PRODUCTION LONG & SHORT SEASONS...................................152 7.1 & 7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District......................................153 7.1 & 7.2b Number of Crop Growing Households Planting Crops by Season and District..................................................153 7.1 & 7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Kahama District.............................................................................................................................154 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year.................................................................................................................155 APPENDIX II 111 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year..................................................................................................................155 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................155 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................155 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................156 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................156 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................157 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................157 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................157 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................158 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................158 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................158 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................158 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................159 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................159 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................159 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................160 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................160 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................161 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 APPENDIX II 112 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................162 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year ....................................................................................................................................162 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year.............................................................................................................................163 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year..............................................................................................................................163 7.1 & 7.2e Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Shinyanya Region ....................................................................................164 7.1 & 7.2e Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District Long & Short Season, Kagera..........................................................................................................164 7.1 & 7.2f Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga.......................................................................164 7.1 & 7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga Region ...............................................................164 7.1 & 7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. ........................................................................................................165 7.1 & 7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Kahama. ........................................................................................165 7.1 & 7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Shinyanga Region......................................................................................166 7.1 &7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Shinyanga Region..............................................166 ANNUAL CROP & VEGETABLES PRODUCTION LONG SEASON........................................................................168 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Kahama District .....................................................................169 7.2b ````Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season..............................................................................................................................................169 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama District .....................................................................169 7.2d Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON ..............................................................................................................................170 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region.....................................................................170 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region.....................................................................170 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON, Kahama Region...................................................................171 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................172 APPENDIX II 113 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................172 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................172 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................173 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................173 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................174 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................174 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................174 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................175 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................176 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................176 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................176 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................177 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................177 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................177 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................178 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................178 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................178 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................179 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................179 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................179 APPENDIX II 114 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................180 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................181 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year .........................................................................................181 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year ..........................................................................................181 PERMANENT CROPS..................................................................................................................................................... 182 7.4 Total Area Planted with Coconut by District - Shinyanga Region......................................................................... 183 7.5 Total Area Planted with Oranges by District - Shinyanga Region ........................................................................ 183 7.6 Total Area Planted with Banana by District - Shinyanga Region.......................................................................... 183 AGROPROCESSING ....................................................................................................................................................... 184 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year......................................................................................................................... 185 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year District ........................................................................................................................................ 185 8.1.1a Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Kahama District ................................................................................................................ 186 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Use of Product and Crop, Kahama District................................................ 187 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Kahama District ...................................................... 188 8.1.1d Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Kahama District ......................................................................................................................... 188 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Kahama District............................................................................................... 189 8.1.1f Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Kahama District ......................................................................................................................... 189 8.1.1g Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Kahama District .............................................................................................. 189 MARKETING.................................................................................................................................................................... 190 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Kahama District................................................................................................................. 191 10.2 Number of Households who Reported Marketing Problems by District during 2002/03 Agricultural Year ................... 191 10.3 Proportion of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year.............................................................................................................................. 191 APPENDIX II 115 IRRIGATION/EROSION CONTROL........................................................................................................................... 192 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District..................................................................................................193 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year ...................................................................................................................193 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year .....................................................193 11.4 Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year ...............................................................................194 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year............................................194 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District .......................................................................................195 11.7 Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year.................................................................................195 ACCESS TO FARM INPUTS AND IMPLEMENTS ................................................................................................... 196 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District, 2002/03 Agricultural Year...................................................................................................................... 197 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year .................................................................................................................................... 197 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................... 198 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year .................................................................................................................................... 198 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year........................ 199 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year................ 199 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................................................................................... 200 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year, ................................................................................................................................... 200 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year .................................................................................................................................... 201 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................... 201 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year........... 202 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year......... 203 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year................................................................................................................. 203 APPENDIX II 116 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Year ......................................................................................................204 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year..........................................................................................................204 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year..........................................................................................................205 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................205 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year........................................................................................205 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year ............................................................................................206 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year ............................................................................................206 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year..........................................................................................................207 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year...............................................................................................................207 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year ...............................................................................................208 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year.........................................................................................................208 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure By district 2002/03 Agricultural Year ...........................................................................................................209 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District 2002/03 Agricultural Year...........................................................................................................210 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District 2002/03 Agricultural Year...........................................................................................................210 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District 2002/03 Agricultural Year ............................................................................................................................211 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................212 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year.........................................................................................................212 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year ............................................................................................................................213 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year..........................................................................................................213 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year......................................................................................................... 213 APPENDIX II 117 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year..........................................................................................................214 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year..........................................................................................................214 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year.............................................................................................................214 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year.............................................................................................................215 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year............................................................................................................215 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year.............................................................................................................216 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year.............................................................................................................216 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year..............216 12.2.1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03.......................................217 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year.............................................................................................................218 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District....218 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District .............................................................................................................................218 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District ...........219 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District....219 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District....................................................................................................................................219 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District .....220 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District ............................................................................................................................................220 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District....................................................................................................................................220 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District .............................................................................................................................221 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District.................................................................................................................221 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District ......................221 APPENDIX II 118 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District ....................................................................................................................................222 12.2.15 Number of Agricultural Households Owning OXEN by Source of Finance and District ............................222 12.2.16 Number of Agricultural Households Owning OX Plough by Source of Finance and District.................222 12.2.17 Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District.....223 12.2.18 Number of Agricultural Households Owning OX CART by Source of Finance and District ......................223 12.2.19 Number of Agricultural Households Owning TRACTOR by Source of Finance and District.....................223 12.2.20 Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District.....208 12.2.21 Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District ...223 AGRICULTURE CREDIT........................................................................................................................................224 13.1a Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year............................................................................................................225 13.1b Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year............................................................................................................225 13.2a Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year........................................................................................209 13.2c Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year .......................................................................................................... 209 TREE FARMING AND AGROFORESTRY..........................................................................................................212 14.1 Number of Households Having Planted Trees By District............................................................................213 contNumber of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region..............................................................................................213 14.1 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Kagera Region……….....214 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Shinyanga Region .......................................214 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region ................................................................................................................214 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District........215 14.4 Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Shinyanga Region..................................................................215 14 Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Shinyanga Region ..........................................................................................................................................215 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region ................................................................................................................215 CROP EXTENSION...................................................................................................................................................216 15.1 Number of Agriculture Households Receiving Extension Messages by District APPENDIX II 119 During the 2002/03 Agriculture Year, Shinyanga Region............................................................................217 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region..........................................................................217 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region...........................................................................217 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................218 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................218 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................218 15.7 Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................219 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.10 Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................220 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................220 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region........................................................220 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................221 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................221 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................221 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................222 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ......................................222 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region..............222 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region..............223 APPENDIX II 120 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region..............224 EXTENSION...............................................................................................................................................................226 15.1 Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 AgricultureYear, Shinyanga Region.............................................................................224 15.2 Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region .......................................................................................224 15.3 Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................224 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................224 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region.......................................................218 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region....................................................... 218 15.7 Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region .....................................219 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year ......................................................................219 15.10 Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................220 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region ..................................... 220 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region..............................................................220 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region................................................................. 21 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region................................................................. 21 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region........................................................221 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................222 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region...............................................................222 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region..............222 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message APPENDIX II 121 and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region...........................................223 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region..............223 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region ...........................223 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region ...........................244 ANIMAL CONTRIBUTION TO CROP PRODUCTION.....................................................................................226 17.1 Number of Households Using Draft Animal to Cultivate Land By District.................................................227 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.................................................................................................................227 17.3 Number of Crop Growing Households Using Organic Fertilizer By Region During 2002/03 Agriculture Year ...............................................................................................227 17.4 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year ......228 CATTLE PRODUCTION..........................................................................................................................................229 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Shinyanga Region..............................................................................................................231 18.2 Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 .............................................................................................231 18.3 Total Number of Cattle by Category and Type of Cattle; on 1st October 2003...........................................231 18.4 Total Number of Cattle by Type and District As of 1st October 2003.........................................................232 18.5 Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003.................232 18.6 Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 ..........................232 18.7 Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003...........................233 18.8 Total Number of Cattle by Category and District as on 1st October 2003..................................................233 GOATS PRODUCTION............................................................................................................................................234 19.1 Total Number of Goats by goat type and District as on 1st October 2003...................................................235 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003................235 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003..............................................236 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003......................................236 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003.........................236 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 ............................237 19.7 Total Number of Goats by Category and District on 1st October 2003 .......................................................237 SHEEP PRODUCTION.............................................................................................................................................238 APPENDIX II 122 20.1 Total Number of Sheep by Breed Type on 1st October 2003.......................................................................239 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003................................239 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003........................................................239 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 ....................................239 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003.........................................240 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003................................240 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003................................244 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003...................................................240 PIGS PRODUCTION.................................................................................................................................................242 21.1 Number of Households Raising or Managing Pigs by District on 1st October 2003...................................243 21.2 Number of Households and Pigs by Herd Size on 1st October 2003 ...........................................................243 21.3 Number of Households and Pigs by District on 1st October 2003 ...............................................................243 LIVESTOCK PESTS AND PARASITE CONTROL ............................................................................................244 22.1 Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year .............................................................................................................................245 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year ..............................................................................................245 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year. ..................................245 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year .............................................................245 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year.................246 22.6 Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. .............................................................................................246 OTHER LIVESTOCK ...............................................................................................................................................248 23a Total Number of Other Livestock by Type as of 1st October 2003 .............................................................249 23b Number of Chicken by Category of chicken and District as of 1st October 2003 .......................................249 23d Total Number of households and chickens raised by flock size as of 1st October 2005 .............................249 23e Head Number of Other Livestock by Type of Livestock and District..........................................................249 23f LIVESTOCK/POULTRY POPULATION TREND: SHINYANGA REGION ..........................................249 LIVESTOCK PRODUCTS: .....................................................................................................................................249 25 Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year..............................................................................................249 APPENDIX II 123 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: ................................................................................250 27.1 Number of households by Distance to Nearest Cattle Dip and District.......................................................249 27.2 Number of households by Distance to Nearest Spray Raced and District...................................................249 27.3 Number of households by Distance to Nearest Hand Powered Sprayer and District..................................249 27.4 Number of households by Distance to Nearest Cattle Crush and District...................................................249 27.5 Number of households by Distance to Nearest Primary Market and District .............................................249 27.6 Number of households by Distance to Nearest Secondary Market and District .........................................249 27.7 Number of households by Distance to Nearest Abattoir and District..........................................................249 27.8 Number of households by Distance to Nearest Slaughter Slab and District................................................249 27.9 Number of households by Distance to Nearest Hide/ Skin Shade and District...........................................249 27.10 Number of households by Distance to Nearest Input Supply and District ..................................................249 27.11 Number of households by Distance to Nearest Veterinary Clinic and District...........................................249 27.12 Number of households by Distance to Nearest Village Holding Ground and District................................249 27.13 Number of households by Distance to Nearest Village Watering Point/ Dam and District........................249 27.14 Number of households by Distance to Nearest Drencher and District ........................................................249 FISH FARMING.........................................................................................................................................................250 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year..251 LIVESTOCK EXTENSION......................................................................................................................................252 29.1a Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year .............................................................................................................................253 29.1b Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District during the 2002/03 Agricultural Year........................................................................................253 29.1c Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year..............................................................................................................254 29.1d Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year......................................................................................254 29.1e Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year ......................................................................................254 29.1f Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year ......................................................................................254 29.1g Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year .....................................................................255 29.1h Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year.............................................................. 255 29.1i Number of Agricultural Households Receiving Extension Advice on Group Formation APPENDIX II 124 and Strengtherning By Source and District, 2002/03 Agricultural Year......................................................256 29.1j Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year...........................................................................................256 29.1k Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year......................................................................................257 29.1l Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year .............................................................................................................................257 29.1m Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year ...........................................................................................................................258 29.13 Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year...............................................................................................................258 GOVERNMENT REGULATORY PROBLEMS: ..........................................................................................................258 30.1 Number of Agricultural Households by Whether Face Problems with Government Regulation During 2003/04 by District, 2002/03 Agricultural Year...................................................................................258 ACCESS TO INFRASRUCTURE AND OTHER SERVICES.............................................................................260 30.1 Number of Agricultural Households by Distance to Services by District, 2002/03 Agricultural Year ......261 30.2 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year..............................................................................................................................262 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural year ..............................................................................................................................262 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year .............................................................................................................................262 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year .............................................................................................................................263 33.6 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year .............................................................................................................................263 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year263 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year ............................................................................................................................264 33.9 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year .............................................................................................................................264 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year .............................................................................................................................264 33.11 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year ............................................................................................................................265 33.12 Number of Agricultural Households by Distance to Tertiary Market and District,....................................265 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year .............................................................................................................................265 33.14 Number of Agricultural Households by Distance to Extension Center.......................................................266 APPENDIX II 125 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year .............................................................................................................................266 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year .............................................................................................................................266 33.17 Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year .............................................................................................................................267 33.18 Number of Agricultural Households by Distance to Livestock Development Center ................................267 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year...............................................................................................................267 33.19b Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year...............................................................................................................267 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year...............................................................................................................267 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ........................................................................................................267 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year...............................................................................................................267 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year ............................................................................................267 33.19g Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year............................................................................................................. 267 HOUSEHOLD FACILITIES ....................................................................................................................................268 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year ..............................................................................................................................269 34.2A Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District, 2002/03 Agricultural Year..........................................................................................269 34.2B Percent of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year.........................................................................................................269 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year ....................................................................................................269 34.4a Number of Agriculture Households by Main Source of Energy Used for Lighting and during 2002/03 Agricultural Year..................................................................................................................270 34.4b Proportion of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year ...................................................................................................270 34.5a Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year.................................................................................................................270 34.5b Proportion of Agriculture Households by Main Source of Energy Used for Cooking and District during 2002/03 Agricultural Year ...................................................................................................270 34.6: Number of Agricultural Households by Main Source of Drinking Water by (wet and dry) and District during 2002/03 Agricultural Year.......................................................................271 APPENDIX II 126 34.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year.......................................................................272 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year .......................................272 34.9: Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year ........................................273 34.10: Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year........................273 34.11: Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year........................273 34.12A Number of Households by Number of Meals the Household Normally Took per Day by District Normally Took per Day by District..............................................................................................................274 34.12B Number of Households by Number of Meals the Household Normally Took per Day by District............274 34.13A Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ...........................................................................................................................274 34.13B Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District .....................................................................................................................274 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District .....................................................................................................................275 34.15A: Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.........................................................................................275 34.15B Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District.........................................................................................275 34.16: Number of Households by Main Source of Cash Income and District during 2002/03 Agricultural Year .............................................................................................................................275 34.17: Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year .............................................................................................................................275 APPENDIX II: CROP TABLES APPENDIX II 127 Type of Agriculture Household.............................................................................................................................................. 128 Number of Agriculture Households ........................................................................................................................................ 130 Rank of Importance of Livelihood Activities ......................................................................................................................... 132 Households Demography......................................................................................................................................................... 134 Land Access/Ownership .......................................................................................................................................................... 146 Land Use……………….......................................................................................................................................................... 148 Total Annual Crop and Vegetable Production Long and short Seasons ............................................................................... 152 Annual Crop and Vegetable Production Long Rainy Seasons ............................................................................................... 168 Permanent Crop Production..................................................................................................................................................... 182 Agro-processing ............................................................................................................................................................. 184 Marketing ............................................................................................................................................................. 190 Irrigation/Erosion Control ....................................................................................................................................................... 192 Access to Farm Inputs ............................................................................................................................................................ 196 Agriculture Credit ............................................................................................................................................................. 208 Tree Farming and Agro-forestry.............................................................................................................................................. 212 Crop Extension ............................................................................................................................................................. 216 Animal Contribution to Crop Production................................................................................................................................ 226 Cattle Production ............................................................................................................................................................. 230 Goat Production ............................................................................................................................................................. 234 Sheep Production ............................................................................................................................................................. 238 Pig Production ............................................................................................................................................................. 242 Livestock Pests and Parasite Control ...................................................................................................................................... 244 Other Livestock ............................................................................................................................................................. 248 Fishing Farming ............................................................................................................................................................. 250 Livestock Extension ............................................................................................................................................................. 252 Access to Infrastructure and other services............................................................................................................................. 260 Household Facilities ............................................................................................................................................................. 268 Appendix II 128 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 129 Rural households involved in Agriculture % of Total rural house holds Rural households NOT involved in Agriculture % of Total Rural house - holds Total Rural Househol d % of Total house - holds Urban Households % of Total house - holds Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Kahama 81,217 94 4,979 6 86,196 85 14,657 15 100,853 Bariadi 77,572 96 2,955 4 80,527 94 5,032 6 85,559 Bukombe 53,240 99 528 1 53,768 88 7,503 12 61,271 Shinyanga Rural 45,263 100 126 0 45,389 100 128 0 45,517 Maswa 43,252 99 641 1 43,893 90 5,028 10 48,921 Kishapu 35,624 97 1,246 3 36,870 93 2,574 7 39,444 Meatu 31,492 93 2,261 7 33,753 96 1,485 4 35,238 Shinyanga Urban 10,198 92 939 8 11,137 39 17,080 61 28,217 Total 377,857 97 13,676 3 391,533 88 53,487 12 445,020 Number of households % Number of households % Number of househol ds % Bariadi 39,487 51 179 0 37,905 49 77,572 77,393 38,084 Maswa 22,774 53 317 1 20,160 47 43,252 42,935 20,478 Shinyanga Rural 21,182 47 102 0 23,979 53 45,263 45,161 24,081 Kahama 49,208 61 143 0 31,866 39 81,217 81,074 32,009 Bukombe 34,546 65 239 0 18,456 35 53,240 53,001 18,695 Meatu 13,820 44 47 0 17,625 56 31,492 31,445 17,672 Shinyanga Urban 4,190 41 783 8 5,226 51 10,198 9,415 6,009 Kishapu 16,108 500 1 19,015 53 35,624 35,124 19,515 Total 201,316 53 2,310 1 174,232 46 377,857 375,547 176,542 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households Crops & Livestock Total Number of Agriculture Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock District Crops Only 2. 2 TYPE OF AGRICULTURE HH: Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year District Livestock Only Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 130 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 131 Number % Average Household Size Number % Average Household Size Number % Bariadi 66,387 86 7 11,185 14 5 77,572 100 7 Maswa 34,626 80 7 8,625 20 5 43,252 100 6 Shinyanga Rural 38,841 86 6 6,422 14 5 45,263 100 6 Kahama 70,196 86 6 11,021 14 4 81,217 100 6 Bukombe 48,282 91 7 4,958 9 5 53,240 100 6 Meatu 27,272 87 8 4,220 13 5 31,492 100 7 Shinyanga Urban 8,214 81 6 1,984 19 5 10,198 100 5 Kishapu 30,103 85 7 5,520 15 5 35,624 100 6 Total 323,921 86 7 53,936 14 5 377,857 100 6 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 1 6 3 2 4 7 5 Maswa 1 4 2 3 6 7 5 Shinyanga Rural 1 4 3 2 5 7 6 Kahama 1 5 2 3 6 7 4 Bukombe 1 4 2 3 5 7 6 Meatu 1 6 2 3 5 7 4 Shinyanga Urban 1 4 2 3 5 7 6 Kishapu 1 6 2 4 5 7 3 Total 1 5 2 3 6 7 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity 3.0: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 132 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 133 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 65,962 0 370 10,875 0 0 696 Maswa 41,348 0 325 1,161 0 0 0 Shinyanga Rural 44,576 0 99 584 0 0 102 Kahama 77,801 135 972 1,982 428 282 141 Bukombe 52,762 0 0 358 0 0 119 Meatu 28,953 83 802 1,521 0 47 83 Shinyanga Urban 9,161 54 103 698 47 0 0 Kishapu 31,690 0 772 2,801 203 0 402 Total 352,253 272 3,444 19,980 678 329 1,544 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 9,512 1,549 30,753 21,952 2,144 0 1,753 Maswa 1,492 2,875 17,036 9,607 938 108 2,342 Shinyanga Rural 485 1,118 21,443 18,001 1,303 102 396 Kahama 2,843 4,993 25,587 21,139 1,522 133 7,248 Bukombe 478 2,507 18,911 10,340 2,142 119 1,075 Meatu 2,015 537 15,369 6,153 461 0 3,609 Shinyanga Urban 626 742 4,226 2,864 559 0 218 Kishapu 2,389 405 15,954 5,586 1,696 81 5,361 Total 19,840 14,726 149,279 95,643 10,764 544 22,003 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Shinyanga Rural 99 2,016 2,727 12,253 1,315 0 1,105 Kahama 0 4,691 5,623 9,663 1,910 0 4,670 Bukombe 0 1,189 4,052 4,179 1,550 0 358 Meatu 193 869 2,392 4,437 1,043 83 4,250 Shinyanga Urban 116 1,094 1,085 1,611 563 0 776 Kishapu 639 406 1,662 4,428 724 0 10,617 Total 2,097 16,836 26,635 55,960 14,759 192 28,021 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Bariadi 170 3,921 714 1,055 1,439 0 1,952 Maswa 0 1,273 527 623 751 0 853 Shinyanga Rural 0 1,501 204 811 610 98 0 Kahama 0 1,729 1,089 556 907 0 2,348 Bukombe 0 478 597 239 239 0 0 Meatu 81 650 211 657 769 333 332 Shinyanga Urban 0 561 152 518 60 0 217 Kishapu 79 638 1,295 1,368 325 0 3,774 Total 330 10,751 4,790 5,826 5,099 431 9,477 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 134 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 135 Number % Number % Number % Less than 4 195,350 51 190,510 49 385,861 100 05 - 09 206,278 52 188,729 48 395,007 100 10 - 14 180,439 52 165,889 48 346,329 100 15 - 19 132,500 53 117,885 47 250,386 100 20 - 24 95,986 48 102,328 52 198,314 100 25 - 29 77,454 44 98,379 56 175,833 100 30 - 34 76,149 49 80,446 51 156,595 100 35 - 39 62,237 52 57,548 48 119,785 100 40 - 44 51,436 55 42,797 45 94,234 100 45 - 49 34,431 50 34,401 50 68,832 100 50 - 54 32,785 52 30,283 48 63,069 100 55 - 59 23,534 58 17,330 42 40,863 100 60 - 64 22,459 54 19,434 46 41,893 100 65 - 69 15,236 53 13,377 47 28,613 100 70 - 74 14,598 56 11,592 44 26,190 100 75 - 79 9,473 66 4,889 34 14,362 100 80 - 84 5,046 46 5,902 54 10,948 100 Above 85 4,790 52 4,503 48 9,293 100 Total 1,240,182 49 1,186,224 51 2,426,406 100 Number % Number % Number % Less than 4 82,018 13 88,990 13 171,007 13 05 - 09 104,818 17 102,672 16 207,490 16 10 - 14 101,601 16 92,510 14 194,111 15 15 - 19 68,064 11 61,926 9 129,989 10 20 - 24 40,272 6 61,291 9 101,563 8 25 - 29 43,942 7 51,603 8 95,544 7 30 - 34 35,049 6 38,261 6 73,310 6 35 - 39 28,872 5 37,812 6 66,684 5 40 - 44 25,932 4 30,220 5 56,152 4 45 - 49 23,468 4 23,258 4 46,726 4 50 - 54 19,919 3 19,937 3 39,856 3 55 - 59 13,381 2 10,934 2 24,315 2 60 - 64 13,033 2 12,749 2 25,782 2 65 - 69 11,024 2 9,540 1 20,565 2 70 - 74 10,535 2 10,146 2 20,681 2 75 - 79 4,869 1 3,763 1 8,632 1 80 - 84 4,058 1 3,400 1 7,458 1 Above 85 3,113 0 3,052 0 6,165 0 Total 633,967 100 662,064 100 1,296,031 100 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 136 Number % Number % Number % Bariadi 196,570 48 209,752 52 406,322 100 Maswa 112,681 49 115,135 51 227,816 100 Shinyanga Rural 113,667 49 116,950 51 230,617 100 Kahama 19,546 48 21,375 52 40,922 100 Bukombe 15,310 52 14,143 48 29,453 100 Meatu 123,622 48 132,669 52 256,291 100 Shinyanga Urban 52,570 50 52,040 50 104,610 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Number % % Bariadi 258,554 73.2 7,315 2.1 0 0.0 87,278 24.7 100 Maswa 140,665 68.9 5,004 2.5 0 0.0 58,514 28.7 100 Shinyanga Rural 143,330 71.2 4,205 2.1 283 0.1 53,363 26.5 100 Kahama 25,756 69.8 1,922 5.2 131 0.4 9,073 24.6 100 Bukombe 19,921 74.4 519 1.9 39 0.1 6,280 23.5 100 Meatu 128,671 59.7 6,330 2.9 750 0.3 79,943 37.1 100 Shinyanga Urban 44,615 51.2 668 0.8 243 0.3 41,651 47.8 100 Total 761,512 68 25,964 2 1,446 0.1 336,102 30 100 Number % Number % Number % Bariadi 87,278 24.7 265,869 75.3 353,147 100.0 Maswa 58,514 28.7 145,669 71.3 204,183 100.0 Shinyanga Rural 53,363 26.5 147,819 73.5 201,182 100.0 Kahama 9,073 24.6 27,809 75.4 36,882 100.0 Bukombe 6,280 23.5 20,479 76.5 26,758 100.0 Meatu 79,943 37.1 135,751 62.9 215,693 100.0 Shinyanga Urban 41,651 47.8 45,527 52.2 87,178 100.0 Total 336,102 29.9 788,922 70.1 1,125,024 100.0 Number % Number % Number % Number % Bariadi 132,142 37.4 162,461 46.0 58,544 16.6 353,147 100 Maswa 69,632 34.1 87,548 42.9 47,003 23.0 204,183 100 Shinyanga Rural 65,362 32.5 90,049 44.8 45,771 22.8 201,182 100 Kahama 11,636 31.5 17,439 47.3 7,807 21.2 36,882 100 Bukombe 9,276 34.7 13,161 49.2 4,322 16.2 26,758 100 Meatu 63,567 29.5 83,470 38.7 68,656 31.8 215,693 100 Shinyanga Urban 25,390 29.1 27,199 31.2 34,588 39.7 87,178 100 Total 377,006 33.5 481,327 42.8 266,691 23.7 1,125,024 100 3.5A HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total Cannot Read and Write Can Read and Write Total District 3.5B HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to STotal Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 137 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % % % Bariadi 152,752 43 1,866 1 144 0 143 0 1 8 Maswa 76,219 37 3,934 2 103 0 107 0 2 8 Shinyanga Rural 77,409 38 1,565 1 1,299 1 1,529 1 1 5 Kahama 9,867 27 898 2 23 0 987 3 2 4 Bukombe 8,770 33 45 0 0 0 942 4 1 5 Meatu 92,233 43 2,552 1 107 0 630 0 1 5 Shinyanga Urban 33,682 39 2,921 3 1,164 1 48 0 0 2 Total 450,932 40 13,782 1 2,839 0 4,387 0 1 6 cont… HOUSEHOLD DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Number % Bariadi 16,606 5 1,439 0 576 0 0 0 570 0 Maswa 7,418 4 919 0 200 0 103 0 1,556 1 Shinyanga Rural 18,315 9 1,566 1 708 0 736 0 2,515 1 Kahama 5,170 14 504 1 985 3 103 0 1,250 3 Bukombe 3,665 14 247 1 148 1 41 0 638 2 Meatu 17,355 8 2,481 1 615 0 216 0 837 0 Shinyanga Urban 14,306 16 98 0 0 0 192 0 582 1 Total 82,834 7 7,254 1 3,231 0 1,391 0 7,948 1 cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Bariadi 116,122 33 29,186 8 280 0 353,147 100 Maswa 63,908 31 23,480 11 809 0 204,183 100 Shinyanga Rural 63,082 31 16,832 8 1,957 1 201,182 100 Kahama 11,348 31 2,635 7 485 1 36,882 100 Bukombe 8,838 33 1,269 5 261 1 26,758 100 Meatu 55,470 26 21,768 10 7,226 3 215,693 100 Shinyanga Urban 24,417 28 7,202 8 716 1 87,178 100 Total 343,184 31 102,373 9 11,735 1 1,125,024 100 Livestock Keeping / Herding Livestock Pastoralist Fishing Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Housemaker / Housewife District Crop/Seaweed Farming Other Total Not Working & Available Student Not Working & Unavailable Main Activity District District Unable to Work / Too Old / Retired / Sick / Disabled Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 138 Number % Number % Number % Number % % Bariadi 153,483 43 11,754 3 143,275 41 44,635 13 100 Maswa 66,982 33 26,928 13 68,254 33 42,019 21 100 Shinyanga Rural 74,537 37 30,593 15 63,190 31 32,863 16 100 Kahama 8,995 24 5,515 15 9,496 26 12,877 35 100 Bukombe 8,093 30 1,458 5 12,725 48 4,483 17 100 Meatu 85,034 39 24,270 11 67,099 31 39,290 18 100 Shinyanga Urban 36,026 41 12,288 14 24,623 28 14,240 16 100 Total 433,150 39 112,805 10 388,661 35 190,408 17 100 Number % Number % Number % Number % % % Bariadi 146 0 288 0 2,314 1 2,450 2 10 2 Maswa - - 1,137 1 2,417 3 3,800 4 14 4 Shinyanga Rural - - 492 1 1,904 2 3,308 4 16 5 Kahama 111 1 167 1 448 3 681 4 12 3 Bukombe - - 23 0 301 2 518 4 14 4 Meatu 540 1 108 0 2,558 3 5,094 6 13 4 Shinyanga Urban 97 0 - - 731 3 925 3 13 1 Total 893 0 2,215 0 10,672 2 16,776 3 13 3 District District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year Education Level 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Under Standard One Standard One Standard Two Standard Three Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 139 Number % Number % Number % Number % Number % Bariadi 128,131 79 1,166 1 145 0 - - 146 0 Maswa 55,775 64 1,731 2 376 0 300 0 - - Shinyanga Rural 55,523 62 1,874 2 338 0 55 0 167 0 Kahama 10,589 61 360 2 30 0 23 0 91 1 Bukombe 8,465 64 250 2 35 0 19 0 67 1 Meatu 53,352 64 1,247 1 - - - - 217 0 Shinyanga Urban 20,391 75 98 0 - - - - - - Total 332,227 69 6,726 1 925 0 397 0 688 0 Number % Number % Number % Number % Number % Bariadi 582 0 144 0 2,588 2 - - 708 0 Maswa 596 1 191 0 2,305 3 - - 107 0 Shinyanga Rural 1,048 1 124 0 1,379 2 - - 84 0 Kahama 73 0 81 0 775 4 10 0 212 1 Bukombe 76 1 22 0 230 2 24 0 22 0 Meatu 520 1 217 0 944 1 - - 212 0 Shinyanga Urban 47 0 - - 433 2 - - 49 0 Total 2,942 1 779 0 8,654 2 34 0 1,393 0 Number % Number % Number % Bariadi - - 1,010 1 162,461 100 Maswa - - 725 1 87,548 100 Shinyanga Rural - - 1,532 2 90,049 100 Kahama 45 0 579 3 17,439 100 Bukombe - - 379 3 13,161 100 Meatu - - 1,253 2 83,470 100 Shinyanga Urban 47 0 386 1 27,199 100 Total 92 0 5,865 1 481,327 100 Training After Secondary Standard Seven Standard Eight ng After Primary Edu Pre Form One Form One Form Six Form Two Form Three Form Four cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District District District g Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year University & Other Tertiary Education Adult Education Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 140 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Bariadi 468,284 66,387 7 54,815 11,185 5 523,099 77,572 7 Maswa 227,390 34,626 7 43,540 8,625 5 270,930 43,252 6 Shinyanga Rural 248,001 38,841 6 31,458 6,422 5 279,459 45,263 6 Kahama 444,770 70,196 6 47,659 11,021 4 492,428 81,217 6 Bukombe 318,090 48,282 7 24,458 4,958 5 342,548 53,240 6 Meatu 210,253 27,272 8 21,603 4,220 5 231,856 31,492 7 Shinyanga Urban 46,129 8,214 6 9,099 1,984 5 55,228 10,198 5 Kishapu 204,861 30,103 7 25,997 5,520 5 230,858 35,624 6 Total 2,167,778 323,921 7 258,628 53,936 5 2,426,406 377,857 6 Number of Househod Members % Number of Househod Members % Number of Househod Members % Bariadi 468,284 86 54,815 14 523,099 100 Maswa 227,390 80 43,540 20 270,930 100 Shinyanga Rural 248,001 86 31,458 14 279,459 100 Kahama 444,770 86 47,659 14 492,428 100 Bukombe 318,090 91 24,458 9 342,548 100 Meatu 210,253 87 21,603 13 231,856 100 Shinyanga Urban 46,129 81 9,099 19 55,228 100 Kishapu 204,861 85 25,997 15 230,858 100 Total 2,167,778 86 258,628 14 2,426,406 100 Mean Median Mode Mean Median Mode Mean Median Mode Bariadi 46 42 40 52 53 60 46 42 40 Maswa 47 43 35 53 54 62 48 45 35 Shinyanga Rural 46 43 42 51 49 50 47 44 42 Kahama 45 42 30 50 50 55 46 44 30 Bukombe 42 38 38 48 50 45 42 39 38 Meatu 45 43 30 49 43 39 46 43 42 Shinyanga Urban 45 42 38 54 55 58 47 43 38 Kishapu 46 45 45 49 45 60 47 45 45 Total 45 42 30 51 50 60 46 43 30 3.10 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households by Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 141 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Bariadi 30,843 44,270 0 1,751 351 356 77,572 Maswa 19,779 22,228 0 1,031 0 214 43,252 Shinyanga Rural 17,623 24,537 303 683 303 1,814 45,263 Kahama 34,612 43,129 397 1,702 559 818 81,217 Bukombe 15,855 36,072 119 716 119 358 53,240 Meatu 14,773 15,403 0 830 156 331 31,492 Shinyanga Urban 4,662 5,083 30 156 46 222 10,198 Kishapu 14,680 19,453 0 1,028 243 219 35,624 Total 152,826 210,174 849 7,898 1,778 4,332 377,857 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education Adult Education Total Attending School 0 1,708 0 15 0 313 2,036 Completed 1,080 208,466 849 7,883 1,778 4,019 224,076 Never Attended to School 151,746 0 0 0 0 0 151,746 Total 152,826 210,174 849 7,898 1,778 4,332 377,857 Bariadi 22,815 34 43,572 66 66,387 100 Maswa 13,174 38 21,452 62 34,626 100 Shinyanga Rural 14,114 36 24,726 64 38,841 100 Kahama 25,482 36 44,714 64 70,196 100 Bukombe 13,265 27 35,017 73 48,282 100 Meatu 11,332 42 15,939 58 27,272 100 Shinyanga Urban 2,957 36 5,257 64 8,214 100 Kishapu 10,635 35 19,468 65 30,103 100 Total 113,776 35 210,146 65 323,921 100 Continued …. 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Bariadi 8,906 80 2,279 20 11,185 100 Maswa 6,489 75 2,137 25 8,625 100 Shinyanga Rural 4,625 72 1,797 28 6,422 100 Kahama 8,147 74 2,875 26 11,021 100 Bukombe 3,658 74 1,300 26 4,958 100 Meatu 3,089 73 1,131 27 4,220 100 Shinyanga Urban 1,501 76 483 24 1,984 100 Kishapu 3,673 67 1,847 33 5,520 100 Total 40,088 74 13,848 26 53,936 100 Continued …. 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Bariadi 31,721 41 45,851 59 77,572 100 Maswa 19,663 45 23,589 55 43,252 100 Shinyanga Rural 18,740 41 26,523 59 45,263 100 Kahama 33,629 41 47,588 59 81,217 100 Bukombe 16,923 32 36,317 68 53,240 100 Meatu 14,422 46 17,070 54 31,492 100 Shinyanga Urban 4,458 44 5,740 56 10,198 100 Kishapu 14,309 40 21,315 60 35,624 100 Total 153,864 41 223,994 59 377,857 100 Can Read and Write Total 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year Education Status Maximum Education Level Attained 3.13 Number of Heads of Agricultural Households reporting Literacy levels by Sex of head and District, 2002/03 Agricultural Year Male District 3.11 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained Cannot Read and Write Cannot Read and Write Can Read and Write Total District Female Cannot Read and Write Can Read and Write Total Total District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 142 Number Percent Number Percent Number Percent Number Percent Bariadi 27,319 59 12,360 27 6,560 14 46,239 100 Maswa 7,958 48 3,942 24 4,580 28 16,481 100 Shinyanga Rural 23,408 73 6,947 22 1,686 5 32,041 100 Kahama 24,544 51 15,981 33 8,003 16 48,528 100 Bukombe 9,994 60 4,157 25 2,506 15 16,657 100 Meatu 5,036 48 2,483 24 2,864 28 10,383 100 Shinyanga 3,725 63 1,646 28 538 9 5,908 100 Kishapu 11,545 70 3,352 20 1,573 10 16,470 100 Total 113,528 59 50,868 26 28,310 15 192,706 100 Attending School Completed Never Attended to School Total Completed Never Attended to School Total Attending School Completed Never Attended School Total Bariadi 356 43,745 22,286 66,387 2,627 8,557 11,185 356 46,372 30,843 77,572 Maswa 433 20,702 13,492 34,626 2,447 6,179 8,625 433 23,148 19,671 43,252 Shinyanga Rural 201 25,540 13,099 38,841 1,899 4,523 6,422 201 27,439 17,623 45,263 Kahama 828 43,188 26,179 70,196 3,018 8,003 11,021 828 46,206 34,182 81,217 Bukombe 119 35,964 12,198 48,282 1,420 3,538 4,958 119 37,384 15,737 53,240 Meatu 83 15,829 11,359 27,272 1,131 3,089 4,220 83 16,961 14,448 31,492 Shinyanga Urban 15 5,154 3,045 8,214 468 1,516 1,984 15 5,621 4,562 10,198 Kishapu 0 19,178 10,926 30,103 1,766 3,755 5,520 0 20,943 14,680 35,624 Total 2,036 209,301 112,585 323,921 14,775 39,161 53,936 2,036 224,076 151,746 377,857 Attending School Completed Never Attended to School Total Completed Never Attended to School Total Attending School Completed Never Attended School Total Bariadi 1 66 34 100 23 77 100 0 60 40 100 Maswa 1 60 39 100 28 72 100 1 54 45 100 Shinyanga Rural 1 66 34 100 30 70 100 0 61 39 100 Kahama 1 62 37 100 27 73 100 1 57 42 100 Bukombe 0 74 25 100 29 71 100 0 70 30 100 Meatu 0 58 42 100 27 73 100 0 54 46 100 Shinyanga Urban 0 63 37 100 24 76 100 0 55 45 100 Kishapu 0 64 36 100 32 68 100 0 59 41 100 Total 1 65 35 100 27 73 100 1 59 40 100 3.14 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm Income Total 3.15B Percent of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Male Female Total 3.15A Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 143 Bariadi 37,733 57 5,661 9 178 0 22,815 34 66,387 100 Maswa 19,797 57 1,438 4 217 1 13,174 38 34,626 100 Shinyanga Rural 23,243 60 1,483 4 0 0 14,114 36 38,841 100 Kahama 41,915 60 2,799 4 0 0 25,482 36 70,196 100 Bukombe 32,748 68 2,149 4 119 0 13,265 27 48,282 100 Meatu 14,562 53 1,294 5 83 0 11,332 42 27,272 100 Shinyanga Urban 4,806 59 451 5 0 0 2,957 36 8,214 100 Kishapu 17,322 58 2,146 7 0 0 10,635 35 30,103 100 Total 192,127 59 17,421 5 598 0 113,776 35 323,921 100 Bariadi 1,929 17 349 3 8,906 80 11,185 100 Maswa 1,921 22 216 3 6,489 75 8,625 100 Shinyanga Rural 1,797 28 0 0 4,625 72 6,422 100 Kahama 2,627 24 247 2 8,147 74 11,021 100 Bukombe 1,300 26 0 0 3,658 74 4,958 100 Meatu 993 24 138 3 3,089 73 4,220 100 Shinyanga Urban 391 20 92 5 1,501 76 1,984 100 Kishapu 1,766 32 81 1 3,673 67 5,520 100 Total 12,723 24 1,125 2 40,088 74 53,936 100 Bariadi 39,662 51 6,010 8 178 0 31,721 41 77,572 100 Maswa 21,718 50 1,655 4 217 1 19,663 45 43,252 100 Shinyanga Rural 25,040 55 1,483 3 0 0 18,740 41 45,263 100 Kahama 44,542 55 3,046 4 0 0 33,629 41 81,217 100 Bukombe 34,048 64 2,149 4 119 0 16,923 32 53,240 100 Meatu 15,555 49 1,432 5 83 0 14,422 46 31,492 100 Shinyanga Urban 5,197 51 543 5 0 0 4,458 44 10,198 100 Kishapu 19,088 54 2,227 6 0 0 14,309 40 35,624 100 Total 204,850 54 18,546 5 598 0 153,864 41 377,857 100 Cont….3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year 3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Ag Swahili & English Any Other Language District Female Swahili Swahili & English Don't Read / Write Total District Cont….3.16 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year Male Swahili Don't Read / Write Total Swahili District Total Total Swahili & English Any Other Language Don't Read / Write Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 144 3.17 Time Series of Male and Female Headed Households: Shinyanga Type of Holding (000') NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed 175 179 192 204 205 200 Female Headed 38 51 63 64 56 64 Total 213 230 255 268 261 264 Male Headed (%) 82 78 75 76 78 76 Female Headed (%) 18 22 25 24 22 24 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Bariadi 43,572 2,279 45,851 22,815 8,906 31,721 66,387 11,185 77,572 Maswa 21,452 2,137 23,589 13,174 6,489 19,663 34,626 8,625 43,252 Shinyanga Rural 24,726 1,797 26,523 14,114 4,625 18,740 38,841 6,422 45,263 Kahama 44,714 2,875 47,588 25,482 8,147 33,629 70,196 11,021 81,217 Bukombe 35,017 1,300 36,317 13,265 3,658 16,923 48,282 4,958 53,240 Meatu 15,939 1,131 17,070 11,332 3,089 14,422 27,272 4,220 31,492 Shinyanga Urban 5,257 483 5,740 2,957 1,501 4,458 8,214 1,984 10,198 Kishapu 19,468 1,847 21,315 10,635 3,673 14,309 30,103 5,520 35,624 Total 210,146 13,848 223,994 113,776 40,088 153,864 323,921 53,936 377,857 3.18 Literacy Rate of Heads of Households by Sex and District District Literacy Know Don;t know Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 145 Appendix II 146 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 147 No of Households % No of Households % No of Household s % No of Households % No of Household s % No of Households % No of Households % Bariadi 3,028 4 58,544 75 14,987 19 19,782 26 3,867 5 1,317 2 2,567 3 77,572 Maswa 1,326 3 32,629 75 8,430 19 9,352 22 3,306 8 749 2 1,257 3 43,252 Shinyanga R 1,116 2 34,482 76 13,113 29 6,218 14 2,731 6 203 0 1,600 4 45,263 Kahama 1,208 1 54,984 68 32,559 40 11,152 14 6,411 8 699 1 2,852 4 81,217 Bukombe 1,314 2 26,297 49 22,658 43 8,444 16 2,963 6 239 0 1,314 2 53,240 Meatu 1,365 4 19,782 63 8,520 27 9,290 29 4,275 14 954 3 1,786 6 31,492 Shinyanga U 1,478 14 7,983 78 1,604 16 1,076 11 672 7 47 0 158 2 10,198 Kishapu 471 1 24,479 69 9,550 27 6,674 19 5,521 15 641 2 882 2 35,624 Total 11,307 3 259,181 69 111,422 29 71,989 19 29,748 8 4,800 1 12,417 3 377,857 Area Leased/ Certificate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Lushoto 3,414 156,403 40,942 23,467 2,095 1,170 3,837 231,328 Korogwe 4,449 121,175 30,595 11,944 3,910 1,869 807 174,749 Muheza 3,621 79,761 32,608 6,484 2,340 91 2,603 127,507 Tanga 1,767 176,703 103,481 12,537 5,841 458 3,129 303,915 Pangani 1,983 95,910 76,239 13,340 2,735 218 2,902 193,327 Handeni 4,225 98,128 47,843 16,285 8,402 1,787 4,185 180,855 Kilindi 2,172 17,236 4,109 1,298 493 7 56 25,371 Kishapu 690 165,863 40,800 13,683 10,261 1,439 1,123 233,859 Total 22,321 911,178 376,618 99,038 36,075 7,038 18,642 1,470,910 % 2 62 26 7 2 0 1 100 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure District Total Number of Households Land Access 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 148 LAND USE Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 149 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Bariadi 74,809 9,122 2,220 1,387 2,055 6,776 2,043 1,704 3,134 2,046 2,688 14,305 77,572 Maswa 38,868 16,151 521 906 4,620 7,605 4,032 837 325 1,484 1,799 6,217 43,252 Shinyanga Rural 41,156 22,882 1,632 711 1,890 2,226 2,423 908 702 805 1,918 11,403 45,263 Kahama 68,120 50,663 2,454 2,925 7,003 3,778 21,587 5,798 852 2,004 2,742 15,649 81,217 Bukombe 42,068 29,455 239 1,074 2,146 2,739 8,521 1,429 478 2,135 1,293 7,490 53,240 Meatu 30,566 11,904 324 1,384 1,593 8,028 4,250 2,005 1,030 1,512 3,084 4,952 31,492 Shinyanga Urban 8,755 5,737 158 244 414 633 769 381 515 96 177 1,070 10,198 Kishapu 33,193 8,061 322 163 558 7,554 7,438 798 473 1,344 2,491 6,131 35,624 Total 150,120 86,312 57,423 42,241 76,275 2,509 35,758 1,542 16,954 4,726 7,899 41,911 377,857 Districts Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Bariadi 168,804 16,893 1,108 1,787 3,927 9,027 1,991 1,899 1,143 3,659 2,751 18,339 231,328 Maswa 94,664 21,124 1,394 1,777 10,626 19,459 7,843 1,028 153 2,344 2,744 11,593 174,749 Shinyanga Rural 69,269 32,008 516 390 2,091 4,329 3,862 1,245 135 598 1,822 11,242 127,507 Kahama 123,882 69,243 1,877 1,811 15,477 6,789 37,778 16,341 362 3,839 3,557 22,960 303,915 Bukombe 88,015 48,751 242 399 3,797 8,631 18,578 3,825 121 3,970 1,986 15,012 193,327 Meatu 88,390 19,067 544 5,602 5,442 27,527 10,120 2,594 1,029 4,454 4,731 11,358 180,855 Shinyanga Urban 11,542 7,122 55 102 525 1,343 1,418 921 89 246 160 1,459 24,981 Kishapu 109,050 19,139 311 132 713 44,277 23,708 6,266 422 2,174 8,679 16,610 231,481 Total 753,616 233,347 6,046 11,999 42,598 121,381 105,297 34,118 3,454 21,284 26,429 108,572 1,468,142 % 51 16 0 1 3 8 7 2 0 1 2 7 100 Land use area Type of Land Use 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 150 Number % Number % Number % Number % Bariadi 75,031 87 11,404 13 86,435 Bariadi 35,993 42 50,442 58 86,435 Maswa 29,280 64 16,420 36 45,700 Maswa 26,375 58 19,325 42 45,700 Shinyanga Rural 32,598 67 16,218 33 48,815 Shinyanga Rural 28,327 58 20,488 42 48,815 Kahama 3,596 42 4,960 58 8,555 Kahama 5,945 69 2,611 31 8,555 Bukombe 4,147 59 2,930 41 7,076 Bukombe 4,694 66 2,382 34 7,076 Meatu 20,561 43 27,070 57 47,631 Meatu 31,637 66 15,994 34 47,631 Shinyanga Urban 10,561 55 8,753 45 19,314 Shinyanga Urban 13,381 69 5,933 31 19,314 Total 175,773 67 87,754 33 263,528 Total 146,353 56 117,175 44 263,528 Number % Number % Bariadi 12,284 14 74,151 86 86,435 Maswa 11,206 25 34,494 75 45,700 Rural 14,802 30 34,013 70 48,815 Kahama 3,459 40 5,097 60 8,555 Bukombe 1,739 25 5,337 75 7,076 Meatu 16,758 35 30,873 65 47,631 Urban 2,326 12 16,988 88 19,314 Total 62,574 24 200,954 76 263,528 No Total Table 5.5: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year District Do any Female Members of the Household own or have customary right to Land Yes No Total Table 5.3: Number of Households by type of household and District during 2002/03 Agricultural Year Table 5.4: Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year District Was all Land Available to the Hh Used during 2002/03? District Do you Consider that you have sufficient land for the Hh? Yes No Total Yes Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 151 Appendix II 152 TOTAL ANNUAL CROP & VEGETABLE PRODUCTION – LONG & SHORT RAINY SEASON Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 153 Number of Household Planted Area (hectare) Number of Household Planted Area (hectare) Bariadi 0 0 77,393 182,648 182,648 0.00 Bukombe 108 580 42,935 111,811 112,392 0.52 Kahama 0 291 45,161 100,937 101,227 0.29 Shinyanga Rural 144 0 81,074 197,060 197,060 0.00 Meatu 239 1,651 52,643 132,870 134,521 1.23 Maswa 915 109 31,111 94,843 94,952 0.12 Shinyanga Urban 156 195 9,260 15,564 15,759 1.24 Kishapu 0 0 35,124 121,691 121,691 0.00 Total 1,561 2,826 374,699 957,423 960,250 0.29 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Bariadi - 77,572 77,393 179 77,572 Maswa 108 43,144 42,935 317 43,252 Shinyanga Rural - 45,263 45,161 102 45,263 Kahama 144 81,073 81,074 143 81,217 Bukombe 239 53,001 52,643 597 53,240 Meatu 915 30,577 31,111 380 31,492 Shinyanga Urban 156 10,042 9,260 939 10,198 Kishapu - 35,624 35,124 500 35,624 Total 1,561 376,296 374,699 3,158 377,857 % Area planted in short rainy season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District District Total area planted (hectare) Short Rainy Season Long Rainy Season 7.1 & 7.2b TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of crop growing Households Planting Crops by Season and Region District Short Rainy Season Long Rainy Season Total Number of Crop Growing households Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 154 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) CEREALS 1,873 1,139 589,543 315,047 591,416 316,187 Maize 1,541 647 420 398,729 190,755 478 400,270 191,402 478 Paddy 244 439 1,802 118,673 104,408 880 118,916 104,847 882 Sorghum 63 14 228 65,854 17,255 262 65,917 17,269 262 Bulrush Millet 26 38 1,482 5,998 2,491 415 6,024 2,530 420 Finger Millet 0 0 0 289 139 481 289 139 481 ROOTS & TUBERS 45 317 48,036 40,253 48,081 40,570 Cassava 0 0 19,235 14,599 759 19,235 14,599 759 Sweet Potatoes 45 317 7,116 27,556 25,059 909 27,601 25,376 919 Irish Potatoes 562 89 158 562 89 158 Yams 641 424 662 641 424 662 Cocoyam 41 82 1,976 41 82 1976 PULSES 104 27 67,704 34,323 67,809 34,350 Mung Beans 0 0 0 64 145 2,274 64 145 2274 Beans 101 25 247 38,843 16,295 420 38,944 16,320 419 Cowpeas 0 0 0 2,731 3,376 1,236 2,731 3,376 1236 Green Gram 0 0 0 755 2,898 3,836 755 2,898 3836 Chich Peas 0 0 0 23,933 10,315 431 23,933 10,315 431 Bambaranuts 3 2 494 1,379 1,295 939 1,382 1,296 938 OIL SEEDS & OIL NUTS 167 32 65,985 31,568 478 66,153 31,601 478 Sunflower 0 0 0 1,434 455 317 1,434 455 317 Simsim 0 0 0 364 194 534 364 194 534 Groundnuts 167 32 194 64,188 30,919 482 64,355 30,951 481 FRUIT & VEGETABLES 0 0 1,421 3,381 1,421 3,381 2380 Tomatoes 0 0 0 524 1,977 3,773 524 1,977 3773 Onions 0 0 0 257 503 1,956 257 503 1956 Egg Plant 0 0 0 203 83 408 203 83 408 Radish 0 0 0 199 121 609 199 121 609 Cabbage 0 0 0 104 461 4,443 104 461 4443 Amaranths 0 0 0 74 140 1,880 74 140 1880 Pumpkins 0 0 0 26 1 55 26 1 55 Cucumber 0 0 0 23 43 1,878 23 43 1878 Chillies 0 0 0 10 51 5,039 10 51 5039 CASH CROPS 637 172 204,383 106,815 205,020 106,987 522 Cotton 637 172 270 198,753 101,423 510 199,390 101,595 510 Tobacco 0 0 0 5,630 5,392 958 5,630 5,392 958 Total 2,826 1,661 977,072 497,065 979,898 498,726 bein produced on the same land during the 2 seasons. Previous surveys have used the Long season to estimate physical land area under production to different crops * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to crops 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Kahama Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 155 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 75,299 101,952 42,799 0.42 101,952 42,799 0.42 1.35 Maswa 108 44 9 0.20 38,409 35,115 14,371 0.41 35,159 14,380 0.41 0.92 Shinyanga Rural - 44,046 44,228 19,359 0.44 44,228 19,359 0.44 1.00 Kahama 144 174 72 0.41 78,402 79,731 58,011 0.73 79,905 58,083 0.73 1.02 Bukombe 239 314 244 0.78 51,714 64,519 37,758 0.59 64,833 38,002 0.59 1.25 Meatu 665 909 273 0.30 24,634 30,284 8,922 0.29 31,193 9,195 0.29 1.27 Shinyanga Urban 124 99 50 0.50 8,372 7,405 2,356 0.32 7,505 2,406 0.32 0.90 Kishapu - - - - 30,359 35,494 7,179 0.20 35,494 7,179 0.20 1.17 Total 1,279 1,541 647 0.42 351,234 398,729 190,755 3.39 400,270 191,402 0.48 1.14 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 17,093 6,914 5,769 0.83 6,914 5,769 0.83 0.40 Maswa 0 . . - 14,438 9,975 11,033 1.11 9,975 11,033 1.11 0.69 Shinyanga Rural - 28,678 20,937 18,119 0.87 20,937 18,119 0.87 0.73 Kahama 144 116 194 1.67 46,180 53,166 46,923 0.88 53,283 47,117 0.88 1.15 Bukombe 239 121 239 1.98 17,924 21,250 18,738 0.88 21,371 18,977 0.89 1.19 Meatu 0 . . - 1,314 349 161 0.46 349 161 0.46 0.27 Shinyanga Urban 32 6 6 0.99 3,396 1,621 1,382 0.85 1,628 1,389 0.85 0.48 Kishapu 7,024 4,459 2,282 0.51 4,459 2,282 0.00 0.63 Total 415 244 439 1.80 136,046 118,673 104,408 6.40 118,916 104,847 0.88 0.87 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 15,252 9,971 4,175 - 9,971 4,175 0.42 0.65 Maswa 0 . . - 9,906 7,950 3,098 - 7,950 3,098 0.00 0.80 Shinyanga Rural - 2,511 1,326 492 - 1,326 492 0.00 0.53 Kahama 0 . . - 427 101 62 0.61 101 62 0.61 0.24 Bukombe 0 . . - 597 227 78 0.34 227 78 0.34 0.38 Meatu 167 51 8 0.16 15,563 24,344 4,244 - 24,395 4,252 0.17 1.57 Shinyanga Urban 30 12 6 0.49 1,273 905 332 - 917 338 0.00 0.72 Kishapu 14,090 21,030 4,775 - 21,030 4,775 0.00 1.49 Total 196 63 14 0.23 59,619 65,854 17,255 0.95 65,917 17,269 0.26 1.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 119 97 6 - 97 6 0.00 0.81 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 32 26 38 1.48 1,271 1,645 1,384 - 1,671 1,422 0.00 1.32 Kishapu 2,473 4,256 1,102 0.26 4,256 1,102 0.00 1.72 Total 32 26 38 1.48 3,864 5,998 2,491 0.26 6,024 2,530 0.42 1.56 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Bulrushmillet District 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District Short Rainy Season Long Rainy Season Total District Paddy Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 156 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 353 180 92 0.51 180 92 0.51 0.51 Maswa 0 . . - 108 22 7 - 22 7 0.00 0.20 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 358 53 32 - 53 32 0.00 0.15 Meatu 0 . . - 83 34 8 - 34 8 0.00 0.40 Shinyanga Urban 0 . . - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 902 289 139 0.51 289 139 0.48 0.32 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Bariadi - 1,159 523 1,513 1.58 523 1,513 1.57 0.45 Maswa - 1,080 335 148 3.44 335 148 3.05 0.31 Shinyanga Rural - 7,173 3,755 5,395 2.37 3,755 5,395 2.36 0.52 Kahama - 16,910 7,752 3,560 2.65 7,752 3,560 2.65 0.46 Bukombe - 7,448 6,697 3,943 1.85 6,697 3,943 1.83 0.90 Meatu - 0 . . 3.52 0 0 2.85 - Shinyanga Urban - 551 174 39 3.07 174 39 3.06 0.32 Kishapu - . . - Total 0 0 0 - 34,321 19,235 14,599 18.48 19,235 14,599 0.76 0.56 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 9,695 2,384 2,075 0.87 2,384 2,075 0.87 0.25 Maswa - 20,195 5,729 5,383 0.94 5,729 5,383 0.94 0.28 Shinyanga Rural - 22,326 6,310 7,634 1.21 6,310 7,634 1.21 0.28 Kahama - 8,261 2,471 2,216 0.90 2,471 2,216 0.90 0.30 Bukombe - 2,852 989 1,351 1.37 989 1,351 1.37 0.35 Meatu - 8,466 2,378 1,136 0.48 2,378 1,136 0.48 0.28 Shinyanga Urban - 4,694 1,324 1,479 1.12 1,324 1,479 1.12 0.28 Kishapu 18,853 5,971 3,785 0.63 5,971 3,785 0.00 0.32 Total 0 0 0 - 95,342 27,556 25,059 7.51 27,556 25,059 0.91 0.29 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 356 144 18 0.12 144 18 0.12 0.40 Maswa - 108 22 26 1.19 22 26 1.19 0.20 Shinyanga Rural - 302 75 31 - 75 31 0.00 0.25 Kahama - 273 299 9 - 299 9 0.00 1.09 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 87 22 5 - 22 5 0.00 0.25 Kishapu - . . - Total 0 0 0 - 1,127 562 89 1.31 562 89 0.16 0.50 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Finger Millet District Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 157 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 178 36 14 - 36 14 0.00 0.20 Maswa - 2,107 451 333 0.74 451 333 0.74 0.21 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 142 57 34 - 57 34 0.00 0.40 Bukombe - 119 24 12 - 24 12 0.00 0.20 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 32 7 2 - 7 2 0.00 0.20 Kishapu 81 65 29 0.44 65 29 0.00 0.81 Total 0 0 0 - 2,659 641 424 1.18 641 424 0.66 0.24 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 - - Maswa - 0 . . - 0 0 - - Shinyanga Rural - 102 41 82 1.98 41 82 1.98 0.40 Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 102 41 82 1.98 41 82 1.98 0.40 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 1,739 372 81 0.22 372 81 0.22 0.21 Maswa 0 . . - 217 22 26 1.20 22 26 1.20 0.10 Shinyanga Rural - 500 100 14 0.14 100 14 0.14 0.20 Kahama 0 . . - 21,864 6,714 2,381 0.35 6,714 2,381 0.35 0.31 Bukombe 0 . . - 21,050 8,718 2,772 - 8,718 2,772 0.32 0.41 Meatu 167 101 25 0.25 869 238 92 0.39 339 117 0.35 0.39 Shinyanga Urban 0 . . - 54 17 9 0.54 17 9 0.54 0.32 Kishapu 70 114 7 0.06 114 7 0.00 1.62 Total 167 101 25 0.25 46,363 16,295 5,383 2.89 16,397 5,408 0.33 0.35 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 158 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 1,916 538 144 - 0 0 0.00 0.00 Maswa 2,276 285 85 0.08 295 24 0.08 0.13 Shinyanga Rural 3,622 700 205 0.21 2,016 482 0.24 0.56 Kahama 2,013 414 88 0.13 383 77 0.20 0.19 Bukombe 1,075 249 100 0.14 998 167 0.17 0.93 Meatu 1,635 392 111 0.20 7,982 1,798 0.23 4.88 Shinyanga Urban 112 45 15 0.18 333 76 0.23 2.98 Kishapu 1,118 752 102 0.14 752 102 0.00 0.67 Total 0 0 0 - 13,767 3,376 851 1.08 12,759 2,726 0.21 0.93 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 350 84 7 0.08 84 7 0.08 0.24 Maswa - 0 . . 0 0 #DIV/0! - Shinyanga Rural - 4,549 1,503 340 0.23 1,503 340 0.23 0.33 Kahama - 286 90 11 0.13 90 11 0.13 0.32 Bukombe - 358 135 55 0.41 135 55 0.41 0.38 Meatu - 393 135 17 0.12 135 17 0.12 0.34 Shinyanga Urban - 62 25 10 0.40 25 10 0.40 0.40 Kishapu 1,585 925 191 0.21 925 191 0.21 0.58 Total 0 0 0 - 7,584 2,898 630 1.57 2,898 630 0.22 0.38 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 2,423 2,503 904 - 2,503 904 0.00 1.03 Maswa - 633 363 193 - 363 193 0.00 0.57 Shinyanga Rural - 5,438 8,927 4,379 - 8,927 4,379 0.00 1.64 Kahama - 987 3,154 1,552 - 3,154 1,552 0.00 3.20 Bukombe - 949 2,922 858 - 2,922 858 0.29 3.08 Meatu - 162 174 90 - 174 90 0.00 1.08 Shinyanga Urban - 220 134 53 - 134 53 0.00 0.61 Kishapu 4,521 5,755 2,286 0.40 5,755 2,286 0.40 1.27 Total 0 0 0 - 15,333 23,933 10,315 0.40 23,933 10,315 0.43 1.56 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 1,516 383 666 - 383 666 0.00 0.25 Shinyanga Rural - 1,203 315 143 - 315 143 0.00 0.26 Kahama 0 . . - 2,266 502 395 - 502 395 0.79 0.22 Bukombe 0 . . - 119 10 7 - 10 7 0.00 0.08 Meatu 0 . . - 0 . . - 0 0 0.00 - Shinyanga Urban 32 3 2 0.49 379 105 50 - 108 51 0.00 0.29 Kishapu 409 64 33 0.51 64 33 0.51 0.16 Total 32 3 2 0.49 5,893 1,379 1,295 0.51 1,382 1,296 0.94 0.23 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 159 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 . . - 0 0 0.00 - Maswa 0 . . - 101 123 55 - 123 55 0.00 1.21 Shinyanga Rural 0 . . - 300 141 45 - 141 45 0.00 0.47 Kahama 0 . . - 425 172 68 - 172 68 0.00 0.40 Bukombe 0 . . - 1,434 859 228 - 859 228 0.00 0.60 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 0 . . - 31 6 6 - 6 6 0.00 0.20 Kishapu 82 133 54 0.41 133 54 0.41 1.62 Total 0 0 0 - 2,373 1,434 455 0.41 1,434 455 0.32 0.60 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 336 83 66 - 83 66 0.00 0.25 Maswa 0 . . - 108 22 0 - 22 0 0.00 0.20 Shinyanga Rural - 190 138 83 0.60 138 83 0.60 0.73 Kahama 0 . . - 0 . . - 0 0 - - Bukombe 0 . . - 0 . . - 0 0 - - Meatu 0 . . - 81 25 7 0.26 25 7 0.26 0.30 Shinyanga Urban 0 . . - 0 . . - 0 0 - - Kishapu 79 96 39 0.41 96 39 0.41 1.21 Total 0 0 0 - 794 364 194 1.27 364 194 0.53 0.46 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 8,131 2,845 1,135 - 2,845 1,135 0.00 0.35 Maswa 0 . . - 14,132 6,427 2,388 0.37 6,427 2,388 0.37 0.45 Shinyanga Rural - 26,037 9,766 5,932 0.61 9,766 5,932 0.61 0.38 Kahama 0 . . - 44,313 19,995 11,691 0.58 19,995 11,691 0.58 0.45 Bukombe 119 97 30 0.31 19,917 11,202 6,512 0.58 11,299 6,542 0.58 0.57 Meatu 83 67 0 - 7,221 2,968 692 0.23 3,035 692 0.23 0.42 Shinyanga Urban 32 3 3 0.79 3,344 1,544 636 0.41 1,547 639 0.41 0.46 Kishapu 14,710 9,441 1,933 0.20 9,441 1,933 0.20 0.64 Total 235 167 32 0.19 137,805 64,188 30,919 3.00 64,355 30,951 0.48 0.47 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 160 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 147 20 14 0.68 20 14 0.68 0.14 Bukombe - 73 6 3 0.46 6 3 0.46 0.09 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 220 26 17 1.14 26 17 0.63 0.12 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 270 36 118 3.24 36 118 3.24 0.13 Kahama - 0 . . - 0 0 0.00 - Bukombe - 59 10 8 0.81 10 8 0.81 0.18 Meatu - 212 129 170 1.32 129 170 1.32 0.61 Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 541 176 296 5.37 176 296 1.69 0.32 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 161 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - . . 0 - 0 0 - - Maswa - . . 0 - 0 0 - - Shinyanga Rural - 171 392 0 - 392 0 0.00 2.29 Kahama - 28 28 0 - 28 0 0.00 0.99 Bukombe - . . 0 - 0 0 - - Meatu - . . 0 - 0 0 0.00 - Shinyanga Urban - . . 31 - 0 31 - - Kishapu 58 83 - - 83 0 0.00 1.43 Total 0 0 0 257 503 31 - 503 31 0.06 1.96 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 342 53 118 2.24 53 118 2.24 0.15 Maswa - 0 . . - 0 0 - - Shinyanga Rural - 101 10 15 - 10 15 1.48 0.10 Kahama - 285 22 307 13.98 22 307 13.98 0.08 Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 47 19 21 1.09 19 21 1.09 0.40 Kishapu - . . - Total 0 0 0 - 776 104 461 17.31 104 461 4.44 0.13 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 357 36 152 4.20 36 152 4.20 0.10 Maswa - 0 . . - 0 0 #DIV/0! - Shinyanga Rural - 805 165 619 3.74 165 619 3.74 0.21 Kahama - 851 160 398 2.48 160 398 2.48 0.19 Bukombe - 119 12 211 17.49 12 211 17.49 0.10 Meatu - 81 16 36 2.22 16 36 2.22 0.20 Shinyanga Urban - 341 93 373 4.04 93 373 4.04 0.27 Kishapu 163 41 188 4.54 41 188 4.54 0.25 Total 0 0 0 - 2,717 524 1,977 38.71 524 1,977 3.77 0.19 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 162 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 106 17 0 - 17 0 0.00 0.16 Shinyanga Rural - 86 5 0 - 5 0 0.00 0.06 Kahama - 54 2 2 0.87 2 2 0.87 0.04 Bukombe - 22 9 0 - 9 0 0.00 0.40 Meatu - 310 31 29 0.92 31 29 0.92 0.10 Shinyanga Urban - 0 . . - 0 0 - - Kishapu - Total 0 0 0 - 579 65 31 1.79 65 31 0.47 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 273 90 668 7.39 90 668 7.39 0.33 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 273 90 668 7.39 90 668 7.39 0.33 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 0.00 - Maswa 0 . . - 0 0 0.00 - Shinyanga Rural 79 8 8 1.04 8 8 1.04 0.10 Kahama 66 7 8 1.17 7 8 1.17 0.10 Bukombe 59 8 4 0.42 8 4 0.42 0.14 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 0.00 - Kishapu - Total 204 23 20 2.63 23 20 0.86 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 193 76 687 9.02 76 687 9.02 0.39 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 21 2 12 5.93 2 12 5.93 0.10 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 214 78 699 14.95 78 699 8.94 0.37 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 163 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 48,808 53,882 32,074 0.60 53,882 32,074 0.60 1.10 Maswa 108 66 15 0.23 32,967 44,575 22,036 0.49 44,640 22,051 0.49 1.35 Shinyanga Rural - 2,303 2,105 963 0.46 2,105 963 0.46 0.91 Kahama 0 . . - 14,316 16,803 12,165 0.72 16,803 12,165 0.72 1.17 Bukombe 119 48 10 0.20 12,882 14,750 12,560 0.85 14,798 12,570 0.85 1.15 Meatu 333 523 147 0.28 20,918 33,505 10,800 0.32 34,028 10,947 0.32 1.63 Shinyanga Urban 0 . . - 380 385 264 0.69 385 264 0.69 1.01 Kishapu 19,267 32,748 10,563 0.32 32,748 10,563 0.32 1.70 Total 561 637 172 0.27 151,840 198,753 101,423 4.45 199,390 101,595 0.51 1.31 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 - - Maswa 0 . . - 0 0 - - Shinyanga Rural 102 41 20 0.49 41 20 0.49 0.40 Kahama 5,406 5,413 5,241 - 5,413 5,241 0.00 1.00 Bukombe 358 109 123 1.13 109 123 1.13 0.30 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 - - Kishapu 82 66 8 0.12 66 8 0.12 0.81 Total 0 0 0 5,948 5,630 5,392 0.96 5,630 5,392 0.96 0.95 Average Planted Area Per household Average Planted Area Per household 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 164 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,671 5,315 65,617 164,355 10,104 12,527 77,393 182,196 Maswa 1,720 9,247 31,164 89,584 10,158 13,085 43,042 111,916 Shinyanga Rural 810 1,229 36,243 86,690 8,108 12,605 45,161 100,524 Kahama 1,520 6,167 16,219 49,833 63,478 140,776 81,218 196,776 Bukombe 1,427 2,240 5,727 32,312 45,727 98,898 52,882 133,450 Meatu 950 4,552 25,373 82,614 5,703 9,328 32,026 96,494 Shinyanga Urban 91 99 6,441 12,183 2,883 3,477 9,415 15,759 Kishapu 562 3,135 31,040 112,432 3,521 6,125 35,124 121,691 Total 8,753 31984.2 217,825 630,001 149,683 296,821 376,261 958,806 % 0.9 3.3 22.7 65.7 15.6 31.0 39.2 100.0 Total Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Planted Area Bariadi 6,857 25,192 1,064 2,158 0 0 69,472 155,298 182,648 Maswa 4,374 13,327 528 1,299 216 175 37,924 97,119 111,920 Shinyanga Rural 8,776 20,436 569 465 0 0 35,816 80,035 100,937 Kahama 15,057 38,570 2,314 3,538 6,722 18,336 57,126 136,906 197,351 Bukombe 4,611 16,482 1,673 3,507 358 931 46,239 112,530 133,450 Meatu 2,418 9,563 83 671 0 0 29,525 86,259 96,494 Shinyanga Urban 2,710 3,393 294 826 32 110 6,380 11,430 15,759 Kishapu 3,266 10,798 567 2,386 79 827 31,212 107,681 121,691 Total 48,069 137,761 7,091 14,850 7,407 20,380 313,694 787,259 960,250 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,921 4,966 74,472 177,682 77,393 182,648 2.7 Maswa 648 1,580 42,395 110,341 43,042 111,920 1.4 Shinyanga Rural 1,824 3,152 43,337 97,784 45,161 100,937 3.1 Kahama 1,830 6,309 79,387 191,042 81,218 197,351 3.2 Bukombe 712 1,338 52,170 132,113 52,882 133,450 1.0 Meatu 167 641 31,859 95,852 32,026 96,494 0.7 Shinyanga Urban 538 863 8,878 14,896 9,415 15,759 5.5 Kishapu 1,283 2,597 33,840 119,094 35,124 121,691 2.1 Total 9,922 21,445 366,339 938,804 376,261 960,250 2.2 % 2.6 2.2 97.4 97.8 100.0 100.0 2.2 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga Region District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Shinyanga District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Shinyanya Region District Soil Preparation y Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 165 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 32,717 103,285 44,676 79,362 77,393 182,648 56.55 Maswa 7,974 25,522 35,068 86,398 43,042 111,920 22.80 Shinyanga Rural 3,313 9,686 41,847 91,251 45,161 100,937 9.60 Kahama 22,480 68,787 58,737 128,564 81,218 197,351 34.86 Bukombe 12,997 47,075 39,885 86,376 52,882 133,450 35.28 Meatu 9,424 34,836 22,602 61,658 32,026 96,494 36.10 Shinyanga Urban 612 1,584 8,804 14,174 9,415 15,759 10.05 Kishapu 7,920 40,118 27,204 81,574 35,124 121,691 32.97 Total 97,437 330,893 278,824 629,357 376,261 960,250 34.5 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,599 3,171 75,794 179,477 77,393 182,648 1.74 Maswa 650 1,053 42,392 110,867 43,042 111,920 0.94 Shinyanga Rural 1,406 2,737 43,755 98,199 45,161 100,937 2.71 Kahama 1,264 2,721 79,954 194,629 81,218 197,351 1.38 Bukombe 597 1,645 52,284 131,806 52,882 133,450 1.23 Meatu 315 884 31,711 95,609 32,026 96,494 0.92 Shinyanga Urban 122 259 9,294 15,500 9,415 15,759 1.64 Kishapu 1,157 5,050 33,967 116,641 35,124 121,691 4.15 Total 7,109 17,521 369,151 942,729 376,261 960,250 1.82 % 2 2 98 98 100 100 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted area using Insecticide District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Herbicide 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Kahama. Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 166 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,446 5,872 74,947 176,775 77,393 182,648 3.2 Maswa 3,566 8,745 39,477 103,175 43,042 111,920 7.8 Shinyanga Rural 1,906 3,494 43,255 97,442 45,161 100,937 3.5 Kahama 4,007 13,910 77,210 183,441 81,218 197,351 7.0 Bukombe 1,668 6,191 51,214 127,259 52,882 133,450 4.6 Meatu 167 742 31,859 95,751 32,026 96,494 0.8 Shinyanga Urban 313 670 9,102 15,089 9,415 15,759 4.3 Kishapu 891 3,384 34,233 118,307 35,124 121,691 2.8 Total 14,963 7,220 423,390 393,090 430,102 400,310 1.8 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 17,809 48,537 59,584 133,659 77,393 182,196 26.64 Maswa 12,159 39,669 30,884 72,247 43,042 111,916 35.45 Shinyanga Rural 3,605 10,983 41,556 89,541 45,161 100,524 10.93 Kahama 13,945 37,903 67,272 158,873 81,218 196,776 19.26 Bukombe 4,293 16,328 48,588 117,122 52,882 133,450 12.24 Meatu 13,388 47,553 18,638 48,941 32,026 96,494 49.28 Shinyanga Urban 1,473 2,197 7,943 13,561 9,415 15,759 13.94 Kishapu 13,285 57,895 21,839 63,796 35,124 121,691 47.58 Total 79,957 261,066 296,304 697,741 376,261 958,806 27.23 % 21 27 79 73 100 100 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Improved Seeds % of Planted area using Fungicide 7.1 & 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Shinyanga Region 7.1 &7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Shinyanga Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total Tanzania Agriculture Sample Census-2003 Shinyanga 167 Appendix II 168 ANNUAL CROP & VEGETABLE PRODUCTION – LONG RAINY SEASON Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 169 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Bariadi 1,671 5,315 65,617 164,355 10,104 12,527 77,393 182,196 Maswa 1,720 9,247 31,056 89,475 10,158 13,085 42,935 111,807 Shinyanga Rural 810 1,229 36,243 86,690 8,108 12,605 45,161 100,524 Kahama 1,520 6,167 16,219 49,833 63,335 140,485 81,074 196,485 Bukombe 1,427 2,240 5,727 32,312 45,488 98,318 52,643 132,870 Meatu 867 4,383 25,206 82,344 5,038 8,115 31,111 94,843 Shinyanga Urban 91 99 6,379 12,077 2,789 3,388 9,260 15,564 Kishapu 562 3,135 31,040 112,432 3,521 6,125 35,124 121,691 Total 8,670 31,815 217,488 629,516 148,541 294,648 374,699 955,980 % 2 3 58 66 40 31 100 100 No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area Bariadi 6,857 25,192 1,064 2,158 0 . 69,472 155,298 77,393 182,648 Maswa 4,374 13,327 420 1,190 216 175 37,924 97,119 42,935 111,811 Shinyanga Rural 8,776 20,436 569 465 0 . 35,816 80,035 45,161 100,937 Kahama 14,913 38,280 2,314 3,538 6,722 18,336 57,126 136,906 81,074 197,060 Bukombe 4,611 16,482 1,553 3,169 358 931 46,120 112,288 52,643 132,870 Meatu 2,335 9,394 83 671 0 . 28,693 84,777 31,111 94,843 Shinyanga Urban 2,584 3,252 294 826 32 110 6,350 11,376 9,260 15,564 Kishapu 3,266 10,798 567 2,386 79 827 31,212 107,681 35,124 121,691 Total 47,716 137,161 6,864 14,402 7,407 20,380 312,714 785,481 374,699 957,423 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Bariadi 2,921 4,966 74,472 177,682 77,393 182,648 2.7 Maswa 648 1,580 42,287 110,231 42,935 111,811 1.4 Shinyanga Rural 1,824 3,152 43,337 97,784 45,161 100,937 3.1 Kahama 1,830 6,309 79,244 190,751 81,074 197,060 3.2 Bukombe 712 1,338 51,931 131,532 52,643 132,870 1.0 Meatu 167 641 30,945 94,202 31,111 94,843 0.7 Shinyanga Urban 538 863 8,722 14,701 9,260 15,564 5.5 Kishapu 1,283 2,597 33,840 119,094 35,124 121,691 2.1 Total 9,922 21,445 364,778 935,978 374,699 957,423 2.2 % 3 2 97 98 100 100 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Kahama Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Irrigation Use % of area planted under irrigation in long rainy season Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 170 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 32,717 103,285 44,676 79,362 77,393 182,648 Maswa 7,974 25,522 34,960 86,289 42,935 111,811 Shinyanga Rural 3,313 9,686 41,847 91,251 45,161 100,937 Kahama 22,480 68,787 58,594 128,273 81,074 197,060 Bukombe 12,997 47,075 39,646 85,795 52,643 132,870 Meatu 9,424 34,836 21,687 60,007 31,111 94,843 Shinyanga Urban 612 1,584 8,648 13,980 9,260 15,564 Kishapu 7,920 40,118 27,204 81,574 35,124 121,691 Total 97,437 330,893 277,263 626,531 374,699 957,423 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 1,599 3,171 75,794 179,477 77,393 182,648 1.7 Maswa 650 1,053 42,284 110,758 42,935 111,811 0.9 Shinyanga Rural 1,406 2,737 43,755 98,199 45,161 100,937 2.7 Kahama 1,264 2,721 79,810 194,339 81,074 197,060 1.4 Bukombe 597 1,645 52,045 131,225 52,643 132,870 1.2 Meatu 315 884 30,796 93,958 31,111 94,843 0.9 Shinyanga Urban 122 259 9,138 15,305 9,260 15,564 1.7 Kishapu 1,157 5,050 33,967 116,641 35,124 121,691 4.2 Total 7,109 17,521 367,590 939,903 374,699 957,423 1.8 % 2 2 98 98 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 2,446 5,872 74,947 176,775 77,393 182,648 3.2 Maswa 3,566 8,745 39,369 103,066 42,935 111,811 7.8 Shinyanga Rural 1,906 3,494 43,255 97,442 45,161 100,937 3.5 Kahama 4,007 13,910 77,067 183,150 81,074 197,060 7.1 Bukombe 1,668 6,191 50,975 126,679 52,643 132,870 4.7 Meatu 83 169 31,028 94,674 31,111 94,843 0.2 Shinyanga Urban 313 670 8,946 14,894 9,260 15,564 4.3 Kishapu 891 3,384 34,233 118,307 35,124 121,691 2.8 Total 14,880 42,435 359,819 914,988 374,699 957,423 4.4 % 4.0 4.4 96.0 95.6 100.0 100.0 % of Planted area using Fungicide Households Not Using Herbicide 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region District Insecticide Use Households Using District Herbicide Use Households Using Herbicide Households Not Using Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Kahama Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total % of Planted area using Herbicide Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 171 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Bariadi 17,809 48,537 59,584 133,659 77,393 182,196 27 Maswa 12,159 39,669 30,776 72,138 42,935 111,807 35 Shinyanga Rural 3,605 10,983 41,556 89,541 45,161 100,524 11 Kahama 13,945 37,903 67,129 158,582 81,074 196,485 19 Bukombe 4,174 15,989 48,469 116,880 52,643 132,870 12 Meatu 12,640 46,172 18,471 48,671 31,111 94,843 49 Shinyanga Urban 1,473 2,197 7,787 13,367 9,260 15,564 14 Kishapu 13,285 57,895 21,839 63,796 35,124 121,691 48 Total 79,089 259,346 295,610 696,634 374,699 955,980 27 % 21 27 79 73 100 100 District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON, Kahama Region Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 172 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 75,299 101,952 42,799 0.42 101,952 42,799 0.42 1.35 Maswa 108 44 9 0.20 38,409 35,115 14,371 0.41 35,159 14,380 0.41 0.92 Shinyanga Rural - 44,046 44,228 19,359 0.44 44,228 19,359 0.44 1.00 Kahama 144 174 72 0.41 78,402 79,731 58,011 0.73 79,905 58,083 0.73 1.02 Bukombe 239 314 244 0.78 51,714 64,519 37,758 0.59 64,833 38,002 0.59 1.25 Meatu 665 909 273 0.30 24,634 30,284 8,922 0.29 31,193 9,195 0.29 1.27 Shinyanga Urban 124 99 50 0.50 8,372 7,405 2,356 0.32 7,505 2,406 0.32 0.90 Kishapu - - - - 30,359 35,494 7,179 0.20 35,494 7,179 0.20 1.17 Total 1,279 1,541 647 0.42 351,234 398,729 190,755 3.39 400,270 191,402 0.48 1.14 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 17,093 6,914 5,769 0.83 6,914 5,769 0.83 0.40 Maswa 0 . . - 14,438 9,975 11,033 1.11 9,975 11,033 1.11 0.69 Shinyanga Rural - 28,678 20,937 18,119 0.87 20,937 18,119 0.87 0.73 Kahama 144 116 194 1.67 46,180 53,166 46,923 0.88 53,283 47,117 0.88 1.15 Bukombe 239 121 239 1.98 17,924 21,250 18,738 0.88 21,371 18,977 0.89 1.19 Meatu 0 . . - 1,314 349 161 0.46 349 161 0.46 0.27 Shinyanga Urban 32 6 6 0.99 3,396 1,621 1,382 0.85 1,628 1,389 0.85 0.48 Kishapu 7,024 4,459 2,282 0.51 4,459 2,282 0.00 0.63 Total 415 244 439 1.80 136,046 118,673 104,408 6.40 118,916 104,847 0.88 0.87 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 15,252 9,971 4,175 - 9,971 4,175 0.42 0.65 Maswa 0 . . - 9,906 7,950 3,098 - 7,950 3,098 0.00 0.80 Shinyanga Rural - 2,511 1,326 492 - 1,326 492 0.00 0.53 Kahama 0 . . - 427 101 62 0.61 101 62 0.61 0.24 Bukombe 0 . . - 597 227 78 0.34 227 78 0.34 0.38 Meatu 167 51 8 0.16 15,563 24,344 4,244 - 24,395 4,252 0.17 1.57 Shinyanga Urban 30 12 6 0.49 1,273 905 332 - 917 338 0.00 0.72 Kishapu 14,090 21,030 4,775 - 21,030 4,775 0.00 1.49 Total 196 63 14 0.23 59,619 65,854 17,255 0.95 65,917 17,269 0.26 1.11 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District Short Rainy Season Long Rainy Season Total District Paddy Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 173 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 119 97 6 - 97 6 0.00 0.81 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 32 26 38 1.48 1,271 1,645 1,384 - 1,671 1,422 0.00 1.32 Kishapu 2,473 4,256 1,102 0.26 4,256 1,102 0.00 1.72 Total 32 26 38 1.48 3,864 5,998 2,491 0.26 6,024 2,530 0.42 1.56 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 353 180 92 0.51 180 92 0.51 0.51 Maswa 0 . . - 108 22 7 - 22 7 0.00 0.20 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama 0 . . - 0 . . - 0 0 0.00 - Bukombe 0 . . - 358 53 32 - 53 32 0.00 0.15 Meatu 0 . . - 83 34 8 - 34 8 0.00 0.40 Shinyanga Urban 0 . . - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 902 289 139 0.51 289 139 0.48 0.32 Average Planted Area Per household Average Planted Area Per household 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Finger Millet District 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Bulrushmillet District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 174 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Bariadi - 1,159 523 1,513 1.58 523 1,513 1.57 0.45 Maswa - 1,080 335 148 3.44 335 148 3.05 0.31 Shinyanga Rural - 7,173 3,755 5,395 2.37 3,755 5,395 2.36 0.52 Kahama - 16,910 7,752 3,560 2.65 7,752 3,560 2.65 0.46 Bukombe - 7,448 6,697 3,943 1.85 6,697 3,943 1.83 0.90 Meatu - 0 . . 3.52 0 0 2.85 - Shinyanga Urban - 551 174 39 3.07 174 39 3.06 0.32 Kishapu - . . - Total 0 0 0 - 34,321 19,235 14,599 18.48 19,235 14,599 0.76 0.56 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 9,695 2,384 2,075 0.87 2,384 2,075 0.87 0.25 Maswa - 20,195 5,729 5,383 0.94 5,729 5,383 0.94 0.28 Shinyanga Rural - 22,326 6,310 7,634 1.21 6,310 7,634 1.21 0.28 Kahama - 8,261 2,471 2,216 0.90 2,471 2,216 0.90 0.30 Bukombe - 2,852 989 1,351 1.37 989 1,351 1.37 0.35 Meatu - 8,466 2,378 1,136 0.48 2,378 1,136 0.48 0.28 Shinyanga Urban - 4,694 1,324 1,479 1.12 1,324 1,479 1.12 0.28 Kishapu 18,853 5,971 3,785 0.63 5,971 3,785 0.00 0.32 Total 0 0 0 - 95,342 27,556 25,059 7.51 27,556 25,059 0.91 0.29 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 356 144 18 0.12 144 18 0.12 0.40 Maswa - 108 22 26 1.19 22 26 1.19 0.20 Shinyanga Rural - 302 75 31 - 75 31 0.00 0.25 Kahama - 273 299 9 - 299 9 0.00 1.09 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 87 22 5 - 22 5 0.00 0.25 Kishapu - . . - Total 0 0 0 - 1,127 562 89 1.31 562 89 0.16 0.50 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 175 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 178 36 14 - 36 14 0.00 0.20 Maswa - 2,107 451 333 0.74 451 333 0.74 0.21 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 142 57 34 - 57 34 0.00 0.40 Bukombe - 119 24 12 - 24 12 0.00 0.20 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 32 7 2 - 7 2 0.00 0.20 Kishapu 81 65 29 0.44 65 29 0.00 0.81 Total 0 0 0 - 2,659 641 424 1.18 641 424 0.66 0.24 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 - - Maswa - 0 . . - 0 0 - - Shinyanga Rural - 102 41 82 1.98 41 82 1.98 0.40 Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - . . - Total 0 0 0 - 102 41 82 1.98 41 82 1.98 0.40 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 1,739 372 81 0.22 372 81 0.22 0.21 Maswa 0 . . - 217 22 26 1.20 22 26 1.20 0.10 Shinyanga Rural - 500 100 14 0.14 100 14 0.14 0.20 Kahama 0 . . - 21,864 6,714 2,381 0.35 6,714 2,381 0.35 0.31 Bukombe 0 . . - 21,050 8,718 2,772 - 8,718 2,772 0.32 0.41 Meatu 167 101 25 0.25 869 238 92 0.39 339 117 0.35 0.39 Shinyanga Urban 0 . . - 54 17 9 0.54 17 9 0.54 0.32 Kishapu 70 114 7 0.06 114 7 0.00 1.62 Total 167 101 25 0.25 46,363 16,295 5,383 2.89 16,397 5,408 0.33 0.35 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 176 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 1,916 538 144 - 0 0 0.00 0.00 Maswa 2,276 285 85 0.08 295 24 0.08 0.13 Shinyanga Rural 3,622 700 205 0.21 2,016 482 0.24 0.56 Kahama 2,013 414 88 0.13 383 77 0.20 0.19 Bukombe 1,075 249 100 0.14 998 167 0.17 0.93 Meatu 1,635 392 111 0.20 7,982 1,798 0.23 4.88 Shinyanga Urban 112 45 15 0.18 333 76 0.23 2.98 Kishapu 1,118 752 102 0.14 752 102 0.00 0.67 Total 0 0 0 - 13,767 3,376 851 1.08 12,759 2,726 0.21 0.93 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 350 84 7 0.08 84 7 0.08 0.24 Maswa - 0 . . 0 0 0 - Shinyanga Rural - 4,549 1,503 340 0.23 1,503 340 0.23 0.33 Kahama - 286 90 11 0.13 90 11 0.13 0.32 Bukombe - 358 135 55 0.41 135 55 0.41 0.38 Meatu - 393 135 17 0.12 135 17 0.12 0.34 Shinyanga Urban - 62 25 10 0.40 25 10 0.40 0.40 Kishapu 1,585 925 191 0.21 925 191 0.21 0.58 Total 0 0 0 - 7,584 2,898 630 1.57 2,898 630 0.22 0.38 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 2,423 2,503 904 - 2,503 904 0.00 1.03 Maswa - 633 363 193 - 363 193 0.00 0.57 Shinyanga Rural - 5,438 8,927 4,379 - 8,927 4,379 0.00 1.64 Kahama - 987 3,154 1,552 - 3,154 1,552 0.00 3.20 Bukombe - 949 2,922 858 - 2,922 858 0.29 3.08 Meatu - 162 174 90 - 174 90 0.00 1.08 Shinyanga Urban - 220 134 53 - 134 53 0.00 0.61 Kishapu 4,521 5,755 2,286 0.40 5,755 2,286 0.40 1.27 Total 0 0 0 - 15,333 23,933 10,315 0.40 23,933 10,315 0.43 1.56 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 177 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa 0 . . - 1,516 383 666 - 383 666 0.00 0.25 Shinyanga Rural - 1,203 315 143 - 315 143 0.00 0.26 Kahama 0 . . - 2,266 502 395 - 502 395 0.79 0.22 Bukombe 0 . . - 119 10 7 - 10 7 0.00 0.08 Meatu 0 . . - 0 . . - 0 0 0.00 - Shinyanga Urban 32 3 2 0.49 379 105 50 - 108 51 0.00 0.29 Kishapu 409 64 33 0.51 64 33 0.51 0.16 Total 32 3 2 0.49 5,893 1,379 1,295 0.51 1,382 1,296 0.94 0.23 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 . . - 0 0 0.00 - Maswa 0 . . - 101 123 55 - 123 55 0.00 1.21 Shinyanga Rural 0 . . - 300 141 45 - 141 45 0.00 0.47 Kahama 0 . . - 425 172 68 - 172 68 0.00 0.40 Bukombe 0 . . - 1,434 859 228 - 859 228 0.00 0.60 Meatu 0 . . - 0 . . - 0 0 - - Shinyanga Urban 0 . . - 31 6 6 - 6 6 0.00 0.20 Kishapu 82 133 54 0.41 133 54 0.41 1.62 Total 0 0 0 - 2,373 1,434 455 0.41 1,434 455 0.32 0.60 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 336 83 66 - 83 66 0.00 0.25 Maswa 0 . . - 108 22 0 - 22 0 0.00 0.20 Shinyanga Rural - 190 138 83 0.60 138 83 0.60 0.73 Kahama 0 . . - 0 . . - 0 0 - - Bukombe 0 . . - 0 . . - 0 0 - - Meatu 0 . . - 81 25 7 0.26 25 7 0.26 0.30 Shinyanga Urban 0 . . - 0 . . - 0 0 - - Kishapu 79 96 39 0.41 96 39 0.41 1.21 Total 0 0 0 - 794 364 194 1.27 364 194 0.53 0.46 Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 178 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 8,131 2,845 1,135 - 2,845 1,135 0.00 0.35 Maswa 0 . . - 14,132 6,427 2,388 0.37 6,427 2,388 0.37 0.45 Shinyanga Rural - 26,037 9,766 5,932 0.61 9,766 5,932 0.61 0.38 Kahama 0 . . - 44,313 19,995 11,691 0.58 19,995 11,691 0.58 0.45 Bukombe 119 97 30 0.31 19,917 11,202 6,512 0.58 11,299 6,542 0.58 0.57 Meatu 83 67 0 - 7,221 2,968 692 0.23 3,035 692 0.23 0.42 Shinyanga Urban 32 3 3 0.79 3,344 1,544 636 0.41 1,547 639 0.41 0.46 Kishapu 14,710 9,441 1,933 0.20 9,441 1,933 0.20 0.64 Total 235 167 32 0.19 137,805 64,188 30,919 3.00 64,355 30,951 0.48 0.47 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 147 20 14 0.68 20 14 0.68 0.14 Bukombe - 73 6 3 0.46 6 3 0.46 0.09 Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 220 26 17 1.14 26 17 0.63 0.12 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 0 . . - 0 0 0.00 - Shinyanga Rural - 270 36 118 3.24 36 118 3.24 0.13 Kahama - 0 . . - 0 0 0.00 - Bukombe - 59 10 8 0.81 10 8 0.81 0.18 Meatu - 212 129 170 1.32 129 170 1.32 0.61 Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 541 176 296 5.37 176 296 1.69 0.32 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District Average Planted Area Per household Average Planted Area Per household 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 179 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - . . 0 - 0 0 - - Maswa - . . 0 - 0 0 - - Shinyanga Rural - 171 392 0 - 392 0 0.00 2.29 Kahama - 28 28 0 - 28 0 0.00 0.99 Bukombe - . . 0 - 0 0 - - Meatu - . . 0 - 0 0 0.00 - Shinyanga Urban - . . 31 - 0 31 - - Kishapu 58 83 - - 83 0 0.00 1.43 Total 0 0 0 257 503 31 - 503 31 0.06 1.96 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 342 53 118 2.24 53 118 2.24 0.15 Maswa - 0 . . - 0 0 - - Shinyanga Rural - 101 10 15 - 10 15 1.48 0.10 Kahama - 285 22 307 13.98 22 307 13.98 0.08 Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 47 19 21 1.09 19 21 1.09 0.40 Kishapu - . . - Total 0 0 0 - 776 104 461 17.31 104 461 4.44 0.13 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 357 36 152 4.20 36 152 4.20 0.10 Maswa - 0 . . - 0 0 0 - Shinyanga Rural - 805 165 619 3.74 165 619 3.74 0.21 Kahama - 851 160 398 2.48 160 398 2.48 0.19 Bukombe - 119 12 211 17.49 12 211 17.49 0.10 Meatu - 81 16 36 2.22 16 36 2.22 0.20 Shinyanga Urban - 341 93 373 4.04 93 373 4.04 0.27 Kishapu 163 41 188 4.54 41 188 4.54 0.25 Total 0 0 0 - 2,717 524 1,977 38.71 524 1,977 3.77 0.19 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 180 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 106 17 0 - 17 0 0.00 0.16 Shinyanga Rural - 86 5 0 - 5 0 0.00 0.06 Kahama - 54 2 2 0.87 2 2 0.87 0.04 Bukombe - 22 9 0 - 9 0 0.00 0.40 Meatu - 310 31 29 0.92 31 29 0.92 0.10 Shinyanga Urban - 0 . . - 0 0 - - Kishapu - Total 0 0 0 - 579 65 31 1.79 65 31 0.47 0.11 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 273 90 668 7.39 90 668 7.39 0.33 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 0 . . - 0 0 0.00 - Bukombe - 0 . . - 0 0 0.00 - Meatu - 0 . . - 0 0 0.00 - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 - 273 90 668 7.39 90 668 7.39 0.33 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 0.00 - Maswa 0 . . - 0 0 0.00 - Shinyanga Rural 79 8 8 1.04 8 8 1.04 0.10 Kahama 66 7 8 1.17 7 8 1.17 0.10 Bukombe 59 8 4 0.42 8 4 0.42 0.14 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 0.00 - Kishapu - Total 204 23 20 2.63 23 20 0.86 0.11 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins Average Planted Area Per household Average Planted Area Per household Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 181 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 0 . . - 0 0 0.00 - Maswa - 193 76 687 9.02 76 687 9.02 0.39 Shinyanga Rural - 0 . . - 0 0 0.00 - Kahama - 21 2 12 5.93 2 12 5.93 0.10 Bukombe - 0 . . - 0 0 - - Meatu - 0 . . - 0 0 - - Shinyanga Urban - 0 . . - 0 0 0.00 - Kishapu - Total 0 0 0 214 78 699 14.95 78 699 8.94 0.37 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi - 48,808 53,882 32,074 0.60 53,882 32,074 0.60 1.10 Maswa 108 66 15 0.23 32,967 44,575 22,036 0.49 44,640 22,051 0.49 1.35 Shinyanga Rural - 2,303 2,105 963 0.46 2,105 963 0.46 0.91 Kahama 0 . . - 14,316 16,803 12,165 0.72 16,803 12,165 0.72 1.17 Bukombe 119 48 10 0.20 12,882 14,750 12,560 0.85 14,798 12,570 0.85 1.15 Meatu 333 523 147 0.28 20,918 33,505 10,800 0.32 34,028 10,947 0.32 1.63 Shinyanga Urban 0 . . - 380 385 264 0.69 385 264 0.69 1.01 Kishapu 19,267 32,748 10,563 0.32 32,748 10,563 0.32 1.70 Total 561 637 172 0.27 151,840 198,753 101,423 4.45 199,390 101,595 0.51 1.31 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Bariadi 0 . . - 0 0 - - Maswa 0 . . - 0 0 - - Shinyanga Rural 102 41 20 0.49 41 20 0.49 0.40 Kahama 5,406 5,413 5,241 - 5,413 5,241 0.00 1.00 Bukombe 358 109 123 1.13 109 123 1.13 0.30 Meatu 0 . . - 0 0 0.00 - Shinyanga Urban 0 . . - 0 0 - - Kishapu 82 66 8 0.12 66 8 0.12 0.81 Total 0 0 0 5,948 5,630 5,392 0.96 5,630 5,392 0.96 0.95 Average Planted Area Per household Average Planted Area Per household 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon Average Planted Area Per household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 182 PERMANENT CROPS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 183 7.4 Total Area Planted with Coconut by District - Kahama District 7.5 Total Area Planted with Oranges by District - Kahama District District Area planted with Mango Total Area planted (ha) % of Total Area Planted hh with Mango Average Planted Area per Household District Area planted with Banana (Ha) Total Area planted (ha) % of Total Area Planted hh with Banana Average Planted Area per Household Shinyanga Rural 979 101,952 1.0 1,114 0.88 Shinyanga Rural 101,952 0.00 0 0.00 Bukombe 5,335 35,159 15.2 3,699 1.44 Meatu 35,159 0.00 0 0.00 Maswa 318 44,228 0.7 951 0.33 Maswa 44,228 0.00 0 0.00 Kahama 20,919 79,905 26.2 12,307 1.70 Bukombe 526.0 79,905 0.66 1,553 0.34 Meatu 84 64,833 0.1 47 1.79 Shinyanga Urban 19.0 64,833 0.03 124 0.15 Bariadi 0 31,193 0.0 0 0.00 Kahama 3,197 31,193 10.25 1,689 1.89 Shinyanga Urban 268 7,505 3.6 464 0.58 Bariadi 7,505 0.00 0 0.00 Kishapu 164 35,494 0.5 243 0.67 Kishapu 21.0 35,494 0.1 70 0.30 Total 28,067.0 400,270 100.0 18,825 0.45 Total 3,763.0 364,775 10.94 3,436 1.10 7.6 Total Area Planted with Banana by District - Kahama District District Area planted with banana(Ha) Total Area planted (ha) % of Total Area Planted hh with bananas Average Planted Area per Household Shinyanga Rural 101,952 0.00 0.00 Maswa 35,159 0.00 217 0.00 Bariadi 30.0 44,228 0.07 528 0.06 Meatu 8.0 79,905 0.01 83 0.10 Shinyanga Urban 85.0 64,833 0.13 314 0.27 Bukombe 351.0 31,193 1.13 597 0.59 Kahama 5,635.0 7,505 75.09 2,932 1.92 Kishapu 167.0 35,494 0.47 406 0.41 Total 6,276.0 364,775 1.72 5,077 1.24 MANGO BANANA PAWPAW Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 184 AGROPROCESSING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 185 Number % Number % Number % Bariadi 66,411 86 11,160 14 77,572 100 Maswa 32,508 75 10,744 25 43,252 100 Shinyanga Rural 42,740 94 2,523 6 45,263 100 Kahama 79,018 97 2,199 3 81,217 100 Bukombe 49,297 93 3,943 7 53,240 100 Meatu 26,461 84 5,031 16 31,492 100 Shinyanga Urban 4,251 42 5,947 58 10,198 100 Kishapu 28,145 79 7,479 21 35,624 100 Total 328,832 87 49,026 13 377,857 100 On Farm by Hand On Farm by Machine y Neighbour Machine By Farmers Association y operative Union By Trader g Scale Farm Other Total Bariadi 6,158 4,444 49,488 0 0 6,322 - 0 81,783 Maswa 1,879 758 24,907 - 0 4,856 0 108 36,364 Shinyanga Rural 6,776 705 18,057 - 204 16,596 - 401 43,887 Kahama 22,398 945 55,392 0 139 - 0 144 6,162 Bukombe 3,332 836 31,595 0 0 13,534 0 - 5,133 Meatu 8,901 406 14,421 166 249 83 1988 247 43,919 Shinyanga Urban 936 56 2,744 0 0 485 31 0 18,537 Kishapu 1,209 1,922 24,634 0 0 141 82 157 Total 51,589 10,071 221,237 166 593 42,017 2,101 1,057 235,784 % 21.88 4.27 93.83 0.07 0.25 17.82 0.89 0.45 139.46 District 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year Method of Processing 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year District Households That Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 186 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other Total Bambaranut 1,499 0 0 0 0 0 0 31 1,530 Beans 7,823 0 1,282 0 0 0 0 128 9,234 Bulrush Millet 0 0 2,324 0 0 297 31 0 2,652 Cabbage 15 0 285 0 0 0 0 0 301 Cassava 5,433 0 3,964 0 0 0 0 260 9,657 Chick Peas 3,630 0 950 0 0 404 0 1,587 6,571 Cotton 1,392 0 1,366 2,368 1,882 201 6,799 0 14,008 Cowpeas 5,275 0 133 0 0 0 0 142 5,549 Finger Millet 0 0 83 0 0 0 0 0 83 Green Gram 1,792 0 0 0 0 0 0 0 1,792 Groundnut 73,472 157 2,945 0 82 1,081 83 7,675 85,495 Irish Potatoes 242 0 0 0 0 0 0 0 242 Maize 42,439 9,558 206,256 83 343 41,995 82 227 300,983 Mango 139 0 0 0 0 0 0 0 139 Paddy 28,780 2,592 69,238 119 102 14,671 0 174 115,678 Pigeon Peas 812 0 178 0 0 0 0 179 1,169 Pyrethrum 0 0 142 0 0 0 0 0 142 Simsim 81 0 0 0 0 99 0 0 180 Sorghum 7,636 1,149 33,510 0 179 2,211 0 0 44,686 Sunflower 141 0 0 0 0 200 99 0 441 Sweet Potatoes 15,592 0 83 83 0 0 0 2,509 18,267 Tobacco 0 0 1,631 0 0 0 0 0 1,631 Tomatoes 81 0 0 0 0 0 0 0 81 Yams 32 0 0 0 0 0 0 0 32 Crop Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 187 Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Maize 298,104 790 635 690 764 300,983 Paddy 111,647 295 2,458 857 420 115,678 Sorghum 44,428 0 0 83 175 44,686 Bulrush Millet 2,623 0 0 29 0 2,652 Finger Millet 83 0 0 0 0 83 Cassava 9,445 0 212 0 0 9,657 Sweet Potatoes 17,915 0 238 114 0 18,267 Irish Potatoes 242 0 0 0 0 242 Yams 32 0 0 0 0 32 Beans 8,971 119 143 0 0 9,234 Cowpeas 5,468 0 82 0 0 5,549 Green Gram 1,792 0 0 0 0 1,792 Pigeon Peas 991 0 178 0 0 1,169 Chick Peas 6,431 0 141 0 0 6,571 Bambaranut 1,530 0 0 0 0 1,530 Sunflower 100 0 341 0 0 441 Simsim 81 0 99 0 0 180 Groundnut 83,378 303 1,139 60 614 85,495 Cotton 2,529 83 9,948 287 1,161 14,008 Tobacco 1,520 0 110 0 0 1,631 Pyrethrum 142 0 0 0 0 142 Mango 139 0 0 0 0 139 Cabbage 301 0 0 0 0 301 Tomatoes 81 0 0 0 0 81 Total 597,975 1,590 15,724 2,121 3,135 620,545 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Product Use Crop Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 188 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 4,490 2,534 422 405 98 451 1,019 324 291,240 300,983 Paddy 7,635 7,019 141 282 250 209 1,001 1,391 97,750 115,678 Sorghum 722 0 54 187 95 81 329 0 43,218 44,686 Bulrush Millet 78 0 0 29 0 0 0 0 2,545 2,652 Finger Millet 0 0 0 0 0 0 0 0 83 83 Cassava 883 455 0 0 0 0 119 264 7,935 9,657 Sweet Potatoes 0 0 54 0 0 0 101 0 18,112 18,267 Irish Potatoes 0 0 0 0 0 0 0 0 242 242 Yams 0 0 0 0 0 0 0 0 32 32 Beans 304 119 0 0 0 0 0 0 8,810 9,234 Cowpeas 0 0 0 143 0 0 0 0 5,406 5,549 Green Gram 102 0 0 0 0 0 0 0 1,690 1,792 Pigeon Peas 0 178 0 0 0 0 0 0 991 1,169 Chick Peas 102 811 101 0 0 0 0 0 5,558 6,571 Bambaranut 0 285 0 0 0 0 0 0 1,245 1,530 Sunflower 0 0 0 101 0 0 0 0 340 441 Simsim 0 0 0 0 0 0 0 0 180 180 Groundnut 4,506 1,814 382 217 101 182 849 708 76,736 85,495 Cotton 95 187 0 7,002 4,016 0 0 235 2,473 14,008 Tobacco 110 0 0 0 0 0 0 0 1,520 1,631 Pyrethrum 142 0 0 0 0 0 0 0 0 142 Mango 0 0 0 0 0 0 0 0 139 139 Cabbage 0 0 0 0 0 0 0 0 301 301 Tomatoes 0 0 0 0 0 0 0 0 81 81 Total 19,169 13,403 1,155 8,366 4,558 923 3,418 2,922 566,630 620,545 Flour / Meal Grain Oil Juice Pulp Other Total Bariadi 63,408 2,118 351 0 0 534 66,411 Maswa 27,055 4,641 500 0 0 311 32,508 Shinyanga Rural 31,990 9,751 505 0 91 402 42,740 Kahama 3,865 74,837 86 0 0 230 79,018 Bukombe 41,670 7,627 0 0 0 0 49,297 Meatu 21,313 1,752 1,181 81 83 2,050 26,461 Shinyanga Urban 3,317 840 63 0 0 32 4,251 Kishapu 25,404 2,338 242 80 0 81 28,145 Total 218,022 103,903 2,929 161 175 3,641 328,832 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Crop Where Sold 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Kahama Region District Main Product Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 189 Household /Human C ti Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Bariadi 66,232 179 0 0 0 66,411 Maswa 32,090 108 310 0 0 32,508 Shinyanga Rural 41,945 102 298 193 201 42,740 Kahama 77,779 270 284 287 397 79,018 Bukombe 48,700 239 119 0 239 49,297 Meatu 24,101 0 1,309 165 886 26,461 Shinyanga Urban 4,129 0 31 92 0 4,251 Kishapu 27,982 0 0 81 82 28,145 Total 322,958 898 2,352 819 1,806 328,832 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Bariadi 529 174 176 0 0 179 0 0 65,353 66,411 Maswa 634 650 217 108 0 108 108 0 30,682 32,508 Shinyanga Rural 495 203 0 203 0 0 102 102 41,635 42,740 Kahama 2,999 1,344 0 144 98 0 571 269 73,594 79,018 Bukombe 914 953 0 0 0 0 239 0 47,191 49,297 Meatu 0 0 138 1,474 994 0 0 0 23,855 26,461 Shinyanga Urban 63 129 0 29 0 0 0 64 3,966 4,251 Kishapu 239 0 0 159 0 163 0 160 27,423 28,145 Total 5,874 3,453 531 2,118 1,091 451 1,020 594 313,699 328,832 Bran Cake Husk Juice Fiber Pulp Oil Shell No by-product Other Total Bariadi 2,813 178 10,625 178 179 0 0 4,035 48,403 0 66,411 Maswa 9,549 203 6,795 108 0 0 95 1,483 14,073 202 32,508 Shinyanga Rural 2,615 399 15,973 0 102 202 102 2,001 21,345 0 42,740 Kahama 72,791 141 2,691 0 0 144 0 733 2,408 110 79,018 Bukombe 9,917 119 7,238 0 0 0 0 1,061 30,961 0 49,297 Meatu 712 256 82 0 81 162 82 490 24,595 0 26,461 Shinyanga Urban 2,167 0 841 0 0 0 32 95 1,117 0 4,251 Kishapu 1,178 82 2,653 245 0 81 163 2,275 21,468 0 28,145 Total 101,742 1,379 46,899 531 362 590 473 12,174 164,368 313 328,832 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Kahama Region District Product Use 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Kahama Region 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Kahama Region District District Where Sold By Product Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 190 MARKETING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 191 Number % Number % Bariadi 51,136 65.9 26,436 34.1 77,572 Maswa 34,296 79.3 8,956 20.7 43,252 Shinyanga Rural 19,829 43.8 25,434 56.2 45,263 Kahama 47,924 59.0 33,293 41.0 81,217 Bukombe 28,751 54.0 24,489 46.0 53,240 Meatu 18,658 59.2 12,833 40.8 31,492 Shinyanga Urban 770 7.6 9,428 92.4 10,198 Kishapu 17,952 50.4 17,671 49.6 35,624 Total 219,317 58.0 158,540 42.0 377,857 District Open Market Price Too Low No Transport Transport Cost Too High Market too Far Farmers Association Problems Co-operative Problems Trade Union Problems Government Regulatory Board Problems Lack of Market Information Other Total Bariadi 3,795 358 174 537 0 177 0 0 0 - 5,041 Maswa 757 0 0 0 0 0 0 0 0 - 757 Shinyanga Rural 6,143 204 99 504 0 0 0 0 0 - 6,950 Kahama 11,651 826 1,264 1,394 142 98 0 0 286 408 16,068 Bukombe 11,778 239 1,434 597 0 0 113 239 239 352 14,991 Meatu 5,824 164 47 570 0 393 749 0 329 823 8,899 Shinyanga Urban 212 30 0 0 0 0 0 0 0 - 242 Kishapu 244 82 81 0 0 0 0 82 0 321 809 Total 40,404 1,903 3,099 3,602 142 667 862 321 854 1,903 53,757 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Bariadi 884 27,922 169 342 534 - 2,960 43,552 76,363 Maswa 433 8,829 - - 433 - 2,968 30,371 43,035 Shinyanga Rural 300 23,259 99 303 - 102 1,194 19,200 44,457 Kahama 2,241 34,141 143 416 254 421 573 35,351 73,539 Bukombe 2,183 25,103 - 119 119 238 1,672 22,974 52,409 Meatu 924 13,118 - - - - 945 15,077 30,065 Shinyanga Urban 229 7,726 32 245 - 62 493 1,126 9,914 Kishapu 732 20,347 - - 163 81 1,675 12,229 35,227 Total 7,925 160,445 442 1,427 1,503 905 12,481 179,880 365,008 10.2 Number of Households who Reported Marketing Problems by District during 2002/03 Agricultural Year 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Kahama Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 192 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 193 Number of Household % Number of Household % Bariadi 1,569 2 76,003 98 77,572 Maswa 1,613 4 41,639 96 43,252 Shinyanga Rural 1,522 3 43,741 97 45,263 Kahama 1,559 2 79,658 98 81,217 Bukombe 468 1 52,772 99 53,240 Meatu 81 0 31,411 100 31,492 Shinyanga Urban 489 5 9,709 95 10,198 Kishapu 1,277 4 34,347 96 35,624 Total 8,578 2 369,279 98 377,857 District Irrigatable Area (ha) Irrigated Land (ha) % Bariadi 331 302 91 Maswa 1,615 1,505 93 Shinyanga Rural 886 589 67 Kahama 411 291 71 Bukombe 308 299 97 Meatu 131 66 50 Shinyanga Urban 186 157 85 Kishapu 1,044 646 Total 4,912 3,856 78 River Dam Well Borehole Canal Pipe water Total Bariadi 1,217 0 352 0 0 0 1,569 Maswa 101 108 0 0 1,404 0 1,613 Shinyanga Rural 713 102 401 0 306 0 1,522 Kahama 0 1,135 425 0 0 0 1,559 Bukombe 0 229 119 0 119 0 468 Meatu 81 0 0 0 0 0 81 Shinyanga Urban 193 0 188 23 0 85 489 Kishapu 1,195 82 0 0 0 0 1,277 Total 3,501 1,655 1,485 23 1,829 85 8,578 % 41 19 17 0 21 1 100 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year 11.1 IRRIGATION: Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District District Households Practicing Irrigation Households not Practicing Irrigation Total Number of households 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 194 Gravity Hand Bucket Hand Pump Motor Pump Other Total Bariadi 179 1,212 178 0 0 1,569 Maswa 1,404 210 0 0 0 1,613 Shinyanga Rural 510 910 0 0 102 1,522 Kahama 143 1,416 0 0 0 1,559 Bukombe 348 119 0 0 0 468 Meatu 81 0 0 0 0 81 Shinyanga Urban 32 369 32 23 32 489 Kishapu 730 547 0 0 0 1,277 Total 3,427 4,783 211 23 134 8,578 % 39.9 55.8 2.5 0.3 1.6 100 Flood Sprinkler Water Hose Bucket / Watering Can Total Bariadi 0 0 178 1,391 1,569 Maswa 1,404 0 0 210 1,613 Shinyanga Rural 612 0 0 910 1,522 Kahama 428 0 0 1,131 1,559 Bukombe 348 0 0 119 468 Meatu 81 0 0 0 81 Shinyanga Urban 32 63 23 371 489 Kishapu 730 0 0 547 1,277 Total 3,635 63 202 4,678 8,578 % 42 1 2 55 100 District Method of Obtaining Water 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year District Method of field Application 11.4 IRRIGATION: Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 195 Number % Number % Bariadi 3,675 5 73,897 95 77,572 Maswa 1,500 3 41,752 97 43,252 Shinyanga Rural 4,022 9 41,241 91 45,263 Kahama 3,194 4 78,023 96 81,217 Bukombe 358 1 52,882 99 53,240 Meatu 577 2 30,915 98 31,492 Shinyanga Urban 754 7 9,444 93 10,198 Kishapu 1,119 3 34,504 97 35,624 Total 15,199 4 362,658 96 377,857 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Bariadi . 7,159 . . 18,685 4,871 887 . 31,603 Maswa . 11,757 325 . 108 759 . . 12,949 Shinyanga Rural . 102,581 1,327 . . 102 705 . 104,714 Kahama 131 3,155 . 4,274 . 14,160 1,815 . 23,535 Bukombe . 478 . 358 . . . . 836 Meatu . 8,858 . 83 333 826 . . 10,100 Shinyanga Urban . 4,224 . . . 152 124 . 4,500 Kishapu . 1,025 . . . 2,693 5,112 79 8,908 Total 131 139,237 1,652 4,716 19,127 23,561 8,643 79 197,146 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year District Type of Erosion Control 11.6 EROSION CONTROL: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District District Presence of Erosion Control/Water Harvesting Facilities Have facility Does Not Have Facility Total Number of households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 196 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tanga 197 District Number % Number % Number % Bariadi 535 1 77,036 99 77,572 100 Maswa 324 1 42,928 99 43,252 100 Shinyanga Rural 402 1 44,861 99 45,263 100 Kahama 8,437 10 72,779 90 81,217 100 Bukombe 597 1 52,643 99 53,240 100 Meatu 0 0 31,492 100 31,492 100 Shinyanga Urban 119 1 10,080 99 10,198 100 Kishapu 315 1 35,308 99 35,624 100 Total 10,730 3 367,127 97 377,857 100 District Number % Number % Number % Bariadi 12,383 16 65,188 84 77,572 100 Maswa 9,126 21 34,126 79 43,252 100 Shinyanga Rural 16,679 37 28,584 63 45,263 100 Kahama 27,407 34 53,931 66 81,337 100 Bukombe 9,019 17 44,221 83 53,240 100 Meatu 4,408 14 27,084 86 31,492 100 Shinyanga Urban 4,201 41 6,029 59 10,230 100 Kishapu 5,189 15 30,596 85 35,785 100 Total 88,413 23 289,758 77 378,171 100 Table 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Chemical Fertilizers Number of Agricultural Households Using Chemical Fertilizers Total Number of Agricultural Households NOT Using Farm Yard Manure Number of Agricultural Households Using Farm Yard Manure 198 District Number % Number % Number % Bariadi 1,937 2 75,634 98 77,572 100 Maswa 1,056 2 42,196 98 43,252 100 Shinyanga Rural 862 2 44,401 98 45,263 100 Kahama 6,134 8 75,083 92 81,217 100 Bukombe 2,270 4 50,970 96 53,240 100 Meatu 83 0 31,409 100 31,492 100 Shinyanga Urban 514 5 9,652 95 10,166 100 Kishapu 1,460 4 34,084 96 35,544 100 Total 14,316 4 363,429 96 377,746 100 District Number % Number % Number % Bariadi 29,297 38 48,274 62 77,572 100 Maswa 5,212 12 38,040 88 43,252 100 Shinyanga Rural 2,216 5 43,047 95 45,263 100 Kahama 17,551 22 63,666 78 81,217 100 Bukombe 12,399 23 40,841 77 53,240 100 Meatu 8,754 28 22,737 72 31,492 100 Shinyanga Urban 408 4 9,791 96 10,198 100 Kishapu 5,196 15 30,427 85 35,624 100 Total 81,034 21 296,824 79 377,857 100 Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Pesticides/Fungicides Number of Agricultural Households Using Pesticides/Fungicides Total Number of Agricultural Households NOT Using COMPOST Manure Number of Agricultural Households Using COMPOST Manure 199 District Number % Number % Number % Bariadi 0 0 77,572 100 77,572 100 Maswa 325 1 42,927 99 43,252 100 Shinyanga Rural 0 0 45,263 100 45,263 100 Kahama 286 0 80,810 100 81,097 100 Bukombe 119 0 53,121 100 53,240 100 Meatu 81 0 31,410 100 31,492 100 Shinyanga Urban 0 0 10,198 100 10,198 100 Kishapu 376 1 35,247 99 35,624 100 Total 1,188 0 376,549 100 377,737 100 District Number % Number % Number % Bariadi 34,676 45 42,896 55 77,572 100 Maswa 21,630 50 21,622 50 43,252 100 Shinyanga Rural 4,475 10 40,788 90 45,263 100 Kahama 18,491 23 62,726 77 81,217 100 Bukombe 10,723 20 42,517 80 53,240 100 Meatu 11,043 35 20,449 65 31,492 100 Shinyanga Urban 1,182 12 9,017 88 10,198 100 Kishapu 16,184 46 19,358 54 35,542 100 Total 118,404 31 259,372 69 377,776 100 Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Total Number of Agricultural Households NOT Using Herbicides Number of Agricultural Households Using Herbicides Total Number of Agricultural Households NOT Using Improved Seeds Number of Agricultural Households Using Improved Seeds 200 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 535 1 0 0 77,036 99 77,572 100 Maswa 108 0 0 0 216 1 0 0 42,928 99 43,252 100 Shinyanga Rural 0 0 0 0 302 1 100 0 44,861 99 45,263 100 Kahama 6,222 8 0 0 2,215 3 0 0 72,779 90 81,217 100 Bukombe 0 0 119 0 478 1 0 0 51,264 99 51,862 100 Meatu 0 0 0 0 0 0 0 0 31,077 100 31,077 100 Shinyanga Urban 0 0 0 0 119 1 0 0 10,080 99 10,198 100 Kishapu 0 0 0 0 235 1 80 0 35,308 99 35,624 100 Total 6,330 2 119 0 4,100 1 181 0 365,334 97 376,064 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 179 0 177 0 0 0 0 0 Maswa 0 0 0 0 0 0 0 0 0 0 0 0 Shinyanga Rural 0 0 0 0 200 0 102 0 0 0 0 0 Kahama 417 1 230 0 0 0 0 0 144 0 0 0 Bukombe 119 0 239 0 0 0 0 0 0 0 0 0 Meatu 0 0 0 0 0 0 0 0 0 0 82 0 Shinyanga Urban 30 0 94 1 62 1 157 2 0 0 0 0 Kishapu 0 0 81 0 0 0 0 0 0 0 0 0 Total 567 0 643 0 441 0 436 0 144 0 82 0 District Number % Number % Number % Number % Number % Bariadi 7,336 9 4,692 6 0 0 65,188 84 77,572 100 Maswa 5,798 13 3,005 7 323 1 34,126 79 43,252 100 Shinyanga Rural 10,568 23 5,202 11 606 1 28,584 63 45,263 100 Kahama 16,708 21 8,867 11 1,041 1 53,931 66 81,337 100 Bukombe 6,287 12 2,374 5 0 0 42,842 83 51,862 100 Meatu 2,168 7 2,074 7 83 0 26,836 86 31,243 100 Shinyanga Urban 2,455 24 1,247 12 157 2 6,029 59 10,230 100 Kishapu 3,019 8 2,089 6 0 0 30,596 85 35,785 100 Total 54,339 14 29,550 8 2,211 1 288,132 77 376,544 100 Cont…..Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Locally Produced by Household Total Not applicable Other Neighbour Local Market / Trade Store Co-operative Total Not applicable Neighbour Local Market / Trade Store Local Farmers Group Co-operative Large Scale Farm Crop Buyers Development Project Secondary Market 201 District Number % Number % Number % Number % Number % Bariadi 0 0 1,224 2 714 1 75,634 98 77,572 100 Maswa 0 0 839 2 217 1 42,196 98 43,252 100 Shinyanga Rural 0 0 679 2 183 0 44,401 98 45,263 100 Kahama 0 0 4,789 6 1,345 2 75,083 92 81,217 100 Bukombe 0 0 2,151 4 119 0 49,592 96 51,862 100 Meatu 0 0 83 0 0 0 30,994 100 31,077 100 Shinyanga Urban 0 0 115 1 400 4 9,652 95 10,166 100 Kishapu 81 0 483 1 895 3 34,084 96 35,544 100 Total 81 0 10,363 3 3,872 1 361,636 96 375,953 100 District Number % Number % Number % Number % Number % Bariadi 2,643 3 0 0 25,801 33 0 0 500 1 Maswa 2,340 5 108 0 2,113 5 542 1 108 0 Shinyanga Rural 204 0 595 1 1,112 2 0 0 306 1 Kahama 8,197 10 286 0 7,316 9 144 0 751 1 Bukombe 1,549 3 473 1 9,067 17 358 1 713 1 Meatu 5,827 19 537 2 1,431 5 629 2 330 1 Shinyanga Urban 32 0 0 0 343 3 0 0 0 0 Kishapu 2,368 7 162 0 1,612 5 0 0 973 3 Total 23,160 6 2,161 1 48,795 13 1,673 0 3,682 1 Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Co-operative Total Not applicable Neighbour Locally Produced by Household Local Market / Trade Store Crop Buyers Secondary Market Local Market / Trade Store Local Farmers Group 202 District Number % Number % Number % Number % Number % Bariadi 175 0 179 0 0 0 48,274 62 77,572 100 Maswa 0 0 0 0 0 0 38,040 88 43,252 100 Shinyanga Rural 0 0 0 0 0 0 43,047 95 45,263 100 Kahama 0 0 857 1 0 0 63,666 78 81,217 100 Bukombe 119 0 0 0 119 0 39,463 76 51,862 100 Meatu 0 0 0 0 0 0 22,487 72 31,242 100 Shinyanga Urban 0 0 32 0 0 0 9,791 96 10,198 100 Kishapu 0 0 81 0 0 0 30,427 85 35,624 100 Total 294 0 1,149 0 119 0 295,195 78 376,229 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 0 0 77,572 100 77,572 100 Maswa 216 1 0 0 108 0 0 0 42,927 99 43,252 100 Shinyanga Rural 0 0 0 0 0 0 0 0 45,263 100 45,263 100 Kahama 144 0 143 0 0 0 0 0 80,810 100 81,097 100 Bukombe 0 0 0 0 0 0 119 0 51,742 100 51,862 100 Meatu 81 0 0 0 0 0 0 0 30,995 100 31,077 100 Shinyanga Urban 0 0 0 0 0 0 0 0 10,198 100 10,198 100 Kishapu 215 1 162 0 0 0 0 0 35,247 99 35,624 100 Total 656 0 305 0 108 0 119 0 374,756 100 375,944 100 Cont…..Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Co-operative Total Not applicable Other Neighbour Locally Produced by Household Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Not applicable Locally Produced by Household Crop Buyers Local Market / Trade Store 203 District Number % Number % Number % Number % Number % Bariadi 4,532 6 0 0 12,022 15 0 0 1,229 2 Maswa 11,643 27 968 2 3,544 8 1,285 3 203 0 Shinyanga Rural 101 0 1,289 3 2,280 5 0 0 703 2 Kahama 10,657 13 0 0 6,379 8 0 0 0 0 Bukombe 4,649 9 1,553 3 2,613 5 0 0 119 0 Meatu 8,069 26 402 1 1,481 5 495 2 0 0 Shinyanga Urban 32 0 0 0 1,094 11 0 0 0 0 Kishapu 8,712 25 568 2 2,730 8 163 0 80 0 Total 48,394 13 4,779 1 32,143 9 1,943 1 2,335 1 District Number % Number % Number % Number % Number % Bariadi 16,383 21 179 0 332 0 42,896 55 77,572 100 Maswa 3,554 8 108 0 325 1 21,622 50 43,252 100 Shinyanga Rural 102 0 0 0 0 0 40,788 90 45,263 100 Kahama 644 1 123 0 688 1 62,726 77 81,217 100 Bukombe 1,191 2 358 1 239 0 41,139 79 51,862 100 Meatu 415 1 81 0 101 0 20,199 65 31,242 100 Shinyanga Urban 0 0 55 1 0 0 9,017 88 10,198 100 Kishapu 3,455 10 237 1 240 1 19,358 54 35,542 100 Total 25,743 7 1,142 0 1,925 1 257,744 69 376,147 100 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 178 33 357 67 535 100 Maswa 216 67 0 0 108 33 0 0 0 0 324 100 Shinyanga Rural 0 0 0 0 0 0 201 50 201 50 402 100 Kahama 3,744 44 2,251 27 1,305 15 575 7 563 7 8,437 100 Bukombe 119 20 0 0 358 60 119 20 0 0 597 100 Shinyanga Urban 0 0 23 20 31 26 64 54 0 0 119 100 Kishapu 79 25 0 0 156 50 80 25 0 0 315 100 Total 4,158 39 2,274 21 1,959 18 1,218 11 1,121 10 10,730 100 Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Cont…..Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Crop Buyers Locally Produced by Neighbour Not applicable Development Project Secondary Market Local Market / Trade Store Local Farmers Group Co-operative 204 District Number % Number % Number % Number % Number % Number % Bariadi 11,713 95 493 4 177 1 0 0 0 0 12,383 100 Maswa 8,390 92 420 5 317 3 0 0 0 0 9,126 100 Shinyanga Rural 15,177 91 600 4 101 1 702 4 99 1 16,679 100 Kahama 23,571 86 2,618 10 1,217 4 0 0 0 0 27,407 100 Bukombe 7,235 80 1,187 13 478 5 119 1 0 0 9,019 100 Meatu 3,744 85 414 9 250 6 0 0 0 0 4,408 100 Shinyanga Urban 3,773 90 352 8 45 1 31 1 0 0 4,201 100 Kishapu 4,394 85 714 14 81 2 0 0 0 0 5,189 100 Total 77,998 88 6,798 8 2,664 3 853 1 99 0 88,413 100 District Number % Number % Number % Bariadi 1,760 91 177 9 1,937 100 Maswa 947 90 108 10 1,056 100 Shinyanga Rural 862 100 0 0 862 100 Kahama 5,326 87 808 13 6,134 100 Bukombe 2,151 95 119 5 2,270 100 Meatu 83 100 0 0 83 100 Shinyanga Urban 514 100 0 0 514 100 Kishapu 1,460 100 0 0 1,460 100 Total 13,104 92 1,212 8 14,316 100 District Number % Number % Number % Number % Number % Number % Bariadi 5,402 18 4,938 17 7,197 25 3,709 13 8,051 27 29,297 100 Maswa 1,460 28 951 18 2,483 48 216 4 101 2 5,212 100 Shinyanga Rural 498 22 402 18 202 9 303 14 811 37 2,216 100 Kahama 4,978 28 4,088 23 3,535 20 2,198 13 2,752 16 17,551 100 Bukombe 1,909 15 2,504 20 6,434 52 956 8 596 5 12,399 100 Meatu 2,237 26 2,643 30 2,993 34 414 5 467 5 8,754 100 Shinyanga Urban 32 8 32 8 89 22 222 54 32 8 408 100 Kishapu 1,833 35 567 11 2,147 41 489 9 161 3 5,196 100 Total 18,349 23 16,126 20 25,080 31 8,507 10 12,972 16 81,034 100 Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Between 10 and 20 km 20 km and Above Total Less than 1 km Between 1 and 3 km Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 205 District Number % Number % Number % Number % Number % Number % Maswa 216 67 0 0 108 33 0 0 0 0 325 100 Kahama 144 50 143 50 0 0 0 0 0 0 286 100 Bukombe 0 0 0 0 0 0 0 0 119 100 119 100 Meatu 0 0 81 100 0 0 0 0 0 0 81 100 Kishapu 148 39 67 18 81 21 81 21 0 0 376 100 Total 508 43 291 24 189 16 81 7 119 10 1,188 100 District Number % Number % Number % Number % Number % Number % Bariadi 12,902 37 8,536 25 5,647 16 3,530 10 4,062 12 34,676 100 Maswa 6,488 30 5,877 27 7,651 35 758 4 857 4 21,630 100 Shinyanga Rural 1,293 29 682 15 906 20 594 13 1,002 22 4,475 100 Kahama 6,661 36 5,406 29 4,439 24 1,000 5 985 5 18,491 100 Bukombe 3,098 29 2,744 26 3,807 36 717 7 357 3 10,723 100 Meatu 2,612 24 2,865 26 3,945 36 467 4 1,154 10 11,043 100 Shinyanga Urban 63 5 247 21 491 42 285 24 95 8 1,182 100 Kishapu 8,065 50 2,362 15 4,145 26 1,124 7 489 3 16,184 100 Total 41,182 35 28,718 24 31,030 26 8,474 7 9,000 8 118,404 100 District Number % Number % Number % Number % Number % Bariadi 357 67 178 33 0 0 0 0 535 100 Maswa 0 0 324 100 0 0 0 0 324 100 Shinyanga Rural 0 0 302 75 100 25 0 0 402 100 Kahama 7,498 89 431 5 243 3 266 3 8,437 100 Bukombe 358 60 119 20 119 20 0 0 597 100 Shinyanga Urban 64 54 55 46 0 0 0 0 119 100 Kishapu 315 100 0 0 0 0 0 0 315 100 Total 8,592 80 1,409 13 463 4 266 2 10,730 100 Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year 20 km and Above Total Sale of Farm Products Other Income generating Bank Loan Other Total Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 206 District Number % Number % Number % Number % Bariadi 8,568 69 1,713 14 179 1 0 0 Maswa 6,883 75 526 6 432 5 0 0 Shinyanga Rural 12,667 76 1,195 7 403 2 0 0 Kahama 24,123 88 1,043 4 410 1 715 3 Bukombe 6,756 75 119 1 956 11 0 0 Meatu 2,684 61 379 9 83 2 0 0 Shinyanga Urban 3,710 88 277 7 0 0 31 1 Kishapu 4,702 91 324 6 0 0 0 0 Total 70,093 79 5,578 6 2,463 3 745 1 District Number % Number % Number % Bariadi 0 0 1,923 16 12,383 100 Maswa 0 0 1,285 14 9,126 100 Shinyanga Rural 0 0 2,414 14 16,679 100 Kahama 0 0 1,116 4 27,407 100 Bukombe 0 0 1,189 13 9,019 100 Meatu 62 1 1,199 27 4,408 100 Shinyanga Urban 0 0 183 4 4,201 100 Kishapu 0 0 163 3 5,189 100 Total 62 0 9,471 11 88,413 100 District Number % Number % Number % Number % Number % Bariadi 1,760 91 0 0 177 9 0 0 1,937 100 Maswa 839 79 0 0 0 0 217 21 1,056 100 Shinyanga Rural 559 65 0 0 0 0 303 35 862 100 Kahama 5,406 88 630 10 0 0 98 2 6,134 100 Bukombe 1,553 68 0 0 239 11 478 21 2,270 100 Meatu 83 100 0 0 0 0 0 0 83 100 Shinyanga Urban 483 94 0 0 0 0 31 6 514 100 Kishapu 1,297 89 81 6 0 0 81 6 1,460 100 Total 11,981 84 711 5 416 3 1,208 8 14,316 100 Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year Cont…..Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year Other Total Produced on form Other Total Sale of Farm Products Other Income generating Remittances Sale of Farm Products Other Income generating Remittances Bank Loan 207 District Number % Number % Number % Number % Number % Bariadi 22,199 76 6,580 22 0 0 0 0 0 0 Maswa 4,492 86 620 12 99 2 0 0 0 0 Shinyanga Rural 1,610 73 504 23 0 0 0 0 0 0 Kahama 15,473 88 1,383 8 144 1 133 1 0 0 Bukombe 10,608 86 1,552 13 0 0 119 1 0 0 Meatu 4,698 54 2,962 34 0 0 83 1 81 1 Shinyanga Urban 408 100 0 0 0 0 0 0 0 0 Kishapu 3,931 76 1,183 23 82 2 0 0 0 0 Total 63,419 78 14,784 18 325 0 336 0 81 0 District Number % Number % Bariadi 519 2 29,297 100 Maswa 0 0 5,212 100 Shinyanga Rural 102 5 2,216 100 Kahama 418 2 17,551 100 Bukombe 119 1 12,399 100 Meatu 930 11 8,754 100 Shinyanga Urban 0 0 408 100 Kishapu 0 0 5,196 100 Total 2,089 3 81,034 100 District Number % Number % Number % Maswa 216 67 108 33 325 100 Kahama 286 100 0 0 286 100 Bukombe 119 100 0 0 119 100 Meatu 81 100 0 0 81 100 Kishapu 148 39 229 61 376 100 Total 851 72 337 28 1,188 100 Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year Cont…. Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year Total Other Total Sale of Farm Products Other Income generating Sale of Farm Products Other Income generating Remittances Bank Loan Produced on form 208 District Number % Number % Number % Number % Bariadi 25,918 75 7,535 22 163 0 179 1 Maswa 17,398 80 3,054 14 315 1 108 1 Shinyanga Rural 2,686 60 1,489 33 98 2 0 0 Kahama 15,249 82 2,965 16 144 1 133 1 Bukombe 9,171 86 955 9 0 0 119 1 Meatu 5,771 52 4,101 37 81 1 0 0 Shinyanga Urban 815 69 304 26 62 5 0 0 Kishapu 14,111 87 1,831 11 161 1 81 0 Total 91,120 77 22,235 19 1,023 1 620 1 District Number % Number % Number % Bariadi 0 0 881 3 34,676 100 Maswa 0 0 755 3 21,630 100 Shinyanga Rural 0 0 202 5 4,475 100 Kahama 0 0 0 0 18,491 100 Bukombe 0 0 478 4 10,723 100 Meatu 136 1 954 9 11,043 100 Shinyanga Urban 0 0 0 0 1,182 100 Kishapu 0 0 0 0 16,184 100 Total 136 0 3,270 3 118,404 100 District Number % Number % Number % Number % Bariadi 28,725 37 43,811 57 348 0 0 0 Maswa 10,123 24 25,565 60 541 1 107 0 Shinyanga Rural 12,233 27 29,590 66 408 1 0 0 Kahama 22,117 30 44,752 61 422 1 572 1 Bukombe 10,476 20 36,095 69 1,195 2 119 0 Meatu 15,510 49 14,287 45 417 1 81 0 Shinyanga Urban 492 5 8,600 85 110 1 0 0 Kishapu 13,901 39 17,800 50 428 1 163 0 Total 113,577 31 220,499 60 3,868 1 1,042 0 Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year Not Available Price Too High No Money to Buy Too Much Labour Required Bank Loan Produced on form Other Total Cont…..Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year Sale of Farm Products Other Income generating Remittances 209 District Number % Number % Number % Number % Number % Bariadi 1,934 3 1,335 2 0 0 884 1 77,036 100 Maswa 1,936 5 3,358 8 216 1 1,082 3 42,928 100 Shinyanga Rural 1,406 3 1,121 2 0 0 102 0 44,861 100 Kahama 1,253 2 2,527 3 0 0 1,136 2 72,779 100 Bukombe 1,772 3 2,746 5 119 0 119 0 52,643 100 Meatu 326 1 448 1 0 0 422 1 31,492 100 Shinyanga Urban 268 3 519 5 0 0 92 1 10,080 100 Kishapu 1,455 4 1,187 3 0 0 373 1 35,308 100 Total 10,350 3 13,242 4 336 0 4,212 1 367,127 100 District Number % Number % Number % Number % Bariadi 1,951 3 1,592 2 42,580 65 10,355 16 Maswa 11,433 34 8,284 24 7,745 23 3,332 10 Shinyanga Rural 7,467 26 4,244 15 12,137 42 602 2 Kahama 18,154 34 12,632 23 17,539 33 1,491 3 Bukombe 16,054 36 16,183 37 7,353 17 836 2 Meatu 1,686 6 3,464 13 15,262 56 2,309 9 Shinyanga Urban 867 14 2,063 34 2,262 38 297 5 Kishapu 1,853 6 5,152 17 17,636 58 3,491 11 Total 59,464 21 53,614 19 122,514 42 22,713 8 District Number % Number % Number % Number % Number % Bariadi 6,152 9 867 1 0 0 1,692 3 65,188 100 Maswa 1,080 3 325 1 0 0 1,927 6 34,126 100 Shinyanga Rural 1,115 4 1,111 4 0 0 1,909 7 28,584 100 Kahama 364 1 2,623 5 123 0 1,002 2 53,931 100 Bukombe 936 2 2,262 5 0 0 597 1 44,221 100 Meatu 1,402 5 834 3 0 0 2,127 8 27,084 100 Shinyanga Urban 182 3 265 4 0 0 93 2 6,029 100 Kishapu 724 2 1,222 4 82 0 436 1 30,596 100 Total 11,955 4 9,509 3 205 0 9,783 3 289,758 100 Cont…,Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Cont….Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year Total Do not Know How to Use Input is of No Use Locally Produced by Other Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Other 210 District Number % Number % Number % Number % Bariadi 1,948 3 1,935 3 28,193 37 8,135 11 Maswa 4,429 10 3,090 7 13,354 32 2,382 6 Shinyanga Rural 4,757 11 2,222 5 13,967 31 2,015 5 Kahama 8,355 11 6,832 9 38,905 52 3,207 4 Bukombe 11,201 22 9,917 19 17,345 34 2,748 5 Meatu 1,788 6 4,219 13 7,802 25 1,229 4 Shinyanga Urban 895 9 2,998 31 2,068 21 188 2 Kishapu 2,929 9 5,015 15 12,956 38 5,801 17 Total 36,302 10 36,229 10 134,592 37 25,706 7 District Number % Number % Number % Number % Number % Bariadi 34,023 45 874 1 0 0 527 1 75,634 100 Maswa 16,371 39 757 2 108 0 1,704 4 42,196 100 Shinyanga Rural 19,711 44 714 2 201 0 814 2 44,401 100 Kahama 13,253 18 3,163 4 656 1 712 1 75,083 100 Bukombe 6,778 13 2,263 4 0 0 717 1 50,970 100 Meatu 12,235 39 2,066 7 167 1 1,903 6 31,409 100 Shinyanga Urban 2,752 29 415 4 0 0 335 3 9,652 100 Kishapu 6,302 18 645 2 81 0 355 1 34,084 100 Total 111,425 31 10,897 3 1,213 0 7,066 2 363,429 100 District Number % Number % Number % Number % Bariadi 3,199 7 35,092 73 1,064 2 0 0 Maswa 4,391 12 27,937 73 756 2 0 0 Shinyanga Rural 4,842 11 31,863 74 1,014 2 987 2 Kahama 7,706 12 46,014 72 414 1 143 0 Bukombe 2,348 6 31,347 77 1,194 3 119 0 Meatu 937 4 19,155 84 325 1 83 0 Shinyanga Urban 301 3 7,667 78 446 5 0 0 Kishapu 1,361 4 26,728 88 489 2 81 0 Total 25,086 8 225,803 76 5,703 2 1,414 0 Cont….Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Other Not Available Price Too High No Money to Buy Too Much Labour Required Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year 211 District Number % Number % Number % Number % Bariadi 3,369 7 4,668 10 882 2 48,274 100 Maswa 3,020 8 975 3 960 3 38,040 100 Shinyanga Rural 2,823 7 1,416 3 102 0 43,047 100 Kahama 3,049 5 5,622 9 718 1 63,666 100 Bukombe 1,413 3 4,300 11 119 0 40,841 100 Meatu 579 3 658 3 999 4 22,737 100 Shinyanga Urban 389 4 805 8 184 2 9,791 100 Kishapu 651 2 886 3 230 1 30,427 100 Total 15,292 5 19,330 7 4,195 1 296,824 100 District Number % Number % Number % Number % Bariadi 30,447 39 22,816 29 866 1 0 0 Maswa 6,135 14 26,942 63 640 1 0 0 Shinyanga Rural 7,114 16 29,258 65 1,322 3 694 2 Kahama 22,937 28 33,166 41 548 1 0 0 Bukombe 11,607 22 29,369 55 1,539 3 239 0 Meatu 9,013 29 14,900 47 327 1 0 0 Shinyanga Urban 432 4 7,325 72 446 4 0 0 Kishapu 5,798 16 23,957 68 870 2 0 0 Total 93,483 25 187,732 50 6,558 2 933 0 District Number % Number % Number % Number % Bariadi 17,649 23 5,268 7 527 1 77,572 100 Maswa 5,991 14 1,921 4 1,298 3 42,927 100 Shinyanga Rural 5,049 11 1,520 3 306 1 45,263 100 Kahama 10,395 13 13,620 17 144 0 80,810 100 Bukombe 6,189 12 4,058 8 119 0 53,121 100 Meatu 4,250 14 2,380 8 539 2 31,410 100 Shinyanga Urban 668 7 1,206 12 122 1 10,198 100 Kishapu 3,093 9 1,177 3 352 1 35,247 100 Total 53,284 14 31,151 8 3,408 1 376,549 100 Cont…..Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year Cont….Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Other Total Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 212 District Number % Number % Number % Number % Bariadi 3,014 7 36,859 86 894 2 357 1 Maswa 3,548 16 16,666 77 433 2 108 1 Shinyanga Rural 7,490 18 31,887 78 509 1 0 0 Kahama 7,597 12 48,247 77 548 1 286 0 Bukombe 3,902 9 35,050 82 1,195 3 119 0 Meatu 1,902 9 17,291 85 244 1 164 1 Shinyanga Urban 381 4 7,800 87 338 4 0 0 Kishapu 1,936 10 16,534 85 327 2 0 0 Total 29,770 11 210,334 81 4,488 2 1,035 0 District Number % Number % Number % Number % Number % Bariadi 357 1 1,061 2 0 0 353 1 42,896 100 Maswa 217 1 217 1 0 0 433 2 21,622 100 Shinyanga Rural 303 1 599 1 0 0 0 0 40,788 100 Kahama 677 1 3,823 6 256 0 1,293 2 62,726 100 Bukombe 1,175 3 836 2 0 0 239 1 42,517 100 Meatu 411 2 62 0 0 0 376 2 20,449 100 Shinyanga Urban 120 1 196 2 0 0 182 2 9,017 100 Kishapu 82 0 163 1 0 0 316 2 19,358 100 Total 3,342 1 6,957 3 256 0 3,191 1 259,372 100 District Number % Number % Number % Number % Bariadi 0 0 535 100 0 0 535 100 Maswa 324 100 0 0 0 0 324 100 Shinyanga Rural 0 0 301 75 101 25 402 100 Kahama 3,715 44 4,219 50 504 6 8,437 100 Bukombe 358 60 239 40 0 0 597 100 Shinyanga Urban 55 47 63 53 0 0 119 100 Kishapu 78 25 237 75 0 0 315 100 Total 4,531 42 5,595 52 604 6 10,730 100 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Cont…….Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Total Excellent Good Average Total Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Locally Produced by Other Not Available Price Too High No Money to Buy Too Much Labour Required 213 District Number % Number % Number % Number % Number % Number % Bariadi 2,950 24 9,433 76 0 0 0 0 0 0 12,383 100 Maswa 5,246 57 3,447 38 433 5 0 0 0 0 9,126 100 Shinyanga Rural 9,463 57 7,011 42 204 1 0 0 0 0 16,679 100 Kahama 9,231 34 16,806 61 1,228 4 0 0 142 1 27,407 100 Bukombe 4,418 49 4,482 50 119 1 0 0 0 0 9,019 100 Meatu 659 15 3,541 80 208 5 0 0 0 0 4,408 100 Shinyanga Urban 941 22 2,685 64 124 3 452 11 0 0 4,201 100 Kishapu 1,913 37 2,625 51 651 13 0 0 0 0 5,189 100 Total 34,822 39 50,030 57 2,967 3 452 1 142 0 88,413 100 District Number % Number % Number % Number % Number % Bariadi 177 9 1,583 82 177 9 0 0 1,937 100 Maswa 202 19 636 60 217 21 0 0 1,056 100 Shinyanga Rural 191 22 397 46 274 32 0 0 862 100 Kahama 524 9 4,033 66 1,577 26 0 0 6,134 100 Bukombe 717 32 1,195 53 239 11 119 5 2,270 100 Meatu 83 100 0 0 0 0 0 0 83 100 Shinyanga Urban 30 6 484 94 0 0 0 0 514 100 Kishapu 321 22 1,058 72 81 6 0 0 1,460 100 Total 2,245 16 9,387 66 2,565 18 119 1 14,316 100 District Number % Number % Number % Number % Number % Number % Bariadi 6,245 21 21,827 75 1,048 4 0 0 178 1 29,297 100 Maswa 1,162 22 3,301 63 749 14 0 0 0 0 5,212 100 Shinyanga Rural 610 28 1,505 68 102 5 0 0 0 0 2,216 100 Kahama 8,279 47 8,855 50 273 2 142 1 0 0 17,551 100 Bukombe 4,059 33 6,907 56 836 7 477 4 119 1 12,399 100 Meatu 1,233 14 5,885 67 1,390 16 247 3 0 0 8,754 100 Shinyanga Urban 129 32 247 61 32 8 0 0 0 0 408 100 Kishapu 1,035 20 3,255 63 617 12 223 4 67 1 5,196 100 Total 22,751 28 51,782 64 5,047 6 1,089 1 365 0 81,034 100 Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Does not Work Total Excellent Good Average Poor Does not Work Total Excellent Good Average Poor Total Excellent Good Average Poor 214 District Number % Number % Number % Number % Number % Maswa 108 33 108 33 108 33 0 0 325 100 Kahama 144 50 143 50 0 0 0 0 286 100 Bukombe 0 0 119 100 0 0 0 0 119 100 Meatu 0 0 81 100 0 0 0 0 81 100 Kishapu 67 18 148 39 81 21 81 21 376 100 Total 319 27 599 50 189 16 81 7 1,188 100 District Number % Number % Number % Number % Number % Number % Bariadi 7,262 21 25,676 74 1,397 4 341 1 0 0 34,676 100 Maswa 9,965 46 10,690 49 758 4 217 1 0 0 21,630 100 Shinyanga Rural 1,407 31 2,968 66 101 2 0 0 0 0 4,475 100 Kahama 6,838 37 11,249 61 404 2 0 0 0 0 18,491 100 Bukombe 4,413 41 4,997 47 478 4 836 8 0 0 10,723 100 Meatu 1,430 13 8,036 73 1,415 13 83 1 79 1 11,043 100 Shinyanga Urban 251 21 822 70 78 7 30 3 0 0 1,182 100 Kishapu 4,406 27 8,029 50 1,890 12 1,860 11 0 0 16,184 100 Total 35,971 30 72,468 61 6,519 6 3,366 3 79 0 118,404 100 District Number % Number % Number % Bariadi 10,564 14 67,008 86 77,572 100 Maswa 2,940 7 40,312 93 43,252 100 Shinyanga Rural 5,952 13 39,311 87 45,263 100 Kahama 25,676 32 55,541 68 81,217 100 Bukombe 12,051 23 41,189 77 53,240 100 Meatu 2,148 7 29,344 93 31,492 100 Shinyanga Urban 1,198 12 9,000 88 10,198 100 Kishapu 2,933 8 32,691 92 35,624 100 Total 63,462 17 314,395 83 377,857 100 Table 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year Does not Work Total Number of Agricultural Number of Agricultural Total Excellent Good Average Poor Excellent Good Average Poor Total 215 District Number % Number % Number % Bariadi 37,354 48 40,218 52 77,572 100 Maswa 16,721 39 26,531 61 43,252 100 Shinyanga Rural 33,702 74 11,561 26 45,263 100 Kahama 39,548 49 41,789 51 81,337 100 Bukombe 31,203 59 22,038 41 53,240 100 Meatu 17,781 56 13,710 44 31,492 100 Shinyanga Urban 5,374 53 4,857 47 10,230 100 Kishapu 13,950 39 21,834 61 35,785 100 Total 195,634 52 182,537 48 378,171 100 District Number % Number % Number % Bariadi 13,704 18 63,867 82 77,572 100 Maswa 3,456 8 39,796 92 43,252 100 Shinyanga Rural 9,941 22 35,322 78 45,263 100 Kahama 13,060 16 68,157 84 81,217 100 Bukombe 16,846 32 36,394 68 53,240 100 Meatu 6,705 21 24,787 79 31,492 100 Shinyanga Urban 993 10 9,173 90 10,166 100 Kishapu 3,780 11 31,764 89 35,544 100 Total 68,484 18 309,261 82 377,746 100 Table 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year Table 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total 216 District Number % Number % Number % Bariadi 47,935 62 29,637 38 77,572 100 Maswa 11,592 27 31,660 73 43,252 100 Shinyanga Rural 7,173 16 38,090 84 45,263 100 Kahama 34,203 42 47,014 58 81,217 100 Bukombe 27,104 51 26,136 49 53,240 100 Meatu 19,853 63 11,639 37 31,492 100 Shinyanga Urban 1,430 14 8,768 86 10,198 100 Kishapu 12,271 34 23,352 66 35,624 100 Total 161,562 43 216,296 57 377,857 100 District Number % Number % Number % Bariadi 4,092 5 73,480 95 77,572 100 Maswa 2,260 5 40,992 95 43,252 100 Shinyanga Rural 2,438 5 42,825 95 45,263 100 Kahama 6,584 8 74,513 92 81,097 100 Bukombe 8,153 15 45,087 85 53,240 100 Meatu 1,532 5 29,960 95 31,492 100 Shinyanga Urban 662 6 9,536 94 10,198 100 Kishapu 3,456 10 32,168 90 35,624 100 Total 29,177 8 348,560 92 377,737 100 District Number % Number % Number % Bariadi 47,448 61 30,124 39 77,572 100 Maswa 25,091 58 18,161 42 43,252 100 Shinyanga Rural 21,196 47 24,067 53 45,263 100 Kahama 34,979 43 46,238 57 81,217 100 Bukombe 27,459 52 25,781 48 53,240 100 Meatu 20,064 64 11,427 36 31,492 100 Shinyanga Urban 2,777 27 7,421 73 10,198 100 Kishapu 20,865 59 14,677 41 35,542 100 Total 199,881 53 177,895 47 377,776 100 Table 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Table 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year Table 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total Number of Agricultural Number of Agricultural Total 217 District Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Bariadi 299,108 876 6,146 15,127 166,411 166,575 41,515 39,254 0 178 7,307 16,680 Maswa 157,151 3,531 7,005 3,398 75,727 86,098 22,267 22,679 325 0 6,168 4,985 Shinyanga Rural 190,969 1,985 3,235 6,544 100,657 86,906 27,251 22,452 0 0 4,043 5,053 Kahama 342,361 14,502 6,467 7,918 89,667 45,568 26,188 14,101 144 0 6,879 3,762 Bukombe 244,232 2,703 6,195 6,088 33,940 8,933 7,529 3,106 0 239 1,413 478 Meatu 128,101 2,982 4,892 4,018 80,458 50,390 15,822 13,176 83 0 4,568 3,138 Shinyanga Urban 36,453 1,308 982 664 17,777 13,708 4,406 3,602 179 0 699 577 Kishapu 140,279 2,773 3,099 4,123 74,090 82,886 20,704 19,576 0 0 4,796 2,896 Total 1,538,653 30,659 38,021 47,880 638,727 541,062 165,681 137,946 731 417 35,873 37,569 District Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Bariadi 175 3,006 175 3,006 0 0 0 0 520,836 244,702 Maswa 0 406 0 406 202 0 0 0 268,845 121,503 Shinyanga Rural 102 204 0 102 0 102 0 0 326,257 123,348 Kahama 143 139 143 139 0 0 0 0 471,991 86,130 Bukombe 0 239 0 239 0 239 0 239 293,309 22,502 Meatu 333 891 250 1,141 0 0 0 0 234,505 75,735 Shinyanga Urban 120 0 0 0 0 0 0 0 60,616 19,859 Kishapu 0 245 0 245 569 0 0 0 243,538 112,743 Total 872 5,131 567 5,278 772 341 0 239 2,419,897 806,521 Cont…..Table 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Table 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Total Implement / Asset Name Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Hand Hoe Hand Powered Sprayer Oxen Implement / Asset Name Ox Plough Ox Seed Planter 218 District Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Tractor Plough Tractor Harrow Threshe rs / Shellers Bariadi 77,397 21,112 68,925 68,907 178 22,937 3,006 3,006 0 0 Maswa 42,617 6,842 35,057 32,307 325 9,637 406 406 101 0 Shinyanga Rural 45,263 7,849 39,770 39,575 0 8,382 204 102 102 0 Kahama 81,086 13,524 31,785 31,515 144 9,815 282 282 0 0 Bukombe 52,300 11,687 9,331 8,032 239 1,772 239 239 239 239 Meatu 31,069 6,880 25,962 22,737 83 7,056 1,141 1,141 0 0 Shinyanga Urban 9,964 876 7,018 6,386 30 1,276 30 0 0 0 Kishapu 35,242 5,312 31,885 30,294 0 7,449 245 245 81 0 Total 374,937 74,081 249,732 239,752 999 68,324 5,553 5,421 524 239 District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 0 0 0 0 175 100 175 100 Maswa 0 0 318 60 216 40 0 0 0 0 534 100 Kahama 0 0 0 0 131 100 0 0 0 0 131 100 Bukombe 223 24 239 25 119 13 358 38 0 0 940 100 Meatu 0 0 256 61 0 0 167 39 0 0 423 100 Shinyanga Urban 15 7 157 77 0 0 32 16 0 0 205 100 Kishapu 0 0 239 80 61 20 0 0 0 0 300 100 Total 238 9 1,210 45 527 19 557 21 175 6 2,707 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 7,155 13 18,375 33 22,521 40 0 0 8,052 14 357 1 56,460 100 Maswa 3,628 10 18,417 51 10,903 30 0 0 3,029 8 432 1 36,410 100 Shinyanga Rural 4,839 13 14,192 38 9,250 25 199 1 8,630 23 303 1 37,414 100 Kahama 4,113 6 29,458 44 15,162 22 0 0 18,959 28 0 0 67,693 100 Bukombe 1,861 5 25,762 63 8,835 22 119 0 4,148 10 239 1 40,964 100 Meatu 3,398 14 9,476 38 7,425 30 0 0 4,147 17 332 1 24,778 100 Shinyanga Urban 387 4 5,846 63 1,847 20 62 1 1,057 11 122 1 9,322 100 Kishapu 2,677 9 18,953 62 5,236 17 82 0 3,363 11 81 0 30,392 100 Total 28,059 9 140,479 46 81,179 27 463 0 51,386 17 1,868 1 303,433 100 Table 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District Table 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District Total Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Not Available Price Too High No Money to Buy / Rent Equipment / Asset of No Use Implement / Asset Name Table 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultura Year 219 District Number % Number % Number % Number % Number % Number % Number % Bariadi 99 1 1,541 18 6,649 77 198 2 161 2 0 0 8,647 100 Maswa 107 1 5,105 62 2,780 34 95 1 108 1 0 0 8,195 100 Shinyanga Rural 0 0 2,016 37 3,374 61 0 0 0 0 102 2 5,493 100 Kahama 847 2 21,541 44 26,476 54 0 0 428 1 141 0 49,432 100 Bukombe 1,049 2 25,570 59 14,325 33 597 1 1,540 4 119 0 43,200 100 Meatu 0 0 2,427 45 2,504 46 164 3 164 3 188 3 5,447 100 Shinyanga Urban 64 2 1,592 50 1,267 40 62 2 195 6 0 0 3,181 100 Kishapu 0 0 2,035 54 1,703 46 0 0 0 0 0 0 3,739 100 Total 2,166 2 61,827 49 59,078 46 1,116 1 2,597 2 550 0 127,333 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 457 5 1,912 22 5,938 69 198 2 161 2 0 0 8,665 100 Maswa 108 1 5,732 52 4,901 45 95 1 108 1 0 0 10,945 100 Shinyanga Rural 0 0 2,418 43 3,270 57 0 0 0 0 0 0 5,688 100 Kahama 1,138 2 21,191 43 26,945 54 0 0 429 1 0 0 49,702 100 Bukombe 944 2 26,390 59 15,507 35 119 0 1,420 3 119 0 44,499 100 Meatu 62 1 3,111 36 4,981 57 164 2 164 2 271 3 8,754 100 Shinyanga Urban 93 2 1,853 49 1,472 39 62 2 301 8 32 1 3,812 100 Kishapu 158 3 3,013 57 2,080 39 0 0 79 1 0 0 5,330 100 Total 2,960 2 65,620 48 65,093 47 638 0 2,663 2 422 0 137,397 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 30,404 39 14,784 19 20,987 27 179 0 10,506 14 533 1 77,394 100 Maswa 12,820 30 15,541 36 13,266 31 0 0 1,192 3 108 0 42,927 100 Shinyanga Rural 16,939 38 16,703 37 8,692 19 0 0 2,826 6 0 0 45,161 100 Kahama 13,960 17 24,937 31 37,274 46 135 0 4,767 6 0 0 81,073 100 Bukombe 7,885 15 23,702 45 18,216 35 239 0 2,131 4 0 0 52,173 100 Meatu 10,946 35 8,671 28 9,937 32 0 0 1,726 6 47 0 31,327 100 Shinyanga Urban 2,156 21 4,458 44 2,977 29 95 1 513 5 0 0 10,198 100 Kishapu 6,740 19 19,023 53 7,430 21 0 0 2,430 7 0 0 35,624 100 Total 101,851 27 127,820 34 118,780 32 648 0 26,090 7 688 0 375,877 100 Table 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District Table 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Table 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District 220 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,276 2 15,413 28 29,886 55 179 0 7,712 14 169 0 54,634 100 Maswa 1,690 5 13,249 39 17,309 51 0 0 1,151 3 216 1 33,615 100 Shinyanga Rural 1,012 3 15,656 42 19,311 52 102 0 699 2 101 0 36,881 100 Kahama 794 1 25,123 35 42,857 60 98 0 2,410 3 120 0 71,402 100 Bukombe 2,066 4 25,623 50 21,179 42 239 0 1,653 3 0 0 50,760 100 Meatu 175 1 12,120 50 11,194 46 0 0 752 3 195 1 24,436 100 Shinyanga Urban 270 3 4,254 48 3,766 42 62 1 570 6 0 0 8,922 100 Kishapu 326 1 18,056 64 8,094 29 0 0 1,537 5 82 0 28,095 100 Total 7,608 2 129,496 42 153,595 50 680 0 16,483 5 883 0 308,745 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,588 2 32,834 44 34,915 47 0 0 5,061 7 169 0 74,566 100 Maswa 3,220 8 19,087 45 19,572 46 0 0 751 2 216 1 42,846 100 Shinyanga Rural 6,055 13 19,348 43 19,050 42 0 0 606 1 0 0 45,059 100 Kahama 8,569 11 32,609 40 34,101 42 278 0 5,378 7 0 0 80,935 100 Bukombe 4,882 9 17,363 33 27,904 53 119 0 2,025 4 0 0 52,293 100 Meatu 504 2 14,782 49 14,476 48 0 0 331 1 94 0 30,186 100 Shinyanga Urban 686 7 4,160 41 4,825 47 32 0 465 5 0 0 10,168 100 Kishapu 163 0 16,265 46 16,355 46 0 0 2,514 7 82 0 35,379 100 Total 25,666 7 156,448 42 171,197 46 429 0 17,130 5 560 0 371,431 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 1,942 3 32,474 44 33,491 45 0 0 6,312 8 347 0 74,566 100 Maswa 2,812 7 18,671 44 20,388 48 0 0 758 2 216 1 42,846 100 Shinyanga Rural 5,950 13 19,443 43 19,364 43 0 0 405 1 0 0 45,161 100 Kahama 8,734 11 33,046 41 33,099 41 141 0 5,915 7 0 0 80,935 100 Bukombe 5,206 10 16,659 32 28,396 54 0 0 2,031 4 0 0 52,293 100 Meatu 550 2 15,935 53 13,441 44 0 0 331 1 94 0 30,351 100 Shinyanga Urban 593 6 4,235 42 4,752 47 64 1 554 5 0 0 10,198 100 Kishapu 241 1 16,487 47 16,055 45 0 0 2,514 7 82 0 35,379 100 Total 26,028 7 156,951 42 168,985 45 205 0 18,821 5 739 0 371,728 100 Table 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District Table 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District Table 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required 221 District Number % Number % Number % Number % Number % Number % Number % Bariadi 15,614 20 24,492 32 26,617 34 0 0 10,685 14 163 0 77,572 100 Maswa 5,582 13 17,227 40 19,252 45 0 0 975 2 216 1 43,252 100 Shinyanga Rural 6,253 14 17,646 39 19,952 44 0 0 1,310 3 0 0 45,161 100 Kahama 12,083 15 30,072 37 32,331 40 141 0 6,589 8 0 0 81,217 100 Bukombe 5,672 11 15,986 31 27,905 53 0 0 2,729 5 0 0 52,293 100 Meatu 2,716 9 14,194 45 10,965 35 0 0 3,569 11 47 0 31,492 100 Shinyanga Urban 619 6 4,444 44 4,424 43 32 0 680 7 0 0 10,198 100 Kishapu 731 2 16,530 46 15,015 42 0 0 3,266 9 82 0 35,624 100 Total 49,271 13 140,592 37 156,460 42 173 0 29,804 8 508 0 376,808 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 23,919 31 16,968 22 22,115 29 354 0 13,693 18 523 1 77,572 100 Maswa 9,114 21 15,301 35 17,430 40 0 0 1,191 3 216 1 43,252 100 Shinyanga Rural 9,987 22 16,902 37 15,646 35 0 0 2,625 6 102 0 45,263 100 Kahama 13,431 17 28,483 35 32,424 40 0 0 6,633 8 247 0 81,217 100 Bukombe 18,922 36 17,645 34 13,820 26 0 0 1,905 4 0 0 52,293 100 Meatu 5,628 18 11,333 36 9,095 29 0 0 5,341 17 94 0 31,492 100 Shinyanga Urban 1,926 19 4,179 41 3,111 31 32 0 950 9 0 0 10,198 100 Kishapu 3,999 11 16,190 45 12,432 35 0 0 2,920 8 82 0 35,624 100 Total 86,927 23 127,001 34 126,074 33 386 0 35,258 9 1,264 0 376,910 100 District Number % Number % Number % Number % Number % Number % Number % Bariadi 52,198 67 21,152 27 1,067 1 178 0 169 0 2,634 3 77,397 100 Maswa 35,271 84 4,062 10 1,381 3 216 1 0 0 1,186 3 42,116 100 Shinyanga Rural 33,165 74 8,985 20 399 1 0 0 204 0 2,205 5 44,958 100 Kahama 64,828 80 12,916 16 1,242 2 144 0 282 0 1,544 2 80,956 100 Bukombe 44,112 85 5,581 11 351 1 119 0 239 0 1,777 3 52,180 100 Meatu 22,822 74 4,789 16 81 0 247 1 83 0 2,874 9 30,896 100 Shinyanga Urban 6,657 67 2,791 28 238 2 64 1 31 0 124 1 9,904 100 Kishapu 31,157 89 3,435 10 80 0 245 1 0 0 244 1 35,160 100 Total 290,210 78 63,709 17 4,840 1 1,213 0 1,008 0 12,588 3 373,568 100 Table 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District Table 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District Table 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District Equipment / Asset of No Other Total Sale of Farm Products Other Income Generating Remittances Bank Loan Credit Other Total Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Other Total 222 District Number % Number % Number % Number % Number % Bariadi 3,523 59 2,462 41 0 0 0 0 5,985 100 Maswa 3,443 100 0 0 0 0 0 0 3,443 100 Shinyanga Rural 1,713 77 400 18 0 0 102 5 2,214 100 Kahama 5,614 89 567 9 0 0 144 2 6,325 100 Bukombe 5,240 90 358 6 239 4 0 0 5,837 100 Meatu 2,390 79 564 19 0 0 83 3 3,037 100 Shinyanga Urban 344 100 0 0 0 0 0 0 344 100 Kishapu 1,704 89 140 7 81 4 0 0 1,926 100 Total 23,971 82 4,491 15 320 1 328 1 29,111 100 District Number % Number % Number % Number % Number % Number % Bariadi 21,647 69 4,957 16 355 1 0 0 4,543 14 31,502 100 Maswa 14,080 92 433 3 325 2 0 0 528 3 15,365 100 Shinyanga Rural 15,423 78 2,106 11 918 5 0 0 1,416 7 19,863 100 Kahama 18,800 90 1,153 6 141 1 144 1 553 3 20,791 100 Bukombe 6,590 95 119 2 0 0 0 0 239 3 6,949 100 Meatu 9,992 67 954 6 83 1 0 0 3,774 25 14,804 100 Shinyanga Urban 3,111 84 423 11 0 0 0 0 154 4 3,687 100 Kishapu 12,134 86 716 5 158 1 0 0 1,042 7 14,048 100 Total 101,777 80 10,860 9 1,980 2 144 0 12,248 10 127,009 100 District Number % Number % Number % Number % Number % Number % Bariadi 24,773 78 5,935 19 177 1 0 0 1,058 3 31,942 100 Maswa 14,076 94 433 3 217 1 0 0 310 2 15,036 100 Shinyanga Rural 15,217 77 2,804 14 918 5 0 0 808 4 19,748 100 Kahama 17,908 89 1,338 7 141 1 134 1 686 3 20,207 100 Bukombe 4,931 93 234 4 0 0 119 2 0 0 5,284 100 Meatu 8,882 76 571 5 0 0 0 0 2,225 19 11,678 100 Shinyanga Urban 2,860 75 632 17 30 1 125 3 154 4 3,801 100 Kishapu 12,290 89 1,050 8 0 0 0 0 488 4 13,828 100 Total 100,938 83 12,997 11 1,483 1 378 0 5,729 5 121,525 100 Table 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District Table 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OXEN by Source of Finance and District Table 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District Total Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total Total Sale of Farm Products Other Income Generating Remittances Bank Loan Other Sale of Farm Products Other Income Generating Credit Other Appendix II 223 District Number % Number % Number % Maswa 325 100 0 0 325 100 Kahama 144 100 0 0 144 100 Meatu 83 100 0 0 83 100 Shinyanga Urban 0 0 30 100 30 100 Total 552 95 30 5 582 100 District Number % Number % Number % Number % Number % Bariadi 5,422 78 1,381 20 0 0 163 2 6,967 100 Maswa 5,086 96 0 0 0 0 216 4 5,302 100 Shinyanga Rural 2,720 77 303 9 306 9 204 6 3,533 100 Kahama 6,217 96 263 4 0 0 0 0 6,480 100 Bukombe 1,294 100 0 0 0 0 0 0 1,294 100 Meatu 3,542 80 323 7 0 0 538 12 4,402 100 Shinyanga Urban 575 82 63 9 0 0 61 9 699 100 Kishapu 3,909 83 647 14 0 0 162 3 4,717 100 Total 28,765 86 2,980 9 306 1 1,343 4 33,394 100 District District Number % Number % Number % Number % Number % Number % Bariadi 0 0 0 0 175 100 175 100 Maswa 101 100 101 100 Shinyanga Rural 102 100 0 0 0 0 102 100 Kishapu 81 100 81 100 Kahama 0 0 143 100 0 0 143 100 Total 183 100 183 100 Meatu 250 100 0 0 0 0 250 100 Shinyanga Urban 30 100 0 0 0 0 30 100 Total 382 55 143 20 175 25 699 100 District Number % Number % Number % Number % Bariadi 0 0 0 0 175 100 175 100 Kahama 0 0 143 100 0 0 143 100 Meatu 250 100 0 0 0 0 250 100 Total 250 44 143 25 175 31 567 100 Table 12.2.21 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District Sale of Farm Products Total Table 12.2.20 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR PLOUGH by Source of Finance and District Table 12.2.19 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District Table 12.2.18 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX CART by Source of Finance and District Table 12.2.17 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District Sale of Farm Products Bank Loan Credit Total Other Total Sale of Farm Products Bank Loan Credit Total Sale of Farm Products Other Income Generating Total Sale of Farm Products Other Income Generating Activities Remittances Tanzania Agriculture Sample Census - 2003 Shinyanga Appendix II 224 AGRICULTURE CREDIT Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 225 Number % Number % Bariadi 1,733 77 525 23 2,258 Maswa 650 75 217 25 867 Shinyanga Rural 100 25 302 75 401 Kahama 2,040 94 137 6 2,177 Bukombe 716 86 119 14 836 Meatu 81 33 165 67 246 Shinyanga Urban 0 0 23 100 23 Kishapu 82 33 164 67 245 Total 5,402 77 1,651 23 7,054 % 77 23 District Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Bariadi 531 0 0 346 1,381 0 2,258 Maswa 542 0 0 108 0 217 867 Shinyanga Rural 0 0 0 0 0 401 401 Kahama 676 0 1,501 0 0 0 2,177 Bukombe 239 0 0 478 0 119 836 Meatu 81 83 0 82 0 0 246 Shinyanga Urban 0 0 0 23 0 0 23 Kishapu 163 0 0 0 0 82 245 Total 2,233 83 1,501 1,037 1,381 819 7,054 % 32 1 21 15 20 12 100 13.2c AGRICULTURE CREDIT: Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year 13.2a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year District Male Female Total Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 226 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Bariadi 3,128 15,731 4,887 3,112 28,173 333 175 0 19,776 75,314 Maswa 3,762 9,983 6,514 1,822 12,849 318 215 209 6,711 42,385 Shinyanga Rural 2,740 9,675 6,394 1,527 10,050 100 908 102 13,366 44,862 Kahama 6,180 12,761 14,721 1,474 20,417 1,163 266 0 22,058 79,040 Bukombe 2,609 20,415 3,564 1,054 11,791 239 358 0 12,374 52,404 Meatu 647 1,710 2,315 2,693 11,645 1,025 164 167 10,879 31,246 Shinyanga Urban 757 843 1,707 163 3,514 61 152 0 2,978 10,175 Kishapu 1,433 3,172 2,256 719 14,517 561 291 81 12,349 35,378 Total 21,257 74,290 42,359 12,564 112,955 3,798 2,529 560 100,492 370,804 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livestock Other Total Credits Bariadi 696 705 0 1,378 528 0 0 179 3,485 Maswa 217 434 0 108 217 0 0 434 1,409 Shinyanga Rural 100 102 100 0 199 0 0 0 502 Kahama 529 1,227 1,368 1,652 392 0 137 410 5,715 Bukombe 478 239 119 358 119 119 0 0 1433.4027 Meatu 0 0 0 163 82 0 83 0 328 Shinyanga Urban 0 0 0 0 0 0 0 23.301541 23.301541 Kishapu 164 82 0 82 82 0 0 0 408.46176 Total Credits 2,183 2,788 1,588 3,741 1,618 119 220 1,046 13,304 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Shinyanga 227 Appendix II 228 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 229 District Senna Spp Gravellis Afzelia Quanzensis Acacia Spp Pinus Spp Eucalyptus Spp Cyprus Spp Casurina Equisetfilia Tectona Grandis Terminalia Catapa Bariadi 10 43 . 181 17 25 . . . . Maswa 38 2,005 . . . 52 . . . . Shinyanga Rural 10 16 . 284 . . . 3 . . Kahama 5 . . . . . 30 . 1 . Bukombe . 125 9 4 . 4 . . . 7 Meatu . 93 . 120 . . . . . . Shinyanga Urban 3 68 . 77 . . . . . 1 Kishapu . 4 . 733 . . . . . . Total 66 2,354 9 1,399 17 81 30 3 1 8 % 0 10 0 6 0 0 0 0 0 0 District Terminalia Ivorensis Berchemoides Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Albizia Spp Calliandra Spp Moringa Spp TOTAL Bariadi . . . . . . . . . 11,261 Maswa . . 70 . 105 . 20 . . 48 Shinyanga Rural 10 . 146 2 499 . 4 . 9 0 Kahama . 32 . 1 91 . . . . 0 Bukombe . . . . . . . . . 0 Meatu . . 5,050 . 6 . . . . 11,261 Shinyanga Urban 2 . 136 . 398 7 . . 22 243 Kishapu . . 370 . 106 7 . 200 . 670 Total 12 32 5,772 3 1,205 14 24 200 31 23,483 % 0 0 25 0 5 0 0 1 0 100 cont…. ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 230 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Bariadi 8 85 10 88 6 83 24 256 Maswa 4 2,056 3 222 2 12 9 2,290 Shinyanga Rural 15 151 9 215 2 617 26 983 Kahama 7 79 4 81 0 . 11 160 Bukombe 7 36 5 13 1 100 13 149 Meatu 1 5 4 5,098 4 166 9 5,269 Shinyanga Urban 28 523 9 191 0 . 37 714 Kishapu 4 1,330 5 63 1 20 10 1,413 Total 74 4,265 49 5,971 16 998 139 11,234 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bariadi 3 1 18 8 0 0 30 Maswa 4 2 7 0 0 1 14 Shinyanga Rural 1 0 23 7 3 0 34 Kahama 7 2 0 1 1 2 13 Bukombe 4 0 3 2 0 3 12 Meatu 0 2 6 2 0 0 10 Shinyanga Urban 1 3 41 30 4 0 79 Kishapu 8 1 2 2 3 0 16 Total 28 11 100 52 11 6 208 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region District Main Use 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Shinyanga Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 231 1-9 10-19 20-29 30-39 40-49 Above 50 Total Bariadi 14,360 4,433 1,180 1,323 705 1,737 23,738 Maswa 297 325 108 425 756 540 2,451 Shinyanga Rural 2,804 808 813 509 714 408 6,057 Kahama 2,283 0 2,137 2,152 0 144 6,716 Bukombe Meatu 852 92 313 203 359 235 2,054 Shinyanga Urban 1,101 118 88 88 0 29 1,426 Kishapu 896 1,106 646 80 642 480 3,850 Total 22,593 6,882 5,286 4,781 3,176 3,574 46,292 % 49 15 11 10 7 8 100 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Bariadi 3 1 18 8 0 0 30 Maswa 4 2 7 0 0 1 14 Shinyanga Rural 1 0 23 7 3 0 34 Kahama 7 2 0 1 1 2 13 Bukombe 4 0 3 2 0 3 12 Meatu 0 2 6 2 0 0 10 Shinyanga Urban 1 3 41 30 4 0 79 Kishapu 8 1 2 2 3 0 16 Total 28.0 11.0 100.0 52.0 11.0 6.0 208.0 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Bariadi 1 1 0 9 19 0 0 30 Maswa 1 4 0 6 1 0 2 14 Shinyanga Rural 2 6 3 8 11 3 1 34 Kahama 1 0 0 10 2 0 0 13 Bukombe 0 3 0 5 4 0 0 12 Meatu 0 0 0 1 2 4 3 10 Shinyanga Urban 1 3 1 23 38 7 2 75 Kishapu 1 8 1 4 0 2 0 16 Total 7 25 5 66 77 16 8 204 District Main Use 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Shinyanga Region District Second Use 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Shinyanga Region District Distance to Community Planted Forest (km) 14 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 232 CROP EXTENSION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 233 Number % Number % Bariadi 16,641 21 60,931 79 77,572 Maswa 2,469 6 40,783 94 43,252 Shinyanga Rural 12,421 27 32,842 73 45,263 Kahama 29,021 36 52,195 64 81,217 Bukombe 7,386 14 45,854 86 53,240 Meatu 14,761 47 16,731 53 31,492 Shinyanga Urban 3,364 33 6,834 67 10,198 Kishapu 18,190 51 17,434 49 35,624 Total 104,252 28 273,606 72 377,857 Total Number % Number % Number % Number % Number % Number Bariadi 4,228 26 12,258 74 0 0 0 0 0 0 16,486 Maswa 324 13 1,617 66 527 21 0 0 0 0 2,469 Shinyanga Rural 3,330 27 7,503 60 1,388 11 200 2 0 0 12,421 Kahama 2,046 7 19,828 72 5,571 20 142 1 0 0 27,587 Bukombe 830 11 5361 74 836 12 239 3 0 0 7,266 Meatu 1,273 9 7,874 53 5,239 35 239 2 135 1 14,761 Shinyanga Urban 104 3 2,082 62 775 23 339 10 64 2 3,364 Kishapu 1,342 7 9,551 53 6,567 36 489 3 159 1 18,109 Total 13,478 13 66,075 64 20,903 20 1,648 2 358 0 102,463 Total Number % Number % Number % Number % Number % Number % Number Bariadi 15,757 95 357 2 348 2 0 0 0 0 179 1 16,641 Maswa 2,144 86.84807554 217 9 108 4 0 0 0 0 0 0 2,469 Bukombe 11,617 95 400 3 0 0 99 1 0 0 100 1 12,217 Kahama 27,094 98 634 2 0 0 0 0 0 0 0 0 27,729 Bukombe 7,028 98 119 2 0 0 0 0 0 0 0 0 7,147 Meatu 14,101 96 494 3 0 0 83 1 0 0 0 0 14,678 Shinyanga Urban 3,301 98 31 1 0 0 0 0 32 1 0 0 3,364 Kishapu 17,547 97 237 1 0 0 160 1 0 0 81 0 18,026 Total 98,589 96 2,489 2 456 0 343 0 32 0 361 0 102,269 Average 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region District Government NGO / Development Project Not Other Very Good Poor Good Cooperative Large Scale Farm 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region District 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Shinyanga Region District Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households No Good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 234 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Bariadi 15,043 357 348 0 0 0 15,748 77,572 20 Maswa 1,927 217 108 0 0 0 2,252 43,252 5 Shinyanga Rural 9,705 400 0 99 0 100 10,304 45,263 23 Kahama 26,219 634 0 0 0 0 26,854 81,217 33 Bukombe 6,192 119 0 0 0 0 6,311 53,240 12 Meatu 13,939 494 0 0 0 0 14,434 31,492 46 Shinyanga Urban 3,001 31 0 0 32 0 3,064 10,198 30 Kishapu 17,004 237 0 0 0 81 17,322 35,624 49 Total 93,030 2,489 456 99 32 182 96,288 377,857 25 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 12,303 179 169 0 179 12,830 77,572 17 Maswa 1,603 216 0 108 0 1,928 43,252 4 Shinyanga Rural 5,052 601 0 0 0 5,652 45,263 12 Kahama 23,762 770 133 0 0 24,665 81,217 30 Bukombe 4,062 119 0 0 358 4,540 53,240 9 Meatu 8,976 0 0 83 245 9,304 31,492 30 Shinyanga Urban 1,226 0 0 0 31 1,256 10,198 12 Kishapu 10,706 81 0 82 0 10,869 35,624 31 Total 67,690 1,966 302 273 814 71,044 377,857 18.8 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Use of Agrochemicals District Spacing Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 235 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 4,742 358 0 5,099 77,572 7 Maswa 325 108 0 433 43,252 1 Shinyanga Rural 5,834 402 0 6,236 45,263 14 Kahama 17,032 328 142 17,502 81,217 22 Bukombe 1,666 0 358 2,025 53,240 4 Meatu 7,638 247 83 7,968 31,492 25 Shinyanga Urban 1,189 0 0 1,189 10,198 12 Kishapu 7,672 0 160 7,832 35,624 22 Total 46,097 1,443 743 48,284 377,857 13 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 10,512 0 348 169 0 11,029 77,572 14 Maswa 1,400 527 0 217 0 2,144 43,252 5 Shinyanga Rural 9,025 900 0 0 0 9,925 45,263 22 Kahama 20,525 0 140 0 142 20,807 81,217 26 Bukombe 4,399 119 0 0 119 4,638 53,240 9 Meatu 10,085 410 0 0 83 10,578 31,492 34 Shinyanga Urban 2,764 0 0 0 62 2,826 10,198 28 Kishapu 12,008 79 0 81 242 12,410 35,624 35 Total 70,719 2,035 488 467 649 74,358 377,857 20 District Organic Fertilizer Use 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year Erosion Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 236 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 2,658 179 0 0 0 0 2,837 77,572 4 Maswa 216 325 0 0 0 0 541 43,252 1 Shinyanga Rural 3,128 701 0 0 0 201 4,030 45,263 9 Kahama 17,766 1,117 0 0 0 394 19,277 81,217 24 Bukombe 2,151 0 0 0 0 358 2,509 53,240 5 Meatu 4,355 165 0 0 0 0 4,519 31,492 14 Shinyanga Urban 539 0 0 0 32 0 571 10,198 6 Kishapu 3,751 237 80 160 0 162 4,390 35,624 12 Total 34,563 2,723 80 160 32 1,116 38,673 377,857 10 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 11,110 0 0 169 0 0 11,279 77,572 15 Maswa 1,291 528 0 0 0 0 1,819 43,252 4 Shinyanga Rural 6,822 1,003 0 102 0 202 8,129 45,263 18 Kahama 21,642 624 275 0 0 282 22,823 81,217 28 Bukombe 4,764 0 0 119 0 0 4,884 53,240 9 Meatu 11,409 416 0 0 0 83 11,909 31,492 38 Shinyanga Urban 2,284 0 0 0 63 31 2,377 10,198 23 Kishapu 12,891 238 0 0 0 644 13,773 35,624 39 Total 72,213 2,809 275 390 63 1,242 76,993 377,857 20 % 93.8 3.6 0.4 0.5 0.1 1.6 100 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seed 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Inorganic Fertilizer Use Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 237 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 2,259 0 179 0 0 2,438 77,572 3 Maswa 324 0 0 0 0 324 43,252 1 Shinyanga Rural 2,730 102 0 0 202 3,035 45,263 7 Kahama 1,407 98 0 0 282 1,787 81,217 2 Bukombe 597 119 0 119 239 1,075 53,240 2 Meatu 3,766 0 0 0 165 3,931 31,492 12 Shinyanga Urban 693 0 0 0 30 723 10,198 7 Kishapu 2,137 0 0 0 238 2,376 35,624 7 Total 13,914 319 179 119 1,157 15,688 377,857 4 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 4,048 0 179 0 0 4,227 77,572 5 Maswa 216 0 0 0 0 216 43,252 1 Shinyanga Rural 4,236 303 0 0 100 4,639 45,263 10 Kahama 7,134 240 0 0 142 7,516 81,217 9 Bukombe 1,912 0 0 0 239 2,151 53,240 4 Meatu 3,686 0 0 0 83 3,770 31,492 12 Shinyanga Urban 1,250 0 0 32 0 1,282 10,198 13 Kishapu 4,329 0 0 0 229 4,559 35,624 13 Total 26,812 543 179 32 794 28,359 377,857 8 District District 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Mechanisation / LST Irrigation Technology 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 238 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 10,470 178 0 348 0 0 10,996 77,572 14 Maswa 1,508 203 0 0 0 0 1,711 43,252 4 Shinyanga Rural 7,525 603 0 99 0 0 8,228 45,263 18 Kahama 21,309 647 275 0 0 0 22,230 81,217 27 Bukombe 2,748 0 0 0 0 119 2,868 53,240 5 Meatu 10,553 307 0 83 0 371 11,313 31,492 36 Shinyanga Urban 2,122 27 0 15 64 0 2,229 10,198 22 Kishapu 8,847 0 0 0 0 240 9,087 35,624 26 Total 65,082 1,965 275 545 64 730 68,660 377,857 18 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 3,512 179 169 0 0 0 3,860 77,572 5 Maswa 210 0 0 108 0 0 318 43,252 1 Shinyanga Rural 5,538 201 0 0 0 0 5,739 45,263 13 Kahama 10,730 240 142 0 0 250 11,362 81,217 14 Bukombe 836 0 0 0 0 358 1,195 53,240 2 Meatu 5,530 0 0 0 0 407 5,937 31,492 19 Shinyanga Urban 1,280 0 0 0 32 0 1,312 10,198 13 Kishapu 5,426 0 0 0 0 226 5,652 35,624 16 Total 33,062 620 311 108 32 1,242 35,375 377,857 9 % 93.5 1.8 0.9 0.3 0.1 3.5 100 Crop Storage Vermin Control 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region. District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 239 Government NGO / Development Project Large Scale Farm Not applicable Total Total Bariadi 5,513 356 174 179 6,222 6,222 77,572 8 Maswa 325 0 0 0 325 325 43,252 1 Shinyanga Rural 5,230 898 99 0 6,228 6,228 45,263 14 Kahama 11,217 0 0 569 11,786 11,786 81,217 15 Bukombe 1,075 0 0 358 1,434 1,434 53,240 3 Meatu 4,982 0 78 409 5,469 5,469 31,492 17 Shinyanga Urban 1,296 0 0 32 1,327 1,327 10,198 13 Kishapu 10,848 0 81 145 11,074 11,074 35,624 31 Total 40,484 1,255 433 1,692 43,864 43,864 377,857 11.6 Government NGO / Development Project Cooperative Not applicable Total Total Number of households % of total number of households Bariadi 1,043 0 0 0 1,043 77,572 1 Maswa 649 203 108 0 960 43,252 2 Shinyanga Rural 4,637 201 0 0 4,838 45,263 11 Kahama 12,406 98 0 283 12,787 81,217 16 Bukombe 956 0 0 239 1,195 53,240 2 Meatu 4,779 83 0 0 4,862 31,492 15 Shinyanga Urban 747 0 0 0 747 10,198 7 Kishapu 3,755 0 80 145 3,980 35,624 11 Total 28,972 584 188 668 30,412 377,857 8.0 % 95.3 1.9 0.6 2.2 100 Agro-progressing % of total number of households Total Number of households 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Agro-forestry District 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 240 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 532 0 0 532 77,572 1 Maswa 324 0 0 324 43,252 1 Shinyanga Rural 2,022 99 102 2,223 45,263 5 Kahama 426 110 276 812 81,217 1 Bukombe 0 0 358 358 53,240 1 Meatu 219 0 333 552 31,492 2 Shinyanga Urban 152 0 0 152 10,198 1 Kishapu 242 0 0 242 35,624 1 Total 3,917 210 1,070 5,196 377,857 1 % 75 4 21 100 Government NGO / Development Project Cooperative Not applicable Total Total Total Number of households % of total number of households Bariadi 179 0 0 0 179 179 77,572 0 Maswa 649 0 108 0 757 757 43,252 2 Shinyanga Rural 605 0 0 0 605 605 45,263 1 Kahama 280 0 0 276 556 556 81,217 1 Bukombe 0 0 0 358 358 358 53,240 1 Meatu 83 0 0 333 416 416 31,492 1 Shinyanga Urban 32 30 0 0 62 62 10,198 1 Kishapu 487 0 0 0 487 487 35,624 1 Total 2,313 30 108 968 3,419 3,419 377,857 0.9 District Fish Farming District 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Shinyanga Region 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Beekeeping Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 241 Received Adopted % Received Adopted % Received Adopted % Bariadi 15,748 13,816 88 12,830 9,117 71 4,925 2,638 54 Maswa 2,252 2,144 95 1,928 1,711 89 433 433 100 Shinyanga Rural 10,406 9,393 90 5,145 1,110 22 6,034 4,120 68 Kahama 26,717 23,855 89 24,528 18,669 76 17,510 12,586 72 Bukombe 6,311 4,882 77 4,062 2,628 65 1,666 1,308 78 Meatu 14,434 10,454 72 8,391 4,265 51 7,395 1,790 24 Shinyanga Urban 3,032 1,957 65 1,168 612 52 1,161 612 53 Kishapu 17,482 14,828 10,869 3,551 7,832 1,720 455 Total 96,382 81,330 84 68,920 41,663 60 46,957 25,207 54 Received Adopted % Received Adopted % Received Adopted % Bariadi 11,029 6,113 55 2,837 1,210 43 11,632 7,659 66 Maswa 2,144 1,718 80 649 216 33 1,711 1,710 100 Shinyanga Rural 10,026 8,010 80 3,422 1,414 41 8,229 3,715 45 Kahama 20,951 17,292 83 18,995 12,215 64 22,686 16,101 71 Bukombe 4,280 2,026 47 2,031 955 47 4,884 2,146 44 Meatu 10,578 3,678 35 4,031 1,659 41 11,993 7,160 60 Shinyanga Urban 2,917 1,924 66 556 239 43 2,377 984 41 Kishapu 12,407 4,861 4,228 478 13,936 8,834 Total 74,332 45,621 61 36,748 18,387 50 77,447 48,310 62 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed District Spacing Use of Agrochemicals 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region Erosion Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 242 Received Adopted % Received Adopted % Received Adopted % Bariadi 2,438 1,896 78 3,359 1,925 57 11,353 9,930 87 Maswa 324 216 67 216 108 50 1,711 1,602 94 Shinyanga Rural 2,734 708 26 4,334 1,109 26 8,225 7,414 90 Kahama 945 562 60 7,099 5,299 75 22,502 19,834 88 Bukombe 478 1,433 300 1,195 717 60 2,748 2,390 87 Meatu 3,018 2,062 68 2,609 1,569 60 11,020 9,745 88 Shinyanga Urban 665 107 16 1,289 388 30 2,288 1,722 75 Kishapu 2,216 149 4,071 872 9,249 5,478 Total 12,818 7,133 56 24,173 11,987 50 69,096 58,115 84 Received Adopted % Received Adopted % Received Adopted % Bariadi 3,155 2,973 94 5,690 5,154 91 1,049 882 84 Maswa 318 318 100 216 325 150 960 311 32 Shinyanga Rural 5,433 4,840 89 5,919 5,430 92 4,838 3,837 79 Kahama 11,221 9,520 85 10,938 10,529 96 12,508 7,771 62 Bukombe 478 956 200 717 1,075 150 597 478 80 Meatu 5,032 5,609 111 4,313 5,388 125 4,779 2,136 45 Shinyanga Urban 1,344 707 53 1,264 891 70 689 401 58 Kishapu 5,162 3,811 10,911 9,643 3,898 481 Total 32,144 28,734 89 39,969 38,435 96 29,320 16,297 56 Received Adopted % Received Adopted % Received Adopted % Bariadi 1,049 882 84 175 175 100 0 0 0 Maswa 960 311 32 324 108 33 865 649 75 Shinyanga Rural 4,838 3,837 79 2,121 503 24 605 0 0 Kahama 12,508 7,771 62 395 393 100 143 143 0 Bukombe 597 478 80 0 0 0 0 0 0 Meatu 4,779 2,136 45 498 331 67 416 250 60 Shinyanga Urban 689 401 58 152 57 38 32 0 0 Kishapu 3,898 481 80 0 162 0 Total 29,320 16,297 56 3,744 1,567 42 2,223 1,220 55 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region District Agro-forestry Beekeeping Fish Farming 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region District Vermin Control Agro-progressing Agro-forestry 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region District Mechanisation / LST Irrigation Technology Crop Storage Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 243 Number % Number % Bariadi 16,641 21 60,931 79 77,572 Maswa 2,469 6 40,783 94 43,252 Shinyanga Rural 12,421 27 32,842 73 45,263 Kahama 29,021 36 52,195 64 81,217 Bukombe 7,386 14 45,854 86 53,240 Meatu 14,761 47 16,731 53 31,492 Shinyanga Urban 3,364 33 6,834 67 10,198 Kishapu 18,190 51 17,434 49 35,624 Total 104,252 28 273,606 72 377,857 Total Number % Number % Number % Number % Number % Number Bariadi 4,228 26 12,258 74 0 0 0 0 0 0 16,486 Maswa 324 13 1,617 66 527 21 0 0 0 0 2,469 Shinyanga Rural 3,330 27 7,503 60 1,388 11 200 2 0 0 12,421 Kahama 2,046 7 19,828 72 5,571 20 142 1 0 0 27,587 Bukombe 830.072222 11.4 5360.97405 74 836 12 239 3 0 0 7,266 Meatu 1,273 9 7,874 53 5,239 35 239 2 135 1 14,761 Shinyanga Urban 104 3 2,082 62 775 23 339 10 64 2 3,364 Kishapu 1,342 7 9,551 53 6,567 36 489 3 159 1 18,109 Total 13,478 13 66,075 64 20,903 20 1,648 2 358 0 102,463 Total Number % Number % Number % Number % Number % Number % Number Bariadi 15,757 95 357 2 348 2 0 0 0 0 179 1 16,641 Maswa 2,144 86.8 217 9 108 4 0 0 0 0 0 0 2,469 Bukombe 11,617 95 400 3 0 0 99 1 0 0 100 1 12,217 Kahama 27,094 98 634 2 0 0 0 0 0 0 0 0 27,729 Bukombe 7,028 98 119 2 0 0 0 0 0 0 0 0 7,147 Meatu 14,101 96 494 3 0 0 83 1 0 0 0 0 14,678 Shinyanga Urban 3,301 98 31 1 0 0 0 0 32 1 0 0 3,364 Kishapu 17,547 97 237 1 0 0 160 1 0 0 81 0 18,026 Total 98,589 96 2,489 2 456 0 343 0 32 0 361 0 102,269 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Shinyanga Region District Government NGO / Development Cooperative Large Scale Other Not applicable District Households Receiving Extension Advice Households Not Receiving Extension Advice 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Total Number of Households Poor No Good 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Shinyanga Region District Very Good Good Average Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 244 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Bariadi 15,043 357 348 0 0 0 15,748 77,572 20 Maswa 1,927 217 108 0 0 0 2,252 43,252 5 Shinyanga Rural 9,705 400 0 99 0 100 10,304 45,263 23 Kahama 26,219 634 0 0 0 0 26,854 81,217 33 Bukombe 6,192 119 0 0 0 0 6,311 53,240 12 Meatu 13,939 494 0 0 0 0 14,434 31,492 46 Shinyanga Urban 3,001 31 0 0 32 0 3,064 10,198 30 Kishapu 17,004 237 0 0 0 81 17,322 35,624 49 Total 93,030 2,489 456 99 32 182 96,288 377,857 25 % 97 3 0 0 0 0 100 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 12,303 179 169 0 179 12,830 77,572 17 Maswa 1,603 216 0 108 0 1,928 43,252 4 Shinyanga Rural 5,052 601 0 0 0 5,652 45,263 12 Kahama 23,762 770 133 0 0 24,665 81,217 30 Bukombe 4,062 119 0 0 358 4,540 53,240 9 Meatu 8,976 0 0 83 245 9,304 31,492 30 Shinyanga Urban 1,226 0 0 0 31 1,256 10,198 12 Kishapu 10,706 81 0 82 0 10,869 35,624 31 Total 67,690 1,966 302 273 814 71,044 377,857 18.8 % 95.3 2.8 0.4 0.4 1.1 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/ Agriculture Year, Shinyanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District District Spacing Use of Agrochemicals Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 245 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 4,742 358 0 5,099 77,572 7 Maswa 325 108 0 433 43,252 1 Shinyanga Rural 5,834 402 0 6,236 45,263 14 Kahama 17,032 328 142 17,502 81,217 22 Bukombe 1,666 0 358 2,025 53,240 4 Meatu 7,638 247 83 7,968 31,492 25 Shinyanga Urban 1,189 0 0 1,189 10,198 12 Kishapu 7,672 0 160 7,832 35,624 22 Total 46,097 1,443 743 48,284 377,857 13 % 95.5 3.0 1.5 100.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 10,512 0 348 169 0 11,029 77,572 14 Maswa 1,400 527 0 217 0 2,144 43,252 5 Shinyanga Rural 9,025 900 0 0 0 9,925 45,263 22 Kahama 20,525 0 140 0 142 20,807 81,217 26 Bukombe 4,399 119 0 0 119 4,638 53,240 9 Meatu 10,085 410 0 0 83 10,578 31,492 34 Shinyanga Urban 2,764 0 0 0 62 2,826 10,198 28 Kishapu 12,008 79 0 81 242 12,410 35,624 35 Total 70,719 2,035 488 467 649 74,358 377,857 20 % 95.1 2.7 0.7 0.6 0.9 100.0 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Erosion Control Organic Fertilizer Use Tanzania Agriculture Sample Census-2003 Tanga Appendix II 246 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 2,658 179 0 0 0 0 2,837 77,572 4 Maswa 216 325 0 0 0 0 541 43,252 1 Shinyanga Rural 3,128 701 0 0 0 201 4,030 45,263 9 Kahama 17,766 1,117 0 0 0 394 19,277 81,217 24 Bukombe 2,151 0 0 0 0 358 2,509 53,240 5 Meatu 4,355 165 0 0 0 0 4,519 31,492 14 Shinyanga Urban 539 0 0 0 32 0 571 10,198 6 Kishapu 3,751 237 80 160 0 162 4,390 35,624 12 Total 34,563 2,723 80 160 32 1,116 38,673 377,857 10 % 89.4 7.0 0.2 0.4 0.1 2.9 100.0 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 11,110 0 0 169 0 0 11,279 77,572 15 Maswa 1,291 528 0 0 0 0 1,819 43,252 4 Shinyanga Rural 6,822 1,003 0 102 0 202 8,129 45,263 18 Kahama 21,642 624 275 0 0 282 22,823 81,217 28 Bukombe 4,764 0 0 119 0 0 4,884 53,240 9 Meatu 11,409 416 0 0 0 83 11,909 31,492 38 Shinyanga Urban 2,284 0 0 0 63 31 2,377 10,198 23 Kishapu 12,891 238 0 0 0 644 13,773 35,624 39 Total 72,213 2,809 275 390 63 1,242 76,993 377,857 20 % 93.8 3.6 0.4 0.5 0.1 1.6 100 District 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 247 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Bariadi 2,259 0 179 0 0 2,438 77,572 3 Maswa 324 0 0 0 0 324 43,252 1 Shinyanga Rural 2,730 102 0 0 202 3,035 45,263 7 Kahama 1,407 98 0 0 282 1,787 81,217 2 Bukombe 597 119 0 119 239 1,075 53,240 2 Meatu 3,766 0 0 0 165 3,931 31,492 12 Shinyanga Urban 693 0 0 0 30 723 10,198 7 Kishapu 2,137 0 0 0 238 2,376 35,624 7 Total 13,914 319 179 119 1,157 15,688 377,857 4 % 89 2 1 1 7 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 4,048 0 179 0 0 4,227 77,572 5 Maswa 216 0 0 0 0 216 43,252 1 Shinyanga Rural 4,236 303 0 0 100 4,639 45,263 10 Kahama 7,134 240 0 0 142 7,516 81,217 9 Bukombe 1,912 0 0 0 239 2,151 53,240 4 Meatu 3,686 0 0 0 83 3,770 31,492 12 Shinyanga Urban 1,250 0 0 32 0 1,282 10,198 13 Kishapu 4,329 0 0 0 229 4,559 35,624 13 Total 26,812 543 179 32 794 28,359 377,857 8 % 95 2 1 0 3 100 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Shinyanga Region District Irrigation Technology District Mechanisation / LST 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 248 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 10,470 178 0 348 0 0 10,996 77,572 14 Maswa 1,508 203 0 0 0 0 1,711 43,252 4 Shinyanga Rural 7,525 603 0 99 0 0 8,228 45,263 18 Kahama 21,309 647 275 0 0 0 22,230 81,217 27 Bukombe 2,748 0 0 0 0 119 2,868 53,240 5 Meatu 10,553 307 0 83 0 371 11,313 31,492 36 Shinyanga Urban 2,122 27 0 15 64 0 2,229 10,198 22 Kishapu 8,847 0 0 0 0 240 9,087 35,624 26 Total 65,082 1,965 275 545 64 730 68,660 377,857 18 % 94.8 2.9 0.4 0.8 0.1 1.1 100.0 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Bariadi 3,512 179 169 0 0 0 3,860 77,572 5 Maswa 210 0 0 108 0 0 318 43,252 1 Shinyanga Rural 5,538 201 0 0 0 0 5,739 45,263 13 Kahama 10,730 240 142 0 0 250 11,362 81,217 14 Bukombe 836 0 0 0 0 358 1,195 53,240 2 Meatu 5,530 0 0 0 0 407 5,937 31,492 19 Shinyanga Urban 1,280 0 0 0 32 0 1,312 10,198 13 Kishapu 5,426 0 0 0 0 226 5,652 35,624 16 Total 33,062 620 311 108 32 1,242 35,375 377,857 9 % 93.5 1.8 0.9 0.3 0.1 3.5 100 District 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Shinyanga Region. District 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Crop Storage Vermin Control Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 249 Government NGO / Development Project Large Scale Farm Not applicable Total Total Bariadi 5,513 356 174 179 6,222 6,222 77,572 8 Maswa 325 0 0 0 325 325 43,252 1 Shinyanga Rural 5,230 898 99 0 6,228 6,228 45,263 14 Kahama 11,217 0 0 569 11,786 11,786 81,217 15 Bukombe 1,075 0 0 358 1,434 1,434 53,240 3 Meatu 4,982 0 78 409 5,469 5,469 31,492 17 Shinyanga Urban 1,296 0 0 32 1,327 1,327 10,198 13 Kishapu 10,848 0 81 145 11,074 11,074 35,624 31 Total 40,484 1,255 433 1,692 43,864 43,864 377,857 11.6 % 92.3 2.9 1.0 3.9 100.0 100.0 Government NGO / Development Project Cooperative Not applicable Total Total Number of households % of total number of households Bariadi 1,043 0 0 0 1,043 77,572 1 Maswa 649 203 108 0 960 43,252 2 Shinyanga Rural 4,637 201 0 0 4,838 45,263 11 Kahama 12,406 98 0 283 12,787 81,217 16 Bukombe 956 0 0 239 1,195 53,240 2 Meatu 4,779 83 0 0 4,862 31,492 15 Shinyanga Urban 747 0 0 0 747 10,198 7 Kishapu 3,755 0 80 145 3,980 35,624 11 Total 28,972 584 188 668 30,412 377,857 8.0 % 95.3 1.9 0.6 2.2 100 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source an District During the 2002/03 Agriculture Year, Shinyanga Regio District District Agro-progressing Total Number of households % of total number of households Agro-forestry 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 250 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Bariadi 532 0 0 532 77,572 1 Maswa 324 0 0 324 43,252 1 Shinyanga Rural 2,022 99 102 2,223 45,263 5 Kahama 426 110 276 812 81,217 1 Bukombe 0 0 358 358 53,240 1 Meatu 219 0 333 552 31,492 2 Shinyanga Urban 152 0 0 152 10,198 1 Kishapu 242 0 0 242 35,624 1 Total 3,917 210 1,070 5,196 377,857 1 % 75 4 21 100 Government NGO / Development Project Cooperative Not applicable Total Total Total Number of households % of total number of households Bariadi 179 0 0 0 179 179 77,572 0 Maswa 649 0 108 0 757 757 43,252 2 Shinyanga Rural 605 0 0 0 605 605 45,263 1 Kahama 280 0 0 276 556 556 81,217 1 Bukombe 0 0 0 358 358 358 53,240 1 Meatu 83 0 0 333 416 416 31,492 1 Shinyanga Urban 32 30 0 0 62 62 10,198 1 Kishapu 487 0 0 0 487 487 35,624 1 Total 2,313 30 108 968 3,419 3,419 377,857 0.9 % 67.6 0.9 3.2 28.3 100.0 100.0 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District Durin the 2002/03 Agriculture Year, Shinyanga Region District District 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Shinyanga Region Beekeeping Fish Farming Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 251 Received Adopted % Received Adopted % Received Adopted % Bariadi 15,748 13,816 88 12,830 9,117 71 4,925 2,638 54 Maswa 2,252 2,144 95 1,928 1,711 89 433 433 100 Shinyanga Rural 10,406 9,393 90 5,145 1,110 22 6,034 4,120 68 Kahama 26,717 23,855 89 24,528 18,669 76 17,510 12,586 72 Bukombe 6,311 4,882 77 4,062 2,628 65 1,666 1,308 78 Meatu 14,434 10,454 72 8,391 4,265 51 7,395 1,790 24 Shinyanga Urban 3,032 1,957 65 1,168 612 52 1,161 612 53 Kishapu 17,482 14,828 10,869 3,551 7,832 1,720 455 Total 96,382 81,330 84 68,920 41,663 60 46,957 25,207 54 Received Adopted % Received Adopted % Received Adopted % Bariadi 11,029 6,113 55 2,837 1,210 43 11,632 7,659 66 Maswa 2,144 1,718 80 649 216 33 1,711 1,710 100 Shinyanga Rural 10,026 8,010 80 3,422 1,414 41 8,229 3,715 45 Kahama 20,951 17,292 83 18,995 12,215 64 22,686 16,101 71 Bukombe 4,280 2,026 47 2,031 955 47 4,884 2,146 44 Meatu 10,578 3,678 35 4,031 1,659 41 11,993 7,160 60 Shinyanga Urban 2,917 1,924 66 556 239 43 2,377 984 41 Kishapu 12,407 4,861 4,228 478 13,936 8,834 Total 74,332 45,621 61 36,748 18,387 50 77,447 48,310 62 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Shinyanga Region District Spacing Use of Agrochemicals Erosion Control 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Shinyanga Region District Organic Fertilizer Use Inorganic Fertilizer Use of Improved Seed Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 252 Received Adopted % Received Adopted % Received Adopted % Bariadi 2,438 1,896 78 3,359 1,925 57 11,353 9,930 87 Maswa 324 216 67 216 108 50 1,711 1,602 94 Shinyanga Rural 2,734 708 26 4,334 1,109 26 8,225 7,414 90 Kahama 945 562 60 7,099 5,299 75 22,502 19,834 88 Bukombe 478 1,433 300 1,195 717 60 2,748 2,390 87 Meatu 3,018 2,062 68 2,609 1,569 60 11,020 9,745 88 Shinyanga Urban 665 107 16 1,289 388 30 2,288 1,722 75 Kishapu 2,216 149 4,071 872 9,249 5,478 Total 12,818 7,133 56 24,173 11,987 50 69,096 58,115 84 Received Adopted % Received Adopted % Received Adopted % Bariadi 3,155 2,973 94 5,690 5,154 91 1,049 882 84 Maswa 318 318 100 216 325 150 960 311 32 Shinyanga Rural 5,433 4,840 89 5,919 5,430 92 4,838 3,837 79 Kahama 11,221 9,520 85 10,938 10,529 96 12,508 7,771 62 Bukombe 478 956 200 717 1,075 150 597 478 80 Meatu 5,032 5,609 111 4,313 5,388 125 4,779 2,136 45 Shinyanga Urban 1,344 707 53 1,264 891 70 689 401 58 Kishapu 5,162 3,811 10,911 9,643 3,898 481 Total 32,144 28,734 89 39,969 38,435 96 29,320 16,297 56 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Shinyanga Region Crop Storage Irrigation Technology Mechanisation / LST District 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Shinyanga Region District Vermin Control Agro-progressing Agro-forestry Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 253 Received Adopted % Received Adopted % Received Adopted % Bariadi 1,049 882 84 175 175 100 0 0 0 Maswa 960 311 32 324 108 33 865 649 75 Shinyanga Rural 4,838 3,837 79 2,121 503 24 605 0 0 Kahama 12,508 7,771 62 395 393 100 143 143 0 Bukombe 597 478 80 0 0 0 0 0 0 Meatu 4,779 2,136 45 498 331 67 416 250 60 Shinyanga Urban 689 401 58 152 57 38 32 0 0 Kishapu 3,898 481 80 0 162 0 Total 29,320 16,297 56 3,744 1,567 42 2,223 1,220 55 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Shinyanga Region District Fish Farming Beekeeping Agro-forestry Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 254 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 255 Number % Number % Number % Bariadi 67,493 87 10,079 13 77,572 100 Maswa 34,293 79 8,959 21 43,252 100 Shinyanga Rural 39,760 88 5,503 12 45,263 100 Kahama 32,470 40 48,747 60 81,217 100 Bukombe 8,972 17 44,268 83 53,240 100 Meatu 24,684 78 6,808 22 31,492 100 Shinyanga Urban 6,894 68 3,305 32 10,198 100 Kishapu 31,630 89 3,994 11 35,624 100 Total 246,196 65 131,662 35 377,857 100 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Bariadi 164,800 325,542 152,258 11,115 8,374 3,985 15,399 10,160 1,405 . . . 191,314 344,077 157,648 Maswa 75,299 158,286 93,455 7,107 4,115 583 39,566 108 0 650 434 0 122,622 162,943 94,038 Shinyanga Rural 99,637 185,114 77,317 13,397 18,527 2,595 14,472 102 21 3,021 1,429 103 130,527 205,171 80,035 Kahama 85,893 131,266 64,232 15,017 18,681 5,136 26,283 4,732 0 2,025 1,450 0 129,219 156,129 69,368 Bukombe 33,230 40,729 33,883 7,126 4,020 2,419 12,166 0 0 0 0 0 52,522 44,749 36,302 Meatu 71,161 115,925 75,234 10,281 18,485 2,094 25,492 2,476 0 1,269 652 66 108,202 137,537 77,393 Shinyanga Urban 16,821 29,891 11,992 2,819 2,523 260 2,249 161 26 350 253 0 22,239 32,829 12,277 Kishapu 73,463 151,641 101,734 4,672 9,069 1,305 1,801 1,128 0 712 2,614 444 80,649 164,453 103,484 Total 620,304 1,138,393 610,105 71,535 83,794 18,377 137,428 18,868 1,451 8,027 6,832 613 837,294 1,247,888 630,546 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total 17 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District Use of Draft animals to cultivate land during 2002/03 agricultural Year Households Using Draft Animals Household Not Using Draft Animals Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 256 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Bariadi 164,800 325,542 376,077.6 11,115 8,374 9,842.6 15,399 10,160 3,469.4 . . . 191,314 344,077 389,389.6 Maswa 75,299 158,286 230,833.7 7,107 4,115 1,440.8 39,566 108 0.0 650 434 0.0 122,622 162,943 232,274.5 Shinyanga Rural 99,637 185,114 190,972.7 13,397 18,527 6,408.6 14,472 102 51.0 3,021 1,429 255.1 130,527 205,171 197,687.4 Kahama 85,893 131,266 158,652.4 15,017 18,681 12,685.9 26,283 4,732 0.0 2,025 1,450 0.0 129,219 156,129 171,338.3 Bukombe 33,230 40,729 83,691.4 7,126 4,020 5,974.2 12,166 0 0.0 0 0 0.0 52,522 44,749 89,665.7 Meatu 71,161 115,925 185,827.1 10,281 18,485 5,171.7 25,492 2,476 0.0 1,269 652 163.0 108,202 137,537 191,161.8 Shinyanga Urban 16,821 29,891 29,619.8 2,819 2,523 642.4 2,249 161 63.2 350 253 0.0 22,239 32,829 30,325.4 Kishapu 73,463 151,641 251,283.9 4,672 9,069 3,224.6 1,801 1,128 0.0 712 2,614 1,096.4 80,649 164,453 255,604.9 Total 620,304 1,138,393 1,506,958.6 71,535 83,794 45,390.8 137,428 18,868 3,583.6 8,027 6,832 1,514.5 837,294 1,247,888 1,557,447.6 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 257 Number % Number % Number % Bariadi 11,364 13.6 64,964 22.3 76,328 20.3 Maswa 7,883 9.4 35,369 12.1 43,252 11.5 Shinyanga Rural 14,532 17.3 30,221 10.4 44,753 11.9 Kahama 25,893 30.9 55,180 18.9 81,073 21.6 Bukombe 11,409 13.6 41,599 14.3 53,008 14.1 Meatu 3,941 4.7 27,089 9.3 31,030 8.3 Shinyanga Urban 3,527 4.2 6,672 2.3 10,198 2.7 Kishapu 5,295 6.3 30,329 10.4 35,624 9.5 Total 83,843 100.0 291,423 100.0 375,266 100.0 Area (Ha) % Area (Ha) % Area (Ha) % Bariadi 11,100 13.5 585 10.2 11,685 13.3 Maswa 10,298 12.5 263 4.6 10,561 12.0 Shinyanga Rural 14,035 17.1 421 7.4 14,456 16.4 Kahama 21,123 25.7 2,875 50.4 23,998 27.3 Bukombe 10,693 13.0 1,301 22.8 11,994 13.6 Meatu 6,643 8.1 7 0.1 6,650 7.6 Shinyanga Urban 3,217 3.9 41 0.7 3,257 3.7 Kishapu 5,134 6.2 214 3.7 5,348 6.1 Total 82,243 100.0 5,707 100.0 87,950 100.0 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Region During 2002/03 Agriculture Year District Organic fertilizer Application during 2002/03 Agriculture Year Households using Organic Fertilizer Households not Using Organic Fertilizer Total 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 258 CATTLE PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 259 Number % Number % Bariadi 34,951 45 42,621 55 77,572 38,084 Maswa 16,643 38 26,609 62 43,252 20,478 Shinyanga Rural 21,141 47 24,122 53 45,263 24,081 Kahama 27,522 34 53,695 66 81,217 32,009 Bukombe 13,120 25 40,120 75 53,240 18,695 Meatu 14,120 45 17,372 55 31,492 17,672 Shinyanga Urban 4,454 44 5,744 56 10,198 6,009 Kishapu 16,264 46 19,359 54 35,624 19,515 Total 148,216 39 229,641 61 377,857 176,542 Number % Number % 1-5 33,399 23 114,330 4 3 6-10 39,489 27 314,678 12 8 11-15 25,933 17 332,706 13 13 16-20 16,263 11 290,695 11 18 21-30 13,966 9 354,786 14 25 31-40 6,737 5 240,901 9 36 41-50 3,927 3 180,556 7 46 51-60 2,964 2 165,182 6 56 61-100 4,320 3 338,570 13 78 101-150 608 0 71,580 3 118 151+ 610 0 200,121 8 328 Total 148216 100 2,604,105 100 7 Number % Number % Number % Number % Regions Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total % Bulls 290,168 92.2 126 0.6 27 7.2 290,322 7.4 Cows 765,236 92.6 712 0.0 8,124 7.4 774,072 40.6 Steers 553,724 92.6 179 0.9 1,389 6.5 555,292 3.5 Heifers 406,859 93.5 . 0.0 618 6.5 407,477 22.9 Male Calves 215,035 91.8 358 0.0 403 8.2 215,796 12.5 Female Calves 360,510 91.8 . 0.0 636 8.2 361,146 13.1 Total 2,591,532 92.6 1,375 0.1 11,198 7.4 2,604,105 100.0 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year,Shinyanga Region Households Rearing Cattle Households Not Rearing Cattle 18.2: Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 District Total Agriculture households Total livestock keeping households Total Improved Beef Cattle Herd Size Cattle Rearing Households Heads of Cattle Average Number Per Household Table 18.3: Total Number of Cattle by Category and Type of Cattle; on 1st October 2003 Improved Dairy Cattle Category of cattle Indigenous Cattle Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 260 Meatu 34,772 540,920 99.3 179 537 0.0 715 3,039 0.6 35,666 544,496 20.9 Maswa 16,643 311,082 0 0.0 108 1,192 16,752 312,274 12.0 Bariadi 21,141 317,388 0 99 398 21,241 317,785 12.2 Shinyanga Rural 27,522 406,317 99.1 142 712 0.0 917 2,962 0.7 28,581 409,991 15.7 Shinyanga Urban 13,120 332,685 0 0.0 0 0.0 13,120 332,685 12.8 Kahama 14,120 332,464 0 326 1,635 14,446 334,099 12.8 Bukombe 4,201 58,903 98.5 32 126 0.0 337 759 1.3 4,570 59,788 2.3 Kishapu 16,264 291,773 0 162 1,214 16,426 292,987 11.3 Total 147,784 2,591,532 99.5 353 1,375 0.0 2,664 11,198 2 150,801 2,604,105 67 Number of Cattle Number of households Indigenous 18.4 CATTLE PRODUCTION: Total Number of Cattle by Type and District As of 1st October 2003 District % % % Number of Cattle Number of households Beef Total Cattle Dairy % Number of households Number of Cattle Number of Cattle Number of households Tanzania Agriculture Sample Census-2003 Shinyanga Appendix II 261 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi 63,559 159,166 143,830 85,604 45,127 43,634 540,920 Maswa 23,994 92,999 70,596 58,897 29,975 34,622 311,082 Shinyanga Rural 46,253 91,477 70,127 50,351 25,775 33,404 317,388 Kahama 45,137 126,373 88,913 65,366 35,447 45,080 406,317 Bukombe 29,617 69,637 30,449 46,004 18,505 138,473 332,685 Meatu 42,782 113,944 70,502 47,055 27,498 30,683 332,464 Shinyanga Urban 8,377 18,090 13,693 8,399 5,555 4,789 58,903 Kishapu 30,448 93,551 65,613 45,183 27,153 29,825 291,773 Total 290,168 765,236 553,724 406,859 215,035 360,510 2,591,532 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi . 1,430 536 537 179 358 3,039 Maswa . 1,192 . . . . 1,192 Shinyanga Rural . 398 . . . . 398 Kahama . 2,789 173 . . . 2,962 Bukombe . . . . . . . Meatu . 816 656 . . 162 1,635 Shinyanga Urban 27 286 23 81 225 116 759 Kishapu . 1,214 . . . . 1,214 Total 27 8,124 1,389 618 403 636 11,198 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi . . 179 . 358 . 537 Maswa . . . . . . . Shinyanga Rural . . . . . . . Kahama . 712 . . . . 712 Bukombe . . . . . . . Meatu . . . . . . . Shinyanga Urban 126 . . . . . 126 Kishapu . . . . . . . Total 126 712 179 0 358 0 1,375 Bulls Cows Steers Heifers Male Calves Female Calves Total Bariadi 63,559 160,596 144,545 86,141 45,663 43,992 544,496 Maswa 23,994 94,191 70,596 58,897 29,975 34,622 312,274 Shinyanga Rural 46,253 91,874 70,127 50,351 25,775 33,404 317,785 Kahama 45,137 129,874 89,086 65,366 35,447 45,080 409,991 Bukombe 29,617 69,637 30,449 46,004 18,505 138,473 332,685 Meatu 42,782 114,760 71,159 47,055 27,498 30,845 334,099 Shinyanga Urban 8,531 18,376 13,716 8,480 5,780 4,905 59,788 Kishapu 30,448 94,765 65,613 45,183 27,153 29,825 292,987 Total 290,322 774,072 555,292 407,477 215,796 361,146 2,604,105 18.5: Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003 District Category - Indigenous 18.7: Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003 18.6: Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 District Number of Improved Dairy Cattle District Total Cattle District Number of Improved Beef 18.8: Total Number of Cattle by Category and District as on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 262 GOATS PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 263 Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats Bariadi 23,501 227,934 99 355 888 0 341 995 0.4 24,197 229,817 Maswa 14,269 207,202 99 215 2,157 1 0 0.0 14,484 209,359 Shinyanga Rural 15,628 154,135 100 0 0 99 199 0.1 15,727 154,334 Kahama 19,988 138,822 99 261 2,024 0 0 0.0 20,249 140,846 Bukombe 17,030 106,688 100 119 238 0 0 0.0 17,149 106,926 Meatu 13,099 214,466 99 245 984 0 137 220 0.1 13,480 215,670 Shinyanga Urban 3,654 31,171 99 81 201 1 62 62 0.2 3,797 31,434 Kishapu 14,936 189,543 100 0 0 0 0.0 14,936 189,543 Total 122,104 1,269,960 99 1,276 6,493 1 640 1,476 0.1 124,019 1,277,929 Number % Number % 1-4 34,804 28.5 98,352 7.7 2.8 5-9 41,317 33.8 270,967 21.2 6.6 10-14 19,156 15.7 216,643 17.0 11.3 15-19 9,619 7.9 158,851 12.4 16.5 20-24 9,161 7.5 192,083 15.0 21.0 25-29 2,000 1.6 51,810 4.1 25.9 30-39 3,308 2.7 105,529 8.3 31.9 40+ 2,914 2.4 183,695 14.4 63.0 Total 122,280 100.0 1,277,929.2 100.0 10.5 Total 19.1 GOAT PRODUCTION: Total Number of Goats by goat type and District as on 1st October 2003 District Indigenous Improved Dairy Improved for Meat Herd Size Goat Rearing Households Head of Goats Average per Household 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 264 Number % Number % Number % Number % Billy Goats 220,420 17 1,049 16 0 221,468 17 She Goats 63,142 5.0 1,545 23.8 115 7.8 64,802 5.1 Castrated Goat 678,195 53.4 2,552 39.3 312 21.1 681,058 53.3 Male Kid 152,433 12.0 308 4.7 177 12.0 152,919 12.0 She Kid 155,771 12.3 1,039 16.0 872 59.1 157,682 12.3 Total 1,269,960 100.0 6,493 100.0 1,476 100.0 1,277,929 100.0 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi 37,541 12,283 121,439 28,963 27,708 227,934 Maswa 31,554 10,467 108,817 26,450 29,914 207,202 Shinyanga Rural 27,369 3,714 84,206 18,521 20,324 154,135 Kahama 26,454 4,248 75,718 15,912 16,489 138,822 Bukombe 21,830 822 66,179 8,688 9,169 106,688 Meatu 41,576 18,921 103,426 25,918 24,625 214,466 Shinyanga Urban 6,403 1,815 16,494 3,171 3,288 31,171 Kishapu 27,693 10,872 101,915 24,810 24,254 189,543 Total 220,420 63,142 678,195 152,433 155,771 1,269,960 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi . . 357 . 531 888 Maswa 965 108 1,084 . . 2,157 Shinyanga Rural . . . . . . Kahama . 1,437 353 . 235 2,024 Bukombe . . 119 119 . 238 Meatu 83 . 485 166 250 984 Shinyanga Urban . . 155 23 23 201 Kishapu . . . . . . Total 1,049 1,545 2,552 308 1,039 6,493 District Type 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 Category of Goats Indigenous Goats Improved Meat Goats Improved Dairy Goats Total 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 District Number of Improved Meat Goats Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 265 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi . . . 177 817 995 Maswa . . . . . . Shinyanga Rural . . 199 . . 199 Kahama . . . . . . Bukombe . . . . . . Meatu . 83 83 . 54 220 Shinyanga Urban . 32 30 . . 62 Kishapu . . . . . . Total . 115 312 177 872 1,476 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Bariadi 37,541 12,283 121,796 29,140 29,057 229,817 Maswa 32,519 10,575 109,901 26,450 29,914 209,359 Shinyanga Rural 27,369 3,714 84,405 18,521 20,324 154,334 Kahama 26,454 5,685 76,071 15,912 16,725 140,846 Bukombe 21,830 822 66,298 8,807 9,169 106,926 Meatu 41,659 19,004 103,994 26,084 24,929 215,670 Shinyanga Urban 6,403 1,847 16,678 3,194 3,311 31,434 Kishapu 27,693 10,872 101,915 24,810 24,254 189,543 Total 221,468 64,802 681,058 152,919 157,682 1,277,929 19.7 Total Number of Goats by Category and District on 1st October 2003 District Total Goats 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 District Number of Improved Dairy Goats Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 266 SHEEP PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 267 Number % Number % Number % Ram 90,767 18 108 100 90,875 18 Castrated Sheep 34,925 7 0 34,925 7 She Sheep 285,032 55 0 285,032 55 Male Lamb 57,431 11 0 57,431 11 She Lamb 48,880 9 0 48,880 9 Total 517,036 100 108 100 517,144 100 Number % Number % Bariadi 10,251 13 67,321 87 77,572 38,084 Maswa 9,212 21 34,040 79 43,252 20,478 Shinyanga Rural 8,072 18 37,191 82 45,263 24,081 Kahama 6,923 9 74,294 91 81,217 32,009 Bukombe 2,482 5 50,758 95 53,240 18,695 Meatu 9,429 30 22,063 70 31,492 17,672 Shinyanga Urban 2,010 20 8,188 80 10,198 6,009 Kishapu 10,166 29 25,458 71 35,624 19,515 Total 58,545 15 319,312 85 377,857 176,542 Number % Number % Number % Bariadi 78,539 15 . 78,539 15 Maswa 106,861 21 108 100 106,969 21 Shinyanga Rural 53,163 10 . 53,163 10 Kahama 30,133 6 . 30,133 6 Bukombe 8,745 2 . 8,745 2 Meatu 95,895 19 . 95,895 19 Shinyanga Urban 12,403 2 . 12,403 2 Kishapu 131,296 25 . 131,296 25 Total 517,036 100 108 100 517,144 100 Number of Households Average Sheep Number of Households Average Sheep Bariadi 24,371 2 1,157 3 24,660 3 Maswa 5,569 4 188 55 5,569 6 Shinyanga Rural 3,027 8 81 1 3,027 8 Kahama 87 11 23 1 109 9 Bukombe 61 3 0 0 61 3 Meatu 640 31 0 0 640 31 Shinyanga Urban 1,314 14 97 3 1,314 14 Kishapu Total 35,068 4 1,547 10 35,381 5 Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003. Breed Number of Indigenous Sheep Number of Improved Mutton Sheep Total Sheep Total Households Raising Sheep Average number of Sheep per household Number of Improved for Mutton Sheep Total Sheep District Number of Indigenous Sheep Indigenous Sheep Improved for Mutton Sheep 20.1 Total Number of Sheep by Breed Type on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 268 Herd Size Number of Households % Number of Sheep % Average Number per Household 1-4 24,068 41 61,760 12 3 5-9 19,302 33 124,766 24 6 10-14 7,749 13 86,035 17 11 15-19 2,834 5 45,230 9 16 20-24 1,185 2 25,694 5 22 25-29 788 1 21,277 4 27 30-39 872 2 28,827 6 33 40+ 1,222 2 123,556 24 101 Total 58,021 100 517,144 100 9 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi 21,540 10,009 35,099 5,314 6,577 78,539 Maswa 15,115 7,369 49,691 23,289 11,396 106,861 Shinyanga Rural 10,997 4,574 24,802 6,953 5,837 53,163 Kahama 4,535 570 18,169 3,425 3,434 30,133 Bukombe 1,653 . 6,263 716 112 8,745 Meatu 22,200 9,071 43,529 9,635 11,462 95,895 Shinyanga Urban 2,230 534 7,815 1,003 821 12,403 Kishapu 12,497 2,799 99,663 7,097 9,241 131,296 Total 90,767 34,925 285,032 57,431 48,880 517,036 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi . . . . . 0 Maswa 108 . . . . 108 Shinyanga Rural . . . . . 0 Kahama . . . . . 0 Bukombe . . . . . . Meatu . . . . . . Shinyanga Urban . . . . . 0 Kishapu . . . . . Total 108 . . . . 108 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Bariadi 21,540 10,009 35,099 5,314 6,577 78,539 Maswa 15,223 7,369 49,691 23,289 11,396 106,969 Shinyanga Rural 10,997 4,574 24,802 6,953 5,837 53,163 Kahama 4,535 570 18,169 3,425 3,434 30,133 Bukombe 1,653 . 6,263 716 112 8,745 Meatu 22,200 9,071 43,529 9,635 11,462 95,895 Shinyanga Urban 2,230 534 7,815 1,003 821 12,403 Kishapu 12,497 2,799 99,663 7,097 9,241 131,296 Total 90,875 34,925 285,032 57,431 48,880 517,144 20.8: Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 269 Appendix II 270 PIGS PRODUCTION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 271 Number % Number % Bariadi 99 0 77,473 100 77,572 Maswa 0 0 43,252 100 43,252 Shinyanga Rural 0 0 45,263 100 45,263 Kahama 110 0 81,107 100 81,217 Bukombe 0 0 53,240 100 53,240 Meatu 164 1 31,328 99 31,492 Shinyanga Urban 202 2 9,974 98 10,176 Kishapu 81 0 35,542 100 35,623 Total 656 0 377,179 100 377,835 Number % Number % 1-4 521 79 1,254 38 2 5-9 112 17 684 21 6 40+ 23 4 1,328 41 57 Total 656 100 3,266 100 5 District Number of Households Number of Pigs Average per Household Bariadi 99 292 3 Kahama 110 221 2 Meatu 164 736 4 Shinyanga Urban 202 1,931 10 Kishapu 81 86 1 Total 656 3,266 5 Boars Castrated Males Sow / Gilt Male Piglets She Piglets Total Bariadi 99 . 198 . . 296 Kahama 110 . 110 . . 221 Meatu 245 . 328 163 . 736 Shinyanga Urban 272 466 451 341 402 1,931 Kishapu 82 . . . . 82 Total 807 466 1,087 503 402 3,266 21.3 Number of Households and Pigs by District on 1st October 2003 20.1 Number of Households Raising or Managing Pigs by District on 1st October 2003 District Pig Type Herd Size 21.2 Number of Households and Pigs by Herd Size on 1st October 2003 21.3 Number of Pigs by Type of Pig and District on 1st October 2003 Heads of pigs Average per Household Pig Rearing Households District Households Raising Pigs Households Not Raising Pigs Number of Agriculture Households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 272 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 273 No of Households % No of Households % Bariadi 20,832 55 17,253 45 38,084 Maswa 6,335 31 13,926 69 20,261 Shinyanga Rural 9,635 45 11,812 55 21,447 Kahama 14,856 52 13,753 48 28,609 Bukombe 6,287 34 12,407 66 18,695 Meatu 7,736 47 8,781 53 16,517 Shinyanga Urban 1,941 33 3,943 67 5,884 Kishapu 4,734 26 13,565 74 18,299 Total 72,356 43 95,440 57 167,796 No of Households % No of Households % No of Households % No of Households % Bariadi 5,643 25 18,241 29 1,943 24 679 13 Maswa 2,459 11 4,733 8 944 12 968 18 Shinyanga Rural 2,103 9 8,336 13 501 6 1,619 30 Kahama 3,473 16 13,504 22 1,091 14 541 10 Bukombe 1,759 8 5,575 9 0 0 0 0 Meatu 4,239 19 6,080 10 2,391 30 1,038 19 Shinyanga Urban 592 3 1,635 3 263 3 102 2 Kishapu 1,886 9 4,055 7 844 11 409 8 Total 22,155 100 62,159 100 7,977 100 5,355 100 No of Households % No of Households % Bariadi 29,822 84 5,793 16 35,615 Maswa 12,964 64 7,297 36 20,262 Shinyanga Rural 14,079 71 5,774 29 19,853 Kahama 22,402 74 8,068 26 30,470 Bukombe 7,564 42 10,421 58 17,985 Meatu 10,954 71 4,516 29 15,470 Shinyanga Urban 2,770 46 3,239 54 6,009 Kishapu 11,744 61 7,526 39 19,269 Total 112,299 68 52,634 32 164,933 22.1 PESTS AND PARASITES: Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year 22.3 PESTS AND PARASITE: 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year Cattle Goats Sheep Pigs District Deworming Livestock Not deworming Livestock Total District Tick problems No Tick problems Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 274 District No of Households age No of Households % No of Households % No of Households % No of Households % Bariadi 3,363 11 25,214 85 179 1 - - 1,066 4 29,822 Maswa 3,172 24 8,061 62 - - 540 4 1,190 9 12,964 Shinyanga Rural 2,207 16 8,321 59 304 2 305 2 2,941 21 14,079 Kahama 1,548 7 19,307 86 - - 286 1 1,261 6 22,402 Bukombe 478 6 6,251 83 239 3 119 2 478 6 7,564 Meatu 1,067 10 8,206 75 710 6 162 1 809 7 10,954 Shinyanga Urban 812 29 1,467 53 243 9 - - 248 9 2,770 Kishapu 1,795 15 9,224 79 82 1 162 1 481 4 11,744 Total 14,444 13 86,052 77 1,756 2 1,575 1 8,473 8 112,299 No of Households % No of Households % Bariadi 5,327 14 32,237 86 37,564 Maswa 108 1 19,722 99 19,830 Shinyanga Rural 101 0 20,232 100 20,334 Kahama 783 3 28,943 97 29,726 Bukombe 951 5 17,624 95 18,575 Meatu 6,548 41 9,430 59 15,977 Shinyanga Urban 182 3 5,674 97 5,856 Kishapu 1,297 7 17,076 93 18,374 Total 15,296 9 150,939 91 166,235 No of Households age No of Households % No of Households % No of Households % Bariadi 1,780 33 2,671 50 536 10 341 6 5,327 Maswa 108 100 0 0 0 0 0 0 108 Shinyanga Rural 101 100 0 0 0 0 0 0 101 Kahama 429 55 354 45 0 0 0 0 783 Bukombe 239 25 712 75 0 0 0 0 951 Meatu 3,502 53 2,048 31 914 14 83 1 6,548 Shinyanga Urban 86 47 96 53 0 0 0 0 182 Kishapu 734 57 564 43 0 0 0 0 1,297 Total 6,318 41 6,444 42 1,449 9 424 3 15,296 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, District Tsetse flies problems No Tsetse flies problems Total 22.6 PESTS AND PARASITE: Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. District Method of Tsetse Flies Control Total None Spray Dipping Trapping Total Method of Tsetse Flies Control Other None Spray Dipping Smearing 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 275 Appendix II 276 OTHER LIVESTOCK Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 277 Type Number % Type Number Indigenous Chicken 2,935,380 99 Ducks 94,783 Layer 11,276 0 Turkeys 708 Broiler 32,934 1 Rabbits 5,263 Donkeys 4,421 Total 2,979,590 100 105,175 Indigenous Chicken Layer Broiler Total number of chicken Shinyanga Rural 528,510 684 22,160 551,354 Meatu 304,689 4,660 . 309,349 Maswa 405,467 102 . 405,569 Bariadi 858,896 3,124 10,775 872,794 Shinyanga Urban 383,126 . . 383,126 Bukombe 227,622 1,524 . 229,146 Kahama 40,741 149 . 40,890 Kishapu 186,328 1,033 . 187,361 Total 2,935,380 11,276 32,934 2,979,590 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 23b OTHER LIVESTOCK: Number of Chicken by Category of chicken and District as of 1st October 2003 District Number of Chicken Chicken Others Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 278 Number % 1 - 4 54,834 21 156,753 3 5 - 9 82,532 32 546,340 7 10 - 19 77,801 30 999,425 13 20 - 29 25,519 10 564,268 22 30 - 39 9,060 4 285,517 32 40 - 49 2,448 1 105,425 43 50 - 99 4,350 2 263,212 61 100+ 501 0 58,649 117 Total 257,044 100 2,979,590 12 Ducks Turkeys Rabbits Donkeys Other Bariadi 53,587 179 5,263 2,170 . Maswa 9,193 . . . 1,734 Shinyanga Rural 13,516 . . 612 1,487 Kahama 5,165 . . 981 1,715 Bukombe 4,063 . . . 3,734 Meatu 2,249 497 . . 2,637 Shinyanga Urban 1,851 32 . 415 . Kishapu 5,160 . . 244 632 Total 94,783 708 5,263 4,421 11,938 1995 1999 2003 Cattle 653,549 277,000 378,338 Improved Dairy 20,420 25,675 28,127 Goats 736,727 317,924 514,620 Sheep 246,263 85,679 164,209 Pigs 1,072 2,715 6,281 Indigenous Chicken 1,670,790 735,916 1,751,278 Layers - 6,136 29,630 Broilers 2,986 22,327 7,859 Total Chickens 1,673,776 764,379 1,788,767 23f LIVESTOCK/POULTRY POPULATION TREND: SHINYANGA REGION Flock size District 23e Head Number of Other Livestock by Type of Livestock and District Type of livestock 23d OTHER LIVESTOCK: Total Number of households and chickens raised by flock size as of 1st October 2005 Chicken rearing Households Number of Chicken Average chicken by households Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 279 Appendix II 280 LIVESTOCK PRODUCTS Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 281 Sold Consumed / Utilised Sold Consumed / Utilised Sold Consumed / Utilised Bariadi 1,066,554 280,940 20,844 1,779 15,613 2,313 Maswa 288,733 160,572 9,891 217 10,466 2,708 Shinyanga Rural 316,508 198,516 6,162 1,222 7,237 611 Kahama 387,363 142,591 3,781 1,972 1,664 431 Bukombe 358,497 481,881 1,553 0 836 0 Meatu 77,085 66,516 28,611 1,717 34,582 1,954 Shinyanga Urban 167,661 35,079 1,730 0 1,697 94 Kishapu 484,980 104,223 15,202 800 19,027 562 Total 3,147,381 1,470,318 87,774 7,707 91,123 8,672 25.1 LIVESTOCK PRODUCTS: Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year District Product Name Eggs Hides Skins Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 282 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 283 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 4,335 0 0 0 0 0 0 4,335 Maswa 3,636 2,037 0 0 0 217 0 5,889 Shinyanga Rural 3,834 3,046 917 0 0 99 0 7,896 Kahama 3,489 3,436 144 849 1,868 1,922 0 11,707 Bukombe 119 0 0 0 0 0 0 119 Meatu 1,985 2,130 183 869 248 2,295 652 8,362 Shinyanga Urban 1,563 320 220 123 0 0 0 2,226 Kishapu 3,511 2,641 974 574 315 1,044 0 9,059 Total 22,470 13,610 2,438 2,414 2,431 5,576 652 49,592 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Bariadi 2,463 179 0 0 0 0 2,642 Maswa 1,934 108 0 0 0 0 2,042 Shinyanga Rural 2,243 204 0 0 0 0 2,447 Kahama 2,830 431 0 144 0 0 3,405 Meatu 2,417 415 167 0 220 934 4,153 Shinyanga Urban 964 127 0 0 0 0 1,090 Kishapu 4,073 78 0 0 0 0 4,152 Total 16,924 1,542 167 144 220 934 19,931 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 27,327 714 179 0 0 176 0 28,395 Maswa 6,610 1,405 541 216 0 0 0 8,772 Shinyanga Rural 8,151 1,321 404 99 296 0 99 10,371 Kahama 11,480 1,949 0 133 133 135 0 13,830 Bukombe 3,331 0 118 0 0 0 0 3,449 Meatu 9,270 576 0 0 165 79 0 10,089 Shinyanga Urban 1,578 158 0 32 0 0 32 1,800 Kishapu 8,659 82 158 0 79 0 0 8,977 Total 76,405 6,205 1,400 480 673 390 130 85,683 27.1 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Dip and District District Distance to Nearest Cattle Dip 27.2 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Spray Raced and District District Distance to Nearest Spray Raced 27.3 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hand Powered Sprayer and District District Distance to Nearest Hand Powered Sprayer Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 284 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Bariadi 3,164 3,662 0 0 179 537 7,542 Maswa 4,175 650 217 0 0 0 5,042 Shinyanga Rural 2,838 815 0 1,429 102 0 5,183 Kahama 4,098 120 0 287 0 0 4,505 Bukombe 597 118 0 0 0 0 715 Meatu 4,053 2,183 652 634 0 164 7,687 Shinyanga Urban 1,090 32 0 0 0 0 1,121 Kishapu 4,313 161 324 328 394 1,268 6,789 Total 24,328 7,740 1,193 2,678 675 1,969 38,584 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 4,134 6,261 878 2,315 3,307 5,613 163 22,672 Maswa 3,474 3,628 2,149 1,608 758 217 0 11,834 Shinyanga Rural 3,156 8,884 4,253 2,134 2,112 299 0 20,837 Kahama 4,432 8,367 1,950 5,877 3,732 1,219 137 25,714 Bukombe 2,258 2,714 2,020 358 1,785 464 0 9,600 Meatu 3,341 2,321 711 1,200 411 1,615 162 9,760 Shinyanga Urban 807 1,048 222 30 32 0 0 2,139 Kishapu 3,493 1,042 1,139 894 1,372 1,363 1,007 10,311 Total 25,096 34,266 13,322 14,416 13,509 10,789 1,469 112,868 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 2,730 1,205 2,299 708 7,064 11,347 1,609 26,962 Maswa 1,388 1,506 1,516 750 1,015 2,899 101 9,176 Shinyanga Rural 3,053 2,615 1,925 915 1,016 2,390 204 12,119 Kahama 1,387 1,272 992 1,577 2,845 2,573 1,777 12,423 Bukombe 948 836 836 119 239 119 119 3,218 Meatu 3,723 566 695 83 736 656 582 7,041 Shinyanga Urban 1,063 321 31 32 64 0 0 1,510 Kishapu 2,850 1,184 374 804 2,578 2,899 2,902 13,592 Total 17,142 9,505 8,670 4,989 15,557 22,883 7,295 86,041 27.4 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Crush and District District Distance to Nearest Cattle Crush 27.5 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Primary Market and District District Distance to Nearest Primary Market 27.6 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Secondary Market and District District Distance to Nearest Secondary Market Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 285 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 1,697 198 1,768 1,598 6,840 12,810 1,965 26,876 Maswa 1,280 2,055 1,516 750 912 1,816 860 9,190 Shinyanga Rural 2,545 102 99 816 204 1,829 3,309 8,903 Kahama 1,972 572 1,417 1,435 1,842 2,860 3,468 13,567 Bukombe 358 0 0 0 119 343 239 1,060 Meatu 2,945 0 0 0 250 2,288 304 5,787 Shinyanga Urban 1,241 390 475 186 32 0 0 2,324 Kishapu 4,242 788 372 231 407 2,654 797 9,491 Total 16,282 4,105 5,648 5,016 10,606 24,600 10,941 77,199 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 3,522 5,062 526 713 3,031 1,413 0 14,267 Maswa 5,487 1,915 1,734 430 862 1,407 108 11,942 Shinyanga Rural 2,582 7,287 4,144 99 1,187 99 0 15,398 Kahama 6,729 5,330 1,285 3,144 1,722 285 0 18,494 Bukombe 2,856 1,054 946 478 119 119 119 5,692 Meatu 2,805 1,125 498 162 1,027 4,113 539 10,268 Shinyanga Urban 1,669 489 194 0 0 0 0 2,352 Kishapu 5,268 1,664 483 888 570 565 315 9,754 Total 30,917 23,926 9,808 5,913 8,519 8,002 1,082 88,167 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 3,003 3,569 1,042 1,069 4,980 9,539 1,786 24,988 Maswa 1,403 2,704 2,167 750 921 3,020 528 11,491 Shinyanga Rural 3,815 4,330 4,139 0 1,196 1,724 0 15,204 Kahama 2,965 144 702 0 1,287 1,019 718 6,835 Bukombe 1,061 0 0 0 0 0 0 1,061 Meatu 1,029 1,338 348 162 1,435 4,910 766 9,988 Shinyanga Urban 1,263 303 285 0 0 0 0 1,851 Kishapu 4,385 710 236 492 164 816 632 7,434 Total 18,923 13,098 8,919 2,472 9,983 21,028 4,430 78,853 27.7 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Abattoir and District District Distance to Nearest Abattoir 27.8 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Slaughter Slab and District District Distance to Nearest Slaughter Slab 27.9 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hide/ Skin Shade and District District Distance to Nearest Hide/ Skin Shade Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 286 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 5,908 6,665 2,262 3,394 9,878 13,511 1,959 43,578 Maswa 1,726 2,811 3,029 430 930 2,695 101 11,722 Shinyanga Rural 3,232 3,135 3,049 408 1,212 1,809 1,590 14,436 Kahama 5,795 4,495 1,290 1,999 2,770 3,004 6,582 25,935 Bukombe 712 1,287 2,019 1,074 3,463 717 0 9,271 Meatu 1,716 655 416 0 1,036 4,164 1,433 9,420 Shinyanga Urban 1,072 710 474 284 97 0 0 2,637 Kishapu 4,793 1,276 967 1,625 408 1,770 1,035 11,873 Total 24,953 21,033 13,506 9,214 19,792 27,671 12,702 128,872 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 2,461 1,071 876 5,131 8,949 11,319 3,398 33,204 Maswa 742 3,127 2,807 433 643 3,786 434 11,971 Shinyanga Rural 2,637 502 1,918 918 605 3,120 3,412 13,112 Kahama 3,510 668 421 0 3,871 3,836 4,099 16,405 Bukombe 836 113 836 119 835 0 956 3,696 Meatu 923 404 83 0 553 4,026 1,735 7,725 Shinyanga Urban 824 392 253 0 0 0 0 1,470 Kishapu 2,863 391 480 0 327 3,056 1,951 9,067 Total 14,797 6,668 7,674 6,601 15,783 29,143 15,984 96,651 <5 5 - 9 15 - 19 30 - 49 50+ Total Bariadi 3,175 0 0 0 535 3,709 Maswa 2,158 324 0 0 0 2,482 Shinyanga Rural 2,602 0 0 0 0 2,602 Kahama 3,782 0 0 0 143 3,925 Bukombe 119 0 0 0 0 119 Meatu 1,742 0 0 1,200 0 2,942 Shinyanga Urban 963 22 32 0 0 1,017 Kishapu 4,880 0 0 952 0 5,832 Total 19,421 346 32 2,153 678 22,630 27.10 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Input Supply and District District Distance to Nearest Input Supply 27.11 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Veterinary Clinic and District District Distance to Nearest Veterinary Clinic 27.12 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Holding Gound and District District Distance to Nearest Village Holding Gound Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 287 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 18,056 5,605 175 178 0 0 0 24,014 Maswa 5,146 325 0 108 0 0 0 5,580 Shinyanga Rural 16,176 1,731 0 0 0 0 0 17,907 Kahama 27,349 1,610 131 0 144 137 0 29,371 Bukombe 4,171 358 0 0 0 0 0 4,530 Meatu 3,695 649 414 62 0 603 162 5,586 Shinyanga Urban 1,153 32 0 0 0 0 0 1,186 Kishapu 8,434 1,051 489 81 0 0 80 10,134 Total 84,182 11,361 1,208 429 144 740 242 98,306 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Bariadi 7,472 1,899 530 175 178 0 0 10,254 Maswa 3,101 1,939 649 216 0 542 325 6,773 Shinyanga Rural 4,230 612 99 99 395 99 0 5,533 Kahama 4,270 991 421 0 429 144 0 6,255 Bukombe 955 0 0 0 0 0 0 955 Meatu 3,144 629 81 0 162 525 0 4,541 Shinyanga Urban 972 0 0 0 0 0 0 972 Kishapu 5,351 78 82 0 0 0 0 5,511 Total 29,494 6,148 1,862 490 1,165 1,310 325 40,794 District Distance to Nearest Drencher 27.13 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Watering Point/ Dam and District District Distance to Nearest Village Watering Point/ Dam 27.14 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Drencher and District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 288 FISH FARMING Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 289 Number % Number % Number % Bariadi 0 0.0 77,572 100.0 77,572 100.0 Maswa 0 0.0 43,252 100.0 43,252 100.0 Shinyanga Rural 0 0.0 45,263 100.0 45,263 100.0 Kahama 430 0.5 80,787 99.5 81,217 100.0 Bukombe 0 0.0 53,240 100.0 53,240 100.0 Meatu 0 0.0 31,492 100.0 31,492 100.0 Shinyanga U b 0 0.0 10,198 100.0 10,198 100.0 Kishapu 0 0.0 35,624 100.0 35,624 100.0 Total 430 0.1 377,427 99.9 377,857 100.0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District Number of Agricultural Households Doing Fish Farming Number of Agricultural Households NOT Doing Fish Farming Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 290 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 291 Number % Number % Number % Bariadi 8,884 11 68,688 89 77,572 100 Maswa 1,942 4 41,310 96 43,252 100 Shinyanga Rural 6,848 15 38,415 85 45,263 100 Kahama 14,122 17 67,095 83 81,217 100 Bukombe 2,369 4 50,871 96 53,240 100 Meatu 6,208 20 25,283 80 31,492 100 Shinyanga Urban 1,403 14 8,795 86 10,198 100 Kishapu 7,957 22 27,667 78 35,624 100 Total 49,733 13 328,124 87 377,857 100 Government NGO / Development Project Bariadi 1,759 0 1,759 Maswa 434 0 434 Shinyanga Rural 2,013 0 2,013 Kahama 7,648 0 7,648 Bukombe 239 0 239 Meatu 1,202 0 1,202 Shinyanga Urban 815 23 839 Kishapu 3,146 0 3,146 Total 17,256 23 17,280 Government NGO / Development Project Bariadi 3,513 179 3,692 Maswa 650 0 650 Shinyanga Rural 3,434 298 3,732 Kahama 9,904 0 9,904 Bukombe 478 0 478 Meatu 2,686 0 2,686 Shinyanga Urban 559 82 641 Kishapu 3,539 0 3,539 Total 24,763 559 25,321 District 29.1b LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year District 29.1c LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year Source of Advice Source of Advice Total Total 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year District g Households Receiving Advice g Households NOT Receiving Total Did Household receive livestock advice during 2002/03? Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 292 Government NGO / Development Project Bariadi 1,410 179 1,589 Maswa 108 0 108 Shinyanga Rural 1,611 199 1,809 Kahama 4,519 0 4,519 Bukombe 239 0 239 Meatu 1,389 0 1,389 Shinyanga Urban 323 116 439 Kishapu 2,252 0 2,252 Total 11,851 493 12,344 Government NGO / Development Project Other Bariadi 2,116 0 0 2,116 Maswa 108 0 0 108 Shinyanga Rural 2,418 199 0 2,617 Kahama 5,518 0 0 5,518 Bukombe 358 0 0 358 Meatu 2,183 0 0 2,183 Shinyanga Urban 327 143 32 502 Kishapu 2,501 0 0 2,501 Total 15,529 342 32 15,903 Government NGO / Development Project Bariadi 7,874 171 8,045 Maswa 867 0 867 Shinyanga Rural 4,726 301 5,026 Kahama 10,007 0 10,007 Bukombe 1,553 0 1,553 Meatu 5,134 0 5,134 Shinyanga Urban 1,097 54 1,151 Kishapu 6,346 0 6,346 Total 37,603 526 38,130 District Source of Advice Total Source of Advice Source of Advice Total 29.1e LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District 29.1f LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year Total 29.1d LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 293 Government NGO / Development Project Other Bariadi 1,767 0 0 1,767 Maswa 434 0 0 434 Shinyanga Rural 1,914 99 0 2,014 Kahama 3,547 0 144 3,691 Bukombe 119 0 0 119 Meatu 2,666 0 79 2,745 Shinyanga Urban 360 23 0 383 Kishapu 4,106 0 81 4,187 Total 14,913 123 304 15,340 Government NGO / Development Project Large Scale Farmer Bariadi 3,698 0 0 3,698 Maswa 325 0 0 325 Shinyanga Rural 2,596 99 0 2,696 Kahama 6,321 0 0 6,321 Bukombe 358 0 0 358 Meatu 2,987 0 0 2,987 Shinyanga Urban 112 23 0 135 Kishapu 3,879 79 82 4,040 Total 20,277 202 82 20,560 Government NGO / Development Project Large Scale Farmer Bariadi 2,641 358 178 3,177 Maswa 217 108 0 325 Shinyanga Rural 1,707 298 0 2,006 Kahama 6,680 0 0 6,680 Bukombe 119 0 0 119 Meatu 1,380 0 0 1,380 Shinyanga Urban 307 54 0 361 Kishapu 2,821 0 0 2,821 Total 15,873 819 178 16,869 Source of Advice Source of Advice Source of Advice District 29.1g LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural Year District Total Total Total 29.1h LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year District 29.1i LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 294 Government NGO / Development Project Other Bariadi 3,353 176 0 3,530 Maswa 434 0 0 434 Shinyanga Rural 2,504 199 0 2,703 Kahama 6,733 0 0 6,733 Bukombe 478 0 0 478 Meatu 1,861 83 0 1,945 Shinyanga Urban 477 82 0 559 Kishapu 2,576 0 78 2,654 Total 18,416 541 78 19,035 Government NGO / Development Project Bariadi 2,122 0 2,122 Maswa 426 108 534 Shinyanga Rural 1,314 200 1,514 Kahama 4,767 144 4,911 Bukombe 239 0 239 Meatu 2,664 0 2,664 Shinyanga Urban 602 55 657 Kishapu 2,661 0 2,661 Total 14,794 506 15,301 Source of Advice Total Source of Advice 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year District 29.1j LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Total Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 295 Number % Number % Number % Number % Number % Number % Bariadi 1,223 13 7,856 85 169 2 0 0 0 0 9,248 100 Maswa 1,406 25 2,266 40 1,834 33 108 2 0 0 5,614 100 Shinyanga Rural 2,319 31 4,727 63 406 5 0 0 0 0 7,452 100 Kahama 1,899 14 10,177 75 1,116 8 393 3 0 0 13,585 100 Bukombe 239 11 1,424 67 358 17 0 0 119 6 2,141 100 Meatu 929 13 3,449 50 2,185 31 0 0 383 6 6,946 100 Shinyanga Urban 78 6 442 32 650 47 217 16 0 0 1,388 100 Kishapu 884 11 3,495 45 3,406 44 0 0 0 0 7,785 100 Total 8,979 17 33,835 62 10,125 19 719 1 503 1 54,160 100 Number % Number % Number % Number % Number % Number % Bariadi 8,884 20 8,884 20 8,884 20 8,884 20 8,884 20 44,419 100 Maswa 1,942 20 1,942 20 1,942 20 1,942 20 1,942 20 9,709 100 Shinyanga Rural 6,848 20 6,848 20 6,848 20 6,848 20 6,848 20 34,238 100 Kahama 14,122 20 13,981 20 13,981 20 13,981 20 13,981 20 70,047 100 Bukombe 2,369 20 2,369 20 2,369 20 2,369 20 2,369 20 11,847 100 Meatu 6,208 20 6,208 20 6,208 20 6,208 20 6,208 20 31,042 100 Shinyanga Urban 1,403 20 1,371 20 1,371 20 1,371 20 1,371 20 6,887 100 Kishapu 7,957 20 7,957 20 7,957 20 7,957 20 7,957 20 39,785 100 Total 49,733 20 49,560 20 49,560 20 49,560 20 49,560 20 247,974 100 29.1l LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year 29.lm LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year District Government NGO / Development Co-operative Large Scale Other Extension Provider Total District Quality of Service Total Very Good Good Average Poor No Good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 296 Number % Number % Number % Bariadi 3,996 5 73,576 95 77,572 100 Maswa 744 2 42,508 98 43,252 100 Shinyanga Rural 3,008 7 42,255 93 45,263 100 Kahama 4,687 6 76,530 94 81,217 100 Bukombe 597 1 52,643 99 53,240 100 Meatu 642 2 30,849 98 31,492 100 Shinyanga Urban 664 7 9,535 93 10,198 100 Kishapu 2,785 8 32,838 92 35,624 100 Total 17,123 5 360,735 95 377,857 100 Number % Number % Number % Bariadi 870 1 76,702 99 77,572 100 Maswa 542 1 42,710 99 43,252 100 Shinyanga Rural 102 0 45,161 100 45,263 100 Kahama 983 1 80,233 99 81,217 100 Bukombe 1,195 2 52,045 98 53,240 100 Meatu 993 3 30,498 97 31,492 100 Shinyanga Urban 140 1 10,059 99 10,198 100 Kishapu 623 2 35,001 98 35,624 100 Total 5,448 1 372,410 99 377,857 100 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Number of Agricultural Households WITH Contact Farmers / Group Members Number of Agricultural Households WITHOUT Contact Farmers / Group Members Total Did you face problems with Govt regulations during 02/03? Total 30.1 GOVERNMENT REGULATORY PROBLEMS: Number of Agricultural Households by Whether Face Problems with Governmet Regulation During 2003/04 by District, 2002/03 Agricultural Year District Yes No Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 297 Appendix II 298 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 299 Primary School Secondary School Health Clinic / Dispensar y Hospital District Capital Regional Capital Feeder Road All weather Road Tarmac Road Primary Market Secondary Market Tertiary Market Bariadi 3.1 14.9 5.2 31.7 34.0 163.9 2.4 13.9 114.0 8.5 20.7 27.9 Maswa 2.4 16.3 6.1 32.5 32.0 102.4 3.3 3.5 98.8 6.5 14.1 22.6 Shinyanga Ruralal 1.8 19.5 4.4 46.7 47.1 49.1 1.4 5.8 43.0 7.5 12.4 43.5 Kahama 2.1 21.0 11.2 44.7 44.6 147.7 1.7 8.0 35.9 6.4 15.7 40.4 Bukombe 2.4 18.7 10.7 52.2 40.3 196.3 2.0 3.9 14.8 7.2 13.5 23.3 Meatu 2.9 22.1 8.3 42.7 46.1 174.7 2.3 5.6 169.4 9.1 13.7 54.1 Shinyanga Urbanan 1.7 7.6 5.1 10.0 11.1 14.9 1.3 2.7 13.1 6.2 9.0 9.4 Kishapu 2.1 23.2 7.4 45.2 38.3 52.8 2.8 3.6 43.9 12.6 26.1 41.3 Total 2.4 18.6 7.7 40.9 39.3 130.6 2.2 7.1 68.3 7.9 16.5 34.2 Regional Capital 130.61 Tarmac Road 68.27 Hospital 40.88 District Capital 39.32 Tertiary Market 34.15 Secondary School 18.65 Secondary Market 16.48 Primary Market 7.90 Health Clinic / Dispensary 7.71 All weather Road 7.10 Primary School 2.39 Feeder Road 2.18 33.1a ACCESS TO SERVICES: Number of Agricultural Households by Distance to Services by District, 2002/03 Agricultural Year District Mean Distance to Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 300 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 17,755 23 36,621 47 22,933 30 0 0 262 0 77,572 3.1 Maswa 6,459 15 20,911 48 15,667 36 108 0 108 0 43,252 2.4 Shinyanga Rural 10,639 24 25,644 57 8,675 19 204 0 102 0 45,263 1.8 Kahama 14,915 18 43,020 53 22,433 28 848 1 0 0 81,217 2.1 Bukombe 6,541 12 29,156 55 17,304 33 0 0 239 0 53,240 2.4 Meatu 2,913 9 12,258 39 16,154 51 167 1 0 0 31,492 2.9 Shinyanga Urban 2,810 28 5,907 58 1,427 14 23 0 32 0 10,198 1.7 Kishapu 7,858 22 17,144 48 10,378 29 244 1 0 0 35,624 2.1 Total 69,889 18 190,660 50 114,971 30 1,594 0 743 0 377,857 2.4 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 178 0 4,946 6 20,598 27 30,164 39 21,686 28 77,572 14.9 Maswa 434 1 3,979 9 13,116 30 15,695 36 10,029 23 43,252 16.3 Shinyanga Rural 204 0 489 1 15,938 35 10,714 24 17,919 40 45,263 19.5 Kahama 570 1 3,669 5 17,108 21 26,228 32 33,643 41 81,217 21.0 Bukombe 232 0 239 0 13,355 25 18,767 35 20,647 39 53,240 18.7 Meatu 165 1 1,734 6 5,328 17 7,792 25 16,472 52 31,492 22.1 Shinyanga Urban 583 6 650 6 5,472 54 3,461 34 32 0 10,198 7.6 Kishapu 163 0 897 3 9,676 27 13,630 38 11,257 32 35,624 23.2 Total 2,527 1 16,603 4 100,591 27 126,451 33 131,684 35 377,857 18.6 Total Number of Households Mean Distance 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to Secondary School 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year Total Number of Households Mean District Distance to Primary School Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 301 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 5,897 8 21,799 28 43,822 56 4,808 6 1,245 2 77,572 5.2 Maswa 3,287 8 10,850 25 23,628 55 4,418 10 1,069 2 43,252 6.1 Shinyanga Rural 2,400 5 12,073 27 28,053 62 2,738 6 0 0 45,263 4.4 Kahama 5,069 6 11,141 14 44,142 54 10,552 13 10,312 13 81,217 11.2 Bukombe 1,309 2 2,390 4 28,505 54 15,547 29 5,489 10 53,240 10.7 Meatu 1,297 4 4,412 14 14,455 46 9,593 30 1,736 6 31,492 8.3 Shinyanga Urban 957 9 1,887 18 6,137 60 1,187 12 31 0 10,198 5.1 Kishapu 2,077 6 8,842 25 18,695 52 3,675 10 2,334 7 35,624 7.4 Total 22,293 6 73,393 19 207,436 55 52,519 14 22,216 6 377,857 7.7 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 177 0 338 0 4,233 5 6,795 9 66,029 85 77,572 31.7 Maswa 542 1 0 0 4,009 9 6,909 16 31,792 74 43,252 32.5 Shinyanga Rural 102 0 0 0 607 1 5,468 12 39,087 86 45,263 46.7 Kahama 0 0 133 0 6,428 8 14,535 18 60,121 74 81,217 44.7 Bukombe 717 1 0 0 2,146 4 8,014 15 42,363 80 53,240 52.2 Meatu 81 0 1,363 4 3,225 10 2,034 6 24,789 79 31,492 42.7 Shinyanga Urban 31 0 835 8 4,630 45 4,051 40 652 6 10,198 10.0 Kishapu 134 0 1,096 3 2,462 7 2,476 7 29,455 83 35,624 45.2 Total 1,784 0 3,765 1 27,740 7 50,283 13 294,286 78 377,857 40.9 Total Number of Households Mean Distance Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Distance (Kilometer) to Health Clinic Total Number of Households Mean Distance 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year 3 - 9 9 10 - 19.9 Above 20 District Distance (Kilometer) to Hospital District Less than 1 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year Above 20 1 - 2.9 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 302 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 0 0 99 0 2,623 3 6,896 9 67,955 88 77,572 34.0 Maswa 325 1 0 0 4,009 9 5,492 13 33,426 77 43,252 32.0 Shinyanga Rural 99 0 0 0 102 0 4,866 11 40,196 89 45,263 47.1 Kahama 0 0 0 0 5,858 7 10,811 13 64,548 79 81,217 44.6 Bukombe 478 1 118 0 696 1 10,544 20 41,404 78 53,240 40.3 Meatu 248 1 704 2 2,979 9 2,030 6 25,531 81 31,492 46.1 Shinyanga Urban 63 1 221 2 4,337 43 4,933 48 643 6 10,198 11.1 Kishapu 0 0 1,186 3 1,095 3 4,344 12 28,998 81 35,624 38.3 Total 1,213 0 2,329 1 21,699 6 49,916 13 302,701 80 377,857 39.3 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 715 1 0 0 178 0 709 1 75,970 98 77,572 163.9 Maswa 325 1 108 0 434 1 217 1 42,168 97 43,252 102.4 Shinyanga Rural 0 0 0 0 204 0 5,468 12 39,592 87 45,263 49.1 Kahama 948 1 133 0 143 0 144 0 79,849 98 81,217 147.7 Bukombe 2,502 5 478 1 119 0 471 1 49,670 93 53,240 196.3 Meatu 163 1 0 0 0 0 0 0 31,329 99 31,492 174.7 Shinyanga Urban 64 1 258 3 4,239 42 4,901 48 736 7 10,198 14.9 Kishapu 160 0 81 0 704 2 1,523 4 33,155 93 35,624 52.8 Total 4,877 1 1,058 0 6,022 2 13,432 4 352,468 93 377,857 130.6 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 30,610 39 24,685 32 17,464 23 4,456 6 356 0 77,572 2.4 Maswa 17,521 41 16,663 39 7,659 18 1,192 3 217 1 43,252 3.3 Shinyanga Rural 23,242 51 14,540 32 7,178 16 303 1 0 0 45,263 1.4 Kahama 43,588 54 24,624 30 10,707 13 2,155 3 144 0 81,217 1.7 Bukombe 17,091 32 28,159 53 6,920 13 956 2 114 0 53,240 2.0 Meatu 11,448 36 9,330 30 10,466 33 165 1 83 0 31,492 2.3 Shinyanga Urban 5,651 55 3,212 31 1,303 13 0 0 32 0 10,198 1.3 Kishapu 18,086 51 13,304 37 4,152 12 0 0 82 0 35,624 2.8 Total 167,236 44 134,517 36 65,849 17 9,226 2 1,029 0 377,857 2.2 Total Number of Households Mean Distance Distance (Kilometer) to Feeder Road Total Number of Households Mean Distance 10 - 19.9 Above 20 10 - 19.9 Above 20 Distance (Kilometer) to District Capital Total Number of Households Mean Distance 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to Districtal Capital District Less than 1 1 - 2.9 3 - 9 9 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 303 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 12,939 17 13,935 18 24,516 32 11,858 15 14,324 18 77,572 13.9 Maswa 10,038 23 15,504 36 13,351 31 3,935 9 424 1 43,252 3.5 Shinyanga Rural 12,094 27 7,004 15 20,110 44 3,648 8 2,408 5 45,263 5.8 Kahama 22,062 27 18,505 23 22,943 28 11,232 14 6,475 8 81,217 8.0 Bukombe 11,727 22 21,514 40 16,296 31 2,627 5 1,075 2 53,240 3.9 Meatu 5,719 18 6,806 22 13,006 41 5,795 18 166 1 31,492 5.6 Shinyanga Urban 3,222 32 3,118 31 3,278 32 580 6 0 0 10,198 2.7 Kishapu 11,200 31 10,364 29 12,021 34 1,320 4 718 2 35,624 3.6 Total 89,001 24 96,751 26 125,522 33 40,994 11 25,590 7 377,857 7.1 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 1,238 2 0 0 707 1 4,646 6 70,981 92 77,572 114.0 Maswa 2,709 6 0 0 434 1 95 0 40,014 93 43,252 98.8 Shinyanga Rural 2,162 5 101 0 0 0 4,143 9 38,858 86 45,263 43.0 Kahama 2,449 3 6,455 8 5,606 7 14,755 18 51,952 64 81,217 35.9 Bukombe 4,528 9 6,368 12 18,144 34 7,727 15 16,473 31 53,240 14.8 Meatu 1,235 4 0 0 0 0 0 0 30,256 96 31,492 169.4 Shinyanga Urban 571 6 336 3 4,207 41 4,210 41 875 9 10,198 13.1 Kishapu 5,692 16 639 2 5,636 16 1,696 5 21,960 62 35,624 43.9 Total 20,585 5 13,898 4 34,734 9 37,271 10 271,370 72 377,857 68.3 Mean Distance 10 - 19.9 Above 20 10 - 19.9 Above 20 District Less than 1 1 - 2.9 3 - 9 9 Distance (Kilometer) to ALL Wealther Road Total Number of Households Mean Distance Distance (Kilometer) to Tarmac Road Total Number of Households District Less than 1 1 - 2.9 3 - 9 9 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 304 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 8,652 11 13,655 18 34,951 45 14,255 18 6,060 8 77,572 8.5 Maswa 2,231 5 10,686 25 25,149 58 3,885 9 1,300 3 43,252 6.5 Shinyanga Rural 1,882 4 7,045 16 22,495 50 12,045 27 1,795 4 45,263 7.5 Kahama 6,768 8 13,347 16 44,088 54 14,598 18 2,416 3 81,217 6.4 Bukombe 2,737 5 8,173 15 30,361 57 11,020 21 948 2 53,240 7.2 Meatu 2,070 7 2,242 7 18,891 60 5,811 18 2,477 8 31,492 9.1 Shinyanga Urban 650 6 1,725 17 6,047 59 1,554 15 223 2 10,198 6.2 Kishapu 2,186 6 4,886 14 10,003 28 10,666 30 7,882 22 35,624 12.6 Total 27,176 7 61,760 16 191,985 51 73,835 20 23,102 6 377,857 7.9 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 3,021 4 4,318 6 11,679 15 15,570 20 42,983 55 77,572 20.7 Maswa 1,244 3 4,822 11 15,383 36 13,785 32 8,017 19 43,252 14.1 Shinyanga Rural 183 0 4,166 9 18,716 41 17,095 38 5,104 11 45,263 12.4 Kahama 691 1 2,385 3 23,374 29 36,103 44 18,664 23 81,217 15.7 Bukombe 717 1 1,791 3 22,646 43 16,716 31 11,370 21 53,240 13.5 Meatu 479 2 1,746 6 11,071 35 11,143 35 7,053 22 31,492 13.7 Shinyanga Urban 633 6 715 7 5,479 54 2,531 25 840 8 10,198 9.0 Kishapu 1,379 4 2,695 8 3,032 9 6,807 19 21,711 61 35,624 26.1 Total 8,347 2 22,637 6 111,380 29 119,751 32 115,742 31 377,857 16.5 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Bariadi 1,538 2 889 1 4,381 6 13,977 18 56,787 73 77,572 27.9 Maswa 650 2 1,841 4 11,117 26 8,957 21 20,687 48 43,252 22.6 Shinyanga Rural 295 1 1,278 3 3,156 7 6,080 13 34,453 76 45,263 43.5 Kahama 1,062 1 503 1 9,236 11 12,721 16 57,695 71 81,217 40.4 Bukombe 829 2 4,119 8 12,535 24 12,471 23 23,286 44 53,240 23.3 Meatu 463 1 1,451 5 1,967 6 1,791 6 25,819 82 31,492 54.1 Shinyanga Urban 556 5 273 3 5,056 50 3,483 34 831 8 10,198 9.4 Kishapu 328 1 1,920 5 3,296 9 3,817 11 26,262 74 35,624 41.3 Total 5,722 2 12,274 3 50,744 13 63,296 17 245,821 65 377,857 34.2 Total Number of Households Mean Distance District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Distance (Kilometer) to Tertiary Market Above 20 10 - 19.9 Above 20 3 - 9 9 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year 1 - 2.9 3 - 9 9 Distance (Kilometer) to Primary Market 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year Total Number of Households Mean Distance Distance (Kilometer) to Secondary Market Total Number of Households Mean Distance 10 - 19.9 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Less than 1 1 - 2.9 District Less than 1 Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 305 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 0 0 1,993 3 178 0 1,071 1 7,639 10 5,800 7.8 57,562 78 74,244 151.8 Maswa 3,467 8 6,133 15 4,404 11 864 2 2,119 5 9,499 23.0 14,841 36 41,328 47.9 Shinyanga Rural 300 1 102 0 2,536 6 2,835 6 2,416 5 14,243 32.2 21,733 49 44,166 50.7 Kahama 4,927 6 7,181 9 4,708 6 6,768 9 9,181 12 11,074 14.0 35,517 45 79,356 50.1 Bukombe 4,894 9 453 1 1,912 4 0 0 3,100 6 118 0.2 41,336 80 51,813 100.1 Meatu 492 2 3,145 10 1,022 3 968 3 2,423 8 6,178 20.2 16,358 53 30,587 83.5 Shinyanga Urban 681 7 2,136 22 534 6 31 0 0 0 0 0.0 6,211 65 9,592 51.5 Kishapu 3,065 9 625 2 2,346 7 81 0 1,466 4 10,264 28.8 17,778 50 35,624 51.5 Total 17,825 5 21,767 6 17,641 5 12,617 3 28,345 8 57,177 15.6 211,337 58 366,709 80.8 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 520 1 2,767 4 4,227 6 3,735 5 22,289 31 25,035 34.8 13,346 19 71,919 49.3 Maswa 3,468 8 6,135 15 4,192 10 1,730 4 3,622 9 12,861 30.7 9,933 24 41,940 37.1 Shinyanga Rural 302 1 303 1 2,530 6 2,835 6 2,623 6 14,846 33.1 21,416 48 44,855 49.5 Kahama 3,262 5 13,711 19 4,371 6 5,549 8 3,291 5 2,239 3.1 38,770 54 71,193 50.1 Bukombe 1,553 3 3,748 7 4,439 8 5,239 10 6,327 12 8,421 16.1 22,690 43 52,416 85.3 Meatu 220 1 4,482 15 1,382 5 1,292 4 2,668 9 6,919 22.8 13,364 44 30,328 44.0 Shinyanga Urban 684 8 1,576 19 90 1 31 0 0 0 0 0.0 6,094 72 8,476 33.0 Kishapu 2,284 7 2,503 8 2,081 6 1,638 5 1,142 4 9,615 29.7 13,102 40 32,365 39.7 Total 12,294 3 35,225 10 23,312 7 22,048 6 41,962 12 79,937 22.6 138,715 39 353,493 51.4 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center District Distance (Kilometer) to Veterinary Clinic Mean Distance Mean Distance Distance (Kilometer) to Extension Center District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 306 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 179 0 0 0 0 0 178 0 179 0 0 0.0 77,036 99 77,572 192.1 Maswa 3,468 8 0 0 108 0 0 0 189 0 744 1.7 38,742 90 43,252 146.9 Shinyanga Rural 201 0 0 0 100 0 0 0 305 1 3,260 7.2 41,396 91 45,263 149.5 Kahama 427 1 0 0 0 0 0 0 0 0 133 0.2 80,657 99 81,217 263.6 Bukombe 358 1 0 0 0 0 0 0 0 0 0 0.0 52,882 99 53,240 318.7 Meatu 489 2 0 0 0 0 0 0 0 0 0 0.0 30,940 98 31,429 253.5 Shinyanga Urban 1,868 19 992 10 0 0 0 0 30 0 0 0.0 6,970 71 9,860 146.4 Kishapu 2,594 7 0 0 810 2 80 0 651 2 82 0.2 31,406 88 35,624 170.1 Total 9,584 3 992 0 1,019 0 258 0 1,355 0 4,219 1.1 360,030 95 377,457 216.8 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 178 0 177 0 0 0 348 0 353 0 76,516 99 77,572 192.8 Maswa 3,468 8 0 0 108 0 95 0 108 0 39,473 91 43,252 147.6 Shinyanga Rural 611 1 0 0 0 0 101 0 3,362 7 41,088 91 45,161 145.5 Kahama 571 1 0 0 0 0 0 0 418 1 80,228 99 81,217 258.3 Bukombe 358 1 0 0 118 0 238 0 0 0 52,526 99 53,240 312.2 Meatu 572 2 0 0 0 0 0 0 83 0 30,836 98 31,492 250.0 Shinyanga Urban 1,778 18 1,022 10 0 0 0 0 0 0 7,026 72 9,826 145.4 Kishapu 2,342 7 0 0 485 1 733 2 164 0 31,900 90 35,624 172.2 Total 9,878 3 1,200 0 711 0 1,513 0 4,488 1 359,592 95 377,383 214.4 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year Distance (Kilometer) to Plant Protection Lab 50 + 30 - 49 20 - 29 10 - 14 5 - 9 <5 Mean Distance District District Distance (Kilometer) to Research Station Mean Distance Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 307 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 346 0 1,082 1 3,698 5 3,556 5 22,834 30 36,025 47 8,573 11 76,113 33.5 Maswa 2,700 6 4,334 10 2,811 7 969 2 4,542 11 21,845 51 5,942 14 43,144 40.7 Shinyanga Rural 201 0 204 0 1,631 4 3,037 7 3,727 8 18,371 41 18,092 40 45,263 48.9 Kahama 417 1 2,716 3 3,110 4 7,640 9 13,550 17 24,131 30 29,281 36 80,846 44.0 Bukombe 239 0 119 0 7,545 14 3,568 7 9,546 18 9,803 18 22,420 42 53,240 40.7 Meatu 162 1 2,395 8 329 1 1,541 5 3,167 11 8,687 29 13,757 46 30,039 46.5 Shinyanga Urban 652 7 2,192 23 594 6 784 8 0 0 5,301 56 0 0 9,522 25.2 Kishapu 1,218 3 547 2 1,198 3 0 0 1,374 4 17,951 50 13,335 37 35,624 50.1 Total 5,935 2 13,589 4 20,916 6 21,095 6 58,741 16 142,115 38 111,401 30 373,792 41.9 Total Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households Bariadi 163 0 10,367 14 5,904 8 11,208 15 7,102 10 533 1 39,127 53 74,405 91.1 Maswa 3,792 9 3,901 9 1,299 3 541 1 419 1 4,327 10 28,756 67 43,035 75.4 Shinyanga Rural 604 2 7,767 19 8,193 20 1,186 3 3,089 8 3,464 9 15,690 39 39,992 44.6 Kahama 10,620 13 565 1 110 0 566 1 2,378 3 1,998 2 64,980 80 81,217 127.3 Bukombe 5,490 10 119 0 236 0 1,314 2 119 0 0 0 45,841 86 53,121 164.6 Meatu 847 3 1,367 4 4,009 13 774 2 1,672 5 4,381 14 18,027 58 31,077 117.9 Shinyanga Urban 1,558 16 1,040 11 472 5 0 0 30 0 0 0 6,475 68 9,575 66.7 Kishapu 3,246 9 78 0 1,958 5 328 1 1,061 3 6,876 19 22,077 62 35,624 84.3 Total 26,320 7 25,205 7 22,181 6 15,917 4 15,871 4 21,578 6 240,972 65 368,045 102.8 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center 10 - 14 5 - 9 <5 Mean Distance Mean Distance Distance (Kilometer) to Livestock Development Center 50 + 30 - 49 20 - 29 15 - 19 10 - 14 5 - 9 <5 50 + 30 - 49 20 - 29 15 - 19 District District Distance (Kilometer) to Land Registration Office Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 308 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 2,110 8 10,808 40 7,582 28 3,934 15 2,311 9 26,745 Maswa 2,273 8 4,287 16 13,730 50 4,969 18 2,250 8 27,509 Shinyanga Rural 2,028 14 1,302 9 4,007 27 2,640 18 4,668 32 14,645 Kahama 1,350 1 24,852 25 11,230 11 29,070 30 31,959 32 98,461 Bukombe 1,538 5 3,784 13 3,565 13 16,353 57 3,215 11 28,455 Meatu 672 2 4,566 12 4,146 11 15,303 41 12,883 34 37,570 Shinyanga Urban 95 3 2,362 72 731 22 92 3 0 0 3,281 Kishapu 568 2 3,965 11 8,647 25 11,996 34 9,761 28 34,937 Total 10,634 4 55,927 21 53,637 20 84,358 31 67,047 25 271,602 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 884 9 6,752 69 1,411 14 452 5 357 4 9,855 Maswa 541 10 2,145 39 2,029 36 528 9 325 6 5,568 Shinyanga Rural 306 13 102 4 808 33 306 13 914 38 2,436 Kahama 787 5 6,226 38 2,826 17 1,786 11 4,688 29 16,312 Bukombe 358 5 2,647 35 1,432 19 2,744 36 357 5 7,538 Meatu 136 2 1,768 23 937 12 2,317 30 2,623 34 7,781 Shinyanga Urban 0 0 864 63 484 35 31 2 0 0 1,379 Kishapu 82 1 3,277 37 1,956 22 2,040 23 1,613 18 8,968 Total 3,094 5 23,780 40 11,883 20 10,203 17 10,877 18 59,838 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 529 17 154 5 1,237 39 889 28 357 11 3,166 Maswa 108 3 0 0 2,044 53 1,300 33 434 11 3,885 Shinyanga Rural 204 11 102 6 102 6 711 39 710 39 1,829 Kahama 141 1 4,147 26 2,475 15 4,937 31 4,398 27 16,098 Bukombe 0 0 119 3 474 12 2,747 70 596 15 3,936 Meatu 0 0 161 4 411 10 2,188 54 1,316 32 4,076 Shinyanga Urban 0 0 152 83 0 0 31 17 0 0 182 Kishapu 0 0 0 0 1,142 23 2,041 42 1,695 35 4,877 Total 982 3 4,836 13 7,884 21 14,842 39 9,505 25 38,049 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Very Good Good Average Poor No good Total number of households Satisfaction of Using Veterinary Clinic District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 309 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 350 14 179 7 1,058 43 536 22 357 14 2,479 Maswa 108 3 108 3 2,044 50 1,408 34 426 10 4,094 Shinyanga Rural 306 17 0 0 0 0 711 39 812 44 1,829 Kahama 141 1 4,061 25 2,648 16 4,850 30 4,398 27 16,098 Bukombe 112 3 119 3 354 9 2,747 70 596 15 3,929 Meatu 83 2 83 2 333 8 2,190 54 1,392 34 4,080 Shinyanga Urban 30 20 121 80 0 0 0 0 0 0 152 Kishapu 161 3 0 0 1,142 24 1,796 38 1,613 34 4,713 Total 1,291 3 4,671 12 7,579 20 14,238 38 9,594 26 37,374 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 174 4 1,060 27 1,408 36 710 18 531 14 3,885 Maswa 108 2 325 7 2,785 62 866 19 424 9 4,508 Shinyanga Rural 908 33 101 4 606 22 303 11 812 30 2,729 Kahama 0 0 7,788 37 1,694 8 4,946 23 6,762 32 21,191 Bukombe 239 5 540 11 593 13 2,866 61 477 10 4,715 Meatu 210 2 1,430 16 1,291 14 3,597 40 2,384 27 8,912 Shinyanga Urban 32 10 244 72 63 19 0 0 0 0 339 Kishapu 81 1 162 3 1,878 32 2,120 36 1,613 28 5,855 Total 1,753 3 11,650 22 10,318 20 15,409 30 13,004 25 52,134 No of Households % No of Households % No of Households % No of Households % No of Households % Bariadi 0 0 715 27 1,233 46 357 13 357 13 2,661 Maswa 325 9 324 9 2,152 62 434 13 217 6 3,452 Shinyanga Rural 102 3 997 31 1,183 37 204 6 710 22 3,196 Kahama 282 3 1,145 12 566 6 1,700 17 6,205 63 9,897 Bukombe 232 6 119 3 354 9 2,627 69 477 13 3,809 Meatu 79 1 333 5 841 13 2,437 39 2,623 42 6,313 Shinyanga Urban 32 13 182 74 31 13 0 0 0 0 245 Kishapu 163 3 0 0 1,142 23 1,878 38 1,695 35 4,877 Total 1,214 4 3,816 11 7,502 22 9,637 28 12,283 36 34,451 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 310 No good No of Households % No of Households % No of Households % No of Households % No of Households 10,634 4 55,927 21 53,637 20 84,358 31 67,047 3,094 5 23,780 40 11,883 20 10,203 17 10,877 982 3 4,836 13 7,884 21 14,842 39 9,505 1,291 3 4,671 12 7,579 20 14,238 38 9,594 1,753 3 11,650 22 10,318 20 15,409 30 13,004 1,214 4 3,816 11 7,502 22 9,637 28 12,283 4 21.214 20.02 30.13 Extension Centre Veterinary Clinic OVERALL % Livestock Development Centre Land Registration Office Plant Protection Lab Research Station TYPE OF SERVICE LEVEL OF SATISFACTION OF THE SERVICE Very Good Good Average Poor 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report 311 Appendix II 312 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 313 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Number of Households Bariadi 9,310 1,764 65,608 533 356 77,572 Maswa 5,344 851 36,651 405 - 43,252 Shinyanga Rural 4,145 2,920 38,005 91 102 45,263 Kahama 16,227 3,866 60,927 197 - 81,217 Bukombe 4,398 1,912 46,691 239 - 53,240 Meatu 892 897 29,353 350 - 31,492 Shinyanga Urban 473 76 9,244 390 15 10,198 Kishapu 2,714 400 32,266 244 0 35,624 Total 43,503 12,686 318,745 2,450 474 377,857 % 11.0 0.7 86.5 1.8 0.1 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Bariadi 3 49,428 333 0 0 17,850 8,371 1,590 77,572 Maswa 3 10,796 217 0 0 6,687 25,552 0 43,252 Shinyanga Rural 3 7,831 200 0 0 24,754 12,477 0 45,263 Kahama 2 23,036 381 123 0 53,009 4,557 110 81,217 Bukombe 2 18,127 239 119 0 23,166 11,588 0 53,240 Meatu 3 8,751 572 0 244 3,867 18,059 0 31,492 Shinyanga Urban 3 2,405 31 0 0 1,575 6,188 0 10,198 Kishapu 3 5,055 82 0 814 1,607 28,066 0 35,624 Total 3 125,429 2,054 243 1,058 132,516 114,858 1,700 377,857 % 33.2 0.5 0.1 0.3 35.1 30.4 0.4 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Bariadi 3 64 0 0 0 23 11 2 100 Maswa 3 25 1 0 0 15 59 0 100 Shinyanga Rural 3 17 0 0 0 55 28 0 100 Kahama 2 28 0 0 0 65 6 0 100 Bukombe 2 34 0 0 0 44 22 0 100 Meatu 3 28 2 0 1 12 57 0 100 Shinyanga Urban 3 24 0 0 0 15 61 0 100 Kishapu 3 14 0 0 2 5 79 0 100 Total 3 33 1 0 0 35 30 0 100 % 33.2 0.5 0.1 0.3 35.1 30.4 0.4 100.0 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year District Type of Toilet 34.2B Percent of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year 34.2A Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year District Average Number of Rooms per Household Type of Roofing Material District Type of Roofing Material Average Number of Rooms per Household Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 314 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Radio 35,698 19,852 23,650 43,003 32,301 13,930 6,001 17,816 192,251 Landline phone 154 189 98 0 119 141 77 80 858 Mobile phone 1,352 297 788 1,541 0 1,186 317 244 5,725 Iron 12,880 6,915 5,969 16,974 6,289 6,936 2,096 6,390 64,449 Wheelbarrow 5,655 4,265 8,757 8,950 2,388 3,495 1,047 4,836 39,393 Bicycle 48,792 26,632 30,282 54,571 36,154 20,598 6,738 22,764 246,531 Vehicle 1,051 541 503 977 353 286 217 307 4,236 Television / Video 1,059 412 506 837 119 397 200 162 3,692 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Radio 46 46 52 53 61 44 59 50 Landline phone 0 0 0 0 0 0 1 0 Mobile phone 2 1 2 2 0 4 3 1 Iron 17 16 13 21 12 22 21 18 Wheelbarrow 7 10 19 11 4 11 10 14 Bicycle 63 62 67 67 68 65 66 64 Vehicle 1 1 1 1 1 1 2 1 Television / Video 1 1 1 1 0 1 2 0 Type of Owned Asset District Total District Type of Owned Asse 34.3 Propotion of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 315 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 792 290 301 137 478 329 158 0 2,485 Solar 175 0 0 0 119 0 0 149 443 Gas (Biogas) 179 108 100 0 0 0 30 81 498 Hurricane Lamp 11,469 6,820 4,262 12,961 6,049 5,340 2,206 5,125 54,233 Pressure Lamp 2,296 1,732 708 3,140 1,193 249 404 2,492 12,214 Wick Lamp 61,260 33,544 39,083 63,503 44,923 25,183 7,337 27,290 302,123 Candles 0 0 301 284 119 81 0 0 785 Firewood 1,402 757 508 1,192 358 310 32 486 5,044 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,491 10,166 35,624 377,825 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 1 1 1 0 1 1 2 0 1 Solar 0 0 0 0 0 0 0 0 0 Gas (Biogas) 0 0 0 0 0 0 0 0 0 Hurricane Lamp 15 16 9 16 11 17 22 14 14 Pressure Lamp 3 4 2 4 2 1 4 7 3 Wick Lamp 79 78 86 78 84 80 72 77 80 Candles 0 0 1 0 0 0 0 0 0 Firewood 2 2 1 1 1 1 0 1 1 Total 100 100 100 100 100 100 100 100 100 34.4a Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year District Main Source of Energy for Lighting Main Source of Energy for Lighting District 34.4b Proportion of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 316 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 349 0 101 0 0 0 31 82 562 Gas (Biogas) 178 0 0 0 0 0 0 0 178 Bottled Gas 0 0 102 267 119 83 92 0 663 Parraffin / Kerocine 154 95 0 0 0 83 47 0 379 Charcoal 1,142 2,737 888 5,213 1,431 1,193 990 1,056 14,650 Firewood 74,864 40,205 44,172 75,465 51,212 29,008 8,931 34,162 358,020 Crop Residues 0 215 0 273 478 1,125 78 245 2,413 Livestock Dung 885 0 0 0 0 0 30 79 993 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 377,857 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Total Mains Electricity 0 0 0 0 0 0 0 0 0 Gas (Biogas) 0 0 0 0 0 0 0 0 0 Bottled Gas 0 0 0 0 0 0 1 0 0 Parraffin / Kerocine 0 0 0 0 0 0 0 0 0 Charcoal 1 6 2 6 3 4 10 3 4 Firewood 97 93 98 93 96 92 88 96 95 Crop Residues 0 0 0 0 1 4 1 1 1 Livestock Dung 1 0 0 0 0 0 0 0 0 Total 100 100 100 100 100 100 100 100 100 District 34.5b Proportion of Agriculture Households by Main Source of Energy Used for Cooking and District during 2002/03 Agricultural Year 34.5a Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Main Source of Energy for Lighting District District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 317 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatunyanga Urban Kishapu Wet 13,845 3,456 4,621 9,580 6,683 3,918 2,114 1,588 Dry 14,006 6,160 4,217 9,449 6,805 3,837 2,081 1,520 Wet 33,369 12,022 5,546 24,020 8,315 9,153 4,219 1,118 Dry 34,233 16,857 6,653 24,188 8,194 9,322 4,365 1,033 Wet 881 325 505 1,991 1,044 165 92 - Dry 704 433 507 1,989 924 249 184 632 Wet 14,145 11,025 14,113 38,002 32,544 3,855 1,605 11,085 Dry 11,505 5,408 15,316 38,990 32,424 4,388 1,747 8,902 Wet 5,605 1,081 3,916 2,849 597 700 278 399 Dry 4,723 1,183 4,418 4,080 956 83 278 1,198 Wet 8,503 9,824 12,315 1,884 357 13,028 1,423 14,941 Dry 11,867 10,829 12,837 1,466 357 13,188 1,452 17,933 Wet 175 95 0 131 239 166 32 1,534 Dry 0 108 101 0 239 166 0 1,122 Wet 1,049 4,412 4,046 2,512 1,314 250 406 4,959 Dry 534 2,274 1,018 697 1,075 83 32 3,284 Wet 0 0 0 247 0 94 30 - Dry 0 0 0 357 0 94 30 - Wet 0 0 0 0 0 81 0 - Dry 0 0 98 0 0 81 31 - Wet 0 1,013 201 0 2,147 81 0 - Dry 0 0 99 0 2,266 0 0 - Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 18 8 10 12 13 12 21 4 Dry 18 14 9 12 13 12 20 4 Wet 43 28 12 30 16 29 41 3 Dry 44 39 15 30 15 30 43 3 Wet 1 1 1 2 2 1 1 - Dry 1 1 1 2 2 1 2 2 Wet 18 25 31 47 61 12 16 31 Dry 15 13 34 48 61 14 17 25 Wet 7 3 9 4 1 2 3 1 Dry 6 3 10 5 2 0 3 3 Wet 11 23 27 2 1 41 14 42 Dry 15 25 28 2 1 42 14 50 Wet 0 0 - 0 0 1 0 4 Dry - 0 0 - 0 1 - 3 Wet 1 10 9 3 2 1 4 14 Dry 1 5 2 1 2 0 0 9 Wet - - - 0 - 0 0 - Dry - - - 0 - 0 0 - Wet - - - - - 0 - - Dry - - 0 - - 0 0 - Wet - 2 0 - 4 0 - - Dry - - 0 - 4 - - - Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Piped Water Protected Well Protected / Covered Spring District 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season Season Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well District 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Piped Water Other Tanker Truck Water Vendor Uncovered Rainwater Catchment Covered Rainwater Catchment Source Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 318 Bariadi Maswa Shinyanga R Kahama Bukombe Meatu Shinyanga UKishapu Wet 2,122 7,076 4,036 15,978 5,329 2,719 2,049 3,054 Dry 2,462 3,380 1,612 13,805 4,498 1,305 1,847 1,193 Wet 8,588 4,863 4,154 5,109 2,146 1,147 498 1,772 Dry 7,892 2,589 1,820 4,343 2,151 496 428 632 Wet 5,137 2,600 599 3,819 956 1,643 226 723 Dry 5,137 1,950 200 3,054 717 1,487 226 401 Wet 22,949 9,040 12,408 15,473 6,801 4,638 1,941 4,858 Dry 20,329 4,708 5,685 14,495 6,562 3,790 1,540 1,495 Wet 27,509 12,325 18,253 27,255 20,646 12,157 4,325 13,961 Dry 25,913 17,184 17,227 26,192 19,572 10,763 4,236 9,039 Wet 7,588 5,633 4,406 8,750 14,502 5,213 620 6,096 Dry 9,525 8,301 8,344 10,314 14,251 6,245 872 6,351 Wet 3,330 1,066 1,102 4,375 2,503 2,972 453 4,231 Dry 5,083 4,065 5,051 5,536 3,220 4,718 869 7,000 Wet 350 650 305 458 358 1,002 86 850 Dry 1,231 1,074 5,324 3,478 2,270 2,388 181 8,229 Wet - - - - - - - 80 Dry - - - - - 299 - 1,285 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga R Kahama Bukombe Meatu Shinyanga UKishapu Wet 3 16 9 20 10 9 20 9 Dry 3 8 4 17 8 4 18 3 Wet 11 11 9 6 4 4 5 5 Dry 10 6 4 5 4 2 4 2 Wet 7 6 1 5 2 5 2 2 Dry 7 5 0 4 1 5 2 1 Wet 30 21 27 19 13 15 19 14 Dry 26 11 13 18 12 12 15 4 Wet 35 28 40 34 39 39 42 39 Dry 33 40 38 32 37 34 42 25 Wet 10 13 10 11 27 17 6 17 Dry 12 19 18 13 27 20 9 18 Wet 4 2 2 5 5 9 4 12 Dry 7 9 11 7 6 15 9 20 Wet 0 2 1 1 1 3 1 2 Dry 2 2 12 4 4 8 2 23 Wet - - - - - - - 0 Dry - - - - - 1 - 4 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 319 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 347 1,703 502 3,116 1,424 737 774 1,129 Dry 844 581 505 2,701 1,190 162 729 233 Wet 14,526 7,415 6,404 18,498 7,824 3,762 1,140 6,305 Dry 10,690 3,631 2,788 13,888 6,156 2,480 954 3,136 Wet 9,781 4,535 6,337 12,756 3,778 2,323 1,089 3,981 Dry 8,546 3,455 3,125 10,587 3,181 1,543 868 1,636 Wet 26,034 11,048 15,193 26,116 20,944 7,041 3,943 10,150 Dry 21,313 8,789 10,558 23,480 18,435 5,434 3,369 6,300 Wet 8,561 2,922 4,645 4,607 3,323 4,100 1,232 1,977 Dry 7,466 2,491 4,245 5,188 3,437 3,536 1,202 1,008 Wet 2,573 3,438 3,736 2,416 1,307 1,528 243 857 Dry 2,768 2,356 1,191 2,609 2,496 1,894 273 553 Wet 15,750 12,190 8,445 13,708 14,641 12,001 1,777 11,224 Dry 25,945 21,949 22,851 22,764 18,344 16,443 2,804 22,759 Total Agricultural Households per District 77,572 43,252 45,263 81,217 53,240 31,492 10,198 35,624 Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Shinyanga Urban Kishapu Wet 0 4 1 4 3 2 8 3 Dry 1 1 1 3 2 1 7 1 Wet 19 17 14 23 15 12 11 18 Dry 14 8 6 17 12 8 9 9 Wet 13 10 14 16 7 7 11 11 Dry 11 8 7 13 6 5 9 5 Wet 34 26 34 32 39 22 39 28 Dry 27 20 23 29 35 17 33 18 Wet 11 7 10 6 6 13 12 6 Dry 10 6 9 6 6 11 12 3 Wet 3 8 8 3 2 5 2 2 Dry 4 5 3 3 5 6 3 2 Wet 20 28 19 17 27 38 17 32 Dry 33 51 50 28 34 52 27 64 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 320 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 714 9 1,607 20 1,715 21 561 7 956 12 2,310 28 71 1 239 3 8,173 2.2 Two 48,466 29 13,758 8 14,494 9 34,903 21 38,793 23 9,744 6 2,537 2 4,352 3 167,046 44.2 Three 28,038 14 27,886 14 28,952 14 45,609 23 13,492 7 19,229 10 7,527 4 30,870 15 201,603 53.4 Four 353 34 0 0 102 10 144 14 0 0 209 20 64 6 163 16 1,035 0.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 714 1 1,607 4 1,715 4 561 1 956 2 2,310 7 71 1 239 1 8,173 2.2 Two 48,466 62 13,758 32 14,494 32 34,903 43 38,793 73 9,744 31 2,537 25 4,352 12 167,046 44.2 Three 28,038 36 27,886 64 28,952 64 45,609 56 13,492 25 19,229 61 7,527 74 30,870 87 201,603 53.4 Four 353 0 0 0 102 0 144 0 0 0 209 1 64 1 163 0 1,035 0.3 Total 77,572 100 43,252 100 45,263 100 81,217 100 53,240 100 31,492 100 10,198 100 35,624 100 377,857 100.0 63 36 36 44 75 38 26 13 46 Bukombe Meatu Bariadi Maswa Shinyanga Rural Kahama One and Two Two Meals Per Day Bukombe Meatu Shinyanga Urban 34.12B Number of Households by Number of Meals the Household Normally Took per Day by District Kishapu Total Number of Meals per Day District Shinyanga Urban Kishapu 34.12A Number of Households by Number of Meals the Household Normally Took per Day by District Number of Meals per Day District Total Bariadi Maswa Shinyanga Rural Kahama Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 321 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 48,154 29 24,829 15 20,071 12 27,827 17 12,744 8 13,263 8 4,524 3 12,325 8 163,738 43.3 One 18,863 16 10,575 9 16,218 13 26,425 22 24,736 20 9,431 8 3,547 3 11,315 9 121,110 32.1 Two 7,940 12 5,003 8 7,083 11 19,653 30 10,688 16 6,828 10 1,383 2 7,879 12 66,457 17.6 Three 1,914 10 2,111 11 1,085 6 5,686 31 3,201 17 959 5 409 2 3,096 17 18,460 4.9 Four 353 8 521 11 302 7 829 18 1,407 30 589 13 266 6 362 8 4,629 1.2 Five 348 16 107 5 99 5 516 24 344 16 246 11 0 0 484 23 2,143 0.6 Six 0 0 0 0 102 38 0 0 119 45 0 0 46 17 0 0 268 0.1 Seven 0 0 107 10 303 29 280 27 0 0 177 17 23 2 163 15 1,052 0.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 48,154 62 24,829 57 20,071 44 27,827 34 12,744 24 13,263 42 4,524 44 12,325 35 163,738 43.3 One 18,863 24 10,575 24 16,218 36 26,425 33 24,736 46 9,431 30 3,547 35 11,315 32 121,110 32.1 Two 7,940 10 5,003 12 7,083 16 19,653 24 10,688 20 6,828 22 1,383 14 7,879 22 66,457 17.6 Three 1,914 2 2,111 5 1,085 2 5,686 7 3,201 6 959 3 409 4 3,096 9 18,460 4.9 Four 353 0 521 1 302 1 829 1 1,407 3 589 2 266 3 362 1 4,629 1.2 Five 348 0 107 0 99 0 516 1 344 1 246 1 0 0 484 1 2,143 0.6 Six 0 0 0 0 102 0 0 0 119 0 0 0 46 0 0 0 268 0.1 Seven 0 0 107 0 303 1 280 0 0 0 177 1 23 0 163 0 1,052 0.3 Total 77,572 100 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 34.13A Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Number of Days District Total Bariadi Shinyanga Urban Kishapu Maswa Number of Days District Bariadi Maswa Shinyanga Rural Meatu Shinyanga Rural Kahama Bukombe Meatu Total Kishapu Kahama Bukombe Shinyanga Urban 34.13B Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 322 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 40,053 47 33,048 11 30,037 11 47,995 1 7,625 1 19,647 20 4,819 9 19,103 9 202,328 53.5 One 15,442 45 6,223 13 7,786 12 18,589 2 24,634 2 6,311 15 3,351 11 7,779 11 90,113 23.8 Two 10,611 39 2,621 16 2,914 16 9,235 2 10,153 2 4,567 17 1,283 8 5,656 8 47,041 12.4 Three 7,104 28 511 18 2,214 20 3,770 3 5,835 3 419 21 458 7 2,146 7 22,457 5.9 Four 2,328 29 533 14 1,512 23 824 4 2,134 3 209 21 255 6 559 6 8,354 2.2 Five 974 16 208 26 295 25 669 6 2,268 4 127 16 0 7 230 7 4,772 1.3 Six 706 13 0 26 403 28 0 5 119 3 0 22 32 2 81 2 1,343 0.4 Seven 352 15 108 29 102 28 133 9 472 5 212 12 0 2 70 2 1,449 0.4 Total 77,572 33 43,252 17 45,263 19 81,217 3 53,240 3 31,492 18 10,198 7 35,624 7 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 15,693 12 8,379 7 17,625 14 42,528 34 17,954 14 7,041 6 3,360 3 13,306 11 125,885 33.3 Seldom 31,327 23 15,379 11 15,831 12 21,727 16 24,022 18 12,262 9 4,006 3 9,448 7 134,001 35.5 Sometimes 3,520 15 3,307 14 2,834 12 6,425 27 3,677 15 1,702 7 231 1 2,423 10 24,119 6.4 Often 13,496 25 11,129 20 6,962 13 3,643 7 4,855 9 5,706 10 1,508 3 7,763 14 55,062 14.6 Always 13,535 35 5,058 13 2,011 5 6,895 18 2,733 7 4,780 12 1,093 3 2,684 7 38,789 10.3 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 15,693 20 8,379 19 17,625 39 42,528 52 17,954 34 7,041 22 3,360 33 13,306 37 125,885 33.3 Seldom 31,327 40 15,379 36 15,831 35 21,727 27 24,022 45 12,262 39 4,006 39 9,448 27 134,001 35.5 Sometimes 3,520 5 3,307 8 2,834 6 6,425 8 3,677 7 1,702 5 231 2 2,423 7 24,119 6.4 Often 13,496 17 11,129 26 6,962 15 3,643 4 4,855 9 5,706 18 1,508 15 7,763 22 55,062 14.6 Always 13,535 17 5,058 12 2,011 4 6,895 8 2,733 5 4,780 15 1,093 11 2,684 8 38,789 10.3 Total 77,572 100 43,252 100 45,263 100 81,217 100 53,240 100 31,492 100 10,198 100 35,624 100 377,857 100.0 Bukombe Meatu Shinyanga Urban Kahama 34.15A Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Status of Food Satisfaction District Total Bariadi Maswa Shinyanga Rural Status of Food Satisfaction District Total Bariadi Maswa Shinyanga Rural Kahama Bukombe Meatu Kishapu Total Maswa Shinyanga Rural Kahama Bukombe Shinyanga Urban Shinyanga Urban 34.15B Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Kishapu Number of Days District Bariadi Meatu Kishapu 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report Appendix II 323 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 5,082 3 9,064 6 14,711 10 53,745 36 38,424 26 7,814 5 6,410 4 12,748 9 147,998 39.2 Sale of Livestock 3,028 16 1,403 8 6,851 37 2,506 14 597 3 2,314 12 741 4 1,076 6 18,516 4.9 Sale of Livestock Products 535 15 311 9 402 11 982 27 587 16 356 10 97 3 318 9 3,588 0.9 Sales of Cash Crops 39,674 33 27,434 23 1,703 1 13,909 12 6,550 5 17,179 14 125 0 13,686 11 120,261 31.8 Sale of Forest Products 1,064 27 108 3 1,009 26 337 9 597 15 549 14 54 1 161 4 3,879 1.0 Business Income 4,022 22 741 4 7,062 38 2,166 12 2,259 12 791 4 434 2 1,139 6 18,613 4.9 Wages & Salaries in Cash 2,178 28 1,026 13 786 10 1,182 15 239 3 857 11 532 7 971 12 7,770 2.1 Other Casual Cash Earnings 21,098 42 2,530 5 11,530 23 5,430 11 2,706 5 1,171 2 1,580 3 4,351 9 50,395 13.3 Cash Remittance 892 22 635 15 706 17 820 20 470 11 0 0 85 2 526 13 4,133 1.1 Fishing 0 0 0 0 504 63 0 0 0 0 128 16 0 0 162 20 794 0.2 not applicable 0 0 0 0 0 0 139 7 810 42 333 17 141 7 486 25 1,910 0.5 Total 77,572 21 43,252 11 45,263 12 81,217 21 53,240 14 31,492 8 10,198 3 35,624 9 377,857 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 49,428 234 10,796 427 7,831 68 23,036 424 18,127 670 8,751 748 2,405 152 5,055 116 125,429 248.9 Tiles 333 2 217 9 200 2 381 7 239 9 572 49 31 2 82 2 2,054 4.1 Concrete 0 0 0 0 0 0 123 2 119 4 0 0 0 0 0 0 243 0.5 Asbestos 0 0 0 0 0 0 0 0 0 0 244 21 0 0 814 19 1,058 2.1 Grass / Leaves 17,850 85 6,687 264 24,754 215 53,009 976 23,166 856 3,867 330 1,575 100 1,607 37 132,516 263.0 Grass & Mud 8,371 40 25,552 1,010 12,477 108 4,557 84 11,588 428 18,059 1,543 6,188 392 28,066 645 114,858 227.9 Other 1,590 8 0 0 0 0 110 2 0 0 0 0 0 0 0 0 1,700 3.4 Total Number of Households 77,572 21 43,252 1,710 45,263 393 81,217 1,496 53,240 1,967 31,492 2,690 10,198 645 35,624 819 377,857 749.8 Kahama Bukombe Shinyanga Urban Meatu Bukombe Meatu 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Cash Income District Total Bariadi Maswa Shinyanga Rural Kishapu Shinyanga Urban Kishapu 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year Roofing Materials District Total Bariadi Maswa Shinyanga Rural Kahama Tanzania Agriculture Sample Census 2003 – Shinyanga Regional Report | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vm: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vm: REGIONAL REPORT: SINGIDA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents ........................................................................................................................................................................................... i Acronyms........................................................................................................................................................................ iv Preface............................................................................................................................................................................... v Executive summary......................................................................................................................................................... vi Illustrations.................................................................................................................................................................... xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION....................................................................................................... 1 1.1 Introduction ..................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................ 1 1.3 Land Area......................................................................................................................................................... 1 1.4 Climate.............................................................................................................................................................. 1 1.4.1 Temperature........................................................................................................................................ 1 1.4.2 Rainfall................................................................................................................................................ 1 1.5 Population ........................................................................................................................................................ 1 1.6 Socio-economic Indicators.............................................................................................................................. 2 PART II: INTRODUCTION..................................................................................................................................... 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................ 3 2.2 Census Objectives............................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................... 4 2.4 Legal Authority of the National Sample Census of Agriculture................................................................ 5 2.5 Reference Period ............................................................................................................................................. 5 2.6 Census Methodology....................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................... 5 2.6.2 Tabulation Plan................................................................................................................................... 6 2.6.3 Sample Design.................................................................................................................................... 6 2.6.4 Questionnaire Design and Other Census Instruments ....................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments..................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators.......................................................................... 7 2.6.7 Information, Education and Communication (IEC) Campaign......................................................... 7 2.6.8 Household Listing............................................................................................................................... 8 2.6.9 Data Collection ................................................................................................................................... 8 2.6.10 Field Supervision and Consistency Checks ....................................................................................... 8 2.6.11 Data Processing .................................................................................................................................. 8 - Manual Editing.............................................................................................................................. 9 - Data Entry ..................................................................................................................................... 9 - Data Structure Formatting ............................................................................................................ 9 - Batch Validation ........................................................................................................................... 9 - Tabulations.................................................................................................................................... 9 - Analysis and Report Preparations ................................................................................................ 9 - Data Quality................................................................................................................................ 10 2.7 Funding Arrangements........................................................................................................................... 10 PART III: CENSUS RESULTS AND ANALYSIS................................................................................................. 11 3.1 Holding Characteristics................................................................................................................................ 11 3.1.1 Type of Holdings.............................................................................................................................. 11 3.1.2 Livelihood Activities/Source of Income.......................................................................................... 11 3.1.3 Sex and Age of Heads of Households.............................................................................................. 11 3.1.4 Number of Household Members...................................................................................................... 15 3.1.5 Level of Education............................................................................................................................ 15 - Literacy ....................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................... 15 - Litaracy Rates for Heads of Households.................................................................................... 15 - Educational Status....................................................................................................................... 16 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.1.6 Off-farm Income............................................................................................................................... 16 3.2 Land Use ..................................................................................................................................................... 17 3.2.1 Area of Land Utilised ....................................................................................................................... 17 3.2.2 Types of Land use............................................................................................................................. 18 3.3 Annual Crops and Vegetable Production................................................................................................... 18 3.3.1 Area Planted...................................................................................................................................... 18 3.3.2 Crop Importance............................................................................................................................... 20 3.3.3 Crop Types........................................................................................................................................ 20 3.3.4 Cereal Crop Production.................................................................................................................... 22 3.3.4.1 Maize .............................................................................................................................. 23 3.3.4.2 Sorghum.......................................................................................................................... 23 3.3.4.3 Other Cereals................................................................................................................... 24 3.3.5 Oil seeds and Oil nuts Production.................................................................................................... 24 3.3.5.1 Sunflower........................................................................................................................ 26 3.3.6 Pulse Crops Production ..................................................................................................................... 29 3.3.6.1 Beans............................................................................................................................... 29 3.3.7 Roots and Tuber Crops Production.................................................................................................. 30 3.3.7.1 Cassava........................................................................................................................... 30 3.3.7.2 Sweet potatoes............................................................................................................... 33 3.3.8 Fruits and Vegetables ........................................................................................................................ 34 3.3.8.1 Onions............................................................................................................................. 34 3.3.8.2 Tomatoes ........................................................................................................................ 34 3.4 Permanent Crops........................................................................................................................................... 36 3.4.1 Mango ......................................................................................................................................... 38 3.4.2 Banana ......................................................................................................................................... 39 3.3.9 Other Annual Crops Production....................................................................................................... 39 3.3.9.1 Cotton .............................................................................................................................. 39 3.3.9.2 Tobacco .......................................................................................................................... 39 3.5 Inputs/Implements Use................................................................................................................................. 42 3.5.1 Methods of land clearing................................................................................................................... 42 3.5.2 Methods of soil preparation............................................................................................................... 42 3.5.3 Improved seeds use........................................................................................................................... 43 3.5.4 Fertilizers use..................................................................................................................................... 44 3.5.4.1 Farm Yard Manure Use................................................................................................... 45 3.5.4.2 Inorganic Fertilizer Use.................................................................................................. 45 3.5.4.3 Compost Use .................................................................................................................. 45 3.5.5 Pesticide Use..................................................................................................................................... 48 3.5.5.1 Insecticide Use................................................................................................................ 49 3.5.5.2 Herbicide Use................................................................................................................. 50 3.5.5.3 Fungicide Use.................................................................................................................. 50 3.5.6 Harvesting Methods.......................................................................................................................... 50 3.5.7 Threshing Methods .......................................................................................................................... 50 3.6 Irrigation .................................................................................................................................................... 51 3.6.1 Area planted with annual crops and under irrigation........................................................................ 51 3.6.2 Sources of water used for irrigation................................................................................................. 53 3.6.3 Methods of obtaining water for irrigation......................................................................................... 54 3.6.4 Methods of water application .......................................................................................................... 54 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing .................................................................................................. 54 3.7.1 Crop Storage ..................................................................................................................................... 54 3.7.1.1 Method of Storage........................................................................................................... 55 3.7.1.2 Duration of Storage ......................................................................................................... 55 3.7.1.3 Purpose of Storage.......................................................................................................... 56 3.7.1.4 The Magnitude of Storage Loss..................................................................................... 56 3.7.2 Agro processing and by-products...................................................................................................... 56 3.7.2.1 Processing Methods........................................................................................................ 57 3.7.2.2 Main Agro-processing Products...................................................................................... 57 3.7.2.3 Main use of primary processed Products........................................................................ 58 3.7.2.4 Outlet for Sale of Processed Products............................................................................ 58 3.7.3 Crop Marketing.................................................................................................................................. 59 3.7.3.1 Main Marketing Problems............................................................................................... 59 3.7.3.2 Reasons for Not Selling................................................................................................... 59 3.8 Access to Crop Production Services............................................................................................................. 59 3.8.1 Access to Agricultural Credits .......................................................................................................... 60 3.8.1.1 Source of Agricultural Credits ....................................................................................... 60 3.8.1.2 Use of Agricultural Credits............................................................................................. 60 3.8.1.3 Reasons for not using agricultural credits...................................................................... 60 3.8.2 Crop Extension .................................................................................................................................. 61 3.8.2.1 Sources of crop extension messages.............................................................................. 61 3.8.2.2 Quality of extension ........................................................................................................ 61 3.9 Access to Inputs ............................................................................................................................................. 64 3.9.2 Inorganic Fertilisers .......................................................................................................................... 64 3.9.3 Improved Seeds ................................................................................................................................. 65 3.9.4 Insecticides and Fungicide ................................................................................................................ 65 3.10 Tree Planting................................................................................................................................................... 66 3.11 Irrigation and Erosion Control Facilities ................................................................................................... 66 3.12 Livestock Results........................................................................................................................................... 67 3.12.1 Cattle Production .............................................................................................................................. 67 3.12.1.1 Cattle Population............................................................................................................. 68 3.12.1.2 Herd size.......................................................................................................................... 68 3.12.1.3 Cattle Population Trend ................................................................................................. 68 3.12.1.4 Improved Cattle Breeds.................................................................................................. 68 3.12.2 Goat Production................................................................................................................................ 69 3.12.2.1 Goat Population.............................................................................................................. 69 3.12.2.2 Goat Herd Size ................................................................................................................ 69 3.12.2.3 Goat Breeds .................................................................................................................... 69 3.12.2.4 Goat Population Trend ................................................................................................... 69 3.12.3 Sheep Production.............................................................................................................................. 72 3.12.3.1 Sheep Population............................................................................................................ 72 3.12.3.2 Sheep Population Trend ................................................................................................. 72 3.12.4 Pig Production .................................................................................................................................. 73 3.12.4.1 Pig Population Trend...................................................................................................... 73 3.12.5 Chicken Production ........................................................................................................................... 73 3.12.5.1 Chicken Population ........................................................................................................ 73 3.12.5.2 Chicken Population Trend.............................................................................................. 73 TOC ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5.3 Chicken Flock Size.......................................................................................................... 73 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................ 73 3.12.6 Other Livestock ................................................................................................................................. 74 3.12.7 Pests and Parasites Incidences and Control ...................................................................................... 78 3.12.7.1 De-worming.................................................................................................................... 78 3.12.8 Access to Livestock Services ........................................................................................................... 78 3.12.8.1 Access to livestock extension Services.......................................................................... 78 3.12.8.2 Access to Veterinary Clinic ............................................................................................ 79 3.12.8.3 Access to village watering points/dam .......................................................................... 79 3.12.9 Animal Contribution to Crop Production......................................................................................... 80 3.12.9.1 Use of Draft Power......................................................................................................... 80 3.12.9.2 Use of Farm Yard Manure ............................................................................................. 80 3.12.9.4 Use of Compost ............................................................................................................ 80 3.12.10 Fish Farming...................................................................................................................................... 80 3.13 Poverty Indicators......................................................................................................................................... 81 3.13.1 Access to Infrastructure and Other Services..................................................................................... 81 3.13.2 Type of Toilets................................................................................................................................... 81 3.13.3 Household’s assets............................................................................................................................. 82 3.13.4 Sources of Light Energy.................................................................................................................... 82 3.13.5 Sources of Energy for Cooking......................................................................................................... 82 3.13.6 Roofing Materials............................................................................................................................. 82 3.13.7 Access to Drinking Water ................................................................................................................. 84 3.13.8 Food Consumption Pattern................................................................................................................ 85 3.13.8.1 Number of Meals per Day.............................................................................................. 85 3.13.8.2 Meat Consumption Frequencies...................................................................................... 85 3.13.8.3 Fish Consumption Frequencies...................................................................................... 85 3.13.9 Food Security.................................................................................................................................... 88 3.13.10 Main Source of Cash Income........................................................................................................... 88 PART IV: SINGIDA PROFILES .............................................................................................................................. 90 4.1 Region Profile ................................................................................................................................................. 90 4.2 District Profiles............................................................................................................................................... 90 4.2.1 Iramba ................................................................................................................................................ 90 4.2.2. Singida Rural ..................................................................................................................................... 92 4.2.3 Manyoni............................................................................................................................................. 94 4.2.4 Singida Urban .................................................................................................................................... 96 ACRONYMS __________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census v PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Singida region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in th e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Albina A Chuwa The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Singida region that were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Singida region and indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Singida region was 179,915 out of which 06,837 (53.8%) were involved in growing crops only, 516 (0.3%) rearing livestock only and 82,563 (45.9%) were involved in crop production as well as livestock keeping. In summary, Singida region had 179,400 households involved in crop production and 83,079 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off farm income, livestock keeping/herding, remittances, permanent crop farming and fishing/hunting The region had a literacy rate of 73 percent. The highest literacy rate was in Singida Urban district (81%) followed by Singida Rural district (78%), Iramba district (71%) and Manyoni district (66%). The literacy rate for the heads of households in the region was 66 percent. The number of heads of agricultural households with formal education in Singida region was 116,473 (65%), those without formal education were 63,442 (35%) and those with only adult education were 2,235 (1%). The majority of heads of agricultural households (62%) had primary level education whereas only 3 percent had post primary education. In Singida region 92,591 (51%) households had one household member each involved in off-farm income generating activity, 49,008 (27%) households had two household members each involved in off-farm income generating activities and 17,437 (10%) households had more than two household members each involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 463,150 ha. The regional average land area utilised for crop production per crop growing household was only 2.2 ha. This figure was higher than the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 321,419 hectares out of which 2,292 hectares (0.71%) were planted during dry season and 319,128 hectares (99.29%) during long rainy season. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii The planted area occupied by cereals was 243,745 ha (76.4% of the total area planted with annuals). This was followed by oil seeds and oil nuts (52,843 hectares, 16.6%), pulses (13,342 hectares, 4.2%), roots and tubers (5,724 hectares, 1.8%), cash crops (2,226 hectares, 0.7%) and fruit and vegetables (1,249 hectares, 0.4%). Maize Maize dominated the production of cereal crop in the region. The number of households growing maize in Singida region during the long rainy season was 132,667, (74% of the total crop growing households in the region during the long rainy season). The total production of maize during the long rainy season was 54,056 tonnes from a planted area of 135,482 hectares resulting in a yield of 0.4 t/ha. Other crops in order of their importance (based on area planted) were sorghum,bulrush millets,wheat, paddy and fingermillets. The average area planted with maize per maize growing household ranged from 0.84 hectares in Singida Rural district to 1.20 hectares in Iramba district. Iramba district had the largest planted area of maize (60,761 ha) followed by Singida Rural (42,787 ha), Manyoni (32,035 ha) and Singida Urban (1,694 ha). Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Singida region during the long rainy season was 82,809. This represented 46 percent of the total crop growing households in Singida region in the long rainy season. Oil Seeds The total production of oil seeds was 24,367 tonnes. The most cultivated oil seed crop was sunflower. The production for this crop was 21,002 tonnes, which constituted 86 percent of the total oil seeds production, followed by groundnuts 2,462 tonnes (10%) and simsim 887 tonnes (4%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 9,242 hectares which is 3 percent of the area planted with annual crops in the region. The most important permanent crop was mango which had a planted area of 3,784 ha (40 percent of the total area planted with permanent crops) followed by bananas 3,373 ha (36%) and guava 1,268 ha (14%). Improved Seeds The planted area using improved seeds was 62,511 ha which represents 20 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seeds was mainly in the long rainy season (95.5%) while in the short rainy season was only 0.5%. Use of Fertilizers The use of fertilizers on annual crops was very small with the application of fertilisers to a planted area of only 129,050 ha (40% of the total planted area in the region). The planted area without fertilizer for annual crops was 190,078 hectares representing 60 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 119,610 ha which represented 37.5 percent of the total planted area. This was followed by compost (5,952 ha, 4.6%). Inorganic fertilisers were used on a small area which represented only 2.7 percent of the area planted with fertilisers EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Irrigation In Singida region, the area of annual crops and vegetables under irrigation was 3,443 ha representing 1.1 percent of the total area planted. The district with the largest planted area under irrigation with annual crops was Manyoni (4,202 ha, 35% of the total irrigated planted area with annual crops in the region). This is closely followed by Singida Rural with (3,916 ha, 32%), Iramba (2,867 ha, 24%) and Singida Urban (1,113 ha, 9%). When expressed as a percentage of the total area planted in each district, Singida Urban had the highest with 10.2 percent of the planted area in the district under irrigation. This is followed by Manyoni (6.7%), Singida Rural (3.4%) and Iramba Crop Storage There were 179,391 crop growing households (14.7% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 115,361 households storing 8,366 tonnes as of 1st January 2004. This was followed by sorghum and millets (96,374 households, 5,413t), beans and pulses (15,765 households, 230t) and groundnuts/bambaranuts (4,894 households, 119t) and paddy (4,894 household, 387t). Other crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 81,720 which represented 45 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Manyoni (52%) followed by Singida Rural (50%) and Iramba (40%). Agricultural Credit In Singida region, few agricultural households (2,698, 1.5%) accessed credit, out of which 1,516 (56%) were male-headed households and 1,182 (44%) were female headed households. In Singida Urban district only female headed households got credit for agriculture purposes, whereas in Singida Rural district only male households accessed credit. In Manyoni and Iramba districts both male and female headed household’s accessed agricultural credit. Crop Extension Services The number of agricultural households that received crop extension was 86,702 (48% of total crop growing households in the region). Some districts have more access to extension services than others with Iramba district having a relatively high proportion of households that received crop extension messages (71.5%), followed by Singida Urban (36.9%), Singida Rural (36.8%) and Manyoni (33.8%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 15,529. This number represented 9 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Singida Rural district (11%) followed by Iramba (10%), Singida Urban (6%) and Manyoni (1%). (iii) Livestock and Poultry Production Cattle EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix The total number of cattle in the region was 1,257,159. Cattle were the dominant livestock in the region followed by goats, sheep and pigs. The region had 7.5 percent of the total cattle population on the Tanzanian Mainland. The number of indigenous cattle was 1,255,118 head (99.8% of the total number of cattle in the region), 1,115 (0.09%) were dairy breeds and only 925 (0.07%) were beef breeds. Goats The number of goat-rearing-households in the region was 60,387 (34% of all agricultural households) with a total of 684,420 goats giving an average of 11 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 39,179 (22% of all agricultural households) with a total of 309,938 sheep giving an average of 8 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,554 (1.4% of the total agricultural households) rearing about 6,375 pigs. This gave an average of 3 pigs per pig-rearing household. Chicken The number of households keeping chickens was 125,895 raising 1,658,178 chickens. This gives an average of 13 chickens per chicken-rearing household. In terms of total number of chickens in the country Singida ranked ninth out of the 21 Mainland regions. Use of Draft Power The region has 199,820 oxen that were used to cultivate 182,070 hectares of land. This represented only 8.9 percent of the total oxen found on the mainland. The largest area cultivated using oxen was found in Iramba district (105,194 ha, 58% of the total area cultivated using oxen). Fish Farming There was no fish farming in the region. iv) Poverty Indicators Availability of Toilets It was estimated that 88.7 percent of all rural agricultural households used the traditional pit latrines, 3.9 percent used flush toilets and 0.4 percent had improved pit latrines. The remaining 0.2 percent of households had other unspecified types of toilets. Households with no toilet facilities represented 6.8 percent of the total agriculture households in the region. Household Assets The radio was the most owned asset with 38.6% households owning it followed by bicycle (29.9%), iron (12.1%), wheelbarrow (4.4%), vehicle (0.8%), mobile phone (0.8%), television/video (0.4%), and landline phone (0.3%). Source of Lighting Energy EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x Wick lamp was the most common source of lighting energy in the region. About 72.8 percent of the total rural households used this source of energy followed by hurricane lamp (17.5%), firewood (4.9%), pressure lamp (3.9%), mains electricity (0.7%), solar (0.1%) and gas or biogas (0.6%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.1 percent of all rural agricultural households. The second most common source of energy for cooking was crop residues (2.3%) and charcoal (1.7%). The rest of energy sources accounted for 0.9 percent. These were solar energy (0.4%), mains electricity (0.2%), paraffin/kerosene (0.1%), bottled gas (0.1%) and livestock dung (0.1%). Roofing Materials The most used roofing material (for the main dwelling) was grass and mud and it was used by 73.2 percent of the rural agricultural households. This was followed by iron sheets (20.7%). Other roofing materials were grass/leaves (5.4%), asbestos (0.2%), tiles (0.1%) and others (0.3%). Number of Meals per Day About 66.5 percent of the holders in the region took two meals per day, 30.3 percent took three meals, 3.0 percent took one meal and 0.2 percent took four meals. Food Security In Singida region, 61,025 households (34% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 9,646 (5%) said they sometimes experience problems, 17 percent often experienced problems and 14 percent always had problems in satisfying the household food requirement. About 31 percent of the agricultural households said they did not experience any food sufficiency problems Main Source of Cash Income Casual cash earnings were the main cash income earning activity reported by 29.6 percent of all rural agricultural households. The second main cash income earning activity was sales of livestock (16.5%) followed by selling of cash crops (16.2%), businesses (10.7%) and sales of food crops (9.1%). Only 6.6% of smallholder households reported the cash remittances as their main source of income, followed by forest products (6.5%) and wages and salaries (3.1%) ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size .............................................................................................................................................. 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season...................................................................................... 20 3.3 Area, Production and Yield of Oil seeds and Oil nuts by Season...................................................................... 24 3.4 Area, Production and Yield of Pulses by Season ................................................................................................26 3.5 Area, Production and Yield of Roots and Tuber Crops by Season.................................................................... 30 3.6 Area, Production and Yield of Fruits and Vegetables by Season ...................................................................... 34 3.7 Area, Production and Yield of Annual Cash Crops by Season.......................................................................... 39 3.8 Land Clearing Methods....................................................................................................................................... 42 3.9 Planted Area by Type of Fertiliser Use and District – Long Rainy Season ...................................................... 43 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District - Long Rainy Season ............................................................................................................................................56 3.11 Number of Households Storing Crops by Estimated Storage Loss and District ............................................... 59 3.12 Reasons for Not Selling Crop Produce............................................................................................................... 59 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 59 3.14 Access to Inputs....................................................................................................................................................64 3.15 Number of Households and Chickens Raised by Flock Size..............................................................................74 3.16 Number of Other Livestock by Type of Livestock and District ........................................................................ 74 3.17 Mean distances from holders dwellings to infrastructure and services by districts ...........................................81 3.18 Number of Households by Number of meals the Household normally has per Day and District .................... 85 List of Charts 3.1 Agricultural Households by Type of Holdings................................................................................................... 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 11 3.3 Percentage Distribution of Population by Age and Sex in 2003........................................................................ 15 3.4 Percentage Literacy Level of Household Members by District......................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District.............................................................................. 15 3.6 Percentage of Person Aged 5 years and above by District and Educational Status .......................................... 16 3.7 Percentage of Population Aged 5 years and Above by District and Education Status.............................................................................................................................. 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 16 3.9 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off farm activities............................................................................................................. 17 3.10 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities............................................................................................................ 17 3.11 Utilized and Usable Land per Household by District......................................................................................... 17 3.12 Land Area by Type of Land Use......................................................................................................................... 18 3.13 Area Planted with Annual Crops by Season (hectares)...................................................................................... 18 3.14 Area Planted with Annual Crops during Long Rainy Season and District.........................................................18 3.15 Area Planted with Annual Crops per Household during Long Rainy Season and District............................... 19 3.16 Planted Area (ha) for the Main Annual Crops.................................................................................................... 19 3.17a Planted Area (ha) per Household by Selected Crops ......................................................................................... 19 3.17b Percentage Distribution of Area Planted with Annual Crops by Crop Type..................................................... 20 3.18 Area planted with Annual Crops by Crop Type and Season.............................................................................. 20 3.19 Area Planted and Yield of Major Cereal Crops.................................................................................................. 20 3.20 Time Series Data on Maize Production – Singida Region................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District .......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Singida Region...................................................................... 23 3.23 Total Planted Area and Area of Sorghum per Household by District ................................................................23 3.24 Time Series Data on Sorghum Production – Singida Region............................................................................ 23 3.25 Time Series of Sorghum Planted Area and Yield – SGD Region.......................................................................24 3.26 Area Planted With Bulrush millets, Finger Millet and Paddy by District ..........................................................24 3.27 Area Planted and Yield of Major Oil seeds and oil nuts.....................................................................................24 3.28 Time series data on Sunflower production – Singida Region.............................................................................24 3.29 Percent of Sunflower Planted Area and percent of Total Land with Sunflower by District..............................26 3.30 Area Planted per sunflower growing households by District (Long rainy Season Only) ................................. 26 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.31 Area Planted and Yield of Major Pulses crops................................................................................................... 29 3.32 Percent of Bean Planted Area and Percent of Total Land with Beans by District ............................................ 29 3.33 Area Planted per Bean Growing Household by District (Long Rainy Season Only)........................................ 29 3.34 Time Series Data on Bean Production – Singida Region................................................................................... 29 3.35 Time Series of Beans Planted Area and Yield - Singida.....................................................................................30 3.36 Area Planted with Cassava during the Census/Survey Year.............................................................................. 30 3.37 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District.................................... 33 3.38 Cassava Planted Area per Cassava Growing Households by District ............................................................... 33 3.39 Sweet Potatoes: Total Area Planted and Planted Area per Household by District............................................ 33 3.40 Sweet Potatoes Planted Area per Sweet Potatoes Growing Households by District......................................... 33 3.41 Area Planted and Yield of Fruit and Vegetables................................................................................................ 34 3.42 Number of Households Growing Onion by District (Long Rainy Season) ...................................................... 34 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District ...........................................36 3.44 Area Planted per Onion Growing Household by District (Long Rainy Season Only)...................................... 36 3.45 Percent of Tomatoes Planted Area and Percent of Total Land with Tomatoes by District............................... 36 3.46 Area planted with Annual Cash Crops ............................................................................................................... 38 3.47 Area Planted (ha) with Main Perennial Crops.....................................................................................................38 3.48 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 38 3.49 Percent of Area Planted with Mango and Average Planted Area per Household by District........................... 38 3.50 Percent of Area Planted with Banana and Average Planted Area per Household by District .......................... 39 3.51a Planted Area with Other Crops (Cash Crops.......................................................................................................39 3.51b Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District................................... 39 3.51c Area Planted with Annual Cops by Method of Land clearing During the Long Rainy Season........................ 42 3.52 Area Cultivated by Cultivation Method.............................................................................................................. 42 3.53 Area Cultivated by Method of Cultivation and District......................................................................................43 3.54 Planted Area with Improved Seed by Crop Type .............................................................................................. 43 3.55 Planted Area with Improved Seed by Crop Type............................................................................................... 43 3.56 Percentage of Crop Type Planted Area with Improved Seed – Annuals............................................................43 3.57 Area of Fertilizer Application by Type of Fertilizer ...........................................................................................44 3.58 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 44 3.59 Planted Area with Farm Yard Manure by Crop Type - Singida ........................................................................ 45 3.60 Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals .................................................... 45 3.61 Proportion of Planted Area Applied with Farm Yard Manure by District .........................................................45 3.62 Planted Area with Inorganic Fertiliser by Crop type – Singida......................................................................... 45 3.63 Percentage of Planted Area with Inorganic Fertiliser by Crop Type................................................................. 48 3.64 Proportion of Planted Area Applied with Inorganic Fertiliser by District......................................................... 48 3.65 Planted Area with Compost by Crop Type......................................................................................................... 48 3.66 Percentage of Planted Area with Compost by Crop Type ................................................................................. 48 3.67 Proportion of Planted Area Applied with Compost by District......................................................................... 48 3.68 Planted area (ha) by Pesticide use....................................................................................................................... 49 3.69 Planted Area applied with Insecticides by Crop Type ........................................................................................49 3.70 Percentage of Crop Type Planted Area applied with insecticides ..................................................................... 49 3.71 Percent of Planted Area applied with Insecticides by District - Singida ........................................................... 49 3.72 Planted Area applied with herbicides by Crop Type...........................................................................................50 3.73 Percentage of Crop Type Planted Area applied with herbicides........................................................................ 50 3.74 Proportion of Planted Area applied with Herbicides by District – Singida Region.......................................... 50 3.75 Planted Area applied with Fungicides by Crop Type......................................................................................... 50 3.76 Percentage of Crop Type Planted Area applied with Fungicides ...................................................................... 51 3.77 Proportion of Planted Area applied with Fungicides by District – Singida region ........................................... 51 3.78 Area of Irrigated Land..........................................................................................................................................51 3.79 Irrigated Area and Percentage of Irrigated Area by District............................................................................ 53 3.80 Time Series of Households with Irrigation – Singida ........................................................................................ 53 8.81 Number of Households with Irrigation by Source of Water.............................................................................. 53 3.82 Number of Households by Method of Obtaining Irrigation Water.....................................................................54 3.83 Number of Households with Irrigation by Method of Field Application.......................................................... 54 3.84 Number of Households and Quantity Stored by Crop Type – Singida Region................................................. 54 3.85 Number of households by Storage Methods - Singida....................................................................................... 55 3.86 Number of households by method of storage and District (based on the most important household crop)......55 3.87 Normal Length of Storage for Selected Crops ................................................................................................... 55 3.88 Quantity of Maize Produced (tonnes), Stored (tones) and Percent Stored by District...................................... 56 3.89 Number of Households by Purpose of Storage and Crop Type......................................................................... 56 3.90 Percentage of Households Processing Crops by District ................................................................................... 56 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.91 Percent of Households Processing Crops by District......................................................................................... 56 3.92 Percent of Crop Processing Households by Method of Processing................................................................... 57 3.93 Percent of Households by Type of Main Processed Product ............................................................................. 57 3.94 Number of Households by Type of Bi-product.................................................................................................. 57 3.95 Use of Processed Product.....................................................................................................................................58 3.96 Percentage of Households Selling Processed Crops by District........................................................................ 58 3.97 Location of Sale of Processed Products............................................................................................................ . 58 Percentage of Households Selling Processed Products by Outlet for Sale and District.................................... 58 3.99 Number of Crop Growing Households Selling Crops by District ..................................................................... 59 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ................... 59 3.101 Percentage Distribution of Households Receiving Credit by Main Sources......................................................60 3.102 Number of Households Receiving Credit by Main Source of Credit and District ............................................ 60 3.103 Proportion of Households who Received Credit by Main Purpose of the Credit.............................................. 60 3.104 Reasons for not using Credit............................................................................................................................... 60 3.105 Number of Households Receiving Extension Advice.........................................................................................61 3.106 Number of Households that Received Extension by District............................................................................. 61 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................. 61 3.108 Number of Households Receiving Extension by Quality of Services ............................................................... 61 3.109 Number of Households by Source of Inorganic Fertiliser ..................................................................................64 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser...................................................64 3.111 Number of Households by Source of Improved Seed.........................................................................................65 3.112 Number of Households reporting Distance to Improved Seed .......................................................................... 65 3.113 Number of Households by Source of Insecticide/Fungicide.............................................................................. 65 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides........................................... 65 3.115 Number of Households with Planted Trees by District...................................................................................... 66 3.116 Number of Planted Trees by Species...................................................................................................................66 3.117 Number of Trees Planted by Smallholders by Species and District ...................................................................66 3.118 Number of Trees Planted by Location................................................................................................................ 66 3.119 Number of Households by purpose of Planted Trees......................................................................................... 66 3.120 Number of Households with Erosion Control/Water Harvesting Facilities ...................................................... 67 3.121 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............67 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility.................................................. 67 3.123 Total Number of Cattle ('000') by District.......................................................................................................... 68 3.124 Numbers of Cattle by Type and District............................................................................................................. 68 3.125 Cattle Population Trend ...................................................................................................................................... 68 3.126 Dairy Cattle Population Trend............................................................................................................................ 69 3.127 Total Number of Goats ('000') by District.......................................................................................................... 69 3.128 Goat Population Trend.........................................................................................................................................69 3.129 Total Number of Sheep by District..................................................................................................................... 72 3.130 Sheep Population Trend...................................................................................................................................... 72 3.131 Total Number of Pigs by District........................................................................................................................ 72 3.132 Pig Population Trend........................................................................................................................................... 73 3.133 Total Number of Chicken by District ................................................................................................................. 73 3.134 Chicken Population Trend .................................................................................................................................. 73 3.135 Number of Improved Chicken by Type and District...........................................................................................74 3.136 Layer Population Trend....................................................................................................................................... 74 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 78 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 78 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........78 3.140 Number of Households by Distance to Veterinary Clinic.................................................................................. 79 3.141 Number of Households by Distance to Veterinary Clinic and District.............................................................. 79 3.142 Number of Households by Distance to Village Watering Point ........................................................................ 79 3.143 Number of Households by Distance to Watering Point and District................................................................. 79 3.144 Number of Households using Draft Animals ..................................................................................................... 80 3.145 Number of Households using Draft Animals by District....................................................................................80 3.146 Number of Households using Organic Fertiliser................................................................................................ 80 3.147 Area of Application of Organic Fertiliser by District ........................................................................................ 80 3.148 Agricultural Households by Type of Toilet Facility .......................................................................................... 81 3.149 Percentage Distribution of Households Owning the Assets................................................................................82 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................82 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking ..............................................82 3.152 Percentage Distribution of Households by Type of Roofing Material .............................................................. 84 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.153 Percentage Distribution of Households With Grass/Mud Roofs by District......................................................84 3.154 Percentage of Households by Main Source of Drinking Water and Season...................................................... 84 3.155 Percentage of Households by Distance to Main Source of Water and Season...................................................84 3.156 Number of Agriculture Households by Number of Meals per day.................................................................... 85 3.157 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season... 85 3.158 Percent Distribution of the Number of Households by Main Source of Income............................................... 88 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District......................................................... 12 3.3 Number of Crop Growing Households by District............................................................................................. 13 3.4 Percent of Crop Growing Households by District.............................................................................................. 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District........................................... 14 3.6 Percent of Crop and Livestock Households by District ..................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ......................................................................... 21 3.8 Total Planted Area (annual crops) by District.....................................................................................................21 3.9 Area planted and Percentage During the Short Rainy Season by District......................................................... 22 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................22 3.11 Planted Area and Yield of Maize by District ......................................................................................................25 3.12 Area Planted per Maize Growing Household..................................................................................................... 25 3.13 Planted Area and Yield of Sorghum by District..................................................................................................27 3.14 Area Planted per Sorghum Growing Household.................................................................................................27 3.15 Planted Area and Yield of Sunflower by District............................................................................................... 28 3.16 Area Planted per Sunflower Growing Household...............................................................................................28 3.17 Planted Area and Yield of Beans by District...................................................................................................... 31 3.18 Area Planted per Beans Growing Household..................................................................................................... 31 3.19 Planted Area and Yield of Cassava by District .................................................................................................. 35 3.20 Area Planted per Cassava Growing Household.................................................................................................. 35 3.21 Planted Area and Yield of Onion by District ..................................................................................................... 37 3.22 Area Planted per Onion Growing Household..................................................................................................... 37 3.25 Planted Area and Yield of Mango by District.................................................................................................... 40 3.26 Area Planted per Mango Growing Household ................................................................................................... 40 3.27 Planted Area and Yield of Banana by District ................................................................................................... 41 3.28 Area Planted per Banana Growing Household................................................................................................... 41 3.29 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................. 46 3.30 Area Planted and Percent of Total Planted Area with Irrigation by District ..................................................... 46 3.31 Percent of households storing crops for 3 to 6 weeks by district....................................................................... 47 3.32 Number of Households and Percent of Total Households Selling Crops by District........................................ 47 3.33 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .... 52 3.34 Number and Percent of Crop Growing Households using Improved Seed by District .....................................52 3.35 Number and percent of smallholder planted trees by district............................................................................. 72 3.36 Number and Percent of Households with water Harvesting Bunds by District................................................. 72 3.37 Cattle population by District as of 1st Octobers 2003.........................................................................................62 3.38 Cattle Density by District as of 1st October 2003...............................................................................................62 3.39 Goat population by District as of 1st Octobers 2003 ..........................................................................................63 3.40 Goat Density by District as of 1st October 2003.................................................................................................63 3.41 Sheep population by District as of 1st Octobers 2003 ....................................................................................... 73 3.42 Sheep Density by District as of 1st October 2003...............................................................................................73 3.43 Pig population by District as of 1st Octobers 2003.............................................................................................70 3.44 Pig Density by District as of 1st October 2003 ...................................................................................................70 3.45 Number of Chickens by District as of 1st October 2003 ....................................................................................75 3.46 Density of Chickens by District as of 1st October 2003.................................................................................... 75 3.47 Number and Percent of Households Infected with Ticks by District ................................................................ 83 3.48 Number and Percent of Households Using Draft Animals by District...............................................................76 3.49 Number and Percent of Households Using Farm Yard Manure by District...................................................... 76 3.50 Number and Percent of Households using Compost by District.........................................................................76 3.51 Number and Percent of Households without Toilets by District ........................................................................77 3.52 Number and Percent of Households using Grass/Leaves for roofing material by District ................................83 3.53 Number and Percent of Households eating 3 meals per day by District ............................................................83 3.54 Number and Percent of Households eating Meat Once per Week by District ...................................................86 3.55 Number and Percent of Households eating Fish Once per Week by District.................................................... 86 ILLUSTRATIONS ___________________________________________________________________________________________________________________________ _ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.56 Number and percent of Households Reporting food insufficiency by District ..................................................87 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Singida region is situated in Central Tanzania. It lies between longitudes 330 27” 5’ and 350 26” east of Greenwich, and latitudes 30 52” and 70 34” south of the equator. Singida town is the regional headquarter. Arusha region bounds the region to the north, Dodoma region to the east, Mbeya and Iringa regions to the south, Tabora region to the west and Shinyanga to the northwest. The region comprises four districts namely Iramba, Singida Rural, Manyoni and Singida Urban. The region headquarters is located in Singida Urban District. 1.4 Land Area Singida region is divided into three administrative districts with three districts with three district councils and one town council namely: Iramba, Singida Rural, Manyoni and Singida Urban. The three districts cover an area of 49,341 square kilometers, equivalent to about six per cent of the total land area of Tanzania Mainland. 1.4 Climate 1.4.1 Temperature Temperature in the region ranges between 150C and 300C depending on season and altitude. The coldest period in the year is July while the hottest period is in October and November. 1.4.2 Rainfall The average annual rainfall ranges between 500-800 millimeters. In normal circumstances, rainfall usually takes place from mid-November ending in April or early May every year. 1.5 Population According to the 2002 Population and Housing Census, there were 1,090,758 inhabitants in Singida region. The population of Singida region ranked 17th out of the 21 regions in Tanzania. 1.6 Socio - Economic Indicators • The contributed about 154,719 million shillings (4%) to Gross Domestic Product (GDP) at current prices in 1998. • Tha main cash crops in the region include cotton and tobacco. Cattle, Goats and Chicken have a significant contribution to GDP. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 2 • The road network is not well developed in Singida region despite the fact that, six regions around it. It has a road network with a total of 3,237.5 kms distributed in three criteria according to types of road surface. The tarmac road covers 15.5 kms, earth roads 2,534.5 kms and 687.5 kms. • The region is served by telephone, telefax and telex services. Also, the region has three post offices with some sub post offices. • The central railway line crosses the region in the southern part of Manyoni district. This line is very crucial economically to Singida region since it serves directly Kintiku, Makutopora, Saranda, Manyoni and itigi villages. Other villages served are Aghondi, Kitaraka and Kalangasi. This line serves passengers and transports goods and livestock (i.e cattle) to potential markets, particularly Dar es Salaam. There is also an extension of railway line from Manyoni to Singida region headquarters. • There is no airport in the region; hence there are no regular commercial flights. However, there are several privete airstrips, which cater for light air craft mainly for emergency cases such as flying doctors. There are three airstrips in Manyoni, two in Singida and one in Iramba district. The region is famous for producing both food and cash crops. The main food crops produced in Singida region include: maize, sorghum, bulrush Millets and finger Millets. The main cash crops include cotton and tobacco. Livestock keeping is also an important economic activity in the region. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from SINGIDA region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 • Fish farming • Livestock extension • Labour use • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,SINGIDA, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the census results of the census data for Singida region which are based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous censuses and surveys more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Singida region was 179,915. The largest number of agriculture households was in Singida Rural 73,197 followed by Iramba 62,528, Manyoni 33,065 and Singida Urban 11,125. (Map 3.1) At district level, the highest density of Household (50/km2) was found in Singida Urban and Iramba for each district (Map 3.2). Most households 96,837 (53.8%) were involved in growing crops only, 516 (0.3%) rearing livestock only, 82,563 (45.9%) were involved in crop production as well as livestock keeping and pastoralist were not found in the region (Chart 3.1) (Maps 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Singida region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by tree/forest resources, off farm income, livestock keeping/herding, remittances, permanent crop farming and fishing/hunting (Table 3.1). 3.1.3 Sex and Age of Heads of Households The number of male-headed agricultural households in Singida region was 139,553 (78% of the total regional agricultural households) whilst the number of female-headed households it was 40,362 (22% of the total regional agricultural households). The mean age of household heads was 47 years (45 years for male heads and 51 years for female heads) (Chart 3.2). Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 1 6 4 3 5 7 2 Singida R 1 5 4 3 6 7 2 Manyoni 3 6 4 1 5 7 2 Singida Urb 1 6 2 3 5 7 4 Total 1 6 4 3 5 7 2 Chart 3.1 Agriculture Households by Type - Singida Crops and Livestock 45.9% Crops Only 53.8% Livestock Only 0.3% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Singida Urban Singida Rural Manyoni 26 16 23 Iramba 3 21.4 to 26 16.8 to 21.4 12.2 to 16.8 7.6 to 12.2 3 to 7.6 Singida Urban Singida Rural Manyoni 11,125 73,197 62,528 33,065 Iramba 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS Tanzania Agriculture Sample Census Map 3.01 SINGIDA Total Number of Ariculture Households by District. Number of Ariculture Households Number of Ariculture Households Map 3.02 SINGIDA Number of Agriculture Households per Square Kilometer of Land by District. Number of Agriculture Households per Square Km Number of Agriculture Households per Square Km 12 Singida Urban Singida Rural 11,125 62,255 33,065 72,954 Manyoni Iramba 50,000 to 80,000 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 Singida Rural Singida Urban 100 99.7 100 99.6 Manyoni Iramba 99.9 to 100 99.8 to 99.9 99.7 to 99.8 99.6 to 99.7 99.5 to 99.6 13 Tanzania Agriculture Sample Census Map 3.03 SINGIDA Number of Crop Growing Households by District. Number of Crop Growing Households Number of Crop Growing Households Map 3.04 SINGIDA Percent of Crop Growing Household by District Percent of Crop Growing Households Percent of Crop Growing Households Iramba Singida Urban Singida Rural 51% 50% 54% 18% Manyoni 50 to 60 40 to 50 30 to 40 20 to 30 10 to 20 Singida Urban Singida Rural Manyoni 26 22 3 16 Iramba 21.4 to 26 16.8 to 21.4 12.2 to 16.8 7.6 to 12.2 3 to 7.6 14 Tanzania Agriculture Sample Census Map 3.05 SINGIDA Number of Crop Growing Households Per Square Kilometer of Land by District. Number of Crop Growing Households Per Square Km Number of Crop Growing Households Per Square Km Map 3.06 SINGIDA Percent of Crop and Livestock Households by District Percent of Crop and Livestock Households Percent of Crop and Livestock Households RESULTS RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Singida region had a total rural agricultural population of 936,792 of which 463,874 (49.5%) were males and 472,918 (50.5) were females. Whereas age group 0-14 constituted 45 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Singida region had an average household size of 5 with Iramba district having the highest household size of 6 whilst other districts had the regional average household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Singida region had a total literacy rate of 73 percent. The highest literacy rate was found in Singida Urban district (81%) followed by Singida Rural district (78%), Iramba district (71%) and Manyoni district (66%). (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 66.1 percent. The literacy rates among the male and female heads of households were 74 and 40 percent respectively. Male head of household literacy rate was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Manyoni (69.3%) followed by Singida Urban (67.9%), Singida Rural (66.2%), and Iramba (64%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - Singida 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 100 Singida Urb Singida Rur Iramba Manyoni District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - Singida 0.0 25.0 50.0 75.0 100.0 Iramba Singida Rur Manyoni Singida Urb District Percent Male Female Total RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 38.5 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 34.9 percent were still attending school. Those who have never attended school were 26.6 percent (Chart 3.6). Agricultural households in Singida Urban district had the highest percentage (40.3%) of population aged 5 years and above who had completed different levels of education. This was followed by Singida Rural (39.4%), Iramba (37.8%) and Manyoni (37.1%). The number of heads of agricultural households with formal education in Singida region was 116,473 (65%), those without formal education were 63,442 (35%) and those with only adult education were 2,235 (1%). The majority of heads of agricultural households (62%) had primary level education whereas only 3 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Singida region, Singida Rural district had the highest percentages (40% for primary and 45% for secondary). This was followed by Iramba (34% primary and 29% secondary), Manyoni (19% primary and 18% secondary) and Singida Urban (6% primary and 8% secondary) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Singida with 88 percent of households having at least one member with off-farm income. In Singida region 92,591 households (51%) had only one member aged 5 and above involved in only one off-farm income generating activity, 49,008 households (27%) had two members involved in off-farm income generating activities and 17,437 households (10%) had more than two members involved in off-farm income generating activities. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 38.5% Never Attended 26.6% Attending School 34.9% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 Iramba Singida Rur Manyoni Singida Urb District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 1% Post Primary Education 3% No Education 34% Primary Education 62% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 17 Manyoni district had the highest percentage of agriculture households with off-farm income (over 99.5% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Singida Rural (89.9%), Singida Urban (82.2%) and Iramba (81.9%). The district with the highest percentages of agriculture households with more than one member with off-farm income was Iramba (55%). Singida Rural district had very few households with more than one member having off-farm income (27%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country, however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 463,150 ha. The Regional average land area utilised for agriculture per household was only 2.2 ha. This figure is higher than the national average which is estimated at 2.0 hectares. Eighty nine percent of the total land available to smallholders was utilised. Only 11 percent of usable land available to smallholders was not used (Chart 3.11). Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Iramba Singida Rur Manyoni Singida Urb Districts Area/household 0 25 50 75 100 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.9 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities One Off Farm Income, 92591, 51% More than Tw o Off Farm Income, 17437, 10% Tw o Off Farm Income, 49008, 27% None, 20879, 12% Chart 3.10 Percentage Distribution of Households by Number of Household members Aged 5 Years and Above who had Off-farm Activities 0% 20% 40% 60% 80% 100% Iramba Singida Rur Manyoni Singida Urb Districts Percent Mo re than Two Two One No ne RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 18 Large differences in land area utilised per household exist between districts with Manyoni (2.6ha), Iramba ((2.5ha), Singida Rural (2.0ha) and Singida Urban (1.3ha). The percentage utilized of the usable land per household is highest in Singida Rural (94%) and lowest in Manyoni (77%). Eighty nine percent of the total land available to smallholders was utilised. Only 11 percent of usable land available to smallholders was not used (Chart 3.11 and Map.7). 3.2.2 Types of Land Use The area of land under temporary mono crop was 273,971 hectares (59.2% of the total land available to smallholders in Singida), followed by temporary mixed crop (48,992 ha, 10.6%), area under fallow (37,900 ha, 8.2%), uncultivated usable land (37,134 ha, 8.0%), area under pasture (18,758 ha, 4.0%), area under natural bush (14,301 ha, 3.1%), unusable area (11,246 ha, 2.4%), permanent/annual mix (8,782 ha, 1.9%), area rented to others (5,344 ha, 1.2%), area under permanent mixed crops (3,488 ha, 0.8%), area under permanent mono crops (2,026 ha, 0.4%) and area planed trees (1,209 ha, 0.3%). 3.3 Annual Crops and Vegetable Production Singida region has one rainy season; however some crops were grown during the dry season of year by using irrigation/wet areas. A total of 2,292 ha were cultivated during dry season. The quantity of crops produced during the long rainy season will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 321,419 hectares out of which 2,292 hectares (0.71%) were planted during dry season and 319,128 hectares (99.29%) during long rainy season. The average areas planted per household during the dry and long rainy seasons were 1.1 and 0.8 ha respectively (Chart 3.13). The district with the largest area planted per household (during long rainy season) were Iramba (0.9 ha) followed by Manyoni (0.8 ha), Singida Rural (0.7 ha) and Singida Urban (0.5 ha) (Chart 3.14 and Map.8). The planted area occupied by cereals was 243,745 ha (76.4% of the total area planted with annuals). This was followed by oil seeds and oil nuts (52,843 hectares, Chart 3.12 Land Area by Type of Use 0.3 0.4 0.8 1.2 1.9 2.4 3.1 4.1 8.0 8.2 59.2 10.6 0 50000 100000 150000 200000 250000 300000 Planted Trees Permanent Mono Crops Permanent Mixed Crops Rented to Others Permanent / Annual Mix Unusable Natural Bush Pasture Uncultivated Usable Land Fallow Temporary Mixed Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.14 Area Planted with Annual Crops During Long Rainy Season and District 0 30000 60000 90000 120000 150000 Iramba Singida Rur Manyoni Singida Urb District Planted Area (ha) Long Rainy Season Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 319128, 99.3% Dry Season, 2,292, 0.7% Dry Season Long Rainy Season RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 19 16.6%), pulses (13,342 hectares, 4.2%), roots and tubers (5,724 hectares, 1.8%), cash crops (2,226 hectares, 0.7%) and fruit and vegetables (1,249 hectares, 0.4%). The average area planted per household during the long rainy season in Singida region was 1.8 hectares, however, there were large district differences. Iramba had the largest planted area per household (2.1 ha) followed by Manyoni (1.9 ha), Singida Rural (1.6 ha) and Singida Urban (1.0 ha) (Chart 3.15 and Map.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of crops regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Singida region and it had a planted area 2 times greater than Sorghum, which had the second largest planted area. The area planted with maize constitutes 43 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are sorghum, sunflower, bulrush Millets, groundnuts and beans (Chart 3.16). Chart 3.17 shows the area planted per household growing selected crops. Households that grow Irish potatoes, cotton and chick peas have larger planted areas per household than other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Singida region. The area planted with cereals was 243,745 ha (76.4% of the total planted area), followed by oil seeds and oil nuts with 52,843 ha (16.6%), pulses 13,342 ha (4.2%), roots and tubers 5,724 ha (1.8%), cash crops 2,226 ha (0.7%) and fruits and vegetables 1,249 ha (0.4%) (Chart 3.17b) Chart 3.15 Area Planted with Annual Crops per Household during Long Rainy Season and District 0.00 0.25 0.50 0.75 1.00 Iramba Manyoni Singida Rur Singida Urb District Area Planted (ha) Long Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops - Singida 0 30000 60000 90000 120000 150000 Maize Sorghum Sunflower Bulrush Millet Groundnuts Beans Finger Millet Paddy Chich Peas Cassava Sweet Potatoes Simsim Tobacco Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - Singida 0.00 0.50 1.00 1.50 2.00 2.50 Irish Potatoes Cotton Chick peas Maize Sunflower Sorghum Simsim Green Gram Bmillets Cauliflower Fmillets Paddy Cassava Beans Egg Plant Onions Groundnuts Crop Planted Area (ha) RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 20 Cereals and oil seeds and oil nuts are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because dry season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.4 Cereal Crop Production The total production of cereals was 89,468 tonnes. Maize was the dominant cereal crop at 54,396 tonnes which was 61 percent of total cereal crops produced, followed by sorghum (24%), bulrush millets (11%), paddy (2.2%), finger millets (1.5%) and wheat (0.02%) (Map. 10) The total area planted with cereals during the dry and long rainy seasons was 245,560 ha out of which 1,816 ha (0.7%) were planted in dry season and 243,744 ha (99.3%) were planted during the long rainy season. The long rainy season accounts for 99.6 percent of the total cereals produced in both seasons. The area planted with maize during the dry season was 98.8 percent of the total area planted with cereals in that season followed by sorghum (1.2%) (Table 3.2) The area planted with maize was large and it represented 55.9 percent of the total area planted with cereal crops, followed by sorghum (28.5%), bulrush millets (12.5%), finger millets (1.6%) and paddy (1.5%). The yield of paddy was 538 kg/ha, followed by wheat (483 kg/ha), maize (396 kg/ha), finger millets (348 kg/ha), bulrush millets (326 kg/ha and sorghum (310 kg/ha) (Chart 3.19). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Singida region during the long rainy season was 132,667, (74% of the total crop growing households in the region during the long rainy Table 3.2: Area, Production and Yield of Cereal Crops by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 1,795 340 190 135,482 54,056 399 137,277 54,396 396 Sorghum 21 11 533 69,884 21,692 310 69,905 21,703 310 Bulrush millets 0 0 0 30783 10,025 326 30,783 10,025 326 Finger Millet 0 0 0 3,901 1,357 348 3,901 1,357 348 Paddy 0 0 0 3,665 1,973 538 3,665 1,973 538 Wheat 0 0 0 29 14 483 29 14 483 Total 1,816 351 243,744 89,117 245,560 89,468 Chart 3.17 b: Percentage Distribution of Area planted with Annual Crops by Crop Type Cereals 76.4% Fruits and Vegetables 0.4% Oil seeds and Oil nuts 16.6% Cash crops 0.7% Pulses 4.2% Roots and Tubers 1.8% Cereals Oil seeds and Oil nuts Pulses Roots and Tubers Cash crops Fruits and Vegetables 1816 13342 0 5724 0 1249 197 52843 335 2226 0 0 100000 200000 300000 Area (hectares) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Dry Season Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 Maize Sorghum Bulrush millets Wheat Paddy Finger Millet Crop Area Planted (ha) 0.00 0.25 0.50 0.75 Yield (t/ha) Area Planted (ha) Yield (t/ha) Singida Urban Manyoni Iramba Singida Rural 132,986ha 10,943ha 63,160ha 114,330ha 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Manyoni Iramba Singida Urban 77% 91% 90% 94% Singida Rural 90.6 to 94 87.2 to 90.6 83.8 to 87.2 80.4 to 83.8 77 to 80.4 RESULTS 21 Tanzania Agriculture Sample Census Map 3.07 SINGIDA Utilized Land Area Expressed as a Percent of Available Land by District Percent of Utilized Land Area Percent of Utilized Land Area Map 3.08 SINGIDA Total Planted Area With Annual Crops by District Annual crops Planted Area Annual crops Planted Area Singida Urban Singida Rural Manyoni Iramba 9,438ha 44,688ha 98,190ha 93,244ha 80,000 to 100,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Manyoni Singida Rural Singida Urban Iramba 0ha 298ha 17ha 1,977ha 1.5% 0% 0.3% 0.2% 1,600 to 1,980 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 RESULTS 22 Tanzania Agriculture Sample Census Map 3.09 SINGIDA Area planted and Percentage During the Short Rainy Season by District Planted Area (ha) Planted Area (ha) Map 3.10 SINGIDA Area Planted with Cereals by District Planted Area (ha) Percentage of Area Planted Planted Area (ha) RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 23 season). The total production of maize was 54,056 tonnes from a planted area of 135,482 hectares resulting in a yield of 0.4 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tonnes) for the long rainy season. There was an increase in maize production 73% over the period of 1997 to 1999 after which the production remained constant until 2000. The average area planted with maize per household was 1.0 hectares however it ranged from 0.5 hectares in Singida Urban district to 1.2 hectares in Manyoni district. Iramba district had the largest area of maize (59,062 ha) followed by Singida Rural (42,699 ha), Manyoni (32,035 ha) and Singida Urban (1,686 ha). (Chart 3.21, Map 3.11 and map 3.12) Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 7 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 1999 and the area has remained constant ever since. However, the yield of maize has shown a gradual decline over the period 1995 to 1998 after which the yield remained almost steady to year 2002 then the yield dropped in 2003 (Chart 3.22). 3.3.4.2 Sorghum Sorghum is the second most important cereal crop in the region in terms of planted area. The number of households that grew sorghum in Singida region during the long rainy season was 82,809. This represents 46 percent of the total crop growing households in Singida region in the long rainy season. The total production of sorghum was 21692 tonnes from a Chart 3.22 Time Series of Maize Planted Area and Yield - Singida 0 50000 100000 150000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area Yield Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 1686 32035 42699 59062 0 10000 20000 30000 40000 50000 60000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.0 0.3 0.6 0.9 1.2 1.5 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.23 Total Planted Area and Area of Sorghum per Household by District 29836 29315 8589 2143 0 10000 20000 30000 40000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.00 0.30 0.60 0.90 1.20 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Sorghum Production - Singida 22 60 59 59 71 75 0 20 40 60 80 1994/95 1995/96 1996/97 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons Chart 3.20: Time Series Data on Maize Production - Singida 88 114 123 54 88 51 66 0 25 50 75 100 125 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 24 planted area of 69,884 hectares resulting in a yield of 0.31 t/ha. The district with the largest area planted with sorghum was Iramba (29,836 ha) followed by Singida Rural (29,315 ha), Manyoni (8,589 ha) and Singida Urban (2,143 ha) (Map 3.13) There are significant variations in the average area planted per crop growing household among the districts ranging from 0.5 ha in Singida Urban district to 1.1 ha in Iramba district (Chart 3.23 and Map 3.14). There was a decreasing trend in the production of sorghum in 1995/96 to 2002/03. The production was almost steady from 1997 to 2000 at around 60,000 tonnes after which it dropped to 22,000 tonnes in the following year. Charts 3.24 and 3.25 shows that the yield and production of sorghum has dropped dramatically over the previous 7 years and the planted area decreased from 74,604 hectares in 1995 to 52,748 hectares in 1997, there after the area increased to 87,715 hectares in 2000 and then dropped to 69,905 hectares in 2003. The area planted with sorghum remained constant from 1999 to 2000 after which the area under production declined until 2003 (Chart 3.25). 3.3.4.3 Other Cereals Other cereals produced include bulrush millet, finger millet and paddy. Bulrush millets is produced in Singida Rural (16,562 ha), Iramba (6,949 ha), Singida Urban (5,156 ha) and Manyoni district (2,116 ha). Finger millet is produced in Singida Rural (3,428 ha), Singida Urban (399 ha) and Manyoni (75 ha). Paddy is produced in Manyoni (1,873 ha), Singida Rural (1,140 ha), Iramba (615 ha) and Singida Urban (39 ha) (Chart 3.26). 3.3.5 Oil seeds and Oil nuts Production The total production of oil seeds and oil nuts during the long rainy season was 24,367 tonnes. Sunflower production was higher than any other oil seed and oil nut crop in the region with a total production of 21,002 tonnes representing 86 percent of the total oil seeds and oil nuts production. This was followed by groundnut with 2,462 tonnes (10%), simsim (887 tonnes (4%) and soya beans 17 tonnes (0.1%) (Table 3.3) Table 3.3: Area, Production and Yield of Oil seeds and Oil nuts by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 279 335 1,201 40,590 21,002 517 40,728 21,281 522 Simsim 0 0 0 2,053 887 432 2,053 887 432 Groundnuts 0 0 0 10,146 2,462 243 25,662 10,146 243 Soyabeans 0 0 0 55 17 329 167 55 309 TOTAL 279 335 52,844 24,368 53,123 24,703 Chart 3.25 Time Series of Sorghum Planted Area and Yield - SGD 0 15000 30000 45000 60000 75000 90000 1994/95 1995/96 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Yield (t/ha) Planted Area Yield Chart 3.26 Area Planted with Bulrush millets, Finger millets and Paddy by District 0 4000 8000 12000 16000 20000 Iramba Singida Rural Manyoni Singida Urban Bulrush millets Finger millets Paddy Chart 3.27 Area Planted and Yield of Major Oil seeds and Oil nuts 0 15000 30000 45000 Sunflower Simsim Groundnut Soyabeans Crop Area Planted (ha) 0.0 0.2 0.4 0.6 Yield (kg/ha) Yield (kg/ha) Singida Urban 1.2ha 0.5ha 1.2ha 0.8ha Singida Rural Manyoni Iramba 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Singida Urban Iramba Manyoni 59,062ha 1,686ha 32,035ha 42,699ha 0.3t/ha 0.4t/ha 0.5t/ha 0.5t/ha Singida Rural 48,000 to 60,000 36,000 to 48,000 24,000 to 36,000 12,000 to 24,000 0 to 12,000 Map 3.11 SINGIDA Planted Area and Yield of Maize by District Planted Area (ha) Planted Area (ha) Map 3.12 SINGIDA Area Planted per Maize Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 25 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 26 The area planted with sunflower was larger than any other oil seeds and oil nuts (12.7% of the total area planted with annual crops and vegetables) and it accounted for77 percent of the area planted with oil seeds and oil nuts, followed by groundnuts (19%), simsim (4%) and soya beans (0.1%). 3.3.5.1 Sunflower The number of households growing sunflower in Singida region was 45,857. The total production of sunflower in the region was 21,337 tonnes from a planted area of 40,869 hectares resulting in a yield of 0.5 t/ha. There has been a large decrease in production of sunflower over the period 1998/99 to 2002/03, from 40,046 tonnes in 1998/99 to 21,281 tonnes in 2002/03. Area planted increased from 32,495 hectares in 1998/99 to 40,590 hectares in 2002/03 (Chart 3.28) Fifty nine percent of the area planted with sunflower was located in Iramba district (23,946 ha) followed by Singida Rural (15,130 ha, 37%), Singida Urban (408 ha, 2.2%) and Manyoni (262 ha, 1.5%). The highest proportion of land with sunflower was found in Singida Urban followed by Singida Rural, Iramba and Manyoni (Chart 3.29 and Map 3.15). The largest area planted per sunflower growing household was found in Iramba district (1.04 ha) and the lowest was in Manyoni (0.45). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.30 and Map 3.16). Table 3.4: Area, Production and Yield of Pulses by Season Dry Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 2 9 4500 2 9 4500 Beans 0 0 0 8328 1645 198 8328 1645 198 Cowpeas 0 0 0 943 299 317 943 299 317 Green Gram 0 0 0 174 75 431 174 75 431 Chick Peas 0 0 0 3201 1624 507 3201 1624 507 Bambaranuts 0 0 0 695 169 243 695 169 243 TOTAL 0 0 13,343 3,821 13,343 3,821 Chart 3.28 Time Series Data on Sunflower Production - Singida 40046 21281 0 10,000 20,000 30,000 40,000 50,000 1998/99 2002/03 Year Production ( tonnes) Chart 3.29 Percent of Sunflower Planted Area and Percent of Total Land with Sunflower by District 0.0 15.0 30.0 45.0 60.0 Iramba Singida Rur Manyoni Singida Urb District Percent of Land 0.0 5.0 10.0 15.0 20.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.25 0.50 0.75 1.00 Area per Household (ha Iramba Singida Rur Singida Urb Manyoni District Chart 3.30 Area Planted per Sunflower Growing Households by District (Long Rainy Season Only) Singida Urban Singida Rural Iramba 0.5ha 1.1ha 0.7ha 0.8ha Manyoni 0.9 to 1.1 0.8 to 0.9 0.7 to 0.8 0.6 to 0.7 0.5 to 0.6 Manyoni Singida Urban Iramba 8,589ha 29,836ha 29,315ha 0.3t/ha 0.3t/ha 0.2t/ha 0.4t/hat/ha Singida Rural 2,143ha 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.13 SINGIDA Planted Area and Yield of Sorghum by District Planted Area (ha) Planted Area (ha) Map 3.14 SINGIDA Area Planted per Sorghum Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULTS 27 Singida Urban Iramba Singida Rural Manyoni 905 23,946 15,130 609 0.45 0.52 0.53 0.43 20,000 to 25,000 15,000 to 20,000 10,000 to 15,000 5,000 to 10,000 0 to 5,000 Singida Urban 0.72 1.04 0.75 0.45 Singida Rural Manyoni Iramba 1.2 to 1.5 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Map 3.15 SINGIDA Planted Area and Yield of Sunflower by District Planted Area (ha) Planted Area (ha) Map 3.16 SINGIDA Area Planted per Sunflower Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 28 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 29 3.3.6 Pulse Crops Production The total area planted with pulses was 13,343 hectares out of which 8,328 ha were planted with beans (62.4 percent of the total area planted with pulses), followed by chick peas (3,201 ha, 24.0%), cow peas (943 ha, 7.1%) bambaranuts 695 ha, (5.2%) and green gram (174 ha, 1.3%). pigeon peas, field peas and soya beans were not cultivated in the region. The total production of pulses was 3,821 tonnes. Beans were the most cultivated crop producing 1,645 tonnes which accounted for 43.1 percent of the total pulse production. This was followed by chick peas (1624t, 42.5%), cow peas (299t, 7.8%), bambaranuts (169t, 4.4%), green gram (75t, 2.0%) and mung beans (9t, 0.2%). Mung beans and chick peas had relatively higher yields of 4,500 and 507 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were green gram 431 kgs/ha, cowpeas 317 kgs/ha and beans 198 kgs/ha. (Chart 3,32). 3.3.6.1 Beans Beans dominated the production of pulse crops in the region. The number of households growing beans in Singida region was 19,913. The total production of beans in the region was 1,645 tonnes from a planted area of 8,328 hectares resulting in a yield of 0.2 t/ha. The largest area planted with beans in the region was in Iramba (4,209 ha, 50.5%) (Chart 3.32 and Map 3.17), however, the largest area planted with beans per household was in Manyoni district (0.5 ha) (Chart 3.33), followed by Iramba district (0.4 ha), Singida Rural (0.3) and Singida Urban (0.2 ha). The average area planted per household in the region during the long rainy season was 0.4 ha (Map 3.18). Chart 3.31 Area Planted and Yield of Major Pulse Crops 0 2,000 4,000 6,000 8,000 10,000 Beans Chich Peas Cowpeas Bambaranuts Green Gram Mung Beans Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) Yield (kg/ha) Chart 3.32 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 Iramba Manyoni Singida Rur Singida Urb District Percent of Land 0 10 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.90 0.42 0.20 0.17 0.00 0.25 0.50 0.75 1.00 Area per Household Manyoni Iramba Singida Urb Singida Rur District Chart 3.33 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.34: Time Series Data on Beans Production - Singida 1,153 1,645 1,390 1,153 - 400 800 1,200 1,600 2,000 1997/98 1998/99 1999/2000 2002/03 Year Production tonnes RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 30 In Singida region, bean production has increased from 1,390 tonnes in 1997/98 to 1,645 tonnes in 2002/03 (Chart 3.34). Charts 3.35 and 3.36 show that, the yield of beans was high in 1996/96 (2.7 t/ha), Over the period 1998/99 to 1999/00 the yield of beans remained constant at around 0.3 t/ha (Chart 3.35). The quantity produced has increased and this has been due to a large increase in the area under production. The area planted with beans has increased erratically over the period from 1996 to 2003. 3.3.7 Roots and Tuber Crops Production The total production of roots and tubers was 5,597 tonnes. Sweet potatoes production was higher than any other root and tuber crop in the region with a total production of 2,807 tonnes representing 50.1 percent of the total root and tuber crops production. This was followed by cassava with 2,424 tonnes (43.3%), Irish potatoes (364t, 6.5%) and yams (2t, 0.04%). (Table 3.5). The area planted with cassava was larger than any other root and tuber crops and it accounted for 52.3 percent of the area planted with roots and tubers, followed by sweet potatoes (44.8%), Irish potatoes (2.8% and yams (0.1%). The yield was high for Irish potatoes (2.3 t/ha) and sweet potatoes (1.1 t/ha), followed by cassava (0.8 t/ha) and yams (0.7 t/ha). 3.3.7.1 Cassava The number of households growing cassava in the region was 6,610. This represents 3.7 percent of the total crop growing households in the region. The total production of cassava during the census year was 2,424 tonnes from a planted area of 2,995 hectares resulting in a yield of 0.8t/ha. Table 3.5: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 0 0 0 2995 2424 809 2995 2424 809 Sweet Potatoes 0 0 0 2564 2807 1095 2564 2807 1095 Irish Potatoes 0 0 0 161 364 2261 161 364 2261 Yams 0 0 0 3 2 667 3 2 667 Cocoyam 0 0 0 0 0 0 0 0 0 TOTAL 0 0 5,724 5,597 5,724 5,597 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.35 Time Series of Beans Planted Area and Yield - Singida 0 3000 6000 9000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.00 1.00 2.00 3.00 Yield (t/ha) Area Yield Chart 3.36 Area Planted with Cassava during the Census/Survey Years 0 12,000 24,000 36,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava Singida Urban 0.4hha 0.2ha 0.3ha 0.5ha Singida Rural Manyoni Iramba 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Iramba Singida Urban 4,208.54ha 17.22ha 1,051.14ha 3,050.75ha 0.1t/hha 0.3t/ha 0.4t/ha 0.3t/ha Singida Rural Manyoni 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.17 SINGIDA Planted Area and Yield of Beans by District Planted Area (ha) Planted Area (ha) Map 3.18 SINGIDA Area Planted per Beans Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 31 Singida Urban 6,294 8,080 488 6% 10% 11% 1% Singida Rural Manyoni Iramba 667 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Manyoni Singida Urban Iramba 1,252 4,606 4,902 3.8% 7.1% 7.4% 6.7% Singida Rural 792 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Map 3.35 SINGIDA Number and percent of smallholder Planted trees by district Number of smallholder Number of smallholder Planted trees Number of households With water harvesting Bunds Number of households With water harvesting Bunds Map 3.36 SINGIDA Number and percent of households With water harvesting Bunds by District Percent of households With water harvesting Bunds Tanzania Agriculture Sample Census Percent of smallholder Planted trees RESULT 32 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 33 Previous censuses and surveys indicate that the area planted with cassava increased from 1,532 in 1994/95 ha in 1994/95 to 30,783 ha in 2002/03 (Chart 3.36). The area planted with cassava accounted for 0.94 percent of the total area planted with annual crops and vegetables during the long rainy season. Manyoni district had the largest planted area of cassava (1,019 ha, 34% of the cassava planted area in the region), followed by Singida Rural (964 ha, 32%), Iramba (842 ha, 28%) and Singida Urban (171 ha, 0.6%) (Map 3.19). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Manyoni district (1.61%). This was followed by Singida Urban (1.56%), Singida Rural (0.84%) and Iramba district (0.64%) (Chart 3.37) The average planted area of cassava per cassava growing households was 0.5 hectares. However, there were small district variations. The area planted per cassava growing household was greatest in Singida Rural (0.8 ha). This was followed by Manyoni (0.6 ha), Iramba (0.27 ha) and Singida Urban (0.26 ha) (Chart 3.38 and Map 3.20). 3.3.7.2 Sweet potatoes The number of households growing sweet potatoes in Singida region was 8,432. This was 3 percent of the total root and tuber crop growing households during the long rainy season. The total production of sweet potatoes during the census year was 2,807 tonnes from a planted area of 2,564 hectares resulting in a yield of 1.1t/ha. Iramba district has the largest planted area for sweet potatoes (911 ha, 36%), followed by Singida Rural (755 ha, 29%), Manyoni (726 ha, 28%) and Singida Urban (171 ha, 7%) (Chart 3.39).Other root and tuber crops are of minor important in terms of area planted compared to cassava and sweet potatoes. The average planted area of sweet potatoes per sweet potatoes growing households was 0.30 hectares. However, there were small district variations. The area planted per sweet potatoes growing household was greatest in Manyoni (0.39 ha). This was followed by Singida Rural (0.33 ha), Singida Urban (0.28 ha) and Iramba (0.23 ha) (Chart 3.40) 0.8 0.6 0.3 0.3 0.0 0.2 0.4 0.6 0.8 Area per Household Singida Rur Manyoni Iramba Singida Urb District Chart 3.38 Cassava Planted Area per Cassava Growing Households by District Chart 3.37 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 34.0 32.2 28.1 5.7 - 10.00 20.00 30.00 40.00 Manyoni Singida Rur Iramba Singida Urb District Percent of Total Area Planted 0.0 0.6 1.2 1.8 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.39 0.33 0.28 0.25 0.00 0.20 0.40 Area per Household Manyoni Singida Rur Singida Urb Iramba District Chart 3.40 Sweet potatoes Planted Area per Sweet potatoes Growing Households by District Chart 3.39 Sweet Potatoes: Total Area Planted and Planted Area per Household by District 911 755 726 171 0 250 500 750 1000 Iramba Singida Rur Manyoni Singida Urb District Area (Ha) 0.00 0.10 0.20 0.30 0.40 Area Planted per Household Planted Area (ha) Area per hh RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 34 3.3.8 Fruits and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. The dry season is relatively important for production of tomatoes, spinach, cucumber and egg plant. However, most of fruit and vegetables are produced during long rainy season. The total production of fruits and vegetables was 1,797 tonnes. The most cultivated fruit and vegetable crop was onions with a production of 830 tonnes (46% of the total fruit and vegetables produced) followed by tomatoes (534t, 30%) and cauliflower (15t, 1%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of onions was 1,072 kg/ha, tomatoes (1,648 kg/ha) and cauliflower (185 kg/ha) (Chart 3.41). 3.3.8.1 Onion The number of households growing tomatoes in the region during the long rainy season was 1,928. This represented 1.2 percent of the total crop growing households in the region during the long rainy season. The highest number of households growing onion was found in Singida Rural followed by Iramba, Singida Urban and Manyoni. (Chart 3.42) Singida Rural district had the largest planted area of onions (84.8% of the total area planted with tomatoes in the region), followed by Iramba (12.9%), Singida Urban (1.5%) and Manyoni (0.7%) (Map 3.21). Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 0 0 0 20 8 400 20 8 400 Radish 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 16 14 875 16 14 875 Onions 0 0 0 775 830 1,071 775 830 1,071 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 50 169 3380 50 169 3380 Tomatoes 109 266 2440 215 268 1,247 324 534 1,648 Spinnach 15 12 800 19 19 1000 34 31 912 Carrot 0 0 0 0 0 0 0 0 0 Chillies 0 0 0 4 5 1250 4 5 1250 Amaranths 0 0 0 36 60 1667 36 60 1667 Pumpkins 10 10 1000 0 0 0 10 10 1000 Cucumber 39 6 154 17 0 0 56 6 107 Egg Plant 24 96 4000 17 19 1118 41 115 2805 Cauliflower 0 0 0 80 15 188 80 15 188 Total 197 390 1,249 1,407 1,446 1,797 Chart 3.41 Area Planted and Yield of Fruit and Vegetables 0 200 400 600 800 Onions Tomatoes Cauliflower Cucumber Cabbage Egg Plant Others Crop A rea Planted (ha) 0 300 600 900 1200 Y ield (kg/ha) 0 500 1000 1500 Area per Household (ha). Singida Rur Iramba Singida Urb Manyoni District Chart 3.42 Number of households Growing Onion by District (Long Rainy Season Only) Singida Urban 0.3ha 0.3ha 0.8ha 0.6ha Singida Rural Manyoni Iramba 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Singida Urban Iramba Manyoni 842ha 964ha 1,019ha 0.9t/ha 1.3t/ha 0.4t/ha 0.8t/ha Singida Rural 171ha 1,000 to 1,250 750 to 1,000 500 to 750 250 to 500 0 to 250 Map 3.19 SINGIDA Planted Area and Yield of Cassava by District Planted Area (ha) Planted Area (ha) Map 3.20 SINGIDA Area Planted per Cassava Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 35 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 36 The highest percentage of land with onion was found in Singida Rural, followed by Singida Urban, Iramba and Manyoni districts (Chart 3.43). The largest area planted per onion growing household was found in Singida Rural district (0.45 ha) followed by Iramba (0.40 ha), Singida Rural (0.09 ha) and Manyoni (0.07 ha) (Chart 3.44 and Map 3.22). The total area planted with onion accounted for 0.6 percent of the total area planted with annual crops and vegetables during the long rainy seasons. 3.3.8.2 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 1,802. This represented one percent of the total crop growing households in the region in the long rainy season. Singida Rural district had the largest planted area of tomatoes during the long rainy season (108 ha, 50.5% of the total area planted with tomato in the region), followed by Singida Urban (82 ha, 38.3%), Manyoni (17 ha, 7.9%) and Iramba (7 ha, 3.3%) (Chart 3.45 and Map 3.23 and 2.24) The total area planted with tomatoes accounted for 0.07 percent of the total area planted with annual crops and vegetables during the long rainy seasons. 3.4 Permanent Crops Permanent crops (sometimes referred as perennial crops) are crops that normally take over a year to mature and once they mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature but survive for more than one year and are thus treated as a permanent crops. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 9,242 hectares (3% of the area planted with annual crops in the region). However, the area planted with crops is not the actual physical land area as it includes the area planted more than Chart 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District 0.0 15.0 30.0 45.0 60.0 75.0 90.0 Singida Rur Iramba Singida Urb Manyoni District Percent of Land 0.00 0.20 0.40 0.60 0.80 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha).. Singida Rur Iramba Singida Urb Manyoni District Chart 3.44 Area Planted per Onion Growing Household by District (Long Rainy Season Only) Chart 3.45 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 Singida Rur Singida Urb Manyoni Iramba District Percent of Land 0.00 0.25 0.50 0.75 1.00 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.12 to 0.15 0.09 to 0.12 0.06 to 0.09 0.03 to 0.06 0 to 0.03 Singida Urban 0.14ha 0.05ha 0.13ha 0.07ha Singida Rural Manyoni Iramba Singida Urban 7ha 108ha 17ha 1.4t/ha 1.5t/ha 0.9t/ha 2.4t/ha Singida Rural Manyoni Iramba 82ha 88 to 110 66 to 88 44 to 66 22 to 44 0 to 22 Map 3.23 SINGIDA Planted Area and Yield of Tomatoes by District Planted Area (ha) Planted Area (ha) Map 3.24 SINGIDA Area Planted per Tomatoes Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census 37 RESULT RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 38 once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in Chart 3.46. The most important permanent crop in Singida region is Mango which had a planted area of 3,784 ha, (40% of the area planted with all permanent crops) followed by banana (3,373 ha, 36%), guava (1,268 ha, 14%) and sugarcane (541 ha, 6%). Each of the remaining permanent crops had an area of less than 2 percent of the total area planted with permanent crops (Chart 3.47). Manyoni district had the largest area under smallholder permanent crops (131,853 ha, 31.6%). This is followed by Singida Urban (117,667 ha, 28.2%), Iramba (97,731 ha, 23.4%) and Singida Rural (70,461 ha, 16.9%). However, Manyoni had the largest area per permanent crop growing household (1.8 ha) followed by Singida Rural (0.7 ha), Singida Urban (0.5 ha) and Iramba (0.4 ha) (Chart 3.48). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Singida Urban had the highest (6.0%) followed by Manyoni (4.8%), Singida Rural (3.3%) and Iramba (1.1%) 3.4.1 Mango The total production of mangoes by smallholders was 254 tonnes. In terms of area planted, mango was the most important permanent crop grown by smallholders in the region. They were grown by 2,599 households (26% of the total crop growing households). The average area planted with mango per mango growing households was moderate at around 1.5 ha per mango growing household and the average yield obtained by smallholders was 3,331 kg/ha from a harvest area of 76 hectares. Singida Rural had the largest area of mango in the region (3,940 ha, 43%) followed by Manyoni (3,159 ha, 34%), Iramba (1,449 ha, 16%) and Singida Urban (695 ha, 8%) (Map 3.25). However, the average area planted with mango per mango growing household was highest in Manyoni (1.8 ha) followed by Singida Rural (0.7 ha), Singida Urban (0.5 ha) and Iramba (0.4 ha) (Chart 3.49 and Map 3.26). Chart 3.47 Area Planted (ha) w ith Main Perennial Crops Orange, 50, 1% Guava, 1,268, 14% Other, 21, 0% Sugarcane, 541, 6% Star Fruit, 70, 1% Pigeon Pea, 65, 1% Mango, 3,784, 40% Paw paw , 72, 1% Banana, 3,373, 36% Guava Orange Banana Paw paw Mango Star Fruit Pigeon Pea Sugarcane Other Chart 3.48 Percent of Area Planted and Average Planted Area with Permanent Crops by District 28.2 23.4 16.9 31.6 0.0 9.0 18.0 27.0 36.0 Manyoni Singida Urban Iramba Singida Rural District % of Total Area Planted 0.0 0.5 1.0 1.5 2.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.49 Percent of Area Planted with Mango and Average Planted Area per Household by District 16 34 8 43 0 20 40 60 Singida Rural Manyoni Iramba Singida Urban District % of Total Area Planted 0.00 0.50 1.00 1.50 2.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.46 Area Planted for Annual and Permanent Crops Annual Crops, 319,143, 97% Permanent Crops, 9,242, 3% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 39 3.4.2 Bananas The total production of bananas by smallholders was 873 tonnes. In terms of area planted, banana was the second most important permanent crop grown by smallholders in the region. It was grown by 2,937 households (0.9% of the total crop growing households). The average area planted with bananas per household was moderate at around 1.1 ha per banana growing household and the average yield obtained by smallholders was 3,371 kg/ha from a harvest area of 259 hectares. Singida Rural had the largest area of bananas in the region (2,739 ha, 81.2%) followed by Iramba (503 ha, 14.9%), Manyoni (86 ha, 2.5%) and Singida Urban (45 ha, 1.3%) (Map 3.27) However, the average area planted with bananas per banana planting household was highest in Singida Rural (2.1 ha) followed by Iramba (0.5 ha), Manyoni (0.21 ha) and Singida Urban (0.18 ha). (Chart 3.50 and Map 3.28) 3.3.8 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 2,074 ha was planted with other annual crops and tobacco was the most prominent followed by cotton. Cash crops were grown in long rainy season only. 3.3.9.1 Tobacco Only 1,083 tonnes of tobacco were produced in Singida region on a planted area of 1,387 ha. It was produced during the long rainy season only. The crop is grown in Manyoni district only (Chart 3.51b) and only 1.0 ha was grown per household. 3.3.9.2 Cotton The quantity of cotton produced was 275 tonnes. Cotton had a planted area of 687 ha, all of which was planted in the long rainy season. Cotton was produced in Manyoni district only. Table 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 687 275 400 687 275 400 Tobacco 0 0 0 1,387 1,083 780 1,387 1,083 780 Jute 0 0 0 0 0 0 0 0 0 TOTAL 0 0 2,074 1,358 2,074 1,358 Chart 3.50 Percent of Area Planted with Bananas and Average Planted Area per Household by District 14.9 1.3 81.2 2.5 0.0 30.0 60.0 90.0 Singida Rural Iramba Manyoni Singida Urban District % of Total Area Planted 0.0 0.5 1.0 1.5 2.0 2.5 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51a:Planted Area with Other Crops (Cash Crops) Tobacco, 1,387, 67% Cotton, 687, 33% Cotton Tobacco Chart 3.51b Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 80.0 100.0 Iramba Singida Rur Manyoni Singida Urb District Percent of Land 0.00 0.80 1.60 2.40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Singida Urban 0.5 0.4 0.7 1.8 Singida Rural Manyoni Iramba 2 to 2.5 1.5 to 2 1 to 1.5 0.5 to 1 0 to 0.5 Singida Urban Singida Rural 1,449 695 3,940 3,159 Manyoni Iramba 3,200 to 4,000 2,400 to 3,200 1,600 to 2,400 800 to 1,600 0 to 800 Map 3.25 SINGIDA Planted Area and Yield of Mango by District Planted Area (ha) Planted Area (ha) Map 3.26 SINGIDA Area Planted per Mango Growing Household by District Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census RESULT 40 Singida Urban Iramba 0.18ha 0.51ha 2.13ha 0.21ha Singida Rural Manyoni 2 to 2.5 1.5 to 2 1 to 1.5 0.5 to 1 0 to 0.5 Singida Urban 45ha 2,739ha 503ha 86ha 3.253t/ha 2.309t/ha 3.363t/ha 7.758t/ha Singida Rural Manyoni Iramba 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 Map 3.27 SINGIDA Planted Area and Yield of Banana by District Planted Area (ha) Planted Area (ha) Area Planted Per Household Yield (t/ha) Area Planted Per Household Tanzania Agriculture Sample Census Map 3.28 SINGIDA Area Planted per Banana Growing Household by District RESULT 41 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 42 3.5 Inputs/Implements Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period and burning, hand slashing or tractor slashing, which is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 267,954 ha which represented 84.3 percent of the total planted area, followed by bush clearing (29,029 ha, 9.1%) and burning (13,722 ha, 4.3%). No land clearing, tractor slashing and other means are less important methods for land clearing and they represent 1.9, 0.2 and 0.04 percent respectively (Chart 3.51c and Table 3.8 ). 3.5.2 Methods of Soil Preparation Oxen ploughing is the most used method of preparation as it was used in an area of 207,558 ha which represented 65 percent of the total planted area, followed by hand cultivation (110,132 ha, 34%) and tractor ploughing (2,287 ha, 1%) (Chart 3.52). In Singida region, Iramba district had the largest planted area cultivated with oxen (118,470 hectares, 57.1%) followed by Singida Rural (68,074 ha, 2.8%), Manyoni (18,799 ha, 9.0%) and Singida Urban (2,215 ha, 1.1%). Table 3.8: Land Clearing Methods Long Rainy Season Dry Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 156,628 267,954 84.3 1,075 2,335 99.5 157,703 270,289 84.4 No Land Clearing 2,195 6,180 1.9 0 0 0 2,195 6,180 1.9 Mostly Bush Clearance 11,822 29,029 9.1 120 12 0.5 11,942 29,041 9.1 Mostly Burning 8,012 13,722 4.3 0 0 0 8,012 13,722 4.3 Mostly Tractor Slashing 556 684 0.2 0 0 0 556 684 0.2 Other 144 117 0 0 0 0 144 117 0 Total 179,357 317686 100 1,195 2,347 100 180,552 320,033 100 Chart 3.52 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 2,299 , 1% Mostly Hand Hoe Ploughing, 111,007, 34% Mostly Oxen Ploughing, 208,962, 65% Chart 3.51c Area Planted with Annual Crops by Method of Land Clearing During the Long Rainy Season 267,954 29,029 13,722 6,180 684 117 0 100,000 200,000 300,000 Mostly Hand S lashing Mostly Bush Clearance Mostly Burning No Land Clearing Mostly Tractor S lashing Ot her Plant e d A re a RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 43 During the long rainy season, 68.9 percent of the total area cultivated by using oxen was planted with cereals followed by oil seeds (18.8%), pulses (7.3%) roots and tubers (3.2%) fruit and vegetables (1.3%) and cash crops (0.5%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 62,511 ha which represents 20 percent of the total planted with the annual crops and vegetables area. Cereals had the largest area planted with improved seeds (43,089 ha, 73.3% of the planted area with improved seeds) followed by Oil seed (10,861 ha, 18.5%), pulses (2,159 ha, 3.7%), cash crops (1,797 ha, 3.1%), fruit and vegetables (550 ha, 0.9%) and root and tubers (341 ha, 0.6%) (Chart 3.55). However, the use of improved seed in cash crops and fruit and vegetables is much greater than in other crop types (81% and 44% respectively), only 8 percent of the planted area for roots and tubers used improved seeds (Chart 3.56). Table3.9 Planted Area by Type of Fertiliser Use and District - Long Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Iramba 62,040 2,569 93 64,702 66,307 Singida R 42,988 2,363 250 45,601 68,431 Manyoni 8,817 547 3,144 12,508 50,652 Singida U 5,765 473 0 6,238 4,688 Total 119,610 5,952 3,487 129,049 190,078 0 40000 80000 120000 Area Cultivated Iramba Singida Rural Manyoni Singida Urban District Chart 3.53 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.54 Planted Area of Improved Seeds - Singida With Improved Seeds, 62,511, 20% Without Improved Seeds, 255,174, 80% v Chart 3.55 Planted Area with Improved Seed by Crop Type Cereals, 43,089, 73.3% Pulses, 2,159, 3.7% Roots & Tubers, 341, 0.6% Oilseeds , 10,861, 18.5% Fruits & Vegetables, 550, 0.9% Cash Crops, 1,797, 3.1% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruit & Vegetables Cash Crops Crop Type Chart 3.56 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 44 3.5.4 Fertilizer Use The use of fertilisers on annual crops is moderate with a planted area of only 129,050 ha (40% of the total planted area in the region). The planted area without fertiliser for annual crops was 190,078 hectares representing 60 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 119,610 ha which represents 37.5 percent of the total planted area (92.7% of the area planted with fertiliser application in the region). This was followed by compost (5,952 ha, 4.6%). Inorganic fertilizers were used on a very small area and represented only 2.7 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Iramba district (50.1%) followed by Singida Rural (35.3%), Manyoni (9.7%) and Singida Urban (4.8%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 255,726 households, 64%) (Map 3.29). The percentage of the planted area applied with fertilisers was highest for cereals (88.1% of the area planted with fertilizers during the long rainy season). This was followed by oil seeds and oil nuts (8.1%), pulses (2.0%), cash crops (1.3%), fruit and vegetables (0.4%) and roots and tubers (0.1%) (Table 3.10). Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Cereals 111,345 106,556 6,471 5,137 2,126 1,984 153,358 130,068 273,300 243,745 Roots & Tubers 476 87 79 32 0 . 14,599 5,605 15,154 5,724 Pulses 6,661 2,412 370 91 74 72 21,641 10,767 28,746 13,342 Oil seeds & Oil nuts 10,060 9,727 879 680 190 90 63,321 42,346 74,450 52,843 Fruits & Vegetables 2,464 452 125 13 78 6 2,501 778 5,168 1,249 Cash Crops 283 376 0 . 1,278 1,335 306 515 1,867 2,226 Total 131,289 119,610 7,924 5,953 3,746 3,487 255,726 190,079 398,685 319,129 0 50,000 100,000 150,000 Area (ha) Iramba Singida R Manyoni Singida U District Chart 3.58 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.57 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 119,582, 37.5% Mostly Inorganic Fertilizer, 3,487, 1.1% Mostly Compost, 5,952, 1.9% No Fertilizer Applied, 190,122, 59.6% RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 45 3.5.4.1 Farm Yard Manure Use The number of households that applied farm yard manure in their annual crops during the long rainy season was 131,289 and it was applied to 119,610 ha. The total planted area applied with farm yard manure in Singida region was 119,610 ha representing 37 percent of the total area planted with annual crops during that season (Table 3.10). Cereals had the highest percentage of the area applied with farm yard manure (89.1%), followed by oil seed and oil nuts (8.1%), pulses (2%), fruit and vegetables (0.4%), cash crop (0.3%) and roots and tubers (0.1%) However, cereals had the highest proportion of its planted area with farm yard manure (43.7% of the total area planted with cereals). This was followed by fruit and vegetables (36.2%), oil seeds (18.4%), pulses (18.1%), cash crop (16.9%) and roots and tubers (1.5%). (Charts 3.59 and 3.60). Farm yard manure was mostly used in Iramba (46.5% of the total planted area in the district), followed by Singida Rural (41.6%), Manyoni (38.2%) and Singida Urban (16.3%) (Chart 3.61) 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Singida region was 3,487 ha which represents 1.1 percent of the total planted area with annuals during the long rainy season and 2.7 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizers on their annual crops during the long rainy season was 3,746 (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (56.9% of the total area applied with inorganic fertilizers), followed by cash crop (38.3%), oil seeds (2.6%), and pulses (2.1%) (Chart 3.62). However, the proportion of cash crops with inorganic fertilizers was 60 percent higher than other crop types, followed by cereals (.8%), oil seeds (.2%) and fruit and vegetables (.5%) (Chart 3.63) Chart 3.59 Planted Area with Farm Yard Manure by Crop Type - Singida Cereals, 106,556, 89.1% Roots & Tubers, 87, 0.1% Pulses, 2,412, 2.0% Oilseeds, 9,727, 8.1% Fruits & Vegetables, 452, 0.4% Cash Crop, 376, 0.3% 0 15 30 45 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.60 Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.62 Planted Area with Inorganic Fertilizer by Crop Type - Singida Roots & Tubers, 0, 0.0% Pulses, 72, 2.1% Oilseeds, 90, 2.6% Fruit & Vegetables, 6, 0.2% Cereals, 1,984, 56.9% Cash Crop, 1,335, 38.3% Chart 3.61 Proportion of Planted Area Applied with Farm Yard Manure by District - Singida 0.0 10.0 20.0 30.0 40.0 50.0 Iramba Singida R Manyoni Singida U District Percent Manyoni Singida Urban Iramba 4,202 1,113 2,867 3,916 6.7 10.2 2.2 3.4 Singida Rural 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Singida Urban Iramba 68,634 69,760 52,847 51 52 61 84 Singida Rural Manyoni 5,611 60,000 to 75,000 45,000 to 60,000 30,000 to 45,000 15,000 to 30,000 0 to 15,000 Map 3.29 SINGIDA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Planted Area (ha) Planted Area (ha) with No Application of Fertilizer Planted Area (ha) Percent of Planted Area (ha) with No Application of Fertilizer Planted Area (ha) with Irrigation Tanzania Agriculture Sample Census Map 3.30 SINGIDA Area Planted and Percent of Total Planted Area with Irrigation by District Percent of Planted Area (ha) with Irrigation RESULT 46 Iramba Singida Urban Manyoni 24,877 36,760 17,251 51% 45% 42% 46% Singida Rural 2,833 32,000 to 40,000 24,000 to 32,000 16,000 to 24,000 8,000 to 16,000 0 to 8,000 Singida Urban Manyoni 51% 42% 46% Singida Rural Iramba 45% 50 to 52 48 to 50 46 to 48 44 to 46 42 to 44 Map 3.31 SINGIDA Percent of households Storing crops for 3 to 6 momths by district Percent of households Storing Crops Percent of households Storing Crops Number of Households Selling Crops Number of Households Selling Crops Map 3.32 SINGIDA Number of Households and Percent of Total Households Selling Crops by District Percent of Total Households Selling Crops Tanzania Agriculture Sample Census RESULT 47 RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 48 Inorganic fertiliser is mostly used in Manyoni (5.0% of the total planted area in the district), followed by Singida Rural (0.2%) and Iramba (0.1%). Singida Urban district used virtually no inorganic fertiliser. (Chart 3.64). In permanent crops inorganic fertiliser were used mainly on cotton (100%). 3.5.4.3 Compost Use The total planted area applied with compost was 5,953 ha which represents only 1.9 percent of the total planted area with annual crops in the region and 4.6 percent of the total planted area with fertiliser in the region. The number of households that applied compost manure on their annual crops during the long rainy season was 7,924 The proportion of area applied with compost was very low for each type of crop (0 to 2%); however the distribution of the total area using compost manure shows that 86 percent of this area was cultivated with cereals, followed by oil seeds (11%), pulses (5%) and root and tubers (1%) (Chart 3.65) Compost is mostly used in Singida Urban (4.3% of the total planted area in the district), and this is closely followed by Singida Rural (2.1%), Iramba (2.0%) and Manyoni (0.9%) (Chart 3.67) 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 24,484 ha of annual crops and vegetables. 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.63 Percentage of Planted Area with Inorganic Fertilizer by Crop Type - Singida Chart 3.64 Proportion of Planted Area Applied with Inorganic Fertiliser by District - Singida 0.0 2.0 4.0 6.0 Manyoni Singida R Iramba Singida U District Percent Chart 3.65 Planted Area with Compost by Crop Type - Singida Roots & Tubers, 32, 1% Fruits & Vegetables, 13, 0% Pulses, 91, 2% Oilseeds, 680, 11% Cash Crop, 0, 0% 0 6 12 18 24 30 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.66 Percentage of Planted Area with Compost by Crop Type- Singida Chart 3.67 Proportion of Planted Area Applied with Compost by District - Singida 0.0 1.0 2.0 3.0 4.0 Singida U Singida R Iramba Manyoni District Percent RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 49 Insecticides are the most common pesticide in use in the region (58% of the total area applied with pesticides). This was followed by fungicides (29%) and herbicides (13%) (Chart 3.68). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 13,763 ha which represented 4.2 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (9,611 ha, 70.1% of the total planted area with insecticides) followed by cash crops (1,928 ha, 14.1%), oil seeds and oil nuts (886 ha, 6.5%), pulses (750 ha, 5.5%), fruit and vegetable (454 ha, 3.3%) and roots and tubers (86 ha, 0.6%) (Chart 3.69). However, the percent of insecticides used in cash crops and fruits and vegetables is much greater than in other crop types (86.6 and 36.4% respectively), while only 1.7 percent of oil seed crops were applied with insecticides (Chart 3.70). Manyoni had the highest percent of planted area with insecticides (16.7% of the total planted area with annual crops in the district). This was followed by Iramba (8.5%), Singida Rural (6.3%) and Singida Urban (4.7%) (Chart 3.71). Chart 3.68 Planted Area (ha) by Pesticide Use Fungicides, 7,220 , 29% Insecticides, 14,057 , 58% Herbicides, 3,207 , 13% Chart 3.69 Planted Area Applied with Insecticides by Crop Type Oil seeds & Oil nuts, 886, 6% Pulses, 750, 5% Roots & Tubers, 86, 1% Fruits & Vegetables, 454, 3% Cash crops, 1928, 14% Cereals, 9611, 71% 0.0 25.0 50.0 75.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.70 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.71 Percent of Planted Area Applied with Insecticides by District - Singida 0.0 6.0 12.0 18.0 Manyoni Iramba Singida Rural Singida Urban District Percent RESULTS – Input/Implement Use _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 50 3.5.5.2 Herbicide Use The planted area applied with herbicides was 2,868 ha which represented 0.9 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (1,777 ha, 62%) followed by oil seeds (856 ha, 30%), pulses (154 ha, 5%), and roots and tubers (49 ha, 2%) and cash crops (32ha, 1%) There was no herbicide use in fruit and vegetables (Chart 3.72). However, the percent of herbicide use on oil seeds, cash crops and pulses was much greater than in other crop types (1.6%, 1.4% and 1.2% respectively) while only 0.7 percent of cereals were applied with herbicides (Chart 3.73). The top six annual crops with highest percentage use of herbicides in terms of planted area were sunflower (28.0%), maize (22.2%), bulrush millet (21.8%), sorghum (16.6%), beans (5.4%) and groundnuts (1.8%). Singida Rural had the highest percent of planted area with herbicides (1.61% of the total planted area with annual crops in the district). This was followed by Manyoni (0.69%), Iramba (0.66%) and Singida Urban (0.32%) (Chart 3.74). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 3,487 ha which represented 1.1 percent of the total planted area for annual crops and vegetables. Cereals had the planted area applied with fungicide (2,513 ha, 72.6%) followed by cash crops (597 ha, 17.2%), oil seeds (167 ha, 4.8%), fruit and vegetables (85 ha, 2.4%), pulses (52ha, 1.5%) and roots and tubers (49 ha, 1.4%) (Chart 3.75) Chart 3.74 Proportion of Planted Area Applied with Herbicides by District - Singida 0.00 0.60 1.20 1.80 Singida Rural Manyoni Iramba Singida Urban District Percent Chart 3.75 Planted Area Applied with Fungicides by Crop Type Oil seeds, 167, 4.8% Fruits & Vegetables, 85, 2.4% Cash crops, 597, 17.2% Roots & Tubers, 49, 1.4% Pulses, 52, 1.5% Cereals, 2,513, 72.6% Chart 3.72 Planted Area Applied with Herbicides by Crop Type Pulses, 154, 5% Roots & Tubers, 49, 2% Cereals, 1777, 62% Cash crops, 32, 1% Oil seeds, 856, 30% 0.0 0.6 1.2 1.8 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruit & Vegetables Cash crops Crop Type Chart 3.73 Percentage of Crop Type Planted Area Applied with Herbicides RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 51 However, the percentage use of fungicide was mainly in cash crops (26.8%) (Chart 3.76). Annual crops with more than 20 percent fungicide use were sorghum (27%) and maize (26%) Manyoni had the highest percent of planted area with fungicides (4.6% of the total planted area with annual crops in the district). This was followed by Singida Rural (1.9%), Iramba (1.2%) and Singida Urban (1.0%) (Chart 3.77). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by draft animals (0.26%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 85.4 percent of the total area planted with cereals during the long rainy season was threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.2 percent, 5.2 percent and 0.6 percent of the total planted area respectively. The remaining 8.6 percent was under not applicable. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Singida region, the area of annual crops under irrigation was 3,443 ha representing 1.1 percent of the total area planted (Chart 3.78). The district with the largest planted area under irrigation with annual crops was Manyoni (4,202 ha, 35% of the total irrigated planted area with annual crops in the region). This is closely followed by Singida Rural with (3,916 ha, 32%), Iramba (2,867 ha, 24%) and Singida Urban (1,113 ha, 9%). When expressed as a percentage of the total area planted in 0.0 6.0 12.0 18.0 24.0 30.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.76 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.77 Proportion of Planted Area with Fungicides by District - Singida 0.0 1.0 2.0 3.0 4.0 5.0 Manyoni Singida Rural Iramba Singida Urban District Percent Chart 3.78 Area of Irrigated Land (hectares) Irrigated Area, 307,029, 98.9% Unirrigated Area, 3,443, 1.1% Singida Urban Iramba 11,020 12,344 6,970 7% 34% 38% 21% Singida Rural Manyoni 2,121 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Singida Urban Iramba 44,677 26,948 10,970 37% 71% 37% 33% Singida Rural Manyoni 4,107 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.33 SINGIDA Number of Households and Percent of Total Households Receiving Crop Extension Services by District Number of Households of Receiving Crop Extension Services Number of Households Receiving Crop Extension Services Number Households Using Improved Seeds Number Households Using Improved Seeds Map 3.34 SINGIDA Number and percent of Crop Growing Households Using Improved Seeds by District Percent of Households Crop Growig Using Improved Seeds Tanzania Agriculture Sample Census Percent of Total Households Receiving Crop Extension Services RESULT 52 RESULTS – Irrigation _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 53 each district, Singida Urban had the highest with 10.2 percent of the planted area in the district under irrigation. This is followed by Manyoni (6.7%), Singida Rural (3.4%) and Iramba (2.2%) (Chart 3.79 and Map 3.30). Of all the different crops and in terms of proportion of the irrigated planted area, cabbage, amaranths, okra, spinach, bitter Aubergine, chillies and mung beans were the most irrigated crops with 100 percent irrigation followed by tomatoes (72%). In terms of crop type, the area under irrigation with cereals was 3,512 ha (60% of the total area under irrigation), followed by roots and tubers with 1,467 ha (25.1%), oil seeds and oil nuts (459 ha, 7.8%), fruit and vegetables (368 ha, 6.3%) and pulses (44 ha, 0.8%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 368 ha which represents 29 percent of the total planted area with fruits and vegetables. Tomatoes, onion, and cabbages were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Singida region appears to have decreased over the 10 year intercensal period from 4,854 to 3,443 hectares. This may not be statically significant due to the small number of households sampled with irrigation (Chart 3.80). 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from canals (58% of households with irrigation). This was followed by well (29.2%), dam (8.7%) and river (4.1%) (Chart 3.81). Most households using irrigation in Singida Urban and Singida Rural get their irrigation water from well (7 3% and 54% respectively) Chart 3.79 Irrigated Area and Percentage of Irrigated Area by District 0 900 1,800 2,700 3,600 4,500 Manyoni Singida Rur Iramba Singida Urb District Irrigated Area (ha) 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Percentage with Irrigation Irrigated Area (ha) Percentage of Irrigated Area Chart 3.80 Time Series of Households with Irrigation - Singida 3,443 4,854 0 1,500 3,000 4,500 6,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Chart 3.81 Number of Households with Irrigation by Source of Water River, 259, 4.1% Well, 1,865, 29.2% Dam, 555, 8.7% Canal, 3,701, 58.0% Canal River Well Dam RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 54 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 63 percent of households using this method. This was followed by hand bucket with 35 percent of households and motor pump (2%) (Chart 3.82). Gravity was used by most households with irrigation in Manyoni (84%), followed by Singida Rural (12%) and Singida Urban (3%). Hand bucket was more common in Singida Rural with 37 percent of households using the method to get water for irrigation, followed by Singida Urban (36%), Manyoni (14%) and Iramba (13%). Motor pump was only used in Iramba district 3.6.4 Methods of Water Application Most households used flood irrigation (71% of households using irrigation) as a method of field application and bucket/watering can (29%). Other methods of field application for irrigation were not used in the region. (Chart 3.83) 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seeds for planting in the following season. The results for Singida region show that there were 179,391 crop growing households (14.7% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 115,361 households storing 8,366 tonnes as of 1st January 2004. This was followed by sorghum and millets (96,374 households, 5,413t), beans and pulses (15,765 households, 230t) and groundnuts/bambaranuts (4,894 households, 119t) and paddy (4,894 household, 387t). Other crops were stored in very small amounts. Chart 3.84 Number of Households and Quantity Stored by Crop Type - Singida 0 40,000 80,000 120,000 Maize Sorghum & Millet Beans & Pulses Gnuts/Bambara Nuts Paddy Cottton Crop Number of households 0 3,000 6,000 9,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.82 Number of Households by Method of Obtaining Irrigation Water Gravity, 3,977, 63% Motor Pump, 143, 2% Hand Bucket, 2,259, 35% Gravity Hand Bucket Motor Pump Chart 3.83 Number of Households with Irrigation by Method of Field Application Bucket / Watering Can, 1,845, 29% Flood, 4,534, 71% Flood Bucket / Watering Can RESULTS – Crop Storage, Processing and Marketing _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 55 3.7.1.1 Methods of Storage The region had 105,564 crop growing households storing their produce in locally made traditional structures (64.7% of households that stored crops in the region). The number of households that stored their produce in sacks/open drum was 54,162 (33.5%). This was followed by improved locally made crib (1,172 households, 0.7%), other types of storage (940 households, 0.6%), air tight drums 537 households, 0.3%), modern store (293hh, 0.2%) and unprotected pile (85 households, 0.1%). Locally made traditional structures were the dominant storage methods in all districts, with the highest percent of households in Singida Rural using this method (73% of the total number of households storing crop products). This is followed by Iramba (69%), Manyoni (48%) and Singida Urban (35%) (Chart 3.86) The highest percent of households using sacks and open drum was in Singida Urban and Manyoni districts (57% and 49% of the total number of households storing crops respectively), followed by Iramba (30%) and Singida Rural (26%). 3.7.1.2 Duration of Storage Most households (46% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those that stored for a period of less than 3 months. The minority of households stored their crop for a period of over 6 months (17%). Most households that stored pulses stored for a period of between 3 to 6 months followed by less than 3 months. A small number of households stored pulses for the period of over 6 months (Chart 3.87). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Iramba district (51%) followed by Manyoni (46%), Singida Urban (45%) and Singida Rural (42%) (Map 3.31) Chart 3.86 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Iramba Singida Rural Manyoni Singida Urban District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.85 Number of households by Storage Methods - Singida Locally Made traditional Crib, 105019, 64.7% Improved Locally Made Crib, 1172, 0.7% Sacks / Open Drum, 54354, 33.5% Unprotected Pile, 85, 0.1% Airtight Drum, 537, 0.3% Other, 940, 0.6% Modern Store, 293, 0.2% 0 30,000 60,000 Number of households Maize Sorghum & Millet Beans & Pulses Crop Chart 3.87 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 56 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.88). However, households in Iramba district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 97.7 percent followed by seed for planting (Chart 3.89). 3.7.1.4 The Magnitude of Storage Loss About 86.1 percent of households that stored crops had little or no loss, followed by household with up to a quarter loss (7.9%), between a quarter and a half (5.2%) and over a half loss (0.8%). The proportion of households that reported a loss of more than a quarter was greatest for maize (9.6% of the total number of households that stored crops). This was followed by sorghum and millet (7.1%) and beans and pulses (1.3%). Most households storing groundnuts and bambara nuts had no storage loss (100%) (Table 3.11). 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Singida region (167,351 households, 93% of the total crop growing households) (Chart 3.90). The percent of households processing crops was very high in all the districts (above 80%) (Chart 3.91) Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba 65,209 5,262 8,832 645 79,948 Singida R 86,432 10,491 2,444 617 99,984 Manyoni 44,612 1,840 950 250 47,652 Singida U 11,100 539 128 42 11,809 Total 207,354 18,133 12,354 1,555 239,396 0% 25% 50% 75% 100% Percent of Households Maize Paddy Sorghum & Millet Beans & Pulses Gnuts/Bambara Nuts Crop Type Chart 3.89 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Chart 3.90 Households Processing Crops Households not Processing, 12,564, 7% Households Processing, 167,351, 93% 0 25 50 75 100 Percent of Households Processing Iramba Singida Rural Manyoni Singida Urban District Chart 3.91 Percentage of Households Processing Crops by District Chart 3.88 Quantity of Maize Produced (tonnes), Stored (tonnes)and Percent Stored by District 0 5,000 10,000 15,000 20,000 25,000 Iramba Singida Rur Manyoni Singida Urb District Quantity (tonnes) 0 7 14 21 % Stored Quantity harvested Quantity stored % stored RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 57 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 83 percent (138,352 households). This was followed by those processing on-farm by hand (17,013 households, 10%), trader (6,417 households, 4%) and on-farm by machine (4,468 households, 3%). The remaining methods of processing were used by very few households (less than 1%). Although processing by neighbours machine was the most common processing method in all districts in Singida region, however district differences existed. Singida Rural has a higher percent of hand processing than other districts (56%), followed by Manyoni (26%), Iramba (17%) and Singida Urban (1%). Processing by trader was more common in Singida Rural and Iramba (44% and 42% respectively), whilst processing on farm by machine was more prevalent in Singida Rural, Manyoni and Singida Urban (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro-processing namely, main product and by-product. The main product is the major product after processing and the by-product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 160,806 households processing crops into flour (96.1%) followed by grain with 3,473 households (2.1%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 20.6 percent of the households processing crops. The most common by-product produced by crop processing households was husk with bran 3,020 with households (60%) followed by husk (1,384 households, 27%), pulp (288 households, 6%) and cake (275 households, 5%). The remaining by- products were produced by a small number of households (Chart 3.94). Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Factory By Co-operative Union By Trader On Large Scale Farm Other Chart 3.93 Percent of Households by Type of Main Processed Product Grain 2.1% Oil 1.3% Other 0.5% Flour / Meal 96.1% Chart 3.94 Number of Households by Type of Bi-product Shell, 0, 0% Oil, 0, 0% Pulp, 288, 6% Other, 125, 2% Cake, 275, 5% Husk, 1,384, 27% Bran, 3,020, 60% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 58 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 99.6 percent of the total households that used primary processed product (Chart 3.95). Singida Rural was the only district that used primary products as fuel for cooking. Out of 167,351 households that sold processed products, 70,259 were from Singida Rural (42% of the total number of households selling processed products in the region), followed by Iramba with 56,039 households (33.5%), Manyoni with 31,583 households (18.9%) and Singida Urban with 9,469 households (5.7%). In Singida region, Iramba was the only district that sold processed products (Chart 3.96) 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold to neighbours (2,842 households, 60.8% of households that sold crops). This was followed by selling to local market/trade store (660 households, 14.1%), market cooperative (258 households, 5.5%), secondary market (169 households, 3.6%), trade at farm (168 households, 3.6%) and farmers association (165 households, 3.5%) (Chart 3.97). There are large differences between districts in the proportion of households selling processed products to neighbours with Singida Rural district having the largest percent of households in the district selling to neighbours (78%), whereas Singida Urban had only 54 percent. Iramba had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Manyoni had the highest percent of households selling processed products to traders at farm. In Singida Urban, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Singida Rural and Iramba. Chart 3.95 Use of Processed Product Household / Human Consumption, 166,761, 99.6% Fuel for Cooking, 120, 0.1% Sale Only, 285, 0.2% Animal Consumption, 143, 0.1% Did Not Use, 42, 0.0% 0.00 25.00 50.00 75.00 100.00 Percentage of households Iramba Singida Rural Manyoni Singida Urban District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Neighbours, 2,842, 60.8% Local Market / Trade Store, 660, 14.1% Marketing Co- operative, 258, 5.5% Other, 410, 8.8% Trader at Farm, 168, 3.6% Secondary Market, 169, 3.6% Farmers Association, 165, 3.5% Chart 3.98 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Secondary Market Trader at Farm Other RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 59 3.7.3 Crop Marketing The number of households that reported selling crops was 81,720 which represent 45 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Manyoni (52%) followed by Singida Rural (50%), Iramba (40%) and Singida Urban (25%) (Chart 3.99 and Map 3.32). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (80.4% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (6.9%), lack of transport (5%), lack of buyers (2.8%) and transport cost too high (2.3%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 95.8 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Singida region very few agricultural households (2,698, 1.5%) accessed credit out of the total number of agricultural households, out of those that received credit 1,516 (56%) were male-headed households and 1,182 (44%) were female headed households. In Singida Urban district only female headed households got agricultural credit whereas in Singida rural district only male households accessed credit. In Manyoni and Iramba districts both male and female headed households accessed agricultural credit (Table 3.13). 3.8.1.1 Source of Agricultural Credit The major agricultural credit providers in Singida region were cooperatives which provided credit to 1,124 agricultural households (41.6% of the total number of households that accessed credit), followed by family, friends and relatives (33.8%), saving and credit society (8%), Religious Organizations/Non Governmental Organizations/ projects (7.5%), private individual (4.6%) and commercial bank (4.5%) (Chart 3.101). Commercial banks were the sole source of credit in Singida Rural district and cooperatives were found in Manyoni district only. Private individual was a major credit provider in Singida Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 101,154 95.8 Other 2,097 2.0 Price Too Low 1,243 1.2 Trade Union Problems 452 0.4 Co-operative Problems 263 0.2 Market Too Far 292 0.3 Government Regulatory Board Problems 125 0.1 Total 105,626 100.0 Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Iramba 548 56 428 44 976 Singida R 246 100 0 0 246 Manyoni 723 50 712 50 1,435 Singida U 0 0 42 100 42 Total 1,517 56 1,182 44 2,699 Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 10,000 20,000 30,000 40,000 Singida Rural Iramba Manyoni Singida Urban District Number of Households 0 15 30 45 60 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Farmers Association Problems 0.5% Open Market Price Too Low 80.4% Government Regulatory Board Problems 0.7% Transport Cost Too High 2.3% Lack of Market Information 0.6% Market too Far 6.9% No Transport 5.0% No Buyer 2.8% Other 0.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 60 Rural district. Family, friends and relatives were more involved in funding a relatively great number of households in Iramba disrtict (Chart 3.102). 3.8.1.2 Use of Agricultural Credit The agricultural credit provided to agricultural households in the region was used as follows unspecified activities (37%), fertilizers (27%), agrochemicals (21%), labour (11%) and tools and equipment (2%). (Chart 3.103). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 66 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (13%), followed by “not wanting to go into debt” (12%) The rest of the reasons were collectively 9 percent of the households. Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Iramba Singida Rural Manyoni Singida Urban District Percent of Households Family, Friend and Relative Commercial Bank Saving & Credit Society Co-operative Religious Organisation / NGO / Project Private Individual Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Other 37% Agro-chemicals 21% Tools / Equipment 2% Seeds 2% Fertilizers 27% Labour 11% Chart 3.104 Reasons for not Using Credit (% of Households) Did not know how to get credit, 74,405, 42% Don't know about credit, 43,336, 24% Not available, 23,298, 13% Did not w ant to go into debt, 21,358, 12% Difficult bureaucracy procedure, 2,315, 1% Not needed, 8,133, 5% Credit granted too late, 679, 0% Other, 909, 1% Interest rate/cost too high, 2,784, 2% Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Religious Organisation / NGO / Project 7.5% Commercial Bank 4.5% Private Individual 4.6% Family, Friend and Relative 33.8% Saving & Credit Society 8.0% Co-operative 41.6% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 61 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 86,702 (48% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Iramba district having a relatively high proportion of households (71.5%) that received crop extension messages followed by Singida Urban (36.9%), Singida Rural (36.8%) and Manyoni (33.8%). (Chart 3.106 and Map 4.33) 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (97.3%, 83,765 households). Large scale farm provided 1.0 percent, NGO/Development project 1 percent, cooperatives 0.3% and other providers 0.4 percent (Chart 3.107). 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 72.5 percent of the households receiving extension ranked the service as being good followed by average (13 %), very good (10.8%), poor (2.6%) and no good (1.1%) (Chart 3.108) However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 93,214, 52% Households Receiving Extension , 86,702, 48% Chart 3.106 Number of Households Receiving Extension by District 0 9,000 18,000 27,000 36,000 45,000 Iramba Singida Rural Manyoni Singida Urban District Number of Households 0 15 30 45 60 75 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Government 97.3% Other 0.4% NGO / Development Project 1.0% Cooperative 0.3% Large Scale Farm 1.0% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 62,764, 72.5% Average, 11,267, 13.0% Poor, 2,254, 2.6% No Good, 925, 1.1% Very Good, 9,349, 10.8% Singida Urban 163 103 127 16 Singida Rural Manyoni Iramba 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Singida Urban Manyoni 450,174 44,501 588,491 173,993 Singida Rural Iramba 480,000 to 600,000 360,000 to 480,000 240,000 to 360,000 120,000 to 240,000 0 to 120,000 Map 3.37 SINGIDA Cattle population by District as of 1st Octobers 2003 Number of Cattle Number of Cattle Number of Cattle Per Squre Km Map 3.38 SINGIDA Cattle Density by District as of 1st October 2003 Number of Cattle Per Squre Km Tanzania Agriculture Sample Census RESULT 62 Iramba Singida Urban Singida Rural Manyoni 92 86 7 67 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Singida Urban Iramba 313,502 37,409 255,680 77,829 Singida Rural Manyoni 400,000 to 500,0000 300,000 to 400,0000 200,000 to 300,0000 100,000 to 200,0000 0 to 100,0000 Map 3.39 SINGIDA Goat population by District as of 1st Octobers 2003 Number of Goat Number of Goat Number of Goat Per Squre Km Map 3.40 SINGIDA Goat Density by District as of 1st October 2003 Number of Goat Per Squre Km Tanzania Agriculture Sample Census RESULT 63 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 64 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was to annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in the previous section (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs particularly the inputs that are not produced on the farm such as improved seeds, fungicides, inorganic fertiliser and herbicides. In Singida region farm yard manure was used by 83,259 households which represent 46 percent of the total number of crop growing households. This is followed by households using improved seeds (15%), compost (4%) fungicide (4%), inorganic fertiliser (1%), and herbicide (0.06%) (Table 2.14). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Singida mostly purchase from cooperative (53.4% of the total number of inorganic fertiliser users) followed by neighbours (28.4%) and local market/trade store (18.2 %) (Chart 3.109). Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing less than 1 km from the source (73%), followed by between 1 and 3 km (8%) and between 3 and 10 km (5%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available”(36%) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 45 percent of households responding to cost factors as the main reason for not using inorganic fertilizers. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. Table 3.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 83,259 46 96,740 54 Improved Seeds 26,415 15 153,375 85 Pestcides/Fungicide 6,912 4 173,003 96 Compost 7,786 4 172,129 96 Inorganic Fertiliser 2,659 1 177,298 99 Herbicide 117 .06 179,799 100 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 53.4 28.4 18.2 0 300 600 900 1200 1500 Co-operative Neighbour Local Market / Trade Store Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 20.0 40.0 60.0 80.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 65 More smallholders use inorganic fertilisers in Manyoni than in other districts in Singida region (83% of households using inorganic fertilisers), followed by Iramba (10.8%), Singida rural (4.6%) and Singida Urban (1.6%). 3.9.3 Improved Seeds The proportion of households that used improved seeds was 15 percent of the total number of crop growing households. Most of the improved seeds were from the local market/trade store (56%). Other less important sources of improved seed are from neighbours (23.8%), locally produced by household (10.1%). Only 0.9 percent of households using improved seeds obtain them from large scale farms (Chart 3.111). Access to improved seed is better than access to chemical inputs with 46 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The district that used improved seeds are Singida Rural (38 percent of the total number of households used improved seeds), followed by Iramba (34%), Manyoni (21%) and Singida Urban (7). (Map 3.34). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (53.1% of the total number of fungicide users). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 17 percent of households responding to “not available” as the reason for not Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.111 Number of Households by Source of Improved Seed 0.6 0.1 1.0 0.9 1.6 2.3 3.6 10.1 23.8 56.0 0 5000 10000 15000 Local Market / Trade Store Neighbour Locally Produced by Household Co-operative Development Project Crop Buyers Secondary Market Large Scale Farm Other Local Farmers Group Source of Im proved Seed Number of Households Chart 3.113 Number of Households by Source of Insecticide/fungicide 53.1 18.5 12.2 10.2 2.1 1.8 0.9 1.2 0 1000 2000 3000 4000 Local Market / Trade Store Co-operative Neighbour Other Secondary Market Local Farmers Group Crop Buyers Development Project Source of Insecticide/fungicide Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 15 30 45 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 66 using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 77 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Manyoni district (42.7 percent of the total number of households used fungicides), followed by Singida Rural (32.8%), Iramba (22.8%) and Singida Urban (1.6%). 3.10 Tree Planting The number of households involved in tree farming was 11,552 representing 6 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 186,395 trees. The average number of trees planted per household planting trees was 18 trees. The main species planted by smallholders is Eucalyptus spp (74,654 trees, 40.16%), followed by Gravellis (45,536, 24.4%), then senna spp (30683, 16.5%) and Moringa (8,976 trees, 4.8%). The remaining trees species are planted in comparatively small numbers (Chart116.). Singida Rural has the largest number of smallholders with planted trees than any other district (50%) which is dominated by Eucalypus species. This is followed by Iramba (29%) dominated by Gravellis species and to a lesser extent Leucena, then Singida Urban (12%) and Manyoni (9%) which are mainly planted with Eucalyptus and Senna species respectively (Chart 3.117 and Map 3.35.). Smallholders mostly plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 61.1 percent, followed by scattered around fields (29.5%) and then trees planted in a plantation or coppice (9.4%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (31.9%). This is followed by shade (21.5%), wood for fuel (15.8%) and poles (12.7%) (Chart 3.119). Chart 3.115 Number of Households with Planted Trees Not growing trees, 168,364, 94% hh growing trees, 11,552, 6% Chart 3.119 Number of Households by Purpose of Planted Trees 0 7 14 21 28 35 Planks / Timber Shade Fuel for Wood Poles Other Medicinal Use Percent of Households Chart 3.118 Number of Trees Planted by Location Field boundary, 79,550, 43% Scattered in field, 69,684, 37% Plantation, 37,160, 20% Chart 2.116 Number of Planted Trees by Species - Singida 0 20,000 40,000 60,000 80,000 Eucalyptus Spp Gravellis Senna Spp Moringa Spp Leucena Spp Azadritachta Spp Syszygium Spp Cyprus Spp Kyaya Spp Acacia Spp Calophylum Inophyllum Jakaranda Spp Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and District 0 150 300 450 600 750 900 Iramba Singida Rural Manyoni Singida Urban Region Number of Trees Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Leucena Spp Syszygium Spp Azadritachta Spp Jakaranda Spp Moringa Spp Kyaya Spp RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 67 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 15,529 which represent 9 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Singida Rural district (11%) followed by Iramba (10%), Singida Urban (6%) and Manyoni (1%) (Chart 3.121). Erosion control bunds accounted for 61 percent of the total number of structures, followed by water harvesting bunds (17.4%), tree belts (11.9%), terraces (5.0%), drainage ditches (2.4%) and vetiver grass (2.1%) (Chart 3.122 and Map 3.36). Erosion control bunds, water harvesting bunds and tree belts together had 166,275 structures. This represented 90.4 percent of the total structures in the region. The remaining 9.6 percentages were shared among the rest of the erosion control methods mentioned above. Singida Rural and Iramba districts had 168,941 erosion control structures (91.8 percent of the total erosion structures in the region). 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 1,257,159. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 7.5 percent of the total cat tle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Singida region was 1,255,118 (99.8 % of the total number of cattle in the region), 1,115 cattle (0.09%) were dairy breeds and 925 cattle (0.07%) were beef breeds. Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households with facilities, 15,529, 9% Households Without Facilities, 164,386, 91% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 11 6 1 10 0 3,000 6,000 9,000 Singida Rural Iramba Singida Urban Manyoni District Number of Households 0 3 6 9 12 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 61.0 17.4 11.9 5.0 2.4 2.1 0.0 0.0 0.0 20000.0 40000.0 60000.0 80000.0 100000.0 120000.0 Erosion Control Bunds Water Harvesting Bunds Tree Belts Terraces Drainage Ditches Vetiver Grass Gabions / Sandbag Dam Type of Facility Number of Structures RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 68 The census results show that 72,363 agricultural households in the region (40% of total agricultural households) kept 1.3 million cattle. This was equivalent to an average of 17 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Singida Rural which had about 588,491cattle (46.8% of the total cattle in the region). This was followed by Iramba (450,174 cattle, 35.8%), Manyoni (173,993 cattle, 13.8%) and Singida Urban (44,501 cattle, 3.5%) (Chart 3.123 and Map 3.37). However, Iramba district had the highest density (163 head per km2) (Map 3.38). Although Singida Rural district had the largest number of cattle in the region, most of then were indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant. Singida Rural was the only district with diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Thirteen percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 44 percent of all cattle in the region. Only 23 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 92 percent of total cattle rearing households had herds of size 1-30 cattle and owned 50 percent of total cattle in the region, resulting in an average of 10 cattle per cattle rearing household. There were about 705 households with a herd size of more than 151 cattle each (291,197 cattle in total) resulting in an average of 413 cattle per household. 3.12.1.3 Cattle Population Trend Cattle population in Singida decreased during the period of eight years from 1,944,272 in 1995 to 1,257,159 cattle in 2003. This trend depicts an overall annual negative growth rate of -4.7 percent (Chart 3.125). There was a decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –4.6 percent whereby the number dropped from 1,944,272 to 1,538,463. The number of cattle further decreased from 1,538,463 in 1999 to 1,257,159 in 2003 at the rate of -4.9 percent. 1,944,272 1,538,463 1,257,159 - 500,000 1,000,000 1,500,000 2,000,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 0 100 200 300 400 500 600 Number of Cattle ('000') Singida Rural Iramba Manyoni Singida Urban Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 44,501 433 493 - - - 1,115 - - 449,741 586,883 173,993 - 150,000 300,000 450,000 600,000 Iramba Singida Rural Manyoni Singida Urban Districts Number of Cattle Indigenous Improved Beef Total Cattle RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 69 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Singida region was 2,040 (1,115 dairy and 925 improved beef). The diary cattle constituted 0.09 percent of the total cattle and 55 percent of improved cattle in the region. The number of beef cattle in the region constituted 45 of the improved cattle in the region. The number of improved cattle increased from 1,662 in 1995 to 2,040 in 2003 at an annual growth rate of 3.21 percent. The growth rate was higher for the period from 1995 to 1999 (26.9%) then there was a sharp decrease from 1999 to 2003 (-16.1%) (Chart 126) 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Singida region ranked 8 out of the 21 regions with 6 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Singida region was 60,387 (34% of all agricultural households in the region) with a total of 684,420 goats giving an average of 11 head of goats per goat-rearing-household. Singida Rural had the largest number of goats (313,502 goats, 46% of all goats in the region), followed by Iramba (255,680 goats, 37%), Manyoni (77,829 goats, 11%) and Singida Urban (37,409 goats, 5%). (Chart 3.127 and Map 3.39). However, Iramba district had the highest density (92 head per km2) (Map 3.40). 3.12.2.2 Goat Herd Size Seven percent of the goat-rearing households had herd size of 1-4 goats with an average of 3 goats per goat rearing household. Seventy five percent of total goat-rearing households had herd size of 1-14 goats and owned 43 percent of the total goats in the region resulting in an average of 6 goats per goat-rearing households. The region had 1,508 households (2.5%) with herd sizes of 40 or more goats each (104,321 goats in total), resulting in an average of 69 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.1 percent of the total goats in Singida region. Improved goats for beef and diary constituted of 0.5 and 1.4 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was -4.4 percent. This negative trend implies eight years of population decrease from 978,772 in 1995 to 684,420 in 2003. The number of goats increased from 978,772 in 1995 at an estimated annual rate of 1.8 percent to 1,052,716 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -10.2 percent (Chart 128). 1,662 4,314 2,040 - 1,500 3,000 4,500 Number of cattle 1995 1999 2003 Year Chart 3.126 Dairy Cattle Population Trend 0 70 140 210 280 350 Number of Goats ('000'). Singida Rural Iramba Manyoni Singida Urban District Chart 3.127 Total Number of Goats ('000') by District 978,772 1,052,716 684,420 - 300,000 600,000 900,000 1,200,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend Singida Rural Singida Urban 3,464 0 2,508 403 Manyoni Iramba 2,760 to 3,470 2,070 to 2,760 1,380 to 2,070 690 to 1,380 0 to 690 Singida Rural Singida Urban 0 1 0 1 Manyoni Iramba 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Map 3.43 SINGIDA Pig population by District as of 1st Octobers 2003 Number of Pig Number of Pig Number of Pig Per Squre Km Map 3.44 SINGIDA Pig Density by District as of 1st October 2003 Number of Pig Per Squre Km Tanzania Agriculture Sample Census RESULT 70 Singida Urban Singida Rural Iramba 3,990 1,129 53,098 32,196 12.1% 84.9% 10.2% 44% Manyoni 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Singida Urban Singida Rural Iramba 20,152 3,419 28,370 4,434 65% 63% 77% 80% Manyoni 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.47 SINGIDA Number and Percent of households Infected with Ticks by District Number of households Number of Households Infected With Ticks Number of households Using Draft Animals Map 3.48 SINGIDA Number and Percent of Households Using Draft Animals by District Number of households Tanzania Agriculture Sample Census Percent of Households Infected With Ticks Percent of households Using Draft Animals RESULT 71 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 72 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Singida region after cattle and goats. The region ranked 4 out of 21 Mainland regions and had 8 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 39,179 (22% of all agricultural households in Singida region) rearing 309,938 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Singida Rural with 141,604 sheep (46%of total sheep in Singida region) followed by Iramba (119,704 sheep, 39%), Manyoni (31,901 sheep, 10%) and Singida Urban (16,729 sheep, 5%) and Map 3.41). Iramba district also had the highest density (43 head per km2 ) (Map 3.42). Sheep rearing was dominated by indigenous breeds that constituted 99 percent of all sheep kept in the region. Only 1 percent of the total sheep in the region was made up of improved breeds. 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at - 4.9 percent. The population decreased at an annual rate of -23.2 percent from 246,263 in 1995 to 85,679 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 17.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 13 out of 21 Mainland regions and is 0.65 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Singida region was 2,554 (1.4% of the total agricultural households in the region) rearing 6,375 pigs. This gives an average of 3 pigs per pig-rearing household. The district with the largest number of pigs was Singida Rural with 3,464 pigs (54% of the total pig population in the region) followed by Iramba (2,508 pigs, 39%) and Manyoni (403 pigs, 6%) (Chart 3.131 and Map 3.44). However, Iramba district had the highest density (1 head per km2) (Map 3.43). There are no pigs were in Singida Urban district. 246,263 85,679 164,209 - 100,000 200,000 300,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 0 35000 70000 105000 140000 N um ber of sheep Singida Rural Iramba Manyoni Singida Urban District Chart 3.129 Total Number of Sheep by District 0 1,000 2,000 3,000 Number of Pigs Singida Rural Iramba Manyoni District Chart 3.131 Total Number of Pigs by District RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 73 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 24.7 percent. During this period the population grew from 1,072 to 6,281. The pig population increased from 1072 in 1995 to 22,093 in 1999 at a high rate of 26.2 percent. The growth rate dropped to 23.3 percent during the following four years from 1999 to 2003 in which pig population increased from 2,715 to 6,281(Chart 3.132). 3.12.5 Chicken Production The poultry sector in Singida region was dominated by chicken production. The region contributed 5.0 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 125,895 raising about 1,658,178 chickens. This gives an average of 13 chickens per chicken-rearing household. In terms of total number of chickens in the country, Singida region was ranked ninth out of the 21 Mainland regions. The District with largest number of chickens was Iramba (788,336 chickens, 47% of the total number of chickens in the region) followed by Singida Rural (644,898, 39%), Manyoni (163,332, 10%) and Singida Urban (61,610, 4%) (Chart 3.133 and Map 3.45) However Iramba district had the highest density (285 chikens per km2) (Map 3.46) 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 2.58 percent. The population decreased at a rate of -1.99 percent from 1995 to 1999 after which it increased at a rate of 7.37 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety nine percent of all chicken in Singida region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 0 200,000 400,000 600,000 800,000 Number of Chickens Iramba Singida Rur Manyoni Singida Urb District Chart 3.133 Total Number of Chickens by District 1,351,988 1,247,658 1,658,178 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend - 22,093 6,375 - 7,000 14,000 21,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 74 3.12.5.3 Chicken Flock Size The results indicate that about 82 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 8 chickens per holder. About 18 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 32 chickens per holder. Only 0.32 percent of holders kept the flock sizes of more than 100 chickens at an average of 389 chickens per holder (Table 3.14). 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Singida Region decreased at an annual rate of 48.2 percent for the period of four years from 10,308 in 1995 to 7,558 in 2003. There were no layers in Iramba and Singida Urban districts (Chart 3.135). The overall annual growth rate for broilers during the four-year period from 1999 to 2003 was -14.18 percent during which the population dropped from 12,195 to 6,616. (Chart 3.136) 3.12.6. Other Livestock There were 35,013 ducks, donkeys, 16,649, turkeys, 7,501 and rabbits 840 raised by rural agricultural households in Singida region. Table 3-16 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Singida Rural District (57% of all ducks in the region), followed by Iramba (24%), Singida Urban (12%) and Manyoni (7%). Turkeys were reported in Singida Rural district only (Table 3.16). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 28,333 23 82,492 3 5 - 9 36,894 29 237,115 6 10 - 19 38,301 30 489,501 13 20 - 29 12,115 10 270,586 22 30 - 39 5,370 4 174,050 32 40 - 49 1,937 2 85,947 44 50 - 99 2,471 2 162,264 66 100+ 401 0 156,222 389 Total 125,823 100 1,658,178 13 Table 3.16 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Iramba 8,357 . . 12,295 1,142 Singida R 19,791 7,501 . 4,354 2,859 Manyoni 2,528 . . . . Singida U 4,336 . 840 . . Total 35,013 7,501 840 16,649 4,001 0 0 2099 3586 5490 0 0 3030 0 1000 2000 3000 4000 Number of Chickens Iramba Singida Rur Manyoni Singida Urb District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers 10,308 0 683 12,195 7,589 6,616 0 5000 10000 15000 Number of layers 1995 1999 2003 Year Chart 3.136 Layers Population Trend Singida Urban Singida Rural 142 285 15 139 Manyoni Iramba Singida Urban Singida Rural 61,611 788,337 163,332 644,898 Manyoni Iramba Map 3.45 SINGIDA Chicken population by District as of 1st Octobers 2003 Number of Chicken Number of Chicken Number of Chicken Per Squre Km Map 3.46 SINGIDA Chicken Density by District as of 1st October 2003 Number of Chicken Per Squre Km Tanzania Agriculture Sample Census 640,000 to 800,000 480,000 to 640,000 320,000 to 480,000 160,000 to 320,000 0 to 160,000 280 to 350 210 to 280 140 to 210 70 to 140 0 to 70 RESULT 75 Iramba Singida Urban 1,147 340 2,043 169 1.8% 3.1% 2.8% 0.5% Singida Rural Manyoni Singida Urban Iramba Singida Rural 4,786 26,267 25,451 3,460 43% 42% 34.8% 10.5% Manyoni Map 3.49 SINGIDA Number and Percent of households Using Farm Yard Manure by District Planted Area (ha) Number of households Using Farm Yard Manure Number of households Using Compost Manure Map 3.50 SINGIDA Number and Percent of households Using Compost by District Planted Area (ha) Tanzania Agriculture Sample Census Percent of households Using Farm Yard Manure Percent of households Using Compost Manure 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 2,400 to 3,000 1,800 to 2,400 1,200 to 1,800 600 to 1,200 0 to 600 RESULT 76 Singida Urban Singida Rural Iramba 4,860 833 1,183 5,363 14.7% 7.5% 1.9% 7.3% Manyoni 4,800 to 6,000 3,600 to 4,800 2,400 to 3,600 1,200 to 2,400 0 to 1,200 Map 3.51 SINGIDA Number and Percent of households Without Toilets by District Number of households Number of Households Without Toilets Tanzania Agriculture Sample Census Percent of Households Without Toilets RESULT 77 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 78 3.12.7 Pest and Parasite Incidence and Control The results indicate that 72 percent and 23 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Manyoni district but lowest in Singida Urban district (Map 3.47). The most practiced method of controlling ticks spraying with 41 percent of all livestock- rearing households in the region using the method. Other methods used were dipping (14%), smearing (3%) and other traditional methods like hand picking (13%). However, 29 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 47 percent of livestock-rearing households and dipping (6%). However, 46 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 34,103 (42 % of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 44.3 percent, goats (31.5%), sheep (14.3%) and pigs (9.9%) (Chart 3.138) 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 45,588, representing 55 percent of the total livestock- rearing households and 25 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 98.5 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (1.5%). About 61 percent of livestock rearing households described the general quality of livestock extension services as being good, 15 percent said they were very good and 12 percent said they were average. However, 7 percent of the livestock rearing households said the quality was not good whilst 5 percent described them as poor (Chart 3.139). Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Iramba Singida Rur Manyoni Singida Urb District Percent Ticks Tsetseflies 0 20 40 60 80 Percent Iramba Singida Rur Manyoni Singida Urb District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Average 12% No good 7% Poor 5% Very Good 15% Good 61% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 79 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 97 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 3 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). Almost all livestock rearing households accessing the services at a distance of less than 14 kms and the majority were within 5kms (Chart 3.141). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 24,573 (87% of livestock rearing households in Singida region) whilst 2,806 households (10%) resided between 5 and 14 kms. However, 848 households (3%) had to travel a distance of 15 or more kms to the nearest watering point (Chart 3.142). Iramba district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Singida Urban, Singida Rural and Manyoni districts. In Manyoni district about 20 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). Chart 3.140 Number of Households by Distance to Verinary Clinic More than 14km, 1,725, 3% Less than 14km, 47,676, 97% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 40,000 Iramba Singida Rur Manyoni Singida Urb District Number of Households Less than 14km More than 14km Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 24,573, 87% 5-14 kms, 2,806, 10% 15 or more kms, 848, 3% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0.0 25.0 50.0 75.0 100.0 Iramba Singida Urb Singida Rur Manyoni District Number of Households Less than 5 kms 5-14 kms 15 or more kms RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 80 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Singida region is encouraging with 90,414 households (50.3% of the total households in the region) using them (Chart 3.144). The number of households that used draft animals in Iramba district was 53,098 (59% of the households using draft animals in the region). In Singida Rural the number of households using draft animals was 32,196 (36%). The use of draft animals was small in Manyoni and Singida Urban (Chart 3.145 and Map 3.48) The region had 199,820 oxen that were used to cultivate 182,070 hectares of land. This represents only 8.9 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Iramba district (105,194 ha, 58% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Singida region was 79,651 (44% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 180,367 ha or 37% of the area planted with annual crops and vegetables in Singida region during the long rainy season) was applied with farm yard manure (Map 3.49). 3.12.9.4 Use of Compost 0 20,000 40,000 60,000 Number of Households Iramba Singida Rural Manyoni Singida Urban District Chart 3.145 Number of Households Using Draft Animals by District - Singida Chart 3.146 Number of Households Using Organic Fertiliser Using Organic Fertilizer, 79,651, 45% Not Using Organic Fertilizer, 97,717, 55% Chart 3.147 Area of Application of Organic Fertiliser by District Singida 0 7,000 14,000 21,000 28,000 35,000 Iramba Singida Rural Manyoni Singida Urban District Area of Fertiliser Application (ha) Farm Yard Manure Compost 3.144 Number of Households Using Draft Amimals Using draft animal, 90,414, 50.3% Not using draft animal, 89,502, 49.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 81 Only 7,523 ha (4% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost was found in Iramba district with 32,951 hectares (47.1% of the total area applied with compost) followed by Singida Rural (27,618 ha, 39.5%), Manyoni (5,504 ha, 7.9%) and Singida Urban (3,905 ha, 5.6%) (Chart 3.147 and Map 3.50) 3.12.10 Fish Farming There was no fish farming in the region. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, tarmac road was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 154.6 kilometers from the agricultural household’s dwelling. Other services and their respective average distances in kilometers from the dwellings were feeder road (2.0), primary school (3.0), all weather road(6.0), health clinlcs (6.8), primary market (7.7), secondary market (11.6), secondary school (18.2), hospital (35.7) and tertiary market (42.2) (Table 3.17). Only 5 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 33 percent reported them to be ‘no good’. Twenty four percent of the agricultural households said the infrastructure and services were good. Those who said the infrastructures and services were poor were 21 percent while 17 percent said they were average. 3.13.2 Type of Toilet A large number of rural agricultural households use traditional pit latrines (159,503 households, 88.7% of all rural agricultural households) 7,005 households. This is followed by flush toilets (7,005 houeholds 3.9%), improved pit latrines (794 households, 0.4%) and other types of toilets (375 household, 0.2%). However, 12,238 households (6.8%) in the region had no toilet facilities (Chart 3.148). The distribution of the households without toilets within the region indicates that 44 percent of them were found in Singida Rural district followed by Manyoni (40%), Iramba (10%), and Singida Urban (7%) (Map 3.51) Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Iramba 14.9 1.8 4.5 2.4 37.0 6.3 167.4 6.5 9.2 41.1 186.6 Singida Rur 18.9 2.9 7.5 2.0 35.8 8.0 115.9 9.0 12.4 40.3 114.0 Manyoni 24.1 5.7 6.8 1.4 41.5 6.0 49.7 8.5 15.8 58.9 221.4 Singida Urb 14.5 2.1 2.4 1.2 11.2 4.3 16.6 3.7 7.4 11.0 44.1 Total 18.2 3.0 6.0 2.0 35.7 6.8 67.7 7.7 11.6 42.2 154.6 Chart 3.148 Agricultural Households by Type of Toilet Facility Flush Toilet, 7005, 3.9% No Toilet , 12238, 6.8% Improved Pit Latrine , 794, 0.4% Other Type, 375, 0.2% Traditional Pit Latrine, 159503, 88.7% RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 82 3.13.3 Household’s Assets Radios were owned by most rural agricultural households in Singida region with 69,474 households (38.6% of the agriculture households in the region) owning the asset followed by bicycle (53864 households, 29.9%), iron (21,799 households, 12.1%), wheelbarrows (8,003 households, 4.4%), vehicles (1,464 households, 0.8%), mobile phones (1,463 households, 0.8%), television/videos (801 households, 0.4%) and landline phone (605 households, 0.3%) (Chart 3.149) 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region with 79.9 percent of the total rural households using this source of energy followed by hurricane lamp (12%), fire wood (5.3%), and pressure lamp (2.4%). The remaining sources of lighting were minor. (Chart 3.150) 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 95.1 percent of all rural agricultural households in Singida region. This is followed by crop residues (2.3%) and charcoal (1.7%). The rest of energy sources accounted for 0.9 percent. These were solar energy (0.4%), mains electricity (0.2%), paraffin/kerosene (0.1%), bottled gas (0.1%) and livestock dung (0.1%) (Chart 3.151). 3.13.6 Roofing Materials The most common material used for roofing the main dwelling was grass and mud and it was used by 73.2 Chart 3.149 Percentage Distribution of Households Owning the Assets 4.4 0.8 0.8 0.4 0.3 38.6 29.9 12.1 0.0 10.0 20.0 30.0 40.0 Radio Bicycle Iron Wheelbarrow Vehicle Mobile phone Television / Video Landline phone Assets Percent Chart 3.150 Percentage Distribution of Households by Main Source of Energy for Lighting Solar, 269, 0.1% Other, 304, 0.2% Firew ood, 9499, 5.3% Gas (Biogas), 118, 0.1% Pressure Lamp, 4330, 2.4% Mains Electricity, 118, 0.1% Hurricane Lamp, 21581, 12.0% Wick Lamp, 143694, 79.9% Chart 3.151 Percentage Distribution of Households by Main Source of Energy for Cooking Firewood, 171131, 95.1% Charcoal, 3104, 1.7% Bottled Gas, 103, 0.1% Mains Electricity, 448, 0.2% Solar, 641, 0.4% Livestock Dung, 143, 0.1% Parraffin / Kerocine, 143, 0.1% Crop Residues, 4202, 2.3% Singida Rural Singida Urban Iramba 11,014 10,744 1,306 31,405 15% 11.7% 32.5% 50.2% Manyoni 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Singida Urban Singida Rural Iramba 8,292 52,230 23,176 48,055 74.5% 71.4% 70.1% 76.9% Manyoni 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Map 3.52 SINGIDA Number and Percent of households Using Grass/mud for rooing materials by Distric Number of household Number of households Using Grass/Mud For Rooing Materials Number of Households Eating 3 Meals Per Day Map 3.53 SINGIDA Number and Percent of households Eating 3 meals per day by District Nuber of household Percent of Households Using Grass/Mud For Rooing Materials Percent of Households Eating 3 Meals Per Day Tanzania Agriculture Sample Census 83 RESULT RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 84 percent of the rural agricultural households. This was followed by iron sheets (20.7%), grass/leaves (5.4%), asbestos (0.2%), tiles (0.1%), and others (0.3%) (Chart 3.152) Singida Rural district had the highest percentage of households with grass and mud roofing (40%) followed by Iramba district (36%), Manyoni (18%) and Singida Urban (6%) (Chart 3.153 and Map 3.52) 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Singida region was unprotected well (31.3 percent of households using the source for both seasons. This is followed by piped water (17.7% of households in the wet season and 20.1 percent during dry season), lake/river (15.7% of households during the wet season and 14.2% in the dry season), protected well (15.2% of households in the wet season and 17.3% during dry season) and uncovered rain water catchments (10.1% of households in the wet season and 7.05 during dry season), unprotected spring (8.0% of household in the wet season and 8.8% during dry season), protected spring (0.9% of household for each season) and other sources (1.0% of household in the wet season and 0.4% during dry season) (Chart 3.154) Chart 3.152 Percentage Distribution of Households by Type of Roofing Material Asbestos 0.2% Grass & Mud 73.2% Iron Sheets 20.7% Grass / Leaves 5.4% Tiles 0.1% Other 0.3% Chart 3.153 Percentage Distribution of Households with Grassy and Mud Roofs by District 40 36 18 6 0 10 20 30 40 Singida Rur Iramba Manyoni Singida Urb District Percent Chart 3.154 Percent of Households by Main Source of Drinking Water and Season 0.0 7.0 14.0 21.0 28.0 35.0 Uprotect - ed Well Piped Water Lake /River Protected Well Uncover -ed Rain Catchment Unprotect -ed Spring Other Main source Percent of Households Wet Season Dry Season Chart 3.155 Percent of Households by Distance to Main Source of Water and Season 0 10 20 30 40 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 85 About 45 percent of the rural agricultural households in Singida region obtained drinking water within a distance of less than one kilometer during wet season compared to 32 percent of the households during the dry season. However, 55 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 68 percent of households in the dry season. The most common distance from the source of drinking water was between 500 meters and 1 km (Chart 3.155). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Singida region normally have 2 meals per day (66.5 percent of the households in the region). This is followed by 3 meals per day (30.3 percent) and 1 meal per day (3.0 percent). Only 0.2 percent of the households have 4 meals per day (Chart 3.156). Singida Rural district had the largest percent of households eating one meal per day whilst Iramba had the highest percent of households eating 3 meals per day. (Table 3.18 and Map 3.53). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 118,687 (66% of the agricultural households in Singida region) with 62,773 households (52.9 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31.8%). Very few households had meat three or more times during the respective week. About 34 percent of the agricultural households in Singida region did not eat meat during the week preceding the census (Chart 3.157 and Map 3.54). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 91,646 (51% of the total agricultural households in Singida region) with 47,096 households (51 % of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish two times (29%). In general, the percentage of households that consumed fish twice or more during the week in Singida region was 44,550 (49% of the agricultural Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Iramba 704 1.1 30420 48.6 31405 50.2 0 0.0 62529 Singida Rur 3474 4.7 58471 79.9 11014 15.0 237 0.3 73196 Manyoni 973 2.9 21265 64.3 10744 32.5 82 0.2 33064 Singida Urb 258 2.3 9519 85.6 1306 11.7 42 0.4 11125 Total 5409 3.0 119675 66.5 54469 30.3 361 0.2 179914 Chart 3.156 Number of Agriculural Households by Number of Meals per Day Three Meals, 54469, 30.3% Two Meals, 119676, 66.5% One Meal, 5409, 3.0% Four Meals, 361, 0.2% Chart 3.157 Number of Households by Frequency of Meat and Fish Cosumption 0 25000 50000 75000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Singida Urban Iramba Manyoni 3,064 23,590 3,541 16,901 9.3% 32.2% 31.8% 27% Singida Rural 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Manyoni Singida Urban Singida Rural Iramba 8,163 3,361 21,534 29,715 24.7% 30.2% 34.4% 40.6% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Map 3.54 SINGIDA Number and Percent of households eating Meat Once per Week by District Number of household Number of Households Eating Meat Once per Week Number of Households Eating Fish Once Per Week Map 3.55 SINGIDA Number and Percent of households eating Fish once per week by District Number of household Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once Per Week Tanzania Agriculture Sample Census RESULT 86 Singida Urban Singida Rural Iramba Manyoni 3,519 16,052 25,746 9,745 32% 26% 35% 29% 20,600 to 25,800 15,400 to 20,600 10,400 to 15,400 5,200 to 10,400 0 to 5,200 Map 3.56 SINGIDA Number and Percent of households Reporting food Insufficiency by District Number of household Number of households Reporting food Insufficiency Percent of households Reporting food Insufficiency Tanzania Agriculture Sample Census RESULT 87 RESULTS – Poverty Indicators _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 88 households that ate fish in the region during the respective period). About 49 percent of the agricultural households in Singida region did not eat fish during the week preceding the census (Chart 3.157 and Map 3.55). 3.13.9 Food Security In Singida region, 61,025 households (34% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 9,646 (5%) said they sometimes experienced problems, 17 percent often experienced problems and 14 percent always had problems in satisfying the household food requirements. About 31 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.56). 3.13.10 Main Sources of Cash Income The main cash income of the households in Singida region was from other casual cash earnings (29.6 percent of smallholder households), followed by sales of livestock (16.5%), selling of cash crops (16.2%), businesses (10.7%) and sales of food crops (9.1%). Only 6.6% of smallholder households reported the cash remittances as their main source of income, followed by forest products (6.5%) and wages and salaries (3.1%) (Chart 3.158). Chart 3.158: Percentage Distribution of the Number of Households by Main Source of Income Fishing 0.7% Livestock Products 0.7% not applicable 0.0% Other 0.4% Forest Products 6.5% Food Crops 9.1% Other Casual Cash Earnings 29.6% Cash Crops 16.2% Livestock 16.5% Wages & Salaries 3.1% Remittance 6.6% Business Income 10.7% DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 90 4 SINGIDA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Singida Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. 4.2.1 District Profiles Thee following district profiles highlight the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Iramba Iramba district had the second largest number of agricultural households in the region and it had among the highest percent of households involved in smallholder agriculture in the region. It was the third highest district with smallholders involved in crop farming only and those involved in crop and livestock production. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Iramba district was annual crop farming, followed by tree forest resources and off farm income. However, the district had the highest percent of households with no off-farm activities and the least percent of households with more than one member with off-farm income. Compared to other districts in the region, Iramba had the least percent of female headed households (20.5%) and it had the highest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Iramba has the second highest literacy rate for agricultural household members (69.7%) and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the heads of household was the least in the region. It has the second highest utilized land area per household (2.5 ha) and the allocated area is not fully utilised indicating a low level of land pressure. The total planted area is the second greatest in the region due to the presence of good wet and dry seasons; however it has the second highest planted area per household as compared to other districts. The district was the most important for maize production in the region with a planted area of 60,761 ha; however the planted area per household was the highest in the region. Paddy production was very important with a planted area of 615 hectares and the production of sorghum was the second highest in the region. Iramba had no wheat production. Cassava production was the highest and accounted for 45 percent of the quantity harvested in the region. The district had no planted area of Irish potatoes. The production of beans in Iramba was the second highest in the region with a planted area of 4,209 ha. Oilseed crops are important in Iramba and had the highest production of sunflower in the region with a planted area of 24,225 ha. Vegetable production was important in the district. It had the second largest area planted with onions (214 ha) accounted for 25.8 percent of the onion production. Traditional cash crops were not grown in the district. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 91 Compared to other districts in the region, Iramba has a moderate planted area with permanent crops which were dominated by mango (806 ha), banana (503 ha) and star fruit (70 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Iramba had the largest area planted with improved seed in Singida region and this was due to the high planted area of vegetables. The district had the largest area planted with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Iramba district had the highest level of insecticide use. The use of fungicides was the third highest in the region. Also the district had the second highest use of herbicide in the region. It had the third largest irrigated area (2,867) ha. The most common source of water for irrigation was from dams and wells using hand bucket. Watering can and bucket were the most common means of water application. The most common method of crop storage was the locally made traditional crib. The proportion of households storing crops in the district was the least in the region. The district had the third largest number of households selling crops, however for those who did not sell, the main reason for not selling was insufficient production. The third highest percent of households processing crops in Singida region was found in Iramba district, most of the processing was done by neighbours machine. The district had the highest percent of households selling processed crops to neighbours in the region and no sales were made to traders on farm, farmers association and secondary market. Although small, access to credit in the district was to both men and women headed households and the main sources of credits were family, friends, relatives and credit societies. A comparatively large number of households received extension services in Iramba and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Iramba (with 54,465 planted trees) and most of the trees were Senna, Gravellis with some Leucena species. The second highest proportion of households with erosion control and water harvesting structures was found in Iramba district and most of these were erosion control bunds, however it also had high number of tree belts, water harvesting bunds, vetiver grass and drainage ditches. The district had the second largest number of cattle in the region and most of them were indigenous. Goat production was the second largest in the region; however it was the second largest district with population of sheep in the region. It had the second largest number of pigs in the region and the largest number of chickens. The district had no layers. The district had high numbers of donkeys, ducks and moderate number of unspecified animals. It had third largest number of households that reported Tsetse and tick problems and also it had the third largest number of households de-worming livestock. The use of draft animals in the district was highest while fish farming was not practiced. It had amongst the best access to primary schools and feeder roads compared to other districts. However, it had one of the worst access to primary markets and tarmac roads. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 92 Iramba district had the least percent of households without toilet facilities and it had the highest percent of households owning bicycles, vehicles and television/video. It had no households using mains electricity in the district. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the smallest percent of households with grass roofs and 21 percent of households had iron sheet roofs. The most common source of drinking water was from surface water. It had the highest percent of households having three and two meals per day and the lowest percent having 1 meal per day. The district had the lowest percent of households that did not eat meat and the second highest percent of households that did not eat fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.2 Singida Rural Singida Rural district had the largest number of agricultural households in the region and it had the third highest percentage of households involved in smallholder agriculture. Most smallholders were involved in crop and livestock production, followed by crops only. It had a very small number of livestock only households and pastoralists were found in the district. The most important livelihood activity for smallholder households in Singida Rural district was annual crop farming, followed by off farm income. The district had the third highest percent of households with no off-farm activities and also the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Singida Rural had small percent of female headed households (23.2%) and it had one of the highest average age of the household head in the region. Its household size of 5 members per household was average for the region. Singida Rural had a comparatively high literacy rate for agricultural household members and this was reflected by the district having the highest level of school attendance in the region. It had a moderate utilized land area per household (2.0ha) and 94 percent of the allocated area was currently being utilised. The district had the second largest planted area in the region. The district was moderately important for maize production in the region with a planted area of 42,787 ha, and the planted area per maize growing household was also moderate for the region. Paddy was grown in the district with a planted area of 1,140 ha being the second in the region. The district had the second largest area planted with sorghum in the region with 29,328 hectares. Though small, cassava production is the second highest in the region with a planted area of 964 hectares. Irish potatoes are not grown in the district. The production of beans in Singida Rural district was the second highest in the region with a planted area of 1,051ha. Singida Rural district has the third largest groundnut planted area in Singida region with a planted area per groundnut growing household of 0.52 ha. Vegetable production was important in the district. It had the third largest planted area with tomatoes (218 ha). Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Singida Rural had the largest planted area with permanent crops which were dominated by bananas (2,739 ha), sugarcane (462 ha), guava (439 ha) and mango (154 ha). Other permanent crops were either not grown or were grown in very small quantities. As with most districts in the region, most land clearing and preparation was done by oxen, with the highest amount of land preparation in Singida Rural district being done by oxen. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 93 The use of inputs in the region was very small, however district differences existed. Singida Rural had the second largest area planted with improved seeds in the region and had the third highest proportion of households using improved seeds. The district had the second largest planted area with the application of fertilizers (farm yard manure, compost and inorganic fertiliser), however most of these were farm yard manure. Compared to other districts in the region, Singida Rural district had low level of insecticide use. The use of fungicides was the second highest in the region. Application of herbicides was the highest. It had the second largest irrigated area (7,832 ha). The most common source of water for irrigation was from well using hand bucket. Flood was the major means of water application. The most common method of crop storage in Singida rural district was the locally made traditional crib. The proportion of households storing crops in the district was relatively high. Singida Rural district was one of the districts with a moderate number of households selling crops, however for those that did not sell, the main reason for not selling was insufficient production. Singida Rural was among the districts with the highest percent of households processing crops in Singida region and most of the processing was done by neighbours machine. The district was among the two districts with households selling processed crops to marketing cooperatives and no sales were made to local market, secondary markets or trade at farm. Although very small, access to credit in the district was to men headed households and the main sources were commercial bank and private individuals. A comparatively small number of households received extension services in Singida Rural district and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was not important in Singida Rural (with 93,465 planted trees) and most of the trees were Ecalyptus species and Gravellis. The district had the highest proportion of households with erosion control and water harvesting structures and most of these were erosion control bunds and water harvesting bunds; however it also had a number of terraces and drainage ditches. The district had the largest number of cattle in the region and almost all of them were indigenous. Goat production was the second largest in the region; however it had the largest population of sheep in the region. It had the largest number of pigs in the region and a large number of chickens. Many ducks, turkeys and donkeys but no rabbits were found in the district. A few households reported tsetse fly problems and many reported tick problems in Singida Rural district and it had the highest number of households de-worming livestock. The district had the second largest number of households using draft animals in the region. Fish farming was not practiced in the district. It has amongst the poorest access to secondary schools, hospitals, district capital and tertiary market compared to other districts. It also had one of the worst access to tarmac road. The percentage of households without toilet facility in Singida Rural district was 7.3 percent and was among the districts with the highest percent of households owning wheel barrows. Also, the district had the lowest percentage of households with vehicles, bicycles, tv/video and mobile phones. It was the only district with households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 94 for cooking. The roofing material for most of the households in the district was grass/mud (71.4%) and iron sheets (21.4%). The most common source of drinking water was from unprotected well. It was the second highest percent of households having two meals per day. The district had the third highest percent of households that did not eat meat and the least district in percentage of household that did not eat fish during the week prior to enumeration, however small number of households seldom had problems with food satisfaction. 4.2.3 Manyoni Manyoni district had the largest number of agricultural households in the region and it had amongst the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in production of crops only, followed by crops and livestock. Livestock only production and pastoralists were not found in the district. The most important livelihood activity for smallholder households in Manyoni district was annual crop farming, followed by off farm income. However, the district has the third highest percent of households with off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Manyoni had the third highest percent of female headed households (23.1%) and it had one of the least average age of the household head in the region. Its average household size of 5 members per household was average for the region. Manyoni has the least literacy rate for agricultural household members and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was the highest than in the region. It has a higher utilized land area per household (2.6ha) than the regional average of 2.2 ha and 77 percent of the allocated area is currently being utilised. The total planted area is lower than in other districts in the region, however it has the highest planted area per household (3.3ha) attributed to the low number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 32,035 ha, however the planted area per household was 1.18 ha which was the second highest in the region. Paddy production was important in the district with the highest area planted (1,873 ha). The district had the third highest production of sorghum (8,589 ha). Irish potatoes were produced in small quantities with no wheat production. The district had the largest planted area of cassava accounting for 34 percent of the cassava planted area in the region. The production of beans in Manyoni was the second highest in the region with a planted area of 3,051 ha. Oilseed crops were important in Manyoni district with the highest area planted with groundnut (5,897 ha) accounting for 58 percent of the total planted area in the region. Vegetable production was not important in the district. Traditional crops were mainly grown in the district with 1,387 ha of tobacco and 687 ha of cotton. Permanent crops were important in Manyoni district (34.2% of the total permanent crop planted area in Singida region was found in the district). The most prominent permanent crops in the district included mangos (2,770 ha) and guava (269 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand and small land preparation was done by oxen. DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 95 The use of inputs in the region was small, however district differences existed. Manyoni had the third largest area planted with improved seeds in Singida region and this was due to the dominance of traditional crops which need improved seed for good harvest. The district had small area planted with the application of fertilizers (farm yard manure, compost and inorganic fertilizer), however most of these were farm yard manure. Compared to other districts in the region, Manyoni district had the second smallest area applied with herbicides and the largest area applied with fungicides. The use of pesticides was relatively moderate. It had the largest irrigated area (8,405 ha). The most common source of water for irrigation was from canal using gravity. Flood was the most common means of water application and bucket/watering can were also used. The most common method of crop storage in Manyoni was in sacks/open drum; however the proportion of households storing crops in the district was the highest in the region. The district had the highest percent of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. Manyoni district had the highest percent of households processing crops in the region and most of the processing was done to neighbours machine. However, the district had the second highest percent of households processing crops on farm by hand. The district had moderate percent of households selling processed crops. The district had the highest percent of households receiving credit with slightly more male headed household accessed credit than female headed households. A comparatively smaller number of households received extension services in Manyoni district and most of the service was from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming was important in Manyoni district (with 16,302 planted trees) and most of these were Moringa species with some Senna species. The least proportion of households with water harvesting bunds was found in Manyoni district and it also had the third largest number of erosion control bunds. The district had a moderate number of cattle in the region and most of these were indigenous. Goat and sheep production was small compared to other districts. It had the smallest number of pigs in the region and the third largest number of chickens, all of which are indigenous. The largest number of layers was found in Manyoni district. The district had small number of ducks; however it had no rabbits, turkeys and donkeys. The largest percent of households reported tsetse fly and tick problems. The district had the least number of household de-worming livestock. The use of draft animals in the district was low with (12%) of household using draft animals. Fish farming was not practiced in the district. It had amongst the best access to feeder roads, primary schools, and all weather roads compared to other districts. However, it had one of the worst accesses to tarmac roads, district capital and hospitals. Manyoni district had the highest percent of households with no toilet facilities and it had no households owning landline, mains electricity, solar, biogas and small percentage of households had vehicles, wheel barrows, Tv/video and mobile phones. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had a high percent of households with grass/mud roofs (70.1%) with 18.2 percent of households having iron sheets. The most common source of drinking water was piped water. Sixty four point three percent of the households in the district reported having two meals per day and 32.5%only 0.2 percent of the household reported having DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 96 three meals per day with only 0.2 percent of households having more than four meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration; however few households seldom had problems with food satisfaction. 4.2.4 Singida Urban Singida Urban district had the least number of households in the region and it had the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. The district had no households with livestock only or pastoralists. The most important livelihood activity for smallholder households in Singida Urban district was annual crop farming, followed by off farm income and tree/forest resources. However, the district had the second lowest percent of households with off-farm activities and also, the second highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Singida Urban had the highest percent of female headed households (26.2%) and it had the third highest average age of the household head. Its average household size of 5 members per household was average for the region. Singida Urban had the highest literacy rate for agricultural household members and this was reflected by the concomitant relatively low level of school attendance in the region. The literacy rate for the heads of household was the second highest in the region. It had the smallest utilized land area per household (1.3ha) and the allocated area was almost fully utilized indicating a high level of land pressure. The total planted area was greater than in other districts in the region due to the presence of good wet and dry seasons, however it had the lowest planted area per household (1.4ha) attributed to the high number of smallholders in the district. The district was moderately important for maize production in the region with a planted area of over 1,694 ha, however the planted area per household was the least in the region. Paddy production was not important with a planted area of only 39 hectares and the production of sorghum was very small. Singida Urban was among the districts that did not produce wheat and Irish potatoes. The production of beans in Singida Urban was the least compared to other districts in the region with a planted area of 17 hectares. Oilseed crops were not important in Singida Urban while simsim and groundnuts were not grown in the district. Vegetable production was less important in the district. It had the second largest area planted with tomatoes (82 ha) and the third largest area planted with onions (12 ha) in the region and accounted for 22 percent of the tomato production, 1.5 percent of the onion production in the region. Traditional cash crops (e.g. tobacco and cotton) were not grown in the district. Compared to other districts in the region, Singida Urban had the area smallest area planted with permanent crops which were dominated by guava (545 ha) and banana (45 ha) and mango (43 ha). Other permanent crops were either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand, however slightly more land preparation was done by oxen compared to most other districts. The use of inputs in the region was very small, however district differences existed. Singida Urban had the smallest area planted with improved seeds in Singida region. The district had the smallest area planted with the application of fertilizers DISTRICT PROFILES. _________________________________________________________________________________________ _ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 97 (farm yard manure, compost and inorganic fertiliser), however most were farm yard manure. Compared to other districts in the region, Singida Urban district had low level of insecticides use. The use of fungicides and herbicides were low compared to other districts. It had the smallest area under irrigation in the region (1,113 ha). The most common source of water for irrigation was from well using hand bucket. Bucket/watering can was the most common means of water application. The most common method of crop storage was the locally made traditional crib; however the proportion of households not storing crops was the highest in the region. The district had the lowest number of households selling crops, however for those that did not sell; the main reason for not selling was insufficient production. The least percent of households processing crops in Singida region was found in Singida Urban district and most of the processing was done by neighbours machine. The district had a high percent of households selling processed crops to neighbours and no sales were made to traders on farm. Although very small, access to credit in the district was to women headed households and the main sources of credit were religious organisations, NGO and project. A comparatively large number of households received extension services in Singida district and all the service was from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming was important in Singida Urban (with 22,410 planted trees) and most of these were Eucalyptus species with some Gravellis species and Syszygium species. The lowest proportion of households with erosion control and water harvesting structures was found in Singida Urban district and most of these were erosion control bunds; however it also has high number of water harvesting bunds and drainage ditches. The district has the least number of cattle in the region and most of them were indigenous. Goat and sheep production were the smallest in the region with a total number of 37,409 goats and 16,729 sheep; It had the smallest number of pigs and chicken in the region. The district had no layers and the second largest number of broilers in the region. The district had a moderate number of ducks and rabbits with no turkeys or donkeys. The smallest number of households reporting Tsetse fly and tick problems was in Singida Urban and it had the third largest number of households de-worming livestock. The use of draft animals in the district was very small and fish farming was practiced It was amongst the districts with the best access to feeder roads, primary schools and all weather roads compared to other districts. However, it had one of the worst accesses to tertiary market and tarmac roads. Singida Urban district had the second highest percent of households with no toilet facilities and it had the lowest percent of households owning pressing iron, vehicles, and land line. It had the no households using mains electricity in the region. The most common source of energy for lighting was the wick lamp and practically all households used firewood for cooking. The district had the second largest percent of households with grass/mud roofs (74.5%), with 23.2 percent of households having iron sheets. The most common source of drinking water was from protected well. It had the highest percent of households having two meals per day and the lowest percent with 3 meals per day. The district had the second highest percent of households that did not eat meat and was the third highest percent of household that did not eat fish during the week prior to enumeration, however very few households seldom had problems with food satisfaction. APPENDIX II 98 4. APPENDICES Appendix I Tabulation List................................................................................................................ 99 Appendix II Tables........................................................................................................................... 119 Appendix III Questionnaires .............................................................................................................. 310 APPENDIX II 99 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD........................................................................................ 199 2.1: Number of Agricultural Households by Type of Household and District, 2002/03 Agriculture Year ............................................................................................................... 120 2.2: Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year .............................................................................................................. 120 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES ......................................................... 121 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District ................................................................................................................. 122 3.1a First Most Importance.................................................................................................................. 122 3.1b Second Most Importance ............................................................................................................. 123 3.1c Third Most Importance................................................................................................................ 123 3.1d Fourth Most Importance .............................................................................................................. 123 3.1e Fifth Most Importance ................................................................................................................. 124 3.1f Sixth Most Importance ................................................................................................................. 124 3.1g Seventh Most Importance ............................................................................................................. 125 HOUSEHOLDS DEMOGRAPHS ........................................................................................................ 127 3.2 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) ......................................................................................... 128 3.3 Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %)........................................................................................... 128 3.4 Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year....................................................................................................... 128 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year............ 129 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year.................................................... 129 3.7 Number of Agricultural Household Members By Main Activity andDistrict, 2002/03 Agricultural Year........................................................................................................ 129 3.8 Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ...................................................... 130 3.9 Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year ............................................................... 130 APPENDIX II 100 3.10 Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year.................................. 131 3.11 Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year................................................ 131 3.12 Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year .................................................................... 131 3.13 Mean, Meadian, Mode of Age of Head of Agricultural Household and District ..................... 131 3.14 Time Series of Male and Female Headed Households............................................................. 132 3.15 Literacy Rates of Heads of Households by Sex and District.................................................... 132 LAND ACCESS/OWNERSHIP ............................................................................................................ 133 4.1 Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year...................................................................................................................... 134 4.2 Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year...................................................................................................................... 135 LAND USE .............................................................................................................................................. 137 5.1 Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year ............................................................................................ 138 5.2 Area of Land (Ha) by type of Land Use and District during 2002/03 Agricultural Year ........ 138 5.3 Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year.................................................................. 138 5.4 Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District during 2002/03 Agricultural Year................. 139 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year................... 139 COMMUNIAL RESOURCES............................................................................................................... 141 6.1 Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year ................................... 142 6.2 Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District............................................................................. 142 6.3 Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year District............................................................................. 143 6.4: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District................................... 143 6.5 Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District................................... 144 APPENDIX II 101 6.6 Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District................................... 144 6.7 Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District................................................ 144 6.8 Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District................................... 145 6.9 Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District........................................ 145 6.10 Number of Agricultural Households with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year District................................... 145 TOTAL ANNUAL CROP & VEGE PRODUCTION - LONG AND SHORT RAINY SEASON .. 147 7.1 & 7.2c Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region..................................................................... 148 7.1 & 7.2d Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region..................................................................... 149 7.1 & 7.2e Total Number of Agriculture Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year- SHORT RAINY SEASON.................................................................................................... 150 7.1 1& 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Singida Region .............................................................................................. 150 7.1 Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 150 7.2 Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON...................................... 150 7.1 & 7.2h Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON................................ 151 7.1 & 7.2i Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 151 7.1 & 7.2j Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON.................................... 151 7.1 & 7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON............................. 151 ANNUAL CROP AND VEGE PRODUCTION - SHORT RAINY SEASON................................... 153 7.1a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON ................... 154 7.1b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON ............................................. 154 APPENDIX II 102 7.1c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 154 7.1d Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON................................... 155 7.1e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 155 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON....................................... 155 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - SHORT RAINY SEASON..................................... 156 ANNUAL CROP AND VEGE PRODUCTION-LONG RAINY SEASON....................................... 157 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON.............. 158 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON ............................................... 158 7.2c Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON......................................... 158 7.2d Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON..................................... 159 7.2e Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON......................................... 159 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District....................................................................................... 160 7.2g Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON................................................ 160 7.2h Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON....................................... 161 7.2i Planted Area and Number of Crop Growing Households in LONG RAINY SEASON During 2002/03 Crop Year By Method of Land Clearing By Crop......................................... 162 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 162 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 162 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District; 2002/03 Agricultural Year ................. 163 APPENDIX II 103 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 163 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 164 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 164 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year........................ 164 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year........................ 165 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 165 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 165 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 166 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 167 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 168 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 APPENDIX II 104 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 169 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 170 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year .................... 170 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 170 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 171 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 172 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 173 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year.......................... 174 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 174 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 174 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year ...................................... 175 PERMANENT CROPS.......................................................................................................................... 177 7.3 Production of Permanent Crops by Crop type and Region - Singida Region........................... 178 APPENDIX II 105 AGROPROCESSING ............................................................................................................................ 181 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District 2002/03 Agricultural Year........................................................................................................ 182 8.0b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year........................................................................................................ 182 8.1.1a Number of Crop Growing Households Processing Crops During 2002/03 agricultural Year by Location and Crop, Singida Region ........................................................ 183 8.1.1b Number of Crop Growing Households Reporting Farm Products Produced During 2002/03 Agricultural Year by Use of Products and Crop, 2002/03 ............................. 183 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop......................... 184 8.1.1d Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District ................................................................................................... 184 8.1.1e Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District......................................................................... 185 8.0f Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District ................................................................................................... 185 8.0g Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District....................................................................................................................... 185 STORAGE............................................................................................................................................... 187 9.0 Number of Households Storing Crops By Estimated Storage Loss and Crop Type ................ 188 9.0a Number of Households Storing Crops By Main Purpose of Storage and Crop Type .............. 190 9.1 Number of Households and Current Quantity Stored (tons) by Crop Type and District ......... 194 9.2 Number of Households that Stored Crops By Length of Storage and Crop Type.................... 195 9.3 Number of Households Storing Crops By Method of Storage and District ............................. 196 MARKETING......................................................................................................................................... 197 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District...................................................................................................... 198 10.2: Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year .......................................................................... 198 10.3 Proportion of Household who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year .......................................................................... 198 \ APPENDIX II 106 IRRIGATION ......................................................................................................................................... 199 11.1. Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District.......................................................................... 200 11.2 Area of Irrigated and Non Irrigatable (ha) Land By District.................................................... 200 11.3: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District......................................................................... 200 11.4 Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District...................................................................................................................... 200 11.5 Number of Households Using Irrigation By Method of Irrigation Application By District ................................................................................................................................ 200 11.6 Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District............................................................................................................... 201 11.7 Number of Erosion Control Harvesting Structures By Type and District................................ 201 ACCESS TO FARM INPUTS/ IMPLEMENTS.................................................................................. 203 12.1.1 Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.3 Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.4 Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.5 Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year...................................................................................................................... 204 12.1.6 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................... 205 12.1.7 Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year.......................................................................................... 205 12.1.8 Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year.......................................................................................... 206 12.1.9 Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year.......................................................................................... 207 12.1.10 Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year.......................................................................................... 207 12.1.11 Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year.......................................................................................... 207 APPENDIX II 107 12.1.12 Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year.......................................................................................... 208 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................... 208 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ....................................................................... 208 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ....................................................................... 209 12.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 209 12.1.17 Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year..................................................................................... 209 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................... 209 12.1.19 Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year.................................................... 210 12.1.20 Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year..................................................... 210 12.1.21 Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year.................................................... 210 12.1.22 Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 210 12.1.23 Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year .................................................................. 211 12.1.24 Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year.......................................................... 211 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year.................................................... 211 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year..................................................... 211 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year.................................................... 212 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 212 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .................................................................. 212 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year.......................................................... 212 APPENDIX II 108 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year..................................................................................... 213 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year........................................................................................................ 214 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year........................................................................................................ 214 12.1.37 Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year .................................................................... 214 12.1.38 Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year ....................................................................... 214 12.1.39 Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year ....................................................................... 215 12.1.40 Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................. 215 12.1.41 Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year..................................................................................... 215 12.1.42 Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year...................................................................................................................... 215 12.2.1 Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 ................. 216 12.2.2 Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 Agricultural Year..................................................................................... 216 12.2.3 Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District ............................................................................................................ 217 12.2.4 Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District.......................................................................................... 217 12.2.5 Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District...................................................................................................................... 217 12.2.6 Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District ............................................................................................................ 217 12.2.7 Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District.......................................................................................... 218 APPENDIX II 109 12.2.8 Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District ............................................................................................................ 218 12.2.9 Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District ............................................................................................................ 218 12.2.10 Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District.......................................................................................... 218 12.2.11 Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District.......................................................................................... 219 12.2.12 Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District.......................................................................................... 219 12.2.13 Number of Agricultural Households Owning Hand Hoes by Source of Finance and District.................................................................................................................. 219 12.2.14 Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District ................................................................................................. 219 12.2.15 Number of Agricultural Households Owning OXEN by Source of Finance and District.................................................................................................................. 220 12.2.16 Number of Agricultural Households Owning OX Plough by Source of Finance and District.................................................................................................................. 220 12.2.17 Number of Agricultural Households Owning OX SEED PLANTER by Source of Finance and District ................................................................................................. 220 12.2.18 Number of Agricultural Households Owning OX CART by Source of Finance and District.................................................................................................................. 221 12.2.19 Number of Agricultural Households Owning TRACTOR by Source of Finance and District.................................................................................................................. 221 12.2.21 Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District ................................................................................................. 221 AGRICULTURE CREDIT.................................................................................................................... 223 13.1a Number of Credit Received By Main Purpose of credit and District....................................... 224 13b Number of Agriculture household Received Credit By Sex .................................................... 224 13c Number of Agriculture household Received Credit By Source of Credit by District .............. 224 13d Number of Agriculture household Received Credit By Reason for not using Credit by District................................................................................................. 224 TREE FARMING AND AGROFORESTRY....................................................................................... 225 14.1 Number of Household having planted Tree by District........................................................... 226 14.2 Number of Household with planted tree on their land and number of tree by planting location226 14.3 Number of Planted tree by Species and District....................................................................... 266 APPENDIX II 110 14: Main Use of Trees By District.................................................................................................. 227 14 Second Use of Trees By District .............................................................................................. 227 14.3 Number of Households By Whether Village Have a Community Tree Planting Scheme By District .................................................................................................... 227 14.4 Number of Households By Distance to Community Planted Forest (Km) By District............ 228 14.5 Number of Households Involved in Community Tree Planting Scheme By Main Use and District......................................................................................................... 228 CROP EXTENSION .............................................................................................................................. 229 15.1 Number of Households Receiving Extension Messages By District........................................ 230 15.2 Number of Households By Quality of Extension Services By District.................................... 230 15.3 Number of Households By Source of Extension Messages By District................................... 230 15.4 Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District ............................................................................................... 231 15.5 Number of Households By Receiving Advice on Agrochemicals By Source of Messages By District ............................................................................................... 231 15.6 Number of Households By Receivingf Advice on Erosion Control By Source of Messages By District ............................................................................................... 231 15.7 Number of Households By Receiving Advice on Organic Fertiliser Use By Source of Messages By District.......................................................................................... 232 15.8 Number of Households By Receiving Advice on Inorganic Fertiliser Use By Source of Messages By District.......................................................................................... 232 15.9 Number of Households By Receivingf Advice on Use of Improved Seed By Source of Messages By District.......................................................................................... 232 15.10 Number of Households By Receiving Advice on Mechanisation / LST By Source of Messages By District.......................................................................................... 233 15.11 Number of Households By Receiving Advice on Irrigation Technology By Source of Messages By District.......................................................................................... 233 15.12 Number of Households By Receiving Advice on Crop Storage By Source of Messages By District............................................................................................................ 233 15.13 Number of Households By Receiving Advice on Vermin Control By Source of Messages By District ............................................................................................... 234 15.14 Number of Households By Receiving Advice on Agro-processing By Source of Messages By District ............................................................................................... 234 15.15 Number of Households By Receiving Advice on Agro-forestry By Source of Messages By District ............................................................................................... 234 APPENDIX II 111 15.16 Number of Households By Receiving Advice on Beekeeping By Source of Messages By District ............................................................................................... 235 15.17 Number of Households By Receiving Advice on Fish Farming By Source of Messages By District ............................................................................................... 235 5.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 1) During the 2002/03 Agriculture Year, Singida Region ......................................................................................................................... 236 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 2) During the 2002/03 Agriculture Year, Singida Region ......................................................................................................................... 236 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 3) During the 2002/03 Agriculture Year, Singida Region........... 236 LIVELIHOOD CONSTRAINTS .......................................................................................................... 237 16.1 Most Important Constraints By District ................................................................................... 238 16.2 Second Most Important Constraints By District....................................................................... 238 16.3 Third Important Constraints By District................................................................................... 239 16.4 Forth Important Constraints By District................................................................................... 239 16.5 Fifth Important Constraints By District.................................................................................... 240 16.6 Least Important Constraints By District................................................................................... 241 16.7 Second Least Important Constraints By District ...................................................................... 241 16.8 Third Least Important Constraints By District......................................................................... 242 16.9 Forth Least Important Constraints By District ......................................................................... 243 16.10 Fifth Least Important Constraints By District .......................................................................... 243 ANIMAL CONTRIBUTION TO CROP PRODUCTION.................................................................. 245 17.1 Number of Households Using Draft Animal to Cultivate Land By District ............................ 246 17.2 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.......................................................................... 246 17.3 Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year.......................................................................... 246 17.4 Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year ............................................................................................ 247 17.5 Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year....................................................................................................................... 247 APPENDIX II 112 CATTLE PRODUCTION...................................................................................................................... 249 18.1 Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year....................................................................................................................... 250 18.2 Number of Cattle By Type and District as of 1st October, 2003 ............................................. 250 18.3 Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 .................................................................................... 251 18.4 Number of Cattle by Category and Type of Cattle as of 1st October 2003.............................. 252 18.5 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 252 18.6 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 252 18.7 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 253 18.8 Number of Indigenous Cattle By Category and as of 1st October, 2003 ................................ 253 18.9 Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year ............................................................................................. 253 GOATS PRODUCTION........................................................................................................................ 255 19.1 Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year....................................................................................................................... 256 19.2 Total Number of Goats by Type and District as of 2st October, 2003..................................... 256 19.3 Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003....................................................................................... 257 19.4.1 Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District ...................................................................................................................... 258 19.6 Number of Indigenous Goat by Category and District as of 1st October, 2003....................... 258 19.7 Number of Improved Meat Goat by Category and District as of 1st October, 2003................ 258 19.8 Number of Improved Dairy Goat by Category and District as of 1st October, 2003............... 258 19.4 Number of Total Goat by Category and District as of 1st October, 2003................................ 259 19.5 Goat Offtake By Type and District .......................................................................................... 259 19.6 Number of Goat Died and % of Offtake By Tpe and District.................................................. 259 19.7 Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year 260 SHEEP PRODUCTION......................................................................................................................... 261 20.1 Number of Households Rearing Sheep by District as of 1st October, 2002.0/Agriculture Year262 20.2 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03.......................... 262 APPENDIX II 113 20.3.1 Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03................................................................ 263 20.4.1 Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year....................... 264 20.5 Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year.......................................................................................... 264 20.6 Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year.......................................................................................... 264 20.7 Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year....................................................................................................................... 265 20.8 Sheep Intake By Type and District........................................................................................... 265 20.9 Number of Sheep Died and % of Offtake By Type and District.............................................. 266 20.10 Number of Sheep Sold and Value (Tshs) by Category and District during 2002/03 Agriculture Year....................................................................................................................... 266 LIVESTOCK PESTS AND PARASITE CONTROL ......................................................................... 269 22.1 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ............................... 271 22.2 Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock..................... 271 22.3 Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ..................... 22.4 Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year......................................... 271 22.5 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year ............... 271 22.6 Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year ............................. 271 OTHER LIVESTOCK ........................................................................................................................... 273 23.1 Total Number of Other Livestock by Breed and Type............................................................. 274 23.2 Number of Households Rearing and number of Other Livestock by Type and District .......... 274 23.3 Number of Chicken by Type and District ................................................................................ 274 23.4 Number of households with chicken and Category of Chicken by Flock Size ........................ 274 23.4 Number of households with chicken and Category of Chicken by District ............................. 274 LIVESTOCK PRODUCTS.................................................................................................................... 275 25.1 Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year......................................................................... 276 APPENDIX II 114 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES:.............................................................. 277 27.1 Number of households by Distance to Nearest Cattle Dip and District .................................. 278 27.2 Number of households by Distance to Nearest Spray Raced and District............................... 278 27.3 Number of households by Distance to Nearest Hand Powered Sprayer and District.............. 278 27.4 Number of households by Distance to Nearest Cattle Crush and District............................... 278 27.5 Number of households by Distance to Nearest Primary Market and District ......................... 278 27.6 Number of households by Distance to Nearest Secondary Market and District ..................... 279 27.7 Number of households by Distance to Nearest Abattoir and District ..................................... 279 27.8 Number of households by Distance to Nearest Slaughter Slab and District ........................... 279 27.9 Number of households by Distance to Nearest Hide/ Skin Shade and District....................... 279 27.10 Number of households by Distance to Nearest Input Supply and District.............................. 280 27.11 Number of households by Distance to Nearest Veterinary Clinic and District....................... 280 27.12 Number of households by Distance to Nearest Village Holding Gound and District ............. 280 27.13 Number of households by Distance to Nearest Village Watering Point/ Dam and District.... 280 27.14 Number of households by Distance to Nearest Drencher and District.................................... 280 FISH FARMING .................................................................................................................................... 281 28.1 Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year........................................................................................................ 282 LIVESTOCK EXTENSION.................................................................................................................. 283 29.1 Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year .................................................................... 284 29.2 Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year................................. 284 29.3 Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 Agricultural Year ................................................................. 284 29.4 Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year ................................................... 285 29.5 Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year ................................................................. 285 29.6 Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year.................................................... 285 APPENDIX II 115 29.7 Number of Agricultural Households Receiving Extension Advice on Herd / Flock Size and Selection By Source and District, 2002/03 Agricultural Year......................... 286 29.8 Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 Agricultural Year ................... 286 29.9 Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source and District, 2002/03 Agricultural Year ................ 286 29.10 Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year.................................................... 287 29.11 Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, 2002/03 Agricultural Year ....................................... 287 29.12 Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year.......................................................................................... 287 29.13 Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural Year.......................................................................................... 288 29.14 Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year ......................................................... 288 GOVERNMENT REGULATORY PROBLEMS:............................................................................... 289 30.1 Number of Agricultural Households by Whether Face Problems with Government Regulation During 2003/04 by District, 2002/03 Agricultural Year .......................................................... 290 LABOUR USE ........................................................................................................................................ 291 31.1 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year................................................................................................... 292 31.2 Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year................................................................................................... 293 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES........................................................ 295 33.1 Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.2 Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.3 Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year...................................................................................................................... 296 33.4 Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year........................................................................................................ 296 33.5 Number of Agricultural Households by Distance to District Capital and District, 2002/03 Agricultural Year........................................................................................................ 297 33.6 Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year........................................................................................................ 297 APPENDIX II 116 33.7 Number of Agricultural Households by Distance to Feeder Road and District, 2002/03 Agricultural Year........................................................................................................ 297 33.8 Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year........................................................................................................ 297 33.9 Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year........................................................................................................ 298 33.10 Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.11 Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.12 Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year........................................................................................................ 298 33.13 Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year........................................................................................................ 299 33.14 Number of Agricultural Households by Distance to Extension Center................................... 299 33.15 Number of Agricultural Households by Distance to Research Station and District, 2002/03 Agricultural Year........................................................................................................ 299 33.16 Number of Agricultural Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year.......................................................................................... 299 33.17 Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year.......................................................................................... 300 33.18 Number of Agricultural Households by Distance to Livestock Development Center ............ 300 33.19 Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year................................................................................... 300 33.20 Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year................................................................................... 300 33.21 Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year................................................................................... 301 33.22 Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year............................................................................ 301 33.23 Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year........................................................................ 301 33.24 Number of Agricultural Households by Satisfaction of Using Livestock Development ........................................................................................................................... 301 HOUSEHOLD FACILITIES................................................................................................................. 303 34.1 Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year..................................................................... 304 APPENDIX II 117 34.2 Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year........................................................................................................ 304 34.3 Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year...................................................................... 305 34.4: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year...................................................................... 305 34.5: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year.......................................... 305 34.6: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year .......................... 306 34.7: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year...................... 306 34.8: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .......................................... 306 34.9: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year........................... 306 34-10: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year .......... 307 34-11: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year............................................................... 307 34-12: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year .................................................. 308 34-13 Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year ........... 308 34-14: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year............. 308 34-15: Number of Agricultural Households Reporting the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year........................................ 309 34-16: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year........................................................................................................ 309 APPENDIX II 118 APPENDIX II: CROPS Number of Agriculture Households.......................................................................................................... 119 Rank of Importance of Livelihood activities ............................................................................................ 121 Households Demographs.......................................................................................................................... 127 Land access/ownership ............................................................................................................................. 133 Land Use .................................................................................................................................................. 137 Communial Resources.............................................................................................................................. 141 Total annual crop & vegetable production - long and short rainy season................................................. 147 Annual crop and vegetable production - short rainy season..................................................................... 153 Annual crop and vegetable production-long rainy season........................................................................ 157 Permanent Crops....................................................................................................................................... 177 Agroprocessing......................................................................................................................................... 181 Storage...................................................................................................................................................... 187 Marketing.................................................................................................................................................. 197 Irrigation ................................................................................................................................................... 199 Access to Farm Inputs/ Implements.......................................................................................................... 203 Agriculture Credit..................................................................................................................................... 223 Tree Farming and Agroforestry ................................................................................................................ 225 Crop Extension ......................................................................................................................................... 229 Livelihood Constraints.............................................................................................................................. 237 Animal Contribution to crop production .................................................................................................. 245 Cattle Production ...................................................................................................................................... 249 Goats Production ...................................................................................................................................... 255 Sheep Production...................................................................................................................................... 261 Pig Production .......................................................................................................................................... 267 Livestock Pests and Parasite Control........................................................................................................ 269 Other livestock.......................................................................................................................................... 273 Livestock Products.................................................................................................................................... 275 Access to functional livestock facilities: .................................................................................................. 277 Fish Farming............................................................................................................................................. 281 Livestock Extension.................................................................................................................................. 283 Government Regulatory Problems: .......................................................................................................... 289 Labour Use................................................................................................................................................ 291 Access to Infrastructure and Other services.............................................................................................. 295 Household Facilities ................................................................................................................................. 303 Appendix II 119 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 120 District Rural hosehold involved in Agriculture % of Total rural households Rural households NOT involed in Agriculture % of Total rural households Total rural households % of Total rural households Urban households Total number of Household (from 2002 pop. Census) Number % Number % Number % Number Number Iramba 62,255 96 2,408 4 64,663 90 7,014 71,677 Singida Rural 72,954 98 1,374 2 74,329 95 4,165 78,494 Manyoni 33,065 95 1,812 5 34,877 81 8,012 42,889 Singida Urban 11,125 97 375 3 11,500 47 13,012 24,512 Total 179,400 97 5,969 3 185,368 85 32,204 217,572 Number % Number % Number % Iramba 30,411 48.6 273 0.4 31,845 50.9 62,528 62,255 32,118 Singida Rural 33,761 46.1 242 0.3 39,193 53.5 73,197 72,954 39,436 Manyoni 27,088 81.9 0 0.0 5,977 18.1 33,065 33,065 5,977 Singida Urban 5,577 50.1 0 0.0 5,549 49.9 11,125 11,125 5,549 Total 96,837 53.8 516 0.3 82,563 45.9 179,915 179,400 83,079 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agriculture households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Crops Only Livestock Only Crops & Livestock Total Number of agriculture Household Total Number of Households Growing Crops Total Number of Households Rearing Livestock Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 121 RANK OF IMPORTANCE OFLIVELIHOOD ACTIVITIES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 122 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Iramba 172,336 50 6 173,435 50 5 345,770 100 6 Singida Rural 178,701 50 5 179,931 50 4 358,632 100 5 Manyoni 84,660 49 6 88,830 51 4 173,491 100 5 Singida Urban 28,177 48 6 30,722 52 4 58,899 100 5 Total 463,874 50 5 472,918 50 4 936,792 100 5 Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 1 6 4 3 5 7 2 Singida Rural 1 5 4 2 6 7 3 Manyoni 1 6 4 2 5 7 3 Singida Urban 1 6 4 2 5 7 3 Total 1 6 4 3 5 7 2 Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Livelihood Activity 3.0: Number of Agriculture Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agriculture Year District Male Female Total Average Household Size Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 123 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 54,364 380,545 0 0 1,233 8,630 4,319 30,230 2,114 14,801 211 1,476 288 Singida Rural 45,408 317,857 124 866 6,616 46,313 18,818 131,727 991 6,940 0 0 744 Manyoni 8,817 61,720 255 1,786 2,950 20,648 14,970 104,791 1,403 9,823 0 0 4,074 Singida Urban 4,693 32,853 0 0 1,022 7,154 3,699 25,891 526 3,685 85 596 1,015 Total 113,282 792,975 379 2,652 11,821 82,745 41,806 292,639 5,036 35,250 296 2,072 6,121 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 7,064 42,383 419 2,514 23,487 140,925 16,355 98,131 3,783 22,699 316 1,898 10,155 Singida Rural 25,834 155,006 1,194 7,161 21,166 126,993 18,327 109,961 1,681 10,085 495 2,970 5,077 Manyoni 17,023 102,136 493 2,957 2,124 12,742 6,650 39,902 1,652 9,913 76 455 4,066 Singida Urban 4,783 28,697 84 505 2,912 17,470 2,112 12,669 402 2,412 0 0 909 Total 54,704 328,222 2,190 13,137 49,688 298,130 43,444 260,663 7,518 45,109 887 5,322 20,207 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 820 4,099 563 2,817 4,869 24,345 14,899 74,496 3,632 18,160 422 2,109 33,578 Singida Rural 1,464 7,318 1,542 7,710 10,417 52,083 15,984 79,921 2,431 12,153 246 1,228 38,204 Manyoni 5,566 27,829 501 2,504 2,778 13,892 4,399 21,994 652 3,259 162 811 16,303 Singida Urban 1,419 7,094 244 1,218 1,530 7,652 1,299 6,495 377 1,884 42 211 5,367 Total 9,268 46,341 2,850 14,248 19,594 97,971 36,581 182,906 7,091 35,457 872 4,358 93,452 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 1,703 6,811 3,664 14,658 8,656 34,625 5,089 20,356 245 980 14,933 Singida Rural 248 993 3,388 13,550 4,196 16,786 7,056 28,223 2,275 9,101 125 500 25,163 Manyoni 1,155 4,619 563 2,253 4,862 19,448 2,447 9,789 1,907 7,628 85 340 5,965 Singida Urban 230 922 1,132 4,527 296 1,182 1,286 5,144 212 848 43 170 2,481 Total 1,633 6,533 6,785 27,141 13,019 52,074 19,445 77,780 9,483 37,933 498 1,991 48,542 Table 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance Table 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance Table 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Table 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 124 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 144 433 852 2,555 1,279 3,836 988 2,965 1,704 5,112 0 0 2,053 Singida Rural 0 0 5,346 16,039 1,226 3,678 1,171 3,514 249 746 121 362 2,202 Manyoni 338 1,014 494 1,481 913 2,738 582 1,745 654 1,961 85 254 914 Singida Urban 0 0 659 1,978 43 128 168 504 170 510 0 0 169 Total 482 1,447 7,351 22,053 3,460 10,379 2,909 8,727 2,776 8,329 205 616 5,339 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 428 856 143 285 140 281 285 570 0 0 0 Singida Rural 0 0 614 1227 0 0 0 0 0 0 0 0 103 Manyoni 0 0 0 0 84 169 160 321 158 317 0 0 0 Singida Urban 0 0 0 0 0 0 43 85 0 0 42 84 0 Total 0 0 1,041 2083 227 454 343 687 444 887 42 84 103 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 0 0 0 0 0 144 144 0 0 0 0 141 Singida Rural 0 0 372 372 124 124 125 125 0 0 0 0 0 Manyoni 0 0 0 0 0 0 0 0 0 0 0 0 0 Singida Urban 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 372 372 124 124 269 269 0 0 0 0 141 Table 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Table 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance Table 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 125 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 0 427,460 0 15,552 0 192,678 144 240,871 0 81,699 0 6,463 141 Singida Rural 0 481,174 372 46,925 124 245,977 125 353,472 0 39,025 0 5,059 0 Manyoni 0 197,318 0 10,981 0 69,637 0 178,541 0 32,901 0 1,860 0 Singida Urban 0 69,566 0 8,228 0 33,586 0 50,788 0 9,339 0 1,061 0 Total 0 1,175,519 372 81,685 124 541,878 269 823,671 0 162,964 0 14,444 141 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Iramba 427,460 15,552 192,678 240,871 81,699 6,463 296,866 Singida Rural 481,174 46,925 245,977 353,472 39,025 5,059 334,149 Manyoni 197,318 10,981 69,637 178,541 32,901 1,860 161,033 Singida Urban 69,566 8,228 33,586 50,788 9,339 1,061 49,829 Total 1,175,519 81,685 541,878 823,671 162,964 14,444 841,878 Iramba 1 6 4 3 5 7 2 Singida Rural 1 5 4 2 6 7 3 Manyoni 1 6 4 2 5 7 3 Singida Urban 1 6 4 2 5 7 3 Total 1 6 4 3 5 7 2 Table 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance Tanzania Agriculture Census Survey 2003 Singida Region 126 Appendix II 127 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 128 Number % Number % Number % Less than 4 61,961 50 62,486 50 124,446 100 05 - 09 75,426 50 76,808 50 152,234 100 10 - 14 74,260 52 67,770 48 142,030 100 15 - 19 52,220 52 48,907 48 101,127 100 20 - 24 33,478 47 37,248 53 70,726 100 25 - 29 28,086 47 31,119 53 59,205 100 30 - 34 24,456 44 31,590 56 56,046 100 35 - 39 22,415 47 25,255 53 47,670 100 40 - 44 20,633 51 19,597 49 40,230 100 45 - 49 15,963 47 17,899 53 33,862 100 50 - 54 13,061 47 14,689 53 27,750 100 55 - 59 10,044 52 9,171 48 19,215 100 60 - 64 10,146 53 8,999 47 19,145 100 65 - 69 6,745 47 7,714 53 14,459 100 70 - 74 6,297 52 5,740 48 12,036 100 75 - 79 4,014 51 3,839 49 7,853 100 80 - 84 2,704 58 1,990 42 4,694 100 Above 85 1,966 48 2,097 52 4,063 100 Total 463,874 50 472,918 50 936,792 100 Number % Number % Number % Less than 4 61,961 13 62,486 13 124,446 13 05 - 09 75,426 16 76,808 16 152,234 16 10 - 14 74,260 16 67,770 14 142,030 15 15 - 19 52,220 11 48,907 10 101,127 11 20 - 24 33,478 7 37,248 8 70,726 8 25 - 29 28,086 6 31,119 7 59,205 6 30 - 34 24,456 5 31,590 7 56,046 6 35 - 39 22,415 5 25,255 5 47,670 5 40 - 44 20,633 4 19,597 4 40,230 4 45 - 49 15,963 3 17,899 4 33,862 4 50 - 54 13,061 3 14,689 3 27,750 3 55 - 59 10,044 2 9,171 2 19,215 2 60 - 64 10,146 2 8,999 2 19,145 2 65 - 69 6,745 1 7,714 2 14,459 2 70 - 74 6,297 1 5,740 1 12,036 1 75 - 79 4,014 1 3,839 1 7,853 1 80 - 84 2,704 1 1,990 0 4,694 1 Above 85 1,966 0 2,097 0 4,063 0 Total 463,874 100 472,918 100 936,792 100 Number % Number % Number % Iramba 172,336 50 173,435 50 345,770 100 Singida Rural 178,701 50 179,931 50 358,632 100 Manyoni 84,660 49 88,830 51 173,491 100 Singida Urban 28,177 48 30,722 52 58,899 100 Total 463,874 50 472,918 50 936,792 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group, 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 129 Number % Number % Number % Number % Number % Iramba 189,432 65 15,025 5 0 0 88,988 30 293,445 100 Singida Rural 149,312 46 74,368 23 0 0 100,316 31 323,996 100 Manyoni 64,567 44 22,686 15 81 0 59,195 40 146,528 100 Singida Urban 30,065 62 5,842 12 0 0 12,470 26 48,377 100 Total 433,376 53 117,921 15 81 0 260,968 32 812,346 100 Number % Number % Number % Number % Iramba 96,219 33 110,939 38 86,287 29 293,445 100 Singida Rural 125,431 39 127,743 39 70,822 22 323,996 100 Manyoni 42,422 29 54,350 37 49,757 34 146,528 100 Singida Urban 19,666 41 19,488 40 9,222 19 48,377 100 Total 283,737 35 312,521 38 216,088 27 812,346 100 Number % Number % Number % Number % Iramba 129,780 44 26,453 9 289 0 1,054 0 Singida Rural 129,711 40 38,245 12 733 0 125 0 Manyoni 74,178 51 9,657 7 0 0 0 0 Singida Urban 19,257 40 5,402 11 0 0 84 0 Total 352,926 43 79,757 10 1,022 0 1,264 0 Number % Number % Number % Number % Iramba 2,626 1 2,525 1 144 0 2,689 1 Singida Rural 2,190 1 3,863 1 1,728 1 9,671 3 Manyoni 745 1 522 0 81 0 1,635 1 Singida Urban 169 0 414 1 184 0 428 1 Total 5,729 1 7,324 1 2,136 0 14,423 2 Number % Number % Number % Number % Iramba 1,141 0 562 0 144 0 417 0 Singida Rural 720 0 473 0 0 0 1,113 0 Manyoni 1,769 1 418 0 0 0 743 1 Singida Urban 305 1 43 0 0 0 43 0 Total 3,934 0 1,495 0 144 0 2,315 0 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total Main Activity District Crop/Seaweed Farming p g Herding Livestock Pastoralist 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Fishing District Main Activity Self Employed (Non Farmimg) without Employees cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Main Activity District Government / Parastatal Private - NGO / Mission / etc Self Employed (Non Farmimg) with Employees p y p (Non Agriculture) Not Working & Available Not Working & Unavailable cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year Housewife Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 130 Number % Number % Number % Number % Iramba 93,234 32 30,565 10 1,823 1 293,445 100 Singida Rural 121,979 38 12,710 4 735 0 323,996 100 Manyoni 41,288 28 14,601 10 892 1 146,528 100 Singida Urban 19,296 40 2,583 5 170 0 48,377 100 Total 275,798 34 60,458 7 3,619 0 812,346 100 Number % Number % Number % Number % Number % Iramba 97,961 33 11,322 4 64,715 22 119,447 41 293,445 100 Singida Rural 68,086 21 17,090 5 153,175 47 85,645 26 323,996 100 Manyoni 10,227 7 22,874 16 86,272 59 27,155 19 146,528 100 Singida Urban 9,116 19 2,371 5 23,013 48 13,877 29 48,377 100 Total 185,389 23 53,656 7 327,175 40 246,125 30 812,346 100 Number % Number % Number % Number % Iramba 431 0 392 0 1,670 2 1,128 1 Singida Rural 124 0 741 1 2,184 2 1,949 2 Manyoni 82 0 82 0 1,837 3 1,875 3 Singida Urban 42 0 42 0 211 1 210 1 Total 679 0 1,257 0 5,903 2 5,163 2 Number % Number % Number % Number % Iramba 9,843 9 2,619 2 1,898 2 87,460 79 Singida Rural 10,314 8 1,476 1 989 1 102,185 80 Manyoni 6,639 12 1,709 3 1,879 3 36,996 68 Singida Urban 1,803 9 212 1 422 2 15,536 80 Total 28,599 9 6,016 2 5,188 2 242,176 77 Number % Number % Number % Number % Iramba 1,131 1 143 0 139 0 143 0 Singida Rural 2,023 2 353 0 0 0 123 0 Manyoni 714 1 0 0 0 0 84 0 Singida Urban 170 1 248 1 0 0 0 0 Total 4,038 1 744 0 139 0 350 0 Number % Number % Number % Number % Iramba 959 1 0 0 1,838 2 0 0 Singida Rural 586 0 0 0 2,525 2 0 0 Manyoni 164 0 170 0 883 2 0 0 Singida Urban 83 0 0 0 381 2 43 0 Total 1,792 1 170 0 5,628 2 43 0 Main Activity cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Retired / Sick / Disabled Other Total Student District 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Total Standard Two Education Level Form Two Form Three Form Four Pre Form One Form One Education Level Form Five District Education Level cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Standard Eight g y Education District Under Standard One Standard One 3.9 HOUSEHOLDS DEMOCRAPHS: Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Education Level District Standard Five Standard Six Standard Seven Standard Three Standard Four Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 131 Number % Number % Number % Number % Number % Iramba 0 0 137 0 0 0 1,009 1 110,939 100 Singida Rural 125 0 240 0 118 0 1,687 1 127,743 100 Manyoni 78 0 65 0 0 0 1,092 2 54,350 100 Singida Urban 0 0 0 0 0 0 85 0 19,488 100 Total 203 0 442 0 118 0 3,873 1 312,521 100 Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Household Size Number of Househod Members Number of Households Average Househol d Size Iramba 286,517 49,682 6 59,253 12,847 5 345,770 62,528 6 Singida Rural 288,561 56,246 5 70,071 16,951 4 358,632 73,197 5 Manyoni 143,554 25,418 6 29,937 7,647 4 173,491 33,065 5 Singida Urban 46,101 8,208 6 12,798 2,917 4 58,899 11,125 5 Total 764,733 139,553 5 172,059 40,362 4 936,792 179,915 5 Number Percent Number Percent Number Percent Number Percent Iramba 37,170 73 9,758 19 4,262 8 51,190 100 Singida Rural 43,622 66 17,787 27 4,395 7 65,804 100 Manyoni 6,210 19 18,821 57 7,870 24 32,901 100 Singida Urban 5,589 61 2,642 29 910 10 9,141 100 Total 92,591 58 49,008 31 17,437 11 159,036 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Attending School 0 871 33 0 0 0 0 903 Completed 185 111,065 326 3,876 185 118 2,257 118,012 Never Attended to School 61,000 0 0 0 0 0 0 61,000 Total 61,185 111,935 359 3,876 185 118 2,257 179,915 Mean Median Mode Mean Median Mode Mean Median Mode Iramba 46 43 30 52 52 65 48 45 40 Singida Rural 45 42 40 52 50 45 47 45 40 Manyoni 44 41 35 47 46 65 45 42 40 Singida Urban 46 42 31 47 46 50 46 44 30 Total 45 42 40 51 50 65 47 44 40 y y Education cont…. Number of Agriculture Housdehold Members By Level of Formal Education Completion and District, 2002/03 Agiculture Year Adult Education Total District Education Level Form Six g y Education 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head Female Total District Male 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year Education Status Maximum Education Level Attained 3.12 Number of Heads of Agricultural Households reporting Maximum level of education attained by Education Status, 2002/03 Agricultural Year District Off farm income One Off Farm Income Two Off Farm Income More than Two Off Farm Income Total 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 132 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 129,691 137,363 140,272 157,641 144,490 139,553 Female Headed (Number in Thousands) 39,069 34,361 34,302 42,722 50,926 40,362 Total 168,760 171,724 174,574 200,363 195,416 179,915 Male Headed (Percentage) 77 80 80 79 74 78 Female Headed (Percentage) 23 20 20 21 26 22 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Iramba 108,988 95,469 204,457 37,683 51,305 88,988 146,671 146,773 293,445 Singida Rural 117,335 106,345 223,680 43,807 56,509 100,316 161,142 162,854 323,996 Manyoni 45,720 41,614 87,334 25,400 33,795 59,195 71,120 75,409 146,528 Singida Urban 17,918 17,988 35,907 5,062 7,408 12,470 22,980 25,396 48,377 Total 289,961 261,417 551,378 111,952 149,016 260,968 401,913 410,433 812,346 District Literacy Know Don't know Total 3.15 Literacy Rate of Heads of Households by Sex and District 3.14 Time Series of male and Female Headed Households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 133 LAND ACCESS/OWNERSHIP Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 134 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Iramba 3,958 6 47,355 76 7,919 13 13,416 22 5,030 8 1,111 2 5,642 9 62,255 Singida Rural 5,544 8 63,662 87 4,873 7 3,162 4 3,385 5 1,209 2 3,062 4 72,954 Manyoni 649 2 29,948 91 2,627 8 633 2 1,846 6 222 1 829 3 33,065 Singida Urban 437 4 10,647 96 42 0 337 3 127 1 169 2 413 4 11,125 Total 10,588 6 151,612 85 15,461 9 17,549 10 10,388 6 2,711 2 9,946 6 179,400 Land Access Leased/Certificate of Ownership Households with Area under Other Forms of Tenure Total number of Households 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year District Area Owned Under Customary Law Bought Rented Borrowed Households with Area Shared Croped Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 135 Area Leased/Certif icate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Iramba 8,650 122,462 12,096 16,975 4,020 968 10,292 175,464 Singida Rural 9,065 123,211 8,085 5,215 4,509 2,653 2,801 155,538 Manyoni 931 91,144 19,564 819 2,102 102 1,635 116,296 Singida Urban 440 14,744 34 290 98 87 158 15,852 Total 19,086 351,560 39,779 23,298 10,730 3,811 14,887 463,150 District Land Access/ Ownership (Hectare) 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Singida 136 Appendix II 137 LAND USE Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 138 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Househ olds with Pasture Househ olds with Fallow Househ olds with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Household Iramba 56,073 12,116 990 144 1,405 1,831 7,339 432 1,497 1,230 1,570 13,796 98,424 Singida Rural 67,143 10,914 2,274 1,667 2,444 5,822 9,806 2,473 1,928 1,288 2,917 6,194 114,869 Manyoni 29,356 9,064 907 239 0 410 9,830 2,396 247 542 962 8,893 62,847 Singida Urban 10,271 1,596 211 572 117 635 1,226 210 423 169 506 1,620 17,557 Total 162,843 33,691 4,382 2,623 3,966 8,698 28,201 5,511 4,094 3,229 5,955 30,503 293,696 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Iramba 113,918 18,419 286 29 2,982 4,265 14,533 466 452 2,052 2,257 15,804 175,464 Singida Rural 99,977 15,723 1,220 3,093 5,777 8,280 8,734 3,763 494 1,151 2,502 4,824 155,538 Manyoni 50,153 13,247 490 153 . 5,168 13,834 9,758 100 2,021 6,022 15,350 116,296 Singida Urban 9,922 1,603 30 212 24 1,045 798 314 163 120 465 1,156 15,852 Total 273,971 48,992 2,026 3,488 8,782 18,758 37,900 14,301 1,209 5,344 11,246 37,134 463,150 % 59 11 0 1 2 4 8 3 0 1 2 8 100 Total Number Percent Number Percent Number Iramba 42,449 68 19,807 32 62,255 Singida Rural 50,629 69 22,326 31 72,954 Manyoni 15,093 46 17,972 54 33,065 Singida Urban 7,386 66 3,740 34 11,125 Total 115,556 64 63,844 36 179,400 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District, 2002/03 Agricultural Year District Land Use 5.2 LAND USE: Area of Land by type of Land Use and District during 2002/03 Agricultural Year District Size of Holding (Ha) Land Use 5.3 Number of Households by type of Hosehold and District During 2002/03 Agriculture Year District Yes No Was all Land Available to the Hh Used During 2002/03? Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 139 Total Number Percent Number Percent Number Iramba 35,016 56 27,240 44 62,255 Singida Rural 32,987 45 39,967 55 72,954 Manyoni 22,964 69 10,100 31 33,065 Singida Urban 3,652 33 7,473 67 11,125 Total 94,620 53 84,780 47 179,400 Total Number Percent Number Percent Number Iramba 11,015 18 51,240 82 62,255 Singida Rural 17,194 24 55,760 76 72,954 Manyoni 6,982 21 26,083 79 33,065 Singida Urban 2,663 24 8,463 76 11,125 Total 37,854 21 141,546 79 179,400 5.4 Number of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District, 2002/03 Agricultural Year 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Yes No Do you Consider that you have sufficient land for the Hh? District Yes No Do any Female Members of the Hh own or have customary right Tanzania Agriculture Census Survey 2003 Singida Region 140 Appendix II 141 COMMUNIAL RESOURCES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 142 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Iramba 0.8 1.5 1.3 2.2 2.2 3.0 2.3 3.1 Singida Rural 0.9 1.7 1.2 2.2 1.7 2.7 2.0 2.1 Manyoni 0.9 2.3 1.5 3.3 2.4 3.5 1.8 2.1 Singida Urban 0.8 1.0 1.2 1.5 1.8 2.7 2.5 2.5 Total 0.9 1.7 1.3 2.3 2.0 2.9 2.1 2.5 Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Distance to resource (km), Wet Season Distance to resource (km), Dry Season Iramba 3.2 3.3 3.5 3.8 4.6 4.6 7.5 7.5 7.7 8.7 Singida Rural 2.6 2.6 3.4 3.6 4.7 4.6 7.8 7.8 7.3 8.1 Manyoni 3.3 3.3 3.4 3.6 7.2 7.3 8.1 8.1 7.7 8.7 Singida Urban 3.1 2.9 3.2 3.1 4.9 4.9 8.0 8.0 7.6 8.4 Total 3.0 3.0 3.5 3.6 5.1 5.1 7.8 7.8 7.5 8.5 District Communal Resource cont….COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Wood for Charcoal Building Poles Forest for Bees (Honey) Hunting (Animal Fishing (Fish) 6.1 COMMUNAL RESOURCES: Average Distance (Km) from Agriculture Household to Communal Resources by Name of Communal Resource, Season and District, 2002/03 Agricultural Year Communal Resource District Water for Humans Water for Livestock Communal Grazing Communal Firewood Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 143 Home of Farm Consumptio n / Utilization Not Used by Household Total Iramba 62,528 0 62,528 Singida Rural 73,079 118 73,197 Manyoni 32,656 409 33,065 Singida Urban 11,125 0 11,125 Total 179,389 526 179,915 Home of Farm Consumptio n / Utilization Sold to Neighbours Not Used by Household Not Available Total Iramba 41,163 144 16,427 4,794 62,528 Singida Rural 49,403 243 21,109 2,441 73,197 Manyoni 7,418 85 25,400 162 33,065 Singida Urban 5,983 0 4,974 168 11,125 Total 103,967 473 67,911 7,565 179,915 Home of Farm Consumptio n / Utilization Sold to Neighbours Sold to Local Wholesale Market Not Used by Household Not Available Total Iramba 34,565 0 0 19,782 8,181 62,528 Singida Rural 39,989 118 122 20,757 12,211 73,197 Manyoni 6,074 0 0 22,421 4,570 33,065 Singida Urban 4,389 43 0 3,976 2,718 11,125 Total 85,018 161 122 66,936 27,679 179,915 District Water for Livestock 6.4: COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Grazing by type of Utilization and District, 2002/03 Agricultural Year District Communal Grazing 6.2 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Humans by type of Utilization and District, 2002/03 Agricultural Year District Water for Humans 6.3 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Water for Livestock by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 144 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 60,828 420 0 0 0 994 288 62,528 Singida Rural 65,766 3,034 248 1,584 0 1,964 601 73,197 Manyoni 31,317 370 74 0 0 1,303 0 33,065 Singida Urban 10,366 339 0 85 42 293 0 11,125 Total 168,276 4,163 322 1,669 42 4,554 889 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 11,228 2,813 280 0 276 289 20,136 27,506 62,528 Singida Rural 13,520 2,725 247 245 728 370 31,820 23,541 73,197 Manyoni 5,218 456 0 149 0 85 26,994 163 33,065 Singida Urban 1,259 635 42 0 0 419 6,754 2,016 11,125 Total 31,226 6,629 569 395 1,004 1,162 85,704 53,226 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 40,786 2,928 0 0 105 144 15,627 2,937 62,528 Singida Rural 47,169 2,048 0 369 1,698 0 13,146 8,766 73,197 Manyoni 26,962 238 139 0 0 0 5,323 402 33,065 Singida Urban 3,380 720 0 42 84 42 5,605 1,252 11,125 Total 118,297 5,935 139 411 1,888 187 39,701 13,357 179,915 6.5 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Communal Firewood by type of Utilization and District, 2002/03 Agricultural Year District Communal Firewood 6.6 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Wood for Charcoal by type of Utilization and District, 2002/03 Agricultural Year District Wood for Charcoal 6.7 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Building Poles by type of Utilization and District, 2002/03 Agricultural Year District Building Poles Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 145 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Traders on the Farm Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 2,450 1,587 144 0 0 0 5,562 52,785 62,528 Singida Rural 3,501 478 0 0 0 118 17,337 51,763 73,197 Manyoni 3,993 610 1,262 82 316 0 13,743 13,059 33,065 Singida Urban 33 209 83 0 0 0 159 10,642 11,125 Total 9,977 2,884 1,489 82 316 118 36,800 128,249 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Local Wholesale Market Not Used by Household Not Available Total Iramba 722 433 133 4,996 56,245 62,528 Singida Rural 120 0 0 2,302 70,774 73,197 Manyoni 82 0 0 2,408 30,575 33,065 Singida Urban 0 0 0 0 11,125 11,125 Total 924 433 133 9,706 168,719 179,915 Home of Farm Consumpti on / Utilization Sold to Neighbours Sold to Village Market Sold to Local Wholesale Market Sold to Major Wholesale Market Not Used by Household Not Available Total Iramba 0 0 0 1,054 0 1,711 59,763 62,528 Singida Rural 483 123 3,594 374 125 4,899 63,600 73,197 Manyoni 84 0 0 0 0 1,169 31,812 33,065 Singida Urban 42 85 0 42 0 1,380 9,575 11,125 Total 609 208 3,594 1,470 125 9,159 164,750 179,915 6.8 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Forest For Bees Products by type of Utilization and District, 2002/03 Agricultural Year District Forest for Bees Products District Fishing Resources 6.9 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Hunting Grounds by type of Utilization and District, 2002/03 Agricultural Year District Hunting Grounds 6.10 COMMUNAL RESOURCES: Number of Agricultural Households with Access to Fishing Resources by type of Utilization and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 146 Appendix II 147 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION - LONG AND SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 148 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cereal 1,816 352 194 243,745 89,117 366 245,560 89,468 364 Maize 1,795 340 190 135,482 54,056 399 137,277 54,396 396 Paddy 0 0 0 3,665 1,973 538 3,665 1,973 538 Sorghum 21 11 533 69,884 21,692 310 69,905 21,703 310 Bulrush Millet 0 0 0 30,783 10,025 326 30,783 10,025 326 Finger Millet 0 0 0 3,901 1,357 348 3,901 1,357 348 Wheat 0 0 0 29 14 494 29 14 494 Barley 0 0 0 0 0 0 0 0 0 Roots and Tubers 0 0 0 5,724 5,597 978 5,724 5,597 978 Cassava 0 0 0 2,995 2,424 809 2,995 2,424 809 Sweet Potatoes 0 0 0 2,564 2,807 1095 2,564 2,807 1095 Irish Potatoes 0 0 0 161 364 2253 161 364 2253 Yams 0 0 0 3 2 741 3 2 741 Cocoyam 0 0 0 0 0 0 0 0 0 Pulses 0 0 0 13,342 3,820 286 13,342 3,820 286 Mung Beans 0 0 0 2 9 4117 2 9 4117 Beans 0 0 0 8,328 1,645 198 8,328 1,645 198 Cowpeas 0 0 0 943 299 317 943 299 317 Green Gram 0 0 0 174 75 429 174 75 429 Pigeon Peas 0 0 0 0 0 0 0 0 0 Chich Peas 0 0 0 3,201 1,624 0 3,201 1,624 507 Bambaranuts 0 0 0 695 169 243 695 169 243 Field Peas 0 0 0 0 0 0 0 0 0 Oil Seeds and Oil nuts 279 335 1200 52,843 24,367 461 53,122 24,702 465 Sunflower 279 335 1200 40,590 21,002 517 40,869 21,337 522 Simsim 0 0 0 2,053 887 432 2,053 887 432 Groundnuts 0 0 0 10,146 2,462 243 10,146 2,462 243 Soya Beans 0 0 0 55 17 304 55 17 304 Castor Seed 0 0 0 0 0 0 0 0 0 Fruit and Vegetables 197 390 1982 1,249 1,406 1126 1,445 1,796 1243 Okra 0 0 0 20 8 398 20 8 398 Radish 0 0 0 0 0 0 0 0 0 Turmeric 0 0 0 0 0 0 0 0 0 Bitter Aubergine 0 0 0 16 14 884 16 14 884 Garlic 0 0 0 0 0 0 0 0 0 Onions 0 0 0 775 830 1072 775 830 1072 Ginger 0 0 0 0 0 0 0 0 0 Cabbage 0 0 0 50 169 3355 50 169 3355 Tomatoes 109 266 2437 215 268 1247 324 534 1648 Spinnach 15 12 823 19 19 962 34 31 902 Carrot 0 0 0 0 0 0 0 0 0 Chillies 0 0 0 4 5 1067 4 5 1067 Amaranths 0 0 0 36 60 1692 36 60 1692 Pumpkins 10 10 988 0 0 0 10 10 988 Cucumber 39 6 154 17 0 20 56 6 113 Egg Plant 24 96 3952 17 19 1112 42 115 2772 Water Mellon 0 0 0 0 0 0 0 0 0 Cauliflower 0 0 0 80 15 185 80 15 185 Cash Crops 0 0 0 2,226 1,370 615 2,226 1,370 615 Seaweed 0 0 0 0 0 0 0 0 0 Cotton 0 0 0 687 275 400 687 275 400 Tobacco 0 0 0 1,387 1,083 780 1,387 1,083 780 Pyrethrum 0 0 0 152 13 0 152 13 0 Jute 0 0 0 0 0 0 0 0 0 Total 2,292 319,128 321,419 * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual area due to being produced on the same land during the 2 seasons. Previous surveys have used the lpno season to estimate physical land area under production to different crops Table 7.1 and 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 149 Number of Households Area Planted (ha) Number of Households Area Planted (ha) Cereals 899 1,816 7,121 3,901 5,717 32 Maize 733 1,795 132,667 135,482 137,277 1 Paddy 0 0 7,173 3,665 3,665 0 Sorghum 166 21 82,809 69,884 69,905 0 Bulrush Millet 0 0 43,386 30,783 30,783 0 Finger Millet 0 0 7,121 3,901 3,901 0 Wheat 0 0 0 0 0 0 Barley 0 0 0 0 0 0 Root and Tubers 0 0 15,155 5,724 5,724 0 Cassava 0 0 6,610 2,995 2,995 0 Sweet Potatoes 0 0 8,432 2,564 2,564 0 Irish Potatoes 0 0 80 161 161 0 Yams 0 0 33 3 3 0 Cocoyam 0 0 0 0 0 0 Pulses 0 0 28,746 13,342 13,342 0 Mung Beans 0 0 43 2 2 0 Beans 0 0 19,913 8,328 8,328 0 Cowpeas 0 0 2,579 943 943 0 Green Gram 0 0 242 174 174 0 Chich Peas 0 0 2,297 3,201 3,201 0 Bambaranuts 0 0 3,673 695 695 0 Field Peas 0 0 0 0 0 0 Oil Seeds and Oil nuts 138 279 74,450 52,843 53,122 1 Sunflower 138 279 45,857 40,590 40,869 1 Simsim 0 2,765 2,053 2,053 0 Groundnuts 0 0 25,662 10,146 10,146 0 Soya Beans 0 0 167 55 55 0 Castor Seed 0 0 0 0 0 0 Fruit and Vegetables 1,080 197 5,168 1,249 1,445 14 Okra 0 0 126 20 20 0 Bitter Aubergine 0 0 84 16 16 0 Onions 0 0 1,928 775 775 0 Cabbage 0 0 321 50 50 0 Tomatoes 600 109 1,802 215 324 34 Spinnach 120 15 265 19 34 43 Carrot 0 0 0 0 0 0 Chillies 0 0 42 4 4 0 Amaranths 0 0 350 36 36 0 Pumpkins 120 10 0 0 10 100 Cucumber 120 39 85 17 56 69 Egg Plant 0 0 43 17 17 0 Water Mellon 0 0 0 0 0 0 Cauliflower 0 0 123 80 80 0 Cash Crops 0 0 1,867 2,226 2,226 0 Cotton 0 0 399 687 687 0 Tobacco 0 0 1,343 1,387 1,387 0 Pyrethrum 0 0 125 152 152 0 Total 430,589 79,284 81,576 Table 7.1 and 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Singida Region Crop Short Rainy Season Long Rainy Season Total Area Planted Short and Long Rainy Season % Area Planted in Short Rainy Season Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 150 Number of Households Planted Area Number of Households Planted Area Number of Household s Planted Area Number of Households Planted Area Iramba 138 2,009 51,714 118,470 10,970 12,193 62,822 132,672 Singida Rural 483 234 31,959 68,074 41,237 45,569 73,679 113,877 Manyoni 0 0 3,838 18,799 29,226 43,685 33,065 62,485 Singida Urban 85 43 1,369 2,215 9,671 8,686 11,125 10,943 Total 706 2,287 88,881 207,558 91,104 110,132 180,691 319,977 % 0.2 0.7 27.8 64.9 28.5 34.4 56.5 100.0 Total Number of Households Planted Area Number of Households Planted Area Number of Household s Planted Area Number of Households Planted Area Planted Area Iramba 26,553 60,010 1,147 3,392 0 0 35,122 69,584 132,986 Singida Rural 25,695 42,261 2,043 2,161 0 0 45,940 69,908 114,330 Manyoni 3,460 6,546 169 171 1,422 3,595 28,014 52,847 63,160 Singida Urban 4,828 5,027 340 305 0 0 5,958 5,611 10,943 Total 60,536 113,845 3,699 6,029 1,422 3,595 115,034 197,951 321,419 Total Number of Household Planted Area Number of Household Planted Area Planted Area Iramba 0 0 567 1,977 1,977 Singida Rural 600 197 125 101 298 Manyoni 0 0 0 0 0 Singida Urban 0 0 41 17 17 Total 600 197 733 2,095 2,292 Total Number of Household Planted Area Number of Household Planted Area Planted Area Iramba 1,559 2,867 60,696 128,142 131,009 Singida Rur 1,584 3,916 71,371 110,116 114,032 Manyoni 2,157 4,202 30,908 58,957 63,160 Singida Urb 775 1,113 10,309 9,814 10,927 Total 6,076 12,098 173,283 307,029 319,128 7.1 and 7.2e: TOTAL ANNUAL CROP AND VEGETABLE: Total Number of Agriculture Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Mostly Farm Yard Manure Mostly Compost Mostly Inorganic No Fertilizer Applied District Households Using Irrigation Households Not Using Irrigation District 7.1 1nd 7.2f Total Annual Crop amd Vegetable Production: Total Number of Agriculture Households and Planted Area by Fertilizer Use and District for the 2002/03 agriculture Year - Long and Short Rainy Season, Morogoro Region Fertilizer Use Irrigation Use 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON Irrigation Use 7.1 ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Households Using Irrigation Households Not Using Irrigation Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 151 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 4,702 11,306 58,120 121,680 62,822 132,986 8.50 Singida Rural 3,930 7,222 69,749 107,108 73,679 114,330 6.32 Manyoni 3,185 10,578 29,880 52,582 33,065 63,160 16.75 Singida Urban 512 515 10,613 10,428 11,125 10,943 4.71 Total 12,329 29,621 168,363 291,798 180,691 321,419 9.22 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 287 875 62,535 132,111 62,822 132,986 0.66 Singida Rural 1,343 1,839 72,336 112,491 73,679 114,330 1.61 Manyoni 210 434 32,855 62,726 33,065 63,160 0.69 Singida Urban 43 34 11,083 10,909 11,125 10,943 0.32 Total 1,882 3,182 178,809 318,237 180,691 321,419 0.99 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 564 1,551 62,258 131,435 62,822 132,986 1.17 Singida Rural 1,686 2,227 71,992 112,102 73,679 114,330 1.95 Manyoni 324 2,901 32,741 60,258 33,065 63,160 4.59 Singida Urban 85 112 11,040 10,832 11,125 10,943 1.02 Total 2,660 6,792 178,031 314,627 180,691 321,419 2.11 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 11,020 27,905 51,802 104,767 62,822 132,672 21.03 Singida Rural 13,069 19,766 60,610 94,111 73,679 113,877 17.36 Manyoni 6,970 12,880 26,136 49,622 33,106 62,501 20.61 Singida Urban 2,846 2,556 9,571 10,663 12,417 13,218 19.33 Total 32,456 62,511 146,902 255,174 179,359 317,685 19.68 Insecticide % of Planted area using Insecticide % of Planted area using Herbicide 7.1 and 7.2h TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON District Total Households Not Using Insecticide Households Using Insecticide % of Planted area using Fungicide % of Planted area using Improved Seed 7.1 and 7.2i TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON 7.1 and 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON 7.1 and 7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Herbicide Total Households Using Improved Seed Households Not Using Improved Seed Total Improved Seed Use Households Not Using Fungicide Total District Herbicide Use Households Using Herbicide District Tanzania Agriculture Census Survey 2003 Singida Region 152 Appendix II 153 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 154 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 0 . 429 1,363 138 614 567 1,977 Singida Rural 120 12 120 24 485 261 724 298 Singida Urban 0 . 41 17 0 . 41 17 Total 120 12 590 1,404 622 875 1,333 2,292 % 5 1 26 61 27 38 58 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 286 1,028 0 . 0 . 281 950 567 1,977 Singida Rural 245 150 0 . 0 . 480 148 724 298 Singida Urban 41 17 0 . 0 . 0 . 41 17 Total 572 1,194 0 . 0 . 761 1,098 1,333 2,292 % 43 52 0 . 0 . 57 48 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 600 197 125 101 724 298 66.08 Singida Urban 0 0 41 17 41 17 0.00 Total 600 197 733 2,095 1,333 2,292 8.58 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-SHORT RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total % of Planted area using Irrigation Use 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON Total hh are indicative as a household may use more than one type of land preparation method for different crops District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 155 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 120 49 605 249 724 298 16.32 Singida Urban 0 0 41 17 41 17 0.00 Total 120 49 1,213 2,243 1,333 2,292 2.12 % 9.0 2 91.0 98 100.0 100 Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Insecticide 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total % of Planted area using Herbicide 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total % of Planted area using Fungicide 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 156 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0.00 Singida Rural 724 298 0 0 724 298 100.00 Singida Urban 0 0 41 17 41 17 0.00 Total 724 298 608 1,994 1,333 2,292 12.99 % 54.3 13 45.6 87 100.0 100 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Improved Seed 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - SHORT RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 157 ANNUAL CROP AND VEGETABLE PRODUCTION- LONG RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 158 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 138 2,009 51,285 117,107 10,832 11,579 62,255 130,695 Singida Rural 363 222 31,839 68,050 40,753 45,307 72,954 113,579 Manyoni 0 0 3,838 18,799 29,226 43,685 33,065 62,485 Singida Urban 85 43 1,328 2,198 9,671 8,686 11,084 10,927 Total 586 2,274 88,291 206,154 90,482 109,257 179,359 317,685 % 0.3 0.7 49.2 64.9 50.4 34.4 100.0 100.0 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Iramba 26,267 58,982 1,147 3,392 0 . 34,841 68,634 62,255 131,009 Singida Rural 25,451 42,111 2,043 2,161 0 . 45,460 69,760 72,954 114,032 Manyoni 3,460 6,546 169 171 1,422 3,595 28,014 52,847 33,065 63,160 Singida Urban 4,786 5,011 340 305 0 . 5,958 5,611 11,084 10,927 Total 59,964 112,651 3,699 6,029 1,422 3,595 114,274 196,853 179,359 319,128 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 1,559 2,867 60,696 128,142 62,255 131,009 2.2 Singida Rural 1,584 3,916 71,371 110,116 72,954 114,032 3.4 Manyoni 2,157 4,202 30,908 58,957 33,065 63,160 6.7 Singida Urban 775 1,113 10,309 9,814 11,084 10,927 10.2 Total 6,076 12,098 173,283 307,029 179,359 319,128 3.8 % 3.4 4 96.6 96 100.0 100 Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Households Using Irrigation Households Not Using Irrigation Total 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-LONG RAINY SEASON District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied % of Planted area using Irrigation Use 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON District Irrigation Use Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 159 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 4,702 11,306 57,553 119,703 62,255 131,009 Singida Rural 3,810 7,173 69,144 106,859 72,954 114,032 Manyoni 3,185 10,578 29,880 52,582 33,065 63,160 Singida Urban 512 515 10,572 10,411 11,084 10,927 Total 12,209 29,573 167,150 289,555 179,359 319,128 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 287 875 61,968 130,134 62,255 131,009 0.67 Singida Rural 1,223 1,790 71,732 112,242 72,954 114,032 1.57 Manyoni 210 434 32,855 62,726 33,065 63,160 0.69 Singida Urban 43 34 11,042 10,892 11,084 10,927 0.32 Total 1,762 3,134 177,596 315,994 179,359 319,128 0.98 % 1 1 99 99 100 100 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in LONG RAINY SEASON District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total % of Planted area using Herbicide Use 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 160 Number % Number % Iramba 24,877 39.8 37,652 60.2 62,528 Singida Rural 36,760 50.2 36,437 49.8 73,197 Manyoni 17,251 52.2 15,814 47.8 33,065 Singida Urban 2,833 25.5 8,292 74.5 11,125 Total 81,720 45.4 98,195 54.6 179,915 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 564 1,551 61,691 129,458 62,255 131,009 1.2 Singida Rural 1,567 2,179 71,388 111,853 72,954 114,032 1.9 Manyoni 324 2,901 32,741 60,258 33,065 63,160 4.6 Singida Urban 85 112 10,999 10,815 11,084 10,927 1.0 Total 2,540 6,743 176,819 312,384 179,359 319,128 2.1 % 1 2 99 98 100 100 District Number of Households that Sold Number of Households that Did not Sell Households Using Fungicide Households Not Using Fungicide Total 7.2f: Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District Did the Hh Sell any Crops from the 2002/03 season? Total Number of Households 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON % of Planted area using Fungicide Use District Fungicide Use Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 161 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 11,020 27,905 51,235 102,790 62,255 130,695 21.4 Singida Rural 12,344 19,468 60,610 94,111 72,954 113,579 17.1 Manyoni 6,970 12,880 26,095 49,605 33,065 62,485 20.6 Singida Urban 2,121 2,258 8,963 8,669 11,084 10,927 20.7 Total 32,456 62,511 146,902 255,174 179,359 317,685 19.7 % 18 20 82 80 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Iramba 0 0 567 1,977 567 1,977 0 Singida Rural 724 298 0 0 724 298 100 Singida Urban 0 0 41 17 41 17 0 Total 724 298 608 1,994 1,333 2,292 13 % 54.3 13 45.6 87 100 100 District Improved Seed Use % of Planted area using Improved Seed g Improved Seed g Improved Seed Total District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total % of Planted area using Fungicide Use 7.2h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 162 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 567 1,698 278 0.2 50,638 59,062 17,170 0.3 60,761 17,448 0.3 Singida Rural 125 88 52 0.6 51,194 42,699 21,146 0.5 42,787 21,198 0.5 Manyoni 0 0 0 0.0 27,194 32,035 15,102 0.5 32,035 15,102 0.5 Singida Urban 41 8 10 1.2 3,641 1,686 639 0.4 1,694 649 0.4 Total 733 1,795 340 0.2 132,667 135,482 54,056 0.4 137,277 54,396 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 845 615 186 0.3 615 186 0.3 Singida Rural 0 0 0 0.0 2,055 1,140 1,128 1.0 1,140 1,128 1.0 Manyoni 0 0 0 0.0 4,104 1,873 589 0.3 1,873 589 0.3 Singida Urban 0 0 0 0.0 169 39 70 1.8 39 70 1.8 Total 0 0 0 0.0 7,173 3,665 1,973 0.5 3,665 1,973 0.5 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0 27,844 29,836 6,296 0.2 29,836 6,296 0.2 Singida Rural 125 13 6 0.5 39,387 29,315 12,474 0.4 29,328 12,480 0.4 Manyoni 0 0 0 0 11,096 8,589 2,233 0.3 8,589 2,233 0.3 Singida Urban 41 8 5 0.6 4,483 2,143 689 0.3 2,151 694 0.3 Total 166 21 11 0.0 82,809 69,884 21,692 0.3 69,905 21,703 0.3 Table 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District; 2002/03 Agricultural Year District Maize Short Rainy bseason Long Rainy bSeason Total Table 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District; 2002/03 Agricultura Year District Paddy Short Rainy bseason Long Rainy bSeason Total Table 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sorghum Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 163 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 5,906 3,428 1,216 0.0 3,428 1,216 0.0 Manyoni 0 0 0 0.0 243 75 21 0.3 75 21 0.3 Singida Urban 0 0 0 0.0 972 399 120 0.0 399 120 0.0 Total 0 0 0 0.0 7,121 3,901 1,357 0.0 3,901 1,357 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 6,475 6,949 1,600 0.2 6,949 1,600 0.2 Singida Rural 0 0 0 0.0 26,832 16,562 6,438 0.0 16,562 6,438 0.0 Manyoni 0 0 0 0.0 1,871 2,116 376 0.0 2,116 376 0.0 Singida Urban 0 0 0 0.0 8,207 5,156 1,610 0.0 5,156 1,610 0.0 Total 0 0 0 0.0 43,386 30,783 10,025 0.0 30,783 10,025 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Table 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District 2002/03 Agricultural Year District Fingemillet Short Rainy bseason Long Rainy bSeason Total Table 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Bulrushmillets Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bulrushmillets Short Rainy bseason Long Rainy bSeason Total Table 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District; 2002/0 Agricultural Year District Wheat Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 164 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 3,116 842 1,100 1.3 842 1,100 1.3 Singida Rural 0 0 0 0.0 1,221 964 354 0.4 964 354 0.4 Manyoni 0 0 0 0.0 1,628 1,019 819 0.8 1,019 819 0.8 Singida Urban 0 0 0 0.0 646 171 151 0.9 171 151 0.9 Total 0 0 0 0.0 6,610 2,995 2,424 0.8 2,995 2,424 0.8 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 3,670 911 127 0.1 911 127 0.1 Singida Rural 0 0 0 0.0 2,300 755 1,845 2.4 755 1,845 2.4 Manyoni 0 0 0 0.0 1,848 726 681 0.9 726 681 0.9 Singida Urban 0 0 0 0.0 614 171 153 0.9 171 153 0.9 Total 0 0 0 0.0 8,432 2,564 2,807 1.1 2,564 2,807 1.1 Table 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Barley Harvested (tons) by Season and District; 2002/03 Agricultural Year District Barley Short Rainy bseason Long Rainy bSeason Total Table 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cassava Short Rainy bseason Long Rainy bSeason Total Table 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sweet potatoes Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 165 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 80 161 364 0.0 161 364 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 80 161 364 0.0 161 364 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 33 3 2 0.0 3 2 0.0 Total 0 0 0 0.0 33 3 2 0.7 3 2 0.7 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Table 7.2.10 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year District Irish potatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District; 2002/03 Agricultural Year District Yams Short Rainy bseason Long Rainy bSeason Total Table 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District 2002/03 Agricultural Year District Cocoyams Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 166 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 2 9 4.1 2 9 4.1 Total 0 0 0 0.0 43 2 9 4.1 2 9 4.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 10,124 4,209 469 0.1 4,209 469 0.1 Singida Rural 0 0 0 0.0 3,396 1,051 374 0.4 1,051 374 0.4 Manyoni 0 0 0 0.0 6,308 3,051 797 0.3 3,051 797 0.3 Singida Urban 0 0 0 0.0 85 17 5 0.3 17 5 0.3 Total 0 0 0 0.0 19,913 8,328 1,645 0.2 8,328 1,645 0.2 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 143 29 3 0.1 29 3 0.1 Singida Rural 0 0 0 0.0 860 237 63 0.3 237 63 0.3 Manyoni 0 0 0 0.0 1,468 653 230 0.4 653 230 0.4 Singida Urban 0 0 0 0.0 108 23 3 0.1 23 3 0.1 Total 0 0 0 0.0 2,579 943 299 0.3 943 299 0.3 Table 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Mungbeans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Mungbeans Short Rainy bseason Long Rainy bSeason Total Table 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Beans Short Rainy bseason Long Rainy bSeason Total Table 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cowpeas Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 167 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 242 174 75 0.4 174 75 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 242 174 75 0.4 174 75 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 980 1,112 604 0.5 1,112 604 0.5 Singida Rural 0 0 0 0.0 495 274 123 0.5 274 123 0.5 Manyoni 0 0 0 0.0 822 1,815 896 0.5 1,815 896 0.5 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 2,297 3,201 1,624 0.5 3,201 1,624 0.5 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 1,697 321 71 0.2 321 71 0.2 Singida Rural 0 0 0 0.0 124 13 7 0.6 13 7 0.6 Manyoni 0 0 0 0.0 1,767 335 88 0.3 335 88 0.3 Singida Urban 0 0 0 0.0 85 26 2 0.1 26 2 0.1 Total 0 0 0 0.0 3,673 695 169 0.2 695 169 0.2 Table 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Greengram Harvested (tons) by Season and District; 2002/0 Agricultural Year District Greengram Short Rainy bseason Long Rainy bSeason Total Table 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District; 2002/0 Agricultural Year District Chick peas Short Rainy bseason Long Rainy bSeason Total Table 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District; 2002/0 Agricultural Year District Bambanuts Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 168 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 138 279 335 1.2 23,115 23,946 12,364 0.5 24,225 12,699 0.5 Singida Rural 0 0 0 0.0 20,120 15,130 7,968 0.5 15,130 7,968 0.5 Manyoni 0 0 0.0 1,361 609 262 0.4 609 262 0.4 Singida Urban 0 0 0 0.0 1,261 905 408 0.5 905 408 0.5 Total 138 279 335 1.2 45,857 40,590 21,002 0.5 40,869 21,337 0.5 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 143 116 26 0.2 116 26 0.2 Singida Rural 0 0 0 0.0 121 49 18 0.4 49 18 0.4 Manyoni 0 0 0 0.0 2,501 1,888 843 0.4 1,888 843 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 2,765 2,053 887 0.4 2,053 887 0.4 Table 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Fieldpeas Harvested (tons) by Season and District; 2002/0 Agricultural Year District Fieldpeas Short Rainy bseason Long Rainy bSeason Total Table 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Sunflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District; 2002/03 Agricultura Year District Simsim Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 169 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) % of area Area per g growig hh Iramba 0 0 0 0.0 8,901 2,917 459 0.2 2,917 459 0.2 28.8 0.33 Singida Rural 0 0 0 0.0 2,549 1,332 355 0.3 1,332 355 0.3 13.1 0.52 Manyoni 0 0 0 0.0 14,211 5,897 1,648 0.3 5,897 1,648 0.3 58.1 0.41 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 0.0 0.00 Total 0 0 0 0.0 25,662 10,146 2,462 0.2 10,146 2,462 0.2 100.0 0.40 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 124 50 15 0.3 50 15 0.3 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 4 2 0.4 4 2 0.4 Total 0 0 0 0.0 167 55 17 0.3 55 17 0.3 Table 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District; 2002/03 Agricultural Year District Groundnuts Short Rainy bseason Long Rainy bSeason Total Table 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District; 2002/03 District Castor oil Short Rainy bseason Long Rainy bSeason Total Table 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Soya beans Harvested (tons) by Season and District; 2002/03 Agricultural Year District Soya beans Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 170 Household Planted Harvested (tons/ha) Household Planted Harvested (tons/ha) Planted Harvested (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 126 20 8 0.4 20 8 0.4 Total 0 0 0 0.0 126 20 8 0.4 20 8 0.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 84 16 14 0.9 16 14 0.9 Total 0 0 0 0.0 84 16 14 0.9 16 14 0.9 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 247 100 214 2.1 100 214 2.1 Singida Rural 0 0 0 0.0 1,473 657 601 0.9 657 601 0.9 Manyoni 0 0 0 0.0 80 5 4 0.7 5 4 0.7 Singida Urban 0 0 0 0.0 127 12 12 1.0 12 12 1.0 Total 0 0 0 0.0 1,928 775 830 1.1 775 830 1.1 Table 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District; 2002/03 Agricultural Year District Okra Short Rainy bseason Long Rainy bSeason Total Table 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District; 2002/03 Agricultural Year District Bitter Aubergine Short Rainy bseason Long Rainy bSeason Total Table 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Onion Harvested (tons) by Season and District; 2002/03 Agricultural Year District Onion Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 171 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 124 25 37 1.5 25 37 1.5 Manyoni 0 0 0 0.0 165 21 127 5.9 21 127 5.9 Singida Urban 0 0 0 0.0 33 4 5 1.3 4 5 1.3 Total 0 0 0 0.0 321 50 169 3.4 50 169 3.4 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 141 7 11 1.5 7 11 1.5 Singida Rural 600 109 266 2.4 841 108 102 0.9 218 368 1.7 Manyoni 0 0 0 0.0 237 17 39 2.4 17 39 2.4 Singida Urban 0 0 0 0.0 583 82 115 1.4 82 115 1.4 Total 600 109 266 2.4 1,802 215 268 1.2 324 534 1.6 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 141 7 6 0.8 7 6 0.8 Singida Rural 120 15 12 0.8 124 13 13 1.0 27 25 0.9 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 15 12 0.8 265 19 19 1.0 34 31 0.9 Table 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cabbage Short Rainy bseason Long Rainy bSeason Total Table 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tomatoes Short Rainy bseason Long Rainy bSeason Total Table 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Spinnach Harvested (tons) by Season and District; 2002/0 Agricultural Year District Spinnach Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 172 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 42 4 5 1.1 4 5 1.1 Total 0 0 0 0.0 42 4 5 1.1 4 5 1.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 158 9 4 0.4 9 4 0.4 Singida Urban 0 0 0 0.0 192 27 57 2.1 27 57 2.1 Total 0 0 0 0.0 350 36 60 1.7 36 60 1.7 Table 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Carrot Harvested (tons) by Season and District; 2002/03 Agricultural Year District Carrot Short Rainy bseason Long Rainy bSeason Total Table 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Chillies Harvested (tons) by Season and District; 2002/03 Agricultural Year District Chillies Short Rainy bseason Long Rainy bSeason Total Table 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Amaranths Harvested (tons) by Season and District; 2002/03 Agricultural Year District Amaranths Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 173 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 10 10 1.0 0 0 0 0.0 10 10 1.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 10 10 1.0 0 0 0 0.0 10 10 1.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 39 6 0.2 0 0 0 0.0 39 6 0.2 Manyoni 0 0 0 0.0 85 17 0 0.0 17 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 120 39 6 0.2 85 17 0 0.0 56 6 0.1 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 120 24 96 4.0 0 0 0 0.0 24 96 4.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 43 17 19 1.1 17 19 1.1 Total 120 24 96 4.0 43 17 19 1.1 42 115 2.8 Table 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District; 2002/03 Agricultural Year District Pumpkins Short Rainy bseason Long Rainy bSeason Total Table 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cucumber Short Rainy bseason Long Rainy bSeason Total Table 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District; 2002/0 Agricultural Year District Eggplant Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 174 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 20 1 6 4.0 0 0 0 0.0 1 6 4.0 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 123 80 15 0.2 80 15 0.2 Manyoni 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 123 80 15 0.2 80 15 0.2 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 399 687 275 0.4 687 275 0.4 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 399 687 275 0.4 687 275 0.4 Table 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District; 2002/03 Agricultural Year District Water Mellon Short Rainy bseason Long Rainy bSeason Total Table 7.2.37 Number of Agricultural Households, Area Planted (ha) and Quantity of Cauliflower Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cauliflower Short Rainy bseason Long Rainy bSeason Total Table 7.2.38 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District; 2002/03 Agricultural Year District Cotton Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 175 Number of Household Area Planted Quantity Harvested Yield (tons/ha) Number of Household Area Planted Quantity Harvested Yield (tons/ha) Area Planted Quantity Harvested Yield (tons/ha) Iramba 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Singida Rural 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Manyoni 0 0 0 0.0 1,343 1,387 1,083 0.8 1,387 1,083 0.8 Singida Urban 0 0 0 0.0 0 0 0 0.0 0 0 0.0 Total 0 0 0 0.0 1,343 1,387 1,083 0.8 1,387 1,083 0.8 Table 7.2.39 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District; 2002/03 Agricultural Year District Tobacco Short Rainy bseason Long Rainy bSeason Total Tanzania Agriculture Census Survey 2003 Singida Region 176 Appendix II 177 PERMANENT CROPS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 178 Planted Area (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Star Fruit 70 58 86 1482 Sugarcane 29 14 28 1976 Banana 503 92 213 2309 Mango 806 0 5 0 Pawpaw 26 0 33 0 Guava 14 0 13 0 Lime/Lemon 0 0 . 0 Total 1,449 164 378 2298 Pigeon Pea 65 65 14 217 Cashewnut . 0 6 0 Sugarcane 462 110 3,773 34236 Banana 2,739 129 433 3363 Mango 164 76 169 2218 Pawpaw 21 35 20 575 Orange 50 25 . 0 Guava 439 215 166 773 Lime/Lemon 1 0 12 0 Total 3,940 654 4,593 7024 Sugarcane 18 9 1,393 161834 Tamarin 7 0 . 0 Banana 86 23 180 7758 Mango 2,770 0 22 0 Pawpaw 3 1 12 12844 Guava 269 0 . 0 Lime/Lemon 7 0 . 0 Total 3,159 33 1,607 49001 Pigeon Pea . . . 0 Star Fruit . 0 10 0 Cashewnut . . 1 0 Sugarcane 33 11 63 5824 Nutmeg . . 1 0 Banana 45 14 46 3253 Mango 43 0 58 0 Pawpaw 22 9 7 841 Orange . . 2 0 Guava 545 6 28 4982 Lime/Lemon 2 2 8 4129 Bilimbi 4 4 10 2487 Total 695 45 234 5174 Pigeon Pea 65 65 14 217 Star Fruit 70 58 95 1652 Cashewnut . 0 7 0 Sugarcane 541 144 5,257 36522.005 Tamarin 7 0 . 0 Nutmeg . . 1 0 Banana 3,373 259 873 3375 Mango 3,784 76 254 3331 Pawpaw 72 44 72 1633 Orange 50 25 2 66 Guava 1,268 220 207 939 Lime/Lemon 10 2 20 10007 Bilimbi 4 4 10 2487 Total 9,242 896 6,812 7600 Manyoni Singida Urban Total Table 7.3 Production of Permanent Crops by Crop type and Region - Singida Region District/Crop Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 179 Cont…..7.3 Production of Permanent Crops by Crop type and Region - Singida Region Crop Area Planted % Mango 3,784 40.9 Banana 3,373 36.5 Guava 1,268 13.7 Sugarcane 541 5.9 Pawpaw 72 0.8 Star Fruit 70 0.8 Pigeon Pea 65 0.7 Orange 50 0.5 Lime/Lemon 10 0.1 Tamarin 7 0.1 Bilimbi 4 0.0 Cashewnut 0 0.0 Nutmeg 0 0.0 Total 9,242 100.0 Mostly Farm Yard Manure Mostly Compost No Fertilizer Applied Total Planted Area (ha) Planted Area (ha) Planted Area (ha) Planted Area (ha) Pigeon Pea 30 . 35 65 Star Fruit . . 70 70 Sugarcane 78 63 399 541 Tamarin . . 7 7 Banana 313 229 2,831 3,373 Mango 470 11 3,303 3,784 Pawpaw 23 0 49 72 Orange 50 . . 50 Guava 75 . 1,194 1,268 Lime/Lemon . . 10 10 Bilimbi . . 4 4 Total 1,037 303 7,901 9,242 Cont…. Planted Area with Fertiliser by type Crop Pigeon Pea 30 65 46.0 Star Fruit . 70 0.0 Sugarcane 78 541 14.5 Tamarin . 7 0.0 Banana 313 3,373 9.3 Mango 470 3,784 12.4 Pawpaw 23 72 31.4 Orange 50 50 100.0 Guava 75 1,268 5.9 Lime/Lemon . 10 0.0 Bilimbi . 4 0.0 Total 1,037 9,242 11.2 PERMANENT CROPS: Number of Households by Planted Area by Fertilizer Use by Crop by District Total % Crop Type Crop Type Mostly Farm Yard Manure Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 180 Mostly Compost Total Planted Area (ha) Planted Area (ha) Pigeon Pea . 65 0.0 Star Fruit . 70 0.0 Sugarcane 63 541 11.7 Tamarin . 7 0.0 Banana 229 3,373 6.8 Mango 11 3,784 0.3 Pawpaw 0 72 0.2 Orange . 50 0.0 Guava . 1,268 0.0 Lime/Lemon . 10 0.0 Bilimbi . 4 0.0 Total 303 9,242 3.3 Crop Type Cont…. Planted Area with Fertiliser by type Crop % Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 181 AGROPROCESSING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 182 Number % Number % Number % Iramba 56,039 90 6,489 10 62,528 100 Singida Rural 70,259 96 2,937 4 73,197 100 Manyoni 31,583 96 1,481 4 33,065 100 Singida Urban 9,469 85 1,657 15 11,125 100 Total 167,351 93 12,564 7 179,915 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Iramba 2,904 143 49,732 0 2,693 0 0 568 56,039 Singida Rural 9,483 2,337 55,266 125 2,801 123 125 0 70,259 Manyoni 4,416 1,339 25,744 0 0 0 84 0 31,583 Singida Urban 210 649 7,611 0 923 0 75 0 9,469 Total 17,013 4,468 138,352 125 6,417 123 284 568 167,351 8.0b Number of Crop Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District 2002/03 Agricultural Year Households That Processed Crops Households That Did Not Process Crops Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 183 Number % Number % Number % Iramba 56,039 90 6,489 10 62,528 100 Singida Rural 70,259 96 2,937 4 73,197 100 Manyoni 31,583 96 1,481 4 33,065 100 Singida Urban 9,469 85 1,657 15 11,125 100 Total 167,351 93 12,564 7 179,915 100 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Other Total Maize 117,228 0 143 143 0 0 117,514 Paddy 5,030 0 0 0 84 0 5,115 Sorghum 71,084 0 0 0 251 65 71,401 Bulrush Millet 39,601 120 123 0 202 0 40,047 Finger Millet 444 0 0 0 0 0 444 Cassava 2,288 0 0 0 0 0 2,288 Sweet Potatoes 1,659 0 0 0 0 0 1,659 Beans 2,524 0 0 0 0 0 2,524 Cowpeas 228 0 0 0 0 0 228 Pigeon Peas 122 0 0 0 0 0 122 Chick Peas 305 0 0 0 0 0 305 Bambaranut 831 124 0 0 0 0 955 Sunflower 4,588 0 142 0 80 0 4,810 Simsim 227 0 0 0 0 0 227 Groundnut 16,876 124 284 0 0 0 17,283 Banana 144 0 0 0 0 0 144 Total 263,179 367 693 143 618 65 265,064 Product Use Crop Table 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 agricultural Year by Location and Crop, Singida Region District Households That Processed Product Households That Did Not Process Product Total 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Farm Products Produced During 2002/03 Agricultural Year by Use of Products and Crop, 2002/03 Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 184 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Trader at Farm Other Did not Sell Total Maize 2,098 518 0 258 165 115 282 114,079 117,514 Paddy 189 0 169 0 0 291 0 4,465 5,115 Sorghum 803 42 0 0 42 121 108 70,286 71,401 Bulrush Millet 611 0 0 123 0 0 246 39,068 40,047 Finger Millet 125 0 0 0 0 0 0 319 444 Cassava 85 0 0 0 0 0 0 2,203 2,288 Sweet Potatoes 0 0 0 0 0 0 0 1,659 1,659 Beans 0 0 0 0 0 0 0 2,524 2,524 Cowpeas 0 0 0 0 0 0 0 228 228 Pigeon Peas 0 0 0 0 0 0 0 122 122 Chick Peas 0 0 0 0 0 80 0 225 305 Bambaranut 0 0 0 0 0 0 0 955 955 Sunflower 421 285 0 143 0 80 0 3,881 4,810 Simsim 0 0 0 0 0 0 0 227 227 Groundnut 414 0 83 0 0 150 0 16,636 17,283 Banana 144 0 0 0 0 0 0 0 144 Total 4,889 845 252 523 207 836 636 256,877 265,064 Flour / Mea Grain Oil Juice Other Total Iramba 53,784 574 843 0 838 56,039 Singida Rural 68,925 1,089 245 0 0 70,259 Manyoni 28,788 1,650 1,064 81 0 31,583 Singida Urban 9,309 160 0 0 0 9,469 Total 160,806 3,473 2,153 81 838 167,351 District Main Product 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product During 2002/03 Agriculture Year and District 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultura Year By Location of Sale of Product and Crop Crop Where Sold Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 185 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumption Did Not Use Total Iramba 55,611 0 285 143 0 56,039 Singida Rural 70,139 120 0 0 0 70,259 Manyoni 31,583 0 0 0 0 31,583 Singida Urban 9,427 0 0 0 42 9,469 Total 166,761 120 285 143 42 167,351 Neighbours Local Market / Trade Store Secondary Market Marketing Co- operative Farmers Association Trader at Farm Other Did not Sell Total Iramba 1,274 575 0 143 0 0 282 53,764 56,039 Singida Rural 859 0 0 115 123 0 0 69,164 70,259 Manyoni 506 85 169 0 0 168 0 30,656 31,583 Singida Urban 202 0 0 0 42 0 128 9,097 9,469 Total 2,842 660 169 258 165 168 410 162,680 167,351 Bran Cake Husk Pulp Oil Shell No by- product Other Total Iramba 1,964 2,018 0 0 0 0 52,058 0 56,039 Singida Rural 368 123 1,080 123 123 0 68,318 125 70,259 Manyoni 1,097 634 2,435 0 84 0 27,333 0 31,583 Singida Urban 124 126 85 165 0 85 8,884 0 9,469 Total 3,553 2,900 3,600 288 207 85 156,593 125 167,351 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product During 2002/03 Agriculture Year and District District Product Use District By Product 8.0g AGRO PROCESSING: Number of Crop Growing Households By By-Product During 2002/03 Agriculture Year and District 8.0f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold During 2002/03 Agriculture Year and District District Where Sold Tanzania Agriculture Census Survey 2003 Singida Region 186 Appendix II 187 STORAGE Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 188 No. of Househol ds % No. of Households % No. of Households % No. of Househ olds % No. of Househol ds % Maize 34,537 79.6 3,204 7.4 5,124 11.8 533 1.2 43,397 100.0 Paddy 143 100.0 0 0.0 0 0.0 0 0.0 143 100.0 Sorghum & Millet 21,296 80.0 2,059 7.7 3,151 11.8 112 0.4 26,619 100.0 Beans & Pulses 7,254 92.9 0 0.0 557 7.1 0 0.0 7,810 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 1,979 100.0 0 0.0 0 0.0 0 0.0 1,979 100.0 Total 65,209 81.6 5,262 6.6 8,832 11.0 645 0.8 79,949 100.0 Maize 36,140 80.1 6,426 14.2 2,082 4.6 492 1.1 45,140 100.0 Paddy 1,810 100.0 0 0.0 0 0.0 0 0.0 1,810 100.0 Sorghum & Millet 46,769 91.3 3,941 7.7 363 0.7 125 0.2 51,198 100.0 Beans & Pulses 1,587 92.7 125 7.3 0 0.0 0 0.0 1,712 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 125 100.0 0 0.0 0 0.0 0 0.0 125 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 86,432 86.4 10,491 10.5 2,444 2.4 617 0.6 99,985 100.0 Maize 22,223 91.5 1,342 5.5 479 2.0 250 1.0 24,294 100.0 Paddy 2,856 100.0 0 0.0 0 0.0 0 0.0 2,856 100.0 Sorghum & Millet 8,952 93.3 416 4.3 230 2.4 0 0.0 9,598 100.0 Beans & Pulses 5,769 94.7 83 1.4 240 3.9 0 0.0 6,092 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 79 100.0 0 0.0 0 0.0 0 0.0 79 100.0 Groundnuts/Ba mbara Nuts 4,648 100.0 0 0.0 0 0.0 0 0.0 4,648 100.0 Total 44,612 93.6 1,840 3.9 950 2.0 250 0.5 47,652 100.0 Maize 2,403 95.0 85 3.3 43 1.7 0 0.0 2,530 100.0 Paddy 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Sorghum & Millet 8,420 94.0 455 5.1 43 0.5 42 0.5 8,959 100.0 Beans & Pulses 108 71.8 0 0.0 43 28.2 0 0.0 151 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/Ba mbara Nuts 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Total 11,100 94.0 539 4.6 128 1.1 42 0.4 11,809 100.0 9.0 CROP STORAGE: Number of Households Storing Crops By Estimated Storage Loss and Crop Type Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba Singida Rural Manyoni Singida Urban Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 189 No. of Househol ds % No. of Households % No. of Households % No. of Househ olds % No. of Househol ds % 9.0 CROP STORAGE: Number of Households Storing Crops By Estimated Storage Loss and Crop Type Crop Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Maize 95,303 82.6 11,056 9.6 7,727 6.7 1,275 1.1 115,361 100.0 Paddy 4,894 100.0 0 0.0 0 0.0 0 0.0 4,894 100.0 Sorghum & Millet 85,438 88.7 6,870 7.1 3,787 3.9 279 0.3 96,374 100.0 Beans & Pulses 14,719 93.4 207 1.3 839 5.3 0 0.0 15,765 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 167 100.0 0 0.0 0 0.0 0 0.0 167 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 79 100.0 0 0.0 0 0.0 0 0.0 79 100.0 Groundnuts/Ba mbara Nuts 6,669 100.0 0 0.0 0 0.0 0 0.0 6,669 100.0 Total 207,354 86.6 18,133 7.6 12,354 5.2 1,555 0.6 239,395 100.0 Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 190 No. of Households % No. of House holds % No. of Households % No. of Households % No. of Househ olds % Maize 43,112 99.3 0 0.0 285 0.7 0 0.0 43,397 100.0 Paddy 143 100.0 0 0.0 0 0.0 0 0.0 143 100.0 Sorghum & Millet 26,189 98.4 0 0.0 430 1.6 0 0.0 26,619 100.0 Beans & Pulses 4,998 64.0 0 0.0 2,813 36.0 0 0.0 7,810 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 986 49.8 0 0.0 994 50.2 0 0.0 1,979 100.0 Total 75,428 94.3 0 0.0 4,521 5.7 0 0.0 79,949 100.0 Maize 43,546 96.5 0 0.0 1,594 3.5 0 0.0 45,140 100.0 Paddy 1,690 93.4 120 6.6 0 0.0 0 0.0 1,810 100.0 Sorghum & Millet 49,364 96.4 607 1.2 1,227 2.4 0 0.0 51,198 100.0 Beans & Pulses 971 56.7 0 0.0 741 43.3 0 0.0 1,712 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 125 100.0 0 0.0 0 0.0 0 0.0 125 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Total 95,696 95.7 728 0.7 3,562 3.6 0 0.0 99,985 100.0 Maize 23,572 97.0 253 1.0 470 1.9 0 0.0 24,294 100.0 Paddy 2,554 89.4 141 4.9 160 5.6 0 0.0 2,856 100.0 Sorghum & Millet 9,371 97.6 84 0.9 143 1.5 0 0.0 9,598 100.0 Beans & Pulses 4,121 67.6 234 3.8 1,737 28.5 0 0.0 6,092 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 79 100.0 79 100.0 Groundnuts/ Bambara Nuts 2,928 63.0 139 3.0 1,580 34.0 0 0.0 4,648 100.0 Total 42,631 89.5 851 1.8 4,090 8.6 79 0.2 47,652 100.0 Iramba Singida Rural Manyoni 9.0a CROP STORAGE: Number of Households Storing Crops By Main Purpose of Storage and Crop Type Crop Food for the Household To Sell for Higher Price Seeds for Planting Other Total Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 191 No. of Households % No. of House holds % No. of Households % No. of Households % No. of Househ olds % 9.0a CROP STORAGE: Number of Households Storing Crops By Main Purpose of Storage and Crop Type Crop Food for the Household To Sell for Higher Price Seeds for Planting Other Total Maize 2,488 98.3 42 1.7 0 0.0 0 0.0 2,530 100.0 Paddy 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Sorghum & Millet 8,876 99.1 83 0.9 0 0.0 0 0.0 8,959 100.0 Beans & Pulses 85 56.4 0 0.0 66 43.6 0 0.0 151 100.0 Wheat 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Groundnuts/ Bambara Nuts 42 100.0 0 0.0 0 0.0 0 0.0 42 100.0 Total 11,619 98.4 125 1.1 66 0.6 0 0.0 11,809 100.0 Maize 112,718 97.7 295 0.3 2,349 2.0 0 0.0 115,361 100.0 Paddy 4,473 91.4 261 5.3 160 3.3 0 0.0 4,894 100.0 Sorghum & Millet 93,801 97.3 774 0.8 1,799 1.9 0 0.0 96,374 100.0 Beans & Pulses 10,174 64.5 234 1.5 5,357 34.0 0 0.0 15,765 100.0 Wheat 85 100.0 0 0.0 0 0.0 0 0.0 85 100.0 Coffee 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cashewnut 167 100.0 0 0.0 0 0.0 0 0.0 167 100.0 Tobacco 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 Cottton 0 0.0 0 0.0 0 0.0 79 100.0 79 100.0 Groundnuts/ Bambara Nuts 3,956 59.3 139 2.1 2,574 38.6 0 0.0 6,669 100.0 Total 225,374 94.1 1,704 0.7 12,239 5.1 79 0.0 239,395 100.0 Total Singida Urban Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 192 No. of Households % No. of Households % No. of Households % Maize 43,397 81.5 9,858 18.5 53,255 100.0 Paddy 143 0.3 52,971 99.7 53,114 100.0 Sorghum & Millet 26,619 50.1 26,496 49.9 53,114 100.0 Beans & Pulses 7,810 14.7 45,304 85.3 53,114 100.0 Wheat 0 0.0 53,114 100.0 53,114 100.0 Coffee 0 0.0 53,114 100.0 53,114 100.0 Cashewnut 0 0.0 53,114 100.0 53,114 100.0 Tobacco 0 0.0 53,114 100.0 53,114 100.0 Cottton 0 0.0 53,114 100.0 53,114 100.0 Groundnuts/Ba mbara Nuts 1,979 3.7 51,135 96.3 53,114 100.0 Total 79,949 15.0 451,336 85.0 531,284 100.0 Maize 45,140 64.9 24,455 35.1 69,595 100.0 Paddy 1,810 2.6 67,785 97.4 69,595 100.0 Sorghum & Millet 51,198 73.6 18,397 26.4 69,595 100.0 Beans & Pulses 1,712 2.5 67,883 97.5 69,595 100.0 Wheat 0 0.0 69,595 100.0 69,595 100.0 Coffee 0 0.0 69,595 100.0 69,595 100.0 Cashewnut 125 0.2 69,470 99.8 69,595 100.0 Tobacco 0 0.0 69,595 100.0 69,595 100.0 Cottton 0 0.0 69,595 100.0 69,595 100.0 Groundnuts/Ba mbara Nuts 0 0.0 69,595 100.0 69,595 100.0 Total 99,985 14.4 595,964 85.6 695,950 100.0 Maize 24,294 80.1 6,053 19.9 30,347 100.0 Paddy 2,856 9.4 27,492 90.6 30,347 100.0 Sorghum & Millet 9,598 31.6 20,749 68.4 30,347 100.0 Beans & Pulses 6,092 20.1 24,255 79.9 30,347 100.0 Wheat 85 0.3 30,262 99.7 30,347 100.0 Coffee 0 0.0 30,347 100.0 30,347 100.0 Cashewnut 0 0.0 30,347 100.0 30,347 100.0 Tobacco 0 0.0 30,347 100.0 30,347 100.0 Cottton 79 0.3 30,268 99.7 30,347 100.0 Groundnuts/Ba mbara Nuts 4,648 15.3 25,699 84.7 30,347 100.0 Total 47,652 15.7 255,820 84.3 303,473 100.0 9.0c CROP STORAGE: Number of Households Storing Crops By Type of Crop Crop Households Storing Crop g Crop Total Iramba Singida Rural Manyoni Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 193 No. of Households % No. of Households % No. of Households % 9.0c CROP STORAGE: Number of Households Storing Crops By Type of Crop Crop Households Storing Crop g Crop Total Maize 2,530 26.1 7,148 73.9 9,678 100.0 Paddy 85 0.9 9,593 99.1 9,678 100.0 Sorghum & Millet 8,959 92.6 719 7.4 9,678 100.0 Beans & Pulses 151 1.6 9,527 98.4 9,678 100.0 Wheat 0 0.0 9,678 100.0 9,678 100.0 Coffee 0 0.0 9,678 100.0 9,678 100.0 Cashewnut 42 0.4 9,636 99.6 9,678 100.0 Tobacco 0 0.0 9,678 100.0 9,678 100.0 Cottton 0 0.0 9,678 100.0 9,678 100.0 Groundnuts/Ba mbara Nuts 42 0.4 9,636 99.6 9,678 100.0 Total 11,809 12.2 84,972 87.8 96,781 100.0 Maize 115,361 70.8 47,515 29.2 162,876 100.0 Paddy 4,894 3.0 157,841 97.0 162,735 100.0 Sorghum & Millet 96,374 59.2 66,361 40.8 162,735 100.0 Beans & Pulses 15,765 9.7 146,969 90.3 162,735 100.0 Wheat 85 0.1 162,650 99.9 162,735 100.0 Coffee 0 0.0 162,735 100.0 162,735 100.0 Cashewnut 167 0.1 162,567 99.9 162,735 100.0 Tobacco 0 0.0 162,735 100.0 162,735 100.0 Cottton 79 0.0 162,655 100.0 162,735 100.0 Groundnuts/Ba mbara Nuts 6,669 4.1 156,065 95.9 162,735 100.0 Total 239,395 14.7 1,388,092 85.3 1,627,487 100.0 Total Singida Urban Tanzania Agriculture Sample census - 2003 Singida Region Appendix II 194 Number of Households Quantity stored (tons) Maize 43,397 1,323 Paddy 143 0 Sorghum & Millet 26,619 535 Beans & Pulses 7,810 11 Groundnuts/Bambara Nuts 1,979 25 Total 79,949 1,895 Maize 45,140 4,275 Paddy 1,810 261 Sorghum & Millet 51,198 3,965 Beans & Pulses 1,712 34 Cashewnut 125 0 Total 99,985 8,535 Maize 24,294 2,762 Paddy 2,856 126 Sorghum & Millet 9,598 804 Beans & Pulses 6,092 186 Wheat 85 0 Cottton 79 2 Groundnuts/Bambara Nuts 4,648 94 Total 47,652 3,974 Maize 2,530 6 Paddy 85 0 Sorghum & Millet 8,959 109 Beans & Pulses 151 0 Cashewnut 42 0 Groundnuts/Bambara Nuts 42 0 Total 11,809 115 Maize 115,361 8,366 Paddy 4,894 387 Sorghum & Millet 96,374 5,413 Beans & Pulses 15,765 230 Wheat 85 0 Cashewnut 167 0 Cottton 79 2 Groundnuts/Bambara Nuts 6,669 119 Total 239,395 14,518 Manyoni Singida Urban Total 9.1 CROP STORAGE: Number of Households and Current Quantity Stored (tons) by Crop Type and District District/Crop Type Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 195 Less than 3 Months Between 3 and 6 Months Over 6 Months Total Maize 13,364 21,648 8,386 43,397 Paddy 143 0 0 143 Sorghum & Millet 9,019 13,228 4,372 26,619 Beans & Pulses 2,835 4,403 572 7,810 Groundnuts/B ambara Nuts 420 1,559 0 1,979 Total 25,781 40,838 13,330 79,949 Maize 19,148 19,080 6,912 45,140 Paddy 122 368 1,321 1,810 Sorghum & Millet 20,790 21,663 8,745 51,198 Beans & Pulses 491 610 611 1,712 Cashewnut 125 0 0 125 Total 40,676 41,721 17,589 99,985 Maize 6,424 11,664 6,205 24,294 Paddy 1,168 1,226 462 2,856 Sorghum & Millet 4,424 3,877 1,297 9,598 Beans & Pulses 959 3,283 1,851 6,092 Wheat 85 0 0 85 Cottton 0 0 79 79 Groundnuts/B ambara Nuts 1,129 2,106 1,413 4,648 Total 14,188 22,156 11,308 47,652 Maize 1,481 964 85 2,530 Paddy 0 85 0 85 Sorghum & Millet 3,893 4,273 793 8,959 Beans & Pulses 43 33 75 151 Cashewnut 42 0 0 42 Groundnuts/B ambara Nuts 0 0 42 42 Total 5,458 5,355 995 11,809 Maize 40,417 53,356 21,588 115,361 Paddy 1,433 1,679 1,782 4,894 Sorghum & Millet 38,125 43,041 15,207 96,374 Beans & Pulses 4,328 8,329 3,109 15,765 Wheat 85 0 0 85 Cashewnut 167 0 0 167 Cottton 0 0 79 79 Groundnuts/B ambara Nuts 1,549 3,665 1,456 6,669 Total 86,104 110,070 43,221 239,395 Manyoni Singida Urban Total 9.2 CROP STORAGE: Number of Households that Stored Crops By Length of Storage and Crop Type Crop Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 196 In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotecte d Pile Other Total Iramba 36,688 255 0 15,885 0 0 284 53,113 Singida Rural 50,339 498 123 18,019 123 0 245 69,347 Manyoni 14,642 81 170 14,959 0 85 326 30,263 Singida Urban 3,350 338 0 5,491 414 0 85 9,678 Total 105,019 1,172 293 54,354 537 85 940 162,401 Less than 3 Months Between 3 and 6 Months Over 6 Months Total Iramba 16,833 27,120 9,160 53,113 Singida Rural 30,076 28,738 10,534 69,347 Manyoni 9,602 13,883 6,778 30,263 Singida Urban 4,499 4,504 676 9,678 Total 61,009 74,245 27,147 162,401 Food for the Household To Sell for Higher Price Seeds for Planting Other Total Iramba 52,400 0 712 0 53,113 Singida Rural 67,264 122 1,962 0 69,347 Manyoni 29,144 337 782 0 30,263 Singida Urban 9,553 125 0 0 9,678 Total 158,362 583 3,456 0 162,401 Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Iramba 43,004 3,882 5,694 533 53,113 Singida Rural 59,629 7,027 2,199 492 69,347 Manyoni 28,109 1,425 479 250 30,263 Singida Urban 9,096 497 85 0 9,678 Total 139,838 12,830 8,457 1,275 162,401 9.3 CROP STORAGE: Number of Households Storing Crops By Method of Storage and District District Method of Storage 9.2 CROP STORAGE: Number of Households Storing 9.2 CROP STORAGE: Number of Households Storing Crops By District Estimate Storage Loss District Normal Duration of Storage 9.2 CROP STORAGE: Number of Households Storing Crops By Main District Main Purpose Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 197 MARKETING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 198 Number % Number % Number % Iramba 24,877 39.8 37,652 60.2 62,528 100.0 Singida Rural 36,760 50.2 36,437 49.8 73,197 100.0 Manyoni 17,251 52.2 15,814 47.8 33,065 100.0 Singida Urban 2,833 25.5 8,292 74.5 11,125 100.0 Total 81,720 45.4 98,195 54.6 179,915 100.0 Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Iramba 137 35,741 0 0 138 287 0 1,136 25,090 62,528 Singida Rural 855 40,008 250 124 125 123 125 372 30,492 72,472 Manyoni 82 17,467 0 0 0 0 0 150 14,875 32,575 Singida Urban 170 7,938 42 0 0 43 0 439 2,409 11,041 Total 1,243 101,154 292 124 263 452 125 2,097 72,866 178,616 District Price Too Low Production Insufficient to Sell Market Too Far Farmers Association Problems Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Iramba 0.22 57.16 0.00 0.00 0.22 0.46 0.00 1.82 40.13 100.00 Singida Rural 1.18 55.20 0.35 0.17 0.17 0.17 0.17 0.51 42.07 100.00 Manyoni 0.25 53.62 0.00 0.00 0.00 0.00 0.00 0.46 45.66 100.00 Singida Urban 1.54 71.90 0.38 0.00 0.00 0.39 0.00 3.97 21.82 100.00 Total 0.70 56.63 0.16 0.07 0.15 0.25 0.07 1.17 40.79 100.00 10.1 Number of Crop Producing Households Reporting Selling Agricultural Products During 2002/03 By District Households that Sold Households that Did not Sell Total Number of Households 10.3 Proportion of Household who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year District Main Reasons for Not Selling Crops 10.2: Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 199 IRRIGATION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 200 Total Number of Household % Number of Household % Number of Household Iramba 426 0.7 62,102 99.3 62,528 Singida Rural 1,338 1.8 71,859 98.2 73,197 Manyoni 3,682 11.1 29,383 88.9 33,065 Singida Urban 933 8.4 10,192 91.6 11,125 Total 6,380 3.5 173,536 96.5 179,915 District Irrigated Area (ha) Irrigated Land (ha) % Iramba 230 46 20 Singida Rural 942 520 55 Manyoni 2,244 1,285 57 Singida Urban 167 167 100 Total 3,583 2,017 56 River Dam Well Canal Total Iramba 141 143 143 0 426 Singida Rural 0 370 720 249 1,338 Manyoni 76 0 322 3,283 3,682 Singida Urban 43 42 680 169 933 Total 259 555 1,865 3,701 6,380 % 4 9 29 58 100 Gravity Hand Bucket Motor Pump Total Iramba 0 283 143 426 Singida Rural 491 847 0 1,338 Manyoni 3,359 322 0 3,682 Singida Urban 127 806 0 933 Total 3,977 2,259 143 6,380 % 62 35 2 100 Flood Bucket / Watering Can Total Iramba 0 426 426 Singida Rural 1,091 247 1,338 Manyoni 3,359 322 3,682 Singida Urban 85 849 933 Total 4,534 1,845 6,380 % 71 29 100 District Households Practicing Irrigation Households not Practicing Irrigation 11.1.Number and Percent of Crop Growing Households Reporting of Practicing Irrigation During 2002/03 Agriculture Year By District 11.3: IRRIGATION: Number of Households Using Irrigation By Source of Irrigation Water During 2003/04 Agricultural Year By District District Source of Irrigation Water 11.2 IRRIGATION: Area of Irrigated and Non Irrigatable (ha) Land By District 11.4: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation of Obtaining Water By District District Method of Obtaining Water District Method of Application 11.5: IRRIGATION: Number of Households Using Irrigation By Method of Irrigation Application By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 201 Total Number % Number % Number Iramba 6,294 10 56,234 90 62,528 Singida Rural 8,080 11 65,117 89 73,197 Manyoni 488 1 32,577 99 33,065 Singida Urban 667 6 10,458 94 11,125 Total 15,529 9 164,386 91 179,915 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Iramba 0 53,203 0 3,088 21,226 3,857 562 0 81,937 Singida Rural 8,497 46,270 . 862 736 26,956 3,685 . 87,004 Manyoni 792 7,898 . . . 820 . . 9,510 Singida Urban . 4,904 . . . 406 254 . 5,564 Total 9,289 112,275 0 3,950 21,962 32,039 4,500 0 184,015 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District District Type of Erosion Control 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District District Have facility Does Not Have Facility Does the Household Have Any Erosion Control/Water Tanzania Agriculture Census Survey 2003 Singida Region 202 Appendix II 203 ACCESS TO FARM INPUTS/ IMPLEMENTS Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 204 Number % Number % Number % Iramba 287 0 62,242 100 62,528 100 Singida Rural 123 0 73,074 100 73,197 100 Manyoni 2,208 7 30,857 93 33,065 100 Singida Urban 41 0 11,125 100 11,167 100 Total 2,659 1 177,298 99 179,957 100 Number % Number % Number % Iramba 36,163 58 26,365 42 62,528 100 Singida Rural 34,198 47 39,124 53 73,322 100 Manyoni 6,641 20 26,424 80 33,065 100 Singida Urban 6,257 56 4,827 44 11,084 100 Total 83,259 46 96,740 54 179,999 100 Number % Number % Number % Iramba 2,845 5 59,683 95 62,528 100 Singida Rural 3,471 5 69,726 95 73,197 100 Manyoni 660 2 32,404 98 33,065 100 Singida Urban 810 7 10,316 93 11,125 100 Total 7,786 4 172,129 96 179,915 100 Number % Number % Number % Iramba 3,155 5 59,373 95 62,528 100 Singida Rural 958 1 72,239 99 73,197 100 Manyoni 2,372 7 30,693 93 33,065 100 Singida Urban 427 4 10,699 96 11,125 100 Total 6,912 4 173,003 96 179,915 100 Number % Number % Number % Iramba 0 0 62,528 100 62,528 100 Singida Rural 117 0 73,080 100 73,197 100 Manyoni 0 0 33,065 100 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 117 0 179,799 100 179,915 100 12.1.1 ACCESS TO INPUTS: Number of Agricultural Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 205 Number % Number % Number % Iramba 5,295 8 57,233 92 62,528 100 Singida Rural 8,740 12 64,332 88 73,072 100 Manyoni 10,901 33 22,164 67 33,065 100 Singida Urban 1,479 13 9,647 87 11,125 100 Total 26,415 15 153,375 85 179,790 100 Number % Number % Number % Number % Number % Iramba 0 0 287 0 0 0 62,242 100 62,528 100 Singida Rural 0 0 123 0 0 0 73,074 100 73,197 100 Manyoni 1,421 4 74 0 712 2 30,857 93 33,065 100 Singida Urban 0 0 0 0 41 0 11,125 100 11,167 100 Total 1,421 1 484 0 754 0 177,298 99 179,957 100 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households and Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Neighbour Not applicable Total 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural Households Using Improved Seeds Number of Agricultural Households NOT Using Improved Seeds Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 206 Number % Number % Number % Number % Number % Number % Iramba 704 1 144 0 133 0 0 0 0 0 577 1 Singida Rural 0 0 0 0 0 0 370 1 122 0 0 0 Manyoni 0 0 0 0 0 0 0 0 0 0 0 0 Singida Urban 0 0 0 0 0 0 0 0 0 0 0 0 Total 704 0 144 0 133 0 370 0 122 0 577 0 Number % Number % Number % Number % Number % Number % Iramba 1,438 2 20,457 33 12,423 20 287 0 26,365 42 62,528 100 Singida Rural 0 0 28,669 39 5,036 7 0 0 39,124 53 73,322 100 Manyoni 0 0 2,810 8 3,831 12 0 0 26,424 80 33,065 100 Singida Urban 0 0 4,642 42 1,615 15 0 0 4,827 44 11,084 100 Total 1,438 1 56,578 31 22,905 13 287 0 96,740 54 179,999 100 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Neighbour Other Not applicable Total District Co-operative Local Farmers Group Secondary Market Development Project Crop Buyers District cont…. ACCESS TO INPUTS: Number of Agricultural Households and Source of Farm Yard Manure by District, 2002/03 Agricultural Year Large Scale Farm Locally Produced by Household Local Market / Trade Store Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 207 Number % Number % Number % Number % Number % Iramba 133 0 0 0 0 0 144 0 2,425 4 Singida Rural 642 1 103 0 207 0 0 0 2,396 3 Manyoni 0 0 0 0 0 0 79 0 581 2 Singida Urban 0 0 0 0 0 0 43 0 767 7 Total 775 0 103 0 207 0 266 0 6,170 3 Number % Number % Number % Iramba 143 0 59,683 95 62,528 100 Singida Rural 122 0 69,726 95 73,197 100 Manyoni 0 0 32,404 98 33,065 100 Singida Urban 0 0 10,316 93 11,125 100 Total 265 0 172,129 96 179,915 100 Number % Number % Number % Number % Number % Iramba 0 0 124 0 1,498 2 143 0 0 0 Singida Rural 0 0 0 0 958 1 0 0 0 0 Manyoni 1,278 4 0 0 787 2 0 0 65 0 Singida Urban 0 0 0 0 427 4 0 0 0 0 Total 1,278 1 124 0 3,670 2 143 0 65 0 Number % Number % Number % Number % Number % Iramba 0 0 684 1 706 1 59,373 95 62,528 100 Singida Rural 0 0 0 0 0 0 72,239 99 73,197 100 Manyoni 82 0 160 0 0 0 30,693 93 33,065 100 Singida Urban 0 0 0 0 0 0 10,699 96 11,125 100 Total 82 0 844 0 706 0 173,003 96 179,915 100 Number % Number % Number % Iramba 0 0 62,528 100 62,528 100 Singida Rural 117 0 73,080 100 73,197 100 Manyoni 0 0 33,065 100 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 117 0 179,799 100 179,915 100 District Co-operative Local Farmers Group Local Market / Trade Store Large Scale Farm Locally Produced by Household Neighbour Not applicable Total District Neighbour Not applicable Total 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households and Source of COMPOST Manure by District, 2002/03 Agricultural Year 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District 2002/03 Agricultural Year 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households and Source of Herbicides by District, 2002/03 Agricultural Year Other Not applicable Total District Co-operative Local Farmers Group Development Project Crop Buyers Neighbour District Local Market / Trade Store District cont... ACCESS TO INPUTS: Number of Agricultural Households and Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year Secondary Market Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 208 Number % Number % Number % Number % Number % Number % Iramba 143 0 0 0 3,736 6 143 0 0 0 0 0 Singida Rural 0 0 0 0 4,593 6 125 0 125 0 0 0 Manyoni 798 2 0 0 5,397 16 0 0 477 1 419 1 Singida Urban 0 0 33 0 1,063 10 0 0 0 0 0 0 Total 941 1 33 0 14,790 8 268 0 602 0 419 0 Number % Number % Number % Number % Number % Number % Iramba 0 0 143 0 1,131 2 0 0 57,233 92 62,528 100 Singida Rural 248 0 2,178 3 1,471 2 0 0 64,332 88 73,072 100 Manyoni 0 0 83 0 3,561 11 165 0 22,164 67 33,065 100 Singida Urban 0 0 255 2 128 1 0 0 9,647 87 11,125 100 Total 248 0 2,658 1 6,291 3 165 0 153,375 85 179,790 100 Number % Number % Number % Number % Number % Number % Iramba 0 0 143 50 143 50 0 0 0 0 287 100 Singida Rural 0 0 0 0 0 0 123 100 0 0 123 100 Manyoni 1,899 86 82 4 0 0 145 7 82 4 2,208 100 Singida Urban 41 100 0 0 0 0 0 0 0 0 41 100 Total 1,940 73 225 8 143 5 268 10 82 3 2,659 100 Number % Number % Number % Number % Number % Iramba 31,603 87 4,292 12 124 0 144 0 36,163 100 Singida Rural 32,477 95 1,104 3 0 0 618 2 34,198 100 Manyoni 5,594 84 804 12 243 4 0 0 6,641 100 Singida Urban 6,090 97 167 3 0 0 0 0 6,257 100 Total 75,763 91 6,367 8 367 0 762 1 83,259 100 District 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year cont… ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Neighbour Other Not applicable Total District Co-operative District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Total 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Crop Buyers Large Scale Farm Locally Produced by Household Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 209 Number % Number % Number % Number % Iramba 2,559 90 287 10 0 0 2,845 100 Singida Rural 2,997 86 228 7 245 7 3,471 100 Manyoni 660 100 0 0 0 0 660 100 Singida Urban 810 100 0 0 0 0 810 100 Total 7,026 90 515 7 245 3 7,786 100 Number % Number % Number % Number % Number % Number % Iramba 1,360 43 371 12 1,143 36 139 4 143 5 3,155 100 Singida Rural 0 0 0 0 249 26 243 25 466 49 958 100 Manyoni 1,503 63 82 3 622 26 165 7 0 0 2,372 100 Singida Urban 0 0 0 0 384 90 43 10 0 0 427 100 Total 2,863 41 453 7 2,398 35 590 9 608 9 6,912 100 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Number % Iramba 2,098 40 562 11 1,857 35 265 5 514 10 5,295 100 Singida Rural 3,523 40 861 10 1,114 13 738 8 2,503 29 8,740 100 Manyoni 6,031 55 1,184 11 1,516 14 1,147 11 1,024 9 10,901 100 Singida Urban 425 29 0 0 553 37 415 28 85 6 1,479 100 Total 12,076 46 2,607 10 5,041 19 2,566 10 4,126 16 26,415 100 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 10 and 20 km Total 12.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Yea District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Herbicides by District, 2002/03 Agricultural Year District Between 1 and 3 km Total 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 210 Number % Number % Number % Number % Iramba 287 100 0 0 0 0 287 100 Singida Rural 123 100 0 0 0 0 123 100 Manyoni 630 29 623 28 955 43 2,208 100 Singida Urban 41 100 0 0 0 0 41 100 Total 1,081 41 623 23 955 36 2,659 100 Number % Number % Number % Number % Number % Number % Number % Iramba 23,815 66 4,247 12 1,820 5 289 1 1,577 4 4,415 12 36,163 100 Singida Rural 22,627 66 3,580 10 862 3 0 0 0 0 7,128 21 34,198 100 Manyoni 3,887 59 1,774 27 326 5 74 1 0 0 580 9 6,641 100 Singida Urban 3,931 63 1,142 18 210 3 0 0 0 0 975 16 6,257 100 Total 54,260 65 10,742 13 3,219 4 363 0 1,577 2 13,099 16 83,259 100 Number % Number % Number % Number % Iramba 2,416 85 287 10 143 5 2,845 100 Singida Rural 2,500 72 476 14 495 14 3,471 100 Manyoni 497 75 85 13 78 12 660 100 Singida Urban 429 53 127 16 254 31 810 100 Total 5,842 75 975 13 969 12 7,786 100 Number % Number % Number % Number % Number % Iramba 1,788 57 943 30 143 5 282 9 3,155 100 Singida Rural 958 100 0 0 0 0 0 0 958 100 Manyoni 797 34 542 23 158 7 874 37 2,372 100 Singida Urban 384 90 43 10 0 0 0 0 427 100 Total 3,927 57 1,528 22 301 4 1,156 17 6,912 100 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Pesticides/Fungicides by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying COMPOST Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Other Total 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Farm Yard Manure by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Bank Loan Produced on form Other Total 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Chemical Fertilizer by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 211 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Iramba 3,754 71 1,541 29 0 0 0 0 5,295 100 Singida Rural 5,239 60 2,433 28 703 8 365 4 8,740 100 Manyoni 2,665 24 7,262 67 414 4 560 5 10,901 100 Singida Urban 546 37 763 52 42 3 127 9 1,479 100 Total 12,204 46 11,999 45 1,160 4 1,052 4 26,415 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 19,319 31 33,214 53 1,738 3 0 0 1,269 2 5,997 10 705 1 62,242 100 Singida Rural 25,679 35 28,673 39 730 1 0 0 4,176 6 12,964 18 852 1 73,074 100 Manyoni 16,193 52 12,025 39 254 1 83 0 798 3 1,420 5 85 0 30,857 100 Singida Urban 1,856 17 6,210 56 296 3 0 0 550 5 2,171 20 42 0 11,125 100 Total 63,046 36 80,121 45 3,019 2 83 0 6,794 4 22,551 13 1,685 1 177,298 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 7,261 28 6,375 24 3,133 12 1,285 5 1,031 4 5,715 22 1,564 6 26,365 100 Singida Rural 18,314 47 6,389 16 6,984 18 2,158 6 248 1 2,951 8 2,080 5 39,124 100 Manyoni 10,264 39 1,324 5 10,451 40 2,349 9 819 3 918 3 300 1 26,424 100 Singida Urban 3,769 78 486 10 286 6 0 0 41 1 117 2 127 3 4,827 100 Total 39,608 41 14,574 15 20,854 22 5,792 6 2,140 2 9,701 10 4,071 4 96,740 100 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Source of Finance for buying Herbicides by District, 2002/03 Agricultural Year District Sale of Farm Products Total 12.1.24 ACCESS TO INPUTS: Number of Agricultural households and Source of Finance for buying Improved Seeds by District, 2002/03 Agricultural Year District Sale of Farm Products Other Income generating activities Remittances Other Total 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 212 Number % Number % Number % Number % Number % Number % Number % Number % Number % Iramba 9,052 15 8,443 14 12,785 21 3,998 7 17,711 30 6,707 11 136 0 851 1 59,683 100 Singida Rural 7,594 11 8,041 12 25,178 36 3,224 5 19,576 28 4,907 7 115 0 1,090 2 69,726 100 Manyoni 728 2 919 3 12,020 37 1,043 3 15,438 48 1,156 4 932 3 170 1 32,404 100 Singida Urban 2,720 26 991 10 3,169 31 127 1 2,122 21 686 7 0 0 500 5 10,316 100 Total 20,094 12 18,394 11 53,152 31 8,392 5 54,847 32 13,456 8 1,183 1 2,611 2 172,129 100 Number % Number % Number % Number % Number % Number % Number % Number % Number % Iramba 6,239 11 44,350 75 566 1 415 1 1,846 3 5,394 9 141 0 421 1 59,373 100 Singida Rural 13,391 19 39,415 55 728 1 123 0 12,172 17 5,687 8 0 0 722 1 72,239 100 Manyoni 9,365 31 16,748 55 415 1 165 1 3,440 11 474 2 0 0 85 0 30,693 100 Singida Urban 254 2 7,310 68 254 2 42 0 548 5 2,162 20 0 0 127 1 10,699 100 Total 29,250 17 107,824 62 1,964 1 746 0 18,007 10 13,717 8 141 0 1,355 1 173,003 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 11,470 18 36,390 58 1,232 2 143 0 2,270 4 10,881 17 143 0 62,528 100 Singida Rural 15,239 21 30,457 42 619 1 372 1 13,284 18 12,387 17 722 1 73,080 100 Manyoni 11,766 36 12,440 38 415 1 165 0 6,763 20 1,430 4 85 0 33,065 100 Singida Urban 338 3 5,474 49 424 4 42 0 486 4 4,192 38 170 2 11,125 100 Total 38,814 22 84,762 47 2,689 1 722 0 22,804 13 28,889 16 1,119 1 179,799 100 Number % Number % Number % Number % Number % Number % Number % Number % Iramba 2,487 4 51,275 90 691 1 276 0 1,520 3 143 0 841 1 57,233 100 Singida Rural 17,733 28 43,047 67 614 1 990 2 985 2 240 0 722 1 64,332 100 Manyoni 5,304 24 15,708 71 167 1 570 3 164 1 82 0 168 1 22,164 100 Singida Urban 762 8 8,248 86 169 2 85 1 127 1 0 0 255 3 9,647 100 Total 26,287 17 118,278 77 1,641 1 1,921 1 2,797 2 465 0 1,987 1 153,375 100 Other Total Other Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Do not Know How to Use Other Input is of No Use Locally Produced by Household Other 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Total Do not Know How to Use Input is of No Use Input is of No Use Locally Produced by Household 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Total Locally Produced by Household Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 213 Number % Number % Number % Number % Iramba 143 50 143 50 0 0 287 100 Singida Rural 123 100 0 0 0 0 123 100 Manyoni 317 14 1,572 71 319 14 2,208 100 Singida Urban 0 0 41 100 0 0 41 100 Total 584 22 1,756 66 319 12 2,659 100 Number % Number % Number % Number % Number % Iramba 11,722 32 23,063 64 1,377 4 0 0 36,163 100 Singida Rural 19,497 57 13,884 41 817 2 0 0 34,198 100 Manyoni 2,697 41 3,777 57 84 1 83 1 6,641 100 Singida Urban 2,090 33 3,702 59 466 7 0 0 6,257 100 Total 36,006 43 44,426 53 2,744 3 83 0 83,259 100 Number % Number % Number % Number % Iramba 855 30 1,848 65 143 5 2,845 100 Singida Rural 1,672 48 1,678 48 121 3 3,471 100 Manyoni 0 0 236 36 424 64 660 100 Singida Urban 42 5 533 66 235 29 810 100 Total 2,569 33 4,295 55 923 12 7,786 100 Number % Number % Number % Number % Number % Iramba 571 18 1,909 61 390 12 285 9 3,155 100 Singida Rural 351 37 358 37 0 0 249 26 958 100 Manyoni 648 27 1,580 67 144 6 0 0 2,372 100 Singida Urban 117 27 277 65 33 8 0 0 427 100 Total 1,687 24 4,124 60 567 8 534 8 6,912 100 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Excellent Good Average Total 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 214 Number % Number % Singida Rural 117 100 117 100 Total 117 100 117 100 Number % Number % Number % Number % Number % Iramba 713 13 4,191 79 392 7 0 0 5,295 100 Singida Rural 3,841 44 4,419 51 480 5 0 0 8,740 100 Manyoni 2,829 26 7,492 69 496 5 84 1 10,901 100 Singida Urban 532 36 787 53 160 11 0 0 1,479 100 Total 7,914 30 16,889 64 1,528 6 84 0 26,415 100 Number % Number % Number % Iramba 1,961 3 60,567 97 62,528 100 Singida Rural 2,568 4 70,629 96 73,197 100 Manyoni 2,551 8 30,514 92 33,065 100 Singida Urban 0 0 11,167 100 11,167 100 Total 7,080 4 172,877 96 179,957 100 Number % Number % Number % Iramba 41,568 66 20,961 34 62,528 100 Singida Rural 49,814 68 23,507 32 73,322 100 Manyoni 14,922 45 18,143 55 33,065 100 Singida Urban 7,096 64 3,988 36 11,084 100 Total 113,400 63 66,599 37 179,999 100 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Farm Yard Manure Number of Agricultural Households With NO Plan to use Next Year Farm Yard Manure Total 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Chemical Fertilizers Number of Agricultural Households With NO Plan to use Next Year Chemica Fertilizers Total 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Good Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 215 Number % Number % Number % Iramba 5,406 9 57,123 91 62,528 100 Singida Rural 12,973 18 60,224 82 73,197 100 Manyoni 4,156 13 28,909 87 33,065 100 Singida Urban 961 9 10,165 91 11,125 100 Total 23,495 13 156,421 87 179,915 100 Number % Number % Number % Iramba 11,331 18 51,197 82 62,528 100 Singida Rural 16,046 22 57,151 78 73,197 100 Manyoni 7,329 22 25,736 78 33,065 100 Singida Urban 554 5 10,572 95 11,125 100 Total 35,260 20 144,655 80 179,915 100 Number % Number % Number % Iramba 2,248 4 60,280 96 62,528 100 Singida Rural 1,596 2 71,601 98 73,197 100 Manyoni 322 1 32,742 99 33,065 100 Singida Urban 0 0 11,125 100 11,125 100 Total 4,166 2 175,749 98 179,915 100 Number % Number % Number % Iramba 17,805 28 44,723 72 62,528 100 Singida Rural 30,914 42 42,158 58 73,072 100 Manyoni 16,732 51 16,333 49 33,065 100 Singida Urban 2,605 23 8,520 77 11,125 100 Total 68,057 38 111,734 62 179,790 100 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year COMPOST Manure Number of Agricultural Households With NO Plan to use Next Year COMPOST Manure Total 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Pesticides/Fungicides Number of Agricultural Households With NO Plan to use Next Year Pesticides/Fungicides Total 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Herbicides Number of Agricultural Households With NO Plan to use Next Year Herbicides Total 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Number of Agricultural Households With Plan to use Next Year Improved Seeds Number of Agricultural Households With NO Plan to use Next Year Improved Seeds Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 216 Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Number Owned Number Rented Iramba 203,512 4,441 3,961 1,950 103,723 109,170 27,669 29,955 423 141 Singida Rural 237,999 1,107 935 1,221 79,536 36,492 23,670 11,415 123 0 Manyoni 110,816 499 5,302 242 17,955 4,744 5,180 1,704 0 84 Singida Urban 35,192 333 308 33 2,648 1,031 1,047 581 0 0 Total 587,519 6,380 10,506 3,445 203,863 151,437 57,565 43,654 546 225 Owned Rented Owned Rented Owned Rented Owned Rented Owned Rented Owned Rented Iramba 4,906 3,745 138 412 0 829 0 0 0 0 344,332 150,643 Singida Rural 3,498 2,647 0 0 0 0 245 0 0 0 346,007 52,882 Manyoni 905 85 0 0 0 0 0 85 0 79 140,158 7,522 Singida Urban 338 338 0 0 0 0 0 0 0 0 39,533 2,316 Total 9,647 6,815 138 412 0 829 245 85 0 79 870,029 213,363 Hand Hoe Hand Powered Sprayer Oxen Ox Plough Ox Seed Planter Ox Cart Tractor Tractor Plough Tractor Harrow Threshers / Shellers Iramba 61,826 2,303 52,565 48,948 421 7,703 406 545 0 0 Singida Rural 72,712 1,677 33,048 31,468 123 6,023 0 0 123 0 Manyoni 33,065 2,158 4,154 4,070 84 823 0 0 85 79 Singida Urban 11,125 341 1,173 1,331 0 371 0 0 0 0 Total 178,728 6,479 90,940 85,816 628 14,919 406 545 208 79 Total District Hand Hoe Hand Powered Sprayer Oxen 12.2.1 ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Implement / Asset Name cont…. ACCESS TO EQUIPMENT: Number of Equipment/Assets Owned/ Rented by the Household During 2002/03 Implement / Asset Name Ox Plough Ox Seed Planter 12.2.2 ACCESS TO EQUIPMENT: Number of Agricultural Households that used Farm Implements/Assets in 2002/03 by District, 2002/03 District Implement / Asset Name Tractor Plough Tractor Harrow Threshers / Shellers District Ox Cart Tractor Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 217 Number % Number % Number % Number % Number % Iramba 137 19 0 0 565 81 0 0 702 100 Singida Rural 0 0 240 66 0 0 123 34 363 100 Total 137 13 240 23 565 53 123 12 1,065 100 Number % Number % Number % Number % Number % Number % Number % Iramba 3,195 5 26,951 45 22,333 37 143 0 6,747 11 857 1 60,225 100 Singida Rural 18,796 26 33,870 47 11,584 16 0 0 7,144 10 125 0 71,519 100 Manyoni 5,910 19 17,205 56 7,306 24 0 0 486 2 0 0 30,907 100 Singida Urban 1,357 13 3,696 34 2,364 22 0 0 3,368 31 0 0 10,785 100 Total 29,258 17 81,722 47 43,587 25 143 0 17,744 10 982 1 173,436 100 Number % Number % Number % Number % Number % Number % Number % Iramba 137 1 3,375 34 6,311 63 0 0 0 0 141 1 9,964 100 Singida Rural 1,345 3 12,571 31 25,372 63 124 0 247 1 489 1 40,148 100 Manyoni 954 3 5,394 19 22,349 77 139 0 0 0 74 0 28,911 100 Singida Urban 212 2 2,701 27 6,678 67 118 1 159 2 43 0 9,910 100 Total 2,648 3 24,041 27 60,711 68 381 0 406 0 747 1 88,933 100 Number % Number % Number % Number % Number % Number % Number % Iramba 428 3 4,158 31 7,595 56 133 1 1,124 8 143 1 13,581 100 Singida Rural 980 2 16,610 40 23,645 57 0 0 247 1 246 1 41,729 100 Manyoni 415 1 5,513 19 22,204 77 502 2 288 1 74 0 28,995 100 Singida Urban 329 3 2,324 24 6,813 70 43 0 244 2 43 0 9,794 100 Total 2,151 2 28,605 30 60,257 64 678 1 1,903 2 506 1 94,099 100 12.2.3 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Hoe by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Equipment / Asset of No Use Total 12.2.4 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using Hand Powered Sprayer by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.5 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OXEN by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.6 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX Plough by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 218 Number % Number % Number % Number % Number % Number % Number % Iramba 9,715 16 24,990 40 18,698 30 143 0 7,852 13 709 1 62,108 100 Singida Rural 25,626 35 27,702 38 12,886 18 0 0 6,364 9 496 1 73,074 100 Manyoni 3,489 11 12,911 39 16,154 49 0 0 428 1 0 0 32,981 100 Singida Urban 594 5 2,721 24 3,816 34 0 0 3,909 35 85 1 11,125 100 Total 39,423 22 68,324 38 51,554 29 143 0 18,553 10 1,290 1 179,287 100 Number % Number % Number % Number % Number % Number % Number % Iramba 573 1 21,184 39 28,529 52 143 0 4,111 7 286 1 54,825 100 Singida Rural 3,442 5 32,671 49 29,096 43 123 0 1,596 2 246 0 67,174 100 Manyoni 905 3 10,990 34 19,771 61 139 0 437 1 0 0 32,242 100 Singida Urban 211 2 3,662 34 5,128 48 0 0 1,583 15 170 2 10,754 100 Total 5,131 3 68,507 42 82,524 50 405 0 7,727 5 702 0 164,996 100 Number % Number % Number % Number % Number % Number % Number % Iramba 812 1 27,141 44 31,631 51 284 0 2,256 4 0 0 62,123 100 Singida Rural 9,849 13 44,463 61 12,033 16 0 0 6,852 9 0 0 73,197 100 Manyoni 1,130 3 22,317 67 9,321 28 0 0 297 1 0 0 33,065 100 Singida Urban 1,635 15 4,115 37 2,406 22 0 0 2,928 26 43 0 11,125 100 Total 13,425 7 98,035 55 55,391 31 284 0 12,333 7 43 0 179,510 100 Number % Number % Number % Number % Number % Number % Number % Iramba 953 2 26,973 44 31,374 51 143 0 2,541 4 0 0 61,983 100 Singida Rural 9,971 14 44,222 60 12,278 17 0 0 6,726 9 0 0 73,197 100 Manyoni 1,284 4 23,365 71 7,403 22 0 0 1,013 3 0 0 33,065 100 Singida Urban 1,593 14 4,196 38 2,407 22 0 0 2,886 26 43 0 11,125 100 Total 13,801 8 98,756 55 53,462 30 143 0 13,165 7 43 0 179,370 100 12.2.10 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR PLOUGH by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.9 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.8 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX CART by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.7 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using OX SEED PLANTER by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 219 Number % Number % Number % Number % Number % Number % Number % Iramba 4,796 8 26,299 42 23,350 37 143 0 7,940 13 0 0 62,528 100 Singida Rural 10,212 14 43,838 60 11,797 16 0 0 7,232 10 118 0 73,197 100 Manyoni 1,363 4 23,054 70 7,465 23 159 0 938 3 0 0 32,980 100 Singida Urban 1,592 14 4,112 37 2,407 22 0 0 2,971 27 43 0 11,125 100 Total 17,964 10 97,303 54 45,019 25 302 0 19,082 11 160 0 179,830 100 Number % Number % Number % Number % Number % Number % Number % Iramba 8,867 14 24,883 40 17,048 27 143 0 11,444 18 143 0 62,528 100 Singida Rural 11,677 16 40,756 56 10,557 14 0 0 10,082 14 125 0 73,197 100 Manyoni 1,299 4 23,619 72 7,287 22 223 1 479 1 79 0 32,986 100 Singida Urban 380 3 2,973 27 2,084 19 0 0 5,604 50 85 1 11,125 100 Total 22,223 12 92,231 51 36,976 21 366 0 27,609 15 432 0 179,836 100 Number % Number % Number % Number % Number % Number % Number % Iramba 38,166 62 11,954 19 3,488 6 0 0 143 0 7,644 12 61,395 100 Singida Rural 47,163 65 21,689 30 1,920 3 118 0 122 0 1,452 2 72,464 100 Manyoni 12,287 37 19,544 59 920 3 80 0 85 0 149 0 33,065 100 Singida Urban 4,561 41 5,105 46 328 3 42 0 0 0 1,089 10 11,125 100 Total 102,177 57 58,292 33 6,656 4 240 0 350 0 10,334 6 178,049 100 Number % Number % Number % Number % Iramba 932 76 143 12 144 12 1,219 100 Singida Rural 709 85 123 15 0 0 832 100 Manyoni 989 52 926 48 0 0 1,916 100 Singida Urban 182 59 83 27 43 14 308 100 Total 2,812 66 1,276 30 187 4 4,275 100 12.2.11 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using TRACTOR HARROW by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.12 ACCESS TO EQUIPMENT: Number of Agricultural Households NOT using THRESHERS/SHELLERS by Main Reason for NOT using and District District Not Available Price Too High No Money to Buy / Rent Too Much Labour Required Equipment / Asset of No Use Other Total 12.2.13 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Hoes by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Remittances Bank Loan Credit Other Total 12.2.14 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning Hand Powered Sprayer by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 220 Number % Number % Number % Number % Number % Number % Iramba 16,998 64 3,674 14 1,422 5 0 0 4,492 17 26,586 100 Singida Rural 16,704 74 4,760 21 246 1 125 1 741 3 22,576 100 Manyoni 2,232 85 387 15 0 0 0 0 0 0 2,619 100 Singida Urban 666 76 126 14 0 0 0 0 84 10 876 100 Total 36,599 70 8,947 17 1,668 3 125 0 5,317 10 52,656 100 Number % Number % Number % Number % Number % Number % Iramba 15,078 64 4,394 19 850 4 0 0 3,205 14 23,527 100 Singida Rural 15,489 75 4,546 22 245 1 249 1 0 0 20,530 100 Manyoni 1,403 54 1,133 43 83 3 0 0 0 0 2,619 100 Singida Urban 455 61 168 22 0 0 0 0 126 17 750 100 Total 32,425 68 10,242 22 1,178 2 249 1 3,331 7 47,426 100 Number % Number % Number % Number % Iramba 0 0 137 49 143 51 280 100 Singida Rural 123 100 0 0 0 0 123 100 Total 123 31 137 34 143 35 403 100 12.2.17 ACCESS TO EQUIPMENT: Number of Agricultural Households District Sale of Farm Products Ot e co e Generating Activities Other Total 12.2.16 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX Plough by Source of Finance and District District Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total 12.2.15 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OXEN by Source of Finance and District District Sale of Farm Products Other Income Generating Remittances Bank Loan Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 221 Number % Number % Number % Number % Number % Iramba 3,336 71 844 18 0 0 497 11 4,677 100 Singida Rural 2,451 73 821 24 103 3 0 0 3,375 100 Manyoni 489 66 249 34 0 0 0 0 738 100 Singida Urban 212 72 42 14 0 0 42 14 296 100 Total 6,488 71 1,955 22 103 1 539 6 9,086 100 Number % Number % Iramba 138 100 138 100 Total 138 100 138 100 Number % Number % Singida Rural 123 100 123 100 Total 123 100 123 100 12.2.18 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning OX CART by Source of Finance and District District Sale of Farm Products Other Income Generating Activities Remittances Other Total 12.2.19 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR by Source of Finance and District District Sale of Farm Total 12.2.21 ACCESS TO EQUIPMENT: Number of Agricultural Households Owning TRACTOR HARROW by Source of Finance and District District Other Income Generating Activities Total Tanzania Agriculture Census Survey 2003 Singida Region 222 Appendix II 223 AGRICULTURE CREDIT Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 224 Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Other Total Credits Iramba 124 0 0 0 0 852 976 Singida Rural 246 0 0 0 0 0 246 Manyoni 76 76 1,117 883 74 646 2,872 Singida Urban 0 0 0 0 0 42 42 Total Credits 445 76 1,117 883 74 1,540 4,136 Number % Number % Number % Iramba 548 56 428 44 976 100 Singida Rural 246 100 0 0 246 100 Manyoni 723 50.4 712 49.6 1,435 100 Singida Urban 0 0 42 100 42 100 Total 1,516 56 1,182 44 2,698 100 Family, Friend and Relative Commercial Bank Co-operative Saving & Credit Society Private Individual Religious Organisation / NGO / Project Total Iramba 837 0 0 139 0 0 976 Singida Rural 0 122 0 0 123 0 246 Manyoni 74 0 1,124 76 0 161 1,435 Singida Urban 0 0 0 0 0 42 42 Total 911 122 1,124 215 123 203 2,698 Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit granted too late Other Don't know about credit Total Iramba 4,030 4,691 8,359 1,133 30,553 1,391 136 560 10,699 61,553 Singida Rural 2,318 11,084 8,061 853 27,783 490 250 242 21,871 72,951 Manyoni 985 6,352 3,700 564 12,180 327 251 65 7,207 31,630 Singida Urban 799 1,172 1,239 234 3,889 107 42 42 3,559 11,083 Total 8,133 23,298 21,358 2,784 74,405 2,315 679 909 43,336 177,217 District Male Female Total District Reason for Not Using Credit 13.1a AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District District Credit Use 13c AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District District Source of Credit 13d AGRICULTURE CREDIT: Number of Households Receiving Credit By Reason for Not Using Credit By District 13b AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 225 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 226 Number % Number % Number % Iramba 4,606 7 57,922 93 62,528 100 Singida Rural 4,902 7 68,295 93 73,197 100 Manyoni 1,252 4 31,813 96 33,065 100 Singida Urban 792 7 10,333 93 11,125 100 Total 11,552 6 168,364 94 179,915 100 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Iramba 2,804 23,500 1,530 28,374 273 2,591 4,606 54,465 Singida Rural 3,315 30,500 988 36,724 598 25,993 4,902 93,217 Manyoni 490 5,432 762 10,871 0 . 1,252 16,302 Singida Urban 454 17,103 126 631 212 4,677 792 22,410 Total 7,063 76,535 3,406 76,598 1,083 33,261 11,552 186,395 61.1 41.1 29.5 41.1 9.4 17.8 District Senna Spp Gravellis Acacia Spp Eucalyptus Spp Cyprus Spp Calophylum Inophyllum Leucena Spp Syszygium Spp Azadritacht a Spp Jakaranda Spp Kyaya Spp Moringa Spp Total Iramba 22,284 15,740 . 5,508 . . 8,149 1,134 1,507 143 . . 54,465 Singida Rural 3,315 23,396 613 53,783 1,850 243 749 2,824 4,743 . 974 728 93,217 Manyoni 4,474 930 . . 78 . . 255 2,402 . . 8,163 16,302 Singida Urban 610 5,470 . 15,363 . . . 883 . . . 85 22,410 Total 30,683 45,536 613 74,654 1,927 243 8,898 5,097 8,652 143 974 8,976 186,395 14.1 ON FARM TREE FARMING: Number of Households Having Planted Trees By District District Did your Hh have any Planted Trees on your land during 2002/ Households Having Planted Households Not Having Total 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and and Number of Trees by Planting Location and District District Where Planted Mostly on Field / Plot Mostly Scattered in Field Mostly in Plantation / Total 14 ON FARM TREE PLANTING: Number of Planted Trees By Species and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 227 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Iramba 1,422 832 1,345 1,277 143 1,836 6,856 Singida Rural 3,183 1,079 1,108 615 622 245 6,852 Manyoni 81 0 0 1,410 85 0 1,576 Singida Urban 530 170 125 210 0 42 1,078 Total 5,215 2,081 2,578 3,512 850 2,124 16,361 31.9 12.7 15.8 21.5 5.2 13.0 100.0 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Iramba 681 423 139 1,691 2,784 286 852 6,856 Singida Rural 1,238 608 0 3,775 863 368 0 6,852 Manyoni 85 85 0 0 165 754 487 1,576 Singida Urban 0 328 0 497 169 42 41 1,078 Total 2,004 1,444 139 5,963 3,981 1,450 1,380 16,361 Number % Number % Number % Iramba 30,810 49 31,718 51 62,528 100 Singida Rural 6,188 9 65,402 91 71,590 100 Manyoni 3,785 11 29,280 89 33,065 100 Singida Urban 4,363 39 6,762 61 11,125 100 Total 45,146 25 133,162 75 178,308 100 14 TREE FARMING: Main Use of Trees By District District Main Use 14 TREE FARMING: Second Use of Trees By District District Second Use 14.3 TREE FARMING: Number of Households By Whether Village Have a Community Tree Planting Scheme By District District does your village have a Community Tree Planting Scheme Have a Community Tree Does not Have a Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 228 0-9 1-19 05-29 30-39 40-49 60+ Total Iramba 5,908 6,439 5,958 4,515 2,852 5,138 30,810 Singida Rural 3,682 608 364 1,181 354 0 6,188 Manyoni 3,720 0 65 0 0 0 3,785 Singida Urban 1,440 1,493 301 831 127 170 4,363 Total 14,751 8,541 6,687 6,527 3,333 5,307 45,146 Poles Timber Logs Charcoal Firewood Not Ready to Use Not Allowed to Use Other Total Iramba 2,512 1,422 0 5,191 14,153 7,532 0 30,810 Singida Rural 2,222 2,851 0 235 123 0 1,768 7,198 Manyoni 0 84 505 505 2,610 80 0 3,785 Singida Urban 2,458 1,014 85 764 43 0 0 4,363 Total 7,191 5,371 590 6,695 16,929 7,612 1,768 46,157 District Main use during 2002/03 14.4 TREE FARMING: Number of Households By Distance to Community Planted Forest (Km) By District District Distance to Community Planted Forest (km) 14.5 TREE FARMING: Number of Households Involved in Community Tree Planting Scheme By Main Use and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 229 CROP EXTENSION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 230 Total Number % Number % Number Iramba 44,677 71.5 17,851 29 62,528 Singida Rural 26,948 36.8 46,249 63 73,197 Manyoni 10,970 33.2 22,095 67 33,065 Singida Urban 4,107 36.9 7,019 63 11,125 Total 86,702 48 93,214 52 179,915 Total Number % Number % Number % Number % Number % Number Iramba 4,865 10.9 31,473 70.7 6,357 14.3 1,277 2.9 562 1.3 44,534 Singida Rural 2,203 8.2 20,347 75.5 3,296 12.2 977 3.6 125 0.5 26,948 Manyoni 1,908 17.4 8,067 73.5 757 6.9 0 0.0 238 2.2 10,970 Singida Urban 372 9.1 2,878 70.1 856 20.8 0 0.0 0 0.0 4,107 Total 9,349 10.8 62,764 72.5 11,267 13.0 2,254 2.6 925 1.1 86,558 Total Number % Number % Number % Number % Number % Number Iramba 44,395 99.7 0 0.0 0 0.0 0 0.0 139 0.3 44,534 Singida Rural 24,980 94.0 368 1.4 250 0.9 855 3.2 125 0.5 26,576 Manyoni 10,452 95.8 453 4.2 0 0.0 0 0.0 0 0.0 10,905 Singida Urban 3,939 96.9 43 1.0 0 0.0 0 0.0 84 2.1 4,065 Total 83,765 97.3 863 1.0 250 0.3 855 1.0 348 0.4 86,081 15.3 EXTENSION MESSAGES: Number of Households By Source of Extension Messages By District District Government NGO / Development Cooperative Large Scale Farm Other Source of Crop Extension 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services By District District Very Good Good Average Poor No Good Quality of service Households Receiving Extension Advice Households Not Receiving Extension Advice 15.1 CROP EXTENSION" Number of Households Receiving Extension Messages By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 231 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Total Iramba 43,442 0 0 0 139 43,581 62,528 70 Singida Rural 23,521 368 250 855 0 24,993 73,197 34 Manyoni 9,951 453 0 0 0 10,404 33,065 31 Singida Urban 3,602 43 0 0 42 3,687 11,125 33 Total 80,516 863 250 855 181 82,665 179,915 46 Governme nt NGO / Development Project Cooperative Other Not applicable Total Iramba 25,744 0 0 281 424 26,449 62,528 42 Singida Rural 8,746 240 0 0 373 9,358 73,197 13 Manyoni 6,425 398 146 0 0 6,969 33,065 21 Singida Urban 1,862 0 0 117 42 2,021 11,125 18 Total 42,776 638 146 398 839 44,797 179,915 25 Governme nt NGO / Development Project Large Scale Farm Other Not applicable Total Iramba 29,272 0 0 139 0 29,411 62,528 47 Singida Rural 11,012 607 0 0 248 11,867 73,197 16 Manyoni 2,228 340 81 0 0 2,648 33,065 8 Singida Urban 2,220 43 0 0 0 2,263 11,125 20 Total 44,732 990 81 139 248 46,189 179,915 26 15.4 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Plant Spacing By Source of Messages By District District Spacing 15.6 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Erosion Control By Source of Messages By District Erosion Control Total Number of Households District % of total number of households Total Number of Households % of total number of households 15.5 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agrochemicals By Source of Messages By District % of total number of households Use of Agrochemicals Total Number of Households District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 232 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 40,414 0 0 0 139 0 40,553 62,528 65 Singida Rural 20,103 345 245 975 125 120 21,912 73,197 30 Manyoni 9,144 65 0 0 0 0 9,210 33,065 28 Singida Urban 3,474 43 0 0 169 0 3,686 11,125 33 Total 73,137 453 245 975 432 120 75,361 179,915 42 Governme nt NGO / Development Project Cooperative Not applicable Total Iramba 13,022 0 140 268 13,430 62,528 21 Singida Rural 1,480 121 0 250 1,851 73,197 3 Manyoni 4,027 889 161 0 5,078 33,065 15 Singida Urban 744 0 0 0 744 11,125 7 Total 19,273 1,011 302 518 21,104 179,915 12 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 35,152 136 0 0 139 696 36,124 62,528 58 Singida Rural 13,651 361 240 1,950 0 623 16,825 73,197 23 Manyoni 8,709 471 81 0 84 0 9,344 33,065 28 Singida Urban 3,021 85 0 0 75 85 3,266 11,125 29 Total 60,534 1,053 321 1,950 298 1,404 65,559 179,915 36 District District Total Number of Household s 15.7 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Organic Fertiliser Use By Source of Messages By District % of total number of households Total Number of Households 15.8 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Inorganic Fertiliser Use By Source of Messages By District 15.9 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Use of Improved Seed By Source of Messages By District % of total number of households Organic Fertilizer Use District % of total number of households Total Number of Households Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 233 Governme nt NGO / Development Project Not applicable Total Iramba 11,420 144 133 11,697 Singida Rural 245 245 370 860 Manyoni 2,187 163 0 2,350 Singida Urban 425 43 0 468 Total 14,277 594 504 15,375 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 9,841 859 0 0 0 267 10,966 62,528 18 Singida Rural 3,932 225 120 360 0 0 4,637 73,197 6 Manyoni 1,605 0 0 0 0 0 1,605 33,065 5 Singida Urban 999 33 108 33 286 0 1,458 11,125 13 Total 16,377 1,116 228 393 286 267 18,666 179,915 10 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 33,494 136 0 0 139 143 33,913 62,528 54 Singida Rural 19,093 592 240 1,595 125 373 22,017 73,197 30 Manyoni 9,017 240 65 0 0 0 9,322 33,065 28 Singida Urban 2,886 0 0 0 85 43 3,014 11,125 27 Total 64,491 969 305 1,595 348 558 68,266 179,915 38 District District Crop Storage District 15.12 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Crop Storage By Source of Messages By District Total Number of Households % of total number of households Mechanisation / LST Irrigation Technology 15.10 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Mechanisation / LST By Source of Messages By District 15.11 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Irrigation Technology By Source of Messages By District Total Number of Households % of total number of households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 234 Governme nt NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Households % of total number of households Iramba 21,387 0 0 0 144 21,531 62,528 34 Singida Rural 9,622 244 0 0 247 10,113 73,197 14 Manyoni 7,460 81 65 0 0 7,606 33,065 23 Singida Urban 1,914 43 0 159 33 2,149 11,125 19 Total 40,383 368 65 159 424 41,400 179,915 23 Governme nt NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Iramba 20,118 0 0 0 282 278 20,678 62,528 33 Singida Rural 12,907 494 120 2,570 0 125 16,215 73,197 22 Manyoni 4,570 85 406 65 0 0 5,126 33,065 16 Singida Urban 1,786 0 0 75 684 0 2,545 11,125 23 Total 39,380 579 526 2,710 966 403 44,564 179,915 25 Governme nt NGO / Development Project Cooperative Other Not applicable Total Iramba 18,553 0 0 139 0 18,692 62,528 30 Singida Rural 7,260 464 0 0 244 7,968 73,197 11 Manyoni 3,242 328 163 82 85 3,900 33,065 12 Singida Urban 2,310 43 43 43 0 2,437 11,125 22 Total 31,365 835 205 264 329 32,997 179,915 18 Vermin Control District 15.13 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Vermin Control By Source of Messages By District % of total number of households District Total Number of Households % of total number of households 15.14 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-processing By Source of Messages By District Total Number of Households District 15.15 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Agro-forestry By Source of Messages By District Agro-progressing Agro-forestry Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 235 Governme nt NGO / Development Project Cooperative Large Scale Farm Not applicable Total Iramba 5,850 266 0 0 0 6,116 62,528 10 Singida Rural 845 984 0 125 0 1,954 73,197 3 Manyoni 1,424 81 78 0 169 1,752 33,065 5 Singida Urban 43 0 0 0 0 43 11,125 0 Total 8,162 1,331 78 125 169 9,865 179,915 5 Governme nt NGO / Development Project Not applicable Total Iramba 2,990 0 0 2,990 62,528 5 Singida Rural 1,342 856 120 2,318 73,197 3 Manyoni 148 85 0 233 33,065 1 Singida Urban 0 0 0 0 11,125 0 Total 4,480 941 120 5,541 179,915 3 District Beekeeping District Total Number of Households % of total number of households 15.16 EXTENSION MESSAGES: Number of Households By Receivingf Advice on Beekiping By Source of Messages By District 15.17 EXTENSION MESSAGES: Number of Households By Receiving Advice on Fish Farming By Source of Messages By District Fish Farming Total Number of Household s % of total number of households Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 236 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 43,576 38,311 88 26,466 7,452 28 29,145 14,298 49 40,698 29,560 73 12,712 2,159 17 Singida Rural 24,870 24,748 100 8,741 3,307 38 11,621 9,668 83 22,164 18,851 85 986 2,465 250 Manyoni 10,478 9,813 94 6,405 2,531 40 2,544 1,381 54 9,203 3,474 38 3,738 2,932 78 Singida Urban 3,687 3,644 99 2,021 365 18 2,263 1,679 74 3,686 2,579 70 702 75 11 Total 82,611 76,516 93 43,633 13,656 31 45,573 27,026 59 75,750 54,464 72 18,139 7,632 42 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 36,532 11,390 31 10,417 1,709 16 10,003 2,863 29 33,916 28,141 83 21,389 18,139 85 Singida Rural 17,193 10,103 59 618 740 120 2,537 3,423 135 22,266 19,421 87 9,003 10,237 114 Manyoni 9,344 5,231 56 2,200 0 0 1,605 464 29 9,237 8,602 93 7,614 7,021 92 Singida Urban 3,266 1,500 46 468 43 9 1,213 553 46 3,014 2,344 78 2,149 1,573 73 Total 66,335 28,223 43 13,703 2,492 18 15,358 7,304 48 68,433 58,508 85 40,155 36,971 92 Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Received Advice Adopted Message % Iramba 20,293 18,874 93 18,548 6,645 36 5,317 2,453 46 2,730 0 0 2,203 1,360 62 Singida Rural 14,874 15,603 105 8,215 5,394 66 1,586 847 53 2,318 495 21 974 605 62 Manyoni 5,210 5,126 98 3,985 1,070 27 1,752 757 43 168 0 0 82 82 100 Singida Urban 2,460 2,386 97 2,470 927 38 43 43 100 0 0 0 42 42 100 Total 42,837 41,989 98 33,218 14,037 42 8,698 4,100 47 5,216 495 9 3,301 2,089 63 Use of Improved Seed Mechanisation / LST Irrigation Technology 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 2) During the 2002/03 Agriculture Year, Singida Region District Crop Storage Vermin Control 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 1) During the 2002/03 Agriculture Year, Singida Region Use of Agrochemicals Spacing Erosion Control Organic Fertilizer Use Inorganic Fertilizer Use District Other 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Messages and District (Part 3) During the 2002/03 Agriculture Year, Singida Region Agro-progressing Agro-forestry Beekeeping Fish Farming District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 237 LIVELIHOOD CONSTRAINTS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 238 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 10,333 1,697 29,436 2,187 3,461 698 0 2,303 429 0 0 Singida Rural 12,036 3,187 24,199 11,005 3,194 1,089 361 5,818 2,080 124 123 Manyoni 408 497 14,516 2,553 2,879 742 329 1,313 736 0 0 Singida Urban 2,316 566 2,920 2,451 836 85 43 419 127 85 0 Access to Potable Water Access to Credit Harvesting Storage Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 4,426 4,190 0 144 141 141 561 0 1,268 140 974 Singida Rural 2,171 1,277 124 353 0 123 3,630 124 1,564 0 613 Manyoni 2,002 823 0 0 85 81 4,341 238 1,286 0 236 Singida Urban 75 203 0 43 0 0 423 43 208 0 286 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 3,467 3,243 12,191 8,543 9,551 1,425 2,367 12,506 428 0 133 Singida Rural 2,776 4,599 17,327 11,522 12,576 2,330 2,338 6,485 3,176 0 0 Manyoni 0 0 6,025 2,912 7,610 568 1,998 3,183 1,144 0 0 Singida Urban 668 926 2,599 2,789 1,146 201 192 929 127 127 0 Access to Potable Water Access to Credit Threshing Storage Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Access to Off Farm Income Iramba 3,134 1,351 0 287 573 576 552 280 1,261 660 Singida Rural 1,954 1,690 124 124 369 0 2,785 122 2,531 369 Manyoni 474 1,873 0 255 0 170 2,485 243 3,880 247 Singida Urban 42 211 0 0 75 0 713 43 169 169 District 2nd Most Importance District 2nd Most Importance 16.2 LIVELIHOOD CONSTRAINTS: Second Most Important Constraints By District 16.1 LIVELIHOOD CONSTRAINTS: Most Important Constraints By District cont…. LIVELIHOOD CONSTRAINTS: Second Most Important Constraints By District 1st Most Importance cont…. LIVELIHOOD CONSTRAINTS: Most Important Constraints By District 1st Most Importance District District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 239 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Access to Potable Water Iramba 1,981 697 5,903 6,336 9,413 3,109 3,333 12,212 1,573 0 4,920 Singida Rural 1,480 1,729 6,185 6,350 12,619 1,723 8,330 10,775 5,661 0 2,425 Manyoni 0 84 2,112 639 5,945 1,812 4,515 5,753 1,213 0 1,370 Singida Urban 680 637 1,417 1,848 1,010 202 245 2,218 700 160 252 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Access to Off Farm Income Iramba 3,008 0 0 282 0 421 1,876 287 289 2,776 4,114 Singida Rural 3,513 220 125 1,540 123 2,033 609 3,034 598 3,767 359 Manyoni 2,044 0 0 590 0 84 819 3,437 167 2,139 340 Singida Urban 414 0 0 42 0 85 0 410 75 244 486 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Iramba 1,081 571 2,662 5,326 8,309 2,131 4,240 8,778 2,081 286 0 Singida Rural 858 725 2,921 2,542 8,103 1,606 4,277 13,806 5,155 122 0 Manyoni 0 82 1,983 489 3,359 554 3,315 6,147 1,719 0 0 Singida Urban 845 340 1,011 837 1,899 160 553 1,570 763 627 85 District 3rd Most Importance 16.3 LIVELIHOOD CONSTRAINTS: Third Important Constraints By District District cont…. LIVELIHOOD CONSTRAINTS: Third Important Constraints By District 3rd Most Importance District 4th Most Importance 16.4 LIVELIHOOD CONSTRAINTS: Forth Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 240 Access to Potable Water Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Iramba 8,788 5,502 286 0 714 143 1,685 1,268 429 0 5,951 144 Singida Rural 2,595 7,275 362 487 2,835 363 2,944 2,147 3,860 246 8,639 0 Manyoni 1,149 3,625 85 0 492 84 415 820 4,140 589 3,611 0 Singida Urban 319 583 43 0 117 0 84 169 578 65 116 33 Access to Off Farm Income Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Access to Potable Water Iramba 2,154 1,390 570 2,467 7,315 4,928 3,127 2,805 7,291 2,148 0 4,241 Singida Rural 1,328 1,239 1,481 3,426 1,548 5,159 1,845 4,054 8,156 8,715 369 1,351 Manyoni 406 0 160 1,462 743 1,419 648 3,085 4,295 2,302 0 989 Singida Urban 328 542 202 888 572 845 342 510 1,539 1,171 210 338 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 6,389 144 0 999 0 2,869 1,398 1,260 418 5,514 1,587 5,668 Singida Rural 5,988 247 231 2,684 243 5,357 2,189 6,283 124 8,987 0 2,785 Manyoni 3,230 0 0 330 0 491 905 4,658 331 6,804 0 1,215 Singida Urban 1,284 0 43 85 0 43 127 762 170 560 0 852 District cont LIVELIHOOD CONSTRAINTS: Fifth Important Constraints By District District 5th Most Importance 4th Most Importance cont…. LIVELIHOOD CONSTRAINTS: Forth Important Constraints By District 5th Most Importance 16.5 LIVELIHOOD CONSTRAINTS: Fifth Important Constraints By District District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 241 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 9,940 2,546 1,948 3,871 1,682 1,287 5,119 2,249 3,330 144 567 979 Singida Rural 6,194 5,623 2,196 4,663 3,565 3,148 4,397 1,229 4,529 1,472 611 2,206 Manyoni 2,495 668 1,652 3,674 2,084 409 2,603 1,000 1,566 83 0 997 Singida Urban 284 235 225 117 455 463 641 291 466 295 75 213 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,636 2,016 2,279 1,259 286 3,782 597 1,034 4,347 5,681 2,235 2,714 Singida Rural 2,824 2,353 3,029 3,271 871 3,160 589 3,069 3,339 2,820 5,363 2,677 Manyoni 2,463 329 326 801 251 811 981 1,714 4,121 2,313 330 1,396 Singida Urban 718 287 329 329 128 965 235 712 1,375 810 506 974 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 3,650 6,216 829 4,640 1,786 1,825 3,143 2,332 7,703 144 284 1,279 Singida Rural 1,162 4,500 1,334 2,324 3,084 3,634 4,286 4,133 5,969 2,103 3,311 2,957 Manyoni 248 1,006 887 2,278 1,479 1,064 3,402 2,455 2,773 0 0 1,633 Singida Urban 328 149 244 159 412 266 276 342 592 234 296 403 16.6 LIVELIHOOD CONSTRAINTS: Least Important Constraints By District 1st Least Importance District 16.7 LIVELIHOOD CONSTRAINTS: Second Least Important Constraints By District 2nd Least Importance District District 1st Least Importance cont…. LIVELIHOOD CONSTRAINTS: Least Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 242 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,879 2,849 1,279 3,729 853 5,337 2,056 2,150 1,313 3,475 713 2,065 Singida Rural 5,918 2,542 2,058 3,998 2,085 3,533 1,348 3,424 2,685 2,593 1,429 2,669 Manyoni 2,957 327 167 1,060 169 1,721 1,400 1,984 2,042 2,070 83 1,859 Singida Urban 742 541 383 659 255 794 296 680 1,333 732 506 502 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 4,879 1,236 834 3,094 1,121 858 4,946 1,542 5,425 288 0 3,147 Singida Rural 1,082 1,674 1,101 2,205 2,070 1,722 3,539 3,184 6,098 4,176 1,852 3,147 Manyoni 83 414 471 1,327 901 803 2,986 1,686 2,690 165 165 2,123 Singida Urban 267 381 242 149 549 320 463 520 792 404 337 340 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 3,554 2,549 3,301 3,828 1,562 4,318 1,567 1,499 3,353 4,564 1,275 3,789 Singida Rural 6,386 2,798 2,751 5,276 1,973 6,458 3,541 2,464 2,562 2,398 1,824 2,917 Manyoni 3,299 750 169 2,488 591 2,886 1,794 1,401 1,312 2,491 83 1,484 Singida Urban 606 552 382 253 85 489 297 1,146 913 930 253 456 District 2nd Least Importance District 16.8 LIVELIHOOD CONSTRAINTS: Third Least Important Constraints By District 3rd Least Importance 3rd Least Importance cont…. LIVELIHOOD CONSTRAINTS: Second Least Important Constraints By District District cont…. LIVELIHOOD CONSTRAINTS: Third Least Important Constraints By District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 243 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 1,390 1,368 534 1,805 1,638 573 3,489 2,987 5,649 423 431 1,140 Singida Rural 2,329 1,694 865 1,095 1,570 1,415 2,914 3,027 3,594 2,339 2,103 1,592 Manyoni 247 336 983 1,484 806 1,129 2,025 1,725 1,872 579 0 970 Singida Urban 276 361 244 210 539 203 403 380 712 497 210 324 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 3,249 1,839 1,697 4,318 1,974 6,645 2,240 5,221 2,081 6,205 1,538 4,096 Singida Rural 5,232 4,479 1,832 5,515 3,045 5,640 5,023 3,450 2,547 4,933 3,319 3,644 Manyoni 2,073 757 331 1,977 839 3,068 1,536 2,403 1,743 2,822 333 1,607 Singida Urban 479 382 255 1,186 212 709 169 827 720 1,043 253 530 Access to Land Ownership of Land Soil Cultivation Soil Fertility Access to Improved Seed Irrigation Facilities Access to Chemical Inputs Cost of Inputs Extension Services Access to Forest Resources Hunting and Gathering Access to Potable Water Iramba 990 1,000 820 2,210 5,308 1,002 3,094 1,251 3,648 288 425 1,951 Singida Rural 1,827 3,420 1,187 843 2,143 1,207 3,288 2,294 3,188 1,225 1,592 869 Manyoni 332 837 993 1,671 824 575 1,705 1,019 2,595 249 0 1,488 Singida Urban 244 212 33 128 369 268 520 488 533 352 84 444 Access to Credit Harvesting Threshing Storage Processing Marketing Information Transport Costs Destruction by Animals Stealing Pest and Disease Local Government Taxation Access to Off Farm Income Iramba 2,702 2,136 1,124 2,667 2,273 3,401 2,963 1,845 2,361 6,814 2,828 9,286 Singida Rural 4,940 1,609 1,573 3,503 1,943 4,367 2,082 4,522 4,667 10,367 3,183 5,876 Manyoni 2,785 583 669 1,311 336 1,204 1,668 1,725 3,129 1,739 419 3,377 Singida Urban 583 509 340 626 213 540 211 904 699 1,916 456 412 District District cont…. LIVELIHOOD CONSTRAINTS: Forth Least Important Constraints By District 16.9 LIVELIHOOD CONSTRAINTS: Forth Least Important Constraints By District 4th Least Importance 4th Least Importance 16.10 LIVELIHOOD CONSTRAINTS: Fifth Least Important Constraints By District 5th Least Importance cont…. LIVELIHOOD CONSTRAINTS: Fifth Least Important Constraints By District 5th Least Importance District District Tanzania Agriculture Census Survey 2003 Singida Region 244 Appendix II 245 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 246 Total Number % Number % Number Iramba 53,098 85 9,430 15 62,528 Singida Rural 32,196 44 41,001 56 73,197 Manyoni 3,990 12 29,075 88 33,065 Singida Urban 1,129 10 9,996 90 11,125 Total 90,414 50 89,502 50 179,915 Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Number Owned Number Used Area Cultivated (Hectares) Iramba 103,723 212,893 105,194 7,145 6,617 3,696 44,071 3,896 467 4,375 3,950 2,006 159,315 227,356 111,363 Singida Rural 75,877 111,895 59,183 12,481 11,906 975 21,231 8,525 143 1,593 1,848 757 111,182 134,174 61,058 Manyoni 17,955 22,298 16,154 593 1,015 0 3,720 0 0 . . . 22,268 23,312 16,154 Singida Urban 2,265 3,296 1,539 338 85 43 168 0 0 . . . 2,770 3,381 1,582 Total 199,820 350,382 182,070 20,556 19,623 4,714 69,190 12,421 611 5,969 5,798 2,763 295,535 388,224 190,158 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Iramba 103,723 212,893 259,830.0 7,145 6,617 9,128.8 44,071 3,896 1,154.4 4,375 3,950 4,954.1 159,315 227,356 275,067.4 Singida Rural 75,877 111,895 146,181.6 12,481 11,906 2,408.5 21,231 8,525 353.6 1,593 1,848 1,869.9 111,182 134,174 150,813.7 Manyoni 17,955 22,298 39,900.7 593 1,015 0.0 3,720 0 0.0 . . . 22,268 23,312 39,900.7 Singida Urban 2,265 3,296 3,801.1 338 85 106.5 168 0 0.0 . . . 2,770 3,381 3,907.6 Total 199,820 350,382 449,713.4 20,556 19,623 11,643.8 69,190 12,421 1,508.0 5,969 5,798 6,824.1 295,535 388,224 469,689.3 Households Using Draft Animals Household Not Using Draft Animals Did you use Draft animals to cultivate your land during 2002/03 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Households Using Draft Animal to Cultivate Land By District District 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total 17.3 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year District Type of Craft Oxen Bulls Cows Donkeys Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 247 Number % Number % Number % Iramba 34,394 43.2 28,134 28.8 62,528 35.3 Singida Rural 33,417 42.0 38,094 39.0 71,511 40.3 Manyoni 6,154 7.7 26,167 26.8 32,321 18.2 Singida Urban 5,686 7.1 5,322 5.4 11,008 6.2 Total 79,651 100.0 97,717 100.0 177,368 100.0 Area (%) % Area (%) % Area (%) % Iramba 32,951 47.1 1,731 56.8 34,682 47.5 Singida Rural 27,618 39.5 1,034 33.9 28,652 39.2 Manyoni 5,504 7.9 119 3.9 5,623 7.7 Singida Urban 3,905 5.6 161 5.3 4,067 5.6 Total 69,978 100.0 3,046 100.0 73,023 100.0 17.4 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By Regio During 2002/03 Agriculture Year District Did you apply organic fertilizer during 2002/03? Using Organic Fertilizer Not Using Organic Fertilizer Total 17.5 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year District Farm Yard Manure Area Applied Compost Area Applied Total Area applied with Organic Fertilisers Tanzania Agriculture Census Survey 2003 Singida Region 248 Appendix II 249 CATTLE PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 250 Number % Number % Number % Iramba 27,972 44.7 34,556 55.3 62,528 100.0 Singida Rural 35,272 48.2 37,925 51.8 73,197 100.0 Manyoni 4,522 13.7 28,543 86.3 33,065 100.0 Singida Urban 4,739 42.6 6,386 57.4 11,125 100.0 Total 72,505 40.3 107,410 59.7 179,915 100.0 Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Number of Households Number of Cattle Iramba 27,830 449,741 289 433 0 . 27,830 450,174 Singida Rural 35,272 586,883 123 493 372 1,115 35,272 588,491 Manyoni 4,522 173,993 0 . 0 . 4,522 173,993 Singida Urban 4,739 44,501 0 . 0 . 4,739 44,501 Total 72,363 1,255,118 412 925 372 1,115 72,363 1,257,159 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year District Households Rearing Cattle Households Not Rearing Cattle Total 18.2 CATTLE PRODUCTION: Number of Cattle By Type and District as of 1st October, 2003 District Indigenous Improved Beef Improved Dairy Total Cattle Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 251 Number of Household % Number of Cattle % Number Per Household 1-5 9,954 36 34,822 8 3 6-10 7,597 27 59,969 13 8 11-15 3,685 13 45,552 10 12 16-20 3,232 12 57,561 13 18 21-30 1,421 5 34,410 8 24 31-40 710 3 25,450 6 36 41-50 250 1 11,621 3 47 61-100 704 3 60,522 13 86 101-150 137 0 19,134 4 140 151+ 140 1 101,132 22 724 Total 27,830 100 450,174 100 16 1-5 10,541 30 36,680 6 3 6-10 11,813 33 92,445 16 8 11-15 5,970 17 75,972 13 13 16-20 1,987 6 36,638 6 18 21-30 2,928 8 73,104 12 25 31-40 830 2 31,021 5 37 41-50 123 0 6,135 1 50 61-100 476 1 43,912 7 92 101-150 123 0 18,405 3 150 151+ 481 1 174,179 30 362 Total 35,272 100 588,491 100 17 1-5 81 2 242 0 3 6-10 330 7 2,554 1 8 11-15 571 13 7,421 4 13 16-20 968 21 17,726 10 18 21-30 507 11 12,669 7 25 31-40 569 13 18,498 11 32 41-50 416 9 19,468 11 47 51-60 163 4 8,984 5 55 61-100 750 17 59,125 34 79 101-150 82 2 11,420 7 140 151+ 84 2 15,886 9 188 Total 4,522 100 173,993 100 38 1-5 1,499 32 5,373 12 4 6-10 1,622 34 13,245 30 8 11-15 836 18 11,359 26 14 16-20 614 13 10,803 24 18 21-30 169 4 3,721 8 22 Total 4,739 100 44,501 100 9 Manyoni Singida Urban 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size as of 2002/03 Herd Size Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 252 Type Number of Indigenous Number of Improved Beef Number of Improved Dairy Total Cattle Bulls 100,657 925 . 101,582 Cows 451,353 . 497 451,850 Steers 235,101 . 247 235,348 Heifers 213,743 . 124 213,866 Male Calves 121,206 . . 121,206 Female Calves 133,059 . 247 133,306 Total 1,255,118 925 1,115 1,257,159 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 37,586 203,723 96,473 51,275 28,101 32,583 449,741 Singida Rural 45,287 165,375 112,942 123,109 68,174 71,996 586,883 Manyoni 12,679 64,675 22,205 33,390 18,737 22,307 173,993 Singida Urban 5,104 17,580 3,480 5,970 6,194 6,173 44,501 Total 100,657 451,353 235,101 213,743 121,206 133,059 1,255,118 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 433 . . . . . 433 Singida Rural 493 . . . . . 493 Manyoni . . . . . . . Singida Urban . . . . . . . Total 925 . . . . . 925 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle as of 1st October 2003 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Indigenous 18.6 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Beef Cattle Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 253 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba . . . . . . . Singida Rural . 497 247 124 . 247 1,115 Manyoni . . . . . . . Singida Urban . . . . . . . Total . 497 247 124 . 247 1,115 Bulls Cows Steers Heifers Male Calves Female Calves Total Iramba 38,019 203,723 96,473 51,275 28,101 32,583 450,174 Singida Rural 45,780 165,872 113,189 123,232 68,174 72,243 588,491 Manyoni 12,679 64,675 22,205 33,390 18,737 22,307 173,993 Singida Urban 5,104 17,580 3,480 5,970 6,194 6,173 44,501 Total 101,582 451,850 235,348 213,866 121,206 133,306 1,257,159 Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Number Died Total Cattle Offtake Iramba 8,190 23,671 37,042 45,382 10,450 28,767 7,922 13,034 11,873 13,689 14,247 15,796 140,339 Singida Rural 13,143 33,773 13,881 25,202 2,078 16,458 3,703 9,657 3,560 4,302 4,616 6,581 95,972 Manyoni 3,408 13,668 3,571 10,325 82 4,061 170 2,626 750 2,322 991 2,230 35,232 Singida Urban 997 4,092 2,614 6,426 42 1,310 1,010 2,592 1,349 2,237 1,596 2,020 18,678 Total 25,738 75,204 57,108 87,334 12,652 50,595 12,805 27,910 17,533 22,550 21,450 26,627 290,220 Female Calves 18.7 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and as of 1st October, 2003 Total Cattle Offtake District Category - Total Cattle 18.9 CATTLE OFFTAKE: Number of Died Cattle and Total Offtake by Category of Cattle and District during 2002/03 Agriculture Year District Bulls Cows Steers Heifers Male Calves Tanzania Agriculture Census Survey 2003 Singida Region 254 Appendix II 255 GOATS PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 256 Total Number % Number % Number Iramba 23,828 38 38,700 62 62,528 Singida Rural 27,499 38 45,698 62 73,197 Manyoni 5,714 17 27,351 83 33,065 Singida Urban 4,026 36 7,100 64 11,125 Total 61,067 34 118,849 66 179,915 Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Number of Households Number of Goat Iramba 23,273 253,149 564 991 701 1,540 23,273 255,680 Singida Rural 27,375 303,892 601 2,669 851 6,941 27,375 313,502 Manyoni 5,629 77,574 0 . 85 255 5,714 77,829 Singida Urban 4,026 36,771 0 . 128 637 4,026 37,409 Total 60,302 671,387 1,165 3,659 1,765 9,374 60,387 684,420 Households Rearing Goats Households Not Rearing 19.1 GOAT PRODUCTION: Number of Agriculture Households Rearing Goats By District during the 2002/03 Agriculture Year 19.2 GOAT PRODUCTION: Total Number of Goats by Type and District as of 2st October, 2003 District Indigenous Improved for Meat Improved Dairy Total Goat Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 257 Number of Household % Number of Goat % Average Number 1-4 5,573 24 16,600 6 3 5-9 8,348 36 53,510 21 6 10-14 4,531 19 50,215 20 11 15-19 1,492 6 23,775 9 16 20-24 1,275 5 26,625 10 21 25-29 951 4 25,871 10 27 30-39 571 2 17,701 7 31 40+ 532 2 41,382 16 78 Total 23,273 100 255,680 100 11 1-4 7,648 28 22,249 7 3 5-9 7,533 28 48,705 16 6 10-14 4,880 18 55,795 18 11 15-19 2,938 11 48,616 16 17 20-24 2,332 9 48,968 16 21 25-29 955 3 24,846 8 26 30-39 366 1 12,300 4 34 40+ 724 3 52,023 17 72 Total 27,375 100 313,502 100 11 1-4 1,127 20 3,290 4 3 5-9 1,542 27 10,380 13 7 10-14 916 16 10,921 14 12 15-19 652 11 11,317 15 17 20-24 724 13 15,082 19 21 25-29 167 3 4,426 6 26 30-39 334 6 11,498 15 34 40+ 252 4 10,916 14 43 Total 5,714 100 77,829 100 14 1-4 1,251 31 3,945 11 3 5-9 1,010 25 6,863 18 7 10-14 1,088 27 11,893 32 11 15-19 297 7 5,054 14 17 20-24 211 5 4,465 12 21 25-29 84 2 2,103 6 25 30-39 85 2 3,087 8 37 Total 4,026 100 37,409 100 9 1-4 15,600 26 46,083 7 3 5-9 18,432 31 119,458 17 6 10-14 11,415 19 128,824 19 11 15-19 5,379 9 88,761 13 17 20-24 4,541 8 95,141 14 21 25-29 2,158 4 57,246 8 27 30-39 1,355 2 44,586 7 33 40+ 1,508 2 104,321 15 69 Total 60,387 100 684,420 100 11 Manyoni Singida Urban Total 19.3 GOAT PRODUCTION: Number of Households Rearing Goats, Herd of Goats and Average Head per Household by Herd Size as of 1st October, 2003 Herd Size Iramba Singida Rural Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 258 District Number of Indigenous Number of Improved for Meat Number of Improved Dairy Total Goat Billy Goat 102,480 675 1,031 104,186 Castrated Goat 50,861 764 3,913 55,538 She Goat 333,822 1,418 1,736 336,975 Male Kid 93,271 114 1,227 94,613 She Kid 90,953 689 1,467 93,108 Total 671,387 3,659 9,374 684,420 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 41,075 22,266 128,344 31,862 29,601 253,149 Singida Rural 45,028 21,328 151,469 43,935 42,133 303,892 Manyoni 10,397 4,889 35,938 12,334 14,015 77,574 Singida Urban 5,980 2,378 18,071 5,140 5,203 36,771 Total 102,480 50,861 333,822 93,271 90,953 671,387 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 430 144 417 . . 991 Singida Rural 246 620 1,000 114 689 2,669 Manyoni . . . . . . Singida Urban . . . . . . Total 675 764 1,418 114 689 3,659 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba . 144 710 400 287 1,540 Singida Rural 861 3,769 601 743 968 6,941 Manyoni 170 . 85 . . 255 Singida Urban . . 339 85 213 637 Total 1,031 3,913 1,736 1,227 1,467 9,374 19.4.1 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat as of 1st October, 2003 and District 19.6 GOAT PRODUCTION: Number of Indigenous Goat by Category and District as of 1st October, 2003 District Number of Indigenous District Number of Improved Dairy 19.7 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District as of 1st October, 2003 District Number of Improved for Meat 19.8 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 259 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Iramba 41,505 22,555 129,471 32,262 29,888 255,680 Singida Rural 46,134 25,717 153,071 44,792 43,789 313,502 Manyoni 10,567 4,889 36,023 12,334 14,015 77,829 Singida Urban 5,980 2,378 18,410 5,225 5,416 37,409 Total 104,186 55,538 336,975 94,613 93,108 684,420 Ram Castrated Goat She Goat Male Kid She Kid Iramba 22,981 11,175 28,858 7,898 6,005 Singida Rural 32,313 15,696 27,613 7,846 7,488 Manyoni 9,797 1,474 6,295 1,350 7,188 Singida Urban 3,310 1,691 5,278 834 1,184 Total 68,400 30,036 68,043 17,927 21,864 Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Number Died Total Goat Offtake Iramba 5,269 22,981 569 11,175 11,022 28,858 4,615 7,898 5,446 6,005 76,917 Singida Rural 4,265 32,313 1,855 15,696 8,326 27,613 3,962 7,846 5,514 7,488 90,955 Manyoni 4,072 9,797 . 1,474 2,637 6,295 1,017 1,350 6,520 7,188 26,103 Singida Urban 658 3,310 . 1,691 1,565 5,278 367 834 761 1,184 12,297 Total 14,264 68,400 2,424 30,036 23,550 68,043 9,961 17,927 18,241 21,864 206,271 District Goat Type 19.6 Goat OFFTAKE: Number of Goat Died and % of Offtake By Tpe and District District Ram Castrated Goat She Goat Male Kid She Kid Total Goat Offtake 19.4 GOAT PRODUCTION: Number of Total Goat by Category and District as of 1st October, 2003 District Total Goat 19.5 Goat OFFTAKE: Goat Offtake By Type and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 260 Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Iramba 13,570 9,229 89,960,894 7,097 12,869 65,961,329 14,035 7,151 67,952,958 Singida Rural 17,165 8,202 89,770,345 11,383 8,703 51,769,745 12,681 10,100 96,347,581 Manyoni 2,731 13,059 29,648,312 898 10,860 9,806,173 2,601 7,403 12,874,921 Singida Urban 1,593 11,389 14,710,229 1,245 9,188 7,046,845 1,981 7,470 13,193,881 Total 35,059 9,239 224,089,779 20,624 10,560 134,584,092 31,298 8,443 190,369,341 Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Number Sold/Traded Average Value Per Head Tshs from Sale Iramba 3,004 4,286 7,220,097 283 4,612 8,378,602 37,989 8,590 239,473,879 Singida Rural 483 2,693 3,312,591 484 24,349 30,011,444 42,197 9,386 271,211,705 Manyoni . 5,053 3,651,056 330 4,142 2,416,375 6,561 9,391 58,396,836 Singida Urban 85 3,541 1,491,637 169 79,428 26,788,421 5,073 13,796 63,231,014 Total 3,572 3,862 15,675,381 1,266 17,026 67,594,842 91,819 9,357 632,313,435 Male Kid She Kid Total 19.7 Goat OFFTAKE: Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year District District Ram Castrated Goat She Goat cont…. Goat OFFTAKE: Number of Goat Sold and Value by Category and District during 2002/03 Agriculture Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 261 SHEEP PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 262 Number % Number % Number % Iramba 14,969 24 47,559 76 62,528 100 Singida Rural 17,985 25 55,212 75 73,197 100 Manyoni 3,467 10 29,598 90 33,065 100 Singida Urban 2,758 25 8,367 75 11,125 100 Total 39,179 22 140,736 78 179,915 100 District Number of Indigenous Number of Improved Total Sheep Iramba 119,704 . 119,704 Singida Rural 139,366 2,238 141,604 Manyoni 31,901 . 31,901 Singida Urban 16,343 386 16,729 Total 307,314 2,624 309,938 20.2 SHEEP PRODUCTION: Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.1 SHEEP PRODUCTION: Number of Households Rearing Sheep by District as of 1st October, 2002.0/ Agriculture Year District Did the household own, raise or manage any Sheep? Households Raising Sheep Households Not Raising Sheep Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 263 Number of Household % Number of Sheep % Average Number Per Household 1-4 7,081 48 19,561 16 3 5-9 4,923 33 31,734 27 6 10-14 961 6 10,568 9 11 15-19 768 5 12,588 11 16 20-24 526 4 10,797 9 21 25-29 140 1 3,911 3 28 30-39 143 1 4,286 4 30 40+ 284 2 26,258 22 92 Total 14,826 100 119,704 100 8 1-4 8,625 48 25,026 18 3 5-9 5,572 31 36,025 25 6 10-14 1,721 10 19,681 14 11 15-19 735 4 12,384 9 17 20-24 718 4 14,713 10 20 30-39 125 1 4,484 3 36 40+ 489 3 29,291 21 60 Total 17,985 100 141,604 100 8 1-4 984 28 2,847 9 3 5-9 1,316 38 8,401 26 6 10-14 500 14 5,651 18 11 15-19 329 10 5,274 17 16 20-24 170 5 3,729 12 22 30-39 169 5 5,999 19 36 Total 3,467 100 31,901 100 9 1-4 1,259 46 3,151 19 3 5-9 1,043 38 6,689 40 6 10-14 286 10 3,242 19 11 15-19 43 2 639 4 15 20-24 85 3 1,817 11 21 25-29 43 2 1,191 7 28 Total 2,758 100 16,729 100 6 1-4 17,949 46 50,586 16 3 5-9 12,854 33 82,849 27 6 10-14 3,468 9 39,141 13 11 15-19 1,875 5 30,886 10 16 20-24 1,498 4 31,056 10 21 25-29 182 0 5,102 2 28 30-39 436 1 14,769 5 34 40+ 773 2 55,550 18 72 Total 39,036 100 309,938 100 8 Singida Rural Manyoni Singida Urban Total 20.3.1 SHEEP PRODUCTION: Number of Households Rearing Sheep, Herd of Sheep and Average Herd Per Household by Herd Size as of 1st October, 2002/03 Herd Size Total Sheep Iramba Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 264 Breed Number of Indigenous Number of Improved for Mutton Total Sheep Ram 46,334 368 46,703 Castrated Sheep 15,989 . 15,989 She Sheep 154,411 1,003 155,414 Male Lamb 52,662 379 53,040 She Lamb 37,918 873 38,792 Total 307,314 2,624 309,938 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 22,032 9,838 57,112 14,961 15,761 119,704 Singida Rural 16,642 4,749 72,517 30,541 14,916 139,366 Manyoni 5,306 1,168 16,292 4,051 5,084 31,901 Singida Urban 2,355 234 8,490 3,108 2,157 16,343 Total 46,334 15,989 154,411 52,662 37,918 307,314 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba . . . . . . Singida Rural 368 . 747 248 873 2,238 Manyoni . . . . . . Singida Urban . . 256 130 . 386 Total 368 . 1,003 379 873 2,624 20.4.1 SHEEP PRODUCTION: Total Number of Sheep By Breed Type During the 2002/03 Agriculture Year 20.5 SHEEP PRODUCTION: Total Number of Indigenous Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Indigenous Number of Indigenous 20.6 SHEEP PRODUCTION: Total Number of Improved Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Number of Improved for Mutton Number of Improved for Mutton Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 265 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 22,032 9,838 57,112 14,961 15,761 119,704 Singida Rural 17,010 4,749 73,265 30,790 15,790 141,604 Manyoni 5,306 1,168 16,292 4,051 5,084 31,901 Singida Urban 2,355 234 8,745 3,238 2,157 16,729 Total 46,703 15,989 155,414 53,040 38,792 309,938 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 3,651 286 571 17,036 20,296 Singida Rural 88,381 689 2,401 17,171 15,810 Manyoni 240 169 164 4,308 5,773 Singida Urban 441 126 932 2,155 1,903 Total 92,713 1,270 4,068 40,670 43,782 Ram Castrated Sheep She Sheep Male Lamb She Lamb Iramba 23,115 7,292 13,731 2,659 4,770 Singida Rural 13,056 5,067 10,025 744 1,971 Manyoni 1,909 74 2,538 169 894 Singida Urban 1,062 212 2,548 423 382 Total 39,142 12,645 28,843 3,995 8,018 District Sheep Type 20.8 SHEEP INTAKE: Sheep Intake By Type and District District Total Sheep Intake 20.9 SHEEP OFFTAKE: Sheep Offtake By Type and District 20.7 SHEEP PRODUCTION: Total Number of Sheep by Category of Sheep and District as of 1st October, 2002/03 Agriculture Year District Total Sheep Total Sheep Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 266 Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Number Died Total Sheep Offtake Iramba 7,584 23,115 1,818 7,292 6,519 13,731 838 2,659 3,217 4,770 Singida Rural 861 13,056 1,237 5,067 2,945 10,025 620 744 616 1,971 Manyoni 159 1,909 . 74 589 2,538 . 169 304 894 Singida Urban 85 1,062 . 212 507 2,548 295 423 42 382 Total 8,688 39,142 3,055 12,645 10,560 28,843 1,753 3,995 4,179 8,018 Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Number Sold / Traded Average Value Per Sheep Tshs from Sale Iramba 5,384 6,487 27,803,172 3,075 6,476 7,977,535 5,501 5,550 22,424,246 . 4,333 1,818,642 . 4,194 2,946,934 Singida Rural 8,674 5,904 30,366,061 1,472 5,886 7,926,491 3,562 5,840 23,571,069 . 10,939 2,716,542 740 2,667 989,103 Manyoni 846 9,508 7,932,457 74 10,000 742,862 930 7,154 4,226,175 169 5,000 422,798 . 3,727 596,701 Singida Urban 732 5,420 3,739,535 85 5,669 721,516 1,021 4,804 4,047,027 85 2,531 749,482 298 2,625 444,942 Total 15,636 6,376 69,841,225 4,706 6,248 17,368,405 11,013 5,707 54,268,517 254 5,442 5,707,464 1,038 3,548 4,977,681 20.9 SHEEP OFFTAKE: Number of Sheep Died and % of Offtake By Type and District District Ram Castrated Sheep She Sheep Male Lamb She Lamb 20.10 SHEEP OFFTAKE: Number of Sheep Sold and Value (Tshs) by Category and District during 2002/03 Agriculture Year District Ram Castrated Sheep She Sheep Male Lamb She Lamb Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 267 PIGS PRODUCTION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 268 Total Number % Number % Number Iramba 1,689 2.7 60,839 97.3 62,528 Singida Rural 703 1.0 72,493 99.0 73,197 Manyoni 161 0.5 32,903 99.5 33,065 Singida Urban 0 0.0 11,125 100.0 11,125 Total 2,554 1.4 177,362 98.6 179,915 District Number of Household Number of Pig g Number Per Household Iramba 1,546 2,508 2 Singida Rural 580 3,464 6 Manyoni 161 403 3 Total 2,288 6,375 3 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Iramba 0 144 1,546 273 545 2,508 Singida Rural 684 . 787 996 996 3,464 Manyoni . . 81 81 242 403 Total 684 144 2,414 1,350 1,784 6,375 21.1 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.2 PIG PRODUCTION: Number of Households Raising Pig by District during 2002/03 Agriculture Year 21.3 PIG POPULATION: Total Number of Pigs by Category of Pigs and District as of 1st October, 2003 Households Raising Pig Households Not Raising Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 269 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 270 Number % age Number % age Number % age Iramba 9,318 29 22,368 71 31,687 100 Singida Rural 20,721 55 16,782 45 37,503 100 Manyoni 1,625 27 4,352 73 5,977 100 Singida Urban 2,439 48 2,648 52 5,086 100 Total 34,103 42 46,150 58 80,253 100 Number % Number % Number % Number % Iramba 5,527 31 7,336 29 2,688 33 1,122 20 Singida Rural 9,755 55 15,223 61 4,251 53 4,125 74 Manyoni 745 4 1,042 4 328 4 314 6 Singida Urban 1,685 10 1,357 5 761 9 33 1 Total 17,712 100 24,959 100 8,029 100 5,593 100 Number % age Number % age Number % age Iramba 20,152 65 10,718 35 30,870 100 Singida Rural 28,370 77 8,515 23 36,885 100 Manyoni 4,434 80 1,079 20 5,513 100 Singida Urban 3,419 63 1,979 37 5,399 100 Total 56,375 72 22,292 28 78,667 100 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultura households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total 22.2 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District and type of dewormed Livestock District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs Yes Yes Yes Yes 22.1 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have dewormed animals during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District Number of Agricultural Number of Agricultural Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 271 Number % age Number % age Number % age Number % age Number % age Number % age Iramba 2,785 14 8,539 42 5,305 26 855 4 2,667 13 20,152 100 Singida Rural 11,155 39 12,247 43 1,249 4 245 1 3,474 12 28,370 100 Manyoni 919 21 1,636 37 1,315 30 227 5 337 8 4,434 100 Singida Urban 1,425 42 679 20 254 7 298 9 763 22 3,419 100 Total 16,285 29 23,101 41 8,123 14 1,625 3 7,241 13 56,375 100 Number % age Number % age Number % age Iramba 7,565 23.6 24,553 76 32,118 100 Singida Rural 8,494 24.1 26,786 76 35,279 100 Manyoni 1,977 33.6 3,916 66 5,893 100 Singida Urban 85 1.7 5,012 98 5,096 100 Total 18,120 23.1 60,266 77 78,387 100 Number % age Number % age Number % age Number % age Iramba 2,566 34 4,423 58 576 8 7,565 100 Singida Rural 4,788 56 3,205 38 500 6 8,494 100 Manyoni 983 50 911 46 83 4 1,977 100 Singida Urban 42 50 43 50 0 0 85 100 Total 8,380 46 8,581 47 1,159 6 18,120 100 22.6 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tsetse flies Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tsetse Flies Control None Spray Dipping Total 22.5 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultura households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Yea District Number of Agricultural Number of Agricultural Total 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District Method of Tick Control None Spraying Dipping Smearing Other Total Tanzania Agriculture Census Survey 2003 Singida Region 272 Appendix II 273 OTHER LIVESTOCK Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 274 Breed Type Current Number Indigenous Chicken 1,643,973 Layer 7,589 Broiler 6,616 Ducks 35,013 Turkeys 7,501 Rabbits 840 Donkeys 16,649 Horse 0 Other 4,001 Total 1,722,182 Number No of Househ olds Number No of Households Number No of Househ olds Number No of Households Number No of House holds Iramba 8,357 1,549 . 0 . 0 12,295 3,821 1,142 427 Singida Rural 19,791 2,093 7,501 125 . 0 4,354 1,694 2,859 370 Manyoni 2,528 483 . 0 . 0 . 0 . 0 Singida Urban 4,336 85 . 0 840 42 . 0 . 0 Total 35,013 4,209 7,501 125 840 42 16,649 5,516 4,001 797 Singida Rural 2,099 3,586 5,685 Manyoni 5,490 . 5,490 Singida Urban . 3,030 3,030 Total 7,589 6,616 14,205 1 - 4 81,920 449 123 82,492 5 - 9 233,377 2,229 1,510 237,115 10 - 19 487,816 1,684 . 489,501 20 - 29 268,123 . 2,463 270,586 30 - 39 174,050 . . 174,050 40 - 49 82,720 3,228 . 85,947 50 - 99 159,744 . 2,520 162,264 100+ 156,222 . . 156,222 Total 1,643,973 7,589 6,616 1,658,178 Indigenous Chicken Layer Broiler Total Iramba 788,337 . . 788,337 49,729 Singida Rur 639,213 2,099 3,586 644,898 55,299 Manyoni 157,842 5,490 . 163,332 13,274 Singida Urb 58,581 . 3,030 61,611 7,520 Total 1,643,973 7,589 6,616 1,658,178 125,823 Total 23.1 OTHER LIVESTOCK: Total Number of Other Livestock by Breed and Type Flock Size Chicken Type 23.3 OTHER LIVESTOCK: Number of Chicken by Type and District District Chicken Type Indigenous Chicken Layer Broiler Layer Broiler Total 23.4 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by Flock Size 23.2 OTHER LIVESTOCK: Number of Households Rearing and number of Other Livestock by Type and District District Ducks Turkeys Rabbits Donkeys Other 23.4 OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District District Chicken Type Households Keeping Chicken Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 275 LIVESTOCK PRODUCTS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 276 Sold Consumed / Utilised Sold Consumed / Utilised Sold Consumed / Utilised Iramba 4,321,619 2,516,280 37,940 1,728 16,053 998 Singida Rural 5,377,708 2,562,195 32,443 4,844 32,860 4,464 Manyoni 1,175,075 712,768 7,538 3,169 8,763 1,876 Singida Urban 524,729 283,580 4,270 379 2,350 997 Total 11,399,132 6,074,824 82,192 10,119 60,025 8,335 25.1 LIVESTOCK PRODUCTS: Number of Eggs, Hides and Skins Sold/Consumed/Utlilized by the household By District, during 2002/03 Agricultural Year District Product Name Eggs Hides Skins Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 277 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 278 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 13,748 8,149 960 1,571 978 25,406 Singida Rural 4,311 1,779 0 497 124 6,711 Manyoni 3,993 739 84 0 0 4,816 Singida Urban 633 297 0 0 0 931 Total 22,686 10,964 1,044 2,068 1,102 37,864 <5 Total Iramba 1,546 1,546 Singida Rural 1,358 1,358 Manyoni 2,406 2,406 Total 5,311 5,311 <5 5 - 9 10 - 14 Total Iramba 4,909 140 1,287 6,336 Singida Rural 6,199 125 0 6,324 Manyoni 2,315 0 0 2,315 Singida Urban 42 0 43 85 Total 13,465 265 1,330 15,060 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 21,328 4,439 843 0 137 26,746 Singida Rural 27,631 3,533 233 123 125 31,644 Manyoni 2,662 254 80 0 0 2,996 Singida Urban 2,794 126 0 0 0 2,921 Total 54,415 8,353 1,155 123 261 64,307 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 8,875 12,342 2,283 2,993 3,513 484 0 30,490 Singida Rural 10,427 9,425 4,442 4,765 3,532 605 0 33,196 Manyoni 5,428 4,070 1,919 1,871 1,499 1,171 164 16,121 Singida Urban 972 548 363 84 426 42 0 2,436 Total 25,703 26,385 9,006 9,714 8,970 2,303 164 82,245 District Distance to Nearest Primary Market 27.4 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Crush and District District Distance to Nearest Cattle Crush 27.5 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Primary Market and District District Distance to Nearest 27.3 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hand Powered Sprayer and District District Distance to Nearest Hand Powered Sprayer 27.1 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Cattle Dip and District District Distance to Nearest Cattle Dip 27.2 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Spray Raced and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 279 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Iramba 1,508 398 289 424 0 0 2,619 Singida Rural 1,966 3,945 1,837 2,205 981 605 11,539 Manyoni 2,310 0 169 83 0 0 2,562 Singida Urban 0 0 0 0 0 43 43 Total 5,784 4,342 2,295 2,713 981 648 16,763 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 1,551 0 0 0 0 143 0 1,694 Singida Rural 2,956 980 0 0 0 457 593 4,986 Manyoni 2,068 0 170 0 0 0 0 2,238 Singida Urban 75 784 842 593 85 0 0 2,379 Total 6,650 1,764 1,012 593 85 600 593 11,297 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 Total Iramba 7,687 1,848 0 1,287 141 0 10,963 Singida Rural 11,386 2,025 0 493 474 860 15,239 Manyoni 2,035 531 85 169 254 0 3,074 Singida Urban 792 794 1,167 170 85 0 3,009 Total 21,901 5,198 1,251 2,120 954 860 32,284 <5 5 - 9 10 - 14 15 - 19 20 - 29 50+ Total Iramba 3,121 279 0 0 0 0 3,400 Singida Rural 4,899 1,227 0 0 946 241 7,312 Manyoni 2,151 0 85 169 254 0 2,660 Singida Urban 183 1,489 1,060 551 127 0 3,410 Total 10,354 2,996 1,145 720 1,327 241 16,782 District Distance to Nearest Slaughter Slab 27.9 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Hide/ Skin Shade and District District Distance to Nearest Hide/ Skin Shade 27.7 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Abattoir and District District Distance to Nearest Abattoir 27.8 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Slaughter Slab and District 27.6 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Secondary Market and District District Distance to Nearest Secondary Market Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 280 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50+ Total Iramba 3,104 1,261 0 424 422 289 1,121 6,621 Singida Rural 2,785 2,229 373 867 6,267 4,972 8,305 25,798 Manyoni 1,697 506 420 488 959 574 239 4,884 Singida Urban 183 1,560 1,742 847 381 42 42 4,798 Total 7,770 5,556 2,535 2,626 8,029 5,876 9,707 42,101 <5 5 - 9 10 - 14 20 - 29 30 - 49 50+ Total Iramba 2,120 433 286 0 0 675 3,514 Singida Rural 1,366 859 115 1,083 2,440 949 6,812 Manyoni 2,087 0 0 0 0 0 2,087 Singida Urban 0 192 0 0 0 0 192 Total 5,573 1,484 401 1,083 2,440 1,625 12,606 <5 5 - 9 10 - 14 20 - 29 Total Iramba 1,695 142 0 0 1,837 Singida Rural 2,917 0 0 487 3,404 Manyoni 2,257 0 0 0 2,257 Singida Urban 33 108 43 0 183 Total 6,902 250 43 487 7,681 <5 5 - 9 10 - 14 15 - 19 20 - 29 Total Iramba 7,938 282 0 0 0 8,220 Singida Rural 13,167 1,941 457 728 120 16,413 Manyoni 2,334 0 84 0 0 2,419 Singida Urban 1,134 42 0 0 0 1,175 Total 24,573 2,264 542 728 120 28,227 <5 5 - 9 10 - 14 15 - 19 Total Iramba 1,694 144 0 1,144 2,982 Singida Rural 5,479 855 0 0 6,334 Manyoni 2,251 0 0 0 2,251 Singida Urban 255 127 43 43 467 Total 9,678 1,126 43 1,187 12,034 District Distance to Nearest Drencher 27.13 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Watering Point/ Dam and Distric District Distance to Nearest Village Watering Point/ Dam 27.14 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Drencher and Distric District Distance to Nearest Veterinary Clinic 27.12 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Village Holding Gound and District District Distance to Nearest Village Holding Gound 27.10 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Input Supply and District District Distance to Nearest Input Supply 27.11 ACCESS TO FUNCTIONAL LIVESTOCK FACILITIES: Number of households by Distance to Nearest Veterinary Clinic and District Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 281 FISH FARMING Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 282 Number % Number % Iramba 62,528 100.0 62,528 100.0 Singida Rural 73,197 100.0 73,197 100.0 Manyoni 33,065 100.0 33,065 100.0 Singida Urban 11,125 100.0 11,125 100.0 Total 179,915 100.0 179,915 100.0 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District, 2002/03 Agricultural Year District g Households NOT Doing Fish Farming Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 283 LIVESTOCK EXTENSION Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 284 Number % Number % Number % Iramba 21,420 34 41,109 66 62,528 100 Singida Rural 9,465 13 63,732 87 73,197 100 Manyoni 2,831 9 30,234 91 33,065 100 Singida Urban 2,476 22 8,650 78 11,125 100 Total 36,191 20 143,724 80 179,915 100 Government Total Iramba 11,956 11,956 Singida Rural 2,691 2,691 Manyoni 1,340 1,340 Singida Urban 807 807 Total 16,795 16,795 Government NGO / Development Project Total Iramba 11,309 144 11,453 Singida Rural 3,988 123 4,111 Manyoni 1,593 0 1,593 Singida Urban 807 0 807 Total 17,697 267 17,965 District Source of Advice District Source of Advice 29.3 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Housing By Source and District, 2002/03 29.2 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Feeds and Proper Feeding By Source and District, 2002/03 Agricultural Year 29.1 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Advice By Type of Service Provider and District, 2002/03 Agricultural Year District Did Household receive livestock advice during 2002/03? Number of Agricultural Number of Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 285 Government NGO / Development Project Total Iramba 9,938 0 9,938 Singida Rural 2,463 123 2,586 Manyoni 248 0 248 Singida Urban 807 0 807 Total 13,457 123 13,580 Government NGO / Development Project Large Scale Farmer Total Iramba 10,760 0 0 10,760 Singida Rural 2,592 246 125 2,964 Manyoni 248 0 0 248 Singida Urban 850 0 0 850 Total 14,450 246 125 14,822 Government NGO / Development Project Large Scale Farmer Total Iramba 17,890 705 0 18,594 Singida Rural 6,898 123 120 7,141 Manyoni 1,913 0 0 1,913 Singida Urban 2,306 0 0 2,306 Total 29,007 828 120 29,955 District Source of Advice 29.5 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Milk Hygene By Source and District, 2002/03 Agricultural Year District Source of Advice 29.6 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Disease Control By Source and District, 2002/03 Agricultural Year 29.4 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Proper Milking By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 286 Government NGO / Development Project Large Scale Farmer Total Iramba 11,532 697 0 12,229 Singida Rural 2,565 0 125 2,690 Manyoni 918 0 0 918 Singida Urban 1,522 0 0 1,522 Total 16,537 697 125 17,359 Government NGO / Development Project Large Scale Farmer Total Iramba 12,060 417 0 12,477 Singida Rural 3,038 123 485 3,646 Manyoni 337 0 0 337 Singida Urban 1,084 0 0 1,084 Total 16,520 540 485 17,545 Government NGO / Development Project Total Iramba 12,342 849 13,191 Singida Rural 2,935 123 3,058 Manyoni 1,261 0 1,261 Singida Urban 797 0 797 Total 17,336 972 18,308 District Source of Advice 29.8 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice Pasture Establishment and Selection By Source and District, 2002/03 District Source of Advice 29.9 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Group Formation and Strengtherning By Source 29.7 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Herd /Flock Size and Selection By Source and District, 2002/03 Agricultural District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 287 Government NGO / Development Project Total Iramba 8,722 280 9,003 Singida Rural 3,209 246 3,455 Manyoni 1,095 0 1,095 Singida Urban 1,147 0 1,147 Total 14,173 527 14,700 Government NGO / Development Project Total Iramba 8,458 0 8,458 Singida Rural 3,281 123 3,404 Manyoni 925 0 925 Singida Urban 1,307 0 1,307 Total 13,971 123 14,094 Number % Number % Number % Number % Number % Number % Iramba 3,716 15 17,657 70 3,547 14 287 1 143 1 25,349 100 Singida Rural 2,399 17 7,200 50 971 7 1,713 12 2,165 15 14,448 100 Manyoni 255 12 1,659 80 169 8 0 0 0 0 2,083 100 Singida Urban 255 7 1,608 43 657 18 298 8 892 24 3,709 100 Total 6,625 15 28,123 62 5,344 12 2,297 5 3,199 7 45,588 100 District Quality of Service Very Good Good Average Poor No Good Total 29.11 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Use of Improved Bulls By Source and District, District Source of Advice 29.12 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural 29.10 LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice on Calf Rearing By Source and District, 2002/03 Agricultural Year District Source of Advice Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 288 Number % Number % Number % Number % Number % Number % Iramba 21,420 20 21,420 20 21,420 20 21,420 20 21,420 20 107,098 100 Singida Rural 9,465 20 9,465 20 9,465 20 9,465 20 9,465 20 47,324 100 Manyoni 2,831 20 2,746 20 2,746 20 2,746 20 2,746 20 13,815 100 Singida Urban 2,476 20 2,476 20 2,476 20 2,476 20 2,476 20 12,378 100 Total 36,191 20 36,106 20 36,106 20 36,106 20 36,106 20 180,614 100 Number % Number % Number % Iramba 9,462 25 27,840 75 37,301 100 Singida Rural 4,010 25 12,267 75 16,278 100 Manyoni 413 15 2,335 85 2,749 100 Singida Urban 457 8 5,103 92 5,561 100 Total 14,343 23 47,545 77 61,888 100 29.14LIVESTOCK EXTENSION: Number of Agricultural Households with/ without Contact farmers/ Group Member and District, 2002/03 Agricultural Year District Number of Agricultural Number of Total 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households By Source of Extension Services and District, 2002/03 Agricultural District Extension Provider Government NGO / Co-operative Large Scale Farmer Other Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 289 GOVERNMENT REGULATORY PROBLEMS Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 290 Number % Number % Number % Iramba 2,525 4 59,860 96 62,385 100 Singida Rural 3,439 5 66,649 95 70,089 100 Manyoni 240 1 32,825 99 33,065 100 Singida Urban 150 1 10,891 99 11,041 100 Total 6,355 4 170,225 96 176,580 100 30.1 GOVERNMENT REGULATORY PROBLEMS: Number of Agricultural Households by Whether Face Problems with Governmet Regulation During 2003/04 by District, 2002/03 Agricultural Year District Did you face problems with Govt regulations during 02/03? Yes No Total Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 291 LABOUR USE Tanzania Agriculture Sample Census - 2003 Singida Region Appendix II 292 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 54,565 19,376 6,538 69,970 1,247 0 586 21,120 3,097 176,501 Soil Preparation by Hand 35,810 9,866 9,908 79,982 779 84 270 25,089 1,772 163,560 Soil Preparation bu Oxen / Tractor 14,219 5,928 1,798 37,946 687 143 422 12,644 2,548 76,334 Planting 18,637 2,831 24,028 83,682 846 250 2,626 44,878 574 178,353 Weeding 13,748 2,297 5,653 89,692 764 84 349 60,636 4,419 177,643 Crop Protection 11,158 2,785 5,012 55,314 1,634 703 7,169 57,773 1,058 142,606 Harvesting 14,349 1,785 4,955 82,224 706 126 697 67,263 1,992 174,096 Crop Processing 15,379 2,752 80,060 31,703 1,452 5,092 6,710 11,388 125 154,659 Crop Marketing 64,776 6,159 4,293 28,363 787 0 370 3,207 125 108,080 Cattle Rearing 35,224 5,508 1,352 11,955 1,357 376 648 7,362 210 63,992 Cattle Herding 23,799 10,130 2,739 9,645 9,198 2,580 6,244 7,638 1,465 73,437 Cattle Marketing 37,537 5,531 924 5,591 433 0 261 694 0 50,971 Goat & Sheep Rearing 26,388 6,140 1,480 9,995 765 433 739 9,816 43 55,797 Goat & Sheep Herding 17,254 8,694 1,926 7,796 6,549 1,981 7,416 10,400 1,399 63,415 Goat & Sheep Marketing 31,570 4,950 1,005 5,239 539 0 342 841 140 44,626 Milking 3,297 1,561 37,336 4,593 1,035 388 2,060 3,726 0 53,996 Pig Rearing 1,622 582 282 691 125 43 123 633 0 4,099 Poultry Keeping 23,688 1,154 21,890 25,315 474 414 1,523 44,019 0 118,477 Collecting Water 13,802 3,209 104,317 16,505 1,475 7,846 11,485 16,225 269 175,134 Collecting Firewood 19,845 4,616 111,881 14,754 1,685 6,384 5,788 10,450 480 175,884 Pole Cutting 54,206 35,091 2,614 4,338 2,124 143 144 616 4,677 103,953 Timber Wood Cutting 2,885 4,472 0 735 0 0 0 0 168 8,260 Building / Maintaining Houses 62,937 32,313 3,062 19,233 1,754 267 185 7,864 5,586 133,200 Making Beer 7,653 1,571 48,381 1,901 42 208 0 143 0 59,899 Beekeeping 6,891 2,117 287 127 0 0 0 118 0 9,541 Fishing 5,449 351 0 271 461 0 43 0 0 6,574 Fish Farming 242 0 0 246 0 0 0 0 0 488 Off - farm Income Generation 60,093 3,460 22,367 42,522 3,511 1,733 955 2,532 155 137,328 31.1 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Activity Type of Household Member Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 293 Head of Household Alone Adults Males Adult Female Adults Boys Girls Boys & Girls All Household Members Hired Labour Total Land Clearing 31 11 4 40 1 0 0 12 2 100 Soil Preparation by Hand 22 6 6 49 0 0 0 15 1 100 Soil Preparation bu Oxen / Tractor 19 8 2 50 1 0 1 17 3 100 Planting 10 2 13 47 0 0 1 25 0 100 Weeding 8 1 3 50 0 0 0 34 2 100 Crop Protection 8 2 4 39 1 0 5 41 1 100 Harvesting 8 1 3 47 0 0 0 39 1 100 Crop Processing 10 2 52 20 1 3 4 7 0 100 Crop Marketing 60 6 4 26 1 0 0 3 0 100 Cattle Rearing 55 9 2 19 2 1 1 12 0 100 Cattle Herding 32 14 4 13 13 4 9 10 2 100 Cattle Marketing 74 11 2 11 1 0 1 1 0 100 Goat & Sheep Rearing 47 11 3 18 1 1 1 18 0 100 Goat & Sheep Herding 27 14 3 12 10 3 12 16 2 100 Goat & Sheep Marketing 71 11 2 12 1 0 1 2 0 100 Milking 6 3 69 9 2 1 4 7 0 100 Pig Rearing 40 14 7 17 3 1 3 15 0 100 Poultry Keeping 20 1 18 21 0 0 1 37 0 100 Collecting Water 8 2 60 9 1 4 7 9 0 100 Collecting Firewood 11 3 64 8 1 4 3 6 0 100 Pole Cutting 52 34 3 4 2 0 0 1 4 100 Timber Wood Cutting 35 54 0 9 0 0 0 0 2 100 Building / Maintaining Houses 47 24 2 14 1 0 0 6 4 100 Making Beer 13 3 81 3 0 0 0 0 0 100 Beekeeping 72 22 3 1 0 0 0 1 0 100 Fishing 83 5 0 4 7 0 1 0 0 100 Fish Farming 50 0 0 50 0 0 0 0 0 100 Off - farm Income Generation 44 3 16 31 3 1 1 2 0 100 Activity Type of Household Member 31.2 LABOUR USE: Number of Households by type of Household member and Activity during the 2002/03 Agriculture Year Tanzania Agriculture Census Survey 2003 Singida Region 294 Appendix II 295 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 296 District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 11,882 36,304 14,068 273 0 62,528 Singida Rural 9,510 35,326 25,735 1,791 835 73,197 Manyoni 8,195 10,762 11,131 2,000 978 33,065 Singida Urban 1,693 5,745 3,688 0 0 11,125 Total 31,280 88,137 54,621 4,064 1,813 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 1,232 5,718 23,977 11,408 20,193 62,528 Singida Rural 1,661 2,442 24,384 20,053 24,656 73,197 Manyoni 993 2,783 7,253 8,734 13,302 33,065 Singida Urban 681 282 3,928 5,686 549 11,125 Total 4,566 11,225 59,542 45,881 58,701 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 5,586 14,406 34,495 3,252 4,789 62,528 Singida Rural 3,748 15,517 39,001 8,044 6,887 73,197 Manyoni 6,948 7,009 11,943 5,193 1,972 33,065 Singida Urban 647 2,857 6,965 657 0 11,125 Total 16,929 39,790 92,403 17,146 13,648 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 282 255 9,151 8,931 43,909 62,528 Singida Rural 363 487 5,949 7,171 59,226 73,197 Manyoni 167 1,093 3,985 8,247 19,572 33,065 Singida Urban 0 108 4,051 6,118 848 11,125 Total 812 1,944 23,136 30,467 123,556 179,915 District Distance (Kilometer) to Hospital District Distance (Kilometer) to Health Clinic 33.4 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Hospital School and District, 2002/03 Agricultural Year 33.3 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Health Clinic School and District, 2002/03 Agricultural Year District Distance (Kilometer) to Secondary School 33.2 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary School and District, 2002/03 Agricultural Year 33.1 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary School and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 297 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 144 0 2,291 1,978 58,115 62,528 Singida Rural 122 0 2,342 235 70,498 73,197 Manyoni 168 85 763 4,010 28,038 33,065 Singida Urban 85 98 3,425 6,543 974 11,125 Total 520 183 8,821 12,765 157,625 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 430 141 430 711 60,816 62,528 Singida Rural 740 0 2,341 235 69,882 73,197 Manyoni 80 0 165 247 32,573 33,065 Singida Urban 33 140 3,435 6,544 975 11,125 Total 1,282 281 6,370 7,737 164,245 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 26,122 24,111 11,603 137 556 62,528 Singida Rural 25,961 29,013 16,325 1,057 841 73,197 Manyoni 16,281 12,524 3,925 334 0 33,065 Singida Urban 4,519 5,101 1,505 0 0 11,125 Total 72,882 70,750 33,358 1,528 1,397 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 19,816 17,288 18,627 2,137 4,660 62,528 Singida Rural 13,508 18,074 27,299 7,712 6,603 73,197 Manyoni 9,449 4,995 11,963 4,571 2,087 33,065 Singida Urban 2,386 3,915 4,825 0 0 11,125 Total 45,159 44,271 62,714 14,420 13,351 179,915 District Distance (Kilometer) to Feeder Road District Distance (Kilometer) to ALL Wealther Road 33.8 ACCESS TO SERVICES: Number of Agricultural Households by Distance to All Weather Road and District, 2002/03 Agricultural Year District Distance (Kilometer) to Districtal Capital 33.7 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Feede Road and District, 2002/03 Agricultural Yea 33.6 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Districtal Capital and District, 2002/03 Agricultural Year District Distance (Kilometer) to District Capital 33.5 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Distric Capital and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 298 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 15,128 144 429 0 46,827 62,528 Singida Rural 29,500 367 496 483 42,351 73,197 Manyoni 3,936 0 0 0 29,129 33,065 Singida Urban 8,034 151 587 590 1,764 11,125 Total 56,597 662 1,512 1,073 120,071 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 17,482 5,324 30,514 2,533 6,675 62,528 Singida Rural 11,921 13,204 26,607 9,016 12,449 73,197 Manyoni 3,030 3,977 17,925 5,279 2,853 33,065 Singida Urban 2,819 1,960 5,547 800 0 11,125 Total 35,253 24,465 80,593 17,628 21,977 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 3,303 3,008 38,308 10,099 7,811 62,528 Singida Rural 1,545 4,884 31,897 21,780 13,090 73,197 Manyoni 2,324 2,958 10,886 8,793 8,103 33,065 Singida Urban 4,055 0 2,759 3,310 1,001 11,125 Total 11,228 10,850 83,849 43,983 30,005 179,915 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Total Iramba 6,933 1,791 8,267 2,405 43,133 62,528 Singida Rural 1,956 539 3,752 3,205 63,746 73,197 Manyoni 495 734 2,409 5,856 23,571 33,065 Singida Urban 245 66 3,679 6,372 763 11,125 Total 9,629 3,129 18,107 17,839 131,212 179,915 District Distance (Kilometer) to Tertiary Market 33.12 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tertiary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Primary Market District Distance (Kilometer) to Secondary Market 33.11 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Secondary Market and District, 2002/03 Agricultural Year District Distance (Kilometer) to Tarmac Road 33.10 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Primary Market and District, 2002/03 Agricultural Year 33.9 ACCESS TO SERVICES: Number of Agricultural Households by Distance to Tarmac Road and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 299 <5 5 - 9 10 - 14 15 - 19 30 - 49 50 + Total Iramba 2,443 0 143 0 0 124 2,710 Singida Rural 34,812 123 0 0 616 858 36,409 Manyoni 2,708 0 0 0 0 85 2,793 Singida Urban 7,404 42 0 43 0 0 7,489 Total 47,368 165 143 43 616 1,067 49,401 <5 5 - 9 10 - 14 15 - 19 30 - 49 50 + Total Iramba 2,429 0 0 143 0 0 2,572 Singida Rural 36,183 244 123 123 371 488 37,532 Manyoni 2,962 0 0 0 0 0 2,962 Singida Urban 7,522 0 0 0 0 0 7,522 Total 49,097 244 123 266 371 488 50,589 <5 20 - 29 30 - 49 50 + Total Iramba 2,306 143 0 124 2,572 Singida Rural 35,681 125 125 373 36,304 Manyoni 2,708 0 0 0 2,708 Singida Urban 7,479 0 0 0 7,479 Total 48,174 268 125 496 49,063 <5 30 - 49 50 + Total Iramba 2,306 0 124 2,429 Singida Rural 35,323 618 739 36,680 Manyoni 2,708 0 0 2,708 Singida Urban 7,564 0 0 7,564 Total 47,901 618 863 49,382 District Distance (Kilometer) to Plant Protection Lab District Distance (Kilometer) to Research Station 33.16 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultura Households by Distance to Plant Protection Lab and District, 2002/03 Agricultural Year 33.15 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultura Households by Distance to Research Station and District, 2002/03 Agricultural Year District Distance (Kilometer) to Veterinary Clinic District Distance (Kilometer) to Extension Center 33.14 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Extension Center 33.13 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Veterinary Clinic and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 300 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Iramba 256 2,149 2,253 0 4,914 11,370 41,444 62,386 Singida Rural 1,565 1,841 834 120 11,560 31,525 25,264 72,710 Manyoni 243 510 1,605 2,733 1,793 7,243 18,938 33,065 Singida Urban 84 3,337 4,606 1,777 849 42 74 10,769 Total 2,148 7,838 9,298 4,630 19,116 50,179 85,720 178,930 <5 5 - 9 10 - 14 15 - 19 20 - 29 30 - 49 50 + Total Iramba 1,004 2,003 2,282 5,716 1,952 13,889 35,178 62,025 Singida Rural 35,556 246 246 0 125 36,044 610 72,827 Manyoni 2,723 0 0 0 0 30,342 0 33,065 Singida Urban 7,683 42 43 0 0 3,315 0 11,083 Total 46,965 2,292 2,571 5,716 2,077 83,590 35,788 179,000 Very Good Good Average Poor No good Not applicable Total Iramba 1,929 17,167 8,441 576 2,535 344,521 375,170 Singida Rural 1,570 1,213 3,643 13,580 21,515 397,660 439,181 Manyoni 723 417 587 254 0 196,408 198,389 Singida Urban 42 84 288 2,712 184 63,443 66,752 Total 4,264 18,881 12,960 17,121 24,234 1,002,032 1,079,492 Very Good Good Average Poor Total Iramba 105 124 0 0 229 Singida Rural 365 125 245 125 860 Manyoni 85 417 169 0 672 Total 556 666 414 125 1,761 District Satisfaction of Using Veterinary Clinic 33.20 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Extension Center District Distance (Kilometer) to Livestock Development Center 33.19 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year 33.18 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Livestock Development Center District Distance (Kilometer) to Land Registration Office 33.17 ACCESS TO LIVESTOCK STRUCTURES: Number of Agricultural Households by Distance to Land Registration Office and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 301 Very Good Poor Total Iramba 105 0 105 Singida Rural 241 249 491 Manyoni 78 0 78 Total 424 249 674 Very Good Good Poor No good Total Iramba 510 0 0 0 510 Singida Rural 471 123 722 123 1,439 Manyoni 255 0 0 0 255 Singida Urban 0 0 42 0 42 Total 1,236 123 764 123 2,246 Very Good Good Average Poor No good Total Iramba 527 9,226 4,363 144 1,268 15,529 Singida Rural 246 965 2,903 11,863 21,277 37,254 Manyoni 84 0 333 254 0 671 Singida Urban 42 84 245 2,627 141 3,139 Total 899 10,275 7,845 14,888 22,686 56,593 Very Good Good Average Poor No good Total Iramba 287 7,817 4,078 432 1,268 13,881 Singida Rural 122 0 370 0 0 493 Manyoni 143 0 0 0 0 143 Singida Urban 0 0 43 42 43 128 Total 552 7,817 4,491 474 1,310 14,644 33.24 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center District Satisfaction of Using Livestock Development Center District Satisfaction of Using Plant Protection Lab 33.23 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Satisfaction of Using Land Registration Office 33.21 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Satisfaction of Using Research 33.22 TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 302 Appendix II 303 HOUSEHOLD FACILITIES Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 304 District Number of rooms Iron Sheet Tiles Asbestos Grass/leaves Grass/mud Other Total Iramba 3 12,985 20.8 0 0.0 0 0.0 1,488 2.4 48,055 76.9 0 0.0 62,528 Singida Rural 3 15,651 21.4 125 0.2 236 0.3 4,343 5.9 52,230 71.4 612 0.8 73,197 Manyoni 3 6,031 18.2 81 0.2 167 0.5 3,610 10.9 23,176 70.1 0 0.0 33,065 Singida Urban 2 2,580 23.2 0 0.0 0 0.0 253 2.3 8,292 74.5 0 0.0 11,125 Total 3 37,246 21 206 0.1 403 0.2 9,695 5.4 131,753 73.2 612 0.3 179,915 Yes No Total Yes No Total Yes No Total Yes No Total Iramba 25,945 41 36,584 62,528 133 0.2 62,395 62,528 133 0.2 62,395 62,528 7,936 13 54,593 62,528 Singida Rural 23,577 32 49,620 73,197 364 0.5 72,833 73,197 1,096 1.5 72,101 73,197 8,958 12 64,239 73,197 Manyoni 16,050 49 17,015 33,065 0 0.0 33,065 33,065 84 0.3 32,981 33,065 3,758 11 29,307 33,065 Singida Urban 3,903 35 7,222 11,125 108 1.0 11,017 11,125 150 1.3 10,976 11,125 1,148 10 9,977 11,125 Total 69,474 39 110,441 179,915 605 0.3 179,310 179,915 1,463 0.8 178,452 179,915 21,799 12 158,116 179,915 Yes No Total Yes No Total Yes No Total Yes No Total Iramba 1,655 3 60,874 62,528 21,454 34 41,075 62,528 800 1.3 61,728 62,528 552 0.9 61,976 62,528 Singida Rural 4,665 6 68,532 73,197 18,667 26 54,530 73,197 366 0.5 72,830 73,197 121 0.2 73,075 73,197 Manyoni 1,280 4 31,785 33,065 10,909 33 22,156 33,065 255 0.8 32,810 33,065 85 0.3 32,980 33,065 Singida Urban 403 4 10,722 11,125 2,835 25 8,291 11,125 43 0.4 11,083 11,125 43 0.4 11,083 11,125 Total 8,003 4 171,912 179,915 53,864 30 126,051 179,915 1,464 0.8 178,451 179,915 801 0.4 179,114 179,915 cont….HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Bicycle District Television / Video Wheelbarrow Vehicle 34.1: HOUSEHOLD FACILITIES: Number of hoseholds reporting average number of rooms and type of Roofing Materials by District, 2002/03 Agricultural Year 34.2: HOUSEHOLD FACILITIES: Number of Agricultural Households reporting ownership of Assets by District, 2002/03 Agricultural Year Iron District Radio Mobile phone Landline phone Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 305 District Mains Electricity Solar Gas (Biogas) Hurricane Lamp Pressure Lamp Wick Lamp Firewood Other Total Iramba 0 0.0 144 0 10,745 22.3 2,386 48,118 992 1.6 143 62,528 Singida Rural 118 0.2 125 118 5,832 9.6 968 61,007 5,028 6.9 0 73,197 Manyoni 0 0.0 0 0 4,327 17.4 573 24,935 3,070 9.3 161 33,065 Singida Urban 0 0.0 0 0 678 7.0 403 9,635 410 3.7 0 11,125 Total 118 0.1 269 118 21,581 15.0 4,330 143,694 9,499 5.3 304 179,915 District Mains Electricity Solar Bottled Gas Parraffin / Kerocine Charcoal Firewood Crop Residues Livestock Dung Total Iramba 0 432 0 143 0.2 1,355 59,894 561 0.9 143 62,528 Singida Rural 373 124 103 0 0.0 1,228 67,855 3,513 4.8 0 73,197 Manyoni 0 85 0 0 0.0 412 32,483 85 0.3 0 33,065 Singida Urban 75 0 0 0 0.0 108 10,899 43 0.4 0 11,125 Total 448 641 103 143 0.1 3,104 171,131 4,202 2.3 143 179,915 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Other Total Iramba 12,223 7,144 285 20,133 1,566 16,574 286 18.2 2,749 1,568 62,528 Singida Rural 6,876 14,352 731 23,046 11,033 6,630 0 0.0 10,530 0 73,197 Manyoni 11,506 1,329 255 9,693 999 4,231 162 65.1 4,642 249 33,065 Singida Urban 1,156 4,437 277 3,421 762 735 0 0.0 337 0 11,125 Total 31,761 27,262 1,548 56,293 14,360 28,170 447 24.6 18,257 1,816 179,915 34.3: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Lighting by District, 2002/03 Agricultural Year 34.4: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Energy for Cooking by District, 2002/03 Agricultural Year 34.5: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 306 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Iramba 4,765 6,403 3,213 14,562 20,662 9,064 2,421 1,439 0 62,528 Singida Rural 5,153 5,007 2,686 19,011 30,124 7,304 3,416 495 0 73,197 Manyoni 735 5,516 2,754 7,141 10,045 4,387 1,825 579 83 33,065 Singida Urban 208 1,231 718 2,665 4,491 1,472 255 85 0 11,125 Total 10,861 18,157 9,370 43,379 65,322 22,227 7,917 2,598 83 179,915 District Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Iramba 3,085 11,438 3,863 22,796 3,487 1,689 16,169 62,528 Singida Rural 736 13,605 6,752 25,452 5,796 3,189 17,666 73,197 Manyoni 574 7,719 2,316 8,935 2,082 2,321 9,116 33,065 Singida Urban 124 1,706 1,605 4,461 1,047 126 2,056 11,125 Total 4,519 34,469 14,537 61,645 12,413 7,326 45,006 179,915 District Piped Water Protected Well Protected / Covered Spring Uprotected Well Unprotecte d Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Uncovered Rainwater Catchment Water Vendor Total HH Iramba 13,929 8,533 285 15,302 1,566 16,926 143 5,843 0 62,528 Singida Rural 8,236 16,787 608 25,727 12,065 4,658 363 4,633 120 73,197 Manyoni 12,676 1,327 332 11,845 1,466 3,363 78 1,979 0 33,065 Singida Urban 1,240 4,479 362 3,419 804 611 0 210 0 11,125 Total 36,081 31,126 1,587 56,292 15,900 25,559 584 12,666 120 179,915 District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Total Iramba 2,066 5,684 2,357 10,999 22,113 8,486 7,822 3,002 0 62,528 Singida Rural 2,798 3,913 1,586 12,095 25,516 11,981 10,650 4,040 618 73,197 Manyoni 160 3,448 1,853 5,507 9,705 5,144 3,031 3,964 253 33,065 Singida Urban 168 1,062 845 2,338 4,407 1,680 424 200 0 11,125 Total 5,192 14,107 6,641 30,939 61,741 27,291 21,926 11,206 871 179,915 34.9: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34.6: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.7: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Wet Season by District, 2002/03 Agricultural Year 34.8: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 307 District Less than 10 Minutes 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Total Iramba 1,107 7,107 3,008 16,109 3,037 1,407 30,754 62,528 Singida Rural 866 7,517 4,191 15,228 5,381 1,224 38,789 73,197 Manyoni 248 5,610 1,796 6,279 2,085 2,001 15,046 33,065 Singida Urban 41 902 1,104 3,267 1,379 259 4,173 11,125 Total 2,262 21,136 10,099 40,882 11,882 4,891 88,763 179,915 District No Toilet / Bush Flush Toilet Traditional Pit Latrine Improved Pit Latrine - hh Owned Other Type Total Iramba 1,183 280 60,799 266 0 62,528 Singida Rural 5,363 5,607 61,728 248 250 73,197 Manyoni 4,860 328 27,643 152 82 33,065 Singida Urban 833 790 9,333 128 43 11,125 Total 12,238 7,005 159,503 794 375 179,915 34-10: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water during Dry Season by District, 2002/03 Agricultural Year 34-11: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting type of TOILET the household normally use by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 308 District One Two Three Four Total Iramba 704 30,420 31,405 0 62,528 Singida Rural 3,474 58,471 11,014 237 73,197 Manyoni 973 21,265 10,744 82 33,065 Singida Urban 258 9,519 1,306 42 11,125 Total 5,409 119,676 54,469 361 179,915 District Not Eaten One Two Three Four Five Six Seven Total Iramba 17,581 21,534 15,431 6,189 1,128 257 142 266 62,528 Singida Rural 22,390 29,715 14,543 4,252 1,213 719 120 245 73,197 Manyoni 16,771 8,163 5,570 1,674 245 569 0 74 33,065 Singida Urban 4,487 3,361 2,197 490 506 42 0 42 11,125 Total 61,228 62,773 37,741 12,604 3,092 1,587 262 628 179,915 District Not Eaten One Two Three Four Five Six Seven Total Iramba 28,811 16,901 13,224 1,558 603 520 316 596 62,528 Singida Rural 26,527 23,590 10,377 5,508 3,028 2,628 827 712 73,197 Manyoni 28,469 3,064 1,040 0 0 161 0 330 33,065 Singida Urban 4,463 3,541 2,069 701 202 107 0 42 11,125 Total 88,270 47,096 26,710 7,767 3,833 3,416 1,143 1,681 179,915 34-12: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of meals the household normally has per day by District, 2002/03 Agricultural Year 34-13: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District, 2002/03 Agricultural Year 34-14: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Fish during the Preceeding Week by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region Appendix II 309 District Never Seldom Sometimes Often Always Total Iramba 16,052 23,248 3,497 8,186 11,545 62,528 Singida Rural 25,746 24,209 4,382 9,906 8,954 73,197 Manyoni 9,745 9,984 1,406 8,684 3,245 33,065 Singida Urban 3,519 3,585 361 2,928 733 11,125 Total 55,062 61,025 9,646 29,705 24,478 179,915 District Sales of Food Crops Sale of Livestock Sale of Livestock Products Sales of Cash Crops Sale of Forest Products Business Income Wages & Salaries in Cash Other Casual Cash Earnings Cash Remittance Fishing Other Total Iramba 2,577 12,554 557 13,065 2,393 3,935 2,735 16,918 6,445 633 717 62,528 Singida Rural 9,121 12,885 471 12,975 3,441 7,166 1,820 21,991 2,833 495 0 73,197 Manyoni 4,280 2,875 0 1,913 4,493 6,252 802 10,702 1,748 0 0 33,065 Singida Urban 411 1,316 211 1,149 1,429 1,819 170 3,670 822 85 42 11,125 Total 16,389 29,629 1,239 29,102 11,756 19,172 5,528 53,280 11,848 1,213 760 179,915 34-16: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Main Source of Income by District, 2002/03 Agricultural Year 34-15: HOUSEHOLD FACILITIES: Number of Agricultural Households Reportin the status of food satisfaction of the household during the Preceeding Year by District, 2002/03 Agricultural Year Tanzania Agriculture Census Survey 2003 Singida Region 310 APPENDIX III QUESTIONNAIRES Appendix III 311 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Appendix III 312 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Appendix III 313 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ 314 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 315 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 316 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 317 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Survival of Main Not applicable for children under 5 years of age Age (4) activity (9) (11) Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 318 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 319 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 320 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 321 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (1) (2) (5) (6) … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 322 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (a) of mix (c) (b) Crop (a) (acre) Total area Total area of mix (acre) (c) Crop Name (b) Name crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 323 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) (1) (2) (5) (6) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 324 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Ground Total no. Total ground Temp crop% Total area Name (acre) Crop of mix (ACRE) (ACRES) area of plants area/plant of plants (a) (b) (c) (d) (e) (f) Temp crop% Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 325 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP (kgs) Number of mature plants Quantity Stored (Kgs) Quantity Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (17) (12) (16) (14) (1) (2) (3) (4) (11) Harvesting & Storage Area Harvested (acres) (kgs) Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 326 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 327 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Total value of sold units (Tsh.) No of units sold (14) (4) (7) S/N Crop Total no of name Crop Code Units Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 328 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 329 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) (2) (5) (7) (1) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 330 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 331 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (2) (1) (3) Source No=2 Distance to -ance (5) (4) Source applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation Yes =1,No=2 for not using Reason Plan to use (2) (3) next year Source of Fin (1) (7) (8) (6) (3) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (acres) (4) (5) year (acres) Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 332 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 333 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Yes=1,No=2 Plan to use next year Reason for not using (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Source Used in Number Source Owned (2) (1) to indicate source use codes Source "a" (4) Equipment/Asset Name tick the boxes below to indicate the use of the credit Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 334 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 335 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… of trees Distance to com -munity planted (1) (2) 2002/03 (4) (6) (7) Code -ment (1) Tree forest (Km) Number purpose (5) Number of Poles Timber hh utilised (4) Main (2) (3) Main use during (3) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 336 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 337 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (1) (2) (3) (4) (1) (2) (1) (2) (1) (2) (4) (1) (2) (3) (4) (3) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 338 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 339 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases per head Helmenthioitis (2) Infected (7) (6) (6) (7) (1) (4) (3) Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (10) (5) -overed Number Treated Number Died No. Rec (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 340 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 341 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season (5) (6) (1) (2) (3) (4) Litres of milk/day No. of Goats milked/day Value/litre Sold to Sold/traded (5) (6) (7) (1) (2) (3) (4) Number died (5) (7) (6) Number given (8) /obtained parasite Infected Disease/ Number Number No. Rec Number Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) (1) (2) (3) (4) for meat Number of Improved Total Dairy Purchased Number given Number Total Intake Average Value of Goats per head (9) (10) (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Tetanus Mange (1) Total Goat Average value Offtake per head Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 342 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 343 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 per head (9) (10) Number Number No. Rec Number Number Number con Number given Number (6) for Mutton Dairy Purchased Number given Total Intake Average Value of Sheep /obtained away/stolen died Sold/traded (8) (7) (1) (2) (3) (4) (3) (4) Total (5) Number of Improved Number sumed by hh (5) (6) (1) (2) (7) (6) (7) Foot Rot (1) (2) (3) (4) (5) Infected Treated -overed Died parasite Average value Offtake per head Disease/ Total Sheep CC PP Helminthiosis Trypa nsomiasis FMD X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 344 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 345 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use (6) (7) Anthrax Helmenthiosis Anemia ASF Number Died (1) (2) (3) (4) (5) parasite Infected Treated (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Offtake per head (5) (3) died Average Value Increase per head (9) (10) Total Pig (4) Number Average value (1) (2) Sold/traded (1) (2) Number Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 346 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 347 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Consumed during 2002/03 (5) Number Average Value/head (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head (3) (4) Average Value/unit (2) (1) (6) (2) (4) Outlets for Sheep Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 348 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 349 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (5) (6) (1) (2) (3) (4) weight weight Size of unit/pond Number of Number of stocked fish fish harvested harvested sold of fish (m2) Tilapia Carp Other (11) (12) Mainly sold to of fish (7) (8) (9) (10) (1) (2) (3) (4) (4) (5) (3) (6) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 350 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 351 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (2) Distance in Km permanent employment/off farm temporary employment/off farm (2) (3) (1) (2) (4) (3) (1) (1) (2) (3) (4) Type of service (1) Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 352 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 353 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 354 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 355 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches kg/acre 35000 40000 50000 30000 40000 50000 25000 70000 150000 100 10000 1000 1400 25000 20000 7000 50000 20000 30000 5000 10000 10000 400 60000 800 500 2500 200 0 0 0 0 20243 12146 16194 14170 0 10121 28340 16194 0 60729 0 20243 4049 405 567 0 0 0 10121 40 0 0 0 0 0 0 0 0 0 0 2834 0 0 0 8097 12146 2024 8097 4049 0 4049 20243 0 0 24291 0 202 1012 81 162 0 0 0 324 0 0 0 0 0 0 0 0 1417 2024 3239 24 24291 607 810 0 405 1619 1012 304 810 607 1619 688 0 526 709 0 3441 4049 2024 0 4 2530 1619 1417 1215 1012 1822 931 2834 3239 0 324 486 810 121 10121 121 202 243 121 243 526 0 243 202 243 0 0 162 121 243 304 1619 1012 121 486 567 1215 486 283 304 142 3500 5000 8000 60/tree 60000 1500 2000 1000 4000 2500 750 2000 1500 4000 1700 1300 1750 8500 10000 5000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 800 1200 2000 300 25000 300 500 600 300 600 1300 600 500 600 400 300 600 750 4000 2500 300 1200 1400 3000 1200 700 750 350 Average Max Max Max kg/ha Average Max kg/acre kg/ha 356 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Number of Kgs Number of Kgs Standard Non-standard Standard Non-standard Bag Tin kgs Bag Tin kgs For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content Southern Maasai Agropastoral Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Southern Maasai Agro-Pastoral1 Livelihood Zone (TLZ 01) February, 20162 Zone Description The Southern Maasai Agropastoral Livelihood Zone covers an extensive area in north eastern Tanzania, including much of the traditional Maasai grazing lands. The administrative units that make up this zone include Simanjiro and Kiteto districts in Manyara Region; parts of Same and Mwanga districts in Kilimanjaro Region; and Kilindi District in Tanga Region3. The main ethnic group living here is the Maasai. The population density is only around 7 people per km2; so although this is a large zone geographically, the population that makes up the zone is relatively small compared to the rest of Tanzania. This livelihood zone consists of lowland plains, found between 400 and 600 meters, and covered with acacia- commiphora woodlands, grasslands and thickets. Extensive plains dotted with acacia trees are typical, and the Maasai who live here share their land with large herds of wildlife, concentrated especially in the Tarangire National Park and the Makame Wildlife Management Area. The Pangani River runs through the zone on its way to the Indian Ocean, providing year-round access to water for those who live close by. Tanzanite mines, found to the north of the zone, have been a source of cash income for some within the area over the past several decades; and there is some traditional mining of green tourmaline in isolated parts of Simanjiro District. This semi-arid expanse has been the home of Maasai pastoralists for centuries. The two rainy seasons – the vuli from November to January and the masika from March to May - generally bring no more than 500-650 mm of rainfall combined. Droughts are not uncommon, occurring on average once every three years. Crop production is a relatively new phenomenon here, dating back to the late 1970s when pastoralists were encouraged to settle and cultivate as part of the national villagisation programme, which came about as a result of the Ujamaa policies of the Arusha Declaration. Pastoralists began cultivating in earnest in the 1990s when terms of trade between livestock and grain became increasingly unfavourable, and when increasing land pressure related to a period of intense land grabbing by large multinational interests led the Maasai to 1 The original name of this zone was the Southern Maasai Pastoral Livelihood Zone; after the field work completed in this phase the team members have suggested re-naming it the Southern Maasai Agropastoral Livelihood Zone to convey the large role agriculture now has. 2 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 3 The livelihood zone boundaries should be redrawn to exclude some of the southern parts of the zone, in particular Sunya and Dongo wards, which do not share many of the characteristics described in this profile, and are more agricultural than pastoral. Southern Maasai Agropastoral Livelihood Zone Profile 2 stake their claims by beginning to cultivate large tracts of land. As it became more and more profitable to grow maize and beans on their land, the local population began to see this production as a means of protecting and increasing their herds, since the more of one’s own food one produced, the fewer animals needed to be sold to secure food4. Livestock production still forms the foundation of the local economy. Huge herds of cattle, goats and sheep are sustained here, grazing freely, and also benefitting from crop residues after the harvest. Households also grow maize and beans, both entirely rain-fed. The soils are fertile, consisting of sandy loams and clay, and people here do not use fertilizers or even manure. When clearing new fields all wealth groups use hand hoes and fires. Land is prepared by hand amongst the poorer wealth groups and using hired labour or by tractor for better off households. Ox ploughs are generally not used. The most labour intensive activities include land preparation, weeding, harvesting and fence making (with the branches of thorny acacia trees) to protect crops from wild animals. For these tasks middle and better off households hire members of poorer households to work for them in their much larger fields. Some labour (generally men from poor families) also migrates into the zone from Singida and Dodoma. Managing large herds in addition to large tracts of land creates a steady demand for seasonal labour. Livestock provide a critical source of food and cash for all households. Cattle are at the centre of the local economy and are critical to Maasai culture, binding families together through marriage and labour relations, and providing the currency by which people’s status is measured. Cattle provide milk for consumption and sale and they are a sort of bank account, drawn down on every year to provide cash for a range of basic necessities. Goats and sheep are also kept here, eaten especially during the festival season (from July through September) and when women give birth. They are also sold for cash income when smaller amounts of cash are needed. Chickens are used for eggs, eaten throughout the year, and they are sold whenever cash is needed. Rainy season water sources for livestock include seasonal ponds and rivers as well as shallow wells dug in seasonal river beds. In the dry season, livestock rely on village taps and shallow wells. Middle and better off households pay to keep the pumps going that keep this water flowing; and they also pay to transport water for their livestock. Men are responsible for taking care of cattle, goats and sheep, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots and fewer livestock, depend on seasonal agricultural labour - land clearing, ploughing, planting, weeding and harvesting - to generate cash income. They also piece together supplemental cash resources in the dry season collecting and selling poles for building, or engaging in petty trade – buying and selling small commodities like tobacco, soda, salt and sugar. This livelihood zone is far from urban centres and service provision here is poor. Water is obtained from open wells and ponds which are almost never clean or safe. Village taps, which require a fee, are used by some. In the dry season middle and better off households pay to pump and transport water from wells. Sanitation facilities consist of uncovered pit latrines; there is no organized garbage collection. There are very few health dispensaries, and even those that exist are not well stocked. People turn to traditional healers (called wakunga) in the absence of more modern alternatives. Primary schools are found in the villages, but these are 7-12 kilometres away for many people. Secondary schools are available in the ward centres, which are even more distant. There is no electricity in this zone. Households depend on battery-operated torches and solar lanterns for light. Households in all wealth groups have mobile phones, with better off households having multiple phones, although the cellular network is quite bad. People do not have access to credit here. In some villages, including Makame, Naberere, Emboret and Sukoro a savings scheme is available, providing households with a small return at the end of the year on weekly set-asides. A number of NGOs operate here, including Urban Crust Support, which provides a focus on education, health facilities and water infrastructure; UCTR, helping with land management; and the Heifer Project, supporting livestock production and especially poultry. 4 Boudreau, T., Household Food Economy Assessment, Arusha Region, Save the Children, 1999 Southern Maasai Agropastoral Livelihood Zone Profile 3 Markets The transportation infrastructure in this zone is relatively poor. The zone is far from urban centres and roads are few and far between. The main roads link the zone to Arusha via Simanjiro and Kiteto; further connections are made to Kijungu, Sunya and Songe in Kilindi. Rough dirt roads provide access to vehicles during the dry season, but these are washed away in the wet season, when even main roads become impassable. There are no bridges and rafts are used to cross the Pangani River in spots where people are unable to wade across. Well-worn dirt tracks take people by foot from villages to cultivated fields, pastures and water points. Donkeys are owned by all households, and these are used to carry goods and people. Motorbikes are the other main means of transportation, but these are owned by only better off households. Maize, beans, cattle, goats and sheep are the commodities sold by households in this zone. Crops are bought up at the farm gate by traders who flock to the area in the post-harvest months, from August to September. These traders arrange for crops to be transported out of the zone on trucks, which can travel on the dirt roads in the dry season. Maize makes its way to Kibaigwa in Dodoma Region and then on to other countries in the region, including Kenya, Uganda, Ethiopia, Rwanda and Sudan. Beans are transported to Arusha or Dodoma first and then on to Dar es Salaam. Cattle, goats and sheep are sold at small weekly ward- and sub-ward level markets within the zone throughout the year. Traders collect large numbers of animals near the road and then truck them on to their final destination. Dar es Salaam is the terminal market for most of the livestock. In addition to the market for commodities supplied by households from the zone, there is a market for food brought into the zone for consumption by local households. Poorer households need to buy maize grain to cover their needs for four to nine months of the year, even in good production years. Maize is the cheapest local staple, and most of this is locally sourced, procured from better off households who generally produce a large surplus. Rice, purchased almost exclusively by the upper wealth groups, is sourced from Shinyanga or Mbeya Region (Kyela) or Morogoro Region and distributed via the Dodoma market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks, often owned by poor or middle households. The labour market is almost entirely local. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms. An additional 5% of labour demand came from local towns and the final 5% came from outside the livelihood zone. Both men and women from poorer households take on paid agricultural work. There are three peak periods of labour demand: November through February for land clearing, land preparation and planting; February through April for weeding; and June through August for harvesting. Demand for labour is so high that there is some labour migration into the zone from other areas to help with ploughing and weeding. A small number of people also find work outside the zone, in the Tanzanite mines in Mereran. In bad years, the demand for local agricultural labour especially for weeding and harvesting, contracts. As a result, people try to find additional work in other zones, or in the mining area. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Southern Maasai Agropastoral Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the planting season in November/December and ends with the harvest in March-June of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average Southern Maasai Agropastoral Livelihood Zone Profile 4 rains, average crop yields and normal food prices. The reference year, however, followed three below average years, and so the baseline information presented in this profile, provides a view into how households in this livelihood zone make ends meet in an average year, but in the process of recovering from a series of below average years. Production Year Rank Critical Events 2014-2015 2 Below average crop and livestock production; high staple food prices and low livestock prices. Increased reliance on livestock sales, casual labour and labour migration. 2013-2014 3 Average rains, average crop yields, average food prices 2012-2013 3 Average rains, average crop yields, average food prices 2011-2012 2 Poor crop and livestock production, high staple food prices, low livestock prices. Increased livestock sales, increased reliance on casual labour and labour migration. 2010-2011 2 Poor crop and livestock production, high staple food prices, low livestock prices. Increased livestock sales, increased reliance on casual labour and labour migration. 2009 - 2010 1 Drought, high staple food prices, no crop harvest. Livestock diseases were rampant; livestock body condition was poor. Abnormal migrations took place, along with high livestock sales, reduced meals, and increased labour migration. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Rainy season r r r r r r r r r r r r Crops Maize - rainfed gh gh gh gh h h h h h h lp lp lp lp p p w w w w Beans w w gh h h h lp lp lp lp p p p p Livestock Cattle milk peak m m m m m m m m m m m m Goats milk peak m m m m m m Peak livestock sales salesalesalesalesalesale Peak livestock purchases 6 6 6 6 Livestock diseases 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 Petty trade peak 4 4 4 4 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Dec Jan Feb Mar Apr May Oct Jun Jul Aug Sep Nov Southern Maasai Agropastoral Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Arusha Region based on a recent 10-year period (2005 – 2014) Source: TZ Meteorology Department There is one long rainy season in this livelihood zone, starting in November and lasting through May, although a short dry spell in February often interrupts the rains. Milk production is highest in the wet season, when cattle and goats give birth, and when fresh pastures and water sources provide animals with the nutrients they need for lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Land preparation (clearing and ploughing), with poorer households cultivating by hand, using hand hoes, axes and machetes, and the upper wealth groups often using tractors, starts in November for maize and beans and lasts two months. Maize is planted in January, once the rains have been fully established and beans are planted in February and March. The weeding period begins in February for maize and as late as April for beans. January through March are especially labour-intensive times of the year and all poorer households have at least one member working on the larger farms of middle and better off households. The weeding period coincides with a time when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as October or November and by January none of the poorer households have their own food stocks left at home. These households need to purchase all of their staple foods just when the price of staple foods is highest (from November through February). This is one reason that livestock sales peak from December through February. Another reason is that households need to pay school fees in these months, and better off households need money to pay for labour and other productive inputs. Thus, demand for labourers from middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize comes in. The main harvest period starts in June for maize and June/July for beans. Crop sales are highest in the post- harvest months. June through October is the dry season. Early in the dry season is when the festival season occurs, since cash from crop sales and full granaries provide a sense of relative plenty. Poorer households take advantage of the post-harvest dry season, when they are no longer engaged in agricultural labour, to increase petty trade activities and the collection and sale of building poles. They also find odd jobs locally, helping repair huts or provide construction labour. People need to set aside money at this time to prepare for the costs associated with the coming agricultural season and to pay back any loans accrued in the past year. Wealth Breakdown In Maasai communities, cattle ownership and family size are the major determinants of wealth. The more cattle a man owns, the more wives he is likely to marry, the more children he tends to have and the bigger his boma.5 The Maasai term which applies to a rich boma, Orkasis, combines material wealth with status, and effectively means that you have a lot of cattle and a lot of children. Ortajiri is a term used for those who have a lot of cattle but a small family, in which case, although food secure, the boma is not really ‘rich’ in local terms, 5The boma is the fundamental economic unit in Maasai society. A boma is a physical settlement comprised of a man, his wives, their children and their associated livestock. Southern Maasai Agropastoral Livelihood Zone Profile 6 and is not viewed as prestigious by the community6. Not just status, but significant economy advantages can accrue with having a large family. Children provide an important pool of labour for the many tasks associated with both crop production and managing large herds of livestock. In addition, when girls marry, their parents are paid in cattle; and older sons may earn money through mining or other means that gets channelled back into the boma. Thus a better off boma may be comprised of up to six wives, each of whom has 7-9 members in her hut; whereas a very poor boma would have just one wife with 6-8 family members. Note: The percentage of household figures represent the mid-point of a range. The livestock numbers are per wife. The man owns the boma’s cattle and he distributes them among his wives, for her use. The livestock numbers in the chart above refer to the average number of livestock per wife. Thus, it is not surprising for a better off household to be in possession of over a thousand cattle if he has five wives, each with 200 cattle. Very poor households, on the other hand, have almost no livestock by Maasai standards, and are just barely scraping by. A secondary factor in determining wealth here is the total amount of land cultivated by the household. This is related largely to the amount of labour the household can draw on, both from within the household and by hiring. Only middle and better off households hire labour, and they are also in a position to rent or own tractors, which significantly increases the area under cultivation. Poorer households cultivate by hand and do not have the cash to hire extra labourers during the critical crunch periods, such as planting and weeding. As a result, poor households generally only cultivate around 1 -3 acres, whereas better off households cultivate 5 – 15 acres. The distribution of wealth in this zone is fairly even. Very poor (25%) and poor (30%) households together comprise just over half of the households in the zone. Middle (30%) and better off (15%) households combined represent just under half the population. However, as middle and better off households are larger, with multiple wives and more members per wife, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is much larger. Intra-community redistribution and support is an important aspect of Maasai culture. The redistribution that takes place via the local agricultural market is one way this support is channelled. Poorer households are also provided with gifts of food in the form of milk, meat and grain, even in good years. In bad years, this support can be life-saving. 6 Boudreau, T., Household Food Economy Assessment, Arusha Region, Save the Children, 1999 Southern Maasai Agropastoral Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Livestock, which are the basis In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. of the household economy, are also fundamental to the household diet in this zone. Milk and meat from households’ own livestock bring in a substantial portion of required calories over the year. Own crop production, purchased food and gifts (for those on the lower end of the wealth spectrum) provide the remaining calories. The traditional Maasai pastoral diet used to be comprised of milk, purchased grain, meat and (occasionally) blood. Over the past thirty years, the diet itself has not changed much, but the balance in how people source their food in years with relatively good rainfall has shifted away from purchased grains and towards their own production. In the reference year - which was deemed by community leaders to be an average year – the calories supplied by households’ own crops accounted for 35-65% of minimum food energy requirements. Most of this was from maize, planted during the masika season; and the rest was from beans. A typical very poor household, cultivating around two acres of land was able to produce around 870 kg of maize and 210 kg of beans. On the upper end, better off households, cultivating around 10 acres of land, generated around 3,180 kg of maize and 1,000 kg of beans. Households sold between 40% and 60% of the maize they produced, generating an important source of cash income. All three of the upper wealth groups also sold a good portion of their beans (50-70%), with this proportion increasing with wealth; it was more common for very poor households to consume rather than sell their beans. Whereas maize and beans provide a large proportion of the calories for households in this zone, milk is still a critical part of the diet, both in nutritional and in cultural terms. Milk provides a primary source of food for young children and all members of the household continue to drink large amounts of it (both fresh and curdled), especially in the wet season, when yields are high. The contribution of milk to the household food basket increases with wealth, since wealthier households are, by definition, those with larger herds. Food is managed at the household level, with each wife allocated a particular number of cattle which provides milk for her children and other household members. Very poor households rely on the milk from around 2 cows and 6-7 goats; poor households have around twice that number of cows; middle and better off households have between 12 and 18 cows milking, and 16 to 18 goats milking. On average, cows here (which are the Zebu variety) produce 2 litres of milk a day during the first rainy season (lasting around four months) and 1 litre of milk a day in the second season (which lasts around two months). Goats yield only around ¼ of a litre a day and lactate for a period of around 2 months. When added together, these sources of milk generated around 700 litres of milk for very poor households and as much as 5,640 litres of milk for better off households during the reference year. Some of this milk was sold by households in the top three wealth groups, but the milk that was consumed accounted for around 10-40% of the calories required by households. Meat (from animals that were either Southern Maasai Agropastoral Livelihood Zone Profile 8 slaughtered or died naturally throughout the year) contributed an additional source of food, especially for middle and better off households, for whom it covered 10-20% of their minimum food needs. The market accounted for almost all the remaining calorie needs of households, comprising around 17-47% of the reference year’s food basket. Those in the upper two wealth groups bought less (17-19% of minimum calories) than those in the bottom two wealth groups (34-47% of minimum calories). This is, in part, because the poorest wealth group did not produce enough of its own food – either in the form of crops or milk and meat, to cover all of its calorie needs, even though it was a relatively good year. Poor, middle and better off households, on the other hand, could have feasibly met all their calorie needs with their own crop production if they had not sold any of their harvests or milk. If very poor households had not sold any of their crops, (they generally do not sell milk) they would have been left with a deficit of over 20% of minimum calorie requirements (assuming no gifts). On the other hand, poor households in the same scenario would have had a surplus of over 20% of minimum food needs; and a typical middle household produced 135-140% of minimum calorie requirements in the form of food, with an additional 45% of minimum calorie requirements produced in the form of milk. Finally, a typical better off household produced 208% of minimum calorie requirements in the reference year in maize and beans and 68% of minimum calorie requirements in milk. Nevertheless, all households sell part of their harvests in average years in order to meet their cash needs, which means that those in the two bottom wealth groups, have a real food deficit (after sales) that needs to be met with purchased food. This is supported by the observation that these two wealth groups bought 18-35% of their calorie needs in the form of maize grain. Middle and better off households did not buy any maize at all, rather buying food to add variety to their diet, including rice, beans, sugar, and oil. Finally, providing assistance to poorer relatives is part of a long tradition of community assistance that forms a vital part of Maasai culture. Gifts of food (mainly milk and meat) made up 2-8% of minimum calorie needs for poor and very poor households during the reference year. Sources of Cash Income As shown in the graph to the right, there are two main sources of cash income in this livelihood zone: crop sales and livestock sales; and because poorer households do not have enough crops or livestock to meet all of their cash requirements, they supplement these by working on local farms and by engaging in various other self- employment activities. The income profiles for the better off and middle households are similar in terms of the relative importance of each source of cash. What differs is the absolute cash income, with the average better off The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 7 1,360,000 – 1,900,000 1,900,000 – 4,000,000 4,000,000 – 7,000,000 5,500,000 – 13,930,000 7 The average exchange rate from April 2014-March 2015 was 1 USD = 1,800 TZS Southern Maasai Agropastoral Livelihood Zone Profile 9 household’s annual income in the reference year around 50% higher than the average middle household’s. This is due mainly to a difference in livestock sales; better off households sold, on average, around 14 cattle during the reference year, whereas middle households sold around 9. Because it was an average (and not a bad) year, cattle were sold by the upper wealth groups primarily to maintain a desirable herd composition. A typical Maasai herd is composed of more than 50% adult females in order to maximize milk production and livestock reproduction rates. The majority of steers are sold off each year, along with old bulls and unproductive females. Thus, the larger the herd, the more cattle that need to be sold to maintain a balance in favour of productive females. This helps explain the high cash incomes seen in this livelihood zone, and it explains why better off households bring in much higher cash incomes than their poorer neighbours. In bad years, when more cash is needed, additional livestock may be sold to generate cash to balance out a loss in crops or to destock in the face of pasture loss. In addition to cattle, all households sell goats, sheep and chickens. The income from chickens is quite marginal, bringing in less than 5% of annual income from livestock for most households. But sheep and goats combined accounted for 17-35% of livestock income in the reference year. In relative terms, sheep and goats are more important for the poorer two wealth groups (making up 30-35% of livestock-based cash income) than for the upper two wealth groups (making up 17-19% of livestock-based cash income). Sales of goats and sheep allow poorer households to generate cash income without selling cattle, allowing these poorer households to focus on building their herds while still helping them meet basic needs. Owning cattle also provides households with the opportunity to generate cash income from milk sales. Milk sales alone accounted for around 14% of the annual cash income for middle households. Poor households benefitted far less from milk sales and better off households simply did not need to go to the trouble given their other income sources. Very poor households did not produce milk for sale, but they did sell eggs. The income from egg sales, however, was negligible, barely showing up on the graph above. All households also sold maize and most sold beans in the reference year. Crop sales combined accounted for 15%, 16%, 15% and 21% of annual cash income for very poor, poor, middle and better off households, respectively. Maize was the more important of the two crops sold, generating 55-100% of crop-based cash income. Very poor households sold no beans at all, consuming what they grew instead. Beans are more valuable on a per kilogram basis than maize, so this balance between maize and bean sales is something that is likely to shift in bad years, with a greater emphasis on sales of beans (a high value crop) in order to fund the purchase of maize when the maize crop fails. Very poor and poor households do not have enough livestock, nor do they generate enough of their own crop production to cover all of their cash needs during the year, so they fall back on seasonal agricultural labour and self-employment or petty trade to help them fill the remaining gap. Seasonal agricultural labour and self- employment combined accounted for around 40% of the annual cash earned by very poor households in the reference year; and agricultural labour and petty trade covered just under 30% of the cash earned by poor households in the reference year. Planting and weeding periods are quite labour intensive, and better off households, who have 5-15 acres under cultivation typically hire poorer household members to help them with these tasks. Poorer households typically had at least one, and sometimes two, members working in the fields of middle or better off households during three months of the cultivation and weeding months. They provided labour again during harvesting times. In addition, very poor households sold building poles, helped build huts and fences and found other ways to earn cash during the dry season. At the same time, poor households were more likely to be engaged in petty trading activities, buying and reselling commodities such as tobacco, soda or household goods, generating a small margin of profit in the process. Southern Maasai Agropastoral Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As indicated in the graph, households here need to spend money on a range of essential items and services throughout the year, including: food (both staple and non-staple), household items, productive The graph provides a breakdown of total annual cash expenditure according to category of expenditure inputs, social services, like schooling and health, as well as clothing and other miscellaneous items. The patterns shown in the graph above highlight a number of points. First, even in a normal year like the reference year, very poor households must devote a relatively large proportion of their annual cash to meeting immediate food needs, with the proportion of annual cash spent on staple foods highest for very poor households. In the reference year, households in the very poor wealth group bought around 35% of their minimum calories in the form of maize grain, the cheapest staple. The amount of maize grain purchased by poor households covered around 18% of their minimum calories; middle and better off households did not purchase any maize grain at all. What shows up on the graph as ‘staple food’ for these wealth groups is actually rice and some oil. Without this purchased maize grain, the two poorer wealth groups would have been facing a food deficit. All households also spent money on non-staple foods, such as sugar and rice. Sugar is used in relatively high amounts here, with around 1-2 kg of sugar purchased by all households every week. Second, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. Households tend to pay for these items week by week in incremental amounts. Within this category, poorer households spent the most money on payment for grinding, followed by soap. These two items alone comprised 50-55% of the inputs budget for poorer households in the reference year. Better off households spent the most on soap followed by grinding. On an annual basis, spending on basic household goods comprised 6-15% of total expenditure, generally decreasing as a proportion of annual expenditure as wealth increases. Third, poor middle and better off households, invest a large proportion of their annual cash in productive inputs. This investment is shown as ‘inputs’ on the expenditure graph above, and includes the following: livestock drugs, water for animals, ploughing, seeds and tools, labour, livestock purchase, and phone credit. Of these items, the poorer two wealth groups spent the majority of their money on livestock drugs, followed by livestock purchases. Poor households were distinct from very poor households in their heavy investment in ploughing (spending sixteen times more than very poor households on this item and 25% of their inputs budget), which highlights a determination to use their resources to maximum effect with the aim of moving up the wealth spectrum. More crop production ultimately translates into bigger herd sizes, since having more of one’s own- produced food reduces the need to sell cattle to buy food; and more crop sales can also fund livestock purchases. Again, this divide between very poor and poor households is highlighted with the difference made in livestock purchases, with poor households spending around four times more than very poor households on Southern Maasai Agropastoral Livelihood Zone Profile 11 buying new livestock in the reference year. Middle households spent the most on livestock purchases – even more than better off households. In relatively good years, like the reference year, the herds of better off households are big enough to ensure a rapid rate of increase through natural reproduction, so their livestock purchases are not as high; middle households, on the other hand, need to augment the rate of increase afforded by natural reproduction with purchases if they want to build herds quickly. Better off households had to invest large amounts of cash into livestock drugs (which took a full third of their inputs budget in the reference year), labour for their fields (which took a fifth of their inputs budget), and water for their livestock (accounting for an additional fifth of this budget). Having larger herds and more land generates a high income, but it also requires enormous investments. Fourth, spending on water for human consumption for middle and better off households is notable. These households in the upper two wealth groups incur costs associated with pumping from dams and shallow wells and paying others to transport water to their bomas by cart. The poorer two wealth groups fetch water themselves, and they generally do not incur costs for pumping because they get their water for free from better off and middle households. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, poor households spent around the same on education as very poor households, whereas middle households spent around 1.5 times more than very poor households, and better off households spent almost 2 times more than the poorer two wealth groups. This additional expenditure reflects the fact that poorer households are usually not able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school. Secondary schools are found only at ward level, which creates costs that are prohibitive for poorer households, including things like transportation, boarding, higher fees and more expensive uniforms and supplies. On health care, better off households spent more than three times as much as very poor households on a per capita basis, indicating that these households may have had access to better clinics. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation (including fuel and service for motorbikes) and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. Hazards There are a number of hazards that affect this zone on a regular basis. The first is crop pests and diseases. Stalk borers, which affect maize; and American bollworm, pollen beetles and yellow blight, which affect beans, cause problems throughout the zone almost every year. The second chronic hazard is livestock disease, such as East Coast fever anaplasmosis, babesiosis, ormillo and trypanosomosis, affecting cattle, sheep and goats, as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively8. Helminthiasis (worms) is also a common problem, along with New Castle Disease, which can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. Wild animals and human diseases are additional challenges faced every year in this zone. The main, and most devastating, periodic hazard is drought, which leads to severe crop failures, degradation of pastures, drying up of local water sources and spikes in food prices. Although pastoralists in this area have been coping with cyclical droughts throughout centuries, and build up herds in good years as a means of insurance 8 http://www.lrrd.org/lrrd26/8/swai26138.htm Southern Maasai Agropastoral Livelihood Zone Profile 12 during bad years, the loss of mobility and access to grazing areas over the past half century puts limits on the capacity of people here to manage droughts as effectively as they once did. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. One of the reasons the Maasai maintain large herds is so they have a buffer in bad years. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Better off households tend to be in a fairly comfortable position in this regard, with large numbers of excess livestock to draw down on. However, it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally (working in many cases in direct exchange for food) or migrating outside the zone. In particular, people may go to the Tanzanite mines to find more work in a bad year. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Poorer households also turn to better off relatives and neighbours for help. Community assistance is a vital part of Maasai culture and internal re-distribution mechanisms provide an important means for poorer households to make it through bad years. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Southern Maasai Agropastoral Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Beans – amount produced Maize – producer price Beans – producer price Livestock production Cow milk – yields Own meat – amount produced Cattle – herd size Goats – herd size Sheep – herd size Chickens – numbers Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Chickens – producer price Southern Maasai Agropastoral Livelihood Zone Profile 13 Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Demand for building poles Petty trade – volume of trade Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Prices of building poles Petty trade - margins Expenditure Maize grain – consumer price Vegetable oil – consumer price Sugar – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve access to and availability of safe and reliable water supplies for humans and animals 2) Improve access to more reliable supplies of drugs and improve health services 3) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 4) Offer subsidies to poorer households on agricultural and livestock inputs to enable them to invest more easily in their production. 5) Develop and implement land use policies that can help protect communal grazing and agricultural lands. 6) Develop and support the infrastructure to enable the proliferation of reliable and fair markets for crops and livestock 7) Improve road infrastructure and invest in maintenance of existing roads 8) Provide electric service throughout the zone 9) Facilitate access to agricultural loans with affordable interest rates for appropriate beneficiaries 10) Improve communication networks/infrastructure 11) Provide means for building cattle dip tank 12) Experiment with alternative income projects, such as bee hives, for poorer households 13) Improve security with establishment of a police post | false |
# Extracted Content Tanga Maize and Cattle Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Tanga Maize and Cattle Livelihood Zone (TLZ 03) February, 20161 Zone Description The Tanga Maize and Cattle Livelihood Zone comprises a very small area in Tanga Region along the north eastern border with Kenya. The administrative units that make up this zone include Mkinga and Lushoto districts, encompassing Mwakijembe, Mng’aro and Lunguza wards. The main ethnic groups living here are the Maasai, Sambaa, Digo, Duruma, Taita, Kamba and Mbugu. The population density is only around 1.2 people per km2. This is a small zone both in geographical coverage and in terms of total population. Despite its small size, the zone is diverse in terms of livelihood patterns. In some villages, such as Mng’aro, Mazinde and Lunguza, there are irrigation schemes which allow households to cultivate rice and plant in three seasons (vuli, masika and utagata – recessional cropping). A further difference discerned by the field teams was that in Lushoto District the main season was associated with the vuli rains, whereas in Mkinga District the masika rains were primary. The profile below describes a generalized pattern for villages where there was no irrigation. The seasonal production shown below is balanced between both seasons, but it should be borne in mind that one harvest will be more prominent than the other depending on the district. It is likely that this zone is an extension of a larger zone in neighbouring Kenya. This livelihood zone consists of lowland plains, found between 100 and 200 meters, and covered with grasslands and thickets. The Umba River runs through the zone, originating in the Usambara Mountains and emptying into the Indian Ocean just across the border in Kenya. The mouth of the river marks the eastern- most point on the border between Kenya and Tanzania. Along the river, the Umba River Game Reserve is found, and the Mkomazi Game Reserve is also found in close proximity to the zone. Green granite is mined by a few households here, although it is not a typical source of cash income. Another natural resource found here – wood – is collected by most poorer households and sold either as firewood or turned into charcoal and sold. Rains come in two distinct seasons - the vuli from November to January and the masika from March to May; annual precipitation is around 600-1000 mm. Soil fertility is low, and although rainfall is generally adequate, production, which is almost entirely rain-fed, is not very high. Maize is the primary, and only, crop of any consequence grown by local households. Poorer households prepare the land with hand hoes, while middle and better off households generally use ox ploughs and sometimes tractors. All households cultivate maize 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in June 2014 and ended in May 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. Tanga Maize and Cattle Livelihood Zone Profile 2 in both seasons, staying busy throughout most of the year with farm-based activities. The most labour- intensive activities are land preparation and weeding. At these times as well as during the planting period, households with larger tracts of land hire those with less (both men and women) to work in their fields. Payment is made in cash. This provides an important source of cash to very poor households in the zone. Livestock production forms another crucial foundation of the local economy. Relatively large herds of cattle, goats and sheep are raised here, grazing freely, and also benefitting from crop residues after the harvest. Households also raise chickens, which are fed grain and food scraps. Cattle provide milk for consumption and sale and they also provide a means of savings, allowing households to convert them to cash when needed to cover a range of basic necessities. Goats and sheep are also kept here, used for cash income, but not for milk. All livestock are slaughtered and eaten, especially during the festival seasons. Livestock rely on water from rivers during both rainy and dry seasons. Men are responsible for taking care of cattle, goats and sheep, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots and fewer livestock, depend on seasonal agricultural labour - land clearing, planting, weeding and harvesting - to generate cash income. They also piece together supplemental cash resources throughout the year, collecting and selling firewood or charcoal, selling building poles, brewing or engaging in petty trade – buying and selling small commodities like tobacco, soda, salt and sugar. This livelihood zone is far from urban centres and service provision here is poor. As most villages are located along the river, both drinking water and water for other purposes comes from the river. It is free, but largely not safe. Sanitation facilities consist of uncovered temporary pit latrines for poorer households and improved pit latrines for better off households. Health dispensaries are found at village level, although for the most part they are not well-stocked. Primary schools are found in the villages as well. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and even college. Secondary schools are available in the ward centres. There is no electricity in this zone. Households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. Almost all households have mobile phones, with better off households having multiple phones. People do not have access to credit here; there are very limited options for savings (VICOBA for some of the wealthier households); and there are no NGOs or development agencies working in the area. Markets The transportation infrastructure in this zone is relatively poor and market access is considered quite bad. The zone is far from any of the main towns in Tanzania and roads are all dirt. They function in the dry season, but quickly deteriorate in the rainy season, leaving much of the area inaccessible by vehicle. The main road stretches from Horo Horo (in Tanzania but on the border with Kenya) to Daluni, Mng’aro and Lunguza. This zone is much more closely tied to the Kenyan market, via Mombasa, than the Tanzanian market, and most people depend on traders who come across the border to buy up local maize and cattle. Maize, cattle and goats are the main commodities sold by households in this zone. These transactions take place at the farm gate, or – in the case of maize – from house to house. Maize is sold in February, June and July, just after the harvest. Cattle and goats are sold throughout the year to traders who come to local villages and buy up livestock, transporting it to various end points, including Zanzibar (via Horohoro and Tanga); Mombasa (in Kenya); Korogwe (via Mombo); and Lushoto town. Chickens are also widely sold, again bought up by traders who take them to Tanga or Korogwe for sale. There is also a market for food brought into the zone for consumption by local households. Poorer households need to buy maize grain to cover their needs for a portion of the year, especially September through December and May to June, even in good production years. Maize is the cheapest local staple, and most of this is locally sourced, procured from better off households who generally produce a sizeable Tanga Maize and Cattle Livelihood Zone Profile 3 surplus. It is also sourced from Handeni via Tanga and Mkinga or via Mombo, Mnazi, Lunguza and Kikumbi. Rice, purchased almost exclusively by the upper wealth groups, is sourced from Morogoro, Kilimanjaro and Korogwe, distributed via the Tanga market or the Mnazi market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks. The labour market is largely local. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding. It was estimated that in the reference year, 70% of seasonal labour was found within the zone on local farms. An additional 30% of labour demand came from Maramba in a neighbouring livelihood zone where people travel every year during the lean season. Both men and women from poorer households take on paid agricultural work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Tanga Maize and Cattle Livelihood Zone the reference year covered the consumption period from June 2014 to May 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in November/December and ends with the masika harvest in July- August of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average rains, average crop yields and normal food prices. The incidence of crop pests was low, and livestock diseases were not widespread. In the past eight seasons, two were below average, and six were average. Production Year Season Rank Critical Events 2014-2015 Vuli 3 Average rainfall; average crop harvest Masika 3 Average rainfall; average crop harvest; no livestock diseases 2013-2014 Vuli 3 Average rainfall; average crop harvest; good prices for maize Masika 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases; no livestock diseases 2012-2013 Vuli 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases Masika 3 Average rainfall; average crop harvest; good prices for maize; crops not badly affected by pests and diseases 2011-2012 Vuli 2 Below average rainfall; poor crop yield; high staple food prices; low livestock prices; people increased charcoal sales, migrated to Maramba; sold more livestock and chickens Masika 2 Below average rainfall; poor crop yield; high staple food prices; low livestock prices; food aid was distributed by the Government of Tanzania; people increased charcoal sales, migrated to Maramba; sold more livestock and chickens 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Tanga Maize and Cattle Livelihood Zone Profile 4 Seasonal Calendar for Reference Year In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until December or January; rains for the second season, called the masika, picks up in March or April and lasts through May or June. Households plant twice, taking advantage of both seasons’ precipitation to reduce the risks of failure in either one. Land preparation for the vuli season starts in September, soon after the masika harvest, and planting begins in November, when the rains are fully established. December and January are busy months, with households engaged in weeding; those at the lower end of the wealth spectrum work in both their own fields and the fields of those with bigger farms, earning cash during this labour intensive period. The green harvest for the vuli crop starts in February, with the main harvest occurring in March. As maize from the vuli crop is being harvested, fields are once again prepared for the next season, with planting for the masika maize taking place in April. May is when households are tied up with weeding activities, again followed by a green harvest in June. The main harvest of masika maize occurs in July and August. The whole cycle starts again in the following month, giving people very little time to enjoy any downtime associated with the post-harvest period. Milk production is highest throughout both rainy seasons (November through April), when cattle give birth, and when fresh pastures and water sources provide animals with the nutrients they need for lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging diseases, such as East Coast Fever and Black quarter, are likely to occur. Livestock sales, which represent the most important income source for many households in this zone, can take place at any time of the year, but cattle are sold in the largest quantities in November and December, to fund the end of year festival season. January is when school fees need to be paid, which helps explain why livestock are also sold at this time. Money is also needed for agricultural inputs in February, March and April, and again September, October and November. April and May is also when staple food prices tend to be highest, generating another requirement for extra cash. Rainy season r r r r r r r r r r r r r r Crops Maize - 1st season (vuli) lp lp lp lp p p w w w w gh gh h h Maize - 2nd season (masika) gh gh h h h h lp lp lp lp p p w w Livestock Cattle milk peak m m m m m m m m m m m m Cattle sales peak salesale salesalesalesalesalesalesalesalesalesalesalesalesalesale Goat sales peak salesalesalesale salesalesalesalesalesalesalesalesalesale salesale Livestock diseases 5 5 5 5 5 5 5 5 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Firewood sales 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp Human diseases 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 2 2 Lean season ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Feb Mar Apr May Jun Jul Dec Aug Sep Oct Nov Jan Tanga Maize and Cattle Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Lushoto District based on a 43 - year period (1971-2013) Source: TZ Meteorology Department People in this livelihood zone are busy throughout the year, juggling the many activities involved with managing two production seasons. Poorer households are especially busy during land preparation and weeding periods, splitting the household to work partly on their own farms and partly on others’ farms for cash. But when they are able, they take advantage of any drier days occurring from July through January to collect and sell firewood to supplement their cash income. Human diseases occur throughout the year as well, but respiratory infections tend to peak during the dry seasons, and malaria is highest in the wet seasons. Having a sick household member is extremely taxing, especially for poorer households who need as much labour on hand as possible to manage the demands of their own farms while taking advantage of changing seasonal employment opportunities. They are also more limited in being able to pay for medicines (where they are available) given the severe constraints on their budgets. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The livestock numbers are per wife. Maize and cattle are the engines of the economy in this zone, so it follows that wealth is determined both by the area of land cultivated and the number of livestock owned. Those at the top of the wealth breakdown cultivate between 6 and 10 acres of land and own 40-70 cattle, along with other livestock; those at the bottom cultivate 1.5 to 2.5 acres and may own no cattle at all, or one or two at most. The difference in access to food and cash income for households at these two ends of the spectrum is quite large, with better off households able to generate all their required food and cash from their own fields and livestock, whereas those at the bottom are just scraping by, needing to supplement their own production with various off-farm pursuits. Tanga Maize and Cattle Livelihood Zone Profile 6 A related factor in wealth differentiation is household size; those with more resources tend to have larger households and those with larger households tend to have more labour, which allows them to maintain more resources. Thus there is some indication that the lower two wealth groups have slightly smaller household sizes, suggesting less access to labour within the family unit. In any case, only middle and better off households hire labour, and they are also in a position to rent or own tractors, which significantly increases the area they have under cultivation. Poorer households cultivate by hand and do not have the cash to hire extra labourers during the critical crunch periods, such as planting and weeding. There is a certain amount of intra-community redistribution and support here. The local labour market acts as a mechanism for redistributing cash, giving poorer households access to needed cash income and better off households access to the labour they need. Some better off households also lend milking cows to poorer households, providing them with access to milk, and in return having the poorer household take responsibility for the care of the animal. The distribution of wealth in this zone is fairly even. Very poor (20%) and poor (33%) households together comprise just over half of the households in the zone. Middle (32%) and better off (15%) households combined represent just under half the population. However, as middle and better off households are larger, and some even have multiple wives, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is larger. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period June 2014 to May 2015. June represents the start of the consumption year because it is when people begin to consume green crops from the masika season (the main season) and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. What is striking about livelihood patterns in this zone is the In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. overwhelming reliance on maize. It is the only crop of any significance grown by all households. Maize is grown in two season, with both seasons of almost equal importance. In the reference year, for example, a typical poor household produced around 840 kg of maize in the vuli season and 1,260 kg in the masika season. A typical middle household produced around 1,000 kg in the vuli season, and 1,400 kg in the masika. It was common for better off households to produce twice that much. Over half of the maize produced is sold, leaving an amount that does not meet the minimum calorie requirements of any wealth group. Sales of maize are critical here, providing households with a portion of the cash they need to cover their expenditure requirements. However, with maize the only crop of any note grown for both consumption and sale, people’s livelihood and food security are highly vulnerable to any hazard that affects maize production, be it a stoppage in rain, damage caused by monkeys (which is pervasive in this area), or any of a wide range of potential crop diseases affecting maize. The risk is countered to some degree by the fact that there are two seasons, however even if rainfall fails in one Tanga Maize and Cattle Livelihood Zone Profile 7 season this wipes out up to half of the annual food and cash supply, a shock that only the better off would be able to withstand. The lack of alternative crops, and the reliance on maize for both consumption and sale means that all households, but especially the poorer two wealth groups, are highly dependent on purchased food, even in an average year, like reference year. It is important to note that, even with these purchases the typical very poor household does not cover its minimum calorie needs. Very poor households purchased around 40-45% of their minimum calorie requirements and poor households purchased 35-40% of minimum calories in the form of maize grain - the cheapest staple - in the reference year. Middle and better off households generally did not purchase maize grain, instead buying wheat flour and rice along with a number of other more expensive non- grain items, such as beans, sugar, meat, oil, and dried fish. The purchase bar on the graphs above, therefore, represents a different basis for decision making: poorer households bought food because they had to fill a real food gap that they were unable to meet through their own production; middle and better off households, on the other hand, tended to buy food to diversify their food basket. This is further supported by the fact that if better off households had consumed all of their own maize production rather than selling half of it, they would have been able to cover over 250% of their minimum food needs with maize alone. Very poor households, on the other hand, given the same assumptions, would only have gleaned 105% of minimum calories from their own production. Even though this appears to be more than enough, it is not, because maize plays a critical role in covering household cash needs. Thus, households need to sell off maize to meet cash flow requirements after the harvest, putting them at a deficit later in the year. Milk contributes substantially to the diet of middle and better off households and to poor households as well to a lesser degree, covering 10%, 18% and 4% of minimum calorie needs in the reference year, respectively. Meat from the households’ own livestock also accounts for 5-10% of calorie needs for better off households. Poor households rely on the milk from around 2 cows; middle have around 7 cows milking, and better off households have, on average, 18 cows milking. On average, cows here produce 1.5 litres of milk a day during the first rainy season (lasting around four months) and 1 litre of milk a day in the second season (which lasts around three months). When added together, the milk from both seasons amounted to around 495 litres for poor households, over 1700 litres for middle households, and almost 4,500 litres for better off households during the reference year. Around 45-55% of this was sold, providing some cash income (shown in the section below) for these three wealth groups. Very poor households, who generally do not own cattle, benefitted neither in food nor in cash terms from milk. It is important to note that the milk from just two cows could have helped very poor households to close the calorie gap (of around 3% of minimum needs) they had in the reference year. Sources of Cash Income As shown in the graph to the right, there are five sources of cash income in this livelihood zone: crop sales, milk sales, livestock sales, agricultural labour, and self-employment. The latter two options are the domain (mainly) of poorer households. Better off households are the only wealth group that can cover all of their cash needs from their own farms, relying exclusively on their crop and livestock production. The bottom two groups rely Tanga Maize and Cattle Livelihood Zone Profile 8 heavily on agricultural labour and self-employment; and middle households need to take on some self- employment activities as well to cover all of their cash needs. What stands out in this The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 2 1,295,000 – 1,640,000 1,640,000 – 2,355,000 3,600,000 – 4,800,000 4,800,000 – 9,650,000 livelihood zone with reference to cash income is the importance of livestock sales, which dominate the income for middle and better off households. If maize was central to the story on the food side, then livestock (and especially cattle) are central to the story on the cash income side. It is no wonder, then, that the name of the zone features both maize and cattle, as these provide the engine for the local economy. Livestock sales make up around 65-70% of annual cash income for middle and better off households; and only around 10-20% for very poor and poor households. In absolute terms, better off households earn from livestock sales almost twice as much as middle households and over 27 times more than very poor households. This is largely due to the sale of cattle; better off households sold 7-8 cattle during the reference year, at around 500,000 Tanzanian Shillings each, providing them with around 3,750,000 Tsh from cattle sales alone. Middle households sold around 4 cattle, and poor households usually sell a single steer once every two years. Very poor households sold no cattle. Goats, worth around only 50,000 Tsh each (or a tenth of a cow), were sold by all wealth groups, ranging from around 2 goats sold by very poor households up to 19 goats sold by better off households. Chickens, which were worth around 9,000 Tsh per hen, were sold most intensively by very poor households, who typically cashed in on around 9 chickens in the reference year. Chickens provided very poor households with almost half of their livestock-based cash income, small as that income may be. Goats and chickens, therefore, are the only source of livestock-based cash for very poor households, whereas the other three wealth groups sell sheep and cattle as well. Having cattle affords the upper three wealth groups with access not just to a larger pool of money from the sale of live animals, but also cash earned from sales of milk. As noted above, households with milking cows sold 45- 55% of the milk they generated in the reference year. This resulted in substantial income for especially middle and better off households, bringing in, on average, 126,500, 433,400, and 1,375,000 Tsh for poor, middle and better off households respectively, or 7%, 11% and 19% of their annual cash income, respectively. Crop sales – which, in this livelihood zone means maize sales – accounted for 12-22% of total cash income for households in the reference year. In absolute terms, better off households earned around four times more from selling maize than very poor households, and twice as much as middle households. Maize is sold in both seasons, and better off households usually sell their maize for a higher price per unit than poor and very poor households. For example, the masika season maize, which is harvested in July and August, was sold by very poor households for around 278 Tsh/kg; better off households sold their maize for 400 Tsh/kg. This is mainly due to the timing of these sales; better off households store their grain and sell it when prices are highest, whereas poorer households usually need to sell right at harvest time, when prices are lowest. The result is that not only do better off households earn more cash from crop sales because they sell more maize, but also because they get significantly more money per unit of maize. Very poor and poor households, because their cash income from crop and livestock sales is so limited, must turn to other sources of cash to make ends meet. Agricultural labour is the most important alternative source for very poor households, making up just over 40% of their annual cash income in the reference year. For poor households, agricultural labour accounted for around 20% of their annual cash income. Land clearing is an especially arduous task, and poorer households are routinely hired throughout the two months when this work is undertaken, bringing them over half of their agricultural labour income. Planting, weeding and harvesting times also see an increase in the demand for seasonal labour, and these three periods bring in the rest of the 2 The average exchange rate from June 2014-May 2015 was 1 USD = 2,000 TZS Tanga Maize and Cattle Livelihood Zone Profile 9 cash income in this category. Most of the labour is performed for local middle and better off households, but some people also go to a neighbouring livelihood zone (the Tanga Maize, Orange and Jackfruit Midlands Livelihood Zone) to find work. The other source of cash income on the graph above is ‘self-employment’. This covers a range of activities that households undertake to try to earn cash at different times of the year. For very poor households this represents around a third of cash income and includes mainly firewood and charcoal sales. For poor households these activities also make up around 30% of cash income, but in addition to firewood and charcoal sales, these households earn cash from pole sales, brick sales and brewing. Middle households also supplement their crop and livestock sales with self-employment activities, but instead of firewood and charcoal, they focus mainly on mining, ox hire, petty trade, prepared food sales and some with motorcycles pursue boda boda (motorcycle transport). An additional point to make is that there is a large spread in income distribution, with those at the upper end of the wealth spectrum generating, on average, seven times more than those at the bottom. Owning livestock is the critical differentiator in this zone, with cattle sales alone for the better off equivalent to more than the total cash income of middle households and over twice the total annual cash income of both very poor and poor household. Expenditure Patterns The graph presents expenditure patterns for the reference year June 2014 to May 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. Households here, as in other areas of Tanzania, need to spend money throughout the year on a range of goods and services. These include: staple and non- staple food, household items, productive inputs, social services The graph provides a breakdown of total annual cash expenditure according to category of expenditure like schooling and health, as well as clothing and other miscellaneous items. There are three main points that emerge when delving into the data that supports the graph above. First, relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum. Even in a normal year like the reference year, very poor households must devote large proportion of their annual cash to meeting food needs, with the proportion of annual cash spent on staple foods highest for very poor households. In the reference year, households in the very poor wealth group bought around 44% of their minimum calories in the form of maize grain, the cheapest staple, and poor households bought 36% of their calories in the form of maize grain. This was the equivalent of around 560 kg and 450 kg of maize, respectively. Middle and better off households did not purchase any maize grain at all3. All households also spent money on other foods, such as dried fish, oil, sugar, rice, meat, vegetables and potatoes. These items are more expensive, and thus take up a larger proportion of annual cash for all wealth groups. In absolute terms, better off 3 What appears on the graph as ‘staple’ purchase for middle and better off households is beans, oil and dried fish. Tanga Maize and Cattle Livelihood Zone Profile 10 households spend more than twice as much as very poor households on these other foods, but because their cash income is more than seven times higher, in relative terms their expenditure is lower than poorer households. Second, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. Within this category, the two poorer wealth groups spent the most money on payment for grinding (taking up anywhere between 34% and 55% of the household items budget) followed by kerosene and soap. Kerosene and soap combined comprised 30-44% of the inputs budget for poorer households in the reference year. Better off households spent the most on kerosene followed by utensils. On an annual basis, spending on basic household goods, which occurred in weekly or daily incremental outlays, comprised 12-18% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Third, it is striking that the investment in productive inputs increases markedly with wealth group. Very poor households generally devote only 0-5% of their annual budget to productive inputs, either unable or unwilling to spend more. Better off households, on the other hand, invest almost 40% of their annual cash back into their production. In absolute terms, better off households spend over 80 times more than very poor households on productive inputs. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, ploughing, seeds and tools, labour, livestock purchase, and phone credit. Households here generally do not buy pesticides or fertilizers. Of these items, the poorer two wealth groups spent the majority of their money on phone credit, followed by livestock drugs and seeds and tools. Poor households were distinct from very poor households in that they also invested in livestock purchases. Middle households spent the most on labour, spending more than two-thirds of their inputs budget on hiring people to help on their farm. Phone credit was the next most important investment for these households, followed by livestock drugs, livestock purchases and then seeds and tools. Better off households invested large amounts of their budget into buying additional livestock, spending around a third of their inputs cash on this category. The next most important expenditure was labour hire, followed by livestock drugs, ploughing (effectively hiring tractors to help till their land), phone credit and then seeds and tools. The priority of better off households is clear from these numbers, and it is in line with the engine of growth here: the accumulation of cattle. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Better off households spent around 1.5 times as much as middle households; middle households spent around 1.5 times as much as poor households; and poor households spent around 1.5 times as much as very poor households. As you move up wealth groups, households are spending more on stationery, books, uniforms and, ultimately, the costs that are associated with secondary school. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to college. With respect to health costs, better off households spent more than six times as much as very poor households on a per capita basis; it is likely that these households sought treatment, when necessary, at facilities other than the village dispensary. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, bicycle service, savings, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. Tanga Maize and Cattle Livelihood Zone Profile 11 Hazards There are a number of hazards that affect this zone on a regular basis. The first is livestock disease, such as Food and Mouth disease (FMD), East Coast fever, trypanosomiases, affecting cattle, sheep and goats, as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively. Helminthiasis (worms) is also a common problem, along with New Castle Disease, which can wipe out an entire flock of chickens The second is crop pests and diseases. Stalk borers, which affect maize; and American bollworm, pollen beetles and yellow blight, which affect beans, cause problems throughout the zone almost every year. Wild animals pose additional challenges, ruining crops and causing damage in fields on a regular basis. The main, and most devastating, periodic hazard is drought, which leads to severe crop failures, degradation of pastures, drying up of local water sources and spikes in food prices and severe declines in livestock prices. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Better off households tend to have larger numbers of excess livestock to draw down on. However, it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through increasing self-employment, especially making more charcoal and collecting and selling more firewood. This option is limited because as the year worsens, the number of people attempting to increasing their income in this way rises, increasing supplies on the market and pushing down prices. The amount of wood available locally is also limited. Poorer households also try to find more work, either locally (working in many cases in direct exchange for food) or migrating outside the zone to Maramba, to the Tanga Maize, Orange and Jackfruit Midlands Livelihood Zone, where labour demand is higher, or even to Kenya. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Tanga Maize and Cattle Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Tanga Maize and Cattle Livelihood Zone Profile 12 Item Key Parameter - Quantity Key Parameter – Price Crops Maize - vuli – amount produced Maize – masika – amount produced Maize - vuli – producer price Maize - masika – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Sheep – herd size Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Firewood/charcoal – amount collected Self-employment – level of activity Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Firewood/charcoal - prices Self-employment – return on activities Expenditure Maize grain – consumer price Wheat flour – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Construct dam to create water source for irrigation 2) Provide affordable loans for agricultural inputs and livestock purchase 3) Improve access to and availability of safe and reliable water supplies for humans and animals 4) Improve access to more reliable supplies of drugs and improve health services 5) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 6) Provide electric service throughout the zone 7) Improve road infrastructure and invest in maintenance of existing roads 8) Develop and support the marketing infrastructure to enable the proliferation of reliable and fair markets for crops and livestock 9) Provide more affordable access to agricultural and livestock inputs 10) Improve communication networks/infrastructure | false |
# Extracted Content Western Usambara-Pare Highlands Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Western Usambara-Pare Highlands Livelihood Zone (TLZ 05) February, 20161 Zone Description The Western Usambara-Pare Highlands Livelihood Zone comprises a mountainous highland area in parts of Tanga and Kilimajaro regions. The administrative units that make up this zone include the wards of Kwai, Malibwi, Rangwi, Mwangoi, Mbaramo, Mtae, Soga, Soni, Mlalo, Shume, Malindi, Hamtoye, Ngweo, Lushoto, Gare, Baga, Mgwashi, Mwamboi, Ubiri, Mbuzii, Mayo, Bumbuli, Vuga, Mponde, Funta, and Tamota, all of which are found in Lushoto District2. The main ethnic groups living here are the Sambaa and the Pare. The population density here is high: 141 people per km2 in the western part of the zone and 104 per km2 in the eastern part, although around Korogwe the density is much lower, around 68 people per km2. This livelihood zone consists of a mountainous areas containing some of the only rain forests in East Africa. The Usambaras are part of a mountain range that stretches from the Taita Hills in southern Kenya to Morogoro and the southern highlands of Tanzania. The Usambaras are commonly split into two sub-ranges, the West Usambara Mountains and the East Usambara Mountains. The East Usambara are closer to the coast, receive more rainfall, and are smaller than the West Usambara. Natural resources include timber and a range of fruit trees, which are exploited for cash by a large proportion of the population. Since the late 19th century, a mix of cash crops like coffee, tea, and timber have been harvested from this area. A range of fruit trees are also found here. In the eastern parts, bananas, mangoes, jackfruit and avocado are grown. In the western part apples, peaches, and avocados are found. Tea plantations can be found in both the eastern and western areas, but most small-holder households do not grow tea. There are two rainy seasons – the masika rains, from March to June, and the vuli rains, from October to December. Total precipitation can be as high as 2,000 mm or as low as 500 mm depending on the year, but on average, based on a 43-year series of data, annual rainfall is around 1,036 mm. Temperatures are cool, ranging from 150C to 30ºC. The soils are fertile here, but there are severe constraints on land, with some of the highest population pressure in the country. Therefore, plot sizes are small, and production per household is low. All households cultivate maize, beans and Irish potatoes, all of which are rain-fed. Those with more land also cultivate a range of horticultural crops, such as cabbages, tomatoes and sweet peppers. These are grown in both seasons and bring in substantial cash income. Because of the mountainous terrain, tractors and ox ploughs are not 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in February 2014 and ended in January 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2 Although the map shows a zone that includes Korogwe and Muheza, these areas are considered to be a separate zone because the masika season is the main season here (rather than the vuli) and there are different fruits cultivated in smaller amounts. Cassava is found in the east not the west; people work on tea estates in the east but not the west. Potatoes are important in the west but not the east. Therefore, a re-zoning exercise is necessary along with a new map. Western Usambara-Pare Highlands Livelihood Zone Profile 2 feasible; therefore, all households – even the better off – use hand hoes to cultivate. Horticultural production is labour intensive, requiring arduous land preparation, planting, weeding, spraying, watering and harvesting. Middle and better off households pay poor household members in cash to help them complete these activities. Both men and women from poorer households work as labourers, helping provide their families with an important source of cash. Livestock are raised here in small numbers. Because of the severe limitations on land, people are unable to keep more than a few cattle and goats or sheep per household. Chickens are also kept by all households Zero grazing is the norm here, and animals are hand fed with grasses and crop residues. Cattle provide milk for consumption and sale and those who have them can convert them into cash when needed to cover a range of basic necessities. Goats and sheep are also kept here, used for cash income, but not for milk. Goats, sheep and chickens slaughtered and eaten throughout the year, but especially during the festival seasons. Livestock rely on water from seasonal rivers during the rainy seasons and shallow wells and springs during the dry season. Men are responsible for taking care of the cattle; both men and women take care of the goats and sheep, whereas women and children manage the chicken flocks. Poorer households depend heavily on seasonal agricultural labour - land clearing, planting, watering, spraying, weeding and harvesting - to generate cash income. Some also piece together supplemental cash by collecting and selling firewood, selling building poles, or brewing. Middle and better off households earn extra cash from petty trade, running small kiosks, and – if they have a motorcycle – boda boda (motorcycle taxi hire). Services in this zone are on a par with much of rural Tanzania. Drinking and washing water is sourced from springs and taps, usually not farther than 1 km from the village. Tap water is not free, costing 1,000 Tsh per household per month. Sanitation facilities consist of pit latrines, most of which are constructed with brick and mud and covered with aluminium sheets. Better off households may have improved concrete floors instead of mud floors. Health dispensaries are found within a 5-6 kilometre radius of most villages. Primary schools also available in villages, with secondary schools found at the ward level. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and vocational college. There is no electricity in this zone so households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. In general, all households have at least one mobile phone and better off households having multiple phones. People do not have access to credit here and there are no options for savings. A few NGOs operate here, including the Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services; Oxfam, which promotes vegetable crop marketing; TwoAfrica, which provides improved yellow bean seeds; and ASARECA, which promotes soil conservation and provides seeds. Markets In this mountainous zone, roads are mostly made of dirt and often in poor repair. One major tarmac road runs through the zone from Lushoto to Korogwe. In the dry season vehicles make it through on all the roads; but during the rains, the more difficult areas to reach, such as Kwai village in Lushoto District, become inaccessible. The majority of bridges are in good condition, although this can change rapidly in the wet season. Motorcycles, bicycles and foot traffic are the means by which most people get around in any case, and people sell their goods to traders who come into the zone to buy directly from farmers. Vegetables, such as cabbage, tomatoes and sweet peppers, along with fruits and livestock are the main commodities sold by households in this zone. These transactions take place at the farm gate. Vegetables are sold in the largest quantities after both harvests, from January to February and June to July, but there are vegetables harvested throughout the year in valleys where water pools, and sales can take place at any time. Traders buy vegetables from farmers and then transport them to Lushoto, where they are sold on to Tanga, Western Usambara-Pare Highlands Livelihood Zone Profile 3 Arusha or Dar es Salaam. Fruits are sold mainly in December and January. They follow the same trade route. Cattle, goats and chickens are sold in small numbers throughout the year at local markets. Given the high requirement for purchased food in this zone, the route by which maize enters the zone is important to understand. Demand for purchased maize grain is high from April to July in Korogwe (the eastern part of the zone) and from August to January in Lushoto (the western part of the zone). All households need to buy maize grain to cover their needs for a large portion of the year. Maize is the cheapest local staple, and this is sourced from Handeni or from Dar es Salaam. It is trucked into the area by local traders and better off households (who own trucks and bring back maize after their sell their vegetables in Dar es Salaam). This helps to moderate maize prices and ensures a fairly steady supply. Beans are sourced from Kilindi and are distributed via local markets from October through December. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks. The labour market is almost entirely local seasonal agricultural work. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms, with middle and better off households hiring poorer household members to work on their land. An additional 10% of labour demand came from Lushoto town, where people regularly go to seek work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Western Usambara-Pare Highlands Livelihood Zone the reference year covered the consumption period from February 2014 to January 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in October/November and ends with the April through July harvest of the following calendar year. Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was average, with average rains, average crop yields and normal food prices. In the past eight seasons, three were below average, three were just below average and two were average. Production Year Season Rank Critical Events 2014-2015 Vuli 2.5 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. Masika 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. 2013-2014 Vuli 3 Average rainfall; average crop production average prices Masika 3 Average rainfall; average crop production average prices 2012-2013 Vuli 2.5 Average rainfall; average crop production average prices Masika 2.5 Average rainfall; average crop production average prices 2011-2012 Vuli 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. Masika 2 Drought, high staple food prices, low crop production. People increased livestock sales and tried to find more seasonal agricultural labour. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Western Usambara-Pare Highlands Livelihood Zone Profile 4 Seasonal Calendar for Reference Year The graph to the right shows average monthly rainfall (mm) in Lushoto District based on a 43 - year period (1971-2013) Source: TZ Meteorology Department In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until January; the second, called the masika, occurs from March through May. Households in the western part of the zone consider the vuli rains to be the main production season, whereas those in the eastern part consider the masika rains to be the main production season. The seasonal calendar below shows the pattern for the western part of the zone, but even here, there is production in both the vuli and masika seasons, and many crops rely on irrigation which, while supported by the rains, is not entirely dependent on them. Land preparation takes place twice a year: from August to October (for the vuli season) and February and March (for the masika season). This is a time of intense labour demand and those at the lower end of the wealth spectrum are working in both their own fields and in the fields of those with bigger farms, earning much of their annual cash during this period. Maize is grown in only one season, but beans and Irish potatoes Rainy season r r r r r r r r r r r r Crops Land preparation lp lp lp lp lp lp lp lp lp lp Maize - (vuli) gh gh gh gh h h h h p p p p w w w w Beans h h p p w w w w h h p p p p w w w w Irish potatoes h h p p w w w w h h h h p p p p w w w w h h Vegetables/fruit h h p p p p w w h h h h p p p p w w h h Livestock Cattle milk peak m m m m m m m m m m Cattle sales peak salesalesalesalesalesale Other Agricultural labor peak 4 4 4 4 4 4 4 4 4 4 Non-agricultural labor peak 4 4 4 4 4 4 4 4 Firewood sales 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp Human diseases 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Oct Nov Dec Jan Feb Mar Aug Apr May Jun Jul Sep Vuli Masika Western Usambara-Pare Highlands Livelihood Zone Profile 5 are planted twice. Maize, beans and horticultural crops are planted in October and November, once the rains are fully established. Irish potatoes are planted before this, starting in September, since they need slightly less water to get started. Weeding takes place from November to January, and once again poorer households are hired by those with larger farms to help with this activity. Irish potatoes and some of the horticultural crops start to get harvested as early as January, and households begin to harvest maize green, and beans, starting in February. The main harvest of vuli maize is in April and March. As maize from the vuli crop is being harvested green, fields are once again prepared for the next season, with planting for the masika beans, Irish potatoes and vegetables taking place in March and April. May is when households are tied up with weeding activities, again followed by a harvest of the second season crops in June and July. The whole cycle starts again in the following month, in August. Milk production is highest from February through June since conceptions are highest in May and cattle give birth around nine months later. This is a time when the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging diseases, such as East Coast Fever and Blackquarter, are likely to occur. Livestock sales can also take place at any time of the year, but November through January tends to be a time of especially high sales, when households need extra cash for food since staple prices are highest in these pre-harvest months. Poorer households in this zone are especially busy during land preparation and weeding periods, splitting the household to work partly on their own farms to grow their own food and cash crops, and partly on others’ farms for cash. February and March, and August through October are periods of intense agricultural labour demand. During the months when there is more time for off-farm work (from April through July), poorer households may seek temporary jobs in town, or they collect and sell firewood to supplement their cash income. June through September is the festival season. This brief period between the masika harvest and the start of the vuli season is when people have slightly more cash available from their cash crop sales, and the break in agricultural labour gives people a time to rest. Human diseases occur throughout the year as well, but respiratory infections tend to peak during the dry seasons, and malaria is highest in the wet seasons. Having a sick household member is extremely taxing, especially for poorer households who need as much labour on hand as possible to manage the demands of their own farms while taking advantage of changing seasonal employment opportunities. They are also more limited in being able to pay for medicines (where they are available) given the severe constraints on their budgets. Wealth Breakdown Given that crop production is the main source of cash income in this zone, it follows that wealth is determined largely by the area of land cultivated by a household. In addition, ownership of productive assets, like motorcycles (which enable households to make money from boda boda), livestock and fruit trees contributes to the basis on which differences of wealth are determined. These other productive assets are relatively more important in this zone than in many others because the population is dense, land is very limited and, thus, the land areas cultivated are severely constrained. No land is left uncultivated, and even better off households are unable to plant on more than 5 acres. Very poor households plant on less than an acre, concentrating mainly on food crops rather than horticulture. Poor households cultivate 1-2 acres and middle households cultivate 2-3 acres. The difference between these two amounts of land seems minor, but there is a critical divide between poor and middle households: poor and very poor households need to work for others to earn enough cash to live on and middle households generally do not. In part this is because middle households have that extra acre that allows them to plant Western Usambara-Pare Highlands Livelihood Zone Profile 6 vegetables for sale and also allows them to cultivate – importantly – a significant number of fruit trees, which provide another source of cash income that poor households do not have. Note: The percentage of household figures represent the mid-point of a range. All asset numbers are per wife (in the case of polygamous households). Another difference between poor and middle households is the number of livestock owned. Although livestock are not a major source of cash income in this zone – limited in numbers because of the lack of land for grazing and maintenance - they still help provide milk for consumption and sale, and the cash from live animal sales is not insubstantial. A middle household with up to 3 cattle has different prospects for cash income than a poor household with none. There is a certain amount of intra-household redistribution in this livelihood zone. All households cultivate with hand hoes, which means that those with more land need extra help, unable to rely exclusively on their intra-household labour to complete all their agricultural tasks throughout the year. Thus, households on the upper end of the wealth spectrum hire those on the lower end, especially during land preparation and weeding. The local labour market acts mechanism for redistributing cash, giving poorer households access to needed cash income and better off households access to the labour they need. In addition, there are some share-cropping arrangements in place, in which middle households provide land, fertilizers and seeds to poorer households in exchange for a portion of the crop that is harvested by the poor household. The distribution of wealth in this zone is fairly even. Very poor (23%) and poor (32%) households together comprise just over half of the households in the zone. Middle (30%) and better off (15%) households combined represent just under half the population. Western Usambara-Pare Highlands Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period February 2014 to January 2015. February represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. What is striking about livelihood patterns in this zone is the heavy reliance on the market for all In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. wealth groups. All households needed to purchase food to cover a production gap – even better off households generally do not produce enough to meet their minimum calorie needs. In the reference year, an average year, very poor households bought almost 60% of their minimum calories in the form of maize grain (the cheapest staple) and better off households bought around 30% of their calories in the form of maize grain. All households also bought some rice, with middle and better off households buying more of this expensive grain than poorer households; and middle and better off households also bought wheat flour, which was around twice as expensive as maize grain. Sugar, meat, oil, Irish potatoes, beans and dried fish also contributed to the purchased food basket. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 70-85% of their minimum calorie requirements in the reference year. It is important to note that, even with these purchases the typical very poor and poor households were left with a gap. In addition to the market, households depended on two other sources of food: their own crop production and their own milk production. All households grow a range of crops, including maize, beans, Irish potatoes and vegetables, such as cabbage, sweet peppers. Better off households also cultivate fruit trees; in the eastern part of the zone, where the altitude is not as high, bananas, mangoes, jackfruit and avocados are grown; in the western, higher altitude part of the zone, apples, peaches, avocados and futari (matunda damu) are grown. Despite this large variety, households do not grow enough to meet their own consumption requirements, even in an average year like the reference year. People have relatively small plots, and only one season of maize is grown. In that one season (the vuli season in the western part of the zone and the masika season in the eastern part), total production of maize was quite low in the reference year, ranging on average from 175 kg for very poor households up to 430 kg for better off households. All of the maize was consumed, but this amount accounted only around 10-30% of minimum calorie requirements. Beans are grown in both seasons, and a large portion of the bean harvest is sold. Given that beans fetch a higher price than maize grain, selling this crop to generate cash for purchased maize makes economic sense. The beans that households retained for consumption covered an additional 4-7% of minimum food needs. Irish potatoes, grown in the masika season, provide an additional 2-5% of minimum calorie needs for households. When combined, own crops accounted for only around 20-40% of households’ annual food needs in the reference year. Milk makes up the last component of the diet for households in this zone, although it does not make a large contribution in calorie terms, providing only 1-6% of minimum calorie needs in the reference year, increasing Western Usambara-Pare Highlands Livelihood Zone Profile 8 with wealth. Middle households typically have around 1 cow milking, and better off households have, on average, 2 cows milking. Very poor and poor households may borrow a cow, or share in the milk from a neighbour. Yields are relatively high, at 3-4 litres a day in the first rainy season (lasting around four months) and 1.5-2 litres a day in the second rainy season (lasting around three months). When added together, the milk from both seasons amounted to around 660 litres for middle households, and 1,300 litres for better off households during the reference year. Around 50-65% of this was sold, providing some cash income (shown in the section below) for these three wealth groups. Sources of Cash Income The graph to the right highlights six main sources of cash income in this livelihood zone: own crop sales, milk/egg sales, livestock sales, agricultural labour, petty trade and boda boda. All households need to depend on sources of cash from off- farm activities, although the majority of cash income for middle and better off households is generated on the farm (from crop and livestock-related sales.) The bottom two groups rely quite heavily on agricultural labour to supplement their crop and livestock-related sales. Their on-farm production is much too low to meet all of their cash needs The importance of vegetable The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 3 1,157,000 – 1,760,000 1,760,000 – 2,355,000 2,600,000 – 5,600,000 5,600,000 – 7,000,000 and fruit sales stands out in this livelihood zone, especially for the upper two wealth groups. For these households, the purchased food that dominated the ‘Sources of Food’ graphs is funded in large part by these sales of vegetables and fruits. All the crop sales combined (including beans, Irish potatoes, vegetables and fruit) accounted for (on average) 9%, 43%, 64% and 65% of annual cash income for very poor, poor, middle and better off households, respectively. Middle and better off households derived over 80% of their crop-based cash income from vegetable and fruit sales. As noted above, in the eastern part of the zone, where the altitude is not as high, bananas, mangoes, jackfruit and avocados are grown; in the western, higher altitude part of the zone, apples, peaches, avocados and futari (matunda damu) are grown. Fruit sales made up 25-30% of the crop- based cash income for middle and better off households in the reference year. Tomatoes, cabbages and sweet peppers are the main horticultural crops grown and sold; better off households marketed as much as 5,400 kg of cabbage, 1,500 kg of sweet peppers and 2,100 kg of tomatoes. Poor households also benefitted from vegetable sales, deriving over 60% of their crop-based cash from horticulture. Very poor households, on the other hand, sold only beans and Irish potatoes, and in only very small quantities. In many ways the main distinction between poor and very poor households is that very poor households are unable to cultivate vegetables, whereas poor households do; the cash incomes of very poor households suffer as a result. 3 The average exchange rate from February 2014-January 2015 was 1 USD = 1,776 TZS Western Usambara-Pare Highlands Livelihood Zone Profile 9 Two other sources of on-farm cash income (milk/egg sales and livestock sales) are less important, making up only 7-19% of annual cash income combined for all wealth groups. People keep small number of cattle, sheep and chickens and use them to generate milk, eggs and cash income from sales of live animals. Poorer households generated around 74,000 Tsh from milk and egg sales in the reference year; this was enough to cover the agricultural inputs budget of very poor households, or at least part of the school fees for their children. So although this does not compare to the 400,000 Tsh generated by better off households from milk and egg sales, it is nevertheless a meaningful amount. Sales of live animals (sheep and chickens for all households and cattle in addition to the sheep and chickens for middle and better off households) brought in around the same amount of money as milk and egg sales did for the poorer two wealth groups, and around twice as much as milk and egg income for better off households. In any case, livestock are not the major engine of the local economy in this livelihood zone, providing a relatively small supplement to other more important sources. Far more important for very poor and poor households than either crop sales or livestock-based income is the cash derived from agricultural labour. Agricultural labour is the single most important source of cash for both of these wealth groups, accounting for almost 85% of annual cash income for very poor households, and 50% of annual cash income for poor households in the reference year. Land preparation for vegetables is an especially arduous task, as everyone is forced to use hand hoes in this highland zone. There are no tractors or ox ploughs. Poorer households are routinely hired throughout the four months when this work is undertaken; land preparation alone accounts for over half of the agricultural labour income for very poor households. Watering, spraying, weeding and harvesting times also see an increase in the demand for seasonal labour, and these activities bring in the rest of the cash income in this category. All of the labour is performed for local middle and better off households. There is no seasonal agricultural labour migration to other areas. The other sources of cash income on the graph above are ‘petty trade’ and ‘boda boda’, both the domains of middle and better off households. Petty trade requires households here to have a means of transporting goods and some extra cash to purchase goods for re-sale. Boda boda requires the ownership of a motorcycle – something only the better off households have. These extra sources of cash make up between 15% and 25% of the cash income for these upper two wealth groups. The spread in income distribution is fairly large here, with those at the upper end of the wealth spectrum generating, on average, four times more than those at the bottom. Being able to cultivate vegetables is large quantities, and fruit trees, is the critical differentiator in this zone, with fruit and vegetable sales alone for the better off equivalent to 175% of the total cash income of poor households and 225% of the total annual cash income of very poor households. Expenditure Patterns The graph presents expenditure patterns for the reference year February 2014 to January 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. Households here, as in other areas of Tanzania, need to spend money throughout the year on a range of goods and services. These include: staple and non- Western Usambara-Pare Highlands Livelihood Zone Profile 10 staple food, household items, productive inputs, social services The graph provides a breakdown of total annual cash expenditure according to category of expenditure like schooling and health, as well as clothing and other miscellaneous items. A number of conclusions can be drawn from the expenditure data for this zone. First, the amount of cash spent on staple food is higher here for the top two wealth groups than in many other zones. This reflects the high purchase requirement for all wealth groups discussed in the ‘Sources of Food’ section. While relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum, in absolute terms, expenditure on food increases with wealth. Very poor households spent, on average, around 608,500 Tsh on staple food in the reference year; better off households spent 781,800 Tsh. Even in a normal year like the reference year, all households must devote a large sum of money to meeting food needs, with the proportion of annual cash spent on staple foods highest for very poor households because their total income is lowest, as discussed in the section above. In the reference year, households in the very poor wealth group bought around 58% of their minimum calories in the form of maize grain, the cheapest staple; better off households bought 31% of their calories in the form of maize grain and the other wealth groups fell somewhere in between. This was the equivalent of around 850 kg and 455 kg of maize, respectively. Middle and better off households also purchased wheat flour, which was twice as expensive as maize. All households also spent money on other foods, such as rice, sugar, meat, dried fish and oil. Very poor households also purchased cassava, as well as some Irish potatoes (along with poor households). These are all included in the non-staple food basket. Second, it is clear from the graph above that middle and better off households are investing heavily in their agricultural production, spending 30 - 40% of their annual cash income on inputs. Very poor and poor households, on the other hand, devoted only 4-8% of their annual budget to productive inputs in the reference year, either unable or unwilling to spend more. In absolute terms, better off households spent over 36 times more than very poor households on productive inputs. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, seeds and tools, pesticides and fertilizers, labour, and phone credit. All households spend part of their inputs budget on seeds and tools, and on phone credit. Very poor households, in fact, spend three-quarters of their inputs budget on phone credit and the rest on seeds and tools. Middle and better off households spend the majority of their inputs budget (60-65%) on hiring labour. Pesticides and fertilizers also account for a sizeable portion of the budget, taking up 35% of poor households’ inputs budget in the reference year and around 16% of middle and better off households’. Only middle and better off households spent money on livestock drugs and house repairs, but combined these took up less than 10% of their inputs budget. Another category of expenditure (‘hh items’) includes all of the items bought by households over the year – often in small incremental amounts - to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils. Within this category, the highest expenditure was on grinding, kerosene and soap; very poor households devoted 55% of their ‘hh items’ budget to grinding in the reference year; better off households spent around 45% of this budget on kerosene; and for middle households, grinding and soap together comprised almost 50% of this same budget. On an annual basis, spending on basic household goods comprised 7-12% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Finding ways to reduce the relatively high costs of grinding for poorer households could help them free us some money for other productive uses. ‘Social services’ includes the money spent on education and medical services. Education covers school fees, uniforms, stationery and transportation, where relevant. Absolute spending on school during the reference year was about the same for very poor and poor households (approximately 125,000 Tsh per year per household). Middle households spent more than double this amount, and better off households spent three times the amount spent by poorer households. As you move up wealth groups, households are spending more on stationery, books, uniforms, school fees and transportation. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to vocational school. Better off and Western Usambara-Pare Highlands Livelihood Zone Profile 11 middle households also spend more on medicine and health care, with each wealth group spending on average 30-50% more than the one below it. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget. Hazards There are a number of hazards that affect this zone on a regular basis. The first is inadequate and erratic rainfall. All households rely heavily on crop production from one season to at least partially meet their food needs. If rains in this season are poor, if they are interrupted at the growing stage, or if they end early, households are at risk of losing their maize, beans and Irish potato crops, all of which are rain-fed. Horticultural crops can also be damaged because, although they rely on irrigation, they are also partially rain-dependent. Thus the food and cash income of households here is substantially reduced when rains are poor. Second, livestock diseases, such as Food and Mouth disease (FMD) and East Coast fever – both of which affect cattle - and New Castle Disease, which can wipe out an entire flock of chickens, are serious problems. Third, crop pests and diseases are a constant threat. Stalk borers, which affect maize; American bollworm and late blight, which affect tomatoes and sweet peppers are among the worst. A new crop pest, known locally as kanitangaze, has been causing problems for tomatoes, African eggplants and sweet peppers. Fourth, human diseases, like malaria and typhoid, undermine the most important livelihood capital held by poorer households – their labour pool. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to find more work, either locally or migrating outside the zone, or sometimes into towns. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Middle and better off households try to increase their livestock sales. The value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Therefore, this option has quite severe limitations in this zone, where people do not have many livestock to begin with. Middle and better off households take their crops directly to markets to try to get a better price, cutting out the middlemen traders in order to increase their cash income. Middle and better off households try to increase their reliance on small businesses, buying and selling goods to make as much cash as they can with which to buy food. Western Usambara-Pare Highlands Livelihood Zone Profile 12 Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Western Usambara-Pare Highlands Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize - vuli – amount produced Beans – vuli – amount produced Beans – masika – amount produced Irish potatoes – masika – amount produced Tomatoes – amount produced Cabbage – amount produced Sweet peppers – amount produced Fruits – amount produced Beans - vuli – producer price Beans - masika – producer price Irish potatoes – masika – producer price Tomatoes – producer price Cabbage – producer price Sweet peppers – producer price Fruits – producer price Livestock production Cow milk – yields Cattle – herd size Cow milk – price Cattle – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, watering, spraying, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Petty trade – amount of trade Boda boda – level of activity Agricultural wage rates (land clearing and preparation, planting, watering, spraying, weeding) Agricultural labour rates (harvesting) Petty trade – margins on trade Boda boda – fares Expenditure Maize grain – consumer price Rice – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Provide subsidized and improved agricultural inputs, especially for seeds and fertilizers 2) Provide affordable loans 3) Improve health services and increase the availability of medicines 4) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities 5) Improve road infrastructure and invest in maintenance of existing roads 6) Construct irrigation infrastructure and provide pumps 7) Develop soil water conservation systems through construction of terraces 8) Improve access to and availability of safe and reliable water supplies for humans 9) Provide electric service throughout the zone 10) Provide support for expansion of dairy cattle industry | false |
# Extracted Content Tanga-Pwani Coastal Belt Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Tanga-Pwani Coastal Belt Livelihood Zone (TLZ 07) April, 20161 Zone Description The Tanga-Pwani Coastal Belt Livelihood Zone comprises a very narrow strip of land along the coast of the Indian Ocean, including parts of Tanga Municipal, Muheza, Mkinga, Pangani, Rufiji, Bagamoyo and Mkuranga districts2. The main ethnic groups residing here include the Zigua, Digo, Bondei, Sambaa, Pemba, Makonde, Tumbatu and Wadoe. The population density is 38 people per square kilometre3. Warm, lowland, flat plains characterise this zone. Villages are located within a narrow strip of land along the coast, interspersed with agricultural land and mangrove forests. The Pangani and Zigi rivers flow through on their way to the Indian Ocean, providing a source of fresh water to those who live in close proximity. The Saadani National Park is located at the southern end of the zone. Fish are the main natural resource, and they provide all households living here with significant food and cash income. Annual rainfall levels vary quite a bit, ranging from 600-1400 mm depending on the year and the location. The average annual precipitation for Pangani, based on a 43-year time series, is 1,176 mm. Rains fall in two seasons, the vuli from October to December and the masika from March to May. The masika rains are far more reliable and plentiful, and crop production relies heavily on these second rains. Soil fertility is relatively high, and this is a moderately productive zone despite inconsistent and unreliable rains. The household economy rests on two main pillars: crop production and fishing. Cassava and maize are the main food crops, although paddy is also produced in small quantities, along with cowpeas and green gram. These crops are all harvested only once a year, because the vuli rains are not sufficient for planting two cycles. Maize is produced almost entirely for home consumption, whereas cassava is grown both for consumption and sale, as are the other crops. Oranges, coconuts and cashews provide additional income for households who own fruit and nut trees. Ox ploughs and tractors are not used here and all households cultivate by hand. The most labour-intensive activities are land preparation and weeding and for these tasks, households with larger tracts of land hire those with less (both men and women) to work in their fields. 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in June 2014 and ended in May 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 Only a very narrow strip of coastal land is included in the zone. The coastal parts of the following wards are included in the zone: Moa, Manza, Kwale, Chongoleani, Mzizima, East Chumbageni, East Nguvumali, East Mzingani, Mabawa, Tangasisi, Tongoni, Kirare, Kigombe, Kimang’a, Pangani, Mashariki, Mwera, Mikunguni, East Tungamaa, and Mkwaja. The following wards are not part of the zone: Madanga, Marungu, Maweni, Mwanzange, Mabokweni, and Duga. 3 District Socio-economic profiles, 2014 Tanga-Pwani Coastal Belt Livelihood Zone Profile 2 People are also hired for planting and harvesting, but the demand is not as high for these tasks. Payment is made in cash, providing an important source of income to poorer households. In addition to crop production, people from all households are engaged in fishing in one way or another throughout the year. The degree to which fishing contributes to a household’s income is related to its ownership of fishing equipment – especially boats – and its ability to hire others to help fish. Poorer households work on the boats of better off households, or absentee urban boat owners, who hire local residents to manage their boats. They are paid in both cash and in fish, some of which is used for household consumption, and some of which is sold. Households with more fishing equipment use nets and bring in much larger quantities of fish, most of which is sold to generate cash income. Fishing is done mostly at night in the Indian Ocean, although some also dive for shell fish during the day. Only men are engaged in fishing. All households own small numbers of livestock, although the types and numbers owned vary by wealth. Very poor households, for example, only have chickens, whereas better off households own cattle, goats and chickens. Even better off households do not have large herds, however, because the demands of fishing and crop production already take most of a household’s time, and adequate grazing areas (and water resources) are not available to sustain large numbers of cattle. Cattle and goats graze (and browse) freely and are also given crop residues after the harvest. Chickens are fed grain and food scraps. Those who own cattle use them for milk, which is consumed at the household level and also sold, and they also sell live animals, especially young bulls, for cash. Goats are also sold for cash, and slaughtered for meat during festivals and other important occasions. Livestock rely on water from small rivers, shallow wells and seasonal pools during the rainy season; in the dry season, water from deep wells is purchased by the bucket for livestock. The expense of keeping livestock watered during the dry season is another reason that people do not keep large herds of cattle. Men are responsible for taking care of cattle and goats, whereas women and children manage the chicken flocks. Poorer households, who have smaller plots, minimal fishing equipment and fewer livestock, earn cash from seasonal labour - clearing land, planting, weeding, harvesting and working on fishing boats. Some find work in local towns on construction projects. During times of low agricultural demand, they also collect and sell firewood or burn and sell charcoal, and produce and sell sea salt. Better off households may own small kiosks or otherwise engage in petty trade, buying and selling household goods like soap, kerosene and tobacco. Service provision here is on a par with much of rural Tanzania. Each village has tap-water, which households purchase for drinking purposes. Water for washing and laundry comes from open wells at no cost. All households use pit latrines, and some better off households use improved pit latrines. Health dispensaries are found at village level and health centres are located in ward centres. Health facilities are not well-staffed, however, and dispensaries are often poorly stocked. Primary schools are found in the villages as well and secondary schools are at ward level. Most poorer households send their children through primary school but not to secondary school because they cannot afford the extra expenses involved with secondary school, including transportation (and sometimes boarding), uniforms, stationery and books. Middle and better off households, on the other hand, typically send their children to secondary school and even college. Electricity is available in only a few villages; most households depend on battery-operated torches and kerosene lanterns for light; some better off households also have solar lanterns. Almost all households have mobile phones, with better off households having multiple phones. Only better off households have access to credit through SACCOS, and options for savings are not available. There are no NGOs or development agencies working in the area. Markets The transportation infrastructure in this zone is not well developed. The zone comprises a narrow strip along the coast with rough dirt roads. The only main towns are Pangani and Tanga. Vehicles can access villages in the dry season, but in the rainy season much of the area is inaccessible. Tanga-Pwani Coastal Belt Livelihood Zone Profile 3 Fish, cassava, sesame, oranges, coconuts and cashews are the main food items produced and sold in this zone. Cattle, goats and chickens are the main livestock sold. All crops are sold at the farm gate to traders who transport them on to urban markets. Cassava is collected by traders in large bags and taken by truck to Tanga from October to March. Oranges (sold from June to August and then December to January) and coconuts (sold from December to March) are likewise taken to Tanga and then trucked onwards to Dar es Salaam, or to Arusha. Sesame has a longer journey, making its way overseas to terminal markets in India via the Dar es Salaam or Mombasa ports. Sesame sales take place in August, after the harvest. The local demand for fish comes from inland villages and nearby towns, like Tanga; but there is also a wider network of distribution, and traders come from Dar es Salaam and Arusha town to buy up local supplies. Dried fish is transported by truck, but fresh fish is taken by vehicle or boats installed with special freezers. The peak trade in fish occurs from February through April, when winds are calm and fishing is most productive. Chickens are sold within villages and to nearby towns like Pangani and Tanga, as are goats. The most common time for these animals to be sold is February through May, at the peak of the lean season. Traders go village to village buying up cattle, which get transported to urban centres for consumption. December and February through May are both peak times for cattle sales. Local households buy food throughout much of the year, with the demand for staple grains increasing during the lean season from January through May, even in years of good production. Maize is the cheapest local staple, and most of this is sourced from Handeni, Dodoma, or Kilimanjaro. Tanga acts as the main distribution point for maize that comes into the zone. Rice, a more expensive grain, is sourced from Morogoro or Mbeya and distributed via the Tanga market. Beans come from Kilimanjaro, Handeni, and Iringa, making their way to village shops via Tanga. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks, often by better off households. The labour market is mostly local, either in the agricultural sector, where seasonal jobs are found, or the fishing sector, where people find work as daily labourers on boats. Middle and better off households hire additional labour to help them complete the more intensive seasonal tasks, such as land clearing and weeding, and people are needed almost year-round on fishing boats. It was estimated that in the reference year, 80% of seasonal labour was found within the zone. An additional 20% of labour demand came from local towns. While men and women both engage in seasonal agricultural labour, only men are involved in fishing labour. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Tanga-Pwani Coastal Belt Livelihood Zone the reference year covered the consumption period from June 2014 to May 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli season planting period in October/November and ends with the masika harvest in June-August/September of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, rainfall during the production year corresponding to the reference year was relatively good in the masika season and below average during the vuli season. Harvests of food and cash crops were relatively good. In the past eight seasons, four were below average, three were average and one was above average. Production Year Season Rank Critical Events 2014-2015 Vuli 2 Poor rainfall distribution and poor maize yields; average cassava yields; high food prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food crops; lower prices for cash crops Tanga-Pwani Coastal Belt Livelihood Zone Profile 4 2013-2014 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 4 Good rainfall distribution; good harvest of food and cash crops; lower cash crop prices; good prices for sesame 2012-2013 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food crops; lower prices for cash crops; striga affected crops in some areas 2011-2012 Vuli 2 Below average rainfall distribution, poor maize yields, average cassava yields, high food crop prices Masika 3 Average annual rainfall distribution, average crop yields, average prices for food and cash crops; wild animals destroyed crops in some areas 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Tanga-Pwani Coastal Belt Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Bagamoyo District based on a 43 - year period (1968-2010) Source: TZ Meteorology Department In this livelihood zone there are two distinct rainy seasons: the first, called the vuli, starts in October and lasts until December or January; rains for the second season, called the masika, start in March and last through May. The main food crops are only planted and harvested once, in the masika season, because the vuli rains cannot support a full production cycle. However, fruit and nut tree crops, which do not require the same consistent distribution of rains, are typically harvested twice a year. January through May are busy months in this livelihood zone. Land preparation begins after the vuli rains have softened the ground, usually starting in January and continuing through February. Maize and paddy are planted in March as soon as the masika rains are well-established. New cassava cuttings are planted as needed a month later, in April. April and May are the weeding months, requiring long days of work in the field. During these first five months of the year, very poor and poor households divide up their intra-household labour pool, with some family members working in their own fields and others hired to work in the fields of middle and better off households. For these households, much of the year’s cash is earned during this time, as shown below in the section on ‘Sources of Cash Income’. The green harvest begins in June along with the orange and mango harvest. The green harvest is particularly important for poorer households who buy the majority of their food when their own stocks run out, usually starting in February or March. Being able to eat maize green helps them to reduce their expenditure requirements. The main harvest for maize and paddy begins in July. Cassava can be harvested throughout the year, but a concerted harvest and sale takes place in August and September, helping households raise revenues to buy inputs for the next year’s agricultural season. December, January and February are months when middle and better off households benefit from the coconut and cashew harvests, along with a second season of mangoes and oranges. This helps them raise the cash they need to hire poorer household members who work for them during the agricultural season. The post-harvest period (August, September, October) is when the majority of petty trade takes place, which benefits middle and better off households who earn money from trading crops and processed foods, or who sell household goods to other households who have newly-earned income from their crop sales. October is also a time when festivals occur, as it is a relative down-period before the peak fishing season starts, and it coincides with a time when people have more cash on hand. Other festival months are July, as harvests are brought in from the fields, and December. The main fishing season is from January through April, when winds are minimal and seas are relatively calm. This coincides with much of the agricultural season, which means that families divide their labour, sending some men to work on fishing boats while women and older children work the fields, or working some evenings on fishing boats and others in their fields. Either way, it is a very busy time and people are fully engaged with productive tasks. Milk production is highest from April through July. This is when fresh pastures and water sources, fed by the masika rains, provide animals with the nutrients they need for birth and lactation. At this time the consumption of milk is highest within the household, and cash income from the sale of milk peaks. Livestock diseases may occur any time throughout the year, but the rainy season is when some of the most damaging ones, such as East Coast Fever, Contagious Caprine Pleuropneumonia (CCPP), and Black quarter, are likely to occur. Cattle sales peak in December, February and April and May. December sales help fund the end of year festival season as well as school fees, which are due in January. Money is also needed for agricultural inputs in February and labour hire Tanga-Pwani Coastal Belt Livelihood Zone Profile 6 in April and May. April and May is also when staple food prices tend to be highest, generating another requirement for extra cash. Human diseases have a seasonal pattern as well, with respiratory infections peaking during the dry seasons, and malaria highest in the wet seasons. Having a sick household member creates hardships on a number of levels, especially for poorer households who need as much labour on hand as possible to manage the competing demands of their own farms, seasonal agricultural labour, fishing labour and income generating activities like firewood sales, salt processing and sales, and charcoal sales. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. In this coastal zone, differences in wealth are determined in part by the area of land cultivated by a household and in part by its ownership of fishing equipment. Livestock numbers are a third differentiating factor. Those at the top of the wealth breakdown cultivate between 4 and 8 acres of land, own 1-2 boats as well as nets and other fishing equipment, and own 5-10 cattle, along with other smaller livestock. Those at the bottom cultivate 0.5 to 1.5 acres, own no cattle, and only a small number of goats (if any) and chickens. The difference in access to food and cash income for households at these two ends of the spectrum is quite large, with better off households able to generate all their required food and cash from their own fields, boats and livestock; whereas those at the bottom need to supplement their own production with various off-farm activities. All households have cell phones and bicycles, although those at the upper end have more than one of each. Bicycles act as a key means of transporting people and goods. Cell phones have become an essential means of staying connected to people and information, and there are both productive as well as social reasons for having them. The distribution of wealth in this zone is fairly even. Very poor (17%) and poor (34%) households together comprise just over half of the households in the zone. Middle (33%) and better off (16%) households combined represent just under half the population. Amongst these groups there is a fair amount of re-distribution and intra- community links are strong; better off and middle households hire poorer household members to work in their fields and on their boats. Without the labour of the lower groups, the production that better off groups generate would not be possible. Likewise, without the cash income supplied from agricultural labour, poorer households would not be able to survive. Tanga-Pwani Coastal Belt Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period June 2014 to May 2015. June represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Households in this zone obtain their food in four ways: they grow it themselves, they buy it, they get it from fishing, and they derive it from In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. their livestock (in the form of milk and meat). The differences in relative reliance on these four sources shown in the graph reflect the differences in wealth discussed above in the ‘Wealth Breakdown’ section. Better off households cultivate more land, and therefore have a higher reliance on own crops; they also have more livestock, which gives them access to milk and meat; and they have fishing equipment, which means they consume more of their own catch. Poorer households, on the other hand, with less land, less livestock and less fishing equipment, must buy more of their food to make up for gaps in their capacity to produce it. A range of different crops are grown for consumption, including maize and cassava, the main staples, along with small amounts of paddy, cowpeas, green grams, sesame and coconut. Maize is grown in the masika season, and cassava can be harvested throughout the year as needed. In the reference year a typical poor household produced around 260 kg of maize, a typical middle household produced around 480 kg of maize, and a typical better off household produced around 670 kg. Between 20% and 40% of the maize produced was sold, with poorer households selling a higher proportion than better off households. Thus home-grown maize contributed 15-35% of the minimum calories needed by households. Cassava is produced in higher quantities than maize, and in the reference year very poor and better off households harvested around 480 kg and 2,300 kg of cassava, respectively. Because of its lower calorie per kg contribution, however, cassava accounted for only 10-20% of the minimum calories needed by households, after sales. The other crops provided an additional 5-10% of annual calories, along with maize eaten green, which provided less than 5% of minimum calories. Most of the calories that people did not grow in their own fields, they purchased instead, and the purchase category as a whole accounted for 50-65% of minimum food requirements in the reference year, decreasing in value as you move up the wealth spectrum. Within this category, purchased maize, the cheapest staple, was most important for very poor and poor households (making up 25-35% of minimum calorie needs) and less important for middle and better off households (contributing only 10-15% of minimum calories). Middle and better off households bought wheat flour and rice (more expensive grains) along with fresh fish, beans, sugar, meat, oil and potatoes. The poorer two wealth groups also bought these more expensive non-staple items, but usually in smaller quantities. The ‘purchase’ bar on the graphs above, therefore, represents a different set of priorities, depending on wealth group: poorer households bought food because they had to fill a real food gap; middle and better off households, on the other hand, bought food in order to diversify their food basket. This is further supported by the fact that if better off households had consumed all of their own maize, cassava and bean production rather than selling much of it, they would have been able to cover over 133% of their minimum food needs. Very poor Tanga-Pwani Coastal Belt Livelihood Zone Profile 8 households, on the other hand, given the same assumptions, would have only been able to obtain 50% of minimum calorie requirements from their own production; and poor households also produced less than the amount needed. (Middle households, if they consumed everything they grew in the reference year could have covered 105-110% of minimum calorie needs.) Crops are grown not just for food, but also to generate cash, however, so all households needed to sell some of their production. The poorer the household, the bigger the post-crop-sale gap for the market to address. Milk and meat contributed a small amount to the diet of middle and better off households, covering 2-5% of minimum calorie needs in the reference year. A typical middle household had 1 cow milking, and better off households had, on average, 2 cows milking. Cows here produce approximately 2.5 litres of milk a day during the first rainy season (lasting around four months) and 1.5 litres of milk a day in the second season (which lasts around three months). When added together, the milk from both seasons amounted to around 435 litres for middle households and 870 litres for better off households during the reference year. Over two-thirds of this was sold, providing some cash income (shown in the section below) for these wealth groups, leaving them with enough to cover 2-4% of their calorie needs. Meat from goats slaughtered throughout the year provides better off households with an additional 1% of minimum calories. Poor households may or may not benefit from milk, depending on their livestock profile. Very poor households, who generally do not own cattle, did not have access to this source of food or cash. It is worth noting that the milk from just one cow could have helped very poor households to close the calorie gap (of around 1% of minimum needs) they had in the reference year. Fish caught by the household provide an additional source of calories. All households fish here, some using lines, hooks and baskets, others using boats and nets. Very poor households brought in around 270 kg of fish in the reference year, whereas better off households got around 840 kg. Much of this was sold, but the part retained for home consumption covered 1-4% of annual calorie needs. Although this is quite minor in terms of calories, the protein contribution is nevertheless important, especially for poorer households who do not have access to milking cows. Sources of Cash Income The graphs to the right highlight the unique importance of fishing in the local economy. Households here take advantage of their coastal location to make the most of this plentiful natural resource. In addition, a range of other income sources are drawn on, including crop sales (both food and perennial tree crops), milk sales, livestock sales, petty trade, self employment and local seasonal labour. A fundamental difference in wealth is demonstrated in The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. Tanga-Pwani Coastal Belt Livelihood Zone Profile 9 these graphs: those in the top two groups were able to generate sufficient cash amounts in the reference year from their on-farm and fishing activities alone; but. those in the bottom two groups needed to supplement their on-farm and fishing sources with casual labour sales (in seasonal construction and agriculture) and self- employment activities. This relates back to the differences in productive assets owned and utilized by the different wealth groups. Poorer households are not able to cultivate enough land, do not own enough livestock, and do not have the means to exploit fishing to the extent that enables them to be ‘self- sufficient’ in terms of their production. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,800,000 – 2,200,000 2,200,000 – 3,000,000 3,000,000 – 4,000,000 4,000,000 – 6,700,000 As shown in the graphs, 30-45% of the annual cash income for households in this livelihood zone is generated through fishing. In absolute terms, better off households earn 2.5 to 3 times more from fishing than poor and very poor households. Fishing takes place in the Indian Ocean, mostly at night, using fishing nets, hooks and lines, and on dhows, canoes, and bigger fishing boats. People from very poor and poor households may act as labourers on fishing boats owned by better off households, or on the bigger fishing vessels owned by urban dwellers. They are paid in cash, but also sometimes with a share of the fish they catch. Part of this is used for home consumption, and part is sold. They also devote some time to catching fish on their own using lines and hooks, or baskets. Those on the upper end of the wealth scale own their own boats, or manage larger boats owned by urban elite from Dar es Salaam, Zanzibar or Tanga. The cash generated from these activities is included in the graphs above under ‘fish sales’, and it helps provide households here with access to a source of cash almost all year round that is not available in neighbouring inland zones. Crop sales are equally important as a source of cash for the top three wealth groups, accounting for 35-40% of annual cash income, but they comprise just over 10% of cash income for very poor households, a much smaller share. Middle and better off households cultivate 4 to 6 times more than poor and very poor households, which allows them to sell more of their production while still meeting a large portion of their food needs. Maize is sold in all quantities by all wealth groups, but this is not the main income earner. Cassava, sold in much larger quantities, provides the bulk of the food crop income. Better off households sold over 1,500 kg of cassava (on average) in the reference year, generating as much as 770,000 TZS. Cassava is more valuable per kilo than maize (450 TZS/kg compared to 350-390 TZS/kg for maize) and it is easier for households to grow larger quantities of this drought- resistant perennial than it is to grow maize, which is more sensitive to rainfall irregularities. Very poor households also depend most heavily on cassava, supplementing this with small amounts of cash from pulses, like cowpeas and green grams. However, their total income from crop sales is quite low most years, even in a relatively good year like the reference year. Another reason for their low cash income in this category is that, unlike the top three wealth groups, very poor households do not own any fruit trees or cashew trees. They gather and sell small 4 The average exchange rate from June 2014-May 2015 was 1 USD = 2,000 TZS Tanga-Pwani Coastal Belt Livelihood Zone Profile 10 amounts of coconuts, but other households sell large quantities of oranges, mangoes and cashew nuts, which helps them to almost double the income derived from food crops alone. In addition to fishing and crop sales, the top two wealth groups depended on livestock sales and milk sales to make up almost all their remaining cash income in the reference year, and combined, these two sources accounted for almost 20% of their cash income. These sources comprised only 5-10% of cash income for poor and very poor households. In absolute terms, middle and better off households earned from livestock sales over 3 ½ times more than poor and very poor households. Middle and better off households typically sell a cow (at around 500,000 TZS) once every two years and they sell 3-4 goats (at 55,000 TZS each) every year. Very poor and poor households sell no cattle, and sell only around 1 goat a year. Chickens, which were worth around 10,000 TZS per hen in the reference year, were also sold by all wealth groups, averaging 5-7 hens sold per household. Chickens provided very poor households with almost half of their livestock-based cash income, small as that income may be. Having cattle affords the upper two wealth groups access to milk as well, much of which gets sold. As noted above, households with milking cows sold over two-thirds of the milk they generated in the reference year. This resulted in almost as much cash for better off households as live animal sales. Very poor and poor households, because they have much less crop-based and livestock-based cash income, and because they earn less from fishing, turn instead to manual labour. Land preparation is a particularly difficult task as it is all done by hand; at least two members from poorer households work for middle and better off households during the months before the rains start getting fields ready to plant. They stay on to help with planting and weeding activities as needed, and some are even employed during the harvest months. Seasonal agricultural labour is the most important source of cash for very poor households outside of fishing, and it provided them with around a quarter of their cash income in the reference year. During the off season, when demand for agricultural labour dries up, poorer households seek daily employment in local towns, helping with house construction. Another source of cash, under ‘self-employment’ comes from ‘harvesting’ salt from the sea. None of these alternative sources of cash comes easy; they all require a large investment of time away from one’s own fields and/or fishing, and they are not a guaranteed stream of income, dependent on the vagaries of the weather as well as their neighbours’ demand. Finally, middle and better off households also run small businesses and engage in petty trade, such as owning kiosks, selling prepared foods, and some with motorcycles pursue boda boda (motorcycle hire/transport). Expenditure Patterns The graph presents expenditure patterns for the reference year June 2014 to May 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other areas of Tanzania, households need to spend money throughout the year on a range of goods and services. These include: staple and non-staple food, household items, productive inputs, social services like schooling and health as well as clothing and other The graph provides a breakdown of total annual cash expenditure according to category of expenditure Tanga-Pwani Coastal Belt Livelihood Zone Profile 11 miscellaneous items. There are three main points that emerge when delving into the data that supports the graph above. First, relative expenditure on food, both staple and non-staple, decreases as we move up the wealth spectrum. In other words, poorer households have to spend a larger portion of their annual cash just to meet basic food needs. Even in a normal year like the reference year, very poor households devoted over a quarter of their income to staple foods, which consisted almost entirely of maize grain, the cheapest staple, along with small amounts of rice, beans, oil and dried fish. They spent the same amount on non-staple foods, which included wheat, sugar, fresh fish, meat, and potatoes. The three upper wealth groups spent more on non-staple foods than they did on staple foods, in part because they grew (or caught) more of their own staple foods, and in part because the non-staple foods were preferred commodities, so with more income available, spending on these increased. Second, investments in productive inputs increase substantially as you move up the wealth spectrum. This category includes spending on livestock drugs, seeds and tools, labour, phone credit and fishing equipment. Very poor households generally devoted only 4-8% of their annual budget to productive inputs, either unable or unwilling to spend more. Middle and better off households spent 25-30% of their cash on their various productive pursuits. In absolute terms, better off households spent almost 24 times more on inputs than very poor households. In the reference year, two categories of spending were particularly high for middle and better off households: fishing equipment and labour hire. Middle households devoted around 50% of their inputs budget to hiring seasonal agricultural labour, and 25% to fishing equipment, similar to better off households. The amount that better off households spent on just hiring labour was equivalent to around ten times the amount very poor households spent on all of their inputs combined. Poorer households spent money on livestock drugs, seeds and tools and fishing equipment. Much of their inputs budget was devoted to phone credit. Only better off households invested in buying livestock. Third, in the graph above, the ‘hh items’ category includes basic household necessities, such as tea, salt, soap, kerosene, grinding services, firewood and utensils. Within this category, the two poorer wealth groups spent the most money on soap and kerosene. Soap alone comprised 20-30% of this budget, and kerosene took up an additional 24% in the reference year. Better off households spent the most on kerosene. On an annual basis, spending on basic household goods, which occurred in weekly or daily incremental outlays, accounted for around 10% of total expenditure for all wealth groups. Another point to note is that unlike in many rural zones of Tanzania, all wealth groups spent money on water for human consumption, with very poor households spending around 4,500 TZS a month on water and better off households spending around 12,500 TZS a month on water. Households also spent money on education and medical services, which are shown on the graph as ‘social services’. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, absolute spending on school during the reference year increased as you moved up the wealth spectrum. Better off households spent around 1.5 times as much as very poor households although the difference between middle and better off households was not significant. Very poor households are generally only able to afford to send their children to primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to college. With respect to health costs, better off households again spent around 1.5-2 times as much as very poor households on a per capita basis; it is likely that these households sought treatment, when necessary, at facilities other than the village dispensary. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, bicycle service, savings, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In absolute terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget; and because the reference year was a relatively good year, the two bottom wealth groups have more in this budget than they would in a bad year. But in relative terms this category is fairly constant across all wealth groups. Tanga-Pwani Coastal Belt Livelihood Zone Profile 12 Hazards There are a number of hazards that affect this zone on a regular basis. The first is wild animals, which damage crops and reduce production. Crop pests and diseases, such as stalk borers and striga (or witch weed), which affect maize, and fruit flies, which damage oranges and mangoes, reduce yields on a regular basis, affecting access to both food and cash income. New Castle Disease, which can wipe out an entire flock of chickens, is also a regular concern, especially for very poor households who have no other livestock of note. Finally, conflict between livestock keepers and farmers is a fairly common occurrence in this zone. Pastoralists from other districts come to the coast to find grazing and water resources in the December to March period. Large herds of cattle destroy standing crops and conflict can erupt. The main, and most devastating, periodic hazard is unreliable or inconsistent rainfall, occurring once every three years, and leading to serious declines in crop production. Heavy winds and storms are a problem for fishermen who find their fishing income decline in these circumstances. Less a hazard than a constraint, unfavourable market conditions for local farmers mean they are often forced to accept unfair prices for their commodities and this lowers the income for local residents every year. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer, or eliminating clothing purchases. Poorer households try to increase their labour income from fishing, working more hours on fishing boats and more days, if possible. This strategy is limited by the demand for fishing labour, which can be quickly saturated given the finite number of fishing boats. All households also try to increase their livestock sales. Poorer households have less protection, because they only have chickens and a few goats. Livestock herds are not large for any wealth group in this area, however, and it should be kept in mind that the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through increasing self-employment, especially making more charcoal and collecting and selling more firewood. They also try to process and sell more salt. This option is limited because as the year worsens, the number of people attempting to increasing their income in this way rises, increasing supplies on the market and pushing down prices. The amount of wood available locally is also limited. Better off households try to increase their fishing income by spending more hours at sea. Better off households also may reduce their spending on agricultural labour, which has knock-on effects for poorer households. Better off households with relatives outside the zone might increase their request for remittances, relying on this external source of funds to get them through the year. Tanga-Pwani Coastal Belt Livelihood Zone Profile 13 Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Tanga-Pwani Coastal Belt Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika – amount produced Paddy – amount produced Cassava – amount produced Sesame – amount produced Coconut– amount produced Oranges– amount produced Cassava – producer price Sesame – producer price Coconut – producer price Oranges – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Cow milk – price Cattle – producer price Goats – producer price Other food and cash income Fishing - yields Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Construction – number of jobs Firewood/charcoal – amount collected Self-employment – level of activity Petty trade – level of activity Fishing – producer prices Agricultural wage rates (land clearing and preparation, planting, weeding) Agricultural labour rates (harvesting) Construction – labour rates Firewood/charcoal - prices Self-employment – return on activities Petty trade – return on activities Expenditure Maize grain – consumer price Fish – consumer price Rice – consumer price Beans – consumer price Sugar – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below, prioritized by wealth group, include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. Very poor Poor Middle Better off Improve access to and availability of safe and reliable water supplies Provide affordable and timely access to agricultural inputs Provide affordable access to modern fishing equipment Improve access to and availability of safe and reliable water supplies Tanga-Pwani Coastal Belt Livelihood Zone Profile 14 Increase access to land for crop production Provide affordable access to modern fishing equipment Improve market infrastructure to ensure fair producer prices for both crop and fish produce Provide electric services throughout the zone. Provide affordable access to modern fishing equipment Improve market infrastructure to ensure fair producer prices Improve market infrastructure to ensure fair producer prices Provide affordable and timely access to agricultural inputs Improve road infrastructure | false |
# Extracted Content Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone (TLZ 18) April, 20161 Zone Description The Mbulu-Karatu Midlands Maize, Beans and Livestock Livelihood Zone encompasses parts of Mbulu and Hanang districts in Manyara Region and part of Karatu District in Arusha Region2. This mid-altitude zone is relatively cool, with flat plains broken up by hills and valleys, extending from 1,000 to 2,400 metres above sea level. Most of the zone is covered by agricultural land, which has taken over much of the previously forested areas. The Kilimapunda and Endamaksi mountains are the highest points in the zone. The lowest points are found along the Endagikot River and the Yaeda River valley, which extends from Lake Eyasi. These waterways provide seasonal access to water for people living in close proximity to them. The zone has a relatively well-developed network of roads, although only one is paved. The main arteries connect Mbulu to Babati, Singida and Arusha; and Karatu to Mang’ola and the Serengeti. The main ethnic group residing here is the Iraqw. The population density is 32-45 people per square kilometre3, with higher densities found in Arusha Region and lower densities found in Manyara. There is one long rainy season, from November through April, although this is typically interrupted in February by a stoppage in the rains. Annual precipitation ranges from 700-1,200 mm, and temperatures are cool, averaging 15 - 240 C, dropping as you move up in elevation. Fertile, silt clays and sandy soils are the norm, and the combination of relatively high rainfall and good soils makes this a moderately productive zone. The household economy is built around crop and livestock production. Maize, beans and pigeon peas are the main food crops. A few households grow sunflower as a cash crop. All production is rain-fed. Households use oxen to plough the earth; some households on the upper end of the wealth spectrum also use tractors. The use of improved seeds is common here, and people fertilize their fields with manure from their own livestock. The use of industrial fertilizers is not customary. Weeding is one of the most labour-intensive activities and middle and better off households hire men and women from poorer households during 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 The wards in Mbulu District are: Maretadu, Haydom, Maghang, Dongobesh, Bashay, Tlawi, Mbulu Mjini, Bargish, Sanu and Masieda. The wards in Karatu District are Baray, Daa, Endabash, Kansay, Endamarariek, Qurus and Karatu. 3 Based on the 2012 national census. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 2 weeding periods, and to a lesser extent for harvesting. Some people also migrate seasonally to coffee estates in Karatu District. Livestock provide a source of food and cash for all households. Cattle are the most valuable livestock, providing milk for consumption and sale and acting as a bank account, drawn down on every year to provide cash for a range of basic necessities. Bulls also get converted into plough oxen, providing a critical source of agricultural labour. Goats and sheep are also kept, eaten especially during festivals and sold for cash income. Chickens are used for eggs, eaten throughout the year, and sold whenever cash is needed, especially by poorer households. Pigs are kept by some households as well. The larger livestock migrate during the dry season, taken to areas within 20 or 30 kilometres from the villages, where better access to pasture and water can be found, such as Yaeda Chini or the Eyasi Basin. Rainy season water sources for livestock include charcoal dams, the perennial rivers, seasonal rivers, shallow wells and seasonal ponds. In the dry season, livestock use reservoirs and dams, the perennial rivers and wells. Men manage the cattle, goats and sheep; women are responsible for the chickens and pigs. In addition to crop and livestock production, brick sales and firewood and charcoal sales bring income to poorer households. These sources of cash, along with seasonal agricultural labour, are of critical importance to households who do not have enough land and livestock to make ends meet. Service provision in this zone is basic. Water for all purposes comes from seasonal rivers, ponds, open wells, boreholes and tap water. There is some payment expected for tap water, but the other sources are free. The quality of water is quite poor in most villages, with the exception of villages where tap water is the main source, such as Endagem, Changarawe and Qurus in Karatu. Sanitation facilities consist of pit latrines with no covers. Waste is collected and burned. Health dispensaries are found in many villages, or at the ward centre, although these are often poorly stocked and under-staffed. Better off households have access to private hospitals if they can make their way to Mbulu, Karatu or Arusha. Primary schools are found in the villages and secondary schools are available in the ward centres, which are often too far for children to reach on a daily basis. Poorer households only send their children to primary, or at most secondary school. Better off households usually manage to send their children to at least secondary school and often to college. There is electricity in only a few villages; in most villages households depend on solar lamps and solar panels. Households in all wealth groups have mobile phones, with better off households having multiple phones. Better off households have access to credit through VICOBA, SILC and SACCOS. Savings facilities are provided through VICOBA and SILC. A number of NGOs and government agencies operate here, including TASAF (Tanzania Social Action Fund), which supports poorer households by providing funds to cover food, education and health as well as helping build hospitals, schools and bridges, etc.; the Diocese of Mbulu Development Department, which undertakes the construction of improved toilets and toilet seat covers for schools; the Roman Catholic church, which supports the construction of bore holes; and HELVETORS, which undertakes actions to prevent post-harvest losses. Markets The transportation infrastructure in this zone is variable, with relatively good access in the dry season, but serious problems during the wet season. Mbulu and Karatu are the main intermediate markets and Arusha is a central terminal market. There is only one tarmac road in the zone, connecting Karatu to Arusha and Ngorongoro gate. The others, from Singida to Haydom and Mbulu; and from Babati to Mbulu are not paved. The more remote villages are hard to reach, accessed via rough dirt roads, many with deep eroded gullies. In the dry season these roads are passable, but they become difficult to traverse in the wet season. Most of the bridges are in relatively good condition. Well-worn dirt tracks take people by foot from villages to cultivated fields, pastures and water points, and walking is the most common means of transportation. Maize, beans, pigeon peas, sunflower, cattle, goats and sheep are the commodities sold by households in this zone. Locally-produced crops are purchased by small traders at the farm gate. August and September are when traders come to villages in order to buy up maize harvests, and any pigeon peas that local Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 3 households might want to sell. The traders arrange for crops to be bundled and transported to larger market hubs during the post-harvest dry season months, when trucks can still travel on the dirt roads. Haydom, in Mbulu, is one of these market hubs; Karatu is another. Arusha is the terminal market for maize, but pigeon peas are often exported after being transported to Dar es Salaam via Arusha. Beans are sold in March and April, following the same trade route used for maize. Sunflower, sold mostly by better off households, is collected in Haydom or Karatu, where it is processed into oil for local consumption. Cattle, goats and sheep are sold at small weekly ward- and sub-ward level markets within the zone throughout the year. Traders generally do not come to the villages for livestock, with the exception of pigs. From the livestock markets, traders collect and transport livestock to Duka Bovu in Arusha, and then on to Weruweru in Kilimanjaro, Korogwe in Tanga and finally the Pugu market in Dar es Salaam. Much of this trade takes place from August to November, just before the rains start in earnest. This is a time when households need extra cash in order to pay for agricultural inputs; and it is also a time when roads throughout the zone are still accessible. In addition to local commodities that are sold for ‘export’ from the zone, there is an active importation of food and other basic goods for consumption by local households. Poorer households need to buy maize grain to cover their needs for seven to nine months of the year, especially from November to March, even in relatively good production years. Maize is the cheapest local staple, and all of this is locally sourced, procured from better off households who generally produce a large surplus. Rice, purchased mostly by the upper wealth groups, is sourced from Magugu and Shinyanga, collected in Mbulu and Karatu and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local markets. The labour market is almost entirely local seasonal agricultural labour. Middle and better off households cultivate large tracts of land, requiring additional labour to help them complete the more intensive seasonal tasks, especially weeding and harvesting. It was estimated that in the reference year, 90% of seasonal labour was found within the zone on local farms. An additional 5% of labour demand came from local towns and the other 5% came from outside the livelihood zone, mainly from the Oldeani coffee estates in Karatu District. Both men and women from poorer households take on paid agricultural work. The coffee estates are a primary place for seeking work in bad years, when poor rains reduce local production. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the planting season in December and ends with the harvest in June through August of the following calendar year). Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year of 2014- 2015 was average, with average rainfall, a decent harvest, average staple food prices, and average livestock prices. The reference year followed an average year and a below average year. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an average year after a fairly normal sequence of years. Production Year Season Rank Critical Events 2014-2015 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 2013-2014 Masika 3 Average rainfall, good crop yields, average staple food and livestock prices. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 4 2012-2013 Masika 3 Average rainfall, good crop yields, average staple food and livestock prices. 2011-2012 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 2010-2011 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, people sold more livestock and poorer households increased the time spent on agricultural labour in the Oldeani coffee estates. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year The seasonal calendar below highlights the competing demands of livestock raising and crop production in this agro-pastoral zone. The rains determine the timing of productive activities here, signalling the start and stop of a range of crop and livestock management tasks. There is one long rainy season, which begins in November and continues through April, although it is common for rains to stop for a while in February. People begin to prepare lands in October and continue this through November, as the new rains help to soften the ground. The November rains also provide a welcome boost to pastures. All crops are planted in December and January, followed by a period of weeding that lasts from mid-January through April. Maize, beans and pigeon peas are inter-cropped; sunflower is planted as a single stand around the edges of fields. The green harvest of maize starts in April, although beans can be harvested green as early as March. June marks the start of the main maize harvest, which lasts through August. This coincides with the sunflower harvest, which is relevant mainly for better off households. Pigeon peas are harvested as late as September and October. As planting activities are in full swing, in January, milk production begins to increase as a result of fresh pastures and renewed sources of water that come with the rains. The rains also bring livestock diseases. Contagious Bovine Pleura-pneumonia (CBPP), Contagious Caprine Pleura-pneumonia (CCPP) and Black Quarter occur with higher frequency during the rains. Thus, as people are busy in their fields, they also must contend with more work related to milking and caring for livestock. Livestock sales are highest from July to October, a time when households are putting together the cash they need for the coming agricultural season. The peak agricultural labour period is during weeding time. Land preparation is not as arduous here as in many areas because ploughing is done with ox ploughs, not hand hoes. Poorer households who do not own oxen themselves obtain access to oxen and ploughs by exchanging their labour for it. This reduces the effort involved in land preparation and ploughing, and it means that poorer households are generally not paid in cash for any work related to land preparation. Weeding, however, is done entirely by hand, and poorer households are hired throughout the weeding period to work on the larger farms of middle and better off households. At the same time, poorer households need to weed their own fields, which leads them to split their labour pool, sending some members to work for cash, while others work in their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. They often also miss the best times for ploughing and planting because they must wait for plough oxen to finish cultivating the farms of the oxen’s owners before being deployed to their farms. The weeding period coincides with a time when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as September or October, but by November none of the poorer households have their own food stocks left at home. These households need to purchase all of their staple foods Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 5 just when the price of staple foods is highest (from December through March). Thus, the paid work offered up by middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize begins. The rainy season is also when most human illnesses occur. Malaria is a serious problem here, and the rains bring about a new influx of mosquitoes and a greater incidence of sickness. This increases the expenditure requirements for medical treatment at a time of year when other outlays (on staple food and education – in January) are already high. Remittances from relatives living outside the zone are most commonly sent in January and February to help cover school fees and also to help cover the costs of staple foods. The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35 -year period (1980-2014). Source: TZ Meteorology Department Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 6 May through October is the dry season. At this time, poorer household members earn extra cash by collecting and selling firewood, or making charcoal. Brick making also peaks at this time. It is often women and children who collect the firewood; men are involved in charcoal and brick production. People need to set aside money at this time to prepare for the costs associated with the coming agricultural season and to pay back any loans accrued in the past year. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The main determinants of wealth in this zone are, first, the amount of land a household cultivates and, second, the number of livestock, particularly cattle, a household owns. In important ways these two things are inter- related: bigger herds generate more cash, which enables people to buy or rent tractors and hire labourers to expand the area they have under cultivation. On the other side, the more land a household has under cultivation, the larger its harvests; and with more crop production, a household is able to reduce the money it spends on food for survival, and – with the proceeds from crop sales - invest more in the health and growth of its livestock herd. A typical better off household, therefore, cultivates around 7-9 acres and owns 15-25 cattle, 20-40 goats, 5-20 sheep and 6-8 oxen. These are slightly bigger households, with around 7-9 members. In addition to land and livestock, other assets, like ploughs, ox carts and cell phones are commonly owned. Of all the households, these are the most likely to have a motorcycle as well, which can provide additional cash through boda boda (motorcycle taxi or transport hire). Better off households benefit from surplus crop production and sizeable supplies of milk. These households hire very poor and poor household members to help with weeding and harvesting activities, because they do not have enough intra-household labour to manage their fields on their own. A typical very poor household, on the other hand, cultivates only 1.5-2 acres of land, working in exchange for access to plough oxen. These households have no cattle, and small numbers of goats (2-6), sheep (0-2) and pigs (0-2). They have 5-15 chickens which are, relatively speaking, significant to them as a source of cash. Very poor households tend to be smaller in size, with only 5-7 members. This means that they have a difficult time managing the many competing labour requirements associated with the cropping season, especially since they need to work on both their own fields and the fields of better off households, where they earn cash that is critical to their survival. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 7 The distribution of wealth in this zone is weighted towards poorer households, with very poor (30%) and poor (32%) households together comprising over 60% of households in the zone. Middle (26%) and better off (12%) households combined represent just over a third of the population. However, as middle and better off households are slightly larger, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is larger than this. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12- month period. This was considered an average year, with average rains, crop yields and prices. Own crops, own milk and meat, and purchased food are the three In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. sources of food in this livelihood zone. Households’ own crop production made up 45-65% of minimum calorie requirements for very poor and poor households in the reference year, with maize, beans and pigeon peas the only food crops grown. This means that even in an average year, poorer households do not depend on their own crop production to cover all of their own food needs. Middle and better off households produced considerably more, meeting the vast majority (90-98%) of their minimum calorie needs with their own crops; in addition, what they consume is only a portion of the total they grow, since a good deal of their crops are sold in a year like the reference year. In fact, if households did not sell any of the crops they produced, consuming them instead, all except for the very poor would well exceed their minimum calorie requirements. The reference year production of maize for typical very poor, poor, middle and better off households was 970 kg, 1,800 kg, 3,200 kg, and 5,050 kg, respectively. For beans and pigeon peas combined it was 210 kg, 315 kg, 495 kg, and 910 kg, respectively. In calorie terms, the total production of maize and beans together represented 90%, 150%, 230% and 330% of minimum calorie requirements, respectively. All households, however, sold at least half of their production for cash (with sales as a proportion of production increasing as you move up with wealth scale) to meet a range of expenditure requirements throughout the year, which means that their own crop production covered less of their food needs than it could have. Milk, and to a much lesser degree meat, provided additional calories in the reference year, but only for the top three wealth groups. Very poor households own neither cattle nor substantial numbers of goats, and do not benefit from this source of food. A typical poor household had around 1 cow milking throughout much of the year, middle households had around 3 cows milking, and better off households had 5 cows milking. Milk yields are not very high in this livelihood zone due to limitations on pasture, but the 1.25 litres per cow per day during the rainy season, and 0.5 litres a day in the dry season accumulated over the year to total around 220 litres for poor households, 660 litres for middle and 1,100 litres for better off households. The upper two wealth groups sold 15-30% of this in the reference year, leaving them with enough milk to cover around 6% of their annual calorie needs; poor households did not sell any of their milk, using it all for home consumption. For them, milk covered around 3% of their food needs. There was also a small contribution (only around 1% of calorie needs) from goat meat for middle and better off households. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 8 Food purchased from the market made up all of the remaining food needs for all wealth groups, comprising around 20-45% of minimum calorie requirements. Those in the upper two wealth groups bought less (20-21% of minimum calories) and those in the bottom two wealth groups bought more (35-45% of minimum calories). This is because, as explained above, poorer households produced less of their own food in the reference year and needed to buy food to make up for the gap. What poorer households purchased supports this argument: 28-36% of their minimum calories were comprised of purchased maize grain, the cheapest staple. Middle households bought only 5% of their calories in the form of maize grain, and better off households purchased no maize grain at all. The ‘purchase’ component for better off households was comprised of high-value, preferred foods, such as rice, wheat, sweet potatoes, meat, oil, sugar, Irish potatoes and dried fish. Thus, the 20% of minimum calories purchased by these households diversified their diets and added nutrients and protein they otherwise could not produce themselves. Poorer households, on the other hand, purchased only around 8-9% of their minimum calories for the sake of diversity, and most of this was oil. The largest portion of their ‘purchase’ component was devoted to filling a real calorie gap and meeting their minimum food needs for the year. Sources of Cash Income The graphs to the right present the sources of cash income in the reference year by wealth group, first in terms of absolute values, and next as a proportion of annual cash income. They reveal a number of points about the local household economy. First, livestock- related income is clearly important for the top three wealth groups. Thus, even in a year of decent crop production, cash income depends more on livestock than on crops. Second, there is a noticeable difference between the sources of cash income for those in the upper three wealth groups and those in the bottom wealth group. Very poor households derived more than half of their annual cash income from off their own farms, working for others, or generating income from self- employment activities. The top three wealth groups, on the other hand, obtained 80- 100% of their cash income from their own farms – both from crops and from livestock – in the reference year. The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 9 There were five main sources of cash income in the reference year: own crop sales, own milk/egg sales, livestock sales, seasonal agricultural labour, and self-employment. On average, better off households’ annual cash income was over four times higher than very poor households’. In the reference year, crop sales accounted for 27-46% of cash income for households. Maize, beans, pigeon peas and sunflower are sold, although sunflower is only sold by better off households. Maize provides the majority of crop-based cash income, accounting for over two-thirds of the cash earnings from crop sales. Beans and pigeon peas garner a higher price than maize, sold at an average of 2 ½ times more per kilogramme, but far larger quantities of maize are sold. In the reference year, beans brought in 30-40% of the crop-sale income for local households. In years when rains are inconsistent, beans become even more important, as they have a higher tolerance to drought than maize, and their price tends to increase in bad years. Better off households grow and sell a small amount of sunflower as well, although this is not crucial income when viewed on an annual basis. In absolute terms, better off households generated over 7 times more from their crop sales than very poor households, which is proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 4.5 times more land than very poor households, but are able to derive more per acre from their efforts, investing more in terms of labour and inputs, and able to time their ploughing, labour and inputs applications for more effective outcomes. Sales of live animals (fattened oxen, cattle, goats, sheep, chickens, and pigs), milk and eggs provided an additional source of earnings in the reference year, making up around 15% of very poor household annual cash income, and 45-65% of middle and better off cash income. Poor, middle and better off households sold, on average, 0-1, 1-2, and 2-3 oxen (at 500,000-600,000 TZS per head), respectively, in the reference year; along with 1-2 heads of cattle (at around 300,000 TZS per head); 2-5 goats (at 35,000 TZS each) and 1-3 sheep (at 25,000-30,000 TZS each). Of these, very poor households sold only goats and sheep, 0-2 in total. All households also sold chickens, averaging around 8 hen sales per year at 8,000 each. Although households sell a number of livestock species, cattle are the most important, and the cash that better off households generated with their cattle and oxen sales alone exceeded the average annual cash income (all sources combined) of both very poor and poor households. Cattle are also important because of the milk they provide, and the upper two wealth groups both benefitted from milk income, accounting for around 4-8% of their total cash earnings. In addition, egg sales contributed a small amount of cash for all four wealth groups. While better off households obtained almost all of their cash income from livestock- and crop-based sources, poorer households needed to supplement their farm-based cash income with other options. Seasonal agricultural labour and self-employment both provided additional cash for poorer households, and these are especially important sources for very poor households. Weeding is a busy time, and very poor and poor households split their efforts between their own farms and the farms of middle and better off households, where they work for a daily fee. As mentioned previously, because middle and better off households use ox ploughs and tractors, land preparation activities are not as labour-intensive, and people are not usually hired for land preparation and planting. But weeding is done entirely by hand and occupies people’s time for three months of the year. People also get hired for harvesting work, but this lasts only for around a month. Seasonal agricultural labour provided very poor households with around a quarter of their cash income in the reference year, and it provided poor households with around 10% of their cash income. In the dry season, after the harvest ends but before the next agricultural season begins (July to December), poorer households rely on making and selling bricks as a source of earnings. Very poor households also gather and sell firewood and make charcoal. These self-employment activities account for around 35% of annual cash income for very poor households and around 5% of poor households’ cash income. Finally, better off households obtained a small amount of their cash during the reference year from credit. Technically this is not ‘income’ in the same sense as other sources, because it must be paid back with interest; but it does provide these upper households with additional financial resources with which to fund their productive activities. None of the other wealth groups had access to credit in the reference year. Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. There are a number of essential goods and services that households in this zone need to spend their money on each year. These include: staple and non-staple food, household items, productive inputs, social services, like schooling and health, in addition to clothing and The graph provides a breakdown of total annual cash expenditure according to category of expenditure other miscellaneous items. The graph illustrates a general trend in rural Tanzania: poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. These trends are discussed in more detail below. In an average year, like the reference year, all wealth groups buy staple foods, however the composition of the staple food basket is not the same for all wealth groups. In this zone, staple foods were defined as maize grain, sweet potatoes, wheat flour and rice. Very poor households devoted almost all of their expenditure on staple foods to maize grain, the cheapest staple, spending nothing on sweet potatoes or wheat, and only a very small amount on rice. Better off households, on the other hand, bought no maize grain, but did spend money on sweet potatoes, wheat flour and rice, all of which are preferred higher-priced foods. (For example, rice costs 2,000 TZS per kg on average, whereas maize grain costs around 555 TZS per kg.) Thus, poorer households bought staple foods to fill a calorie gap, whereas better off households bought staple foods to fill a diversity gap. This is an important point, because without the purchase of staple foods, the very poor wealth group would have been facing a food deficit, but the same cannot be said for the two upper wealth groups. The same motivation extended to non-staple food purchases, a category in which better off households spent over three times more than very poor households. The non-staple foods category includes money spent on beans, sugar, meat, oil, fried fish, vegetables and Irish potatoes. Sugar and oil comprised 50-60% of the non-staple food budget for all wealth groups; sugar is used in relatively high amounts here, with around 1.5-1.75 kg of sugar purchased and consumed by the upper two wealth groups every week, and closer to ½ kg per week consumed by the lower two wealth groups. The lower two wealth groups did not buy vegetables and Irish potatoes, mainly buying sugar, oil and dried fish, along with small amounts of beans. Their spending on meat was quite minimal. Middle and better off households spent substantially more on meat, but tended not to buy beans (since they produced enough of these on their own). They also devoted more cash income to vegetables and Irish potatoes, although the latter was purchased only by better off households. The dark blue bar on the graph above represents spending on productive inputs, including the following: livestock drugs, spare parts for fixing ploughs, seeds and tools, labour hire, livestock purchase, house repair, phone credit and loan repayment. Of these items, very poor households spent money only on seeds/tools and phone credit, with a roughly equal amount spent on each. Poor households spent most of their money on seeds/tools (30% of their inputs budget), livestock purchase (28% of their inputs budget) and phone credit (26% of their inputs budget). They also spent some cash on livestock drugs and house repairs. Middle and better off households spent the majority of their inputs budget on labour hire and livestock purchases. In absolute terms, better off households Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 11 spent more than 20 times the amount spent by very poor households and double the amount spent by middle households. Better off households had to invest large amounts of cash into hiring labour (which took almost a third of their inputs budget in the reference year), and livestock purchase (which took around a quarter their inputs budget). A typical better off household spent around 502,200 TZS on hiring labour in the reference year. When we compare this to the amount of seasonal labour income very poor households obtained in the reference year (around 234,000 TZS) we see that every better off household supported around 2 households in the very poor wealth group. This highlights the particular importance of this intra-community exchange of labour and cash: very poor households could not survive without this income; and better off households need the labour from very poor households to generate their surplus production. One final point is that better off households are the only ones who have to spend money repaying loans: this takes up around 10% of their inputs budget. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, kerosene, grinding services and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor households spent the most money on payment for grinding, which took up around 40% of their spending in this category, followed by soap. Poor households also spent the most money on these two categories, with the combined spending on these two items alone comprising around 60% of their inputs budget in the reference year. Middle and better off households spent the most on soap followed by grinding and utensils. On an annual basis, spending on basic household goods comprised 7-13% of total expenditure, decreasing as a proportion of annual expenditure as wealth increases (although increasing in absolute terms). ‘Social services’ includes schooling and health costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, middle and better off households spent around the same amount on education, and these two wealth groups spent around 2 times more than very poor households, although not much more than poor households. Very poor households are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent three times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute and relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was a relatively good year, even the very poor wealth group had more in this budget than it would in a bad year. Hazards There are a number of hazards that affect this zone on a regular basis. The first is livestock disease, such as Foot and Mouth Disease (FMD), tick-borne diseases and East Coast Fever. Contagious Bovine Pleuropneumonia (CBPP) and Contagious Caprine Pleuropneumonia (CCPP) affect cattle and goats, respectively4. Helminthiasis (worms) is a common problem, as well as New Castle Disease, which can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. The second is crop pests and diseases. Stalk borers, which affect maize; and aphids and rust fungus, which reduce yields for beans, cause lossees throughout the zone almost every year. Birds can also ruin crops. The main, and most devastating, periodic hazard is inadequate rainfall, which leads to serious declines in crop production, degradation of pastures, drying up of local water sources and spikes in food prices. This occurs once 4 http://www.lrrd.org/lrrd26/8/swai26138.htm Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 12 every three years. Army worms devastate local maize harvests once every five years. Floods also cause damage to crops once every five years, on average. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. All households also try to increase their livestock sales. Poorer households sell more goats, sheep and chickens, and some sell pigs. Middle and better off households sell more cattle, oxen, goats, sheep and chickens. This strategy is far more successful for middle and better off households than for poorer households. Poorer households have less protection, because they can afford to sell only a few animals and still maintain viable herds. Also, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people go to the Oldeani coffee estates in Karatu District. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Better off households decrease the amount of money they pay (wage rates) for agricultural labour. This directly contradicts the attempts made by poorer households to increase their casual labour income. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika – amount produced Beans – amount produced Pigeon peas – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Livestock production Cow milk – yields Fattened oxen – numbers per household Cattle – herd size Goats – herd size Sheep – herd size Pigs – numbers per household Cow milk – price Fattened oxen - price Cattle – producer price Goats – producer price Sheep – producer price Pigs – producer price Mbulu-Karatu Midlands Maize, Beans & Livestock Livelihood Zone Profile 13 Chickens – flock size Chickens – producer price Other food and cash income Agricultural labour (weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Brick production – numbers produced Firewood/charcoal – bundles collected Self-employment – level of activity Credit – amount of credit issued Agricultural wage rates (weeding) Agricultural labour rates (harvesting) Bricks – prices Firewood/charcoal – price per bundle Self-employment – return on activities Credit – terms/rates of repayment Expenditure Maize grain – consumer price Sugar – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than credit, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Timely and affordable provision of crop and livestock inputs to all households Access to affordable and safe sources of water for humans and animals Provision of health services at village level, including qualified health professionals and sufficient and affordable supplies of medicines Improved maintenance of existing road networks and increased construction of new roads Provision of electricity at village level Improved livestock health infrastructure, including dip tanks, charcoal dams and crushes Targeted capital investments in agricultural activities and entrepreneurship | false |
# Extracted Content Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone (TLZ 25) April, 20161 Zone Description The Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone2 is found in the central-northern part of Tanzania, and it includes parts of Babati, Hanang and Singida districts. The zone sits at a relatively high altitude, with elevation ranging from 1,000 to 2,000 metres above sea level. Mt. Hanang, which is found here, rises to 3,420 meters above sea level. The topography is made up of rolling plains and valleys, and mountainous terrain around Mt. Hanang. Agricultural fields surround villages, and outside of these areas one finds bush-covered savannahs and some marshlands in the Bubu River catchment. This river, along with a number of seasonal waterways, such as the Bagara, Endasaki and Dirma rivers, provide water for people living nearby. Other open water sources include Kisisi and Matumbo lakes, along with a number of smaller seasonal ponds. Bassotu, Gendabi, and Balandalalu are salt lakes, providing occasional opportunities for salt mining. The zone’s road network is fairly extensive, with a tarmac road connecting Babati and Singida, and dirt or marram roads connecting Katesh to Kondoa via Dirma; Katesh to Hydom via Basutu; and Singida to Meatu via Mudida and Mkalama. The main ethnic groups found here are the Iraqw, Gorowa and Barabaig in Babati and Hanang; and the Nyaturu in Singida. The population density is 28-78 people per square kilometre3, with higher densities found in Manyara Region and lower densities found in Singida. The rains here fall from mid-November to April, interrupted for one month in February by a dry spell. Annual precipitation ranges from 350-1,2004 mm and temperatures average 20-300 C in the hot season, and 16-200 C in the cooler months. The soils are fertile red and black loams, and when rains are good, this zone can expect high levels of crop production. In years when the rains are insufficient or poorly distributed, production drops substantially and households have trouble covering their food needs. The household economy is based on crop production and livestock husbandry. Maize, sorghum, beans, pigeon peas, and sunflower are all grown, with maize and beans the central food crops; and sunflower the 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2013 and ended in March 2014. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 The zonal boundaries for TLZ25, as drawn during the 2008 FEWS NET livelihood zoning, need to be revised as follows: Qash, Bonga and Gidas are not in this zone, but in TLZ16; and Nkaiti, Mwada, Magugu and part of Kiru wards should form a separate zone as this area benefits from irrigation and grows maize, cotton, sesame, rice, sugarcane and watermelon, and there are more cattle per household. 3 Based on the 2012 national census. 4 Hanang DC gets 350-900 mm; Babati DC gets 500-1200 mm; Singida DC gets 500-850 mm. Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 2 main cash crop. However, it is misleading to think of the food crops as being grown just for consumption, since all food crops are also sold, with pulses especially important in terms of cash earnings. All production is rain-fed. Ploughing is done using oxen for the most part, although some households on the upper end of the wealth spectrum use tractors, and those at the bottom end may use hand hoes. Some poorer households work for better off households in exchange for use of their plough oxen. Most households buy improved seeds but they do not buy industrial fertilisers. People either fertilise their fields with manure from their own livestock or they do not use it. The agricultural season involves periods of intense labour; weeding is especially arduous, done using hand hoes, and threshing is also done by hand. Middle and better off households have more land under cultivation than they can manage with just their intra-household labour, so they hire members from poor and very poor households to work for them during these labour-heavy times of the year. This provides important cash for poorer households, who could not survive without this seasonal work. This zone is distinct from neighbouring livelihood zones like TLZ16 and TLZ55 in that these other zones rely on different crops, like bulrush millet, sesame and groundnuts. Livestock is a secondary, but vital, source of food and cash for all households. Cattle are the most prized of the livestock, and they are owned in the greatest numbers by households at the upper end of the wealth spectrum. Cattle provide milk for consumption and young bulls are sold for substantial amounts of cash when needed. Select bulls also get converted into plough oxen. Goats are also sold for cash income, and slaughtered for meat during festivals or special events. Chickens are eaten and sold whenever cash is needed, especially by poorer households. The larger livestock migrate during the driest months of September, October and November, taken to grazing areas in Singida around a national forest in south- eastern Ngimu, or to the southern parts of Hanang, where better pasture and water sources can be found. Wet season water sources for livestock include seasonal and perennial rivers and seasonal ponds. In the dry season, livestock use water from deep wells. There is payment for tap water for use by livestock in some villages. Men manage the cattle and goats; women are responsible for the chickens. If households are unable to find enough work locally, they may also send members to work in towns or to sugar plantations in Moshi or flower plantations in Arusha. A few individuals also find work mining salt or sand and gravel, but this is not typical for all households. A minority of households near the lakes engage in fishing but this is not typical for the zone. In bad years, poorer households also collect and sell firewood to earn extra cash. The services in this zone are similar to many rural areas in Tanzania. Water for all purposes comes from open wells, charcoal dams, local shallow wells, boreholes and village taps. People usually pay a small fee to use the tap water, but all other sources are free. However, there is no guarantee that these other sources are safe to drink. Sanitation facilities consist of pit latrines, most without covers. Health dispensaries are found in many villages, or at the ward centre, but they are not always well-stocked or staffed with qualified medical professionals. Traditional healers are sought out in many cases. Primary schools are found in the villages and secondary schools are available in the ward centres. It is common for all households to send their children through primary school, but only middle and better off households are able to afford the extra costs of secondary school. There is no electricity, so poorer households depend on kerosene lamps, battery-operated torches and some solar lamps; better off households generally use solar lamps. Households in all wealth groups have mobile phones, with better off households owning multiple phones. Telecommunications services are provided by Airtel and Vodacom networks. Credit facilities do not exist for the most part. Households can take part in VICOBA savings schemes, which provide a rotating mechanism that allows each member to contribute cash on a regular basis throughout the year and receive annual disbursements. No NGOs of note are working in this zone. Markets The transportation infrastructure is relatively good. A main inter-regional tarmac road, from Babati to Singida, passes through the zone and there are other decent dirt roads connecting Katesh to Kondoa, and Kateshi to Highdom. Access to more remote, interior villages is not ensured during the rainy season, when Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 3 roads become muddy and impassable; but in the dry season, vehicles are able to get around with relative ease. People travel by foot from villages to cultivated fields, pastures and water points, and walking is the most common means of transportation for most. Babati, Katesh and Singida are the main intermediate markets, along with Arusha. Dar es Salaam, Mwanza and Nairobi are all terminal markets. Market information is conveyed through relatively good mobile phone networks, and there are emerging small business centres at the village and ward levels. Locally-grown maize, beans, pigeon peas, and sunflower are sold by all households, providing the most important source of cash for many. Livestock, cattle, goats and chickens, provide a secondary source of income. Sheep and pigs are not commonly kept here. Transactions around crops occur at the farm gate; traders circulate from village to village and buy up crops and then transport them to either Babati, Katesh or Singida. The traders arrange for crops to be bundled and transported to larger market hubs during the post-harvest dry season months, when trucks can still travel on the dirt roads. Maize typically remains in these terminal markets for regional consumption, whereas beans, pigeon peas and sunflowers continue onwards. These crops are taken either to Arusha or Singida and then to Dar es Salaam or Nairobi (from Arusha) or Mwanza (from Singida). Maize is traded from July to September; sunflower is traded from May to August; and beans are traded from August to October. Livestock are sold at small mobile ward- and sub-ward level markets within the zone throughout the year. From the livestock markets, traders collect and transport livestock to one of the intermediate markets (Babati, Katesh or Singida) and then on to Arusha or Dar es Salaam. Cattle are sold most frequently from July to August; this is a time when livestock body condition is good, with animals fattened on recent crop residues, and roads are still accessible before the heavier rains in March and April. Middle and better off households need money at this time to cover school fees, uniforms and stationery for the second term. They also are putting cash together to pay for the many cash needs associated with the agricultural season. Also, traditional festivals, marriages and religious ceremonies occur in this period. Peak months for selling goats are July, December and March, the first two of which are associated with school fees, festival or holidays seasons and the last of which is associated with peak staple food expenditures, weeding payment and livestock drugs. Poorer households need to buy maize grain, the cheapest staple, to cover their needs for five to seven months of the year, especially from December to March, even in relatively good production years. Most maize is locally sourced, procured from better off households who generally produce a large surplus. In bad years, maize comes into the zone from Arusha. Rice is purchased as well, most commonly by the upper wealth groups, and this is sourced from Igunga, Magugu and Shinyanga and comes into the zone via Babati, Katesh and Singida and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local markets. The labour market is mostly local and consists of seasonal agricultural labour. There is also a sizeable demand from local towns and some work is found outside the livelihood zone. It was estimated that in the reference year, 70% of seasonal labour was found within the zone on local farms. An additional 20% of labour demand came from local towns, especially Singida town, and the other 10% came from outside the livelihood zone, mainly from sugar plantations in Moshi or flower plantations in Arusha. The balance shifts in bad years, with more people traveling to local towns or to areas outside the zone to find work. A certain amount of casual labour is also found in the salt mining areas of Gendabi, Balangidalalu, and Basutu, or from sand and gravel mining, but this is not typical for most households. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Manyara- Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone the reference year covered the consumption period from April 2013 to March 2014. This followed on the production year of 2012-2013. The production year starts with the planting season in November/December and ends with the harvest in June through Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 4 August/September of the following calendar year. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the responses of the community leaders, shows year quality by production year. The reason that the consumption year of 2014-2015 (following the 2013- 2014 production year) could not be used as a reference year is because it was an excellent year, which would not have been representative of livelihoods in this zone. Thus, the production year of 2012-2013, which corresponds to the consumption year of 2013-2014 was used, as this was an average year. In the past five years most have been average, with one excellent year and one below average year. This most recent production year (2014-2015) is the worst of the past five years. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an average year. Production Year Season Rank Critical Events 2014-2015 Masika 2 Poorly distributed rains leading to low crop yields; high staple food prices with low livestock prices. As a result, the top three wealth groups sold more livestock; there was increased attempt to find work among very poor and poor households, with migration to other areas 2013-2014 Masika 5 Excellent amount and distribution of rainfall leading to bumper harvest and low staple prices 2012-2013 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 2011-2012 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 2010-2011 Masika 3 Average rains in terms of amounts and distributions; average harvest; normal food prices 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year There is one long rainy season which begins in November and lasts through April. A dry spell occurs most years in February, and the rains that follow, in March and April, are usually heavier than those from November through January. The rains determine the timing of all the productive activities, signalling the start and stop of a range of crop-related and livestock management tasks. People begin to prepare their fields just after all of the crops from the previous year have been harvested, starting in September, and continuing through November. The November rains help to soften the ground enough to allow for planting of maize to begin part way through November. Pulses and sunflower are planted in December. Maize is often inter-cropped with the other crops, with combinations of maize and beans, maize and pigeon peas and maize and sunflower found throughout the zone. The green harvest of maize starts at the end of March or the beginning of April, although beans can be harvested green as early as February. June marks the start of the main maize harvest for maize and sorghum, which lasts through August. Beans can be planted and harvested twice, with March and July the main harvesting months for this crop. The sunflower harvest occurs from May through June. Pigeon peas, a long cycle crop, are harvested as late as August and September. A period of threshing and sales follows the harvest of each crop. Livestock activities occur in tandem with many agricultural tasks. Milk production begins to peak in January, just as households are in the midst of planting and weeding. Milk yields increase as a result of fresh pastures and renewed sources of water that come with the rains. Milk is consumed almost exclusively by the upper wealth groups, although some poor households may also benefit from this boost in nutrition. On the downside, the rains Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 5 also bring livestock diseases, such as Contagious Bovine Pleura-pneumonia (CBPP) and Contagious Caprine Pleura-pneumonia (CCPP) and Black Quarter, which occur with higher frequency during wet season. Thus, as people are busy in their fields, they also must contend with more work related to milking and caring for sick livestock. Livestock sales peak from October through February. In October, better off households are putting together the cash they need for the coming agricultural season; and later in the year, especially in January and February, households need cash both for school fees and for staple food expenditures, which peak during the lean season from January through March. The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35-year period (1980-2014) Source: TZ Meteorology Department The peak agricultural labour periods are from January through March and then June through August. The first period is associated with planting and weeding; the second is when harvesting occurs. Land preparation is not as arduous here as in many areas because ploughing is done with ox ploughs, not hand hoes. Poorer households who do not own oxen themselves obtain access to oxen and ploughs by exchanging their labour for it. This reduces the effort involved in land preparation and ploughing, but some poorer households are still paid to help with land clearing and ploughing. Weeding, however, is done entirely by hand, and this is when poorer Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 6 households are hired in the highest numbers and for the most money. The weeding period lasts 2-3 months, and during this time members of poor and very poor households work on the larger farms of middle and better off households, while, at the same time, tending to their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. They often also miss the best times for ploughing and planting because they must wait for plough oxen to finish cultivating the farms of the oxen’s owners before being deployed to their farms. The weeding period coincides with the lean season, which is when poorer households have run out of their stocks from the previous year’s harvest. Some, in fact, run out as early as October or November, but by January none of the poorer households have any of their own food stocks left at home. They need to purchase all of their staple grains just when the price of staple foods is highest (from December through March). Thus, the paid work offered up by middle and better off households helps provide needed cash to poorer households, allowing them to bridge the gap until April, when the green harvest of maize is available. The rainy season is also when most human illnesses occur. Malaria is brought about by an influx of mosquitoes that come with the wet season. Upper respiratory illnesses also occur at this time. This increases the expenditure requirements for medical treatment at a time of year when other outlays (on staple food and education – in January) are already high. It is also worth keeping in mind that the most important livelihood capital that poorer households have is their own labour; when an active labourer is sick in a poor household, the income for this household rapidly drops. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. Remittances from relatives living outside the zone are most commonly sent in January and February to help cover school fees and also to help cover the costs of staple foods. Petty trade and other off-farm activities peak from June through September. This is also a time of relative plenty, when people are able to take a break before the next agricultural season. Most festivals and weddings occur at this time, making the most of new harvests to supply the grain for brewing activities and the cash to fund large gathering. Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. There are two factors that determine wealth in this livelihood zone: first, the amount of land a household cultivates, and second, the number of livestock it owns. How much land a household cultivates is, in turn, governed by the amount of land it owns and/or is able to rent in; the amount of labour it has available within the household alongside its capacity to hire additional labour; and the number of plough oxen and ploughs it has. A Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 7 relatively large pool of intra-household labour is also essential for managing larger livestock herds, as is having access to sufficient grazing, and the financial resources to buy veterinary medicines and, occasionally, water. Typical better off households own around 8-13 acres of land and cultivate all of it, using hired labour as well as intra-household labour. They have 6-10 oxen and 2 ox ploughs, which they use to prepare their land for planting. They harvest a sizeable surplus of crops which get used for both home consumption and sale. Alongside their crop production, they own 10-20 cattle, 10-20 goats, a few sheep; 2-3 donkeys and 10-20 chickens. Their household sizes are usually a little bigger than poor and very poor households, with around 7-9 members. These households also own other assets, like an ox cart for transporting crops, a bicycle and a motorcycle for transporting people, and several cell phones. Typical very poor households, on the other hand, own only 1-3 acres of land and cultivate only around 1-2 acres. They do not produce enough in any year to cover all of their food and cash needs. They have no oxen or ploughs of their own and, in order to get their fields ploughed, work in the fields of better off households. These households have no cattle, and only a small number of goats, if any (0-5), as well as some chickens (2-10), sheep (0-2) and pigs (0-2). Very poor households tend to be slightly smaller in size, with 6-8 members. They face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone. The distribution of wealth in this zone is weighted slightly towards the top. Very poor (10-15%) and poor (25-40%) households together make up around 40-50% of households in the zone. Middle (35-45%) and better off (10-20%) households combined represent around 55% of the households. In addition, since middle and better off households are slightly larger, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is even larger than this. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2013 to March 2014. April represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12- month period. This was considered an average year, with average rains, crop yields and prices. There are three sources of food in this livelihood zone: own crops, milk In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. and meat from the household’s own livestock, and purchased food. The contribution of own crops increases with wealth; inversely, the reliance on purchased food increases as you become poorer. Maize, sorghum, beans, and sunflower are the main food crops grown; collectively, these accounted for 45-85% of the minimum calorie requirements for households in the reference year. Very poor and poor households covered 45-57% of their food needs with their own crops, which means that even in an average year, very poor households cannot even meet half of their annual food needs from crop production. Middle and better off households, on the Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 8 other hand, derived around 85% of their required calories from their fields. The majority of the own crop contribution is from maize; the importance of green maize is especially notable for poorer households. It is also important to recognize that what households consume is only a portion of the total they grow, since a large proportion of crops are sold in a year like the reference year. In fact, if households did not sell any of the crops they produced, consuming them instead, all except for the very poor would exceed their minimum calorie requirements. The reference year production of maize for typical very poor, poor, middle and better off households was around 700 kg, 1,120 kg, 4,000 kg, and 6,900 kg, respectively. For beans and pigeon peas combined it was 175 kg, 520 kg, 1,500 kg, and 2,500 kg, respectively. Sorghum added 100-200 kilos across the board. Hypothetically, if households kept all of their production for consumption, the total production of maize, sorghum and beans would have covered 75%, 125%, 320% and 535% of minimum calorie requirements for very poor, poor, middle and better off households, respectively. This is not to suggest that households should not have sold their production, but rather to highlight the large difference in the choices that better off households have, compared to very poor households: very poor households have no choice but to purchase food in order to fill a production gap, whereas better off households could have easily covered all of their food needs with their own crop production alone if they decided that was more beneficial to them. The top two wealth groups also consumed milk from their own livestock, and to a much lesser degree meat. Very poor households do not own cattle or substantial numbers of goats, and do not benefit from this source of food. A typical middle household had 1-2 cows milking throughout part of the reference year and better off households had 3-4 cows milking. Milk yields are relatively low here, but the 1 litres per cow per day during the rainy season, and .05 litres a day in the dry season accumulated over the year to total around 270 litres for middle households and 630 litres for better off households. All of this is consumed within the households, contributing 3-7% of annual calorie needs. There was also a small contribution (only around 1-2% of calorie needs) from meat for better off households. The market accounted for all of the remaining food needs for all wealth groups. For very poor and poor households, food purchases met 48-52% of calorie requirements; for middle and better off households, purchased food comprised 23-27% of minimum food needs. As explained above, poorer households produced less of their own food in the reference year and needed to buy food to make up for the gap, as demonstrated by what they purchased: most of what poorer households purchased was in the form of maize grain, the cheapest staple. While very poor households bought 43% of their calories in the form of maize grain and poor households purchased 37% of their calories as maize grain, middle households bought only 10% of their calories in the form of maize grain, and better off households purchased no maize grain at all. The ‘purchase’ component for better off households was comprised of high-value, preferred foods, such as rice, beans, sugar, meat, oil, and dried fish. Thus, these households used the market to diversify their diets and add nutrients and protein they otherwise could not produce themselves. Poorer households, on the other hand, purchased only around 10% of their minimum calories in the form of these more nutritious items. Sources of Cash Income The graphs below present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. They convey a number of points about the local household economy. As a general statement, there are three core sources of cash in this zone: crop sales, livestock sales and seasonal agricultural labour. Better off households also earn cash renting out their oxen, and all wealth groups earn an insignificant amount of money selling eggs. Crop sales provided the most important source of revenue for the upper two wealth groups. Maize, beans, pigeon peas, and sunflower are all sold, along with small amounts of sorghum. The pulses, and especially pigeon peas, are a particularly important cash source. In the reference year, typical middle and better off households sold around 2,800 kg and 5,500 kg of maize; and 1,300 kg and 2,200 kg of pulses, respectively. At 700 TZS/kg, pulses are worth almost 2 ½ times more than maize, so although much larger quantities of maize were sold, pulses brought in almost as much, and sometimes more, cash. Sunflower, the other cash crop, provided around 5-10% of the cash income of local households. Overall, crop sales accounted for 25-40% of the annual cash income of very poor and poor Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 9 households; and 65-70% of the cash income of middle and better off households. In absolute terms, better off households generated around 13 times more from their crop sales than very poor households, which is proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 5.25 times more land than very poor households, but are able to derive substantially more value per acre from their efforts. They invest more in terms of labour and inputs, and are able to better time their ploughing, labour and inputs applications, enabling them to produce more in absolute terms; but their emphasis on growing more of the high value crops also means that what they produce is more valuable in cash terms. Livestock-related income made up the remainder of cash income for the top two wealth groups in the reference year. Sales of live animals (cattle, goats, chickens, and pigs) and eggs covered around 6% of very poor household annual cash income, and 18-23% of poor, middle and better off cash income. Middle and better off households sold, on average, The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 5 855,000 – 1,600,000 1,600,000 – 2,000,000 2,000,000 – 3,200,000 3,200,000 – 6,5000,000 1-2 cattle at 525,000-700,000 TZS per head in the reference year; along with 2-4 goats (at 35,000-40,000 TZS each). Poor households sold around 2 goats, and might also sell a cow once every two years. Better off households were able to get a better price per head than middle and poor households because their animals were in better condition and they chose the best times of year and the best markets in which to sell. For example, a typical better off household sold its goats for 40,000 per head, whereas poor households only brought in 30,000 per head. Very poor households had neither cattle nor goats to sell. All households also sold chickens, averaging around 11-12 hen sales per year at 5,000-5,200 each. In addition, regular egg sales contributed a small amount of cash for all four 5 The average exchange rate from April 2013-March 2014 was 1 USD = 1,600 TZS Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 10 wealth groups. Middle and better off households also took advantage of their oxen ownership to generate cash from renting them out to poorer households for ploughing at the beginning of the agricultural season. While middle and better off households obtained all of their cash income from on-farm sources, poorer households needed to supplement their farm-based income by pursuing activities that took them away from their own fields. Seasonal agricultural labour provides a critical source of cash for both of the bottom two wealth groups. Seasonal agricultural labour provided very poor households with around 70% of their cash income in the reference year, and it provided poor households with around 45% of their cash income. Because this source of cash is so critical to poorer households, it is important to monitor this casual labour market (including changes in demand and the availability of jobs, and changes in the daily wage rate) in order to understand changes in the well-being of these households. Expenditure Patterns The graph presents expenditure patterns for the reference year April 2013 to March 2014. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in all parts of rural Tanzania, households here need to spend cash on a number of essential goods and services, including: staple and non-staple food, household items, productive inputs, social services, like schooling and health, as well as clothing and other miscellaneous The graph provides a breakdown of total annual cash expenditure according to category of expenditure items. The graph illustrates a general trend in rural Tanzania: poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. These trends, as well as number of other points, are discussed in more detail below. Even in an average year, like the reference year, all wealth groups buy staple foods, however the composition of the staple food basket is not the same for all wealth groups. In this zone, the items included in staple food expenditure were maize grain and rice. Very poor and poor households devoted almost all of their expenditure on staple foods to maize grain, the cheapest staple, spending only a small amount on rice. For example, a typical very poor household spent around 277,200 TZS on maize grain in the reference year, and 44,800 TZS on rice, which was four times more expensive. The three bottom wealth groups bought around 400-440 kg of maize grain in the reference year, but no more than 55 kg of rice. Better off households, on the other hand, bought no maize grain at all and devoted their entire staple food expenditure to rice, with a typical better off household spending around 230,400 TZS for around 145 kg of rice. Without the purchase of staple foods, the two bottom wealth groups would have been facing a food deficit, but the same cannot be said for the two upper wealth groups. In the reference year, the proportion of cash income spent on staple foods for very poor, poor, middle and better off households was around 27%, 17%, 5%, and 5%, respectively. While, in both absolute and relative terms, poorer households spent more on staple foods than any other wealth group, better off households spent the most in absolute terms on non-staple foods, expending three time more than very poor households. The non-staple food category included beans, sugar, meat, oil, fried fish, vegetables and fruit. The lower two wealth groups did not buy fruits, but their spending on all the other non-staple foods was Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 11 relatively even. Middle and better off households spent substantially more on meat, along with sugar and oil. These three food items together comprised 70-75% of their non-staple expenditure. In the reference year, the proportion of cash income spent on non-staple foods for very poor, poor, middle and better off households was around 21%, 19%, 17%, and 16%, respectively. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 7%, 9%, 10% and 18%, respectively. Thus, better off households are able to buy a much more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less. Moving up the graph, the ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor and poor households spent the most money on payment for grinding, and soap, which took around 60-70% of their inputs budget in the reference year. Middle and better off households spent the most on soap followed by grinding and utensils. On an annual basis, spending on basic household goods comprised 6-12% of total expenditure, decreasing as a proportion of annual expenditure as wealth increases (although increasing in absolute terms). The graph makes it clear that middle and better off households spend heavily on productive inputs, as represented by the dark blue bar. Included in this category are the following: livestock drugs, water for animals, seeds and tools, pesticides, labour hire, livestock purchase, and phone credit. Very poor households spent most of their money on seeds/tools (75% of their inputs budget), and phone credit (25% of their inputs budget). Poor households also spent some cash on livestock drugs and livestock purchase. Middle and better off households spent money on all items within the category; the majority of their inputs budget was spent on labour hire (45-55% of their inputs budget), livestock purchases (13-16% of their inputs budget) and seeds and tools (12-17% of their inputs budget). In absolute terms, the amount spent by better off households on inputs was more than 35 times the amount spent by very poor households, around 10 times the amount spent by poor households, and double the amount spent by middle households. Better off households had to invest large amounts of cash into hiring labour (which took over half of their inputs budget in the reference year). A typical better off household spent around 1,200,000 TZS on hiring labour in the reference year. Very poor and poor households could not survive without this income; and better off households could not generate their surplus production without this labour. Next on the graph, ‘social services’ includes schooling and health costs. Households spent 5-10% of their annual cash on these costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, middle and better off households spent around the same amount on education, and these two wealth groups spent around 2 times more than very poor households, although not much more than poor households. Very poor households usually are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent three times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Better off households spent around 15-25% more than middle and poor households on health. Spending on clothes and other miscellaneous items are the last two categories included here. Clothes accounted for 5-8% of the annual budget for all households. The ‘other’ category includes things like beer, tobacco, cigarettes, transportation and festivals, and in the reference year households devoted 15-20% of their cash to these items. This budget can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 5 times more in this category than very poor households); and because the reference year was an average year, even the very poor wealth group had more in this budget than it would in a bad year. Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 12 Hazards There are a number of hazards that affect this zone on a regular basis. The first is intermittent or poorly distributed rains. If crops do not receive the moisture they need at the right time of year, this reduces crop yields, which has knock on effects throughout the local economy. The second is crop pests and diseases. Elegant grasshoppers, which affect both maize and sorghum; leaf hoppers and stem rot, which affect beans; and quelea quelea birds, which affect sorghum, cause problems throughout the zone almost every year. The third is livestock disease, such as Foot and Mouth Disease (FMD), as well as contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) for cattle and goats, respectively. New Castle Disease can wipe out an entire flock of chickens. Livestock diseases can cause significant herd losses, translating into large declines in income. Human diseases are also endemic, especially malaria and upper respiratory diseases. Because household labour is so critical to income generation, especially for poorer households, losing this labour at a critical time of year can translate into significant drops in income. The main periodic hazard is flooding, which can cause damage to crops in lowland areas every other year, or three years out of six. Floods also create transportation difficulties, and market access problems. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Middle and better off households try to increase their livestock sales. Poorer households are not as able to turn to this option because they can afford to sell only a few animals and still maintain viable herds. Also, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people may go to Singida town, sugar plantations in Moshi, and flower plantations in Arusha. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Manyara-Singida Maize, Sorghum, Beans & Sunflower Livelihood Zone Profile 13 Crops Green maize – amount produced Maize – amount produced Sorghum – amount produced Beans – amount produced Pigeon peas – amount produced Sunflower – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Sunflower – producer price Livestock production Cattle – herd size Goats – herd size Chickens – flock size Cattle – producer price Goats – producer price Chickens – producer price Other food and cash income Agricultural labour (land preparation, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Firewood/charcoal – bundles collected Agricultural wage rates (land preparation, weeding) Agricultural labour rates (harvesting) Firewood/charcoal – price per bundle Expenditure Maize grain – consumer price Oil - consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than pasture improvement, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Improved maintenance of existing road networks and increased construction of new roads Provision of electricity at village level Access to affordable and safe sources of water for humans and animals Timely and affordable provision of crop and livestock inputs or subsidies, especially seeds Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines Improved security at village level Improved markets for crops and livestock, including market infrastructure, market information, and standardisation of weights and measures Improved livestock health infrastructure, including dip tanks Construction of dams for irrigation and flood dikes and terraces to protect fields Construction of warehouses for storage Provision of land right titles Access to credit facilities and affordable loans Improvement of educational services, including construction of teachers’ houses, primary schools, and curriculum development Resolution of land conflicts with national reserves Development of phone networks Sunflower oil extraction facilities Provision of agricultural and livestock extension work Access to affordable construction materials, especially iron sheets Improvement of pasture lands | false |
# Extracted Content Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Chalinze-Ngerengere Maize, Sesame & Cattle1 Livelihood Zone (TLZ 41) February, 20162 Zone Description The Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone is a warm lowland to midland zone found in parts of Pwani and Morogoro regions. In Morogoro District, the wards included in this zone are Bwakila, Chini, Ngerengere and Kidugalo; in Kibaha District, the wards included are Gwata and Magindu; and in Bagamoyo District, the wards included are Lugoba, Msoga, Talawanda, Pera and Bwilingu.3 The main ethnic groups living here are the Kwere in Bagamoyo, Chalinze and Kibaha; and the Luguru and Kutu in Morogoro District. The Uluguru Mountains border the zone to the southwest, and major rivers, like the Ruvu, Ngerengere, Mvuha and Bwakila provide a source of water for local residents. The main towns found here include Chalinze, Ngerengere, Lugoba and Mvuha, and the zone is well connected to Dar es Salaam via a major tarmac road between Morogoro and the coastal capital as well as the central railway. This is a low- to mid-altitude area, ranging from 100 to 480 metres above sea level, with undulating plains and forested areas interspersed with agricultural land. The forests are an important source of charcoal, firewood and timber. The Selous Game Reserve also borders this zone, stretching southwards to cover an expanse larger than the country of Switzerland. The population density is approximately 23 people per km2. This zone has two rainy seasons – the masika rains, from March to June, and the short vuli rains, from November to December. The long masika rains are the most reliable and the most important for crop production. Total precipitation ranges from 800 to 1,000 mm, and the temperatures are hot and humid, typically hovering around 300 C from October to March, the summer months. Winter is cooler, with temperatures dropping to around 250 C between May and August. The soils are sandy loams, moderately fertile and suitable for cultivation. 1 The previous name of this zone was Chalinze-Tununguo Maize, Cassava & Cattle, but after the current field work, team members proposed a new name that reflects livelihood patterns in the zone. It should be noted that within the same geographical area there are households practicing pastoralism, agro-pastoralism and cropping. This profile covers the livelihood patterns of the agro-pastoralists and cropping households. 2 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in May 2014 and ended in April 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 3 The southern part of the zone shown on the map should be separated from the current zone because it has a different economic base, dependent on irrigated crops along the rivers, including paddy, water melons, tomatoes and bananas. The three wards that should be separated from this zone are Tununguo, Mvuha and Bwakila in Morogoro District. The information contained in this profile does not apply to these wards. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 2 This zone is considered self-sufficient in the sense that rarely do people need external assistance. This does not mean that households grow all of their own food; they do not, relying heavily on the market to meet food needs every year, especially on the poorer end of the wealth spectrum. The foundation of the household economy in this livelihood zone is two-fold: people grow crops for consumption and sale; but just as importantly they raise livestock. Livestock are more important in cash terms than crops, and milk is consumed by those in the top two wealth groups. Maize, sorghum and cassava - all of which are rain-fed - are the main food crops grown, along with some pulses; households sell part of these food crops for cash. Sesame is grown as a cash crop, sold to markets as far away as India. Cassava used to be more important in this zone, but in recent years a number of factors have led to its diminished role; wild pigs, for one, root up cassava, creating a year-round requirement to scare them off. Also, cattle numbers have increased, which has elevated the labour requirements around livestock and reduced the time available for households to manage cassava throughout the year. An additional factor is the growth in importance of sesame; households prefer to focus on this high-value crop over cassava. Hand hoes are the dominant form of cultivation; ox ploughs are not used, although a few better off households hire tractors. Land clearing/preparation and weeding are the most labour-intensive activities and for these tasks middle and better off households hire members from poor and very poor households to help them. It is mostly the men from poorer households who work as seasonal labourers, helping provide their families with an important source of cash. Livestock are the second important pillar of the economy. Cattle, goats, sheep and chickens are raised, relying on free grazing/browsing and some crop residues. During the wet season, livestock find water in rivers and seasonal streams. In the dry season they turn also to shallow wells and dams, and cattle are moved to rivers within the zone towards the end of the dry season. Cattle are the most important livestock from an economic viewpoint; they provide significant amounts of milk for consumption and sale and those who have them are able to sell young steers or other unproductive animals to generate cash when needed. Goats and sheep are used for meat, slaughtered especially during the festival season, and also sold when needed. Very poor households own only chickens, also sold throughout the year when cash is required. Men are responsible for taking care of the cattle, goats and sheep; women and children manage the chicken flocks. To earn additional cash, poorer households depend heavily on seasonal agricultural labour - all of it local - and on selling charcoal. Charcoal is produced by cutting down and burning trees from local forests. The charcoal then gets bundled and sold to local urban areas. This practice, carried out especially during the hunger season (February to April) and in the dry season (July to October) is having a devastating effect on the local environment. Middle and better off households earn extra cash from petty trade and running small kiosks. Services in this zone are on a par with much of rural Tanzania. Drinking water is obtained from government- run taps, which require payment of around 50-100 Tsh per household per day. Water for washing comes from rivers and wells (both shallow and deep). Sanitation facilities consist of pit latrines, most of which are constructed with brick and mud and covered with aluminium sheets. Better off households may have improved concrete floors instead of mud floors. Most villages have a health dispensary, although these may not be well-stocked. Better off households typically travel to health facilities in the ward centre, or hospitals in regional centres when necessary. Primary schools also available in villages, with secondary schools found at the ward level. Most poorer households send their children through primary school but not to secondary school. Middle and better off households, on the other hand, can afford to send their children to secondary school and vocational college. There is no electricity in this zone so households depend on battery-operated torches and kerosene lanterns for light; most better off households use solar lanterns. In general, all households have at least one mobile phone and better off households have multiple phones. People do not have access to credit here; VICOBA offers an opportunity to save money, but this is done only by better off households. A few NGOs operate here, including the Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services; CAMFED, which supports girls’ education; MUVI, which helps support sesame production. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 3 Markets The transportation infrastructure in this zone is relatively good. There is a tarmac road from Dar es Salaam to Morogoro and Tanga which passes along the zone; and feeder roads extend throughout the zone, from Chalinze to Ngerengere, Chalinze to Magindu, and Chalinze to Talawanda. For the most part roads are accessible throughout the year and bridges are all in good condition, although some of the more remote areas can be difficult to traverse in the peak of the rainy season. The zone is close to urban centres, which provide a steady demand for local commodities. Morogoro is the main intermediary market, providing ready access to Dar es Salaam, the main terminal market for most goods. Maize, sorghum and cassava are the main food crops sold by households in this livelihood zone. Sesame, however, is the most important cash crop. Food crops are sold from August through October. Traders come to the farm gate, traveling from village to village to buy up local commodities. They transport crops to Morogoro, where they are sold at retail; or on to Dar es Salaam. Sesame is also purchased by traders directly from local households in June and July; the terminal market for sesame is India. It transported by traders to Morogoro and then on to Dar es Salaam, from where it is shipped on freighters headed east. Livestock and milk are a more important commodity (in terms of cash earned per household) than crops. Cattle – the biggest earner – and goats and sheep are sold at local markets called mnada or gulio twice a month. The urban population in Dar es Salaam ensures a relatively constant demand for livestock; traders purchase the animals locally and then truck them on to the city. Chickens are also sold at local markets throughout the year, but consumed within the region. Households in all wealth groups also buy some maize grain during the year, especially from October through April, when local stocks are low and the new harvest has not yet come in. Maize is the cheapest local staple, and most of this is sourced from Ruvuma and distributed via local markets. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks owned by better off households. The labour market is entirely local seasonal agricultural work. It was estimated that in the reference year, 100% of seasonal labour was found within the zone on local farms, with middle and better off households hiring poorer household members to work on their land. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Chalinze- Ngerengere Maize, Cattle & Cassava Livelihood Zone the reference year covered the consumption period from May 2014 to April 2015. During community leader interviews, informants were asked to rank the last four years (eight seasons) in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli rains in October/November and ends with the May through July harvest of the following calendar year. Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was relatively good, with good rainfall, good harvests and average food prices. In the past nine seasons, including the recent vuli season, five were below average, three were average and one was slightly above average. Production Year Season Rank Critical Events 2015-2016 Vuli 3 Fairly good vuli rains; farmers have planted 2014-2015 Masika (2015) 1.5 Inadequate rainfall, high food prices; normal livestock migration; increased livestock sales and charcoal sales Vuli 1 No vuli rains Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 4 2013-2014 Masika (2014) 3.5 Good rainfall, good harvest and average food prices Vuli 1 No vuli rains 2012-2013 Masika (2013) 3 Average rainfall; average crop production average prices Vuli 2 Below average rains 2011-2012 Masika (2012) 3 Mixed picture by village – some average and some inadequate rainfall, poor harvest with high food prices; normal livestock migration; people increased livestock sales and charcoal sales Vuli 1.5 Poor rains 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Rainy season r r r r r r r r r r r r Crops Maize gh gh gh gh h h h h lp lp p p w w gh gh h h lp lp p p w w Sorghum h h h h lp lp lp lp p p w w Sesame h h h h lp lp lp lp p p w w Cassava h h h h h h h lp p p w w w w Livestock Cattle milk peak m m m m m m m Cattle sales peak salesalesalesalesalesale Goat sales peak salesale salesalesalesalesalesale salesalesalesale Livestock diseases 5 5 5 5 5 5 5 5 Other Agricultural labor peak 4 4 4 4 4 4 4 4 Charcoal sales 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Stress & High Expenditure Periods High staple prices sp sp sp sp sp sp sp sp sp sp Human diseases 7 7 7 7 7 7 Festival season 2 2 2 2 2 2 2 2 Lean season ls ls ls ls ls ls Legend Land prep Sowing Weeding Green Cons. Harvest/Thresh. Jan Feb Mar Apr May Jun Nov Jul Aug Sep Oct Dec Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Kibaha for a 50-year period from 1964 to 2013. Source: TZ Meteorology Department This livelihood zone benefits from two rainy seasons. The first, called the vuli, is short, starting in October and lasting until the end of December; the second, called the masika, occurs from March through May. Masika rains are when the main planting takes place here because vuli rains do not provide enough precipitation and they are not as reliable. Nevertheless, as shown on the calendar above, most households attempt to plant a vuli crop of maize, taking what comes from it if it succeeds. Most maize, however, is planted in March, when the masika rains are fully established. Sorghum, sesame and cassava are also planted at this time, following a month of land preparation in February. January through April is when seasonal agricultural labour is most intense. Within that period, April is an especially challenging month, with weeding the main focus of agricultural activities. Poorer households need to buy food at this time of year as they tend to have none of their own food stocks left from February through April. This is the worst month of the lean period, when prices are high and food stocks are low; human and livestock diseases (especially malaria for people and East Coast Fever and Blackquarter – both highest in the rainy season) are starting to peak at this time too, imposing additional expenditure requirements on already- stretched households. Poorer households, in need of extra cash to buy food, medicines and possibly livestock drugs, find work on the farms of middle and better off households, paid to weed their larger fields. They also burn and sell charcoal or collect and sell firewood at this time to shore up their cash income. Middle and better off households, who own cattle, see their milk production peak from April through June, as the condition of cows improves with replenished pastures from the recent rains, and with plentiful supplies of water. Milk helps boost the nutritional content of the diet for these households, and especially for children, while at the same time improving the income flows, since households sell at least half of their milk. Cattle and goat sales peak from August through October. Body condition is highest at this time, which brings in the best prices. There is also higher demand locally since people have extra money from crop sales, and the dry season facilitates the movement of trucks which are deployed to transport livestock to Dar es Salaam. Goats are also sold in higher quantities in the lean season – but mainly by poorer households. May marks the beginning of the consumption year as households begin to eat maize from the masika harvest. At first, maize is eaten green – especially by poorer households, who cannot afford to wait the additional month or two for the dried harvest. In July and August the main maize harvest is taken in from the fields and August and September are when sales of maize are highest. Cassava and sesame can be harvested starting in June. Sales of sesame – the main cash crop - are highest in July. People sell cassava for months afterwards, with peak sales occurring from October through December. The festival season occurs from September through December, when harvests are in, cash flow is a bit higher and people have a chance to rest before delving into the next production year. Meat consumption is highest during these months as goats are slaughtered; and expenditures on weddings or other celebrations is highest at this time as well. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. Both crop and livestock production are central in this zone, and so it follows that the area of land cultivated by a household along with the number of livestock it owns are the two key determinants of wealth. Households with smaller areas of land and fewer livestock are generally poorer, whereas those with larger plots also have more livestock and are considered better off. In addition, ownership of productive assets, like motorcycles (which enable households to make money from trading activities), contributes to the basis on which differences of wealth are determined. Very poor households plant on 1.5-2.5 acres and have no livestock other than chickens. Poor households cultivate 2.5-3.5 acres and own 0-10 goats and 0-5 sheep along with a few chickens. A jump occurs between poor and middle households, with middle households typically cultivating 4-5 acres and owning 30-50 cattle, 20-40 goats, possibly some sheep and 10-20 chickens. The difference between these two wealth groups is seen more in the livestock than in the land. Middle households cultivate just an acre or two more than poor households, but they own twenty to thirty times more cattle. Better off households cultivate 4-8 acres (not much different from middle households) and own 40-80 cattle, 30-70 goats and 20-50 sheep. Cattle are critical because they bring in significant amounts of cash income from live animal and milk sales; and they provide extra nutrition and calories in the form of milk. The other critical divide between poor and middle households is that poor and very poor households need to work for others to earn enough cash to live on and middle households do not. Thus, middle and better off households hire labour to work for them; very poor and poor households are the labour that gets hired. Middle and better off households are engaged in trade activities, providing them with another source of cash. This trade is enabled by their ownership of motorcycles. Almost all better off households own at least one motorcycle and some middle households do as well. Bicycles are another common means of transport, and all wealth groups except for the very poor own at least one bicycle. Almost all households also own at least one cell phone. Over the last decade, cell phone ownership has become ubiquitous throughout rural Africa. There are more households falling into the very poor and poor categories than into the middle and better off categories. Very poor (30%) and poor (33%) households together comprise just under two-thirds of the households in the zone. Middle (25%) and better off (13%) households combined represent just over a third of the population. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period May 2014 to April 2015. May represents the start of the consumption year because it is when people begin to consume green crops and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. Households in this livelihood zone depended on three main sources of food in the reference In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. year: their own crop production; their own milk and meat production; and the market. A range of crops are grown here, including maize, sorghum, cassava, pulses (like pigeon peas and cowpeas) and sesame. Only the top two wealth groups are able to produce enough from their own fields to come close to meeting all of their own food needs, even in a good year like the reference year. Better off households harvested around 1,200 kg of maize, 250 kg of sorghum and 320 kg of cassava in the reference year along with small amounts of pulses for consumption. Very poor households, on the other end of the wealth spectrum, produced only around 390 kg of maize, 390 kg of sorghum, and 100 kg of cassava along with small amounts of pulses. If these poorer households had consumed all the maize, sorghum and cassava they produced, they could have covered around 65-70% of their minimum calorie needs, leaving a fairly sizeable gap. Better off households could have covered closer to 125% of their minimum calorie needs. However, all households here sell some of their crops for cash, which means that even better off households are left with a staple grain gap that needs to be filled with purchased food. When combined, the contribution of own crops (after sales and seed) accounted for around 40-68% of households’ annual food needs in the reference year, increasing with wealth. The upper two wealth groups fill in a good portion of the remaining gap with milk and meat. Middle households typically had around 12 cows milking during much of the reference year, and better off households had, on average, 15 cows milking. Very poor and poor households did not own any cattle and were not able to benefit from this source of food. Yields are relatively low, at 1.5 litres a day in the first rainy season (lasting around four months) and 0.75 litres a day in the second rainy season (lasting around two months). When added together, the milk from both seasons amounted to around 2,700 litres for middle households, and 3,375 litres for better off households during the reference year. Around 50-70% of this was sold, providing some cash income (shown in the section below) for these two wealth groups. The remainder was consumed, providing 8-18% of the minimum calories for these households. Meat from cattle and goats consumed throughout the year contributed an additional 4% of minimum food needs for the upper two wealth groups. Goats are the main livestock slaughtered, usually in April, June, July and December during festivals; but cattle that die from natural causes are also eaten. Given the remaining gap, all households needed to purchase staple grain to cover a production gap – even better off households. In the reference year, an average year, very poor households bought almost 600 kg of maize grain, the cheapest staple, which is equivalent to 45-50% of their minimum calories; poor, middle and better off households bought around 40%, 12%, 6% of their calories in the form of maize grain, respectively. All households also bought some rice, with middle and better off households buying more of this expensive grain Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 8 than poorer households. Beans, sugar, meat, oil, Irish potatoes, and dried fish also contributed to the purchased food basket. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 30-60% of their minimum calorie requirements in the reference year. Sources of Cash Income The graph to the right highlights six main sources of cash income in this livelihood zone: own crop sales, milk/egg sales, livestock sales, agricultural labour, petty trade and firewood/charcoal sales. The majority of cash income for middle and better off households is generated on the farm (from crop and livestock-related sales.) The bottom two groups rely heavily on agricultural labour and firewood and charcoal sales to supplement their crop and livestock-related cash income. Their on-farm production meets less than half of their annual cash needs. The importance of livestock sales and milk sales is striking The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,140,000 – 1,640,000 1,640,000 – 2,10,000 3,000,000 – 5,000,000 5,000,000 – 6,000,000 for the upper two wealth groups. Combined, these two sources of income account for around 55-65% of annual cash for middle and better off households; for very poor and poor households, on the other hand, they only make up 3-12% of annual cash income. The difference is due almost entirely to cattle, owned by the upper two groups but not by the lower two. Cattle are worth 300,000 – 350,000 Tsh per head. Typical middle and better off households each sold 4-5 head of cattle in the reference year, bringing in 1,200,000-1,750,000 Tsh. This stream of income alone is more than the total annual income of some poor households. In addition, these households also sold goats, sheep and chickens. Their total income from livestock sales ranged from 1,565,000 Tsh to 2,207,000 Tsh. Poor households sold only goats, sheep and chickens in the reference year, averaging around 200,000 Tsh from livestock sales; very poor households had only chickens to sell, which brought them around 40,000 Tsh. Cattle also afforded middle and better off households with cash income from milk sales, adding another 825,000 – 950,000 Tsh. Comparing livestock-based cash income (including both the sale of live animals and milk) across wealth groups we see that better off households had a total that 75 times higher than very poor households’ and 15 times higher than poor households’. Without cattle this difference would have been only 11 times higher (better off vs very poor) and 2 times higher (better off vs poor) respectively. Crop sales generated 15-30% of cash income for households in this zone in the reference year. It is worth remembering that the reference year was a good year, so the contribution from crop sales is as high as it would ever be. In a bad year the share will decrease. This suggests that crops are more important as a source of food than cash here. Maize, sorghum, cassava and sesame were the main crops sold; sesame generated 34-56% of crop-based cash income, with middle households making the most of this crop. Sorghum sales were most 4 The average exchange rate from May 2014-April 2015 was 1 USD = 1,810 TZS Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 9 important for very poor households who generated around half of their crop-based cash income from this crop alone. Better off households generated around 2 ½ times as much cash from crop sales as very poor households. Although crops contribute to the local economy, they are not as important as livestock. Poorer households depend on two main sources of cash other than crop and livestock sales: agricultural labour and charcoal/firewood sales. Middle and better off households hire men and women from poorer households to help with land preparation and weeding activities. January and February are especially busy months for agricultural labour, when land preparation occurs, as well as April, when weeding takes place. The wage rate for land preparation is higher than for weeding, but weeding generates more revenue for very poor households, who may send additional people to work during this time and/or spend more days working. Agricultural labour accounts for around a third of annual cash income for the bottom two wealth groups. Selling charcoal and/or firewood brought in even more money for very poor households in the reference year, making up around 45% of their cash income. Middle households may also be engaged in charcoal sales. Men are responsible for charcoal production and sales; women gather and sell firewood. Local towns are the main source of demand. Wood for both is found in the forests within the zone and environmental degradation is clearly a serious problem given the high reliance on this income source. Petty trade is very important for better off households, and also for middle households. This trade is done mainly by middle and better off households who have motorcycles and extra money and can buy up local produce, selling in more profitable markets to make a small margin. Better off or middle households may also have small kiosks where they sell salt, soap, kerosene or other household goods. Better off households relied on petty trade to make up around a third of their cash income in the reference year. Those at the upper end of the wealth spectrum generated, on average, three and a half times more than those at the bottom. Owning cattle is the critical differentiator in this zone, affording the two upper wealth groups with cash income from the sales of cattle as well as milk. Having the means to trade provides a further advantage, with petty trade bringing in – for better off households – almost as much on its own as very poor households made from all of their sources combined. Expenditure Patterns The graph presents expenditure patterns for the reference year May 2014 to April 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. There are a range of essential goods and services that households here need to spend money on, including: staple and non-staple food, household items, productive inputs, social services, clothing and other The graph provides a breakdown of total annual cash expenditure according to category of expenditure miscellaneous items. There are four main points to make about the information displayed in the graph. First, both absolute and relative expenditure on staple foods decreases as we move up the wealth spectrum, but the opposite is true for non-staple foods. Very poor households spent, on average, around 390,000 Tsh on Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 10 staple foods5 in the reference year; better off households spent around 220,000 Tsh. But if we look just at spending on maize grain it becomes clear that poorer households spent far more on ensuring they had sufficient calories and better off households spent more on diversifying their diet: very poor households spent around 360,000 Tsh (of the 390,000 Tsh) on just maize grain, whereas better off households spent 62,400 Tsh (of the 220,000 Tsh) on maize grain. The rest of the staple expenditure was on beans, oil and dried fish. All households also spent money on other foods, such as rice, sugar, meat, and potatoes. These are all included in the non- staple food basket. Better off households spent almost twice as much on non-staple foods as very poor households, again using the market to help diversify their diets. Second, expenditure on basic household goods (‘hh items’), including all of the items bought by households over the year – often in small incremental amounts - to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils, ate up a large amount of the cash earned by the two poorer groups. Within this category, the highest expenditure was on grinding; very poor households devoted 45-50% of their ‘hh items’ budget to grinding in the reference year; no wealth group devoted less than 30% of their ‘hh items’ budget on grinding. Soap took up the next largest chunk. On an annual basis, spending on basic household goods comprised 7-16% of total expenditure, generally decreasing in proportional terms (although increasing in absolute terms) with increasing wealth. Finding ways to reduce the relatively high costs of grinding for poorer households could help them free us some money for other productive uses. Third, productive inputs accounts for a much larger portion of the budget for middle and better off households than for the poorer two wealth groups. ‘Inputs’ on the expenditure graph above includes the following: livestock drugs, house repair, seeds and tools, labour, livestock purchase and phone credit. Very poor households spent all of their inputs budget on phone credit. Poor households, in addition to phone credit, spent a small amount on seeds and tools. Middle and better off households spent the majority of their inputs budget (58-68%) on two items: labour and livestock purchase. Livestock drugs took up almost all of the rest of their budget. On the whole, middle and better off households devoted 30 - 40% of their annual cash income to productive inputs whereas very poor and poor households devoted only 5-6% of their annual budget to productive inputs in the reference year. In absolute terms, better off households spent almost 20 times more than very poor households on productive inputs. Fourth, this is one of the livelihood zones where households need to spend a noticeable proportion of their budget on water. An average household buys 80-100 buckets of water from village taps every month throughout the year, spending 100-250 Tsh per bucket. In annual terms this adds up to around 5-6% of total expenditure. Water can also be obtained from local rivers and streams, but this is not safe for drinking and is used only for washing. ‘Social services’ includes the money spent on education and medical services. Education covers school fees, uniforms, stationery and transportation. Absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Very poor households spent around 76,000 Tsh on schooling compared to 240,000 Tsh spent by better off households. As you move up, households are spending more on stationery, books, uniforms, school fees and transportation. Very poor households are unlikely to be able to afford to send their children beyond primary school, whereas those at the upper ends of the wealth scale are likely to send them through at least secondary school, and sometimes on to vocational school. Better off and middle households also spend more on medicine and health care, with each wealth group spending on average 20-50% more than the one below it. Spending on clothes and other miscellaneous items are the last two categories included here. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. There is also some savings included here for the better off wealth group. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those at the upper end of the wealth spectrum have the most available in this discretionary budget. 5 The team included maize grain, beans, oil and dried fish in the staple food basket. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 11 Hazards There are a number of hazards that affect this zone on a regular basis. The first is inadequate and erratic rainfall and occasional drought. All households rely heavily on crop production from one season to at least partially meet their food and cash needs. If rains in this season are poor, if they are interrupted at the growing stage, or if they end early, households are at risk of losing their crops, all of which are rain-fed. Thus the food and cash income of households here is substantially reduced when rains are poor. Pastures and water supplies are also affected when droughts occur, reducing milk yields and leading to a deterioration in livestock body condition and value. Second, conflict between farmers and pastoralists is high in this zone. Competition over scarce pasture and cropping lands as well as prime water sources has resulted in contested access to resources crucial for both farmers and livestock keepers. Third, livestock diseases, such as Food and Mouth disease (FMD) and East Coast fever – both of which affect cattle - and New Castle Disease, which can wipe out an entire flock of chickens, are serious problems. Fourth, crop pests and diseases are a constant threat. Elegant grasshoppers and army worms are especially problematic as well as quelea quelea, which threaten the sorghum harvest. Wild animals also cause damage to crops. Finally, poor markets for cash crops are a consistent constraint on the income of households here. With better market infrastructure and ensured access to markets that offer good producer prices, households here would have higher and more assured incomes. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to increase the sale of charcoal, intensifying the burning and selling of wood products. The expandability of this option is limited in bad years because as more people turn to this option, supplies of charcoal on the market increase, thereby reducing the price of each bag. There are also serious environmental downsides to this strategy. More must be done to provide poor households with an alternative to charcoal as an income source, both in normal and bad years. Poorer households also try to increase their production and sale of handicrafts. Again, this is an option with limited expansion since the market for handicrafts is limited, and the more households pursuing this option, the lower the returns on each sale. Poorer households also sell more chickens. However, as the number of chickens owned by very poor and poor households does not exceed 10-15, and each chicken is worth only around 8,000 Tsh in a good year, this option will only go so far in terms of raising cash income. Middle and better off households try to increase their livestock sales. The value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. However, middle and better off households have relatively large herds of cattle here, so this option could provide people with a substantial amount of additional cash. Middle and better off households try to increase their reliance on petty trade and small businesses, buying and selling goods to make as much cash as they can with which to buy food. Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone Profile 12 Middle and better off households also use some of their savings in bad years, buying food and other necessities with money saved from the previous good year. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Chalinze-Ngerengere Maize, Cattle & Cassava Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – masika - amount produced Sorghum – masika – amount produced Cassava – amount produced Sesame – amount produced Maize – masika – producer price Sorghum - masika – producer price Cassava – producer price Sesame – producer price Livestock production Cow milk – yields Cattle – herd size Goats – herd size Sheep – herd size Chickens - numbers Cow milk – price Cattle – producer price Goats – producer price Sheep – producer price Chickens – producer price Other food and cash income Agricultural labour (land clearing and preparation, weeding) – number of jobs Petty trade – amount of trade Firewood/Charcoal – bundles/bags sold Agricultural wage rates (land clearing and preparation, weeding) Petty trade – margins on trade Firewood/Charcoal – prices Expenditure Maize grain – consumer price Oil – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve health services and increase the availability of medicines 2) Provide agricultural extension services 3) Provide affordable loans for agriculture 4) Improve road infrastructure and invest in maintenance of existing roads 5) Resolve conflict between farmers and pastoralists 6) Develop market infrastructure 7) Improve access to and availability of safe and reliable water supplies for humans 8) Provide subsidized and improved agricultural inputs, for example, access to a village tractor for rental 9) Provide access to mechanized agriculture 10) Improve education services, deploying sufficient numbers of primary and secondary school teachers and adequate school facilities | false |
# Extracted Content Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone (TLZ 42) February, 20161 Zone Description The Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone is a unique zone found in Morogoro Region, and geographically separated into two parts – one at the north eastern boundary of the Kilosa-Mvomero Maize and Paddy Lowlands Livelihood Zone (TLZ 44) and one on the southern boundary of the same zone. Most of the zone is found in three districts: Kilombero (Sanje and Mkula wards); Kilosa (Kidodi and Ruhembe wards); and Mvomero (Sungaji, Kanga, Mtibwa and Djongoya wards). The main ethnic groups living here are the Pogoro, Wavidunda, Nguu and Zigua. The Nguu, Udzungwa, and Kanga mountains are found here, and major rivers, like the Ruaha and Mjonga flow through the zone, providing a source of water for local residents. This warm zone is situated at around 270-500 meters above sea level, and has a mix of flat plains, river valleys and mountainous areas, covered with forests and agricultural land. The Ruaha River provides some with access to fishing, but this is not a typical source of food or cash for most households. The Mikumi and Udzungwa national parks are found nearby. This zone is unique due to the existence of sugarcane estates and factories, which are surrounded by outgrower farmers who supply sugarcane via producer associations to the factories. The profile describes the livelihoods of these outgrowers, who work, essentially, as contract farmers for the sugarcane factories. Many households own or rent farm plots far from their homes, where they grow paddy and maize. Plots near the homestead have been converted into sugarcane fields, which makes land for farming crops scarce. With the expansion of sugarcane, food crops have been exposed to fires and pests that are associated with sugarcane fields, which makes it difficult to grow food crops near the sugarcane fields. This means many households are juggling various demands from different agricultural plots as well as the care of home and children.2 Poorer households concentrate more on food crop production, unable to manage the heavy demands of both sugar cane and food crops. Better off households use the proceeds from sugarcane to help support their food crop production, essentially reducing the risks of failure from either their food or cash 1 Fieldwork for the current profile was undertaken in November and December of 2015. The information presented in this profile refers to the reference year, which was the consumption year that started in May 2014 and ended in April 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2http://www.plaas.org.za/blog/tanzanias-commuter-farmers-facing-livelihoods-challenges#sthash.X4ckdtvf.dpuf Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 2 sources. Cash incomes are, relatively speaking, higher than in neighbouring zones, and there is a noticeably higher investment in schooling as a result. There are two rainy seasons – the masika rains, from March to June, and the short vuli rains, from November to December. Maize is grown in two seasons, but the other crops are long cycle varieties, depending on the rains from both seasons to reach maturity. Total precipitation ranges from 600 to 1,200 mm, and the temperatures can be as low as 18 oC in the winter and as high as 30 oC in the summer. The soils are fertile clay loams with a high potential for good crop production. Maize and paddy are the main food crops, but portions of both are also sold for cash by all households. Maize is rain fed; paddy is both rain fed and irrigated. Pigeon peas and sesame are also grown, primarily as cash crops, but partially consumed as well. Hand hoes are the dominant form of cultivation for poorer households, whereas better off households use tractors. Sugar cane and paddy are both very labour- intensive crops, especially at planting, weeding and harvesting times. During these periods, middle and better off households hire members from poor and very poor households to help them. Other than chickens, which are widely kept, livestock are not a source of either food or cash income in this livelihood zone, unlike many zones in rural Tanzania. There is not enough land to raise livestock, and it is not a part of the traditional livelihood patterns of the local inhabitants. To earn additional cash, poorer households depend heavily on seasonal agricultural labour on both the farms of local outgrowers as well as at the larger sugarcane estates. They also engage in a range of other income generating activities, such as brick making, brewing and petty trade. Middle and better off households earn extra cash from petty trade and from boda boda (motorcycle taxi hire). There are serious constraints to production in this zone, including severe limitations on the amount of land available for food crop production. As more and more land is taken over for sugarcane production, people are forced to rent plots farther and farther away from their villages in order to grow food. Crop diseases and pests, such rice blast fungus, army worms and rodents, are a constant challenge. Local outgrowers claim that their income is limited by unfair practices on the part of the sugarcane companies, which has led to a climate of distrust and frustration. In addition, there is ongoing conflict between local cropping residents and pastoralists who migrate into the zone to access pasture and water resources. Services in this zone are good compared to much of rural Tanzania, especially for better off households. Drinking water is obtained from rivers and wells that are all fairly close to villages. Tap water, which is found in the village centres, requires a monthly contribution to maintain the pumps. Better off households generally have tap water in their houses. Poorer households use pit latrines and maintain separate pits for garbage disposal; better off households have improved flush toilets in their houses. Most villages have a health dispensary, although these may not be well-stocked. Better off households typically travel to health facilities in the ward centre, or hospitals in regional centres when necessary. Primary schools also available in villages, with secondary schools found at the ward level. Almost all households send their children through secondary school, even poorer households. Middle and better off households send their children through to the university level. There is no electricity in this zone so households depend on battery-operated torches, kerosene lanterns and solar lamps for light. In general, all households have at least one mobile phone and better off households have multiple phones. VICOBA provides access to loans and to savings schemes. The Tanzania Social Action Fund (TASAF), which provides grants to poor households to start income generating projects or to access social services, operates here. Markets The transportation infrastructure in this zone is relatively good. The zone is split into two parts, as discussed above, with one section found in Mvomero, in the north of Morogoro, and the other in Kilombero, in the central western part of Morogoro. The Kilombero part of the zone is very close to a major junction in Tanzania’s railway line, with one arm extending from Mbeya to Dar es Salaam and the other heading north Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 3 to Dodoma. This part of the zone has ready access to the tarmac road that goes from Morogoro to Iringa. The other part of the zone is close to Tanga and Morogoro town. Feeder roads extend throughout the zone, from Dumila to Kilindi, Dumila to Kilosa, and Mikumi to Kilombero. Almost all roads are accessible throughout the year (even in the wet season) and most bridges are in good condition, with the exception of the Mjonga bridge to reach Digoma village. The zone is close to urban centres, which provide a steady demand for local commodities, and good roads make the movement of goods and services relatively easy. Morogoro is the main intermediary market, providing ready access to Dar es Salaam, the main terminal market for most goods. Paddy, maize, pigeon peas and sesame are the main food crops sold by households in this livelihood zone. Sugar cane is the most important cash crop, but this is grown and sold only by middle and better off households. Poorer households rely on maize, pigeon peas, sesame and paddy to generate their crop-based cash income. Maize is sold after both harvests: in February (from the vuli harvest) and June to September (from the masika harvest). Maize is sold locally and generally does not get transported out of the zone. Sesame is sold from June through September and pigeon peas are sold in September. Paddy is sold at its lowest price from July through September and at higher prices from November through April. Only better off households are able to sell at higher prices because they produce surplus paddy and store it until prices peak. Traders come to the farm gate, traveling from village to village to buy up local commodities. They transport crops to Morogoro, where they are sold at retail; or on to Dar es Salaam. The terminal markets for sesame are India and China. It transported by traders to Morogoro and then on to Dar es Salaam, from where it is shipped eastwards on freighters. Pigeon peas follow the same route, but are usually exported only to India, not China. Sugarcane is sold to local sugarcane plantations where it is processed into sugar and sold for national consumption as well as export. There are numerous issues with the marketing of sugarcane that have led to a sense that local farmers are being treated unfairly. These include a lack of transparency with respect to the measurement of sucrose levels (which determines payment to the farmers), lack of representation when it comes to disputes, lack of awareness about rights, concerns about the deductions taken from the farmers’ payments, and suspicion of corruption and exploitation on the part of the sugarcane executives. Households in all wealth groups also buy some maize grain during the year, especially in the lean season, from January through April, when local stocks are low. Maize is the cheapest local staple, and most of this is sourced locally from traders who buy up maize at harvest time and store it for sale later in the year. Beans are also purchased throughout the year; these originate from Mbeya and come into the zone via the main Morogoro market. Non-food essentials, like salt, soap, batteries and kerosene, are sold in local kiosks owned by better off households. The labour market is almost entirely local, with seasonal agricultural work taking place on the sugar plantations as well as on the farms of middle and better off households. It was estimated that in the reference year, 95% of seasonal labour was found within the zone. A very small percentage of work (around 5% of the total) is also found in local towns. There is some in-migration to this livelihood zones; people from other areas come to work on the sugar plantations. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Kilombera- Mvomero Paddy, Maize & Sugarcane Livelihood Zone the reference year covered the consumption period from May 2014 to April 2015. During community leader interviews, informants were asked to rank the last four years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the response of the community leaders, shows year quality by production year (which starts with the vuli rains in October/November and ends with the May through September harvest of the following calendar year.) Thus, the production year of 2013-2014 corresponds to the consumption year of 2014-2015. As shown in the table, the production year corresponding to the reference year was relatively good, with heavy rainfall, average yields and good crop prices. The past four Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 4 years have all been relatively good in terms of rainfall, with the exception of last year; although the incidence of pests and crop diseases is a limiting factor every year. Production Year Rank Critical Events 2014-2015 2.8 Poor rainfall distribution; average crop yields; average staple food prices; occurrence of Rice Yellow Mottle Virus (RYMV) and quelea quelea birds 2013-2014 3 Heavy rainfall; average crop yields; good crop prices; rodents and grasshoppers 2012-2013 3 Good rainfall distribution; good yields; rodents and army worms 2011-2012 3 Average rainfall; average yields; average staple food prices; rodents 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Kilosa for a 50-year period from 1968 to 2008. Source: TZ Meteorology Department There are two rainy seasons in this livelihood zone. The first, called the vuli, is short, starting in October and ending in December; the second, called the masika, takes place from March through May. Because many of the crops grown here are medium- to long-cycle varieties, both rains play a role in the agricultural production season. However, it is after the masika season that the main harvests occur, with the exception of vuli maize, which is harvested in February. There are two maize harvests: the first is planted with the vuli rains in October and harvested in February; the second is planted in March, at the onset of the masika rains, and harvested in July. Pigeon peas are inter-cropped with maize in October, when the vuli rains are fully established. They are harvested seven to nine months later, with the green crop coming in July and the main harvest occurring in September. Sugar cane, another long cycle crop, is planted as a single stand in October and harvested seven to eight months later, from June to August. The paddy production cycle depends on both irrigation and the rains. The vuli rains help soften the ground to prepare for planting. Land preparation for paddy takes place in December, followed by planting in January and February. The green harvest is in May, and the main harvest takes place from June through August. Sesame is also planted in single stands, planted and harvested at the same time as paddy. Given the long production season, and the intensity of labour required for the paddy and sugar cane crops, people here are busy with agricultural activities almost year-round. Land preparation activities begin as early as September and harvests end the following August. The peak labour requirements, however, occur from January through July. In some months, like January, paddy and sesame are being planted at the same time that fields for masika maize are being prepared, vuli maize is being harvested, and sugarcane needs to be weeded. This is a month when poorer household food stocks are low and staple food prices are high. It is the start of the lean season, which lasts through April; a time of relative hardship, when people are working hard and food is harder to come by. Two months of the lean season coincide with a higher incidence of human disease (March and April), which means that household expenditure requirements (to buy medicines) – already stretched from the need to buy more food at higher prices – are even higher. Poorer households, in need of extra cash at this time of year, work on sugarcane plantations and in the fields of middle and better off households, who need extra labour, especially to manage their paddy and sugarcane crops. Most of the cash that poorer households earn throughout the year comes from this seven-month period. The seasonal calendar also shows that chicken sales are highest at this time of year, helping supplement the cash from labour and crop sales. May marks the beginning of the consumption year as households begin to eat paddy green, followed in June by the consumption of green maize and the main paddy harvest. Both access to food and cash flow starts to increase in June as a number of crops are harvested and sold, including sugar cane, paddy, and sesame. The harvest of pigeon peas in September finishes off the production cycle and brings in additional cash for all households. The festival season follows the harvest period, because this is a time when all households have a bit more cash and there is a brief respite before the next production season begins. Petty trade activities are at a peak in these months (July through September) as wealthier households buy up local produce to sell in central markets, and re-stock their kiosks full of basic commodities to be sold locally. Off-farm labour, like brick making and selling, also peaks at this time as poorer households take advantage of the dry season and a break in agricultural labour demand. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. Differences in wealth in this livelihood zone are determined by the amount of land a household cultivates. This, in turn, is related to how much land the household owns along with how much it can rent; and how much labour the household can draw on, both within the household and through hiring. Sugar cane and paddy – the most important cash crops - are both highly labour intensive crops, requiring extra labour investments (relative to the requirements for maize and other crops) at planting, weeding and harvesting times. In addition, ownership of productive assets, like motorcycles (which enable households to make money from boda boda - motorcycle taxi hire), contributes to the basis on which differences of wealth are determined. Livestock ownership is not an important differentiating factor. The graph and table above summarizes the percentage of households falling into each wealth group along with its associated productive assets. One thing to note about the information in the table above is the difference between ‘land area owned’ and ‘land area cultivated’. The existence of large sugar cane plantations limits the amount of land that people can use for planting food and cash crops. Many people start with inherited land or land allocated by the village government to plant sugarcane, but they add to that area by purchasing or renting more land for paddy and maize production. For the most part, the three lower wealth groups own less land than they cultivate, which means they need to rent extra land from either better off households within the zone or from non-resident land owners. The market for rented land has grown enormously in recent years as the squeeze on available arable land increases. Very poor households plant on 1-3 acres, poor households cultivate 3-4 acres, middle households cultivate 5- 8 acres, and better off households cultivate 8-15 acres. Thus, the typical better off households is cultivating more than five times the amount cultivated by the typical very poor household. The other critical divide between poor and middle households is that poor and very poor households need to work for others to earn enough cash to live on and middle households do not work for others. In other words, middle and better off households hire labour to work for them; very poor and poor households provide the labour that gets hired by these upper two wealth groups. Middle and better off households are engaged in trade activities, providing them with another source of cash. This trade is enabled by their ownership of motorcycles. Almost all better off households own at least one motorcycle and some middle households do as well. Bicycles are another common means of transport, and all Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 7 wealth groups except for the very poor own at least one bicycle. Almost all households also own at least one cell phone. Over the last decade, cell phone ownership has become ubiquitous throughout rural Africa. There are more households falling into the very poor and poor categories than into the middle and better off categories. Very poor (29%) and poor (32%) households together comprise just under two-thirds of the households in the zone. Middle (27%) and better off (12%) households combined represent just over a third of the population. Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period May 2014 to April 2015. May represents the start of the consumption year because it is when people begin to consume green crops - especially paddy - and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year. There are only two sources of food in this livelihood zone: own In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. crop production and the market. The relative importance of own crops increases as you move up the wealth spectrum, and the opposite is true for market purchases; poorer households need to buy more food than better off households. However, all households bought a substantial portion of their food in the reference year, which was an average (not a bad) year. This is generally not because households do not produce enough food to cover their own consumption needs: in fact, if households did not sell any of their crops, and consumed them instead, they would meet 140-520% of their minimum calorie requirements.3 Even very poor households could have met their minimum food needs with their own crop production alone, which highlights the productive nature of this zone. However, because there are no other substantive sources of cash income – no livestock, for example – crops are the means for generating both food and cash requirements. Therefore, households needed to sell over half of their crops to fund all the other cash-related expenses in their lives, leaving them with a gap that got filled by the market. In the reference year maize, grown and harvested in two seasons, was the dominant food crop. Although paddy generated more output on a seasonal basis in the one season it was grown, it is used more heavily as a cash crop. The average production reported for maize by households in the reference year was 800-1200 kg per acre, with most poorer households growing maize without the use of industrial fertilizers or pesticides. Combining both seasons, very poor and poor households harvested around 1,130 and 1,930 kg of maize, respectively, in the reference year. Over half of this was sold, leaving these households with enough to cover 29-36% of their minimum calorie requirements. The green maize (fresh maize) harvest covered an additional 2-4% of calorie needs. Middle and better off households produced around 2,350 kg and 4,680 kg of maize respectively, with a balance of approximately 70-80% grown in the masika season. After selling the majority of this, these households retained enough maize to cover 40-55% of their minimum calorie needs during the reference year. 3 Very poor, poor, middle and better off households would have been able to cover 140%, 210%, 315%, and 520% of minimum calorie needs respectively in the reference year with their own crop production alone. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 8 Paddy is the second-most important food crop, although it functions more as a source of cash than food. The average production per acre for paddy during the reference year was 1000-1200 kg per acre. Thus, household production ranged from around 950 kg for very poor households up to 3,700 kg for better off households; 75- 85% of this was sold, leaving households with enough paddy to cover 10-20% of minimum calorie needs. A very small contribution was also made from the sesame grown by the top three wealth groups, although again, most of this was sold. As a whole, own crops accounted for around 43-77% of households’ minimum food needs in this zone during the reference year. To fill the gap, all households purchased food. Poorer households bought mainly maize grain – the cheapest staple. They purchased maize for four to six months of the year, meeting 20-25% of their food needs this way; whereas middle and better off households bought maize for only one to three months of the year, covering 7- 14% of their calorie requirements. All households also purchased rice, although at 1.6 times the price of maize, poorer households limited their expenditure on this grain. Nevertheless, purchased rice accounted for around 10% of household food needs for very poor households and around half of that for better off households. Other purchased foods, like beans, sugar, meat, oil, dried fish, sweet potatoes and vegetables, contributed an additional 23-33% of minimum calories for all wealth groups. Combining both staple grain and non-staple food purchases, households here relied on the market to cover 45-57% of their minimum calorie requirements in the reference year. Sources of Cash Income The graph to the right provides a detailed breakdown of the income sources in this livelihood zone. The main source of cash for the two upper wealth groups is crop sales. The main source of cash for the bottom two wealth groups is agricultural labour. Other sources of cash, depending on the wealth group, include brick sales, petty trade and boda boda (taxi hire). The income table below the graph summarizes absolute cash income ranges in Tanzanian Shillings for each wealth group in the reference year. The average income of better off households is at least three times higher than the average income of very poor households. The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 2,220,000 – 2,700,000 2,700,000 – 3,800,000 3,800,000 – 6,000,000 6,000,000 – 9,900,000 It is clear from the income graph that crops are the main driver of the local economy in this livelihood zone. Of particular importance are paddy and maize sales (for all wealth groups) and sugar cane sales (for the upper two wealth groups). As noted in the section above, households sell the majority of their crop production, retaining less than half for consumption. It is here – in this graph – that we see the economic value of that decision. For 4 The average exchange rate from May 2014-April 2015 was 1 USD = 1,810 TZS Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 9 the upper two wealth groups, these sales are especially important, generating 60-75% of their cash income in the reference year. The bottom two wealth groups, with less to sell, derive 25-45% of their annual cash income from crop sales. Maize and paddy sales combined bring in over 90% of the crop-based cash income for very poor households; the other three wealth groups depend also on sesame sales (not grown by the very poor); and the top two wealth groups grow sugar cane. Maize is sold in both seasons, but the maize from the masika season brings in substantially more in terms of cash income, contributing – for example – 23% of crop-based cash income in the reference year for better off households, compared to the 4% brought in by vuli maize. In addition to maize from both seasons, paddy, sesame and sugar cane, pigeon peas are also sold, providing 4-9% of crop-based cash income in the reference year. An even more important source of cash for very poor households than crop sales is seasonal agricultural labour. This source alone accounted for around 60% of cash income in the reference year for very poor households and around 36% for poor households. Sugar cane and paddy are highly labour-intensive crops, especially at planting and weeding times. Many people are also required to harvest sugar cane, and people are hired to scare birds from paddy fields in the weeks before the harvest as well. Better off and middle households, who cultivate fields that are larger than their household labour can manage on their own, hire members of very poor and poor households to help throughout the year. In the reference year, a typical very poor household sent 1-2 people to work on others’ farms during land preparation, planting and weeding periods, bringing in, on average, over 1,000,000 Tsh from cultivation labour. Harvest labour (including harvesting, threshing and bird scaring) generated an additional 395,000 Tsh. Poor households, who had more of their own land to look after, brought in slightly less than this: around 800,000 Tsh from cultivation labour and 320,000 Tsh from harvest labour. In the off season, when households have finished harvesting and before the rains start again, poorer households seek additional cash earning opportunities, making and selling bricks, preparing and selling food, brewing or gathering and selling firewood. Brick production was especially wide-spread in the reference year, bringing in around 10% of annual cash income for very poor and poor households. Some poor households also engage in small amounts of petty trade, although they are limited by a lack of transportation and investment capital. Petty trade is more important for middle and better off households. These households have some extra money and some means of transport, allowing them to buy up sizeable quantities of local produce and sell it in more profitable markets to make a small margin. Better off or middle households may also have small kiosks where they sell salt, soap, kerosene or other household goods. In addition, many middle and almost all better off households have a motorcycle, which they hire out for a fee (called boda boda) to transport people or goods. These two sources of cash income (petty trade and boda boda,) combined, provided middle and better off households with (on average) 35-40% and 20-25%, respectively, of their cash income in the reference year. Finally, all households derive a very small amount of cash by selling chickens. These are sold throughout the year when cash needs arise, but the total sales on an annual basis do not make up more than 3% of cash income. Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 10 Expenditure Patterns The graph presents expenditure patterns for the reference year May 2014 to April 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other parts of Tanzania, households in this livelihood zone have to buy a number of essential goods throughout the year, and they need to pay for basic services. These include food (both staple and non- The graph provides a breakdown of total annual cash expenditure according to category of expenditure staple), household items, productive inputs, social services (school and health), clothes and miscellaneous items. The graph highlights a number of points. First, the two poorer wealth groups spend more money on staple food, in both absolute and relative terms; but the two upper wealth groups spend more in absolute terms on non-staple foods. As explained above in the section on ‘Sources of Food’, very poor and poor households bought maize grain for 4-6 months of the year. They spent between 260,000 and 290,000 Tsh on maize alone, taking up 15-20% of their cash income. Middle and better off households, on the other hand, spent 90,000 – 185,000 Tsh and had to devote less than 10% of their annual cash to maize. The rest of the staple expenditure was on a very small amount of cassava, beans, oil and dried fish. All households also spent money on other foods, such as rice, sugar, meat, sweet potatoes and vegetables. These are all included in the non-staple food basket. Better off households spent twice as much on non-staple foods as very poor households; the market helps middle and better off households increase their dietary diversity and provides access to preferred foods. Because these non-staple foods are generally more expensive, poorer households can afford to buy less of them, but what they do buy takes a larger chunk of their budget. For example, very poor and poor households spent around 30% of their annual cash on non-staple foods, whereas better off households (who actually spent more in absolute terms in this category) devoted around 20% of their annual cash to non-staple foods. Second, middle and better off households spent a lot more money on productive inputs than the poorer two wealth groups. ‘Inputs’ on the expenditure graph above includes the following: house repairs, land rental, seeds and tools, pesticides and fertilizers, labour, small business investment, and phone credit. Very poor and poor households did not spend any money on pesticides and fertilizers, labour or small business, devoting the majority of their inputs budget to phone credit, followed by house repairs and then land rental. The least is spent on seeds and tools. Middle and better off households spent the majority of their inputs budget (60-70%) on labour. This reflects the high-labour requirements of sugar cane and paddy and highlights the fact that, although better off households make more than three times what very poor households make, this comes at a cost. Business investment and phone credit are the next most important input costs for these households. In absolute terms, better off households spent around 13 times more than very poor households on productive inputs. In relative terms, the poorer two wealth groups allocated around 10% of their annual cash to productive inputs and the top two wealth groups spent 30-40% of their annual income on this category. Third, ‘social services’, which includes the money spent on education and health services, accounted for a significant proportion of annual expenditure. Education covers school fees, uniforms, stationery and Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 11 transportation. Absolute spending on school during the reference year increased substantially as you moved up the wealth spectrum. Very poor households spent around 245,700 Tsh on schooling compared to 735,300 Tsh spent by better off households. This is much higher than in neighbouring zones, where spending on school is less than half of this amount. In this zone, the poorer two wealth groups are typically sending their children to both primary and secondary school, whereas in other zones poorer households only sent children as far as primary school. This is, in large part, because of the cash income derived from sugarcane outgrowing5. Better off households are funding their children’s education all the way through university. Also, as you move up the wealth spectrum, households are spending more on stationery, books, uniforms, school fees and transportation. Better off and middle households also spend more on medicine and health care; the poorer two wealth groups spent around 80,000 – 86,000 Tsh on health in the reference year, whereas middle and better off households spent 155,000 – 188,000 Tsh. Of course, these are general statements and individual households will have had very different requirements depending on whether or not a household member became sick and whether or not medical treatment was sought. Fourth, expenditure on basic household goods (‘hh items’), including all of the items bought by households over the year to meet basic needs, such as tea, salt, soap, kerosene, grinding services and utensils, took up 5-10% of the expenditure basket for all households. Within this category, very poor and poor households spent the most on soap (28% and 26% of the ‘HH items’ budget, respectively), followed by grinding (20% and 23% of the ‘HH items’ budget, respectively). Middle and better off households spent the most within this category on kerosene and firewood; these two items combined accounted for 45-50% of the ‘HH items’ budget in the reference year. Soap took up the next largest chunk. Finding ways to reduce the relatively high costs of soap and grinding for poorer households could help them free us some money for other productive uses. Spending on clothes and other miscellaneous items are the last two categories included here. These two categories combined made up 18-22% of the expenditure basket for all wealth groups in this livelihood zone. The ‘other’ category includes things like beer, tobacco, cigarettes, cosmetics, hair braiding, transportation and festivals. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. As a reminder, the reference year was a relatively good year, so this discretionary category is higher here than it would be in bad years. Hazards There are a number of hazards that affect this zone on a regular basis. The first is crop pests and diseases, especially army worms, which affect maize and rice, rice blast and quelea quelea birds, which threaten the rice harvest, and rodents. Second, less of a hazard than a constraint, is a scarcity of land for agricultural production. This is a particular problem in the areas around the sugarcane plantations and near the national park (in the south). Third, conflict between farmers and pastoralists is high in this zone. Competition over scarce pasture and cropping lands as well as prime water sources has resulted in contested access to resources crucial for both farmers and livestock keepers. There are also occasional floods that can seriously undermine production during one or both seasons two out of every five years. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: 5 “Study of Sugarcane Outgrowing at Kilombero”, May 2015, page 4, http://dspace.africaportal.org/jspui/bitstream/123456789/35492/1/Kilombero%20stakeholder%20report_English%20Version.pdf?1 Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 12 All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Poorer households try to increase their local agricultural labour, working more days per month and sending more household members to work. There are limits on this strategy in a bad year since an increase in labour supply will inevitably drive down wages after a while. Thus, although more hours of work might be obtained by the household, the payment per day is likely to be reduced. Poorer households also try to sell more chickens. However, as the number of chickens owned by very poor and poor households does not exceed 20, and each chicken is worth only around 9,000 Tsh in a good year, this option will only go so far in terms of raising cash income, especially since the price is likely to drop in bad years. Middle and better off households try to reduce the amount they pay for agricultural labour, freeing up some of their cash income to spend on other essentials. This works in direct counterpoint to poorer households’ strategy of attempting to increase their agricultural labour income. Middle and better off households try to increase their sales of crops, selling their surplus at a higher price given the limited supplies on the market. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non- staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – vuli – amount produced Maize - masika - amount produced Pigeon peas – amount produced Paddy – amount produced Sesame – amount produced Sugar cane – amount produced Maize – vuli – producer price Maize - masika – producer price Pigeon peas – producer price Paddy – producer price Sesame – producer price Sugar cane – producer price Livestock production Chickens - numbers Chickens – producer price Other food and cash income Agricultural labour (land clearing and preparation, planting, weeding) – number of jobs Agricultural labour (bird scaring, harvesting, threshing) – number of jobs Petty trade – amount of trade Bricks – numbers produced Agricultural labour (land clearing and preparation, planting, weeding) – wage rates Agricultural labour (bird scaring, harvesting, threshing) – wage rates Petty trade – margins on trade Bricks – prices Expenditure Maize grain – consumer price Rice – consumer price Beans – consumer price Sugar – consumer price Oil – consumer price Kilombero-Mvomero Paddy, Maize & Sugarcane Livelihood Zone Profile 13 Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. 1) Improve education services, ensuring that each school has an adequate number of qualified teachers 2) Provide access to affordable loans for agriculture 3) Set aside reserved areas of land for dedicated crop cultivation 4) Provide affordable agricultural inputs with adequate lead time for cultivation period 5) Improve health services by providing well-equipped dispensaries with affordable medicines at village level 6) Improve market infrastructure to ensure local households receive the best prices for their crops 7) Resolve conflict between farmers and pastoralists In addition, there are specific problems related to the payment for sugarcane which lead to households receiving less payment than they should. These could be addressed as follows: Identify which policies of the sugarcane cooperative create unfair conditions for the local farmers. Reduce the deduction take from the payment received by farmers. Create a more open and transparent system of standard measurement so that systems for weighing, sucrose measurement and payment calcuation are more open and fair and involve representation from outgrowers. Rotate district agricultural officers who are responsible for farmers in sugarcane plantations to reduce potential for corruption. Regularly assess the amount paid per ton of sugarcane in relation to the economic situation facing the farmers and producers. | false |
# Extracted Content Morogoro Highland Maize & Vegetable Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Morogoro Highland Maize & Vegetable Livelihood Zone (TLZ 47) April, 20161 Zone Description The Morogoro Highland Maize and Vegetable Livelihood Zone is a small zone found in Mvomero District in Morogoro Region, including seven wards: Mlali, Bunduki, Mgeta, Langali, Nyandira, Tchenzema and Kikeo. At 2,000 to 2,300 metres above sea level, this is a highland area overlooking the town of Morogoro. The topography is made up of mountainous terrain, with hills and valleys following the contours of two main rivers: the Mgeta and Mbakana. The rivers are part of the Ruvu sub-basin, which is found at the base of the Uluguru mountains. They provide a year-round source of water for irrigation. This was originally a heavily forested area, much of which has been cleared for agriculture. Only a third of the forest cover that existed here in 1900 remained by the mid-1990s2. Rainforests in on the high mountain slopes have been declared forest reserves, but enforcement of the protections associated with this status are not easily imposed. Agricultural lands, surrounded by forests, are the main ground cover. The population density is around 42 people per square kilometre3. The rains here fall in two periods, from October to January, and then March through May. Annual precipitation ranges from 700-2,300 mm, with higher amounts found at higher elevations. Temperatures average around 180 C in the cool season and 300 C in the warmer months. The soils are well-drained, moderately deep to deep, reddish and yellowish sandy clay loams and sandy clays. Soil fertility is low, and land is hard to come by. The local economy rests on the cultivation and sale of vegetable crops. Households here generally do not produce enough food crops to cover their annual consumption needs. Thus, the strategy is to grow higher value vegetable crops throughout the year using both rain-fed and irrigated plots, and to use the cash from the sales of these crops to fund essential food and non-food purchases. This strategy depends on households’ access to markets, which is not always assured during the rainy season. Livestock are not a central part of the household economy, but provide small amounts of supplemental income. Households cultivate on small plots of land, constrained by the mountainous terrain and a growing population density. They use these small plots to maximum effect, however, growing a large array of crops, 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in February 2014 and ended in January 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020-2025). All prices referred to in the document are for the reference year. 2 Nobert, Joel, et al, Investigating the effects of landuse change on the streamflows of upper Ruvu River Subbasin, Tanzania, www.waternetonline.ihe.nl/symposium/10/.../Nobert-%20J.doc 3 Based on the 2012 national census. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 2 including maize, beans, pigeon peas, green peas, tomatoes, cabbages, sweet peppers, cow peas, carrots, eggplants and bananas. Maize and beans, as well as small amounts of Irish potatoes, green peas and bananas, are grown for household consumption; a portion of these crops is also sold. All the vegetable crops are grown almost exclusively for sale. Tomatoes and cabbages are especially important cash crops, and these tend to be grown mainly by middle and better off households, who can afford the expensive inputs associated with these crops. The vegetable crops are irrigated during the dry season, or when rainfall distribution is poor; maize, beans and bananas are entirely rain-fed. All cultivation is done by hand, using hand hoes and machetes. It is not possible to use oxen because of the mountainous terrain. All households use improved seeds, as well as fertilisers and pesticides, although the quantities vary by wealth group. The agricultural season extends throughout the year, and people are busy almost every month with one task or another. Land preparation, planting and transplanting tomatoes, and weeding are especially arduous, and for these tasks middle and better off households hire members from poor and very poor households to work for them. This provides important cash for poorer households, who could not survive without this seasonal work. It also provides critical labour for middle and better off households, without which they could not produce their surplus crops. Livestock is a minor source of cash for all households. Goats, pigs and chickens are raised. Chickens are the only animals owned by all wealth groups; very poor households do not own significant numbers of goats or pigs. Goats graze and browse freely; pigs are stall-fed on crop residues, maize husks and green leaves; chickens range freely, subsisting on maize husks and food scraps. The main water sources for livestock are minor rivers and streams; water is not purchased for animals. In addition to vegetable sales and local agricultural labour, households here earn cash through self- employment activities (such as brick making, brewing, and firewood/charcoal sales for poorer households) and petty trade (such as owning kiosks, or boda boda for middle and better off households). The services in this zone are similar to many rural areas in Tanzania, with the exception of access to water, which is better here than in most places. Fresh, potable water is obtained from rivers, streams and mountain springs. Sanitation facilities consist of pit latrines, most without covers and of poor quality. Health dispensaries are found in many villages, or at the ward centre, but they are not always well-stocked or staffed with qualified medical professionals. Most people use Community Health Funds (CHF). Primary schools are found in the villages and secondary schools are available in the ward centres. It is common for all households to send their children through primary school, but only middle and better off households are able to afford the extra costs of secondary school. Some better off households also send their children to college. There is no electricity, so poorer households depend on kerosene lamps, while better off households also use battery-operated torches. Households in all wealth groups have mobile phones, with better off households having multiple phones. There are no sources of credit, nor are there savings schemes available. Markets Market access is especially important in this zone, because household depend heavily on the sale of fresh vegetables throughout the year. On the one hand, the transportation infrastructure in this zone is good: trucks can always reach Nyandira, the central vegetable market, where households bring their commodities for sale; and from Nyandira there is a good tarmac road to Morogoro, which has easy access to the terminal market in Dar es Salaam or Dodoma. Therefore, if people reach Nyandira, they are almost guaranteed to have a market for their goods. On the other hand, the road access for farmers living in remote villages is not always secure. In the rainy season vehicles get stuck in the mud or are blocked by seasonal streams or boulders that get washed into roads. Households sell a range of food crops and vegetables, including maize, beans, pigeon peas, green peas, Irish potatoes, tomatoes, cabbages, onions, carrots, sweet peppers, eggplants and cucumbers. Tomatoes and cabbages are particularly important cash crops. All locally-grown food crops and vegetables follow the same trade route. After harvesting, farmers must transport their goods to Nyandira, and from there they are sold Morogoro Highland Maize & Vegetable Livelihood Zone Profile 3 on to Morogoro, Dar es Salaam and/or Dodoma. Tomatoes are sold throughout the year, but the peak sales occur in January, from the vuli harvests. The peak selling time for beans is in February; for cabbages it is November; and for green peas it is July. People reach the central market on foot, by bicycle or motorcycle. Unlike in many parts of Tanzania, traders do not buy up vegetables at the farm gate. Vegetables need to be transported to market soon after harvesting, and there is a short window of opportunity for selling them. Many are vulnerable to bruising and rotting, especially in hot weather, so care needs to be taken during transport. Traders do not want to take on the risks involved, preferring to transfer these to local farmers. Traders buy up commodities once they reach the central market of Nyandira, where vegetables are collected and bundled for onward sale to Morogoro, Dar es Salaam and Dodoma. Thus all the risks of transporting fresh vegetables to market rest on the farmers, who must traverse rocky, mountainous dirt roads that often become inaccessible in the rainy season. From interior villages like Kikeo, Tchenzema, Tandari, Luale and Bumu, these risks are not insubstantial. Livestock are sold at small mobile ward- and sub-ward level markets within the zone throughout the year. Most livestock are for local consumption and do not get sold onwards. Sales occur throughout the year, when people need extra cash for school fees, medical expenses, festivals, or unexpected emergencies. All households also buy food during much of the year. Poorer households buy maize grain, the cheapest staple, to cover their needs for nine to ten months of the year, starting in August, even in relatively good production years. Most maize is sourced from Morogoro and Kibaigwa, and sold through the Nyandira market. Rice, purchased mostly by better off households, comes from Turiani and Kilosa via Morogoro to the Nyandira market. Non-food essentials, like salt, soap, batteries and kerosene, are sold at local kiosks that are owned by middle and better off households. The labour market is mostly local and consists of seasonal agricultural labour. There is also a small demand from local towns and some seasonal employment is found outside the livelihood zone. It was estimated that in the reference year, 85% of seasonal labour was found within the zone on local farms. An additional 10% came from local towns, and the other 5% came from outside the livelihood zone, mainly from Mbigiri and Magole, in Kilosa District, where there is often work to be found on tomato and paddy farms. The balance shifts in bad years, with more people traveling to local towns or to areas outside the zone to find work. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Morogoro Highland Maize & Vegetable Livelihood Zone the reference year covered the consumption period from February 2014 to January 2015. The production year starts with the planting season in October/November and ends with the harvest in February through April of the following calendar year. Thus, the 2014-2015 consumption year corresponds to the production year that starts with the 2013-2014 vuli season. During community leader interviews, informants were asked to rank the last five years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below, which summarizes the responses of the community leaders, shows year quality by production year. The production year of 2013-2014, which corresponds to the consumption year of 2014-2015 was considered an average year. In the past 10 seasons, there have been 5 average seasons, 2 below average seasons, and 3 above average seasons. The baseline information presented in this profile provides a view into how households in this livelihood zone make ends meet in an average year. Production Year Season Rank Critical Events 2014-2015 Masika 4 Above average rainfall, good crop yields, good producer prices, low staple food prices 2014-2015 Vuli 4 Above average rainfall, good crop yields, good producer prices, low staple food prices 2013-2014 Masika 4 Above average rainfall, good crop yields, good producer prices, low staple food prices Morogoro Highland Maize & Vegetable Livelihood Zone Profile 4 2013-2014 Vuli 3 Average rainfall, normal harvest, decent producer prices 2012-2013 Masika 3 Average rainfall, normal harvest, decent producer prices 2012-2013 Vuli 3 Average rainfall, normal harvest, decent producer prices 2011-2012 Masika 3 Average rainfall, normal harvest, decent producer prices 2011-2012 Vuli 3 Average rainfall, normal harvest, decent producer prices 2010-2011 Masika 2 Below average rains, with below average harvest and high staple food prices; received food aid from the government 2010-2011 Vuli 2 Below average rains, with below average harvest and high staple food prices 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year This is a bi-modal area: the first rains occur from October through December (vuli) and the second are from March through May (masika). The masika rains are usually heavier and more reliable. Agricultural activities are linked to the timing of the rains, but because irrigation is also used, households here are busy year-round with different crop-based activities. Land preparation occurs in September for the vuli crops, and in February for the masika crops. The October rains soften the ground enough so that people start to plant maize towards the end of October. Tomatoes are planted towards the beginning of October, often with the use of irrigation from streams. Beans are planted at the same time as these two crops, inter-cropped with both maize and tomatoes. Cabbage and Irish potatoes are planted as single stands. Cabbages are grown in two main seasons; the first corresponds to the masika season, planted in March and harvested in May and June; the second season relies on irrigation and is planted just after the first harvest and harvested two months later in September. Irish potatoes are planted in June, also irrigated using the water from streams and rivers, and harvested in October and November. Most maize is harvested in March and April, preceded by a month of green consumption. A period of sales follows the harvest of each crop. The peak agricultural labour periods are, first, from October through February, corresponding to planting of the first maize crop, and planting and transplanting of the first tomato crop; weeding for both crops; the first tomato harvest; the tomato harvest and land preparation for cabbages. And, second, from June through July, which is when cabbages are harvest, tomatoes are re-planted, Irish potatoes are planted, and all the irrigated vegetables are weeded. All activities are done by hand, and land preparation, transplanting tomatoes and weeding are especially arduous. Even though middle and better off households do not cultivate large areas of land, they need extra help to manage the intensive periods of the year, and so they hire members of very poor and poor households to work for them on all of these tasks. Land preparation takes place over 2.5-4 months (at different times of year); planting/transplanting occurs for 3 months (although not consecutively); and weeding also is being undertaken for 3 months at different times of year depending on the crop and the season. The harvesting periods also take place for around 2 ½ months of the year. During these times, members of poor and very poor households work on the larger farms of middle and better off households, while, at the same time, tending to Morogoro Highland Maize & Vegetable Livelihood Zone Profile 5 their own fields. The ultimate result is that poorer households have lower yields due to less-intensive management on their own fields during critical periods. The graph to the right shows average monthly rainfall (mm) in Morogoro District based on a 20 -year period (1994-2013) Source: TZ Meteorology Department December and January is when the lean season occurs. These are the months that households have run out of their maize stocks from the previous year’s harvest. Poorer households, in fact, run out as early as June or July, but by December, all households have depleted their stocks. They need to purchase all of their staple grains just when the price of staple foods is highest (from December through January). Thus, the paid work for weeding maize and harvesting tomatoes, which is offered up by middle and better off households at this time, helps provide needed cash to poorer households, allowing them to bridge the gap until February, when the green harvest of maize is available. The dry season starts in earnest in June and lasts through September. This is a time when most human illnesses, especially pneumonia and upper respiratory diseases, occur. The weather during this period in this high, mountainous zone is quite cold, creating the conditions for these sicknesses. It is worth keeping in mind that the most important livelihood capital that poorer households have is their own labour; when an active labourer is sick in a poor household, the income for this household rapidly drops. Because this coincides with one of the peak labour periods, it can be especially damaging for a productive household member to be sick at this time. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. The festival season takes place in September and October, when the proceeds from the previous year are available to spend, and before the intensive work of the coming agricultural season has kicked into high gear. It is a rare moment of relative downtime in the otherwise very busy schedules of people living here. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 6 Wealth Breakdown Note: The percentage of household figures represent the mid-point of a range. The main determinant of wealth in this livelihood zone is how much land a household cultivates, and related to this, the type and quantity of vegetable crops grown. How much land a household cultivates is, in turn, governed by the amount of land it owns and/or is able to rent in; the size of its intra-household labour pool as well as its capacity to hire additional labour; and the amount of cash it has available to buy seeds, fertilizers and pesticides, which are especially important when it comes to the success of vegetable crops. Arable land is not easy to come by in this mountainous terrain, and plot sizes are small; even better off households do not cultivate more than 4 acres. All households use hand hoes, as the terrain is not amenable to ox ploughing. Typical better off households cultivate around 2.5-4 acres of land, using hired labour as well as intra-household labour. They devote as much of their land as possible to tomatoes and cabbages, which offer up the highest returns. These crops also demand high investments, and better off households buy the most pesticides, fertilizers and improved seeds. They also hire the most seasonal agricultural labourers. Better off households have more livestock than other households, usually keeping a herd of around 10-18 goats and a few pigs, alongside 10-30 chickens. Their household sizes are a little smaller than poor and very poor households, with around 4-6 members. These households may also own other assets, like a motorcycle for boda boda, or they may operate a kiosk. They typically own several cell phones, which are used to gather price and market information as well as to keep in touch with far-away relatives. Typical very poor households, on the other hand, cultivate only 0.5-1.5 acres of land. They do not produce enough in any year to cover all of their food and cash needs. These households have very few goats, if any (0-2), and pigs (0-2) as well as some chickens (4-8). Very poor households tend to be slightly bigger in size, with 5-7 members. They face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone. The distribution of wealth in this zone is weighted towards the bottom. Very poor (30-40%) and poor (20-40%) households together make up around 50-80% of households in the zone. Middle (20-30%) and better off (8-15%) households combined represent around 28-45% of the households. In addition, since middle and better off households are slightly smaller, it is important to remember that the percent of the population (as opposed to the percent of households) represented by the upper wealth groups is even smaller than this. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 7 Sources of Food The graph to the right presents the sources of food for households in different wealth groups in the livelihood zone for the period February 2014 to January 2015. February represents the start of the consumption year because it is when people begin to harvest green maize and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an average year, with average rains, crop yields and prices. There are only two sources of food In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. in this livelihood zone: own crops and purchased food. Own milk and meat do not contribute to the food basket, as they do in many other zones. As you move up the wealth spectrum, reliance on own crops increases. Food purchases are important for all wealth groups, but especially for poorer households. Maize, along with very small amounts of beans, pigeon peas, green peas, cassava and Irish potatoes, provide the calories shown in the ‘own crops’ bar on the graph above. Collectively, these accounted for 44-67% of the minimum calorie requirements for households in the reference year. The majority of these came from maize, which contributed (including green maize) 36%, 36% 48%, and 61% of minimum food needs for very poor, poor, middle and better off households, respectively. The other crops accounted for only around 7-11% of food needs. Thus, even in an average year, very poor and poor households are meeting, at most, only half of their annual food needs with crop production. Taking a closer look at production, typical middle and better off households produced around 600 kg and 1,000 kg of maize, respectively, in the reference year, along with 430 kg and 480 kg of pulses, respectively, and around 350-400 kg of Irish potatoes. With the exception of maize, the production values for food crops do not vary much between middle and better off households. Very poor and poor households produced around 450 kg and 540 kg of maize, respectively, 150 kg and 250 kg of pulses, respectively, and 190 kg of Irish potatoes (for both). These are not high levels of production, reflecting the fact the households have very small agricultural plots. The only households that could cover all of their food needs with their own production alone, if they consumed all (rather than selling part) of their food crops would be the better off households. (Even then, they would only be able meet around 135% of their calorie needs, which does not represent a large surplus.) The vast majority of households here produce significantly less than they need for survival in an average year. The market is, therefore, especially important in this livelihood zone, accounting for around 47-48% of minimum food needs for all households. The poorer two wealth groups purchased mostly maize grain, the cheapest staple. Of the 47-48% of minimum calories these households bought, 32-36% were in the form of maize grain, or in other words, around three-quarters of their purchased food (in calorie terms) was made up of maize grain. Middle and better off households, on the other hand, purchased only around 14% and 9% of their minimum calories in the form of maize grain. In other words, less than a third of their purchased food (in calorie terms) was made up of maize grain. For middle and better off households, the ‘purchase’ component was comprised of more high-value, preferred foods, such as wheat flour (2% of minimum calories), rice (13% of minimum calories), sugar (6% of minimum calories), meat (1-2% of minimum calories), oil (8-11% of minimum calories), dried fish (2% of minimum calories), and sweet potatoes (1% of minimum calories). By comparison, very poor and poor households purchased only around 11-15% of their minimum calories in the form of these higher-value food items, and much of this was oil. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 8 Sources of Cash Income The graphs to the right present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. Because households need to purchase at least half of their food every year in this zone, it is especially important to know where the cash to fund those purchases comes from. Crop sales provide the most important source of revenue for all but the bottom wealth group. Especially striking is the contribution made by sales of tomatoes and vegetables. With smaller areas under cultivation, households here choose to use a good portion of their available land for high-value vegetable production. In the reference year, the combined value of tomato and vegetable sales accounted for 16%, 28%, 38%, and 42% of the annual cash income of typical very poor, poor, middle and better off households, respectively. Maize, beans, pigeon peas, green peas, Irish potatoes and bananas are also sold. The pulses, and especially beans and pigeon peas, garner the highest price (around 1,500/kg in the reference The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 1,500,000 – 2,000,000 2,000,000 – 3,000,000 3,000,000 – 4,000,000 4,000,000 – 6,500,000 year) so even small amounts can earn households a meaningful amount of cash. Typical middle and better off households sold 270-410 kg of pulses, generating around 425,000 – 535,000 TZS, or 11-12% of annual cash income. Sales of maize and the other food crops brought in substantially less than this. Overall, crop sales accounted for 28% of the annual cash income of typical very poor households, 53% of the annual cash income of typical poor households; and 65-70% of the cash income of middle and better off households. In absolute terms, better off households generated around 7 times more from their crop sales than very poor households, which is 4 The average exchange rate from February 2014 - January 2015 was 1 USD = 1,777 TZS Morogoro Highland Maize & Vegetable Livelihood Zone Profile 9 proportionally more than the difference in land they cultivate. Better off households cultivate, on average, 3.25 times more land than very poor households, but are able to derive substantially more value per acre from their efforts. They invest more in terms of labour and inputs, and are able to better time their ploughing, labour and inputs applications, enabling them to produce more in absolute terms; and they can also grow more of the higher- value crops, which allows them to make the most of their investments. For middle and better off households, small business and trade (shown as ‘petty trade’ on the graphs) was the next most important source of cash income in the reference year, comprising 17% and 24% of their annual cash income, respectively. These households are able to use some of their cash to buy household goods and commodities, like salt, soap, kerosene and batteries in bulk; they set up kiosks in the villages and generate extra income through this business. Some also make money from boda boda, or motorcycle hire, which is especially important for transporting agricultural commodities and people from the villages to the central vegetable market in Nyandira. Very poor and poor households do not have the financial means to set up shops or buy motorcycles for transporting goods, so they turn instead to casual labour as a means of securing needed cash. Casual labour is, in fact, the most important source of cash income for very poor households, accounting for 45-50% of their cash income in the reference year. Poor households derived around a third of their cash income from this source. Agricultural activities take place throughout the year in this zone, and poorer households provide a good portion of the labour pool for middle and better off households. Labour is hired for land preparation, planting, weeding and harvesting. Very poor households derived a relatively even amount of their annual cash from each of these activities (around a quarter of their labour-based cash income from each). Poor households earned the most from land preparation, followed by weeding. In a bad year, harvest-related labour may be eliminated, and demand for the other activities would be much reduced. Livestock sales provided the remainder of cash income for the top three wealth groups in the reference year. Overall, livestock sales accounted for only around 5-15% of cash income for households in this livelihood zone. Goats, pigs and chickens are sold. A typical better off household sold around 4 goats (at 45,000 TZS per head), 8 chickens (at 8,000 TZS per head) and 1 pig (at 10,000 TZS) in the reference year; middle households sold more pigs – around 4 – because they have less in the way of crop income, so try to make up for that through pig ownership. They also sold around 2-3 goats and 6 chickens. Very poor and poor households sold only around 4 chickens, along with 0-2 goats and 0-2 pigs. The price of animals did not vary much by wealth group. Livestock are not a significant differentiator in this zone, and although better off households did earn around 3 times more than very poor households from livestock sales, they actually earned less than middle households and almost the same as poor households. Vegetable sales are crucial here, not livestock sales. One final source of cash income for very poor households was self-employment, which included mainly brick production, but also brewing and firewood/charcoal sales. These activities contributed almost a fifth of the annual cash income for these households in the reference year. Expenditure Patterns The graph below presents expenditure patterns for the reference year February 2014 to January 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. The goods and services on which households in this zone spend their cash include: staple and non-staple food, household items, productive inputs, social services, like schooling and health, clothing and other non-essential items, such as tobacco, cosmetics and festivals. As in many other areas of rural Tanzania, poorer households spend a larger proportion of their available cash on food, and those in the top two wealth groups spend a larger portion of their money on productive inputs. All wealth groups spent some of their available cash on staple foods, which includes (in this case) maize grain, wheat and rice. In both absolute and relative terms, very poor households spent more than any other wealth group Morogoro Highland Maize & Vegetable Livelihood Zone Profile 10 on staple foods. In the reference year, very poor and poor households spent around 28-33% of their annual cash on staple foods; and middle and better off households spent 8%-13% on this category. The make-up of the staple food basket is not the same for all wealth groups. Very poor and poor households spent a total of 530,000-539,000 TZS on staple food; 405,000-459,000, or 75-85% of this was, on maize grain, the cheapest staple. Middle and better off households spent around 460,000 and 407,000 TZS, respectively, on staple foods, but only 144,000 and 90,000 TZS, or The graph provides a breakdown of total annual cash expenditure according to category of expenditure around 20-30%, on maize grain. They concentrated their spending on rice, first, which is a preferred food, and then wheat. Unlike in many zones, where middle and better off households do not need to spend cash on staple grain, in this zone all households, with the exception of some better off households, need to buy staples to fill a calorie gap, although this gap decreases as you move up the wealth spectrum. Poorer households spent more in absolute terms on staple foods, but middle and better off households spent more in absolute terms on non-staple foods. The non-staple food category included beans, Irish potatoes, sugar, meat, oil, dried fish, sweet potatoes and vegetables. Of these, the lower two groups spent the most on meat and dried fish, supplementing their heavily grain-based diet with protein, followed by oil and then sugar. Middle and better off households spent the most on meat. After this, relatively equal amounts were spent on sugar, oil and dried fish. In the reference year, the proportion of cash income spent on non-staple foods for very poor, poor, middle and better off households was around 22%, 21%, 19%, and 17%, respectively. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 9%, 10%, 19% and 23%, respectively. Thus, better off households are able to buy a more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less. Middle and better off households both spent the largest portion of their annual cash income on productive inputs, as represented by the dark blue bar in the graph. In proportional terms, their spending on productive inputs (27- 34% of annual expenditure) is similar to very poor and poor household spending on staple foods (28-33% of annual expenditure). The following are included in this category: livestock drugs, land rental, seeds/tools, pesticides/fertiliser, labour hire, business investment, and phone credit. Within this set, very poor households spent money only on seeds/tools, pesticides/fertilisers and phone credit, with the most spent on seeds/tools, followed by phone credit and finally pesticides/fertilisers. Middle and better off households spent money on all items within the category (with the exception of land rental, which only applies to better off households); the majority of their inputs budget was on seeds, tools, pesticides and fertilisers (35-39% of their inputs budget), and labour hire (27-32% of their inputs budget). Fertilisers and pesticides are more important in this zone than they are in other zones because of the dependence on vegetables and tomatoes for cash income. In many zones there is no spending at all on those items, but here all households devote at least part of their budget to these goods. In absolute terms, the amount spent by better off households on productive inputs was 9-10 times the amount spent by very poor and poor households, and almost 2 times the amount spent by middle households. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services, firewood and utensils. Within this category, very poor and poor households spent the most money on soap, which took up around a third of this budget, followed by payment for lighting and grinding, each of which made up around 15-20% of the ‘hh items’ budget. Middle and better off households spent the most on lighting. Middle households spent the next most on soap, whereas better off households spent the next most on firewood. Neither very poor nor poor households spent money on firewood, Morogoro Highland Maize & Vegetable Livelihood Zone Profile 11 collecting it themselves, and selling extra bundles to the top two wealth groups. All households spent the least on salt and tea. On an annual basis, spending on basic household goods made up 12-13% of annual expenditure. ‘Social services’, shown in orange on the graph, includes schooling and health costs. Households spent 9-11% of their annual cash on these costs. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, better off households spent on education around 1 ½ times more than middle households and 2-2 ½ times more than poor and very poor households. Very poor and poor households usually are not able to send their children beyond primary school, whereas those in the upper wealth groups may send them at least as far as secondary school, and sometimes on to college. Secondary schools are found only at ward level, and this means paying for things like transportation, boarding, higher fees and more expensive uniforms and supplies. In addition, better off households spent 3 ½ times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Very poor households seek medical care at village dispensaries and ward-level health centres, which – although free or very reasonably priced - are often understocked and understaffed. Spending on clothes and other miscellaneous items are the last two categories included here. Spending on clothes accounted for 5% of the annual budget for all households. The ‘other’ category includes things like cosmetics, hair, beer, tobacco, cigarettes, community obligations, transportation and festivals; in the reference year households devoted 7-15% of their cash to these items. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was an average year, even the very poor wealth group had more in this budget than it would in a bad year. Hazards Two hazards affect this zone on a regular basis. The first is crop pests and diseases. Tomato leaf miner (tuta absoluta) is especially destructive, as it can destroy a whole season’s crop. Elegant grasshoppers, which affect maize and leaf hoppers and stem rot, which affect beans cause problems throughout the zone almost every year. The second is livestock disease, such as contagious caprine pleuropneumonia (CCPP) for goats, worms for pigs, and New Castle Disease, which can wipe out an entire flock of chickens. Human diseases are also endemic, especially malaria and upper respiratory diseases. Because household labour is so critical to income generation, especially for poorer households, losing this labour can translate into significant drops in income. The main periodic hazards are drought, which can seriously damage crop production once every three years. Droughts result in a series of inter-related shocks, such as rapid increases in staple food prices, declines in livestock production, reduced labour income and reduced returns on self-employment. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple – maize – instead, or cutting down on festivals, tobacco and beer. Middle and better off households try to increase their irrigation activities. When the rains fail, households who have the means to do so attempt to increase their production of irrigated crops. In years when rain-fed crops fail, irrigated crops fetch even higher prices than normal, so if the strategy succeeds, it can be quite effective. Morogoro Highland Maize & Vegetable Livelihood Zone Profile 12 Very poor and poor households try to increase cash income through finding more casual work, either locally or migrating outside the zone. In particular, people may go to Mbigiri and Kilosa districts, where they find work on tomato and paddy farms. The expandability of this option is limited in bad years because of the increase in labour supply as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Morogoro Highland Maize & Vegetable Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Beans – amount produced Pigeon peas – amount produced Green peas – amount produced Irish potatoes – amount produced Sweet potatoes – amount produced Bananas – amount produced Tomatoes – amount produced Maize– producer price Beans – producer price Pigeon peas – producer price Green peas – producer price Irish potatoes – producer price Tomatoes – producer price Livestock production Goats – herd size Pigs - numbers Goats – producer price Pigs – producer price Other food and cash income Agricultural labour (land preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Bricks – numbers produced Petty trade – volume of trade Agricultural wage rates (land preparation, planting, weeding) Agricultural labour rates (harvesting) Bricks – price per brick Petty trade – returns on trade Expenditure Maize grain – consumer price Rice – consumer price Sugar – consumer price Oil - consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. Other than pasture improvement, all of the options were proposed for all wealth groups. All of these suggestions require further detailed feasibility studies. Timely and affordable provision of crop inputs Improved maintenance of existing road networks and increased construction of new roads Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines | false |
# Extracted Content Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 1 Tanzania Livelihood Baseline Profile Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone (TLZ 56) April, 20161 Zone Description The Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone2 is found in Dodoma Region, in central Tanzania, and includes parts of Bahi, Dodoma Municipal and Chamwino districts.3 This is a warm, semi-arid, lowland area, interspersed with hills and valleys, and located on a broad plateau ranging between 900 and 1,200 metres above sea level. The vegetation is largely semi-desert and bush with areas of savannah grassland. There are no mountains or permanent rivers of note. This zone is relatively well-connected to other parts of Tanzania owing to its central location. A major highway connects Dodoma with Dar es Salaam via Morogoro to the east. To the west, there are roads to Mwanza and Kigoma through Tabora. The Great North Road links the area to Arusha via Kondoa to the north. The central railway line also connects Dodoma to Dar es Salaam to the east, Kigoma to the west, and Mwanza to the north-west. The population density is around 38 people per square kilometre. There is one rainy season, starting in December and lasting until April or May. Annual precipitation is quite limited, ranging from 500 to 600 mm. Poorly distributed rains are a regular occurrence, with dry spells particularly common in January, when most of the crops are sown. Average temperatures vary from 180 C in July to 310 C in November. The cool dry season begins in June and ends in early September. The soils are loamy sands and reddish loamy sands. The household economy is based on both crop production and livestock raising. Food crops are all rain-fed, and because of poorly distributed and inadequate rainfall, there are frequent bad years, leading to deficits among poorer households that need to be filled with food aid. Grapes are the main cash crop, and they provide a meaningful source of income, but only for households in the upper two wealth groups. 1 Fieldwork for the current profile was undertaken in February of 2016. The information presented in this profile refers to the reference year, which was the consumption year that started in April 2014 and ended in March 2015. Provided there are no fundamental and rapid shifts in the economy, the information in this profile is expected to remain valid for approximately five to ten years (i.e. until 2020- 2025). All prices referred to in the document are for the reference year. 2 In the 2008 FEWS NET Livelihood Zoning, this zone was called the Dodoma Lowland Sorghum, Bulrush Millet, Sunflower & Grape Livelihood Zone, but because oilseed crops (like sesame) are important, and sorghum and sunflower are less important, the name has been changed. 3 The wards included in the zone are Mtitaa, Mwitikira and Chibelela in Bahi District; Mpunguzi, Mbabala, Zuzu, Nala, Hombolo, Chihanga, Ipala, Buigiri, Msalato, Nzuguni, Miyuji, Kizota, Mkonze, Mbalawala, Makole, Hazina, Uhuru, Chamwino, Kikuyu North, Kikuyu South, Dodoma Makulu, Kilimani, Tambuka Reli, and Makutupora in Dodoma Municipal; Makang’wa, Mvumi Mission, Mvumi Makulu, Mlowa Bwawani and Iringa Mvumi in Chamwino District. There are some wards originally included in this zone that should be removed and put into Dodoma urban because they are more urban in nature. These include: Kizota, Msalato, Nzuguni, Makole, Miyuji, Hazina, Uhuru, Chamwino, Kikuyu North, Kikuyu South, Dodoma Makulu, Klimani and Tambuka Reli. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 2 Households cultivate bulrush millet, sorghum and maize, with bulrush millet (a relatively successful drought- resistant crop) the most important of the cereal crops for home consumption. Bambara nuts and groundnuts are the main pulses grown for food, and they are grown just as importantly for sale as for consumption. Sesame and sunflowers are two other crops grown principally for sale, but also consumed in small amounts. Grapes, the main cash crop, are grown only by the upper two wealth groups, but they provide an important source of cash, indirectly, to poorer households, who get hired within the vineyards to help prune, spray and harvest. Oxen are used widely for ploughing. Some at the upper end also use tractors, and poorer households use hand hoes when they are unable to get access (through labour exchange) to plough oxen. Most households do not use improved seeds or industrial fertilizers and pesticides. However, middle and better off households do buy pesticides for use in their vineyards, and they may use animal manure to fertilise their fields. The peak agricultural labour period is from December through March, corresponding to planting and weeding periods; but other times of year are also busy. Extra labour is required in the vineyards for land preparation, pruning, spraying and harvesting; and it is also needed for land preparation, harvesting and threshing of the food and oil crops, in addition to planting and weeding. Middle and better off households hire members of very poor and poor households to work for them during the labour-intensive times of the year. This provides the most important source of cash for poorer households, who could not survive without this seasonal work. It also provides essential labour for middle and better off households, without which they could not produce their surplus crops. Livestock is also a vital source of cash (and a minor source of food) for some. Cattle, goats, sheep and chickens are raised. All of these animals are sold live throughout the year when cash is needed and milk from cattle is sold for cash and consumed at home. Chickens are the only animals owned by all wealth groups; very poor households do not own cattle, goats or sheep. All livestock graze and/or browse freely, and also eat crop residues at harvest time. None of the livestock are stall-fed. The main water sources for livestock during the wet season are seasonal rivers, open wells, boreholes, seasonal ponds and dams. In the dry season, they turn to shallow wells and boreholes, and there is payment for tap water in some villages. In addition, the larger livestock are taken to areas in Morogoro, where pastures and water sources are more reliable. Men are usually in charge of taking care of the cattle; boys, and sometimes girls, are responsible for taking care of goats, sheep and calves. In addition to crop and livestock-related income, and – for poorer households – casual employment income, households earn cash through self-employment activities (such as firewood/charcoal sales for poorer households) and petty trade (such as prepared food sales for poorer households, or owning kiosks, renting out oxen, or boda boda for middle and better off households). The services in this zone are very basic. Access to water in this semi-arid zone is more limited here than in many other areas of the country. Open wells, shallow wells, boreholes, and seasonal ponds are the main sources of water. In some villages, payment for water is typical. Access to clean, potable water is not guaranteed throughout the zone. Health dispensaries are found at the ward centre, health centres are found at each division, and every district has a hospital; however, these are not always well-stocked or fully-staffed with qualified medical professionals. Primary schools are found in the villages and secondary schools are present in the ward centres. It is common for all households to send their children through primary school, and some (but not all) poorer households also send their children to secondary school; however, only middle and better off households are able to afford the extra costs of vocational schools or colleges. There is no electricity, so poorer households depend on kerosene lamps and battery-operated torches, whereas better off households also use solar panels. Households in all wealth groups have mobile phones, with better off households having multiple phones. There are no sources of credit, nor are there savings schemes available. There are no NGOs operating in this zone. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 3 Markets The transportation infrastructure in this livelihood zone is mixed. There are tarmac roads connecting the central market of Dodoma to Morogoro, to Iringa, to Singida and to Arusha via Kondoa. From all of these points it is possible to reach terminal markets like Kenya and Dar es Salaam. However, the many feeder roads that connect villages to Dodoma are made of dirt or marram, and most are in poor condition. They function adequately during the dry season, but in the wet season access becomes challenging. Inundation by seasonal streams during the wet season is a common occurrence, requiring long waiting periods until waters recede and vehicles are able to make their way through. Bridges are few and far between; most passages over rivers are not bridges at all, but cemented portions of the river bed. Nevertheless, the zone is well-connected to other urban centres and market access, once commodities reach Dodoma town, is good. Households sell a range of food and cash crops, as well as livestock. Maize, sorghum, bulrush millet, groundnuts, Bambara nuts and sesame are grown for both home consumption and sale. The cash income generated from sesame and pulses (groundnuts and Bambara nuts) is especially important, as discussed below in the section on ‘Sources of Cash Income’. Sunflowers and grapes are the main cash crops, grown almost exclusively for sale. Whereas the cereal crops are sold locally, rarely leaving the region, the other crops are exported to other regions. Traders purchase bulrush millet or maize at the farm gate and take it by truck to markets and stocking facilities in Dodoma and Dar es Salaam. Traders from village shops also go to farmsteads to buy maize or bulrush millet. Some farmers carry bulrush millet by bicycle or head-lots to ward markets (in Kiswahili known as minadas) or village shops. Most maize and bulrush millet farmers in the zone do not have storage facilities and must sell all bulrush millet or maize immediately after harvest. If local grain storage facilities were improved, many farmers would not need to sell their grain at a low price directly after harvest only to buy bulrush millet or maize later in the season at a high price. Sunflowers are transported to Dodoma and then on to Dar es Salaam and other regional centres for processing into oil. Sesame and groundnuts get exported to Dar es Salaam and then on to distant markets in Asia. Some groundnuts are also destined for Nairobi. Groundnuts are sold from April to August; sesame and sunflowers have a more limited window of sale, from June to August. Grapes have a number of different terminal points: some are used within Dodoma Region for wine production; some are sent via Dodoma to Dar es Salaam as fruit for direct consumption; others are transported via Dodoma to Arusha and then on to Kenya for both consumption and wine production. The two periods of peak grape sales are February to March and August to September. The first period coincides with the rainy season, when road access is often compromised, which means some grapes never make it to market before rotting. Cattle, goats and sheep are sold to traders at mobile markets within the zone, from where they get transported to Dodoma and then on to Dar es Salaam. Chickens are sold locally. Sales occur throughout the year, when people need extra cash for school fees, medical expenses, festivals, or unexpected emergencies. However, peak sales are from January through March, the lean season, when most households need extra cash to purchase food; and in the harvest season, from June through August, when livestock prices are high after animals have been fattened on crop residues. (See ‘Seasonal Calendar’ section, below.) Poorer households buy maize grain, the cheapest staple, to cover their needs for two to three months of the year (December through February), even in relatively good production years. Most maize is sourced from Iringa and sold through the Dodoma market. Rice, purchased by middle and better off households, comes from Shinyanga and Morogoro to the Dodoma market. The labour market is mostly local and consists of seasonal agricultural labour. There is also a small demand from local towns and some seasonal employment is found outside the livelihood zone. It was estimated that in the reference year, 80% of seasonal labour was found within the zone on local farms. An additional 15% of the casual employment opportunities were from local towns, and the other 5% came from outside the livelihood zone, mainly from Kongwa (in Dodoma), Kiteto (in Manyara), Mvomero and Kilosa (both in Morogoro) and Kilindi (in Tanga). The balance shifts in bad years, with more people traveling to local towns Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 4 or to areas outside the zone to find work, especially from December to February. There is no labour migration into this zone. Timeline and Reference Year The baseline assessment refers to a very specific time period called the reference year. In the Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone the reference year covered the consumption period from April 2014 to March 2015. The production year starts with the planting season in November/December and ends with the harvest in April through July of the following calendar year. Thus, the 2014-2015 consumption year corresponds to the production year that starts with the 2013-2014 agricultural season. During community leader interviews, informants were asked to rank the last five production years in terms of seasonal performance with ‘1’ indicating a poor season and ‘5’ an excellent season. The table below summarizes the responses of the community leaders. The production year of 2013-2014, which corresponds to the consumption year of 2014-2015, was considered an above average year. In the past 5 years, there have been 2 average or above average years; 2 slightly below average years; and 1 well-below average year. The baseline information presented in this profile, therefore, provides a view into how households in this livelihood zone make ends meet in an above-average year. Production Year Season Rank Critical Events 2014-2015 Masika 1.4 Poor rainfall distribution, low crop yields, poor pastures, high staple food prices, low livestock prices, higher livestock mortality; unusual migration of livestock; food aid was distributed; extra livestock sales; more charcoal sales. 2013-2014 Masika 3.7 Good rainfall distribution; good crop yields; good pastures; low staple food prices; good livestock prices. 2012-2013 Masika 3.1 Average rainfall distribution; average crop harvests; average pastures; average food prices; average livestock prices. 2011-2012 Masika 2.4 Average rainfall distribution, below average crop yields; average pastures; average staple food prices; average livestock prices. 2010-2011 Masika 2.5 Average rainfall distribution; average crop harvests; average pastures; average food prices; average livestock prices. 5 = an excellent season for household food security (e.g. due to good rains, good prices, good crop yields, etc.) 4 = a good season or above average season for household food security 3 = an average season in terms of household food security 2 = a below average season for household food security 1 = a poor season (e.g. due to drought, flooding, livestock disease, pest attack) for household food security Seasonal Calendar for Reference Year There is one long rainy season in this zone, starting in December and lasting partway through April. Agricultural activities are linked to the timing of the rains, but because irrigation is also used in the vineyards, households here are occupied year-round with different crop-based and livestock-rearing activities. Land preparation starts in September – a full two months before the planting period – as the cereal and oilseed crops are all planted in November and December, with some planting extending into the beginning of January. Sorghum, maize and groundnuts are inter-cropped, while Bambara nuts, grapes, sesame, sunflower and bulrush millet are grown as single stands. From late December through March, people are busy with weeding. The main harvests occur in May and last through July; however, sesame is harvested as early as March; and part of the maize, groundnut and Bambara nut harvests are eaten green, beginning mid-way through March. Grapes are harvested twice a year, once in March and once in August/September. A period of threshing (where applicable) and sales follows the harvest of each crop. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 5 The graph to the right shows average monthly rainfall (mm) in Dodoma District based on a 35-year period (1980-2014). Source: TZ Meteorology Department The peak agricultural labour period is from December through March, corresponding to planting and weeding of the cereal and oil seed crops; but that does not mean that the other times of year are not busy. Extra labour is required in the vineyards almost year-round for land preparation, pruning, spraying and harvesting; and it is also needed for the land preparation, harvesting and threshing of food and oil crops. Middle and better off households cultivate large areas of land, which they cannot manage without extra help. They hire members of very poor and poor households to work for them during these labour-intensive times of the year. Thus, poorer households are busy working for others while, at the same time, tending to their own fields. The ultimate result Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 6 is that poorer households have lower yields due to less-intensive management on their own fields during critical management times. One reason that poorer households seek work off their own farms is that they run out of their own food stocks from the previous year’s harvest before the next harvest is available. This means they need to buy a good bit of their food every year, and they need cash to do that. Local agricultural labour offers them the best means for earning cash without having to migrate away from the villages. Very poor households can deplete their stocks as early as December, but by February and March (the lean season) almost all households in the lower two wealth groups are buying food. Thus, the paid work for weeding helps provide needed cash, allowing them to bridge the gap until mid-March or April, when green harvests are available. Unfortunately, this is also a time of year when human diseases, and especially malaria, peaks. The most important livelihood capital that poorer households have is their own labour, so when an active labourer is sick in a poor household, income for this household is lost. Because the months of peak human illness coincide with one of the peak labour periods, it can be especially damaging for a productive household member to be sick at this time. Protecting the health and well-being of poorer households goes hand in hand with protecting their income. People in this zone are not only busy with cropping activities, but also with livestock-related work. Milk sales peak from January through March (as pastures and water sources regenerate with the rains) and again from June through August (as livestock benefit from harvest residues). Milking animals is a time-consuming task, competing with the demands of weeding and harvesting in these months, but it brings with it the reward of extra nutrition for the household and cash income from milk that is sold. These same two periods (January through March and June through August) are when livestock sales are highest. In January through March, livestock are sold (by poorer households) in response to the need for cash to pay for food during the lean season, and (for middle and better off households) to cover the cost of hiring labour during the agricultural season. The June to August period of peak sales corresponds to the fact that livestock are in good condition at this time and garner high prices, and this is also when middle and better off households are putting aside cash for the coming agricultural season. In September, as the dry season deepens, livestock are taken to areas in Morogoro, where pasture and water sources are more reliable, returning to the villages in January or February. Those without livestock are busy with other activities in the dry season, especially collecting and selling firewood. Wild foods are also available at this time. Petty trade peaks in the harvest months, with some households transporting and re-selling local commodities, and others transporting goods into the zone for sale to local households that have new cash from crop sales. The festival season also takes place at this time, when the proceeds from the harvest are available to spend, and before the intensive work of the coming agricultural season has kicked into high gear. Wealth Breakdown The main determinants of wealth in this zone are, first, the amount of land a household cultivates and, second, the number of livestock - particularly oxen and cattle – it owns. In important ways these two things are inter- related: ownership of oxen allows people to increase the area they cultivate; and bigger herds generate more cash, which enables people hire labourers to carry out the many tasks associated with having more land. On the other side, the more land a household has under cultivation, the larger its harvests; and with more crop production, a household is able to generate proceeds from crop sales that can be invested in the health and growth of its livestock herd. Additional factors that determine how much land a household cultivates include the amount of land they own, the intra-household labour they have on hand, and their ability to hire additional help. Typical better off households own around 12-28 acres of land and cultivate 10-16 acres of these, using several teams of their own oxen for ploughing, or tractors in some cases. They also hire seasonal agricultural labourers. Better off households have more livestock than other households, usually keeping a herd of around 4-6 oxen, 25- 40 cattle, 15-35 goats and 0-15 sheep, alongside 15-25 chickens. Their household sizes are a little bigger than the other wealth groups. These households also own other assets, such as 1-3 ox-ploughs, an ox cart, a bicycle or two, Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 7 and possibly a motorcycle for boda boda. They typically own several cell phones, which are used to gather price and market information as well as to keep in touch with far-away relatives. Typical very poor households, on the other hand, own around 3-5 acres and cultivate only 2-3 acres, usually by hand, although they may exchange labour for access to plough oxen from better off households. They do not produce enough in any year to cover all of their food and cash needs. Very poor households have no livestock at all, except for 2-12 chickens. They have around 5-7 household members and face many competing labour requirements during the cropping season, because they need to work in both their own fields and in the fields of middle and better off households, where they earn cash that is critical to their survival. These households do not have any additional assets other than, possibly, a cell phone and a bicycle, but many do not even have these. Note: The percentage of household figures represent the mid-point of a range. Another distinction between the wealth groups is that middle and better off households grow grapes, whereas very poor and poor households do not, lacking the financial means to invest in the inputs and labour required to manage successful vineyards. In addition, the upper two wealth groups grow more sesame and sunflower, the other main cash crops, and they hire people to work for them, whereas the lower two wealth groups are the hired labourers. The distribution of wealth in this zone is weighted towards the bottom. Very poor (20-38%) and poor (25-35%) households together make up around 45-70% of households in the zone. Middle (20-35%) and better off (10-20%) households combined represent around 30-55% of the households. Sources of Food The graph below presents the sources of food for households in different wealth groups in the livelihood zone for the period April 2014 to March 2015. April represents the start of the consumption year because it is when people begin to harvest green maize and it marks the end of the hunger period. Food is presented as a percentage of 2100 kcal per person per day for the 12-month period. This was considered an above-average year, with good rains, good crop yields, and low staple food prices. There are two main sources of food in this livelihood zone, and two supplemental sources: own crops and purchased food make up the majority of calories, while those in the upper two wealth groups also benefitted from their own milk and meat; and all households received a small amount of food aid. As you move up the wealth spectrum, reliance on own crops increases and the importance of the market decreases. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 8 Own crops covered 44-95% of minimum calorie needs in the reference year, increasing with wealth. In this lowland, semi-arid zone, maize is not the primary food crop; a more drought-tolerant crop – bulrush millet – is. Alongside maize and bulrush millet, households grow sorghum, groundnuts, Bambara nuts, and sunflower. Bulrush millet provides the most calories of any single crop, accounting for 20-44% of minimum food needs in the reference year. Maize, on the other hand, contributed 15-25% of minimum calories (including eaten green). In the graph, food access is expressed as a percentage of minimum food requirements, taken as an average food energy intake of 2100 kcals per person per day. The other crops, which were mainly pulses, made up 8-14% of reference year food needs. Taking a closer look at production, typical very poor, poor, middle and better off households produced around 400 kg, 630 kg, 750 kg and 1,240 kg of bulrush millet, respectively, in the reference year; along with 150 kg, 400 kg, 500 kg and 840 kg of maize; 40 kg, 120 kg, 330 kg and 450 kg of sorghum; 80 kg, 140 kg, 210 kg and 300 kg of groundnuts; 50 kg, 100 kg, 130 kg and 150 kg of Bambara nuts; as well as 65 kg, 80 kg, 320 kg and 500 kg of sesame, all respectively. In the reference year, households sold a sizeable portion of all of these crops, but if they had consumed, rather than sold, all of their maize, sorghum, groundnuts, bulrush millet and Bambara nuts, all but the very poor group would have been able to cover their minimum calorie requirements. In fact, in pure calorie terms, these crops could be converted into 60%, 108%, 150% and 205% of minimum calorie needs for very poor, poor, middle and better off households, respectively. The point here is not that households should not have sold their crops: crop sales offer a necessary means for generating the cash required to cover a range of essential goods and services. But it is important to note that households in the top two categories are able to produce substantially more than those in the bottom two categories, and this has implications for their ability to survive in bad years. Even if half of their crop production is wiped out in a bad year, better off households still have enough to cover their minimum needs, whereas very poor households would be left with a deficit of over 70% of minimum calories. It also explains differences in what these households purchased in the reference year, as discussed below. Purchased food accounts for most of the remaining calories consumed by all households in the reference year, covering 20-52% of minimum calorie requirements, decreasing with wealth. The poorer two wealth groups purchased mostly maize grain and bulrush millet, the cheapest staples. Purchased maize grain and bulrush millet together accounted for around 44% of minimum calories (for typical very poor households) and 32% of minimum calories (for poor households) in the reference year, or over three-quarters of their purchased calories. Middle households, on the other hand, purchased only around 4% of their minimum calories in the form of maize grain and no millet; and better off households purchased no maize or millet at all. For middle and better off households, the ‘purchase’ component was comprised of more high-value, preferred foods, such as wheat flour, rice, beans, sugar, meat, oil and dried fish. Thus, almost the entire value of their purchased calories came from high-value preferred foods. By comparison, very poor and poor households purchased only around 8% of their minimum calories in the form of these higher-value food items, and did not buy meat or wheat flour in meaningful amounts. The final two sources of food are own milk/meat and food aid. Only middle and better off households obtain significant quantities of milk and meat from their livestock. In the reference year a typical middle household had around 4 cows milking, and better off households had around 6 cows milking. Milk yields vary over the year, reaching their peak of around 1.75 litres per day in the rainy season, and dropping off to around 0.5 litres per day in the dry season. Given this variation and the period of time that cows here continue to lactate, households obtained a total of around 1,085-1,630 litres over the year. Approximately 45-50% of the milk got sold, leaving middle and poor households with enough to cover 6-8% of their minimum calorie needs in the reference year. An Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 9 additional 3% or so of minimum calories accrued to better off households in the form of meat from slaughtered cattle and goats. While only the upper two wealth groups benefitted from milk (and meat), all households who sent their children to school received some help in the form of school feeding, shown as ‘food aid’ on the graph. Most households have at least 1 child attending school, and this household member was fed one meal a day during the school term, helping to add to the required calories for the household in the reference year. Sources of Cash Income The graphs to the right present an accounting of cash income sources for all four wealth groups in the reference year, first in terms of absolute values, and next as a proportion of annual cash income. It is immediately clear that households in the upper two wealth groups have a very different income profile from those in the bottom two wealth groups. Although ‘grapes’ is in the title of this zone, the income from this source only benefits middle and better off households directly. The land, labour and pesticides required to grow a successful crop of grapes puts this crop out of reach for very poor and poor households. The other major difference is that middle and better off households round out their cash income with livestock- related income, relying on milk sales and live animal sales to meet almost all of the rest of their needs. Poorer households, on the other hand, do not have enough livestock to make this possible, and rely instead on casual labour and self- employment. Neither of these provide guaranteed income in any year, and both sources The graph provides a breakdown of total annual cash income in Tanzanian Shillings according to income source. The graph provides a breakdown of total annual cash income as a percent of annual cash income. INCOME SUMMARY TABLE (in Tanzanian Shillings) Wealth group Very poor Poor Middle Better off Annual income per household 4 900,000 – 1,400,000 1,400,000 – 2,500,000 2,500,000 – 5,500,000 5,500,000 – 7,500,000 4 The average exchange rate from April 2014 - March 2015 was 1 USD = 1,800 TZS Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 10 are linked to the surpluses held by those at the upper end of the wealth spectrum. Poor households also depend to a small extent on petty trade, as do middle and better off households, but the nature of this trade is different, as discussed below. In the reference year, the combined value of crop sales accounted for 19%, 27%, 50% and 51% of the annual cash income of typical very poor, poor, middle and better off households, respectively. Maize, sorghum, groundnuts, Bambara nuts, Bulrush millet, sunflower, and sesame are all sold, as well as grapes, the main cash crop. Sesame, Bambara nuts and groundnuts are the highest value crops, sold at around 850-1,500 TZS/kg in the reference year. The lower end of the range corresponds to the price that poorer households got for their groundnuts. Middle and better off households are able to get a higher price for their groundnuts (1,200 TZS/kg) because the quality of their produce is higher and they sell at more advantageous times of the year and/or to markets where they get a better price. The upper end of the range applies to sesame. Either way, these prices compare favourably with the cereal crops, which are valued at around 400-500 TZS/kg. Therefore, even small amounts of pulses and sesame can earn households a meaningful amount of cash. For example, in the reference year, typical middle and better off households sold 300-450 kg of sesame, 150-185 kg of groundnuts and 130-150 kg of Bambara nuts. The combined total for these three crops represented around 16-18% of annual cash income for the upper wealth groups. The poorer two wealth groups only sold 50-90 kg of groundnuts, 60-70 kg of sesame and 0-40 kg of Bambara nuts but still earned around 132,500-221,500 TZS, or approximately 10-13% of their annual cash from these relatively small quantities. Cereal crop sales (maize, sorghum and bulrush millet) contributed around 5-11% of annual cash income for all wealth groups. Sunflowers only earned households 2-4% of their annual cash. The real cash earner was grapes, but these were only grown by the top two wealth groups. Grape sales alone provided middle and better off households with 20-25% of their annual cash income. Better off households earned from grapes alone more than very poor households earned from all of the cash sources combined in the reference year. As a whole, better off households generated 13 times more from crop sales than very poor households, despite only having, on average, 5 times more land under cultivation. This is explained, at least in part, by the capacity of better off households to buy sufficient inputs and to apply timely management practices. Poorer households cannot afford to buy many inputs, and their labour pool is split during key times of the year, partly on their own farms and partly working for others, but never fully devoted to their own fields. The resulting difference in yields is apparent in these figures. For middle and better off households, livestock sales and livestock product sales (including milk, meat and eggs) are the next most important income earner, making up 40-45% of annual cash income; on the other hand, very poor and poor households only derived 3-14% of their annual cash from these sources. As discussed in the ‘Sources of Food’ section, middle and better off households both own milking cows. Around half of the milk produced in the reference year was sold. In addition, better off households sell eggs and meat. The total income from livestock product sales accounted for 10-15% of cash income for the two upper wealth groups. Poor households also sold a very small amount of milk, but this resulted in an insignificant amount of cash. More important than the livestock product sales were sales of live animals, which made up 25-35% of cash income for middle and better off households, and 3-13% of annual cash for very poor and poor households. Cattle, goats, chickens, and a few sheep, are sold. Cattle bring in the most cash per animal (at around 95,000-1,320,000 per head); in contrast goats are sold for around 40,000 TZS and chickens for 6,500-8,000. Better off households typically sold around 3 cattle, 6 goats, 1 sheep and 7 chickens in the reference year; very poor households only sold around 6 chickens. The other two wealth groups fell in between these two extremes. Casual labour is the most important source of income for very poor and poor households. In the reference year, this stream of earnings accounted for 60% of a typical very poor household’s annual cash income and 40-45% of poor households’ cash income. Middle and better off households cultivate more land than they can manage with their own household labour, so they hire members of these poorer households to help throughout the agricultural season. People are hired to prepare land, to plough, to plant, weed, harvest and thresh. The majority of the cash income is associated with pre-harvest tasks, which account for 60-70% of the agricultural labour income. It is important to keep in mind that this income, as critical as it is in an average year, shrinks in a bad year because Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 11 losses in production translate into losses in the demand for labour, especially for harvest and threshing labour. This leaves poorer households struggling to find ways to fill this large gap. The last source of cash income for very poor households is self-employment, which means, primarily firewood and charcoal sales. Both women and men from the poorer wealth groups engage in this activity, with women focusing more on firewood, and men focusing on charcoal burning and sale. July to October, the dry season, is when these sales are concentrated. The environmental damage that ensues from this cash income is of concern, especially as the population grows and especially given the large proportion of the population already depending on this income. Self-employment made up almost a fifth of the cash income of very poor households in the reference year. Poor, middle and better off households also engage in ‘petty trade’ to earn extra cash. This may take the form of prepared food sales (for poorer households), or sales of household items, which middle and better off households are able to buy in bulk; they set up kiosks in the villages and generate extra income through this business. Some also make money from boda boda, or motorcycle hire, which can be used to transport goods and people, or ox plough and/or ox cart hire. Expenditure Patterns The graph presents expenditure patterns for the reference year April 2014 to March 2015. While absolute expenditure increases with wealth in line with total cash income, the expenditure breakdown by percent in this graph shows the relative amount of income spent on different categories. As in other areas of the country, households need to spend cash on a range of goods and services throughout the year, including: staple and non-staple food, household items, productive inputs, social services, like schooling and health, clothing and other non- The graph provides a breakdown of total annual cash expenditure according to category of expenditure essential items, such as tobacco, cosmetics and festivals. As shown in the graph to the right, two common trends appear in this zone, mirroring the findings in other rural areas: first, the poorer you are, the more cash you have to spend on securing basic staple foods; second, the richer you are, the more money you need to spend on productive inputs. The fact that typical households here need to buy water sets this zone apart from many other rural areas of the country; and the relatively large amount of cash in the ‘other’ category is also notable. All wealth groups spend some of their available cash on staple foods, which includes (in this case) maize grain, millet, wheat and rice. In both absolute and relative terms, very poor households spent more than the other wealth groups on staple foods. In the reference year, very poor and poor households spent around 16-26% of their annual cash on staple foods; and middle and better off households spent only 3-4%. The make-up of the staple food basket is not the same for all wealth groups. Typical very poor and poor households spent a total of 265,000-340,000 TZS on staple food, and 220,000-305,000 TZS (or 80-90%) of this was on maize grain and millet, the cheapest staples. Middle and better off households spent around 160,000-180,000 TZS, respectively, on staple foods, but only middle households spent a small amount on maize grain and neither bought millet at all. They spent money on rice, first, which is a preferred food, and better off households also bought a small amount of wheat flour. Thus, middle and better off households did not need to buy staple grains to fill a calorie gap; but rather to fill a preference gap. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 12 Although middle and better off households spent much less in both absolute and relative terms on staple food, on non-staple foods, they spent 2 ½ to 3 ½ times more in absolute terms than very poor households. The non-staple food category included beans, sugar, meat, oil, dried fish, and vegetables. Of these, the lower two groups spent the most on beans, dried fish, and oil, supplementing their heavily grain-based diet with proteins and fats. They spent the least on vegetables. Middle and better off households spent the most on meat and sugar. In the reference year, the proportion of cash income spent on non-staple foods was around 16% for very poor and poor households, and around 11-12% for middle and better off households. The calories purchase for this expenditure (in relation to minimum calories required for the year) were 6-8% (for very poor and poor households) and 13-15% (for middle and better off households). Thus, middle and better off households are able to buy a more nutritious and diverse diet than the other wealth groups, even though in relative terms they spend less than the other two wealth groups. In the reference year, middle and better off households both spent the largest portion of their annual cash income on productive inputs, as represented by the dark blue bar in the graph. In proportional terms, their spending on productive inputs (37-41% of annual expenditure) is larger than any other wealth group spends on any of the other categories. The following are included in this category: livestock drugs, seeds/tools, pesticides/fertiliser, livestock purchases, labour hire, business investment, phone credit and house repairs. Within this set, very poor households spent money only on seeds/tools and phone credit, with the most spent on phone credit. Poor households, in addition to these two categories, spent on money on livestock drugs. Middle and better off households spent money on all items within the category (with the exception of business investment, which only applies to better off households). The majority of their inputs budget was devoted to labour hire (47-57% of their inputs budget), followed by livestock purchase (15-19% of their inputs budget). Collectively, seeds, tools, pesticides and fertilisers comprised only around 11-12% of their inputs budget. In absolute terms, better off households spent 44 times more on productive inputs than very poor households, 17 times more than poor households, and 1 ½ times more than middle households. The ‘hh items’ category (in yellow) includes basic household necessities, such as tea, salt, soap, lighting (such as batteries, solar lamps solar panels, etc.), grinding services, firewood and utensils. These are items that households usually pay for in incremental amounts on a week-by-week basis. Within this category, very poor and poor households spent the most money on grinding, which took up around a quarter to a third of this budget, followed by payment for lighting. Middle and better off households spent the most on utensils, followed by lighting and soap. All households spent the least on salt and tea. On an annual basis, spending on basic household goods made up 7-13% of annual expenditure. Somewhat unusually, households in this zone also needed to spend money regularly on water, especially during the dry season, highlighting the particularly poor access people have to fresh, potable water. ‘Social services’, shown in orange on the graph, includes schooling and health costs. In the reference year, households spent 8-11% of their annual cash on these services. Schooling expenses included school fees, uniforms, stationery and transportation, where relevant. On a per capita basis, holding household size constant, better off households spent around 25% more than middle households and around 2-3 times more than poor and very poor households on schooling. In addition, better off households spent up to 11 times more on health care than very poor households on a per capita basis, indicating that these households may have had access to better clinics and private hospitals. Spending on clothes and other miscellaneous items are the last two categories included here. Spending on clothes accounted for 3-5% of the annual budget for all households. The ‘other’ category includes things like cosmetics, hair, beer, tobacco, cigarettes, community obligations, transportation and festivals; in the reference year households devoted 24-26% of their cash to these items. This is discretionary spending that can be reduced or redirected in bad years to buy more essential items if necessary. In both absolute are relative terms, those in the upper three wealth groups had the most available in this discretionary budget (better off households had 6 times more in this category than very poor households); and because the reference year was an above average year, even the very poor wealth group had more in this budget than it would in a bad year. In fact, this discretionary Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 13 budget, in relative terms, is larger than in most other zones, which is related to the fact that in many other zones the reference year was average, not above average. Hazards Three hazards affect this zone on a regular basis. The first is poor rainfall distribution. All the food crops in this zone are rain-fed; only grapes benefit from irrigation. Crops require an even, reliable distribution of rain to perform well. When too much or not enough rain falls during critical development periods, especially the vegetative and reproductive stages, yields can drop dramatically. Thus even if overall seasonal precipitation is normal, poor distribution can cause crop losses of 50-60%. The second chronic hazard is crop and livestock pests and diseases. Quelea quelea birds are especially problematic, damaging both the sorghum and bulrush millet crops. Army worm, which affects all cereal crops, and fungal diseases, which affect grapes, also reduce yields on a regular basis. The most commonly-occurring livestock diseases are contagious bovine pleuropneumonia (CBPP) for cattle, caprine pleuropneumonia (CCPP) for goats, and Foot and Mouth Disease (FMD). Newcastle Disease is also common and can wipe out an entire flock of chicken. Livestock diseases reduce the value of animals, lowering income levels, while at the same time increasing expenditure requirements related to livestock drugs. In the worst case, animals die, reducing the productive asset holdings of a household. The third chronic hazard is human diseases, especially malaria and typhoid fever. Because household labour is so critical to income generation, especially for poorer households, having a household member sick at a critical time of year can translate into significant drops in income, while at the same time increasing the medical expenditure requirements. The main periodic hazards are drought, which can seriously damage crop production once every three years. Droughts result in a series of inter-related shocks, such as rapid increases in staple food prices, declines in livestock production, reduced labour income and reduced returns on self-employment. Floods occur once every three years as well. Floods can damage standing crops and wash away roads, making it difficult for people to reach markets, and usually causing a spike in staple food prices. Less of a hazard, and more of a structural constraint, poor marketing infrastructure means that households are selling their agricultural commodities are prices that barely cover their production costs. Response Strategies In response to hazards and years with bad production, households attempt to meet their minimum food needs and cash requirements through a number of strategies. These strategies are detailed for this livelihood zone below: All households try to reduce expenditure on non-essential or more expensive items first, buying less sugar and rice, for instance, and using that money to buy the cheaper staple instead, or cutting down on festivals, tobacco and beer. Very poor and poor households try to increase cash income through finding more agricultural labour and casual employment, either locally or migrating outside the zone. In particular, people may go to Kongwa in Dodoma, Kiteto in Manyara, Mvomero and Kilosa districts in Morogoro, and Kilindi in Tanga. The expandability of this option is limited in bad years because the labour market gets saturated as more and more people look for work. This puts a downward pressure on wages so that even if people do find more days of work, they may earn less per day, making it hard to substantially increase cash income above normal year levels. This problem is somewhat mitigated if the bad year is localised. All households also try to increase their self-employment income. Poorer households try to increase cash income from charcoal and firewood sales. However, as more and more households try to do the same thing in a bad year, the value of each bundle of wood or charcoal decreases, which makes it difficult to expand this source of income substantially. The environmental damage that accumulates from this pursuit should be a cause for serious concern. Middle and better off households try to increase income from petty trade. Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 14 Middle and better off households also try to increase their livestock sales. However, the value of livestock tends to drop in bad years, both because supplies increase as more people try to earn cash in the same way, and because their body condition deteriorates as grazing and water resources decline. Key Parameters for Monitoring The key parameters listed in the table below are food and income sources that make a substantial contribution to the household economy in the Dodoma Lowlands Cereals, Oilseeds & Grapes Livelihood Zone. These should be monitored to indicate potential losses or gains to local household economies, either through on-going monitoring systems or through periodic assessments. It is also important to monitor the prices of key items on the expenditure side, including staple and non-staple food items. Item Key Parameter - Quantity Key Parameter – Price Crops Maize – amount produced Sorghum – amount produced Groundnuts – amount produced Sunflower – amount produced Sesame – amount produced Bulrush millet – amount produced Bambara nut – amount produced Grapes – amount produced Maize– producer price Sorghum – producer price Groundnuts – producer price Sunflower – producer price Sesame – producer price Bulrush millet – producer price Bambara nut – producer price Grapes – producer price Livestock production Cows’ milk – yields Meat – amount sold Cattle – herd size Goats – herd size Chickens - numbers Cows’ milk – producer price Meat – producer price Cattle – producer price Goats – producer price Chickens – producer price Other food and cash income Agricultural labour (land preparation, planting, weeding) – number of jobs Agricultural labour (harvesting) – number of jobs Bricks – numbers produced Firewood/charcoal – amount sold Petty trade – volume of trade Agricultural wage rates (land preparation, planting, weeding) Agricultural labour rates (harvesting) Bricks – price per brick Firewood/charcoal – price per bundle Petty trade – returns on trade Expenditure Maize grain – consumer price Rice – consumer price Programme Implications The longer-term programme implications suggested below include those that were highlighted by the wealth group interviewees themselves and those made by the assessment team following detailed discussions and observations in the field. All of these suggestions require further detailed feasibility studies. Very poor/poor households Provision of health services at village level, including building dispensaries and providing qualified health professionals and sufficient and affordable supplies of medicines Improved maintenance of existing road networks Timely and affordable provision of crop and livestock inputs Access to safe and sufficient water at all times of year Provision of school buildings, qualified teachers and appropriate teaching materials for all children Dodoma Lowland Cereals, Oilseeds & Grapes Livelihood Zone Profile 15 Development of fair, standardised and efficient agricultural markets Construction of dam for irrigation Middle/better off households Timely and affordable provision of crop and livestock inputs Development of livestock health infrastructure, including affordable veterinary services and dip tanks, etc. Access to safe and sufficient water at all times of year Provision of school buildings, qualified teachers and appropriate teaching materials for all children Development of fair, standardised and efficient agricultural markets Provision of electricity at village level Construction of dam for irrigation | false |
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# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA WIZARA YA KILIMO Simu ya Upepo: “KILIMO” Dodoma Idara ya Utawala, Simu: +255 (026) 2321407 Mji wa Serikali - Mtumba, Nukushi: +255 (026) 2320037 S.L.P. 2182, Barua Pepe: [email protected] DODOMA. Tovuti: www.kilimo.go.tz TAARIFA KWA VYOMBO VYA HABARI SERIKALI YAPANGA KURASIMISHA BIASHARA YA MAZAO YA KILIMO NCHINI Dodoma, 14 Julai 2023 Waziri wa Kilimo, Mhe. Hussein Bashe (Mb) amefanya kikao cha pamoja na wafanyabiashara na wadau wanaouza mazao ya kilimo ndani na nje ya nchi kujadili mwenendo wa usafirishaji wa mazao, jitihada za Serikali katika kuondoa vikwazo vya biashara na urasimishaji wa biashara ya mazao ya kilimo. Waziri Bashe ameeleza kuwa takwimu zinaonesha mchango wa kilimo katika uchumi ni asilimia 26.1 ambapo mauzo ya mazao ya kilimo nje ya nchi yameongezeka kutoka Dola za Marekani milioni 994.5 mwaka 2021 hadi Dola za Marekani bilioni 1.38 kufikia Aprili 2023. Serikali imepanga kurasimisha biashara ya mazao ya kilimo ambapo malengo mahususi ya urasimishaji huo ni kuongeza thamani ya mazao ya kilimo ili kumlinda mkulima na mfanyabiashara wa ndani dhidi ya usumbufu na utapeli unaotokea katika biashara ya mazao ya kilimo. Aidha, Mhe. Bashe amesema kuwa Tanzania ina hali nzuri ya chakula kutokana na mavuno yaliyopatikana na kupelekea utoshelevu wa chakula kwa asilimia 114 . Vile vile, aliwakumbusha kauli ya Mhe. Dkt. Samia Suluhu Hassan, Rais wa Jamhuri ya Muungano wa Tanzania umuhimu wa nchi kulinda akiba ya chakula na kuwahasa wakulima kuuza ziada ya chakula popote pale duniani kwa kufuata utaratibu uliowekwa na Serikali. Mhe. Bashe amesema kuwa Serikali inawezesha NFRA kuhifadhi tani 3,000,000 ifikapo mwaka 2030 ikiwa sehemu ya kuimarisha usalama wa chakula na lishe. Hatua nyingine ni kuiongezea Wakala wa Taifa wa Uhifadhi wa Chakula (National Food Reserve Agency) uwezo wa kununua mazao ya wakulima ili kuongeza hifadhi hadi kufikia tani 500,000 na kwa msimu huu Mhe. Bashe ameagiza Wakala wa Taifa wa Hifadhi ya Chakula kununua mahindi kwa shilingi 1,000 kwa kilo kwa mkulima yeyote anayetaka kuwauzia NFRA ofisi za Dodoma. Kuhusu jitihada za kurahisisha usajili wa ghala za Sekta ya Umma, Sekta Binafsi na Vyama vya Ushirika, Serikali imebuni mfumo wa kidijitali unaoitwa Crop Stock Dynamics System. Vile vile, Mhe. Bashe amewaahidi wafanyabiashara kuwa ataimarisha mfumo wa kidigitali wa upatikanaji wa vibali kwa njia ya mtandao ili wafanyabiashara wapate vibali kwa urahisi. Waziri Bashe ameongeza kuwa Tanzania imekuwa katika maandalizi ya kuwa mwenyeji wa Mkutano wa Mifumo ya Chakula Afrika - 2023 (Africa’s Food Systems Forum), ambao ni sehemu ya hatua za kuimarisha usalama wa chakula. Mkutano huo umepangwa kufanyika tarehe 5 hadi 8 Septemba 2023 na utahusisha wadau mbalimbali wa kilimo na biashara kutoka ndani ya nchi, wadau kutoka Jumuiya ya Maendeleo Kusini mwa Afrika (SADC) na Jumuiya ya Afrika Mashariki (EAC). Imetolewa na: Kitengo cha Mawasiliano Serikalini | false |
# Extracted Content 1 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO YA CHAKULA 21 - 25 Juni, 2021 Jedwali1: Wastani wa bei za jumla kitaifa (TZS/ Kilo100) Jedwali 2: Wastani wa bei za jumla za mahindi kwa wiki (TZS/kilo 100) Mazao Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Mahindi 43,100 42,122 43,000 ▲2 Mchele 135,240 133,500 136,260 ▲2 Mtama 97,070 98,469 94,500 ▼4 Maharage 175,700 173,684 174,150 ►0 Viazi mviringo 69,500 70.647 67,800 ▼4 Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 44,000 44,000 46,500 ▲6 Dar - Kinondoni 42,500 42,500 42,500 ►0 Dodoma (Majengo) 50,000 53,500 51,500 ▼4 Bukoba 47,500 46,500 46,500 ►0 Babati 39,000 40,500 40,500 ►0 Musoma 52,500 52,500 52,500 ►0 Morogoro 46,297 46,297 46,297 ►0 Mpanda 30,000 30,000 30,000 ►0 Mtwara DC 40,000 40,000 40,000 ►0 Mwanza 50,000 50,000 56,500 ▲13 Sumbawanga 33,000 31,500 31,500 ►0 Shinyanga 45,000 42,500 45,000 ▲6 Songea 45,000 35,000 36,500 ▲4 Tabora 36,000 36,000 36,000 ►0 Tanga/Mgandini 43,518 43,518 48,570 ▲2 Ujumbe Mkuu ✓ Wastani wa bei kitaifa umebadilika kwa viwango tofauti tofauti. Bei za mahindi na mchele zimeongezeka kwa asilimia 2, bei za maharage hazijabadilika, wakati bei mtama na viazi mviringo zimepungua kwa asilimia 4. ✓ Mboga na Matunda (Horticulture): Bei katika masoko mbalimbali nchini zimebadilika kwa viwango tofauti. Bei za nanasi, na vitunguu zimeongezeka kwa asilimia 1, wakati bei za tikiti maji, pilipili hoho na tango, zimepungua kwa asilimia 5, 3 na 2 mtawalia. ✓ Tumbaku: Hadi kufikia tarehe 20 Juni, 2021 kiasi cha tumbaku kilichouzwa ni Kilo 29,122,687 zenye thamani ya Dola za Kimarekeni za 44,633,382. ✓ Kahawa: Hadi kufikia tarehe 27 Mei, 2021 kahawa iliyouzwa kwa msimu wa mauzo 2020/21 ni tani 70,043 zenye thamani ya Dola za Kimarekani milioni 137.6. ✓ Ufuta: Hadi kufikia tarehe 24 Juni, 2021 ufuta uliouzwa kwa msimu wa mauzo 2021/22 ni Kilo 19,741,410 zenye thamani ya shilingi 45,632,860,313. 2 Jedwali 3. Wastani wa bei za jumla za mchele kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 152,500 152,500 152,500 ►0 Dar – Kinondoni 150,000 150,000 140,000 ▼7 Dar – Ilala 170,000 170,000 170,000 ►0 D'Salaam – Tandika 150,000 150,000 150,000 ►0 Dodoma (Majengo) 162,500 160,000 165,000 ▲3 Bukoba 129,000 129,000 129,000 ►0 Babati 150,000 145,000 145,000 ►0 Morogoro 125,000 125,000 125,000 ►0 Mwanza 132,500 132,500 180,000 ▲36 Sumbawanga 100,000 100,000 105,000 ▲5 Shinyanga 105,000 105,000 105,000 ►0 Songea 165,000 170,000 175,000 ▲3 Tabora 110,000 110,000 110,000 ►0 Tanga/Mgadini 135,000 135,000 135,000 ►0 Jedwali 4. Wastani wa bei za jumla za mtama kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 72,500 72,500 72,500 ►0 Dar - Kinondoni 90,000 90,000 70,000 ▼22 Dar - Ilala 85,000 85,000 85,000 ►0 D'Salaam – Tandika 95,000 95,000 95,000 ►0 Dodoma (Majengo) 51,000 65,500 65,000 ▼1 Bukoba 135,000 135,000 135,000 ►0 Babati 70,000 70,000 70,000 ►0 Morogoro 150,000 150,000 150,000 ►0 Mpanda 82,500 82,500 82,500 ►0 Mtwara DC 95,000 95,000 95,000 ►0 Mwanza 165,000 165,000 165,000 ►0 Shinyanga 82,500 82,500 65,000 ▼21 Tabora 145,000 145,000 145,000 ►0 Tanga/Mgandini 90,000 90,000 85,000 ▼4 Jedwali 5. Wastani wa bei za jumla za maharage kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07- 11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 152,500 155,000 152,500 ▼2 Dar – Kinondoni 210,000 210,000 210,000 ►0 Dar – Ilala 210,000 210,000 210,000 ►0 D'Salaam – Tandika 205,000 205,000 205,000 ►0 Dodoma (Majengo) 195,000 210,000 211,500 ▲1 Bukoba 132,500 132,500 130,000 ▼2 Babati 165,000 165,000 165,000 ►0 Morogoro 187,500 187,500 187,500 ►0 Mpanda 175,000 175,000 175,000 ►0 Mtwara DC 177,500 177,500 175,000 ▼1 Sumbawanga 97,500 97,500 132,500 ▲36 Shinyanga 175,000 175,000 175,000 ►0 Songea 180,000 170,000 190,000 ▲12 Tabora 185,000 185,000 185,000 ►0 Tanga/Mgandini 185,000 185,000 175,000 ▼5 Jedwali 6. Wastani wa bei za jumla za viazi mviringo kwa wiki (TZS/Kilo 100) Soko Wiki ya nyuma (07-11 Juni, 2021) Wiki iliyopita (14 -18 Juni, 2021) Wiki hii (21-25 Juni, 2021) Badiliko Wiki iliyopita vs wiki hii (%) Arusha (Urban) 75,000 75,000 75,000 ►0 Dar - Kinondoni 52,000 52,500 55,000 ▲5 Dar – Ilala 64,800 64,800 64,800 ►0 D'Salaam – Tandika 72,500 75,000 75,000 ►0 Dodoma (Majengo) 62,000 63,000 63,000 ►0 Babati 65,000 60,000 52,500 ▼13 Musoma 90,000 90,000 90,000 ►0 Morogoro 75,500 75,500 75,500 ►0 Mtwara DC 57,500 57,500 57,500 ►0 Mwanza 75,000 75,000 75,000 ►0 Sumbawanga 67,500 67,500 67,500 ►0 Songea 72,500 77,500 77,500 ►0 Tabora 72,500 72,500 67,500 ▼7 Tanga/Mgandini 59,000 56,500 56,500 ►0 3 Jedwali 7: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Uganda (bei za jumla) 1,824 1,955 489 512 Uganda (bei za rejareja) 1,955 2,281 847 912 Chanzo: https://farmgainafrica.org/ Tarehe 25 Juni, 2021 Jedwali 8A: Wastani wa bei za mazao ya horticulture kwa wiki ya tarehe (6-12) Mei, 2021 Zao Wiki ya nyuma (23-28 Aprili, 2021) Wiki iliyopita (30 Apr- 5 Mei, 2021) Wiki hii (6-12 Mei, 2021) Badiliko wiki iliyopita na wiki hii (%) Nyanya (40 Kg kreti) 53,475 45,913 45,437 ▼1 Vitunguu (100 Kg Gunia) 153,200 176,714 177,902 ▲1 Tikiti maji (Kilo) 539 551 523 ▼5 Nanasi (Kilo) 729 762 770 ▲1 Pilipili hoho (50 Kg Gunia) 53,770 56,945 55,070 ▼3 Tango (100 Kg Gunia) 72,806 73,513 72,015 ▼2 Chanzo: TAHA, 2021 Jedwali 8B: Bei za mazao ya Horticulture katika masoko mbalimbali kwa wiki la tarehe (6-12) Mei, 2021 Soko Nyanya (40kg kreti) Vitunguu (100 Kg Gunia) Tikiti maji (Kilo) Nanasi (Kilo) Pilipili hoho (50 Kg Gunia) Tango (100 Kg Gunia) Nairobi 46,933 161,333 777 660 70,400 99,000 Mombasa 50,600 177,833 660 66,000 66,000 Zanzibar 70,000 250,000 767 800 108,333 73,333 Dar es salaam 45,000 190,000 350 400 91,667 90,000 Morogoro 38,667 168,333 417 1,000 41,667 69,667 Dodoma 48,333 150,000 317 533 38,889 66,667 Shinyanga 35,000 126,389 500 500 29,333 40,000 Mwanza 38,333 155,556 467 1,067 33,333 47,333 Arusha 40,000 220,000 550 517 50,833 70,000 Tanga 43,000 132,000 671 1,000 45,500 77,000 Lindi 45,000 210,000 500 567 40,000 56,667 Mtwara 50,000 208,333 500 600 75,000 75,000 Mbeya 46,000 147,500 690 1,500 49,333 125,000 Chanzo: TAHA, 2021 4 Jedwali 9A: Mauzo ya tumbaku katika msimu wa 2021/2022 hadi kufikia tarehe 20 Juni, 2021 kwa kampuni AINA YA TUMBAKU KAMPUNI KILO ZA MKATABA MASOKO YALIYOTHAMINISHWA MPAKA SASA (CUMMULATIVE) BELO KG THAMANI(USD) BEI YA WASITANI (USD/KG) (USD) VFC Alliance One Tobacco Tanzania Ltd 20,040,000 269,378 12,732,539 18,868,592 1.48 JTI Leaf Services Ltd 14,460,000 153,195 7,433,245 12,722,387 1.71 Premium Active Tanzania Ltd 16,000,000 83,479 4,076,237 6,149,241 1.51 Pachtec Company Ltd 4,461,838 43,888 2,024,662 2,832,423 1.40 Mo Green International Company Limited 2,800,000 5,377 255,084 359,362 1.41 Naile Leaf (T) Co. Ltd 2,535,000 27,295 1,230,743 1,869,755 1.52 Magefa Growers Ltd 4,400,000 20,198 927,521 1,218,853 1.31 Jespan Company Ltd 760,000 6,990 357,097 484,028 1.36 ENV Services Ltd 800,000 1,743 85,560 128,742 1.50 SUB TOTAL VFC 68,071,838 611,543 29,122,687 44,633,382 1.53 DFC Premium Active Tanzania Ltd 500,000 - - - GRAND TOTAL 68,571,838 611,543 29,122,687 44,633,382 1.53 Jedwali 9B: Mauzo ya tumbaku (kimkoa) katika msimu wa masoko 2021/2022 hadi kufikia tarehe 20 Juni, 2021 Mkoa Kilo za Mkataba Kiasi cha tumbaku kilichonunuliwa Belo Kilo Katavi 7,350,000 51,767 2,434,695 Mbeya 10,280,000 32,418 1,596,321 Songwe 670,000 4,108 209,278 Kigoma 4,705,000 46,454 2,225,923 Tabora 32,546,838 380,284 17,980,725 Shinyanga 9,930,000 83,260 3,981,547 Geita 1,070,000 10,858 546,263 Kagera 70,000 1,180 58,557 Iringa 200,000 1,214 89,377 Singida 1,250,000 Jumla ya VFC 68,071,838 611,543 29,122,687 Ruvuma (DFC) 500,000 JUMLA KUU (DFC+VFC) 68,571,838 611,543 29,122,687 5 Jedwali 10A: Mauzo ya kahawa kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 27 Mei, 2021 Mkoa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD Arabika laini 18,900,851 51,340,876 9,449,747 30,391,503.67 54,881 132,565.16 28,405,409 81,864,945.03 Arabika ngumu 145,527 291,691 2,143,620 3,453,241.00 16,620 15,972.00 2,305,767 3,760,903.98 Robusta 1,524,910 2,539,431 37,431,848 48,952,780.96 375,192 441,839.32 39,331,950 51,934,051.20 Jumla 20,571,288 54,171,998 49,025,215 82,797,525.63 446,623 590,376.48 70,043,126 137,559,900.21 Chanzo: Bodi ya Kahawa, 2021 Jedwali 10B: Mauzo ya kahawa (kimkoa) kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 27 Mei, 2021 Mkoa Mnada Soko la moja kwa moja Viwanda vya ndani Jumla Kilo USD Kilo USD Kilo USD Kilo USD KAGERA 1,631,070 2,739,386.60 39,426,488 52,098,305.96 391,812 457,811.32 41,449,370 55,295,503.88 SONGWE 6,859,673 18,411,063.41 2,710,804 7,948,200.71 - - 9,570,477 26,359,264.13 RUVUMA 8,688,220 23,073,124.19 3,480,035 10,028,372.23 10,076 28,618.80 12,178,331 33,130,115.22 MBEYA 1,754,341 5,219,692.24 576,889 1,749,402.94 29,963 74,742.56 2,361,193 7,043,837.75 KILIMANJARO 573,990 1,749,557.79 1,030,571 3,854,232.40 4,515 10,853.70 1,609,076 5,614,643.88 KIGOMA 476,042 1,288,566.78 230,143 661,727.00 - - 706,185 1,950,293.78 TANGA 122,241 317,481.42 - - - - 122,241 317,481.42 ARUSHA 361,727 1,108,443.28 1,355,255 5,956,817.25 10,257 18,350.10 1,727,239 7,083,610.63 IRINGA 21,210 50,225.82 - - - - 21,210 50,225.82 MANYARA 1,936 5,950.05 - - - - 1,936 5,950.05 MOROGORO 314 1,030.39 - - - - 314 1,030.39 MARA 39,367 91,735.30 147,060 298,116.00 - - 186,427 389,851.30 NJOMBE 41,157 115,740.83 67,970 202,351.13 - - 109,127 318,091.96 TOTAL 20,571,288 54,171,998.10 49,025,215 82,797,525.63 446,623 590,376.48 70,043,126 137,559,900.21 Chanzo: Bodi ya Kahawa, 2021 6 Jedwali 11: Mauzo ya ufuta kwa msimu wa 2021/22 hadi kufikia tarehe 24 Juni, 2021 NA HALMASHAURI MAKISIO KIASI (KG) THAMANI (TZS) 1 MTAMA (LINDI VIJIJINI) 8,000,000 4,305,358 9,912,231,853.00 2 LINDI MC 3,500,000 3,169,073 7,320,953,838.00 3 KILWA 19,000,000 6,743,479 15,617,491,613.00 4 NACHINGWEA 12,000,000 2,152,176 4,982,211,930.00 5 RUANGWA 13,000,000 2,289,082 5,293,607,396.00 6 LIWALE 13,000,000 1,082,242 2,506,363,683.00 JUMLA 68,500,000 19,741,410 45,632,860,313.00 Chanzo: Mrajisi Lindi Jedwali 12: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati mzuri wa kuvuna Wakati mbaya wa kuvuna Muda sahihi wa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb Chanzo: TAHA 2021 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ Bei elekezi za mbolea ni za rejareja na zinatofautiana kwenye mikoa kulingana na umbali. ✓ N/A bei haikupatikana ✓ Chanzo cha takwimu: Wizara ya Kilimo/Wizara ya Viwanda na Biashara/TAHA. Kwa maelezo zaidi wasiliana na: Kaimu Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, | false |
# Extracted Content 1 05 Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO YA CHAKULA 26-30 Oktoba 2020 Jedwali1: Wastani wa bei za jumla kitaifa (TZS/ Kilo100) Jedwali 2. Wastani wa bei za jumla za mahindi kwa wiki (TZS/Kilo 100) Mazao Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Mahindi 58,000 58,000 57,000 ▼2 Mchele 139,600 141,500 142,300 ▲1 Maharage 202,000 202,900 197,600 ▼3 Mtama 89,000 86,200 95,100 ▲10 Viazi mviringo 75,500 71,000 70,100 ▼1 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26- 30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha -Mjini 51,500 51,500 51,000 ▼1 Bukoba 62,500 63,500 62,500 ▼2 Dar es Salaam - Ilala 60,500 62,000 57,000 ▼8 Dar es Salaam- Kinondoni 72,500 72,500 57,000 ▼21 Dodoma Majengo 62,000 61,500 64,000 ▲4 Dodoma-Kibaigwa 61,000 53,500 56,500 ▲6 Mpanda 51,000 52,500 52,500 ►0 Musoma 60,000 67,500 67,500 ►0 Babati 64,000 64,000 64,000 ►0 Morogoro 55,500 55,500 57,800 ▲4 Mtwara DC 58,000 57,000 57,000 ►0 Tabora 51,500 51,000 51,500 ►0 Tanga/Mgandini 62,500 60,700 60,600 ▼0 Ujumbe Mkuu ✓ Wastani wa bei za mazao makuu ya chakula kitaifa zimeongezeka na kupungua kwa viwango tofauti ambapo bei za mtama zimeongezeka kwa asilimia 10 na mchele kwa asilimia 1 na bei za maharage, mahindi, na viazi mviringo zimepungua kwa asilimia 3, 2 na 1 mtawalia. ✓ Mahindi: Bei zimeonekana kuwa za juu zaidi katika soko la Musoma, Dodoma-majengo na Babati. Bei za chini zimeonekana katika soko la Arusha Mjini, Tabora na Mpanda. ✓ Mchele: Bei zimeonekana kuwa za juu zaidi katika soko la Dar es Salaam-Ilala, Dar es Salaam Kinondoni na soko la Babati ambapo bei ya chini imeonekana katika soko la Mpanda na soko la Musoma. ✓ Maharage Bei zimeonekana kuwa za juu zaidi katika soko la Mpanda na soko la Tabora ambapo bei za chini zimeonekana katika soko la Morogoro na Iringa Mjini. ✓ Korosho: Kwa msimu wa 2020/21 wa mauzo, mahitaji mpaka sasa yamezidi korosho iliyopo kwa tani 234,733. 2 Jedwali 3: Wastani wa bei za jumla za mchele kwa wiki (TZS/kilo 100) Jedwali 4: Wastani wa bei za jumla za maharage kwa wiki (TZS/kilo 100) Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha- mjini 160,000 165,000 165,000 ►0 Dar es Salaam - Ilala 220,000 220,000 220,000 ►0 Dar es Salaam-Kinondoni 220,000 220,000 220,000 ►0 Dodoma -majengo 220,000 216,000 217,500 ▲1 Bukoba 207,500 195,000 195,000 ►0 Babati 186,000 186,000 186,000 ►0 Morogoro 182,500 182,500 182,500 ►0 Iringa- mjini 180,000 180,000 185,000 ▲3 Mpanda 210,000 240,000 240,000 ►0 Mtwara DC 210,000 215,000 215,000 ►0 Tabora 225,000 225,000 225,000 ►0 Tanga/Mgandini 205,000 215,000 215,000 ►0 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita vs wiki hii (%) Arusha - Mjini 145,000 140,000 135,000 ▼4 Dar es Salaam - Ilala 170,000 170,000 170,000 ►0 Dar es Salaam-Kinondoni 165,000 165,000 165,000 ►0 Dodoma - majengo 135,000 136,500 142,500 ▲4 Bukoba 134,000 136,000 136,000 ►0 Babati 160,000 160,000 160,000 ►0 Morogoro 130,000 130,000 130,000 ►0 Mpanda 85,000 85,000 85,000 ►0 Mtwara DC 150,000 145,000 145,000 ►0 Musoma 97,500 97,500 97,500 ►0 Iringa Mjini 160,000 160,000 160,000 ►0 Tabora 145,000 145,000 145,000 ►0 Tanga/Mgandini 170,000 155,000 155,000 ►0 3 Jedwali 5: Wastani wa bei za jumla za mtama kwa wiki (TZS/Kilo100) Jedwali 6: Wastani wa bei za jumla za viazi mviringo kwa wiki (TZS/Kilo 100) Table 7: Wastani wa bei za mazao ya Horticulture kwa tarehe 23-28 October 2020 Eneo la Soko (Mji) Nyanya (40 Kg Crate) Vitunguu (100 Kg Sack) Tikiti maji (Kilo) Nanasi (Kilo) Green Pepper (50 Kg Sack) Cucumber (100 Kg Sack) Nairobi 44,000 74,800 719 609 52,800 96,800 Mombasa 33,293 80,667 550 - 51,333 77,000 Zanzibar 44,250 98,333 767 833 39,167 76,667 Dar es Salaam 21,667 80,000 300 400 36,111 100,000 Morogoro 37,500 73,000 425 - 45,000 83,333 Dodoma 24,000 70,000 267 333 35,000 60,000 Shinyanga 25,000 75,000 533 500 33,333 31,667 Mwanza 18,000 70,833 400 550 16,500 35,000 Mbeya 35,333 64,444 433 1,167 54,333 130,667 Arusha 24,500 80,000 530 475 30,000 75,000 Tanga 25,500 90,000 633 800 40,000 70,000 Lindi 19,000 90,000 300 350 30,000 55,000 Mtwara - 100,000 400 - 30,000 75,000 Chanzo: TAHA, 2020 Soko Wiki ya nyuma (Okt 12-16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt26-30) Badiliko Wiki iliyopita na wiki hii (%) Arusha- mjini 72,500 72,500 72,500 ►0 Dar es Salaam –Kinondoni 55,000 55,000 57,500 ▲5 Dar es Salaam – Ilala 62,000 62,000 62,000 ►0 Dodoma - majengo 62,500 63,000 63,500 ▲1 Bukoba 95,000 97,500 97,500 ►0 Babati 67,500 67,500 67,500 ►0 Morogoro 76,000 76,500 76,500 ►0 Musoma 105,000 105,000 105,000 ►0 Mpanda 95,000 95,000 95,000 ►0 Mtwara DC 95,000 67,500 67,500 ►0 Tabora 77,500 72,500 72,500 ►0 Tanga/mgandini 58,900 58,900 58,900 ►0 Soko Wiki ya nyuma (Okt 12- 16) Wiki iliyopita (Okt 19-23) Wiki hii (Okt 26-30) Badiliko Wiki iliyopita na wiki hii (%) Arusha -mjini 65,000 62,500 65,000 ▲4 Dar es Salaam - Kinondoni 80,000 80,000 80,000 ►0 Dar es Salaam - Ilala 105,000 105,000 105,000 ►0 Dodoma - Majengo 47,500 49,000 50,500 ▲3 Dodoma-Kibaigwa 54,500 54,000 54,500 ▲1 Bukoba 140,000 145,000 145,000 ►0 Babati 60,000 60,000 60,000 ►0 Morogoro 95,000 95,000 95,000 ►0 Mtwara DC 80,000 80,000 80,000 ►0 Tabora 145,000 145,000 145,000 ►0 Tanga - mgandini 90,000 95,000 95,000 ►0 4 Jedwali 8: Mauzo ya korosho kwa msimu wa mwaka 2020/21 hadi kufikia tarehe 30 Oktoba, 2020 Tarehe ya mnada Jina la chama Kikuu Kiasi kilichokusanywa (kilo) Mahitaji ya wanunuzi (kilo) Idadi ya wanunuzi Bei (Sh/kilo) Kiasi kilichouzwa (kilo) Ya chini Ya juu 9/10/2020 TANECU 3,109,568 15,952,000 22 2,421 2,707 3,109,568 9/10/2020 MAMCU 6,975,897 31,215,783 25 2,439 2,607 5,526,113 10/10/2020 MWAMBAO 7,143,773 21,247,546 19 2,329 2,470 7,143,773 11/10/2020 RUNALI 2,854,008 16,128,868 21 2,345 2,555 2,854,008 16/10/2020 TANECU 4,109,347 17,883,000 22 2,404 2,459 4,109,347 16/10/2020 MAMCU 9,603,182 32,910,536 21 2,265 2,459 9,602,982 17/10/2020 MWAMBAO 4,755,685 11,994,166 17 2,242 2,395 4,738,653 18/10/2020 RUNALI 7,225,504 16,149,454 17 2,301 2,435 7,225,504 23/10/2020 TANECU 4,726,622 17,333,000 26 2,351 2,415 3,759,000 23/10/2020 MAMCU 8,074,188 39,483,656 22 2,271 2,450 8,074,188 24/10/2020 MWAMBAO 3,180,884 11,051,522 15 1,7501 2,412 3,180,884 25/10/2020 RUNALI 4,989,359 20,974,022 18 1,630 2,410 4,989,359 29/10/2020 TAMCU 2,729,158 11,114,118 16 2,245 2,369 2,729,158 30/10/2020 TANECU 4,761,780 14,293,000 21 2,380 2,459 4,761,780 30/10/2020 MAMCU 5,978,692 34,844,966 21 2,290 2,479 5,978,692 Jumla 80,217,647 312,575,637 77,783,009 Chanzo: Bodi ya Korosho Tanzania, 2020 ✓ Kwa msimu wa 2020/21 wa mauzo, hadi kufikia tarehe 30 Oktoba, 2020, jumla ya tani 77,783 zilikuwa zimeuzwa kwa njia ya minada kati ya tani 80,218 zilizokuwa zimekusanywa na wakulima ambapo mahitaji ya wanunuzi yalikuwa ni jumla ya tani 312,576. 1 Bei ya korosho ya daraja la chini (Undergrade) ni Shilingi 1,750 na bei ya chini ya korosho ya daraja la juu (standard grade) ni shilingi 2,305, ambapo bei ya juu ya korosho daraja la juu ni shilingi 2,412. 5 Jedwali 9: Bei elekezi (shilingi) ya mbolea iliyotangazwa tarehe 11 Agosti, 2020 Kituo cha Mauzo DAP UREA Kilo 50 Kilo 25 Kilo 50 Kilo 25 Arusha 55,539 28,770 47,757 24,879 Dodoma 54,109 28,054 46,321 24,161 Dar es Salaam 48,892 25,446 41,462 21,731 Geita 58,496 30,248 50,709 26,355 Iringa 54,746 28,373 46,959 24,480 Kagera 59,378 30,689 52,337 27,168 Katavi 59,614 30,807 52,595 27,297 Kigoma 58,653 30,326 51,546 26,773 Kilimanjaro 54,499 28,250 46,712 24,356 Lindi 54,226 28,113 46,439 24,219 Manyara 56,643 29,321 48,856 25,428 Mara 59,510 30,755 52,481 27,240 Mbeya 56,476 29,238 48,689 25,344 Morogoro 53,211 27,606 45,424 23,712 Mtwara 54,963 28,482 47,176 24,588 Mwanza 58,370 30,185 50,583 26,291 Njombe 55,571 28,785 47,784 24,892 Pwani 51,819 26,909 44,032 23,016 Rukwa 59,439 30,719 52,403 27,202 Ruvuma 57,585 29,793 49,798 25,899 Shinyanga 57,716 29,858 49,929 25,964 Simiyu 57,727 29,864 49,940 25,970 Singida 55,134 28,567 47,347 24,673 Songwe 57,663 29,832 49,876 25,938 Tabora 56,863 29,432 49,594 25,797 Tanga 53,206 27,603 45,419 23,709 Wastani 55,756 28,878 48,126 25,063 Chanzo: Wizara ya Kilimo, 2020 6 Jedwali 10: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati mzuri wa kuvuna Wakati mbaya wa kuvuna Muda sahihi wa kupanda Vitunguu Feb- Julai Julai- Novemba Sept- Des Nyanya Jan- Mei Juni- Desemba Sept- Des Hoho kijani Feb- Aprili Juni- Januari Okt- Nov Karoti Okt- Machi April- Sept Julai- Okt Matango Feb- Mei Mei- Jan Des- Jan Viazi mviringo Machi- Juni Julai- Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba-Desemba Mei- Sept, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Des- Mei Feb- Machi Tangawizi Aprili- Julai Agosti - Machi Des- Feb Chanzo: TAHA 2020 Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ Bei elekezi za mbolea ni za rejareja na zinatofautiana kwenye mikoa kulingana na umbali. ✓ Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara. Kwa maelezo zaidi wasiliana na: Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 786 465 121 au +255 754 419 813 | false |
# Extracted Content Juni, 2021 WIZARA YA KILIMO Idara ya Usalama wa Chakula – Sehemu ya Uratibu wa Mazao na Tahadhari ya Awali TAARIFA YA TATHMINI YA AWALI YA UZALISHAJI WA MAZAO YA CHAKULA MSIMU 2020/2021 NA UPATIKANAJI WA CHAKULA 2021/2022 Sehemu ya Uratibu wa Mazao ya Chakula na Tahadhari ya Awali © Julai, 2021 JAMHURI YA MUUNGANO WA TANZANIA i YALIYOMO YALIYOMO ....................................................................................................................................... i ORODHA YA JEDWALI ................................................................................................................ ii ORODHA YA VIELELEZO ........................................................................................................... ii VIFUPISHO ..................................................................................................................................... iii SURA YA KWANZA ...................................................................................................................... 1 1.0 UTANGULIZI ............................................................................................................................ 1 SURA YA PILI ................................................................................................................................. 3 2.0 LENGO LA TATHMINI ............................................................................................................ 3 2.1 Malengo Mahsusi ..................................................................................................................... 3 SURA YA TATU.............................................................................................................................. 4 3.0 METHODOLOJIA ..................................................................................................................... 4 SURA YA NNE ................................................................................................................................ 6 4.0 MATOKEO YA TATHMINI ...................................................................................................... 6 4.1 Mwenendo wa Unyeshaji wa mvua katika Msimu wa Uzalishaji wa Mazao ya Chakula 2020/2021 na Athari zake kwenye Kilimo ................................................................................... 6 4.2 Mvua za Vuli, Oktoba – Desemba, 2020 na Mchango wake katika Uzalishaji wa Mazao ya Chakula .......................................................................................................................... 6 4.3 Mwenendo wa unyeshaji wa mvua za msimu Novemba, 2020 – Aprili, 2021 ............... 7 4.4 Mwenendo wa Unyeshaji wa Mvua za Masika, Machi – Mei, 2021................................. 9 4.5 Ulinganifu wa unyeshaji mvua Msimu wa 2020/2021 na 2019/2020: ........................... 10 4.6 Uzalishaji wa Mazao ya Chakula ......................................................................................... 11 4.7 Mahitaji ya chakula kwa Mwaka 2021/2022 Ikilinganishwa na Uzalishaji .................... 12 4.8 Mchango wa Uzalishaji wa Mazao ya Chakula ................................................................. 15 4.9 Mtiririko wa viwango vya SSR ............................................................................................. 15 4.10 Hali ya Uzalishaji wa Mazao ya Chakula na Viwango vya Uwiano (SSR) Kimkoa ... 16 4.11 Maeneo yenye Dalili za kuwa na Upungufu wa Chakula Nchini .................................. 18 SURA YA TANO ........................................................................................................................... 19 5.0 MWENENDO WA BEI KWA BAADHI YA MAZAO YA CHAKULA HADI KUFIKIA TAREHE 31 MEI, 2021 ................................................................................................................ 19 SURA YA SITA ............................................................................................................................. 21 ii 6.0 ATHARI ZA UGONJWA WA VIRUSI VYA KORONA (UVIKO-19) KATIKA UZALISHAJI WA MAZAO YA CHAKULA ................................................................................. 21 SURA YA SABA ........................................................................................................................... 22 7.0 CHANGAMOTO ..................................................................................................................... 22 SURA YA NANE ........................................................................................................................... 23 8.0 HITIMISHO NA USHAURI .................................................................................................... 23 VIAMBATISHO ............................................................................................................................. 25 Kiambatisho Na:1a. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Nafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei, 2021 .................................................................. 25 Kiambatisho Na:1b. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Yasiyonafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei,2021 ............................................. 26 Kiambatisho Na:2. Kiwango cha mvua na mtawanyiko wake kwa kila mwezi katika msimu wa mvua 2020/2021. .................................................................................................................... 27 Kiambatisho Na:3. Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (SSR) Msimu wa 2020/2021 .................................................................................................................. 30 ORODHA YA JEDWALI Jedwali Na: 1. Matarajio ya Uzalishaji wa Mazao ya Chakula Kimkoa ................................ 12 Jedwali Na: 2. Uzalishaji mazao ya Chakula kwa Msimu wa 2020/2021 Zao kwa zao na Mahitaji ya Chakula kwa Mwaka 2021/2022 (Tani) Kwa Mlinganisho ................................. 13 Jedwali Na: 3. Uwiano wa Uzalishaji na Mahitaji ya Mazao ya Chakula kwa Mwaka 2020/2021 ...................................................................................................................................... 17 Jedwali Na: 4. Halmashauri zenye Maeneo yenye Dalili ya Upungufu wa Chakula kwa Mwaka 2021/2022 ......................................................................................................................... 18 ORODHA YA VIELELEZO Kielelezo Na: 1. Viwango vya Unyeshaji mvua na Mtawanyiko wake kwa Kipindi cha Kuanzia Tarehe 1 Oktoba – 31 Desemba, 2020 ....................................................................... 7 Kielelezo Na: 2. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Novemba, 2020 – 30 Aprili, 2021 ................................................................. 8 Kielelezo Na: 3. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Machi – 31 Mei, 2021. .................................................................................... 9 Kielelezo Na: 4. Ulinganifu wa Viwango vya unyeshaji mvua (Anomalia) na mtawanyiko wake kwa kipindi cha kuanzia Tarehe Septemba 1, 2020 – Mei 31, 2021 na kuanzia Tarehe Septemba 1, 2019 – Mei 31, 2020. ............................................................................. 10 Kielelezo Na: 5. Asilimia ya uzalishaji ya mazao makuu ya chakula nchini ....................... 15 Kielelezo Na: 6. Mtiririko wa Uwiano wa Uzalishaji na Mahitaji (SSR) Kuanzia Mwaka 2002/2003 hadi 2021/2022 .......................................................................................................... 16 Kielelezo Na: 7. Mwenendo wa bei za mahindi, mchele na maharage kwa gunia la kilo 100 (Juni 2019-Mei 2021). ........................................................................................................... 19 iii VIFUPISHO ARDS: Agriculture Routine System CMEWs: Crop Monitoring and Early Warning System CPB: Cereal and other Produce Board HYC: Hali ya Chakula M&E: Monitoring and Evaluation NFRA: National Food Reserve Authority SSR: Self Sufficiency Ratio TMA: Tanzania Meterogical Authority UVIKO-19: Ugonjwa wa Virusi vya Korona 1 SURA YA KWANZA 1.0 UTANGULIZI Tathmini ya Uzalishaji wa Mazao ya Chakula na Upatikanaji wa Chakula nchini ni ya muhimu katika kupata taarifa ya uzalishaji wa mazao ya chakula na upatikanaji wa chakula nchini. Tathmini hizi huiwezesha Serikali kuchukua maamuzi stahiki katika utekelezaji wa jukumu la hali endelevu ya utengamano wa usalama wa chakula na lishe nchini kwa wakati wote. Tathmini hii hufanyika mara mbili katika msimu wa uzalishaji (Tathmini ya Awali na ya Mwisho). Tathmini ya Awali hufanyika kila mwaka mwezi Mei/Juni na Tathmini ya Mwisho mwezi Novemba/Desemba. Tathmini hizo huratibiwa na Idara ya Usalama wa Chakula Sehemu ya Uratibu wa Mazao na Tahadhari ya Awali. Sehemu hii hufanya shughuli za ufuatiliaji na ukusanyaji wa takwimu na taarifa mbalimbali zinazohusiana na Usalama wa Chakula nchini. Takwimu na taarifa hizo ni pamoja na: - hali ya unyeshaji wa mvua, ukuaji wa mazao mashambani, athari katika ukuaji wa mazao zinazoweza kusababishwa na visumbufu, mwenendo wa bei na upatikanaji wa chakula sokoni, hali ya biashara ya mazao ya chakula (export & import) na akiba ya mazao (stocks). Takwimu za uzalishaji wa mazao ya chakula hukusanywa kwa kutumia Mfumo wa Uratibu wa Mazao na Tahadhari ya Awali (Crop Monitoring and Early Warning System – CMEWs) sambamba na Mfumo wa Ukusanyaji na Utoaji wa Taarifa na Takwimu za Sekta ya Kilimo nchini (Agriculture Routine Data System - ARDS) ambapo nyenzo (tools) mbalimbali hutumika katika ukusanyaji wa takwimu na taarifa hizo. Katika tathmini hizo, mazao makuu ya chakula yanayoratibiwa kwa sasa ni mahindi, mpunga, mtama, uwele, ulezi, ngano, ndizi, muhogo, viazi vitamu, viazi mviringo, maharage, soya, mbaazi, kunde, choroko, karanga, njegere na njugumawe. Katika msimu wa 2020/2021 mazao haya yamelimwa katika eneo la ukubwa wa hekta 10,264,339 kati ya takriban hekta 44,000,000 zinazofaa kwa kilimo Tanzania Bara. Katika kipindi cha mwezi Juni 2021, timu ya wataalam wa Idara ya Usalama wa Chakula kwa kushirikiana na Idara ya Sera na Mipango - Sehemu ya Uratibu na 2 Tathmini (M&E) Wizara ya Kilimo, Ofisi ya Rais – Ikulu, Ofisi ya Rais –TAMISEMI, Ofisi ya Waziri Mkuu na Ofisi ya Taifa ya Takwimu ilifanya Tathmini ya Awali ya Uzalishaji wa Mazao ya Chakula kwa msimu wa 2020/20211. Katika tathmini hiyo, takwimu na taarifa mbalimbali za uzalishaji, upatikanaji wa mazao makuu ya chakula na mwenendo wa unyeshaji mvua kutoka Halmashauri zote za Tanzania Bara zilikusanywa na kufanyiwa uchambuzi wa kina na kutolewa taarifa. 1 Hapa nchini, msimu wa uzalishaji huanza kuhesabiwa kuanzia katikati ya mwezi Septemba ya mwaka husika hadi katikati ya mwezi Agosti ya mwaka unaofuata (Mfano Septemba, 2020 hadi Agosti, 2021), Aidha, kila msimu hupata unyeshaji wa mvua kama inavyoonesha yaani mvua za Vuli –Septemba-Desemba, Msimu –Desemba-Mei, na Masika-Machi –Mei. 3 SURA YA PILI 2.0 LENGO LA TATHMINI Lengo kuu ni kupata takwimu na taarifa za hali ya uzalishaji wa mazao ya chakula inayotarajiwa katika msimu wa 2020/2021 na upatikanaji wa chakula nchini kwa mwaka 2021/2022 ili kuiwezesha Serikali na wadau wa masuala ya usalama wa chakula kuchukua maamuzi stahiki katika utekelezaji wa jukumu la hali endelevu ya utengamano wa usalama wa chakula na lishe nchini. 2.1 Malengo Mahsusi Malengo mahsusi ni pamoja na; 1. Kukusanya takwimu za malengo ya uzalishaji wa mazao ya chakula kwa msimu wa 2020/2021 na utekelezaji wake kufikia Mei 31, 2021 ; 2. Kukusanya takwimu na taarifa za visumbufu na mwenendo wa unyeshaji wa mvua katika maeneo ya uzalishaji wa mazao ya chakula; 3. Kukusanya na kufuatilia taarifa za mwenendo wa bei za mazao ya chakula na mifugo, hali ya maji na malisho na upatikanaji wa chakula katika Halmashauri zote Tanzania bara ;na 4. Kufuatilia na kukusanya takwimu na taarifa za akiba ya mazao ya chakula katika maghala ya wafanya biashara na wakulima. 4 SURA YA TATU 3.0 METHODOLOJIA Tathmini hii ilihusisha jumla ya timu 9 za Wataalam ambapo takwimu na taarifa mbalimbali za uzalishaji wa mazao ya chakula zilikusanywa katika Halmashauri 184 katika Mikoa 26 ya Tanzania Bara. Takwimu na taarifa hizo zilikusanywa kwa kutumia mfumo wa CMEWs na ARDS. Timu hizo zilirejea na kuhakiki takwimu na taarifa mbalimbali za uzalishaji wa mazao ya chakula katika msimu wa 2020/2021. Aidha, timu ya wataalam walikutana Mkoani Morogoro kuendelea na kazi ya kuchambua, kuchakata na kuandaa taarifa ya awali ya uzalishaji wa mazao ya chakula katika msimu wa 2020/2021 na matarajio ya upatikanaji wa chakula kwa mwaka 2021/2022. Katika uchambuzi na uchakataji wa takwimu, vigezo vifuatavyo vilizingatiwa: - 1. Kigezo cha Upimaji wa Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (Self Sufficiency Ratio – SSR): Kigezo hiki hukokotolewa kwa kulinganisha uzalishaji na mahitaji (kutafsiriwa kwa kuzingatia asilimia - %) , ambapo Kiwango cha asilimia 0 - 99 inaashiria Upungufu wa chakula; asilimia 100 – 119 inaashiria Utoshelevu wa chakula na asilimia 120 na zaidi inaashiria Ziada ya chakula; 2. Ukokotoaji wa Mahitaji ya Chakula: Mahitaji ya chakula kwa mwaka hukokotolewa kwa kuzingatia idadi ya watu kwa mwaka wa chakula2 (mid-year population),3 mahitaji ya chakula (food consumption requirement) na mahitaji mengine yasiyokuwa ya chakula cha binadamu (non-food requirement) kama vile mbegu, chakula cha mifugo, biashara na upotevu wa mazao ambayo ni sehemu ya asilimia ya chakula kilichozalishwa; na 2 Hapa nchini, mwaka wa chakula huanzia tarehe 1 Juni hadi tarehe 31 Mei ya mwaka unaofuata, mfano Juni, 2021 hadi tarehe 31 Mei, 2022 kwa msimu wa uzalishaji 2020/2021. 3 ‘Mid-Year Population’ ni Idadi ya watu watakao kuwepo katikati ya mwaka husika wa chakula. Hii hukokotolewa kwa kutumia viwango vya ukuaji wa idadi ya watu (population growth rate) kulingana na Sensa ya idadi ya watu inayotolewa na NBS. 5 3. Ukokotoaji wa Ziada/Upungufu: Ziada au uhaba hukokotolewa kutokana na uzalishaji wa msimu husika baada ya kutoa mahitaji ya chakula ya mwaka husika (Production less Requirement) ambapo jibu linaweza kuwa chanya (+) inayoashiria ziada au hasi (-) inayoashiria upungufu kulingana na uzalishaji ulivyokuwa na; 4. Athari za visumbufu vya mazao na mwenendo wa unyeshaji wa mvua katika msimu husika. 6 SURA YA NNE 4.0 MATOKEO YA TATHMINI Matokeo ya tathmini hii ya awali yanaonesha kuwa, hali tarajiwa ya upatikanaji wa chakula kwa mwaka 2021/2022 itaendelea kutengamaa kutokana na uzalishaji wa kuridhisha wa mazao ya chakula katika mikoa yote ya Tanzania Bara. Aidha, kutokana na sababu mbalimbali zilizoleta athari katika baadhi ya mazao hususan nafaka, uzalishaji huu unatarajiwa kushuka kidogo ikilinganishwa na msimu wa 2019/2020. 4.1 Mwenendo wa Unyeshaji wa mvua katika Msimu wa Uzalishaji wa Mazao ya Chakula 2020/2021 na Athari zake kwenye Kilimo Uzalishaji wa mazao ya kilimo hutegemea kwa kiasi kikubwa unyeshaji wa mvua za kutosha na mtawanyiko wa kuridhisha. Unyeshaji wa mvua hapa nchini umegawanyika katika sehemu mbili, ambapo kuna maeneo yanayopata msimu mmoja wa mvua kwa mwaka (Msimu) na maeneo yanayopata misimu miwili ya mvua kwa mwaka (Vuli na Masika). 4.2 Mvua za Vuli, Oktoba – Desemba, 2020 na Mchango wake katika Uzalishaji wa Mazao ya Chakula Katika msimu wa mvua za Vuli 2020/2021, mvua zilianza mapema mwezi Septemba katika maeneo ya mikoa ya Mara na Kagera, na kutawanyika katika maeneo mengine ya Kanda ya Ziwa Viktoria pamoja na maeneo machache ya mikoa ya Pwani na Dar es Salaam katika kipindi cha mwezi Oktoba. Mvua hizi ziliendelea kunyesha kwa kiwango cha juu ya wastani katika maeneo mengi hasa ya Kanda ya Ziwa Viktoria. Katika maeneo mengine ya Pwani ya Kaskazini na Kanda ya Kaskazini Mashariki, mvua zilichelewa kuanza (zilianza mwezi Novemba, 2020) na ziliendelea kwa mtawanyiko hafifu. Mvua hizi ziliendelea kunyesha hadi katika kipindi cha mwezi Januari, 2021 na hivyo kuisha nje ya msimu. Hali hii ilisababisha athari kidogo kwenye mazao yaliyokuwa yamekomaa katika baadhi ya maeneo. Hata hivyo, uzalishaji wa mazao kwa ujumla ulikuwa mzuri Kielelezo Na. 1. 7 Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Vuli, 2020 ikilinganishwa na wastani Asilimia ya unyeshaji mvua za Vuli, 2020 (wastani ni 75 – 125%) Kielelezo Na: 1. Viwango vya Unyeshaji mvua na Mtawanyiko wake kwa Kipindi cha Kuanzia Tarehe 1 Oktoba – 31 Desemba, 2020 Chanzo: TMA, GeoWRSI 2020 4Anomalia 4.3 Mwenendo wa unyeshaji wa mvua za msimu Novemba, 2020 – Aprili, 2021 Mvua za Msimu zilianza kwa wakati katika wiki ya pili ya mwezi Novemba, 2020 katika maeneo mengi yanayopata mvua hizo isipokuwa maeneo ya mikoa ya Dodoma, Iringa, Njombe, Ruvuma, Mtwara, Lindi na Morogoro-kusini. Katika maeneo hayo, mvua zilianza kati ya wiki ya pili na wiki ya tatu ya mwezi Desemba, 2020. Ziliendelea vizuri katika miezi ya Januari na Februari, 2021 katika maeneo yote. Kipindi cha Mwezi Machi, 2021 kilitawaliwa na vipindi vya ukosefu wa mvua (prolonged dry spells) katika maeneo mengi isipokuwa kusini mwa nchi. Mvua hizi ziliwahi kuisha mapema zaidi katika wiki ya kwanza ya mwezi Aprili, 2021 katika maeneo ya mkoa wa Ruvuma na maeneo ya kanda ya kati. Maeneo mengine 4 Anomalia: Kiwango cha wa unyeshaji mvua mwenendo wa kawaida 8 yaliyosalia, mvua hizo ziliendelea mpaka kufikia wiki ya kwanza ya mwezi Mei, 2021. Aidha, mvua chache zilinyesha katika maeneo ya magharibi na kusini mwa mkoa wa Morogoro katika wiki ya kwanza ya mwezi Mei, 2021 na maeneo ya Pwani ya kusini katika wiki ya mwisho ya mwezi Mei, 2021. Mvua hizi zimechangia uharibifu kiasi wa mazao yaliyokuwa yamefikia hatua ya kukomaa na pia menejimenti ya ukaushaji wa mazao yaliyokuwa yanavunwa. Hata hivyo, kwa ujumla mvua za wastani hadi juu ya wastani zilinyesha katika maeneo yote yanayopata mvua za Msimu, lakini mtawanyiko wake haukuwa mzuri katika baadhi ya maeneo na hivyo kupunguza tija ya uzalishaji katika maeneo mengi yanayopata mvua hizo za Msimu hasa kwa mazao ya nafaka Kielelezo Na. 2. Chanzo: TMA, GeoWRSI 2021 Kiasi cha mvua (mm) iliyonyesha kwenye kipindi cha Msimu Novemba, 2020 – Aprili, 2021 Asilimia ya unyeshaji mvua za Msimu Novemba, 2020 – Aprili, 2021 (wastani ni 75 – 125%) Kielelezo Na: 2. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Novemba, 2020 – 30 Aprili, 2021 9 4.4 Mwenendo wa Unyeshaji wa Mvua za Masika, Machi – Mei, 2021 Kwa mwaka 2021, mvua za Masika zilichelewa sana kuanza. Mvua hizo zilianza katika wiki ya nne katika maeneo machache badala ya wiki ya pili ya mwezi Machi kama ilivyokawaida na kuendelea kwa wingi katika mwezi Aprili. Hata hivyo, mvua hizo hazikuwa na mtawanyiko mzuri kimaeneo (spatial distribution) na kwa kipindi cha unyeshaji (temporal distribution). Aidha, mvua hizo ziliwahi kuisha katika baadhi ya maeneo na kusababisha mazao kukosa unyevunyevu wa kutosha hasa mazao ya mahindi na mpunga. Hata hivyo, uchache wa mvua hizi uliwezesha mazao ya mizizi kustawi vizuri na hivyo kuongeza uzalishaji wa mazao hayo. Kwa ujumla, mvua zilikuwa za wastani hadi juu ya wastani katika maeneo mengi isipokuwa maeneo ya mkoa wa Tanga na kaskazini mwa mkoa wa Pwani na hivyo kusababisha uzalishaji wa mazao kiujumla kuwa wa wastani Kielelezo Na.3. Chanzo: TMA, GeoWRSI 2021 Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Masika, 2021 ikilinganishwa na wastani Asilimia ya unyeshaji mvua za Masika, 2021 (wastani ni 75 – 125%) Kielelezo Na: 3. Viwango vya unyeshaji mvua na mtawanyiko wake kwa kipindi cha kuanzia Tarehe 1 Machi – 31 Mei, 2021. 10 4.5 Ulinganifu wa Unyeshaji mvua Msimu wa 2020/2021 na 2019/2020: Mvua katika msimu wa 2020/2021 ilinyesha katika kiwango cha wastani hadi juu ya wastani kama ilivyokuwa katika msimu uliopita wa 2019/2020 katika maeneo mengi ya nchi. Hata hivyo, katika msimu wa 2020/2021 mvua ilinyesha kwa kiwango pungufu ikilinganishwa na msimu wa 2019/2020. Aidha, Maeneo machache ya Kaskazini hasa mikoa ya Kilimanjaro, Tanga, Dar es Salaam na kaskazini mwa mkoa wa Pwani mvua zimenyesha kwa kiwango cha wastani hadi chini ya wastani, hali hii ni pungufu zaidi ikilinganishwa na msimu uliopita Kielelezo Na. 4 na Kiambatisho Na. 2. Chanzo: TMA, GeoWRSI 2021 & 2020 Mtawalia Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Kilimo kuanzia Septemba 1, 2020 – Mei 31, 2021 ikilinganishwa na wastani Tofauti ya mvua (mm) iliyonyesha kwenye kipindi cha msimu wa Kilimo kuanzia Septemba 1, 2019 – Mei 31, 2020 ikilinganishwa na wastani Kielelezo Na: 4. Ulinganifu wa Viwango vya unyeshaji mvua (Anomalia) na mtawanyiko wake kwa kipindi cha kuanzia Tarehe Septemba 1, 2020 – Mei 31, 2021 na kuanzia Tarehe 1 Septemba, 2019 – 31 Mei, 2020. 11 4.6 Uzalishaji wa Mazao ya Chakula Tathmini ya Awali ya hali ya Uzalishaji wa Mazao ya Chakula Msimu wa 2020/2021 na Upatikanaji wa Chakula kwa Mwaka 2021/2022 imeonesha kuwa, hali ya uzalishaji wa chakula inatarajiwa kufikia kiasi cha tani 18,425,250 kwa mlinganisho wa nafaka (Grain Equivalent). Ikilinganishwa na tani 18,196,733 msimu wa 2019/2020 uzalishaji huu umeongezeka kwa kiasi cha tani 228,517 sawa na asilimia 1.3. Kwa msimu wa uzalishaji wa 2020/2021, uzalishaji wa mazao ya nafaka unatarajiwa kufikia tani 10,639,990. Uzalishaji huu umepungua kwa tani 229,606 sawa na asilimia 2.1 ikilinganishwa na uzalishaji wa tani 10,869,596 kwa msimu wa 2019/2020. Aidha, kwa mazao yasiyo nafaka uzalishaji unatarajiwa kufikia tani 7,785,260. Ikilinganishwa na uzalishaji wa tani 7,327, 137 msimu wa 2019/2020, uzalishaji huu umeongezeka kwa tani 458,123 sawa na ongezeko la asilimia 6.2. Uzalishaji wa mahindi unatarajiwa kufikia kiasi cha tani 6,908,318 ikilinganishwa na tani 6,711,002 za uzalishaji msimu wa 2019/2020. Uzalishaji wa mchele unatarajiwa kufikia kiasi cha tani, 2,629, 519 ikilinganishwa na tani 3,038,080 kwa msimu wa 2019/2020. Uzalishaji wa mahindi umeongezeka kwa tani 197,316 na mchele umepungua kwa tani 408,561 sawa na asilimia 3.0 na 13.5 mtawalia. Uzalishaji wa mazao ya chakula kwa kuzingatia mkoa ulioongoza katika uzalishaji wa mazao hayo ni kama inavyoonekana katika Jedwali Na.1. 12 Jedwali Na: 1. Matarajio ya Uzalishaji wa Mazao ya Chakula Kimkoa 1 Ruvuma 352,796 998,550 Kagera 364,220 972,960 Ruvuma 509,976 1,341,740 Ruvuma 2 Mbeya 303,434 865,715 Kigoma 350,816 693,780 Mbeya 452,090 1,253,699 Mbeya 3 Morogoro 410,843 770,966 Mwanza 244,547 550,806 Kigoma 599,633 1,215,621 Kigoma 4 Rukwa 329,706 768,033 Mbeya 148,656 387,985 Kagera 489,866 1,139,154 Kagera 5 Songwe 255,162 595,429 Tanga 283,096 385,144 Rukwa 514,207 1,041,067 Rukwa 6 Tabora 337,520 573,624 Mara 130,175 371,093 Mwanza 482,779 978,820 Mwanza 7 Kigoma 248,817 521,841 Ruvuma 157,180 343,190 Morogoro 510,529 973,508 Morogoro 8 Manyara 302,889 514,471 Geita 231,561 340,944 Tabora 598,952 892,093 Tabora 9 Dodoma 423,517 455,012 Mtwara 200,227 323,845 Songwe 394,432 843,847 Songwe 10 Mwanza 238,232 428,014 Tabora 261,432 318,469 Tanga 571,407 741,809 Tanga 11 Simiyu 309,655 396,602 Kilimanjaro 117,755 300,237 Dodoma 604,175 715,512 Dodoma 12 Arusha 207,728 361,570 Rukwa 184,500 273,033 Geita 445,974 699,841 Geita 13 Singida 313,055 360,965 Dodoma 180,658 260,499 Manyara 443,849 655,780 Manyara 14 Geita 214,413 358,897 Arusha 113,510 253,675 Mara 293,094 628,399 Mara 15 Tanga 288,311 356,666 Pwani 80,028 248,513 Arusha 321,238 615,245 Arusha 16 Shinyanga 246,209 356,427 Songwe 139,270 248,418 Simiyu 517,353 585,422 Simiyu 17 Iringa 160,427 322,132 Morogoro 99,686 202,542 Kilimanjaro 241,858 569,184 Kilimanjaro 18 Njombe 143,195 280,960 Shinyanga 181,882 189,499 Shinyanga 428,090 545,926 Shinyanga 19 Kilimanjaro 124,103 268,947 Simiyu 207,699 188,820 Singida 398,457 523,665 Singida 20 Katavi 132,452 268,286 Njombe 115,818 175,863 Iringa 261,667 471,490 Iringa 21 Mara 162,919 257,306 Katavi 78,684 165,541 Njombe 259,013 456,824 Njombe 22 Kagera 125,646 166,194 Singida 85,402 162,700 Katavi 211,136 433,827 Katavi 23 Lindi 143,240 156,983 Iringa 101,240 149,358 Mtwara 297,546 417,908 Mtwara 24 Pwani 110,052 151,553 Manyara 140,960 141,308 Pwani 190,080 400,066 Pwani 25 Mtwara 97,319 94,063 Lindi 80,197 128,185 Lindi 223,437 285,168 Lindi 26 Dar es Salaam 926 818 Dar es Salaam 2,573 8,852 Dar es Salaam 3,499 9,670 Dar es Salaam Jumla 5,982,567 10,639,990 Jumla 4,239,083 7,785,260 Jumla 10,264,339 18,425,250 Jumla Matarajio ya Mavuno Yote (Tani) Mkoa Eneo (Hekta) Mkoa Mavuno (Tani) Mavuno (Tani) Mkoa Mkoa Mavuno (Tani) Matarajio ya Mazao ya Nafaka (Tani) Eneo (Hekta) Matarajio ya Mazao yasiyo Nafaka (Tani) Eneo (Hekta) Chanzo: Tathmini ya HYC 2020/2021 4.7 Mahitaji ya chakula kwa Mwaka 2021/2022 Ikilinganishwa na Uzalishaji Mahitaji ya chakula kwa mwaka 2021/2022 ni kiasi cha tani 14,796, 751 ambapo tani 9,417,888 ni za mazao ya nafaka na tani 5,378,864 ni mazao yasiyo nafaka. Kutokana na mahitaji haya yakilinganishwa na uzalishaji, nchi inategemewa kuwa na ziada ya tani 3,628,499 za chakula ambapo tani 1,222,103 ni mazao ya nafaka na tani 2,406,396 ni mazao yasiyo nafaka. Aidha, mahitaji ya mahindi ni kiasi cha tani 5,956,814, ikilinganishwa na uzalishaji, nchi inatarajiwa kuwa na ziada ya tani 951,504 za mahindi. 13 Mahitaji ya mchele ni tani 1,091,778, kiasi hiki kikilinganishwa na uzalishaji, nchi itakuwa na ziada ya tani 1,537,741. Kulingana na uzalishaji unaotarajiwa, nchi itaendelea kuwa na utengamano wa usalama wa chakula, ambapo uwepo na upatikanaji wa chakula nchini utaendelea kuwa wa kuridhisha Jedwali Na. 2. Jedwali Na: 2. Uzalishaji mazao ya Chakula kwa Msimu wa 2020/2021 Zao kwa zao na Mahitaji ya Chakula kwa Mwaka 2021/2022 (Tani) Kwa Mlinganisho wa Nafaka (Grain Equivalent). Nafaka Mahindi Mtama&Malezi Mchele Ngano Nafaka Uzalishaji 6,908,318 1,031,865.0 2,629,519 70,288 10,639,990 Mahitaji 5,956,814 2,087,357.8 1,091,778 281,938 9,417,888 Uhaba (-)/Ziada(+) 951,504 -1,055,493 1,537,741 -211,650 1,222,103 SSR (%) 116 49 241 25 113 Sinafaka Mikunde Ndizi Muhogo Viazi Yasiyonafaka Uzalishaji 2,135,522 1,392,970 2,643,915 1,612,852 7,785,260 Mahitaji 859,337 990,670 2,473,437 1,055,420 5,378,864 Uhaba (-)/Ziada(+) 1,276,185 402,300 170,478 557,433 2,406,396 SSR (%) 249 141 107 153 145 JUMLA Nafaka Yasiyonafaka Uzalishaji 10,639,990 7,785,260 Mahitaji 9,417,888 5,378,864 Uhaba (-)/Ziada(+) 1,222,103 2,406,396 SSR (%) 113 145 125 JUMLA 18,425,250 14,796,751 3,628,499 Chanzo: Tathmini ya HYC 2021 14 4.7.1 Mahitaji ya Ngano ikilinganishwa na Uzalishaji Tathmini ambazo zimekuwa zikifanyika hapa nchini, zimeendelea kubainisha uzalishaji wa kiwango kidogo cha ngano. Mahitaji ya ngano kwa majumbani na viwandani hapa nchini ni takribani tani 1, 000,000 kwa mwaka. Kupitia tathmini hii, jumla ya tani 70,288 za ngano zinatarajiwa kuzalishwa ambapo kiasi hiki ni sawa na asilimia 7 ya mahitaji ya ngano kwa mwaka 2021/2022. Kwakuwa kiasi kinachozalishwa hakikidhi mahitaji, nchi imeendelea kuagiza ngano kutoka nje kutoka nchi za Canada, India, Uturuki, Urusi, Argentina na Australia kama inavyoonekana kwenye Jedwali Na.3. Jedwali Na. 3. Mtiririko wa Uagizaji wa Ngano kutoka Nje kwa Kipindi cha Miaka 3. Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Buck wheat HS CODE 10081000 Hard/grain wheat HS CODE 10019910 Bulgur wheat HS CODE 19043000 Buck wheat HS CODE 10081000 CANADA 5,000.00 - 5,000.00 INDIA 6.27 - 5.36 1.60 116.67 129.90 UTURUKI - 7.08 17.41 21.32 45.80 URUSI 40,000.00 10,000.00 50,000.00 ARGENTINA 8,960.00 8,960.00 AUSTRALIA 27,319.77 27,319.77 91,455.47 50,022.77 36,419.36 JUMLA 5,013.35 JUNI 2019 - MEI 2020 JUNI 2020-MEI 2021 JUNI 2018 - MEI 2019 JUMLA NCHI INAPOTOKA Chanzo: Mamlaka ya Mapato Tanzania 15 4.8 Mchango wa Uzalishaji wa Mazao ya Chakula Matarajio ya uzalishaji wa mazao ya chakula katika msimu wa 2020/2021 unaonesha kuwa, mahindi yatachangia asilimia 37.5, mchele asilimia 14.3, muhogo asilimia 14.3, mikunde asilimia 11.6 na mazao mengine yamechangia asilimia 22.3 kwa pamoja Kielelezo Na.5: Chanzo: Tathmini ya HYC 2020/2021 Kielelezo Na: 5. Asilimia ya uzalishaji ya mazao makuu ya chakula nchini 4.9 Mtiririko wa viwango vya SSR Kwa kuzingatia Kigezo cha Upimaji wa Uwiano wa Uzalishaji na Mahitaji (Self Sufficiency Ratio – SSR), kwa kipindi cha miaka 7 nchi imeendelea kuwa na viwango vya ziada kati ya asilimia 120 na 126. Katika mwaka 2021/2022 nchi inatarajia kuwa na ziada kwa uwiano wa asilimia 125 16 Kielelezo Na.6. Chanzo: Tathmini za HYC – Wizara ya Kilimo Kielelezo Na: 6. Mtiririko wa Uwiano wa Uzalishaji na Mahitaji (SSR) Kuanzia Mwaka 2002/2003 hadi 2021/2022 Ufunguo: Ziada: SSR ≥120 Utoshelevu: SSR 100-119 Upungufu: SSR≤100 4.10 Hali ya Uzalishaji wa Mazao ya Chakula na Viwango vya Uwiano (SSR) Kimkoa Hali ya chakula inatarajiwa kuwa ya kiwango cha: Ziada kati ya asilimia 240 na 120 katika mikoa 13 ambayo ni Ruvuma, Rukwa, Songwe, Katavi, Njombe, Mbeya, Kigoma, Iringa, Kagera, Morogoro, Geita, Manyara na Mtwara. Utoshelevu kati ya asilimia 119 na 104 kwenye mikoa 12 ya Pwani, Simiyu, Singida, Lindi, Tabora, 17 Shinyanga, Tanga, Mara, Kilimanjaro, Dodoma, Arusha na Mwanza na Upungufu kwa asilimia 1 katika mkoa wa Dar es Salaam Jedwali Na.3, Kiambatisho Na.1 a, 1 b na 3. Jedwali Na: 3. Uwiano wa Uzalishaji na Mahitaji ya Mazao ya Chakula kwa Mwaka 2020/2021 Chanzo: Tathmini ya HYC 2020/2021. * Pamoja na kwamba Mkoa wa Dar es Salaam unaonesha upungufu, mkoa huu siyo wa uzalishaji. Ufunguo: Ziada: SSR ≥120 Utoshelevu: SSR 100-119 Upungufu: SSR≤100 18 4.11 Maeneo yenye Dalili za kuwa na Upungufu wa Chakula Nchini Wakati hali ya chakula Kitaifa inatarajiwa kuwa ya kiwango cha Ziada (SSR ya 125), Halmashauri 17 katika mikoa 8 ina maeneo yenye dalili za upungufu wa chakula kwa mwaka 2021/2022 katika vipindi tofauti. Upungufu huo umechangiwa na sababu mbalimbali ikiwemo mtawanyiko mbaya wa mvua, visumbufu vya mimea kama vile wanyama pori, ndege aina ya kwelea kwelea na viwavijeshi vamizi. Maeneo yanayotarajiwa kuwa na upungufu huo ni kama inavyoonekana katika Jedwali Na.4. Jedwali Na: 4. Halmashauri zenye Maeneo yenye Dalili ya Upungufu wa Chakula kwa Mwaka 2021/2022 Na Jina La Mkoa Idadi ya Halmashauri Jina la Halmashauri Kipindi cha Upungufu 1 Tanga 6 Korogwe DC, Korogwe TC, Handeni DC, Handeni TC, Kilindi, Mkinga Sept 2021-Machi 2022 2 Manyara 1 Mbulu DC Des 2021 -Machi 2022 3 Arusha 2 Monduli, Longido Okt 2021-Machi 2022 4 Kilimanjaro 2 Same, Mwanga Okt 2021-Machi 2022 5 Mara 2 Rorya, Musoma DC Okt 2021 - Feb 2022 6 Singida 2 Manyoni na Mkalama Sept 2021-Machi 2022 7 Simiyu 1 Meatu Jan 2022 -Machi 2022 8 Dodoma 1 Bahi Sept 2021-Machi 2022 JUMLA = 8 17 Chanzo: Tathmini ya HYC 2020/2021 NB: Pamoja na kwamba Mkoa wa Dar es Salaam unaonesha upungufu, Halmashauri zake hazioneshwi katika jedwali hili kwa kuwa siyo mkoa wa uzalishaji. Mkoa huo unapokea vyakula kutoka katika mikoa mingine. *Tahadhari inatolewa dhidi ya upungufu wa chakula unaoweza kujitokeza katika maeneo hayo katika kipindi cha 2021/2022. 19 SURA YA TANO 5.0 MWENENDO WA BEI KWA BAADHI YA MAZAO YA CHAKULA HADI KUFIKIA TAREHE 31 MEI, 2021 Hadi kufikia tarehe 31 Mei, 2021, upatikanaji wa chakula sokoni umeendelea kuwa mzuri ambapo bei za mazao ya chakula hususan mahindi, mchele na maharage zimeendelea kushuka ikilinganishwa na bei za mazao hayo katika kipindi kama hicho kwa mwaka 2020 Kielelezo Na: 7. Chanzo:Wizara ya Viwanda na Biashara, 2020 Kielelezo Na: 7. Mwenendo wa bei za mahindi, mchele na maharage kwa gunia la kilogramu 100 (Juni 2019-Mei 2021). Mlinganisho wa bei za mazao haya umezingatia mwaka wa chakula husika ambapo katika uchambuzi huu miaka iliyozingatiwa ni Juni 2019 hadi Mei 2020 na Juni, 2020 hadi Mei, 2021. Kwa kuzingatia mlinganisho huo, bei ya wastani kwa mazao ya mahindi na mchele haijatofautiana sana. Bei ya wastani ya mahindi kwa gunia la kilogramu 100 kwa mwaka wa chakula 2019/2020 ilikuwa juu ikilinganishwa na mwaka wa chakula 2020/2021. Mfano, hadi kufikia mwezi Mei 2020, bei ya mahindi kwa gunia la kilogramu 100 ilikuwa shilingi za kitanzania 56,355 ikilinganishwa na shilingi za kitanzania 43,466 kwa mwezi Mei, 2021. 20 Bei ya wastani ya mchele kwa gunia la kilogramu 100 kwa mwaka wa chakula 2019/2020 ilikuwa juu ikilinganishwa na mwaka wa chakula 2020/2021. Hadi kufikia, Mei 2020, bei ya mchele kwa gunia la kilogramu 100 ilikuwa shilingi za kitanzania 165,294 ikilinganishwa na shilingi za kitanzania 136,666 kwa mwezi Mei, 2021. Kwa ujumla, mwenendo wa bei ya maharage kwa kipindi cha kuanzia Juni, 2020 hadi Novemba, 2020 ilikuwa juu ikilinganishwa na bei ya kipindi kama hicho kwa mwaka 2019. Bei ya gunia la kilogramu 100 liliuzwa kuanzia shilingi 205,234 mwezi Juni 2020 hadi shilingi 207,382 mwezi Novemba 2020 ikilinganishwa na shilingi 164,587 Juni 2019 hadi shilingi 196,527 mwezi Novemba 2019. Hali hii ilichangiwa na mvua nyingi katika msimu wa uzalishaji wa 2019/2020 zilizosababisha zao hilo kuharibikia shambani na hivyo kuathiri uzalishaji wa zao hilo katika maeneo mengi ya nchi. Aidha, kuanzia kipindi cha mwezi Desemba 2020 hadi Mei 2021, mwenendo wa bei ya maharage ulikuwa chini ikilinganishwa na bei ya kipindi kama hicho kwa mwaka 2019/2020. Hali hii ilichangiwa na uzalishaji mzuri wa maharage katika msimu wa vuli wa 2020. Kutokana na mwelekeo mzuri wa uzalishaji wa mazao ya chakula ikiwemo mahindi, mchele na maharage, bei inatarajiwa kuendelea kushuka na hivyo kuimarisha utengamano wa upatikanaji wa chakula nchini. 21 SURA YA SITA 6.0 ATHARI ZA UGONJWA WA VIRUSI VYA KORONA (UVIKO-19) KATIKA UZALISHAJI WA MAZAO YA CHAKULA Ugonjwa wa UVIKO umekuwa tishio kubwa katika shughuli mbalimbali za kiuchumi ikiwemo shughuli za uzalishaji na usafirishaji wa mazao ya chakula duniani. Ugonjwa huo unaweza kuleta athari hasi katika masuala ya usalama wa chakula nchini hususan katika ngazi ya kaya. Taarifa mbalimbali zilizopatikana kutoka katika mikoa yote ya Tanzania bara, zimeonesha kuwa uzalishaji wa mazao ya chakula kwa msimu wa 2020/2021 haujaathiriwa na uwepo wa mlipuko wa ugonjwa huo hapa nchini. Hata hivyo, iwapo hali hii ya uwepo wa ugonjwa wa UVIKO-19 itaendelea katika nchi zinazozalisha pembejeo, shughuli za kilimo kwa msimu wa 2021/2022 zinaweza kuathiriwa katika upatikanaji wa pembejeo muhimu za kilimo kama vile mbegu, mbolea, viuatilifu na zana za kilimo. Hivyo basi, mikakati madhubuti inatakiwa ili kukabiliana na changamoto yoyote itakayoweza kujitokeza. 6.1 Mikakati ya Kuimarisha Uhakika wa Usalama wa Chakula katika kipindi cha UVIKO-19 (i) Kuboresha mifumo ya uhifadhi wa mazao ya chakula katika ngazi zote; (ii) Kuimarisha mfumo wa stakabadhi za mazao ghalani ili kuongeza viwango vya mazao kupunguza uharibifu; (iii) Kuendelea kuimarisha miundombinu ya umwagiliaji ili kuongeza upatikanaji wa chakula; (iv) Kufanya maandalizi mapema ya ununuzi wa pembejeo za kilimo kwa ajili ya msimu wa uzalishaji wa 2021/2022; (v) Kuendelea kuelimisha wananchi juu ya matumizi sahihi ya chakula katika ngazi ya kaya na; (vi) Kuendelea kujenga mazingira rafiki na wezeshi ya usafirishaji wa mazao ya chakula na bidhaa zake kwenda nje ya nchi. 22 SURA YA SABA 7.0 CHANGAMOTO Katika msimu wa uzalishaji 2020/2021, changamoto mbalimbali zilijitokeza na kusababisha kutofikiwa kwa malengo ya uzalishaji katika baadhi ya maeneo nchini. Changamoto hizo ni kama zilivyofafanuliwa hapo chini: (i) Mvua kuchelewa kunyesha na kuisha mapema katika baadhi ya maeneo na hivyo kusababisha kupungua kwa uzalishaji hususan mazao ya nafaka; (ii) Unyeshaji wa mvua juu ya kiwango uliosababisha kutokea kwa mafuriko na kutuama kwa maji katika baadhi ya maeneo hususan katika mikoa ya Kilimanjaro, Morogoro, Mbeya na Kagera. Hali hii imechangia kushuka kwa uzalishaji wa mazao hususan mpunga, jamii ya mikunde na mizizi katika maeneo hayo; (iii) Kuongezeka kwa gharama za uzalishaji uliotokana na upotevu wa mbolea ardhini (leaching) katika baadhi ya maeneo; (iv) Mvua za nje ya msimu zilisababisha uharibifu wa mazao yaliokuwa yamefikia hatua ya kukomaa hasa mpunga na maharage; (v) Hali ya vipindi virefu vya ukosefu wa mvua ilisababisha kupungua kwa uzalishaji hasa katika baadhi ya maeneo ya mikoa ya Morogoro, Katavi, Lindi, Arusha, Tanga, Mara, Mtwara na Kilimanjaro; (vi) Bei kubwa za pembejeo hasa mbolea na mbegu bora zimechangia kushuka kwa matumizi ya pembejeo na hivyo kuchangia kushuka kwa uzalishaji katika baadhi ya maeneo na; (vii) Uvamizi wa visumbufu hususan batobato kali, kwelea kwelea, tembo, kiboko na nguruwe pori kwenye baadhi ya mashamba nchini. 23 SURA YA NANE 8.0 HITIMISHO NA USHAURI Hali ya uzalishaji na upatikanaji wa mazao ya chakula nchini imeendelea kuwa nzuri katika kipindi cha zaidi ya miaka saba mfululizo kufuatia uzalishaji mzuri wa mazao ya chakula ikilinganishwa na mahitaji ya chakula nchini. Katika kipindi cha miaka ya chakula 2013/2014 na 2021/2022, nchi imekuwa na SSR kati ya asilimia 118 hadi 126 na imekuwa ikizalisha ziada kati ya tani 2,234,725 hadi tani 3,792,562. Mafanikio hayo yanatokana na sababu mbalimbali ikiwemo hali ya hewa nzuri pamoja na usimamizi na utekelezaji mzuri wa sera na mikakati mbalimbali ya Serikali pamoja na wadau wengine wa masuala ya kilimo na usalama wa chakula. Kwa mwaka wa uzalishaji 2020/2021, hali ya uzalishaji wa mazao ya chakula ni ya kuridhisha ambapo kwa mwaka wa chakula 2021/2022, nchi inatarajia kujitosheleza kwa asilimia 125. Kwa kuzingatia vigezo vya upimaji wa upatikanaji na mahitaji, kiwango hiki kinaashiria nchi itakuwa na ziada. Uzalishaji wa msimu huu haujatofautiana sana na msimu wa 2019/2020 ambapo kwa mwaka wa chakula wa 2020/2021 nchi ilifikia kiwango cha asilimia 126. Kutokana na matokeo ya Tathmini hii, ushauri ufuatao unapendekezwa: - (i) Kuendelea kuboresha Mfumo wa Uratibu wa Mazao na Tahadhari ya Awali ili kuwezesha upatikanaji wa takwimu na taarifa sahihi za usalama wa chakula nchini kwa wakati; (ii) Kuendelea kuwajengea uwezo wataalam wa kilimo katika ngazi ya Taifa, Mkoa na Halmashauri katika masuala ya takwimu za usalama wa chakula na kilimo; (iii) Kuboresha na kuhuisha vituo vya mvua ili kupata takwimu za unyeshaji wa mvua katika maeneo ya kilimo; (iv) Wananchi waendelee kuhamasishwa kuhifadhi chakula cha kutosha kwa ajili ya kaya zao; 24 (v) Ili kuongeza tija katika uzalishaji wa mazao ya kilimo, ruzuku iwekwe kwenye pembejeo ili kurahisisha upatikanaji na kuongeza matumizi sahihi; (vi) Biashara ya mazao ya chakula ndani na nje ya nchi iendelee kwa kufuata sheria na taratibu zilizopo; (vii) Wakala wa Taifa wa Hifadhi ya Chakula (NFRA), waanze ununuzi wa mazao mapema kwa ajili ya usalama wa chakula wa nchi; (viii) Bodi ya Nafaka na Mazao Mchanganyiko (CPB), iongeze kasi ya kufungua vituo vipya vya uuzaji wa mazao ya chakula ndani na nje ya nchi; (ix) Mamlaka za Mikoa na Halmashauri za pembezoni mwa nchi ziendelee kuimarisha udhibiti wa utoroshaji wa chakula nje ya nchi kupitia mipaka isiyo rasmi; (x) Kuendelea kuimarisha mfumo wa upatikanaji na usambazaji wa pembejeo na zana za kilimo katika ngazi zote; (xi) Kuendelea kuimarisha na kuongeza miundombinu ya umwagiliaji; (xii) Kufanya maandalizi mapema ya ununuzi wa pembejeo za kilimo kwa ajili ya msimu wa uzalishaji wa 2021/2022; (xiii) Wafanyabiashara waendelee kuhamasishwa kuwekeza katika viwanda vya kuchakata mazao ya chakula ili kuyaongezea thamani na kupata bei nzuri ndani na nje ya nchi na; (xiv) Kuendelea kuhamasisha sekta binafsi kuwekeza katika ujenzi wa maghala katika ngazi zote. VIAMBATISHO Kiambatisho Na:1a. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Nafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei, 2021 Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Tija Uzalishaji (Tani) Eneo (Hekta) Uzalishaji (Tani) Mkoa Arusha 122,974 1.6 196,758 23,613 0.8 19,339 534 1.4 739 52,847 2.4 126,833 4,000 2.8 11,259 3,760 1.8 6,642 207,728 361,570 Arusha Pwani 73,980 1.4 103,571 2,743 1.7 4,653 33,330 1.3 43,328 110,052 151,553 Pwani Dar es Salaam 388 1.0 388 538 0.8 430 926 818 Dar es Salaam Dodoma 125,858 1.0 125,858 169,992 1.1 185,414 4,012 1.0 3,820 118,442 1.1 125,846 5,213 2.7 14,075 423,517 455,012 Dodoma Iringa 130,008 2.0 260,016 7,414 0.7 5,133 3,627 1.0 3,688 17,577 2.8 49,214 1,802 2.3 4,081 160,427 322,132 Iringa Njombe 127,578 2.0 255,156 1,301 1.2 1,549 1,605 1.2 1,922 904 2.0 1,808 11,807 1.7 20,525 143,195 280,960 Njombe Kagera 93,765 1.4 131,271 9,789 1.1 10,480 2,498 1.2 2,931 452 1.0 456 19,142 1.1 21,056 125,646 166,194 Kagera Kigoma 215,754 2.1 453,083 5,230 2.5 13,320 600 1.6 969 27,234 2.0 54,468 248,817 521,841 Kigoma Kilimanjaro 106,726 2.1 224,124 663 0.7 449 529 1.0 523 13,489 2.7 36,420 1,087 3.9 4,211 1,610 2.0 3,220 124,103 268,947 Kilimanjaro Lindi 90,665 1.2 108,798 29,719 1.1 32,186 22,856 0.7 15,999 143,240 156,983 Lindi Manyara 270,694 1.7 460,180 13,213 1.7 22,396 4,065 1.5 5,977 1,138 1.4 1,596 6,578 2.2 14,472 7,115 1.4 9,679 86 2.0 172 302,889 514,471 Manyara Mara 88,680 1.7 150,756 57,010 1.5 85,553 5,400 0.7 3,644 686 0.9 639 11,143 1.5 16,715 162,919 257,306 Mara Mbeya 205,831 2.7 555,744 4,401 11,012 1,152 1,226 87,604 3.3 289,093 4,446 8,640 303,434 865,715 Mbeya Songwe 178,289 2.5 445,723 29,160 39,033 8,393 13,581 650 1,020 38,277 2.5 95,693 393 380 255,162 595,429 Songwe Morogoro 100,567 1.6 160,907 14,778 0.9 13,394 100 0.8 76 141 1.2 169 295,257 2.0 596,420 410,843 770,966 Morogoro Mtwara 54,578 1.1 60,036 15,748 1.0 15,115 439 0.7 324 26,554 0.7 18,588 97,319 94,063 Mtwara Mwanza 109,868 1.7 186,776 16,349 1.2 19,138 26 0.7 18 3,078 1.4 4,260 108,911 2.0 217,822 238,232 428,014 Mwanza Geita 99,543 1.7 169,223 7,200 1.0 7,514 413 0.9 386 1,032 1.2 1,189 106,227 1.7 180,585 214,413 358,897 Geita Rukwa 256,503 2.5 641,258 9,230 1.2 11,040 17,785 1.2 20,850 7 1.1 8 41,282 2.1 86,692 4,900 1.7 8,185 329,706 768,033 Rukwa Katavi 58,910 1.7 100,147 860 1.3 1,114 103 1.2 120 19 0.9 17 72,560 2.3 166,888 132,452 268,286 Katavi Ruvuma 290,488 3.2 929,560 875 1.0 859 7,000 0.8 5,928 51,652 1.1 58,874 2,782 1.2 3,328 352,796 998,550 Ruvuma Shinyanga 91,764 1.4 128,470 27,177 1.5 41,530 10,614 1.1 11,447 116,654 1.5 174,981 246,209 356,427 Shinyanga Simiyu 187,055 1.3 243,172 62,157 1.3 81,340 1,200 0.8 999 59,242 1.2 71,090 309,655 396,602 Simiyu Singida 179,453 1.1 197,398 71,840 1.2 88,607 9,968 1.7 16,539 40,621 1.1 45,013 11,173 1.2 13,408 313,055 360,965 Singida Tabora 200,614 1.5 300,920 22,137 1.4 31,884 148 0.8 113 114,622 2.1 240,706 337,520 573,624 Tabora Tanga 265,855 1.2 319,025 12,082 1.1 13,780 - - 10,374 2.3 23,860 288,311 356,666 Tanga Jumla 3,726,386 1.7 6,908,318 614,681 1.2 755,832 68,395 1.1 83,374 178,079 1.1 192,659 1,351,239 1.9 2,629,519 38,331 2.1 70,288 5,456 1.9 10,034 5,982,567 10,639,990 Jumla Uwele Mchele Ngano Jumla Tathmini ya Awali ya Uzalishaji (Tani) Kimkoa kwa Msimu wa 2020/2021 (Kufikia Tarehe 31 Mei 2021) Nafaka ( Eneo (Hekta), Tija na Uzalishaji (Tani) kwa Hekta) Mkoa Mahindi Shayiri Mtama Ulezi Chanzo: Tathmini ya HYC 2020/2021 24 26 Kiambatisho Na:1b. Tathmini ya Awali ya Uzalishaji (Tani) Mazao ya Yasiyonafaka Kimkoa kwa Msimu wa 2020/2021 kufikia tarehe 31 Mei,2021 Chanzo: Tathmini ya HYC 2020/2021 Kiambatisho Na:2. Kiwango cha mvua na mtawanyiko wake kwa kila mwezi katika msimu wa mvua 2020/2021. 28 29 Chanzo: TMA, GeoWRSI 2020/2021 30 Kiambatisho Na:3. Kiwango cha Uwiano wa Uzalishaji na Mahitaji ya Chakula (SSR) Msimu wa 2020/2021 Chanzo: Tathmini ya Awali ya Uzalishaji wa Mazao ya Chakula Msimu wa 2019/2020 na Upatikanaji wa Chakula kwa Mwaka 2020/2021. | false |
# Extracted Content 1 Sehemu ya Masoko ya Mazao ya Kilimo Jamhuri ya Muungano wa Tanzania Wizara ya Kilimo Sehemu ya Masoko ya Mazao ya Kilimo TAARIFA YA WIKI YA MWENENDO WA BEI ZA MAZAO Septemba 06-10, 2021 Jedwali 1: Wastani wa bei za jumla Kitaifa (TZS/Kilo 100) Wiki iliyopita Agost 30-Septemba 03 Wiki hii Septemba 06-10 Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Wiki hii 41,700 134,000 162,100 86,600 106,600 154,000 59,700 Wiki iliyopita 41,900 133,100 163,400 87,100 102,600 145,900 59,800 Badiliko ▼0.5% ▲0.7% ▼0.8% ▼0.6% ▲3.8% ▲5.3% ▼0.2% Wastani wa Nchi Ujumbe Mkuu Kwa ujumla, zimebadilika kiasi kidogo ikilinganishwa na viwango vya bei wiki iliyopita. Bei za mahindi, maharage, mtama, na viazi zimepungua kwa asilimia 0.5, 0.8, 0.6 na 0.2 mtawalia. Hata hivyo, bei ya mchele,uwele na ulezi iliongezeka kwa kiasi cha asilimia 0.7,3.8 na 5.3 mtawalia. Bei za mazao makuu ya chakula zinategemewa kubadilika kwa viwango vidogo wiki inayofuata. Upatikanaji wa mazao katika masoko ni wa kuridhisha kutokana na kuendelea kwa msimu wa mavuno. Tumbaku: Hadi kufikia tarehe 22 Agosti, 2021 kiasi cha tumbaku kilichouzwa ni Kilo 55,722,247 zenye thamani ya Dola za Marekeni Milioni 86.4. Pamba: Hadi kufikia tarehe 29 Agosti, 2021, pamba iliyouzwa kwa msimu wa mauzo 2021/2022 ni kilo 138, 482,490. Mbaazi: Hadi kufikia tarehe 02 Septemba, 2021, mbaazi zilizouzwa kwa msimu wa mauzo 2021/2022 ni kilo 3,572,532 zenye thamani ya Shilingi Bilioni 4.68 2 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 2: Wastani wa bei za jumla kwa Mikoa (TZS/Kilo 100) Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Dodoma Wiki hii 38,700 142,500 185,000 50,200 49,500 122,500 62,000 Wiki iliyopita 39,300 142,500 182,500 48,500 48,500 120,000 63,000 Badiliko ▼1.6% ►0.0% ▲1.4% ▲3.4% ▲2.0% ▲2.0% ▼1.6% Arusha Wiki hii 47,000 160,000 155,000 67,500 70,000 NA 42,500 Wiki iliyopita 47,500 160,000 155,000 69,000 71,000 NA 42,500 Badiliko ▼1.1% ►0.0% ►0.0% ▼2.2% ▼1.4% ►0.0% Dar es Salaam Wiki hii 50,300 155,000 211,700 85,000 80,000 157,500 52,300 Wiki iliyopita 51,200 155,000 211,700 82,500 76,300 160,000 51,700 Badiliko ▼1.8% ►0.0% ►0.0% ▲2.9% ▲4.6% ▼1.6% ▲1.1% Morogoro Wiki hii 39,500 170,000 180,000 120,000 120,000 160,000 70,000 Wiki iliyopita 39,500 150,000 182,500 120,000 115,000 160,000 74,000 Badiliko ►0.0% ▲11.8% ▼1.4% ►0.0% ▲4.2% ►0.0% ▼5.7% Tanga Wiki hii 44,000 145,000 165,000 85,000 100,000 170,000 45,000 Wiki iliyopita 43,100 145,000 160,000 95,000 100,000 NA 45,500 Badiliko ▲2.0% ►0.0% ▲3.0% ▼11.8% ►0.0% ▼1.1% Ruvuma Wiki hii 26,000 170,000 120,000 NA NA NA 73,500 Wiki iliyopita 27,000 175,000 130,000 NA NA NA 73,800 Badiliko ▼3.8% ▼2.9% ▼8.3% ▼0.4% Iringa Wiki hii 34,000 160,000 145,000 90,000 NA 150000 50,000 Wiki iliyopita 34,000 160,000 145,000 90,000 NA 150000 50,000 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Njombe Current 36,500 145,000 152,000 NA NA 125,500 31,300 Previous week 36,500 145,000 152,000 NA NA 125,500 31,300 Change ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Rukwa Wiki hii 31,500 105,000 170,000 NA NA 175,000 65,000 Wiki iliyopita 34,300 105,000 173,800 NA NA 142,500 65,000 Badiliko ▼8.9% ►0.0% ▼2.2% ▲18.6% ►0.0% 3 Sehemu ya Masoko ya Mazao ya Kilimo Mkoa Wiki Mahindi Mchele Maharage Mtama Uwele Ulezi Viazi mviringo Katavi Wiki hii 33,000 90,000 175,000 60,000 NA 165,000 45,000 Wiki iliyopita 31,300 90,000 175,000 60,000 NA 165,000 45,000 Badiliko ▲5.2% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Tabora Wiki hii 35,500 102,500 170,000 145,000 NA 175,000 62,500 Wiki iliyopita 35,500 102,500 170,000 145,000 NA 175,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% Zingatia: ✓ Bei hizi ni za wastani kwa masoko ya jumla. ✓ Alama (▲▼►) zinaelezea mabadiliko ya bei: (▲) bei imeongezeka; (▼) bei imepungua; (►) hakuna mabadiliko au mabadiliko ni chini ya asilimia moja. ✓ N/A bei haikupatikana Chanzo cha takwimu: Wizara ya Kilimo na Wizara ya Viwanda na Biashara Kigoma Wiki hii 47,200 93,500 125,000 80,000 NA 145,000 55,000 Wiki iliyopita 47,200 88,500 135,000 80,000 NA 150,000 55,000 Badiliko ►0.0% ▲5.3% ▼8.0% ►0.0% ▼3.4% ►0.0% Kagera Wiki hii 55,000 130,000 130,000 125,000 155,000 155,000 60,000 Wiki iliyopita 54,500 135,000 130,000 125,000 127,500 150,000 60,000 Badiliko ▲0.9% ▼3.8% ►0.0% ►0.0% ▲17.7% ▲3.2% ►0.0% Mara Wiki hii 62,500 105,000 195,000 62,500 190,000 190,000 92,500 Wiki iliyopita 62,500 105,000 195,000 62,500 190,000 125,000 92,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲34.2% ►0.0% Manyara Wiki hii 45,000 150,000 135,000 70,000 90,000 125,000 65,000 Wiki iliyopita 45,000 150,000 135,000 70,000 90,000 125,000 62,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ▲3.8% Shinyanga Wiki hii 43,500 110,000 175,000 115,000 105,000 115,000 85,000 Wiki iliyopita 43,500 110,000 177,500 115,000 105,000 115,000 85,000 Badiliko ►0.0% ►0.0% ▼1.4% ►0.0% ►0.0% ►0.0% ►0.0% Mtwara Wiki hii 40,000 145,000 167,500 57,500 NA 180,000 57,500 Wiki iliyopita 40,000 145,000 167,500 57,500 NA 180,000 57,500 Badiliko ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% ►0.0% 4 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 3: Bei za mchele na mahindi kwa masoko ya Uganda (TZS/Kilo) Mchele Mahindi Bei ya chini Bei ya juu Bei ya chini Bei ya juu Uganda (bei za jumla) 1,750 1,900 470 500 Uganda (bei za rejareja) 1,900 2,185 820 900 Chanzo: https://farmgainafrica.org/ Tarehe 10 Septemba, 2021 Jedwali 4A: Mauzo ya tumbaku katika msimu wa 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 kwa kampuni AINA YA TUMBAKU KAMPUNI KILO ZA MKATABA MASOKO YALIYOTHAMINISHWA MPAKA SASA (CUMMULATIVE) BELO KG THAMANI(USD) BEI YA WASITANI (USD/KG) (USD) VFC Alliance One Tobacco Tanzania Ltd 20,040,000 410,978 18,857,569 28,307,316 1.50 JTI Leaf Services Ltd 14,460,000 297,865 14,074,601 24,034,375 1.71 Premium Active Tanzania Ltd 16,000,000 287,194 13,488,012 20,740,505 1.54 Pachtec Company Ltd 4,461,838 57,284 2,609,127 3,627,934 1.39 Mo Green International Company Limited 2,800,000 36,017 1,677,408 2,545,870 1.52 Naile Leaf (T) Co. Ltd 2,535,000 43,336 1,851,806 2,775,124 1.50 Grand Tobacco Limited 1,815,000 Magefa Growers Ltd 4,400,000 40,179 1,755,989 2,414,887 1.38 Jespan Company Ltd 760,000 9,865 486,296 661,391 1.36 ENV Services Ltd 800,000 7,932 360,503 520,860 1.44 Biexen Company Limited 29,145 717 29,145 40,041 1.37 JUMLA NDOGO 68,071,838 1,191,367 55,190,456 85,668,303 1.55 DFC Premium Active Tanzania Ltd 500,000 11,022 531,792 698,768 1.31 JUMLA KUU 68,571,838 1,202,389 55,722,247 86,367,071 1.55 5 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali 4B: Mauzo ya tumbaku (kimkoa) katika msimu wa masoko 2021/2022 hadi kufikia tarehe 22 Agosti, 2021 Mkoa Kilo za Mkataba Kiasi cha tumbaku kilichonunuliwa Belo Kilo Katavi 7,350,000 141,785 6,229,618 Mbeya 10,280,000 167,660 8,067,643 Songwe 670,000 12,953 624,655 Kigoma 4,705,000 93,825 4,194,878 Tabora 32,546,838 575,479 26,682,758 Shinyanga 9,930,000 162,321 7,648,131 Geita 1,070,000 17,809 871,093 Kagera 70,000 1,180 58,557 Iringa 200,000 2,446 157,631 Singida 1,250,000 15,909 655,493 Jumla ya VFC 68,071,838 1,191,367 55,190,456 Ruvuma (DFC) 500,000 11,022 531,791.96 JUMLA KUU (DFC+VFC) 68,571,838 1,202,389 55,722,247 Jedwali 5: Ununuzi na usafirishaji wa pamba kwa msimu 2021/22 wiki na. 16 kuishia tarehe 29Agosti, 2021. UNUNUZI USAFIRISHAJI JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) JUMLA YA WIKI YA NYUMA (Kilo) KWA WIKI HII (Kilo) JUMLA (Kilo) 133,918,964 4,563,526 138, 482,490 133,918,964 4,563,526 138, 482,490 Chanzo: Bodi ya Pamba, 2021 6 Sehemu ya Masoko ya Mazao ya Kilimo Jedwali :6 Mauzo ya mbaazi hadi tarehe 25 Agosti 2021 Tarehe Wilaya Chama cha Ushirika Kampuni Kilo Shilingi/Kilo Jumla Ndogo (Shilingi) 11/08/2021 Namtumbo Ushirika B Afrisian Ginning 41,428 1,280 53,027,840 12/08/2021 Tunduru Mtetesi MeTL 150,000 1,300 195,000,000 Mtetesi RBST 210,251 1,290 271,223,790 18/08/2021 Namtumbo Ushirika B MeTL 206,517 1,320 272,602,440 Ushirika B LENIC 200,000 1,320 264,000,000 19/08/2021 Tunduru Asema LENIC 300,000 1,344 403,200,000 Asema LENIC 845,498 1,340 1,132,967,320 25/08/2021 Namtumbo Namtumbo LENIC 819,149 1,380 1,130,425,620 02/09/2021 Tunduru Naluwale MeTL 280,000 1,203 336,840,000 Naluwale LENIC 519,689 1,200 623,626,800 JUMLA KUU 3,572,532 4,682,913,810 Jedwali 7: Miezi sahihi ya kupanda na kuvuna ili kupata bei nzuri Zao Wakati unaofaa kuvuna Wakati usiofaa kuvuna Wakati unaofaa kupanda Vitunguu Feb- Julai Julai- Nov Sept- Des Nyanya Jan- Mei Des - Juni Sept- Des Hoho kijani Feb- Aprili Juni - Jan Okt- Nov Karoti Okt- Machi Sep - Apr Julai- Okt Matango Feb- Mei Mei - Jan Des- Jan Viazi mviringo Machi- Juni Julai - Jan Des- Feb Tikiti maji Machi- Aprili, Oktoba - Desemba Mei- Sep, Des- Feb Jan- Feb, Ago- Sept Hoho za rangi Jun- Nov Mei - Des Feb- Machi Tangawizi Aprili- Julai Machi - Aug Des- Feb 7 Sehemu ya Masoko ya Mazao ya Kilimo Habari Muhimu ✓ Mwezi Agosti, Serikali ya Tanzania imetoa jumla ya shilingi bilioni 19 kwa Wakala wa Taifa wa Hifadhi ya Chakula (NFRA) na Bodi ya Nafaka na Mazao Mchanganyiko (CPB) kwa ajili ya ununuzi wa mahindi. ✓ Wizara ya Kilimo imeanzisha jukwaa la soko la mtandaoni (M-Kilimo) ili kuwezesha upatikanaji wa masoko kwa wakulima na wafanyabiashara. Tembelea M-Kilimo - MarketPlace ✓ Utabiri wa Hali ya hewa Oktoba-Desemba 2021. o Mvua za vuli zinatarajiwa kuwa chini ya kawaida na vipindi virefu vya ukavu. o Msimu wa mvua za vuli unatarajiwa kuwa hafifu kwa wiki ya tatu na ya nne ya mwezi Oktoba 2021 na usambaaji duni katika maeneo mengi. o Mbali na uwepo wa mvua chini ya kiwango, joto kali kuliko kawaida linatarajiwa katika maeneo yanayopata mvua mara mbili (bimodal) wakati wa msimu wa mvua za vuli. o Ili kupata taariza za kina tembelea |Tanzania Meteorological Authority Kwa maelezo zaidi wasiliana na: Mkurugenzi Msaidizi, Sehemu ya Masoko ya Mazao, Wizara ya Kilimo, S.L.P 2182, DODOMA. Barua pepe: [email protected] Simu: +255 686 107 673 / +255 713 309 122 | false |
# Extracted Content Tanzania Agriculture Sample Census United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vr: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government December 2007 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vn: REGIONAL REPORT: TABORA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar September 2006 TOC i ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census TABLE OF CONTENTS Table of contents................................................................................................................................................................i Acronyms.......................................................................................................................................................................... v Preface..............................................................................................................................................................................vi Executive summary.........................................................................................................................................................vii Illustrations......................................................................................................................................................................xii ENSUS RESULTS AND ANALYSIS PART I: BACKGROUND INFORMATION........................................................................................................ 1 1.1 Introduction ...................................................................................................................................................... 1 1.2 Geographical Location and Boundaries............................................................................................................. 1 1.3 Land Area.......................................................................................................................................................... 1 1.4 Climate............................................................................................................................................................... 1 1.4.1 Temperature......................................................................................................................................... 1 1.4.2 Rainfall................................................................................................................................................. 1 1.5 Population ......................................................................................................................................................... 1 1.6 Socio-economic Indicators............................................................................................................................... 1 PART II: INTRODUCTION...................................................................................................................................... 2 2.1 The Rationale for Conducting the National Sample Census of Agriculture............................................. 2 2.2 Census Objectives............................................................................................................................................. 2 2.3 Census Coverage and Scope............................................................................................................................ 3 2.4 Legal Authority of the National Sample Census of Agriculture................................................................. 4 2.5 Reference Period .............................................................................................................................................. 4 2.6 Census Methodology........................................................................................................................................ 4 2.6.1 Census Organization............................................................................................................................ 5 2.6.2 Tabulation Plan.................................................................................................................................... 5 2.6.3 Sample Design..................................................................................................................................... 5 2.6.4 Questionnaire Design and Other Census Instruments ........................................................................ 6 2.6.5 Field Pre-Testing of the Census Instruments...................................................................................... 6 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................... 6 2.6.7 Information, Education and Communication (IEC) Campaign.......................................................... 6 2.6.8 Household Listing................................................................................................................................ 7 2.6.9 Data Collection .................................................................................................................................... 7 2.6.10 Field Supervision and Consistency Checks ........................................................................................ 7 2.6.11 Data Processing ................................................................................................................................... 8 - Manual Editing............................................................................................................................... 8 - Data Entry ...................................................................................................................................... 8 - Data Structure Formatting ............................................................................................................. 8 - Batch Validation ............................................................................................................................ 8 - Tabulations..................................................................................................................................... 8 - Analysis and Report Preparations ................................................................................................. 9 - Data Quality................................................................................................................................... 9 2.7 Funding Arrangements.............................................................................................................................. 9 PART III: CENSUS RESULTS AND ANALYSIS.................................................................................................. 10 3.1 Holding Characteristics................................................................................................................................. 10 3.1.1 Type of Holdings............................................................................................................................... 10 3.1.2 Livelihood Activities/Source of Income........................................................................................... 10 3.1.3 Sex and Age of Heads of Households............................................................................................... 14 3.1.4 Number of Household Members....................................................................................................... 14 3.1.5 Level of Education............................................................................................................................. 14 - Literacy ........................................................................................................................................ 14 - Literacy Level for Household Members ..................................................................................... 14 - Literacy Rates for Heads of Households..................................................................................... 15 - Educational Status........................................................................................................................ 15 3.1.6 Off-farm Income................................................................................................................................ 16 TOC ii ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.2 Land Use ...................................................................................................................................................... 16 3.2.1 Area of Land Utilised ........................................................................................................................ 17 3.2.2 Types of Land use.............................................................................................................................. 17 3.3 Annual Crops and Vegetable Production.................................................................................................... 17 3.3.1 Area Planted....................................................................................................................................... 18 3.3.2 Crop Importance................................................................................................................................ 18 3.3.3 Crop Types......................................................................................................................................... 19 3.3.4 Cereal Crop Production..................................................................................................................... 19 3.3.4.1 Maize ............................................................................................................................... 19 3.3.4.2 Paddy ............................................................................................................................... 22 3.3.4.3 Other Cereals................................................................................................................... 23 3.3.5 Roots and Tuber Crops Production................................................................................................... 23 3.3.5.1 Cassava............................................................................................................................ 23 3.3.5.2 Sweet Potatoes................................................................................................................. 26 3.3.6 Pulse Crops Production ..................................................................................................................... 27 3.3.6.1 Beans................................................................................................................................ 27 3.3.7 Oil Seed Production........................................................................................................................... 30 3.3.7.1 Groundnuts ...................................................................................................................... 30 3.3.8 Fruits and Vegetables ........................................................................................................................ 31 3.3.8.1 Onions.............................................................................................................................. 33 3.3.8.2 Tomatoes ......................................................................................................................... 33 3.3.8.3 Amaranths........................................................................................................................ 34 3.3.8.4 Cabbage ........................................................................................................................... 34 3.3.9 Other Annual Crops Production........................................................................................................ 34 3.3.9.1 Tobacco ........................................................................................................................... 34 3.3.9.2 Cotton .............................................................................................................................. 39 3.4 Permanent Crops............................................................................................................................................ 39 3.4.1 Mango ......................................................................................................................................... 40 3.4.2 Palm Oil ......................................................................................................................................... 40 3.4.3 Banana ......................................................................................................................................... 40 3.4.4 Pawpaw ......................................................................................................................................... 41 3.5 Inputs/Implements Use.................................................................................................................................. 42 3.5.1 Methods of land clearing................................................................................................................... 42 3.5.2 Methods of soil preparation............................................................................................................... 42 3.5.3 Improved seeds use............................................................................................................................ 48 3.5.4 Fertilizers use..................................................................................................................................... 48 3.5.4.1 Farm Yard Manure Use................................................................................................... 49 3.5.4.2 Inorganic Fertilizer Use................................................................................................... 50 3.5.4.3 Compost Use ................................................................................................................... 51 3.5.5 Pesticide Use...................................................................................................................................... 51 3.5.5.1 Insecticide Use................................................................................................................. 52 3.5.5.2 Herbicide Use.................................................................................................................. 52 3.5.5.3 Fungicide Use.................................................................................................................. 53 3.5.6 Harvesting Methods........................................................................................................................... 54 3.5.7 Threshing Methods .......................................................................................................................... 54 3.6 Irrigation .................................................................................................................................................... 54 3.6.1 Area planted with annual crops and under irrigation........................................................................ 54 3.6.2 Sources of water used for irrigation.................................................................................................. 55 3.6.3 Methods of obtaining water for irrigation......................................................................................... 55 3.6.4 Methods of water application ........................................................................................................... 56 TOC iii ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.7 Crop Storage, Processing and Marketing ................................................................................................... 56 3.7.1 Crop Storage ...................................................................................................................................... 56 3.7.1.1 Method of Storage........................................................................................................... 56 3.7.1.2 Duration of Storage ......................................................................................................... 58 3.7.1.3 Purpose of Storage........................................................................................................... 58 3.7.1.4 The Magnitude of Storage Loss...................................................................................... 59 3.7.2 Agro processing and by-products...................................................................................................... 59 3.7.2.1 Processing Methods......................................................................................................... 59 3.7.2.2 Main Agro-processing Products...................................................................................... 60 3.7.2.3 Main use of primary processed Products........................................................................ 60 3.7.2.4 Outlet for Sale of Processed Products............................................................................. 61 3.7.3 Crop Marketing.................................................................................................................................. 61 3.7.3.1 Main Marketing Problems............................................................................................... 62 3.7.3.2 Reasons for Not Selling................................................................................................... 62 3.8 Access to Crop Production Services............................................................................................................. 62 3.8.1 Access to Agricultural Credits .......................................................................................................... 62 3.8.1.1 Source of Agricultural Credits ........................................................................................ 63 3.8.1.2 Use of Agricultural Credits............................................................................................. 63 3.8.1.3 Reasons for not using agricultural credits....................................................................... 63 3.8.2 Crop Extension .................................................................................................................................. 65 3.8.2.1 Sources of crop extension messages............................................................................... 65 3.8.2.2 Quality of extension ........................................................................................................ 66 3.9 Access to Inputs ............................................................................................................................................. 66 3.9.1 Inorganic Fertilisers .......................................................................................................................... 66 3.9.2 Improved Seeds ................................................................................................................................. 67 3.9.3 Insecticides and Fungicide ................................................................................................................ 67 3.10 Tree Planting................................................................................................................................................... 68 3.11 Irrigation and Erosion Control Facilities ................................................................................................... 69 3.12 Livestock Results............................................................................................................................................ 72 3.12.1 Cattle Production .............................................................................................................................. 72 3.12.1.1 Cattle Population............................................................................................................. 72 3.12.1.2 Herd size.......................................................................................................................... 72 3.12.1.3 Cattle Population Trend .................................................................................................. 73 3.12.1.4 Improved Cattle Breeds................................................................................................... 73 3.12.2 Goat Production................................................................................................................................. 73 3.12.2.1 Goat Population............................................................................................................... 73 3.12.2.2 Goat Herd Size ................................................................................................................ 74 3.12.2.3 Goat Breeds ..................................................................................................................... 74 3.12.2.4 Goat Population Trend .................................................................................................... 74 3.12.3 Sheep Production............................................................................................................................... 74 3.12.3.1 Sheep Population............................................................................................................. 74 3.12.3.2 Sheep Population Trend .................................................................................................. 75 3.12.4 Pig Production ................................................................................................................................... 75 3.12.4.1 Pig Population Trend....................................................................................................... 75 3.12.5 Chicken Production ........................................................................................................................... 75 TOC iv ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census 3.12.5.1 Chicken Population ......................................................................................................... 76 3.12.5.2 Chicken Population Trend............................................................................................... 76 3.12.5.3 Chicken Flock Size.......................................................................................................... 76 3.12.5.4 Improved Chicken Breeds (layers and broilers)............................................................. 82 3.12.6 Other Livestock ................................................................................................................................. 82 3.12.7 Pests and Parasites Incidences and Control ..................................................................................... 82 3.12.7.1 Deworming...................................................................................................................... 83 3.12.8 Access to Livestock Services ............................................................................................................ 83 3.12.8.1 Access to livestock extension Services........................................................................... 83 3.12.8.2 Access to Veterinary Clinic ............................................................................................ 84 3.12.8.3 Access to village watering points/dam ........................................................................... 84 3.12.9 Animal Contribution to Crop Production.......................................................................................... 85 3.12.9.1 Use of Draft Power.......................................................................................................... 85 3.12.9.2 Use of Farm Yard Manure .............................................................................................. 85 3.12.9.4 Use of Compost ............................................................................................................. 86 3.12.10 Fish Farming...................................................................................................................................... 86 3.13 Poverty Indicators......................................................................................................................................... 87 3.13.1 Access to Infrastructure and Other Services..................................................................................... 87 3.13.2 Type of Toilets................................................................................................................................... 87 3.13.3 Household’s assets............................................................................................................................. 87 3.13.4 Sources of Light Energy.................................................................................................................... 91 3.13.5 Sources of Energy for Cooking......................................................................................................... 91 3.13.6 Roofing Materials.............................................................................................................................. 91 3.13.7 Access to Drinking Water ................................................................................................................. 92 3.13.8 Food Consumption Pattern................................................................................................................ 92 3.13.8.1 Number of Meals per Day............................................................................................... 92 3.13.8.2 Meat Consumption Frequencies...................................................................................... 93 3.13.8.3 Fish Consumption Frequencies....................................................................................... 93 3.13.9 Food Security..................................................................................................................................... 93 3.13.10 Main Source of Cash Income............................................................................................................ 94 PART IV: TABORA PROFILES ............................................................................................................................... 98 4.1 Region Profile ................................................................................................................................................. 98 4.2 District Profiles............................................................................................................................................... 98 4.2.1 Nzega ................................................................................................................................................. 98 4.2.2. Igunga ..............................................................................................................................................100 4.2.3 Uyui..................................................................................................................................................102 4.2.4 Urambo ............................................................................................................................................104 4.2.5 Sikonge ............................................................................................................................................106 4.2.6 Tabora Urban...................................................................................................................................108 ACRONYMS v __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ____________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics, Tanzania Mainland and the Office of the Chief Government Statistician, Tanzania Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the President’s Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (data on household characteristics and livestock count were collected in 1993/1994 while data on crop area and production were collected in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Tabora region data disaggregated to district level. Due to numerous variables collected, the analysis is based on the most important smallholder variables. More variables can be found in the table of results annex. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Special thanks should go to all those who in one-way or the other contributed to the success of the survey. In particular, I would like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician, Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Finally, let me extend my sincere gratitude to all professional staff of the National Bureau of Statistics and Office of the Chief Government Statistician, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. I am also indepted to the respondents, particularly the heads of households, for spending much of their valuable time in providing data and all necessary information during enumeration. Certainly without their dedication, the census would not have been successful. Albina A. Chuwa Director General, National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Tabora region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings on agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Tabora region. Included are activities’ indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Tabora region were 235,917 out of which 148,046 (62.8%) were involved in growing crops only, 296 (0.1%) rearing livestock only, and 87,575 (37.1%) were involved in crop production as well as livestock keeping. In summary, Tabora region had 235,621 households involved in crop production and 87,871 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock keeping/herding ,permanent crop farming, remittances and fishing/hunting and gathering. The region had a literacy rate of 52.5 percent. The highest literacy rate was in Tabora Urban district (67.4%) followed by Urambo district (56.0%) and Sikonge district (55.7%). Igunga, Uyui and Nzega districts had the lowest literacy rates of 53.3 percent, 51.8 percent and 46.0 percent respectively. The literacy rate for the heads of households in the region was 58.9 percent. The number of heads of agricultural households with formal education in Tabora region was 135,084 (57.3%), those without formal education were 97,767 (41.4%) and those with only adult education were 3,066 (1.3%). The majority of heads of agricultural households (54%) had primary level education whereas only 3 percent had higher than post primary level education. In Tabora region, of the households with at least one household member engaged in off-farm income generating activity, 117,453 household members (50%) had only one member engaged in an off-farm income generating activity, 52,284 (22%) had two members involved in off-farm income generating activities and 37,162 (16%) had more than two members involved in off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 899,225 ha. The regional average land area utilised for crop production per crop growing household was only 2.6 ha. This figure is slightly above the national average of 2.0 hectares. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census viii Planted Area The area planted with annual crops and vegetables was 532,615 hectares. The area planted with permanent crops was 9,929 hectares (1.8% of the total planted area). An estimated area of 347,455 ha (65.2% of the total planted area with annual and vegetable crops) was with cereals, followed by 69,862 hectares (13.1%) of oil seeds, 54,948 ha (10.3%) of cash crops, 31,535 ha (5.9%) of root and tuber crops, 25,911 ha (4.9%) of pulses and 2,904 ha (0.5%) of fruits and vegetables. Maize Maize was the dominant annual crop grown in Tabora region and it had a planted area 3.4 times greater than groundnuts, which had the second largest planted area. The area planted with maize constitutes 44 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) were paddy, sorghum, tobacco, cotton, cassava, beans, sweet potatoes, bulrush millet, finger millet, simsim and sunflower. There was 62 percent decrease in maize production in 1996/97 followed by a 36 percent increase in maize production the following year (1997/98). The total production of maize in 2002/03 was 143,122 tonnes. The average area planted with maize per household ranged from 0.8 hectares in Nzega and Tabora Urban to 1.3 hectares in Igunga District. Igunga district had the largest planted area for maize (56,579 ha) followed by Nzega (52,986 ha), Uyui (46,418 ha), Urambo (46,076 ha), Sikonge (22,958 ha) and Tabora (7,844 ha). Paddy Paddy was the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tabora region during the long rainy season was 92,037. This represented 39 percent of the total crop growing households in Tabora Region in the long rainy season. Cassava The area planted with cassava was larger than that of any other root and tuber crop in Tabora region accounted for 4 percent of the total area planted with annual crops and vegetables and accounted for 68 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 5,847 tonnes. The most cultivated fruit and vegetable crop was onions with a production of 2,550 tonnes (44% of the total fruits and vegetables produced) followed by tomatoes 2,522 tonnes (43%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The smallholders’ planted area with permanent crops was 9,929 hectares which was 1.9 percent of the area planted with crops in the region. The most important permanent crop was mango which accounted for 38 percent of the total area planted with permanent crops followed by palm oil (22%), banana (16%) and pawpaw (7%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census ix Improved Seeds The planted area using improved seeds was 88,125 ha which represented 17 percent of the total area planted with annual crops and vegetables. Use of Fertilizers Most annual crop growing households did not use any fertilisers. The area planted without fertiliser for annual crops was 352,800 hectares representing 66 percent of the total area planted with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 101,423 ha which represented 56% of the planted area applied with fertilisers. This was followed by inorganic fertilizers (64,675 ha, 36%). Compost manure was used on a small area which represented only 8 percent of the area planted with fertilizers. Irrigation In Tabora region, the area of annual crops and vegetables under irrigation was 34,866 ha representing 7 percent of the total planted area. Crop Storage There were 217,899 crop growing households (92.4% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 206,605 households storing 28,060 tonnes as of 1st January 2004. This was followed by paddy (76,850 households and 11,758 tonnes), groundnuts /bambara nuts (111,290 households and 6,695 tonnes) and sorghum and millet (21,828 households and 6,195 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 131,403 which represent 55.7 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Urambo (80.3%) followed by Sikonge (62.2%), Uyui (53.0%), Igunga (47.9%), Tabora Urban (45.5%) and Nzega (42.1%). Agricultural Credit In Tabora region, few agricultural households (25,655, 10.9%) accessed credit, out of which 24,679 (96%) were male- headed households and 977 (4%) were female headed households. In Nzega, Igunga and Urambo districts only male headed households got credit for agriculture purposes, whereas in Sikonge and Tabora Urban both male and female headed households accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 62,956 (27% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.108). Tabora Urban had a relatively high proportion of households that received crop extension messages (73%), followed by Uyui (30%), Sikonge (27%), Urambo (25%), Nzega (24%) and Igunga (19%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities on their farms was 5,399. This number represented 2.3 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Tabora Urban District (7.1%) followed by Uyui (4.9%), Nzega (2.5%), Urambo (1.8%), Sikonge (1.8%) and Igunga (0.2%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census x iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 1,568,691. Cattle were the dominant livestock type in the region followed by goats, sheep and pigs. The region had 9.1 percent of the total cattle population on Tanzanian Mainland. The number of indigenous cattle was 1,566,169 head (98.8% of the total number of cattle in the region), 1,851 (0.12 %) were dairy breeds and only 671 (0.04 %) were beef breeds. Goats The number of goat-rearing-households in the region was 65,167 (27.6 % of all agricultural households) with a total of 718,996 goats giving an average of 11 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 28,126 (12% of all agricultural households) with a total of 235,213 sheep giving an average of 8 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,614 (1.2% of the total agricultural households) rearing about 6,286 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 168,339 raising 2,507,469 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country Tabora ranked fourth out of the 21 Mainland regions. Use of Draft Power The region had 370,495 oxen and they were found in all districts as follows: Igunga (162,466), Nzega (120,742), Uyui (42,341), Urambo (25,202), Sikonge (15,992) and Tabora Urban (3,752). Tabora region has 6 percent of the total 4,195,100 head of oxen found on the Mainland and were used to cultivate 223,878 hectares of land. Fish Farming The number of households involved in fish farming was 222 (0.1 percent of the total agricultural households in the region). Sikonge and Uyui were the leading districts each with 98 agricultural households involved in fish farming (44%) followed by Tabora Urban 26 (2%). Fish farming was not practiced in Nzega, Igunga and Urambo districts. iv) Poverty Indicators Availability of Toilets It was estimated that 81.2 percent of all rural agricultural households used the traditional pit latrines, 1.0 percent used flush toilets and 0.8 percent used improved pit latrines. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represented 16.9 percent of the total agriculture households in the region. Household Assets Out of all assets bicycle were owned by most households (69.7% of households) followed by radio (53.7%), iron (17.8%), wheelbarrow (5.4%), vehicle (1.4%), mobile phone (1.0%), television/video (0.9 and landline phone (0.2%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xi Source of Lighting Energy Wick lamp was the most common source of lighting energy in the region. About 84 percent of the total rural households used this source of energy followed by hurricane lamp (10.1%), pressure lamp (3.4%), firewood (2.0%), mains electricity (0.5%), candle (0.2%), solar (0.15%), and gas or biogas (0.06%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.8 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.7%). The rest of energy sources accounted for 2.9 percent. These were parrafin/kerosene (1.2%), crop residues (0. 8%), bottled gas (0.2%), livestock dung (0.13%), mains electricity (0.11%), solar (0.06%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 70.1 percent of the rural agricultural households followed by grass/mud (14.9%). This was closely followed by iron sheets (13.8%). Other roofing materials are tiles (0.6%), asbestos (0.3%), concrete (0.1%) and others (0.3%). Number of Meals per Day About 58.2 percent of the holders in the region took three meals per day, 37.7 percent took two meals, 3.2 percent took one meal and 0.9 percent took four meals. Food Security Households which had never experienced food shortage represented 44.8 percent of the total number of agriculture households in the region. Households which seldom had problems in satisfying their food needs represented 32.4 percent and the households which were often faced with food shortage represented 8.7 percent. Those with little problems represented 7.2 percent and whilst about 6.9 percent of agriculture households always faced food shortages problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 22.8 percent of all rural agricultural households. The second main cash income earning activity was casual labor (20.9%) followed by selling of cash crops (16.0%), businesses (11.0%), sale of livestock (10.3%) and sale of forest products (7.5%). Other income earning activities were cash remittances (5.0%), employment (2.2%), sale of livestock products (1.1%) and fishing (0.2%). ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size ...........................................................................................................................................…5 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 10 3.2 Area, Production and Yield of cereal crops.........................................................................................................19 3.3 Area Planted and Quantity Harvested and Yield of Root and Tuber Crop.........................................................23 3.4 Area, Quantity Harvested and Yield of Pulses....................................................................................................26 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops......................................................................................30 3.6 Area, Production and Yield of Fruits and Vegetables.........................................................................................31 3.7 Land Clearing Methods........................................................................................................................................42 3.8 Planted Area by Type of Fertiliser Use and District ...........................................................................................49 3.9 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District.......................... 49 3.10 Number of Households Storing Crops by Estimated Storage Loss and District ................................................59 3.11 Reasons for Not Selling Crop Produce................................................................................................................62 3.12 Number of Agricultural Households that Received Credit by Sex of Household head and District ................ 62 3.13 Access to Inputs....................................................................................................................................................66 3.14 Total Number of Households and Chickens Raised by Flock Size ....................................................................76 3.15 Head Number of Other Livestock by Type of Livestock and District................................................................82 3.16 Mean distances from holders dwellings to infrastructure and services by districts ...........................................87 3.17 Number of Households by Number of meals the Household normally has per Day and District .................... 93 List of Charts 3.1 Agricultural Households by Type....................................................................................................................... 10 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head............................................. 14 3.3 Percentage Distribution of Population by Age and Sex – Tabora Region..........................................................14 3.4 Percentage Literacy Level of Household Members by District..........................................................................14 3.5 Literacy Rates for Heads of Household by Sex and District – Tabora Region ..................................................15 3.6 Percentage of Persons Aged 5 years and above by Educational Status..............................................................15 3.7 Percentage of Population Aged 5 years and Above by District and Education Status.......................................15 3.8 Percentage Distribution of Heads of Household by Educational Attainment ................................................... 15 3.9 Number of Households by Number of Members with Off Farm Income...........................................................16 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities..................................16 3.11 Utilized and Usable Land per Household by District..........................................................................................17 3.12 Percentage Distribution of Land Area by Type of Land Use..............................................................................17 3.13 Area Planted with Annual Crops (ha)..................................................................................................................17 3.14 Area Planted with Annual Crops by District.......................................................................................................18 3.15 Area Planted with Annual Crops per Household by District ..............................................................................18 3.16 Planted Area (ha) for the Main Annual Crops (ha) – Tabora Region.................................................................18 3.17 Planted Area (ha) per Household by Selected Crops – Tabora Region..............................................................18 3.20 Area Planted and Yield of Major Cereal Crops...................................................................................................19 3.21 Time Series Data on Maize Production – Tabora Region...................................................................................19 3.22 Maize: Total Area Planted and Planted Area per Household by District ...........................................................19 3.23 Time Series of Maize Planted Area and Yield – Tabora Region........................................................................22 3.24 Total Planted Area and Area of Paddy per Household by District .....................................................................22 3.25 Time Series Data on Paddy Production – Tabora Region...................................................................................22 3.26 Time Series of Paddy Planted Area and Yield – Tabora Region........................................................................22 3.27 Area Planted With Sorghum, Bulrush Millet and Finger Millet District............................................................23 3.28 Area Planted and Yield of Major Root and Tuber Crops....................................................................................23 3.29 Area planted with Cassava during the census/survey years................................................................................23 3.30 Percent of Cassava Planted Area and percent of Total Land with Cassava by District .....................................26 3.31 Cassava Planted Area per Cassava Growing Households by District ................................................................26 3.32 Total Area Planted with Sweet Potatoes and Planted Area per Household by District......................................26 3.33 Area Planted and Yield of Major Pulse Crops ....................................................................................................27 3.34 Percent of Bean Planted Area and Percent of Total Land with Beans by District .............................................27 3.35 Area Planted with Beans per Household by District...........................................................................................27 3.36 Time Series Data on Bean Production – Tabora Region.....................................................................................27 3.37 Time Series of Beans Planted Area and Yield - Tabora......................................................................................30 3.38 Area Planted and Yield of Major Oil Seed Crops...............................................................................................30 3.39 Time Series Data on Groundnut production – Tabora Region............................................................................30 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.40 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District .........................31 3.41 Area Planted per Groundnut Growing Household by District (Long Rainy Season).........................................31 3.42 Area Planted and Yield of Fruit and Vegetables.................................................................................................31 3.43 Percent of Onions Planted Area and Percent of Total Land with Onions by District ........................................33 3.44 Area Planted per Onions Growing Household by District..................................................................................33 3.45 Percent of Tomatoes Planted Area and Percent of Total Land with tomato by District ....................................33 3.46 Area Planted per Tomato Growing Household by District.................................................................................33 3.47 Percent of Amaranths Planted Area and Percent of Total Land with Amaranths by District............................34 3.48 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ...................................34 3.49 Area planted with Annual Cash Crops ................................................................................................................34 3.50 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District....................................34 3.51 Area Planted Annual and Permanent Crops ........................................................................................................39 3.52 Area Planted with the Main Permanent Crops ....................................................................................................39 3.53 Percent of Area Planted and Average Planted Area with Permanent Crops by District ....................................39 3.54 Percent of Area Planted with Mango and Average Planted Area per Household by District............................40 3.55 Percent of Area Planted with Palm Oil and Average Planted Area per Household by District.........................40 3.56 Percent of Area Planted with Banana and Average Planted Area per Household by District ...........................41 3.57 Percent of Area Planted with Pawpaw and Average Planted Area per Household by District..........................41 3.58 Number of Households by Method of Land Clearing.........................................................................................41 3.59 Area Cultivated by Cultivation Method...............................................................................................................42 3.60 Area Cultivated by Method of Cultivation and District......................................................................................42 3.61 Planted Area of Improved Seeds – Tabora Region .............................................................................................48 3.62 Planted Area with Improved Seed by Crop Type................................................................................................48 3.63 Percentage of Crop Type Planted Area with Improved Seed – Annuals............................................................48 3.64 Area of Fertilizer Application by Type of Fertilizer ...........................................................................................48 3.65 Area of Fertilizer Application by Type of Fertilizer and District...................................................................... 48 3.66 Planted Area with Farm Yard Manure by Crop Type – Tabora Region.............................................................49 3.67a Percent of crop type planted with Farm Yard Manure – Annuals ......................................................................49 3.67b Proportion of Planted Area Applied with Farm Yard Manure by District – Tabora Region.............................50 3.68 Planted Area with Inorganic Fertilizer by Crop type – Tabora Region..............................................................50 3.69a Percentage of Planted Area with Inorganic Fertilizer by Crop Type – Tabora Region .....................................50 3.69b Proportion of Planted Area Applied with Inorganic Fertilizer by District – Tabora Region.............................50 3.70a Planted Area with Compost Manure by Crop Type – Tabora Region................................................................51 3.70b Percentage of Planted Area with Compost by Crop Type ..................................................................................51 3.70c Proportion of Planted Area Applied with Compost by District..........................................................................51 3.71 Planted area (ha) by Pesticide use........................................................................................................................51 3.72 Planted Area applied with Insecticides by Crop Type ........................................................................................52 3.73 Percentage of Crop Type Planted Area applied with insecticides ......................................................................52 3.74 Percentage of Planted Area applied with Insecticides by District ......................................................................52 3.75 Planted Area applied with herbicides by Crop Type...........................................................................................52 3.76 Percentage of Crop Type Planted Area applied with herbicides.........................................................................53 3.77 Proportion of Planted Area applied with Herbicides by District – Tabora Region............................................53 3.78 Planted Area applied with Fungicides by Crop Type..........................................................................................53 3.79 Percentage of Crop Type Planted Area applied with Fungicides .......................................................................53 3.80 Proportion of Planted Area applied with Fungicides by District – Tabora Region............................................54 3.81 Area of Irrigated Land..........................................................................................................................................54 3.82 Planted Area and Percentage of Planted Area with Irrigation by District..........................................................54 3.83 Time Series of Households with Irrigation – Tabora..........................................................................................55 8.84 Number of Households with Irrigation by Source of Water...............................................................................55 3.85 Number of Households by Method of Obtaining Irrigation Water.................................................................... 55 3.86 Number of Households with Irrigation by Method of Field Application...........................................................55 3.87 Number of Households and Quantity Stored by Crop Type – Tabora Region...................................................56 3.88 Number of households by Storage Methods – Tabora Region .......................................................................... 56 3.89 Number of households by method of storage and District (based on the most important household crop)..... 56 3.90 Normal Length of Storage for Selected Crops ....................................................................................................58 3.91 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District ...................................................58 3.92 Number of Households by Purpose of Storage and Crop Type..........................................................................58 3.93a Households Processing Crops by District............................................................................................................59 3.93b Percent of Households Processing Crops by District..........................................................................................59 3.94 Percent of Crop Processing Households by Method of Processing................................................................... 60 3.95 Percent of Households by Type of Main Processed Product ..............................................................................60 3.96 Number of Households by Type of By-product..................................................................................................60 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.97 Use of Processed Product.....................................................................................................................................60 3.98 Percentage of Households Selling Processed Crops by District.........................................................................61 3.99 Location of Sale of Processed Products...............................................................................................................61 3.100 Percentage of Households Selling Processed Products by Outlet for Sale and District ....................................61 3.101 Number of Crop Growing Households Selling Crops by District ......................................................................61 3.102 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem ....................62 3.103 Percentage Distribution of Households Receiving Credits by Main Source......................................................63 3.104 Number of Households Receiving Credits by Main Source of Credits and District..........................................63 3.105 Proportion of Households Receiving Credit by Main Purpose of the Credit .....................................................63 3.106 Reasons for Not using Credit...............................................................................................................................63 3.107 Number of Households Receiving Extension Advice.........................................................................................65 3.108 Number of Households that Received Extension by District..............................................................................65 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider..................................65 3.110 Number of Households that Received Extension by Reported Quality of Services...........................................65 3.111 Number of Households by Source of Inorganic Fertilizer ..................................................................................66 3.112 Number of Households Reporting Distance to Source of Inorganic Fertilizer...................................................66 3.113 Number of Households by Source of Improved Seed.........................................................................................67 3.114 Number of Households reporting Distance to source of Improved Seed ...........................................................67 3.115 Number of Households by Source of Insecticide/Fungicide...............................................................................67 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides............................................67 3.117 Number of Households with Planted Trees.........................................................................................................68 3.118 Number of Planted Trees by Species...................................................................................................................68 3.119 Number of Trees Planted by Smallholders by Species and District ...................................................................68 3.120 Number of Trees Planted by Location.................................................................................................................68 3.121 Number of Households by purpose of Planted Trees..........................................................................................69 3.122 Number of Households with Erosion Control/Water Harvesting Facilities .......................................................69 3.123 Number and Proportion of Households with Erosion Control/Water Harvesting Facilities by District............69 3.124 Number of Erosion Control/Water Harvesting structures by Type of Facility...................................................69 3.125 Total Number of Cattle by District......................................................................................................................72 3.126 Numbers of Cattle by Type and District..............................................................................................................72 3.127 Cattle Population Trend .......................................................................................................................................73 3.128 Improved Cattle Population Trend.......................................................................................................................73 3.129 Total Number of Goats by District .....................................................................................................................73 3.130 Goat Population Trend.........................................................................................................................................74 3.131 Total Number of Sheep by District......................................................................................................................74 3.132 Sheep Population Trend.......................................................................................................................................75 3.133 Total Number of Pigs by District.........................................................................................................................75 3.134 Pig Population Trend............................................................................................................................................75 3.135 Total Number of Chicken by District ..................................................................................................................76 3.136 Chicken Population Trend ...................................................................................................................................76 3.137 Number of Improved Chicken by Type and District...........................................................................................82 3.138 Improved Chicken Population Trend...................................................................................................................82 3.139 Percentage Keeping Households that Reported Tsetse flies and Ticks Problems by District............................82 3.140 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District............83 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services.........83 3.142 Number of Households by Distance to Veterinary Clinic...................................................................................84 3.143 Number of Households by Distance to Veterinary Clinic and District...............................................................84 3.144 Number of Households by Distance to Village Watering Point .........................................................................84 3.145 Number of Households by Distance to village Watering Point and District......................................................84 3.146 Number of Households using Draft Animals ......................................................................................................85 3.147 Number of Households using Draft Animals by District....................................................................................85 3.148 Number of Households using Organic Fertilizer.................................................................................................85 3.149 Area of Application of Organic Fertilizer by District .........................................................................................85 3.150 Number of Households Practicing Fish Farming – Tabora.................................................................................86 3.151 Number of Households Practicing Fish Farming by District – Tabora ..............................................................86 3.152 Fish Production.....................................................................................................................................................86 3.153 Agricultural Households by Type of Toilet Facility .......................................................................................... 87 3.154 Percentage Distribution of Households Owning the Assets................................................................................87 3.155 Percentage Distribution of Households by Main Source of Energy for Lighting ..............................................91 3.156 Percentage Distribution of Households by Main Source of Energy for Cooking ..............................................91 3.157 Percentage Distribution of Households by Type of Roofing Material ...............................................................91 3.158 Percentage Distribution of Households With Grass/Leaves Roofs by District ..................................................91 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.159 Percentage Distribution of the Number of Households by Main Source of Income..........................................92 3.160 Percentage Distribution of Households Reporting Distance to Main Source of Drinking Water by Season....92 3.161 Number of Agriculture Households by Number of Meals per day.....................................................................92 3.162 Number of Households by Frequency of Meat and Fish Consumption..............................................................93 3.163 Number of Households by level of Food Availability ........................................................................................93 3.164 Percentage of Households reporting food availability Status by District...........................................................94 3.165 Percentage Distribution of the Number of Households by Main Source of Income..........................................94 List of Maps 3.1 Total Number of Agricultural Households by District....................................................................................... 11 3.2 Number of Agricultural Households per Square Km of Land by District..........................................................11 3.3 Number of Crop Growing Households by District..............................................................................................12 3.4 Percent of Crop Growing Households by District...............................................................................................12 3.5 Number of Crop Growing Households per Square Kilometer of Land by District............................................13 3.6 Percent of Crop and Livestock Households by District ......................................................................................13 3.7 Utilized Land Area Expressed as a Percent of Available Land ..........................................................................20 3.8 Total Planted Area (annual crops) by District.....................................................................................................20 3.9 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District ...................................21 3.10 Planted Area and Yield of Maize by District ......................................................................................................24 3.11 Area Planted per Maize Growing Household......................................................................................................24 3.12 Planted Area and Yield of Paddy by District ......................................................................................................25 3.13 Area Planted per Paddy Growing Household......................................................................................................25 3.14 Planted Area and Yield of Cassava by District ...................................................................................................28 3.15 Area Planted per Cassava Growing Household...................................................................................................28 3.16 Planted Area and Yield of Beans by District.......................................................................................................29 3.17 Area Planted per Beans Growing Household......................................................................................................29 3.18 Planted Area and Yield of Groundnuts by District .............................................................................................32 3.19 Area Planted per Groundnuts Growing Household.............................................................................................32 3.20 Planted Area and Yield of Onions by District.....................................................................................................35 3.21 Area Planted per Onions Growing Household ....................................................................................................35 3.22 Planted Area and Yield of Tomatoes by District.................................................................................................36 3.23 Area Planted per Tomatoes Growing Household................................................................................................36 3.24 Planted Area and Yield of Amaranths by District...............................................................................................37 3.25 Area Planted per Amaranths Growing Household ..............................................................................................37 3.26 Planted Area and Yield of Tobacco by District...................................................................................................38 3.27 Area Planted per Tobacco Growing Household..................................................................................................38 3.28 Area Planted per Cotton Growing Household.....................................................................................................43 3.29 Planted Area and Yield of Cotton by District......................................................................................................43 3.30 Planted Area and Yield of Mango by District.................................................................................................... 44 3.31 Area Planted per Mango Growing Household ....................................................................................................44 3.32 Planted Area and Yield of Palm Oil by District..................................................................................................45 3.33 Area Planted per Palm Oil Growing Household .................................................................................................45 3.34 Planted Area and Yield of Banana by District ....................................................................................................46 3.35 Area Planted per Banana Growing Household....................................................................................................46 3.36 Planted Area and Yield of Pawpaw by District...................................................................................................47 3.37 Area Planted per Pawpaw Growing Household ..................................................................................................47 3.38 Planted Area and Percent of Planted Area with No Application of Fertilizer by District..................................57 3.39 Area Planted and Percent of Total Planted Area with Irrigation by District ......................................................57 3.40 Percent of households storing crops for 3 to 6 weeks by district........................................................................64 3.41 Number of Households and Percent of Total Households Selling Crops by District........................................ 64 3.42 Number of Households and Percent of Total Households Receiving Crop Extension Services by District .....70 3.43 Number and Percent of Crop Growing Households using Improved Seed by District .....................................70 3.44 Number and percent of smallholder planted trees by district..............................................................................71 3.45 Number and Percent of Households with water Harvesting Bunds by District..................................................71 3.46 Cattle population by District as of 1st Octobers 2003.........................................................................................77 3.47 Cattle Density by District as of 1st October 2003...............................................................................................77 3.48 Goat population by District as of 1st Octobers 2003 ..........................................................................................78 3.49 Goat Density by District as of 1st October 2003.................................................................................................78 3.50 Sheep population by District as of 1st Octobers 2003 ........................................................................................79 3.51 Sheep Density by District as of 1st October 2003...............................................................................................79 3.52 Pig population by District as of 1st Octobers 2003.............................................................................................80 3.53 Pig Density by District as of 1st October 2003 ...................................................................................................80 ILLUSTRATION ___________________________________________________________________________________________________________________________ __________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.54 Number of Chickens by District as of 1st October 2003 ....................................................................................81 3.55 Density of Chickens by District as of 1st October 2003.....................................................................................81 3.56 Number and Percent of Households Infected with Ticks by District .................................................................88 3.57 Number and Percent of Households Using Draft Animals by District...............................................................88 3.58 Planted Area and Percent of Planted are with Farm Yard Manure application by District................................89 3.59 Planted Area and Percent of Planted are with Compost application by District ................................................89 3.60 Number and Percent of Households Practicing Fish Farming by District..........................................................90 3.61 Number and Percent of Households Without Toilets by District .......................................................................90 3.62 Number and Percent of Households using Grass/Leaves for roofing material by District ................................95 3.63 Number and Percent of Households eating 3 meals per day by District ............................................................95 3.64 Number and Percent of Households eating Meat Once per Week by District ...................................................96 3.65 Number and Percent of Households eating Fish Once per Week by District.....................................................96 3.66 Number and percent of Households Reporting food insufficiency by District ..................................................97 INTRODUCTION Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the region by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information aims at providing the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Tabora region is situated at the Midwest part of Tanzania between 40 and 70degrees below the Equator and 310 – 430 degrees East of the Greenwich Meridian. The region lies on the central plateau whereby in the north east it shares the border with Shinyanga region, on the western side it borders Kigoma while in the south it shares the border with Rukwa and Mbeya regions. The region comprises six districts of Nzega, Igunga, Uyui, Urambo, Sikonge, and Tabora Urban. The region headquarters is located in Tabora Urban. 1.3 Land Area The region has an area of 76,151 square kilometers, of which 194.3 square kilometers (1,943,280 ha) are arable land. 1.4 Climate 1.4.1 Temperature The dominant climate is warm with temperatures reaching the peak during September and October just before the long rainy season starts. The Central Plateau has the average temperature of 230C with the minimum temperature of 17oC and maximum temperature of 280C. 1.4.2 Rainfall The region has one rainy season, the long rainy seasons. The season falls almost entirely between November and May. The total annual precipitation decreases from West to East. In the west the rainfall total over 1,000mm while in the East it drops to 700mm or less 1.5 Population According to the 2002 Population and Housing Census, there were 1,717,908 inhabitants in Tabora region. The population of Tabora region ranked 7th out of the 21 regions on Tanzania Mainland. 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 1998 was estimated to be TShs 196,803 million with a per capita income of 151,208 shillings. Tabora region is famous for forestry industry and game reserves. The region has 34,698 square kilometers of forestry reserves and 17,122 square kilometers of game reserves. The region is also famous for producing both food and cash crops. The main food crops produced in Tabora region include: maize, paddy, sorghum and finger millet. The main cash crops include cotton and tobacco. Livestock keeping is also a very important economic activity. The main livestock raised are cattle, goats and sheep. INTRODUCTION Tanzania Agriculture Sample Census 2 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: • Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; INTRODUCTION Tanzania Agriculture Sample Census 3 • Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. • Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. • Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: • Identification (i.e. region, district, ward and village) • Household and holding characteristics • Household information • Land ownership/tenure • Land use • Access and use of resources • Crop and vegetable production • Agro processing and by-Products • Crop storage and marketing • On-farm investment • Access to farm inputs and implements • Use of credit for agricultural purposes • Tree farming/agro-forestry • Crop extension services • Livelihood constraints • Animal contribution to crop production • Livestock • Livestock products • Fish farming • Livestock extension • Labour use INTRODUCTION Tanzania Agriculture Sample Census 4 • Access to infrastructure and other services • Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pretesting of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using ArcView and Freehand. - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the INTRODUCTION Tanzania Agriculture Sample Census 5 Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree, the regional supervisors were either agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION Tanzania Agriculture Sample Census 6 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. • Skip patterns were used to avoid asking unnecessary questions • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: • Village listing forms that were used for listing households in the villages and from these list a systematic sample of 15 agricultural households were selected from each village. • Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during tha training • Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the INTRODUCTION Tanzania Agriculture Sample Census 7 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census were by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff were used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. INTRODUCTION Tanzania Agriculture Sample Census 8 2.6.11 Data Processing Data processing consisted of the following processes: • Manual editing • Data entry • Data structure formatting • Batch validation • Tabulation • Illustration production • Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations INTRODUCTION Tanzania Agriculture Sample Census 9 Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 10 3. CENSUS RESULTS This part of the report presents the results of the census for Tabora region based on the statistical tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables, graphs and maps in order to make it easy for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses and surveys’ results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Survey, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The results are divided into four main sections which are household characteristics, crop results, livestock results and poverty indicators. Compared to previous census and surveys, more effort has been placed in analyzing the results in order to formulate solid conclusions. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Tabora region was 235,917. The largest number of agricultural households was in Nzega (65,566) followed by Urambo (54,120), Igunga (45,141), Uyui (41,318), Sikonge, (19,514) and Tabora Urban (10,258) (Map 3.1). The highest density of households was found in Nzega (27/km2) followed by Igunga (17/km2) (Map 3.2). Most households (148,046, 62.8%) were involved in growing crops only, 296 (0.1%) rearing livestock only, and 87,575 (37.1%) were involved in crop production as well as livestock keeping (Chart 3.1) (Maps 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Tabora region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, tree/forest resources, livestock keeping/herding, permanent crop farming, remittances and fishing/hunting and gathering (Table 3.1). Annual crop farming was the most important source of livelihood for all districts while fishing/hunting and gathering was the least important source of income to all districts. Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permane nt Crop Farming Livestock Keeping / Herding Off Farm Income Remitta nces Fishing / Hunting & Gathering Tree / Forest Resources Nzega 1 5 3 4 6 7 2 Igunga 1 5 4 2 6 7 3 Uyui 1 4 3 2 6 7 5 Urambo 1 5 4 2 6 7 3 Sikonge 1 5 2 3 6 7 4 Tabora Urban 1 4 3 2 6 7 5 Total 1 5 4 2 6 7 3 Chart 3.1 Agriculture Households by Type - Tabora Crops & Livestock 37% Crops Only 63% Livestock Only 0% Tabora Urban Uyui Urambo Sikonge Igunga Nzega 15 9 7 2 17 27 24 to 30 18 to 24 12 to 18 6 to 12 0 to 6 Igunga Nzega Tabora Urban Uyui 45,141 65,566 41,318 10,258 19,514 54,120 Urambo Sikonge 56,000 to 70,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Tanzania Agriculture Sample Census Number of Agricultural Households Number of Agricultural Households Number of Agricultural Households Per Square Km Number of Agricultural Households Per Square Km Map 3.01 TABORA Total Number of Agriculture Households by District Map 3.02 TABORA Number of Agricultural Households Households Per Square Kilometer of Land by District RESULTS 11 Tabora Urban Uyui Sikonge Igunga Nzega Urambo 99.8% 99.7% 99.7% 99.7% 100% 100% 99.94 to 100 99.88 to 99.94 99.82 to 99.88 99.76 to 99.82 99.7 to 99.76 Sikonge Tabora Urban Uyui Igunga Nzega 19,464 10,233 41,212 45,025 65,566 54,120 Urambo 56,000 to 70,000 42,000 to 56,000 28,000 to 42,000 14,000 to 28,000 0 to 14,000 Tanzania Agriculture Sample Census Number of crop Growing Households Number of crop Growing Households Percent of crop Growing Households Percent of crop Growing Households Map 3.3 TABORA Number of crop Growing Households by District Map 3.4 TABORA Percent of crop Growing Households by District RESULTS 12 Tabora Urban Uyui Sikonge Igunga Nzega 22.2 35.5 29.7 52 42.2 25.4 Urambo 48 to 60 36 to 48 24 to 36 12 to 24 0 to 12 Tabora Urban Sikonge Urambo Igunga Nzega Uyui 15 2 7 17 27 9 24 to 30 18 to 24 12 to 18 6 to 12 0 to 6 Tanzania Agriculture Sample Census Number of Crop Growing Households Per Square Km Number of crop Growing Households Percent of Crop Growing Households Percent of Crop Growing Households Map 3.05 TABORA Number of Crop Growing Households Per Square Kilometer of Land by District Map 3.06 TABORA Percent of Crop and Livestock Households by District RESULTS 13 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 14 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Tabora region was 202,097 (86% of the total regional agricultural households) whilst the female-headed households it were 33,820 (14% of the total regional agricultural households). The mean age of household heads was 46 years (46 years for male heads and 52 years for female heads) (Chart 3.2) The percentage trend for six censuses/surveys’ years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Tabora region had a total rural agricultural population of 1,420,300 of which 732,811 (52%) were males and 687,489 (48%) were females. Whereas age group 0-14 constituted 44 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Tabora region had an average household size of 6 persons per household with Nzega and Tabora Rural districts having the lowest household size of 5 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Tabora region had a total literacy rate of 52.5 percent. The highest literacy rate was found in Tabora Urban district (67.4%) followed by Urambo district (56.0%) and Sikonge district (55.7%). Igunga, Uyui and Nzega districts had the lowest literacy rates of 53.3, 51.8 and 46.0 percent respectively (Chart 3.4). Chart 3.3 Percent Distribution of Population by Age and Sex - TABORA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85+ Age Group Percent Male Female Chart 3.4 Percent Literacy Level of Household Members by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Tabora Urb Urambo Sikonge Igunga Uyui Nzega District Percent Chart 3.2: Percentage Distribution of Agricultural Households by Sex of Household Head 0 10 20 30 40 50 60 70 80 90 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/96 NSCA 2002/03 Year Percent of Households Male Headed Households Female Headed Households RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 58.9 percent. The literacy rate for the male heads was 63.0 percent and that of female heads of households has 34.1 percent. The literacy rate of male heads was higher than that of female heads in all districts. The district with the highest literacy rate amongst for all heads of households was Sikonge (69.2%) followed by Tabora Urban (68.9%), Urambo (67.6%), Uyui (62.0%), Igunga (52.3%) and Nzega (49.7%) (Chart 3.5). Educational Status Information on educational status was collected from individual agricultural households. The results show that 34 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 21 percent were still attending school. Those who have never attended school were 45 percent (Chart 3.6). Agricultural households in Tabora Urban district had the highest percentage (42%) of population aged 5 years and above who had completed different levels of education. This was followed by Sikonge and Urambo districts with 41 and 35 percent respectively. Igunga, Uyui and Nzega districts had the lowest percentages of 33, 33 and 30 respectively. The number of heads of agric ultural households with formal education in Tabora region was 135,084 (57.3%), those without formal education were 97,767 (41.4%) and those with only adult education were 3,066 (1.3%). The majority of heads of agricultural households (54.2%) had primary level education whereas only 3.1 percent had higher than primary level education. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 34% Attending School 21% Never Attended 45% Chart 3.5 Literacy Rates of Heads of Household by Sex and District - TABORA 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Sikonge Tabora Urb Urambo Uyui Igunga Nzega District P ercent Male Female Total Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0 10 20 30 40 50 60 Tabora Urban Sikonge Urambo Igunga Uyui Nzega District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Primary Education 54.2% No Education 41.4% Post Primary Education 3.1% Adult Education 1.3% RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 With regard to the heads of agricultural households with primary or secondary education in Tabora region, Sikonge district had the highest percentages (64.6% for primary and 3.8% for secondary). This was followed by Tabora Urban (62.3% primary and 4.0% secondary), Urambo (60.8% primary and 2.8% secondary) and Uyui (57.3% primary and 3.0% secondary), Igunga (48.9% primary and 1.0% secondary) and Nzega (46.1% primary and 2.1% secondary). Tabora Urban had the highest percentage of heads of agricultural households with secondary school education while Igunga had the lowest. (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or laborers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Tabora with 87.7 percent of households having at least one member with off-farm income. In Tabora region, there were 206,899 households with at least one household member engaged in off-farm income generating activity 117,453 households (50%) had only one member aged 5 years and above engaged in an off-farm income generating activity, 52,284 households (22%) had two members involved in off-farm income generating activities and 37,162 households (16%) had more than two members involved in off-farm income generating activities. Igunga and Nzega district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Urambo (89%) and Tabora Urban (86%). Uyui and Sikonge districts had the lowest percent of agriculture households with off-farm income (77% and 74% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Nzega (54%). Uyui district had few households with more than one member having off-farm income (17%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on it in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the Chart 3.9 Number of Household by Number of Members with Off-farm Income More than Two,37,162, 16% None, 29,018, 12% One , 117,453, 50% Two, 52,284, 22% Chart 3.10 Percentage Distribution of Agricultural Household by Number of Off-farm Activities 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Nzega Igunga Uyui Urambo Sikonge Tabora Urb District P ercent One Two More than Two None RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 country, but it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 899,225 ha. The regional average land area utilised for agriculture per household was only 2.9 ha. This figure is above the national average which is estimated at 2.0 hectares. Large differences in land area utilised per household exist between districts with Igunga and Nzega utilizing between 3.8 and 1.9 ha per household. The percentage utilized of the usable land per household was highest in Igunga (92%) and lowest in Urambo (69%) (Map 3.7). Seventy eight percent of the total land available to smallholders was utilised. Twenty two percent of usable land available to smallholders was not used (Chart 3.11, Map 3.7) 3.2.2 Types of Land Use The area of land under temporary mono-crops was 336,318 hectares (37.4% of the total land available to smallholders in Tabora), followed by temporary mix (182,793 ha, 20.3%), uncultivatable usable land (122,977, 13.7%), natural bush (63,072 ha, 7%), area under fallow (62,016 ha, 6.9%), unusable land (33,763 ha, 3.8), pasture (33,264 ha, 3.7%), permanent annual mix (25,917 ha, 2.9%), permanent mono-crops (15,179 ha, 1.7%), area rented to others (10,553 ha, 1.2%), permanent mixed crops (10,136 ha, 1.1%) and area planted with trees (3,237 ha, 0.4%). 3.3 Annual Crop and Vegetable Production Tabora region has only one rainy season, namely the long rainy season (November to May). The quantity of crops produced in that season will be used as a base for comparison with the past surveys and censuses. Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 5.0 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Districts Area/household 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation Chart 3.12 Land Area by Type of Use 20.3 37.4 13.7 7.0 6.9 3.8 3.7 2.9 1.7 1.2 1.1 0.4 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 Planted Trees Permanent Mixed Crops Rented to Others Permanent Mono Crops Permanent / Annual Mix Pasture Unusable Fallow Natural Bush Uncultivated Usable Land Temporary Mixed Crops Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops Long Rainy Season, 532,615, 100% Planted Area - Long Rainy Season RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 3.3.1 Area Planted The area planted with annual crops and vegetables was 532,615. The average areas planted per household was 0.7. The district with the largest area planted per household was Igunga (1.1 ha) followed by Sikonge (0.9 ha) and Uyui (0.8 ha). The district with the smallest average area planted per household was Tabora Urban (0.5ha). (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 347,455 ha (65.2% of the total area planted with annuals). This was followed by oil seeds (69,862 hectares, 13.1%), cash crops (54,948 hectares, 10.3%), root and tuber crops (31,535 hectares, 5.9%), pulses (25,911 hectares, 4.9%) fruits and vegetables (2,904 hectares, 0.5%). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Tabora region and it had a planted area 3.4 times greater than groundnuts, which had the second largest planted area. The area planted with maize constituted 44 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are paddy, sorghum, tobacco, cotton, cassava and beans (Chart 3.16). Households that grow bulrush millet, cotton, sorghum, maize and tobacco have larger planted areas per household than those growing other crops (Chart 3.17). Chart 3.14 Area Planted with Annual Crops by District 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Igunga Urambo Nzega Uyui Sikonge Tabora Urban District Planted Area (Ha) Chart 3.15 Area Planted with Annual Crops per Household by District 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Igunga Sikonge Uyui Urambo Nzega Tabora Urb District A rea pe r H o u seh o ld (H a ) Chart 3.16 Planted Area (ha) for the Main Crops - TABORA 0 100,000 200,000 300,000 Maize Groundnuts Paddy Sorghum Tobbaco Cotton Cassava Beans Sweet Potatoes Bambaranuts Cowpeas Bulrush Millet Onion Crop Area Planted (ha) Chart 3.17 Planted Area (ha) per Household by Selected Crop - TABORA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Bulrush Millet Cotton Sorghum Maize Tobacco Paddy Simsim Groundnuts Onions Cassava Beans Sunflower Sweet Potatoes Bambatanuts Tomatoes Cowpeas Greemgram Crop Planted Area (ha) RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 19 3.3.3 Crop Types Cereals are the main crops grown in Tabora region. The area planted with cereals was 347,455 ha (65.% of the total area planted with annuals), followed by oil seeds (69,862 hectares, 13.%), cash crops (54,948 hectares, 10%), root and tuber crops (31,535 hectares, 6%), pulses (25,911 hectares, 5%) fruits and vegetables (2,904 hectares, 1%). Cereals and oil seeds and oil seeds are the dominant crops and other crop types are of minor importance in comparison (Chart 18). 3.3.4 Cereal Crop Production The total production of cereals was 222,315 tonnes. Maize was the dominant cereal crop at 143,122 tonnes which was 64.4 percent of total cereal crops produced, followed by paddy (26.4%) sorghum (8.5%), finger millet (0.4%) and bulrush millet (0.3%). Production of wheat and barley was very small. Igunga district had the largest planted area of Cereals in the region (101,943ha) followed by Nzega, (79,731ha), Uyui (64,269ha), Urambo (59,115), Sikonge (32,371ha) and Tabora Urban (10,025ha) (Map 3.9). Maize had the largest planted area which represented 67 percent of the total area planted with cereal crops. It was followed by paddy (19%), sorghum (13%), bulrush millet (0.4%) and finger millet 0.3%). Areas planted with wheat and barley were very small. Paddy had the largest yield at 893 kg/ha, followed by finger millet (873 kg/ha), maize (615 kg/ha), bulrush millet (453 kg/ha) and sorghum (409 kg/ha) (Chart 3.20). 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Tabora region was 229,901, (65% of the total annual crop growing households in the region). The total production of maize was 143,122 tonnes from a planted area of 232,860 hectares resulting in a yield of 0.6 t/ha. Chart 3.21 indicates maize production trend (in thousand metric tonnes). There was a sharp decrease in maize production by 62 percent in 1996/97 followed by a steady increase in production until 2002/03. The average area planted with maize Table 3.2: Area, Production and Yield of Cereal Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Maize 232,860 143,122 615 Paddy 65,657 58,661 893 Sorghum 46,379 18,959 409 Bulrush Millet 1,545 700 453 Finger Millet 881 769 873 Wheat 33 15 455 Barley 100 89 889 Total 347,455 222,315 Chart 3.20 Area Planted and Yield of Major Cereal Crops 0 50,000 100,000 150,000 200,000 250,000 Maize Paddy Sorhum Bulrush Millet Finger Millet Crop Area Planted (Ha) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Yield (T/Ha) Area Planted (Ha) Yield (T/Ha) Chart 3.21: Time Series Data on Maize Production - TABORA 143 126 126 98 72 191 186 0 50 100 150 200 250 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Agriculture Year Production ('000') Chart 3.22 Maize: Total Area Planted and Planted Area per Household by District 7,844 22,958 46,076 46,418 52,986 56,579 0 10,000 20,000 30,000 40,000 50,000 60,000 Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Acre (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Area Planted per Household Area Planted (Ha) Area Planted / Household Sikonge Tabora Urban Uyui Igunga Nzega 142,453 52,716 17,606 95,654 109,322 114,863 Urambo 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tabora Urban Uyui Sikonge Igunga Nzega 70.4% 73.2% 90.1% 69.9% 69.1% 92.1% Urambo Tanzania Agriculture Sample Census Percent of Utilized Land Area Percent of Utilized Land Area Annual crops Planted Area Annual crops Planted Area Map 3.7 TABORA Utilized Land Area Expressed as a Percent of Available Land by District Map 3.8 TABORA Total Planted Area with Annual crops by District 87.5 to 92.2 82.9 to 87.5 78.3 to 82.9 73.7 to 78.3 69.1 to 73.7 RESULTS 20 Nzega Tabora Urban Igunga Uyui Sikonge 79,731ha 59,115ha 10,025ha 101,943ha 64,269ha 32,371ha 72.9% 51.5% 56.9% 71.6% 67.2% 61.4% Urambo 120,000 to 150,000 90,000 to 120,000 60,000 to 90,000 30,000 to 60,000 0 to 30,000 Tanzania Agriculture Sample Census Planted Area (ha) Planted Area (ha) Map 3.09 TABORA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District Percent of Planted Area With Cereal Crops RESULTS 21 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 per household was 1.0 hectare, however it ranged from 0.8 hectares in Tabora Urban and Nzega districts to 1.3 hectares in Igunga district (Map 3.11). Igunga district had the largest area of maize (56,579 ha) followed by Nzega (52,986 ha), Uyui (46,418 ha), Urambo (46,076 ha), Sikonge (22,958 ha) and Tabora Urban (7,844 ha) (Chart 3.22 and Map 3.10). Charts 3.21 and 3.23 show that, over the period of 8 years from 1994/95 to 2002/03 both the yield and production decreased during the first half of the period and increased gradually during the remaining half. The area planted with maize remained constant but low over the period from 1994 to 1996 after which the area expanded rapidly 1997/98 and remained constant up to the year 2002/03. During the period 1997/98 to 2002/03, the yield increased gradually from 0.3 t/ha in 1997/98 to 0.6 t/ha in 2002/03 (Chart 3.23). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tabora region was 92,037. This represents 39 percent of the total annual crop growing households in Tabora region. The total production of paddy was 58,661 tonnes from a planted area of 65,657 hectares resulting in a yield of 0.9 t/ha. The district with the largest area planted with Paddy was Nzega (25,289 ha) followed by Uyui (14,587 ha), Urambo (11,904 ha), Igunga (6,560 ha), Sikonge (5,193 ha), and Tabora Urban (2,124 ha) (Map 3.12). There were variations in the average area planted per crop growing household among the districts ranging from 0.5 ha in Tabora Urban to 1.1 ha in Sikonge (Chart 3.24 and Map 3.13) There was a sharp rise in the production of paddy in 1997/98 and in 2002/03 compared to 1996/97 and 1999/2000 respectively. The production rose from 3,861 tonnes in 1996/97 to 46,601 tonnes in 1997/98 after which it dropped to 24,370 tonnes in the following year. Also, the production rose from 24,370 tonnes in 1999/00 to 58,661 tonnes in 2002/03. Charts 3.25 and 3.26 show that, whilst the yield of paddy has been erratic over the 8 year period from 1994/95 to 2002/03, the quantity produced increased due to a large increase of the planted area. From 1997/98 to 2002/03 the yield Chart 3.23 Time Series Data of Maize Planted Area and Yield - TABORA 0 100,000 200,000 300,000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Yield (t/ha) Planted Area (Ha) Yield Chart 3.24: Total Planted Area and Area of Paddy per Household by District 2,124 5,193 6,560 11,904 14,587 25,289 0 5,000 10,000 15,000 20,000 25,000 30,000 Nzega Uyui Urambo Igunga Sikonge Tabora Urban District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Area Planted per Household Area Planted (Ha) Area Planted / Household Chart 3.25: Time Series Data on Paddy Production - TABORA 47 59 24 24 4 6 9 0 10 20 30 40 50 60 70 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Agriculture Year Production ('000') tones Chart 3.26 Time Series Data of Paddy Area and Yield - TABORA 0 20000 40000 60000 80000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Yield (t/ha) Planted Area (Ha) Yield RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 has not dropped. The area planted with paddy and the production dropped drastically from 1994/95 to 1996/97 followed by rapid increase in 1997/98 after which the area planted and the production dropped rapidly in 1998/99. From 1999/2000 to 2002/03 the area planted and the production has been increasing (Chart 3.26). 3.3.4.3 Other Cereals Other cereals are produced in small quantities except sorghum of which the planted areas were as follows: Igunga (38,804 ha) followed by Uyui (3,162 ha), Sikonge (2,665 ha), Nzega (1,347 ha), Urambo (345 ha) and Tabora Rural (57 ha). Bulrush millet is produced in Sikonge (1,436 ha), Urambo (70 ha) and Uyui (39 ha) while finger millet was produced in Urambo (722 ha), Nzega (98 ha), Uyui (43 ha) and Sikonge (19 ha). The production of wheat and barley were very small. 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 41,380 tonnes. Cassava production was the highest being 28,416 tonnes, representing 68.7 percent of the total root and tuber crops production. This was followed by sweet potatoes with 12,351 tonnes (29.8%), Irish potatoes (329 tonnes, 0.8%) and yams (283 tonnes, 0.7%) (Table 3.3). The area planted with cassava was the largest in the region root and tuber crops. It accounted for 67.8 percent of the area planted with roots and tubers, followed by sweet potatoes (29.1%), Irish potatoes (2.3%) and yams (0.8%). There was a significant increase in area planted with cassava in the eight year period from 1994/95 to 2002/03. The area for sweet potato and yams remained more or less constant. The estimated yield was highest for sweet potatoes (1.34 t/ha) and cassava (1.32 t/ha), followed by yams (1.14 t/ha) and Irish potatoes 0.5 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 47,395. This represents 20 percent of the total crop growing households in the region. The total production of cassava during the census year was 28,416 tonnes from a planted area of 21,391 hectares resulting in a yield of 1.3 t/ha. Table 3.3: Area, Quantity Harvested and Yield of Root and Tuber Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Cassava 21,391 28,416 1,328 Sweet Potatoes 9,173 12,351 1,346 Irish Potatoes 723 329 455 Yams 248 283 1,143 Total 31,535 41,380 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Area (Ha) Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.27 Area Planted with Sorghum, Bulrush Millet and Finger Millet by District Sorghum Finger Millet Bulrush Millet Chart 3.28 Area Planted and Yield of Major Root and Tuber Crops 0 5,000 10,000 15,000 20,000 25,000 Cassava Sweet Potatoes Irish Potatoes Yams Crop Area Planted (Ha) 0 500 1,000 1,500 Yield (Kg/Ha) Area Planted (Ha) Yield (Kg/Ha) Chart 3.29 Area Planted with Cassava during the Census/Survey Year 0 15000 30000 45000 1994/95 1995/96 1997/98 1998/99 2002/03 Agriculture Year Area (Ha) Cassava Tabora Urban Urambo Igunga Sikonge Uyui Nzega 0.8ha 0.9ha 1.3ha 1.2ha 1.1ha 0.8ha 1.2 to 1.3 1.1 to 1.2 1 to 1.1 0.9 to 1 0.8 to 0.9 Sikonge Urambo Uyui Tabora Urban Nzega Igunga 22,958ha 46,076ha 46,418ha 7,844ha 52,986ha 56,579ha 0.8t/ha 0.8t/ha 0.6t/ha 0.5t/ha 0.7t/ha 0.3t/ha 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 RESULTS 24 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.10 TABORA Planted Area and Yield of Maize by District Map 3.11 TABORA Area Planted per Maize Growing Household by District Yield(t/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.5ha 0.8ha 0.7ha 0.7ha 0.6ha 1.1ha Tabora Urban Uyui Urambo Nzega Igunga Sikonge 2,124ha 14,587ha 11,904ha 25,289ha 6,560ha 5,193ha 0.8% 0.9% 0.9% 1.2% 0.9 0.5% Tanzania Agriculture Sample Census RESULTS 25 Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.12 TABORA Planted Area and Yield of Paddy by District Map 3.13 TABORA Area Planted per Paddy Growing Household by District Yield(t/ha) 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 0.98 to 1.11 0.86 to 0.98 0.74 to 0.86 0.62 to 0.74 0.5 to 0.62 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 26 Previous censuses and surveys indicate that the area planted with cassava increased for the period 1994/95 to 1998/99. Since 1998/99 the area planted with cassava dropped from 40,582 ha in 1998/99 to 21,391 ha in 2002/03 (Chart 3.29). The area planted with cassava accounted for 7 percent of the total area planted with annual crops and vegetables in the census year. Urambo district had the largest planted area of cassava (8,795 ha, 41% of the cassava planted area in the region), followed by Nzega (4,388 ha, 21%), Uyui (3,316 ha, 16%), Tabora Urban (2,326 ha, 11%), Sikonge (1,829 ha, 9%) and Igunga (736 ha, 3%) (Map 3.14). However, the district with the highest proportion of land planted with cassava was Tabora Urban (13.2%). This was followed by Urambo (7.7%), Nzega (4.0%), Uyui and Sikonge (3.5% each) and Igunga (0.5%) (Chart 3.30). The average cassava planted area per cassava growing household was 0.5 hectares. However, there were small district variations. The area planted per cassava growing household was largest in Tabora Urban (0.6 ha). This was followed by Sikonge (0.5 ha), Uyui (0.5 ha), Urambo (0.5 ha), Nzega (0.4 ha) and Igunga (0.4 ha) (Chart 3.31 and Map 3.15). 3.3.5.2 Sweet Potatoes The number of households growing sweet potatoes in Tabora region was 27,635. The total production of sweet potatoes during the census year was 12,351 tonnes from a planted area of 9,173 hectares resulting in a yield of 1.3t/ha. Igunga District has the largest planted area for sweet potatoes (3,639 ha, 39.7%), followed by Urambo (1,483 ha, 16.2%), Uyui (1,440 ha, 15.7%), Sikonge (1,166 ha, 12.7%), Tabora Urban (772 ha, 8.4%) and Nzega (673 ha, 7.3%). Other root and tuber crops are of minor importance in terms of area planted compared to cassava and sweet potatoes. Table 3.4: Area, Quantity Harvested and Yield of Pulse Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Beans 19,331 7,143 369.5 Bambara nuts 3,593 1,424 396.4 Cowpeas 1,802 544 301.7 Chick Peas 682 437 640.4 Green Gram 436 91 209.2 Mung Beans 66 19 287.9 Pigeon Peas 0 0 0.0 Field Peas 0 0 0.0 Total 25,910 9,658 Chart 3.30 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 41.1 20.5 15.5 10.9 3.4 8.6 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 Urambo Nzega Uyui Tabora Urban Sikonge Igunga District Percent of Total Area Planted 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.6 0.5 0.5 0.5 0.4 0.4 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Area per Household Tabora Urban Sikonge Uyui Urambo Nzega Igunga District Chart 3.31 Cassava Planted Area per Cassava Growing Households by District Chart 3.32 Total Area Planted with Sweet Potatoes and Planted Area per Household by District 673 772 1,166 1,440 1,483 3,639 0 1,000 2,000 3,000 4,000 Igunga Urambo Uyui Sikonge Tabora Urban Nzega District Area (H a) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Area Planted per H ousehod Area Planted (Ha) Area Planted/Hh RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 3.3.6 Pulse Crops Production The total area planted with pulses was 25,910 hectares representing 5 percent of total area planted with annual crops out of which 19,3318 ha were planted with beans (74.6 percent of the total area planted with pulses), followed by bambara nuts (3,593 ha, 13.9%), cowpeas (1,802 ha, 7.0%), chick peas (682 ha, 2.6%), green gram (436 ha, 1.7%) and mung beans (66 ha, 0.3%). Pigeon peas and field peas were not cultivated in the region. The total production of pulses was 9,658 tonnes. The production of beans was 7,143 tonnes and it accounted for 74 percent of the total pulse production. This was followed by bambara nuts (1,424t, 14.7%), cow peas (544t, 5.6%), chick peas (437t, 4.5%), green gram (91t, 0.9%) and mung beans (19t, 0.2%). Chick peas had a relatively higher yield of 640 kgs/ha than other pulses. The yields of the rest of the pulses in kilograms per hectare were bambara nuts 396 kgs/ha, beans 370 kgs/ha, cow peas 302 kgs/ha, mung beans 288 kgs/ha and green gram 209 kgs/ha (Chart 3,33). 3.3.6.1 Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Tabora region was 56,189. The total production of beans in the region was 7,143 tonnes from a planted area of 19,331 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Urambo (10,308 ha, 53.3% of the area planted with beans in the region) (Chart 3.34 and Map 3.16), however, the largest area planted with beans per household was in Igunga district (0.7 ha) (Chart 3.35). With exception of Igunga district, the variations in area planted with beans per household for the rest of the districts were small ranging from 0.2 ha in Nzega districts to 0.4 ha in Urambo and Sikonge districts (Map 3.17). In Tabora region, bean production has increased over the period 1995 to 2003 from 1,423 tonnes in 1995 to 7,143 tonnes in 2003 (Chart 3.36). Chart 3.33 Area Planted and Yield of Major Pulse Crops 0 5,000 10,000 15,000 20,000 25,000 Beans Bambaranuts Cowpeas Chick Peas Green GramMung Beans Crop Area Planted (Ha) 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 Yield (Kg/Ha) Area Planted Yield(Kg/Ha) Chart 3.34 Percent of Bean Planted Area and Pecent of Total Land with Beans by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Urambo Uyui Sikonge Tabora Urban Nzega Igunga District Percent of Land 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.7 0.4 0.4 0.3 0.3 0.2 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Area per Household Igunga Urambo Sikonge Uyui Tabora Urban Nzega District Chart 3.35 Area Planted per Household by District Chart 3.36 Time Series Data on Beans Production - TABORA 1.4 3.6 10.4 1.1 24.3 7.1 0.0 5.0 10.0 15.0 20.0 25.0 30.0 1994/95 1995/96 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Tabora Urban Nzega Sikonge Urambo Igunga Uyui 4,388ha 2,326ha 3,316ha 1,829ha 8,795ha 736ha 0.9t/ha 0.8t/ha 0.9t/ha 1.1t/ha 1.9t/ha 1.5t/ha 8,000 to 9,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Sikonge Uyui Nzega Igunga Tabora Urban Urambo 0.5ha 0.5ha 0.4ha 0.4ha 0.6ha 0.5ha 0.56 to 0.61 0.52 to 0.56 0.48 to 0.52 0.44 to 0.48 0.4 to 0.44 Area Planted per Household Map 3.14 TABORA Planted Area and Yield of Cassava by District Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.15 TABORA Area Planted per Cassava Growing Household by District Yield(t/ha) RESULTS 28 Tabora Urban Uyui Nzega Igunga Urambo Sikonge 0.3ha 0.2ha 0.7ha 0.4ha 0.4ha 0.3ha 0.6 to 0.7 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 1,439ha 3,654ha 10,308ha 1,064ha 319ha 2,547ha 0.2t/ha 0.3t/ha 0.4t/ha 1.5t/ha 0.2t/ha 0.3t/ha 8,000 to 11,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.16 TABORA Planted Area and Yield of Beans by District Map 3.17 TABORA Area Planted per Beans Growing Household by District Yield(t/ha) RESULTS 29 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 Charts 3.36 and 3.37 show that, whilst the area under beans production remained fairly constant the previous 4 years the quantity produced and the yield were fluctuating. The production increased rapidly in 1999/2000 due to the high yield of that year whilst the production decreased in the 2002/03 due to rapid decrease of yield (Chart 3.37). 3.3.7 Oil Seed Production The total production of oilseed crops was 31,877 tonnes planted on an area of 69,863 hectares representing 13 percent of the total area planted with annual crops. Groundnuts were the most important oilseeds with 68,730 ha (98.4% of the total area planted with oil seeds), followed by simsim (0.8%), sunflower (0.7%) and soya beans (0.1%) (Chart 3.38). The yield of groundnuts was 460 kg/ha. Sunflower had a yield of 292 kg/ha, soya beans of 213 kg /ha and simsim 172 kg/ha. In terms of production, groundnuts at 31,618 tonnes, accounted for 99.2 percent of the total production of oil seeds, followed by sunflower (0.5%) and simsim (0.3%). The production of soya beans was very small while castor seeds were not produced at all. 3.3.7.1 Groundnuts The number of households growing groundnuts in Tabora region was 143,462. The total production of groundnuts in the region was 31,618 tonnes from a planted area of 68,730 hectares resulting in a yield of 0.5 t/ha. There was a large increase in the production of groundnuts over the period 1995 to 2003, from 9,876 tonnes in 1994/95 to 31,618 tonnes in 2002/03. The area planted increased from 12,120 hectares in 1994/95 to 32,184 hectares in 1995/96 and 68,730 hectares in 2002/03 (Chart 3.39). Twenty nine percent of the area planted with groundnuts was located in Nzega District (19,722 ha) followed by Urambo (17,001 ha, 25%), Uyui (11,660 ha, 17%), Igunga (10,391 ha, 15%), Sikonge (7,863 ha, 11%) and Tabora Urban (2,093 ha, 3%). (Chart 3.40 and Map 3.18). Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Groundnuts 68,730 31,618 460.0 Simsim 548 94 171.9 Sunflower 510 149 291.8 Soya Beans 75 16 213.3 Total 69,863 31,877 Chart 3.37 Time Series of Beans Planted Area and Yield - TABORA 0 10000 20000 30000 40000 50000 1995/96 1998/99 1999/00 2002/03 Agriculture Year Area (Hectares) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Yield (T/Ha) Area Yield Chart 3.38 Area Planted and Yield of Major Oil Seed Crops 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Groundnuts Simsim Sunflower Soya Beans Crop Area Planted (Ha) 0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.5 Yield (Kg/Ha) Area Yield Chart 3.39 Time Series Data on Groundnut Production - TABORA 0 10000 20000 30000 40000 1994/95 1995/96 2002/03 Year Production (Tonnes) RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 31 The highest proportion of land with groundnuts was found in Nzega followed by Sikonge, Urambo, Uyui, Tabora Urban and Igunga. planted per household depicts small variations in area planted among the districts (Chart 3.41 and Map 3.19). The largest area planted per groundnut growing household was found in Sikonge District (0.6 ha) and the lowest was in Tabora Urban with 0.36 ha. The range between the district with the highest and the lowest area 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. Reliable historical data for time series analysis of fruit and vegetables were not available.The total production of fruits and vegetables was 5,847 tonnes. The most cultivated fruit and vegetable crop was onion with a production of 2,550 tonnes (44% of the total fruit and vegetables produced) followed by tomatoes (2,522t, 43%), radish (419t, 7%), amaranths (98t, 1.7%), bitter aubergine (85t, 1.4%) and cabbage (55t, 0.9%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 3,048 kg/ha, onions (1,692 kg/ha), amaranths (1,632 kg/ha) and radish (1,480 kg/ha). Cabbages and bitter aubergine had yields of 1,140 kg/ha and 872 kg/ha respectively (Chart 3.42). Table 3.6: Area, Quantity Harvested and Yield of Fruit and Vegetable Crops Crops Area Planted (ha) Quantity Harvested (tonnes) Yield (kg./ha) Onion 1,507 2,550 1,692 Tomatoes 827 2,522 3,048 Radish 283 419 1,480 Bitter Aubergine 97 85 872 Amaranths 60 98 1,632 Cabbage 48 55 1,140 Pumpkins 38 53 1,408 Okra 21 31 1,469 Egg Plant 12 11 865 Ginger 5 13 2,371 Cucumber 3 2 790 Chillies 1 7 5,558 Total 2,904 5,847 Chart 3.40 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Nzega Urambo Uyui Igunga Sikonge Tabora Urban District Percent of Land 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.0 0.2 0.4 0.6 0.8 Area per Household ((Ha) Sikonge Igunga Urambo Uyui Nzega Tabora Urban District Chart 3.41 Area Planted per Groundnut Growing Households by District Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 200 400 600 800 1,000 1,200 1,400 1,600 Onion Tomotoes Radish Bitter Aubergine Amaranths Cabbage Others Crop Area Planted (ha) 0 500 1000 1500 2000 2500 3000 3500 Yield (kg/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.4ha 0.5ha 0.5ha 0.4ha 0.5ha 0.6ha 0.56 > 0.52 to 0.56 0.48 to 0.52 0.44 to 0.48 0.4 to 0.44 Uyui Sikonge Tabora Urban Nzega Urambo Igunga 11,660ha 7,863ha 19,722ha 2,093ha 17,001ha 10,391ha 0.5t/ha 0.3t/ha 0.5t/ha 0.4t/ha 0.3t/ha 0.6t/ha 16,000 to 20,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.18 TABORA Planted Area and Yield of Groundnuts by District Map 3.19 TABORA Area Planted per Groundnuts Growing Household by District Yield(t/ha) RESULTS 32 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 33 3.3.8.1 Onions The number of households growing onion in the region was 3,250. This represented 1.4 percent of the total crop growing households. Igunga district had the largest planted area of onions (80.4% of the total area planted with tomatoes in the region), followed by Nzega (10%), Urambo (4.8%), Tabora Rural (2.7%) and Uyui (2%) (Map 3.20). The district with the highest proportion of land under onions was Igunga, followed by Tabora Urban. With exception of Igunga district, the rest of the districts had relatively small percentages of land under onion (Chart 3.43). The largest area planted per onion growing household was found in Igunga district (0.8 ha) followed by Nzega and Tabora Urban (0.2 ha) and Uyui and Urambo (0.1 ha each) (Chart 3.44 and Map 3.21). The total area planted with onion accounted for 0.3 percent of the total area planted with annual crops in the region. 3.3.8.2 Tomatoes The number of households growing tomatoes in the region was 5,471. This represented 2.3 percent of the total crop growing households. Uyui district had the largest planted area for tomatoes (31% of the total area planted with tomatoes in the region), followed by Tabora Urban (27%), Urambo (21%), Nzega (14%), Igunga (6%) and Sikonge (1%) (Map 3.22). The highest proportion of land with onion was found in Tabora Urban, followed by Uyui. All the districts had relatively low percentage of land used for tomatoes production (Chart 3.45). The largest area planted per onion growing household was found in Tabora Urban district (0.19 ha) followed by Nzega (0.16 ha), Uyui (0.15 ha), Igunga (0.13 ha) Urambo (0.12 ha) and Sikonge (0.1 ha) (Chart 3.46 and Map 3.23). The total area planted with tomatoes accounted for 0.2 percent of the total area planted with annual crops in the region. Chart 3.43 Percent of Onion Planted Area and Percent of Total Land with Onion by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 Igunga Nzega Urambo Tabora Urban Uyui Sikonge District Percent of Land 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.0 0.2 0.4 0.6 0.8 1.0 A rea per H o useho ld (H a ) Igunga Nzega Tabora Urban Uyui Urambo Sikonge District Chart 3.44 Area Planted per Household by DistrictArea/Hh Chart 3.45 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 10.0 20.0 30.0 40.0 Uyui Tabora Urban Urambo Nzega Igunga Sikonge District Percent of Land 0.0 0.5 1.0 1.5 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.04 0.08 0.12 0.16 0.20 Area per H ousehold Tabora Urban Nzega Uyui Igunga Urambo Sikonge District Chart 3.46 Area Planted per Tomato Growing Household by District RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 34 3.3.8.3 Amaranths The number of households growing amaranths in the region was 568. This represented 0.07 percent of the total crop growing households. Urambo district had the largest planted area of amaranths (36 ha, 60% of the total area planted with amaranths in the region), followed by Tabora Urban (24 ha, 40%). The rest of the districts did not plant amaranths (Chart 3.47 and Map 3.24 and 3.25). The total area planted with amaranths accounted for 0.01 percent of the total area planted with annual crops in the region. 3.3.8.4 Cabbage The number of households growing cabbage in the region was 246. This represented 0.10 percent of the total crop growing households. Uyui district had the largest planted area for cabbage (42 ha, 86% of the total area planted with amaranths in the region), followed by Tabora Urban (7 ha, 14%). Rest of the districts had not planted cabbages (Chart 3.48). The total area planted with cabbage accounted for 0.01 percent of the total area planted with annual crops in the region. 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. Of the 54,948 ha planted with other annual crops, tobacco was the most prominent followed by cotton. Pyrethrum was also planted but area planted was very small. 3.3.9.1 Tobacco The quantity of tobacco produced was 29,613 tonnes. Tobacco had a planted area of 32,490 ha. Tobacco production was concentrated in three districts with Urambo having the largest planted area (15,565 ha, 48% of total area planted with tobacco in the region), followed by Uyui (9,635 ha, 29%), Sikonge (5,735 ha, 18%), Nzega (1,078 ha 3%), Tabora Urban (246 ha, 0.8%) and Igunga (230 ha, 0.7%) (Chart 3.50) (Map 3.26 and 3.37). Chart 3.47 Percent of Amaranthus Planted Area and Percent of Total Land with Amaranths by District 0 20 40 60 80 Urambo Tabora Urban Nzega Igunga Uyui Sikonge District P ercent of Land 0.00 0.04 0.08 0.12 0.16 Percent Area Pla nted of Total Land Area Percent of Land Proportion of Land Chart 3.48 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 75.0 100.0 Uyui Tabora Urban Nzega Igunga Urambo Sikonge District Percent of Land 0.00 0.01 0.02 0.03 0.04 0.05 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted with Annual Cash Crops Cotton, 22,409, 41% Pyrethrum, 49, 0% Tobacco, 32,490, 59% Chart 3.50 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Urambo Uyui Sikonge Nzega Tabora Urban Igunga District Percent of Land 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Sikonge Urambo Tabora Urban Uyui Nzega Igunga 0ha 0.1ha 0.2ha 0.1ha 0.2ha 0.8ha 0.64 to 0.8 0.48 to 0.64 0.32 to 0.48 0.16 to 0.32 0 to 0.16 Tabora Urban Uyui Igunga Nzega Urambo Sikonge 41ha 30ha 1,212ha 151ha 72ha 0ha 1.2t/ha 5.5t/ha 1.2t/ha 2t/ha 8.2t/ha 0t/ha Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.20 TABORA Planted Area and Yield of Onions by District Map 3.21 TABORA Area Planted per Onions Growing Household by District Yield(t/ha) 1,200 to 1,300 900 to 1,200 600 to 900 300 to 600 0 to 300 RESULTS 35 Sikonge Tabora Urban Uyui Urambo Nzega Igunga 0.1ha 0.2ha 0.2ha 0.1ha 0.2ha 0.1ha 0.18 to 0.2 0.16 to 0.18 0.14 to 0.16 0.12 to 0.14 0.1 to 0.12 Tabora Urban Uyui Sikonge Urambo Nzega Igunga 221 255 5ha 173ha 120ha 54ha 3.4% 2.5t/ha 1.5t/ha 2.4t/ha 3.5t/ha 3% 200 to 260 150 to 200 100 to 150 50 to 100 0 to 50 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.22 TABORA Planted Area and Yield of Tomatoes by District Map 3.23 TABORA Area Planted per Tomatoes Growing Household by District Yield(t/ha) RESULTS 36 Sikonge Tabora Urban Uyui Urambo Igunga Nzega 0ha 0.1ha 0.1ha 0ha 0 ha 0ha Area Planted per Household 0.08 to 0.1 0.06 to 0.08 0.04 to 0.06 0.02 to 0.04 0 to 0.02 Urambo Igunga Tabora Urban Nzega Uyui 0ha 36ha 0ha 0ha 24ha 0ha 0t/ha 0.9t/ha 0t/ha 0t/ha 2.8t/ha 0t/ha Sikonge 28 > 21 to 28 14 to 21 7 to 14 0 to 7 Tanzania Agriculture Sample Census Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.24 TABORA Planted Area and Yield of Amaranths by Map 3.25 TABORA Area Planted per Amaranths Growing Household by District Yield(t/ha) District RESULTS 37 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 246ha 9,635ha 15,565ha 1,078ha 230ha 5,735ha 0.8t/ha 0.9t/ha 0.8t/ha 0.4t/ha 0.9t/ha 1.1t/ha 12,000 to 16,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tabora Urban Uyui Urambo Igunga Sikonge 0.8ha 1ha 1.2ha 1ha 1ha 1.2ha Nzega 1.12 to 1.21 1.04 to 1.12 0.96 to 1.04 0.88 to 0.96 0.8 to 0.88 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.26 TABORA Planted Area and Yield of Tobacco by Map 3.27 TABORA Area Planted per Tobacco Growing Household by District Yield(t/ha) District RESULTS 38 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 39 3.3.9.2 Cotton Only 9,932 tonnes of cotton were produced in Tabora Region on a planted area of 22,409 ha. The crop was grown in four districts only (Igunga, Urambo, Nzega and Uyui). Igunga had the largest area planted with cotton (21,751 ha, 97.1%) followed by Urambo district (494 ha, 2.2%), Nzega (145 ha, 0.6%) and Uyui (19 ha, 0.1%) (Map 3.28) and an average of 1.7 ha was grown per household (Map 3.29). 3.4 Permanent Crops Permanent crops (sometimes referred to as perennial crops) are crops that normally take over a year to mature and once mature can be harvested for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produce only one harvest, whilst other varieties survive for more than one year and produce several harvests. In this census, cassava is treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore no time series analysis is made in this section. The area of smallholders planted with permanent crops was 9,931 hectares (2% of the area planted with crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area of crops planted more than once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage of physical area planted with permanent crops would be higher than indicated in Chart 3.51. The most important permanent crop in Tabora region is mango which accounts for a planted area of 3,807 ha, (38.3% of the planted area of all permanent crops) followed by palm oil (2,159 ha, 21.7%), banana (1,599 ha, 16.1%), pawpaw (670 ha, 6.7%) and guava (656 ha, 6.6%). All the remaining permanent crops accounted for 10.5 percent of the total area planted with permanent crops (Chart 3.52). Urambo district had the largest area under smallholder permanent crops (5,820 ha, 58.6%). This is followed by Nzega (1,429 ha, 14.4%), Uyui (1,287 ha, 13%), Tabora Urban (932 ha, 9.4%), Igunga (327 ha, 3.8%) and Sikonge (85 ha, 0.9%). However, Tabora Urban had the largest area per permanent crop growing household (0.8 ha) followed by Urambo and Uyui (0.4 ha), Nzega (0.3 ha) and Sikonge (0.1 ha) (Chart 3.53). Chart 3.53 Percent of Area Planted and Average Planted Area with Permanent Crops by District 58.6 0.9 3.8 9.4 13.0 14.4 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Urambo Nzega Uyui Tabora Urban Igunga Sikonge District % of Total Area Planted 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Average Panted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.51 Area Planted Annual and Permanent Crops Annual Crops, 532,615, 98% Permanent Crops, 9,931, 2% Chart 3.52 Area Planted with Main Permanent Crops Palm Oil, 2,159, 22% Banana, 1,599, 16% Mango, 3,807, 38% Pawpaw, 670, 7% Guava, 656, 7% Orange, 440, 4% Others, 132, 1% Coconut, 54, 1% Lime/Lemon, 110, 1% Sugarcane, 303, 3% RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Tabora Urban had the highest percent (5.0%) followed by Urambo (4.8%), Igunga (1.3%), Uyui (1.3%), Nzega (0.3%) and Sikonge (0.2%). 3.4.1 Mango The total production of mangoes by smallholders was 20,763 tonnes. In terms of area planted, mango was the most important permanent crop grown by smallholders in the region. They were grown by 9,338 households (4% of the total crop growing households). The average area planted with mangoes per household was relatively small at around 0.4 ha per mangoes growing household and the average yield obtained by smallholders was 45,600 kg/ha from a harvest area of 455 hectares. Urambo had the largest area of mangoes in the region (1,618 ha, 42.5%) followed by Tabora Urban (788 ha, 20.7%), Nzega (649 ha, 17.0%), Uyui (432 ha, 11.3%), Igunga (268 ha, 7.0%) and Sikonge (53 ha, 1.4%) (Map3.30). However, the average area planted with mangoes per mango growing household was highest in Tabora Urban (1.9 ha) followed by Urambo, Uyui and Igunga (0.4 ha each), Nzega (0.3 ha) and Sikonge (0.1 ha) (Chart 3.54 and Map 3.31). 3.4.2 Palm Oil The total production of palm oil by smallholders was 416 tonnes. In terms of area planted, palm oil was the second most important permanent crop grown by smallholders in the region. It was grown by 3,425 households (1.5% of the total crop growing households). The average area planted with palm oil per household was at around 0.6 ha per palm oil growing household and the average yield obtained by smallholders was 3,525 kg/ha from a harvest area of 118 hectares. Urambo had the largest area of palm oil in the region (1,858 ha, 86.1%) followed by Uyui (291 ha, 13.5%) and Tabora Urban (10 ha, 0.4%). Palm oil production was not reported in the rest of the districts (Map 3.32). However, the average area planted with palm oil per palm oil planting household was highest in Uyui (0.7 ha) followed by Urambo (0.6 ha) and Tabora Urban (0.4 ha) (Chart 3.55 and Map 3.33). 3.4.3 Banana The total production of banana by smallholders was 2,616 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 5,058 households (2.1% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.32 ha per banana growing household and the average yield obtained by smallholders was 5,300 kg/ha from a harvested area of 490 hectares. Chart 3.54 Percentage of Area Planted with Mango and Average Planted Area per Household by District 1.4 7.0 11.3 17.0 20.7 42.5 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 Urambo Tabora Urban Nzega Uyui Igunga Sikonge District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Average Area Planted per Household % of Total Area Planted Average Planted Area per Household Chart 3.55 Percent of Area Planted with Palm Oil and Average Planted Area per Household by District 0.0 0.0 0.0 0.4 13.5 86.1 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Uyui Tabora Urban Nzega Igunga Sikonge District % of Total Area Planted 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 41 Urambo had the largest planted area of bananas in the region (1,362 ha, 85.2%) followed by Nzega (92 ha, 5.7%), Uyui (70 ha, 4.4%), Tabora Urban (56 ha, 3.5%) and Sikonge (19 ha, 1.2%). Banana was not planted in Igunga (Map 3.34). However, the area planted with banana per banana growing household was highest in Sikonge (0.40 ha), followed by Urambo (0.36 ha), Tabora Urban (0.24 ha), Uyui (0.17 ha) and Nzega (0.15 ha) (Chart 3.56 and Map 3.35). 3.4.4 Pawpaw The total production of pawpaw by smallholders was 926 tonnes. In terms of area planted, pawpaw was the fourth most important permanent crop grown by smallholders in the region. It was grown by 2,745 households (0.4% of the total crop growing households). The average area planted with pawpaw per household was relatively small at around 0.2 ha per pawpaw growing household and the average yield obtained by smallholders was 4,700 kg /ha from a harvest area of 197 hectares. Urambo has the largest area of pawpaw in the region (516 ha, 77.1%) followed by Nzega (84 ha, 12.6%), Igunga (40 ha, 6.0%), Uyui (25 ha, 3.7%) and Tabora (4 ha, 0.6%) (Map 3.36). The average area planted per pawpaw growing household was highest in Urambo (0.34 ha), followed by Nzega (0.30 ha), Igunga (0.09 ha), Uyui (0.06 ha) and Tabora Urban (0.04 ha) (Map 3.37). Sikonge district reported no pawpaw production. Chart 3.57 Percent of Area Planted with Pawpaw and Average Planted Area per Household by District 77.0 12.5 6.0 3.8 0.6 0.0 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Nzega Igunga Uyui Tabora Urban Sikonge District % of Total Area Planted 0.00 0.10 0.20 0.30 0.40 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.58 Number of Households by Method of Land Clearing 208,502 19,557 3,262 2,361 670 150 0 50,000 100,000 150,000 200,000 250,000 Mostly Hand Slashing Mostly Bush Clearance No Land Clearing Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.56 Percent of Area Planted with Banana and Average Planted Area per Household 0.0 1.2 3.5 4.4 5.7 85.1 0.0 20.0 40.0 60.0 80.0 100.0 Urambo Nzega Uyui Tabora Urban Sikonge Igunga District % of Total Area Planted 0.00 0.10 0.20 0.30 0.40 0.50 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 42 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period while the other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widely used method for land clearing. The area cleared by hand slashing in the region was 451,452 ha which represented 88.5 percent of the total planted area. Burning and tractor slashing are less important methods for land clearing and they represented 0.9 and 0.3 percent respectively (Table3.7). 3.5.2 Methods of Soil Preparation Ox-ploughing is the most method used for soil preparation and was used in an area of 261,638 ha which represented 51 percent of the total planted area, closely followed by hand cultivation (244,900 ha, 48%) and tractor ploughing (5,117 ha, 1%). In Tabora region, Igunga district had the largest planted area cultivated with oxen (129,795 hectares, 25.4%) followed by Nzega (64,739 ha, 12.7%), Uyui (31,866 ha, 6.2%), Sikonge (18,060 ha, 3.5%), Urambo (15,290 ha, 2.44%), and Tabora Urban (1,888 ha, 0.4%). Table 3.7: Land Clearing Methods Method of Land Clearing Number of Households Area Planted % Mostly Hand Slashing 208,502 451,452 88.5 Mostly Bush Clearance 19,557 46,763 9.2 No Land Clearing 3,262 5,635 1.1 Mostly Burning 2,361 4,611 0.9 Mostly Tractor Slashing 670 1,535 0.3 Other 150 122 0.0 Total 234,501 510,117 100.0 Chart 3.59 Area Cultivated by Cultivation Method Mostly Hand Cultivation, 244,900, 48% Mostly Tractor Ploughing, 5,117, 1% Mostly Oxen Ploughing, 261,638, 51% 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 A r ea C u ltiv a te d ( h a ) Igunga Nzega Uyui Sikonge Urambo Tabora Urban District Chart 3.60 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand Cultivation Mostly Tractor Ploughing Igunga Tabora Urban Nzega Uyui Sikonge 21,751ha 145ha 0ha 494ha 0ha 19ha 0.4t/ha 0.4t/ha 0t/ha 0.8t/ha 0t/ha 1.5t/ha Urambo 16,000 to 22,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tabora Urban Uyui Nzega Igunga Sikonge 0ha RESULTS 43 0.6ha 0.2ha 1.7ha 1.3ha 0ha Urambo Planted Area (ha) Map 3.28 TABORA Planted Area and Yield of Cotton by District Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Map 3.29 TABORA Area Planted per Cotton Growing Household by District Yield(t/ha) 1.2 to 1.7 0.9 to 1.2 0.6 to 0.9 0.3 to 0.6 0 to 0.3 Tabora Urban Uyui Urambo Igunga Nzega Sikonge 1.9ha 0.4ha 0.4ha 0.4 0.3ha 0.1ha 1.7 > 1.3 to 1.7 0.9 to 1.3 0.5 to 0.9 0.1 to 0.5 Igunga Nzega Tabora Urban Urambo Uyui Sikonge 268ha 649ha 1,618ha 788ha 432ha 53ha 17.9t/ha 50.8t/h 72.5t/ha 19.1t/ha 31.1t/ha 9.8t/ha 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Planted Area (ha) Map 3.30 TABORA Planted Area and Yield of Mango by District Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Map 3.31 TABORA Area Planted per Mango Growing Household by District Yield(t/ha) RESULTS 44 Tabora Urban Urambo Nzega Igunga Uyui Sikonge 0.4ha 0.6ha 0ha 0ha 0.7ha 0ha 0.56 to 0.7 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Tabora Urban Uyui Sikonge Nzega Igunga 10ha 0ha 1,858ha 0ha 0ha 291ha 1t/ha 0t/ha 0t/ha 3.6t/ha 0t/ha 0t/ha Urambo 1,600 to 1,900 1,200 to 1,600 800 to 1,200 400 to 800 0 to 400 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.32 TABORA Planted Area and Yield of Palm Oil by District Map 3.33 TABORA Area Planted per Palm Oil Growing Household by District RESULTS 45 Yield(t/ha) Tabora Urban Uyui Urambo Nzega Igunga Sikonge 0.2ha 0.4ha 0.2ha 0ha 0.2ha 0.4ha RESULTS 46 0.32 to 0.4 0.24 to 0.32 0.16 to 0.24 0.08 to 0.16 0 to 0.08 Sikonge Tabora Urban Uyui Nzega Igunga 19ha 56ha 70ha 1,362ha 0ha 4.1% 9.3% 0.8% 0% 5.5% 7.3% Urambo Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.34 TABORA Planted Area and Yield of Banana by District Map 3.35 TABORA Area Planted per Banana Growing Household by District Yield(t/ha) 1,200 to 1,400 900 to 1,200 600 to 900 300 to 600 0 to 300 Tabora Urban Uyui Sikonge Urambo Nzega Igunga 0.04ha 0.09ha 0.06ha 0ha 0.34ha 0.3ha 0.28 to 0.34 0.21 to 0.28 0.14 to 0.21 0.07 to 0.14 0 to 0.07 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 4ha 516ha 84ha 40ha 26ha 0ha 0.6t/ha 0t/ha 8.8t/ha 5.1t/ha 3.4t/ha 0.5t/ha 400 to 600 300 to 400 200 to 300 100 to 200 0 to 100 Tanzania Agriculture Sample Census Area Planted per Household Area Planted per Household Planted Area (ha) Planted Area (ha) Map 3.36 TABORA Planted Area and Yield of Pawpaw by District Map 3.37 TABORA Area Planted per Pawpaw Growing Household by District Yield(t/ha) RESULTS 47 RESULTS _________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 88,125 ha which represents 17 percent of the total area planted with the annual crops and vegetables area. Cash crops had the largest area planted with improved seeds (47,636 ha, 62% of the planted area with improved seeds) followed by cereals (24,144 ha, 31%), Oil seeds (2,568 ha, 3%), pulses (1,550 ha, 2%), fruits and vegetables (1,526 ha, 2%) and roots and tubers (236 ha, 0.3%) (Chart 3.62). However, the use of improved seed in cash crops and fruits and vegetables is much greater than in other crop types (87% and 53% respectively), only 2.2 percent of the planted area for root and tuber crops used improved seed (Chart 3.63). 3.5.4 Fertilizer Use The use of fertilisers on annual crops is small with a planted area of only 179,816 ha (34% of the total planted area in the region) having been applied with fertilizers. The planted area without fertiliser for annual crops was 352,800 hectares representing 66 percent of the total area planted with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 101,423 ha which represented 56 percent of the planted area applied with fertilisers in the region. This was followed by inorganic fertilizers (64,676 ha, 36%). Compost manure was used on a very small area which represented only 8 percent of the area planted with fertilizers. Chart 3.62 Planted Area with Improved Seed by Crop Type Cash Crops, 47,636, 62% Cereals, 24,144, 31% Pulses, 1,550, 2% Oilseeds , 2,568, 3% Roots & Tubers, 236, 0% Fruits & Vegetables, 1,526, 2% 0 20 40 60 80 100 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.63 Percent of Crop Type Planted with Improved Seed - Annuals Chart 3.61 Planted Area of Improved Seeds - TABORA Without Improved Seeds, 444,490, 83% With Improved Seeds, 88,125, 17% 0 50,000 100,000 150,000 Area (ha) Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.65 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.64 Area of Fertiliser Application by Type of Fertiliser No Fertilizer Applied, 352,800, 66% Mostly Compost, 13,717, 3% Mostly Inorganic Fertilizer, 64,675, 12% Mostly Farm Yard Manure, 101,423, 19% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 49 The highest percentage of the area planted with fertilizer (all types) was in Nzega (26.4%) followed by Urambo (24.2%), Igunga (12.6%), Sikonge (12.6%) and Tabora Rural (3.6%) (Table 3.8 and Charts 3.64 and 3.65). Most annual crop growing households do not use any fertiliser (approximately 170,306 households, 72.3%) (Map 3.38). Table 3:9 Number of Crop Growing Households and Planted Area by Type of Fertilizer Use and District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Nzega 12,860 38,652 3,087 6,086 1,413 2,767 48,206 61,817 65,566 109,322 Igunga 3,998 20,436 460 625 862 1,562 39,705 119,830 45,025 142,453 Uyui 3,850 16,464 1,124 2,750 8,428 17,736 27,811 58,704 41,212 95,654 Urambo 3,102 12,782 1,364 3,716 13,908 27,027 35,746 71,339 54,120 114,863 Sikonge 1,943 9,520 47 331 5,258 12,859 12,217 30,005 19,464 52,716 Tabora Urban 1,228 3,570 160 209 2,197 2,724 6,622 11,104 10,206 17,606 Total 26,982 101,423 6,240 13,717 32,066 64,676 170,306 352,800 235,594 532,615 3.5.4.1 Farm Yard Manure Use The total planted area applied with farm yard manure in Tabora region was 101,423 ha. The number of households that applied farm yard manure in their annual crops was 26,982 (Table 3.9). Cereals had the highest percent of the total area planted with applied farm yard manure (87.0%), followed by oil seeds (8.0%), pulses (2.7%), root and tuber (1.0%), cash crops (1.0%) and fruits and vegetables (0.4%). Also, cereals had the highest proportion of the planted area with farm yard manure (25% of the total area of cereals in Tabora). This was followed by fruits and vegetables (15%), oil seeds (12%), pulses (11%), roots and tubers (3%) and cash crops (2%) (Chart 3.67a). Table3.8 Planted Area by Type of Fertilizer Use and District Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Nzega 38,652 6,086 2,767 47,505 61,817 Igunga 20,436 625 1,562 22,623 119,830 Uyui 16,464 2,750 17,736 36,950 58,704 Urambo 12,782 3,716 27,027 43,525 71,339 Sikonge 9,520 331 12,859 22,710 30,005 Tabora Urban 3,570 209 2,724 6,503 11,104 Total 101,423 13,717 64,675 179,816 352,800 Chart 3.66 Planted Area with Farm Yard Manure by Crop Type - TABORA Pulses, 2,789, 3% Roots & Tubers, 975, 1% Cash Crop, 902, 1% Oilseeds, 8,118, 8% Fruits & Vegetables, 433, 0% Cereals, 88,206, 87% 0 5 10 15 20 25 30 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.67a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 Farm yard manure was mostly used in Nzega (35.4% of the total planted area in the district), followed by Tabora Urban (24.0%), Sikonge (22.4%), Uyui (17.2%), Igunga (14.3%) and Urambo (11.1%) (Chart 3.67b). For permanent crops, most farm yard manure was used in the production of palm oil (32.%), followed by mango (25.%), banana (23.%), pawpaw (12%) oranges (2%), sugar cane (1.3%), coconut (1.1%), mandarine/tangerine, lemon/lime (1.3%), guava (0.3%) and jack fruits (0.2%) 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Tabora region was 64,676 ha which represents 12.1 percent of the total area planted with annuals in the region and 36 percent of the total planted area with fertilizers. The number of households that applied inorganic fertilizer on their annual crops was 32,066 representing 13.6 percent of the total household planted annual crops (Table 3.10). The largest area applied with inorganic fertilizers was on cash crops (47.4% of the total area applied with inorganic fertilizers) followed by cereals (47.0), fruits and vegetables (2.6%), oil seeds (1.5%), pulses (1.1%) and root and tubers (0.4%) (Chart 3.68). However, the proportion of planted area applied with inorganic fertilizer for fruit and vegetables was 57 percent. This was followed by cash crops (56%), cereals (9%), pulses (23%), oil seeds (1%) and roots and tubers (1%) (Chart 3.69a). Inorganic fertiliser was mostly used in Urambo (23.5% of the total planted area in the district), followed by Uyui (18.5%), Sikonge (6.4%), Nzega (2.5%) and Igunga (1.1%). Tabora Urban reported to have used no inorganic fertilisers (Chart 3.67b). In permanent crops inorganic fertilizers were used in orange (76.2%), followed by sugar cane (22.0%) and mango (1.8%). Chart 3.68 Planted Area with Inorganic Fertilizer by Crop Type - TABORA Cereals, 30,409, 47% Pulses, 712, 1% Cash Crop, 30,634, 47% Oilseeds, 993, 2% Fruits & Vegetables, 1,661, 3% Roots & Tubers, 267, 0% Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop 0 10 20 30 40 50 60 Percent of Planted A rea Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 69a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - TABORA Chart 3.69b Proportion of Planted Area Applied with Inorganic Fertilizer by District - TABORA 0.0 10.0 20.0 30.0 Urambo Uyui Sikonge Nzega Igunga Tabora Urban District P ercent Chart 3.67b Proportion of Planted Area with Farm Yard Manure by District - TABORA 0.0 10.0 20.0 30.0 40.0 Nzega Tabora Urban Sikonge Uyui Igunga Urambo District Percent RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 3.5.4.3 Compost Use The total planted area applied with compost was 13,717 ha which represents only 2.6 percent of the total area planted with annual crops in the region and 7.6 percent of the total planted area applied with fertiliser in the region. The number of households that applied compost manure on their annual crops was 6,240 representing 2.6 percent of the total households that planted annual crops (Table 3.9 and Chart 3.70a). The proportion of area applied with compost was very low for each type of crop (1 to 3%) (Chart 3.70b); however the distribution of the total area using compost manure shows that 67 percent of this area was cultivated with cereals, followed by oil seeds (16%), cash crops (7%) roots and tubers (5%), pulses (5%) and fruits and vegetables (0.1%) (Chart 3.70a). Compost was mostly used in Nzega (5.6% of the total planted area in the district) followed by Tabora Urban (3.2%). Other districts used very little compost (Chart 3.70c). In permanent crops, compost was mostly used in the production of orange (23.1%) followed by mango (22.3%), banana (20.5%), avocado (5.3%) palm oil (11.1%) lime/lemon (7.4%), pawpaw (7.3%), guava (7.3%) and sugar cane (1.0%). 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 115,141 ha of annual crops and vegetables. Insecticides are the most common pesticides used in the region (74% of the total area applied with pesticides). This was followed by fungicides (18%) and herbicides (8%) (Chart 3.71). 0 1 2 3 4 Percent of Planted Area Cereals Ro o ts & Tubers P uls es Oils eeds Fruits & Vegetables Cas h Cro p Crop Type Chart 3.70b Percentage of Planted Area with Compost by Crop Type - TABORA Chart 3.70c Proportion of Planted Area Applied with Compost by District - TABO RA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Nzega Urambo Uyui Tabora Urban Sikonge Igunga D is t ric t Chart 3.71 Planted Area (ha) by Pesticide Use Fungicides, 20,875, 18% Herbicides, 9,327, 8% Insecticides, 84,939, 74% Chart 3.70a Planted Area with Compost Manure by Crop Type - TABORA Pulses, 639, 5% Roots & Tubers, 685, 5% Oilseeds, 2,127, 16% Fruits & Vegetables, 15, 0% Cash Crop, 974, 7% Cereals, 9,276, 67% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 84,939 ha which represented 16 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with insecticides (42,110 ha, 49.6% of the total planted area with insecticides) followed by cash crops (36,819 ha, 43.3%), oil seeds (2,169 ha, 2.6%), pulses (1,629 ha, 1.9%), fruits and vegetables (1,588 ha, 1.9%) and roots and tubers (626 ha, 0.7%) (Chart 3.72). However, the percent of insecticides used in cash crops and fruits and vegetables is much greater than in other crop types (67.0% and 54.7% respectively), while only 2 percent of roots and tubers were applied with insecticides (Chart 3.73). Annual Crops with more than 50 percent insecticide use were cabbage (100%), ginger (100%), radish (92.2%), tobacco (85.3%) and onions (61.3%). Sikonge had the highest percent of planted area applied with insecticides (25.5% of the total planted area with annual crops in the district). This was closely followed by Uyui (23.6%) then Urambo (22.3%), Tabora Urban (21.3%), Igunga (9.7%) and Nzega (5.2%) (Chart3.74). 3.5.5.2 Herbicide Use The planted area applied with herbicides was 9,327 ha which represented 1.8 percent of the total area planted with annual crops and vegetables. Cereals had the largest planted area applied with herbicides (4,871 ha, 51%) followed by cash crops (2,761 ha, 30%), oil crops (738 ha, 8%), pulses (451 ha, 5%) and roots and tubers (340 ha, 4%) and fruits and vegetables (166 ha, 2%) (Chart 3.75). Chart 3.74 Percent of Planted Area Applied with Insecticide by District - TABORA 0.0 10.0 20.0 30.0 Sikonge Uyui Urambo Tabora Urban Igunga Nzega District Percent Chart 3.75 Planted Area Applied with Herbicide by Crop Type Roots & Tubers, 340, 4% Pulses, 451, 5% Oil Seeds & Oil Nuts, 738, 8% Cereals, 4,871, 51% Cash Crops, 2,761, 30% Fruits & Vegetables, 166, 2% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 P ercent o f P la nted A rea Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.73 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Planted Area Applied with Insecticides by Crop Type Roots & Tubers, 625, 1% Pulses, 1,629, 2% Oil Seeds & Oil Nuts, 2,169, 3% Fruits & Vegetables, 1,588, 2% Cereals, 42,110, 49% Cash Crops, 36,819, 43% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 However, the percent of herbicide use on fruits/ vegetables and cash crops was much greater than in other crop types (5.7% and 5.0% respectively) while only 1.1 percent of roots and tubers and 1.1 percent of oil seeds was applied with herbicides (Chart 3.76). The top six annual crops with highest percentage use of herbicides in terms of planted area were tomatoes (11.3%), tobacco (6.7%), yams (6.1%), onions (4.8%), cotton (2.6%) and beans (2.1%). Urambo had the highest percent of planted area applied with herbicides (3.1% of the total planted area with annual crops in the district). This was followed by Tabora Urban (2.2%) then Sikonge (1.9%), Uyui (1.7%) and Igunga (1.2%). The smallest percentage use was recorded in Nzega district (0.9%) (Chart 3.77). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 20,875 ha which represented 3.9 percent of the total area planted with annual crops and vegetables. Cash crops had the largest planted area applied with fungicides (9,013ha, 44%) followed by cereals (8,548 ha, 41%), fruits and vegetables (1,343 ha, 6%), oil seeds (1,011 ha, 5%) roots and tubers (508 ha, 2%) and pulses (451 ha, 2%) (Chart 3.78). However, the percentage use of fungicide in cash crops and cereals was much greater than in other crop types (8.2% and 7.4% respectively), while only 0.9 percent of fruits and vegetables was applied with fungicides (Chart 3.79). Annual crops with more than 40 percent fungicide use were ginger (100%), cucumber (100%), radish (92.2%) and onion (56.8%). Chart 3.77 Proportion of Planted Area Applied with Herbicides by District - TABORA 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Urambo Tabora Urban Sikonge Uyui Igunga Nzega District P ercent Chart 3.78 Planted Area Applied with Fungicide by Crop Type Roots & Tubers, 508, 2% Pulses, 451, 2% Oil Seeds & Oil Nuts, 1,011, 5% Fruits & Vegetables, 1,343, 6% Cereals, 8,548, 41% Cash Crops, 9,013, 44% 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.79 Percentage of Crop Type Planted Area Applied with Fungicide 0.0 2.0 4.0 6.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil Seeds & Oil Nuts Fruits & Vegetables Cash Crops Crop Type Chart 3.76 Percentage of Crop Type Planted Area Applied with Herbicides RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 Urambo had the highest percent of planted area with fungicides (7.4% of the total planted area with annual crops in the district). This was followed by Sikonge (5.5%), Tabora Urban (4.2%), Uyui (3.4%), Igunga (2.9%) and Nzega (1.2%) (Chart 3.80). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by draft animals (0.3%) and by powered tools (0.1%) while paddy was harvested by draft animals (0.1%) and powered animal (0.1) percent. All other cereals and annual crops were harvested by hand except small amount of oil seeds and cash crops which were harvested by machines (oil seeds - groundnuts were harvested by draft animals (0.3%) and powered tools (0.3%), cash crops – tobacco was harvested by draft animals (0.7%), powered tools (0.9%) and driven machine (0.9%). 3.5.7 Threshing Methods Hand threshing was the most common method used, with 99.1 percent of the total area planted with cereals being threshed by hand. Human powered tools and engine driven machines were used on cereal crops harvested from 0.1 percent and 0.8 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other agricultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation for different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Tabora region, the area of annual crops under irrigation was 34,866 ha representing 7 percent of the total area planted (Chart 3.81). The area under irrigation during the dry season was not reported. The district with the largest planted area under irrigation for annual crops was Urambo (9,624 ha, 27.6% of the total irrigated planted area with annual crops in the region). This is followed by Uyui (7,037 ha, 20.2%), Igunga (6,822 ha,19.6%), Nzega (6,125 ha, 17.6%), Tabora Urban (2,738 ha, 7.9%) and Sikonge (2,520 ha, 7.2%). When expressed as a percentage of the total area planted in each district, Tabora Urban had the higher percentage with 15.6 percent under irrigation. This was followed by Urambo (8.4%), Uyui (7.4%), Nzega (5.6%), Igunga (4.8%) and Sikonge (4.8%) (Chart 3.82) and Map 3.39). Chart 3.81 Area of Irrigated Land Unirrigated Area, 497,749, 93% Irrigated Area, 34,866, 7% Chart 3.82 Planted Area with Irrigation by District - TABORA 0 2,000 4,000 6,000 8,000 10,000 12,000 Urambo Uyui Igunga Nzega Tabora Urban Sikonge District Irrig a ted A rea (ha ) 0.0 4.0 8.0 12.0 16.0 20.0 P ercenta g e Irrig a tio n Irrigated Area Percent of Irrigated Land Chart 3.80 Proportion of Planted Area with Fungicide by District - TABORA 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 Urambo Sikonge Tabora Urban Uyui Igunga Nzega District Percent RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 Of all the different crops and in terms of proportion of the irrigated planted area, ginger, chillies and cucumber were the most irrigated crops with 100 percent irrigation followed by tomatoes (79.6%), onions (73.8%), amaranths (57.9%) and cabbages (44.2%). In terms of crop type, the area under irrigation for roots and tubers was 19,713 ha (56.5% of the total area under irrigation), followed by cereals with 10,780 ha (30.9%), fruit and vegetables (1,836 ha, 5.3%), cash crops (1,701 ha, 4.9%), oil seeds (741 ha, 2.1%) and pulses (94 ha, 0.3%). All of the irrigation on cereals was applied to maize, paddy and sorghum. The number of households practicing irrigation in Tabora region appears to have increased over the eight year intercensal period from 9,000 to 17,181 households. This may not be statically significant due to the small number of households sampled. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from dams (43% of households with irrigation). This was followed by wells (41%) and rivers (7%). Proportions of households that used boreholes and canals as a source of water for irrigation were very small being 4% and 5% respectively (Chart 3.84). Most households using irrigation in Uyui, Nzega and Igunga get their irrigation water from dams (79%, 61% and 60 % respectively). 3.6.3 Methods of Obtaining Water for Irrigation Hand bucket was the most common method of getting water for irrigation with 69 percent of households using this method. This was followed by gravity with 29 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.85). Most households that used the hand bucket for irrigation were Urambo (38.7%), followed by Uyui (23.6%), Nzega (11.1%), Sikonge (9.9%), Tabora Chart 3.84 Number of Household with Irrigation by Source of Water Well, 7,054, 41% Dam, 7,418, 43% Borehole, 654, 4% Canal, 859, 5% River, 1,196, 7% Canal River Well Dam Borehole Chart 3.85 Number of Households by Method of Obtaining Irrigation Water Hand Bucket, 11,828, 69% Gravity, 4,987, 29% Other, 293, 2% Hand Pump, 46, 0% Motor Pump, 26, 0% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.86 Number of Households with Irrigation by Method of Field Application Water Hose, 99, 1% Flood, 5,926, 34% Bucket / Watering Can, 10,821, 63% Sprinkler, 334, 2% Flood Bucket / Watering Can Sprinkler Water Hose Chart 3.83 Time Series of Households with Irrigation - TABORA 17,181 9,000 0 5,000 10,000 15,000 20,000 1995/96 2002/03 Agriculture Year Number of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 (9.0%) and Igunga (7.7%). Gravity was more common in Igunga with 49 percent of households using the method to get water for irrigation, followed by Nzega (32.5), Uyui (8.2%), Sikonge (6.2%), Urambo (2.5%) and Tabora Urban (1.6%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Tabora Urban used some hand and motor pumps for obtaining water. 3.6.4 Methods of Water Application Most households used bucket/watering can (63% of households using irrigation) as a method of field application. This was followed by flood irrigation (34%). Sprinklers and water hose were not widely used (2% and 1% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices or as seed for planting in the following season. The results for Tabora region show that there were 217,899 crop growing households (92.5% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 206,605 households storing 28,060 tonnes as of 1st January 2004. This was followed by groundnuts/bambaranuts (111,290 households, 6,695t), paddy (76,850 households, 11,758t), Pulses (50,527 households, 1,995t) and sorghum/millet (21,828 households, 6,195t). Other crops were stored in very small quantities. 3.7.1.1 Methods of Storage The region had 120,421 crop growing households storing their produce in sacks and/or open drums (55% of households that stored crops in the region). The number of households that stored their produce in locally made traditional cribs was 93,554 (43%). This was followed by improved locally made structure (2,312 households, 1%), unprotected piles (685 households, 0.3%), other methods (575 households, 0.3%) and airtight drums (351 households, 0.2 (Chart 3.88). Sacks and/or open drums were the dominant storage method in all districts, with the highest percent of households in Urambo using this method (70% of the total number of households storing crop products in the district). This was followed by Uyui (68%), Tabora Urban (59%), Nzega (54%), Sikonge (46%) and Igunga (27%) (Chart 3.89). Chart 3.87 Number of Households and Quantity Stored by Crop Type - TABORA 0 50,000 100,000 150,000 200,000 250,000 Maize Gnuts/Bamb Nuts Paddy Pulses Sorghum & Millet Cotton Tobacco Crop Number of Household 0 5,000 10,000 15,000 20,000 25,000 30,000 Quantity (t) Number of households Quantity stored (Tons) Chart 3.89 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Percent of households Locally Made Traditional Crib Improved Locally Made Crib Modern Store Sacks / Open Drum Airtight Drum Unprotected Pile Other Chart 3.88 Number of households by Storage Methods - TABORA Locally Made traditional Crib, 93,554, 43% Sacks / Open Drum, 120,421, 56% Modern Store, 0, 0% Airtight Drum, 351, 0% Other, 575, 0% Improved Locally Made Structure, 2,312, 1% Unprotected Pile, 685, 0% Sikonge Igunga Tabora Urban Nzega Urambo Uyui 2,520ha 6,822ha 6,125ha 9,624ha 2,738ha 7,037ha 4.8% 4.8 5.6% 8.4% 15.6% 7.4% 8,000 to 10,000 6,000 to 8,000 4,000 to 6,000 2,000 to 4,000 0 to 2,000 Uyui Sikonge Igunga Tabora Urban Nzega Urambo 46,116ha 51,227ha 59,851ha 76,141ha 84,091ha 1,725 86% 91.2% 80% 91.1% 93.7% 78.5% 80,000 to 90,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 Tanzania Agriculture Sample Census Percent of Planted Area (ha) with Irrigation Planted Area (ha) Planted Area (ha) Planted Area With No Application of Fertilizer Map 3.38 TABORA Planted Area and Percent of Planted Area with No Application of Fertilizer by District Map 3.39 TABORA Area Planted and Percent of Total Planted Area With Irrigation by District Percent of Planted Area (ha) with No Application of Fertilizer Planted Area (ha) With Irrigation RESULTS 57 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 58 The highest percent of households using locally made traditional cribs was in Igunga (72% of the total number of households storing crops) followed by Sikonge (50%), Nzega (45%), Tabora Rural (39%), Uyui (31%) and Urambo (27%). 3.7.1.2 Duration of Storage Most households (56.7% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of over 6 months (24.6%). The minority of households stored their crop for a period of less than 3 months (18.8%). Most households that stored pulses stored them for a period of 3 to 6 months followed by over 6 months. A small number of households stored pulses for the period of less than 3 months (Chart 3.90). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Tabora Urban (77.6%) followed by Urambo (57.4%), Nzega (57.2%), Uyui (56.7%), Igunga (52.9%) and Sikonge (49.1%) (Map 3.40). District comparison of duration of storage cannot be done for all crops combined. The analysis has therefore been done for maize only as it is the most commonly stored crop. In general, the quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st January 2004 (Chart 3.91). However, households in Igunga district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 90.8 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at a higher price (Chart 3.92). 0 30,000 60,000 90,000 120,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.90 Normal Length of Storage for Selected Crops Less than 3 Months Between 3 and 6 Months Over 6 Months 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Wheat Cotton Tobacco Gnuts Bamb Nuts Crop Type Chart 3.92 Number of Household by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others Chart 3.91 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 Nzega Urambo Igunga Uyui Sikonge Tabora Urban District Quantity (tonnes) 0 5 10 15 20 % Stored Quantity harvested Quantity stored % stored RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.7.1.4 The Magnitude of Storage Loss About 78.5 percent of households that stored crops had little or no loss. The proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as cotton, tobacco and paddy. The proportion of households that reported a loss of more than a quarter was greatest for maize (6.4% of the total number of households that stored maize). This was followed by sorghum and millet (3.4%), beans and pulses (2.4%), groundnuts/bambaranuts (1.3%) and paddy (0.7%). 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the crop. Agro-processing was practiced in most crop growing households in Tabora region (223,896 households, 95% of the total crop growing households) (Chart 3.93a). The percent of households processing crops was very high in all districts (above 80%). Igunga had the lowest percent of households processing crops (80% of crop growing households respectively) (Chart 3.93b). 3.7.2.1 Processing Methods Most households processed their crops using neighbour’s machines representing 85.8 percent (192,153 households). This was followed by those processing on-farm by hand (21,628 households, 9.7%) and farm machines (9,031 households, 4.0%). The remaining methods of processing were used by very few households (less than 1%). Table 3.10: Number of Households Storing Crops By Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Nzega 48,747 9,664 3,076 729 62,216 Igunga 31,956 3,628 1,041 114 36,739 Uyui 27,605 7,179 2,486 735 38,004 Urambo 38,296 10,218 3,083 488 52,084 Sikonge 16,937 1,215 684 335 19,172 Tabora Urban 7,518 1,479 405 282 9,684 Total 171,060 33,383 10,774 2,683 217,899 80 100 Percent of Households Processing Sikonge Tabora Rural Nzega Uyui Urambo Igunga District Chart 3.93b Percentage of Households Processing Crops by District Chart 3.93a Households Processing Crops Households not Processing, 11,725, 5% Households Processing, 223,896, 95% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 Although processing by machine was the most common processing method in all districts in Tabora region, however district differences existed. Nzega has the highest percent of hand processing (30.8%), followed by Urambo (22.2%), and Uyui (18.3%). Processing by trader was more common in Igunga and Nzega (71% and 25% respectively), whilst processing on farm by machine was more prevalent in Nzega, Urambo and Uyui (Chart 3.94). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely the main product and the by-product. The main product is the major product after processing and the by-product is the secondary after processing. For example the main product after processing maize is normally flour whilst the by-product is normally the bran. The main processed product was flour/meal with 201,164 households processing crops into flour (90%) followed by grain with 18,970 households (8%). The remaining products were produced by a small number of households (Chart 3.95). The number of households producing by-products accounted for 69 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 126,638 households (81%) followed by husks (23,999 households, 16%) and pulp (1,483 households, 1%). The remaining by-products were produced by a small number of households (Chart 3.96). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 99 percent of the total households that used primary processed product (Chart 3.97). Tabora Urban was the only district that used primary products as fuel for cooking. Chart 3.94 Percent of Crop Processing Households by Methods of Processiong 0 25 50 75 100 125 Sikonge Nzega Uyui Urambo Igunga Tabora Rural District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Factory By Co-operative Union By Trader Other Chart 3.95 Percent of Households by Type of Main Processed Product Grain 8% Oil 1% Juice 0.1% Rubber 0% Pulp 0.9% Flour / Meal 90% Chart 3.96 Number of Households by Type of By-product Oil, 265, 0% Juice, 123, 0% Shell, 832, 1% Other, 97, 0% Pulp, 1,483, 1% Cake, 1,023, 1% Bran, 126,638, 81% Husk, 23,999, 16% Chart 3.97 Use of Processed Product Did Not Use, 268, 0% Fuel for Cooking, 54, 0% Animal Consumption, 1,141, 1% Sale Only, 628, 0% Household / Human Consumption, 221,805, 99% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 61 Out of 10,955 households that sold processed products, 2,981were from Igunga (27.2% of the total number of households selling processed products in the region), followed by Sikonge with 2,809 households (25.6%), Nzega with 2,098 households (19.1%), Urambo with 1,523 households (13.9%), Uyui with 1,103 household (10.1%) and Tabora Urban with 434 households (4.0%) (Chart 3.98). 3.7.2.4 Outlets for Sale of Processed Products Most households that sold processed products sold them to unspecified markets (4,976 households, 45% of households that sold crops). This was followed by selling to neighbours (3,175 households, 29%), local markets and trade stores (1,194 households, 11%), trader at farm (993 households, 9%), marketing co-operatives (231 households, 2%), large scale farm (173 households, 2%) farmers associations (114 households, 1%) and secondary markets (99 households, 1%) (Chart 3.99). There were large differences between districts in the proportion of households selling processed products to unspecified markets with Sikonge district having the largest percent of households in the district selling to those markets (46.7%), whereas Tabora Urban had only 0.5 percent. In Nzega and Urambo no sales were made to unspecified markets. Tabora Urban and Urambo had a higher percent of households relying on neighbours than other outlets. In Nzega, the sale of processed produce to local markets/trade stores and traders at farm were most prominent compared to other districts. The district that had the highest proportion of households selling processed products to marketing cooperative was Uyui. 3.7.3 Crop Marketing The number of households that reported selling crops was 131,403 which represent 55.7 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Urambo (80.3%) followed by Sikonge (62.2%), Uyui (53.0%), Igunga (47.9%), Tabora Urban (45.5%) and Nzega (42.1%) (Chart 3.101 and Map 3.41). 0.0 10.0 20.0 30.0 Percentage of Household Igunga Sikonge Nzega Urambo Uyui Tabora Urban District Chart 3.98 Percentage of Household Selling Processed Crops by District Chart 3.99 Location of Sale of Processed Products Farmers Association, 114, 1% Large Scale Farm, 173, 2% Trader at Farm, 993, 9% Other, 4,976, 45% Marketing Co- operative, 231, 2% Local Market / Trade Store, 1,194, 11% Neighbours, 3,175, 29% Secondary Market, 99, 1% Chart 3.100 Percent of Households Selling Processed Products by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Urambo Tabora Urban Igunga Nzega Sikonge Uyui District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Secondary Market Chart 3.101 Number of Crop Growing Households Selling Crops by Districts 0 10,000 20,000 30,000 40,000 50,000 Urambo Nzega Uyui Igunga Sikonge Tabora Urban District Number of Households 0.0 20.0 40.0 60.0 80.0 100.0 Percent Number of Households Selling Crops Percentage of Households Selling Crops RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (76% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (11%), lack of transport (7%), high transport costs (4%) and lack of market information (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems (Chart 3.102). 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 93.3 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.12). This general trend applies to all districts. 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Tabora region few agricultural households (25,655, 10.9%) accessed agricultural credit out of which 24,679 (96%) were male-headed households and 977 (4%) were female headed households. In Nzega, Igunga and Tabora Urban districts only male headed households got agricultural credit whereas in Uyui, Urambo and Sikonge districts both male and female headed households accessed agricultural credit (Table 3.12). Table 3.11 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 121,210 93.3 Other 4,094 3.2 Price Too Low 3,635 2.8 Trade Union Problems 614 0.5 Co-operative Problems 248 0.2 Market Too Far 100 0.1 Government Regulatory Board Problems 25 0.0 Total 129,925 100.0 Table 3.12 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Nzega 1,411 100 0 0 1,411 Igunga 336 100 0 0 336 Uyui 7,629 96 309 4 7,938 Urambo 11,186 95 618 5 11,803 Sikonge 3,985 99 50 1 4,034 Tabora Urban 132 100 0 0 132 Total 24,679 96 977 4 25,655 Chart 3.102 Percentage Distribution of Household that Reported Marketing Problems by Type of Problem Market to o Far 11% Open Market P rice To o Lo w 76% No Transpo rt 7% Transpo rt Cos t To o High 4% Other 0% Co -o perative P ro blems 0% Lack o f Market Info rmatio n 1% No Buyer 1% Farmers Ass o ciatio n P ro blems 0% Go vernment Regulato ry Bo ard P ro blems 0% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Tabora region were Cooperatives which provided credit to 22,049 agricultural households (85.9% of the total number of households that accessed credit), followed by family, friends and relatives (5.6%), religious organizations/NGO/projects (4.2%), commercial bank (1.5%), traders / trade stores (1.3%), savings and credit society (1.0%) and other sources (0.5%) (Chart 3.103). Cooperatives were the sole credit providers in Tabora Urban while other credit providers were found in Urambo district only. Religious organizations, NGOs and projects were the major credit providers in Nzega district (Chart 3.104). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region was used on fertilizers (40%) and other agro-chemicals (30%) followed by seeds (14%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment and hiring labour was very low (Chart 3.105). 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 57 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (23%), followed by “not wanting to get into debt” (10%) and ‘credit not needed’ (4%). The rest of the reasons were collectively reported by less than 8 percent of the households. Chart 3.103 Percentage Distribution of Households Receiving Credit by Main Source Co-operatives, 86, 85% Other, 1, 1% Trader / Trade Store, 1, 1% Commercial Bank, 2, 2% Saving & Credit Society, 1, 1% Family, Friend and Relative, 6, 6% Religious Organisation / NGO / Project, 4, 4% Chart 3.104 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Percent of Households Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Co-operative Chart 3.105 Proportion of Households Receiving Credit by Main Purpose of the Credit Livestock 1% Seeds 14% Tools / Equipment 5% Irrigation Structures 2% Agro-chemicals 30% Other 6% Fertilizers 40% Labour 2% Chart 3.106 Reasons for not Using Credit (% of Households) Did not know how to get credit, 66,223, 31% Don't know about credit, 54,206, 26% Not available, 47,318, 23% Did not want to go into debt, 21,580, 10% Difficult bureaucracy procedure, 5,730, 3% Not needed, 8,744, 4% Credit granted too late, 1,418, 1% Other, 275, 0% Interest rate/cost too high, 4,768, 2% Tabora Urban Uyui Nzega Igunga Sikonge 77.6% 57.2% 56.7% 57.4% 52.9% 49.1% Urambo Uyui Urambo Igunga Sikonge Tabora Urban Nzega 21,884 43,449 21,622 12,147 4,669 27,633 53% 80.3% 47.9% 62.2% 45.5% 42.1% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 71.9 > 66.2 to 71.9 60.5 to 66.2 54.8 to 60.5 49.1 to 54.8 Tanzania Agriculture Sample Census Percent of Total Households Selling Crops Number of Households Selling Crops Percent of Households Storing Crops Percent of Households Storing Crops Map 3.40 TABORA Percent of Households Storing Crops for 3 to 6 Months by District Map 3.41 TABORA Number of Households and Percent of Total Households Selling Crops by District Number of Households Selling Crops RESULTS 64 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 62,956 (27% of total crop growing households in the region) (Chart 3.107). Some districts had more access to extension services than others, with Tabora Urban having a relatively high proportion of households (73%) that received crop extension messages in the district followed by Uyui (30%), Sikonge (27%), Urambo (25%), Nzega (24%) and Igunga (19%). (Map 3.42) 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (80%, 49,275 households). NGOs provided 13.8 percent, cooperatives (4.8%), large scale farms (0.9%) and the remaining providers (0.5%) (Chart 3.109). District differences existed with the proportion of the households receiving advice from government services ranging from between 54.2 percent in Urambo to 98.6 percent in Igunga. Chart 3.109 Number of Households Receiving Extension Messages by Type of Extension Provider Government 80.0% Other 0.5% NGO / Development Project 13.8% Cooperative 4.8% Large Scale Farm 0.9% Chart 3.108 Number of Households Receiving Extension by District 0 10,000 20,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District N um ber of Households 0 20 40 60 80 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.110 Number of Households Receiving Extension by Quality of Services Very Good, 9,547, 15.4% No Good, 358, 0.6% Poor, 1,361, 2.2% Average, 10,282, 16.6% Good, 40,449, 65.2% Chart 3.107 Number of Households Receiving Extension Advice Households Receiving Extension Advice, 62,956, 27% Households Not Receiving Extension Advice, 172,665, 73% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.8.2.2 Quality of Extension On the quality of extension, 65.2 percent of the households receiving extension ranked the service as being good followed by average (16.6 %), very good (15.4%), poor (2.2%) and no good (0.6%) (Chart 3.110). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tabora region regardless of whether the households grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from those in previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm eg., improved seeds, inorganic fertilizers, insecticides, fungicides and herbicides. In Tabora region farm yard manure was used by 65,279 households which represent 28 percent of the total number of crop growing households. This was followed by households using insecticides/fungicides (20%), inorganic fertilizers (20%), improved seeds (19%), compost manure (7%) and herbicides (1%) (Table 2.13). 3.9.1 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Tabora mostly purchased them from the local cooperatives (57.3% of the total number of inorganic fertiliser users), from the local markets (33.7%) and from local farmers groups (5%). The remaining sources of inorganic fertilisers were of minor importance (Chart 3.111). Access to inorganic fertiliser was mainly less than 10 km from the household with most households residing less than 1 km from the source (30.5%), followed by between 3 and 10 km (21.9%) and between 1 and 3 km (21%) (Chart 3.112). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (20% ) as the reason for not using, it may be assumed that access is not the main reason for not using them. Other reasons such as cost are more important with 73 percent of households responding to cost factors as the main reason for not using the fertilizers. Table 3.13 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 65,279 28 170,342 72 Improved Seeds 45,706 19 189,914 81 Insecticides/Fungicide 47,859 20 187,761 80 Compost Manure 15,368 7 220,253 93 Inorganic Fertilizers 46,287 20 189,334 80 Herbicides 2,056 1 233,565 99 Chart 3.111 Number of Households by Source of Inorganic Fertiliser 0.1 0.2 0.1 0.3 0.9 2.5 5.0 33.7 57.3 0 10,000 20,000 30,000 Co-operative Local market/Trade Local Farmers Group Neighbour Crop Buyers Locally Produced by Household Secondary Market Development Project Large Scale Farm Source of Inorganic Fertiliser Number of Households Chart 3.112 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 In other words, if the cost was affordable the demand would be higher and inorganic fertiliser would be made more available.More smallholders use inorganic fertilisers in Urambo than in other districts in Tabora region (46.1% of households using inorganic fertilisers), followed by Uyui (23.8%) and Sikonge (14.6%). Other districts use very little inorganic fertiliser. 3.9.2 Improved Seeds The percent of households that used improved seeds was 19.4 percent of the total number of crop growing households. Most of the improved seeds were obtained from the cooperatives (55.1%) followed by from local markets/trade stores (29%). Other less important sources of improved seeds were from local farmers group (5.1%), locally produced by households (3.3%), neighbours (2.6%), crop buyers (2.5%) and development projects (1.7%). Only 0.6 percent and 0.1 percent of households using improved seeds were from secondary markets and other sources respectively (Chart 3.113). Access to improved seeds was mainly less than 10 km from the household with most households residing less than 1 km from the source (33%), followed by between 1 and 3 km (21%) and between 3 and 10 km (21%) (Chart 3.114). The districts that used improved seeds most were Igunga (35.7 percent of the total number of households in the district), followed by Urambo (20.1%). Use of improved seeds in other districts is of minor importance (Map 3.42). 3.9.3 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchased them from cooperatives (55.2% of the total number of fungicides users) and local markets/trade stores (32.9%). Other sources of insecticides/ fungicides were of minor importance (Chart 3.115). Chart 3.116 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticides/fungicides. Chart 3.115 Number of Household by Source of Insecticide/fungicide 55.2 32.9 4.2 3.4 1.9 1.4 0.7 0.4 0.1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Co-operative Local Market/Trade Local Farmers Group Neighbour Crop Buyers Secondary Market Locally Produced by Household Development Project Large Scale Farms Source of Insecticide/fungicide Number of Households Chart 3.116 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.113 Number of Households by Source of Improved Seed 0.1 0.6 1.7 2.5 2.6 3.3 5.1 29.0 55.1 0 5,000 10,000 15,000 20,000 25,000 30,000 Co-operative Local Market / Trade Store Local Farmers Group Locally Produced by Household Neighbour Crop Buyers Development Project Secondary Market Other Source of Improved Seeds Number of Households Chart 3.114 Number of Households Reporting Distance to Source of Improved Seed 0 10 20 30 40 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 68 The small number of households using insecticides/fungicides coupled with the 18 percent of households responding to “not available” as the reason for not using them, it may be assumed that access is not the main reason for not using them. Other reasons such as cost are more important with 72 percent of households responding to cost factor as the main reason for not using them. In other words, if the cost was affordable, the demand would be higher and insecticides/fungicides would be made more available. Fungicides were mostly used in Urambo district (33.7 percent of the total number of households that use fungicide in the region), followed by Uyui (24.7%), Igunga (12.9%) and Sikonge (12.7%). Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 4,619 representing 2 percent of the total number of agriculture households (Chart 3.117). The number of trees planted by smallholders on their allotted land was 190,349 trees. The average number of trees planted per household planting trees was 41. The main species planted by smallholders was Moringa spp (52,394 trees, 27.5%), followed by Albizia Spp (34,292, 18.0%), then Acacia Spp (32,393, 17.0%) and Eucalyptus Spp (29,003 trees, 15.2%). The remaining trees species were planted in comparatively small numbers (Chart118.). Uyui has the largest numbers of smallholders with planted trees than any other district (44.0%) and the trees were dominated by Moringa Spp. and Eucalyptus Spp. This is followed by Urambo (40.0%) with the trees dominated by Albizia Spp and Acacia Spp and Nzega (7.3%) where the trees were mainly Gravellis Spp. (Chart 3.119 and Map 3.45.). Smallholders mostly plant trees on plantation or coppice. The proportion of households that plant on plantation is 58 percent, followed by scattered around fields (32%) and then trees planted on the field boundaries (10%) (Chart 3.120). Chart 2.118 Number of Planted Trees by Species - TABORA 0 10,000 20,000 30,000 40,000 50,000 60,000 Moringa Spp Albizia Spp Acacia Spp Eucalyptus Spp Leucena Spp Senna Spp Gravellis Azadritachta Spp Pinus Spp Terminalia Ivorensis Syszygium Spp Others Tree Species Number of Trees Chart 3.119 Number of Trees Planted by Smallholders by Species and District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Uyui Urambo Sikonge Igunga Nzega Tabora Urban District Number of Trees Moringa Spp Albizia Spp Acacia Spp Eucalyptus Spp Leucena Spp Senna Spp Gravellis Azadritachta Spp Pinus Spp Terminalia Ivorensis Syszygium Spp Others Chart 3.120 Number of Trees Planted by Location Plantation/Copp- ice, 109,041, 58% Scattered in field, 61,461, 32% Field boundary, 19,847, 10% Chart 3.117 Number of Households with Planted Trees Growing Trees, 4,619, 2% Not Growing Trees, 231,298, 98% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 The main purpose of planting trees was to obtain wood for fuel (42.57%). This was followed by shade (25.9%), planks/timber (6.3%), poles (4.1%) and medicinal (1.7%). Other purposes were reported by 19.4 percent of the households (Chart 3.121, Map 3.44). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 5,399 which represented 2 percent of the total number of agricultural households in the region (Chart 3.122). The proportion of households with soil erosion control and water harvesting facilities was highest in Tabora Urban (7.1%) followed by Uyui (4.9%), Nzega (2.5%), Urambo (1.8%), Sikonge (1.8%) and Igunga (0.2%) (Chart 3.123). Erosion control bunds accounted for 50 percent of the total number of structures, followed by dam (16.1%), tree belts (14.7%), water harvesting bunds (11.4%), drainage ditches (3.4%), terraces (1.9%), vetiver grass (1%) and gabions / sandbag (1.1%) (Chart 3.124 and Map 3.45). Erosion control bunds, dam and tree belts together had 23,131 structures. This represented 81 percent of the total structures in the region. The remaining 19 percentages were shared among the rest of the erosion control methods mentioned above. Urambo and Uyui districts had 16,859 erosion control structures (59 percent of the total erosion structures in the region). Chart 3.122 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 230,518, 98% Households with facilities, 5,399, 2% Chart 3.123 Number of Households with Erosion Control/Water Harvesting Facilities 0 500 1,000 1,500 2,000 2,500 Tabora Urban Uyui Nzega Urambo Sikonge Igunga District Number of Households 0.0 2.0 4.0 6.0 8.0 Percent Number of Households Percent Chart 3.124 Number of Erosion Control/Water Harvesting Structures by Type of Facility 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Erosion Control Bunds Dam Tree Belts Water Harvesting Bunds Drainage Ditches Terraces Vetiver Grass Gabions / Sandbag Type of Faciliy Number of Structures Chart 3.121 Number of Households by Purpose of Planted Trees 0.0 15.0 30.0 45.0 Wood for Fuel Shade Other Planks / Timber Poles Medicinal Use Percent of Households Tabora Urban Uyui Nzega Igunga Urambo Sikonge 1,700 21,710 2,416 29,712 8,173 5,370 45.4% 2.9% 34.4% 14.9% 29.1% 11.4 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 236 5,692 11,036 570 21,533 1,066 6.3% 0.7% 24.9% 20.1% 7.6% 2.3% 16,000 to 22,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Percent of Crop Growing HouseholdsUsing Improved Seeds Number Households Using Improved Seeds Number of Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services Map 3.42 TABORA Number of Households and Percent of Total HouseholdsReceiving Crop Extension Services by District Map 3.43 TABORA Number and Percent of Crop Growing Households Using Improved Seeds by District Number Households Using Improved Seeds Number of Households Receiving Crop Extension Services % RESULTS 70 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 727 2,209 965 1,041 115 343 7.1% 2.5% 1.8% 0.2% 4.9% 1.8% 2,000 to 3,000 2,000 to 2,000 2,000 to 2,000 1,000 to 2,000 0 to 1,000 Tabora Urban Uyui Sikonge Urambo Igunga Nzega 555,548 2,438,158 2,685,052 643,721 2,642,671 5,361,219 3.9% 37.4% 18.7% 4.5% 17% 18.4% 4,000,000 to 6,000,000 3,000,000 to 4,000,000 2,000,000 to 3,000,000 1,000,000 to 2,000,000 0 to 1,000,000 Tanzania Agriculture Sample Census Percent of Households with Water Harvesting Bunds Number of Smallholder Number of Smallholder Planted Trees Map 3.44 TABORA Number and Percent of Smallholder Planted Trees by district Map 3.45 TABORA Number and Percent of Households With Water Harvesting Bunds by District Number of Households with Water Harvesting Bunds Percent of Smallholder Planted Trees Number of Households with Water Harvesting Bunds RESULTS 71 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 1,568,691. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 9.3 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Tabora region was 1,566,169 (99.8 % of the total number of cattle in the region), 1,851 cattle (0.12%) were dairy breeds and 671 cattle (0.04%) were beef breeds. The census results show that 65,925 agricultural households in the region (27.9% of total agricultural households) kept 1.6 million cattle. This was equivalent to an average of 24 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Igunga which had about 466,892 cattle (29.8% of the total cattle in the region). This was followed by Nzega (425,021 cattle, 27.1%), Sikonge (272,100 cattle, 17.3%), Uyui (205,865 cattle, 13.1%) and Urambo (131,000 cattle, 8.4%). Tabora Urban had the least number of cattle (67,812 cattle, 4.3%) (Chart 3.126 and Map 3.46). Igunga district had the highest density (176 head per km2 ) (Map 3.47). Although Igunga district had the largest number of cattle in the region, most of it was indigenous. Also the district had the largest number of dairy cattle but it had no beef cattle. In general, the number of beef cattle in the region was insignificant (Chart 3.126). 3.12.1.2 Herd Size Twenty four percent of the cattle-rearing households had herds of size 1-5 cattle with an average of three cattle per household. Herd sizes of 6-30 accounted for about 38 percent of all cattle in the region. Only 15.4 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 82.5 percent of total cattle rearing households had herds of size 1-30 cattle and owns 41 percent of total cattle in the region, resulting in an average of 12 cattle per cattle rearing household. There were about 782 households with herd sizes of more than 151 cattle each (278,198 cattle in total) resulting in an average of 356 cattle per household. 0 100 200 300 400 500 Number of Cattle ('000') Igunga Nzega Sikonge Uyui Urambo Tabora Urban District Chart 3.125 Total Number of Cattle ('000') by District Chart 3.126 Number of Cattle by Type and District 0 100,000 200,000 300,000 400,000 500,000 Igunga Nzega Sikonge Uyui Urambo Tabora Urban District Num ber of Cattle Indigenous Beef Dairy RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 73 3.12.1.3 Cattle Population Trend Cattle population in Tabora increased during the period of eight years from 1,009,571 in 1995 to 1,568,691 cattle in 2003. This implies an overall annual positive growth rate of 5.7 percent (Chart 3.127). However, there was a very sharp increase in number of cattle for the period of four years from 1995 to 1999 at the rate of 12.7 percent whereby the number increased from 1,009,571 to 1,626,130. The number of cattle is estimated to have decreased from 1,626,130 in 1999 to 1,568,691 in 2003 at the rate of -0.9 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in Tabora region was 2,522 (1,851 dairy and 671 improved beef). The diary cattle constituted 0.11 percent of the total cattle and 73.4 percent of improved cattle in the region. The number of beef cattle in the region was small constituting 26.6 percent of the total number of the improved cattle and 0.04 percent of the total cattle. The number of improved cattle increased from zero in 1995 to 2,522 in 2003 whilst the number increased from 904 in 1999 to 2,522 in 2003 at the growth rate of 29%. 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Tabora region ranked 6 out of the 21 regions with 6.1 percent of the total number goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Tabora region was 65,487 (28% of all agricultural households in the region) with a total of 718,996 goats giving an average of 11 head of goats per goat-rearing-household. Igunga had the largest number of goats (234,077 goats, 32.6% of all goats in the region), followed by Nzega (185,172 goats, 25.8%), Uyui (124,998 goats, 17.4%) and Urambo (93,826 goats, 13.0). Sikonge and Tabora Urban had the least number of goats (54,087 goats, 7.5% and 26,836 goats, 3.7% respectively) (Chart 3.129 and Map 3.48). Igunga district had also the highest density of goats (88 head per km2 ) (Map 3.49). 1,009,571 1,626,130 1,568,691 0 500,000 1,000,000 1,500,000 2,000,000 Number of Cattle 1995 1999 2003 Year Chart 3.127 Cattle Population Trend 0 904 2,522 0 1000 2000 3000 Number of Cattle 1995 1999 2003 Year Chart 3.128 Improved Cattle Population Trend 0 50 100 150 200 250 Number of Goats Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Chart 129 Total Number of Goats ('000') by District RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12.2.2 Goat Herd Size Twenty four percent of the goat-rearing households had herd sizes of 1-4 goats with an average of 3 goats per goat rearing household. Seventy seven percent of total goat-rearing households had herd size of 1-14 goats and owned 47 percent of the total goats in the region resulting in an average of 7 goats per goat-rearing households. The region had 2,188 households (3%) with herd sizes of 40 or more goats each (113,118 goats in total), resulting in an average of 52 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 98.4 percent of the total goats in Tabora region. Improved goats for meat and diary goats constituted 0.83 and 0.81 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was 5.6 percent. This positive trend implies eight years of population increase from 464,327 in 1995 to 718,996 in 2003. The number of goats increased from 464,327 in 1995 at an estimated annual rate of 18.1 percent to 903,652 in 1999. From 1999 to 2003, the goat population decreased at an annual rate of -5.5 percent (Chart 130). 3.12.3. Sheep Production Sheep rearing was the third most important livestock keeping activity in Tabora region after cattle and goats. The region ranked 6 out of 21 Mainland regions and had 6 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 28,126 (12% of all agricultural households in Tabora region) rearing 235,213 sheep, giving an average of 8 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Igunga with 101,570 sheep (43.2% of total sheep in Tabora region) followed by Uyui (60,347 sheep, 25.7%), Nzega (42,118 sheep, 17.9%) and Sikonge (19,838 sheep, 8.4%). Urambo and Tabora Urban had the least number of sheep [6,019 sheep (2.6%) and 5,321 sheep (2.3%) respectively] (Chart 3.131 and Map 3.50). Igunga district also had the highest density of sheep (38 head per km2 ) (Map 3.51). Sheep rearing was dominated by indigenous breeds that constituted 88 percent of all sheep kept in the region. Only 12 percent of the total sheep in the region were improved breeds. 0 20,000 40,000 60,000 80,000 100,000 120,000 Number of Sheep Igunga Uyui Nzega Sikonge Urambo Tabora Urban District Chart 3.131 Total Number of Sheep by District 464,327 903,652 718,996 0 200,000 400,000 600,000 800,000 1,000,000 Number of Goats 1995 1999 2003 Year Chart 3.130 Goat Population Trend RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 75 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated to be 5.7 percent. The population increased at an average annual rate of 13 percent from 151,034 in 1995 to 245,723 in 1999. From 1999 to 2003, sheep population decreased at an annual rate of -1.1 percent (Chart 3.132). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranked 16 out of 21 Mainland regions and had 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Tabora region was 2,719 (1.2% of the total agricultural households in the region) rearing 6,286 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Urambo with 4,172 pigs (66.4% of the total pig population in the region) followed by Nzega (1,083 pigs, 17.2%), Uyui (739 pigs, 11.8%) and Tabora Urban (292 pigs, 4.6%) (Chart 3.133 and Map 3.52). However Urambo district had the highest density of pigs (0.5 head per km2 ) (Map 3.53). There were no pigs in Igunga and Sikonge districts. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population over the eight-year period from 1995 to 2003 was 5.6 percent. During this period the population grew from 4,071 to 6,286. The pig population increased very much from 4,071 in 1995 to 30,406 in 1999 at a rate of 65.3 percent. The growth rate dropped to -32.6 percent during the following four years from 1999 to 2003 in which pig population decreased from 30,406 to 6,286 (Chart 3.134). 3.12.5 Chicken Production The poultry sector in Tabora region was dominated by chicken production. The region contributed 7.5 percent to the total chicken population on Tanzania Mainland. 151,034 245,723 235,213 0 100,000 200,000 300,000 Number of Sheep 1994/95 1998/99 2002/03 Year Chart 3.132 Sheep Population Trend 0 1,000 2,000 3,000 4,000 5,000 Number of Pigs Urambo Nzega Uyui Tabora Urban District Chart 3.133 Total Number of Pigs by District 4,071 30,406 6,286 0 10,000 20,000 30,000 40,000 N um ber o f P ig s 1995 1999 2003 Year Chart 3.134 Pig Population Trend RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.5.1 Chicken Population The number of households keeping chicken was 168,339 raising about 2,507,469 chickens. This gives an average of 15 chickens per chicken-rearing household. In terms of total number of chickens in the country, Tabora region was ranked fourth out of the 21 Mainland regions. The District with largest number of chickens was Urambo with 647,562 chickens (25.8% of the total number of chickens in the region) followed by Uyui (582,803, 23.2%), Nzega (496,490, 19.8%), Igunga (360,864, 14.4%) and Sikonge (341,572, 13.6%). Tabora Urban had the smallest number of chickens (78,178, 3.1%) (Chart 3.135 and Map 3.54). However Nzega district had the highest density of chickens (201 chickens per km2 ) (Map 3.55). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 5.1 percent. The population increased at a rate of 11.4 percent from 1995 to 1999 after which it decreased by -0.7 percent for the remaining four years from 1999 to 2003 (Chart 3.136). About 99.6 percent of all chicken in Tabora region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 74.6 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 8 chickens per holder. About 25.0 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 31 chickens per holder. Only 0.3 percent of holders kept the flock sizes of more than 100 chickens at an average of 366 chickens per holder (Table 3.14). Table 3.14 Number of Household and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1 - 4 28,432 17 83,765 3 5 - 9 46,552 28 309,940 7 10 - 19 50,056 30 645,709 13 20 - 29 23,087 14 517,953 22 30 - 39 9,792 6 312,264 32 40 - 49 4,126 2 173,702 42 50 - 99 4,771 3 289,704 61 100+ 477 0 174,432 365 Total 167,294 100 2,507,469 15 1,679,258 2,584,112 2,507,469 0 1,000,000 2,000,000 3,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.136 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Number of Chicken Urambo Uyui Nzega Igunga Sikonge Tabora Urban District Chart 3.135 Total Number of Chicken by District Tabora Urban Uyui Urambo Nzega Igunga Sikonge 96.2 16.4 172.2 175.5 42.9 24.8 160 to 200 120 to 160 80 to 120 40 to 80 0 to 40 Uyui Tabora Urban Igunga Nzega Sikonge Urambo 205,865 466,892 425,021 272,100 131,000 67,812 400,000 to 500,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 Tanzania Agriculture Sample Census Number of Cattle Map 3.46 TABORA Cattle population by District as of 1st Octobers 2003 Map 3.47 TABORA Cattle Density by District as of 1st October 2003 Number of Cattle Per Square Km Number of Cattle Number of Cattle Per Square Km RESULTS 77 Tabora Urban Uyui Urambo Sikonge Igunga Nzega 38.1 11.8 4.9 26 88.3 75.1 80 to 90 60 to 80 40 to 60 20 to 40 0 to 20 Uyui Sikonge Igunga Tabora Urban Nzega Urambo 124,998 54,087 234,077 185,172 93,826 26,836 200,000 to 250,000 150,000 to 200,000 100,000 to 150,000 50,000 to 100,000 0 to 50,000 Tanzania Agriculture Sample Census Number of Goats Map 3.48 TABORA Goat population by District as of 1st Octobers 2003 Map 3.49 TABORA Goats Density by District as of 1st October 2003 Number of Goats Per Square Km Number of Goats Number of Goats Per Square Km RESULTS 78 Tabora Urban Uyui Urambo Sikonge Nzega Igunga 7.6 0.8 1.8 12.6 17.1 38.3 40 to 50 30 to 40 20 to 30 10 to 20 0 to 10 Tabora Urban Urambo Nzega Igunga Uyui Sikonge 5,321 6,019 42,118 101,570 60,347 19,838 Tanzania Agriculture Sample Census Number of Sheep Map 3.50 TABORA Sheep population by District as of 1st Octobers 2003 Map 3.51 TABORA Sheep Density by District as of 1st October 2003 Number of Sheep Per Square Km Number of Sheep Number of Sheep Per Square Km 80,000 to 110,000 60,000 to 80,000 40,000 to 60,000 20,000 to 40,000 0 to 20,000 RESULTS 79 Nzega Igunga Sikonge Tabora Urban Urambo Uyui 0 0 0 0 1 0 0.8 to 1 0.6 to 0.8 0.4 to 0.6 0.2 to 0.4 0 to 0.2 Igunga Sikonge Uyui Nzega Urambo Tabora Urban 0 0 739 1,083 4,172 292 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 Tanzania Agriculture Sample Census Number of Pig Map 3.52 TABORA Pig population by District as of 1st Octobers 2003 Map 3.53 TABORA Pig Density by District as of 1st October 2003 Number of Pig Per Square Km Number of Pig Number of Pig Per Square Km RESULTS 80 Tabora Urban Uyui Urambo Nzega Igunga Sikonge 111 81.3 201.3 136.1 121.4 31.2 Urambo Igunga Tabora Urban Nzega Uyui Sikonge 647,562 360,864 496,490 78,178 582,803 341,572 Tanzania Agriculture Sample Census Number of Chicken Map 3.54 TABORA Chicken population by District as of 1st Octobers 2003 Map 3.55 TABORA Chicken Density by District as of 1st October 2003 Number of Chicken Per Square Km Number of Chicken Number of Chicken Per Square Km 400,000 to 700,000 300,000 to 400,000 200,000 to 300,000 100,000 to 200,000 0 to 100,000 200 to 250 150 to 200 100 to 150 50 to 100 0 to 50 RESULTS 81 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.5.4 Improved Chickens (layers and broilers) The overall annual growth rate for layers during the eight-year period from 1995 to 2003 decreased at an annual rate of - 6.1 percent during which the population decreased from 6,507 to 3,949. For the last four year period layers chicken population decreased at an annual rate of -5.5 percent from 4,950 in 1999 to 3,949 in 2003. The number of improved chicken was most significant in Nzega District followed by Uyui (Chart 3.137). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 9.0 percent during which the population grew from 2,675 to 5,330. The average annual growth rate was higher (65.7%) during the period of four years from 1995 to 1999. The broiler population exhibited a decreasing trend at the rate of -28.3 percent per annum for the period of four years resulting at decrease from 20,142 in 1999 to 5,330 2003 (Chart 3.138). 3.12.6. Other Livestock There were 57,565 ducks, 1,830 turkeys, 7,171 rabbits and 26,294 donkeys raised by rural agricultural households in Tabora region. Table 3.15 shows the number of livestock kept in each district. The biggest number of ducks in the region was found in Uyui District (47% of all ducks in the region), followed by Nzega (22%), Urambo (16%), Igunga (9%) and Sikonge (4%). Tabora Urban had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Nzega, Igunga and Sikonge districts only (Table 3.15). 3.12.7 Pest and Parasite Incidence and Control According to the results indicate that 59 percent and 37 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.139 shows that there was a predominance of tick related diseases over tsetse related diseases. Incidence of ticks’ problem was highest in Igunga district whilst the incidence of tsetse flies problem was highest in Sikonge district. The incidences of both problems were lowest in Tabora Urban. (Map 3.56). Table 3.15 Number of Other Livestock by Type of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Nzega 12,653 890 0 1,197 901 Igunga 5,420 656 0 11,055 341 Uyui 27,042 0 633 13,896 1,019 Urambo 9,171 0 6,438 0 2,552 Sikonge 2,129 285 99 146 0 Tabora Urban 1,151 0 0 0 0 Total 57,565 1,830 7,171 26,294 4,813 3,522 438 109 811 317 2,740 0 1,242 0 99 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Number of Chickens Nzega Igunga Uyui Urambo Sikonge District Chart 3.137 Number of Improved Chicken by Type and District Layer Broiler Chart 3.139 PercentageKeeping Households Reporting Tsetseflies and Tick Problems by District 0 20 40 60 80 Igunga Nzega Sikonge Uyui Urambo Tabora Urb District Percent Ticks Tsetseflies 6,507 2,675 4,950 20,142 3,949 5,330 0 5,000 10,000 15,000 20,000 25,000 Number of Improved Chickens 1995 1999 2003 Year Chart 3.138 Improved Chicken Population Trend Layers Broilers RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 83 The most practiced method of tick control was spraying with 49 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (10%), smearing (5%) and other traditional methods like hand picking (9%). However, 25 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 29 percent of livestock- rearing households. This was followed by dipping (6%) trapping (6%) and smearing (3%). However, 41 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 30,028 (34% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 34, goats (17%) and sheep (15%) (Chart 3.140). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The total number of households that received livestock advice was 16,853, representing 19.2 percent of the total livestock- rearing households and 7.1 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 83.8 percent of all households receiving livestock extension services followed by co-operatives (11.1%). The rest of the households got services from NGOs/development projects (4.1%) and large- scale farmers (0.5%). About 45 percent of livestock rearing households described the general quality of livestock extension services as being good, 10 percent said they were average and 16 percent said they were very good. However, 25 percent of the livestock rearing households said the quality was not good whilst 4 percent described them as poor (Chart 3.141). 0 10 20 30 40 50 Percent Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Chart 3.140 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.141 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services Good 45% Very Good 16% Poor 4% No Good 25% Average 10% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 75 percent of the livestock rearing households accessed the services, at a distance of more than 14 km. Only 25 percent of them accessed the services within 14 km from their dwellings (Chart 3.142). The most affected district was Sikonge district with 91 percent of all livestock rearing households accessing the services at a distance of more than 14 km. Tabora Urban was the least affected because about 60 percent of the households could access the service within a distance of 14 kilometers. (Chart 3.143). 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 km from the nearest watering point was 52,689 (86% of livestock rearing households in Tabora region) whilst 7,597 households (12%) resided between 5 and 14 km. However, 1,282 households (2%) had to travel a distance of 15 or more km to f the nearest watering point (Chart 3.144). Uyui district had the best livestock water supply with the majority of livestock rearing households residing within 5 km from the nearest watering point. This is followed by Urambo, Sikonge, Nzega and Tabora Urban districts. In Igunga district about 32 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.145) Chart 3.142 Number of Households by Distance to Veterinary Clinic Less than 14km, 19,482, 25% More than 14km, 59,848, 75% Chart 3.144 Number of Households by Distance to Village Watering Points 15 or more kms, 1,282, 2% 5-14kms, 7,597, 12% Less than 5kms, 52,689, 86% Chart 3.143 Number of Households by Distance to Veterinary Clinic and District 0 5,000 10,000 15,000 20,000 25,000 30,000 Nzega Uyui Urambo Igunga Sikonge Tabora Urban District Number of Households Less than 14km More than 14km Chart 3.145 Number of Households by Distance to Village Watering Point and District 0 5,000 10,000 15,000 20,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District N um ber o f H o useho lds Less than 5kms 5-14kms 15 or more kms RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 85 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Tabora region is limited in some districts while it is common in other districts. Draft animals were used by 88,862 households (38% of the total agricultural households in the region) (Chart 3.146). The number of households that used draft animals in Igunga was 34,913 representing 39.3 percent of the households using draft animals in the region followed by Nzega (34,629 households, 39.0%), Uyui (9,192 households, 10.3%), Urambo (5,525 households, 6.2%) and Sikonge (3,754 households, 4.2%). In Tabora Urban only 849 households (1%) used draft animals. (Chart 3.147 and Map 3.57). The region had 370,495 oxen (162,466 oxen in Igunga, 120,742 oxen in Nzega, 42,341 oxen in Uyui, 25,202 oxen in Urambo, 15,992 oxen in Sikonge and 3,752 oxen in Tabora Urban) that were used to cultivate 223,878 hectares of land. This represents 8.8 percent of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Igunga district (162,466 ha, 44% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Tabora region was 68,504 (29% of total crop growing households in the region) (Chart 3.148). The total area applied with organic fertilizer was 176,963 ha of which 159,104 hectares (90% of the total area applied with organic fertilizer or 29.9% of the area planted with annual crops and vegetables in Tabora region during the long rainy season) was applied with farm yard manure. The largest area applied with farm yard manure was found in Nzega district with 26,328 hectares (40.9% of the total area applied with farm yard manure) followed by Igunga (11,737 ha, 18.2%), Urambo (8,972 ha, 13.9%), Uyui (8,880 ha, 13.8%), Sikonge (5,695 ha, 8.8%) and Tabora Urban (2,803 ha, 4.4%) (Chart 3.149 and Map 3.58). 3.146 Number of Households Using Draft Amimals Not Using Draft Animals, 147,055, 62% Using Draft Animals, 88,862, 38% 0 10,000 20,000 30,000 40,000 N um ber o f H o useho lds Igunga Nzega Uyui Urambo Sikonge Tabora Urban District Chart 3.147 Number of Households Using Draft Animals by District - TABORA T Chart 3.148 Number of Household Using Organic Fertilizer Using Organic Fertilizer, 68,504, 29% Not Using Organic Fertilizer, 167,117, 71% Chart 3.149 Area of Application of Organic Fertilizer by District - TABORA 0 10,000 20,000 30,000 Nzega Igunga Uyui Urambo Sikonge Tabora Urban District Area of Fertilizer Application (ha) Farm Yard Manure Compost Manure RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 3.12.9.4 Use of Compost Only 7,230 ha (10.% of the area of organic fertilizer application) was applied with compost. The largest area applied with compost manure was found in Urambo district with 4,104 hectares (56.8% of the total area applied with compost manure) followed by Nzega (1,713 ha, 23.7%), Uyui (732 ha, 10.1%), Igunga (537 ha, 7.4%), Sikonge (84 ha, 1.2%) and Tabora Urban (60 ha, 0.8%) (Chart 3.149 and Map 3.59). 3.12.10 Fish Farming The number of households involved in fish farming in Tabora region was 222, representing 0.1 percent of the total agricultural households in the region (Chart 3.150 and Map 3.60). Sikonge and Uyui districts were the leading districts each with 98 households involved in fish farming. This was followed by Tabora Urban (26 households). Fish farming was not practiced in Nzega, Igunga and Urambo districts (Chart 3.151). The main source of fingerings was the neighbours which provided fingering to 49 percent of the fish farming households. About 38 percent of households practicing fish farming got fingerings from the government and 12 percent got them from non-governmental organizations and projects. All fish farming households in the region used the dug-out-pond system and the main fish specie planted was Carp. The number of fish harvested in Tabora region was 76,689, of which 55,768 fish (73%) were carp and 15,767 (21%) were tilapia whilst 5,153(7%) were other types (Chart 3.152) . All households (100%) did not sell fish. 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. Chart 3.150 Number of Households Practicing Fish Farming - TABORA Households Not Practicing Fish Farming, 235,694, 100% Households Practicing Fish Farming, 222, 0% 0 20 40 60 80 100 N u m b er o f H o u seh o ld s Sikonge Uyui Tabora Urban Nzega Igunga Urambo District Chart 3.151 Number of Households Practicing Fish Farming by District - TABORA Chart 3.152 Fish Production Number of Others, 5,153, 6.7% Number of Carp, 55,768, 72.7% Number of Tilapia, 15,767, 20.6% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, the regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 113 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were tarmac road (88), hospital (44), tertiary market (43), secondary school (27), all weather road (14), primary market (12), health clinic (10), primary school (4) and feeder road (3) (Table 3.17). Table 3.16: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Nzega 19.4 2.7 6.7 3.2 31.4 9.8 41.9 105.8 8.5 15.9 26.6 69.2 Igunga 13.6 2.4 9.1 2.1 25.2 6.4 46.3 163.9 7.0 14.9 27.0 107.1 Uyui 43.7 5.8 11.8 4.5 61.1 18.1 70.5 68.5 13.1 32.4 64.4 68.6 Urambo 22.4 5.7 19.0 3.2 58.4 8.9 63.5 125.8 13.3 19.4 48.3 115.8 Sikonge 67.3 3.5 47.1 2.0 67.0 7.8 76.8 133.4 28.6 25.8 86.0 119.4 Tabora Urban 14.6 4.1 3.8 0.8 13.5 8.2 14.0 14.5 9.4 13.3 13.9 5.0 Total 27.0 4.0 14.1 3.0 43.8 10.1 54.4 113.3 11.8 20.1 42.6 88.4 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (191,542 households, 81.2% of all rural agricultural households) 1,987 households (0.8%) use improved pit latrine and 2,357 households (1.0%) use flush toilets. The remaining 118 household (0.0%) use other toilets facilities. However, 39,914 households (16.9%) in the region had no toilet facilities (Chart 3.153). The distribution of the households without toilets within the region indicates that 32.8 percent of them were found in Nzega District and 0.6 percent was from Tabora Urban. The percentages of households without toilets in other districts were as follows Igunga (27.1%), Uyui (14.4%), Urambo (14.1%), and Sikonge (11.0%) Map 3.61). 3.13.3 Household’s Assets Bicycles are owned by most rural agricultural households in Tabora region with 164,536 households (69.7% of the agriculture households in the region) owning the asset followed by radio (126,723 households, 53.7%), iron (42,071 households, 17.8%), wheelbarrow (12,671 households, 5.4%), vehicles (3,214 households, 1.4%), mobile phone (2,336 households, 1.0%), television/video (2,127 households, 0.9%) and landline phone (368 households, 0.2%) (Chart 3.154). Chart 3.53 Agricultural Households by Type of Toilet Facility Other Type, 118, 0% Improved Pit Latrine - hh Owned, 1,987, 1% No Toilet , 39,914, 17% Flush Toilet, 2,357, 1% Traditional Pit Latrine, 191,542, 81% Chart 3.154 Percentage Distribution of Households Owning the Assets 17.8 69.7 53.7 0.2 0.9 1.0 1.4 5.4 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Bicycle Radio Iron Wheelbarrow Vehicle Mobile phone Television/Video Landline phone Assets Percent Urambo Sikonge Tabora Urban Uyui Igunga Nzega 5,525 3,754 849 9,192 34,913 34,629 10.2% 19.2% 8.3% 22.2% 77.3% 52.8% 28,000 to 35,000 21,000 to 28,000 14,000 to 21,000 7,000 to 14,000 0 to 7,000 Uyui Tabora Urban Igunga Nzega Sikonge 3,754 5,525 9,192 34,629 34,913 849 19.2% 10.2% 22.2% 52.8% 77.3% 8.3% Urambo 16,000 to 18,000 12,000 to 16,000 8,000 to 12,000 4,000 to 8,000 0 to 4,000 Tanzania Agriculture Sample Census Number of Households Map 3.56 TABORA Number and Percent of Households Infected With Ticks by District Map 3.57 TABORA Number and Percent of HouseholdsUsing Draft Animals by District Percent of Households Using Draft Animals Number of Households Infected with Ticks Number of Households Using Draft Animals Percent of Households Infected with Ticks Number of Households Using Draft Animals RESULTS 88 Igunga Nzega Uyui Sikonge Tabora Urban Urambo 11,737ha 26,328ha 8,880ha 5,695ha 2,803ha 8,972ha 12.1% 18.4% 8% 10.8% 15.1% 7.4% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Igunga Nzega Tabora Urban Urambo Sikonge 732ha 537ha 1,713ha 60ha 84ha 4,104ha 0.66% 0.55% 1.2% 0.33% 0.16% 3.4% Tanzania Agriculture Sample Census Planted Area (ha) Map 3.58 TABORA Planted Area and Percent of Total Planted Area With Farm Yard Manure application by District Map 3.59 TABORA Planted Area and Percent of Total Planted Area with Compostapplication by District Planted Area (ha) with Compost applied Planted Area (ha) with Farm Yard Manure applied Planted Area (ha) Percent Planted Area (ha) with Farm Yard Manure applied Percent of Planted Area (ha) with Compost applied 4,000 to 5,000 3,000 to 4,000 2,000 to 3,000 1,000 to 2,000 0 to 1,000 RESULTS 89 Nzega Tabora Urban Uyui Sikonge Urambo Igunga 13,083 10,807 5,764 4,406 229 5,625 20% 23.9% 14% 22.6% 2.2% 10.4% 12,000 to 14,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Urambo Uyui Sikonge Tabora Urban Igunga Nzega 0 98 98 26 0 0 0%% 0.24% 0.5% 0.26% 0% 0% Tanzania Agriculture Sample Census Number of Households Map 3.60 TABORA Number and Percent of Households Practicing Fish Farming by District Map 3.61 TABORA Number and Percent of Households Without Toilets by District Number Households Without Toilets Number of Households Practicing Fish Farming Number of Households Percent of Households Practicing Fish Farming Percent of Households Without Toilets 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 RESULTS 90 RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 3.13.4 Sources of Lighting Energy Wick lamp was the most common source of lighting energy in the region. with 83.6 percent of the total rural households using this source of energy followed by hurricane lamp (10.1%), pressure lamp (3.4%), fire wood (2.0%), mains electricity (0.5%), candles (0.2%), solar and gas or biogas (0.1% each). Other source of lighting energy accounted for 0.1 percent (Chart 3.155). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 94.84 percent of all rural agricultural households in Tabora region. This is followed by charcoal (2.67%). The rest of energy sources accounted for 2.49 percent. These were paraffin/kerosene (1.19%), crop residue (0.77%), bottled gas (0.24%), livestock dung (0.13%), mains electricity (0.11%) and solar (0.06%) (Chart 3.156). 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 70.1 percent of the rural agricultural households. This was followed by grass and mud (14.9%) which was closely followed by iron sheets (13.8%), tiles (0.6%), asbestos (0.3%) concrete (0.1%) and others (0.3%) (Chart 3.157). Urambo district had the highest percentage of households with grass/leaves roofing material (83%) and was followed by Uyui district.(81%), Nzega (77%), Sikonge (75%), Tabora Urban (72%) and Igunga (31%) (Chart 3.158 and Map 3.62). Chart 3.155 Percentage Distribution Of Households by Main Source of Energy for Lightining Solar, 346, 0% Candles, 484, 0% Pressure Lamp, 8,051, 3% Mains Electricity, 1,075, 0% Gas (Biogas), 151, 0% Other, 149, 0% Firewood, 4,687, 2% Wick Lamp, 197,211, 85% Hurricane Lamp, 23,763, 10% Chart 3.156 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 562, 0% Crop Residues, 1,814, 1% Mains Electricity, 250, 0% Solar, 152, 0% Livestock Dung, 300, 0% Parraffin / Kerocine, 2,807, 1% Charcoal, 6,299, 3% Firewood, 223,732, 95% Chart 3.157 Percentage Distribution of Households by Type of Roofing Material Other 0% Grass & Mud 15% Grass / Leaves 70% Tiles 1% Concrete 0% Asbestos 0% Iron Sheets 14% Chart 3.158 Percentage Distribution of Households with Grass/Lafy by District 77 31 72 75 81 83 11 16 12 21 23 13 0 10 20 30 40 50 60 70 80 90 Urambo Uyui Nzega Sikonge Tabora Urb Igunga District P e r c e n t %Grass/Leaves % Iron Sheets RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Tabora region was unprotected wells (67.5 percent of households use unprotected wells during the wet season and 68.2 percent of the households during the dry seasons). This was followed by protected wells (8.2 % of households during wet season and 7.8 % in dry season), unprotected springs (5.3% of households during the wet season and 9.3% in the dry season), surface water (5.5% of households in the wet season and 8.6% during dry season), uncovered rain water (8.1% of households during the wet season and 1.9% in the dry season), piped water (2.2% of households during the wet season and 1.8% in the dry season) and protected / covered springs (1.1% of households during the wet season and 1.3% in the dry season). Covered rain water was used as a main source by 0.3 percent of the households in the wet season and by 0.1 percent in the dry season and other services accounted for 1.9 percent in wet season and 1.3 percent in dry season Chart 3.159). About 59 percent of the rural agricultural households in Tabora region obtained drinking water within a distance of less than one kilometer during wet season compared to 43 percent of the households during the dry season. However, 41 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 57 percent of households in the dry season. The most common distance from the source of drinking water was between 500m and 2 km (Chart 3.160). 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Tabora region normally had 3 meals per day (58 percent of the households in the region). This was followed by 2 meals per day (38 percent) and 1 meal per day (3 percent). Only 1 percent of the households had 4 meals per day (Chart 3.161). Chart 3.160 Percent of Households by Distance to Main Source of Drinking Water and Season 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 10Km and above Distance Percent Wet Season Dry Season Chart 3.159 Percent of Households by Main source of Drinking Water and Season 0.0 20.0 40.0 60.0 80.0 Pip ed W ater Pro tected W ell Pro tected / Co v ered Sp rin g U p ro tected W ell U n p ro tected Sp rin g Su rface W ater (L ak e / D am / Riv er / Stream ) Co v ered Rain w ater Catch m en t U n co v ered Rain w ater Catch m en t O th er Main Source P ercent o f H o useho lds Wet Season Dry Season Chart 3.161 Number of Agriculural Households by Number of Meals per Day Three, 137,213, 58% One, 7,492, 3% Four, 2,159, 1% Two, 89,052, 38% RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 93 Tabora Urban had the largest percent of households eating one meal per day whilst Igunga had the highest percent of households eating three and four meals per day. (Table 3.17 and Map 3.63). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 156,187 (66.2% of the agricultural households in Tabora region) with 77,552 households (49.7 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (31.3%). Very few households had meat three or more times during the respective week. About 33.8 percent of the agricultural households in Tabora region did not eat meat during the week preceding the census (Chart 3.162 and Map 3.64). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 117,195 (49.7% of the total agricultural households in Tabora region) with 54,881 households (46.8% of those who consumed fish) consuming fish once during the respective week. This was followed by those who had fish twice (29,025 households, 24.8 %), those who had fish three times (13.8%). In general, the percentage of households that consumed fish twice or more times during the week in Tabora region was 62,314 (53.2% of the agricultural households that ate fish in the region during the respective period). About 50.3 percent of the agricultural households in Tabora region did not eat fish during the week preceding the census (Chart 3.162 and Map 3.65). 3.13.9 Food Security In Tabora region, 76,446 households (32.4% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement while 20,610 (8.7%) said they often experienced problems. However 7.2 percent sometimes experienced problems and 6.9 percent always had problems in satisfying the household food requirements. About 44.8 percent of the agricultural households said they did not experience any food insufficiency. (Map 3.66). Table 3.17: Number of Households by Number of Meals the Household Normally District One % Two % Three % Four % Total Nzega 1,190 1.8 19,042 29.0 44,886 68.5 447 0.7 65,566 Igunga 2,202 4.9 8,983 19.9 33,151 73.4 804 1.8 45,141 Uyui 1,934 4.7 14,990 36.3 23,789 57.6 605 1.5 41,318 Urambo 733 1.4 32,149 59.4 21,130 39.0 109 0.2 54,120 Sikonge 914 4.7 8,737 44.8 9,669 49.5 194 1.0 19,514 Tabora Urban 519 5.1 5,151 50.2 4,589 44.7 0 0.0 10,258 Total 7,492 3.2 89,052 37.7 137,213 58.2 2,159 0.9 235,917 Chart 3.162 Number of Households by Frequency of Meat and Fish Consuption 0 25,000 50,000 75,000 100,000 Once Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Chart 3.163: Number of Households by Level of Food Availability Always, 16,249, 7% Often, 20,610, 9% Sometimes, 16,953, 7% Seldom, 76,446, 32% Never, 105,659, 45% Never Seldom Sometimes Often Always RESULTS ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 Tabora Urban had the highest percent of households that had problems in satisfying their household food requirements (35% of the agricultural households always or often having food problems). The percentage of households with food problems is also high in Igunga, Sikonge and Uyui. Urambo and Nzega districts had the lowest percentages of households that always or often faced food problems being between 20 and 21% of the agricultural households (Chart 3.164). 3.13.10 Main Sources of Cash Income The main cash income of the households in Tabora region came from the selling of food crops (22.8 percent of smallholder households), followed by casual labour (20.9%), selling of cash crops (16.0%), businesses (11.8%), sale of livestock (10.3%) and cash remittances (6.0%). Only 2.2 percent of smallholder households reported the wages and salaries in cash were their main source of income followed by livestock products (1.1%) and fishing (0.2%) (Chart 3.165). Chart 164: Percentage of Household Reporting Food Availability Status by District 0% 25% 50% 75% 100% Sikonge Urambo Uyui Nzega Igunga Tabora Urban District Percentage of Households Never Seldom Sometimes Often Always Chart 3.165: Percentage Distribution of the Number of Households by Main Source of Income Remittance, 6.0, 6% not applicable, 0.2, 0% Other, 0.9, 1% Wages & Salaries, 2.2, 2% Livestock Products, 1.1, 1% Forest Products, 7.5, 8% Livestock, 10.3, 10% Business Income, 11.8, 12% Other Casual Cash Earnings, 20.9, 21% Cash Crops, 16.0, 16% Food Crops, 22.8, 23% Fishing, 0.2, 0% Uyui Tabora Urban Nzega Urambo Sikonge Igunga 23,789 9,669 4,589 44,886 21,130 33,151 57.6% 49.5% 44.7% 68.5% 39% 73.4% 40,000 to 50,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Uyui Tabora Urban Igunga Urambo Sikonge Nzega 14,622 33,359 13,968 50,779 7,367 45,166 75% 81% 31% 77% 72% 83% 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Tanzania Agriculture Sample Census Number of Households Map 3.62 TABORA Number and Percent of Households Using Grass/leaves for Roofing Material by District Map 3.63 TABORA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Practicing Fish Farming Number of Households Using Grass/ Leaves for Roofing Material Number of Households Percent of Households Using Grass/Leaves for Roofing Material Percent of Households Practicing Fish Farming RESULTS 95 Igunga Nzega Tabora Urban Uyui Sikonge Urambo 13,859 29,694 3,777 RESULTS 96 10,558 4,649 15,015 30.7% 45.3% 36.8% 25.6% 23.8% 27.7% 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Tabora Urban Sikonge Nzega Igunga 7,331 2,712 2,769 11,844 23,718 6,506 17.7% 26.4% 14.2% 21.9% 14.45 36.2% Urambo Tanzania Agriculture Sample Census Number of Households Map 3.64 TABORA Number and Percent of Households Eating Meat Once per Week by District Map 3.65 TABORA Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Number of Households Eating Meat Once per Week Number of Households Percent of Households Eating Meat Once per Week Percent of Households Eating Fish Once per Week 24,000 to 30,000 18,000 to 24,000 12,000 to 18,000 6,000 to 12,000 0 to 6,000 Uyui Tabora Urban Nzega Sikonge Urambo Igunga 33,897 7,519 56,827 16,516 47,380 36,920 82% 73.3% 86.7% 84.6% 87.5% 81.8% 40,000 to 60,000 30,000 to 40,000 20,000 to 30,000 10,000 to 20,000 0 to 10,000 Number of Households Map 3.66 TABORA Number and percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency RESULTS 97 TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 98 4 TABORA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Region Profile The region profile describes the status of the agriculture sector in the region and compares it with other regions in the country. Tabora has a land area of around 600,000 hectares under cultivation. It is characterised by annual cropping with a very small amount of permanent crops. The percent of land available to smallholders that was utilised during the census year is one of the lowest in the country. This, coupled with its having one of the lowest number of crop growing households per square kilometre in Tanzania may indicate that there is more than sufficient accessible land in the region to satisfy the needs of the smallholder households. This is reflected by the low number of households responding to insufficiency of land. The region has only one planting season (the long rainy season). Tabora has the fourth largest planted area of maize and rice in the country, however the yields during the census year were low. Although not the largest sorghum producing region, it has one of the largest area planted per household. It is a predominant tobacco growing region and has the second largest planted areas of groundnuts and onions in the country. Cassava and beans are of moderate to low importance in the region. Permanent crops consist of small areas of mangos and oil palm. Although small, the region has a moderate planted area under irrigation and the number of households using irrigation has remained stable over a 10 year period. Wells and dams are the most common source of water for irrigation. Land clearing is predominantly by hand, however around half of the households use oxen for cultivation while the other half cultivates by hand. Tabora is one of the four regions in the country that uses noticeable quantities of inorganic fertilisers however, as with all other regions most of the planted area has no fertiliser application. Small amounts of insecticides and fungicides were used and the region is placed second in the use of these inputs. Crops are either stored unprotected or in traditional cribs. Compared to other regions, the percent of households selling crops was low. Practically all crop processing was done on neighbours machines, with small amounts sold to neighbours. A low percent of households received extension services in Tabora compared to other regions. Smallholders do not plant trees in Tabora and there are virtually no erosion control/water harvesting structures in the region. 4.2 District Profiles The following district profiles highlights the characteristics of each district and compares them in relation to population, main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Nzega Nzega district had the largest number of households in the region and it had one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. The district had no households keeping livestock only and no pastoralists were found in the district. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 The most important livelihood activity for smallholder households in Nzega district was annual crop farming, followed by tree / forestry resources and livestock keeping. However, the district had the second lowest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Nzega had the highest percent of female headed households (17.1%) and it had one of the highest average age of the household head. With an average household size of 5 members per household it had about the same average as the region. Nzega has a comparatively low literacy rate among smallholder households and this was reflected by the concomitant relatively low level of school attendance in the region.. The literacy rate for the heads of household is also lower than other districts in the region. It had the smallest utilized land area per household (1.9ha) and the allocated area was almost fully utilized indicating a high level of land pressure. The total planted area was greater than in some other districts in the region, however it had the lowest planted area per household (1.7ha) attributed to the high number of smallholders in the district. The district is important for maize production in the region and had a planted area of over 52,000ha; however the planted area per household was the lowest in the region. Paddy production was also very important with a largest planted area of 25,289 hectares but the production of sorghum is small. Cassava production was moderate accounting for 14.2 percent of the quantity harvested in the region. The district had the smallest planted area of sweet potatoes (673 ha) and it was one of the two districts in the region which didn’t grow Irish potatoes. The district was among the lowest beans producer in the region with a planted area of 1,064ha. Oilseed crops were very important in Nzega and the district had the largest area planted with groundnuts (19,722ha). Vegetable production was moderately important in the district. It had moderate area planted with tomatoes and onion (120 ha and 151 ha respectively). Traditional cash crops (e.g. tobacco and cotton) were grown in small quantities. Compared to other districts in the region, Nzega had the second smallest area planted with permanent crops which were dominated by mango (649 ha), guava (279 ha) and oranges (234 ha). Other permanent crops were either not grown or were grown in very small quantities. In Nzega district most land clearing and preparation was done by oxen followed by hand cultivation, however slightly more land preparation was done by tractor compared to most other districts. The use of inputs in the region is very small, however district differences exist. Nzega has the second smallest planted area with improved seed in Tabora region. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), however most of this is farm yard manure. Compared to other districts in the region, Nzega district has a small level of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. The use of herbicides is also small. The district has the fourth largest area with 6,125 ha of irrigated land. The most common source of water for irrigation is from dams using gravity and hand bucket. Flood and bucket are the most common means of irrigation water application. The most common method of crop storage is in sacks / open drums followed by storing in locally made traditional structures, however the district has the second largest proportion of households storing crops in sacks / open drums compared to other districts in the region. The district has the second largest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The highest percent of households TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 processing crops in Tabora region is found in Nzega district and is almost all done by neighbor machines. The district also has a higher percent of households selling processed crops to local markets/trade stores than other districts and no sales are to secondary markets, marketing cooperatives, farmers association or large scale farms. Although small, access to credit in the district is to men only and the main sources are religious organisations/NGO projects and traders/trade stores. A comparatively larger number of households receive extension services in Nzega and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Nzega (with 98 planted trees) and is mostly Gravellis with some Azadirachta and leucena spp. The second highest proportion of households with erosion control and water harvesting structures is found in Nzega district and are mostly erosion control bunds; however it also has moderate number of dams and drainage ditches compared to other districts. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has a moderate number of pigs in the region and has the third highest number of chickens. Although small, the district has the highest number of layers in the region. Nzega district has moderate to small numbers of ducks, turkeys and donkeys are also found in the district. The smallest number of households reporting Tsetse and tick problems was in Nzega district and it had the second largest number of households de-worming livestock. The use of draft animals in the district is high. Fish farming is virtually absent in the district. It has amongst the best access to primary schools, all weather roads and primary and secondary markets compared to other districts. However, it has one of the worst accesses to health clinics and regional capital. Nzega district has the third highest percent of households with no toilet facilities. The district has the highest percent of households owning bicycles, the second highest number of households owning vehicles and the third highest number of households owning TV/Video sets. It has small number of households using mains electricity. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the third highest percent of households with grass roofs with 12 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. The district is among the districts with the lowest percent of households having one meal per day. It has the moderate percent of households having two meals per day compared to other districts and amongst the highest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat during the week prior to enumeration and amongst the district with highest percent of household that did not eat fish in the same week; however most households never had problems with food satisfaction. 4.2.2 Igunga Igunga district had the third largest number of households in the region and was among the districts with the highest percentages of households involved in smallholder agriculture in the region. Most smallholders were involved in crop and livestock production, followed by crop farming only. It had a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Igunga district was annual crop farming, followed by off farm income. The district had the lowest percent of households with no off-farm activities although it had the second TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Igunga had a lowest percent of female headed households (11.3%) and it had one of the moderate average age of the household head in the region. With an average household size of 7 members per household it was above the average for the region. Igunga has a comparatively moderate literacy rate among smallholder households and this was reflected by the district having the moderate level of school attendance in the region. The literacy rate for the heads of household was lower than most districts in the region. It has a largest utilized land area per household (3.8ha) and 92.1 percent of the allocated area was being utilized. The district had the largest planted area in the region, and the largest planted area per household (3.2ha). The district is important for maize production in the region and had the largest planted area of over 56,000 ha, and the planted area per household was also large for the region. The district had moderate planted area of paddy in the region with 6,560 hectares. Igunga had the largest planted area for sorghum (38,804ha) whilst cassava production was low, accounting for 3.9 percent of the quantity harvested in the region. The district had the largest area planted with sweet potatoes (3,639ha) but a very small planted area of Irish potatoes (112 ha). The production of beans in Igunga was very small compared to other districts in the region with a planted area of 319ha. Igunga district had a moderate planted area for groundnuts and an area planted per household of 0.5 ha. Vegetable production was important in the district. It had the largest planted area for onions in the region accounting for 80.4 percent of the onions planted area. Other vegetables were grown in small quantities. Cotton and tobacco were the cash crops grown in the district. The district had the largest area planted with cotton (21,751ha). Tobacco was very small. Compared to other districts in the region, Igunga had the third largest area planted with permanent crops which were dominated by mango (2,069 ha), coconuts (268 ha), sugar cane (47 ha) and pawpaw (40 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by oxen ploughing followed by hand cultivation, however a very small amount of land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Igunga has the fifth largest planted area with improved seed in Tabora region. Also, the district has the fifth largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), most of these are farm yard manure and inorganic fertilizers. Compared to other districts in the region, Igunga district has the third largest area of insecticide use and has the second largest area of fungicide and herbicide use. It has the third largest area with irrigation compared to other districts with 6,822 ha of irrigated land. The most common source of water for irrigation is from dams using gravity. Flood irrigation is the most common means of irrigation water application and a small amount of bucket / watering can is used. The most common method of crop storage in Igunga is locally made traditional structures, however the proportion of households storing crops in the district is lower compared to other districts in the region. The district has the fourth highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Igunga district is one of the districts in Tabora region with moderate percent of households processing crops and is almost all done by neighbor machines. There is no agro-processing carried out by co-operatives. The district has the second largest number of households selling primary processed products. Although very small, access to credit in the district is to men (100% of those who accessed credit) and the main sources are family friends and relatives. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 A comparatively small number of households receive extension services in Igunga district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. Tree farming is not very important in Tabora region. Igunga district has the smallest number of planted trees in the region (with 32 planted trees) and is mostly Moringa Spp with some Sena Spp and Azadirachta Spp. Igunga has the lowest number of households with water control bunds. The district has a largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is also highest compared to other districts. Pigs were virtually absent in the district and has the third largest number of chickens, almost all are indigenous. Igunga has the fourth largest number of improved chickens in the region. The district has the largest number of ducks and donkeys, however small numbers of rabbits are also found in the district. Turkeys are virtually not found in the district. A number of households reported tsetse and tick problems in Igunga district. De- worming of livestock is also practiced in Igunga. The use of draft animals in the district exists. A small number of households’ practice fish farming, however the district has the second largest number in the region. The district has the second largest number of donkeys and turkeys. Some ducks are also found in the district. A number of households reported tsetse problem. Igunga district had the second largest number of households reported of ticks and it had the second largest number of households de-worming livestock. The district has the largest number of households using draft animals in the region. Fish farming is virtually absent in the region. It has amongst the best access to secondary schools, primary schools, all feeder roads, health clinics and primary, secondary and tertiary markets compared to other districts. However, it has one of the worst access to regional capital and tarmac roads. Igunga district has the highest percentage of households without toilet facility (23.9%) and it is among the districts with the lowest percent of households owning radios and iron. The district has the second percent of households owning bicycles and has third percent of households owning mobile phones and vehicles. It has the largest percent of households owning wheelbarrows and televisions/videos. The most common source of drinking water is from unprotected wells and uncovered rainwater catchments. It is one of the districts with the highest percent of households having three meals per day. The district had the second highest percent of households that did not eat meat and has the highest percent of households that did not eat fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.3 Uyui Uyui district had the forth largest number of households in the region and it had the highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. It had a small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Uyui district was annual crop farming, followed by off-farm income. The district had the second highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Uyui had a relatively low percent of female headed households (13.8%) and it had one of the moderate average age of the household head in the region. With an average household size of 7 members per household it was above the average for the region. Uyui had a comparatively low literacy rate among smallholder households and this was reflected by the TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 concomitant relatively high level of population not attended schools in the region. The literacy rate for the heads of household was moderate compared with other districts in the region. It had higher utilized land area per household (3.2ha) than the regional average of 2.9 ha and 73.2 percent of the allocated area was being utilized. The district had the fourth largest total planted area as compared to other districts in the region. Also, the district had the third largest planted area per household (2.3ha). The district is moderately important for maize production in the region and had a planted area of over 46,418 ha, however the planted area per household was 1.1 ha which was moderate in the region. Paddy production was also important with a planted area of 14,587 hectares. Sorghum was less important with a planted area of 3,162 hectares. Irish potatoes and wheat were not produced in the district. The district had a moderately large planted area of cassava accounting for 15.5 percent of the cassava planted area in the region. The production of beans in Uyui was much lower than Urambo district but higher than other districts in the region with a planted area of 3,654ha. Oilseed crops were important in Uyui with 98.2 percent of the groundnuts grown in the district. Uyui district had the largest area planted with vegetable in the region. A very small quantity of cotton was planted in the district. The district had the second largest planted area for tobacco. Permanent crops were less important in Uyui district (12.9% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district include mango (432 ha), guava (329 ha) and palm oil (291 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, only very small land preparation was done by tractors. The use of inputs in the region is very small, however district differences exist. Uyui has the second largest planted area with improved seed in Tabora region. The district has the third largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer), most of these are inorganic fertilizers and farm yard manure. Compared to other districts in the region, Uyui district has the second largest area of insecticide use and has the third largest area of fungicide and herbicide use. It has the second largest area with irrigation compared to other districts with 7,037 ha of irrigated land. The most common source of water for irrigation is from dams using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Uyui is sacks and open drums, however the proportion of households storing crops in the district is moderate compared to other districts in the region. The district has the third highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Uyui district is one of the districts in Tabora region with a high percent of households processing crops and is almost all done by neighbor machines. In the district the agro-processing is not carried out neither by traders, co-operatives nor factories. The district has the smallest number of households selling primary processed products. Although very small, access to credit in the district is mostly to men (96% of those who accessed credit) and the main sources are cooperatives, family friends and relatives. A comparatively moderate number of households receive extension services in Uyui district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 Tree farming is not very important in Tabora region. However, Uyui district has the largest number of planted trees in the region (with 793 planted trees) and is mostly Moringa Spp with some Eucalyptus Spp. Uyui has the highest number of households with dams, tree belts and water harvesting bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the third largest number of pigs in the region and the second largest number of chickens. Most of them are indigenous. Uyui has the second largest number of improved chickens in the region. The district has the largest number of ducks and donkeys, however small numbers of rabbits are also found in the district. Turkeys are virtually not found in the district. A number of households reported tsetse and tick problems in Uyui district. De-worming of livestock is also practiced in Uyui. The use of draft animals in the district exists. A small number of households’ practice fish farming, however the district has the second largest number in the region. Uyui district is not amongst the best access to any infrastructure compared to other districts. However, it has one of the worst access to secondary schools, primary schools, feeder roads, hospitals, health clinics, district capital, secondary markets and tertiary markets. Uyui district has a moderate percent of households with no toilet facilities and it has the highest percent of households owning vehicles and has the second highest percent of households owning land lines, TV/Video and mobile phones. It has the third lowest number of households owning wheelbarrows, radios and bicycles. Uyui district has the third highest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (80.7%) with 16.2 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Forty one percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district had a highest percent of households that did not eat meat compared to other districts and moderate percent of households that did not eat fish during the week prior to enumeration, however most households reported to have no food satisfaction. 4.2.4 Urambo Urambo district had the second largest number of households in the region and it had the fifth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Urambo district there were no households involved in livestock only. Also, no pastoralists were found. The most important livelihood activity for smallholder households in Urambo district was annual crop farming followed by off-farm income. It had the third lowest percent of households with no off-farm activities and the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Urambo district had a relatively low percent of female headed households (13.7%) and it had one of the lowest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Urambo district had a comparatively high literacy rate among smallholder households and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the female heads of household was lower than that of Sikonge district but slightly higher than those of other districts in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 It has the third largest utilized land area per household (3.0 ha) and only 69.1 percent of the allocated land area had been utilized. The total planted area was moderate compared to other districts in the region, however it had the second lowest planted area per household (2.2 ha) attributed to the high number of smallholders in the district. Urambo district is more or less important for maize production in the region and had a planted area of 46,076 ha, however the planted area per household was among the lowest in the region. Paddy production was also more or less important with a planted area of only 11,904 hectares but the production of sorghum was small. The production of cassava and beans in Urambo district was much higher than in other districts. The district had the second largest area planted with oil seeds especially groundnuts. Vegetable production was not very important in the district. The most important vegetable produced was tomatoes followed by amaranths and onions. Other vegetables were produced in very small quantities. Urambo district had the largest area planted with tobacco (15,565 ha). Cash crops such as cotton were grown in small quantities. Urambo district had the largest area planted with permanent crops (58.6% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district include palm oil (1,859 ha), mango (1,618 ha), banana (1,362 ha) and pawpaw (516 ha). Other permanent crops were either not grown or were grown in small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Urambo has the largest planted area with improved seed in Tabora region. The district has the second largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are inorganic fertilizers followed by farm yard manure. Compared to other districts in the region, Urambo district has the largest area of insecticide use and has the largest area of fungicide and herbicide use. It has the largest area with irrigation compared to other districts with 9,624 ha of irrigated land. The most common source of water for irrigation is from wells using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Urambo is sacks and open drums, however the proportion of households storing crops in the district is high compared to most of other districts in the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Urambo district is one of the districts in Tabora region with a high percent of households processing crops and is almost all done by neighbor machines. However, the agro-processing is not done by traders, co- operatives or by factories. The district has no households selling primary processed products. Although small, access to credit in the district is mostly to men (99% of those who accessed credit) and the main sources are co-operatives. Sikonge district has the third largest number of households received agricultural credits in the region. A comparatively high number of households receive extension services in Urambo district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 Tree farming is not very important in Tabora region. However, Urambo district has the second largest number of planted trees in the region (with 608 planted trees) and is mostly Albizia Spp with some Acacia Spp. Urambo has the highest number of households with dams, tree belts and water harvesting bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate to low compared to other districts. It has the largest number of pigs in the region and the largest number of chickens, all of which are indigenous. Urambo has the third largest number of improved chickens in the region. The district has the largest number of rabbits and has the third largest number of ducks. Turkeys and donkeys are virtually not present in the district. A number of households reported tick problem is relatively small but the district has the largest number of households reported tsetse problems in the region. De-worming of livestock is also practiced in Urambo. The use of draft animals in the district exists. Fish farming is virtually absent in the district. Urambo district is not amongst the best access to any infrastructure compared to other districts. However, it has one of the worst accesses to primary schools, hospitals, district capital, regional capital and tarmac road. Urambo district has relatively low percent of households with no toilet facilities and it has the highest percent of households owning radio and has the second highest percent of households owning iron. It has the third lowest number of households owning bicycle. Urambo district has the lowest percent of households owning vehicles and the use of is vrtuall absent. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a highest percent of households with grass roofs (83.3%) with 10.9 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Sixty one percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district was amongst the districts with the lowest percent of households that did not eat meat or fish the week prior to enumeration, however most households reported to have food satisfaction. 4.2.5 Sikonge Sikonge district had the lowest number of households in the region and it had the fourth highest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Sikonge district, very few households were involved in livestock only. Also, pastoralists were virtually absent. The most important livelihood activity for smallholder households in Sikonge district was annual crop farming followed by livestock keeping / herding. It had the highest percent of households with no off-farm activities and the forth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Sikonge district had a relatively low percent of female headed households (13.5%) and it had one of the lowest average age of the household head. Its average household size of 6 members per household was higher than the average for the region. Sikonge district has a comparatively high literacy rate among smallholder households and this was reflected by the concomitant relatively high level of school attendance in the region. The literacy rate for the female heads of household was the highest in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 It had the third largest utilized land area per household (3.0 ha) and only 69.9 percent of the allocated land area had been utilized. The total planted area was small compared to other districts in the region, however it had the second largest planted area per household (2.7 ha) attributed to the low number of smallholders in the district. Sikonge district was more or less important for maize production in the region with a planted area of 22,958 ha and had the second largest planted area per household in the region. Paddy, cassava and groundnuts production were more or less important with a planted area of only 5,193 hectares, 1,829 hectares and 7,863 hectares respectively. The production of sorghum and beans in Sikonge district was also more or less important in the region for which it had the third largest planted area in the region. Vegetable production was not very important in the district. The most important vegetable produced is radish followed by okra. Other vegetables were produced in very small quantities. Sikonge district had a moderate planted area of tobacco (5,735 ha) compared to other districts in the region. Sikonge district had the smallest area planted with permanent crops (0.9% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district was mango (53 ha) followed by banana (19 ha) and oranges (8 ha). Other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractor. The use of inputs in the region is very small, however district differences exist. Sikonge has the forth largest planted area with improved seed in Tabora region. The district has the third largest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are inorganic fertilizers followed by farm yard manure. Compared to other districts in the region, Sikonge district has the forth largest area of insecticide use, fungicide and herbicide use. It has the smallest area with irrigation compared to other districts with 2,520 ha of irrigated land. The most common source of water for irrigation is from wells using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of flood irrigation is used. The most common method of crop storage in Sikonge is locally made traditional structures followed by sacks and open drums. The proportion of households storing crops in the district is highest compared to most of other districts in the region. The district has the second highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Sikonge district is one of the districts in Tabora region with a highest percent of households processing crops and is almost all done by neighbor machines. However, the agro-processing is not done by traders or by factories. The district has small number of households selling primary processed products. Most of the products are sold to neighbours. Although small, access to credit in the district is mostly to men (99% of those who accessed credit) and the main sources are co-operatives. Sikonge district has the third largest number of households received agricultural credits in the region. A comparatively low number of households receive extension services in Sikonge district and most of this is from the government. The quality of extension services was rated between good and very good by the majority of the households. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 Tree farming is not very important in Tabora region. However, Sikonge district has the second smallest number of planted trees in the region (with 226 planted trees) and is mostly Moringa Spp with some Pinus Spp. and Acacia Spp. Sikonge is among the districts with the highest number of households water harvesting bunds and a moderate number of households with erosion control bunds. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate to small compared to other districts. Pig rearing in Sikonge district is virtually absent. Sikonge has the second smallest number of chickens and very small number of improved chickens. Also, the district has very small number of ducks, turkeys, rabbits and donkeys. A number of households reported tick problem is relatively small but the district has the moderate number of households reported tsetse problems in the region. De-worming of livestock is also practiced in Urambo. The use of draft animals in the district exists. Very small number of households’ practice fish farming; however the district has the largest number of harvested fish in the region. Sikonge district is amongst the worst access to some infrastructure compared to other districts. It is one amongst districts with the worst access to secondary schools, primary schools, all weather roads, hospitals, district capital, regional capital, primary markets, secondary markets tertiary markets and tarmac road. Sikonge district has a high percent of households with no toilet facilities and it has the highest percent of households owning iron. It has the second highest percent of households owning radio and wheelbarrow and has the third, forth and fifth percent of households owning television/video, mobile telephones and bicycle respectively. Sikonge district has the lowest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (74.9%) with 20.5 percent of households having iron sheets. The most common source of drinking water is from unprotected wells. Fifty percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. Very few households were having four meals per day. The district had the second smallest percent of households that did not eat meat during the week prior to enumeration and among the district with moderate percent of household that did not eat fish in the same week; however most households never had problems with food satisfaction. 4.2.6 Tabora Urban Tabora Urban district had the second lowest number of households in the region and it had the smallest percent of households involved in smallholder agriculture in the region. Most smallholders were involved in crop farming only, followed by crop and livestock production. In Tabora Urban, very few households were involved in livestock only. Also, pastoralists were virtually absent. The most important livelihood activity for smallholder households in Tabora Urban district was annual crop farming followed by off-farm income. It had the third highest percent of households with no off-farm activities and the fifth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tabora Urban had a relatively high percent of female headed households (16.75%) and it had one of the highest average age of the household head. Its average household size of 5 members per household was about the same as the average for the region. Tabora Urban has a highest literacy rate among smallholder households. The literacy rate for the female heads of household was moderate as compared to other districts in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 It had the fifth largest utilized land area per household (2.3 ha) and only 70.4 percent of the allocated land area had been utilized. The total planted area was the smallest in the region, it also had the smallest planted area per household (1.7 ha) attributed to the large number of smallholders in the district. Tabora Urban is almost important for maize production in the region and had a planted area of 7,844 ha and has the least planted area per household in the region. Paddy production was also more or less important with a planted area of 2,124 ha. A very small area was planted with sorghum while the production of bulrush millet and finger millet was virtually absent. Cassava production was low accounting for 6.4 percent of the quantity harvested in the region. The district had a small planted area of sweet potatoes (772 ha). The production of beans in Tabora Urban was smaller than in other districts in the region with a planted area of 1,439ha. Oilseed crops were not important in Tabora Urban and it had the sixth groundnuts planted area in the region. Vegetable production was not very important in the district. It had the second largest planted area for tomatoes (221ha) and a small planted area of onions (41ha) and amaranths (24ha). The production of tomatoes and amaranths accounted for 30.1 percent and 67.6 percent respectively in the region. Traditional cash crops (especially tobacco) were grown in very small quantities. Tabora Urban has the third smallest planted area for permanent crops (9.4% of the total permanent crop planted area in Tabora region is found in the district). The most prominent permanent crops in the district was mango (788 ha) followed by banana (56 ha) and sugar cane (62 ha). Oil palm was grown in small quantities (10ha) whilst other permanent crops were either not grown or were grown in very small quantities. As with other districts in the region, most land clearing and preparation was done by hand followed by oxen, very small land preparation was done by tractors. The use of inputs in the region is very small, however district differences exist. Tabora Urban has the smallest planted area with improved seed in Tabora region. The district has the smallest planted area with fertilizers (Farm yard manure, compost and inorganic fertilizer). Most of these are farm yard manure followed by inorganic fertilizers. Compared to other districts in the region, Tabora Urban district has the smallest area of insecticide use, fungicide and herbicide use. It has the second smallest area with irrigation compared to other districts with 2,738 ha of irrigated land. The most common source of water for irrigation is from dams using hand bucket. Bucket/watering cans is the most common means of irrigation water application and a small amount of water hose irrigation is used. The most common method of crop storage in Tabora Urban is sacks and open drums followed by locally made traditional structures. The proportion of households storing crops in the district is higher compared to some other districts in the region. The district has the fifth highest percent of households selling crops, however for those who did not sell, the main reason for not selling is the fact that the open market price was too low. Tabora Urban is one of the districts in Tabora region with a highest percent of households processing crops and most of them are done by neighbor machines. However, the agro-processing done by factories is virtually absent. The district has small number of households selling primary processed products. Most of the products are sold to neighbours. Although small, access to credit in the district is to men (100% of those who accessed credit) and the main sources are co-operatives. Tabora Urban has the smallest number of households received agricultural credits in the region. TABORA PROFILES ___________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 A comparatively low number of households receive extension services in Tabora Urban and most of this is from the government. The quality of extension services was rated between average and good by the majority of the households. Tree farming is not very important in Tabora region. Tabora Urban has the smallest number of planted trees in the region (with 108 planted trees) and is mostly Albizia Spp with some Moringa Spp. and Leucena Spp. Tabora Urban is among the districts with moderate to small number of households with erosion control bunds, drainage ditches and terraces. The district has the smallest number of cattle, goats, sheep and pigs in the region and they are almost all indigenous. It has the least number of chickens in the region and rearing of improved chicken is virtually absent. The district has the smallest number of ducks in the region and it has no turkeys, rabbits or donkeys. A number of households reported tsetse and tick problems in Tabora Urban district is small. De-worming of livestock is also practiced in Tabora Urban. The use of draft animals in the district exists. Very small number of households’ practice fish farming; however the district has the largest number of harvested fish in the region. Tabora Urban is the best access to most infrastructures compared to other districts. It is the best district with the best access to all weather roads, feeder roads, district capital, regional capital, secondary markets, tertiary markets and tarmac roads. Also, the district is amongst the districts with best access to primary and secondary schools, health clinics, hospitals and primary markets. Tabora Urban has a lowest percent of households with no toilet facilities and it has the highest percent of households owning mobile phones. It has the second highest percent of households owning radio and has the third highest percent of households owning landline phones and wheelbarrows. The district has the fourth percent of households owning iron and has the smallest percent of households owning bicycles. Tabora Urban has the second highest percent of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a second lowest percent of households with grass roofs (71.8%) and a highest percent of households having iron sheets (22.8%). The most common source of drinking water is from unprotected wells. Fifty five percent of the households in the district reported having one or two meals per day and the rest were having three meals per day. The district had the third largest percent of households that did not eat meat during the week prior to enumeration and among the district with lowest percent of household that did not eat fish in the same week; however most households seldom had problems with food satisfaction. Appendix II 129 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 130 Rural Household Involved in Agriculture % of Total Rural House- hold Rural Households NOT Involved in Agriculture % of Total Rural House- hold Total Rural Household % of Total Rural House- hold Urban Households % of Total Urban House- holds Total Number of Households (From 2002 Population Census) Number % Number % Number % Number % Number Nzega 65,566 97.0 2,001 22.5 67,567 27.6 6,012 12.9 73,579 Igunga 45,141 96.2 1,771 19.9 46,912 19.2 4,264 9.2 51,176 Uyui 41,318 96.6 1,439 16.2 42,757 17.5 409 0.9 43,166 Urambo 54,120 95.1 2,800 31.4 56,920 23.2 5,713 12.3 62,633 Sikonge 19,514 97.7 466 5.2 19,980 8.2 2,269 4.9 22,249 Tabora Urban 10,258 96.1 421 4.7 10,679 4.4 27,887 59.9 38,566 Total 235,917 96.4 8,908 100.0 244,824 100.0 46,545 100.0 291,369 Number Percent Number Percent Number Percent Number Percent Nzega 37,921 26 0 0 27,645 32 65,566 28 65,566 27,645 Igunga 21,553 15 116 39 23,472 27 45,141 19 45,025 23,588 Uyui 26,559 18 105 36 14,653 17 41,318 18 41,212 14,758 Urambo 40,380 27 0 0 13,740 16 54,120 23 54,120 13,740 Sikonge 13,677 9 50 17 5,787 7 19,514 8 19,464 5,837 Tabora Urban 7,956 5 25 9 2,276 3 10,258 4 10,233 2,302 Total 148,046 100 296 100 87,575 100 235,917 100 235,621 87,871 2.2 TYPE OF AGRICULTURE HOUSEHOLD:Number of Agriculture Households By Type of Holding and District, 2002/03 Agricultural Year Crops Only Livestock Only Total Number of Agricultural Households Rearing Livestock Agriculture, Non Agriculture and Urban Households 2.1: TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by Type of Household and District, 2002/03 Agriculture Year District Crops & Livestock Total District Type of Agriculture Household Total Number of Agricultural Households Growing Crops Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 131 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 132 Number of Households % Average Household Size Number of Households % Average Household Size Number of Households % Average Household Size Nzega 54,327 83 6 11,239 17 3 65,566 100 5 Igunga 40,038 89 7 5,103 11 4 45,141 100 7 Uyui 35,609 86 7 5,708 14 5 41,318 100 7 Urambo 46,691 86 6 7,429 14 4 54,120 100 6 Sikonge 16,882 87 6 2,631 13 3 19,514 100 6 Tabora Urban 8,549 83 6 1,709 17 4 10,258 100 5 Total 202,097 86 6 33,820 14 4 235,917 100 6 3.0 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 133 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 134 Nzega 1 5 3 4 6 7 2 Igunga 1 5 4 2 6 7 3 Uyui 1 4 3 2 6 7 5 Urambo 1 5 4 2 6 7 3 Sikonge 1 5 2 3 6 7 4 Tabora Urban 1 4 3 2 6 7 5 Total 1 5 4 2 6 7 3 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 58,722 601 1,952 3,004 718 296 138 Igunga 18,172 110 7,535 16,131 1,751 114 996 Uyui 35,913 0 404 3,485 505 0 801 Urambo 48,593 125 821 3,307 1,273 107 247 Sikonge 15,991 0 438 2,032 329 0 723 Tabora Urban 7,505 126 326 1,249 438 78 436 Total 184,896 962 11,476 29,208 5,014 596 3,340 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 6,278 2,340 23,383 19,320 4,503 0 9,747 Igunga 22,496 627 10,573 7,580 1,304 0 3,018 Uyui 4,992 2,880 9,984 18,350 2,678 0 2,334 Urambo 4,797 5,084 10,962 23,948 2,252 466 6,270 Sikonge 3,182 781 5,435 5,601 776 142 3,591 Tabora Urban 2,396 1,051 1,414 3,485 490 13 1,228 Total 44,142 12,762 61,751 78,283 12,003 622 26,187 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 426 3,944 10,453 13,602 4,464 136 27,639 Igunga 3,370 2,015 5,050 9,123 2,727 0 20,420 Uyui 307 5,137 9,280 8,018 1,656 0 2,837 Urambo 361 12,827 10,026 8,296 2,526 232 15,799 Sikonge 291 2,021 5,069 3,339 828 337 3,108 Tabora Urb 286 2,312 1,963 2,484 544 0 1,168 Total 5,041 28,256 41,840 44,863 12,745 705 70,971 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District District Livelihood Activity Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Tanzania Agriculture Census - 2003 Tabora Appendix II 135 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 6,347 6,074 6,735 2,317 0 16,906 Igunga 773 5,083 2,997 4,859 2,161 110 16,197 Uyui 0 1,635 3,874 1,647 701 106 811 Urambo 0 6,905 5,801 2,080 1,093 327 19,025 Sikonge 49 1,486 2,802 1,485 489 148 1,688 Tabora Urban 0 2,038 1,686 940 123 51 413 Total 822 23,493 23,233 17,746 6,885 742 55,040 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 4,465 1,754 750 1,113 0 4,123 Igunga 224 3,836 2,078 952 547 112 1,234 Uyui 0 100 208 701 301 106 0 Urambo 0 2,259 1,924 867 733 126 7,281 Sikonge 0 1,068 476 384 147 0 291 Tabora Urban 0 450 1,118 159 27 0 106 Total 224 12,178 7,559 3,813 2,868 344 13,035 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Nzega 0 1,908 119 0 150 0 0 Igunga 0 115 109 0 110 0 0 Uyui 0 0 0 0 0 203 0 Urambo 0 121 487 125 473 0 853 Sikonge 0 0 146 43 49 0 0 Tabora Urban 0 49 54 0 27 0 27 Total 0 2,193 915 168 809 203 880 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Igunga 0 0 110 0 0 0 0 Uyui 0 0 0 0 0 0 105 Urambo 120 0 0 0 0 0 0 Sikonge 0 0 0 0 0 50 50 Tabora Urb 0 0 27 0 0 0 0 Total 120 0 137 0 0 50 155 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Census - 2003 Tabora 136 Appendix II 137 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 138 Number % Number % Number % Less than 4 97,618 51 92,435 49 190,053 100 05 - 09 121,677 51 114,599 49 236,276 100 10 - 14 105,672 54 91,793 46 197,465 100 15 - 19 84,870 55 70,772 45 155,643 100 20 - 24 57,246 47 64,992 53 122,237 100 25 - 29 53,708 47 60,021 53 113,729 100 30 - 34 43,396 50 42,548 50 85,944 100 35 - 39 35,393 54 30,611 46 66,004 100 40 - 44 28,093 53 24,554 47 52,647 100 45 - 49 19,436 47 21,691 53 41,127 100 50 - 54 18,516 52 17,093 48 35,608 100 55 - 59 15,504 51 14,624 49 30,128 100 60 - 64 13,585 48 14,514 52 28,099 100 65 - 69 13,941 60 9,131 40 23,073 100 70 - 74 9,608 50 9,539 50 19,147 100 75 - 79 7,796 68 3,634 32 11,430 100 80 - 84 4,414 61 2,841 39 7,255 100 Above 85 2,338 53 2,097 47 4,435 100 Total 732,811 52 687,489 48 1,420,300 100 Number % Number % Number % Less than 4 97,618 13 92,435 13 190,053 13 05 - 09 121,677 17 114,599 17 236,276 17 10 - 14 105,672 14 91,793 13 197,465 14 15 - 19 84,870 12 70,772 10 155,643 11 20 - 24 57,246 8 64,992 9 122,237 9 25 - 29 53,708 7 60,021 9 113,729 8 30 - 34 43,396 6 42,548 6 85,944 6 35 - 39 35,393 5 30,611 4 66,004 5 40 - 44 28,093 4 24,554 4 52,647 4 45 - 49 19,436 3 21,691 3 41,127 3 50 - 54 18,516 3 17,093 2 35,608 3 55 - 59 15,504 2 14,624 2 30,128 2 60 - 64 13,585 2 14,514 2 28,099 2 65 - 69 13,941 2 9,131 1 23,073 2 70 - 74 9,608 1 9,539 1 19,147 1 75 - 79 7,796 1 3,634 1 11,430 1 80 - 84 4,414 1 2,841 0 7,255 1 Above 85 2,338 0 2,097 0 4,435 0 Total 732,811 100 687,489 100 1,420,300 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Census - 2003 Tabora Appendix II 139 Number % Number % Number % Nzega 187,171 54 158,195 46 345,366 100 Igunga 157,202 51 153,059 49 310,261 100 Uyui 135,903 51 133,076 49 268,979 100 Urambo 168,695 51 159,259 49 327,955 100 Sikonge 56,742 50 56,159 50 112,900 100 Tabora Urban 27,098 49 27,741 51 54,839 100 Total 732,811 52 687,489 48 1,420,300 100 Number % Number % Number % Number % Number % Nzega 134,146 42 11,184 4 136 0 170,905 54 316,371 100 Igunga 127,922 50 9,149 4 215 0 120,066 47 257,353 100 Uyui 111,264 47 9,758 4 300 0 112,963 48 234,284 100 Urambo 141,661 51 13,348 5 0 0 121,964 44 276,972 100 Sikonge 51,852 54 1,893 2 43 0 42,807 44 96,596 100 Tabora Urban 31,541 65 1,228 3 54 0 15,848 33 48,671 100 Total 598,385 49 46,560 4 748 0 584,554 48 1,230,247 100 Number % Number % Number % Number % Nzega 57,727 18 94,452 30 164,192 52 316,371 100 Igunga 55,993 22 84,604 33 116,756 45 257,353 100 Uyui 49,696 21 76,825 33 107,763 46 234,284 100 Urambo 66,043 24 97,841 35 113,088 41 276,972 100 Sikonge 16,951 18 39,365 41 40,280 42 96,596 100 Tabora Urban 12,700 26 20,449 42 15,521 32 48,671 100 Total 259,109 21 413,537 34 557,601 45 1,230,247 100 Number % Number % Number % Number % Number % Nzega 194,747 62 13,916 4 136 0 146 0 1,403 0 Igunga 104,449 41 23,567 9 338 0 222 0 910 0 Uyui 130,995 56 5,783 2 310 0 211 0 713 0 Urambo 164,093 59 5,094 2 1,001 0 222 0 1,052 0 Sikonge 61,918 64 3,991 4 0 0 0 0 390 0 Tabora Urban 20,136 41 1,943 4 199 0 0 0 627 1 Total 676,338 55 54,294 4 1,984 0 802 0 5,095 0 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Main Activity Crop/Seaweed Farming Livestock Keeping / Livestock Pastoralist Fishing Government / Parastatal 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 District School Attendancy Attending Completed Never Attended Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write Total 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District, 2002/03 Agricultural Year District Sex Male Female Total Tanzania Agriculture Census - 2003 Tabora Appendix II 140 Number % Number % Number % Number % Number % Nzega 1,691 1 1,028 0 272 0 1,027 0 299 0 Igunga 1,968 1 663 0 12,566 5 1,290 1 444 0 Uyui 2,786 1 1,622 1 5,083 2 2,472 1 184 0 Urambo 1,996 1 734 0 1,218 0 1,070 0 326 0 Sikonge 198 0 490 1 393 0 764 1 99 0 Tabora Urban 473 1 148 0 7,203 15 52 0 697 1 Total 9,112 1 4,684 0 26,734 2 6,676 1 2,049 0 Number % Number % Number % Number % Number % Number % Nzega 0 0 6,016 2 52,014 16 40,187 13 3,490 1 316,371 100 Igunga 116 0 9,482 4 52,575 20 48,089 19 675 0 257,353 100 Uyui 317 0 1,210 1 43,676 19 38,503 16 418 0 234,284 100 Urambo 126 0 1,314 0 61,673 22 32,377 12 4,675 2 276,972 100 Sikonge 0 0 197 0 15,397 16 11,847 12 913 1 96,596 100 Tabora Urban 26 0 77 0 11,757 24 5,172 11 160 0 48,671 100 Total 585 0 18,296 1 237,091 19 176,175 14 10,331 1 1,230,247 100 Number % Number % Number % Number % Number % Nzega 195,227 62 7,110 2 61,660 19 52,374 17 316,371 100 Igunga 114,990 45 7,672 3 79,772 31 54,919 21 257,353 100 Uyui 124,460 53 8,156 3 58,994 25 42,674 18 234,284 100 Urambo 161,836 58 5,255 2 64,371 23 45,511 16 276,972 100 Sikonge 62,408 65 3,901 4 14,186 15 16,101 17 96,596 100 Tabora Urban 19,269 40 5,663 12 16,694 34 7,045 14 48,671 100 Total 678,190 55 37,757 3 295,677 24 218,623 18 1,230,247 100 Total Main Activity 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activivty and District, 2002/03 Agricultural Year District Involvement in Farming Works Full- time on Farm Works Part- time on Farm Rarely Works on Farm Never Works on Farm Total Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Not Working & Unavailable Housemaker / Housewife Student Unable to Work / Too Old / Retired / Sick / Disabled Other Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District, 2002/03 Agricultural Year District Private - NGO / Mission / etc p y (Non Farmimg) p y (Non Farmimg) without p y Helper (Non Agriculture) Not Working & Available Main Activity Tanzania Agriculture Census - 2003 Tabora Appendix II 141 Number % Number % Number % Number % Number % Nzega 0 0 878 1 3,213 3 2,726 3 10,289 11 Igunga 224 0 228 0 1,132 1 1,466 2 6,476 8 Uyui 200 0 1,320 2 3,077 4 2,128 3 9,351 12 Urambo 1,099 1 600 1 2,600 3 4,069 4 11,318 12 Sikonge 50 0 434 1 1,263 3 1,444 4 4,012 10 Tabora Urban 27 0 523 3 670 3 973 5 2,446 12 Total 1,599 0 3,984 1 11,955 3 12,806 3 43,893 11 Number % Number % Number Number % Number % Nzega 2,483 3 2,555 3 68,074 72 708 1 574 1 Igunga 2,112 2 1,812 2 66,602 79 887 1 562 1 Uyui 1,921 2 2,937 4 50,751 66 1,536 2 103 0 Urambo 4,454 5 4,258 4 63,770 65 357 0 124 0 Sikonge 672 2 877 2 28,387 72 439 1 292 1 Tabora Urban 748 4 748 4 12,612 62 633 3 37 0 Total 12,389 3 13,186 3 290,195 70 4,560 1 1692 0 Number % Number % Number % Number % Number % Nzega 0 0 119 0 445 0 291 0 1,536 2 Igunga 0 0 0 0 109 0 109 0 973 1 Uyui 0 0 310 0 504 1 0 0 1,537 2 Urambo 0 0 0 0 349 0 375 0 1,845 2 Sikonge 148 0 95 0 244 1 46 0 913 2 Tabora Urban 27 0 52 0 103 1 25 0 416 2 Total 175 0 576 0 1756 0 847 0 7,220 2 Number % Number % Number % Number % Number % Nzega 0 0 147 0 124 0 290 0 94,452 100 Igunga 330 0 204 0 0 0 1,378 2 84,604 100 Uyui 208 0 0 0 0 0 942 1 76,825 100 Urambo 0 0 126 0 0 0 2,497 3 97,841 100 Sikonge 0 0 0 0 0 0 49 0 39,365 100 Tabora Urban 27 0 0 0 27 0 355 2 20,449 100 Total 566 0 476 0 151 0 5,511 1 413,537 100 District Education Level Education Level Education Level Education Level Form Six Training After Secondary University & Other Adult Education Total 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont….HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Cont…. HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District District Form Four Pre Form One Form One Form Two Form Three Standard Three Standard Four Standard Five Standard Six Standard Seven Standard Eight Training After District Under Standard One Standard One Standard Two Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 142 Number % Average Household Size Number % Average Household Size Number % Average Household Size Nzega 54327 83 6 11239 17 3 65566 100 5 Igunga 40038 89 7 5103 11 4 45141 100 7 Uyui 35609 86 7 5708 14 5 41318 100 7 Urambo 46691 86 6 7429 14 4 54120 100 6 Sikonge 16882 87 6 2631 13 3 19514 100 6 Tabora Urban 8549 83 6 1709 17 4 10258 100 5 Total 202097 86 6 33820 14 4 235917 100 6 Number % Number % Number % Number % Nzega 26,082.13 43 18,726.87 31 16,469.31 27 61,278.31 100 Igunga 23,285.70 55 10,971.36 26 8,205.83 19 42,462.89 100 Uyui 24,801.56 78 4,545.28 14 2,431.98 8 31,778.82 100 Urambo 28,648.95 59 12,552.49 26 6,983.64 14 48,185.08 100 Sikonge 8,709.02 60 3,459.75 24 2,240.38 16 14,409.15 100 Tabora Urb 5,925.18 67 2,028.46 23 831.00 9 8,784.64 100 Total 117,452.54 57 52,284.21 25 37,162.14 18 206,898.89 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Nzega 32,985 30,197 300 1,383 147 124 431 65,566 Igunga 21,763 22,085 340 450 94 0 409 45,141 Uyui 15,801 23,665 103 1,223 0 0 526 41,318 Urambo 18,012 32,915 124 1,516 126 0 1,427 54,120 Sikonge 6,018 12,610 98 740 0 0 49 19,514 Tabora Urban 3,190 6,393 13 412 0 27 224 10,258 Total 97,767 127,864 979 5,724 367 151 3,066 235,917 Mean Median Mode Mean Median Mode Mean Median Mode Nzega 47.39448261 45 60 54.28974015 54 50 48.57643073 48 60 Igunga 45.7464136 42 40 51.20685666 49 55 46.36371093 43 40 Uyui 45.40639926 42 30 52.5523658 52 70 46.39364742 44 30 Urambo 43.54515626 40 35 49.0763008 50 55 44.30442272 41 40 Sikonge 43.07979649 40 30 50.72944103 49 45 44.11132617 41 30 Tabora Urb 48.88210258 48 65 52.06704642 52 50 49.41278829 49 65 Total 45.5308498 42 30 51.99676421 52 70 46.45777754 44 30 District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households by Number of Household Members with Off-farm Income Generating Activities and District, 2002/03 Agricultural Year District Off farm income One Two More than Two Total 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year District Male Female Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 143 Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed (Number in Thousands) 151 159 158 175 174 209 Female Headed (Number in Thousands) 25 34 36 32 29 52 Total 176 193 194 207 203 261 Male Headed (Percentage) 86 82 81 84 86 80 Female Headed (Percentage) 14 18 19 16 14 20 Total 100 100 100 100 100 100 Male Female Total Male Female Total Male Female Total Nzega 28867 3715 32582 25460 7524 32985 54,327 11,239 65,566 Igunga 22287 1315 23602 17751 3788 21539 40,038 5,103 45,141 Uyui 24097 1522 25618 11513 4186 15699 35,609 5,708 41,318 Urambo 33820 2757 36577 12871 4672 17543 46,691 7,429 54,120 Sikonge 11838 1658 13496 5044 974 6018 16,882 2,631 19,514 Tabora Urban 6487 581 7068 2062 1128 3190 8,549 1,709 10,258 Total 127396 11548 138944 74701 22272 96973 202,097 33,820 235,917 3.14 Time Series of Male and Female Headed Households Know Don't Know Total Literacy District 3.15 Literacy Rates of Heads of Households by Sex and District Tanzania Agriculture Sample Census - 2003 Tabora 144 Appendix II 145 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 146 Households with Area Leased/Certif icate of Ownership % Households with Area Owned Under Customary Law % Households with Area Bought From Others % Households with Area Rented From Others % Households with Area Borrowed From Others % Households with Area Shared Croped From Others % Households with Area under Other Forms of Tenure % Total Number of Households Nzega 150 0 55,082 84 13,660 21 4,482 7 4,400 7 585 1 1,008 2 65,566 Igunga 1,437 3 33,952 75 10,720 24 10,393 23 4,139 9 2,265 5 1,344 3 45,141 Uyui 909 2 28,668 69 11,291 27 3,011 7 5,011 12 616 1 1,675 4 41,318 Urambo 1,546 3 39,267 73 11,302 21 3,413 6 6,455 12 477 1 2,961 5 54,120 Sikonge 341 2 16,462 84 2,398 12 830 4 1,762 9 99 1 615 3 19,514 Tabora Urban 674 7 8,346 81 2,016 20 577 6 630 6 113 1 244 2 10,258 Total 5,057 2 181,777 77 51,387 22 22,706 10 22,397 9 4,155 2 7,847 3 235,917 Area Leased/Certif icate of Ownership Area Owned Under Customary Law Area Bought From Others Area Rented From Others Area Borrowed From Others Area Shared Croped From Others Area under Other Forms of Tenure Total Nzega 213 116,954 22,792 2,620 2,539 179 611 145,908 Igunga 3,681 126,635 35,872 15,382 6,634 3,853 1,021 193,077 Uyui 5,193 130,792 37,005 4,406 5,781 1,470 3,447 188,093 Urambo 4,078 171,784 49,247 5,171 6,405 1,644 13,350 251,678 Sikonge 1,285 69,040 9,810 1,246 1,955 241 2,597 86,174 Tabora Urb 1,497 25,164 5,666 826 629 235 300 34,318 Total 15,946 640,369 160,392 29,651 23,943 7,622 21,326 899,248 Land Access 4.1 LAND ACCESS/OWNERSHIP: Number of Agricultural Households By Type of Land Ownership/Tenure and District, 2002/03 Agricultural Year 4.2 LAND ACCESS/OWNERSHIP: Area of Land by type of Ownership/Tenure (Hectare) and District, 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 147 LAND USE Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 148 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Nzega 51,560 39,574 7,994 1,898 5,295 124 9,862 738 676 882 3,284 15,156 65,566 Igunga 40,335 19,440 1,284 1,349 1,356 5,977 2,066 749 114 1,919 1,774 10,258 45,141 Uyui 31,741 27,979 5,696 1,933 2,707 3,479 8,536 3,283 822 1,320 3,557 19,013 41,318 Urambo 42,042 29,079 11,415 2,309 9,542 2,959 15,591 12,325 876 1,328 7,253 18,972 54,120 Sikonge 13,358 13,330 3,470 484 1,060 1,112 4,162 2,266 288 291 625 7,601 19,514 Tabora Urban 7,066 7,730 4,013 659 1,659 497 2,473 736 79 186 775 5,155 10,258 Total 186,102 137,132 33,871 8,631 21,619 14,147 42,690 20,096 2,855 5,927 17,268 76,155 235,917 Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Nzega 61,148 44,348 3,144 636 4,578 125 12,225 512 131 1,126 4,406 13,528 145,908 Igunga 113,001 27,521 327 2,970 4,315 16,095 3,319 1,592 46 5,710 4,851 13,330 193,077 Uyui 57,360 43,216 2,484 2,609 3,194 7,704 12,261 11,085 606 2,280 8,076 37,219 188,093 Urambo 73,930 36,474 5,904 2,636 10,490 6,589 25,353 41,471 2,241 688 13,910 31,968 251,655 Sikonge 24,826 22,518 1,310 414 1,652 2,012 5,930 7,130 188 388 1,433 18,373 86,174 Tabora Urban 6,053 8,716 2,009 871 1,688 739 2,928 1,283 24 361 1,087 8,560 34,318 Total 336,318 182,793 15,179 10,136 25,917 33,264 62,016 63,072 3,237 10,553 33,763 122,977 899,225 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year District Land Use Area Land Use District 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District during 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 149 Number % Number % Number % Number % Nzega 40,492 62 25,074 38 65,566 Nzega 40,042 61 25,524 39 65,566 Igunga 28,055 62 16,970 38 45,025 Igunga 21,242 47 23,783 53 45,025 Uyui 13,245 32 27,968 68 41,212 Uyui 27,506 67 13,706 33 41,212 Urambo 14,588 27 39,532 73 54,120 Urambo 36,872 68 17,248 32 54,120 Sikonge 6,808 35 12,656 65 19,464 Sikonge 13,666 70 5,799 30 19,464 Tabora Urban 3,372 33 6,861 67 10,233 Tabora Urban 7,819 76 2,413 24 10,233 Total 106,559 45 129,061 55 235,621 Total 147,147 62 88,474 38 235,621 Total Number % Number % Number Nzega 10,308 16 55,258 84 65,566 Igunga 2,223 5 42,802 95 45,025 Uyui 4,076 10 37,137 90 41,212 Urambo 4,245 8 49,875 92 54,120 Sikonge 2,827 15 16,637 85 19,464 Tabora Urban 1,009 10 9,224 90 10,233 Total 24,688 10 210,933 90 235,621 Total 5.4 LAND SUFFICIENCY: Number of Agricultural Households by Whether they Consider Having Sufficient Land for the Household and District during 2002/03 Agricultural Year Do you Consider that you have sufficient land for the Hh? District Yes No Total 5.3 LAND SUFFICIENCY: Number of Agricultural Households by Whether All Land Available to the Household Was Used and District, 2002/03 Agricultural Year Was all Land Available to the Hh Used During 2002/03? 5.5 LAND SUFFICIENCY: Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District, 2002/03 Agricultural Year District Yes No District Yes No Do any Female Members of the Hh own or have Tanzania Agriculture Sample Census - 2003 Tabora 150 Appendix II 151 ANNUAL CROP & VEGETABLE PRODUCTION - LONG RAIN SEASON Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 152 District Number of Households Planted Area (hectare Nzega 65,566 109,322 Igunga 45,141 142,453 Uyui 41,318 95,654 Urambo 54,120 114,863 Sikonge 19,514 52,716 Tabora Urban 10,258 17,606 Total 235,917 532,615 Number of Households Growing Crops Number of Households NOT Growing Crops Total Number of Crop Growing Households Number Number Number Nzega 65,428 138 65,566 Igunga 45,025 116 45,141 Uyui 41,212 105 41,318 Urambo 54,120 0 54,120 Sikonge 19,464 50 19,514 Tabora Urban 10,206 52 10,258 Total 235,456 461 235,917 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) By District - LONG RAINY SEASON District Long Rainy Season 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households Planting Crops By Season and District-LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 153 Planted area (ha) Quantity Harvested (tons) Yield (kg/ha) CEREALS 347455 222315 Maize 232860 143122 615 Paddy 65657 58661 893 Sorghum 46379 18959 409 Bulrush Millet 1545 700 453 Finger Millet 881 769 873 Wheat 33 15 468 Barley 100 89 889 ROOTS & TUBERS 31535 41380 Cassava 21391 28416 1328 Sweet Potatoes 9173 12351 1346 Irish Potatoes 723 329 455 Yams 248 283 1143 PULSES 25911 9659 Mung Beans 66 19 295 Beans 19331 7143 370 Cowpeas 1802 544 302 Green Gram 436 91 209 Chich Peas 682 437 640 Bambaranuts 3593 1424 396 OIL SEEDS & OIL NUTS 69862 31877 456 Sunflower 510 149 292 Simsim 548 94 172 Groundnuts 68730 31618 460 Soya Beans 75 16 211 FRUITS & VEGETABLES 2904 5847 Okra 21 31 1469 Radish 283 419 1480 Turmeric 0 0 0 Bitter Aubergine 97 85 872 Garlic 0 0 0 Onions 1507 2550 1692 Ginger 5 13 2371 Cabbage 48 55 1140 Tomatoes 827 2522 3048 Chillies 1 7 5558 Amaranths 60 98 1632 Pumpkins 38 53 1408 Cucumber 3 2 790 Egg Plant 12 11 865 CASH CROPS 54948 39604 Seaweed 0 0 0 Cotton 22409 9932 443 Tobacco 32490 29613 911 Pyrethrum 49 58 1186 Jute 0 1 3088 Total 532615 7.1c CROP AND VEGETABLE PRODUCTION: Area Planted (ha) and Quantity Harvested by Season and Crop for the Year 2002/03 Agriculture Year, Tabora Region Crop Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 154 Number of Households Planted area (ha) Area Planted per Household (ha/hh) CEREALS 353280 347455 Maize 229901 232860 1.0 Paddy 92037 65657 0.7 Sorghum 28207 46379 1.6 Bulrush Millet 554 1545 2.8 Finger Millet 2311 881 0.4 Wheat 221 33 0.1 Barley 49 100 2.0 ROOTS & TUBERS 77055 31535 Cassava 47395 21391 0.5 Sweet Potatoes 27635 9173 0.3 Irish Potatoes 1193 723 0.6 Yams 832 248 0.3 PULSES 79687 25911 Mung Beans 163 66 0.4 Beans 56189 19331 0.3 Cowpeas 7792 1802 0.2 Green Gram 2015 436 0.2 Chich Peas 948 682 0.7 Bambaranuts 12580 3593 0.3 OIL SEEDS & OIL NUTS 146161 69862 Sunflower 1525 510 0.3 Simsim 976 548 0.6 Groundnuts 143462 68730 0.5 Soya Beans 198 75 0.4 FRUITS & VEGETABLES 10815 2904 Okra 76 21 0.3 Radish 258 283 1.1 Bitter Aubergine 240 97 0.4 Onions 3250 1507 0.5 Ginger 27 5 0.2 Cabbage 246 48 0.2 Tomatoes 5471 827 0.2 Chillies 25 1 0.0 Amaranths 568 60 0.1 Pumpkins 476 38 0.1 Cucumber 26 3 0.1 Egg Plant 150 12 0.1 CASH CROPS 44413 54948 Cotton 13395 22409 1.7 Tobacco 30946 32490 1.0 Pyrethrum 48 49 1.0 Jute 24 0 0.0 Total 711411 532615 Long Rainy Season Crop 7.1d CROP AND VEGETABLE PRODUCTION: Number of Agriculture Household by Area Planted (ha) and Crop for the Agricuture Year 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 155 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 571 1,353 29,292 64,739 35,566 38,842 65,428 104,934 Igunga 901 1,875 37,154 129,795 6,970 10,112 45,025 141,782 Uyui 412 749 8,794 31,866 32,007 59,899 41,212 92,515 Urambo 126 115 4,950 15,290 49,043 90,783 54,120 106,188 Sikonge 589 983 3,041 18,060 15,835 31,873 19,464 50,916 Tabora Urban 51 42 670 1,888 9,485 13,391 10,206 15,321 Total 2,650 5,117 83,901 261,638 148,905 244,900 235,456 511,655 % 0.5 1.0 16.4 51.1 29.1 47.9 46.0 100.0 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 12,860 24,016 3,087 6,515 1,413 3,154 48,206 75,637 65,566 109,322 Igunga 3,998 8,517 460 1,792 862 3,136 39,705 129,008 45,025 142,453 Uyui 3,850 12,907 1,124 1,993 8,428 24,771 27,811 55,984 41,212 95,654 Urambo 3,102 9,090 1,364 1,549 13,908 38,531 35,746 65,694 54,120 114,863 Sikonge 1,943 8,234 47 66 5,258 15,973 12,217 28,443 19,464 52,716 Tabora Urb 1,228 2,843 160 258 2,197 4,618 6,622 9,888 10,206 17,606 Total 26,982 65,605 6,240 12,173 32,066 90,184 170,306 364,654 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 10,673 23,021 54,893 86,301 65,566 109,322 21.1 Igunga 3,227 8,425 41,799 134,028 45,025 142,453 5.9 Uyui 6,708 14,011 34,505 81,643 41,212 95,654 14.6 Urambo 12,546 24,666 41,574 90,197 54,120 114,863 21.5 Sikonge 2,540 11,910 16,924 40,805 19,464 52,716 22.6 Tabora Urban 3,009 6,457 7,197 11,149 10,206 17,606 36.7 Total 38,702 88,491 196,892 444,124 235,594 532,615 16.6 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 5,747 12,895 59,819 96,428 65,566 109,322 Igunga 6,710 32,343 38,315 110,111 45,025 142,453 Uyui 12,766 39,897 28,447 55,758 41,212 95,654 Urambo 18,095 52,083 36,025 62,780 54,120 114,863 Sikonge 6,670 23,218 12,795 29,498 19,464 52,716 Tabora Urb 3,939 8,474 6,267 9,133 10,206 17,606 Total 53,927 168,908 181,667 363,707 235,594 532,615 % of Area Planted Under Irrigation District Irrigation Use Households Using Irrigation 7.1h ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing and Planted Area By Insecticide Use and District for the 2002/03 Crop Year - LONG RAINY SEASON District Insecticide Use Households Using Pesticide Households Not Using Pesticide Total Households Not Using Irrigation Total District Mostly Farm Yard Mostly Compost Mostly Inorganic Fertilizer Use Total No Fertilizer Applied 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION:Number of Crop Growing Households and Planted Area By Irrigation Use and District for the 2002/03 Crop Year - LONG RAINY SEASON 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District for the 2002/03 Crop Year-LONG RAINY SEASON 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means of Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Tabora Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 156 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 601 1,350 64,965 107,973 65,566 109,322 Igunga 569 1,544 44,456 140,909 45,025 142,453 Uyui 726 1,882 40,486 93,772 41,212 95,654 Urambo 2,568 7,520 51,552 107,343 54,120 114,863 Sikonge 99 542 19,365 52,174 19,464 52,716 Tabora Urb 287 492 9,919 17,114 10,206 17,606 Total 4,850 13,330 230,744 519,285 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 900 3,249 64,666 106,073 65,566 109,322 Igunga 1,589 7,215 43,436 135,238 45,025 142,453 Uyui 1,565 4,017 39,648 91,637 41,212 95,654 Urambo 6,436 17,503 47,684 97,361 54,120 114,863 Sikonge 1,134 4,185 18,331 48,531 19,464 52,716 Tabora Urb 620 1,510 9,586 16,096 10,206 17,606 Total 12,244 37,680 223,350 494,935 235,594 532,615 No. of H/holds Planted Area No. of H/holds Planted Area No. of H/holds Planted Area Nzega 4,630 7,588 60,799 97,346 65,428 104,934 Igunga 3,815 17,066 41,210 124,716 45,025 141,782 Uyui 6,237 19,024 34,976 73,490 41,212 92,515 Urambo 12,950 31,224 41,170 74,964 54,120 106,188 Sikonge 3,057 10,548 16,407 40,368 19,464 50,916 Tabora Urban 1,788 2,675 8,418 12,646 10,206 15,321 Total 32,477 88,125 202,980 423,530 235,456 511,655 Number % Number % Nzega 27633 42 37933 58 65566 Igunga 21622 48 23519 52 45141 Uyui 21884 53 19434 47 41318 Urambo 43449 80 10671 20 54120 Sikonge 12147 62 7367 38 19514 Tabora Urban 4669 46 5589 54 10258 Total 131403 56 104514 44 235917 District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total 7.1k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON 7.1j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total 7.1i ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON District Herbicide Use Households Using Herbicide Households Not Using Herbicide Total 7.2a Number of Crop Producing Households Reporting Selling Agricultural Produce by District; 2003/04 Agriculture Year District Households that Sold Produce Households that Did not Sell Produce Total Number of Households Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 157 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area CEREALS 29743 303639 1124 5669 5594 122 345891 Maize 18,660 20,329 204,004 205,806 670 795 2,110 1,758 3,352 3,152 150 122 228,946 231,963 Paddy 5,347 5,607 77,445 53,189 256 73 4,889 3,708 3,656 2,442 0 . 91,592 65,020 Sorghum 3,034 3,807 24,805 42,268 114 231 108 44 0 . 0 . 28,060 46,349 Bulrush Millet 0 . 554 1,545 0 . 0 . 0 . 0 . 554 1,545 Finger Millet 0 . 1,702 697 125 25 484 159 0 . 0 . 2,311 881 Wheat 0 . 221 33 0 . 0 . 0 . 0 . 221 33 Barley 0 . 49 100 0 . 0 . 0 . 0 . 49 100 ROOTS & TUBERS 1,356 8,670 125 115 309 . 10,575 Cassava 0 . 1,429 431 0 . 0 . 0 . 0 . 1,429 431 Sweet Potatoes 4,038 1,274 21,780 7,397 232 103 222 90 1,362 309 0 . 27,635 9,173 Irish Potatoes 145 59 940 642 109 22 0 . 0 . 0 . 1,193 723 Yams 114 23 595 200 0 . 123 25 0 . 0 . 832 248 Cocoyam 0 . 0 . 0 . 0 . 0 . 0 . 0 . PULSES 5,899 2,397 71,672 22,533 267 69 1,198 696 624 195 0 . 79,661 25,889 Mung Beans 114 46 49 20 0 . 0 . 0 . 0 . 163 66 Beans 3,215 1,347 51,280 17,127 267 69 1,198 696 229 93 0 . 56,189 19,331 Cowpeas 969 305 6,728 1,465 0 . 0 . 95 32 0 . 7,792 1,802 Green Gram 476 129 1,539 307 0 . 0 . 0 . 0 . 2,015 436 Pigeon Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chich Peas 0 . 948 682 0 . 0 . 0 . 0 . 948 682 Bambaranuts 1,125 569 11,128 2,933 0 . 0 . 300 70 0 . 12,553 3,571 Field Peas 0 . 0 . 0 . 0 . 0 . 0 . 0 . OIL SEEDS & OIL NUTS 6,010 61,568 3 572 1,169 . 69,320 Sunflower 341 116 1,184 394 0 . 0 . 0 . 0 . 1,525 510 Simsim 244 94 732 453 0 . 0 . 0 . 0 . 976 548 Groundnuts 11,082 5,800 127,899 60,645 27 3 1,075 572 2,727 1,169 0 . 142,810 68,188 Soya Beans 0 . 198 75 0 . 0 . 0 . 0 . 198 75 Castor Seed 0 . 0 . 0 . 0 . 0 . 0 . 0 . FRUITS & VEGETABLES 439 2,407 21 22 15 . 2,904 Okra 50 20 27 1 0 . 0 . 0 . 0 . 76 21 Radish 149 261 0 . 0 . 109 22 0 . 0 . 258 283 Turmeric 0 . 0 . 0 . 0 . 0 . 0 . 0 . Bitter Aubergine 0 . 240 97 0 . 0 . 0 . 0 . 240 97 Garlic 0 . 0 . 0 . 0 . 0 . 0 . 0 . Onions 741 110 2,359 1,381 0 . 0 . 150 15 0 . 3,250 1,507 Ginger 0 . 27 5 0 . 0 . 0 . 0 . 27 5 Cabbage 0 . 246 48 0 . 0 . 0 . 0 . 246 48 Tomatoes 242 46 5,052 760 177 21 0 . 0 . 0 . 5,471 827 Spinnach 0 . 0 . 0 . 0 . 0 . 0 . 0 . Carrot 0 . 0 . 0 . 0 . 0 . 0 . 0 . Chillies 0 . 25 1 0 . 0 . 0 . 0 . 25 1 Amaranths 26 1 542 60 0 . 0 . 0 . 0 . 568 60 Pumpkins 27 1 449 37 0 . 0 . 0 . 0 . 476 38 Cucumber 0 . 26 3 0 . 0 . 0 . 0 . 26 3 Egg Plant 0 . 150 12 0 . 0 . 0 . 0 . 150 12 Water Mellon 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cauliflower 0 . 0 . 0 . 0 . 0 . 0 . 0 . CASH CROPS 6,929 47,710 181 67 20 . 54,908 Seaweed 0 . 0 . 0 . 0 . 0 . 0 . 0 . Cotton 1,909 2,252 11,262 19,951 114 139 110 67 0 . 0 . 13,395 22,409 Tobacco 3,970 4,677 26,772 27,710 106 43 0 . 50 20 0 . 30,897 32,450 Pyrethrum 0 . 48 49 0 . 0 . 0 . 0 . 48 49 Jute 0 . 24 0 0 . 0 . 0 . 0 . 24 0 Total 46,875 446,526 1,523 7,140 7,302 122 509,488 Total Crop 7.2b ANNUAL CROP & VEGETABLE PRODUCTION: Planted Area and Number of Crop Growing Households During the Long Rainy Season by Method of Land Clearing and Crop; 2002/03 Agriculture Year Land Clearing Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning No Land Clearing Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 158 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 64,428 52,986 36,466 0.7 Igunga 42,764 56,579 18,821 0.3 Uyui 40,700 46,418 28,017 0.6 Urambo 52,445 46,076 37,839 0.8 Sikonge 19,375 22,958 17,841 0.8 Tabora Urban 10,189 7,844 4,138 0.5 Total 229,901 232,860 143,122 0.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 36,736 25,289 22,484 0.9 Igunga 10,553 6,560 7,924 1.2 Uyui 17,627 14,587 13,713 0.9 Urambo 17,943 11,904 10,422 0.9 Sikonge 4,627 5,193 2,470 0.5 Tabora Urban 4,551 2,124 1,648 0.8 Total 92,037 65,657 58,661 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 2,176 1,347 712 0.5 Igunga 20,424 38,804 15,621 0.4 Uyui 2,899 3,162 1,660 0.5 Urambo 1,152 345 100 0.3 Sikonge 1,381 2,665 850 0.3 Tabora Urban 176 57 15 0.3 Total 28,207 46,379 18,959 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 97 39 29 0.7 Urambo 115 70 5 0.1 Sikonge 341 1,436 666 0.5 Tabora Urban 0 0 0 0.0 Total 554 1,545 700 0.5 7.2.5 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.3 Number of Households by Planted Area (ha) and Quantity of Sorghum Harvested (tons) by District and Crop-Long Rainy Season District Bulrush Millet 7.2.1 Number of Households by Planted Area (ha) and Quantity of Maize Harvested (tons) by District and Crop-Long Rainy Season Maize Sorghum Paddy District 7.2.2 Number of Households by Planted Area (ha) and Quantity of Paddy Harvested (tons) by District and Crop-Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 159 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 432 98 152 1.6 Igunga 0 0 0 0.0 Uyui 106 43 76 1.8 Urambo 1,726 722 513 0.7 Sikonge 48 19 28 1.5 Tabora Urban 0 0 0 0.0 Total 2,311 881 769 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 49 100 89 0.9 Tabora Urban 0 0 0 0.0 Total 49 100 89 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 119 12 0 0.0 Igunga 0 0 0 0.0 Uyui 102 21 15 0.7 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 221 33 15 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 10,904 4,388 4,024 0.9 Igunga 2,088 736 1,114 1.5 Uyui 7,176 3,316 3,115 0.9 Urambo 19,146 8,795 16,274 1.9 Sikonge 3,906 1,829 2,062 1.1 Tabora Urban 4,175 2,326 1,827 0.8 Total 47,395 21,391 28,416 1.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 1,602 673 490 0.7 Igunga 11,500 3,639 2,590 0.7 Uyui 4,234 1,440 3,715 2.6 Urambo 5,546 1,483 3,396 2.3 Sikonge 2,299 1,166 923 0.8 Tabora Urban 2,453 772 1,237 1.6 Total 27,635 9,173 12,351 1.3 District District 7.2.6 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.7 Number of Households by Planted Area (ha) and Quantity of Bulrush Millet Harvested (tons) by District and Crop-Long Rainy Season 7.2.8 Number of Households by Planted Area (ha) and Quantity of Cassava Harvested (tons) by District and Crop-Long Rainy Season Barley Wheat District 7.2.9 Number of Households by Planted Area (ha) and Quantity of Sweet Potatoes Harvested (tons) by District and Crop-Long Rainy Season District 7.2.4 Number of Households by Planted Area (ha) and Quantity of Finger Millet Harvested (tons) by District and Crop-Long Rainy Season Finger Millet Sweet Potatoes Cassava Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 160 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 444 112 81 0.7 Uyui 105 21 17 0.8 Urambo 618 579 218 0.4 Sikonge 0 0 0 0.0 Tabora Urban 27 11 13 1.2 Total 1,193 723 329 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 419 129 247 1.9 Igunga 114 23 3 0.1 Uyui 0 0 0 0.0 Urambo 123 25 0 0.0 Sikonge 149 60 25 0.4 Tabora Urban 27 11 9 0.8 Total 832 248 283 1.1 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 6612 1064 300 0.3 Igunga 451 319 493 1.5 Uyui 10854 3654 912 0.2 Urambo 26666 10308 4318 0.4 Sikonge 6669 2547 870 0.3 Tabora Urban 4936 1439 250 0.2 Total 56189 19331 7143 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 5487 1353 691 0.5 Igunga 1903 659 112 0.2 Uyui 2020 782 305 0.4 Urambo 1324 294 103 0.3 Sikonge 918 327 133 0.4 Tabora Urban 928 177 81 0.5 Total 12580 3593 1424 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 2,024 560 135 0.2 Igunga 1,306 187 62 0.3 Uyui 1,125 236 76 0.3 Urambo 1,852 444 169 0.4 Sikonge 713 245 55 0.2 Tabora Urban 772 130 47 0.4 Total 7,792 1,802 544 0.3 7.2.12 Number of Households by Planted Area (ha) and Quantity of Beans Harvested (tons) by District and Crop-Long Rainy Season Beans District District 7.2.14 Number of Households by Planted Area (ha) and Quantity of Cowpeas Harvested (tons) by District and Crop-Long Rainy Season District 7.2.11 Number of Households by Planted Area (ha) and Quantity of Irish Potatoes Harvested (tons) by District and Crop-Long Rainy Season Yams District District 7.2.13 Number of Households by Planted Area (ha) and Quantity of Bambaranuts Harvested (tons) by District and Crop-Long Rainy Season Bambaranuts 7.2.10 Number of Households by Planted Area (ha) and Quantity of Irish Potatoes Harvested (tons) by District and Crop-Long Rainy Season Irish Potatoes Cowpeas Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 161 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 150 16 9 0.6 Igunga 798 667 428 0.6 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 948 682 437 0.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 450 86 12 0.1 Uyui 407 85 10 0.1 Urambo 1101 258 68 0.3 Sikonge 43 1 1 0.6 Tabora Urb 13 6 1 0.1 Total 2015 436 91 0.2 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 114 46 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 49 20 19 1.0 Tabora Urban 0 0 0 0.0 Total 163 66 19 0.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 46,773 19,722 9,820 0.5 Igunga 19,892 10,391 2,972 0.3 Uyui 25,553 11,660 5,422 0.5 Urambo 32,741 17,001 10,343 0.6 Sikonge 12,635 7,863 2,298 0.3 Tabora Urban 5,869 2,093 763 0.4 Total 143,462 68,730 31,618 0.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 147 179 0 0.0 Igunga 0 0 0 0.0 Uyui 399 211 48 0.2 Urambo 244 94 35 0.4 Sikonge 186 64 12 0.2 Tabora Urban 0 0 0 0.0 Total 976 548 94 0.2 District 7.2.17 Number of Households by Planted Area (ha) and Quantity of Mung Beans Harvested (tons) by District and Crop-Long Rainy Season Mung Beans 7.2.16 Number of Households by Planted Area (ha) and Quantity of Green Gram Harvested (tons) by District and Crop-Long Rainy Season Green Gram District 7.2.18 Number of Households by Planted Area (ha) and Quantity of Groundnuts Harvested (tons) by District and Crop-Long Rainy Season Groundnuts District 7.2.15 Number of Households by Planted Area (ha) and Quantity of Chick Peas Harvested (tons) by District and Crop-Long Rainy Season Chich Peas District District 7.2.19 Number of Households by Planted Area (ha) and Quantity of Simsim Harvested (tons) by District and Crop-Long Rainy Season Simsim Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 162 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 998 328 74 0.2 Uyui 0 0 0 0.0 Urambo 252 77 45 0.6 Sikonge 194 77 23 0.3 Tabora Urban 80 28 6 0.2 Total 1525 510 149 0.3 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 198 75 16 0.2 Tabora Urban 0 0 0 0.0 Total 198 75 16 0.2 District District 7.2.20 Number of Households by Planted Area (ha) and Quantity of Sunflower Harvested (tons) by District and Crop-Long Rainy Season 7.2.21 Number of Households by Planted Area (ha) and Quantity of Soya Beans Harvested (tons) by District and Crop-Long Rainy Season Soya Beans Sunflower Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 163 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 747 151 298 2.0 Igunga 1488 1212 1446 1.2 Uyui 203 30 166 5.5 Urambo 598 72 591 8.2 Sikonge 0 0 0 0.0 Tabora Urban 215 41 49 1.2 Total 3250 1507 2550 1.7 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 743 120 304 2.5 Igunga 417 54 80 1.5 Uyui 1658 255 767 3.0 Urambo 1417 173 599 3.5 Sikonge 49 5 12 2.4 Tabora Urb 1187 221 760 3.4 Total 5471 827 2522 3.0 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 109 22 5 0.2 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 149 261 413 1.6 Tabora Urban 0 0 0 0.0 Total 258 283 419 1.5 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 116 47 65 1.4 Uyui 0 0 0 0.0 Urambo 124 50 20 0.4 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 240 97 85 0.9 District District Bitter Aubergine 7.2.22 Number of Households by Planted Area (ha) and Quantity of Onion Harvested (tons) by District and Crop-Long Rainy Season 7.2.23 Number of Households by Planted Area (ha) and Quantity of Tomatoes Harvested (tons) by District and Crop-Long Rainy Season 7.2.24 Number of Households by Planted Area (ha) and Quantity of Radish Harvested (tons) by District and Crop-Long Rainy Season 7.2.25 Number of Households by Planted Area (ha) and Quantity of Bitter Aubergine Harvested (tons) by District and Crop-Long Rainy Season Radish Onions Tomatoes District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 164 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 358 36 32 0.9 Sikonge 0 0 0 0.0 Tabora Urban 211 24 67 2.8 Total 568 60 98 1.6 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 206 42 46 1.1 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 40 7 9 1.4 Total 246 48 55 1.1 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 476 38 53 1.4 Total 476 38 53 1.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 50 20 30 1.5 Tabora Urban 27 1 1 1.2 Total 76 21 31 1.5 District District District Okra 7.2.26 Number of Households by Planted Area (ha) and Quantity of Amaranths Harvested (tons) by District and Crop-Long Rainy Season 7.2.27 Number of Households by Planted Area (ha) and Quantity of Cabbage Harvested (tons) by District and Crop-Long Rainy Season 7.2.28 Number of Households by Planted Area (ha) and Quantity of Pumpkins Harvested (tons) by District and Crop-Long Rainy Season District 7.2.29 Number of Households by Planted Area (ha) and Quantity of Okra Harvested (tons) by District and Crop-Long Rainy Season Pumpkins Cabbage Amaranths Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 165 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 150 12 11 0.9 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 150 12 11 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 27 5 13 2.4 Total 27 5 13 2.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 26 3 2 0.8 Total 26 3 2 0.8 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 0 0 0 0.0 Tabora Urban 25 1 7 5.6 Total 25 1 7 5.6 District Chillies 7.2.30 Number of Households by Planted Area (ha) and Quantity of Egg Plant Harvested (tons) by District and Crop-Long Rainy Season 7.2.31 Number of Households by Planted Area (ha) and Quantity of Ginger Harvested (tons) by District and Crop-Long Rainy Season 7.2.32 Number of Households by Planted Area (ha) and Quantity of Cucumber Harvested (tons) by District and Crop-Long Rainy Season 7.2.33 Number of Households by Planted Area (ha) and Quantity of Chillies Harvested (tons) by District and Crop-Long Rainy Season Cucumber Ginger Egg Plant District District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 166 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 1,101 1,078 889 0.8 Igunga 221 230 85 0.4 Uyui 8,363 9,635 8,286 0.9 Urambo 16,304 15,565 13,758 0.9 Sikonge 4,637 5,735 6,401 1.1 Tabora Urban 320 246 194 0.8 Total 30,946 32,490 29,613 0.9 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 260 145 61 0.4 Igunga 12,674 21,751 9,438 0.4 Uyui 95 19 28 1.5 Urambo 367 494 404 0.8 Sikonge 0 0 0 0.0 Tabora Urban 0 0 0 0.0 Total 13,395 22,409 9,932 0.4 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0 0 0.0 Igunga 0 0 0 0.0 Uyui 0 0 0 0.0 Urambo 0 0 0 0.0 Sikonge 48 49 58 1.2 Tabora Urban 0 0 0 0.0 Total 48 49 58 1.2 Number of Households Area Planted (ha) Quantity Harvested (tons) Yield (tons/ha) Nzega 0 0.0 0.0 0.0 Igunga 0 0.0 0.0 0.0 Uyui 0 0.0 0.0 0.0 Urambo 0 0.0 0.0 0.0 Sikonge 0 0.0 0.0 0.0 Tabora Urban 24 0.4 1.2 3.1 Total 24 0.4 1.2 3.1 District 7.2.37 Number of Households by Planted Area (ha) and Quantity of Jute Harvested (tons) by District and Crop-Long Rainy Season Jute District 7.2.36 Number of Households by Planted Area (ha) and Quantity of Pyrethrum Harvested (tons) by District and Crop-Long Rainy Season Pyrethrum District 7.2.35 Number of Households by Planted Area (ha) and Quantity of Cotton Harvested (tons) by District and Crop-Long Rainy Season Cotton District 7.2.34 Number of Households by Planted Area (ha) and Quantity of Tobacco Harvested (tons) by District and Crop-Long Rainy Season Tobacco Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 167 PERMANENT CROPS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 168 Area Planted (ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/Ha) Malay Apple 29 9 7 823 Sugarcane 0 0 . 0 Jack Fruit 7 0 . 0 Banana 92 52 42 822 Mango 649 105 5,320 50,756 Pawpaw 84 0 201 0 Orange 234 15 83 5,620 Guava 279 0 153 0 Lime/Lemon 56 0 3 0 Total 1,429 180 5,809 32,263 Sugarcane 47 23 145 6,175 Tamarin 5 0 . 0 Mango 268 9 165 17,883 Pawpaw 40 22 191 8,766 Guava 17 10 60 5,709 Total 377 65 560 8,633 Palm Oil 291 0 22 0 Coconut 1 0 2 0 Sugarcane 64 0 . 0 Jack Fruit 0 . 16 0 Banana 70 17 123 7,323 Avocado 0 . 59 0 Mango 432 129 4,028 31,123 Pawpaw 26 25 86 3,408 Orange 74 52 147 2,828 Guava 329 171 71 416 Total 1,285 394 4,555 11,552 Pigeon Pea 39 31 9 278 Malay Apple 0 0 126 0 Palm Oil 1,858 106 382 3,609 Coconut 53 0 . 0 Sugarcane 125 49 1,872 37,824 Jack Fruit 0 . 7 0 Banana 1,362 360 1,983 5,502 Mango 1,618 141 10,186 72,476 Pawpaw 516 80 406 5,078 Orange 119 78 2,175 27,886 Mandarine/Tangerine 51 . 6 0 Guava 28 28 16 589 Lime/Lemon 51 . 20 0 Total 5,820 873 17,188 19,686 Sugarcane 5 5 5 988 Jack Fruit 0 . 1 0 Banana 19 19 78 4,056 Mango 53 32 311 9,802 Pawpaw 0 4 2 497 Orange 8 8 40 5,055 Guava 0 0 3 0 Total 86 67 440 6,523 7.3.1 Production of Permanent Crops by Crop Type and District - Tabora Region Uyui Urambo Sikonge District/Crop Nzega Igunga Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 169 Palm Oil 10 12 12 992 Coconut 0 . 21 0 Sugarcane 62 40 1,527 37,975 Banana 56 42 390 9,343 Avocado 1 0 . 0 Mango 788 39 753 19,144 Pawpaw 4 66 40 613 Orange 6 8 192 22,609 Guava 3 2 57 26,391 Plums 0 . . 0 Lime/Lemon 3 17 186 10,999 Total 933 227 3,178 14,026 Pigeon Pea 39 31 9 278 Malay Apple 29 9 134 15,285 Palm Oil 2,158 118 416 3,538 Coconut 53 0 23 0 Sugarcane 303 118 3,549 30,031 Tamarin 5 0 . 0 Jack Fruit 7 0 24 0 Banana 1,600 490 2,616 5,341 Avocado 1 0 59 0 Mango 3,807 455 20,762 45,630 Pawpaw 670 197 926 4,712 Orange 440 161 2,637 16,352 Mandarine/Tangerine 51 . 6 0 Guava 656 211 360 1,706 Plums 0 . . 0 Lime/Lemon 110 17 209 12,325 Total 9,929 1,806 31,730 17,566 7.3.2: Area Planted by Crop Type - Tabora Region Crop Area Planted % Mango 3,807 38.3 Palm Oil 2,158 21.7 Banana 1,600 16.1 Pawpaw 670 6.7 Guava 656 6.6 Orange 440 4.4 Sugarcane 303 3.0 Lime/Lemon 110 1.1 Coconut 53 0.5 Mandarine/Tangerine 51 0.5 Pigeon Pea 39 0.4 Malay Apple 29 0.3 Jack Fruit 7 0.1 Tamarin 5 0.0 Avocado 1 0.0 Plums 0 0.0 Total 9,929 100.0 Cont…. Production of Permanent Crops by Crop Type and District - Tabora Region Tabora Urban Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 170 District Area Planted with Banana Total Area Planted (Ha) % of Total Area Planted Hh with Banana Average Planted Area per Household District Area Planted with Palm Oil Total Area Planted (Ha) % of Total Area Planted Hh with Palm Oil Average Planted Area per Household Urambo 1,618 120,683 1.3 3,953 0.4 Urambo 1,858 120,683 1.5 2,983 0.0 Tabora Urban 788 18,539 4.2 416 1.9 Uyui 291 110,751 0.3 419 0.0 Nzega 649 142,830 0.5 2,490 0.3 Tabora Urban 10 18,539 0.1 24 0.0 Uyui 432 110,751 0.4 1,221 0.4 Nzega 0 142,830 0.0 0 0.0 Igunga 268 96,939 0.3 669 0.4 Igunga 0 96,939 0.0 0 0.0 Sikonge 53 52,801 0.1 590 0.1 Sikonge 0 52,801 0.0 0 0.0 Total 3,807 542,544 0.7 9,338 0.4 Total 2,158 542,544 0.4 3,425 0.0 District Area Planted with Banana Oil Total Area Planted (Ha) % of Total Area Planted Hh with Banana Oil Average Planted Area per Household District Area Planted with Pawpaw Total Area Planted (Ha) % of Total Area Planted Hh with Pawpaw Average Planted Area per Household Urambo 1,362 120,683 1.1 3,767 0.4 Urambo 516 120,683 0.43 1,517 0.34 Nzega 92 142,830 0.1 601 0.2 Nzega 84 142,830 0.06 275 0.30 Uyui 70 110,751 0.1 404 0.2 Igunga 40 96,939 0.04 448 0.09 Tabora Urban 56 18,539 0.3 239 0.2 Uyui 26 110,751 0.02 400 0.06 Sikonge 19 52,801 0.0 47 0.4 Tabora Urban 4 18,539 0.02 105 0.04 Igunga 0 96,939 0.0 0 0.0 Sikonge 0 52,801 0.00 0 0.00 Total 1,600 542,544 0.3 5,058 0.3 Total 670 542,544 0.12 2,745 0.24 BANANA PAWPAW 7.3.3 Total Area Planted with Mango by District - Tabora Region 7.3.6 Total Area Planted with Pawpaw by District - Tabora Region 7.3.4 Total Area Planted with Palm Oil by District - Tabora Region 7.3.5 Total Area Planted with Banana by District - Tabora Region MANGO PALM OIL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 171 Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Pigeon Pea 0 0 0 39 39 Malay Apple 0 0 0 29 29 Palm Oil 1,282 84 0 782 2,148 Coconut 51 0 0 2 53 Sugarcane 53 8 13 230 303 Tamarin 0 0 0 5 5 Jack Fruit 7 0 0 0 7 Banana 911 157 0 531 1,600 Avocado 0 0 0 1 1 Mango 998 170 1 2,638 3,807 Pawpaw 479 56 0 110 645 Orange 72 176 43 149 440 Mandarine/Tangerine 51 0 0 0 51 Guava 12 56 0 588 656 Plums 0 0 0 0 0 Lime/Lemon 51 57 0 2 110 Total 3,968 764 57 5,106 9,895 Crop Mostly Farm Yard Manure Total % Jack Fruit 7 7 100.0 Mandarine/Tangerine 51 51 100.0 Coconut 51 53 96.0 Pawpaw 479 645 74.3 Palm Oil 1,282 2,148 59.7 Banana 911 1,600 57.0 Lime/Lemon 51 110 46.5 Mango 998 3,807 26.2 Sugarcane 53 303 17.4 Orange 72 440 16.3 Guava 12 656 1.9 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Tamarin 0 5 0.0 Avocado 0 1 0.0 Plums 0 0 0.0 Total 3,968 9,895 40.1 7.3.7 Planted Area with Fertiliser by Fertiliser Type and Crop - Tabora Region Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Fertilizer Use Crop Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 172 Crops Mostly Inorganic Fertilizer Total % Orange 43 440 9.9 Sugarcane 13 303 4.1 Mango 1 3,807 0.0 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Palm Oil 0 2,148 0.0 Coconut 0 53 0.0 Tamarin 0 5 0.0 Jack Fruit 0 7 0.0 Banana 0 1,600 0.0 Avocado 0 1 0.0 Pawpaw 0 645 0.0 Mandarine/Tangerine 0 51 0.0 Guava 0 656 0.0 Plums 0 0 0.0 Lime/Lemon 0 110 0.0 Total 57 9,895 0.6 Crops Mostly Compost Total % Lime/Lemon 57 110 51.6 Orange 176 440 40.1 Banana 157 1,600 9.8 Pawpaw 56 645 8.6 Guava 56 656 8.5 Mango 170 3,807 4.5 Palm Oil 84 2,148 3.9 Sugarcane 8 303 2.5 Pigeon Pea 0 39 0.0 Malay Apple 0 29 0.0 Coconut 0 53 0.0 Tamarin 0 5 0.0 Jack Fruit 0 7 0.0 Avocado 0 1 0.0 Mandarine/Tangerine 0 51 0.0 Plums 0 0 0.0 Total 764 9,895 7.7 Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Cont….Planted Area with Fertiliser by Fertilizer Type - Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 173 AGROPROCESSING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 174 Number % Number % Number % Nzega 63,856 97 1,710 3 65,566 100 Igunga 39,049 87 6,093 13 45,141 100 Uyui 39,991 97 1,326 3 41,318 100 Urambo 51,694 96 2,426 4 54,120 100 Sikonge 19,273 99 241 1 19,514 100 Tabora Urban 10,032 98 226 2 10,258 100 Total 223,896 95 12,021 5 235,917 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader Others By Factory Total Nzega 6,670 4,605 52,292 138 150 0 0 63,856 Igunga 2,858 215 35,432 0 432 0 110 39,049 Uyui 3,951 1,210 34,831 0 0 0 0 39,991 Urambo 4,805 1,996 44,893 0 0 0 0 51,694 Sikonge 2,817 835 15,474 147 0 0 0 19,273 Tabora Urban 526 169 9,231 26 27 54 0 10,032 Total 21,628 9,031 192,153 311 609 54 110 223,896 % 9.66 4.03 85.82 0.14 0.27 0.02 0.05 100.00 Crops On Farm by Hand On Farm by Machine By Neighbour Machine By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 14,399 9,146 9,146 311 495 0 54 0 33,552 Paddy 25,839 1,549 49,294 26 0 0 0 0 76,708 Sorghum 585 617 20,577 0 0 0 0 0 21,779 Bulrush Millet 0 50 313 0 0 0 0 0 363 Finger Millet 0 123 364 0 0 0 0 0 486 Cassava 4,167 224 10,599 0 0 150 50 0 15,190 Sweet Potatoes 270 0 0 0 0 0 0 0 270 Beans 427 0 50 0 0 0 0 0 477 Cowpeas 594 0 0 0 0 0 0 0 594 Chick Peas 112 0 0 0 0 0 0 0 112 Green Gram 0 0 98 0 0 0 0 0 98 Bambaranut 987 150 0 0 150 0 0 1,288 Groundnut 100,253 599 3,492 126 717 0 616 0 105,802 Sunflower 0 49 101 0 0 0 0 110 260 Simsim 49 0 0 0 0 0 0 0 49 Tobacco 0 0 0 0 0 0 0 27 27 Pawpaw 102 0 0 0 0 0 0 0 102 Orange 102 0 0 0 0 0 0 0 102 Oil Palm 1,682 0 230 0 0 0 0 0 1,912 8.0a: AGROPROCESSING: Number of Crops Growing Households Reported to have Processed Farm Products by District; 2002/03 Agriculture Year District Households That Processed Product Households That Did Not Process Product Total 8.0b AGRO PROCESSING: Number of Crop Growing Households by Method Processing and District; 2002/03 Agriculture Yearof Farm Products Produced During 2002/03 Agriculture Year District Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agriculture Year by Location and Crop, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 175 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Other Total Maize 211,896 54 50 1,141 268 0 213,408 Paddy 74,695 121 685 471 498 237 76,708 Sorghum 21,779 0 0 0 0 0 21,779 Bulrush Millet 363 0 0 0 0 0 363 Finger Millet 486 0 0 0 0 0 486 Cassava 14,940 0 249 0 0 0 15,190 Sweet Potatoes 270 0 0 0 0 0 270 Beans 477 0 0 0 0 0 477 Cowpeas 594 0 0 0 0 0 594 Green Gram 98 0 0 0 0 0 98 Chick Peas 112 0 0 0 0 0 112 Bambaranut 987 0 300 0 0 0 1,288 Sunflower 211 0 49 0 0 0 260 Simsim 49 0 0 0 0 0 49 Groundnut 104,419 161 671 0 525 27 105,802 Oil Palm 1,794 0 118 0 0 0 1,912 Tobacco 0 0 27 0 0 0 27 Pawpaw 102 0 0 0 0 0 102 Orange 102 0 0 0 0 0 102 Total 433,375 336 2,149 1,613 1,291 263 439,027 Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 2,455 744 99 231 114 173 1,245 4,544 203,803 213,408 Paddy 2,200 1,329 126 27 0 250 1,475 1,684 69,617 76,708 Sorghum 232 114 0 0 0 0 0 1,175 20,259 21,779 Bulrush Millet 0 0 0 0 0 0 0 0 363 363 Finger Millet 0 0 0 0 0 0 0 0 486 486 Cassava 27 401 0 0 0 0 125 198 14,439 15,190 Sweet Potatoes 0 0 0 0 0 0 0 0 270 270 Beans 0 0 0 0 0 0 0 0 477 477 Cowpeas 0 0 0 0 0 0 0 0 594 594 Green Gram 0 0 0 0 0 0 0 0 98 98 Chick Peas 0 0 0 0 0 0 0 0 112 112 Bambaranut 0 0 0 0 0 0 0 0 1,288 1,288 Sunflower 49 0 0 0 0 0 0 0 211 260 Simsim 0 0 0 0 0 0 0 0 49 49 Groundnut 945 641 0 228 0 0 539 2,945 100,504 105,802 Oil Palm 469 0 0 0 0 0 0 0 1,443 1,912 Tobacco 0 0 0 0 27 0 0 0 0 27 Pawpaw 0 0 0 0 0 0 102 0 0 102 Orange 0 0 0 0 0 0 102 0 0 102 Total 6,375 3,229 225 485 141 423 3,588 10,547 414,013 439,027 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Use of Product and Crop, Tabora Region 8.1.c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2003/04 Agricultural Year By Location of Sale of Product and Crop, Tabora Region Product Use Crop Where Sold Crops Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 176 Flour / Meal Grain Oil Juice Pulp Rubber Total Nzega 56,063 7,210 147 149 286 0 63,856 Igunga 35,784 2,256 110 0 789 110 39,049 Uyui 36,402 3,189 97 0 303 0 39,991 Urambo 46,450 4,260 621 126 115 121 51,694 Sikonge 17,045 1,550 147 0 532 0 19,273 Tabora Urban 9,421 505 27 0 54 27 10,032 Total 201,164 18,970 1,148 276 2,079 258 223,896 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumptio n Did Not Use Total Nzega 62,988 0 300 300 268 63,856 Igunga 38,401 0 230 418 0 39,049 Uyui 39,889 0 0 102 0 39,991 Urambo 51,449 0 0 245 0 51,694 Sikonge 19,126 0 98 49 0 19,273 Tabora Urban 9,952 54 0 27 0 10,032 Total 221,805 54 628 1,141 268 223,896 Neighbours Local Market / Trade Store Secondary Market Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Nzega 451 899 0 0 0 0 748 0 61,758 63,856 Igunga 688 116 0 0 114 0 232 1,837 36,062 39,049 Uyui 106 0 0 204 0 0 0 794 38,888 39,991 Urambo 1,273 126 0 0 0 124 0 0 50,171 51,694 Sikonge 340 0 99 0 0 49 0 2,322 16,463 19,273 Tabora Urban 317 54 0 27 0 0 13 24 9,598 10,032 Total 3,175 1,194 99 231 114 173 993 4,976 212,941 223,896 Bran Cake Husk Juice Pulp Oil Shell No by-product Other Total Nzega 49,205 0 7,851 0 294 147 0 6,360 0 63,856 Igunga 5,718 110 4,178 0 570 0 229 28,244 0 39,049 Uyui 18,887 106 7,022 0 499 0 0 13,380 97 39,991 Urambo 33,547 464 3,040 123 0 118 334 14,069 0 51,694 Sikonge 11,583 343 978 0 97 0 243 6,029 0 19,273 Tabora Urban 7,697 0 931 0 24 0 27 1,354 0 10,032 Total 126,638 1,023 23,999 123 1,483 265 832 69,436 97 223,896 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year - Tabora Region District Main Product 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District During 2002/03 Agriculture Year, Tanga Region District Product Use 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year - Tabora Region District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By Type of By-Product and District During 2002/03 Agriculture Year, Tabora Region District By Product Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 177 MARKETING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 178 Number % Number % Nzega 27,633 42 37,933 58 65,566 Igunga 21,622 48 23,519 52 45,141 Uyui 21,884 53 19,434 47 41,318 Urambo 43,449 80 10,671 20 54,120 Sikonge 12,147 62 7,367 38 19,514 Tabora Urban 4,669 46 5,589 54 10,258 Total 131,403 56 104,514 44 235,917 Open Market Price Too Low No Transport Transport Cost Too High No Buyer Market too Far Farmers Association Problems Co- operative Problems Government Regulatory Board Problems Lack of Market Information Other Not applicable Total Nzega 10,860 1,332 741 0 1,030 0 0 0 0 0 13,670 27,633 Igunga 2,859 116 0 0 444 116 114 0 319 0 17,655 21,622 Uyui 6,769 512 410 100 1,136 0 0 0 102 0 12,854 21,884 Urambo 15,504 1,481 980 458 2,252 0 0 124 248 121 22,282 43,449 Sikonge 4,849 344 244 49 494 50 0 0 96 0 6,022 12,147 Tabora Urban 596 40 40 27 210 0 0 25 0 0 3,730 4,669 Total 41,437 3,825 2,415 634 5,565 165 114 149 764 121 76,214 131,403 District Open Market Price Too Low No Transport Transport Cost Too High No Buyer Market too Far Farmers Association Problems Co- operative Problems Government Regulatory Board Problems Lack of Market Information Other Not applicable Total Nzega 39.30 4.82 2.68 0.00 3.73 0.00 0.00 0.00 0.00 0.00 49.47 100.00 Igunga 13.22 0.54 0.00 0.00 2.05 0.54 0.53 0.00 1.47 0.00 81.65 100.00 Uyui 30.93 2.34 1.88 0.46 5.19 0.00 0.00 0.00 0.47 0.00 58.74 100.00 Urambo 35.68 3.41 2.25 1.05 5.18 0.00 0.00 0.29 0.57 0.28 51.28 100.00 Sikonge 39.92 2.83 2.01 0.41 4.06 0.41 0.00 0.00 0.79 0.00 49.58 100.00 Tabora Urban 12.77 0.86 0.85 0.57 4.50 0.00 0.00 0.54 0.00 0.00 79.89 100.00 Total 31.53 2.91 1.84 0.48 4.24 0.13 0.09 0.11 0.58 0.09 58.00 100.00 District Households that Sold Households that Did not Sell 10.1 MARETING: Number of Crop Growing Households Reported to have Sold Agricultural Produce by District During 2003/04 Agriculture Year, Tabora Region Total Number of Household 10.3 Proportion of Households who Reported Main Reason for Not Selling their Crops by District During 2002/03 Agriculture Year 10.2 MARKETING: Number of Households who Reported Main Reason for Not Selling their Crops by District during 2002/03 Agriculture Year, Tabora Region District Main Problem Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 179 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 180 Total Number of Households Number of Households % Number of Households % Number Nzega 2,938 4 62,628 96 65,566 Igunga 3,350 7 41,791 93 45,141 Uyui 3,310 8 38,008 92 41,318 Urambo 4,701 9 49,419 91 54,120 Sikonge 1,479 8 18,034 92 19,514 Tabora Urban 1,403 14 8,855 86 10,258 Total 17,181 7 218,736 93 235,917 District Irrigatable Area (ha) Irrigated Land (ha) % Nzega 1,641 1,241 76 Igunga 2,865 2,782 97 Uyui 1,977 1,709 86 Urambo 1,607 810 50 Sikonge 740 531 72 Tabora Urban 541 408 75 Total 9,371 7,480 80 River Dam Well Borehole Canal Total Nzega 0 1,798 570 0 571 2,938 Igunga 966 2,037 346 0 0 3,350 Uyui 106 2,607 597 0 0 3,310 Urambo 0 125 3,971 605 0 4,701 Sikonge 97 93 979 50 261 1,479 Tabora Urban 27 758 591 0 27 1,403 Total 1,196 7,418 7,054 654 859 17,181 Gravity Hand Bucket Hand Pump Motor Pump Other Total Nzega 1,622 1,316 0 0 0 2,938 Igunga 2,445 904 0 0 0 3,350 Uyui 407 2,797 0 0 105 3,310 Urambo 125 4,576 0 0 0 4,701 Sikonge 309 1,171 0 0 0 1,479 Tabora Urban 79 1,063 46 26 188 1,403 Total 4,987 11,828 46 26 293 17,181 11.4 IRRIGATION: Number of Agriculture Households by Method Used to obtain Water and District During 2002/03 Agriculture Year District Method of Obtaining Water 11.2 IRRIGATION: Area (ha) of Irrigatable and NON Irrigated Land by District During 2002/03 Agriculture Year 11.3 IRRIGATION: Number of Agriculture Households Using Irrigation By Source of Irrigation Water by District During the 2003/04 Agricultural Year District Source of Irrigation Water District Household Practicing Irrigation Household Not Practicing Irrigation 11.1 IRRIGATION: Number and Percent of Households Reporting Use of Irrigation During 2002/03 Agriculture Year by District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 181 Flood Sprinkler Water Hose Bucket / Watering Can Total Nzega 1,622 0 0 1,316 2,938 Igunga 2,775 114 0 461 3,350 Uyui 618 0 0 2,692 3,310 Urambo 378 0 0 4,323 4,701 Sikonge 507 195 0 778 1,479 Tabora Urban 27 25 99 1,252 1,403 Total 5,926 334 99 10,821 17,181 Total Number of Household Number % Number % Number Nzega 1,041 2 64,525 98 65,566 Igunga 115 0 45,026 100 45,141 Uyui 2,209 5 39,109 95 41,318 Urambo 965 2 53,155 98 54,120 Sikonge 343 2 19,171 98 19,514 Tabora Urban 727 7 9,531 93 10,258 Total 5,399 2 230,518 98 235,917 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Nzega 0 3,857 0 0 0 0 281 901 5,039 Igunga 0 230 0 0 0 0 0 0 230 Uyui 0 619 317 0 3,058 1,372 204 3,679 9,248 Urambo 0 7,034 0 385 193 0 0 0 7,612 Sikonge 99 1,501 0 0 446 1,239 0 0 3,286 Tabora Urban 455 1,068 0 0 520 646 487 26 3,202 Total 554 14,309 317 385 4,217 3,258 971 4,606 28,616 11.7 EROSION CONTROL: Number of Erosion Control Harvesting Structures By Type and District as of 2002/03 Agriculture Year District Type of Erosion Control District Method of Field Application District Have facility Does Not Have Facility Presence of Erosion Control/Water Harvesting Facilities 11.6: IRRIGATION: Number of Households With Erosion Control/Water Harvesting Facilities on their Land By District 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agriculture Year Tanzania Agriculture Sample Census - 2003 Tabora 182 Appendix II 183 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 184 No. of Households % No. of Households % Nzega 2,887 4 62,679 96 65,566 Igunga 1,206 3 43,935 97 45,141 Uyui 11,025 27 30,293 73 41,318 Urambo 21,354 39 32,766 61 54,120 Sikonge 6,773 35 12,741 65 19,514 Tabora Urban 3,042 30 7,216 70 10,258 Total 46,287 20 189,630 80 235,917 No. of Households % No. of Households % Nzega 29,333 45 36,233 55 65,566 Igunga 12,244 27 32,897 73 45,141 Uyui 8,020 19 33,297 81 41,318 Urambo 8,576 16 45,545 84 54,120 Sikonge 4,202 22 15,312 78 19,514 Tabora Urban 2,903 28 7,355 72 10,258 Total 65,279 28 170,638 72 235,917 No. of Households % No. of Households % Nzega 6,580 10 58,986 90 65,566 Igunga 459 1 44,682 99 45,141 Uyui 2,973 7 38,345 93 41,318 Urambo 4,696 9 49,425 91 54,120 Sikonge 295 2 19,219 98 19,514 Tabora Urb 365 4 9,893 96 10,258 Total 15,368 7 220,549 93 235,917 No. of Households % No. of Households % Nzega 4,294 7 61,272 93 65,566 Igunga 6,162 14 38,979 86 45,141 Uyui 11,823 29 29,494 71 41,318 Urambo 16,130 30 37,990 70 54,120 Sikonge 6,095 31 13,419 69 19,514 Tabora Urban 3,355 33 6,903 67 10,258 Total 47,859 20 188,057 80 235,917 District Using Insecticide/Fungicides NOT Using Insecticide/Fungicides Table 12.1.4 ACCESS TO INPUTS: Number of Agricultural Households Using Insecticide/Fungicides by District, 2002/03 Agricultural Year Total District Using Compost Not Using Compost Table 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District, 2002/03 Agricultural Year Total District Using Farm Yard Manure NOT Using Farm Yard Manure Total Table 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year Total Number of Crop Growing Households Table 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District, 2002/03 Agricultural Year District Using Chemical Fertilizers NOT Using Chemical Fertilizers Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 185 No. of Households % No. of Households % Nzega 149 0 65,417 100 65,566 Igunga 345 1 44,797 99 45,141 Uyui 306 1 41,012 99 41,318 Urambo 973 2 53,148 98 54,120 Sikonge 248 1 19,266 99 19,514 Tabora Urban 37 0 10,221 100 10,258 Total 2,056 1 233,861 99 235,917 No. of Households % No. of Households % Nzega 5,774 9 59,792 91 65,566 Igunga 10,971 24 34,170 76 45,141 Uyui 6,679 16 34,639 84 41,318 Urambo 16,300 30 37,820 70 54,120 Sikonge 3,730 19 15,784 81 19,514 Tabora Urban 2,253 22 8,005 78 10,258 Total 45,706 19 190,210 81 235,917 District Using Improved Seeds NOT Using Improved Seeds Table 12.1.6 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year Total District Using Herbicides NOT Using Herbicides Table 12.1.5 ACCESS TO INPUTS: Number of Agricultural Households Using Herbicides by District, 2002/03 Agricultural Year Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 186 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 0 0 543 1 1,922 3 0 0 0 0 272 0 0 0 0 0 150 0 62,679 96 65,566 Igunga 106 0 0 0 1,100 2 0 0 0 0 0 0 0 0 0 0 0 0 43,935 97 45,141 Uyui 7,630 18 211 1 2,977 7 0 0 0 0 0 0 0 0 102 0 106 0 30,293 73 41,318 Urambo 14,360 27 1,099 2 5,661 10 109 0 0 0 0 0 0 0 0 0 126 0 32,766 61 54,120 Sikonge 4,288 22 343 2 1,205 6 0 0 49 0 149 1 0 0 0 0 739 4 12,741 65 19,514 Tabora Urban 134 1 99 1 2,732 27 0 0 0 0 0 0 26 0 26 0 25 0 7,216 70 10,258 Total 26,518 11 2,296 1 15,595 7 109 0 49 0 420 0 26 0 128 0 1,146 0 189,630 80 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 150 0 149 0 150 0 0 0 0 0 0 0 23,679 36 5,055 8 150 0 36,233 55 65,566 Igunga 0 0 114 0 204 0 0 0 114 0 109 0 6,932 15 4,772 11 0 0 32,897 73 45,141 Uyui 0 0 0 0 106 0 196 0 98 0 0 0 5,797 14 1,718 4 106 0 33,297 81 41,318 Urambo 0 0 0 0 126 0 0 0 124 0 0 0 4,916 9 1,966 4 1,443 3 45,545 84 54,120 Sikonge 98 1 0 0 0 0 0 0 0 0 740 4 2,727 14 587 3 50 0 15,312 78 19,514 Tabora Urban 53 1 0 0 53 1 27 0 27 0 0 0 1,438 14 1,281 12 24 0 7,355 72 10,258 Total 302 0 262 0 639 0 223 0 362 0 849 0 45,489 19 15,380 7 1,772 1 170,638 72 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 149 0 149 0 0 0 0 0 0 0 0 0 5,989 9 294 0 58,986 90 65,566 Igunga 0 0 0 0 0 0 0 0 116 0 0 0 344 1 0 0 44,682 99 45,141 Uyui 1,354 3 98 0 104 0 98 0 0 0 0 0 1,221 3 98 0 38,345 93 41,318 Urambo 0 0 124 0 0 0 0 0 236 0 0 0 4,335 8 0 0 49,425 91 54,120 Sikonge 0 0 0 0 0 0 0 0 0 0 99 1 196 1 0 0 19,219 98 19,514 Tabora Urban 0 0 0 0 0 0 27 0 0 0 0 0 292 3 46 0 9,893 96 10,258 Total 1,503 1 371 0 104 0 125 0 352 0 99 0 12,377 5 438 0 220,549 93 235,917 Table 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year Table 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Development Project Crop Buyers Large Scale Farm Neighbour Other Not applicable Total Development Project Crop Buyers Large Scale Farm Locally Produced by Household District Co-operative Local Farmers Group Local Market / Trade Store Neighbour Not applicable Total Locally Produced by Household Neighbour Not applicable Total Table 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households by Source of COMPOST Manure by District, 2002/03 Agricultural Year District Co-operative Crop Buyers Large Scale Farm Locally Produced by Household Local Farmers Group Local Market / Trade Store Secondary Market Development Project Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 187 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 124 0 543 1 3,055 5 150 0 150 0 272 0 0 0 0 0 0 0 61,272 93 65,566 Igunga 3,992 9 115 0 1,825 4 114 0 0 0 0 0 0 0 0 0 116 0 38,979 86 45,141 Uyui 7,418 18 211 1 3,383 8 193 0 0 0 197 0 0 0 105 0 317 1 29,494 71 41,318 Urambo 11,340 21 730 1 3,187 6 124 0 0 0 124 0 0 0 126 0 499 1 37,990 70 54,120 Sikonge 3,361 17 294 2 1,369 7 50 0 49 0 246 1 0 0 47 0 678 3 13,419 69 19,514 Tabora Urban 161 2 99 1 2,939 29 26 0 0 0 53 1 26 0 51 0 0 0 6,903 67 10,258 Total 26,395 11 1,993 1 15,758 7 657 0 200 0 891 0 26 0 330 0 1,610 1 188,057 80 235,917 Number % Number % Number % Number % Number % Number % Number % Nzega 0 0 0 0 149 0 0 0 0 0 0 0 65,417 100 65,566 Igunga 0 0 0 0 345 1 0 0 0 0 0 0 44,797 99 45,141 Uyui 0 0 105 0 102 0 98 0 0 0 0 0 41,012 99 41,318 Urambo 864 2 0 0 0 0 0 0 109 0 0 0 53,148 98 54,120 Sikonge 149 1 50 0 50 0 0 0 0 0 0 0 19,266 99 19,514 Tabora Urban 0 0 0 0 17 0 0 0 0 0 20 0 10,221 100 10,258 Total 1,013 0 155 0 662 0 98 0 109 0 20 0 233,861 99 235,917 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Nzega 124 0 282 0 4,374 7 0 0 721 1 136 0 0 0 138 0 0 0 59,792 91 65,566 Igunga 8,632 19 223 0 1,086 2 116 0 0 0 340 1 115 0 459 1 0 0 34,170 76 45,141 Uyui 4,072 10 628 2 1,662 4 0 0 0 0 317 1 0 0 0 0 0 0 34,639 84 41,318 Urambo 10,622 20 855 2 2,845 5 118 0 0 0 233 0 1,385 3 241 0 0 0 37,820 70 54,120 Sikonge 1,694 9 245 1 1,354 7 49 0 49 0 50 0 0 0 289 1 0 0 15,784 81 19,514 Tabora Urban 54 1 119 1 1,935 19 0 0 0 0 67 1 0 0 51 0 27 0 8,005 78 10,258 Total 25,198 11 2,352 1 13,256 6 282 0 771 0 1,142 0 1,500 1 1,179 0 27 0 190,210 81 235,917 Table 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households Source of Improved Seeds by District, 2002/03 Agricultural Year Other Not applicable Total District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Locally Produced by Household Neighbour Table 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households by Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Development Project Locally Produced by Household Neighbour Not applicable Neighbour Not applicable Large Scale Farm Locally Produced by Household Total Total Table 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides by District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Development Project Crop Buyers Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 188 Number % Number % Number % Number % Number % Nzega 996 34 150 5 858 30 737 26 146 5 2,887 Igunga 110 9 106 9 459 38 114 9 416 35 1,206 Uyui 2,207 20 3,444 31 1,872 17 936 8 2,566 23 11,025 Urambo 7,982 37 4,899 23 4,477 21 2,843 13 1,154 5 21,354 Sikonge 2,601 38 1,018 15 1,505 22 1,066 16 582 9 6,773 Tabora Urban 211 7 87 3 953 31 1,582 52 209 7 3,042 Total 14,107 30 9,704 21 10,124 22 7,279 16 5,073 11 46,287 Number % Number % Number % Number % Number % Nzega 29,183 99 0 0 0 0 0 0 150 1 29,333 Igunga 11,361 93 666 5 217 2 0 0 0 0 12,244 Uyui 7,630 95 292 4 0 0 0 0 98 1 8,020 Urambo 8,223 96 227 3 0 0 126 1 0 0 8,576 Sikonge 3,907 93 295 7 0 0 0 0 0 0 4,202 Tabora Urban 2,347 81 424 15 53 2 53 2 27 1 2,903 Total 62,650 96 1,904 3 270 0 179 0 275 0 65,279 District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Table 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year Total Number Table 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 189 Number % Number % Number % Number % Nzega 6,580 100 0 0 0 0 0 0 6,580 Igunga 459 100 0 0 0 0 0 0 459 Uyui 2,973 100 0 0 0 0 0 0 2,973 Urambo 4,076 87 0 0 115 2 505 11 4,696 Sikonge 295 100 0 0 0 0 0 0 295 Tabora Urban 312 86 26 7 0 0 26 7 365 Total 14,696 96 26 0 115 1 531 3 15,368 Number % Number % Number % Number % Number % Nzega 1,230 21 0 0 1,337 23 2,324 40 883 15 5,774 Igunga 4,438 40 3,515 32 2,162 20 440 4 417 4 10,971 Uyui 1,790 27 2,088 31 933 14 205 3 1,663 25 6,679 Urambo 6,260 38 3,318 20 3,594 22 2,225 14 903 6 16,300 Sikonge 1,167 31 531 14 858 23 780 21 394 11 3,730 Tabora Urban 184 8 156 7 676 30 1,102 49 133 6 2,253 Total 15,069 33 9,608 21 9,560 21 7,077 15 4,393 10 45,706 Number % Number % Number % Number % Number % Nzega 1,080 25 0 0 1,158 27 860 20 1,197 28 4,294 Igunga 1,476 24 1,712 28 2,407 39 115 2 452 7 6,162 Uyui 2,815 24 3,230 27 2,167 18 830 7 2,781 24 11,823 Urambo 5,496 34 4,062 25 3,110 19 2,632 16 830 5 16,130 Sikonge 2,003 33 928 15 1,210 20 782 13 1,171 19 6,095 Tabora Urban 157 5 149 4 1,052 31 1,851 55 146 4 3,355 Total 13,028 27 10,081 21 11,103 23 7,071 15 6,576 14 47,859 Between 10 and 20 km 20 km and Above Total Table 12.1.17 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Insecticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km 20 km and Above Total Table 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km Between 10 and 20 km Total Number Table 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year District Less than 1 km Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 190 Number % Number % Number % Number % Number % Number % Number % Nzega 8,849 14 51,521 82 0 0 281 0 2,029 3 0 0 0 0 62,679 Igunga 20,332 46 17,655 40 693 2 904 2 4,124 9 0 0 228 1 43,935 Uyui 3,591 12 24,391 81 413 1 502 2 1,197 4 0 0 200 1 30,293 Urambo 3,420 10 27,367 84 107 0 373 1 1,373 4 125 0 0 0 32,766 Sikonge 2,160 17 10,062 79 95 1 0 0 331 3 0 0 93 1 12,741 Tabora Urban 0 0 7,032 97 27 0 39 1 92 1 0 0 25 0 7,216 Total 38,352 20 138,027 73 1,335 1 2,099 1 9,147 5 125 0 546 0 189,630 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 19,964 55 10,334 29 4,529 12 0 0 119 0 863 2 0 0 424 1 36,233 Igunga 6,114 19 3,019 9 13,396 41 1,258 4 4,364 13 2,940 9 108 0 1,697 5 32,897 Uyui 19,353 58 4,170 13 4,460 13 2,493 7 920 3 1,020 3 0 0 880 3 33,297 Urambo 27,577 61 4,877 11 8,877 19 1,655 4 1,571 3 626 1 123 0 240 1 45,545 Sikonge 10,394 68 2,291 15 1,709 11 343 2 246 2 230 2 50 0 50 0 15,312 Tabora Urban 4,515 61 806 11 1,823 25 67 1 66 1 53 1 0 0 25 0 7,355 Total 87,917 52 25,497 15 34,794 20 5,817 3 7,285 4 5,733 3 280 0 3,315 2 170,638 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,806 10 10,547 18 19,735 33 1,175 2 20,097 34 425 1 0 0 1,201 2 58,986 Igunga 2,453 5 2,780 6 14,008 31 1,250 3 21,375 48 2,602 6 108 0 106 0 44,682 Uyui 4,616 12 3,056 8 10,766 28 1,796 5 17,184 45 927 2 0 0 0 0 38,345 Urambo 6,290 13 3,903 8 26,931 54 1,842 4 8,886 18 876 2 698 1 0 0 49,425 Sikonge 2,522 13 1,706 9 9,826 51 756 4 3,980 21 330 2 0 0 99 1 19,219 Tabora Urban 239 2 794 8 7,428 75 61 1 1,174 12 120 1 0 0 77 1 9,893 Total 21,926 10 22,785 10 88,694 40 6,879 3 72,696 33 5,279 2 806 0 1,484 1 220,549 Table 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.19 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, Table 12.1.20 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, Other Total Total Total District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other District Not Available Price Too High No Money to Buy Do not Know How to Use Input is of No Use Locally Produced by Household Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 191 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,930 10 51,565 84 150 0 0 0 2,906 5 571 1 0 0 150 0 61,272 Igunga 8,462 22 24,258 62 793 2 0 0 4,797 12 668 2 0 0 0 0 38,979 Uyui 6,070 21 21,185 72 707 2 104 0 804 3 414 1 106 0 105 0 29,494 Urambo 11,099 29 23,289 61 1,081 3 0 0 1,187 3 1,123 3 96 0 115 0 37,990 Sikonge 2,762 21 9,300 69 444 3 198 1 479 4 140 1 0 0 96 1 13,419 Tabora Urban 53 1 6,379 92 188 3 0 0 125 2 80 1 0 0 79 1 6,903 Total 34,376 18 135,975 72 3,362 2 302 0 10,299 5 2,996 2 202 0 545 0 188,057 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 5,296 8 50,658 77 451 1 0 0 6,072 9 2,817 4 0 0 124 0 65,417 Igunga 10,186 23 21,012 47 1,599 4 0 0 9,289 21 2,711 6 0 0 0 0 44,797 Uyui 7,631 19 20,425 50 918 2 104 0 8,693 21 3,137 8 106 0 0 0 41,012 Urambo 20,861 39 20,973 39 1,170 2 0 0 6,392 12 3,424 6 109 0 219 0 53,148 Sikonge 4,536 24 10,665 55 591 3 149 1 2,416 13 810 4 0 0 99 1 19,266 Tabora Urban 256 3 2,819 28 262 3 0 0 6,778 66 81 1 0 0 25 0 10,221 Total 48,765 21 126,552 54 4,991 2 253 0 39,639 17 12,979 6 214 0 468 0 233,861 Number % Number % Number % Number % Number % Number % Number % Number % Nzega 13,186 22 45,270 76 150 0 0 0 140 0 744 1 0 0 300 1 59,792 Igunga 13,850 41 17,577 51 461 1 0 0 1,951 6 217 1 0 0 114 0 34,170 Uyui 11,091 32 21,699 63 821 2 0 0 403 1 626 2 0 0 0 0 34,639 Urambo 15,048 40 21,575 57 825 2 0 0 373 1 0 0 0 0 0 0 37,820 Sikonge 4,616 29 9,542 60 198 1 149 1 99 1 146 1 985 6 50 0 15,784 Tabora Urban 26 0 7,510 94 206 3 0 0 65 1 146 2 0 0 52 1 8,005 Total 57,818 30 123,173 65 2,661 1 149 0 3,030 2 1,879 1 985 1 516 0 190,210 Input is of No Use Locally Produced by Household Price Too High No Money to Buy Other Total Total Total Table 12.1.22 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Table 12.1.23 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Too Much Labour Required Do not Know How to Use Locally Produced by Household Other District Not Available Other District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Table 12.1.21 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 192 Number % Number % Number % Number % Number % Nzega 1,033 36 1,568 54 286 10 0 0 0 0 2,887 Igunga 686 57 519 43 0 0 0 0 0 0 1,206 Uyui 3,882 35 6,104 55 724 7 315 3 0 0 11,025 Urambo 10,928 51 8,556 40 1,495 7 376 2 0 0 21,354 Sikonge 2,376 35 4,052 60 345 5 0 0 0 0 6,773 Tabora Urban 578 19 2,013 66 290 10 134 4 27 1 3,042 Total 19,484 42 22,812 49 3,140 7 825 2 27 0 46,287 Number % Number % Number % Number % Nzega 15,446 53 12,461 42 1,426 5 0 0 29,333 Igunga 4,681 38 6,553 54 1,010 8 0 0 12,244 Uyui 2,571 32 4,354 54 994 12 102 1 8,020 Urambo 5,193 61 2,846 33 537 6 0 0 8,576 Sikonge 1,814 43 2,294 55 94 2 0 0 4,202 Tabora Urban 692 24 1,973 68 238 8 0 0 2,903 Total 30,398 47 30,480 47 4,299 7 102 0 65,279 Number % Number % Number % Number % Nzega 1,285 20 4,999 76 296 5 0 0 6,580 Igunga 0 0 230 50 230 50 0 0 459 Uyui 1,459 49 1,221 41 294 10 0 0 2,973 Urambo 602 13 2,240 48 1,853 39 0 0 4,696 Sikonge 48 16 198 67 50 17 0 0 295 Tabora Urban 73 20 239 66 26 7 27 7 365 Total 3,466 23 9,127 59 2,748 18 27 0 15,368 District Excellent Excellent Good Total Total Good Average Poor Table 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Average Poor Table 12.1.24 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year Table 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year Total District Excellent Good Average Poor Does not Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 193 Number % Number % Number % Number % Number % Nzega 1,126 26 2,901 68 124 3 144 3 0 0 4,294 Igunga 1,266 21 4,450 72 224 4 222 4 0 0 6,162 Uyui 5,110 43 6,510 55 203 2 0 0 0 0 11,823 Urambo 6,837 42 8,421 52 747 5 125 1 0 0 16,130 Sikonge 2,093 34 3,668 60 241 4 43 1 50 1 6,095 Tabora Urban 732 22 2,396 71 200 6 27 1 0 0 3,355 Total 17,163 36 28,345 59 1,739 4 562 1 50 0 47,859 Number % Number % Number % Nzega 0 0 149 100 0 0 149 Igunga 115 33 230 67 0 0 345 Uyui 0 0 306 100 0 0 306 Urambo 505 52 468 48 0 0 973 Sikonge 149 60 50 20 50 20 248 Tabora Urban 0 0 37 100 0 0 37 Total 769 37 1,238 60 50 2 2,056 Number % Number % Number % Number % Number % Number % Number % Nzega 2,724 47 2,613 45 438 8 0 0 0 0 5,774 Nzega 14,192 22 51,374 78 65,566 Igunga 3,652 33 5,522 50 1,569 14 114 1 114 1 10,971 Igunga 4,918 11 40,224 89 45,141 Uyui 2,527 38 4,152 62 0 0 0 0 0 0 6,679 Uyui 15,651 38 25,667 62 41,318 Urambo 8,976 55 6,973 43 227 1 124 1 0 0 16,300 Urambo 32,925 61 21,195 39 54,120 Sikonge 1,165 31 2,370 64 195 5 0 0 0 0 3,730 Sikonge 9,732 50 9,782 50 19,514 Tabora Urban 560 25 1,494 66 172 8 27 1 0 0 2,253 Tabora Urban 3,825 37 6,433 63 10,258 Total 19,603 43 23,123 51 2,601 6 265 1 114 0 45,706 Total 81,242 34 154,675 66 235,917 Table 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Chemical Fertilizer by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Agricultural Households With NO Plan to use Next Year District Total Poor Does not Work Total Table 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year District Excellent Good Average Good Average Poor Average Total District Excellent Good Table 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 District Excellent Does not Total Table 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 194 Number % Number % Number % Number % Nzega 47,418 72 18,148 28 65,566 Nzega 20,760 32 44,806 68 65,566 Igunga 31,132 69 14,009 31 45,141 Igunga 2,519 6 42,622 94 45,141 Uyui 12,879 31 28,438 69 41,318 Uyui 3,804 9 37,514 91 41,318 Urambo 15,250 28 38,870 72 54,120 Urambo 7,485 14 46,635 86 54,120 Sikonge 6,507 33 13,006 67 19,514 Sikonge 740 4 18,774 96 19,514 Tabora Urban 3,533 34 6,725 66 10,258 Tabora Urban 1,027 10 9,231 90 10,258 Total 116,720 49 119,197 51 235,917 Total 36,336 15 199,581 85 235,917 Number % Number % Number % Number % Nzega 25,067 38 40,499 62 65,566 Nzega 3,391 5 62,175 95 65,566 Igunga 22,236 49 22,905 51 45,141 Igunga 6,510 14 38,631 86 45,141 Uyui 18,136 44 23,182 56 41,318 Uyui 2,896 7 38,422 93 41,318 Urambo 22,444 41 31,676 59 54,120 Urambo 4,108 8 50,012 92 54,120 Sikonge 8,259 42 11,255 58 19,514 Sikonge 775 4 18,739 96 19,514 Tabora Urban 3,672 36 6,586 64 10,258 Tabora Urban 149 1 10,109 99 10,258 Total 99,814 42 136,103 58 235,917 Total 17,829 8 218,088 92 235,917 Number % Number % Nzega 29,068 44 36,498 56 65,566 Igunga 29,364 65 15,777 35 45,141 Uyui 12,035 29 29,283 71 41,318 Urambo 27,331 51 26,789 49 54,120 Sikonge 6,411 33 13,102 67 19,514 Tabora Urban 2,729 27 7,529 73 10,258 Total 106,937 45 128,979 55 235,917 District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households using Improved Seeds by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Herbicides by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Insecicides/Fungicides by District, 2002/03 Agricultural Year Table 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year COMPOST Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Table 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Next Year Farm Yard Manure by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 195 AGRICULTURE CREDIT Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 196 Number % Number % Nzega 1,411 100 0 0 1,411 Igunga 336 100 0 0 336 Uyui 7,629 96 309 4 7,938 Urambo 11,186 95 618 5 11,803 Sikonge 3,985 99 50 1 4,034 Tabora Urban 132 100 0 0 132 Total 24,679 96 977 4 25,655 District Family, Friend and Relative Commercial Bank Co- operative Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Nzega 150 0 0 146 286 829 0 1,411 Igunga 230 0 0 0 0 106 0 336 Uyui 306 210 7,318 104 0 0 0 7,938 Urambo 503 125 11,051 0 0 0 125 11,803 Sikonge 245 48 3,548 0 47 145 0 4,034 Tabora Urban 0 0 132 0 0 0 0 132 Total 1,434 384 22,049 250 333 1,080 125 25,655 % 6 1 86 1 1 4 0 100 District Not needed Not available Did not want to go into debt Interest rate/cost too high Did not know how to get credit Difficult bureaucracy procedure Credit grante d too late Other Don't know about credit Total Nzega 2,835 9,141 7,727 1,316 22,339 854 150 0 19,793 64,155 Igunga 1,581 16,372 3,082 1,376 10,589 1,031 226 0 10,548 44,805 Uyui 1,091 6,299 4,338 616 11,904 1,113 105 0 7,913 33,379 Urambo 1,926 10,437 3,627 952 12,812 2,052 690 126 9,694 42,317 Sikonge 920 3,446 2,180 294 3,956 331 247 149 3,956 15,480 Tabora Urban 391 1,622 626 213 4,621 350 0 0 2,302 10,126 Total 8,744 47,318 21,580 4,768 66,223 5,730 1,418 275 54,206 210,261 District Labour Seeds Fertilizers Agro- chemicals Tools / Equipment Irrigation Structures Livest ock Other Total Credits Nzega 282 418 975 829 407 0 150 446 3,508 Igunga 336 106 106 106 106 0 106 106 972 Uyui 0 3,043 7,419 5,028 105 206 105 308 16,214 Urambo 446 4,580 11,438 9,447 2,309 757 0 2,189 31,166 Sikonge 96 537 3,750 2,868 143 242 0 544 8,179 Tabora Urban 0 0 107 107 25 0 25 107 372 Total Credits 1,159 8,684 23,795 18,386 3,095 1,205 386 3,701 60,410 13.2a AGRICULTURE CREDIT: Number of Households Reported Main Reasons for Not Using Credit By District During the 2002/03 Agriculture Year 13.2b AGRICULTURE CREDIT: Number of Credits Received By Main Purpose of Credit and District During the 2002/03 Agriculture Year 13.1a AGRICULTURE CREDIT: Number of Agriculture Households Receiving Credit By Sex of Household Head Receiving Credit and District During the 2002/03 Agriculture Year 13.1b AGRICULTURE CREDIT: Number of Households Receiving Credit By Source of Credit By District Total District Male Female Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 197 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 198 District Senna Spp Gravellis Acacia Spp Pinus Spp Eucalyptus Spp Melicia excelsa Casurina Equisetfilia Tectona Grandis Terminalia Catapa Terminalia Ivorensis Leucena Spp Syszygium Spp Azadritachta Spp Albizia Spp Moringa Spp Total Nzega 1,201 5,599 119 . . . . . 576 144 1,474 751 3,068 . 895 13,828 Igunga 695 547 . . . . . . . . 342 . 683 . 1,366 3,633 Uyui . . 98 633 29,003 633 197 . . . 10,557 . 308 0 42,229 83,659 Urambo 3,915 . 30,087 . . . . . . . 4,352 . 241 32,717 4,819 76,131 Sikonge 1,168 297 2,088 2,424 . . . 495 . 1,636 . . . . 2,909 11,018 Tabora Urban 134 . . . . . . . . . 197 . . 1,575 175 2,081 Total 7,114 6,443 32,393 3,058 29,003 633 197 495 576 1,780 16,922 751 4,300 34,292 52,394 190,349 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees 0-9 1-19 05-29 30-39 40-49 60+ Total Nzega 1,280 8,485 291 5,343 0 . 1,570 13,828 Nzega 4,115 1,197 0 296 0 0 5,609 Igunga 223 888 344 2,744 0 . 567 3,633 Igunga 693 1,839 2,072 577 0 106 5,288 Uyui 204 1,562 418 50,425 211 31,672 833 83,659 Uyui 626 0 98 0 0 0 724 Urambo 483 7,005 0 . 741 69,127 1,224 76,131 Urambo 5,532 829 2,040 1,070 251 1,374 11,096 Sikonge 50 198 198 2,577 97 8,242 345 11,018 Sikonge 149 744 727 98 0 99 1,817 Tabora Urban 47 1,709 33 372 0 . 80 2,081 Tabora Urba 692 507 157 105 157 367 1,984 Total 2,285 19,847 1,284 61,461 1,049 109,041 4,619 190,349 Total 11,807 5,116 5,094 2,146 408 1,946 26,518 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Planks / Timber Poles Charcoal Fuel for Wood Shade Medicina l Other Total Nzega 288 147 1,248 419 0 294 2,397 Nzega 150 0 0 297 942 588 419 2,397 Igunga 0 0 0 453 0 114 567 Igunga 0 0 0 453 0 114 0 567 Uyui 0 106 210 295 103 422 1,135 Uyui 0 106 0 415 207 197 106 1,030 Urambo 0 0 983 241 0 241 1,465 Urambo 126 371 126 120 362 241 118 1,465 Sikonge 98 0 97 149 0 98 442 Sikonge 0 50 0 48 196 48 99 442 Tabora Urban 0 0 47 20 0 13 80 Tabora Urba 0 0 0 20 47 13 0 80 Total 386 252 2,585 1,576 103 1,183 6,085 Total 277 526 126 1,353 1,754 1,202 742 5,980 14.5 TREE FARMING: Number of Responses by Second Use of Planted Trees and District for the 2002/03 Agriculture Year, Tabora RegionSecond Use of Trees By District District Second Use 14.1 ON FARM TREE PLANTING: Number of Planted Trees By Species and District During the 2002/03 Agriculture Year, Tabora Region 14.2 TREE FARMING: Number of Households with Planted Trees on their Land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Tabora District District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total 14.4 TREE FARMING: Number of Agriculture Households Classified By Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Tabora Region District Distance to Community Planted Forest (km) 14.3 TREE FARMING: Number of Responses by Main Use of Trees By District and District for the 2002/03 Agriculture Year, Tabora Region District Main Use Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 199 CROP EXTENSION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 200 Number % Number % Nzega 15,560 24 50,006 76 65,566 Igunga 8,662 19 36,479 81 45,141 Uyui 12,311 30 29,006 70 41,318 Urambo 13,710 25 40,411 75 54,120 Sikonge 5,173 27 14,341 73 19,514 Tabora Urban 7,539 73 2,719 27 10,258 Total 62,956 27 172,961 73 235,917 Number % Number % Number % Number % Number % Nzega 1,862 12 9,464 61 3,339 21 749 5 147 1 15,560 Igunga 1,608 19 5,819 67 1,125 13 0 0 109 1 8,662 Uyui 2,533 21 7,914 64 1,656 13 106 1 102 1 12,311 Urambo 2,540 20 7,746 60 2,296 18 242 2 0 0 12,824 Sikonge 719 14 3,596 70 760 15 50 1 0 0 5,124 Tabora Urban 284 4 5,910 79 1,107 15 214 3 0 0 7,516 Total 9,547 15 40,449 65 10,282 17 1,361 2 358 1 61,997 Total Number % Number % Number % Number % Number % Number % Number Nzega 14,157 91 984 6 119 1 150 1 0 0 150 1 15,560 Igunga 8,436 99 0 0 0 0 116 1 0 0 0 0 8,552 Uyui 8,845 72 2,199 18 1,267 10 0 0 0 0 0 0 12,311 Urambo 6,885 54 4,119 32 1,483 12 96 1 118 1 0 0 12,701 Sikonge 3,716 72 1,125 22 93 2 192 4 0 0 46 1 5,173 Tabora Urban 7,237 97 40 1 0 0 26 0 160 2 25 0 7,488 Total 49,275 80 8,468 14 2,962 5 581 1 278 0 222 0 61,785 15.1 CROP EXTENSION" Number of Agriculture Households Receiving Extension Messages By District During the 2002/03 Agriculture Year, Tabora Region Total 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District District During the 2002/03 Agriculture Year, Tabora Region Households Receiving Households Not Not applicable Very Good Good Average Poor No Good 15.3 CROP EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Tabora Region Total Number of Households District Government NGO / Development Cooperative Large Scale Farm Other Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 201 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Received Advice Total Number of Household % of Total Number of Household Nzega 13,888 844 0 150 0 150 15,032 65,566 23 Igunga 8,321 0 0 116 0 0 8,436 45,025 19 Uyui 8,113 2,095 1,267 0 0 0 11,475 41,212 28 Urambo 6,297 4,119 1,483 96 118 0 12,113 54,120 22 Sikonge 3,474 978 93 143 0 0 4,688 19,464 24 Tabora Urban 6,400 40 0 0 26 25 6,492 10,233 63 Total 46,493 8,075 2,843 505 144 175 58,236 235,621 25 % 80 14 5 1 0 0 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 6,243 1,088 0 150 0 0 7,481 65,566 11 Igunga 5,511 106 0 0 0 0 5,617 45,025 12 Uyui 6,046 2,614 1,161 0 0 0 9,821 41,212 24 Urambo 1,759 4,926 222 96 590 126 7,719 54,120 14 Sikonge 2,329 1,023 99 148 0 50 3,649 19,464 19 Tabora Urban 4,079 40 0 0 239 27 4,385 10,233 43 Total 25,967 9,798 1,483 394 829 202 38,673 235,621 16 % 67 25 4 1 2 1 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 3,083 571 0 0 0 150 3,804 65,566 6 Igunga 1,453 0 0 0 0 106 1,559 45,025 3 Uyui 3,011 1,048 211 0 0 0 4,270 41,212 10 Urambo 1,422 1,095 115 0 0 251 2,882 54,120 5 Sikonge 2,021 149 50 50 0 50 2,319 19,464 12 Tabora Urban 2,713 0 0 52 53 27 2,845 10,233 28 Total 13,703 2,862 376 102 53 583 17,680 235,621 8 % 78 16 2 1 0 3 100 15.4 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Plant Spacing By Source and District During the 2002/03 Agriculture Year, Tabora Region 15.5 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Agrochemical By Source and District During the 2002/03 Agriculture Year, Tabora Region District 15.6 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Erosion Control By Source and District During the 2002/03 Agriculture Year, Tabora Region Spacing District District Erosion Control Use of Agrochemicals Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 202 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 11,085 150 119 269 0 0 11,623 65,566 18 Igunga 6,951 0 0 116 0 343 7,410 45,025 16 Uyui 5,410 940 106 0 0 106 6,560 41,212 16 Urambo 4,433 973 193 0 244 251 6,093 54,120 11 Sikonge 2,069 333 50 149 0 50 2,650 19,464 14 Tabora Urban 3,379 25 0 26 266 54 3,751 10,233 37 Total 33,326 2,421 467 560 511 802 38,087 235,621 16 % 88 6 1 1 1 2 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 5,445 690 0 150 0 0 6,285 65,566 10 Igunga 4,358 212 0 0 0 220 4,790 45,025 11 Uyui 5,329 3,253 1,267 0 0 0 9,849 41,212 24 Urambo 2,462 6,101 96 332 590 244 9,826 54,120 18 Sikonge 1,590 1,415 149 149 0 146 3,449 19,464 18 Tabora Urban 3,446 67 0 0 293 25 3,831 10,233 37 Total 22,631 11,739 1,512 631 883 635 38,030 235,621 16 % 60 31 4 2 2 2 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 8,453 1,941 0 150 0 0 10,544 65,566 16 Igunga 6,051 106 0 0 0 231 6,387 45,025 14 Uyui 5,900 2,722 950 106 0 211 9,889 41,212 24 Urambo 3,891 4,546 220 96 236 126 9,115 54,120 17 Sikonge 2,899 636 50 98 0 0 3,683 19,464 19 Tabora Urban 3,014 67 27 0 400 0 3,508 10,233 34 Total 30,207 10,018 1,247 450 636 568 43,126 235,621 18 % 70 23 3 1 1 1 100 Inorganic Fertilizer Use District 15.7 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Organic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Tabora Region 15.8 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use By Source and District During the 2002/03 Agriculture Year, Tabora Region Organic Fertilizer Use Use of Improved Seed District 15.9 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Use of Improved Seeds By Source and District During the 2002/03 Agriculture Year, Tabora Region District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 203 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 738 0 0 0 150 888 65,566 1 Igunga 1,026 0 0 0 115 1,141 45,025 3 Uyui 418 0 0 0 211 629 41,212 2 Urambo 613 124 96 0 363 1,197 54,120 2 Sikonge 245 0 50 50 0 344 19,464 2 Tabora Urban 926 0 0 0 0 926 10,233 9 Total 3,966 124 146 50 839 5,124 235,621 2 % 77 2 3 1 16 100 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,519 147 300 0 0 2,966 65,566 5 Igunga 1,838 0 0 0 115 1,953 45,025 4 Uyui 2,715 104 0 0 211 3,030 41,212 7 Urambo 797 738 0 0 125 1,660 54,120 3 Sikonge 594 198 50 0 50 891 19,464 5 Tabora Urban 1,665 0 0 134 54 1,853 10,233 18 Total 10,128 1,187 350 134 554 12,353 235,621 5 % 82 10 3 1 4 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 6,739 1,096 0 1,170 300 149 9,455 65,566 14 Igunga 6,034 575 0 0 0 114 6,723 45,025 15 Uyui 7,188 419 528 0 0 0 8,134 41,212 20 Urambo 3,597 1,831 230 0 0 118 5,776 54,120 11 Sikonge 2,454 438 0 50 0 99 3,040 19,464 16 Tabora Urban 6,092 13 0 79 133 0 6,317 10,233 62 Total 32,104 4,373 758 1,298 433 480 39,445 235,621 17 % 81 11 2 3 1 1 100 15.10 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Mechanization/LST By Source and District During the 2002/03 Agriculture Year, Tabora Region District District District 15.11 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Irrigation Technology By Source and District During the 2002/03 Agriculture Year, Tabora Region Mechanisation / LST 15.12 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Crop Storage By Source and District During the 2002/03 Agriculture Year, Tabora Region Irrigation Technology Crop Storage Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 204 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Household % of Total Number of Household Nzega 1,034 0 0 0 269 1,303 65,566 2 Igunga 1,213 0 0 0 0 1,213 45,025 3 Uyui 4,992 103 106 0 0 5,200 41,212 13 Urambo 986 1,101 96 347 369 2,900 54,120 5 Sikonge 1,162 0 0 198 50 1,410 19,464 7 Tabora Urban 2,418 27 0 27 103 2,575 10,233 25 Total 11,805 1,230 202 572 791 14,601 235,621 6 % 81 8 1 4 5 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,114 300 0 2,904 269 0 5,588 65,566 9 Igunga 1,110 0 0 0 0 0 1,110 45,025 2 Uyui 1,215 105 211 0 0 317 1,848 41,212 4 Urambo 483 377 0 251 0 356 1,467 54,120 3 Sikonge 680 385 50 50 0 50 1,213 19,464 6 Tabora Urban 4,777 27 0 79 267 24 5,173 10,233 51 Total 10,380 1,194 260 3,283 536 746 16,400 235,621 7 % 63 7 2 20 3 5 100 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 2,900 928 0 0 0 0 3,829 65,566 6 Igunga 1,757 0 0 0 0 0 1,757 45,025 4 Uyui 2,918 312 106 0 0 0 3,336 41,212 8 Urambo 1,093 471 220 118 472 240 2,614 54,120 5 Sikonge 682 96 0 99 0 50 927 19,464 5 Tabora Urban 1,725 54 0 0 54 0 1,832 10,233 18 Total 11,076 1,861 326 217 526 290 14,295 235,621 6 % 77 13 2 2 4 2 100 District 15.13 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Vermin Control By Source and District During the 2002/03 Agriculture Year, Tabora Region District 15.14 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Agro-processing By Source and District During the 2002/03 Agriculture Year, Tabora Region District Vermin Control Agro-forestry Agro-progressing 15.15 CROP EXTENSION MESSAGES: Number of Agriculture Households Receivingf Advice on Agro-forestry By Source and District During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 205 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of Household % of Total Number of Household Nzega 297 0 0 0 0 297 65,566 0 Igunga 116 0 0 0 0 116 45,025 0 Uyui 838 211 0 0 0 1,049 41,212 3 Urambo 357 239 0 244 243 1,083 54,120 2 Sikonge 694 140 99 0 0 934 19,464 5 Tabora Urban 239 75 27 0 0 341 10,233 3 Total 2,541 665 126 244 243 3,819 235,621 2 % 67 17 3 6 6 100 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of Household % of Total Number of Household Nzega 447 519 0 0 0 966 65,566 1 Igunga 106 115 0 0 0 221 45,025 0 Uyui 0 0 0 0 0 0 41,212 0 Urambo 249 0 124 0 243 615 54,120 1 Sikonge 446 92 0 99 50 687 19,464 4 Tabora Urban 105 0 0 26 0 131 10,233 1 Total 1,353 726 124 125 292 2,620 235,621 1 % 52 28 5 5 11 100 15.16 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Beekeeping By Source and District During the 2002/03 Agriculture Year, Tabora Region District District Fish Farming Beekeeping 15.17 CROP EXTENSION MESSAGES: Number of Agriculture Households Receiving Advice on Fish Farming By Source and District During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 206 Received Adopted e % Received Adopted % Received Adopted % Received Adopted % Nzega 14,612 10,942 75 7,031 4,465 64 3,322 1,397 42 11,337 8,274 73 Igunga 8,436 7,308 87 5,617 2,500 45 1,339 671 50 7,296 4,277 59 Uyui 11,577 10,733 93 9,821 7,345 75 4,165 2,193 53 6,349 3,139 49 Urambo 12,231 12,001 98 7,837 6,464 82 2,635 1,200 46 5,605 2,630 47 Sikonge 4,688 3,918 84 3,649 2,916 80 2,175 1,410 65 2,650 1,549 58 Tabora Urban 6,547 5,915 90 4,331 3,349 77 2,820 2,312 82 3,672 2,558 70 Total 58,092 50,816 87 38,287 27,040 71 16,455 9,183 56 36,909 22,427 61 Received Adopted % Received Adopted % Received Adopted % Received Adopted % Nzega 6,144 2,303 37 10,544 5,763 55 738 0 0 2,816 1,779 63 Igunga 4,456 1,681 38 6,387 2,373 37 1,035 221 21 1,721 1,606 93 Uyui 9,951 7,137 72 9,995 4,712 47 312 0 0 2,721 2,087 77 Urambo 9,708 8,984 93 8,993 7,708 86 707 118 17 1,535 1,330 87 Sikonge 3,399 2,917 86 3,585 3,090 86 198 50 25 744 545 73 Tabora Urban 3,772 2,271 60 3,482 1,946 56 900 27 3 1,641 1,112 68 Total 37,431 25,294 68 42,985 25,592 60 3,890 415 11 11,177 8,460 76 Received Adopted % Received Adopted % Received Adopted % Received Adopted % Nzega 9,455 7,937 84 884 587 66 5,469 4,962 91 3,829 1,030 27 Igunga 6,609 5,485 83 1,213 780 64 994 765 77 1,749 983 56 Uyui 7,923 7,398 93 4,989 4,472 90 1,326 1,856 140 3,230 938 29 Urambo 5,654 4,566 81 2,539 2,646 104 1,106 1,111 100 2,386 731 31 Sikonge 3,040 2,524 83 1,361 1,113 82 1,164 732 63 976 739 76 Tabora Urban 6,237 6,054 97 2,190 2,323 106 5,117 4,856 95 1,324 583 44 Total 38,918 33,964 87 13,175 11,920 90 15,177 14,281 94 13,494 5,004 37 District Erosion Control Crop Storage Vermin Control 15.18 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tabora Region 15.19 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tabora Region 15.20 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tabora Region Spacing Use of Agrochemicals District District Agro-progressing Agro-forestry Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed Mechanisation / LST Irrigation Technology Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 207 Received Adopted % Received Adopted % Nzega 297 0 0 966 0 0 Igunga 0 0 0 0 0 0 Uyui 421 316 75 0 0 0 Urambo 598 598 100 124 0 0 Sikonge 934 643 69 492 248 50 Tabora Urban 128 77 60 53 26 50 Total 2,378 1,635 69 1,634 274 17 District Beekeeping Fish Farming 15.21 EXTENSION MESSAGES: Number of Agriculture Households By Receiving and Adopting Extension Messages By Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tabora Region Tanzania Agriculture Sample Census - 2003 Tabora 208 Appendix II 209 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 210 Number of Households % Number of Households % Nzega 34,629 53 30,937 47 65,566 Igunga 34,913 77 10,228 23 45,141 Uyui 9,192 22 32,126 78 41,318 Urambo 5,525 10 48,595 90 54,120 Sikonge 3,754 19 15,760 81 19,514 Tabora Urban 849 8 9,409 92 10,258 Total 88,862 38 147,055 62 235,917 Number Owned Number Used Area Cultivated (Acres) Number Owned Number Used Area Cultivated (Acres) Nzega 83,769 120,742 155,244 83,769 120,742 155,244 Igunga 102,641 162,466 277,122 102,641 162,466 277,122 Uyui 34,417 42,341 63,200 34,417 42,341 63,200 Urambo 14,865 25,202 24,585 14,865 25,202 24,585 Sikonge 12,227 15,992 28,100 12,227 15,992 28,100 Tabora Urban 3,381 3,752 4,728 3,381 3,752 4,728 Total 251,299 370,494 552,978 251,299 370,494 552,978 Number % Number % Nzega 30,698 45 34,868 21 65,566 Igunga 11,351 17 33,791 20 45,141 Uyui 8,867 13 31,727 19 40,594 Urambo 10,884 16 42,391 26 53,275 Sikonge 3,959 6 15,555 9 19,514 Tabora Urban 2,746 4 7,407 4 10,154 Total 68,504 100 165,739 100 234,244 Area (Ha) % Area (Ha) % Area (Ha) (%) Nzega 26,328 41 1,713 24 28,042 39 Igunga 11,737 18 537 7 12,274 17 Uyui 8,880 14 732 10 9,612 13 Urambo 8,972 14 4,104 57 13,075 18 Sikonge 5,695 9 84 1 5,779 8 Tabora Urban 2,803 4 60 1 2,863 4 Total 64,415 100 7,230 100 71,645 100 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of Farm Yard Manure and Compost Application By District During 2002/03 Agriculture Year, Tabora Region District Farm Yard Manure Area Applied Compost Area Applied Total Area Applied with Organic Fertilizers 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft Animal By Number Owened, Used and Area Cultivated (Acres) By District During 2002/03 Agriculture Year, Tabora Region Total Type of Craft District Oxen District Using Organic Fertilizer Not Using Organic Fertilizer 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing Households Using Organic Fertilizer By District During 2002/03 Agriculture Year, Tabora Region Total Number of Crop Growing Households District Using Draft Animals Not Using Draft Animals 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of Agriculture Households Using Draft Animal to Cultivate Land By District During 2002/03 Agriculture Year, Tabora Region Total Households Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 211 CATTLE PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 212 Number % Number % Nzega 22,876 35 42,690 65 65,566 27,645 Igunga 21,452 48 23,689 52 45,141 23,588 Uyui 9,429 23 31,889 77 41,318 14,758 Urambo 6,624 12 47,496 88 54,120 13,740 Sikonge 4,275 22 15,238 78 19,514 5,837 Tabora Urban 1,269 12 8,989 88 10,258 2,302 Total 65,925 28 169,992 72 235,917 87,871 Number % Number % 1-5 15,840 24 52,711 3 3 6-10 12,660 19 100,927 6 8 11-15 9,495 14 121,805 8 13 16-20 7,284 11 133,088 8 18 21-30 9,097 14 234,411 15 26 31-40 3,459 5 129,682 8 37 41-50 2,359 4 108,258 7 46 51-60 839 1 47,044 3 56 61-100 3,506 5 288,935 18 82 101-150 605 1 73,633 5 122 151+ 782 1 278,198 18 356 Total 65,925 100 1,568,691 100 24 Number % Number % Number % Number % Bulls 204,261 100.0 0 0.0 46 0.0 204,307 13.0 Cows 488,048 99.8 0 0.0 1,089 0.2 489,137 31.2 Steers 259,614 99.7 671 0.3 0 0.0 260,285 16.6 Heifers 274,899 99.9 0 0.0 345 0.1 275,243 17.5 Male Calves 150,648 100.0 0 0.0 46 0.0 150,694 9.6 Female Calves 188,699 99.8 0 0.0 325 0.2 189,024 12.0 Total 1,566,169 99.8 671 0.0 1,851 0.1 1,568,691 100.0 Total Cattle 18.4 CATTLE PRODUCTION: Number of Cattle by Category and Type of Cattle; on 1st October 2003 Category of Cattle Catle Rearing Households Heads of Catle Average Number per Household Herd Size 18.3 CATTLE PRODUCTION: Number of Households Rearing Cattle, Head of Cattle and Average Head per Household by Herd Size; on 1st October 2003 Indigenous Cattle Improved Beef Cattle 18.1 CATTLE PRODUCTION: Total Number of Households Rearing Cattle By District During 2002/03 Agriculture Year, Tabora Region Total Number of Agricultural Households Rearing Livestock Total Agriculture Households Improved Dairy Cattle District Households Rearing Cattle Households Not Rearing Cattle Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 213 Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Number of Households Number of Cattle % Nzega 22,876 424,721 99.9 150 300 0.1 0 0 0.0 22,876 425,021 27.1 Igunga 21,452 465,399 99.7 0 0 0.0 115 1,493 0.3 21,452 466,892 29.8 Uyui 9,429 205,865 100.0 0 0 0.0 0 0 0.0 9,429 205,865 13.1 Urambo 6,624 130,629 99.7 124 371 0.3 0 0 0.0 6,624 131,000 8.4 Sikonge 4,229 271,820 99.9 0 0 0.0 96 279 0.1 4,275 272,100 17.3 Tabora Urban 1,244 67,734 99.9 0 0 0.0 52 79 0.1 1,269 67,812 4.3 Total 65,854 1,566,169 99.8 274 671 0.0 262 1,851 0.1 65,925 1,568,691 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega 49,505 130,919 82,744 72,958 38,799 49,797 424,721 Igunga 40,747 160,218 102,951 64,432 45,213 51,839 465,399 Uyui 25,178 65,451 34,556 32,588 22,476 25,615 205,865 Urambo 16,505 40,744 20,445 20,860 15,359 16,716 130,629 Sikonge 67,715 64,890 13,808 66,392 23,469 35,547 271,820 Tabora Urban 4,611 25,827 5,111 17,669 5,333 9,184 67,734 Total 204,261 488,048 259,614 274,899 150,648 188,699 1,566,169 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega . . 300 . . . 300 Igunga . . . . . . . Uyui . . . . . . . Urambo . . 371 . . . 371 Sikonge . . . . . . . Tabora Urban . . . . . . . Total . . 671 . . . 671 Total Cattle 18.6 CATTLE PRODUCTION: Number of Beef Cattle By Category and District as on 1st October, 2003 District Category - Improved Beef Cattle 18.2 CATTLE PRODUCTION: Total Number of Cattle By Type and District as of 1st October, 2003 District 18.5 CATTLE PRODUCTION: Number of Indigenous Cattle By Category and District as on 1st October, 2003 District Category - Indigenous Indigenous Improved Beef Improved Dairy Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 214 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega . . . . . . . Igunga . 919 . 345 . 230 1,493 Uyui . . . . . . . Urambo . . . . . . . Sikonge 46 92 . . 46 96 279 Tabora Urban . 79 . . . . 79 Total 46 1,089 . 345 46 325 1,851 Bulls Cows Steers Heifers Male Calves Female Calves Total Nzega 49,505 130,919 83,044 72,958 38,799 49,797 425,021 Igunga 40,747 161,137 102,951 64,776 45,213 52,069 466,892 Uyui 25,178 65,451 34,556 32,588 22,476 25,615 205,865 Urambo 16,505 40,744 20,816 20,860 15,359 16,716 131,000 Sikonge 67,761 64,982 13,808 66,392 23,515 35,642 272,100 Tabora Urban 4,611 25,905 5,111 17,669 5,333 9,184 67,812 Total 204,307 489,137 260,285 275,243 150,694 189,024 1,568,691 District Total Cattle 18.7 CATTLE PRODUCTION: Number of Dairy Cattle By Category and District as on 1st October, 2003 District Category - Improved Dairy Cattle 18.8 CATTLE PRODUCTION: Total Number of Cattle By Category and District as on 1st October, 2003 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 215 GOATS PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 216 Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat % Number of Households Number of Goat Nzega 17,692 183,820 99 150 901 0.5 300 451 0.2 17,692 185,172 Igunga 17,664 230,075 98 338 1,825 0.8 453 2,177 0.9 17,664 234,077 Uyui 11,852 121,592 97 516 1,558 1.2 512 1,849 1.5 11,852 124,998 Urambo 11,777 91,975 98 370 1,349 1.4 126 502 0.5 11,777 93,826 Sikonge 3,998 53,445 99 99 347 0.6 49 296 0.5 3,998 54,087 Tabora Urban 2,184 26,288 98 0 . 0.0 104 547 2.0 2,184 26,836 Total 65,167 707,195 98 1,473 5,979 0.8 1,543 5,821 0.8 65,167 718,996 Number % Number % Average Per Household 1-4 15,561 23.9 43,747 6 3 5-9 21,112 32.4 138,722 19 7 10-14 13,399 20.6 154,144 21 12 15-19 5,930 9.1 98,153 14 17 20-24 4,395 6.7 92,037 13 21 25-29 930 1.4 25,191 4 27 30-39 1,651 2.5 53,884 7 33 40+ 2,188 3.4 113,118 16 52 Total 65,167 100.0 718,996 100 11 Number % Number % Number % Number % Billy Goat 118,728 98.7 793 0.7 766 0.6 120,287 17 Castrated Goat 35,905 88.4 2,192 5.4 2,505 6.2 40,602 6 She Goat 361,261 99.4 1,019 0.3 1,338 0.4 363,619 51 Male Kid 88,817 98.2 1,146 1.3 522 0.6 90,485 13 She Kid 102,484 98.5 828 0.8 691 0.7 104,003 14 Total 707,195 98.4 5,979 0.8 5,821 0.8 718,996 100 19.1 GOAT PRODUCTION: Total Number of Goats by Goat Type and District as on 1st October, 2003 District 19.3 GOAT PRODUCTION: Total Number of Goats by Category and Type of Goat on 1st October, 2003 Total Goat 19.2 GOAT PRODUCTION: Number of Households Rearing Goats and Head of Goats by Herd Size on 1st October 2003 Goat Rearing Households Head of Goats Herd Size Category of Goats Total Goat Improved Dairy Improved for Meat Indigenous Indigenous Goats Improved Meat Goats Improved Dairy Goats Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 217 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega 29,304 10,183 96,015 20,218 28,099 183,820 Igunga 35,784 13,767 117,179 30,866 32,478 230,075 Uyui 21,994 5,629 59,806 17,051 17,112 121,592 Urambo 17,784 3,378 48,730 10,071 12,013 91,975 Sikonge 10,210 2,007 25,555 7,205 8,468 53,445 Tabora Urban 3,651 941 13,977 3,405 4,315 26,288 Total 118,728 35,905 361,261 88,817 102,484 707,195 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega . 901 . . . 901 Igunga 695 . 914 216 . 1,825 Uyui 98 616 105 633 106 1,558 Urambo . 626 . . 723 1,349 Sikonge . 50 . 297 . 347 Tabora Urban . . . . . . Total 793 2,192 1,019 1,146 828 5,979 Billy Goat Castrated Goat She Goat Male Kid She Kid Total Billy Goat Castrated Goat She Goat Male Kid She Kid Total Nzega 150 300 . . . 451 Nzega 29,455 11,385 96,015 20,218 28,099 185,172 Igunga . 1,838 . . 338 2,177 Igunga 36,479 15,606 118,094 31,082 32,816 234,077 Uyui 512 205 632 199 299 1,849 Uyui 22,604 6,450 60,543 17,884 17,516 124,998 Urambo . . 502 . . 502 Urambo 17,784 4,003 49,232 10,071 12,735 93,826 Sikonge . . . 296 . 296 Sikonge 10,210 2,056 25,555 7,798 8,468 54,087 Tabora Urban 103 161 204 26 53 547 Tabora Urban 3,754 1,102 14,180 3,431 4,368 26,836 Total 766 2,505 1,338 522 691 5,821 Total 120,287 40,602 363,619 90,485 104,003 718,996 19.7 GOAT PRODUCTION: Total Number of Goat by Category and District as of 1st October, 2003 District Total Goat 19.5 GOAT PRODUCTION: Number of Improved Meat Goat by Category and District on 1st October, 2003 194 GOAT PRODUCTION: Number of Indigenous Goat by Category and District on 1st October, 2003 District Number of Indigenous Goats District Number of Improved Meat Goats 19.6 GOAT PRODUCTION: Number of Improved Dairy Goat by Category and District as of 1st October, 2003 District Number of Improved Dairy Goats Tanzania Agriculture Sample Census - 2003 Tabora 218 Appendix II 219 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 220 Number % Number % Number % Ram 37,225 62 22,459 38 59,684 25 Castrated Sheep 3,721 82 828 18 4,549 2 She Sheep 110,926 98 2,042 2 112,969 48 Male Lamb 25,454 93 1,841 7 27,295 12 She Lamb 29,269 95 1,448 5 30,717 13 Total 206,595 88 28,618 12 235,213 100 Number % Number % Nzega 7,912 12 57,654 88 65,566 27,645 Igunga 10,454 23 34,687 77 45,141 23,588 Uyui 5,082 12 36,235 88 41,318 14,758 Urambo 1,826 3 52,294 97 54,120 13,740 Sikonge 2,016 10 17,498 90 19,514 5,837 Tabora Urban 836 8 9,422 92 10,258 2,302 Total 28,126 12 207,790 88 235,917 87,871 Number % Number % Number % Nzega 40,616 96 1,502 4 42,118 18 Igunga 98,197 97 3,373 3 101,570 43 Uyui 38,240 63 22,107 37 60,347 26 Urambo 5,076 84 943 16 6,019 3 Sikonge 19,410 98 428 2 19,838 8 Tabora Urban 5,056 95 265 5 5,321 2 Total 206,595 88 28,618 12 235,213 100 District Number of Indigenous Number of Improved for Mutton Total Number of Sheep Total Household Raising Sheep Average Sheep Nzega 40,616 1,502 42,118 7,912 5 Igunga 98,197 3,373 101,570 10,454 10 Uyui 38,240 22,107 60,347 5,082 12 Urambo 5,076 943 6,019 1,826 3 Sikonge 19,410 428 19,838 2,016 10 Tabora Urban 5,056 265 5,321 836 6 Total 206,595 28,618 235,213 28,126 8 Breed 20.1 SHEEP PRODUCTION: Total Number of Sheep By Breed Type on 1st October 2002/03 Total Sheep Number of Indigenous Sheep Number of Improved Mutton Sheep 20.3 Number of Sheep by Type of Sheep and District as of 1st October, 2002/03 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.4 Number of Sheep per Household by District as of 1st October 2003 Number of Indigenous Number of Improved for Mutton Total Sheep District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 221 Head Size Number of Households % Number of Sheep % Average Number Per Household 1-4 12,999 46 32,772 14 3 5-9 8,550 31 55,667 24 7 10-14 2,781 10 31,232 13 11 15-19 1,496 5 24,471 10 16 20-24 863 3 18,294 8 21 25-29 486 2 12,873 5 26 30-39 485 2 16,330 7 34 40+ 367 1 43,573 19 119 Total 28,028 100 235,213 100 8 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 7,539 892 24,122 3,213 4,850 40,616 Igunga 14,347 1,535 53,264 13,999 15,052 98,197 Uyui 9,314 943 18,042 4,475 5,465 38,240 Urambo 844 . 3,268 474 490 5,076 Sikonge 4,091 138 9,916 2,484 2,781 19,410 Tabora Urban 1,089 213 2,314 809 631 5,056 Total 37,225 3,721 110,926 25,454 29,269 206,595 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 300 . 150 1,051 . 1,502 Igunga 927 232 1,288 232 695 3,373 Uyui 21,115 317 . 190 486 22,107 Urambo 118 . 472 236 118 943 Sikonge . 279 . . 149 428 Tabora Urban . . 132 133 . 265 Total 22,459 828 2,042 1,841 1,448 28,618 Ram Castrated Sheep She Sheep Male Lamb She Lamb Total Nzega 7,840 892 24,272 4,264 4,850 42,118 Igunga 15,274 1,767 54,552 14,230 15,747 101,570 Uyui 30,429 1,259 18,042 4,665 5,952 60,347 Urambo 962 . 3,740 710 608 6,019 Sikonge 4,091 418 9,916 2,484 2,930 19,838 Tabora Urban 1,089 213 2,446 942 631 5,321 Total 59,684 4,549 112,969 27,295 30,717 235,213 20.5 Number of Households and Heads of Sheep by Head Size on 1st October 2003 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2002 District Number of Indigenous 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2002 District Total Sheep 20.7 Total Number of Mutton Sheep by Sheep Type and District on 1st October 2002 District Number of Improved for Mutton Tanzania Agriculture Sample Census - 2003 Tabora 222 Appendix II 223 PIGS PRODUCTION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 224 Number % Number % 1-4 2,386 91 4,076 65 2 5-9 106 4 739 12 7 10-14 123 5 1,471 23 12 Total 2,614 100 6,286 100 2 District Number of Household Number of Pig Average Number Per Household Nzega 532 1,083 2 Uyui 106 739 7 Urambo 1,844 4,172 2 Tabora Urban 132 292 2 Total 2,614 6,286 2 District Boar Castrated Male Sow / Gilt Male Piglet She Piglet Total Nzega 413 119 551 . . 1,083 Uyui 317 0 422 0 0 739 Urambo 1,612 . 1,098 729 733 4,172 Tabora Urban 54 . 81 106 52 292 Total 2,395 119 2,152 835 785 6,286 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 21.2 Number of Households and Pigs by District on 1st October 2003 21.3 Number of Pigs by Type of Pigs and District on 1st October, 2003 Pig Rearing Households Heads of Pigs g Number Per Household Herd Size Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 225 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 226 Number % Number % Nzega 8,133 29 19,512 71 27,645 Igunga 10,622 46 12,621 54 23,243 Uyui 3,511 26 10,122 74 13,634 Urambo 5,587 41 7,910 59 13,497 Sikonge 1,070 19 4,668 81 5,738 Tabora Urban 1,103 49 1,162 51 2,265 Total 30,028 35 55,995 65 86,022 Number % Number % Number % Number % Nzega 6,237 28 3,085 28 868 21 720 19 Igunga 9,316 42 2,918 27 1,212 29 972 26 Uyui 1,440 6 1,235 11 737 18 1,468 39 Urambo 3,865 17 2,224 20 489 12 360 10 Sikonge 732 3 683 6 396 10 48 1 Tabora Urban 581 3 767 7 426 10 150 4 Total 22,172 100 10,913 100 4,127 100 3,717 100 No. of Households % No. of Households % Nzega 17,269 63 9,955 37 27,224 Igunga 16,662 75 5,609 25 22,271 Uyui 7,612 55 6,127 45 13,739 Urambo 6,805 50 6,688 50 13,493 Sikonge 3,081 56 2,432 44 5,513 Tabora Urban 847 39 1,323 61 2,171 Total 52,275 62 32,135 38 84,410 Number % Number % Number % Number % Number % Nzega 3,857 22 7,993 46 2,605 15 300 2 2,514 15 17,269 Igunga 4,094 25 9,841 59 1,718 10 114 1 894 5 16,662 Uyui 2,115 28 3,357 44 632 8 890 12 617 8 7,612 Urambo 1,903 28 3,340 49 96 1 855 13 611 9 6,805 Sikonge 1,154 37 714 23 297 10 634 21 280 9 3,081 Tabora Urban 187 22 502 59 106 13 53 6 0 0 847 Total 13,310 25 25,747 49 5,455 10 2,847 5 4,916 9 52,275 22.1 PESTS AND PARASITES: Number of Livestock Rearing Households deworming Livestock by District During the 2002/03 Agriculture Year District Demworming Livestock NOT Demworming Livestock Total 22.3 PESTS AND PARASITE: Number and Percent of agricultural households reporting to have encountered tick problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year 22.2 PESTS AND PARASITES: Number of Livestock Rearing Households dewormed Livestock byType of Livestock and District During the 2002/03 Agriculture Year District Dewormed Goats Dewormed Cattles Dewormed Sheep Dewormed Pigs District Tick Problems No Tick Problems Total Method of Tick Control 22.4 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households by Method of Tick Control during 2002/03 Agriculture Year and District, 2002/03 Agricultural Year District None Spraying Dipping Smearing Other Total Tanzania Agriculture Sample Census Appendix II 227 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 228 Number % Type Number Indigenous Chicken 2,498,191 99.63 Ducks 57,565 Layer 3,949 0.16 Turkeys 1,830 Broiler 5,330 0.21 Rabbits 7,171 0.00 Donkeys 26,294 0.00 Total 2,507,469 100.00 92,861 Indigenous Chicken Layer Broiler Total Number of Chicken Ducks Turkeys Rabbits Donkeys Other Nzega 492,529 3,522 438 496,490 Nzega 12,653 890 0 1,197 901 Igunga 359,944 109 811 360,864 Igunga 5,420 656 0 11,055 341 Uyui 579,747 317 2,740 582,803 Uyui 27,042 0 633 13,896 1,019 Urambo 646,320 . 1,242 647,562 Urambo 9,171 0 6,438 0 2,552 Sikonge 341,473 . 99 341,572 Sikonge 2,129 285 99 146 0 Tabora Urban 78,178 . . 78,178 Tabora Urban 1,151 0 0 0 0 Total 2,498,191 3,949 5,330 2,507,469 Total 57,565 1,830 7,171 26,294 4,813 Flock Size Number of Households % Number of Chicken Average Chicken by Households 1995 1999 2003 1 - 4 28,432 17 83,765 3 Cattle 1,009,571 1,626,130 1,568,691 5 - 9 46,552 28 309,940 7 Improved Dairy 0 947 1,851 10 - 19 50,056 30 645,709 13 Goats 464,327 930,652 718,996 20 - 29 23,087 14 517,953 22 Sheep 151,034 245,723 235,213 30 - 39 9,792 6 312,264 32 Pigs 4,071 30,406 6,286 40 - 49 4,126 2 173,702 42 Indigenous Chicken 1,670 2,559,020 2,498,191 50 - 99 4,771 3 289,704 61 Layers 6,507 4,950 3,949 100+ 477 0 174,432 365 Broilers 2,675 20,142 5,330 Total 167,294 100 2,507,469 15 Total Chicken 1,679,258 2,584,112 2,507,469 Chicken Others Type 23c OTHER LIVESTOCK: Total Number of Households and Chickens raised by Flock Size as of 1st October 2003 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 District Chicken Type 23b OTHER LIVESTOCK: Number of households with chicken and Category of Chicken by District Type of Livestock 23e OTHER LIVESTOCK/POULTRY POPULATION TREND District 23d OTHER LIVESTOCK: Head Number of Other Livestock by Type of Livestock and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 229 FISH FARMING Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 230 Yes % No % Nzega 0 0 65,566 100 65,566 Igunga 0 0 45,141 100 45,141 Uyui 98 0 41,220 100 41,318 Urambo 0 0 54,120 100 54,120 Sikonge 98 1 19,416 99 19,514 Tabora Urban 26 0 10,232 100 10,258 Total 222 0 235,694 100 235,917 Dug out Pond Total Uyui 196 196 Sikonge 148 148 Tabora Urban 53 53 Total 396 396 Government Institution NGOs / Project Other (Neighbour) Uyui 0 0 196 Sikonge 99 48 0 Tabora Urban 53 0 0 Total 152 48 196 Did not Sell Number Uyui 196 196 Sikonge 148 148 Tabora Urban 53 53 Total 396 396 District Number of Tilapia Number of Carp Number of Others Uyui 3,424 196 196 Sikonge 9,697 0 4,958 Tabora Urban 2,646 55,573 0 Total 15,767 55,768 5,153 District Total 28.1 FISH FARMING: Number of Agricultural Households involved in Fish Farming and District During 2002/03 Agricultural Year Was Fish Farming Carried Out by this Household During 2002/03 28.2 FISH FARMING: Number of Agricultural Households By System of Farming and District During the 2002/03 Agricultural Year District System of Fish Farming District 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year Total District 28.3 FISH FARMING: Number of Agricultural Households By Source of Fingerings and District During the 2002/03 Agricultural Year Source of Fingerlings 28.4 FISH FARMING: Number of Agricultural Households By Location of Selling Fish and District During the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 231 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 232 Number % Number % Nzega 5,387 8 60,179 92 65,566 27,645 19 Igunga 4,180 9 40,961 91 45,141 23,588 18 Uyui 1,780 4 39,538 96 41,318 14,758 12 Urambo 2,877 5 51,244 95 54,120 13,740 21 Sikonge 764 4 18,750 96 19,514 5,837 13 Tabora Urban 1,866 18 8,392 82 10,258 2,302 81 Total 16,853 7 219,063 93 235,917 87,871 19 Government NGO / Development Project Large Scale Farmer Nzega 3,827 421 138 Igunga 2,270 0 0 Uyui 1,261 0 0 Urambo 1,652 0 126 Sikonge 471 96 0 Tabora Urban 1,135 51 0 Total 10,614 567 263 District Source of Advice 29.1b LIVESTOCK EXTENSION PROVIDERS: Number of Households By Source of Extension and District during the 2002/03 Agriculture Year % 29.1a LIVESTOCK EXTENSION: Number of Agricultural Households Receiving Extension Advice By District During 2002/03 Agricultural Year District Received Livestock Advice Did Not Receive Livestock Advice Total Total Number of Households Raising Livestock Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 233 Government NGO / Development Project Total Nzega 447 0 447 27,645 1.6 Igunga 681 0 681 23,588 2.9 Uyui 317 0 317 14,758 2.1 Urambo 0 0 0 13,740 0.0 Sikonge 195 0 195 5,837 3.3 Tabora Urban 263 27 290 2,302 12.6 Total 1,903 27 1,930 87,871 2.2 % 98.6 1.4 100.0 Government NGO / Development Project Total Nzega 1,198 0 1,198 27,645 4.3 Igunga 681 0 681 23,588 2.9 Uyui 422 0 422 14,758 2.9 Urambo 104 0 104 13,740 0.8 Sikonge 195 0 195 5,837 3.3 Tabora Urban 448 27 474 2,302 20.6 Total 3,048 27 3,075 87,871 3.5 % 99.1 0.9 100.0 % Receiving Advice out of Total 29.1c LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking By Source and District 29.1d LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene By Source and District District Source of Advice on Milk Hygene Total Number of Households Raising Livestock Total Number of Households Raising Livestock District Source of Advice opn Proper Milking % Receiving Advice out of Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 234 Government NGO / Development Project Large Scale Farmer not applicable Total Nzega 3,841 150 0 0 3,991 27,645 14.4 Igunga 3,623 0 0 0 3,623 23,588 15.4 Uyui 1,472 0 0 0 1,472 14,758 10.0 Urambo 1,566 0 126 0 1,691 13,740 12.3 Sikonge 474 0 0 0 474 5,837 8.1 Tabora Urban 925 27 26 27 1,006 2,302 43.7 Total 11,901 177 152 27 12,257 87,871 13.9 % 97.1 1.4 1.2 0.2 100.0 Government NGO / Development Project Total Nzega 1,457 150 1,607 27,645 5.8 Igunga 2,269 0 2,269 23,588 9.6 Uyui 317 0 317 14,758 2.1 Urambo 126 0 126 13,740 0.9 Sikonge 237 0 237 5,837 4.1 Tabora Urban 608 24 631 2,302 27.4 Total 5,015 174 5,188 87,871 5.9 % 96.7 3.4 100.0 Total Number of Households Raising Livestock % Receiving Advice out of Total Total Number of Households Raising Livestock % Receiving Advice out of Total District Source of Advice on Herd/Flock Size $ Selection 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control By Source and District District Source of Advice on Disease Control (Dipping/Spraying) 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection By Source and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 235 Government NGO / Development Project Total Nzega 1,042 124 1,166 27,645 4.2 Igunga 663 0 663 23,588 2.8 Uyui 211 0 211 14,758 1.4 Urambo 0 0 0 13,740 0.0 Sikonge 50 99 149 5,837 2.5 Tabora Urban 131 0 131 2,302 5.7 Total 2,096 223 2,319 87,871 2.6 % 90.4 9.6 100.0 Government NGO / Development Project Co-operative Total Nzega 2,061 721 0 2,783 27,645 10.1 Igunga 2,484 0 566 3,050 23,588 12.9 Uyui 947 0 0 947 14,758 6.4 Urambo 930 0 0 930 13,740 6.8 Sikonge 333 0 0 333 5,837 5.7 Tabora Urban 471 51 0 522 2,302 22.7 Total 7,227 772 566 8,565 87,871 9.7 % 84.4 9.0 6.6 100.0 % Receiving Advice out of Total 291h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengtherning By Source and District Total Number of Households Raising Livestock Total Number of Households Raising Livestock % Receiving Advice out of Total District Source of Advice on Group Formation & Strenthening District Source of Advice on Pasture Establishment 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment By Source and District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 236 Government NGO / Development Project Total Nzega 2,608 150 2,759 27,645 10.0 Igunga 2,371 0 2,371 23,588 10.1 Uyui 528 0 528 14,758 3.6 Urambo 125 0 125 13,740 0.9 Sikonge 287 0 287 5,837 4.9 Tabora Urb 334 27 361 2,302 15.7 Total 6,254 177 6,431 87,871 7.3 % 97.2 2.8 100.0 Government NGO / Development Project Total Nzega 721 150 871 27,645 3.2 Igunga 912 0 912 23,588 3.9 Uyui 106 0 106 14,758 0.7 Urambo 0 0 0 13,740 0.0 Sikonge 145 50 195 5,837 3.3 an 209 27 236 2,302 10.2 Total 2,093 227 2,319 87,871 2.6 % 90.2 9.8 100.0 Number % Number % Number % Number % Number % Nzega 1,135 18 3,956 64 566 9 570 9 0 0 6,227 Igunga 1,130 14 2,916 35 797 10 110 1 3,325 40 8,279 Uyui 739 19 936 24 106 3 0 0 2,097 54 3,877 Urambo 1,061 25 1,896 45 242 6 0 0 978 23 4,177 Sikonge 0 0 633 53 464 39 0 0 92 8 1,189 Tabora Urban 116 5 1,339 61 341 15 386 18 25 1 2,207 Total 4,182 16 11,676 45 2,516 10 1,066 4 6,517 25 25,956 Quality of Service Total District Very Good Good Average Poor No Good 29.1k LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year 29.1j LIVESTOCK EXTENSION: Number of Households Receiving Advice on Use of Improved Bulls By Source and District District Source of Advice on Improved Bulls Total Number of Households Raising Livestock % Receiving Advice out of Total 29.1i LIVESTOCK EXTENSION: Number of Households Receiving Advice on Calf Rearing By Source and District District Source of Advice on Calf Rearing Total Number of Households Raising Livestock % Receiving Advice out of Total Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 237 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Total Number of Households Raising Livestock % Nzega 5,387 5,387 5,387 5,387 5,387 26,933 27,645 97 Igunga 4,180 4,180 4,180 4,180 4,180 20,899 23,588 89 Uyui 1,780 1,780 1,780 1,780 1,780 8,901 14,758 60 Urambo 2,877 2,877 2,877 2,877 2,877 14,383 13,740 105 Sikonge 764 718 569 569 569 3,189 5,837 55 Tabora Urban 1,866 1,866 1,866 1,866 1,866 9,332 2,302 405 Total 16,853 16,807 16,659 16,659 16,659 83,637 87,871 95 % 20.2 20.1 19.9 19.9 19.9 100.0 29.1l LIVESTOCK EXTENSION: Number of Households Receiving Advice on Other Extension Messages by Source and District Other Livestock Extension District Tanzania Agriculture Sample Census - 2003 Tabora 238 Appendix II 239 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 240 Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics District Capital Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Nzega 19.4 2.7 6.7 3.2 31.4 9.8 41.9 105.8 8.5 15.9 26.6 69.2 Igunga 13.6 2.4 9.1 2.1 25.2 6.4 46.3 163.9 7.0 14.9 27.0 107.1 Uyui 43.7 5.8 11.8 4.5 61.1 18.1 70.5 68.5 13.1 32.4 64.4 68.6 Urambo 22.4 5.7 19.0 3.2 58.4 8.9 63.5 125.8 13.3 19.4 48.3 115.8 Sikonge 67.3 3.5 47.1 2.0 67.0 7.8 76.8 133.4 28.6 25.8 86.0 119.4 Tabora Urban 14.6 4.1 3.8 0.8 13.5 8.2 14.0 14.5 9.4 13.3 13.9 5.0 Total 27.0 4.0 14.1 3.0 43.8 10.1 54.4 113.3 11.8 20.1 42.6 88.4 Regional Capital 113.3 Tarmac Roads 88.4 District Capital 54.4 Hospitals 43.8 Tertiary Market 42.6 Secondary Schools 27.0 Secondary Market 20.1 All weather roads 14.1 Primary Markets 11.8 Health Clinics 10.1 Primary Schools 4.0 Feeder Roads 3.0 33 01a Mean Distances from Holders Dwellings to Infrastructures and Services by District District Mean Distance to Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 241 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 297 0.5 1,216 1.9 11,463 17.5 26,739 40.8 25,850 39.4 65,566 19.4 Igunga 1,097 2.4 2,200 4.9 16,608 36.8 13,312 29.5 11,924 26.4 45,141 13.6 Uyui 2,589 6.3 1,233 3.0 5,154 12.5 5,404 13.1 26,937 65.2 41,318 43.7 Urambo 346 0.6 869 1.6 14,530 26.8 13,718 25.3 24,657 45.6 54,120 22.4 Sikonge 99 0.5 99 0.5 2,201 11.3 3,991 20.5 13,124 67.3 19,514 67.3 Tabora Urban 54 0.5 227 2.2 3,127 30.5 5,054 49.3 1,796 17.5 10,258 14.6 Total 4,482 1.9 5,845 2.5 53,082 22.5 68,218 28.9 104,289 44.2 235,917 27.0 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 10,622 16.2 17,491 26.7 20,752 31.7 13,415 20.5 3,286 5.0 65,566 6.7 Igunga 12,436 27.5 9,625 21.3 10,961 24.3 4,915 10.9 7,204 16.0 45,141 9.1 Uyui 9,128 22.1 5,959 14.4 13,617 33.0 7,098 17.2 5,515 13.3 41,318 11.8 Urambo 12,171 22.5 8,898 16.4 15,351 28.4 5,021 9.3 12,680 23.4 54,120 19.0 Sikonge 5,194 26.6 1,753 9.0 5,536 28.4 2,346 12.0 4,686 24.0 19,514 47.1 Tabora Urban 4,947 48.2 3,104 30.3 1,819 17.7 361 3.5 26 0.3 10,258 3.8 Total 54,498 23.1 46,830 19.9 68,036 28.8 33,157 14.1 33,397 14.2 235,917 14.1 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 28,747 43.8 23,782 36.3 11,558 17.6 883 1.3 596 0.9 65,566 3.2 Igunga 22,550 50.0 12,717 28.2 8,292 18.4 1,365 3.0 217 0.5 45,141 2.1 Uyui 24,633 59.6 9,627 23.3 5,846 14.1 208 0.5 1,004 2.4 41,318 4.5 Urambo 23,105 42.7 15,973 29.5 10,717 19.8 3,086 5.7 1,239 2.3 54,120 3.2 Sikonge 10,413 53.4 4,242 21.7 4,125 21.1 637 3.3 97 0.5 19,514 2.0 Tabora Urban 6,462 63.0 3,094 30.2 675 6.6 27 0.3 0 0.0 10,258 0.8 Total 115,910 49.1 69,435 29.4 41,213 17.5 6,205 2.6 3,154 1.3 235,917 3.0 1 - 2.9 km 3 - 9 9 km District District Distance to ALL Wealther Road Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km 33.01d: Number of Households by Distance to Feeder Road and District for 2002/03 Agriculture Year Total Number of Households Mean Distance Total Mean Distance Distance to Feeder Road 10 - 19.9 km Above 20 km District Less than 1 km 33.01b: Mean distances from holders dwellings to Secondary Schools by District for 2002/03 Agriculture Year 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 Agriculture Year Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km Mean Distance Total Number of Households Distance to Secondary School Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 242 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 1,414 2.2 689 1.1 6,271 9.6 17,180 26.2 40,012 61.0 65,566 31.4 Igunga 788 1.7 210 0.5 8,632 19.1 11,104 24.6 24,408 54.1 45,141 25.2 Uyui 712 1.7 0 0.0 0 0.0 2,597 6.3 38,010 92.0 41,318 61.1 Urambo 0 0.0 422 0.8 6,731 12.4 6,137 11.3 40,829 75.4 54,120 58.4 Sikonge 0 0.0 0 0.0 2,003 10.3 4,338 22.2 13,173 67.5 19,514 67.0 Tabora Urban 157 1.5 122 1.2 2,751 26.8 5,305 51.7 1,922 18.7 10,258 13.5 Total 3,071 1.3 1,443 0.6 26,388 11.2 46,661 19.8 158,354 67.1 235,917 43.8 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 5,039 7.7 15,275 23.3 27,239 41.5 13,233 20.2 4,780 7.3 65,566 9.8 Igunga 4,983 11.0 7,712 17.1 20,363 45.1 11,855 26.3 229 0.5 45,141 6.4 Uyui 2,826 6.8 5,916 14.3 18,084 43.8 8,807 21.3 5,684 13.8 41,318 18.1 Urambo 5,100 9.4 8,378 15.5 26,816 49.5 9,863 18.2 3,963 7.3 54,120 8.9 Sikonge 2,257 11.6 2,304 11.8 8,625 44.2 5,002 25.6 1,326 6.8 19,514 7.8 Tabora Urban 688 6.7 1,838 17.9 6,539 63.7 1,122 10.9 71 0.7 10,258 8.2 Total 20,894 8.9 41,423 17.6 107,666 45.6 49,881 21.1 16,052 6.8 235,917 10.1 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 8,610 13.1 30,783 46.9 25,136 38.3 1,037 1.6 0 0.0 65,566 2.7 Igunga 7,097 15.7 23,066 51.1 14,641 32.4 221 0.5 116 0.3 45,141 2.4 Uyui 7,023 17.0 14,164 34.3 15,643 37.9 3,162 7.7 1,325 3.2 41,318 5.8 Urambo 10,824 20.0 21,594 39.9 18,316 33.8 2,651 4.9 735 1.4 54,120 5.7 Sikonge 5,911 30.3 6,191 31.7 5,199 26.6 1,792 9.2 420 2.2 19,514 3.5 Tabora Urban 2,532 24.7 4,571 44.6 2,915 28.4 186 1.8 54 0.5 10,258 4.1 Total 41,996 17.8 100,369 42.5 81,851 34.7 9,050 3.8 2,650 1.1 235,917 4.0 Above 20 km Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Total Number of Households Mean Distance District 33.01g: Number of Households by Distance to Primary School by District for 2002/03 Agriculture Year Distance to Primary School Less than 1 km 1 - 2.9 km 3 - 9 9 km 10 - 19.9 km Above 20 km 33.01f Number of Households by Distance to Health Clinic by District for 2002/03 Agriculture Year Total Number of Households Mean Distance District Distance to Health Clinic Distance to Hospital Less than 1 km 1 - 2.9 km 33.01e Number of Households by Distance to Hospital by District for 2002/03 Agriculture Year Total Number of Households Mean Distance District 3 - 9 9 km 10 - 19.9 km Above 20 km Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 243 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 150 0.2 150 0.2 296 0.5 268 0.4 64,702 98.7 65,566 105.8 Igunga 114 0.3 0 0.0 338 0.7 0 0.0 44,689 99.0 45,141 163.9 Uyui 600 1.5 0 0.0 0 0.0 203 0.5 40,515 98.1 41,318 68.5 Urambo 757 1.4 0 0.0 126 0.2 623 1.2 52,613 97.2 54,120 125.8 Sikonge 0 0.0 0 0.0 195 1.0 96 0.5 19,224 98.5 19,514 133.4 Tabora Urban 107 1.0 53 0.5 2,766 27.0 5,407 52.7 1,925 18.8 10,258 14.5 Total 1,729 0.7 203 0.1 3,721 1.6 6,595 2.8 223,668 94.8 235,917 113.3 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 10,836 16.5 150 0.2 3,869 5.9 2,045 3.1 48,665 74.2 65,566 69.2 Igunga 9,442 20.9 223 0.5 112 0.2 107 0.2 35,257 78.1 45,141 107.1 Uyui 1,008 2.4 0 0.0 308 0.7 97 0.2 39,904 96.6 41,318 68.6 Urambo 10,046 18.6 0 0.0 126 0.2 0 0.0 43,949 81.2 54,120 115.8 Sikonge 2,812 14.4 0 0.0 99 0.5 0 0.0 16,603 85.1 19,514 119.4 Tabora Urb 7,290 71.1 60 0.6 1,309 12.8 1,001 9.8 598 5.8 10,258 5.0 Total 41,434 17.6 433 5,824 2.5 3,250 1.4 184,976 78.4 235,917 88.4 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 6,595 10.1 9,070 13.8 30,342 46.3 15,123 23.1 4,437 6.8 65,566 8.5 Igunga 5,997 13.3 7,247 16.1 22,044 48.8 8,035 17.8 1,818 4.0 45,141 7.0 Uyui 4,108 9.9 5,465 13.2 15,503 37.5 8,341 20.2 7,901 19.1 41,318 13.1 Urambo 5,628 10.4 5,384 9.9 22,498 41.6 9,163 16.9 11,446 21.1 54,120 13.3 Sikonge 2,588 13.3 1,902 9.7 8,732 44.7 3,561 18.2 2,732 14.0 19,514 28.6 Tabora Urb 1,807 17.6 289 2.8 3,525 34.4 3,522 34.3 1,115 10.9 10,258 9.4 Total 26,723 11.3 29,357 12.4 102,643 43.5 47,745 20.2 29,449 12.5 235,917 11.8 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 715 1.1 4,614 7.0 14,443 22.0 28,418 43.3 17,376 26.5 65,566 15.9 Igunga 2,329 5.2 3,251 7.2 18,272 40.5 7,248 16.1 14,040 31.1 45,141 14.9 Uyui 1,620 3.9 1,014 2.5 5,269 12.8 5,844 14.1 27,571 66.7 41,318 32.4 Urambo 2,468 4.6 4,689 8.7 18,748 34.6 14,118 26.1 14,098 26.0 54,120 19.4 Sikonge 632 3.2 1,227 6.3 6,456 33.1 4,212 21.6 6,987 35.8 19,514 25.8 Tabora Urb 284 2.8 273 2.7 2,989 29.1 4,648 45.3 2,065 20.1 10,258 13.3 Total 8,048 3.4 15,068 6.4 66,176 28.1 64,487 27.3 82,137 34.8 235,917 20.1 33.01h Number of Households by Distance to Regional Capital and District for 2002/03 Agriculture Year Distance to Regional Capital Total Mean Distance Distance to Secondary Market District District District District 33.01k Number of Households by Distance to Secondary Marketand District for 2002/03 Agriculture Year 33.01j Number of Households by Distance to Primary Market and District for 2002/03 Agriculture Year 33.01i Number of Households by Distance to Tarmac Road and District for 2002/03 Agriculture Year Distance to Tarmac Road Distance to Primary Market Total 10 - 19.9 km Mean Distance Total Mean Distance Total Mean Distance 3 - 9 9 Less than 1 km 1 - 2.9 km 3 - 9 9 km 3 - 9 9 Above 20 km Above 20 Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Less than 1 1 - 2.9 10 - 19.9 10 - 19.9 Above 20 Less than 1 1 - 2.9 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 244 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 1,389 2.1 1,676 2.6 10,153 15.5 13,920 21.2 38,428 58.6 65,566 26.6 Igunga 1,921 4.3 2,349 5.2 8,900 19.7 9,505 21.1 22,467 49.8 45,141 27.0 Uyui 1,112 2.7 202 0.5 1,536 3.7 368 0.9 38,099 92.2 41,318 64.4 Urambo 2,867 5.3 978 1.8 7,368 13.6 6,246 11.5 36,661 67.7 54,120 48.3 Sikonge 828 4.2 294 1.5 3,879 19.9 1,835 9.4 12,678 65.0 19,514 86.0 Tabora Urb 242 2.4 78 0.8 2,807 27.4 5,127 50.0 2,004 19.5 10,258 13.9 Total 8,359 3.5 5,576 2.4 34,643 14.7 37,001 15.7 150,337 63.7 235,917 42.6 Total Mean Distance 33.01l Number of Households by Distance to Tertiary Marketand District for 2002/03 Agriculture Year Distance to Tertiary Market District Less than 1 1 - 2.9 3 - 9 9 10 - 19.9 Above 20 Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 245 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 689 1.4 7,815 16.2 6,894 14.3 4,277 8.9 28,498 59.2 48,173 Igunga 1,265 1.8 6,963 9.7 6,389 8.9 56,429 78.6 771 1.1 71,817 Uyui 2,074 16.0 4,533 35.0 1,336 10.3 2,585 20.0 2,414 18.7 12,942 Urambo 1,125 10.2 4,099 37.3 1,966 17.9 2,678 24.4 1,112 10.1 10,980 Sikonge 1,299 14.1 2,608 28.2 1,307 14.2 3,208 34.8 809 8.8 9,231 Tabora Urban 365 8.4 2,770 63.4 809 18.5 373 8.5 53 1.2 4,371 Total 6,818 4.3 28,787 18.3 18,702 11.9 69,550 44.2 33,657 21.4 157,514 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 689 4.9 5,246 37.0 3,219 22.7 290 2.1 4,718 33.3 14,163 Igunga 919 5.3 4,154 24.1 4,403 25.5 7,548 43.8 217 1.3 17,242 Uyui 1,146 18.9 3,596 59.2 916 15.1 209 3.4 211 3.5 6,078 Urambo 624 11.2 3,357 60.0 875 15.6 425 7.6 315 5.6 5,597 Sikonge 244 6.2 2,082 53.1 960 24.5 591 15.1 43 1.1 3,922 Tabora Urban 73 3.2 1,857 82.8 232 10.4 80 3.6 0 0.0 2,242 Total 3,696 7.5 20,293 41.2 10,605 21.5 9,144 18.6 5,506 11.2 49,243 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 424 7.8 431 7.9 4,566 84.2 5,421 Igunga 0 0.0 0 0.0 108 1.0 10,605 99.0 0 0.0 10,713 Uyui 200 9.7 417 20.2 0 0.0 1,132 54.8 317 15.3 2,066 Urambo 0 0.0 248 25.4 124 12.7 508 52.0 96 9.9 976 Sikonge 97 7.1 142 10.4 50 3.6 940 68.6 142 10.3 1,371 Tabora Urban 106 25.3 132 31.4 102 24.2 54 12.8 27 6.4 421 Total 404 1.9 939 4.5 808 3.9 13,670 65.2 5,148 24.5 20,968 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Extension Center and District, 2002/03 Agricultural Year District Satisfaction of Using Veterinary Clinic Total Number of Households Very Good Good Average Poor No good Satisfaction of Using Extension Center Good Average Poor No good Total Number of Households 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year Satisfaction of Using Research Station Total Number of Households Very Good Good Average Poor No good Very Good 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year District District Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 246 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 424 7.8 290 5.4 4,707 86.8 5,421 Igunga 0 0.0 0 0.0 216 2.0 10,487 96.0 224 2.0 10,927 Uyui 204 17.8 106 9.2 0 0.0 413 36.1 422 36.9 1,145 Urambo 0 0.0 0 0.0 96 12.1 412 51.6 289 36.3 797 Sikonge 518 91.3 0 0.0 0 0.0 50 8.7 0 0.0 567 Tabora Urban 53 29.0 26 14.3 50 27.4 54 29.3 0 0.0 183 Total 775 4.1 132 0.7 787 4.1 11,706 61.5 5,642 29.6 19,041 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 0 0.0 398 5.6 1,642 22.9 5,126 71.5 7,166 Igunga 116 1.1 115 1.1 223 2.1 10,259 94.8 108 1.0 10,820 Uyui 106 6.8 97 6.3 209 13.5 310 20.0 830 53.5 1,552 Urambo 126 6.5 247 12.8 501 26.0 738 38.3 315 16.4 1,927 Sikonge 50 3.1 191 11.8 198 12.3 1,032 64.0 142 8.8 1,612 Tabora Urban 27 9.0 20 6.7 169 57.5 79 26.8 0 0.0 294 Total 424 1.8 669 2.9 1,698 7.3 14,059 60.2 6,521 27.9 23,372 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % Nzega 0 0.0 1,444 18.8 1,231 16.1 422 5.5 4,566 59.6 7,663 Igunga 116 1.2 0 0.0 217 2.2 9,607 95.5 114 1.1 10,055 Uyui 208 22.0 106 11.2 0 0.0 209 22.2 422 44.7 945 Sikonge 50 33.8 0 0.0 0 0.0 0 0.0 97 66.2 147 Tabora Urban 0 0.0 13 11.3 78 66.0 27 22.7 0 0.0 118 Total 373 2.0 1,563 8.3 1,526 8.1 10,266 54.2 5,200 27.5 18,928 No. of Households % No. of Households % No. of Households % No. of Households % No. of Households % 6818 4 28787 18 18702 12 69550 44 33657 21 3696 8 20293 41 10605 22 9144 19 5506 11 404 2 939 5 808 4 13670 65 5148 25 775 4 132 1 787 4 11706 62 5642 30 424 2 669 3 1698 7 14059 60 6521 28 373 2 1563 8 1526 8 10266 54 5200 28 3 6 8 47 23 Poor No good 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab and District, 2002/03 Agricultural Year Satisfaction of Using Plant Protection Lab Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year Satisfaction of Using Land Registration Office Very Good Good Average Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock Development Center Very Good Good District District District Total Total Satisfaction of Using Livestock Development Center Total Extension Centre Research Station Land Registration Office 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and Type of Servive, 2002/03 Agricultural Year Veterinary Clinic Livestock Development Centre OVERALL % Plant Protection Lab Satisfaction of Using Livestock Development Center Very Good Good Average Poor No good Type of Service Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 247 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 248 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Nzega 13,083 446 51,613 424 0 65,566 Igunga 10,807 558 33,323 453 0 45,141 Uyui 5,764 708 34,114 731 0 41,318 Urambo 5,625 253 47,921 204 118 54,120 Sikonge 4,406 247 14,761 99 0 19,514 Tabora Urban 229 144 9,810 75 0 10,258 Total 39,914 2,357 191,542 1,987 118 235,917 % 16.9 1.0 81.2 0.8 0.0 100.0 District Number of rooms Iron Sheets Tiles Concrete Asbestos Grass/ Leaves Grass & Mud Other Total Nzega 2 7,644 447 0 0 50,779 6,695 0 65,566 Igunga 2 5,935 201 0 445 13,968 24,269 323 45,141 Uyui 3 6,684 300 92 106 33,359 587 190 41,318 Urambo 3 5,875 253 0 0 45,166 2,701 124 54,120 Sikonge 2 4,006 99 46 96 14,622 645 0 19,514 Tabora Urban 3 2,336 39 104 95 7,367 317 0 10,258 Total 2 32,481 1,339 243 741 165,263 35,213 637 235,917 % 13.8 0.6 0.1 0.3 70.1 14.9 0.3 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 34,533 27 21,466 17 21,841 17 31,874 25 11,363 9 5,645 4.5 126,723 35.8 Landline Phone 0 0 0 0 201 55 0 0 147 40 20 5.4 368 0.1 Mobile Phone 300 13 444 19 1,135 49 0 0 146 6 310 13.3 2,336 0.7 Iron 10,079 24 5,435 13 8,412 20 11,467 27 4,856 12 1,822 4.3 42,071 11.9 Wheelbarrow 2,470 19 4,941 39 2,571 20 568 4 1,425 11 696 5.5 12,671 3.6 Bicycle 47,255 29 32,427 20 27,587 17 38,059 23 12,612 8 6,597 4.0 164,536 46.5 Vehicle 1,045 32 452 14 1,305 41 222 7 98 3 93 2.9 3,214 0.9 Television/Video 574 27 780 37 503 24 0 0 193 9 77 3.6 2,127 0.6 Total Number of Households 96,257 27 65,945 19 63,554 18 82,190 23 30,840 9 15,260 4.3 354,046 100.0 Sikonge Tabora Urban 34.1: Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year Type of Toilet District 34.2: Number of hoseholds Reporting AverageNumber of Rooms and Type of Roofing Materials by District, 2002/03 Agricultural Year 34.3: Number of Agricultural Households by Type of Owned Assets and District During 2002/03 Agricultural Year District Total Type of Owned Asset Nzega Igunga Uyui Urambo Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 249 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 147 13.7 648 60.3 205 19.0 0 0.0 0 0.0 75 7.0 1,075 0.5 Solar 150 43.4 0 0.0 98 28.3 0 0.0 98 28.3 0 0.0 346 0.1 Gas (Biogas) 0 0.0 0 0.0 102 67.6 0 0.0 49 32.4 0 0.0 151 0.1 Hurricane Lamp 7,474 31.5 4,126 17.4 3,237 13.6 5,276 22.2 2,257 9.5 1,392 5.9 23,763 10.1 Pressure Lamp 2,368 29.4 1,466 18.2 1,243 15.4 1,223 15.2 1,409 17.5 342 4.3 8,051 3.4 Wick Lamp 54,399 27.6 36,769 18.6 35,935 18.2 46,530 23.6 15,270 7.7 8,308 4.2 197,211 83.6 Candles 438 90.5 0 0.0 0 0.0 0 0.0 0 0.0 46 9.5 484 0.2 Firewood 441 9.4 2,132 45.5 499 10.6 1,091 23.3 430 9.2 94 2.0 4,687 2.0 Other 149 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 149 0.1 Total 65,566 27.8 45,141 19.1 41,318 17.5 54,120 22.9 19,514 8.3 10,258 4.3 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 148 59.2 0 0.0 102 40.8 0 0.0 0 0.0 0 0.0 250 0.1 Solar 0 0.0 0 0.0 103 67.6 0 0.0 49 32.4 0 0.0 152 0.1 Bottled Gas 149 26.4 0 0.0 211 37.6 126 22.5 49 8.7 27 4.8 562 0.2 Parraffin / Kerocine 2,553 91.0 107 3.8 98 3.5 0 0.0 49 1.7 0 0.0 2,807 1.2 Charcoal 1,655 26.3 1,296 20.6 1,186 18.8 1,219 19.4 685 10.9 258 4.1 6,299 2.7 Firewood 60,187 26.9 43,391 19.4 39,303 17.6 52,418 23.4 18,487 8.3 9,947 4.4 223,732 94.8 Crop Residues 574 31.7 347 19.1 315 17.3 357 19.7 195 10.7 27 1.5 1,814 0.8 Livestock Dung 300 100.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 300 0.1 Total 65,566 27.8 45,141 19.1 41,318 17.5 54,120 22.9 19,514 8.3 10,258 4.3 235,917 100.0 Sikonge 34.4: Number of Agricultural Households by Main Source of Energy Used for Lighting and District During 2002/03 Agriculture Year Nzega Igunga Uyui Urambo Uyui Urambo Sikonge Tabora Urb District District Total 34.5: Number of Agricultural Households by Main Source of Energy for Cooking and District During 2002/03 Agriculture Year Tabora Urban Main Source of Energy for Lighting District Nzega Igunga Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 250 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 1,489 224 1,932 742 144 602 Dry 1,489 0 1,228 867 0 609 Wet 5,422 2,240 3,501 4,419 1,388 2,460 Dry 5,332 1,677 3,489 4,062 1,340 2,462 Wet 989 457 92 370 335 255 Dry 1,135 564 0 617 335 328 Wet 41,951 15,651 34,815 45,514 14,834 6,477 Dry 42,294 15,909 35,052 45,998 15,175 6,382 Wet 6,175 1,813 102 1,677 2,423 265 Dry 11,940 5,202 206 1,706 2,571 292 Wet 1,886 9,542 668 613 142 79 Dry 2,174 16,038 1,241 623 92 159 Wet 409 0 106 235 0 27 Dry 150 0 0 0 0 0 Wet 6,342 11,881 102 549 50 93 Dry 0 4,017 102 248 0 26 Wet 901 3,333 0 0 198 0 Dry 1,051 1,734 0 0 0 0 Total Agricultural Households per District 65,566 45,141 41,318 54,120 19,514 10,258 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 2 0 5 1 1 6 Dry 2 0 3 2 0 6 Wet 8 5 8 8 7 24 Dry 8 4 8 8 7 24 Wet 2 1 0 1 2 2 Dry 2 1 0 1 2 3 Wet 64 35 84 84 76 63 Dry 65 35 85 85 78 62 Wet 9 4 0 3 12 3 Dry 18 12 0 3 13 3 Wet 3 21 2 1 1 1 Dry 3 36 3 1 0 2 Wet 1 0 0 0 0 0 Dry 0 0 0 0 0 0 Wet 10 26 0 1 0 1 Dry 0 9 0 0 0 0 Wet 1 7 0 0 1 0 Dry 2 4 0 0 0 0 District District 34.6: Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District During 2002/03 Agriculture Year Source District 34.7: Proportion of Agricultural Households by Maion Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Season Season Other Uncovered Rainwater Catchment Covered Rainwater Catchment Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well Protected Well Piped Water Piped Water Other Uncovered Rainwater Catchment Covered Rainwater Catchment Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 251 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 5,690 3,253 4,659 15,745 2,690 1,698 Dry 3,957 1,231 3,440 11,882 1,809 1,616 Wet 10,551 4,716 10,067 9,635 2,811 1,335 Dry 6,184 3,005 8,018 7,223 2,415 1,203 Wet 3,516 2,822 2,955 2,679 1,744 207 Dry 2,642 1,961 3,047 2,651 1,746 206 Wet 18,155 7,637 8,720 9,823 5,771 2,942 Dry 11,117 2,969 6,922 8,632 5,232 2,765 Wet 20,922 16,694 10,372 11,084 4,184 2,677 Dry 23,335 9,913 10,743 15,224 4,625 2,747 Wet 5,118 5,749 3,180 3,446 1,924 1,150 Dry 10,641 7,540 3,806 5,294 2,709 1,097 Wet 1,014 2,926 943 1,353 241 212 Dry 4,182 9,924 4,244 2,244 832 453 Wet 599 1,345 422 355 99 37 Dry 2,922 6,090 1,098 970 97 171 Wet 0 0 0 0 49 0 Dry 587 2,507 0 0 49 0 Season Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 9 7 11 29 14 17 Dry 6 3 8 22 9 16 Wet 16 10 24 18 14 13 Dry 9 7 19 13 12 12 Wet 5 6 7 5 9 2 Dry 4 4 7 5 9 2 Wet 28 17 21 18 30 29 Dry 17 7 17 16 27 27 Wet 32 37 25 20 21 26 Dry 36 22 26 28 24 27 Wet 8 13 8 6 10 11 Dry 16 17 9 10 14 11 Wet 2 6 2 3 1 2 Dry 6 22 10 4 4 4 Wet 1 3 1 1 1 0 Dry 4 13 3 2 0 2 Wet 0 0 0 0 0 0 Dry 1 6 0 0 0 0 34.8: Number of Agricultural Households Reporting Distance to Main Source of Drinking Water during Wet Season by District, 2002/03 Agriculture Year 34.9: Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year 3 - 4.99 Km 2 - 2.99 Km 1 - 1.99 Km 500 - 999 m 300 - 499 m 100 - 299 m Less than 100m Season 1 - 1.99 Km 500 - 999 m 300 - 499 m Source 100 - 299 m Less than 100m 10Km and above 5 - 9.99 Km 3 - 4.99 Km 2 - 2.99 Km District 10Km and above 5 - 9.99 Km District Distance to Main Source of Drinking Water Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 252 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 2,814 447 1,026 6,457 446 304 Dry 1,939 116 1,012 4,390 198 271 Wet 15,112 4,483 9,898 16,552 4,468 3,061 Dry 8,706 1,020 7,744 13,906 3,772 2,741 Wet 13,653 3,391 5,222 6,413 2,749 1,132 Dry 8,891 1,004 4,726 5,678 2,701 1,157 Wet 17,693 11,726 10,768 11,221 5,733 3,085 Dry 13,704 4,688 10,268 9,877 4,949 3,027 Wet 5,818 5,627 3,329 1,084 634 517 Dry 6,651 3,286 2,363 1,443 779 568 Wet 3,822 2,219 3,255 6,723 1,597 545 Dry 2,922 1,211 2,867 6,271 1,105 443 Wet 6,654 17,248 7,819 5,670 3,887 1,614 Dry 22,752 33,816 12,336 12,555 6,009 2,052 Nzega Igunga Uyui Urambo Sikonge Tabora Urban Wet 4 1 2 12 2 3 Dry 3 0 2 8 1 3 Wet 23 10 24 31 23 30 Dry 13 2 19 26 19 27 Wet 21 8 13 12 14 11 Dry 14 2 11 10 14 11 Wet 27 26 26 21 29 30 Dry 21 10 25 18 25 30 Wet 9 12 8 2 3 5 Dry 10 7 6 3 4 6 Wet 6 5 8 12 8 5 Dry 4 3 7 12 6 4 Wet 10 38 19 10 20 16 Dry 35 75 30 23 31 20 34.10: Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year 34.11: Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District During 2002/03 Agriculture Year District Season above one Hour 50 - 59 Minutes 40 - 49 Minutes 30 - 39 Minutes 20 - 29 Minutes 10 - 19 Minutes Less than 10 District Season District Less than 10 10 - 19 Minutes 20 - 29 Minutes District 30 - 39 Minutes 40 - 49 Minutes 50 - 59 Minutes above one Hour Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 253 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 1,190 16 2,202 29 1,934 26 733 10 914 12 519 7 7,492 3.2 Two 19,042 21 8,983 10 14,990 17 32,149 36 8,737 10 5,151 6 89,052 37.7 Three 44,886 33 33,151 24 23,789 17 21,130 15 9,669 7 4,589 3 137,213 58.2 Four 447 21 804 37 605 28 109 5 194 9 0 0 2,159 0.9 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 19,244 24 16,501 21 16,334 20 17,902 22 6,179 8 3,570 4 79,730 33.8 One 29,694 38 13,859 18 10,558 14 15,015 19 4,649 6 3,777 5 77,552 32.9 Two 11,603 24 8,669 18 8,546 17 13,197 27 4,870 10 1,952 4 48,837 20.7 Three 2,921 17 2,824 16 3,154 18 5,920 34 2,053 12 632 4 17,504 7.4 Four 1,538 21 1,825 25 1,725 23 1,349 18 771 10 204 3 7,411 3.1 Five 290 10 778 27 693 24 361 13 658 23 96 3 2,876 1.2 Six 0 0 579 70 0 0 125 15 95 12 26 3 825 0.3 Seven 277 23 107 9 308 26 251 21 240 20 0 0 1,182 0.5 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 34.12: Number of Agricultural Households by Number of Meals the Household NormallyTook by District District Tabora Urban Sikonge Urambo 34-13: HOUSEHOLD FACILITIES: Number of Agricultural Households Reporting Number of days the household Consumed Meat during the Preceeding Week by District Uyui Igunga Nzega District Number of Days Number of Meals per Day Total Total Tabora Urban Uyui Igunga Nzega Sikonge Urambo Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 254 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 37,526 32 31,863 27 17,811 15 20,445 17 8,961 8 2,116 2 118,722 50.3 One 23,718 43 6,506 12 7,331 13 11,844 22 2,769 5 2,712 5 54,881 23.3 Two 2,182 8 4,320 15 8,515 29 8,381 29 3,043 10 2,584 9 29,025 12.3 Three 696 4 1,774 11 4,455 28 5,680 35 2,088 13 1,448 9 16,141 6.8 Four 1,298 13 678 7 1,649 17 3,881 39 1,525 15 834 8 9,865 4.2 Five 146 3 0 0 1,029 21 2,697 54 786 16 353 7 5,011 2.1 Six 0 0 0 0 211 26 379 46 98 12 133 16 822 0.3 Seven 0 0 0 0 315 22 813 56 244 17 77 5 1,450 0.6 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 29,554 28 16,357 15 19,873 19 27,117 26 10,285 10 2,473 2 105,659 44.8 Seldom 22,394 29 17,097 22 11,882 16 16,042 21 4,819 6 4,212 6 76,446 32.4 Sometimes 4,879 29 3,466 20 2,143 13 4,221 25 1,411 8 834 5 16,953 7.2 Often 4,761 23 3,742 18 4,970 24 3,799 18 1,748 8 1,591 8 20,610 8.7 Always 3,978 24 4,480 28 2,450 15 2,942 18 1,251 8 1,148 7 16,249 6.9 Total 65,566 45,141 41,318 54,120 19,514 10,258 235,917 100.0 Igunga Nzega 34.14: Number of Households by Number of Days the Household Consumed Fish during the Preceeding Week by District 34.15: Number of Households Reporting the status of Food ASatisfaction of the Household during the Preceeding Year by District District District Status of Food Satisfaction Number of Days Tabora Urb Sikonge Total Uyui Igunga Nzega Total Tabora Urb Sikonge Urambo Urambo Uyui Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 255 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 17,562 33 6,988 13 8,802 16 14,250 27 4,926 9 1,225 2 53,753 22.8 Sale of Livestock 9,875 41 8,774 36 2,725 11 1,316 5 1,155 5 383 2 24,229 10.3 Sale of Livestock Products 300 12 223 9 414 17 718 29 390 16 444 18 2,489 1.1 Sales of Cash Crops 985 3 8,719 23 7,402 20 16,197 43 4,013 11 412 1 37,727 16.0 Sale of Forest Products 7,218 41 1,551 9 3,147 18 1,328 7 2,884 16 1,658 9 17,786 7.5 Business Income 5,611 20 3,765 13 6,044 22 8,801 31 1,507 5 2,223 8 27,950 11.8 Wages & Salaries in Cash 1,705 32 998 19 727 14 794 15 489 9 576 11 5,288 2.2 Other Casual Cash Earnings 14,834 30 12,347 25 8,586 17 8,037 16 3,239 7 2,265 5 49,309 20.9 Cash Remittance 5,555 39 1,433 10 3,158 22 2,332 16 770 5 930 7 14,177 6.0 Fishing 296 57 0 0 0 0 107 21 92 18 26 5 522 0.2 Other 1,175 53 343 15 313 14 239 11 49 2 117 5 2,236 0.9 not applicable 451 100 0 0 0 0 0 0 0 0 0 0 451 0.2 Total 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 Total Main Source of Cash Income 34.16: Number of Households by Main Source of Income and District During 2002/03 Agriculture Year District Tabora Urban Sikonge Urambo Uyui Igunga Nzega Tanzania Agriculture Sample Census - 2003 Tabora Appendix II 256 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 7,644 24 5,935 18 6,684 21 5,875 18 4,006 12 2,336 7 32,481 13.8 Tiles 447 33 201 15 300 22 253 19 99 7 39 3 1,339 0.6 Concrete 0 0 0 0 92 38 0 0 46 19 104 43 243 0.1 Asbestos 0 0 445 60 106 14 0 0 96 13 95 13 741 0.3 Grass / Leaves 50,779 31 13,968 8 33,359 20 45,166 27 14,622 9 7,367 4 165,263 70.1 Grass & Mud 6,695 19 24,269 69 587 2 2,701 8 645 2 317 1 35,213 14.9 Other 0 0 323 51 190 30 124 19 0 0 0 0 637 0.3 Total Number of Households 65,566 28 45,141 19 41,318 18 54,120 23 19,514 8 10,258 4 235,917 100.0 34.17: Number of Households by Type of Roofing Materials and District During 2002/03 Agriculture Year Total Roofing Materials District Tabora Urb Sikonge Urambo Uyui Igunga Nzega Tanzania Agriculture Sample Census - 2003 Tabora 257 APPENDIX III QUESTIONNAIRES Appendix III 258 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 259 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 260 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 261 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 262 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 263 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 264 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vement Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farming No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 265 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 266 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 266 267 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 268 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 269 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 270 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Land prep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 271 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 272 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert Herb Fun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 273 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 274 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 275 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 276 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 277 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 278 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method of Method of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 279 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 280 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source "a" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 281 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 282 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 283 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 284 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importance Constraint Order of least importance Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 285 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 286 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 287 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 288 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 289 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 290 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 291 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 292 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 293 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 294 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 295 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 296 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Source frequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 297 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 298 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick ifMain Tick if Activity carriedrespo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used for used for nonCheck hh -ility in activitysubsistancesubsistence Total (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 299 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 300 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 301 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 302 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 303 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content JAMHURI YA MUUNGANO WA TANZANIA WIZARA YA KILIMO MAOMBI YA MAFUNZO YA KILIMO KWA VIJANA Serikali kupitia Wizara ya Kilimo inatekeleza Programu ya Kuwezesha Ushiriki wa Vijana katika Kilimo Biashara (Building a Better Tomorrow Youth Initiative for Agribusiness (BBT-YIA). Programu hii inatarajiwa kuongeza ajira kwa vijana kufikia milioni tatu (3) na kuongeza ukuaji wa sekta ya kilimo hadi kufikia asilimia10 ifikapo mwaka 2030 (Ajenda 10/30). Kupitia BBT, Wizara inaratibu uanzishwaji wa mashamba makubwa ya pamoja (Block Farms) kwa ajili ya vijana. Mradi huu utatekelezwa nchi nzima na vijana wote wenye sifa watapata fursa ya kufanya kilimo biashara katika mnyororo wa thamani. Kwa kuanzia, Wizara imetambua mashamba yenye jumla ya ekari 162,492 katika Wilaya ya Chunya (Mbeya); Bahi na Chamwino (Dodoma); na Misenyi na Karagwe (Kagera); na Uvinza na Kasulu (Kigoma). Wizara inatangaza fursa za mafunzo ya kilimo biashara kwa awamu ya kwanza kwa vijana katika Kituo cha Mafunzo ya Kilimo Bihawana mkoani Dodoma. Mafunzo hayo yanatarajiwa kuanza tarehe 15 Februari 2023 ambapo vijana watapatiwa mafunzo kwa muda wa miezi mitatu. Baada ya mafunzo hayo, wahitimu watakabidhiwa mashamba kwa ajili ya kilimo kwa taratibu na masharti yatakayoainishwa Maombi yote yatumwe kupitia kiunganishi cha bbt.kilimo.go.tz kuanzia leo tarehe 10 Januari, 2023. Mwisho wa kutuma maombi ni tarehe 30 Januari 2023 Sifa za vijana wanaotakiwa kuomba ni pamoja na:- i. Awe Mtanzania; ii. Awe na umri kati ya miaka 18 - 40; iii. Awe anapenda kufanya kilimo biashara; na iv. Awe anashiriki kwenye shughuli za kilimo. Imetolewa na: KATIBU MKUU WIZARA YA KILIMO | false |
# Extracted Content T.O.C. Tanzania Agriculture Sample Census i United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 Volume Vd: REGIONAL REPORT: National Bureau of Statistics, Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar September 2006 United Republic of Tanzania NATIONAL SAMPLE CENSUS OF AGRICULTURE 2002/2003 VOLUME Vd: REGIONAL REPORT:TANGA REGION National Bureau of Statistics, Ministry of agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing, Presidents Office, Regional Administration and Local Government, Ministry of Finance and Economic Affairs – Zanzibar December 2007 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census i TABLE OF CONTENTS Table of contents........................................................................................................................................................... i Acronyms..................................................................................................................................................................... v Preface.......................................................................................................................................................................... vi Executive summary.................................................................................................................................................... vii Illustrations................................................................................................................................................................. xii ENSUS RESULT ANALYSIS PART I: BACKGROUND INFORMATION .................................................................................................... 1 1.1 Introduction.................................................................................................................................................. 1 1.2 Geographical Location and Boundaries......................................................................................................... 1 1.3 Land Area..................................................................................................................................................... 1 1.4 Climate.......................................................................................................................................................... 1 1.4.1 Temperature..................................................................................................................................... 1 1.4.2 Rainfall ............................................................................................................................................ 1 1.5 Population..................................................................................................................................................... 1 1.6 Socio-economic Indicators........................................................................................................................... 2 PART II: INTRODUCTION.................................................................................................................................. 3 2.1 The Rationale for Conducting the National Sample Census of Agriculture........................................... 3 2.2 Census Objectives ........................................................................................................................................ 3 2.3 Census Coverage and Scope........................................................................................................................ 4 2.4 Legal Authority of the National Sample Census of Agriculture.............................................................. 5 2.5 Reference Period.......................................................................................................................................... 5 2.6 Census Methodology.................................................................................................................................... 5 2.6.1 Census Organization........................................................................................................................ 5 2.6.2 Tabulation Plan................................................................................................................................ 6 2.6.3 Sample Design................................................................................................................................. 6 2.6.4 Questionnaire Design and Other Census Instruments...................................................................... 7 2.6.5 Field Pre-Testing of the Census Instruments................................................................................... 7 2.6.6 Training of Trainers, Supervisors and Enumerators........................................................................ 7 2.6.7 Information, Education and Communication (IEC) Campaign ....................................................... 7 2.6.8 Household Listing............................................................................................................................ 8 2.6.9 Data Collection................................................................................................................................ 8 2.6.10 Field Supervision and Consistency Checks..................................................................................... 8 2.6.11 Data Processing ............................................................................................................................... 8 - Manual Editing .......................................................................................................................... 9 - Data Entry.................................................................................................................................. 9 - Data Structure Formatting.......................................................................................................... 9 - Batch Validation ........................................................................................................................ 9 - Tabulations ................................................................................................................................ 9 - Analysis and Report Preparations.............................................................................................. 9 - Data Quality............................................................................................................................. 10 2.7 Funding Arrangements........................................................................................................................ 10 PART III: CENSUS RESULTS AND ANALYSIS .............................................................................................. 11 3.1 Holding Characteristics............................................................................................................................. 11 3.1.1 Type of Holdings........................................................................................................................... 11 3.1.2 Livelihood Activities/Source of Income........................................................................................ 11 3.1.3 Sex and Age of Heads of Households ........................................................................................... 11 3.1.4 Number of Household Members ................................................................................................... 15 3.1.5 Level of Education......................................................................................................................... 15 - Literacy.................................................................................................................................... 15 - Literacy Level for Household Members .................................................................................. 15 - Literacy Rates for Heads of Households.................................................................................. 15 - Educational Status.................................................................................................................... 16 3.1.6 Off-farm Income............................................................................................................................ 16 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census ii 3.2 Land Use ................................................................................................................................................. 17 3.2.1 Area of Land Utilised .................................................................................................................... 17 3.2.2 Types of Land use.......................................................................................................................... 18 3.3 Annual Crops and Vegetable Production ................................................................................................ 18 3.3.1 Area Planted .................................................................................................................................. 18 3.3.2 Crop Importance............................................................................................................................ 20 3.3.3 Crop Types .................................................................................................................................... 20 3.3.4 Cereal Crop Production ................................................................................................................. 22 3.3.4.1 Maize ........................................................................................................................... 23 3.3.4.2 Paddy ........................................................................................................................... 23 3.3.4.3 Other Cereals ............................................................................................................... 26 3.3.5 Roots and Tuber Crops Production................................................................................................ 26 3.3.5.1 Cassava........................................................................................................................ 27 3.3.5.2 Irish Potatoes ............................................................................................................... 28 3.3.6 Pulse Crops Production ................................................................................................................. 28 3.3.6.1 Beans ........................................................................................................................... 30 3.3.7 Oil Seed Production....................................................................................................................... 32 3.3.7.1 Groundnuts .................................................................................................................. 32 3.3.8 Fruits and Vegetables ..................................................................................................................... 33 3.3.8.1 Tomatoes ..................................................................................................................... 35 3.3.8.2 Cabbage ....................................................................................................................... 37 3.3.8.3 Chillies......................................................................................................................... 37 3.3.9 Other Annual Crops Production .................................................................................................... 40 3.3.9.1 Cotton ........................................................................................................................... 40 3.3.9.2 Tobacco ....................................................................................................................... 40 3.4 Permanent Crops....................................................................................................................................... 40 3.4.1 Coconuts ..................................................................................................................................... 43 3.4.2 Oranges ..................................................................................................................................... 45 3.4.3 Banana ..................................................................................................................................... 45 3.4.4 Cashew Nuts.................................................................................................................................. 45 3.5 Inputs/Implements Use.............................................................................................................................. 48 3.5.1 Methods of land clearing ................................................................................................................ 48 3.5.2 Methods of soil preparation........................................................................................................... 48 3.5.3 Improved seeds use........................................................................................................................ 50 3.5.4 Fertilizers use................................................................................................................................. 51 3.5.4.1 Farm Yard Manure Use ............................................................................................... 51 3.5.4.2 Inorganic Fertilizer Use ............................................................................................... 52 3.5.4.3 Compost Use................................................................................................................ 53 3.5.5 Pesticide Use ................................................................................................................................. 54 3.5.5.1 Insecticide Use............................................................................................................. 54 3.5.5.2 Herbicide Use .............................................................................................................. 55 3.5.5.3 Fungicide Use.............................................................................................................. 55 3.5.6 Harvesting Methods....................................................................................................................... 56 3.5.7 Threshing Methods ....................................................................................................................... 56 3.6 Irrigation ................................................................................................................................................. 56 3.6.1 Area planted with annual crops and under irrigation..................................................................... 56 3.6.2 Sources of water used for irrigation............................................................................................... 57 3.6.3 Methods of obtaining water for irrigation...................................................................................... 59 3.6.4 Methods of water application ....................................................................................................... 59 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census iii 3.7 Crop Storage, Processing and Marketing................................................................................................ 59 3.7.1 Crop Storage.................................................................................................................................. 59 3.7.1.1 Method of Storage ....................................................................................................... 60 3.7.1.2 Duration of Storage...................................................................................................... 60 3.7.1.3 Purpose of Storage....................................................................................................... 62 3.7.1.4 The Magnitude of Storage Loss................................................................................... 62 3.7.2 Agro processing and by-products ................................................................................................... 63 3.7.2.1 Processing Methods..................................................................................................... 63 3.7.2.2 Main Agro-processing Products .................................................................................. 63 3.7.2.3 Main use of primary processed Products..................................................................... 64 3.7.2.4 Outlet for Sale of Processed Products.......................................................................... 64 3.7.3 Crop Marketing ............................................................................................................................. 65 3.7.3.1 Main Marketing Problems ........................................................................................... 65 3.7.3.2 Reasons for Not Selling............................................................................................... 65 3.8 Access to Crop Production Services......................................................................................................... 66 3.8.1 Access to Agricultural Credits....................................................................................................... 66 3.8.1.1 Source of Agricultural Credits..................................................................................... 66 3.8.1.2 Use of Agricultural Credits.......................................................................................... 66 3.8.1.3 Reasons for not using agricultural credits.................................................................... 67 3.8.2 Crop Extension .............................................................................................................................. 67 3.8.2.1 Sources of crop extension messages............................................................................ 67 3.8.2.2 Quality of extension..................................................................................................... 69 3.9 Access to Inputs .......................................................................................................................................... 69 3.9.2 Inorganic Fertilisers ....................................................................................................................... 69 3.9.3 Improved Seeds .............................................................................................................................. 70 3.9.4 Insecticides and Fungicide.............................................................................................................. 70 3.10 Tree Planting............................................................................................................................................... 71 3.11 Irrigation and Erosion Control Facilities ............................................................................................... 72 3.12 Livestock Results........................................................................................................................................ 74 3.12.1 Cattle Production ........................................................................................................................... 74 3.12.1.1 Cattle Population ......................................................................................................... 74 3.12.1.2 Herd size...................................................................................................................... 74 3.12.1.3 Cattle Population Trend............................................................................................... 76 3.12.1.4 Improved Cattle Breeds ............................................................................................... 76 3.12.2 Goat Production............................................................................................................................. 76 3.12.2.1 Goat Population ........................................................................................................... 76 3.12.2.2 Goat Herd Size............................................................................................................. 78 3.12.2.3 Goat Breeds ................................................................................................................. 78 3.12.2.4 Goat Population Trend................................................................................................. 78 3.12.3 Sheep Production........................................................................................................................... 78 3.12.3.1 Sheep Population ......................................................................................................... 78 3.12.3.2 Sheep Population Trend............................................................................................... 80 3.12.4 Pig Production ............................................................................................................................... 80 3.12.4.1 Pig Population Trend ................................................................................................... 80 3.12.5 Chicken Production ....................................................................................................................... 82 3.12.5.1 Chicken Population...................................................................................................... 82 TOC ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census iv 3.12.5.2 Chicken Population Trend ........................................................................................... 82 3.12.5.3 Chicken Flock Size...................................................................................................... 82 3.12.5.4 Improved Chicken Breeds (layers and broilers) .......................................................... 84 3.12.6 Other Livestock ............................................................................................................................. 84 3.12.7 Pests and Parasites Incidences and Control ................................................................................... 84 3.12.7.1 Deworming .................................................................................................................. 86 3.12.8 Access to Livestock Services......................................................................................................... 86 3.12.8.1 Access to livestock extension Services........................................................................ 86 3.12.8.2 Access to Veterinary Clinic......................................................................................... 86 3.12.8.3 Access to village watering points/dam ........................................................................ 87 3.12.9 Animal Contribution to Crop Production ...................................................................................... 87 3.12.9.1 Use of Draft Power ...................................................................................................... 87 3.12.9.2 Use of Farm Yard Manure........................................................................................... 88 3.12.9.3 Use of Compost ......................................................................................................... 88 3.12.10 Fish Farming.................................................................................................................................. 88 3.13 Poverty Indicators...................................................................................................................................... 91 3.13.1 Access to Infrastructure and Other Services.................................................................................. 91 3.13.2 Type of Toilets .............................................................................................................................. 91 3.13.3 Household’s assets......................................................................................................................... 91 3.13.4 Sources of Light Energy................................................................................................................ 91 3.13.5 Sources of Energy for Cooking ..................................................................................................... 91 3.13.6 Roofing Materials.......................................................................................................................... 94 3.13.7 Access to Drink Water................................................................................................................... 94 3.13.8 Food Consumption Pattern ............................................................................................................ 95 3.13.8.1 Number of Meals per Day ........................................................................................... 95 3.13.8.2 Meat Consumption Frequencies .................................................................................. 95 3.13.8.3 Fish Consumption Frequencies.................................................................................... 95 3.13.9 Food Security................................................................................................................................. 97 3.13.10 Main Source of Cash Income ........................................................................................................ 97 PART IV: TANGA PROFILES.............................................................................................................................. 99 4.1 Region Profile.............................................................................................................................................. 99 4.2 District Profiles ......................................................................................................................................... 100 4.2.1 Lushoto......................................................................................................................................... 100 4.2.2. Korogwe ....................................................................................................................................... 102 4.2.3 Muheza ......................................................................................................................................... 104 4.2.4 Tanga............................................................................................................................................ 106 4.2.5 Pangani ......................................................................................................................................... 108 4.2.6 Handeni ........................................................................................................................................ 110 4.2.7 Kilindi........................................................................................................................................... 111 ACRONYMS Tanzania Agriculture Sample Census v ACRONYMS ASDP Agricultural Sector Development Project CSPro Census and Survey Processing Program DFID Department For International Development DIAS District Integrated Agricultural Survey DS District Supervisor EAS Expanded Agricultural Survey EAs Enumeration Areas EU European Union FE Field Enumerator GDP Gross Domestic Product Ha Hectares IAS Integrated Agricultural Survey ICR Intelligent Character Recognition IEC Information, Education and Communication JICA Japanese International Cooperation Agency LRS Long Rainy Season, MAFS Ministry of Agriculture and Food Security MCM Ministry of Co-operatives and Marketing MWLD Ministry of Water and Livestock Development NBS National Bureau of Statistics NGO Non Governmental Organization NMS National Master Sample NSCA National Sample Census of Agriculture NSGRP National Strategy for Growth and Reduction of Poverty PORALG President’s Office, Regional Administration and Local Government PPS Probability Proportional to Size PSU Primary Sampling Unit RAAS Rapid Appraisal Agricultural Survey RS Regional Supervisor RSM Regional Statistical Manager SAC Scotts Agriculture Consultancy Ltd SPSS Statistical Package for Social Science SRS Short Rainy Season TOT Training of Trainers ULG Ultek Laurence Gould UNDP United Nations Development Programme UNFAO United Nations Food and Agriculture Organization VPO Vice President Office PREFACE ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census vi PREFACE At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar in collaboration with the Ministries of Agriculture and Food Security; Water and Livestock Development; Cooperatives and Marketing as well as the Presidents Office, Regional Administration and Local Government (PORALG) conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95). It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, tree farming, access to infrastructures and services and poverty indicators. In addition to this, the census was large in its coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 1998/99 District Integrated Agricultural Survey. The census covered smallholders in rural areas only and large scale farms. This report presents Tanga region data disaggregated to district level. It was very difficult to discuss all variables collected in a single report hence the analysis was based on the most important smallholder variables. The rest of the variables are found in the e attached annex of table of results. The analysis in the report includes time series comparisons using data from the previous censuses and surveys. The extensive nature of the census in relation to its scope and coverage is a result of the increasing demand for more detailed information to assist in the proper planning of this sector and in the administrative decentralization of planning to district level. It is hoped that this report will provide new insights for planners, policy makers, researchers and others involved in the agricultural sector in order to improve the prevailing conditions faced by crop producers and livestock keepers in the country. On behalf of the Government of Tanzania, I wish to express my appreciation for the financial support provided by the development partners, in particular, the European Union as well as DFID, UNDP, Japanese Government, JICA and others who contributed through the pool fund mechanism. Finally, my appreciation goes to all those who in one-way or the other contributed to the success of the survey. In particular, I would also like to mention the enormous effort made by the Planning Group composed of professionals from the Agriculture Statistics Department of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician in Zanzibar (OCGS) and the Statistics Unit of the Ministry of Agriculture and Food Security (MAFS) with technical assistance provided by Ultec Lawrence Gould (ULG), Scotts Agriculture Consultancy Ltd and the Food and Agriculture Organisation of the United Nations (FAO). Additionally, I would like to extend my appreciation to all professional staff of the National Bureau of Statistics, the sector Ministries of Agriculture and PORALG, the Consultants as well as Regional and District Supervisors and field enumerators for their commendable work. Certainly without their dedication, the census would not have been such a success. Cletus P. B. Mkai The Director General National Bureau of Statistics EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census vii EXECUTIVE SUMMARY The executive summary highlights the main survey results obtained during the National Sample Census of Agriculture 2002/03. This report covers small-scale agriculture households in rural areas of Tanga region who were selected using statistical sampling techniques. The results in the report do not cover urban areas and large-scale farmers. The highlights describe the important findings in relation to agricultural production, productivity, husbandry, access to resources, levels of involvement in agricultural related activities and poverty in Tanga region activities indicators for one to get an overview, at regional level, of the rural agricultural households and their levels of involvement in agricultural related activities. i) Household Characteristics The number of agricultural households in Tanga region were 265,198 out of which 178,406 (67.3%) were involved in growing crops only, 1,477 (0.6%) rearing livestock only, 194 (0.1%) were pastoralist, and 85,121 (32%) were involved in crop production as well as livestock keeping. In summary, Tanga region had 263,527 households involved in crop production and 86,792 involved in livestock production. Most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances. The region has a literacy rate of 70 percent. The highest literacy rate is in Pangani district (70%) followed by Tanga district (68%) and Lushoto district (65%). Kilindi and Handeni districts have the lowest literacy rates of 44 and 53 percent respectively. The literacy rate for the heads of households in the region was 73.6 percent. The number of heads of agricultural households with formal education in Tanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. In Tanga region 46,351 household members (76%) were involved in one off-farm income generating activity, 34,169 (18%) involved in two off-farm income generating activities and 12,023 (6%) involved in more than two off-farm income generating activities. ii) Crop Production Land Area The total area of land available to smallholders was 524,451 ha. The regional average land area utilised for crop production per crop growing household was only 1.7 ha. This figure is below the national average of 2.0 hectares. Planted Area The area planted with annual crops and vegetables was 428,533 hectares out of which 160,820 hectares (37.5%) were planted during short rainy season and 267,713 hectares (62.5%) during long rainy season. An estimated area of 295,529 ha (69.0% of the total planted area with annual and vegetable crops) was with cereals, followed by 77,017 hectares (18.0%) of pulses, 47,614 ha (11.1%) of roots and tubers, 5,346 ha (1.2%) of fruit and vegetables, 2,564 ha (0.6%) of oil seed and 465 ha (0.1%) of cash crops. EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census viii Maize Maize is the dominant annual crop grown in Tanga region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 67 percent of the total area planted with annual crops. Other crops in order of their importance (based on area planted) are cassava, Irish potatoes, cowpeas, paddy, tomatoes, green gram, groundnuts and sweet potatoes. There was a sharp increase in maize production (122%) over the period of 1997 to 1999, whereas there was a sharp decrease in maize production (46%) over the period from 2000 to 2003. The total production of maize in 2002/03 was 173,602 tonnes. The average area planted with maize per household ranged from 0.5 hectares in Lushoto District to 1.3 hectares in Kilindi District. Handeni district had the largest planted area of maize (95,688 ha) followed by Lushoto (51,118 ha), Muheza (50,778 ha), Korogwe (46,369 ha), Kilindi (32,536 ha), Pangani (7,042 ha) and Tanga (3,946 ha). Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tanga region during the long rainy season was 15,443. This represented 66 percent of the total crop growing households in Tanga Region in the long rainy season. Cassava The area planted with cassava was larger than any other root and tuber crop in Tanga in terms of planted area (7.2% of the total area planted with annual crops and vegetables) and it accounted for 64.5 percent of the area planted with roots and tubers. Fruit and Vegetables The total production of fruit and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoes. The production for this crop was 10,852 tonnes, which amounts to 55 percent of the total fruit and vegetable production, followed by cabbage 3,472 tonnes (18%) and chilies 1,973 tonnes (10%). The production of the other fruit and vegetable crops was relatively small. Permanent Crops The area of smallholders planted area with permanent crops was 62,403 hectares which is 13 percent of the area planted with annual crops in the region. The most important permanent crop is coconuts which accounts for 24 percent of the total area planted with permanent crops followed by oranges (15%), banana (13%) and cashew (13%). Improved Seeds The planted area using improved seeds was 52,089 ha which represents 13 percent of the total planted area with the annual crops and vegetables. The percentage use of improved seed in the short rainy season was 13.4 percent which is slightly higher than the corresponding percentage use for the long rainy season (12.73%). Use of Fertilizers Most annual crop growing households do not use any fertiliser. The planted area without fertiliser for annual crops was 367,237 hectares representing 85.6 percent of the total planted area with annual crops. Of the planted area with fertiliser EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census ix application, farm yard manure was applied to 45,411 ha which represented 10.6 percent of the total planted area (73.3 % of the area planted with fertiliser application). This was followed by compost (12,491 ha, 20.1%). Inorganic fertilizers were used on a very small area and represented only 6.6 percent of the area planted with fertilizers. Irrigation In Tanga region, the area of annual crops and vegetables under irrigation was 41,089 ha representing 9.6 percent of the total area planted. The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. However, the percentage of the planted area under irrigation during the long rainy season was 12.3 percent compared with 5 percent in the short rainy season. Crop Storage There were 228,187 crop growing households (87% of the total crop growing households) that reported storing various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and pulses (104,155 households and 1,914 tonnes), paddy (14,828 households and 827 tonnes) and groundnuts and bambara nuts (1,674 households and 54 tonnes). The rest of the crops were stored in very small amounts. Crop Marketing The number of households that reported selling crop was 197,168 which represent 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Tanga (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%). Agricultural Credit In Tanga region, few agricultural households (1,022, 0.4%) accessed credit, out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got credit for agriculture purposes, whereas in Korogwe, Tanga and Handeni districts only male households accessed credit. In Muheza district both male and female headed household’s accessed credit. Crop Extension Services The number of agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region). Some districts have more access to extension services than others (Chart 3.96). Korogwe district had a relatively high proportion of households that received crop extension messages (84%), followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Tanga (14%). Soil Erosion and Water Harvesting Facilities The number of agricultural households that reported the presence of soil erosion and water harvesting facilities in their farms was 30,288. This number represents 11 percent of total number of agricultural households in the region. The proportion of farmers with soil erosion control and water harvesting facilities was highest in Lushoto District (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Tanga (1%) Pangani (0.5%). iii) Livestock and Poultry Production Cattle The total number of cattle in the region was 378,338. Cattle rearing are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on the Tanzanian Mainland. The number EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census x of indigenous cattle was 350,210 head (92.6% of the total number of cattle in the region), 27,829 (7%) were dairy breeds and only 298 (1.4%) were beef breeds. Goats The number of goat-rearing-households in the region was 68,764 (26% of all agricultural households) with a total of 514,620 goats giving an average of 7 head of goats per goat-rearing-households. Sheep The number of sheep-rearing households was 35,381 (13% of all agricultural households) with a total of 164,209 sheep giving an average of 5 heads of sheep per sheep-rearing household. Pigs The number of pig-rearing households in the region was 2,601 (1% of the total agricultural households) rearing about 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. Chicken The number of households keeping chickens was 176,806, raising 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country Tanga ranked eighth out of the 21 Mainland regions. Use of Draft Power The region has 738 oxen and they were only found in two districts, Korogwe and Kilindi with 592 and 146 head respectively. Tanga region has 0.03 percent of the total 2,233,927 head of oxen found on the Mainland and were used to cultivate 2,653 hectares of land. Fish Farming The number of households involved in fish farming was 1,423 (0.5 percent of the total agricultural households in the region). Korogwe was the leading district with 634 agricultural households involved in fish farming (1.4%) followed by Lushoto 430 (0.5%), Muheza 336 (0.7%) and Tanga 23 (0.3%). Fish farming was not practiced in Pangani and Handeni districts. iv) Poverty Indicators Availability of Toilets It was estimated that 86.5 percent of all rural agricultural households used the traditional pit latrines, 1.8 percent used improved pit latrine and 0.7 percent had flush toilets. The remaining 0.1 percent of households had other unspecified types of toilets. Households with no toilet facilities represent 11 percent of the total agriculture households in the region. Household Assets Out of all assets, radios had the highest percent of households owning them (61.3% of households) followed by bicycle (32.1%), iron (18.9%), wheelbarrow (3.4%), mobile phone (1.9%), television/video (1.0%), vehicle (0.9%) and landline phone (0.5%). EXECUTIVE SUMMARY ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census xi Source of Lighting Energy Wick lamp is the most common source of lighting energy in the region. About 77 percent of the total rural households used this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%). Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households. The second most common source of energy for cooking was charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), paraffin/kerosene (0.03%) and gas/biogas (0.01%). Roofing Materials The most used roofing material (for the main dwelling) was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households however, this was closely followed by iron sheets (43.6%). Other roofing materials are grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%). Number of Meals per Day About 72.3 percent of the holders in the region took three meals per day, 25.2 percent took two meals, 2.4 percent took one meal and 0.1 percent took four meals. Food Security Households which seldom had problems in satisfying their food needs represent 42 percent of the total number of agriculture households in the region. Households with recurring food shortage problems represent 8.3 percent whereas those with little problems represent 7.6 percent. About 7 percent of agriculture households always faced food shortages whilst 35 percent had not experienced any food shortage problems. Main Source of Cash Income Selling of food crops was the main cash income earning activity reported by 25.5 percent of all rural agricultural households. The second main cash income earning activity was casual labor (20.9%) followed by selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Other income earning activities were employment (5.0%), sale of livestock (4.0%), sale of forest products (2.5%), sale of livestock products (1.7%) and fishing (0.9%). ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xii ILLUSTRATIONS List of Tables 2.1 Census Sample Size........................................................................................................................................... 6 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District .. 11 3.2 Area, Production and Yield of cereal crops by Season.................................................................................... 22 3.3 Area, Production and Yield of Root and Tuber Crops by Season.................................................................... 27 3.4 Area, Production and Yield of Pulse by Season .............................................................................................. 28 3.5 Area, Quantity Harvested and Yield of Oil Seed Crops by Season ................................................................. 32 3.6 Area, Production and Yield of Fruits and Vegetables by Season..................................................................... 35 3.7 Area, Production and Yield of Annual Cash Crops by Season........................................................................ 37 3.8 Land Clearing Methods.................................................................................................................................... 48 3.9 Planted Area by Type of Fertiliser Use and District – Long and Short Rainy Season..................................... 51 3.10 Number of Crop Growing Households and Planted Area (ha) by Fertilizer Use and District during the Long Rainy Season......................................................................................................................... 51 3.11 Number of Households Storing Crops by Estimated Storage Loss and District.............................................. 62 3.12 Reasons for Not Selling Crop Produce ............................................................................................................ 65 3.13 Number of Agricultural Households that Received Credit by Sex of Household head and District................ 66 3.14 Access to Inputs............................................................................................................................................... 69 3.15 Number of Households and Chickens Raised by Flock Size............................................................................82 3.16 Number of Other Livestock by Type of Livestock and District....................................................................... 84 3.17 Mean distances from dwellings to infrastructure and services by districts...................................................... 91 3.18 Number of Households by Number of meals the Household normally takes per Day and District................. 95 List of Charts 3.1 Agricultural Households by Type of Holdings ................................................................................................ 11 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head ........................................... 11 3.3 Percentage Distribution of Population by Age and Sex in 2003...................................................................... 15 3.4 Percentage Literacy Level of Household Members by District ....................................................................... 15 3.5 Literacy Rates for Heads of Household by Sex and District............................................................................ 15 3.6 Percentage Distribution of Persons Aged 5 years and above in Agricultural Households by Education Status ................................................................................................. 16 3.7 Percentage of Population Aged 5 years and above by District and Educational Status................................... 16 3.8 Percentage Distribution of Heads of Household by Educational Attainment .................................................. 16 3.9 Number of Households by number of members with Off Farm Income – Tanga Region ............................... 17 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities ................................ 17 3.11 Utilized and Usable Land per Household by District ...................................................................................... 17 3.12 Land Area by Type of Land Use...................................................................................................................... 18 3.13 Area Planted with Annual Crops (ha) by Season............................................................................................. 18 3.14 Area Planted with Annual Crops by Season and Region................................................................................. 18 3.15 Area Planted with Annual Crops per Household by Season and District ........................................................ 20 3.16 Planted Area for the Main Annual Crops (ha) ................................................................................................. 20 3.17a Planted Area per Household by Selected Crops................................................................................................20 3.17b Percentage Distribution of Area planted with Annual Crops by Crop Type.................................................... 22 3.18 Area planted with Annual Crops by Type of Crops and Season...................................................................... 22 3.19 Area Planted and Yield of Major Cereal Crops ............................................................................................... 22 3.20 Time Series Data on Maize Production – Tanga Region................................................................................. 23 3.21 Maize: Total Area Planted and Planted Area per Household by District......................................................... 23 3.22 Time Series of Maize Planted Area and Yield – Tanga Region ...................................................................... 23 3.23 Total Planted Area and Area of Paddy per Household by District................................................................... 26 3.24 Time Series Data on Paddy Production – Tanga Region................................................................................. 26 3.25 Time Series of Paddy Planted Area and Yield – Tanga Region ...................................................................... 26 3.26 Area Planted With Sorghum, Finger Millet and Wheat by District ................................................................. 26 3.27 Area Planted and Yield of Major Root and Tuber Crops................................................................................. 26 3.28 Area planted with Cassava during the census/survey years..............................................................................27 3.29 Percent of Cassava Planted Area and percent of Total Land with Cassava by District ....................................28 3.30 Cassava Planted Area per Cassava Growing Households by District.............................................................. 28 3.31 Total Area Planted and Planted Area per Household by District..................................................................... 28 3.32 Area Planted and Yield of Major Pulse Crops................................................................................................. 30 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District ........................................... 30 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiii 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only)....................................... 30 3.35 Time Series Data on Bean Production – Tanga Region................................................................................... 30 3.36 Time Series of Beans Planted Area and Yield - Tanga.................................................................................... 32 3.37 Area Planted and Yield of Major Oil Seed Crops............................................................................................ 32 3.38 Time Series Data on Groundnut planted area – Tanga Region........................................................................ 32 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District........................ 33 3.40 Area Planted per Groundnut Growing Household by District (Long Rainy Season Only).............................. 33 3.42 Area Planted and Yield of Fruit and Vegetables.............................................................................................. 33 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District .................................... 35 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) .................................. 35 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District ................................. 37 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District .................................... 37 3.47 Area planted with Annual Cash Crops............................................................................................................. 40 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District.................................. 40 3.49 Area Planted for Annual and Permanent Crops ............................................................................................... 40 3.50 Area Planted with the Main Permanent Crops................................................................................................. 43 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District .................................. 43 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District....................... 43 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District ........................ 45 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District.......................... 45 3.55 Percent of Area Planted with Cashew nuts and Average Planted Area per Household by District ................. 48 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season..................................... 48 3.57 Area Cultivated by Cultivation Method............................................................................................................48 3.58 Area Cultivated by Method of Cultivation and District................................................................................... 50 3.59 Planted Area of Improved Seeds – Tanga.........................................................................................................50 3.60 Planted Area with Improved Seed by Crop Type ............................................................................................ 50 3.61 Percentage of Crop Type Planted Area with Improved Seed – Annuals.......................................................... 50 3.62 Area of Fertilizer Application by Type of Fertilizer........................................................................................ 51 3.63 Area of Fertilizer Application by Type of Fertilizer and District .................................................................... 51 3.64 Planted Area with Farm Yard Manure by Crop Type - Long Rainy Season.................................................... 52 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure – Annuals................................................... 52 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District....................................................... 52 3.66 Planted Area with Inorganic Fertiliser by Crop type – Annuals ...................................................................... 52 3.67a Percentage of Planted Area with Inorganic Fertiliser by Crop Type ............................................................... 53 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District ....................................................... 53 3.68a Planted Area with Compost by Crop Type ...................................................................................................... 53 3.68b Percentage of Planted Area with Compost by Crop Type................................................................................ 53 3.68c Proportion of Planted Area Applied with Compost by District ....................................................................... 53 3.69 Planted area (ha) by Pesticide use.................................................................................................................... 54 3.70 Planted Area applied with Insecticides by Crop Type..................................................................................... 54 3.71 Percentage of Crop Type Planted Area applied with insecticides.................................................................... 54 3.72 Proportion of Planted Area applied with Insecticides by District during the Long Rainy Season................... 54 3.73 Planted Area applied with herbicides by Crop Type........................................................................................ 55 3.74 Percentage of Crop Type Planted Area applied with herbicides...................................................................... 55 3.75 Proportion of Planted Area applied with Herbicides by District during the Long Rainy Season .................... 55 3.76 Planted Area applied with Fungicides by Crop Type ...................................................................................... 55 3.77 Percentage of Crop Type Planted Area applied with Fungicides..................................................................... 56 3.78 Proportion of Planted Area applied with Fungicides by District during the Long Rainy Season .................... 56 3.79 Area of Irrigated Land ..................................................................................................................................... 56 3.80 Planted Area and Percentage of Planted Area with Irrigation by District........................................................ 57 3.81 Time Series of Households with Irrigation – Tanga ........................................................................................ 57 8.82 Number of Households with Irrigation by Source of Water ............................................................................ 57 3.83 Number of Households by Method of Obtaining Irrigation Water.................................................................. 57 3.84 Number of Households with Irrigation by Method of Field Application......................................................... 59 3.85 Number of Households and Quantity Stored by Crop Type ............................................................................ 59 3.86 Number of households by Storage Methods.................................................................................................... 60 3.87 Number of households by method of storage and District (based on the most important household crop)..... 60 3.88 Normal Length of Storage for Selected Crops................................................................................................. 60 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District................................................. 62 3.90 Number of Households by Purpose of Storage and Crop Type ....................................................................... 62 3.91a Percentage of Households Processing Crops by District ................................................................................. 63 3.91b Percent of Households Processing Crops by District....................................................................................... 63 3.92 Percent of Crop Processing Households by Method of Processing ................................................................. 63 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xiv 3.93 Percent of Households by Type of Main Processed Product ........................................................................... 63 3.94 Number of Households by Type of By-product............................................................................................... 64 3.95 Use of Processed Product................................................................................................................................. 64 3.96 Percentage of Households Selling Processed Crops by District ...................................................................... 64 3.97 Location of Sale of Processed Products........................................................................................................... 64 3.98 Percent of Household selling Processed Products by Outlets for Sale and Distance........................................65 3.99 Number of Crop Growing Households Selling Crops by District.................................................................... 65 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem................... 65 3.101 Percentage Distribution of Households Receiving Credit by Main Sources.................................................... 66 3.102 Number of Households Receiving Credit by Main Source of Credit and District........................................... 66 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit................................................... 66 3.104 Reasons for Not using Credit (% of Household).............................................................................................. 66 3.105 Number of Households Receiving Extension Advice...................................................................................... 67 3.106 Number of Households Receiving Extension by District ................................................................................ 67 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider................................ 67 3.108 Number of Households Receiving Extension by Quality of Services.............................................................. 67 3.109 Number of Households by Source of Inorganic Fertiliser ............................................................................... 69 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser................................................. 69 3.111 Number of Households by Source of Improved Seed...................................................................................... 70 3.112 Number of Households reporting Distance to Source of Improved Seed ........................................................ 70 3.113 Number of Households by Source of Insecticide/Fungicide............................................................................ 70 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides.......................................... 70 3.115 Number of Households with Planted Trees by District.................................................................................... 71 3.116 Number of Planted Trees by Species ................................................................................................................71 3.117 Number of Trees Planted by Smallholders by Species and District................................................................. 71 3.118 Number of Trees Planted by Location ............................................................................................................. 71 3.119 Number of Households by purpose of Planted Trees....................................................................................... 72 3.120 Number of Households with Erosion Control/Water Harvesting Facilities..................................................... 72 3.121 Number of Households with Erosion Control/Water Harvesting Facilities by District................................... 72 3.122 Number of Erosion Control/Water Harvesting structures by Type of Facility ................................................ 72 3.123 Total Number of Cattle ('000') by District ....................................................................................................... 74 3.124 Numbers of Cattle by Type and District .......................................................................................................... 74 3.125 Cattle Population Trend................................................................................................................................... 76 3.126 Improved Cattle Population Trend................................................................................................................... 76 3.127 Total Number of Goats ('000') by District ....................................................................................................... 76 3.128 Goat Population Trend..................................................................................................................................... 78 3.129 Total Number of Sheep by District.................................................................................................................. 78 3.130 Sheep Population Trend................................................................................................................................... 80 3.131 Total Number of Pigs by District..................................................................................................................... 80 3.132 Pig Population Trend ....................................................................................................................................... 80 3.133 Total Number of Chicken by District .............................................................................................................. 82 3.134 Chicken Population Trend ............................................................................................................................... 82 3.135 Number of Improved Chicken by Type and District.........................................................................................84 3.136 Improved Chicken Population Trend............................................................................................................... 84 3.137 Percentage of Livestock Keeping Households Reporting Tsetse flies and Ticks Problems by District........... 84 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District........... 86 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services ....... 86 3.140 Number of Households by Distance to Veterinary Clinic................................................................................ 87 3.141 Number of Households by Distance to Veterinary Clinic and District............................................................ 87 3.142 Number of Households by Distance to Village Watering Point ...................................................................... 87 3.143 Number of Households by Distance to Watering Point and District................................................................ 87 3.144 Number of Households using Draft Animals................................................................................................... 87 3.145 Number of Households using Draft Animals by District................................................................................. 87 3.146 Number of Households using Organic Fertiliser.............................................................................................. 88 3.147 Area of Application of Organic Fertiliser by District ...................................................................................... 88 3.148 Number of Households Practicing Fish Farming – Tanga............................................................................... 88 3.149 Number of Households Practicing Fish Farming by District – Tanga............................................................. 91 3.150 Fish Production................................................................................................................................................ 91 3.151 Agricultural Households by Type of Toilet Facility ........................................................................................ 92 3.152 Percentage Distribution of Households Owning the Assets............................................................................. 92 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting .............................................92 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking ............................................ 92 3.155 Percentage Distribution of Households by Type of Roofing Material............................................................. 94 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xv 3.156 Percentage Distribution of Households with Grassy/Leafy Roofs by District................................................. 94 3.157 Percentage of Households by Main Source of Drinking Water and Season .................................................... 94 3.158 Percentage of Households by Distance to Main Source of Water and Season................................................. 94 3.159 Number of Agriculture Households by Number of Meals per day .................................................................. 95 3.160 Number of Households by Frequency of Meat and Fish Consumption............................................................95 3.161 Percentage Distribution of the Number of Households by Main Source of Income........................................ 97 List of Maps 3.1 Total Number of Agricultural Households by District..................................................................................... 12 3.2 Number of Agricultural Households per Square Km of Land by District........................................................ 12 3.3 Number of Crop Growing Households by District .......................................................................................... 13 3.4 Percent of Crop Growing Households by District ........................................................................................... 13 3.5 Number of Crop Growing Households per Square Kilometer of Land by District.......................................... 14 3.6 Percent of Crop and Livestock Households by District ................................................................................... 14 3.7 Utilized Land Area Expressed as a Percent of Available Land ....................................................................... 19 3.8 Total Planted Area (annual crops) by District.................................................................................................. 19 3.9 Area planted and Percentage During the Short Rainy Season by District........................................................ 21 3.10 Area Planted with Cereals and Percent of Total Land Planted with Cereals by District.................................. 21 3.11 Planted Area and Yield of Maize by District................................................................................................... 24 3.12 Area Planted per Maize Growing Household .................................................................................................. 24 3.13 Planted Area and Yield of Paddy by District................................................................................................... 25 3.14 Area Planted per Paddy Growing Household .................................................................................................. 25 3.15 Planted Area and Yield of Cassava by District................................................................................................ 29 3.16 Area Planted per Cassava Growing Household ............................................................................................... 29 3.17 Planted Area and Yield of Beans by District ................................................................................................... 31 3.18 Area Planted per Beans Growing Household................................................................................................... 31 3.19 Planted Area and Yield of Groundnuts by District .......................................................................................... 34 3.20 Area Planted per Groundnuts Growing Household.......................................................................................... 34 3.21 Planted Area and Yield of Tomato by District................................................................................................. 36 3.22 Area Planted per Tomato Growing Household................................................................................................ 36 3.23 Planted Area and Yield of Cabbage by District................................................................................................38 3.24 Area Planted per Cabbage Growing Household .............................................................................................. 38 3.25 Planted Area and Yield of Chillies by District................................................................................................. 39 3.26 Area Planted per Chillies Growing Household................................................................................................ 39 3.27 Planted Area and Yield of Cotton by District .................................................................................................. 41 3.28 Area Planted per Cotton Growing Household ................................................................................................. 41 3.29 Planted Area and Yield of Tobbaco by District............................................................................................... 42 3.30 Area Planted per Tobacco Growing Household............................................................................................... 42 3.31 Planted Area and Yield of Coconuts by District.............................................................................................. 44 3.32 Area Planted per Coconuts Growing Household ............................................................................................. 44 3.33 Planted Area and Yield of Oranges by District................................................................................................ 46 3.34 Area Planted per Orange Growing Household................................................................................................. 46 3.35 Planted Area and Yield of Banana by District................................................................................................. 47 3.36 Area Planted per Banana Growing Household ................................................................................................ 47 3.37 Planted Area and Yield of Cashew nut by District .......................................................................................... 49 3.38 Area Planted per Cashew nut Growing Household.......................................................................................... 49 3.39 Planted Area and Percent of Planted Area with No Application of Fertilizer by District................................ 58 3.40 Area Planted and Percent of Total Planted Area with Irrigation by District.................................................... 58 3.41 Percent of households storing crops for 3 to 6 weeks by district..................................................................... 61 3.42 Number of Households and Percent of Total Households Selling Crops by District....................................... 61 3.43 Number of Households and Percent of Total Households Receiving Crop Extension Services by District.... 68 3.44 Number and Percent of Crop Growing Households using Improved Seed by District ....................................68 3.45 Number and percent of smallholder planted trees by district........................................................................... 73 3.46 Number and Percent of Households with water Harvesting Bunds by District ............................................... 73 3.47 Cattle population by District as of 1st Octobers 2003 ......................................................................................75 3.48 Cattle Density by District as of 1st October 2003.............................................................................................75 3.49 Goat population by District as of 1st Octobers 2003 ....................................................................................... 77 3.50 Goat Density by District as of 1st October 2003 ............................................................................................. 77 3.51 Sheep population by District as of 1st Octobers 2003 ..................................................................................... 79 3.52 Sheep Density by District as of 1st October 2003 ........................................................................................... 79 3.53 Pig population by District as of 1st Octobers 2003.......................................................................................... 81 3.54 Pig Density by District as of 1st October 2003................................................................................................ 81 ILLUSTRATIONS ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census xvi 3.55 Number of Chickens by District as of 1st October 2003 ................................................................................. 83 3.56 Density of Chickens by District as of 1st October 2003.................................................................................. 83 3.57 Number and Percent of Households Infected with Ticks by District............................................................... 85 3.58 Number and Percent of Households Using Draft Animals by District ............................................................ 85 3.59 Number and Percent of Households Using Farm Yard Manure by District..................................................... 89 3.60 Number and Percent of Households using Compost by District...................................................................... 89 3.61 Number and Percent of Households Practicing Fish Farming by District ....................................................... 90 3.62 Number and Percent of Households without Toilets by District...................................................................... 90 3.63 Number and Percent of Households using Grass/Leaves for roofing material by District .............................. 93 3.64 Number and Percent of Households eating 3 meals per day by District.......................................................... 93 3.65 Number and Percent of Households eating Meat Once per Week by District ................................................. 96 3.66 Number and Percent of Households eating Fish Once per Week by District................................................... 96 3.67 Number and percent of Households Reporting food insufficiency by District ................................................ 98 INTRODUCTION _________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 1 1. BACKGROUND INFORMATION 1.1 Introduction This part of the report presents a brief description of the regional profile by providing information on geographical location, land area, climate, administrative set up, population and socio-economic indicators. The information will provide the user with a general understanding of the region and its resources. 1.2 Geographical Location and Boundaries Tanga region is situated at the North-East corner of Tanzania between 40 and 60degrees below the Equator and 370 – 39010’ degrees East of the Greenwich Meridian. Tanga shares borders with Kenya to the North, Morogoro and Coast regions to the South, Kilimanjaro and Arusha regions to the West and the Indian Ocean to the East. The region comprises seven districts namely Lushoto, Korogwe, Muheza, Tanga, Pangani, Handeni and Kilindi. The region headquarters is located in Tanga District. 1.3 Land Area The region has an area of 26,808 square kilometers, of which 17,000 square kilometers are arable land. 1.4 Climate 1.4.1 Temperature The dominant climate is warm and wet along the coast and inland of the Tanga region. The Western Plateau of Handeni district has a hot and dry climate and in the Usambara Mountain range a temperate climate is found. In most cases, there is no big variation of temperature at the coast due to the influence of the Indian Ocean. The coolest month is June with minimum temperature of 200C. The hottest month is December with maximum temperature of 320C. 1.4.2 Rainfall The region has two rainy seasons, the short and the long rainy seasons. The short rainy season (Vuli) is from October to November and the Long rainy season (Masika) from April to May. In Tanga region, most areas get rainfall of at least 750mm per year. The amount of rainfall is about 1,100 to 1,400mm along the coast, decreasing inland with the exception of the Usambara Mountains, where, depending upon the slope position and height, the amount of rainfall may exceed 2000mm per year. In the Maasai Plains (North West of Handeni) and in the dry plains of Korogwe, the average rainfall is below 600mm. 1.5 Population According to the 2002 Population and Housing Census, there were 1,642,015 inhabitants in Tanga region. The population of Tanga region ranked 10th of the 21 regions in Tanzania. INTRODUCTION _________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 2 1.6 Socio - Economic Indicators The regional Gross Domestic Product (GDP) at current prices for the year 2003 was estimated to be TShs 418,816 million with a per capita income of shillings 236,115. The region held 10th position among regions on GDP and contributed about 4.3 percent to the national GDP1 Tanga region is famous for limestone and gypsum mineral deposits, all of which are used in the cement factory situated in the region. It has many tourist attractions such as Mkomazi Game Reserve, Amboni Caves, Totten Islands, Tongoni Ruins, Pangani Beach and Hot Water Baths in Amboni and Amani Nature Reserve and has first class hotels (including Mkonge Hotel and Baobab Tree Inn) with conference facilities. The region is famous for producing both food and cash crops. The main food crops produced in Tanga region include: maize, paddy, beans and sorghum. The main cash crops include sisal and tea. Livestock keeping is also an important economic activity in the region. 1 Hali ya Uchumi wa Taifa Katika Mwaka 2003 INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 3 2. INTRODUCTION This part of the report provides the technical and operational description of the National Sample Census of Agriculture (NSCA), carried out in the rural areas of Tanzania Mainland and Zanzibar during the 2002/03 agricultural year. It details the background and the rationale for carrying out the NSCA in 2002/03 agricultural year. It also explains the sampling procedures, designing and implementation of the data processing system. 2.1 The Rationale for Conducting the National Sample Census of Agriculture In 2003, the Government of Tanzania launched the Agricultural Sample Census as an important part of the Poverty Monitoring Master Plan which supports the production of statistics for advocacy of effective public policy, including poverty reduction, access to services, gender, as well as the standard crop production data normally collected in an agriculture census. The census is intended to fill the information gap and support planning and policy formulation by high level decision making bodies. It is also meant to provide critical benchmark data for monitoring Agriculture Sector Development Programme (ASDP) and other agriculture and rural development programs as well as prioritising specific interventions of most agriculture and rural development programs. Following the decentralisation of the Government’s administration and planning functions, there has been a pressing need for agriculture and rural development data disaggregated at regional and district levels. The provision of district level estimates will provide essential baseline information on the state of agriculture and support decision making by the Local Government Authorities in the design of District Agricultural Development and Investment Projects (DADIPS). The increase in investment is an essential element in the national strategy for growth and reduction of poverty. This report (Volume V) is among the 21 regional reports for the mainland. Other Census reports include the Technical Report (Volume I), crop sector at national and regional levels including Zanzibar estimates (Volume II), Livestock Report (Volume III), Smallholder Household Characteristics and Access to Natural Resources Report (Volume IV), 21 Regional Reports for the Mainland (Volume V), Large Scale Farms Report (Volume VI) and a separate report for Zanzibar (Volume VII). In order to address the specific issue of gender, a separate thematic report on gender has been published. Other thematic reports will be produced depending on the demand and availability of funds. In addition to these reports two dissemination applications have been produced to allow users to create their own tabulations, charts and maps. The report is divided into five main sections: Background Information, Introduction, Results, Evaluation and Conclusion and Appendices. The definitions relating to all aspects of this report can be found in the questionnaire (Appendix III). 2.2 Census Objectives The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, Non government Organisations (NGOs), farmer organisations, etc. As a result, the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa. The census was carried out in order to: INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 4 Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc. 2.3 Census Coverage and Scope The census was conducted for both large and small scale farms. The National Sample Census of Agriculture covered a total of 3,221 selected rural villages of Tanzania Mainland out of which 215 villages were from Tanga region. The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three types of questionnaires: Small scale farm questionnaire Community level questionnaire Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; issues on poverty, gender and subsistence versus profit making production units. The main sections covered are as follows: Identification (i.e. region, district, ward and village) Household and holding characteristics Household information Land ownership/tenure Land use Access and use of resources Crop and vegetable production Agro processing and by-Products Crop storage and marketing On-farm investment Access to farm inputs and implements Use of credit for agricultural purposes Tree farming/agro-forestry Crop extension services Livelihood constraints Animal contribution to crop production Livestock INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 5 Livestock products Fish farming Livestock extension Labour use Access to infrastructure and other services Household facilities The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The large scale farm questionnaire was administered to large scale farms that were either privately or corporately managed. There will be a national report on large scale farming on Tanzania Mainland. 2.4 Legal Authority of the National Sample Census of Agriculture The NSCA 2002/03 was conducted under the legal authority of the 2000 National Bureau of Statistics Act which, among other things, makes data collected from individuals strictly confidential and to be used for statistical purposes only. 2.5 Reference Period Two types of reference periods were used namely the agricultural year and the reference date for livestock enumeration. The agricultural year 2002/03 (that is October 2002 to September 2003) was used for the data items that are related to crop production. The reference date of enumeration for livestock and poultry count was 1st October 2003. 2.6 Census Methodology The main focus at all stages of the census execution was on data quality and this is emphasised in this section. The main activities undertaken include: - Census organisation - Tabulation plan preparation - Sample design - Design of census questionnaires and other instruments. - Field pre-testing of the census instruments - Training of trainers, supervisors and enumerators - Information Education and Communication (IEC) campaign - Data Collection - Field supervision and consistency checks - Data processing: Scanning ICR extraction of data Structure formatting application Batch validation application Manual data entry application Tabulation preparation using SPSS - Table formatting and charts using Excel, map generation using Arc View and Freehand. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 6 - Report preparation using Word and Excel. 2.6.1 Census Organization The Census was conducted by the National Bureau of Statistics in collaboration with the sector ministries of agriculture, and the Office of the Chief Government Statistician in Zanzibar. At the national level the Census was headed by the Director General of the National Bureau of Statistics with assistance from the Director of Economic Statistics. The Planning Group, made up of staff from the National Bureau of Statistics, Department of Agricultural Statistics and three representatives from the Ministry of Agriculture and Food Security (Department of Policy and Planning), oversaw the overall operational aspects of the Census. At the regional level, implementation of census activities was overseen by the Regional Statistical Officer of NBS and the Regional Agriculture Supervisor from the Ministry of Agriculture and Food Security. At the District level, two supervisors from the President’s Office, Regional Administration and Local Government (PORALG), managed the enumerators who also came from the same ministry. Members of the Planning Group had a minimum qualification of a bachelor degree; the regional supervisors were agricultural economists, statisticians or statistical officers. The district supervisors and enumerators had diploma level qualifications in agriculture. The Census and Surveys Technical Working Group provided support in sourcing financing, approving budget allocations and technical assistance inputs as well as monitoring the progress of the census. A Technical Committee for the census was established with members from key stakeholder organisations (i.e. NBS, sector ministries of agriculture, President’s Office, Planning and Privatization (POPP), PORALG, University of Dar es Salaam (UDSM), Tanzania Food and Nutrition Centre (TFNC) and the Office of Chief Government Statistician (OCGS) in Zanzibar). The main function of the committee was to approve the proposed instruments and procedures developed by the Planning Group. It also approved the tabulations and analytical reports prepared from the Census data. 2.6.2 Tabulation Plan The tabulation plan was developed following three user group workshops and thus reflects the information needs of the end users. It took into consideration the tabulations from previous census and surveys to allow trend analysis and comparisons. 2.6.3 Sample Design The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. In most cases, within each selected village, data was collected from a sub-sample of fifteen agricultural households. In few large villages thirty households were selected. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 EAs were selected and 4,755 agricultural households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar). In both Mainland and Zanzibar a stratified two stage sample was used. In the first stage, villages/enumeration areas (EAs) were selected with probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of Number of Mainland Zanzibar Total Households 48,315 4,755 53,070 Villages/Eas 3,221 317 3,539 Districts 117 9 126 Regions 21 5 26 Table 2.1: Census Sample Size INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 7 farming households in each Village/EA using systematic random sampling. Table 2.1 gives the sample size of households, villages and districts for Tanzania Mainland and Zanzibar. 2.6.4 Questionnaire Design and Other Census Instruments The census questionnaires were designed following user/producer meetings to ensure that the information collected was in line with their data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of the data: Where feasible all variables were extensively coded to reduce post enumeration coding error. The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and ICR technologies for data entry. Skip patterns were used to avoid asking unnecessary questions Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications. Besides the questionnaires, there were other instruments used: Village listing forms that were used for listing households in the villages and from this list a systematic sample of 15 agricultural households were selected from each village. Training manual which was used by the trainers for the cascade/pyramid training of supervisors and enumerators. This manual was trainers guiding document on the procedures to follow during the training Enumerator Instruction Manual which was used as reference material. 2.6.5 Field Pre-Testing of the Census Instruments The Questionnaire was pre-tested in five locations (Arusha, Dodoma,,Tanga, Unguja and Pemba). This was done purposely to test the wording, flow and relevance of the questions and to finalise crop lists, questionnaire coding and manuals. In addition to this, several data collection methodologies had to be finalised, namely, livestock numbers in pastoralist communities, cut flower production, mixed cropping, use of percentages in the questionnaire and finalising skip patterns and documenting consistency checks. 2.6.6 Training of Trainers, Supervisors and Enumerators Cascade/pyramid training techniques were employed to maintain statistical standards. The top level training was provided to 66 national and regional supervisors (3 per region plus Zanzibar). The trainers were members of the Planning Group and the trainees were from the National Bureau of Statistics and the sector ministries of agriculture. The second level training was for the district supervisors and enumerators. This training was conducted in the regions. In each region three training sessions were conducted for the district supervisors and enumerators. In addition to training in field level Census methodology and definitions, emphasis was placed on training the enumerators and supervisors in consistency checking. Tests were given to the enumerators and supervisors and the best 50 percent of the trainees were selected to administer the smallholder and community level questionnaires. This increased the number of interviews per enumerator but it also released finance to increase the number of supervisors and hence the Supervisor Enumerator Ratio. The household listing exercise was carried out by all trained enumerators. INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 8 2.6.7 Information, Education and Communication (IEC) Campaign Information, Education and Communication (IEC) is an important aspect of any census/survey undertaking. This is due to the fact that inadequately informed and hence uncooperative citizens may jeopardize the entire census/survey. As far as the 2002/03 Agricultural Sample Census was concerned, the main objective of the IEC program was to sensitize and mobilize Tanzanians to support, cooperate and participate in the census exercise. Radio, television, newspapers, leaflets, t-shirts and caps were used to publicise the Sample Census. T-shirts and caps were used by the field staff and the village chairmen as official uniforms during the field work. The village chairmen helped to locate the selected households. 2.6.8 Household Listing The household listing exercise was done in seven days. During the listing exercise, forms ACLF1 and ACLF2 were administered. The information collected included the number of fields operated by the household, the number of different types of livestock and poultry. This information was used to determine the agricultural households. From the list of agricultural households, 15 households were selected for the interview. The selection was done using the Random Number Table. 2.6.9 Data Collection Data collection activities for the 2002/2003 Agricultural Sample Census took three months from January to March 2004. The data collection methods used during the census was by interview and no physical measurements, e.g., crop cutting and field area measurement were taken. Field work was monitored by a hierarchical system of supervisors at the top of which was the Mobile Response Team followed by the national, regional, and district supervisors. The Mobile Response Team consisted of three principal supervisors who provided overall direction to the field operation and responded to queries arising outside the scope of the training exercise. The mobile response team consisted of the Manager of Agriculture Statistics Department, Long-term Consultant and Desk Officer for the Census. Decisions made on definitions and procedures were then communicated back to all enumerators via the national, regional and district supervisors. District supervision and enumeration were done by staff from the President’s Office, Regional Administration and Local Government (PORALG). National and regional supervisions were provided by senior staff of the National Bureau of Statistics and the sector ministries of agriculture. During the household listing exercise 3,221 extension staff was used. For the enumeration of the small holder questionnaire, 1,611 enumerators were used and additional 5 percent enumerators were held in reserve in case of drop outs during the enumeration exercise. 2.6.10 Field Supervision and Consistency Checks Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded them in the questionnaire. The first check of the questionnaires was done by enumerators in the field during enumeration. The second check was done by the district supervisors followed by regional and national supervisors. Supervisory visits at all levels of supervision focused on consistency checking of the questionnaires. Inconsistencies encountered were corrected, and where necessary a return visit to the respondent was made by the enumerator to obtain the correct INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 9 information. Further quality control checks were made through a major post enumeration checking exercise where all questionnaires were checked for consistencies by all supervisors in the district offices. 2.6.11 Data Processing Data processing consisted of the following processes: Manual editing Data entry Data structure formatting Batch validation Tabulation Illustration production Report formatting Manual Editing Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys. Data entry/Scanning and ICR extraction technologies Scanning and ICR data capture technology was used for the small holder questionnaire. This not only increased the speed of data entry, it also increased the accuracy due to the reduction in keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended that this technology be adopted for future censuses/surveys. The Census and Surveys Processing Program (CSPro) was used to enter 2,880 of small holder questionnaires that were rejected by the Intelligent Character Recognition (ICR) extraction application. Data structure formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village Identification (ID) code and saved the data of one village in a file named after the village code. Batch validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to more complexes checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaire. After the long process of data cleaning, the results were prepared based on a pre-designed tabulation plan. Tabulations INTRODUCTION _________________________________________________________________________________________ ___________________________________________________________________________________________________________________________ _ Tanzania Agriculture Sample Census 10 Statistical Package for Social Sciences (SPSS) was used to produce the Census results and Microsoft Excel was used to organize the tables and compute additional indicators. Analysis and report preparation The analysis in this report focuses on regional and district production estimates, districts comparisons and time series analysis. Microsoft Excel was used to produce charts; whereas Microsoft Word was used to compile the report. Data quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this NBS believes that the Census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables can be found in the Technical Report (Volume I). 2.7 Funding Arrangements The Agricultural Sample Census was supported mainly by the European Union (EU) who financed most of the operational activities. Other funds for operational activities came from the Government of Tanzania, Government of Japan, United Nations Development Programme (UNDP) and other partners in the Pool Fund of the Vice President’s Office (VPO). In addition to this, technical assistance was provided by the European Union (EU), Department for International Development (DFID) and Japanese International Cooperation Agency (JICA). Technical assistances were managed by Ultek Laurence Gould Consultants (ULG), Scotts Agriculture Consultancy Ltd (SAC) and the Food and Agriculture Organisation (FAO). RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 11 3. CENSUS RESULTS This part of the report presents the results of the census data for Tanga region. Which are based on the data tables presented in Appendix A2. The results are presented in different forms including brief summaries, charts, condensed tables and graphs and Maps in order to make it easier for the users to understand. Comparisons are made between related variables and between districts. Comparisons are also made with past censuses/surveys results such as the 1994/95 National Sample Census of Agriculture (NSCA), the 1995/96 and the 1996/97 Expanded Agricultural Surveys, the 1997/98 Integrated Agricultural Surveys, the 1998/99 District Integrated Agricultural Survey and the 1999/00 Rapid Agricultural Appraisal Survey. . The presentation of results is divided into four main sections which are household characteristics, crop results, livestock results and Poverty indicators. More effort has been placed in analyzing the results in order to formulate solid conclusions than in previous censuses and surveys. 3.1 Household Characteristics 3.1.1 Type of Household The number of agricultural households in Tanga region was 265,198. The largest number of agriculture households was in Lushoto (86.580) followed by Muheza (49,195), Handeni (47739), Korogwe (45,990) Kilindi, (19,654) Tanga (8,914) and Pangani (7,128) (Map 3.1). The highest density of households was found in Tanga (74/km2) and Lushoto (63%) (Map 3.2). Most households (178,406, 67.2%) were involved in growing crops only, 1,477 (0.6%) rearing livestock only, 194 (0.1%) pastoralists, and 85,121 (32.1%) were involved in crop production as well as livestock keeping (Chart 3.1) (Map 3.3, 3.4, 3.5 and 3.6). 3.1.2 Livelihood Activities/Source of Income The census results for Tanga region indicates that most of the agricultural households ranked annual crop farming as an activity that provides most of their cash income followed by off farm Income, fishing/hunting tree/forest resources, permanent crop farming, livestock keeping/herding and remittances (Table 3.1). Tanga and Pangani districts are the only ones whereby annual crop farming was not the most important source of livelihood, being replaced by Off-farm income 3.1.3 Sex and Age of Head of Households The number of male-headed agricultural households in Tanga region was 200,432 (76% of the total regional agricultural households) whilst in female-headed households it was 64,766 (24% of the total regional agricultural households). The mean age of household heads is 45 years (44 years for male heads and 49 years for female heads) (Chart 3.2) Table 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District Livelihood Activity District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remitt -ances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1 3 6 2 7 4 5 Korogwe 1 5 6 2 7 3 4 Muheza 1 2 6 5 7 4 3 Tanga 3 2 5 1 6 7 4 Pangani 2 5 6 1 7 4 3 Handeni 1 6 5 2 7 3 4 Kilindi 1 6 5 2 7 3 4 Total 1 5 6 2 7 3 4 Chart 3.1 Agriculture Households by Type - Tanga Pastoralists 0.1% Livestock Only 0.6% Crops Only 67.3% Crops and Livestock 32.1% Chart 3.2 Percentage Distribution of Agricultural Households by Sex of Household Head 0 25 50 75 100 NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Year Percent of Households Male headed households Female headed households Handeni Muheza Pangani Lushoto Kilindi 8,914 47,739 49,195 45,990 Tanga Korogwe 19,654 7,128 86,580 Total Number of Agricultural Households by District 70,700 to 86,600 54,800 to 70,700 38,900 to 54,800 23,000 to 38,900 7,100 to 23,000 Number of Agriculture Households MAP 3.1 TANGA 74 30 30 63 14 9 11 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 61 to 74 48 to 61 35 to 48 22 to 35 9 to 22 Agricultural Households per Square Km MAP 3.2 TANGA Number of Agricultural Households per Square Kilometer of Land by District Tanzania Agriculture Sample Census RESULTS 12 37,830 48,594 14,833 32,853 6,216 6,974 31,105 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto Number of Crop Growing Households by District MAP 3.3 TANGA 40,200 to 48,600 31,700 to 40,200 23,200 to 31,700 14,700 to 23,200 6,200 to 14,700 Crops Growing Households 75% 87% 78% 69% 68% 77% 56% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.4 TANGA Percent of Crop Growing Households by District 80.8 to 87 74.6 to 80.8 68.4 to 74.6 62.2 to 68.4 56 to 62.2 Percent of Crop Growing Households Tanzania Agriculture Sample Census RESULTS 13 9 58 23 35 20 10 6 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.5 TANGA Number of Crop Growing Households per Square Kilometer of Land by District 47.6 to 58 37.2 to 47.6 26.8 to 37.2 16.4 to 26.8 6 to 16.4 Crop Growing Households per Sq Km 18% 12% 23% 31% 32% 22% 44% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.6 TANGA Percent of Crop and Livestock Households by District 37.6 to 44 31.2 to 37.6 24.8 to 31.2 18.4 to 24.8 12 to 18.4 Percent of Crop and Livestock Households Tanzania Agriculture Sample Census RESULTS 14 RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 15 The percentage trend for six censuses/surveys years shows that there has not been any significant change in the distribution of agricultural households between male and female headed households. 3.1.4 Number and Age of Household Members Tanga region had a total rural agricultural population of 1,296,031 of which 633,967 (49%) were males and 662,064 (51%) were females. Whereas age group 0-14 constituted 44 percent of the total rural agricultural population, age group 15–64 (active population) was only 51 percent. Tanga region had an average household size of 5 with Pangani district having the lowest household size of 4 (Chart 3.3). 3.1.5 Level of Education In order to obtain information on the level of education, information on literacy and education attainment were obtained for all persons aged five years and above in all households. Literacy The information on literacy level for family members aged five years and above was obtained by asking individual private households if their respective family members could read and write in Kiswahili only, English only, both English and Swahili or in any other language. Literacy is based on the ability to read and write Swahili, English or both. Literacy Level for Household Members Tanga region had a total literacy rate of 70 percent. The highest literacy rate was found in Pangani district (70%) followed by Tanga district (68%) and Lushoto district (65%). Kilindi and Handeni districts had the lowest literacy rates of 44 and 53 percent respectively (Chart 3.4). Literacy Rates for Heads of Households The literacy rate for the heads of households in the region was 73.6 percent. The literacy rates among the male and female heads of households were 82 and 48 percent respectively. Male head of household literacy rate was higher than that of females in all districts. The district with the highest literacy rate amongst heads of households was Pangani (79.4%) followed by Lushoto (76.4%), Muheza (75.4%), Korogwe (74.8%), Tanga (73.5%), Handeni (71.3%) and Kilindi (58.4%) (Chart 3.5). Chart 3.3 Percent Distribution of Population by Age and Sex - TANGA 0 6 12 18 00 - 04 05 - 09 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 59 60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85 + Age Group Percent Male Female Chart 3.4 Percent Literatecy Level of Household Members by District 0 20 40 60 80 Pangani Tanga Lushoto Muheza Korogwe Handeni Kilindi District Percent Chart 3.5 Literacy Rates of Head of Household by Sex and District - TANGA 0.0 25.0 50.0 75.0 100.0 Pangani Lushoto Muheza Korogwe Total Tanga Handeni Kilindi District Percent Male Female Total RESULTS – Household Characteristics __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 16 Educational Status Information on educational status was collected from individual agricultural households. The results show that 42.8 percent of the population aged 5 years and above in agricultural households in the region had completed different levels of education and 33.5 percent were still attending school. Those who have never attended school were 23.7 percent (Chart 3.6). Agricultural households in Korogwe district had the highest percentage (49.2%) of population aged 5 years and above who had completed different levels of education. This was followed by Muheza and Pangani districts with 47.3 and 46 percent respectively. Kilindi and Handeni districts had the lowest percentages of 31.2 and 38.7. The number of heads of agricultural households with formal education in Tanga region was 191,081 (72%), those without formal education were 70,819 (27%) and those with only adult education were 3,298 (1%). The majority of heads of agricultural households (69%) had primary level education whereas only 3 percent had post primary education. With regard to the heads of agricultural households with primary or secondary education in Tanga region, Lushoto district had the highest percentages (34% for primary and 26% for secondary). This was followed by Muheza (19% primary and 20% secondary), Korogwe (18% primary and 26% secondary) and Handeni (17% primary and 11% secondary). Pangani had the lowest percentage of heads of agricultural households with both primary education (3%) and secondary education (3%) (Chart 3.8). 3.1.6 Off-farm Income Off-farm income refers to cash generated from non-agricultural activities. This can be either from permanent employment (i.e., government, private sector or other), temporary employment or labourers. It also includes cash generated from working on farms belonging to other farmers. Off-farm income is important amongst agriculture households in Tanga with 73 percent of households having at least one member with off-farm income. In Tanga region 146,351 households (55%) had only one member aged 5 and above involved in only one off-farm income generating activity, 34,169 households (13%) had two members involved in off-farm income generating activities and 12,023 households (5%) had more than two members involved in off-farm income generating activities. Chart 3.6 Percentage of Persons Aged 5 Years and Above by Education Status Completed 42.8% Never Attended 23.7% Attending School 33.5% Chart 3.7 Percentage of Population Aged 5 Years and Above by District and Educational Status 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Korogwe Muheza Pangani Lushoto Tanga Handeni Kilindi District Percent Attending School Completed Never Attended Chart 3 .8 Percentage Distribution of Heads of Household by Educational Attainment Adult Education 1% Post Primary Education 3% No Education 27% Primary Education 69% RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 17 Tanga district had the highest percentage of agriculture households with off-farm income (over 90% of total agriculture households in the district). Other districts with high percent of agriculture households with off-farm income were Pangani (85%), Korogwe (85%), Kilindi (82%) and Handeni (80%). Muheza and Lushoto districts had the lowest percent of agriculture households with off-farm income (63% and 60% respectively). The district with the highest percent of agriculture households with more than one member with off-farm income was Tanga (50%). Lushoto district had very few households with more than one member having off-farm income (9%). 3.2 Land Use Land area and planted area are two different types of area measurements. Land area refers to the physical area of land and is the same regardless of the number of crops planted on the land in one year. Planted area is the total area of crops planted in a year and the area is summed if there were more than one crop on the same land per year. A number of terms are used in this section which requires defining for clarification as follows: Land available refers to the area of land that has been allocated to smallholders through customary law, official title or other forms of ownership. Land available does NOT mean the total area of land that is designated as agriculture land in the country; however it is the land that is available to smallholders given the location of villages and lack of access to more remote parcels of unused agriculture designated land. Usable land refers to the available land minus the land that cannot be used e.g. bare rock, shallow soils, steep slopes, swamp areas etc. It does however include un-cleared bush, Utilised land refers to the land that was used during the year. 3.2.1 Area of Land Utilised The total area of land available to smallholders was 524,451 ha. The regional average land area utilised for agriculture per household was only 1.7 ha. This figure is below the national average which is estimated at 2.0 hectares. Eighty eight percent of the total land available to smallholders was utilised. Only 11.1 percent of usable land available to smallholders was not used (Chart 3.11). Large differences in land area utilised per household exist between districts with Handeni and Kilindi utilizing between 2.5 and 2.6 ha per household. The smallest land area utilised per household is found in Lushoto (1.1 ha). The percentage utilized of the usable land per household is highest in Lushoto (99%) Chart 3.9 Number of Household by Number of Members with Off-farm Income One, 146,351, 55% Two, 34,169, 13% More than Two, 12,023, 5% None, 72,655, 27% Chart 3.10 Percentage Distribution of Agricultural Households by Number of Off-farm Activities 0% 20% 40% 60% 80% 100% Tanga Handeni Pangani Korogwe Kilindi Muheza Lushoto Districts Percent Mo re than Two Two One No ne Chart 3.11 Utilized and Usable Land per Household by District 0.0 1.0 2.0 3.0 4.0 Handeni Kilindi Pangani Muheza Tanga Korogwe Lushoto Districts Area/household 0 20 40 60 80 100 120 Percentage utilized Total Usable Area available (ha) Area utilised (Ha) Percent Utilisation RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 18 and lowest in Tanga (76%). Eighty eight percent of the total land available to smallholders was utilised. Only 11.1 percent of usable land available to smallholders was not used (Chart 3.11 and Map 3.7). 3.2.2 Types of Land Use The area of land under temporary monocrop was 167,575 hectares (32% of the total land available to smallholders in Tanga), followed by permanent/annual mix (81,938 ha, 15.6%), temporary mixed crops (78,356 ha, 14.9%), uncultivatable usable land (57,053 ha, 10.9%), area under fallow (43,926 ha, 8.4%), permanent mixed crop (40,080 ha, 7.6%), permanent monocrop (33,108 ha, 6.3%), unusable area (9,597 ha, 1.8%), area rented to others (4,236 ha, 0.8%), area planted with trees (3,959 ha, 0.8%), area under natural bush (2,771 ha, 0.5%) and area under pasture (1,852 ha, 0.4%). 3.3 Annual Crop and Vegetable Production Tanga region has two rainy seasons, namely the short rainy season (October to November) and the long rainy season (April to May). The quantity of crops produced in both seasons will be used as a base for comparison with the past surveys and censuses. 3.3.1 Area Planted The area planted with annual crops and vegetables was 428,533 hectares out of which 160,820 hectares (37.5%) were planted during short rainy season and 267,713 hectares (62.5%) during long rainy season. The average areas planted per household during the short and long rainy seasons was 0.8 and 1.0 ha respectively (Chart 3.13). The districts with the largest area planted per household (the average of the two seasons) were Kilindi (1.5 ha) followed by Handeni (1.3 ha). The district with the smallest average area planted was Tanga (0.77ha). While in Lushoto district the average area planted during the short rainy season in higher than that of the long rainy season the reverse is true in the rest of the districts (Chart 3.14 and Map 3.8). The planted area occupied by cereals was 295,529 ha (69.0%of the total area planted with annuals). This was followed by pulses (77,017 hectares, 18.0%), roots and tubers (47,614 hectares, 11.1%), fruit and vegetables (5,346 hectares, 1.2%), oil seeds (2,564 hectares, 0.6%) and cash Chart 3.12 Land Area by Type of Use 0.4 0.5 0.8 0.8 1.8 6.3 7.6 8.4 10.9 14.9 32.0 15.6 0 50,000 100,000 150,000 200,000 Pasture Natural Bush Planted Trees Rented to Others Unusable Permanent Mono Crops Permanent Mixed Crops Fallow Uncultivated Usable Land Temporary Mixed Crops Permanent / Annual Mix Temporary Mono Crops Land Use Area (hectares) Chart 3.13 Area Planted with Annual Crops by Season (hectares) Long Rainy Season, 267,714, 62% Short Rainy Season, 160,820, 38% Long Rainy Season Short Rainy Season Chart 3.14 Area Planted with Annual Crops by Season and Region 0 20,000 40,000 60,000 80,000 Lushoto Pangani Tanga Muheza Handeni Korogwe Kilindi Region Area Planted (ha) 0.00 20.00 40.00 60.00 80.00 Percentage Planted Short Rainy Season Long Rainy Season % Area planted in short rainy season 89% 89% 84% 84% 76% 89% 99% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.7 TANGA Utilized Land Area Expressed as a Percent of Available Land by Distrct 94.4 to 99 89.8 to 94.4 85.2 to 89.8 80.6 to 85.2 76 to 80.6 Percent of Utilized Land Area Pangani 8,198ha 10,260ha 111,249ha 43,153ha 69,468ha 61,078ha 125,020ha Kilindi Handeni Tanga Korogwe Muheza Lushoto MAP 3.8 TANGA Total Planted Area (Annual Crops) by District 104,000 to 126,000 80,000 to 104,000 56,000 to 80,000 32,000 to 56,000 8,000 to 32,000 Total Planted Area Tanzania Agriculture Sample Census RESULTS 19 RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 20 Crops (465 hectares, 0.1%). The average area planted per household during the long rainy season in Tanga region was 0.82 hectares, however, there were large district differences. Kilindi had the largest planted area per household (2.8 ha) followed by Pangani (2.5 ha) and Korogwe (1.7 ha). The smallest planted area per household is in Muheza (1.1 ha). In Lushoto the area planted per household in the short rainy season represents 58 percent of the total planted area per household, whereas in Kilindi the corresponding figure is 24 percent (Chart 3.15 and Map 3.9). Analysis of the Most Important Crops Results on crop production are presented in two different sections. The first section compares the importance of each crop regardless of whether they are annual or permanent. The second section contains a more detailed analysis on production based on crop types. 3.3.2 Crop Importance Maize is the dominant annual crop grown in Tanga region and it had a planted area 4.56 times greater than beans, which had the second largest planted area. The area planted with maize constitutes 67 percent of the total area planted with annual crops in the region. Other crops in order of their importance (based on area planted) are cassava, Irish potatoes, cowpeas, paddy and tomatoes (Chart 3.16). Households that grow sorghum, maize and cowpeas have larger planted areas per household than for other crops (Chart 3.17a). 3.3.3 Crop Types Cereals are the main crops grown in Tanga region. The area planted with cereals was 295,529 ha (69.0% of the total planted area), followed by pulses with 77,017 ha (18.0%), root and tubers 47,614 ha (11.1%), fruits and vegetables 5,346 ha (1.2%) and oil seeds 2,564 ha (0.6%). Annual cash crops that are mainly constituted of cotton and tobacco had got the least planted area of about 465 ha (0.1%) (Chart 3.17b). Chart 3.15 Area Planted with Annual Crops per Household by Season and District 0.00 1.00 2.00 3.00 Kilindi Pangani Handeni Korogwe Tanga Lushoto Muheza District Area Planted (ha) Long Rainy Season Short Rainy Season Chart 3.16 Planted Area (ha) for the Main Crops Tanga 0 100,000 200,000 300,000 Maize Beans Cassava Irish Potatoes Cowpeas Paddy Tomatoes Green Gram Groundnuts Sweet Potatoes Cabbage Simsim Chillies Crop Planted Area (ha) Chart 3.17a Planted Area (ha) per Household by Selected Crop - TANGA 0.00 0.50 1.00 1.50 2.00 Sorghum Maize Cowpeas Water Mellon Sunflower Beans Simsim Irish Potatoes Carrot Green Gram Cotton Tomatoes Yams Cocoyam Chillies Paddy Groundnuts Crop Planted Area (ha) Tanga 3,902ha 2,335ha 24,062ha 34,643ha 9,928ha 16,755ha 69,194ha 28% 35% 27% 31% 23% 55% 38% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.9 TANGA Area Planted and Percentage During the Short Rainy Season by District 55,900 to 69,200 42,500 to 55,900 29,100 to 42,500 15,700 to 29,100 2,300 to 15,700 Area Planted During Short Rain Season Area Planted (ha) Percent of Area Planted Tanzania Agriculture Sample Census RESULTS 21 Tanga Korogwe 7,565ha 4,504ha 97,042ha 52,422ha 49,028ha 32,678ha 52,289ha 74% 55% 75% 87% 80% 76% 42% Kilindi Handeni Pangani Muheza Lushoto MAP 3.10TANGA Area Planted with Cereals and Percent of Total Land Planted with Cereals by District 78,500 to 97,100 60,000 to 78,500 41,500 to 60,000 23,000 to 41,500 4,500 to 23,000 Area Planted (ha) Planted Area With Cereal Crops Percent of Total Land Planted With Cereals RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 22 Cereals and pulses are the dominant crops in both seasons and other crop types are of minor importance in comparison. There is little difference in the proportions of the different crop types grown between seasons and because short rainy season production was very small compared to long rainy season it is inappropriate to make detailed comparisons between the two seasons (Chart 3.18). 3.3.4 Cereal Crop Production The total production of cereals was 180,987 tonnes. Maize was the dominant cereal crop at 173,602 tonnes which was 96 percent of total cereal crops produced, followed by paddy (4%) sorghum (0.19%), wheat (0.03%) and finger millet (0.01%).Handeni district had the largest planted area of Cereals in the region (97,042ha) followed by Lushoto, (51,118ha), Muheza (50,778ha) and Korogwe 46,369) (Map 3.10). The total area planted with cereals during the short and long rainy seasons was 295,529 ha out of which 111,875 ha (37.8%) were planted in short rainy season and 183,654 ha (62.1%) were planted during the long rainy season. The long rainy season accounts for 64 percent of the total cereals produced in both seasons. The area planted with maize during the short rainy season was 98.4 percent of the total area planted with cereals in that season followed by Paddy (1.6%) and Sorghum (0.1%) (Table 3.2). The area planted with maize was dominant and it represented 97.3 percent of the total area planted with cereal crops, then followed by paddy (2.59%), wheat 0.07%), Sorghum 0.04%) and finger millet 0.02%). The yield of paddy was 908 kg/ha, followed by maize (604 kg/ha), finger millet (346 kg/ha) and wheat (280 kg/ha). Bulrush millet and barley were not grown in the region (Chart 3.19). Table 3.2: Area, Production and Yield of Cereal Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tonnes) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Maize 110,043 61,910 563 177,433 111,692 629 287,476 173,602 604 Paddy 1,735 3,488 2,010 5,930 3,472 585 7,665 6,960 908 Sorghum 97 338 3,485 19 7 357 116 345 2969 Finger Millet 0 0 0 66 23 346 66 23 346 Wheat 0 0 0 205 57 280 205 57 280 Total 111,875 65,736 183,654 115,251 295,529 180,987 111,875 42,393 34,624 36,856 10,759 2,525 2,821 1,839 725 448 17 0 100,000 200,000 300,000 Area (hectares) Cereals Pulses Roots & Tubers Fruits & Vegetables Oil seeds & Oil Nuts Cash Crops Crop Type Chart 3.18 Area Planted with Annual Crops by Crop Type and Season Long Rainy Season Short Rainy Season Chart 3.19 Area Planted and Yield of Major Cereal Crops 0 100,000 200,000 300,000 Maize Paddy Wheat Sorghum Finger Millet Crop Area Planted (ha) 0.00 1.00 2.00 3.00 4.00 Yield (t/ha) Area Planted (ha) Yield (t/ha) Chart 3.17b: Percentage Distribution of Area planted w ith Annual Crops by Crop Type Oil seeds & Oil nuts, 0.6% Roots & Tubers, 11.1% Fruits & Vegetables, 1.2% Cash crops, 0.1% Pulses, 18.0, % Cereals, 69.0% RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 23 3.3.4.1 Maize Maize dominates the production of cereal crops in the region. The number of households growing maize in Tanga region during the long rainy season was 189,772, (81% of the total crop growing households in the region during the long rainy season). The total production of maize was 173,602 tonnes from a planted area of 287,476 hectares resulting in a yield of 0.6 t/ha. Chart 3.20 indicates maize production trend (in thousand metric tonnes) for the combined long and short rainy seasons. There was a sharp increase in maize production (122%) over the period of 1998 to 1999 after which the production remained constant until 2003. The average area planted with maize per household was 0.91 hectares; however it ranged from 0.4 hectares in Lushoto district to 1.4 hectares in Kilindi district (Map 3.12). Handeni district had the largest area of maize (95,688 ha) followed by Lushoto (51,118 ha), Muheza (50,778 ha), Korogwe (46,369 ha), Kilindi (32,536 ha), Pangani (7,042 ha) and Tanga (3,946 ha) (Chart 3.21 and Map 3.11). Charts 3.20 and 3.22 show that, whilst the yield of maize has dropped over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with maize remained constant over the period from 1994 to 1996 after which the area under production expanded gradually until 2000 and the area has remained constant ever since. However, the yield of maize has shown a gradual decline over the period 1996 to 2003 (from 1.3t/ha in 1995 to 0.6 t/ha in 2003) (Chart 3.22). 3.3.4.2 Paddy Paddy is the second most important cereal crop in the region in terms of planted area. The number of households that grew paddy in Tanga region during the long rainy season was 15,443. This represents 66 percent of the total crop growing households in Tanga region in the long rainy season. The total production of paddy was 6,960 tonnes from a planted area of 7,665 hectares resulting in a yield of 0.91 t/ha. The district with the largest area planted with Paddy was Korogwe (2,659 ha) followed by Muheza (1,644 ha), Handeni (1,245 ha), Lushoto (931 ha), Tanga (545 ha), Pangani (500 ha) and Kilindi (142 ha) (Map 3.13). There are small insignificant variations in the average area planted per crop growing household among the districts ranging from 0.32 ha in Muheza to 0.45 ha in Handeni (Chart 3.23 and Map 3.14) Chart 3.20: Time Series Data on Maize Production - TANGA 320 166 126 174 306 138 197 0 100 200 300 400 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Census/Survey year Production ('000') tonnes Chart 3.21 Maize: Total Area Planted and Planted Area per Household by District 3,946 7,042 32,536 46,369 50,778 51,118 95,688 0 20,000 40,000 60,000 80,000 100,000 120,000 Handeni Lushoto Muheza Korogwe Kilindi Pangani Tanga District Area (Ha) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Area Planted per Household Area planted (ha) Area planted/hh Chart 3.22 Time Series of Maize Planted Area & Yield -TANGA 0 100000 200000 300000 400000 500000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 Yield (t/ha) Area Yield Korogwe Tanga 46,369ha 7,042ha 3,946ha 95,688ha 32,536ha 50,778ha 51,118ha 0.5t/ha 0.4t/ha 0.8t/ha 0.7t/ha 0.5t/ha 0.3t/ha 0.6t/ha Kilindi Handeni Pangani Muheza Lushoto MAP 3.11 TANGA Planted Area and Yield of Maize by District 79,000 to 96,000 60,000 to 79,000 41,000 to 60,000 22,000 to 41,000 3,000 to 22,000 Maize Planted Area (ha) Planted Area Yield (t/ha) (ha) Tanzania Agriculture Sample Census RESULTS 24 Tanga Korogwe 0.8ha 0.5ha 0.7ha 1.5ha 1.4ha 0.8ha 0.4ha Kilindi Handeni Pangani Muheza Lushoto MAP 3.12 TANGA Area Planted per Maize Growing Household by District 1.2 to 1.5 1 to 1.2 0.8 to 1 0.6 to 0.8 0.4 to 0.6 Area Planted Per Household Planted Area Per Household (ha) Tanga Korogwe 545ha 500ha 1,644ha 931ha 2,659ha 1,245ha 142ha 0.2t/ha 0.9t/ha 0.5t/ha 0.3t/ha 0.5t/ha 1.3t/ha 1.5t/ha Kilindi Handeni Pangani Muheza Lushoto Planted Area and Yield of Paddy by District MAP 3.13 TANGA 2,140 to 2,660 1,640 to 2,140 1,140 to 1,640 640 to 1,140 140 to 640 Paddy Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 25 Korogwe 0.43ha 0.38ha 0.45ha 0.39ha 0.31ha 0.42ha 0.38ha Kilindi Handeni Pangani Tanga Muheza Lushoto MAP 3.14 TANGA Area Planted Per Paddy Growing Household by District 0.43 to 0.45 0.4 to 0.43 0.37 to 0.4 0.34 to 0.37 0.31 to 0.34 Area Planted Per Household Area Planted Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 26 There was a sharp rise in the production of paddy in 1996/97 compared to 1995/96. The production rose from 8,000 tons in 1995/96 to 26,000 tonnes in 1996/97 after which it dropped to 5,000 tonnes in the following year. Thereafter the yield increased gradually to 16,000 tonnes in 1999/2000 and this was followed by another decline in 2002/03 to 7,000 tonnes. Charts 3.23 and 3.25 show that, whilst the yield of paddy has dropped dramatically over the previous 10 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with paddy remained constant over the period from 1995 to 2003 after which the area under production expanded rapidly until 1999 after which it declined to 7,500 ha in 2003. Over the period 1995 to 1997 the yield of paddy fluctuated at around 3t/ha. However, there was a sharp decline in yield over the period 1996 to 1998 (down to 0.5 t/ha) and it has remained at this low level since then (Chart 3.25). 3.3.4.3 Other Cereals Other cereals are produced in small quantities. A small quantity of Sorghum is produced in Handeni (43 ha), Lushoto (35 ha), Pangani (24 ha) and Tanga (14 ha). Fingermillet is produced in Handeni district only (66 ha) and wheat is produced in Lushoto district only (205 ha) (Chart 3.26). 3.3.5 Roots and Tuber Crops Production The total production of roots and tubers was 66,967 tonnes. Cassava production was higher than any other root and tuber crop in the region with a total production of 44,500 tonnes representing 67.5 percent of the total root and tuber crops production. This was followed by Irish potatoes with 20,736 tonnes (30%), sweet potatoes (1,002t, 1.4%), coco yams (675t, 1.0%) and yams (55t, 0.1%) (Table 3.3). The area planted Chart 3.23 Total Planted Area and Area of Paddy per Household by District 2,659 1,644 1,245 931 545 500 142 0 500 1,000 1,500 2,000 2,500 3,000 Korogwe Muheza Handeni Lushoto Tanga Pangani Kilindi District Area (Ha) 0.00 0.10 0.20 0.30 0.40 0.50 Area planted per household Planted Area (ha) Area planted/hh Chart 3.24 Time Series Data on Paddy Production - TANGA 8 7 7 13 5 26 16 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/200 2002/03 Census/Survey year Production ('000') tons 0 50 100 150 200 250 Area (Ha) Handeni Lushoto Pangani Tanga Korogwe Muheza Kilindi District Chart 3.26 Area Planted with Sorghum, Fingermillet and Wheat by District Sorghum Fingermillet Wheat Chart 3.27 Area Planted and Yield of Major Root and Tuber Crops 0 10,000 20,000 30,000 Cassava Sweet Potatoes Irish Potatoes Yams Cocoyam Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Chart 3.25 Time Series of Paddy Planted Area and Yield - TANGA 0 2500 5000 7500 10000 12500 15000 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Yield (t/ha) Planted Area Yield RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 27 with cassava was larger than any other root and tuber crops and it was the most important root and tuber crop in Tanga in terms of planted area accounting for 64.5 percent of the area planted with roots and tubers, followed by Irish potatoes (32.3%), sweet potatoes (2.3%), cocoyams (0.6%) and yams (0.3%). It is difficult to determine the total planted area and production for the short and long rainy seasons for roots and tubers as the total production of cassava was reported under the long rainy season. However, excluding cassava, 54 percent of the area planted with roots and tubers was during the short rainy season. Cocoyams and Irish potatoes had a larger planted area in the short rainy season (68 percent and 54 respectively). However sweet potatoes had a larger planted area in the long rainy season (55.3%). The percentage planted area of yams during the short rainy season was estimated at 39 percent. There was a significant increase in area planted with cassava and Irish potatoes from 1994/95 to 2002/03. The area for sweet potato and yams remained more or less constant. The total production of roots and tubers was estimated at 66,966 tonnes. Cassava with an estimate of 44,500 tonnes was the most important root and tuber crop. It accounted for 66.9 percent of the total roots and tubers production, followed by Irish potatoes with 20,736 tonnes (30.5%), sweet potatoes with 1,002 tonnes (1.5%), cocoyams with 675 tonnes (1.0%) and yams with 55 tonnes (0.1%). The estimated yield was high for cocoyams (2.5 t/ha) and cassava (2.3 t/ha), followed by Irish potatoes (1.3 t/ha), sweet potatoes (0.9 t/ha) and yams (0.4 t/ha). 3.3.5.1 Cassava The number of households growing cassava in the region was 78,627. This represents 30 percent of the total crop growing households in the region. The total production of cassava during the census year was 45,499 tonnes from a planted area of 30,732 hectares resulting in a yield of 2.4t/ha. Previous censuses and surveys indicate that the area planted with cassava increased for the period 1996 to 1999. Since 1999 the area planted with cassava dropped from 43,000 ha to 30,732 ha (Chart 3.28). The area planted with cassava accounted for 7 percent of the total area planted with annual crops and vegetables in the census year. Muheza district had the largest planted area of cassava (11,772 ha, 38% of the cassava planted area in the region), followed by Lushoto (6,457 ha, 21%), Korogwe (4,020 ha, 13%), Handeni (3,162 ha, 10%) Tanga (2,730 ha, 9%), Kilindi (1,475 ha, 5%) and Pangani (1,117 ha, 4%) (Map Table 3.3: Area, Production and Yield of Root and Tuber Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Cassava 1,725 2,131 1,235 29,007 43,368 2,358 30,732 45,499 2,358 Sweet Potatoes 480 537 1,119 593 465 784 1,073 1,002 934 Irish Potatoes 8,314 11,973 1,440 7,089 8,763 1,236 15,402 20,736 1,346 Yams 51 0 0 80 55 684 132 55 417 Cocoyam 188 574 3,045 86 101 1,169 275 675 2,455 TOTAL 10,759 15,214 36,856 52,752 47,614 67,966 Note: Cassava is produced in both the long and short rainy season. However, it was not possible to separate cassava production in the different growing seasons as the growth period spans both seasons and even over a year in certain varieties. Because of this, cassava has been combined and is reported in the long rainy season only. Chart 3.28 Area Planted with Cassava during the Census/Survey Years 0 15,000 30,000 45,000 1994/95 1995/96 1998/99 2002/03 Year Area (Ha) Cassava RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 28 3.15). However, the highest proportion of land planted with cassava, expressed as a percent of the total land area was in Tanga district (33%). This was followed by Muheza (17%), Pangani (11%), Korogwe (7%), Lushoto (5%), Handeni (3%) and Kilindi (3%) (Chart 3.29). The average cassava planted area per cassava growing household was 0.4 hectares. However, there were small district variations. The area planted per cassava growing household was greatest in Kilindi (0.6 ha). This was followed by Muheza (0.5 ha), Tanga (0.5 ha), Handeni (0.5 ha), Pangani (0.4 ha), Korogwe (0.3 ha) and Lushoto (0.2 ha) (Chart 3.30 and Map 3.16). 3.3.5.2 Irish Potatoes The number of households growing Irish potatoes in Tanga region was 52,200. This was 2.5 percent of the total root and tuber crop growing households during the long rainy season. The total production of Irish potatoes during the census year was 20,736 tonnes from a planted area of 15,402 hectares resulting in a yield of 1.3t/ha. Lushoto District has the largest planted area for Irish potatoes (15,309 ha, 99.39%), followed by Korogwe (90 ha, 0.58%) and Pangani (4 ha, 0.02%). Irish potatoes were not grown in the other districts of Tanga region(Chart 3.31).Other root and tuber crops are of minor important in terms of area planted compared to cassava and Irish potatoes. 3.3.6 Pulse Crops Production The total area planted with pulses was 77,017 hectares out of which 63,028 ha were planted with beans (82 percent of the total area planted with pulses), followed by cow peas (12,007 ha, 15.6%), green gram (1,863 ha, 2.4%), mung beans (64 ha, 0.1%) and field peas (50 ha, 0.1%). Pigeon peas and soya beans were not cultivated in the region. Table 3.4: Area, Production and Yield of Pulses by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Mung Beans 0 0 0 64 88 1,385 64 88 1,385 Beans 24,185 8,699 360 38,843 15,325 395 63,028 24,023 381 Cowpeas 9,276 2,125 229 2,731 499 183 12,007 2,624 219 Green Gram 1,108 288 260 755 248 329 1,863 536 288 Chich Peas 2 0 198 0 0 0 2 0 198 Bambaranuts 2 1 296 0 0 0 2 1 296 Field Peas 50 109 2,159 0 0 0 50 109 2,159 TOTAL 34,624 11,221 42,393 16,160 77,017 27,381 Chart 3.29 Percent of Cassava Planted Area and Percent of Total Land with Cassava by District 38.3 21.0 13.1 10.3 8.9 4.8 3.6 0 15 30 45 Muheza Lushoto Korogwe Handeni Tanga Kilindi Pangani District Percent of Total Area Planted 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Area Planted Proportion of Land 0.57 0.50 0.50 0.47 0.43 0.34 0.25 0.00 0.20 0.40 0.60 Area per Household Kilindi Muheza Tanga Handeni Pangani Korogwe Lushoto District Chart 3.30 Cassava Planted Area per Cassava Growing Households by District Chart 3.21 Irish Potatoes: Total Area Planted and Planted Area per Household by District 15,309 90 0 0 4 0 0 0 4,000 8,000 12,000 16,000 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Area (Ha) 0.00 20.00 40.00 60.00 80.00 100.00 120.00 Area Planted per Household Planted Area (ha) Area per hh Tanga 1,117ha 2,730ha 3,162ha 11,772ha 1,475ha 4,020ha 6,457ha 1.8t/ha 2.6t/ha 2.8t/ha 3.1t/ha 2.4t/ha 3t/ha 1.6t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.15 TANGA Planted Area and Yield of Cassava by District 9,500 to 11,800 7,400 to 9,500 5,300 to 7,400 3,200 to 5,300 1,100 to 3,200 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 29 Korogwe 0.4ha 0.5ha 0.4ha 0.6ha 0.5ha 0.5ha 0.2ha Kilindi Handeni Pangani Tanga Muheza Lushoto MAP 3.16 TANGA Area Planted Per Cassava Growing Household by Distrct 0.52 to 0.61 0.44 to 0.52 0.36 to 0.44 0.28 to 0.36 0.2 to 0.28 Area Planted Per Households RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 30 The area planted with pulses in the short rainy season was 34,624 ha which represented 45 percent of total area planted with pulses during the year. Beans was the most dominant crop during long rainy season with 38,843 ha (91.2 % of the total area planted with pulses in that particular season), followed by cow peas (2,731 ha, 6.4%), green gram (755 ha, 1.8%) and mung beans 64 ha (0.2%). The total production of pulses was 27,381 tonnes. Beans were the most cultivated crop producing 24,023 tonnes which accounted for 88 percent of the total pulse production. This was followed by cow peas (2,624t, 10%), green gram (536t, 1.9%), field peas (109t, 0.4%), mung beans (88t, 0.3%), bambaranuts (1t, 0.002%) and chick peas (0.4t, 0.002%). Field peas and mung beans had relatively higher yields of 2,159 and 1,385 kgs/ha respectively. The yields of the rest of the pulses in kilograms per hectare were beans 381 kgs/ha, bambaranuts 296 kgs/ha, green gram 288 kgs/ha, cowpeas 219 kgs/ha and chick peas 198 kgs/ha (Chart 3,32). 3.3.6.1 Beans Beans dominate the production of pulse crops in the region. The number of households growing beans in Tanga region was 166,192. The total production of beans in the region was 24,023 tonnes from a planted area of 63,028 hectares resulting in a yield of 0.4 t/ha. The largest area planted with beans in the region was in Lushoto (46,981 ha, 74.5%) (Chart 3.33 and Map 3.17), however, the largest area planted with beans per household was in Kilindi district (0.92 ha) (Chart 3.34). The average area planted per household in the region during the long rainy season was 0.4 ha. With exception of Kilindi district, the variations in area planted with beans for the rest of the districts were small ranging from 0.2 ha in Tanga and Pangani districts to 0.4 ha in Lushoto district (Map 3.18). Chart 3.32 Area Planted and Yield of Major Pulse Crops 0 20,000 40,000 60,000 80,000 Beans Cowpeas Green Gram Mung Beans Field Peas Bambaranuts Chich Peas Crop Area Planted (ha) 0 1,000 2,000 3,000 Yield (kg/ha) Yield (kg/ha) Chart 3.33 Percent of Bean Planted Area and Percent of Total Land with Beans by District 0 20 40 60 80 Lushoto Kilindi Korogwe Muheza Handeni Tanga Pangani District Percent of Land 0 10 20 30 40 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.92 0.40 0.35 0.25 0.24 0.19 0.00 0.00 0.25 0.50 0.75 1.00 Area per Household Kilindi Lushoto Korogwe Muheza Handeni Tanga Pangani District Chart 3.34 Area Planted per Bean Growing Household by District (Long Rainy Season Only) Chart 3.35: Time Series Data on Beans Production - TANGA 12 4 13 21 24 2 11 0 10 20 30 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2002/03 Year Production ('000') tons Tanga 4ha 13ha 1,374ha 5,979ha 432ha 46,981ha 8,245ha 0.2t/ha 0.1t/ha 0.4t/ha 0.1t/ha 0.3t/ha 0.6t/ha 0.4t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.17 TANGA Planted Area and Yield of Beans by District 36,000 to 47,000 27,000 to 36,000 18,000 to 27,000 9,000 to 18,000 0 to 9,000 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 31 0.2ha 0.2ha 0.3ha 0.5ha 0.7ha 0.3ha 0.3ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.18 TANGA Area Planted per Beans Growing Household by District. Area Planted Per Household 0.6 to 0.8 0.5 to 0.6 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 32 In Tanga region, bean production has increased steadily over the period 1995 to 2003 from 2,000 tonnes in 1995 to 24,000 tonnes in 2003 (Chart 3.35). Charts 3.35 and 3.36 show that, whilst the yield of beans remained fairly constant the previous 8 years, the quantity produced has increased and this has been due to a large increase in the area under production. The area planted with beans has increased erratically over the period from 1986 to 2003. Over the period 1997 to 2003 the yield of beans remained constant at around 0.4 t/ha. (Chart 3.36). 3.3.7 Oil Seed Production The total production of oilseed crops was 1,516 tonnes planted on an area of 2,564 hectares... The total planted area of oilseeds in the long rainy season was 1,839 ha representing 72 percent of the total area planted with oil seeds. Groundnuts were most important oilseed crop with 1,645 ha (64% of the total area planted with oil seeds), followed by simsim (32%), sunflower (3%) and castor seed (0.8%) (Chart 3.37). The yield of groundnuts was moderate (714 kg/ha). Castor seed had a yield of 498 kg/ha, sunflower of 451 kg /ha and simsim 362 kg/ha. In terms of production, groundnuts were 1,174 tonnes and accounted for 77 percent of the total production of oil seeds, followed by simsim (20%), sunflower (2%) and castor seed (1%). 3.3.7.1 Groundnuts The number of households growing groundnuts in Tanga region was only 5,645. The total production of groundnuts in the region was 1,174 tonnes from a planted area of 1,645 hectares resulting in a yield of 0.7 t/ha. Area planted dropped from 310 hectares in 1994/95 to 196 hectares in 1995/96 after which it increased to 1,645 hectares in 2002/03 (Chart 3.38) Table 3.5: Area, Quantity Harvested and Yield of Oil Seed Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Sunflower 0 0 0 78 35 451 78 35 451 Simsim 92 26 281 729 271 372 822 297 362 Groundnuts 613 212 346 1,032 961 932 1,645 1,174 714 Castor Seed 20 10 494 0 0 0 20 10 494 Total 725 248 1,839 1,268 2,564 1,516 Chart 3.37 Area Planted and Yield of Major Oil Seed Crops 0 500 1,000 1,500 2,000 Groundnuts Simsim Sunflower Castor Seed Crop Area Planted (ha) 0 200 400 600 800 1,000 Yield (kg/ha) Yield (kg/ha) Chart 3.36 Time Series of Beans Planted Area & Yield - TANGA 0 20000 40000 60000 1996/97 1998/99 1999/00 2002/03 Agriculture Year Area (hectares) 0 0.2 0.4 0.6 0.8 Yield (t/ha) Area Yield 310 196 1400 1645 0 400 800 1200 1600 Planted Area 1994/95 1995/96 1998/99 2002/03 Year Chart 3.38 Time Series Data on Groundnut Planted area RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 33 There has been a large increase in production of groundnuts over the period 1995 to 2003, from 310 tonnes in 1994/95 to 1,174 tonnes in 2002/03. Area planted dropped from 310 hectares in 1994/95 to 196 hectares in 1995/96 after which it increased to 1,645 hectares in 2002/03 (Chart 3.38). Fifty percent of the area planted with groundnuts was located in Muheza District (828 ha) followed by Korogwe (359 ha, 21.8%), Handeni (228 ha, 13.8%), Tanga (104 ha, 6.3%), Pangani (93 ha, 5.6%) and Kilindi (34 ha, 2.0%). Groundnuts were not grown in Lushoto district (Map 3.19). The highest proportion of land with groundnuts was found in Tanga followed by Muheza, Pangani, Korogwe, Handeni and Kilindi (Chart 3.39 and Map 3.20). The largest area planted per groundnut growing household was found in Tanga District (0.43 ha) and the lowest was in Handeni (0.27). The range between the district with the highest and the lowest area planted per household depicts small variations in area planted among the districts (Chart 3.40). 3.3.8 Fruit and Vegetables The collection of fruit and vegetables production data was difficult due to the small quantities produced per household. Most of the data presented here gives the production of smallholders who grew these crops as cash crops and not merely for household consumption. Most fruit production is from permanent crops and only water melon is reported as an annual crop in this section. The short rainy season is relatively important for fruit and vegetables production since 53 percent of the total area planted with fruit and vegetables was during the short rainy season. For tomatoes, water Mellon, ginger, spinach and radish over 60 percent of the planted area of each crop was during the short rainy season. The planted area for cucumber in the long rainy season was abnormally large (100% of the total planted area was in the long rainy season). Reliable historical data for time series analysis of fruit and vegetables were not available. Chart 3.39 Percent of Groundnuts Planted Area and Percent of Total Land with Groundnuts by District 0.0 20.0 40.0 60.0 Muheza Korogwe Handeni Tanga Pangani Kilindi Lushoto District Percent of Land 0.0 0.5 1.0 1.5 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.20 0.40 0.60 Area per Household (ha Tanga Kilindi Pangani Korogwe Muheza Handeni Lushoto District Chart 3.40 Area Planted per Groundnut Growing Households by District (Long Rainy Season Only) Chart 3.42 Area Planted and Yield of Fruit and Vegetables 0 1,000 2,000 3,000 Tomatoes Cabbage Chillies Water Mellon Bitter Aubergine Carrot Others Crop Area Planted (ha) 0 1,000 2,000 3,000 4,000 5,000 Yield (kg/ha) Tanga 0ha 104ha 828ha 93ha 228ha 34ha 359ha 0t/ha 0.6t/ha 0.4t/ha 0.3t/ha 1.8t/ha 0.5t/ha 0.4t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.19 TANGA Planted Area and Yield of Groundnuts by District- 680 to 830 510 to 680 340 to 510 170 to 340 0 to 170 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 34 0.5ha 0.4ha 0.3ha 0.3ha 0.2ha 0.3ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.20 TANGA Area Planted Per Groundnuts Growing Household by District. 0.4 to 0.5 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Planted Area Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 35 The total production of fruits and vegetables was 19,550 tonnes. The most cultivated fruit and vegetable crop was tomatoes with a production of 10,852 tonnes (55% of the total fruit and vegetables produced) followed by cabbage (3,472t, 18%) and chilies (1,973t, 10%). The production of the other fruit and vegetables crops was relatively small (Table 3.6). The yield of tomatoes was 4,225 kg/ha, cabbage (4,105 kg/ha), water melon (3,634 kg/ha) and pumpkins (3,384 kg/ha). Radish and spinach had yields of 529 and 251 kg/ha respectively (Chart 3.42). 3.3.8.1 Tomatoes The number of households growing tomatoes in the region during the long rainy season was 4,100 and 7,462 households in the short rainy season. This represented 1.7 percent of the total crop growing households in the region during the long rainy season and 3.8 percent during the short rainy season. Lushoto district had the largest planted area of tomatoes (65.4% of the total area planted with tomatoes in the region), followed by Korogwe (17.8%), Kilindi (4.7%), Muheza (4.2%), Pangani (3.6%), Tanga (2.5%) and Handeni (1.9%) (Map 3.21). The highest percentage of land with tomatoes was found in Lushoto, followed by Pangani district. With exception of Lushoto district, the rest of the districts have relatively low percentage of land used for tomato production (Chart 3.43). The largest area planted per tomato growing household was found in Pangani district (0.34 ha) followed by Tanga (0.25 ha), Lushoto (0.23 ha), Korogwe (0.21 ha), Kilindi (0.20 ha), Muheza (0.11 ha) and Handeni (0.08 ha) (Chart 3.44 and Map 3.22). The total area planted with tomatoes accounted for 0.6 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. Table 3.6: Area, Production and Yield of Fruits and Vegetables by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Okra 9 13 1,422 26 17 629 35 29 831 Radish 4 2 529 0 0 0 4 2 529 Bitter Aubergine 18 216 11,856 176 296 1,685 194 512 2641 Onions 18 85 4,681 100 279 2,782 119 364 3072 Ginger 88 66 746 0 0 0 88 66 746 Cabbage 344 1,410 4,099 502 2,062 4,109 846 3,472 4105 Tomatoes 1,621 7,220 4,455 948 3,632 3,832 2,569 10,852 4225 Spinnach 30 8 251 0 0 0 30 8 251 Carrot 51 182 3,584 143 145 1,017 194 328 1691 Chillies 414 1,054 2,549 307 919 2,990 721 1,973 2737 Amaranths 65 140 2,153 66 59 886 131 199 1515 Pumpkins 13 234 17,324 65 31 475 78 265 3384 Cucumber 0 0 0 90 668 7,390 90 668 7390 Egg Plant 9 11 1,227 23 20 856 32 31 960 Water Mellon 137 82 599 78 699 8,936 215 781 3634 Total 2,821 10,723 2,525 8,827 5,346 19,550 Chart 3.43 Percent of Tomato Planted Area and Percent of Total Land with Tomato by District 0.0 20.0 40.0 60.0 80.0 Lushoto Korogwe Kilindi Muheza Pangani Tanga Handeni District Percent of Land 0.00 0.50 1.00 1.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land 0.00 0.10 0.20 0.30 0.40 Area per Household (ha). Pangani Tanga Lushoto Korogwe Kilindi Muheza Handeni District Chart 3.44 Area Planted per Tomato Growing Household by District (Short Rainy Season Only) Tanzania Agriculture Sample Census RESULTS 36 Tanga 63ha 92ha 108ha 456ha 49ha 120ha 1,680ha 2.2t/ha 1.7t/ha 1.7t/ha 1.9t/ha 6.4t/ha 1.8t/ha 5.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.21 TANGA Planted Area and Yield of Tomatoes by District 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Planted Area (ha) Planted Area (ha) Yield (t/ha) 0.3ha 0.2ha 0.3ha 0.1ha 0.1ha 0.2ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.22 TANGA Area Planted Per Tomatoes Growing Household by District 0.28 to 0.33 0.23 to 0.28 0.18 to 0.23 0.13 to 0.18 0.08 to 0.13 Area Planted Per Household RESULTS – Annual Crop and Vegetable Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 37 3.3.8.2 Cabbage The number of households growing cabbages in the region during the long rainy season was 2,277 and 1,582 in the short rainy season. This represented 0.97 percent of the total crop growing households in the region in the long rainy season and 0.8 percent in the short rainy season. Lushoto district had the largest planted area of cabbage (751 ha, 88.8% of the total area planted with cabbage in the region), followed by Korogwe (35 ha, 4.1%), Handeni (32 ha, 3.8%), Kilindi (17 ha, 2.0%), Muheza (9 ha, 1.1%) and Tanga (2 ha, 0.2%) (Chart 3.45 and Map 3.23 and 2,24). The total area planted with cabbages accounted for 0.2 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. 3.3.8.3 Chillies The number of households growing chillies in the region during the long rainy season was 1,367 households and 1,691 in the short rainy season. This represents 0.58 percent of the total crop growing households in the region in the long rainy season and 0.86 percent in the short rainy season. Lushoto district had the largest planted area of chillies (438 ha, 60.8% of the total area planted with chillies in the region), followed by Korogwe (237 ha, 32.9%), Tanga (23 ha, 3.2%), Muheza (18ha, 2.5%), Kilindi (2 ha, 0.3%) and Pangani (2 ha, 0.3%) districts (Map 3.25 and 3.26). Chillies are not produced in Handeni district. The largest proportion of the area planted with chillies was found in Korogwe district (0.39%), followed by Lushoto (0.35%), Tanga (0.28%), Muheza (0.03%), Pangani (0.02%) and Kilindi (0.005) (Chart 3.46). The total area planted with chillies accounted for 0.17 percent of the total area planted with annual crops and vegetables during the short and long rainy seasons. able 3.7: Area, Production and Yield of Annual Cash Crops by Season Short Rainy Season Long Rainy Season Total Crop Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Seaweed 2 7 2,964 0 0 0 2 7 2,964 Cotton 0 0 0 264 165 625 264 165 625 Tobacco 15 3 198 166 70 422 180 73 404 Jute 0 0 0 18 12 642 18 12 642 TOTAL 17 10 448 247 465 256 Chart 3.45 Percent of Cabbage Planted Area and Percent of Total Land with Cabbage by District 0.0 25.0 50.0 75.0 100.0 Lushoto Korogwe Handeni Kilindi Muheza Tanga Pangani District Percent of Land 0.00 0.20 0.40 0.60 0.80 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.46 Percent of Chillies Planted Area and Percent of Total Land with Chillies by District 0.0 20.0 40.0 60.0 80.0 Lushoto Korogwe Tanga Muheza Kilindi Pangani Handeni District Percent of Land 0.00 0.10 0.20 0.30 0.40 0.50 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Tanzania Agriculture Sample Census RESULTS 38 0.2ha 0ha 0ha 0.3ha 0.1ha 0.1ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.24 TANGA Area Planted Per Cabbage Growing Household by District 0.24 to 0.3 0.18 to 0.24 0.12 to 0.18 0.06 to 0.12 0 to 0.06 Area Planted Per Household Tanga 0ha 2ha 32ha 17ha 9ha 751ha 35 0t/ha 1.7t/ha 2.1t/ha 1.3t/ha 0t/ha 2.7t/ha 4.5t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.23 TANGA Planted Area and Yield of Cabbage by District 600 to 760 450 to 600 300 to 450 150 to 300 0 to 150 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanga 23ha 2ha 0ha 18ha 237ha 2ha 438ha 0t/ha 0.4t/ha 1.2t/ha 3.9t/ha 2.9t/ha 7t/ha 2.7t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.25 TANGA Area Planted Per Chillies Growing Household by District 352 to 438 264 to 352 176 to 264 88 to 176 0 to 88 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 39 Tanga 0.1ha 0.4ha 0ha 0.1ha 0.2ha 0.1ha 0.3ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.26 TANGA Area Planted per Chillies Growing Household by District 0.28 to 0.35 0.21 to 0.28 0.14 to 0.21 0.07 to 0.14 0 to 0.07 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 40 3.3.9 Other Annual Crop Production Most of the other annual crops are cash crops. An area of 465ha was planted with other annual crops and cotton was the most prominent followed by tobacco, jute and seaweed. The area planted with annual cash crops in short rainy season was 17 ha which represents 3.6 percent of the total area planted with other annual cash crops in short and long rainy season. 3.3.9.1 Cotton Only 165 tonnes of cotton was produced in Tanga Region on a planted area of 264 ha it was produced during the long rainy season only. The crop is grown in Handeni district only (Map 3.27) and only 0.6 ha was grown per household (Map 3.28). 3.3.9.2 Tobacco The quantity of tobacco produced was 73 tonnes. Tobacco had a planted area of 180 ha, most of which was planted in the long rainy season. Tobacco production is concentrated in 4 districts with Kilindi having the largest planted area (46.1% of total area planted with tobacco in the region), followed by Muheza (25.6%), Korogwe (15.0%), Lushoto (8.3%) and Pangani (5.0%) (Chart 3.43) (Map 3.29 and 3.30). 3.4 Permanent Crops Permanent crops (sometimes referred as permanent crops) are crops that normally take over a year to mature and once mature can be harvest for a number of years. For most crops, it is easy to determine if they are annual or permanent. However, for crops like cassava and bananas the distinction is not so clear. Cassava has varieties that mature within a year and produces only one harvest, whilst other varieties survive for more than one year and produces several harvests. In this census, cassava was treated as an annual crop. Conversely, bananas normally take less than a year to mature, survive for more than one year and are thus treated as a permanent crop. In this report the agriculture census results are presented for the most important permanent crops in terms of production, yield and area planted. Previous censuses and surveys did not measure these variables for permanent crops, therefore any time series analysis is made in this section. The area of smallholders planted with permanent crops was 62,403 hectares (13% of the area planted with annual crops in the region). However, the area planted with annual crops is not the actual physical land area as it includes the area planted more than once on the same land, whilst for the planted area for permanent crops is the same as physical planted land area. So the percentage physical area planted with permanent crops would be higher than indicated in Chart 3.49. Chart 3.47 Area planted with Annual Cash Crops Seaweed, 2, 0% Cotton, 264, 57% Tobacco, 180, 39% Jute, 18, 4% Chart 3.48 Percent of Tobacco Planted Area and Percent of Total Land with Tobacco by District 0.0 20.0 40.0 60.0 Kilindi Muheza Korogwe Lushoto Pangani Tanga Handeni District Percent of Land 0.00 0.10 0.20 0.30 Percent Area Planted of Total Land Area Percent of Land Proportion of Land Chart 3.49 Area Planted for Annual and Permanent Crops Annual , 428,533, 87% Permanent , 62,402 13% 0ha 0ha 0ha 0ha 264ha 0ha 0ha 0t/ha 0t/ha 0.6t/ha 0t/ha 0t/ha 0t/ha 0t/ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.27 TANGA Planted Area and Yield of Cotton by District 200 to 270 150 to 200 100 to 150 50 to 100 0 to 50 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 41 0ha 0.6ha 0ha 0ha 0ha 0ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.28 TANGA Area Planted Per Cotton Growing Household by District 0.4 to 0.7 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Household Tanga 0ha 0ha 9ha 46ha 83ha 27ha 15ha 0t/ha 0t/ha 0.9t/ha 0t/ha 0.2t/ha 0.6t/ha 0.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.29 TANGA Planted Area and Yield of Tobbaco by District 80 to 90 60 to 80 40 to 60 20 to 40 0 to 20 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 42 0ha 0.4ha 0.3ha 0ha 0.6ha 0.1ha 0.1ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.30 TANGA Area Planted Per Tobacco Growing Household by Distrct 0.48 to 0.58 0.36 to 0.48 0.24 to 0.36 0.12 to 0.24 0 to 0.12 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 43 The most important permanent crop in Tanga region is coconuts which accounts for a planted area of 14,765 ha, (23.7% of the planted area of all permanent crops) followed by orange (9,342 ha, 15%), banana (8,125 ha, 13%), cashew nuts (7,905 ha, 12.7%), mango 4,268 ha, 6.8%) and coffee (3,199 ha, 5.1%). Each of the remaining permanent crops had an area of less than 5 percent of the total area planted with permanent crops (Chart 3.50). Muheza district had the largest area under smallholder permanent crops (28,263 ha, 45%). This is followed by Korogwe (9,357 ha, 15%), Lushoto (6,808 ha, 11%), Handeni (6,360 ha, 10%), Kilindi (4,914 ha, 8%), Pangani (4,623 ha, 7%) and Tanga (2,078 ha, 3%). However, Pangani had the largest area per permanent crop growing household (0.9 ha) followed by Muheza (0.7 ha), Kilindi (0.5 ha), Korogwe (0.4 ha), Handeni (0.3 ha), Tanga (0.3 ha) and Lushoto (0.1 ha) (Chart 3.51). In terms of area of permanent crops planted expressed as a percentage of the total area planted with crops per district, Pangani had the highest (31%) followed by Muheza (29%), Tanga (20%), Korogwe (13%), Kilindi (10%), Handeni (5%) and Lushoto (5%). 3.4.1 Coconuts The total production of coconuts by smallholders was 26,328 tonnes. In terms of area planted, coconut was the most important permanent crop grown by smallholders in the region. They were grown by 32,814 households (12.4% of the total crop growing households). The average area planted with coconuts per household was relatively small at around 0.45 ha per cashew nut growing household and the average yield obtained by smallholders was 3,479 kg/ha from a harvest area of 7,568 hectares. Muheza had the largest area of coconuts in the region (9,380 ha, 63.5%) followed by Pangani (2,417 ha, 16.4%), Korogwe (1,682.1 ha, 11.4%), Tanga (964.6 ha, 6.5%), Handeni (248.1 ha, 1.7%) and Lushoto (72.4 ha, 0.5%). There was no coconut production in Kilindi district (Map 3.31). However, the average area planted with coconuts per coconut growing household was highest in Pangani (0.69 ha) followed by Muheza (0.58 ha), Korogwe (0.38 ha), Tanga (0.22 ha), Lushoto (0.18 ha) and Handeni (0.07 ha) (Chart 3.52 and Map 3.32). Chart 3.50 Area Planted with the Main Perennial Crops Tea, 1,941, 3% Sugarcane, 2,356, 4% Pigeon Pea, 2,484, 4% Cardamon, 2,952, 5% Coffee, 3,200, 6% Mango, 4,268, 7% Cashewnut, 7,905, 14% Banana, 8,125, 14% Orange, 9,342, 16% Coconut, 14,765, 27% Chart 3.51 Percent of Area Planted and Average Planted Area with Permanent Crops by District 15.0 10.9 10.2 7.9 7.4 3.3 45.3 0.0 20.0 40.0 Muheza Korogwe Lushoto Handeni Kilindi Pangani Tanga District % of Total Area Planted 0.0 0.2 0.4 0.6 0.8 1.0 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.52 Percent of Area Planted with Coconuts and Average Planted Area per Household by District 0.0 1.7 0.5 11.4 16.4 6.5 63.5 0.0 20.0 40.0 60.0 80.0 Muheza Pangani Korogwe Tanga Handeni Lushoto Kilindi District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 965ha 9,380ha 2,418ha 248ha 0ha 1,682ha 72ha 3.8t/ha 7.2t/ha 2t/ha 7.1t/ha 1.6t/ha 7.3t/ha 1.2t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.31 TANGA Planted Area and Yield of Coconuts by District 6,400 to 9,380 4,800 to 6,400 3,200 to 4,800 1,600 to 3,200 0 to 1,600 Area Planted (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 44 0.2ha 0.7ha 0.6ha 0.1ha 0ha 0.4ha 0.2ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.32 TANGA Area Planted per Coconuts Growing Households by District 0.56 to 0.69 0.42 to 0.56 0.28 to 0.42 0.14 to 0.28 0 to 0.14 Area Planted Per Household RESULTS – Permanent Crops __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 45 3.4.2 Oranges The total production of oranges by smallholders was 65,210 tonnes. In terms of area planted, orange was the second most important permanent crop grown by smallholders in the region. It was grown by 9,342 households (3.5% of the total crop growing households). The average area planted with oranges per household was relatively small at around 0.39 ha per orange growing household and the average yield obtained by smallholders was 10,952 kg/ha from a harvest area of 5,954 hectares. Muheza had the largest area of oranges in the region (6,433 ha, 68.9%) followed by Handeni (2,201 ha, 23.6%), Korogwe (404 ha, 4.3%), Pangani (158 ha, 1.7%), Kilindi (79 ha, 0.9%), Tanga (63 ha, 0.7%) and Lushoto (4.3ha, 0.1%) (Map 3.33). However, the average area planted with oranges per orange planting household was highest in Muheza (0.6 ha) followed by Handeni (0.3 ha), Korogwe (0.3 ha), Pangani (0.1 ha), Kilindi (0.07 ha), Tanga (0.04 ha) and Lushoto (0.03 ha) (Chart 3.53 and Map 3.34). 3.4.3 Banana The total production of banana by smallholders was 34,126 tonnes. In terms of area planted, banana was the third most important permanent crop grown by smallholders in the region. It was grown by 61,464 households (23.3% of the total crop growing households). The average area planted with banana per household was relatively small at around 0.13 ha per banana growing household and the average yield obtained by smallholders was 6,311 kg/ha from a harvested area of 5,408 hectares. Muheza had the largest planted area of bananas in the region (2,281 ha, 28%) followed by Korogwe (2,069 ha, 25%), Lushoto (1,751 ha, 22%), Handeni (1,143 ha, 14%), Kilindi (662 ha, 8%), Pangani (152 ha, 2%) and Tanga (68 ha, 1%) (Map 3.35). However, the area planted with banana per banana growing household was highest in Kilindi (0.22 ha), followed by Handeni (0.21 ha), Korogwe (0.20 ha), Muheza (0.16 ha), Pangani (0.13 ha), Lushoto (0.07 ha) and Tanga (0.06 ha) (Chart 3.49 and Map 3.36). 3.4.4 Cashew Nuts The total production of cashew nuts by smallholders was 4,557 tonnes. In terms of area planted, cashew nut was the fourth most important permanent crop grown by smallholders in the region. It was grown by 16,074 households (6.1% of the total crop growing households). The average area planted with cashew nuts per household was relatively small at around 0.49 ha per cashew nut growing household and the average yield obtained by smallholders was 977 kg /ha from a harvest area of 4,664 hectares. Chart 3.53 Percent of Area Planted with Oranges and Average Planted Area per Household by District 0.68 0.05 23.56 1.69 68.86 0.85 4.33 0.00 20.00 40.00 60.00 Muheza Handeni Korogwe Pangani Kilindi Tanga Lushoto District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Chart 3.54 Percent of Area Planted with Banana and Average Planted Area per Household by District 21.55 8.15 28.07 14.07 25.46 1.87 0.83 0.00 10.00 20.00 30.00 Muheza Korogwe Lushoto Handeni Kilindi Pangani Tanga District % of Total Area Planted 0.00 0.10 0.20 0.30 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 63ha 79ha 2,201ha 158ha 6,433ha 404ha 4ha 35.5t/ha 4.1t/ha 11.4t/ha 7.4t/ha 11.7t/ha 2.5t/ha 6.1t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.33 TANGA Planted Area and Yield of Oranges by District 5,200 to 6,500 3,900 to 5,200 2,600 to 3,900 1,300 to 2,600 0 to 1,300 Planted Area (ha) Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 46 Tanga Pangani Kilindi Handeni Korogwe Muheza Lushoto 0ha 0.1ha 0.6ha 0.3ha 0.3ha 0.1ha 0ha MAP 3.34 TANGA Area Planted per Orange Growing Households by District 0.4 to 0.6 0.3 to 0.4 0.2 to 0.3 0.1 to 0.2 0 to 0.1 Area Planted Per Households Tanga 68ha 152ha 1,143ha 2,281ha 2,069ha 662ha 1,751ha 18t/ha 7.6t/ha 6t/ha 3.6t/ha 7.4t/ha 6.9t/ha 13.3t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP3.35 TANGA Planted Area and Yield of Banana by District 2,000 to 2,300 1,500 to 2,000 1,000 to 1,500 500 to 1,000 0 to 500 Planted Area (ha) Tanzania Agriculture Sample Census RESULTS 47 Tanga 0.1ha 0.1ha 0.2ha 0.21ha 0.2ha 0.2ha 0.1ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.36 TANGA Area Planted per Banana Growing Household by District 0.18 to 0.22 0.15 to 0.18 0.12 to 0.15 0.09 to 0.12 0.06 to 0.09 Area Planted Per Household RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 48 Muheza has the largest area of cashew nuts in the region (4,600 ha, 58%) followed by Pangani (1,766 ha, 22%), Tanga (950 ha, 12%), Korogwe (578 ha, 7%) and Lushoto (11 ha, 0.1%) (Map 3.37). However, the average area planted per cashewnut growing household was highest in Pangani (0.87 ha), followed by Muheza (0.54 ha), Tanga (0.43 ha), and Korogwe (0.25 ha) (Map 3.38). Handeni and Kilindi districts reported no cashew nuts production. 3.5 Input/Implement Use 3.5.1 Methods of Land Clearing Land clearing is a common pre-tillage operation practiced by most farmers in the region. Land clearing is divided into two categories: bush clearing, which by definition implies either expansion into virgin areas or into areas which have been left fallow for a long period. The other category, which includes burning, hand slashing or tractor slashing, is normally an annual clearing exercise to remove vegetation growth from the previous season. Hand slashing is the most widespread method used for land clearing. The area cleared by hand slashing in the region during the long rainy season was 172,247 ha which represented 72.2 percent of the total planted area. Bush clearance, burning and tractor slashing are less important methods for land clearing and they represent 3.6, 0.8 and 0.4 percent respectively (Chart 3.56 and Table 3.8 ). 3.5.2 Methods of Soil Preparation Hand cultivation is mostly used for soil preparation as it has been used in an area of 379,283 ha which represented 95 percent of the total planted area, followed by ox-ploughing (17,519 ha, 4%) and tractor ploughing (3,509 ha, 1%) (Chart 3.57). Table 3.8: Land Clearing Methods Long Rainy Season Short Rainy Season Total Method of Land Clearing Number of Households Area Planted % Number of Households Area Planted % Number of Households Area Planted % Mostly Hand Slashing 266,868 172,247 72.2 288,964 127,858 79.7 555,831 300,105 75.2 No Land Clearing 70,212 54,961 23.0 48,698 25,488 15.9 118,910 80,450 20.2 Mostly Bush Clearance 8,438 8,584 3.6 8,307 4,180 2.6 16,745 12,764 3.2 Mostly Burning 3,014 1,896 0.8 2,579 1,682 1.0 5,593 3,577 0.9 Mostly Tractor Slashing 1,684 875 0.4 1,267 457 0.3 2,951 1,332 0.3 Other 98 56 0.0 998 691 0.4 1,096 747 0.2 Total 350,314 238,619 100.0 350,812 160,357 100.0 701,126 398,976 100.0 Chart 3.57 Area Cultivated by Cultivation Method Mostly Tractor Ploughing, 3,509, 1% Mostly Hand Hoe, 379,283, 95% Mostly Oxen Ploughing, 17,519, 4% Chart 3.56 Number of Households by Method of Land Clearing during the Long Rainy Season 266,868 70,212 8,438 3,014 1,684 98 0 100,000 200,000 300,000 Mostly Hand Slashing No Land Clearing Mostly Bush Clearance Mostly Burning Mostly Tractor Slashing Other Method of Land Clearing Number of Households Chart 3.55 Percent of Area Planted with Cashewnuts and Average Planted Area per Household by District 0.00 0.00 12.01 0.14 58.19 7.31 22.34 0.00 20.00 40.00 60.00 Muheza Pangani Tanga Korogwe Lushoto Handeni Kilindi District % of Total Area Planted 0.00 0.25 0.50 0.75 1.00 Average Planted Area per Household % of Total Area Planted Average Planted Area per Household Tanga 950ha 1,766ha 4,600ha 0ha 0ha 578ha 11.1ha 12.3t/ha 1.7t/ha 0t/ha 0t/ha 0.7t/ha 1.5t/ha 0t/ha Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.37 TANGA Planted Area and Yield of Cashewnut by District 3,680 to 4,600 2,760 to 3,680 1,840 to 2,760 920 to 1,840 0 to 920 Planted Area (ha) 0.9ha 0.5ha 0ha 0ha 0.4ha 0.3ha 0ha Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.38 TANGA Area Planted Per Cashewnut Growing Household by District 0.68 to 0.87 0.51 to 0.68 0.34 to 0.51 0.17 to 0.34 0 to 0.17 Area Planted Per Household Planted Area (ha) Yield (t/ha) Tanzania Agriculture Sample Census RESULTS 49 RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 50 Slightly more hand cultivation was used during short rainy season at 96 percent against 94 percent for the long rainy season, whereas, oxen and tractor ploughing was more common in the long rainy season with 5 percent and 1 percent respectively. For the short rainy season the corresponding percentages are 3 and 1 respectively. In Tanga region, Handeni district has the largest planted area cultivated with oxen (9,515 hectares, 8.8%) followed by Kilindi (1,570 ha, 3.8%), Muheza (1,830 ha, 3.2%), Pangani (244 ha, 2.7%), Lushoto (2,919 ha, 2.44%), Korogwe (1,386 ha, 2.4%) and Tanga (55 ha, 1%). During the long rainy season, 91.7 percent of the total area cultivated by using oxen was planted with cereals followed by pulses (5.0%), fruit and vegetables (1.1%), roots and tubers (1.0%), oil seeds (0.6%) and cash crops (0.5%). 3.5.3 Improved Seed Use The planted area using improved seeds was estimated at 52,089 ha which represents 13 percent of the total planted with the annual crops and vegetables area. The percentage use of improved seed in the short rainy season was 13.4 percent, slightly higher than the corresponding percentage use for the long rainy season (12.73%). Cereals had the largest planted area with improved seeds (35,171 ha, 67% of the planted area with improved seeds) followed by pulses (8,748 ha, 17%), fruit and vegetables (4,291 ha, 8%), roots and tubers (3,415 ha, 7%), cash crops (280 ha, 1%) and Oil seed (185 ha, 0.3%) (Chart 3.54). However, the use of improved seed in fruit and vegetables and cash crops is much greater than in other crop types (80% and 60% respectively), only 7 percent of the planted area for oil seed crops used improved seed (Chart 3.55). 0 20,000 40,000 60,000 80,000 100,000 120,000 Area Cultivated Handeni Lushoto Muheza Kilindi Korogwe Pangani Tanga District Chart 3.58 Area Cultivated by Method of Cultivation and District Mostly Oxen Ploughing Mostly Hand hoe ploughing Mostly Tractor Ploughing Chart 3.59 Planted Area of Improved Seeds - TANGA With Improved Seeds, 52,089, 13% Without Improved Seeds, 348,221, 87% Chart 3.60 Planted Area with Improved Seed by Crop Type Roots & Tubers, 3,415, 7% Pulses, 8,748, 17% Oilseeds , 185, 0% Fruits & Vegetables, 4,291, 8% Cereals, 35,171, 67% Cash Crops, 280, 1% 0 20 40 60 80 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.61 Percentage of Crop Type Planted Area with Improved Seed - Annuals RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 51 3.5.4 Fertilizer Use The use of fertilisers on annual crops is very small with a planted area of only 57,966 ha (15.6% of the total planted area in the region). The planted area without fertiliser for annual crops was 370,460 hectares representing 86.5 percent of the total planted area with annual crops. Of the planted area with fertiliser application, farm yard manure was applied to 40,772 ha which represents 9.5 percent of the total planted area (70.3% of the area planted with fertiliser application in the region). This was followed by compost (12,226 ha, 21.1%). Inorganic fertilizers were used on a very small area and represented only 8.6 percent of the area planted with fertilizers. The highest percentage of the area planted with fertilizer (all types) was in Lushoto district (54.3%) followed by Korogwe (18%), Handeni (14%), Muheza (6%), Kilindi (5%), Tanga (1.4%) and Pangani (0.7%) (Table 3.9 and Charts 3.62 and 3.63). Most annual crop growing households do not use any fertiliser (approximately 27,847 households, 11.5%) (Map 3.39). The percentage of the planted area with applied fertiliser was highest for fruit and vegetables (78% of the area planted with these fruit and vegetables during the long rainy season had an application of fertilizers). This was followed by roots and tubers (17%), pulses (13%), cereals (12%) and oil seeds (6%). There was no fertiliser application in cash crops (Table 3.10). 3.5.4.1 Farm Yard Manure Use Table 3.10: Number of Crop Growing Households and Planted Area by Type of Fertiliser Use and District – Long Rainy Season Fertiliser Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertiliser No Fertiliser Applied Total District Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 12,690 9,955 2,039 1,259 1,153 817 58,902 43,795 74,784 55,826 Korogwe 3,590 4,259 2,243 1,944 403 379 36,599 37,741 42,835 44,323 Muheza 1,411 1,549 79 32 0 43,881 43,825 45,371 45,406 Tanga 523 291 174 121 52 7 6,959 5,445 7,708 5,863 Pangani 99 123 44 110 0 5,779 6,125 5,922 6,357 Handeni 1,491 4,772 632 1,570 204 366 44,453 69,898 46,779 76,606 Kilindi 243 629 729 1,933 49 30 17,273 30,633 18,294 33,225 Total 20,047 21,577 5,939 6,968 1,861 1,598 213,846 237,462 241,693 267,605 Table3.9 Planted Area by Type of Fertiliser Use and District - Long and Short Rainy Season Fertilizer Use District Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer Total No Fertilizer Applied Lushoto 24,102 3,971 3,386 31,459 93,561 Korogwe 5,830 3,677 913 10,419 50,659 Muheza 3,226 248 95 3,570 65,898 Tanga 656 142 22 819 7,379 Pangani 209 182 0 391 9,869 Handeni 6,051 1,810 482 8,343 102,906 Kilindi 699 2,197 69 2,965 40,188 Total 40,772 12,226 4,968 57,966 370,460 0 50,000 100,000 150,000 Area (ha) Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Chart 3.63 Area of Fertiliser Application by Type of Fertiliser and District No Fertilizer Applied Mostly Compost Mostly Inorganic Fertilizer Mostly Farm Yard Manure Chart 3.62 Area of Fertiliser Application by Type of Fertiliser Mostly Farm Yard Manure, 40,772, 10% Mostly Inorganic Fertilizer, 4,968, 1% Mostly Compost, 12,226, 3% No Fertilizer Applied, 370,460, 86% RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 52 The total planted area applied with farm yard manure in Tanga region was 45,375 ha. The number of households that applied farm yard manure in their annual crops during the long rainy season was 20,047 and it was applied to 25,286 ha representing 7.5 percent of the total area planted during that season (Table 3.10). Cereals had the highest percent of the total area planted with applied farm yard manure (56%), followed by roots and tubers (22%), pulses (17%) and fruit and vegetables (8%). However, fruit and vegetables had the highest percent of the planted area with farm yard manure (65.8% of the total area of fruit and vegetables in Tanga). This was followed by roots and tubers (21%), cereals (9%), pulses (8.0%) and oil seeds (4%) (Charts 3.64 and 3.65a). Farm yard manure is mostly used in Lushoto (18.5% of the total planted area in the district), followed by Korogwe (9.5%), Tanga (7.5%), Handeni (5.0%), Muheza (4.5%), Pangani (2.0%) and Kilindi (1.6%) (Chart 3.65b). For permanent crops, most farm yard manure is used for the production of passion fruits (40.8%), followed by apples (31.8%) and coffee (25.7%). 3.5.4.2 Inorganic Fertiliser Use The total planted area applied with inorganic fertilisers in Tanga region was 4,071 ha which represents 0.95 percent of the total planted area with annuals in the region and 6.6 percent of the total planted area with fertiliser. The number of households that applied inorganic fertilizer on their annual crops during the long rainy season was 1,861 and it was applied to 1,687 ha representing 0.6 percent of the total area planted during that season (Table 3.10). The largest area applied with inorganic fertilizers was on cereals (53% of the total area applied with inorganic fertilizers), followed by pulses (16%), fruit and vegetables (16%) and roots and tubers (15%) (Chart 3.66). However, the proportion of fruit and vegetables with inorganic fertilizers was 12.7 percent higher than other crop types, followed by roots and tubers (1.1%), Pulses (0.8%) and cereals (0.3%) (Chart 3.67a). Inorganic fertiliser is mostly used in Lushoto (2.7% of the total planted area in the district), followed 0 25 50 75 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.65a Percentage of Crop Type Planted Area with Farm Yard Manure - Annuals Chart 3.65b Proportion of Planted Area Applied with Farm Yard Manure by District - TANGA 0.0 5.0 10.0 15.0 20.0 Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Percent Chart 3.64 Planted Area with Farm Yard Manure by Crop Type - TANGA Roots & Tubers, 10,203, 22% Pulses, 3,407, 17% Oilseeds, 111, 0% Fruits & Vegetables, 3,458, 8% Cereals, 25,344, 56% Cash Crops, 0, 0% Chart 3.66 Planted Area with Inorganic Fertilizer by Crop Type - TANGA Pulses, 638, 16% Oilseeds, 0, 0% Cash Crop, 0, 0% Cereals, 2,168, 53% Roots & Tubers, 594, 15% Fruit & Vegetables, 671, 16% RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 53 by Korogwe (1.5%). Other districts used virtually no inorganic fertiliser and Pangani recorded zero inorganic fertiliser use (Chart 3.67b). In permanent crops inorganic fertiliser were used on tea (5.2%), followed by sugarcane (1.1%), coconut (0.3%), mangoes (0.15%) and oranges (0.14%). 3.5.4.3 Compost Use The total planted area applied with compost was 12,490 ha which represents only 2.9 percent of the total planted area with annual crops in the region and 20 percent of the total planted area with fertiliser in the region. The number of households that applied compost on their annual crops during the long rainy season was 6,818 and it was applied to 7,650 ha representing 3.0 percent of the total area planted (Table 3.10 and Chart 3.68a). The proportion of area applied with compost was very low for each type of crop (0 to 4%); however the distribution of the total area using compost shows that 71 percent of this area was cultivated with cereals, followed by pulses (17%), roots & tubers (9%) and fruit and vegetables (0.5%)(Chart 3.68b). Compost is mostly used in Lushoto (6% of the total planted area in the district), and this is closely followed by Korogwe (5%). Other districts, like Kilindi used the least compost (0.2%) (Chart 3.67b). In permanent crops, compost was mostly used to durian (100.0%) followed by cloves (8.6%), pears (7.8%), avocado (5.3%) cinnamon (4.7%) and mango (4.0%). 0 5 10 15 20 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crops Crop Type Chart 3.67a Percentage of Planted Area with Inorganic Fertilizer by Crop Type - TANGA Chart 3.67b Proportion of Planted Area Applied with Inorganic Fertiliser by District - TANGA 0.0 1.0 2.0 3.0 Lushoto Korogwe Handeni Tanga Kilindi Muheza Pangani District Percent Chart 3.68a Planted Area with Compost by Crop Type - TANGA Roots & Tubers, 1,073, 9% Cereals, 9,067, 72% Fruits & Vegetables, 86, 1% Pulses, 2,265, 18% Oilseeds, 0, 0% Cash Crop, 0, 0% Chart 3.68c Proportion of Planted Area Applied with Compost by District - TANGA 0.0 2.0 4.0 6.0 8.0 Lushoto Korogwe Tanga Handeni Muheza Pangani Kilindi District Percent 0 5 10 15 20 25 Percent of Planted Area Cereals Roots & Tubers Pulses Oilseeds Fruits & Vegetables Cash Crop Crop Type Chart 3.68b Percentage of Planted Area with Compost by Crop Type- TANGA RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 54 3.5.5 Pesticide Use Pesticides are chemicals used for controlling insects, diseases and weeds. This section analyses the use of these chemicals by smallholders on both annual and permanent crops in the region. Pesticides were applied to a planted area of 25,121 ha of annual crops and vegetables. Insecticides are the most common pesticide used in the region (56% of the total area applied with pesticides). This was followed by fungicides (29%) and herbicides (14%) (Chart 3.69). 3.5.5.1 Insecticide Use The planted area applied with insecticides was estimated at 14,175 ha which represented 3.3 percent of the total planted area for annual crops and vegetables. Cereals had the largest planted area applied with insecticides (7,762 ha, 54% of the total planted area with insecticides) followed by fruit and vegetables (3,642 ha, 26%), pulses (1,379 ha, 10%), roots and tubers (1,100 ha, 8%), cash crops (273 ha, 2%) and oil seed (18 ha, 0.1%) (Chart 3.70). However, the percent of insecticides used in fruits and vegetables and cash crops is much greater than in other crop types (68 and 59% respectively), while only 0.7 percent of oil seed crops were applied with insecticides (Chart 3.71). Annual Crops with more than 50 percent insecticide use were spinach (100%), cucumber (100%), cotton (100%), water mellon (85.4%), tomatoes (83.3%), onions (75.7%), cabbage (71.3%), field peas (56.6%) and chillies (52.2%). Handeni had the highest percent of planted area with insecticides (5.4% of the total planted area with annual crops in the district). This was closely followed by Pangani (5%) then Lushoto (3.8%), Tanga (3.3%) and Korogwe (3.2%). The smallest percentage use was recorded in Muheza district (0.3%) (Chart 3.72). Chart 3.69 Planted Area (ha) by Pesticide Use Fungicides, 7346, 29% Herbicides, 3600, 14% Insecticides, 14175, 56% Chart 3.70 Planted Area Applied with Insecticides by Crop Type Cash crops, 273, 1.9% Cereals, 7,762, 54.8% Fruits & Vegetables, 3,642, 25.7% Oil seeds & Oil nuts, 18, 0.1% Pulses, 1,379, 9.7% Roots & Tubers, 1,100, 7.8% 0.0 25.0 50.0 75.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds & Oil nuts Fruits & Vegetables Cash crops Crop Type Chart 3.71 Percentage of Crop Type Planted Area Applied with Insecticides Chart 3.72 Percent of Planted Area Applied with Insecticides by District - TANGA 0.0 2.0 4.0 6.0 Handeni Pangani Lushoto Tanga Korogwe Kilindi Muheza District Percent RESULTS –Input/Implements Use __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 55 3.5.5.2 Herbicide Use The planted area applied with herbicides was 3,207 ha which represented 0.8 percent of the total planted area annual crops and vegetables. Cereals had the largest planted area applied with herbicides (2,119 ha, 59%) followed by roots and tuber (636 ha, 18%), pulses (383 ha, 11%), fruits and vegetables (310 ha, 9%) and oil seed (153 ha, 4%) (Chart 3.73). However, the percent of herbicide use on oil seeds and fruit and vegetables was much greater than in other crop types (6.0% and 5.8% respectively) while only 0.5 percent of pulses was applied with herbicides (Chart 3.74). The top six annual crops with highest percentage use of herbicides in terms of planted area were amaranths (13.0%), eggplant (10.3%), groundnuts (9.3%), onions (9.2%), tomatoes (8.2%) and cabbages (5.6%). Tanga had the highest percent of planted area with herbicides (3.3% of the total planted area with annual crops in the district). This was followed by Kilindi (1.5%) then Lushoto (0.9%), Muheza (0.6%) and Korogwe (0.6%). The smallest percentage use was recorded in Pangani district (0.2%) (Chart 3.75). 3.5.5.3 Fungicide Use The planted area applied with fungicides was 7,346 ha which represented 1.7 percent of the total planted area for annual crops and vegetables. The percentage use of fungicides in the short rainy season at (2.5%) was higher than the corresponding percentage for the long rainy season (1.2%). Fruits and vegetables had the largest planted area applied with fungicides (3,005ha, 40.9%) followed by cereals (2,851 ha, 38.8%), roots and tubers (664 ha, 9.0%), pulses (590 ha, 8.0%), cash crops (218 ha, 3.0%) and oil seeds (18 ha, 0.2%) (Chart 3.76). Chart 3.73 Planted Area Applied with Herbicides by Crop Type Cash crops, 0, 0% Cereals, 2,119, 59% Fruits & Vegetables, 310, 9% Oil seeds & Oil nuts, 153, 4% Pulses, 383, 11% Roots & Tubers, 636, 18% 0.0 2.0 4.0 6.0 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.74 Percentage of Crop Type Planted Area Applied with Herbicides Chart 3.76 Planted Area Applied with Fungicides by Crop Type Roots & Tubers, 664, 9% Pulses, 590, 8% Oil seeds, 18, 0.2% Fruits & Vegetables, 3,005, 41% Cereals, 2,851, 39% Cash crops, 218, 3% Chart 3.75 Proportion of Planted Area Applied with Herbicides by District - TANGA 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Tanga Kilindi Lushoto Muheza Korogwe Handeni Pangani District Percent RESULTS – Irrigation __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 56 However, the percentage use of fungicide in fruits and vegetables and cash crops was much greater than in other crop types (0.562% and 0.470% respectively), while only 0.008 percent of pulses was applied with fungicides (Chart 3.77). Annual crops with more than 40 percent fungicide use were field peas (100%), tomatoes (81%), cotton (79%), cucumber (78%), Onions (74%), chillies (43%) and egg plants (42%). Pangani had the highest percent of planted area with fungicides (3.8% of the total planted area with annual crops in the district). This was closely followed by Tanga (3.4%) and Lushoto (3.0%). The smallest percentage use was recorded in Muheza district (0.3%) (Chart 3.78). 3.5.6 Harvesting Methods The main harvesting method for cereals was reported to be by hand. Very small amounts of maize were harvested by machine (0.2%) All other cereals and annual crops were harvested by hand. 3.5.7 Threshing Methods Hand threshing was the most common method used, with 89 percent of the total area planted with cereals during the long rainy season was threshed by hand. Draft animals, human powered tools and engine driven machines were only used on crops harvested from 0.1%, 0.1 percent and 0.2 percent of the total planted area respectively. 3.6 Irrigation Water is the limiting factor to crop production in the majority of areas in Tanzania and without water most other cultural practices applied to crops do not result in significant increases in yields. This section deals with the area under irrigation by different crops and the means by which water was extracted from the source and applied to the field. 3.6.1 Area Planted with Annual Crops and Under Irrigation In Tanga region, the area of annual crops under irrigation was 41,089 ha representing 9.6 percent of the total area planted (Chart 3.79). The area under irrigation during the short rainy season was 8,088 ha accounting for 20 percent of the total area under irrigation. Some crops, especially vegetables, were predominantly grown in the short rainy season with irrigation. In the short rainy season, 84 percent of the area planted with vegetables was irrigated, whilst 74 percent of the vegetables were irrigated in the long rainy season. 0.0 0.2 0.4 0.6 Percent of Planted Area Cereals Roots & Tubers Pulses Oil seeds Fruits & Vegetables Cash crops Crop Type Chart 3.77 Percentage of Crop Type Planted Area Applied with Fungicides Chart 3.78 Proportion of Planted Area with Fungicides by District - TANGA 0.0 1.0 2.0 3.0 4.0 Pangani Tanga Lushoto Korogwe Handeni Kilindi Muheza District Percent Chart 3.79 Area of Irrigated Land Unirrigated Area, 387,336, 90% Irrigated Area, 41,089, 10% RESULTS – Irrigation __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 57 The district with the largest planted area under irrigation with annual crops was Lushoto (13,424 ha, 33% of the total irrigated planted area with annual crops in the region). This is closely followed by Muheza with (11,336 ha, 28%) and then Korogwe (6,600 ha, 16%). When expressed as a percentage of the total area planted in each district, Tanga had the highest with 34 percent of the planted area in the district under irrigation. This is followed by Muheza (16%), Pangani (13%), Korogwe (11%), Lushoto (11%), Kilindi (4%) and Handeni (4%) (Chart 3.80 and Map 3.40). Of all the different crops and in terms of proportion of the irrigated planted area, field peas and spinach were the most irrigated crops with 100 percent irrigation followed by cabbage (96%), onions (96%), Amaranths (89%) and tomatoes (89%). In terms of crop type, the area under irrigation with roots and tubers was 47,505 ha (71% of the total area under irrigation), followed by cereals with 5,858 ha (14%), fruit and vegetables (4,218 ha,10%) and pulses (1,754 ha, 4%). All of the irrigation on cereals was applied to maize and paddy. The area of fruit and vegetables under irrigation was 4,218 ha which represents 79 percent of the total planted area with fruit and vegetables. Tomatoes, cabbages and chillies were the most irrigated crops. Irrigation was not used on annual cash crops. The Planted area with irrigation in Tanga region appears to have decreased over the 10 year intercensal period from 18,109 to 13,555 hectares. This may not be statically significant due to the small number of households sampled with irrigation. 3.6.2 Sources of Water Used for Irrigation The main source of water used for irrigation was from canals (45% of households with irrigation). This was followed by river (43%) and wells (8%). Only 0.5 percent of the households used water from boreholes and the proportion of households that used wells, dams and pipe water as a source of water for irrigation were very few (8.4%, 3.3% and 1.1% respectively). Most households using irrigation in Lushoto and Korogwe get their irrigation water from rivers (90 and 92 % respectively) Chart 3.82 Number of Households with Irrigation by Source of Water Canal, 10,176, 45% River, 10,052, 43% Well, 1,965, 8% Dam, 774, 3% Pipe water, 258, 1% Borehole, 113, 0% Canal River Well Dam Pipe water Borehole Chart 3.80 Planted Area with Irrigation by District - TANGA Region 0 4,000 8,000 12,000 16,000 Lushoto Muheza Korogwe Handeni Tanga Kilindi Pangani Region Irrigated Area (ha) 0 10 20 30 40 Percentage Irrigation Irrigated Area Percentage of Irigated Land Chart 3.81 Time Series of Households with Irrigation - TANGA 13,555 18,109 0 5,000 10,000 15,000 20,000 1995/96 2002.03 Agriculture Year Planted Area ubder Irrigation Tanga 9,888ha 7,179ha 49,019ha 102,660ha 39,912ha 64,350ha 93,481ha 96% 88% 93% 92% 92% 80% 75% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 2.39 TANGA Planted Area and Percent of Planted Area with No Application of Fertilizer by District 83,500 to 102,700 64,400 to 83,500 45,300 to 64,400 26,200 to 45,300 7,100 to 26,200 Area Planted and Percent of Planted Area with no Fertilizer Applied Area Planted Percent of Planted Area with no Fertilizer Applied Tanzania Agriculture Sample Census RESULTS 58 Tanga Pangani 6,600ha 3,927ha 2,767ha 1,337ha 1,699ha 11,336ha 13,424 ha 4% 34% 13% 4% 16% 11% 11% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.40 TANGA Area Planted and Percent of Total Planted Area with Irrigation by District Planted Area (ha) Percent of Total Planted Area with Irrigation Planted Area (ha) 13,400 to 13,500 11,300 to 13,400 6,600 to 11,300 2,800 to 6,600 1,300 to 2,800 RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 59 3.6.3 Methods of Obtaining Water for Irrigation Gravity was the most common means of getting water for irrigation with 55.2 percent of households using this method. This was closely followed by hand bucket with 43.4 percent of households. The remaining methods (hand pump, motor pump and others) were of minor importance (Chart 3.76). Gravity was used by most households with irrigation in Lushoto (65.8%), followed by Korogwe (32.2%), Muheza (1.3%), Kilindi (0.4%), Tanga (0.2%) and Pangani (0.1%). Hand bucket was more common in Lushoto with 68.3 percent of households using the method to get water for irrigation, followed by Korogwe (13.2), Muheza (7.6%), Kilindi (4.3%), Handeni (3.2%), Tanga (2.4%) and Pangani (1.1%). Although the method of obtaining irrigation water by hand bucket was the most common method in all seven districts, Tanga and Korogwe districts used some hand and motor pumps for obtaining water. 3.6.4 Methods of Water Application Most households used flood irrigation (52% of households using irrigation) as a method of field application. This was closely followed by hand bucket/watering can (45%). Sprinklers and water hose were not widely used (2.2% and 0.9% respectively). 3.7 Crop Storage, Processing and Marketing 3.7.1 Crop Storage Crop storage means keeping a crop for a certain period of time as food for the household, in order to sell at higher prices and as seed for planting in the following season. The results for Tanga region show that there were 228,187 crop growing households (87% of the total crop growing households) that stored various agricultural products in the region. The most important stored crop was maize with 220,402 households storing 28,187 tonnes as of 1st January 2004. This was followed by beans and other pulses (104,155 households, 1,914t), paddy (14,828 households, 827t) and groundnuts and bambara nuts (1,674 households, 54t). Other crops were stored in very small amounts. Chart 3.83 Number of Households by Method of Obtaining Irrigation Water Gravity, 12,883, 55.2% Hand Bucket, 10,123, 43.4% Motor Pump, 36, 0.2% Hand Pump, 84, 0.4% Other, 212, 0.9% Gravity Hand Bucket Other Hand Pump Motor Pump Chart 3.84 Number of Households with Irrigation by Method of Field Application Sprinkler, 521, 2% Bucket / Watering Can, 10,588, 45% Flood, 12,006, 52% Water Hose, 222, 1% Flood Bucket / Watering Can Sprinkler Water Hose Chart 3.85 Number of Households and Quantity Stored by Crop Type - TANGA 0 50,000 100,000 150,000 200,000 250,000 Maize Pulses Paddy Gnuts/Bamb Nuts Cloves Sorghum & Millet Seaweed Tobacco Cashewnut Crop Number of households 0 5,000 10,000 15,000 20,000 25,000 30,000 Quantity (t) Number of households Quantity stored (Tons) RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 60 3.7.1.1 Methods of Storage The region had 171,393 crop growing households storing their produce in locally made traditional structures (74% of households that stored crops in the region). The number of households that stored their produce in sacks and/or open drums was 43,125 (19%). This was followed by : unprotected piles (6,288 households, 3%), improved locally made structures (3,918 households, 2%), air tight drums (2,136 households, 1%) and modern stores (134 households, 0.1%). Locally made traditional structures were the dominant storage method in all districts, with the highest percent of households in Handeni using this method (88% of the total number of households storing crop products). This is followed by Lushoto (78%), Korogwe (73.5%), Muheza (71.3%), Pangani (67%), Tanga (57%) and Kilindi (52.4%) (Chart 3.80). The highest percent of households using sacks and open drum was in Tanga and Kilindi districts (37% and 36% of the total number of households storing crops), followed by Pangani (24.7%), Korogwe (21.5%), Muheza (18.6%), Lushoto (17.4%) and Handeni (9.6%). 3.7.1.2 Duration of Storage Most households (52% of the households storing crops) stored their produce for a period of 3 to 6 months followed by those who stored for a period of less than 3 months. The minority of households stored their crop for a period of over 6 months (17%). Most households that stored pulses stored for a period of less than 3 months followed by 3 to 6 months. A small number of households stored pulses for the period of over 6 months (Chart 3.88). The proportion of households that stored their produce for the duration of 3 to 6 months was highest in Korogwe district (67%) followed by Kilindi (60%), Muheza (59%), Handeni (58%), Pangani (47%), Tanga (38%) and Lushoto (37%) (Map 3.41). Chart 3.86 Number of households by Storage Methods - TANGA Unprotected Pile, 6,288, 3% Improved Locally Made Crib, 3,918, 2% Other, 1,193, 1% Airtight Drum, 2,136, 1% Modern Store, 134, 0% Sacks / Open Drum, 43,125, 19% Locally Made traditional Crib, 171,393, 74% Chart 3.87 Number of Households by Method of Storage and District (based on the most important household crop) 0 20 40 60 80 100 Lushoto Handeni Muheza Korogwe Kilindi Pangani Tanga District Percent of households In Locally Made Traditional Structure In Improved Locally Made Structure In Modern Store In Sacks / Open Drum In Airtight Drum Unprotected Pile Other 0 30,000 60,000 90,000 120,000 Number of households Maize Paddy Beans & Pulses Crop Chart 3.88 Normal Length of Storage for Selected Crops Less than 3 months 3 to 6 months Over 6 months Tanga Pangani 37.6% 47.3% 58.2% 60% 59.3% 66.8% 37% Kilindi Handeni Korogwe Muheza Lushoto Tanga 4,977 6,605 41,149 69,510 29,751 30,492 14,684 70% 74% 80% 65% 84% 64% 75% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.42 TANGA Number of Households and Percent of Total Households Selling Crops by District 56,000 to 70,000 43,000 to 56,000 30,000 to 43,000 17,000 to 30,000 4,000 to 17,000 Number of Households Sells Crops Number of Households Sells Crops Percent of Total Households Selling Crops MAP 2.41 TANGA Percent of Households Storing Crops for 3 to 6 Months by District Percent of Households Storing Crops 70 to 70 60 to 70 50 to 60 40 to 50 30 to 40 Tanzania Agriculture Sample Census RESULTS 61 RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 62 District comparison of duration of storage cannot be done for all crops combined. However, the analysis has been done for maize only as it is the most commonly stored crop. In general, quantity stored was related to the quantity produced. Districts with greater production had a higher percent of their crop stored as on 1st October 2003 (Chart 3.89). However, households in Lushoto district stored relatively little maize in comparison to the quantity produced indicating that the quantity stored was determined by the food and seed requirement of the household and not to sell during the “off-season” when the farm gate price of maize is higher. 3.7.1.3 Purposes of Storage Subsistence food crops (maize, paddy, sorghum and millet, beans and pulses) are mainly stored for household consumption. The percent of households that stored maize for household consumption as the main purpose of storage was 93.4 percent followed by seed for planting. Practically all stored annual cash crops were stored for selling at higher price. A high percent of the stored permanent crops was used for household consumption as was the case of cloves and cashew nuts (73.5% and 62% respectively). This is followed by selling at a higher price (26,5% and 38% respectively) (Chart 3.90). 3.7.1.4 The Magnitude of Storage Loss About 69 percent of households that stored crops had little or no loss, however the proportion of households that experienced a loss of more than a quarter was higher for food crops than crops that are produced for sale such as coffee, tobacco, cashew nut, groundnut and bambara nuts. The proportion of households that reported a loss of more than a quarter was greatest for sorghum and millet (9.3% of the total number of households that stored crops). This was followed by maize (9.1%), groundnuts and bambaranut (5.4%), beans and pulses (2.9%) and paddy (1.1%). All households that stored cash crops such as seaweed, cloves, cashew nut and tobacco had no loss. Most households storing groundnuts and bambara nuts had little or no storage loss (94%) (Table 3.10). Table 3.11: Number of Households Storing Crops by Estimated Storage Loss and District Estimate Storage Loss District Little or no Loss Up to 1/4 Loss Between 1/4 and 1/2 Loss Over 1/2 Loss Total Lushoto 72,408 8,108 1,276 426 82,219 Korogwe 31,199 4,146 693 213 36,251 Muheza 21,120 15,921 3,756 792 41,589 Tanga 3,641 800 213 0 4,654 Pangani 2,870 1,713 140 66 4,788 Handeni 15,611 17,138 7,113 968 40,831 Kilindi 10,642 4,920 1,953 340 17,855 Total 157,491 52,746 15,145 2,806 228,187 Chart 3.89 Quantity of Maize Produced (tonnes), Stored and Percent Stored by District 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Handeni Muheza Kilindi Korogwe Pangani Lushoto Tanga District Quantity (tonnes) 0 5 10 15 20 25 30 % Stored Quantity harvested Quantity stored % stored 0% 20% 40% 60% 80% 100% Percent of Households Maize Paddy Sorghum & Millet Pulses Sea weed Cloves Cashew nut Tobacco Gnuts Bamb Nuts Crop Type Chart 3.90 Number of Households by Purpose of Storage and Crop Type Food for the household To sell for higher price Seeds for planting Others RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 63 3.7.2 Agro processing and By-products Agro processing refers to a process that converts a crop product from one form to another form in order to add value or increase the palatability of the product. Agro-processing was practiced in most crop growing households in Tanga region (235,784 households, 89% of the total crop growing households) (Chart 3.91a). The percent of households processing crops was very high in most districts (above 80%). Tanga amd Pangani had the lowest percent of households processing crops (69% and 72% of crop growing households respectively) (Chart 3.91b). 3.7.2.1 Processing Methods Most crop processing households processed their crops using neighbour’s machines representing 86 percent (202,137 households). This was followed by those processing on-farm by hand (16,189 households, 6.9%), trader (9,495 households, 4%) and on-farm by machine (7,094 households, 3%). The remaining methods of processing were used by very few households (less than 1%). Although processing by machine was the most common processing method in all districts in Tanga region, however district differences existed. Pangani has a higher percent of hand processing than other districts.(27.2%), followed by Tanga (13.4%), and Handeni (13.2%). Processing by trader was more common in Muheza and Kilindi (10% and 6% respectively), whilst processing on farm by machine was more prevalent in Tanga, Pangani and Handeni (Chart 3.92). 3.7.2.2 Main Agro-processing Products Two types of products can be produced from agro- processing namely, main product and by-product. The main product is the major product after processing and the by- product is secondary after processing. For example the main product after processing maize is normally flour whilst the bi-product is normally the bran. The main processed product was flour/meal with 218,715 Chart 3.92 Percent of Crop Processing Households by Method of Processing 0% 25% 50% 75% 100% Pangani Tanga Handeni Kilindi Korogwe Muheza Lushoto District Percent of Households On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co-operative Union By Trader On Large Scale Farm Other Chart 3.93 Percent of Households by Type of Main Processed Product Flour / Meal 92% Pulp 0.1% Other 1% Juice 0.3% Oil 1% Grain 6% Chart 3.91a Households Processing Crops Households not Processing, 29,414, 11% Households Processing, 235,784, 89% 0 20 40 60 80 100 Percent of Households Processing Lushoto Kilindi Handeni Muheza Korogwe Pangani Tanga District Chart 3.91b Percentage of Households Processing Crops by District RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 64 households processing crops into flour (93%) followed by grain with 13,494 households (5.7%). The remaining products were produced by a small number of households (Chart 3.93). The number of households producing by-products accounted for 20.6 percent of the households processing crops. The most common by-product produced by crop processing households was bran with 40,044 households (82%) followed by Husks (3,807 households, 8%), cake (1,765 households, 4%) and pulp (1,576 households, 3%). The remaining by-products were produced by a small number of households (Chart 3.94). 3.7.2.3 Main Use of Primary Processed Products Primary processed products were used for households or human consumption, fuel for cooking, for selling and for animal consumption. The most important use was for household/human consumption which represented 98 percent of the total households that used primary processed product (Chart 3.95). Korogwe was the only district that used primary products as fuel for cooking. Out of 1,768 households that sold processed products, 871 were from Lushoto (49% of the total number of households selling processed products in the region), followed by Korogwe with 636 households (36%), Tanga with 115 households (6.5%), Pangani with 98 households (5.5%) and Kilindi with 49 households (2.8%) (Chart 3.96). Compared to other districts in Tanga region, Pangani had the highest percent of households that sold processed products. This is followed by Tanga (1.86), Korogwe (1.75%), Lushoto (1.06%) and Kilindi (0.28%). 3.7.2.4 Outlets for Sale of Processed Products Most houseyholds that sold processed products sold to local market and trade stores (9,180 households, 41% of households that sold crops). This was followed by selling to neighbours (7,582 households, 35%), trader at farm (2,374 households, 11%), marketing co-operatives (1,334 households, 6%), large scale farm (595 households, 2.7%) and Farmers Associations (568 households, 2.6%) (Chart 3.97). Chart 3.94 Number of Households by Type of By-product Juice, 99, 0% Shell, 352, 1% Other, 879, 2% Cake, 1,765, 4% Pulp, 1,576, 3% Bran, 40,044, 82% Husk, 3,807, 8% Chart 3.95 Use of Processed Product Household/ human consumption, 277,966, 98% Fuel for Cooking, 218, 0% Sale Only, 4,194, 1% Did Not Use, 984, 0% Animal Consumption, 278, 0% 0.00 10.00 20.00 30.00 40.00 50.00 Percentage of households Lushoto Korogwe Tanga Pangani Kilindi Muheza Handeni District Chart 3.96 Percentage of Households Selling Processed Crops by District Chart 3.97 Location of Sale of Processed Products Neighbours, 7,582, 35% Local Market / Trade Store, 9,180, 41% Marketing Co- operative, 1,334, 6% Other, 169, 1% Trader at Farm, 2,374, 11% Large Scale Farm, 595, 3% Farmers Association, 568, 3% RESULTS – Crop Storage, Processing and Marketing __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 65 There are large differences between districts in the proportion of households selling processed products to neighbours with Tanga district having the largest percent of households in the district selling to neighbours (65%), whereas Lushoto had only 24 percent. Lushoto had a higher percent of households relying on local markets/trade stores than other outlets. Compared to other districts, Pangani had the highest percent of households selling processed products to traders at farm. In Muheza, the sale of processed produce to farmer associations was most prominent compared to other districts. The districts that had the highest proportion of households selling processed products to marketing cooperative were Lushoto and Korogwe. 3.7.3 Crop Marketing The number of households that reported selling crops was 197,168 which represent 74.8 percent of the total number of crop growing households. The percent of crop growing households selling crops was highest in Muheza (84%) followed by Lushoto (80%), Tanga (77%), Kilindi (76%), Pangani (70%) Korogwe (65%) and Handeni (64%) (Chart 3.99 and Map 3.42). 3.7.3.1 Main Marketing Problems Low price for agricultural produce was the main marketing problem reported by households (82% of crop growing households). Apart from low market prices, other problems were longer distances to the markets (8%), lack of transport (4%), high transport costs (4%), lack of buyers (1%) and lack of market information (1%). Other marketing problems are minor and represented less than 1 percent of the total reported problems. 3.7.3.2 Reasons for Not Selling Crops The main reason for not selling crops was reported as “insufficient production to sell”, representing 86 percent of the smallholders. The remaining reasons for not selling are in such low numbers that it is not appropriate to rank their importance (Table 3.11). This general trend applies to all districts except for Pangani and Korogwe where the proportion of households reporting other reasons for not marketing their agricultural products is relatively high (16% and 12% respectively). Table 3.12 Reasons for Not Selling Crop Produce Main Reason Household Number % Production Insufficient to Sell 72,966 86.3 Other 6,735 8.0 Price Too Low 2,253 2.7 Trade Union Problems 1,668 2.0 Co-operative Problems 491 0.6 Market Too Far 284 0.3 Government Regulatory Board Problems 146 0.2 Total 84,543 100.0 Chart 3.99 Number of Crop Growing Households Selling Crops by District 0 20,000 40,000 60,000 80,000 Lushoto Muheza Handeni Korogwe Kilindi Tanga Pangani District Number of Households 0 20 40 60 80 100 Percent Number of Households Selling Crops Percent of Households Selling Crops Chart 3.100 Percentage Distribution of Households that Reported Marketing Problems by Type of Problem Open Market Price Too Low 82% Co-operative Problems 0% Transport Cost Too High 4% Lack of Market Information 1% Market too Far 8% No Transport 4% No Buyer 1% Chart 3.98 Percent of Households Selling Pro cessed Pro ducts by Outlet for Sale and District 0% 20% 40% 60% 80% 100% Tanga Muheza Pangani Handeni Kilindi Korogwe Lushoto District Percent of Households Selling Neighbours Local Market / Trade Store Marketing Co-operative Farmers Association Large Scale Farm Trader at Farm Other RESULTS – Access to Crop Production Services __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 66 3.8 Access to Crop Production Services 3.8.1 Access to Agricultural Credit The census result shows that in Tanga region very few agricultural households (1,022, 0.4%) accessed credit out of which 453 (44%) were male-headed households and 569 (56%) were female headed households. In Lushoto district only female headed households got agricultural credit whereas in Korogwe, Tanga and Handeni districts only male households accessed credit. In Muheza district both male and female headed households accessed agricultural credit (Table 3.12). 3.8.1.1 Source of Agricultural Credit The major agricultural credit provider in Tanga region were Religious Organizations/Non Governmental Organizations/ projects which collectively provided credit to 382 agricultural households (38% of the total number of households that accessed credit), followed by family, friends and relatives (21%), saving and credit society (20%), trader/trade store (8%), commercial bank (3%) and other sources (10%) (Chart 3.101). Commercial banks were the sole source of credit in Tanga district and savings and credit societies were found in Handeni district only. Trader/trader store was a major credit provider in Muheza district. Religious organization, NGO and projects were more involved in funding a relatively great number of households in Lushoto disrtict (Chart 3.102). 3.8.1.2 Use of Agricultural Credit A large proportion of the agricultural credit provided to agricultural households in the region were used on unspecified activities (24%), followed by hiring labour (22%), fertilizers (16%) and seeds (12%). The proportion of credits intended to be used for livestock rearing, irrigation structures, tools, equipment and agro-chemicals was very low (Chart 3.103). Table 3.13 Number of Agricultural Households that Received Credit by Sex of Household Head and District Male Female District Number % Number % Total Lushoto 0 0 404 100 404 Korogwe 107 100 0 0 107 Muheza 78 32 165 68 243 Tanga 61 100 0 0 61 Handeni 208 100 0 0 208 Total 453 44 569 56 1,022 Chart 3.102 Number of Households Receiving Credit by Main Source of Credit and District 0% 20% 40% 60% 80% 100% Lushoto Korogw e Muheza Tanga Handeni District Percent of Households Family, Friend and Relative Commercial Banks Saving & Credit Society Trader/Trade Store Religious Organisation/NGO/Project Other Chart 3.101 Percentage Distribution of Households Receiving Credit by Main Source Trader / Trade Store 8% Other 10% Saving & Credit Society 20% Family, Friend and Relative 21% Religious Organisation / NGO / Project 38% Commercial Bank 3% Chart 3.103 Proportion of Households Receiving Credit by Main Purpose of the Credit Seeds 12% Tools / Equipment 7% Irrigation Structures 7% Agro-chemicals 7% Other 27% Fertilizers 17% Labour 23% Chart 3.104 Reasons for not Using Credit (% of Households) Interest rate/cost too high, 4,097, 2% Other, 659, 0% Credit granted too late, 684, 0% Not needed, 4,490, 2% Difficult bureaucracy procedure, 9,470, 4% Did not w ant to go into debt, 15,787, 6% Not available, 27,302, 10% Don't know about credit, 50,220, 19% Did not know how to get credit, 151,467, 57% RESULTS – Access to Crop Production Services __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 67 3.8.1.3 Reasons for Not Using Agricultural Credit The main reason for not using agricultural credit as a source of finance was little credit awareness accounting to 76 percent of the agricultural households (“did not know how to get credit” and “don’t know about credit”). This was followed by households reporting the un-availability of credit (10.3%), followed by “not wanting to go into debt” (6.0%) The rest of the reasons were collectively less than 8 percent of the households. 3.8.2 Crop Extension The number of Agricultural households that received crop extension was 121,486 (46% of total crop growing households in the region) (Chart 3.105). Some districts have more access to extension services than others, with Korogwe having a relatively high proportion of households (84%) that received crop extension messages in the district followed by Lushoto (49%), Muheza (43%), Pangani (39%), Kilindi (27%), Handeni (22%) and Tanga (14%) (Chart 3.106 and Map 4.43). 3.8.2.1 Sources of Crop Extension Messages Of the households receiving extension advice the Government provided the greatest proportion (98.9%, 119,592 households). NGOs provided 0.4 percent, large scale farms 0.4 percent and the remaining providers less than 0.3 percent (Chart 3.107), however district differences exist with the proportion of the households receiving advice from government services ranging from between 94.0 percent and 100 percent in Handeni and Lushoto respectively. Chart 3.105 Number of Households Receiving Extension Advice Households Not Receiving Extension , 143,711, 54% Households Receiving Extension , 121,487, 46% Chart 3.106 Number of Households Receiving Extension by District 0 10,000 20,000 30,000 40,000 50,000 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Number of Households 0 20 40 60 80 100 Percent of Households Households Receiving Extension Percentage of Households Receiving Extension Chart 3.107 Number of Households Receiving Extension Messages by Type of Extension Provider Large Scale Farm 0.4% Cooperative 0.1% NGO / Development Project 0.4% Other 0.2% Government 98.9% Chart 3.108 Number of Households Receiving Extension by Quality of Services Good, 75,884, 62.5% Average, 32,287, 26.6% Poor, 1,505, 1.2% No Good, 1,594, 1.3% Very Good, 10,217, 8.4% Pangani Tanga Korogwe 737 14,855 8,835 1,166 818 5,183 1,907 17.2% 19.2% 13.1% 4% 10.3% 10.9% 3.9% Kilindi Handeni Muheza Lushoto 12,000 to 15,000 9,000 to 12,000 6,000 to 9,000 3,000 to 6,000 0 to 3,000 Tanga 2,807 1,266 21,091 42,132 38,500 10,334 5,356 39% 14% 49% 84% 43% 22% 27% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.43 TANGA Number of Households and Percent of Total Households Receiving Crop Extension Services by District 33,000 to 43,000 25,000 to 33,000 17,000 to 25,000 9,000 to 17,000 1,000 to 9,000 Number Households Receiving Crop Extension Services Number Households Receiving Crop Extension Services Percent of Total Households Receiving Crop Extension Services MAP 3.44 TANGA Number and Percent of Crop Growing Households Using Improved Seeds by District Number of Households Growing Crops Using Improved Seeds Number of Households Growing Crops Using Improved Seeds Percent of Total Households Selling Crops Tanzania Agriculture Sample Census RESULTS 68 RESULTS – Access to Inputs __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 69 3.8.2.2 Quality of Extension An assessment of the quality of extension indicates that 63 percent of the households receiving extension ranked the service as being good followed by average (27 %), very good (8%), no good (1%) and poor (1%) (Chart 3.108). However, care should be exercised when making decisions on quality of extension and also other variables in the extension report as all the enumerators were extension agents and some degree of bias is expected. 3.9 Access to Inputs Access to inputs in this section refers to all crop growing households in Tanzania regardless of whether the household grew annual or permanent crops. In previous sections the reference was on annual crops only. Because of this, some of the figures presented in this section may be slightly different from the previous section on inputs use (Section 3.5). Data on source of inputs is only found in this section and it applies to both annual and permanent crops. A small number of households use inputs and this is particularly true of inputs that are not produced on farm i.e., improved seeds, fungicides, inorganic fertiliser and herbicides. In Tanga region farm yard manure is used by 51,812 households which represents 19.7 percent of the total number of crop growing households. This is followed by households using improved seeds (12.7%), compost (5.5%) fungicide (5.3%), inorganic fertiliser (3%), and herbicide (0.3%) (Table 2.13). 3.9.2 Inorganic Fertilisers Smallholders that use inorganic fertiliser in Tanga mostly purchase from the local market/trade store (90.5% of the total number of inorganic fertiliser users). The remaining sources of inorganic fertilisers are minor (Chart 3.109). Access to inorganic fertiliser is mainly less than 10 km from the household with most households residing between 3 and 10 km from the source (39%), followed by between 1 and 3 km (30%) and less than 1 km (20%) (Chart 3.110). Due to the very small number of households using inorganic fertilisers coupled with the small number of households responding to “not available” (12% ) as the reason for not using, it may be assumed that access to inorganic fertiliser is not the main reason for not using it. Other reasons such as cost are more important with 70 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable the demand would be higher and access to inorganic fertiliser would be made more available. Table 2.14 Access to Inputs Households With Access to Input Households Without Access to Inputs Type of Input Number % Number % Farm Yard Manure 51,812 19.7 211,716 80.3 Improved Seeds 33,500 12.7 230,028 87.3 Pestcides/Fungicide 13,971 5.3 249,557 94.7 Compost 14,580 5.5 248,948 94.5 Inorganic Fertiliser 8,223 3.1 255,304 96.9 Herbicide 835 0.3 262,692 99.7 Chart 3.109 Number of Households by Source of Inorganic Fertiliser 90.5 3.1 1.9 1.8 1.6 1.2 0 2,000 4,000 6,000 8,000 Local Market / Trade Store Co-operative Large Scale Farm Locally Produced by Household Neighbour Development Project Source of Inorganic Fertiliser Number of Households Chart 3.110 Number of Households Reporting Distance to Source of Inorganic Fertiliser 0.0 10.0 20.0 30.0 40.0 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Access to Inputs __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 70 More smallholders use inorganic fertilisers in Lushoto than in other districts in Tanga region (72% of households using inorganic fertilisers), followed by Korogwe (17%) and Muheza (6.2%). Other districts use very little inorganic fertiliser. 3.9.3 Improved Seeds The percent of households that use improved seeds was 13 percent of the total number of crop growing households. Most of the improved seeds are from the local market/trade store (77.4%). Other less important sources of improved seed are from development partners (6.5%), neighbours (6.3%) and locally produced by household (6.3%). Only 0.9 percent of households using improved seed obtain them from large scale farms (Chart 3.111). Access to improved seed is better than access to chemical inputs with 30 percent of households obtaining the input within 1 km of the household (Chart 3.112). This is in line with the higher use of improved seed compared to other chemical inputs, which further supports the concept that it is not the availability that is the main issue in the use of inputs but rather other factors such as cost. The districts that mostly use improved seeds are Lushoto (44.3 percent of the total number of households using improved seeds in Tanga region), followed by Korogwe (26.4%) and Handeni (15.5%). Use of improved seeds in other districts is of minor importance (Map 3.44). 3.9.4 Insecticides and Fungicide Most smallholder households using insecticides and fungicides mainly purchase them from local markets/trade stores (91% of the total number of fungicide users). Other sources of insecticides/ fungicides are of minor importance (Chart 3.113). Chart 3.114 shows that there is no distinct pattern for the number of households with varying distances from the source of insecticide/fungicide. The small number of households using insecticides/fungicides coupled with the 7 percent of Chart 3.111 Number of Households by Source of Improved Seed 0.4 0.1 0.6 0.6 0.9 1.0 6.3 6.3 6.5 77.4 0 10,000 20,000 30,000 Local Market / Trade Store Development Project Neighbour Locally Produced by Household Co-operative Large Scale Farm Crop Buyers Local Farmers Group Other Secondary Market Source of Improved Seed Number of Households Chart 3.113 Number of Households by Source of Insecticide/fungicide 91.0 1.5 1.4 1.3 1.2 1.2 0.8 0.9 0.1 0.8 0 3,000 6,000 9,000 12,000 Local Market / Trade Store Crop Buyers Locally Produced by Household Development Project Co-operative Neighbour Large Scale Farm Other Secondary Market Local Farmers Group Source of Insecticide/fungicide Number of Households Chart 3.112 Number of Households reporting Distance to Source of Improved Seed 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households Chart 3.114 Number of Households Reporting Distance to Source of Insecticides/Fungicides 0 10 20 30 Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Distance (km) Percent of Households RESULTS – Tree Planting __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 71 households responding to “not available” as the reason for not using it may be assumed that access is not the main reason for not using. Other reasons such as cost are more important with 74 percent of households responding to cost factors as the main reason for not using. In other words, it is assumed that if the cost was affordable, the demand would be higher and access to insecticides/fungicides would be made more available. Fungicide is used more in Lushoto district (60.9 percent of the total number of households that use fungicide in the region), followed by Korogwe (15.8%) and Handeni (15%). ,Insecticides/fungicides use in other districts is of minor importance. 3.10 Tree Planting The number of households involved in tree farming was 28,110 representing 11 percent of the total number of agriculture households (Chart 3.115). The number of trees planted by smallholders on their allotted land was 1,215,222 trees. The average number of trees planted per household planting trees was 43 trees. The main species planted by smallholders is Gravellia spp (648,235 trees, 53%), followed by Tectona grandis (313,570, 26%), then Eucalyptus (91,754, 7%) and Cyprus spp (72,130 trees, 6%). The remaining trees species are planted in comparatively small numbers (Chart116.). Lushoto has the largest number of smallholders with planted trees than any other district (49.3%) and is dominated by Gravellia species. This is followed by Muheza (32.9%) which is dominated by Tectona grandis and to a lesser extent Gravellia, then Korogwe (17%) and Kilindi (0.4%) which is mainly planted with Moringa (Chart 3.117 and Map 3.45.). Chart 2.116 Number of Planted Trees by Species - TANGA 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp Leucena Spp Others Tree Species Number of Trees Chart 3.117 Number of Trees Planted by Smallholders by Species and Region 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Lushoto Korogw e Muheza Tanga Pangani Handeni Kilindi Region Number of Trees Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp Leucena Spp Other Chart 3.118 Number of Trees Planted by Location Field boundary, 482,086, 40% Scattered in field, 427,672, 35% Plantation, 305,464, 25% Chart 3.115 Number of Households w ith Planted Trees Growing trees, 28,110, 11% Not growing trees, 235,417, 89% RESULTS –Irrigation and Erosion Control Facilities __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 72 Smallholders mostly plant trees on the boundary of fields. The proportion of households that plant on field boundaries is 40 percent, followed by scattered around fields (35%) and then trees planted in a plantation or coppice (25%) (Chart 3.118). The main purpose of planting trees is to obtain planks/timber (45.9%). This is followed by wood for fuel (29.8%), shade (11.0%) and poles (10.7%) (Chart 3.119). 3.11 Irrigation and Erosion Control Facilities Erosion control and water harvesting facilities are grouped together as they normally have dual purposes of reducing erosion and increasing the amount of water available for crop production. The number of agricultural households that had soil erosion and water harvesting facilities on their farms was 30,288 which represents 11 percent of the total number of agricultural households in the region (Chart 3.120). The proportion of households with soil erosion control and water harvesting facilities was highest in Lushoto district (23%) followed by Korogwe (10%), Muheza (8%), Kilindi (3%), Handeni (2%), Tanga (1%) and Pangani (0.5%) (Chart 3.121). Terraces accounted for 28 percent of the total number of structures, followed by vetiver grass (21%), water harvesting bunds (20%), erosion control bunds (14%), tree belts (12%), drainage ditches (4%) gabions/sandbags (1%) and dams (0.5%) (Chart 3.122 and Map 3.46). Erosion control by terraces, vetiver grass and water harvesting bunds together had 207,920 structures. This represented 69 percent of the total structures in the region. The remaining 31 percentages were shared among the rest of the erosion control methods mentioned above. Lushoto and Korogwe districts had 258,206 erosion control structures (86 percent of the total erosion structures in the region). Chart 3.119 Number of Households by Purpose of Planted Trees 0.0 10.0 20.0 30.0 40.0 50.0 Planks / Timber Wood for Fuel Shade Poles Other Medicinal Use Percent of Households Chart 3.120 Number of Households with Erosion Control/Water Harvesting Facilities Households Without Facilities, 234,910, 89% Households with facilities, 30,288, 11% Chart 3.121 Number of Households with Erosion Control/Water Harvesting Facilities 23 10 8 3 2 1 0.5 0 5,000 10,000 15,000 20,000 25,000 Lushoto Korogwe Muheza Kilindi Handeni Tanga Pangani District Number of Households 0 5 10 15 20 25 Percent Number of Households Percent Chart 3.122 Number of Erosion Control/Water Harvesting Structures by Type of Facility 28.0 21.0 19.9 14.1 12.0 3.8 1.0 0.2 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Terraces Vetiver Grass Water Harvesting Bunds Erosion Control Bunds Tree Belts Drainage Ditches Gabions / Sandbag Dam Type of Facility Number of Structures Tanga Handeni Kilindi 68 0 0 925 13,571 1,587 43,906 0.8% 0% 27.6% 50.7% 3.5% 0% 5% Pangani Korogwe Muheza Lushoto 77 424 5,277 143 5,902 16,093 195 0.9% 0.9% 11.5% 2% 1% 12% 18.6% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.45 TANGA Number and Percent of Smallholder Planted Trees by District Number of Smallholder Planted Trees Number of Smallholder Planted Trees Percent of Smallholder Planted Trees MAP 3.46 TANGA Number and Percent of Households with Water Harvesting Bunds by District Number of Households with Water Harvesting Bunds Number of Households with Water Harvesting Bunds Percent of Households with Water Harvesting Bunds 12,800 to 16,100 9,600 to 12,800 6,400 to 9,600 3,200 to 6,400 0 to 3,200 35,200 to 44,000 26,400 to 35,200 17,600 to 26,400 8,800 to 17,600 0 to 8,800 Tanzania Agriculture Sample Census RESULTS 73 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 74 3.12 LIVESTOCK RESULTS 3.12.1 Cattle Production The total number of cattle in the region was 378,338. Cattle are the dominant livestock type in the region followed by goats, sheep and pigs. The region had 2.2 percent of the total cattle population on Tanzania Mainland. 3.12.1.1 Cattle Population The number of indigenous cattle in Tanga region was 350,210 (92.6 % of the total number of cattle in the region), 27,829 cattle (7%) were dairy breeds and 298 cattle (1.4%) were beef breeds. The census results show that 86,792 agricultural households in the region (32.7% of total agricultural households) kept 0.4 million cattle. This was equivalent to an average of 7 heads of cattle per cattle-keeping-household. The district with the largest number of cattle was Handeni which had about 106,901cattle (28.3% of the total cattle in the region). This was followed by Lushoto (75,911 cattle, 20.1%), Korogwe (74,238 cattle, 19.6%), Muheza (63,355 cattle, 16.7%), Kilindi (46,019 cattle, 12.2%) and Tanga (11,012 cattle, 2.9%). Pangani district had the least number of cattle (901 cattle, 0.2%) (Chart 3.123 and Map 3.47). However Tanga district had the highest density (92 head per km2 ) (Map 3.48). Although Handeni district had the largest number of cattle in the region, most of it was indigenous. The number of dairy cattle was very small and the number of beef cattle was insignificant. Lushoto district had the largest number of diary cattle in the region. In general, the number of beef cattle in the region was insignificant (Chart 3.124). 3.12.1.2 Herd Size Eighty one percent of the cattle-rearing households had herds of size 1-5 cattle with an average of two cattle per household. Herd sizes of 6-30 accounted for about 30 percent of all cattle in the region. Only 3 percent of the cattle rearing households had herd sizes of 31- 100 cattle. About 97.5 percent of total cattle rearing households had herds of size 1-30 cattle and owns 59 percent of total cattle in the region, resulting in an average of 4 cattle per cattle rearing household. There were about 280 households with a herd size of more than 151 cattle each (95,883 cattle in total) resulting in an average of 342 cattle per household. 0 20 40 60 80 100 120 Number of Cattle ('000') Handeni Lushoto Korogwe Muheza Kilindi Tanga Pangani Districts Chart 3.123 Total Number of Cattle ('000') by District Chart 3.124 Number of Cattle by Type and District 0 40,000 80,000 120,000 Handeni Korogwe Lushoto Muheza Kilindi Tanga Pangani Districts Number of Cattle Indigenous Beef Dairy 11,012 63,355 901 46,019 106,901 74,238 75,911 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 48 1 92 39 20 32 55 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.48 TANGA Cattle Density by District as of 1st October 2003 80 to 100 60 to 80 40 to 60 20 to 40 0 to 20 Number of Cattle per Square Km MAP 3.47 TANGA Cattle population by District as of 1st Octobers 2003 84,000 to 107,000 63,000 to 84,000 42,000 to 63,000 21,000 to 42,000 0 to 21,000 Number of Cattle Tanzania Agriculture Sample Census RESULTS 75 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 76 3.12.1.3 CattlePopulation Trend Cattle population in Tanga decreased during the period of eight years from 653,549 in 1995 to 378,337 cattle in 2003. This trend depicts an overall annual negative growth rate of -6.6 percent (Chart 3.125). However, there was a very sharp decrease in number of cattle for the period of four years from 1995 to 1999 at the rate of –19.3 percent whereby the number dropped from 653,549 to 276,739. However, the number of cattle is estimated to have increased from 276,739 in 1999 to 378,337 in 2003at the rate of 8.13 percent. 3.12.1.4 Improved Cattle Breeds The total number of improved cattle in tanga region was 28,127 (27,829 dairy and 298 improved beef). The diary cattle constituted 7.4 percent of the total cattle and 99 percent of improved cattle in the region. The number of beef cattle in the region was insignificant constituting only 1 percent of the total number of the improved cattle and 0.1 percent of the total cattle The number of improved cattle increased from 20,420 in 1995 to 28,127 in 2003 at an annual growth rate of 4.1 percent. The growth rate was higher for the period from 1995 to 1999 (5.9%) than from 1999 to 2003 (2.3%) (Chart 126). 3.12.2. Goat Production Goat rearing was the second most important livestock keeping activity in the region followed by sheep and pig rearing. In terms of total number of goats on the Mainland, Tanga region ranked 11 out of the 21 regions with 4.4 percent of the total goats on the Mainland. 3.12.2.1 Goat Population The number of goat-rearing-households in Tanga region was 68,227 (26% of all agricultural households in the region) with a total of 514,620 goats giving an average of 8 head of goats per goat-rearing-household. Handeni had the largest number of goats (170,860 goats, 33% of all goats in the region), followed by Muheza (96,195 goats, 19%), Korogwe (86,441 goats, 17%), Lushoto (73,449 goats, 14%) and Kilindi (66,928 goats, 13%). Tanga and Pangani districts had the least number of goats (10,390 goats, 2% and 10,357 goats, 2% respectively) (Chart 3.127 and Map 3.49). However Tanga district had the highest density (87 head per km2 ) (Map 3.50). 653,549 277,000 378,338 - 200,000 400,000 600,000 800,000 Number of cattle 1995 1999 2003 Year Chart 3.125 Cattle Population Trend 0 40 80 120 160 200 Number of Goats ('000'). Handeni Muheza Korogwe Lushoto Kilindi Tanga Pangani District Chart 3.127 Total Number of Goats ('000') by District 20,420 25,675 28,127 - 20,000 40,000 Number of cattle 1995 1999 2003 Year Chart 3.126 Improved Cattle Population Trend Pangani 10,357 10,390 96,195 66,928 170,860 86,441 73,449 Kilindi Handeni Tanga Korogwe Muheza Lushoto 15 87 60 29 51 56 54 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.50 TANGA Goat Density by District as of 1st October 2003 71 to 87 57 to 71 43 to 57 29 to 43 15 to 29 Number of Goats per Square Km MAP 3.49 TANGA Goat Population by District as of1st Octobers 2003 138,000 to 171,000 106,000 to 138,000 74,000 to 106,000 42,000 to 74,000 10,000 to 42,000 Number of Goats Tanzania Agriculture Sample Census RESULTS 77 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 78 3.12.2.2 Goat Herd Size Forty eight percent of the goat-rearing households had herd size of 1-4 goats with an average of 2 goats per goat rearing household. Eighty seven percent of total goat-rearing households had herd size of 1-14 goats and owned 57 percent of the total goats in the region resulting in an average of 5 goats per goat-rearing households. The region had 765 households (1.1%) with herd sizes of 40 or more goats each (53,587 goats in total), resulting in an average of 70 goats per household. 3.12.2.3 Goat Breeds Goat husbandry in the region was dominated by the indigenous breeds that constituted 95 percent of the total goats in Tanga region. Improved goats for meat and diary goats constituted 3 and 2 percent of total goats respectively. 3.12.2.4 Goat Population Trend The overall annual growth rate of goat population from 1995 to 2003 was -4.4 percent. This negative trend implies eight years of population decrease from 736,727 in 1995 to 514,620 in 2003. The number of goats decreased from 736,727 in 1995 at an estimated annual rate of -18.9 percent to 317,924 in 1999. From 1999 to 2003, the goat population increased at an annual rate of 12.8 percent (Chart 128). 3.12.3. Sheep Production Sheep rearing was the third important livestock keeping activity in Tanga region after cattle and goats. The region ranked 9 out of 21 Mainland regions and had 4 percent of all sheep on Tanzania Mainland. 3.12.3.1 Sheep Population The number of sheep-rearing households was 35,381 (13% of all agricultural households in Tanga region) rearing 164,209 sheep, giving an average of 5 heads of sheep per sheep-rearing household. The district with the largest number of sheep was Lushoto with 64,742 sheep (39%of total sheep in Tanga region) followed by Korogwe (35,367 sheep, 22%), Muheza (25,140 sheep, 15%), Handeni (19,570 sheep, 12%), Kilindi (18,222 sheep, 11%) and Tanga (1,010 sheep, 0.6%). Pangani District had the least number of sheep (158 sheep) (Chart 3.129 and Map 3.51). Lushoto district also had the highest density (47 head per km2 ) (Map 3.52). Sheep rearing was dominated by indigenous breeds that constituted 91 percent of all sheep kept in the region. Only 9 percent of the total sheep in the region were improved breeds. 736,727 317,924 514,620 - 200,000 400,000 600,000 800,000 Number of goats 1995 1999 2003 Year Chart 3.128 Goat Population Trend 0 20,000 40,000 60,000 80,000 Number of sheep Lushoto Korogwe Muheza Handeni Kilindi Tanga Pangani District Chart 3.129 Total Number of Sheep by District 35,367 25,140 1,010 158 18,222 19,570 64,742 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto Lushoto 0 8 8 6 23 16 47 Kilindi Handeni Pangani Tanga Korogwe Muheza MAP 3.52 TANGA Sheep Density by District as of 1st October 2003 37.6 to 47 28.2 to 37.6 18.8 to 28.2 9.4 to 18.8 0 to 9.4 Number of Sheep per Square Km MAP 3.51 TANGA Sheep population by District as of 1st Octobers 2003 51,700 to 64,800 38,800 to 51,700 25,900 to 38,800 13,000 to 25,900 100 to 13,000 Number of Sheep Tanzania Agriculture Sample Census RESULTS 79 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 80 3.12.3.2 Sheep Population Trend The overall annual growth rate of the sheep population for the eight year period from 1995 to 2003 is estimated at -4.9 percent. The population decreased at an annual rate of -23.2 percent from 246,263 in 1995 to 85,679 in 1999. From 1999 to 2003, sheep population increased at an annual rate of 17.7 percent (Chart 3.130). 3.12.4. Pig Production Piggery is the least important livestock keeping activity in the region after cattle, goats and sheep. The region ranks 16 out of 21 Mainland regions and is 0.64 percent of the Mainland total pigs. The number of pig-rearing agricultural households in Tanga region was 2,601 (1% of the total agricultural households in the region) rearing 6,281 pigs. This gives an average of 2 pigs per pig-rearing household. The district with the largest number of pigs was Korogwe with 2,886 pigs (46% of the total pig population in the region) followed by Muheza (1,582 pigs, 25%), Handeni (759 pigs, 12%), Kilindi (389 pigs, 6%), Tanga (373 pigs, 6%) and Lushoto (292 pigs, 5%) (Chart 3.131 and Map 3.53). However Tanga district had the highest density (3.1 head per km2 ) (Map 3.54). There are no pigs were in Pangani district. 3.12.4.1 Pig Population Trend The overall annual growth rate of the pig population for the eight years period from 1995 to 2003 was 24.7 percent. During this period the population grew from 1,072 to 6,281. The pig population increased from 1072 in 1995 to 2, in 1995 a higher rate of 26.2 percent. The growth rate dropped to 23.3 percent during the following four years from 1999 to 2003 in which pig population increased from 2,715 to 6,281(Chart 3.132). 246,263 85,679 164,209 - 100,000 200,000 300,000 Number of sheep 1995 1999 2003 Year Chart 3.130 Sheep Population Trend 0 1,000 2,000 3,000 Number of Pigs Korogwe Muheza Handeni Kilindi Tanga Lushoto District Chart 3.131 Total Number of Pigs by District 1,072 2,715 6,281 - 4,000 8,000 Number of pigs 1995 1999 2003 Year Chart 3.132 Pig Population Trend 0 373 1,582 389 759 2,886 292 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 0.2 0.2 0 3.1 1 1.9 0.2 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.54 TANGA Pig Density by District as of 1st October 2003 2.48 to 3.1 1.86 to 2.48 1.24 to 1.86 0.62 to 1.24 0 to 0.62 Number of Pigs per Square Km MAP 3.53 TANGA Pig Population by District as of 1st Octobers 2003 2,890 to 2,890 1,580 to 2,890 760 to 1,580 370 to 760 0 to 370 Number of Pigs Tanzania Agriculture Sample Census RESULTS 81 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 82 3.12.5 Chicken Production The poultry sector in Tanga region was dominated by chicken production. The region contributed 5.4 percent to the total chicken population on Tanzania Mainland. 3.12.5.1 Chicken Population The number of households keeping chicken was 176,806 raising about 1,788,767 chickens. This gives an average of 10 chickens per chicken-rearing household. In terms of total number of chickens in the country, Tanga region was ranked eighth out of the 21 Mainland regions. The District with largest number of chickens was Muheza (468,300 chickens, 26% of the total number of chickens in the region) followed by Handeni (430,586, 24%), Korogwe (264,547, 15%), Lushoto (247,867, 14%), Kilindi (162,907, 9%) and Pangani (121,397 chickens, 7%). Tanga district had the smallest number of chickens (93,168, 5%) (Chart 3.133 and Map 3.55). However Tanga district had the highest density (776 head per km2 ) (Map 3.56). 3.12.5.2 Chicken Population Trend The overall annual chicken population growth rate during the eight-year period from 1995 to 2003 was 0.8 percent. The population decreased at a rate of -17.8 percent from 1995 to 1999 after which it increased to 23.7 percent for the four year period from 1999 to 2003 (Chart 3.134). Ninety two percent of all chicken in Tanga region were of indigenous breed. The dominance of indigenous breed makes the population trend for the indigenous chicken more-or-less the same as that of the total chickens in the region. 3.12.5.3 Chicken Flock Size The results indicate that about 85 percent of all chicken-rearing households were keeping 1-19 chickens with an average of 6 chickens per holder. About 16 percent of holders were reported to be keeping the flock size of 20 to 99 chickens with an average of 31 chickens per holder. Only 0.13 percent of holders kept the flock sizes of more than 100 chickens at an average of 208 chickens per holder (Table 3.14). Table 3.15 Number of Households and Chickens Raised by Flock Size Flock Size Number of Households % Number of Chicken Average Chicken by Households 1-4 66,036 37 164,365 2 5-9 47,677 27 308,323 6 10-19 36,365 21 461,035 13 20-29 15,520 9 345,418 22 30-39 4,980 3 157,343 32 40-49 3,245 2 137,272 42 50-99 2,760 2 168,679 61 100+ 223 0 46,333 208 Total 176,806 100 1,788,767 10 1,673,776 764,379 1,788,767 - 1,000,000 2,000,000 Number of Chicken 1995 1999 2003 Year Chart 3.134 Chicken Population Trend 0 100,000 200,000 300,000 400,000 500,000 Number of Chickens Muheza Handeni Korogwe Lushoto Kilindi Pangani Tanga District Chart 3.133 Total Number of Chickens by District 121,393 93,168 468,300 430,586 162,907 264,547 247,867 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto 181 776 290 71 127 170 181 Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.56 TANGA Density of Chicken by District as of 1st October 2003 630 to 780 490 to 630 350 to 490 210 to 350 70 to 210 Number of Chickens per Square Km MAP 3.55 TANGA Number of Chicken by District as of 1st October 2003 393,000 to 469,000 318,000 to 393,000 243,000 to 318,000 168,000 to 243,000 93,000 to 168,000 Number of Chickens Tanzania Agriculture Sample Census RESULTS 83 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 84 3.12.5.4 Improved Chickens (layers and broilers) Layers chicken population in Tanga Region increased at an annual rate of 48.2 percent for the period of four years from 6,136 in 1999 to 29,630 in 2003. The number of improved chicken was most significant in Tanga District followed by Lushoto District (Chart 3.135). The overall annual growth rate for broilers during the eight-year period from 1995 to 2003 was 12.9 percent during which the population grew from 2,986 to 7,859. The annual growth rate was higher (65.4%) for the period of four years from 1995 to 1999. The broiler population exhibited a decreasing trend at the rate of -23 percent per annum for the period of four years resulting at increase from 22,327 in 1999 to 7,859 2003 (Chart 3.136). 3.12.6. Other Livestock There were 117,486 ducks, 503 turkeys, 16,611 rabbits and 17,502 donkeys raised by rural agricultural households in Tanga region. Table 3-32 indicates the number of livestock kept in each district. The biggest number of ducks in the region was found in Muheza District (37% of all ducks in the region), followed by Korogwe (24%), Handeni (22%), Lushoto (7%), Tanga (5%) and Kilindi (4). Pangani district had the least number of ducks estimated at 2 percent of total ducks in the region. Turkeys were reported in Muheza and Tanga districts only (Table 3.14). 3.12.7 Pest and Parasite Incidence and Control The results indicate that 40 percent and 25 percent of the total livestock-keeping households reported to have encountered ticks and tsetse fly problems respectively. Chart 3.137 shows that there is a predominance of tick related diseases over tsetse related diseases. Incidences of both problems were highest in Kilindi district but lowest in Lushoto district (Map 3.57). Table 3.16 Number of Other Livestock byType of Livestock and District Type of Livestock District Ducks Turkeys Rabbits Donkeys Other Lushoto 7,722 0 12,558 8,764 0 Korogwe 28,561 0 2,024 643 0 Muheza 42,980 322 674 0 0 Tanga 5,556 182 416 25 239 Pangani 1,822 0 0 48 22 Handeni 25,758 0 940 6,082 530 Kilindi 5,088 0 0 1,940 773 Total 117,486 503 16,611 17,502 1,563 8,764 1,022 533 1,172 0 78 20,332 5,381 0 205 0 0 0 0 0 5,000 10,000 15,000 20,000 25,000 Number of Chickens Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Chart 3.135 Number of Improved Chicken by Type and District Layers Broilers - 2,986 6,136 22,327 29,630 7,859 - 10,000 20,000 30,000 Number of layers 1995 1999 2003 Year Chart 3.136 Layers Population Trend Chart 3.137 Percentage of Livestock Keeping Households Reporting Tsetseflies and Tick Problems by District. 0 20 40 60 80 100 Kilindi Handeni Tanga Korogwe Muheza Pangani Lushoto District Percent Ticks Tsetseflies Pangani 0 0 0 0 395 49 0 0% 0% 0% 0% 0% 0.2% 0.9% Kilindi Handeni Tanga Korogwe Muheza Lushoto Tanga 4,554 8,775 6,130 339 8,442 3,653 814 43% 24% 43% 38% 60% 82% 45% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.57 TANGA Number and Percent of Households Infected with Ticks by District Number of Households Infected with Ticks Number of Households Infected with Ticks Percent of Households Infected with Ticks MAP 3.58 TANGA Number and Percent of Households Using Draft Animals by District Number of Households Using Draft Animals Number of Households Using Draft Animals Percent of Households Using Draft Animals 7,100 to 8,800 5,400 to 7,100 3,700 to 5,400 2,000 to 3,700 300 to 2,000 320 to 400 240 to 320 160 to 240 80 to 160 0 to 80 Tanzania Agriculture Sample Census RESULTS 85 RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 86 The most practiced method of tick controlling was spraying with 64 percent of all livestock-rearing households in the region using the method. Other methods used were dipping (9%), smearing (1%) and other traditional methods like hand picking (10%). However, 15 percent of livestock-keeping households did not use any method. The most common method used to control tsetse flies was spraying which was practiced by 50 percent of livestock-rearing households This was followed by dipping (13%) and trapping (1%). However, 36 percent of the livestock rearing households did not use any of the three aforementioned methods. 3.12.7.1 Deworming Livestock rearing households that dewormed their animals were 48,587 (57% of the total livestock rearing households in the region). The percentage of the households that dewormed cattle was 38 percent, goats (32%), sheep (17%) and pigs (4%) (Chart 3.138). 3.12.8. Access to Livestock Services 3.12.8.1 Access to Livestock Extension Services The toal number of households that received livestock advice was 53,666, representing 62 percent of the total livestock- rearing households and 20.2 percent of the agricultural households in the region. The main livestock extension agent was the government which provided service to about 98.6 percent of all households receiving livestock extension services. The rest of the households got services from NGOs/development projects (1.1%) and large-scale farmers (0.3%). About 63 percent of livestock rearing households described the general quality of livestock extension services as being good, 19 percent said they were average and 15 percent said they were very good. However, 2 percent of the livestock rearing households said the quality was not good whilst 1 percent described them as poor (Chart 3.139). 3.12.8.2 Access to Veterinary Clinic Many veterinary clinics were located very far from livestock rearing households. About 70 percent of the livestock rearing households accessed the services, at a distance of more than 14 kms. Only 30 percent of them accessed the services within 14 kms from their dwellings (Chart 3.140). The most affected district was Pangani district with almost all livestock rearing households accessing the services at a distance of more than 14 kms. Tanga District was the least affected because about 53 percent of the households could access the service within a distance of 14 kilometres. (Chart 3.141). 0 20 40 60 Percent Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi District Chart 3.138 Percent of Livestock Rearing Households that Dewormed Livestock by Livestock Type and District Cattle Goats Sheep Pigs Chart 3.139 Percentage Distribution of Livestock Rearing Households by Quality of Livestock Extension Services No good, 2% Very Good 15% Good, 63% Average, 19% Poor, 1% RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 87 3.12.8.3 Access to Village Watering Points/dam The number of livestock rearing households residing less than 5 kms from the nearest watering point was 26,350 (92% of livestock rearing households in Tanga region) whilst 1,587 households (6%) resided between 5 and 14 kms. However, 597 households (2%) had to travel a distance of 15 or more kms to f the nearest watering point (Chart 3.142). Korogwe district had the best livestock water supply with the majority of livestock rearing households residing within 5 kms from the nearest watering point. This is followed by Tanga, Handeni and Lushoto districts. In Kilindi district about 37 percent of the livestock rearing households had to travel a distance of more than five kilometers to the nearest watering point (Chart 3.143). 3.12.9. Animal Contribution to Crop Production 3.12.9.1 Use of Draft Power Use of draft animals to cultivate land in Tanga region is very limited with only 443 households (0.17% of the total households in the region) using them (Chart 3.144). Chart 3.142 Number of Households by Distance to Village Watering Points Less than 5 kms, 26,350, 92% 5-14 kms, 1,587, 6% 15 or more kms, 597, 2% Chart 3.143 Number of Households by Distance to Village Watering Point and District 0 2,500 5,000 7,500 10,000 Korogwe Handeni Lushoto Muheza Kilindi Pangani Tanga District Number of Households Less than 5 kms 5-14 kms 15 or more kms Chart 3.140 Number of Households by Distance to Verinary Clinic Less than 14km, 37,901, 30% More than 14km, 87,316, 70% Chart 3.141 Number of Households by Distance to Verterinary Clinic and District 0 10,000 20,000 30,000 Lushoto Handeni Korogwe Muheza Kilindi Tanga Pangani District Number of Households Less than 14 kms More than 14kms 3.144 Number of Households Using Draft Amimals Using draft animal, 443, 0.2% Not using draft animal, 264,755, 100% 0 100 200 300 400 Number of Households Korogwe Kilindi Lushoto Muheza Tanga Pangani Handeni District Chart 3.145 Number of Households Using Draft Animals by District - TANGA RESULTS – Livestock Production __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 88 The number of households that used draft animals in Korogwe was 395 representing 89 percent of the households using draft animals in the region were from Korogwe whilst in Kilindi only 49 households (11%) used draft animals. Use of draft animals was not reported in the other districts (Chart 3.145 and Map 3.58). The region had 1,132 oxen (987 oxen in Korogwe and 146 in Kilindi) that were used to cultivate 2,653.3 hectares of land. This represents only 0.03 perce nt of the total oxen found on the Mainland. The largest area cultivated using oxen was found in Korogwe district (1,973.4 ha, 74.4% of the total area cultivated using oxen). 3.12.9.2 Use of Farm Yard Manure The number of Households using organic fertilizer in Tanga region was 51,503 (20% of total crop growing households in the region) (Chart 3.146). The total area applied with organic fertiliser was 27,331 ha of which 21,954 hectares (80% of the total area applied with organic fertiliser or 9.4% of the area planted with annual crops and vegetables in Tanga region during the long rainy season) was applied with farm yard manure (Map 3.59). 3.12.9.3 Use of Compost Only 5,377 ha (20% of the area of organic fertilizer application) was applied with compost. The largest area applied with farm yard manure was found in Lushoto district with 13,238 hectares (60% of the total area applied with farm yard manure) followed by Korogwe (4,160 ha, 19%), Muheza (2,467 ha, 11%), Handeni (896 ha, 4%), Tanga (657 ha, 3%), Kilindi (389 ha, 2%) and Pangani (147 ha, 1%) (Chart 3.147 and Map 3.60). 3.12.10 Fish Farming The number of households involved in fish farming in Tanga region was 1,423, representing 0.5 percent of the total agricultural households in the region (Chart 3.148 and Map 3.61). Korogwe was the leading district with 634 households (1.4% of agricultural households) involved in fish farming. This was followed by Lushoto (430 households, 0.5%), Muheza (336 households, 0.7%) and Tanga (23 households, 0.3%). Fish farming was not practiced in Pangani and Handeni districts (Chart 3.149). Chart 3.148 Number of Households Practicing Fish Farming - TANGA Households Prcticing Fish Farming, 1,423, 1% Households Not Prcticing Fish Farming, 263,775, 99% Chart 3.147 Area of Application of Organic Fertiliser by District TANG A 0 5,000 10,000 15,000 Lushoto Korogwe Muheza Handeni Tanga Kilindi Pangani District Area of Fertiliser Application (ha) Farm Yard Manure Compost Chart 3.146 Number of Households Using Organic Fertiliser Not Using O rganic Fertilizer, 212,025, 80% Using Organic Fertilizer, 51,503, 20% Tanga Pangani 1,668ha 772ha 17ha 1,440ha 105ha 340ha 1,035ha 0% 0.01% 0.01% 0.02%% 0% 0.01% 0% Kilindi Handeni Korogwe Muheza Lushoto Tanga 4,160ha 147ha 389ha 896ha 657ha 2,467ha 13,238ha 6.4% 10% 1% 0.8% 5.9% 1% 2.5% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.59 TANGA Planted Area and Percent of Total Planted Area with Farm Yard Manure application by District Planted Area with Farm Yard Manure Application Planted Area with Farm Yard Manure Application Percent of Total Planted Area with Farm Yard Manure Application MAP 3.60 TANGA Planted Area and Percent of Total Planted Area with Compost Manure Application by District Planted Area with Compost Manure Application Planted Area with Compost Manure Application Percent of Total Planted Area with Compost Manure Application 10,500 to 13,300 7,900 to 10,500 5,300 to 7,900 2,700 to 5,300 100 to 2,700 1,200 to 1,700 900 to 1,200 600 to 900 300 to 600 0 to 300 Tanzania Agriculture Sample Census RESULTS 89 Tanga 1,661 7,747 723 1,883 1,679 12,191 3,310 18.6% 23.6% 15.7% 4.1% 25.5% 17% 0.8% Kilindi Handeni Pangani Korogwe Muheza Lushoto Tanga 105 1,035 1,440 340 17 772 1,668 1.4% 0.7% 0.3% 0.5% 0% 0% 0% Kilindi Handeni Pangani Korogwe Muheza Lushoto MAP 3.61 TANGA Number and Percent of Households Practicing Fish Farming by District Number of Households Practicing Fish Farming Number of Households Practicing Fish Farming Percent of Households Practicing Fish Farming MAP 3.62 TANGA Number and Percent of Households Without Toilets by District Number of Households Without Toilets Number of Households Without Toilets Percent of Households Without Toilets 520 to 640 390 to 520 260 to 390 130 to 260 0 to 130 9,900 to 12,200 7,600 to 9,900 5,300 to 7,600 3,000 to 5,300 700 to 3,000 Tanzania Agriculture Sample Census RESULTS 90 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 91 The main source of fingerings was the non governmental organizations and/or projects which provided fingering to 55 percent of the fish farming households. About 28 percent of households practicing fish farming got fingerings from their neighbours and 11 percent got them from government institutions. All fish farming households in the region used the dug-out- pond system and the main fish specie planted is Tilapia. The number of fish harvested in Tanga region was 249,570, of which 248,888 fish (99.7%) were tilapia and 682 (0.3%) were carp (Chart 3.150). About 75 percent of the fish farming households sold their fish while 25 percent did not sell. All fish were sold to their neighbours. ] 3.13. POVERTY INDICATORS The agricultural census collected data on poverty for the purpose of providing a base for tracking progress in poverty reduction strategies undertaken by the government. 3.13.1 Access to Infrastructure and Other Services The results indicate that among the evaluated services, regional capital was a service located very far from most of the household’s dwellings than any other service. It was located at an average distance of 131 kilometers from the agricultural household’s dwellings. Other services and their respective average distances in kilometers from the dwellings were all weather road (38), tarmac road (38), hospital (36), tertiary market (32), secondary market (28), secondary school (17), primary market (9), health clinic (6), primary school (2) and feeder road (1) (Table 3.15). Only 3 percent of the agricultural households reported the available infrastructures and services as ‘very good’ whereas 29 percent reported them to be average. Twenty four percent of the agricultural households said the infrastructure and services were poor were , and 20 percent said they were ‘no good’. Table 3.17: Mean Distances from Household Dwellings to Infrastructures and Services by District Mean Distance to District Secondary Schools Primary Schools All weather roads Feeder Roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac Roads Lushoto 10.9 2.0 38.1 2.3 34 6.0 167.4 5.7 20.8 27.8 38.1 Korogwe 12.6 1.8 23.1 0.8 35 7.0 115.9 9.6 20.6 24.3 23.1 Muheza 13.1 2.2 24.5 1.1 28 5.6 49.7 12.3 23.8 29.2 24.5 Tanga 15.1 2.9 12.3 1.2 17 7.6 16.6 26.2 62.8 18.8 12.3 Pangani 21.4 2.3 48.7 0.7 24 4.7 67.7 10.6 56.1 27.3 48.7 Handeni 26.9 2.2 30.7 0.8 39 7.6 134.9 8.4 43.8 40.4 30.7 Kilindi 32.2 3.0 131.1 2.0 75 6.2 276.1 8.1 27.0 61.3 131.1 Total 16.5 2.2 38.0 1.5 36 6.4 131.1 9.1 28.3 31.9 38.0 0 100 200 300 400 500 600 700 Number of Households KorogweLushoto Muheza Tanga Pangani Handeni Kilindi District Chart 3.149 Number of Households Practicing Fish Farming by District - Tanga Chart 3.150 Fish Production Number of Tilapia, 248,888, 99.7% Number of Carp, 682, 0.3% RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 92 3.13.2 Type of Toilets A large number of rural agricultural households use traditional pit latrines (229,330 households, 86.5% of all rural agricultural households) 4,663 households (1.8%) use improved pit latrine and 1,733 households (0.7%) use flush toilets. The remaining 279 household (0.1%) use other toilets facilities. However, 29,194 households (11%) in the region had no toilet facilities (Chart 3.151). The distribution of the households without toilets within the region indicates that 41.8 percent of them were found in Handeni District and 2.5 percent were from Lushoto. The percentages of households without toilets in other districts were as follows Muheza (26.5%), Kilindi (11.3%), Korogwe (6.4%), Pangani (5.8) and Tanga (2.5%) Map 3.62). 3.13.3 Household’s Assets Radios are owned by most rural agricultural households in Tanga region with 162,610 households (61.3% of the agriculture households in the region) owning the asset. followed by bicycle ( 85,039 households, 32.1%), iron (50,029 households, 18.9%), wheelbarrow (8,928 households, 3.4%), mobile phone (5,112 households, 1.9%), television/video (2,714 households, 1.0%), vehicle (2,319 households, 0.9%) and landline phone (1,337 households, 0.5%) (Chart 3.152). 3.13.4 Sources of Lighting Energy Wick lamp is the most common source of lighting energy in the region. with 77.3 percent of the total rural households using this source of energy followed by hurricane lamp (16.6%), pressure lamp (4.2%), mains electricity (1.3%), firewood (0.3%), solar (0.1%), candle (0.1%) and gas or biogas (0.1%) (Chart 3.153). 3.13.5 Sources of Energy for Cooking The most prevalent source of energy for cooking was firewood, which was used by 96.4 percent of all rural agricultural households in Tanga region. This is followed by charcoal (2.72%). The rest of energy sources accounted for 0.88 percent. These were bottled gas (0.28%), crop residues (0.28%), mains electricity (0.14%), solar (0.10%), livestock dung (0.04%), parrafin/kerosene (0.03%) and gas/biogas (0.01%) (Chart 3.154) Chart 3.151 Agricultural Households by Type of Toilet Facility Traditional Pit Latrine, 229,330, 86.5% Flush Toilet, 1,733, 0.7% No Toilet , 29,194, 11.0% Other Type, 279, 0.1% Improved Pit Latrine , 4,663, 1.8% Chart 3.152 Percentage Distribution of Households Owning the Assets 3.4 1.9 1.0 0.9 0.5 61.3 32.1 18.9 0.0 20.0 40.0 60.0 Radio Bicycle Iron Wheelbarrow Mobile phone Television / Video Vehicle Landline phone Assets Percent Chart 3.153 Percentage Distribution of Households by Main Source of Energy for Lighting Firewood, 915, 0.35% Solar, 383, 0.14% Candles, 321, 0.12% Hurricane Lamp, 44,098, 16.63% Pressure Lamp, 11,043, 4.16% Mains Electricity, 3,315, 1.25% Gas (Biogas), 137, 0.05% Wick Lamp, 204,986, 77.30% Chart 3.154 Percentage Distribution of Households by Main Source of Energy for Cooking Bottled Gas, 736, 0.28% Crop Residues, 735, 0.28% Mains Electricity, 378, 0.14% Solar, 278, 0.10% Livestock Dung, 106, 0.04% Charcoal, 7,210, 2.72% Firewood, 255,643, 96.4% Parraffin / Kerocine, 90, 0.03% Gas (Biogas), 21, 0.01% Tanga Pangani 5,845 5,638 41,120 40,232 37,482 48,899 12,543 65.6% 79.1% 83.6% 84.3% 64% 81.5% 56.5% Kilindi Handeni Korogwe Muheza Lushoto Pangani Tanga 5,973 7,300 20,191 19,973 33,362 31,471 12,227 43.4% 83.8% 81.9% 67.8% 23.3% 65.9% 62% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.63 TANGA Number and Percent of Households Using Grass /Leaves for Roofing Material by District Number of Households Using Grass/Leaves for Roofing Material Number of Households Using Grass/ Leaves for Roofing Material Percent of Households Using Grass/ Leaves for Roofing Material MAP 3.64 TANGA Number and Percent of Households Eating 3 Meals per Day by District Number of Households Eating 3 Meals per Day Number of Households Eating 3 Meals per Day Percent of Households Eating 3 Meals per Day 27,900 to 33,400 22,400 to 27,900 16,900 to 22,400 11,400 to 16,900 5,900 to 11,400 40,400 to 48,900 31,700 to 40,400 23,000 to 31,700 14,300 to 23,000 5,600 to 14,300 Tanzania Agriculture Sample Census RESULTS 93 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 94 3.13.6 Roofing Materials The most common material used for roofing of the main dwelling was grass and/or leaves and it was used by 49.2 percent of the rural agricultural households. This was closely followed by iron sheets (43.6%), grass/mud (4.8%), asbestos (1.1%), tiles (1.0%), concrete (0.1%) and others (0.2%) (Chart 3.155). Pangani district had the highest percentage of households with grass/leaves roofing (84%) followed by Tanga district (82%), Muheza (68%), Handeni (66%), Kilindi (62%), Korogwe (43%) and Lushoto (23%) (Chart 3.156 and Map 3.63). 3.13.7 Access to Drinking Water The main source of drinking water for rural agricultural households in Tanga region was unprotected spring (26 percent of households use unprotected wells during the wet season and 24 percent of the households during the dry seasons. This is followed by piped water (22% of households for each season), unprotected wells (20% of households during the wet season and 21% in the dry season), surface water (17% of households in the wet season and 18% during dry season) and protected wells with 9 percent of households using the source for both seasons. Covered spring was used as a main source by 3 percent of the households in the wet season and by 4 percent in the dry season Chart 3.157) About 55 percent of the rural agricultural households in Tanga region obtained drinking water within a distance of less than one kilometer during wet season compared to 46 percent of the households during the dry season. However, 45 percent of the agricultural households obtained drinking water from a distance of one or more kilometers during wet compared to 54 percent of households in the dry season. The most common distance from the source of drinking water was between 1 and 2 km (Chart 3.158). Chart 3.155 Pe rce ntage Distribution of H ous e holds by Type of Roofing M ate rial Asbestos 1.1% Grass & Mud 4.8% Iron Sheets 43.6% Grass / Leaves 49.2% Tiles 1.0% Other 0.2% Concrete 0.1% Chart 3.156 Percentage Distribution of Households w ith G rassy/Leafy Roofs by District 23 43 62 66 68 82 84 0 25 50 75 100 Pangani Tanga Muheza Handeni Kilindi Korogwe Lushoto District Percent Chart 3.157 Percent of Households by M ain Source of Drinking Water and Season 0.0 10.0 20.0 30.0 Unprotected Spring Piped Water Uprotected Well Lake /River Protected Well Protected Spring Other M ain source Percent of Households Wet Season Dry Season Chart 3.158 Percentof Households by Distance to M ain Source of Water and Season 0 10 20 30 < 100m 100 - 299m 300 - 499m 500 - 999m 1 - 1.99Km 2 - 2.99Km 3 - 4.99Km 5 - 9.99Km 10Km and above Distance Percent wet season Dry season RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 95 3.13.8 Food Consumption Pattern 3.13.8.1 Number of Meals per Day The majority of households in Tanga region normally have 3 meals per day (72.3 percent of the households in the region). This is followed by 2 meals per day (25.2 percent) and 1 meal per day (2.4 percent). Only 0.1 percent of the households have 4 meals per day (Chart 3.159). Lushoto district had the largest percent of households eating one meal per day whilst Handeni had the highest percent of households eating 3 meals per day. (Table 3.16 and Map 3.64). 3.13.8.2 Meat Consumption Frequency The number of agricultural households that consumed meat during the week preceding the census was 177, 887 (67% of the agricultural households in Tanga region) with 86,741 households (48.8 % of those who consumed meat) consuming meat only once during the respective week. This was followed by those who had meat twice during the week (33.4%). Very few households had meat three or more times during the respective week. About 32.9 percent of the agricultural households in Tanga region did not eat meat during the week preceding the census (Chart 3.160 and Map 3.65). 3.13.8.3 Fish Consumption Frequencies The number of agricultural households that consumed fish during the week preceding the census was 225, 800 (85% of the total agricultural households in Tanga region) with 52,958 households (23.5 % of those who consumed fish) consuming fish twice during the respective week. This was followed by those who had fish three times (21.1%). In general, the percentage of households that consumed fish twice or more during the week in Tanga region was 191,435 (84.8% of the agricultural households that ate fish in the region during the respective period). About 14.9 percent of the agricultural households in Tanga region did not eat fish during the week preceding the census (Chart 3.160 and Map 3.66) Chart 3.18: Number of Households by Number of Meals the Household Normally Takes per Day and District Number of meals per day District One % Two % Three % Four % Total Lushoto 4,337 5.0 33,209 38.4 48,899 56.5 135 0.2 86,580 Korogwe 615 1.3 7,894 17.2 37,482 81.5 0 0.0 45,990 Muheza 525 1.1 7,550 15.3 41,120 83.6 0 0.0 49,195 Tanga 133 1.5 2,926 32.8 5,845 65.6 10 0.1 8,914 Pangani 68 1.0 1,408 19.8 5,638 79.1 14 0.2 7,128 Handeni 523 1.1 6,878 14.4 40,232 84.3 106 0.2 47,739 Kilindi 146 0.7 6,964 35.4 12,543 63.8 0 0.0 19,654 Total 6,346 2.4 66,829 25.2 191,758 72.3 265 0.1 265,198 Chart 3.159 Number of Agriculural Households by Number of Meals per Day . Three Meals, 191,758, 72.3% Two Meals, 66,829, 25.2% Four Meals, 265, 0.1% Chart 3.160 Number of Households by Frequency of M eat and Fish Cosumption 0 25,000 50,000 75,000 100,000 O nce Twice Three Times Four times Five Times Six Times Seven Times Frequency Number of Households Meat Fish Pangani Tanga 660 622 4,623 3,741 5,023 4,089 15,606 9% 7% 10% 11% 19% 8% 18% Kilindi Handeni Korogwe Muheza Lushoto 33,590 1,613 17,868 10,811 1,841 14,692 6,327 38.8% 18.1% 36.3% 23.5% 25.8% 30.8% 32% Kilindi Handeni Pangani Tanga Korogwe Muheza Lushoto MAP 3.65 TANGA Number and Percent of Households Eating Meat Once per Week by District Number of Households Eating Meat Once per Week Number of Households Eating Meat Once per Week Percent of Households Eating Meat Once per Week MAP 3.66 TANGA Number and Percent of Households Eating Fish Once per Week by District Number of Households Eating Fish Once per Week Number of Households Eating Fish Once per Week Percent of Households Eating Fish Once per Week 27,200 to 33,600 20,800 to 27,200 14,400 to 20,800 8,000 to 14,400 1,600 to 8,000 12,600 to 15,700 9,600 to 12,600 6,600 to 9,600 3,600 to 6,600 600 to 3,600 Tanzania Agriculture Sample Census RESULTS 96 RESULTS – Poverty Indicators __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 97 3.13.9 Food Security In Tanga region, 111,515 households (42% of the total agricultural households in the region) said they rarely experienced problems in satisfying the household food requirement. However 20,029 (7.6%) said they sometimes experience problems, 8.3 often experienced problems and 7.1 percent always had problems in satisfying the household food requirement. About 35 percent of the agricultural households said they did not experience any food sufficiency problems (Map 3.67). 3.13.10 Main Sources of Cash Income The main cash income of the households in Tanga region was from selling food crops (25.5 percent of smallholder households), followed by casual labour (20.9%), selling of cash crops (16.8%), businesses (14.3%) and cash remittances (7.4%). Only 4% of smallholder households reported the sale of livestock as their main source of income, followed by forest products (2.5%), livestock products (1.7%) and fishing (0.9%) (Chart 3.161). Chart 3.161: Percentage Distribution of the Number of Households by M ain Source of Income not applicable, 0.0, 0% Food Crops, 25.5, 26% Cash Crops, 16.8, 17% Other Casual Cash Earnings, 20.9, 21% Business Income, 14.3, 14% Remittance, 7.4, 7% Wages & Salaries, 5.0, 5% Livestock Products, 1.7, 2% Forest Products, 2.5, 3% Fishing, 0.9, 1% Other, 0.0, 0% Livestock, 4.0, 4% Tanga Pangani 1,960 1,556 10,168 12,979 9,825 19,078 5,410 22% 21.8% 22.1% 22% 20% 27.2% 28% Kilindi Handeni Korogwe Muheza Lushoto MAP 3.67 TANGA Number and Percent of Households Reporting Food Insufficiency by District Number of Households Reporting Food Insufficiency Number of Households Reporting Food Insufficiency Percent of Households Reporting Food Insufficiency 15,500 to 19,100 12,000 to 15,500 8,500 to 12,000 5,000 to 8,500 1,500 to 5,000 Tanzania Agriculture Sample Census RESULTS 98 DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 99 4 TANGA PROFILES This section presents the status of crops and livestock production, access to natural resources and services, demography and poverty for both the region as a whole and for each district. 4.1 Tanga Region Profile The region profile describes the status of the Agriculture sector in the region and compares it with other regions in the country. Tanga region has a land area of around 470,000 hectares under crop production and it has a relatively large number of crop growing households compared to other regions. It has the fifth largest number of crop growing households per square kilometer. The available land area per household is low (1.8 ha/household) with a utilized land area of 1.5 ha per crop growing households. Whilst most of the region is under annual crop production, it has significant areas of permanent crops mainly planted as a mixture with annual crops. It has the sixth largest planted area of cereals with maize having the third largest planted area in the country. The region has the third largest planted area of beans in the country and vegetable production is important with the exception of onions. Paddy and cassava production are low and sorghum is almost absent in the region. Important permanent crops are oranges having the largest planted area in the country and coconuts and sugar cane having the second largest planted area. Small quantities of bananas, cashew nut, mangoes, coffee and pigeon peas are produced. Compared to other regions, Tanga has a moderate planted area with irrigation and the number of households practicing irrigation has remained more or less unchanged over the a period of 10 years prior to the census. The source of irrigation water is equally split between rivers and canals. Gravity is the most common method of obtaining irrigation water closely followed by buckets/watering cans. Irrigation application is equally split between buckets/watering cans and flood. The method of cultivation in Tanga is almost entirely by hand. A very small quantity of fertilizer is used and is mostly farm yard manure and compost to a lesser extent. Virtually no pesticides are used. Compared to other regions, smallholder households in Tanga store moderate quantities of maize. Most of the storage is mostly in locally made traditional cribs, with small amounts stored in sacks or open drums. A relatively high number of households sell crops compared to other regions. The large majority of households process their crops by neighbours machines and very few households sell their processed produce. Compared to other regions, the number of smallholders in Tanga receiving extension services is moderate to high. Tanga has a small number of planted trees by smallholders and the species is mainly gravellis. Compared to other regions, the percent of households with erosion control/water harvesting facilities is moderate to high with terraces being one of the most prominent. Tanga has a low livestock population compared to other regions. It has a similar number of cattle and goats as Kilimanjaro; however it has a moderate to low density. Most of the cattle kept are indigenous, however there are more dairy cattle kept than in most other regions. Milk production is moderate and the farm gate price of milk is average. Goat numbers are moderate to low and there is a small population of sheep and pigs. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 100 Tanga has a moderate to high population of chickens, almost entirely made up of indigenous types. Egg production is moderate to low compared to other regions. The use of organic fertilizer is comparatively low and draft animals are not used for cultivation. The disease infection rate is moderate to high for most diseases. Access to livestock infrastructure and services is between average and poor. In relation to livestock population Tanga receives disproportionately more extension advice compared to other regions with much higher livestock populations. Tanga has moderate number of fish farmers. 4.2 District Profile The following district profiles highlights the characteristics of each district and compares them in relation to Population, Main crops and livestock, production and productivity, access to services and resources and levels of poverty. 4.2.1 Lushoto Lushoto district has the largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Lushoto district is Annual Crop Farming, followed by Off farm Income and Permanent crop farming. However, the district has the highest percent of households with no off-farm activities and the lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Lushoto has a relatively high percent of female headed households (26%) and it has one of the lowest average age of the household head. With an average household size of 4.7 members per household it is average for the region. Lushoto has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region.. The literacy rate for the heads of household is also slightly higher than most of districts in the region. It has the smallest utilized land area per household (1.1ha) and the allocated area is fully utilised indicating a high level of land pressure. The total planted area is greater than in other districts in the region due to the presence of good wet and dry seasons, however it has the second lowest planted area per household (1.5ha) attributed to the high number of smallholders in the district. The district is moderately important for maize production in the region with a planted area of over 51,000ha, however the planted area per household is the lowest in the region. Paddy production is not important with a planted area of only 900 hectares and the production of sorghum is very small. Lushoto is the only district in the region that produces wheat (200ha). Cassava production is moderate accounting for 21 percent of the quantity harvested in the region. The district has a large planted area of Irish potatoes (15,000 ha) and it is the only district in the region that grows this crop. The production of beans in Lushoto is much higher than in other districts in the region with a planted area of 25,000ha. Oilseed crops are not important in Lushoto and no groundnuts were grown in the district. Vegetable production is important in the district. It has the largest planted area with tomatoes, cabbage and chilies (1,600 ha, 750 ha and 450 ha respectively) than other districts in DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 101 the region and accounts for 65 percent of the tomato production, 89 percent of the cabbage production and 60 percent of the chilly production in the region. Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. Compared to other districts in the region, Lushoto has a moderate planted area with permanent crops.which is dominated by coffee (2,000 ha), tea (1,000 ha) and bananas (1,000 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing and preparation is done by hand, however very slightly more land preparation is done by oxen compared to most other districts. The use of inputs in the region is very small, however district differences exist. Lushoto has the largest planted area with improved seed in Tanga region and this is due to the higher planted area of vegetables. The district has the largest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), however most of this is farm yard manure. Compared to other districts in the region, Lushoto district has a moderate level of insecticide use. The use of fungicides, although small, was moderate to high compared to other districts. Virtually no herbicide was used. It has the largest area with irrigation compared to other districts with 13,500 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity. Flood and bucket are the most common means of irrigation water application and a very small amount of sprinkler irrigation is used. The most common method of crop storage is in locally made traditional cribs, however the proportion of households not storing crops in the district is lower than other districts in the region. The district has the largest number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The highest percent of households processing crops in Tanga region is found in Lushoto district and is almost all done by hand. The district also has a higher percent of households selling processed crops to local markets/trade stores than other districts and no sales are to traders on farm. Although very small, access to credit in the district is to women only and the main sources are religious organisations/NGO projects and family friends and relatives. A comparatively larger number of households receive extension services in Lushoto and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Lushoto (with 600,000 planted trees) and is mostly Gravellis with some Cyprus and eucalyptus. The highest proportion of households with erosion control and water harvesting structures is found in Lushoto district and is mostly terraces, however it also has the highest number of vetiver grass strips, water harvesting bunds and tree belts than other districts. The district has the second largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts, however it has the largest population of sheep in the region. It has the smallest number of pigs in the region and a moderate number of chickens. Although small, the district has the second highest number of layers in the region. Small numbers of ducks, rabbits and donkeys are also found in the district. The smallest number of households reporting Tsetse and tick problems was in Lushoto district and it had the largest number of households de- worming livestock. The use of draft animals in the district is very small, A small number of households practice fish farming, however the district has the second largest number in the region. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 102 It has amongst the best access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to all weather roads and regional capital. Lushoto district has the second highest percent of households with no toilet facilities and it has the lowest percent of households owning bicycles, vehicles and tv/video and mobile phones. It has the second lowest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the smallest percent of households with grass roofs with 70 percent of households having iron sheets. The most common source of drinking water is from unprotected springs. It has the highest percent of households having two or one meal per day compared to other districts and the lowest percent with 3 meals per day. The district had the highest percent of households that did not eat meat or fish during the week prior to enumeration, however most households seldom had problems with food satisfaction. 4.2.2 Korogwe Korogwe district has the fourth largest number of households in the region and it has a high percentage of households involved in smallholder agriculture. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Korogwe district is Annual Crop Farming, followed by Off farm Income. The district has the fourth highest percent of households with no off-farm activities although it has the third highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Korogwe has a relatively high percent of female headed households (25%) and it has one of the highest average age of the household head in the region. With a household size of 5 members per household it is average for the region. Korogwe has a comparatively high literacy rate among smallholder households and this is reflected by the district having the highest level of school attendance in the region. It has a moderate utilized land area per household (1.6ha) and 89 percent of the allocated area is currently being utilised. The district has the fourth largest planted area in the region, and the third largest planted area per household (1.8ha in the long rainy season and 1.1ha in the short rainy season). The district is moderately important for maize production in the region with a planted area of over 46,369 ha, and the planted area per maize growing household is also moderate for the region. The district has the largest planted area of paddy in the region with 2,659 hectares. Sorghum is not grown in the district. Cassava production is moderate to low, accounting for 13 percent of the quantity harvested in the region. The district has a very small planted area of Irish potatoes (90 ha). The production of beans in Korogwe, district is moderate to low with a planted area of 5,979ha. Korogwe district has the second largest groundnut planted area in Tanga region with a planted area per groundnut growing household of 0.34 ha. Vegetable production is moderately important in the district. Although small, it has the second largest planted area with tomatoes, cabbage and chilies (456 ha, 35 ha and 237 ha respectively)Traditional cash crops (e.g. tobacco and cotton) are grown in very small quantities. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 103 Compared to other districts in the region, Korogwe has the second largest planted area with permanent crops which is dominated by bananas (2,069 ha), coconuts (1,682 ha), Mango (1,487 ha) and Cardamon (1,232 ha). Cashewnuts, coffee, tea, sugarcane, oranges and jack fruit are also grown in smaller quantities. As with other districts in the region, most land clearing is done by hand slashing, however there is a substantial area with no land clearing indicating bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Korogwe has the second largest planted area with improved seed in the region as well as the highest proportion of households using improved seeds. Though small, the district has the second highest planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with farm yard manure. Compared to other districts in the region, Korogwe district has a moderate level of insecticide use. The use of fungicides and herbicides is low. It has the second largest area with irrigation compared to other districts with 6,600 ha of irrigated land. The most common source of water for irrigation is from rivers using gravity methods. Flood is the most common means of irrigation water application followed by bucket/watering can and a very small amount of sprinkler irrigation is used. The most common method of crop storage in Korogwe district is in locally made traditional cribs, however the proportion of households not storing crops is average for the region. Korogwe has moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Korogwe is among the districts with the lowest percent of households processing crops in Tanga region and is almost all done by neighbours machine. The district also has the second highest percent of households selling processed crops to marketing cooperatives than other districts and no sales are to farmers associations or large scale farms. Access to credit in the district is extremely small. A comparatively larger number of households receive extension services in Korogwe district and all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Korogwe (with 207,720 planted trees) and is mostly Gravellis and Eucalyptus. The second highest proportion of households with erosion control and water harvesting structures is found in Korogwe district and is mostly erosion control bunds and vertiver grass, however it also has the a number of tree belts and drainage ditches. The district has the third largest number of cattle in the region and they are almost all indigenous. Goat production is moderate compared to other districts, however it has the second largest population of sheep in the region. It has the largest number of pigs in the region and a moderate number of chickens. Some ducks, rabbits and donkeys are also found in the district. A number of households reported tsetse and tick problems and it has the second largest number of households de- worming livestock. A small number of households use draft animals, however it is the highest in the region. A small number of households practice fish farming, however the district has the largest number in the region. It has amongst the best access to secondary schools, primary schools, health clinics and primary and secondary markets compared to other districts. However, it has one of the worst access to regional capital. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 104 The percentage of households without toilet facility in Korogwe district is comparatively low. It is amongst the districts with the lowest percent of households owning wheel barrows, vehicles, bicycles, tv/video and mobile phones. It has the third largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The roofing material for most of the households in the district is grass/leaves (43%), however it has a high percent of households with iron sheet roofing (42%) compared to most other districts. The most common source of drinking water is from unprotected springs. It is one of the districts with the highest percent of households having three meals per day. The district had one of the lowest percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.3 Muheza Muheza district has the second largest number of households in the region and it has one of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Muheza district is Annual Crop Farming, followed by Permanent Crop Farming. However, the district has the second highest percent of households with no off-farm activities and the second lowest percent of households with more than one member with off-farm income. Compared to other districts in the region, Muheza has a relatively high percent of female headed households (26%) and it has one of the highest average age of the household head in the region. With an average household size of 4.7 members per household it is slightly below average for the region. Muheza has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. The land area utilized per household (1.8ha) is around average for the region and 89 percent of the allocated area is currently being utilized which is moderate to high for the region. The district has the third largest planted area in the region and the forth largest planted area per household (0.92ha in the long rainy season and 0.84ha in the short rainy season). The planted area in the long rainy season is almost the same as that of the short rainy season. The district is moderately important for maize production in the region with a planted area of over 50,778 ha and the planted area per household is 0.7 ha which average for the region is. Paddy production is not important with a planted area of only 1,644 hectares; however it is the second highest in the region. Sorghum, Irish potatoes and wheat are not produced in the district. The district has the largest planted area of cassava accounting for 38 percent of the cassava planted area in the region. The production of beans in Muheza is much lower than in other districts in the region with a planted area of 875ha. Oilseed crops are important in Muheza with 50 percent of the groundnuts grown in the district. Vegetable production is not important and very small quantities of tobacco are grown in the district. Permanent crops are very important in Muheza district (45% of the total permanent crop planted area in Tanga region) and are more important than any other district in the region. The most prominent permanent crops in the district include coconuts (9,380 ha), cashew nuts (4,600 ha) bananas (2,281 ha) and cardamom (1,466 ha). It is the only district that produces black pepper (1,521 ha) and it has the highest area with oranges in the region (6,433 ha). Other permanent crops are either not grown or are grown in very small quantities. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 105 As with other districts in the region, most land clearing is done by hand slashing, however it has the largest area cleared by burning and a relatively small area of bare ground before planting. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by oxen and tractor. The use of inputs in the region is very small, however district differences exist. Muheza has the smallest planted area with improved seed in Tanga region and this is due to the dominance of permanent crops which do not need frequent planting. The district also has a small planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and practically all is with farm yard manure. Compared to other districts in the region, Muheza district has the smallest area of insecticide and fungicide use and the use of herbicides is relatively small. It has the second largest area with irrigation in the region with 21,896ha of irrigated land. The most common source of water for irrigation is from wells and rivers and almost all water application is by using hand bucket. The most common method of crop storage is in Muheza is locally made traditional cribs, and the proportion of households not storing crops in the district is moderate to low for the region. The district has the highest percent of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Muheza district has a high percent of households processing crops in the region and is almost all done by hand; however, the district has the highest percent of households processing crops by trader. Small quantities of processed crops are sold and very few households have access to credit. A moderate number of households receive extension services in Muheza district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is important in Muheza district (with 403,112 planted trees) and is mostly Tectona Grandis with some Gravellis and Sienna Spp. The second highest proportion of households with water harvesting bunds is found in Muheza district and it also has the third highest number of erosion control bunds. The district has a moderate number of cattle in the region and they are almost all indigenous. Goat and sheep production is moderate compared to other districts. It has the second largest number of pigs in the region and the largest number of chickens, all of which are indigenous. Virtually no improved chicken are found in the district. The district has the largest number of ducks, and a small number of rabbits and turkeys are found in the district. A small number of households reported tsetse and tick problems in Muheza district. A small amount of de-worming of livestock is practiced in the district No draft animals are used. Fish farming is practiced by a small number of households; however the district has the third largest number in the region. It has amongst the best access to secondary schools, primary schools, health clinics, feeder roads and primary markets compared to other districts. However, it has one of the worst accesses to tertiary markets and the regional capital. The percentage of households without toilet facility in Muheza district is average for the region; however it has the second highest percent of households with no toilet facilities. It has the lowest percent of households owning land line phones, vehicles and TV/video. It has the third lowest number of households using mains electricity in the region and the most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has a high percent of households with grass roofs (68%) and only 29 percent of households have iron sheet roofing. The DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 106 most common source of drinking water is from unprotected wells. Sixteen percent of the households in the district reported having one or two meals per day and virtually no household reported having more than three meals per day. The district had a moderate percent of households that did not eat meat or fish during the week prior to enumeration and most households seldom had problems with food satisfaction. 4.2.4 Tanga Tanga district has an average number of households for the region and it has the smallest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Tanga district is off-farm income followed by Permanent crop farming. It has the lowest percent of households with no off-farm activities and the highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Tanga district has a relatively high percent of female headed households (28%) and it has one of the highest average ages of the household head. With an average household size of 4.6 members per household it is average for the region. Tanga district has a comparatively high literacy rate among smallholder households and this is reflected by the concomitant relatively high level of school attendance in the region. It has the second smallest utilized land area per household (1.4 ha) and only 76 percent of the allocated land area is utilised. The total planted area is the smallest in the region however it has the second lowest planted area per household (0.78ha in the long rainy season and 0.664ha in the short rainy season. Tanga district is not important for maize production in the region with a planted area of only 3,946 ha, and the planted area per household is among the lowest in the region. Paddy production is also not important with a planted area of only 545 hectares and the production of sorghum is small. Cassava and bean production in Tanga district was small and Irish potato and wheat is not grown. Oilseed crops and vegetables are not important in the district however, whist the district has one of the smallest planted areas with tomatoes it is the second in terms of tomato planted area per household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Tanga district has the smallest planted area with permanent crops (3.3% of total permanent crop planted area) which is dominated by cashew nuts (959 ha), coconuts (964 ha), A small area of bananas and oranges are grown. Apart from a minor amount of sugarcane no other permanent crop is grown. As with other districts in the region, most land clearing and preparation is done by hand, however the smallest land preparation done by oxen is found in the district. As with other districts in the region, land clearing by hand slashing is predominant and practically all land preparation is by hand. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 107 The use of inputs in the region is very small, however district differences exist. Tanga district has the smallest planted area with improved seed; however it has the highest planted area per household in the region. The district also has the smallest percent of planted area with fertilizers (Farm yard manure, compost and inorganic fertiliser), and most of this is with farm yard manure. Compared to other districts in the region, Tanga district has the lowest area planted with insecticide but has the second highest percent of the total planted area in the region. The percent of planted area with fungicides is amongst the highest in the region and is the highest for herbicides. It has one of the smallest areas of irrigation 2679 ha. The most common source of water for irrigation is from rivers using hand buckets/Bucket. Watering cans are the most common means of irrigation water application. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in Tanga district is the highest in the region. The number of households selling crops in the district is among the smallest in the region, however for those who did not sell, the main reason for not selling is insufficient production. The smallest percent of households processing crops in the region is found in Tanga district and processing is mostly done by neighbor’s machine. The district has the largest number of households processing crops on farm by machine. It also has the second largest number of households processing crops on farm by hand. Most households that sell crops sell to neighbors and no sales are to traders on neither farm nor large scale farms. Access to credit in the district is very small. A very small number of households receive extension services in Tanga district and almost all of this is from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Tanga district (with only 296 planted trees) and all of them are Sienna Spp. The largest proportion of households in Tanga district use terraces for erosion control. Tanga district has the second smallest number of cattle in the region and most of them are indigenous. It is one of the districts with the least number of goats in the region, however the district has the highest density (87 head per km2) Tanga is also one of the districts with the smallest number of sheep, pigs and chicken, however it has the largest number of improved chickens (both layers and broilers) in the region. Small numbers of ducks, rabbits, turkeys and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Tanga district and it had one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and very few households practice fish farming. It is amongst the districts with the best access to secondary schools, primary schools, feeder roads, all weather roads, health clinics, hospitals, regional capital, tarmac roads and tertiary markets compared to other districts. However, it has the worst access to primary and secondary markets. Tanga district has a small number of households with no toilet facilities. The district has the highest percent of households owning wheel barrows, vehicles and television/video, land line and mobile phones and it has the second highest percent of households with radio, bicycles and irons. It has the largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the second largest percent of households with grass roofs with only 16 percent of households having iron sheets. The most common source of drinking water is piped water and it has the second highest percent of households having two or one meal per day compared to other districts and the third lowest percent with 3 meals per day. The district had the highest DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 108 percent of households that did not eat meat during the week prior to enumeration but has the lowest percent of households that did not eat fish. Most households seldom had problems with food satisfaction. 4.2.5 Pangani Pangani district has the smallest number of households in the region and it has the second lowest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock farming. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Pangani district is off farm income followed by Annual Crop Farming, Tree/Forest Resources and Fishing/Hunting and Gathering. The district has the third lowest percent of households with no off-farm activities and the second largest percent of households with more than one member with off- farm income. Compared to other districts in the region, Pangani has a moderate percent of female headed households (24%) and it has one of the highest average ages of the household head. With an average household size of 4.1 members per household it is slightly lower than the regional average. Pangani has the highest literacy rate among smallholder households in the region and this is reflected by the concomitant relatively high level of school attendance. The rate of “Never Attended” is among the lowest in the region. It has one of the smallest utilized land area per household (1.4 ha) which is slightly lower than the regional average of 1.7 ha per household. The district has smallest planted area in the region, however it has the second largest planted area per household (1.6 ha) in the long rainy season. The district is not important for maize production with a planted area of 7,042 ha, however the planted area per household is moderate compared to other districts in the region. Paddy production is also not important with a planted area of only 500 hectares and the production of sorghum is very small. Wheat and finger millet are not grown in the district. The district has among the lowest percent of cassava planted area in the region and it has virtually no Irish or sweet potatoes. The production of beans in Pangani district is the smallest in the region with a planted area of only 4 ha and oil crops are not important in the district. Vegetable production is also not important in the district; however the district has largest planted area per tomato growing household. Traditional cash crops (e.g. tobacco and cotton) are not grown in the district. Compared to other districts in the region, Pangani has a small planted area with permanent crops (4,623 ha) which is dominated by coconuts (2,418 ha) and cashew nuts (1,766 ha). Other permanent crops are either not grown or are grown in very small quantities. As with other districts in the region, most land clearing is done by hand slashing, however “no land clearing” is relatively high indicating bare land before cultivation. Practically all Land preparation is done by hand, however a very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Pangani has one of the smallest planted areas with improved seed in Tanga region however it has one of the highest percent of planted area using improved seed. The district has the smallest planted area with fertilizers and most of this is with farm yard manure with no inorganic fertiliser. Compared to other districts in the region, Pangani district has the second highest percent of its planted area with DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 109 insecticides in the region. The use of fungicides was the was one of the lowest in the region and virtually no herbicide was used. It has the smallest planted area with irrigation in the region with only 2310 ha of irrigated land. Rivers, wells boreholes and canals is used as the source of irrigation water and hand bucket was mainly used. Buckets/Water cans are the most common means of irrigation water application and a very small amount of flood irrigation is used. The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is the second highest in the region. The district has the smallest number of households selling crops and the main reason for not selling is insufficient production. Pangani district has the highest percent of households processing crops on farm by hand and a small percent of households selling processed crops mainly to neighbours and trader at farm. No sales were made to farmers associations, marketing cooperatives or large scale farms. Access to credit is non existent in the district and the main reason for not using credit is lack of awareness. A comparatively small number of households receive extension services in Pangani district and all of this is from the government. The quality of extension services was rated between good and average by most of the households. Tree farming is not important in Pangani (with only 3,229 planted trees) and is mostly with Tectona Grandis with some Azadritachta Spp, Moringa Spp and Gravellis. The smallest number of erosion control and water harvesting structures is found in Pangani district and they are tree belts only. The district has the smallest number of cattle in the region and they are mostly all indigenous. Goat and sheep production is smallest in the region, and no pigs are found in the district. It has a comparatively smallest number of chickens. Small numbers of ducks and donkeys are also found in the district. A moderate number of households reported Tsetse and tick problems in Pangani district and has the smallest number of households de-worming livestock. The use of draft animals in the district is non existent and no fish farming is practiced in the district. It is amongst the districts with the best access to primary schools, feeder roads, health clinics and primary markets; however it has one of the worst accesses to all weather roads, regional capital, secondary markets and tarmac roads. Pangani district has a low percent of households with no toilet facilities. The district has the largest percent of households owning radios and bicycles and no ownership of land line phones was reported. Very small number of households reported ownership of vehicles, mobile phones, wheel barrows and televisions/videos. It has the second largest number of households using mains electricity in the region. The most common source of energy for lighting is the wick lamp and practically all households use firewood for cooking. The district has the largest percent of households with grass roofs and only 13 percent of households having iron sheets. The most common source of drinking water is from piped water, unprotected wells and surface water... It has a moderate percent of households having two or one meal per day compared to other districts and is among the districts with a high percent of households with 3 meals per day. The district had the second highest percent of households that did not eat meat during the week prior to enumeration; however it is among the districts with low percent of households that did not eat fish during the week. Most households in the district seldom had problems with food satisfaction. 4.2.6 Handeni DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 110 Handeni district has a moderate number of households in the region and it has one of the highest percents of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and no pastoralists were found in the district. The most important livelihood activity for smallholder households in Handeni district is Annual Crop Farming, followed by off farm Income, Fishing/Hunting and Gathering and Tree/Forest resources. The district has a high percent of households with no off-farm activities however it has the forth highest percent of households with more than one member with off-farm income. Compared to other districts in the region, Handeni has the second lowest percent of female headed households (21%) and it has one of the lowest average ages of the household head. With an average household size of 5.4 members per household it is the largest for the region. The literacy rate among smallholder households in Handeni is low compared to other districts in the region and associated with this is a number of household members who have never attended school. It has the largest utilized land area per household (2.6 ha) in Tanga region. The total planted area is the second largest in the region and has the largest planted area in the long rainy season. However the planted area per household in the long rainy season the district had the fifth largest planted area per household with 0.63 ha per household in the short rainy season and 0.98 ha in the long rainy season. The district is the most important for maize production in the region with a planted area of 95,688 ha and the planted area per household is the second largest in the region. Paddy production is moderate for the region with a planted area of 1,245 hectares and the district has the largest planted area per paddy growing household. Production of sorghum and finger millet is very small. The district also has the largest planted area of cow peas (7,982) and green grams (817 ha), however very little beans and field peas are produced. Cassava production is relatively low accounting for 10.3 percent of the total cassava planted area in the region. Oilseed crops are important in Handeni with the largest planted area of simsim in the region (680 ha) and the third largest planted area of groundnuts. Vegetable production is not important in the district; however tomatoes, cabbage, water melon, bitter aubergine, pumpkins and amaranths are produced in very small quantities. Handeni is the only district that cultivates cotton although the planted area is small. Compared to other districts in the region, Handeni has a moderate planted area with permanent crops which is dominated by oranges (2,201 ha), Mango (1,271 ha), bananas (1,143 ha) and Jack fruit (904 ha). Other permanent crops are either not grown or are grown in small quantities. Most land clearing is done by hand slashing, however it has the highest Planted Area with “no land clearing” indicating the presence of a large area of bare land before cultivation. It has also the largest area of bush clearance in the region. Most land preparation is done by hand, however a it has the highest planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Handeni has a moderate planted area with improved seed in Tanga region. The use of fertilizer is very small and is mostly farm yard manure and compost. No inorganic fertilizer is used. Compared to other districts in the region, Handeni district has a small percentage of the planted area in the district with fungicides application and a small amount of herbicide was used. It has the third largest area with irrigation with a planted area of 5,380 ha under irrigation. The most common source of water for irrigation is from wells using hand buckets. Buckets/Watering cans are the only means of irrigation water application in the district. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 111 The most common method of crop storage is in locally made traditional cribs; however the proportion of households not storing crops in the district is moderate to low when compared to other districts in Tanga region. The district has a moderate number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. Handeni is among the districts in Tanga region with a high percent of households processing crops and is mostly done using neighbors machines. The district also has a small percent of households selling processed crops mostly to neighbours and traders on farm. Access to credit in the district small. A comparatively small number of households receive extension services in Handeni and mostly from the government. The quality of extension services was rated between good and average by the majority of the households. Tree farming is not important in Handeni (with only 2,014 planted trees) and is mostly Senna Spp with some Saraca Spp and Gravellis. A small proportion of households with erosion control and water harvesting structures is found in Handeni district and is mostly drainage ditches, terraces and erosion control bunds, It also has a small number of tree belts for erosion control. The district has the largest number of cattle in the region and they are almost all indigenous. Goat population is also the largest in the region; however it has one of the smallest populations of sheep in the region. The district has a comparatively moderate to low number of pigs in the region but it has the second largest chicken population, all of which are indigenous. A moderate numbers of ducks, donkeys and rabbits are also found in the district. It has the second highest proportion of households reporting Tsetse and tick problems in the region and it had a moderate to low number of households de-worming livestock compared to other districts. Draft animals are not used and fish farming is not practiced. It is amongst the districts with the best access to primary schools, feeder roads, health clinics and primary markets, however it has one of the worst access to regional capital, secondary and tertiary markets, tarmac roads and all weather roads. Handeni district has the highest percent of households with no toilet facilities. Though small, it has the second highest percent of households with wheel barrows and mobile phones, however and it among the districts with a low percent of households owning vehicles and land line phones. It has a small number of households using mains electricity. The most common source of energy for lighting is the wick lamp and almost all households use firewood for cooking. The district has a moderate to high percent of households with grass roofs with and 29 percent of households have iron sheet roofing. The most common sources of drinking water are from unprotected wells and piped water. It has the highest percent of households having three meals per day compared to other districts and moderate percent with one or two meals per day. The district has a moderate to high percent of households that did not eat meat or fish during the week prior to enumeration; however most households seldom had problems with food satisfaction. 4.2.7 Kilindi Kilindi district has the second smallest number of households in the region; it has however it has of the highest percent of households involved in smallholder agriculture in the region. Most smallholders are involved in crop farming only, followed by crop and livestock production. It has a very small number of livestock only households and though small, it is the only district with pastoralists. DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 112 The most important livelihood activity for smallholder households in Kilindi district is Annual Crop Farming, followed by off farm Income/ Fish/hunting and Gathering and tree/Forest Resources. However, the district has a moderate to high percent of households with no off-farm activities and a moderate percent of households with more than one member with off-farm income compared to other districts in the region, Kilindi has the lowest percent of female headed households (18%) in the region and it has the lowest average age of the household head. With an average household size of 5.3 members per household it is the second largest for the region. Kilindi has the lowest literacy rate among smallholder households in and this is reflected by the relatively high level of never attended school in the region... The literacy rates for the heads of household are the lowest in the region. It has the second largest utilized land area per household (2.5 ha) in the region. The total planted area is moderate compared to other districts in the region due to the presence of good wet and dry seasons, however it has the largest planted area per household (1.8 ha during the long rainy season and 1.1 ha in the short rainy season). The district is moderately important for maize production in the region with a planted area of over 32,536 ha and the planted area per maize growing household is the largest in the region. The district has the smallest planted area of paddy (142 ha) and sorghum, finger millet and wheat are not produced in the district. Cassava production is small accounting for only 5 percent of the cassava planted area in the region. The production of beans in Kilindi though comparatively small (8,245 ha) is higher than in most other districts in the region. Other pulses produced in the district are of minor importance. Oilseed crops are not important in Kilindi, however it is the only district in the region which grows castor seeds. Vegetable production is not important in the district; however tomatoes, cabbage, onions and other vegetables are grown in small quantities. Tobacco is the only traditional cash crop grown in the district in small quantities. Compared to other districts in the region, Kilindi has a moderate planted area with permanent crops which is dominated by pigeon peas (2,417 ha) and mangoes (1,320 ha). Small quantities of banana, sugar cane, cardamom and jack fruit are also grown and other permanent crops are either not grown or are grown in very small quantities. Most land clearing is done by hand slashing, however it has a high planted area with “no land clearing” indicating the presence of a large area of bare land before cultivation. Most land preparation is done by hand, however it has a very small planted area cultivated by oxen. A very small amount of land preparation is done by tractor. The use of inputs in the region is very small, however district differences exist. Kilindi has a one of the smallest percentaqge of its planted area with improved seed and fertilizers (compost and Farm yard manure, however most of this is compost). The district has a relatively small level of insecticide and fungicides use, however the use of herbicides, though small, was the second highest in the region. It has the second smallest area of irrigation with only 2,927 ha of irrigated land. The most common source of water for irrigation is from wells using hand buckets. Buckets/Watering cans are the most common means of irrigation water application and a very small amount of food irrigation is used. The most common method of crop storage is in locally made traditional cribs and sacks/open drums. The proportion of households not storing crops in the district is the second lowest in the region. The district has a small number of households selling crops, however for those who did not sell, the main reason for not selling is insufficient production. The second highest percent of households processing crops in Tanga region is found in Kilindi district and is mostly done using DISTRICT PROFILES. __________________________________________________________________________________________ ____________________________________________________________________________________________________________________________ Tanzania Agriculture Sample Census 113 neighbors machines, virtually no processing as done on farm by machine... The district has a small percent of households selling processed crops mostly to neighbours and local markets/trade stores. There is no access to credit in the district. A comparatively small number of households receive extension services in Kilindi district and almost all of this is from the government. The quality of extension services was rated bet ween good and average by the majority of the households. Tree farming is not important in Kilindi (with only 4,326 planted trees) and is mostly Morringa and Gravellis with some Eucalyptus Spp, Terminala Catapa and Syszygium Spp. A relatively small proportion of households with erosion control and water harvesting structures is found in Kilindi district and is mostly tree belts and erosion control bunds; however it also has a number of water harvesting bunds, drainage ditches and vetiver grass. The district has a moderate to low number of cattle in the region and they are all indigenous. Goat production is also moderate to low compared to most other districts, however it has a relatively small population of sheep compared to other districts in the region. It has one of the smallest numbers of pigs in the region and a moderate to low number of chickens, with no improved chicken. Small numbers of ducks and donkeys are also found in the district. The largest number of households reporting tsetse and tick problems was in Kilindi district; however it has one of the smallest numbers of households de-worming livestock. The use of draft animals in the district is very small and no fish farming is practiced in the district. It is amongst the districts with the best access to primary schools, feeder roads, health clinics, and primary markets, however it has one of the worst access to the regional capital, tarmac roads, all weather roads, tertiary markets, secondary markets and secondary schools. Kilindi district has the third highest percent of households with no toilet facilities and it has one of the lowest percent of households owning landline and mobile phones, vehicles and televisions/video. It has no access to mains electricity. The most common source of energy for lighting is the wick lamp and most of the households use firewood for cooking. The district has a moderate percent of households with grass roofs with 26 percent of households having iron sheet roofing. The most common source of drinking water is from unprotected well. It has the second highest percent of households having two or one meal per day compared to other districts and the second lowest percent with 3 meals per day. The district had the lowest percent of households that did not eat meat during the week prior to enumeration; however it has the second highest percent of households that did not eat fish during the respective period. Most households seldom had problems with food satisfaction. APPENDIX II 114 4. APPENDICES Appendix I Tabulation List.................................................................................................. 115 Appendix II Tables ................................................................................................................ 130 Appendix III Questionnaires ................................................................................................. 301 APPENDIX II 115 APPENDIX I: CROP TABULATION TYPE OF AGRICULTURE HOUSEHOLD 2.1 Number of Agricultural Households by type of Household and District during 2002/03 Agriculture Year.......... 131 2.2.1 Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year.................. 131 NUMBER OF AGRICULTURE HOUSEHOLDS.......................................................................................................... 133 3.0 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year ..................................................................................................................................... 134 3.1 The Livelihood Activities/Source of Income of the Households Ranked in Order of Importance by District ........................................................................................................................................... 134 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES..................................................................................... 135 3.1a First Most Importance............................................................................................................................................ 136 3.1b Second Most Importance ....................................................................................................................................... 136 3.1c Third Most Importance .......................................................................................................................................... 136 3.1d Fourth Most Importance ........................................................................................................................................ 136 3.1e Fifth Most Importance ........................................................................................................................................... 136 3.1f Sixth Most Importance........................................................................................................................................... 136 3.1g Seventh Most Importance ...................................................................................................................................... 136 HOUSEHOLDS DEMOGRAPHS.................................................................................................................................... 139 3.2 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (row %) .......................................................................................................................................................... 140 3.3 Number of Agricultural Household Members by Sex and Age Group for the 2002/03 Agricultural Year (col %) .......................................................................................................................................................... 140 3.4 Number of Agricultural Household Members by Sex and District for the 2002/03 Agricultural Year ................. 141 3.5 Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year............................................................................. 141 3.6 Number of Agricultural Household Members 5 years and above By School Attendance and District, 2002/03 Agricultural Year ..................................................................................................................................... 141 3.7 Number of Agricultural Household Members by Main Activity and District ....................................................... 141 Cont… Number of Agricultural Household Members by Main Activity and District.......................................... 142 Cont… Number of Agricultural Household Members by Main Activity and District.......................................... 142 3.8 Number of Agricultural Household Members by Level of involvement in Farming Activity and District, 2002/03 Agricultural Year ..................................................................................................................................... 142 3.9 Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ..................................................................................................................................... 143 APPENDIX II 116 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 Cont … Number of Agricultural Household Members by Level of Formal Education Completion and District, 2002/03 Agricultural Year ....................................................................................................................... 143 3.10 Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year................................................................................................................. 144 3.11 Number of Agricultural Households Involved in Off Farm Income Generating Activity by Number of Off Farm Income Activities and District, 2002/03 Agricultural Year ................................................................... 144 3.12 Number of Heads of Agricultural Households by Maximum Education Level Attained and District, 2002/03 Agricultural Year ................................................................................................................................................... 144 3.13 Mean, Median, Mode of Age of Head of Agricultural Household and District..................................................... 144 3.14 Time Series of Male and Female Headed Households .......................................................................................... 145 3.15 Literacy Rate of Heads of Households by Sex and District................................................................................... 145 LAND ACCESS/OWNERSHIP........................................................................................................................................ 147 4.1 Number of Farming Households by Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year .......................................................................................................................................................... 148 4.2 Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year..................... 148 LAND USE .......................................................................................................................................................... 149 5.1 Number of Agricultural Households by Type of Land Use and District for the 2002/03 Agricultural Year......... 150 5.2 Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year ...................................... 150 5.3 Number of Households by type of household and District during 2002/03 Agricultural Year.............................. 151 5.4 Number of Agricultural Households by whether they consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year.................................................................................... 151 5.5 Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year ......................................................................................... 151 TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION- LONG & SHORT RAINY SEASON ................. 153 7.1&7.2a Number of Crop Growing Households and Area Planted (ha) by Season and District ........................................ 154 7.1&7.2b Number of crop growing Households Planting Crops by Season and Region ..................................................... 154 7.1&7.2c Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 Agriculture Year, Tanga Region .......................................................................................................................................................... 155 7.1&7.2d Number of Agriculture Households by Area Planted (ha) and crop for the Agriculture Year 2002/03- Short and Long Season, Tanga Region.................................................................................................................. 156 7.1&7.2e Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Tanga .................................................................................................................. 157 APPENDIX II 117 7.1&7.2f Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 Agriculture Year - LONG & SHORT RAINY SEASON, Tanga ......................................................................... 157 7.1&7.2g Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 Agriculture Year - LONG & SHORT RAINY SEASON, Tanga Region.............................................................. 157 7.1&7.2h Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 Agriculture year - LONG & SHORT RAINY SEASON....................................................................................... 158 7.1&7.2i Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 Agriculture year - LONG & SHORT RAINY SEASON, Tanga........................................................................... 158 7.1&7.2j Number of Crop Growing Households and Planted Area by Fungicide Use and District during 2002/03 Crop Year LONG & SHORT RAINY SEASON, Tanga Region .......................................................................... 159 7.1&7.2k Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Tanga Region........................................................................ 159 ANNUAL CROP AND VEGETABLE PRODUCTION – SHORT RAINY SEASON ................................................ 161 7.1a Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Tanga Region........................................................................................................................................ 162 7.1b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON, Tanga Region ................................................................................................... 162 7.1c Number of Crop Growing Households and Planted Area by Irrigation Use and District during 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region........................................................................................... 162 7.1d Number of Crop Growing Households and Planted Area by Insecticide Use and District during 2002/03 Crop Year in SHORT RAINY SEASON............................................................................................................... 163 7.1e Number of Crop Growing Households and Planted Area by Herbicide Use and District during 2002/03 Crop Year SHORT RAINY SEASON.................................................................................................................. .163 7.1f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON............................................................................................................................ 164 . 7.1g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region............................................................................. 164 ANNUAL CROP AND VEGETABLE PRODUCTION – LONG RAINY SEASON .................................................. 165 7.2a Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District during 2002/03 Crop Year-LONG RAINY SEASON, Tanga Region...................................................... 166 7.2b Number of Crop Growing Households and Planted Area by Fertilizer Use and District during the Long Rainy Season ................................................................................................................................................ 166 7.2c Number of Crop Growing Households and Planted Area by Irrigation Use and District during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................ 166 7.2d Number of Crop Growing Households & Planted Area by Insecticide Use and District – LONG RAINY SEASON....................................................................................................................................... 167 7.2e Number of Crop Growing Households and Planted Area by Herbicide Use and District during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................. 167 APPENDIX II 118 7.2J Number of Crop Selling Households and Reported Agriculture Products during 2002/03 Crop Year LONG RAINY SEASON, Tanga Region............................................................................................. 167 7.2f Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region ..................................................................................................... 168 7.2g Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG RAINY SEASON, Tanga Region ............................................................................ 168 7.2h Planted Area and Number of Crop Growing Households during the Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agricultural Year ................................................................................................... 169 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 170 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 170 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................................. 170 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Finger millet Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 170 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................................. 171 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 171 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 171 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 171 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District 2002/03 Agricultural Year.................................................................................................................. 172 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyam Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 172 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 172 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 172 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 173 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 173 APPENDIX II 119 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Field peas Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 174 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 174 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District 2002/03 Agricultural Year................................................................................................. 175 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 175 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 175 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District 2002/03 Agricultural Year ...................................................................................... 175 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 176 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 176 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 176 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District 2002/03 Agricultural Year..................................................................................................... 177 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 177 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District 2002/03 Agricultural Year ..................................................................................... 177 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Jute Harvested (tons) by Season and District 2002/03 Agricultural Year...................................................................................................... 178 APPENDIX II 120 PERMANENT CROPS ......................................................................................................................................................... 179 7.3.1 Production of Permanent Crops by crop type and Region – Tanga ....................................................................... 180 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 181 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 182 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 183 Cont…Production of Permanent Crops by crop type and Region – Tanga ........................................................... 184 Cont…Area planted and area per Household by Region – Tanga ......................................................................... 185 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 186 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 187 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 188 Cont…Production of Permanent Crops by crop type and Region – Tanga............................................................ 189 AGROPROCESSING........................................................................................................................................................ 191 8.0a Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year ................................................................................................................................................... 192 8.0b Number of Crops Growing Households by Method of Processing and District 2002/03 Agricultural Year- Tanga Region ............................................................................................................................................... 192 8.1.1a Number of Crop Growing Households Processing Crops during 2002/03 Agricultural Year by Location and Crop, Tanga Region ......................................................................................................................... 192 8.1.1b Number of Crop Growing Households Reporting Processing of Farm Products Produced during 2002/03 Agricultural Year By Use of Product and Crop, Tanga Region............................................................................. 193 8.1.1c Number of Crop Growing Households Reporting Processing of Farm Products Produced during 2002/03 Agricultural Year By Location of Sale of Product and Crop, Tanga Region......................................................... 193 8.1.1d Number of Crop Growing Households by Main Product and District during 2002/03 Agriculture Year, Tanga Region ......................................................................................................................................................... 193 8.1.1e Number of Crop Growing Households by Use of Primary Processed Product and district during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................ 194 8.1.1f Number of Crop Growing Households by Where Product Sold and District during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................................... 194 8.1.1g Number of Crop Growing Households By type of By-Product and District during 2002/03 Agriculture Year, Tanga Region ............................................................................................................................................... 194 MARKETING .......................................................................................................................................................... 195 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Tanga Region.................................................................................................................. 196 10.2 Number of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year.......................................................................................................................... 196 10.3 Proportion of Households who reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year ................................................................................................................................................... 196 APPENDIX II 121 IRRIGATION /EROSION CONTROL ........................................................................................................................... 197 11.1 Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural Year by District.................................................................................................................................................... 198 11.2 Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year................................ 198 11.3 Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year..................................................................................................................... 198 11.4 Number of Agriculture Households by method of used to obtain water and district during 2002/03 Agriculture Year .......................................................................................................................................................... 198 11.5 Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year ..................................................................................................................................... 199 11.6 Number of Households with Erosion Control/Water Harvesting Facilities on their Land by District................... 199 11.7 Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 Agriculture Year .................................................................................................................................................... 199 ACCESS TO FARM INPUTS/IMPLEMENTS .............................................................................................................. 201 12.1.1 Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year .......... 202 12.1.2 Number of Agricultural Households Using Farm Yard Manure by District during 2002/03 Agricultural Year .......................................................................................................................................................... 202 12.1.3 Number of Agricultural Households Using COMPOST Manure by District during 2002/03 Agricultural Year .......................................................................................................................................................... 202 12.1.4 Number of Crop Growing Households Using Insecticides/Fungicides by District during 2002/03 Agricultural Year ................................................................................................................................................... 203 12.1.5 Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year.............. 203 12.1.6 Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year............ 203 12.1.7 Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.8 Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.9 Number of Agricultural Households by Source of COMPOST Manure and District, 2002/03 Agricultural Year ................................................................................................................................................... 204 12.1.10 Number of Agricultural Households by Source of Pesticides/Fungicides and District, 2002/03 Agricultural Year ................................................................................................................................................... 205 12.1.11 Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year............... 205 12.1.12 Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year ................................................................................................................................................... 205 12.1.13 Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year ................................................................................................................................................... 206 12.1.14 Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 206 APPENDIX II 122 12.1.15 Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.18 Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.16 Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................................... 207 12.1.25 Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.26 Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.27 Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year ................................................................................................................................................... 208 12.1.28 Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year ................................................................................................................................................... 209 12.1.29 Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year .......................................................................................................................................................... 209 12.1.30 Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year ................................................................................................................................................... 209 12.1.31 Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.32 Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.33 Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year .......................................................................................................................................................... 210 12.1.34 Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year .......................................................................................................................................................... 211 12.1.35 Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year.............. 211 12.1.36 Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year .......................................................................................................................................................... 211 12.1.37 Number of Agricultural Households with Plan to use Chemical Fertilizers Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 211 12.1.38 Number of Agricultural Households with Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.39 Number of Agricultural Households with Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.40 Number of Agricultural Households with Plan to use Pesticides/Fungicides Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.41 Number of Agricultural Households with Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 12.1.42 Number of Agricultural Households with Plan to use Improved Seeds next year by District, 2002/03 Agricultural Year ................................................................................................................................................... 212 APPENDIX II 123 AGRICULTURE CREDIT ............................................................................................................................................... 213 13.1a Number of Households Reporting the Main reasons for Not Using Credit by District during the 2002/03 Agriculture Year..................................................................................................................................................... 215 13.1b Number of Credits Received by Main Purpose of Credit and District during the 2002/03 Agriculture Year........ 215 13.2a Number of Agriculture Households receiving Credit by sex of household head and District during the 2002/03 Agriculture Year....................................................................................................................................... 214 13.2b Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year..................................................................................................................................................... 214 TREE FARMING AND AGROFORESTRY .................................................................................................................. 217 14.1 Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region ............. 218 Cont…. Number of Planted Trees by Species and District during the 2002/03 Agriculture Year, Tanga Region ......................................................................................................................................................... 218 14.2 Number of Households with planted trees on their land and Number of Trees by Planting Location and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 219 14.3 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region ......................................................................................................................................................... 219 14.4 Number of Households with planted trees on their land and Number of Trees by Planting Location and District during the 2002/03 Agriculture Year, Tanga Region ........................................................................ 220 14.5 Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Tanga Region......................................................................................................................................................... 220 14.6 Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region ......................................................................................................................................................... 221 CROP EXTENSION .......................................................................................................................................................... 223 15.1 Number of Agriculture Households Receiving Extension Messages by District during the 2002/03 Agriculture Year, Tanga Region ........................................................................................................................... 224 15.2 Number of Households by Quality of Extension Services and District during the 2002/03 Agricultural Year, Tanga Region ......................................................................................................................................................... 224 15.3 Number of Agriculture Households by Source of Crop Extension Messages and District during the 2002/03 Agriculture Years, Tanga Region........................................................................................................................... 224 15.4 Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 225 15.5 Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District during the 2002/03 Agriculture Year, Tanga Region .............................................................................................................. 225 15.6 Number of Agriculture Households Receiving Advice on Erosion Control by Source and District during the 2002/03 Agriculture Year, Tanga Region .............................................................................................................. 225 15.7 Number of Agriculture Households Receiving Advice on Organic Fertilizer Use by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 226 APPENDIX II 124 15.8 Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................... 226 15.9 Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District during the 2002/03 Agriculture Year ........................................................................................................ 226 15.10 Number of Agriculture Households Receiving Advice on Mechanization /LST by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 227 15.11 Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................... 227 15.12 Number of Agriculture Households Receiving Advice on Crop Storage by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 227 15.13 Number of Agriculture Households Receiving Advice on Vermin Control by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 228 15.14 Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District during the 2002/03 Agriculture Year, Tanga Region............................................................................................. 228 15.15 Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 228 15.16 Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District during the 2002/03 Agriculture Year, Tanga Region................................................................................ 229 15.17 Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region............................................................................................ 229 15.18 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) during the 2002/03 Agriculture Year, Tanga Region ......................................... 229 15.19 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) during the 2002/03 Agriculture Year, Tanga Region ............................................. 230 15.20 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) during the 2002/03 Agriculture Year, Tanga region............................................... 230 15.21 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) during the 2002/03 Agriculture Year, Tanga Region ............................................. 231 15.22 Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) during the 2002/03 Agriculture Year, Tanga region............................................... 231 ANIMAL CONTRIBUTION TO CROP PRODUCTION .................................................................................................................. 247 17.1 Number of agriculture households using draft animal to cultivate land by District during 2002/03 agriculture year, Tanga Region .......................................................................................................................................................................... 248 17.2 Type of Draft by Number Owned, Used and Area Cultivated (acres) By District during 2002/03 agriculture year, Tanga Region .......................................................................................................................................................................... 248 17.3 Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Tanga region .......................................................................................................................................................................... 248 17.4 Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Tanga Region .................. 248 CATTLE PRODUCTION...................................................................................................................................................................... 249 18.1 Total Number Households rearing Cattle by District during 2002/03 agriculture year, Tanga Region..................................... 250 APPENDIX II 125 18.2 Total Number of Cattle by Type and District as of 1st October 2003....................................................................................... 250 18.3 Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 ................................................................................................................................................ 250 18.4 Total Number of Cattle by Category and Type of Cattle; on 1st October 2003........................................................................ 250 18.5 Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003............................................... 251 18.6 Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003........................................................ 251 18.7 Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003......................................................... 252 18.8 Total Number of Cattle by Category and District as on 1st October 2003............................................................................... 252 GOAT PRODUCTION .......................................................................................................................................................................... 253 19.1 Total Number of Goats by goat type and District as on 1st October 2003................................................................................ 254 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003............................................... 254 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 ........................................................................... 255 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 ................................................................... 255 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003....................................................... 255 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003.......................................................... 256 19.7 Total Number of Goats by Category and District on 1st October 2003 .................................................................................... 256 SHEEP PRODUCTION......................................................................................................................................................................... 257 20.1 Total Number of Sheep by Breed Type on 1st October 2003 ................................................................................................... 258 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 ............................................................. 258 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003..................................................................................... 258 20.4 Average Number of Sheep by Type of Sheep and District on 1st October 2003, Tanga Region. ............................................. 258 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003...................................................................... 259 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003............................................................. 259 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 ............................................................. 259 20.8 Total Number of Sheep by Sheep Type and District on 1st October 2003................................................................................ 259 PIG PRODUTION .......................................................................................................................................................................... 261 21.1 Number of Households and Pigs by Herd Size on 1st October 2003........................................................................................ 262 21.2 Number of Households and Pigs by District on 1st October 2003............................................................................................ 262 21.3 Number of Pigs by Type of Pig and District on 1st October 2003............................................................................................ 262 LIVESTOCK PESTS AND PARASITE CONTROL.......................................................................................................................... 263 22.1 Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year .............. 264 22.2 Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year ...................................................................................................................................................................... 264 APPENDIX II 126 22.3 Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year............................................................................................ 264 22.4 Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. .......................................................................................................................................................................... 264 OTHER LIVESTOCK .......................................................................................................................................................................... 265 23a Total Number of Other Livestock by Type as of 1st October 2003 .......................................................................................... 266 23b Number of Chicken by Category of chicken and District as of 1st October 2003..................................................................... 266 23c Head Number of Other Livestock by Type of Livestock and District ...................................................................................... 266 23d Total Number of households and chickens raised by flock size as of 1st October 2005........................................................... 266 23e Livestock / Poultry Population Trend ....................................................................................................................................... 266 FISH FARMING .......................................................................................................................................................................... 267 28.1a Number of Agriculture Households by Fish Farming and District during the 2002/03 Agriculture Year................................. 268 28.2a Number of Agriculture Households by System of Fish Farming and District during the 2002/03 Agriculture Year................ 268 28.2b Number of Agriculture Households by Source of Fingerling and District during the 2002/03 Agriculture Year ..................... 268 28.2c Number of Agriculture Households by Location of Selling Fish and District during the 2002/03 Agriculture Year................ 268 28.5 Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year ................................................................. 268 LIVESTOCK EXTENSION .................................................................................................................................................................. 269 29.1a Number of households receiving extension advice by District during the 2002/03 agriculture year ....................................... 270 29.1b Livestock Extension Service Providers: Number of Households by Source of Extension and District during the 2002/03 Agriculture year .......... ............................................................................................................................................................. 270 29.1c Number of Households Receiving Advice on Proper Milking by Source and Region.............................................................. 271 29.1d Number of Households Receiving Advice on Milk Hygiene by Source and District................................................................ 271 29.1e Number of Households Receiving Advice on Disease Control by Source and District ............................................................ 272 29.1f Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District........................................ 273 29.1g Number of Households Receiving Advice on Pasture Establishment by Source and District................................................... 273 29.1h Number of Households Receiving Advice on Group Formation and Strengthen by Source and District ................................. 273 29.1i Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District during the 2002/03 Agriculture Year.......... ............................................................................................................................................................. 274 29.1j Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District during the 2002/03 Agriculture Year.......... ............................................................................................................................................................. 274 29.1k Number of Households Receiving Advice on Milk Hygiene by Source and District................................................................ 274 29.1l Number of Agricultural Households by Quality of Extension Services and District, 2002/03 Agricultural Year .................... 274 29.1m Number of Households Receiving Advice on Other Extension Message by Source and District............................................. 274 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES ........................................................................................................ 283 33.01a Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 284 APPENDIX II 127 33.01b Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 285 33.01c: Number of Households by Distance to All Weather Road by District for 2002/03 agriculture year......................................... 285 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year ................................................ 285 33.01e: Number of Households by Distance to Hospital by District for 2002/03 agriculture year........................................................ 286 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year............................................... 286 33.01g : Number of Households by distance to Primary School for 2002/03 agriculture year ............................................................. 286 33.01h Number of Households by Distance to Feeder Road by District............................................................................................... 287 33.01i Number of Households by Distance to Regional Capital.......................................................................................................... 287 33.01j Mean distances from holders dwellings to infrastructures and services by districts ................................................................. 288 33.01k Number of Households by Level of Satisfaction Using Infrastructure and Service by Region................................................. 288 33.01l Number of Households by Distance to Tarmac Road and District for the 2002/03 Agricultural Year ..................................... 288 33.01m Number of Households by Distance to Primary Market and District for the 2002/03 Agricultural Year.................................. 288 33.01n Number of Households by Distance to Tertiary Market and District for the 2002/03 Agricultural Year.................................. 288 33.01o Number of Households by Distance to Secondary Market and District for the 2002/03 Agricultural Year.............................. 288 33.19a Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 289 33.19b: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year ................ 289 33.19c Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 289 33.19d Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 290 33.19e Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year ............ ............................................................................................................................................................. 290 33.19f Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year ........ ............................................................................................................................................................. 290 33.19g Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year............ 290 HOUSEHOLD FACILITIES... ............................................................................................................................................................. 291 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year.............................. 292 34.2 Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year ....... ............................................................................................................................................................. 292 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural Year District......... 292 34.4 Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year ............ ............................................................................................................................................................. 293 34.5 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year..................... 293 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ............................................................................................................................................. 294 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year ............................................................................................................................................. 295 APPENDIX II 128 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year.......................................................................................................................... 295 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year........................................................................................................................... 296 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year.......................................................................................................................... 296 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year................................................................................................. 296 34.12 Number of Households by Number of Meals the Household Normally Took per Day by District........................................... 297 34.13 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District ............ 297 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District.............. 298 34.15 Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District ........................................................................................................................................................ 298 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year................................. 299 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year........... 300 34.18 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year..................... 300 APPENDIX II 129 APPENDIX II: CROP TABLES Type of Agriculture Household........................................................................................................................................... 131 Number of Agriculture Households ..................................................................................................................................... 134 Livelihood Activities .......................................................................................................................................................... 136 Households Demography..................................................................................................................................................... 140 Land Access/Ownership....................................................................................................................................................... 148 Land Use .......................................................................................................................................................... 150 Total Annual Crop and Vegetable Production – LONG and SHORT Rainy Seasons ......................................................... 154 Annual Crop and Vegetable Production – SHORT Rainy Season....................................................................................... 162 Annual Crop and Vegetable Production – LONG Rainy Season......................................................................................... 166 Permanent Crop Production ................................................................................................................................................. 180 Agro-processing .......................................................................................................................................................... 192 Marketing .......................................................................................................................................................... 196 Irrigation/Erosion Control.................................................................................................................................................... 198 Access to Farm Inputs and Implements ............................................................................................................................... 202 Agriculture Credit .......................................................................................................................................................... 214 Tree Farming and Agro-forestry .......................................................................................................................................... 218 Crop Extension .......................................................................................................................................................... 224 Animal Contribution to Crop Production............................................................................................................................. 248 Cattle Production .......................................................................................................................................................... 250 Goat Production .......................................................................................................................................................... 254 Sheep Production .......................................................................................................................................................... 258 Pig Production .......................................................................................................................................................... 262 Livestock Pests and Parasite Control ................................................................................................................................... 264 Other Livestock .......................................................................................................................................................... 266 Fishing Farming .......................................................................................................................................................... 268 Livestock Extension .......................................................................................................................................................... 272 Access to Infrastructure and other services.......................................................................................................................... 284 Household Facilities .......................................................................................................................................................... 292 Appendix II 130 TYPE OF AGRICULTURE HOUSEHOLD Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 131 District Rural households involved in Agriculture % of Total rural house - holds Rural households NOT involved in Agriculture % of Total Rural house - holds Total Rural Household % of Total house - holds Urban Households % of Total house - holds Total Number of Households (from 2002 Pop. Census) Number % Number % Number % Number % Number Lushoto 86,580 99 1062 1 87,642 97 2,621 3 90,263 Korogwe 45,990 95 2252 5 48,242 82 10,270 18 58,512 Muheza 49,195 89 5929 11 55,124 89 7,059 11 62,183 Tanga 8,914 70 3895 30 12,809 24 40,295 76 53,104 Pangani 7,128 82 1526 18 8,653 77 2,630 23 11,283 Handeni 47,739 98 1074 2 48,813 93 3,427 7 52,240 Kilindi 19,654 99 130 1 19,784 67 9,624 33 29,408 Total 265,198 94 15,869 6 281,067 79 75,926 21 356,993 Number of households % Number of households % Number of household % Number of households % Lushoto 48,594 56 144 0 0 0 37,841 44 86,580 86,435 37,986 Korogwe 31,105 68 290 1 0 0 14,596 32 45,990 45,700 14,885 Muheza 37,830 77 379 1 0 0 10,985 22 49,195 48,815 11,365 Tanga 6,974 78 358 4 0 0 1,581 18 8,914 8,555 1,939 Pangani 6,216 87 51 1 0 0 860 12 7,128 7,076 911 Handeni 32,853 69 108 0 0 0 14,777 31 47,739 47,631 14,886 Kilindi 14,833 75 146 1 194 1 4,481 23 19,654 19,314 4,820 Total 178,406 67 1,477 1 194 0 85,121 32 265,198 263,528 86,792 Livestock Only Pastoralist 2.1 TYPE OF AGRICULTURE HOUSEHOLD: Number of Agricultural Households by type of household and District during 2002/03 Agriculture Year Agriculture, Non Agriculture and Urban Households 2. 2 TYPE OF AGRICULTURE HH: Number of Agriculture Households by type of Holding by District during 2002/03 Agriculture year Crops & Livestock Total Number of Agriculture Households Total Number of Households Growing Crops Total Number of Households Rearing Livestock District Crops Only Tanzania Agriculture Sample Census - 2003 Tanga 132 Appendix II 133 NUMBER OF AGRICULTURE HOUSEHOLDS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 134 Number % Average Household Size Number % Average Household Size Number % Lushoto 63,785 74 5 22,795 26 4 86,580 100 5 Korogwe 34,421 75 5 11,569 25 4 45,990 100 5 Muheza 36,415 74 5 12,779 26 4 49,195 100 5 Tanga 6,424 72 5 2,490 28 4 8,914 100 5 Pangani 5,402 76 4 1,726 24 4 7,128 100 4 Handeni 37,875 79 6 9,864 21 4 47,739 100 5 Kilindi 16,111 82 6 3,543 18 4 19,654 100 5 Total 200,432 76 5 64,766 24 4 265,198 100 5 3.0: Number of Agricultural Households and Average Household Size by Sex of the Head of Household and District, 2002/03 Agricultural Year Average Household Size District Male Female Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 135 RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 136 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 27,825 11,033 3,462 38,782 5,331 292 292 Korogwe 9,061 5,880 4,955 18,040 6,534 365 1,139 Muheza 10,236 16,697 1,419 14,876 3,474 891 659 Tanga 511 2,499 347 4,136 345 948 157 Pangani 911 1,537 66 3,439 231 590 430 Handeni 19,300 3,027 1,920 17,279 2,217 107 2,825 Kilindi 6,819 676 1,461 9,484 825 0 341 Total 74,663 41,349 13,630 106,035 18,958 3,192 5,842 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 50,682 17,863 12,699 4,054 275 3,478 2,898 Korogwe 24,066 5,472 2,865 6,947 2,442 2,265 2,783 Muheza 27,576 10,719 1,923 4,337 1,254 1,239 1,975 Tanga 3,103 2,634 566 1,652 586 112 219 Pangani 3,550 1,435 314 920 180 230 454 Handeni 23,112 2,457 6,333 6,758 1,046 4,489 4,064 Kilindi 8,607 1,849 1,511 3,504 729 2,433 923 Total 140,696 42,430 26,211 28,171 6,513 14,246 13,316 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 5,328 14,399 21,672 4,933 1,600 15,877 15,373 Korogwe 5,680 5,240 5,635 5,254 3,934 10,668 8,155 Muheza 5,843 4,846 5,532 5,887 1,669 8,614 17,231 Tanga 2,361 1,325 779 1,110 1,009 516 1,344 Pangani 1,141 661 533 706 292 1,052 2,686 Handeni 4,050 3,469 6,275 5,139 1,676 18,046 9,075 Kilindi 2,334 1,799 2,193 1,600 1,119 7,062 3,546 Total 26,737 31,739 42,620 24,630 11,300 61,834 57,411 3.1a RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: First Most Importance 3.1b RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Second Most Importance 3.1c RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Third Most Importance Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1 3 6 2 7 4 5 Korogwe 1 5 6 2 7 3 4 Muheza 1 2 6 5 7 4 3 Tanga 3 2 5 1 6 7 4 Pangani 2 5 6 1 7 4 3 Handeni 1 6 5 2 7 3 4 Kilindi 1 6 5 2 7 3 4 Total 1 5 6 2 7 3 4 3.1 The Livelihood Activities/Source of Income of the Households Raked in Order of Importance by District District Livelihood Activity Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 137 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 1,587 7,205 10,952 1,011 3,485 28,555 31,168 Korogwe 1,807 1,927 3,749 3,468 3,047 14,714 14,569 Muheza 1,473 1,759 3,362 3,108 1,154 20,397 16,910 Tanga 1,019 612 1,393 386 645 588 2,813 Pangani 448 365 453 559 351 2,519 2,298 Handeni 644 3,310 4,582 3,517 1,388 14,289 17,344 Kilindi 729 1,851 1,511 879 781 6,229 7,044 Total 7,707 17,029 26,004 12,928 10,851 87,291 92,146 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 433 5,755 11,521 1,565 3,297 24,711 24,521 Korogwe 2,845 2,247 2,105 1,405 3,109 10,986 11,360 Muheza 1,153 3,952 3,504 1,790 590 14,351 8,230 Tanga 269 221 866 205 333 515 2,205 Pangani 280 691 641 371 442 1,739 741 Handeni 432 5,124 4,350 1,912 925 7,230 9,763 Kilindi 534 1,456 2,337 487 824 3,540 4,925 Total 5,946 19,445 25,324 7,736 9,519 63,071 61,745 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 144 6,178 5,630 1,740 1,127 11,203 5,784 Korogwe 1,229 989 1,883 832 411 4,989 3,576 Muheza 479 964 2,490 893 911 2,835 2,395 Tanga 0 55 274 18 223 235 409 Pangani 207 395 225 162 164 472 400 Handeni 93 2,958 2,582 952 1,254 1,374 2,767 Kilindi 340 1,071 1,507 239 292 242 2,534 Total 2,492 12,609 14,591 4,838 4,384 21,351 17,866 District Annual Crop Farming Permanent Crop Farming Livestock Keeping / Herding Off Farm Income Remittances Fishing / Hunting & Gathering Tree / Forest Resources Lushoto 292 870 289 869 835 862 144 Korogwe 408 0 827 316 0 206 525 Muheza 248 426 639 255 0 260 167 Tanga 0 32 30 29 41 33 0 Pangani 14 35 35 0 155 257 14 Handeni 0 414 489 216 315 108 430 Kilindi 0 243 385 244 195 49 243 Total 963 2,021 2,696 1,928 1,541 1,774 1,524 3.1e RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fifth Most Importance 3.1f RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Sixth Most Importance 3.1g RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Seventh Most Importance 3.1d RANK OF IMPORTANCE OF LIVELIHOOD ACTIVITIES: Fourth Most Importance Tanzania Agriculture Sample Census - 2003 Tanga 138 Appendix II 139 HOUSEHOLDS DEMOGRAPHS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 140 Number % Number % Number % Less than 4 82,018 48 88,990 52 171,007 100 05 - 09 104,818 51 102,672 49 207,490 100 10 - 14 101,601 52 92,510 48 194,111 100 15 - 19 68,064 52 61,926 48 129,989 100 20 - 24 40,272 40 61,291 60 101,563 100 25 - 29 43,942 46 51,603 54 95,544 100 30 - 34 35,049 48 38,261 52 73,310 100 35 - 39 28,872 43 37,812 57 66,684 100 40 - 44 25,932 46 30,220 54 56,152 100 45 - 49 23,468 50 23,258 50 46,726 100 50 - 54 19,919 50 19,937 50 39,856 100 55 - 59 13,381 55 10,934 45 24,315 100 60 - 64 13,033 51 12,749 49 25,782 100 65 - 69 11,024 54 9,540 46 20,565 100 70 - 74 10,535 51 10,146 49 20,681 100 75 - 79 4,869 56 3,763 44 8,632 100 80 - 84 4,058 54 3,400 46 7,458 100 Above 85 3,113 51 3,052 49 6,165 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Less than 4 82,018 13 88,990 13 171,007 13 05 - 09 104,818 17 102,672 16 207,490 16 10 - 14 101,601 16 92,510 14 194,111 15 15 - 19 68,064 11 61,926 9 129,989 10 20 - 24 40,272 6 61,291 9 101,563 8 25 - 29 43,942 7 51,603 8 95,544 7 30 - 34 35,049 6 38,261 6 73,310 6 35 - 39 28,872 5 37,812 6 66,684 5 40 - 44 25,932 4 30,220 5 56,152 4 45 - 49 23,468 4 23,258 4 46,726 4 50 - 54 19,919 3 19,937 3 39,856 3 55 - 59 13,381 2 10,934 2 24,315 2 60 - 64 13,033 2 12,749 2 25,782 2 65 - 69 11,024 2 9,540 1 20,565 2 70 - 74 10,535 2 10,146 2 20,681 2 75 - 79 4,869 1 3,763 1 8,632 1 80 - 84 4,058 1 3,400 1 7,458 1 Above 85 3,113 0 3,052 0 6,165 0 Total 633,967 100 662,064 100 1,296,031 100 3.3 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (col %) Age Group Sex Male Female Total 3.2 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and Age Group for the 2002/03 Agricultural Year (row %) Age Group Sex Male Female Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 141 Number % Number % Number % Lushoto 196,570 48 209,752 52 406,322 100 Korogwe 112,681 49 115,135 51 227,816 100 Muheza 113,667 49 116,950 51 230,617 100 Tanga 19,546 48 21,375 52 40,922 100 Pangani 15,310 52 14,143 48 29,453 100 Handeni 123,622 48 132,669 52 256,291 100 Kilindi 52,570 50 52,040 50 104,610 100 Total 633,967 49 662,064 51 1,296,031 100 Number % Number % Number % Number % % Lushoto 258,554 73.2 7,315 2.1 0 0.0 87,278 24.7 100 Korogwe 140,665 68.9 5,004 2.5 0 0.0 58,514 28.7 100 Muheza 143,330 71.2 4,205 2.1 283 0.1 53,363 26.5 100 Tanga 25,756 69.8 1,922 5.2 131 0.4 9,073 24.6 100 Pangani 19,921 74.4 519 1.9 39 0.1 6,280 23.5 100 Handeni 128,671 59.7 6,330 2.9 750 0.3 79,943 37.1 100 Kilindi 44,615 51.2 668 0.8 243 0.3 41,651 47.8 100 Total 761,512 68 25,964 2 1,446 0.1 336,102 30 100 Number % Number % Number % Number % Lushoto 132,142 37.4 162,461 46.0 58,544 16.6 353,147 100 Korogwe 69,632 34.1 87,548 42.9 47,003 23.0 204,183 100 Muheza 65,362 32.5 90,049 44.8 45,771 22.8 201,182 100 Tanga 11,636 31.5 17,439 47.3 7,807 21.2 36,882 100 Pangani 9,276 34.7 13,161 49.2 4,322 16.2 26,758 100 Handeni 63,567 29.5 83,470 38.7 68,656 31.8 215,693 100 Kilindi 25,390 29.1 27,199 31.2 34,588 39.7 87,178 100 Total 377,006 33.5 481,327 42.8 266,691 23.7 1,125,024 100 3.7 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % % % Lushoto 152,752 43 1,866 1 144 0 143 0 1 8 Korogwe 76,219 37 3,934 2 103 0 107 0 2 8 Muheza 77,409 38 1,565 1 1,299 1 1,529 1 1 5 Tanga 9,867 27 898 2 23 0 987 3 2 4 Pangani 8,770 33 45 0 0 0 942 4 1 5 Handeni 92,233 43 2,552 1 107 0 630 0 1 5 Kilindi 33,682 39 2,921 3 1,164 1 48 0 0 2 Total 450,932 40 13,782 1 2,839 0 4,387 0 1 6 Main Activity 3.6 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members 5 years and above By School Attendancy and District , 2002/03 Agricultural Year District School Attendancy Attending School Completed Never Attended to School Total 3.5 HOUSEHOLDS DEMOGRAPHS: Number of Agriculture Household Members 5 years and above Who Can Read and Write Languages By Type of Language and District, 2002/03 Agricultural Year District Read & Write Swahili Swahili & English Any Other Language Don't Read / Write 3.4 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Sex and District for the 2002/03 Agricultural Year District Sex Male Female Total Fishing District Crop/Seaweed Farming Livestock Keeping / Herding Livestock Pastoralist Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 142 cont… HOUSEHOLD DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Number % Lushoto 16,606 5 1,439 0 576 0 0 0 570 0 Korogwe 7,418 4 919 0 200 0 103 0 1,556 1 Muheza 18,315 9 1,566 1 708 0 736 0 2,515 1 Tanga 5,170 14 504 1 985 3 103 0 1,250 3 Pangani 3,665 14 247 1 148 1 41 0 638 2 Handeni 17,355 8 2,481 1 615 0 216 0 837 0 Kilindi 14,306 16 98 0 0 0 192 0 582 1 Total 82,834 7 7,254 1 3,231 0 1,391 0 7,948 1 cont… HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Main Activity and District Number % Number % Number % Number % Lushoto 116,122 33 29,186 8 280 0 353,147 100 Korogwe 63,908 31 23,480 11 809 0 204,183 100 Muheza 63,082 31 16,832 8 1,957 1 201,182 100 Tanga 11,348 31 2,635 7 485 1 36,882 100 Pangani 8,838 33 1,269 5 261 1 26,758 100 Handeni 55,470 26 21,768 10 7,226 3 215,693 100 Kilindi 24,417 28 7,202 8 716 1 87,178 100 Total 343,184 31 102,373 9 11,735 1 1,125,024 100 Number % Number % Number % Number % % Lushoto 153,483 43 11,754 3 143,275 41 44,635 13 100 Korogwe 66,982 33 26,928 13 68,254 33 42,019 21 100 Muheza 74,537 37 30,593 15 63,190 31 32,863 16 100 Tanga 8,995 24 5,515 15 9,496 26 12,877 35 100 Pangani 8,093 30 1,458 5 12,725 48 4,483 17 100 Handeni 85,034 39 24,270 11 67,099 31 39,290 18 100 Kilindi 36,026 41 12,288 14 24,623 28 14,240 16 100 Total 433,150 39 112,805 10 388,661 35 190,408 17 100 District District Too Old / Retired / Sick / Disabled Not Working & Unavailable Student 3.8 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of involvement in Farming Activity and District, 2002/03 Agricultural Year Self Employed (Non Farmimg) without Employees Unpaid Family Helper (Non Agriculture) Housemaker / Housewife Other Total Not Working & Available District Involvement in Farming Works Full-time on Farm Works Part-time on Farm Rarely Works on Farm Never Works on Farm Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 143 Number % Number % Number % Number % % % Lushoto 146 0 288 0 2,314 1 2,450 2 10 2 Korogwe - - 1,137 1 2,417 3 3,800 4 14 4 Muheza - - 492 1 1,904 2 3,308 4 16 5 Tanga 111 1 167 1 448 3 681 4 12 3 Pangani - - 23 0 301 2 518 4 14 4 Handeni 540 1 108 0 2,558 3 5,094 6 13 4 Kilindi 97 0 - - 731 3 925 3 13 1 Total 893 0 2,215 0 10,672 2 16,776 3 13 3 Number % Number % Number % Number % Number % Lushoto 128,131 79 1,166 1 145 0 - - 146 0 Korogwe 55,775 64 1,731 2 376 0 300 0 - - Muheza 55,523 62 1,874 2 338 0 55 0 167 0 Tanga 10,589 61 360 2 30 0 23 0 91 1 Pangani 8,465 64 250 2 35 0 19 0 67 1 Handeni 53,352 64 1,247 1 - - - - 217 0 Kilindi 20,391 75 98 0 - - - - - - Total 332,227 69 6,726 1 925 0 397 0 688 0 Number % Number % Number % Number % Number % Lushoto 582 0 144 0 2,588 2 - - 708 0 Korogwe 596 1 191 0 2,305 3 - - 107 0 Muheza 1,048 1 124 0 1,379 2 - - 84 0 Tanga 73 0 81 0 775 4 10 0 212 1 Pangani 76 1 22 0 230 2 24 0 22 0 Handeni 520 1 217 0 944 1 - - 212 0 Kilindi 47 0 - - 433 2 - - 49 0 Total 2,942 1 779 0 8,654 2 34 0 1,393 0 Number % Number % Number % Lushoto - - 1,010 1 162,461 100 Korogwe - - 725 1 87,548 100 Muheza - - 1,532 2 90,049 100 Tanga 45 0 579 3 17,439 100 Pangani - - 379 3 13,161 100 Handeni - - 1,253 2 83,470 100 Kilindi 47 0 386 1 27,199 100 Total 92 0 5,865 1 481,327 100 District District District g Secondary Form Six Under Standard One Standard One Standard Two Standard Three y Tertiary Education Adult Education Total Form Two Form Three Form Four cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year Education Level Standard Seven Standard Eight Training After Primary Education Pre Form One Form One 3.9 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year cont … HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Household Members By Level of Formal Education Completion and District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 144 Number % Average Household Size Number % Average Household Size Number % Lushoto 63,785 74 5 22,795 26 4 86,580 100 5 Korogwe 34,421 75 5 11,569 25 4 45,990 100 5 Muheza 36,415 74 5 12,779 26 4 49,195 100 5 Tanga 6,424 72 5 2,490 28 4 8,914 100 5 Pangani 5,402 76 4 1,726 24 4 7,128 100 4 Handeni 37,875 79 6 9,864 21 4 47,739 100 5 Kilindi 16,111 82 6 3,543 18 4 19,654 100 5 Total 200,432 76 5 64,766 24 4 265,198 100 5 Number % Number % Number % Number % Tanga 3,664 45 3,047 37 1,521 18 8,232 100 Handeni 27,704 73 6,445 17 3,604 10 37,753 100 Pangani 3,999 67 1,475 25 539 9 6,013 100 Korogwe 27,323 70 9,037 23 2,926 7 39,286 100 Kilindi 12,256 76 2,872 18 1,019 6 16,147 100 Muheza 25,227 78 5,388 17 1,552 5 32,168 100 Lushoto 46,179 87 5,904 11 862 2 52,945 100 Total 146,351 76 34,169 18 12,023 6 192,543 100 No Education Primary Education Post Primary Education Secondary Education Post Secondary Education University & Equivalent Education Adult Education Total Lushoto 20,754 62,658 145 1,734 427 144 718 86,580 Korogwe 11,060 32,741 209 1,681 - - 299 45,990 Muheza 12,223 34,685 164 1,318 84 - 720 49,195 Tanga 2,448 5,410 10 605 77 45 319 8,914 Pangani 1,450 5,183 11 201 - - 282 7,128 Handeni 14,564 31,725 - 721 106 - 623 47,739 Kilindi 8,319 10,614 - 287 49 47 338 19,654 Total 70,819 183,016 539 6,548 742 236 3,298 265,198 Mean Median Mode Mean Median Mode Mean Median Mode Lushoto 42 40 30 49 48 40 44 41 40 Korogwe 47 44 35 50 47 65 47 45 35 Muheza 46 45 30 50 48 60 47 45 60 Tanga 49 48 45 55 55 70 51 50 70 Pangani 46 44 25 49 46 70 47 45 65 Handeni 43 40 30 47 45 30 44 40 30 Kilindi 42 40 30 45 42 50 42 40 30 Total 44 42 30 49 47 40 45 43 30 District Male Female Total 3.11 HOUSEHOLD DEMOGRAPHS: Number of Agricultural Households Involved in Off Farm Income Generating Activity By Number of Off Farm Income Activities and District, 2002/03 Agricultural Year District Off farm income Total One Two More than Two Average Household Size 3.10 HOUSEHOLDS DEMOGRAPHS: Number of Agricultural Households and Average Household Size By Sex of the Head of Household and District, 2002/03 Agricultural Year 3.13 HOUSEHOLDS DEMOGRAPHS: Mean, Meadian, Mode of Age of Head of Agricultural Household and District District Male Female Total 3.12 HOUSEHOLDS DEMOGRAPHS: Number of Heads of Agricultural Households By Maximum Education Level Attained and District, 2002/03 Agricultural Year District Maximum Education Level Attained Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 145 3.14 Time Series of Male and Female Headed Households Male Female Total Male Female Total Male Female Total Lushoto 55,415 10,703 66,117 8,370 12,092 20,462 63,785 22,795 86,580 Korogwe 28,146 6,252 34,399 6,274 5,317 11,591 34,421 11,569 45,990 Muheza 30,491 6,580 37,071 5,924 6,200 12,124 36,415 12,779 49,195 Tanga 5,430 1,123 6,554 994 1,367 2,360 6,424 2,490 8,914 Pangani 4,598 1,058 5,656 803 668 1,472 5,402 1,726 7,128 Handeni 29,694 4,337 34,031 8,181 5,527 13,708 37,875 9,864 47,739 Kilindi 10,220 1,261 11,481 5,891 2,282 8,172 16,111 3,543 19,654 Total 163,994 31,314 195,308 36,438 33,452 69,890 200,432 64,766 265,198 3.15 Literacy Rate of Heads of Households by Sex and District District Literacy Know Don;t know Total Type of Holding NSCA 1994/95 EAS 1995/96 EAS 1996/97 IAS 1997/98 DIAS 1998/99 NSCA 2002/03 Male Headed ( Number in Thousands) 175 179 192 204 205 200 Female Headed ( Number in Thousands) 38 51 63 64 56 64 Total 213 230 255 268 261 264 Male Headed (Percentage) 82 78 75 76 78 76 Female Headed (Percentage) 18 22 25 24 22 24 Total 100 100 100 100 100 100 Tanzania Agriculture Sample Census - 2003 Tanga 146 Appendix II 147 LAND ACCESS/OWNERSHIP Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 148 No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 2,451 3 81,583 94 14,865 17 2,127 2 3,002 3 863 1 1,304 2 86,435 Korogwe 7,554 17 28,457 62 12,194 27 7,104 16 6,613 14 1,326 3 1,999 4 45,700 Muheza 9,683 20 26,895 55 12,370 25 1,838 4 10,581 22 697 1 2,860 6 48,815 Tanga 3,652 43 2,266 26 1,639 19 384 4 1,740 20 131 2 347 4 8,555 Pangani 272 4 5,228 74 1,423 20 41 1 1,100 16 72 1 359 5 7,076 Handeni 17,106 36 24,959 52 7,298 15 428 1 3,813 8 1,662 3 1,936 4 47,631 Kilindi 1,824 9 14,670 76 1,307 7 438 2 873 5 49 0 2,827 15 19,314 Total 42,541 16 184,058 70 51,095 19 12,361 5 27,721 11 4,800 2 11,632 4 263,528 District Total Number of Households Land Access 4.1 LAND ACCESS/OWNERSHIP: Number of Farming Households By Type of Land Ownership/Tenure and District for the 2002/03 Agricultural Year Leased/Certificate of Ownwership Owned under Customary Law Bought Rented Borrowed Households with Area Shared Cropped Households with Area under Other Forms of Tenure Area Leased/ Certificate of Ownership Area Owned Under Customary Law Area Bought Area Rented Area Borrowed Area Shared Cropped Area under Other Forms of Tenure Total Lushoto 2,370 82,638 9,649 734 1,321 264 566 97,543 Korogwe 10,034 37,725 18,227 6,229 4,395 1,343 3,159 81,111 Muheza 15,746 46,914 24,133 1,238 9,938 272 3,666 101,907 Tanga 7,653 3,743 3,283 525 1,711 156 600 17,671 Pangani 517 10,141 2,556 17 931 80 560 14,803 Handeni 52,143 63,069 20,618 581 4,236 4,605 5,494 150,746 Kilindi 5,471 41,526 3,238 463 973 79 8,865 60,614 Total 93,934 285,756 81,704 9,786 23,506 6,800 22,910 524,396 % 18 54 16 2 4 1 4 100 4.2 LAND ACCESS/OWNERSHIP: Area of Land (ha) by Ownership/Tenure (Hectare) and District for the 2002/03 Agricultural Year District Land Access/ Ownership (Hectare) Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 149 LAND USE Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 150 Households with Temporary Mono Crops Households with Temporary Mixed Crops Households with Permanent Mono Crops Households with Permanent Mixed Crops Households with Permanent / Annual Mix Households with Pasture Households with Fallow Households with Natural Bush Households with Planted Trees Households Renting to Others Households with Unusable Land Households with Uncultivated Usable Land Total Number of Households Lushoto 27,522 41,392 21,570 4,613 33,010 421 7,063 289 9,902 581 730 1,167 86,580 Korogwe 34,049 13,313 7,128 8,922 8,549 423 6,000 0 2,097 2,089 914 8,675 45,990 Muheza 27,406 13,807 15,007 15,586 15,868 988 6,832 400 4,382 566 1,589 8,090 49,195 Tanga 3,286 1,481 2,036 2,952 3,337 191 158 0 0 95 529 2,943 8,914 Pangani 5,032 1,401 2,365 1,953 1,454 125 470 18 121 90 277 1,418 7,128 Handeni 41,619 8,302 6,447 6,219 9,544 216 12,319 641 210 1,160 2,309 13,687 47,739 Kilindi 11,205 6,617 2,870 1,996 4,514 146 2,916 194 243 146 1,552 5,931 19,654 Total 150,120 86,312 57,423 42,241 76,275 2,509 35,758 1,542 16,954 4,726 7,899 41,911 265,198 Districts Area under Temporary Mono Crops Area under Temporary Mixed Crops Area under Permanent Mono Crops Area under Permanent Mixed Crops Area under Permanent / Annual Mix Area under Pasture Area under Fallow Area under Natural Bush Area under Planted Trees Area Rented to Others Area Unusable Area of Uncultivated Usable Land Total Lushoto 15,136 31,558 7,664 2,611 33,082 71 4,729 117 1,621 186 296 473 97,543 Korogwe 35,542 11,038 3,122 6,396 7,707 162 4,857 0 654 2,200 562 8,871 81,111 Muheza 21,727 11,289 12,593 17,539 16,691 663 6,620 893 1,362 430 1,619 10,481 101,907 Tanga 1,799 1,085 1,343 4,038 3,884 429 91 0 0 138 727 4,137 17,671 Pangani 4,350 1,316 2,480 2,685 1,599 84 478 20 19 51 254 1,522 14,859 Handeni 68,474 9,664 4,486 5,385 11,126 304 22,534 1,565 222 1,093 3,628 22,267 150,746 Kilindi 20,547 12,408 1,419 1,427 7,848 138 4,616 176 83 138 2,511 9,303 60,614 Total 167,575 78,356 33,108 40,080 81,938 1,852 43,926 2,771 3,959 4,236 9,597 57,053 524,451 % 32 15 6 8 16 0 8 1 1 1 2 11 100 Land use area Type of Land Use 5.1 LAND USE: Number of Agricultural Households By Type of Land Use and District for the 2002/03 Agricultural Year Districts 5.2 LAND USE: Area of Land (Ha) by type of Land Use and District for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 151 Number % Number % Number % Number % Lushoto 75,031 87 11,404 13 86,435 Lushoto 35,993 42 50,442 58 86,435 Korogwe 29,280 64 16,420 36 45,700 Korogwe 26,375 58 19,325 42 45,700 Muheza 32,598 67 16,218 33 48,815 Muheza 28,327 58 20,488 42 48,815 Tanga 3,596 42 4,960 58 8,555 Tanga 5,945 69 2,611 31 8,555 Pangani 4,147 59 2,930 41 7,076 Pangani 4,694 66 2,382 34 7,076 Handeni 20,561 43 27,070 57 47,631 Handeni 31,637 66 15,994 34 47,631 Kilindi 10,561 55 8,753 45 19,314 Kilindi 13,381 69 5,933 31 19,314 Total 175,773 67 87,754 33 263,528 Total 146,353 56 117,175 44 263,528 Number % Number % Lushoto 12,284 14 74,151 86 86,435 Korogwe 11,206 25 34,494 75 45,700 Muheza 14,802 30 34,013 70 48,815 Tanga 3,459 40 5,097 60 8,555 Pangani 1,739 25 5,337 75 7,076 Handeni 16,758 35 30,873 65 47,631 Kilindi 2,326 12 16,988 88 19,314 Total 62,574 24 200,954 76 263,528 No Total Table 5.5: LAND SUFFICIENCY Number of Agricultural Households by whether Female Members of the Household Own or Have Customary Right to Land and District; 2002/03 Agricultural Year District Do any Female Members of the Household own or have customary right to Land Yes No Total Table 5.3 : LAND SUFFICIENCY Number of Households by type of household and District during 2002/03 Agricultural Year Table 5.4: LAND SUFFICIENCYNumber of Agricultural Households by Whether they Consider themselves to have Sufficient Land for the Household and District during 2002/03 Agricultural Year District Was all Land Available to the Hh Used during 2002/03? District Do you Consider that you have sufficient land for the Hh? Yes No Total Yes Tanzania Agriculture Sample Census - 2003 Tanga 152 Appendix II 153 TOTAL ANNUAL CROP & VEGETABLE PRODUCTION – LONG & SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 154 Number of Household Planted Area (hectare) Number of Household Planted Area (hectare) Lushoto 78,808 69,194 72,230 50,351 119,544 57.88 Pangani 4,631 3,902 5,730 5,260 9,162 42.59 Tanga 4,586 2,335 5,675 3,173 5,508 42.39 Muheza 36,437 24,062 43,558 33,883 57,945 41.53 Handeni 36,056 34,643 46,671 74,099 108,742 31.86 Korogwe 26,637 16,755 41,687 40,899 57,655 29.06 Kilindi 9,345 9,928 18,050 31,825 41,754 23.78 Total 196,502 160,820 233,601 239,490 400,310 40.17 Number of households Growing Crops Number of households NOT Growing Crops Number of households Growing Crops Number of households NOT Growing Crops Lushoto 78,808 7,771 72,230 14,349 86,435 Korogwe 26,637 19,353 41,687 4,303 45,700 Muheza 36,437 12,757 43,558 5,637 48,815 Tanga 4,586 4,328 5,675 3,239 8,555 Pangani 4,631 2,496 5,730 1,397 7,076 Handeni 36,056 11,682 46,671 1,068 47,631 Kilindi 9,345 10,309 18,050 1,604 19,314 Total 196,502 68,697 233,601 31,597 263,528 7.1 & 7.2b TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of crop growing Households Planting Crops by Season and Region District Short Rainy Season Long Rainy Season Total Number of Crop Growing households % Area planted in short rainy season 7.1 & 7.2a TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Area Planted (ha) by Season and District District Total area planted (hectare) Short Rainy Season Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 155 Area Planted (ha) Quantity Harvested (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) Area Planted (ha) Quantity Harveste d (tons) Yield (kg/ha) CEREALS 111,875 65,736 183,654 115,251 295,529 180,987 Maize 110,043 61,910 563 177,433 111,692 629 287,476 173,602 604 Paddy 1,735 3,488 2,010 5,930 3,472 585 7,665 6,960 908 Sorghum 97 338 3,485 19 7 357 116 345 2969 Finger Millet 0 0 0 66 23 346 66 23 346 Wheat 0 0 0 205 57 280 205 57 280 ROOTS & TUBERS 10,759 15,214 36,856 52,752 47,614 67,966 Cassava 1,725 2,131 1,235 29,007 43,368 2,358 30,732 45,499 2358 Sweet Potatoes 480 537 1,119 593 465 784 1,073 1,002 934 Irish Potatoes 8,314 11,973 1,440 7,089 8,763 1,236 15,402 20,736 1346 Yams 51 0 0 80 55 684 132 55 417 Cocoyam 188 574 3,045 86 101 1,169 275 675 2455 PULSES 34,624 11,221 42,393 16,160 77,017 27,381 Mung Beans 0 0 0 64 88 1,385 64 88 1385 Beans 24,185 8,699 360 38,843 15,325 395 63,028 24,023 381 Cowpeas 9,276 2,125 229 2,731 499 183 12,007 2,624 219 Green Gram 1,108 288 260 755 248 329 1,863 536 288 Chich Peas 2 0 198 0 0 0 2 0 198 Bambaranuts 2 1 296 0 0 0 2 1 296 Field Peas 50 109 2,159 0 0 0 50 109 2159 OIL SEEDS & OIL N 725 248 1,839 1,268 2,564 1,516 Sunflower 0 0 0 78 35 451 78 35 451 Simsim 92 26 281 729 271 372 822 297 362 Groundnuts 613 212 346 1,032 961 932 1,645 1,174 714 Castor Seed 20 10 494 0 0 0 20 10 494 FRUIT & VEGETAB 2,821 10,723 2,525 8,827 5,346 19,550 Okra 9 13 1,422 26 17 629 35 29 831 Radish 4 2 529 0 0 0 4 2 529 Bitter Aubergine 18 216 11,856 176 296 1,685 194 512 2641 Onions 18 85 4,681 100 279 2,782 119 364 3072 Ginger 88 66 746 0 0 0 88 66 746 Cabbage 344 1,410 4,099 502 2,062 4,109 846 3,472 4105 Tomatoes 1,621 7,220 4,455 948 3,632 3,832 2,569 10,852 4225 Spinnach 30 8 251 0 0 0 30 8 251 Carrot 51 182 3,584 143 145 1,017 194 328 1691 Chillies 414 1,054 2,549 307 919 2,990 721 1,973 2737 Amaranths 65 140 2,153 66 59 886 131 199 1515 Pumpkins 13 234 17,324 65 31 475 78 265 3384 Cucumber 0 0 0 90 668 7,390 90 668 7390 Egg Plant 9 11 1,227 23 20 856 32 31 960 Water Mellon 137 82 599 78 699 8,936 215 781 3634 CASH CROPS 17 10 448 247 465 256 Seaweed 2 7 2,964 0 0 0 2 7 2964 Cotton 0 0 0 264 165 625 264 165 625 Tobacco 15 3 198 166 70 422 180 73 404 Jute 0 0 0 18 12 642 18 12 642 Total 160,820 91,930 267,714 178,344 428,534 270,274 * The total area planted includes the sum of the planted area for both Long and Short Season and is an overestimation of the actual ar bein produced on the same land during the 2 seasons. Previous surveys have used the Long season to estimate physical land area u production to different crops 7.1 & 7.2c TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Area planted (ha) and Quantity Harvested by Season and Crop for the 2002/03 agriculture year, Tanga Region Crop Short Rainy Season Long Rainy Season Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 156 Number of Households Planted Area (Ha) Number of Households Planted Area (Ha) CEREALS 190,720 111,875 205,932 183,654 295,529 37.9 Maize 186,153 110,043 189,772 177,433 287,476 38.3 Paddy 4,247 1,735 15,443 5,930 7,665 22.6 Sorghum 320 97 66 19 116 83.5 Finger Millet 0 0 217 66 66 0.0 Wheat 0 0 433 205 205 0.0 ROOTS & TUBERS 38,281 10,759 27,925 36,856 47,614 22.6 Cassava 5,155 1,725 2,315 29,007 30,732 5.6 Sweet Potatoes 2,041 480 2,468 593 1,073 44.7 Irish Potatoes 29,786 8,314 22,414 7,089 15,402 54.0 Yams 213 51 213 80 132 39.0 Cocoyam 1,085 188 515 86 275 68.6 PULSES 106,989 34,624 100,762 42,393 77,017 45.0 Mung Beans 0 0 133 64 64 0.0 Beans 77,157 24,185 89,035 38,843 63,028 38.4 Cowpeas 25,741 9,276 8,833 2,731 12,007 77.3 Green Gram 3,798 1,108 2,760 755 1,863 59.5 Chich Peas 22 2 0 0 2 100.0 Bambaranuts 23 2 0 0 2 100.0 Field Peas 248 50 0 0 50 100.0 OIL SEEDS & OIL N 2,546 725 4,608 2,871 3,596 20.2 Sunflower 0 0 96 78 78 0.0 Simsim 202 92 1,163 729 822 11.2 Groundnuts 2,296 613 3,350 1,032 1,645 37.3 Castor Seed 48 20 0 1,032 1,051 1.9 FRUITS & VEGETA 13,080 2,821 11,089 2,525 5,346 52.8 Okra 56 9 220 26 35 25.5 Radish 14 4 0 0 4 100.0 Bitter Aubergine 90 18 541 176 194 9.4 Onions 203 18 399 100 119 15.3 Ginger 291 88 0 0 88 100.0 Cabbage 1,582 344 2,277 502 846 40.7 Tomatoes 7,462 1,621 4,100 948 2,569 63.1 Spinnach 107 30 0 0 30 100.0 Carrot 286 51 286 143 194 26.3 Chillies 1,691 414 1,367 307 721 57.4 Amaranths 890 65 628 66 131 49.6 Pumpkins 92 13 579 65 78 17.3 Cucumber 0 0 273 90 90 0.0 Egg Plant 88 9 204 23 32 28.1 Water Mellon 227 137 214 78 215 63.6 CASH CROPS 166 17 1,075 448 465 3.6 Seaweed 23 2 0 0 2 100.0 Cotton 0 0 419 264 264 0.0 Tobacco 143 15 565 166 180 8.1 Jute 0 0 91 18 18 0.0 Total 351,782 351,391 268,745 429,566 0.0 % Area Planted in Short Rainy Season 7.1 & 7.2d TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Agriculture Households by Area Planted (ha) and crop for the agriculture year 2002/03- Short and Long Season, Tanga Region Crop Short Rainy Season Long Rainy Season Total Area Planted Short & Long Rainy Season Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 157 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,011 847 3,448 2,919 146,579 115,779 151,039 119,544 Korogwe 591 1,063 912 1,386 66,821 55,206 68,324 57,655 Muheza 320 273 2,675 1,830 77,000 55,842 79,995 57,945 Tanga 43 83 168 55 10,051 5,370 10,261 5,508 Pangani 424 510 287 244 9,651 8,409 10,361 9,162 Handeni 210 428 5,541 9,515 76,976 98,798 82,728 108,742 Kilindi 243 305 1,069 1,570 26,082 39,879 27,395 41,754 Total 2,843 3509.1 14,101 17,519 413,159 379,283 430,102 400,310 % 0.7 0.9 3.5 4.4 103.2 94.7 107.4 100.0 Total Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Planted Area Lushoto 28,758 25,274 5,361 3,389 4,607 2,649 112,313 88,233 119,544 Korogwe 9,005 7,108 4,652 3,922 1,199 793 53,467 45,831 57,655 Muheza 5,714 4,410 580 307 340 226 73,362 53,001 57,945 Tanga 1,504 747 364 184 104 29 8,289 4,548 5,508 Pangani 316 259 107 64 0 . 9,938 8,839 9,162 Handeni 3,199 6,104 1,035 2,090 192 350 78,301 100,197 108,742 Kilindi 488 951 1,405 2,231 49 20 25,453 38,552 41,754 Total 48,984 44,853 13,504 12,187 6,491 4,068 361,124 339,202 400,310 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 8,304 8,065 142,734 111,480 151,039 119,544 6.7 Korogwe 3,414 3,177 64,910 54,478 68,324 57,655 5.5 Muheza 493 480 79,502 57,465 79,995 57,945 0.8 Tanga 217 120 10,044 5,388 10,261 5,508 2.2 Pangani 253 276 10,109 8,886 10,361 9,162 3.0 Handeni 1,076 1,447 81,652 107,295 82,728 108,742 1.3 Kilindi 389 383 27,006 41,371 27,395 41,754 0.9 Total 14,145 13,947 415,958 386,363 430,102 400,310 3.5 % 3.3 3.5 96.7 96.5 100.0 100.0 3.5 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. 7.1 & 7.2e TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Means of Soil Preparation and District LONG & SHORT SEASON, Tanga District Soil Preparation y Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total 7.1 & 7.2f TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Fertiliser Use and District for the 2002/03 agriculture year - LONG & SHORT RAINY SEASON, Tanga District Fertilizer Use Mostly Farm Yard Mostly Compost Mostly Inorganic No Fertilizer Applied 7.1 & 7.2g TOTAL ANNUAL CROP AND VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Irrigation Use and District for the 2002/03 agriculture year - LONG District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 158 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 7,050 6,054 146,543 118,966 153,593 125,020 4.84 Korogwe 2,380 2,918 67,093 58,160 69,472 61,078 4.78 Muheza 413 259 81,395 69,210 81,808 69,468 0.37 Tanga 327 246 11,967 7,952 12,294 8,198 3.00 Pangani 380 581 10,173 9,678 10,554 10,260 5.66 Handeni 2,293 6,490 80,543 104,759 82,836 111,249 5.83 Kilindi 919 1,309 26,719 41,844 27,639 43,153 3.03 Total 13,762 17,857 424,433 410,568 438,195 428,425 Number of households is an over estimate due to the double counting of hopuseholds growing crops in both long and short seasons. To compare previous surveys use Number of Long Season planters only. % of Planted area using Herbicide Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,143 1,094 149,895 118,450 151,039 119,544 0.92 Korogwe 497 336 67,827 57,319 68,324 57,655 0.58 Muheza 226 345 79,769 57,599 79,995 57,945 0.60 Tanga 264 183 9,997 5,325 10,261 5,508 3.32 Pangani 11 21 10,350 9,141 10,361 9,162 0.23 Handeni 703 578 82,024 108,164 82,728 108,742 0.53 Kilindi 390 650 27,005 41,104 27,395 41,754 1.56 Total 3,235 3,207 426,867 397,103 430,102 400,310 0.80 % 1 1 99 99 100 100 7.1 & 7.2i TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Herbicide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season, Tanga. Total % of Planted area using Insecticide District Insecticide Use g Insecticide g Insecticide Total 7.1 & 7.2h TOTAL ANNUAL CROP & VEGETABLE PRODUCTION: Total Number of Agriculture Households and Planted Area by Insecticide Use and District for the 2002/03 agriculture year - Long & Short Rainy Season. District Herbicide Use Households Using Herbicide Households Not Using Herbicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 159 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 3,035 3,609 148,003 115,936 151,039 119,544 3.0 Korogwe 1,297 1,069 67,027 56,586 68,324 57,655 1.9 Muheza 349 202 79,646 57,743 79,995 57,945 0.3 Tanga 347 185 9,914 5,323 10,261 5,508 3.4 Pangani 156 338 10,206 8,824 10,361 9,162 3.7 Handeni 1,140 1,348 81,588 107,394 82,728 108,742 1.2 Kilindi 388 469 27,006 41,285 27,395 41,754 1.1 Total 6,713 7,220 423,390 393,090 430,102 400,310 1.8 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 21,528 19,826 129,510 99,718 151,039 119,544 16.58 Korogwe 13,961 15,465 54,362 42,190 68,324 57,655 26.82 Muheza 2,883 2,145 77,112 55,799 79,995 57,945 3.70 Tanga 1,554 1,048 8,706 4,461 10,261 5,508 19.02 Pangani 2,026 2,150 8,335 7,013 10,361 9,162 23.46 Handeni 6,421 9,090 76,307 99,652 82,728 108,742 8.36 Kilindi 1,108 2,365 26,287 39,388 27,395 41,754 5.66 Total 49,482 52,089 380,620 348,221 430,102 400,310 13.01 % 12 13 88 87 100 100 % of Planted area using Improved Seeds % of Planted area using Fungicide 7.1 & 7.2j ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT & LONG RAINYSEASON, Tanga Region 7.1 &7.2k ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and District During 2002/03 Crop Year - LONG & SHORT RAINY SEASON, Tanga Region District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total District Improved Seed Use Households Using Improved Seed Households Not Using Improved Seed Total Tanzania Agriculture Sample Census - 2003 Tanga 160 Appendix II 161 ANNUAL CROP & VEGETABLE PRODUCTION – SHORT RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 162 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 866 614 1,868 1,800 76,074 66,779 78,808 69,194 Korogwe 301 415 103 161 26,233 16,179 26,637 16,755 Muheza 236 162 1,194 716 35,007 23,185 36,437 24,062 Tanga 8 24 61 26 4,516 2,286 4,586 2,335 Pangani 132 140 176 137 4,323 3,625 4,631 3,902 Handeni 0 . 2,461 1,846 33,595 32,798 36,056 34,643 Kilindi 0 . 244 292 9,101 9,636 9,345 9,928 Total 1,544 1,355 6,107 4,978 188,850 154,487 196,502 160,820 % 1 1 3 3 96 96 100 100 Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Number of Households Planted Area Lushoto 15,223 15,178 3,327 2,118 3,031 1,684 57,227 50,214 78,808 69,194 Korogwe 2,789 1,508 2,302 1,642 709 482 20,837 13,124 26,637 16,755 Muheza 2,482 1,588 331 189 79 80 33,546 22,206 36,437 24,062 Tanga 701 366 73 21 42 12 3,770 1,936 4,586 2,335 Pangani 172 91 63 51 0 . 4,397 3,760 4,631 3,902 Handeni 1,493 1,290 203 261 96 116 34,264 32,975 36,056 34,643 Kilindi 98 69 387 254 49 10 8,811 9,595 9,345 9,928 Total 22,959 20,089 6,686 4,537 4,005 2,383 162,852 133,811 196,502 160,820 % 12 12 3 3 2 1 83 83 100 100 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 4,267 4,735 74,541 64,459 78,808 69,194 7 Korogwe 2,409 1,767 24,228 14,988 26,637 16,755 11 Muheza 336 296 36,101 23,767 36,437 24,062 1 Tanga 101 87 4,485 2,248 4,586 2,335 4 Pangani 135 88 4,496 3,814 4,631 3,902 2 Handeni 864 1,028 35,193 33,615 36,056 34,643 3 Kilindi 193 87 9,152 9,841 9,345 9,928 1 Total 8,306 8,088 188,196 152,732 196,502 160,820 5 % 4 5 96 95 100 100 Total hh figures are indicative as a household may use more than one type of Land preparation method for different crops District Irrigation Use Households Using Irrigation Households Not Using Irrigation Total % of area planted under irrigation in short rainy season 7.1c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region 7.1b ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fertilizer Use and District During 2002/03 Crop Year-SHORT RAINY SEASON, Tanga Region District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.1a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Households and Planted Area by Means Used for Soil Preparation and District - SHORT RAINY SEASON, Tanga Region. District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 163 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 2,437 1,675 76,371 67,518 78,808 69,194 Korogwe 794 739 25,844 16,016 26,637 16,755 Muheza 172 86 36,266 23,976 36,437 24,062 Tanga 261 179 4,324 2,156 4,586 2,335 Pangani 143 162 4,488 3,740 4,631 3,902 Handeni 1,057 1,944 34,999 32,699 36,056 34,643 Kilindi 242 191 9,103 9,737 9,345 9,928 Total 5,106 4,977 191,395 155,843 196,502 160,820 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 716 617 78,092 68,576 78,808 69,194 0.9 Korogwe 291 243 26,346 16,513 26,637 16,755 1.4 Muheza 167 155 36,270 23,908 36,437 24,062 0.6 Tanga 166 127 4,419 2,209 4,586 2,335 5.4 Pangani 0 . 4,631 3,902 4,631 3,902 - Handeni 324 196 35,733 34,447 36,056 34,643 0.6 Kilindi 147 89 9,198 9,839 9,345 9,928 0.9 Total 1,811 1,427 194,690 159,394 196,502 160,820 0.9 % 1 1 99 99 100 100 7.1e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON. District Herbicide Use % of Planted area using Herbicide Households Using Herbicide Households Not Using Herbicide Total 7.1d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Insecticide Use and District During 2002/03 Crop Year in SHORT RAINY SEASON. District Insecticide Use Households Using Insecticide Households Not Using Insecticide Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 164 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,878 2,327 76,930 66,867 78,808 69,194 3.4 Korogwe 497 486 26,140 16,270 26,637 16,755 2.9 Muheza 167 109 36,270 23,954 36,437 24,062 0.5 Tanga 228 129 4,358 2,206 4,586 2,335 5.5 Pangani 87 144 4,544 3,758 4,631 3,902 3.7 Handeni 745 693 35,312 33,950 36,056 34,643 2.0 Kilindi 193 125 9,152 9,803 9,345 9,928 1.3 Total 3,796 4,012 192,706 156,808 196,502 160,820 2.5 % 1.9 2.5 98.1 97.5 100.0 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 10,823 11,394 67,986 57,800 78,808 69,194 16 Korogwe 6,606 4,918 20,031 11,838 26,637 16,755 29 Muheza 1,758 1,106 34,679 22,956 36,437 24,062 5 Tanga 774 512 3,812 1,823 4,586 2,335 22 Pangani 1,063 983 3,569 2,919 4,631 3,902 25 Handeni 2,438 1,957 33,618 32,686 36,056 34,643 6 Kilindi 484 729 8,861 9,200 9,345 9,928 7 Total 23,945 21,599 172,556 139,221 196,502 160,820 13 % 12 13 88 87 100 100 District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.1g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year SHORT RAINY SEASON, Tanga Region District Fungicide Use % of Planted area using Fungicide Households Using Fungicide Households Not Using Fungicide Total 7.1f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year SHORT RAINY SEASON. Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 165 ANNUAL CROP & VEGETABLE PRODUCTION – LONG RAINY SEASON Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 166 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Lushoto 146 233 1,580 1,118 70,504 49,000 72,230 50,351 Korogwe 290 648 809 1,225 40,588 39,027 41,687 40,899 Muheza 84 112 1,481 1,114 41,993 32,657 43,558 33,883 Tanga 35 59 106 30 5,535 3,084 5,675 3,173 Pangani 291 369 111 106 5,328 4,785 5,730 5,260 Handeni 210 428 3,080 7,670 43,381 66,001 46,671 74,099 Kilindi 243 305 825 1,278 16,981 30,242 18,050 31,825 Total 1,299 2,154 7,993 12,541 224,309 224,795 233,601 239,490 % 1 1 3 5 96 94 100 100 No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area No. of H/hold Planted Area Lushoto 13,534 10,096 2,033 1,270 1,576 965 55,086 38,019 72,230 50,351 Korogwe 6,216 5,601 2,351 2,280 490 311 32,630 32,708 41,687 40,899 Muheza 3,232 2,822 249 119 261 147 39,816 30,795 43,558 33,883 Tanga 803 381 291 163 62 17 4,520 2,612 5,675 3,173 Pangani 144 168 44 13 0 . 5,542 5,079 5,730 5,260 Handeni 1,706 4,814 832 1,829 96 234 44,037 67,221 46,671 74,099 Kilindi 390 882 1,018 1,976 0 10 16,642 28,957 18,050 31,825 Total 26,025 24,764 6,818 7,650 2,485 1,684 198,272 205,392 233,601 239,490 No.of H/holds Planted Area No.of H/holds Planted Area No.of H/holds Planted Area Lushoto 4,037 3,330 68,193 47,021 72,230 50,351 6.6 Korogwe 1,004 1,410 40,682 39,489 41,687 40,899 3.4 Muheza 157 184 43,401 33,698 43,558 33,883 0.5 Tanga 116 33 5,559 3,141 5,675 3,173 1.0 Pangani 117 188 5,613 5,073 5,730 5,260 3.6 Handeni 212 418 46,459 73,680 46,671 74,099 0.6 Kilindi 195 296 17,854 31,530 18,050 31,825 0.9 Total 5,839 5,859 227,762 233,631 233,601 239,490 2.4 % 2 2 98 98 100 100 District Irrigation Use % of area planted under irrigation in long rainy season Households Using Irrigation Households Not Using Irrigation Total 7.2c ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Irrigation Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region 7.2b Number of Crop Growing Households and Planted Area By Fertilizer Use and District During the Long Rainy Season District Fertilizer Use Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total 7.2a ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area (ha) By Means Used for Soil Preparation and District During 2002/03 Crop Year-LONG RAINY SEASON, Tanga Region District Soil Preparation Mostly Tractor Ploughing Mostly Oxen Ploughing Mostly Hand Cultivation Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 167 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 4,613 4,378 70,172 51,448 74,784 55,826 Korogwe 1,586 2,179 41,249 42,143 42,835 44,323 Muheza 242 173 45,129 45,233 45,371 45,406 Tanga 65 66 7,643 5,796 7,708 5,863 Pangani 237 419 5,685 5,938 5,922 6,357 Handeni 1,236 4,546 45,544 72,059 46,779 76,606 Kilindi 678 1,118 17,616 32,107 18,294 33,225 Total 8,656 12,880 233,037 254,725 241,693 267,605 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 428 477 71,803 49,874 72,230 50,351 0.9 Korogwe 205 94 41,481 40,806 41,687 40,899 0.2 Muheza 59 191 43,499 33,692 43,558 33,883 0.6 Tanga 98 56 5,577 3,117 5,675 3,173 1.8 Pangani 11 21 5,719 5,239 5,730 5,260 - Handeni 380 382 46,292 73,717 46,671 74,099 0.5 Kilindi 243 561 17,806 31,265 18,050 31,825 1.8 Total 1,424 1,781 232,177 237,709 233,601 239,490 0.7 % 1 1 99 99 100 100 Number % Number % Lushoto 69,510 80 17,069 20 86,580 Korogwe 29,751 65 16,240 35 45,990 Muheza 41,149 84 8,045 16 49,195 Tanga 6,605 74 2,309 26 8,914 Pangani 4,977 70 2,151 30 7,128 Handeni 30,492 64 17,247 36 47,739 Kilindi 14,684 75 4,970 25 19,654 Total 197,168 74 68,030 26 265,198 District Insecticide Use g Insecticide District Herbicide Use Households Using Herbicide Households that Sold Produce Households that Did not Sell Produce Total Number of households % of Planted area using Herbicide Total 7.2d ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households & Planted Area By Insecticide Use and District - LONG RAINY SEASON 7.2e ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Herbicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region g Insecticide Total 7.2j: Number of Crops Producing Households Reporting Selling Agricultural Produce by District; 2002/03 Agricultural Year District Households Not Using Herbicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 168 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 1,157 1,282 71,073 49,069 72,230 50,351 2.5 Korogwe 800 583 40,887 40,316 41,687 40,899 1.4 Muheza 182 93 43,376 33,789 43,558 33,883 0.3 Tanga 119 56 5,556 3,117 5,675 3,173 1.8 Pangani 69 194 5,661 5,066 5,730 5,260 3.7 Handeni 395 654 46,276 73,444 46,671 74,099 0.9 Kilindi 195 344 17,855 31,481 18,050 31,825 1.1 Total 2,917 3,208 230,684 236,282 233,601 239,490 1.3 % 1.2 1.3 98.8 98.7 100.0 100.0 Number of Household Planted Area Number of Household Planted Area Number of Household Planted Area Lushoto 10,706 8,432 61,525 41,919 72,230 50,351 17 Korogwe 7,356 10,547 34,331 30,352 41,687 40,899 26 Muheza 1,124 1,039 42,433 32,844 43,558 33,883 3 Tanga 781 535 4,895 2,638 5,675 3,173 17 Pangani 964 1,166 4,766 4,094 5,730 5,260 22 Handeni 3,982 7,133 42,689 66,965 46,671 74,099 10 Kilindi 624 1,637 17,425 30,189 18,050 31,825 5 Total 25,537 30,490 208,064 209,000 233,601 239,490 13 % 11 13 89 87 100 100 District Fungicide Use Households Using Fungicide Households Not Using Fungicide Total District Improved Seed Use % of area planted using improved seed Households Using Improved Seed Households Not Using Improved Seed Total 7.2f ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Fungicide Use and District During 2002/03 Crop Year LONG RAINY SEASON, Tanga Region 7.2g ANNUAL CROP AND VEGETABLE PRODUCTION: Number of Crop Growing Households and Planted Area By Improved Seed Use and DistrictDuring 2002/03 Crop Year - LONG RAINY SEASON, Tanga Region % of Planted area using Fungicide Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 169 Number of House - holds Planted Area Number of House -holds Planted Area Number of House - holds Planted Area Numbe r of House - holds Planted Area Number of House - holds Planted Area Numbe r of House - holds Planted Area Number of House - holds Planted Area CEREALS 6,895 7,865 153,422 129,869 1,032 677 2,299 1,739 41,404 42,651 66 53 205,117 182,855 Maize 6,475 7,718 142,137 125,559 903 564 1,865 1,592 37,598 41,165 66 53 189,044 176,651 Paddy 420 147 10,700 4,046 129 113 434 147 3,675 1,459 0 . 15,357 5,913 Sorghum 0 . 44 15 0 . 0 . 22 5 0 . 66 19 Finger Millet 0 . 108 44 0 . 0 . 108 22 0 . 217 66 Wheat 0 . 433 205 0 . 0 . 0 . 0 . 433 205 ROOTS & TUBERS 0 . 23,431 7,311 59 12 0 . 4,435 1,309 0 . 27,925 8,632 Cassava 0 . 1,993 628 59 12 0 . 263 143 0 . 2,315 783 Sweet Potatoes 0 . 1,718 349 0 . 0 . 749 244 0 . 2,468 593 Irish Potatoes 0 . 19,351 6,283 0 . 0 . 3,063 806 0 . 22,414 7,089 Yams 0 . 0 . 0 . 0 . 213 80 0 . 213 80 Cocoyam 0 . 369 51 0 . 0 . 146 35 0 . 515 86 PULSES 1,544 719 77,819 31,433 571 183 535 124 20,137 9,883 0 . 100,606 42,342 Mung Beans 46 29 0 . 87 35 0 . 0 . 0 . 133 64 Beans 1,109 532 70,361 29,291 107 22 284 56 17,125 8,903 0 . 88,986 38,803 Cowpeas 388 159 5,409 1,650 140 61 165 42 2,624 810 0 . 8,727 2,720 Green Gram 0 . 2,049 493 237 66 87 26 388 171 0 . 2,760 755 OIL SEEDS & OIL NU 0 . 2,874 1,222 0 . 180 33 1,448 562 0 . 4,502 1,817 Sunflower 0 . 0 . 0 . 0 . 96 78 0 . 96 78 Simsim 0 . 942 570 0 . 90 18 131 141 0 . 1,163 729 Groundnuts 0 . 1,932 652 0 . 90 15 1,221 344 0 . 3,243 1,010 FRUITS & VEGETABL 0 . 8,509 1,995 21 2 0 . 2,526 525 33 3 11,089 2,525 Okra 0 . 160 19 21 2 0 . 39 5 0 . 220 26 Bitter Aubergine 0 . 239 38 0 . 0 . 302 138 0 . 541 176 Onions 0 . 300 80 0 . 0 . 99 20 0 . 399 100 Cabbage 0 . 1,963 429 0 . 0 . 315 73 0 . 2,277 502 Tomatoes 0 . 3,441 823 0 . 0 . 659 125 0 . 4,100 948 Carrot 0 . 140 121 0 . 0 . 146 22 0 . 286 143 Chillies 0 . 1,025 253 0 . 0 . 342 54 0 . 1,367 307 Amaranths 0 . 573 62 0 . 0 . 23 1 33 3 628 66 Pumpkins 0 . 119 5 0 . 0 . 460 59 0 . 579 65 Cucumber 0 . 174 70 0 . 0 . 99 20 0 . 273 90 Egg Plant 0 . 182 18 0 . 0 . 22 5 0 . 204 23 Water Mellon 0 . 193 76 0 . 0 . 21 2 0 . 214 78 CASH CROPS 0 . 813 416 0 . 0 . 262 32 0 . 1,075 448 Cotton 0 . 313 253 0 . 0 . 107 11 0 . 419 264 Tobacco 0 . 409 145 0 . 0 . 156 21 0 . 565 166 Jute 0 . 91 18 0 . 0 . 0 . 0 . 91 18 Total 8,438 8,584 266,868 172,247 1,684 875 3,014 1,896 70,212 54,961 98 56 350,314 238,619 % 4 72 0 1 23 0 100 7.2h: Planted Area and Number of Crop Growing Households During the Long Rainy Season by Method of Land Clearing and Crops; 2002/03 Agricultural Year Crop Land Clearing Method Mostly Bush Clearance Mostly Hand Slashing Mostly Tractor Slashing Mostly Burning Not cleared Other Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 170 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 77,511 35,639 21,772 0.611 34,582 15,479 8,971 0.580 51,118 30,743 0.601 Korogwe 24,375 12,945 4,224 0.326 40,827 33,425 11,484 0.344 46,369 15,709 0.339 Muheza 35,248 21,126 13,574 0.643 42,339 29,652 25,753 0.869 50,778 39,327 0.774 Tanga 3,744 1,774 811 0.457 4,310 2,171 946 0.436 3,946 1,757 0.445 Pangani 4,040 2,950 1,428 0.484 5,205 4,092 2,126 0.520 7,042 3,554 0.505 Handeni 32,034 26,149 14,467 0.553 46,454 69,539 50,471 0.726 95,688 64,938 0.679 Kilindi 9,201 9,460 5,635 0.596 16,053 23,076 11,940 0.517 32,536 17,575 0.540 Total 186,153 110,043 61,910 0.563 189,772 177,433 111,692 0.629 287,476 173,602 0.604 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1,650 557 1,094 1.963 994 374 263 0.703 931 1,356 1.457 Korogwe 2,102 972 2,226 2.290 4,039 1,686 1,178 0.699 2,659 3,405 1.281 Muheza 424 171 141 0.825 4,738 1,472 1,282 0.871 1,644 1,424 0.866 Tanga 0 . . 0.000 1,443 545 112 0.205 545 112 0.205 Pangani 23 5 12 2.470 1,156 495 224 0.452 500 235 0.471 Handeni 0 . . 0.000 2,781 1,245 361 0.290 1,245 361 0.290 Kilindi 48 29 15 0.494 291 113 52 0.463 142 67 0.470 Total 4,247 1,735 3,488 2.010 15,443 5,930 3,472 0.585 7,665 6,960 0.908 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 146 35 321 9.057 0 . . 0.000 35 321 9.057 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 33 14 6 0.445 14 6 0.445 Pangani 68 18 0 0.024 33 6 1 0.145 24 1 0.053 Handeni 107 43 16 0.371 0 . . 0.000 43 16 0.371 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 320 97 338 3.485 66 19 7 0.357 116 345 2.969 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 217 66 23 0.346 66 23 0.346 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 217 66 23 0.346 66 23 0.346 Long Rainy Season Total 7.2.1 Number of Agricultural Households, Area Planted (ha) and Quantity of Maize Harvested (tons) by Season and District;2002/03 Agricultural Year 7.2.2 Number of Agricultural Households, Area Planted (ha) and Quantity of Paddy Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season District Maize Short Rainy Season Long Rainy Season Total District Paddy 7.2.3 Number of Agricultural Households, Area Planted (ha) and Quantity of Sorghum Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Sorghum District 7.2.4 Number of Agricultural Households, Area Planted (ha) and Quantity of Fingermillet Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Fingermillet District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 171 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 433 205 57 0.280 205 57 0.280 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 433 205 57 0.280 205 57 0.280 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha)* Lushoto 3,066 862 1,273 1.477 22,490 5,595 8,549 1.581 6,457 9,822 1.566 Korogwe 593 216 96 0.443 10,005 3,804 4,388 3.439 4,020 4,484 3.046 Muheza 678 196 396 2.023 22,608 11,576 16,155 2.373 11,772 16,551 2.363 Tanga 0 0 . 0.000 5,479 2,730 5,041 2.648 2,730 5,041 2.648 Pangani 44 7 0 0.000 2,513 1,110 844 1.855 1,117 844 1.829 Handeni 726 440 356 0.809 5,628 2,722 4,695 3.519 3,162 5,051 2.847 Kilindi 49 5 10 1.976 2,434 1,470 3,697 3.068 1,475 3,707 3.064 Total 5,155 1,725 2,131 1.235 71,157 29,007 43,369 2.358 30,732 45,500 2.264 *The yield is based on physical area harvested and not the physical area planted on the above table No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1154 223 372 1.673 1,154 311 122 0.392 533 494 0.927 Korogwe 0 . . 0.000 209 32 21 0.657 32 21 0.657 Muheza 259 26 23 0.859 91 18 12 0.642 45 34 0.769 Tanga 134 39 65 1.665 187 69 145 2.096 108 210 1.940 Pangani 22 9 2 0.247 103 18 25 1.401 27 27 1.009 Handeni 422 171 55 0.322 431 76 16 0.213 247 71 0.288 Kilindi 49 12 20 1.647 292 69 124 1.801 81 144 1.778 Total 2041 480 537 1.119 2,468 593 465 0.784 1,073 1,002 0.934 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 29593 8270 11875 1.436 22,184 7,039 8,662 1.231 15,309 20,537 1.341 Korogwe 194 44 98 2.227 194 46 98 2.122 90 195 2.173 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 37 4 4 0.988 4 4 0.988 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 29786 8314 11973 1.440 22,414 7,089 8,763 1.236 15,402 20,736 1.346 7.2.5 Number of Agricultural Households, Area Planted (ha) and Quantity of Wheat Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Wheat District 7.2.6 Number of Agricultural Households, Area Planted (ha) and Quantity of Cassava Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cassava 7.2.7 Number of Agricultural Households, Area Planted (ha) and Quantity of Sweet potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sweet potatoes 7.2.8 Number of Agricultural Households, Area Planted (ha) and Quantity of Irish potatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Irish potatoes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 172 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 213 51 0 0.000 213 80 55 0.684 132 55 0.417 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 213 51 0 0.000 213 80 55 0.684 132 55 0.417 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 437 88 127 1.444 437 78 101 1.287 166 228 1.370 Korogwe 213 22 365 16.916 0 . . 0.000 22 365 16.916 Muheza 435 79 82 1.038 79 8 0 0.000 87 82 0.944 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 1,085 188 574 3.045 515 86 101 1.169 275 675 2.455 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 87 35 52 1.482 35 52 1.482 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 46 29 36 1.265 29 36 1.265 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 133 64 88 1.385 64 88 1.385 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 68309 21587 7885 0.365 63,635 25,394 9,396 0.370 46,981 17,280 0.368 Korogwe 6409 1850 663 0.358 11,917 4,129 2,711 0.656 5,979 3,374 0.564 Muheza 1977 499 119 0.239 3,478 875 424 0.485 1,374 543 0.396 Tanga 31 6 1 0.084 31 6 0 0.079 13 1 0.082 Pangani 22 4 1 0.198 0 . . 0.000 4 1 0.198 Handeni 312 170 22 0.129 1,076 261 40 0.154 432 62 0.144 Kilindi 97 69 8 0.120 8,898 8,176 2,753 0.337 8,245 2,761 0.335 Total 77157 24185 8699 0.360 89,035 38,843 15,325 0.395 63,028 24,023 0.381 7.2.9 Number of Agricultural Households, Area Planted (ha) and Quantity of Yams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Yams 7.210 Number of Agricultural Households, Area Planted (ha) and Quantity of Cocoyams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cocoyams 7.2.11 Number of Agricultural Households, Area Planted (ha) and Quantity of Mung beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Mung beans 7.2.12 Number of Agricultural Households, Area Planted (ha) and Quantity of Beans Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Beans Tanzania Agriculture Sample Census-2003 Tanga Appendix II 173 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.00 0 . . 0.000 0 0 0.000 Korogwe 799 141 12 0.083 614 154 12 0.080 295 24 0.081 Muheza 4,138 1,174 306 0.261 2,996 842 176 0.209 2,016 482 0.239 Tanga 1,137 239 58 0.245 705 144 19 0.129 383 77 0.201 Pangani 1,812 633 115 0.181 1,239 365 52 0.144 998 167 0.167 Handeni 16,732 6,823 1,571 0.230 3,087 1,159 227 0.196 7,982 1,798 0.225 Kilindi 1,122 266 63 0.238 194 66 12 0.183 333 76 0.227 Total 25,741 9,276 2,125 0.229 8,833 2,731 499 0.183 12,007 2,624 0.219 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 139 56 83 1.482 56 83 1.482 Korogwe 103 42 10 0.247 107 22 1 0.035 64 11 0.174 Muheza 1,064 226 74 0.329 1,579 355 69 0.194 582 143 0.246 Tanga 561 97 13 0.130 264 52 10 0.186 149 22 0.149 Pangani 349 123 47 0.384 190 53 15 0.282 176 62 0.354 Handeni 1,721 620 143 0.231 433 197 68 0.343 817 211 0.258 Kilindi 0 . . 0.000 49 20 3 0.150 20 3 0.150 Total 3,798 1,108 288 0.260 2,760 755 248 0.329 1,863 536 0.288 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 22 2 0 0.198 0 . . 0.000 2 0 0.198 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 22 2 0 0.198 0 . . 0.000 2 0 0.198 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 23 2 1 0.296 0 . . 0.000 2 1 0.296 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 23 2 1 0.296 0 . . 0.000 2 1 0.296 7.2.13 Number of Agricultural Households, Area Planted (ha) and Quantity of Cowpeas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cowpeas 7.2.14 Number of Agricultural Households, Area Planted (ha) and Quantity of Green grams Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Green gram 7.2.15 Number of Agricultural Households, Area Planted (ha) and Quantity of Chick peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Chick peas 7.2.16 Number of Agricultural Households, Area Planted (ha) and Quantity of Bambaranuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bambaranuts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 174 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 140 28 84 2.964 0 . . 0.000 28 84 2.964 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 108 22 24 1.112 0 . . 0.000 22 24 1.112 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 248 50 109 2.159 0 . . 0.000 50 109 2.159 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 96 78 35 0.451 78 35 0.451 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 96 78 35 0.451 78 35 0.451 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 90 18 12 0.642 18 12 0.642 Tanga 26 21 2 0.099 64 18 6 0.326 39 8 0.203 Pangani 67 27 8 0.279 45 27 3 0.124 54 11 0.201 Handeni 108 44 16 0.371 867 636 246 0.387 680 262 0.386 Kilindi 0 . . 0.000 97 30 4 0.148 30 4 0.148 Total 202 92 26 0.281 1,163 729 271 0.372 822 297 0.362 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 206 53 3 0.060 903 306 640 2.092 359 643 1.790 Muheza 1657 448 166 0.370 1,289 380 158 0.416 828 324 0.391 Tanga 254 52 34 0.666 117 52 29 0.547 104 63 0.606 Pangani 70 38 9 0.235 143 54 16 0.300 93 25 0.273 Handeni 108 22 0 0.000 753 206 104 0.506 228 104 0.457 Kilindi 0 . . 0.000 144 34 14 0.425 34 14 0.425 Total 2296 613 212 0.346 3,350 1,032 961 0.932 1,645 1,174 0.714 7.2.17 Number of Agricultural Households, Area Planted (ha) and Quantity of Field peas Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Field Peas 7.2.18 Number of Agricultural Households, Area Planted (ha) and Quantity of Sunflower Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Sunflower 7.2.19 Number of Agricultural Households, Area Planted (ha) and Quantity of Simsim Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Simsim 7.2.20 Number of Agricultural Households, Area Planted (ha) and Quantity of Groundnuts Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Groundnuts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 175 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 48 20 10 0.494 0 . . 0.000 20 10 0.494 Total 48 20 10 0.494 0 . . 0.000 20 10 0.494 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 56 9 13 1.422 147 20 14 0.683 29 26 0.913 Pangani 0 . . 0.000 73 6 3 0.458 6 3 0.458 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 56 9 13 1.422 220 26 17 0.629 35 29 0.831 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 14 4 2 0.529 0 . . 0.000 4 2 0.529 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 14 4 2 0.529 0 . . 0.000 4 2 0.529 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 90 18 216 11.856 270 36 118 3.236 55 334 6.109 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 59 10 8 0.813 10 8 0.813 Handeni 0 . . 0.000 212 129 170 1.317 129 170 1.317 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 90 18 216 11.856 541 176 296 1.685 194 512 2.641 7.2.21 Number of Agricultural Households, Area Planted (ha) and Quantity of Castor oil Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Castor oil District 7.2.22 Number of Agricultural Households, Area Planted (ha) and Quantity of Okra Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Okra District 7.2.23 Number of Agricultural Households, Area Planted (ha) and Quantity of Radish Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total Radish District 7.2.24 Number of Agricultural Households, Area Planted (ha) and Quantity of Bitter Aubergine Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Bitter Aubergine Tanzania Agriculture Sample Census-2003 Tanga Appendix II 176 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 146 59 146 2.470 59 146 2.470 Korogwe 107 11 11 0.988 186 38 126 3.359 48 137 2.827 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 19 2 4 1.976 2 4 1.976 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 95 7 74 10.246 49 2 4 1.902 9 78 8.448 Total 203 18 85 4.681 399 100 279 2.782 119 364 3.072 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 291 88 66 0.746 0 . . 0.000 88 66 0.746 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 291 88 66 0.746 0 . . 0.000 88 66 0.746 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 1285 302 1349 4.475 2,013 449 2,013 4.481 751 3,362 4.479 Korogwe 87 18 . 0.000 87 18 0 0.000 35 0 0.000 Muheza 92 9 20 2.134 0 . . 0.000 9 20 2.134 Tanga 23 1 2 1.976 23 1 1 1.482 2 3 1.729 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 106 32 42 1.317 32 42 1.317 Kilindi 95 15 39 2.662 49 2 5 2.717 17 44 2.669 Total 1582 344 1410 4.099 2,277 502 2,062 4.109 846 3,472 4.105 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 5062 1176 6116 5.199 1,742 504 2,569 5.099 1,680 8,685 5.169 Korogwe 1137 240 433 1.805 1,000 216 389 1.800 456 822 1.803 Muheza 430 47 105 2.221 343 60 80 1.319 108 184 1.714 Tanga 190 48 121 2.516 148 15 17 1.148 63 139 2.192 Pangani 131 44 98 2.247 265 49 61 1.247 92 159 1.720 Handeni 323 27 21 0.774 217 22 70 3.211 49 91 1.866 Kilindi 191 38 326 8.483 387 82 446 5.435 120 772 6.406 Total 7462 1621 7220 4.455 4,100 948 3,632 3.832 2,569 10,852 4.225 7.2.25 Number of Agricultural Households, Area Planted (ha) and Quantity of Onions Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Onions 7.2.26 Number of Agricultural Households, Area Planted (ha) and Quantity of Ginger Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Ginger 7.2.27 Number of Agricultural Households, Area Planted (ha) and Quantity of Cabbage Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cabbage 7.2.28 Number of Agricultural Households, Area Planted (ha) and Quantity of Tomatoes Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tomatoes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 177 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 106 17 0 0.000 17 0 0.000 Muheza 0 . . 0.000 86 5 0 0.000 5 0 0.000 Tanga 21 2 6 2.964 54 2 2 0.874 4 8 1.886 Pangani 22 9 223 24.700 22 9 0 0.000 18 223 12.350 Handeni 0 . . 0.000 310 31 29 0.916 31 29 0.916 Kilindi 49 2 4 1.853 0 . . 0.000 2 4 1.853 Total 92 13 234 17.324 579 65 31 0.475 78 265 3.384 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 273 90 668 7.390 90 668 7.390 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 273 90 668 7.390 90 668 7.390 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 96.849 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 79 8 8 1.037 8 8 1.037 Tanga 66 7 10 0.000 66 7 8 1.171 13 17 1.307 Pangani 22 2 1 24.037 59 8 4 0.425 11 5 0.461 Handeni 0 . . 106.178 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 88 9 11 227.064 204 23 20 0.856 32 31 0.960 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 97 10 0 0.000 193 76 687 9.018 86 687 7.990 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 21 2 12 5.928 2 12 5.928 Pangani 24 19 29 1.482 0 . . 0.000 19 29 1.482 Handeni 106 107 53 0.494 0 . . 0.000 107 53 0.494 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 227 137 82 0.599 214 78 699 8.936 215 781 3.634 7.2.29 Number of Agricultural Households, Area Planted (ha) and Quantity of Pumpkins Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Pumpkins 7.2.30 Number of Agricultural Households, Area Planted (ha) and Quantity of Cucumber Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cucumber 7.2.31 Number of Agricultural Households, Area Planted (ha) and Quantity of Eggplant Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Eggplant 7.2.32 Number of Agricultural Households, Area Planted (ha) and Quantity of Water Mellon Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Water Mellon Tanzania Agriculture Sample Census-2003 Tanga Appendix II 178 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 23 2 7 2.964 0 . . 0.000 2 7 2.964 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 23 2 7 2.964 0 . . 0.000 2 7 2.964 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 0 . . 0.000 0 0 0.000 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 419 264 165 0.625 264 165 0.625 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 419 264 165 0.625 264 165 0.625 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 143 15 3 0.000 0 . . 0.000 15 3 0.198 Korogwe 0 . . 96.849 214 27 15 0.549 27 15 0.549 Muheza 0 . . 0.000 183 46 42 0.909 46 42 0.909 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 24.037 22 9 0 0.000 9 0 0.000 Handeni 0 . . 106.178 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 146 83 13 0.157 83 13 0.157 Total 143 15 3 227.064 565 166 70 0.422 180 73 0.404 No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) No. of H/Holds Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Planted Area (ha) Quantity Harvested (tons) Yield (tons/ha) Lushoto 0 . . 0.000 0 . . 0.000 0 0 0.000 Korogwe 0 . . 0.000 0 . . 0.000 0 0 0.000 Muheza 0 . . 0.000 91 18 12 0.642 18 12 0.642 Tanga 0 . . 0.000 0 . . 0.000 0 0 0.000 Pangani 0 . . 0.000 0 . . 0.000 0 0 0.000 Handeni 0 . . 0.000 0 . . 0.000 0 0 0.000 Kilindi 0 . . 0.000 0 . . 0.000 0 0 0.000 Total 0 . . 0.000 91 18 12 0.642 18 12 0.642 7.2.33 Number of Agricultural Households, Area Planted (ha) and Quantity of Seaweed Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Seaweed 7.2.34 Number of Agricultural Households, Area Planted (ha) and Quantity of Cotton Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Cotton 7.2.35 Number of Agricultural Households, Area Planted (ha) and Quantity of Tobacco Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Tobacco 7.2.36 Number of Agricultural Households, Area Planted (ha) and Quantity of Jute Harvested (tons) by Season and District;2002/03 Agricultural Year Short Rainy Season Long Rainy Season Total District Jute Tanzania Agriculture Sample Census-2003 Tanga Appendix II 179 PERMANENT CROPS Tanzania Agriculture Sample Census-2003 Tanga Appendix II 180 Area planted(Ha) Area Harvested (ha) Quantity Harvested (tons) Yield (Kgs/ha) Cassava 5,500.3 5,314 8,519.17 1603 Coconut 72.4 72 85.96 1187 Cashewnut 11.1 11 0.00 0 Coffee 477 Tea 2338 Wattle 147.8 0 0.00 0 Sugarcane 686.1 392 9,924.73 25340 Cardamon 115.3 115 25.83 224 Jack Fruit 0.0 . 67.75 0 Mpesheni 0.0 . 35.74 0 Banana 1,750.7 1,096 3,977.66 3630 Avocado 0.0 . 34.97 0 Mango 0.0 . 211.10 0 Pawpaw 0.0 . 26.07 0 Pineapple 0.0 . 0.73 0 Orange 4.3 6 14.47 2470 Mandarine/Tangerine 0.0 . 14.54 0 Plums 29.2 29 494.52 16913 Apples 0.0 6 849.71 146796 Pears 146.7 93 62,845.52 672846 Pitches 0.0 . 8.61 0 Lime/Lemon 0.0 0 0.00 0 Total 12,308.9 10,623 90,879.21 8555 Cassava 3,449.3 921 4,166.31 4525 Star Fruit 0.7 0 133.45 0 Coconut 1,682.1 539 3,912.58 7254 Cashewnut 578.2 73 110.94 1511 Coffee 453.5 2,878 34.72 12 Tea 455.3 338 1,148.74 3402 Kapok 20.9 21 0.00 0 Sugarcane 564.5 2,983 5,566.85 1866 Cardamon 1,231.5 721 111.72 155 Mshelisheli 0.1 0 0.00 0 Jack Fruit 262.1 127 2,321.44 18344 Banana 2,069.1 1,416 10,409.51 7353 Avocado 38.0 34 2,723.65 79218 Mango 1,487.0 1,350 13,879.09 10284 Pineapple 0.0 . 7.99 0 Orange 404.2 68 499.57 7379 Mandarine/Tangerine 10.8 0 4.26 0 Guava 1.0 0 31.96 0 Lime/Lemon 97.9 0 31.04 0 Total 12,806.1 11,468 45,093.82 3932 7.3 Production of Permanent Crops by crop type and Region - Tanga Lushoto Korogwe Tanzania Agriculture Sample Census-2003 Tanga Appendix II 181 Black Pepper 1,520.6 470 686.52 1460 Cassava 11,523.5 6,757 16,137.28 2388 Star Fruit 35.8 36 13.25 371 Palm Oil 18.3 18 9.02 494 Coconut 9,380.0 4,722 9,349.80 1980 Cashewnut 4,599.6 3,527 2,361.91 670 Coffee 47.4 0 2.42 0 Tea 339.9 340 1,655.56 4871 Cocoa 306.2 312 232.55 746 Sugarcane 407.6 410 12,877.44 31446 Cardamon 1,487.8 1,273 197.07 155 Tamarin 47.4 47 4.50 95 Cinamon 105.4 32 122.00 3793 Cloves 361.5 74 351.76 4755 Jack Fruit 260.3 245 4,194.57 17119 Mpesheni 0.0 . 0.00 0 Banana 2,280.9 1,930 11,511.85 5966 Avocado 32.7 16 183.73 11197 Mango 145.4 153 4,309.18 28151 Pawpaw 110.3 117 196.51 1680 Pineapple 188.6 514 242.01 470 Orange 6,432.8 3,993 45,425.51 11376 Grape Fruit 35.7 36 81.06 2268 Mandarine/Tangerine 0.0 . 46.53 0 Guava 0.0 . 87.27 0 Pitches 15.8 . 3.12 0 Lime/Lemon 103.0 95 320.52 3391 Total 39,786.4 25,117 110,602.95 4404 Sour Soup 0.0 . 0.57 0 Cassava 2,689.4 1,863 5,025.41 2698 Pigeon Pea 0.0 0 0.00 0 Star Fruit 0.0 . 83.29 0 Coconut 964.6 837 3,171.02 3789 Cashewnut 949.7 23 288.73 12310 Sugarcane 23.8 24 139.67 5871 Mshelisheli 0.0 . 0.68 0 Jack Fruit 0.0 0 103.03 0 Banana 67.6 34 612.56 18032 Avocado 0.0 . 71.76 0 Mango 6.2 6 2,498.04 408339 Pawpaw 0.0 . 125.02 0 Pineapple 0.0 0 69.82 0 Orange 63.3 49 1,741.18 35517 Mandarine/Tangerine 0.0 0 23.02 0 Guava 0.0 . 1.86 0 Lime/Lemon 1.1 1 125.83 118823 Total 4,765.7 2,837 14,081.49 4964 Muheza Tanga cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 182 Cassava 1,097.1 442 843.85 1910 Pigeon Pea 44.2 18 15.87 883 Star Fruit 4.3 4 107.09 25001 Palm Oil 0.0 . 0.14 0 Coconut 2,417.8 1,043 7,508.51 7198 Cashewnut 1,766.1 1,029 1,795.16 1745 Sugarcane 6.8 7 46.90 6918 Jack Fruit 2.2 0 313.66 0 Mpesheni 3.3 . 0.90 0 Banana 151.7 82 624.67 7609 Mango 38.4 0 739.18 0 Pawpaw 0.0 . 6.70 0 Pineapple 14.6 18 9.16 504 Orange 157.7 443 1,833.55 4139 Mandarine/Tangerine 0.0 . 3.56 0 Guava 0.0 . 44.66 0 Lime/Lemon 16.2 0 156.35 0 Durian 0.0 . 55.35 0 Total 5,720.5 3,086 14,105.26 4571 Sour Soup 64.5 21 106.18 4940 Cassava 2,565.3 1,177 4,564.91 3878 Pigeon Pea 21.8 22 8.09 371 Coconut 248.1 315 2,238.68 7103 Cashewnut 0.0 0 23.32 0 Kapok 4.4 4 243.66 55575 Sugarcane 471.9 205 5,320.73 25948 Jack Fruit 904.0 496 3,191.32 6428 Mpesheni 8.5 . 361.00 0 Banana 1,143.1 670 4,587.48 6852 Mango 1,271.2 911 9,151.86 10051 Pawpaw 21.5 19 310.13 15989 Orange 2,200.7 1,278 14,980.37 11725 Lime/Lemon 0.0 . 0.00 0 Total 8,925.1 5,119 45,087.73 8809 Cassava 1,399.4 1,134 3,660.84 3229 Pigeon Pea 2,417.4 1,490 450.05 302 Malay Apple 0.0 . 81.29 0 Coconut 0.0 39 62.01 1582 Sugarcane 195.1 196 5,810.68 29632 Cardamon 117.6 118 10.04 85 Cinamon 0.2 0 0.73 0 Jack Fruit 118.9 40 366.43 9265 Banana 662.1 181 2,401.84 13259 Avocado 0.0 . 0.59 0 Mango 1,319.9 332 4,852.79 14607 Pawpaw 0.0 . 0.34 0 Orange 79.3 118 715.46 6086 Mandarine/Tangerine 0.1 0 0.29 0 Guava 4.0 . 4.36 0 Total 6,313.9 3,647 18,417.71 5050 Kilindi Pangani Handeni cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 183 Sour Soup 64.5 21 106.75 4966 Black Pepper 1,520.6 470 686.52 1460 Cassava 28,224.4 17,607 42,917.77 2438 Pigeon Pea 2,483.5 1,530 474.01 310 Malay Apple 0.0 . 81.29 0 Star Fruit 40.7 40 337.08 8417 Palm Oil 18.3 18 9.16 502 Coconut 14,765.1 7,568 26,328.55 3479 Cashewnut 7,904.7 4,664 4,580.07 982 Coffee 3,199.5 5,250 1,168.37 223 Tea 1,941.3 1,794 5,415.18 3018 Cocoa 306.2 312 232.55 746 Wattle 147.8 0 0.00 0 Kapok 25.3 25 243.66 9642 Sugarcane 2,356.0 4,216 39,687.01 9414 Cardamon 2,952.1 2,227 344.66 155 Tamarin 47.4 47 4.50 95 Cinamon 105.6 32 122.74 3815 Cloves 361.5 74 351.76 4755 Mshelisheli 0.1 0 0.68 0 Jack Fruit 1,547.3 908 10,558.20 11633 Mpesheni 11.8 . 397.65 0 Banana 8,125.1 5,408 34,125.57 6311 Avocado 70.7 51 3,014.69 59356 Mango 4,268.1 2,751 35,641.24 12953 Pawpaw 131.9 136 664.78 4874 Pineapple 203.2 533 329.70 619 Orange 9,342.3 5,954 65,210.11 10952 Grape Fruit 35.7 36 81.06 2268 Mandarine/Tangerine 10.9 0 92.20 0 Guava 4.9 0 170.10 0 Plums 29.2 29 494.52 16913 Apples 0.0 6 849.71 146796 Pears 146.7 93 62,845.52 672846 Pitches 15.8 . 11.73 0 Lime/Lemon 218.2 96 633.74 6631 Durian 0.0 . 55.35 0 Total 90,626.6 61,896 338,268.16 5465 Total cont… Production of Permanent Crops by crop type and Region - Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 184 cont… Area Planted by crop type - Tanga Region Crop Area planted % Coconut 14,765.1 23.7 Orange 9,342.3 15.0 Banana 8,125.1 13.0 Cashewnut 7,904.7 12.7 Mango 4,268.1 6.8 Coffee 3,199.5 5.1 Cardamon 2,952.1 4.7 Pigeon Pea 2,483.5 4.0 Sugarcane 2,356.0 3.8 Tea 1,941.3 3.1 Jack Fruit 1,547.3 2.5 Black Pepper 1,520.6 2.4 Cloves 361.5 0.6 Cocoa 306.2 0.5 Lime/Lemon 218.2 0.3 Pineapple 203.2 0.3 Wattle 147.8 0.2 Pears 146.7 0.2 Pawpaw 131.9 0.2 Cinamon 105.6 0.2 Avocado 70.7 0.1 Sour Soup 64.5 0.1 Tamarin 47.4 0.1 Star Fruit 40.7 0.1 Grape Fruit 35.7 0.1 Plums 29.2 0.0 Kapok 25.3 0.0 Palm Oil 18.3 0.0 Pitches 15.8 0.0 Mpesheni 11.8 0.0 Mandarine/Tangerine 10.9 0.0 Guava 4.9 0.0 Mshelisheli 0.1 0.0 Malay Apple 0.0 0.0 Apples 0.0 0.0 Durian 0.0 0.0 Total 62,402.2 100.0 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 185 7.4 Total Area Planted with Coconut by District - Tanga Region 7.5 Total Area Planted with Oranges by District - Tanga Region District Area planted with coconuts Total Area planted (ha) % of Total Area Planted hh with coconuts Average Planted Area per Household District Area planted with oranges(Ha) Total Area planted (ha) % of Total Area Planted hh with oranges Average Planted Area per Household Muheza 9,380.0 69,468 63.5 16,250 0.58 Muheza 6,432.8 69,468 68.86 10,742 0.60 Pangani 2,417.8 111,307 16.4 3,525 0.69 Handeni 2,200.7 111,307 23.56 7,449 0.30 Korogwe 1,682.1 0.38 Korogwe 404.2 61,104 4.33 1,346 0.30 Tanga 964.6 0.22 Pangani 157.7 10,260 1.69 1,501 0.11 Handeni 248.1 43,153 1.7 3,402 0.07 Kilindi 79.3 43,153 0.85 1,122 0.07 Lushoto 72.4 8,198 0.5 412 0.18 Tanga 63.3 8,198 0.68 1,662 0.04 Kilindi 0.0 125,045 0.0 341 0.00 Lushoto 4.3 125,045 0.05 145 0.03 Total 14,765.1 357,171 100.0 32,814 0.45 Total 9,342.3 428,535 100.00 23,967 0.39 7.6 Total Area Planted with Banana by District - Tanga Region 7.7 Total Area Planted with Cashewnuts by District - Tanga Region District Area planted with banana(Ha) Total Area planted (ha) % of Total Area Planted hh with bananas Average Planted Area per Household District Area planted with cashewnuts(Ha ) Total Area planted (ha) % of Total Area Planted hh with cashewnuts Average Planted Area per Household Muheza 2,280.9 69,468 0.53 14,380 0.16 Pangani 4,599.6 69,468 3031.51 8,508 0.54 Korogwe 2,069.1 61,104 0.48 10,403 0.20 Tanga 1,766.1 10,260 1164.03 2,042 0.87 Lushoto 1,750.7 125,045 0.41 26,066 0.07 Muheza 949.7 8,198 625.93 2,213 0.43 Handeni 1,143.1 111,307 0.27 5,325 0.21 Korogwe 578.2 61,104 381.06 2,350 0.25 Kilindi 662.1 43,153 0.15 2,966 0.22 Lushoto 11.1 125,045 7.29 427 0.03 Pangani 151.7 10,260 0.04 1,133 0.13 Handeni 0.0 111,307 0.00 534 0.00 Tanga 67.6 8,198 0.02 1,193 0.06 Kilindi 0.0 43,153 0.00 0 0.00 Total 8,125.1 428,535 1.90 61,464 0.13 Total 7,904.7 428,535 5209.82 16,074 0.49 COCONUTS Oranges CASHEWNUTS Banana Tanzania Agriculture Sample Census-2003 Tanga Appendix II 186 7.8 Production of Permanent Planted Crops with Fertiliser by Fertiliser Use - Tanga Region Mostly Farm Yard Manure Mostly Compost Mostly Inorganic Fertilizer No Fertilizer Applied Total Apples 1,005 0 0 2,153 3,159 Avocado 0 180 0 3,235 3,415 Banana 6,551 1,047 0 53,040 60,637 Black Pepper 0 86 0 3,434 3,520 Cardamon 214 173 0 7,207 7,594 Cashewnut 547 0 0 15,118 15,665 Cinamon 92 92 0 1,763 1,946 Cloves 92 178 0 1,809 2,079 Cocoa 0 0 0 249 249 Coconut 1,202 183 101 30,572 32,058 Coffee 2,838 146 0 8,051 11,035 Durian 0 22 0 0 22 Grape Fruit 0 0 0 90 90 Guava 97 0 0 561 658 Jack Fruit 106 86 0 13,434 13,626 Kapok 0 0 0 211 211 Lime/Lemon 314 0 0 3,872 4,185 Malay Apple 0 0 0 98 98 Mandarine/Tangerine 0 0 0 766 766 Mango 616 1,294 49 30,404 32,363 Mpesheni 143 0 0 207 350 Mshelisheli 23 0 0 203 226 Orange 826 447 32 21,631 22,935 Palm Oil 0 0 0 113 113 Pawpaw 168 0 0 2,266 2,434 Pears 578 584 0 6,349 7,511 Pigeon Pea 0 0 0 1,873 1,873 Pineapple 88 0 0 1,896 1,984 Pitches 143 0 0 1,234 1,377 Plums 143 0 0 873 1,016 Plums 143 0 0 873 1,016 Sour Soup 23 0 0 106 129 Star Fruit 0 0 0 357 357 Sugarcane 401 476 146 11,971 12,993 Tamarin 0 0 0 90 90 Tea 0 0 247 4,467 4,714 Wattle 0 0 0 730 730 Total 17,668 5,690 606 297,600 321,564 Fertilizer Use Tanzania Agriculture Sample Census-2003 Tanga Appendix II 187 7.9 Production of Permanent Planted Crops with Fertiliser by Farm Yard Manure - Tanga Region Mostly Farm Yard Manure Total % Mpesheni 143 350 40.8 Apples 1,005 3,159 31.8 Coffee 2,838 11,035 25.7 Sour Soup 23 129 17.6 Guava 97 658 14.7 Plums 143 1,016 14.1 Plums 143 1,016 14.1 Banana 6,551 60,637 10.8 Pitches 143 1,377 10.4 Mshelisheli 23 226 10.1 Pears 578 7,511 7.7 Lime/Lemon 314 4,185 7.5 Pawpaw 168 2,434 6.9 Cinamon 92 1,946 4.7 Pineapple 88 1,984 4.5 Cloves 92 2,079 4.4 Coconut 1,202 32,058 3.8 Orange 826 22,935 3.6 Cashewnut 547 15,665 3.5 Sugarcane 401 12,993 3.1 Cardamon 214 7,594 2.8 Mango 616 32,363 1.9 Jack Fruit 106 13,626 0.8 Avocado 0 3,415 0.0 Black Pepper 0 3,520 0.0 Cocoa 0 249 0.0 Durian 0 22 0.0 Grape Fruit 0 90 0.0 Kapok 0 211 0.0 Malay Apple 0 98 0.0 Mandarine/Tangerine 0 766 0.0 Palm Oil 0 113 0.0 Pigeon Pea 0 1,873 0.0 Star Fruit 0 357 0.0 Tamarin 0 90 0.0 Tea 0 4,714 0.0 Wattle 0 730 0.0 Total 16,353 253,227 6.5 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 188 7.10 Production of Permanent Planted Crops with Fertiliser by Inorganic Fertiliser - Tanga Region Mostly Inorganic Fertilizer Total % Tea 247 4,714 5.25 Sugarcane 146 12,993 1.12 Coconut 101 32,058 0.32 Mango 49 32,363 0.15 Orange 32 22,935 0.14 Apples 0 3,159 0 Avocado 0 3,415 0 Banana 0 60,637 0 Black Pepper 0 3,520 0 Cardamon 0 7,594 0 Cashewnut 0 15,665 0 Cinamon 0 1,946 0 Cloves 0 2,079 0 Cocoa 0 249 0 Coffee 0 11,035 0 Durian 0 22 0 Grape Fruit 0 90 0 Guava 0 658 0 Jack Fruit 0 13,626 0 Kapok 0 211 0 Lime/Lemon 0 4,185 0 Malay Apple 0 98 0 Mandarine/Tangerine 0 766 0 Mpesheni 0 350 0 Mshelisheli 0 226 0 Palm Oil 0 113 0 Pawpaw 0 2,434 0 Pears 0 7,511 0 Pigeon Pea 0 1,873 0 Pineapple 0 1,984 0 Pitches 0 1,377 0 Plums 0 1,016 0 Plums 0 1,016 0 Sour Soup 0 129 0 Star Fruit 0 357 0 Tamarin 0 90 0 Wattle 0 730 0 Total 575 253,227 0.23 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 189 7.11 Production of Permanent Planted Crops with Fertiliser by Inorganic Fertiliser - Tanga Region Mostly Compost Total % Durian 22 22 100.0 Cloves 178 2,079 8.6 Pears 584 7,511 7.8 Avocado 180 3,415 5.3 Cinamon 92 1,946 4.7 Mango 1,294 32,363 4.0 Sugarcane 476 12,993 3.7 Black Pepper 86 3,520 2.5 Cardamon 173 7,594 2.3 Orange 447 22,935 1.9 Banana 1,047 60,637 1.7 Coffee 146 11,035 1.3 Jack Fruit 86 13,626 0.6 Coconut 183 32,058 0.6 Apples 0 3,159 0.0 Cashewnut 0 15,665 0.0 Cocoa 0 249 0.0 Grape Fruit 0 90 0.0 Guava 0 658 0.0 Kapok 0 211 0.0 Lime/Lemon 0 4,185 0.0 Malay Apple 0 98 0.0 Mandarine/Tangerine 0 766 0.0 Mpesheni 0 350 0.0 Mshelisheli 0 226 0.0 Palm Oil 0 113 0.0 Pawpaw 0 2,434 0.0 Pigeon Pea 0 1,873 0.0 Pineapple 0 1,984 0.0 Pitches 0 1,377 0.0 Plums 0 1,016 0.0 Plums 0 1,016 0.0 Sour Soup 0 129 0.0 Star Fruit 0 357 0.0 Tamarin 0 90 0.0 Tea 0 4,714 0.0 Wattle 0 730 0.0 Total 5,690 321,564 Tanzania Agriculture Sample Census-2003 Tanga 190 Appendix II 191 AGROPROCESSING Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 192 Number % Number % Number % Lushoto 81,783 94 4,796 6 86,580 100 Korogwe 36,364 79 9,627 21 45,990 100 Muheza 43,887 89 5,308 11 49,195 100 Tanga 6,162 69 2,752 31 8,914 100 Pangani 5,133 72 1,995 28 7,128 100 Handeni 43,919 92 3,820 8 47,739 100 Kilindi 18,537 94 1,117 6 19,654 100 Total 235,784 89 29,414 11 265,198 100 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other Total Lushoto 1,875 1,131 75,285 0 0 3,348 144 0 81,783 Korogwe 1,901 1,051 32,787 213 0 411 0 0 36,364 Muheza 2,241 760 36,316 78 78 4,327 86 0 43,887 Tanga 827 659 4,476 0 0 201 0 0 6,162 Pangani 1,396 441 3,010 0 0 18 0 268 5,133 Handeni 5,809 2,954 35,155 0 0 0 0 0 43,919 Kilindi 2,140 98 15,109 0 0 1,190 0 0 18,537 Total 16,189 7,094 202,137 291 78 9,495 231 268 235,784 % 6.87 3.01 85.73 0.12 0.03 4.03 0.10 0.11 100.00 On Farm by Hand On Farm by Machine By Neighbour Machine By Farmers Association By Co- operative Union By Trader On Large Scale Farm Other By Factory Total Maize 11,403 6,575 199,258 291 78 9,479 86 0 0 227,170 Paddy 1,836 260 11,381 0 0 188 0 0 0 13,665 Sorghum 33 0 107 0 0 0 0 0 0 140 Finger Millet 0 0 108 0 0 0 0 0 0 108 Wheat 143 0 146 0 0 0 0 0 0 290 Cassava 10,367 596 17,445 0 0 335 90 283 0 29,117 Sweet Potat 0 0 146 0 0 0 0 0 0 146 Beans 857 0 1,356 0 0 142 0 0 0 2,355 Cowpeas 235 0 0 0 0 0 0 0 0 235 Green Gram 43 0 0 0 0 0 0 0 0 43 Groundnut 760 108 0 0 0 0 0 0 0 868 Oil Palm 23 0 0 0 0 0 0 0 0 23 Coconut 5,828 18 24 0 0 0 0 380 0 6,250 Cashewnut 85 0 0 0 0 0 0 0 0 85 Coffee 0 872 903 0 0 0 0 0 0 1,774 Tea 0 0 0 0 0 0 144 0 146 291 Sugarcane 422 262 0 0 0 0 0 0 0 685 Pineapple 180 0 0 0 0 0 0 0 0 180 Tomatoes 108 0 0 0 0 0 0 0 0 108 Amaranths 108 0 0 0 0 0 0 0 0 108 Crop Method of Processing 8.0b: Number of Crops Growing Households by Method of Processing and District; 2002/03 Agricultural Year District Method of Processing 8.1.1a AGROPROCESSING: Number of Crop Growing Households Processing Crops During 2002/03 Agricultural Year By Location and Crop, Tanga Region 8.0a: Number of Crops Growing Households reported to have Processed Farm Products by District; 2002/03 Agricultural Year District Households That Processed Crops Households that did not Process Crops Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 193 Household / Human Consumption Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Total Maize 226,323 107 171 127 441 227,170 Paddy 13,141 89 225 0 210 13,665 Sorghum 140 0 0 0 0 140 Finger Millet 108 0 0 0 0 108 Wheat 290 0 0 0 0 290 Cassava 28,546 0 266 81 224 29,117 Sweet Potat 146 0 0 0 0 146 Beans 2,065 0 290 0 0 2,355 Cowpeas 235 0 0 0 0 235 Green Gram 43 0 0 0 0 43 Groundnut 369 0 391 0 108 868 Oil Palm 23 0 0 0 0 23 Coconut 6,056 22 102 70 0 6,250 Cashewnut 85 0 0 0 0 85 Coffee 0 0 1,774 0 0 1,774 Tea 0 0 291 0 0 291 Sugarcane 0 0 685 0 0 685 Pineapple 180 0 0 0 0 180 Tomatoes 108 0 0 0 0 108 Amaranths 108 0 0 0 0 108 Total 277,966 218 4,194 278 984 283,641 Neighbours Market / Trade Store Secondary Market Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Maize 6,956 8,169 0 646 277 450 2,113 82 208,477 227,170 Paddy 385 1,745 0 0 93 105 14 175 11,148 13,665 Sorghum 0 0 0 0 0 0 0 0 140 140 Finger Millet 0 0 0 0 0 0 0 0 108 108 Wheat 0 0 0 0 0 0 0 0 290 290 Cassava 319 5,179 142 0 0 91 0 0 23,387 29,117 Sweet Potat 0 0 0 146 0 0 0 0 0 146 Beans 0 340 0 0 0 0 144 0 1,870 2,355 Cowpeas 106 0 0 0 0 0 0 0 129 235 Green Gram 0 0 0 0 0 0 0 0 43 43 Groundnut 0 198 0 0 0 0 175 108 387 868 Oil Palm 0 0 0 0 0 0 0 0 23 23 Coconut 653 0 0 0 0 0 55 0 5,543 6,250 Cashewnut 0 0 0 0 0 0 0 0 85 85 Coffee 0 0 0 979 583 0 0 0 213 1,774 Tea 0 0 0 0 0 144 146 0 0 291 Sugarcane 107 49 0 0 0 0 214 0 316 685 Pineapple 0 0 0 0 0 0 90 0 90 180 Tomatoes 0 0 0 0 0 0 0 0 108 108 Amaranths 0 0 0 0 0 0 0 0 108 108 Total 8,525 15,679 142 1,771 953 792 2,951 365 252,464 283,641 Flour / Meal Grain Oil Juice Pulp Other Total Lushoto 74,995 6,644 0 0 144 0 81,783 Korogwe 33,525 2,310 0 528 0 0 36,364 Muheza 41,503 1,099 1,095 146 0 43 43,887 Tanga 5,348 741 64 0 0 8 6,162 Pangani 3,442 349 78 39 0 1,225 5,133 Handeni 42,000 1,812 107 0 0 0 43,919 Kilindi 17,902 537 0 48 0 49 18,537 Total 218,715 13,494 1,344 762 144 1,325 235,784 District Main Product 8.1.1c AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Location of Sale of Product and Crop, Tanga Region Crop Where Sold 8.1.1d AGRO PROCESSING: Number of Crop Growing Households By Main Product and District During 2002/03 Agriculture Year, Tanga Region 8.1.1b AGROPROCESSING: Number of Crop Growing Households Reporting Processing of Farm Products Produced During 2002/03 Agricultural Year By Use of Product and Crop, Tanga Region Crop Product Use Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 194 Household /Human Consumption Fuel for Cooking Sale Only Animal Consumpti on Did Not Use Total Lushoto 80,767 0 871 0 146 81,783 Korogwe 35,415 107 636 0 205 36,364 Muheza 43,722 0 0 79 86 43,887 Tanga 6,047 0 115 0 0 6,162 Pangani 5,012 0 98 23 0 5,133 Handeni 43,814 0 0 0 105 43,919 Kilindi 18,440 0 49 48 0 18,537 Total 233,217 107 1,768 150 542 235,784 Neighbours Local Market / Trade Store Marketing Co- operative Farmers Association Large Scale Farm Trader at Farm Other Did not Sell Total Lushoto 2,899 7,147 1,017 291 291 0 0 70,139 81,783 Korogwe 641 416 107 0 0 321 0 34,879 36,364 Muheza 332 0 0 76 91 90 87 43,210 43,887 Tanga 174 54 0 0 0 0 33 5,900 6,162 Pangani 182 54 0 0 0 136 0 4,760 5,133 Handeni 2,818 972 210 201 214 1,729 0 37,776 43,919 Kilindi 535 538 0 0 0 97 48 17,318 18,537 Total 7,582 9,180 1,334 568 595 2,374 169 213,982 235,784 Bran Cake Husk Juice Pulp Shell No by- product Other Total Lushoto 851 0 825 0 872 144 79,091 0 81,783 Korogwe 1,871 0 1,598 99 626 101 32,069 0 36,364 Muheza 14,914 1,160 399 0 78 0 27,336 0 43,887 Tanga 1,462 73 713 0 0 57 3,857 0 6,162 Pangani 1,563 533 164 0 0 0 2,103 770 5,133 Handeni 18,802 0 108 0 0 0 24,901 108 43,919 Kilindi 581 0 0 0 0 49 17,907 0 18,537 Total 40,044 1,765 3,807 99 1,576 352 187,263 879 235,784 District By Product 8.1.1f AGRO PROCESSING: Number of Crop Growing Households By Where Product Sold and District During 2002/03 Agriculture Year, Tanga Region District Where Sold 8.1.1g AGRO PROCESSING: Number of Crop Growing Households By type of By-Product and District During 2002/03 Agriculture Year, Tanga Region 8.1.1e AGRO PROCESSING: Number of Crop Growing Households By Use of Primary Processed Product and District during 2002/03 Agriculture Year, Tanga Region District Product Use Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 195 MARKETING Tanzania Agriculture Sample Census-2003 Tanga Appendix II 196 Number % Number % Lushoto 69,510 80.3 17,069 19.7 86,580 Korogwe 29,751 64.7 16,240 35.3 45,990 Muheza 41,149 83.6 8,045 16.4 49,195 Tanga 6,605 74.1 2,309 25.9 8,914 Pangani 4,977 69.8 2,151 30.2 7,128 Handeni 30,492 63.9 17,247 36.1 47,739 Kilindi 14,684 74.7 4,970 25.3 19,654 Total 197,168 74.3 68,030 25.7 265,198 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Lushoto 292 17,772 0 143 721 146 874 65,760 85,708 Korogwe 512 15,936 105 204 189 0 2,311 23,561 42,819 Muheza 514 11,287 0 0 635 0 703 35,102 48,241 Tanga 87 2,891 0 26 26 0 325 5,315 8,670 Pangani 94 2,309 21 118 0 0 500 4,085 7,128 Handeni 755 17,509 108 0 0 0 1,389 23,814 43,575 Kilindi 0 5,261 49 0 97 0 632 13,419 19,458 Total 2,253 72,966 284 491 1,668 146 6,735 171,056 255,599 District Price Too Low Production Insufficient to Sell Market Too Far Co- operative Problems Trade Union Problems Government Regulatory Board Problems Other Not applicable Total Lushoto 0.34 20.74 0.00 0.17 0.84 0.17 1.02 76.73 100.00 Korogwe 1.19 37.22 0.25 0.48 0.44 0.00 5.40 55.02 100.00 Muheza 1.06 23.40 0.00 0.00 1.32 0.00 1.46 72.76 100.00 Tanga 1.01 33.34 0.00 0.30 0.30 0.00 3.75 61.30 100.00 Pangani 1.32 32.40 0.30 1.65 0.00 0.00 7.02 57.31 100.00 Handeni 1.73 40.18 0.25 0.00 0.00 0.00 3.19 54.65 100.00 Kilindi 0.00 27.04 0.25 0.00 0.50 0.00 3.25 68.97 100.00 Total 0.88 28.55 0.11 0.19 0.65 0.06 2.64 66.92 100.00 10.2 Number of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.3 Proportion of Households who Reported Main Reason for Not Selling Their Crops by District during 2002/03 Agricultural Year 10.1 Number of Crop Growing Households Reported to have Sold Agricultural Produce by District during 2002/03 District, Tanga Region District Households that Sold Households that Did not Sell Total Number of households Tanzania Agriculture Sample Census-2003 Tanga Appendix II 197 IRRIGATION / EROSION CONTROL Tanzania Agriculture Sample Census-2003 Tanga Appendix II 198 Number of Household % Number of Household % Lushoto 15,391 18 71,188 82 86,580 Korogwe 5,673 12 40,317 88 45,990 Muheza 929 2 48,266 98 49,195 Tanga 306 3 8,608 97 8,914 Pangani 129 2 6,998 98 7,128 Handeni 427 1 47,312 99 47,739 Kilindi 482 2 19,172 98 19,654 Total 23,338 9 241,860 91 265,198 District Irrigatable Area (ha) Irrigated Land (ha) % Lushoto 4,819 4,011 83 Korogwe 2,817 2,276 81 Muheza 229 156 68 Tanga 237 181 77 Pangani 150 149 99 Handeni 289 202 70 Kilindi 119 103 87 Total 8,660 7,079 82 River Dam Well Borehole Canal Pipe water Total Lushoto 4,731 718 433 0 9,375 135 15,391 Korogwe 4,539 0 422 0 609 103 5,673 Muheza 354 0 418 79 78 0 929 Tanga 133 56 96 0 0 21 306 Pangani 41 0 36 34 18 0 129 Handeni 108 0 319 0 0 0 427 Kilindi 147 0 240 0 95 0 482 Total 10,052 774 1,965 113 10,176 258 23,338 % 43 3 8 0 44 1 100 Gravity Hand Bucket Hand Pump Motor Pump Other Total Lushoto 8,480 6,911 0 0 0 15,391 Korogwe 4,149 1,334 84 0 106 5,673 Muheza 164 764 0 0 0 929 Tanga 23 248 0 36 0 306 Pangani 18 111 0 0 0 129 Handeni 0 321 0 0 106 427 Kilindi 49 433 0 0 0 482 Total 12,883 10,123 84 36 212 23,338 % 55.2 43.4 0.4 0.2 0.9 100 11.1 IRRIGATION: Number and Percent of Households Reporting use of irrigation during 2002/03 Agricultural year by District District Households Practicing Irrigation Households not Practicing Irrigation Total Number of households 11.2 IRRIGATION: Area (ha) of Irrigatable and NON irrigated land by district during 2002/03 agriculture year District Method of Obtaining Water 11.3 IRRIGATION: Number of Agriculture Households using irrigation by Source of Irrigation Water by districts during the 2002/03 agricultural Year District Source of Irrigation Water 11.4 IRRIGATION: Number of Agriculture Households by method of used to obtain water and district during 2002/03 agriculture year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 199 Flood Sprinkler Water Hose Bucket / Watering Can Total Lushoto 7,898 434 0 7,060 15,391 Korogwe 3,941 87 186 1,459 5,673 Muheza 78 0 0 851 929 Tanga 23 0 36 248 306 Pangani 18 0 0 111 129 Handeni 0 0 0 427 427 Kilindi 49 0 0 433 482 Total 12,006 521 222 10,588 23,338 % 51 2 1 45 100 Number % Number % Lushoto 20,308 23 66,271 77 86,580 Korogwe 4,540 10 41,450 90 45,990 Muheza 3,815 8 45,380 92 49,195 Tanga 55 1 8,859 99 8,914 Pangani 33 0 7,095 100 7,128 Handeni 952 2 46,787 98 47,739 Kilindi 585 3 19,069 97 19,654 Total 30,288 11 234,910 89 265,198 Terraces Erosion Control Bunds Gabions / Sandbag Vetiver Grass Tree Belts Water Harvesting Bunds Drainage Ditches Dam Total Number of Structures Lushoto 77,536 11,978 0 46,100 24,407 43,906 578 146 204,651 Korogwe 1,825 21,794 2,203 14,657 6,957 1,587 4,112 421 53,555 Muheza 1,654 5,956 919 2,290 1,433 13,571 2,104 . 27,925 Tanga 2,388 227 45 91 205 68 114 45 3,183 Pangani 0 0 0 0 410 0 0 0 410 Handeni 644 321 . . 192 . 3,963 . 5,120 Kilindi 436 2,243 . 245 2,710 925 582 . 7,141 Total 84,481 42,520 3,167 63,382 36,312 60,056 11,453 613 301,985 11.7 EROSION CONTROL: Number of Erosion Control/Water Harvesting Structures by Type and District as of 2002/03 agriculture year District Type of Erosion Control 11.6 EROSION CONTROL: Number of Households with Erosion Control/Water Harvesting Facilities on their Land By District District Presence of Erosion Control/Water Harvesting Facilities Have facility Does Not Have Facility Total Number of households 11.5 IRRIGATION: Number of Agriculture Households by Method of Field Application of Irrigation Water and District for the 2002/03 Agricultural Year District Method of field Application Tanzania Agriculture Sample Census-2003 Tanga 200 Appendix II 201 ACCESS TO FARM INPUTS / IMPLEMENTS Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 202 NOT Using Chemical Fertilizer No of households % No of households % Lushoto 5,915 7 80,665 93 86,580 Korogwe 1,388 3 44,602 97 45,990 Muheza 509 1 48,686 99 49,195 Tanga 158 2 8,756 98 8,914 Pangani 0 0 7,086 100 7,086 Handeni 204 0 47,535 100 47,739 Kilindi 49 0 19,605 100 19,654 Total 8,223 3 256,933 97 265,156 No of households % No of households % Lushoto 33,587 39 53,285 61 86,872 Korogwe 8,623 19 37,367 81 45,990 Muheza 5,103 10 44,092 90 49,195 Tanga 1,449 16 7,465 84 8,914 Pangani 275 4 6,963 96 7,238 Handeni 2,238 5 45,501 95 47,739 Kilindi 537 3 19,117 97 19,654 Total 51,812 20 213,789 80 265,601 No of households % No of households % Lushoto 5,932 7 80,647 93 86,580 Korogwe 5,434 12 40,556 88 45,990 Muheza 688 1 48,507 99 49,195 Tanga 442 5 8,471 95 8,914 Pangani 85 1 7,021 99 7,106 Handeni 935 2 46,804 98 47,739 Kilindi 1,063 5 18,590 95 19,654 Total 14,580 5 250,597 95 265,177 12.1.1 ACCESS TO INPUTS: Number of Crop Growing Households Using Chemical Fertilizer by District, 2002/03 Agricultural Year District Using Chemical Fertilizer Total Number of Crop growing households 12.1.2 ACCESS TO INPUTS: Number of Agricultural Households Using Farm Yard Manure by District during 2002/03 Agricultural Year District Using Farm Yard Manure Not Using Farm Yard Manure Total Number of Crop growing households 12.1.3 ACCESS TO INPUTS: Number of Agricultural Households Using COMPOST Manure by District during 2002/03 Agricultural Year District Using Compost Not Using Compost Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 203 No of households % No of households % Lushoto 8,505 10 77,929 90 86,434 Korogwe 2,214 5 43,776 95 45,990 Muheza 469 1 48,725 99 49,195 Tanga 201 2 8,713 98 8,914 Pangani 201 3 6,903 97 7,104 Handeni 2,093 4 45,646 96 47,739 Kilindi 289 1 19,365 99 19,654 Total 13,971 5 251,058 95 265,029 No of households % No of households % Lushoto 721 1 86,150 99 86,871 Korogwe 103 0 45,887 100 45,990 Muheza 0 0 49,195 100 49,195 Tanga 0 0 8,914 100 8,914 Pangani 11 0 7,092 100 7,104 Handeni 0 0 47,739 100 47,739 Kilindi 0 0 19,654 100 19,654 Total 835 0 264,630 100 265,466 No of households % No of households % Lushoto 14,855 17 71,433 83 86,288 Korogwe 8,835 19 37,155 81 45,990 Muheza 1,907 4 47,288 96 49,195 Tanga 1,166 13 7,748 87 8,914 Pangani 737 10 6,391 90 7,128 Handeni 5,183 11 42,556 89 47,739 Kilindi 818 4 18,836 96 19,654 Total 33,500 13 231,407 87 264,907 12.1.4 ACCESS TO INPUTS: Number of Crop Growing Households Using Insecticides/Fungicides by District during 2002/03 Agricultural Year District Using Insecticide/Fungicide Not Using Insecticide/Fungicide Total Number of Crop growing households 12.1.5 ACCESS TO INPUTS: Number of Crop Growing Households Using Herbicides by District during 2002/03 Agricultural Year District Using Herbicides Not Using Herbicides Total Number of Crop growing households 12.1.6 ACCESS TO INPUTS: Number of Crop Growing Households using Improved Seeds by District during 2002/03 Agricultural Year District Using Improved Seeds Not Using Improved Seeds Total Number of Crop growing households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 204 Number % Number % Number % Number % Number % Number % Number % Lushoto 146 0 5,623 6 0 0 0 0 146 0 0 0 80,665 93 86,580 Korogwe 107 0 1,175 3 0 0 0 0 0 0 107 0 44,602 97 45,990 Muheza 0 0 352 1 0 0 156 0 0 0 0 0 48,686 99 49,195 Tanga 0 0 135 2 0 0 0 0 0 0 23 0 8,756 98 8,914 Pangani 0 0 0 0 0 0 0 0 0 0 0 0 7,086 100 7,086 Handeni 0 0 108 0 96 0 0 0 0 0 0 0 47,535 100 47,739 Kilindi 0 0 49 0 0 0 0 0 0 0 0 0 19,605 100 19,654 Total 253 0 7,443 3 96 0 156 0 146 0 129 0 256,933 97 265,156 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 582 1 0 0 0 0 0 0 20,335 23 12,524 14 146 0 53,285 61 86,872 Korogwe 103 0 107 0 0 0 0 0 4,456 10 3,957 9 0 0 37,367 81 45,990 Muheza 0 0 91 0 92 0 0 0 2,158 4 2,761 6 0 0 44,092 90 49,195 Tanga 21 0 0 0 18 0 23 0 428 5 926 10 33 0 7,465 84 8,914 Pangani 0 0 0 0 0 0 0 0 110 2 128 2 37 1 6,963 96 7,238 ACCESS TO 106 0 0 0 0 0 0 0 1,169 2 963 2 0 0 45,501 95 47,739 Kilindi 0 0 0 0 0 0 0 0 243 1 293 1 0 0 19,117 97 19,654 Total 812 0 199 0 110 0 23 0 28,900 11 21,552 8 216 0 213,789 80 265,601 Number % Number % Number % Number % Lushoto 146 0 5,202 6 584 1 80,647 93 86,580 Korogwe 0 0 5,125 11 309 1 40,556 88 45,990 Muheza 0 0 688 1 0 0 48,507 99 49,195 Tanga 0 0 442 5 0 0 8,471 95 8,914 Pangani 0 0 41 1 44 1 7,021 99 7,106 Handeni 0 0 935 2 0 0 46,804 98 47,739 Kilindi 0 0 1,063 5 0 0 18,590 95 19,654 Total 146 0 13,497 5 937 0 250,597 95 265,177 Total Total Total 12.1.9 ACCESS TO INPUTS: Number of Agricultural Households by Source of COMPOST Manure and District, 2002/03 Agricultural Year District Co-operative Locally Produced by Household Neighbour Not applicable 12.1.8 ACCESS TO INPUTS: Number of Agricultural Households by Source of Farm Yard Manure and District, 2002/03 Agricultural Year District Local Market / Trade Store Secondary Market Development Project Large Scale Farm Locally Produced by Household Neighbour Other Not applicable 12.1.7 ACCESS TO INPUTS: Number of Agricultural Households by Source of Chemical Fertilizer and District, 2002/03 Agricultural Year District Co-operative Local Market / Trade Store Development Project Large Scale Farm Locally Produced by Household Neighbour Not applicable Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 205 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 146 0 0 0 8,358 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 77,929 90 86,434 Korogwe 0 0 0 0 1,896 4 105 0 107 0 0 0 0 0 105 0 0 0 0 0 43,776 95 45,990 Muheza 0 0 0 0 384 1 0 0 0 0 0 0 0 0 85 0 0 0 0 0 48,725 99 49,195 Tanga 0 0 0 0 201 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8,713 98 8,914 Pangani 21 0 11 0 63 1 0 0 72 1 0 0 22 0 0 0 11 0 0 0 6,903 97 7,104 Handeni 0 0 0 0 1,566 3 0 0 0 0 204 0 106 0 0 0 108 0 108 0 45,646 96 47,739 Kilindi 0 0 0 0 242 1 0 0 0 0 0 0 0 0 0 0 47 0 0 0 19,365 99 19,654 Total 167 0 11 0 12,711 5 105 0 179 0 204 0 128 0 190 0 166 0 108 0 251,058 95 265,029 Number % Number % Number % Lushoto 577 1 144 0 86,150 99 86,871 Korogwe 103 0 0 0 45,887 100 45,990 Muheza 0 0 0 0 49,195 100 49,195 Tanga 0 0 0 0 8,914 100 8,914 Pangani 0 0 11 0 7,092 100 7,104 Handeni 0 0 0 0 47,739 100 47,739 Kilindi 0 0 0 0 19,654 100 19,654 Total 679 0 156 0 264,630 100 265,466 Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 292 0 0 0 13,846 16 0 0 0 0 0 0 0 0 430 0 286 0 0 0 71,433 83 86,288 Korogwe 0 0 192 0 5,950 13 0 0 881 2 0 0 0 0 1,217 3 597 1 0 0 37,155 81 45,990 Muheza 0 0 0 0 1,379 3 0 0 0 0 0 0 91 0 171 0 265 1 0 0 47,288 96 49,195 Tanga 0 0 0 0 979 11 21 0 57 1 0 0 0 0 35 0 43 0 31 0 7,748 87 8,914 Pangani 0 0 0 0 581 8 0 0 72 1 0 0 0 0 30 0 54 1 0 0 6,391 90 7,128 Handeni 0 0 0 0 2,416 5 0 0 1,168 2 204 0 212 0 214 0 859 2 108 0 42,556 89 47,739 Kilindi 48 0 0 0 769 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18,836 96 19,654 Total 341 0 192 0 25,921 10 21 0 2,178 1 204 0 303 0 2,097 1 2,104 1 140 0 231,407 87 264,907 Total Other Not applicable Neighbour Other Not applicable 12.1.10 ACCESS TO INPUTS: Number of Agricultural Households by Source of Pesticides/Fungicides and District, 2002/03 Agricultural Year Neighbour 12.1.12 ACCESS TO INPUTS: Number of Agricultural Households by Source of Improved Seeds and District, 2002/03 Agricultural Year District Co-operative Local Farmers Group Local Market / Trade Store Secondary Market Total Development Project Crop Buyers Large Scale Farm Total District Local Market / Trade Store Neighbour Not applicable Locally Produced by Household District Co-operative Local Farmers Group Local Market / Trade Store Locally Produced by Household Development Project Crop Buyers Large Scale Farm 12.1.11 ACCESS TO INPUTS: Number of Agricultural Households by Source of Herbicides and District, 2002/03 Agricultural Year Secondary Market Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 206 Number % Number % Number % Number % Number % Lushoto 1,297 22 1,443 24 3,029 51 145 2 0 0 5,915 Korogwe 107 8 779 56 0 0 101 7 401 29 1,388 Muheza 78 15 169 33 79 15 0 0 183 36 509 Tanga 10 6 0 0 93 59 55 35 0 0 158 Handeni 96 47 0 0 0 0 0 0 108 53 204 Kilindi 0 0 0 0 0 0 0 0 49 100 49 Total 1,587 19 2,392 29 3,201 39 302 4 741 9 8,223 Number % Number % Number % Number % Lushoto 31,565 94 1,735 5 143 0 144 0 33,587 Korogwe 7,930 92 492 6 202 2 0 0 8,623 Muheza 4,511 88 500 10 91 2 0 0 5,103 Tanga 1,114 77 264 18 62 4 8 1 1,449 Pangani 275 100 0 0 0 0 0 0 275 Handeni 1,707 76 531 24 0 0 0 0 2,238 Kilindi 390 73 147 27 0 0 0 0 537 Total 47,492 92 3,668 7 498 1 153 0 51,812 Between 10 and 20 km Total Number 12.1.13 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Chemical Fertilizer by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number District Less than 1 km Between 1 and 3 km Between 3 and 10 km 12.1.14 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Farm Yard Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 207 Number % Number % Lushoto 5,932 100 0 0 5,932 Korogwe 5,237 96 197 4 5,434 Muheza 598 87 90 13 688 Tanga 409 92 33 8 442 Pangani 85 100 0 0 85 Handeni 935 100 0 0 935 Kilindi 1,063 100 0 0 1,063 Total 14,259 98 321 2 14,580 Number % Number % Number % Number % Number % Lushoto 5,481 37 4,178 28 4,473 30 291 2 431 3 14,855 Korogwe 2,626 30 1,300 15 1,201 14 2,383 27 1,325 15 8,835 Muheza 556 29 92 5 160 8 398 21 701 37 1,907 Tanga 154 13 53 5 569 49 234 20 156 13 1,166 Pangani 113 15 0 0 67 9 108 15 448 61 737 Handeni 846 16 1,269 24 743 14 638 12 1,687 33 5,183 Kilindi 238 29 47 6 49 6 144 18 341 42 818 Total 10,013 30 6,939 21 7,263 22 4,197 13 5,088 15 33,500 Number % Number % Number % Number % Number % Number % Lushoto 2021 24 2731 32 3169 37 437 5 146 2 8505 100 Korogwe 0 0 364 16 522 24 713 32 615 28 2214 100 Muheza 0 0 85 18 0 0 0 0 384 82 469 100 Tanga 0 0 0 0 104 52 66 33 31 16 201 100 Pangani 82 41 0 0 11 6 0 0 108 54 201 100 Handeni 321 15 210 10 430 21 0 0 1132 54 2093 100 Kilindi 142 49 0 0 0 0 49 17 98 34 289 100 Total 2565 18 3389 24 4236 30 1265 9 2515 18 13971 100 District Less than 1 km Between 1 and 3 km Total Number 12.1.18 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Improved Seeds by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total Number 12.1.16 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of Pesticides/Fungicides by District, 2002/03 Agricultural Year District Less than 1 km Between 1 and 3 km Between 3 and 10 km Between 10 and 20 km 20 km and Above Total 12.1.15 ACCESS TO INPUTS: Number of Agricultural Households and Distance to Source of COMPOST Manure by District, 2002/03 Agricultural Year Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 208 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 4,053 5 70,581 87 4,580 6 0 0 583 1 726 1 0 0 142 0 80,665 Korogwe 4,222 9 33,146 74 825 2 305 1 1,229 3 3,851 9 0 0 1,024 2 44,602 Muheza 3,853 8 34,042 70 617 1 0 0 2,464 5 7,448 15 0 0 262 1 48,686 Tanga 543 6 5,867 67 47 1 0 0 656 7 1,564 18 45 1 33 0 8,756 Pangani 1,678 24 3,706 52 289 4 0 0 199 3 1,192 17 0 0 22 0 7,086 Handeni 9,209 19 19,831 42 428 1 0 0 6,849 14 10,358 22 0 0 860 2 47,535 Kilindi 6,388 33 4,581 23 95 0 0 0 775 4 7,523 38 0 0 243 1 19,605 Total 29,946 12 171,754 67 6,880 3 305 0 12,756 5 32,663 13 45 0 2,586 1 256,933 Number % Number % Number % Number % Number % Number % Number % Lushoto 5,555 10 9,733 18 28,458 53 7,676 14 711 1 1,151 2 0 0 53,285 Korogwe 3,023 8 2,953 8 25,114 67 1,865 5 1,114 3 2,374 6 924 2 37,367 Muheza 10,410 24 1,484 3 22,556 51 3,370 8 1,794 4 4,298 10 180 0 44,092 Tanga 2,441 33 323 4 2,646 35 739 10 270 4 1,013 14 32 0 7,465 Pangani 2,525 36 2,020 29 1,494 21 381 5 131 2 366 5 46 1 6,963 Handeni 5,880 13 1,165 3 25,498 56 935 2 3,147 7 8,230 18 647 1 45,501 Kilindi 2,629 14 2,245 12 5,989 31 98 1 1,119 6 6,795 36 243 1 19,117 Total 32,464 15 19,922 9 111,756 52 15,063 7 8,286 4 24,228 11 2,071 1 213,789 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 6,831 8 13,925 17 39,102 48 9,281 12 5,020 6 6,488 8 0 0 0 0 80,647 Korogwe 1,785 4 3,676 9 25,266 62 2,198 5 3,390 8 3,422 8 0 0 820 2 40,556 Muheza 1,804 4 1,248 3 24,437 50 5,196 11 10,654 22 4,282 9 268 1 618 1 48,507 Tanga 1,006 12 378 4 3,398 40 213 3 2,151 25 1,163 14 0 0 163 2 8,471 Pangani 553 8 2,043 29 2,315 33 396 6 1,232 18 328 5 0 0 154 2 7,021 Handeni 3,087 7 1,912 4 19,665 42 520 1 13,602 29 7,267 16 106 0 647 1 46,804 Kilindi 1,216 7 2,583 14 4,869 26 195 1 2,782 15 6,360 34 245 1 340 2 18,590 Total 16,282 6 25,764 10 119,052 48 17,999 7 38,831 15 29,310 12 618 0 2,741 1 250,597 12.1.25 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Chemical Fertilizer by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total 12.1.26 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Farm Yard Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.27 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using COMPOST Manure by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 209 Number % Number % Number % Number % Number % Number % Number % Lushoto 1,599 2 72,257 93 584 1 146 0 1,162 1 2,182 3 0 0 77,929 Korogwe 2,975 7 32,004 73 1,047 2 300 1 2,170 5 4,568 10 712 2 43,776 Muheza 2,417 5 34,766 71 403 1 0 0 2,713 6 8,072 17 355 1 48,725 Tanga 306 4 5,308 61 92 1 21 0 1,216 14 1,707 20 63 1 8,713 Pangani 1,105 16 4,812 70 369 5 36 1 257 4 259 4 65 1 6,903 Handeni 3,805 8 25,653 56 205 0 108 0 11,384 25 3,950 9 541 1 45,646 Kilindi 4,243 22 9,480 49 290 1 0 0 1,021 5 4,039 21 291 2 19,365 Total 16,449 7 184,281 73 2,990 1 611 0 19,923 8 24,777 10 2,027 1 251,058 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 5,101 6 66,833 78 728 1 0 0 3,930 5 9,558 11 0 0 0 0 86,150 Korogwe 3,607 8 33,365 73 419 1 302 1 3,173 7 3,680 8 107 0 1,234 3 45,887 Muheza 1,522 3 34,018 69 407 1 0 0 4,969 10 7,927 16 0 0 351 1 49,195 Tanga 336 4 4,507 51 66 1 24 0 2,402 27 1,517 17 0 0 63 1 8,914 Pangani 1,134 16 4,790 68 411 6 0 0 373 5 361 5 0 0 22 0 7,092 Handeni 5,261 11 23,281 49 309 1 0 0 12,776 27 5,466 11 0 0 647 1 47,739 Kilindi 4,535 23 8,747 45 387 2 0 0 1,116 6 4,625 24 0 0 243 1 19,654 Total 21,496 8 175,541 66 2,727 1 327 0 28,740 11 33,132 13 107 0 2,560 1 264,630 Number % Number % Number % Number % Number % Number % Number % Number % Lushoto 2,744 4 68,105 95 146 0 0 0 292 0 146 0 0 0 0 0 71,433 Korogwe 2,024 5 31,981 86 522 1 195 1 613 2 693 2 107 0 1,020 3 37,155 Muheza 5,726 12 38,231 81 404 1 0 0 356 1 1,920 4 357 1 250 1 47,245 Tanga 1,282 17 5,446 70 18 0 0 0 181 2 676 9 45 1 100 1 7,748 Pangani 1,640 26 4,263 67 356 6 0 0 23 0 87 1 0 0 22 0 6,391 Handeni 6,653 16 31,820 75 0 0 105 0 1,714 4 1,616 4 108 0 540 1 42,556 Kilindi 5,987 32 9,059 48 341 2 48 0 436 2 2,625 14 49 0 291 2 18,836 Total 26,054 11 188,905 82 1,787 1 349 0 3,617 2 7,762 3 667 0 2,223 1 231,364 12.1.28 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Pesticides/Fungicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Other Total 12.1.29 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Herbicides by District, 2002/03 Agricultural Year District Not Available Price Too High No Money to Buy Too Much Labour Required Do not Know How to Use Input is of No Use Locally Produced by Household Other Total 12.1.30 ACCESS TO INPUTS: Number of Agricultural Households and Reason for NOT using Improved Seeds by District, 2002/03 Agricultural Year Do not Know How to Use Input is of No Use Locally Produced by Household District Not Available Price Too High No Money to Buy Other Total Too Much Labour Required Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 210 Number % Number % Number % Number % Lushoto 1,019 17 3,616 61 1,139 19 140 2 5,915 Korogwe 879 63 316 23 193 14 0 0 1,388 Muheza 157 31 261 51 91 18 0 0 509 Tanga 41 26 63 40 54 34 0 0 158 Handeni 108 53 96 47 0 0 0 0 204 Kilindi 0 0 49 100 0 0 0 0 49 Total 2,205 27 4,400 54 1,478 18 140 2 8,223 Number % Number % Number % Number % Lushoto 6,246 19 23,720 71 3,622 11 0 0 33,587 Korogwe 1,957 23 5,956 69 710 8 0 0 8,623 Muheza 2,151 42 2,260 44 691 14 0 0 5,103 Tanga 368 25 924 64 128 9 29 2 1,449 Pangani 104 38 159 58 11 4 0 0 275 Handeni 216 8 2,135 83 213 8 0 0 2,564 Kilindi 98 18 439 82 0 0 0 0 537 Total 11,140 21 35,593 68 5,375 10 29 0 52,137 Number % Number % Number % Number % Lushoto 859 14 4,791 81 142 2 140 2 5,932 Korogwe 835 15 4,296 79 304 6 0 0 5,434 Muheza 173 25 254 37 260 38 0 0 688 Tanga 129 29 280 63 33 7 0 0 442 Pangani 18 22 67 78 0 0 0 0 85 Handeni 105 11 734 78 96 10 0 0 935 Kilindi 243 23 774 73 47 4 0 0 1,063 Total 2,363 16 11,195 77 881 6 140 1 14,580 12.1.31 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Chemical Fertilizer by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Total 12.1.32 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Farm Yard Manure by District, 2002/03 Agricultural Year District Excellent Good Average Poor Total Excellent Good Average Poor 12.1.33 ACCESS TO INPUTS: Number of Agricultural Households and Quality of COMPOST Manure by District, 2002/03 Agricultural Year District Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 211 Number % Number % Number % Number % Lushoto 1,452 17 5,185 61 1,727 20 140 2 8,505 Korogwe 382 17 1,536 69 190 9 106 5 2,214 Muheza 235 50 235 50 0 0 0 0 469 Tanga 32 16 136 68 32 16 0 0 201 Pangani 21 11 180 89 0 0 0 0 201 Handeni 0 0 1,709 82 383 18 0 0 2,093 Kilindi 98 34 191 66 0 0 0 0 289 Total 2,220 16 9,171 66 2,332 17 247 2 13,971 Number % Lushoto 721 100 721 Korogwe 103 100 103 Pangani 11 100 11 Total 835 100 835 Total Number % Number % Number % Number % Number % Number % Number % Lushoto 2,478 17 10,523 71 1,854 12 0 0 0 0 14,855 Lushoto 19,382 22 67,197 78 86,580 Korogwe 2,248 25 5,651 64 723 8 107 1 106 1 8,835 Korogwe 10,738 23 35,252 77 45,990 Muheza 778 41 1,069 56 59 3 0 0 0 0 1,907 Muheza 1,804 4 47,391 96 49,195 Tanga 422 36 694 60 49 4 0 0 0 0 1,166 Tanga 717 8 8,197 92 8,914 Pangani 118 16 573 78 22 3 23 3 0 0 737 Pangani 474 7 6,611 93 7,086 Handeni 638 12 4,332 79 432 8 107 2 0 0 5,508 Handeni 1,912 4 45,827 96 47,739 Kilindi 244 30 525 64 49 6 0 0 0 0 818 Kilindi 633 3 19,020 97 19,654 Total 6,925 20 23,369 69 3,188 9 237 1 106 0 33,825 Total 35,660 13 229,496 87 265,156 District Excellent Good Average District Good Total 12.1.36 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Improved Seeds by District, 2002/03 Agricultural Year Does not Work Total Number Total Poor District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year 12.1.37 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Chemical Fertilizers Next Year by District, 2002/03 Agricultural Year 12.1.34 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Pesticides/Fungicides by District, 2002/03 Agricultural Year 12.1.35 ACCESS TO INPUTS: Number of Agricultural Households and Quality of Herbicides by District, 2002/03 Agricultural Year District Excellent Good Average Poor Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 212 District Number % Number % Number % Number % Lushoto 52,735 61 34,136 39 86,872 Lushoto 18,205 21 68,374 79 86,580 Korogwe 25,606 56 20,384 44 45,990 Korogwe 16,446 36 29,544 64 45,990 Muheza 10,943 22 38,251 78 49,195 Muheza 3,869 8 45,325 92 49,195 Tanga 3,675 41 5,239 59 8,914 Tanga 1,716 19 7,198 81 8,914 Pangani 820 11 6,418 89 7,238 Pangani 589 8 6,517 92 7,106 Handeni 14,829 31 32,910 69 47,739 Handeni 4,126 9 43,613 91 47,739 Kilindi 3,753 19 15,900 81 19,654 Kilindi 3,157 16 16,497 84 19,654 Total 112,362 42 153,239 58 265,601 Total 48,108 18 217,069 82 265,177 District Total Number Number % Number % Number % Number % Lushoto 16,325 19 70,109 81 86,434 Lushoto 3,455 4 83,416 96 86,871 Korogwe 12,094 26 33,896 74 45,990 Korogwe 5,668 12 40,322 88 45,990 Muheza 2,918 6 46,277 94 49,195 Muheza 916 2 48,278 98 49,195 Tanga 1,110 12 7,804 88 8,914 Tanga 267 3 8,646 97 8,914 Pangani 1,023 14 6,081 86 7,104 Pangani 318 4 6,785 96 7,104 Handeni 6,690 14 41,048 86 47,739 Handeni 3,729 8 44,010 92 47,739 Kilindi 3,704 19 15,950 81 19,654 Kilindi 1,751 9 17,903 91 19,654 Total 43,864 17 221,165 83 265,029 Total 16,104 6 249,361 94 265,466 Number % Number % Lushoto 28,186 33 58,103 67 86,288 Korogwe 25,581 56 20,409 44 45,990 Muheza 14,687 30 34,507 70 49,195 Tanga 3,657 41 5,257 59 8,914 Pangani 1,733 24 5,395 76 7,128 Handeni 18,984 40 28,755 60 47,739 Kilindi 7,961 41 11,693 59 19,654 Total 100,788 38 164,118 62 264,907 12.1.42 ACCESS TO INPUTS: Number of Agricultural Households with Plan to use Improved Seeds next year by District, 2002/03 Agricultural Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total 12.1.40 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Pesticides/Fungicides Next Year by District, 2002/03 Agricultural Year 12.1.41 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Herbicides Next Year by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total 12.1.38 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use Farm Yard Manure Next Year by District, 2002/03 Agricultural Year 12.1.39 ACCESS TO INPUTS: Number of Agricultural Households With Plan to use COMPOST Manure Next Year by District, 2002/03 Agricultural Year Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Total District Agricultural Households With Plan to use Next Year Agricultural Households With NO Plan to use Next Year Total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 213 AGRICULTURE CREDIT Tanzania Agriculture Sample Census-2003 Tanga Appendix II 214 Number % Number % Lushoto 0 0 404 100 404 Korogwe 107 100 0 0 107 Muheza 78 32 165 68 243 Tanga 61 100 0 0 61 Handeni 208 100 0 0 208 Total 453 44 569 56 1,022 % 44 56 District Family, Friend and Relative Commercial Bank Saving & Credit Society Trader / Trade Store Religious Organisation / NGO / Project Other Total Lushoto 135 0 0 0 270 0 404 Korogwe 0 0 0 0 0 107 107 Muheza 79 0 0 78 86 0 243 Tanga 0 35 0 0 26 0 61 Handeni 0 0 208 0 0 0 208 Total 213 35 208 78 382 107 1,022 % 21 3 20 8 37 10 100 13.2a AGRICULTURE CREDIT: Number of Agriculture Households receiving Credit by sex of household head and District During the 2002/03 Agriculture Year District Male Female Total 13.2c AGRICULTURE CREDIT: Number of Households receiving Credits by Main Source of credit and region District the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 215 District Did not know how to get credit Don't know about credit Not available Did not want to go into debt Difficult bureaucracy procedure Not needed Interest rate/cost too high Credit granted too late Other Total Lushoto 54,575 13,490 12,226 3,326 1,156 291 975 135 0 86,175 Korogwe 26,004 11,093 2,914 2,459 1,161 603 1,275 281 94 45,883 Muheza 27,538 7,663 2,894 5,247 3,511 1,298 721 80 0 48,952 Tanga 4,076 1,293 689 1,459 500 418 265 32 121 8,853 Pangani 2,994 1,803 527 424 650 190 356 0 183 7,128 Handeni 26,688 10,207 4,021 2,336 2,299 1,253 409 107 212 47,531 Kilindi 9,591 4,671 4,031 536 193 436 97 49 49 19,654 Total 151,467 50,220 27,302 15,787 9,470 4,490 4,097 684 659 264,176 District Total Credits Other Labour Fertilizers Seeds Tools / Equipment Irrigation Structures Agro- chemicals Livestock Lushoto 404 404 0 0 0 0 0 0 0 Korogwe 533 0 0 107 107 107 107 107 0 Muheza 400 0 79 157 79 0 0 0 86 Tanga 61 0 61 0 0 0 0 0 0 Handeni 208 0 208 0 0 0 0 0 0 Total Credits 1,606 404 347 263 185 107 107 107 86 13.1b AGRICULTURE CREDIT: Number of Credits Received by Main Purpose of Credit and District During the 2002/03 Agriculture Year 13.1a AGRICULTURE CREDIT: Number of Households Reporting the Main reasons for Not Using Credit by District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga 216 Appendix II 217 TREE FARMING AND AGROFORESTRY Tanzania Agriculture Sample Census-2003 Tanga Appendix II 218 Gravellis Tectona Grandis Eucalyptus Spp Cyprus Spp Senna Spp Pinus Spp Albizia Spp Trichilia Spp Casurina Equisetfilia Kyaya Spp 430,520 983 51,640 72,130 1,156 19,121 10,639 8,516 5,014 2,808 157,977 . 37,210 . 4,080 . . . 872 1,612 58,367 311,076 2,758 . 25,285 . . . . . . . . . 296 . . . . . 361 1,511 . . 290 . . . . . 424 . . . 1,060 . . . . . 587 . 147 . . . . . 196 . 648,235 313,570 91,754 72,130 32,166 19,121 10,639 8,516 6,082 4,420 3 53 2 7 6 0 26 0 0 0 Leucena Spp Azadritachta Spp Terminalia Catapa Terminalia Ivorensis Saraca Spp Sesbania Spp Jakaranda Spp Syszygium Spp Total . . . . . . 584 . . 603,112 . . 2,270 2,000 1,301 . . 206 194 207,720 4,052 . 504 336 . 734 . . . 403,112 . . . . . . . . . 296 . 447 576 . . . . 45 . 3,229 . . . . . 531 . . . 2,014 . 3,200 . 147 . . . . 49 4,326 4,052 3,646 3,350 2,483 1,301 1,265 584 251 243 1,223,809 0 0 0 1 0 0 0 0 1 100 cont…. ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region 14.1 ON FARM TREE PLANTING: Number of Planted Trees by Species and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 219 Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Number of Households Number of Trees Lushoto 10,157 277,992 4,338 227,967 1,597 89,302 16,093 595,261 Korogwe 3,269 36,615 1,698 61,283 310 109,625 5,277 207,523 Muheza 3,878 163,425 1,495 133,151 529 106,536 5,902 403,112 Tanga 77 296 0 . 0 . 77 296 Pangani 121 1,900 22 1,328 0 . 143 3,229 Handeni 318 1,271 106 743 0 . 424 2,014 Kilindi 98 587 97 3,200 0 . 195 3,787 Total 17,917 482,086 7,757 427,672 2,436 305,464 28,110 1,215,222 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total Lushoto 8,931 1,148 9,152 1,595 144 0 20,971 Korogwe 3,685 425 845 945 0 504 6,403 Muheza 3,305 2,002 424 834 0 87 6,653 Tanga 0 0 0 77 0 0 77 Pangani 40 112 0 101 0 46 299 Handeni 106 0 106 318 0 0 530 Kilindi 147 98 0 0 49 97 391 Total 16,214 3,785 10,527 3,870 193 735 35,324 14.3 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region District Main Use 14.2 TREE FARMING: Number of Households with planted trees on their land and Number of Trees by Planting Location and District During the 2002/03 Agriculture Year, Tanga Region District Mostly on Field / Plot Boundaries Mostly Scattered in Field Mostly in Plantation / Coppice Total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 220 1-9 10-19 20-29 30-39 40-49 Above 50 Total Lushoto 10,235 3,878 3,905 1,746 0 146 19,909 Korogwe 854 522 736 852 213 103 3,279 Muheza 81 0 1,183 79 0 0 1,343 Tanga 458 0 0 0 0 0 458 Pangani 59 0 0 0 0 0 59 Handeni 0 0 485 862 192 0 1,539 Kilindi 0 97 0 0 0 390 487 Total 11,687 4,497 6,309 3,539 405 638 27,073 % 43 17 23 13 1 2 100 Planks / Timber Poles Charcoal Fuel for Wood Shade Medicinal Other Total Lushoto 6,154 3,008 0 10,678 1,277 0 0 21,117 Korogwe 535 814 0 4,222 531 203 97 6,403 Muheza 601 1,079 90 4,375 253 84 260 6,742 Tanga 0 77 0 0 0 0 0 77 Pangani 0 0 0 176 22 78 0 277 Handeni 0 106 0 318 106 0 0 530 Kilindi 98 0 0 49 196 48 0 391 Total 7,388 5,084 90 19,818 2,384 414 357 35,536 14.4 TREE FARMING: Number of Agriculture Households Classified by Distance to Community Planted Forest (Km) By District During the 2002/03 Agriculture Year, Tanga Region District Distance to Community Planted Forest (km) District Second Use 14.5 ON FARM TREE PLANTING: Number of responses by Second use of planted trees and District for the 2002/03 agriculture yea, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 221 Planks / Timber Poles Fuel for Wood Shade Medicinal Other Total 8,931 1,148 9,152 1,595 144 0 20,971 3,685 425 845 945 0 504 6,403 3,305 2,002 424 834 0 87 6,653 0 0 0 77 0 0 77 40 112 0 101 0 46 299 106 0 106 318 0 0 530 147 98 0 0 49 97 391 16,214 3,785 10,527 3,870 193 735 35,324 14 ON FARM TREE PLANTING: Number of responses by main use of planted trees and District for the 2002/03 agriculture yea, Tanga Region Main Use Tanzania Agriculture Sample Census-2003 Tanga 222 Appendix II Tanzania Agriculture Sample Census – 2003 Tanga 223 CROP EXTENSION Appendix II 224 Number % Number % Lushoto 42,132 49 44,448 51 86,580 Korogwe 38,500 84 7,490 16 45,990 Muheza 21,091 43 28,103 57 49,195 Tanga 1,266 14 7,648 86 8,914 Pangani 2,807 39 4,321 61 7,128 Handeni 10,334 22 37,405 78 47,739 Kilindi 5,356 27 14,298 73 19,654 Total 121,487 46 143,711 54 265,198 Total Number % Number % Number % Number % Number % Number Lushoto 3,038 7 23,310 55 14,941 35 140 0 702 2 42,132 Korogwe 4,187 11 26,875 70 6,943 18 495 1 0 0 38,500 Muheza 2,093 10 13,998 66 3,703 18 406 2 892 4 21,091 Tanga 63 5 841 66 234 18 127 10 0 0 1,266 Pangani 54 1,141 41 35 1 0 0 2,807 Handeni 538 5 5,684 55 3,909 38 203 2 0 0 10,334 Kilindi 194 4 3,647 68 1,417 26 98 2 0 0 5,356 Total 10,217 8 75,884 62 32,287 27 1,505 1 1,594 1 121,487 Total Number % Number % Number % Number % Number % Number % Number Lushoto 42,132 100 0 0 0 0 0 0 0 0 0 0 42,132 Korogwe 37,886 99 321 1 0 0 104 0 0 0 97 0 38,407 Pangani 104 4 1,527 0 0 0 0 0 0 0 89 0 21,001 Tanga 1,194 94 10 1 0 0 21 2 10 1 32 3 1,266 Pangani 2,677 96 18 1 0 0 24 1 22 1 47 2 2,788 Handeni 9,624 94 0 0 107 1 284 3 215 2 0 0 10,231 Kilindi 5,258 98 0 0 0 0 0 0 49 1 49 1 5,356 Total 119,592 99 438 0 107 0 433 0 296 0 313 0 121,180 15.1 CROP EXTENSION: Number of Agriculture Households Receiving Extension Messages by District During the 2002/03 Agriculture Year, Tanga Region District Households Receiving Extension Advice Households Not Receiving Extension Advice Total Number of Households 15.2 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Tanga Region District Good No Good 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During the 2002/03 Agriculture Year, Tanga Region District Government NGO / Development Project Cooperative Large Scale Farm Other Not Very Good Average Poor Tanzania Agriculture Sample Census-2003 Tanga Appendix II 225 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Lushoto 41,406 0 0 0 0 0 41,406 86,580 48 Korogwe 37,461 321 0 0 0 97 37,878 45,990 82 Muheza 20,606 0 0 0 0 89 20,695 49,195 42 Tanga 1,148 0 0 21 0 32 1,201 8,914 13 Pangani 2,538 18 0 24 22 47 2,649 7,128 37 Handeni 9,520 0 107 284 215 0 10,127 47,739 21 Kilindi 5,160 0 0 0 49 49 5,258 19,654 27 Total 117,838 339 107 329 287 313 119,213 265,198 45 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 31,324 2,439 145 0 432 34,340 86,580 39.7 Korogwe 19,453 720 0 107 307 20,587 45,990 44.8 Muheza 9,849 630 0 0 214 10,693 49,195 21.7 Tanga 340 0 0 0 323 663 8,914 7.4 Pangani 665 142 0 0 95 901 7,128 12.6 Handeni 1,574 217 0 0 2,253 4,044 47,739 8.5 Kilindi 926 49 0 0 489 1,464 19,654 7.5 Total 64,130 4,197 145 107 4,113 72,692 265,198 27.4 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Tanga Region District Spacing 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 226 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 23,282 146 0 146 2,171 25,745 86,580 29.7 Korogwe 12,384 194 0 107 1,918 14,602 45,990 31.8 Muheza 7,325 0 0 0 986 8,311 49,195 16.9 Tanga 246 0 21 0 381 647 8,914 7.3 Pangani 862 0 0 0 164 1,027 7,128 14.4 Handeni 1,033 217 0 0 2,559 3,809 47,739 8.0 Kilindi 586 0 0 0 637 1,222 19,654 6.2 Total 45,718 557 21 253 8,815 55,363 265,198 20.9 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Organic Fertilizer Use 15.8 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Tanga Region District Inorganic Fertilizer Use 15.9 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seeds Tanzania Agriculture Sample Census-2003 Tanga Appendix II 227 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 3,304 0 0 146 1,441 4,891 86,580 6 Korogwe 8,660 107 0 107 1,225 10,098 45,990 22 Muheza 1,972 0 0 0 215 2,187 49,195 4 Tanga 338 0 23 0 321 681 8,914 8 Pangani 494 65 24 0 167 750 7,128 11 Handeni 3,331 108 188 0 2,351 5,979 47,739 13 Kilindi 975 0 0 49 832 1,857 19,654 9 Total 19,073 280 235 302 6,552 26,443 265,198 10 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 25,905 708 436 27,049 86,580 31 Korogwe 17,626 506 1,227 19,360 45,990 42 Muheza 4,716 0 584 5,300 49,195 11 Tanga 250 0 350 600 8,914 7 Pangani 254 72 164 490 7,128 7 Handeni 1,055 0 2,350 3,405 47,739 7 Kilindi 534 49 734 1,317 19,654 7 Total 50,340 1,335 5,846 57,521 265,198 22 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 39,553 0 0 144 146 39,844 86,580 46.0 Korogwe 28,076 210 204 0 495 28,986 45,990 63.0 Muheza 15,724 59 0 0 322 16,106 49,195 32.7 Tanga 607 0 0 0 248 855 8,914 9.6 Pangani 1,789 73 0 0 143 2,004 7,128 28.1 Handeni 6,176 213 0 107 971 7,467 47,739 15.6 Kilindi 3,364 146 49 49 146 3,755 19,654 19.1 Total 95,290 701 253 301 2,472 99,017 265,198 37.3 District Crop Storage 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Tanga Region. 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Tanga Region District Mechanisation / LST District Irrigation Technology 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 228 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Lushoto 36,643 140 0 0 581 37,364 86,580 43.2 Korogwe 19,470 84 107 0 599 20,260 45,990 44.1 Muheza 8,033 183 0 0 213 8,429 49,195 17.1 Tanga 254 0 0 0 445 699 8,914 7.8 Pangani 499 177 0 0 143 818 7,128 11.5 Handeni 1,353 0 0 643 2,125 4,121 47,739 8.6 Kilindi 2,590 0 0 0 49 2,639 19,654 13.4 Total 68,840 584 107 643 4,156 74,331 265,198 28.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Vermin Control 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Tanga Region District Agro-progressing Total Number of households % of total number of households 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga Region District Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 229 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 3,025 710 859 4,594 86,580 5.3 Korogwe 2,031 958 1,017 4,007 45,990 8.7 Muheza 927 0 59 986 49,195 2.0 Tanga 36 0 404 440 8,914 4.9 Pangani 162 48 167 377 7,128 5.3 Handeni 212 316 2,774 3,302 47,739 6.9 Kilindi 293 48 783 1,125 19,654 5.7 Total 6,685 2,082 6,064 14,831 265,198 6 % 12,337 3,841 11,190 27,368 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 2,877 713 0 0 433 4,022 86,580 4.6 Korogwe 2,478 1,384 0 0 1,124 4,986 45,990 10.8 Muheza 1,843 720 59 78 0 2,701 49,195 5.5 Tanga 0 0 0 0 440 440 8,914 4.9 Pangani 0 48 0 0 191 239 7,128 3.4 Handeni 106 418 0 0 2,672 3,196 47,739 6.7 Kilindi 97 0 0 0 734 832 19,654 4.2 Total 7,400 3,284 59 78 5,594 16,415 265,198 6.2 Received Adopted % Received Adopted % Received Adopted % Lushoto 41,407 38,827 94 26,611 5,749 22 33,324 11,795 35 Korogwe 37,795 36,111 96 14,048 1,391 10 20,486 4,442 22 Muheza 20,695 16,121 78 7,189 824 11 10,493 4,477 43 Tanga 1,169 1,061 91 565 213 38 308 153 50 Pangani 2,625 2,533 97 1,626 637 39 764 372 49 Handeni 10,231 9,919 97 2,925 812 28 1,477 427 29 Kilindi 5,209 4,476 86 2,193 191 9 1,073 293 27 Total 119,130 109,047 92 55,156 9,817 18 67,925 21,958 32 District 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Tanga Region Beekeeping District District Spacing Use of Agrochemicals 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tanga Region Fish Farming Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 230 Received Adopted % Received Adopted % Received Adopted % Lushoto 39,095 20,744 53 23,283 4,031 17 36,633 12,112 33 Korogwe 30,635 9,858 32 11,666 1,073 9 30,299 8,881 29 Muheza 13,699 4,629 34 7,145 553 8 16,716 2,664 16 Tanga 839 494 59 168 51 30 892 447 50 Pangani 1,459 529 36 884 172 19 1,941 1,065 55 Handeni 4,923 1,270 26 625 213 34 8,085 3,666 45 Kilindi 1,661 341 21 537 195 36 3,553 726 20 Total 92,312 37,865 41 44,307 6,288 14 98,120 29,562 30 Received Adopted % Received Adopted % Received Adopted % Lushoto 1,713 714 42 25,453 9,346 37 39,697 37,242 94 Korogwe 8,438 793 9 16,525 4,665 28 28,757 20,086 70 Muheza 1,876 85 5 4,165 585 14 15,888 10,513 66 Tanga 291 32 11 240 51 21 607 528 87 Pangani 583 176 30 254 145 57 1,909 1,697 89 Handeni 3,419 511 15 851 428 50 6,500 4,500 69 Kilindi 1,024 97 9 485 193 40 3,804 2,436 64 Total 17,344 2,408 14 47,974 15,413 32 97,163 77,002 79 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tanga Region 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tanga region District Mechanisation / LST Irrigation Technology Crop Storage District Organic Fertilizer Use Inorganic Fertilizer Use Use of Improved Seed Tanzania Agriculture Sample Census-2003 Tanga Appendix II 231 Received Adopted % Received Adopted % Received Adopted % Lushoto 7,975 5,521 69 36,200 34,752 96 28,547 15,683 55 Korogwe 27,020 22,813 84 19,441 16,567 85 13,222 2,949 22 Muheza 11,855 9,030 76 8,370 6,197 74 6,810 3,120 46 Tanga 801 685 86 254 297 117 274 241 88 Pangani 2,031 1,843 91 652 520 80 534 470 88 Handeni 3,300 3,086 94 1,357 1,678 124 3,231 1,252 39 Kilindi 2,735 2,540 93 2,639 2,493 94 1,317 195 15 Total 55,716 45,519 82 68,912 62,505 91 53,935 23,909 44 Received Adopted % Received Adopted % Received Adopted % Lushoto 28,547 15,683 55 2,282 718 31 2,131 0 0 Korogwe 13,222 2,949 22 2,354 178 8 3,336 531 16 Muheza 6,810 3,120 46 596 0 0 2,530 449 18 Tanga 274 241 88 36 0 0 0 0 0 Pangani 534 470 88 138 162 117 0 0 0 Handeni 3,231 1,252 39 102 0 0 204 104 51 Kilindi 1,317 195 15 341 147 43 97 0 0 Total 53,935 23,909 44 5,849 1,205 21 8,297 1,085 13 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Agro-progressing Agro-forestry 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Tanga region District Agro-forestry Beekeeping Fish Farming Tanzania Agriculture Sample Census-2003 Tanga Appendix II 232 Number % Number % Number % Number % Number % Lushoto 3,038 7 23,310 55 14,941 35 140 0 702 2 Korogwe 4,187 11 26,875 70 6,943 18 495 1 0 0 Muheza 2,093 10 13,998 66 3,703 18 406 2 892 4 Tanga 63 5 841 66 234 18 127 10 0 0 Pangani 104 4 1,527 54 1,141 41 35 1 0 0 Handeni 538 5 5,684 55 3,909 38 203 2 0 0 Kilindi 194 4 3,647 68 1,417 26 98 2 0 0 Total 10,217 8 75,884 62 32,287 27 1,505 1 1,594 1 Total Number % Number % Number % Number % Number % % Number Lushoto 42,132 100 0 0 0 0 0 0 0 0 0 42,132 Korogwe 37,886 99 321 1 0 0 104 0 0 0 0 38,407 Muheza 20,822 99 90 0 0 0 0 0 0 0 0 21,001 Tanga 1,194 94 10 1 0 0 21 2 10 1 3 1,266 Pangani 2,677 96 18 1 0 0 24 1 22 1 2 2,788 Handeni 9,624 94 0 0 107 1 284 3 215 2 0 10,231 Kilindi 5,258 98 0 0 0 0 0 0 49 1 1 5,356 Total 119,592 99 438 0 107 0 433 0 296 0 0 121,180 15.3 EXTENSION MESSAGES: Number of Agriculture Households By Source of Crop Extension Messages and District During th 2002/03 Agriculture Year, Tanga Region District Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable 15.1 CROP EXTENSION: Number of Households By Quality of Extension Services and District During the 2002/03 Agricultural Year, Tanga Region District Very Good Good Average Poor No Good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 233 Government NGO / Development Project Cooperative Large Scale Farm Other Not applicable Total receiving advice Total Number of households % of total number of households Lushoto 41,406 0 0 0 0 0 41,406 86,580 48 Korogwe 37,461 321 0 0 0 97 37,878 45,990 82 Muheza 20,606 0 0 0 0 89 20,695 49,195 42 Tanga 1,148 0 0 21 0 32 1,201 8,914 13 Pangani 2,538 18 0 24 22 47 2,649 7,128 37 Handeni 9,520 0 107 284 215 0 10,127 47,739 21 Kilindi 5,160 0 0 0 49 49 5,258 19,654 27 Total 117,838 339 107 329 287 313 119,213 265,198 45 % 99 0 0 0 0 0 100 Government NGO / Development Project Large Scale Farm Other Not applica ble Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 % 91.8 1.1 0.0 0.2 6.9 100 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Plant Spacing by Source and District During the 2002/03 Agriculture Year, Tanga Region 15.5 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals District Spacing Tanzania Agriculture Sample Census-2003 Tanga Appendix II 234 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 31,324 2,439 145 0 432 34,340 86,580 39.7 Korogwe 19,453 720 0 107 307 20,587 45,990 44.8 Muheza 9,849 630 0 0 214 10,693 49,195 21.7 Tanga 340 0 0 0 323 663 8,914 7.4 Pangani 665 142 0 0 95 901 7,128 12.6 Handeni 1,574 217 0 0 2,253 4,044 47,739 8.5 Kilindi 926 49 0 0 489 1,464 19,654 7.5 Total 64,130 4,197 145 107 4,113 72,692 265,198 27.4 % 88.2 5.8 0.2 0.1 5.7 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 % 93.8 2.3 0.2 0.1 3.6 100.0 Erosion Control 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Erosion Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Organic Fertilizer Use 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 235 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 23,282 146 0 146 2,171 25,745 86,580 29.7 Korogwe 12,384 194 0 107 1,918 14,602 45,990 31.8 Muheza 7,325 0 0 0 986 8,311 49,195 16.9 Tanga 246 0 21 0 381 647 8,914 7.3 Pangani 862 0 0 0 164 1,027 7,128 14.4 Handeni 1,033 217 0 0 2,559 3,809 47,739 8.0 Kilindi 586 0 0 0 637 1,222 19,654 6.2 Total 45,718 557 21 253 8,815 55,363 265,198 20.9 % Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 District Use of Improved Seeds 15.6 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Inorganic Fertilizer Use by Source and District During the 2002/03 Agriculture Year, Tanga Region District Inorganic Fertilizer Use 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 236 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 3,304 0 0 146 1,441 4,891 86,580 6 Korogwe 8,660 107 0 107 1,225 10,098 45,990 22 Muheza 1,972 0 0 0 215 2,187 49,195 4 Tanga 338 0 23 0 321 681 8,914 8 Pangani 494 65 24 0 167 750 7,128 11 Handeni 3,331 108 188 0 2,351 5,979 47,739 13 Kilindi 975 0 0 49 832 1,857 19,654 9 Total 19,073 280 235 302 6,552 26,443 265,198 10 % 72 1 1 1 25 100 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 25,905 708 436 27,049 86,580 31 Korogwe 17,626 506 1,227 19,360 45,990 42 Muheza 4,716 0 584 5,300 49,195 11 Tanga 250 0 350 600 8,914 7 Pangani 254 72 164 490 7,128 7 Handeni 1,055 0 2,350 3,405 47,739 7 Kilindi 534 49 734 1,317 19,654 7 Total 50,340 1,335 5,846 57,521 265,198 22 % 88 2 10 100 15.10 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Mechanisation/LST by Source and District During the 2002/03 Agriculture Year, Tanga Region District Irrigation Technology District Mechanisation / LST 15.11 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Irrigation Technology by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 237 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 39,553 0 0 144 146 39,844 86,580 46.0 Korogwe 28,076 210 204 0 495 28,986 45,990 63.0 Muheza 15,724 59 0 0 322 16,106 49,195 32.7 Tanga 607 0 0 0 248 855 8,914 9.6 Pangani 1,789 73 0 0 143 2,004 7,128 28.1 Handeni 6,176 213 0 107 971 7,467 47,739 15.6 Kilindi 3,364 146 49 49 146 3,755 19,654 19.1 Total 95,290 701 253 301 2,472 99,017 265,198 37.3 % 96.2 0.7 0.3 0.3 2.5 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 District Crop Storage 15.12 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Crop Storage by Source and District During the 2002/03 Agriculture Year, Tanga Region. District Vermin Control 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 238 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,643 140 0 0 581 37,364 86,580 43.2 Korogwe 19,470 84 107 0 599 20,260 45,990 44.1 Muheza 8,033 183 0 0 213 8,429 49,195 17.1 Tanga 254 0 0 0 445 699 8,914 7.8 Pangani 499 177 0 0 143 818 7,128 11.5 Handeni 1,353 0 0 643 2,125 4,121 47,739 8.6 Kilindi 2,590 0 0 0 49 2,639 19,654 13.4 Total 68,840 584 107 643 4,156 74,331 265,198 28.0 % 92.6 0.8 0.1 0.9 5.6 100.0 Government NGO / Development Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 Agro-progressing Agro-forestry 15.14 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Processing by Source and District During the 2002/03 Agriculture Year, Tanga Region District 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga region District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 239 Government NGO / Development Project Not applicable Total Total Number of households % of total number of households Lushoto 3,025 710 859 4,594 86,580 5.3 Korogwe 2,031 958 1,017 4,007 45,990 8.7 Muheza 927 0 59 986 49,195 2.0 Tanga 36 0 404 440 8,914 4.9 Pangani 162 48 167 377 7,128 5.3 Handeni 212 316 2,774 3,302 47,739 6.9 Kilindi 293 48 783 1,125 19,654 5.7 Total 6,685 2,082 6,064 14,831 265,198 5.6 % 45.1 14.0 40.9 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 2,877 713 0 0 433 4,022 86,580 4.6 Korogwe 2,478 1,384 0 0 1,124 4,986 45,990 10.8 Muheza 1,843 720 59 78 0 2,701 49,195 5.5 Tanga 0 0 0 0 440 440 8,914 4.9 Pangani 0 48 0 0 191 239 7,128 3.4 Handeni 106 418 0 0 2,672 3,196 47,739 6.7 Kilindi 97 0 0 0 734 832 19,654 4.2 Total 7,400 3,284 59 78 5,594 16,415 265,198 6.2 % 45.1 20.0 0.4 0.5 34.1 100.0 15.16 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Bee Keeping by Source and District During the 2002/03 Agriculture Year, Tanga Region Beekeeping Fish Farming 15.17 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Fish Farming by Source and District During the 2002/03 Agriculture Year, Tanga Region District District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 240 Received Adopted % Received Adopted % Received Adopted % Lushoto 41,407 38,827 94 26,611 5,749 22 33,324 11,795 35 Korogwe 37,795 36,111 96 14,048 1,391 10 20,486 4,442 22 Muheza 20,695 16,121 78 7,189 824 11 10,493 4,477 43 Tanga 1,169 1,061 91 565 213 38 308 153 50 Pangani 2,625 2,533 97 1,626 637 39 764 372 49 Handeni 10,231 9,919 97 2,925 812 28 1,477 427 29 Kilindi 5,209 4,476 86 2,193 191 9 1,073 293 27 Total 119,130 109,047 92 55,156 9,817 18 67,925 21,958 32 Received Adopted % Received Adopted % Received Adopted % Lushoto 39,095 20,744 53 23,283 4,031 17 36,633 12,112 33 Korogwe 30,635 9,858 32 11,666 1,073 9 30,299 8,881 29 Muheza 13,699 4,629 34 7,145 553 8 16,716 2,664 16 Tanga 839 494 59 168 51 30 892 447 50 Pangani 1,459 529 36 884 172 19 1,941 1,065 55 Handeni 4,923 1,270 26 625 213 34 8,085 3,666 45 Kilindi 1,661 341 21 537 195 36 3,553 726 20 Total 92,312 37,865 41 44,307 6,288 14 98,120 29,562 30 15.19 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 2) During the 2002/03 Agriculture Year, Tanga Region District Use of Improved Seed Inorganic Fertilizer Use Organic Fertilizer Use 15.18 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 1) During the 2002/03 Agriculture Year, Tanga Region District Spacing Use of Agrochemicals Erosion Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 241 Received Adopted % Received Adopted % Received Adopted % Lushoto 1,713 714 42 25,453 9,346 37 39,697 37,242 94 Korogwe 8,438 793 9 16,525 4,665 28 28,757 20,086 70 Muheza 1,876 85 5 4,165 585 14 15,888 10,513 66 Tanga 291 32 11 240 51 21 607 528 87 Pangani 583 176 30 254 145 57 1,909 1,697 89 Handeni 3,419 511 15 851 428 50 6,500 4,500 69 Kilindi 1,024 97 9 485 193 40 3,804 2,436 64 Total 17,344 2,408 14 47,974 15,413 32 97,163 77,002 79 Received Adopted % Received Adopted % Received Adopted % Lushoto 7,975 5,521 69 36,200 34,752 96 28,547 15,683 55 Korogwe 27,020 22,813 84 19,441 16,567 85 13,222 2,949 22 Muheza 11,855 9,030 76 8,370 6,197 74 6,810 3,120 46 Tanga 801 685 86 254 297 117 274 241 88 Pangani 2,031 1,843 91 652 520 80 534 470 88 Handeni 3,300 3,086 94 1,357 1,678 124 3,231 1,252 39 Kilindi 2,735 2,540 93 2,639 2,493 94 1,317 195 15 Total 55,716 45,519 82 68,912 62,505 91 53,935 23,909 44 15.21 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 4) During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Agro-progressing Agro-forestry 15.20 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 3) During the 2002/03 Agriculture Year, Tanga region Crop Storage Irrigation Technology Mechanisation / LST District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 242 Received Adopted % Received Adopted % Received Adopted % Lushoto 28,547 15,683 55 2,282 718 31 2,131 0 0 Korogwe 13,222 2,949 22 2,354 178 8 3,336 531 16 Muheza 6,810 3,120 46 596 0 0 2,530 449 18 Tanga 274 241 88 36 0 0 0 0 0 Pangani 534 470 88 138 162 117 0 0 0 Handeni 3,231 1,252 39 102 0 0 204 104 51 Kilindi 1,317 195 15 341 147 43 97 0 0 Total 53,935 23,909 44 5,849 1,205 21 8,297 1,085 13 15.22 CROP EXTENSION: Number of Agriculture Households Receiving and Adopting Extension Messages by Type of Message and District (Part 5) During the 2002/03 Agriculture Year, Tanga region District Fish Farming Beekeeping Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 243 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 26,180 140 0 0 728 27,049 86,580 31.2 Korogwe 14,577 285 0 107 921 15,890 45,990 34.6 Muheza 7,374 0 0 0 292 7,666 49,195 15.6 Tanga 624 0 21 0 201 845 8,914 9.5 Pangani 1,626 0 0 0 119 1,745 7,128 24.5 Handeni 3,026 217 0 0 1,712 4,956 47,739 10.4 Kilindi 2,193 0 0 0 196 2,388 19,654 12.2 Total 55,601 643 21 107 4,169 60,540 265,198 22.8 % 91.8 1.1 0.0 0.2 6.9 100.0 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 37,396 1,560 0 0 292 39,248 86,580 45.3 Korogwe 29,487 401 104 0 1,116 31,107 45,990 67.6 Muheza 13,274 0 0 0 396 13,670 49,195 27.8 Tanga 733 42 43 10 190 1,018 8,914 11.4 Pangani 1,414 45 0 0 119 1,577 7,128 22.1 Handeni 4,918 108 0 107 1,062 6,196 47,739 13.0 Kilindi 1,611 49 0 0 196 1,856 19,654 9.4 Total 88,833 2,206 147 117 3,370 94,673 265,198 35.7 % 93.8 2.3 0.2 0.1 3.6 100.0 District Organic Fertilizer Use 15.4 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agrochemicals by Source and District During the 2002/03 Agriculture Year, Tanga Region District Use of Agrochemicals 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Organic Fertiliser Use by Source and District During the 2002/03 Agriculture Year, Tanga Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 244 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 36,343 292 0 0 286 36,921 86,580 42.6 Korogwe 28,534 721 0 0 1,229 30,484 45,990 66.3 Muheza 15,977 0 0 59 656 16,692 49,195 33.9 Tanga 839 19 21 23 61 963 8,914 10.8 Pangani 1,848 45 48 0 71 2,012 7,128 28.2 Handeni 7,377 216 188 108 427 8,316 47,739 17.4 Kilindi 3,262 49 0 49 196 3,555 19,654 18.1 Total 94,180 1,341 257 239 2,924 98,942 265,198 37.3 % 95.2 1.4 0.3 0.2 3.0 100.0 15.7 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Use of Improved Seeds by Source and District During the 2002/03 Agriculture Year District Use of Improved Seeds Tanzania Agriculture Sample Census-2003 Tanga Appendix II 245 Government NGO / Developmen t Project Cooperative Large Scale Farm Not applicable Total Total Number of households % of total number of households Lushoto 26,965 1,283 0 0 578 28,826 86,580 33.3 Korogwe 12,040 1,173 107 107 611 14,040 45,990 30.5 Muheza 5,896 720 0 0 217 6,833 49,195 13.9 Tanga 274 0 0 0 283 557 8,914 6.3 Pangani 492 65 0 0 167 724 7,128 10.2 Handeni 2,824 213 0 96 2,357 5,491 47,739 11.5 Kilindi 1,268 97 0 0 0 1,366 19,654 6.9 Total 49,760 3,553 107 203 4,213 57,837 265,198 21.8 % 86.0 6.1 0.2 0.4 7.3 100.0 15.15 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Agro-Forestry by Source and District During the 2002/03 Agriculture Year, Tanga region District Agro-forestry Tanzania Agriculture Sample Census-2003 Tanga Appendix II 246 Government NGO / Development Project Large Scale Farm Other Not applicable Total Total Number of households % of total number of households Lushoto 11,037 140 0 0 2,332 13,509 86,580 15.6 Korogwe 27,016 401 0 0 1,115 28,531 45,990 62.0 Muheza 11,579 88 0 0 129 11,797 49,195 24.0 Tanga 801 0 0 0 259 1,060 8,914 11.9 Pangani 1,961 0 22 0 120 2,103 7,128 29.5 Handeni 2,289 106 476 429 1,399 4,699 47,739 9.8 Kilindi 2,735 0 0 0 48 2,783 19,654 14.2 Total 57,417 735 498 429 5,403 64,482 265,198 24.3 % 89.0 1.1 0.8 0.7 8.4 100.0 15.13 CROP EXTENSION: Number of Agriculture Households Receiving Advice on Vermin Control by Source and District During the 2002/03 Agriculture Year, Tanga Region District Vermin Control Tanzania Agriculture Sample Census-2003 Tanga Appendix II 247 ANIMAL CONTRIBUTION TO CROP PRODUCTION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 248 Using draft animal Not using draft animal No of households % No of households % Korogwe 395 1 45,595 99 45,990 Kilindi 49 0 19,605 100 19,654 Lushoto 0 0 86,580 100 86,580 Muheza 0 0 49,195 100 49,195 Tanga 0 0 8,914 100 8,914 Pangani 0 0 7,128 100 7,128 Handeni 0 0 47,739 100 47,739 Total 443 0 264,755 100 265,198 Number Owned Number Used Area Cultivated (acres) Number Owned Number Used Area Cultivated (acres) Korogwe 592 987 1,973.4 592 987 1,973.4 Kilindi 146 146 679.9 146 146 679.9 Total 738 1,132 2,653.3 738 1,132 2,653.3 Using Organic Fertilizer Not Using Organic Fertilizer Number % Number % Lushoto 31,882 37 54,406 63 86,288 Korogwe 9,889 22 34,951 78 44,841 Muheza 5,076 10 44,040 90 49,116 Tanga 1,302 15 7,576 85 8,878 Pangani 245 3 6,883 97 7,128 Handeni 1,894 4 45,526 96 47,420 Kilindi 1,215 6 18,439 94 19,654 Total 51,503 20 211,820 80 263,323 Area (Ha) % Area (Ha) % Area (%) % Lushoto 13,238 60 1,035 19 14,273 52 Korogwe 4,160 19 1,440 27 5,600 20 Muheza 2,467 11 340 6 2,807 10 Tanga 657 3 105 2 762 3 Pangani 147 1 17 0 164 1 Handeni 896 4 772 14 1,668 6 Kilindi 389 2 1,668 31 2,057 8 Total 21,954 100 5,377 100 27,331 100 Total households 17.2 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Type of Draft By Number Owned, Used and Area Cultivated (acres) By District during 2002/03 agriculture year, Tanga Region 17.1 ANIMAL CONTRIBUTION TO CROP PRODUCTION: Number of agriculoture households using draft animal to cultive land by District during 2002/03 agriculture year, Tanga Region District Type of Craft Oxen Total 17.3 ANIMAL CONTRIBUTION TO CROPS: Number of Crop Growing households using organic fertilizer by District during 2002/03 agriculture year, Tanga region District Did you apply organic fertilizer during 2002/03? Total number of crop growing households 17.4 ANIMAL CONTRIBUTION TO CROPS: Area of farm yard manure and Compost Application by District during 2002/03 agriculture year, Tanga Region District Farm Yard Manure Area Applied Compost Area Applied Total Area aplied with Organic Fertilizers Tanzania Agriculture Sample Census-2003 Tanga Appendix II 249 CATTLE PRODUCTION Tanzania AgricultureSample Census-2003 Tanga Appendix II 250 Number % Number % Lushoto 33,672 39 52,908 61 86,580 37,986 Korogwe 9,314 20 36,676 80 45,990 14,885 Muheza 3,778 8 45,416 92 49,195 11,365 Tanga 1,093 12 7,821 88 8,914 1,939 Pangani 191 3 6,936 97 7,128 911 Handeni 5,231 11 42,508 89 47,739 14,886 Kilindi 2,484 13 17,170 87 19,654 4,820 Total 55,762 21 209,436 79 265,198 86,792 Number % Number % 1-5 45,258 81 107,005 28 2 6-10 4,931 9 37,621 10 8 11-15 1,310 2 16,539 4 13 16-20 1,632 3 30,286 8 19 21-30 1,253 2 30,831 8 25 31-40 389 1 14,253 4 37 41-50 49 0 2,448 1 50 51-60 374 1 21,053 6 56 61-100 286 1 22,417 6 78 151+ 280 1 95,883 25 342 Total 55,762 100 378,338 100 7 Number % Number % Number % Number % Regions Number of Indigenous % Number of Improved Beef % Number of Improved Dairy % Total % Bulls 25,822 92.2 175 0.6 2,022 7.2 28,018 7.4 Cows 142,064 92.6 0 0.0 11,357 7.4 153,421 40.6 Steers 12,100 92.6 123 0.9 846 6.5 13,069 3.5 Heifers 81,149 93.5 0 0.0 5,654 6.5 86,803 22.9 Male Calves 43,500 91.8 0 0.0 3,862 8.2 47,362 12.5 Female Calves 45,576 91.8 0 0.0 4,088 8.2 49,664 13.1 Total 350,210 92.6 298 0.1 27,829 7.4 378,338 100.0 18.3: Number of Households Rearing Cattle, Heads of Cattle and Average Heads per Household by Herd Size; on 1st October 2003 Total Improved Beef Cattle Herd Size Cattle Rearing Households Heads of Cattle Average Number Per Household Table 18.4: Total Number of Cattle by Category and Type of Cattle; on 1st October 2003 District Total Agriculture households Total livestock keeping households 18.1 CATTLE PRODUCTION: Total Number Households rearing Cattle by District during 2002/03 agriculture year, Tanga Region Households Rearing Cattle Households Not Rearing Cattle Improved Dairy Cattle Category of cattle Indigenous Cattle Tanzania AgricultureSample Census-2003 Tanga Appendix II 251 Handeni 5,125 106,690 99.8 0 0 0.0 106 212 0.2 5,231 106,901 28.3 Korogwe 8,895 72,264 97.3 0 0 0.0 720 1,975 2.7 9,314 74,238 19.6 Lushoto 27,444 60,120 79.2 143 143 0.2 8,264 15,648 20.6 33,672 75,911 20.1 Muheza 2,235 57,618 90.9 0 0 0.0 1,800 5,736 9.1 3,778 63,355 16.7 Kilindi 2,484 46,019 100.0 0 0 0.0 0 0 0.0 2,484 46,019 12.2 Tanga 663 7,003 63.6 52 155 1.4 526 3,854 35.0 1,093 11,012 2.9 Pangani 101 497 55.1 0 0 0.0 114 405 44.9 191 901 0.2 Total 46,947 350,210 92.6 195 298 0.1 11,529 27,829 7.4 55,762 378,338 100.0 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 3,603 22,614 1,004 15,192 7,762 9,945 60,120 Korogwe 4,149 30,262 1,544 14,027 10,130 12,153 72,264 Muheza 3,372 30,612 244 10,920 5,637 6,833 57,618 Tanga 772 2,805 570 1,272 793 792 7,003 Pangani 37 74 37 242 70 37 497 Handeni 7,938 38,925 5,146 31,644 12,872 10,164 106,690 Kilindi 5,951 16,771 3,556 7,852 6,237 5,652 46,019 Total 25,822 142,064 12,100 81,149 43,500 45,576 350,210 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 727 6,523 . 3,622 2,750 2,026 15,648 Korogwe 422 720 97 320 107 308 1,975 Muheza 301 2,475 227 1,072 496 1,165 5,736 Tanga 550 1,394 481 544 484 400 3,854 Pangani 21 138 42 96 24 84 405 Handeni . 106 . . . 106 212 Kilindi . . . . . . . Total 2,022 11,357 846 5,654 3,862 4,088 27,829 18.6: Total Number of Dairy Cattle by Category of cattle and District as on 1st October 2003 District Number of Improved Dairy Cattle Number of Cattle Number of households Indigenous 18.2 CATTLE PRODUCTION: Total Number of Cattle by Type and District As of 1st October 2003 % Number of Cattle Number of households % Number of households Number of Cattle Number of Cattle Total Cattle Dairy District % % Number of households Beef 18.5: Total Number of indigenous Cattle by Category of Cattle and District as on 1st October 2003 District Category - Indigenous Tanzania AgricultureSample Census-2003 Tanga Appendix II 252 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 143 . . . . . 143 Korogwe . . . . . . . Muheza . . . . . . . Tanga 32 . 123 . . . 155 Pangani . . . . . . . Handeni . . . . . . . Kilindi . . . . . . . Total 175 . 123 . . . 298 Bulls Cows Steers Heifers Male Calves Female Calves Total Lushoto 4,473 29,138 1,004 18,814 10,512 11,971 75,911 Korogwe 4,570 30,982 1,640 14,347 10,237 12,461 74,238 Muheza 3,673 33,087 471 11,992 6,133 7,998 63,355 Tanga 1,354 4,199 1,174 1,816 1,277 1,192 11,012 Pangani 58 212 78 338 94 121 901 Handeni 7,938 39,031 5,146 31,644 12,872 10,269 106,901 Kilindi 5,951 16,771 3,556 7,852 6,237 5,652 46,019 Total 28,018 153,421 13,069 86,803 47,362 49,664 378,338 18.8: Total Number of Cattle by Category and District as on 1st October 2003 District Total Cattle District Category - Number of Improved Beef 18.7: Total Number of Beef Cattle by Category of Cattle and District as on 1st October 2003 Tanzania AgricultureSample Census-2003 Tanga Appendix II 253 GOATS PRODUCTION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 254 Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats % Number of households Number of Goats Lushoto 18,308 60,498 82 280 9,049 12 283 3,901 5.3 18,447 73,449 Korogwe 12,551 85,858 99 99 99 0 291 484 0.6 12,648 86,441 Muheza 11,478 94,480 98 246 1,222 1 121 493 0.5 11,478 96,195 Tanga 1,445 10,287 99 0 . 0 51 103 1.0 1,445 10,390 Pangani 839 10,278 99 0 . 0 80 80 0.8 839 10,357 Handeni 18,159 163,482 96 204 1,529 1 845 5,849 3.4 18,159 170,860 Kilindi 5,212 65,615 98 97 1,166 2 49 147 0.2 5,212 66,928 Total 67,991 490,499 95 925 13,064 3 1,720 11,057 2.1 68,227 514,620 Number % Number % 1-4 684,045 50.1 2,742,006 23.2 4.0 5-9 412,350 30.2 3,268,273 27.7 7.9 10-14 143,889 10.5 1,890,115 16.0 13.1 15-19 52,541 3.8 957,755 8.1 18.2 20-24 31,066 2.3 721,644 6.1 23.2 25-29 13,098 1.0 395,397 3.3 30.2 30-39 13,013 1.0 480,002 4.1 36.9 40+ 16,615 1.2 1,351,536 11.4 81.3 Total 1,366,618 100.0 11,806,728 100.0 8.6 Improved for Meat Herd Size Goat Rearing Households Head of Goats Average per Household 19.2 Number of Households Rearing Goats and Heads of Goats by Herd Size on 1st October 2003 Total 19.1 GOAT PRODUCTION: Total Number of Goats by goat type and District as on 1st October 2003 District Indigenous Improved Dairy Tanzania Agriculture Sample Census-2003 Tanga Appendix II 255 Number % Number % Number % Number % Billy Goats 62,759 82.5 9,164 12.0 4,180 5.5 76,102 15 She Goats 256,571 99.1 331 0.1 1,884 0.7 258,786 50 Castrated G 28,226 98.5 0.0 423 1.5 28,649 6 Male Kid 65,381 96.3 2,234 3.3 258 0.4 67,873 13 She Kid 77,562 93.2 1,335 1.6 4,312 5.2 83,209 16 Total 490,499 95.3 13,064 2.5 11,057 2.1 514,620 100 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 6,879 437 36,646 7,997 8,539 60,498 Korogwe 8,660 1,856 41,725 13,967 19,650 85,858 Muheza 11,368 6,186 51,204 13,261 12,461 94,480 Tanga 1,613 1,301 5,019 1,319 1,035 10,287 Pangani 1,497 179 5,647 1,672 1,283 10,278 Handeni 22,561 11,839 87,103 16,701 25,278 163,482 Kilindi 10,181 6,428 29,226 10,465 9,315 65,615 Total 62,759 28,226 256,571 65,381 77,562 490,499 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 8,347 . . 702 . 9,049 Korogwe . . . 99 . 99 Muheza 156 . 234 413 418 1,222 Tanga . . . . . . Pangani . . . . . . Handeni 611 . . . 917 1,529 Kilindi 49 . 97 1,020 . 1,166 Total 9,164 . 331 2,234 1,335 13,064 District Number of Improved Meat Goats 19.3 Total Number of Goats by Category and Type of Goat on 1st October 2003 Category of Goats Indigenous Goats Improved Meat Goats Improved Dairy Goats Total 19.4 Total Number of Indigenous Goat by Category and District on 1st October 2003 District Type 19.5 Total Number of Improved Goat for Meat by Category and District on 1st October 2003 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 256 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 3,609 292 . . . 3,901 Korogwe . . 484 . . 484 Muheza . . 258 78 156 493 Tanga . 23 23 57 . 103 Pangani 43 . . 19 18 80 Handeni 528 108 1,070 104 4,039 5,849 Kilindi . . 49 . 98 147 Total 4,180 423 1,884 258 4,312 11,057 Billy Goats Castrated Goats She Goats Male Kids She Kids Total Lushoto 18,835.52 729.41 36,646.29 8,698.66 8,539.13 73,449.01 Korogwe 8,660.33 1,855.64 42,209.41 14,065.41 19,650.27 86,441.06 Muheza 11,524.54 6,186.39 51,696.48 13,752.16 13,034.94 96,194.52 Tanga 1,612.70 1,323.78 5,041.44 1,376.74 1,034.97 10,389.63 Pangani 1,539.24 178.62 5,647.18 1,690.63 1,301.64 10,357.32 Handeni 23,700.82 11,947.11 88,172.98 16,804.35 30,235.00 170,860.25 Kilindi 10,229.16 6,427.91 29,372.40 11,484.89 9,413.38 66,927.74 Total 76,102.31 28,648.85 258,786.17 67,872.86 83,209.33 514,619.53 19.6 Total Number of Improved Dairy Goats by Category and District on 1st October 2003 District Number of Improved Dairy Goats District Total Goats 19.7 Total Number of Goats by Category and District on 1st October 2003 Tanzania Agriculture Sample Census-2003 Tanga Appendix II 257 SHEEP PRODUCTION Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 258 Number % Number % Number % Ram 16,121 61 10,275 39 26,396 16 Castrated Sheep 11,043 100 . 0 11,043 7 She Sheep 87,623 98 1,400 2 89,023 54 Male Lamb 15,318 84 2,945 16 18,262 11 She Lamb 19,292 99 194 1 19,485 12 Total 149,396 91 14,813 9 164,209 100 Number % Number % Lushoto 24,660 28 61,919 72 86,580 37,986 Korogwe 5,569 12 40,421 88 45,990 14,885 Muheza 3,027 6 46,168 94 49,195 11,365 Tanga 109 1 8,804 99 8,914 1,939 Pangani 61 1 7,067 99 7,128 911 Handeni 640 1 47,099 99 47,739 14,886 Kilindi 1,314 7 18,340 93 19,654 4,820 Total 35,381 13 229,817 87 265,198 86,792 Number % Number % Number % Lushoto 60,715 94 4,028 6 64,742 39 Korogwe 24,975 71 10,391 29 35,367 22 Muheza 25,059 100 81 0 25,140 15 Tanga 988 98 23 2 1,010 1 Pangani 158 100 0 0 158 0 Handeni 19,570 100 0 0 19,570 12 Kilindi 17,932 98 290 2 18,222 11 Total 149,396 91 14,813 9 164,209 100 Number of Households Average Sheep Number of Households Average Sheep Lushoto 24,371 2 1,157 3 24,660 3 Korogwe 5,569 4 188 55 5,569 6 Muheza 3,027 8 81 1 3,027 8 Tanga 87 11 23 1 109 9 Pangani 61 3 0 0 61 3 Handeni 640 31 0 0 640 31 Kilindi 1,314 14 97 3 1,314 14 Total 35,068 4 1,547 10 35,381 5 20.1 Total Number of Sheep by Breed Type on 1st October 2003 20.2 Number of Households Raising or Managing Sheep by District on 1st October 2003 District Households Raising Sheep 20.4 Number of Sheep per Household by Category and Region as of 1st October 2003 District Number of Indigenous Sheep Indigenous Sheep Improved for Mutton Sheep Breed Number of Indigenous Sheep Number of Improved Mutton Sheep District Total Sheep Households Not Raising Sheep Number of Agriculture Households Total Livestock Keeping Households 20.3 Number of Sheep by Type of Sheep and District on 1st October 2003. Total Households Raising Sheep Average Sheep Number of Improved for Mutton Sheep Total Sheep Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 259 Herd Size Number of Households % Number of Sheep % Average Number per Household 1-4 27,110 77 57,107 35 2 5-9 5,431 15 33,298 20 6 10-14 1,649 5 19,175 12 12 15-19 296 1 4,636 3 16 20-24 227 1 4,764 3 21 25-29 91 0 2,559 2 28 30-39 233 1 7,559 5 32 40+ 344 1 35,111 21 102 Total 35,381 100 164,209 100 5 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 6,070 1,722 40,668 5,750 6,504 60,715 Korogwe 3,741 643 14,093 3,295 3,204 24,975 Muheza 2,684 604 14,765 2,384 4,622 25,059 Tanga 64 33 614 97 179 988 Pangani 61 . 98 . . 158 Handeni 1,067 5,357 10,269 1,600 1,277 19,570 Kilindi 2,436 2,684 7,116 2,191 3,506 17,932 Total 16,121 11,043 87,623 15,318 19,292 149,396 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 144 . 1,296 2,588 . 4,028 Korogwe 10,130 . . 261 . 10,391 Muheza . . 81 . . 81 Tanga . . 23 . . 23 Pangani . . . . . . Handeni . . . . . . Kilindi . . . 96 194 290 Total 10,275 . 1,400 2,945 194 14,813 Rams Castrated Sheep She Sheep Male Lambs She Lambs Total Lushoto 6,214 1,722 41,964 8,338 6,504 64,742 Korogwe 13,871 643 14,093 3,556 3,204 35,367 Muheza 2,684 604 14,846 2,384 4,622 25,140 Tanga 64 33 636 97 179 1,010 Pangani 61 . 98 . . 158 Handeni 1,067 5,357 10,269 1,600 1,277 19,570 Kilindi 2,436 2,684 7,116 2,287 3,699 18,222 Total 26,396 11,043 89,023 18,262 19,485 164,209 20.6 Total Number of Indigenous Sheep by Sheep Type and District on 1st October 2003 District Number of Indigenous Sheep 20.8: Total Number of Sheep by Sheep Type and District on 1st October 2003 District Total Sheep 20.7 Total Number of Improved Mutton Sheep by Type and District on 1st October 2003 District Number of Improved for Mutton 20.5 Number of Households and Heads of Sheep by Herd Size on 1st October 2003 Tanzania Agriculture Sample Census - 2003 Tanga 260 Appendix II Tanzania Agriculture Sample Census – 2003 Tanga 261 PIGS PRODUCTION Appendix II 262 Number % Number % 1-4 2,118 81 3,336 53 2 5-9 467 18 2,694 43 6 10-14 8 0 117 2 14 15-19 8 0 134 2 16 Total 2,601 100 6,281 100 2 District Number of Households Number of Pigs Average per Household Lushoto 146 292 2 Korogwe 1,160 2,886 2 Muheza 972 1,582 2 Tanga 58 373 6 Handeni 217 759 4 Kilindi 49 389 8 Total 2,601 6,281 2 Boars Castrated Males Sow / Gilt Male Piglets She Piglets Total Lushoto 146 . 146 . . 292 Korogwe 633 796 942 300 215 2,886 Muheza 347 181 873 90 90 1,582 Tanga 27 . 68 87 192 373 Handeni 108 . 434 217 . 759 Kilindi 49 . 146 97 97 389 Total 1,310 977 2,609 791 594 6,281 District Pig Type Herd Size 21.1 Number of Households and Pigs by Herd Size on 1st October 2003 21.3 Number of Pigs by Type of Pig and District on 1st October 2003 21.2 Number of Households and Pigs by District on 1st October 2003 Heads of pigs Average per Household Pig Rearing Households Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 263 LIVESTOCK PESTS AND PARASITE CONTROL Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 264 No of Households % No of Households % Lushoto 22,075 59 15,180 41 37,255 Korogwe 6,784 46 7,908 54 14,692 Muheza 6,064 55 4,973 45 11,037 Tanga 961 51 934 49 1,895 Pangani 411 46 478 54 889 Handeni 9,176 63 5,495 37 14,671 Kilindi 3,116 65 1,656 35 4,772 Total 48,587 57 36,624 43 85,210 No of Households % No of Households % No of Households % No of Households % Lushoto 19,044 58 8,100 30 10,263 69 1,004 29 Korogwe 4,329 13 3,463 13 1,640 11 1,356 39 Muheza 2,765 8 3,519 13 1,310 9 543 16 Tanga 679 2 434 2 90 1 86 2 Pangani 87 0 365 1 0 0 0 0 Handeni 4,044 12 8,322 31 529 4 424 12 Kilindi 1,703 5 2,676 10 973 7 49 1 Total 32,653 100 26,881 100 14,805 100 3,463 100 No of Households % No of Households % Lushoto 3,047 8 34,500 92 37,547 Korogwe 3,823 26 10,764 74 14,587 Muheza 3,014 27 8,264 73 11,278 Tanga 633 34 1,254 66 1,887 Pangani 396 45 493 55 889 Handeni 7,054 48 7,723 52 14,777 Kilindi 3,167 69 1,410 31 4,577 Total 21,134 25 64,409 75 85,543 No of Households age No of Households % No of Households % No of Households % Lushoto 2,760 91 287 9 0 0 0 0 3,047 Korogwe 1,191 31 2,113 55 305 8 215 6 3,823 Muheza 1,042 35 1,892 63 80 3 0 0 3,014 Tanga 260 41 373 59 0 0 0 0 633 Pangani 143 36 165 42 41 10 46 12 396 Handeni 1,615 23 3,630 51 1,809 26 0 0 7,054 Kilindi 585 18 2,049 65 533 17 0 0 3,167 Total 7,595 36 10,510 50 2,768 13 261 1 21,134 22.4 PESTS AND PARASITE: Number of Livestock Rearing Households by methods of tsetse flies control use and district during the 2002/03 Agricultural Year. District Method of Tsetse Flies Control Total None Spray Dipping Trapping Not deworming Livestock Total District Tsetse flies problems No Tsetse flies problems Total 22.1 PESTS AND PARASITES: Number of Livestock Rearing households deworming Livestock by District during the 2002/03 Agricultural Year 22.3 LIVESTOCK PESTS AND PARASITE CONTROL: Number and Percent of agricultural households reporting to have encountered tsetse flies problems during 2002/03 Agriculture Year by District, 2002/03 Agricultural Year District 22.2 PESTS AND PARASITE: Number of Livestock Rearing Households that dewormed Livestock by type of Livestock and District during the 2002/03 Agricultural Year Cattle Goats Sheep Pigs District Deworming Livestock Tanzania Agriculture Sample Census- 2003 Tanga Appendix II 265 OTHER LIVESTOCK Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 266 Type Number % Type Number Indigenous Chicken 1,751,278 98 Ducks 117,486 Layer 29,630 2 Turkeys 503 Broiler 7,859 0 Rabbits 16,611 Donkeys 17,502 Total 1,788,767 100 152,103 Indigenous Chicken Layer Broiler Total number of chicken Ducks Turkeys Rabbits Donkeys Other Muheza 468,222 . 78 468,300 Lushoto 7,722 0 12,558 8,764 0 Handeni 430,586 . . 430,586 Korogwe 28,561 0 2,024 643 0 Korogwe 262,842 533 1,172 264,547 Muheza 42,980 322 674 0 0 Lushoto 238,080 8,764 1,022 247,867 Tanga 5,556 182 416 25 239 Kilindi 162,907 . . 162,907 Pangani 1,822 0 0 48 22 Pangani 121,187 . 205 121,393 Handeni 25,758 0 940 6,082 530 Tanga 67,454 20,332 5,381 93,168 Kilindi 5,088 0 0 1,940 773 Total 1,751,278 29,630 7,859 1,788,767 Total 117,486 503 16,611 17,502 1,563 1995 1999 2003 Number % Cattle 653,549 277,000 378,338 1 - 4 66,036 37 164,365 2 Improved Dairy 20,420 25,675 28,127 5 - 9 47,677 27 308,323 6 Goats 736,727 317,924 514,620 10 - 19 36,365 21 461,035 13 Sheep 246,263 85,679 164,209 20 - 29 15,520 9 345,418 22 Pigs 1,072 2,715 6,281 30 - 39 4,980 3 157,343 32 Indigenous Chicken 1,670,790 735,916 1,751,278 40 - 49 3,245 2 137,272 42 Layers - 6,136 29,630 50 - 99 2,760 2 168,679 61 Broilers 2,986 22,327 7,859 100+ 223 0 46,333 208 Total Chickens 1,673,776 764,379 1,788,767 Total 176,806 100 1,788,767 10 23f LIVESTOCK/POULTRY POPULATION TREND Chicken Others 23a OTHER LIVESTOCK: Total Number of Other Livestock by Type as of 1st October 2003 District 23e Head Number of Other Livestock by Type of Livestock and District Type of livestock 23d OTHER LIVESTOCK: Total Number of households and chickens raised by flock size as of 1st October 2005 Chicken rearing Households Number of Chicken Average chicken by households 23b OTHER LIVESTOCK: Number of Chicken by Category of chicken and District as of 1st October 2003 District Number of Chicken Flock size Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 267 FISH FARMING Tanzania Agriculture Sample Census-2003 Tanga Appendix II 268 Yes % No % Total Korogwe 634 1.4 45,356 98.62 45,990 Lushoto 430 0.5 86,149 99.50 86,580 Muheza 336 0.7 48,858 99.32 49,195 Tanga 23 0.3 8,891 99.74 8,914 Pangani 0 0.0 7,128 100.00 7,128 Handeni 0 0.0 47,739 100.00 47,739 Kilindi 0 0.0 19,654 100.00 19,654 Total 1,423 0.5 263,775 99.5 265,198 Natural Pond Dug out Pond Natural Lake Water Resevoir Other Lushoto 0 576 0 0 0 Korogwe 0 532 0 0 0 Muheza 0 336 0 0 0 Tanga 0 23 0 0 0 Total 0 1,467 0 0 0 Own Pond Government Institution NGOs / Project Neighbour Private Trader Other Lushoto 0 0 576 0 0 0 Korogwe 0 0 213 319 0 0 Muheza 0 156 0 90 0 90 Tanga 0 0 23 0 0 0 Total 0 156 812 409 0 90 District Neighbour Local Market Large Scale Farm Trader at Farm Did not Sell Other Lushoto 576 0 0 0 0 0 Korogwe 319 0 0 0 213 0 Muheza 180 0 0 0 156 0 Tanga 23 0 0 0 0 0 Total 1,098 0 0 0 369 0 District Number of Tilapia Number of Carp Number of Others Lushoto 124.4 0 0 Korogwe 95.9 0 0 Muheza 28.2 0 0 Tanga 0.5 0.7 0 Total 248,888 682 0 Source of fingerlings District Where sold 28.5 FISH FARMING: Total Number of Fish Harvested by Type and District, 2002/03 Agricultural Year 28.1a FISH FARMING: Number of Agriculture Households By Fish Farming And District during the 2002/03 Agriculture Year 28.2b FISH FARMING: Number of Agriculture Households by Source of Fingerling and District During the 2002/03 Agriculture Year 28.2c FISH FARMING: Number of Agriculture Households by Location of Selling Fish and District During the 2002/03 Agriculture Year District 28.2a FISH FARMING: Number of Agriculture Households by System of Fish Farming and District during the 2002/03 Agriculture Year Was Fish farming carried out by this household during 2002/03 System of fish farming District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 269 LIVESTOCK EXTENSION Tanzania Agriculture Sample Census-2003 Tanga Appendix II 270 No of households % No of households % Lushoto 15,548 18.0 71,031 82.0 86,580 37,986 41 Korogwe 16,976 36.9 29,014 63.1 45,990 14,885 114 Muheza 9,898 20.1 39,296 79.9 49,195 11,365 87 Tanga 608 6.8 8,305 93.2 8,914 1,939 31 Pangani 1,064 14.9 6,064 85.1 7,128 911 117 Handeni 7,485 15.7 40,254 84.3 47,739 14,886 50 Kilindi 2,086 10.6 17,567 89.4 19,654 4,820 43 Total 53,666 20.2 211,532 79.8 265,198 86,792 62 Government NGO / Development Project Co-operative Large Scale Farmer Other(former coding) Other Lushoto 10,493 140 0 0 0 0 Korogwe 13,369 0 0 0 0 0 Muheza 6,219 85 0 89 0 0 Tanga 212 40 0 0 0 0 Pangani 567 0 0 0 0 0 Handeni 1,057 104 0 0 0 0 Kilindi 582 0 0 0 0 0 Total 32,500 370 0 89 0 0 29.1a LIVESTOCK EXTENSION: Number of households receiving extension advice by District during the 2002/03 agriculture year District % Source of extension advice District 29.1b Livestock Extension Service Providers: Number of Households By Source of Extension and District during the 2002/03 agriculture year Received livestock advice Did Not receive livestock advice Total Total Number of households raising livestock Tanzania Agriculture Sample Census-2003 Tanga Appendix II 271 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,885 562 0 0 0 8,447 37,986 22.2 Korogwe 2,899 107 0 0 0 3,006 14,885 20.2 Muheza 1,777 0 0 0 0 1,777 11,365 15.6 Tanga 168 76 0 0 0 243 1,939 12.6 Pangani 135 0 0 0 0 135 911 14.9 Handeni 520 104 0 0 0 624 14,886 4.2 Kilindi 242 0 0 0 0 242 4,820 5.0 Total 13,626 849 0 0 0 14,475 86,792 16.7 % 94.1 5.9 0.0 0.0 0.0 100.0 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 29.1c LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking by Source and Region District Source of Advice Proper Milking Total Number of households raising livestock % receiving advice out of total 29.1d LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 272 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 11,368 0 0 0 146 11,514 37,986 30.3 Korogwe 11,807 107 0 0 0 11,914 14,885 80.0 Muheza 5,060 0 0 89 0 5,148 11,365 45.3 Tanga 234 76 0 0 0 310 1,939 16.0 Pangani 492 0 0 0 22 515 911 56.5 Handeni 5,711 104 0 0 0 5,815 14,886 39.1 Kilindi 1,359 0 0 0 0 1,359 4,820 28.2 Total 36,031 286 0 89 169 36,574 86,792 42.1 % 41.5 0.3 0.0 0.1 0.2 42.1 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 6,578 146 0 0 0 6,724 37,986 17.7 Korogwe 3,001 107 0 0 0 3,107 14,885 20.9 Muheza 1,570 0 0 0 0 1,570 11,365 13.8 Tanga 95 76 0 0 0 170 1,939 8.8 Pangani 269 0 0 0 0 269 911 29.5 Handeni 961 104 0 0 0 1,065 14,886 7.2 Kilindi 290 0 0 0 48 338 4,820 7.0 Total 12,764 433 0 0 48 13,245 86,792 15.3 % 14.7 0.5 0.0 0.0 0.1 15.3 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control by Source and District District Source of Advice on Disease control (dipping/spraying) Total Number of households raising livestock % receiving advice out of total 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District District Source of Advice on Herd / Flock Size & Selection Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 273 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 3,088 146 0 0 0 3,234 37,986 8.5 Korogwe 2,057 0 0 0 0 2,057 14,885 13.8 Muheza 2,025 0 0 0 0 2,025 11,365 17.8 Tanga 39 32 0 0 0 71 1,939 3.7 Pangani 111 0 0 0 0 111 911 12.2 Handeni 637 104 0 0 0 741 14,886 5.0 Kilindi 580 0 0 0 0 580 4,820 12.0 Total 8,537 282 0 0 0 8,819 86,792 10.2 % 9.8 0.3 0.0 0.0 0.0 10.2 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment by Source and District District Source of Advice on Pasture Establishment Total Number of households raising livestock % receiving advice out of total 29.1h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengthing by Source and District District Source of Advice on Group Formation & Strengthening Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 274 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,169 281 0 0 0 8,449 37,986 22.2 Korogwe 4,330 107 0 0 0 4,436 14,885 29.8 Muheza 3,328 92 0 0 0 3,509 11,365 30.9 Tanga 236 40 0 0 0 277 1,939 14.3 Pangani 386 0 0 0 0 386 911 42.3 Handeni 1,363 104 0 0 0 1,467 14,886 9.9 Kilindi 533 0 0 0 0 533 4,820 11.1 Total 18,345 624 0 0 0 19,057 86,792 22.0 % 98.8 3.4 0.0 0.0 0.0 102.6 Number % Number % Number % Number % Number % Lushoto 4,946 27 9,088 50 3,927 22 146 1 0 0 18,108 Korogwe 2,107 12 12,024 68 2,431 14 619 4 405 2 17,586 Muheza 1,773 10 12,265 70 3,431 20 0 0 0 0 17,469 Tanga 32 6 209 41 144 28 117 23 11 2 513 Pangani 39 3 470 37 744 59 17 1 0 0 1,270 Handeni 305 5 3,861 69 847 15 0 0 614 11 5,626 Kilindi 341 13 1,749 65 194 7 0 0 391 15 2,675 Total 9,543 15 39,666 63 11,718 19 899 1 1,421 2 63,247 29.1i LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District During the 2002/03 Agriculture Year District Source of Advice on Calf Rearing Total Number of households raising livestock % receiving advice out of total 29.1l LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Quality of Service Total Very Good Good Average Poor No Good 29.1j LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District During the 2002/03 Agriculture Year District Source of Advice on Use of Improved Bulls Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census-2003 Tanga Appendix II 275 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,885 562 0 0 0 8,447 37,986 22.2 Korogwe 2,899 107 0 0 0 3,006 14,885 20.2 Muheza 1,777 0 0 0 0 1,777 11,365 15.6 Tanga 168 76 0 0 0 243 1,939 12.6 Pangani 135 0 0 0 0 135 911 14.9 Handeni 520 104 0 0 0 624 14,886 4.2 Kilindi 242 0 0 0 0 242 4,820 5.0 Total 13,626 849 0 0 0 14,475 86,792 16.7 % 94.1 5.9 0.0 0.0 0.0 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 Total Number of households raising livestock % receiving advice out of total 29.1e LIVESTOCK EXTENSION: Number of Households Receiving Advice on Proper Milking by Source and Region 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District District Source of Advice on Milk Hygene Source of Advice Proper Milking Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 276 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 11,368 0 0 0 146 11,514 37,986 30.3 Korogwe 11,807 107 0 0 0 11,914 14,885 80.0 Muheza 5,060 0 0 89 0 5,148 11,365 45.3 Tanga 234 76 0 0 0 310 1,939 16.0 Pangani 492 0 0 0 22 515 911 56.5 Handeni 5,711 104 0 0 0 5,815 14,886 39.1 Kilindi 1,359 0 0 0 0 1,359 4,820 28.2 Total 36,031 286 0 89 169 36,574 86,792 42.1 % 98.5 0.8 0.0 0.2 0.5 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 6,578 146 0 0 0 6,724 37,986 17.7 Korogwe 3,001 107 0 0 0 3,107 14,885 20.9 Muheza 1,570 0 0 0 0 1,570 11,365 13.8 Tanga 95 76 0 0 0 170 1,939 8.8 Pangani 269 0 0 0 0 269 911 29.5 Handeni 961 104 0 0 0 1,065 14,886 7.2 Kilindi 290 0 0 0 48 338 4,820 7.0 Total 12,764 433 0 0 48 13,245 86,792 15.3 % 96.4 3.3 0.0 0.0 0.4 100.0 Total Number of households raising livestock % receiving advice out of total 29.1g LIVESTOCK EXTENSION: Number of Households Receiving Advice on Disease Control by Source and District 29.1h LIVESTOCK EXTENSION: Number of Households Receiving Advice on Herd/Flock Size & Selection by Source and District District District Source of Advice on Herd / Flock Size & Selection Source of Advice on Disease control (dipping/spraying) Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 277 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 3,088 146 0 0 0 3,234 37,986 8.5 Korogwe 2,057 0 0 0 0 2,057 14,885 13.8 Muheza 2,025 0 0 0 0 2,025 11,365 17.8 Tanga 39 32 0 0 0 71 1,939 3.7 Pangani 111 0 0 0 0 111 911 12.2 Handeni 637 104 0 0 0 741 14,886 5.0 Kilindi 580 0 0 0 0 580 4,820 12.0 Total 8,537 282 0 0 0 8,819 86,792 10.2 % 96.8 3.2 0.0 0.0 0.0 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Source of Advice on Group Formation & Strengthening Total Number of households raising livestock % receiving advice out of total 29.1i LIVESTOCK EXTENSION: Number of Households Receiving Advice on Pasture Establishment by Source and District 29.1j LIVESTOCK EXTENSION: Number of Households Receiving Advice on Group Formation and Strengthing by Source and District District District Source of Advice on Group Formation & Strengthening Source of Advice on Pasture Establishment Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 278 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 7,732 421 0 0 0 8,153 37,986 21.5 Korogwe 5,174 107 0 0 0 5,281 14,885 35.5 Muheza 2,565 0 0 0 0 2,654 11,365 23.4 Tanga 188 40 0 0 0 228 1,939 11.8 Pangani 134 0 0 0 0 134 911 14.7 Handeni 1,277 104 0 0 108 1,489 14,886 10.0 Kilindi 628 0 0 0 0 628 4,820 13.0 Total 17,698 673 0 0 108 18,567 86,792 21.4 % 95.3 3.6 0.0 0.0 0.6 100.0 Governmen t NGO / Developme nt Project Co- operative Large Scale Farmer Other Total Lushoto 8,169 281 0 0 0 8,449 37,986 22.2 Korogwe 4,330 107 0 0 0 4,436 14,885 29.8 Muheza 3,328 92 0 0 0 3,509 11,365 30.9 Tanga 236 40 0 0 0 277 1,939 14.3 Pangani 386 0 0 0 0 386 911 42.3 Handeni 1,363 104 0 0 0 1,467 14,886 9.9 Kilindi 533 0 0 0 0 533 4,820 11.1 Total 18,345 624 0 0 0 19,057 86,792 22.0 % 98.8 3.4 0.0 0.0 0.0 102.6 Total Number of households raising livestock % receiving advice out of total 29.1k LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Calf Rearing by Source and District During the 2002/03 Agriculture Year 29.1l LIVESTOCK EXTENSION: Number of Agriculture Households Receiving Advice on Improved Bulls by Source and District During the 2002/03 Agriculture Year District District Source of Advice on Use of Improved Bulls Source of Advice on Calf Rearing Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 279 Government NGO / Development Project Co-operative Large Scale Farmer Other Total Lushoto 8,616 562 0 0 0 9,178 37,986 24.2 Korogwe 4,045 107 0 0 0 4,153 14,885 27.9 Muheza 1,792 81 80 0 0 1,954 11,365 17.2 Tanga 203 76 0 0 0 278 1,939 14.4 Pangani 158 0 0 0 0 158 911 17.3 Handeni 735 104 0 0 0 839 14,886 5.6 Kilindi 435 0 0 0 0 435 4,820 9.0 Total 15,984 930 80 0 0 16,995 86,792 19.6 % 94.1 5.5 0.5 0.0 0.0 100.0 29.1f LIVESTOCK EXTENSION: Number of Households Receiving Advice on Milk Hygene by Source and District District Source of Advice on Milk Hygene Total Number of households raising livestock % receiving advice out of total Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 280 Number % Number % Number % Number % Number % Lushoto 4,946 27 9,088 50 3,927 22 146 1 0 0 18,108 Korogwe 2,107 12 12,024 68 2,431 14 619 4 405 2 17,586 Muheza 1,773 10 12,265 70 3,431 20 0 0 0 0 17,469 Tanga 32 6 209 41 144 28 117 23 11 2 513 Pangani 39 3 470 37 744 59 17 1 0 0 1,270 Handeni 305 5 3,861 69 847 15 0 0 614 11 5,626 Kilindi 341 13 1,749 65 194 7 0 0 391 15 2,675 Total 9,543 15 39,666 63 11,718 19 899 1 1,421 2 63,247 29.13 LIVESTOCK EXTENSION: Number of Agricultural Households By Quality of Extension Services and District, 2002/03 Agricultural Year District Total Quality of Service No Good Very Good Good Average Poor Tanzania Agriculture Sample Census - 2003 Tanga Appendix II 281 Government NGO / Developme nt Project Co- operative Large Scale Farmer Other(form er coding) Other Total Total Number of households raising livestock % Lushoto 15,548 14,975 14,975 14,975 14,975 75,446 37,986 50 Korogwe 16,976 16,274 16,331 16,331 16,331 82,244 14,885 18 Muheza 9,898 9,898 9,898 9,898 9,898 49,492 11,365 23 Tanga 608 608 608 608 608 3,042 1,939 64 Pangani 1,088 1,040 1,064 1,064 1,064 5,318 911 17 Handeni 7,485 7,389 7,389 7,389 7,389 37,041 14,886 40 Kilindi 2,086 2,038 2,038 2,038 2,038 10,237 4,820 47 Total 53,690 52,221 52,303 52,303 52,303 262,821 86,792 33 % 20 20 20 20 0 20 100 29.1 LIVESTOCK EXTENSION: Number of Households Receiving Advice on Other Extension Message by Source and District District Other Livestock Extension Tanzania Agriculture Sample Census - 2003 Tanga 282 Appendix II 283 ACCESS TO INFRASTRUCTURE AND OTHER SERVICES Tanzania Agriculture Sample Census-2003 Tanga Appendix II 284 Secondary Schools Primary Schools All weather roads Feeder roads Hospitals Health Clinics Regional Capital Primary Markets Secondary Market Tertiary Market Tarmac roads Lushoto 10.9 2.0 38.1 2.3 34 6.0 167.4 5.7 20.8 27.8 38.1 Korogwe 12.6 1.8 23.1 0.8 35 7.0 115.9 9.6 20.6 24.3 23.1 Muheza 13.1 2.2 24.5 1.1 28 5.6 49.7 12.3 23.8 29.2 24.5 Tanga 15.1 2.9 12.3 1.2 17 7.6 16.6 26.2 62.8 18.8 12.3 Pangani 21.4 2.3 48.7 0.7 24 4.7 67.7 10.6 56.1 27.3 48.7 Handeni 26.9 2.2 30.7 0.8 39 7.6 134.9 8.4 43.8 40.4 30.7 Kilindi 32.2 3.0 131.1 2.0 75 6.2 276.1 8.1 27.0 61.3 131.1 Total 16.5 2.2 38.0 1.5 36 6.4 131.1 9.1 28.3 31.9 38.0 Regional Capital 131.09 All weather roads 37.98 Tarmac roads 37.98 Hospitals 36.08 Tertiary Market 31.90 Secondary Market 28.29 Secondary Schools 16.50 Primary Markets 9.06 Health Clinics 6.40 Primary Schools 2.17 Feeder roads 1.45 District Mean Distance to 33.01a Mean distances from holders dwellings to infrustructures and services by districts Tanzania Agriculture Sample Census-2003 Tanga Appendix II 285 No of households % No of households % No of households % No of households % No of households % Lushoto 1,603 1.9 12,147 14.0 43,017 49.7 18,432 21.3 11,381 13.1 86,580 10.9 Korogwe 312 0.7 4,078 8.9 16,012 34.8 15,625 34.0 9,963 21.7 45,990 12.6 Muheza 1,372 2.8 5,077 10.3 14,786 30.1 16,467 33.5 11,491 23.4 49,195 13.1 Tanga 4 0.0 166 1.9 3,007 33.7 3,277 36.8 2,460 27.6 8,914 15.1 Pangani 169 2.4 112 1.6 2,060 28.9 2,495 35.0 2,292 32.2 7,128 21.4 Handeni 1,478 3.1 2,094 4.4 8,771 18.4 14,018 29.4 21,378 44.8 47,739 26.9 Kilindi 569 2.9 1,738 8.8 4,239 21.6 1,417 7.2 11,690 59.5 19,654 32.2 Total 5,507 2.1 25,413 9.6 91,893 34.7 71,731 27.0 70,655 26.6 265,198 16.5 No of households % No of households % No of households % No of households % No of households % Lushoto 23,935 27.6 22,413 25.9 28,563 33.0 5,654 6.5 5,113 5.9 86,580 38.1 Korogwe 20,979 45.6 11,323 24.6 11,459 24.9 10,668 23.2 1,289 2.8 45,990 23.1 Muheza 27,694 56.3 8,466 17.2 8,984 18.3 6,661 13.5 528 1.1 49,195 24.5 Tanga 4,815 54.0 1,578 17.7 2,347 26.3 2,175 24.4 35 0.4 8,914 12.3 Pangani 3,183 44.7 1,120 15.7 2,399 33.7 463 6.5 77 1.1 7,128 48.7 Handeni 21,142 44.3 9,232 19.3 11,998 25.1 4,632 9.7 650 1.4 47,739 30.7 Kilindi 6,103 31.1 1,165 5.9 4,436 22.6 0 0.0 5,268 26.8 19,654 131.1 Total 107,852 40.7 55,298 20.9 70,187 26.5 30,254 11.4 12,959 4.9 265,198 38.0 No of households % No of households % No of households % No of households % No of households % Lushoto 42,213 48.8 31,134 36.0 11,637 13.4 1,451 1.7 144 0.2 86,580 2.3 Korogwe 31,404 68.3 11,037 24.0 3,441 7.5 107 0.2 0 0.0 45,990 0.8 Muheza 37,686 76.6 5,864 11.9 4,574 9.3 981 2.0 90 0.2 49,195 1.1 Tanga 7,355 82.5 1,198 13.4 227 2.6 104 1.2 29 0.3 8,914 1.2 Pangani 4,994 70.1 1,720 24.1 372 24 0.3 17 0.2 7,128 0.7 Handeni 31,037 65.0 13,082 27.4 3,620 7.6 0 0.0 0 0.0 47,739 0.8 Kilindi 13,074 66.5 3,409 17.3 2,879 14.6 97 0.5 195 1.0 19,654 2.0 Total 167,764 63.3 67,444 25.4 26,750 10.1 2,764 1.0 476 0.2 265,198 1.5 Distance to All Weather Road Total number of households Mean Distance Total number of households Mean Distance Distance to Feeder Road Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 33.01c: Number of Households By Distance to All Weather Road by Distcrict for 2002/03 agriculture year 33.01d: Number of Households by Distance to Feeder Road by District for 2002/03 agriculture year District District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Above 20 km Total number of households 33.01b Mean distances from holders dwellings to infrustructures and services by districts Distance to Secondary School District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 286 No of households % No of households % No of households % No of households % No of households % Lushoto 291 0.3 6,465 7.5 14,370 16.6 11,611 13.4 53,842 62.2 86,580 34 Korogwe 107 0.2 174 0.4 3,860 8.4 10,759 23.4 31,090 67.6 45,990 35 Muheza 608 1.2 0 0.0 9,467 19.2 9,016 18.3 30,103 61.2 49,195 28 Tanga 0 0.0 96 1.1 2,010 22.6 3,670 41.2 3,137 35.2 8,914 17 Pangani 0 0.0 102 1.4 1,691 23.7 2,939 41.2 2,396 33.6 7,128 24 Handeni 408 0.9 713 1.5 2,984 6.3 16,990 35.6 26,644 55.8 47,739 39 Kilindi 145 0.7 0 0.0 0 0.0 2,001 10.2 17,507 89.1 19,654 75 Total 1,560 0.6 7,550 2.8 34,383 13.0 56,986 21.5 164,720 62.1 265,198 36 No of households % No of households % No of households % No of households % No of households % Lushoto 2,685 3.1 28,612 33.0 43,991 50.8 10,127 11.7 1,164 1.3 86,580 6.0 Korogwe 6,139 13.3 10,583 23.0 21,926 47.7 2,963 6.4 4,380 9.5 45,990 7.0 Muheza 3,792 7.7 9,381 19.1 27,967 56.9 7,290 14.8 764 1.6 49,195 5.6 Tanga 1,432 16.1 2,740 30.7 3,975 44.6 709 8.0 58 0.7 8,914 7.6 Pangani 1,198 16.8 2,509 35.2 2,716 605 8.5 99 1.4 7,128 4.7 Handeni 4,227 8.9 7,551 15.8 22,103 46.3 11,941 25.0 1,917 4.0 47,739 7.6 Kilindi 4,262 21.7 3,301 16.8 8,966 45.6 1,466 7.5 1,658 8.4 19,654 6.2 Total 23,734 8.9 64,679 24.4 131,644 49.6 35,101 13.2 10,040 3.8 265,198 6.4 No of households % No of households % No of households % No of households % No of households % Lushoto 17,016 19.7 53,745 62.1 14,944 17.3 291 0.3 584 0.7 86,580 Korogwe 18,721 40.7 19,165 41.7 7,680 16.7 213 0.5 212 0.5 45,990 Muheza 12,612 25.6 21,399 43.5 14,582 29.6 515 1.0 87 0.2 49,195 Tanga 3,633 40.8 3,556 39.9 1,632 18.3 0 0.0 93 1.0 8,914 Pangani 1,983 27.8 3,462 48.6 1,516 21.3 95 1.3 72 1.0 7,128 Handeni 12,777 26.8 18,614 39.0 15,824 33.1 418 0.9 105 0.2 47,739 Kilindi 7,289 37.1 8,031 40.9 4,141 21.1 48 0.2 145 0.7 19,654 Total 74,029 27.9 127,973 48.3 60,319 22.7 1,579 0.6 1,298 0.5 265,198 33.01g: Number of Households by distance to Primary School for 2002/03 agriculture year Distance to Primary Schools District Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Total number of households 33.01e: Number of Households By Distance to Hospital by District for 2002/03 agriculture year 33.01f: Number of Households by Distance to Health Clinic by District for 2002/03 agricultural year Distance to hospital Above 20 km District 10.0-19.9 3.0-9.9 1-2.9 km Less than 1 km District Total number of households Mean Distance Total number of households Mean Distance Health clinic Less than 1 km Above 20 km 10.0-19.9 3.0-9.9 1-2.9 km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 287 Region Less than 1 km 1-2.9 km 3.0-9.9 10.0-19.9 Above 20 km Total Mean Distance Lushoto 1,157 144 135 0 85,143 86580 167.4 Korogwe 202 0 285 107 45,395 45990 115.9 Muheza 426 87 176 1,221 47,284 49195 49.7 Tanga 0 73 1,800 4,220 2,820 8914 16.6 Pangani 108 40 17 65 6,897 7128 67.7 Handeni 105 0 0 0 47,634 47739 134.9 Kilindi 49 0 0 49 19,556 19654 276.1 Total 2,047 345 2,414 5,662 254,730 265198 131.1 District Very Good Good Average Poor No good Dodoma 20,709 90,132 31,607 31,297 3,761 Arusha 16,615 45,509 26,865 15,292 7,340 Kilimanjaro 26,187 99,001 121,096 66,003 21,901 Tanga 5,679 64,192 49,751 29,061 7,120 Morogoro 8,272 43,910 26,476 88,592 28,157 Pwani 4,978 17,948 10,989 9,970 12,308 Dar es Salaam 745 4,045 5,935 6,606 936 Lindi 4,100 10,064 7,053 20,340 2,727 Mtwara 5,602 22,341 35,140 88,342 18,229 Ruvuma 10,629 59,679 45,037 19,278 7,838 Iringa 21,138 89,479 34,882 20,547 11,705 Mbeya 15,987 62,374 44,200 114,683 20,802 Singida 4,264 18,881 12,960 17,121 24,234 Tabora 6,818 28,787 18,702 69,550 33,657 Rukwa 1,358 6,158 7,035 7,494 7,751 Kigoma 11,644 16,820 34,718 29,280 1,304 Shinyanga 10,634 55,927 53,637 84,358 67,047 Kagera 9,677 59,292 28,756 35,937 5,897 Mwanza 13,417 43,860 48,127 71,684 58,486 Mara 11,188 23,922 17,080 27,217 21,643 Manyara 8,114 35,656 43,539 22,040 35,506 Total 217,754 897,977 703,585 874,695 398,349 33.01h Number of Households by Distance to Regional Capital 33.01i Number of Households By Level of Satisfaction Using Infrastructure and Service by Region Tanzania Agriculture Sample Census-2003 Tanga Appendix II 288 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 0 1,845 10,506 5,654 68,574 86580 38.1 Korogwe 3,891 4,807 8,106 10,668 18,518 45990 23.1 Muheza 4,447 3,475 8,730 6,661 25,881 49195 24.5 Tanga 519 572 3,705 2,175 1,943 8914 12.3 Pangani 619 72 32 463 5,942 7128 48.7 Handeni 5,483 4,214 6,390 4,632 27,021 47739 30.7 Kilindi 95 49 196 0 19,314 19654 131.1 Total 15,054 15,034 37,664 30,254 167,192 265198 38.0 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 13,940 28,206 31,217 8,863 4,353 86580 5.7 Korogwe 9,883 8,124 17,879 5,941 4,164 45990 9.6 Muheza 2,805 4,196 19,683 12,040 10,471 49195 12.3 Tanga 324 105 1,205 2,067 5,213 8914 26.2 Pangani 987 858 2,019 2,441 821 7128 10.6 Handeni 8,400 6,077 16,587 11,208 5,467 47739 8.4 Kilindi 4,099 2,381 7,113 4,009 2,052 19654 8.1 Total 40,438 49,948 95,703 46,569 32,540 265198 9.1 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 1,880 6,185 20,040 13,491 44,983 86580 27.8 Korogwe 1,465 2,810 9,029 13,126 19,561 45990 24.3 Muheza 403 59 6,928 9,780 32,024 49195 29.2 Tanga 28 91 1,568 4,347 2,880 8914 18.8 Pangani 345 92 1,488 2,812 2,391 7128 27.3 Handeni 108 0 4,733 13,962 28,936 47739 40.4 Kilindi 1,825 333 1,413 2,733 13,350 19654 61.3 Total 6,055 9,569 45,198 60,250 144,126 265198 31.9 Region Less than 1 km 1-2.9 km 3.0-9.9km 10.0-19.9km Above 20 km Total Mean Distance Lushoto 8,536 10,288 14,620 21,564 31,572 86580 20.8 Korogwe 5,065 1,475 7,122 13,835 18,493 45990 20.6 Muheza 4,125 1,049 7,053 14,030 22,939 49195 23.8 Tanga 202 14 790 1,272 6,636 8914 62.8 Pangani 1,085 61 583 908 4,489 7128 56.1 Handeni 2,164 0 1,939 10,499 33,137 47739 43.8 Kilindi 1,064 580 6,141 5,076 6,792 19654 27.0 Total 22,243 13,466 38,248 67,183 124,058 265198 28.3 33.01jNumber of Households By Distance toTarmac Road and Distric for the 2002/03 Agricultural Year 33.01k Number of Households By Distance to Primary Market and Distric for the 2002/03 Agricultural Year 33.01l Number of Households By Distance to Tertiary Market Market and Distric for the 2002/03 Agricultural Year 33.01m Number of Households By Distance to Secondary Market Market and Distric for the 2002/03 Agricultural Year Tanzania Agriculture Sample Census-2003 Tanga Appendix II 289 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 1,314 2 28,724 42 21,083 31 16,013 23 1,011 1 68,145 Korogwe 2,752 8 19,800 60 9,095 28 1,160 4 0 0 32,807 Muheza 59 0 5,971 37 2,513 16 2,450 15 5,203 32 16,197 Tanga 199 6 869 26 1,572 48 645 20 0 0 3,285 Pangani 180 5 335 9 970 27 2,141 59 0 0 3,626 Handeni 836 4 6,408 29 9,743 44 4,846 22 418 2 22,251 Kilindi 340 4 2,085 22 4,775 50 1,806 19 487 5 9,492 Total 5,679 4 64,192 41 49,751 32 29,061 19 7,120 5 155,804 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 584 2 16,456 58 9,370 33 1,602 6 146 1 28,159 Korogwe 1,161 8 10,195 70 3,202 22 107 1 0 0 14,665 Muheza 0 0 3,092 54 1,517 26 450 8 706 12 5,765 Tanga 23 2 320 35 361 206 23 0 0 910 Pangani 101 8 268 21 881 70 0 0 0 0 1,250 Handeni 203 2 3,463 40 4,363 50 619 7 0 0 8,649 Kilindi 242 7 1,020 30 1,857 54 244 7 49 1 3,412 Total 2,314 4 34,816 55 21,550 34 3,228 5 901 1 62,810 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 4 146 4 144 4 3,060 84 146 4 3,643 Korogwe 215 50 215 50 0 0 0 0 0 0 430 Muheza 0 0 863 36 405 17 359 15 794 33 2,421 Tanga 0 0 27 12 176 79 19 9 0 0 222 Pangani 0 0 0 0 0 0 503 100 0 0 503 Handeni 96 5 108 5 973 46 824 39 107 5 2,109 Kilindi 0 0 49 6 390 50 293 38 48 6 780 Total 457 5 1,407 14 2,088 21 5,059 50 1,095 11 10,106 33.19a TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Veterinary Clinic and District, 2002/03 Agricultural Year Very Good Good Average Poor No good Total number of households Satisfaction of Using Veterinary Clinic District 33.19b TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Extension Centre and District, 2002/03 Agricultural Year District Extension Centre Total number of households Very Good Good Average Poor No good 33.19c TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Research Station and District, 2002/03 Agricultural Year District Research Station Total number of households Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 290 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 4 0 0 436 12 2,765 76 282 8 3,629 Korogwe 107 50 0 0 0 0 107 50 0 0 215 Muheza 0 0 90 6 91 6 355 25 879 62 1,416 Tanga 0 0 8 2 227 66 107 31 0 0 342 Pangani 0 0 0 0 23 24 73 76 0 0 95 Handeni 214 10 108 5 867 39 824 37 216 10 2,230 Kilindi 0 0 49 10 145 30 293 60 0 0 487 Total 468 6 256 3 1,789 21 4,524 54 1,377 16 8,414 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 0 0 281 5 2,604 47 2,476 45 146 3 5,506 Korogwe 215 3 1,884 27 4,216 60 741 11 0 0 7,056 Muheza 0 0 304 12 260 10 852 33 1,146 45 2,561 Tanga 7 1 47 8 434 71 119 20 0 0 607 Pangani 18 3 18 3 67 11 527 84 0 0 631 Handeni 106 5 542 25 529 24 924 42 96 4 2,197 Kilindi 0 0 194 12 725 45 390 24 293 18 1,603 Total 347 2 3,271 16 8,834 44 6,029 30 1,680 8 20,161 No of Households % No of Households % No of Households % No of Households % No of Households % Lushoto 146 1 6,535 50 3,621 28 2,621 20 146 1 13,069 Korogwe 101 11 484 54 210 23 103 11 0 0 898 Muheza 0 0 323 21 240 16 87 6 885 58 1,535 Tanga 53 12 165 39 157 37 48 11 0 0 422 Pangani 42 7 24 4 0 0 521 89 0 0 587 Handeni 217 10 108 5 1,183 53 714 32 0 0 2,222 Kilindi 0 0 0 0 586 60 293 30 97 10 975 Total 559 3 7,639 39 5,996 30 4,386 22 1,128 6 19,708 No of Households % No of Households % No of Households % No of Households % No of Households % Veterinary Clinic 5,679 4 64,192 41 49,751 32 29,061 19 7,120 0 Extension Centre 2,314 4 34,816 55 21,550 34 3,228 5 901 1 Research Station 457 5 1,407 14 2,088 21 5,059 50 1,095 11 Plant Protection Lab 468 6 256 3 1,789 21 4,524 54 1,377 16 Land Registration Office 347 2 3,271 16 8,834 44 6,029 30 1,680 8 Livestock Development Centre 559 3 7,639 39 5,996 30 4,386 22 1,128 6 OVERALL % 3 19.83 29.37 23.58 3 33.19g TYPE OF SERVICE: Number of Agricultural Households by Level of Satisfaction of the Service and District, 2002/03 Agricultural Year 33.19d TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Plant Protection Lab. and District, 2002/03 Agricultural Year District Plant Protection Lab Total number of households Very Good Good Average Poor No good 33.19e TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Land Registration Office and District, 2002/03 Agricultural Year District Land Registration Office Total number of households Very Good Good Average Poor No good 33.19f TYPE OF SERVICE: Number of Agricultural Households by Satisfaction of Using Livestock development Centre and District, 2002/03 Agricultural Year District Livestock Development Centre Total number of households Very Good Good Average Poor No good TYPE OF SERVICE LEVEL OF SATISFACTION OF THE SERVICE Very Good Good Average Poor No good Tanzania Agriculture Sample Census-2003 Tanga Appendix II 291 HOUSEHOLD FACILITIES Tanzania Agriculture Sample Census-2003 Tanga Appendix II 292 No Toilet Flush Toilet Traditional Pit Latrine Improved Pit Latrine Other Type Total Number of Households Lushoto 723 566 84,273 1,017 - 86,580 Korogwe 1,883 301 43,200 607 - 45,990 Muheza 7,747 322 39,502 1,345 279 49,195 Tanga 1,661 296 6,590 367 - 8,914 Pangani 1,679 47 5,286 115 - 7,128 Handeni 12,191 202 34,519 826 - 47,739 Kilindi 3,310 - 15,959 385 - 19,654 Total 29,194 1,733 229,330 4,663 279 265,198 % 11.0 0.7 86.5 1.8 0.1 100.0 Iron Sheets Tiles Concrete Asbestos Grass / Leaves Grass & Mud Other Total Lushoto 2 60,726 1,022 0 1,308 20,191 3,187 146 86,580 Korogwe 2 19,288 300 0 980 19,973 5,449 0 45,990 Muheza 2 14,233 519 43 323 33,362 626 89 49,195 Tanga 3 1,451 112 0 52 7,300 0 0 8,914 Pangani 3 918 171 21 0 5,973 44 0 7,128 Handeni 2 13,821 401 106 108 31,471 1,724 108 47,739 Kilindi 2 5,193 146 98 146 12,227 1,747 97 19,654 Total 2 115,628 2,671 268 2,917 130,497 12,778 440 265,198 % 43.6 1.0 0.1 1.1 49.2 4.8 0.2 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Radio 52,670 32 25,596 16 32,362 20 6,032 4 5,415 3 29,309 18 11,227 7 162,610 61.3 Landline phone 427 32 181 14 356 27 110 8 0 0 214 16 49 4 1,337 0.5 Mobile phone 987 19 982 19 1,060 21 551 11 86 2 1,254 25 191 4 5,112 1.9 Iron 20,307 41 9,144 18 9,181 18 1,956 4 832 2 6,380 13 2,229 4 50,029 18.9 Wheelbarrow 2,720 30 809 9 1,583 18 812 9 146 2 2,275 25 584 7 8,928 3.4 Bicycle 12,641 15 12,226 14 19,009 22 4,602 5 4,098 5 24,042 28 8,420 10 85,039 32.1 Vehicle 282 12 562 24 380 16 222 10 155 7 427 18 291 13 2,319 0.9 Television / Video 285 10 562 21 520 19 286 11 81 3 738 27 241 9 2,714 1.0 Total Number of Households 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.3 Number of Agricultural Households by Type of Owned Assets and District during 2002/03 Agricultural YearDistrict Type of Owned Asset District 34.1 Number of Agricultural Households by Type of Toilet and District during the 2002/03 Agriculture Year District Type of Toilet 34.2 Number of Households Reporting Average Number of Rooms and Type of Roofing Materials by District; 2002/03 Agricultural Year Type of Roofing Material Average Number of Rooms per Household District Tanzania Agriculture Sample Census-2003 Tanga Appendix II 293 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 561 17 1,088 480 14 482 15 198 6 506 15 0 0 3,315 1.3 Solar 146 38 0 0 0 0 0 22 6 215 56 0 0 383 0.1 Gas (Biogas) 137 100 0 0 0 0 0 0 0 0 0 0 0 137 0.1 Hurricane Lamp 20,468 46 4,465 9,198 21 1,382 3 1,553 4 4,704 11 2,328 5 44,098 16.6 Pressure Lamp 2,747 25 1,677 3,557 32 282 3 179 2 1,824 17 776 7 11,043 4.2 Wick Lamp 62,374 30 38,655 35,653 17 6,719 3 5,131 3 39,953 19 16,501 8 204,986 77.3 Candles 146 45 0 0 0 49 15 21 6 105 33 0 0 321 0.1 Firewood 0 0 105 306 33 0 0 23 3 432 47 49 5 915 0.3 Total 86,580 33 45,990 49,195 19 8,914 3 7,128 3 47,739 18 19,654 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 0 190 0 0 64 17 22 6 102 27 0 0 378 0.1 Solar 278 100 0 0 0 0 0 0 0 0 0 0 0 278 0.1 Gas (Biogas) 0 0 0 0 0 0 0 21 100 0 0 0 0 21 0.0 Bottled Gas 289 39 0 267 36 52 7 79 11 0 0 49 7 736 0.3 Parraffin / Kerocine 0 0 0 90 100 0 0 0 0 0 0 0 0 90 0.0 Charcoal 572 8 1,564 650 9 515 7 123 2 3,302 46 484 7 7,210 2.7 Firewood 85,151 33 44,027 48,188 19 8,283 3 6,743 3 44,226 17 19,024 7 255,643 96.4 Crop Residues 289 39 103 0 0 0 0 138 19 108 15 97 13 735 0.3 Livestock Dung 0 0 106 0 0 0 0 0 0 0 0 0 0 106 0.0 Total 86,580 45,990 49,195 8,914 3 7,128 47,739 19,654 7 265,198 100.0 Pangani 34.4 Number of Agriculture Households by Main Source of Energy Used for Lighting and District during 2002/03 Agricultural Year Main Source of Energy for Lighting District Total Lushoto Korogwe Muheza Tanga Handeni Kilindi Pangani 34.5 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Main Source of Energy for Cooking District Total Korogwe Muheza Handeni Kilindi Lushoto Tanga Tanzania Agriculture Sample Census-2003 Tanga Appendix II 294 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 17,828 10,171 6,667 4,415 2,244 16,269 917 Dry 15,090 9,737 7,152 4,961 2,247 17,675 1,698 Wet 4,777 6,271 8,074 1,108 1,097 1,399 1,941 Dry 4,628 6,551 6,906 1,115 1,252 1,399 2,281 Wet 2,874 2,887 2,120 154 83 531 535 Dry 3,159 2,774 2,526 253 39 642 633 Wet 4,057 3,737 11,539 2,530 1,681 21,080 9,286 Dry 3,913 6,062 12,566 1,906 1,504 18,276 11,335 Wet 41,372 13,741 7,910 224 422 751 3,314 Dry 42,086 12,133 7,766 400 433 320 829 Wet 14,959 8,715 11,377 210 1,534 4,920 3,660 Dry 17,129 8,380 11,132 191 1,630 6,967 2,684 Wet 424 174 429 0 0 108 0 Dry 285 84 349 0 0 108 0 Wet 290 197 818 145 66 2,149 0 Dry 146 99 239 26 23 1,716 194 Wet 0 0 258 32 0 0 0 Dry 0 171 474 32 0 108 0 Wet 0 0 0 8 0 0 0 Dry 142 0 84 8 0 105 0 Wet 0 0 0 21 0 0 0 Dry 0 0 0 21 0 0 0 Wet 0 97 0 68 0 533 0 Dry 0 0 0 0 0 424 0 Total Agricultural Households per District 86,580 45,990 49,195 8,914 7,128 47,739 19,654 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 21 22 14 50 31 34 5 Dry 17 21 15 56 32 37 9 Wet 6 14 16 12 15 3 10 Dry 5 14 14 13 18 3 12 Wet 3 6 4 2 1 1 3 Dry 4 6 5 3 1 1 3 Wet 5 8 23 28 24 44 47 Dry 5 13 26 21 21 38 58 Wet 48 30 16 3 6 2 17 Dry 49 26 16 4 6 1 4 Wet 17 19 23 2 22 10 19 Dry 20 18 23 2 23 15 14 Wet 0 0 1 0 0 0 0 Dry 0 0 1 0 0 0 0 Wet 0 0 2 2 1 5 0 Dry 0 0 0 0 0 4 1 Wet 0 0 1 0 0 0 0 Dry 0 0 1 0 0 0 0 Wet 0 0 0 0 0 0 0 Dry 0 0 0 0 0 0 0 Wet 0 0 0 0 0 0 0 Dry 0 0 0 0 0 0 0 Wet 0 0 0 1 0 1 0 Dry 0 0 0 0 0 1 0 34.6 Number of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year District Piped Water Other Bottled Water Tanker Truck Water Vendor Uncovered Rainwater Catchment Covered Rainwater Catchment Source 36.7 Proportion of Agricultural Households by Main Source of Drinking Water by Season (wet and dry) and District during 2002/03 Agricultural Year Source Season Season Surface Water (Lake / Dam / River / Stream) Unprotected Spring Uprotected Well Protected / Covered Spring Protected Well Piped Water Protected Well Protected / Covered Spring District Uprotected Well Unprotected Spring Surface Water (Lake / Dam / River / Stream) Covered Rainwater Catchment Other Uncovered Rainwater Catchment Water Vendor Tanker Truck Bottled Water Tanzania Agriculture Sample Census-2003 Tanga Appendix II 295 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 29,092 6,397 9,918 1,181 1,339 5,307 2,507 Dry 27,073 4,295 4,837 943 961 1,794 1,308 Wet 5,632 8,608 10,895 2,746 987 6,313 2,786 Dry 5,345 8,500 8,959 2,395 907 4,928 1,563 Wet 1,018 911 4,224 835 334 0 976 Dry 1,018 830 4,378 646 384 0 880 Wet 13,736 9,344 9,195 1,796 1,087 7,122 2,388 Dry 13,584 8,597 7,683 1,460 947 5,203 2,244 Wet 26,671 14,901 10,830 982 2,036 15,087 7,294 Dry 27,251 14,129 10,293 683 1,733 8,743 6,601 Wet 7,245 3,153 3,336 889 1,004 7,928 2,387 Dry 8,260 3,986 5,229 1,084 1,196 9,942 3,304 Wet 2,757 1,973 564 395 319 5,018 682 Dry 3,339 3,910 2,966 1,111 842 9,825 1,998 Wet 428 703 233 91 21 965 634 Dry 708 1,742 4,602 526 158 6,111 1,660 Wet 0 0 0 0 0 0 0 Dry 0 0 247 67 0 1,193 97 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 34 14 20 13 19 11 13 Dry 31 9 10 11 13 4 7 Wet 7 19 22 31 14 13 14 Dry 6 18 18 27 13 10 8 Wet 1 2 9 9 5 0 5 Dry 1 2 9 7 5 0 4 Wet 16 20 19 20 15 15 12 Dry 16 19 16 16 13 11 11 Wet 31 32 22 11 29 32 37 Dry 31 31 21 8 24 18 34 Wet 8 7 7 10 14 17 12 Dry 10 9 11 12 17 21 17 Wet 3 4 1 4 4 11 3 Dry 4 9 6 12 12 21 10 Wet 0 2 0 1 0 2 3 Dry 1 4 9 6 2 13 8 Wet 0 0 0 0 0 0 0 Dry 0 0 1 1 0 2 0 34.8 Number of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Distance to Main Source of Drinking Water Season District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km 34.9 Proportion of Agricultural Households Reporting Distance to Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agriculture Year Source Season District Less than 100m 100 - 299 m 300 - 499 m 500 - 999 m 10Km and above 1 - 1.99 Km 2 - 2.99 Km 3 - 4.99 Km 5 - 9.99 Km Tanzania Agriculture Sample Census-2003 Tanga Appendix II 296 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 2,947 866 5,389 592 474 1,485 243 Dry 2,384 589 3,609 497 320 523 97 Wet 16,553 13,128 13,140 2,759 2,423 8,474 4,670 Dry 15,669 9,466 9,318 1,915 2,051 6,353 2,732 Wet 9,829 7,670 5,492 511 441 2,948 3,207 Dry 8,661 7,155 3,565 447 423 1,149 1,696 Wet 33,306 12,275 11,633 1,964 1,470 14,536 5,257 Dry 33,440 10,961 8,868 1,326 1,097 8,521 5,049 Wet 4,928 1,735 3,353 289 480 3,710 1,121 Dry 5,501 2,227 4,066 239 510 1,468 1,412 Wet 5,026 2,750 4,687 1,452 45 3,154 1,507 Dry 5,330 2,543 3,887 1,331 59 2,189 1,119 Wet 13,991 7,567 5,502 1,348 1,795 13,433 3,650 Dry 15,596 13,049 15,882 3,159 2,667 27,537 7,547 Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Wet 3 2 11 7 7 3 1 Dry 3 1 7 6 4 1 0 Wet 19 29 27 31 34 18 24 Dry 18 21 19 21 29 13 14 Wet 11 17 11 6 6 6 16 Dry 10 16 7 5 6 2 9 Wet 38 27 24 22 21 30 27 Dry 39 24 18 15 15 18 26 Wet 6 4 7 3 7 8 6 Dry 6 5 8 3 7 3 7 Wet 6 6 10 16 1 7 8 Dry 6 6 8 15 1 5 6 Wet 16 16 11 15 25 28 19 Dry 18 28 32 35 37 58 38 34.10 Number of Agricultural Households by Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes 34.11 Proportion of Agricultural Households Reporting Time Spent to and from Main Source of Drinking Water by Season (Wet and Dry) and District during 2002/03 Agricultural Year Time Spent to and from Main Source of Drinking Water Season District 40 - 49 Minutes 50 - 59 Minutes above one Hour Less than 10 10 - 19 Minutes 20 - 29 Minutes 30 - 39 Minutes Tanzania Agriculture Sample Census-2003 Tanga Appendix II 297 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % One 4,337 68 615 10 525 8 133 2 68 1 523 8 146 2 6,346 2.4 Two 33,209 50 7,894 12 7,550 11 2,926 4 1,408 2 6,878 10 6,964 10 66,829 25.2 Three 48,899 26 37,482 20 41,120 21 5,845 3 5,638 3 40,232 21 12,543 7 191,758 72.3 Four 135 51 0 0 0 0 10 4 14 5 106 40 0 0 265 0.1 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 29,863 34 12,020 14 18,561 21 4,870 6 2,922 3 15,141 17 3,934 5 87,311 32.9 One 33,590 39 10,811 12 17,868 21 1,613 2 1,841 2 14,692 17 6,327 7 86,741 32.7 Two 17,538 29 13,673 23 9,011 15 1,440 2 1,661 3 10,416 17 6,271 10 60,009 22.6 Three 3,443 18 6,028 32 2,465 13 328 2 277 1 4,644 24 1,806 10 18,992 7.2 Four 722 12 1,883 30 764 12 258 4 227 4 1,690 27 683 11 6,227 2.3 Five 566 19 829 29 264 9 68 2 158 5 628 22 390 13 2,903 1.1 Six 719 51 430 31 90 6 8 1 0 0 106 8 49 3 1,402 0.5 Seven 139 9 315 20 171 11 329 20 43 3 422 26 194 12 1,613 0.6 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Total 34.13 Number of Households by Number of Days the Household Consumed Meat during the Preceding Week by District 34.12 Number of Households by Number of Meals the Household Normally Took per Day by District Kilindi Total Number of Meals per Day District Lushoto Korogwe Muheza Tanga Pangani Handeni Number of Days District Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Tanzania Agriculture Sample Census-2003 Tanga Appendix II 298 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Not Eaten 18,417 47 4,517 11 4,189 11 311 1 496 1 7,824 20 3,644 9 39,398 14.9 One 15,606 45 4,623 13 4,089 12 622 2 660 2 5,023 15 3,741 11 34,365 13.0 Two 20,754 39 8,321 16 8,621 16 1,270 2 1,033 2 8,779 17 4,180 8 52,958 20.0 Three 13,112 28 8,743 18 9,394 20 1,577 3 1,327 3 10,048 21 3,457 7 47,658 18.0 Four 10,499 29 4,988 14 8,188 23 1,264 4 1,198 3 7,494 21 2,245 6 35,877 13.5 Five 4,017 16 6,652 26 6,519 25 1,546 6 1,077 4 4,055 16 1,852 7 25,718 9.7 Six 1,291 13 2,607 26 2,773 28 521 5 330 3 2,205 22 244 2 9,971 3.8 Seven 2,884 15 5,539 29 5,421 28 1,802 9 1,006 5 2,310 12 292 2 19,254 7.3 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Never 26,975 29 18,422 20 22,501 24 3,211 3 3,392 4 11,013 12 7,194 8 92,707 35.0 Seldom 40,527 36 17,400 16 16,869 15 3,743 3 2,180 2 23,747 21 7,049 6 111,515 42.0 Sometimes 6,508 32 2,935 15 4,374 22 544 3 716 4 2,955 15 1,998 10 20,029 7.6 Often 6,493 29 3,572 16 3,424 15 920 4 441 2 5,438 25 1,850 8 22,138 8.3 Always 6,078 32 3,661 19 2,027 11 497 3 399 2 4,586 24 1,562 8 18,810 7.1 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 34.15 Number of Agricultural Households Reporting the Status of Food Satisfaction of the Household during the Preceding Year by District Number of Days District Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.14 Number of Households by Number of Days the Household Consumed Fish during the Preceding Week by District Total Status of Food Satisfaction District Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi Tanzania Agriculture Sample Census-2003 Tanga Appendix II 299 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Sales of Food Crops 27,232 40 6,905 10 9,047 13 553 1 602 1 17,694 26 5,498 8 67,531 25.5 Sale of Livestock 3,321 31 4,294 40 412 4 33 0 0 0 1,281 12 1,313 12 10,655 4.0 Sale of Livestock Products 720 16 1,040 23 1,009 23 340 8 48 1 1,067 24 244 5 4,468 1.7 Sales of Cash Crops 11,767 26 6,876 15 17,481 39 2,421 5 1,739 4 3,133 7 1,073 2 44,491 16.8 Sale of Forest Products 433 6 1,338 20 735 11 222 3 431 6 3,161 47 438 6 6,758 2.5 Business Income 13,747 36 6,318 17 5,077 13 2,621 7 1,247 3 6,985 18 1,800 5 37,795 14.3 Wages & Salaries in Cash 2,843 21 4,345 33 2,227 17 936 7 702 5 2,066 16 190 1 13,308 5.0 Other Casual Cash Earnings 20,467 37 8,440 15 8,063 15 596 1 1,345 2 8,788 16 7,789 14 55,488 20.9 Cash Remittance 5,613 29 6,434 33 3,523 18 246 1 290 1 2,641 13 873 4 19,620 7.4 Fishing 0 0 0 0 891 37 913 37 633 26 0 0 0 0 2,437 0.9 not applicable 0 0 0 0 0 0 0 0 0 0 0 0 97 100 97 0.0 Total 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Handeni 34.16 Number of Households by Main Source of Cash Income and District during 2002/03 Agriculture Year Main Source of Cash Income District Total Lushoto Korogwe Muheza Kilindi Tanga Pangani Tanzania Agriculture Sample Census-2003 Tanga Appendix II 300 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Iron Sheets 60,726 53 19,288 17 14,233 12 1,451 1 918 1 13,821 12 5,193 4 115,628 43.6 Tiles 1,022 38 300 11 519 19 112 4 171 6 401 15 146 5 2,671 1.0 Concrete 0 0 0 0 43 16 0 0 21 8 106 40 98 36 268 0.1 Asbestos 1,308 45 980 34 323 11 52 2 0 0 108 4 146 5 2,917 1.1 Grass / Leaves 20,191 15 19,973 15 33,362 26 7,300 6 5,973 5 31,471 24 12,227 9 130,497 49.2 Grass & Mud 3,187 25 5,449 43 626 5 0 0 44 0 1,724 13 1,747 14 12,778 4.8 Other 146 33 0 0 89 20 0 0 0 0 108 25 97 22 440 0.2 Total Number of Households 86,580 33 45,990 17 49,195 19 8,914 3 7,128 3 47,739 18 19,654 7 265,198 100.0 Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Number of Households % Mains Electricity 0 190 0 64 22 102 0 378 0.1 Solar 278 0 0 0 0 0 0 278 0.1 Gas (Biogas) 0 0 0 0 21 0 0 21 0.0 Bottled Gas 289 0 267 52 79 0 49 736 0.3 Parraffin / Kerocine 0 0 90 0 0 0 0 90 0.0 Charcoal 572 1,564 650 515 123 3,302 484 7,210 2.7 Firewood 85,151 44,027 48,188 8,283 6,743 44,226 19,024 255,643 96.4 Crop Residues 289 103 0 0 138 108 97 735 0.3 Livestock Dung 0 106 0 0 0 0 0 106 0.0 Number of Households 86,580 45,990 49,195 8,914 7,128 47,739 19,654 265,198 100.0 Main Source of Energy for Cooking District Handeni Kilindi Total Lushoto Korogwe Muheza Tanga Pangani Handeni Kilindi 34.17 Number of Agricultural Households by Type of Roofing Material and District during the 2002/03 Agricultural Year 34.18 Number of Households by Main Source of Energy for Cooking and District during 2002/03 Agricultural Year Roofing Materials District Total Lushoto Korogwe Muheza Tanga Pangani Tanzania Agriculture Sample Census-2003 Tanga 301 APPENDIX III QUESTIONNAIRES Appendix III 302 Page Number …………………. ACLF 1: Sub-village leader listing form Region Code Ward _______________ Code District _____________________ Code Village _______________Code From office register After enumeration (3) (4) Total Name of enumerator……………………………… Signature ……………………………. Date……………. Name of supervisor…………………………………Signature ……………………………. Date……………. Sub-village leader number (1) Name of sub-village leader Agriculture Sample Census 2002/03 Confidential UNITED REPUBLIC OF TANZANIA Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Cooperatives and Marketing and the National Bureau of Statistics Name of Village Chairman:………………………………………………………………………………………….. Number of households Comments (5) (2) Appendix III 303 Interval Starting point Page Number……………….. ACLF: 2 Household listing form - form for listing household heads and their agriculture activities Region Code Name of Sub-village Leaader _______________________________ District Code Subvillage leader code Ward Code Village Code Name of Sub-village _______________________________ Adult female cattle Goats Rabbit (1) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Totals * NOTE: (Column 13) Place a " 3" if the household has at least 1 field over 25m2 and/or keeps at least 1 Cow, 5 Goats/Sheep/Pigs or 50 Chicken/poultry or ducks É(Column 3) A field must be at least 25 m2 Name of enumerator…………………………………….. Signature ……………………………. Date……………………..…. Name of supervisor…………………………………. Signature ……………………………. Date………………..………. Cooperatives and Marketing and the National Bureau of Statistics (2) Household head name Total Number Adult male cattle Sheep Household Number Pigs Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of poultry/ducks Agriculture Sample Census 2002/03 UNITED REPUBLIC OF TANZANIA Farmer Serial Numbers Confidential Number of 3 if the respodent qualifies to be a farmer * Calves Fields É Cattle Appendix III 304 ACLF: 3 Household listing of 15 selected farmers Region Code District Code Ward Code Village Code S/N Rabbits (4) (5) (6) (7) (8) (9) (10) (12) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Cooperatives and Marketing and the National Bureau of Statistics Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Ministry of Name of Supervisor______________________Signature__________________Date________________________ (1) (2) (3) Name of Enumerator:_____________________Signature__________________Date________________________ Pig Poultry /ducks Sub village leader number Name of sub-village leader Agriculture hh serial number Name of selected head of household Fields Cattle Goat Number of UNITED REPUBLIC OF TANZANIA National Agriculture Sample Census 2002/03 Confidential Sheep 305 ACQ 1 CONFIDENTIAL Enumerator Name Signature Start time Date Enumerated End time Field level checking by: District Supervisor: Name signature Date / / Regional Supervisor: Name signature Date / / National Supervisor: Name signature Date / / District checking in Office: District Supervisor Name signature Date / / For Use at National Level only: Data Entered by Name signature Date / / Queried Name signature Date / / United Republic of Tanzania National Bureau of Statistics and Executed by the Ministry of Agriculture and Food Security, Ministry of Water and Livestock Development, Agriculture Sample Census 2002/2003 Ministry of Cooperatives and Marketing Small holder/Small Scale Farmer Questionnaire Hour Minutes y y m m d d / / To be completed by the supervisor ONLY after field/farm level checking of the enumeration process. This should be countersigned by the enumerator. All questionnaires must be checked at the district office. See back page for details of query 306 1.0 IDENTIFICATION DETAILS 1.1 Location S/N Location Name 1.1.1 Region …………………………………………………………………… 1.1.2 District …………………………………………………………………… 1.1.3 Ward …………………………………………………………………… 1.1.4 Village …………………………………………………………………… 1.2 Details of the respondent and household head S/N 1.2.1 Name & number of local leader ……………………………………….. 1.2.2 Name & number of household head ……………………………………….. 1.2.3 Sex of household head (Male = 1, Female = 2) 1.2.4 Name of respondent ……………………………………….. 1.2.5 Relationship of Respondent to Household Head 2.0 ACTIVITIES OF THE HOUSEHOLD 2.1 Type of Agriculture Household 2.2 Rank the following livelihood activities/source of income of the household in order of importance Rank in order S/N Livelihood/source of income activity. of importance 1=most 7=least 2.2.1 Annual Crop farming % 2.2.2 Permanent crop farming % 2.2.3 Livestock keeping/herding % 2.2.4 Off Farm Income % 2.2.5 Remittances % 2.2.6 Fishing/hunting and gathering % 2.2.7 Tree/forest resources (eg honey, firewood, timber,etc) % (2) (1) How important are each Codes Codes (3) of these activities expressed in percentage. Relationship to household head codes (Q 1.2.5) Head of Household…...1 Son/Daughter ……...3 Grandson/Granddaughter …...5 Other (friend, employee, etc)…8 Spouse ……………..…2 Father/Mother …...…4 Other relative..………………...6 Agriculture household codes(Q2.1) Crops only.…………..1 Livestock only …………….2 Pastoralist……………..3 Crops and Livestock …………….4 1 0 0 % 307 Definition and working page for page 1 General Definitions Question Specific Definitions: Procedures for Questions: Household: A group of people who occupy the whole or part of one or more housing units and makes joint provisions for food and/or other essentials for living. Household Head: A person who is acknowledged by all other members of the household either by virtue of his age or standing in the household as the head. He/she should be a permanent resident of the house and he/she is the main person responsible for making decissions. Type of Agriculture Holdings Codes (Q2.1): - Crops only: A holding is referred to be a crops only holding if it has cultivated a piece of land equal or exceeding 25 sq Meter. This also applies to all households owning or have kept livestock whose number does not qualify such household to be an agricultural holding (No cattle, less than 5 goats/sheep/pigs, less than 50 chickens/turkeys/ducks/rabbits) - Livestock only: A holding is referred to be a Livestock only holding if it has exercised Livestock husbandry only during the agricultural year. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. - Livestock pastoralism: This refers to a household which practices livestock production as its major income generating activity and a means of subsistence, but moves from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they have no permanent place of residence. For both livestock only and pastoralism , the number of livestock has to be at least 1 head of cattle, 5 goats/sheep/pigs or 50 chickens/turkeys/ ducks/rabbits. This also applies to all households owning or have cultivated a piece of land less than 25 sq meter, which does not qualify such household be an agricultural holding. - Both crops and livestock: A holding is referred to be a both crops and livestock if it has cultivated a piece of land equal or exceeding 25 sq meter and if such households is owning or have kept livestock whose number qualify such household be an agricultural holding. Important livelihood activities/source of income (Q 2.2): - Crop farming: This refers to a household where crop production is its major means of subsistence and income generation. - Livestock farming/herding/pastoralism: This refers to a household where livestock farming/herding is its major means of subsistence & income generation. - Off Farm Income This refers to cash generated from activities other than from the households holding. This can be from permanent employment (eg government/other), temporary employment/labouring and includes cash generated from working on other farmers farms. -Remittances: Assistance from family members who are not currently part of the household, or from a relative or family friend. This assistance is usually in the form of cash but it can also be in-kind (eg food, clothes, building material, farm tools, etc). The money is a gift and is not paid back. -Fishing/hunting and gathering The use of non farmed resources for food eg fishing, hunting wildlife and gathering mushrooms, berries, wild honey roots from uncultivated land. Small holder hh/small scale farm: Should have between 25sq metres and 20 Hectares under production, and/or between 1 and 50 head of Cattle, and/or between 5 and 100 head of Sheep/Goats/Pigs, and/or between 50 and 1000 chickens/turkeys/ducks/rabbits. Agricultural Holding: This is an economic unit of agricultural production under single management. It consists of all livestock kept and all land used for agricultural production without regard to title. For the purpose of this survey, the agricultural holdings are restricted to those which meet one of the following conditions: - Having or operated at least 25 sq meter of arable land - Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agricultural year 2002/03 (October 2002 to September 2003) . Q 2.1 Type of agriculture household/holding 1. Using the options under the question classify the type of agriculture hh/holding Note: If the hh had 1 acre of crops and raised 40 chickens during 2002/03 it is classified as 'Crops only' as the number of chickens do not qualify the hh as keeping livestock. Q 2.2 Important hh livelihood activities /source of income 1. Read the list in column 1 to the respondent and ask him to rank them in order of importance during the reference year. 2. In column 2 Indicate the importance of each activity by placing '1' against the most important, '2' against the second most important, etc until you reach '7' the least important activity/source of income. Note: You must attempt to fill in all boxes. Most households will carry out these activities to a greater or lesser degree. You will normally have to probe to get remittances. If the hh did not undertake an activity during the 2002/2003 agriculture year then mark the appropriate box in column 2 with an 'X'. 3. For each activity/source of income assign a percentage. The enumerator should assist the respondent in assigning the percentage based on the information provided by the farmer. 4. After completing column 3 make sure the percentages add up to 100. Note: It is not essential to be 100% accurate. This question is just to give the relative importance of the different items in general terms 308 3.0 HOUSEHOLD INFORMATION 3.1 Give details of personal particulars of all household members beginning with the head of the household Rela- Read Edu- Invol- Off-farm ion- Sex & ca- vemen Income S/N ship to M=1 Mo- Fa- Write tion in Yes=1 head F=2 ther ther Status farmin No=2 (1) (2) (3) (5) (6) (7) (8) (10) (12) 3.1.1 ………………… 3.1.2 ………………… 3.1.3 ………………… 3.1.4 ………………… 3.1.5 ………………… 3.1.6 ………………… 3.1.7 ………………… 3.1.8 ………………… 3.1.9 ………………… 3.1.10 ………………… 3.1.11 ………………… 3.1.12 ………………… 3.1.13 ………………… 3.1.14 ………………… 3.1.15 ………………… 3.1.16 ………………… Names of household members & above) Parents (if age is above Education Level reached (for aged 5 99 years then write 99) (4) activity (9) (11) Survival of Main Not applicable for children under 5 years of age Age 1 Relation to head (Col 2) Head of household ……….1 Spouse …………………….2 Son/daughter ……………..3 Father/Mother ………….…4 Grandson/granddaughter .5 Other Relative ………….....6 Others …………………..…8 Survival of Parents (Col 5 & 6) Yes ………………………..1 No ………………………..2 Don't know ……………….3 Read & Write (Col 7) Swahili ……………………1 English ……………………2 Swahili & English ………...3 Any other language ……..4 Don’t Read/ Write ……….5 Education Status (Col 8) Attending School …………..1 Completed ……….....……...2 Never attended School ……3 Education Level Reached (Col 9) Primary Education Secondary Education Not of school age ...........NA Form one ............................11 Under Standard One .... 00 Form two ............................12 Standard One ................01 Form three ..........................13 Standard Two ................02 Form four ............................14 Standard Three .............03 Form five ............................15 Standard Four ...............04 Form six ..............................16 Standard Five ................05 Training after Secondary Standard Six ..................06 Education ............................17 Standard Seven ...........07 University & other tertiary Standard Eight ..............08 Education ............................18 Training after Primary Adult Education ...................19 Education ......................09 Not applicable .....................99 Pre Form One ..............10 Involvement in farming activities (Col 10) Works full time on farm ...1 Works part-time on farm 2 Rarely works on farm ….3 Never works on farm..….4 Main activity (Col 11) Crop Farming .....................01 Livestock Keeping/Herding..02 Livestock Pastoralism..........03 Fishing ................................04 Paid employment: - Government/parastatal ....05 - Private- NGO/mission/etc .06 Self employed (non farming) - with employees .................07 - without employees ............08 Unpaid family helper (non agriculture) .........................09 Not working & available.......10 Not working & unavailable...11 Housemaker/housewife ......12 Student ...............................13 Unable to work /too old/ Retired/sick/disabled)..........14 Other .................................98 309 Definition and working page for page 2 Question Specific Definitions: Overview to section 3.0 Procedures for questions Relation to head (Col 2): - Household Head: A person who is acknowledged by all other members of the household either by virtue of their age or standing as the household head. S Wif H b d Read and Write (Col 7): - Any other language: Must be a written language. For someone who can read and write in Swahili and any other language apart from English, the correct code is 1. For one who can read and write in English and any other language apart from Swahili the correct code is 2. Code 4 should only be used for another language but not English or Swahili Education Level Reached (Col 9): Indicate the highest level only. For those still attending school fill in the last year reached before the survey period. For example if a hh member is currently in standard 7 this year his highest grade reached is standard 6 Main Activity (Col 11): - Crop farming: The persons main activity is crop production. This can be annual crops, vegetables, permanent crops or tree farming. - Livestock farming/herding: The persons main activity is livestock farming/herding. The livestock can be herded in search for areas of pasture, but the core household unit always remains in the same place and the herder is rarely away from this place for long periods at a time. This category also includes fish farming but not fishing. - Livestock pastoralism: The persons main activity is in moving livestock from one place to another searching for water and pasture for the livestock. This movement usually involves long distances and in many cases the whole household unit moves with the livestock and they may have no permanent place of residence. -Paid employment - In full time employment earning a cash income - Government/Parastatal - In full time employment for a government Ministry, Department or Board that is controlled by the Government - Private/NGO/Mission/etc - employed by Non public/government organisation -Self employee - works for own business for cash income - With employees - Works for own business for cash and employs other workers - Without employees - Works for own business for cash but does not employ other workers - Not working but available to work - No productive activity but would like to have one. - Not working & nor available for work - No productive activity and does not want to have one. - Unable to work too old, too young, retired, disabled, etc Off-farm Income (Col 12) - Income made from activities NOT on the HH's farming activities. This can be any off farm income generation activity and includes working for cash on other peoples farms. Indicate whether each member was involved in an off farm income generating activity during 2002/03 Section 3.0 - Preliminary note 1. Make sure that you define the hh properly to ensure that all the members of the hh are included. Make sure you stress that the hh is not just the hh heads direct family and that it includes other people living and eating together with the family. 2. If you notice that his house is large or you see many people around his house and he has only given you small number of hh members enquire further until you are sure that you have captured all the hh members. Section 3.0 - Household Information 1. For each household member complete columns 1, 2 & 3. 2. After completing columns 1, 2 & 3 for each household member go back to the first household member and complete the remaining columns for that member. 3. Repeat step 2 for the rest of the household members IMPORTANT NOTE: Cross check responses in columns 11 and 12 with section 2 especially in relation to: off-farm income - if a hh member was involved in off farm income then there should be a response in question 2.2.4 and vice versa. 310 4.0 LAND ACCESS/OWNERSHIP/TENURE 4.1 Details of area "owned" by the household in the 2002/03 agricultural year. Give area reported by the respondent in "acres". 4.1.1 Area Leased/Certificate of ownership 4.2 Was all land available to the hh used 4.1.2 Area owned under Customary Law during 2002/03 (Yes=1, No=2) 4.1.3 Area Bought from others 4.1.4 Area Rented from others 4.3 Do you consider that you have 4.1.5 Area Borrowed from others sufficient land for the hh (Yes=1, No=2) 4.1.6 Area Share -cropped from others 4.1.7 Area under Other forms of tenure ……… 4.4 Do any female members of the hh own or have Total area customary right to land (Yes=1, No=2) 5.0 LAND USE 5.1 Area operated by household under different forms of land use during 2002/03 agriculture year. Give area reported by the respondent in "acres". Calculation area 5.1.1 Area under Temporary Mono-crops 5.1.2 Area under Temporary Mixed crops (eg Maize & beans) 5.1.3 Area under Permanent Mono-crops 5.1.4 Area under Permanent Mixed crops (eg bananas, coffee & trees) 5.1.5 Area under Permanent/temporary mix (eg bananas & maize) 5.1.6 Area under Pasture 5.1.7 Area under Fallow 5.1.8 Area under Natural Bush 5.1.9 Area under Planted Trees 5.1.10 Area Rented to others 5.1.11 Area Unusable 5.1.12 Area of Uncultivated Usable land (excluding fallow) Total area 6.0 ACCESS AND USE OF RESOURCES 6.1 In the following table indicate the distance to the different fields used by the household S/N Field Number 6.1.1 1 6.1.2 2 6.1.3 3 6.2 In the following table indicate the distance and use of the following communal resources Communal Resource 6.2.1 Water for humans 6.2.2 Water for livestock 6.2.3 Communal Grazing 6.2.4 Communal Firewood 6.2.5 Wood for Charcoal 6.2.6 Building poles 6.2.7 Forest for bees (honey) 6.2.8 Hunting(animal products) 6.2.9 Fishing (Fish) (1) S/N Main (4) dry season (2) (3) wet season Distance to resource (km) hh use Area in Acres Area in Acres Distance (in kilometres) from field to: Homestead Nearest road Nearest Market Main hh use (Col 4) Home or farm Consumption/utilisation…..1 Sold to Neighbours...............…...…..…..2 Sold to trader on the farm….............…...3 Sold to village market ….…..............…..4 Sold to local wholesale market...............5 Sold to major wholesale market ..............6 Not used by household.………................7 Not available ........................................8 . . . . . . . . . . . . . . . . . . . . Instructions for distance to resource (Col 2 and 3): If under 1km, write 0 If above 1km round to whole numbers eg 1.5km= 2km, 1.25km= 1km . Distance codes less than 100m …………1 between 2 and 3km ….6 between 100 and 300m .2 between 3 and 5km …..7 between 300 and 500m .3 between 5 and 10 km ..8 between 500 and 1km....4 Over 10 km …………...9 between 1 and 2km .…..5 310 311 Definition and working page for page 3 Question Specific Definitions Overview to section 4 Procedures for Questions Section 4.1 - Land Access/Ownership Lease/Certificate of Ownership Area under lease/certificate of ownership refers to the area for which the household possesses a government issued leasehold title or certificate of ownership. The land will normally be officially surveyed and boundaries marked. This includes leased land bought from others where the lease/certificate of ownership has been transferred. Customary Law: This refers to the land which the hh does not have an official government title to but its right of use is granted by the traditional leaders. This user-right agreement does not have to be granted directly by the village leaders as right of access may be passed on through heredity. Bought: This refers to the area of customary land that has been bought from others. This land does not have an official title and therefore is not leasehold. Rented from others: Land rented from others for Cash or for a fixed amount in crop produce (eg fixed number of bags at harvest). Borrowed: Use granted by land owner free of charge. Land owner can either be a lease holder or has right of access through customary law. Share Cropping: where the hh is permitted to use land which is then paid for from a percentage of the harvested crop. Use of Communal Resources (Q6.2): -Communal resources - refers to the place on which all individual households can have access to. It is not individually owned or controlled by one hh. NOTE: The listed resources refers to communal resources and not those individually owned or part shared. The resource has to be freely accessible to the whole village Section 5.0 Land Use - Temporary crops: are sown and harvested during the same agricultural year - Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). - Mixed Crops: This is a mixture of two or more crops planted together and mixed in the same plot/field. The two crops can either be randomly planted together or they can be planted in a particular patterm eg intercropping (1 row of maize and 1 row of beans). A field that has been divided into plots for different crops is not mixed. This is further subdivided into: Permanent Mixed -two or more permanent crops grown together, Permanent/Temporary Mix - permanent crop and annual crop together, Temporary Mixed - two or more temporary, annual crops grown together. - Pasture Land: This is an area of owned/allocated land which is set aside for livestock grazing. It can be improved pasture where the farmer has planted grass, applied fertilized or applied other production increasing technologies to improve the grazing. Or it can be rough pasture. - Fallow: This is the area of land that is normally used for crop production, but is not used for crop production during a year or a number of years. This is normally to allow for self generation of fertility/soil structure and is often an integral part of the crop rotation system. - Natural Bush: Land which is considered productive but is not under cultivation or used extensively for livestock production and has naturally growing shrubs and trees. -Planted trees: Land which is used for planting trees for poles or timber - Unusable: Land that is known to be non-productive for agriculture purposes Uncultivated Usable: This is land that was not used for reasons other than fallow. The reasons could be lack of inputs/money/rainfall/etc Section 4.0 - Land Ownership 1. Ask the respondent if he knows the total area of land the household has sole access to. If he knows make a note in the calculation space 2. Ask the respondent the area of the different land ownership categories the household has sole access to (Q4.1.1 to 4.1.7) and record in the appropriate spaces. 3. Add up the area of the different categories of land and compare it with the total area obtained in step 1 (if the respondent provided the information). 4. If the total area is different find out which one is correct and make amendments where appropriate. Section 5.0 - Land Use 1. Ask the respondent the area of the different landuse categories the household has sole access to (Q5.1.1 to 5.1.12) and record in the appropriate spaces. 2. Add up the area of the different categories of land and compare it with the total area obtained in section 4.0. The total area should be the same. 3. If the total area is different find out which one is correct and make amendments where appropriate. Distance to fields (Q6.1): -fields A field is a contiguous piece of land holding which the farmer considers as a single entity. The field may be divided into plots for growing different crops. A holding may consist of one or more fields in different localities. Section 4.0 - Preliminary note Land Access/ Ownership Access/Ownership refers to the area utilized by the members of the household. This does not include communal land where the resources are shared between households. It does include official communal land that the hh has sole access to eg a plot for crop farming in the communal area. Section 6.2 Communal resources Note: the code "Not available" means that the resource does not exist. The code "Not Used" means that the resource does exist but is not used by the hh. 312 7.0 ANNUAL CROP AND VEGETABLE PRODUCTION - SHORT RAINY SEASON 7.1.1 Did the hh plant any crops during the Short Rainy season? (Yes = 1, No=2) If the response is 'NO' give main reason Then go to section 7.2 7.1.2 For each crop planted during 2002/03 Short Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod Mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.1.3 Main reason for difference between Area Planned and Area Planted 7.1.4 Main reason for difference between Area Planted and Area Harvested (1) (2) (5) (6) Planting Inputs Marketing (19) (15) area (acres) (17) Quantity harvested (Kgs) (18) Actual Planted Crop Code Planned area (acres) Area Harvested (acres) Harvesting & Storage (kgs) Quantity Stored (kgs) Quantity sold … … … … … … … … … … … … … … … … … … … … … … … … … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops ............3 No money 4 Don’t get Vuli season ..5 Illness/social problems ......................6 Has irrigation & does not follow season (give annual production in Masika) ............7 Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2 of crop…..…3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Threshed/harvested (Col13 & 14) By hand …………………….1 By draft animal …………….2 By human powered tool…...3 By engine driven machine...4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...……1 Green cob/green pod...…2 Green leaves & Stem……3 Straw, dry stems etc …….4 Root, tuber, etc ….……...5 Flower eg pyrethrum …...6 Fruit/bunch ...…………...7 Other………...…………..8 Not harvested yet ………9 Reason for difference between area planned and planted (Q7.1.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ...................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.1.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ……….……………8 Not applicable .…………..9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 Irrigation Use (Col 8) Used on all crop …….….1 Used on 3/4 of crop ……2 Used on 1/2 of crop..…..3 Used on 1/4 of crop …...4 Used on less than 1/4….5 Not used …………….…6 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing………..5 … … … 313 Definitions and working page for page 4 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Crop total check crop% (d) crop area of plants area of plants (ACRE) (ACRES) (e) Crop Name (b) Name Total area of mix (acre) (c) (a) of mix (c) (b) Crop (a) (acre) Total area (d) Ground Total no. (e) Ground area/plant area/plant (ACRE) crop% (f) Total ground Total no. Total ground (ACRES) (f) area of plants of plants Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that produced a harvest. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage. Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Co Crop -de 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix, Step C C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix/ (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed 314 7.2 ANNUAL CROP AND VEGETABLE PRODUCTION - LONG RAINY SEASON 7.2.1 Did the hh plant any crops during the LONG RAINY season? (Yes=1 No=2) If the response is 'NO' give main reason Then go to section 7.3 7.2.2 For each crop planted during 2002/03 Long Rainy season provide the following information Soil % Irrig Fer Her Fun Pest main Landprep impr -at -til -bic -gic -tic How How prod mostly Crop Clea -arat -oved -ion -iser -ide -ide -ide harv thres -uct sold Name -ring -ion seed use use use use use ested hed code to (3) (4) (7) (8) (9) (10) (11) (12) (13) (14) (16) (20) ……. ……. ……. ……. ……. ……. ……. ……. ……. Total Planned/Planted Total area harvested 7.2.3 Main reason for difference between Area Planned and Area Planted 7.2.4 Main reason for difference between Area Planted and Area Harvested (kgs) Crop Planned Code area (acres) area (acres) (acres) Planting Inputs (19) Planted Harvested Actual Area Stored Quantity harvested (1) (2) (5) (6) Quantity Harvesting & Storage (15) Quantity (Kgs) (17) Marketing (18) sold (Kgs) … … … … … … … … … … … … … … … … … … … … … … … … … … … Soil preparation Method (Col 4) Mostly tractor ploughing .1 Mostly Oxen ploughing ..2 Mostly Hand cultivation ..3 Fertiliser codes (Col 9) Mostly Farm Yard Manure 1 Mostly Compost ….………2 Mostly Inorganic fertiliser ..3 No fertiliser applied …… ..4 Improved seed Use (Col 7) all Improved …………....1 approx 3/4 improved…..2 approx 1/2 improved…..3 approx 1/4 improved…..4 less than 1/4 improved ..5 No improved seed used.6 Land Clearing (Col 3) Mostly bush clearance ...1 Mostly hand slashing .....2 Mostly tractor slashing ...3 Mostly burning …………4 No land clearing ……….5 Irrigation Use (Col 8) Used on all crop ……….1 Used on 3/4 crop …..…2 Used on 1/2 crop ……..3 Used on 1/4 of crop…...4 Used on less than 1/4 …5 Not used …………….…6 Agrochemical use codes (Col 10,11 &12) Used on all crop …………1 Used on 3/4 of crop …….2 Used on half of crop….....3 Used on 1/4 of crop ..…...4 Used on less than 1/4 …..5 Not used …………………6 Reason for difference between area planned and planted (Q7.2.3) Drought ………………………………………….......…....1 Floods …………………………………….......…………...2 Access to land preparation tools (Draft animal/tractors).3 Credit ...……………………………………...…………….4 Access to seeds/planting material...................................5 Access to other inputs ..................................................6 Other ............…................……………………………….8 Not applicable ..………...………………………………...9 Reason for difference between area planted and harvested (Q7.2.4) Drought …………………..1 Rain/flood damage ………2 Fire damage ……………..3 Pest damage …………….4 Animal damage ………….5 Theft ……………………...6 Illness/social problems ......7 Other ………..……………8 Not applicable..…………..9 … … … Main Reason (Above) No rains.....1 Rains came too late …..2 Does not plant annual crops .........3 No money 4 Illness/social problems ..5 Threshed/harvested (Col13 & 14) By hand ……………………..1 By draft animal ……………..2 By human powered tool……3 By engine driven machine…4 Not applicable ……………..9 Main product (Col 16) Dry Grain…………...………1 Green cob/green pod...…...2 Green leaves & Stem……...3 Straw, dry stems etc ……...4 Root, tuber, etc ….………..5 Flower eg pyrethrum ……..6 Fruit/bunch.………………..7 Others ……………………..8 Not harvested yet ………...9 Mostly sold to (Col 20) Neighbour………...01 Local market/trade store ......................02 Secondary Market..03 Tertiary Market …..04 Marketing Coop ….05 Farmer Association06 Largescale farm ....07 Trader at Farm ….08 Contract Partner ...09 Did not sell ……….10 Other ………....….98 315 Definitions and working page for page 5 Working table for the calculation of area occupied by annual crop in a mixture Crop mixture 1 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Permanent/Temporary crop name 1 Permanent/Temporary crop name 2 Permanent/Temporary crop name 3 Total area check Temoporary crop total check Crop mixture 2 Permanent crop 1 Permanent crop 2 Permanent crop 3 Permanent crop 4 Total Area of permanent crops in mix REMAINING AREA UNDER TEMPORARY CROPS Temp crop area Temporary/permanent crop name 1 Temporary/permanent crop name 2 Temporary/permanent crop name 3 Total area check Temoporary crop total check (e) (f) Temp crop% (a) (b) (c) (d) (ACRE) (ACRES) area of plants area/plant of plants Name (acre) Crop of mix Ground Total no. Total ground Temp crop% Total area (ACRES) (a) (b) (c) (d) (e) (f) Name (acre) (ACRE) Total ground Crop of mix area/plant of plants area of plants Total area Ground Total no. Temporary/Annual Crop: Crops which are planted and harvested within a period of 12 months after which time the plants die. Most annual crops are planted and harvested on a seasonal basis. Crop Codes (Cereals /tubers/roots): Code Crop 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 22 Sweet Potatos 23 Irish potatos 24 Yams 25 Cocoyams 26 Onions 27 Ginger Cash Crop Codes: Code Crop 50 Cotton 51 Tobacco 53 Pyrethrum 62 Jute 19 Seaweed Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc) Planned Area: Area in Acres the household planned to plant before the season started Actual Planted Area: The area in Acres the household was able to plant. Area Harvested: The area in Acres that the household got most of its production from. This is the same as the area planted minus the area that was destroyed by major flood/pest/ animal/etc damage Crop Codes Legumes Oil & fruit: Code Crop 31 Beans 32 Cowpeas 33 Green gram 35 Chick peas 36 Bambara nuts 37 Field peas 41 Sunflower 42 Simsim 43 Groundnut 47 Soyabeans 48 Caster seed Vegetable Codes: Code Crop 27 Ginger 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 20 Garlic 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . 0.00 0 . 0.00 0 0.00 0 0.00 0 0 . 0 . 0 . 0 . 0 . . . . . . . Instructions for calculating the area of mixed crops in a mixture. A. If the mixed crop is mixed annual only enter the total area of the field in the REMAINING AREA UNDER TEMPORARY CROPS. and goto step 1 of these instructions. B. If the mixed crop is mixed permanent and annual try to get the % occupied by the different crops and calculate the area of annual crops outlined in step 1. Otherwise use the number of trees method to calculate the area of annual crops in the mix (Step C). C. Number of trees method to calculate annual crop areas in a peranent-annual crop mix (i) list each of the permanent crops in column b and enter the ground area per acre for each permanent crop (from instructions for page 6) in column 'd'. (ii) obtain the number of permanent trees in the mix from the respondent and enter the number in column 'e'. (iii) calculate the area occupied by each crop by multiplying column 'd' with column 'e' and sum these to obtain the total area of permanent crops in the mix. (iv) subtract the total area of permanent crops in the mix from the total area of mix and enter the result in the total area under temporary crops. (v) proceed to step 1 to calculate the area under each temporary crop. 1. Enter the name of each annual crop in the mix & estimate the percentage of each crop. 2. Using the percentages for each crop calculate the area of each crop from the REMAINING AREA UNDER TEMPORARY CROPS. 3. After completing this exercise for all fields, sum the area of each crop in the mix plus any monocrops and enter totals in section 7.1 col 6. 4. Obtain an estimate of the planned area for each crop and enter it in column 5 5. If the area harvested is different to the area planted estimate the harvest area 6. Once the quantity harvested is obtained calculate the Yield (Metric tonnes/acre) & compare the figure with the norms given in the crop codes box. If it is excessively different check the area and the amount harvested. 316 7.3 PERMANENT/PERENNIAL CROPS AND FRUIT TREE PRODUCTION 7.3.1 Does your household have any permanent/perennial crops or fruit trees (Yes=1, No=2) 7.3.2 For each of the permanent crops and fruit trees owned by the household provide the following information Perm Perman Number of Irrig Fert HerbFun Pest main If no -anent -ent crop/ permanent -at -ilis -ic -gic -ici prod harvest mostly Crop fruit tree Plants/trees in a -ion -er -ide -ide -de -uct give re sold Name crop Code MIXED CROP use use use use use code -ason to (5) (6) (7) (8) (9) (10) (13) (15) (18) …… …… …… …… …… …… …… …… …… (11) Harvesting & Storage Area Harvested (acres) (kgs) (1) (2) (3) (4) (17) (12) (16) (14) Size of production unit Quantity sold Area covered by Permanent Crop in a MIXED CROP Marketing Inputs Area of Plants/ harvested (kgs) Number of mature plants Quantity Stored (Kgs) Quantity MIXED CROP MONOCROP (acres) (acre) trees/Bushes in MONO CROP Fertiliser codes (Col 7) Mostly Farm Yard Manure…...1 Mostly Compost ………………2 Mostly Inorganic fertiliser …….3 No fertiliser applied …………..4 Main product (Col 13) Dry Grain…………...…1 Green cob/green pod..2 Green leaves & Stem..3 Straw, dry stems etc ...4 Root, tuber, etc ….…..5 Flower ………………..6 Fruit/bunch………..…7 Other ………………..8 Not harvested yet …..9 Main Reason for no harvest(Col 15) Crop not harvested yet ………...1 Drought ………………………....2 Rain/flood damage ………….....3 Fire damage ……………………4 Pest damage …………………...5 Animal damage ………………...6 Theft …………………………….7 Other ….........…………………..8 Not applicable .…………………9 Mostly sold to (Col 18) Neighbour…………..…......01 Local market/trade store.....02 Secondary Market ….........03 Tertiary Market ……….......04 Marketing Coop ….........…05 Farmer Association .….......06 Largescale farm …….........07 Trader at farm ……........…08 Contract Partner ……........09 Did not sell …………..........10 Other ................................98 Irrigation Use (Col 6) Used on all crop …………….….1 Used on most crop …………….2 Used on half crop ………….…..3 Used on small amount of crop..4 Not used on crop .….………….5 . . . . . . 1 Agrochemical use codes (Col 8, 9 & 10) Used on all crop …………1 Used on 3/4 of crop …….2 Used on 1/2..of crop….....3 Used on 1/4 of crop ..…...4 less than 1/4 of crop …….5 Not used …………………6 . . . . . . . . . . . . . . . . . . . . . 317 Definitions and working page for page 6 . Permanent Crop: Permanent crops: are sown or planted once and then , they occupy the land for some years and need not to be replanted after each annual harvest. Permanent crops are mainly trees (e.g., apples) but also bushes and shrubs (e.g., berries), palms (e.g., dates), vines (e.g., grapes), herbaceous stems (e.g., bananas) and stemless plants (e.g., pineapples). Permanent crops (oils): Code Crop Ground area/plant 44 Palm Oil 0.00049 45 Coconut 0.00037 46 Cashewnut 0.00062 Permanent (Cash crops) Code Crop Ground area/plant 53 Sisal 0.00012 54 Coffee 0.00049 55 Tea 0.00037 56 Cocoa 0.00049 57 Rubber 0.00099 58 Wattle 0.00099 59 Kapok 0.00124 60 Sugar Cane 0.00012 61 Cardamom 0.00049 63 Tamarin 0.00099 64 Cinamon 0.00124 65 Nutmeg 0.00099 66 Clove 0.00074 18 Black Pepper 0.00037 34 Pigeon pea 0.00025 21 Cassava 0.00019 75 Pineapple 0.00006 Number of mature plants: This is the number of plants which bared harvest. Permanent Crops: Code Crop Ground area/plant 70 Passion Fruit 0.00074 71 Banana 0.00037 72 Avocado 0.00099 73 Mango 0.00099 74 Papaw 0.00037 76 Orange 0.00074 77 Grapefruit 0.00074 78 Grapes 0.00012 79 Mandarin 0.00074 80 Guava 0.00074 81 Plums 0.00074 82 Apples 0.00074 83 Pears 0.00074 84 Peaches 0.00074 85 Lime/lemon 0.00074 68 Pomelo 0.00099 69 Jack fruit 0.00074 97 Durian 0.00074 98 Bilimbi 0.00074 99 Rambutan 0.00074 67 Bread fruit 0.00099 38 Malay apple 0.00074 39 Star fruit 0.00074 Total number of plants: This includes both mature harvestable plants and immature non harvestable plants. Instructions for Permanent crop mono stands and mixtures A. For fields that are monocrop permanent, ONLY enter the area of plants in column 3. B. For fields that are mixed permanent calculate the area of each crop based on the % occupied by each crop method (NOT using the number of trees method) and ONLY enter the area in column 4 C. For fields that are mixed permanent/annual either: - ONLY enter the area in column 4 if the area of the permanent crop was based on the % occupied by each crop method OR - ONLY enter the number of trees in column 5 if the number of permanent crop plants was provided Working Area/calculation space 318 7.4 Main use of Secondary Products 7.5 Did you use Secondary Products from any of your crops during the 2002/03 year. (Yes=1, No=2) If the response is 'NO' go to section 8.0 7.6 List the main crops with secondary products and provide the following details: Secondary Prod Used product code for Unit (4) (5) (6) 7.6.1 …………. ……………… 7.6.2 …………. ……………… 7.6.3 …………. ……………… 7.6.4 …………. ……………… 7.6.5 …………. ……………… 7.6.6 …………. ……………… 8.0 AGROPROCESSING AND BY-PRODUCTS 8.1 Did the household process any of the products harvested on the farm during 2002/03 (Yes=1, No=2) If the response is 'NO' go to section 9.0 8.2 List the main crops processed and provide the following details: Main By- S/N Proc Prod Quantity Whe Prod Quantity Quan Crop Crop -ess -uct Used of main Quantity -re -uct Used of by- -tity name Code -ed code for Unit product Sold sold code for Unit product Sold (3) (5) (6) (8) (9) (11) (12) 8.2.1 ……. 8.2.2 ……. 8.2.3 ……. 8.2.4 ……. 8.2.5 ……. 8.2.6 ……. (14) (4) (7) S/N Crop Total no of name Crop Code Units Total value of sold units (Tsh.) No of units sold (13) (10) (1) (3) (8) (9) (7) (2) (1) (2) Mainly used for (Col 5) Feeding to livestock ..1 Consumed by hh .……….4 Building material …...2 Sold …………………….....5 Fuel for cooking ….. 3 Did not use….....……….…6 Unit (Col 6) Loose Bundle/bunch ..……1 kg …………...…5 Compressed bunch/Bail….2 Stems ………….6 Tin ……………………….. 3 Sack ……………7 Bucket …………………....4 Other ………..…8 Used for (Col 5 & 11) Household/human consumption ..1 Fuel for cooking ………………….2 Sale …..………………...………..3 Animal consumption……………..4 Did not use ………………………5 Other ………...…………………..8 Unit (Col 6 & 12) Loose bundle/bunch ..……1 Compressed bunch/bail….2 Tin ….…………….……….3 Bucket …………………….4 kg …………...…………….5 litre ………………………..6 Other ……………………..8 Processed (Col 3) On farm by hand…...……1 On farm by machine…….2 By neighbours machine...3 By farmers association …4 By Cooperative union …..5 By trader ………………...6 On Large scale farm …...7 By factory ………............9 Other .............................8 Where sold (Col 9) Neighbour…………..…1 Local market/trade store ………….……….2 Secondary Market …..3 Marketing Coop …...…4 Farmer Association .….5 Largescale farm ………6 Trader at farm …….….7 Did not sell …………….9 Other ………..........…..8 By-product code (Col 10) Bran ……………...01 Cake ……………..02 Husk ……………..03 Juice ……………..04 Fiber ……………..05 Pulp ……………...06 Oil ………………..07 Shell ……………..08 Other ……….……98 Main product code (Col 4) Flour/meal..……….1 Grain………………2 Oil .. ………………3 Juice………………4 Fiber..……………..5 Pulp ………………6 Sheet ………..……7 Other …………….8 Main product (Col 4) Green leaves & Stem..1 Flower …4 Straw, dry stems etc …2 Fruit …...5 Root, tuber, etc ….…..3 Other …..8 319 Definition and working page for page 7 Temporary/annual crop codes for section 7.4 col 2 General Definition for Section 7.4 Secondary Crop Crop Product Main Products Code Name Question 7.4 (Section 8.0) 1 2 11 Maize Stems/straw Flour Bran 12 Paddy Stems/straw polished rice grain husk 13 Sorghum Stems/straw flour 14 Bulrush Millet Stems/straw flour 15 Finger Millet Stems/straw flour 16 Wheat Stems/straw flour Bran 17 Barley Stems/straw flour Bran 21 Cassava Leaves/stems flour 22 Sweet Potatoes Leaves 23 Irish potatoes Procedures for Questions 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans straw/stems 32 Cowpeas straw 33 Green gram straw 34 Pigeon peas stems 35 Chick peas straw 36 Bambara nuts straw/stems oil cake 41 Sunflower Stems oil Cake 42 Simsim straw oil Cake 43 Groundnut straw oil Cake 47 Soya beans straw oil Cake 48 Caster seed straw oil Cake 75 Pineapple Juice 50 Cotton straw fibre/seed oil cake 51 Tobacco 53 Pyrethrum straw insecticide 62 Jute fibre 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies dried powder 91 Amaranths 92 Pumpkins leaves 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 44 Oil Palm leaves oil outer oil inner cake 45 Coconut leaves/husk milk 46 Cashewnut Fruit fruit juice shell liquid Question Specific Definitions 52 Sisal stems fibre oil 54 Coffee stems beans husks 55 Tea stems 56 Cocoa stems cocoa cocoa butter 57 Rubber stems 58 Wattle stems 59 Kapok stems 60 Sugar Cane sugar/juice molasses ethanol 61 Cardamom 71 Banana leaves/stems juice 72 Avocado stems 73 Mango stems Juice 74 Paw paw Juice 76 Orange stems Juice 77 Grape fruit stems Juice 78 Grapes stems Juice 79 Mandarin stems Juice 80 Guava stems 81 Plums stems 82 Apples stems 83 Pears stems 84 Pitches stems 85 Lime/Lemon stems juice Bi-product (Sect 8.0) Agroprocessing & bi-products Secondary Products: Second most important product from a crop. Eg a household may consider the grain from maize as the primary product and the stems/straw as the secondary product. Note: Secondary products are NOT the same as bi-products. By-products are the result of a processing activity and are dealt with in section 8.0. Q 7.6 Details of Secondary Products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondent if the hh used any secondary products. List the crop names and codes in column 1 and 2 for those crops that the hh used secondary products. 2. For the listed crops give details of the secondary products used. 3. If no units were sold, enter "0" in columns 8 & 9. Agroprocessing and bi-products (Q 8.2) (Note: Agroprocessing refers to the processing of crops for hh utilisation and for sale) Main Product (Col 5): Main Product after processing. Eg for Paddy it may be the polished grain. For Maize it may be flour. Bi-Product code (Col 11): is the secondary residue after processing, eg for rice it may be the husk. for maize it may be the bran. Mainly used for (Col 5 & 11): - Consumed by household can mean eaten or utilised in another way (eg by animals) by the hh. Q 8.0 Agroprocessing & bi-products: 1. From the list of crops in Q 7.1.2, 7.2.2 & 7.3.2, ask the respondant if the hh processed any of these crops during the 2002/03 agriculture year. List the crop names and codes in column 1 and 2 for those crops that were processed by the hh. 2. For the listed crops give details of the secondary crops used. 3. If no main product or bi-product was sold enter "0" in columns 8 & 14. 4. If no bi-product was produced enter "0" in columns 10, 11, 12, 13 &14. 320 9.0 CROP STORAGE 9.1 Did the household store any crops during the 2002/03 agriculture year? (Yes =1, No=2) If the response is 'NO' go to section 10.0 9.2 For each of the listed crops provide the following details on storage Stor Normal Estimate S/N Crop Name -ed Method duration Main Estimate Y=1 of of pur Storage No=2 Storage storage -pose loss (2) (6) 9.2.1 Maize 9.2.2 Paddy 9.2.3 Sorghum/Millet 9.2.4 Beans, peas, etc 9.2.5 Wheat 9.2.6 Coffee 9.2.7 Cashewnut 9.2.8 Tobacco 9.2.9 Cotton 9.2.10 Groundnuts/bambara 10.0 MARKETING 10.1 Did the household sell any crops from the 2002/03 agriculture year? (Yes=1, No=2) (If the response is 'YES' or 'NO' go to section 10.2) 10.2 For each of the following crops what was the main marketing problem faced by the household during 02/03 Main Main Crop problem Crop problem 10.2.1 Maize 10.2.9 Vegetables 10.2.2 Rice 10.2.10 Tree Fruits 1 10.2.3 Sorghum/millet 10.2.11 Cashewnut 10.3.1 Biggest problem 10.2.4 Wheat 10.2.12 Cotton 10.3.2 2nd problem 10.2.5 Beans, peas etc 10.2.13 Tobacco 10.3.3 3rd problem 10.2.6 Cassava 10.2.14 Groundnuts/bamabara 10.3.4 4th problem 10.2.7 Bananas 10.2.15 Trees/timber/poles 10.3.5 5th problem 10.2.8 Coffee 10.2.16 Fish 10.4 What was the main reason for not selling crops during 2002/03 year ………………………………… (2) (5) (7) (1) 2 (1) Current Quantity Stored (kg) (2) (1) (3) (4) Main method of Storage (Col 4) In locally made traditional structure..1 In Improved locally made structure .2 In modern store …................……...3 In Sacks/open drum..............……...4 In airtight drum …………………….5 Unprotected pile ............................6 Other ...............………………........8 Duration of Storage (Col 5) Less than 3 months …....…….........1 Between 3 and 6 months ...............2 Over 6 months …………................3 Main purpose of storage (Col 6) Food for the household ………………1 To sell for higher price ……………….2 seed for planting.……………………..3 Other ………...……………………….8 Storage loss (Col 67) Little or no loss …………...1 Up to 1/4 loss …………….2 Between 1/4and 1/2 loss ..3 Over 1/2 loss …..………...4 Market problems (Q10.2 & 10.3 (Col 2)) Open market price too low …....01 Market too far ……………….......05 Government Regulatory board problems...09 No transport ……….......……....02 Farmer association problems .....06 Lack of market Information .......................10 Transport cost too high ….....…03 Cooperative Problems ................07 Other (specify) .........……………………....98 No buyer ……………….......…..04 Trade Union problems ...............08 Not Applicable ............................................99 Reason for not selling crops (Q10.4) Price too low ………….....................1 Farmer association problems ..…................4 Government regulatory board problems ....7 Production insufficient to sell…….....2 Cooperative Problems.................................5 Other (specify) .…………………….............8 Market too far ……………………. ...3 Trade Union problems ................................6 Not Applicable ……………………..............9 10.3 From the list of marketing problems below, for all produce rank the five most important problems 321 Definition and working page for page 8 Question Specific definitions (Section 9.0) Procedures for Questions Crop Storage, Section 9 Marketing problems Q 10.2 and 10.3 col 2: - Farmer Association: A village or community based group of farmers who have formed an organisation to purchase inputs/sell/store their products in order to achieve a better price for their products. - Cooperative Union: Large inter-village /community organisation set up on a district/regional or national basis for providing inputs, marketing and storing farmers products. - Government Regulatory board: Government control body for setting prices and controlling quality of certain agriculture commodities. Q 9.2 Details of Crop Storage: 1. For the crops listed indicate if the household stored any during 2002/03 in column 2. 2. Check that the crops correspond to the crop lists in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments 3. For the listed crops give details of storage. Q 10.2 Details on Crop Marketing: 1. For each of the crops listed indicate the main problems in marketing during 2002/03 in column 2. 2. Check if the crops correspond to the crop lists list in Q 7.1.2, 7.2.2 & 7.3.2. If there is a difference inquire on the reason why. It is possible that a crop was missed during the enumeration of these questions and if so make necessary amendments Working Area/calculation space Q 10.3 Ranking of market problems: Rank in order of importance the 5 most important marketing problems from the codes in the Market Problems code box. Method of Storage (column 4) - Locally made structure: The structures that have been inherited from their fore fathers - Improved locally made structure: Traditional structures that have been improved using modern technology. - Normal duration of storage: Often there are stored stocks from different seasons and different years. The normal duration refers to the number of months that the most of the crop is stored for. 322 11.0 ON-FARM INVESTMENT 11.1 Does the household practice irrigation (Yes=1, No=2) If the response is 'NO' go to section 11.3 S/N 11.1.1 11.2 Does the household have any erosion control/water harvesting facilities on their land (Yes=1, No=2) If the response is 'NO' go to section 12.0 Type of erosion control/ Number Year of Type of erosion control/ Number Year of S/N water harvesting of con- water harvesting of con- structure structures struction structure structures struction 11.2.1 Terraces 11.2.5 Tree belts 11.2.2 Erosion control bunds 11.2.6 Water harvesting bunds 11.2.3 Gabions/Sandbags 11.2.7 Drainage ditches 11.2.4 Vetiver Grass 11.2.8 Dam 12.0 ACCESS TO FARM INPUTS AND IMPLEMENTS 12.1 Give details of farm inputs used during the 2002/03 agriculture year S/N Quality of Input name Input 12.1.1 Chemical Fertiliser 12.1.2 Farm Yard Manure 12.1.3 Compost 12.1.4 Pesticide/fungicide 12.1.5 Herbicide 12.1.6 Improved Seeds 12.1.7 Other ……………. (acres) (4) (5) year (acres) Source of water water ated land this Area of irrig obtaining Method ofMethod of Irrigatable area (7) (8) (6) (3) (2) (3) next year Source of Fin (1) Yes =1,No=2 for not using Reason Plan to use applic -ation Used Yes=1 (1) (1) (3) (2) (2) Irrigation -ance (5) (4) Source (2) (1) (3) Source No=2 Distance to Source (Col 3) Cooperative ……………......01 Local farmers group …... ....02 Local market/Trade Store ...03 Secondary Market ...............04 Development project ….......05 Crop buyers ………….........06 Large scale farm …….….....07 Locally produced by hh .......08 Neighbour ...........................09 Other (specify) ……….........98 Not applicable ………….......99 Distance to source (Col 4) Less than 1 Km ………….1 Between 1 and 3km …….2 between 3 and 10 km.. …3 Between 10 and 20 km …4 20km and above ......…….5 not applicable ..… ….…..9 Quality of input (Col 7) Excellent ......…1 Good ..........…..2 Average ……...3 Poor ................4 Does not work .5 not applicable...9 Source of irrigation water (Col 1) River ………1 Borehole ……………..5 Lake ……...2 Canal …………………6 Dam ………3 Tap Water ……………7 Well ……....4 Method of obtaining water (Col 2) Gravity ………………………1 motor pump ……….4 Hand bucket ……………….2 Other ………..……8 Hand pump ………………...3 Method of application (Col 3) Flood …………………….1 Sprinkler …………………2 water hose.………………3 Bucket/watering can ……4 Reason for not using (Col 6) Not available …….......... …1 Price too high ......... …... ...2 No money to buy ...............3 Too much labour required..4 Do not know how to use......5 Input is of no use ...............6 Locally produced by hh ......7 Other ............…………......8 Not applicable ....……….....9 Source of finance (Col 5) Sale of farm products .1 Other income generating activities ….2 Remittances …...……..3 Bank Loan/Credit.…….4 produced on farm ...….5 Other ……….. ...……..8 Not applicable ..……….9 . . 323 Definition and working page for page 9 Overview of Investment activities (Section 11.0) Question Specific Definitions (Q 11.1) Question Specific Definitions (Q 11.3) Source of irrigation Water (Col 1): The main source of water from which water is obtained for irrigation. Method of obtaining water (Col 2): The mechanism by which the water is extracted from the source, Application Method (Col 3): How the water is applied on the field. - Flood - is the application of water down the slope of the land by means of gravity - Sprinkler - is the application of pressurised water through pipes. The water passes through a device which sprays the water onto the crop from above. Irrigatable Area (Col 4): The area the irrigation system is designed to cover in acres. Area of irrigated land this year (Col 5): Area of land under irrigation during the 2002/03 agric year. This is the physical area and NOT the cumulative area of 2 or more croppings. Erosion control/water harvesting structure (Col 1) Terraces: Are structures constructed on the side of a hill to provide a level ground to plant crops. They are often used to trap water for paddy/lowland rice production. Erosion Control Bunds: These are banks of earth/stones built perpendicular to the slope to slow down water and prevent erosion. They are different to Terraces in that the soil behind the banks are not level. Gabions: A gabion is a wire mesh box filled with rocks/stones and used to control or prevent gully erosion Sandbags Used to prevent or control gully erosion Tree belts/Wind breaks: A band of trees planted perpendicular to the prevailing wind whose main purpose is to slow down wind speed Water Harvesting bunds: A bank of earth constructed horizontal to the slope of the land to trap water. They are usually banana shaped. Dam: A bank of earth/material which traps river water to form a catchment of water behind it. Farm Inputs (Q 12.1.1 to 12.1.7) Farm yard Manure: An organic fertiliser made on farm composed of animal dung. Compost: An organic fertiliser made on farm from decomposed plant material Pesticide: Chemical used to either protect the plant from or kill insects, birds, molluscs, mites, etc attacking the plant Fungicide: is a chemical that s used to protect the plant from or control a fungal disease. Herbicide: A chemical used to control weeds. Investment activities: Investment activities refer to medium to long term farm development structures and projects. This can be Irrigation structures, erosion and water harvesting structures or other permanent or semi-permanent investment made on the land that the household owns. Q 11.1 Irrigation 1. If the hh practices irrigation give details on the main source, main method of obtaining and applying water. 2. Cross check column 8, Q 7.1.2, 7.2.2 & 7.3.2 to check if irrigation was used on any crops. Q 11.3 erosion control/water harvesting 1. Number of structures refers to the number of working/maintained structures and does not include derelict or irreparable structures. 2. Year of construction refers to the year that the structures were first constructed. It is not the year that the structures were last maintained. Q 12.0 Farm Inputs 1. Indicate in column 1 whether each of the inputs are used or not. 2. Complete cols 3, 4, 6, and 7 for inputs that are used and place '9' in column 5 (for not applicable). 3. Complete cols 5 & 7 for inputs not used. NOTE: Cross check column 6, 7, 8 & 9 , Q 7.1.2, 7.2.2 & 7.3.2 to check what inputs were used. 324 12.2 Give details of farm implements and assets used and owned by the household during 2002/03 agriculture year S/N rent -ed (3) 12.2.1 Hand Hoe 12.2.2 Hand Powered Sprayer 12.2.3 Oxen 12.2.4 Ox Plough 12.2.5 Ox Seed Planter 12.2.6 Ox Cart 12.2.7 Tractor 12.2.8 Tractor Plough 12.2.9 Tractor Harrow 12.2.10Shellers/threshers 13.0 USE OF CREDIT FOR AGRICULTURE PURPOSES 13.1 During the year 2002/03 did any of the hh members borrow money for agriculture (Yes = 1, No = 2) (if the response is 'NO' go to section 13.3) 13.2 Give details of the credit obtained during the agricultural year 2002/03 (if the credit was provided in kind , for example by the provision of inputs, then estimate the value in 13.2.9) Provided to Male = 1, Female 2 13.2.1 Labour 13.2.2 Seeds 13.2.3 Fertilisers 13.2.4 Agrochemicals 13.2.5 Tools/equipment 13.2.6 Irrigation structures 13.2.7 Livestock 13.2.8 Other ……………. 13.2.9 Value of Credit (Tsh.) 13.2.10 Value of repayment (Tsh.) 13.2.11 Period of repayment (months) 13.3 If the answer to question 13.1 above is 'NO' what is the reason for not using Credit? Equipment/Asset Name tick the boxes below to indicate the use of the credit Owned (2) (1) to indicate source use codes Source "a" (4) Source Used in Number Source (8) (7) (5) tick the boxes below to indicate the use of the credit tick the boxes below to indicate the use of credit Source "b" Source "c" (6) Yes=1,No=2 Plan to use next year Reason for not using of Fin -ance 2002/03 Yes 1,No=2 -ment of Equip Source of equipment (Col 5) Neighbour....................... ....…1 Development project .....5 Cooperative ............................2 Government .................6 Local farmers association…....3 Large scale farm ...…....7 market/Trade store ................4 Other (specify) .............8 Source of finance (Col 6) Sale of farm products ……………...1 Other income generating activities .2 Remittances ………………………..3 Bank Loan ………………………….4 Credit ……………………………….5 Other ……….. ……………………..8 Not applicable ..…………………….9 Reason for not using (Col 7) Not available …….......... …...1 Price too high ......... …... …..2 No money to buy/rent......…..3 Too much labour required….4 Equipment/Asset of no use …5 Other ……….………………..8 Not applicable ...................…9 Reason for not using credit (Q13.3) Not needed …1 Not available ...2 Did not want to go into debt.....3 Interest rate/cost too high......4 Did not know how to get credit....5 Difficult bureaucratic procedure ...6 Credit granted too late ...7 Other (specify) ...8 Dont know about credit ....9 Source of credit (Q 13.2-a, b and c)) Family, friend or relative....1 Commercial Bank…..2 Cooperative …...3 Savings & credit Soc ......4 Trader/trade store ……..5 Private individual ……...6 Religious Organisation/NGO/Project …7 Other (Specify)......................................8 325 Definition and working page for page 10 Question Specific Definitions (Q 12.2) Procedures for questions Question Specific Definitions (Q 13.0) Farm Implements (Col 1): Hand powered Sprayer: Knapsack or bicycle pump sprayer Reason for not using (Col 6): Be careful about using "too much labour required" as this code generally refers to hand hoes only. The codes for this should "NOT" be read out to the farmer as a prompt. Note: If remittance is given as the main source of finance check for a response to remittances in question 2.2.5 Section 13.0 Credit for Agriculture Purposes Credit is defined as finance in the form of cash or in-kind contributions (eg direct provision of inputs, machinery, livestock or other material) for the purpose of crop and livestock production whereby the value of the credit must be paid back to the borrower. The value of repayment may either be with interest or interest free. Credit may be paid back in the form of cash or agriculture produce. Section 13.0 Credit for Agriculture Purposes Value of credit: is the amount in cash received from the borrower. If the credit was paid in-kind, estimate the value of this. Value of repayment: This is the amount to be repaid to the borrower and includes the principal amount (value of credit) plus any interest repayment. If the credit is paid back in agriculture produce, then the cash value of this must be estimated. Period of repayment: This is the time in months the borrower has given for full repayment. Section 13.2 Source of agriculture credit If the farmer obtained credit from more than one source then use the columns "a" , "b" and "c" for the different sources of credit. Start with the main source of credit in column "a". NOTE: Check for use of inputs in column 7, 8 & 9 of questions 7.1.2, 7.2.2 & 7.3.2. Working Area/calculation space Q 12.0 Farm Inputs 1. Indicate in column 2 and 3 whether each of the implements were used or not. 2. Complete cols 4, 5, 6, and 8 for inputs that are used and place '9' in column 7 (for not applicable). 3. Complete cols 7 & 8 for inputs not used. 326 14.0 TREE FARMING/AGROFORESTRY 14.1 Did your household have any Planted Trees on your land during 2002/03 agric year? (Yes =1, No=2) If the response is 'NO' go to section 14.3 14.2 Give details of the planted trees you have on your land. Whe Ma Sec Number of Number of S/N re pl -in -ond Plank trees Pole trees Total Value anted Use Use Sold Sold (Tsh.) (2) (3) (4) (5) (6) (7) (8) (9) (10) 14.2.1 14.2.2 14.2.3 14.2.4 14.3 Does your village have a Community tree planting scheme (Yes=1, No=2) If the response is 'NO' go to section 15.0 14.4 Household involvement in community tree planting scheme S/N hh Involve (1) 15.0 CROP EXTENSION SERVICES 15.1 Did your household receive extension advice for crop production during 2002/03 (Yes=1,No=2) If the response is 'NO' go to section 16.0 Source of If you pay for Contact farmer No. of visits No. of message S/N extension extension, what /group member by extension adopted in the Quality of Extension Provider (Y=1,N=2) is the cost/yr (Yes=1,No=2) agency per year last 3 years Service 15.1.1 Government extension 15.1.2 NGO/development project 15.1.3 Cooperative 15.1.4 Large Scale farmer 15.1.5 Other………………… (4) Main (2) (3) Main use during (3) (5) Number of Poles Timber hh utilised Code -ment (1) Tree forest (Km) Number purpose (6) (7) (2) 2002/03 (4) of trees Distance to com -munity planted (1) Use (Col 4 & 5) Planks/Timber….....1 Shade ……...…5 Poles ………...……2 Medicinal……....6 Charcoal ………….3 Other ………….8 Fuel wood ...……...4 Where Planted (Col 3) Mostly on field/plot boundaries.1 Mostly scattered in fields …….2 Mostly in plantation/coppice …3 HH involvement (Col 2) Only planting ………………….....1 Only protection and thinning…....2 Only cutting …………………...…3 Most or all activities……………...4 Quality of service (Col 7) Very good .………...1 good …..…….2 Average……. …3 Poor…………4 No Good ………5 . Main Use during 02/03(Col 4) Poles ………….1 Not ready to use …...5 Timber logs …..2 Not allowed to use …6 Charcoal ….. ...3 Other (specify) …….8 Firewood ……..4 Main Purpose (Col 3) Erosion control………..1 Environment rehaiblitation …4 Production of poles …..2 Restoration of wildlife ………5 production of firewood..3 Other (specify) …….………8 327 Definition and working page for page 11 General Definitions for section 14.0 Question Specific Definitions Tree Name Guide Col 1 Code Local Name Botanical Name English Name Code Local Name Botanical Name English Name 01 Senna siamea Cassod tree 16 02 Msongoma Gravellia Silver oak 17 03 Mbarika Afzelia quanzensis Pod mahogony 18 04 Mkeshia Acacia spp Umbrella thorn 19 05 Msindano Pinus spp Pine 20 06 Mkaratusi Eucalyptus spp Red River Gum 21 07 Cyprus spp Cyprus tree 22 08 Mtondoo Calophylum inophyllum 23 09 Mvule Melicia excelsa Iroko 24 10 Mvinji Casurina equisetfilia Whistling oak 25 11 Msaji Tectona grandis Teak 26 12 Mkungu wa kienyeji Terminalia catapa Sea almond 27 13 Mkungu india Terminilia ivorensis Black afara 28 14 Muhumula Maesopsis berchemoides 29 15 30 Tree farming (Section 14.0) Pole trees (Col 6): These are young trees which have a maximum diameter of 6 inches at the bottom and are often used for house construction. They are often the thinning harvest after 3 - 5 years. Plank trees (Col 7): Trees for sawing into timber planks. Animal shade: Trees grown for the purpose of providing shade to animals. Crop Extension Services (Section 15.1) Contact Farmer: A farmer who is used by the extension agent as a focal point to demonstrate new interventions. The contact farmer then passes on the message to other farmers Group member: Member of a group under which the contact farmer leads Adoption: This is the uptake of an intervention for 2 or more years Tree Farming/Agroforestry This section refers to trees planted for wood (firewood, poles, planks, carving, charcoal, medicinal, etc, but NOT fruit trees). It does not include naturally growing trees on the farm (unless special care has been given to promote their establishment) or trees growing naturally on the communal areas. Tree farming is the planting of trees on an area of land for which the main purpose is the production and regeneration of trees for wood on that land. Agroforestry: is the planting of trees on land for the purpose of complementing other farming activities like crop and animal production. For the purpose of this questionnaire Agroforestry trees are trees planted on boundaries and scattered throughout fields. The main productive unit in this case is Crops and Livestock. Community tree planting scheme (Section 14.3) Community Forest: A forest planted on the communal land which is planted, replanted or spot planted by the members of the village. Section 14.2 Details of planted trees 1. Enter the tree codes of the main species grown by the hh 2. If no planks or poles are sold enter a "0" in columns 8, & 9. 3. Total value includes both value of hh utilised trees and sold trees. 4. If no trees were utilised by the hh or sold enter "0" in column 10 Section 15.1 Crop Extension Services 1. For each of the extension providers ask if the hh received extension during 2002/2003 agriculture year and indicate in column 2. 2. For each of the providers complete the rest of the columns 328 15.2 Crop Extension Messages Received Adopted Source of Received Adopted Source of S/N Advice Crop S/N Advice Crop Yes=1 Yes=1 Extension Yes=1 Yes=1 Extension Extension Message No=2 No=2 Extension Message No=2 No=2 15.2.1 Spacing 15.2.9 Crop Storage 15.2.2 Use of agrochemicals 15.2.10 Vermin control 15.2.3 Erosion control 15.2.11 Agro-processing 15.2.4 Organic fertiliser use 15.2.12 Agro-forestry 15.2.5 Inorganic fertiliser use 15.2.13 Bee Keeping 15.2.6 Use of improved seed 15.2.14 Fish Farming 15.2.7 Mechanisation/LST 15.2.15 Other 15.2.8 Irrigation Technology 16.0 LIVELIHOOD CONSTRAINTS From the list of constraints on the right select: List of constraints 16.1 the 5 most important problems 16.2 the 5 least important problems Order of most importanceConstraint Order of least importanc Constraint 16.1.1 most important 16.2.1 Least important 16.1.2 2nd most important 16.2.2 2nd least important 16.1.3 3rd most important 16.2.3 3rd least important 16.1.4 4th most important 16.2.4 4th least important 16.1.5 5th most important 16.2.5 5th least important 17.0 ANIMAL CONTRIBUTION TO CROP PRODUCTION 17.1 Did you use Draft animals to cultivate 17.2 Did you apply organic fertiliser your land during 02/03 (Yes=1, No=2) during 02/03 (Yes=1, No=2) (If no, go to question 17.2) (If no, go to question 18) Area S/N Area S/N Type of Number Number cultivated Type of organapplied Draft owned used (acres) Fertiliser (acres) (1) (2) 17.1.1 Oxen 17.2.1 FYM 17.1.2 Bulls 17.2.2 Compost 17.1.3 Cows 17.1.4 Donkeys (2) (3) (4) (3) (1) (2) (4) (1) (1) (2) (1) (2) (1) (2) (3) (4) . Source of extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) …8 Not applicable …….9 1. Access to Land 2. Ownership of Land 3. Poor farm Inputs 4. Soil Fertility 5. Access to improved seed 6. Irrigation facilities 7. Access to chemical Inputs 8. Cost of Inputs 9. Extension Services 10.Access to forest resources 11. Hunting and Gathering 12. Access to potable water 13. Access to credit 14. Harvesting 15. Threshing 16. Storage 17. Processing 18. Market Information 19. Transport costs 20. Distruction by animals 21. Stealing 22. Pests and Diseases 23. Local government taxation 24. Access to off Farm Income . . . . . 329 Definitions and working page for page 12 Question Specific Definitions Crop Extension Advice (Section 15.2) Mechanisation/LST: LST means Labour Saving Technology Section 16.0 Livelihood constraints 16.1 List the five most important problems in order of most importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are a problem. Place a 3 against the constraints that are a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the largest problems 3. Ask the farmer to list these in order of importance and enter in column 2 16.2 List the five least important problems in order of least importance: 1. Read out the list of constraints to the respondent and ask him to select the ones that are NOT a problem. Place an 2 against the constraints that are NOT a problem. 2. Read the selected constraints and ask the farmer to select 5 which create the least problems 3. Ask the farmer to list these in order of least importance and enter in column 2 330 18.0 CATTLE POPULATION, INTAKE AND OFFTAKE 18.1 Did the household own, raise or manage any CATTLE during 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 19.0) 18.2 Cattle Population as of 1st October 2003 18.3 Cattle Intake during 2002/2003 Number of Number S/N Cattle type Indigenous S/N Born 18.2.1 Bulls 18.3.1 18.2.2 Cows 18.3.2 18.2.3 Steers 18.3.3 18.2.4 Heifers 18.3.4 18.2.5 Male Calves 18.3.5 18.2.6 Female Calves 18.3.6 Grand Total Total Intake 18.5 Cattle diseases 18.4 Cattle Offtake during 2002/2003 Last Main S/N vacci Sou S/N Cattle type nated -rce 18.4.1 Bulls 18.5.1 18.4.2 Cows 18.5.2 CBPP 18.4.3 Steers 18.5.3 18.4.4 Heifers 18.5.4 18.4.5 Male Calves 18.5.5 18.4.6 Female Calves 18.5.6 FMD Total Offtake 18.6 Milk Production S/N Season 18.6.1 Wet Season 18.6.2 Dry Season Average Value per head (1) (1) (2) (3) (3) (2) (1) Purchased Beef Dairy (6) (2) Total Number Number of Improved (3) (4) (5) Number sumed by hh Sold to (5) Offtake Litres of milk/day No. of cattle milked/day Value/litre Sold/traded (6) (4) Number con Number given away/stolen died Number (4) Sold/day (Litres) (5) (10) (5) -overed Number Treated Number Died No. Rec Total Intake of Cattle (9) Total Cattle /obtained Number given (7) (8) Average value Number (7) (6) (6) (7) (1) (4) (3) per head Helmenthioitis (2) Infected Disease/ parasite Trypanosomiasi s Lumpy Skin Disease Tick Borne diseases Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q18.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ………......8 X X X X X X X X X X X X X X X X 331 Definitions and working page for page 13 General definitions for page 13 Question Specific Definitions (Section 18.0) Cattle type (Q 18.2 & 18.4, Col 1) Bull: Mature Uncastrated male cattle used for breeding Cow: Mature female cattle that has given birth at least once Steer: Castrated male cattle over 1 year Heifer: Female cattle of 1 year up to the first calving Calves: Young cattle under 1 year of age Cattle vaccination (18.5 col 1) ECF: East Coast Fever FMD: Foot and Mouth Disease CBPP: Contagious Bovine Pleura Pneumonia Average Value per Head (Q 18.3, (Col 7 & 9) & 18.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Cattle Intake during 2002/03: Cattle purchased, given or born which increases the number of cattle in the herd. Cattle Offtake during 2002/03: Cattle removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 13 Section 18.0 Cattle Population, Intake & Offtake. NOTE: Section 18.1 is for the current population (as of 1st October 2003); Section 18.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 18.4 is for diseases encountered during the agriculture year. 1. If the household has cows, you would normally expect them to have calves in column 8 2. If calves are reported in column 2, 3, or 4 (18.2.6, 18.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of cattle the importance of this must be reflected in Q 2.2.3 Section 18.5 If cattle are reported to have died in Column 5 then at least that number should be reported in 18.4 col 4 332 19.0 GOAT POPULATION, INTAKE AND OFFTAKE 19.1 Did the household own, raise or manage any GOATS during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 20.0) 19.2 Goat Population as of 1st October 2003 19.3 Goat Intake during 2002/2003 Number of Number S/N Goat type Indigenous S/N Born 19.2.1 Billy Goat 19.3.1 19.2.2 Castrated Goat 19.3.2 19.2.3 She Goat 19.3.3 19.2.4 Male Kid 19.3.4 19.2.5 She Kid 19.3.5 Grand Total Total Intake 19.4 Goat Offtake during 2002/2003 19.5 Goat diseases Last Main S/N Goat type S/N vacci Sou nated -rce 19.4.1 Male goat 19.4.2 Castrated Goat 19.5.1 19.4.3 She Goat 19.5.2 19.4.4 Male Kid 19.5.3 19.4.5 She Kid 19.5.4 Total Offtake 19.5.5 19.6 Milk Production S/N Season 19.6.1 Wet Season 19.6.2 Dry Season Tetanus Mange (1) Total Goat Average value Offtake per head (7) Foot Rot CC PP Helminthiosis (3) (4) (5) (6) Average Value of Goats per head (9) (10) Purchased Number given Number Total Intake for meat Number of Improved Total Dairy (1) (2) (3) (4) Sold/day (Litres) Treated Number sumed by hh away/stolen Number con -overed Died (2) parasite Infected Disease/ Number Number No. Rec Number (8) /obtained Number died (5) (7) (6) Number given (1) (2) (3) (4) Sold/traded (5) (6) (7) Litres of milk/day No. of Goats milked/day Value/litre Sold to (5) (6) (1) (2) (3) (4) Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 Sold to Q19.6 Col 5) Neighbour…….........1 Largescale farm ..5 Local Market..……...2 Trader at Farm ...6 Secondary Market ...3 Did not sell ..........7 Processing industry .4 Other ……….......8 X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X X X 333 Definitions and working page for page 14 Goat definitions for page 14 Question Specific Definitions (Section 19.0) Goat type (Q 19.2 & 19.4, Col 1) Billy Goat (he-goat): Mature Uncastrated male goat used for breeding Castrated goat: Male goat that has been castrated. She Goat: Mature female goat over 9 months of age Kid: Young goat under 9 months of age. Goat vaccination (19.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia LSD: Lumpy Skin Disease Average Value per Head (Q 19.3, (Col 7 & 9) & 19.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Goat Intake during 2002/03: Goat purchased, given or born which increases the number of goats in the herd. Goat Offtake during 2002/03: Goat removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 14 Section 19.0 Goat Population, Intake & Offtake. NOTE: Section 19.1 is for the current population (as of 1st October 2003); Section 19.2 and 18.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 19.4 is for diseases encountered during the agriculture year. 1. If the household has she goats, you would normally expect them to have kids in column 8 2. If kids are reported in column 2, 3, or 4 (19.2.6, 19.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of goats the importance of this must be reflected in Q 2.2.3 Section 19.5 If goats are reported to have died in Column 5 then at least that number should be reported in 19.4 col 4 334 20.0 SHEEP POPULATION, INTAKE AND OFFTAKE 20.1 Did the household own, raise or manage any SHEEP during the 2002/03 agriculture year? (Yes =1 No =2) (If no go to section 21.0) 20.2 Sheep Population as of 1st October 2003 20.3 Sheep Intake during 2002/2003 Number of Number S/N Sheep type Indigenous S/N Born 20.2.1 Ram 20.3.1 20.2.2 Castrated Sheep 20.3.2 20.2.3 She Sheep 20.3.3 20.2.4 Male lamb 20.3.4 20.2.5 She lamb 20.3.5 Grand Total 20.4 Sheep Offtake during 2002/2003 20.5 Sheep diseases Last Main S/N Sheep type S/N vacci Sou nated -rce 20.4.1 Ram 20.4.2 Castrated Sheep 20.5.1 20.4.3 She Sheep 20.5.2 20.4.4 Male lamb 20.5.3 20.4.5 She lamb 20.5.4 Total Offtake 20.5.5 CC PP Helminthiosis Trypa nsomiasis FMD parasite Average value Offtake per head Disease/ Total Sheep Infected Treated -overed Died (6) (7) Foot Rot (1) (2) (3) (4) (5) (5) (6) (1) (2) (7) (3) (4) Total (5) Number of Improved Number sumed by hh (1) (2) (3) (4) away/stolen died Sold/traded (8) (7) Number given Total Intake Average Value of Sheep /obtained Number Number con Number given Number (6) for Mutton Dairy Purchased per head (9) (10) Number Number No. Rec Number X X X Last Vaccinated (Col 6) 2003 ……………1 2000 …………....4 2002 …………....2 before 2000 …...5 2001 …………....3 Not Vaccinated...6 X X X X X X X X X X X X X X X X X X X X X Main Source of vaccine (Col 7) Private Vet Clinic ..1 Other ………..….8 District Vet Clinic ..2 Not applicable ….9 NGO/Project…....3 X X X X 335 Definitions and working page for page 15 Sheep definitions for page 15 Question Specific Definitions (Section 20.0) Sheep type (Q 20.2 & 20.4, Col 1) Ram: Mature Uncastrated male goat used for breeding Castrated sheep: Male sheep that has been castrated. Ewe: Mature female sheep over 9 months of age Lamb: Young sheep under 9 months of age. Sheep vaccination (20.5 col 1) FMD: Foot and Mouth Disease CCPP: Contagious Caprine Pleura Pneumonia Average Value per Head (Q 20.3, (Col 7 & 9) & 20.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Sheep Intake during 2002/03: Sheep purchased, given or born which increases the number of Sheep in the herd. Sheep Offtake during 2002/03: Sheep removed from the herd, either by selling, hh consumption, given away or stolen. Working area for page 15 Section 20.0 Sheep Population, Intake & Offtake. NOTE: Section 20.1 is for the current population (as of 1st October 2003); Section 20.2 and 20.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 20.4 is for diseases encountered during the agriculture year. 1. If the household has ewes, you would normally expect them to have kids in column 8 2. If lambs are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Sheep the importance of this must be reflected in Q 2.2.3 Section 20.5 If Sheep are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 336 21.0 PIG POPULATION AND PRODUCTION 21.1 Did the household own, raise or manage any PIGS during the 2002/03 agriculture year (Yes =1 No =2) (If no go to section 22.0) 21.2 PIG Population as of 1 st October 2003 21.3 Pig increase during 2002/2003 Number S/N Pig type Number S/N Born 21.2.1 Boar 21.3.1 21.2.2 Castrated male 21.3.2 21.2.3 Sow/Gilt 21.3.3 21.2.4 Male piglet 21.3.4 21.2.5 She piglet 21.3.5 Grand Total 21.4 Pig decrease during 2002/2003 21.5 Pig diseases/pests/conditions Last Main S/N Pig type vacci Sou nated -rce 21.4.1 Boar 21.4.2 Castrated male 21.5.1 21.4.3 Sow/Gilt 21.5.2 21.4.4 Male piglet 21.5.3 21.4.5 She piglet 21.5.4 Total Offtake 22.0 LIVESTOCK PEST & PARASITE CONTROL 22.3 Do you normally encounter a tick problem (Yes=1,No-2) (If the response is 'NO' go to section 22.5) 22.1 Did you deworm your animals during 2002/03 (Yes=1, No-2) 22.4 Which methods of tick control did you use (If the response is 'NO' go to section 22.3) 22.5 Do you normally encounter a tsetse fly problem (Y=1,N=2) 22.2 Which animals did you deworm? (Tick appropriate boxes) (If the response is 'NO' go to section 23.0) Cattle Goats Sheep Pigs 22.6 Which methods of control did you use Number given Purchased (3) (4) sumed by hh Number con Number given Number away/stolen /obtained (1) (2) Sold/traded (1) (2) Number died Average Value Increase per head (9) (10) Total Pig (4) Number Average value Offtake per head (5) (3) (5) Number No. Rec Disease/ -overed (6) (7) Number S/N Total Pig Number Died (1) (2) (3) (4) (5) parasite Infected Treated (6) (7) Anthrax Helmenthiosis Anemia ASF Main Source (Col 7) Private Vet Clinic ..1 District Vet Clinic ..2 NGO/Project….....3 Other ……….....…8 Not applicable ...…9 Last Vaccinated (Col 6) 2003 ..1 2000 ………….4 2002 ..2 before 2000 ….5 2001 ..3 Not Vaccinated.6 Control method (Q 22.4) None..1 Spraying ..2 Dipping..3 Smearing ..4 Other.8 Control method (Q22.6) None .1 Spray .2 Dipping .3 Trapping .4 Other .8 X X X X X X X X X X X X X 337 Definitions and working page for page 16 Pigs definitions for page 16 Question Specific Definitions (Section 21.0) Pigs type (Q 21.2 & 21.4, Col 1) Boar: Mature Uncastrated male pig used for breeding Castrated Pig: Male pig that has been castrated. Sow: Mature female pig that has given birth to at least one litter of pigs. Gilt: Female pig of 9 months up to the first farrowing. Piglet: Young pig under 3 months of age. Pig vaccination (21.5 col 1) ASF: African Swine Fever Average Value per Head (Q 21.3, (Col 7 & 9) & 21.4 (Col 3, 5 & 7)) In these columns give the average value per head during 2002/03. For given, traded, consumed by the hh & given away/stolen estimate the value. Pig Intake during 2002/03: Pigs purchased, given or born which increases the number of Pigs in the production unit. Pig Offtake during 2002/03: Pigs removed from the production unit, either by selling, hh consumption, given away or stolen. Working area for page 16 Section 21.0 Pig Population, Intake & Offtake. NOTE: Section 21.1 is for the current population (as of 1st October 2003); Section 21.2 and 21.3 is for movement in and out of the herd during the 2002/03 agriculture year. Section 21.4 is for diseases encountered during the agriculture year. 1. If the household has sows, you would normally expect them to have piglets in column 8 2. If piglets are reported in column 2, 3, or 4 (20.2.6, 20.2.5) then there must be at least that number repeated in column 8 Note: If the farmer reports sales of Pigs the importance of this must be reflected in Q 2.2.3 Section 20.5 If Pigs are reported to have died in Column 5 then at least that number should be reported in 20.4 col 4 338 23.0 Other Livestock currently available and details of consumption and sales during the last 12 months Animal type 23.1 Indigenous Chicken 23.2 Layer 23.3 Broiler 23.4 Ducks 23.5 Turkeys 23.6 Rabbits 23.7 Donkeys 23.8 Horses 23.9 Other …………… 24.0 CHICKEN DISEASES 24.1 Newcastle Disease 24.2 Gumboro 24.3 Coccidiosis 24.4 Chorysa 24.5 Fowl typhoid 25.0 LIVESTOCK PRODUCTS 25.1 Eggs 25.2 Hides 25.3 Skins 26.0 List in order of importance the outlets for 27.0 Access to functional Livestock structures the sale of Livestock /accessories Impo Out Outl Outlets Type Source Distance -rtan Outlets -lets -ets for S/N of of to struct S/N -ce of for for for Chick structure/accessory Structure -ure (Km) outlet Cattle Goat Pigs -ens (1) (3) (5) 27.1 Cattle Dip 26.1 1st 27.2 Spray Race 26.2 2nd 27.3 Hand powered sprayer 26.3 3rd 27.4 Cattle crush 26.4 4th 27.5 Primary Market 26.5 5th 27.6 Secondary Market 27.7 Abattoir 27.8 Slaughter Slab 27.9 Hide/skin shed 27.10 Input supply 27.11 Veterinary Clinic 27.12 Village holding ground 27.13 village watering point/dam 27.14 Drencher (6) (2) (4) Outlets for Sheep (3) (4) Average Value/unit (2) (1) (1) (2) (3) Sold during 2002/03 Current Number Number Average Value/head Consumed during 2002/03 (5) Number Average Value/head Number Number Recovered Number infected Number Treated Number Died Consumed/utilised during 2002/03 Number Average Value/unit Sold during 2002/03 Outlet code (Col 2, 3, 4 & 5) Trader at farm….………….….1 Abattoir/factory..………5 Local Market ……….. ……..…2 Another farmer ………6 Secondary market/auction.…..3 Other (Specify)……….8 Neighbour …………………….4 Source of structure (Q27.0 - Col 2) Owns …………………………..1 NGO …………………..…6 Cooperative ...................……..2 Large scale farm ……..…7 Local farmers association …... 3 Other ........... …………...8 Gov extension/veterinary …….4 Not applicable .………......9 Development project ……. …..5 X X X X X X X X . . . . . . . . . . . . . . X 339 Definition and working page for page 17 Question Specific Definitions Section 26.0) Procedures for questions Question Specific Definitions Section 27.0) Access to functional Livestock Structures/accessories (Section 27.0): NOTE: The structures must be functional. If they are not working/derelict then they should not be included. The distance to the next nearest functional structure should be taken. Spray Race: A fixed spray structure on an animal race for spraying acaricide Cattle crush: Corridor structure for restraining cattle. Abattoir: Large building designed for slaughtering a large amount of animals. It normally has complex structures to assist in the slaughter and storage and a high level of hygiene is maintained. Slaughter Slab: Concrete slab designed fos slaughtering a small amount of animals Hides: obtained from Cattle Skins: Obtained from sheep and goats Hide/Skin Shed: Shed for curing/tanning animal skins and hides Village holding Pen: Enclosure for containing large amount of livestock which is owned communally. Drencher: Device for orally administering medicine to livestock. If no product was sold in 2002 enter "0" in columns 6, 7& 9. Section 26.0 - Outlets for livestock: Using the codes enter the outlets for the sale of different livestock in order of importance. If there are, for example, only 2 outlets mark the rest with a "X". Section 23.0 - Other Livestock: 1. The current number includes both adult and young animals. For example The number of chickens in col 1 would include adults and chicks. 340 28.0 FISH FARMING 28.1 Was Fish farming carried out by this household during 2002/2003? (Yes =1, No=2) (If the response is 'NO' go to section 29.0) 28.2 Specify details of fish farming practices Product Fish Sourcefrequency S/N ion unit farming of fing of stocking number system -erling (No/year) (1) (2) 28.1.1 28.1.2 28.1.3 29.0 LIVESTOCK EXTENSION 29.1 Did you receive livestock extension advice during 02/03 (Yes=1,No=2) (If the response is 'NO' go to section 30.0) Received Adopted Source of 29.2 For the following Livestock Extension Service Providers give details S/N Advice Yes=1 Livestock If you pay for Contact far No. of visits No. of mess Quality Livestock Extension Message Yes=1,No=2 No=2 Extension S/N extension, what -mer/group by extension -ages adopted of Extension Provider is the cost/yr member agency/year in the last 3 yrs Service 29.1.1 Feed and Proper feeding (Y=1,N=2) 29.1.2 Housing (Goat, Dairy, Poultry, Pigs) 29.1.3 Proper Milking 29.2.1 Government 29.1.4 Milk Hygiene 29.2.2 NGO/dev project 29.1.5 Disease control (dipping/spraying) 29.2.3 Cooperative 29.1.6 Herd/Flock size and selection 29.2.4 Large Scale farmer 29.1.7 Pasture Establishment 29.2.5 Other…………… 29.1.8 Group formation and strengthening 29.1.9 Calf rearing 30.0 GOVERNMENT REGULATORY PROBLEMS 29.1.10 Use of improved bulls 31.1 Did you face problems with government regulations during 2002/03 (Y=1, N=2) 29.1.11 Other livestock extension List in order of importance Problem code 30.1.1 1st 30.1.2 2nd 30.1.3 3rd (4) (5) (3) (6) (1) (2) (3) (4) (7) (8) (9) (10) (11) (12) Mainly sold to of fish (m2) Tilapia Carp Other fish harvested harvested sold of fish weight weight Size of unit/pond Number of Number of stocked fish (5) (6) (1) (2) (3) (4) 1 2 3 Source of fingerlings (Col 4) Own pond ………………1 NGO/Project...3 P rivate trader ...5 Government Institution ..2 Neighbour …..4 Other……………8 Mainly sold to (Col 12) Neighbour……....1 Secondary Market......3 Largescale farm ........5 Did not sell .................7 Local Market..…..2 Processing industry ....4 Trader at Farm .........6 Other .........................8 Quality of service (Col 6) Very good ...1 good ….2 Average…3 Poor…4 No Good ...5 Source of livestock extension (Col 4) Government …..1 NGO/Dev project ..2 Cooperative …3 Large scale farmer …..4 Other (Specify) ….8 Farming System (Col 2) Natural Pond. ..1 Natural Lake…..3 Other …..8 Dug out pond...2 Water resevoir..4 Problem code Land ownership by government …….1 Restriction of sale between regions ..2 Import of food items …………………3 Other (specify)……………………….8 (If the response is no go to section 31.0) 341 Definitions and working page for page 18 General definitions for Section 28.0 Question Specific Definitions (Section 28.2) Production unit number (Col 1): A production unit is a pond river/lake which is treated as a separate entity for the production of fish eg it may be by virtue of manageable size, maturity of fish, type of fish etc. Eg a farmer may have 3 fish ponds. (each one is a separate production unit). Frequency of stocking (Col 5): What is the number of times the farmer puts new fingerlings into the pond each year. Fingerlings: These are young immature fish used for stocking ponds. Sold: (Col 10 & 11) If no fish were sold enter "0" in column 10 and 11) Fish farming: Refers to the rearing/production of fish. It is different to fishing in that the fish have to be reared and fed in fish farming. Fishing traps or captures naturally occurring fish in rivers, lakes and the sea and should not be included in this section. Working area for page 18 Livestock Extension Services (Section 29.1) Adopted (Col 3): This is the uptake of an intervention for 2 or more years Livestock Extension Service providers (Section 29.2) Contact Farmer: A farmer who is used by the extension services as a focal point to demonstrate new interventions to. The contact farmer then passes on the message to other farmers Adopted (Col 5): This is the uptake of an intervention for 2 or more years 342 31.0 LABOUR USE 32.0 SUBSISTENCE vs NON-SUBSISTENCE 31.1 Who is mainly responsible for 32.1 Indicate if any members of the household was involved in the undertaking the following tasks: following activities and assess the percentage used for subsistence/consumption by the household: Tick i Main Tick if Activity carrie respo hh was Estimate Estimate % S/N out by-nsib S/N Activity involved % used forused for noCheck hh -ility in activitysubsistancesubsistenceTotal (1) (5) 31.1.1 Land Clearing 32.1.1 Crop production 31.1.2 Soil preparation (by hand) 32.1.2 Livestock production 31.1.3 Soil preparation (oxen/tractor) 32.1.3 Vegetable production 31.1.4 Planting 32.1.4 Tree cutting for firewood 31.1.5 Weeding 32.1.5 Tree logging for poles 31.1.6 Crop Protection 32.1.6 Tree logging for timber 31.1.7 Harvesting 32.1.7 Tree logging for charcoal 31.1.8 Crop processing 32.1.8 fishing 31.1.9 Crop marketing 32.1.9 bee keeping 31.1.10 Cattle rearing/husbandry 32.1.10 31.1.11 Cattle herding 32.1.11 31.1.12 Cattle marketing 32.1.12 Remittances 31.1.13 Goat/sheep rearing/husbandry 31.1.14 Goat and sheep herding 31.1.15 Goat and sheep marketing 31.1.16 Milking 33.0 ACCESS TO INFRASTRUCTURE & OTHER SERVICES 31.1.17 Pig rearing/husbandry Distance in Distance in 31.1.18 Poultry keeping S/N Type of service Km S/N Km 31.1.19 Collecting Water (2) 31.1.20 Collecting Firewood 33.1 Primary School 32.7 Feeder Road 31.1.21 Pole cutting 33.2 Secondary School 32.8 All weather road 31.1.22 Timber wood cutting 33.3 Health Clinic 32.9 Tarmac road 31.1.23 Building/maintaining houses 33.4 Hospital 32.10Primary market 31.1.24 Making Beer 33.5 District Capital 32.11Secondary market 31.1.25 Bee keeping 33.6 Regional Capital 32.12Tertiary market 31.1.26 Fishing 31.1.27 Fish farming No of Satisfied 31.1.28 Off-farm income generation S/N Type of service visits/year with service 33.13 Vet Clinic 33.14 Extension Centre 33.15 Research Station 33.16 Plant protection Lab 33.17 Land registration office 33.18 Livestock Dev Centre (4) (3) (1) (1) (2) (3) (4) Type of service (1) (2) (3) (1) (2) (2) Distance in Km permanent employment/off farm temporary employment/off farm Responsibility (Col 3) HH head alone ….1 Girls ……….………….. …..6 Adult Males ……..2 Boys & Girls …………...…..7 Adult Females…..3 All household members..….8 Adults...………… 4 Hired labour ………………..9 boys ……………. 5 . . Satisfied with service (Col 4) Very good .…….1 Average…….3 No good ……5 Good …………..2 Poor ………..4 Not applicable 9 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . . . . . . . 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 . . . . . 343 Definition and working page for page 19 Question specific definitions (Section 31.1) Procedures for (Section 31.1) Question Specific Definitions (Section 32.0.0) Activity (Col 1): Land Clearing: Refers to removing trees/bush/grass prior to ploughing Soil Preparation: Refers to the seedbed preparation (ploughing, harrowing, etc). Cattle Rearing: Tending to cattle at home, eg assisting with births, castration,etc. Different livestock keeping activity to herding. Cattle Herding: Moving livestock from place to place for grazing and water. If herding is carried out the respondent must also give a response to rearing/husbandry Section 31.1 ((Labour use) 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 27.1.1 and complete column 3. 3. Make sure you stress MAINLY responsible. NOTE: If an activity has been mentioned previously in the questionnaire eg that the hh keeps chickens, make sure a response is obtained in the appropriate place ie poultry keeping. If off-farm income generation is mentioned, check for responses to off farm income in other parts of the questionnaire Activity (Col 1): Subsistence: For the family’s survival, rather than for the generation of cash. This includes feeding the hh, provision of water and fuel for cooking. The source of these products are usually from the land resources available to the family. Remember that not all cash earnings are for non subsistence purposes/activities as cash can be used to purchase subsistence items eg food. Non -subsistence: Cash used for items and activities which are not crucial for the survival of the family. This includes modern medication, non working clothes, refined beer, school fees, etc. Section 32.0 - Subsistence vs Non- subsistence 1. For each listed activity in column 1, place a tick in column 2 if any member of the household was involved in that activity during the 2002/03 agriculture year. 2. After completing column 2 return to the first activity in row 32.1.1 and complete column 3 & 4. For each activity make an assessment of the percentage used for subsistence survival and the percent converted to cash for non subsistence goods and items. 3. Make sure you stress MAINLY responsible. NOTE: Cross check the responses with previous sections in the questionnaire. eg if a response is given to remittances check for an entry in question 2.2.5 344 34.0 HOUSEHOLD FACILITIES 34.1 House Construction 34.2 Household assets For the main dwelling, what are the main building Does your household own the following? materials used in the construction of the following Y=1 Asset N=2 34.1.1: Roof 34.1.2Number of rooms 34.2.1Radio/cassette, music system) 34.2.2Telephone (landline) 34.2.3Telephone (mobile) 34.2.4Iron 34.2.5Wheelbarrow 34.2.6Bicycle 34.2.7Vehicle 34.2.8Television 34.3 Energy use by the Household 34.4 Access to drinking water Main sou Distance Time to and Season -rce of to source from source Energy use and access by the household drinking (in km) (Hour : minute) water 34.3.1 Lighting 34.3.2 Cooking 34.4.1Wet Season 34.4.2Dry Season 34.5 Access to toilet facilities 34.6 Food consumption patterns 34.5.1 What type of toilet does your hh use 34.6.1Number of meals the hh normally has per day 34.6.2Number of days hh consumed meat last week 34.6.3How often did the hh have problems in satisfying the food needs of the hh last year? 34.7 Source of Household income 34.7.1 What is the households main source of cash income? Main Source of energy for (4) (1) (2) (3) Roof Material Iron Sheets.……1 Tiles ………...…2 Concrete ……...3 Asbestos ….….4 Grass/leaves.....5 Grass & mud.....6 Other (Specify) 8 . : Lighting energy Mains electricity……01 Solar …………….…02 Gas (biogas) ………03 Hurricane Lamp .….04 Pressure Lamp ……05 Wick Lamp ….……..06 Candles ...…………07 Firewood ………….08 Other (specify) ….. 98 Cooking energy Mains electricity……01 Solar …………….…02 Gas (hh biogas) ..…03 Bottled gas ………..04 Paraffin/kerocine.….05 Charcoal……………06 Firewood …………..07 Crop Residues ……08 Livestock dung ……09 Other (specify) ……98 Main Source of drinking water Piped water …………………..……..…01 Covered rainwater catchment ...07 Protected well ……. ………….…….…02 Uncovered rainwater catchment 08 Protected/covered spring ... .…...……03 Water Vendor ............................09 Unprotected Well ……………….. …..04 Tanker truck ......................……10 Unprotected spring ………….…… …05 Bottled water .............................11 Surface water (lake/dam/river/stream)06 Other (Specify) ..........................98 Problems satisfying hh food needs (row 34.6.3) Never ……………………1 Seldom ………………….2 Sometimes ……………..3 Often ……………………4 Always …………………..5 Source of Income codes Sale of food crops …...........01 Wages or salaries in cash .....07 Sale of Livestock…………...02 Other casual cash earnings ..08 Sale of livestock products ...03 Cash remittances ..................09 Sale of cash crops…………04 Fishing ..................................10 Sale of forest products …...05 Other .....................................98 Business income.................06 Not applicable ........................99 Type of toilet No toilet/bush………….1 Improved pit latrine - hh owned…….4 Flush toilet ..…………..2 Other type (specify) …………………5 Pit latrine - traditional ..3 . : 345 Definition and working page for page 20 Household facilities (Section 34): Number of rooms used for sleeping in the household (Q 34.1) Include sitting room, dining room, kitchen, etc if used for sleeping. It also includes rooms outside the main dwelling A room is defined as a space which is separate from the rest of the building by a permanent wall or division. A building/house that is not divided into rooms is considered to have one room. Household assets (Q 34.2): these assets must be functioning. Do not include if broken. Access to drinking water (Q 34.4): If there is more than one source, use the one, which the hh uses most frequently. Main source of hh cash income: Activity that provides the hh with the most cash during 2002/03 agriculture year. 346 Average/maximum yields Use this table to compare the yields calculated in sections 7.1, 7.2, and 7.3. They are STRICTLY to be used as guidelines only and the sole purpose is to assist in getting the correct area and harvest for each crop Crop Crop Name Average Name Average 11 Maize 86 Cabbage 12 Paddy 87 Tomatoes 13 Sorghum 88 Spinach 14 Bulrush Millet 89 Carrot 15 Finger Millet 90 Chillies 16 Wheat 91 Amaranths 17 Barley 92 Pumpkins 21 Cassava 93 Cucumber 22 Sweet Potato 94 Egg Plant 23 Irish potatoes 95 Water Mellon 24 Yams 96 Cauliflower 25 Cocoyams 52 Sisal 26 Onions 54 Coffee 27 Ginger 55 Tea 31 Beans 56 Cacao 32 Cowpeas 57 Rubber 33 Green gram 58 Wattle 34 Pigeon pea 59 Kapok 35 Chick peas 60 Sugar Cane 36 Bambara nut 61 Cardamom 41 Sunflower 71 Banana 42 Simsim 72 Avocado 43 Groundnut 73 Mangoes 47 Soyabeans 74 Papaw 48 Caster seed 76 Orange 75 Pineapple 77 Grape fruit 50 Cotton 78 Grapes 51 Tobacco 79 Mandarin/tange 53 Pyrethrum 80 Guava 62 Jute 81 Plums 44 Palm Oil 82 Apples 45 Coconut 83 Pears 46 Cashewnut 84 Pitches Max kg/ha Average Max kg/acre kg/ha Average Max Max 1200 700 750 350 300 1200 1400 3000 600 750 4000 2500 400 300 600 500 600 600 300 600 1300 300 25000 300 500 800 1200 2000 9 6250 4000 3500 3000 2500 4500 2300 7000 8000 8500 10000 5000 1300 1750 2000 1500 4000 1700 1000 4000 2500 750 60000 1500 2000 3500 5000 8000 60/tree 486 283 304 142 121 486 567 1215 243 304 1619 1012 0 0 162 121 0 243 202 243 243 121 243 526 121 10121 121 202 0 324 486 810 4 2530 1619 1417 1215 1012 1822 931 2834 3239 3441 4049 2024 0 0 526 709 0 810 607 1619 688 405 1619 1012 304 24291 607 810 0 1417 2024 3239 24 0 0 0 0 0 0 0 0 0 0 0 324 202 1012 81 162 0 0 24291 0 4049 0 4049 20243 8097 12146 2024 8097 2834 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10121 40 4049 405 567 0 0 60729 0 20243 0 10121 28340 16194 20243 12146 16194 14170 0 0 0 0 800 500 2500 200 400 60000 10000 10000 50000 20000 30000 5000 20000 7000 25000 100 10000 1000 1400 150000 50000 25000 70000 kg/acre 35000 40000 50000 30000 40000 347 Back Page Reference material This page contains reference information that may be required to complete some of the questions in the questionnaire. Weights and measures Conversions 1 hectare = 10,000 sq metres (100 x 100 metres) 1 hectare = 2.47 acres 1 kilometre = 1000 metres 1 mile = 1.61 Kilometres 1 acre = 4840 square yards (110 x 44 yards) Kg equivalents The following standards may be used as a guide to obtain kg if the reported unit is different. Only use these conversions if the respondent is unable to provide weights in kgs. Crop Crop Name Name Name Name 11 Maize 100 18 Rumbesi 140 86 Cabbage 50 12 Paddy 75 15 87 Tomatoes 90 13 Sorghum 100 18 88 Spinach 45 14 Bulrush Millet 100 18 89 Carrot 110 15 Finger Millet 120 20 90 Chillies 85 16 Wheat 75 15 91 Amaranths 50 17 Barley 75 15 92 Pumpkins 60 21 Cassava 60 12 93 Cucumber 80 22 Sweet Potatoe 80 16 94 Egg Plant 70 23 Irish potatoes 80 16 95 Water Mellon 80 24 Yams 80 16 96 Cauliflower 50 25 Cocoyams 80 16 52 Sisal 130 26 Onions 80 16 54 Coffee 55 27 Ginger 75 15 55 Tea 60 31 Beans 100 20 56 Cacao 60 32 Cowpeas 100 20 57 Rubber 33 Green ram 100 20 58 Wattle 90 34 Pigeon pea 100 20 59 Kapok 35 Chick peas 100 20 60 Sugar Cane 120 36 Bambara nut 100 20 61 Cardamom 100 41 Sunflower 60 12 71 Banana 120 42 Simsim 100 20 72 Avocado 140 43 Groundnut 50 10 73 Mangoes 130 47 Soyabeans 100 20 74 Papaw 100 48 Caster seed 100 20 76 Orange 130 75 Pineapple 90 18 77 Grape fruit 120 50 Cotton 50 10 78 Grapes 80 51 Tobacco 70 14 79 Mandarin/tange 110 53 Pyrethrum 60 12 80 Guava 110 62 Jute 50 10 81 Plums 110 44 Palm Oil 100 82 Apples 110 45 Coconut 75 83 Pears 110 46 Cashewnut 80 84 Pitches 110 Non-standard Bag Tin kgs Bag Tin kgs Number of Kgs Number of Kgs Standard Non-standard Standard For official use only: If a question has a query, an indication will be made by the supervisor/data entry controller on the front page of the questionnaire. This space is to note what and where the problem is, the action required to be taken and the responsible person to take follow up action. Nature of the problem: _____________________________________________________________________________________________ _________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________ Action Required: National supervisor action Field supervisor action Overall Status: Does not affect overall integrity of the questionnaire. Discard and resample More data is required before it can be used Discard as missing data | false |
# Extracted Content UNITED REPUBLIC OF TANZANIA TANZANIA CLIMATE SMART AGRICULTURE PROGRAMME COORDINATED BY MINISTRY OF AGRICULTURE, FOOD SECURITY AND COOPERATIVES AND VICE PRESIDENT’S OFFICE 2015 – 2025 Tanzania Climate Smart Agriculture Program 2015 - 2025 i Contents LIST OF TABLES ................................................................................................................................ iv LIST OF FIGURES .............................................................................................................................. iv FOREWORD ..................................................................................................................................... vi ACKNOWLEDGEMENT .................................................................................................................. viii ACRONYMS AND ABBREVIATIONS ................................................................................................ ix EXECUTIVE SUMMARY .................................................................................................................. xii 1.0 INTRODUCTION ....................................................................................................................... 1 1.1 Background ......................................................................................................................... 1 1.2 Alignment with the Comprehensive African Agriculture Development Programme, National Development Goal, Agriculture Sector Strategies, National Climate Change Strategy and Action Plans, Water Resources Management Strategic Interventions and Action Plan for Climate Change Adaptation ........................................................................ 2 1.3 Preparation Process ........................................................................................................... 3 2.0 SITUATION ANALYSIS ............................................................................................................. 4 2.1 General Trends ................................................................................................................... 4 2.2 Agricultural Production Trends ....................................................................................... 4 2.2.1 Crop Production .......................................................................................................... 4 2.2.2 Livestock Production ................................................................................................. 7 2.2.3 Fisheries Production .................................................................................................. 8 2.2.4 Forest Resources ........................................................................................................ 9 2.3 Food Consumption and Nutrition Trends ....................................................................... 9 2.3.1 Levels of food consumption...................................................................................... 9 2.3.2 Nutrition trends ........................................................................................................ 10 2.4 Enabling Policy Environment ......................................................................................... 10 Agricultural Sector ............................................................................................................. 12 National Agricultural Policy .............................................................................................. 12 Tanzania Climate Smart Agriculture Program 2015 - 2025 ii National Climate Change Strategy (NCCS) ..................................................................... 13 2.5 Constraints to Agriculture Development and Growth ............................................... 13 2.5.1 Land Degradation and Soil Health ......................................................................... 13 2.5.2 Climate Change and Variability ............................................................................. 14 2.5.3 Agricultural Finance and Investments .................................................................. 19 2.6 Agricultural Growth Potential and Sources of Growth .............................................. 20 3.0 VISION AND OBJECTIVES ..................................................................................................... 21 3.1 Vision ................................................................................................................................. 21 3.2 Objectives ......................................................................................................................... 21 4.0 PROGRAMATIC RESULT AREAS ............................................................................................ 23 4.1 Result Area 1: Improved Productivity and Incomes ................................................... 23 4.1.1 Component 1: Improved productivity and nutrition .......................................... 23 4.1.2 Component 2: Irrigation and agricultural water management ........................ 24 4.1.3 Component 3: Improved Food Storage and Distribution ................................... 25 4.1.4 Component 4: Increased Growth of Incomes ...................................................... 26 4.2 Result Area 2: Building resilience and associated mitigation co-benefits............. 28 4.2.1 Component 1: Improve soil health, and restore degraded lands .................... 28 4.2.2 Component 2: Conservation of Natural Resources and Catchments ............... 29 4.2.3 Component 3: Insurance and Other Safety Nets ................................................. 31 4.2.4 Component 4: Early Warning System and Emergency Preparedness .............. 31 4.2.5 Component 5: Synergies in adaptation and mitigation enhanced ................... 32 4.3 Result Area 3: Value Chain Integration ........................................................................ 33 4.3.1 Component 1: Value addition process for agricultural products ..................... 33 4.3.2 Component 2: Increased competitiveness and enhanced integration into domestic, regional and international markets .............................................................. 33 4.4 Result Area 4: Research for Development and Innovations ..................................... 35 Tanzania Climate Smart Agriculture Program 2015 - 2025 iii 4.4.1 Component 1: Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain .................................................. 35 4.4.2 Component 2: Research Extension Linkage strengthened and made functional by 2018 ..................................................................................................................................... 36 4.5 Result Area 5: CSA Knowledge, Extension and Agro-weather Services .................. 36 4.5.1 Component 1: CSA knowledge generation and dissemination.......................... 36 4.5.2 Component 2: Enhance extension, climate information services and agro- weather advisories ............................................................................................................. 37 4.6 Result Area 6: Improved Institutional Coordination .................................................. 38 4.6.1 Component 1: Improve Inter-Ministerial and Local Government Coordination ............................................................................................................................................... 38 4.6.2 Component 2: Partnerships with private sector and civil society organizations ....................................................................................................................... 39 4.6.3 Component 3: Programmatic Coordination with Development Partners strengthened ....................................................................................................................... 40 5.0 COORDINATION FRAMEWORK ............................................................................................. 41 5.1 Institutional Arrangements ............................................................................................ 41 5.2 Coordination of Activities ......................................................................................... 41 6.0 ROLES AND RESPONSIBILITIES OF DIFFERENT SECTORS ............................................ 43 6.1 MAFC and MANR Divisions and Units ........................................................................ 43 6.2 Ministries, Departments and Agencies (MDAs) ...................................................... 43 6.3 Non-State Actors ......................................................................................................... 43 6.4 Sub-National Entities ................................................................................................. 44 7.0 MONITORING AND EVALUATION .................................................................................... 46 8.0 TEN - YEAR PROGRAMME FINANCING FRAMEWORK ................................................... 47 8.1 Cost Estimates and indicative Financing Plan ............................................................ 47 ANNEXES ....................................................................................................................................... 49 Annex I: Tanzania Map ........................................................................................................... 49 Annex IIa: Tanzania Agricultural Zones .............................................................................. 50 Tanzania Climate Smart Agriculture Program 2015 - 2025 iv Annex IIb: Tanzania Agricultural Map ................................................................................. 53 Annex III: Agricultural production ....................................................................................... 54 Annex IV: Agriculture Sector Financing Gap (TShs) 2010/2011 – 2014/2015 ............... 56 Annex V: Resource Requirement for Zanzibar................................................................... 56 Annex VI: Wood Fuel Demand and Consumption .............................................................. 57 Annex VII: Logical Framework Matrix or Program Design Matrix ............................... 58 Annex VIII: Budget Estimates for 2015 - 2025 ................................................................... 66 LIST OF TABLES Table 1: Share of Agriculture in the National Gross Domestic Product: 2005 - 2013 ..................... 4 Table 2: Production of livestock products 2008/2009 to 2013/2014 ............................................. 7 Table 3: Trends in per capita supply of major foods groups (in g/per day) .................................... 9 Table 4: The prevalence of various forms of nutrient deficiencies in Tanzania according to population groups ......................................................................................................................... 10 Table 5: Key policies relevant for CSA implementation and scale out in Tanzania ....................... 11 Table 6: Roles and Responsibilities of Different Sectors ............................................................... 44 Table: 7. Summary of CSA Cost Estimates for 10 Years ................................................................ 48 LIST OF FIGURES Figure 1: Food Crop Yield 2004 – 2013............................................................................................ 5 Figure 2: Industrial Crop Yield 2004 – 2014 .................................................................................... 5 Figure 3: Sugarcane Yield 2004 – 2013. .......................................................................................... 6 Figure 4: Horticultural Crops Yield 2004 – 2013.............................................................................. 6 Figure 5: Livestock Population Trend. ............................................................................................. 7 Figure 6: Aquaculture Production Trend in Tanzania (2010-2014) ................................................. 8 Figure 7: Climate change impacts in Tanzania with respect to temperature under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios.................................................... 14 Figure 8: Climate change impacts in Tanzania with respect to precipitation in Tanzania under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios ................................. 15 Tanzania Climate Smart Agriculture Program 2015 - 2025 v Figure 9: Percent change in precipitation in 2080 under the higher RCP 8.5 greenhouse gas emissions scenario based on an ensemble of 19 climate models from the IPCC Fifth Assessment Report. ........................................................................................................................................... 16 The darker bars represent months with greater average precipitation (from Climate Wizard, CIAT, 2015). Climate Impacts to Crops .......................................................................................... 16 Figure 10: Percent change in suitable area for major crops in Tanzania due to climate change. 17 Figure 11: Projected changes Above ground Net Primary Productivity (ANPP) in Tanzania’s rangelands ANPP by 2050s and RCP8.5 (high-end emissions) in relation to the mean value of 1971-1980. .................................................................................................................................... 17 Figure 12: Future emission projections 2007 – 2030 Source: The Economics of Climate Change in Tanzania ........................................................................................................................................ 18 Figure 13: Trend in Agricultural Financing (2001/02 - 2010/11). .................................................. 19 Figure 14: Coordination mechanism among the different implementers of CSA practices ......... 42 Tanzania Climate Smart Agriculture Program 2015 - 2025 vi FOREWORD In Sub-Saharan Africa, heavy reliance on rain-fed agriculture renders farming communities more vulnerable to effect of climate change and variability resulting in widespread food insecurity and poverty. Climate change and variability present new challenges particularly for smallholder farmers whose main stay is agriculture. Providing food for the future will require a holistic approach in order to produce on less land and by using appropriate methods. Farming communities and researchers are obliged to re-evaluate mainstreaming of farming practices and techniques and look for ways of securing food through adoption of conservation agriculture, integrated livestock keeping, fish farming and agro-forestry. High dependence on rain-fed agriculture and poor soil health increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience to external shocks. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are therefore needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. The most affected will be the rural poor, who are dependent on farming as a livelihood. Because of their poverty status, they have less ability to accumulate and protect assets and have the least adaptive capacity to respond to climatic shocks occasioned through extreme events as well as variability in weather during the cropping seasons. Changes in climate may be faster and more intense than in the past and existing knowledge on approaches and practices in agriculture may not be sufficient to address the adaptation needs. To ensure that the country is food secure and for food producers to improve their livelihoods, climate smart agriculture (CSA) is the most appropriate approach. The CSA approach would ensure sustainable increase in agricultural productivity; build resilience in food systems and adapt to climate change; Tanzania Climate Smart Agriculture Program 2015 - 2025 vii reduce food losses and waste; and contribute to the reduction and removal of greenhouse gas emissions, where possible. I believe that this CSA Programme, which is the result of a collective, sector- wide consultation effort, places Tanzania firmly on a new and ambitious growth trajectory for the future. We recognise the vital role that agriculture must play in growing the economy and creating decent jobs. In this respect, the agriculture sector as a whole is determined to optimise its contribution. The successful implementation of this programme will require multi-level partnerships between the public and private sector, civil society and citizens. I acknowledge with appreciation the constructive and cooperative relationships we have already built in this regard with all parties involved. I believe that agriculture in this country will grow from strength to strength. This, however, will require a shift in the way we do things, in line with the new strategic approach. Finally, I would like to thank the many people who have contributed to the development of this programme. Our thanks to the panel of 10 experts from across all stakeholder groups in the sector, chaired by Ms. Shakwaanande Natai, for the pivotal role they played in guiding the development of the Programme, and for their commitment to the process. I would also like to express our appreciation for those who submitted comments and made inputs that tmade the document better. We are grateful for your commitment and dedication to walk this path with our Ministry. Steven Masatu Wassira (MP) MINISTER FOR AGRICULTURE FOOD SECURITY AND COOPERATIVES Tanzania Climate Smart Agriculture Program 2015 - 2025 viii ACKNOWLEDGEMENT The preparation of the Tanzania Climate Smart Agriculture (CSA) Program has been spearheaded by a multi-disciplinary and multi-stakeholders National Expert Team from relevant Ministries, Departments, Agencies, Researchers and Academia, Civil Society Organization (CSOs) and Private Sector under the auspices of the Ministry of Agriculture Food Security and Cooperatives (MAFC) and the Vice President’s Office (VPO). Following the development of National Adaptation Program of Action (NAPA), adoption of the National Climate Change Strategy (NCCC) and Agriculture Climate Resilience Plan (ACRP), it was found necessary to prepare the Tanzania Climate Smart Agriculture (CSA) Program to guide implementation of the identified interventions. Preparation of the Tanzania CSA Program would not have been possible without the financial and technical support from the New Partnership for Africa’s Development Agency (NEPAD), Southern African Development Cooperation (SADC), Common Market for Eastern and Southern Africa (COMESA), East African Community (EAC) and the Consultative Group for International Agricultural Research Program on Climate Change, Agriculture and Food Security (CCAFS). Special thanks are due to National Team of Experts led by Shakwaanande Natai (Chairperson, National CSA Program Task Force), Eng. Isaria Mwende, Ombaeli Lemweli, Elirehema Swai, Mary Majule, Tereza Massoy, (MAFC), Joseph Kihaule (VPO), Dr. Lucy Ssendi (PMO-RALG), Lucia Chacha (MLFD), Nassor Mkarafuu (MANR - Zanzibar), Dr. Fadhila Hemed (NEMC), Mathew Ndaki (TMA) Prof. Salim Maliondo (SUA) and Mary Swai (TaTEDO) for their expertise and valuable inputs in the development of the program. Special gratitude is extended to the Tanzania government officials in relevant ministries, Development Partners, NGOs, Private Sector and other stakeholders who went through the draft and shared their ideas and opinions. We would also like to acknowledge tireless support of Dr. George Wamukoya (Climate Advisor, COMESA Secretariat) and Dr. James Kinyangi (Regional Program Leader - CCAFS) during the process of developing the CSA program. Finally, we appreciate the constructive contributions received from National Stakeholder’s Validation Workshop participants. Sophia Elias Kaduma PERMANENT SECRETARY MINISTRY OF AGRICULTURE FOOD SECURITY AND COOPERATIVES Tanzania Climate Smart Agriculture Program 2015 - 2025 ix ACRONYMS AND ABBREVIATIONS ACRP Agriculture Climate Resilience Plan AEZ Agro-ecological zone AfDB African Development Bank AGOA Africa Growth Opportunity Act ANSAF Agricultural Non State Actors Forum ARI Agricultural Research Institutes AR5 Fifth Assessment Report ASDP Agriculture Sector Development Programme ASDP-2 Second Agriculture Sector Development Programme ASLM Agriculture Sector Lead Ministries AU African Union BFSC Basket Fund Steering Committee BRN Big Results Now CA Conservation Agriculture CAADP Comprehensive Africa Agriculture Development Programme CBF Community Based Forest Management CARE CARE International CBO Community Based Organization CCAFS Climate Change, Agriculture and Food Security CGIAR Consultative Group for International Agricultural Research COMESA Common Market for Eastern and Southern Africa (COMESA) CSA Climate Smart Agriculture CSO Civil Society Organization DALDO District Agricultural and Livestock Officer DADP District Agriculture Development Plan DPP Department of Policy and Planning DRD Department of Research and Development DRTE Department of Research, Training and Extension DRM Disaster Risk Management EAC East African Community EEZ Exclusive Economic Zone EMU Environment Management Unit FANR Food, Agriculture and Natural Resources Division FAO Food and Agriculture Organization FSDP Fishery Sector Development Program GDP Gross Domestic Product HEMU Head, Environment Management Unit ICRAF International Center for Research in Agroforestry ICT Information and Communication Technology IFAD International Fund for Agricultural Development IPCC Intergovernmental Panel on Climate Change KR Key result area LDCs Least Developed Countries LGA Local Government Authority LSDS Livestock Sector Development Strategy Tanzania Climate Smart Agriculture Program 2015 - 2025 x MAFC Ministry of Agriculture Food Security and Cooperatives MANR Ministry of Agriculture and Natural Resources - Zanzibar MDAs Ministries/Departments/Agencies MDGs Millennium Development Goals MEM Ministry of Energy and Minerals MICCA Mitigation of Climate Change in Agriculture Programme MITM Ministry of Industries, Trade and Marketing MIVARF Marketing, Infrastructure, Value Addition and Rural Finance MJUMITA Mtandao wa Jamii wa Usimamizi wa Misitu Tanzania MKUKUTA National Strategy for Growth and Reduction of Poverty MLDF Ministry of Livestock Development and Fisheries MLHHS MNRT Ministry of Natural Resources and Tourism MoFEP Ministry of Finance and Economic Planning MNRT Ministry of Natural Resource and Tourism MoW Ministry of Water MT Metric Tones MTEF Medium Term Expenditure Framework NAFORMA National Forest Resource Monitoring and Assessment NAPA National Adaptation Plan of Action NARS National Agricultural Research System NCCFP National Climate Change Focal Point NCCS National Climate Change Strategy NCCSC National Climate Change Steering Committee NCCTC National Climate Change Technical Committee NCSATF National Climate Smart Agriculture Task Force NEMC National Environmental Management Council NEPAD New Partnership for Africa’s Development (NEPAD) NGOs Non-Governmental Organizations NPS National Panel Survey NSGRP National Strategy for Growth and Reduction of Poverty PMORALG Prime Minister’s Office Regional Administration and Local Government PPP Public Private Partnership PPVA Postharvest Process and Value Addition REDD Reduced Emissions from Deforestation and Degradation RCP Representative Concentration Pathways SACCOs Savings and Credit Cooperative Societies SADC Southern African Development Community (SADC) SAGCOT Southern Agricultural Growth Corridor of Tanzania SECAP Soil Erosion Control and Agro forestry Project SRI Sustainable Rice Intensification SUA Sokoine University of Agriculture TaCRI Tanzania Coffee Research Institute TADB Tanzania Agricultural Development Bank TDV Tanzania Development Vision TAFIRI Tanzania Fisheries Research Institute TAFORI Tanzania Forest Research Institute Tanzania Climate Smart Agriculture Program 2015 - 2025 xi TAFSIP Tanzania Agriculture and Food Security Investment Plan TASAF Tanzania Social Action Fund TaTEDO Tanzania Traditional Energy Development and Environment Organisation TCCIA Tanzania Chamber of Commerce, Industry and Agriculture TFCG Tanzania Forest Conservation Group TIB Tanzania Investment Bank TMA Tanzania Meteorological Agency TNA Training Needs Assessment TORITA Tobacco Research Institute of Tanzania TPRI Tropical Pesticide Research Institute TRIT Tea Research Institute of Tanzania TV Television TWG Technical Working Group UDSM University of Dar es Salaam UN United Nations UNDP United Nations Development Programme UNFCCC United Nations Framework Convention on Climate Change UNEP United Nations Environmental Programme URT United Republic of Tanzania USAID United States Agency for International Development VPO-DoE Vice President's Office - Division of Environment WARC Ward Agricultural Resource Centre WB World Bank WG I Working Group I WG II Working Group I WUE Water Use Efficiency Tanzania Climate Smart Agriculture Program 2015 - 2025 xii EXECUTIVE SUMMARY Tanzania, an East African country, is endowed with important land and water resources that have a high agricultural potential. Agriculture is a key sector of Tanzania’s economy, as it accounts for 24.1 percent of GDP and is the source of livelihoods for more than three-quarters of the population. Majority of the population still live in rural areas although urbanization has increased in the last three decades to reach 38 percent. The population is very young, as the youth (18-35 years) accounts for 65 percent. High dependence on rain-fed agriculture and poor soil health increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience to external shocks. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are therefore needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. Given that over 90.4 percent of active women in Tanzania are engaged in agricultural activities, producing about 70 percent of the country’s food requirements, and that youth who constitute about 65 percent of the total labor force in Tanzania are less engaged in agricultural activities and emerging opportunities, it is imperative that transformation and growth in the agriculture sector target both women and the youth. To address these challenges and to harmonize and enhance CSA initiatives being undertaken by different stakeholders throughout the country, the Government of Tanzania through the CSA programme, has identified six strategic priorities as sources of Tanzania’s agricultural development and growth in a changing climate. The six strategic priorities are as follows: Improved Productivity and incomes – a pro-growth and pro-poor development agenda that supports agricultural sustainability and includes better targeting to climate change impacts will improve resilience and climate change adaptation. Because climate change has a negative impact on agricultural production, achieving any given food and nutrition security target will require greater investments in agricultural productivity. It is important that Agricultural growth Tanzania Climate Smart Agriculture Program 2015 - 2025 xiii does not jeopardize soil quality or groundwater resources. Public and private sectors as well as public-private partnerships will play a critical role. Building resilience and associated mitigation co-benefits - CSA practices that will help reduce vulnerability of Tanzania’s agriculture sector by increasing productivity, enhancing adaptation and resilience of the farming systems and reducing emissions intensity in the context of achieving food and nutrition security, sustainable development and poverty reduction. Value Chain Integration - This approach is holistic in that considers input supply, production, agricultural services, traceability, marketing and business support services as necessary building blocks. Under the approach, both public and private sectors are seen as critical actors in the value chain. Knowledge and capacity building are critical strategic priorities to leverage innovations and increase efficiencies. The approach also provides enabling framework for integrating gender and the needs of the youth. Research for Development and Innovations - Although Tanzania has a well- developed agricultural research system, use of modern science and climate smart technologies in agricultural production is still limited. Inadequate research–extension–farmer linkages to facilitate demand-driven research and increased use of improved technologies continue to constrain efforts to increase agricultural productivity as farmers continue to use outdated and ineffective technologies. The role of research will be reoriented to support innovations that facilitate the transition to climate-smart agriculture by smallholder farmers. New and emerging agricultural research partnerships will identify technological advances that respond to the impacts of climate change and climate variability. A major thrust will be on the use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and aquaculture intensification, in order to bolster farmers’ adaptive capacity and support the national vision of achieving food security. Improving and Sustaining Agricultural Advisory Services - Agro-advisory services that include climate applications for agriculture will help farmers to better make informed decisions in the face of risks and uncertainties, in addition to the integrated management of present and emerging pests and disease challenges. Climate knowledge applications include seasonal weather forecasts, monitoring and early warning products for drought, floods and pests and disease surveillance. These products and services would increase the preparedness of the farmers, well in advance, to cope with risks and Tanzania Climate Smart Agriculture Program 2015 - 2025 xiv uncertainties. In this regard, dissemination of agro-weather advisories and other climate-smart agricultural practices will be enhanced through Public Private Partnerships. Furthermore, robust agro-advisory services are expected to catalyze private sector investment in priority areas such as weather-based index insurance and associated infrastructure. Further, insurance instruments shall be linked to incentives for adaptation (or risk prevention and reduction, e.g. by introducing drought resistant crops, drip irrigation, or similar measures). Improved Institutional Coordination – Improved institutional coordination is crucial for achievement of horizontal and vertical integration required for effective discharge of the CSA Programme. The achievement of horizontal integration requires a framework that provides for high-level guidance while vertical integration is instrumental in determining the roles of various sector institutions and devolved governments in performing CSA mandates. The proposed coordination framework will improve Inter-Ministerial and Local Government coordination, enhance partnerships with private sector and civil society organizations, and strengthen coordination with development partners. Tanzania Climate Smart Agriculture Program 2015 - 2025 1 1.0 INTRODUCTION 1.1 Background The agriculture sector is key to overall economic growth and development of Tanzania. It provides livelihoods to over 80 per cent of the population, generates about 24.1 percent of GDP, contributes 30 percent of export earnings and employs 75 percent of the total labor force (URT, 2013). In the national development agenda, agriculture is expected to lead the growth and structural transformation of the economy and maximize the benefits of accelerated growth. Significant improvements in the productivity of the agriculture sector are required to raise the average real incomes of Tanzanians. The food and agriculture sector also has direct impact on the attainment of at least five of the Millennium Development Goals (MDGs) and the emerging sustainable development goals (SDGs) that include poverty reduction. Agricultural growth is a proven driver of poverty reduction. When agriculture stimulates growth in Africa, the growth is twice as effective in reducing poverty as growth based in other sectors. Thus, agricultural growth also means more production, improved food security and economic growth. Tanzania depends largely on agriculture, which is strongly dependent on natural resources such as land, forests, air, and water. Sustainable utilization of these resources is vital for the growth and sustainability of the sector. However, agriculture is vulnerable to the effects of climate change associated with global warming. Smallholder farmers dominate the agricultural sector with average farm sizes of between 0.2 and 2.0 hectares, depending on the location. Yields have been mostly stagnant for the last ten years and agricultural productivity gains have been based more on the expansion of cultivated land, which is one of the major drivers of deforestation and land degradation in the country. Studies by the Tanzania Meteorological Agency (TMA) have shown that some of the previously known highly productive areas such as the Southern and Northern Highlands will continue to be affected by declining rainfall, frequent droughts and significant increase in spatial and temporal variability of rainfall with long term implications in the agricultural sector planning and resources allocation, such as improved seeds -, pesticides and even the shifts in types of agricultural produce (URT, 2009). Tanzania’s National Adaptation Program of Action (NAPA, 2007) ranked agriculture and food security as the most vulnerable and important sector that is severely impacted by climate change and advocated that studies on the impact of climate change in the sector and on food security be a priority activity. Despite the uncertainty and recognizing the potential risks, climate challenges for agriculture are reflected in Tanzania’s development plans at the highest levels. For example, the Five-Year Development Plan (FYDP 2011/12 – Tanzania Climate Smart Agriculture Program 2015 - 2025 2 2015/16), MKUKUTA-II, National Climate Change Strategy (NCCS, 2012) and Agriculture Climate Resilience Plan (ACRP, 2014-2019) include climate change as a threat to economic growth and an “underlying pre-requisite” which must be addressed to ensure success of agriculture as a core growth priority. The NCCS highlights agriculture as a key climate-sensitive sector where impacts of climate variability are already experienced by farmers, including declines in agricultural productivity, shifting Agro Ecological Zones (AEZ), increased incidents of pests and diseases, and increasingly unreliable rainfall. This CSA Program will support climate change adaptation and mitigation initiatives in the agricultural sector. Climate-smart agriculture, forestry and fisheries (CSA), as defined by FAO 2010, - contributes to the achievement of sustainable development goals and integrates the three dimensions of sustainable development (economic, social and environmental) by jointly addressing food security and climate challenges. CSA has three main pillars: Sustainably increasing agricultural productivity and incomes. Adapting and building resilience to climate change. Reducing and/or removing greenhouse gases emissions, where possible. CSA is an approach to developing the technical, policy and investment conditions to achieve sustainable agricultural development for food security under climate change. In this context, the CSA approach in Tanzania is designed to identify and operationalize sustainable agricultural development within the explicit parameters of climate change and variability 1.2 Alignment with the continental, regional and national agriculture and climate change policies, strategies and plans This CSA Programme is aligned with the national economic blue print – Tanzania Vision 2025 and the National Development Plan. The Programme is also in line with the broad national objectives of the agricultural sector of contributing towards attainment and maintenance of domestic supply of main food items, production of raw materials for industries and creation of gainful employment of men, women and the youth. Similarly, the CSA Programme is aligned with the Water Resources Management Strategic Interventions and Action Plan for Climate Change Adaptation. The programme is further aligned with National REDD+ Strategy and Action Plan as it addresses the main drivers of deforestation and forest degradation. At the regional level, the CSA Program enhances the implementation of the Comprehensive African Agriculture Development Programme (CAADP) and responds to the 23rd Ordinary African Union Assembly – Decisions and Declaration (Malabo Declaration), in particular: Assembly/AU/Dec. 538 (XXIII) on Climate Change and agriculture; Assembly/AU/Decl.1 (XXIII) on Accelerated agricultural growth and transformation; and Assembly/AU/Decl.4 (XXIII) on Nutrition security for Inclusive economic Growth and Sustainable Development. At the national level, Tanzania Climate Smart Agriculture Program 2015 - 2025 3 the CSA Program will contribute to Tanzania’s efforts to adapt and build resilience in - agriculture under the National Adaptation plan of Action (NAPA), The National Climate Change Strategy (NCCS), Agriculture Climate Resilient Plan (ACRP) and The National REDD+ Strategy and Action Plan. The CSA Program is intended to harmonize and enhance CSA initiatives being undertaken by different stakeholders. 1.3 Preparation Process In preparation of this CSA Program, the Ministry of Agriculture Food Security and Cooperatives and the Vice President’s Office pursued a consultative approach under the guidance of a Multi-disciplinary Team of Experts drawn from relevant Ministries and Departments, Agencies, Civil Society Organization (CSOs), Private Sectors, Researchers and Academia. The Program was developed through a four-step procedure as follows: 1. conducting technical working sessions that took stock of the sector’s programmes, strategies and performance from a historical perspective, as well as an analysis of options for agricultural sector growth in a changing climate; 2. consultative sessions were carried out with interested groups, particularly the National Designated Authority (NDA) for Green Climate Fund (GCF), Global Environment Facility (GEF) Focal Point, Planning Commission, Revolutionary Government of Zanzibar, CSOs, umbrella private sector organizations such as the Tanzania private sector association and farmer organizations, Local Government Authority and Development Partners; 3. National stakeholder validation workshop where comments from stakeholders were discussed and incorporated; and 4. Resource mobilization to support implementation of Tanzania CSA Programme. Tanzania Climate Smart Agriculture Program 2015 - 2025 4 2.0 SITUATION ANALYSIS 2.1 General Trends The agriculture sector in Tanzania provides livelihoods to over 80 percent of the population, generates about 24.1 percent of GDP (Table 1), contributes 30 percent of export earnings and employs 75 percent of the total labor force (URT, 2013). Tanzania is endowed with 44 million hectares (46 percent of total land) suitable for agriculture. However, part of this arable land is only marginally suitable for agricultural production due to a combination of factors including infertile soils, soil erosion, degradation and likelihood of drought. Moreover, about 28% of the land area is inaccessible to agriculture as it is under protection as Forest reserves and Wildlife protected areas. Currently, only 32 percent of the available arable land is cultivated. Tanzania also has significant potential for irrigated agriculture, with the area suitable for irrigation estimated to be about 29.4 million ha. Yet only 1.5 percent (441,000 ha) of potential irrigated areas is currently under irrigation. Smallholder agriculture is predominantly rain fed especially in arid and semi-arid regions that depend entirely on subsistence livestock and food crop production for their livelihoods. Table 1: Share of Agriculture in the National Gross Domestic Product: 2005 - 2013 YEAR SECTOR (percent) Agriculture Industry Services Other (Net Indirect Taxes) 2005 26.9 20.8 42.5 9.8 2006 25.3 20.8 43.3 10.6 2007 25.0 21.2 43.3 10.5 2008 24.9 21 43.8 10.3 2009 23.8 22 43.6 10.6 2010 24.1 21 49.5 5.4 2011 24.7 21 50 4.3 2012 24.8 21 50 4.2 2013 24.7 25 47.7 24.7 Source: URT (2013). The Economic Survey, Ministry of Finance. 2.2 Agricultural Production Trends 2.2.1 Crop Production Smallholder farmers dominate the agricultural sector with average farm sizes of between 0.2 and 2.0 hectares, depending on the location. Yields have been Tanzania Climate Smart Agriculture Program 2015 - 2025 5 mostly stagnant for the last ten years and agricultural productivity gains have been based more on the expansion of cultivated land, which is one of the major drivers of deforestation and land degradation in the country. The major food crops include maize, sorghum, rice, pulses, cassava and potatoes (Figure 1). Figure 1: Food Crop Yield 2004 – 2013 Source: FAOSTAT 28/03/2015 Industrial crops (Figures 2 & 3), commonly referred to as cash crops, are mainly grown as a source of income. These include tea, coffee, pyrethrum, tobacco, sisal, cashew and sugarcane among others. Figure 2: Industrial Crop Yield 2004 – 2014 Source: FAOSTAT 28/03/2015 Tanzania Climate Smart Agriculture Program 2015 - 2025 6 Figure 3: Sugarcane Yield 2004 – 2013. Source: FAOSTAT 28/03/2015 The horticulture sub-sector is one of the fastest growing sectors contributing to food security, nutrition improvements and economic growth (Figure 4). It has been identified as one of the priority sub-sectors in the National Export Strategy (2008), the Kilimo Kwanza Resolution and a key component in the diversification of the agricultural sector from over dependence on traditional primary agricultural products. The sub-sector has a potential to become one of the main sources of foreign exchange earnings and a significant driver of economic growth. For instance, indigenous fruits, vegetables, spices and flowers have been cultivated in Tanzania for generations and traded throughout the region and internationally (e.g. the country is thought to have started exporting bean seed to Europe in the 1950s). Horticulture is mainly practised by small-scale farmers with a few large-scale operators. Local and foreign investors endow the floriculture and export vegetables sub-sector. Figure 4: Horticultural Crops Yield 2004 – 2013 Source: FAOSTAT 28/03/2015 Tanzania Climate Smart Agriculture Program 2015 - 2025 7 2.2.2 Livestock Production The country has an estimated population of 22.8 million cattle, 15.6 million goats, 7 million sheep, 35.5 million local chickens; 24.5 million improved chicken breed and 2.1 million pigs1. However, 97 percent of all livestock are indigenous breeds which are kept by rural farmers and are grazed under natural pasture, while only 3 percent are improved breeds either grazed and or fed in cut and carry systems with minimal supplements. Figure 5: Livestock Population Trend. Source: Ministry of Livestock and Fisheries Development, 2014 Table 2: Production of livestock products 2008/2009 to 2013/2014 Source: Ministry of Livestock and Fisheries Development (2014) 1 Budget Speech 2014/2015 Product 2008/09 2009/10 2010/11 2011/12 2012/13 2013/2014 Meat Production (Tonnes) Cattle 225,178 243,943 262,606 289,835 299,581 309,353 Goats/sheep 82,884 86,634 103,709 111,106 115,652 120,199 Pig 36,000 38,180 43,647 47,246 50,814 79,174 Chicken 78,168 80,916 93,534 84,524 87,408 54,360 Total 422,230 449,673 503,496 532,711 553,455 563,086 Milk Production ('000' litres) Local Cattle 1,012,436 997,261 1,135,422 1,255,938 1,297,775 1,339,613 Modern Cattle 591,690 652,596 577,962 597,161 623,865 650,570 Total 1,604,126 1,649,857 1,713,384 1,853,098 1,921,640 1,990,183 Egg Production ('000') Eggs 2,806,350 2,917,875 3,339,566 3,494,584 3,725,200 3,899,568,750 Tanzania Climate Smart Agriculture Program 2015 - 2025 8 Despite the large livestock population size, its contribution to the national economy (GDP) has persistently been declining from 18 percent in 2001 to 4.4 percent (TBS, 2013). Major challenges include recurring droughts which reduce pasture productivity and water availability; alien invasive species, pests and diseases. Furthermore, uncontrolled livestock mobility brings about conflicts between crop farmers and livestock keepers. 2.2.3 Fisheries Production Tanzania has total water area of 62,000 km2 potential currently employing more than 4 million people. In Zanzibar, the fisheries sector is largely artisanal currently employing about 20 percent of the island population with mariculture activities such as seaweed and prawn farming also supplementing the incomes of - island households. Climate change impacts on fisheries are mainly associated with degradation of fish areas and fish stock. For instance, sea level rise, which is associated with global warming, may cause sea water to rise above optimal levels, and increased sea water acidification bleaching corals, causing degradation of fish nursery grounds, breeding and feeding areas. Moreover, drought and frequent floods increases sedimentation in freshwaters, negatively affecting fisheries in fresh water bodies. Aquaculture in Tanzania has a huge potential but yet untapped for widespread household and commercial use. The high potential for development of aquaculture is due to availability of water resources and diversified species in the wild potentially suitable for aquaculture. Currently, the total number of people involved in the aquaculture is about 17,100 (with 14,100 involved in freshwater fish farming and about 3,000 in seaweed farming). Youths play an important role in aquaculture in pond construction, management and distribution of fish. Figure 6: Aquaculture Production Trend in Tanzania (2010-2014) Source: Ministry of Livestock and Fisheries Development Tanzania Climate Smart Agriculture Program 2015 - 2025 9 2.2.4 Forest Resources The total forest area in Tanzania is 48 million ha, of which 93 percent of this is woodlands and only 7 percent are classified as forest reserves (mangroves, coastal forests, humid montane forests and plantations). Forest ecosystems in Tanzania are major sources of various ecosystem goods and services. They cover and protect most of the water catchments in the country and serve as a link in the agriculture-water-energy nexus. Besides timber and other non- timberforest products, the most important use of wood in Tanzania is provision biomass energy (fuel wood and charcoal) used by over 90% of the population. Some forest areas also support agriculture and livestock keeping. 2.3 Food Consumption and Nutrition Trends 2.3.1 Levels of food consumption Cereals and roots and tubers serve as staples for the majority of the population in rural as well as in urban areas. Maize is consumed in all regions, especially in rural areas while rice is mostly consumed in urban and coastal regions. Other staples include plantain, potatoes, rice, cassava and sorghum. Other cereals such as sorghum and millet; roots and tubers such as yams and sweet potatoes are known but contribute less to the diet, as they are less preferred. The main dish is a stiff porridge (known in Kiswahili as ugali) made from maize flour, sorghum or cassava. The staple is eaten with a relish either made of vegetables, sardines, pulses or meat. The diet is often monotonous with a limited diversity of foods; it is based on starchy foods with high fibre content. Frequency of vegetable consumption is high, especially among rural communities where they are included in every meal, but generally quantities are small. Therefore, vegetables do not contribute substantially to nutrient intake. Table 3: Trends in per capita supply of major foods groups (in g/per day) Major food groups Supply for human consumption in g/day 1966-68 1973-75 1980-82 1987-89 1994-96 2001-2003 Starchy roots 742 755 691 494 592 518 Cereals (excl. beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oil crops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Tanzania Climate Smart Agriculture Program 2015 - 2025 10 Source: FAOSTAT In rural areas and among the low-income section of the urban population, the quantity of food consumed can be limited and meal frequency varies with the season. It is limited to one meal per day during the wet season (lean months) and to two meals during the dry or harvest season. Frequency of meat and milk consumption is extremely low, on average once a week or even less. Among certain communities these products are consumed very rarely, for example once a month or less. 2.3.2 Nutrition trends Under-nutrition and malnutrition are still highly prevalent in Tanzania. More than a third of children under five years are affected by chronic malnutrition (stunting). In the Southern zone prevalence surpasses 50 percent. Stunting is due to a combination of factors including maternal malnutrition, inadequate infant feeding practices, low quality of health care and poor hygiene. Breastfeeding is widely practiced but exclusive breastfeeding is not widespread and complementary feeding practices are inadequate. At the same time, the country is undergoing a nutrition transition due to changes in dietary habits, especially among middle and high-income groups living in urban areas who consume energy dense and processed foods. The prevalence of overweight and obesity is noticeable among women (almost one woman out of five). Table 4: The prevalence of various forms of nutrient deficiencies in Tanzania according to population groups Category of population affected Type of deficiency and percent affected PED Anaemia IDD VAD Children under-five years 52.0 45.0 13.0 30.0 Pregnant and lactating women 13.0 80.0 52.0 0.7 Remaining groups 20.0 20.0 40.0 0.1 General population 28.0 32.0 25.0 6.1 Source: Kavishe F.P (1987), TFNC Report no. 1215 2.4 Enabling Policy Environment Policy reforms are cited as one of the drivers of productivity gains experienced in the agriculture sector. These policy reforms substantially improve the economic environment for agriculture through improvements in better policies on pricing -, trade, exchange rates, institutions and markets. The Government of the United Republic of Tanzania has over the years developed policies and strategies to enhance agricultural growth, natural resource management and climate change interventions. The Table 5 below summarizes the key policies and strategies that the GoT ratified and implemented in the country, and which, through their objectives and action plans, have an impact on CSA Tanzania Climate Smart Agriculture Program 2015 - 2025 11 implementation (Table 3). The summary of the enabling and (potentially) obstructing policies are provided in Table 5. Table 5: Key policies relevant for CSA implementation and scale out in Tanzania Regional Comprehensive Africa Agriculture Development Programme (CAADP) Based on four reinforcing pillars for investment in agriculture to improve performance through strengthening country presence, focused lending program based on coordinated sector plans, enhanced capacity for policy, analytical work, and knowledge/partnership management: 1. Expanding the areas under sustainable land management and reliable water control systems. 2. Improving rural infrastructure and trade related capacities for market access 3. Increasing food supply and reducing hunger 4. Expanding agricultural research and technology transfer and dissemination East Africa Community Food Security Action Plan Developed to address food insecurity in the region. It forms the initial step of implementing the provisions of the EAC Treaty as set out in Chapter 18 Articles 105 -110. One of the main objectives of the EAC as set out in the Treaty is the achievement of food security and rational agricultural production. The EAC- Food Security Action Plan will guide coordination and implementation of the joint programmes and projects emanating from this plan. East Africa Community Climate Change Policy The purpose is to guide EAC Partner States and other stakeholders on the implementation of collective measures to address climate change impacts and causes in the region through adaptation and mitigation actions while assuring sustainable social and economic development. Macro economics Tanzania Development Vision (TDV) 2025 Developed with the intention of coordinating and directing national’s efforts and resources towards economic and social development by 2025. 1. Achieving quality life for all, 2. Good governance and the rule of law, and 3. Building a strong and resilient economy that can effectively withstand global competition. Tanzania Climate Smart Agriculture Program 2015 - 2025 12 The National Strategy for Growth and Reduction of Poverty II Sets targets and goals on accelerating economic growth, reducing poverty and improving living standards and social welfare of Tanzanians. Agricultural Sector National Agricultural Policy Aims at setting instruments for the development of an efficient, competitive and profitable agricultural industry that contributes to nation’s economic growth and wellbeing of Tanzanians. Tanzania Agriculture and Food Security Investment Plan (TAFSIP) Ten-year investment plan, which maps the investments, needed to achieve the CAADP target of six percent annual growth in agricultural sector GDP. It aims to contribute to the national economic growth, household income and food security in line with national and sectoral development aspirations. Agricultural Sector Development Programme (ASDP) Main objectives are to enable farmers to have better access to and use of agricultural knowledge, technologies, marketing systems and infrastructures for higher productivity and profitability; and to promote involvement of the private sector in agricultural transformation under improved regulatory and policy frameworks. Livestock Sector Development Strategy (LSDS) Aims at developing a competitive and more efficient livestock industry that contributes to the improvement of the livelihoods of all livestock keepers and the national economy. Fisheries Sector Development Programme (FSDP) Designed to develop a sustainable, competitive and more efficient fisheries and aquaculture industry that contribute to the sustainable livelihood improvement and the national economy. Tanzania Agriculture Climate Resilience Plan (ACRP) Developed to implement strategic adaptation and mitigation actions in the crops sub-sector. It presents a wide range of adaptation options including, but not limited to: improving agricultural land and water management, accelerating uptake of CSA, reducing impacts of climate-related shocks through risk management, and strengthening knowledge and systems to targeted climate action. Southern Agricultural Growth Corridor of Tanzania (SAGCOT) The goal is to expand investment in agribusiness leading to income growth among smallholders and employment generation across agribusiness value chains in the Southern Corridor Tanzania Climate Smart Agriculture Program 2015 - 2025 13 Big Result Now (BRN) The objective is to address critical sector constraints and challenges and to speed-up agriculture GDP, improve smallholder incomes and ensure food security by 2015, mainly through smallholder aggregation models for main cereals and high potential crops contributing to import substitution, farm income and food security. Environment and Climate Change National Environmental Policy (NEP) Aims at ensuring sustainable and equitable use of resources for meeting basic needs, preventing and controlling degradation of land, water, vegetation and air, and improving the condition and productivity of degraded rural and urban areas National Climate Change Strategy (NCCS) Sets out strategic interventions for climate change adaptation measures and greenhouse gas emissions reductions. It has outlined objectives for all sectors and proposed strategic interventions in those sectors and themes that are highly vulnerable to climate change such as agriculture. Land, Land use and Forestry The National Strategy (and Action Plan) for Reduced Emissions from Deforestation and Forest Degradation (REDD+) The strategy (and plan) aims to facilitate effective and coordinated framework for reducing deforestation and forest degradation. It guides the implementation and coordination of mechanisms required for Tanzania to benefit from a post-2012 internationally approved system for forest carbon trading, based on demonstrated emission reductions from deforestation and forest degradation and other aspects of REDD+ 2.5 Constraints to Agriculture Development and Growth 2.5.1 Land Degradation and Soil Health Demands on the land for economic development and pressures from a growing population are leading to unprecedented land use change. In turn, unsustainable land use is driving land degradation. The result is - loss of land productivity with impacts on livelihoods and the economy. The impacts of land degradation and desertification include a reduction in crop and pasture productivity and fuel-wood and non-timber forest products, which are closely linked to poverty and food insecurity. The damage to soil, loss of habitat, water shortages, and siltation reduce biodiversity and ecosystem services and has wider economic consequences. Land degradation manifests itself in many forms; among them are soil erosion, increased sediment loading of water bodies, loss of soil fertility, increased salinity, reduced ground cover, and the reduced carrying capacity of pastures. To address this challenge, the Tanzania Climate Smart Agriculture Program 2015 - 2025 14 government launched the National Strategy on Urgent Actions to Combat the Degradation of Land and Water Catchment Areas in Tanzania (URT, 2006) that has not yet been fully implemented. 2.5.2 Climate Change and Variability Agriculture in Tanzania is acutely vulnerable to the impacts of climate change due to dependency on climate. Unreliable rainfall, extreme weather events and poor rainfall distribution are the most damaging risks of production among smallholder farmers and fisher-folks. Drought and floods are the major natural disasters in Tanzania accounting for up to 70 percent of all recorded natural calamities causing large-scale famine, diseases and deaths for human beings, plants and animals. A range of Global Circulation Models (GCM) and emission scenarios projections indicate future changes in rainfall and increases in average annual temperatures of 1ºC to 3ºC above the baseline period (1961-1999) by the 2050s, with the latest projections indicating a high certainty of a 1 ºC rise across the country. Figures 7 and 8 show Climate change impacts in Tanzania with respect to temperature and rainfall respectively under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios. Figure 7: Climate change impacts in Tanzania with respect to temperature under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios Tanzania Climate Smart Agriculture Program 2015 - 2025 15 The thick black lines represent the average of 29 different climate models, whereas the grey box and dashed lines represent the range of climate models. Although precipitation is projected to increase by most climate models, the timing of precipitation is also changing with some months projected to decrease. Figure 8: Climate change impacts in Tanzania with respect to precipitation in Tanzania under lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emissions scenarios Although climate change is projected to bring more rain to Tanzania in some areas, models show that this increase in rainfall is only during the middle of the rainy season (November-April rain season) with all other months projected to decrease in precipitation (see Figure 9). This would result in the rainy season becoming shorter but more intense, and the dry season becoming drier. Increased intensity in frequency of storms, drought, flooding, may alter the hydrological cycles while variable precipitation may have implications for food, pasture and water availability. Tanzania Climate Smart Agriculture Program 2015 - 2025 16 Figure 9: Percent change in precipitation in 2080 under the higher RCP 8.5 greenhouse gas emissions scenario based on an ensemble of 19 climate models from the IPCC Fifth Assessment Report. The darker bars represent months with greater average precipitation (from Climate Wizard, CIAT, 2015). Climate Impacts to Crops Agricultural crop modeling shows that climate change has impacts depending on the crop. Maize is expected to have 25 to 75 percent decreases in area suitable for cultivation (Figure 10). Likewise, sorghum is expected to have a moderate decrease in area suitable for cultivation. However other crops such as beans, cassava and banana are expected to increase in area suitable. While forage for livestock grazing is very important to Tanzania, climate change is projected to decrease rangeland productivity (Figure 11 below). Tanzania Climate Smart Agriculture Program 2015 - 2025 17 Figure 10: Percent change in suitable area for major crops in Tanzania due to climate change. The red line represents the average projected change and the blue box and dashed lines represent uncertainty associated with the crop modeling. Analysis provide by J. Vargas, CIAT Figure 11: Projected changes Above ground Net Primary Productivity (ANPP) in Tanzania’s rangelands ANPP by 2050s and RCP8.5 (high-end emissions) in relation to the mean value of 1971-1980. This provides a good proxy for climate change impacts to livestock productivity. Tanzania Climate Smart Agriculture Program 2015 - 2025 18 Tanzania currently has very low emissions of Greenhouse Gases (GHG), in total and per capita. The published inventory for 1994 puts per capita emissions at 1.3 tones of CO2e (all GHGs) and 0.1 tCO2 (CO2 only). However, if land use changes and forestry (including deforestation) are included, the per capita emission estimates rise to 2.67 (all GHGs) and 1.65 (CO2 only). The key emitting sectors are forestry, due to deforestation, and agriculture, primarily from livestock (CH4 from enteric fermentation) and soils (N2O from fertilizers, animal manure, etc.). These two sectors accounted for 93percent of emissions in 1994 (forests 70percent, agriculture 23percent). In the future, it is inevitable that GHG emissions in Tanzania will increase under the planned current development baseline. For example, between 2005 and 2030 under the current projected baseline, per capita emissions are set to increase to 1.5 tCO2e and 0.5 tCO2 (CO2 only). The future emission projections (excluding LUCF sector) are shown in Figure below Figure 12: Future emission projections 2007 – 2030 Source: The Economics of Climate Change in Tanzania Building resilience and adaptation in the agriculture sector is very crucial due to the vulnerability and the observed impacts of climate change in the country. With a vulnerable rainfed agricultural sector, a well-functioning early warning system is a key factor in risk reduction and enhancing productivity. The institution responsible for provision of early warning information in Tanzania include Tanzania Meteorological Agency (TMA), in collaboration with international partners and national partners such as Ministry of Agriculture Food Security and Cooperatives (MAFC), Ministry of Livestock and Fisheries Development - and Ministry of Natural Resources and Tourism. However, these early warning systems are inefficient in terms of the means of communicating the intended information. The common means of communicating the information is via radio and Television broadcasting, newspapers, websites and Tanzania Climate Smart Agriculture Program 2015 - 2025 19 emails. With this method, the information is not delivered on time, and thus difficult to integrate it into farming decisions. 2.5.3 Agricultural Finance and Investments The Government through the national budget is the main funder of the agricultural sector, supplemented by Development Partners (DPs), private sector and civil society organizations thus making significant contributions to the sector. According to the Maputo Declaration of the African Union in 2003, it was agreed that all African countries, including Tanzania strive to commit at least 10 percent of the national budgets to agriculture. Although Tanzania has not attained the annual target of 10 percent, over the years, there has been a remarkable increase in investments in agriculture currently standing at about 8 percent. Figure 13: Trend in Agricultural Financing (2001/02 - 2010/11). In addition, the Government in collaboration with DPs and private sector have put in place measures aimed at improving the flow of finance and investment to the agriculture sector such as: the Export Credit Guarantee Scheme, USAID Guarantee for Input Scheme, Private Agriculture Sector Support (PASS), the Agro-Dealers Scheme and the Agriculture Input Trust Fund (AGIFT). Other initiatives that enhance Public Private Partnerships include the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) and Big Results Now (BRN). One of the main constraints to private sector investment in agriculture is lack of appropriate financing arrangement, particularly considering the high risks associated with investments in the agriculture as compounded by the impacts of climate change and climate variability. Tanzania Climate Smart Agriculture Program 2015 - 2025 20 2.6 Agricultural Growth Potential and Sources of Growth Agriculture in Tanzania has a huge potential and opportunities for development. About 44 million hectares are suitable for agricultural production and only 10.8 million hectares (25%) are cultivated mostly under subsistence agriculture (i.e., smallholders operating between 0.2 and 2 hectares with low productivity). The potential therefore exists for expansion and intensification. In addition, the area with irrigation potential is 29.4 million hectares, but only 1.5 % (440,000 ha) so far utilized. Tanzania has a dual agricultural economy: smallholder farmers on one side dominate the agricultural sector, carrying out rainfed agriculture, producing a variety of subsistence crops, such as maize, sorghum, millet, cassava, sweet potatoes, pulses, paddy, wheat, fruits and vegetables. On the other side, cash crops like sisal, sugarcane and tea are grown on large-scale commercial farms and cashew nut, coffee, cotton and tobacco are grown on small-scale farms. Peri-urban agriculture (mainly horticultural crops) for household food consumption is rapidly increasing. High dependence on rainfed agriculture and poor soil health largely due to land mismanagement increases vulnerability of farming systems and predisposes rural households to food insecurity and poverty thus eroding their productive assets and weakening their coping strategies and resilience. Increasingly, the onset, duration and intensity of rains vary considerably from year to year, while the frequency and intensity of extreme weather events such as drought and floods are on the increase with devastating impacts on the national economy and the livelihoods of the people. Moreover agricultural seasons in some areas of the country are expected to shift. Drastic and innovative measures are needed to help farmers and consumers cope with the changes in emerging and projected weather patterns. Over 90.4 percent of active women in Tanzania are engaged in agricultural activities, producing about 70 percent of the country’s food requirements. Moreover, youth who constitute about 65 percent of the total labor force in Tanzania, are less engaged in agricultural activities and emerging opportunities. It is imperative that transformation and growth in the agriculture sector target both women and the youth. Tanzania Climate Smart Agriculture Program 2015 - 2025 21 3.0 VISION AND OBJECTIVES 3.1 Vision The Vision for the CSA Program is to have an “Agricultural sector that sustainably increases productivity, enhances climate resilience and food security for the national economic development in line with Tanzania National Development Vision 2025.” 3.2 Objectives The five core objectives of the Country CSA Programme are: 1. Increase productivity of the agricultural sector through (appropriate) climate smart agriculture practices that consider gender. 2. Enhance climate resilience of agricultural and food systems. 3. Strengthen policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture. 4. Improve infrastructure to support value addition, marketing, trade and postharvest management. 5. Develop financing mechanisms to solicit resources through national, international and public private partnerships to support climate smart agriculture. The Programme, therefore, aims to build resilience of agricultural farming systems for enhanced food and nutrition security through six Programmatic Result Areas, namely: Improved Productivity and incomes – a pro-growth and pro-poor development agenda that supports agricultural sustainability and includes better targeting to climate change impacts will improve resilience and climate change adaptation. Because climate change has a negative impact on agricultural production, achieving any given food and nutrition security target will require greater investments in agricultural productivity. It is important that Agricultural growth does not jeopardize soil quality or groundwater resources. Public and private sectors as well as public-private partnerships will play a critical role. Building resilience and associated mitigation co-benefits - CSA will help reduce vulnerability of Tanzania’s agriculture sector by increasing productivity, enhancing adaptation and resilience of the farming systems and reducing emissions intensity in the context of achieving food and nutrition security, sustainable development and poverty reduction. Value Chain Integration - This approach is holistic in that it considers input supply, production, agricultural services, traceability, marketing and business support services as necessary building blocks. Under the approach, both public and private sectors are seen as critical actors in the value chain. Knowledge Tanzania Climate Smart Agriculture Program 2015 - 2025 22 and capacity building are critical strategic priorities to leverage innovations and increase efficiencies. The approach also provides enabling framework for integrating gender and the needs of the youth. Research for Development and Innovations - Although Tanzania has a well- developed agricultural research system, use of modern science and climate smart technologies in agricultural production is still limited. Inadequate research–extension–farmer linkages to facilitate demand-driven research and increased use of improved technologies continue to constrain efforts to increase agricultural productivity as farmers continue to use outdated and ineffective technologies. The role of research will be reoriented to support innovations that facilitate the transition to climate-smart agriculture by smallholder farmers. New and emerging agricultural research partnerships will identify technological advances that respond to the impacts of climate change and climate variability. A major thrust will be on the use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and fisheries intensification, in order to bolster farmers’ adaptive capacity and support the national vision of achieving food security. Improving and Sustaining Agricultural Advisory Services - Agro-advisory services that include climate applications for agriculture will help farmers to better make informed decisions in the face of risks and uncertainties, in addition to the integrated management of present and emerging pests and disease challenges. Climate applications include seasonal weather forecasts, monitoring and early warning products for drought, floods and pests and disease surveillance. These products and services would increase the preparedness of the farmers, well in advance, to cope with risks and uncertainties. In this regard, dissemination of agro-weather advisories and other climate-smart agricultural practices will be enhanced through Public Private Partnerships. Furthermore, robust agro-advisory services would catalyze private sector investment in priority areas such as weather-based index insurance and associated infrastructure. Improved Institutional Coordination – Improved institutional coordination is crucial for achievement of horizontal and vertical integration required for effective discharge of the CSA Programme. The achievement of horizontal integration requires a framework that provides for high-level guidance while vertical integration is instrumental in determining the roles of various sector institutions and devolved governments in performing CSA mandates. The proposed coordination framework will improve Inter-Ministerial and Local Government coordination; enhance partnerships with private sector and civil society organizations; and strengthen coordination with development partners. Tanzania Climate Smart Agriculture Program 2015 - 2025 23 4.0 PROGRAMATIC RESULT AREAS 4.1 Result Area 1: Improved Productivity and Incomes 4.1.1 Component 1: Improved productivity and nutrition Development issues: Low use of CSA technologies and practices in crops, livestock and fisheries by men and women farmers/fisher-folk. Low use of inputs by smallholder men and women farmers. High levels of stunting and high mineral deficiency levels. High poverty levels. Low capacity for adaptation to climate change and variability Poor knowledge on CSA technologies 4.1.1.1 Output 1: Sustainable CSA technologies adopted by smallholder farmers and yields of staple crops (such as maize, rice, sorghum, cassava, potatoes and beans) increased by 50 percent by 2025. Actions: 1. Identify, upgrade, disseminate and practice climate smart technological packages. 2. Introduce improved crop varieties (high yielding, early maturing, disease and pest resistant and nutrient fortified). 3. Increase access to farm inputs (fertilizers/pesticides/seeds/vet drugs) and its wise application/use 4. Strengthen surveillance of agricultural input trade and use. 5. Identification of best indigenous knowledge and its interaction with scientific knowledge to enhance climate change adaptation 6. Train farmers on CSA agronomic practices 4.1.1.2 Output 2: Production of poultry, cattle, small ruminants and pigs increased by 30 percent through adoption of sustainable CSA technologies Actions: 1. Introduce improved livestock breeds (increased productivity, disease resistant and drought tolerant). 2. Undertake genetic characterization and improvement of local livestock breeds. 3. Identify, upgrade, disseminate and practice livestock technological packages. 4. Train farmers on livestock husbandry and disease management. Tanzania Climate Smart Agriculture Program 2015 - 2025 24 4.1.1.3 Output 3: Productivity of aquaculture increased by 50 percent by 2025. Actions: 1. Develop and disseminate best management practices of aquaculture throughout the country. 2. Train fisher folks in good fishing practices. 3. Strengthen fish health and disease surveillance. 4. Strengthen and increase fingerlings breeding and multiplication centers 5. Strengthen integrated fish farming (e.g. in paddy farms) 6. Sensitize and support private sector involvement in fingerling and feed production and distribution 4.1.1.4 Output 4: Stunting and underweight in children as well as micronutrient deficiencies in children and women of reproductive age reduced by 50 percent by 2025. Actions: 1. Promote production and consumption of high quality protein cereals, orange fleshed sweet potatoes (for vitamin A) and leafy vegetables. 2. Develop other high quality staples through breeding – cassava, rice, potatoes etc. 3. Promote fortification of staples during processing (micronutrient fortification and blending products). 4. Educate and train consumers on appropriate food combination 4.1.2 Component 2: Irrigation and agricultural water management Development issues: Overdependence of agriculture on inadequate and erratic rainfall (rain- fed agriculture). Inadequate infrastructure development for irrigation, drainage and water storage Inefficient water use of existing irrigation systems. Low productivity on existing irrigation schemes. Inadequate and un-coordinated information in irrigation research, science and technology. Inadequate operation and maintenance practices of existing irrigation schemes. Limited knowledge on the role of in-situ rainwater harvesting technologies through tillage and Conservation Agriculture. Tanzania Climate Smart Agriculture Program 2015 - 2025 25 4.1.2.1 Output 1: Irrigation schemes productivity increased by 25 percent and integrated farming systems increased by 50 percent by 2025. Actions: 1. Promote development and diffusion of appropriate efficient small-scale irrigation technological packages. 2. Train extension workers on irrigation and water management technologies and skills. 3. Build the capacity of Irrigators Organizations in agricultural water management and their obligations 4. Undertake comprehensive management needs assessment of existing large scale irrigation schemes. 4.1.2.2 Output 2: 1.5 million ha of irrigation developed by 2025 to benefit 2.3 million households. Actions: 1. Review of the National Irrigation Master Plan (2002) and update irrigation potential areas for small scale irrigation systems. 2. Train farmers in the installation, operation and maintenance of recommended irrigation technologies. 3. Establish links to input and output markets and service providers (strengthen value chain and technical backstopping). 4.1.2.3 Output 3: 500,000 ha of integrated farming systems with sustainable water harvesting and management systems developed by 2025 to benefit 700,000 households. Actions: 1. Identify suitable areas for rainwater harvesting and agricultural water management systems. 2. Train farmers/household members in water harvesting and agricultural water management technologies. 3. Facilitate the construction of water harvesting structures at household and community levels. 4. Introduce and promote in-situ rainwater harvesting technologies (e.g. Conservation agriculture) 4.1.3 Component 3: Improved Food Storage and Distribution Development issues: High post-harvest losses along the value chain. Tanzania Climate Smart Agriculture Program 2015 - 2025 26 Low integration of agricultural commodity markets Inadequate cold storage and cool trucks for perishable produce Inadequate agro-processing industries 4.1.3.1 Output 1: Post harvest losses for staple food crops (such as maize, rice, sorghum, cassava, potatoes and beans), horticultural crops, livestock and fish value chains reduced by 30 percent by 2025. Actions: 1. Invest in improved appropriate storage facilities and technologies along the value chain. 2. Promote small scale agro-processing industries in rural areas. 3. Train producers, processers and marketers in post-harvest management. 4. Provide regular market information (deficit/surplus areas) to improve distribution of agricultural commodities/food stuffs. 5. Facilitate establishment of market centres in rural areas with the appropriate infrastructure. 6. Link Region and District by feeder roads to various market centres and highways. 4.1.3.2 Output 2: Private sector capacity enhanced to store 5000 Mt of grain annually and to process and package 50 percent of cereals, cassava and sorghum products annually by 2025. Actions: 1. Strengthen and link the smallholder farmers to the Warehouse Receipt System (WRS) in the grain supply chain. 2. Rehabilitate existing warehouses and silos and establish Public-Private- Partnerships. 3. Support private sector to invest in food processing as well as value addition, including packaging and branding. 4. Facilitate linkages with relevant service providers and markets (inputs and outputs). 4.1.4 Component 4: Increased Growth of Incomes Development issues: Low levels of income from food and cash crop production by smallholder farmers (men, women and youth). Low productivity of animal breeds and low production of improved breeds to meet demand. Tanzania Climate Smart Agriculture Program 2015 - 2025 27 High levels of animal diseases and inadequate feed and water for animals. Limited market linkages for livestock and livestock products. Low production of aquaculture to meet the increasing demand. Limited adoption of integrated farming production systems with potential high incomes. Limited access to input and output markets. Potential for urban and peri-urban agriculture as a source of food and income is under exploited. 4.1.4.1 Output 1: Income from food and cash crop production by men and women increased by 20 percent and 30 percent, respectively by 2025. Actions 1. Build capacity of nursery operators in all crop growing areas and support them to expand and improve quality of seedlings. 2. Build capacity of Quality Declared Seed producers and support them to expand and improve quality of seed. 3. Build capacity of food and cash crop farmers to improve productivity and produce quality. 4. Facilitate contractual arrangements between food and cash crop producers and market/industry. 5. Develop and promote innovative micro-financing packages to facilitate food and cash crop farmers to access credit. 4.1.4.2 Output 2: Income from livestock production by men and women increased by 20 percent and 25 percent respectively by 2025. Actions 1. Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. 2. Facilitate and support the acquisition of improved breeding stocks by men and women farmers. 3. Provide adequate and effective extension knowledge and agro-weather information. 4. Strengthen and/or establish efficient and sustainable animal health and artificial insemination services. 5. Develop and support innovative micro-financing packages to support livestock keepers’ access to credit and markets. 6. Identify areas with acute problem of water for livestock and construct water infrastructures. 7. Facilitate improvement of demarcated grazing lands. 8. Promote use of crop residues and agro-industry byproducts. Tanzania Climate Smart Agriculture Program 2015 - 2025 28 9. Promote value addition for livestock products. 4.1.4.3 Output 3: Income from aquaculture production by men and women increased by 20 percent by 2025. Actions 1. Facilitate and support acquisition of fingerlings by men and women fish farmers. 2. Promote value addition for fish products. 3. Facilitate contractual arrangements between fish farmers and market. 4. Establish and support innovative micro-financing packages to support fisherfolks access to credit. 4.1.4.4 Output 4: Output for Urban and peri-urban agriculture increased by 30 percent by 2025. Actions 1. Support Local Governments to identify and demarcate potential areas within urban and peri-urban areas for agricultural activities. 2. Train urban and peri-urban producers in CSA Practices. 3. Monitor the safety of outputs from urban and peri-urban agriculture. 4. Enforce laws and bylaws related to urban and peri-urban sustainable land use. 4.2 Result Area 2: Building resilience and associated mitigation co- benefits 4.2.1 Component 1: Improve soil health, and restore degraded lands Development issues: Land degradation Soil and water conservation. Soil erosion and nutrient depletion Loss of biodiversity Low capacity at all levels for implementation CSA and SLM practices Low adoption of CSA and SLM technologies and practices at community level Most CSA and SLM activities are of pilot in nature Weak collaboration of relevant ministries and agencies to ensure CSA and SLM up scaling. Tanzania Climate Smart Agriculture Program 2015 - 2025 29 4.2.1.1 Output 1: Adoption of sustainable climate smart technologies and sustainable land management practices by 5 million households by 2025. Actions 1. Promote integrated soil fertility and water management interventions. 2. Establish CSA/SLM knowledge hubs across the country to support adoption of CSA and SLM technologies and practices by men and women that improve soil health and restore degraded lands. 3. Enhance the capacities of private sector service providers and farmer- based organizations to support farmers’ adoption of existing/new/improved CSA and SLM technologies and practices. 4. Develop and integrate CSA and SLM principles into farmer-field schools, primary, secondary and tertiary curriculum. 5. Establish mechanisms for joint planning and implementation of CSA and SLM at the local level. 4.2.1.2 Output 2: Technology dissemination and adoption for scaling up of CSA and SLM promoted by 2025. Actions: 1. Develop and implement sustained awareness creation program on CSA and SLM in addressing soil health and land degradation challenges. 2. Facilitate the development and implementation of at least five (5) small scale CSA Projects annually. 3. Facilitate the dissemination and adoption of CSA and SLM technologies and practices at the farm level across the country through Local Government’s CSA Projects. 4.2.1.3 Output 3: CSA and SLM knowledge to support policy and investment decision making generated and adequately managed by 2025 Actions 1. Establish CSA/SLM Knowledge Platform with disaggregated data on men and women. 2. Document and publicize successful CSA/SLM technologies, practices and interventions. 4.2.2 Component 2: Conservation of Natural Resources and Catchments Development issues: High Deforestation and Forest Degradation Poor Natural forest management including low adoption of Participatory Forest Management Low Forest Plantation area to meet the high wood demand Tanzania Climate Smart Agriculture Program 2015 - 2025 30 Low adoption of Agroforestry/Community Forestry Extensive Land degradation, Soil erosion and siltation High loss of natural and agro- biodiversity Unsustainable Biomass Energy Production and use 4.2.2.1 Output 1: The National REDD+ Strategy implemented in 25 percent of Natural forests in the country by 2025 Actions 1. Upscale Natural Forest Conservation through Participatory Forest Management (PFM) 2. Protect water catchment areas through integrated watershed management. 3. Increase forest cover through natural regeneration, Agroforestry, Reforestation. and Afforestation. 4. Promote best management practices for natural resources management to improve and maximize net benefits for the farmers and other downstream users (e.g. power generation and urban water supply). 5. Promote and support on farm soil conservation activities 6. Promote sustainable production and marketing of charcoal from miombo woodlands 7. Promote sustainable land use management. 4.2.2.2 Output 2: Farm/community forest cover increased by 20 percent by 2025 Actions 1. Develop a business model for ecosystem management in order to facilitate payment for ecosystem services (e.g. tourism revenue used to motivate farmers to conserve wildlife and payment for water in urban areas used to pay farmers for conservation of water catchments). 2. Develop and implement management plans for ecosystems in order to encourage sustainable use 3. Document biodiversity in the ecosystems including below ground biodiversity and develop eco-tourism opportunities in such areas 4. Undertake natural resources accounting for ecosystem services. 5. Identify agroforestry species for different agro-ecological zones and support farmers to increase tree cover 6. Undertake afforestation and reforestation through Public-Private Partnerships. Tanzania Climate Smart Agriculture Program 2015 - 2025 31 4.2.3 Component 3: Insurance and Other Safety Nets Development issues: Vulnerability and increasing risks to climate change. Shifting spatial distribution of events High incidence of poverty making it difficult for small scale farmers to recover after experiencing extreme weather events and climate variability Inadequacy of traditional approaches to risk transfer and risk management. 4.2.3.1 Output 1: Crop and livestock weather-indexed insurance increased by 30 percent by 2025. Actions 1. Develop and implement varied innovative crop and livestock weather- indexed insurance packages. 2. Develop agro-meteorological infrastructure to support weather-indexed insurance and to use them for improved weather and climate information services for farmers. 3. Enhance the capacity of micro-finance institutions to act as agents to deliver innovative crop and livestock weather-indexed insurance packages. 4. Raise awareness within the insurance industry of extreme weather and climate risks and communicate actions and opportunities. 5. Undertake farmer education to address their concerns regarding insurance products with a view to gain their trust 6. Establish livestock insurance schemes and use of insured livestock as collateral 7. Explore ways of using existing and other safety nets such as cash transfers or workfare programmes. 4.2.4 Component 4: Early Warning System and Emergency Preparedness Development issues: Susceptibility of crops, livestock and fisheries to extreme weather events, pests and diseases. Fragmented and inefficient early warning systems. Inadequate systems, knowledge and capacity at household, LGAs and national levels to respond to emergencies. Lack of contingency plans at district level. Tanzania Climate Smart Agriculture Program 2015 - 2025 32 4.2.4.1 Output 1: A Comprehensive Early Warning System and Contingency Plan developed and implemented by 2017 Actions: 1. Prepare vulnerability maps for targeting food security and emergency preparedness interventions. 2. Develop tools to support vulnerable households and communities to establish household community systems that can respond to emergencies (with regards to food insecurity) 3. Monitor crops, livestock and fish pests and diseases. 4. Integrate scientific weather forecasting and indigenous knowledge for early warning and to inform farmer decisions. 5. Establish a National Seed Emergency stock. 6. Improve EWS messages (clear, consistent) that include risk information; designed to link threat levels. 7. Capacity development to farmers on early warning systems and emergency preparedness. 8. Improve mass delivery system particularly on content development and communication channels. 9. Establish a feedback and evaluation process of messages delivered. 10. Develop an effective frame-work for collaboration emergency communication centres/stakeholders. 11. The explicit development of contingency plans on district level is not mentioned as an activity. 4.2.5 Component 5: Synergies in adaptation and mitigation enhanced Development issues: Agriculture sector is a source of GHG emissions Some adaptation actions have mitigation as co-benefits Increased soil carbon has beneficial effects on soil fertility 4.2.5.1 Output 1: Reduction of GHG emissions intensity from the agriculture sector Actions 1. Promote adoption of low cost climate smart technologies that minimize emission of carbon dioxide and enhance soil carbon sequestration. 2. Develop a national carbon accounting and measurement, reporting and verification system. Tanzania Climate Smart Agriculture Program 2015 - 2025 33 4.3 Result Area 3: Value Chain Integration 4.3.1 Component 1: Value addition process for agricultural products Development issues: Most agricultural commodities are sold on the farm as a result the quality is compromised and the farmers obtain low prices. Most of agricultural produce are sold raw and thus bulky with short shelf lives. Lack of supportive infrastructure for agricultural value chain. Disjointed value chains with regards to most agricultural commodities. 4.3.1.1 Output 1: At least two new commercially viable products developed from each of the staple crops, horticultural crops, livestock and fisheries by 2025. Actions 1. Solicit funds for research and innovation into agricultural value chains. 2. Develop improved infrastructure for agricultural value chains. . 3. Institute competitive grant scheme for agriculture value chains. 4. Identify existing value addition technologies and incentivize the private sector to promote them. 4.3.1.2 Output 2: Efficient pilot value chains developed for two selected commodities in each agro-ecological zone. Actions 1. Establish regional hubs (a cluster of livelihood zones in the same AEZ) for value chain development and backstopping. 2. Identify and build capacity of actors in value chain processes. 3. Undertake advanced market feasibility studies to promote demand for the selected commodities. 4. Facilitate linkages to markets for the selected commodities. 4.3.2 Component 2: Increased competitiveness and enhanced integration into domestic, regional and international markets Development issues Low levels of local market penetration by smallholder men and women farmers. Low capitalization of bulk traders. Poor grading and standardization system. Tanzania Climate Smart Agriculture Program 2015 - 2025 34 High consumer preference of imported commodities that have local substitutes. Inadequate volumes with the required specifications and quality to supply the international market. Limited capacity to fully comply with international sanitary and phytosanitary (SPS) standards. 4.3.2.1 Output 1: Marketed output of food and cash crops, livestock and fish products by smallholders increased by 50 percent by 2025. Actions: 1. Create agricultural, livestock and fish commodity hubs through participation of private sector especially micro-financiers and apply viable models of linkage with smallholders. 2. Facilitate capacity building of farmers on demand- and market-driven production. 3. Design and launch a market promotion program for import substitution commodities. 4. Work with supermarkets, hotels and restaurants to participate in selected commodity value chains with a smallholder production base. 4.3.2.2 Output 2: Export of non-traditional agricultural commodities by men and women smallholders increased by 50 percent by 2025 Actions: 1. Identify successful lead private sector firms with access to assured markets and apply viable models of linkage with smallholders. 2. Design sustainable programmes to support the certification of smallholders for export markets. 3. Develop branding of Tanzania produce for regional and international markets. 4.3.2.3 Output 3: Grading and standardization systems of agricultural commodities (crops, livestock and fish) developed and improved. Actions: 1. Develop grading and standardization systems for agricultural commodities that do not have grades and standards 2. Promote the adoption of grading and standardization systems for all agricultural commodities for both domestic and export markets. Tanzania Climate Smart Agriculture Program 2015 - 2025 35 4.4 Result Area 4: Research for Development and Innovations 4.4.1 Component 1: Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain Development issues: Low public expenditure funding into agricultural research. Limited participation of private sector in funding agricultural research and innovations. Poor dissemination and management of agricultural research information. Poor coordination and collaboration among the institutions involved in research. 4.4.1.1 Output 1: Increased funding in research and development and innovations by 50percent by 2025. Actions: 1. Increase public expenditure into research and development and innovations through national budget. 2. Incentivize private sector investments in research and development and innovations. 4.4.1.2 Output 2: Adoption of improved CSA technologies and practices by men and women along the value chain increased by 30 percent by 2025. Actions 1. Conduct participatory research work on improved technologies and practices that is informed by needs of users and agro-ecological zones along the value chain. 2. Conduct on-farm research into low-cost appropriate technologies and practices and deliver them as packages. 3. Build the capacity of extension, producers and other stakeholders in the use of existing/new/improved CSA technologies and practices. 4. Support development of private sector input and appropriate CSA technologies outreach and distribution networks. 5. Intensify field demonstration/field days/study tours to enhance adoption of existing/new/improved CSA technologies and practices. Tanzania Climate Smart Agriculture Program 2015 - 2025 36 4.4.2 Component 2: Research Extension Linkage strengthened and made functional by 2018 Development issues: Poor management and sharing of agricultural research information. Poor packaging of research information for the benefit of farmers. Lack of appropriate platforms for researchers and farmers to interact and share knowledge and experiences. 4.4.2.1 Output 1: Research Extension Linkage and made functional by 2018 Actions: 1. Establish a platform through which researchers will have regular contacts with stakeholders and other users at the national, local and farm levels. 2. Prepare CSA information packages and disseminate them to interested stakeholders using ICT. 4.5 Result Area 5: CSA Knowledge, Extension and Agro-weather Services 4.5.1 Component 1: CSA knowledge generation and dissemination Development issue Fragmented CSA knowledge and understanding of what CSA is. Lack of CSA knowledge Management System across the country. 4.5.1.1 Output 1: Robust CSA Knowledge Management System (Platform/Hub) across the country Actions 1. Undertake a CSA knowledge mapping, audit and analysis. 2. Build CSA knowledge Resource Centre. 3. Develop and maintain a robust and functional CSA knowledge management system. 4. Build capacity to different stakeholders in the agricultural value chain at the national and local levels. Tanzania Climate Smart Agriculture Program 2015 - 2025 37 4.5.1.2 Output 2: Synthesis reports and case studies on CSA best approaches and guidelines prepared and disseminated Actions: 1. Undertake analyses and provide tools to support CSA decision-making. 2. Bundle and provide synthesized information on CSA approaches and case studies on CSA best approaches. 3. Develop and test CSA guidelines and decision-making support tools. 4.5.1.3 Output 3: Multimedia CSA knowledge products, training and communications packages produced Actions: 1. Produce regular CSA information and communication materials for influential stakeholders to support and inform policies, planning and agricultural advisory services. 2. Produce CSA information and communication materials to strengthen capacity of researchers, private sector, CSOs and farmer organizations to influence policy and decision makers. 3. Develop practical guides and applied training materials and packages for training on best practices for CSA. 4.4.5.4 Output 4: CSA knowledge networks and partnerships strengthened Actions: 1. Strengthen CSA knowledge and information sharing networks/forums. 2. Develop a portfolio of information sharing technology tools to support sharing of CSA information and learning resources. 3. Establish CSA knowledge partnerships on knowledge generation, sharing and mobilization with governments, international organizations, research institutions, farmer organizations, private sector and civil society organizations. 4.5.2 Component 2: Enhance extension, climate information services and agro- weather advisories Development issues Low use of climate information services and agro-weather advisories in agricultural planning and farm management decision making (Highly inadequate agro-climate information services and inappropriate agro- weather products) Low reliability and availability of climate information Tanzania Climate Smart Agriculture Program 2015 - 2025 38 Role of climate change and weather variability in the increased post- harvest losses, and increased energy use, along value chains are not clearly known Low integration of climate research with agricultural research, Poor knowledge on weather data processing, packaging and timely dissemination. 4.5.2.1 Output 1: Agro-climate information services and timely-use of agro- weather products increased by 40 percent by 2025. Actions: 1. Identify appropriate climate/weather services and products for small scale farmers 2. Apply user friendly software such as INSTAT to generate products for improving smallholder decision making. 3. Promote integrated weather observation for improving availability and reliability of climate information. 4. Digitize historical climate data to enhance availability and accessibility of climate information. 5. Downscaling forecasted weather to various localities to promote the appropriate climate/weather services and products for small scale farmers, and pre-season dissemination of agro weather advisories 6. In-season community agro-weather monitoring and post-season agro- weather review 7. Upscale the mobile phone based early warning system. 8. Strengthen integration of climate research with agricultural research 9. Training of Regional Coordinators on CSA 4.6 Result Area 6: Improved Institutional Coordination 4.6.1 Component 1: Improve Inter-Ministerial and Local Government Coordination Development issue: Inadequate inter-ministerial coordination including collaboration with PMO Disaster Management Department. Inadequate coordination between national and local governments on agriculture related issues. Low capacity for cross-sectoral planning. Ineffective communication within and between ministries. Tanzania Climate Smart Agriculture Program 2015 - 2025 39 4.6.1.1 Output 1: A joint platform for collaboration between ministries responsible agriculture, livestock, fisheries, environment, forestry, water, finance and planning established and strengthened by end of 2015. Actions: 1. Develop and implement an inter-ministerial communications strategy with respect to inter-ministerial coordination on matters relating to climate smart agriculture. 2. Introduce a biannual joint planning and review session between inter- ministerial team and the country government officials responsible for agriculture. 3. Train national and local government staff in cross-sectoral planning and implementation. 4. Build policy review and analytical capacity at the national and local levels. 5. Strengthen the planning, implementation, monitoring and evaluation at the national and local levels. 6. Establish a framework for disseminating CSA programmatic planning and implementation as well as annual reports and studies and receiving feedback at national and local levels. 4.6.2 Component 2: Partnerships with private sector and civil society organizations Development issue: Lack of structured framework for private sector and CSOs to engage national and local governments on CSA issues. Inadequate incentives for private sector to invest in CSA. 4.6.2.1 Output 1: A platform for private sector and CSOs engagement with national and local governments established and strengthened by end of 2017. Actions: 1. Engage private sector to identify opportunities for increased investments in CSA. 2. Organize regular consultative meetings with private sector and CSOs on the planning and implementation of the CSA Program. 3. Identify appropriate incentives to catalyze private sector and CSO investments in CSA activities. 4. Publicize the Country CSA Program to private sector and CSOs with a view to identifying areas for their participation. Tanzania Climate Smart Agriculture Program 2015 - 2025 40 5. Establish communication channels for consultations between private sector and CSOs in the programmatic planning and implementation of CSA activities at the national and local levels 4.6.3 Component 3: Programmatic Coordination with Development Partners strengthened Development issue: Fragmented projects/programmes on CSA or CSA-related initiatives. Varied financial management, procurement, monitoring and evaluation systems. Weak ownership of intervention at the national and local levels. 4.6.3.1 Output 1: GoT – Development Partner Coordination and Collaboration strengthened and Development Partners fund a common Country CSA Program by end of 2015 Actions: 1. Harmonize GoT and development partners’ investments in climate smart agriculture through a common Country (National) CSA Program. 2. Strengthen collaboration between GoT and the Development Partners’ Agriculture Coordination Group (with a standing agenda item programmatic planning and implementation of CSA Program). Tanzania Climate Smart Agriculture Program 2015 - 2025 41 5.0 COORDINATION FRAMEWORK 5.1 Institutional Arrangements The National Climate Change Technical Committee (NCCTC) and National Climate Change Steering Committee (NCCSC) will guide the coordination and implementation of the CSA Program. The NCCTC shall provide technical advice to the National Climate Change Focal Point (NCCFP) in the Vice President’s Office – Division of Environment, while the NCCSC shall provide policy guidance and ensure coordination of Programmatic Result Areas as well as cross-sectorial participation. The MAFC Environment Management Unit (EMU) will be the implementation Sector focal point for the Country CSA Program. In that case Head of EMU is responsible and accountable for ensuring the smooth implementation of the Country CSA Program. The main constraint is that EMU does not currently have a budget allocation for climate change activities including CSA. The National Climate Smart Agriculture Task Force (NCSATF) formed under the EAC directives with a broad range of government and non-governmental stakeholders will have an overall responsibility for coordination and delivery of the expected Programmatic Result Areas outcomes. Hence, NCSATF will monitor implementation of the Country CSA Program, serve as a vital coordination function between MAFC, MDAs, NSAs, and regional entities such as the EAC, SADC, COMESA and issue directives to all relevant MAFC departments and units for implementing Programmatic Result Areas. 5.2 Coordination of Activities Coordination mechanism of different activities that will be implemented by different sectors involved in the promotion of CSA practices is highlighted in Figure 10. Tanzania Climate Smart Agriculture Program 2015 - 2025 42 Figure 14: Coordination mechanism among the different implementers of CSA practices Tanzania Climate Smart Agriculture Program 2015 - 2025 43 6.0 ROLES AND RESPONSIBILITIES OF DIFFERENT SECTORS The implementing partners of the Country CSA Program will have different roles and responsibilities as highlighted in the following table: 6.1 MAFC and MANR Divisions and Units All MAFC and MANR Divisions/Units will be instrumental in implementing the Country CSA Program as well, and include technical and research units at the national and sub-national levels. Of particular importance is the Department of Policy and Planning (DPP) under MFC– as the entity with responsibility for strategic planning and policy development, will need to assist with ensuring that resources are allocated for the program implementation. The ICT unit will have a key role in managing the developed ACRP website where all the information and communication- on CSA will be done. Technical divisions/departments will have a key role in implementing Programmatic Result Areas. Importantly MAFC will work closely with major agricultural programmes and initiatives related to agriculture as well as climate change, including the ASDP-2 Secretariat, the Big Results Now Presidential Delivery Bureau- and the SAGCOT Centre to promote the implementation of the Programmatic Result Areas. Large agriculture programmes and initiatives are well placed to promote climate resilience, pilot innovations, and reduce the environmental impacts of the sector that can drive climate vulnerability. 6.2 Ministries, Departments and Agencies (MDAs) Several other MDAs are linked with agricultural activities and necessary for implementation of CSA activities for building resilience in the agriculture sector. MAFC will be responsible for forging links with these MDAs and incentives to coordinate. It will be important for other sectors with linked activities to coordinate with MAFC, as their action plans are developed to identify opportunities to link activities, since climate change is an issue that cuts across sectors. 6.3 Non-State Actors Non-State Actors, including research institutions, universities, the private sector, NGO and CSOs, and Development Partners include key stakeholders that can contribute to fulfilling research needs, providing financial resources, and technical assistance toward implementation of the Country CSA Program. MAFC will need to coordinate closely especially with NGOs who are working in the field and are on the front line of practices that can be scaled up with additional support. Tanzania Climate Smart Agriculture Program 2015 - 2025 44 6.4 Sub-National Entities Sub-national entities will be key recipients of Programmatic Result Areas, including training, finance, and technical assistance, but much of the Result Areas implementation will rest at the sub-national level as well. Entities such as District-level Local Government Authorities, District Irrigation Development Teams, Zonal Plant Health Centres, regional Agricultural Research Institutes, and River Basin Offices will all play a role in each of the Programmatic Result Areas actions. Table 6: Roles and Responsibilities of Different Sectors ORGANIZATION/ STAKEHOLDER ROLES/ RESPONSIBILITY COMPARATIVE ADVANTAGE TARGET WHAT THEY CAN DO FOR CSA COUNTRY PROGRAMME VPO / 1st VP (Zanzibar) Climate Change Focal Point Climate Change Expertise Climate Change adaptation and mitigation Technical support by Climate Change Secretariat MAFC Coordination Monitoring and Evaluation Technical Expertise Productivity and food security Technical and financial support Monitoring and Evaluation MANR (Zanzibar) Co-coordination Technical Expertise Productivity and food security Technical and financial support National Climate Smart Agriculture Taskforce (NCSATF) Solicit funds, information sharing Technical Expertise Climate Smart Agriculture adoption Mainstreamin g and adoption MoF Climate financing Financial Expertise Climate finance Technical and financial support MNRT, MLFD, PMO- RALG, NEMC, TMA, MITM, MoW, MEM, Planning Commission, MLHHS, Policy formulation, capacity building, monitoring and evaluation, technical backstopping on CSA - Technical Expertise - Physical and financial resources Service provision, CC adaptation and mitigation Enabling environment Regional Secretariat Coordination of LGAs Linkage between Sector Ministries and LGAs Monitoring and evaluation Coordination mechanism Provide linkage Coordination and reporting LGAs Policies / strategies / programmes Nationwide coverage in implementation Adoption of CSA technologies Dissemination Tanzania Climate Smart Agriculture Program 2015 - 2025 45 ORGANIZATION/ STAKEHOLDER ROLES/ RESPONSIBILITY COMPARATIVE ADVANTAGE TARGET WHAT THEY CAN DO FOR CSA COUNTRY PROGRAMME implementers Formulation of by - laws and practices Research Institutions / Academia Research and technology development High tertiary level Training (short and long-term) Scientific knowledge management Scientific expertise Training capacity Access to new scientific knowledge Infrastructure International collaboration Identification and development of sustainable CSA technologies Research on improving CSA technologies Technology evaluation, improvement and validation, Disseminatio n of innovative CSA technologies to different to agro- ecological zones NGOs, CBOs, FBOs Dissemination of CSA extension packages/ awareness raising Close to the community, lobbying and advocacy on CSA related matters Adoption of CSA technologies and practices, awareness creation Dissemination Private Sector (TCCIA, ANSAF, etc.) Resource mobilization Entrepreneursh ip investment facility, input supply, credit facility Investment and business opportunities Financial support Development Partners Resource mobilization, technical assistance Technical expertise Financial resources Climate Change adaptation and mitigation Financial and technical support Regional initiatives (CCAFS, COMESA, EAC and SADC) Resource mobilization, technical assistance Technical expertise Financial resources Climate Change adaptation and mitigation Financial and technical support Tanzania Climate Smart Agriculture Program 2015 - 2025 46 7.0 MONITORING AND EVALUATION Participatory Monitoring and Evaluation (PM&E) framework that ensures the project targets are met and learning achieved will be an emphasis of the proposed investment plan. Capacity building in PM&E and mentoring process for site team and other core members will be done in each target area. The process will include participatory monitoring and tracking of major outcomes for each specific objective. The PM&E will serve several functions such as tracking progress, learning and change as well as collecting data for answering key questions, and for project management. Technical and financial reports will be delivered on an agreed-upon schedule to communicate progress to the different stakeholders. The reporting framework including the content of reports, frequency of submission, responsible parties and target recipients will be developed and agreed between parties involved. As mentioned in the previous sections this is a multi-partner programme involving the central government, local government, private sector and non-governmental organisations. The tools for M&E will include the programme log frame and annual work plan and budget. Audit of project activities constitutes part of M&E system. Activity Based Result framework is attached as annex VII. Tanzania Climate Smart Agriculture Program 2015 - 2025 47 8.0 TEN - YEAR PROGRAMME FINANCING FRAMEWORK The CSA programme document is mainly intended to be a guiding document that will be used to leverage financial support from the Government of Tanzania and various Development Partners. It is in particular anticipated that most of the activities will carried out as separate projects with detailed operationalization narratives and budgets. Prior to, and during the Stakeholders’ Validation workshop, different Development Partners have expressed interest in funding various components depending on their priorities. As such the document therefore broadly identify focus areas where funding during the next 10-years should be directed. The sustainability of CSA programme is mainly based on the premise that activities under different focus areas will be mainstreamed in various plans of the different ministries and other stakeholders. 8.1 Cost Estimates and indicative Financing Plan Table 7 shows cost estimates of US $32.158 Million projected over ten years in nominal terms. Budget for first three years are higher due the needed investment in terms of infrastructure and equipment. However, this figure is only indicative and does not prescribe a limit. Tanzania Climate Smart Agriculture Program 2015 - 2025 48 Table: 7. Summary of CSA Cost Estimates for 10 Years Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total A: Investment 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 B: Components 1.1 Improved productivity and nutrition 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 1.2 Irrigation and water management 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 1.3 Improved Food Storage and Distribution 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 1.4 Increased Growth of Incomes 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 2.1 Improve soil health and restore degraded lands 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 2.2 Conservation of Natural Resources and Catchments 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 2.3 Insurance and Other Safety Nets 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.4 Early Warning System and Emergency Preparedness 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 2.5 Synergies in adaptation and mitigation enhanced 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 3.1 Development of new agricultural products 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 3.2 Increased competitiveness and enhanced integration into domestic, regional and international markets 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 4.2 Research Extension Linkage strengthened and made functional by 2018 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 5.1 CSA knowledge generation and dissemination 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 5.2 Enhance extension, climate information services and agro- weather advisories 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 6.1 Improve Inter-Ministerial and Local Government Coordination 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 6.2 Partnerships with private sector and civil society organizations 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 6.3 Programmatic Coordination with Development Partners strengthened 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 GRAND TOTAL 6,347,000 5,272,000 5,364,000 3,979,000 3,284,000 2,521,000 2,194,000 2,154,000 1,904,000 1,889,000 32,158,000 BASE COSTS IN US$ Summary Cost by Component Tanzania Climate Smart Agriculture Program 2015 - 2025 49 ANNEXES Annex I: Tanzania Map Tanzania showing regional and international boundaries Tanzania Climate Smart Agriculture Program 2015 - 2025 50 Annex IIa: Tanzania Agricultural Zones Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season COAST North: Tanga (except Lushoto), Coast and Dar- es- Salaam Infertile sands on gently rolling uplands, Alluvial soils in Rufiji, Sand and infertile soils Under 3000 North: Bimodal, 750- 1200mm October- December and March- June South: Eastern Lindi and Mtwara (except Makonde Plateau) Fertile clays on uplands and river flood plains South: Unimodal, 800- 1200mm December- April ARID LANDS North: Serengeti, Ngorongoro Parks, Part of Masai land North: Volcanic ash and sediments. Soils variable in texture and very susceptible to water erosion 1300- 1800 North: Unimodal, unreliable, 500-600mm March- May Masai Steppe, Tarangire Park, Mkomazi Reserve, Pangani and Eastern Dodoma South: Rolling plains of low fertility. Susceptible to water erosion. Pangani river flood plain with saline, alkaline soil 500-1500 South: Unimodal and Unreliable, 400-600mm SEMI-ARID LANDS Central Dodoma, Singida, Northern Iringa, some of Arusha, Shinyanga Central: Undulating plains with rocky hills and low scarps. Well drained soils with low fertility. Alluvial hardpan and saline soils in Eastern Rift Valley and lake Eyasi. Black cracking soils in Shinyanga. 1000- 1500 Central: unimodal and unreliable: 500-800mm December - March Tanzania Climate Smart Agriculture Program 2015 - 2025 51 Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season Southern: Morogoro (except Kilombero and Wami Basins and UluguruMts).Also Lindi and Southwest Mtwara Southern: Flat or undulating plains with rocky hills, moderate fertile loams and clays in South (Morogoro), infertile sand soils in centre 200-600 South-eastern: Unimodal 600- 800mm PLATEAUX Western: Tabora, Rukwa (North and Centre), Mbeya Western: Wide sandy plains and Rift Valley scarps 800-1500 Western: unimodal, 800- 1000mm November- April North: Kigoma, Part of Mara Flooded swamps of Malagarasi and Ugalla rivers have clay soil with high fertility 1,500- 1,700 Southern: Ruvuma and Southern Morogoro Southern: upland plains with rock hills. Clay soils of low to moderate fertility in south, infertile sands in North. 500- 2,000 Southern: unimodal, very reliable, 900- 1300mm SOUTHERN AND WESTERN HIGHLANDS Southern: A broad ridge of from N. Morogoro to N. Lake Nyasa, covering part of Iringa, Mbeya Southern: Undulating plains to dissected hills and mountains. Moderately fertile clay soils with volcanic soils in Mbeya 1200- 1500 Unimodal, reliable, local rain shadows, 800-1400 December – April South-western: Ufipa plateau in Sumbawanga South-western: Undulating plateau above Rift Valleys and sand soils of low fertility 1400- 2300 Unimodal, reliable, 800- 1000 November- April Western: Along the shore of Lake Tanganyika in Kigoma and Kagera Western: North-south ridges separated by swampy valleys, loam and clay soils of low fertility in hills, with alluvium and ponded clays in the valleys 100-1800 Bimodal, 1000- 2000 October- December and February- May Tanzania Climate Smart Agriculture Program 2015 - 2025 52 Zone Sub-Zone and areas Soils and Topography Altitude (m) Rainfall (mm/yr) Growing season NOTHERN HIGHLANDS Northern: foot of Mt. Kilimanjaro and Mt. Meru. Eastern Rift Valley to Eyasi Northern: Volcanic uplands, volcanic soils from lavas and ash. Deep fertile loams. Soils in dry areas prone to water erosion. 1,000- 2,500 Bimodal, varies widely 1000- 2000 November- January and March-June Granite MtsUluguru in Morogoro, Pare Mts in Kilimanjaro and UsambaraMts in Tanga, Tarime highlands in Mara Granite steep Mountain side to highland plateaux. Soils are deep, arable and moderately fertile on upper slopes, shallow and stony on steep slopes 1,000- 2,000 Bimodal and very reliable 1000-2000 October- December and March- June ALLUVIAL PLAINS Kilombero (Morogoro) Cental clay plain with alluvial fans east and west 750-1200 Unimodal, very reliable, 900- 1300 November- April Rufiji (Coast) Wide mangrove swamp delta, alluvial soils, sandy upstream, loamy down steam in floodplain <500 Unimodal, often inadequate 800-1200 December- April Usangu (Mbeya) Seasonally Flooded clay soils in North, alluvial fans in South 2,400- 5,000 Unimodal, 500- 800 December- March Wami (Morogoro) Moderately alkaline black soils in East, alluvial fans with well drained black loam in West 400- 1,000 Unimodal, 600- 1800 December- March Source: Modified from de Pawn, 1984 Tanzania Climate Smart Agriculture Program 2015 - 2025 53 Annex IIb: Tanzania Agricultural Map Source: SUA Tanzania Climate Smart Agriculture Program 2015 - 2025 54 Annex III: Agricultural production ‘000 Metric Tons Year 2003/0 4 2004/0 5 2005/0 6 2006/0 7 2007/0 8 2008/0 9 2009/1 0 2010/1 1 2011/1 2 2012/1 3 2013/14 * Maize 3,157 3,219 3,423 3,302 3,556 3,326 4,475 4,341 5,104 5,288 6,734 Sorghum 757 714 712 971 861 709 789 807 839 782 883 Millets 201 221 228 194 203 220 372 312 214 292 363 Rice 688 759 805 872 875 868 1,700 1,461 1,170 1,342 1,681 Wheat 67 102 110 83 92 95 62 113 109 102 167 Pulses 879 886 1,050 1,156 1,126 1,116 1,254 1,632 1,827 1,871 1,697 Cassava 1,480 1,846 2,053 1,733 1,797 1,972 1,464 1,549 1,821 1,878 1,664 Bananas 734 991 1,169 1,028 982 1,073 975 1,048 842 1,317 1,064 Potatoes 874 931 1,396 1,322 1,379 1,392 1,231 1,710 1,418 1,808 1,761 Crop Metric Tons 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 Tea 32,000 30,000 34,446 32,698 34,165 33,160 35,000 33,000 33,700 33,000 Sugarcane 229,620 263,317 192,535 265,434 276,605 279,850 317,000 260,055 286,380 293,011 Tobacco 51,970 56,500 65,299 55,567 58,702 60,900 78,000 126,624 74,240 100,000 Cotton 344,210 376,591 130,565 200,662 368,229 267,004 260,000 225,938 351,151 246,767 Pyrethrum 1,000 2,800 1,500 2,800 3,280 3,320 5,000 5,700 6,100 7,000 Sisal 26,800 27,794 30,934 33,039 33,208 26,363 35,000 33,406 23,344 41,104 Coffee 54,000 34,334 48,869 43,000 62,345 40,000 60,575 33,219 71,200 48,599 Cashew 81,600 77,158 92,232 99,107 79,068 74,169 121,070 160,00 121,704 127,939 Tanzania Climate Smart Agriculture Program 2015 - 2025 55 Crop 2008/2009 2009/10 2010/11 2011/12 2012/13 2013/14 Fruits 557,400 3,297,910 3,751,170 3,938,730 4,096,280 4,416,690 Vegetables 602,000 766,570 858,740 901,680 937,750 1,005,305 Flower 8,670 9,100 9,850 10,200 10,790 Spices 6,865 7,150 7,370 8,125 8,377 Source: BEST, 2014 Tanzania Climate Smart Agriculture Program 2015 - 2025 56 Annex IV: Agriculture Sector Financing Gap (TShs) 2010/2011 – 2014/2015 Annex V: Resource Requirement for Zanzibar Tanzania Climate Smart Agriculture Program 2015 - 2025 57 Annex VI: Wood Fuel Demand and Consumption Wood Fuel Demand (2012) Woodfuel Demand Firewood Charcoal Total Charcoal & Firewood in m3 Fuel Wood (mi) Tonnes (mi) M3 Fuel wood (mi) Tonnes (mi) M3 Fuel wood equiv (mi) Rural 20.97 29.96 0.52 3.88 33.83 Urban 1.64 2.34 1.51 11.38 13.72 Total 22.60 32.29 2.03 15.26 47.55 Source: Adapted from BEST, 2014 Tanzania Fuel Wood Consumption by household (2012) Area Total Population percent Population using wood No. using wood Dar es Salaam 4,364,541 3.0 percent 130,936 Other Urban 7,316,739 19 percent 1,381,334 Rural 33,246,720 90.0 percent 29,922,048 Total 44,928,000 70.0 percent 31,434,318 Sources: National Bureau of Statistics 2002 and 2012 Census, and 2007 Household Budget Survey, and Tanzania Commission for AIDS, Tanzania HIV/AIDS and Malaria Indicator Survey 2011-12 (NBS, 2007, NBS, 2009, NBS, 2013b and TACACIDS, 2013) Tanzania Climate Smart Agriculture Program 2015 - 2025 58 Annex VII: Logical Framework Matrix or Program Design Matrix Verifiable Indicators Source of Verification Assumptions Overall Goal Tanzania achieves enhanced sustainable productivity, climate resilience and food security for the agricultural sector growth CSA Policy index (CSA-Pol) CSA Results index (CSA-Res) Specialized targeted surveys End of Program evaluation Report Available policies to support CSA Available services and infrastructure to support CSA Governments continue to support agriculture and poverty reduction as priorities Equitable distribution of benefits occurs PDO (Purpose) The PDO is: A: Enhanced climate resilience of agricultural and food systems B: CSA Program - Strengthens policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture C: Enhance collaboration in CSA related activities among ministries, agencies institutions and private sector service providers % of farming communities practicing CSA (disaggregated by gender) Rate of change of adoption of sustainable climate smart technologies and sustainable land management practices (disaggregated by type) – (in %) Rate of increase in CSA information and knowledge transfer among stakeholders Rate for adaptation to climate change and variability End of Program evaluation Report Mid-Term Reports Quarterly Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 59 Verifiable Indicators Source of Verification Assumptions Tanzania CSA programs accesses climate financing and uses it effectively to support climate change resilience and low carbon sustainable growth Level of stakeholder satisfaction with the CSA technologies and innovations (%) by number of products users (by gender, age, and location) Transparent national Climate Change financing mechanism established Intermediate Outcomes Component 1: Improved Productivity and incomes CSA Program has enhanced use of climate-smart agricultural practices, promoting improved land management and sustainable crop-livestock and fisheries intensification New CSA practices developed relative to plan (%) Number of Sustainable CSA technologies adopted by smallholder farmers Increased annual yields of targeted crops (such as maize, rice, sorghum, cassava, potatoes and beans, aquaculture and livestock Percent of farmers using improved inputs. Number of extension officers and management of Irrigators Evaluation Reports Annual Reports Communication priority setting document Annual survey reports. Mid Term Reports Review Missions Implementation support Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 60 Verifiable Indicators Source of Verification Assumptions Organization trained. Number of farmers trained on irrigation technologies % increase in irrigated land Number of irrigation schemes constructed to its full potentiality. % increase in Income from crop, livestock, aquaculture production by men and women Component 2: Building resilience and associated mitigation co-benefits Strengthened policy, legal and institutional framework to increase efficiency and effective implementation of climate smart agriculture in identified priority areas. Number of evidence based policy responses to food insecurity adopted Number of established CSA/SLM Knowledge Platforms with disaggregated data on men and women. Number of villages with land use plan. Number of small scale CSA projects implemented annually. % change in Farm/community forest cover Quarterly Reports Annual survey reports. Evaluation Reports CSA Program Annual Reports Specialized survey Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 61 Verifiable Indicators Source of Verification Assumptions Rate of Adoption of sustainable climate smart technologies and sustainable land management practices Number of generated CSA and SLM knowledge to support policy and investment decision making % change in Crop and livestock weather-indexed insurance Reduction of GHG emissions intensity from the agriculture sector (%) Component 3: Value Chain Integration Availability of infrastructure to support value addition, marketing, trade and postharvest management. Number of new commercially viable products developed from each of the staple crops, horticultural crops, livestock and fisheries Number of Efficient pilot value chains developed for selected commodities in each agro-ecological zone Value and Quantity of Marketed output of food and cash crops, livestock and fish products by smallholders Quarterly Reports Evaluation Reports Annual Reports Mid Term Reports Review Missions Implementation support Reports TRA data. Annual survey reports Partnerships and platforms with adequate capacity for generation and uptake of technologies and innovations exist Government, non- government, regional and national organizations operate effectively at appropriate levels. Tanzania Climate Smart Agriculture Program 2015 - 2025 62 Verifiable Indicators Source of Verification Assumptions Value of Export of non-traditional agricultural commodities by men and women smallholders Established Grading and standardization systems of agricultural commodities Component 4: Research for Development and Innovations Generated and disseminated improved land management and gender sensitive climate resilient agricultural practices and technologies in targeted areas Hectares of land managed under climate-resilient practices Number of CSA technologies developed Increased funding in research and development and innovations % adoption of improved CSA technologies and practices by men and women along the value chain Quarterly Reports Publications Mass media Evaluation Reports Annual survey reports Annual Reports Mid Term Reports Review Missions Implementation support Reports Diagnostic Survey Reports Agricultural research in support of CSA Conducive policy environment maintained Component 5: Improving and Sustaining Agricultural Advisory Services Knowledge on Climate Smart Agriculture documented and scaled up and out in targeted areas. Number of existing and new CSA practices disseminated targeted areas Number of Ward Resource Centres equipped with CSA knowledge. Quarterly Reports Publications Mass media Annual survey reports. Evaluation Reports Annual Reports Mid Term Reports Government, non- government, regional and national organizations operate effectively at appropriate levels. Conducive policy environment maintained Partnerships and platforms Tanzania Climate Smart Agriculture Program 2015 - 2025 63 Verifiable Indicators Source of Verification Assumptions Number of demand-driven gender- responsive CSA made available to uptake pathways Number of technology uptake pathways (e.g. web-based information platform, radio, TV program, etc.) compared to plan. Established robust CSA Knowledge Management System (Platform/Hub) across the country Number of synthesis reports and case studies on CSA best approaches and guidelines prepared and disseminated % increase in agro-climate information services and timely-use of agro-weather products Level of satisfaction of stakeholders with the technology uptake pathways (%) Number of stakeholders whose capacity building needs have been addressed Number of networks and stakeholder Review Missions Implementation support Reports with adequate capacity for generation and uptake of technologies and innovations exist Primary schools leavers with CSA knowledge and practice Tanzania Climate Smart Agriculture Program 2015 - 2025 64 Verifiable Indicators Source of Verification Assumptions platforms Number of staff trained (short-term and study tours) and applying skills acquired in conducting CSA practices Component 6: Improved Institutional Coordination Coordination and management of CSA activities and initiatives in all implementing agencies enhanced Number of Climate Change plans developed in key sector ministries, private sector Percent of CSA Program activities implemented according to plan. Harmonized M&E system for CSA Program developed, adopted, and implemented according to plan (%). Established effective joint platform for collaboration between ministries responsible agriculture, livestock, fisheries, environment, forestry, water, finance and planning Number of relevant policies, laws, regulations, and/or procedures reviewed for harmonization Level of compliance with the Environment and Social Safeguards. Evaluation Reports Annual Reports Mid Term Reports Review Missions Implementation support Reports Quarterly Reports Tanzania Climate Smart Agriculture Program 2015 - 2025 65 Footnote: 1. The CSA-Pol reflects the most significant aspects of the enabling environment for implementing CSA at the national level. 2. The CSA-Res indicators provide an understanding about the short-term to medium-term results of a CSA intervention which may relate to food security, poverty reduction and environmental sustainability. Tanzania Climate Smart Agriculture Program 2015 - 2025 66 Annex VIII: Budget Estimates for 2015 - 2025 Activities Expendit ure Account Unit of measure Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Unit Cost (in US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total Rehabilitate existing warehouses and silos Works Set 0 2 2 1 0 30,000 0 60,000 60,000 30,000 0 0 0 0 0 0 150,000 Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. Works Set 1 1 1 0 0 100,000 100,000 100,000 0 0 0 0 0 0 0 0 200,000 Develop agro-meteorological infrastructure to support weather-indexed insurance Works Unit 0 2 2 0 0 150,000 0 300,000 300,000 0 0 0 0 0 0 0 600,000 Construction of water harvesting structures at household and community levels. Works Unit 5 5 5 5 5 5 5 50,000 0 250,000 250,000 250,000 250,000 250,000 250,000 250,000 100,000 710,000 610,000 280,000 250,000 250,000 250,000 250,000 0 0 950,000 Procurement of office equipment/a Goods Unit 24 0 12 0 0 15 50,000 1,200,000 0 600,000 0 0 0 0 0 0 1,800,000 Procurement of vehicles Goods Unit 10 0 0 5 0 10 50,000 500,000 0 0 250,000 0 0 0 0 0 0 750,000 1,700,000 0 600,000 250,000 0 0 0 0 0 0 2,550,000 Short term courses Study tour Tour Lump sum 60 50 50 50 0 5,000 300,000 250,000 250,000 250,000 0 0 0 0 0 0 1,050,000 short-term training Training Lump sum 50 50 50 50 50 20 20 20 20 3,000 150,000 150,000 150,000 150,000 150,000 0 0 0 0 0 750,000 0 0 0 0 0 0 0 0 0 0 0 450,000 400,000 400,000 400,000 150,000 0 0 0 0 0 1,800,000 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 ** Footnotes: a/ Computer set= computer, printer, scanner and accessories, photocopiers, GPS Total Cost Physical and Human Resources BASE COSTS US$ 1.1. Physical resources Quantities A: Investment 1.2: Human resources Sub Total Civil Works Sub Total Office Equipments Sub Total Human Resources 1.1.2: Office equipments 1.1.1: Civil works 1.2.2: Trainings and tours Tanzania Climate Smart Agriculture Program 2015 - 2025 67 4.1 Improved Productivity and Incomes Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total Identify, upgrade, disseminate and practice climate smart technological packages service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Introduce improved crop varieties (high yielding, early maturing, disease and pest resistant and nutrient fortified) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Increase access to farm inputs (fertilizers/pesticides/seeds/vet drugs) and its wise application Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen surveillance of agricultural input trade and use Service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 600,000 Identification of best indigenous knowledge and its interaction with scientific knowledge to enhance climate change adaptation Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Train farmers on CSA agronomic practices Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Introduce improved livestock breeds (increased productivity, disease resistant and drought tolerant) Service Lumpsum 1 2 2 1 1 0 0 0 0 0 30,000 30,000 60,000 60,000 0 0 0 0 0 0 0 150,000 Undertake genetic characterization and improvement of local livestock breeds Service Lumpsum 1 1 1 1 1 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 200,000 Identify, upgrade, disseminate and practice improved livestock technological packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 40,000 40,000 40,000 40,000 0 0 0 0 0 0 0 120,000 Train farmers on livestock husbandry and disease management Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Develop and disseminate best management practices of aquaculture throughout the country Service Lumpsum 1 1 1 1 1 1 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 210,000 Train fisher folks in good fishing practices Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Strengthen fish health and disease surveillance Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Strengthen and increase fingerlings breeding and multiplication centers Service Lumpsum 1 1 1 1 0 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 0 160,000 Sensitize and support private sector involvement in fingerling and feed production and distribution Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Strengthen integrated fish farming (e.g. in paddy farms) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote production and consumption of high quality protein cereals, orange fleshed sweet potatoes (for vitamin A) and leafy vegetables Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Develop other high quality staples through breeding – cassava, rice, potatoes etc Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote fortification of staples during processing (micronutrient fortification and blending products) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Educate and train consumers on appropriate food combination Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 Unit Cost (in US$) Sub Total BASE COSTS IN US$ Component Activities Quantities 4.1.1 Improved productivity and nutrition Expenditure Account Unit of measure Tanzania Climate Smart Agriculture Program 2015 - 2025 68 Promote development and diffusion of appropriate efficient small-scale irrigation technological packages. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Train extension workers on irrigation and water management technologies and skills. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Build the capacity of Irrigators Organizations in agricultural water management and their obligations Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Undertake comprehensive management needs assessment of existing large scale irrigation schemes. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Review of the National Irrigation Master Plan (2002) and update irrigation potential areas for small scale irrigation Service Lumpsum 1 1 0 0 0 0 0 0 0 0 35,000 35,000 35,000 0 0 0 0 0 0 0 0 70,000 Train farmers in the installation, operation and maintenance of recommended irrigation technologies Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Establish links to input and output markets and service providers (strengthen value chain and technical backstopping). Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Identify suitable areas for rainwater harvesting and agricultural water management systems. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Train farmers/household members in water harvesting and agricultural water management technologies. Service Lumpsum 1 1 1 1 1 1 1 1 1 0 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 0 135,000 Facilitate the construction of water harvesting structures at household and community levels. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Introduce and promote in-situ rainwater harvesting technologies (e.g. Conservation agriculture) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 45,000 450,000 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 4.1.2 Irrigation and water management Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 69 Invest in improved appropriate storage facilities and technologies along the value chain. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 0 0 200,000 Promote small scale agro-processing industries in rural areas. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Train producers, processers and marketers in post-harvest management. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Provide regular market information (deficit/surplus areas) to improve distribution of agricultural commodities/food stuffs. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Facilitate establishment of marketing centres in rural areas with the appropriate infrastructure. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Link Region and District by feeder roads to various marketing centres and highways. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Strengthen and link the smallholder farmers to the Warehouse Receipt System (WRS) in the grain supply chain. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 180,000 Establish Public-Private-Partnerships management. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Support private sector to invest in food processing, pasture and pasture seed production as well as value addition, Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Facilitate linkages with relevant service providers and markets (inputs and outputs). Service Lumpsum 1 1 1 1 1 1 0 0 0 0 12,000 12,000 12,000 12,000 12,000 12,000 12,000 0 0 0 0 72,000 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 4.1.3 Improved Food Storage and Distribution Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 70 Build capacity of nursery operators in all crop growing areas and support them to expand and improve quality of seedlings. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Build capacity of Quality Declared Seed producers and support them to expand and improve quality of seed. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Build capacity of food and cash crop farmers to improve productivity and produce quality. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Facilitate contractual arrangements between food and cash crop producers and market/industry. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 150,000 Develop and promote innovative micro- financing packages to facilitate food and cash crop farmers to access credit. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Rehabilitate, restock and build capacity of livestock breeding centres to produce improved breeds of livestock. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 120,000 Facilitate and support the acquisition of improved breeding stocks by men and women farmers. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Provide adequate and effective extension knowledge and agro-weather information Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen and/or establish efficient and sustainable animal health and artificial insemination services. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Develop and support innovative micro- financing packages to support livestock keepers’ access to credit and markets. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Identify areas with acute problem of water for livestock and construct water infrastructures. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 30,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Facilitate improvement of demarcated grazing lands Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Promote use of crop residues and agro- industry byproducts Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Promote value addition for livestock products Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Facilitate and support acquisition of fingerlings by men and women fish farmers Service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 0 150,000 Promote value addition for fish products Service Lumpsum 1 1 1 1 1 0 0 0 0 0 20,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Facilitate contractual arrangements between fish farmers and market Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Establish and support innovative micro- financing packages to support fisherfolks access to credit. Service Lumpsum 1 1 1 1 0 0 0 0 0 0 20,000 15,000 15,000 15,000 15,000 0 0 0 0 0 0 60,000 Support Local Governments to identify and demarcate potential areas within urban and peri-urban areas for agricultural activities. Service Lumpsum 1 1 1 1 0 0 0 0 0 0 30,000 20,000 20,000 20,000 20,000 0 0 0 0 0 0 80,000 Train urban and peri-urban producers in Good Agricultural Practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Monitor the safety of outputs from urban and peri-urban agriculture. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Enforce laws and bylaws related to urban and peri-urban land use. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 6,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 1,707,000 1,737,000 1,702,000 1,447,000 1,372,000 1,062,000 850,000 850,000 850,000 835,000 12,412,000 4.1.4 Increased Growth of Incomes Sub Total TOTAL RESULT AREA 1 : IMPROVED PRODUCTIVITY AND INCOMES Tanzania Climate Smart Agriculture Program 2015 - 2025 71 4.2. Building resilience and associated mitigation co-benefits Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Unit Cost (in US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Promote integrated soil fertility and water management interventions. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Establish CSA/SLM knowledge hubs across the country to support adoption of CSA and SLM technologies and practices by men and women that improve soil health and restore degraded lands. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Enhance the capacities of private sector service providers and farmer-based organizations to support farmers’ adoption of existing/new/improved CSA and SLM technologies and practices. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Develop and integrate CSA and SLM principles into farmer-field schools, primary, secondary and tertiary curriculum. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 20,000 20,000 20,000 20,000 20,000 20,000 0 0 0 0 0 100,000 Establish mechanisms for joint planning and implementation of CSA and SLM at the local level. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Develop and implement sustained awareness creation program on CSA and SLM in addressing soil health and land degradation challenges. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Facilitate the development and implementation of at least five (5) small scale CSA Projects annually. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Facilitate the dissemination and adoption of CSA and SLM technologies and practices at the farm level across the country through Local Government’s CSA Projects. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 100,000 1,000,000 Establish CSA/SLM Knowledge Platform with disaggregated data on men and women. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Document and publicize successful CSA/SLM technologies, practices and interventions Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 Total BASE COSTS IN US$ Component Activities Unit of measure Expenditure Account Quantities Sub Total 2.1 Improve soil health and restore degraded lands Tanzania Climate Smart Agriculture Program 2015 - 2025 72 Upscale Natural Forest Conservation through Participatory Forest Management (PFM) Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 Protect water catchment areas through integrated watershed management. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Increase forest cover through natural regeneration, Agroforestry, Reforestation. and Afforestation Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Promote best management practices for natural resources management to improve and maximize net benefits for the farmers and other downstream users (e.g. power generation and urban water supply). Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Promote and support on farm soil conservation activities Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Promote sustainable production and marketing of charcoal from miombo woodlands Service Lumpsum 1 1 1 1 1 1 1 1 1 1 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 13,000 130,000 Promote sustainable land use management Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Develop a business model for ecosystem management in order to facilitate payment for ecosystem services (e.g. tourism revenue used to motivate farmers to conserve wildlife and payment for water in urban areas used to pay farmers for conservation of water catchments). Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Develop and implement management plans for ecosystems in order to encourage sustainable use Service Lumpsum 1 1 1 1 1 0 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 0 0 0 0 0 75,000 Document biodiversity in the ecosystems including below ground biodiversity and develop eco-tourism opportunities in such areas Service Lumpsum 1 1 1 1 1 0 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 0 0 0 0 0 75,000 Undertake natural resources accounting for ecosystem services. Service Lumpsum 0 0 0 0 1 1 1 1 1 1 15,000 0 0 0 0 15,000 15,000 15,000 15,000 15,000 15,000 90,000 Identify agroforestry species for different agro-ecological zones and support farmers to increase tree cover Service Lumpsum 1 1 1 0 0 0 0 0 0 0 12,000 12,000 12,000 12,000 0 0 0 0 0 0 0 36,000 Undertake afforestation and reforestation through Public-Private Partnerships. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 Sub Total 2.2 Conservation of Natural Resources and Catchments Tanzania Climate Smart Agriculture Program 2015 - 2025 73 Develop and implement varied innovative crop and livestock weather-indexed insurance packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Develop agro-meteorological infrastructure to support weather-indexed insurance and to use them for improved weather and climate information services for farmers. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Enhance the capacity of micro-finance institutions to act as agents to deliver innovative crop and livestock weather- indexed insurance packages. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Raise awareness within the insurance industry of extreme weather and climate risks and communicate actions and opportunities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Undertake farmer education to address their concerns regarding insurance products with a view to gain their trust Service Lumpsum 1 1 1 1 1 1 1 1 1 1 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 150,000 Establish livestock insurance schemes and use of insured livestock as collateral Service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Explore ways of using existing and other safety nets such as cash transfers or workfare programmes. Service Lumpsum 0 0 1 1 1 0 0 0 0 0 6,000 0 0 6,000 6,000 6,000 0 0 0 0 0 18,000 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.3 Insurance and Other Safety Nets Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 74 Prepare vulnerability maps for targeting food security and emergency preparedness interventions. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 Develop tools to support vulnerable households and communities to establish household community systems that can respond to emergencies (with regards to food insecurity). Service Lumpsum 1 1 0 0 0 0 0 0 0 0 20,000 20,000 20,000 0 0 0 0 0 0 0 0 40,000 Monitor crops, livestock and fish pests and diseases. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Integrate scientific weather forecasting and indigenous knowledge for early warning and to inform farmer decisions. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 Establish a National Seed Emergency stock. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 60,000 60,000 60,000 0 0 0 0 0 0 0 0 120,000 Improve EWS messages (clear, consistent) that include risk information; designed to link threat levels. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Capacity development to farmers on early warning systems and emergency preparedness. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 20,000 200,000 Improve mass delivery system particularly on content development and communication channels. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 Establish a feedback and evaluation process of messages delivered. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 Develop an effective frame-work for collaboration emergency communication centres/stakeholders. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 10,000 10,000 10,000 10,000 0 0 0 0 0 0 0 30,000 The explicit development of contingency plans on district level Service Lumpsum 1 1 1 1 1 1 1 1 1 1 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 100,000 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 Promote adoption of low cost climate smart technologies that minimize emission of carbon dioxide and enhance soil carbon t ti Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 Develop a national carbon accounting and measurement, reporting and verification Service Lumpsum 1 1 1 0 0 0 0 0 0 0 20,000 20,000 20,000 20,000 0 0 0 0 0 0 0 60,000 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 829,000 829,000 705,000 463,000 478,000 402,000 402,000 402,000 402,000 402,000 5,314,000 2.4 Early Warning System and Emergency Preparedness 2.5 Synergies in adaptation and mitigation enhanced Sub Total Sub Total TOTAL RESULT AREA 2 : BUILDING RESILIENCE AND ASSOCIATED MITIGATION CO-BENEFITS Tanzania Climate Smart Agriculture Program 2015 - 2025 75 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Solicit funds for research and innovation into agricultural value chains service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Develop improved infrastructure for agricultural value chains. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 10,000 10,000 10,000 10,000 10,000 10,000 0 0 0 0 0 50,000 Institute competitive grant scheme for agriculture value chains. Service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Identify existing value addition technologies and incentivize the private sector to promote them. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 16,000 16,000 16,000 16,000 16,000 16,000 0 0 0 0 0 80,000 Establish regional hubs (a cluster of livelihood zones in the same AEZ) for value chain development and backstopping. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 15,000 15,000 15,000 15,000 0 0 0 0 0 0 0 45,000 Identify and build capacity of actors in value chain processes. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 18,000 180,000 Undertake advanced market feasibility studies to promote demand for the selected commodities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Facilitate linkages to markets for the selected commodities. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 16,000 16,000 16,000 16,000 16,000 16,000 0 0 0 0 0 80,000 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 Unit of measure Expenditure Account Total Unit Cost (in US$) BASE COSTS IN US$ 4.3.1 Development of new agricultural products Component Activities Quantities Sub Total 3. Value Chain Integration Tanzania Climate Smart Agriculture Program 2015 - 2025 76 Create agricultural, livestock and fish commodity hubs through participation of private sector especially micro-financiers and apply viable models of linkage with smallholders Service Lumpsum 1 1 1 0 0 0 0 0 0 0 16,000 16,000 16,000 16,000 0 0 0 0 0 0 0 48,000 Facilitate capacity building of farmers on demand- and market-driven production. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Design and launch a market promotion program for import substitution commodities. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 12,000 12,000 12,000 12,000 0 0 0 0 0 0 0 36,000 Work with supermarkets, hotels and restaurants to participate in selected commodity value chains with a smallholder production base. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 8,000 80,000 Identify successful lead private sector firms with access to assured markets and apply viable models of linkage with smallholders. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 5,000 5,000 5,000 0 0 0 0 0 0 0 0 10,000 Design sustainable programmes to support the certification of smallholders for export markets. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 10,000 10,000 10,000 0 0 0 0 0 0 0 0 20,000 Develop branding of Tanzania produce for regional and international markets. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 20,000 20,000 20,000 0 0 0 0 0 0 0 0 40,000 Develop grading and standardization systems for agricultural commodities that do not have grades and standards Service Lumpsum 1 1 0 0 0 0 0 0 0 0 26,000 26,000 26,000 0 0 0 0 0 0 0 0 52,000 Promote the adoption of grading and standardization systems for all agricultural commodities for both domestic and export markets. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 245,000 245,000 184,000 116,000 116,000 74,000 74,000 74,000 74,000 74,000 1,276,000 Sub Total TOTAL RESULT AREA 3 : VALUE CHAIN INTEGRATION 4.3.2 Increased competitivenes s and enhanced integration into domestic, regional and international markets Tanzania Climate Smart Agriculture Program 2015 - 2025 77 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Increase public expenditure into research and development and innovations through national budget. service Lumpsum 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Incentivize private sector investments in research and development and innovations. Service Lumpsum 1 1 1 0 0 0 0 0 0 0 35,000 35,000 35,000 35,000 0 0 0 0 0 0 0 105,000 Conduct participatory research work on improved technologies and practices that is informed by needs of users and agro- ecological zones along the value chain. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 55,000 55,000 55,000 55,000 55,000 55,000 55,000 0 0 0 0 330,000 Conduct on-farm research into low-cost appropriate technologies and practices and deliver them as packages. Service Lumpsum 1 1 1 1 1 1 0 0 0 0 60,000 60,000 60,000 60,000 60,000 60,000 60,000 0 0 0 0 360,000 Build the capacity of extension, producers and other stakeholders in the use of existing/new/improved CSA technologies and practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 600,000 Support development of private sector input and appropriate CSA technologies outreach and distribution networks. Service Lumpsum 1 1 1 1 1 0 0 0 0 0 54,000 54,000 54,000 54,000 54,000 54,000 0 0 0 0 0 270,000 Intensify field demonstration/field days/study tours to enhance adoption of existing/new/improved CSA technologies and practices. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 400,000 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 Establish a platform through which researchers will have regular contacts with stakeholders and other users at the national, local and farm levels. Service Lumpsum 1 1 0 0 0 0 0 0 0 0 30,000 30,000 30,000 0 0 0 0 0 0 0 0 60,000 Prepare CSA information packages and disseminate them to interested stakeholders using ICT. Service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 369,000 369,000 339,000 304,000 304,000 250,000 135,000 135,000 135,000 135,000 2,475,000 Total Unit Cost (in US$) 4: Research for Development and Innovations Sub Total TOTAL RESULT AREA 4 : RESEARCH FOR DEVELOPMENT AND INNOVATIONS 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 4.2 Research Extension Linkage strengthened and made functional by 2018 Expendit ure Account Unit of measure BASE COSTS IN US$ Quantities Component Activities Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 78 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Undertake a CSA knowledge mapping, audit and analysis. service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 Equip Ward Resource Centres with CSA knowledge. service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Develop and maintain a robust and functional CSA knowledge management system. service Lumpsum 1 1 1 1 1 1 1 1 1 1 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 250,000 Build capacity to different stakeholders in the agricultural value chain at the national and local levels. service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Undertake analyses and provide tools to support CSA decision-making. service Lumpsum 1 1 0 0 0 0 0 0 0 0 25,000 25,000 25,000 0 0 0 0 0 0 0 0 50,000 Bundle and provide synthesized information on CSA approaches and case studies on CSA best approaches. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Develop and test CSA guidelines and decision- making support tools. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Produce regular CSA information and communication materials for influential stakeholders to support and inform policies, planning and agricultural advisory services. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Produce CSA information and communication materials to strengthen capacity of researchers, private sector, CSOs and farmer organizations to influence policy and decision makers. service Lumpsum 1 1 1 1 1 1 0 0 0 0 30,000 30,000 30,000 30,000 30,000 30,000 30,000 0 0 0 0 180,000 Develop practical and applied training materials and packages for training on CSA. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Strengthen CSA knowledge and information sharing networks/forums. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Develop a portfolio of information sharing technology tools to support sharing of CSA information and learning resources. service Lumpsum 1 1 1 1 1 1 1 1 1 1 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 33,000 330,000 Establish CSA knowledge partnerships on knowledge generation, sharing and mobilization with governments, international organizations, research institutions, farmer organizations, private sector and civil society organizations. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Strengthen curriculum and put emphasis on practical experience. service Lumpsum 1 1 1 35,000 35,000 35,000 35,000 0 0 0 0 0 0 105,000 Sub total 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 BASE COSTS IN US$ Unit Cost (in US$) Component Activities Quantities 4.5.1 CSA knowledge generation and dissemination 5: CSA Knowledge, Extension and Agro-weather Services Total Unit of measure Expenditure Account Tanzania Climate Smart Agriculture Program 2015 - 2025 79 Identify appropriate climate/weather services and products for small scale farmers service Lumpsum 1 1 1 1 1 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 125,000 Promote integrated weather observation for improving availability and reliability of climate information. service Lumpsum 1 1 1 1 1 1 1 1 1 1 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 50,000 500,000 Digitize historical climate data to enhance availability and accessibility of climate information. service Lumpsum 1 1 1 1 1 0 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Downscaling forecasted weather to various localities to promote the appropriate climate/weather services and products for small scale farmers, and pre-season dissemination of agro weather advisories service Lumpsum 1 1 1 1 0 0 0 0 0 0 45,000 45,000 45,000 45,000 45,000 0 0 0 0 0 0 180,000 Promote in-season community agro-weather monitoring and post-season agro-weather review service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Improve dissemination channels of climate information (e.g. use of mobile phone based early warning system). service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 300,000 Generate user friendly and tailor made products for improving smallholder farmers ‘decision making. service Lumpsum 1 1 1 1 1 1 1 1 1 1 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 350,000 Strengthen integration of climate research with agricultural research service Lumpsum 1 1 1 1 1 0 0 0 0 0 35,000 35,000 35,000 35,000 35,000 35,000 0 0 0 0 0 175,000 Training of Regional Coordinators on CSA. service Lumpsum 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 0 0 0 280,000 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 463,000 498,000 458,000 458,000 378,000 283,000 283,000 243,000 243,000 243,000 3,550,000 Sub Total TOTAL RESULT AREA 5 : CSA KNOWLEDGE, EXTENSION AND AGRO-WEATHER SERVICES 4.5.2 Enhance extension, climate information services and agro- weather advisories Tanzania Climate Smart Agriculture Program 2015 - 2025 80 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Develop and implement an inter- ministerial communications strategy with respect to inter-ministerial coordination on matters relating to climate smart agriculture. service Lumpsum 1 1 0 0 0 0 0 0 0 0 40,000 40,000 40,000 0 0 0 0 0 0 0 0 80,000 Introduce a biannual joint planning and review session between inter-ministerial team and the country government officials responsible for agriculture. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 150,000 Train national, regional and local government staff in cross-sectoral planning and implementation. service Lumpsum 1 1 1 1 1 1 1 1 1 1 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 60,000 300,000 Build policy review and analytical capacity at the national and local levels. service Lumpsum 1 1 1 0 0 0 0 0 0 0 50,000 50,000 50,000 50,000 0 0 0 0 0 0 0 150,000 Strengthen the planning, implementation, monitoring and evaluation at the national and local levels. service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 200,000 Establish a framework for disseminating CSA programmatic planning and implementation as well as annual reports and studies and receiving feedback at national and local levels. service Lumpsum 1 1 1 0 0 0 0 0 0 0 25,000 25,000 25,000 25,000 0 0 0 0 0 0 0 75,000 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 Total 6: Improved Institutional Coordination Expenditure Account Unit of measure Unit Cost (in US$) BASE COSTS IN US$ 4.6.1 Improve Inter-Ministerial and Local Government Coordination Component Activities Quantities Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 81 Engage private sector to identify opportunities for increased investments in CSA. service Lumpsum 1 1 1 1 0 0 0 0 0 0 25,000 25,000 25,000 25,000 25,000 0 0 0 0 0 0 100,000 Organize regular consultative meetings with private sector and CSOs on the planning and implementation of the CSA Program. service Lumpsum 1 1 1 1 1 1 1 1 1 1 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 30,000 150,000 Identify appropriate incentives to catalyze private sector and CSO investments in CSA activities. service Lumpsum 1 1 1 0 0 0 0 0 0 0 30,000 30,000 30,000 30,000 0 0 0 0 0 0 0 90,000 Publicize the Country CSA Program to private sector and CSOs with a view to identifying areas for their participation. service Lumpsum 1 1 0 0 0 0 0 0 0 0 33,000 33,000 33,000 0 0 0 0 0 0 0 0 66,000 Establish communication channels for consultations between private sector and CSOs in the programmatic planning and implementation of CSA activities at the national and local levels. service Lumpsum 1 1 0 0 0 0 0 0 0 0 45,000 45,000 45,000 0 0 0 0 0 0 0 0 90,000 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 Harmonize GoT and development partners’ investments in climate smart agriculture through a common Country (National) CSA Program. service Lumpsum 1 1 1 1 1 0 0 0 0 0 36,000 36,000 36,000 36,000 36,000 36,000 0 0 0 0 0 180,000 Strengthen collaboration between GoT and the Development Partners’ Agriculture Coordination Group (with a standing agenda item programmatic planning and implementation of CSA Program). service Lumpsum 1 1 1 1 1 1 1 1 1 1 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 200,000 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 484,000 484,000 366,000 261,000 236,000 200,000 200,000 200,000 200,000 200,000 1,831,000 Sub Total 6.3 Programmatic Coordination with Development Partners strengthened TOTAL RESULT AREA 6 : IMPROVED INSTITUTIONAL COORDINATION 4.6.2 Partnerships with private sector and civil society organizations Sub Total Tanzania Climate Smart Agriculture Program 2015 - 2025 82 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total A: Investment 2,250,000 1,110,000 1,610,000 930,000 400,000 250,000 250,000 250,000 0 0 5,300,000 B: Components 1.1 Improved productivity and nutrition 650,000 680,000 680,000 530,000 490,000 450,000 395,000 395,000 395,000 395,000 5,060,000 1.2 Irrigation and water management 295,000 295,000 260,000 200,000 200,000 170,000 170,000 170,000 170,000 155,000 2,085,000 1.3 Improved Food Storage and Distribution 222,000 222,000 222,000 222,000 222,000 157,000 45,000 45,000 45,000 45,000 1,447,000 1.4 Increased Growth of Incomes 540,000 540,000 540,000 495,000 460,000 285,000 240,000 240,000 240,000 240,000 3,820,000 2.1 Improve soil health and restore degraded lands 270,000 270,000 220,000 165,000 165,000 135,000 135,000 135,000 135,000 135,000 1,765,000 2.2 Conservation of Natural Resources and Catchments 186,000 186,000 186,000 149,000 164,000 134,000 134,000 134,000 134,000 134,000 1,541,000 2.3 Insurance and Other Safety Nets 125,000 125,000 131,000 51,000 51,000 45,000 45,000 45,000 45,000 45,000 708,000 2.4 Early Warning System and Emergency Preparedness 188,000 188,000 108,000 58,000 58,000 48,000 48,000 48,000 48,000 48,000 840,000 2.5 Synergies in adaptation and mitigation enhanced 60,000 60,000 60,000 40,000 40,000 40,000 40,000 40,000 40,000 40,000 460,000 3.1 Development of new agricultural products 100,000 100,000 100,000 60,000 60,000 18,000 18,000 18,000 18,000 18,000 510,000 3.2 Increased competitiveness and enhanced integration into domestic, regional and international markets 145,000 145,000 84,000 56,000 56,000 56,000 56,000 56,000 56,000 56,000 766,000 4.1 Agricultural research funding and Uptake of Agricultural Technologies and Innovations along the Value Chain 304,000 304,000 304,000 269,000 269,000 215,000 100,000 100,000 100,000 100,000 2,065,000 4.2 Research Extension Linkage strengthened and made functional by 2018 65,000 65,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 35,000 410,000 5.1 CSA knowledge generation and dissemination 138,000 173,000 133,000 133,000 98,000 98,000 98,000 98,000 98,000 98,000 1,165,000 5.2 Enhance extension, climate information services and agro- weather advisories 325,000 325,000 325,000 325,000 280,000 185,000 185,000 145,000 145,000 145,000 2,385,000 6.1 Improve Inter-Ministerial and Local Government Coordination 245,000 245,000 205,000 130,000 130,000 130,000 130,000 130,000 130,000 130,000 955,000 6.2 Partnerships with private sector and civil society organizations 163,000 163,000 85,000 55,000 30,000 30,000 30,000 30,000 30,000 30,000 496,000 6.3 Programmatic Coordination with Development Partners strengthened 76,000 76,000 76,000 76,000 76,000 40,000 40,000 40,000 40,000 40,000 380,000 GRAND TOTAL 6,347,000 5,272,000 5,364,000 3,979,000 3,284,000 2,521,000 2,194,000 2,154,000 1,904,000 1,889,000 32,158,000 BASE COSTS IN US$ Summary Cost by Component | false |
# Extracted Content THE UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL JULY, 2017 CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | iii TABLE OF CONTENTS TABLE OF CONTENTS iii ACKNOWLEDGEMENT vi LIST OF ABBREVIATION AND SYMBOLS vii INTRODUCTION viii 1. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1 1.1 DEFINITION OF TERMS 1 1.2 THE CONCEPT OF CLIMATE CHANGE 1 1.3 THE IMPACTS OF CLIMATE CHANGE ON AGRICULTURE 2 1.4 THE IMPACTS OF AGRICULTURE ON CLIMATE CHANGE 3 1.5 CLIMATE CHANGE RISKS AND VULNERABILITIES IN AGRICULTURE 3 1.6 ADAPTATION AND MITIGATION OF CLIMATE CHANGE 4 1.6.1 Adaptation Options 4 1.6.2 Mitigation Actions 5 2 CLIMATE-SMART AGRICULTURE 6 2.1 INTRODUCTION 6 2.2 THE THREE PILLARS OF CSA 6 2.2.1 Productivity 6 2.2.2 Adaptation 6 2.2.3 Mitigation 7 2.3 CSA PRACTICES AND TECHNOLOGIES 7 2.3.1 Key characteristics of CSA 7 2.4 CROP SUB SECTOR PRACTICES AND TECHNOLOGIES 8 2.4.1 Rain Water Harvesting and Storage 8 2.4.2 Irrigation Practices and Technologies 9 2.4.3 Soil and Water Conservation Practices and Technologies 11 2.4.4 Agro forestry Practices and Technologies 13 2.4.5 Conservation Agriculture (CA) 15 2.4.6 Common CA practices and technologies 16 2.4.7 Soil Fertility Management Practices and Technologies 18 TABLE OF CONTENTS iv | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4.8 Crop Management Practices and Technologies 19 2.5 LIVESTOCK SUBSECTOR PRACTICES AND TECHNOLOGIES 21 2.5.1 Improved Livestock Breeds 21 2.5.2 Improved Feeds 21 2.5.3 Livestock Improved Feedings 21 2.5.4 Pasture and Grazing Land Management 22 2.5.5 Improved Grazing Land Management 23 2.5.6 Manure Management 24 2.6 FISHING AND AQUACULTURE ACTIVITIES 25 2.6.1 Pond Aquaculture/Fish Ponds 25 2.6.2 Integrated Aquaculture and Cage Culture 26 2.6.3 Sustainable Fishing 26 2.6.4 Seaweed Farming 26 2.7 OTHER CSA PRACTICES AND TECHNOLOGIES 27 2.7.1 Bee-keeping 27 2.8 UPSCALING CSA PRACTICES AND TECHNOLOGIES 28 2.8.1 The challenges in upscaling CSA 28 3: CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 29 3.1 INTRODUCTION 29 3.2 IDENTIFICATION OF STAKEHOLDERS 29 3.3 ROLES OF DIFFERENT STAKEHOLDERS ON IMPLEMENTATION AND UPSCALING OF CSA 29 3.3.1 Government 29 3.3.2 NGOs 30 3.3.3 Research partners 31 3.3.4 Private Sector 31 3.3.5 Farmers 31 3.3.6 Media 32 3.3.7 Development Partners/Inter-governmental Institutions 32 3.3.8 Religious institutions and communities 32 3.4 STAKEHOLDERS ENGAGEMENT MECHANISMS 32 3.5 APPROACHES FOR CSA INTEGRATION 32 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 34 4.1 INTRODUCTION 34 4.2 AWARENESS CREATION AND SENSITIZATION ON CSA 34 4.2.1 Meaning of awareness 34 4.2.2 Meaning of sensitization 34 4.2.3 How to create awareness 34 TABLE OF CONTENTS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | v 4.2.4 Target for Awareness Creation 35 4.3 CSA RELATED ACTIVITIES AND THEIR JUSTIFICATION 35 4.3.1 CSA Related Activities 36 4.3.2 Justification for CSA activities 36 4.4 PLANNING CSA ACTIVITIES WITH GENDER CONSIDERATION 37 4.4.1 Mainstreaming Gender into CSA Planning Process 37 4.4.2 Gender Analysis 37 4.5 BUDGETING FOR CSA RELATED ACTIVITIES 37 4.5.1 Gender responsive budgeting 38 4.5.2 Potential Costs of Maladaptation 38 4.5.3 Source of Finance for CSA 38 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS 41 5.1 INTRODUCTION 41 5.2 BASELINE INDICATORS FOR CSA RELATED 41 5.3 PERFORMANCE INDICATORS 41 5.4 MONITORING TOOLS AND RECORD KEEPING 42 5.5 CREATION OF EVIDENCE FOR CSA INTERVENTIONS 42 CONCLUSION 43 REFERENCES 44 TABLE OF CONTENTS vi | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL ACKNOWLEDGEMENT The preparation of the Climate-Smart Agriculture (CSA) Training of Trainers (ToT) Manual involved a number of individuals who worked to ensure that the document captures essential details. In a very special way, I would like to thank all the Technical Team Members from the Ministry of Agriculture Livestock and Fisheries who actively participated in the preparation of this Training of Trainers Manual especially from Department of Crop Development (DCD), Department of Training (DT), Livestock Training Agency (LIT A) and Environment Management Unit (EMU). I acknowledge and appreciate the valued contributions from World Vision, Sokoine University of Agriculture (SUA) and VUNA Climate Smart Agriculture programme for their great efforts in the development of the CSA Training of Trainers Manual. Finally, I do acknowledge and appreciate the technical and financial support provided by the Food and Agriculture Organization of the United Nations (FAO). We appreciate and value their cooperation and support. Shakwaanande Natai Head - Environment Management Unit Ministry of Agriculture Livestock and Fisheries AKNOWLEDGEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | vii LIST OF ABBREVIATION AND SYMBOLS ASDP Agriculture Sector Development Programme BRN Big Results Now CAADP Comprehensive African Agriculture Development Programme CH4 Methane CO2 Carbon dioxide CSA Climate-Smart Agriculture CSO Civil Society Organization ERPP Expanding Rice Production Project FAO Food and Agriculture Organizations of United Nations GHGs Green House gases IPCC Intergovernmental Panel on Climate Change M & E Monitoring and Evaluation N2O Nitrogen oxide NAMA National Appropriate Mitigation Actions NAPs National Adaptation Plans NGOs Non-Government Organizations RWH Rain Water Harvesting SUA Sokoine University of Agriculture SRI System of Rice Intensification URT United Republic of Tanzania LIST OF ABBREVIATION AND SYMBOLS viii | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL INTRODUCTION Climate-smart agriculture is “Agriculture that sustainably increases productivity, resilience (adaptation), reduces or removes Greenhouse Gases (GHGs) (mitigation) where possible, and enhances achievement of national food security and development goals” (FAO, 2010). However, in the Tanzanian context, the adapted definition of Climate- Smart Agriculture is “agriculture that sustainably increases productivity and income, increases the ability to adapt and build resilience to Climate Change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” (National Task Force Planning Workshop Report, 2016). CSA aims to achieve food security and broader development goals under a changing climate and increasing food availability using different practices and technologies. CSA practices and technologies on crop, livestock and fisheries aims at addressing tradeoffs and synergies between the three pillars: productivity, adaptation, and mitigation. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies also embrace priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. In understanding the importance of CSA in crops, livestock and fisheries production; practices and technologies were identified and mapped according to Agro-Climatic Zones of Tanzania. These Practices and technologies may serve as tool for deciding options within which the three pillars of CSA can be achieved. It is because of the importance of CSA in the Tanzanian context that this Training of Trainers (ToT) Manual has been developed, in order to guide agricultural stakeholders on how to accelerate the uptake of CSA practices and technologies within the agricultural sector. This manual is divided into five chapters where by chapter 1 aims at helping users to understand some of the potential impacts of climate change and possible solutions for addressing climate related risks with regard to agriculture. It also provides an understanding of how changes in climate can affect agriculture and subsequently identifies best practices that will help farmers to adapt in their respective agro- climatic zones. Chapter 2 introduces in detail the concept of CSA practices and technologies in crop, livestock and fisheries production. Chapter 3 provides guidance on identification, roles and engagement mechanisms of different stakeholders on implementation of CSA related activities. Chapter 4 helps elaborate on issues related to mainstreaming of CSA into agricultural plans, programmes and budgets. Lastly, chapter 5 give guidance on how to carry out monitoring and evaluation of CSA related activities and interventions. INTRODUCTION CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 1 CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1.1 DEFINITION OF TERMS Climate change and climate variability Climate change is defined as the long-term continuous change to average weather conditions. Specifically, it is the rise in average surface temperatures on earth. The way climate fluctuates yearly above or below a long-term average value is climate variability Risk Risk can be defined as a probability or threat of damage, injury, liability, loss, or any other negative occurrence that is caused by external or internal vulnerabilities, and that may be avoided through pre-emptive action. Vulnerability Vulnerability is the state of being open to injury, or susceptibility to harm and lack of capacity to cope and adapt Adaptation Adaptation is defined as an adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities. Mitigation Mitigation refers to effort that seek to prevent or slow down the increase of atmospheric Green House Gases (GHGs) Concentration by limiting current and future emission and enhancing their potential sinks . 1.2 THE CONCEPT OF CLIMATE CHANGE Climate refers to the average weather conditions in a certain place over many years. Climate encompasses temperature, humidity, atmospheric pressure, wind, rainfall, atmospheric particle count and other meteorological elements in a given region. The average climate around the world is called global climate. Rising global temperatures lead to other changes around the world, such as melting glaciers, submerging of islands, rising of sea levels and the loss of wildlife habitats. Many places have seen changes in rainfall, resulting in more floods, droughts, or intense rain, as well as more frequent and severe heat waves. That’s because the Earth’s air, water, and land are all related to one another and to the climate. This means a change in one place can lead to other changes somewhere else. For example, when air temperatures rise, the oceans absorb more heat from the atmosphere and become warmer. Warmer oceans, in turn, can cause stronger storms. As these and other changes become more pronounced in the coming decades, they will likely present challenges to our society and our environment. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 1| 2 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Climate change is largely caused by human activities, and it presents a serious threat to nature and people now, and in the future. It affects the plants and animal populations and distributions of species, the composition of ecological communities, and nature’s provision of goods and services – such as food, fuel and clean water. Climate change also compounds other major threats to biodiversity, such as invasive alien species, habitat fragmentation and over exploitation. The principal drivers of climate change are variations in atmospheric concentrations of greenhouse gasses (GHG, including water vapour, carbon dioxide, methane, nitrous oxide, and ozone) and aerosols, as well as changes in land cover and solar radiation, all of which alter the energy balance of the Earth’s climate. Terrestrial and marine ecosystems currently sequester carbon, acting as ‘sinks’. Changes to atmospheric carbon dioxide (CO2) concentrations could shift the global carbon cycle towards annual net emissions, turning these ecosystems into ‘sources’. Concentrations of other greenhouse gasses, including methane (CH4) and Nitrogen Oxide (N2O), which have similar effects, have also increased markedly as a result of human activities. Without ambitious mitigation efforts, global temperature rise this century could exceed four (4) degrees Celsius above pre-industrial levels, with catastrophic impacts. 1.3 THE IMPACTS OF CLIMATE CHANGE ON AGRICULTURE There are several impacts associated with Climate change in Agriculture: • Lowering crop production This is due to either erratic rains prolonged drought, changing temperatures, and nutrient constraints due to erosion or leaching. This may counteract the potential increases in yield. For example, if temperature exceeds a crop’s optimal level, if sufficient water and nutrients are not available, yield may be adversely affected. Extreme events, especially flooding and drought, can harm crops and reduce yields. • Lowering livestock production Climate change is expected to further shrink rangelands which are important for livestock production. Climate change and variability are expected to lead to pasture and water shortages. • Persistent Poverty The majority of rural poor farmers depend on seasonal rainfall that could be unreliable for agricultural production causing them to get low yields that perpetuate the cycle of poverty. • The prevalence of crop and livestock pests and diseases This situation has been exacerbated by a conducive environment influenced by the change in climate. Many pests and diseases thrive under warmer temperatures, wetter climates, and increased CO2 levels. Farmers will spend more money to fight pests and diseases. The spatial and temporal distribution of pests and diseases is likely to increase with climate change. This could cause new problems for farmers’ crops previously unexposed to these species. • Water stress affecting agriculture This is due to changes in temperature and rainfall patterns. Although increased irrigation might be possible in some places, in other places water supplies may also be reduced, leaving less water available for irrigation. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 3 • Reduced nutritional value of most food crops Some laboratory experiments suggest that elevated CO2 levels can increase plant growth. Though rising CO2 can stimulate plant growth, it also reduces the nutritional value of most food crops. Rising levels of atmospheric carbon dioxide reduce the concentrations of protein and essential minerals in most plant species, including wheat, soybeans, and rice. This direct effect of rising CO2 on the nutritional value of crops represents a potential threat to human health. Human health is also threatened by increased pesticide use due to increased pest pressures and reductions in the efficacy of pesticides. 1.4 THE IMPACTS OF AGRICULTURE ON CLIMATE CHANGE • Industrial agriculture is a huge carbon contributing factor. It has a hugely negative impact on global warming. Figures from the Intergovernmental Panel on Climate Change (IPCC) say that agricultural land use contributes 12 percent of global greenhouse gas emissions. Supporting industrial agriculture perpetuates these disturbing practices. • Greenhouse gas emissions from fertilizer and pesticide use; manufacture and use of pesticides and fertilizers, fuel and oil for tractors, equipment, trucking and shipping, electricity for lighting, cooling, and heating, and emissions of carbon dioxide, methane, nitrous oxide and other greenhouse gases significantly bumps the impact to the climate. • Land use changes significantly contribute to climate change. Large-scale changes such as deforestation contribute to increased carbon dioxide concentrations in the atmosphere. Soil erosion by water, wind and tillage affects both agriculture and the natural environment. Soil loss, and its associated impacts, is one of today’s most important environmental problems. 1.5 CLIMATE CHANGE RISKS AND VULNERABILITIES IN AGRICULTURE The Agriculture sector faces many risks that could pose potentially serious consequences for all stakeholders. Volatility in the prices of agricultural commodities and “inputs” such as fertilizer, pesticides and equipment, as well as impact from pests, diseases, droughts and floods which have become more frequent and severe due to climate change—can negatively affect farmers and others involved in the agriculture industry. They can also put a severe fiscal strain on government. Malnutrition, gender inequality and bad governance also curb productivity and raise vulnerability over the long term. The extent of vulnerability can be determined by undertaking assessments. Agricultural risk and vulnerability assessment helps identify appropriate risk management strategies, which often include: • Mitigation such as Improved water management; Use of drought and flood tolerant seeds, Early warning systems and other activities that reduce the likelihood of adverse events and the severity of losses • Risk transfer: Insurance and other arrangements • Coping: Savings and targeted safety net programs, risk financing These are accompanied by appropriate agricultural investments, policy support, and technical assistance activities to make the agriculture sector more resilient. CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE 4 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 1.6 ADAPTATION AND MITIGATION OF CLIMATE CHANGE Climate change and its associated impacts on agriculture sectors is a major concern in Tanzania. It has far-reaching consequences for agriculture that keeps disproportionately affect the poor. Greater risks of crop failures and livestock deaths are already imposing economic losses and undermining food security and they are likely to get far more severe as global warming continues. More than 80% of the population in Tanzania depends on climate sensitive rain fed agriculture as source of livelihood. Reducing vulnerability of agriculture to climate change will significantly contribute to socio-economic development and ensure food security. Adaptation measures are needed urgently to reduce the adverse impacts of climate change, facilitated by concerted international action and strategic country planning. The National Climate Change Strategy (URT, 2012) sets out strategic interventions for climate change adaptation measures and greenhouse gas emissions reductions. The goal is to enable Tanzania to effectively adapt to and participate in global efforts to mitigate climate change with a view to achieving sustainable economic growth in the context of the Tanzania’s national development blueprint, Vision 2025; Five Years National Development Plan; and national cross-sectoral policies in line with established international policy frameworks. The National Climate Change Strategy has outlined objectives for all sectors and proposed strategic interventions in those sectors and themes that are highly vulnerable to climate change such as agriculture. The Agriculture Climate Resilience Plan (URT, 2014) has been developed to implement strategic adaptation and mitigation actions in the crops sub-sector. The Climate-smart Agriculture Programme for Tanzania (2015 – 2025) aims to build resilience of agricultural farming systems for enhanced food and nutrition security through six programmatic result areas namely: Improved Productivity and incomes; Building resilience and associated mitigation co-benefits; Value Chain Integration; Research for Development and Innovations; Improving and Sustaining Agricultural Advisory Services; and Improved Institutional Coordination. The Climate change agriculture (CSA) programme enhances the implementation of the Comprehensive African Agriculture Development Programme (CAADP) and responds to the 23rd Ordinary African Union Assembly Decisions and Declaration (Malabo Declaration), This CSA guideline has therefore been developed to support the implementation of Tanzania CSA programme. 1.6.1 Adaptation Options Potential adaptation options that can help to integrate resilience in agricultural policy decisions, influence planning processes, and implement investments on the ground include: • Improving agricultural land and water use and management through proper land use planning and management • Accelerating uptake of climate-smart agriculture • Strengthening knowledge on Early warning and community preparedness and establish early information systems • The potential adaptation in the livestock sector include promoting climate change resilient traditional and modern knowledge on sustainable pasture and range management systems; enhancing development of livestock infrastructure and services; promoting development of livestock insurance strategies; strengthening weather forecast information sharing for pastoralists; promoting livelihood diversification of livestock keepers; and promoting improved traditional livestock keeping systems • In fisheries promote aquaculture and enhance protection and conservation of aquatic ecosystems. • In forests and ecosystems; application of best practices in soil and water conservation; promotion of fast growing tree species; farmer and pastoralist managed natural regenerations and use of alternative sources of energy CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 5 CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE • As a major source of greenhouse gas (GHG) emissions, agriculture also has much untapped potential to reduce emissions through reduced deforestation and changes in land use and agricultural practices • Better climate information is another potentially cost-effective way of adapting to climate change. • The greater uncertainty from climate change can be best addressed through contingency planning across sectors and identify immediate priorities to improve preparedness for climate change. • Mainstreaming climate change in the broader economic agenda, rather than taking a narrow agricultural perspective • Devise new mechanisms to provide climate information and forecasting, research and development of diverse crops adapted to new weather patterns, and techniques to reduce land degradation. • Diversify livestock types and varieties to address the environmental variations and economic risks associated with climate change. • Change the intensification of production to address the environmental variations and economic risks associated with climate change. • Change timing of farm operations to address the changing duration of growing seasons and associated changes in temperature and moisture. • Diversify source of household income in order to address the risk of climate-related income loss. 1.6.2 Mitigation Actions • Agriculture is also a major contributor of lowering carbon sequestration (storage) through land use change (the loss of soil organic matter in cropland and pastures, and forest conversion to agriculture), although quantitative estimates are uncertain. Emissions of carbon dioxide from changes in agricultural land use can be reduced by slowing deforestation. • Promote carbon trading to reduce emission of Green House Gases this will motivate communities living adjacent to forest reserves to conserve trees and other biota. Carbon financing can support mitigation; the emerging market for trading carbon emissions offers new possibilities for agriculture to benefit from land uses that sequester carbon. • Changes in agricultural land management (conservation tillage, agroforestry, and rehabilitation of degraded crop and pasture land, promoting afforestation and reforestation), overall improvement of nutrition and genetics of ruminant livestock • Storage and capture technologies for manure, and conversions of emissions into biogas (production of valuable by-products, such as bio energy) is a better management of natural resources • Development of low-emission crop varieties and livestock breeds. Therefore, it is important to put in place strategies aiming at adapting to climate change and reducing its impacts through research, awareness raising, advocacy, mobilization and empowerment of most vulnerable communities. Adaptive strategies have to be implemented from household, community, and national levels in order to enhance already existing adaptation strategies while designing new ones. One of these strategies is to promote Climate- Smart Agriculture. 6 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.1 INTRODUCTION Climate-Smart Agriculture (CSA) addresses climate change related risks. Contrary to conventional agricultural development, systematically integrates climate change into the planning and development of sustainable agricultural systems (Lipper et al., 2014). Also, CSA integrates multiple goals and manages trade-offs. Frequently, when it comes time to implement CSA, trade-offs must be made. This requires identification of synergies and weighs the costs and benefits of different options based on intended objectives (CSA guide, 2016). By definition (FAO, 2010) CSA defined as “agriculture that sustainably increases productivity, enhances resilience (adaptation), reduces/removes GHGs (mitigation) where possible, and enhances achievement of national food security and development goals”. In this definition, the principal goal of CSA is identified as food security and development; while productivity, adaptation, and mitigation are identified as the three interlinked pillars necessary for achieving this goal. However, in Tanzanian context the adopted definition of Climate-Smart Agriculture is “agriculture that sustainably increases productivity and income (profitability), increases the ability to adapt and build resilience to Climate Change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” as defined at the National Climate-Smart Agriculture Task Force Planning Workshop Report of 2016. 2.2 THE THREE PILLARS OF CSA 2.2.1 Productivity CSA aims to sustainably increase agricultural productivity and incomes from crops, livestock and fish, without having a negative impact on the environment. This, in turn, will raise food and nutritional security. A key concept related to raising productivity is sustainable intensification. 2.2.2 Adaptation CSA aims to reduce the exposure of farmers to short-term risks, while also strengthening their resilience by building their capacity to adapt and prosper in the face of shocks and longer-term stresses. Attention is given to protect the ecosystem services, whereby these services are essential for farmers on maintaining productivity and enhances our ability to adapt climate changes. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE 2| CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 7 CLIMATE-SMART AGRICULTURE 2.2.3 Mitigation Wherever and whenever possible, CSA should help to reduce and/or remove greenhouse gas (GHG) emissions. This implies that we reduce emissions for each calorie or kilo of food, fibre and fuel that we produce and that we avoid deforestation from agriculture, we manage soils, crops, livestock and vegetation in ways that maximizes their potential to acts as carbon sinks and absorb CO2 from the atmosphere. 2.3 CSA PRACTICES AND TECHNOLOGIES In agriculture practices refer to management activities at the farm and landscape level while technologies are highly productive, high quality, efficient and resource-saving (water, energy, labour) techniques and expertise for agricultural production. It also refers to techniques appropriate for the protection and improvement of the environment In view of the observed climate change impacts, different strategies are being employed to adapt to the changing climate. These strategies vary from place to place and includes early land preparation, early planting, dry planting, planting of drought tolerant crops, planting of early maturing crops, mulching, irrigation, tree planting, and the use of indigenous knowledge. Other strategies include re-planting, intercropping, crop rotation, minimum tillage, use of water harvesting technologies, digging irrigation trenches and terracing. Livestock farmers also adapt by growing grasses and perennial fodders, using farm by-products and doing additional activities such as crop farming. Fish farmers uses practices and technologies such as Pond Aquaculture/Fish Ponds, Integrated fish farming, Cage culture, Seaweed Farming and Mariculture. 2.3.1 Key characteristics of CSA • CSA maintains ecosystems services: Ecosystems provide essential services, including clean air, water, food and materials. • CSA has multiple entry points at different levels: CSA has multiple entry points, ranging from the development of technologies and practices to the elaboration of climate change models and scenarios, information technologies, insurance schemes, value chains and strengthening of institutional and political enabling environments. As such, it goes beyond single technologies at the farm level and includes the integration of multiple interventions at the food system, landscape, and value chain or policy level. • CSA is context specific: What is climate-smart in one-place may not be climate-smart in another, and no interventions are climate-smart everywhere or every time. Interventions must take into account how different elements interact at the landscape level, within or among ecosystems and as a part of different institutional arrangements and political realities. The fact that CSA often strives to reach multiple objectives at the system level makes it particularly difficult to transfer experiences from one context to another. • CSA engages women and marginalized groups: To achieve food security goals and enhance resilience, CSA approaches must involve the poorest and most vulnerable groups. These groups often live on marginal lands which are most vulnerable to climate events like drought and floods. Gender is another central aspect of CSA. Women typically have less access and legal right to the land which they farm, or to other productive and economic resources which could help build their adaptive capacity to cope with events like droughts and floods. • Stakeholder Involvement: CSA strives to involve stakeholders at local, regional and national stakeholders in decision-making. Only by doing so, it is possible to identify the most appropriate interventions, form of partnerships and alliances needed to enable sustainable development. 8 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4 CROP SUB SECTOR PRACTICES AND TECHNOLOGIES 2.4.1 Rain Water Harvesting and Storage Rain water harvesting (RWH) involves collecting, storing and conserving local surface runoff for agriculture (Boers and Ben-Asher, 1982). In crop production systems, RWH is composed of a runoff producing area normally called the Catchment Area (CA) and a runoff utilization area normally called Cropped Basin (CB) as explained by Hatibu and Mahoo (1999). The Rain water Harvesting and Storage Practices are highly recommended in semi-arid regions where there is limited water availability and storage capacities such as Dodoma, Singida and parts of Manyara and Shinyanga. Water shortage affects more rural women since it is their cultural role to provide water for the family. They are more concerned with rainwater harvesting as compared to men. Therefore, small-scale rainwater harvesting can ensure a significant and steady supply of water for farming even in times of drought, and permit year-round vegetable cultivation with significant nutritional impacts on families. 2.4.1.1 Types of rain water harvesting practices and technologies • In-situ rain water harvesting Is a method of increasing the amount of water stored in the soil profile by trapping or holding the rain where it falls such as bunded basin (Majaluba). In essence, in situ rainwater harvesting technologies are soil management strategies that aim at maximum infiltration and minimize surface runoff to achieve better yields where soil moisture is a constraint. This technology often serves primarily to recharge soil water for crop and other vegetation growth in the landscape. CLIMATE-SMART AGRICULTURE Farmers learning how to prepare bunds (Majaluba) Transplanted rice in bunds – Mbarali, Mbeya • Chololo pits This is harvesting technology initiated by a farmer in Chololo village, Dodoma. They are made during land preparation (before rains) and the soil is heaped below the pit. Crop seeds (millet seeds) are planted in the pits and part of the soil (sometimes mixed with manure) is returned to cover the seeds. The pit holds and conserves runoff water during the growing season. Contour bunds are constructed on the upper side of the farm to control excessive runoff’. CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 9 CLIMATE-SMART AGRICULTURE Chololo pits consist of pits of about 0.2 – 0.25m deep and 0.2-0.25m diameter dug in a line across the slope spaced at 0.5m within line and about 1.0m between lines. The adjacent line of pits is set such that the pits are dug in a middle position to the above ones so as to tap runoff that has drained through the first line of pits. 2.4.2 Irrigation Practices and Technologies • Irrigation canal lining Canal lining is a process of reducing seepage loss of irrigation water by adding an impermeable layer to the edges of the trench. Seepage can result in losses of 30 to 50 percent of irrigation water from canals, so adding lining can make irrigation systems more efficient. Canal linings are also used to prevent weed growth, which can spread throughout an irrigation system and reduce water flow. Lining a canal can also prevent water logging around low lying areas of the canal. The most commonly used types of lining include: concrete, concrete blocks, bricks or stone masonry, sand cement, plastic; and compacted clay. Rain water harvesting at Mbigiri Village in Kilolo District, Iringa • Dam Construction of dam is a system that involves the collection of runoff from large areas, which are at an appreciable distance from where it is being used. This may involve traditional water harvesting technologies e.g. Ndiva system in Pare Mountains, or Kitivo in Usambara Mountains. 10 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Lined canals at Lower Moshi irrigation scheme • Drip/trickle irrigation Drip irrigation is a technology of using water efficiently, reducing evaporation and enhancing infiltration and moisture retention in the soil profile through soil organic matter (SOM) management combined with the use of more drought-resilient species Drip irrigation, also known as trickle irrigation, is an irrigation method that saves water and fertilizer by allowing water to drip slowly to the plant roots, either onto the soil surface or directly onto the root zone, through a network of valves, pipes, tubing, and emitters. It is easy to design, install and much less water is wasted during irrigation. The farmers can use low cost drip irrigation system, which will enable them to produce high value crops especially vegetables. • System of Rice Intensification (SRI) SRI is a technology of increasing productivity of irrigated rice by changing the management of plants, soil, water and nutrients. It is a water saving technology for lowland (paddy) rice farmers, it involves controlled irrigation, (rice fields are alternately flooded and dried and fields monitored via simple, perforated tube). SRI Drip irrigation system CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 11 technology allows weed control by using hand tools such as push-weeders. It improves farmers’ livelihoods; decreases costs of (water-related) inputs and increases resilience to both price shocks (e.g. increased energy costs) and weather variability. Paddy rice cultivation is a primary source of non-CO2 GHG emissions from the agriculture sector Therefore, SRI is widely accepted as climate-smart technology for its potential to significantly reduce methane emissions and increasing yields. SRI is now well used by farmers in Mcholi 1 ward in Ruvuma River Basin and Dakawa in Wami River Basin. Farmers at KATC practicing on use of push-weeder ERPP SRI Demonstration plot at Kigugu, Morogoro 2.4.3 Soil and Water Conservation Practices and Technologies Soil and water conservation practices and technologies reduce run-off and eventually soil erosion, conserve the soil productivity and therefore help to increase yields, especially on sloping farmlands. There are different types of soil and water conservation practices, which can be used under specific conditions such as low rainfall, high rainfall, steep slopes, gentle slopes, deep soil, shallow soil etc. • Ridging Ridging is the farming practice of ploughing or placing stones across the slope following its contour line for the purpose of controlling soil erosion and enhancing water infiltration. This practice is mostly adopted in gentle slopes to control run-off and retain moisture and nutrients. Ridging creates a water break, which reduces the formation of rills and gullies during the times of heavy water runoff which is a major cause of soil erosion. The ridges should traverse the slope to capture the rainfall rather than running downhill, channelling water and soil away. The ridges can be tied (Tie-ridging) with small earth ties within the ridge/furrow to collect and store runoff in the soil to be used by crops planted on the ridges. CLIMATE-SMART AGRICULTURE 12 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Contour Ridges in Kibwaya village, Morogoro • Water Retaining/Harvesting Pits A series of pits are dug into the ground where runoff normally occurs to allow seepage, minimize soil erosion and nutrient loss to improve soil fertility. The soil from the pit is used to make banks around the pits where by four ridges are tied together. Furrows carry excess water from one pit to the next. Traditionally, this system is mainly practiced by the Matengo tribe of Mbinga District, living on the steep slopes of the Matengo highlands. The pits are locally called Matengo pits or Ngoro. The system is suitable for steep slopes of 20% - 50%, which are prone to erosion. Matengo (Ngoro)pits in Ruvuma CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 13 Terraces Terrace farming is a method of farming using “steps” that are built into the side of a mountain or hill. On each level, various crops are planted. When it rains, instead of washing away all of the nutrients in the soil, the nutrients are carried down to the next level. Terraced fields decrease both erosion and surface runoff, and may be used to support growing crops that require irrigation. Small terraces with the size of a ladder are dug on steep slopes for the purpose of breaking the slope and controlling soil erosion. They are used for growing mainly vegetable crops such as cabbage, onions, green pea and beans. • Fanya Juu terraces Fanya juu terraces are made by digging a trench along the contour and throwing the soil uphill to form an embankment. The embankments are stabilized with fodder grasses and in between cultivated portions. Over time, the Fanya Juu develops into bench terraces. FanyaJuu is a very versatile technology - ideally suited to smallholder farms, especially in sub-humid areas where the land is sloping and erosion a threat Fanya juu terraces are useful in semi-arid areas in harvesting and conserving water. The measure is suitable for soil too shallow for level bench terracing and moderate slopes below 20%. Fodder grasses may be planted on the bunds and fed to livestock. In the dry areas, water harvested from roads is directed into the trenches which allow production of bananas and fruits. However, they are not applicable on stony soils. • Fanya chini terraces Fanya chini terraces are made by digging a trench along the contour and the soil is put on the lower side of the contour trench. It is used to conserve soil and divert water. The embankment can be used to grow fodder. This is applicable on slopes of up to 20%. • Bench terraces Bench terraces are level or nearly level steps constructed or formed on the contour and separated by embankments known as risers. They are formed by excavation or developed from grass strips or Fanya Juu terraces. They are suitable on slopes up to 55%. • Stone terraces Stone terraces are useful in areas with steep slopes but high population density and scarce land. The terrace risers are made of stones collected from the land. Stone terraces are suitable where there is abundant availability of stones. 2.4.4 Agro forestry Practices and Technologies It is a dynamic, ecologically based, natural resource management system that, through integration of trees on farms and in the agricultural landscape, diversifies and sustains production for increased social, economic and environmental benefits. Agroforestry systems include both traditional and modern land-use systems where trees are managed together with crops and/or animal production systems in agricultural settings. Agroforestry play important roles in increasing the resilience to climate change impacts for small scale farmers and CLIMATE-SMART AGRICULTURE 14 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL in larger landscape approaches. Trees help fight climate change by storing carbon. Carbon, sequestered by trees intercropped with food and fodder crops and stored in above ground biomass and soil, contributes to reducing greenhouse gas concentrations in the atmosphere. Trees buffer against weather-related production losses, such as reducing soil erosion through e.g. hedgerow and contour planting - thus enhancing resilience against climate impacts. Trees bring nutrients from deeper soil layers, or in case of legume trees, through nitrogen fixation, and decomposition of leaf litter into fertilizer for crops. Trees on farms provide additional income and diversity of food sources through tree-based products. Agroforestry with Indigenous fruits trees can provide women with significant income. The combination of trees, crops and livestock mitigates environmental risk, creates a permanent soil cover against erosion and minimizes damage from flooding and acts as water storage, benefitting crops and pastures. Agroforestry serves to enrich farmers through the harvesting of diverse products at different times of the year. It also brings job opportunities from the processing of tree products, expanding the economic benefits to rural communities and national economies. Planting of heavy feeder trees (e.g. some of Eucalyptus spps) is discouraged in crop lands. 2.4.4.1 Common Agroforestry Practices • Tree in crop land This is the practice of growing crops in association with trees left during land preparation or planted for their economic, social or cultural value. Among the common values include production of fruits, fuel wood, timber, medicine, fodder and shade or soil fertility improvement. Some of the common species found on cropped lands include Leucaena spps. Faidherbia albida agroforestry in Mbarali (Source – ICRAF Tanzania) • Rotational woodlot The rotational woodlot is an agroforestry practice which involves alternating arable crops with improved tree fallow on the same piece of land over time. The practice is intended to simulate the effects of shifting cultivation systems, with tree species carefully selected for their fast growth rates, high wood yields, and/or soil enrichment capacity. The practice involves three phases namely; tree establishment phase (crop and young trees), fallow phase (woodlot) and the post-fallow phase (clearing for cultivation). CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 15 • Improved fallow This is a practice of improving a farm which after continuous cultivation is rested (fallowed) for one or two seasons to regain fertility by introducing fast growing, high fertility enriching plants normally herbaceous legumes, grasses and/or shrubs. Some of the species used to improve fallow land are Sesbania sesban (sesbania), fish poisoning plant (utupa), Chick Peas (Cajanus cajan/mbaazi), Marejea (Crotalaria ochroleuca) and herbaceous legumes like Lablab. • Fodder bank The practice involves growing of high quality fast-growing and high-yielding trees, shrubs, grass and herbaceous legumes in small homestead plots in order to provide low cost fodder supply to alleviate shortages of fodder and nutrition deficiencies to sustain livestock production. The animals are given supplements of protein-rich feedstuffs during the dry season when other good-quality fodder is scarce. The fodder may be cut, carried and fed to livestock in their enclosure (kraal). The kraal manure in turn is applied to crops thus enhancing nutrient cycle (soil resilience). The amount and quality of manure increase with good feeding of the animals. Some species used in fodder bank include; Leucaena leucocephala, Panicum maximum and Acacia spp. • Tree planting / afforestation It involves planting seedlings over an area of land where the forest has been harvested or damaged by fire or disease or insects. Trees contribute to climate change adaption by reducing wind speed, and decreasing damage to crops and degradation/erosion to the soil. They contribute to climate change mitigation by removing CO2 from the atmosphere. Trees provide shades to mitigate the impact of climate induced temperature rise. Reforestation provides other benefits by reducing land degradation and soil erosion, and improving water infiltration. Also forests provide multiple benefits for local communities such as wood and non-wood products, timber, fruits, fibre, medicines and honey, all of which can be important for the livelihood. 2.4.5 Conservation Agriculture (CA) Conservation Agriculture is a set of soil management practices that minimize the disruption of the soil structure, composition and natural biodiversity and has a potential to improve crop yields, while improving the long-term environmental and financial sustainability of farming. It encompasses farming practices which have three key characteristics: • First, minimal mechanical soil disturbance (i.e. no tillage and direct seeding); • Second, maintenance of a mulch of carbon-rich organic matter covering and feeding the soil (e.g. straw and/ or other crop residues including cover crops); and • Third, rotations or sequences and associations of crops including trees and legumes which are nitrogen-fixing. CA offers climate change adaptation and mitigation solutions while improving food security through sustainable production intensification and enhanced productivity of resource use. Management of soil fertility and organic matter, and improvement of the efficiency of nutrient inputs, enable more to be produced with proportionally less fertilizers. It also saves on energy use in farming and reduces emissions from the burning of crop residues. Moreover, it helps to sequester carbon in soil. CA contributes to adaptation to climate change by reducing crop vulnerability and protects crops from extreme temperatures. Hence, CA offers opportunities for climate change adaptation and mitigation solutions, while improving food security through sustainable production intensification and enhanced productivity. CLIMATE-SMART AGRICULTURE 16 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.4.6 Common CA practices and technologies • Cover cropping Cover cropping is a technology that aims to maintain or cover soil surface during and between cropping operations. It is well known by farmers and extension agents. It can be achieved by planting leafy legumes between the plants of the main crop, providing shade, suppressing weeds, reducing ground temperature and evapo-transpiration, and thereby retaining soil moisture. It has also been used for reducing effects of raindrop impact and aggregate disintegration from slaking. Ground cover also prevents raindrops from directly striking the soil surface and allows rainfall to slowly penetrate the soil surface. Ground cover helps to sequester carbon dioxide in the soils but also control soil erosion. • Mulching Mulching is a technology of applying a protective covering, usually of organic matter such as grass, leaves, straw, or peat, around plants or on the surface of the soil. Mulching helps to conserve moisture, improve the fertility and health of the soil and reduce weed growth. When applied correctly, mulching can dramatically improve soil productivity. Maintenance of a mulch layer provides a substrate for soil-inhabiting microorganisms which helps to improve and maintain water and nutrients in the soil. This also contributes to net increase of soil organic matter - derived from carbon dioxide captured by photosynthesis in plants, whose residues above and below the surface are subsequently transformed and sequestered by soil biota. • Crop Rotation Crop rotation is a practice of growing different crops in a field each year or season. The new crop planted during the succeeding season will be from a different family. The idea behind this is to change what soil nutrients the crop uses, and the insects it attracts. So, the pests never get used to one field because crops are constantly changed. In terms of soils, each crop needs different nutrients. Changing the crop every year prevents depletion of any one nutrient in the field. Crop rotation is also effective in suppressing weeds because of regular changes in the root zone composition and patterns of nutrient absorption. Rotations and crop associations that include legumes are capable of hosting nitrogen-fixing bacteria in their roots, which contributes to optimum plant growth without increased gas emissions induced by fertiliser’s production. Crop rotation over several seasons also minimises the outbreak of pests and diseases. • Intercropping Intercropping is a multiple cropping technology involving growing two or more crops in proximity in the same field. The farmers commonly use a cereal-legume intercrop, mixing of crops for example millet, sorghum or maize with cowpeas or groundnuts. Farmers acknowledge leguminous crops such as beans, cowpeas, lablab and pigeon peas are suitable for intercropping as they contribute nutrients to the soils by biological nitrogen fixation. In this case, intercropping reduces depletion of individual soil nutrients. It can also involve new crop varieties (e.g. drought resistant). CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 17 Maize-Pigeon pea intercropping in Babati, Manyara The most common goal of intercropping is to produce higher yields on a given piece of land by making use of resources that would otherwise not be utilized by a single crop. It provides a family with a balanced diet of staple grains, protein-rich beans, and green leaves for essential vitamins. It also reduces risk of total crop failure by having two crops instead of one. Also intercropping increase resilience to drought and reduced pest and diseases • Minimum / Zero Tillage Minimum Tillage means reducing tillage operations required to plant a crop that usually involves scratching or ripping along the row where the crop is to be planted and leaving the rest of the land untouched until weeding is required. Alternatively, farmers may just dig holes or pits where the seed will be sown (such as chololo pits in Dodoma and basins in Newala). It is a practice that minimizes run-off and increases infiltration rates. It actually ensures enough moisture is stored in the soil for plant growth. Avoidance of tillage minimises occurrence of net losses of carbon dioxide by microbial respiration and oxidation of the soil organic matter and builds soil structure and bio-pores through soil biota and roots. Zero tillage has many advantages among others including minimal soil disturbance; retention of crop residues; seeds planted directly into previous crop’s residue; and crop rotation. It reduces erosion; improves soil quality and structure, soil biota; reduces evaporation of water, helps retain nutrients. In addition, depending on rotation, no-till reduces greenhouse gas emissions of nitrous oxides. • Crop Residue Management Crop residues management is the practice where by crop residues are left in the field /farm after the crops have been harvested. These residues include sticks and stubble/stems, leaves and seed pots. Crop residues can also be used as animal feed outside the crop field. The protective soil cover of leaves stems and stalks from the previous crop protect the soil surface from heat, wind and rain, keeps the soil cooler and reduces moisture losses by evaporation. In drier conditions, it reduces crop water requirements, makes better use CLIMATE-SMART AGRICULTURE 18 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL of soil water and facilitates deeper rooting of crops. In extremely wet conditions, crop residues management facilitates rain water infiltration, reducing soil erosion and the risk of downstream flooding. 2.4.7 Soil Fertility Management Practices and Technologies A healthy soil is fundamental for sustained agricultural productivity and the maintenance of other vital soil- mediated ecosystem processes. To cope with climate change, specific management practices need to be adapted. Management practices that increase soil organic carbon (SOC) content from year to year through organic matter management will bring benefits. Soil Fertility Management Practices and Technologies include: • Manure Application Farm Yard Manure (FYM) - is an appropriate technology to enhance nutrient availability for ensuring high yields. FYM is also good for improving soil structure and control evaporation. Use of FYM increases crop– livestock integration such that crop residues from well managed crops are fed to livestock. The livestock manure is then returned to the fields at the start of the cropping season. A large proportion of the mitigation potential of agriculture (excluding bio-energy) arises from soil carbon sequestration, which has strong synergies with sustainable agriculture and generally reduces vulnerability to climate change. With regard to CO2 sequestration in soils, use of FYM can achieve high carbon and improve soil structure and quality, because the accumulated carbon is in the organic form of humus. This will improve climate adaptation by reducing the impacts of flooding, droughts, water shortages and desertification, thereby also improving food and water security. Compost manure - refers to a mixture of organic matter, from leaves and manure that has decayed or has been digested by organisms, and can be used to improve soil structure and provide nutrients. It helps dry soil to absorb and retain more water, compacted soils to regain their elasticity and poor soils to bring forth abundant farm produce; they provide plants with nutrients which they require to grow to their full potential. Harvesting crops removes carbon from the soil that would otherwise return to the soil when the plant dies and decomposes. Compost returns organic matter to the soil. The nitrogen in compost can increase soil productivity, which can lead to increased crop residues and an increased return of carbon to the soil. Composting increases the formation of stable carbon that remains bound in the soil for long periods of time. Applying organic matter to soils is one of the most effective ways to divert CO2 from the atmosphere and convert it into organic carbon in the soil. Compost use can supply at least some of the mineral nitrogen that would otherwise have to be provided through mineral fertilisers, as well as most, if not all, of the crop’s phosphorous, potassium and trace element requirements. Substituting the use of mineral fertiliser through compost use offers an opportunity of reducing GHG emissions caused by the manufacturing and transportation of fertilisers. Efficient Use of Fertilizer (Micro Dosing) - involves the application of small and affordable, quantities of fertiliser onto or close to the seed at planting time, or a few weeks after emergence. This can be done by filling a soda bottle cap with fertiliser and applying it directly to the root of the crop. The micro-dosing technique increases the efficiency of fertilizer use, and helps improve productivity. For efficient use of Fertilizer soil status need to be known through soil testing. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 19 Integrated Soil Fertility Management (ISFM) - aims to make available required soil nutrients by balancing different on-farm soil organic sources (amendments) with nutrients from mineral fertilizers (to address deficiencies) and reducing nutrient losses through soil and water conservation. It is advised that use of fertilizers should be under the concept of ISFM which is a set of agricultural practices adapted to local conditions to optimise the efficiency of nutrient and water use and improve agricultural productivity. ISFM aims to optimise the use of organic matter that provides nutrients, sequesters C and enhances water storage (e.g. compost, animal manures or green manures); and enhance nutrient efficiency through crop rotations or intercropping with nitrogen-fixing crops and judicious/precision use of inorganic fertilizer to reduce losses. Also ISFM minimize GHGs emissions (reduced traffic and tillage and efficient use of organic and inorganic fertilizers). ISFM strategies centre on the combined use of mineral fertilizers and locally available soil amendments (such as lime and rock phosphate) and organic matter (crop residues, compost and green manure) to replenish lost soil nutrients. This improves both soil quality and the efficiency of fertilizers and other agro-inputs. In addition, ISFM promotes improved germ-plasm, agroforestry and the use of crop rotation and/or intercropping with legumes (a crop which also improves soil fertility). Farmers who have adopted ISFM technologies have more than doubled their agricultural production and increased their farm-level incomes. ISFM improves resilience of soils and agricultural production to weather variability; increases soil organic matter and soil organic carbon; improves soil health and fertility leading to increased yields and; lowers potential for nitrogen leaching and greenhouse gas emissions, potentially increases soil carbon. Other soil fertility management practices include; mulching, crop rotation (see under CA). 2.4.8 Crop Management Practices and Technologies • Adapted crops and crop varieties Adapted crops and crop varieties involves improved seeds for high yielding, fast maturing, drought tolerant, salinity tolerant and flood tolerant. Climate change affects the agricultural yield directly through changes in temperature and precipitation, and indirectly through changes in soil quality, pests and diseases. One key technology is improved seeds which are early maturing and drought tolerant crop varieties. It is noted that farmers understand and are using improved seeds in their crop production with the main objective to grow high yielding varieties as an adaptation strategy to climate change. Improved, high-yielding varieties include grain, legume, fruit and vegetable varieties that have been bred to improve and increase yields. Early maturing crop varieties enable the crop to escape stress at the end of the season and are ideal for intercropping as they provide less competition for moisture, light and nutrients as compared to late maturing varieties. In addition, they offer flexibility in planting dates, which enables multiple plantings in a season to avoid risk of losing a single crop due to drought and avoidance of known terminal drought periods during the cropping season. These advantages make the early maturing crop varieties more remunerative and less risky to climate change impacts. Drought tolerant crops bred specifically to be adapted to climate challenges in a particular region escape drought through early maturity. CLIMATE-SMART AGRICULTURE 20 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL • Integrated Pest Management (IPM) Integrated Pest Management (IPM) is a broad-based approach that integrates practices for economic control of pests. It aims to suppress pest populations below the Economic Injury Level (EIL). It is a strategy that promotes a safer and more sustainable management of pesticides. IPM lies at the centre of insect, disease and weed control. The combination of farming strategies, biological control agents, and necessary pesticide (e.g. herbicide, fungicides and insecticides) use can help farmers address pest problems using a variety of methods. IPM reduces the need for pesticides by using several pest management methods; shields the environment from excessive or unnecessary pesticide applications; fosters clean water supplies; and promotes sound structures and healthy plants. IPM contributes to climate change adaptation by providing a healthy and balanced ecosystem in which the vulnerability of plants to pests and diseases is decreased. By promoting a diversified farming system, the practice of IPM builds farmers’ resilience to potential risks posed by climate change, such as damage to crop yields caused by newly emerging pests and diseases. However, the multiple impacts of climate change could significantly reduce the effectiveness of current IPM strategies, leading to higher crop losses. Better knowledge and understanding of pest behaviour under different projected scenarios are required to adopt and develop new IPM technologies to respond to threats resulting from climate change. • Timely or early planting/sowing Timely or early planting/sowing (in some places also dry sowing) is a practice of adapting to climate change. The practice ensures optimal use of the short rain season and makes efficient use of accumulated nutrients from organic sources during the dry season (nitrogen flush). The use of this practice can be strengthened by climate services through timely provision of weather information. • Crop Insurance and Safety Nets Crop insurance is purchased by agricultural producers, including farmers, ranchers, and others to protect themselves against either the loss of their crops due to natural disasters, such as hail, drought, and floods, or the loss of revenue due to declines in the prices of agricultural commodities. The two general categories of crop insurance are called crop-yield insurance and crop-revenue insurance. Safety nets are a form of social insurance comprising programmes supported by the public sector or NGOs that provide transfers to prevent the poor from falling below a certain poverty level. These programmes include cash transfers, food distribution, seeds and tools distributions, or conditional cash transfers (Devereaux, 2002). Safety net programmes can actually be a form of social investment into human capital (e.g. nutrition, education) and productive capital (e.g. allowing households to adopt higher risk and higher productivity strategies; (SOFI, 2010). Safety nets are increasingly being linked to rights based approaches to food security moving from a charity to entitlements. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 21 2.5 LIVESTOCK SUBSECTOR PRACTICES AND TECHNOLOGIES 2.5.1 Improved Livestock Breeds One key technology in livestock production is improving the genetic potential of cattle, poultry, pigs, sheep and goats to produce livestock which grow bigger and faster and at the same time resistant to stress (e.g. water, heat , diseases stress etc). This can be achieved by combining the desirable traits of the exotic breeds with the hardiness, and disease resistance of local breeds through cross-breeding or upgrading. The aim of cross-breeding is to improve local breeds to improve production (e.g. meat, milk and eggs), maturity time, resistant to stress etc. In this way, livestock keepers increase incomes by selling more Livestock products and by-products. Different livestock types and breeds require specific environmental conditions. Climate determines the type and quality of pasture, availability of water, livestock pests and diseases and therefore overall livestock types and their productivity. Adapted livestock types and breeds often survive and do well under extreme climatic conditions. Under the changing climate, care should be taken in deciding the appropriate livestock enterprise for any particular area. 2.5.2 Improved Feeds Improved feeds includes pastures, concentrates formulated using agro industry by products (molasses, brewers waste, maize/rice/wheat bran, oilseed cake). These feeds can be altered to improve its digestibility and provide needed nutrients. Addition of feed additive can also be used to improve digestibility and nutritive value of feeds. Such Feed improvement aims at reducing methane (CH4) emissions. Climate change mitigations result from a more efficient absorption of nutrients, with a consequent reduction in gaseous losses, and the ability to produce comparable amounts of dairy and meat with fewer animals. Feed supplements are required in small amount but are very important in enhancing productivity of livestock. Examples of feed supplements are urea–molasses multi-nutrient blocks, low bypass protein, lipids, and calcium hydroxide. Succulent plants can offer an alternative source of water as well as feed to grazing animals especially during the dry season. Example of succulent plants includes Commelina spps, Pyrenacantha malvifolia and Water melons (Citrullus vulgaris) locally known as “mahikwi”. 2.5.3 Livestock Improved Feedings Improved feeding strategies include; cut and carry; rotational grazing by paddocks, fodder crops, and grassland restoration and conservation may be adopted to improve Livestock productivity. This entails storing animal feeds (stover, grass, grain) and making better use of feed (by combining types of feed), growing grass varieties specifically suited to the agro-ecological zone, and many other practices, such as fodder conservation and animal fattening. The strategies also involve managing paddocks and/or pastures for ensuring enough fodder for livestock feeding at home, especially under zero grazing. Keeping livestock under zero grazing and in paddocks helps in improving manure management practices. CLIMATE-SMART AGRICULTURE 22 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 2.5.4 Pasture and Grazing Land Management • Pasture Management Pasture management is a practice of growing healthy grass and related plants to profitably sustain forage availability and livestock production while ensuring ecological health. Pasture management can provide significant benefits including improved forage yields, lower feed costs and improve livestock performance. Pasture spps African fox tail grass (left) and Elephant grass (right) Good pasture management tends to decrease carbon release to the atmosphere. The key to reducing GHG emission is to maintain healthy and high quality pastures. High quality feed means higher feed efficiency and more nutrients absorbed by the animal. The rate of consumption by animal (e.g. cattle) is influenced with high quality forage, increasing the efficiency of digestion and reducing the amount of time needed to graze. Faster digestion and greater feed use efficiency means less production of methane. Improved pastures also have numerous indirect benefits to reduce GHG production from animal production. Perennial forages trap atmospheric CO2 with their extensive root systems, storing carbon meters below the ground. Grasses and alfalfa not only improve the soil by increasing organic carbon, but are capable of absorbing excess water, lowering the water table and helping to control soil salinity. Reducing soil moisture also limits the risk of N losses by de-nitrification, cutting down the amount of nitrous oxide (N2O) creation. Pastures also provide soil cover, protecting against erosion, and maintain or improve water quality. • Grazing Land Management Different methods can be employed to manage grazing land depending on indigenous knowledge in regard to natural resources management, human and animal diseases relative to their environment. Both traditional and improved grazing land systems can be employed managing grazing lands. Under, traditional grazing land Management system, the communities control resource use pattern, and conservation using the traditional knowledge of the ecosystem and the biological diversity of the areas. Some of the traditional grazing land Management systems are Ngitili and Olelii. CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 23 Ngitili - is a traditional fodder conservation system that was developed by the Sukuma agro-pastoralists (Shinyanga) as a means of alleviating acute dry season fodder shortage. Ngitili encompasses retaining of an area of standing hay until the rainy season ends, the area remains closed to livestock and other activities at the onset of the rainy season and is opened up at the peak of the dry season to allow the livestock get dry season fodder. Grazing under ngitili normally starts from July/August after crop residues and forage in fallow areas has been depleted.Animals also removed from ngitili after all the fodder is exhausted or when fodder becomes available outside the ngitili. Ngitili System in Shinyanga Olelii -is a traditional fodder conservation system developed by the Maasai pastoralists (Arusha) as means of conserving fodder for the dry season or for the calves, sick animals and/or milking herd. The vegetation is left to grow and regenerate during wet season and livestock are allowed to graze in dry season. The elder groups oversee and directs on management and use of resources such as grazing pattern and conservation of fodder for dry season grazing. The Traditional ecological and farming knowledge (TEK) systems such as grassland and forest conservation and use, uses of biological diversity (including ethno-veterinary, nutritional and medicinal uses) is practiced and passed from one generation to another through the traditional institutions 2.5.5 Improved Grazing Land Management • Zero Grazing A zero-grazing system is where grass is mechanically mown and brought to livestock. Its appeal is that it allows livestock to consume forages from fields that are too far away, or are separated by busy road, to be included in the grazing rotation. Zero-grazing can also play a role when utilizing fields too wet for grazing, provided the machines employed have sufficiently wide wheels to safely distribute their load. This system increases productivity to livestock due to minimum energy utilization, also there is no land trampling so controlling soil erosion realization. CLIMATE-SMART AGRICULTURE 24 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL Livestock kept under zero grazing 2.5.6 Manure Management Major emissions from manure come in the form of methane (CH4) from anaerobic decomposition of manure during storage as well as N2O formed during storage and application. The creation of these gases is influenced by a variety of factors: temperature, oxygen level, moisture or amount of nutrients. In turn, these factors are affected by manure type, animal diet, the type of manure storage and handling and manure application techniques. To help reduce GHGs creation and work with large amounts of excess manure, it is important that manure management in the area concentrates on disposing manure in an environmentally and economically friendly manner. One of the economic and environmental friendly systems of managing manure is the use of Biogas digester On Farm Biogas Production This aims at reduce Greenhouse Gases (GHGs) emissions and develop more sustainable livestock operations. The GHGs are reduced by production of renewable energy as a substitute for fossil fuels via reduction of fugitive GHGs emissions from stored and land applied manures, as well as by reduction in use of chemical fertilizers in crop production. Utilization of livestock droppings (residue) in this way is important for preventing environmental pollution, also decomposed manure (slurry) is rich in nutrients and hence applied to crops be it food crops and pasture increases productivity. Biogas plant Cooking using biogas CLIMATE-SMART AGRICULTURE CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 25 2.6 FISHING AND AQUACULTURE ACTIVITIES The main elements of climate change that could potentially impact fishing and aquaculture production are mostly associated with water level changes in water bodies and temperature fluctuations. These changes are triggered by the impacts of climate change such as changes in rain seasons and patterns, an increase in extreme events such as prolonged dry spell periods, drought and flood, water stress which results in changes of oxygen levels, solute concentration and water pollution through algae proliferation. However, there some fishing and aquaculture practices which are considered climate-smart based on their ability to ensure sustainable productivity in the face of climate change. 2.6.1 Pond Aquaculture/Fish Ponds It is a common technology which uses pond to raise fish for domestic or market purposes. It is commonly practiced in areas with easy access to water, though it can also be practiced in dry areas where water can be harvested and stored for fish farming. Inland finfish culture which uses ponds is a dominant form of aquaculture in Tanzania. The Size of pond used in this type of aquaculture ranges from a few hundred square meters to a few hectares and are often shallow ponds. CLIMATE-SMART AGRICULTURE Cement Fish pond Earth fish ponds in Kalenga, Iringa The practice of culturing more than one species of fish in the same pond is known as Polyculture and is known to have higher yield through proper food utilization, because different species of fish exploit food at different trophic levels in the pond. Proper management of fish pond is critical to reduce production of noxious gases and mitigate risks of disease outbreak. It is advised to consider species of fish which are adaptable to changes in oxygen, temperature and saline species such as Nile Tilapia and catfish. In Marine milk fish is known to be tolerant to oxygen, temperature and poor water quality. Planning of pond management based on the knowledge of climate change impact such as water availability, temperature changes, flooding events and periods of prolonged dry spell are critical on ensuring sustainable fish production. 26 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL CLIMATE-SMART AGRICULTURE 2.6.2 Integrated Aquaculture and Cage Culture Integrated aquaculture practice involves an integration of fish with another production system such as rice which is known as rice cum fish culture or integration of aquaculture with animal husbandry. In this way, the integrated aquaculture practice may exist in different forms. Though, in most cases fish species cultured are those which feed at low trophic levels of food chain. The practice is mostly practiced by a single-family unit, conducted at small-scale level and takes various traditional forms. The practice is considered climate-smart as it contributes to food security and diversification, fish species are less susceptible to temperature changes and contribute on carbon sequestration Integrated fish farming with crops 2.6.3 Sustainable Fishing This include fishing practices which uses passive fishing gears such as gill nets, pots, hook, lines and traps with minimal destruction to aquatic environment, fish reproduction sites and ensure sustainability in productivity. Such practices may involve use of bio-degradable materials and use of innovative technologies such as echo-sounders in vulnerable or sensitive habitats. The practices are climate-smart because they focus on increasing productivity and sustainability of production systems even under the impact of climate change. 2.6.4 Seaweed Farming Seaweed farming is the practice of cultivating and harvesting seaweed. In its simplest form, it consists of the management of naturally found batches. In its most advanced form, it consists of fully controlling the life cycle of the algae. It is practiced mainly along the sea shores and in Tanzania is practiced widely in Zanzibar and along the shore. The culture of seaweed requires minimal energy inputs and, therefore, has a relatively small carbon footprint. The rapid turnover in seaweed culture of approximately three months per crop (in the tropics) makes one of the climate-smart practices. This is because its carbon uptake potential far exceeds that obtained through other agricultural activity of the same comparable area. Additionally, sea weed farming systems can filter nutrients and provide a “cleaning service” to coastal marine environments and thus contributing on enhancing ecosystem service. CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 27 Seaweed farming 2.7 OTHER CSA PRACTICES AND TECHNOLOGIES 2.7.1 Bee-keeping Beekeeping or apiculture is the maintenance of honey bee colonies, commonly in man-made hives. A beekeeper (or apiarist) keeps bees in order to collect their honey and other products that the hive produces (including beeswax, propolis, pollen, and royal jelly), to pollinate crops, or to produce bees for sale to other beekeepers. Hence, bee keeping contributes in increasing agricultural productivity through pollination, protection of surrounding environments as bee keepers need to maintain vegetation or forest cover and enhance resilience as source of income. CLIMATE-SMART AGRICULTURE Beekeeping in Iringa Traditional beehives are hung on trees close to a nearby forest. They are made by cutting a cylindrical log, carefully scooping inner content to make a hollow structure and sealing the two ends with small holes for exit and entry. Contrast to traditional hives, modern hives have straws to test honey is readiness before harvesting. By opening the hive and taking out the straw, the farmer will know whether the honey is ready to harvest. This method helps beekeepers to increase productivity. 28 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL CLIMATE-SMART AGRICULTURE 2.7.2 Climate Information Services Timely communication of climate information helps prevent the economic setbacks and humanitarian disasters that can result from climate extremes and long term climate change. Climate information also plays a crucial role in national development planning, for managing development opportunities and risks as well as for mitigation and adaptation. Efficient application of climate services requires that climate information become available to stakeholders. Availability of climate information services offers great potential to enable farmers to make informed decisions, better manage risk, take advantage of favourable climate conditions, and adapt to change. 2.7.3 Improved Post-Harvest Appropriate post-harvest practices and technologies are important on ensuring sustainable applications of CSA practices by ensuring produces are sold in good quality and condition. Practices and technologies such as winnowing, drying, improved storage facilities, cold room transportation vans and other processing methods are key for sustainable productivity and market linkages of agricultural produce. This in turn increases community resilience to the impact of climate change by ensuring food and nutrition security. 2.8 UPSCALING CSA PRACTICES AND TECHNOLOGIES Agriculture is considered climate-smart when it sustainably increases agricultural productivity and incomes, builds resilience to climate change and reduces greenhouse gas emissions. To achieve this, there is urgent need to upscale CSA practices which can be facilitated through; • Proof of concept at sites/field established based on clear objectives set by farmers, extension officers and possibly researcher where possible using inclusive and participatory multi stakeholder planning approach. • Creation of innovative CSA practices toolbox customized to an area, will allow farmers extension officer, researchers and other relevant stakeholders to identify CSA technologies and practices prioritized based on yield, resilience potential and other beneficial features customized to an area. • Promotion of holistic approaches which are cross-sectoral will foster linkages between relevant stakeholders across value chain for sustainable and profitable CSA practice adoption at all levels and scales by farmers. • Promotion of climate-smart agricultural innovative CSA financing arrangements and business models needs to be encouraged by policy and decision makers such that agribusinesses, SACCOS, banks and farmers based organization can spread risk and develop substitutes for collateral through multi-party financing mechanisms (PWC, 2012). • Ensure equitable land access to men and women alike, increase investment in agriculture, promote sustainable use of inputs and ensure availability of reliable markets of the produce. • Improve knowledge management system –by strengthening farmers knowledge of CSA practices, facilitate sharing the techniques and provide the greatest support to local knowledge system 2.8.1 The challenges in upscaling CSA While CSA technologies and practices are generating significant benefits, their adoption often faces a variety of challenges or barriers by famers such as:- • Insufficient information on potential gains of adopting new technologies, training and extension • Limited availability and access to inputs • Limited capacities on implementing improved practices • Significant upfront expenditure required on adopting new technology • Limited number of CSA projects CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 29 CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 3.1 INTRODUCTION Successful CSA implementation requires strong institutional support to: promote inclusivity in decision making; improve the dissemination of information; provide financial support and access to markets; provide insurance to cope with risks associated with climate shocks and the adoption of new practices; and support farmers’ collective actions. In this regard, there are specific roles to be fulfilled by different stakeholders, also there are series of approaches and methods that should be considered based on local situation and the characteristics of the target group. 3.2 IDENTIFICATION OF STAKEHOLDERS Multi-stakeholders’ participation and active community involvement in projects/program design and development are critical for successful climate-smart agriculture implementation and upscaling. Different stakeholders have been identified with different roles to play in the CSA implementation among them are; Government, NGOs, Development and Research Partners, Private Sector, Farmers and Media. 3.3 ROLES OF DIFFERENT STAKEHOLDERS ON IMPLEMENTATION AND UPSCALING OF CSA Different institutions have different roles to play in order to make CSA Implementation successful and sustainable for agriculture development. The following are some of the roles of stakeholders in different levels; 3.3.1 Government • Sensitization and Awareness Creation at all levels This can be done using various means such as Policy briefs, mass media (radio, TV, newspapers, social media and drama groups), farmers’ exhibitions and resource centers (demonstrations), workshops, incorporating CSA concept in curriculums at different levels of education. • Amendment and enforcement of related agriculture policies Climate-Smart Agriculture is an initiative adopted from abroad, and it has got specific principles, practices and technologies, but also it is globally implemented under UN agencies such as FAO. Due to that, the need for the Government to amend Agricultural related Policies to accommodate CSA concepts where it is found necessary to speed up CSA up-take, is a core responsibility, and ensures their enforcement. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 3| 30 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL • Capacity Building of Extension agents The Government has to organize and conduct workshops and meeting for capacity building for the extension agents to enable them understand and then engage in disseminating and promoting the CSA guideline appropriately • Establish Partnership with Other Institutions The government should establish partnership/collaboration with institutions and the private sector that will help and improve access of required implements/equipment including promoting local manufacturing of equipment and maintenance/service of equipment or facilitating purchase of that equipment such as rippers and biogas plants, for upscaling identified CSA technologies and practices • Distribution on incentivizing agricultural subsidies The government has to help the implementation of CSA by providing subsidies to agricultural inputs that support CSA practices and technologies to open a door for economic disadvantaged farmers to adopt CSA. • Establish Monitoring and Evaluation Systems To ensure CSA good performance and sustainability, the Government, in relation with other CSA stakeholders has to develop monitoring systems which will help to evaluate CSA achievements basing on the temporal and spatial scales, but also will merge a door for mistake correction towards higher CSA achievements • To establish link to connect farmers with markets and service providers In relation with other CSA stakeholders the Government has to provide suitable atmosphere on legal and policy aspects which will allow farmers to be linked easily and assuredly with markets and other service providers. To have Investments that support agricultural marketing and the food system, including roads and market infrastructure • To Develop and provide improved early warning information (weather and climate) The concept of Climate-Smart Agriculture, refers, agriculture activities to be carried out with great achievements by making farmers smart by being aware and make adaptation of the on-going changes of weather and climate. This requires developing reliable and trusted systems of early warning information 3.3.2 NGOs NGOs are typically strong in providing social services, especially when supporting poor communities. For example, building social capital by organizing farmer groups to articulate their own needs and formulate solutions collaboratively, brings immediate positive effects at the local level. • To fast up-take of CSA technologies by Improving the quality and relevance of research on CSA through local participation. • Promote Indigenous CSA Knowledge, Practices and Technologies which are identified as CSA practices and technologies. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 31 3.3.3 Research partners Research Institutions can help in bringing together different stakeholders using Learning and Practice Alliance (LPA) approach which engages key stakeholders including policy makers, practitioners and farmers to join and work together in addressing existing problems and identify potential solutions. The LPA approach has the capacity to influence change in attitude, strategies, planning and resource allocations for upscaling CSA best technologies and practices. Some of the roles of research partners include; • Participatory Research on Improved Technologies and Practices • Strengthening capacity of agricultural research systems for linking with other actors (e.g. through stakeholder platforms, alliances and consortia, technology transfer and commercialization • Bring Together Stakeholders Through Learning and Practice Alliance 3.3.4 Private Sector As markets become increasingly important in developing economies, private sector actors also become significant providers of research and development, education and extension services. When seeking private sector support for CSA initiatives, it is important to bear in mind that the private sector’s main priorities are profit and public perception. CSA works to establish a ‘triple win’ scenario in which innovative practices produce higher yields, build resilience to climate change (reducing long-term risks) and lower carbon emissions all along the supply chain. By contributing to CSA, private businesses can enhance their brand recognition among key suppliers and consumers. Key private sector actors and the possible support they might provide to CSA initiatives include; • Strengthening of informal agricultural Markets (e.g. certification and training of traders) • Develop and Implement Risk Management Strategies such as productive social safety nets (e.g. cash transfers, food distribution, and seed and tool distribution, conditional cash transfers, food for work 3.3.5 Farmers Farmers should form groups but also identify champion farmers who are very effective in obtaining and disseminating knowledge of CSA technologies and practices. Establishing farmers’ groups and champion farmers should of course consider social dimensions due to the fact that the preferences of dissemination pathways always differ among gender groups Farmers should engage in farmer field schools (FFS), which will include demo plots to help learn and disseminate practical knowledge on CSA packages. Learning visits and/or farmer field days/shows should be organized and facilitated for farmers. In addition, extension staff, private sector and policy and decision makers should learn by seeing. This will help farmers share knowledge and experiences of CSA practices among themselves, but also with policy and decision makers, extension agents and private sector Knowledge sharing products (KSPs) should be designed to suit each category of stakeholder. Those with low education level, field days could be more appropriate mode of dissemination; farmers with small farm size prefer fellow farmer/trainers field visits; while young and educated farmers, print materials, electronic knowledge sharing such as use of media and mobile phones could be appropriate CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 32 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 3.3.6 Media Mass media can reach large audiences with messages about CSA. Broadcast and electronic media include radio, television, film and the internet; print media includes newspapers, journals, publications; outdoor media includes posters, billboards and other materials placed in public view. An important channel for disseminating informative and educational contents, media can both reflect public opinion and shape it. In recent years, more and more people, even in rural areas have gained access to media hardware such as radios, televisions, computers and smart phones. Innovative technologies, such as solar-powered electronic devices, are also becoming increasingly important in mobilizing the media for development purposes. 3.3.7 Development Partners/Inter-governmental Institutions Development partners are very crucial stakeholders in CSA implementation in Tanzania. They help in changing the mind-set of policy makers, practitioners and also farmers by emphasizing the importance of Indigenous Knowledge (IK) that is compatible with best CSA technologies and practices, and supported with scientific knowledge in scaling up through communicating research findings on IK and through training. Some of their roles are; Provide technical assistance, Provision of sourcebook, Provide financial assistance in promoting CSA and facilitate capacity building to increase knowledge and skills on upscaling best CSA technologies and practices 3.3.8 Religious institutions and communities The term ‘institutions’ does not merely refer to types of organizations; it also encompasses cultural and social norms and conventions. An awareness of public opinions and values is therefore important when formulating a CSA strategy. While religious institutions or issue groups are unlikely to provide CSA-related advisory services, they can offer indispensable insights into prevailing beliefs and values. They can be mobilized as powerful tools for advocacy and endorsement 3.4 STAKEHOLDERS ENGAGEMENT MECHANISMS Basing on the provided roles of stakeholders, mechanisms for implementation are very important; hence the need to identify stakeholders’ engagement mechanisms is crucial for effective implementation of Climate-Smart Agriculture. Establishment of different platforms at all levels will be used as the main mechanism to engage different stakeholders to be involved in the CSA implementation, for example creation of CSA Networks and convening for national/regional events. Also the stakeholders have to be aware on how they engage in the implementation of CSA basing on their roles. For example Government through mainstreaming of CSA initiative in policies and strategy is one of the mechanisms for its engagement. 3.5 APPROACHES FOR CSA INTEGRATION The agricultural extension approach in Tanzania involves farmers’ groups in the planning and implementation process. It is also integrating different extension providers, allowing room for pluralistic extension approaches and empowering farmers organizationally and financially to demand for appropriate services. The extension services use a combination of dissemination pathways such as • Gender responsive approach Social inequality and social inclusion, particularly in reference to gender, have been recognized as a CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 33 foundational issue in development .The successful of CSA practices requires institutional and behavioral change, which is not possible without social analysis (including gender analysis) influencing policies, projects, and other interventions aimed at achieving sustainable CSA. • Community Based Approach This is the approach whereby a practicing farmer or livestock keeper selected by their community and trained to a standard where they can offer credible advice and services in a specific area of production. A sizeable proportion of those trained 5-10 years ago have built a loyal client base by charging affordable fees for their services, and plan to continue in the role indefinitely • Farmer Field School Approach It is used throughout the country and is incorporated within DADPs. It uses experiential learning and group approach and currently its successes have been seen especially in smallholder’s irrigated rice farms where production has increased, key farmers train others. The impact of the approach is an increase in production seen in FFS members compared to non-FFS. Agricultural resource centres are permanently established in each District/ward used for demonstration of good agricultural technologies/practices. • Farming System Approach This is the approach where by farmers priorities are incorporated into the research agenda & user-friendly technologies are developed. • Farmer to Farmer Extension Approach This is the approach whereby there are trained farmers who can train others. • Champion Farmer Approach This is the approach whereby extension services choose farmers to work with them in implementing their programs. Those farmers selected to lead “farmer-to-farmer” extension are often called model, master, or lead farmers and are chosen according to their agricultural expertise • Landscape and Ecosystem Services Approach This approach deals with large-scale processes in an integrated and multidisciplinary manner, combining natural resources management with environmental and livelihood considerations, It is also factors in human activities and their institutions, viewing them as an integral part of the system rather than as external agents • Payment of Ecosystem Services Approach These are incentives offered to farmers or landowners in exchange for managing their land to provide some sort of ecological service. They have been defined as “a transparent system for the additional provision of environmental services through conditional payments to voluntary providers. • Nucleus and Out Growers Approach Formal arrangement between agriculture companies and farmers (contract farming), the private sector facilitates farmers’ access to credit, improved inputs, pooling of farmers’ produce, processing and developing market links. CLIMATE-SMART AGRICULTURE STAKEHOLDERS INVOLVEMENT 34 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 4.1 INTRODUCTION This topic addresses the issue of mainstreaming Climate-Smart Agriculture (CSA) into development plans at different levels. The first part of the topic looks at awareness and sensitization on CSA. The second part addresses the CSA related activities. Finally, the third part focuses on budgeting for CSA activities and how climate change affects investment needs for agricultural development to support food security, poverty reduction and economic growth. 4.2 AWARENESS CREATION AND SENSITIZATION ON CSA 4.2.1 Meaning of awareness Awareness is having knowledge that something exists, or understanding of a situation or subject at a given time based on information or experience (in simple term is knowing what is going on). Creating awareness is letting the right people know that the information/service exists and is available. To raise awareness is to inform and educate people about a topic or issue with the intention of influencing their attitudes, behaviours and beliefs towards the achievement of a defined purpose or goal. 4.2.2 Meaning of sensitization Is the process of making someone react to something that previously had no effect. Basing on CSA dissemination, sensitization aims at making all stake holders to be responsive to their roles and contributions on the implementation of CSA practices and technologies 4.2.3 How to create awareness Many African smallholder farmers and farm communities experience low crop and animal yields but they are not aware that, this is partly a result of climate change. Most of them are not aware of what to do to remedy the situation. The current climate change discourse is very much promoted by international NGOs and some CSOs with little contribution from local farmers and communities. Other stakeholders such as CSOs can be consulted to be involved in awareness creation. Awareness raising is an important stage for effective dissemination of knowledge and technologies, to be successful, it needs to use all appropriate communication channels such as radio, television, print media, leaflets, brochures, oral communication, and traditional communication. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 4| MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 35 MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS • Training Training of key stakeholders in climate change and climate-smart agriculture is important in order to increase knowledge and understanding, which eventually contribute to change or shape their mind-sets in their undertakings. Training should therefore be done based on the roles of the stakeholders at different levels. Training can be offered through different ways such as; technology-based learning, on field training, coaching, lectures, group discussion, films and videos. Likewise, training should also take into account the specific role of each target group (stakeholders). Relevant training manuals should be prepared for the target group, which will also serve as a reference during the implementation stage. • Integration of CSA in the Syllabus Educational institutions actually prepare and shape future working force of different professionals including the rural agrarian community. Most of the agrarian communities use knowledge and skills acquired at different stages of their education. Introduction of CSA in the syllabus would therefore help building capacity of not only future farmers but also future stakeholders of CSA (Policy maker, Researcher, Planner, Economist, Engineer, and Doctor etc.). The government should take up the agenda and oversee possibilities of mainstreaming it in the curriculum or syllabus. 4.2.4 Target for Awareness Creation Awareness raising targets different groups such as, government authorities, central and local administrative authorities, religious, traditional leaders, opinion leaders, NGOs, civil society, donors, media and community. Planning for awareness raising strategy should therefore take into account the target group, the message for each target group (preferably specific to the group), and the appropriate channels for communicating those messages. 4.3 CSA RELATED ACTIVITIES AND THEIR JUSTIFICATION CSA activities can range over a very broad range, depending on the relative importance of its three pillars – food security (productivity), adaptation, and GHG mitigation. 36 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL 4.3.1 CSA Related Activities The table below shows some of the CSA related projects/activities together with the Practices and its related pillar(s); CSA RELATED ACTIVITIES CSA PRACTICES OR INTERVENTION RELATED CSA PILLAR(s) Soil and water Management • Water use efficient (drip irrigation, lining of canals) • Rain water harvesting and storage • Land and catchment management • System of Rice Intensification • Conservation agriculture( Cover cropping, Crop residue management, crop rotation, agro forest and Mulching • Productivity • adaptation Research • Resilient crop varieties (Drought tolerant varieties, Early maturing varieties and Water efficient varieties) • Productivity • Adaptation crop production & land preparation • Resilient crop varieties • Pest and diseases control • Post harvest and storage facilities • Productivity • Adaptation • Mitigation Livestock • Improved livestock breed • Improved Feeding • Efficient manure management; • Productivity • Adaptation • Mitigation Fisheries and aquaculture • Pond aquaculture • integrated aquaculture • cage aquaculture, • seaweed farming • Productivity • mitigation Disaster and risk reduction • crop insurance • productive social safety nets • Adaptation 4.3.2 Justification for CSA activities The changes in agricultural systems needed to achieve agricultural growth for food security, nutrition, and economic development under climate change are largely built upon sustainable agricultural intensification activities. Building an evidence base to identify the most suitable activities is an essential part of developing CSA strategies, investments and financing plans. Innovative financing mechanisms that link and blend climate and agricultural finance and investments from public and private sectors are a key means of implementing CSA. New climate financing instruments such as the Green Climate Fund are currently under development and could be a way of spurring sustainable agricultural development. Strong and all-encompassing Nationally Appropriate Mitigation Actions (NAMAs) and National Adaptation Plans (NAPs) are key national policy instruments important in creating links to national and international sources of finance. National sector budgets will continue to be the main sources of funding, climate integration into LGAs planning and budgeting is therefore a prerequisite for successfully addressing climate change. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 37 4.4 PLANNING CSA ACTIVITIES WITH GENDER CONSIDERATION Gender is pertinent to CSA, hence the need to put emphasis on the importance and ultimate goal of integrating gender in CSA activities is inevitable. The aim for integration is to reduce gender inequalities and ensure that men, youth and women can equally benefit from CSA related interventions in the agricultural sectors, so that to reduce risks linked to climate change. Taking a gender responsive approach to CSA, means that particular needs, priorities and realities of youth, men and women are recognized and adequately addressed in the design and application of CSA activities. Gender transformative CSA interventions seek to transform gender roles and promote more gender- equitable relationships between men and women. Planning of CSA activities must be flexible enough to reflect gender priorities and needs (specific to women). The active participation of women in the planning process, development of funding criteria and allocation of resources for climate change initiatives is critical, particularly at local levels. Gender analysis of all plans, budget lines and financial instruments for CSA is needed to ensure gender-sensitive investments in programmes for adaptation, mitigation, technology transfer and capacity building. 4.4.1 Mainstreaming Gender into CSA Planning Process The adverse impacts of climate change have disproportionate bearing on youth, men and women. It is therefore important to consider gender specific concerns and subsequent solutions in climate change adaptation planning processes. Women are not only differently vulnerable to climate change but they are also crucial in implementing adaptation solutions and building resilience. Similar to mainstreaming climate change adaptation development activities, gender integration in climate change can be internalized through systematic integration in policies, programmes, projects and activities. 4.4.2 Gender Analysis In order to support women’s and men’s equal uptake of and benefit in site-specific CSA practice or technology, gender analysis as well as equal participation and engagement of women and men are the key actions to be taken at the outset of any CSA intervention. In the longer term, broader changes are needed in order to reduce the constraints women and men may face in terms of accessing resources, services and information. Gender analysis of how women are differently affected by climate change and identification of gender specific responses during the planning stage can help make CSA activities and outputs gender sensitive. Socio-economic vulnerability assessments, assessing the CSA activities to address woman’s access to resources (e.g. finance, information, etc.) can help to set up gender specific objectives at an initial stage of the planned CSA related activity, project or programme. 4.5 BUDGETING FOR CSA RELATED ACTIVITIES Significant progress in addressing climate change in the agricultural sectors can only be achieved if climate concerns are considered in the context of all agricultural investment decisions, rather than in climate change specific projects. The need of adaptation to climate change in the near, medium and long term implies that, changes in agricultural investment needs, ranging from the farm scale up to the national and international levels. Current agricultural investment flows are insufficient to adequately finance sustainable agricultural development. This financing deficit is due not only to a lack of overall funds, but also to the fact that, the activities which are currently allocated resources do not generate the highest returns for sustainable agricultural growth. The main sources of agricultural investment MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 38 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL finance are the farmers, herders, fishers and foresters themselves. For this reason, public investment that enables agricultural producers to make investments in CSA is a priority. 4.5.1 Gender responsive budgeting Gender-responsive budgeting aims to address the lack of resources for gender mainstreaming activities by translating gender commitments into fiscal commitments through the application of a gender lens to the entire budgeting process. In addition to making the work undertaken by women economically visible, gender-responsive budgeting is advocated as a means of increasing transparency and accountability by delineating the amount of the budget allocated to women that is actually spent. Gender budgeting can be used as an important tool to allocate resources for implementing gender specific adaptation actions. Adequate financial resource allocation is key to the achievement in the gender mainstreaming process, and is one of the biggest challenges in efforts to implement gender mainstreaming across climate change related and other activities. 4.5.2 Potential Costs of Maladaptation Important issue to consider is the potential costs of maladaptation (e.g. agricultural investments that increase vulnerability to climate change or increase risks of economic losses associated with unsustainable and unprofitable investments). Investments, particularly large fixed capital investments with significant lifetimes, are particularly vulnerable to being maladaptive if climate risks are not considered. An example that is likely to be maladaptive and essentially add to the adaptation deficit is a case where major capital expenditures on irrigation systems use out- dated estimates of water demand and supply in areas where climate change is predicted to have major impacts. Screening agricultural investment plans for their degree of “climate smartness” is a simple first step that can be taken to identify the potential overlap between adaptation and development investments, as well as potential maladaptive agricultural investments. The screening methodology considers the potential contribution of planned activities to various aspects of adaptation as well as mitigation. This suggests that climate-smart agricultural investments with mitigation co-benefits should be identified within the context of existing agricultural investment strategies developed for the purposes of agricultural growth for a specific context. 4.5.3 Source of Finance for CSA Financing options specifically targeting CSA are still limited, necessitating a strategic use and combination of existing funding sources. The basis for any CSA activity should be the identification of a country’s opportunities and vulnerabilities, corresponding needs and preferred options for CSA activities. After priorities have been defined, a strategic approach to sources of finance based on an understanding of available channels will not only increase the chances for approval, but also enhance the fit between the finance option and the country’s overall approach to climate change in agriculture. • Internal Finance The Government through the national budget is the main funder of the agricultural sector, supplemented by Development Partners (DPs), private sector and CSOs thus making significant contributions to the sector. In addition, the Government in collaboration with DPs and private sector have put in place measures MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 39 aimed at improving the flow of finance and investment to the agriculture sector such as: the Export Credit Guarantee Scheme, USAID Guarantee for Input Scheme, Private Agriculture Sector Support (PASS), the Agro- Dealers Scheme and the Agriculture Input Trust Fund (AGIFT). Other initiatives that enhance Public Private Partnerships include the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) and Big Results Now (BRN). ASDP2 is the potential source for funding especially at the local level as it aims to increase resilience of agricultural systems to climate change and variability. ASDP-2 interventions will be undertaken with climate change considerations factored into the interventions, including Climate-Smart Agriculture in sustainable landscapes and appropriate climate change mitigation strategies. Farmers’ adaptive capacities will be strengthened to ensure the impact is understood and integrated into their farming systems/activities. Capacity building programmes for FFSs, extension officers and subject matter specialists on current climate related issues will be developed, implemented and periodically updated • External Finance Main sources of external public financing for climate change adaptation and mitigation include the following: i. Financing mechanisms directly under the UNFCCC; ii. United Nations (UN) organizations or programmes; UN Agencies and Programmes play a central role as implementing agencies for the activities financed through the funding channels under the UNFCCC. In addition, UN Agencies also provide climate financing directly, primarily through multi-donor trust funds financed by member states e.g. the UN REDD programme. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS 40 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL iii. Multilateral Development Banks (MDBs); The primary function of MDBs is to provide loans under conditions and objectives based on their overall principles as well as the specific agreements between a specific country and the respective development bank. The agricultural sector remains one of the primary target sectors of MDB loans. As MDBs are increasingly incorporating environmental sustainability criteria into their agricultural lending practices, their loans play an increasing role as a financing option for CSA activities iv. Bilateral public financing channels Bilateral instruments remain one of the primary sources of climate finance. Bilateral Financial Institutions play a central role as intermediaries disbursing climate funding to developing countries. Examples include Japan International Cooperation Agency (JICA) v. Compliance and voluntary carbon markets Compliance carbon markets are marketplaces through which regulated entities obtain and surrender emissions permits (allowances) or offsets in order to meet predetermined regulatory targets. The voluntary carbon markets function outside of the compliance market. They enable businesses, governments, NGOs, and individuals to offset their emissions by purchasing offsets that were created either through the CDM or in the voluntary market vi. Private sector actors and philanthropy. Looking at the entire landscape of climate finance, the private sector is an international private sector funding that contributes to catalysing this transition. It is in fact the single largest source of financing. MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 41 5.1 INTRODUCTION Monitoring and Evaluation (M&E) aims at evaluation of CSA interventions in order to understand their performance, challenges, potentials and opportunities for upscaling and adoption. Also helps to determine the extent to which a CSA intervention has been achieved, its effectiveness and provide recommendation for consideration in other endeavour. Through M&E framework it is easier to track progress at different levels of the CSA implementation by looking at: • Impact on people’s livelihood and the environment • Effect on behavior and institutional change, and CSA mainstreaming in plans • Output reflecting on the CSA pillars • Multidisciplinary involvement of the stakeholder and gender mainstreaming 5.2 BASELINE INDICATORS FOR CSA RELATED A baseline indicator is a value of a performance before the implementation of projects or activities, while targeting a specific level of result to be achieved within an explicit timeframe. In order to monitor and evaluate an impact of CSA intervention a baseline indicator(s) needs to be identified. The process of identifying indicator(s) is always done at the early CSA intervention planning stage to get knowledge of the current status of an item. For CSA interventions this is important because baseline result will show how different aspects have changed as a result of implementing CSA Practices and Technologies. Baseline indicators is recommended to come from officially recognized sources of information national statistics, policy documents, budget speeches, local plans, comparison between seasons, food reserve and market price. Targets need to be established and agreed against the selected baseline indicators. The classification of baseline indicators for CSA interventions can be set according to the three CSA pillars which are Productivity, Adaptation and Mitigation or mitigation co-benefit. 5.3 PERFORMANCE INDICATORS A Key Performance Indicator (KPI) is a measurable value that will demonstrates how CSA intervention has been achieved considering key objectives of the intervention and respective baseline indicator(s). The key characteristics of the indicator is that; it should be SMART, specific to the objective, Measurable either quantitatively or qualitatively, Available at an acceptable cost, Relevant to the information needs and Time-bound so that it is easier to monitor and evaluate against expected objective or targets to be achieved. MONITORING AND EVALUATION OF CSA INTERVENTIONS 5| MONITORING AND EVALUATION OF CSA INTERVENTIONS 42 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL The Performance indicators in most cases differ between project and interventions based on set targets or goals. However, the process of indicators identification is similar by starting with clear identification of goals to be achieved, mechanism to reach the goal and metrics to achieve. Contrary to baseline indicators, the key performance indicators are extracted from the intervention plan to correlate with baseline indicator(s) identified. 5.4 MONITORING TOOLS AND RECORD KEEPING Monitoring tools are continuously used to keep track of the status of agreed plan on implementing CSA intervention in order to identify defects or problems and give early warning signs on failure or successes. Selection of monitoring tools for a certain project depends on the nature and type of indicators, also type of metric data needed. In the case of CSA interventions, the tools are such as record keeping data sheet, Checklist, field observation and documentation of evidence. 5.5 CREATION OF EVIDENCE FOR CSA INTERVENTIONS This is the process by which evidence of project succession or failures are compiled together in an easy manner with the aim of sharing lessons learnt with others. The effectiveness on compiling the evidence depends on the baseline and key performance indicators identified in the intervention plan. However the monitoring tool identified, quality of data collected and analysis will determine the influencing power of evidence created. Hence, for effective upscaling or sharing of lesson learnt from implementing CSA intervention, identification of baseline indictor, KPI and appropriate monitoring tools are essential. For example, a farmer in Kiroka Village in Morogoro after receiving high-yielding and early-maturing banana cultivars he managed to document (see picture below) landscape transformation before and after. This is one way of creating evidence which would allow sharing of lessons learnt with others for upscaling and adoption. The farm BEFORE The farm AFTER (Source: Henry Mahoo - SUA) MONITORING AND EVALUATION OF CSA INTERVENTIONS CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL | 43 CONCLUSION CSA practices and technologies aims at achieving food security and broader development goals under a changing climate and increasing food demand. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies can coordinate priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. Effective use of this ToT Manual is an important step toward the achievement of the national goals of sustainable agriculture production in a changing climate through application of CSA practices and technologies. This manual compliments Government efforts and initiatives on implementation of sustainable development goals by creating awareness, identifying CSA practices and technologies and mainstreaming of CSA in plans and programmes. CONCLUSION 44 | CLIMATE-SMART AGRICULTURE: TRAINING OF TRAINERS MANUAL REFERENCES Boers, T.M. and Ben-Asher, J. (1982) A review of rainwater harvesting: In Agriculture Water Management, 5:145-158 Food and Agriculture Organization (2010) “Climate-Smart” Agriculture Policies, Practices and Financing for Food Security, Adaptation and Mitigation: Food and Agriculture Organization of the United Nations. Hatibu, N. and Mahoo H., (1999): Rainwater harvesting technologies for agricultural production: A case for Dodoma, Tanzania. In: Kaumbutho P G and Simalenga T E (eds.), 1999. Conservation tillage with animal traction: a resource book of the Animal Traction Network for Eastern and Southern Africa (ATNESA). Harare. Zimbabwe. 173p. A publication supported by French Cooperation, Namibia. http://www.atnesa.org. United Republic of Tanzania (2017) Climate-Smart Agriculture Guideline. Ministry of Agriculture Livestock and Fisheries. United Republic of Tanzania (2014) Agriculture Climate Resilience Plan. Ministry of Agriculture Food Security and Cooperatives. United Republic of Tanzania (2008).Study on strategies for addressing negative effects of climate change in food insecure areas of Tanzania. Dar-es-Salaam, Tanzania: Ministry of Agriculture, Food Security and Cooperatives. United Republic of Tanzania (2015) Climate-smart Agriculture Program. Ministry of Agriculture Food Security and Cooperatives. REFERENCES | false |
# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE AND FOOD SECURITY Participatory Agricultural Development and Empowerment Project (PADEP) ENVIRONMENTAL AND SOCIAL FRAMEWORK Environmental Guidelines for PADEP March 2003 TABLE OF CONTENTS 1. BACKGROUND .............................................................................................................1 1.1 Introduction..........................................................................................................1 1.2 Project description ...............................................................................................1 2 SUBPROJECT TYPOLOGIES AND THEIR POTENTIAL ENVIRONMENTAL IMPACTS AND MITIGATION MEASURES ...............................................................3 2.1 Introduction and Background ..............................................................................3 2.2 Benefits of PADEP Subprojects ..........................................................................5 2.3 Environmental impacts of PADEP subprojects and proposed measures.............7 3. THE ENVIRONMENTAL ASSESSMENT AND APPROVAL PROCESSES FOR PADEP SUBPROJECTS.................................................................................................21 4. GUIDLENES FOR INSTITUTIONAL ARRANGEMENTS, TRAINING NEEDS AND COST ESTIMATES FOR MITIGATION MEASURES – PROCEDURES FOR COST ESTIMATE..................................................................................................34 5. PADEP SENSITIZATION MEETINGS AND LAUNCHING WORKSHOPS TO ADDRESS ENVIRONMENTAL ISSUES .....................................................................35 6. COMPLIANCE OF PADEP ACTIVITIES WITH BOTH WORLD BANK AND TANZANIA’S POLICIES, GUIDELINES, LEGISLATION AND REGULATIONS..............................................................................................................37 6.1 Compliance with World Bank safeguard policies ...............................................37 6.2 Compliance with Tanzania’s environmental management policies.....................39 7. PUBLIC CONSULTATION PROCESS.........................................................................41 Annex 1: Sample check lists for sub-projects.......................................................................43 i LIST OF ABBREVIATIONS AG Attorney General ASDS Agricultural Sector Development Strategy CADS Community Development Subprojects CIS Community Investment Subprojects CSC Community Subproject Committee DC District Commissioner DED District Executive Officer DFT District Facilitation Team DMT District Management Team DoE Division of Environment DPO District Project Officer DPO District Project Officer EIA Environmental Impact Assessment EMP Environmental Management Plan EP Environmental Permit EP Environmental Profile ESMP Environmental Social Management and Plans EU European Union FAO Food and Agricultural organization FGIS Farmer Group Investment Subprojects GDP Gross Domestic Product GoT Government of Tanzania IPM Integrated Pest Management IPNS Integrated Plant Nutrition Techniques/Strategies IRA Institute of Resource Management LEAT Legal Environmental Action Team MAC Ministry of Agriculture and Cooperatives MAFS Ministry of Agricultural and Food Security MNRT Ministry o f Natural Resources and Tourism MRALG Ministry of Regional Administration and Local Government MRP Minjingu Rock Phosphate MW Ministry of Water MWLD Ministry of Water and Livestock Development NEMC National Environmental Management Council NEP National Environment Policy NGOs Non-Governmental Organizations NPSC National Technician Steering Committee NRT National Resource Team NSSF National Social Security Fund NTSC Natural Technician Steering Committee OD Operational Directive PADEP Participatory Agricultural Development and Empowerment Project PCU Project Coordinating Unit PEP Provisional Environmental Permit PLUM Participatory Land Use planning and Management PM Prime Minister POM PADEP Operation Manual PPP Policy, Plan or Programme PRA Participatory Rural Assessment ii RC Regional Commissioner RDS Rural Development Strategy RPF Resettlement Policy Framework SC Subproject Committee SEA Strategic Environmental Assessment SPC Subproject Cycle T.S.A.E Tanzania Society of Agricultural Engineers TASAF Tanzania Social Action Fund TRC Technical Review Committee UN United Nations UNCHS United Nations Commission for Housing and human settlements VEOs Village Executive Officers WB World Bank WEO Ward Executive Officer iii EXECUTIVE SUMMARY This report provides guidelines for assessing possible environmental and social impacts of the subprojects to be funded under the Participatory Agricultural Development and Empowerment Project (PADEP). The guidelines provide a framework for screening community and farmer groups subprojects to determine their environmental and social impacts. The guidelines furthermore show how determination should be made and appropriate mitigating measures incorporated into the subprojects report. The main objective of PADEP is to raise the production of food, incomes, and assets of participating households and groups in a sustainable manner through the implementation of small agricultural development sub-projects planned and managed by groups of community members and farmers. The project has two components: (i) Community Agricultural Development Sub-projects; and (ii) Capacity Building and Institutional Strengthening. The total project cost is estimated to be US$ 70.6 million equivalent, of which IDA will finance US$ 56.0 million, beneficiaries will contribute US$ 12.0 million, and Government (national and district councils) will provide US$ 2.6 million. The project will provide grants to communities and farmer groups for investment in agricultural development subprojects, focusing primarily on improving soil fertility and land management, adopting sustainable agricultural technologies and increasing efficiency in inputs and outputs marketing. The soil fertility and land management subprojects will included watershed management for soil and water conservation, conservation tillage and efficient use of inorganic fertilizers. Similarly, under the adoption of sustainable agricultural technologies, subprojects such as integrated plant nutrition techniques/strategies (IPNS), integrated pest management, water harvesting techniques, improvement of traditional irrigation schemes, improved livestock production, introduction of non-traditional crops and rehabilitation of rural infrastructure will be undertaken. Finally, subprojects aiming at increasing efficiency in input and output marketing like supply of farm inputs, rural processing of agricultural and livestock products as well as improvement of products marketing will be funded. There are several positive socio-economic and environmental impacts that are expected due to implementation of subprojects which are eligible for PADEP funding. Amongst them are: improved skills for farmers; improved soil fertility and better land management; higher degree of environmental awareness; increased productivity; increased land, soil and water conservation; improved soil structure due to the use of manure and organic fertilizers; value added due to processing; and reduced post harvest losses through improvement of rural storage facilities. While beneficial subprojects are likely to represent a substantial portion of overall PADEP funded subprojects, it is recognised that negative environmental and social impacts are also likely to be generated in the course of implementation of the aforementioned subprojects. In this report, the typical environmental and social impacts for each of the likely subprojects have been analysed, and mitigation measures to be deployed have been proposed. Overall, PADEP which is a community driven development (CDD) project is classified as Category B project. However, since the subprojects to be supported by PADEP are small and because rural people will be the drivers of the subprojects, the process of environmental and social screening has been made simple and informative. The process will consist of the following steps: preparation of environmental profiles; assigning category to a subproject; scooping and public consultations; conducting environmental assessment; review and approval of environmental assessment reports; and disclosure and appeal procedures. These steps have been described in details to enable districts and communities understand the process involved. An environmental and social checklist by subproject types has been included to assist district facilitation teams, communities and farmer groups in the screening process. The environmental screening process, therefore, will include questions pertaining to safeguard policy requirements. The subsequent EA work will be carried out based on the screening results and related recommendations on subproject’s category. For example, as a result of the environmental screening process, the resulting EA work may also require a subproject-specific Pest Management Plan based on Integrated Pest Management approaches, or Resettlement Action Plan. If the later is being prepared as a result of the EA work, the RAP will be a separate document and disclosed separately after being cleared by NEMC and the Bank. The environmental assessment (including social and socio-economic aspects) itself will follow a number of steps, including impact assessment - based on screening and scoping exercise; analysis of alternatives - to enhance the design of a subproject, including do nothing alternative; predictions – to provide information on the potential implication of the proposed subproject; evaluation of significance – to determine the predicted or measured change in an environment and social attributes; identify mitigation measures – to reduce adverse environmental and social impacts; and public consultations – with affected or interested groups and NGOs during screening, scooping and preparation of ToR and EA report. iv The review and approval of Category B environmental assessment report, which includes social aspects will be done by the National Environmental Management Council (NEMC), or an agency accredited by NEMC, which is responsible for EIA clearance in Tanzania. The EA report will include a section on the Environmental and Social Management Plan (ESMP). For subprojects which are likely to increase pest problems, a subproject- specific Pest Management Plan (PMP) based on Integrated Pest Management (IPM) will be prepared. In subprojects that are expected to introduce changes in access to land or changes in ownership and use of land and property, a concise Resettlement Action Plan (RAP) will be prepared according to the Resettlement Policy Framework (RPF), which has been disclosed separately. The institutional arrangements will seek to promote and enhance efficiency, effectiveness, transparency and accountability, reduce red tape and bureaucracy. Instead, they will aim at strengthening community participation, empowerment and ownership of processes leading to the subprojects. The Community Subproject Committee (CSC) and Farmer Groups Subproject Committee (FGSC) will be responsible for overseeing the preparation of EA reports and implementation of agreed mitigation measures for community investments (CIS) and farmer groups investments (FGIS) subprojects, according to the environmental and social plan (ESMP), Resettlement Action Plan (RAP) and project-specific Pest Management Plan (PMP). The District Facilitation Team (DFT) will be responsible for assisting the communities in preparing their specific ToRs and EA reports and developing ESMP and RAP plans. The DFT will also monitor and supervise the implementation of these plans and report progress back to PADEP. At national level, PADEP/Ministry of Agriculture and Food Security (MAFS) Environmental Assessment Unit will be responsible for developing the generic Terms of Reference (ToRs) for EA, capacity building and backstopping of districts and supervision of implementation of ESMP, RAP and project-specific PMP based on IPM. Resources will be made available for training of MAFS EU staff, DFT and communities to identify and address environmental and social issues of the subprojects. The costs of capacity building for environmental assessment and social aspects shall be part of the component 2 of the project. The estimated costs of undertaking training in environmental and social assessment will be determined according to the needs assessment. The Environmental Assessment and Social aspects training manual prepared by NEMC will provide the basis for developing project-specific modules. Training on Bank safeguards will be added into the modules prepared by PADEP consultant. Public understanding about the proposed subprojects and their possible environmental and social impacts will be key to their successful implementation. These environmental and social issues shall therefore be fully covered in the participatory assessment leading up to selection of the proposed subprojects, and in subsequent design. The District Facilitation Team (DFT) shall be fully prepared to lead public discussion of environmental and social issues. In order to raise awareness of communities about the potential environmental and social impacts of PADEP funded activities, a number of sensitisation meetings will be held. These will include meeting with village leaders, village assembles, workshops to launch implementation of mitigation plans and seminars to discuss various environmental and social assessment themes. PADEP will design communication strategy to enhance consultations. This will include the right choices of the agenda of meetings, launching workshops and seminars, media for message delivery; cultural considerations; and publicity or advocacy activities. PADEP will ensure that the World Bank environmental and social safeguard polices are adhered to. The safeguard policies that are triggered by the proposed PADEP project are: OP/BP 4.01 Environmental Assessment, OP 4.09 Pest Management, OP 4.12 Involuntary Resettlement, and OP 7.50 Projects on International Waterways. To the extent that subprojects trigger World Bank safeguard policies, subproject- specific safeguard documentation, such as subproject PMPs, subproject Dam Safety Measures and subproject RAP will be prepared. v PADEP Environmental Assessment 1. INTRODUCTION AND BACKGROUND 1.1 Introduction Environmental Assessment (EA) is a process used to evaluate projects’ potential environmental risks and impacts in the area of influence; examines project alternatives; identifies ways of improving project selection, siting, planning, design, and implementation by preventing, minimizing, mitigating, or compensating for adverse environmental impacts and enhancing positive impacts; and includes the process of mitigating and managing adverse environmental impacts throughout project implementation. Whenever feasible, preventive measures are favoured over mitigatory or compensatory measures. This report provides guidelines for assessing possible environmental and social impacts of the subprojects. The guidelines indicate how projects should be screened to determine their environmental and social impacts. The guidelines furthermore show how determination should be made and appropriate mitigating measures incorporated into the subprojects report. The guidelines specify institutional responsibilities for undertaking environmental assessment including the social aspects, implementation of preventive, mitigatory or compensatory measures, and monitoring and evaluation. The guidelines also set out the criteria according to which a project would be disqualified for support as a result of likely environmental or social impact. 1.2 Project description The Government of Tanzania with assistance from the World Bank has prepared the “Participatory Agricultural Development and Empowerment Project (PADEP)”. The main objective of the project is to raise the production of food, incomes, and assets of participating households and groups in at least 840 villages in a sustainable manner through the implementation of small agricultural development sub-projects planned and managed by groups of community members and farmers. This objective will be achieved by: (i) empowering self-selected rural communities and farmers' groups to make decisions regarding choice of sustainable and remunerative productive technology; (ii) sharing of costs by the public sector and participants, and hence sharing the risk of adoption of improved technologies, again for self-selected participants; (iii) enhancing demand for products and services provided by the private sector in rural areas by increasing the purchasing power of participating groups and encouraging the growth of savings; (iv) promoting improved land and crop husbandry practices by participants; (v) supporting the ongoing decentralization process at the district level; and (vi) partially financing maintenance and/or construction of roads, bridges, and other small sub-projects to improve access to markets. The project has two components: (i) Community Agricultural Development Sub-projects; and (ii) Capacity Building and Institutional Strengthening. The total project cost is estimated to be US$ 70.6 million equivalent, of which IDA will finance US$ 56.0 million, beneficiaries will contribute US$ 12.0 million, and Government (national and district councils) will provide US$ 2.6 million. Component 1: Community Agricultural Development Sub-projects This project component will consist of (a) Community Investment Sub-projects (CIS); and (b) Farmer Group Investment Sub-projects (FGIS). The aim of this component is to empower rural communities and farmer groups to make decisions to improve their economic well-being and to act on them. Village Councils and organized farmers’ groups will have the primary responsibility for using participatory approaches in implementing small-scale investment activities supported by the project, including identification, undertaking environmental assessment, planning of subprojects, implementation of technical recommendations, local procurement of inputs, contracting of service providers and monitoring and evaluation. The project will build capacity of local authorities, communities and farmers' groups by conducting tailor-made basic training in participatory methodologies (PRA), sub-project cycle, basic financial and procurement skills, participatory monitoring and evaluation (PM&E), environmental and social assessments, and HIV/AIDS awareness and prevention. A community is defined as a single village, or a significant portion thereof, with a common investment interest. Thus a community sub-project would be any investment that draws public 1 PADEP Environmental Assessment interest and brings common benefits. A "Farmer Group" is defined as a small group (10 - 40 households) of the same village in which members have voluntarily agreed, with endorsement of their Village Council, to engage in an investment sub-project that introduces technological innovation. Possible sub-projects include: soil fertility and better land management (watershed management for soil and water conservation, restoration of soil fertility using rock phosphate, conservation and no tillage techniques, and fuel efficiency technologies - biogas); agricultural investments and technologies (integrated plant nutrition strategy (IPNS), integrated pest management (IPM), rainwater harvesting, improvement of traditional schemes, production of non-traditional crops and improved livestock); and input-output marketing (production of organic fertilizers, primary processing of crop and livestock products, contract farming etc.). Criteria for approval of sub-projects will include gender balance, sustainability and empowerment of rural communities. In order to share risks involved in adopting new improved technologies, efforts of communities and farmers' groups will be complemented with direct transfers of financial resources to them (through local governments) on a matching-grant basis. This will allow them to shop and compare prices among several suppliers of goods and services needed to implement their sub-projects. Mechanisms for community-driven development will be introduced in a phased manner, to allow for improvements in the course of project implementation. Before implementing the sub-projects, each Village Council or farmer group committee will undergo a participatory planning process to identify key challenges and practical ways to overcome them. The sub-projects thus derived will then be costed and the implied share of the cost to the beneficiaries, including mitigation measures for the likely environmental problems made clear. If the beneficiaries wish to undertake the project, it will be submitted for approval to the District Facilitation Team (DFT) of the District Authority. With each participating community or farmers group, the cycle of sub- projects will unfold over three years. The initial year will be devoted to capacity building, PRA, and identification of the sub-projects. The second and third years will be devoted to implementation. For CIS, beneficiaries will contribute (labour, materials or in cash) at least 20% of total sub-project costs and the project will contribute the difference up to a maximum of US$ 35,000 equivalent per village. For FGIS, the project will contribute in cash 50% of the cost of consumable inputs (seeds, fertilizers, and plant protection chemicals) up to US$ 25 equivalent per household per year for a maximum of 2 years, and up to US$ 11,000 equivalent per village. The total project contribution for CIS and FGIS subprojects per village will be US$ 46,000 equivalent. This amount includes all costs related to preventive or mitigation measures of environmental and social problems due to implementation of the chosen subprojects. The project will also contribute up to 80% of other costs, up to a maximum of US$ 750 equivalent per FGIS. Other costs might cover, for example, advisory services for effective marketing, repair of access roads, small infrastructure for grading or sorting, and other activities. Farmers participating in the group investment sub-projects will be required to have a savings account and to deposit their 50% share into the account prior to receiving the matching grant. At the end of the first year, they will be required to deposit a portion of the value of the initial grant, plus another 50% down payment on the second year's cost of consumable inputs. In this way, farmers will build up savings adequate to sustain use of the technology at the completion of the sub-project cycle. They will also build up a relationship with a local bank and with input dealers. Component 2: Capacity Building and Institutional Strengthening This component enhances the institutional and human capacity to ensure that the sub-projects chosen are adequately considered in key dimensions, including environmental, economic, and social, and implemented with acceptable quality. At the community/village level the project will finance technical assistance and training to village/farmer groups committee members with the aim to support preparation, implementation, monitoring and evaluation of sub-projects. Specific training needs will be identified during the PRA process, and will include environmental and social assessment, and managerial and technical issues relevant to the success of the subprojects. Basic business skills, such as bookkeeping and management of business relations with providers of services and inputs will be included. Grants of up to US$ 5,000 equivalent would be provided for capacity building to communities after they complete 2 PADEP Environmental Assessment the PRA exercise. Resources will be used for need-based and "just in time" technical assistance and training, particularly at the local levels, and to hire in advisory services as needed. In all participating district councils the project will support training to upgrade capacities in participatory planning methodologies, project implementation, monitoring and evaluation, financial and procurement management skills, environmental and social assessments, and public-private partnership in service delivery. Staff of the district councils will also undergo training to enable them guide communities and farmers' groups as needed. Technical assistance will be provided in the preparation of District Agricultural Development Plans (DADPs), which are integral part of the overall District Development Plans (DDPs). Under this component conditional block grants to the districts will be in cash in the amount of US$ 175,000 equivalent for three years. The District Councils will contribute 10% (US$ 17,500 equivalent). Planning for the use of these funds will be the responsibility of the District Councils through the DFTs. Support of the project at national level will include funding for capacity building in key entities and for additional analytical work to underpin ongoing reforms. The capacities of national institutions responsible for policy analysis and regulatory functions, such as planning, monitoring and evaluation, seed agency and plant protection units will be strengthened through training, technical assistance and provision of required equipment. The project will also finance various policy studies aiming at reviewing, harmonizing and rationalizing agricultural taxes, levies and fees on crop and livestock sub- sectors. Other studies to be supported will cover surveys of sectoral performance and beneficiary assessments. The project will support further development and updating of the agricultural sector monitoring and evaluation system, and improvement of its management information system (MIS). In addition, the project will support the implementation of the Seed Act (2000) and the Plant Breeders Right Act (2002), which provide the regulatory framework for seed industry, including the establishment of Seed Executive Agency. The project will carry out the rehabilitation of four strategically located soil testing laboratories, provide the required laboratory chemicals and equipment, including soil-testing kits for on-site soil diagnosis. Finally, the project will finance the national coordination and facilitation unit operating costs. Overall, the national level capacity building and institutional strengthening support budget amounts to US$ 8.9 million equivalent. The framework for environmental and social management under the PADEP project is intended to safeguard the health and resources of rural people in a way that is simple enough to be implemented within the context of a community driven developmental initiative. The administrative procedures are therefore simple but sufficient to accomplish the desired objective. 2. SUBPROJECT TYPOLOGIES AND THEIR POTENTIAL ENVIRONMENTAL IMPACTS AND MITIGATION MEASURES 2.1 Subproject Typologies In the PADEP Guidelines for Preparation and Implementation of Community Agricultural Development Subprojects it is indicated that community and farmer group agricultural investments would focus on the following thematic areas: • Soil fertility and better land management • Agricultural technologies • Inputs and outputs marketing The types of likely projects eligible for financing under this categorization, with some examples, are presented in Table 2.1. This list is not exhaustive. 3 PADEP Environmental Assessment Table 2.1: Types of possible projects eligible for financing by PADEP Type Possible subprojects Examples Soil fertility and better land management Watershed management for soil and water conservation Conservation tillage Efficient use of inorganic fertilizers Fuel efficient technology Construction of contours, protection of gullies, construction of terraces, agro-forestry, establishing and enforcing by-laws, bulking of seed/plant materials required for agro-forestry, woodlot establishment, promotion of gender awareness in soil and water conservation Improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion, use of green manure Use of rock phosphate, use of high analysis fertilizers Biogas technology that utilizes manure and reduces use of fuel to safeguard forests Agricultural technologies Increase productivity Integrated plant nutrition techniques/strategies (IPNS) Integrated pest management (IPM) Increased use of labour saving technologies Use of organic manure in combination with mineral fertilizers, production and use of bio- fertilizers Use of organic manure in combination with mineral fertilizers, production and use of bio- fertilizers Observation, preventive and intervention methods in crops, particularly vegetable and fruit production Safe use of pesticides in combinations with improved management related to IPM approaches Use of farm implements, such as ox-drawn ploughs, ridgers, rippers, weeders, power tillers and use of herbicides, etc Use of rainwater harvesting techniques Improvement of traditional irrigation schemes Improvement in livestock production Production of non-traditional crops Rehabilitation of infrastructure Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc Rehabilitation of weirs, irrigation canals and construction of division boxes Dairy animals, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dips, etc Production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture Rehabilitation of soil testing laboratories, rural roads, bridges, storage facilities and other rural infrastructure 4 PADEP Environmental Assessment Input/output marketing Supply of farm inputs Initial processing of agricultural and livestock products Improvement of crop produce marketing Input shops at farm level, etc Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, processing of dairy products, etc Establishment of village marketing centres, construction of market yards, grain storage, group- led grain marketing, etc Source: PADEP – Guidelines for Preparation and Implementation of Community Agricultural Development Projects (draft) Many subprojects funded by PADEP can have positive impacts on the surrounding environment if they are well designed and implemented. Watershed management, for example, can enhance soil and water conservation; Integrated Pest Management (IPM) can prevent increased use of pesticides through use of other measures to keep pest populations low. For example, breeding and cultural practices are used to make the environment less hospitable to pests and to keep the crop healthy and resistant or tolerant to attack. Other subprojects are also expected to produce positive socio-economic and environmental impacts, which include, based on the type of projects eligible for PADEP funding: • Improved skills for farmers • Improved soil fertility and better land management in general • Higher degree of environmental awareness • Increased production per unit area, with reduced pressure to expand area • Expected increased income and higher living standards, including better housing, better nutrition • Strengthened farmers’ groups and organizations • Improved gender awareness • Improved Land, soil and water conservation practices • Increase in soil fertility through use of livestock manure and other organic matter • Value added produce through processing and better marketing strategies • Forest conservation through use of fuel efficient technologies 2.2 Benefits of PADEP Subprojects Environmentally beneficial projects are likely to represent a substantial portion of PADEP subprojects. The benefits of this type of subprojects are long-term rather than short-term, and will not be limited to the members of village community. Below are a few examples of environmentally beneficial subprojects that will be financed by PADEP: • Watershed management for soil and water conservation: The primary advantage of watershed based management for soil and water conservation is that it provides the link between the resources and the system that generates and modifies them. Watershed forms a nested hierarchical system of units, which link the smallest hill slop to the local, district and regional watershed. The linkages of the watershed to runoff generation also provide for the necessary integration of water quantity management with planning for water quality and erosion and sedimentation control. • Conservation tillage: This offers numerous benefits. Added crop residue and minimal tillage both provide the effect of drastically reducing runoff of soil and agrochemicals. The result is to minimize impact on the water ecosystem. Conservation tillage main benefits are: decreased erosion, improved water quality, better long term production, higher soil moisture, improved water infiltration, decreased soil compaction, improved soil tilt, more biological activity, reduced release of carbon gases and reduced air pollution. Reducing and eliminating tillage helps increase soil fertility. Residue left on the soil not only serves in the capacity of soil conservation it also adds organic matter to the soil as it decomposes. Soil fertility, tilt, and structure are improved by conservation tillage practices. 5 PADEP Environmental Assessment • Fuel efficient technology: Biogas is one of the fuel-efficient technologies, which will be promoted by PADEP as one of the subprojects. The main positive impacts of biogas technology include: (i) conservation of the forest resource as a result of decreased use of fuel wood which will also result in carbon sequestration by reduction in the cutting of the forest, (ii) renewable source of energy, (iii) reduces workload on the part of women to collect fuel wood, (iv) cheaper when compared to kerosene, (iv) promotes a nutrient cycling strategy. Considering the biogas technology as gas generation and slurry production for soil conditioning purposes, it becomes apparent that it produces positive impacts at farm and public levels as shown in Table 2.2. below. Table 2.2: Positive impacts from biogas at farmer and public levels Farmers’ interests Public interests Reduction of pollutants Quality improvement of organic fertilizer/reduction of mineral fertilizer Reduction of odour Risk of increased NH4 Positive impact on resource protection Reduction of the use of pesticides Positive impact on climate protection Stabilization & improvement of soil fertility/reduction of desertification Compared to other fuels positive emission behaviour of biogas • Integrated plant nutrition techniques/strategies (IPNS): The strategy optimises all aspects of nutrient cycling – supply, uptake, and loss to the environment – to improve food production. At farm level, IPNS aims to optimise the productivity of nutrient flows that pass through the farming system during a crop rotation. This means application of external plant nutrient sources and amendments, efficient processing, and recycling of crop residues and on-farm organic wastes that limit plant nutrient losses. In the process, IPNS empower farmers by increasing their technical know-how and decision-making capacity, and promote changes in land use, crop rotation, and interactions among forestry, livestock and cropping systems in support of agricultural intensification. At village or farming community level, IPNS take into account plant nutrient sources outside cropped areas, including those in irrigation water and flood sediments, livestock manure, and forest litter and organic material that is physically transferred from forest and pastures. IPNS promotes rationalization in the transfer of organic matter and plant nutrients from non-cropped to cropped areas, and the mobilization of unused nutrient resources or the saving of valuable nutrient sources diverted as domestic fuel, raw materials for building or for industrial purposes. • Integrated pest management (IPM): This has broad application since it integrates management of all pests, it is a holistic approach, ecologically based and can be applied to any ecosystem. IPM integrates multiple pest management tactics (chemical, biological, cultural, mechanical) and management of multiple pests (insects, weeds, disease pathogens, nematodes, vertebrates, etc). IPM incorporates environmental and social concerns. The main goals of IPM are: sustain resource (agricultural and natural over the long term), more rational use of pesticides, reduce environmental contamination and costs, utilize natural biological controls, minimize pesticides resistance problems, food safety (reduce residues of pesticides on food products) and worker safety (rely on pest management tactics that are safe for workers). • Use of rain harvesting techniques: High intensity rains commonly cause devastating effects on the environment particularly in areas of low or no vegetation. Runoff arising from rainwater often causes erosion with subsequent land degradation and sometimes sets the desertification process in motion. Preventing and mitigating soil erosion may achieve environmental conservation. One method to achieve this is through runoff control by rainwater harvesting methods. Surface catchment is the most effective among the rainwater harvesting methods that could mitigate the possible environmental hazards caused by rain. • Rehabilitation of infrastructure: High marketing costs are partly related to the poor rural infrastructure, including poor condition of roads, lack of bridges on some rivers and streams and poor storage facilities. By supporting the rehabilitation of these rural infrastructure, PADEP will be able to reduce transaction costs, through linking rural producer to the urban markets, and reducing post harvest losses. Reduced transportation costs due to accessibility of 6 PADEP Environmental Assessment rural areas will increase profit margins of various crops produced by farmers, hence contribute to reduction of rural poverty. Loss of soil fertility has been identified by the Soil Fertility Initiative document as the biggest threat to smallholder agricultural development. By supporting rehabilitation of strategically located soil testing laboratories, technical services would be readily available to districts and communities, on demand-driven basis. The PADEP may also generate environmental benefits through a variety of other mechanisms, including: • Improved awareness and concern for environmental issues on the part of beneficiaries, local communities and districts • Training of environmental specialists, thus increasing the availability of staff conversant with environmental issues within PADEP and districts • Generation of environmental assessment guidelines that are then used by other institutions or line ministries and districts, or are adopted by the National Environmental Management Council (NEMC) for enhancing environmental procedures. • Improvement of tradition irrigation schemes • Improved livestock production • Introduction of non-traditional crops 2.3 Environmental impacts of PADEP subprojects and proposed mitigation measures Subprojects may have impacts that change environmental characteristics of the project area, and these impacts may be ambiguous or negative in their effects. The environmental screening process, therefore, will include questions pertaining to safeguard policy requirements. The subsequent EA work will be carried out based on the screening results and related recommendations on subproject’s category. For example, as a result of the environmental screening process, the resulting EA work may also require a subproject-specific Pest Management Plan based on Integrated Pest Management approaches. 2.3.1 Watershed management of soil and water conservation The project will support watershed management for soil and water conservation subprojects, including construction of contours and terraces, protection of gullies, bulking of seed/planting materials required for agro-forest, establishment of woodlot, enforcement of catchment management by-laws and creation of awareness in soil and water resources conservation. Watershed management subprojects are undertaken for purposes consistent with sound environmental management, but they may also generate environmental impacts that warrant mitigation. These include changes in land, water, morphological and physical characteristics, as well as quality and quantity of these resources; changes in natural habitats, loss of biodiversity or changes in biodiversity characteristics of both fauna and flora, infringement of property rights and possible intrusion on social/cultural resources, such as archaeological sites and religious shrines. 2.3.2 Conservation tillage Examples of conservation tillage subprojects include improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion and use of green manure. Impacts during conservation tillage are usually associated with management aspects. While conservation tillage offers many advantages, it does require a change in agricultural practice. If certain elements are not managed correctly, impact can occur. Amongst these are: soil and ground water contaminations, river pollution, increased herbicide use, weed infested fields, increased use of fertilizers, increased diseases, soil compaction, etc. Table 2.4 summarizes possible impacts and their mitigation measures. The most important mitigation measures related to conservation tillage are developing subproject-specific PMP based on IPM approaches, integrated weed management, proper fertilization management, residue management, etc. 7 PADEP Environmental Assessment Table 2.3: Typical Impacts and Mitigation Measures of Watershed Management for Soil and Water Conservation Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Changes in Land, Water, morphological and physical characteristic as well as quality and quantity of resources Awareness raising Participatory land use planning and management (PLUM) By-laws and their effective enforcement Joint management programmes Biological Environment Natural Habitats Fauna and Flora Changes in natural habitats Loss of biodiversity Changes in biodiversity characteristics of both fauna/ flora and ecosystems Careful site selection Use of indigenous plant species Biodiversity Assessment and monitoring Developing subproject-specific EA and related Environmental Management Plan (EMP) Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Infringement on property rights Possible intrusion on physical/cultural resources e.g. archaeological and religions shrines Awareness raising Provision of alternative income sources Enforcement of by-laws Compensation as per provisions of the resettlement policy framework Table 2.4: Typical impacts and mitigation measures of conservation tillage Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Contamination of ground water table and river pollution Soil conservation measures Fertilization management Proper residue management Enforcement of air quality standards Awareness raising Biological Environment Fauna and Flora Disturbance on ecological functioning of farming systems Integrated weed management Promote Integrated pest management approaches Proper residue management Biodiversity assessment and monitoring Subproject-specific PMP based on IPM approaches “Social Environment” Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Loss of historical/cultural sites Reluctance to reduce ploughing Proper site selection Propose disease management Awareness raising 8 PADEP Environmental Assessment 2.3.3. Efficient use of inorganic fertilizers There are three examples of possible subprojects on efficient use of fertilizers among the PADEP's possible subproject types. These are use of rock phosphate, use of high analysis fertilizers and use of organic manure. Table 2.5 summarizes the most frequently encountered environmental impact, particularly for rock phosphate, related to mining and processing. In phosphorus-deficient soils, Minjingu rock phosphate (MRP) exploited from Manyara Region near Lake Manyara is as effective and profitable as imported triple super phosphate (TSP). Farmers are applying 125-250 kg P/Ha as a capital investment, and expect a five-year residual effect. A particular important environmental consideration in the case of Minjingu rock phosphate is dust, presence of heavy metals and radionuclides. MRP like other Rock Phosphate (RP) mines contains heavy metals. Of the metals contained in MRP, Cadmium (Cd) represents the greatest concern because of the potential human risks via transfers within the food chain. The Cd level is considered low (9 mg/kg) and within the same range as those reported from other RP mines. Despite this, there is a need to monitor the Cd levels in soils as phosphate fertilizers are continuously being applied to soils. With regard to radioactive materials, the levels of radionuclides are not much different from the levels found in other RP mines. Table 2.5: Typical impacts and mitigation measures of efficient use of inorganic fertilizers Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Stalinization of soils Contamination of groundwater Pollution of surface water Heavy metals Dust Air pollution Conduct training on safe use and handling Use of high grade fertilizers Salinity monitoring Use of masks to prevent inhaling of dust Stored and transported in closed containers Bringing the moisture content to 7-8 percent Enforce air quality standards Biological Environment Fauna and Flora Promoting weed growth Loss of natural plant and wildlife habitats and species Increased pest problems Conduct training on safe use of fertilizers Weed control, e.g. through lining of irrigation canals Biodiversity assessment and monitoring Promoting Integrated Pest Management (IPM) approaches Developing subproject- specific Pest Management Plans (PMP) Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Loss of natural recreational, historical and archaeological sites Health risks Increased use of labour- saving technologies Land reclamation Disease surveillance Provision of protective gear Proper screening of herbicides Training on IPM approaches 9 PADEP Environmental Assessment 2.3.4 Fuel efficient technology Fuel efficient (e.g. biogas technology subprojects) do not usually result in major impacts. Table 2.6 summarizes the most frequently encountered environmental impacts of these types of subprojects. PADEP fuel-efficient technology subprojects will finance construction of biogas plants. Biogas subprojects are likely to increase ammonia content of digested manure. Combined with a slightly increased pH will a higher risk of ammonia losses in treated slurry compared to untreated manure. Therefore, digested slurry must be handled more carefully and farmers have to follow manure-handling instructions given by the extension service officers. Table 2.6: Typical impacts and mitigation measures of fuel-efficient technology Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Ground water pollution Ammonia losses Control surpluses of slurry Cover the soil Biological Environment Natural Habitats Fauna and Flora Effect on vegetables and fodder Locate far from residential settings Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Odour complaints Lost income opportunity, e.g. for charcoal traders Different design concept Build far from residential houses Provision of alternative income sources 2.3.5 Increasing productivity Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers are subproject activities supported by PADEP. Table 2.7 shows some typical impacts of these subprojects. All studies conducted in the country have indicated that the application of organic manures in combination with mineral fertilizer gives higher crop yield increases than when both are applied separately. In addition, studies have concluded that Nitrogen and phosphorous applied in combination have resulted in significantly high yield. The potential impacts from these subprojects are salinization of soil, contamination of surface and ground water, loss of plant species. 2.3.6 Integrated plant nutrition techniques/strategies (IPNS) PADEP will support IPNS subprojects with the aim to address nutrient management, including improving organic matter in the soil, increasing plant available nitrogen, and combining organic and inorganic fertilizers. These interventions have the potential to increase and sustain production levels, increase the economic potential of a production system, and counteract and minimize environmental pollution. However, the interactions between nutrient applications and other agricultural activities and the likelihood of unforeseen problems such as environmental contamination of soil, surface and ground water should be a great concern and a monitoring system with key indicators should be developed. Table 2.8 summarizes typical impacts and mitigation measures of IPNS. 10 PADEP Environmental Assessment Table 2.7: Typical impacts and mitigation measures of increasing productivity through use of organic manure in combination with mineral fertilizers and bio-fertilizers Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Salinization of soils Contamination/pollution of surface and groundwater Conduct training on safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility management Public awareness raising Biological Environment Fauna and Flora Loss of plant species Promoting weed growth Increased pest problems Weed control measures, e.g. lining of irrigation canals Biodiversity assessment and monitoring Promoting IPM approaches Developing PMP which are subproject-specific Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Change of scenery Health risks Increased use of labour- saving technologies Awareness and training on safe use Promote high value crops Provision of protective gear Proper screening of herbicides Training in IPM approaches Table 2.8: Typical impacts and mitigation measures of integrated plant nutrition techniques / strategies (IPNS) Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Salinization of soils Contamination/pollution of surface & groundwater Conduct training on safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility Management Biological Environment Fauna and Flora Loss of some plant species Scientific studies on plant nutrition Promoting weed growth Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks Awareness and training on safe use Promote high value crops Provision of protective gear 2.3.7 Integrated pest management (IPM) PADEP will finance subprojects aimed at promoting safe use of pesticides in combinations with observation, preventive and intervention methods in crops, particularly vegetable and fruit production. According to FAO definition, an IPM is a pest management that in the context of the associated environment and the population dynamics of pest species, utilizes all suitable techniques and methods in as compatible a manner as possible and maintains pest population at levels below those causing economically unacceptable damage or loss. Therefore, an IPM involves a combination of various measures to ensure effective pest management without disturbing the ecosystem, reduce environmental pollution and eliminate direct and indirect health hazards to human beings. Due to changes in project 11 PADEP Environmental Assessment design, PADEP has now become demand-driven, hence subsequent to the screening procedures, each subproject will have its own case-specific Pest Management Plan based on IPM approaches. The PMP prepared in 2001 will be re-formulated and used as a guide/reference document in the preparation of subproject-specific PMPs. Table 2.9 summarizes typical impacts and mitigation measures of IPM. Most of IPM methods have little or no impacts at all, especially use of botanical pesticides like neem trees, biological control, such as concinellid beetles, intercropping, resistance varieties, etc. Typical negative impacts include soil contamination, water resources pollution, loss of animal and plant species. Table 2.9: Typical impacts and mitigation measures of Integrated Pest Management (IPM) Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Soil contamination Water resources pollution Adherence to provisions of the subproject-specific pest management plan Awareness and training Treatment/purification of water for domestic use Provision of safe watering points/structures for livestock Adopt leaching techniques Biological Environment Fauna and Flora Loss of animal and plant species Aggravating pest problems due to increased pesticides resistance Conduct Biodiversity assessment and monitoring Effective screening of pesticides entering the market Promoting and adopting IPM approaches to pest control Developing PMPs which are subproject-specific Enhanced research and extension support services Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks Awareness and training on safe handling of pesticides Pesticide-related hazards adequately addressed Enforcement of by-laws Clean-up and disposal to appropriate land fills 2.3.8 Increased use of labour saving technologies PADEP will support labour saving technologies, such as use of farm implements, such as ox-drawn ploughs, ridgers, rippers, weeders, power tillers, etc. The objective of supporting these subprojects is to increase the marginal labour productivity in the existing smallholder farms. The project will not support use of labour saving technologies to open up new areas. Table 2.10 summarizes typical impacts and mitigation measures of increased use of labour saving technologies. The potential impacts of the inappropriate use of labour saving technologies are loss of soil fertility, loss of water sources and air and noise pollution. There is also loss of plant and animal species due to the use of non-selective herbicides, accidents to human beings and potential land use conflicts. 2.3.9 Use of rainwater harvesting techniques Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc are interventions supported by PADEP. Table 2.11 summarizes typical impacts and mitigation measures of increased use of rainwater harvesting techniques. Potential environmental impacts of rainwater harvesting techniques are: land degradation at livestock watering points, 12 PADEP Environmental Assessment contamination of stored water, water and land use conflicts, loss of natural habitats, loss of fauna and flora, etc. Table 2.10: Possible impacts and mitigation measures of increased use of labour-saving technologies Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Loss of soil fertility Soil compaction, deterioration of structure Soil and water contamination due to herbicides use Employ farm management principles Use of appropriate technology Awareness raising and training in herbicides use and handling methods Effective screening of herbicides used by farmers Biological Environment Fauna and Flora Loss of plants species due to use of non-selective weed killers/herbicides Biodiversity assessment and monitoring Participatory land - use planning from the grass root levels Training on proper use and handling of herbicides Use of selective herbicides Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Gender inappropriateness, e.g. increasing of women’s burden Land use conflicts Accidents due to farm machinery operations Accidents due to unsafe handling of herbicides Participatory land-use planning at all levels Recognition of indigenous knowledge Adherence to safety regulations on herbicides handling Enforcement of by-laws governing screening of herbicides Gender awareness in selection of technology 2.3.10 Improvement of traditional irrigation schemes PADEP will finance the rehabilitation of weirs, irrigation canals, drainage systems and construction of diversion boxes. PADEP will not finance the construction of new irrigation schemes. Irrigation and drainage systems will be designed to manage water for enhancing agriculture production. There is a wide range of irrigation schemes, which can accommodate many variations in the source, and availability of water, types of climate, and form of agriculture (e.g. rivers and streams, underground water, rainwater, reservoirs etc.). However, since most of the traditional irrigation schemes in Tanzania draw water from rivers and streams, PADEP support primarily the improvement of open irrigation and drainage canals. Rehabilitation of weirs will involve appropriately designed system to provide effective and efficient supply of water. Rehabilitation of earth canals will include excavation and earthworks. If subprojects will involve rehabilitation of chacos or small dams, subproject-specific dam safety analysis in addition to subproject-specific EA will be carried out consistent with the Bank’s safeguard policy. Table 2.12 summarizes the most frequently encountered environmental impacts of small-scale irrigation and minor civil works subprojects. Irrigation subprojects often intensify agricultural production in the irrigation zone and environmental problems may result from increasing use and concentrations of agrochemicals. Such agricultural intensification can also cause accelerated nutrient loading of receiving waters, resulting in algae blooms, proliferation of aquatic weeds, and 13 PADEP Environmental Assessment deoxygenation. Other impacts from irrigation subprojects include water logging and salinization of soils, degradation of downstream surface water systems, and biotic and chemical changes to aquatic ecosystems. Abstractions of water from dams or reservoirs have the potential to cause significant hydrological disturbances. Diverting water from river systems, especially during seasonal low flows, can cause changes to riverine ecology, fisheries, and aquatic vegetation. Irrigation schemes may also cause an increase in waterborne diseases, because disease vectors proliferate in irrigation canals under some circumstances. If canals are not properly maintained, animal and human waste may be deposited into irrigation systems and spread communicable diseases. The incidence of schistosomiasis, malaria, and onchocerciasis has increased in some irrigation schemes in Tanzania due to poor drainage systems. Social problems may arise because of multiple demands for limited water resources. Water right issues cause disruption of historical land use practices. Conflicting demands for water and inequities in distribution can also cause problems. Table 2.11: Typical impacts and mitigation measures of increased use of rainwater harvesting techniques Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Siltation due to erosion Land degradation at livestock watering points Contamination of stored water Water and land use conflicts Potential floods during heavy rains Awareness & training on safe handling and storage of water Disinfection of water sources By-laws and their effective enforcement Adherence to water rights by irrigators associations Enforcement of water rights by Basin Water Officers Provision of safe watering points/structures for livestock Participatory planning Erosion control measures at the watering points. Prepare and have in place contingency/emergency plans Dam safety analysis in addition to EA of subproject Biological Environment Fauna and Flora Loss of natural habitats Loss of Fauna and Flora species Increased pest problems Introduction of alien weeds species Awareness & training on safe handling and storage Careful site selection Planting trees and other vegetation around chaco dams Biodiversity assessment and monitoring Developing subproject-specific EA and related Environmental Management Plan (EMP) Develop weed monitoring plan and control measures Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Change of scenery Health hazards e.g. malaria, schistosomiasis and other related diseases. Child accidents Infringement on property and access rights Participatory planning Alternative income sources Awareness raising to avoid accidents and provide basic knowledge on methods of preparing clean water Use of treated mosquito nets Improved drainage systems Compensation as per provisions of the RPF 14 PADEP Environmental Assessment Table 2.12: Typical impacts and mitigation measures of improvement of traditional irrigation schemes Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Introducing salinity Soil acidification Land and water use conflicts Secondary water uses (domestic, livestock) Water logging Poor water quality for downstream users caused by irrigation return flow quality Flooding and siltation of irrigation canals Reduction in irrigation water quality Contamination of water sources by agro- chemicals Dust pollution Noise pollution Construction wastes Provide drainage including disposal of water Analyse soils and monitor changes so that potential problems can be managed Participatory land and water use planning and management, e.g. WUAs and dialogues. Provide water for leaching as a specific operation Provide water for domestic and livestock water supply Include access crossings at convenient locations for people and livestock Provide for drainage of tail waters Salinity monitoring Provision of flood control and de- silting structures in subproject designs Provide plans for disposal of construction wastes Provide protective gear against dust and noise Biological Environment Fauna and Flora Loss of fauna and flora species Loss of habitat Proliferation of aquatic weeds Increased pest problems Effective screening of agro-chemicals Training in proper use and handling of agro-chemicals Adopting IPM approaches to pest management Preparing subprojects-specific PMP based on IPM approach Biodiversity assessment and monitoring and evaluation of fauna and flora species Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Increase incidence of water-borne diseases Infringement on property and access rights Increased inequity Weaker community infrastructure Educate about cause of diseases Improve health facility Disease surveillance Awareness and training By-laws and enforcement Allow sufficient time and money for extensive public participation that all affected groups are considered and that district and village institutions are involved to sustain irrigated agriculture, particularly in respect of land and water rights Include economic activity like household vegetables, fodder or growing trees for firewood Compensation as per provisions of the RPF 15 PADEP Environmental Assessment 2.2.11 Rehabilitation of rural infrastructure The project will also support small civil works including the rehabilitation of rural roads, bridges and other small infrastructure, such as, storage facilities. Rehabilitation of soil testing laboratories, marketing yards and dipping facilities will also be supported by the project. The objective of supporting small scale civil works will be to open up inaccessible rural areas and improve rural infrastructure so that marketing costs an post harvest losses are reduced. In terms of rehabilitation of the soil testing laboratories, the aim will be to enable research institutes to immediately respond to the demands for soil analyses from districts within the given ecological zone. Negative impact of minor civil works include noise pollution, generation of construction wastes and dust during the construction phase. In some cases, open pits could be left behind after the excavation of sand and aggregate materials. Loss of vegetation and habitat from excavation sites. A summary of likely impacts and mitigation measures is given in Table 2.13. Table 2.13: Typical impacts and mitigation measures of rehabilitation of rural infrastructure Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Open pits Dust pollution Noise pollution Construction wastes Contract conditions defining working practices and monitoring Consultation with stakeholders Provide plans for disposal of construction wastes Provide protective gear against dust and noise Biological Environment Fauna and Flora Loss of fauna and flora species Loss of habitat Loss of crops or livestock grazing land Provision of landfill requirement in the contracts Biodiversity assessment and monitoring and evaluation of fauna and flora species Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Infringement on access and movement for humans and livestock Health problems due to dust inhalation and noise Accidents from construction sites Improve health facilities Occupational disease surveillance Awareness and training on safety measures Subproject-specific EA required Compensation of lost plants, land or displacement according to RPF 2.3.12 Improvement in livestock production The PADEP project will also finance subprojects related to improvement of dairy farming, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dip, etc. Table 2.14 summarizes the most frequently encountered environmental impacts of improvement in livestock production. The potential impacts of improved in livestock production are overgrazing, degradation of land and vegetation, soil erosion, gas emissions, loss of natural habitats through overgrazing, 16 PADEP Environmental Assessment Table 2.14: Typical impacts and mitigation measures of improvement in livestock production Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Overgrazing Degradation of land and vegetation Soil erosion Gas emissions Awareness & training Observing land carrying capacity Establishment of stock routes Combine with biogas technology Market research Rotational grazing Zero grazing Biological Environment Fauna and Flora Loss of natural habitats through overgrazing Wildlife displacement Biodiversity assessment and monitoring Joint wildlife management i.e. integrated management Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks from use of acaricides in dips Conflicts between pastoralists and wildlife management areas Environmental risks from emptying water from dips into rivers/water sources Infringement of property and access rights Provision of protective gear Training on safe handling of chemicals and animal drugs Participatory planning and management. By-law enforcement on disposal of waste waters from the dips Compensation as per provisions of the RPF 2.3.13 Production of non-traditional crops PADEP will support subprojects that are related to the production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture. Table 2.15 summarizes the most frequently encountered environmental impacts of production of non-traditional crops subprojects. The potential impacts of production of non-traditional crops are contamination of soil, fruits and mushrooms (quality control). 17 PADEP Environmental Assessment Table 2.15: Typical impacts and mitigation measures of production of non-traditional crops Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Soil contamination by agro- chemicals Water sources contamination Treatment/purification of water for domestic use Provision of safe watering points/structures for livestock Training on agro-chemicals handling and safety measures Biological Environment Fauna and Flora Introduction of new pests Introduction of new diseases in the farming systems Quarantine / screening of imported varieties Adherence to phytosanitary regulations of Ministry of Agriculture and Food Security Biodiversity assessment and monitoring Development of subproject- specific PMP based on IPM approaches Enhanced research and extension services support to farmers growing new crops Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Fruits might be contaminated if watered by streams loaded with industrial effluents Lack of reliable markets Awareness and promotional campaigns Market research and products promotion Enforcement of by-laws Adherence to environmental quality standards. 2.3.14 Supply of farm inputs The project will support farmer groups intending to stock agricultural inputs in the rural areas. Table 2.16 summarizes the most frequently encountered environmental impacts of supply of farm inputs. Table 2.16: Typical impacts and mitigation measures of supply of farm inputs Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes from packaging materials plastics, tins and cans Awareness campaigns Proper disposal of wastes By-laws enforcement Design alternative packaging materials. Biological Environment Natural Habitats Fauna and Flora Livestock and wildlife might consume the plastic materials which are deadly to their health Ecological disruption due to overuse of pesticides and herbicides Raise awareness and training farmers in IPM approaches Enforcement of by-laws governing use and handling of agrochemicals Promoting an IPM approaches Screening / inspection of approved agrochemical 18 PADEP Environmental Assessment Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Health risks from agro- chemicals especially if repackaging is undertaken Awareness and training Provision of protective gear 2.3.15 Initial processing of agricultural and livestock products Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, and processing of dairy products, are typical examples of subprojects under this category. Table 2.17 summarizes the most frequently encountered environmental impacts of improvement in livestock production. The potential environmental impacts of initial processing of agricultural and livestock products are wastes from processing, contamination of products, noise pollution, vibrations and dust. Table 2.17: Typical impacts and mitigation measures of initial processing of agricultural and livestock products Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes from processing Contamination of products Noise pollution Vibrations Dust Provide for proper waste disposal Ensure hygienic conditions Careful site selection O & M strategies Biological Environment Natural Habitats Fauna and Flora Solid and liquid wastes from the processing might affect plant and animal species Conduct Biodiversity assessment and monitoring Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Gender concerns in ownership and operation Workers’ health in the processing plants might be affected Increased pesticides residue in foodstuff Strategic group targeting Provision of protective gears, health insurance, awareness raising Adherence to Industrial and occupational health regulations Promoting IPM approaches 2.3.16 Improvement of crop produce marketing Establishment of village marketing centers, construction of market yards, grain storage and group-led grain marketing are typical examples of subprojects to be supported by PADEP under this category. Table 2.18 summarizes the most frequently encountered environmental impacts of improvement of crop produce marketing. The potential environmental impacts of improved crop produce marketing include wastes at markets, smells and odour, change of aesthetic values, air pollution and soil contamination, etc. 19 PADEP Environmental Assessment Table 2.18: Typical impacts and mitigation measures of improvement of crop produce marketing Environmental and Social Components Impacts Mitigation Measures Physical Environment Soils Water Resources Air Quality Wastes at markets Smells and odour Change of aesthetic values Air pollution Soil contamination Waste management strategies Careful site selection Monitoring Biological Environment Fauna and Flora Livestock might consume hazardous materials from the damp sites Spread of storage pests to other locations Design an appropriate sanitary land-fill Developing subproject- specific Environmental Management Plan (EMP) Develop subproject-specific PMP based on integrated approaches Social Environment Aesthetics and Landscape Historical/Cultural Sites Human Health Human Communities Poor sanitation due to absence of sanitation facilities Infringement on property and access rights Provide for water supply and sanitation facilities Consensus building through participatory site selection and planning Compensation as per provisions of the RPF 3. THE ENVIRONMENTAL ASSESSMENT AND APPROVAL PROCESSES FOR PADEP SUBPROJECTS Since the sub-projects supported by PADEP are small and because rural people will be the drivers of the projects, the process of environmental screening must be simple and informative. The process will consist of the following steps: Step 1: Preparation of environmental profiles The preparation of an environmental profile of subprojects is an important phase in subproject planning in general and in the environmental assessment of subprojects in particular. An environmental profile is a description of the socio-economic, physical and environmental characteristics of the subproject area. The EP describes the subproject area’s development-environment situation and relationships, giving recognition to the relationship among resources, resource users, institutions, socio-economic and cultural setting. The preparation of an EP should be as participatory as possible, drawing on the knowledge of and involving the local people. Step 2: Assigning category to a subproject After basic information is collected in the profile, projects should be screened and categorized according to their likely environmental and social impact. Screening serves two purposes: • To determine which projects, of all those proposed at the identification phase of the project cycle of PADEP, need further environmental consideration, and to eliminate those likely to have harmful environmental impacts • To indicate the level of environmental appraisal that a project will require 20 PADEP Environmental Assessment Assignment of project categories at screening EA process is indicated in Box.3.1. stage of Box 3.1 Assignment of Project Categories at Screening Stage of Environmental Impact Assessment (OD. 4.01) Category A: Environmental Assessment is normally required as projects may have diverse and significant environmental impacts Category B: More limited environmental analysis is appropriate as projects may have specific environmental impacts Category C: Projects in this category are likely to have minimal or no adverse environmental impacts Environmental screening of each proposed subproject to be financed under PADEP will be done to determine the appropriate extent and type of environmental assessment required. PADEP subprojects will be classified as A, B or C depending on the type, location, sensitivity, and scale of the subproject and the nature and magnitude of its potential environmental impacts. The process for identification and approval of PADEP subprojects is elaborated in the GUIDELINES FOR PREPARATION AND IMPLEMENTATION OF COMMUNITY AGRICULTURAL DEVELOPMENT SUBPROJECTS. In brief, the PADEP process with regard to environmental and social assessment is as follows. During the first year of project participation, a village undergoes capacity building and PRA to assess opportunities and identify possible sub-projects to be supported within the envelope of resources available to the community. The District Facilitation Team guides this process, and is well trained to assure that environmental and social considerations form an integral part of the PRA process. Once the community has identified one or several possible subprojects, the proposals are categorized as A, B, or C according to criteria summarized below. Category A projects are those with significant adverse environmental impacts that are sensitive, diverse, or unprecedented. The impacts may affect an area broader than the sites or facilities subject to physical works. For example, direct pollutant discharges large enough to cause degradation of air, water, or soil; large-scale physical disturbance of the site or surroundings; extraction, consumption, or conversion of substantial amounts of forest and other natural resources, measurable modification of hydrological cycles; use of hazardous materials in more than incidental quantities; and involuntary displacement of people and other significant social disturbances. EA for Category A project examines the project’s potential negative and positive environmental impacts, compares them with those of feasible alternatives (including the “without project” option), and recommends any measures needed to prevent, minimize, mitigate, or compensate for adverse impacts and improve environmental performance. The PADEP process is not likely to generate these, but if such proposals surface they should be rejected during the PRA process because PADEP, which is a Community Driven Development project is not equipped to finance the environmental remediation that would be needed to make them acceptable. Category B projects are those with potential adverse environmental impacts on human populations or environmentally important areas - including wetlands, forests, grasslands, and other natural habitats – are less adverse than those of Category A projects. These impacts are normally site-specific; few if any of them are irreversible; and in most cases mitigatory measures can be designed more readily than for Category A projects. The scope of EA for Category B project may vary from project to project, but it is narrower than that of Category A’s. Category B EA examines the project’s potential negative and positive environmental impacts, compares them with those of feasible alternatives (including the “without project” option), and recommends any measures needed to prevent, minimize, mitigate, or compensate for adverse impacts and improve environmental performance. Category C projects are those which are likely to have minimal or no adverse environmental impacts. Beyond screening, no further EA action is required for a Category C project. However, PADEP financed Category C subprojects will have to show clearance from NEMC with regard to their classification. 21 PADEP Environmental Assessment All subproject proposals will be required to include an environmental categorization with justification and clearance by NEMC. Category B subprojects will require an environmental assessment. Subprojects which are likely to result in a significant conversion of natural habitats or the destruction of cultural property will not be supported by PADEP. Changes in access to land or changes in ownership and use of land and property that may be detrimental to the society will be addressed according to the Resettlement Policy Framework, which is disclosed separately. Communities and farmer groups wishing to prepare subprojects will have access to grants to hire technical assistance, primarily through contracting services to private sector/NGOs to undertake the environmental and social assessment. The generic ToRs for the EA will be prepared by the PADEP/MAFS EA unit and customized to suit specific subproject needs by the District Facilitation Team (DFT), which also helps communities/farmer groups with the preparation of EA reports for their respective subprojects. The ToRs and the resulting EA reports shall be approved by NEMC (or an agency accredited by NEMC). Final approval of category B subprojects by the District Management Team (DMT) will require evidence of NEMC (or accredited agency) clearance of the EA report. Evidence that appropriate mitigatory measures, such as, Environmental Management Plan are included and costed in the project proposal will be required. Environmental and social indicators will be included among those monitored to assess progress in implementation of the project. The implementation of the preventive or mitigation measures, will be the responsibility of communities and farmer groups undertaking the subproject. PCU in collaboration with the District Facilitation Teams will undertake regular monitoring and evaluation of the mitigation measures implementation by communities and farmer groups. Any project that entails changes in access to land or changes in use of land that may be detrimental to interests of current land holders or users will be subject to provisions of the Resettlement Policy Framework (separately disclosed). Provisions for treatment of agricultural chemicals, particularly pesticides, will be included in the subproject-specific Pest Management Plan based on Integrated Pest Management approaches. Tanzania EIA Procedure and Guidelines also categorize projects according to impact magnitudes i.e., “Mandatory list of projects requiring EIA” and “List of small scale activities and enterprises that require registration” (may or may not require EIA) . According to “Tanzania EIA Procedure and Guidelines”, the screening procedure can lead to one of the following decisions: • Environmental Impact Assessment is required where the project is known to have significant adverse environmental impacts. • Preliminary environmental assessment is required where the project may have environmental impacts • Environmental Impact Assessment is not necessary where the project is unlikely to cause significant environmental impacts. • No further consideration at all for projects contravening Government policies or other global obligations. Within Tanzanian EIA Procedure and Guidelines, the following criteria need to be taken into account while conducting screening to determine whether EIA is required or not: • Key project parameters • Affected area • Importance and scale of impacts on the environment • The likely degree of public opposition i.e. controversial issues which raise public concern as a result of type and scale of the undertaking, sensitivity of the site location, technology used, conflict of interest in land issues and any other factor related to a particular project may required detailed scrutiny and assessment. Step 3: Scoping and public consultations Scoping is defined as a consultative procedure that culminates in the determination of the extent and approach to an Impact Assessment study for category B sub-projects requiring assessments. The procedure follows upon classification of the project into an environmental category. It is an early and 22 PADEP Environmental Assessment an open process for determining the scope of issues related to the proposed action. The objective of consulting communities is to determine how their concerns will be addressed in the EA study. When a proposed subproject is classified as category B, the PADEP project will provide funds for the group to consult as needed with NEMC and Environmental Units in relevant sectoral authorities, as well as affected or interested parties, and to hire consultants to undertake an assessment. All the concerned parties shall be given adequate opportunities to participate in the Scoping exercise. Draft Terms of Reference (ToRs) for the EA study and the scoping report should be submitted to NEMC for review with assistance of the Technical Review Committee (TRC) for some projects for approval. Since most of these projects will be similar in nature, standard ToRs could be developed in consultation with NEMC. The standard TORs can be customized for the specific subprojects using information collected during the Environmental Profile preparation stage of the EA process and additional comments received from the key stakeholders. Step 4: Conducting an environmental assessment Where necessary NEMC will conduct a visit to the site(s). The outcome of the study, which could be a rejection or revision/modification or approval should be communicated by NEMC to the project group in a period not exceeding 30 days. When a subproject is classified as Category B, a partial (preliminary) environmental assessment (EA) should be undertaken, resulting in a brief EA report. As part of an EA report, an environmental and social management and monitoring plan (ESMP) should be incorporated. If Resettlement Action Plans (RAP) are being prepared as a result of the EA work, the RAPs will be separate documents and disclosed separately. The responsibility for assuring that the EIA report is done lies with the proposing group and or consultants hired by the group. The main items included in the environmental assessment study are; baseline survey and inventory, development of proposal options, potential impact identification and prediction, mitigation consideration and cost estimates, environmental management plans and other issues specified in the ToRs. The following steps should be adopted in this procedure for environmental assessment: Impact Assessment: Based on the screening and scoping, the EA shall identify and assess positive and negative impacts likely to result from the proposed subproject. This uses a variety of methods including checklists, questionnaires, matrices, overlays, modelling, network analysis and simulations. Opportunities for environmental enhancement should be explored. The extent and quality of available data, key gaps in data, and uncertainties associated with predictions shall be identified or estimated. Topics that do not require further attention should be specified. • • • • Analysis of alternatives: Assessment of subprojects from an environmental perspective. This is a key purpose of EA work and the more proactive side of EA – enhancing the design of a project through consideration of alternatives, as opposed to the more defensive task of reducing the adverse impacts of a given design. This provides a detailed review of alternative approaches and prioritises them into a feasible approach. For each alternative, the environmental costs and benefits should be quantified to the extent possible. The do nothing alternative should always be included, with a discussion of it being adopted; that is what would the future look like without the proposal? The do nothing (or no project) alternative is always feasible and gives a “base case” against which the performance of other alternatives can be compared in terms of environmental impact, economic effects and other performance measures indicated by the objectives. Predictions: The principal function of EA is to provide predictive information on the potential implication of projects. Prediction should determine the cause and effect relationship of direct and indirect impacts based on data and information from a wide number of sources on the physical, social, biological, institutional, economic and cultural issues. The quality and availability of data and the analytical techniques and assumptions frequently limit the reliability of prediction. In this context open dialogue with key stakeholders and the public is vital. Evaluation of significance: This determines the significance at subproject and influence area levels. Within specified time and space a significant impact is the predicted or measured 23 PADEP Environmental Assessment change in an environmental attribute that should be considered in project design, depending on the reliability and accuracy of the prediction and the magnitude of the change. Mitigation: This identifies measures to avoid and/or to reduce adverse impacts. It also assesses how to plan and manage environmental enhancement. The identified measures need to be undertaken early enough to embed ideas thoroughly into the basic design of a proposed subproject and show how future monitoring and evaluation would be carried out. These measures are drawn together into coherent Environmental and Social Management and Monitoring Plans. • • • Public consultation: Consultation throughout EA preparation is generally encouraged, particularly for subprojects like those to be supported by PADEP that affect people’s livelihoods. Public consultation can be undertaken during screening, scoping and preparation of ToR, EA report, review of EA report by the NEMC and other stakeholders and during preparation of terms and conditions for EA acceptance or approval. All the information gathered during the impact assessment is compiled in the format given in the NEMC Reporting Procedure and Guidelines and submitted to NEMC for review. In all cases the documentation should be kept as brief and simple as possible. Step 5: Review and approval of environmental assessment report The EA report prepared for each subproject (Category B) should be reviewed by district facilitation team and NEMC as appropriate and public consultations should be undertaken during the review period. The outcome of the review is of the EA is one of the following: • EA accepted • EA not accepted Acceptance and clearance of the EA (for Category B projects) or the checklist (for Category C projects) by NEMC will serve as a sufficient environmental permit to proceed with further consideration for approval of the project by district council and PADEP. The review of the environmental assessment report should also include the determination of whether or not any people have been identified as owners/users of the land upon which or where the sub-project will be located or if the sub-project in any other way will affect people/ property and access so that there is a negative impact (loss) as a result of the sub-project. If that is found to be the case, the appropriate measures need to be taken in accordance with the Resettlement Policy Framework. The environmental assessment report should be short and clear, so that project participants can understand it. It should state clearly the main environmental issues, both positive and negative, likely impacts, potentially affected people, mitigating measures, and costs of mitigation. The report should include a section called the Environmental and Social Management Plan (ESMP). The ESMP should be a practical, action oriented plan specifying measures to be taken to address the negative environmental impacts. It should also specify the actions, resources and responsibilities needed to implement the agreed actions and details on key social and environmental management and monitoring performance indicators. Further, ESMP should ensure that the costs of implementing the EA report recommendations are budgeted into the total subprojects costs. Responsibility for preparation of the ESMP will be with the group under guidance of the DFT. The DFT will supervise the implementation of action plans in close cooperation with communities. The PADEP/MAFS EA unit in consultation with NEMC will undertake periodic monitoring and evaluation. The ESMP should be formulated in such a way that it easy to use. The ESMP should cover the following aspects: Summary of impacts, description of mitigation measures, description of monitoring programme, institutional arrangements, implementation schedule and reporting procedures, cost estimate and sources of funds, and capacity development for implementation of the environmental and social management plan. The contents of an ESMP are further elaborated below. Summary of Impacts: The predicted adverse environmental and social impacts for which mitigation is required should be established and briefly summarized. Cross-referencing the 24 PADEP Environmental Assessment ESMP report to RPF and subproject-specific PMP, so that additional detail can readily be accessed. Description of mitigation measures: Cost-effective and feasible mitigation measures are often detailed and technical in nature. The mitigation measure proposed for PADEP’s subprojects should draw on findings from identified impacts and analysis of compliance with the GoT policies, legislation and administrative matters, and WB Safeguard Policies. Each mitigation (or enhancement) measure should be briefly described with reference to the impact to which it relates and the conditions under which it is required. • • • • • • • Description of monitoring plan: Environmental monitoring should be designed to ensure that mitigation measures are implemented. The ESMP should demonstrate that all identified impacts are matched with mitigation measures and monitoring plans. The monitoring plan will use the findings of existing baseline data, as the means to measure the progress in compliance with the GoT and WB Safeguard Policies. In a nutshell, an effective monitoring plan should consist of the following elements: - Monitoring objectives - Description of performance indicators, which provide linkages to impacts and mitigation measures identified in EA - Description of parameters to be measured, methods to be employed, sampling locations, frequency of measurements, detection limits (where appropriate) and definition of thresholds that will signal the need for remedial actions - Institutional responsibilities, timing and timescales for monitoring - Reporting arrangements (to the NEMC) - Cost and financing provisions - As part of monitoring plan for PADEP's subprojects a table format should be presented with performance indicators, monitoring site and frequency, responsible institution, time frame and provisional cost for each subproject. Institutional arrangements: Responsibilities for mitigation and monitoring should be clearly defined. The ESMP should identify arrangements for coordination between the various government institutions and environmental agencies responsible for mitigation impacts of subprojects. Environmental management in Tanzania involves many government institutions and other agencies, and links between the various actors are often complex. Capacity Development and Training: This comprises a plan for improving institutional environmental management capabilities in the PADEP’s subprojects, based on findings of a rapid training needs assessment and review of the existing capacities and institutional roles. Capacity building would be undertaken for staff of PADEP’s environmental unit, districts for raising their awareness about environmental issues and for upgrading of skills related to environmental management of subprojects. The ESMP will detail the resources needed and the timing of these staff. Specifically, the ESMP provides a specific description of institutional arrangements – who is responsible for carrying out the mitigatory and monitoring measures (e.g. for operation, supervision, enforcement, monitoring of implementation, remedial actions, financing, reporting, and staff training). Implementation schedule and cost estimates: The ESMP should provide the timing, frequency, and duration of mitigation measures, specified in an implementation schedule, showing links with the overall subprojects project implementation plans (PIP). Moreover, the capital and recurrent cost estimates and sources of funds for implementing the ESMP should be considered and also integrated into the total subproject cost. Integration of ESMP with Subprojects: In a nutshell, the ESMP should be specific in its description of the individual mitigation and monitoring measures and its assignment of institutional responsibilities, and it must be integrated into the subprojects overall planning, design, budget, and implementation arrangements Approval: As mentioned earlier, most of the potential subprojects to be supported by PADEP are not expected to generate significant adverse environmental impacts. If it is confirmed 25 PADEP Environmental Assessment through the screening process that the subproject is of Category C, which means no EA is necessary, District Facilitation Team should, on behalf of the community or farmer group request clearance of the subproject from NEMC, or agency accredited by NEMC to clear EA reports. Subprojects classified as Category B would require an EA, and would undergo the formal approval process, in which case the NEMC will review and approve the EA report. In case RAP has been prepared, it should first be cleared by NEMC (or agency accredited by NEMC) before the District Facilitation Team seeking clearance from the Bank through PADEP. According to WB policy on resettlement (OP 4.12), all RAPs should be reviewed and approved of by the Bank, before resettlement activities are implemented. Upon receiving clearance from NEMC, District Facilitation Team shall request PADEP to proceed with funding of the subproject. Supervision: Once the approval process is completed, the supervision becomes part and parcel of the normal subproject cycle management, including monitoring, evaluation and reporting. Environmental monitoring and supervision should be undertaken by all implementing agencies. The DFT should bear the responsibility of supervision at district level and reporting to the PADEP. The PADEP environmental unit staff in consultation with NEMC should be undertaking periodical field visits as part of their supervisory responsibilities. In the process they should also participate in the process of developing and appraising new subproject proposals, which is the prime responsibility of communities, assisted by the DFT. • Step 6: Disclosure and appeal process As project proposals are finalized, the complete proposal shall include the environmental category of the subproject. For category B subprojects, the proposal shall include the EA report and proof of its approval by NEMC. For category C subprojects, the environmental checklist shall be included, together with a list of mitigating measures. The checklist will include an enumeration of possible environmental impact (such as those listed above for the various projects and/or others) and planned mitigating measures. Sample templates for the checklist are included in Annex 1. Box 3.2 Contents of an Environmental and Social Management Plan (ESMP) • Identification and summary of major anticipated adverse environmental impacts • Description of mitigation measure • Description of elements of monitoring program • Institutional arrangement • Implementation schedule for mitigation measures • Performance monitoring and reporting procedures designed to ensure early detection of conditions necessitating corrective actions, and provide information on progress and results of mitigation and institutional strengthening measures • Cost estimates and sources of funds The EA reports of subprojects should be disclosed to the public by presenting the findings and recommendations to the village assembly and distributing copies to PADEP, district and village government. NGOs and other civil societies in the community should be informed of the meeting and copies of report should be made available to them if needed. A summary of findings should be posted at the village government and political parties’ offices. The Community Subproject Committees will be responsibility for disclosing the EA reports for community subprojects, while the Farmer Groups Committees will be responsible for disclosing EA report for farmer groups subprojects. The village governments will be responsible for taking minutes of EA disclosure on behalf of the village councils. PADEP groups or any affected/interested party, has the right of appeal. If dissatisfied with the decision reached at any stage in the EA process, the affected party has the right of appeal to the Minister responsible for Environment. The Minister shall appoint a panel of five people to hear the appeals. The 26 PADEP Environmental Assessment Chairman of the panel shall be the Director of Environment in the Vice President’s Office and the remaining members shall be three (3) environmental management experts and one member from the general public. The results of appeal shall be communicated to NEMC for action. A summary of institutional responsibilities for key steps in the environmental and social management process is given in Table 3.1 below. Table 3.1: Institutional responsibilities for environmental and social management process Subproject Cycle Process Outputs EA Process Outputs Responsible agency Community participation Approval and Clearance 1. Subproject plan prepared Sub-Project Environmental Profile Environmental Screening Report (Full and partial for Category B. No EA required for Category C). District Management Team (DMT), Environmental Unit (EU), and District Facilitation Team (DFT) District Management Team (DMT), Environmental Unit (EU), and District Facilitation Team (DFT) Participated actively in examining and analysing environmental problems related to subproject Provide input to subprojects classification, and EA and subproject- specific PMP and RPF reports District Council NEMC 2. Desk Appraisal of Subproject proposal Scoping and TOR for Category B EU with external consultant / NGOs Consulted interested and affected parties NEMC 3. Field Appraisal of Subproject report EA draft report for Category B subprojects, RAP and ESMP DFT with external consultant / NGO Participated in disclosure workshops NEMC/Bank 4. Subprojects approved ESMP agreed for subprojects implementation EU, monitoring, evaluation and PADEP supervision Partner in implementation of ESMP NEMC 27 PADEP Environmental Assessment Table 3.2: Environmental checklist by subproject types Eligible subprojects Examples Environmental checklist Watershed management for soil and water conservation Construction of contours, protection of gullies, construction of terraces, agro-forestry, establishing and enforcing by-laws, bulking of seed/plant materials required for agro-forestry, woodlot establishment, promotion of gender awareness in soil and water conservation Is there likelihood of biodiversity loss? Will there be infringement on property and access rights? Are the necessary by-laws in place? Conservation tillage Improved fallows, use of cover crops, use of farm implements for soil and water conservation, practices to control soil erosion, use of green manure Are herbicides going to be used to control weeds? Have they (herbicides) been screened and approved by the authorized plant protection agency? Have cover crops been screened by research? Has an IMP approach been adopted? Has a project-specific PMP been prepared? Is the PMP prepared based on IPM approaches? Are herbicides-related hazards adequately addressed? Efficient use of fertilizers Use of rock phosphate, use of high analysis fertilizers, organic manure What measures are in place to prevent health risks to farmers? Are there signs of salinity in the area? Will the fertilizer be stored safely prior to use? Is there a likelihood of polluting surface and groundwater? Are requisite soil and water quality control measures in place? Have soil tests been done? Are there any recommendations on application rates? Fuel efficient technology Biogas technology that utilizes manure and reduces use of fuel to safeguard forests Is there a segment of the community depending on current energy source for income, e.g. charcoal selling? If yes, what alternative is proposed for the lost opportunity? Increase productivity Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers Are there health risks to farmers? Has an IMP approach been adopted? Has a project-specific PMP been prepared? Is the PMP prepared based on IPM approaches? Are herbicides-related hazards adequately addressed? Is training on IPM approaches required by farmers? 28 PADEP Environmental Assessment Integrated plant nutrition techniques/strategies (IPNS) Use of organic manure in combination with mineral fertilizers, production and use of bio-fertilizers Are there any health risks to farmers? Do the farmers have the necessary knowledge and skills? Integrated pest management (IPM) Safe use of pesticides in combinations with observation, preventive and intervention methods in crops, particularly vegetable and fruit production What pests are found in the area? Which pesticides are effective against the pests? Are there alternative control methods? Is it safe to use pesticides? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Are there any measures to prevent health risks to farmers? Will special protective gear be required and is it available locally? Are the farmers competent enough to handle the pesticides? If not, what kind of training will be required on how to apply the pesticides? What equipment will be used? Is there likelihood of polluting the soils, surface and groundwater? Is there likelihood of the pesticides concentrating in the food chains? Is the activity consistent with the pest management plan? Increased use of labour saving technologies Use of farm implements, such as ox- drawn ploughs, ridgers, rippers, weeders, power tillers, etc Are the implements appropriate for use by women and men? Have the herbicides been screened and approved for use by farmers? Are herbicides-related hazards adequately addressed? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Has training on IPM approaches, and safe use and handling of herbicides been conducted? Is research and extension technical support on IPM and use of herbicides adequate? 29 PADEP Environmental Assessment Use of rainwater harvesting techniques Rainwater harvesting for irrigation, domestic and livestock use, such as chaco dams, water bunds in rice irrigation, etc Are measures in place to avoid contamination of stored water? Is there a segment of the community depending on water vending for their income? If yes, what alternative is proposed for the lost opportunity? Are measures in place against child accidents? Are water and land use conflicts likely to emerge? Are measures in place against land degradation at livestock watering points? Will there be infringement on property and access rights? Improvement of traditional irrigation schemes Rehabilitation of weirs, irrigation canals and construction of division boxes Will the subproject cause land and water use conflicts? What measures will be put in place to avoid water logging and poor water quality especially for downstream users? What measures will be used to prevent scouring and clogging of canals? Will there be infringement on property and access rights? Will it cause salinity problems? Will it cause changes in gender relations? Has provision been made for domestic and livestock water supply? Which water-borne diseases are prevalent in the village? Will the subproject lead to an increase in disease incidences? Will the subproject lead to an increase in pest problems? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Is salinity a problem? If yes, is the subproject likely to increase the salinity problem? What measures will be put in place to prevent or control salinity? Will the improvement lead to expansion of the irrigated area? If yes, would this encroach on ecologically sensitive areas? 30 PADEP Environmental Assessment Livestock production Improvement Rehabilitation of infrastructure Dairy animals, pig production, poultry, improvement of indigenous livestock, construction and rehabilitation of cattle dips, etc Rehabilitation of soil testing laboratories, rural roads, bridges, storage facilities and other rural infrastructure Is land currently enough for existing livestock herds? Are signs of overgrazing and soil erosion? Will the subproject contribute to degradation of land and vegetation through overgrazing? Are their dips in the village? If yes, who operates them? What measures are in place against health risks from use of acaricides in dips? What is done with animal manure? Is it used for biogas production? What measures will be put in place to prevent degradation of vegetation and soil at water points? Is there wildlife in the vicinity of the village? If yes, what measures will be instituted to avoid conflicts between livestock and wildlife? Will there be infringement on property and access rights? Will the subproject cause land conflict? Is it likely to cause dust and/or noise pollution? What measures are in place for disposal of construction wastes? Will it result in open pits? If yes, how are they going to be filled? Have the communities and stakeholders been consulted? Is the construction site going to be protected? Will the contract provide protective gear to workers? Is the construction contract include working practices and monitoring of environmental impacts? Are there plans to monitor biodiversity and evaluate fauna and flora species? How is compensation for lost crops or grazing land going to be effected? Is there a mechanism to monitor occupational diseases? Is there any training plan for safety and precautionary measures? 31 PADEP Environmental Assessment Production of non- traditional crops Production of mushrooms, vanilla, fruits, and other diversification initiatives in agriculture Do the farmers have the necessary knowledge and skills? What measures are in place for control of potential new pests? Has an IMP approach been adopted? Has a project-specific PMP been prepared? If yes, is the PMP prepared based on IPM approaches? Are pesticides-related hazards adequately addressed? Has training on IPM approaches been conducted? Is research and extension technical support on IPM adequate? Supply of farm inputs Input shops at farm level, etc What measures are in place against health risks from agro-chemicals? Initial processing of agricultural and livestock products Oil processing, cassava processing, rice milling, processing of cashew nuts, small fruits and vegetable processing units, processing of dairy products, etc Are there any crop processing facilities in the village? If yes, who owns and operates them? Are women involved in the processing and do they own any of the facilities? Will addition of new facilities cause any conflicts? How will the operations be sustained? What will be done with the by- products from processing facilities? How will waste management be organized? How will the hygiene of processed products be controlled? Will the subproject cause adverse changes in gender relationships? Improvement of crop produce marketing Establishment of village marketing centres, construction of market yards, grain storage, group-led grain marketing, etc How will waste management be organized? Is there a provision for water supply and sanitation facilities at market places? Who will operate these facilities? What are the roles of women and men? Will there be infringement on property and access rights? Environmental supervision will be an important activity to assure successful implementation of projects. For category B subprojects that require environmental assessment, the key indicators of the Environmental and Social Management Plan will become indicators that are monitored regularly to assess performance of the subproject. For category C subprojects, the general areas highlighted on the checklist should be reported on in the supervision reports, with measures of indicators where relevant. 32 PADEP Environmental Assessment 4. GUIDELINES FOR INSTITUTIONAL ARRANGEMENTS, TRAINING NEEDS AND COST ESTIMATES FOR MITIGATION MEASURES Institutional arrangements should seek to promote and enhance efficiency, effectiveness, transparency and accountability, reduce red tape and bureaucracy. They should also aim at strengthening participation, empowerment and ownership of stakeholders. At community/village level: The community subproject committee (CSC) will have direct oversight for preparation of EA reports and implementation of agreed mitigation measures, according to environmental and social management plan (ESMP), as part of the overall subproject cycle management and monitoring at community/village level. . Communities and farmer groups will report on the environmental indicators as part of their regular reporting process for implementation of the subproject. The CSC will communicate implementation progress of the ESMP to the district, through their village government, with copies of such correspondence to the Ward Executive Officer (WEO) for information. The periodic reports on implementation of the PADEP project will include a section on achievement of environmental objectives as shown by the indicators. At district level: The District Executive Director (DED), should assign the task of monitoring the implementation of the ESMP at district level to the DFT, which is lead by District Agricultural and Livestock Development Officer (DALDO). Again, this should be part and parcel of the overall management/monitoring function for the subproject cycle at district level, which is the responsibility of the DMT/DFT. The subproject EA reports, including their ESMPs, should be forwarded by DFT to NEMC (or an agency accredited by NEMC) for their clearance, before sending to PADEP for funding. On behalf of DED, the DALDO should send progress reports on implementation of the ESMP to the PADEP/MAFS EA unit, with copy to the Regional Secretariat for information. DFT should be responsible for ensuring that DALDO sends the reports on regular basis, as required by PADEP’s operational guidelines. At national or project level: A decision has been made to build capacity of the EA unit of MAFS, and earmark two individuals to be directly responsible for EA aspects of PADEP during its implementation. The mainstreaming of EA function into the Ministry’s EA unit has an advantage of ensuring sustainability of environmental screening beyond the project life. Environmental assessment should be taken as an integral part of the technical evaluation of subprojects proposal. The environmental audit function needs to be taken into consideration at every step of subprojects cycle. In view of this, PADEP should allocate funding for building capacity of EA unit of MAFS, both in terms of required human resources, office equipment and logistical support. The EA unit of MAFS should be responsible for preparing generic TORs for EA, have an oversight on the overall implementation of ESMPs by communities and farmer groups, and provide technical backstopping to districts. Resources are available under the project for training of MAFS EU staff, DFT and communities to identify and address environmental and social issues. The costs of capacity building for environmental assessment including social aspects should be part of the component 2 of the project. The estimated costs of undertaking training in environmental and social assessment is summarized in Table 4.1 below. The Environmental Assessment training manual prepared by NEMC should provide the basis for developing project specific modules. Training on Bank safeguards will be added into the modules prepared by PADEP consultant. Table 4.1: Estimated costs of training in environmental assessment Area of activity Responsible Target Outcomes Proposed timing Cost Estimates US$ Conduct training needs assessments for PADEP/MAFS, districts, Villages PADEP – PCU, District authorities & Village governments MAFS/PAD EP staff, District staff, villagers Training needs identified and documented 2003 for MAFS/PADEP & pilot districts & villages, yearly for new districts and villages come on board 50,000 33 PADEP Environmental Assessment Arrange for & coordinate training in environment in general & EA, WB & GoT policies MAFS/PADE P staff, district authorities MAFS/PAD EP staff, District staff, villagers Increased environmental awareness, appreciation of EA, skills for EA 2003 for MAFS/PADEP & pilot districts & villages, yearly for new districts and villages come on board 100,000 Ensure initial PRAs in villages contain EA messages PADEP – PCU, DMTs, DFTs, DFTs, (DMTs) PRA reports address environ- mental concerns, incliner impacts, mitigation, ESMP at subproject level 2003 for pilot districts/villages, yearly for new districts and villages come on board 20,000 Monitoring and follow-up PADEP – PCU, DMTs & DFTs Village governments, subproject committees Subproject EMPs successfully implemented Continuously 30,000 5. PADEP SENSITIZATION MEETINGS AND LAUNCHING WORKSHOPS TO ADDRESS ENVIRONMENTAL ISSUES Public understanding about the proposed subprojects and their possible environmental and social impacts is key to successful implementation. These issues should therefore be fully covered in the participatory assessment leading up to selection of the proposed subproject, and in subsequent design. The District Facilitation Team (DFT) should be fully prepared to lead public discussion of environmental and social issues. When DFT visits a village and hold meetings with the village Government leaders to discuss project concepts, objectives and types of eligible subproject etc., and process to be followed to evolve subprojects, they should introduce environmental issues. In order to raise awareness of communities about the potential environmental and social impacts of PADEP funded activities, a number of sensitisation meetings are proposed. These will enhance stakeholders participation in EA processes. Sensitisation should also target the National Resource Team and District Authorities in order to raise their awareness and understanding of the major environmental issues/concepts, such as: EIA; impact identification and prediction methods/techniques; social-cultural dimension of EIA; impact mitigation; and inspection and monitoring of environmental standards. Having been sensitised the District authorities, will in turn sensitise communities when they contact them to introduce and discuss the project concepts, objectives, components and focus through the DFT. When orienting the DFT on project objectives, implementation procedures and roles of teams in facilitating the communities the NRT should also include importance of assessing environment impact on each activity to be undertaken especially during implementation stage. Meeting village leaders: When DFT visits a village and hold meetings with the village Government leaders to discuss project concepts, objectives and types of eligible subproject etc, and process to be followed to evolve subprojects, they should introduce environmental issues concerning resource management and environmental conservation. • 34 PADEP Environmental Assessment First Village Meeting: The purpose should be to create awareness about the project. In this meeting DFT members should emphasize on the importance of observing natural impact on resource management, including soils, trees, sources of water etc., • • • • • • • • • • Village Meeting for prioritisation of problems: After prioritising their problems, the villagers and their facilitators should point out environmental issues related to the prioritised problem. Launching Workshop: Implementation processes will commence with the project launch workshop. The aim of launch workshop is to bring together stakeholders to revisit the project objectives, activities, work plans and each stakeholders responsibilities. This is a good opportunity for DFT to emphasize on the environmental impacts of the different activities to be undertaken and ways to avoid or mitigate. Other meetings: Meetings should be held on a regular basis with district authorities and communities at which PADEP activities in general, and their environmental consequences in particular are explained in simple and easily understandable terms. Depending on the prevailing social and cultural norms, there may be need to arrange separate meetings for different groups. For example, meeting with elders, women and youths. Workshops and seminars: These should be arranged for district authorities and communities around relevant environmental and social assessment themes. Plays and songs: Use/hire school children and drama groups to sing and play/act with messages related to environmental management and social protection. In order to enhance the effectiveness of these campaigns, the following strategies are recommended: Content: It is important to make sure that the contents of the launching workshops; seminars and meetings are relevant to the situation in village. Build speeches around real environmental problems within the village. Delivery strategy: The messages should be delivered in simple and easily understandable language. In order to facilitate understanding of the messages, use of visual aids – films, videos, placards etc is recommended. The occasions should include events like tree planting (season permitting or with watering) and study tours. As far as is feasible, the events should involve local government and national leaders. Cultural considerations: It is important to consider cultural and norms prevailing in the community. If free mixing is not possible due to social and cultural norms, there may be need to form groups according to age, gender and maybe wealth status. Publicity/advocacy: The launching ceremonies should be covered in local media – radio, newspapers, TV. Invite representatives from other communities to participate and let them say a word on their experiences. A training team should consist of an environmental specialist familiar with environmental assessment issues of PADEP subprojects, an agriculturalist familiar with PADEP’s subprojects, and an experienced training facilitator, who should be responsible for logistical planning and facilitation. 35 PADEP Environmental Assessment 6. COMPLIANCE OF PADEP ACTIVITIES WITH BOTH WORLD BANK AND TANZANIA’S POLICIES, GUIDELINES, LEGISLATION AND REGULATIONS 6.1 Compliance with World Bank safeguard policies A list of World Bank environmental and social safeguard polices is summarized in Box 6.1. The following safeguard policies are triggered by the proposed PADEP project: OP/BP 4.01 Environmental Assessment, OP 4.09 Pest Management, OP 4.12 Involuntary Resettlement, and OP 7.50 Projects on International Waterways. To the extent that sub-projects trigger World Bank safeguard policies, sub-project-specific safeguard documentation such as sub-project PMPs or sub-project Dam Safety Measures will be prepared. OP 4.01 Environmental Assessment: The Bank requires environmental assessment (EA) of projects proposed for Bank financing to help ensure that they are environmentally sound and sustainable, and thus to improve decision making. EA takes into account the natural environment (air, water, land); human and safety; social aspects (involuntary resettlement, indigenous peoples, and cultural property); and transboundary and global environmental aspects. EA considers natural and social aspects in an integrated way. It also takes into account the variations in project and country conditions; the findings of country environmental studies; national environmental action plans; the country’s overall policy framework, national legislation, and institutional capabilities related to the environment and social aspects; and obligations of the country, pertaining to project activities, under relevant international environmental treaties and agreements. The Bank does not finance project activities that would contravene such country obligations, as identified during the EA. OP 4.09 Pest Management: In assisting Borrowers to manage pests that affect either agriculture or public health, the Bank supports a strategy that promotes the use of biological or environmental control methods and reduces reliance on synthetic chemical pesticides. In Bank-financed projects, the Borrower addresses pest management issues in the context of the project’s environmental assessment. In appraising a project that will involve pest management, the Bank assesses the capacity of the country’s regulatory framework and institutions that promote and support safe, effective, and environmentally sound pest management. As necessary, the Bank and the Borrower incorporate in the project components to strengthen such capacity. OP 7.50 Projects on International Waterways: This policy applies to the following types of international waterways: (a) any river, canal, lake, or similar body that forms a boundary between, or any river or body of surface water that flows through, two or more states, whether Bank members or not, (b) any tributary or other body of surface water that is a component of any waterway describe in (a) above; and (c) any bay, gulf, strait, or channel bounded by two or more states, or, if within one state, recognized as a necessary channel of communication between the open sea and other states – any river flowing into such waters. This policy applies to the following types of projects (a) hydroelectric, irrigation, flood control, navigation, drainage, water and sewerage, industrial, and similar projects that involve the use or potential pollution of international waterways as described above and (b) detailed design and engineering studies of these projects, including those to be carried out by the Bank as executing agency or in any other capacity. Due to the use of international waters by future sub-projects, this safeguard policy is triggered, and the relevant riparians (Kenya, Uganda, Rwanda, Malawi and Mozambique) are being notified. Involuntary Resettlement (OP 4.12). The resettlement policy is triggered when people are affected by loss of land, loss of property and/or loss of access to resources. It is therefore irrelevant whether or not the impact will entail physically relocation of the affected people, the policy is triggered in all such cases. This means that the impact may be of such kind that only compensation in cash or kind is necessary. For this purpose, the Government of Tanzania has prepared a Resettlement Policy Framework which is a document that explains the procedures for resettlement and/or compensation, which must be followed once the Environmental Assessment has determined that people will be adversely affected by a project activity". 36 PADEP Environmental Assessment The PADEP project will not cause involuntary resettlement, but some of the sub-projects may require changes in land use or changes in access to land. For that reason a Resettlement Policy Framework has been prepared. 37 PADEP Environmental Assessment Box6 6.1 World Bank Environmental and Social Safeguard Policies • Environmental Assessment (OP 4.01). Outlines Bank policy and procedure for the environmental assessment of Bank lending operations. The Bank undertakes environmental screening of each proposed project to determine the appropriate extent and type of EA. The Bank classifies the proposed project into one of four categories, depending on the type, location, sensitivity , and the scale of the project and the nature and magnitude of its potential environmental impacts. This environmental screening process will apply to all sub- projects to be funded by PADEP; sub-projects may be classified as category A, B, or C (category FI will not be applicable in this context). As indicated in the EA report, subsequent EA work for sub-projects will depend on the environmental classification of the sub-project. . • Natural Habitats (OP 4.04). The conservation of natural habitats, like other measures that protect and enhance the environment, is essential for long-term sustainable development. The Bank does not support projects involving the significant conversion of natural habitats unless there are no feasible alternatives for the project and its siting, and comprehensive analysis demonstrates that overall benefits from the project substantially outweigh the environmental costs. If the environmental assessment indicates that a project would significantly convert or degrade natural habitats, the project includes mitigation measures acceptable to the Bank. Such mitigation measures include, as appropriate, minimizing habitat loss (e.g. strategic habitat retention and post-development restoration) and establishing and maintaining an ecologically similar protected area. The Bank accepts other forms of mitigation measures only when they are technically justified. Should the sub-project-specific EAs indicate that natural habitats might be affected negatively by the proposed sub-project activities, such sub-projects will not be funded under the proposed PADEP project. • Pest Management (OP 4.09). The policy supports safe, affective, and environmentally sound pest management. It promotes the use of biological and environmental control methods. An assessment is made of the capacity of the country’s regulatory framework and institutions to promote and support safe, effective, and environmentally sound pest management. As outlined in the EA report, sub-projects will prepare sub-project specific pest management plans as required. A revised PMP for the PADEP project will serve as a guidance/reference document for the preparation of sub-project PMPs. • Involuntary Resettlement (OP 4.12). The resettlement policy is triggered when people are affected by loss of land, loss of property and/or loss of access to resources. It is therefore irrelevant whether or not the impact will entail physically relocation of the affected people, the policy is triggered in all such cases. This means that the impact may be of such kind that only compensation in cash or kind is necessary. For this purpose, the Government of Tanzania has prepared a Resettlement Policy Framework which is a document that explains the procedures for resettlement and/or compensation, which must be followed once the Environmental Assessment has determined that people will be adversely affected by a project activity". This policy has been revised in FY 99/00 with the direct participation of technical Bank staff representing various networks. It also benefited from a four month external consultation process, in which the drafting team received and reviewed nearly 300 comments from NGO representatives, resettlement researchers, and government officials from around the world. This draft was approved in December 2001. The Resettlement Sourcebook, which will synthesize best practices in resettlement and provide guidance to staff in application of the policy, is now available. • Indigenous Peoples (OD 4.20). This directive provides guidance to ensure that indigenous people benefit from development projects, and to avoid or mitigate adverse effects of Bank-financed development projects on indigenous people. Measures to address issues pertaining to indigenous peoples must be based on the informed participation of the indigenous people themselves. Sub-projects that would have negative impacts on indigenous people will not be funded under the proposed PADEP project. • Forests (OP 4.36). This policy applies to the following types of Bank-financed investment projects: (a) projects that have or may have impacts on the health and quality of forests; (b) projects that affect the rights and welfare of people and their level of dependence upon or interaction with forests; and (c) projects that aim to bring about changes in the management, protection, or utilization of natural forests or plantations, whether they are publicly, privately, or communally owned. The Bank does not finance projects that, in its opinion, would involve significant conversion or degradation of critical forest areas or related critical habitats. If a project involves the significant conversion or degradation of natural forests or related natural habitats that the Bank determines are not critical, and the Bank determines that there are no feasible alternatives to the project and its siting, and comprehensive analysis demonstrates that overall benefits from the project substantially outweigh the environmental costs, the Bank may finance the project provided that it incorporates appropriate mitigation measures. Sub-projects that are likely to have negative impacts on forests will not be funded under the proposed PADEP project. • Cultural Property (OPN 11.03). The term “cultural property” includes sites having archaeological (prehistoric) , paleontological, historical, religious, and unique natural values. The Bank’s general policy regarding cultural property is to assist in their preservation, and to seek to avoid their elimination. 38 PADEP Environmental Assessment Specifically, the Bank (i) normally declines to finance projects that will significantly damage non-replicable cultural property, and will assist only those projects that are sited or designed so as to prevent such damage; and (ii) will assist in the protection and enhancement of cultural properties encountered in Bank-financed projects, rather than leaving that protection to chance. The management of cultural property of a country is the responsibility of the government. The government’s attention should be drawn specifically to what is known about the cultural property aspects of the proposed project site and appropriate agencies, NGOs, or university departments should be consulted; if there are any questions concerning cultural property in the area, a brief reconnaissance survey should be undertaken in the field by a specialist. The proposed PADEP project will not fund sub-projects that will have negative impacts on cultural property. • Safety of Dams (OP 4.37). For the life of any dam, the owner is responsible for ensuring that appropriate measures are taken and sufficient resources provided for the safety to the dam, irrespective of its funding sources or construction status. The Bank distinguishes between small and large dams. Small dams are normally less than 15 m in height; this category includes, for example, farm ponds, local silt retention dams, and low embankment tanks. For small dams, generic dam safety measures designed by qualified engineers are usually adequate. Sub-projects that will include small dams, i.e. chaco dams and other water management structures will prepare a generic dam safety analysis. • International waterways (O 7.50). The Bank recognizes that the cooperation and good will of riparians is essential for the efficient utilization and protection of international waterways and attaches great importance to riparians making appropriate agreements or arrangement for the entire waterway or any part thereof. Projects that trigger this policy include hydroelectric, irrigation, flood control, navigation, drainage, water and sewerage, industrial, and similar projects that involve the use or potential pollution of international waterways. The riparians are being notified in accordance with this policy; no additional steps need to be taken at the level of the sub-projects. • Disputed Areas (OP/BP/GP 7.60). Project in disputed areas may occur the Bank and its member countries as well as between the borrower and one or more neighbouring countries. Any dispute over an area in which a proposed project is located requires formal procedures at the earliest possible stage. The Bank attempts to acquire assurance that it may proceed with a project in a disputed area if the governments concerned agree that, pending the settlement of the dispute, the project proposed can go forward without prejudice to the claims of the country having a dispute. This policy is not expected to be triggered by sub-projects. This policy is unlikely to be triggered by sub-projects to be funded by the proposed PADEP project. 6.2 Compliance with Tanzania’s environmental management policies Implementation of the PADEP project will be undertaken in conformity to provisions of the Tanzanian National Environment Policy (NEP) of 1997 and The National Land Policy of 1995. Also relevant is the National Environment Management Council Act (no. 19 of 1983) which principally provided establishment of the National Environment Management Council (NEMC). Among others; the Act also stipulated the following functional roles and responsibilities for NEMC: • To advise government on all environmental-related issues (i.e. including impacts of PADEP activities) • To formulate environment policy • To establish multisectoral/multidisciplinary coordination among both institutions as well as respective individuals dealing with environmental issues. In other words, this incorporates aspects of community participation/involvement as required by PADEP. Also relevant are the Land Acts especially both no, 4 and 5 of 1999. These make far-reaching provisions for environmental management and natural resources because they provide for categorization of lands into three areas: namely: (a) general (i.e. unreserved or public lands) (b) reserved ( i.e. protected/conserved lands) (c) village lands (i.e. lands to be administered by village government authorities; as opposed to lands to be administered by central government) Other pertinent Land Acts (among several) are: • Land Acquisition Act no. 47 of 1967: which provides for compulsory acquisition of land in the interest of the public. 39 PADEP Environmental Assessment • National Land use Planning Commission Act; 1984 which mainly provides for establishment of the National Land use Planning Commission, but more importantly together with the Rural Lands (planning and utilization) Act no 22 of 1979 establishes the need for ensuring proper land use through e.g. multisectoral/multidisciplinary/coordination as well as cooperation, both of which are in the spirit of PADEP. • Town and Country Planning Ordinance Cap 378 of 1956, which provides for both methodology and approach to land use planning in both urban and rural areas. Local authorities will be essential to successful implementation of the PADEP project, and the powers of these are specified in several relevant pieces of legislation. The key legislations are as follows: • Local Government District Authorities Act no. 7 of 1982 duly amended in Act no. 8 of 1992, Act no.4 of 1985 and Act no, 13 of 1988 • Decentralization of government administration (interim provisions Act no. 27 of 1972, duly amended among several others in Act 26 of 1975, Act no. 12 of 1982 as well as in Act no. 19 of 1992. • There is a long list of district by-laws, most of which pertain to agriculture, for example the following: ♦ Manyoni District Development Council (Cultivation of Agricultural lands by-laws) ♦ Kilosa District Development Council (Cultivation of Agricultural lands by-laws) ♦ Bagamoyo District Development Council (Cultivation of Agricultural lands by-laws), etc., Several pieces of legislation govern use of specific resources. Key among them are: (i) Range Development and Management Ordinance (Cap 569), which provides for among others demarcation and improvement of range areas for livestock grazing. (ii) Wildlife Conservation Act no. 12 of 1974, which provides for protection of wildlife reserved areas from human activities. (iii) Forests Ordinance (Cap 389), which similar to Wildlife Act also provides for protection of forestry related reserved areas from human activities. (iv) Among several others; the following acts/ordinance in their totality provide for proper agricultural practices and thence products: • Grass-fires (control) Ordinance (Cap 13) • Plant protection Ordnance (Cap 133) • Food (control) of quality Act no. 10 of 1978 • Pharmaceuticals and poisons Act no. 9 of 1978 • Penal Code (Cap 16) • Section: 179: Negligent Spreading of diseases • Sections:180-81: Adulteration and sale of noxious food • Tropical Pesticides Research Institute Act no, 18 of 1979 • Water utilization (control and regulations) Act no. 42 of 1974 as duly amended in Act no 10 of 1981 as well as Act no 17 of 1989 Acts which promote/control industrial production and trade: • Small Industries Development Organization Act no 28 of 1973 • National Industries (Licensing and Registration Act) no 10 of 1967 with its amendments in Act 13 of 1982, no. 13 of 1991 and also amended by Investment Promotion Centre Act no 10 of 1992 • Penal code Cap 16; Section 186: on Trade 40 PADEP Environmental Assessment 7. PUBLIC CONSULTATION PROCESS As mentioned earlier, PADEP will not support subprojects classified as Category A because of limited capacity, both in terms of technical and financial resources, to implement preventive or mitigation measures required for this type of subprojects. According to Bank’s OP 4.01, all Category A and B subprojects proposed for PADEP financing, during the EA process, the implementing agencies (PCU, districts councils and communities/farmer groups) shall be required to consult subprojects-affected groups and local non-governmental organizations (NGOs) about the subproject’s environmental aspects and shall take their views into account. PADEP implementing agencies shall initiate such consultations as early as possible. PADEP should consult these groups at least twice: shortly after environmental screening and before the terms of reference for the EA are finalized; and once a draft EA report is prepared. In addition, the PADEP should consult with such groups throughout project implementation as necessary to address EA-related issues that affect them. For meaningful consultations between the implementing agencies and subproject-affected groups and local NGOs, relevant material shall be provided in a timely manner prior to consultation, and in a form and language that are understandable and accessible to the groups being consulted. Any Category B report for a subproject proposed for PADEP financing shall be made available to subproject-affected groups and local NGOs. For Category B subprojects, public availability of EA reports in Country is a prerequisite to PADEP funding of these subprojects. The consultation process with the subproject-affected groups will be as follows: Stakeholder identification: There should be an explicitly designed consultation strategy based upon NEMC guidelines and the Bank’s safeguard policies. Key stakeholders should be defined. The means for identifying and weighing the relative participation in the consultations of “affected communities” “beneficiaries” and other “stakeholders” should be considered. These should included representatives of government agencies, NGOs, religious groups, and village and community leaders. Gender and ethnicity should be considered in stakeholder identification and consultation process. • • • Information dissemination: A range of means for information dissemination is available, such as posters, radio reports, and public meetings and hearings. Key stakeholders should be targeted for information campaigns prior to meetings or hearings. Information materials for communities affected by subprojects should be translated into Kiswahili language. Consultation mechanism: The types of consultation mechanisms to be used in PADEP should include public meetings and workshops and seminars. A systematic survey to elicit opinions of persons affected directly by the subprojects could be considered. There are a wide variety of other effective techniques, which could be used for consultation, but apparently they are not tested in the country. These include public hearings, citizen advisory groups, focus groups, community opinion survey and expert panels discussions. According to the NEMC guidelines, public consultations are paramount during impact assessment, especially at the stage of scoping, ToR preparation and EA preparation. DFT should identify the main issues of concern and the affected or interested parties during the scoping exercise. To ensure satisfactory public (affected and/or interested people) involvement, DFT should initiate a public information programme of the area likely to be affected by the proposed subprojects. Any concern raised by the public should be recorded and addressed in the process of categorization of proposals. Public notice of the scoping process for the subprojects should be issued by NEMC (or accredited agency) through village leaders and/or other appropriate mechanisms. . NEMC requires that a summary of the draft EA conclusions, including the ESMP, be presented to affected communities and interested NGOs in a form and language meaningful to the groups being consulted. Comments made by the communities and NGOs must be incorporated into the EA report submitted to NEMC (or accredited agency) and subsequently PADEP for funding. Under the PADEP implementation procedures, public consultation will begin with the PRA on environmental issues in the communities. During the PRA, the subproject will be defined and, through 41 PADEP Environmental Assessment the screening process, its associated potential environmental impacts and category of the EA will be determined. During the subsequent scoping stages, if the project will be classified as category B, another public consultation will be held with the communities affected by the proposed subproject. Involvement of the public will continue throughout the EA process, using the community and farmer group subcommittees and village and community leaders. Once the draft EA report has been prepared, another consultation involving as many community members as possible, will be held to review the findings and recommendations of the draft EA report. Comments and observations shall be incorporated into the final EA report and the resulting ESMP report. 42 PADEP Environmental Assessment Annex 1 Sample check list for watershed management for soil and water conservation sub- project Name of Sub-project: _________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Reduce biodiversity? 3. Adversely affect downstream users? 4. Affect areas of water sources extraction? 5. Affect wetland/swamps areas? 6. Affect rare/endangered species? 7. Adversely effect human health? 8. Provide benefits to both men and women? 9. Cause changes in land, water morphology and physical characteristics as well as quality and quantity of resources? 10. Reduce quality of land, water, or health of plants or animals? Mitigation 11. Awareness raising? measures: 12. Improved designing and construction method. 13. Compensation if appropriate. 14. Are IPM approaches being adopted? 15. Have subproject-specific PMP been developed? 16. Are agro-chemical-related hazards being addressed? 17. Have PMP based on IPM approaches been developed? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 43 PADEP Environmental Assessment Annex 1 Sample check list for conservation tillage sub-project Name of Sub-Project: _________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to soil erosion? 2. Provide benefits to both men and women? 3. Entail loss of access to or use of land by current users? 4. Increase ability of soil to retain water? 5. Require use of unfamiliar agricultural chemicals? 6. Enable water resources conservation? 7. Affect groundwater table? 8. Introduce new pests? 9. Require storage of manure? 10. Lead to use of new implements? 11. Lead to appropriate management of residue? 12. Are IPM approaches being adopted? 13. Have subproject-specific PMP been developed? 14. Have agro-chemical-related hazards been addressed? 15. Have PMPs based on IPM approaches been developed? 16. Is training in IPM approaches planned? Comments by DFO: I recommend the proposal: Signature: (DFO Date: (clearance by NEMC and date) 44 PADEP Environmental Assessment Annex 1 Sample check list for fuel-efficient technology subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Provide benefits for both men and women? 2. Result in loss of access to or use of land by present landholders and users? 3. Increased cutting of trees or bushes? 4. Lead to loss of land cover and soil disturbances? 5. Lead to unsightly or foul smelling storage of compost or other matter? 6. Leaching of contaminants into water supply? 7. Lead to land degradation and soil disturbance? Mitigation 9. Are public awareness and training in biogas technology planned? 10. Are safe disposal methods of slurry in place? measures: 10. Siting of storage areas Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 45 PADEP Environmental Assessment Annex 1 Sample check list to increase productivity subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to application of organic manure? 2. Require significantly increased use of water? 3. Lead to loss of access to or use of land by present landholders or users? 4. Require use of new or unfamiliar agricultural chemicals? 5. Lead to salinization of soils? 6. Lead to contamination/pollution of surface and/or groundwater? 7. Lead to benefits for both men and women? 8. Introduction of new pests? Mitigation 9. Soil testing. measures: 10. Are public awareness and training in IPM approaches being considered? 11. Are soil, water and pests being monitored?. 12. Are IPM approaches being adopted? 13. Are subproject-specific PMP being developed? 14. Have agro-chemical-related hazards being addressed? 15. Are PMPs based on IPM approaches in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 46 PADEP Environmental Assessment Annex 1 Sample check list for integrated plant nutrition techniques/strategies (IPNS) sub- projects Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to application of organic manure, mineral fertilizers, bio-fertilizers? 2. Entail loss of access to or change in use of land by present landholders and/or users? 3. Provide benefits to both men and women? 4. Adversely affect quality of surface and ground water? 5. Increase weeds or pests? 6. Lead to salinization of soils? 7. Lead to loss of some plant species? Mitigation 8. Public awareness and training on IPM approaches? measures: 9. Are soil and water quality being monitored? 10. Are IPM approaches being adopted? 11. Have subproject-specific PMPs been developed? 12. Have agro-chemical-related hazards been addressed? 13. Is PMP based on IPM approaches being used? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 47 PADEP Environmental Assessment Annex 1 Sample check list for integrated pest management (IPM) subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Provide benefit to both men and women? 2. Entail loss of access to or use of land by current land holders and/or users? 3. Entail use of new or unfamiliar agricultural chemicals? 4. Adversely affect micro organisms in soil? 5. Adversely affect surface and groundwater (terrestrial or aquatic ecosystems)? 6. Adversely affect consumers crops (residues in vegetables and fruits)? 7. Soil contamination? 8. Water resources pollution? Mitigation 9. Has awareness campaign and training in IPM approaches been done? measures: 10. Is there adequate capacity for proper handling and storage of agrochemicals? 14. Have IPM approaches been adopted? 15. Are subproject-specific PMP developed? 16. Are agro-chemical-related hazards addressed? 17. Is the PMP based on IPM approaches? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) 48 PADEP Environmental Assessment Annex 1 49 Sample check list for increased use of labour saving technology subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Lead to loss of access to or use of land by present landholders or users? 2. Provide benefits to both men and women? 3. Entail production of more manure? 4. Introduce increased risk of accidents to humans? Mitigation 5. Awareness and training on safe use and handling of herbicides available? measures: 6. Proper storage and use of manure in place? 7. Are IPM approaches adopted? 9. Are herbicides-related hazards addressed? 10. Are PMP based on IPM approaches in place? 7. Compensation if appropriate Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 50 Sample check list for use of rainwater harvesting techniques subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Lead to increased incidence of water-borne disease? 3. Lead to land degradation at livestock watering points? 4. Provide benefits to men and women? 5. Increase risk of flooding during heavy rain? 6. Lead to siltation due to erosion? Mitigation 7. Is awareness and training plan in place? measures: 8. Are there plans to plant protective vegetation? 9. Are design specifications able to withstand reasonable risks of flooding? 10. Are IPM approaches adopted? 11. Are agrochemicals-related hazards addressed? 12. Are PMP based on IPM approaches in place? 13. Is there a need for the preparation of generic dam safety measures? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 51 Sample check list for improvement of traditional irrigation schemes subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Provide benefits to both men and women? 3. Result in increased salinity of soil or water? 4. Increase incidence of water borne disease? 5. Adverse impact on downstream users? 6. Land and water use conflicts? Mitigation 7. Provide drainage including disposal of water. measures: 8. Monitoring of soil and water 9. Is salinity monitoring plan in place? 10. Is awareness and training plan in place? 11. Are there plans to plant protective vegetation? 12. Are design specifications able to withstand reasonable risks of flooding? 13. Are IPM approaches adopted? 14. Are agrochemicals-related hazards addressed? 15 Are PMP based on IPM approaches in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 52 Sample check list for improvement in livestock production subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Create conflicts with customs/traditions of local communities with respect to livestock keeping? 3. Increase quantities of manure? 4. Lead to overgrazing? 5. Increase exposure of humans to animal borne disease? 6. Increase exposure to agricultural chemicals (dips)? Mitigation 7. Are the grazing arrangements rotational? measures: 8. Is public awareness and training planned? 9. Are the arrangements for handling and storage of manure and chemicals in place? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 53 Sample check list for production of non-traditional crops subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Entail loss of access to or use of land by present landholders and/or users? 2. Provide benefits to men and women? 3. Contribute to deterioration in soil quality? 4. Entail introduction of new pests? Mitigation measures: 5. Is public awareness and training program in place? 6. Is a pest monitoring and surveillance in plan in place? 7. Are PMP based on IPM approaches in place? 8. Are IPM approaches adopted? 9. Are agrochemicals-related hazards addressed? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 54 Sample check list for supply of farm inputs subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Entail loss of access to or use of land by present land holders and or users? 2. Entail local storage of agricultural chemicals? 3. Provide benefits to both men and women? 4. Enhance risk of robbery or theft? 5. Increase population of vermin or rats? Mitigation 6. Has security for money and goods (locks) been provide? measures: 7. Has public awareness been raised? 8. Is there good storage facility of agricultural chemicals and seeds? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 55 Sample check list for initial processing of agricultural and livestock products subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Increase production of by-products? 2. Entail loss of access to or use of land by present land holders and/or users? 3. Contribute to soil contamination? 4. Create unpleasant odours? 5. Affect water quality 6. Lead to benefits for men and women? 7. Lead to contamination of products? Mitigation 8. Is there proper disposal of wastes planned? measures: 9. Is the site appropriate?. 10. Is training and public awareness plan in place?. Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 56 Sample check list for improvement of crop produce marketing subproject Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 2. Provide benefits to men and women? 3. Create plant waste requiring disposal? 4. Create needs for latrines to accommodate gatherings of people? 5. Unpleasant odours? Mitigation 6. Is the plan for disposal of waste in place?. measures: 7. Has the site been carefully selected? . 8. Are the water supply and sanitation facilities provided? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 57 Sample check list for rehabilitation of infrastructure sub-projects Name of Sub-project: ________________________________________________________ Proposed Environmental Category Aspect of EA needs Sample checklist questions Will the subproject be likely to: Yes No Additional Data 1. Will it cause land use conflicts? 2. Is any person living on or near the land needed for the subproject, or is any person farming there, using the land for grazing or watering of animals or for any other purpose? 3. Generates excessive dust and noise? 4. Leads to creation of open pits? 5. Reduces biodiversity? 6. Leads to construction wastes? 7. Leads to loss of vegetation? Mitigation measures: 8. How is compensation for lost crops or grazing land going to be done? 9. Are protective gear provided? 10. Landfill arrangements in place? 11. Construction wastes management in place? 12. Biodiversity monitoring plan available? 13. Training on safety and precautionary measures planned? Comments by DFO: I recommend the proposal: Signature: (DFO) Date: (clearance by NEMC and date) PADEP Environmental Assessment Annex 1 58 | false |
# Extracted Content The United Republic of Tanzania MINISTRY OF AGRICULTURE AND FOOD SECURITY Participatory Agricultural Development and Empowerment Project (PADEP) RESETTLEMENT POLICY FRAMEWORK February 2003 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP TABLE OF CONTENTS A. Introduction ………………………………………………………………… 1 B. Policy Principles and Objectives Government Resettlement Preparation and Implementation …………………………………………………………… 2 C. Description of the Process for Preparing and Approving Resettlement Plans 4 D. Subprojects Identified Categories of Potential Impacts ……………………… 11 E. Eligibility Criteria for Defining various Categories of Affected Persons …… 15 F. A Legal Framework comparing the Borrower Laws and Regulations with the Bank Policy Requirements and Measures proposed to Bridge any Gaps between them ……………………………………………………………… 17 G. Methods of Valuing Affected Assets ……………………………………… 18 H. Organizational Procedures for Delivery of Entitlements, Including, for Projects Involving Private Sector Intermediaries, the Responsibilities of the Financial Intermediary, the Government, and the Private Developer …………………… 24 I. A Description of the Implementation Process, Linking Resettlement Implementation to Civil Works ……………………………………………… 25 J. A Description of Grievance Redress Mechanisms …………………………. 25 K. A Description of Mechanisms for Consultations with, and Participation of, Displaced Persons in Planning, Implementation and Monitoring …………….. 27 L. Arrangements for Monitoring by the Implementing Agency and, if Required, By Independent Monitors …………………………………………………….. 28 i WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP A. INTRODUCTION Tanzania is essentially an agricultural country. Over 80% of its population lives in rural areas and depends mostly on traditional agricultural and related activities. Agriculture contributes approximately 50% of GDP. The envisaged PADEP project seeks to increase productivity of smallholder farmers, to increase farm incomes, to reduce food insecurity, and to enhance management of soil fertility. The PADEP project will benefit 840 villages in 28 participating districts (out of a total of 121 in mainland Tanzania, and additional areas in Zanzibar. Specifically, it is planned that through the Community Investment Subprojects and Farmer Group Investment Subprojects of PADEP communities and farmer groups will request financing for sub-projects. Some of these sub projects may involve the construction of irrigation infrastructure, such as small dams, water retention ponds and other water management schemes, as well as those related to improved agricultural technology and marketing of inputs and output. Tanzania's average population density is relatively low at about 32 people /km2, and therefore population pressure on scarce land resources is not a major problem theoretically, but it is important in some localities, particularly semi-arid areas. Nonetheless, efforts should be made in the design and screening stages of the sub projects to avoid negative impacts on people, land, and property, including people’s access to natural and other economic resources, as far as possible. The necessity for land acquisition, compensation and resettlement of people may arise for certain categories of sub projects. When that occurs, the World Bank Operational Policy, OP 4.12 on Involuntary Resettlement and the Government of Tanzania's relevant policies and acts especially Land Acquisition Act of 1967 will be triggered. The preparation of a Resettlement Plan is not required at this stage since the sub projects, to be created on a demand driven basis have not yet been defined. Resettlement plans, when required, will be specific to particular sub-projects. Notwithstanding, in line with the Bank's Involuntary Resettlement Policy OP 4.12, the Government of Tanzania is required to prepare a resettlement policy framework to be disclosed before appraisal. The resettlement framework establishes the resettlement and compensation principles, organizational arrangements and design criteria to be applied to the sub-projects that will be prepared during project implementation in compliance with the laws of Tanzania and the Bank’s safeguards policy on involuntary resettlement. The subproject resettlement/compensation plans will be subsequently prepared consistent with this policy framework and will be submitted to the Bank for approval after specific planning information becomes available. All efforts will be deployed to minimize the need for resettlement in the project design stage. According to World Bank Operation Policy 4.12 on involuntary resettlement this resettlement policy framework will cover the following: • Policy principles and objectives governing resettlement preparation and implementation 1 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP • A description of the process for preparing and approving resettlement plans • Land acquisition and likely categories of impact. • Eligibility criteria for defining various categories of project affected persons • A Legal framework comparing the borrower laws and regulations and Bank policy requirements and measures proposed to bridge any gaps between them • Methods of valuing affected assets • Organizational procedures for delivery of entitlements, including, for projects involving private sector intermediaries, the responsibilities of the financial intermediary, the government, and the private developer • A description of the implementation process, linking resettlement implementation to civil works • Description of grievance redress mechanisms • A description of mechanisms for consultations with, and participation of, displaced persons in planning, implementation, and monitoring • Arrangements for monitoring by the implementing agency and, if required, by independent monitors. B. POLICY PRINCIPLES AND OBJECTIVES GOVERNING RESETTLEMENT PREPARATION AND IMPLEMENTATION The impacts due to involuntary resettlement from development projects, may give rise to economic, social and environmental risks resulting in production systems being dismantled, people facing impoverishment when their productive assets or income sources are lost, people being relocated to environments where their productive skills may be less applicable and the competition for resources increases; community institutions and social networks being weakened; kin groups being dispersed; and cultural identity, traditional authority, and the potential for mutual help being diminished or lost. The resettlement policy may be triggered because the project activity causes land acquisition, namely: a physical piece of land is needed and people may be affected because they are cultivating that land, they may have buildings on the land, they will use the land for watering and grazing of animals or they may otherwise access the land economically, spiritually or in any other way which may not be possible during and after the project is implemented. Therefore people will appropriately be compensated for their loss (of land, property or access) either in kind or in cash, of which the former is preferred. The Land Act No.4 and Village Land Act No.5 of 1999 have set clear procedures for full, fair and prompt compensation while acquiring land from citizens,. These procedures should be adhered to, especially the Land (assessment of the value of compensation) Regulations – made under S.179 of Land Act No. 4 of 1999. GN 78 published on 4/5/2001. 2 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Therefore, the objectives of this policy are the following: i) Involuntary resettlement and land acquisition should be avoided where feasible, or minimized, exploring all viable alternative sub projects design. ii) Where involuntary resettlement and land acquisition is unavoidable, resettlement and compensation activities should be conceived and executed as sustainable development programs, providing sufficient investment resources to give the persons displaced by the project the opportunity to share in project benefits. Displaced and compensated persons should be meaningfully consulted and should have opportunities to participate in planning and implementing resettlement programs. iii) Displaced and compensated persons should be assisted in their efforts to improve their livelihoods and standards of living or at least to restore them, in real terms, to pre-displacement levels or to levels prevailing prior to the beginning of project implementation, whichever is higher. Here, the affected people, according to the Bank policy, refer to people who are directly affected socially and economically by the Bank assisted investment projects, caused by: (a) the involuntary taking of land and other assets resulting in : (i) relocation or loss of shelter; (ii) loss of assets or access to assets; (iii) loss of income sources or means of livelihood, whether or not the affected persons must move to another location; or (b) the involuntary restriction of access to legally designated parks and protected areas results in adverse impacts on the livelihood of the displaced persons. The resettlement policy applies to all components under the project, whether or not they are directly funded in whole or in part by the Bank. The policy applies to all displaced persons regardless of the total number affected, the severity of impact and whether or not they have legal title to land. Particular attention should be paid to the needs of vulnerable groups among those displaced; especially those below the poverty line, the landless, the elderly, women and children, indigenous groups and ethnic minorities or other displaced persons who may not be protected through Tanzania land compensation legislation. In particular for PADEP, the policy requires that resettlement plans be developed for sub projects that entail acquisition of land and for which displacement or restriction of access may result. Determination of which sub-projects require resettlement plans will be made during the PRA process leading to the decision to formulate a proposal for a sub-project. Sub-projects that entail acquisition of land and for which displacement or restriction of access may result will require resettlement plans; others will not. Implementation of the sub-projects requiring resettlement plans cannot commence before necessary measures for resettlement and compensation are in place according to steps identified in the resettlement plan. These measures will include provision for compensation and other assistance required for relocation, prior to displacement, and preparation and provision of resettlement sites with adequate facilities, where required. In 3 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP particular, the taking of land and related assets may take place only after compensation has been paid and, where applicable, resettlement sites, new homes, related infrastructure, public services and moving allowances have been provided to displaced persons. For sub projects requiring relocation or loss of shelter, the policy further requires that measures to assist the displaced persons be implemented in accordance with the sub project’s resettlement plan of action. The policy aims to have the affected persons perceive the process and any compensation to be full, fair and prompt. C. DESCRIPTION OF THE PROCESS FOR PREPARING AND APPROVING RESETTLEMENT PLANS. To address the impacts under this policy, sub projects resettlement plans must include measures to ensure that the displaced persons are; a) informed about their options and rights pertaining to resettlement b) consulted on, offered choices among, and provided with technically and economically feasible resettlement alternatives c) and provided prompt and effective compensation at full replacement cost for losses of assets and access attributable to the sub project. Before implementation of the subproject, three interrelated documents will have to be prepared, namely, a) A socio-economic study (this study will include determination of impacts) b) Resettlement plan c) A valuation report of land and landed properties of the site 4 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP The purpose of the socio-economic study is to collect base line data within the project targeted areas thereby enabling the social assessment of potentially affected populations/communities. Under this study a comprehensive census would be carried out to identify potentially affected people on the individual and household levels, vulnerable groups (women, children, the elderly, female headed households, etc.). The social assessment would focus on identification of stakeholders (demographic data), the participation process, identification of affected people and impact on their property and their production systems, the institutional analysis and the system for monitoring and evaluation. Detailed calculation of household economies and identification of all impacts will be necessary in the social assessment and be the determinant in the potential compensation process. The components of the sub project resettlement/compensation plan will be: • Description of the Sub project • Potential Impacts • Sub project Objectives • Relevant findings of the socio-economic study • Legal framework • Institutional framework • Eligibility • Valuation of and compensation of losses • Resettlement measures • Site selection, site preparation, and relocation • Housing, infrastructure and social services • Environmental protection and management • Community participation • Integration with host populations • Grievance procedures • Organizational responsibilities • Implementation schedule • Costs and budget • Monitoring and evaluation The local communities who are to be assisted by PADEP, will be advised during the subproject identification/preparation stage whether of not the resettlement policy will be triggered. At that stage the local community may decide to drop the sub project on that basis. If they chose to continue with the sub project, however, then they will be advised to prepare a resettlement plan, and will be assisted to do so. The resettlement plan will then be forwarded for screening and approval through the District Council in compliance with the project institutional administrative arrangements. The Ministry responsible for Agriculture and Food Security will have representatives to provide the necessary technical support required at this level. Sub projects requiring resettlement plans that are approved at the district level will be subject to final screening by the PADEP Project Coordination Unit. The EA and resettlement plans would also be reviewed and approved by the Bank to ensure compliance with Bank Safeguards, thereby 5 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP ensuring that before the sub project is approved for funding by the Bank, the resettlement plans are consistent with this framework policy. Therefore, each sub project that is proposed to be included would be screened and classified according to its environmental and social impact. The screening and classification process should follow certain criteria already established and the mitigation measures that will be proposed vis a vis environmental and social issues should be in compliance with all Government of Tanzania environmental policies and World Bank Safeguard policies. Certain activities will not be funded by the project, including those likely to trigger selected safeguards for e.g. disputed areas, cultural property, indigenous peoples and natural habitats. The DMT will screen the proposed sub projects that it receives from the beneficiaries. The Screening Process The screening process would take the form of: General sub project sub sector classification: a. Dam construction b. Expand irrigated areas c. Expanded land areas or consolidation in order to make more rational use of land Agro-ecological zonal location of Sub project • Coastal zone • Semi-arid zone • Highland zone • Mountainous zones 1.) Classifying the sub projects by activity into the following categories; Identification of the type of sub-project, and determination of whether the sub- project will entail repair/ rehabilitation or new construction. In general sub- projects that repair and/or rehabilitate existing infrastructure will not trigger the resettlement policy. Those that entail new construction are more likely to trigger the policy if the activity involves acquisition of land and if displacement or restriction of access may result. Types of activity might require resettlement plans include the following, inter alia; e.g., i) Dam construction ii) Expanded irrigated areas iii) Expansion or consolidation of land areas to improve use 2.) Identifying and evaluating potential impacts for each proposed sub project according to whether land is acquired and whether displacement or loss of access may result. 3.) Triggering of the resettlement policy will be one criterion by which sub projects can be rejected. 6 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 4.) Alternatively, triggering of the resettlement policy would require further a preliminary determination of whether the sub project should be proposed or not, based on an assessment of the intensity of the impact and on the mitigation measures that would need to be developed and proposed. The communities and/or farmer groups may then determine whether or not to proceed to present the proposal to the DMT even where extensive/cumbersome mitigation measures are deemed necessary in the sub project. Determining the need for land acquisition and, if so, whether it is necessary to obtain legal title to the land. Under the right-of-occupancy land tenure system, legal title as expressed in a property deed is not always necessary. 5.) Use of the Socio Economic Studies to identify affected people on the household level and vulnerable groups in the sub project impact area(s) and to calculate household economies. 6.) Using the environmental assessments 7.) Ensuring that land required/acquired is not, (i) in disputed areas, (ii) cultural property, (iii) negatively affecting indigenous peoples and (iv) is not in natural habitats. This is a pre-condition for approval. The above screening process should be used by the local communities assisted by technical personnel in the district in the preparation of their sub projects to enhance likelihood approval. At the level of the DMT, project proposals will be reviewed according to the same criteria. The DMT would also review the sub project Environmental Assessment (EA) reports. Furthermore, the DMT should as a guideline consider the cumulative factor and not approve sub projects that have individual high impact intensity. For example, where land acquisition is required to such an extent that it would require more than 20% of a community’s or individual household’s total land under cultivation or when the mitigation measures are so cumbersome that their efficacy cannot be ensured or they cost more than 20% of the investment budget, district authorities should in general reject such proposals. Before a decision to approve a sub project requiring a resettlement plan is taken, the DMT will need to approve the resettlement plan of the sub project together with the overall environmental and social screening process that has been applied for each sub project and to also approve or disapprove of the proposed mitigation measures, if any. With respect to PADEP in Tanzania the following is a sample of possible sub projects that may be proposed by the communities and/or farmer groups that would trigger the involuntary resettlement policy with probable environmental and social impact; Sub project Impact OP 4.12 Construction of Dams for Irrigation and water supply Land acquisition, lack of access, loss of shelter. Risk of flooding. Yes Expansion of areas under irrigation -as above -as above 7 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Expansion of area or consolidation of parcels for improved agricultural production -as above -as above The sub projects are expected to be small in scale. The cumulative effect of hundreds of sub projects, however, may be significant and a review must be made at a level higher than the community level on the possible cumulative impact of the sub projects. If the impact is significant, individual mitigation measures per sub project should be assessed to determine their adequacy relative to the cumulative impact. When the cumulative impact of sub projects is being considered at the local, regional and/or national levels, additional mitigation measures may be deemed necessary. These would have to be integrated into the resettlement plans of sub projects and the monitoring and evaluation plan of the project. Capacity will be built at the community levels by providing technical assistance to allow communities to screen their sub-project ideas for environmental and social concerns. This training will also include the capacity to develop mitigation measures to meet environmental and social impacts and to prepare implementation of such measures. Capacity will also be built at the decentralized (departmental) levels of the district authorities as well as at national level of the Ministry of Agriculture and Food Security to assist them effectively to carry out their role at both the district levels and at the central levels. District Facilities Teams that are required to work with local communities should be targeted for training to enhance their skills and to produce more of them. This would build capacity at the local level, which is crucial for the success of this project. Communities and/or farmer groups may use the templates below during the PRA process to determine whether or not proposed sub-projects will entail acquisition of land, and if so, who may be among the affected people. 8 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP PARTICIPATORY AGRICULTURAL DELOPMENT AND EMPOWERMENT PROJECT SUBPROJECT LAND REQUIREMENT AND ACQUISITION FORMS (a); Existing land resources 1. Name of Village:……………………………………. Postal Address: P. O. Box…………………District ……………….Region ……………………. 2. Current land tenure/ownership in the village Ha. • Individual land...……………………………………………………………....……. • Household land …………………………………………………..… ……………... • Community land, e.g. belonging to religious organizations, • CBOs, other (specify) .………………………………………… ….………...……. • Village land (under Village Government) ………………… … …….………...….. • Government land (under Central Government) ………………….. ……...……….. TOTAL LAND RESOURCES …………………………..…….. 3. Subproject land requirement..….…….. 4. Agreement to meet subproject land requirement, as per Village Government Meeting of (day/month/year) and confirmed by Village Assembly of (day/month/year) Sample form for agreement regarding identification of land needed for a sub-project: With compensation Ha Without compensation Ha Sub- total Ha Wholly from village land Partly as follows: From individual land From household land From community land From village land From government land Grand-total allocation Assessment of overall current land use 9 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP Tenure system Current land use in ha. Remarks Fallow Cropped Grazing/ pasture Forest Mixed (specify) Individual land Household land Community land Village land Government land TOTAL Assessing current use of earmarked land Tenure system Current land use in ha. Remarks Fallow Cropped Grazing/ pasture Forest Mixed (specify) Individual land Household land Community land Village land Government land TOTAL 10 WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 11 Analyzing Subproject land allocation from individual land with corresponding compensation Name of individual With compensa tion Ha Compens ation rate /ha TShs. Compensat ion per individual TShs. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. Total The first table above gives an overview of the land resources available in the village. The next table shows the current land use in overall terms while the next gives the current land use of that land which is earmarked for allocation to the development project. The last specifies the contribution of individuals to the land earmarked for the subproject, and the agreed compensation. D. SUBPROJECTS IDENTIFIED CATEGORIES OF POTENTIAL IMPACTS Generally, the subprojects, which are likely to be proposed by community, are individually not expected to generate major negative environmental impacts to the human and natural environment. However, their cumulative impacts could be significant. Again, based the types of possible projects to be funded by PADEP, potential negative social and environmental impacts are presented in the Table below, together with their mitigation measures. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 12 Table 2.1: Potential negative impacts & mitigation measures by PADEP possible subproject types Subproject type Potential impacts Mitigation measures Watershed management for soil and water conservation Land use conflicts, loss of land and property Illegal harvesting Encroachment Lost opportunities Infringement on property rights Awareness raising Participatory land use planning and management Application of the Resettlement Policy Framework (resettlement and compensation) By-laws and their effective enforcement Joint management programmes Provision of alternatives Conservation tillage Contamination of ground water table and river pollution Disturbance on ecological functioning of farming systems Loss of historical/cultural sites Reluctance to reduce plowing Soil conservation measures Fertilization management Proper residue management Awareness raising IPM Proper site selection Efficient use of fertilizers Health risks Salinization Surface & groundwater contamination/pol lution Dust Air pollution Promoting weed growth Conduct training of safe use Use of high grade fertilizers Salinity monitoring Integrated soil fertility management Provision of protective gear Bringing the moisture content to 7-8 percent Biodiversity assessment and monitoring Fuel efficient technology Ground water pollution Ammonia losses Effect on vegetables and fodder Control surpluses of slurry Cover the soil Locate far from residential settings Different design concepts WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 13 Increasing productivity through use of organic manure in combination with mineral fertilizers, bio-fertilizers Salinization of soils Contamination of surface and groundwater Loss of plant species Awareness and training Promote high value crops Use of high grade fertilizers Integrated plant nutrition techniques/strategies (PNS) Salinization of soils Pollution of surface and groundwater Loss of some plant Health risks Awareness and training Salinity monitoring Integrated soil fertility management Promoting weed growth Integrated pest management (IPM) Soil contamination Water resources pollution Loss of animal and plant species Awareness and training High value crops Conduct biodiversity assessment and monitoring Increased use of labour saving technologies Loss of soil fertility Loss of water sources Loss of plant and animal species Potential land conflicts Employ farm management principles Use of appropriate technology Awareness raising Participatory land-use planning Gender awareness in selection of technology Use of rainwater harvesting techniques Contamination of stored water Siltation due to erosion Potential floods during heavy rains Water and land use conflicts Land degradation at livestock watering points Awareness & training on safe handling and storage Disinfections By-laws and their effective enforcement Provision of safe watering points/structures for livestock Participatory planning Improvement of traditional irrigation schemes Land and water use conflicts Loss of land and property Water-borne diseases Secondary water uses (domestic, Awareness & training Participatory land and water use planning & management, e.g. WUAs Application of the Resettlement Policy Framework (resettlement and compensation). By-laws and enforcement Provide for domestic and livestock WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 14 livestock) Infringement on access and movement for humans and livestock Water logging Poor water quality esp. for downstream users water supply Include access crossings at convenient locations for people and livestock Provide for drainage of tail waters Improvement in livestock production Overgrazing Land degradation Health risks from use of acaricides in dips Gas emissions Awareness & training Observing land carrying capacity Combine with biogas technology Production of non- traditional crops Soil contamination Introduction of new pests Loss of habitats and species Quarantine Adherence to regulations Awareness & training Biodiversity assessment and monitoring Supply of farm inputs Wastes from packaging materials plastics, tins and cans Livestock and wildlife might consume the plastic materials Health risks from agro-chemicals Proper disposal of wastes Institute by-laws Awareness & training Provision of protective gear Initial processing of agricultural and livestock products Wastes from processing Contamination of products Vibrations Soil and liquid wastes from processing might affect plant and animal species Provide for proper waste disposal Ensure hygienic conditions Conduct biodiversity assessment and monitoring Provision of protective gears, health insurance, awareness raising Adherence to industrial health regulations Improvement of crop produce marketing Wastes at markets Contamination of products Soil contamination Poor sanitation Waste management strategies Design an appropriate sanitary land- fill Provide for water supply and sanitation facilities WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 15 E. ELIGIBILITY CRITERIA FOR DEFINING VARIOUS CATEGORIES OF AFFECTED PERSONS At this stage it would not be possible to attempt to quantify the estimated likely number of people who may be affected since the sub projects have not been created. However, the likely displaced persons can be categorized into three groups, namely; i) Affected Individual - An individual who suffers loss of assets or investments, land and property and/or access to natural and/or economical resources as a result of the sub- projects and to whom compensation is due. For example, an affected individual is a person who farms, or who has built a structure on land that is now required by a sub project for purposes other than farming or residence by the initial individuals. ii) Affected Household - A household is affected if one or more of its members is affected by project activities, either by loss of property, land, loss of access or otherwise affected in any way by project activities. This provides for: a) any members in the households, men, women, children, dependent relatives and friends, tenants. b) vulnerable individuals who may be too old or ill to farm along with the others c) relatives who depend on one another for their daily existence. d) any members in the households, men, women, children, dependent relatives and friends, tenants, and e) Other vulnerable people who cannot participate for physical or cultural reasons in production, consumption, or co-residence. Compensation will not be limited to people who live together in a co-resident group, since this might leave out people whose labor contributions are critical to the functioning of the “household”. iii) Affected local community – A community is affected if project activities affect their socio-economic and/or social-cultural relationships or cohesion. For example project activities could lead into such improvement of socio-economic welfare that class- consciousness arises coupled with cultural erosion etc. iv) Vulnerable Households - vulnerable households may have different land needs from most households or needs unrelated to the amount of land available to them.: a) unmarried women b) Non-farming c) Elderly d) The infirm or ill e) Orphans Each category of vulnerable person or household must be compensated according to the nature of the economic loss suffered by loss of access to or use of the land acquired by the sub-project. The Bank’s OP4.12 suggests the following three criteria for eligibility; WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 16 a) Those who have formal legal rights to land (including customary and traditional rights recognized under the laws of Tanzania); b) Those who do not have formal legal rights to land but have a claim to such land or assets- provided that such claims are recognized under the laws of Tanzania or become recognized through a process identified in the resettlement plan. c) Those who have no recognizable legal right or claim to the land they are occupying. Those covered under a) and b) above are to be provided compensation for the land they lose, and other assistance in accordance with the policy. Persons covered under c) above are to be provided with resettlement assistance in lieu of compensation for the land they occupy, and other assistance, as necessary, to achieve the objectives set out in this policy, if they occupy the project area prior to a cut-off date established by the Government of Tanzania and acceptable to the Bank. Persons who encroach on the area after the cut-off date are not entitled to compensation or any other form of resettlement assistance. All persons included in a), b) or c) above are to be provided with compensation for loss of assets other than land. Therefore, it is clear that all affected persons irrespective of their status or whether they have formal titles, legal rights or not, are eligible for some kind of assistance if they occupied the land before the entitlement cut-off date. The entitlement cut-off date refers to the time when the assessment of persons and their property in the project area is carried out, i.e. the time when the project area has been identified and when the socio-economic study is taking place. Thereafter, no new cases of affected people will be considered. Persons who encroach the area after the socio-economic survey (census and valuation) are not eligible for compensation or any form of resettlement assistance. Eligibility for Community Compensation Local Communities (villages, cantons wards; divisions etc) permanently losing land and/or access to assets on under customary rights will be eligible for compensation. F. A LEGAL FRAMEWORK COMPARING THE BORROWER LAWS AND REGULATIONS WITH THE BANK POLICY REQUIREMENTS AND MEASURES PROPOSED TO BRIDGE ANY GAPS BETWEEN THEM. LAND TENURE AND OWNERSHIP Land in Tanzania is owned by the state, and ownership is vested with the President. It is categorized as follows: general/public land on which socio-economic activities are permitted; reserved/restricted lands for national parks; protected areas; and forest/wildlife reserves. About 25% of Tanzania falls into the category of reserved/ restrictive. By international standards this is a high proportion of land under restriction.. Only about 20% of potentially arable land is actually cultivated. Communities and individuals are not permitted to use reserved or restricted land for economic activities. Land is so designated by order of the President or the Minister charged with conservation of natural resources. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 17 Tenure rights to land in the first category can be held by individuals and by communities. Village communities are allowed to hold land and to manage it, although they do not formally own the land. Holdings of individuals can be as follows:- • By leasehold right of occupancy for varying periods; e.g. for 33,66,99 years • By customary lands i.e. in usufruct in perpetuity. Tenure rights are defined by the Land Act and the Village Act. The Land Act No. 5 of 1999 provides for village land to be administered and managed by the local communities. Land that is not village land can be allocated by the state to users under specified tenure regimes. In addition, Participatory Land Use Planning and Management (PLUM) is explicitly recognized in the Land Policy of 1995. The adjudication function on village lands is assigned to the village government. Taxation is the prerogative of local authorities. Villagers hold rights of occupancy and use for an indefinite (i.e., unlimited) period. Village lands do not have to be titled for rights of users and occupants to be recognized, and are not subject to rental payments. Security of tenure is not a major issue at the village level. In accordance with provisions of the Tanzanian legal framework, a process for preparing and approving resettlement plans should be based on PLUM (with technical assistance of relevant district functional officers). The Village government should therefore be able to: • Review the proposal to prepare a resettlement plan • Discuss the proposal in its village organs • Prepare and agree on proposals of the resettlement plan • Approve the resettlement plan subject national legislations esp. Land Act no. 4 of 1999 and Land Acquisition Act of 1967. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 18 Land Tenure for Sub Projects Village government has administrative control over the village land and acts as a liaison between the government and the inhabitants of the village. Within villages, use of land is controlled by various committees of village government. At present, local communities are operating on their own land. However, if their sub projects require more land, extension of their existing land or new land, they would have to acquire the land through the village government. G. METHODS OF VALUING AFFECTED ASSETS The valuation of affected assets will be carried out by estimation of the market value, when it is known, and/or by estimation of the replacement cost. Graves are valued separately – under the Graveyard Removal Act of 1968.. Valuations methods for affected land and assets would depend on the type of asset. The land asset types identified under Tanzania law in this policy framework are; i) State Land not within the jurisdiction of a village ii) Village Land, including customary rights of villagers State owned land would be allocated free (perhaps except for surveying and registration fees), and the sub project would be expected to pay to acquire land in this category in cases where the state-owned land is being used by individual farmers. This is because, although state owned, the land may be used by individuals and/or household farmers. The guiding principle is that whoever was using the land to be acquired by the sub project, would be provided other land of equal size and quality. Assets held under customary rights on state owned land would have to be valued according to the following method and compensation paid for. The sub projects would value and duly compensate for assets and investments, including land, crops, buildings, and other improvements, according to the provisions of the resettlement plan. Compensation rates would be market rates as of the date and time that the replacement is to be provided. The current prices for cash crops would have to be determined. Compensation would be based on valuation at or before the entitlement cut off date in compliance with this policy. Homestead sites such as bush are community property. Only structures on the site belong to individuals. The permanent loss of any homestead site will be covered by community compensation which will be in-kind only. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 19 Compensation for Land Compensation is intended to provide a farmer whose land is acquired and used for sub project purposes with compensation for land, labor, and crop loss. For this reason, and for transparency, land is defined as an area: • In cultivation • Being prepared for cultivation, or • Cultivated during the last agricultural season This definition recognizes that the biggest investment a farmer makes in producing a crop is his or her labor. A farmer works in his/her land ,most of the months of the year. The major input for producing a crop is not seed or fertilizer, but the significant labor put into the land each year by the farmer. As a result, when land acquired has a standing crop, the farmer will be compensated in full for the expected market value of the crop. This compensation will cover loss of investment of labor and purchased inputs for the production year in question. FORMS OF COMPENSATION Cash Payments Compensation will be calculated and paid in the national currency. Rates will be based on the market value of land when known, or estimated when not known, plus compensation for the value of standing crops. In-Kind Compensation Compensation may include items such as land, houses, other buildings, building materials, seedlings, agricultural inputs and financial credits for equipment. Assistance Assistance may include moving allowance, transportation and labor Because land market transactions are not recorded in Tanzania, market values may not be observable, and will have to be imputed through simple estimation of discounted loss of the stream of future income derived from land. As an approximate rule in a country with ample land and labor-intensive agriculture, the contribution of land can be imputed as about 25% of the gross market value of output. The present value of this future income stream in perpetuity, when discounted back to the present at a discount rate of 12% amounts to approximately twice the average annual value of output. Therefore a person who gives up a parcel of agricultural land for use by a sub-project could be adequately compensated in cash in the amount of twice the average value of gross annual output (plus the additional value of the standing crop, if any). Compensation in kind would take the form of provision of an alternative parcel of equal size and quality. If cash compensation is used, financial institutions should encourage the use of their facilities to reduce likelihood of loss or theft when beneficiaries are compensated in cash. Each recipient in consultation with the project implementation unit will decide upon the time and place for in-kind compensation payments. A subproject that interferes with pastoralists or grazing land will not be approved for financing by the Project unless the affected people have been offered alternative land as compensation in kind and acceptable to the affected people. Compensation for buildings and Structures. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 20 Compensation will be paid by replacing structures such as huts, houses, farm outbuildings, latrines, and fences on alternative land provided as in-kind compensation. Cash compensation would be available as a preferred option for structures (i.e. extra buildings) lost, that are not the main house or house in which someone is living. The going market prices for construction materials will be determined. Alternatively, compensation will be paid in-kind for the replacement cost without depreciation of the structure. Compensation will be made for structures that are: • Abandoned because of relocation or resettlement of an individual or household, or • Directly damaged by construction activities. Replacement values will be based on: • Related structures and support services • Average replacement costs of different types of homestead buildings and structures based on collection of information on the numbers and types of materials used to construct different types of structures (e.g. bricks, rafters, bundles of straw, doors etc.), • Prices of these items collected in different local markets, • Costs for transportation and delivery of these items to acquired/ replacement land or building site, • Estimates of construction of new buildings including labor required. Compensation for Sacred Sites The use of sacred sites, ritual sites, tombs and cemeteries is not permitted under this project. Compensation for vegetable gardens and beehives. These are planted primarily for use within the household. Until a replacement garden starts to bear, the family losing gardens or beehives will have to purchase vegetables and honey in the market. The replacement costs therefore, will be calculated based on the local market rates for these products at the time. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 21 Beehives are placed in various locations in the bush by some individuals that specialize in honey gathering. If such hives would be disturbed by the sub project activities, or access to the hives denied, beekeepers can move them, and the bees will adapt to the new locations. Activities of beekeepers would be valued and duly compensated based on value of one season’s production costs of honey for each hive that is moved and any reasonable costs associated with moving the hive. Large fruit and crop trees Large fruit/trees e.g. mangoes and coconut important as a source of: • Subsistence food for families • Petty market income in some areas, and • Shade Given their significance to the local subsistence economy, which this project intends to enhance, mango and coconut trees will be compensated on a combined replacement/market value. Mango and coconut trees used for commercial purposes will be compensated at market value based on historical production records. If households chose to resettle, they will be compensated for the labor invested in the trees they leave behind. The compensation rate will be based on information obtained from the socio-economic study. From this study, a compensation schedule for trees can be developed incorporating the following goals: • Replace subsistence mango and coconut production yields as quickly as possible. • Provide subsistence farmers with trees to extend the number of months of the year during which fruit is produced and can be harvested as a supplemental source of food for their families during their “hungry season”. • Provide farmers with the opportunity to derive additional production income from trees bearing more valuable fruits at off-season periods. • Provide cash payments to farmers to replace pre-subproject income derived from the sale of excess production until replacement trees produce the equivalent (or more) in projected cash income. It should be pointed out the Valuation Division in the Ministry of Lands and Human Settlements Development has developed crop compensation rates. These rates are to be reviewed every year. Compensation assessment must be approved by Chief Government Valuer. Displaced people have to be issued with land form 59 and 70 which allows them to indicate what they expect to be compensated. The compensation schedule is based on providing a combination of new grafted and local trees to farmers, as well as cash payments to offset lost yearly income. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 22 Proposed Schedule for Mango and Coconut Trees Cut Down Type/Age of Tree Est. Years In-kind replacement for Local Mangoes Sapling Trees planted after sub project cut-off date in area will not be eligible for compensation 0-1 Deliver to Farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade. Sapling/Young Tree First minor production 12-50 fruits occurs about age 4-5 1-6 Deliver to farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade Mango Trees Fruit Producing 6-30+ Deliver to farmer: • Choice of two mango trees (local and/or improved grafted) • Supplies: fencing to protect Tree, a bucket for watering, and a spade Mature Trees – Low or Non- Fruit Producing 30+ Same as for mature trees above No compensation will be paid for minor pruning of trees. Compensation for removal of limbs will be prorated on the basis of the number of square metres of surface area removed. The total surface area of the tree will be calculated using the following formula: (½ diameter of canopy) 2 x 3.14. Other domestic fruit and shade trees. These trees have recognized local market values. Depending upon the species and age. Individual compensation for wild trees “owned” by individuals, who are located in lands as defined in this policy, will be paid. Note that wild, productive trees belong to the community when they occur in the true bush as opposed to a fallow land. These trees will be compensated under the umbrella of the village or community compensation. Examples include: avocado, bananas, lemon, guava, lime, oranges, grapefruits, papaya, tamarind etc. INDIVIDUAL COMPENSATION Sub-Category Unit Compensation Value (TSHS) WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 23 Foodstuffs & others Domestic Fruit Trees Avocado Non-productive productive 13,000 Banana Non-productive productive 11,000 Lemon Non-productive productive 5,000 Guava Non-productive Productive 6000 Lime Non-productive Productive 5,000 Orange Non-productive Productive 14,000 Grapefruit Non-productive Productive 2,000 Papaya Non-productive productive 4,000 Shade Trees Young 2,000 adult 5,000 Individual Owned Wild Productive Trees Non-productive 13,000 Tamarind productive Crops Yield/ha 1,200 110,000 Maize Rice Yield/ha 1,000 180,000 Beans Yield/ha 500 87,000 Vegetables Yield/ha 8,300 220,000 Tomatoes Water melon Yield/ha 8,300 860,000 Lettuce Yield/ha 3,500 305,000 Cauliflower Yield/ha 5,000 275,000 Carrot Yield/ha 10,000 880,000 H. ORGANIZATIONAL PROCEDURES FOR DELIVERY OF ENTITLEMENTS, INCLUDING, FOR PROJECTS INVOLVING PRIVATE SECTOR INTERMEDIARIES, THE RESPONSIBILITIES OF THE FINANCIAL INTERMEDIARY, THE GOVERNMENT, AND THE PRIVATE DEVELOPER. Compensation (and resettlement) will be funded like any other activity eligible under the projects’ administrative and financial management rules and manuals. Payments will be included WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 24 in the costing of the project, and finances for the payments will be made available to the communities and/or farmer groups through the usual flow of funds. For sub-projects involving payment of compensation, monitoring activities will include confirmation that payments were received by those entitled to them. The compensation process will involve several steps and would be in accordance with the sub- project resettlement plans, significantly; • Public Participation: Local communities would initiate assessment of the appropriateness of compensation at the concept stage of the sub project. Affected individual/households will be invited to become involved in design activities. • Notification Affected individuals and households will be identified during the PRA process and notified. The user will be informed through both a formal notification in writing and, as many as people are illiterate, by verbal notification delivered in the presence of the village chief or his or her representative. In addition, the chairman, village chiefs committees individuals who control fishing areas, wild trees, or beehives will accompany the survey teams to identify sensitive areas. • Documentation of Holdings and Assets – village officials and District Project Officer to arrange meetings with affected individuals and/or households to discuss the compensation process. For each individual or household affected, the District Project Officer completes a compensation dossier containing necessary personal information on, the affected party and those that s/he claims as household members, total land holdings, inventory of assets affected, and information for monitoring their future situation. This information is confirmed and witnessed by village officials; Dossiers will be kept current and will include documentation of lands surrendered. This is necessary because it is possible that an individual will surrender several parcels of land over time and will eventually become eligible for resettlement. All claims and assets will be documented in writing. • Agreement on Compensation and Preparation of Contracts – All types of compensation are clearly explained to the individual or household. The District Project Officer (DPO) draws up a contract listing all property and land being surrendered, and the types of compensation (cash and/or in-kind) selected. A person selecting in-kind compensation has an order form, which is signed and witnessed. The compensation contract is read aloud in the presence of the affected party and the village Chairman and other village leaders prior to signing. • Compensation Payments – All payments and transfers in kind will be made in the presence of the affected party and the village authorities. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 25 Community Compensation Payments Community compensation will be in-kind only for a community as a whole in the form of reconstruction of the facility to at least the same standard or better standard to that being built by local NGO’s. Examples of community compensation include, • School Building (public) • Public Toilets • Well or Pump • Market Place • Road • Storage warehouse I. A DESCRIPTION OF THE IMPLEMENTATION PROCESS, LINKING RESETTLEMENT IMPLEMENTATION TO CIVIL WORKS. Before any project activity is implemented, people who are affected and have been determined to be entitled to compensation will need to be compensated in accordance to the policy and the resettlement policy framework. For sub projects involving land acquisition, it is further required that these measures include provision of compensation and of other assistance required for relocation, prior to displacement, and preparation and provision of resettlement sites with adequate facilities, where required. In particular, the taking of land and related assets may take place only after compensation has been paid and, where applicable, resettlement sites and moving allowances have been provided to displaced persons. For sub projects requiring relocation or loss of shelter, the policy further requires that measures to assist the displaced persons be implemented in accordance with the sub project’s resettlement plan of action. The measures to ensure compliance with this policy directive would be included in the resettlement plans that would be prepared for each sub project involving resettlement or compensation. The timing mechanism of these measures would ensure that no individual or affected household would be displaced due to civil works activity before compensation is paid and resettlement sites with adequate facilities are prepared and provided for to the individual or household affected. Once the resettlement plan is approved by the local and national authorities, the resettlement plan should be sent to the World Bank for review and approval. J. A DESCRIPTION OF GRIEVANCE REDRESS MECHANISMS. At the time the resettlement plan is approved and individual compensation contracts are signed, affected individuals would have been informed of the process for expressing dissatisfaction and to seek redress. The grievance procedure will be simple, administered as far as possible at the local level to facilitate access, flexible and open to various proofs taking into cognizance the fact most people are illiterate requiring a speedy, just and fair resolution of their grievances. Communities and/or farmer groups will in general be a party to the contract would not be the best organizations to receive, handle and rule on disputes. Therefore, taking these concerns into account, all grievances concerning non-fulfillment of contracts, levels of compensation, or seizure of assets without compensation should be addressed to the district authorities either in writing or in person. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 26 In the local cultures it takes people time to decide that they are aggrieved and want to complain. Therefore, the grievance procedures will give people up to the end of the next full agricultural season after surrendering their assets to set forth their case. All attempts would be made to settle grievances. It is anticipated that the PRA process in land acquisition would avoid, or at least minimize complaints arising from the loss of land and resources as a result of implementing any subproject. However, should any complaint still arise, it addressed as follows: • The Community or Farmer Group Subproject Committee would discuss the matter as the case may be. • The outcome would be reported to the Village Government for records, if it is resolved or for further action if it were not resolved at the Subproject Committee level. If the Village Council cannot settle the complaint, a special Village Assembly should be convened to make a final decision on the fate of the subproject. Individual and household compensation will be made in cash, in kind, and/or through assistance. The type of compensation will be an individual choice although efforts will be made to encourage in kind compensation if the loss amounts to more than 20% of the total loss of subsistence assets. Depending on the nature and significance of grievances; PADEP's redressing mechanisms will incorporate interrelated approaches, which are based on the following two different legal institutional structures: - (a) central/local government legal- institutional structures: i.e. fully utilizing existing laid down legal institutional mechanisms e.g. the following: - • Local government acts and organizational structure • District council organizational structures i.e. including their laid down committees • Ward/ Village council organizational structures i.e. again including their laid down committees (b) PADEP institutional structure as stipulated Chapter 3 of the project Operational Manual: namely the following: - Community- level: village as a whole or farmer group levels which will implement PADEP subprojects through Subproject Committees (SC) duly elected by village Community Assemblies and Farmer Group Assembles. Aggrieved parties can air grievances either through central/ local government organs i.e. through village on to wards, divisions, districts and up to central government organic or strictly through PADEP’s institutional structure i.e. starting through farmers groups on to village/ community level, and their forward to District Project Officer, District Facilitation Team, District Executive Director, National Technical Steering Committee, ever as far as National Project Steering Committee. K. A DESCRIPTION OF MECHANISMS FOR CONSULTATIONS WITH, AND PARTICIPATION OF, DISPLACED PERSONS IN PLANNING, IMPLEMENTATION AND MONITORING. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 27 Public consultation and participation are essential because they afford potential displaced persons the opportunity to contribute to both the design and implementation of the sub projects. This fits perfectly with the demand driven nature of the PADEP project. The sub projects would be initiated, planned, designed, implemented and operated (i.e. demand driven) by communities and/or farmer groups who by their very nature are members of the rural community and therefore, are an integral part of and play a crucial role in the community that may be effected. Furthermore, it is the local communities who are to claim ownership of this project for it to be successful and their wealth of knowledge of local conditions are invaluable assets to the project. In recognition of this, particular attention would be paid to public consultation with potentially affected individuals/households when resettlement concerns are involved. Public consultation has taken place at the identification of the sub projects during the PRA process and EA. The participation strategy would evolve around the provision of a full opportunity for involvement. This process would not be an isolated one because of the very nature of the project, which through its implementation and design ensures continuous public participation and involvement at the local level. Therefore, as a matter of strategy, public consultation would be an on-going activity taking place through out the entire project cycle. For example, public consultation would also occur during the preparation of the; (i) the socio- economic study, (ii) the resettlement plan and (ii) the environmental assessment and (iv) during the drafting and reading of the compensation contract. Public participation and consultation would take place through meetings, radio programmes, request for written proposals/comments, filling in of questionnaires/forms, public readings and explanations of sub project ideas and requirements, making public documents available at the regional, district, canton and village levels at suitable locations like the official residences/offices of local leaders/elders. These measures would take into account the low literacy levels prevalent in these communities by allowing enough time for responses and feedback. Notwithstanding, the best guarantor for public interest is the communities and farmer groups who are responsible members of their local communities and are very likely to be knowledgeable about the likely impact of the project. Monitoring of this process would be through the overall monitoring and evaluation mechanism of the entire PADEP project. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 28 L. ARRANGEMENTS FOR MONITORING BY THE IMPLEMENTING AGENCY AND, IF REQUIRED, BY INDEPENDENT MONITORS. The arrangements for monitoring would fit the overall monitoring plan of the entire PADEP project which would be through the PCU and decentralized to the DMT and DFT which is expected to have monitoring and evaluation guides established and functional by end of year one in the project cycle. The objective will be to make a final evaluation in order to determine if the people who were affected by the project have been affected in such a way that they are now living at a higher standard than before, living at the same standard as before, or they are they are actually poorer than before. For sub-projects triggering the resettlement safeguard, indicators tracking the households affected by the acquisition of land will be assessed in comparison to those of households not affected. The resettlement plans will indicate parameters to be monitored, institute monitoring milestones and provide resources necessary to carry out the monitoring activities. In order to access whether these goals are met, the resettlement plans will indicate parameters to be monitored, institute monitoring milestones and provide resources necessary to carry out the monitoring activities. For example the following parameters and verifiable indicators will be used to measure the resettlement plans performance; • Questionnaire data will be entered into a database for comparative analysis at the DMT and PCU levels, • Each individual will have a compensation dossier recording his or her initial situation, all subsequent sub project use of assets/improvements, and compensation agreed upon and received. • The project will maintain a complete database on every individual impacted by the project land use requirements including relocation/resettlement, land impacts or damages • Percentage of individuals selecting cash or a combination of cash and in-kind compensation, • Proposed use of payments • The number of contention cases out of the total cases • The number of grievances and time and quality of resolution • Ability of individuals and families to re-establish land and crops or other alternative incomes • Agricultural productivity of new lands • Number of impacted locals in the workforce • Seasonal or inter annual fluctuation on key foodstuffs • General relations in the local communities WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 29 The following indicators will be used to monitor and evaluate the implementation of resettlements plans; VERIFIABLE INDICATORS Monitoring Evaluation Outstanding compensation or resettlement contracts not completed before next agricultural season. Outstanding individual compensation or resettlement contracts. Communities unable to set village-level compensation after two years. Outstanding village compensation contracts. Grievances recognized as legitimate out of all complaints lodged. All legitimate grievances rectified Pre-sub project production and income (year before land used) versus present production and income of resettlers, off- farm-income trainees, and users of improved agricultural techniques. Affected individuals and/or households compensated or resettled in first year that have maintained their previous standard of living at final evaluation. Pre- subproject production versus present production (crop for crop, land/land for land/land). Equal or improved production per household. Financial records will be maintained by the DMT/PCU to enable calculation of the final cost of resettlement per individual or household. Each individual receiving compensation will have a dossier containing; • Individual bio-data information, • Number of people s/he claims as household dependents • Amount of land available to the individual or household when the dossier is opened. Additional information will be acquired for individuals eligible for resettlement/compensation: • Level of income and of production • Inventory of material assets and improvements in land, and • Debts. Each time land is used by the project; the dossier will be updated to determine if the individual or household is being affected to the point of economic non-viability and eligibility for compensation/resettlement or its alternatives. These dossiers will provide the foundation for monitoring and evaluation, as well as documentation of compensation agreed to, received, and signed for. WORLDBANK/GOVERNMENT OF Tanzania RESETTLEMENT POLICY FRAMEWORK PADEP 30 It is normal that some compensation procedures and rates may require revision at some time during the project cycle. PCU and DMT will implement changes through the Change Management Process in the Monitoring and Evaluation manuals of the project, which will require feed back from: • Indicators monitored by the DMT to determine whether goals are being met, and a grievance procedure for the local community to express dissatisfaction about implementation of compensation and resettlement. | false |
# Extracted Content TRAINING GUIDE FOR CLIMATE SMART AGRICULTURE PRACTICES AND TECHNOLOGY PRACTITIONERS UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES TRAINING GUIDE FOR CLIMATE SMART AGRICULTURE PRACTICES AND TECHNOLOGY PRACTITIONERS UNITED REPUBLIC OF TANZANIA MINISTRY OF AGRICULTURE LIVESTOCK AND FISHERIES ii TABLE OF CONTENTS TABLE OF CONTENTS .................................................................................................................. ii ACRONYMS .................................................................................................................................. iii INTRODUCTION .......................................................................................................................... v CHAPTER ONE ............................................................................................................................. 1 1. TOPIC 1: CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE .................................................. 1 CHAPTER TWO ............................................................................................................................. 3 2. TOPIC 2: CLIMATE SMART AGRICULTURE ............................................................................................. 3 2.1 PERIOD 1: Concept of Climate Smart Agriculture ........................................................................ 3 2.2 PERIOD 2: Soil and Water Conservation Practices and Technologies...................................... 5 2.3 PERIOD 3: Conservation agriculture (CA) Practices and Technologies.................................... 6 2.4 PERIOD 4: Rain Water Harvesting and Irrigation Practices ........................................................ 7 2.5 PERIOD 5: Soil Fertility Management Practices ............................................................................. 8 2.6 PERIOD 6: Crop Management Practices and Technologies ....................................................... 9 2.7 PERIOD 7: Agroforestry Practices and Technologies ................................................................. 11 2.8 PERIOD 8: Adaptation Practices and Technologies in Livestock Keeping ............................. 12 2.9 PERIOD 9: Manure Management Practices .................................................................................. 14 2.10 Period 10: Climate Smart Agriculture in Fishing and Aquaculture ........................................ 15 2.11 PERIOD 11: Upscaling of Climate Smart Agriculture ................................................................. 17 CHAPTER THREE ......................................................................................................................... 19 3. TOPIC 3: CSA STAKEHOLDERS INVOLVEMENT ................................................................................... 19 CHAPTER FOUR .......................................................................................................................... 21 4. TOPIC 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS ............................................... 21 CHAPTER FIVE ............................................................................................................................ 23 5.TOPIC 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS ........................................... 23 iii ACRONYMS CSA Climate Smart Agriculture SUA Sokoine University of Agriculture FAO Food and Agriculture Organization of the United Nations MIN Minutes UNFCCC United Nations Framework Convention for Climate Change M&E Monitoring and Evaluation SACCOs Savings and Credit Cooperatives iv AKNOWLEDGEMENT This Training Guide has been prepared by a technical team from various Departments, Units and Agencies within the Ministry of Agriculture Livestock and Fisheries with a wealth of valuable information sourced from different stakeholders around the country including Sokoine University of Agriculture and World Vision. The Ministry is highly indebted to The Food and Agriculture Organization of the United Nations and DFID funded Vuna Climate Smart Agriculture Programme for the technical and financial support that enabled the preparation of this training Guide. Shakwaanande Natai Head - Environment Management Unit Ministry of Agriculture Livestock and Fisheries v INTRODUCTION Climate-Smart Agriculture is “agriculture that sustainably increases productivity, resilience (adaptation), reduces or removes Greenhouse Gases (GHGs) (mitigation) where possible, and enhances achievement of national food security and development goals” (FAO, 2010). However, in Tanzanian context, the adapted definition of Climate-Smart Agriculture is “agriculture that sustainably increases productivity and income, increases the ability to adapt and build resilience to climate change and enhances food and nutrition security while achieving mitigation co-benefits in line with national development priorities” (National Task Force Planning Workshop Report, 2016). CSA aims to achieve food security and broader development goals under a changing climate and increasing food availability using different practices and technologies. CSA practices and technologies on crop, livestock and fisheries aim at addressing tradeoffs and synergies between the three pillars; productivity, adaptation, and mitigation. By addressing challenges in environmental, social, and economic dimensions across productive landscapes, CSA practices and technologies also embrace priorities of multiple countries and stakeholders in order to achieve more efficient, effective, and equitable food systems. In understanding the importance of CSA in crops, livestock and fisheries production practices and technologies were identified and mapped according to Agro-Climatic Zones of Tanzania. These Practices and technologies serve as tools for deciding options within which the three CSA pillars can be achieved. It is because of the importance of CSA in the Tanzanian context that this Training Guide has been developed, in order to guide trainers on how to equip relevant stakeholders on the uptake of CSA practices and technologies within the agricultural sector. This guide is divided into five chapters whereby chapter 1 aims at helping users to understand some of the impacts of climate change and possible solutions for addressing climate related risks with regard to agriculture. It also provides an understanding of how changes in climate can affect agriculture and subsequently identifies best practices that will help farmers to adapt in their respective agro-climatic zones. Chapter 2 introduces in detail the concept of CSA practices and technologies in crop, livestock and fisheries production. Chapter 3 provides guidance on identification, roles and engagement mechanisms of different stakeholders on implementation of CSA related activities. Chapter 4 helps elaborate on issues related to mainstreaming of CSA into agricultural plans, programmes and budgets. Lastly, chapter 5 give guidance on how to carry out monitoring and evaluation of CSA related activities and interventions. It is important to note that, the effective use of this guide requires to go hand in hand with the use of CSA manual, Guideline document and other relevant materials as may be recommended in this training guide. The supplementary documents have detailed explanations and elaborations to help the trainer on preparation and development of the lessons. In this way, it is expected for the trainer to achieve intended learning objectives to the trainees. 1 1. TOPIC 1: CLIMATE CHANGE AND ITS IMPACT ON AGRICULTURE VENUE: Classroom DURATION: 60 Min SUB-TOPICS • Definition of terms • The Concept of Climate change • The impacts of climate change on agriculture • The impacts of agriculture on climate change • Climate change risks and vulnerabilities in agriculture • Adaptation and mitigation of climate change MAIN OBJECTIVE The main objective of the lesson is to enable participants to understand what climate change is, as well as its impact in agriculture so that they can be able to facilitate targeted group on appropriate measures for effective adaptation and mitigation of climate change in their respective agro-ecological zones. SPECIFIC OBJECTIVES It is expected that at the end of the lesson participants will be able to:- • Define key terms commonly used in explaining the impact of Climate Change in agriculture (Climate change, Risks, Vulnerability, Adaptation, and Mitigation) • Understand the concept of Climate Change • List at least five impacts of Climate Change on agriculture and three impacts of agriculture on climate change • Explain potential Climate Change risks and vulnerabilities in agriculture • Explain at least three potential adaptation actions and two mitigation actions LESSON DEVELOPMENT Start the lesson by giving a general introduction followed by explaining the main objective as well as specific objectives of the lesson. Ask participants few questions related to the subject matter in order to know their level of understanding of the subject, while listing all their answers on the writing board. Write proper answers on the writing board so that participants can compare. Continue with the lesson by defining five key terms commonly used when explaining the impact of Climate Change in agriculture. Explain clearly the concept of Climate Change by giving examples. Divide participants into groups depending on their number and ask each group to list five impacts of Climate CHAPTER ONE 2 Change on agriculture and three impacts of agriculture on Climate Change for 15 minutes. Ask each group to present their work while listing the results on the writing board. Thereafter, explain the impacts of climate change on agriculture and the impacts of agriculture on Climate Change and then conclude the lesson by summarizing and ask participant if they have any questions. TEACHING METHODS Lecturing, Plenary discussions, Question & Answers and group work/discussion TEACHING AIDS Video for Climate Smart Agriculture, internet access to play the video in real time or embed it in a PowerPoint ahead of time, writing board, marker pen/chalks, Posters, Flip Chart 3 2. TOPIC 2: CLIMATE SMART AGRICULTURE 2.1 PERIOD 1: Concept of Climate Smart Agriculture SUB TOPICS • Introduction to Climate Smart Agriculture • CSA Pillars • Characteristics of CSA Practice and Technologies VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand the concept of Climate Smart Agriculture. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain Climate Smart Agriculture • Identify Pillars of Climate Smart Agriculture • Characterize CSA Practices and Technologies LESSON DEVELOPMENT Start by probing the understanding of Climate Smart Agriculture (CSA) by asking participants the question “who can tell the meaning of CSA?” Write down answers from participants on a flip chart. Thereafter, give participants the definition of CSA as defined by FAO and make them aware of keywords (pillars of CSA) which are Productivity, Adaptation and Mitigation. Start with global definition followed by Tanzania definition which has emphasis on increased income, food and nutrition security, achievement of mitigation co-benefits through adaptation, but all should be in line with national development priorities. Explain in details, the need to practice CSA in light of climate change adaptation while achieving mitigation co-benefits because in Tanzania, adaptation is the key priority followed by mitigation. Examples should be given such as Tanzania and other developing countries are more vulnerable to the impact of Climate Change as compared to developed countries with ability to adapt and at the same time to mitigate the impact of climate change can be given to make the lesson more understood. Explain the three pillars of CSA (Productivity, Adaptation and Mitigation). Elaborate each pillar to the participants by explaining their actual meaning and what they intend to achieve through CSA. Give examples on how each pillar can be achieved through CSA to enhance understanding. Use illustrations or short relevant videos where possible. Then ask participants to form groups and allow them to discuss CHAPTER TWO 4 for 10 minutes if the aforementioned practices in their local area adhere to the three pillars of CSA and how. Allow groups to present their findings in plenary and let the groups ask two or three questions after each presentation. After all groups have presented, give overall feedback by emphasizing that, sometimes it’s hard to have all three pillars attained in one practice. Ask participants to give examples of CSA practices and technologies based on the definitions of CSA and the three CSA pillars. Note down the examples on the flip chart or writing board, and then give definition of CSA practices and technologies. Expand the definitions given by sharing examples of CSA practices and technologies readily available in the local areas, or by emphasizing on the ones already mentioned and move on to mention others which are not practiced in the geographical area but relevant. Lastly, discuss with the participants on the key characteristics of CSA. End the training session by asking questions to the participants about their understanding of CSA, CSA pillars, CSA practices and technologies. Give them training manuals/notes for further reading and referencing. TEACHING METHODS Plenary/group/group discussion questions and answers and lecture TEACHING AIDS Projector, Posters, Video on CSA, stationary (Flip chart, Exercise books, pens, marker pen), loud speaker 5 2.2 PERIOD 2: Soil and Water Conservation Practices and Technologies SUB TOPICS: • Meaning of soil and water conservation practices and technologies • Types of soil and water conservation practices and technologies • Suitable Soil and water conservation Practices and technologies in different agro-climatic zones VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe soil and water conservation practices and technologies that are used in the country, and in the different agro-climatic zones. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Comprehensively define the meaning of soil and water conservation practices and technologies • Mention different types of soil and water conservation practices and technologies • Describe the types of soil and water conservation practices and technologies and its suitability in different agro-climatic zones and for their localities. LESSON DEVELOPMENT Start by asking the participants what they know about the meaning and importance of soil and water conservation. Write on flip chart the answers and allow five minutes for plenary discussion. Thereafter write down on flip chart or project the meaning and importance of soil and water conservation. Ask participants to write on the card different types of soil and water conservation practices they know (each participant should write only one), place the card on board by grouping cards with the same answers together. Thereafter finish by projecting different types of soil and water conservation practices. Provide group work to the participants to write down on flip charts, the types of soil and water conservation practices and their suitability in different agro-climatic zones. Afterwards, groups should present their work and discuss. Thereafter project the types of soil and water conservation practices in different agro-climatic zones. Finish the lesson, by asking participants (sampling at two) questions on soil and water conservation practices and technologies. TEACHING METHODS Groups and Plenary discussion, Questions & Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Manila cards, Projector and Computer/laptop. 6 2.3 PERIOD 3: Conservation agriculture (CA) Practices and Technologies SUB TOPICS: • Meaning of Conservation agriculture • Types of conservation agriculture practices and technologies • Suitable conservation agriculture practices in different agro-climatic zones VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training participants will be able to understand conservation agriculture practices and technologies, their uses and suitability in different agro-climatic zones. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain the meaning of conservation agriculture • Mention different types of conservation agriculture practiced in the country • Identify different types of conservation agriculture practices suitable for their localities. LESSON DEVELOPMENT Introduce the subject by projecting a picture of CA practice/technology and allow five minutes for discussion. Thereafter, project on the board the meaning of conservation agriculture and explain the projected picture. Afterward, allow participants to discuss in groups and write on flip chart different types of conservation practices and their advantage to the environment. Then group representatives present their answers, and allow other group members to contribute and ask questions. Thereafter, write down on a flip chart or project different types of conservation agriculture and explain their importance. Then, provide manila cards to the participants to write conservation agriculture practices from their localities. Place the card on the board by grouping them based on similarities, this will help to know commonly used CA practices to allow the trainer to emphasize on the potential practices to be introduced or perfected in the area. At the end of the session, ask questions to the participants on conservation practices and technologies. TEACHING METHODS Brainstorming, Group discussion, questions & answers, Lecture. TEACHING AIDS Picture/Photo, Flip Chart, Maker Pen, Manila cards, Projector, Blackboard and Compute 7 2.4 PERIOD 4: Rain Water Harvesting and Irrigation Practices SUB TOPICS: • Meaning and Importance of rain water harvesting • Rain water harvesting technologies • Irrigation practices and technologies VENUE: Classroom DURATION: 75 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe the concept of rainwater harvesting and irrigation practices. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the rain water harvesting concept • Identify types of rain water harvesting techniques suitable in their localities • Explain CSA irrigation practices • Describe rain water harvesting and irrigation practices LESSON DEVELOPMENT Start by asking the participants what they know about rainwater harvesting and irrigation practices. Write on flip chart the answers and allow 10 minutes for plenary discussion. Thereafter, write down on flip chart or project the answers from the participants. Ask participants to write on the card different types of rain water harvesting techniques and irrigation practices suitable in their localities then place the card on board by grouping cards with the same answers together. Thereafter, finish by projecting on the board different types of rain water harvesting techniques and irrigation practices suitable in their localities. At the end of the lesson, finish by asking participants (sampling at four) questions on rain water harvesting and irrigation practices. TEACHING METHODS Group and Plenary discussion, Questions & Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Manila cards, Projector and Computer/laptop, chart/drawings showing recommended CSA practices in different Agro-climatic zones of Tanzania 8 2.5 PERIOD 5: Soil Fertility Management Practices SUB TOPICS: • Meaning and importance of soil fertility management practices • Manure application • Efficient use of fertilizer (micro dozing) • Integrated soil fertility management VENUE: Classroom DURATION: Classroom 75 Min MAIN OBJECTIVE At the end of the training session, participants will be able to describe soil management practices which are relevant on addressing impact of climate change in agriculture. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of soil fertility management practices • Define the efficient use of fertilizers • Identify soil management practices in line with CSA pillars • Explain soil fertility in line with CSA pillars LESSON DEVELOPMENT Start by asking the participants what they know about the meaning and importance of soil fertility management practices. Write on flip chart the answers and allow five minutes for plenary discussion. Thereafter, write down on flip chart or project on the board the meaning and importance of soil fertility management practices. Provide group work to the participants to write down on flip chart types of soil fertility management practices. Afterward, the groups should present their work and discuss in plenary. Later on, finish by projecting the types of soil fertility management practices and its importance on CSA. Ask question and discuss in plenary the soil fertility and its contribution on CSA pillars. Write the answers on flip chart and finish by providing the notes. TEACHING METHODS Group and Plenary discussion, Questions and Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Projector and Computer/laptop, manila sheets 9 2.6 PERIOD 6: Crop Management Practices and Technologies SUB TOPICS: • Meaning of crop management • Management practices and technologies in crops • Adaptable crops and crop varieties • Integrated Pest and Diseases Management (IPM) • Timely/early planting/sowing VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand crop management practices and technologies in relation to CSA pillars SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of crop management • Explain different crop management practices and technologies • Identify desirable adapted crop and crop varieties • Explain the benefit of using Integrated Pest Management (IPM) • Explain the importance of timely/early planting/sowing practices LESSON DEVELOPMENT Start the lesson by asking the participants what they know about crop management and their importance. Write answers on flip chart and allow five minutes for plenary discussion. Thereafter, write down on flip chart or project the meaning and importance of crop management. Continue the session by asking the participants to mention different crop management practices and technologies available in their locality and continue plenary discussion. Then, let participants mention characteristics of adaptable crop and crop varieties. Write their answers on the board and allow plenary discuss, then continue by displaying different types of adaptable crops and crop varieties. Afterward, stress the link between different crop management practices and technologies, improved seeds and crop productivity in relation to Climate Change adaptation strategies. Ask participants the methods used to manage pest in their areas. Note down their answers on the board. Emphasize on the ones which are related to Integrated Pest Management and concur with CSA pillars. Continue by defining the term Integrated Pest Management as a broad-based approach that integrates practices for economic control of pests with minimal impact to human health and environment. Stress the point by saying that IPM aims to suppress pest populations below the Economic Injury Level and promotes a safer and more sustainable management and control of pests in agriculture. Tell participants that IPM lies at the centre of insect, disease, and weed control. Later, explain the combination of farming strategies and biological control agents as necessary methods to pesticide and herbicide use that can help farmers to address pest problems. 10 Explain to participants that IPM can provide a healthy and balanced ecosystem in which the vulnerability of plants to pests and diseases is decreased; hence it contributes to climate change adaptation. Give emphasis by telling the participants that it is important to diversify farming system by using IPM as it builds farmers’ resilience to potential risks posed by climate change such as proliferation of pests. Make it clear that it is important to understand pest behavior indifferent agro ecological zones because it helps on adopting and developing new IPM technologies to respond to threats resulting from Climate Change. Ask participants about the importance of timely land preparation and early planting/sowing advantages and disadvantages? Write down their answers on the board and later on give them the right answer, tell them that early land preparation and planting is the practice that ensures optimal use of the short rains and increases efficient use of organic nutrient accumulated in the soil dry season (nitrogen flush). Make it clear to the participants that the use of this practice can be more effective when supplemented with timely of weather information provided by relevant authorities. Conclude the lesson by questions and answers session and by distributing to the participants handouts for further reading. TEACHING METHODS Lecturing, question and answers, brain storming TEACHING AIDS Flip chart, marker pens, pictures 11 2.7 PERIOD 7: Agroforestry Practices and Technologies SUB TOPICS: • Meaning and importance of agroforestry • Common agroforestry practices and technologies VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to describe agroforestry practices and technologies in their respective agro-climatic zone. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Explain the meaning and importance of agroforestry • Describe the common agroforestry practices and technologies in their respective agro-climatic zone. LESSON DEVELOPMENT Start by asking participants what they know about the meaning and importance of agroforestry. Write on flip chart answers and allow 10 minutes for plenary discussion. Thereafter write down on flip chart or project the meaning and importance of agroforestry. Provide group work to the participants to write down on flip chart common agroforestry practices and Technologies in their respective agro-climatic zone. Afterward, the groups should present their work and discuss. Conclude the training session by projecting common agroforestry practices and technologies. TEACHING METHODS Group and plenary discussion, Questions and Answers, group work, Lecture. TEACHING AIDS Flip Chart, Maker Pen, Projector, Computer/laptop, note book, real plant materials. 12 2.8 PERIOD 8: Adaptation Practices and Technologies in Livestock Keeping SUB TOPICS: • Climate change and livestock keeping • Improved Livestock Breeds • Improved feeds and feeding • Pasture and grazing land management • Alternative source of water for livestock VENUE: Classroom DURATION: 120 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand adaptation practices and technologies in livestock keeping in relation to climate change. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Understand the relationship between climate change and livestock keeping • Identify desirable livestock breeds adaptable to a agro-ecological zone • Outline methods used to improve livestock breeds • Identify available feeds and methods of improving them for different livestock breeds available in a given area • Identify different methods of conserve and manage forage/pasture • Identify alternative water sources for livestock LESSON DEVELOPMENT Start the lesson by asking participants to mention the impacts of climate change in livestock production. Write answers on the board so that are clearly seen and make the necessary corrections on plenary discussion. Afterward ask participants if they think livestock keeping has any contribution to the impacts of Climate Change. Based on their responses, explain the relationship between Climate Change and livestock keeping. Emphasize on the effect of the release of methane from enteric fermentation of livestock keeping, manure management and land degradation. Ask few questions on the relationship between livestock keeping and Climate Change. Divide participants in small groups and ask them to differentiate between Local and exotic breeds, let them present their answers later on summaries the answers. Prepare slideshow of different breeds, select few and explain their adaptation capacity to climate change. A local based example of the breed would be better if present. Ask participants the way they do conserve forage in their areas. Note down the answers on the board. Emphasize the desirable forage conservation methods as described in the CSA guideline or CSA Manual. Continue the lesson by showing pictures and explaining few pastures and grazing land management practices which are regarded as climate smart as elaborated in the CSA Guideline and summarized in the CSA manual. Ask participants if there are any alternative sources of water for livestock production in their area. Write the answers on the board. Show them the common alternative sources of water for livestock production. Emphasis should be given on how to make them available for use during the periods of prolonged dry spell as projected by climate change models. 13 TEACHING METHODS Group discussion, Lecturing, Presentation, demonstration TEACHING AIDS Flip chart, laptop, projector, pictures, illustration and demonstration area, real materials 14 2.9 PERIOD 9: Manure Management Practices SUB TOPICS: • Meaning and importance of manure • Source of manure • Manure management VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session participants will be able to understand different forms of utilizing manure in relation to climate change. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain the meaning and importance of manure • Outline different ways of proper manure utilization LESSON DEVELOPMENT Ask participants what they understand about manure and different sources of manure in their area. Write the answers on the board and make the necessary corrections on plenary discussion. Afterward ask participants how do they handle and dispose manure from their locality. Note down the answers on the board and stress the desirable ways of disposing and handling manure especially those environmentally/Climate Change friendly technologies or practices. Ask participants if there is any person with environmentally/climate change friendly technologies. Emphasis on the mentioned technologies in relation to the three pillars of CSA. Finalize by associating environmentally/Climate Change friendly technologies and soil management practices (nutrient losses). Stress that all these are essential for building resilience and mitigating to Climate Change impacts. TEACHING METHODS Group discussion, Lecturing, Presentation TEACHING AIDS Flip chart, laptop, projector, pictures, illustration and demonstration area, real materials 15 2.10 Period 10: Climate Smart Agriculture in Fishing and Aquaculture SUB TOPICS: • Impact of Climate Change on Fishing and Aquaculture enterprises • Climate Smart Fishing and Aquaculture practices • Sustainable Fishing • Seaweed Farming VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand the Climate-Smart agriculture practices in Fishing and Aquaculture enterprises. SPECIFIC OBJECTIVES At the end of the subject participants will be able to: • Explain impacts of climate change on fishing and aquaculture enterprise • Identify Climate-Smart Fishing and Aquaculture practices • Explain sustainable fishing in the context of climate smart fishing • Describe seaweed farming in the context of mitigating Climate Change impact LESSON DEVELOPMENT The trainer start by probing participants’ understanding on the meaning of aquaculture by asking a question such as “what comes into minds when someone says Aquaculture?” After a little discussion on its meaning, then the trainer summarizes the discussion by giving the actual meaning of Aquaculture. Thereafter, the trainer ask participants to think of any ways by which weather variability or climate change can impact fishing enterprises and aquaculture. Thereafter, the trainer writes answers obtained on the flip chart or writing board. After that the trainer explains each of the mentioned response with emphasize on the impact of temperature on oxygen availability, biophysical characteristics of the aquatic organisms, water pollution through formation of algae bloom and increase of solute concentration triggered by evaporation. On giving explanation the trainer may use video or demonstrate by drawings on the writing boards. Afterward, the trainer introduces the concept of sustainable fishing by giving few examples of sustainable fishing practices aided by pictures. In the end the trainer give an explanation on how sustainable fishing is related to Climate-Smart agriculture by associating with CSA pillar of increase of agricultural productivity. The concept of seaweed farming is then introduced as another CSA practice mostly practiced along the sea coast. The trainer explain seaweed farming as a practice which has bigger contribution on sequestrating atmospheric carbon compared to similar area under terrestrial agricultural activity. This explanation should be related to the third pillar of CSA which is target on mitigation of GHG by reducing GHG in the atmosphere. 16 Then the trainer concludes the lesson by encouraging participants to visit any nearby place where aquaculture or seaweed farming is practiced. The trainer should also provide manual for further reading at the end of the session. TEACHING METHODS Plenary discussion, questions and answers and lecture TEACHING AIDS Flip Chart, Maker Pen, Projector and Computer and pictures 17 2.11 PERIOD 11: Upscaling of Climate Smart Agriculture SUB TOPICS: • CSA practices and technologies • Challenges on upscaling practices and technologies • Ways for upscaling CSA practices and technologies VENUE: Classroom DURATION: 45 Min MAIN OBJECTIVE: At the end of the training session, participants will be able to understand on how to upscale Climate- Smart Agriculture practices and technologies in their localities. SPECIFIC OBJECTIVES At the end of the subject, participants will be able to: • Define CSA practices and technologies • Understand challenges on upscaling CSA practices and technologies • Explain ways for upscaling CSA practices and technologies LESSON DEVELOPMENT At the beginning present to participants the main concept of CSA practices and technologies in relation to three CSA pillars. Then ask the participants a question such as“ is there a need to upscale CSA in their localities?” Write down answers obtained from the participants on the flip chart. Afterward, arrange participants in groups of livestock keepers, crop farmers, fisheries and let them discuss common CSA practices applicable to them. While still in their groups ask them to pick one practice and describe how they can be able to upscale in other areas and within their communities. Let this discussion last for about 20 minutes. Then, allow groups to present their findings in plenary and take two or three question after each presentation. After all the group have presented give overall feedback and elaborate more on methods they could further consider for upscaling of the CSA practices. Then discuss with the participants on common challenges associated with the upscaling of CSA. Let participants share their experience and on the same time the trainer will have to be presenting possible solution on overcoming the challenges. Based on the discussion and solutions presented, list down various ways which can be considered for upscaling of CSA practices. In the end, ask general questions about CSA upscaling and their relevance in the respective area and emphasize on the possible solutions to overcome CSA upscaling challenges in the respective area. Then give them the training manual/notes for further reading and referencing. TEACHING METHODS Plenary discussion questions and lecture TEACHING AIDS Projector, standby generator, stationaries (Flip chart, Exercise books, pens, marker pen) 19 3. TOPIC 3: CSA STAKEHOLDERS INVOLVEMENT SUB TOPICS: • Identification of stakeholders • Roles of different stakeholders on implementation and upscaling of CSA • Stakeholders engagement mechanisms • Approaches for CSA integration VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: At the end of training session participants will be able to identify CSA stakeholders and their roles in the implementation and scaling up of CSA practices and technologies SPECIFIC OBJECTIVES At the end of the session, Participant will be able to; • Identify CSA Stakeholders • Explain roles of different CSA stakeholders • Describe different mechanisms for stakeholder engagement • Identify different approaches for CSA implementation LESSON DEVELOPMENT Start session by asking participants if they can mention stakeholders that they think are important in implementation of CSA. After that, mention other stakeholders that were not mentioned and describe why they are important. Thereafter, group participants in groups which represent major categories of stakeholders such as policy makers, planners, farmers, private sectors, NGOs, youth, women and men and let them discuss their roles on any CSA intervention of their choice. Afterward, ask the groups to present their discussed roles, allow plenary discussion for twenty minutes after presentation from each group. Then ask participants if there is necessity for the different stakeholder to work together. If the answer is yes, ask them to mention mechanisms which can allow them to work together. Ask them to discuss those mechanisms briefly on how they are effective on engaging different stakeholders on implementing CSA intervention. Afterward, present and describe other mechanisms which were not mentioned and how they can be used adopted to help bring and engage CSA stakeholders on implanting CSA intervention. Then introduce different approaches which should be considered on implementing different mechanisms for engaging stakeholder such as gender inclusive and participatory approach. Emphasis should be given on issues such as gender, inclusion of the three CSA pillars and evolvement of multi- CHAPTER THREE 20 stakeholders. In the end, present summary on key stakeholder to be considered on implementing CSA intervention and their roles, give summary of different mechanisms of stakeholder engagement; briefly give emphasis on approaches to be considered and their application in the respective area. TEACHING METHODS; Lecturing, group discussion, questions and answers, TEACHING AIDS; Projecting board, projector, laptop, notebooks, pens, flip chat, marker pens 21 4. TOPIC 4: MAINSTREAMING OF CSA INTO AGRICULTURAL PLANS SUB TOPICS: • Awareness creation and sensitization of CSA • CSA related activities and their relevant justifications • Planning of CSA activities with gender consideration • Budgeting for CSA related activities VENUE: Classroom DURATION: 120 Min MAIN OBJECTIVE To teach participants on mainstreaming of CSA in agricultural related plans in order to increase agriculture resilience to the impact of climate change, increase agricultural productivity, sustainability and farmers’ income. SPECIFIC OBJECTIVES At the end of the training session participants will be able to: • Define CSA awareness creations • Create awareness to stakeholders • Identify at least three target groups for CSA awareness creation • Mainstream CSA activities into agricultural plans Explain CSA related activities in a given area • Plan CSA activities with gender considerations • Budget for CSA activities LESSON DEVELOPMENT Start the lesson by asking participants to define the word awareness by associating it to CSA. Take a note of the answers and write them on the board. Later ask participants what they understand about awareness creation and sensitization. Assist participants to give the right definitions of the words awareness and awareness creation in relation to Climate Smart Agriculture (CSA). Give clarifications on the meaning of Climate Change and how it affects agriculture and livelihood. Show participants the impacts of Climate Change using power point slides or pictures/photos. Then ask participants to explain at least five methods of creating awareness. Take note of the answers. Afterward, give more elaboration on the method of awareness creation and give examples on their failure or success. CHAPTER FOUR 22 Ask participants to give example of few target groups which can be considered for awareness creation purpose. Note down their responses and then tell the participants that the target groups for CSA awareness creation include government authorities, central and local administrative authorities, religious, traditional leaders, opinion leaders, NGOs, civil society, donors and media. On mentioning the target group, give more elaboration and examples in relation to awareness creation methods. Emphasize the points by saying that a successful awareness raising strategy takes into account the type of target group, type of message to be reached out for each particular target group and selection of appropriate awareness creation method for communicating the messages. Now divide participants into four groups and let them discuss how they may create CSA awareness activities to the target group of their choice. Go around the groups to see whether they have understood the assignment and assist them accordingly. Then, allow a representative member from each group to a make brief presentation and allow others to contribute to the presentation after its done. Ask participants to mention main sources of finance to agricultural investments in Tanzania. Write down their responses and later give them the more sources those from the farmers, herders, fishers and foresters, development partners, central and local government as well as NGOs. Emphasize by saying that for successive public investment, it is better to consider potential stakeholders in a given locality and identify the most suitable activities when developing CSA strategies, investments and financing plans. Explain to participants’ things that have to be considered when budgeting for CSA related activities. Give elaborations by saying that large fixed capital investments with significant lifetimes are particularly vulnerable to being maladaptive if climate risks are not considered. Continue by telling participants that for successful investment they must screen agricultural investment plans for their degree of “climate smartness”. The screening methodology considers potential contribution of planned activities to the three pillars of CSA and other aspects of adaptation as well as mitigation. This suggests that Climate- Smart agricultural investments with mitigation co-benefits should be identified within the context of existing agricultural investment strategies developed for the purposes of agricultural growth. Start by pointing out that financing options specifically targeting CSA are still limited, necessitating for a strategic use and combination of funding sources in existence. Ask participants to mention sources of funds they thought could be used for CSA activities in their respective areas. Moderate and remind them to include internal and external sources. The internal sources are: Local Government Authorities (LGAs), budgets, National budgets and Agricultural Sector Development Programme (ASDP), while the external sources include United Nations Framework Convention for Climate Change (UNFCC), United Nations (UN) organizations, Multilateral Development Banks (MDBs); bilateral public financing channels; Compliance and voluntary carbon markets; and Private sector actors and philanthropy. Tell participants the roles played by each financing agencies on CSA activities and how they may get access to such funds. Conclude the session by asking different questions to participants and tell them what is expected to be done in the next training session. TEACHING METHODS Question and answers, brainstorming, group discussion, questions at the end of the period, TEACHING AIDS Flip charts, black/white board, marker pens, projector 23 5.TOPIC 5: MONITORING AND EVALUATION OF CSA INTERVENTIONS SUB TOPICS: • The meaning of Monitoring and evaluation (M&E) • Identification of baseline indicators for CSA • Performance Indicators for CSA interventions • Monitoring tools and Record keeping • Creation of evidence for CSA practices performance VENUE: Classroom DURATION: 60 Min MAIN OBJECTIVE: In the end of the lesson, participants will be able to know how to monitor and evaluate CSA interventions or related projects in their respective areas. SPECIFIC OBJECTIVES: At the end of the subject Participants will be able to: • Explain the meaning and importance of M&E • Describe and identify the baseline indicators • Describe and identify key performance indicators and their uses • Distinguish between baseline and key performance indicators • Identify different M&E tools • Explain importance of records keeping for evidence based creation • Describe how CSA evidence can be created LESSON DEVELOPMENT Start lesson by asking the participants if they know anything about Monitoring and evaluation. Thereafter, provide the proper definition of M&E so that there is common understanding among participants. Then, explain the importance of Monitoring and Evaluation for CSA interventions or related projects. Then, introduce the concept of baseline indicator, describe its characteristics and lead them to identify sources of the indicators. After that introduce the concept of key performance indicators, describe their characteristic and explain how they can be obtained. Then, ask the participants to briefly reflect on the main differences between the two types of indicators. After that, divide participants into groups and give them simple CSA intervention for them to develop baseline indicators and key performance indicator. Then let them discuss their outputs in the plenary. CHAPTER FIVE 24 Then continue by introducing participants on different tools for monitoring and evaluation. Explain the importance of these different tools including their usefulness in record keeping for monitoring and evaluation. Then give emphasis of record keeping for evidences creating with the purpose of sharing lessons learnt with others during project or activity implementation. Describe various ways by which participants can be able to document their M&E data and create evidence for sharing with other in an easy and customizable way. Finally, end the training session by providing the summary of the topics and emphasis on the importance of M&E, the two types of indicators, tools for M&E and their importance. TEACHING METHODS Group work, lecture, plenary discussions, questions and answers TEACHING AIDS Flip charts, writing board, marker pens, notebooks, laptop and projector Ministry of Agriculture Livestock and Fisheries P.O. Box 2182 40487 Dodoma Telegram: “Kilimo Dodoma” Tel: +255 (026) 2321407/ 2320035 Fax: +255 (026) 2320037 Email: [email protected] www.kilimo.go.tz | false |